REPUBLIC OF RWANDA Revising Nationally Determined Contribution (NDC) mitigation and adaptation priorities for Rwanda Final Report 24 March 2020 Prepared by: Gregory Cook (Mitigation lead), Alex Mulisa (Adaptation lead), Innocent Nkurikiyimfura (Energy), Elisée Gashugi (Waste and IPPU), and Svetlana Gaidashova (Agriculture and Forestry) Task Team Leader: Pablo Benitez Ponce, Senior Environmental Economist, ENB Global Practice ACKNOWLEDGEMENTS This report was prepared by a team led by Pablo Benitez (Senior Environmental Economist) of the World Bank and under the expert guidance of Juliet Kabera (Director General of Environment and Climate Change) and Immaculee Uwimana (Climate Change Mitigation officer) at the Ministry of Environment. The main contributing authors are Gregory Cook (Carbon Counts), Alex Mulisa, Innocent Nkurikiyimfura, Elisée Gashugi, and Svetlana Gaidashova. The team would also like to express its gratitude to the many individuals from within the Government of Rwanda for the provision of data, information and expertise, without which the analysis could not be possible. These include in particular officials and experts from the Ministry of Environment, the Rwanda Environment Management Authority, the Ministry of Agriculture and Animal Resources, the Ministry of Infrastructure, the Ministry of Finance and Economic Planning, National Institute of Statistics of Rwanda, and the Rwanda Agriculture Board. In addition, the team would also like to thank peer reviewers Joern Huenteler, Esdras Byiringiro, Adam Stone Diehl, and Abebaw Alemayehu, and to Sandra Namukaya, Michael John Hammond, and Peter Katanisa for their contributions. Finally, the team would also like to thank the participants in the various consultation sessions including those of the inception and validation workshops conducted in Kigali between February 2019 and November 2019 for their valuable inputs and feedback. The findings, interpretations, and conclusions expressed in this report do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The study was funded by the NDC Support Facility of the World Bank as part of the NDC Partnership programme. Rwanda NDC Implementation: Final Report Page i CONTENTS EXECUTIVE SUMMARY ................................................................................................................ VI 1 INTRODUCTION .................................................................................................................. 1 1.1 Background: the UNFCCC and Paris Agreement ................................................................ 1 1.2 Rwanda’s national context ................................................................................................. 2 1.3 Rwanda’s Nationally Determined Contribution ................................................................. 3 1.4 Project aims and scope of work ......................................................................................... 4 1.5 Outline of this report .......................................................................................................... 5 2 METHODOLOGY ................................................................................................................. 7 2.1 Mitigation ........................................................................................................................... 7 2.2 Adaptation .......................................................................................................................... 8 3 BAU EMISSIONS PROJECTIONS .......................................................................................... 11 3.1 Overview and approach ................................................................................................... 11 3.2 GHG emissions inventory ................................................................................................. 12 3.3 Energy ............................................................................................................................... 17 3.4 Industrial processes and product use............................................................................... 28 3.5 Agriculture ........................................................................................................................ 31 3.6 Waste................................................................................................................................ 35 3.7 Summary and sensitivity analysis ..................................................................................... 38 4 ASSESSMENT OF NDC MITIGATION OPTIONS ..................................................................... 46 4.1 Overview........................................................................................................................... 46 4.2 Identifying mitigation options .......................................................................................... 46 4.3 Assessing the potential..................................................................................................... 53 4.4 Evaluating the options ...................................................................................................... 57 5 ALTERNATIVE GHG PATHWAYS ......................................................................................... 65 5.1 NDC mitigation scenarios ................................................................................................. 65 5.2 Modelling results .............................................................................................................. 65 5.3 Sensitivity analysis ............................................................................................................ 67 5.4 Summary........................................................................................................................... 76 6 ADAPTATION AND RESILIENCE INITIATIVES IN RWANDA .................................................... 77 6.1 Policy and legal framework .............................................................................................. 77 6.2 Adaptation in priority Sector Strategic Plans ................................................................... 78 7 CHALLENGES IN ADAPTATION AND RESILIENCE ................................................................. 83 7.1 Water Resources .............................................................................................................. 84 Rwanda NDC Implementation: Final Report Page i 7.2 Agriculture ........................................................................................................................ 85 7.3 Land Use Management .................................................................................................... 85 7.4 Forestry............................................................................................................................. 85 7.5 Mining............................................................................................................................... 86 7.6 Energy ............................................................................................................................... 86 7.7 Climate data management ............................................................................................... 87 7.8 Health ............................................................................................................................... 87 7.9 Transport .......................................................................................................................... 87 7.10 Housing and human settlement ....................................................................................... 87 8 EVALUATION OF ADAPTATION ACTIVITIES AND INDICATORS ............................................. 89 8.1 Overview........................................................................................................................... 89 8.2 Summary of adaptation activities and their corresponding indicators ............................ 89 8.3 Categorisation of adaptation indicators......................................................................... 109 8.4 Priority adaptation interventions ................................................................................... 110 9 MONITORING, EVALUATION AND REPORTING................................................................. 115 9.1 Mitigation ....................................................................................................................... 115 9.2 Adaptation ...................................................................................................................... 127 10 FUNDING REQUIREMENTS .............................................................................................. 131 10.1 Overview......................................................................................................................... 131 10.2 Mitigation ....................................................................................................................... 131 10.3 Adaptation ...................................................................................................................... 135 10.4 Capacity building and technology transfer..................................................................... 137 11 CONCLUSIONS AND RECOMMENDATIONS....................................................................... 139 11.1 Mitigation ....................................................................................................................... 139 11.2 Adaptation ...................................................................................................................... 140 REFERENCES ............................................................................................................................ 142 ANNEX A – MITIGATION PROJECT ASSESSMENTS .......................................................................A-1 ANNEX B – ADAPTATION PROJECT EVALUATIONS ...................................................................... B-1 ANNEX C - FORESTRY ................................................................................................................ C-1 Rwanda NDC Implementation: Final Report Page ii ACRONYMS AND ABBREVIATIONS AFOLU Agriculture, Forestry and Other Land Use BAU ‘Business as usual’ CBA Cost-benefit analysis CCL CIMERWA Cement Limited Ltd CDM Clean Development Mechanism CFL Compact fluorescent lamp CO2 Carbon dioxide CO2e Carbon dioxide equivalent CoK City of Kigali CORs Continuous Operating Reference System CSA Climate Smart Agriculture DDS District Development Strategy DRR Disaster risk reduction DSM Demand side management EDPRS Economic Development and Poverty Reduction Strategy EE Energy Efficiency EIB European Investment Bank EICV5 Fifth Integrated Household Living Survey EMS Energy management system ENR Environment and Natural Resources ESSP Energy Sector Strategic Plan EV Electric vehicle FAO Food and Agriculture Organization of the United Nations FIP Forest Investment Plan FONERWA Rwanda’s Green Fund FTE Full time employees GCF Green Climate Fund GDP Gross Domestic Product GEF Global Environmental Facility GGCRS Green Growth and Climate Resilience Strategy GHG Greenhouse gas GoR Government of Rwanda GWh Gigawatt-hour GWP Global warming potential Ha Hectare HFC Hydrofluorocarbon HH Household IMF International Monetary Fund INDC Intended Nationally Determined Contribution IPCC Intergovernmental Panel on Climate Change IPPU Industrial Processes and Product Use Rwanda NDC Implementation: Final Report Page iii IWRM Integrated Water Resources Management km Kilometre kW Kilowatt kWe Kilowatt-electric L litre LAIS Land Administration and Information System LCPDP Least Cost Power Development Plan LDC Least Developed Country LDV Light duty vehicle LEAP Long-Range Energy Alternative Planning LED Light emitting diode LFG Landfill gas LPG Liquefied petroleum gas M&E Monitoring and Evaluation MACC Marginal abatement cost curve MIDIMAR Ministry of Disaster Management and Refugee Affairs MINAGRI Ministry of Agriculture and Animal Resources MINALOC Ministry of Local Government MINECOFIN Ministry of Finance and Economic Planning MINEDUC Ministry of Education MININFRA Ministry of Infrastructure MJ Megajoule MoE Ministry of Environment MRV Monitoring, Reporting and Verification Mt Million tonnes MW Megawatt N Nitrogen NAMA Nationally Appropriate Mitigation Actions NAP National Adaptation Plan NDC Nationally Determined Contribution NGO Non-Governmental Organisation NISR National Institute of Statistics of Rwanda NLUDMP National Land Use Development Master Plan NPV Net present value NST National Strategy for Transformation O&M Operating and maintenance ODS Ozone depleting substances PA Paris Agreement PPCR Pilot Program for Climate Resilience PSF Private Sector Federation PV Photovoltaic RAB Rwanda Agriculture Board RBME&L Results-based monitoring, evaluation and learning Rwanda NDC Implementation: Final Report Page iv REDD+ Reducing Emissions from Deforestation and Forest Degradation REG Rwanda Energy Group Ltd REMA Rwanda Environment Management Authority RHA Rwanda Housing Authority RLMUA Rwanda Land Management and Use Authority RTDA Rwanda Transport Development Agency RURA Rwanda Utilities Regulatory Authority RWFA Rwanda Water and Forestry Authority SHS Solar home system SIDS Small Island Developing States SPCR Strategic Program for Climate Resilience SREP Scaling Up Renewable Energy Program SSP Sector Strategic Plan SWDS Solid waste disposal site SWH Solar water heater t Tonne TJ Tera-joule TNC Third National Communication to the UNFCCC UNFCCC United Nations Framework Convention on Climate Change USAID United States Agency for International Development USD United States (US) dollar WBG World Bank Group WtE Waste to Energy Rwanda NDC Implementation: Final Report Page v EXECUTIVE SUMMARY Introduction Rwanda submitted its Intended Nationally Determined Contribution (INDC) to the United Nations Framework Convention on Climate Change (UNFCCC) in September 2015 setting out its adaptation and mitigation goals. The INDC formally became the country’s first Nationally Determined Contribution (NDC) with the entry into force of the Paris Agreement in 2016. Rwanda is currently revising its NDC ahead of the 26th Conference of the Parties of the UNFCCC (COP26) in Glasgow. This requires building upon existing work in developing quantifiable mitigation and adaptation targets, and the prioritization of interventions to support these two areas. The World Bank is providing technical assistance to support Rwanda in this process. This report describes the results of technical and economic analysis relating to both the mitigation and adaptation components of the NDC. It covers the following: • Mitigation: An evaluation of greenhouse gas (GHG) mitigation actions based on in-depth assessment of the country’s mitigation potential. This has been undertaken using detailed technical and economic analysis and multi-criteria based evaluation involving extensive stakeholder consultation. The development of business as usual (BAU) and alternative GHG pathways through 2030 is used to inform the choice of NDC mitigation targets for Rwanda and support its implementation framework. • Adaptation: Production of quantified targets for adaptation and resilience, criteria-based evaluation of priority interventions, and development of a monitoring and evaluation (M&E) framework for adaptation actions to strengthen national capacity for resource mobilization. Based on the analysis undertaken, funding requirements and support needs for both conditional and unconditional measures in mitigation and adaptation through 2025 and 2030 are estimated. The work aims to provide a robust technical basis for subsequent actions to strengthen climate change planning and implementation activities in Rwanda. Mitigation BAU emissions projections In order to determine Rwanda’s mitigation potential and choice of NDC targets, GHG emissions were first projected through 2030 under a BAU scenario according to which NDC mitigation policies and actions are not implemented. The national GHG inventory for the base year was updated according to International Panel on Climate Change (IPCC) reporting guidelines and bottom-up projections made based on updated forecasts of sector-specific activity data and official outlooks for gross domestic product (GDP) and population growth. At an aggregate level, total emissions are forecast to more than double over the 2015-2030 period, rising from 5.3 million tCO2e in the base year to 12.1 million tCO2e in 2030. As shown in the graph below, the most significant growth is forecast within energy use emissions, expanding its share of total emissions from around 31% in the base year to 40% by 2030. The share of emissions from waste generation remains at around 12-13%, whilst agricultural sources decline from 55% to 43%. Rwanda NDC Implementation: Final Report Page vi The forecast indicates the growing contribution from fossil fuels to national emissions, arising from increasing demand for power generation, road transport and other modern energy uses. At the same time, despite potential for increased productivity, agricultural output in expected to be limited due to land availability, thereby limiting emissions growth from this sector. Figure ES-1 BAU emissions projections in Rwanda to 2030 Assessment of NDC mitigation options A detailed assessment of GHG mitigation options for Rwanda was next undertaken in order to determine which options are most suitable for inclusion in the NDC. The analysis was undertaken according to a three-step process: • Step 1: Identifying mitigation options. A ‘long-list’ of potentially suitable emission reduction projects and measures was developed through discussions and consultation with government officials, technical and sector experts, and other stakeholders. • Step 2: Assessing the potential. The identified options were then assessed in terms of their mitigation potential through 2030 compared to the BAU reference scenario and their economic costs and benefits, by undertaking cost-benefit analysis (CBA). • Step 3: Evaluating the options. The quantitative analysis undertaken in Step 2 was complimented by a broader, multi criteria-based, assessment in order to identify those options considered most suitable or feasible to be implemented under the NDC and to determine which will be implemented through domestic efforts alone (‘unconditional’ projects) and which require international support and finance (‘conditional’ projects), Rwanda NDC Implementation: Final Report Page vii including through international market-based approaches e.g. under Article 6 of the Paris Agreement. The figure below summarises the estimated emissions reduction potential against BAU in 2030 for all mitigation measures assessed from the ‘long list’. The total mitigation potential is estimated at around 4.6 million tCO2e in 2030 against the BAU emissions in the same year of 12.1 million tCO2e. According to the analysis, mitigation measures identified within the agriculture sector accounts for 49% of the total potential, followed by energy (34% of total), waste (14%), and IPPU (3%). Figure ES-2 Estimated GHG mitigation potential in 2030 from all measures Note: Some mitigation measures are grouped for simplicity The figure below shows a marginal abatement cost curve (MACC) in which each of the identified NDC mitigation options is sorted in ascending order of abatement cost. The costs represent socio- economic costs of abatement, reflecting both costs and benefits to the wider economy. Rwanda NDC Implementation: Final Report Page viii Many of the projects shown on the curve – representing around 72% of the total potential - are considered to be achievable with a net socio-economic benefit. This is most noticeable for energy projects, most of which involve the displacement or reduction of imported fossil fuels through increasing the use of indigenous renewable energy and cost-saving demand-side measures. The majority of the waste sector options identified are also considered to be cost-effective on an economic basis, including landfill gas utilisation and waste-to-energy projects which utilise waste materials for economic energy production whilst also delivering wider employment and revenue benefits. Within agriculture, cost-effective options such as crop rotation and improved livestock husbandry can also deliver GHG reductions with important co-benefits such as increasing yields and economic output. Figure ES-3 Marginal abatement cost curve for all identified mitigation measures in 2030 Development of alternative GHG pathways A series of alternative emissions pathways were modelled through 2030 based on the technical analysis of mitigation projects. Two basic NDC mitigation scenarios were modelled: • All NDC measures: Implementation of all identified mitigation options considered suitable as NDC measures, includes both “unconditional” and “conditional” measures, and representing Rwanda NDC Implementation: Final Report Page ix an ‘upper end’ estimate of how much mitigation potential could be achieved within the NDC sectors through 2030 subject to support. • Domestic measures only: Implementation of unconditional domestically supported projects only, representing those projects already committed within government plans and programmes or considered sufficiently incentivised for private sector implementation to proceed. The grouping of mitigation options into unconditional and conditional measures was informed by the criteria-based evaluation and through extensive consultation with relevant government departments and agencies as well as through workshops held with non-state actors including civil society and private sector. The BAU and NDC mitigation scenarios are summarised in the figure below, which also shows the contribution of each sector to the total estimated potential based on the technical assessments of all mitigation measures. According to the mitigation pathways, a GHG reduction against BAU of around 16% (domestic measures) and 38% (all NDC measures) is achieved by 2030. Figure ES-4 NDC emissions reduction scenarios The ability of Rwanda to achieve these mitigation outcomes will be subject to a range of factors determining both the BAU emissions forecast and the ability of NDC measures to deliver expected reductions. Sensitivity analysis was therefore undertaken, focusing on (a) an alternative lower GDP Rwanda NDC Implementation: Final Report Page x growth scenario; (b) a reduced outlook for project implementation and mitigation; and (c) inclusion of the Lake Kivu methane power projects, for which international GHG reporting guidance and project emissions data are currently lacking). As expected, the lower mitigation scenario delivers a lower reduction outcome relative to BAU. The lower GDP growth scenario results in a larger emissions reduction achieved relative to BAU. This is because lower growth is assumed to result in reduced economy-wide emissions projected under BAU but not reduced reductions from mitigation projects.1 Accounting for emissions reductions from the Lake Kivu methane project could have a significant impact on delivering additional reductions, arising mainly from utilisation of methane gas otherwise assumed to be released to atmosphere. This is however subject to a high level of uncertainty around methane formation and release rates, the lack of GHG accounting methodology and project monitoring data. The results therefore indicate the potential range of mitigation delivered by identified NDC measures according to key uncertainties around baseline and mitigation factors. For domestic measures only, this range is estimated at a 12-18% reduction against BAU in 2030, which is increased to 27-58% for the inclusion of all NDC measures. Guided by the principle that Rwanda should only adopt targets considered capable of being delivered, the choice of which mitigation target(s) to adopt within the revised NDC should necessarily be informed by a view on which scenario is considered most feasible. In this context, it should be noted that the base case scenario is based on official target assumptions for GDP growth (Vision 2050) and also project outcomes. Overestimating GDP growth has the tendency to underestimate mitigation outcomes relative to BAU, while overestimating project success and mitigation outcomes has the tendency to overestimate mitigation outcomes relative to BAU. From this, it might reasonably be concluded that the base case represents a feasible forecast of what could be delivered under the first NDC, subject to an enabling domestic policy framework and attracting the necessary international funding and support. Adaptation Overview The adaptation work is aligned with the mitigation analysis, seeking to prioritise adaptation interventions, establish baselines, develop sector-level performance indicators and targets as well as estimating costs for prioritized interventions. The overall approach to the choice of adaptation indicators considered the following factors as critical: (i) Differentiating between climate change related issues and business-as-usual development, (ii) Basing on Local/sector context to climate vulnerability/resilience assessment, and (iii) Data availability to measure impact. This was conducted using a detailed review and analysis of adaptation and resilience initiatives in Rwanda with related key interventions and indicators. In addition, the consultation with experts from multiple sectors relied on an analytical framework that gained consensus from broad stakeholders. The specific objectives for the consultations were to: 1this is a key methodological simplification since some projects will in reality be impacted by reduced demand, and thus mitigation results are likely to be overestimated. Rwanda NDC Implementation: Final Report Page xi • Check if the information included in the adaptation analytical framework are relevant to the sector; • Share other internal reports that have consistently informed monitoring and evaluation of sectors; • Advise on the long term projections to 2025 and 2030 targets; • Inform and develop consensus on the costing of climate adaptation specific priority actions including outline of sources of finance categorized as “conditional” (supported measures) and “unconditional” (unilaterally funded); and • Agree on the MRV to report which in the case of adaptation focuses on monitoring and reporting on financial flows to address adaptation/resilience action. Thus, the overall approach involved extensive review of relevant documents on climate adaptation that have developed over time starting with the Green Growth Climate Resilience Strategy (GGCRS) and associated sector working papers, and also the Strategic Programs for Climate Resilience (SPCRs). It is important to note that this was the basis of the INDC and subsequently the NDC that was ratified under the Paris Agreement. Adaptation interventions In total, 24 adaptation interventions were formulated in the context of this WB technical assistance and were built on existing adaptation initiatives and the robust stakeholder consultations. The interventions are classified in eight main sectors selected for Rwanda’s NDC agenda towards 2030 as summarized in the table below. Table ES-1: NDC selected adaptation interventions by sector HUMAN TRANS WATER AGRICULTURE LAND AND FORESTRY HEALTH MINING CROSS-SECTORAL SETTLEMENT PORT Integrated approach to planning and monitoring for Promote afforestation / reforestation of designated Develop and implement a management plan for all conservation practices, wetlands restoration, water Capacity building and development for cross-sector Expand irrigation and improve water management Water resource models, water quality testing, and Improve Forest Management for degraded forest Establish an integrated earlywarning system, and Develop sustainable land management practices Develop climate resilient postharvest and value Inclusive land administration that regulate and High density buildings and informal settlement Improved transport infrastructure and services Development of Agroforestry and Sustainable management system for sustainable land use Develop climate resilient crops and promote Strengthen preventive measures and create provide guidance for land tenure security A National Water Security through water Harmonised and integrated spacial data Strengthen crop management practices capacity to adapt to disease outbreaks Expand crop and livestock insurance addition facilities and technologies storage and efficient water use Climate compatible mining Storm water management hydro-related information climate resilient livestock sustainable land use mgt Disaster risk monitoring disaster response plans NDC implementation Level 1 catchments Access to finance Agriculture upgrading resources areas 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 Rwanda NDC Implementation: Final Report Page xii Adaptation indicators The above adaptation interventions have identified a total of 38 adaptation indicators that are aligned with baselines and adaptation targets that have significantly drawn from existing national initiatives on climate adaptation/resilience analytics. Basing on the experiences in reporting at global level (including expectations of adaptation investment funds) and national level (including projects), the indicators outlined in the report were divided into categories A and B for global and national reporting, respectively. The indicators for reporting on adaptation interventions at global level shown in the table below have the potential to position Rwanda’s envisaged robust engagement and efforts at addressing challenges of measurement of climate adaptation/resilience. Table ES-2: Selected adaptation indicators global level reporting SN INDICATORS 1 Water storage per capita 2 Percentage of arable land (to the land area) Number of hectares under irrigation within Integrated Water Resource Management 3 framework 4 Change in land area covered by agroforestry 5 Percentage of forest area (to the land area) Percentage of (i) urban population living in informal settlements, (ii) rural population 6 living in clustered settlements 7 Malaria proportional mortality rate per 1,000 population Percentage of extreme weather events for which advance warning was provided at least 8 30 minutes in advance Cumulative volume of finance [USD millions] mobilized for climate and environmental 9 purposes Funding requirements for NDC actions Extensive analysis and consultations with sector experts were undertaken to produce “conditional” and “unconditional” cost estimates for the mitigation and adaptation measures identified in the report through 2025 and 2030. The total estimated cost for Rwanda’s identified NDC mitigation measures through 2030 is estimated at around 5.7 billion USD, and over 5.3 billion USD for adaptation priorities, representing a combined funding requirement of around 11 billion USD. Table ES-3 below summarises the estimated investment requirements over the two periods. Within mitigation, energy sector projects dominate the period 2020-2025 associated with near term state- funded low carbon energy programmes such as expansion of grid-connected hydropower and solar pumping for irrigation, and projects such as the introduction of electric vehicles requiring international support. The majority of agriculture sector investments are realised within the period 2026-2030 with the scaling up and implementation of domestic fertiliser, crop rotation and livestock programmes as well as those projects requiring additional finance flows. Rwanda NDC Implementation: Final Report Page xiii For both mitigation and adaptation combined, it can be seen that unconditional measures account for around 40% of the total estimated funding requirements, and conditional measures around 60%. In addition to funding, international support in the form of capacity building and technology transfer will also be required. Table ES-3: Estimated mitigation and adaptation funding needs USD million Unconditional Conditional Grand Total Mitigation measures 2020-2025 1,057 1,754 2,811 2026-2030 953 1,912 2,866 Mitigation Total 2,010 3,667 5,677 Adaptation measures 2020-2025 916 1,374 2,290 2026-2030 1,229 1,844 3,073 Adaptation Total 2,145 3,218 5,364 Combined Total 4,155 6,885 11,041 Conclusions and recommendations The technical analysis described in the report provides a basis for Rwanda to submit its revised NDC with targets for mitigation and adaptation, as well as strengthening its implementation planning and framework. The following recommendations are made for implementation of the mitigation component of Rwanda’s NDC: • Decision on choice of NDC targets to adopt, based on the technical and economic analysis of mitigation options and estimated reductions from conditional and unconditional components against BAU through 2030. • Develop an MRV framework for tracking the progress of project implementation and Rwanda’s pathway towards achieving the NDC, whilst meeting its international obligations under the Paris Agreement. Such a framework will include developing a set of performance indicators and supporting metrics for monitoring and reporting the progress towards meeting the NDC for the identified prioritized sectors/mitigation actions within each sector and approach to tracking climate finance. • Elaborate a detailed financing strategy through the revised NDC implementation plan that considers prioritized mitigation measures and guidance on accessing climate finance. This should include overarching strategies and interventions required to address financial challenges and leverage funds from private and international sources, with identification of appropriate sources of funding and support needs matched to the identified actions. • Request guidance from IPCC regarding GHG accounting from lake methane utilization whilst developing project and emissions data from Lake Kivu power project. Rwanda NDC Implementation: Final Report Page xiv • Establish a detailed implementation plan with a timeline and roadmap of actions through 2025 and 2030, with roles and steps identified within each sector (electricity generation, transport, industry, waste, agriculture) describing how mitigation projects and programs will be embedded within national and regional planning. The following recommendations are made for implementation of the adaptation component: • Consideration of the selected adaptation indicators for program and projects design, implementation and reporting to funders. Climate action requires performance measures to monitor and report progress for purposes of accountability. It is therefore important that sectors continually improve the relevancy of monitoring and evaluation framework. • Provide national level adaptation reporting that align and respond to data and information demands at strategic levels including NST and sector strategic plans. National policies and strategies must rely on responsive data to effectively integrate climate adaptation to achieve national sustainable development goals. • Develop a strategy to evaluate investments in adaptation projects and programs based on reliable metrics to increase likelihood of replication and scale up of proven interventions. • Design strategic ways to provide capacity building to sectors, including sector experts, to facilitate planning and continuous NDC monitoring in general and in particular on climate adaptation. • Elaborate a detailed financing strategy through the revised NDC implementation plan that consider the prioritized adaptation interventions and provide guidance for accelerating national access to scalable climate finance. FONERWA has been institutionalized to support a coherent national climate resources mobilization strategy. Notably, the fund is poised to streamline and boost domestic resources and private sector, which is crucial for NDC resources mobilization to fill unconditional resources gap. Rwanda NDC Implementation: Final Report Page xv 1 INTRODUCTION 1.1 Background: the UNFCCC and Paris Agreement At the 21st Conference of the Parties (COP21) in Paris, on 12 December 2015, Parties to the United Nations Framework on Climate Change (UNFCCC) reached a landmark agreement to combat climate change and to accelerate and intensify the actions and investments needed for a sustainable low carbon future. The Paris Agreement (PA) entered into force in November 2016, following the universal adoption of the Agreement by Parties. Through the PA, developed and developing countries made individual commitments to transition toward a climate-resilient and low-emissions future. Importantly, the Agreement acknowledges that the Sustainable Development Goals (SDGs) ambitions will require a collective and concerted action on climate change, and therefore an ambitious climate action underpin the potential achievement of sustainable development. It was immediately evident that transitioning the high-level targets into concrete action would require elaborate country level planning and sector coordination, reliable and predictable financial resources to make investments and results impactful. Countries as Parties to the agreement would lead the process of planning, implementing, monitoring, reporting and revising their climate efforts. It was understood and repeatedly communicated that international effort would require developed countries to provide developing countries with technology transfer, capacity building and finance in order to deal with climate change impacts especially adaptation. Additionally, Article 7 of the Paris Agreement cautions against any additional reporting burden for developing country Parties. As such, many Parties will likely communicate adaptation as part of their progress updates on NDC implementation, or as part of their national communications (FAO, 2016). The Paris Agreement sets the following three long-term goals: 1. to hold global warming to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C; 2. to increase the ability to adapt to the adverse effects of climate change and to foster resilience; and 3. to make finance flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development (Article 2.1). Parties are required to undertake and communicate efforts to contribute to the achievement of these goals in the form of Nationally Determined Contributions (NDCs) communicated to the UNFCCC (Article 3). NDC’s are therefore the centrepiece of the Paris Agreement agreed through an international partnership that forms the foundation for the pathway towards a low-carbon and climate resilient development. Rwanda NDC Implementation: Final Report Page 1 Box 1.1 Nationally Determined Contributions (NDC) under the Paris Agreement In the lead up to the Paris Climate Conference in 2015, all Parties to the UNFCCC were invited to submit their Intended Nationally Determined Contributions (INDCs) outlining how they will make contributions to both the mitigation of climate change and adaptation to its impacts. Parties have since made submissions to the UNFCCC containing a wide variety of commitments and pledges, including economy wide emissions reductions, intensity reduction targets, and future emission targets set as a deviation from a business-as-usual (BAU) scenario. Most INDCs included a range of technology, sectoral, policy and/or programme specific pledges. With the formal entry into force of the Paris Agreement (PA) on 4 November 2016, these INDCs become binding Nationally Determined Contributions (NDCs) from 2020 onwards. To ensure increasing levels of ambition to combat climate change, the PA requires that, at a minimum of every five years, Parties submit revised NDCs that represent a progression beyond the Party’s then current NDC. The PA also establishes a new ‘transparency framework’ for action and support, providing the basis for Parties to monitor and report on their progress in implementing their NDCs (Article 13). The PA also introduced the possibility for new mechanisms to emerge to support the financing of low carbon technology deployment in developing countries (Article 6), including the use of voluntary Cooperative Approaches and a Sustainable Development Mechanism (SDM) to provide a project-based crediting mechanism administered by the UNFCCC. Climate finance is central to the Agreement and the ability of developing countries to reach more ambitious levels of emissions reduction. Recognising this need, Article 9 of the Agreement requires developed country Parties to provide financial resources to assist developing country Parties in achieving mitigation. The detailed modalities, procedures and guidelines covering all parts of the PA have since been subject to ongoing discussions with the UNFCCC process. In December 2018 in Katowice, Poland, Parties agreed on a Paris Agreement ‘rulebook’ to put those in place, work which has progressed through 2019 and during the 25TH Conference of Parties to the UNFCCC (COP25) held in Madrid, December 2019. Although several elements of the rulebook are still to be finalised, Parties have now established many of the rules and guidelines detailing how the PA will operate and be implemented in practice. Source: authors 1.2 Rwanda’s national context 1.2.1 Climate impacts and vulnerability A global warming effect ranging from between 0.8°C to 1.2°C, compared to the pre-industrial revolution, has been largely attributed to human activities (IPCC, 2018). As with many other countries, Rwanda is increasingly experiencing the impacts of climate change. Rainfall has become increasingly intense and the variability is predicted to increase by 5% to 10% (GoR, 2017b). Changes in temperature and precipitation and their distributions are the key drivers of climate and weather- related disasters that negatively affect Rwandans and the overall economy. The main risks/impacts that adversely affect the population include droughts, floods, landslides and storms. These are associated with damages of infrastructures, loss of lives and property including crops, soil erosion, water pollution, etc. (GoR, 2017b; REMA, 2015). Rwanda NDC Implementation: Final Report Page 2 A rise in temperature is predicted across Rwanda in the coming years up to 2050, especially during the dry seasons. An additional seasonal increase of between 0.10 °C and 0.30 °C is projected to be added on annual mean temperature throughout the country expect for the northern region where a decrease of 0.06°C is anticipated. Furthermore, a decreasing trend in mean rainfall and number of rainy days is projected (GoR, 2018a). This explains that more dry spells are anticipated across the country especially in the eastern region. Climate change will also upset the north-west highlands and south-western districts of Rwanda with rise in rainfall intensities. According to the TNC report, there is high probability that the number of days with extreme temperature will continue to increase by 2050 whereas the days with extreme rainfall will be relatively constant (GoR, 2018a). The impacts of climate change on Rwanda, however, are disproportionate to its contribution. Rwanda is, in fact, extremely vulnerable to climate change. The National Risk Atlas of Rwanda highlights that the country is highly prone to drought, flood, landslide, earthquake and windstorm (MIDIMAR, 2015). Besides, other activating factors to climate change vulnerability consist of socio- economic drivers such as building in flood prone areas, high population density in prone areas, increased value of assets in flood-prone areas, poor management of soil erosion, etc. (SEI R. a., 2009). 1.2.2 Green Growth and Climate Resilience Strategy The Government of Rwanda (GoR) is committed to taking urgent action to mitigate and adapt to the effects of climate change. As a Party to the UNFCCC, the country seeks to contribute to the ambitious goal of limiting temperature rise to 1.5oC agreed under the Paris Agreement (UNFCCC, 2015). Though Rwanda is among the countries with lowest emission per capita (GoR, 2011), it is vulnerable to climate change mainly due to the hilly topography, high population density and dependence on rain-fed agriculture. Therefore, adaptation to climate change is a key concern and a priority for the country. As is true of most African nations, Rwanda’s contribution to climate change in the form of greenhouse gas (GHG) emissions is relatively small, although emissions from deforestation, agriculture, and land use, combined with string expected emission growth from expected economic development and energy use, and are significant enough within Rwanda’s carbon footprint to demand mitigation response. In 2011, the country adopted the Green Growth and Climate Resilience Strategy (GGCRS) which sets out the country’s actions and priorities on climate change and how these with be mainstreamed within economic planning (GoR, 2011). The strategy provides a vision for how Rwanda can tackle climate change through become a climate resilient and low carbon economy, and projects actions to be undertaken to inform Rwanda’s strategy for economic development, Vision 2050. The document provides the basis for the subsequent development of its Nationally Determined Contribution (NDC), as described below. 1.3 Rwanda’s Nationally Determined Contribution Rwanda submitted its Intended Nationally Determined Contribution (INDC) to the UNFCCC in September 2015, setting out its adaptation and mitigation goals. With the entry into force of the Rwanda NDC Implementation: Final Report Page 3 Paris Agreement in November 2016, the INDC formally became Rwanda’s first NDC. The NDC is built upon the GGCRS, as well as other key national guiding documents including Vision 2050, NST1, Sector Strategic Plans, SPCR, and Sustainable Energy for All (2015-2030). Rwanda’s NDC has two components, as has been elaborated in the GGCRS through the following programmes of actions: • Mitigation: Seven broad programmes of action are identified, covering a wide range of interventions within each of the key sectors. These include low carbon electricity generation from hydropower and solar PV, small-scale generation, and energy efficiency and demand side management (energy); promotion of public transport and vehicle emission standards (transport); resource efficiency and energy demand reductions (industry); implementation of low carbon urban systems (waste); and sustainable forestry, agroforestry and biomass energy (agriculture and forestry).2 • Adaptation: Priority interventions are identified as Sustainable intensification of agriculture; Agricultural diversity in local and export market; Sustainable forestry, agroforestry and biomass energy; Ecotourism conservation and payment of ecosystem services promotion in protected areas, Integrated water resources management (IWRM) and planning; Integrated approach to sustainable land use planning and management, disaster management; and climate data and projections. The NDC states that while the GoR will continue to commit significant resources to climate change- relevant strategies, the full implementation of the strategic mitigation actions is conditional on the support of international stakeholders (GoR, 2015a). In addition, Rwanda intends to meet its commitments and/or increase the level of its contribution through the use of international market mechanisms where appropriate, building upon the experience of the Clean Development Mechanism (CDM) and other existing market mechanisms such as Nationally Appropriate Mitigation Actions (NAMAs) and the mechanism for Reducing Emissions from Deforestation and Forest Degradation (REDD+). Rwanda has since taken steps to align the NDC with existing national policy frameworks and sector strategies such as Vision 2050, the National Strategy for Transformation (NST) and the GGCRS. This will help ensure that national development programming effectively integrates climate action that is in alignment with the sustainable development goals (SDGs). 1.4 Project aims and scope of work Rwanda is planning to submit its updated NDC to the UNFCCC ahead of the 26th Conference of the Parties (COP26) in Glasgow in November 2020. This requires building upon existing work in developing quantifiable mitigation and adaptation targets, and the prioritization of interventions to support these two areas. 2 The mitigation contribution is based on estimated emission reductions against a projected ‘business as usual’ (BAU) baseline for the target year of 2030 based on policies and actions conditional on availability of international support for finance, technology and capacity building. The NDC is economy-wide covering emissions from energy, road transport, industry, waste and agriculture, forestry, and other land use (AFOLU) and covers the three GHGs carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) (GoR, 2015a). Rwanda NDC Implementation: Final Report Page 4 After joining the NDC partnership in 2018, Rwanda through the Ministry of Environment (MoE) as the lead focal institution, requested technical support from the NDC Partnership to help coordinate implementation of Rwanda’s NDCs across participating sectors. Following that request, the NDC Support Facility of the World Bank has provided technical assistance to produce targets and evaluate priority interventions to be included in the revised NDC. The support builds on the World Bank’s support for the Strategic Program for Climate Resilience (SPCR), the Forest Investment Plan (FIP), the Scaling Up Renewable Energy Program (SREP), and the forthcoming Climate Smart Agriculture Investment Plan. The main government counterparts for this work are the MoE, Ministry of Agriculture and Animal Resources (MINAGRI), Ministry of Infrastructure (MININFRA), Ministry of Finance and Economic Planning (MINECOFIN), and the Rwanda Environmental Management Authority (REMA). The scope of technical assistance provided by the World Bank covers both mitigation and climate adaptation aspects of Rwanda’s revised NDC to be submitted ahead of COP26: • Mitigation: produce quantified targets for GHG emissions reductions, evaluate priority interventions and develop the implementation roadmap • Adaptation: Produce quantified targets for adaptation/resilience, evaluate priority interventions, develop monitoring and evaluation (M&E) framework for adaptation actions and strengthen national capacity for resource mobilization This scope of work will help Rwanda to set mitigation and adaptation targets and respective costs for achieving those targets through 2025 and 2030. Once validated by the GoR and key stakeholders, these will be reflected in the revised NDC to be submitted to UNFCCC ahead of COP26. 1.5 Outline of this report This report presents the results of the technical analysis provided in support of Rwanda’s NDC development for both its mitigation and adaptation components. The outline of the document is broadly based around these two components with Sections 3, 4 and 5 covering the mitigation analysis and Sections 6, 7, 8 and 9 covering the adaptation analysis. Estimated funding requirements, and conclusions and recommendations are subsequently presented for both components together. The report is structured as follows: • Section 2 outlines the methodology and overall approach to the assessment and scope of analysis for both the mitigation and adaptation components. • Section 3 presents the development of a BAU emissions projection under which NDC mitigation actions are not implemented, including analysis of key drivers for future emissions growth. • Section 4 describes a technical and economic assessment of GHG mitigation options identified for Rwanda in order to determine which options are most suitable as prioritised mitigation actions within the NDC. Options are quantified in terms of their mitigation and economic potential, and prioritised according to a criteria-based evaluation, before grouping them into either “unconditional” or “conditional” NDC measures. Rwanda NDC Implementation: Final Report Page 5 • Section 5 describes the results of scenario-based modelling to determine the potential emissions reduction contribution from the identified NDC mitigation options through 2030 compared to BAU. • Section 6 sets out the current framework of adaptation and resilience initiatives in Rwanda including the role of adaptation within priority Sector Strategic Plans and the key baseline data and information considered relevant to climate adaptation and resilience. • Section 7 addresses some of the key challenges to implementation of adaptation and resilience options at a national and regional policy planning level as well as a project/program level. • Section 8 provide an evaluation of adaptation interventions and sets out a framework of indicators. • Section 9 proposes a monitoring, evaluation and reporting framework for mitigation and adaptation aligned with the prioritised options, drawing upon stakeholder and expert consultation. • Section 10 presents estimates of funding requirements for both mitigation and adaptation components of the NDC through 2025 and 2030, including a breakdown by sector and according to “unconditional” or “conditional” measures. • Section 11 provides key conclusions and recommendations for the next stage of work in Rwanda’s NDC implementation A series of technical annexes are appended to the report: • Annex A provides a detailed description of the technical and economic analysis undertaken for the identified NDC mitigation projects. • Annex B describes the criteria-based evaluation for adaptation interventions. • Annex C provides an initial assessment of potential mitigation measures within the forestry sector.3 3Due to large methodological and data uncertainties in emissions and emission removals estimation and baseline determination, forestry is not included within the scope of the NDC targets Rwanda NDC Implementation: Final Report Page 6 2 METHODOLOGY This section summarises the methodology and overall approach used in undertaking mitigation and adaptation components of the technical assistance. Further detail is provided in subsequent sections of the report and in the technical annexes. 2.1 Mitigation The overall objective of the technical support is to assist the GoR in the development of their NDC implementation framework for mitigation. The analysis aimed to address several key questions: • What are the most feasible BAU and GHG emission reduction pathways through 2030? • What can be delivered across sectors and programs (GHG emissions mitigation)? • What are the economic impacts from GHG mitigation actions (costs and benefits)? • What type of NDC target(s) could be adopted? • What factors could impact Rwanda’s ability to achieve the NDC through 2030? • What actions, arrangements and funding sources will be needed to implement the NDC? The support includes a technical analysis phase of work, the results of which will then be used to inform Rwanda’s NDC mitigation targets and subsequently a framework for NDC implementation covering policy planning, MRV, and financing aspects. This has been undertaken through a process that integrates an analysis of Rwanda’s existing sectoral and climate policy framework, the generation of qualitative information through consultation with government officials, experts and stakeholders, quantitative modelling of mitigation options and scenarios, and the development of actions to help implement the revised NDC and track its progress. This report describes the technical analysis undertaken. The aim was to develop an evaluation of NDC mitigation actions based on updated information and an in-depth assessment of the country’s mitigation potential. This has been undertaken using detailed technical and economic analysis and multi-criteria evaluation of mitigation options. In so doing, the analysis builds on the work undertaken in support of Rwanda’s INDC submission in 2015 and other more recent studies including e.g. GHG mitigation estimates made in the context of NAMAs and the Third National Communication (TNC) to the UNFCCC (GoR, 2018a), and a variety of other official data and information sources. The technical analysis comprises of three main tasks: • Task 1: Develop BAU emissions forecasts: Based on the national GHG inventory emissions in all IPCC sectors (energy, transport, industry, waste, and agriculture, forestry and other land use; AFOLU) for the base year of 2015, develop a revised BAU baseline scenario through 2030. Variations on the BAU baseline to be developed according to key drivers of national GHG emissions e.g. alternative GDP and/or population projections. • Task 2: Assess and prioritise mitigation actions: Identify and collect information on mitigation options within the NDC sectors based on discussions with in-country officials and experts, quantify their emissions reduction potential through 2030 compared to BAU and undertake an economic cost-benefit analysis (CBA) of each option. In order to prioritize actions and determine which can be supported domestically and which require international Rwanda NDC Implementation: Final Report Page 7 support, undertake multi-criteria-based assessment of the identified measures to determine environmental effectiveness, socio-economic effectiveness and feasibility. • Task 3: Develop alternative GHG pathways: Model alternative GHG pathways based on the identified and prioritised mitigation options against the BAU baseline through 2030 to understand emissions reduction potential across NDC sectors and associated costs and investment needs. The interaction between these three elements is summarised below in Figure 2.1. Figure 2.1 Overview of approach to mitigation technical analysis Source: Authors 2.2 Adaptation Lessons from the World Bank Action Plan and 2025 Climate Change targets identified the following major areas of focus relevant to Rwanda’s NDC implementation in relation to adaptation: • Boost adaptation financing by increasing access to and effectiveness of additional climate adaptation finance. Rwanda NDC Implementation: Final Report Page 8 • Drive a mainstreamed, whole-of-government programmatic approach through systematic climate risk management at the country and sector levels and subsequently implemented through sub-national levels. • Development of an effective and reliable rating system basing on a clear analytical framework to facilitate improved tracking and incentivizing progress on adaptation and resilience. The commitment to implementing the target on better tracking underpins the focus of this assignment aiming to provide support in the following areas: • Technical assistance to develop consensus on priority interventions and targets on adaptation to inform Rwanda’s revised NDC. • Support the development and implementation of the Monitoring and Evaluation Framework for adaptation actions partly drawing from and strengthening the Environment and Natural Resources Results Based Monitoring and Evaluation (ENR RBME) and in particular provide capacity development support building on the resilience indicators. • Support strengthening of national capacity specifically targeting public and private resources mobilization to implement the NDC starting with Deep dive resources US$2.2 Million that the WB through the NDC facility is implementing in partnership with the National Fund for Environment (FONERWA). The methodology was based on reviewing the existing analytical work carried out in the Green Growth and Climate Resilience Strategy (2011), the Strategic Program for Climate Resilience (2017), the Forest Investment Program (2017), the vulnerability index (National, 2015 and District 2018), Rwanda National Communication to UNFCCC (2018), the Sector Strategic Plans (2017) and the NDC implementation Plan (2017). As shown in Figure 2.2, the methodology considered the development of a long list of adaptation actions, their prioritization, indicators development which will inform the framework for NDC implementation and revised actions/activities. Figure 2.2 Framework of analysis and scope for the adaptation work Rwanda NDC Implementation: Final Report Page 9 Consultation with experts from multiple sectors was conducted based on the developed analytical framework. The specific objectives for the consultation were: 1. To check if the information included in the adaptation analytical framework is relevant to the sector. 2. Share other internal reports that can be useful for the measurement, reporting and verification (MRV) for sector guidance and validation. 3. Advise on the projected 2025 and 2030 sectoral targets, since the existing ones are primarily drawn from NST 1 that has projections up to 2024 only; 4. Inform and develop consensus on the costing of climate adaptation specific priority actions, including an outline of sources of finance categorized as “conditional” (where the Party would be willing to increase its ambition level given certain conditions were met, otherwise referred to as supported measures) and “unconditional” (unilaterally funded). 5. Agree on the MRV to report which in the case of adaptation focuses on monitoring and reporting on financial flows to address adaptation/resilience action. The process involved an extensive review of relevant documents on climate adaptation that have developed over time starting with the Green Growth and Climate Resilience Strategy and the associated sector working papers. It is important to note that this was the basis of the INDC and subsequently the NDC that was ratified under the PA. Other documents and reports that were reviewed to significantly inform and influence this assignment were the SPCR along with the Gaps and Needs Analysis, FIP and the NDC implementation plans (2017 & 2018) as well as the national reports on the vulnerability index (2015 and 2019) and the third National communications. The Sector Strategic Plans (SSPs) served as the critical reference documents for sector consultation even considering their scope is remarkably beyond the climate adaptation/resilience. It is recognized that in order to influence effective mainstreaming of climate adaptation in sector priorities and consequently in a strategic way for national uptake including at the NST and therefore policy levels, clear adaptation metrics including indicators and targets must be generated and agreed upon as measures to guide collection of gender disaggregated data. To achieve this in a systematic way, the assessment ensured priorities were set in a manner that identified adaptation actions even as additional to development targets. This then helped set adaptation indicators to guide baselines and categories of metrics at global, national/sub-national (to influence SSPs and DDSs) and finally at program and project levels. Only then can it be possible to map out specific capacity needs including those targeting institutional coordination that improve the environmental conditions for design of projects and programs that can attract financing at scale to address Rwanda’s sustainable development needs. This served as the context of the analytical framework that consistently influenced the Results Based Monitoring Evaluation and Learning (RBME&L). It was therefore crucial in development of a functional framework for ENR sector in order to serve as a tool for cross sector mainstreaming of climate change adaptation/resilience. Rwanda NDC Implementation: Final Report Page 10 3 BAU EMISSIONS PROJECTIONS 3.1 Overview and approach This section describes the development of a BAU GHG emissions forecast for Rwanda. Firstly, an updated inventory of GHG emissions sources covered by the NDC sectors is presented for the base year of 2015 according to International Panel on Climate Change (IPCC) reporting categories (IPCC, 2006). Emissions are then projected from this base year through 2030 under a BAU scenario according to which NDC mitigation policies and actions are not implemented. This projection provides the reference case against which the emissions reduction potential from specific mitigation actions (as described in Section 4) can be estimated under alternative GHG reduction pathways (as described in Section 5). The section concludes with a sensitivity analysis around key drivers influencing future emissions through 2030. The BAU modelling approach is based on detailed bottom-up activity and GHG projections developed for each emitting sector through 2030. These reflect a number of assumptions determining changes in inter alia energy supply and demand, sector output, technology uptake, and policy choices. In so doing, existing government projections and plans were assessed, and experts consulted within relevant ministries, agencies and organisations. These are described in more detail below according to each of the key emitting sectors; energy, IPPU, waste, agriculture. Note that as work is currently ongoing to better quantify national emissions and removals from forestry, these are excluded from the BAU analysis. The modelling draws heavily upon, and updates, the emissions projections work undertaken as part of the TNC work (GoR, 2018a). These provide long-term emissions projections for Rwanda through 2050 using the Long-range Energy Alternatives Planning System (LEAP) software system developed by the Stockholm Environment Institute (SEI, 2009a) and supplemented by various excel-based calculations. The BAU modelling described in this section departs from the TNC projections in several ways. These include: 1. Modelling more dynamically linked to GDP growth and other emissions drivers. Whereas the TNC projections are based on projecting future emissions by extending previous trends from the historic emissions data, the current BAU links future changes more closely to relevant factors driving output and emissions changes, including economic growth, population growth, official agricultural production plans and power expansion planning. As described in the sensitivity analysis further below, two key sources have been used to develop alternative outlooks for GDP growth: - National GDP growth forecast aligned with Rwanda’s Vision 2050 strategy for economic growth (GoR, 2017a) - IMF World Economic Outlook, Rwanda GDP growth outlook (IMF, 2019) The former source - representing the GoR official growth outlook - has been used as the base case GDP assumption in the detailed BAU projection described in this section. National population projections have been based on the low, medium and high scenarios contained in the Fifth Integrated Household Living Survey (EICV5) (GoR, 2018b); the medium scenario has been adopted as the base case BAU assumption. Rwanda NDC Implementation: Final Report Page 11 2. Use of regression analysis. Extensive use of regression analysis has been undertaken based on latest available data to better understand and inform relationships between certain forecast model parameters (e.g. analysis of vehicle growth by type/class according to GDP and population changes, from historic data). 3. More detailed characterisation of emitting sectors to enable more in-depth and robust modelling of factors determining output and corresponding energy use and GHG emissions (e.g. development of detailed road transport fleet modelling). In addition, the revised BAU projection makes use of more recently available information sources such as e.g. transport and vehicle survey data, official statistics, policy planning documents etc., as described within each sector below. Taken together, and along with some revisions and corrections made to the base year inventory data (see below), these revisions are considered to result in a more robust and accurate basis for developing a BAU scenario. Importantly, they also allow for key drivers such as economic and population growth to be varied within the modelling in order to assess their potential impact upon future emissions (sensitivity analysis). 3.2 GHG emissions inventory The latest official GHG inventory data, as reported in Rwanda’s TNC (GoR, 2018a) covers emissions up to the year 2015. This year was adopted as the common base year for the revised BAU modelling. Within the resources and time schedule of the technical assistance, a review of the GHG inventory data was undertaken. This resulted in the correction of some errors and inconsistencies4. In addition, more recently available information and survey data allowed for actual activity and energy consumption data to replace previously estimated values (described further below according to each sector).5 The historic and base year data described below are therefore based on this revised dataset which is considered the most recent and accurate information available against which to assess NDC mitigation contributions. Figure 3.1 shows national GHG emissions for the years 2006-2015 from each of the sectors and activities covered by the NDC, excluding forestry. The series shows that emissions increased significantly over the ten-year period, from around 3.7 million tonnes carbon dioxide equivalent (tCO2e) to 5.3 million tCO2e, representing an overall increase of 46%. Emissions from industrial processes and product use (IPPU), waste, and energy use have seen the fastest growth rates over this period - increasing by 102%, 76%, and 58% respectively. Emissions from agriculture, representing the largest contributor to total emissions, increased by around 33% over the same period. The overall trend in emissions growth closely reflects production and output across these sectors, which has seen rapidly increasing industrial output, waste generation and demand for fossil- based energy at the same time as more modest growth in agricultural output e.g. livestock and crop production. 4 Most noticeably the over-estimation of emissions associated with urea fertiliser application within IPPC reporting category 3.C.3. 5 These revisions have been described in more detail in a note submitted to the GoR on 6 September 2019. Rwanda NDC Implementation: Final Report Page 12 Figure 3.1 GHG emissions by sector 2006-2015, MtCO2e Source: Rwanda National GHG Inventory data (September 2019) GHG inventory data in the base year 2015 is shown in Table 3.1 according to IPCC reporting categories for all GHG emissions sources, and summarised in aggregated form in Figure 3.2. Total emissions excluding forestry are estimated at 5.33 million tCO2e for 2015. The agriculture sector accounted for the largest share of the total (2.94 million tCO2e, 55% of total), followed by energy (1.68 million tCO2e, 31% of total) and waste (0.64 million tCO2e, 12% of total). Emissions from IPPU represented just 0.08 milliontCO2e, equivalent to around 2% of total emissions in 2015 (mainly associated with calcination CO2 emissions from clinker production). Emissions from livestock, predominantly CH4 from enteric fermentation in cattle, represented the largest emissions source category in the base year, followed by N2O emissions from managed soils in crop production. Following these agriculture sources, major sources included CO2 emissions from fuel combustion for heating and cooking in buildings (LPG, kerosene), which accounted for 14% of the total, and CO2 emissions from liquid fuel use in road transport (diesel, gasoline), which accounted for 13% of the total. The data shows that fossil fuel combustion in power generation accounted for a small share of overall emissions, reflecting the current relatively low level of power generation per capita in Rwanda and also the dominant share of non-emitting hydropower within the grid mix (as discussed in more detail below). Rwanda NDC Implementation: Final Report Page 13 Table 3.1 GHG emissions by source in 2015, MtCO2e IPCC Reporting Categories GgCO2e MtCO2e 1.A.1.a.Electricity and Heat 1.A.1.Energy Industries 159 0.16 Production 1.A.2.Manufacturing Industries and Construction 91 0.09 1.A. Fuel 1. Energy Combustion 1.A.3.Transport 1.A.3.b.Road Transport 686 0.69 Activities 1.A.4.a.Commercial/Institutional 102 0.10 1.A.4.Other Sectors 1.A.4.b.Residential 639 0.64 2.A. Mineral Industry 69 0.07 2.C. Metal Industry 2 0.002 2. IPPU 2.D. Non-Energy Products from Fuels and Solvent Use 4 0.004 2.F. Product Uses as Substitutes for Ozone Depleting Substances 7 0.01 3.A.1.Enteric Fermentation 1,284 1.28 3.A. Livestock 3.A.2.Manure Management 673 0.67 3.B. Land 3.B.1.Forest Land - - 3.C.3.Urea application 6 0.01 3. AFOLU 3.C. Aggregate Sources and 3.C.4.Direct N2O Emissions from managed soils 540 0.54 Non-CO2 3.C.5.Indirect N2O Emissions from managed soils 191 0.19 Emissions Sources on 3.C.6.Indirect N2O Emissions from manure management 148 0.15 Land 3.C.7.Rice cultivation 98 0.10 4.A. Solid Waste Disposal 187 0.19 4.B. Biological Treatment of Solid Waste 159 0.16 4. Waste 4.C. Incineration and Open Burning of Waste 1 0.001 4.D. Wastewater Treatment and Discharge 290 0.29 Total emissions Energy 1,677 1.68 Total emissions IPPU 82 0.08 Total emissions AFOLU 2,940 2.94 Total emissions Waste 637 0.64 TOTAL emissions (excluding forestry) 5,337 5.33 Note: Transport emissions data are available for road transport only; civil aviation, rail and waterborne transport categories are not include due to lack of data and their very small contribution. Source: Rwanda National GHG Inventory data (as of September 2019); forestry excluded. Rwanda NDC Implementation: Final Report Page 14 Figure 3.2 National GHG emissions by source in 2015, MtCO2e Note: Transport emissions data are available for road transport only; civil aviation, rail and waterborne transport categories are not include due to lack of data and their very small contribution. Source: Rwanda National GHG Inventory data (as of September 2019); forestry excluded. For comparative purposes, Figure 3.3 benchmarks Rwanda’s total GHG emissions against other East African countries on a per capita basis, and also emissions intensity of economic output i.e. emissions per unit of gross domestic product (GDP). The data show that Rwanda has relatively low per capita emissions - around 0.5 tCO2e - compared to other countries within the region. This figure is around one fifth of the regional average and just thirteenth of the world average, reflecting Rwanda’s predominantly agricultural economy based on subsistence farming and low fossil energy demand compared to traditional energy sources such as wood and other biomass. The data also show that Rwanda has a relatively low emissions intensity - around 1.3 tCO2e per ‘000 (thousand) USD GDP – which is also around one fifth of the regional average. Although per capita GDP is relatively low in Rwanda at around 750 USD, the low intensity value mainly reflects the importance of non-energy intensive and low emitting sectors within the national economy such as agriculture, tourism and services. The sections below next describe the BAU development according to each sector, followed by a summary of BAU total emissions through 2030 and sensitivity analysis. Rwanda NDC Implementation: Final Report Page 15 Figure 3.3 Regional comparison of Rwanda per capita and per GDP emissions Source data: USAID, 2015 Note: Emissions exclude land use change and forestry Rwanda NDC Implementation: Final Report Page 16 3.3 Energy Figure 3.4 shows the BAU emissions projection for energy sector emissions through 2030 for the base case (consistent with Vision 2050). Total emissions are forecast to almost treble over the period, rising from around 1.7 million tCO2e in the base year to 4.8 million tCO2e in 2030. As shown in the graph, emissions from all sub-sectors are forecast to increase with rapid growth seen in particular from power generation and manufacturing industry. The former reflects the current power system plan which foresees a large expansion of fossil-based generation on the grid, including from new peat and the Lake Kivu methane gas-fired capacity (see below), whereas the latter reflects strong growth assumptions in rapidly expanding sectors such as cement production and construction. Emissions from road transport are also forecast to rise significantly with increasingly vehicle ownership and assuming low levels of electric vehicle (EV) penetration and an absence of controls on vehicle standards. A more modest increase in emissions from buildings is expected, partly reflecting the large contribution of traditional and low carbon fuels in residential energy use and electricity use in the commercial and public sectors. These sectors however also see increasing emissions in the absence of targeted mitigation policies to increase renewable and off-grid energy use. Figure 3.4 BAU GHG emissions projection, Energy (base case) Source: Authors Rwanda NDC Implementation: Final Report Page 17 Table 3.2 BAU GHG emissions projection, Energy (base case) GHG emissions (MtCO2e) 2015 2020 2025 2030 Electricity generation 0.16 0.74 1.15 1.38 Manufacturing industry 0.09 0.16 0.30 0.52 Construction 0.02 0.03 0.05 0.07 Food industry 0.001 0.002 0.003 0.004 Non-Metallic minerals 0.07 0.12 0.22 0.41 Mining industry 0.01 0.01 0.02 0.03 Transport (road transport) 0.69 0.97 1.25 1.54 Motorcycles 0.31 0.42 0.53 0.66 Passenger cars 0.15 0.25 0.32 0.39 Light duty trucks 0.07 0.09 0.11 0.14 Trucks and buses 0.16 0.22 0.28 0.35 Other sectors (buildings) 0.74 0.88 1.09 1.38 Residential 0.64 0.71 0.78 0.86 Commercial and public 0.10 0.18 0.31 0.52 Total 1.68 2.76 3.79 4.82 Source: Authors Table 3.3 below summarises the approach to developing BAU projections for the energy sector across each of the relevant emissions source categories. A more detailed description is provided below for each key category, along with methodological choices, assumptions and data sources. Rwanda NDC Implementation: Final Report Page 18 Table 3.3 Summary of approach to BAU projections, Energy IPCC category Description Based on analysis of forecast electricity demand and planned generation through 2030 as published in the recent Energy Sector Strategic Plan (ESSP) (GoR, 2018c) and the Least Cost Power Development Plan (LCPDP) (REG, 2019). The model developed applying a reserve 1. A.1. Energy 1. A.1.a. Electricity and margin of 15 % (REG, 2019) with all new Industries Heat Production generation through 2030 met by fossil fuel capacity. GHG emissions calculated in LEAP power generation module based on fuel use, heat rate and other assumptions, through agreement with REG, and application of IPCC 2006 Tier 1 emissions factors. Energy demand linked to official GDP growth outlook (GoR, 2017a) through use of regression 1. A.2. Manufacturing Industries and analysis within energy-using industrial sectors. Construction GHG emissions modelled within LEAP industry module applying IPCC 2006 Tier 1 emissions factors. 1.A. Fuel Fuel consumption forecast for different vehicle Combustion classes based on road vehicle survey Activities information, transport demand, fuel use and fuel economy assumptions, and vehicle fleet 1. A.3. Transport 1. A.3.b. Road Transport modelling through 2030. Supplemented by use of regression analysis to develop correlation between vehicle ownership, and per capita GDP (based on GoR, 2017a; GoR, 2018b). 1. A.4.a. GHG emissions from buildings (commercial, Commercial/institutional residential and institutional energy use) linked to GDP and population growth (GoR, 2017a; GoR, 2018b) and simulated in the LEAP 1. A.4. Other buildings module. Emissions from residential Sectors buildings closely linked to population; 1. A.4.b. Residential emissions from commercial and institutional buildings linked to GDP and historical growth rates. Energy demand assumed to grow in line with 1. A.5. Non-specified official GDP growth outlook (GoR, 2017a) and based on trends over past decade. Source: Authors 3.3.1 Electricity generation The electricity generation BAU projection was developed based on the planned generation projects as detailed in the least-cost power development plan (LCPDP) (REG, 2019). Development of future renewable energy projects were considered to be NDC mitigation measures and therefore not included within the BAU scenario; existing renewable projects were assumed to continue generating Rwanda NDC Implementation: Final Report Page 19 at existing levels through 2030. The projection begins from a 2016 base year and includes generation and GHG modelling from four main fossil fuels: diesel (light fuel oil), residual fuel (heavy fuel oil), peat and methane gas. The power generation demand forecast is included in the LCPDP (REG, 2019), according to which, demand is expected to grow according to three main scenarios: a low growth scenario (8%), medium growth scenario (10 %) and high growth scenario (12%). The BAU ‘base case’ described in this section is based on the medium growth scenario6. According to this scenario, grid electricity generation is expected to more than double from current levels to 2,100 GWh in 2030. Figure 3.5 National electricity demand projections to 2030 (GWh) Source: REG, 2019 According to electric power generation plan published by the Rwanda Energy Group Ltd (REG), total available capacity in 2018 was around 154 MW (installed capacity was 216 MW) of which hydropower accounts for around one third (49.5 MW) and fossil based units the remaining two thirds (99 MW) (Table 3.4). Several small solar PV and biomass installations account for around 2 MW, with imports of 3.5 MW. 6The other two scenarios were considered within sensitivity analysis, with the ‘low growth’ scenario adopted to align with the lower GDP forecast as described by the IMF WEO; see Section 3.7.2. Rwanda NDC Implementation: Final Report Page 20 Table 3.4 National installed generating capacity as of 2018 Installed Available Capacity Type of Plant Name Owner COD Status Xstics Location Capacity (MW) (MW) Technology Ntaruka 11.25 2.5875 GoR 1959 Existing Renewable Burera Hydro Mukungwa I 12.00 6 GoR 1982 Existing Renewable Musanze Hydro Nyabarongo I 28.00 13.44 GoR 2014 Existing Renewable Muhanga Hydro Gisenyi 1.20 0.78 Prime Energy 1957 Existing Renewable Rubavu Hydro Gihira 1.80 1.26 RMT 1984 Existing Renewable Rubavu Hydro Murunda 0.1 0.045 Repro 2010 Existing Renewable Rutsiro Hydro Rukarara I 9.5 3.8 Ngali Energy 2010 Existing Renewable Nyamagabe Hydro Rugezi 2.2 1.1 RMT 2011 Existing Renewable Burera Hydro Keya 2.2 1.1 Adre Hydro&Energicotel 2011 Existing Renewable Rubavu Hydro Nyamyotsi I 0.1 0.06 Adre Hydro&Energicotel 2011 Existing Renewable Nyabihu Hydro Nyamyotsi II 0.1 0.06 Adre Hydro&Energicotel 2011 Existing Renewable Nyabihu Hydro Agatobwe 0.2 0.07 Carera-Ederer 2010 Existing Renewable Nyaruguru Hydro Mutobo 0.2 0.09 Repro 2009 Existing Renewable Musanze Hydro Nkora 0.68 0.34 Adre Hydro&Energicotel 2011 Existing Renewable Rutsiro Hydro Cyimbili 0.3 0.15 Adre Hydro&Energicotel 2011 Existing Renewable Rutsiro Hydro Gaseke 0.582 0.5238 Novel Energy 2017 Existing Renewable Gakenke Hydro Mazimeru 0.5 0.245 Carera-Ederer 2012 Existing Renewable Nyaruguru Hydro Janja 0.2 0.16 RGE Energy UK ltd 2012 Existing Renewable Nyabihu Hydro Gashashi 0.2 0.08 Prime Energy 2013 Existing Renewable Rutsiro Hydro Nyabahanga I 0.2 0.11 GoR 2012 Existing Renewable Karongi Hydro Nshili I 0.4 0.24 GoR 2012 Existing Renewable Nyamagabe Hydro Musarara 0.45 0.2205 Amahoro Energy 2013 Existing Renewable Nyabihu Hydro Mukungwa II 2.5 1.825 Prime Energy 2013 Existing Renewable Musanze Hydro Rukarara II 2.2 1.155 Prime Energy 2013 Existing Renewable Nyamagabe Hydro Nyirabuhombohombo 0.5 0.175 RGE Energy UK ltd 2013 Existing Renewable Nyamasheke Hydro Giciye I 4 1.6 RMT 2013 Existing Renewable Nyabihu Hydro Giciye II 4 1.6 RMT 2016 Existing Renewable Nyabihu Hydro Ruzizi II 12.00 10.68 GoR 1984 Existing Renewable Rusizi Hydro S-total 97.56 49.50 Hydro Jabana 1 7.8 7.41 GoR 2004 Existing None Renewable Gasabo Diesel Jabana 2 20 19 GoR 2009 Existing None Renewable Gasabo HFO-Diesel So Energy 30 28.5 So Energy&SP 2017 Existing None Renewable Gaasabo/Musanze Diesel S-total 57.8 54.91 Diesel Gishoma 15 14.25 GoR 2016 Existing None Renewable Rusizi Peat S-total 15 14.25 Peat Biomass (Rice Husk) 0.07 0.0665 Novel Energy 2016 Existing None Renewable Nyagatare Biomass S-total 0.07 0.0665 Biomass KP1 3.6 3.42 GoR 2008 Existing None Renewable Rubavu Methane Kivuwatt Phase I 26.4 26.4 Contour Global 2016 Existing None Renewable Karongi Methane S-total 30 29.82 Methane Jali 0.25 0.04 Mainz Stadwerke/Local Agency 2007 Existing Renewable Gasabo Solar GigaWatt /Rwamagana 8.50 1.19 Gigawatt Global 2013 Existing Renewable Rwamagana Solar Nyamata Solar 0.03 0.01 NMEC Nyamata 2009 Existing Renewable Bugesera Solar Nasho Solar PP 3.30 0.66 GoR 2017 Existing Renewable Kirehe Solar S-total 12.08 1.90 Solar Ruzizi 1 3.50 3.50 Snel Sarl 1957 Existing Renewable Rusizi Imports S-total 3.50 3.50 Imports Grand Total 216.0 153.9 Source: REG, 2019 The generation mix by technology for 2018 is shown in Figure 3.6. The figure shows that hydropower represents around one half of generation. The use of indigenous fossil fuels such as Lake Kivu methane gas (considered as natural gas fuel combustion in the base case analysis) and peat is growing while the use of imported fossil remains steady. This reflects the national energy policy to reduce imported fossil fuels in the national energy mix. Rwanda NDC Implementation: Final Report Page 21 Figure 3.6 National electricity generation, 2018 Source: REG, 2019 Assuming no new renewable generation (solar PV and hydro) is added under the BAU scenario, all planned thermal power plants (diesel, peat and methane gas) were modelled, and expected installation/retirement dates accounted for in the subsequent generation mix. Table 3.5 shows the planned power generation projects and their estimated commissioning dates, from the LCPDP (REG, 2019). Only projects falling within the first NDC period are included (i.e. committed before 2030). Table 3.5 Existing and planned generation projects from LCPDP # Power Station Nominal Capacity (MW) Commissioning date Non-renewable power plants 1 Hakan 80 2020 2 Symbion 50 2022 3 Symbion Extension 25 2022 5 KivuWatt 26.4 2015 6 Jabana 1&2 27.8 2004 and 2009 8 SO-Energy 30 2017 TOTAL: Non-renewable 222.2 Solar Power plants 1 Gigawatt global 8.5 2013 2 Nasho solar 3.3 2017 TOTAL: Solar 11.8 Hydro Stations<=5MW 1 Agatobwe 0.2 2010 2 Base 1 2.9 2020 3 Base 2 2.9 2020 Rwanda NDC Implementation: Final Report Page 22 4 Gisenyi 0.7 1957 5 Kabavu 0.1 2022 6 Kavumu 0.4 2018 7 Kigasa 0.2 2017 8 Kore 1.3 2022 9 Mpenge I&III 1.0 2019 10 Muganza 0.3 2022 11 Muhembe 0.3 2018 12 Mukungwa 2 1.0 2013 13 Mutobo 0.8 2019 14 Ngororero 2.7 2018 15 Ntaruka A 2.1 2020 16 Nyirahindwe I&II 1.2 2019 17 Nyirantaruco 1.3 2018 18 Nyundo 4.0 2020 19 Rubagabaga 0.3 2019 20 Rucanzogera 1.6 2022 21 Rugezi 1.1 2019 22 Rukarara V 5.0 2020 23 Rukore 2.0 2022 24 Rwaza I-Muko 2.6 2020 25 Rwondo 2.3 2020 TOTAL: Hydro Stations<=5MW 38.3 Hydro Stations>5MW 1 Bihingore 5.35 2021 2 Giciye III 7.2 2021 3 Nyabarongo II 37.5 2025 4 Rukarara VI 6.7 2020 TOTAL: Hydro>5MW 56.75 Regional Projects (hydro) 1 Rusizi III 48.3 2023 2 Rusumo 26.7 2022 Source: REG, 2019 (page 14) The electricity generation demand forecast was added in the energy demand module of the LEAP software system, with committed power generation projects added exogenously in the transformation module. The reserve margin was set to 15%; thermal efficiencies were set to 30% for diesel, biomass and residual fuel, and 40% for peat and gas. Figure 3.7 shows the resulting generation forecast, based on the medium demand projection chosen for the BAU case. GHG emissions were calculated within the LEAP software based on calculated fuel consumption and Tier 1 IPCC 2006 emissions factors. Figure 3.8 shows the corresponding GHG emissions intensity forecast. The forecast shows how the national grid emissions intensity is expected to increase through 2030 as additional plants are commissioned to meet rising demand, in the absence of NDC mitigation measures such as solar PV and hydropower. Rwanda NDC Implementation: Final Report Page 23 Figure 3.7 National electricity generation forecast, BAU base case (medium demand) Source: Authors, based on REG, 2019 Figure 3.8 BAU emissions intensity of grid generation, BAU base case (medium demand) Source: Authors, based on REG, 2019 Rwanda NDC Implementation: Final Report Page 24 3.3.2 Manufacturing industries GHG emissions from manufacturing industries were modelled based on the data published in the TNC (GoR, 2018a). The relationship between GDP growth and historic GHG emissions was analysed for each energy-using industry (non-metallic minerals industries, mining industries, food industries and construction). Emissions were modelled within the industry module of LEAP based on projected fossil energy use, which was assumed to grow at the same rate as national GDP for mining industries, food industries and construction, while emissions from non-metallic minerals industries (cement and clinker) were projected based on assumed production growth. Based on data provided by CIMERWA Cement Limited (CCL), a 13% growth rate was assumed. 3.3.3 Transport According to the national GHG inventory, road transport was the main contributor to total transport sector GHG emissions in 2015. Due to a lack of data and their relatively small contribution, emissions from other sources including civil aviation, rail and waterborne transport are not reported and have not been estimated as part of the projections. Given road transport’s large contribution to Rwanda’s energy emissions, a relatively simplified forecast of fuel use and GHG emissions from road vehicles was undertaken using available information from national statistics databases and various in-country and international studies. This improves on the previous approach which applies a simple aggregated forecast of sectoral emissions based on previous trends, with no modelling of vehicle and fleet characteristics or turnover. However, it should be noted that the approach remains relatively simple as it does not capture the impacts from various factors determining travel efficiency (in addition to vehicle efficiency). The approach to developing a BAU forecast for road transport is summarised below. Step 1: Characterization of existing vehicle fleet. Rwanda’s existing vehicle fleet was first characterised according to vehicle type, class, fuel type, and fuel economy. Vehicle numbers were based on official registration data for recent years provided in the National statistical yearbooks (Table 3.6) (NISR, 2014; NISR, 2015; NISR, 2016; NISR, 2017; NISR, 2018). Average fuel economy values (litres per 100 km) for each vehicle class and fuel type were developed, based on estimates including recent analysis undertaken by REMA of fuel economy for road vehicles registered in Rwanda (REMA, 2019), and data from the Rwanda NAMA report. Improvements in average fuel economy rates for future vehicles were estimated based on assumed vehicle efficient metrics provided by the Global Fuel Economic Initiative (GFEI, 2019)7. Based on national data for diesel and gasoline consumption in transport, average annual distances for each vehicle category were then developed (km per year). Total fuel consumption for the base year of 2015 was then calculated for each vehicle category, and fuel type within each category (diesel; gasoline), according to: 7 Equal to an overall assumed improvement of around 15% for all vehicles across the forecast period. This is acknowledged to be a major simplifying assumption, since it does not quantify the potential for decreasing efficiency of travel km arising from urban congestion and poor road quality. As such, the potential for measures to address these factors (i.e. through improved road networks and transport system planning) are also not captured in the methodology, either within the baseline or mitigation scenario(s). This issue is identified as an important area for further and more systematic analysis, including through support to improve national transport modelling and associated GHG impacts modelling. Rwanda NDC Implementation: Final Report Page 25 Fuel consumption = total number of vehicles x fuel economy (l/km) x distance travelled per vehicle (km) Table 3.6 Estimated vehicle fleet in Rwanda, 2006-2015 Category 2006 2009 2011 2013 2015 Motorcycles 15,224 33,121 49,367 68,846 83,338 Passenger cars 21,693 31,439 37,765 49,720 54,795 Light duty trucks 8,119 11,448 12,974 15,067 15,766 Buses 87 250 469 597 1,020 Microbuses 61 115 144 155 235 Trailers 457 667 733 831 808 Half trailers 89 162 186 188 203 Trucks 1,805 2,490 3,134 3,931 4,502 Other vehicles 96 327 552 814 1,258 Total vehicles 47,631 80,019 105,324 140,149 161,925 Source: based on NISR, 2018 Table 3.7 Fuel economy assumptions for existing and new vehicles l/100 km Existing fleet New fleet Motorcycles 4.00 3.39 Passenger cars (gasoline) 7.82 6.63 Passenger cars (diesel) 9.26 7.85 Buses 54.00 45.78 Microbuses 44.00 37.30 Trailers 29.00 24.59 Half trailers 15.00 12.72 Trucks 39.50 33.49 Other vehicles 39.50 33.49 Source: based on NAMA and REMA data Step 2: Vehicle fleet projected through 2030. A forecast was then made of numbers for each vehicle category through 2015-2030. Numbers of new vehicle registrations were estimated based on an increased demand in road transport. Regression models were built and used to analyse the relationship between vehicle numbers and population and GDP per capita; strong correlations were observed between GDP per capita and vehicle ownership per capita, which was applied to future growth projections. An average annual scrappage rate of 5% was assumed, in common with estimated historic scrappage rates in Rwanda, which are also in alignment with typical reported OECD values. From an estimated national fleet of 0.16 million road vehicles in 2016, numbers are Rwanda NDC Implementation: Final Report Page 26 projected to increase significantly to around 0.33 million by 2030, of which motorcycles account for 54% and passenger vehicles account for 36%. Figure 3.9 Projected vehicles numbers by mode 2015-2030 Source: Authors Note: LDVs include passenger cars and light-duty trucks Step 3: Estimation of fuel use and GHG emissions through 2030. Based on Steps 1 and 2 described above, fuel use estimates were next calculated for diesel, gasoline in each forecast year and a GHG forecast was made using the IPCC emission factors for mobile emission sources (IPCC, 2006). In the absence of robust alternative assumptions, the existing split between diesel and gasoline usage was assumed to remain the same through the forecast period. Figure 3.10 shows projected total road transport sector GHG emissions by mode through 2030. The outlook estimates total emissions to roughly double from around 0.77 million tCO2e in the base year of 2015 to 1.64 million tCO2e in 2030. Whilst this represents a major increase in GHG emissions, it should be noted that the rate of increase is lower than the projections for transport demand and vehicle numbers, largely reflecting assumptions around fuel economy improvements over time. While the methodology described above is considered an improvement over the previous LEAP forecasting, it should be noted that it remains relatively simplistic resulting in a high degree of uncertainty. A key limitation is that certain types of transport intervention are not quantified, including for example urban transport and road network improvements. These would have the effect of reducing aggregate emissions, although other factors such as increased congestion would similarly increase per km fuel consumption and resulting emissions. Modelling these and other Rwanda NDC Implementation: Final Report Page 27 factors, requiring additional resources and data/information collection, is recommended for future improvements in forecasting Rwanda’s road transport sector. Figure 3.10 Projected road transport sector GHG emissions by mode 2015-2030 Source: Authors Note: LDVs include passenger cars and light-duty trucks 3.3.4 Commercial and residential GHG emissions projection from energy use in buildings were linked to socio-economic variables GDP and population growth and simulated in the building module of LEAP. Whereas GHG emissions from residential buildings were assumed to grow in line with population for purposes of projecting LPG and wood fuels use, using existing estimates of per capita fuel use included in the TNC, GHG emissions from kerosene and biogas were assumed to grow in line with historical growth trends. GHG emissions from commercial and institutional buildings were assumed to grow as per historic growth rates for diesel and in line with GDP for other fuels. 3.4 Industrial processes and product use Figure 3.11 shows the BAU emissions projection for IPPU emissions through 2030 for the base case (consistent with Vision 2050). Total emissions are forecast to increase very significantly over the period, albeit from a very low base, rising from around 0.08 million tCO2e in the base year to 0.51 million tCO2e in 2030. The graph shows that emissions growth is dominated by the minerals production category (calcination CO2 emissions from clinker and cement production), with much smaller although growing contributions from other industrial sources. The increase reflects Rwanda NDC Implementation: Final Report Page 28 assumptions around ongoing growth from CCL and assumes current rates of clinker substitution and fuel use (see below). Figure 3.11 BAU GHG emissions projection, IPPU (base case) Source: Authors Table 3.8 BAU GHG emissions projection, IPPU (base case) GHG emissions (MtCO2e) 2015 2020 2025 2030 Minerals production 0.069 0.127 0.235 0.432 Metals production 0.002 0.003 0.005 0.010 Non-Energy products 0.004 0.007 0.013 0.024 ODS Substitutes 0.007 0.013 0.024 0.045 Total 0.08 0.15 0.28 0.51 Source: Authors Table 3.9 below summarises the approach to developing BAU projections for the IPPU sector across each of the relevant emissions source categories. A more detailed description is provided below for each key category, along with methodological choices, assumptions and data sources. Rwanda NDC Implementation: Final Report Page 29 Table 3.9 Summary of approach to BAU projections, IPPU IPCC category Description Based on forecast cement (clinker) and lime products applying IPCC 2006 emissions factors. Forecast output linked to GDP growth in industrial sector (GoR, 2017a) and 2.A. Mineral Industry informed by CCL facility expansion and renovation, which has almost doubled from 2015 to 2018, based on strong demand from construction sector. Calculations made using IPCC 2006 guidelines and based on quantity of production. 2.C. Metal Industry 2. IPPU Production output linked to GDP growth forecasts in industrial sector (GoR, 2017a). Calculations made using IPCC 2006 guidelines 2.D. Non-Energy Products from Fuels and and based on quantity of production. Solvent Use Production output linked to GDP growth forecasts in industrial sector (GoR, 2017a). Calculations made using IPCC 2006 guidelines 2.F. Product Uses as Substitutes for Ozone and based on quantity of production. Depleting Substances Production output linked to GDP growth forecasts in industrial sector (GoR, 2017a). Source: Authors 3.4.1 Mineral Industry The mineral industry covers process emissions from the activity data in cement production and lime production. For cement, the baseline emissions associated with cement kiln dust has been calculated using the IPCC 2006 Tier 1 estimation method applying the default calcination emission factor of 0.52 (IPCC, 2016). Similarly, emissions from two type of lime produced in Rwanda - namely high- calcium lime and dolomitic lime - were calculated by using Tier 1 method and their respective emission factors of 0.75 and 0.77 (ibid). The baseline projection consistent with Vision 2050 was based on the change of GDP in industry sector which is projected to increase by 13% average growth rate per year (GoR, 2017a). This growth was applied throughout the IPPU sector; the overall share from minerals industry to total IPPU emissions from the mineral sector was assumed constant during the projection period at 84.6% (GoR, 2018a). The expansion of the CCL facility in 2015 and the rising demand of cement from the construction sector as shown in Table 3.10 is expected to maintain BAU emissions from minerals industry at a significantly higher rate level other IPPU sub-sectors. Rwanda NDC Implementation: Final Report Page 30 Table 3.10 Projected clinker and cement production (tonnes) Item 2015 2020 2025 2030 Clinker 88,090 347,876 531,627 716,200 Cement 125,842 496,966 759,467 1,023,143 Source: MINECOFIN, 2018 and authors 3.4.2 Product Uses as Substitutes for Ozone Depleting Substances The BAU approach was based on the quantity of hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) used for refrigeration and air-conditioning; mainly R134a, R404a, R 410a, R407c, and R507a and which are also used for mobile air conditioning (GoR, 2018a). The projection, for substitutes of ozone depleting substances (ODS) sub-sector emissions through 2030, was consistent with the expected average increase of industrial sector GDP by 13% (GoR, 2017a). The contributing share to the total IPPU emissions of 8.8% from the substitutes of ODS was assumed constant through 2030 (GoR, 2018a). 3.4.3 Other sources Two other sub-categories were considered, namely emissions from (i) metal industry and (ii) Non- Energy Products from Fuels and Solvent Use. The IPCC 2006 methodology was used during the BAU development and was based on local production data for iron, steel and ferroalloys production (extremely low volumes) as well as the emissions from lubricants and paraffin wax use (GoR, 2018a). Similar to the other IPPU sub-categories, emissions for the base case in these two categories were projected to increase with the GDP average growth from Vision 2050. The current contribution to total IPPU emissions, estimated at 1.86% from the metal industry and 4.74 % from Non-Energy Products from Fuels and Solvent Use was assumed constant throughout 2030 (GoR, 2018a). 3.5 Agriculture Figure 3.12 shows the BAU emissions projection for agriculture sector emissions through 2030 for the base case (consistent with the targeted/high output)8. Steadier growth is forecast overall, compared to other sectors, rising from around 2.9 million tCO2e in the base year to 5.1 million tCO2e in 2030. As shown in the graph, emissions from all sub-sectors are forecast to increase in the absence of specific mitigation measures, with the largest growth expected from N2O emissions arising from managed land reflecting increased crop production and commodity exports such as tea and horticultural products. Despite assumptions around increased livestock output and productivity, emissions from these sources are expected to rise at comparatively lower rates through 2030. 8 This reflects a high sector scenario for agricultural output reflecting e.g. growth in fertilizer use, improved soil fertility, increased per Ha yields. Rwanda NDC Implementation: Final Report Page 31 Figure 3.12 BAU GHG emissions projection, Agriculture (base case) Source: Authors Table 3.11 BAU GHG emissions projection, Agriculture (base case) GHG emissions (MtCO2e) 2015 2020 2025 2030 Livestock 1.96 2.35 2.70 3.10 Enteric fermentation 1.28 1.50 1.71 1.96 Manure management 0.67 0.85 0.99 1.14 Aggregate Sources and Non-CO2 Emissions Sources 0.98 1.31 1.63 2.04 Urea application <0.01 <0.01 <0.01 <0.01 Direct N2O Emissions from managed soils 0.54 0.76 0.95 1.20 Indirect N2O Emissions from managed soils 0.19 0.25 0.31 0.38 Indirect N2O Emissions from manure management 0.15 0.16 0.18 0.21 Rice cultivation 0.10 0.14 0.18 0.23 Total 2.94 3.66 4.33 5.14 Source: Authors Rwanda NDC Implementation: Final Report Page 32 Table 3.12 below summarises the approach to developing BAU projections for the agriculture sector across each of the relevant emissions source categories. A more detailed description is provided below for each key category, along with methodological choices, assumptions and data sources. The projections were based on the trends reported in TNC (GoR, 2018a) with use of additional regression analysis from the existing historic data to assess correlations between growth rates and GDP and population data using the MINITAB 18 statistics software (MINITAB 18).9 Production forecasts, also drawing upon official agricultural outlooks for Rwanda, were then used to model GHG emissions forecasts using AFOLU IPCC Tier 1 emissions factors (IPCC, 2006). Errors observed in the GHG inventory data for both the historic series and BAU base year were corrected as part of the revised BAU analysis.10 Table 3.12 Summary of approach to BAU projections, AFOLU IPCC category Description Emissions from livestock calculated based on 3.A.1.Enteric IPCC Tier 1 emissions factors applied to projected livestock population growth per Fermentation species (Shapiro et al., 2017) and using regression analysis (MINITAB 18). 3. A. Livestock Emissions from manure management were based on IPCC Tier 1 emission factors applied 3.A.2.Manure to projected increases in livestock population per species, assuming manure management Management systems remain unchanged through 2030, (Shapiro et al., 2017). Regression analysis was used. Not included within current analysis (work 3. AFOLU 3. B. Land 3.B.1.Forest Land currently ongoing in parallel to estimate forest land emissions and removals). Projections to 2030 calculated based on IPCC Tier 1 emission factors applied to projected 3.C.3.Urea application urea utilisation (corrected from GHG inventory and TNC analysis). 3. C. Aggregate 3.C.4.Direct N2O Direct N2O emissions from managed soils Sources and linked to crop biomass and projections for Non-CO2 Emissions from 2016-2030 made using regression analysis Emissions managed soils (MINITAB 18). Sources on Land 3.C.5.Indirect N2O Indirect N2O emission from managed soils correlated to growth in direct N2O emissions Emissions from from managed soils using regression analysis managed soils (MINITAB 18). 9 Historic data on GHG emissions from TNC (2006-2015) (GoR, 2018a) were used to derive regression equations with reported GDP and population in the same period (2006-2015) using MINITAB 18. 10 Most notably relating to urea application (kilogrammes urea were previously counted in the GHG Inventory as tonnes) Rwanda NDC Implementation: Final Report Page 33 Projections inked to manure management of 3.C.6.Indirect N2O kraal (livestock enclosures), calculated based Emissions from manure on regression analysis showing a high management correlation to direct N2O emissions from managed soils (MINITAB 18). Emissions calculated based on IPCC Tier 1 emissions factors applied to rice area 3.C.7.Rice cultivation projections on basis of government’s official planned cultivation expansion (MINAGRI, 2013). Source: Authors 3.5.1 Livestock The national livestock population is projected to rise through the forecast period. Although the official national policy does not set clear limits on the maximum size of the livestock population per species, subject to available resources, it is assumed populations per species will continue to increase - reflecting government policy aims. GHG emissions from livestock in Rwanda are dominated by cattle. During the period 2006-2015, cattle population increased by 2.7%, goats by 4.8%, swine by 6% and sheep by 1%. For cattle, to meet official productivity targets, 46% of the current herd is planned to be replaced by cross-breeds, and red meat production is planned to grow from 58,579 tonnes in 2016/17 to 79,586 tonnes in 2021/22, representing an increase by 36% (Shapiro et al., 2017). It is assumed this will be achieved partially through the introduction of meat breeds along with natural population increase, as per historical growth. Based on the current policy focus and historical trends, a 3-4% annual growth in cattle herds was assumed for BAU livestock projections. This results in total cattle numbers rising from around 1.4 million in 2016 to 2.1 million by 2030. Other livestock were assumed to remain at historical growth rates. 3.5.2 Crops National population growth projections require a doubling of crop productivity by 2050 to sustain basic food requirements (GoR, 2017a). In addition, certain export products such as horticulture are seeing very strong demand.11 Because expansion of agricultural land has reached its limit in Rwanda, expanding output requires an increase in agricultural inputs in the form of organic and mineral fertilizers, use of improved crop varieties and better agroecosystem management practices, allowing sustainable production and improved nutrient balance in soil. Use of regression analysis from available historic data indicates that emissions from managed soils are not closely correlated with population and GDP. An alternative parameter of crop biomass was instead chosen within the BAU analysis. Crop biomass output was found to have highly significant correlation with direct N2O emissions from managed soils, while indirect N2O emissions from soil and manure were found to be strongly related to direct N2O emissions from managed soils. Thus, regression analysis was performed (MINITAB 18), and regression equations were used to project N2O emissions for the 11The new strategic pan (2019-2024) for the National Agricultural Export Development Board (NAEB) aims at increasing agricultural exports to over USD 1 billion per annum by 2024, from around USD 516 million in 2018. Horticultural product exports are expected to see the largest growth rate, moving to second place after tea. These will have a major impact on increased demand of irrigation (including diesel engine pumping and fertilizer usage). Rwanda NDC Implementation: Final Report Page 34 period 2016-2030. Table 3.13 below shows the projected crop biomass increase through 2030 under the BAU projection. Table 3.13 Projected increase in crop biomass, BAU 2016-2030 Tonnes 2016 2020 2025 2030 Total crop biomass 7,593,356 9,300,295 11,983,272 15,440,243 Source: Authors, derived from TNC data (GoR, 2018a) 3.6 Waste Figure 3.13 shows the BAU emissions projection for emissions from waste through 2030 for the base case (consistent with Vision 2050). A significant increase is forecast, rising from around 0.64 million tCO2e in the base year to 1.59 million tCO2e in 2030. Emissions from all sub-sectors are forecast to increase in the absence of specific mitigation measures, with the largest growth expected from emissions arising from solid waste production, including solid waste disposal sites (reflecting increasing urbanisation rates through 2030) and biological treatment of solid waste (composting). These closely reflect projected population increases and rising per capita waste generation levels, as described further below. The projections assume that current waste practices continue in the absence of targeted actions e.g. investments in landfill gas utilisation. Note that emissions from waste incineration are extremely low, and data and are not visible in the graph, reflecting the prohibition of open burning of waste, the lack of data for open burning of waste and the practice of incineration for mainly clinical waste. Rwanda NDC Implementation: Final Report Page 35 Figure 3.13 BAU GHG emissions projection, Waste (base case) Source: Authors Table 3.14 BAU GHG emissions projection, Waste (base case) GHG emissions (MtCO2e) 2015 2020 2025 2030 Solid waste disposal 0.19 0.28 0.43 0.59 Biological treatment of solid waste 0.16 0.24 0.41 0.59 Incineration and open burning 0.001 0.001 0.002 0.002 Wastewater Treatment and Discharge 0.29 0.33 0.37 0.40 Total 0.64 0.85 1.22 1.59 Source: Authors Table 3.15 below summarises the approach to developing BAU projections for the waste sector across each of the relevant emissions source categories. A more detailed description is provided below for each key category, along with methodological choices, assumptions and data sources. Rwanda NDC Implementation: Final Report Page 36 Table 3.15 Summary of approach to BAU projections, Waste IPCC category Description Base year emissions calculated according to IPCC 2006, Tier 1 methodology with African waste generation assumptions of 4. A. Solid Waste Disposal 0.29 tonnes/capita/year. Emissions projections through 2030 were calculated based on official GDP and population forecasts (GoR, 2017a; GoR, 2018b). Base year emissions calculated according to IPCC 2006, Tier 1 methodology with African waste generation assumptions of 4. B. Biological Treatment of 0.29 tonnes/capita/year. Emissions projections through 2030 Solid Waste were calculated based on official GDP and population forecasts (GoR, 2017a; GoR, 2018b). 4. Waste Base year emissions calculated according to IPCC 2006, Tier 1 methodology and incinerated waste generation assumptions. 4. C. Incineration and Open Emissions projections through 2030 were calculated based on Burning of Waste official GDP and population forecasts (GoR, 2017a; GoR, 2018b). Base year emissions calculated according to IPCC 2006, Tier 1 4. D. Wastewater Treatment methodology. Emissions projection through 2030 were and Discharge calculated based on official GDP and population forecasts (GoR, 2017a; GoR, 2018b). Source: Authors 3.6.1 Solid waste The solid waste category comprises of the following three sub-categories: (i) solid waste disposal site (SWDS), (ii) biological treatment of solid waste, and (iii) waste incineration. Based on national circumstances in waste management, the urban population uses predominantly SWDS while the rural population practises composting; waste incineration is mainly carried out only in hospitals. IPCC Tier 1 methodologies (IPCC 2006) were applied to calculate base year emissions (GoR, 2018a). The NAMA study assumption of 3% growth in urban population from the base year through 2030 was applied (GoR, 2015b), resulting in an average 35%/65% urban/rural split of population by 2030. Emissions projection through 2030 were calculated by using a multiple regression model using official GDP and population forecasts (GoR, 2017a; GoR, 2018b). The regression results showed strong correlation between the base year emissions, the GDP and the population, with R2= 0.99 for SWDS, R2= 0.92 for the biological treatment of solid waste and R2= 0.99 for waste incineration. Table 3.16 below shows the projected population in urban and rural areas from the base year until 2030. Table 3.16 Urban and rural population forecasts to 2030 Population (millions) 2015 2020 2025 2030 Urban 2.63 3.05 3.54 4.10 Rural 8.59 9.61 10.62 11.61 Total 11.23 12.66 14.16 15.71 Source: Adapted from GoR, 2018b and GoR, 2015b Rwanda NDC Implementation: Final Report Page 37 3.6.2 Wastewater treatment and discharge The wastewater sub-sector is divided into: (i) Domestic wastewater treatment and discharge and (ii) Industrial wastewater treatment and discharge. IPCC Tier 1 methodologies (IPCC, 2006) were used to calculate base year emissions (GoR, 2018a). The estimated emissions through 2030 were then calculated by using a multiple regression model with official GDP and population forecasts (GoR, 2017a; GoR, 2018b). The regression results reveal a strong correlation with R2= 0.99 between the base year emissions from wastewater treatment and discharge, forecast GDP and population. 3.7 Summary and sensitivity analysis 3.7.1 Aggregated BAU results The bottom-up BAU projections described are aggregated below to produce an economy-wide forecast of BAU emissions through 2030 (Figure 3.14). This represents the BAU baseline projection, consistent with the Vision 2050 outlook, against which the contribution from NDC mitigation actions across each of the key sectors can be quantified. At an aggregate level, total emissions are forecast to more than double over the 2015-2030 period, rising from 5.3 million tCO2e in the base year to 12.1 million tCO2e in 2030. The graph shows that this represents an increased rate of growth compared to that seen during the period 2006-2015, closely reflecting the assumptions around economic and population growth and official planning, instead of projections based on past trends.12 The current projection compares with the TNC projection of around 10.2 million tCO2e in 2030, representing a doubling from the base year.13 As described above, the most rapid growth is forecast within industrial processes and energy use: the former expands its share of total emissions from 2% to around 4%, and the latter from 31% to 40% by 2030. The share of emissions from waste generation remains at around 12-13%, whilst agricultural sources decline from 55% to 43%. Although these do not represent dramatic shifts in emissions sources, they clearly indicate the growing contribution from fossil fuels to national emissions, arising from increasing demand for power generation, road transport services and other modern energy uses. At the same time, despite potential for increased productivity, agricultural output in expected to be limited due to land availability, thereby limiting emissions growth from this sector. 12 This pattern is consistent with developing countries emissions trajectories; see for example historic Non-Annex B emissions in https://www.carbonbrief.org/what-global-co2-emissions-2016-mean-climate-change 13 Note that this value is ‘corrected’ to account for data errors in the TNC reported data (GoR, 2018a). Rwanda NDC Implementation: Final Report Page 38 Figure 3.14 BAU GHG emissions projection, total emissions (base case) Source: Authors Per capita and emissions intensity BAU projections are shown below in Figure 3.15. These represent base case forecasts results assuming the GoR official population forecast (medium case) and Vision 2050 economic growth rates, respectively. Per capita emissions can be seen to increase steadily through 2030 according to the BAU projection, broadly in line with previous trends. This pattern is typical for developing countries experiencing strong economic growth and development with rising living standards, reflecting such factors as inter alia: • Increased population growth and urban population, driving e.g. solid waste disposal emissions and energy use in buildings • Increased demand for transport and vehicles • Increasing electricity demand, met by mainly fossil-based generation • Economic, industrial and agricultural growth in line with government strategy and policy aims Emissions per unit GDP are by contrast forecast to decrease through the same period. Again, this continues broadly in line with historic trends albeit at a reduced rate. This decoupling effect can be attributed to a range of sector-specific factors. For example, agricultural output – which dominates national emissions - is expected to be physically limited beyond a certain level of productivity gain by land availability. Similarly, empirical evidence shows that even with rapid economic growth, road vehicle numbers do not increase at the same rate. The overall factor is that economic growth is forecast to increase at a higher rate than fossil-based energy use, agricultural output and emissions. Rwanda NDC Implementation: Final Report Page 39 Figure 3.15 BAU GHG emissions projection, per capita and per unit GDP (base case) Source: Authors Rwanda NDC Implementation: Final Report Page 40 3.7.2 Sensitivity analysis Approach Changes in production, energy use and GHG emissions through 2030 will be driven by a number of factors. The two most important drivers in the specific context of Rwanda’s NDC sectors are considered to be: • Economic growth: Economic growth within key sectors will drive demand for energy, industrial output and services such as road transport and housing. Lower rates of GDP growth over the coming years will therefore tend to restrain demand and output, and GHG emissions levels. • Population growth: Population increases within rural and urban areas will drive demand for road transport, housing, and other services, as well as levels of waste generation and resource use. Lower population growth will tend to restrain demand and GHG emissions levels. Because the ability to meet a certain NDC goal rests on the future projection of baseline emissions, it was considered important to test the relative significance of these drivers. A sensitivity analysis was therefore undertaken, generating a set of different BAU projections to 2030 reflecting the impact of these factors. Economic growth outlook As set out in the country’s vision for continued economic development14, Vision 2050, Rwanda aspires to reach Middle Income Country (MIC) and High-Income Country (HIC) status by 2035 and 2050, respectively. The Vision will be affected through a series of seven-year National Strategies for Transformation (NST1), underpinned by detailed sectoral strategies (World Bank, 2019a). The current NST1 covers the period 2017-2024 (GoR, 2017a). GDP growth assumptions consistent with the Vision have been used as the ‘base case’ assumption for the BAU emissions projections. However, given the importance of economic growth to the projections, an alternative and independent outlook for growth in Rwanda produced by the International Monetary Fund (IMF) World Energy Outlook has also been assessed.15 The two different projections are shown in Figure 3.16 below. It can be seen that the IMF outlook, whilst forecasting strong growth (around 6-7% per annum) is more conservative than the rate of growth envisaged by Vision 2050. As such it provides a useful alternative forecast to the GoR official outlook. 14GDP growth averaged 7.5% over the decade to 2018 while per capita GDP grew at 5% annually (World Bank, 2019a). 15The IMF WEO outlook is to 2024 only; growth in 2025-2030 has therefore been extrapolated based on the final year growth rate. Rwanda NDC Implementation: Final Report Page 41 Figure 3.16 GDP per capita projections to 2030 Source: Calculated based on Vision 2050 (GoR, 2017a) and IMF World Economic Outlook (IMF, 2019) Note: WEO projections extrapolated after 2024 based on final year growth rates. Table 3.17 GDP per capita projections to 2030 GDP per capita (USD) 2015 2020 2025 2030 Vision 2050 736 1,240 2,172 3,103 IMF WEO 736 879 1,229 1,732 Source: Calculated based on Vision 2050 (GoR, 2017a) and IMF World Economic Outlook (IMF, 2019) Note: WEO projections extrapolated after 2024 based on final year growth rates. Population growth outlook The National Institute of Statistics Rwanda (NISR) publishes population projections based on regulator household surveys and censuses. The most recent of these is the Fifth Integrated Household Living Survey, EICV5, (NISR, 2018). The EICV5 provides detailed projections of population according to low, medium and high scenarios. The medium population scenario has been used as the ’base case’ assumption in BAU emissions projections, with the low and high forecasts used as the alternative cases. The three different projections are shown in Figure 3.17 below. The medium scenario predicts a total population growth of around 39% over the period 2015-2030; this rises to 43% under the high scenario and falls to 32% under the low scenario. Rwanda NDC Implementation: Final Report Page 42 Figure 3.17 Rwanda population projections to 2030 Source: Fifth Integrated Household Living Survey; EICV5, (NISR, 2018) Table 3.18 Rwanda population projections to 2030 Population (millions) 2015 2020 2025 2030 High case 11.26 12.74 14.37 16.14 Medium case 11.26 12.66 14.16 15.71 Low case 11.26 12.42 13.63 14.90 Source: Fifth Integrated Household Living Survey; EICV5, (NISR, 2018) Results The combination of two alternative economic outlooks and three population growth scenarios gives rise to six alternative BAU emissions projections. These are shown below for each of the four key sectors (Figure 3.18). The results show the relative influence of GDP and population assumptions within the BAU modelling across the different activities. In all cases, assumptions around economic growth and production are seen to be a driver of emissions outcomes, most notably within the industrial processes and waste sectors which are closely linked in the modelling to economic growth factors. The effect is less marked within energy use, in part because the official power generation plans, whilst reflecting demand forecasting, are centrally planned and not directly linked to GDP growth assumptions through the period. Rwanda NDC Implementation: Final Report Page 43 Figure 3.18 BAU sensitivity results to 2030 by key sector Source: Authors Figure 3.19 shows the six alternative BAU projections for all emissions sources. The base case BAU results presented throughout this section are shown by the “V2050 med pop” series. The different projections are seen to cluster into two distinct groups according to two alternative GDP assumptions, within which the variations reflect the range of population forecasts. This clearly illustrates the importance of GDP growth assumptions to future BAU emissions, according to the methodological approach. According to the Vision 2050 assumption, emissions are forecast to rise to 12.1 million tCO2e in 2030; under the economic growth rates envisaged by the IMF WEO source, this falls to 10.3 million tCO2e, representing a reduction of around 15%.16 Although noticeable, the impact of population upon emissions is secondary: within the Vision 2050 projections, population variations produce a range in emissions in 2030 of up to 5%, and within the IMF WEO projection a variation of up to 3%. 16 Based on the medium population forecast. Rwanda NDC Implementation: Final Report Page 44 Figure 3.19 BAU sensitivity results to 2030, total emissions Source: Authors Table 3.19 BAU sensitivity results to 2030, total emissions GHG emissions (million tCO2e) 2015 2020 2025 2030 Vision2050; high population 5.34 7.47 9.78 12.37 Vision2050; medium population (base case) 5.34 7.42 9.61 12.06 Vision2050; low population 5.34 7.30 9.39 11.72 IMF WEO; high population 5.34 7.03 8.72 10.56 IMF WEO; medium population 5.34 6.96 8.59 10.34 IMF WEO; low population 5.34 6.97 8.55 10.24 Source: Authors Rwanda NDC Implementation: Final Report Page 45 4 ASSESSMENT OF NDC MITIGATION OPTIONS 4.1 Overview This section describes an assessment of GHG mitigation options for Rwanda, undertaken in order to determine which options are most suitable within the NDC. The analysis was undertaken according to a three-step process: • Step 1: Identifying mitigation options. A ‘long-list’ list of potentially suitable emission reduction projects and measures was developed through discussions and consultation with government officials, technical and sector experts, and other stakeholders. • Step 2: Assessing the potential. The identified options were then assessed in terms of their mitigation potential through 2030 compared to the BAU reference scenario and their economic costs and benefits - by undertaking cost-benefit analysis (CBA). • Step 3: Evaluating the options. The quantitative analysis undertaken in Step 2 was complimented by a broader, multi criteria-based, assessment in order to identify those options considered most suitable or feasible to be implemented under the NDC and to determine which can be implemented through domestic efforts (‘unconditional’ projects) and those requiring international support and finance (‘conditional’ projects), including through international market-based approaches e.g. under Article 6 of the Paris Agreement. 4.2 Identifying mitigation options The first step of the assessment involved identifying a range of mitigation options from within the each of the NDC sectors for further consideration and quantitative analysis. A bottom-up ‘long-list’ was developed through close consultation with various stakeholders and experts, based on the following key sources: • Rwanda’s NDC (GoR, 2015a) • Assessment of NAMAs in Rwanda (GoR, 2015b) • “Adjusted” list of NDC options, as contained in the Rwanda NDC Implementation Plan (GoR, 2017b) • Rwanda’s TNC to the UNFCCC (GoR, 2018a) Additional mitigation measures, including those identified from World Bank initiatives/plans and more recent government proposals, were also included. A workshop was held in June 2019 in order to identify and discuss the ‘long-list’ according to sector-based discussion groups.17 Guided discussions focused on three elements: 1. Review of NDC options: What is the current status of these projects? What is the planned timing? What are the implementation arrangements and needs? 2. Discussion of additional options: What other options could be applicable in Rwanda? What are the key challenges? What are the policy gaps and support needs? 17 Rwanda NDC Implementation Workshop on BAU and mitigation options, held on 18 June 2019, Serena Hotel Kigali Rwanda NDC Implementation: Final Report Page 46 3. Identifying data sources and gaps: What are the existing information sources? Where are the key data gaps required for detailed analysis? Discussion of contact points and specific arrangements for follow-up data collection. A modified ‘long list’ emerging from the workshop discussions was further refined, based on subsequent meetings held between the consulting team and government officials and sector experts though July 2019 - January 2020. The projects identified in the NDC were re-assessed, as well as additional projects and programmes. In some cases, the details, and context, regarding many of the projects were found to have changed since the time of INDC submission. The ‘long list’ of options identified thereby reflects a set of real projects and programmes under consideration, or having been studied, from within government departments and agencies.18 As such, it represents a bottom- up process of national information gathering rather than an independent technical assessment of Rwanda’s full mitigation potential. The table below presents the ‘long-list’ of mitigation across each of the sectors. The table indicates which of the identified measures were considered suitable/feasible for quantitative modelling as part of the mitigation technical assessment. Reasons for exclusion included one or more of the following: 1. Uncertain mitigation effect: several of the measures identified, including within the NDC, are likely to have valuable cross-cutting and/or ‘enabling’ effects upon mitigation outcomes although there is no clear methodological basis for quantifying possible GHG reductions (e.g. sustainable charcoal use). 2. Lack of data and complexity: some of the measures lack the specific data and assumptions considered necessary to undertake mitigation assessment, even at a high-level, and/or require complex calculations unsupported by sufficient information and data (e.g. Eco-park developments; Lake Kivu power project, which is considered as a mitigation project under the sensitivity analysis - see Section 5). 3. Additionality and inclusion within BAU: several measures considered as possible mitigation measures are considered to fall within the BAU scenario (e.g. reduction of power grid losses). It should also be noted that these factors present inherent difficulties in demonstrating and quantifying mitigation effects from projects and programmes against the BAU baseline, which is a requirement of NDC reporting (e.g. transparent MRV). The table is a summary only: several of the measures shown comprise of sub-measures or different projects, each with their own technical and economic assumptions requiring separate assessment.19 A total of thirty-eight separate mitigation assessments were identified for mitigation assessment (described further below). 18 As such, the long-list of mitigation options can be considered to be a comprehensive list of mitigation options across Rwanda’s emitting sector but does not represent a technical assessment of the country’s full mitigation potential. Technically possible by highly unfeasible options (e.g. carbon capture storage) were not considered. 19 Similarly, some of the measures also comprise several different actions or projects grouped together as a ‘package' for convenience. Rwanda NDC Implementation: Final Report Page 47 Table 4.1 Long list of mitigation measures for Rwanda Sector Source Mitigation Mitigation option Brief description Mitigation effect Sector Source A-NDC NDC Other modelling Development of 56.75 MW large hydro capacity (capacity > 5 Displacement of fossil-based Grid connected large hydropower MW), 24.5 MW small and mini hydro projects (capacity <5MW) generation (peat, diesel) and CO2 a a a and 75 MW regional projects by 2030. emissions 68 MWp of solar mini-grids to be installed in off-grid rural areas Displacement of diesel and kerosene Solar mini-grids by 2030 for domestic uses a a a Electricity Displacement of fossil-based generation and Installaiton of solar lighting installations and panels for street distribution Solar street lighting lighting and public spaces generation (peat, diesel) and CO2 a a a emissions Displacement of fossil-based Lake Kivu methane-to-power Additional 50 MW of CCGT capacity (Rwanda allocation) to project reach total of 80 MW by 2028 generation (peat, diesel) and CO2 a emissions ENERGY Reduction in fossil-based generation Reduction of grid losses Reduction of grid losses from 21% to 15% by 2030 and CO2 emissions a a Improved public transport Wide range of measures including bus rapid transport (BRT) Reduced demand for personal vehicle infrastructure and services in project, bus lanes, non-motorised transport lanes, and other use; reduced fuel use and CO2 a a a Kigali modal shift projects. emissions. Range of policies introduced to increase vehicle emissions Improvement in fuel efficiency of Vehicle emissions standards and fleet renewal performance of fleet, including tax incentives and scrappage of vehicle fleet, reducing fuel demand a a a older vehicles and CO2 emissions Transport Phased adoption of electric buses, passenger vehicles (cars), Displacement of diesel and gasoline Electric vehicles motorocycles from 2020 fuel use by grid electricity a a a Displacement of diesel and gasoline Electric rail between Isaka Implementation of the recently signed agreement to construct and Kigali an electric rail between Isaka and Kigali. fuel use by HGVs and buses by grid a electricity Note: A-NDC = Adjusted NDC (contained within the Rwanda Detailed NDC Implementation Plan; GoR, 2017b); although no IPPC accounting methodology exists and project data are not available, Lake Kivu is modelled at a high-level as a mitigation option as part of the sensitivity analysis; see Section 5. Rwanda NDC Implementation: Final Report Page 48 Sector Source Mitigation Mitigation option Brief description Mitigation effect Sector Source A-NDC NDC Other modelling Demand side management: reduced Dissemination of CFL and LED lamps to replace inefficient ones Efficient lighting in buildings in residential, commercial and institutional buildings fossil-based generation and CO2 a a a emissions Reduced firewood and fossil energy Dissemination of efficient cook stoves to 80% of rural Efficient cook stoves population and 50% of urban population by 2030 consumption for cooking (and CO2 a a a emissions) Displacement of diesel and kerosene Off-grid solar and rooftop solar PV Penetration of off-grid solar and rooftop solar PV panels for domestic and commercial energy a a a use ENERGY Buildings Installation of solar thermal water heaters within urban Displacement of grid power and diesel (commercial Solar water heaters residential buildings consumption a a and residential) Renewable biomass: Increasing average charcoal yields up to 50% by 2030. sustainable charcoal value Development of a sustainable charcoal value chain that can a a chain reduce demand of wood in charcoal production. Reduced fossil fuel and non- renewable biomass consumption, Clean cooking: LPG for Clean cooking: Diffusion of LPG for cooking up to 25% in urban cooking areas leading to reduced CH4 , N2O and CO2 a a emissions Renewable biomass: Biogas Diffusion of biogas digesters, targeted at 3,500 domestic units digesters and 15 institutional units per year (see below) a a a Note: A-NDC = Adjusted NDC (contained within the Rwanda Detailed NDC Implementation Plan; GoR, 2017b) Rwanda NDC Implementation: Final Report Page 49 Sector Source Mitigation Mitigation option Brief description Mitigation effect modelling Sector Source A-NDC NDC Other A range of energy efficiency measures focused on reducing Energy efficiency in agro- Reduction in fossil-based generation processing firewood and electricity consumption in the coffee and tea and CO2 emissions a a a sector Development of industrial parks at Kigali SEZ (276 Ha) and Increased efficiencies in energy and Development of eco- industrial parks Bugesera (330 Ha) with companies deploying best practise and resource use reducing energy a a green technologies emissions Energy use in Phasing out of diesel gensets for on-site electricity consumption, Displacement of fossil-based on-site manufacturing Climate compatible mining to be replaced with grid and/or on-site renewable power generation (diesel gensets) and CO2 a a a industry production emissions Reduction of fuel consumption in ENERGY Implementation of efficient Phasing out the clamp kilns, and apply energy efficiency brick kilns measures in brick industries brick manufacturing and CO2, CH4 and a a N2 O Energy reduction in cement Waste heat recovery (WHR) and use of rice husks as fuel within Reduced energy consumption (peat production clinker production and fuel oil) and CO2 emissions a a Energy use: Solar pumping Use of solar water pumping systems for irrigation to replacing Displacement of fossil fuel use and for irrigation diesel pumps associated CO2 emissions a a Energy use in agriculture Displacement of fossil fuel use and Energy use: On-farm On-farm anaerobic digestion of manure for bioenergy (links to anaerobic digestion biogas digesters above) associated CO2 emissions, and also a a CH4 from manure Note: A-NDC = Adjusted NDC (contained within the Rwanda Detailed NDC Implementation Plan; GoR, 2017b) Rwanda NDC Implementation: Final Report Page 50 Sector Source Mitigation Mitigation option Brief description Mitigation effect Sector Source A-NDC NDC Other modelling Non-metallic Increased share of pozzalanas within cement beyond current Increased use of pozzalanas Reduction in CO2 emissions from mineral in cement production cement-to-clinker ratio of 0.7. Introduction of a 2% substitution clinker production a a industries of clinker with pozzalanas from 2025 to 2029 IPPU The calculated level of their consumption expressed in CO2 eq. Process Gradual substitution of F- was set to gradually decrease and not to exceed the following Gradual reduction of ODS such as HFC- emissions: F- gases by less polluting percentages: (a) 2020 to 2024: 95%; (b) 2025 to 2028: 65%; (c) 134a, HFC-125, HFC-143a and HFC-32 a a gas substitutes 2029 to 2033: 30% Reduced CH4 emissions from landfill Extraction and utilization of landfill gas (LFG) for power sites and avoided CO2 from Landfill gas utilisation generation in connection to semi- or fully- controlled landfills displacement of fossil-based a a a for urban areas electricity use. Waste-to-energy (WtE) Development of WtE plants in Kigali and other urban areas Avoided CO2 from displacement of plants through energy recovery options other than LFG. fossil-based electricity use. a a Solid waste Improved waste management reduces Integrated solid waste Improved efficiency of waste management with reduced CH4 emissions. Materials and energy management (ISWM) emissions to air, water and soil. recovery from waste reduces CH4 and a WASTE CO2 emissions. Development of commercial scale aerobic composting systems Reduction in CH4 emissions, since for agricultural and forestry residue, manure, food processing, Aerobic composting kitchen and garden waste, and biosolids (organic solids from methane-producing microbes are not a a active in the presence of oxygen. treated sewage). Rural areas only. Development of sludge management projects within six Reduction in CH4 emissions and N2O Sludge management secondary cities, as described in the Water and Sanitation emisisons. a Sector Strategic Plan 2018-2024. Waste water Energy production from wastewater using waste-to-energy Waste-water treatment and re-use technologies, reducing methane emissions from wastewater and Reduction of CH4, and CO2 emissions. a a a expansion of wastewater treatment plants. Note: A-NDC = Adjusted NDC (contained within the Rwanda Detailed NDC Implementation Plan; GoR, 2017b) Rwanda NDC Implementation: Final Report Page 51 Sector Source Mitigation Mitigation option Brief description Mitigation effect Sector Source A-NDC NDC Other modelling Increased use of organic waste in soil fertilizers, supported by target to apply composting within all agricultural households by Reduced N2O emissions from urea Improved efficiency of applied fertilizers 2030; more judicious fertilizer use - introduction of site- and fertilizer use. Reduced CH4 from a a a a crop- specific mineral fertilizer recommendation for all major (avoided) waste sent to disposal. crops. Promotion of fertigation to enhance fertiliser uptake.. Comprises three measures: (1) Installation of 165,000 Ha land Soil and water conservation protection terracing structures in sloped arable areas to present measures (terracing; crop soil erosion; (2) Continous rop rotation of 600,000 Ha; (3) Prevention of soil erosion, leasing to a a a rotation; multicropping) Multicropping of coffee and bananas of 40,000 Ha. reduce CH4 and N2O emissions and carbon sequestration in soils. Reduction in vertical movement of soil, leaving more crop a a AFOLU Conservaton tillage Agriculture residue on the soil surface, thereby reducing soil erosion. Improved livestock Promotion of better livestock feed (i.e. legume fodder species) Reduction in GHG emissions (CH4) husbandary and training in better livestock management. from enteric fermentation a a Replacement of 10% domestic cows with improved cow species; Improved livestock species expansion of fish farming, poultry and other small livestock to Reduction in GHG emissions (CH4) and population increase protein food supply without increasing cows; and from enteric fermentation a a change in livestock mix Improved manure Adoption of more efficient manure management systems, Reduction in GHG emissions from management includin promotion of collective farms and training manure management. a a Note: A-NDC = Adjusted NDC (contained within the Rwanda Detailed NDC Implementation Plan; GoR, 2017b) Rwanda NDC Implementation: Final Report Page 52 4.3 Assessing the potential 4.3.1 Mitigation potential Figure 4.1 summarises the estimated emissions reduction potential in 2030 for all mitigation measures assessed from the ‘long list’ presented in Table 4.1. The pie charts indicate the relative contribution made from projects within the key sectors of energy (electricity generation, industry, transport, commercial and residential, and agriculture), waste, IPPU and agriculture against the base case BAU projected emissions described in Section 2. The total mitigation potential is estimated at around 4.6 million tCO2e in 2030 compared to base case BAU emissions in the same year of 12.1 million tCO2e. According to the analysis, mitigation measures identified within the agriculture sector accounts for 49% of the total potential, followed by energy (34% of total), waste (14%), and IPPU (3%). Within agriculture, soil conservation measures – which include terracing, conservation tillage, multi- cropping and crop rotation practices – account for around half of the sector’s mitigation potential. The bulk of the remaining mitigation potential includes measures to reduce enteric fermentation emissions from livestock, including the introduction of new species to replace local herds and improved husbandry, and the use of windrow composting. Within energy use, increased use of renewables to meet increasing energy demand dominates the mitigation potential. Significant emissions reduction potential exists across each of the main sub- sectors. Hydropower, covering large- and small-scale new generation, represents the largest share of the identified GHG reduction potential, followed by the use of solar energy for water heating, pumping for agricultural irrigation and off-grid electricity which together account for around a quarter of all mitigation. Emissions reductions arising from use of electric vehicles and vehicle fuel economy standards are also considered to be potentially significant, although assumptions around the rate of implementation over the coming decade (e.g. new vehicles entering the fleet and development of charging infrastructure) and the rate of electricity grid decarbonisation achieved are key to the net level of abatement achieved. Within waste, the most significant potential is identified within energy utilisation measures such as landfill gas recovery and direct waste-to-energy (WtE) plants. Mitigation potential from IPPU sources is by comparison relatively limited, with the majority of emissions reductions arising from increased use of clinker substitute for cement production (volcanic pozzolanas), followed by reduction of fluorinated gases (F-gases), in line with the Kigali amendment of the Montreal Protocol on Substances that Deplete the Ozone Layer (UN, 1987). Rwanda NDC Implementation: Final Report Page 53 Figure 4.1 Estimated GHG mitigation potential in 2030 from all measures Source: Authors The total mitigation potential against the base case BAU projection through 2030 is shown in Figure 4.2 below. The graphs show the relative contribution of each sector, clearly illustrating the dominance of those measures aimed at reducing emissions from agriculture and energy use. Rwanda NDC Implementation: Final Report Page 54 Figure 4.2 Mitigation potential from all projects versus BAU projection, 2016-2030 Source: Authors 4.3.2 Mitigation costs and benefits Figure 4.3 shows a marginal abatement cost curve (MACC) in which each of the identified NDC mitigation options is sorted in ascending order of abatement cost. The costs shown are taken from the NPV values generated by the CBA and therefore represent socio-economic costs of abatement, reflecting both costs and benefits to the wider economy. The MACC presents a useful way of assessing the relative costs and contribution of the mitigation potential for each of the key options assessed, although their use has limitations with results being highly sensitive to input assumptions (see Annex A)20. Due to the large number of measures included, a number of smaller options are not indicated. These are however shown within the sector-specific MACCs presented further below. 20 Mitigation options can interact and overlap according to their specific mix within a scenario seeking to simulate the energy system. This is particularly the case in which supply- and demand-side mitigation measures co-exist: the emissions reductions estimated for a demand-side measure reducing demand for grid electricity must reflect the carbon-intensity of the grid associated with the inclusion of supply-side mitigation projects and not the BAU baseline grid. Otherwise, total emissions reductions shown on the curve would be overestimated. Because the mitigation options were not modelled top- down according to e.g. cost optimization or computable general equilibrium (CGE) type modelling, abatement from supply- side options were calculated before the calculation of mitigation from the (relatively few) relevant demand-side options. For these reasons, CBA and abatement costs were recalculated for each NDC mitigation scenario in order to ensure a mutually consistent suite of options developed as a scenario avoiding overestimation of mitigation potential. Rwanda NDC Implementation: Final Report Page 55 Figure 4.3 Marginal abatement cost curve for all identified mitigation measures in 2030 Source: Authors The figure highlights the large mitigation potential within the long list of identified options principally through measures within agriculture and energy use. Importantly, many of the projects are seen to be cost-effective with net benefits outweighing net costs, shown here as ‘negative’ abatement costs - the majority of the abatement potential shown on the curve, around 3.3 million tCO2e or 72% of the total, is achieved at negative socio-economic cost. This is most noticeable for energy projects. This is consistent with other abatement cost curves globally, reflecting the fact that these include a range of measures involving the displacement of imported fossil fuels through increasing the use of indigenous renewable energy and cost-efficient demand-side interventions (e.g. reducing diesel fuel use in inefficient and polluting generation sets, and diesel and gasoline in road transport). The majority of the waste sector options identified are also considered to be cost- effective on an economic basis, including landfill gas utilisation and WtE projects which utilise waste materials for economic energy production whilst also delivering wider employment and revenue benefits. Within agriculture, cost-effective options such as crop rotation and improved livestock husbandry can also deliver GHG reductions with important co-benefits e.g. through increased yields and economic output. Rwanda NDC Implementation: Final Report Page 56 The higher cost options shown on the curve are seen to fall mainly within the agriculture sector. These include the use of terracing which is assessed to have extremely high investment costs relative to the estimated mitigation potential achieved and the introduction of improved livestock species involving significant compensation for existing herds and capital costs of replacement crossbreed cow species. EV passenger cars are also estimated to be high cost, reflecting the incremental vehicle costs relative to conventional models and significant charging infrastructure costs. A more detailed description of the economic assessment is provided in Annex A for each sector, including a description of each mitigation measure and the mitigation and CBA analysis assumptions. Investment cost estimates are presented in Section 10 (Funding Requirements). 4.4 Evaluating the options The identified mitigation options were assessed according to a multi-criteria evaluation framework. This was undertaken partly to assess the suitability of the identified measures within the NDC, and also to help inform the decision of which could be considered ‘unconditional’ domestically supported measures, and which could be instead considered as ‘conditional’ on international support. The above sections describe an economic assessment made for the full list of options, presenting the results of a cost-benefit analysis and estimated abatement costs. Although economic efficiency is a key criterion, mitigation prioritised are typically not optimised solely for cost-effectiveness. This is because the choice of options, and the national policy framework designed to deliver mitigation and adaptation aims, must also respond to other key issues such as e.g. local pollution reduction, energy security, energy access, poverty, and seeking reduced electricity tariffs. A broader evaluation framework is needed. Suitable mitigation options seek to maximise the following key criteria: • Environmental effectiveness: mitigation actions should achieve real emissions reductions, at the national and global level, whilst minimising indirect environmental impacts and ensuring resilience to climate change impacts. • Socio-economic impacts and co-benefits: mitigation actions should prioritize the most cost- effective options including those with developmental co-benefits and be acceptable to all entities involved taking account of impacts and risks to affected groups including households, businesses, and communities. • Feasibility of implementation: mitigation actions should be feasible to implement in the specific context of the national infrastructure and the legal framework, be in alignment with national policy aims and objectives, and be suitable to international support and climate finance. A set of criteria was chosen according to these three broad categories, drawing from international literature and guidance on good practice climate policy development (IPCC, 2007). Table 4.2 describes the evaluation criteria used to assess and prioritise each of the identified mitigation options. Rwanda NDC Implementation: Final Report Page 57 Table 4.2 Evaluation criteria for mitigation options Does the mitigation option offer the ability to deliver significant Contribution towards and/or scaled-up and replicable GHG benefits towards meeting NDC target the NDC target through 2030? Are there other (non-GHG) environmental impacts arising from Environmental Indirect implementation? May include negative impacts (e.g. biodiversity effectiveness environmental effects and landscape loss) and positive impacts (environmental co- benefits). Adaptation and Are there interactions and alignment with adaptation and climate considerations climate change vulnerability risks and policy aims? Does the mitigation option deliver GHG reductions cost- Cost-effectiveness effectively i.e. at low or negative economic net cost? Are there possible changes to welfare within effected groups, including changes to prices and distributional outcomes? May Welfare and equity include both negative impacts (e.g. increased costs for low Socio-economic income households) and positive impacts. impacts and co- benefits What are the potential impacts upon business and the wider Competitiveness and economy? May include negative impacts (e.g. increased productivity operating costs and administrative burden) and positive impacts (e.g. increased efficiency, reduced operating costs). Green growth and Ability to deliver additional employment and green growth employment opportunities within the country. Is the mitigation option in alignment with national policy aims Alignment with other and objectives (e.g. national strategies for economic policy aims development, employment, poverty alleviation and energy provision)? Legal and regulatory Are there potential issues with implementation arising from the feasibility legal and/or regulatory framework? Feasibility of implementation Is the mitigation option suited to attracting funding, including Suitability to funding both commercial investment and public sector lending and/or and climate finance international and bilateral climate finance (e.g. suitability of technology or project type)? Are there other key challenges, risks and barriers likely to impact Other implementation the chance of project implementation within a mix of options challenges designed to meet the NDC? Source: Adapted from various sources including IPCC, 2007 Through discussion exercises within the consulting team, each option was assessed against the criteria and classified according to one of the following: • High performance: clearly performs very well against the criteria, accounting for key uncertainties and the specific real-world context under which the option would be implemented. • Medium performance: performs well against the criteria, although to a lesser extent than above. Rwanda NDC Implementation: Final Report Page 58 • Mixed or uncertain performance: there are likely to be mixed outcomes against the criteria or significant uncertainties around the likely performance. • Low performance: performs poorly against the criteria, accounting for key uncertainties and the specific real-world context under which the option would be implemented. Based on these evaluations, each option was then assessed according to whether it was considered to be a high, medium or lower priority option. This process was undertaken through discussion and expert judgement based on the overall performance within each of the three broad categories, but also noting the benefit of including within the NDC a range of options implemented across multiple sectors and mitigation project types. A formalised scoring or ranking system was not used. The tables below summarise the results of the evaluation and prioritization process for each of the sectors (energy, IPPU, waste, and agriculture). The colours and symbols shown in the evaluation tables are explained as follows: On the balance of the criteria evaluation framework, and informed by some of the additional considerations noted above, the majority of the assessed options were considered to be ‘high priority’ or ‘medium priority’ options; no options are considered inappropriate as part of Rwanda’s NDC efforts. All measures were also considered to be potentially applicable for implementation before 2030, subject to finance support and overcoming implementation challenges. The outcome of the initial evaluation and prioritisation can be summarised as follows: • Energy: The large majority of the identified measures are considered to be suitable or highly suitable as NDC actions. All measures are well aligned with national policy aims and goals, including e.g. improving access to modern energy sources, increasing electrification, reducing resource use and fuel import dependence, and developing indigenous low carbon energy - as envisaged within guiding strategies such as the ESSP, Vision 2050, Sustainable Energy for All (2015-2030), National Electrification Plan (NEP) and others. As demonstrated above, most measures are considered cost-effective from a socio-economic perspective, having important co-benefits such as job creation, reduced fossil fuel dependency and socio- economic development. Despite having important benefits, several measures within road transport are considered to be high cost options (e.g. electric passenger cars and public transport bus schemes), although it should be noted that health benefits associated with reduced urban air pollution have not been quantified. Furthermore, the analysis of public transport measures is very simplified and excludes the potential role of e.g. road network improvements and urban decongestion investments which can have significant benefits in terms of fuel and emissions savings. Other measures face significant implementation Rwanda NDC Implementation: Final Report Page 59 challenges such e.g. local expertise and capacity to install off-grid systems and access to finance to support energy efficiency investments in industry. Such projects will require support through international funding sources and/or climate finance (discussed further below). • IPPU and waste: All of the measures are considered suitable or highly suitable as mitigation options, and well aligned with government policy priorities and goals relating to industrial, waste and economic development policy. Although making a relatively small contribution in terms of overall emissions reductions, both F-gas reduction and clinker reduction measures within IPPU represent cost-effective mitigation actions consistent with environmentally sustainable industrial practise as well as others e.g. Kigali Amendment to the Montreal Protocol and the national ‘Made in Rwanda’ policy goal. The identified waste sector measures are similarly considered to be cost-effective and well-aligned with key government policies such as the 2016 National Sanitation Policy and NST1 objectives. A range of technical and financing challenges, as well as the need for increasing local capacity and expertise, will likely require international support to deliver waste-to-energy and landfill gas utilisation projects, however. • Agriculture: As with the other sectors, most of the measures are considered to be suitable as mitigation options and well aligned with key sector policies, for example the national Crop Intensification Program (CIP) and Livestock Intensification Program (LIP). The techno- economic analysis also indicates the significant emissions reduction potential within both crop/soil management and livestock activities, arising largely from enhanced carbon stock retention and a reduction in methane emissions from enteric fermentation. Despite these benefits, several measures such as the introduction of new livestock species and conservation terracing are considered to be high-cost relative to their estimated mitigation levels and face significant funding and other implementation challenges. As such, several agriculture measures will require significant international technical and financial support. Rwanda NDC Implementation: Final Report Page 60 ENERGY Electricity Manufacturing Transport Commercial & residential Agriculture Electric LDVs Hydropower projects Solar mini-grids Solar street lighting EE agroprocessing Climate compatible mining Efficient brick kilns EE cement production Public transport (buses) Vehicle emissions standards Electric motorcycles Efficient lighting in buildings Efficient cook stoves Off-grid solar electrification Roof top solar PV Solar water heaters Solar pumping for irrigation On-farm biogas z Contribution towards NDC target l l l l l l l l l l l l l l l l l l Environmental effectiveness Indirect environmental effects l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l Adaptation and resilience considerations Cost-effectiveness l l l l l l l l l l l l l l l l l l EVALUATION CRITERIA Socio-economic impacts and co- Equity and welfare l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l Competitiveness and benefits productivity Green growth and employment l l l l l l l l l l l l l l l l l l Alignment with other policy aims l l l l l l l l l l l l l l l l l l Feasibility of Legal and regulatory feasibility l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l implementation Suitability to funding and climate finance l l l l l l l l l l l l l l l l l l Other implementation challenges Short-term options - 2020-2025 a a a a a a a a a a a a a a a a ? a OUTCOME Medium-term options - 2025-2030 Unconditional measure (domesticly supported) Conditional measure (international support) Rwanda NDC Implementation: Final Report Page 61 AGRICULTURE IPPU WASTE Crops and soil Livestock Increased pozzalanas in cement F-gases substitution Landfill gas utilisation Waste-to-energy (WtE) plants Aerobic composting Waste-water treatment & re-use Compost production Improved fertilizer efficiency Soil conservation - terracing Soil conservation - rotation Soil conservation - multicropping Soil conservation - cons.tillage Improved livestock husbandry Improved livestock Improved manure management z Contribution towards NDC target l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l Environmental Indirect environmental effects effectiveness l l l l l l l l l l l l l l l Adaptation and resilience considerations Cost-effectiveness l l l l l l l l l l l l l l l Socio-economic impacts and co- Equity and welfare l l l l l l l l l l l l l l l benefits Competitiveness and productivity l l l l l l l l l l l l l l l Green growth and employment l l l l l l l l l l l l l l l Alignment with other policy aims l l l l l l l l l l l l l l l Feasibility of Legal and regulatory feasibility l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l implementation Suitability to funding and climate finance Other implementation challenges l l l l l l l l l l l l l l l Short-term options - 2020-2025 a a a a a a Medium-term options - 2025-2030 a a ? a a a a ? a Unconditional measure (domesticly supported) Conditional measure (international support) Rwanda NDC Implementation: Final Report Page 62 4.4.1 Unconditional and conditional projects The above indicates that all the options are potentially suitable as NDC measures. However, as shown from the economic analysis, many of the identified projects will require significant financial support. Developing country Parties to the UNFCCC are asked to identify the ‘means of implementation’ relating to their NDC mitigation measures, including the scale of international support required. In response, most are communicating their NDC contributions according to two different components: • Unconditional contribution: Those mitigation measures and policies which will be implemented ‘unconditionally’ through domestic efforts alone (e.g. funded within committed national policy plans and actions); and • Conditional contribution: Additional mitigation measures which could be implemented, but only conditional upon the availability of international support (including funding and other types of support from donors, climate finance and potentially carbon markets). This approach was taken within Rwanda’s INDC, and after discussions with the GoR, it was agreed that this approach would also be used to frame the NDC target(s) for mitigation. This there required classifying each of the mitigation measures as either an ‘unconditional’ or ‘conditional’ action. The multi-criteria evaluation process outlined above provided a basis for the consulting team to discuss and then propose such a grouping of the mitigation measures.21 In so doing, the following broad considerations were also used to help guide the choices: 1. Costs and investment levels: Higher cost projects and those requiring significant investment levels are typically considered more suitable to international support given national budget and resource constraints. 2. Inclusion within existing national policies and sector plans: Several projects and measures are already included within national policy planning and budgeted within sector plans: these can therefore be viewed as domestically committed. 3. Suitability to international support: Measures are more or less suited to existing and emerging forms of support (e.g. under Article 6 of the Paris Agreement), both in terms of projects types and their likelihood to demonstrate real and measurable, and additional, mitigation outcomes. The subsequent proposed grouping of conditional and unconditional NDC measures was shared with key stakeholders and government departments for in-depth discussion and validation from October 2019 to January 2020. The resulting classification is shown below. 21This discursive approach was intentionally adopted instead of a more structured or formal methodology, based on the judgment of the consulting team and through discussion within the counterpart. This was informed in part by time constraints and also the ‘bottom up’ nature of the approach to project identification and evaluation, according to which the government had already taken a clear view on which projects were part of centrally budgeted plans and policies, and which required additional support as mitigation interventions. The consulting team acknowledge that other more formalised approaches can be adopted through use of tools, checklists, criteria-based scoring systems etc. Rwanda NDC Implementation: Final Report Page 63 Table 4.3 Unconditional and conditional NDC mitigation measures NDC measure Unconditional Conditional Hydropower a Solar mini grids a Solar street lighting a EE agro-processing a Climate compatible mining a Efficient brick kilns a EE cement production a Public road transport (buses) a Vehicle emissions standards a ENERGY Electric motorcycles a Electric cars a Electric buses a Efficient lighting in buildings a Efficient cook stoves a Off-grid solar electrification a Roof top solar PV a Solar water heaters a Solar pumping for irrigation a On-farm biogas a Improved fertilizers a Soil and water conservation (terracing) a a AGRICULTURE Soil and water conservation (rotation) Soil and water conservation (multicropping) a Conservation tillage a Improved livestock husbandry a Improved livestock species and population a Improved manure management a Increased pozzolanas in cement a IPPU F-gases substitution a Landfill gas utilisation a WASTE Waste-to-energy (WtE) plants a Aerobic composting a Waste-water treatment and re-use a Rwanda NDC Implementation: Final Report Page 64 5 ALTERNATIVE GHG PATHWAYS 5.1 NDC mitigation scenarios This section presents alternative GHG emissions pathways through 2030 based on the technical analysis described in the sections above. The implementation of NDC mitigation measures through the period 2030 will determine the level of emissions reductions achieved against the BAU baseline. Against the BAU emissions baseline, two basic NDC mitigation scenarios were modelled: • All NDC measures: This scenario estimates the emissions reduction pathway achieved through implementation of all the identified mitigation options considered suitable as NDC measures. This includes both unconditional and conditional measures. Because none of the identified options were assessed to be inappropriate, this scenario can therefore be seen as an ‘upper end’ estimate of how much mitigation potential could be achieved within the NDC sectors through 2030, subject to support. • Domestic measures: This scenario estimates the emissions pathway achieved through implementation of ‘unconditional’ domestically supported projects only. These represent those projects already committed within government plans and programmes or incentivised sufficiently for private sector implementation to proceed. These two mitigation scenarios provide the basis for Rwanda to propose an unconditional and conditional contribution within its revised NDC. Mitigation and investment cost requirements for each scenario were also estimated, followed by sensitivity analysis relating to variations in (a) the BAU emissions forecast and (b) reduced project implementation and mitigation outcomes relative to BAU, as described further below. 5.2 Modelling results Figure 5.1 illustrates the emission projections for the (base case) BAU baseline and the two alternative NDC mitigation scenarios. The associated values are shown in Table 5.1. The graph shows emissions more than doubling under the BAU projection from 5.3 MtCO2e in the base year to around 12.1 MtCO2e in 2030. According to the alternative GHG pathway which implements the domestically supported unconditional NDC measures, it is estimated that by 2030 emissions would instead rise to around 10.2 MtCO2e, representing a reduction against BAU of around 16%. The second NDC mitigation scenario, showing the total mitigation potential from both domestic and conditional mitigation measures, sees emissions increasing only slightly over the period, to around 7.5 MtCO2e, equal to a reduction of 38% by 2030 against the same baseline. Rwanda NDC Implementation: Final Report Page 65 Figure 5.1 NDC emission reduction scenarios against BAU (base case) Source: Authors Table 5.1 Emissions projections under NDC scenarios and BAU (base case) Scenario 2015 2020 2025 2030 Total emissions (MtCO2e) BAU reference case (Vision2050) 5.33 7.42 9.61 12.06 Domestic NDC measures 5.33 7.27 8.26 10.16 All NDC measures 5.33 6.59 6.64 7.50 Reduction relative BAU Domestic NDC measures - 2% 14% 16% All NDC measures - 11% 31% 38% Source: Authors Rwanda NDC Implementation: Final Report Page 66 The BAU and NDC mitigation scenarios are summarised in Figure 5.2 below, which also shows the contribution of each sector to the total estimated potential based on the technical assessments of all mitigation measures. Figure 5.2 NDC emissions reduction scenarios Source: Authors 5.3 Sensitivity analysis Sensitivity analysis was undertaken around three key areas of uncertainty with an important impact on future GHG pathways and the levels of mitigation reported under NDC scenarios: • Economic growth outlook. Lower GDP growth has the primary effect of reducing economy-wide emissions growth in the baseline scenario with the potential for defined mitigation measures to achieve greater relative mitigation (i.e. in percentage terms) • Project implementation and implementation. Sub-optimal implementation of mitigation measures — whether through project delay, scale-back, cancellations or lower than expected delivery — will result in lower mitigation outcomes. • Treatment of Lack Kivu methane power generation. Due to lack of IPCC reporting guidance and lack of data required to estimate project emissions, the Lake Kivu methane power project has not been assessed as an NDC measure within the base scenario. If Rwanda NDC Implementation: Final Report Page 67 treated as a low carbon project, its inclusion as a conditional project could however deliver significant additional emissions reductions. Each of these three sensitivity cases is presented below. 5.3.1 Economic growth outlook Sensitivity analysis was undertaken in order to estimate the impact of a lower GDP growth scenario. As described earlier, future GDP growth is considered to be a major driver guiding sector activity and associated GHG emissions growth through 2030. Developing an assessment of emissions growth and mitigation potential based on an alternative economic outlook is therefore useful in testing the impacts of uncertainty around this key driver. Figure 5.3 and Table 5.2 summarise the results of the same two NDC scenarios presented above applying an alternative lower GDP projection. In this case, BAU emissions increase to around 10.3 mtCO2e in 2030, compared to the value of 12.1 MtCO2e in 2030 based on Vision 2050 growth assumptions (base case). According to this lower growth forecast, it can be seen that the relative emissions reductions achieved through each of the NDC scenarios is now larger, compared to the base case. This result is largely due to the fact the emissions reductions estimated for most of the identified measures are assumed to be implemented independent of economic growth assumptions in the baseline. For example, assumptions and data inputs around the roll-out and coverage of most government programmes relating to energy use, waste and agriculture are assumed to remain the same independent of economic performance and future demand.22 22 This is recognised as a simplification and limitation within the methodology since implementation and coverage will in many cases respond to changes in factors such as energy demand, household numbers, agricultural output etc. In some cases under a lower growth scenario certain identified measures may not even proceed due to lack of demand e.g. new renewable generating capacity. These dynamic effects have not been captured, with the result that the mitigation potential is likely to be overestimated for this specific sensitivity case. Rwanda NDC Implementation: Final Report Page 68 Figure 5.3 NDC emission reduction scenarios against BAU (lower GDP) Table 5.2 Emissions projections under NDC scenarios and BAU (lower GDP) Scenario 2015 2020 2025 2030 Total emissions (MtCO2e) BAU reference case (lower GDP) 5.33 6.96 8.59 10.34 Domestic NDC measures 5.33 6.81 7.25 8.44 All NDC measures 5.33 6.13 5.63 5.78 Reduction relative BAU Domestic NDC measures - 2% 16% 18% All NDC measures - 12% 35% 44% As a result, it can be seen that lower than expected economic growth has the effect of achieving greater relative emissions reductions (not absolute emission reductions) compared to the BAU projection through 2030, although caution must be applied given the likelihood of overestimating mitigation potential under this case.23 In general terms, this indicates a greater 23 See above footnote. Rwanda NDC Implementation: Final Report Page 69 likelihood of achieving a relative NDC target type (i.e. a % reduction against BAU baseline); an important finding in the event of an official government GDP growth outlook (i.e. as per Vision 2050) being adopted for BAU modelling within the NDC. 5.3.2 Project implementation and mitigation Sensitivity analysis was next undertaken in order to assess the potential for lower GHG mitigation outcomes arising from delayed, reduced or unsuccessful project implementation through the period 2020-2030. An assessment was made within each of the sectors concerning the potential for reduced implementation or application rates for NDC programme and projects compared to the base case mitigation scenario. The approach taken was to consider ‘realistic’ alternative outcomes arising from various challenges including e.g. project delays and funding issues, rather than a ‘worst case scenario’ approach according to which most or all projects would not be implemented. The assumptions applied are summarised in Table 5.3 below. Reduced implementation assumptions were applied to over half of the identified projects; IPPU options were not considered given the very high certainty these will be realised and following consultation with MINIFRA staff only one measure (Waste-to-Energy) was entirely excluded. Table 5.3 Summary of lower mitigation scenario NDC measure Assumptions 117 MW of planned hydropower projects realised within period Hydropower compared to 156 MW under base case, reflecting investment challenges and other barriers. Reduced rate of 50 MWp of solar mini-grids installed in off-grid rural Solar mini grids ENERGY areas by 2030 compared to planned 68 MWp under base case. Programme assumed to achieve only 75% of household penetration rate Efficient cook stoves achieved under base case by 2030. Solar pumping for Reduced irrigation area of 63,379 Ha achieved by 2030 compared to irrigation government target of 84,505 Ha under base case. Compost application achieved on reduced area compared to base case Improved fertilizers of 165,000 ha; deep fertilizer placement and biomass management achieved on 25,000 ha. New terraces established on reduced area of 110,000 ha; crop rotation Soil and water achieved on 440,000 ha; coffee-banana multicropping achieved on conservation 15,900 ha; conservation tillage achieved on 180,000 ha. AGRICULTURE Improved livestock Improved fodder planted on reduced area of 60,600 ha. husbandry Improved livestock Reduced herd replacement rates assumed compared to base case, with species and improved dairy cows totalling 97,500 animals will replace 195,000 local population cows. Improved manure Improved manure management achieved for a reduced rate of 350,000 management cows and 350,000 goats. Rwanda NDC Implementation: Final Report Page 70 Lower extraction rates for landfill methane gas, increasing to 40% by Landfill gas utilisation 2030 compared to base case assumption of 60%. Waste-to-energy WtE plants are not implemented within the first NDC period due to lack (WtE) plants of funding and other barriers. WASTE Decrease in quantity of waste treated by biological treatment/ aerobic Aerobic composting composting methods, resulting in a 3% annual increment in composted waste compared to base case assumption of 5% per annum. Reduced rate of urban population connected to wastewater treatment Waste-water plants projected to be 7% by 2022 compared to base case assumption of treatment and re-use 11%, reflecting project pipeline delays e.g. Kigali central wastewater treatment plant in Nyarugenge. Figure 5.4 and Table 5.4 below show the forecast emissions projections against the BAU baseline according to this alternative lower mitigation pathway. It can be seen that in 2030, mitigation against the baseline is lowered to a 27% reduction for all NDC measures, and 12% for domestic measures only. The associated emissions reductions delivered in 2030 under the lower mitigation scenario and base case scenario are shown by sector in Figure 5.5. Figure 5.4 NDC emission reduction scenarios against BAU (lower mitigation case) Rwanda NDC Implementation: Final Report Page 71 Table 5.4 Emissions projections under NDC scenarios and BAU (lower mitigation case) Scenario 2015 2020 2025 2030 Total emissions (MtCO2e) BAU reference case (Vision2050) 5.33 7.42 9.61 12.06 Domestic NDC measures 5.33 7.16 8.56 10.60 All NDC measures 5.33 6.65 7.41 8.76 Reduction relative BAU Domestic NDC measures - 2% 11% 12% All NDC measures - 10% 23% 27% Source: Authors Figure 5.5 Annual GHG mitigation versus BAU by sector in 2030 (all NDC measures) Source: Authors 5.3.3 Lake Kivu methane power generation Lake Kivu contains large volumes of non-anthropogenic methane which can be extracted for use in grid electricity production and other energy uses. Following a number of pilot projects supported by the World Bank and others, a 26 MW power generation project was developed by ContourGlobal (KivuWatt) and commissioned in late 2015, and there are plans to further expand capacity to around 101 MW (ContourGlobal, 2020). Utilisation of the extracted gas offers the Rwanda NDC Implementation: Final Report Page 72 potential to reduce Rwanda’s reliance on imported oil to meet its increasing demand for power as well as reducing the risk of a catastrophic degassing event as seen in Cameroon (see Box 5.1). Box 5.1 Non-anthropogenic methane formation in Lake Kivu Lake Kivu, located on the border between the Democratic Republic of the Congo and Rwanda, is unique in the world because its deeper waters contain an enormous quantity of dissolved gas: estimates range from 250 billion m³ of carbon dioxide (CO2) and 50 to 55 billion m³ of non-anthropogenic methane gas (CH4) (Doevenspeck, M., 2007). This makes the lake one of the largest freshwater reservoirs of dissolved methane on Earth (Morana et al, 2015). The methane is generated by fermentation processes and by the reduction of volcanic carbon dioxide by the same bacteria (Tietze et al., 1980). It is estimated that 100 to 150 million m³ of methane are generated annually in the lake (Doevenspeck, M., 2007). Like other lakes the waters of Lake Kivu show a stratified structure with stable horizontal homogenous layers which have different physical and chemical properties. Studies show that the highest concentrations of carbon dioxide and methane measured in layers below the depth of 260- 270 m where high density gradients prevent any mixing, thus facilitating the gas accumulation (ibid; Pasche et al, 2011; Milucka et al, 2015). Aerobic CH4 oxidation is the main process preventing the methane from escaping to the atmosphere (Pasche et al, 2011). Simulations of physical mixing in the lake show that if the current methane production remains stable a dangerous concentration of the gas composition could be reached in about 100 years. However, this time span will diminish if methane production within the sediment continues to increase at the rate measured recently (Schmid et al. 2005). Indeed, one study has reported that methane concentrations in the lake have increased by up to 15% in the last 30 years and that accumulation at this rate could lead to catastrophic outgassing by around 2100 (Pasche et al, 2011). Although studies also indicate a low risk of such an event occurring (Doevenspeck, M., 2007) there remains a concern that Lake Kivu could erupt within the next 100-200 years, releasing large quantities of methane, as occurred in Cameroon at Lake Nyos in 1986 and at Lake Monoun in 1984 with large fatalities. The risk of such an event could have a devastating impact on the entire Lake Kivu catchment area of 10,000 km² (ibid). In this context, scientists have postulated a controlled degassing of the lake, as has been carried out in Cameroon (Schmid et al. 2003). Extracting Lake Kivu’s methane gas for power generation also offers the potential to reduce the risk of an eruption, whilst offering the ability to reduce Rwanda’s dependence on imported oil to meet electricity demand. The KivuWatt project, commissioned by ContourGlobal in December 2015, is the only gas/water extraction project currently operating in the world. The first phase of this project is powering three gensets to produce 26 MW of electricity for the local grid. The next phase of this project plans to deploy nine additional gensets at 75 MW to create a total capacity of over 100 MW (ContourGlobal, 2020). Source: various In addition to these important benefits, utilisation of lake methane for power generation has the potential to reduce GHG emissions in two principal ways. Firstly, by displacement of oil-fired generation by combustion of methane due to the latter’s lower emission factor, and secondly, by utilisation of methane which would otherwise be vented to atmosphere. The first effect is relatively simple to quantify - subject to the assumption of oil-fired generation under the ‘baseline scenario’ against which any emissions reductions can be quantified. The second effect Rwanda NDC Implementation: Final Report Page 73 is more problematic. This is partly because the rate and degree to which Lake Kivu’s methane is vented to atmosphere over time is not fully understood or quantified. Limnological studies typically classify Lake Kivu as permanently stratified with much of the dissolved methane stored within lower depths over long periods of time. The KivuWatt project pumps water containing this dissolved methane (and also CO2) from these lower layers for transportation to shore and subsequent combustion, these activities also resulting in a certain volume of fugitive emissions. Assumptions around fugitive methane emissions under a counterfactual ‘baseline scenario’ are therefore not clear, nor are the rate of fugitive methane and CO2 emissions occurring during the project activity itself (i.e. during the pumping of gas to the surface). Lake Kivu is unique worldwide, and utilisation of lake methane is a novel technology. There are no existing guidelines from the IPCC or other internationally recognised organisation pertaining to emissions accounting for such a project. At the current time, it is understood that additional research involving methane flux characterisation and collection of robust monitoring data will be required to develop suitable accounting guidelines consistent with UNFCCC reporting requirements. This will be needed before such projects can be quantified for purposes of meeting NDC targets (and/or generating “MRV-able” emissions reduction units consistent with the Paris Agreement “rulebook”). Full consideration of these issues is beyond the current scope of work. However, an illustrative calculation has been made in order to estimate the likely scale of GHG reduction potential from Lake Kivu methane utilisation. This is based on the following simple scenario-based assumptions: • Project emissions: Includes CO2 emissions from combustion of CH4 at power generation plant plus fugitive emissions of CH4 arising from the extraction process (fugitive CO2 emissions not quantified). • Baseline emissions: Includes fugitive emissions from CH4 released from the lake to the atmosphere plus CO2 emissions from combustion of fuel oil used to generate the equivalent power generation as per the project (fugitive CO2 emissions not quantified). Emissions reductions are calculated as the baseline emissions minus the project emissions. The calculation assumptions and results are summarised in the tables below. The results are shown for the existing KivuWatt project capacity of 26 MW and also its possible expansion to 101 MW. As discussed above, there is high uncertainty around the net rate of fugitive methane emissions in both the baseline and project scenarios24. Two simple cases are therefore considered, with net fugitive releases to atmosphere of 25% and 50% of the captured lake methane. The results provide a ‘first pass’ estimate of the mitigation potential from utilisation of lake methane subject to its recognition under international emissions accounting rules. Notwithstanding the high degree of uncertainty, these are seen to be significant, ranging from around 0.6-0.9 24i.e. how much of the utilized methane gas can be treated as fugitive emissions in the baseline, and also how much of the captured methane gas is lost at the surface as releases to atmosphere; in this case only the rate of project fugitive emissions are varied, for simplicity. CO2 releases represent another emissions source not quantified here. Rwanda NDC Implementation: Final Report Page 74 MtCO2e/year for the existing KivuWatt Phase 1 plant up to 2.4-3.4 MtCO2e/year under KivuWatt Phase 2.25 Table 5.5 Lake Kivu methane power production; key assumptions Parameter Value Unit Source KivuWatt Phase 1 26.4 MW ContourGlobal, 2020 KivuWatt Phase 2 101.4 MW Average plant availability 80 % Annual generation (Phase 1) 185,011 MWh Project assumptions Annual generation (Phase 2) 525,600 MWh 7,870 Btu/kWh US EIA, 2016 Gas-fired power plant heat rate 8.30 GJ/MWh Calculated 10,811 Btu/kWh US EIA, 2016 Oil-fired power plant heat rate 11.41 GJ/MWh Calculated Natural gas combustion emission factor 54300 kgCO2/TJ IPCC, 2006 Fuel oil combustion emission factor 72600 Oxidation factor 1 - IPCC, 2006 Global Warming Potential (GWP) - CH4 28 - IPCC, 2014 Table 5.6 Lake Kivu methane power production; emissions reduction calculations KW Phase 1 (26 MW) KW Phase 1 (101 MW) Parameter Fugitive Fugitive Fugitive Fugitive CH4 25% CH4 50% CH4 25% CH4 50% Baseline emissions (MtCO2e per year) Oil-fired power plant emissions 0.15 0.15 0.59 0.59 Fugitive methane emissions 1.10 1.10 4.24 1.10 Total GHG emissions 1.26 1.26 4.83 4.83 Project emissions (MtCO2e per year) Gas-fired power plant emissions 0.08 0.08 0.32 0.32 Fugitive methane emissions 0.28 0.55 1.06 2.12 Total GHG emissions 0.36 0.63 1.38 2.44 Emissions reductions (MtCO2e per year) Total GHG emissions 0.90 0.62 3.45 2.39 Source: consultant calculations 25 The choice of power generation technology in the baseline represents another important area of uncertainty. Rwanda NDC Implementation: Final Report Page 75 5.4 Summary Table 5.7 summarises the model results for the alternative GHG pathways in terms of reductions against the BAU baseline scenario through the NDC period 2020-2030. For the target year 2030, the base case scenario is estimated to achieve a reduction of 16% for unconditional measures increasing to 38% with conditional measures included. As presented within the sensitivity analysis above, the lower mitigation scenario delivers a lower reduction outcome relative to BAU, while the lower GDP growth scenario results a in higher reduction relative to BAU. Taken together, the results therefore indicate the potential range of mitigation delivered by identified NDC measures according to key uncertainties around baseline and mitigation factors. For domestic measures only, this range is a 12-18% reduction against BAU in 2030, increasing to 27-58% for all NDC measures subject to inclusion of Lake Kivu methane for power generation. Guided by the principle that Rwanda should only adopt targets considered capable of being delivered, the choice of which mitigation target(s) to adopt within the revised NDC should necessarily be informed by a view on which scenario is considered most feasible. In this context, it should be noted that the base case scenario is based on official target assumptions for GDP growth and project outcomes. Overestimating the former has the tendency to underestimate mitigation outcomes relative to BAU, while overestimating the latter has the tendency to overestimate mitigation outcomes relative to BAU. From this, it might be reasonably concluded that the base case represents a feasible estimation of what could be delivered under the NDC through 2030, subject to an enabling domestic policy framework and attracting international funding and support. Table 5.7 Mitigation achieved relative to BAU for alternative GHG pathways Scenario 2015 2020 2025 2030 Domestic NDC measures Lower mitigation scenario - 2% 11% 12% Base case scenario - 2% 14% 16% Lower GDP growth scenario - 2% 16% 18% Inclusion of Lake Kivu methane project - 2% 14% 16% All NDC measures Lower mitigation scenario - 10% 23% 27% Base case scenario - 11% 31% 38% Lower GDP growth scenario - 12% 35% 44% Inclusion of Lake Kivu methane project - 20% 56% 58% Note: Inclusion of Lake Kivu assumes expansion of current Phase 1 (26MW) to 101 MW under Phase 2 2025-2030; an estimated net fugitive methane release rate of 50% is assumed for conservativesness. Rwanda NDC Implementation: Final Report Page 76 6 ADAPTATION AND RESILIENCE INITIATIVES IN RWANDA 6.1 Policy and legal framework Rwanda has undertaken a progressive trajectory in efforts to climate-proof its development. It ratified the United Nation Framework Convention on Climate Change (UNFCCC) in 1995, the Kyoto Protocol in 2004, and the Paris Agreement in 2016. Rwanda submitted its National Adaptation Programmes of Actions (NAPA) in 2006. In line with the Paris Agreement, Rwanda submitted its Intended Nationally Determined Contribution (INDC) in 2015 that later became NDC in 2016. Rwanda submitted its initial communication to the UNFCCC in 2005, the second in 2012, and the third in 2018. The objective of the National communication is to build capacity for successful implementation of the convention; general awareness and updates; assist for policy formulation and national planning; update on GHG emission status, mainstreaming scenarios for emission reduction, and update adaptation status and mainstreaming into planning (GoR, 2018a). The NDC is a commitment towards the implementation of the Paris agreement with mitigation and adaptations actions. In the same framework, Rwanda has joined the NDC partnership and launched a plan during the Africa Green Growth Forum held in Kigali in November 2018. Rwanda has adopted the new Environmental law 26 that takes into account climate change more than the previous Environmental organic law. In addition, recently in June, a new National Environment and Climate Change Policy was enacted with the goal of achieving a climate resilient nation with a clean and heathy environment (MoE, 2019a). The Green Growth and Climate Resilience Strategy was adopted in 2011 with a time horizon of 2050. The strategy has 14 Programmes of Action (PoA) that include adaptation to climate change in the following programmes: • PoA 1: Sustainable intensification of agriculture • PoA 2: Agriculture diversity in local and export markets • PoA 3:Integrated Water Resources Management (IWRM) and planning • PoA 4: Integrated Land Use and Management • PoA 11: Ecotourism, Conservation and Payment of Ecosystem Services • PoA 12: Sustainable Forest and Agroforestry • PoA 13: Disaster and Diseases prevention • PoA 14: Climate data and projections A recent review of the strategy indicated that it is still valid and relevant to Rwanda’s vision (vision 2020/vision 2050) as well as strategic plan such as National Strategy for Transformation (NST) for the period between 2018 - 2024 (MoE, 2018). Furthermore, in 2019, a new Environment and Climate Change Policy was adopted with remarkable consideration of climate change with clear climate relevant objectives outlined below: 26 LAW N°48/2018 OF 13/08/2018 ON ENVIRONMENT, Official Gazette no. Special of 21/09/2018 Rwanda NDC Implementation: Final Report Page 77 • Greening economic transformation (resource efficiency, low carbon, climate resiliency, circular economy, green technology and procurement, green urbanization and settlements, and green mobility). • Strengthening meteorological and early warning services (climate and weather services production and mainstreaming into all sectors of Rwanda’s socio-economic development, production and access of meteorological, climate and weather services for better planning in all sectors of economy; • Promoting climate change adaptation, mitigation and response (strengthen mitigation and adaptation in both planning and implementation; • Strengthening environment and climate change governance (mainstreaming of environment and climate change into all sector policies, national coordination for the management of critical ecosystems, inclusive decision-making and interventions for environment and climate change management, education & awareness of Rwandan society on environment, weather and climate change, and strengthen the institutional framework and coordination mechanisms); and • Promoting green foreign and domestic direct investment and other capital inflows (strengthening environment & climate financial mechanisms for more efficiency, effectiveness and impact and strengthening climate proofing capital inflow in national economic planning) (MoE, 2019a). This is a demonstration of the progressive policy relevancy of climate change to Rwanda’s economic growth and development that lends the momentum to address climate change in general and adaptation/resilience in particular as a national development challenge that must be addressed by sectors. 6.2 Adaptation in priority Sector Strategic Plans Priority sectors were identified based on the NDC Partnership Plan that was led by the Ministry of Environment with the support of the NDC Secretariat. The consideration was also based on the focus of the World Bank support in the context of the NDC partnership plan endorsed by the GoR in November, 2018. The following section outlines the status of the sectors and the key baseline data and information that is considered relevant to climate adaptation and resilience as a follow up to inform NDC implementation in Rwanda. 6.2.1 Water Resources / IWRM Integrated Water Resources Management (IWRM) is the approach adopted to enhance climate change resilience at community level through Catchment Management Committees, among other options. Catchment management committees were established at 35% and available for the catchments of Muvumba, Nyabarongo, Nyabugogo, and Sebeya, water permits issued at 8% with the system accessible online on water portal, while for transboundary basins, two cooperation frameworks were established by the fiscal year 2017/2019 (MoE, 2017a). In addition, a new water law was established on 13/08/2018 and six ministerial orders were developed. Water resources availability is reported to be 670 m³ /capita/annum and the water bodies with ambient water quality are at 15% in the year 2017 (MoE, 2017a). Furthermore, by 2016irrigation Rwanda NDC Implementation: Final Report Page 78 systems had been developed as part of IWRM approach covering 48,508 hectares (MoE, 2017a), and a map of degraded areas in four priority catchments was available from 2017 (MoE, 2017a). Catchment water balance modelling is in place for Muvumba, Nyabarongo, Sebeya and Nyabugogo were completed (MoE, 2018). In an effort to increase water storage and availability to Rwandans, household level adoption of rain water harvesting has increased and has reached 17% in 2014 (NISR, Integrated Household Living Conditions Survey 4 (EICV 4), Rwanda, 2015). In the context of adaptation to climate change, the Landscape Approach to Forest Restoration and Conservation (LAFREC) project, funded by the World Bank targets an early warning system for flood management within the Sebeya Catchment. The WB supported project objective is to demonstrate landscape management in the context of environmental as well as climate resilience and livelihood restoration. The following actions are ongoing and by the end of the project (December 2019), the following are targeted: • 90 Households (HH) in the project area with advanced warning of individual major rainfall or floods; • Land area converted to enhanced biological protection practices is targeted to reach 3,428 ha by end of the project; • A total of 70 sub-projects are also expected to support livelihoods; • Flood hazard mapping for selected flood hotspots will be available by the end of the project; and • Impact monitoring on land rehabilitation techniques will be produced (World Bank, 2019c) 6.2.2 Agriculture Rwanda’s economy depends primarily on agriculture, which is predominantly rain fed. Land is also vulnerable to heavy rainfall associated with soil erosion and landslides (resulting in the loss of fertility) in North, Western, and Southern province, while Eastern Province is often vulnerable to draught. To reduce land degradation, 110,905 ha of radical terraces, and 923,604 ha of progressive terraces were completed in 2017 (GoR, 2017a). Up to 2015, 41% of farmers used improved seeds on consolidated land to increase up to 635,603 ha in 2017, and irrigation was implemented on 48,508 ha in the same year (GoR, 2017a). Value addition to the agriculture produce is still a challenge given that in 2014, agro-processing facilities were estimated at 10% with a capacity of 400,000 megatons (MINAGRI, 2016). Crop rotation is implemented by 48% of farmers, 65% of households are using manure, 146,652 MT of compost used in 2018, 197 plant extension doctors trained, 75 plant clinics, 18 on-station research plots. In addition, fertilizer deep placement projects in rice are ongoing. Regarding agriculture diversification in local and export market, 41% of farmers were using improved seeds on consolidated land in 2018 (MoE, 2018). Thus, these improvements in agricultural practices are likely to spur growth of the sector with potential to accelerate penetration of value added products on Rwandan and export markets. 6.2.3 Land Use Management The high population density puts pressure on natural resources (land for housing, agriculture, wood for domestic use in construction, cooking, infrastructure, etc.). Without proper land use Rwanda NDC Implementation: Final Report Page 79 planning and implementation, and with a growing population, the pressures are likely to increase. In addition, Rwanda must increasingly incorporate climate change considerations into land use planning to optimize land allocation to productive uses. By using instruments such as a Spatial Data Guidelines or Policies, cities will be able to use spatial information to integrate climate resilience in their planning processes. It is also essential to monitor and evaluate progress on implementation to facilitate and guide compliance and ensure enforcement measures are reliable. In this framework, Land Administration and Information System (LAIS), National Land Use Development Master Plan (NLUDMP) and 8 sectoral plans including that of the City of Kigali (CoK) were already available in the year 2017 (MoE, 2017a). On the other hand, assessment report done in the same year showed that only 25% compliance of districts to the LUDMP. Rwanda land use portal is operational and LAIS accessible for all 30 Districts with five irembo e-services linked and mobile phone application operational (MoE, 2018). In all, it is important that the impacts of climate change on natural resources is incorporated during land use planning. Climate resilience of natural resources such as land and energy links must serve as critical considerations when developing land use plans (FONERWA, 2017). 6.2.4 Forestry Though forests mainly contribute to mitigation of climate change as carbon sinks, they also have adaptation benefits, which include erosion control, and reduction or retention of runoff, which can reduce flood and landslide risks. According to the Ministry of Environment (MoE), the targeted forest cover of 30% was reached in the fiscal year July 2018/2019, from the 29.8 % reported in 2016/2017 (GoR, 2017a; MoE, 2019a). 6.2.5 Housing In 2016, it was reported that 62.60% of urban population live in informal settlements, while less than 20% of the urban population in areas covered by master plans had storm water considerations in 2016 (MININFRA, 2017a). MINALOC has identified grouped settlement, a critical entry point for the Integrated Development Program (IDP) as the main solution to reduce pressure on land for housing. In this regard affordable housing projects are being implemented in the country either by private sector or with support from the Government such as 537 units in Batsinda II and 56 units in Abadahigwa settlement in the suburbs of Kigali City. Moreover, an Affordable Housing Fund was adopted by the Cabinet in 2017 to increase access to affordable housing for the low to middle income groups . The need for affordable housing units is predicted to reach 340,000 by 2024 (MININFRA, 2017b). The current initiative on climate change impacts data and information is crucial in informing planning to achieve the ambitious targets in the housing sector. 6.2.6 Health In the fiscal year 2016/2017, 308 malaria incidents per 1,000 population were reported and the malaria proportion mortality rate was at 5.7 per 1,000 in the same year. Among children under 5 years, , 80% slept under mosquito nets (LLIN) (MINISANTE, 2018). There is growing evidence that an increasing disease burden, from Malaria in particular, is associated with climate change and its impacts27. 27 https://www.irishtimes.com/news/science/scientists-prove-link-between-climate-change-and-malaria-1.1715589 Rwanda NDC Implementation: Final Report Page 80 6.2.7 Transport Climate change adaptation is being mainstreamed in the transport sector by increasing the number of all-weather roads through improving roads from unpaved to paved roads with a focus on national roads. In 2018, from a total length of national roads of 2749km, 1385.5km were paved (50%). Furthermore, Rwanda Transport Development Agency (RTDA) with a grant from the Nordic Development Fund (NDF) signed in 2016 has initiated a project for “Developing Capacity for Climate Resilient Road Infrastructure’’. The project is intended to build capacity for all stakeholders involved in road construction and management to mainstream environment and climate change into the whole life cycle of transport infrastructure through vulnerability mapping, training and awareness, and development and testing of manuals, guidelines and standards. Vulnerability mapping is ongoing in collaboration with stakeholders such as MoE, Meteo-Rwanda, RWFA and REMA. The sustainability of this initiative will benefit from establishing an analytical framework that RTDA and its partners can reliably use to monitor and address the impacts of climate change on road infrastructure. 6.2.8 Mining Model mine concepts and mining standards were recently developed and Strategic Environmental Assessment for mining sector was done, while environmental and social impact assessment and mining licence are mandatory for every mining project28. The annual contribution of the mining sector to export revenues was 250 M USD in the fiscal year 2017/18. However, minerals are exported in raw material form (MoE, 2017a). Regarding the water use, it was reported that all mines are complying with rules on efficient use of water in their operations (MoE, 2018). Even with these initiatives, it is important that a framework to monitor and deal with the impacts of climate change in the mining sector be put in place to address critical sustainable development challenges such as soil erosion and water resources management. 6.2.9 Disaster risk reduction Since the year 2017, routine weather forecasts have supported early warnings for heavy rainfall events and flooding with early weather warning registered for 70% of extreme weather events (MoE, 2017a). Sectoral use of weather related hazards information over 2017 and 2018 was as follows: Agriculture: 30%, Health: 20%, Infrastructure: 50%. In addition, online forms for data requests, CLIMSOFT, an open-source Climate Data Management System improved accuracy in weather forecasting up to 80 % by 2018 (MoE, 2017a). Furthermore, disaster prone areas in drought, earthquake, landslide and flood were mapped and also the disaster inventory system was put in place with disaster pre-warned at 80% (GoR, 2019). National Contingency plan matrix is in place. District Disaster Management plans are available in 70 % of Districts and various methods were used to train key community groups on disaster preparedness and response (MoE, 2018). In order to reduce the adverse impacts of natural hazards, the Government of Rwanda has provided in recent years a policy framework for Disaster Risk Reduction which include a policy and a law for disaster management. In addition, DRR has been strongly mainstreamed in the first National strategy for transformation-NST1. 28 https://waterportal.rwfa.rw/sites/default/files/inline-files/Towards%20sustainable%20mining.pdf Rwanda NDC Implementation: Final Report Page 81 6.2.10 Finance for climate resilience Financial limitation is one of the major challenges among others, which results in gaps for technical and technological capacity, pressure on natural resources linked to high population density. By the fiscal year 2017/18, 99 million USD had been mobilized by the National Fund for the Environment, FONERWA, since 2013/2014 while the target is to mobilize 217.78 million USD by 2023/2024 (MoE, 2017a). However, the later target is considerably underestimated because it does not consider other channels through which climate finance flows to Rwanda such as agriculture, infrastructure, NGOs, etc. Rwanda NDC Implementation: Final Report Page 82 7 CHALLENGES IN ADAPTATION AND RESILIENCE Challenges to the implementation of adaptation and resilience options are mainly classified at policy/strategic; global/national (sub-national); program and project levels. Both the 2017 and 2018 Rwanda NDC implementation and partnership plans identified the following areas to have broadly captured the demonstrated gaps that need to be addressed and strengthened (GoR, 2018d): • Institutional and regulatory framework for sector coordination • Data availability, collection , management, reporting and verification • Limited financing opportunities for flagship projects implementation • Institutional and technical capacity among sectors involved in adaptations strategies (government, private sector, and Civil Society Organizations), particularly for developing bankable projects for domestic and external funds mobilization • Challenges on the operational level focus on metrics, data management, monitoring, reporting and verification. The following are primary areas of concern in the development of reliable metrics on adaptation and resilience: 1. Unlike mitigation, there is lack of a well-established standard M&E methodology and indicators for adaptation interventions. In Rwanda’s case, M&E including indicators to track progress have been iteratively developed, revised and refined to inform sector specific development indicators that include those relevant to adaptation and resilience. In addition, various other initiatives including Baseline Vulnerability Index for Rwanda29, National Communications, and the Strategic Program for Climate Resilience (SPCR) have specifically generated M&E relevant to adaptation. The current M&E developed in the context of WB technical assistance builds on these experiences and initiatives and the robust stakeholder consultations and inputs to inform a useful tool that is practical and realistic in supporting Rwanda’s NDC agenda towards 2030. 2. The nature of adaptation as an addition to development interventions makes the determination of baselines for specific adaptation investment challenging to establish unequivocally. The current approach worked on the assumption that adaptation interventions can be tracked as a standalone and quantifiable complement to development investments. This approach can realistically facilitate tracking and attribution of adaptation measures either as a standalone as may be the case for rain water harvesting or additional as in the case of soil erosion. 3. The attribution of adaptation benefits to expected results in the normal lifetime of standard projects and programs poses unique challenges to selection of interventions. It is therefore important that investments in adaptation projects and programs be evaluated to ensure impacts are appropriated to interventions. Importantly, the evaluations will allow for guiding future interventions including replication and scale up of good adaptation interventions and practices. There is a problem of attributing 29http://www.climdev- africa.org/sites/default/files/DocumentAttachments/Baseline%20climate%20change%20vulnerability%20index%20for %20Rwanda2.pdf Rwanda NDC Implementation: Final Report Page 83 outcomes in the form of increased resilience directly to specific adaptation investments. It is important to note that adaptation is inherently a complex process cutting across sectors and levels of interventions. 4. Identifying the best possible proxy outcome indicator is a key challenge in designing M&E frameworks. In addition, composite indicators such as a vulnerability index and adaptive capacity while useful in broad terms as a guide on national and sub-national vulnerability and resilience, present challenges in mapping and therefore guiding sector specific interventions. Whereas a collaborative multi-sectoral approach is required for robust planning and analysis to reduce vulnerability, in all likelihood it poses challenges in determining sector specific adaptation actions. It is therefore important that the methodology for adaptation M&E responds to sector specific measurements including investments in order to address the attribution problem cited above. These challenges have been addressed using the following approaches: • Ensuring consistency in identifying adaptation priority action lists for 2021 and 2030 • Formulating performance indicators with clear metadata that can support consistent monitoring and reporting at strategic levels (UNFCCC, NST and SSPs (ENR RBM)) as well as facilitate tracking progress of NDC implementation. • Providing reliable support to sectors to generate baselines and to facilitate ongoing monitoring. In addition to the above, sector specific challenges and gaps on climate change adaptation and resilience have been identified in different sectors through analysis including the comprehensive Gaps and Needs analysis conducted to inform the PPCR process, as outlined below. 7.1 Water Resources Rwanda is still a water scarce country with 670 m³ of water per capita per year and 25% of the population are still unable to access safe drinking water. In addition to water scarcity, other challenges were identified: Limited human capacity; high competition among water users; inadequate wastewater management, and water pollution and these are associated with inadequate management of wastewater and agricultural inputs from rural areas (GoR, 2017a; MoE, 2017a). Specifically, the water and sanitation subsector has its own challenges that are affected by gaps in the analytical scope including: • gaps in water access especially in scattered and unplanned settlements; • high costs of service provision due to the depletion of water resources; • gaps in human capacity for planning, operation, and maintenance; • consolidation and institutional responsibility, the integrated water resources management in Rwanda has been evolving and the recent parliamentary approval of the water board will usher in institutional stability that will lead to effective management of climate related issues such as flooding; • low level of sustainability of WASH Services, poor quality services, especially in rural areas; Rwanda NDC Implementation: Final Report Page 84 • insufficient water and wastewater treatment and solid waste management, issues in technical and financial capacity among government and private sector and community for investment in water and sanitation sector, and • weak monitoring systems (MININFRA, 2017a). 7.2 Agriculture Given that arable land is 48 % of the total Rwandan area (26,338 km2) plot size and land availability are limited. In addition, land fragmentation is also another issue among other constraints that limit the production and profitability of most farmers. Though efforts have been made through terracing and other mitigation measures, land degradation is accelerated by high slopes and high rainfall intensity which are the main drivers of soil erosion. In addition, soil acidity which is observed in three quarters of total arable land is another threat to soil productivity. Pressure on land and other natural resources mainly as a result of population density and growth, exacerbates the challenges of agriculture production. Furthermore, inadequate agriculture commodity market and value chains limits profitability and food security (MINAGRI, 2017). Unequal distribution of benefits at household and community levels and limited profit to women and youth who are more involved in agriculture activities as well as limited financing alternatives constitutes another limitation. Production and profitability are also constrained by limited skills among farmers with low levels of formal education. Access to finance is a cross-cutting issue that is also felt by the agriculture sector (MINAGRI, 2017). The above challenges are further exacerbated by climate-related factors such as flash floods and extensive soil loss. Thus, improved management of agriculture practice in Rwanda will greatly benefit from efficient planning that can be facilitated by appropriate and targeted analytics that adequately inform climate adaptation and resilience of smallholder farmers, in particular. 7.3 Land Use Management Annual monitoring of human settlement in both urban and rural area and the population growth is considered one of the key challenges (MININFRA, 2017b). In fact, the urban population compared to the last census is projected to increase from 1.7 million in 2012 up to 4.9 million in 2032, i.e. a rise of 30%. Similarly, the rural population with the same rate of increase over 20 years is projected to rise from 8.7 million in 2012 to 11.4 million in 2032 (GoR, 2018b). Another key challenge to adaptation is that less than 10 % of households are able to afford a formal housing unit, and this has pushed the government to facilitate affordable housing unit as a high level priority. Furthermore, an increase of un-authorized construction on agricultural land in urban area is still observed and would compromise food security (MININFRA, 2017b). Thus, weak land use planning and compliance need to benefit greatly from reliable analytics that can address competing interests among land users. In fact, land use master plans at districts levels are not harmonized with national land use master plan which makes difficult monitoring of compliance (MoE, 2017a) factors that lead to exposure to climate change impacts. In summary, soil erosion, land degradation, urbanization, pollution, population growth are current major challenges of land use management. Rwanda NDC Implementation: Final Report Page 85 7.4 Forestry The forestry sector is also constrained by competition with other land users (agriculture, housing, etc.). In addition, unproductive forest management practices like illegal tree felling, poor agroforestry practices, and the predominance of one species, mostly eucalyptus. Differences between demand and production (more demand than production, mainly for fuelwood and construction) are major challenges in the subsector (MoE, 2017a). These inevitably result in deforestation and erosion and soil loss especially in the wake of climate change and its impacts which are increasingly prevalent. Furthermore, uneven distribution of forest (more in Western province than the rest of the country); poor genetic quality of manmade forest associated with poor productivity; low involvement of private sector in forestry management (low investment financial return), and limited technical skills and capacity are other identified challenges (MINILAF, 2018). Analytics on climate change impacts can help address these areas to improve planning for forestry and agro- forestry management. 7.5 Mining Identified challenges in mining subsector are mainly related to the limited capacity like in other sectors. Additional sector specific challenges include: • inadequate and unpredictable finance; • dominance of small-scale mining which is export-oriented with contribution to soil erosion and loss as well as overall environmental degradation; • inadequate infrastructure and services; • limited research and knowledge on mineral availability and professional and technical knowledge, shortage in skilled labour; obsolete technology and processes; inadequate environmental management, including occupational, social, health and safety risks; price volatility of mining produce; and • illegal mining, etc. All these factors can be addressed through provision of reliable data and information including climate adaptation and resilience metrics and significantly improve planning and overall sector performance. 7.6 Energy The energy sector challenges are summarized below according to subsectors: • Electricity: Generation of electricity is constrained by various challenges including those related to climate change impacts such as: achieving correct mix of generation, timely maintenance of infrastructure, high investment cost of electricity generation infrastructure and high investment cost of transmission lines. Concerning access, issues are linked with limited connectivity of remote areas, aligning on- and off-grid power, maintenance, and finance. Energy efficiency is also constrained by limited capacity and awareness among energy utility company, private sector, and end-users, poor quality technologies, coordination of different initiatives, etc. There has already been evidence Rwanda NDC Implementation: Final Report Page 86 that climate impacts such as soil erosion causes sedimentation and therefore generation capacity and flash flooding that destroys infrastructure and increases maintenance costs. • Biomass: Deficit in wood supply, gaps in institutional coordination, limited promotion of alternative sources of cooking energy (like Liquefied Petroleum Gas, LPG). These factors are associated with deforestation and soil loss that is accelerated by climate change impacts (MININFRA, 2017c). 7.7 Climate data management Insufficient modern infrastructure, and limited human capacity to translate climate and weather information into end user products are among the challenges of climate data management. High quality research is another gap that must be addressed to guide monitoring and ensure high quality forecast and early warning system products (MoE, 2017a). 7.8 Health In the health sector, major issues are related to the capacity gaps particularly at district level (district health units) that limits effective coordination of health services. In addition, gaps in technical skills as well as high turn-over among health personnel is another challenge. An additional challenge is the limited capacity for supply chain management at different levels as well as unsustainable external financing of health sector (MINISANTE, 2018). Both areas can be addressed through strengthened preventive measures including capacity to adapt to disease outbreaks which can benefit from improved analytics on climate change impacts. 7.9 Transport In terms of adaptation, the transport sector is challenged by lack of all-season roads in rural areas which hampers transfer of agriculture produce from farm gates to the market. Overloading is another challenge that triggers high cost of road maintenance as well as limitation of accessibility especially in case of bridge damages. Unpredictability and delays of public transport services as well as the lack of integrated transport modes are other challenges in the transport sector. Accident and incidents occurrence have also been identified among the challenges (MININFRA, 2017d). Other issues are related to the limitation in infrastructure, and limited analytical information that can facilitate planning for proper storm water management in the face of growing climate change impacts. 7.10 Housing and human settlement The sector experiences challenges of monitoring demographic growth and movement that is not proportionate to existing housing initiatives. Clear demarcation between urban and peri-urban areas must be well defined to address inconsistency in population projections (e.g. between NISR and WB reports) as well as gaps in land use planning and monitoring. Alignment between Urbanization policy with Human Settlement policy was also another challenge that will likely be addressed through National land use master plan currently under review to improve spatial planning. Other identified challenges include unregulated construction, both in urban and rural areas that contributes to the depletion of land and other natural resources; conflict with other land uses Rwanda NDC Implementation: Final Report Page 87 (especially agriculture); gaps in compliance with land use plans. Additional challenges include limited financing mechanisms in urban development; high cost of land, poor quality construction materials; high speculation of landholders, lack of technical capacity (e.g. limited expertise at national level, urban planners particularly in local governments). (MININFRA, 2017b). Addressing these issues will require improved planning especially in the face of a changing climate that adds to existing challenges. Thus, improving the analytical framework of the sector has the potential to support informed planning to improve sector performance. Rwanda NDC Implementation: Final Report Page 88 8 EVALUATION OF ADAPTATION ACTIVITIES AND INDICATORS 8.1 Overview A comprehensive review and analysis of adaptation and resilience initiatives in Rwanda to date provides an overview of key interventions, activities and metrics, and indicators that can be crucial in monitoring and reporting on Rwanda’s progress in implementing the NDC. This provides an opportunity to align national planning, monitoring and reporting on adaptation actions as well as managing transparency and accountability for purposes of global reporting and tracking finance flows to Rwanda in particular. The key reference documents included various national reports seeking to address the following questions: • How do the national reports and other initiatives, include national efforts such as NAPs/vulnerability studies/communications (adaptation – challenges)/Green Growth Climate Resilience Strategy (GGCRS)-SPCR/Forest Investment Plan (FIP), relevant to NDC options and analytics on climate adaptation and resilience? • How adaptation/resilience is reflected in and facilitate delivery on national sustainable development priorities in SSPs and linkages to NST 1? • RBME&L: What are the opportunities to improve the metrics to serve as a guide to data collection and overall strategic planning, implementation and reporting on NDCs? The goal is to make informed decisions on practical adaptation actions and to base measures to respond to climate change on a sound, scientific, technical and socio-economic foundation, taking into account current and future climate change and variability (WMO, 2007). Addressing the above questions will inform the national context and improve over time the options outlined below. • Identify and develop climate adaptation and resilience analytics of national relevance to report on NST/7-year Government program implementation progress through the sector strategic plans and integrate in ENR MoE RBME/aligned with NISR; • Facilitate sectors to design climate adaptation and resilience analytics to consistently inform development and review/revision of sector strategies in a way that includes a comprehensive review of climate vulnerability in their sector programs; • Facilitate Districts to monitor and report (including Imihigo) on sector specific climate adaptation and resilience indicators to increasingly address and reduce vulnerability; • Develop indicators, baselines and targets as well as metadata at various levels to facilitate progress monitoring and evaluation at projects/programs and enhance capacity for application; • Align national information with international reporting (UNFCCC) and identify/fill any data gap 8.2 Summary of adaptation activities and their corresponding indicators The summary of activities, sub-activities and the metrics including indicators, baselines, milestones and targets were selected through extensively rigorous consultations with sector expert teams through various iterative discussions within sectors and in workshops. The Rwanda NDC Implementation: Final Report Page 89 workshops had group discussions and plenary sessions of representatives from various sectors that articulated the selected options and metrics that form the summary Tables Table 8.1 toTable 8.8. It is also important to underscore the importance of using evaluation criteria elaborated in Table 8.10 - adapted from the framework applied to mitigation projects - and also used for the mitigation methodology to guide priority adaptation options. The summary table was consequently presented to other stakeholders including civil society organizations and Rwanda Association of Professional Environmental Practitioners (RAPEP) to solicit inputs and promote consultation, consensus, inclusiveness with women’s participation in consultations and therefore national ownership of the NDCs deliverables. Tables Table 8.1 to Table 8.8 presents the summary with prioritized sector adaptation interventions, corresponding indicators, baselines and targets characterized as unconditional (domestically supported) and conditional (need for international support) m³. Rwanda NDC Implementation: Final Report Page 90 Table 8.1 List of adaptation interventions in the water sector and corresponding indicators Sector: Water Uncond Conditi itional onal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Integrated Water Develop a National Water (i) Water storage per (i) Water storage capacity (i) 10 m³ per capita storage Resource Planning Security through water capita (m³ per capita) per capita (artificial dam) by 2025 [3]; and Management [2] conservation practices, [3] is estimated at 6.89m³ in wetlands restoration, 2018 [3]; (ii) 12 m³ per capita storage water storage and efficient by 2030; water use (ii) Renewable water (ii) Rwanda is still a water (iii) 1000 m³ /capita/a of resource availability scarce country with 670 renewable resource ✓ per capita per annum m³ of water per capita per availability by 2030 [3]. (m³ /capita/a) [3] year and 25% of the population still unable to access safe drinking water in 2015 [1,3] Develop water resource (i) Percentage of (i) 30 % of catchments (i) 60% and 100% of models, water quality catchments with water with water balance and catchments with water testing, and improved balance and allocation allocation models in 2019 balance and allocation hydro-related information models models respectively by 2025 systems [2] and 2030 ✓ (ii) Number of (ii) 43 hydrological stations (iii) 100 hydrological hydrological stations in 2019 stations in 2030 Rwanda NDC Implementation: Final Report Page 91 Sector: Water Uncond Conditi itional onal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Develop and implement a Percentage of water 15% of water bodies with 45% of water bodies with management plan for all bodies with ambient ambient water quality by ambient water quality by Level 1 catchments [3] water quality (2017/18) [3] 2025 ✓ Note: It should be noted that the following indicators were discussed during the consultations and mentioned as good indicators. However, the concerned sectors were not ready to do the monitoring and thus should be considered in the NDC timeline 2025 – 2030: • Indicator: Soil erosion and soil loss rate decreased • Baseline: In 2015, soil erosion was 62T/Ha and soil loss at 5.5T/Ha (NISR, 2019b) • Target: Not yet set, policy action not yet in place using NCA indicators Rwanda NDC Implementation: Final Report Page 92 Table 8.2 List of adaptation interventions in the agriculture sector and corresponding indicators Sector: Agriculture Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Climate Resilient Develop climate resilient crops (i) Number of climate (i) In 2019, 40 climate (i) By 2025 and 2030, respectively Value Chain and promote climate resilient resilient crop resilient crop varieties 100 and 200 climate resilient Development [2] livestock [3] varieties developed released, (PSTA4) varieties will be released (based on vision 2050) (ii) Percentage of (ii) In 2019, 11.8% of (ii) By 2025 and 2030, farmers adopting farmers use improved seeds respectively 50% and 90% of ✓ resilient crop/ varieties (NISR, 2019b) farmers will be using improved varieties [3] seeds varieties (iii) % of crossbreed (iii) To be determined (iii) To be determined livestock at national herd species Develop climate resilient (i) Capacity of (i) In 2018, agro processing (i) In 2030, agro processing postharvest and value addition storage constructed facilities were estimated at facilities will increase at a facilities and technologies [3] in MT [1, 3] a capacity of 400,000 MT capacity of 1,200,000 MT [3] ✓ [3] Strengthen crop management (i) Number of (i) 2000 farmers using (i) 9000 farmers using practices (disease prevention, farmers using surveillance tools in 2019 surveillance tools by 2025 and diagnostic, surveillance and surveillance tool 18,000 farmers by 2030 ✓ (FAW Database, BXW control) [3] apps etc.) Rwanda NDC Implementation: Final Report Page 93 Sector: Agriculture Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Develop sustainable land (i) Area of Land (i) In June 2017, an (i) The target is to reach 142,500 management practices (soil under erosion estimated 103,918 ha of Ha of land with radical terraces erosion control, landscape control measures radical terraces and 913,884 and 1,007,624 Ha of progressive management) [3] and used optimally ha of progressive terraces terraces by 2025 [3]; [3] have been implemented [1, ✓ 3] TBD (ii) Biological soil conservation practices of 150,000 ha by 2025 (ii) Percentage of (ii) 52% of the national arable land (to the total surface area in 2019 land area) used as arable land Expand irrigation and improve (i) Number of (i) By 2016, only 48,508 ha (i) 102,284 Ha to be irrigated by water management [3] hectares under (7.5% of land with irrigation 2025 [3]; irrigation within potential) had been ✓ IWRM framework [1, equipped with irrigation (ii) 200,000 Ha to be irrigated by 3] technology [3] 2030 Rwanda NDC Implementation: Final Report Page 94 Sector: Agriculture Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Expand crop and livestock (i) Ha of crops under (i) Crop insured by 2019: (i) 37,462 Ha of crops insured by insurance insurance (by - Maize: 247.61 Ha 2025. Including the following: season) - Rice: 1,588 Ha - Maize: 16,244 Ha - Rice: 10,322 Ha - Banana: 928 Ha - Cassava: 975 Ha ✓ - Beans: 278 Ha - Irish potato: 2785 Ha - Soybeans: 278 Ha Horticulture: - French beans: 975 Ha - Chili: 500 Ha -Tea: 4177 Ha (ii) 102,284 Ha of crops insured by 2030 (the total irrigated area by 2025, i.e. half of the irrigated area targeted by 2030) (ii) Number of cows (ii) Livestock insured by (iii) 585,792 livestock insured by under insurance 2019: 2025. Including the following: - Poultry: To be determined - Poultry: 464,100 - Piggery: To be determined - Piggery: 23,205 - Cows: 3,496 - Cows: 98,487 Rwanda NDC Implementation: Final Report Page 95 Sector: Agriculture Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets (iv) TBD livestock insured by 2030 (Assuming to maintain 585,792 livestock previously insured) Note: For soil erosion control, MINAGRI is proposing to revise the efficiency of existing infrastructures, e.g. Terraces, and to design the best soil erosion control measures through a study that will be conducted in partnership with the MoE. Rwanda NDC Implementation: Final Report Page 96 Table 8.3 List of adaptation interventions in Land and Forestry sectors and corresponding indicators Sector: Land and Forestry Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Sustainable Development of Agroforestry (i) Change in land area (i) In 2019, agroforestry is (i) Agroforestry covering management of and Sustainable Agriculture covered by agroforestry covering 212,214 ha, i.e. 50% and 80% of arable land forestry and (control soil erosion and [1] 25% of arable land respectively by 2025 and Agroforestry [2] improved soil fertility) [2] 2030 ✓ Promote afforestation / (i) Hectares of forest (i) In 2019 it is indicated (i) To have a sustained reforestation of designated restored/ afforested in that 724,666 ha (30.4%) of forest cover of 724,666 ha areas [1] program area and Rwandan dry land was (30.4%) by 2025 and 2030; hectares of protected covered by forest; ✓ forest in project/ program area [3]; (ii) Percentage of forest (ii) 20,000 Ha of new land area area afforested by 2030 (i.e. 10,000 Ha by 2025 and additional 10,000 Ha by 2030) Rwanda NDC Implementation: Final Report Page 97 Sector: Land and Forestry Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Wood Supply Improve Forest Management (i) Number of Ha of (i) 880 Ha of private forest (i) 10,000 Ha of private Chain, Improved for degraded forest resources private forest restored were restored, and forest will be restored, and Efficiency and [1] and whose owners are owners were grouped into owners will be grouped into Added Value [2] grouped into cooperatives by 2019; cooperatives by 2030 (i.e. cooperatives; 5,000 Ha by 2025 and additional 5,000 Ha by ✓ 2030); (ii) Number of Ha of (ii) 36% (22,148.7 Ha) of (ii) 60% and 80% of public forest plantation whose public forest plantations forest plantations allocated management is allocated to private to private operators transferred to the operators by 2019 respectively by 2025 and private operators; 2030 (iii) Change in Forest area degraded/ rehabilitated [1] Rwanda NDC Implementation: Final Report Page 98 Climate-sensitive Integrated approach to (i) NLUDMP that (i) National land use (i) 100% of Land Use Plans Integrated Land planning and monitoring for includes comprehensive development master plan (LUP) harmonized with Use Planning and sustainable land use measures and (NLUDMP) is being NLUDMP by 2025[3]; Spatial Planning management [1] procedures for developed [2] sustainable land use (ii) 100% agriculture and practices; premium land protected by 2025 [3]; (Note: premium (ii) Detailed spatial land includes ecosystems); plans for all districts; (iii) Materialization of (iii) % of compliance of physical boundaries for LUDP to the NLUDMP Kigali, surrounding districts ✓ [3] of Kigali and six secondary cities by 2025; (iv) 100% streamlined coherence between sectors and stakeholders relevant to the use of land by 2025; (v) Spatial/land use planning linked with economic planning by 2030; (vi) To develop and strengthen the Land use monitoring and supervision by 2025; (vii) To develop a land use monitoring index by 2025 Rwanda NDC Implementation: Final Report Page 99 Sector: Land and Forestry Uncond Conditio itional nal Activity name Adaptation intervention Selected indicators (with stakeholders) [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Develop a harmonized and (i) Accurate data on (i) 8 Continuous Operating (i) To have an operational integrated spatial data exposure to climate Reference System (CORs) and integrated National management system for vulnerability on HHs with 50% of coverage Spatial Data Infrastructure sustainable land use and infrastructure in 2017/18) [3]; (NSDI) by 2030 [1]; management [1] high risk areas reported [3] ✓ (ii) Percentage of (ii) low accurate and (ii) To develop updated and operational integrated outdated geospatial data accurate geospatial data geospatial information in place and tools to guide every framework integrated planning in the country by with environmental and 2030 socio-economic statistics Inclusive land administration (i) Percentage of (i) 11,4 million parcels (i) To ensure the security of that regulate and provide registered state land registered/8,8 titles issued tenure and access to land guidance for land tenure optimally used by 2019 for the rational use of land security by 2025; (ii) Up to date land ✓ (Note: Effective land register (ii) To update the land administration that increase registration data/ the security of tenure, access (iii) Model linking land information by 2025 to land and create an use/administration in incentive for landowners to place use their land in a sustainable manner) Rwanda NDC Implementation: Final Report Page 100 Table 8.4 List of adaptation interventions in Human Settlements sector and corresponding indicators Sector: Human Settlements Uncond Conditi itional onal Activity name Adaptation Selected indicators (with stakeholders) intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Land Use and High density (i) Percentage of (1) urban (i) 62.60% of urban population (i) 47 % of urban population Spatial Planning [2] buildings and population living in informal living in informal settlements in living in informal settlements informal settlements, (2) rural population 2016 [3] by 2025 [3] settlement living in clustered settlements upgrading [3] [3] (ii) 67.9% of rural households are (ii) 35% of urban population settled in integrated, planned, living in informal settlements (ii) Average share of the built-up green rural settlements in 2019 by 2030 ✓ area of cities that is open and [3] green space for public use for all (iii) 80% of rural households (SDG) (iii) The CoK is comprised of more settled in integrated, planned, than 30% public space in 2018 [3] green rural settlements by (iii) Access to water and 2025 [3] sanitation services [3] (iv) 87.4% of HH using an improved water source and (iv) To have a sustained (with 86.2% of HH accessing basic qualitative maintenance) of sanitation facilities in 2017 [3] 30% urban green and public space [3] (v) 100% of HH using an improved water source and 100% of HH accessing basic sanitation facilities by 2030 [3] Rwanda NDC Implementation: Final Report Page 101 Sector: Human Settlements Uncond Conditi itional onal Activity name Adaptation Selected indicators (with stakeholders) intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Storm water and Storm water (i) Percentage of urban (i) Less than 20% of urban (i) 90% of urban population in Drainage management [3] population in areas covered by population in areas covered by areas covered by master plans Management [3] master plans with storm water master plans with storm water with storm water ✓ considerations [3] considerations in 2016 [3] considerations by 2025 [3] (ii) Regular maintenance and upgrading of road and drainage infrastructures [2] Note: It should be noted that the following indicators were discussed during the consultations and mentioned as good indicators. However, the concerned sectors were not ready to do the monitoring and thus should be considered in the NDC timeline 2025 – 2030: • Indicator: Kigali City quick flow (runoff) rate reduced • Baseline: In 2015, storm water as quick flow was 1,356M per hectare (NISR, 2019b) • Target: There is not target yet set Rwanda NDC Implementation: Final Report Page 102 Table 8.5 List of adaptation interventions in Health sector and corresponding indicators Sector: Health Uncond Conditi Activity name Adaptation itional onal Selected indicators (with stakeholders) intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Vector-based Strengthen (i) Malaria proportional (i) 5.7 Malaria proportional (i) 3 Malaria proportional disease prevention preventive mortality rate per 1,000 mortality rate in 2016/17 [3] mortality rate by 2025 [3] [1] measures and population [3] create capacity to Note: The following programs ✓ adapt to disease are among the initiatives to be outbreaks [1] carried out in the country: Indoor Residual Spraying (IRS), Long Lasting Insecticidal Nets (LLINs), Presidential Malaria initiative (PMI), etc. Rwanda NDC Implementation: Final Report Page 103 Table 8.6 List of adaptation interventions in Transport sector and corresponding indicators Sector: Transport Uncond Conditi Activity name Adaptation Selected indicators (with stakeholders) itional onal intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Sustainable, Improved (i)Environmental and (i) Draft road design manuals are (i) Guidelines developed by climate-resilient transport engineering guidelines available but without consideration of 2025 on: roads and bridges infrastructure and developed (for climate climate change adaptation - road material stabilization [2] services [1] resilient road infrastructure) - Seals technology - Gravel roads inspection and maintenance ✓ - emergency response to landslide & floods - erosion control - quarry and borrow pits management (i) Reduction of Length of (i) In 2015, the total length of roads (i) To be determined roads vulnerable to flood vulnerable to landslide was estimated and landslides at 979 km (with 165 km for national Note: Accurate and paved roads, 210 km for national additional information will be unpaved roads and 604 km for district supplemented from a project roads) (MIDIMAR, The National Risk on Capacity development for ✓ Atlas of Rwanda,, 2015) Climate Resilient Road Transport Infrastructure currently being conducted across the country with expected end date July 2022 Rwanda NDC Implementation: Final Report Page 104 (i) Length of paved national (i) In 2017, the total length of urban (i) Establishing Scheduled Bus roads road was estimated at 421.4 Km [3] Routes, Construction of Urban Roads and rural roads (ii) Number of km of feeder (ii) In 2017, the total length of feeder rehabilitated, route roads rehabilitated road rehabilitated was estimated at franchising, and ✓ 2060 Km [3] (iii) Number of passengers Operationalization of Smart using the public transport Ticketing System [3] each year [1] Rwanda NDC Implementation: Final Report Page 105 Table 8.7 List of adaptation interventions in Mining sector and corresponding indicators Sector: Mining Uncond Conditi Activity name Adaptation Selected indicators (with stakeholders) itional onal intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Climate Climate (i) Percentage of companies (i) All active mines are complying (i) All (100%) mines comply compatible mining compatible deploying climate compatible with water use efficiency in 2017 water use efficiency by 2025 [1] mining [1] mining [1] [1]; and 2030; (ii) In 2017/18 [3]: (ii) Rehabilitation of abandoned mining sites ✓ (a) Model mines concept has been developed (b) Mining standards developed (c) report for SEA for mining (d) EIA required for each mining license f) Mining law 58/2018 Rwanda NDC Implementation: Final Report Page 106 Table 8.8 List of adaptation interventions in cross-sectors and corresponding indicators Sector: cross-sectors Uncond Conditi Activity name Adaptation Selected indicators (with stakeholders) itional onal intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets DRR program Disaster risk (i) Number of effective city (i) National risk atlas of Rwanda (i) Review contingency plans (Disaster monitoring contingency plans developed developed in 2015 and Disaster and develop districts disaster ✓ preparedness and risk maps management plans [1] emergency (ii) Population covered by response) [1] Disaster risk reduction (DRR) (ii) Detailed National risk and programs [1] vulnerability atlas developed by 2025 [3] Establish an (i) Percentage of occurred (i) 70% occurred extreme weather (i) 95% occurred extreme integrated early extreme weather events for events are warned in lead time by weather events are warned in warning system, which advance warning was 2017 [3] lead time by 2025 and 2030 ✓ and disaster provided at least 30 minutes [3] response plans [1] in advance [3] (ii) Population covered by DRR (ii) In 2015, around 30,000 (ii) Community-based DRR programs [1] households in high risk zone were with developed farming recorded [1] techniques, first aid training, public awareness for disease prevention, and relocation of 10,209 households from high risk zones by 2030 [1,3] Institutional Institutional (i) Number of staff who (i) MoE staff and focal point in (i) Sectors effectively capacity capacity building acquired technical skills to other sectors are available to coordinated to implement development and development effectively coordinate and support coordination across NDC priorities by 2025 and ✓ for cross-sector NDC report on NDC sectors but will need additional 2030 implementation implementation [3] technical skills [3] Rwanda NDC Implementation: Final Report Page 107 Sector: cross-sectors Uncond Conditi Activity name Adaptation Selected indicators (with stakeholders) itional onal intervention [Sources: 1- NDC, 2- SPCR, 3- SSP and others] Indicators Baselines Targets Finance (Resources Access to finance (i) Cumulative volume of (i) 99 USD millions mobilized in (i) 217.78 USD millions to be mobilization) [2] finance [USD millions] 2017/18 [3] mobilized by 2025 [3] mobilized for climate and ✓ environmental purposes [3] Rwanda NDC Implementation: Final Report Page 108 8.3 Categorisation of adaptation indicators Based on the selected adaptation interventions, the consultations with stakeholders and the existing RBME indicators, 42 indicators in total were considered to guide baselines and adaptation targets. In addition, by considering the experiences in reporting at global level (including expectations of adaptation investment funds) and national level (including projects), the indicators were divided into two categories A and B. The category A indicators should be used for reporting on adaptation interventions at global level while category B indicators should be used at national level. In total 9 indicators were selected for category A while 33 indicators belong to category B. Overall, both category indicators are designated to measure progress in the course of developing and implementing adaptation interventions as well as for informing project M&E frameworks seeking funding for implementing those interventions. Table 8.9 below provide the categorisation of selected indicators. Table 8.9 Categorisation of selected adaptation indicators SN INDICATORS CATEGORY Water sector 1 Water storage per capita A Renewable water resource availability per capita per annum (m³ 2 B /capita/a) 3 Percentage of catchments with water balance and allocation models B 4 Number of hydrological stations B 5 Percentage of water bodies with ambient water quality B Agriculture sector 6 Number of climate resilient crop varieties developed B 7 Percentage of farmers adopting resilient crop/ varieties B 8 Percentage of crossbreed livestock at national herd species B 9 Capacity of storage constructed in MT B Number of farmers using surveillance tool (FAW Database, BXW apps 10 B etc.) 11 Area of Land under erosion control measures and used optimally B 12 Percentage of arable land (to the land area) A 13 Number of hectares under irrigation within IWRM framework A 14 Ha of crops under insurance B 15 Number of cows under insurance B Land and Forestry sectors 16 Change in land area covered by agroforestry A Hectares of forest restored/ afforested in program area and hectares of 17 B protected forest in project/ program area 18 Percentage of forest area (to the land area) A Number of Ha of private forest restored and whose owners are grouped 19 B into cooperatives Number of Ha of forest plantation whose management is transferred to 20 B the private operators 21 Change in Forest area degraded/ rehabilitated B National land use development master plan (NLUDMP) that includes 22 comprehensive measures and procedures for sustainable land use B practices Rwanda NDC Implementation: Final Report Page 109 SN INDICATORS CATEGORY 23 Detailed spatial plans for all districts B 24 % of compliance of land use development plans (LUDP) to the NLUDMP B Accurate data on exposure to climate vulnerability on households (HHs) 25 B and infrastructures in high risk areas reported Percentage of operational integrated geospatial information framework 26 B integrated with environmental and socio-economic statistics 27 Percentage of registered state land optimally used B 28 Model linking land use/administration in place B Human Settlements sector Percentage of (1) urban population living in informal settlements, (2) 29 A rural population living in clustered settlements Percentage of urban population in areas covered by master plans with 30 B storm water considerations Average share of the built-up area of cities that is open and green space 31 B for public use for all (SDG) 32 Access to water and sanitation services  B Health Sector 33 Malaria proportional mortality rate per 1,000 population A Transport sector Environmental and engineering guidelines developed (for climate 34 B resilient road infrastructure) 35 Reduction of length of roads vulnerable to flood and landslides B 36 Number of passengers using the public transport each year B Mining sector 37 Percentage of companies deploying climate compatible mining B Cross-sectors 38 Population covered by Disaster risk reduction (DRR) programs B 39 Number of effective city contingency plans developed B Percentage of extreme weather events for which advance warning was 40 A provided at least 30 minutes in advance Number of staff who acquired technical skills to effectively coordinate 41 B and report on NDC implementation Cumulative volume of finance [USD millions] mobilized for climate and 42 A environmental purposes 8.4 Priority adaptation interventions Multi-criteria analysis constitutes a decision analysis tool that can serve as a substitute for a single-criterion approach such as cost-benefit analysis and mostly in environmental and social impacts cases that are not easily amenable to monetary values measurements. MCA, appropriately applied can address a comprehensive range of social, environmental, technical, economic, and financial criteria (UNFCCC, 2004). An MCA methodology was adapted as a proposed decision tool for prioritization of interventions particularly as a useful guide during program and project design. A summary of the Identified intervention areas and indicators for Rwanda’s NDC developed on the basis of the methodology is explained in Table 8.10. The identified adaptations interventions were then assessed for prioritisation by using the below evaluation criteria. The outcome of the process is reported in Table 8.11 to Table 8.13. Rwanda NDC Implementation: Final Report Page 110 Table 8.10 Evaluation criteria for adaptation activities Does the adaptation activity offer the ability to adjust to Contribution towards climate change, to moderate potential damages and/ or to NDC target deal with consequences towards meeting the NDC target through 2030? Are there other environmental impacts arising from Environmental Indirect implementation? May include negative impacts (e.g. effectiveness environmental effects biodiversity and landscape loss) and positive impacts (environmental co-benefits). Are there interactions and alignment with benefits related to Mitigation Co-Benefits the reduction of greenhouse gases (mitigation) and policy aims? Does the adaptation activity moderate potential damages Cost-effectiveness with cost effectiveness? i.e. cost implication Are there possible changes to welfare within affected groups, including changes to prices and distributional EVALUATION CRITERIA Welfare and equity outcomes? May include both negative impacts (e.g. Socio-economic increased costs for low income households) and positive impacts and co- impacts. benefits What are the potential impacts upon business and the wider Competitiveness and economy? May include negative impacts (e.g. increased productivity operating costs and administrative burden) and positive impacts (e.g. increased efficiency, reduced operating costs). Green growth and Ability to deliver additional employment and green growth employment opportunities within the country. Is the adaptation activity in alignment with national policy Alignment with other aims and objectives (e.g. national strategies for economic policy aims development, employment, poverty alleviation and energy provision). Legal and regulatory Are there potential issues with implementation arising from feasibility the legal and/or regulatory framework? Feasibility of implementation Is the adaptation activity suited to attracting funding, including both commercial investment and public sector Suitability to funding lending and/or international and bilateral climate finance and climate finance (e.g. suitability of technology or project type) Are there other key challenges, risks and barriers likely to Other implementation impact the chance of project implementation within a mix of challenges options designed to meet the NDC? Source: Adapted from Carbon Counts Rwanda NDC Implementation: Final Report Page 111 Table 8.11 Evaluation summary for priority adaptation activities in water and agriculture sectors WATER AGRICULTURE EVALUATION CRITERIA l High performance Integrated Water Resource Planning and Management Climate Resilient Value Chain Development l Moderate performance Develop and implement a management plan for Develop climate resilient postharvest and value Water resource models, water quality testing, l Mixed or uncertain performance Develop climate resilient crops and promote conservation practices, wetlands restoration, A National Water Security through water Strengthen crop management practices l Low performance Develop sustainable land management Expand irrigation and improve water Expand crop and livestock insurance addition facilities and technologies and hydro-related information climate resilient livestock all Level 1 catchments management practices Contribution towards NDC target l l l l l l l l l Environmental effectiveness Indirect environmental effects l l l l l l l l l Mitigation Co-Benefits l l l l l l l l l Cost-effectiveness l l l l l l l l l EVALUATION CRITERIA Socio-economic impacts and co- Equity and welfare l l l l l l l l l benefits Competitiveness and productivity l l l l l l l l l Green growth and employment l l l l l l l l l Alignment with other policy aims l l l l l l l l l Feasibility of Legal and regulatory feasibility l l l l l l l l l implementation Suitability to funding and climate finance l l l l l l l l l Other implementation challenges l l l l l l l l l Short-term options - 2020-2025 aaaaaaaaa OUTCOME Medium-term options - 2025-2030 aa aaa aa Not applicable or long-term only >2030 Note: The use of short term and long-term options for one adaptation intervention consider that two different targets were sets in both terms as details in tables 8.1 to 8.8. Example: Develop a National Water Security through water conservation practices has two targets: (i) 10 m³ per capita storage by 2025, and (ii) 12 m³ per capita storage by 2030. Rwanda NDC Implementation: Final Report Page 112 Table 8.12 Evaluation summary for priority adaptation activities in land and forestry and human settlement sectors HUMAN LAND AND FORESTRY EVALUATION CRITERIA SETTLEMENT l High performance Sustainable management of forestry and Wood Supply Climate-sensitive Integrated Land Use Urban Land Storm water l Moderate performance Agroforestry Chain Planning Use l Mixed or uncertain performance Integrated approach to planning and monitoring Inclusive land administration that regulate and High density buildings and informal settlement Development of Agroforestry and Sustainable management system for sustainable land use Improve Forest Management for degraded l Low performance provide guidance for land tenure security Harmonised and integrated spacial data Promote afforestation / reforestation of for sustainable land use mgt Storm water management designated areas forest resources Agriculture upgrading Contribution towards NDC target l l l l l l l l Environmental effectiveness Indirect environmental effects l l l l l l l l Mitigation Co-Benefits l l l l l l l l Cost-effectiveness l l l l l l l l Socio-economic impacts and co- Equity and welfare l l l l l l l l benefits Competitiveness and productivity l l l l l l l l Green growth and employment l l l l l l l l Alignment with other policy aims l l l l l l l l Feasibility of Legal and regulatory feasibility l l l l l l l l implementation Suitability to funding and climate finance l l l l l l l l Other implementation challenges l l l l l l l l Short-term options - 2020-2025 aa a aaaaa Medium-term options - 2025-2030 aa a aa a Not applicable or long-term only >2030 Rwanda NDC Implementation: Final Report Page 113 Table 8.13 Evaluation summary for priority adaptation activities in health, transport, mining and cross-sectoral TRANS HEALTH MINING CROSS-SECTORAL EVALUATION CRITERIA PORT l High performance Vector- Roads based and Climate compatibl DRR program Capacity Resource develop mobilizat l Moderate performance diseases bridges e mining ment ion l Mixed or uncertain performance Improved transport infrastructure and services Capacity building and development for cross- Establish an integrated earlywarning system, Strengthen preventive measures and create l Low performance capacity to adapt to disease outbreaks sector NDC implementation and disaster response plans Climate compatible mining Disaster risk monitoring Access to finance Contribution towards NDC target l l l l l l l Environmental effectiveness Indirect environmental effects l l l l l l l Mitigation Co-Benefits l l l l l l l Cost-effectiveness l l l l l l l Socio-economic impacts and co- Equity and welfare l l l l l l l benefits Competitiveness and productivity l l l l l l l Green growth and employment l l l l l l l Alignment with other policy aims l l l l l l l Feasibility of Legal and regulatory feasibility l l l l l l l implementation Suitability to funding and climate finance l l l l l l l Other implementation challenges l l l l l l l Short-term options - 2020-2025 a a a aaa a Medium-term options - 2025-2030 a aa Not applicable or long-term only >2030 Rwanda NDC Implementation: Final Report Page 114 9 MONITORING, EVALUATION AND REPORTING 9.1 Mitigation 9.1.1 Overview The successful implementation of Rwanda’s NDC requires an effective Measurement, Reporting and Verification (MRV) system, enabling the country to monitor the effectiveness of its mitigation actions and facilitating its access to international climate finance. Internationally, the implementation of an MRV system is the basis for understanding the current GHG emission levels, the ambition of the existing efforts, and the progress made in contributing towards the goals of the Paris Agreement. Monitoring and reporting requirements for Parties to the Paris Agreement are encapsulated within the UNFCCC process by way of new requirements set out in the ‘Paris Rulebook’30 governing implementation of the agreement. Drawing on the Paris Rulebook, Table 9.1 below lists some of the key aspects of an MRV system that will be needed to track progress consistent with NDC implementation. Table 9.1 MRV systems needed to track NDC implementation MRV system Key implementation aspects • Assess current GHG emissions for all Intergovermental Panel on Climate Change (IPCC) reporting sectors and sub-sectors; • Assess Busines-as Usual (BAU) GHGs, where dynamic baselines are considered for GHG emission NDC modeling; and • Assess current progress in reducing GHG emissions towards the overall target (by reductions reviewing the greenhouse gas inventory), and expected future emissions (by reviewing greenhouse gas projections), at national and sectoral levels, to understand the aggregate impact of mitigation actions now and in the future. • Monitor the implementation of the mitigation measures (e.g. implementation of renewable energy generation measures, low carbon transport measures, waste projects); Mitigation • Assess whether the mitigation measures deliver the targeted impact on GHG measures emissions; • Assess whether the mitigation measures deliver the expected low emission development impact (e.g. implementation of solar water heating systems in households); • Track climate finance flows for NDC implementation, including international public Finance of finance, national domestic budgets and private climate finance, to improve the mitigation overall transparency of climate finance flows, and measures • Assess whether the scale/type of financing requirements for NDC implementation are being addressed. 30As contained in Decisions 1 to 20 of the first Conference of the Parties serving as the meeting of the Parties to the Paris Agreement (CMA), held at the Katowice Climate Change Conference in December 2018. Rwanda NDC Implementation: Final Report Page 115 This section outlines the key elements of an MRV framework consistent with these requirements. These actions will allow Rwanda to effectively track progress of mitigation activities identified in the NDC consistent with UNFCCC reporting standards, and carry out ongoing evaluation of whether the country is on course to meet its targets through 2030. It covers the following key elements: • Reporting requirements under UNFCCC and Paris Agreement • Tracking progress towards the NDC • Monitoring international support (climate finance) A framework of indicators is then proposed for monitoring progress towards meeting the NDC and implementing the mitigation actions described in this document. The indicators, which can be used for international reporting as well as for domestic tracking of NDC implementation, are presented for each of the key emitting sectors. 9.1.2 Reporting requirements under UNFCCC and Paris Agreement All Parties to the UNFCCC are required to implement a domestic MRV system that can annually quantify national GHG emissions by sources and removals by sinks, and report the specific actions made to identify and implemented mitigation measures. This information is at present compiled by Rwanda and is submitted to the UNFCCC through two channels: • National Communications (NCs) to be submitted every four years, covering measurements of GHG emissions by sources and removals by sinks compiled in accordance with IPCC reporting guidelines (i.e. a National GHG inventory). These should also include a description of steps made to implement mitigation actions in support of the UNFCCC goal, among other aspects (as required under Decision 17/CP.8 and other decisions on implementation details); and • Biennial Update Reports (BURs) to be submitted every two years. These should include an up-dated GHG inventory report from that of the NC, a measurement of mitigation actions and their impacts, reporting on the domestic MRV system and a description of needs and international support received. All non-Annex I countries should have submitted their first BUR by December 2014 and then every two years thereafter (Decision 2/CP.17; Decision 19/CP.18; Decision 9/CP.21). Rwanda submitted its Third National Communication (TNC) in September 2018, reporting on its national GHG inventory for the year 2015. The country is currently preparing its first BUR and an updated GHG inventory. The Paris Agreement contains several additional MRV requirements which, when taken together with the existing UNFCCC arrangements, provide an enhanced basis for Rwanda’s international reporting requirements relating to the mitigation component of the NDC. New requirements are mainly covered by Article 13, which establishes a new Enhanced Transparency Framework (ETF) through which Parties must regularly account for their NDCs alongside other reporting requirements similar to those contained in NCs, BURs and the International Consultation and Analysis (ICA). Rwanda NDC Implementation: Final Report Page 116 The Paris Rulebook, most of which was agreed in 2018, included Modalities, Procedures and Guidelines (MPGs) for the ETF, covering new MRV requirements for signatory Parties (widely referred to as the “MPGs” under Decision 18/CPA.1 and the Annex thereto). The MPGs require all Parties to submit Biennial Transparency Reports (BTRs) including a National Inventory Report (NIR) by the end of 2024, and every two years thereafter, covering a range of aspects which include, add to and enhance MRV requirements under the UNFCCC, including: • Provision of information by which to track progress in implementing and achieving NDCs; • Provision of information on adaptation (see Section 9.2 below); • Enhanced rules around reporting of annual inventories of GHG emissions and removals; and • Information on financial, technology development and transfer and capacity-building support received and needed in the future. In all cases, the MPGs allow for flexibility in implementing MRV for developing countries, recognising their national capacities. However, all Parties are expected to: • Report information in the BTR on each selected NDC indicator in each reporting year during the NDC implementation period; • Report GHG emissions and removals data for a reporting year no older than three years before the date of submission of the BTR or NIR (i.e., the vintage of reporting data must not exceed 3 years). Therefore, under the Paris Rulebook, Rwanda will be required to regularly and systematically monitor and report information on its mitigation actions in a way that provides clarity and allows regular review of the level of progress being made in achieving the mitigation targets specified in the NDC. Information submitted in the BTR and NIR will be used to assess progress in NDC implementation through a Global Stocktake (GST) of efforts made by the UNFCCC, as specified under Article 14 of the PA.31 9.1.3 Tracking progress towards the NDC In addition to the international reporting requirements outlined above, domestic reporting of Rwanda’s GHG emissions and efforts taken to reduce emissions will be important to building national transparency around the country’s climate response as well as helping to inform good policy-making. Robust NDC monitoring is therefore needed at both the international and domestic levels, to meet the following twin objectives: Objective 1: Monitoring the effectiveness of policies and programs This report identifies a large number of NDC mitigation measures covering a wide range of projects, policies and programs across multiple sectors. A successful monitoring system will enable the GoR to not only monitor the GHG emissions and related emission reductions, but also to monitor whether certain measures deliver the expected impacts in terms of expected policy and socio-economic development outcomes, including co-benefits (e.g. clean energy access, 31 The GST will help determine whether Parties are collectively on track to meet the Paris Agreement’s ultimate goal of limiting mean global temperature increases to within 2oC compared to preindustrial levels or, more ambitiously, 1.5oC. Rwanda NDC Implementation: Final Report Page 117 increased public transport investment). Information on key indicator values to demonstrate progress in implementing those actions can therefore be viewed as useful additional information. Reporting information on mitigation actions aggregated at the sector level is also useful, because the indicators used to monitor the impacts of the NDC mitigation measures can help in understanding the changes in sectoral GHG emissions through 2030. To enable transparent MRV and assessment of progress in implementing each measure, the tracking framework will need to include information on (i) measures being implemented for achieving the mitigation target for the current accounting period at that time; (ii) measures planned for achieving the mitigation target for the next NDC accounting period; and (iii) key indicator values to report the impacts/outcomes of the measures being implemented for the current NDC accounting period at that time. Objective 2: Monitoring of GHG emissions and progress towards NDC target The nature of Rwanda’s target, including the coverage of sectors, will determine the specific information needing to be monitored to track progress of the NDC. At the time of writing, it is understood that the national target will be defined on the basis of achieving a certain percentage (%) reduction in absolute GHG emissions in 2030 with respect to a BAU baseline reference case. The scope of the target is economy-wide, excluding forestry for reasons of data quality. The emissions reduction achieved in each year will therefore be determined by the relative difference between the emissions level achieved through implementation of the NDC mitigation actions in 2030 (actual emissions) and a BAU emissions projection for the same year. This latter projection represents the case under which no actions additional to those already being implemented are taken to reduce GHG emissions. For NDC mitigation targets expressed as reductions of GHG emissions below BAU, reporting information on the description of the mitigation actions, and on the projections of national GHG emissions with mitigation measures, provides sufficient information on tracking progress in implementing an NDC (Desgain and Sharma, 2016). The use of progress indicators, grouped according to key emitting sectors, are therefore a useful element of the MRV framework needed to track the progress of the NDC. The information required is similar to that which Rwanda is currently required to report under UNFCCC.32 Timeline for MRV of NDC Rwanda has submitted an NDC for the period to 2030 and is required to communicate or update its NDC in 2020 (i.e. based on the analysis presented in this report), and then every five years thereafter. Rwanda’s second NDC will therefore need to be submitted in 2025 (for the accounting period 2031-2035). The ‘global stocktake’ of all NDCs will take place three years after the start of each accounting period. So for example, during the period 2021-2025, the global stocktake will take place in 2023. Figure 9.1 below summarises the NDC development and MRV cycle under the Paris Agreement. Within this timeline, Rwanda will need to make an ongoing review of its NDC target and the ability to increase the level of ambition. This will be informed by the collection and preparation 32For example, the requirements for reporting under the BURs include: Name and description of each mitigation action, including information on the nature of the action, coverage, quantitative goals related to the action, if any, and progress indicators; steps taken or planned to implement the mitigation action; progress with implementing the mitigation actions and the results achieved; and information on the domestic MRV system. Rwanda NDC Implementation: Final Report Page 118 of national statistics, as well as tracking the progress of the mitigation actions described in this report. Importantly, with each successive NDC period, existing NDC actions (at that time) will become part of the BAU baseline thereby ensuring ongoing strengthening of ambition. Figure 9.1 Rwanda’s NDC reporting and tracking cycle Source: GFA and Carbon Counts, 2019 Rwanda’s NDC submissions should include information on the most recent BAU scenario projection, with a base year defined as the start year of the NDC accounting period ongoing at that time (i.e. five years prior to year of NDC submission). The BAU scenario should run until the end of the accounting period for which the NDC is being submitted (ibid.) i.e. 2030 for the first NDC; 2035 for the second NDC. The NDC should also include information on the NDC mitigation scenario (as described in this report). For the base year, national GHG emissions will be represented by the estimated national GHG inventory for that year (2015). 9.1.4 Monitoring international support The Paris Rulebook requires Rwanda to report on financial, technical and capacity building needs, as well as indicating the support received to help meet these needs. Some of these elements are also reported in the BUR. Under Annex III of Decision 2/CP.17, the following items should be monitored and reported: • Rwanda’s national contribution to climate finance (million USD); • International financial contribution received by Rwanda (million USD); • Technology development and transfer (activities undertaken); and • Capacity building (activities undertaken) In addition, some other elements must be monitored which are not at present fully covered in the BURs. These include the following: 1. Other voluntary schemes: in accordance with Article 6.2 of the Paris Agreement, the progress of Nationally Appropriate Mitigation Actions (NAMAs) should be monitored, including those prepared to date. Rwanda NDC Implementation: Final Report Page 119 2. Internationally Transferred Mitigation Outcomes (ITMOs): in accordance with Article 6 and of the Paris Agreement, any emission reductions units generated in Rwanda but subsequently transferred to other Parties need to be monitored and recorded. These emission reductions should not be counted towards fulfilment of Rwanda’s NDC, in order to avoid double counting. These elements should therefore also be included in a framework of indicators used to track Rwanda’s NDC implementation, as described below. 9.1.5 Framework of indicators This section sets out an initial high-level framework of progress indicators for use in tracking and report on implementation of the NDC mitigation component, consistent with the MRV requirements of the UNFCCC and Paris Rulebook.33 A series of MRV tables are provided, enabling for monitoring of GHG emissions as well as the effectiveness of mitigation measures within each sector. Indicators are proposed which monitor both the emissions and also non-GHG indicators of progress linked, closely to each of the mitigation actions within each of the key emitting sectors. The choice of indicator has also been informed by existing indicator frameworks applied internationally in the context of climate change, which also support the metrics required under the Paris Rulebook. Simply reporting on emissions and activity data is an overly simplistic approach which cannot always help to assess the effectiveness of a given measure in reaching the NDC. Separate tables of indicators are therefore developed for each of the key sectors covered by the NDC, providing a more detailed framework for tracking progress. Each of the sector tables is structured as following: • Headline indicators: These include a breakdown by sector of emissions reductions against the BAU baseline. They also include other high-level indicators specific to each sector relating to emissions and mitigation activity. • Supporting indicators: The headline indicators are underpinned by a set of more detailed indicators which track progress in implementing the mitigation measures required to achieve sustainable emission reductions. A series of supporting indicators help quantify the progress in implementing the specific actions within each sector. • Other factors: Various factors will act as drivers of emissions over the coming years, many of which are outside Rwanda’s control. No indicators are proposed for these, but they can be tracked as part of a monitoring framework in order to understand, and report on, their influence upon NDC implementation. Monitoring tables are provided for the four main IPCC reporting categories: Energy; IPPU; AFOLU; and waste (note that AFOLU is at present focused only on agriculture). In addition, an aggregated economy-wide overall NDC progress monitoring template is presented. 33It should be noted that developing detailed MRV frameworks for each of the specific mitigation actions identified in this document is also recommended. This would allow for robust and detailed tracking of each measure needed to achieve NDC implementation, and will also be required by project financers/supporters. This falls beyond the scope of the current report. Rwanda NDC Implementation: Final Report Page 120 NDC progress indicators: Aggregated all sectors GHG emissions 2015 2020 2021 2022 2023 Energy IPPU BAU GHG emissions Agriculture (MtCO2e) Waste      TOTAL      Energy      IPPU      Current GHG emissions Agriculture      (MtCO2e) Waste      TOTAL Unconditional Mitigation from NDC measures Conditional       (MtCO2e) TOTAL      Unconditional       Mitigation from NDC measures Conditional       (% change from BAU) TOTAL      Other 2015 2020 2021 2022 2023 GDP (million USD)      Population (millions)      Finance and mechanisms 2015 2020 2021 2022 2023 Domestic climate finance Direct (million USD) Indirect International climate finance Grants (million USD) Other Internationally Transferred Mitigation Outcomes (MtCO2e)  Technology development and transfer     (describe activities undertaken) Capacity building and strengthening      (describe activities undertaken) Other voluntary co-operation (describe activities undertaken) Rwanda NDC Implementation: Final Report Page 121 NDC progress indicators: Energy (electricity generation) Headline indicators 2015 2020 2021 2022 2023 BAU GHG emissions (MtCO2e) Current GHG emissions (MtCO2e) BAU electricity demand (GWh) Current electricity demand (GWh) BAU emissions intensity of grid supply (tCO2e/MWh) Current emissions intensity of grid supply (tCO2e/MWh) Share of renewables in total electricity supply (%) Supporting indicators 2015 2020 2021 2022 2023 Electricity supply 2015 2020 2021 2022 2023 Hydropower Solar/wind Natural gas Generation Peat (GWh and % of total) HFO Imports      TOTAL Mitigation measures 2015 2020 2021 2022 2023 Hydropower Capacity (MW)      # Tier 1 households Off-grid electrification # Tier 2 households Solar minigrids (MWp) # Solar LED streetlights Solar street lighting # Solar traffic lights International finance and support 2015 2020 2021 2022 2023 International contribution to finance mitigation measures (indicate activities and amounts) Technology transfer and capacity building activities (indicate activities) Other factors Development and strengthening of grid infrastructure, including grid losses (indicate key developments) Lake Kivu methane gas utilisation and emissions monitoring programme (indicate key developments) Rural Energy Strategy development (progress towards goals and milestones achieved) Rwanda NDC Implementation: Final Report Page 122 NDC progress indicators: Energy (other) Headline indicators 2015 2020 2021 2022 2023 BAU GHG emissions (MtCO2e) Current GHG emissions (MtCO2e) BAU fossil fuel use (% of total energy use) Current fossil fuel use (% of total energy use) BAU renewable energy use (% of total energy use) Current renewable energy use (% of total energy use) Supporting indicators 2015 2020 2021 2022 2023 Transport 2015 2020 2021 2022 2023 Buses Average fuel economy for newly registered vehicles LDVs (litres per 100 km) HDVs # EV motorcycles Electric vehicles (EV) # EV buses # EV LDVs Other activities 2015 2020 2021 2022 2023 Rooftop solar (MWp) Buildings and household # CFL replacements energy use Efficient stoves (# HH)       # SWH installations # Efficient brick kilns Cement (% non-fossil Mnaufacturing industry and      energy use) agriculture # On-farm biodigesters      Solar irrigation (Ha) International finance and support 2015 2020 2021 2022 2023 International contribution to finance mitigation measures (indicate activities and amounts) Technology transfer and capacity building activities (indicate activities) Other factors E-mobility, modal shift and other public transport progress (indicate key developments) Indicators of activity by mode of transport e.g. occupancy rates; average distances (once studies are available) Ongoing developments and trends within buildings practices and household and SME energy use (describe) Availability and cost of new and low carbon energy technologies and practices Rwanda NDC Implementation: Final Report Page 123 NDC progress indicators: IPPU Headline indicators 2015 2020 2021 2022 2023 BAU GHG emissions (MtCO2e) Current GHG emissions (MtCO2e) Supporting indicators 2015 2020 2021 2022 2023 Cement production 2015 2020 2021 2022 2023 Pozzolana use (t) Clinker substitution Clinker/cement ratio (%) Substitution of F-gases 2015 2020 2021 2022 2023 Imported HFC (kg) Substitution of F-gases with low F-gas use (list the gases GWP refrigerants      and amounts in kg) F-gas substitution (%) International finance and support 2015 2020 2021 2022 2023 International contribution to finance mitigation measures (indicate activities and amounts) Technology transfer and capacity building activities (indicate activities) Other factors Progress with enabling continued and/or greater use of clinker substitute materials in cement production Progress with implementation of MRV system for GHG emissions in industry (indicate developments) Substitution of F-gases and progress towards targets under Kigali amendment to Montreal Protocol Rwanda NDC Implementation: Final Report Page 124 NDC progress indicators: AFOLU (agriculture) Headline indicators 2015 2020 2021 2022 2023 BAU GHG emissions (MtCO2e) Current GHG emissions (MtCO2e) Crop production (total t crop biomass) Livestock production (# population) Supporting indicators 2015 2020 2021 2022 2023 Crops 2015 2020 2021 2022 2023 Compost application (ha) Compost application (t/ha) Nutrient use efficiency Deep fertiliser and biomass use      in rice production (kg/t rice) Terraced land (ha) Crop rotation (ha) Soil and water conservation Banana and coffeee multi-crop      production (ha) Conservation tillage (ha)      Livestock 2015 2020 2021 2022 2023 New fodder species production (ha) Livestock husbandry New fodder use (# cows) and species New species (# cows replaced      with cross-breeds) # new kraals      Manure management Manure yields (t/cow)      International finance and support 2015 2020 2021 2022 2023 International contribution to finance mitigation measures (indicate activities and amounts) Technology transfer and capacity building activities (indicate activities) Other factors Government fertilizer production and distribution policy (decribe progress and outcomes) Agricultural and horticultural production, domestic food demand, and export and market developments Climactic and other key factors influencing yields and agricultural practices Rwanda NDC Implementation: Final Report Page 125 NDC progress indicators: Waste Headline indicators 2015 2020 2021 2022 2023 BAU GHG emissions (MtCO2e) Current GHG emissions (MtCO2e) BAU total waste disposal (t) Current total waste disposal (t) BAU organic waste disposal (t) Current organic waste disposal (t) Supporting indicators 2015 2020 2021 2022 2023 Solid waste 2015 2020 2021 2022 2023 # sites with LFG capture Landfil gas (LFG) utilisation LFG generation (MW) # WtE sites Waste-to-energy (WtE) WtE generation (MW) Amount produced (t)      Aerobic composting Composting rate (% organic waste      composted) Wastewater 2015 2020 2021 2022 2023 # WWTP facilities Wastewater treatment plants (WWTP) # households connected to WWTP International finance and support 2015 2020 2021 2022 2023 International contribution to finance mitigation measures (indicate activities and amounts) Technology transfer and capacity building activities (indicate activities) Other factors Developments in waste infrastructure investment and management measures (indicate activities developed) Development of national and regional waste regulations and enforcement Waste recycling progress (e.g. policies and practices; plastic, metals and paper recycling rates) Rwanda NDC Implementation: Final Report Page 126 9.2 Adaptation The Monitoring and Evaluation and Reporting framework that includes MRV on financing in the case of adaptation aligns with the adaptation options and the relevant analytics agreed to among various stakeholder consultations. Additionally, an approach has been proposed to organize M&E framework in a way that facilitates reporting at selected levels. The levels have identified indicators that are relevant at global and national (see above). The national level reporting will respond to data and information demands at strategic levels including NST and sector strategic plans that inform joint sector reviews and other reporting requirements at the prime minister and MINECOFIN levels and Imihigo reporting for sub- national entities in particular. Importantly, these should ideally be guided by the ENR RBME framework which has oversight over cross cutting areas of environment and climate change in the national planning and budgeting framework. Finally, the selection of indicator driven data will be required for program and projects design, implementation and reporting to funders. This reporting framework demands periodic and timely data collection, analysis and overall management to ensure efficient reporting. Moreover, the clustering will serve as a useful guide to identify targeted resources mobilization from both domestic and external sources. To the extent possible, national and global indicators design features must make a strong case for mobilizing resources and therefore must be smart and results oriented and formulated as outcome and/or impact level indicators. The general guide to the selection of adaptation indicators has considered the following factors as critical: • Differentiate between climate change related issues and business-as-usual development. Climate change has been taken seriously in Rwanda as evidenced by the policy prescriptions including Vision 2050, NST and the GGCRS and the regional and global programs to which Rwanda subscribes including NDC, Africa Agenda 2063 and the SDGs. However, significant gaps have been equally evident in how climate change actions in these programs are prioritised for financing that is essential for implementation. The global climate financing agencies are usually overzealous to draw a wedge where it does not even exist or merited between climate change and development. This is especially the case for climate adaptation where “climate rationale” in the case of GCF seriously hampers the ability to direct resources to address the impacts of climate change. It is crucial that climate financing decisions acknowledge the seamlessness of climate adaptation and development even as climate rationale is reasonably pursued in validating finance flows to address the impacts of climate change. • Local/sector context is crucial to climate vulnerability/resilience assessment. Rwanda has been vigilant in addressing the impacts of climate change starting with the NAPA in 2006 to GGCRS that was approved by Cabinet in 2011. The current efforts are aimed at implementing the PA through the NDCs. Additionally, assessments have been carried out to understand the extent of climate change impacts. Such analyses have included the economics of climate change that measured the economic costs of climate change and made a compelling case for increased financing, the Vulnerability index studies at Rwanda NDC Implementation: Final Report Page 127 various scales; national and sub-national outlining the vulnerability of districts and the design of investment plans including the SPCR and the FIP. The NDC partnership document highlighted the extreme need for inter-ministerial coordination mechanisms. The mechanisms can be used to support coordinated implementation, monitoring and reporting, which can reduce transaction costs and overlapping work, and promote cross- sectoral synergies. The stakeholder engagement that began to robustly involve civil society and private sector presents the potential to use climate action as a driver for sustainable development, in line with countries’ ambitions under the 2030 Agenda. • Consider data availability to measure the impact (to know that change has happened). Rwanda is increasingly making the case for global efforts to support effective climate action through the climate vulnerable countries forum. The stronger case will require continuous improvement of climate analytics that inform national and global reporting for adaptation in particular where harmonized reporting is found wanting. Integration of clear and simplified climate analytics into the ENR RBME will play a significant role in establishing a framework that Rwanda can use to build a reliable and informative database on climate adaptation metrics that systematically guides an ambitious climate action. The technical support provided to the GoR on climate change analysis has proposed to harmonize the various national reporting initiatives and streamline a reporting structure on climate adaptation analytics. The analytical framework takes into account the need and therefore formats for clustering national and global reporting obligations. Below are the high- level indicators for the proposed reporting arrangements highlighting the source documents (References) that provide information on metadata for the selected indicators. The code classification and sources referenced from the RBME for which MoE is the custodian. Table 9.2 High level indicators, data sources (metadata) for the proposed reporting RBME code Indicator Source (Metadata) International and regional good practices (Selected for National communication to UNFCCC) Percentage change in national climate change 07 ECC01 vulnerability index Source: Vulnerability Index study Number and Percentage of districts at high risk of report 01 ECC02 suffering major climate change effect National framework: (i) NST1; (ii) Sector strategic Plans (SSPs) and District Development Plans (DDSs); and (iii) Programs and Projects Percentage of the rural population living in Green 02 ECC04 Source: Green Assessment tool Villages Average level of satisfaction of major Weather 05 MET06 and Climate information institutional users with Source: Weather and Climate METEO RWANDA Weather and Climate information Users Survey information Source: Department of Surveying, Percentage of compliance of land use LAM20 land use plans and Mapping, development plans to the NLUDMP (RLMUA) Rwanda NDC Implementation: Final Report Page 128 RBME code Indicator Source (Metadata) Number and % of a) Mines, and b) Source: Adapted Inspections Process Processors/Exporters, using appropriate GEM23 or Mining Sites and Processors technologies to ensure industry standard Survey/Assessment recovery rates Source: IWRM, Water Monitoring WRM05 Water storage per capital and Development Unit Number (%) of (a) Households, and (b) WRM06 Institutions with a Rain Water Harvesting (RWH) NISR, EICV system installed. Proportion of land surface covered by forest RWFA, Forestry department-GIS FNC10 [Forest cover]. This excludes agro-forestry area. Report {FMES : IND005} Percentage of extreme weather events for which METEO RWANDA, Quarterly high MET11 advance warning was provided at least 30 min in impact weather report advance Total amount of finance mobilized for Green FON07 Investments (by major category – Climate MOUs and MINECOFIN Reports Change mitigation; Green Energy production etc.) Soil erosion and soil loss (To be further - RWFA/IWRM elaborated and confirmed) Ha of crops under insurance (To be further - MINAGRI elaborated and confirmed) It is also important to consider additional indicators outlined below that provide examples of High level National/Global indicators for which alignment will be necessary and on-going dialogue and consensus built as Rwanda (Africa Centre for reporting on SDGs) drives the agenda on harmonizing reporting on climate adaptation/resilience at regional and global levels. • Proportion of the rural population who live within 2 km of an all-season road (SDG indicator 9.1.1); • Percentage of health centres with at least one food and nutrition outreach programme (MINISANTE or MINAGRI); • Annual loss due to damage caused by weather-related hazards / number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population (SDG 13.1.1); • Number of people with access to improved climate-related early warning information or systems for extreme weather events; • Change in climate sensitive agricultural production / Proportion of agriculture land protected against erosion (NDC); • Freshwater withdrawal rate / National Water Security Plan to employ water storage and rain water harvesting, water conservation practices, efficient irrigation established and operational (NDC); • Change of malaria hazards; Rwanda NDC Implementation: Final Report Page 129 • Specialized support, and amount of support, including finance, technology and capacity- building, for mechanisms for raising capacities for effective climate change-related planning and management (SDG 13.B.1). Rwanda NDC Implementation: Final Report Page 130 10 FUNDING REQUIREMENTS 10.1 Overview According to Article 13 of the Paris Agreement and its associated decisions, developed countries reiterated their previous commitment to channel at least USD 100 billion in annual climate finance to developing countries by 2020. They also agreed to establish a more ambitious climate finance target from 2025. Developing countries are requested to report on the support they have received and any additional needs they have in these areas. For adaptation financing, the GCF has committed to allocate at least half of its resources to adaptation, and half of its adaptation resources to LDCs, SIDS and countries in Sub-Saharan Africa. There is also a particular drive by many bilateral donors to scale up their support for adaptation. Rwanda’s Third National Communication to the UNFCCC highlighted three main challenges in climate finance in Rwanda as: (i) insufficient funds, (ii) limited budget for the implementation of climate action, and (iii) limited involvement of private sector investment in environment and climate change activities. Furthermore, the TNC indicated a need for more bilateral and multilateral financial support (GoR, 2018a). Rwanda has undertaken various initiatives to identify climate finance. These have included a series of Public Environmental Expenditure Review (including climate change), costing exercise for the GGCRS in addition to what information can be gleaned from the costing of SSPs. The gaps and needs analysis to the SPCR made efforts at tracking climate finance. This section summarises the funding requirements, estimated in real terms (i.e. 2019 USD), for Rwanda’s NDC measures for mitigation and adaptation described in this report. It shows that the total estimated cost for Rwanda’s identified NDC mitigation measures through 2030 is estimated at around 5.7 billion USD, and over 5.3 billion USD for adaptation priorities, representing a combined funding requirement of around 11 billion USD. The current technical support provided by the World Bank is seeking to establish a baseline for climate finance that can facilitate a framework for reporting requirements. This includes capturing “unconditional and conditional” resources according to the Paris Agreement framework for 2025 and 2030 respectively. The present analysis made use of extensive consultations with sector experts to generate “conditional” and “unconditional” costing estimates for both mitigation and adaptation measures projected through to 2025 and 2030. This will guide and position Rwanda for strategic resources mobilization to meet the climate action ambition, and help inform a process of tracking climate finance flows towards climate mitigation and adaptation action. This is essential for mobilizing resources for climate action that meets Rwanda’s sustainable development ambition. 10.2 Mitigation Figure 10.1 and Table 10.1 below show the funding requirements associated with all identified mitigation options described in Section 4, estimated at 5.7 billion USD through 2030. These represent the Rwanda NDC Implementation: Final Report Page 131 capital investment costs required for new plant, installations and equipment.34 The investment levels for each sector broadly correspond to the estimated mitigation shares across each emitting sector, with agriculture and energy projects accounting for the majority (each accounting for 47% of the total 2020-2030 respectively). Investments in waste facilities account for the bulk of the remaining requirement. In order to achieve the projected mitigation outcomes, around half of the total 5.7 USD billion will be required in the period 2020-2025 and half in the period 2026-2030. Figure 10.1 Investment requirements for all identified measures through 2030 Table 10.1 Investment requirements for all mitigation measures (USD million) Sector 2020-2025 2026-2030 2020-2030 Electricity generation 495 57 552 Industry energy 6 19 26 Transport 506 585 1,091 Buildings 510 150 660 Agriculture energy 306 20 327 Energy - total 1,824 831 2,655 IPPU - total 4 0 4 Fertilizer use and composting 179 540 719 Manure 15 15 30 34 Ongoing operating costs are not included Rwanda NDC Implementation: Final Report Page 132 Livestock 206 231 437 Soil and water conservation 299 1,160 1,459 Agriculture - total 700 1,946 2,645 Solid waste 194 0 194 Wastewater 89 89 178 Waste - total 283 89 372 TOTAL 2,811 2,866 5,677 Figure 10.2 shows the estimated funding requirements, now according to the grouping of “unconditional” (domestically supported) and “conditional” measures through to 2025 and 2030. The levels of funding required within each grouping broadly corresponds with the associated mitigation estimates, with conditional measures representing around 65% of the total investment levels estimated to implement all NDC measures. Figure 10.2 Estimated investment requirements for NDC measures Source: authors A breakdown by sector for each of the contributions is shown below. Within the domestically supported (unconditional) measures, energy sector investments are seen to dominate the period 2020-2025 associated with near term state-funded low carbon energy programmes such as expansion of grid-connected hydropower and solar pumping for irrigation. The majority of agriculture sector investments are realised within the period 2026-2030 with the scaling up and implementation of fertiliser, crop rotation and livestock programmes. For conditional measures, Rwanda NDC Implementation: Final Report Page 133 energy projects also account for most if the investment requirements during the period 2020- 2025, along with waste sector projects, with agriculture projects accounting for most of the estimated investment requirements during the period 2026-2030. Figure 10.3 Estimated investment requirements for NDC measures, by sector Rwanda NDC Implementation: Final Report Page 134 10.3 Adaptation The cost estimates for adaptation interventions was also made for the two phases, i.e. 2020- 2025 and 2025-2030. Estimates were made by referring to different planning documents, among others, the National strategy for transformation (NST 1: 2017-2024), Sector Strategic Plans (SSPs) and the cost of other similar projects. Some interventions will be conditioned by availability of external financial support (conditional) while others may be implemented through internal funding (unconditional) or co-financing (internal and external sources of budget). The total amount of NDC adaptation interventions is estimated at above 5.3 billion USD through 2030. The consultation with sector experts, considering the existing government initiatives, proposed that the breakdown of adaptation total cost should be estimated at 40% unconditional budget (domestic support) and 60% conditional budget (international support). Table 10.2 Estimated costs of adaptation interventions Budget 2020- Budget 2026- Uncond Conditi Activity Intervention 2025 (USD) 2030 (USD) itional onal Develop a National Water Security through water conservation practices, wetlands 100,000,000 64,308,682 ✓ restoration, water storage and efficient water use IWR planning Develop water resource models, and water quality testing, and management 5,000,000 5,000,000 ✓ improved hydro-related information systems Develop and implement a management plan for all Level 1 180,000,000 180,000,000 ✓ catchments Develop climate resilient crops and promote climate resilient 12,029,020 12,029,020 ✓ livestock Develop climate resilient postharvest and value addition 100,000,000 100,000,000 ✓ Climate facilities and technologies Resilient Value Chain Strengthen crop management Development practices (disease prevention, [2] 1,500,000 1,500,000 ✓ diagnostic, surveillance and control) Develop sustainable land management practices (soil 173,086,918 173,086,918 ✓ erosion control; landscape management) Rwanda NDC Implementation: Final Report Page 135 Budget 2020- Budget 2026- Uncond Conditi Activity Intervention 2025 (USD) 2030 (USD) itional onal Expand irrigation and improve 765,219,726 1,496,264,765 ✓ water management Expand crop and livestock 18,279,826 91,399,132 ✓ insurance Development of Agroforestry and Sustainable Agriculture (control Sustainable 46,033,406 46,033,406 ✓ management soil erosion and improved soil of forestry fertility) and Agroforestry Promote afforestation / 8,417,567 8,417,567 ✓ reforestation of designated areas Wood Supply Chain, Improve Forest Management for Improved 4,067,245 4,067,245 ✓ degraded forest resources Efficiency and Added Value Integrated approach to planning and monitoring for sustainable 30,000,000 30,000,000 ✓ land management Climate- sensitive Develop a harmonized and Integrated integrated spatial data Land Use 10,000,000 10,000,000 ✓ management system for Planning and sustainable land use management Spatial Planning Inclusive land administration that regulate and provide guidance for 2,500,000 2,500,000 ✓ land tenure security Land Use and High density buildings and Spatial 200,000,000 200,000,000 ✓ informal settlement upgrading Planning Storm water and Drainage Storm water management 200,000,000 200,000,000 ✓ Management Vector-based Strengthen preventive measures disease and create capacity to adapt to 85,000,000 100,000,000 ✓ prevention disease outbreaks Rwanda NDC Implementation: Final Report Page 136 Budget 2020- Budget 2026- Uncond Conditi Activity Intervention 2025 (USD) 2030 (USD) itional onal Sustainable, climate- Improved transport infrastructure 300,000,000 300,000,000 ✓ ✓ resilient roads and services and bridges Climate compatible Climate compatible mining 29,645,336 29,645,336 ✓ mining DRR program Establish an integrated early (Disaster warning system, and disaster 5,000,000 5,000,000 ✓ preparedness response plans and emergency response) Disaster risk monitoring 10,000,000 10,000,000 ✓ Institutional Institutional capacity building and capacity development for cross-sector 3,000,000 3,000,000 ✓ development NDC implementation Finance (Resources Access to finance 1,500,000 1,500,000 ✓ mobilization) TOTAL (USD) 2,290,279,044 3,073,752,071 ✓ ✓ OVERALL 5,364,031,115 COST (USD) 60% 10.4 Capacity building and technology transfer Under the Paris Agreement, developed countries have committed to provide financial support, technology transfer and capacity building to developing countries. Many developing countries will require enhanced capacities to effectively track inflows of bilateral and multilateral resources and support and identify pending gaps and needs. It is critical that the Paris Agreement’s capacity building provisions are implemented successfully (Khan, 2017). The stakeholder consultations undertaken in the course of this technical assistance has brought to the fore clear messages on the urgent need to design strategic ways to build and further develop capacity of sector experts in monitoring and evaluation in general and in particular on climate adaptation. There is evidence of a protracted period within which implementation of programs has created demand for reliable metrics. Such demand has clearly been manifest in the series of poverty reduction strategies including the most recent EDPRS 2 and currently the NST. These key strategies have demonstrated lack of climate adaptation data despite the impacts of climate change such as floods on infrastructure and soil erosion on agricultural Rwanda NDC Implementation: Final Report Page 137 productivity. It is important that this WB technical assistance makes a strong case for capacity development particularly in improving analytics around climate change adaptation/resilience. In the face of advanced IT, there are ample opportunities to bundle M&E systems with IT enabled processes and tools to improve systems and therefore efficiencies for monitoring and reporting. Rwanda’s case of smart phone enabled data management in the health sector and the increasing use of drone technology for data collection are key pointers on how domestication of capacities and technology transfer can fast-track development of reliable M&E systems on climate adaptation. ENR RBME that has been initiated at MoE presents a rare opportunity for the WB technical assistance to build on in streamlining and further developing the analytics on climate adaption and resilience as is evident in the table 6.1 above that has captured the climate adaptation relevant indicators consolidated in the RBME scheme from a wide range of sector documents. However, for this to be useful, a number of deliberate capacity building initiatives will be undertaken at various levels. The following are specific areas to consider for capacity building: • Institutional development and strengthening; • Developing human resources through education, training, and research; • Strong financial support for capacity building targeting Rwanda’s compliance in reporting; • National ownership of capacity building efforts that is aimed to ensure sustainability; • Networking, partnerships, and sharing of experiences across sectors and beyond; • Application of Web-based tools to improve capacity building. There is significant scope to build capacity in cross sector M&E systems including upstream work that is vital to setting up functional M&E systems and frameworks. Investing in M&E systems is crucial to manage progress in implementing climate adaptation. M&E and lesson learning are critical to effective and efficient delivery of project results and sustainable impacts to secure investor confidence that is essential to meet resources mobilization ambition and consequently the national ambition of climate resilient economy by 2050. Identifying capacity building (incl. technical/technology/ resources mobilization) will greatly benefit from: • Improving the use of existing data and analytical tools bearing in mind that Local/sector context is crucial to climate vulnerability/resilience assessment; • Differentiating between climate change related issues and business-as-usual development; • Putting in place measures to facilitate data availability to measure the impact (to know that change has happened). The consultations have created momentum for ongoing engagement. It is important to recognize that technical knowledge resides with sector specialists and any capacity building and effective application of technology for mainstreaming climate change must draw from that experience and facilitate cross learning among climate change experts and subject matter experts from sectors. It is imperative that this harmony/coherence continually capitalized on to guide successful mainstreaming of climate change into sector priorities. Rwanda NDC Implementation: Final Report Page 138 11 CONCLUSIONS AND RECOMMENDATIONS 11.1 Mitigation The analysis of mitigation options described in this report show how significant economy-wide emissions reductions can be achieved in Rwanda as part of its NDC efforts. For the target year 2030, the base case scenario is estimated to achieve a reduction against BAU of 16% for domestically supported “unconditional” measures increasing to 38% with “conditional” measures included. The sensitivity analysis shows the level of uncertainty involved in estimating mitigation outcomes and the critical role of assumptions around economic growth, success in project implementation and recognition of Lake Kivu methane power as a mitigation option. For domestic measures only, the results show a range of 12-18% reduction against BAU in 2030, increasing to 27-58% for all NDC measures. Guided by the principle that Rwanda should only adopt targets considered capable of being delivered, the choice of which mitigation target(s) to adopt within the revised NDC should necessarily be informed by a view on which scenario is considered most feasible. In this context, it should be noted that the base case scenario is based on official target assumptions for GDP growth and also project outcomes. Overestimating the former has the tendency to underestimate mitigation outcomes relative to BAU, while overestimating the latter has the tendency to overestimate mitigation outcomes relative to BAU. From this, it might be reasonably concluded that the base case represents a feasible estimation of what could be delivered under the NDC through 2030, subject to an enabling domestic policy framework and attracting international funding and support. As shown in the analysis, the estimated funding requirements associated with achieving the identified measures are significant - totaling around 5.7 billion USD through 2030. Accessing climate finance to help drive investment into projects and enabling programs to support mitigation goals across energy, waste, industry and agriculture will be critical. This needs to be accompanied by a roadmap of actions, policies and programs aimed at embedding mitigation priorities within national and regional policy planning. At the same time, a robust framework to monitor, track and review the implementation of NDC actions will be needed to ensure effective delivery and meet reporting requirements under the UNFCCC and Paris Agreement. In this context, the following recommendations are made for implementation of the mitigation component of Rwanda’s NDC: • Decision on choice of NDC targets to adopt, based on the technical and economic analysis of mitigation options and estimated reductions from conditional and unconditional components against BAU through 2030. • Develop an MRV framework for tracking the progress of project implementation and Rwanda’s pathway towards achieving the NDC, whilst meeting its international obligations under the Paris Agreement. Such a framework will include developing a set of performance indicators and supporting metrics for monitoring and reporting the progress towards meeting the NDC for the identified prioritized sectors/mitigation actions within each sector and approach to tracking climate finance. Rwanda NDC Implementation: Final Report Page 139 • Elaborate a detailed financing strategy through the revised NDC implementation plan that considers prioritized mitigation measures and guidance on accessing climate finance. This should include overarching strategies and interventions required to address financial challenges and leverage funds from private and international sources, with identification of appropriate sources of funding and support needs matched to the identified actions. • Request guidance from IPCC regarding GHG accounting from lake methane utilization whilst developing project and emissions data from Lake Kivu power project. • Establish a detailed implementation plan with a timeline and roadmap of actions through 2025 and 2030, with roles and steps identified within each sector (electricity generation, road transport, industry, waste, agriculture) describing how mitigation projects and programs will be embedded within national and regional planning. 11.2 Adaptation Within adaptation, significant work undertaken by sectors has elaborated metrics for indicators, baselines, milestones and the associated metadata. However, the information and data has been highly fluid with significant changes over the years. This has had adverse impact on adaptation relevant analytics and sector priorities. The ability to measure and monitor has also presented its own challenges as has been evident in tracking progress on implementation of GGCRS which has been fraught with lack of consistency and coherency. The current exercise seeks to streamline the measurement and monitoring protocols aimed at consolidation and organizing data and information that can facilitate trend analysis that improves monitoring and evaluation of adaptation strategies, programs and projects. The above can only be possible through Sector Wide Approach (SWAp) engagement using the national process of Joint Sector Reviews (JSR) scheduled semi-annually across sectors. While these seem to serve as clear avenues to manage adaptation information/data, they are not designed to facilitate detailed analysis. Thus, there is a need to identify sector specific focal groups that can engage in meaningful and focused discussions that are critical to manage the levels of complexity that adaptation metrics and data analysis demands. For this to succeed, clear incentives that include but are not limited to technical training (in-country as well as external) present realistic opportunities for acquisition and application of new knowledge. Despite growing acknowledgement that climate change impacts have adversely affected food security through soil erosion, loss of property and in the extreme lives of affected populations, infrastructure and energy generation and supply resulting from flooding and sedimentation of water bodies, there is limited link and application of sector specific data to climate adaptation targets. The development paradigm has increasingly dominated data and information management even where it is clearly evident that climate impacts are responsible for the risks. It is essential to approach this work with a level of confidence that climate adaptation and resilience undergird sustainable development. Therefore, this work should lay the foundation for measurement and monitoring of risks with a view to manage the identified risks and foster progress through selection of priority adaptation options that improve the likelihood of catalysing and accelerating resources flow for successful implementation. Rwanda NDC Implementation: Final Report Page 140 The following points provide a summary of the key recommendations that must be considered in order for the adaptation interventions to result into climate action in various sectors to the benefit of national economy: • Consideration of the selected adaptation indicators for program and projects design, implementation and reporting to funders. Climate action requires performance measures to monitor and report progress for purposes of accountability. It is therefore important that sectors continually improve the relevancy of monitoring and evaluation framework. • Provide national level adaptation reporting that align and respond to data and information demands at strategic levels including NST and sector strategic plans. National policies and strategies must rely on responsive data to guide policy reforms essential to effective integration of climate adaptation to achieve national sustainable development goals. • Develop a strategy to evaluate investments in adaptation projects and programs based on reliable analytics to increase likelihood of replication and scale up of proven interventions. • Design strategic ways to provide capacity building to sectors, including sector experts, to facilitate planning and continuous NDC monitoring in general and in particular on climate adaptation. • Elaborate a detailed financing strategy through the revised NDC implementation plan that considers the prioritized adaptation interventions and provide guidance for the accelerating national access to scalable climate finance. FONERWA has been institutionalized to support a coherent national climate resources mobilization strategy. 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Rwanda NDC Implementation: Final Report Page 148 Annex A – Mitigation project assessments Rwanda NDC Implementation: Final Report Page A-1 A-1 MITIGATION PROJECT ASSESSMENTS A-1.1 Methodological approach A-1.1.1 Mitigation potential Emissions reductions arising from mitigation projects can be calculated according to various methodologies. The approach taken with most of the projects was similar to that used in the Clean Development Mechanism (CDM) approved methodologies, according to which annual emission reductions (ER) are calculated on the basis of describing and then quantifying scenarios for baseline emissions (BE) and project emissions (PE) for each year of the mitigation project(s). Thus, mitigation achieved in each year, n, was derived for each mitigation measure as follows: Emission reductions (ER)n = Baseline emissions (BE)n – Project emissions (PE)n Where: Baseline emissions (BE) represent the emissions arising from energy use in the project, activity or sector in the absence of the NDC mitigation action, to deliver a defined outcome or product (e.g. one GWh of grid electricity; unit of industrial output; irrigation pumping power output). These were informed by, and were ensured to be consistent with, the BAU scenario developed for each sector. Project emissions (PE) represent the emissions arising from implementation of the NDC action whilst maintaining the equivalent outcome or product as per the baseline emissions scenario. These can include additional sources of emissions arising from project implementation including, where feasible, so-called ‘leakage’ emissions in order to allow for a fair calculation of net emissions reductions35 (e.g. increases in use of electricity or direct energy). These parameters could be readily defined for most mitigation actions, according to which the counter-factual baseline scenario and baseline emissions (BE) could be easily defined and appropriate assumptions made in order to calculation project emissions (PE) and emissions reductions (ER). These include for example off-grid projects displacing diesel or grid electricity with an equivalent renewable energy (and therefore zero-carbon) supply. It should be noted that the analysis of energy sector projects allows projects to be modelled together as a suite of actions within the energy system as a whole. For example, with increasing supply of hydropower with the energy mix on the grid (under mitigation scenarios), energy efficiency actions resulting in reduced demand for grid power achieve relatively less mitigation, than when compared to a static BAU baseline dominated by fossil-based power. Assessing the mitigation and economic potential of the projects undertaken as a consistent suite of options within the same energy system is essential to developing a credible mitigation scenario and ensuring that emissions reductions are not double counted. 35Note that because of the complexities involved and the lack of equivalent analysis in the baseline scenario, life-cycle type assessments were not made Rwanda NDC Implementation: Final Report Page A-2 A-1.1.2 Cost-benefit analysis Economic cost-benefit analysis (CBA) was undertaken for each of the identified mitigation options, in order to assess not only the direct costs for each option (e.g. investment and operating costs) but also the wider socio-economic benefits arising from their implementation. Most mitigation options give rise to a range of costs and benefits, the scope of which is typically determined by whether an economic or financial analysis is being undertaken. The CBA presented in this section was undertaken from a socio-economic perspective, thereby aiming to reflect economy-wide costs and benefits for each of the options, as opposed to a financial analysis which typically involves appraises projects from a private company’s or individual’s perspective. The inclusion of wider benefits to the economy such as job creation effects and additional revenue streams to rural communities thus allows for an appraisal of the relative economic performance from mitigation options which is more suited to policymaking and the provision of international support. Cash-flow analysis of annual costs and benefits was undertaken for each of the identified mitigation options in order to calculate a net project value (NPV). This value represents the difference between discounted benefits and discounted costs as they occur over time. The economic NPV of each project was therefore calculated as: − (, ) = ∑ (1 + ) =0 Where: n = number of periods t = time period; B = benefits; C = costs; and i = discount rate For purposes of transparency and simplicity, a common public lending discount rate of 6% was applied to all projects based on guidance for economic appraisal of World Bank projects (World Bank, 2016).36 Economic time periods were chosen according to each specific project type, with large infrastructure projects or policy programme requiring several implementation stages typically requiring longer appraisal periods (e.g. 20 years) that for simpler and/or smaller projects (e.g. 10 years). An important limitation to the calculation of NPV and its use in CBA is its high sensitivity to the discount rate. The NPV is a summation of multiple discounted cash flows—both positive and negative—converted into present value terms for the same point in time. As such, the discount rate used in the denominators of each present value (PV) calculation is critical in determining the final NPV value. A small increase or decrease in the discount rate can have a significant effect on the final output. 36In practice, certain investments will require finance from private sector organisations and individuals which can be better reflected by higher discount rate; other large infrastructure projects may warrant discount rates of as low as 2- 3%. Rwanda NDC Implementation: Final Report Page A-3 An extensive range of project data and assumptions were used in undertaking the economic analysis. Information on costs and benefits, and supporting project details and technical information, were requested from relevant government department and stakeholders. Wherever possible this was used in the analysis, although significant information gaps and the need to ensure consistent values for common assumptions meant that in-country data was complimented by a range of assumptions and inputs drawn from the international literature and analogous/regional project case studies and schemes. Key assumptions and data sources used in the cost-benefit analyses are provided in the detailed project descriptions provided further below. A-1.1.3 Marginal abatement cost curves The estimated emissions reductions (tCO2) and economic costs (NPV) for each identified measure were complied into a series of sectoral marginal abatement cost curves (MACC). These present the list of NDC mitigation options sorted in ascending order of cost. As such they can be useful — as part of a broader evaluation process — in prioritising options. They do however have important limitations meaning that their use in informing policy-making and investment choices should be approached with care. Limitations of MACCs identified in the literature include the following:37 1. Do not capture non-market barriers to implementation, including indirect or non- transaction costs. 2. Contain very limited treatment of uncertainties in the underlying analysis and assumptions (e.g. technology economics, learning rates, choice of discount rates, time of retirement for working capital goods). 3. Do not address dimensions other than direct costs, including strategic, operational, or political factors. These may include both ancillary benefits (air and water pollution) or market failures. In general, the MAC curve is unable to capture the wider social implications related to climate change mitigation. 4. Have difficulty capturing interactions between different measures that may limit the total abatement potential. Abatement measures interact, creating synergies and conflicts that mean that the cumulative outcome of two measures may be more than the sum of its parts, or less. Point (4) is particularly important to the current analysis because mitigation options can often interact and overlap according to their specific mix within a scenario, in particular when seeking to simulate an energy system. This is particularly the case in which supply- and demand-side mitigation measures co-exist: the emissions reductions estimated for a demand-side measure reducing demand for grid electricity must reflect the carbon-intensity of the grid associated with the inclusion of supply-side mitigation projects and not the BAU baseline grid. Otherwise, total emissions reductions shown on the curve would be overestimated. This has been addressed within the current analysis as follows. Because the mitigation options were not modelled top-down according to e.g. cost optimization or computable general 37A review of relevant literature with full references is available from: http://planwashington.org/blog/archive/understanding-carbon-reduction-marginal-abatement-cost-curves/ Rwanda NDC Implementation: Final Report Page A-4 equilibrium (CGE) type modelling, abatement from supply-side options were calculated before the calculation of mitigation from the (relatively few) relevant demand-side options. For these reasons, CBA and abatement costs were recalculated for each NDC mitigation scenario in order to ensure a mutually consistent suite of options developed as a scenario avoiding overestimation of mitigation potential. A-1.2 Energy Figure A-1 presents the cost-ordered MACC for all identified measures within energy use for the year 2030. The corresponding data are shown in Table A-1. Figure A-1 Marginal abatement cost curve for identified measures in 2030, Energy Source: Authors Rwanda NDC Implementation: Final Report Page A-5 Table A-1 Mitigation measures ordered according to abatement costs, Energy Abatement cost Mitigation 2030 Mitigation option Sub-Sector (USD/tCO2e) (MtCO2e) Rooftop solar PV Buildings -266.15 0.029 Solar water heaters Buildings -252.59 0.041 EE agro-processing Manufacturing industry -207.93 0.001 Efficient lighting in buildings Buildings -184.30 0.016 Solar street lighting Electricity and heat -181.96 0.008 Solar mini grids Electricity and heat -161.83 0.146 Efficient cook stoves Buildings -138.80 0.195 Off-grid solar electrification Buildings -130.91 0.010 Efficient brick kilns Manufacturing industry -118.97 0.001 Solar pumping for irrigation Agriculture -88.80 0.150 Vehicle emissions standards Transport -84.55 0.154 Electric motorcycles Transport -46.88 0.136 EE cement production Manufacturing industry -46.21 0.019 Hydropower Electricity and heat -41.96 0.482 On-farm biogas Agriculture -28.98 0.117 Electric buses Transport -21.72 0.003 Climate compatible mining Manufacturing industry -7.98 0.007 Public transport measures Transport 158.63 0.008 Electric cars Transport 331.09 0.001 Total mitigation potential in 2030 1.53 Source: Authors Table A-2 below provides a summary of the key assumptions and data sources used in the cost- benefit analyses. The subsequent tables describe the assessment of each of the mitigation measures in more detail. Rwanda NDC Implementation: Final Report Page A-6 Table A-2 Key assumptions and data sources used in cost benefit analyses, Energy Parameter Value Source Notes Energy prices Diesel 1.17 USD/litre RURA, 2019 Final consumer price Gasoline 1.17 USD/litre RURA, 2019 Final consumer price Average cost of thermal power Electricity 0.14 USD/kWh REG, 2018 generation, sourced from REG 38 Employment 3,744 USD per employee per Estimate based on Based on average gross salary reported Skilled labour cost in National Electrification plan (NEP). year MININFRA, 2016 Multiplier for indirect job creation; Employment IFC, 2013; average value assumed within range 3.0 multiplier World Bank, 2012 and other published employment studies. Electricity generation According to plant schedule Comprises plant costs, transmission Hydro costs from 2020 onwards. Total costs REG, 2019 costs and opex. 1.45 billion USD. Based on job creation impact study of 5 FTE/MW (construction) Direct employment ODI, 2013 the Bugoye large-scale hydropower 2 FTE/MW (operation) project, Uganda. 68 MW of solar mini-grids to be Based on installed in off-grid rural areas MININFRA, 2018 Off-grid by 2030 (Tier 1); HH targeted for and the data Contained in Final ESSP electrification targets off-grid electrification through provided by SHS (Tier 2): 1.5 m, equivalent to MININFRA 250,000 connections per year Off-grid energy Tier 1: 29 kWh/a MININFRA, 2018 Contained in Final ESSP demand Tier 2: 10 kWh/a Capex: 164 million USD (for 68 Solar minigrids  MWp), of which 48 million USD MININFRA, 2016 National Electrirication Plan (NEP) for battery banks. Tier 1: 1,250 USD/HH Off-grid capex MININFRA, 2018 Midpoints of ranges provided in ESSP Tier 2: 125 USD/HH USD per unit: Solar traffic lights: 5,000 Based on estimates provided as part of Street lighting capex World Bank, 2018 LED tower lights: 1,495 Zimbabwe NDC technical analysis Solar LED lights: 1,908 Manufacturing Industry Boiler economiser capex: 7,300 USD Agroprocessing Values reported from press for Avoided cost of fuelwood: Reported in Rwanda (tea and coffee implementation of boiler economiser 12,307 USD/Factory/a press industry) at Kitabi tea factory Savings in boiler economiser operation: 4,800 USD/Factory/a 38 This estimate excludes T&D costs, taxes, marketing and other costs Rwanda NDC Implementation: Final Report Page A-7 Based on analysis of motor Capex and opex for replacement programme in Chilean electric motor Fawkes et al (2016); Various mining sector: applied to Rwanda replacements in GoR, 2017a mining sector based on estimated mining sector energy use. Cost of modern kiln: 6,111 USD Reported in Rwanda Modern brick kilns Avoided cost of fuelwood: 15 - press USD/tonne Road transport Capital cost of conventional ICE Shanghai Public transport: bus: 11,000 USD Analysis based on incremental cost of Automobile Co modern buses Capital cost of modern diesel increasing modern bus fleets Limited, 2019 bus: 40,000 USD Additional technology (vehicle) costs Incremental costs above associated with an improvement of estimated as $US 54 fuel economy in all new vehicle (motocycles), $US 361 ICCT, 2014 imports (based on GFEI targets) are (passenger cars), $US 2,958 estimated based on an economic study (buses) and $US 2,632-5,394 Vehicle fuel of mandatary Euro V standard for ICE (HGV, according to class). economy standards vehicle classes and regulation Set-up and policy study costs: $US 5 million; annual Author estimates, administation and based on previous - inspection/enforcement costs: work $US 3 million. Capex conventional ICE LDV: 18,000 USD Capex equivalent EV LDV: 23,000 USD (based on VW Golf gasoline and VW eGolf electric Ofgem, 2018. model costs). Additional capital costs include Capex conventional bus: incremental cost between an EV and 500,000 USD equivalent ICE vehicle purchase, and Capex equivalent E-bus: 750,000 the charging infrastructure needed to USD. provide for reliable charging. Capex conventional ICE Data provided motorcycle: 2,741 USD directly by Electric vehicles Capex equivalent EV motocycle: Ampersand 2,960 USD company. Per vehicle capital cost of $US It is assumed that wide-spread rapid 2,500 applied, based on a unit charging (as opposed to cost of USD 37,500 for a 50kW Energy Saving Trust, overnight/slow; or fast) will be rapid charger supplying fleet of 2017. required for commercial scale EV 15 vehicles for EVs and 7,500 uptake. applied. Average vehicle power demand Based on Global Fuel Economy values 2020-2030 (kWh/100 km) GFEI, 2019 Inititiave (GFEI) analysis. based on GFEI assumptions. Energy use in agriculture Assumption made on basis of marginal capex requirements to conventional Solar irrigation diesel pump system. Average total 2,000 USD/kWp Hoque et al, 2016 system capex capex for solar pumpinng assumed to be 3,000 USD/kWp based on Hoque et al, 2016. Rwanda NDC Implementation: Final Report Page A-8 Operating cost of PV system is negligible (no batteries). Cost of Solar irrigation Project team 1% of capex maintenance for pump and distribution system O&M costs assumption is assumed to be similar to diesel- powered system. Government and/or donor support programme relating to awareness, Solar irrigation public Project team tranidng and finance. Cost estimate support programme USD 80 million Estimate based on existing schemes e.g. cost Practical Action Green Livelihoods Programme in Gwanda. Based on authors’ knowledge of Solar irrigation Project team 5% of capex existing solar irrigation pumping labour cost assumption projects in E. Africa and S.E. Asia. Bsed on the study conducted by SNV Biodigestor capex: 1,260 USD SNV, 2008 on financing domestic biogas in per unit Rwanda Twice as amount of original Govt. support programme: USD programme for 7400 units. Amount for 10 million capacity building and awareness. Excludes subsidies. On-farm anaerobic digestion of manure O&M cost: 19 USD/unit/year for biogas SNV/HIVOS, 2012 Avoided cost of firewood: 168 USD/HH/year Fertilizer replacement cost: 280 Based on detailed domestic biogas USD/HH/year programme feasibility study. Bio-slurry utilization: 100 USD/HH/year Direct job creation: 700 Buildings 1.6 million CFL bulbs at 2 UD per bulb CFL bulb capex USD 3.2 million GoR, 2018c (ESSP target) CFL demand Estimated electricity demand reduction 54,000 MWh/year GoR, 2018c reduction potential (ESSP) According to cook stove dissamination program Efficient cook stoves MINIFRA, 2018 Estimated based on ESSP cost analysis published in ESSP, total cost is 184 million USD. Of which USD 12 million for battery Based on World Capex: USD 28 million banks; assumes 7 years useful battery Rooftop solar Bank, 2018 life. systems Annual opex: 1% of capex Assumption - Solar water heating Assumes 200 l/day SWH system cost 1,300 USD per unit EWSA, 2014 capex published in EWSA (2014) Solar water heating Assumption based on the previous Govt. support USD 8 million EWSA, 2014 residential solar water heating programme program published in EWSA, 2014 Rwanda NDC Implementation: Final Report Page A-9 ENERGY (electricity) Mitigation measure Grid connected hydropower Development of 56.75 MW large hydro capacity (capacity > 5 MW), 24.5 Short description MW small and mini hydro projects (capacity <5MW) and 75 MW regional projects by 2030. Overview Scope of project Low carbon energy supply Gradual construction of both large and small-scale hydro based on the REG Timing of project plans as published in the Least Cost Power Development plan (LCPDP) Displacement of GHG from diesel power generation and new build fossil- Mitigation effect based electricity generation. GHG mitigation Estimated mitigation in 0.475 2030 (MtCO2e/yr) Total project mitigation 4.193 (MtCO2e) Costs estimated include planning, construction and operation as detailed in Description of costs ESSP and LCPDP. Total capital costs estimated at 328 million USD; O&M costs estimated at 3.6 USD/MWh (fixed) and 0.85 USD/MWh (variable). Avoided costs of diesel and fuel oil for power generation (approx. 55 million USD/year over period). Other benefits include job creation (estimated at Description of benefits approx. 45 million USD/year during construction; 18 million USD/year during operation). Cost-benefit analysis Economic assessment 20 years period Discount rate 6% NPV of project (Million 175.96 USD) Economic cost analysis based on implementation costs published in the Notes on economic analysis ESSP and LCPDP. Abatement cost -41.96 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-10 ENERGY (electricity) Mitigation measure Solar minigrids With a potential of 4.5 kWh per m2 per day and approximately 5 peak sun hours, solar energy has large potential in Rwanda. The country has already engaged private sector participation into solar solutions as a lighting substitute for remote areas. Currently, 258,414 households have benefited access to electricity with the solar energy through IPPs nationally. Households located far from the planned national grid coverage are Overview Short description encouraged to use mini-grid solar photovoltaics (PVs) to reduce the cost of access to electricity. The Rural Electrification Strategy approved by the cabinet in June 2016 outlines strategies through which Rwanda’s households could increase access. 68 MW of solar mini-grids are planned to be installed in off-grid rural areas by 2030. Mini grids will be developed by the private sector with Government playing a key role in identifying sites and establishing a financial incentive framework. Scope of project Rural electrification Construction of micro-grids between 2020 and 2024. Operation to last until Timing of project 2050. Mitigation effect Displacement of emissions generated by Jabana power plant (HFO) GHG mitigation Estimated mitigation in 0.146 2030 (MtCO2e/yr) Total project mitigation 1.611 (MtCO2e) Total programme costs estimated at around 206 million USD (194 million Description of costs USD capital costs including battery bank replacements after 7 years; 12 million USD O&M costs). Avoided costs of fossil fuel power generation and transmission Description of benefits infrastructure; employee earnings from solar jobs and indirect jobs. Total economic benefits estimated at up to 54 million USD per year. Cost-benefit analysis Economic assessment 15 years period Discount rate 6% NPV of project (Million 260.72 USD) Economic assessment does not include transaction costs and administrative Notes on economic analysis costs to government from establishing financial incentive framework and other enabling measures. Abatement cost -163.83 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-11 ENERGY (electricity) Mitigation measure Solar LED streetlights The analysis assumes that approximately 10,000 solar powered LED streetlights will be installed to replace existing High-Pressure Sodium lights. Overview Short description While traffic lights are not separately addressed in the analysis their costs and benefits are included under streetlights. Scope of project Energy efficiency measures Timing of project Beginning in 2019. Ending in 2044 (although may continue). Mitigation effect Energy efficiency (reduced grid power). GHG mitigation Estimated mitigation in 0.008 2030 (MtCO2e/yr) Total project mitigation 0.100 (MtCO2e) Capital cost of LED streetlights, batteries and installation estimated at Description of costs around 20 million USD over period; O&M costs (battery replacement) estimated at 8 million USD over period. Avoided cost of grid electricity and conventional light bulb purchase and Description of benefits replacement estimated at around 5-6 million USD/year. Cost-benefit analysis Economic assessment 15-year period. While documentation gives no clear indication, we assume period the project will last for 25 years (for consistency with other projects). Discount rate 6% NPV of project (Million 18.23 USD) The cost analysis was based on the implementation cost sourced from the Notes on economic analysis ESSP. Abatement cost -181.96 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-12 ENERGY (road transport) Mitigation measure Vehicle fuel economy standards This project aims at setting vehicle emission standards for new imported Short description road vehicles and enforcement regulations, and integrated national Overview transportation planning. Scope of project Efficient resilient transport system Timing of project Phased in from 2022 Improved technology and standards for conventional ICE vehicles in road Mitigation effect transport, resulting in avoided fossil fuel emissions GHG mitigation Estimated mitigation in 0.154 2030 (MtCO2e/yr) Total project mitigation 0.696 (MtCO2e) Incremental technology costs for efficient vehicle models within each Description of costs class/type and policy set-up and ongoing administration costs estimated to total around 190 million across period. Avoided costs of imported petro-diesel and gasoline (from increased fuel Description of benefits efficiency) estimated at 285 million across period. Analysis does not quantify potential health benefits i.e. from reduced local pollution. Cost-benefit analysis Economic assessment 10 years period Discount rate 6% NPV of project (Million 58.83 USD) Notes on economic analysis N/A Abatement cost -84.55 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-13 ENERGY (road transport) Mitigation measure Electric vehicles (buses and passenger cars) Introduction of electric vehicles from around 2020 onwards, reaching up to 0.2% of new vehicle sales by 2023/24 and 8% by 2029/30 for EV cars; and 1% by 2023/24 and 20% by 2029/30 for EV Buses. Requires support to Short description overcome additional capex associated with vehicles and charging points. Overview This project is consistent with the e-mobility initiative, a program that is being developed by the GoR. Scope of project Efficient resilient transport system Timing of project From 2020 onwards Displacement of conventional ICE vehicles in road transport, resulting in Mitigation effect avoided fossil fuel emissions GHG mitigation Estimated mitigation in 0.001 For E-V cars and 0.003 for E-buses 2030 (MtCO2e/yr) Total project mitigation 0.004 for E-V cars and 0.014 for E-buses (MtCO2e) Additional capex for EV vehicles, rapid charger infrastructure and electricity Description of costs costs estimated at 8 USD million for buses and 6 USD million for passenger cars trough period to 2030. Avoided costs of imported diesel and gasoline estimated at 8.8 million for Description of benefits buses and 4 million for passenger cars through period. Cost-benefit analysis Economic assessment 15 years period Discount rate 6% NPV of project (Million -1.22 for E-V cars and 0.29 buses USD) Notes on economic analysis N/A Abatement cost 331.09 for EV cars and -21.72 buses (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-14 ENERGY (road transport) Project title Electric motorcycles This project is part of the ambitious e-mobility program being developed by the GoR. It aims at a phased adoption of electric Short description Overview motorcycles from 2020 with the following targets: 2.3% by 2023/24 and 33% by 2029/30. Scope of project Efficient resilient transport system Timing of project From 2020 onwards Displacement of conventional ICE vehicles in road transport, Mitigation effect GHG mitigation resulting in avoided fossil fuel emissions Estimated mitigation 0.136 in 2030 (MtCO2e/yr) Total project 2.034 mitigation (MtCO2e) Capital and charging costs estimated based on the prices provided by the local companies that are running pilot projects; Description of costs based on the ambitions reaching up to 38,000 new e-vehicles by 2030, total costs through period are estimated to total over 980 USD million. Description of Avoided costs of imported fuels estimated at over 1.1 USD Cost-benefit analysis benefits billion through period. Health benefits not quantified. Economic assessment 10 period Discount rate 6% NPV of project 95.36 (Million USD) Notes on economic N/A analysis Abatement cost -46.88 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-15 ENERGY (road transport) Mitigation measure Public transportation measures (buses) This project aims at bus promotion as part of public transport development, replacement of minibuses by modern buses and promotion of mass rapid transportation. Additional measures such as improving road networks easing urban congestion have not been assessed within the scope Overview Short description of the analysis due to lack of data and resources. However, depending on the development of sufficient baseline assumptions, these could deliver significant additional benefits in terms of transport efficiency, and associated fuel and GHG savings. Scope of project Efficient resilient transport system Timing of project From 2020 onwards Displacement of conventional ICE vehicles in road transport from increased Mitigation effect public bus use, resulting in avoided fossil fuel emissions GHG mitigation Estimated mitigation in 0.008 2030 (MtCO2e/yr) Total project mitigation 0.054 (MtCO2e) Capital costs estimated based on the cost of new efficient buses and Description of costs minibuses; estimated at around 25 million USD for annual purchase of up to 200 new vehicles by 2030. Avoided costs of imported diesel estimated at over 15 million USD through Description of benefits period. Does not quantify potential health benefits from reduced local pollution (considered to be minor). Cost-benefit analysis Economic assessment 15 years period Discount rate 6% NPV of project (Million -8.59 USD) Notes on economic analysis N/A Abatement cost 158.63 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-16 ENERGY (buildings) Mitigation measure Rooftop solar in commercial buildings (grid back-up) Most of commercial building and institutional buildings in remote areas of Rwanda use diesel generators the main source of electricity. Diesel Short description generators are also used for grid back-up. The project aims at installing Overview cumulative 10 MWp in three years and is aligned with the Rwanda rural electrification strategy. Scope of project Energy efficiency Project assumed to begin in 2019 with a few pilots and completed within 3 Timing of project years. Mitigation effect Displacement of diesel used in back-up generators GHG mitigation Estimated mitigation in 0.029 2030 (MtCO2e/yr) Total project mitigation 0.279 (MtCO2e) Capital costs estimated to total around 40 UDS million through 2030 Description of costs including battery costs. O&M costs estimated at 3 million through 2030. Displacement of diesel generation costs, grid electricity and creation of new Description of benefits solar jobs estimated to total almost 120 USD million across project assessment period. Cost-benefit analysis Economic assessment 10 period Discount rate 6% NPV of project (Million 47.02 USD) The project is expected to boost employment opportunities, estimated to Notes on economic analysis activate or create new jobs in SMEs for 3,790 men and 4,166 women (due to availability of power during outages). Abatement cost -168.76 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-17 ENERGY (buildings) Mitigation measure Energy efficient lighting Supported by Government subsidy, REG distributed 800,000 CFLs in place of incandescent light bulbs between 2007 and 2014. To further support this initiative, an exemption of VAT on energy saving lamps was introduced in 2013. Benefits of this included a reduction in annual energy demand of 54 Short description GWh and USD 11 million in savings for consumers. Considering the Overview environmental and economic benefits of this previous initiative, a project aiming to further promote the use of efficient light bulbs (LED lamps) was proposed. This is also in line with the Rwanda Green building minimum compliance system. Energy efficiency measures under Rwanda Green building minimum Scope of project compliance system. Timing of project Beginning in 2020. Ending in 2030 (although it may continue). Mitigation effect Energy efficiency. GHG mitigation Estimated mitigation in 0.016 2030 (MtCO2e/yr) Total project mitigation 0.181 (MtCO2e) Total cost of scheme estimated at around 6.4 million USD based on Description of costs assumed replacement of 1.6 million CFL bulbs through 2030 with CFL unit costs of 2 USD and average lifetime of 7 years. Energy efficiency savings (purchased grid electricity) estimated at around Description of benefits 38 million USD through 2030; avoided cost of standard bulbs estimated at almost 12 million USD through 2030. Cost-benefit analysis Economic assessment 15 years period Discount rate 6% NPV of project (Million 33.27 USD) Notes on economic analysis N/A Abatement cost -184.30 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-18 ENERGY (buildings) Mitigation measure Efficient cook stoves The type of stove has a significant impact on the amount of fuel required and health of households. Most households (66%) use three-stone cookstoves (a simple cookstove, made by placing a pot on three stones, which are positioned around a fire) or traditional cooking stoves. These normally use firewood. The average household uses around 1.8 tonnes of firewood each year with this type of cookstove. The average monthly consumption per household on firewood is RWF 1,930 (USD 2.27). A Government programme to support the use of improved cooking technologies has been running since the 1980s with Overview Short description 30% household penetration. Private sector led efforts are also distributing cook stoves that are up to three times more efficient than the traditional 3- stone stove and can reduce biomass consumption by anywhere between 68- 94%. This will free up the time spent by women and children in collecting firewood. The project aims to halve the number of households using traditional cooking technologies to achieve a sustainable balance between supply and demand of biomass through promotion of biomass efficient technologies. The project aligns with the ESSP targets. Scope of project Energy efficiency Timing of project 2019-2030 Mitigation effect Avoided charcoal and firewood consumption GHG mitigation Estimated mitigation in 0.195 2030 (MtCO2e/yr) Total project mitigation 1.896 (MtCO2e) Costs include new stoves, training and monitoring on kiln use (certification), Description of costs estimated to cost up to 380 million USD through 2030. Description of benefits Avoided costs of charcoal and firewood, and additional job creation. Cost-benefit analysis Economic assessment 10 years period Discount rate 6% NPV of project (Million 263.17 USD) Notes on economic The economic impact will be achieved progressively with the expansion of analysis improved cookstoves use. Abatement cost -138.79 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-19 ENERGY (buildings) Mitigation measure Solar water heaters in the residential sector A major ongoing initiative is the SolaRwanda Solar Water Heater Program, which promotes the use of solar water heaters, with the aim of reducing the use of electricity from the grid for water heating. The program was initiated in 2009 with the support of development partners and was formally launched in March 2012 with a pilot phase of 100 SWHs. Loans Overview Short description and grants are used to subsidise the cost of purchasing a SWH. Implementation commenced in April 2013 and a total of 2,256 SWHs have been installed. This project focussed on the implementation of the Rwanda Green building compliance system. It aims at encouraging the commercial building to install solar water heaters instead of using electricity. Scope of project The project is part of Rwanda Green building minimum compliance system Timing of project 2021-2030 and beyond Mitigation effect Displacement of electricity consumption GHG mitigation Estimated mitigation in 0.041 2030 (MtCO2e/yr) Total project mitigation 0.24 (MtCO2e) Capital costs include equipment and costs of a implementing a government support programme. Capital costs estimated to total 52 USD million through 203 based on installing 4,000 SWH units per year at unit cost of Description of costs 1,300 USD. Government support programme cost estimated at 8 million USD. Equipment O&M. estimated to total around 28 million USD through 2030 Avoided costs of electricity, plus job creation benefits estimated to total around 180 million USD (156 USD million electricity costs; 24 USD million Cost-benefit analysis Description of benefits job creation benefits) through 2030. Economic assessment 10 period Discount rate 6% NPV of project (Million 60.03 USD) Notes on economic analysis N/A Abatement cost -252.59 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-20 ENERGY (buildings) Mitigation measure Off-grid solar electrification (SHS and mini-grids) Considering the challenges associated with the grid-connected electricity, the government of Rwanda considers the access to off-grid electricity as the primary mean through which the electricity access could be expanded Short description through the country. In recent years, the off-grid electricity has been one of Overview the key achievements of the electricity sector with a growth from 0% to 11%. According to the government plans, the latter access will be increased via solar home systems and solar mini grid. Scope of project Rural electrification Timing of project Universal access to be achieved by 2025. Displacement of kerosene used for lighting in rural households, and to a Mitigation effect lesser extent, diesel/petrol used in small gensets. GHG mitigation Estimated mitigation in 0.010 2030 (MtCO2e/yr) Total project mitigation 0.075 (MtCO2e) According to REG estimates, a total capital costs of include the solar PV mini-grids and SHS, per REMA estimates. Total amounts to $200 million. Main operating cost is the cost of replacement of solar batteries. While the Description of costs SHS/mini-grid market is expected to be private sector led, a public support programme to offer training, financing, etc. has been factored in in the cost. Avoided consumption of more basic forms of energy (kerosene, candles, Description of benefits batteries, phone charging services, etc.) and grid electricity, plus job Cost-benefit analysis creation benefits estimated to total around 1 billion through 2030. Economic assessment 15 years period Discount rate 6% NPV of project (Million 9.76 USD) Other benefits of solar technologies vs other sources (pollution, health, fuel Notes on economic analysis independence, better quality of light, etc.) were not quantified. Abatement cost -130.91 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-21 ENERGY (manufacturing industry) Mitigation measure Energy efficient brick kilns The project aims at replacing the existing traditional kilns by energy efficient brick kilns to reduce the fuel consumption the construction sector. Short description Overview Project is aligned with the GoR policy to reduce the biomass consumption in industries and promote cleaner production. Scope of project Energy efficiency. Timing of project The project is assumed to start in 2020 through 2030 and beyond. Mitigation effect Energy efficiency. GHG mitigation Estimated mitigation in 0.143 2030 (MtCO2e/yr) Total project mitigation 0.916 (MtCO2e) Total capital cost requirement for replacement energy efficient brick kilns Description of costs estimated at around 13 million USD through 2030. Avoiding purchase of fuelwood estimated to total over 20 million USD. Description of benefits Additional health benefits from reduced pollution not quantified. Economic assessment 10 years. Cost-benefit analysis period Discount rate 6% NPV of project (Million 42.35 USD) Health benefits were not estimated. Analysis does not include figures on Notes on economic analysis the costs of establishing the programme and developing a database to monitor the programme. Abatement cost -46.21 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-22 ENERGY (manufacturing industry) Mitigation measure Energy efficiency in agro-processing industries Implementation of energy efficiency equipment and management systems Overview Short description within tea (e.g. tea driers) and coffee. Scope of project Energy efficiency improvement in tea driers Timing of project Ongoing Mitigation effect Energy efficiency. GHG mitigation Estimated mitigation in < 0.001 2030 (MtCO2e/yr) Total project mitigation 0.007 (MtCO2e) Capital cost grants for improvement equipment estimated at around 2 Description of costs million through 2030. Ongoing costs of management and operation of programme not estimated. Avoided purchase of fuelwood and electricity estimated to total around 4.3 Description of benefits million through 2030. Cost-benefit analysis Economic assessment 15 years. period Discount rate 6% NPV of project (Million 1.39 USD) Economic analysis does not include figures on the costs of establishing the Notes on economic analysis programme and developing a database to monitor the programme, for which data estimates are unavailable. Abatement cost -207.93 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-23 ENERGY (manufacturing industry) Mitigation measure Energy efficient cement industry The project aims at replacing fossil fuel use by wood wastes (rice husks and sawdust) within the cement industry. The project is aligned with the GoR Short description Overview policy to reduce the biomass consumption in industries and promote cleaner production. Scope of project Replacement of residual fuel oils by wood wastes. Timing of project The project is assumed to start in 2020. Mitigation effect Energy efficiency. GHG mitigation Estimated mitigation in 0.1426 2030 (MtCO2e/yr) Total project mitigation 0.916 (MtCO2e) Capital and operating costs estimated to total 10.8 million USD through Description of costs 2030. Avoiding purchase of fossil fuels estimated to be up to 80 million USD Description of benefits through 2030. Potential health benefit impacts were not estimated. Cost-benefit analysis Economic assessment 10 years period Discount rate 6% NPV of project (Million 42.35 USD) Analysis does not include figures on the costs of establishing the Notes on economic analysis programme and developing a database to monitor the programme. Abatement cost -46.21 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-24 ENERGY (manufacturing industry) Mitigation measure Electric motor replacement in mining The project aims at phasing out the fossil fuel use in the mining industries and to replace it by onsite-generated electricity and/or grid connected Short description electricity. Reduction in diesel consumption will reduce associated GHG Overview emissions and other related air pollutants. The project is aligned with the energy efficiency in industries and the cleaner production program. Replacement of existing fossil fuel motors with electric motors in mining Scope of project companies. Timing of project From 2020 onwards. Mitigation effect Energy efficiency. GHG mitigation Estimated mitigation in 0.011 2030 (MtCO2e/yr) Total project mitigation 0.056 (MtCO2e) Includes capital costs (via grants for replacement of motors) and O&M Description of costs costs (management and operation of programme). Description of benefits Avoiding purchase of diesel fuel. Economic assessment Cost-benefit analysis 10 years period Discount rate 6% NPV of project (Million 0.31 USD) Assessment does not include costs of establishing the programme and Notes on economic analysis developing a database to monitor the programme. Abatement cost -5.53 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-25 ENERGY (agriculture) Mitigation measure Domestic on-farm biogas The project, which is aligned with ESSP targets, will aim at enforcing the promotion and use of biogas. Biogas utilisation is proposed as potential alternative to biomass. The 2007 National Domestic Biogas programme supported the use of biogas, targeting 9,500 rural households with at least two cows. Since 2007, around 3,700 digesters, based on standard Short description construction design using local materials, have been disseminated. The Overview government provided a 50% subsidy and the remaining provided through local credit institutions. However, recent site visits suggest that use of biogas digesters is limited, with users citing unreliability and insufficient fuel. At the institutional level, there have been 68 installations, with 11 out of 14 prisons reached and the remaining 3 under development. 29,000 on-farm small-scale biodigesters (capacity 4-20 m³ ) to replace Scope of project (mainly) fuelwood used for cooking; roll-out of government support programme (awareness, training, subsidies) Timing of project Ongoing Mitigation effect Avoided emissions from manure. Avoided deforestation. GHG mitigation Estimated mitigation in 0.117 2030 (MtCO2e/yr) Total project mitigation 0.869 (MtCO2e) Capital and annual costs estimated based on SNV feasibility studies. Total capex estimated at 37 million USD through 2030 based on reaching Description of costs cumulative installation of 29,000 biodigesters (at unit cost of 1260 USD); O&M costs estimated at 4 million USD; government support programme 10 million USD. Quantified: Avoided cost of fuelwood, replacement cost of fertiliser, revenue from utilisation of bio-slurry estimated to total almost 120 million Cost-benefit analysis Description of benefits USD through 2030. Not quantified: job creation, reduced workload for rural households, health benefits. Economic assessment 10 years period Discount rate 6% NPV of project (Million 33.20 USD) Notes on economic analysis N/A Abatement cost -38.22 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-26 ENERGY (agriculture) Mitigation measure Solar pumping for irrigation According to NST1, the national area under irrigation will increase from 48,508 ha (2017) to 102,284 ha in 2024, driven by increasing crop production and exports of tea, horticulture and other products to meet Short description growing international demand. Priority will be given to the scale up of marshland and small-scale technologies for irrigation, considered most cost-effective. This project aims at an irrigation area of 84,505 Ha by 2030. Overview Investment in small-scale solar irrigation as opposed to diesel pumps for 84,505 Ha. Public-support programme to create awareness, help farmers finance investment (through credit and/or subsidies) and train technicians). Scope of project Rwanda Agriculture Board (RAB) implements and Coordinates SSIT countrywide where a subsidy of 50% is given to farmers and funds are earmarked to selected districts while MINAGRI and RAB mobilize farmers to adopt climate resilient methods which include irrigation equipment. Implementation/investment over 5 years between 2020 and 2024 Timing of project (assumption based on NST1). Displacement of diesel consumption in small-scale irrigation schemes, Mitigation effect targeting 84,505 Ha. GHG mitigation Estimated mitigation in 0.150 2030 (MtCO2e/yr) Total project mitigation 1.202 (MtCO2e) Capital costs include the solar irrigation system equipment (PV modules, mounting structure, pump controller, pump, distribution and water storage) and its installation, compared to the cost of a diesel irrigation Description of costs system of equivalent performance. Estimated to total around 380 million USD through 2030, including 5-year public-support programme and ongoing O&M costs. Cost-benefit analysis Avoided costs of imported diesel fuel (and its transportation to farms), plus Description of benefits job creation benefits estimated to total 625 million USD through 2030. Economic assessment 10 years period Discount rate 6% NPV of project (Million 106.77 USD) The economic analysis assumes solar pumps are used throughout the year Notes on economic analysis (as opposed to seasonal use). Abatement cost -88.80 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-27 A-1.3 IPPU and waste Figure A-2 presents the cost-ordered MACC for all identified measures within the IPPU and waste sectors for the year 2030. The corresponding data are shown in Table A-3. Figure A-2 Marginal abatement cost curve for identified measures in 2030, IPPU and Waste Source: Authors Rwanda NDC Implementation: Final Report Page A-28 Table A-3 Mitigation measures ordered according to abatement costs, IPPU and Waste Abatement cost Mitigation 2030 Mitigation option Sub-Sector (USD/tCO2e) (MtCO2e) Increased pozzolanas in cement IPPU; Mineral industries -74.71 0.104 Waste-water treatment Waste; Wastewater -60.93 0.022 Waste-to-energy Waste; Solid waste -51.46 0.220 Landfill gas utilisation Waste; Solid waste -9.52 0.356 Aerobic composting Waste; Solid waste 1.68 0.060 F-gases substitution IPPU; F-gases 7.49 0.029 Total mitigation potential in 2030 0.79 Table A-4 below provides a summary of the key assumptions and data sources used in the cost- benefit analyses. The subsequent tables describe the assessment of each of the mitigation measures in more detail. Table A-4 Key assumptions and data sources used in cost benefit analyses, IPPU and Waste Parameter Value Source Notes Industrial Processes and Product Use (IPPU) Reduced clinker from current 70% ratio Considered feasible increase in clinker to cement: 5% pozzalana use 2020-2030, and Clinker reduction market acceptance of non-structural from increased CCl, 2019 concrete products, through use of pozzalanas Reduced clinker use due to increased discussions with industry use of non-structural concrete: 20% stakeholders Pozzalana costs based on weighted Clinker production: USD 75/tonne Cement average of estimated costs from clinker CCL, 2019 production costs Rubavu (7,000 FWR/t) and Rusizi Pozzalana material cost: USD 6/tonne (4,000 FWR/t) pozzalana sources. F-gas reduction assumptions: Substitution of Proposed government reduction 2020-2024: 30% GoR, 2018a F-gases targets, as included in TNC 2024: 2030: 65% HFCs costs at the local market in Imported HFC-134a: 9 USD/kg HFC costs REMA, 2016 Rwanda during the November 2016 Imported R290: 54 USD/kg survey Waste Calculated, Based on TNC calculations of LFG Landfill gas Estimated energy available from 2020 based on GoR, availability applying IPCC 2006 utilisation to 2030: 38.5 TJ 2018a methodology (IPCC, 2006) Rwanda NDC Implementation: Final Report Page A-29 Capital costs: LFG collection and control system: 1 USD million AFD, 2013; Cost assumptions based on similar Internal combustion engine power USEPA, 2008 project undertaken in Addis Ababa plant: 1 USD million Direct use project: 3 USD million financed by AFD in 2013, and pre- Sanitary landfill: 22 USD million Feasibility Study for LFG Recovery and Utilization at Los Cocos Landfill O&M costs: site, Colombia. Power plant: 0.3 USDm/year USEPA, 2008 Gas collection system: 0.1 USDm/year Landfill operaiton: 0.5 USDm/year Calculated based on the baseline GHG emission per unit waste in SWDS: Based on GoR, year 2015 for the quantity of waste 0.38 tCO2e/tonne SWDS waste 2018a going to SWDS and their corresponding emissions Waste-to-Energy Karlsson L & Total capital costs: 161 USD million Based on pre-feasibility study of a Jönsson T.L., O&M costs: 8 USD million/year Waste to Energy plant in Moldova. 2012 Employment creation: 500 jobs Assumption - Estimated based on the project Base year composting rate: 20% implimentation requirering capacity Annual increase potential: 5% Assumption building at household level and at 2030 composting rate: 33% large scale Production cost, small scale Windrow Based on cost provided by RAB and Aerobic biological composting: 20 USD/tonne Assumption estimate of transport costs, and the treatment Capacity building needs and program discussion on capacity building needs (composting) implementation: 5 USD million Based on waste composting CDM Compost produced (% of waste AENOR, 2008 project 2008/018/CDM/005.1 in handled): 22% Uganda Based on 20,000 FRW average cost Price of compost: 22 USD/tonne RAB, 2019 value provided by RAB Based on feasibility studies of Kigali Urban population connected to the EIB, 2016a; WWTP, Kibagabaga and Kinyinya WWTP by 2022: 11.1% REMA, 2017 Catchments Total estimated capital cost of WWTP Based on EIB, Includes total estimated investment system: 89 USD million 2016b ; author costs, 10% contingency and Annual O&M costs: 0.8 USD million estimates government support programme Waste-water treatment and Benefit assumptions: reuse Sewage tariff: 0.9 USD/m³ Calculation of benefits based on EIB Health benefits: 19 USD/person/year local survey data, national census Household pit latrine emptying savings: Based on EIB, and the WHO estimates for the 11 USD/HH/year 2016a; EIB, average economic benefit of Annualised replacement costs of HH 2016b, GoR, improved sanitation. Health benefits septic tanks: 11 USD/HH/year 2018b. include those from introducing piped Estimated maximum treated sewerage: sanitation to a household which has 12,000 m³ per day piped water but non-piped sanitation Average population per HH: 4 Rwanda NDC Implementation: Final Report Page A-30 INDUSTRIAL PROCESSES AND PRODUCT USE (IPPU) Mitigation measure Clinker substitution: Increased use of pozzolanas in cement Clinker substitution recognise the need to lower the carbon in cement production industry. A rational 5% substitution of clinker with pozzolanas from the current 70% (cement-to-clinker ratio) has started to be Short description Overview implemented. The CCL plant envisage to produce the cement of 50% clinker ratio for non-structural application. It is assumed that 20% of the total cement production is used for non-structural concrete use. Production of cement by substitution of clinker with pozzolanas alternative Scope of project to reduce the GHG emission while at the same time reducing the cost of cement production. Timing of project 2020-2030 Mitigation effect Reduces CO2 emissions from the calcination reaction of clinker. GHG mitigation Estimated mitigation in 0.104 2030 (MtCO2e/yr) Total project mitigation 1.183 (MtCO2e) Capital costs estimated at 1.2 million USD; pozzolana material costs Description of costs estimated to total around 7 million USD through 2030 based on 6 USD/tonne assumption. Use of local materials which results in new job opportunities, GHG reduction in clinker process emissions. In addition, energy related emissions (coal; electricity) will be reduced from the reduction of fossil fuel Description of benefits combustion in clinker production. Thus, the increase of pozzolanas in Cost-benefit analysis cement while reducing the clinker-to-cement ratio means lower emissions and lower energy use. Economic benefits from clinker reduction is estimated at 95 million USD through 2030. NPV of project (Million 88.41 USD) Economic gains are significant from both technical and sustainability Notes on economic perspectives, as well as from an aesthetic point of view. Pozzolana clinker analysis substitute typically costs less than clinker-based cement. Abatement cost -74.71 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-31 INDUSTRIAL PROCESSES AND PRODUCT USE (IPPU) Mitigation measure Gradual substitution of F-gases by less polluting substitutes The category 2F emissions will be reduced to comply with the Kigali amendment of the Montreal Protocol on substances that deplete the ozone layer (UN, 2016). 2F gases are mainly imported for refrigeration, stationary Short description air conditioning and mobile air conditioning. By using climate-friendly Overview alternatives to HFCs, emissions are projected to be reduced by 30% in 2020 to 65% in 2030 relative to BAU. Gradual replacement of the ODS alternatives that were surveyed in Rwanda on the list of controlled substances as per Annex F of the Montreal Protocol, Scope of project such as HFC-134a, HFC-125, HFC-143a and HFC-32 (UN, 2016). The study assumes the substitution of existing F-gases with hydrocarbon refrigerants such as R290. Timing of project 2020-2030 Reduction of F-gases, with higher GWP, from refrigeration and servicing Mitigation effect sector. GHG mitigation Estimated mitigation in 0.029 2030 (MtCO2e/yr) Total project mitigation 0.303 (MtCO2e) Additional costs associated with importing climate-friendly alternatives to Description of costs HFCs (R290) estimated to have capital costs of 3.2 million USD and material costs of around 20 million USD through 2030. HFCs are greenhouse gases with high global warming potential (GWP). The solution is to shift to low GWP substitutes. The lower the GWP, the more Description of benefits Cost-benefit analysis climate-friendly the substance. Reduced cost of imported HFC R-134a gases estimated at around 17 million USD through 2030. NPV of project (Million -2.27 USD) Notes on economic N/A analysis Abatement cost 7.49 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-32 WASTE Mitigation measure Landfill Gas Utilisation Generation of electricity power from landfill gas (LFG) collection and their burning applied to sanitary landfills. The project also will improve solid waste collection in urban areas. Approximately 86% of primary energy in Rwanda Short description comes from biomass, in the form of firewood (57%) and charcoal, together with smaller amounts of crop residues and peat (6%). Thus, LFG will provide an Overview alternative renewable energy by capturing a large portion of CH 4 and oxidizes it in combustion. The scope of work will include: Landfill sites preparation, waste sorting, landfill gas (methane) generation estimate, landfill gas collection and utilization Scope of project options, and financial income generation and other government support programmes (awareness, training, subsidies). Timing of project 2020-2030 Reduction of methane (CH4) emissions from landfill sites and avoided Carbon Dioxide (CO2) from displacement of fossil-based electricity use. The use of Mitigation effect GHG mitigation methane landfill gas will reduce methane emissions from 30% to 60% between 2020 and 2030. Estimated mitigation in 0.356 2030 (MtCO2e/yr) Total project mitigation 2.234 (MtCO2e) Investment for LFG Plants of 6 MW and improved landfills is estimated at 28 million USD. The electricity generation capacity of 3 MWh is estimated from the very beginning of the project from 2020 to 2025 and 6 MWh from 2026 to 2030. The capital costs will be involved in purchasing of materials, design and Description of costs construction of landfill gas collection system and landfill gas cleaning and treatment system. Operating costs will be focused on landfill gas flaring system, gas storage and compression system, and in LFG utilization system as fuel (estimated at around 9 million USD through 2030). .Cost-benefit analysis Quantified: Avoided cost of fuel from biomass, compensation cost of electricity demand, revenue from utilisation of landfill gas, and generated additional financial income for the landfill site operations (estimated at over 80 million Description of benefits USD through 2030). Not quantified: job creation, welfare improvements, reduced workload for rural households, health benefits, improved air, water and soil quality, reduction of leachate and improvement of on-site conditions NPV of project (Million 21.27 USD) It is assumed that this project will boost employment opportunities, activating Notes on economic or creating new jobs. Landfill gas Utilization will meet and contribute to analysis electricity demand and avoided costs of electricity in Rwanda and this will harness economic growth within the country Abatement cost -9.52 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-33 WASTE Mitigation measure Waste to Energy (WtE) plants This project seeks to implement national strategies to recover energy from waste by conversion of non-recyclable waste materials into usable heat or electricity through different processes. The WtE plants will only consider the Short description conversion of non-recyclable waste material from urban area into usable Overview energy. The WtE plant should have a capacity of processing up to 800 tons of solid waste per day and shall be able to generate power capacity of 15 MW per hour by 2020 which will increase to 30 MW in 2025. Implementation and establishment of a WtE plant for collection of all wastes Scope of project for disposal and their transformation into energy by incinerating all wastes, thus preventing future emission from the same waste. Timing of project 2020-2030 Avoided CO2 emissions from displacement of fossil-based electricity. This Mitigation effect project has a high mitigation potential since the technology incinerates all GHG mitigation wastes. Estimated mitigation in 0.220 2030 (MtCO2e/yr) Total project mitigation 2.313 (MtCO2e) Assumes investment for WtE plant in urban area with the capacity of 800 tons of solid waste per day and 15 MW of electricity generation with an Description of costs estimate investment cost of 161 million USD per plant, and other government support programmes and maintenance costs estimated to total around 8 million USD per year. Quantified: WtE electricity generation will translate into revenues per year Cost-benefit analysis for job creation and economic growth, estimated at up to around 50 million Description of benefits USD pa. Not quantified: job creation, improved quality of environment, electricity generation, GHG reduction, high public awareness about the efficacy and potency of renewable energy technologies. NPV of project (Million 119.01 USD) With the increase of urbanization and improvement of living standards, Notes on economic waste to energy project will provide job opportunities, respond to electricity analysis demand and increase the GDP by ensuring access to affordable and clean energy. Abatement cost -51.46 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-34 WASTE Mitigation measure Aerobic biological treatment (composting) The project implements the windrow composting method at household level. Organic waste is placed into rows of long piles called windrows and aerated Short description by turning the pile periodically by either manual or mechanical methods. Overview Usually a height of 1.2-2.4 m allows oxygen to flow to the windrow’s core. The project will be implemented in rural households where solid waste is typically collected into small pits for composting. The project envisages the Scope of project recovery and reuse of organic waste by neighbouring households, i.e. village/umudugudu in order to restore and maintain soil fertility. Timing of project 2020-2030 The aerobic process of composting does not generate methane because Mitigation effect methane-producing microbes are not active in the presence of oxygen (i.e. GHG mitigation methane avoidance). Estimated mitigation in 0.060 2030 (MtCO2e/yr) Total project mitigation 0.502 (MtCO2e) At the community level, composting offers an attractive economic advantage because the existing land area for composting will be used. The major cost is labour cost collecting and turning the pile periodically. Labour cost can be Description of costs reduced by the proximity of households involved in the projects. the assessment assumes a capacity building needs and program implementation cost of 5 million USD and annual costs of up to 6 million based on a unit labour cost assumption of 20 USD/tonne compost. Composting requires relatively simple and scalable technology. In addition to methane gas emissions reduction, composting offers numerous other climate Cost-benefit analysis change adaptation co-benefits such as: improving retention of soil fertiliser, reducing compostable waste, enhancing soil buffering capacity and moisture Description of benefits holding capacity, adding a source of organic matter that stimulates biological activity, improving the pool of nutrients, adding a liming effect on the soil, soil structure improvement. Compost sales of up to 7 million USD per year are estimated based on unit price assumption of 22 USD/tonne. NPV of project (Million -0.84 USD) Considering the economic and technological context of Rwanda and the Notes on economic country waste management approach in rural areas, the windrow composting analysis is seen as a viable option at household levels. Abatement cost 1.68 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-35 WASTE Mitigation measure Wastewater treatment and re-use The proposed project will involve the construction of a sewerage network and wastewater treatment plant (WWTP). The planned projects include: (i) Kigali central WWTP in Nyarugenge and (ii) the Centralized Sewerage System Short description for Kibagabaga and Kinyinya Catchments in Gasabo District, etc. In addition, Overview there are other initiatives of semi-centralized wastewater treatment systems in Kigali. In the short term, treating wastewater is the priority while in the long run, reuse of the treated water is targeted to address increasing water scarcity, Scope of project and increase drought resilience as well as restoring and maintaining soil fertility. Timing of project 2020-2030 Mitigation effect Reduction of methane (CH4) and Nitrogen oxide (N2O) emissions. GHG mitigation Estimated mitigation in 0.022 2030 (MtCO2e/yr) Total project mitigation 0.348 (MtCO2e) Capital costs of 89 million USD per 1 WWTP (178 million USD in total for 2 plants) estimated based on the project of Kigali central wastewater treatment plant. Capital costs will cover the consolidation of basic Description of costs infrastructures in terms of collection of sewage and operational costs and other costs will be attributed to the functioning of wastewater treatment plant. O&M costs are estimated at around 1.5 million USD per year in total. Quantified: The project has benefits of reduced costs of on-site treatment and emptying of pits/septic tanks. Other benefits include job creation, Cost-benefit analysis increased tourism due to cleanliness, increased agriculture production due to wastewater reuse, reduced water footprint, and groundwater recharge Description of benefits (estimated to total around 32 million USD per year). Not quantified: Quantifying the economic benefits of improved river water quality and health is a complex task which would require a collection of substantial amounts of data that is beyond the scope of this project. NPV of project (Million -21.22 USD) The project will boost employment opportunities and creating new jobs. The Notes on economic project will promote cost savings from wastewater reuse and will save the analysis costs related to the environment decontamination and health diseases previously due to wastewater discharge. Abatement cost -60.93 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-36 A-1.4 Agriculture Figure A-3 presents the cost-ordered MACC for all identified measures within the agriculture sector for the year 2030. The corresponding data are shown in Table A-5. Figure A-3 Marginal abatement cost curve for identified measures in 2030, Agriculture Source: Authors Rwanda NDC Implementation: Final Report Page A-37 Table A-5 Mitigation measures ordered according to abatement costs, Agriculture Abatement cost Mitigation 2030 Mitigation option Sub-Sector (USD/tCO2e) (MtCO2e) Improved fertilizers efficiency Agriculture -159.61 0.039 Improved livestock husbandry Agriculture -126.91 0.133 Soil conservation (multicropping) Agriculture -111.59 0.066 Soil conservation (rotation) Agriculture -108.66 0.551 Conservation tillage Agriculture -68.74 0.197 Manure management Agriculture -10.45 0.058 Compost production Agriculture 1.83 0.624 Soil conservation (terracing) Agriculture 57.49 0.451 Improved livestock species Agriculture 136.34 0.126 Total mitigation potential in 2030 2.24 Source: Authors Table A-6 below provides a summary of the key assumptions and data sources used in the cost- benefit analyses. The subsequent tables describe the assessment of each of the mitigation measures in more detail. Table A-6 Key assumptions and data sources used in cost benefit analyses, Agriculture Parameter Value Source Notes Soil and water conservation measures The rate of fertilizer redution and 30% reduction in fertilizer use; 5% Bowen et al. yield increase was adapted yield increase on rice 2005 Nutrient use efficiency downwards from Bowen et al., 2005. (deep fertilizer Seed cost = 1500 frw/kg RAB  1ha requires 10kg of seed placement in rice) Emission factor urea for CO2 =  0.733; Emission factor N2O = 0.01 IPCC 2006  for direct emission and 0.100 for indirect emission from soil  Proportional estimate – application of Soil C retained in soil 150days 10t/ha compost will retain 0.85Mg Fabrizio et al., after compost application of C/ha (during 2 cropping seasons). To 2009 50t/ha =4.24Mg/ha be conservative, this was considered Nutrient use efficiency as single time effect  (compost) One cow produces 10kg dung per RAB; our This would be enough for making 5 day and 2-2.5 tonnes/year. assumption tons of compost Rajkhova et al. 4-5tonnes of fresh crop/weed 1ha of crops produces 5-20 tons of 2005 and our biomass is required to make 5-5.5 fresh biomass assumption tonnes of compost Soil conservation Maize and bean production cost RAB research - (rotation)  data programs Yield increase from rotation: Midpoint of 5-20% yield increase  Bullock, 1992 12.5% indicated in source Soil C increase 0.02-0.76 Mg/ha Soil C increase of 0.195tons/ha per Conservation tillage Lal et al. 2004 per year year assumed to be conservative Rwanda NDC Implementation: Final Report Page A-38 Assessment has estimated soil C stock C soil stock under monocropped Hergoualc'h et as about 20Mg C/ha for coffee: 24-29 Mg C/ha al, 2012 monocropped coffee C increase in above ground biomass Aboveground biomass stock for Van Asten et al, of banana-coffee estimated at 32/8 Multi-cropping monocropped coffee: 10.5 Mg/ha 2015 years = 4 tons C per year. (banana-coffee) Above ground biomass stock for  - polycropped coffee: 42.5 Mg/ha Cost of training programme: 2 million USD/year; Estimated - Follow up: 1 million USD year Cost of radical terraces: 694 Bizimana & Study of radical terraces cost-benefit USD/ha Kannan, 2011 analysis with maize and beans yields. Cost of progressive terraces: 378 Bizoza A., 2011 - USD/ha Soil loss on unprotected slopes in Soil loss prevention potential on 1ha Rwanda: 41.5t/ha per year; Soil Kagabo et al due to terracing therefore calculated loss on terrace protected slopes: 2013 at 23.5t/ha per year. 18t/ha Terracing Taken from annual RAB targets Share of radical versus progressive contained in the RAB Annual Action RAB, 2017 terraces: 33%/67% plan 2017-2018, assuming annual area of 15,000ha. Maize and Irish potatoes seed RAB research - costs programs Seasonal Agricultural Survey Report, Mean yield for maize NISR, 2019 2018 Livestock The area for improved fodder will be 75,500ha Improved fodder expansion New fodder species will be planted Assumption is assumed along new and old on a total of 75,500 ha by 2030. terraces, roadsides and sites identified for forage production. Yield of dry matter estimated at Brachiaria yield: 5.6 t/ha of dry Mutimura and 4t/ha, and fresh biomass yield about matter Everson, 2012 20t/ha Livestock husbandry 2 tons of Brachiaria needed for 1 cow Consumption of feed per day for 1 Nduwamungu (improved fodder per year; this can be obtained from cow: 10 kg et al., 2019 expansion) 0.1ha. Proportion of improved fodder in animal feed to improve enteric Knapp et al. . fermentation reduction: 50% 2014 Associated reduction achieved: 5% Cost of establishing fodder: 600 USD/ha; cost of maintenance : RAB Animal 500USD/ha per year nutrition - program Milk cost (revenues): 350Frw/litre Cost of improved cow:1000 USD Cost of local cow: 110 USD RAB Animal Livestock species Cow maintenance cost: 125,000 FRW nutrition - program Length of milking period: 220 days/year; 10-20 l milk per day Other mitigation measures Rwanda NDC Implementation: Final Report Page A-39 30% reduction in N2O emission with Chadwick et al. - covering manure 2011 Manure management Chadwick et al. No emissions in slurry systems - 2011 Rwanda NDC Implementation: Final Report Page A-40 AGRICULTURE Mitigation measure Nutrient use efficiency (multiple measures) The project is focused on 2 components: compost production and improved biomass and fertilizer management in rice, with the target to achieve compost production and application on 200,000 ha agricultural land at rate of 5 tons/ha per year by 2030. This quantity may be achieved if about 350,000 rural Short description households will produce each about 3tonnes of compost per year. For rice, the practice of reduced biomass application in fields will be practiced on the whole Overview rice area, and mineral fertilizers will be applied at deep placement, which will improve nutrient use from mineral fertilizers and reduce fertilizer quantities by 30% while assuring same or better yield levels. The project will provide training, technical support and follow up of the planned expansion of compost making and application, deep fertilizer placement and Scope of project reduced organic amendment in rice to provide improved nutrients and thus lead to reduced use of mineral fertilizers alone and reduced carbon addition to soil. Timing of project 2020-2030 Increased compost application will increase C-stock in soil, especially where soils have been cultivated without fallow and rotation. Use of crop biomass for Mitigation effect GHG mitigation compost production will reduce storage period for manure as it will be used for compost making and it will reduce emissions from manure management Estimated mitigation in 0.624 MtCO2e (compost component); 0.038 MtCO2e (rice component) 2030 (MtCO2e/yr) Total project mitigation 3.431MtCO2e (compost component); 0.352 MtCO2e (rice component) (MtCO2e) Costs include production and seed costs, training, implementation and Description of costs monitoring of composting units and rice fields. Estimated at around 700 million USD total (compost) and 700 million USD (rice) through 2030. The new composting units will supply nutrients and generate yield with reduced use of mineral fertilizers per unit area. Other benefits include reduced GHG emissions, improved soil physical structure; increased carbon in nutrient depleted soils, and job creation for composting units management (it can be done for CIP consolidated sites and cooperatives); for rice, reduced organic Description of benefits amendment in form of rice bio-mass application in rice fields will reduce Cost-benefit analysis methane emissions; there will be reduced N2O emissions as mineral N-fertilizer use will be reduced to produce the same or better yields using deep fertilizer placement. Total benefits estimated at 780 million USD (rice) and 713 million USD (compost) through 2030. NPV of project (Million -6.27 M USD (compost component); 56.19 M USD (rice component) USD) For compost, the increased production of compost will generate revenues from compost sale, and economic study on improved crop productivity and return Notes on economic from combined use of compost and mineral fertilizers would be conducted as analysis part of project monitoring. The economic benefits of the project are calculated using the avoided costs of mineral fertilizer use (i.e. lesser mineral fertilizer quantities are used to be applied per unit area) for rice. Abatement cost 1.83 USD/tCO2e (compost component); -159.61 USD/tCO2e (rice component) (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-41 AGRICULTURE Mitigation measure Soil and water conservation (multiple measures) The project targets to achieve 165,000 ha with establishment of new terraces in addition to the existing ones, introduce regular crop rotation on 660,000ha, Short description introduce coffee into banana systems on 25,000ha and expand conservation Overview tillage on 275,000ha by 2030. Project will provide training, technical support and follow up of the planned expansion targets of terracing, crop rotation, coffee-banana and conservation Scope of project tillage options to sustainably improve soil and water conservation, which will result in stable increase of soil C-stock, and thus, improved crop yields. Timing of project 2020-2030 Reduction of N2O emissions from reduced mineral N-fertilizer use per unit area as it will be used in combination with increased compost quantities and Mitigation effect increased rotation with leguminous N-fixing crops; increased C-supply in soil; GHG mitigation reduced CO2 emissions from bare soil; increased C-fixation in biomass in coffee- banana systems Estimated mitigation in 0.45 MtCO2e for terracing; 0.55 MtCO2e for crop rotation; 0.07 MtCO2e for 2030 (MtCO2e/yr) coffee-banana systems and 0.2 MtCO2e for conservation tillage Total project mitigation 2.48 Mt CO2e for terracing; 3.03 MtCO2e for crop rotation; 0.16 MtCO2e for (MtCO2e) coffee-banana systems and 1.18 MtCO2e for conservation tillage Costs include terracing, plants, fertilizer, management, training, implementation and monitoring. Total costs estimated at 3.8 billion USD (terracing), 4.5 billion Description of costs USD (crop rotation); 378 million USD (coffee-banana systems) and 5 billion USD (conservation tillage) through 2030. New terraces will reduce carbon loss from soil with reduced erosion and improved crop yields; terracing preparation will provide employment for rural community; introduction of regular crop rotation will increase N-fixation in soil; increase yields and biomass production; reduce pests and diseases; coffee- banana intercropping will provide economy of space and improve quality of coffee berries, increase soil carbon and carbon sequestration in banana and Cost-benefit analysis coffee biomass, reduce bare soil extent and reduce solar insolation with Description of benefits mulching as essential management practice contributing to soil moisture and increased C addition to soil. Tillage will contribute to increased accumulation of carbon stock in soil and slowing down decomposition of soil organic matter. Other benefits include reduced GHG emissions from agricultural soils, improved physical structure of soil. Total benefits estimated at 3.6 billion USD (terracing), 4.5 billion USD (crop rotation); 415 million USD (coffee-banana systems) and 5.2 billion USD (conservation tillage) through 2030. NPV of project (Million -137.71 for terracing; 328.99 for crop rotation; 17.68 for coffee-banana USD) multicropping; and 81.17 for conservation tillage Notes on economic The economic benefits of the project are based on increased crop production analysis after application of the suggested mitigation options. 55.47 USD/tCO2e for terracing; - 108.66 USD/tCO2e for crop rotation; -111.59 Abatement USD/tCO2e for coffee-banana multicropping and -68.74 USD/tCO2e for costs(USD/tCO2e) conservation tillage. Rwanda NDC Implementation: Final Report Page A-42 AGRICULTURE Mitigation measure Improved livestock husbandry The target for the proposed project to improve livestock husbandry is to expand fodder species (e.g. Calliandra, Leucaena, Medicago and Brachiaria spp. For Short description different agro-ecologies) using terrace edges and roadsides to reach 75,500 ha and Overview use the production of improved fodder to feed 377,5000 cows. The project will support establishment of improved fodder species and the follow Scope of project up of their expansion. Timing of project 2020-2030 Increase of soil carbon through supply of organic matter through root Mitigation effect underground biomass, increased aboveground biomass produced per unit area, GHG mitigation and reduced soil losses due to erosion. Estimated mitigation in 2030 0.133 (MtCO2e/yr) Total project 0.626 mitigation (MtCO2e) Costs include planting material, establishment and monitoring of Brachiaria fields. Description of costs Estimated to total 413 million USD through 2030. Fodder plants will increase soil carbon, provide quality nutrition for cows and goats thus resulting in increase in milk production and improved growth. Besides, Description of planted on roadsides and terrace edges they will reduce soil erosion and runoff Cost-benefit analysis benefits thus contributing to soil and water conservation. Economic benefits estimated to total 465 million USD through 2030. NPV of project 79.46 M USD (Million USD) Notes on economic The economic benefits of the project are calculated using the increased milk analysis production resulting from improved fodder use. Abatement cost -126.91 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-43 AGRICULTURE Mitigation measure Improved livestock species and population The target for the project is to replace 260,000 local cows with 130,000 Short description improved cows (pure and crossbreed) to achieve reduction in enteric fermentation and increase cow productivity per head. Overview The project will provide training, technical support and follow up of the planned Scope of project replacement of local cows within the set target and thus lead to reduced emissions from enteric fermentation. Timing of project 2020-2030 Main mitigation effect will be through reduction of emissions from enteric Mitigation effect fermentation from reduced number of cows while maintaining and improving GHG mitigation the production of milk Estimated mitigation in 0.126 2030 (MtCO2e/yr) Total project mitigation 1.034 (MtCO2e) Costs include training, cost of improved cows, compensation for local cow Description of costs replacement and monitoring; estimated to total almost 2 billion USD through 2030. A higher milk production will be achieved with lower population of cows and Cost-benefit analysis Description of benefits lower emissions from enteric fermentation; benefits from increased production estimated to total 1.8 billion USD through 2030. NPV of project (Million -140.92M USD USD) Notes on economic The economic benefits of the project are calculated using the sales of milk, meat analysis and manure from improved cows. Abatement cost 136.34 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-44 AGRICULTURE Mitigation measure Improved manure management The target for the project is to promote collective cow keeping and kraals with improved manure management facilities (1000 new kraals) achieve improved Short description manure management in existing farms with more frequent manure removal; Overview use of manure covering and straw for manure storage, and promotion of slurry systems. Project will provide training, technical support and follow up of the proposed Scope of project mitigation options; collective farms with improved manure storage facilities. Timing of project 2020-2030 GHG emissions will be reduced with promotion and expansion of covering of Mitigation effect manure, using higher straw quantity in stored manure and by covering manure GHG mitigation during storage, and promotion of slurry systems. Estimated mitigation in 0.058 2030 (MtCO2e/yr) Total project mitigation 0.379 (MtCO2e) Costs include farm/kraal construction, training, construction of improved Description of costs manure storage facilities and monitoring; estimated to total 36 million USD through 2030. The proposed improved manure management options will result in generating better quality of manure with higher nutrients, especially for nitrogen. Manure Cost-benefit analysis Description of benefits yield in terms of quantities will also be increased as losses will be reduced. Total benefits from increased sales of manure and milk estimated to total 74 million USD through 2030. NPV of project (Million 3.96 USD) Notes on economic The economic benefits of the project calculated considering the sales of analysis manure and milk from the cows in new kraals with slurry system. Abatement cost -10.45 (USD/tCO2e) Rwanda NDC Implementation: Final Report Page A-45 Annex B – Adaptation project evaluations Rwanda NDC Implementation: Final Report Page B-1 B-1 ADAPTATION PROJECT EVALUATIONS Table B-1 Evaluation summary for prioritisation of water sector interventions WATER Integrated Water Resource Planning and Management management plan for all Level restoration, water storage and models, water quality testing, and improved hydro-related through water conservation A National Water Security information management Develop and implement a Develop water resource practices, wetlands efficient water use 1 catchments Significant adaptation Significant adaptation Significant adaptation Contribution towards potential in terms of human potential on reliable data potential for critical NDC target resources and institutional from which policy decisions catchment restoration systems could be based (+) Increased number of Improved seasonal data at May include negative Environmental Indirect environmental beneficiaries trained in ways catchment level impacts such as biodiversity effectiveness effects to build climate change and landscape loss resilience Significant impact through Moderate impact through Significant impact through wetland management and policy alignment and forest management and Mitigation Co-Benefits restoration improvement restoration Moderately costs effective Usually low cost Moderately cost effective due to conservation Cost-effectiveness benefits (+) impacts on equity and No negative impact on (-) impacts may arise from welfare due to vulnerable equity and walfare the population relocation Equity and welfare community involvement and land compensation EVALUATION CRITERIA Socio-economic impacts and co- Positive impacts through Increased efficiency on Reduced costs from water benefits Competitiveness and increased efficiency & water business through the related disasters productivity availability integration of climate change in water planning Employment and green Moderate employment Job creation: Green growth and growth opportunities through the use of models implementation of employment including vulnerable and water quality testing catchment management population In line with NST 1 and MoE, In line with NST 1 and MoE, In line with NST 1, SPCR and Alignment with other 2017 Strategic Plan for the 2017 Strategic Plan for the MoE, 2017 Strategic Plan for policy aims ENR ENR the ENR No legal and regulatory No legal and regulatory Potential issues arising with Legal and regulatory issues anticipated issues anticipated existing activities in feasibility catchments Feasibility of implementation Highly suitable to funding Highly suitable to funding Highly suitable to funding Suitability to funding and climate finance and climate finance and climate finance and climate finance Capacity building of local Potential capacity gap in the May require land Other implementation population related to use of models and info compensation challenges restoration of wetlands management Rwanda NDC Implementation: Final Report Page B-2 Table B-2 Evaluation summary for prioritisation of agriculture sector interventions AGRICULTURE Climate Resilient Value Chain Development Expand irrigation and improve Strengthen crop management management practices (soil crops and promote climate erosion control; landscape Expand crop and livestock Develop climate resilient Develop climate resilient Develop sustainable land addition facilities and postharvest and value water management resilient livestock management) technologies insurance practices Significant adaptation for Modest adaptation Modest adaptation potential Significant adaptation Significant adaptation Significant adaptation to Contribution towards resilient to drought potential: capacity of food through disease prevention, potential to increase food especially in drought season offset potential losses due NDC target storage facilities surveillance and control production in target areas to climate change Loss of native species and Improved agro processing Positive to determine Biodiversity and landscape Over-extraction, lowering Positive impact in the most Environmental Indirect environmental biodiversity facilities needed actions in crop loss, improved production groundwater table, affected regions as well as effectiveness effects management on time increased productivity for crop and lvestock Uncertain performance for Possible increase in energy Proper plant management, Potential increase of carbon Small effect on crop Restoration of degraded mitigation consumption and GHG including nutrition, reduces sink surface area resilience and carbon sink lands, i.e. Carbon sink Mitigation Co-Benefits emissions GHG emissions Positive performance due to Cost effective due to the Positive performance due to Cost-effective due to Moderate positive Cost-effective due to increased productivity benefits of post harvest and increased productivity avoided costs of fertilizers performance due to avoided losses or unpaid Cost-effectiveness value addition and pollution control (co- increased productivity farmers debt benefits) Possible changes to prices Positive changes in equity Positive changes such as Positive changes within the Possible increase of market Reduced poverty and access and distributional of seeds and welfare due to farmer education, affected group from the prices due to the cost of to new agricultural Equity and welfare and livestock minimized existing post communications and crop increased crop yield water technologies by farmers EVALUATION CRITERIA Socio-economic impacts and co- harvest losses resistance Positive on economy Reduced market prices and Productivity benefits Increased crop production (+)Productivity benefits, (-) Adaptation insurance could benefits Competitiveness and through the promotion of increased quality of through reduced plant costs and increased Increased crop production be unaccessible to the productivity early yielding, drought agriculture products infestation production efficiency costs poorest farmers tolerant, shorter cycle, etc. Medium green job creation Green job creation such as Green jobs creation Green job creation such as Green job creation through Additional employment and Green growth and through seed multiplication agro processing facilities and including youth and women radical and progressive irrigation and land green growth due to employment & livestock farming business crop storage in districts using GIS in agriculture terraces consolidation expanded insurance In line with MINAGRI -2017 In line with GGCRS and NST 1 In line with GGCRS and NST 1 In line with GGCRS and NST 1 In line with GGCRS and NST 1 In line with GGCRS and NST 1 Alignment with other Strategic Plan for Agricultural policy aims Transformation No legal and regulatory No legal and regulatory No legal and regulatory No legal and regulatory Possible need of Regulation need to be well Legal and regulatory issues anticipated issues anticipated issues anticipated issues anticipated transboundary cooperation established to avoid issues feasibility to reduce water conflicts such as insurance on the Feasibility of used fake seeds implementation Highly suitable to funding Possible local funding, such Highly suitable to funding Highly suitable to funding Moderately suitable to Highly suitable to funding Suitability to funding and climate finance as public sector lending and climate finance and climate finance funding and climate finance and climate finance and climate finance Long term research is Gap in local skills for best Moderate issues related to May require massive inputs Current small surface of Farmers awareness to Other implementation required to find sustainable applicable technologies in capacity building in GIS of labor and strong consolidated land understand what such an challenges solutions & minimise post harvest technique protection (e.g. To avoid insurance program is trying impacts terrace destruction) to achieve Rwanda NDC Implementation: Final Report Page B-3 Table B-3 Evaluation summary for prioritisation of land use and forestry sector interventions LAND AND FORESTRY Sustainable management of forestry and Agroforestry Wood Supply Chain Climate-sensitive Integrated Land Use Planning for degraded forest resources Improve Forest Management Development of Agroforestry Inclusive land administration planning and monitoring for Harmonised and integrated and Sustainable Agriculture reforestation of designated system for sustainable land that regulate and provide spacial data management guidance for land tenure (control soil erosion and Promote afforestation / Integrated approach to improved soil fertility) sustainable land use use management management security areas Significant adaptation and Significant adaptation and Significant adaptation and Significant adaptation due to Significant adaptation due to Significant adaptation for Contribution towards enhancing ecosystem enhancing ecosystem enhancing ecosystem the small size of the country the small size of the country sustainable management of NDC target resilience resilience resilience and demographic pressure and demographic pressure lands To sustain ecosystem but can Cleaner water and air, rich Poor planing may include Dissemination of Increased climate change Environmental Indirect environmental Reduction in soil losses and also alter carbon cycles, forest wildlife habitat, and biodiversity and landscape information: increased adaptation through effectiveness effects increased carbon sequestration water, energy, and thus, increased recreational loss monitoring capacity environmental protection and pollination services ecosystem services opportunities Carbon sink: contribute to Carbon sink: contribute to Carbon sink: contribute to GHG mitigation in planning, GHG mitigation in planning, Reduced GHG emissions mitigating global warming mitigating global warming mitigating global warming development and development and related to poor land use Mitigation Co-Benefits management of land management of land decisions resources resources Cost effective due to the Moderate cost effective due Cost effective due to the Cost effective due to the Cost effective due to data Highly cost effective due to reduced soil losses, ecosystem to the reduced soil losses and reduced soil losses and planning that control land accessibility and information reduced environmental Cost-effectiveness services and large community ecosystem services ecosystem services use changes to adaptation to climate losses (i.e. Soil loss & involvement change erosion) Increased participation in Increased participation in Positive impacts on No negative impact on No negative impact on No negative impact on association activities and association activities and community-managed forest, equity and walfare equity and walfare equity and walfare Equity and welfare improved household welfare improved household welfare for instance on firewood EVALUATION CRITERIA Socio-economic impacts and co- (+) Productivity benefits (+) Wood productivity (+) Improved forest benefits (+) Improved economy (+) Improved economy Increased competition due benefits Competitiveness and benefits, (-) reduced arable and other ecosystem through geospatial data through optimal choices on to land ownership of productivity land services the future uses of land collection and adaptation individuals or groups measures formulation Green jobs: Agroforestry Green jobs: Forestation and Green jobs: Management of Green jobs and other May have a strong impact on Increased green jobs due to Green growth and plantation and management of management of forest forest ecosystem services employments: e.g. green jobs and other secured access to land employment forest ecosystem services ecosystem services infrastructural development employments creation In line with GGCRS and the In line with GGCRS and the In line with GGCRS and the In line with GGCRS and NST 1 In line with GGCRS and NST 1 In line with GGCRS and NST 1 Alignment with other 2018 Rwanda national forest 2018 Rwanda national forest 2018 Rwanda national forest policy aims policy policy policy Land owners issues on No legal and regulatory issues No legal and regulatory No legal and regulatory No legal and regulatory Except land compensation, Legal and regulatory agroforestry plantation can be anticipated issues anticipated issues anticipated issues anticipated no legal and regulatory feasibility anticipated issues anticipated Feasibility of implementation Moderately suitable to funding Highly suitable to funding and Highly suitable to funding Highly suitable to funding Moderately suitable to Moderately suitable to Suitability to funding and climate finance climate finance and climate finance and climate finance funding and climate finance funding and climate finance and climate finance Capacity building of farmers, Increased urbanisation and Increased urbanisation and Implementation of Skill development in spacial Pressure on land due to Other implementation land ownership challenges to population pressure population pressure sustainable land use data management and the increasing population and challenges decide on what to plant practices: require capacity accuracy of the system climate change building Rwanda NDC Implementation: Final Report Page B-4 Table B-4 Evaluation summary for prioritisation of human settlements interventions HUMAN SETTLEMENTS Urban Land Use Storm water and drainage informal settlement upgrading Storm water management High density buildings and Significant adaptation for Significant adaptation to Contribution towards sustainable management of moderate potential flood NDC target lands and to moderate damages and for water potential damages conservation Minimise risks from climate Improve groundwater Environmental Indirect environmental change impacts in informal recharge but poor planing effectiveness effects settlement may disturb the natural water cycle Reduced materials in Strenghten hydropower buildings and energy plants: Energy production Mitigation Co-Benefits consumption Highly cost effective due to Highly cost effective: reduced loss of properties infrastructure protection, Cost-effectiveness and improved quality of life flood management Reduced storm water Increased costs or relocation, impacts from the affected Equity and welfare lost of social network for low groups EVALUATION CRITERIA Socio-economic income households impacts and co- Reduced maintenance cost benefits Competitiveness and (+) Competitiveness due to for public and private productivity the increased quality of life infrastructures and value of properties Green buildings construction Employment through Green growth and and related additional maintenance and upgrading employment imployment of road and drainage infrastructures In line with GGCRS and NST 1 In line with GGCRS and NST 1 Alignment with other policy aims Except land compensation, Except land compensation, Legal and regulatory no legal and regulatory no legal and regulatory feasibility issues anticipated issues anticipated Feasibility of implementation Moderately suitable for Highly suitable for funding Suitability to funding funding and climate finance and climate finance and climate finance Access to finance and Access to finance and Other implementation funding are the key funding are the key challenges challenges challenges Rwanda NDC Implementation: Final Report Page B-5 Table B-5 Evaluation summary for prioritisation of health, transport and mining interventions HEALTH TRANSPORT MINING Climate-resilient roads and Vector-based diseases Climate compatible mining bridges measures and create capacity to adapt to disease outbreaks Climate compatible mining infrastructure and services Strengthen preventive Improved transport Significant adaptation for the Significant based on Rwanda's Moderate impact through Contribution towards expected increase hilly topography and to erosion control, water use NDC target proliferation of the diseases support the economy efficiency, finance, etc. Disease vector control with Biodiversity and landscape loss Environmental benefits from Environmental Indirect environmental insecticides may harm the during construction, improved cleaner production measures effectiveness effects ecosystem and diversity infrastructures disruption No direct mitigation, but Reduction of GHG emissions Reduction of GHG emissions there is a reduction of through mass common through cleaner production Mitigation Co-Benefits migration of vector born transport diseases Cost effective, considering Highly cost effective, mainly in Highly cost effective due to vectors proliferation and the districts prone to flooding and reduced loss of row Cost-effectiveness current Malaria incidence in landslides materials Rwanda Reduced mortality rate, Reduced cost and time of Increased investment cost mainly in the vulnerable transport and increased for artisanal and small scale Equity and welfare population welfare: access to markets miners EVALUATION CRITERIA Socio-economic impacts and co- Positive impacts, e.g. (+) Reduced maintenance cost Increased efficiency in benefits Competitiveness and increased Life expectancy, and market easier access to mining production productivity efficiency and well-being local amenities Additional imployment from Green jobs from transport Green jobs through cleaner Green growth and the well-being and the services and additional production, infrastructure employment reduced mortality construction and maintanance development, etc. employment In line with health sector In line with transport sector In line with GGCRS program Alignment with other policy, GGCRS and NST 1 policy, GGCRS and NST 1 of actions, Rwanda Mining policy aims Policy and NST 1 Some disease vector control No legal and regulatory issues No legal and regulatory Legal and regulatory measures may be governed anticipated issues anticipated feasibility by law Feasibility of implementation Highly suitable for funding Highly suitable for funding and Suitable for private sector Suitability to funding and climate finance climate finance funding and climate finance Capacity builiding on Access to finance and funding Rehabilitation of abondoned Other implementation measures for vector diseases are the key challenges mining as a risk to achieve challenges control the target Rwanda NDC Implementation: Final Report Page B-6 Table B-6 Evaluation summary for prioritisation of cross-sectoral interventions CROSS-SECTORAL DRR program Capacity development Resource mobilization Institutional capacity building Establish an integrated early warning system and disaster sector NDC implementation and development for cross- Disaster risk monitoring Access to finance response plans Significant adaptation to Significant adaptation to Significant to integrate Very significant to reduce Contribution towards monitor and moderate monitor and moderate adaptation priorities in and adapt to impacts of NDC target extreme weather events extreme weather events national planning climate change Positive impact through Loop holes in the plans may Positive impact to help Positive impact in the most Environmental Indirect environmental controlling the frequency increase the severity of the sector´s implement their affected regions and for the effectiveness effects and intensity of hazards disaster specific NDC activities high priority actions Indirect GHG reduction Indirect GHG reduction Co-benefits in adaptation Co-benefits in financed through protection of through protection of activities that contribute to activities that contribute to Mitigation Co-Benefits forests, land, hydropowers, forests, land, hydropowers, reducing GHG emissions reducing GHG emissions etc. etc. Cost effective: the targets Cost effective trough Cost effective to meet Cost effective activity include disaster resilence preventing or reducing immediate and long-term enabling all other NDC Cost-effectiveness strategy and detailed further damages planned activities activities national risk atlas No negative impact on Positive changes on welfare Enabling activity that induce Enabling activity that induce equity and walfare of vulnerable population positive impact on equity positive impact on equity Equity and welfare and walfare and walfare EVALUATION CRITERIA Socio-economic impacts and co- Increased efficiency on Increased efficiency on Increased competitiveness Increased efficiency on benefits Competitiveness and business through reduced business through reduced from the developed capacity business through CC productivity damages from hazards damages from hazards resilience and adaptation May have a moderate impact Potential green jobs creation Green jobs creation through Green jobs creation through Green growth and on green jobs and risk in disaster response NDC projects funded NDC projects employment monitoring employments Planning/ actions In line with GGCRS, national In line with GGCRS, national In line with GGCRS and NST 1 In line with GGCRS and NST 1 Alignment with other vulnerability risk assessment vulnerability risk assessment policy aims and NST 1 and NST 1 No legal and regulatory Legal and regulatory No legal and regulatory No legal and regulatory Legal and regulatory issues anticipated frameworks are necessary to issues anticipated issues anticipated feasibility foster the early warning Feasibility of system implementation Highly suitable for funding Moderately suitable for Highly suitable for funding Adaptation finance are still Suitability to funding and climate finance funding and climate finance and climate finance low compared to those funds and climate finance for mitigation support Skill development in disaster Access to finance and To identify priority capacity Lack of finance to cover the Other implementation risk monitoring at national funding are the key building and skills needed costs of adaptation challenges level challenges for NDC implementation Rwanda NDC Implementation: Final Report Page B-7 Annex C - Forestry Rwanda NDC Implementation: Final Report Page C-1 C-1 MITIGATION POTENTIAL IN FORESTRY C-1.1 Overview Forests play a critical role in Rwanda’s climate change policy, with a total estimated sequestration potential of 11,359 Gg CO2e as of 2015 (GoR, 2018a). According to a recent forest cover mapping exercise undertaken in 2018/2019, forests cover over 30.5% of the total national land area, occurring mainly in the southwest and northwest of the country along the Congo-Nil Crest (Figure C-1). The woodland ecosystems in Rwanda comprise of natural highland forests, forest plantations, wooded savanna, and shrub land and bamboo - covering a total of 724,660 Ha (Table C-1). Figure C-1 Areas dominated by woodland forest ecosystems in Rwanda Source: Nduwamungu et al., 2013 The area of natural forests has declined since 1990, largely as a result of increased demand for agricultural land and fuel wood plantations. The government has protected the remaining areas of intact natural forest and has led efforts to increase their size through a number of afforestation activities. The current National Forest Policy aims to promote conservation of natural forests, sustainable forest management and appropriate regulatory instruments for efficient biomass supply, enhanced ecosystem services, adoption of agroforestry, and more active involvement of private sector in forest investment (MINILAF, 2018). Rwanda NDC Implementation: Final Report Page C-2 Table C-1 Forest area in Rwanda, 2018 Land cover Area, Ha Share, % Natural highland forest 138,910 19.2% Forest plantation 387,393 53.5% Wooded savanna 153,785 21.2% Shrubland 42,313 5.8% Degraded shrubland 1,647 0.2% Bamboo 616 0.1% Total land area 724,660 100% Source: Rwanda forest cover mapping 2018/2019, unpublished The national forest plantations consist mostly of Eucalyptus and Pinus spp. Planted forests supply almost all fuelwood, with charcoal accounting for about 15.2 % of households’ primary energy sources (GoR, 2018a). Bamboo occurs naturally as a lower belt of natural highland forest and has also been planted recently along river belts to protect them from intensive erosion within the hilly landscape. Shrubland and wooded savanna occur within the drier eastern parts of the country, in the region of the Akagera National Park. Rwanda is actively promoting agro- forestry on agricultural land to provide wood for fuel during the transition to more widely available and affordable electricity supply (GoR, 2018a). Due to increased use of forest resources, standing forest biomass declined from 20,865,594 m³ in 2007 (ISAR Forest Inventory, 2007) to 7,080,069 m³ in 2014 (National Forest Inventory, 2015). However, more recently there have been positive changes in afforested areas with increased afforestation over deforestation recorded between 2009 and 2019 (Table C-2). Table C-2 Deforestation and afforestation area in Rwanda, 2009-2019 Item Area, Ha Deforested area 102,106 New planted forest 153,251 No change 571,411 Balance (net afforestation) 51,145 Source: Rwanda forest cover mapping 2018/2019, unpublished. C-1.2 Mitigation options Rwanda’s climate change mitigation options for forestry can be classified into measures that either: • Expand forest vegetation and carbon pools in wood products; • Maintain the existing stands of trees; or • Substitute fossil fuels and fossil fuel intensive materials with wood derived from renewable sources, e.g., plantations. Rwanda NDC Implementation: Final Report Page C-3 Based on the Third National Communication (GoR, 2018a), the following mitigation options have been identified and assessed: 1. Development of agro-forestry for sustainable agriculture 2. Promotion of afforestation and reforestation 3. Rehabilitation and improved forest management of degraded forest resources 4. Efficient wood conversion; and 5. Sustainable biomass energy Brief descriptions of these options are as follows: Development of agro-forestry for sustainable agriculture: Agro-forestry technologies would be mainstreamed within national agriculture intensification programmes through increasing tree numbers per hectare on farms and promotion of multipurpose tree species (wood-fodder-stalks- fruits). Both indigenous and exotic tree species would be cultivated in nurseries and distributed to farmers in different agro-ecological zones. Promotion of afforestation and reforestation would be undertaken in designated areas using improved germplasm and good practices in planting and post-planting (maintenance/tending activities). The focus would be in using quality germplasm, planting trees at optimal times (rainy season) and improving post-planting care and replanting. The priority areas would be steep slopes, roads and settlements. Mixed species planting and seedling availability for indigenous species would be promoted, targeting the increase of mitigation benefits (higher carbon sequestration in multi-species tree communities), biodiversity and ecosystem resilience. More indigenous species planting materials would be produced, disseminated and planted to reduce the current dominance of Eucalyptus. Afforestation and reforestation will increase carbon stock through growth of new forests. Rehabilitation and improved forest management of degraded forest resources: To increase the existing low productivity of the degraded forest plantations, improved forest management would be applied to increase forest productivity without converting additional land, while public-private partnerships would be promoted. Forest rehabilitation will lead to increased carbon stock through better productivity of the forests. Efficient wood conversion and sustainable biomass energy: Poor wood conversion efficiency implies that more trees are cut to meet wood demand. Reducing waste of biomass through development of more efficient charcoal value chain and use of improved kilns for charcoal making would be promoted as demand for charcoal increases with urban growth, and charcoal is replacing firewood for use by the urban poor. Use of improved kilns would lead to more efficient use of wood for charcoal production and thus reduce firewood usage (tree use) whilst producing the same quantity of charcoal. Sustainable forest and landscape management: To reduce soil losses and increase soil protection, bamboo and indigenous tree species would be promoted and planted along river belts and wetland borders. Seedlings would be multiplied and planted in designated areas with conservation status (free wood harvest strictly regulated – prohibited for indigenous tree species Rwanda NDC Implementation: Final Report Page C-4 and limited to minimal annual thinning for bamboo). Planting trees along rivers and wetlands would sequester significant carbon amounts in growing tree biomass. A techno-economic assessment is made of each of these measures in order to estimate their emissions reduction potential and cost of abatement. The assessment is undertaken based on the same methodology described in the main body of the report. Project summaries, along with technical and economic assumptions used to assess each of projects are provided below. C-1.2.1 Agroforestry Table C-3 Agroforestry - project description Project title Agroforestry for wood, fruits and fodder The target for the project is to plant additional 25 trees/ha on 600,000ha of agriculture land; expand new fruit area to 100,000ha; increase agroforestry Short description with fodder species on 50,000ha and with these options to achieve increase Overview of trees on agricultural land from 25 (current number from baseline) to 50. Scope of project Project includes training, seedlings production, planting, and follow up. Timing of project Implementation period is 2020-2030 (11 years) The project will lead to GHG mitigation offset through accumulation of Mitigation effect carbon in tree biomass and soil due to reduced erosion, accumulation of organic matter from litter and tree roots GHG mitigation 0.477 MtCO2e/yr for Agroforestry for wood component; 0.495 Mt CO2e/yr Estimated for Agroforestry for fruit component and 0.133 MtCO2e/yr for Agroforestry mitigation in 2030 for fodder component Total project 1.920 MtCO2e for wood component; 2,846 MtCO2e for fruit component; mitigation to 2030 0.906 MtCO2e/yr for Agroforestry for fodder component. Description of Costs include training, seedling production, planting and follow up. costs Agroforestry trees will increase carbon stock in soil, provide nutrients via Description of nitrogen fixation, improve soil quality, increase agriculture production, benefits reduce erosion, provide fuelwood, stalks for climbing beans and fodder, Cost-benefit analysis produce high market value fruits and nuts. - 5.753 M USD for wood component; 120.366 for M USD for fruit NPV of project component and -4.657 M USD for fodder component. Key challenges Requires substantial investment to achieve the proposed targets. 2.996 USD/tCO2e for wood component; -42.292 USD/tCO2e for fruit Abatement cost component and 5.141 USD/tCO2e for fodder component Rwanda NDC Implementation: Final Report Page C-5 Table C-4 Agroforestry assumptions Assumption Value Source Notes Mean annual 20-40 t/ha per increment IPCC, 2006 12 t/ha at 100% tree density year (Eucalyptus, Pinus) Accumulation of C 0.141-0.256 Murthy et al., in agroforestry tons C /ha per Soil C increase estimated as 0.14 tons C/ha /year 2013, systems year Rwanda Forest Target to increase Increase from Sector Strategic agroforestry tree 25 to 50 - policy 2018- density trees/ha 2024. From year 4 to year 8, C stock is assumed to C stock increase at 0.18t/ha per year (half of the further Lal et al., 2004 accumulation years). Adapted from Lal et al. 2004 (decreased conservatively). Assumed for 20years old tree; total C = 92kg Mean annual x277trees/ha divide by 20yrs=1.3tons/yr (MAI 92kg of C/guava Gupta and increment (MAI) for guava). Tree density (6x6 m spacing) = 277 tree Sharma, 2014 guava trees/ha; MAI estimated =1.3tons/ha/yr starting from year 4. Assumed for 20years old tree; total C = 38kg x 38kg of 833trees/ha divide by 20yrs=1.6 tons/yr (MAI C/papaya tree Gupta and MAI for Papaya papaya); tree density (3x4m (Gupta and Sharma, 2014 spacing)=833trees/ha; MAI Sharma, 2014) estimated=1.6tons/ha/yr starting from year 3. MAI -1m³ /yr for Murphy et al., MAI for Macadamia yr 6-12; 1.7-2m³ Tree density 8 x 8 m = 156 trees/ha 2012 /yr for yr 13-25 Assumed for 20years old tree; total C = 126 x 156 trees/ha=1ton/yr tree density (8x8m spacing=156 MAI Avocado 126kg C/tree Eneji et al.,2014 trees/ha, MAI estimated 1tons/ha/yr starting from year 4. 1000fr for papaya and guava; 2000fr NAEB and RAB Seedling cost - for avocado; consultation 4000fr for Macadamia Leycaena MAI = 2.59- Kumar et al., Median value of 7.9 t/ha applied for MAI of leycocephala fresh 13.16 t/ha 1998 Leucaena spp. biomass Rwanda NDC Implementation: Final Report Page C-6 C-1.2.2 Afforestation Table C-5 Afforestation - project description Project title Afforestation (protective new forests on slopes, and urban forests) The project will focus on production and planting of trees in areas identified for protection as degraded lands, steep slopes, and prone to flooding (a total of 42,440 ha) in rural areas with Eucalyptus, Pinus and Short description Alnus spp.; and 2,100 ha to be planted as urban forests with indigenous tree and bamboo spp. For urban forests, the strategy will Overview be using multiple species mix as an option of higher ecological productivity. Tree seedlings production, dissemination, planting and follow up with Scope of project survival data. 7 years for seedling production and planting, then maintenance and Timing of project follow until the end of the project (2030). A significant carbon sink will be produced, and this will offset GHG Mitigation effect emissions through increasing carbon storage in tree biomass and soil. GHG mitigation Estimated mitigation in 0.348 MtCO2e/yr for protective forests and 0.004 MtCO2e/yr for 2030 urban forests Total project mitigation 1.045 MtCO2e for protective forests; 0.015 MtCO2e for urban forests to 2030 by 2030 Costs include training, site preparation, seedling production and tree Description of costs planting. The newly planted forests will generate sinks, protect soil from erosion Description of benefits or floods and landslides, and produce wood and firewood. Cost-benefit analysis Protective forests: -13,810 M USD for 2020-2030 period Urban forests: NPV of project - 1.029 M USD for 2020-2030 period The main economic benefit from newly planted forests will come after 2030 for greater part of the emission reduction, wood harvest, and Notes on economic firewood source. The main economic benefits from newly planted analysis urban forests will be health benefits for urban citizens, as these forests will not produce firewood and will only serve recreational and conservation purposes. Abatement cost Protective forests: 13.22 USD/tCO2e; Urban forests: 70.63 USD/tCO2e Rwanda NDC Implementation: Final Report Page C-7 Table C-6 Afforestation - assumptions Assumption Value Source Notes Rwanda Protective forests on This will be planted with Pinus spp. 10745+31695=42440 Restoration very steep and steep (21220ha) And Eucalyptus spp. ha Opportunities slopes (21220ha) assessment, 2014 Increase of C-stock in soil due to Increase in soil C-stock Johnson et al., 1996 afforestation estimated at 0.8 Mg C 0.8-1 Mg/ha/year due to afforestation in Lal et al., 2004 per ha per year, starting on 5th year from tree planting. MAI for the native species estimated Min annual increment 0.9-2 m³ /ha/year as 1.2m³ per ha per year, starting for native species from year 7 to be conservative. 10m³ /ha per year. MAI for Pinus, Alnus and Eucalyptus Mean annual Pinus data are 40 m³ for degraded lands estimated as 7 increment for /ha per year in IPCC, 2006 (Pinus) and 7 (Alnus) and 5.5 Eucalyptus and Pinus productive forests, (Eucalyptus) m³ per ha per year and on degraded soil no data for degraded , starting from year 7 forests Cost of establishment RWFA Forestry of new forest 450 USD / ha department plantation consultation Revised downwards from RWFA at 8 years :40 consultation of 60 and 200 t/ha at Harvest of firewood in tons/ha; at 18 years = 8th and 18th years for the reason of new forests 150 tons/ha degraded lands and steep slopes topography. Rwanda NDC Implementation: Final Report Page C-8 C-1.2.3 Rehabilitation and improved forest management Table C-7 Rehabilitation and improved forest management - project description Project title Rehabilitation and improved forest management The project aims to promote and perform improved forest Short description management in the existing forest plantations (a total of 273,779 ha) Overview Perform improved forest management on a total of 273,779 ha of Scope of project Pinus and Eucalyptus forests for better productivity Timing of project 20 years Mitigation effect will be through increase in carbon sink in tree Mitigation effect biomass after application of improved forest management to offset GHG mitigation GHG emissions. -1.039 Mt CO2e/yr (net increase over 2020-2030 period due to Estimated mitigation in 2030 harvesting in early years) Total project mitigation to -2.29 Mt CO2e (net increase over 2020-2030 period due to 2030 harvesting in early years) Costs are estimated in USD and include application of improved Description of costs forest management, training and follow up cost. The Project will result in better tree growth, thus increase in sinks, Description of benefits fuelwood and wood products, reduce soil erosion and have positive Cost-benefit analysis effect on climate resilience. NPV of project -209.8 M USD The economic impact will be in achieving more sustainable yields in Notes on economic analysis existing forests; contribute to agro system resilience to climate change. Abatement cost -91.81 USD/tCO2e Rwanda NDC Implementation: Final Report Page C-9 Table C-8 Rehabilitation and improved forest management - assumptions Assumption Value Source Notes Rwanda Eucalyptus forests: Area identified for Restoration The project targeted the full area 255,930 ha; Pinus restoration Opportunities of 273,779 ha forests: 17,849 ha assessment, 2014 Cost of existing forest Assumes 1,100 USD/ha as forest rehabilitation and 1,100 USD/ha rehabilitation cost management 7 years for Pinus Assumes 7 years for Pinus and 8 Harvesting periods: and 8 years for years for Eucalyptus from Thinning Eucalyptus planting to thinning Harvest at thinning (yr 7 for Pinus; yr 8 for 60 - 70 m³ /ha Assumes 60m³ for thinning Eucalyptus) RWFA Harvest at clear-cut consultation 200 m³ /ha Assumes 180 m³ /ha for clear-cut (year 18) Mean annual Improved management will increment of forest 9m³ /ha per year increase MAI up to 14 m³ /ha per plantations in Rwanda year (+5m³ /ha per year). Price of wood at 1m³ = 5,000 Frw - thinning (firewood) Price of sawn timber: 1m³ = 190,000 Frw - Pinus Price of sawn timber: 1m³ = 102,000 Frw - Eucalyptus Rwanda NDC Implementation: Final Report Page C-10 C-1.2.4 Efficient wood conversion and sustainable biomass management Table C-9 Efficient wood conversion - project description Project title Efficient wood conversion and sustainable biomass energy The project aims to expand the use of improved kilns for higher Short description charcoal production. Overview Scope of project Improved charcoal production Timing of project 11 years Mitigation effect will be through decreased use of wood to produce Mitigation effect required quantity of charcoal. GHG mitigation Estimated mitigation in 0.908 MtCO2e/yr 2030 Total project mitigation to 4.374 MtCO2 2030 Costs are estimated in USD and include trainings and monitoring on Description of costs kiln use (certification). The Project will provide wood economy for wood used for charcoal Description of benefits Cost-benefit analysis production. NPV of project 32.22 Million USD Notes on economic The economic impact will be achieved progressively with the analysis expansion of improved kilns use. Abatement cost -35.47 USD/tCO2e Rwanda NDC Implementation: Final Report Page C-11 Table C-10 Efficient wood conversion – assumptions Assumption Value Source Notes 120,000 tonnes per year was 120,000 tonnes of demand in Kigali (World Bank, charcoal from 2012a); Thus with 5% increase in Charcoal demand 850,000tons of World Bank, 2012a. production of charcoal, in 2020 the wood, 14% demand is estimated at 177,295 efficiency tonnes Unpublished unofficial Current wood supply 2,474,000 m³ data from new forest map - study, 2019 Link between economic 5% annual development of a increase in country with Girard, P., 2002 - charcoal use increased use of estimated charcoal over firewood 1 tonne of wood will produce Efficiency of additional 75kg of Girard, P., 2002 - improved kilns charcoal with improved kilns 100kg = Charcoal price RWFA consultation - 12,000frw Rwanda NDC Implementation: Final Report Page C-12 C-1.2.5 Sustainable forest and landscape management Table C-11 Sustainable forest and landscape management - project description Project title Sustainable forest and landscape management The project will focus on production and planting of trees Short description (indigenous and bamboo species) in areas identified as wetland perimeters and riparian buffer forests zones (a total of 80,100 ha). Overview Scope of project Tree planting 5 years for seedling production and planting, then maintenance and Timing of project follow up until the end of the project (2030). Production of sinks that will offset CO2 emissions in tree biomass Mitigation effect and soil. GHG mitigation Estimated mitigation in 0.596 MtCO2e/yr 2030 Total project mitigation 2.349 MtCO2e to 2030 Costs include seedling production and planting, site preparation and Description of costs training. The newly planted forests will generate sinks, protect soil from Description of benefits erosion or floods, some of land slides, produce wood and firewood. Cost-benefit analysis NPV of project -31.35 USD million The main economic benefit from newly planted forests will come Notes on economic after 2030 for greater part of the emission reduction, wood harvest, analysis and firewood source. Abatement cost 13.35 USD/tCO2e Rwanda NDC Implementation: Final Report Page C-13 Table C-12 Sustainable forest and landscape management – assumptions Assumption Value Source Notes Rwanda Restoration Riparian buffer 3152+19586 This will be planted with native tree Opportunities forests =22738ha species and bamboo. assessment, 2014 Rwanda Restoration This will be planted with native tree Wetland perimeters 57362 ha Opportunities species and bamboo. assessment, 2014 Survival rate estimated at 90%, RFRA, Forestry 1600 implying that 10% plants will be Tree density department plants/ha produced additionally to meet the consultation whole planned area cover. Increase of C-stock in soil due to Increase in soil C- 0.8-1 Johnson et al., 1996 in afforestation estimated at 0.8 Mg C stock due to Mg/ha/year Lal et al., 2004 per ha per year, starting on 5th year afforestation from tree planting. Mean annual MAI for the native species estimated 0.9-2 m³ increment for native IPCC, 2006 as 1.2m³ per ha per year, starting /ha/year for native species from year 7 to be conservative. Carbon content in 0.47 IPCC, 2006 - trees Below ground to 0.27 for above ground montane IPCC, 2006 - biomass ratio forests Cost of establishing RWFA Forestry new forest 450 USD / ha department - plantation consultation Harvest of firewood in bamboo Mean annual forests is estimated at 40% of annual increment for 5m³ IPCC, 2006 increment. Thus, harvest for firewood bamboo is estimated at 2m³ in bamboo forests C-1.3 Evaluation of options The options described above have been evaluated based on their emissions mitigation potential and economic viability. The estimated mitigation potential and abatement costs in 2030 are shown in the below table and marginal abatement cost curve (MACC). Rehabilitation and improved forest management is found to be the most cost-effective option, largely due to the benefits of wood harvesting occurring earlier on, when compared to other projects involving tree planting (e.g. afforestation). However, early wood harvesting removes much of the carbon stocking in the standing tree biomass and the net mitigation balance is calculated to be negative in the first ten years or so. Fruit tree planting project is found to be the second most cost-effective options and provides significant mitigation with carbon sequestration in tree biomass. Although fruit trees have Rwanda NDC Implementation: Final Report Page C-14 slower growth than timber plantations, they are not harvested for wood and thus progressively accumulate carbon in standing biomass. Efficient wood conversion using improved kilns is also found to be highly cost-effective, as well as having the highest overall estimated mitigation potential. Those projects involving tree planting (i.e. afforestation, sustainable landscape restoration, urban forests) have increased positive cost elements and require investments with their economic harvesting potential being either delayed (afforestation), minimal (landscape restoration), or neither (e.g. urban forests with recreational purpose). However, these projects provide an important basis for long-term mitigation strategies within the forestry sector and should be implemented subject to attracting funding. Table C-13 Mitigation potential and estimates marginal abatement costs, forestry 2030 Abatement cost in Mitigation in Mitigation option 2030 ($/tCO2e) 2030 (MtCO2e) Rehabilitation and improved forest management -91.81 * Agroforestry for fruits -42.29 0.49 Efficient wood conversion and sustainable -35.47 0.91 biomass management Agroforestry for wood 3.00 0.48 Agroforestry for fodder/stalks 5.14 0.13 Afforestation (new timber forests) 13.22 0.35 Sustainable forest and landscape management 13.35 0.60 Afforestation in urban forests 70.93 0.004 TOTAL mitigation, 2030 - 2.93 *Note: Forest rehabilitation is not included due to negative mitigation values through 2030 Rwanda NDC Implementation: Final Report Page C-15 Figure C-2 Marginal abatement costs of mitigation forestry measures in Rwanda, 2030 Note: Forest rehabilitation is not included due to negative mitigation values through 2030 All of the forestry projects have both a beneficial climate change mitigation and adaptation effect, and each of the proposed mitigation projects can also be implemented as part of national adaptation responses within the NDC. For example, the development of new forests or sustainable management of existing forests and their biomass will lead to increased tree cover, growth and/or productivity and thus improve climate resilience as trees offset solar insolation and create microclimate with cooler and milder environment. Rwanda NDC Implementation: Final Report Page C-16