Geographic Hotspots For World Bank Action on Climate Change and Health Investing in Climate Change and Health Series Geographic Hotspots for World Bank Action on Climate Change and Health Investing in Climate Change and Health Series © 2017 International Bank for Reconstruction and Development/The World Bank  The World Bank  1818 H St. NW  Washington, DC 20433  Telephone: 202-473-1000  Internet: www.worldbank.org  The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent.  The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.  Rights and Permissions  The material in this work is subject to copyright. Because the World Bank encourages dissemination of their knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H St. NW, Washington, DC 20433, USA; fax: 202-522-2422; email: pubrights@worldbank.org. This document is part of the “Investing in climate change and health” series, which aims to enable management and task teams with the tools and resources necessary to improve World Bank action on climate change and health. Current documents in this series include: • “World Bank approach and action plan for climate change and health” • “Geographic hotspots for World Bank action on climate change and health” • “Climate-smart healthcare: low carbon and resilience strategies for the health sector” Acknowledgements This report is a joint production of the World Bank Group Health Nutrition and Population Global Practice and Climate Change Cross- Cutting Solutions Area. Gary Kleiman, Timothy Bouley, Montserrat Meiro-Lorenzo and Hui Wang authored the work, with key advice and input from Patrick Osewe, Tamer Rabie, Richard Seifman, and Sanjay Srivastava. Katie McWilliams built the maps. The ND-GAIN Country Index group of the University of Notre Dame provided the underlying vulnerability data upon which this study was produced and Chris Sall of the Institute for Health Metrics and Evaluation (IHME) provided global burden of disease data. The Nordic Develop- ment Fund (NDF) provided resources, and the team is indebted to the goodwill and support of the NDF team, particularly Pasi Hellman, Martina Jagerhorn, and Leena Klossner. The concept and impetus for this work originated at a meeting of the Prince of Wales’ Char- ity Foundation’s International Sustainability Unit, convened by HRH The Prince of Wales and with support from Justin Mundy, Eric Chivian, Andy Haines, Hugh Montgomery, and Laura Partridge. Overall guidance within the World Bank was provided by John Roome, Tim Evans, James Close, Olusoji Adeyi, and Stephen Hammer. Tegan Blaine (US Agency for International Development), Joy Guillemot (World Health Organization/World Meteorological Organization), and Urvashi Narain provided peer-review. Important contributions were also made by Sameer Akbar, Perpetual Boateng, Laura Bonzanigo, Shun Chonabayashi, Jane Ebinger, Paula Garcia, Yin Qiu, and Kanta Rigaud. Editing services were provided by Robert Reinecke. Formatting and graphic development were undertaken by Shepherd Incorporated. iii Contents Foreword vii Acronyms ix Executive Summary xi Introduction 1 1. Health Impacts Due to Climate Change and Its Drivers 3 The Scale and Scope of Health Impacts Due to Climate Change and Climate Drivers 3 How Climate and Climate Drivers Affect Health Outcomes 4 Drivers of Climate Change and Their Sources 8 2. Hotspot Identification Methodology 11 What Is a Climate Change and Health “Hotspot”? 11 Identification of “Impact” Hotspots 11 Identification of Emissions Hotspots 14 Caveats and Limitations of This Analysis 15 3. Hotspots 17 Assessing “Impact” Hotspots Associated with Climate Effects 17 Country Characterization Using ND-GAIN Indexes 18 Hotspots Associated with Emissions, the Drivers of Climate Change 20 4. What Can Be Done: Adaptation and Mitigation 31 Adaptation 31 Mitigation 33 Geographic Analysis of Potential Reduction in Air-Pollution Health Impacts 34 Multiple Benefits of Mitigation 35 Conclusion 37 References 39 Typology of Pollutants That Drive Climate Change, Annex A.  Health Impacts, or Both 43 Annex B. Geographic Analysis of Climate Drivers 45 Annex C. Health Driver Mapping Based on Burden of Disease 49 Adaptation Approaches to Manage Current and Projected Annex D.  Risks of Climate Change to Health 51 v Foreword Climate change is a risk multiplier that threatens to unravel decades of development gains. Among the most critical and direct risks to humans is the impact of climate change on health. Heat stress will worsen as high temperatures become more common and water scarcity increases; malnutrition, particularly in children, could become more prevalent in some parts of the world where droughts are expected to become more frequent; and water- and vector-borne diseases are likely to expand in range as conditions favor mos- quitoes, flies, and water-borne pathogens. Worse still, these threats will be greatest in regions where the population is most dense, most vulnerable, and least equipped to adapt, pushing more people in poverty and reinforcing a cycle of environmental degradation, poor health and slow development. Addressing these climate-associated health risks is critical. Alongside risk, there is opportunity. Responses to climate change have unearthed significant potential for improving both human health and the environ- ment. Low carbon hospitals can draw upon the many advances made by the energy sector in developing cleaner and renewable resources. Pharmaceutical supply chains can benefit from more efficient and less polluting transport. And food and nutrition can be improved by the advances achieved through climate- smart agriculture. Climate change challenges are multi-sectoral and so too are the solutions. At the World Bank Group, we are tackling different dimensions of these environment and health threats in different ways. For example, the ‘Pollution Management and Environmental Health’ Trust Fund addresses air pollution, toxic land pol- lution, and marine litter. Work on Climate-Smart Agriculture aims to sustainably increase food productivity and human well-being in a changing climate. We are putting in place a new operational framework for strengthening human, animal, and environmental health systems in response to disease threats. And within the health sector, we have made Universal Health Coverage core and increasingly considerate of climate change and resilience. At the World Bank Group, we work with the broader development community to create solutions that can respond to and reduce these risks. Our work aligns with other global efforts aimed at improving envi- ronmental and human health, such as the work of the Climate and Clean Air Coalition, Global Alliance for Clean Cookstoves, One Health and Planetary Health communities, and broader efforts to achieve the Sustainable Development Goals. vii G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Along with developing approaches and interventions, identifying geographic “hotspots” will help target resources to maximize impact and minimize risk. This report draws on the latest literature to highlight those regions and countries most likely to be adversely impacted and where action is most needed. While it is not a comprehensive resource for climate and health geography, the report creates entry points for discussions with country-level stakeholders. The work presented here is expected to assist the development community in further mainstreaming climate change and health into development operations so that we may address the emerging needs of vulnerable communities, particularly women and children. We are committed to working with development practitioners around the world on climate change and health, capitalizing upon associ- ated opportunities and technologies, and contributing to the overall goals of ending extreme poverty and boosting shared prosperity. James Close Olusoji Adeyi Director Director Climate Change Group Health, Nutrition, and Population World Bank World Bank viii Acronyms AIDS Acquired Immune Deficiency MDR-TB Multi Drug Resistant Tuberculosis Syndrome NDGAIN Notre Dame Global Adaptation BEM Building Energy Management Initiative BREEAM British Research Establishment Ltd— NHS National Health Service (UK) Environmental Assessment Method N2O Nitrous Oxide CCSA Cross-cutting solutions area PAHO Pan American Health Organization CFL C  ompact Fluorescent Lightbulb QALY Quality Adjusted Life Year CO2 Carbon Dioxide SE4All Sustainable Energy for All CO2e Carbon Dioside equivalent SDG Sustainable Development Goal EDGE Excellence in Design for Greater SMART Specific, Measurable, Achieveable, Efficiencies Relevant, Time-bound GAVI Global Alliance for Vaccines and tCO2 Tons of Carbon Dioxide Immunizations UNEP United Nations Environment GDP Gross Domestic Product Program GHG Greenhouse Gases UNFPA United Nations Population Fund GP Global Practice (previously UN Fund for Population HCWH Healthcare Without Harm Activities) HFC Hydrofluorocarbon UNHCR United Nations High Commissioner HIV Human Immunodeficiency Virus for Refugees HNP Health Nutrition and Population UNICEF United Nations Children’s Emergency (World Bank Global Practice) Fund HVAC Heating, Ventilation, & Air UNITAID Not an acronym, this is a global Conditioning health initiative, hosted by WHO to IPCC  Intergovernmental Panel on Climate tackle deficiencies in management of Change HIV/AIDS, Tuberculosis and Malaria kBTU/sf/yr Kilo (x1000) British Thermal Unit UNOPS United Nations Office for Project per Square Foot per Year Services LED Light Emitting Diode USAID United States Agency for LEED Leadership in Energy & international Development Environmental Design WHO World Health Organization MAC Marginal Abatement Curve MATCCH Mobilizing Action Toward Climate Change and Health ix Executive Summary Climate change and the pollutants associated with it1 have impacts across many dimensions of life. Importantly this includes the health of those who are living in areas most vulnerable to its effects and who are subject to the various forms of air pollution that help drive climate change in the first place. Accordingly, countries should be encouraged to place health improvements at the core of their efforts to address climate change and its drivers, based on the best estimates of how they or their regions are being impacted now and will be in the years ahead. Without proactive, integrated planning, the impacts of climate change will fall disproportionately on the poorest people worldwide, further hampering efforts to alleviate poverty, provide universal health coverage, and ensure shared prosperity. Climate impacts on population’s health can be direct (heat waves, floods), or mediated through natural systems (air quality, water and vectors), or socioeconomic systems (food production, health care, poverty). Naturally, climate change and the drivers behind it affect countries differently, and each country will also differ in terms of its readiness and capacity to cope with these developments and implications for national health. The question that has become more pressing is which countries are most vulnerable to climate change and its drivers from a health perspective and what they could do to mitigate or adapt in the face of this challenge. This report addresses this need by examining the latest climate change research and evaluating the strength of national health systems worldwide to provide a guide to those countries that would most benefit from immediate efforts to ensure that health considerations are at the forefront of climate change adaptation responses and mitigation measures. We have drawn upon recognized vulnerability indices related to health outcomes, data outlining the disease burden linked to pollution, and proxies that measure country health systems’ performance or readiness to cope with increased burden of disease. The objective is not to rank countries, but rather to provide a ready guide to those most vulner- able. The World Bank Group and others can then prioritize their efforts to help countries mitigate the drivers of climate change (thereby alleviating the associated health impacts of air pollution) or adapt to the impacts of climate change in their respective development policies and programs. It is important to recognize that climate change and the emissions that promote it are not limited by national borders or regional boundaries. However, the World Bank and others work with national governments to help them adapt and mitigate impacts, requiring data provision and analysis on a country basis. It should also be noted that threats can vary within countries, and indeed climate change and emissions might well not even rank among a country’s most significant sources of death and disease in the face of other health threats. As such, this work will inform the World Bank’s approach to health-related aspects of climate change across its work with countries, including through a proposed 5-year action plan to integrate 1  Climate drivers that affect health outcomes include fine particulate matter (including black carbon which is a strong warming agent and other components of aerosol particulate that may offset a portion of that warming) and methane, which contributes to the formation of ground-level ozone or smog. xi G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth health-related climate considerations in its strategies and invest- Southeast Asia is also at risk for climate change-influenced food- ments. The Bank will be able to bring its combined strengths in and waterborne diseases while this region and Sub-Saharan Africa, analysis and operations to those countries seeking an integrated East Asia, and the Pacific are vulnerable to food supply problems approach to reduce the health impacts of climate change and its associated with climate change. drivers that encompasses health, transport, energy, agriculture, Judging which individual countries might be at greatest risk environmental management and economic sectors. from climate change-related health problems is complicated by the fact that many key factors do not map neatly to country borders; Climate Change, Its Drivers, e.g., rising seas or heat impacts. However, the World Bank has and Their Impacts on Health used the “ND-GAIN” country index to best assess the risks, as it takes into account a country’s vulnerability across a number of There is mounting evidence that climate change is and will continue measures that are updated regularly, including ecosystem services, to negatively impact health in many countries. Rising tempera- food, health, human habitats, infrastructure, and water. tures bring heat stress and encourage the spread of vector-borne By combining a number of the ND-GAIN measures to judge diseases. A rising number of more extreme weather events—such a country’s vulnerability to health impacts as well as its relative as storms and torrential rains—cause death and injuries, foster readiness to cope with such problems, a picture emerges of those water-borne diseases, and destroy crops, greatly increasing food countries that should prioritize their efforts to adapt or mitigate insecurity and the risk of undernutrition. The emissions that these impacts, possibly with help from the World Bank or others. contribute to climate change are already degrading air quality, The group of hotspots that emerges as being most at risk from causing respiratory and cardiac problems and certain cancers, both direct exposure to climate change as well as its effects on killing more than 5.5 million people each year. disease includes several Africa nations (including Benin, Burkina Highly conservative estimates from WHO suggest that, compared Faso, Burundi, Central African Republic, Chad, Congo, Democratic to projections without climate change for the years between 2030 Republic of Congo, Djibouti, Eritrea, Ethiopia, Gambia, Ghana, and 2050, more than 38,000 additional people are expected to die Guinea, Guinea-Bissau, Liberia, Niger, Rwanda, Sao Tome and of heat exposure, 48,000 due to diarrhea, 60,000 from malaria, and Principe, Sierra Leone, Somalia, Togo, and Zambia), a few in the 95,000 from childhood undernutrition, a total of 251,000 deaths Pacific (Micronesia, Papua New Guinea, Solomon Islands, Timor- each year for only three diseases. Analysis suggests that the added Leste, and Vanuatu), and Yemen in the Middle East. Many others costs of coping with malaria, diarrheal illnesses, and malnutrition are particularly vulnerable from either direct exposure or disease alone could cost between US$4–12 billion per year. Natural disas- impact from climate change, but not both. ters from weather-related causes pose additional costs. Data for developing countries are sparse but climate-related disasters in the Broadening the Analysis US likely cost around US$14 billion over a single 10-year period. to Include “Emissions” Hotspots Identifying the Countries Most at Risk Countries most at risk can be viewed as either climate “impact” for Climate Change Impacts on Health hotspots, which are those most likely to experience a significant change in the climate-sensitive burden of disease, and climate Climate-sensitive health impacts can be traced to certain geog- “emissions” hotspots, which refers to those most vulnerable to raphies: tropical and equatorial areas are more sensitive to heat emission-sensitive disease associated with exposure to air pollution increases as are cities, as these magnify heat impacts. Accordingly, co-emitted with key drivers of climate change (i.e., greenhouse parts of South Asia are seen to be most at risk in this regard, as gases or GHGs and short-lived climate pollutants). Those countries are parts of Sub-Saharan Africa, particularly inland populations listed above are climate-sensitive “impact” hotspots. with already scarce water supplies. People living on flood plains, “Emission” hotspots that are already experiencing a high burden small catchments, or on coastlines are also at risk from floods and of disease from ambient air pollution (as opposed to household air storms and can include those living in Asia, Africa, small island pollution, produced by residential cooking or heating) include Azer- states, and Central and South America. baijan, China, Mauritania, Tajikistan, Turkmenistan, and Uzbekistan. Regions at risk for vector-borne diseases associated with climate Hotspots for household air pollution include Haiti, Laos, Nepal, Papua shifts include Africa and Southeast Asia (malaria), Asia-Pacific New Guinea, Philippines, Solomon Islands, Sri Lanka, Timor Leste, (dengue), temperate parts of Europe, Asia, and North America Vanuatu and 22 countries in Sub-Saharan Africa. Afghanistan, Bangla- (Lyme disease), and Russia, Mongolia, and China (encephalitis). desh, Cambodia, India, Myanmar and North Korea suffer from both. xii E x e cu ti v e S u mma ry Nearly all of these hotspot countries are estimated to have need to be tailored to each country’s circumstances, geography, challenges with their health system readiness to address the health and preparedness, but the World Bank is emphasizing a “climate- impacts from air pollution. smart” strategy that aims to improve on the one hand the health system, and on the other those systems that mediate a good part Adaptation and Mitigation Efforts of the heath impact of climate change such as access to energy Can Save Millions of Lives and clean water, and urban development. Emission reduction strategies likely represent the most effective Positive change is possible. It has long been understood that steps mitigation steps that would benefit both the climate and health can be taken to reduce the impacts of climate change in many conditions in vulnerable countries. By some estimates, more than fields, including health outcomes. Most of the identified hotspots 2.4 million lives could be saved each year from 2030 by reducing are poorer nations, often insufficiently prepared to reduce their emissions of short-lived climate pollutants, such as black carbon vulnerability through proper adaptation and emission reduction and methane. (climate mitigation) measures. As such, the World Bank can play a Climate change, its drivers, and its impacts are issues that significant role—both through financial and technical assistance—in require solutions beyond a single sector, location, country or region helping countries take steps to adapt to or mitigate climate change and as such the World Bank can play a significant part in helping impacts on the health of their people. countries confront these challenges. The Bank not only has the On the adaptation side, better preparedness in Bangladesh, for financial and technical resources to provide direct assistance, it can example, has helped reduce the casualties from cyclones and severe also bring together those players with additional expertise to help storms in recent decades. To fight the threat posed by malaria during a country strengthen its planning and response to climate-related lengthening wet seasons, countries could extend their insecticide health impacts. This paper represents an effort to identify those spraying efforts or broaden their reach to match the expansion countries and regions that should be viewed as priority hotspots of breeding areas fostered by climate change. Approaches will by the Bank and its allies as it seeks to target its support. xiii Introduction In the last 5 years, the number of voices calling for stronger international action on climate change and health has increased,2 as has the scale and depth of activities. But current global efforts in climate and health are inadequately integrated. As a result, actions to address climate change—including World Bank Group investment and lending—are missing opportunities to simultaneously promote better health outcomes and resilience. Accordingly, the World Bank Group has developed a 4-year action plan and new approaches to integrate health-related climate considerations into World Bank sector plans and investments. This “Approach and Action Plan” seeks to stimulate and support greater attention to both the health dimensions of climate-smart investments across sectors and to climate risk in health sector knowledge products and operations. An initial step—presented here—is the use of existing indicators to identify countries where climate change, or exposure to drivers of climate change (i.e., kinds of air pollution), are expected to most significantly alter the burden of disease and expose vulnerabilities in existing health systems. While not based on primary analysis, this paper will serve as an initial filter, focusing the approach on spe- cific countries or “hotspots” where World Bank operations can maximize positive health outcomes in the face of climate change and its drivers, and to prioritize the approach on the basis of vulnerability and exposure. The analysis presented in this work will ultimately be combined with sector analyses in additional analytic work to further specify approaches to climate-health action. This paper begins by identifying the health impacts that are being felt today and that are projected to worsen in the future without efforts to ensure health considerations are central to any and all cli- mate change adaptation and mitigation measures. Chapter 1 includes an outline of the scope of health impacts from climate change and its drivers, the means of transmission, and a description of the drivers of climate change, and their sources. What is needed to ensure that health is put at the forefront of climate change action is a guide to those countries most vulnerable to increasing numbers of deaths and greater illness from climate change, and co-pollutants from GHG sources, referred to here as climate drivers. Chapter 2 describes the methodology used to identify these nations and determine their preparedness for coping with these impacts. Chapter 3 identifies hotspot countries based on this analysis, and narrows the focus to those countries that are both most likely to bear the brunt of a greater burden of disease and death from climate change and climate drivers, and that are the least ready to cope. Coping mechanisms—through mitigation and adaptation measures—are outlined in Chapter 4, as are the multiple benefits that can be expected from multi-sector, concerted efforts to address health impacts from climate change, and its drivers. 2  Climate change has been called both the ‘biggest global health threat’ and the ‘greatest global health opportunity” of the 21st century (Costello, 2009; Watts, 2015). The Director General of the World Health Organization (WHO) has called climate change “the defining global health threat of the 21st century,” and the Executive Secretary of the United Nations Framework Convention on Climate Change has noted “a climate agreement is a global health agreement.” 1 Chapter 1 Health Impacts Due to Climate Change and Its Drivers The Scale and Scope of Health Impacts Due to Climate Change and Climate Drivers Climate change complicates the search for solutions to almost all development challenges and threatens to erase the many development gains of the past several decades. There is clear and mounting evidence that health outcomes will—in large part—be negatively impacted by climate change. Heat stress is seen increasing with higher temperatures. A growing number of climate-related extreme events such as floods and torrential rains could increase the incidence of waterborne diseases and affect crops, increase food insecurity and, potentially, undernutrition. Rising sea levels affect populations of entire islands and coastal areas. Rising average temperatures can open new areas to the transmission of certain vector-borne diseases (i.e., those transmitted by carriers such as insects). These effects are detailed below. The emissions that drive climate change are also associated with various public health threats through air quality impacts that are linked to respiratory and cardiac threats, as well as certain cancers. These impacts will be greatest in the poorest countries and regions where the populations are most dense, most vulnerable, and least equipped to adapt. Here, health and malnutrition hold the potential for broad intergenerational impacts; a whole generation of youth risks becoming disenfranchised and held back in school (World Bank, 2014). Moreover, in general, poor and disenfranchised groups, women, elderly and children, are most at risk (Smith et al., 2014; World Bank, 2012, 2013). Given the complexity of social and environmental factors that influence disease and health outcomes, the precise extent of these impacts is difficult to establish, though estimates from the most informed health sources expect climate change will increase the incidence of several diseases. The World Health Organization (WHO), for example, estimated in the early 2000s that climate change was already account- ing for an additional 150,000 deaths a year (WHO, 2004). Updated data suggest that, compared to a future without climate change (for the year 2030), an additional 38,000 deaths are expected due to heat exposure in elderly people, 48,000 due to diarrhea, 60,000 due to malaria, and 95,000 due to childhood undernutrition3 (WHO, 2014b). This will correspond to an additional 250,000 deaths per year from heat exposure, undernutrition, malaria, and diarrheal disease due to climate change each year from 2030 through 2050. This estimate is low, however, because it does not include all climate-sensitive health impacts, such as pollution, injuries, non-malarial infectious diseases, and others for which projection data are lacking (WHO, 2014b). This additional burden of disease comes with significant economic impacts. One study estimated additional costs associated with climate-change related cases of just three sets of diseases (malaria, diarrheal illnesses, and malnutrition) to be between US$4–12 billion in 2030 under a 750 parts per 3  Following this period, there is a projected decline in child mortality from malnutrition and diarrheal disease between 2030 and 2050. Conversely, over the same period, deaths related to heat exposure (over 100,000 per year) are projected to increase. 3 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Table 1.1: Projected excess costs (US$, millions) to manage climate change-related cases of select climate-sensitive diseases for two scenarios relative to baseline. Scenario Diarrheal Diseases Malnutrition Malaria   mid high Mid HIgh Mid High S550 1,706 6,024 53.9–71.5 112.9–149.9 1,573–2,145 3,236–4,515 S750 1,983 6,814 81.3–107.9 162.5–215.6 1,928–2,691 3,994–5,573 UE 2,731 9,010 62.2–82.6 125.2–166.2 3,059–4,269 6,293–8,781 Source: Ebi, 2008. million (ppm; business as usual) scenario. Costs increase with There is a significant economic cost associated with the air greater climate change as illustrated in Table 1.1 (Ebi, 2008). pollution-related burden of disease. A recent study by WHO and Separate work suggests there are significant costs associated the Organization for Economic Co-operation and Development with disaster-related health impacts as well. Though little data (OECD, 2015) estimated that in Europe alone, 600,000 annual has been produced on this topic for the developing world, it premature air pollution-related deaths cost US$1.6 trillion. was estimated that climate-related disasters have already caused Separately, OECD (2014) found that air pollution morbidities US$14 billion in health-related costs over a 10-year period in the and mortalities correspond to US$1.7 trillion in costs annually US alone (Knowlton, 2011). Other research has estimated that in OECD countries, US$1.4 trillion in China, and US$500 billion impacts associated with labor productivity losses due to excess in India. A significant portion of these deaths can be avoided heat (correlating to health stress) might be as much as 11–20 per- with stringent climate mitigation, given air pollution’s role as a cent by 2080 in heat-prone regions like Asia and the Caribbean. co-emitted by-product of fossil-fuel combustion. The remaining This results in billions of dollars in associated impacts from labor deaths could also be averted through mitigation of black carbon losses and direct health impacts (Kjellstrom, 2009). Avoiding and methane, the so-called short-lived climate pollutants or SLCPs these health impacts (and limiting global warming to 2°C) can (Rogelj et al., 2014). yield economic savings that exceed the US$1.5–2 billion per year outlaid for health sector adaptation and can begin to approach How Climate and Climate Drivers Affect the estimated US$70–100 billion per year of overall adaptation Health Outcomes investment needed by 2050 (World Bank, 2010). Importantly, not all climate-related health impacts of concern Figure 1.1 shows the spectrum of climate-sensitive health impacts will occur in the future. Along with some direct impacts, the emis- and correlates them to environmental variables, sensitive to a cycle sions that drive climate change are largely co-emitted by the same of broader climatic change. Such a framework can be useful for sources that are responsible for air pollution. WHO has recognized quantifying health impacts, identifying disease-specific or envi- the large and significant role that ambient air pollution (AAP) and, ronmental interventions, or for interacting with health specialists in the developing world, household air pollution (HAP) play in (and others) comfortable with health impacts and outcomes. To increasing morbidity and mortality around the globe (WHO, 2014a). meet the overarching goal of the World Bank Climate and Health The most recent Global Burden of Disease estimates suggest that Approach Paper, a framework is needed that will go beyond AAP and HAP combined were killing more than 5.5 million people merely identifying health impacts to address the development of annually by 2013 (GBD 2013 Risk Factors Collaborators, 2015). solutions. At the same time, it is essential to create a framework Of the 5.5 million total premature deaths per year—more deaths that identifies the pathways by which climate change results in than those attributable to malaria or tuberculosis—2.9 million health impacts. are due to exposure to household smoke from cooking, which In March 2014, the Intergovernmental Panel on Climate Change constitutes the fourth ranked risk factor for disease in developing (IPCC) released its Fifth Assessment Report, including a chapter countries (WHO, 2014a) and is a major source of black carbon, a on health and climate change (Smith et al., 2014). The authors short-lived but powerful driver of a warmer atmosphere. Tens of describe three pathways through which climate impacts health: millions more suffer from related, preventable diseases, including 1) a direct exposure; 2) indirect exposure, in which health impacts pneumonia (which predominantly affects children), lung cancer, are mediated through environmental and ecosystem changes; and cardiovascular disease, stroke, and chronic obstructive pulmonary 3) another indirect pathway mediated through societal systems disease, which includes emphysema and bronchitis (WHO, 2014a). (e.g., food and water distribution systems). 4 H ealt h Impact s Du e to C li mat e Ch ang e a n d It s D riv er s Figure 1.1: The ways climate change can affect health; all are preventable. Impact of climate change on human health Asthma, Injuries, fatalities cardiovascular disease Severe Malaria, dengue, Heat stress, Air pollution weather encephalitis, hantavirus, cardiovascular failure Rift Valley fever U ERAT RES Vector-borne Heat EMP W diseases T G EA IN TH RIS ER EXTREME Water and Malnutrition, food Allergies Respiratory allergies, diarrhea, harmful supply LS poison ivy algal blooms VE S LE A RISING SE Waterborne Mental health diseases Environmental refugees Cholera, Anxiety, despair, cryptosporidiosis, depression, campylobacter, post-traumatic stress Forced migration, leptospirosis civil conflict Source: Adapted from J. Patz. National Oceanic and Atmospheric Administration (https://toolkit.climate.gov/image/505). In Figure 1.2, the green box indicates the moderating influences it does not adequately address the health impacts of exposure to of local environmental conditions on climate change exposure the drivers of climate change and co-emitted air pollution. Fig- pathways in a particular population. The gray box indicates the ure 1.3 provides a more comprehensive picture in that it includes extent to which factors as background public health and socioeco- pathways through which health-relevant drivers of climate change nomic conditions, and adaptation measures moderate the actual are also determinants of health and health outcomes. health burden produced by the three categories of exposure. The The health impacts from emissions are underway now and, green arrows at the bottom indicate that there may be feedback barring change, they will increase in the coming years as the mechanisms—positive or negative—between societal infrastruc- exposure pathways of climate change add to the current exposure ture, public health, and adaptation measures and climate change to air pollution. Ultimately, the overall impact will depend on itself (Smith et al., 2014). While this provides a framework for emissions scenarios, population growth, and other biophysical considering the exposure pathways of climate impacts on health, and socially mediated factors. 5 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 1.2: Exposure pathways by which climate change affects health. Mediating factors Environmental Social infrastructure Public health capability conditions and adaptation Direct exposures • Geography • Warning systems • Baseline weather • Flood damage • Socioeconomic • Soil/dust • Storm vulnerability status • Vegetation • Heat stress • Health and nutrition • Baseline air/water status quality • Primary healthcare CLIMATE CHANGE Indirect exposures HEALTH IMPACTS Mediated through natural • Precipitation systems: • Undernutrition • Heat • Allergens • Drowning • Floods • Disease vectors • Heart disease • Storms • Increased water/air • Malaria pollution Via economic and social disruption • Food production/ distribution • Mental stress Source: Smith et al., 2014. Despite its narrower consideration of only one aspect of air with the drivers of climate change and is classified in terms of pollution’s impact on health,4 we adopt the three-pathway IPCC sources that contribute to ambient air pollution versus those that model (over a more health-centric approach, as illustrated in contribute to household air pollution. Figure 1.1) to classify various health impacts of climate change for this analysis. In doing so, we acknowledge the importance of Direct Pathway to Health Impacts understanding discrete health endpoints, but opt for a classifica- tion that highlights the linkage between environmental drivers of This pathway refers to direct illness and death due to exposure to disease and vulnerability and indices that point toward approaches extreme weather events in which climate change may play a role. to adaptation and mitigation. In addition, we classify climate These include effects of high heat (including “heat exhaustion” drivers by source type and their impact on health as recognized and heat waves), floods, storms, etc. by the World Health Organization. The IPCC classification (Smith et al., 2014) includes: the direct Heat and Cold-Related Impacts pathway of climate change impact on health; an ecosystem-mediated The association between hot days and mortality is well-defined. pathway for health impacts; and a human-institution mediated IPCC has concluded that it is very likely there has been a greater pathway for health impacts. Co-emitted air pollution is treated number of hot days and nights on account of climate change, separately to better account for the health impacts associated likely correlating to mortality from heat waves. This rise in temperatures means, however, that minimum temperatures have increased, potentially lowering winter mortality rates. While 4  Changes in air quality due to warmer temperatures and changing meteorological this may be the case, research suggests that the detriments of patterns are addressed by the IPCC framework. The framework does not direct air quality health impact from pollution that is co-emitted with the drivers of climate heat extremes outweigh the benefits of fewer cold days (Smith change; i.e., both greenhouse gases and short-lived climate pollutants. et al., 2014). 6 H ealt h Impact s Du e to C li mat e Ch ang e a n d It s D riv er s Figure 1.3: Links between greenhouse gas emissions, climate change and health. Greenhouse gas emissions Climate change Ocean acidification Raised average and extreme temperatures Other air pollutants (e.g., particulates) Altered rainfall patterns Sea-level rise Extreme weather Flood Heatwaves Drought Fire Social mediating factors Reduced fishery Reduced Loss of habitation and aquaculture physical work productivity capacity Poverty Mass migration Reduced Biodiversity Ozone Particulate Pollen agricultural loss, ecosystem increase pollution allergenicity productivity collapse, pests burden Violent conflict Bacterial diarrhea Other social determinants of health Impact on Cardiovascular Respiratory Harmful Vector-borne Undernutrition mental health disease disease algal blooms disease Source: Watts, 2015. Floods and Storms waterborne diseases caused by warmer conditions and increased These are particularly important events, given they are the most precipitation and runoff. frequent types of natural disaster, with significant correlation to climate fluctuations. Floods and storms can lead to many socially- Vector-Borne Diseases mediated health impacts following disaster events: malnutrition, These diseases, transmitted by biting or blood-sucking insects, are disease, and mental illness. However, available data usually refer among the most closely studied in relation to climate change, given to direct health impacts, typically only injuries and mortality their known sensitivity to weather and climatic factors. Malaria (Smith et al., 2014). and dengue fever are perhaps the two most significant diseases, with nearly 300 million cases combined each year (WHO, 2009). Ecosystem-Mediated Pathway There are also many tens of thousands of cases annually of Lyme disease, tick-borne encephalitis, hemorrhagic fever, and others. This applies to illnesses and deaths due to such as shifts in pat- The sensitivities of these diseases to specific climatic variables terns of disease-carrying mosquitoes and ticks, or increases in (temperature, precipitation, humidity) is nonlinear and variable 7 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth by species and transmitted disease. Nevertheless, confidence the greater share of attributable mortality: 80 percent in the case levels are high that the incidence of many of these diseases will of ambient air pollution and 60 percent in the case of household increase as the climate changes, particularly in their endemic air pollution, followed by chronic obstructive pulmonary disease, regions (Smith et al., 2014). lung cancers and pneumonia (WHO, 2014c). The concept of air pollution and its importance for development is not new and the Food and Waterborne Infections World Bank’s Environment Global Practice has a strong history Humans are exposed to these pathogens by ingesting contaminated of engagement with client countries on improving air quality, as water or food or through contact while swimming, bathing, or outlined in Box 1.1. other environmental contact with orifices or open wounds. Cli- Changes in climate can also result in incremental changes in mate may affect the growth of these organisms, resulting in higher air quality through, for example, increased stagnation, warmer environmental concentrations and increasing likelihood that they temperatures, increased humidity and other meteorological fac- will infect humans. Examples include Vibrio cholerae, salmonella, tors that control the secondary formation of ground-level ozone campylobacter, and harmful algal blooms. Most infection rates are and fine particle matter (Jacob & Winner, 2009). However, emis- associated with higher temperatures and precipitation, which can sions constitute a far greater determinant of both ambient and cause agricultural runoff leading to water contamination (Smith et al., 2014). Many studies project an increased correlation of diarrheal diseases at regional and country levels in a future with Box 1.1: The World Bank and Air greater climate change. Quality Initiatives around the World Air Quality Colombia. Analytical work conducted by the World Bank in Acute air pollution episodes from wildfires and aeroallergens are Colombia included a study of the costs of environmental degrada- projected to worsen with warmer temperatures and will have an tion, which estimated that outdoor air pollution was responsible for effect on asthma and allergic respiratory diseases (Beggs, 2010). approximately 6,000 premature deaths a year, equal to a cost of We address the health effects of air pollution through a separate approximately 0.8 percent of GDP. This work highlighted the need exposure pathway shortly in this chapter. for revising air quality standards and resulted in a broad public debate, which was taken up by politicians and led to development Pathway Mediated through Societal Systems of a more stringent Fuel Quality Law after 13 failed attempts at revi- and Human Institutions sion over the course of a decade. Mongolia. Due to famines and hunger among nomads This includes death and sickness from altered systems created by throughout the vast lands of the Mongolian steppe, extensive immi- humans. These include agricultural production and distribution, gration is occurring into the Ger areas around Mongolia’s capital, Ulaanbaatar, almost tripling its population. It is estimated there have urban environments and food insecurity, stress and undernutri- been 1,600 premature deaths a year in Ulaanbaatar, largely attribut- tion and violent conflict caused by population displacement, able fine particle pollution from low-efficiency, high-polluting heaters economic losses due to widespread “heat exhaustion” impacts and stoves in these areas; particle concentrations in the city have on the workforce, or other environmental stressors. been up to 35 times WHO-recommended standards. The World Bank undertook a comprehensive air quality management study Undernutrition for Ulaanbaatar that has led to a program that replaces ovens in Food, being a function of agriculture, is both closely connected all 170,000 Ger households. This, combined with other abatement to climate change and to socioeconomic factors that influence initiatives, has resulted in the gradual return of clean, clear air with production. From the extensive modeling of climate impacts on fewer reports of deaths and illness. agriculture, it is clear that many regions are susceptible to food China. In China, the World Bank—in cooperation with the system impacts (Smith et al., 2014). Ministry of Environmental Protection—prepared a report designing a national program to reduce two types of airborne pollution (known Drivers of Climate Change as PM10 and PM2.5) in all 655 cities. In 2012, China’s State Coun- cil authorized new air quality regulations aiming for a 30 percent and Their Sources reduction in PM10 and establishing new standards for PM2.5. New standards went into effect on January 1, 2016 and each of the 655 Air pollution is a risk factor for several causes of death and is the cities in China are now preparing plans for how to achieve these leading environmental contributor to the global burden of disease. targets on a staggered time schedule. Cardiovascular and cerebrovascular causes of death account for 8 H ealt h Impact s Du e to C li mat e Ch ang e a n d It s D riv er s household air pollution levels relative to climate change impacts a variety of pollutants in a combined exhaust mixture (see on meteorological factors. While the health sector is not the larg- Box 1.3). In addition, some sources are natural in origin (e.g., est source of air pollution or associated drivers of climate change, sea salt aerosol) or are associated with non-combustion related it can take steps to address its share of these emissions as noted human activities, such as mineral dust from unpaved roads or in Box 1.2 below. agricultural activities. There is less scope for World Bank initia- tives in addressing these pollution sources and as such they are Pollutants versus Sources not the focus of this work. When assessing linkages to public health, one must consider co- While each pollutant may be responsible for various environ- emitted pollutants in addition to greenhouse gases and short-lived mental or public health concerns, the source of emissions—whether climate pollutants (SLCPs), the principal drivers of long-term and it is a power plant, a car or a cookstove—may contribute to one or near-term climate change, respectively. These emissions must more categories of impact (i.e., health, climate, agriculture, etc.). be assessed in the context of the comprehensive effects of all Significant overlap exists between sources whose emissions drive species emitted by a given source. Some sources drive climate climate change and those with significant health impact via fine change (e.g., emitters of greenhouse gases or hydrofluorocarbons particle and ozone pollution. alone) and have no apparent health impact at all, but these are extremely rare; most sources of climate or air pollution emit Box 1.3: Examples of Sources Box 1.2: The Health Sector with Multiple Pollutants as a Climate Driver and Multiple Effects For those health impacts that flow directly from air emissions, it To meet its primary obligation to do no harm, the health sector has is important to distinguish the pollutants from their sources. For a responsibility to put its own house in order so that its practices, example, diesel engines are among the largest sources of black the products it consumes, and the buildings it operates do not harm carbon, a powerful short-lived climate pollutant, but they also emit human health and the environment. In this way, the health sector carbon dioxide (CO2), nitrogen oxides (NOX), volatile organic com- can play a leadership role in mitigating climate change by reducing pounds (VOC), air toxins and other components of air pollution with the energy- and resource-intensity of health care provision. This will public health consequences. Through this panoply of pollutants, significantly reduce emissions that drive climate change, along with diesel engines have a clear impact on long-term climate instability the attendant health consequences associated with climate vulner- (from CO2 emissions), near-term warming (black carbon) and are a ability and respiratory and other illness associated with air pollution. ubiquitous source of ambient air pollution through black carbon’s Actions include health system designs that embrace energy effi- contribution to primary fine particulate matter (PM2.5) and the addi- ciency, green building design, alternative energy generation, ‘green’ tional emission of NOX and VOC, which contribute to formation of transportation for staff and patients, sustainable and local food ground-level ozone (smog) and secondary PM2.5. provision, integrated solid waste management and water conserva- Assessing the impacts from the use of solid biomass fuels— tion measures. used for residential energy in many parts of the world—is even more In addition to a focus on the built environment and the provision complex. The damage to public health is undeniable with residential of services, there are a range of possible initiatives for multilateral aid biomass combustion contributing strongly to household air pollu- agencies and international institutions, ministries of health, health tion and more than 4.3 million premature deaths each year in 2010 care agencies and health providers. Everyone has a role to play (Lim et al., 2012). Its influence on climate, however, depends on a in minimizing the climate footprint of the health sector by ensur- number of factors including combustion conditions, the location of ing adequate finance for change, embracing an economic system emissions and the source of biomass. Residential biomass combus- that promotes health, social justice, and survival for current and tion is a large source of black carbon, co-emitted organic carbon, future generations, and raising awareness of current and projected CO2, methane and other pollutants. The net change in warming adverse and inequitable health impacts of climate change (including from all these climatically important pollutants (taking into account health co-benefits of mitigation). the reflectivity of the underlying geography) will determine the overall These specific actions are the focus of a new World Bank near-term climate impact. Its long-term climate impact depends report: “Climate Smart Healthcare: Low Carbon & Resilience Strate- on whether the biomass is sustainably harvested, since the carbon gies for the Health Sector.” from most biomass is taken up again when it is regrown (i.e., when Source: Healthy Hospitals, Healthy Planet, Healthy People: Addressing climate forests grow back after firewood is harvested or grasses grow back change in health care settings, WHO/Health Care Without Harm (2008). after dung-producing animals graze). 9 Chapter 2 Hotspot Identification Methodology What Is a Climate Change and Health “Hotspot”? For the purpose of this paper a “hotspot” is defined as a country that is already experiencing, or is likely to experience, a changed burden of disease due either to: 1) the direct, ecosystem-mediated, or human system-mediated impacts of climate change (an “impact” hotspot); or 2) a population’s exposure to emissions associated with the drivers of climate change, such as greenhouse gases or short-lived climate pollutants (an “emissions” hotspot). Given that substantial work has been done on the health effects of both vulnerability to climate impacts and exposure to air pollution emission by country, we have built upon existing methodologies and datasets at the national level to answer the questions posed in this paper. However, there remain several gaps with respect to the ideal methodology for characterizing health outcomes in a detailed and comprehensive way at this level. Identification of “Impact” Hotspots There is no available comprehensive estimate of the change in burden of disease attributable to climate effects. While the burden of many climate-sensitive diseases has been identified, it is impossible to correlate the changes in incidence and prevalence of this burden with a specific change in climate ver- sus other factors (let alone correlate a specific pathway with death and disease). This is the case both for acute natural disasters caused by climate extremes (heat waves, floods and drought, storm surges, typhoons, etc.), and progressive climate changes (increasing overall temperature and number of hot days, rising sea levels, etc.). The exceptions are a handful of climate-sensitive transmissible diseases. The ultimate heath outcome of a disease is a function of, among other things, the exposure to the disease-causing factor, the genetics and socioenvironmental factors of the individual, the quality of health care, general socioeconomic development of the country and other mediating factors mentioned in Figure 1.2. Taking into consideration a few of these factors and the abundant literature on some diseases and accepted climate models, certain research/advocacy groups have developed composite indices attempting to quantify the effects of climate in a very limited number of transmissible diseases, as well as direct exposure to health impacts and nutrition. Several widely used indices are described in Table 2.1 and assessed for their relative merits, includ- ing ND-GAIN, Climate Monitor, Center for Global Development, and the Global Climate Risk Index. Based on a review of the indices, the ND-GAIN country index was chosen for its robust methodol- ogy for characterizing health vulnerability due to climate change and, in particular, for its specificity in including multiple health and human habitat impacts in its analysis that span the full range of recognized exposure pathways. The ND-GAIN country index is a “living” index that is updated regularly but as used here it represents the November 2015 release of the 2014 indices. The ND-GAIN summarizes a country’s vulnerability 11 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Table 2.1: Comparative analysis of available vulnerability indices. Vulnerability Index Approach/Sources Advantage Disadvantage ND-GAIN Considers most up-to-date literature to assess • Systematic and transparent. • Disability-adjusted life years separate vulnerability through 2030 for six sectors • Comprehensive country (DALYs) are calculated for that impact human well-being. Also provides a coverage. regions of the world and for readiness index that assesses the overall country • Includes principal causes of groups of countries within the capacity (public, private and communities) to climate-related mortality (i.e., 14 different region groups. respond to climate change threats. diarrheal disease, malnutrition, Thus, many countries share the The Health index includes diarrheal disease and vector-borne disease) in a same value of the measure. malnutrition from Ebi (2008); malaria from Caminade single, transparent “Health” • “Readiness” to leverage private et al. (2014); and number of malaria cases/1,000/ metric based on recent, peer- and public sector investment for month from WHO Global Malaria Report (2013). reviewed scientific studies. adaptation actions is provided, This data is then moderated by slum population • Direct climate-health pathways albeit in a separate index, rather (UN Millennium Development Goals Indicators, 2015), captured by “human habitat than integrated into vulnerability access to sanitation and health systems performance metric.” measures. This requires a proxies data from World Development Indicators • Covers 192 countries. separate step to include it (data.worldbank.org). within the metric as assessed by vulnerability alone (e.g., the The Human Habitat index relies on the Warm “health” index). Spell Duration Index (Silliman et al., 2013) and monthly maximum precipitation in 5 consecutive days extracted from (Silliman et al., 2013). Urban concentration is a combined measure of the Herfindahl Index and population statistics as contained in the World Development Indicators. DARA Similar approach to ND-GAIN with respect to • More ambitious in scope with • Less straightforward drawing on peer-reviewed studies and transforming multiple indices for each sector presentation of results requires these to systematize and normalize their use as requiring greater numbers greater effort to interpret and an index. Meningitis indicator calculated based on of data transformations and understand results. S. Adamo (2011); All other impacts—McMichael methodological steps. More • Based on older data sets (2004). comprehensive categorization (McMichael, 2004, uses of health impacts (e.g., underlying disease data from including meningitis). 2000) and posters as opposed • Covers 184 countries. to peer-reviewed publications (Adamo, 2011). • Many separate indices (e.g., climate vs. carbon) that require integration. 12 Ho t spo t Ide nti f i cat i on Me th o d ology Vulnerability Index Approach/Sources Advantage Disadvantage Wheeler Index Develops country impact indicators for three critical • Integrates social factors and • Not health specific, thereby dimensions of climate change: more extreme vulnerability factors (including requiring a step to combine weather, sea level rise and loss of agricultural determinants of resilience, health data with climate productivity. Based on econometric analysis of namely economic development, vulnerability data. EM-DAT database (extreme weather; Dasgupta demographic change, and et al., 2009a, b [SLR]), and agricultural productivity governance) into a set of (Cline, 2007). metrics by climate impact type, allowing for consideration of individual categories of disease. • Comprehensive jurisdictional coverage with 233 countries represented (including 20 small, low-income island states). German Watch Based on damage and loss for more than 159 • Based on actual data. • Only a single category of Global Climate countries between 1994 and 2013, based on vulnerability. Risk Index reporting by Munich Re NatCatSERVICE and • Not health specific. economic and population indicators from the • Within loss and damage due International Monetary Fund (IMF). Indicators to storms, the indicator does include: (i) number of deaths, (ii) number of deaths not take into account important per 100,000 inhabitants, (iii) sum of losses in US$ in aspects such as sea-level rise, purchasing power parity (PPP) as well as (iv) losses glacier melting or more acidic per unit of gross domestic product (GDP). and warmer seas. ND-GAIN: University of Notre Dame Global Adaptation Index. http://index.gain.org DARA Climate Vulnerability Monitor v2. http://daraint.org/climate-vulnerability-monitor/climate-vulnerability-monitor- 2012/ Wheeler (2011). Quantifying Vulnerability to Climate Change: Implications for Adaptation Assistance, Working Paper 240, Center for Global Development. http://www.cgdev.org/publication/quantifying-vulnerability-climate-change-implications-adaptation-assistance- working German Watch Global Climate Risk Index 2015. https://germanwatch.org/en/download/10333.pdf to climate change and other global challenges in combination disease), and famine (malnutrition), influenced by socioeconomic with its readiness to improve resilience through the develop- factors like access to sanitation and adequate housing, and prox- ment of a two-part suite of indices. Vulnerability is assessed by ies for health system performance. However, based on the IPCC means of six sectors including: ecosystem services, food, health, typology of climate exposure pathways (Chapter 1), the ND-GAIN human habitat, infrastructure, and water. The underlying factors “Health” subindex omits the direct exposure pathway that includes that contribute to vulnerability within each of these sectors are increased heat extreme and flood and storm exposure. The ND- built into the index. Readiness is assessed through economic fac- GAIN “Human Habitat” subindex does, however, include proxy tors (essentially the “Doing Business” ranking published by the data that measure “projected change of heatwave hazard, projected International Finance Corp.) and governance and social factors, change of flood hazard, urban concentration, age dependency ratio, including social inequality, information communications technol- quality of transport and trade infrastructure, and paved roads.” ogy infrastructure, education, and innovation. These two subindices are the best current metrics by which The “Health” subindex would appear to be the most relevant we can establish a list of priority countries for action without basis for assessing individual country vulnerability to climate conducting a detailed research study. The two vulnerability impacts. A review of the methodology reveals that this index subindices selected (Health and Human Habitat) are compared includes proxy data for exposure to vector-borne disease (i.e., against each other and this serves to identify all countries that malaria), food- and waterborne infectious disease (diarrheal lie more than one standard deviation beyond the median value 13 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth of vulnerability for each subindex. The “Readiness” Index is used as a third dimension to assess where country capacity can reduce Box 2.1: Identifying Climate Health biophysical vulnerability. Together, these steps generate a set of Impact Hotspots within Countries countries that face the greatest potential challenges with respect to the pathways of climate exposure identified by the IPCC. We have Adopting an integrated approach to address climate change and included a qualitative description of key factors that determine health is of particular importance within countries because it is at climate health impact to provide a more comprehensive picture this level that there is potential for policy adoption, regulation, and of geographically correlated climate-sensitive health impacts. ground-level action. Identifying health impact hotspots in a country differs from the approach to mapping them globally or regionally. At the macro level, identification of impact hotspots relies on global Identification of Emissions Hotspots indices and very large global data sets. At the country level, there is a need for different tools to identify geographies for action, such As noted, there is a strong association between sources of fine as data on land use, vegetation, the built environment, and others. airborne particulates (referred to as PM2.5), other forms of air Because we are working with smaller data sets, we can better hone pollution, and sources of either greenhouse gases GHGs or SLCPs. in on the precise areas of impact, correlated to human habitat type It is also clear that black carbon and many other co-emitted (ecological or built) and show more faithful correlation to climate fine particulate species play a strong role in influencing climate health impact than a geographic region defined political boundary. change. However, the role of aggregate (i.e., undifferentiated) Unfortunately, an approach that focuses within national borders PM2.5 mass in warming the climate is complex, as some types has not been attempted with any degree of comprehension. It has, (like black carbon) lead to strong warming and others (such as however, been performed for specific diseases, such as malaria and sulfate aerosol) generate significant cooling. We simply note dengue, to identify present and future impact areas. Different habitat here that not all fine particulate pollution affects climate the types are parameterized and geographies of greatest current and potential threats then identified. For historic data, results can be same way. In fact, the uncertainties associated with aerosols compared to health data to determine accuracy. and their impact on the climate system are among the largest The precise type of habitat to map will vary by health impact remaining research challenges facing climate scientists. Given but will include a mix of natural and built environments. For example, the large overlap between sources of combustion-related PM2.5 dengue is prone in regions that are hotter, wetter, and often urban; and greenhouse gases, we simply note that health, climate and whereas malaria typically only correlates to areas that are hot- other development benefits need to be fully considered when ter, wetter, and rural. Other considerations, such as proximity to assessing control options. swamps, deserts, bodies of water, roads, population can be used in While more work is needed to untangle the climate and health disease-specific mapping. A list of different habitat-related environ- impacts of various emission sources at a global and national mental determinants of disease should be generated prior to starting level, the Institute for Health Metrics and Evaluation (IHME) at such an exercise, and correlated to health impacts to ensure most the University of Washington has already drawn a connection comprehensive results. between burden of disease health outcomes (including respiratory, Because such a step needs to be performed for only one coun- try, it is best to do this individually for a number of different climate cardiac, and cancer risks) to the observed levels of air pollution. and health impacts, which again, is different than the global work There have been independent assessments of both ambient air that combines these impact types to produce a composite index. pollution—which is co-emitted with a range of sources that con- Impact hotspot areas for specific diseases within a country are then tribute to accumulation of greenhouse gases—and household air mapped out. This data can then be compared against health data, pollution (one of the largest aggregate sources of the short-lived which is often collected at a subnational (county/district) level for climate pollutant, black carbon). The IHME data are 2013 statistics validation. that have then been aggregated at the country level (IHME, 2015). Using the Global Burden of Disease data, we carried out two distinct analyses. The first characterized countries in terms of does not indicate the significance of air pollution when viewed their burden of disease due to climate drivers (air pollution), against other major causes of death or illness—such as malnutri- with respect to other countries (an intercountry comparison). The tion or sexually transmitted diseases—in each country. analysis was performed initially in terms of absolute burden, and Accordingly, we used an alternative approach to look at the then normalized by population (disability-adjusted life years per national impact of air pollution within a country relative to other 10,000) to correct for country size. However, while this approach health risk factors. Here we again made use of the global burden provides a comparative view of countries’ burden of disease, it of disease statistics to identify all countries in which household 14 Ho t spo t Ide nti f i cat i on Me th o d ology air pollution ranked within the top five national health risk factors Similar limitations also apply when considering emission and those countries where ambient air pollution was among the hotspots at the national level. Air quality is typically an urban top nine national health risk factors. In both cases, we used the phenomenon attributable to the concentrated emissions of thou- Global Burden of Disease “Level-4” risk factors, which refer to sands of individuals, businesses, or activities without adequate the level of disaggregation of risk factors. We chose these (admit- space (related to the atmospheric volume) necessary to disperse tedly arbitrary) thresholds as they provide a number of hotspots and break down pollutants at a rate to avoid the buildup of unac- (~28 ambient air pollution, ~39 household air pollution coun- ceptable levels of pollution. While the regional pattern of city loca- tries) similar to that of the intercountry comparison. Finally, we tion, geography, and regulatory structures can make some nations analyzed the intersection of the results from the two methods. more susceptible to poor air quality, hotspots are more naturally That comparison is presented separately in Chapter 3. identified at the municipal scale than the national scale. Identify- Additionally, various analyses have been reviewed that identify ing hotspots based on national burden of disease attributable to the greatest benefits of various climate mitigation interventions air pollution will be skewed toward countries that are geographi- that can be achieved for specific sectors (i.e., where sector-specific cally large, with big populations. The national-level approach to interventions are likely to yield the greatest health benefits). This estimate “population-normalized” burdens of disease does not second analysis provides verification that the identified emissions account for variation in geographic size, which may introduce a hotspots (based on existing pollution levels) are also areas that bias for countries with extremely high or low population densities. will benefit from potential mitigation responses. Nevertheless, for the reasons already stated, we have used these and other statistics to identify national hotspots. Caveats and Limitations of This Analysis We acknowledge that in taking the national approach, we have also relied on available statistics that may potentially under- Trying to identify national hotspots is a difficult task as the eco- estimate risk and exposure in some locations. The earlier Global systems (as well as biophysical and geographical factors that affect Burden of Disease data (IHME, 2010) had relied on satellite-based climate and emissions health impacts) do not map to country measurements of total-column PM2.5 to estimate surface level PM2.5 boundaries. Rising sea levels affect primarily coastal areas, as concentrations where measurements are unavailable. Recent work do storm surges, while cities suffer from the heat island effects, has shown that in some cases, this may underestimate surface intensifying the impact of heat waves. Nevertheless, given that concentrations and—therefore—human exposure in areas that the World Bank works at the country level, this remains the most lack ground-based monitors, particularly in regions with high appropriate basis for analysis. wintertime and nighttime concentrations where satellite data is While national hotspots have been identified using the data and lacking (Van Donkelaar et al., 2015). To address some of these following the methods described above, these national aggrega- deficiencies, 2013 Global Burden of Disease estimates make use tions of climate risk will miss some areas of highly concentrated of vertical profile data, updated inventories and sub-grid-scale vulnerability that occur at the subnational level. The first section urban exposure algorithms to improve estimates relative to 2010 of Chapter 3 attempts to address this limitation by providing a results (Brauer et al., 2015). qualitative description of the geographies and scales at which Finally, we recognize that not all sources of pollution are various vulnerabilities occur. Table 3.1 describes the factors anthropogenic or related to combustion, as is the case with sea involved in developing a more detailed, subnational vulnerability salt and mineral dust aerosols. While there are health impacts assessment, but we acknowledge that the current report does not associated with all components of fine particle pollution, there is provide such a level of detail. less scope for addressing natural particle emissions. 15 Chapter 3 Hotspots Assessing “Impact” Hotspots Associated with Climate Effects As stated, the impacts of climate change do not follow country boundaries but as the World Bank’s operational work and policy dialogues are country-driven, we assess and present “impact” hotspots at the national level. Nevertheless, there are many ways to characterize both climate-sensitive health impacts and the geographies to which they correlate; many of those either cut across countries or describe variability within a country. Some of the most salient are discussed below. Tropical and equatorial latitudes have been identified as more vulnerable to illness and disease due to heat. These impacts will also be greatest in cities, which amplify heat effects. Additional stud- ies have suggested that heat will be a particularly significant problem for South Asia (Takahashi et al., 2007, as cited in The World Bank, 2013) and Sub-Saharan Africa, especially inland populations with limited water supplies. Populations in flood plains, in small catchments and on coasts are most susceptible to floods and storms, particularly in the tropics where heavy rain and storm events are most common. Asia, Africa, and Central and South America also have been highlighted by IPCC (Smith et al., 2014). Those regions most vulnerable for vector-borne disease include: for malaria, Africa and Southeast Asia; for Dengue, Asia/Pacific; for Lyme disease, temperate areas of Europe, Asia and North America. Encephalitis is present in Europe, Russia, Mongolia, and China. Hemorrhagic fever occurs globally (Smith et al., 2014; World Bank, 2013), dengue is more frequent in cities, and leishmaniasis—spread by sand flies—is common in desert regions. Food- and waterborne diseases are projected to have significant impacts in Southeast Asia (Kolstad & Johansson, 2011, as cited in World Bank, 2013). Models suggest Sub-Saharan Africa, South Asia, East Asia and the Pacific are the regions most susceptible to food system disruptions due to climate change (Lloyd et al., 2011, as cited in World Bank, 2013). 17 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Table 3.1: Geographic correlations to climate-sensitive health impacts. Human institution-   Direct impacts Ecosystem-mediated mediated Vector- Food and Heat Floods borne waterborne   and Cold and storms disease infection Air quality Undernutrition Geographies Lower latitudes Low-lying areas/ Tropics—variable by Tropics SE Asia Sub-Saharan Africa of greatest flood plains disease impact Cities Coasts Dengue: South Subtropics Cities East Asia and Pacific American cities South Asia Tropics Leishmaniasis: SE Asia India Latin America desert Sub-Saharan Africa Asia Encephalitis: Low-lying areas China Sahel Europe, Russia, Mongolia, China   Africa Upland mountains Food insecure Pakistan Conflict zones with population regions pressure   Central/South   Cholera—SE Asia Sub-Saharan Africa Upland mountains with America household pollution population pressures   Atolls     Source: Authors. Country Characterization Using This provides a sense of which countries will also require higher levels of support in the areas of governance, business climate and ND-GAIN Indexes social capacity. These countries likely will be less able to cope with As indicated in the methodology section, to identify national vulner- the systemic stresses thrown at them by climate change impacts. ability we can plot the distribution of countries as shown in Figure 3.1, Yellow shading indicates countries that lie at least one standard where the ND-GAIN Health Index (a proxy for ecosystem- and deviation above the median value of the complete sample. In order human system-mediated pathways) is plotted against the Human to best identify the extremes revealed in this sample, the upper right Habitat index (proxy for direct exposure pathways) for 2014. There quadrant has been enlarged and reproduced in Figure 3.2. Here the is a fairly high degree of correlation between the two, with many dotted lines indicate regions that lie at least 1 standard deviation countries in the upper right hand corner of the graph exhibiting above the median of the full sample for both indices. higher vulnerability to both direct and mediated health impacts.5 The proposed set of climate-sensitive “impact” hotspot coun- tries are listed in Figure 3.3 and shown in Figure 3.4. Figure 3.3 5  The “Health” subindex assesses the projected variation in expected deaths from climate change-induced diseases (diarrhea and malnutrition), projected change of malaria hazard, dependency on external resources for health services, slum populations, medical staff, and access to improved sanitation facilities. The “Human Habitat” subindex assesses vulnerability of human living conditions to climate change, considering weather extremes, urban development, demography, and transport infrastructure. Indicators include: projected change of heatwave hazard, projected change of flood hazard, urban concentration, age dependency ratio, quality of transport and trade infrastructure, and paved roads. Both subindices incorporate aspects of ecosystem response through the underlying climate modeling on which the two different aspects of risk are measured. This inclusion of ecosystem response in both subindices is necessary to accurately reflect both sets of risk, but is not the cause of the observed correlation. 18 Figure 3.1: Identifying vulnerable countries using ND-GAIN subindexes. 0.8 0.7 0.6 0.5 0.4 0.3 Human Habitat Vulnerability (direct pathways) 0.2 0.1 0 0.2 0.4 0.6 0.8 Health Vulnerability (mediated pathways) 19 Hot sp ot s G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 3.2: Highly vulnerable countries by ND-GAIN Health and Human Habitat indexes (inset of Figure 3.1). 0.80 Burundi Eritrea Human Habitat Vulnerability (direct pathways) 0.75 Timor−Leste Solomon Islands Central African Republic Papua New Guinea Liberia Somalia 0.70 DR Congo Congo Togo Sierra Leone Guinea Djibouti Chad Niger Micronesia Rwanda 0.65 Benin Sao Tome and Principe Ghana Gambia Guinea−Bissau Ethiopia Yemen Burkina Faso 0.60 Vanuatu Zambia 0.55 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 Health Vulnerability (mediated pathways) assigns those countries at elevated risk into three groups. Those in of Health Metrics and Evaluation and the Health Effects Institute the green color are at higher comparative risk in both the Human for the World Bank (IHME, 2015). Habitat and Health dimensions. Those in the gold and blue colors are at elevated risk in one dimension or the other. Figure 3.4 shows Intercountry Comparison their locations on the map. IHME 2013 burden of disease data have been used to develop Hotspots Associated with Emissions, indicators of health burden (both in absolute terms and normal- ized by population) attributable to individual countries and are the Drivers of Climate Change presented in Annex C. Figure 3.5 shows the burden of disease The best means of assessing health impacts of climate-driving attributable to ambient air pollution and household air pollution. emissions is to acknowledge the high degree of overlap between The tables in Annex C and Figure 3.5 reveal a significant degree drivers of climate change and air pollution sources of all types. A of commonality between countries affected by ambient air pollu- geographic analysis of the drivers of climate change is presented in tion (AAP) and household air pollution (HAP), but also important Annex B, however the most direct link between health and emis- distinguishing characteristics of countries affected by one or the sions is the co-emitted pollutant fine particulate matter, or PM2.5, other, but not both. rather than greenhouse gases or short-lived climate pollutants. China and India have the highest total burden of disease due Therefore, the hotspot analysis here focuses on data addressing primarily to their very large populations that are routinely exposed the burden of disease attributable to both ambient air pollution to ambient and household air pollution. These two countries and household air pollution for 2013 developed by the Institute alone account for half of the global burden of both ambient and 20 Hot sp ot s Figure 3.3: Characterization of climate-sensitive “impact” hotspots based on ND-GAIN. Afghanistan Gabon* Papua New Guinea Angola Gambia Peru Bangladesh Ghana Rwanda Benin Guinea Samoa Bhutan Guinea-Bissau Sao Tome and Principe Burkina Faso Haiti Senegal Burundi* India Sierra Leone Cambodia Kenya Solomon Islands Cameroon Lesotho Somalia* Central African Republic Liberia Sri Lanka Chad Madagascar* Sudan Comoros Malawi Tanzania Congo Marshall Islands Timor-Leste** Cote d’Ivoire Mauritania Togo Democratic Republic of Congo Micronesia Tuvalu* Djibouti Mozambique Uganda Ecuador Myanmar Vanuatu Equatorial Guinea Nepal Yemen Eritrea* Niger* Zambia Ethiopia* Palau Zimbabwe Health Habitat Both Source: Authors. *At highest risk (i.e., more than two standard deviations above median). **At highest risk in both health and habitat dimensions. household air pollution, when considering mortality and morbidity threats are greatest, additional analysis is needed in proposing or in disability-adjusted life years (DALYs). Together they represent developing appropriate mitigation responses in various locations. 52 and 60 percent of premature mortalities from ambient and Therefore, in addition to characterizing the countries by their household air pollution, respectively. However, looking exclusively overall burden, we also present the data normalized by popula- at national burdens in absolute terms obscures the fact that many tion. For example, Figure 3.6 compares the population-normalized other countries suffer a disproportionately high burden of disease burden of disease associated with ambient air pollution to the at the individual level. Anyone who has struggled to breathe or normalized burden due to household air pollution. While there to see through a thick layer of smog in a country with a small is strong correlation for many countries, a few typologies quickly population like Mongolia can attest to this fact. reveal themselves. While a strict ranking of population exposed to various types of Burden of disease is normalized by population and presented air pollution is useful for identifying areas where the climate-health in DALYs per 10,000 people for 2013. Countries within the yellow 21 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 3.4: Climate “impact” hotspots. shaded area represent countries that are more than one standard emissions from other modern conveniences such as power plants deviation above the median level of either ambient or household and vehicles. Thus Turkmenistan, Belarus, Ukraine, Bulgaria, air pollution observed in all countries (or both). Countries within and Moldova have high burdens of disease attributable to ambient the green zone have a statistically significant (two standard devia- air pollution, but not household air pollution. tions) elevation of ambient or household air pollution (or both) Figure 3.7 zooms in on the upper right quadrant so that we get and countries within the purple zone have unusually high eleva- a closer look at countries that lie significantly outside the range tion of ambient pollution (Turkmenistan), household pollution of others in terms of both household and ambient air pollution (Somalia), or both (Chad, Afghanistan). (Afghanistan, Chad, Central African Republic, Guinea-Bissau, Afghanistan, Chad, Central African Republic, Guinea Bissau, Mali, Sierra Leone, South Sudan, Democratic Republic of Congo, Sierra Leone, and Mali stand out as having populations exposed Niger, North Korea, Guinea, and Laos). to multiple air pollution-related health threats. In these countries, A second tier of countries with significant levels of both ambi- significant use of biomass fuel for home purposes results in the ent and household air pollution that may require comprehensive emission of black carbon and other components of fine particulate responses to address access to modern fuels as well as other matter. This contributes—in part—to the existing ambient air pol- emission sources emerges in Figure 3.7 (i.e., Cambodia, Burkina lution, which itself stems from many different combustion sources Faso, Cote d’Ivoire, Myanmar, and Cameroon). that may also emit CO2. Countries with easy access to modern In Figure 3.6, we can easily distinguish another cluster of fuels for cooking and heating are also likely to have significant countries, including Somalia, Madagascar, Malawi, Equatorial 22 Figure 3.5: 2013 burden of disease attributable to ambient air pollution (top panel) and household air pollution (bottom). Source: Institute for Health Metrics and Evaluation (IHME, 2015). From Global Burden of Diseases, Injuries, and Risk Factors Study, aggregated by country in disability-adjusted life years (DALYs). 23 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 3.6: 2013 burden of disease attributable to ambient versus household air pollution (2013). 400 Somalia Chad Afghanistan Central African Republic 350 Guinea−Bissau Burden of disease attributed to HAP Sierra Leone Mali South Sudan DR Congo (DALY per 10,000 population) 300 Guinea Niger Madagascar Malawi North Korea Papua New Guinea Equatorial Guinea Laos Cote d’Ivoire Cambodia 250 Burkina Faso Mongolia BurundiCameroon Ethiopia Lesotho Myanmar Solomon Islands Vanuatu Swaziland Tanzania Angola Liberia The Gambia Zambia Uganda Togo Nigeria 200 Mozambique Rwanda Congo India Georgia Haiti Comoros Kiribati Eritrea Bangladesh Pakistan Zimbabwe Kenya Benin Timor-Leste Ghana Sri Lanka Nepal 150 Sao Tome and Principe Philippines Sudan Mauritania Kyrgyzstan Tajikistan China 100 Yemen 50 Kazakhstan Uzbekistan Azerbaijan Armenia Latvia Albania Moldova SerbiaLithuaniaRomania Russia Bulgaria Ukraine Belarus Turkmenistan 0 Macedonia Hungary Montenegro 0 50 100 150 200 250 Burden of disease attributed to AAP (DALY per 10,000 population) Figure 3.7: Burden of disease attributable to ambient versus pollution death and illness more than two standard deviations household air pollution: Extremely impacted countries (2013). above the median. Yet not one of these countries has the same distinction with respect to ambient air pollution deaths. Opera- 400 Burden of disease attributed to HAP tional approaches to address the climate and health linkages Chad Afghanistan (DALY per 10,000 population) within each of these countries therefore should recognize that it Central African Republic 350 Sierra Leone Guinea−Bissau is essential to build health systems that can address the current South Sudan DR Congo Mali burden of disease associated with current residential cooking 300 Guinea Niger and lighting technologies while simultaneously considering North Korea Laos how that burden can be eliminated through access to modern Cote Cambodia 250 d’Ivoire Burkina Faso fuels. Such planning should also encompass the broader goal of Cameroon Myanmar putting the country on a path to zero net carbon emissions by The Gambia the end of the century. Each of these countries also appears on Nigeria 200 the list as having among the 100 least efficient health systems, 100 150 200 250 pointing to lower capacity to undertake adaptive measures or Burden of disease attributed to AAP prevention programs. (DALY per 10,000 population) Countries such as Kyrgyzstan, Tajikistan, China, Uzbeki- stan, Kazakhstan, Yemen, Armenia, and Azerbaijan each have a level of normalized ambient air pollution incidence of death and disease that is more than one standard deviation above the Guinea, Papua New Guinea, and Mongolia that would benefit median, but none has that level of departure from the median with from strategies with a focus on reducing short-lived climate respect to household air pollution. The countries in this group pollutants and other emissions associated with household air have made progress in the shift to modern fuels for heating and pollution. Each of these countries has a level of household air 24 Hot sp ot s Figure 3.8: Characterization of climate-driver “burden” hotspots based on Global Burden of Disease. Afghanistan Haiti Papua New Guinea Albania Hungary Philippines Angola India Romania Armenia Kazakhstan Russia Azerbaijan Kenya Rwanda Bangladesh Kiribati Sao Tome and Principe Belarus Kyrgyzstan Serbia Benin Laos Sierra Leone Bulgaria Latvia Solomon Islands Burkina Faso Lesotho Somalia Burundi Liberia South Sudan Cambodia Lithuania Sri Lanka Cameroon Macedonia Sudan Central African Republic Madagascar Swaziland Chad Malawi Tajikistan China Mali Tanzania Comoros Mauritania The Gambia Congo Moldova Timor-Leste Cote d’Ivoire Mongolia Togo Democratic Republic of Congo Montenegro Turkmenistan Equatorial Guinea Mozambique Uganda Eritrea Myanmar Ukraine Ethiopia Nepal Uzbekistan Georgia Niger Vanuatu Ghana Nigeria Yemen Guinea North Korea Zambia Guinea-Bissau Pakistan Zimbabwe AAP HAP Both Note: In this figure, the gold color indicates the respective populations normalized burden of ambient air pollution (AAP) more than one standard deviation above the median of all countries. The blue color indicates the respective populations normalized burden of household air pollution (HAP) more than one standard deviation above the median of all countries. The green color indicates the respective populations normalized burden of both AAP and HAP more than one standard deviation above the median of all countries. cooking; however, access to, versus the sustainable use of, natural policies to move away from CO2 and the co-emitted contributions resources are two different things. The toll that air pollution is to ambient air pollution that are elevating their health risks. This is taking on these societies indicates inefficient use of their natural quite a different task than addressing the energy access concerns resources that results in excess air pollution. Operational guidance of the prior list of countries. Figure 3.8 lists these countries and for these countries should be to orient climate and public health Figure 3.9 maps these results globally. 25 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 3.9: Countries with elevated (population normalized) burden of disease attributable to ambient air pollution (AAP, blue), household air pollution (HAP, yellow) or both (green). Intra-Country Comparison lists these countries and Figure 3.11 maps them utilizing the same color scheme as for Figure 3.9. An alternative approach for identifying countries with increased health risk associated with ambient air pollution, household air Intersection of Intercountry pollution or both also uses 2013 statistics from the Global Bur- and Intra-Country Methods den of Disease (GBD) project, but does not rely on intercountry comparisons. The GBD also assessed the risk of both types of air While there are advantages and disadvantages to each approach pollution relative to other in-country health risks for each country. for assessing which countries are in greatest need of addressing By selecting those countries where household air pollution ranks emission-related health impacts, the most robust set of hotspots within the top five national health risks and those countries where will be found by looking at the intersection of both methods. In ambient air pollution ranks within the top nine national health Table 3.2, a country appears as a hotspot with respect to ambient air risks, we find a similar sample size (~28 ambient countries; ~39 pollution (AAP) if it was (a) found to have a significantly elevated household air pollution countries) to the other metrics. Figure 3.10 population-adjusted burden of disease due to AAP, and (b) AAP 26 Hot sp ot s Figure 3.10: Characterization of climate-driver “risk” hotspots based on Global Burden of Disease. Afghanistan Guinea Papua New Guinea Azerbaijan Guinea-Bissau Philippines Bangladesh Haiti Rwanda Belgium Honduras Sao Tome and Principe Benin India Sierra Leone Bhutan Iran Singapore Burkina Faso Iraq Solomon Islands Cambodia Israel South Korea Cameroon Laos Sri Lanka Cape Verde Lebanon Sudan China Liberia Tajikistan Comoros Madagascar Tanzania Congo Malawi The Gambia Cote d’Ivoire Mauritania Timor-Leste Egypt Mozambique Togo Equatorial Guinea Myanmar Turkey Ethiopia Nepal Turkmenistan Ghana Netherlands Uzbekistan Greece North Korea Vanuatu Vietnam AAP HAP Both Note: In this figure, the gold color indicates the respective populations with AAP ranking within the top nine national health risks. The blue color indicates the respective populations with HAP ranking within the top five national health risks. Green indicates the respective populations with both AAP ranking within the top nine national health risks and HAP ranking within the top five national health risks. was found to be among the countries nine most-significant health with the highest per-capita health burden from air pollution does risks. Similarly, a country appears in Table 3.2 as a household air not target the same countries where air pollution is among the top pollution (HAP) hotspot if it was (c) found to have a significantly health risks. As such, the list of “intersection” hotspots is much elevated population-adjusted burden of disease due to HAP, and shorter than either of the individual approaches. Some countries (d) HAP was found to be among the countries top five health risks. clearly have a relatively high share of people suffering from ambient A country is listed as a “Both” hotspot only if conditions (a), (b), air pollution, but also have other, more pressing health risks (e.g., (c), and (d) are met. Those countries that satisfy conditions (a) Lithuania, Macedonia, Romania). Whereas other countries have and (c) but only one of conditions (b) or (d) are indicated by an ambient air pollution as one of the most significant health risks asterisk. Nepal satisfied condition (b), (c), and (d) but was not to the population, but they do not have a high relative burden; an AAP hotspot by the ‘burden’ approach. they are just very healthy societies (e.g., Netherlands, Belgium). A This intersection method of identifying national-level hotspots unique set of counties emerges from the intersection. Many of the is instructive as well as validating. For example, it makes clear ambient air pollution hotspots identified by both methods (e.g., that with respect to ambient air pollution, targeting the countries Tajikistan, Turkmenistan, Kazakhstan) share access to modern fuels, 27 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Figure 3.11: Countries in which ambient (blue), household (yellow) or both types of air pollution (green) rank highly in their burden of disease. and thus are not on the list of household air pollution countries, Additional analysis is needed at the national level to determine but they use these modern fuels very inefficiently, resulting in specific mitigation approaches that will best balance climate and excess air pollution. This has direct implications for the operations health considerations for countries that face simultaneous chal- that would be needed to address ambient air pollution in these lenges to health through ambient and household air pollution. countries that is distinct from programs to address household air Determining the optimal balance for the many countries that are pollution or countries that suffer from both. in between these poles requires a more concerted effort to assess It is also notable that the list of household air pollution hotspots all sources of health risk linked to climate changes, as well as is strikingly similar across methods and thus there is a long list the mitigation options (both now, and in the future). Tailored (almost the entire list) identified at the intersection between meth- development plans must address those urgent health priorities ods. This implies that there is a very robust association with these that are contributing to the current burden of disease, as well as countries and that clearly these countries—where household air reduce the impact of, and appropriately transition away from, pollution is a top health risk and exacts a high toll—must address those sources found to be the drivers of future climate change. household air pollution as an aspect of public health and climate operations. 28 Hot sp ot s Figure 3.12: Emissions hotspots. Note that countries listed in each category represent countries with elevated, population- normalized burden of disease. Afghanistan Guinea* Philippines Azerbaijan Guinea-Bissau* Rwanda Bangladesh Haiti Sao Tome and Principe Benin India Sierra Leone* Burkina Faso* Laos* Solomon Islands Cambodia Liberia Sri Lanka Cameroon* Madagascar Sudan* China Malawi Tajikistan Comoros Mauritania* Tanzania Congo Mozambique The Gambia* Cote d’Ivoire* Myanmar Timor-Leste Equatorial Guinea Nepal** Togo Ethiopia North Korea Turkmenistan Ghana Papua New Guinea Uzbekistan Vanuatu AAP HAP Both Source: Authors. Notes: * Met criteria for BOTH based on burden approach, but only AAP or HAP criterion by risk approach. ** Met criteria for BOTH based on risk approach, but only HAP criterion by burden approach. AAP = ambient air pollution. In this figure, the gold color indicates the countries with the AAP burden more than 1 standard deviation above the median and in the top 9 national risks. HAP = household air pollution. In this figure, the blue color indicates the countries with the HAP burden more than 1 standard deviation above the median and in the top 5 national risks. Both = both AAP and HAP. In this figure, the green color indicates the countries with the AAP burden more than 1 standard deviation above the median and the HAP risk in the top 5 national risks. 29 Chapter 4 What Can Be Done: Adaptation and Mitigation Global average temperature increases due to climate change are expected to increase the frequency and severity of extreme weather events, as well as climate variability. As has already been observed, these events are and will continue affecting health outcomes, mostly negatively. These impacts could slow or, on occasion, even reverse the decades-long trend of gains in health. Globally, those most vulnerable to these effects are poorer countries and poorer populations. Reducing greenhouse gas (GHG) emissions (mitigation) will, in the long term, reduce the magnitude of global climate change and, if adequately targeted, can reduce local co-pollutants that worsen short-term health outcomes. But projections indicate that the world is already locked into a two-degree centigrade warmer climate, which is expected to have negative health effects. Minimizing these effects will require institutional, behavioral, built environment, etc., adjustments (adaptation). Therefore, minimizing the health impacts of climate change and CO2 co-pollutants requires both adaptation and mitigation. Some global trends add to the complexity in taking action. These include rapid and unplanned urbanization, aging populations, and rising energy demand from a growing population. Other global trends, however, can facilitate mitigation efforts and boost population resilience. These include increased literacy, improvements in health service coverage, and technological innovations in infrastructure engineering, medical prevention diagnosis and treatment, renewable energies, remote sensing, and disaster preparedness. In climate change and in other areas, development can have positive as well as negative effects on vulnerable populations. Environmentally sustainable and well targeted measures (i.e., pro-poor and covering the most vulnerable populations) can ensure positive net final outcomes. Adaptation The Intergovernmental Panel on Climate Change (IPCC) defines adaptation as “the process of adjustment to actual or expected climate and its effects.” In the case of health, the purpose of the adjustments is to avoid harm or exploit beneficial opportunities to improve health outcomes. Climate change effects on health outcomes are mediated through multiple environmental, social and public health factors. Effec- tive adaptation measures to reduce both the current and future estimated additional burden of disease are equally complex, requiring structural, behavioral and technological changes that are well targeted and cost-effective across several sectors and administrative levels. In most cases, such measures reduce the burden of disease due to both climate- and non-climate-sensitive diseases. General improvements in infrastructure and interventions to improve health in general can also reduce the burden of disease due to climate change. WHO estimates that climate change may add as much as US$2–4 billion in annual health sector costs by 2030. International funding for health adaptation to safeguard against these costs, by contrast, would be less than 1 percent of this figure (WHO Euro, 2013). World Bank financing could therefore have a significant impact and result in long-term cost savings. 31 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth The value of adaptation is clear. Whether in infectious disease, the rainy season starts, the same intervention may be modified heat waves or natural disasters, history has proven that prepared- taking into consideration climate change projections suggesting ness and response to threats can greatly limit the losses to health, that temperature and humidity changes could expand the breeding human life and economies. For example, in 1970 a Category 3 areas for the malaria-transmitting mosquitoes. This adjustment hurricane hit East Pakistan (present day Bangladesh) resulting would make the measure transitional, proactive, short-term, local, in 500,000 deaths. Similar storms hit in 1991 and 2007, causing and (depending on its costs and other factors) either low-regrets 140,000 and 3,400 deaths, respectively. Collaborative adaptation or win-win. Alternatively, a new technology such as a vaccine or over the intervening decades led to these dramatic improvements genetic modification of the vector to prevent disease transmission, in lives lost (Smith et al., 2014) by increasing Bangladesh resilience applied across the world, would be transformational, proactive, to natural disasters. long term, general, and potentially no-regrets. The academic health and climate literature has classified Adaptation is country-, place- and context-specific, and no single adaptation measures and options in multiple ways including: approach to reduce the actual or expected climate effects will be appropriate everywhere. However, countries identified as climate • Incremental, transitional, and fundamental actions: accord- “impact” hotspots for health outcomes in this paper share some ing to the depth of the change, measures can be incremental commonalities that could guide a general adaptation approach. when they imply simply increasing the frequency or quantity For the most part, these countries have high prevalence of climate- of existing interventions that may or may consider climate sensitive diseases, or are by dint of their geographic location at change. Changes are said to be transitional if they deliberately high risk of suffering from climate-related natural disasters such take into consideration climate change and expected health as floods and heat waves, while also having weak health systems outcomes due to climate change. Fundamental is change that and being at an early stage of economic development. is classified as transformational and permanent. We have modified the approaches for managing the risks of • Short- versus long-term measures. climate change from the most recent report of the IPCC Working • Proactive versus reactive measures: proactive measures are Group II to reflect the characteristics of the “impact” hotspots and taken to prevent events that have not happened yet but for the health focus. For these countries, reducing current vulnerability which there exists a risk; reactive measures address events and exposure to climate and climate variability is not just a first that have already happened and are likely to recur with greater step but at the core of adaptation efforts to counter the negative or lesser intensity. impact of climate change in health outcomes. Regarding health sector-specific interventions, the World Bank focuses on supporting • “No regrets,” “low regrets” and win-win solutions: in terms countries who accelerate the achievement of universal health cov- of cost-benefit, “no-regrets” adaptation measures are those erage6 (UHC). For the World Bank, accelerating country’s progress whose socioeconomic benefits exceed their costs, regardless of towards UHC requires a combination of not only increased access what happens to the climate. Measures are considered “low- to service and financial protection, but also to work across sectors regrets” when the associated costs are somewhat low and the to achieve HNP outcomes (examples provided in Annex 4). This benefits are expected to be large if the projected climate change last aspect focuses on public health-enhancing measures that fall occurs. Win-win options are those that minimize social risk outside the purview of the health sector. Climate-smart measures and/or exploit potential opportunities and also have other in non-HNP sectors are an important element for achieving UHC, socioeconomic or environmental benefits. and include issues such as access to energy and clean water. • Local and general actions: in terms of geographical scope, Most interventions, whether implemented in health or other measures can be local (such as vector control in an area), or sectors, could be integrated across the Bank’s policy dialogues general/systemic. and economic analyses and/or be supported through World Bank • Sector-specific or broader: adaptation measures may be taken investments. In many cases, The Bank could improve the impact either in the health sector or in other sectors. of its development work by including climate-sensitive health out- comes while considering adaptation measures across non-health Using vector control as an illustration, the length of an sectors. By ensuring that climate change issues are considered insecticide-spraying, mosquito-control campaign could be increased to account for higher rainfall. This would be an incremental, reac- tive, short-term, local, and—in some areas—win-win measure if it 6 UHC is defined by World Bank and WHO as: “everyone—irrespective of their ability also reduces dengue, or eastern equine zoonosis in horses. Gener- to pay—gets the health services they need in a timely fashion without undue financial ally, this would be a health sector-implemented measure. Before hardship as a result of receiving them.” (World Bank/WHO 2014). 32 W hat Can B e Do n e : Ad aptati on a n d M itigation within its universal health care strategy, the Bank could ensure Figure 4.1: Drivers of climate change and environmental that this approach to the health sector both maximizes health health. outcomes and makes them as sustainable as possible. Mitigation GHGs Beyond air quality, other actions to address the emissions that drive climate change can affect health in more moderate ways.7 Given that actions to address the key drivers of climate change can influence important determinants of health, we describe the relationship between these drivers and various components of the burden of disease, present the geographic patterns of that Ambient air burden, and discuss how it could be reduced in response to vari- SLCPs pollution ous mitigation pathways being discussed. Unlike the climate-health impacts discussed in the prior sec- tion that lend themselves to adaptive responses, the health effects of air pollution are more directly linked to mitigation responses (although some future adaptive measures may still be needed to deal with extreme air quality conditions associated with natural Household air pollution emissions such as wildfire, pollen, or mineral dust). Nevertheless, as stated in the Introduction, the objective of this work is to identify the geographic areas where a change in burden of disease is anticipated as a result of climate impacts or changes Climate driver Health driver in the drivers of climate change. Sector-specific guidance notes will focus more on the proposed adaptive and mitigation responses to the climate-health threats identified and assessed in this work. Appropriate operational strategies will hinge upon the recog- nition that some co-emitted types of airborne pollution may not respect to categorization. Some emissions contribute to climate have a climate impact but will still have a strong health impact. change—either in the long- or the short-term—and others con- Immediate threats from air pollution can be prioritized now tribute to health impacts via exposure in or near the home or in while health services prepare for new threats that are expected the ambient atmosphere. Many of these pollutants are common to emerge over time that require adaptive strategies. Additionally, to two or more categories and many sources contribute to mul- health impact analyses must consider changes in health risk fac- tiple impacts; the reduction of these sources therefore can lead tors associated with the mitigation activities themselves, for those to multiple benefits. mitigation actions that may have non-air quality health benefits. For current purposes, we present a more detailed typology The schematic shown in Figure 4.1 attempts to demonstrate of various atmospheric pollutants with a focus on health effects the complexity of this situation. The targets of the present analysis that result from degraded air quality, principally due to fine par- are those sources with emissions that both drive climate and lead ticles and ground-level ozone. Globally, fine particulate matter is to direct health impacts. It illustrates that pollution is not neatly responsible for more than 95 percent of deaths due to ambient defined—in terms of either emission sources or pollutants—with air pollution; however, ground-level ozone is a significant source of chronic obstructive pulmonary disease and other health com- plications (WHO, 2009; Lim, 2012; US EPA, 2013). The typology presented in Annex A is stratified by the timescales across which 7 It is also important to note that some drivers of climate change (or mitigation strategies) may have an effect on health that is not mediated through air quality (e.g., they impact the climate system, and we review the health impacts chlorofluorocarbons and some hydrofluorocarbons may increase risk of skin cancers and important co-emitted species of each category, noting other through stratospheric ozone depletion; active transportation strategies yield health impacts of these co-emitted species where important. benefits by reducing emissions, but also by improving cardiovascular health through exercise; reduced deforestation can ameliorate malaria spread, climate smart agriculture Based on these general observations, it is clear that some can reduce emissions while increasing productivity and improving nutrition, etc.). countries would benefit from climate and health interventions 33 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth that focus on emission reduction strategies that target the com- quality or other health risk reduction that accompanies mitiga- mon sources of both greenhouse gas emissions and ambient air tion of greenhouse gases and short-lived climate pollutants will pollution. Others would benefit—to a greater degree—from strate- have different geographical features relative to these generalized gies that focus on short-lived climate pollutants and household climate change impacts. air pollution (while ensuring that such strategies are consistent As noted earlier, several studies have examined the “co-benefits” with long-term net carbon neutrality). In Annex C, we explore the of climate mitigation associated with improvements in ambient statistics in more detail to identify countries that are experiencing air quality. Figure 4.2 shows results from one of these analyses the greatest rates of disease (as opposed to overall burden) stem- using state-of-the-science atmospheric models and new relation- ming from each type of air pollution. ships between chronic mortality and exposure to fine particulate These lists provide an important starting point for disentangling matter (West et al., 2013). As noted within that study, the overall the individual climate and health risks facing each nation, but a level of health benefit depends on the scenario choice modeled careful analysis at the national level that examines the common and, in particular, the assumed level of air pollution control in the sources of greenhouse gases, short-lived climate pollutants and other counterfactual scenario and technology choice in the abatement air pollutants (along the lines of the global analysis conducted by scenario. They find that greenhouse gas abatement consistent with Rogelj et al., 2014)—is needed to fully understand optimal strategies the Representative Concentration Pathway 4.5 (RCP4.5) scenario for addressing climate and health risks simultaneously. It is clear, avoids 0.5±0.2, 1.3±0.5 and 2.2±0.8 million premature deaths however, that in the absence of such an analysis those countries in 2030, 2050 and 2100, respectively. The greatest benefits occur appearing near the top of the lists presented in Annexes B and where air pollution is currently worse, in South and East Asia, C offer clear opportunities for climate and health interventions followed by the Eastern U.S., Central Europe, and parts of West spanning a wide range of pollutants, with multiple benefits. and Central Africa, and Central America. Similarly (UNEP/WHO, 2011) assessed the health benefits of Geographic Analysis of Potential undertaking key measures to reduce black carbon and methane and Reduction in Air-Pollution Health determined that more than 2.4 million lives could be saved each year by 2030 through air quality improvements associated with Impacts interventions to curb short-lived climate pollutants. Importantly, Various efforts have documented the health impacts of climate these analyses assessed only those health benefits attributable to change—and therefore the health benefits of climate mitigation—but reduced ambient air pollution, despite the fact that several of the most prominently the IPCC (Smith et al., 2014). The geographic key measures would likely reduce household exposure as well. range of these benefits has already been assessed under the adap- This work was refined and repeated in 2013 (World Bank/ICCI, tation sections of this report. However, the health benefits of air 2013) using updated inventories and examining the 14 measures Figure 4.2: Avoided premature mortality from PM2.5 (cardio-pulmonary disease plus lung cancer) and ozone (respiratory) in 2030, 2050 and 2100 (deaths per year per 1,000 km2, color scale). Co-benefits are presented for the specific reference and greenhouse gas abatement scenarios modeled in West et al. (2013). 34 W hat Can B e Do n e : Ad aptati on a n d M itigation individually. Results from this re-analysis confirmed that ambient Multiple Benefits of Mitigation air pollution benefits would be large but arrived at a somewhat lower total of approximately 2.2 million premature deaths avoided Health will be significantly affected by our changing climate and annually (i.e., the average of two models). these changes are driven by the emission of greenhouse gases as Figure 4.2 presents the geographical distribution of avoided well as short-lived climate pollutants. However, detailed examina- premature mortality that could be achieved in 2030, with full global tion of mitigation scenarios has revealed that reducing these health implementation of 14 measures that address the most significant impacts is just one of many reasons to reduce harmful emissions sources of black carbon and methane (World Bank/ICCI, 2013). to the atmosphere. India, China, Pakistan, and Indonesia stand out. In Africa, Kenya Several studies have confirmed large anticipated air quality- and Democratic Republic of Congo would stand to benefit from related health benefits that would accrue at various levels of the full suite of measures targeting short-lived climate pollutants. carbon mitigation (Nemet et al., 2010; Hamilton et al., 2014; Parry It should be noted that this is relative to a zero CO2 mitigation et al., 2014; West et al., 2013; Thompson et al., 2014). A smaller reference scenario, so these are upper estimates of what could be number have considered other benefits that would accompany achieved with this kind of mitigation alone but lower estimates large-scale emissions reductions, such as energy savings and of what could be achieved through the combined mitigation of energy security, net employment and/or other economic benefits short-lived pollutants and CO2 simultaneously. Because these and avoided crop losses and other ecosystem services (IEA, 2014; results are integrated within national borders, the larger, more New Climate Economy, 2014; World Bank/ClimateWorks, 2014; populous countries stand out. Taken together, Figure 4.2 and 4.3 New Climate Institute, 2015; Driscoll et al., 2014). Even fewer confirm that regions that are currently experiencing the greatest assess the direct benefits of avoided climate change alongside the public health burden associated with air pollution are the same multiple benefits that could accompany mitigation actions with to benefit the most from efforts to reduce it. self-consistent discounting and monetization procedures across Figure 4.3: Health benefits of 14 key black carbon and methane interventions. Regional distribution of avoided premature mortality in 2030 as estimated by the BenMAP tool for all PM2.5 and ozone impacts, with all measures combined (including the fan-assisted cookstove measure and the 50-percent reduction in global fire measure). Source: World Bank/ICCI (2013). 35 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth the different categories of benefits (e.g., few studies quantify the other environmental benefits, etc.) should be quantified where costs and benefits of impacts attributable to different pollutants feasible but acknowledged where quantification is not possible as a time series, thereby differentiating pollutants with near-term (World Bank/ClimateWorks, 2014). Some mitigation actions yield versus long-term effects, and then apply a consistent social dis- health benefits that are unrelated to air quality improvements count rate to both the impacts and the valuation of costs as they (such as active transportation, reduced deforestation, etc. (Patz are incurred (Shindell, 2015)). et al., 2014; Garg 2015)). Given the focus of the present analysis These large and immediate benefits of mitigation action on air on linkages to human health benefits, results presented here quality and health notwithstanding, it is important to recognize are focused solely on identifying geographical regions where the full social value that accrues with low-emission development. the health benefits can be realized, while acknowledging that All benefits (e.g., energy and food security, net employment additional social value is likely to accrue both within these same benefits and other economic benefits, ecosystem services and regions as well as globally. 36 Conclusion The drivers of climate change and co-emitted pollutants8 have significant impact on both the health of humans and the planet. This paper is an attempt to identify the geographies and people within that are most vulnerable to the health impacts of these climate co-pollutants as well as the impacts of climate change. The paper also links these impacts to country readiness to improve resilience in an attempt to tie these physical functions to sociological response. This analysis of hotspots provides the foundation for developing better responses and provides a guide for these geographies and countries that face the highest burden of impact so that they can confront them in ways that are cost-effective and scalable. These data can be used to prioritize both countries and types of interventions. Following the results of this paper, a next step might be to perform a more detailed diagnosis of the causes and sources of the climate-sensitive health impacts. Better understanding of vulnerability can inform systematic country diag- nostics, country partnership frameworks, and other relevant operations under preparation. Tailoring relevant projects—chiefly in health, nutrition, and population (HNP), but also in sectors that have direct impacts on HNP outcomes—can ensure that climate-health considerations are woven into economic analysis and project design. Some tools exist and others are under development to support team efforts and minimize their bur- den; for instance, two operational guidance notes to guide health sector interventions are in progress. The Climate Change Cross-Cutting Solutions Group can provide technical support to HNP teams to carry out climate and health vulnerability assessments and the design of interventions, such as climate services for health, early warning systems, climate smart surveillance systems, “greening” the health sector, and preparing requests for climate funds. The Cross-Cutting Solutions Group is also developing a programmatic approach to efficient, clean cooking and heating that can significantly reduce household air pollution, including black carbon. This is in addition to developing new operational tools that will help municipal administrations to under- stand the potential air quality and health benefits of actions that are within their authority. Moreover, additional analysis can better identify operational strategies to maximize development benefits tailored for countries suffering from ambient air pollution, household air pollution, or both. These steps to curb emissions have the dual benefits of saving lives now and contributing to climate change mitigation, thereby reducing impacts on health in the future. In general, this paper should be taken as an entry-point for furthering dialogue with countries and regions to improve understanding and action on climate change and health. There are an increasing number of tools available for making most appropriate climate changes and health interventions, and it is expected that we will work further to improve and enhance this chest of resources moving forward. It is important that World Bank staff and others working in development become aware of these challenges and opportunities so that we might collectively—and simultaneously—improve climate, health, and overall development outcomes. 8 Climate drivers that affect health outcomes include fine particulate matter (including black carbon which is a strong warming agent and other components of aerosol particulate that may offset a portion of that warming) and methane, which contributes to the formation of ground-level ozone or smog. 37 References Adamo S., S. Trzaska, G. Yetman, J. del Corral, M. Thomson, and C. Perez, 2011. Integration of Demographic, Cli- mate, and Epidemiological Factors in the Modeling of Meningococcal Meningitis Epidemic Occurrence in Niger. Poster presented at the 2011 Annual Meeting of the Population Association of America in Washington, D.C., March 30–April 1. Retrieved: http://www.ciesin.org/documents/adamo-model-meningoccal_paa_mar2011.pdf Beggs, Paul J., 2010. Adaptation to Impacts of Climate Change on Aeroallergens and Allergic Respiratory Diseases. Int J Environ Res Public Health. Bond, T. C., Bhardwaj, E., Dong, R., Jogani, R., Jung, S., Roden, C., Streets, D. G., Fernandes, S., and Trautmann, N., 2007. Historical Emissions of Black and Organic Carbon Aerosol from Energy-related Combustion, 1850–2000. Global Biogeochemical Cycles 21 (2): GB2018. doi:10.1029/2006GB002840, with new emissions factors developed in collaboration with C. Liousse as contained in World Bank/ICCT (2014). Bond, T. C., S. J. Doherty, D. W. Fahey, P. M. Forster, T. Berntsen, B. J. DeAngelo, M. G. Flanner, S. Ghan, B. Kärcher, D. Koch, S. Kinne, Y. Kondo, P. K. Quinn, M. C. Sarofim, M. G. Schultz, M. Schulz, C. Venkataraman, H. Zhang, S. Zhang, N. Bellouin, S. K. Guttikunda, P. K. Hopke, M. Z. Jacobson, J. W. Kaiser, Z. Klimont, U. Lohmann, J. P. Schwarz, D. Shindell, T. Storelvmo, S. G. Warren, and C. S. Zender, 2013. “Bounding the Role of Black Carbon in the Climate System: A Scientific Assessment.” Journal of Geophysical Research: Atmospheres 10.1002/ jgrd.50171. Brauer, Michael, Greg Freedman, Joseph Frostad, Aaron van Donkelaar, Randall V. Martin, Frank Dentener, Rita Van Dingenen, Kara Estep, Heresh Amini, Joshua Schulz Apte, Kalpana Balakrishnan, Lars Barregard, David M. Broday, Valery Feigin, Santu Ghosh, Philip K. Hopke, Luke David Knibbs, Yoshihiro Kokubo, Yang Liu, Stefan Ma, Lidia Morawska, José Luis Texcalac Sangrador, Gavin Shaddick, Hugh Ross Anderson, Theo Vos, Moham- mad H. Forouzanfar, Richard T. Burnett, and Aaron Cohen, “Ambient Air Pollution Exposure Estimation for the Global Burden of Disease 2013” Environ. Sci. Technol., Just-accepted manuscript. DOI: 10.1021/acs.est.5b03709, publication date (web): 23 Nov 2015. Caminade, C. et al., 2014. Impact of climate change on global malaria distribution. Proceedings of the National Academy of Sciences, 111.9, pp. 3286–91. Chafe, Z. A., M. Brauer, Z. Klimont, R. Van Dingenen, S. Mehta, S. Rao, K. Riahi, F. Dentener, K. R. Smith, 2014. “Household Cooking with Solid Fuels Contributes to Ambient PM2.5 Air and the Burden of Disease.” Environ- mental Health Perspectives 122:1314-1320; http://dx.doi.org/10.1289/ehp.1206340 CCAC, 2013. Time to act to reduce short-lived climate pollutants, Climate and Clean Air Coalition, Paris, France. Cline, William, 2007. Global Warming and Agriculture: Impact Estimates by Country. Washington, DC: Center for Global Development and Peterson Institute for International Economics. Costello, Anthony, Mustafa Abbas, Adriana Allen, Sarah Ball, Sarah Bell, Richard Bellamy, Sharon Friel, Nora Groce, Anne Johnson, Maria Kett, Maria Lee, Caren Levy, Mark Maslin, David McCoy, Bill McGuire, Hugh Montgomery, David Napier, Christina Pagel, Jinesh Patel, Jose Antonio Puppim de Oliveira, Nanneke Redclift, Hannah Rees, Daniel Rogger, Joanne Scott, Judith Stephenson, John Twigg, Jonathan Wolff, Craig Patterson, 2009. “Managing the health effects of climate change: Lancet and University College London Institute for Global Health Commission.” The Lancet, Vol. 373, No. 9676. Dasgupta, Susmita, Benoit Laplante, Craig Meisner, David Wheeler and Jianping Yan, 2009a. The Impact of Sea Level Rise on Developing Countries: A Comparative Analysis. Climatic Change, 93:379–388. Dasgupta, Susmita, Benoit Laplante, Siobhan Murray and David Wheeler, 2009b. Climate Change and the Future Impacts of Storm Surge Disasters in Developing Countries. Center for Global Development Working Paper No. 182. http://www.cgdev.org/content/publications/detail/1422836 Driscoll, Charles, Jonathan Buonocore, Habibollah Fakhraei, Kathy Fallon Lambert, 2014. Co-benefits of Carbon Standards: Air Pollution Changes under Different 111d Options for Existing Power Plants, Syracuse University and Harvard School of Public Health, Harvard University, May 27, 2014. Ebi, Kristie, L., 2008. Adaptation costs for climate change-related cases of diarrhoeal disease, malnutrition, and malaria in 2030, Globalization and Health, Vol. 4, 2008. EM-DAT, 2010. The International Disaster Database. Center for Research on the Epidemiology of Disasters. http:// www.emdat.be/ 39 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Fischedick M., J. Roy, A. Abdel-Aziz, A. Acquaye, J. M. All- Nemet, G. F. et al., 2010. “Implications of incorporating air-quality co- w o o d , J . - P. C e r o n , Y. G e n g , H . K h e s h g i , A . L a n z a , benefits into climate change policymaking,” Environ. Res. Lett. 5 D. Perczyk, L. Price, E. Santalla, C. Sheinbaum, and K. Tanaka, 2014: (2010) 014007 (9pp), doi:10.1088/1748-9326/5/1/014007. Industry. In: Climate Change 2014: Mitigation of Climate Change. New Climate Economy, 2014. Better Growth, Better Climate: The New Contribution of Working Group III to the Fifth Assessment Report Climate Economy Report, The Global Commission on the Economy of the Intergovernmental Panel on Climate Change [Edenhofer, O., and Climate, New Climate Economy c/o World Resources Institute, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, Washington, D.C. A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, New Climate Institute, Assessing the missed benefits of countries’ national S. Schlömer, C. von Stechow, T. Zwickel and J. C. Minx (eds.)]. contributions, 30 March, 2015. NewClimate Institute for Climate Policy Cambridge University Press, Cambridge, United Kingdom and New and Global Sustainability, Cologne, Germany. York, NY, USA. OECD, 2014. The Cost of Air Pollution: Health Impacts of Road Transport, Garg, T., 2015. http://blogs.worldbank.org/impactevaluations/ Organization for Economic Cooperation and Development, Geneva, hidden-local-costs-deforestation-tropics-guest-post-teevrat-garg Switzerland. DOI: 10.1787/9789264210448-en. GBD authors, 2015, Global, regional, and national comparative risk OECD, 2015. Economic cost of the health impact of air pollution in assessment of 79 behavioural, environmental and occupational, and Europe: Clean air, health and wealth. Copenhagen: WHO Regional metabolic risks or clusters of risks in 188 countries, 1990–2013: a Office for Europe. systematic analysis for the Global Burden of Disease Study 2013. The Parry, Ian W. H., Dirk Heine, Shanjun Li, and Eliza Lis, 2014. Getting Lancet, Volume 386, Issue 10010, 2287–2323. Energy Prices Right: From Principle to Practice. International Monetary Hartmann, D. L., A. M. G. Klein Tank, M. Rusticucci, L. V. Alexander, Fund, Washington, DC. S. Brönnimann, Y. Charabi, F. J. Dentener, E. J. Dlugokencky, Patz, J. A. et al., The potential health impacts of climate variability and D. R. Easterling, A. Kaplan, B. J. Soden, P. W. Thorne, M. Wild and change for the United States: executive summary of the report of P. M. Zhai, 2013: Observations: Atmosphere and Surface. In: Climate the health sector of the U.S. National Assessment. Environ. Health Change 2013: The Physical Science Basis. Contribution of Working Perspect., 108(4): 367–76 (2000). Group I to the Fifth Assessment Report of the Intergovernmental Panel Patz, Jonathan, A. Patz, Howard Frumkin, Tracey Holloway, Daniel J. on Climate Change [Stocker, T. F., D. Qin, G.-K. Plattner, M. Tignor, Vimont, and Andrew Haines, 2014. Climate Change: Challenges and S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P. M. Midgley Opportunities for Global Health, JAMA, doi:10.1001/jama.2014.13186. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and Rogelj, J. et al., 2014. “Disentangling the effects of CO2 and short-lived New York, NY, USA. climate forcer mitigation,” PNAS, www.pnas.org/cgi/doi/10.1073/ Hamilton, Kirk, Milan Brahmbhatt, Nicholas Bianco and Jiemei Liu, 2014. pnas.1415631111. Multiple Benefits from Climate Mitigation: Assessing the evidence, Shindell, Drew T., The social cost of atmospheric release, Climatic Change, background paper for New Climate Economy report, Global Commis- published online: 25 February, 2015. DOI 10.1007/s10584-015-1343-0. sion on Climate and Economy, c/o WRI, Washington, DC. Silliman, J., Kharin, V. V., Zwiers, F. W., Zhang, X., and Bronaugh, D., IEA, 2014. Capturing the Multiple Benefits of Energy Efficiency, ISBN 978- 2013. “Climate extremes indices in the CMIP5 multimodel ensemble— 92-64-22072-0, International Energy Agency, Paris, 232 pp. Part 2—Future climate projections.” Journal of Geophysical Research IHME, 2010. Institute for Health Metrics and Evaluation, University of Atmospheres, v. 118, no. 6, p. 2473–2493. Washington, Seattle. Global Health Data Exchange, Global Burden of Smith, K. R., A. Woodward, D. Campbell-Lendrum, D. D. Chadee, Y. Honda, Disease Study 2010 (GBD 2010) Data Downloads, GBD 2010 Results Q. Liu, J. M. Olwoch, B. Revich, and R. Sauerborn, 2014: Human by Risk Factor 1990–2010, available at http://ghdx.healthdata.org/ health: impacts, adaptation, and co-benefits. In: Climate Change 2014: global-burden-disease-study-2010-gbd-2010-data-downloads Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral IHME, 2015. Institute for Health Metrics and Evaluation, University of Aspects. Contribution of Working Group II to the Fifth Assessment Washington, Seattle. Global Health Data Exchange, Global Burden of Report of the Intergovernmental Panel on Climate Change [Field, C. B., Disease Study 2013 (GBD 2013) Data Downloads, available at http:// V. R. Barros, D. J. Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilir, vizhub.healthdata.org/gbd-compare/# M. Chatterjee, K. L. Ebi, Y. O. Estrada, R. C. Genova, B. Girma, Jacob, Daniel J., and Darrel A. Winner, 2009. Effect of climate change on E. S. Kissel, A. N. Levy, S. MacCracken, P. R. Mastrandrea, and air quality. Atmospheric Environment 43(1): 51–63. L. L. White (eds.)]. Cambridge University Press, Cambridge, United Kjellstrom, 2009. http://www.ncbi.nlm.nih.gov/pubmed/20007118 Kingdom and New York, NY, USA, pp. 709–754. Knowlton, K. et al., 2011. “Six Climate Change-Related Events in the United Thompson, Tammy M., Sebastian Rausch, Rebecca K. Saari, and Noelle E. States Accounted for about $14 Billion in Lost Lives and Health Costs,” Selin, 2014. A systems approach to evaluating the air quality co-benefits doi: 10.1377/hlthaff.2011.0229, Health Aff., November 2011 vol. 30 of US carbon policies, Nature Climate Change, published online: 24 no. 11 2167–2176. http://content.healthaffairs.org/content/30/11/2167 August, 2014, DOI: 10.1038/NCLIMATE2342. .full United Nations. The Millennium Development Goals Report (2015). United Lim et al., 2012. “A comparative risk assessment of burden of disease Nations. New York, NY.  and injury attributable to 67 risk factors and risk factor clusters in UNEP, 2011a. Near-term Climate Protection and Clean Air Benefits: Actions 21 regions, 1990–2010: a systematic analysis for the Global Burden of for Controlling Short-Lived Climate Forcers, United Nations Environ- Disease Study 2010,” Lancet 2012; 380: 2224–60. ment Programme (UNEP), Nairobi, Kenya, 78 pp. McMichael, A. “Global Climate Change,” (pp. 1543–1650), by D. Campbell- UNEP, 2011b. HFCS: A Critical Link in Protecting Climate and the Ozone Lendrum, S. Kovats, S. Edwards, P. Wilkinson, T. Wilson, Layer—A UNEP Synthesis Report. United Nations Environment Pro- R. Nicholls, S. Hales, F. Tanser, D. Le Sueur, M. Schlesinger and gramme (UNEP), Nairobi, Kenya. N. Andronova (2004). In Comparative Quantification of Health U.S. Environmental Protection Agency, 1998. Draft Integrated Urban Air Risks, Global and Regional Burden of Disease Attributable to Selected Toxics Strategy to Comply with Section 112(d), 112(c)(3) and Section Major Risk Factors : M. Ezzati M, A. D. Lopez, A. Roders and 202(l) of the Clean Air Act; Notice. Fed Register 63(177): 49239–49258. C. J. L. Murray (eds.), World Health Organization, Geneva, Switzerland. U.S. EPA, 2012. “Report to Congress on Black Carbon.” U.S. Environmental Protection Agency, Washington, D.C. 40 Refe r enc es U.S. EPA, 2013. “Integrated Science Assessment for Particulate Matter (Final .who.int/phe/health_topics/outdoorair/databases/FINAL_HAP_AAP_ Report).” U.S. Environmental Protection Agency, EPA/600/R-08/139F, BoD_24March2014.pdf, accessed 10 May 2015. 2009: Washington, DC. Accessed October 15, 2013: http://cfpub.epa WHO Global Malaria Report, 2013. World Health Organization. Geneva, .gov/ncea/cfm/recordisplay.cfm?deid=216546 Switzerland. Van Donkelaar, Aaron et al., 2015. “Use of Satellite Observations for Long World Bank, 2010. Economics of adaptation to climate change— Term Exposure Assessment of Global Concentrations of Fine Particulate Synthesis report . Washington, DC: World Bank. http:// Matter.” Environmental Health Perspectives. documents.worldbank.org/curated/en/2010/01/16436675/ Watts, Nick, W. Neil Adger, Paolo Agnolucci, Jason Blackstock, Peter Byass, economics-adaptation-climate-change-synthesis-report Wenjia Cai, Sarah Chaytor, Tim Colbourn, Mat Collins, Adam Cooper, ———. 2012. Turn Down the Heat: Why a 4°C Warmer World Must Be Peter M. Cox, Joanna Depledge, Paul Drummond, Paul Ekins, Victor Avoided. A report for the World Bank by the Potsdam Institute for Galaz, Delia Grace, Hilary Graham, Michael Grubb, Andy Haines, Ian Climate Impact and Climate Analytics. Washington, DC: World Bank. Hamilton, Alasdair Hunter, Xujia Jiang, Moxuan Li, Ilan Kelman, Lu ———. 2013. Turn Down the Heat: Climate Extremes Regional Impacts, and Liang, Melissa Lott, Robert Lowe, Yong Luo, Georgina Mace, Mark the Case for Resilience. A report for the World Bank by the Potsdam Maslin, Maria Nilsson, Tadj Oreszczyn, Steve Pye, Tara Quinn, My Institute for Climate Impact and Climate Analytics. Washington, DC: Svensdotter, Sergey Venevsky, Koko Warner, Bing Xu, Jun Yang, World Bank. Yongyuan Yin, Chaoqing Yu, Qiang Zhang, Peng Gong, Hugh Mont- ———. 2014. Turn Down the Heat: Confronting the New Climate Normal. A gomery, Anthony Costello, 2015. “Health and climate change: policy report for the World Bank by the Potsdam Institute for Climate Impact responses to protect public health.” The Lancet, Vol. 386, No. 10006. and Climate Analytics. Washington, DC: World Bank. West, J. Jason, Steven J. Smith, Raquel A. Silva, Vaishali Naik, Yuqiang World Bank/ClimateWorks, 2014. Climate-Smart Development: Adding Zhang, Zachariah Adelman, Meridith M. Fry, Susan Anenberg, Larry up the benefits of actions that help build prosperity, end poverty and W. Horowitz and Jean-Francois Lamarque, 2013. Co-benefits of mitigat- combat climate change. The World Bank, Washington, DC, and the ing global greenhouse gas emissions for future air quality and human ClimateWorks Foundation, San Francisco, CA. health, Nature Climate Change, published online: 22 September, 2013, World Bank/ICCI, 2013. On Thin Ice: How cutting pollution can slow DOI: 10.1038/NCLIMATE2009. warming and save lives, The World Bank, Washington, DC and the Wheeler, 2011. http://www.cgdev.org/sites/default/files/1424759_file_ International Cryosphere Climate Initiative, Charlotte, VT. Wheeler_Quantifying_Vulnerability_FINAL.pdf World Bank/ICCT, 2014. Reducing Black Carbon Emissions from Diesel WHO, 2009. Global Health Risks: Mortality and burden of disease attrib- Vehicles: Impacts, Control Strategies, and Cost-Benefit Analysis, The utable to selected major risks, World Health Organization, Geneva, World Bank and the International Council on Clean Transportation, Switzerland. Washington D.C. WHO, 2013. Protecting health from climate change: vulnerability and adap- World Bank/World Health Organization, 2014. Monitoring Progress Towards tation assessment. World Health Organization, Geneva, Switzerland. Universal Health Coverage at Country and Global Levels: Framework, WHO, 2014a. WHO Indoor Air Quality Guidelines: Household Fuel Combus- Measures and Targets. Joint WHO/WB paper. Washington, DC, Geneva. tion, World Health Organization, Geneva, Switzerland. WMO/IGAC, 2012. Impacts of Megacities on Air Pollution and Climate, World WHO, 2014b. Quantitative risk assessment of the effects of climate change Meteorological Organization, Global Atmosphere Watch (WMO/GAW) on selected causes of death, 2030s and 2050s. World Health Organiza- Geneva, Switzerland and International Global Atmospheric Chemistry tion, Geneva, Switzerland. project (IGAC), Boulder, Co. ISBN 978-0-9882867-0-2. WHO, 2014c. Burden of disease from household air pollution for 2012. Xu Y. et al., 2013. The role of HFCs in mitigating 21st century climate Summary of results. Geneva: World Health Organization http://www change, Atmos Chem Phys 13:6083–6089. 41 annex A Typology of Pollutants That Drive Climate Change, Health Impacts, or Both Carbon Dioxide and Long-Lived Greenhouse Gases The chief driver of climate change is unquestionably carbon dioxide (CO2) due to its long atmospheric lifetime and its key role in stabilizing the climate system at a habitable temperature. Human activities have altered the global carbon cycle causing a rise in ambient concentrations of CO2 and upsetting a balance that has been in place for centuries. Based on the latest observations, a 7.5 percent increase in radiative forcing from greenhouse gases (GHGs) occurred between 2005 and 2011 alone, with CO2 contributing 80 percent toward this increase (Hartmann et al., 2013). Long-term climate stabilization cannot be achieved without large and rapid reductions of CO2 emission that achieve net zero carbon emissions in the latter half of this century (World Bank, 2014). The sources of CO2 are numerous and include virtually all forms of combustion spanning our energy system, as well as a few other sources such as the calcination reaction in cement production (Fischedick, et al., 2014). While CO2 itself is not toxic to humans at ambient concentrations, it is almost never emitted alone. Rather, a wide variety of co-emitted pollutants constituting a large majority of global air pollution accompany the release of CO2 from various combustion sources. The variation in sources tracks the variation in co-emitted pollution and, therefore, the variation in health impacts. Nitrogen oxides (NOX), sulfur dioxide (SO2), mercury and other heavy metals accompany the CO2 emitted from fossil-fuel power generating facilities. These co-emitted pollutants vary considerably in terms of their emission rate depending on the fuel type and the degree of post-combustion control technology in use at individual generating units. These pollutants play a significant role in the second- ary formation of particulate matter (PM2.5) and contribute to the regional transport and formation of ground-level ozone (WMO/IGAC, 2012). Transportation sources (cars, trucks, buses, aircraft), residential and commercial buildings, and industrial sources also are collectively significant sources of CO2 while emitting NOX, SO2, volatile organic compounds (VOC) and carbon monoxide (CO), which is subsequently oxidized to become CO2, and other precursors to fine particulate matter and ground-level ozone. Short-Lived Climate Pollutants (SLCPs) SLCPs, such as black carbon (BC), methane (CH4), ground-level ozone (O3), and many hydrofluoro- carbons (HFCs), have a warming effect on climate, and most of them are also dangerous air pollutants with detrimental impacts on human health, agriculture and ecosystems (CCAC, 2013). The rapid reduc- tion of black carbon emissions along with co-emitted components of particulate matter could avert approximately 0.18–0.19°C of warming by 2050 (Rogelj et al., 2014; Shindell et al., 2012). Interventions that address methane could yield a similar climate benefit with combined temperature reductions of 43 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth black carbon and methane estimated at 0.4–0.5°C in 2050 (UNEP, precursor of ground-level ozone (CCAC, 2013). Ozone air pollu- 2011a; World Bank/ICCI, 2013). Recent studies estimate that replac- tion has been estimated to cause around 150,000 deaths annually ing high-Global Warming Potential (GWP) HFCs with low-GWP worldwide and affects the health of many more (Lim et al., 2012). alternatives could avoid an additional 0.1°C of warming by 2050 Ozone near the surface in the lower atmosphere is harmful (Xu Y. et al., 2013). to human health and ecosystems due to its ability to oxidize bio- In total, SLCPs could avoid more than half a degree of tem- logical tissue. A common human health impact of ground-level perature rise over the next several decades while climate adapta- ozone is respiratory illnesses such as asthma in children (WMO/ tion measures are being deployed and implemented, extending IGAC, 2012). It also damages ecosystem structure and functions and improving the quality of lives. It is important to point out and the health and productivity of crops, thus threatening food that—precisely because of the significant overlap in sources security. Ozone also reduces the ability of plants to absorb CO2, that emit both CO2 and SLCPs—the degree of avoided warming altering their growth and variety and threatening food security through SLCP measures alone is strongly dependent on the rate and malnutrition in the case of staple crops. of coincident carbon mitigation (Rogelj et al., 2014). While HFCs emissions are currently small, they are projected to Several sectors have black carbon-rich sources that emit varying rise and could be equivalent to 7 to 19 percent of CO2 emissions by amounts of black carbon along with several other co-emitted air 2050 (UNEP 2011b); however, they do not have adverse air quality- pollutants including: agriculture-related open burning, residential related health effects similar to black carbon, methane or ozone. energy, transportation, industry (especially brick kilns), and oil and gas flaring. Black carbon is only one component of primary PM2.5 Co-Emitted Air Pollutants with Air and typically makes up less than 10 percent of ambient PM2.5 mass Quality/Health Impacts (Bond et al., 2013), but can constitute much higher fractions for specific sources such as diesel particulate emissions. Diesel par- In addition to greenhouse gases and SLCPs, there are a variety of ticulate emissions can be up to 80 percent black carbon by weight other common air pollutants that originate from common sources as for older vehicles (Bond et al., 2007, World Bank/ICCT, 2014). the many drivers of climate change discussed above. In particular, The residential sector bears special mention due to the propor- the precursor pollutants that aid in secondary formation of fine tionately high burden of disease attributable to black carbon and particulate and ground-level ozone (i.e., sulfur dioxide, nitrogen co-emitted PM2.5 from this sector. It is the second largest source of oxides, non-methane VOCs, etc.) do not typically result in direct black carbon emissions, primarily linked with the residential burning health impacts at their regulated levels observed in most parts of biomass, but also other solid fuels, for cooking and heating. Some of the world, but their co-emission is responsible for the bulk of 3 billion people in the developing world—representing nearly half the adverse public health exposure to air quality. This result is the world’s population—burn solid fuels such as wood, dung, coal, explained by the fact that the majority of PM2.5 mass is typically charcoal and crop residues in traditional stoves and open fires for comprised of secondary sulfate, nitrate or organic material (and, these purposes (U.S. EPA, 2012). The World Health Organization unlike black carbon, these components of particulate matter do (WHO, 2014a) estimates that 4.3 million deaths a year worldwide not drive climate change; in fact, they mostly act to offset global are attributed to diseases associated with cooking and heating with warming by reflecting some degree of solar radiation back to space). solid fuels. This includes household exposure to cooking smoke Methane aids the increase of global background concentrations of as well as the contribution of this smoke to ambient pollution ground-level ozone, but contributes a far smaller proportion of the outside the home. In 2010, household cooking with solid fuels observed peak (urban) ground-level ozone exposure that leads to accounted for 12 percent of ambient PM2.5 globally, varying from the majority of severe health effects. Peak urban concentrations zero percent in five high-income regions to 37 percent (2.8 μg/m3 are a combination of local emissions of NOX and non-methane of 6.9 μg/m3 total) in southern Sub-Saharan Africa (Chafe et al., VOC combining with regionally transported precursors and global 2014). In fact, pollution from cooking kills more men, women, background ozone (WMO/IGAC, 2012). and children than AIDS, malaria, and tuberculosis combined. In Finally, mercury, benzene, dioxin and a variety of other air addition to these premature deaths, millions more are sickened toxics are released via different combustion processes related to from acute and chronic lung and heart diseases while hundreds of many of the sources listed previously. While these pollutants do thousands more suffer burns or disfigurement from open flames not have a direct role in altering the climate in the near-term or and dangerous cookstoves. over the long-term, they have a significant effect on health (U.S. Methane has indirect impacts on human health and ecosystems, EPA, 1998). including agricultural production, through its role as the primary 44 Annex B Geographic Analysis of Climate Drivers Greenhouse gas emissions serve as an excellent basis for identifying hotspots that reflect the drivers of climate change. Table B.1 presents national emissions of greenhouse gas (GHG) emissions expressed as CO2 equivalent or CO2e (sorted two ways). However, these lists are a relatively poor indicator of the geographical specificity of the health impacts given that the drivers of health impacts are the co-emitted pollutants that accompany emission of GHGs rather than the GHGs themselves. This imper- fect alignment between GHGs versus traditional air pollutants (fine particles and ground-level ozone) limits the analysis presented here. For example, the degree of overlap between climate and health drivers will differ significantly by national circumstance. China, U.S., India, Russia, and Japan top the list of GHG emitters and clearly are the focus of carbon mitigation efforts. However, with respect to health impacts of co-emitted air pollution, these countries are at very different stages of addressing their air quality concerns. Table B.2 presents similar data on greenhouse gas emissions, but it presents the top 10 GHG emitters within various income brackets sorted by gross national income per capita. Countries at the top of these lists will have lower economic efficiency per unit of GHG emissions (alternatively, these countries could be described as having a relatively higher GHG intensity per unit of GDP). This often is correlated with less efficient combustion and greater health impacts, but also will result in less direct association with the determinants of health most directly associated with mitigation activities discussed in the main text. A second way to examine the same data is by income bracket. The second list also presents to top GHG emitters (expressed in CO2e) but presents only the top 10 emitters for each income bracket based on the World Bank fiscal year 2015 income classifications (high income with annual per capita GNI ≥ US$12,746; upper-middle income: US$4,125–12,745, lower-middle income: US$1,046–4,125, and lower-income ≤ US$1,045). 45 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Table B.1: Climate driver mapping, based on carbon. The Table B.2: Top carbon emitters by income bracket. data below are taken from the World Bank World Development Indicators database (data.worldbank.org) and include country- 2010 Top Income Brackets Based on 2013 Carbon Emitters level data for the top carbon emitters as of 2010. It presents GNI per Capita (Atlas Method) (kton CO2e) all countries that emit more than 100 million metric tons Bangladesh 56,153 (100,000 ktons) of carbon dioxide equivalent annually. Zimbabwe 9,428 2010 Top Carbon Emitters Afghanistan 8,236 (kton (CO2e) Tanzania 6,846 Low Income China 8,286,892 Ethiopia 6,494 United States 5,433,057 Benin 5,189 India 2,008,823 Cambodia 4,180 Russian Federation 1,740,776 Uganda 3,784 Japan 1,170,715 Nepal 3,755 Germany 745,384 Congo, Dem. Rep. 3,040 Iran, Islamic Rep. 571,612 India 2,008,823 Korea, Rep. 567,567 Indonesia 433,989 Canada 499,137 Lower-Middle Income Ukraine 304,805 United Kingdom 493,505 Egypt, Arab Rep. 204,776 Saudi Arabia 464,481 Pakistan 161,396 South Africa 460,124 Vietnam 150,230 Mexico 443,674 Uzbekistan 104,443 Indonesia 433,989 Philippines 81,591 Brazil 419,754 Nigeria 78,910 All Income Levels Italy 406,307 Morocco 50,608 Australia 373,081 China 8,286,892 France 361,273 Iran, Islamic Rep. 571,612 Poland 317,254 Upper-Middle Income South Africa 460,124 Ukraine 304,805 Mexico 443,674 Turkey 298,002 Brazil 419,754 Thailand 295,282 Turkey 298,002 Spain 269,675 Thailand 295,282 Kazakhstan 248,729 Kazakhstan 248,729 Malaysia 216,804 Malaysia 216,804 Egypt, Arab Rep. 204,776 Venezuela, RB 201,747 Venezuela, RB 201,747 United States 5,433,057 Netherlands 182,078 Russian Federation 1,740,776 Pakistan 161,396 Japan 1,170,715 Vietnam 150,230 Germany 745,384 High Income Algeria 123,475 Korea, Rep. 567,567 Iraq 114,667 Canada 499,137 Czech Republic 111,752 United Kingdom 493,505 Belgium 108,947 Saudi Arabia 464,481 Uzbekistan 104,443 Italy 406,307 Australia 373,081 46 Ge o g r ap h i c A naly s i s o f Cli mat e D riv e rs The short-lived pollutants black carbon and methane are also from direct exposure to fine particulate matter will occur as well. drivers of climate change and may serve as a better geographical Figure B.2 (U.S. EPA, 2012) shows the geographical distribution indicator of health impacts. Black carbon is most directly linked to of two key components of black carbon climate impacts (direct local health impacts as a component of fine particulate pollution radiative forcing and cryosphere forcing). The radiative forcing with direct health effects. Figure B.1 presents global emissions of (warming or cooling) related to cloud impacts is more uncertain black carbon by region that provides a basis for assessing where and less understood. Again, South and East Asia show significant this pollutant is likely having its greatest impact on health. Clearly, local forcing, but strong radiative forcing is apparent in Africa the developing world is a large source of black carbon and the as well. Here it is important to point out the role of open burn- concentration of industrial and biofuel cooking sources in South ing in the black carbon climate forcing because the high organic and East Asia make this a likely candidate for significant health carbon co-emitted through biomass combustion may offset some effects given what is known about the health impacts of these degree of this climate forcing, particularly in Africa. The greatest source categories. cryosphere forcing occurs near snow and ice where both black Unlike CO2, the climate impacts of black carbon are not dis- carbon and organic carbon are absorbing incoming solar energy tributed uniformly, and it will have the greatest warming effect relative to underlying snow which would reflect back to space in close to where it is emitted. This is where the health impacts absence of the emissions. Figure B.1: Global emissions of black carbon estimated for 2000, (Bond et al., 2014). Totals are presented from two different emissions models (SPEW and GAINS) as reflected by the black and red dots. North America (380) Latin America (1150) Africa Emission sources (1690) Diesel engines On-road Europe Off-road (470) Industrial coal EECCA Residential solid fuel (400) Biofuel cooking Biofuel heating Middle East Coal (80) Open burning Agricultural fields South Asia Forests (710) Grasses and woodlands Other Southeast Asia SPEW/RETRO (850) GAINS/GFED East Asia (1550) Pacific (320) (Total 7620) 0 1000 2000 3000 –1 Black carbon (BC) emissions (Gg yr ) 47 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth The geographical influence of methane for both health and a methane effect that is global in nature whereas co-emitted NOx climate (and the climate influence of short-lived HFCs) is less and VOC species contribute to local health impact. region-specific and more global given the longer atmospheric life- In summary, this analysis demonstrates that the drivers of time relative to black carbon (several years versus several days). climate change have geographical patterns that are identified While the health impacts of ground-level ozone are normally in the main text, but are less direct means of establishing areas quite local, the contribution of methane to ozone health impacts that will enjoy the greatest health benefits of mitigation action. is through a shift in the global background concentration to which For that, metrics explored in the main text and Annex C provide local air pollutants are added (analogous to the rising global sea a more direct relationship between mitigation opportunities and level that contributes to higher local storm surges). This results in health benefits. Figure B.2: Direct radiative forcing as measured from the top of atmosphere (TOA) and cryosphere forcing due to black carbon (U.S. EPA, 2012). Black carbon direct TOA forcing (W m–2) 90 5 2 45 1 0.5 0 0.25 –45 0.1 0.05 –90 0.025 Black carbon cryosphere forcing (W m–2) 90 5 2 45 1 0.5 0 0.25 –45 0.1 0.05 –90 0.025 48 annex C Health Driver Mapping Based on Burden of Disease The data below are taken from 2013 Global Burden of Disease analysis performed by the Institute of Health Metrics and Evaluation and the Health Effects Institute (IHME, 2015). Both tables present the population normalized burdens of disease (in terms of disability adjusted life-years, or DALYs) attribut- able to ambient air pollution (AAP, in second column) and household air pollution (HAP, third column) in 2013 (fine particulate pollution only). Only countries with levels greater than one standard deviation above the median value of all countries appear in the table. The left table is ranked by AAP and the right table by HAP. Shaded rows indicate countries that lie more than one standard deviation (yellow), two standard deviations (orange) or three standard deviations above the median value in both lists. 49 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Table C.1: National (normalized) burden of disease statistics attributed to AAP (left) and HAP (right; DALYs per 10,000 for 2013, IHME, 2015). AAP DALYs HAP DALYs AAP DALYs HAP DALYs Country per 100,000 per 100,000 Country per 100,000 per 100,000 Turkmenistan 228.388051 1.11187139 Somalia 60.5118178 396.33399 Afghanistan 207.223582 380.847399 Afghanistan 207.223582 308.847399 Chad 191.352904 375.649164 Belarus 191.695099 0 Central African Republic 143.726699 357.632212 Chad 191.352904 375.649164 Guinea-Bissau 167.259832 341.828408 Ukraine 185.124223 0 Sierra Leone 144.486018 335.26503 Mali 168.284683 333.795889 Mali 168.284683 333.795889 South Sudan 108.941111 327.12751 Guinea-Bissau 167.259832 341.828408 Democratic Republic of the Congo 125.083904 324.669871 Niger 158.968447 300.156773 Niger 158.968447 300.156773 Bulgaria 158.268407 0 Guinea 133.863711 295.885737 Malawi 47.8550404 290.785126 North Korea 151.30028 290.113178 North Korea 151.30028 290.113178 Georgia 151.034944 196.754213 Madagascar 7.44873776 285.922488 Moldova 150.937578 0 Laos 133.37224 278.964656 Pakistan 146.881828 176.405974 Equatorial Guinea 70.8062025 278.11457 Papua New Guinea 11.8531166 274.684608 Sierra Leone 144.486018 335.26503 Cambodia 117.141596 259.70455 Central African Republic 143.726699 357.632212 Cote d’Ivoire 114.680685 252.95423 Mauritania 138.693702 147.169032 Burkina Faso 124.033842 252.951753 Russia 136.964143 0 Mongolia 39.106394 249.531494 Uzbekistan 136.439965 50.1864472 Cameroon 113.127537 246.701503 Burundi 82.3558195 244.446268 China 134.123987 113.164962 Myanmar 121.861776 242.389011 Guinea 133.863711 295.885737 Ethiopia 77.4468773 236.36928 Laos 133.37224 278.964656 Vanuatu 35.9112053 234.001744 Azerbaijan 131.891551 39.8601462 Solomon Islands 1.93796679 229.829575 Lesotho 82.4978805 226.849705 Kazakhstan 131.282442 47.2806374 Swaziland 72.4123257 225.3621043 Romania 130.235803 0 Liberia 89.674168 223.09878 India 130.209485 198.520454 Tanzania 34.6186236 219.286747 Montenegro 127.276907 0 Angola 82.1992498 217.887781 The Gambia 111.983902 217.597183 Democratic Republic of the Congo 125.083904 324.669871 Togo 95.5500287 214.359994 Burkina Faso 124.033842 252.951753 Uganda 71.0824867 207.600994 Hungary 122.991597 0 Nigeria 119.589077 206.818103 Myanmar 121.861776 242.389011 Zambia 57.762024 201.836004 Nigeria 119.589077 206.818103 Congo 75.5663931 199.175204 India 130.209485 198.520454 Bangladesh 119.138114 179.097708 Georgia 151.034944 196.754213 Armenia 118.494999 32.5356619 Rwanda 65.2825362 196.216042 Lithuania 117.673751 0 Mozambique 16.598487 189.542522 Cambodia 117.141596 259.70455 Haiti 67.9417166 189.261689 Kiribati 30.2672153 179.408348 Cote d’Ivoire 114.680685 252.95423 Bangladesh 119.138114 179.097708 Kyrgyzstan 114.050048 120.449526 Eritrea 102.599388 178.308727 Tajikistan 113.78175 115.684734 Pakistan 146.881828 176.405974 Cameroon 113.127537 246.701503 Benin 80.7686672 171.51407 Comoros 9.31425875 171.447129 Macedonia 112.682453 0 Zimbabwe 38.7675456 166.936827 The Gambia 111.983902 217.597183 Kenya 39.947077 166.063523 Yemen 111.270068 68.1365278 Ghana 84.830794 165.329467 Serbia 110.850459 0 Timor-Leste 3.95407023 157.552039 Albania 110.240375 0 Nepal 96.5253526 154.354269 Sudan 88.4549174 153.421977 Latvia 109.864679 0 Sao Tome and Principe 8.27023498 151.478872 South Sudan 108.941111 327.12751 Sri Lanka 67.7922612 151.016328 Mauritania 138.693702 147.169032 Philippines 37.8390512 146.2448 50 annex D Adaptation Approaches to Manage Current and Projected Risks of Climate Change to Health Non-health Sector Examples Health Sector Examples Improved access to education, energy, safe housing, Universal coverage of quality essential health and nutrition settlement structures and social support structures. services, increased access to health facilities. Increased Reduced gender inequality and marginalization. coverage of public health services such as vector control measures and surveillance. Improved access to, and control, of local resources: land Universal financial coverage for health services. Subsidies tenure, disaster risk reduction, social safety nets and to increase demand for basic and preventive health social protection insurance. services. Income, asset and livelihood diversification, improved infrastructure; access to technology and decision making forums; increased decision making power; changed cropping, livestock and aquaculture practices; reliance on social networks. Early-warning systems; hazard and vulnerability mapping; Climate-sensitive disease & morbidity surveillance & diversifying water resources; improved drainage; floods forecasting systems; heat waves, epidemics & emergency and cyclones shelter; building codes & practices; preparedness & response systems. Building codes & storm and weather management; transport and road practices for health facilities, back-up systems in health infrastructure improvements. facilities, resilient health services infrastructure and communication systems, alternative routes to health facilities; Air & water quality and temperature alert systems. Maintaining wetlands & urban green spaces; coastal Vector and pests control and management by reduction/ afforestation; watershed & reservoir management; elimination of breeding sites. reduction of other stressors on ecosystems and habitat fragmentation, maintenance of genetic biodiversity. Provision of adequate housing, infrastructure & services; Locating new health facilities taking into consideration managing development in flood prone and other high potential extended flood areas, alternative routes to risk areas; urban planning and upgrading programs; land reach health facilities, strategic situation of health facilities zoning laws; easement areas. according to disaster preparedness and response plans. Engineering and built environment options: sea walls, Building codes and practices for health facilities, back-up flood levees, & costal protection structures; water systems in health facilities, resilient health services storage, improved drainage power plant & electricity grid infrastructure and communication systems, alternative adjustments. routes to health facilities, etc. 51 G eo g r a phic hots p ot s f or wor l d b a nk acti o n o n cli mate chan g e and he alth Non-health Sector Examples Health Sector Examples Technology options: new crop and animal varieties, Vaccines, development if new drugs; Climate-sensitive indigenous, traditional knowledge and methods, efficient disease and morbidity forecasting and surveillance irrigation, desalinization, food storage and preservation, systems, health waves, epidemics & emergency hazard and vulnerability mapping and monitoring, early preparedness & response systems. Climate adequate warning systems, building insulation. health infrastructure, to minimize the use of energy to maintain adequate temperature. Accelerated vaccine development, temperature stable diagnostic text, drugs & vaccines. Ecosystems-based options: ecological restoration; soil Natural & genetic vector control systems. Reduction of conservation; afforestation & reforestation; mangrove vector bleeding sites. conservation and replanting, assisted species migration and green infrastructure, control overfishing, seed banks, gene banks. Services: social safety nets & social protection; food Vaccination programs essential public health services banks & distribution of food surplus; municipal services including surveillance; enhanced emergency medical (water & sanitation). services. Economic options: financial incentives; insurance; Health insurance, including catastrophic health insurance. catastrophe bonds; payments for ecosystem services; pricing water to encourage universal provision and careful use. Laws and regulations: land zoning laws, building standard Building codes, laws to encourage health insurance and practices, easements, whether regulations. purchasing. National & subnational government policies & programs: Health system adaptation and disaster preparedness National and subnational adaptation plans. plans at all levels of health system linked to other sectoral adaptation & disaster plans. Educational options awareness raising & integration into Awareness raising of climate impacts & health emergency education gender equity in education, extension services signs integrated in medical education & in health services sharing indigenous, traditional and local knowledge. to population and patients. Medical education includes Participatory action research. emerging diseases. Information options: hazard and vulnerability mapping; Climate-sensitive disease and morbidity surveillance & early warning & response system, systematic monitoring forecasting systems linked to climate services, health and remote sensing; climate services; participatory waves, epidemics & emergency preparedness, & response scenario development; integrated assessments. systems. Air & water quality & temperature alert system. Behavioral options: household preparation & evacuation Household awareness of actions in case of health alert or planning; migration; soil and water conservation; storm emergency, household knowledge of alternative routines and drain clearance ; livelihood diversification; changed to reach health facilities and health facility location and cropping, livestock, & aquaculture practices. services provided in case of emergency. Practical: social and technical innovations, behavioral Practical: Technical innovations in forecasting, prevention, skills, or institutional & managerial changes that produce diagnostic and treatment options. substantial shift in outcomes. Political: Political, social, cultural, & ecological decisions & Political: political climate-smart decisions and investment actions consistent with reducing vulnerability & risk & for health system. supporting adaptation and sustainable development. Personal: individual & collective assumptions, beliefs, Personal: idem. values & worldviews influencing climate-change responses. 52 WORLD BANK REPORT NUMBER 113571-GLB