Document of
The World Bank
FOR OFFICIAL USE ONLY
Report No: ICR00006577
IMPLEMENTATION COMPLETION AND RESULTS REPORT
TF-A9121
ON A
GRANT
FROM THE GLOBAL ENVIRONMENT FACILITY
IN THE AMOUNT OF US$7,580,597
TO THE
PEOPLE'S REPUBLIC OF CHINA
FOR A
China: GEF Efficient and Green Freight Transport Project
August 27, 2024
Transport Global Practice
East Asia And Pacific Region
CURRENCY EQUIVALENTS
(Exchange Rate Effective December 31, 2023
Currency Unit = RMB
RMB 1.00 = US$0.14099
US$1.00 = RMB 7.09294
FISCAL YEAR
January 1 – December 31
Regional Vice President: Manuela V. Ferro
Country Director: Mara K. Warwick
Regional Director: Sudeshna Ghosh Banerjee
Practice Manager: Benedictus Eijbergen
Task Team Leader: Mengling Shen
ICR Main Contributor: Sam Johnson; Zhaoyuan Wang
ABBREVIATIONS AND ACRONYMS
BAU Business-As-Usual IWT Inland Waterway Transport
BRI Belt and Road Initiative LCS Least Cost Selection
CATS China Academy of LOGINK National Public Information Platform
Transportation Sciences for
CCM Climate Change Transportation and Logistics
Mitigation
CO2 Carbon Dioxide M&E Monitoring and Evaluation
CPS Country Partnership MAC Marginal Abatement Cost
Strategy
CQS Selection Based on MOF Ministry of Finance
Consultants’
Qualifications MOT Ministry of Transport
CTN China Transport News NCB National Competitive Bidding
DA Designated Account NPMO National Project Management Office
DLI Disbursement Linked OECD Organization for Economic Co-
Indicator operation
DS Direct Selection and Development
EA Executing Agency PDO Project Development Objective
ESMF Environmental and Social PIU Project Implementing Unit
Management
Framework PMO Project Management Office
EU European Union PP Procurement Plan
FB Finance Bureau PPSD Project Procurement Strategy for
FBS Fixed Budget Selection Development
FM Financial Management PQA Professional Qualification Authority
FMM Financial Management PSG Project Steering Group
Manual
GA Grant Agreement QCBS Quality and Cost Based Selection
GDP Gross Domestic Product RIOH Research Institute of Highway
GEF Global Environment RMB Renminbi
Facility
GHG Greenhouse Gas SOE Statement of Expenditure
GRS Grievance Redress SORT Systematic Operations Risk-rating
Service Tool
IBRD International Bank for TA Technical Assistance
Reconstruction and
Development TOR Terms of Reference
IC Individual Consultant TPRI Transport Planning and Research
ICB International Institute
Competitive Bidding
ICT Information and TransFORM Transport Transformation and
Communication Innovation Platform
Technology
IDA International US$ United States Dollar
Development Association
IEA International Energy WA Withdrawal Application
Agency
INDC Intended Nationally WTRI Waterborne Transport Research
Determined Institute
Contribution YREB Yangtze River Economic Belt
TABLE OF CONTENTS
DATA SHEET ......................................................................................................................... Ⅰ
I. PROJECT CONTEXT AND DEVELOPMENT OBJECTIVES ....................................................... 1
A. CONTEXT AT APPRAISAL .........................................................................................................1
B. SIGNIFICANT CHANGES DURING IMPLEMENTATION (IF APPLICABLE) .......................................5
II. OUTCOME ...................................................................................................................... 6
A. RELEVANCE OF PDOs ..............................................................................................................6
B. ACHIEVEMENT OF PDOs (EFFICACY) ........................................................................................7
C. EFFICIENCY ........................................................................................................................... 18
D. JUSTIFICATION OF OVERALL OUTCOME RATING .................................................................... 18
E. OTHER OUTCOMES AND IMPACTS (IF ANY) ............................................................................ 18
III. KEY FACTORS THAT AFFECTED IMPLEMENTATION AND OUTCOME ................................ 19
A. KEY FACTORS DURING PREPARATION ................................................................................... 19
B. KEY FACTORS DURING IMPLEMENTATION ............................................................................. 19
IV. BANK PERFORMANCE, COMPLIANCE ISSUES, AND RISK TO DEVELOPMENT OUTCOME .. 20
A. QUALITY OF MONITORING AND EVALUATION (M&E) ............................................................ 20
B. ENVIRONMENTAL, SOCIAL, AND FIDUCIARY COMPLIANCE ..................................................... 21
C. BANK PERFORMANCE ........................................................................................................... 22
D. RISK TO DEVELOPMENT OUTCOME ....................................................................................... 23
V. LESSONS AND RECOMMENDATIONS ............................................................................. 23
ANNEX 1. RESULTS FRAMEWORK AND KEY OUTPUTS ........................................................... 25
ANNEX 2. BANK LENDING AND IMPLEMENTATION SUPPORT/SUPERVISION ......................... 35
ANNEX 3. PROJECT COST BY COMPONENT ........................................................................... 38
ANNEX 4. EFFICIENCY ANALYSIS ........................................................................................... 39
ANNEX 5. CARBON EMISSION REDUCTION CALCULATION .................................................... 40
ANNEX 6. BORROWER, CO-FINANCIER AND OTHER PARTNER/STAKEHOLDER COMMENTS ... 59
The World Bank
China: GEF Efficient and Green Freight Transport Project (P159883)
DATA SHEET
BASIC INFORMATION
Product Information
Project ID Project Name
P159883 China: GEF Efficient and Green Freight Transport Project
Country Financing Instrument
China Investment Project Financing
Original EA Category Revised EA Category
Partial Assessment (B) Partial Assessment (B)
Organizations
Borrower Implementing Agency
PEOPLE'S REPUBLIC OF CHINA Ministry of Transport
Project Development Objective (PDO)
Original PDO
The development objective of the project is to (i) improve the Recipient’s institutional capacity to formulate and
evaluate policies and strategies to promote green freight transport systems; and (ii) pilot innovative carbon
emission reduction measures in the freight transport sector in selected provinces.
PDO as stated in the legal agreement
The development objective of the project is to (i) improve the Recipient’s institutional capacity to formulate and
evaluate policies and strategies to promote green freight transport systems; and (ii) pilot innovative carbon
emission reduction measures in the freight transport sector in selected provinces.
I
The World Bank
China: GEF Efficient and Green Freight Transport Project (P159883)
FINANCING
Original Amount (US$) Revised Amount (US$) Actual Disbursed (US$)
World Bank Financing
8,246,095 7,580,597 7,580,597
TF-A9121
Total 8,246,095 7,580,597 7,580,597
Non-World Bank Financing
0 0 0
Borrower/Recipient 5,420,000 5,420,000 13,629,309
Total 5,420,000 5,420,000 13,629,309
Total Project Cost 13,666,095 13,000,597 21,209,906
KEY DATES
Approval Effectiveness MTR Review Original Closing Actual Closing
18-Dec-2018 31-May-2019 22-Nov-2021 31-Dec-2022 31-Dec-2023
RESTRUCTURING AND/OR ADDITIONAL FINANCING
Date(s) Amount Disbursed (US$M) Key Revisions
01-Dec-2022 3.83 Change in Results Framework
Change in Components and Cost
Change in Loan Closing Date(s)
Change in Implementation Schedule
KEY RATINGS
Outcome Bank Performance M&E Quality
Satisfactory Satisfactory Substantial
RATINGS OF PROJECT PERFORMANCE IN ISRs
Actual
No. Date ISR Archived DO Rating IP Rating Disbursements
(US$M)
01 21-Apr-2019 Satisfactory Satisfactory 0
II
The World Bank
China: GEF Efficient and Green Freight Transport Project (P159883)
02 13-Dec-2019 Satisfactory Moderately Satisfactory 0
03 30-Jun-2020 Satisfactory Moderately Satisfactory 1.00
04 02-Sep-2020 Satisfactory Moderately Satisfactory 1.00
05 04-Mar-2021 Satisfactory Moderately Satisfactory 1.36
06 07-Sep-2021 Moderately Satisfactory Moderately Satisfactory 1.77
07 14-Feb-2022 Moderately Satisfactory Moderately Satisfactory 2.76
08 19-Sep-2022 Moderately Satisfactory Moderately Satisfactory 3.62
09 18-Apr-2023 Satisfactory Moderately Satisfactory 4.83
10 25-Oct-2023 Satisfactory Satisfactory 5.75
SECTORS AND THEMES
Sectors
Major Sector/Sector (%)
Transportation 100
Urban Transport 20
Public Administration - Transportation 30
Rural and Inter-Urban Roads 10
Ports/Waterways 20
Railways 20
Themes
Major Theme/ Theme (Level 2)/ Theme (Level 3) (%)
Economic Policy 100
Trade 100
Trade Facilitation 63
Trade Logistics 100
Trade Policy 63
III
The World Bank
China: GEF Efficient and Green Freight Transport Project (P159883)
Private Sector Development 63
Regional Integration 63
ICT 63
ICT Solutions 63
Human Development and Gender 63
Gender 63
Environment and Natural Resource Management 100
Climate change 100
Mitigation 100
ADM STAFF
Role At Approval At ICR
Vice President: Victoria Kwakwa Manuela V. Ferro
Country Director: Bert Hofman Mara K. Warwick
Director: Guangzhe Chen Sudeshna Ghosh Banerjee
Practice Manager/Manager: Binyam Reja Benedictus Eijbergen
Project Team Leader: Hua Tan Mengling Shen
ICR Co Author: Sam William Johnson
IV
The World Bank
China: GEF Efficient and Green Freight Transport Project (P159883)
I. PROJECT CONTEXT AND DEVELOPMENT OBJECTIVES
A. CONTEXT AT APPRAISAL
Context
Country Context
1. China had experienced rapid economic growth over the previous three decades, resulting in increased energy
consumption and greenhouse gas (GHG) emissions. From 2002 to 2017, China's total energy consumption grew at an
annual rate of 6.3 percent, reaching 3105 Mtoe. During the same period, carbon dioxide (CO2) emissions increased at an
annual rate of 6.6 percent, reaching 9297 Mt. At the time of appraisal, China was the largest GHG emitter, accounting for
about one quarter of global GHG emissions. Reducing emissions in China is thus a global public good. To address these
challenges, the Chinese government had implemented various policies, strategies, and action plans to promote energy
conservation and carbon emission reduction. In 2015, China's Intended Nationally Determined Contribution (INDC) set a
target of reducing carbon intensity by 60 to 65 percent by 2030 compared to the 2005 level.
2. At the stage of project preparation, the project was consistent with the 2013-2016 World Bank Group’s Country
Partnership Strategy (CPS) for China (Report No. 67566-CN), where the World Bank Group’s China strategy focus in the
areas of Greener Development and Low-carbon Transport. In particular, it supported Strategic Theme 1 of the CPS:
Supporting Greener Growth.
Sectoral and Institutional Context
3. In order to maintain economic growth, while at the same time fulfil its commitment to global carbon reduction
and environmental sustainability, China needed to develop a cost competitive, efficient, and green freight transport
system as a national strategic priority. In 2016, total freight volume in China was 43 billion tons and 18 trillion ton-
kilometers. Compared to the United States, China’s total freight volume was approximately 2.5 times in tonnage terms
and 2 times in tonnage-kilometer terms. It was expected that China’s freight volume would continue to grow at an annual
rate of 7 to 8 percent during the 2016-2020 13th Five-Year Plan period.
4. Cost effective and environmentally friendly railway and waterway transport was underutilized. Seventy-six
percent of the freight in China was moved by carbon intensive road transport. The major impediments to intermodal
transport were: (i) lack of multimodal freight hubs to facilitate seamless connection between modes; (ii) lack of
standardization of transport units, equipment and operational rules and documentations of each mode, making the
interconnection between modes inefficient; (iii) institutional barriers between mode operators and lack of incentives for
them to work across modes; and (iv) lack of information sharing among various stakeholders, such as cargo owners, freight
forwarders, infrastructure operators, and carriers. Recognizing these challenges, the Government had instituted a series
of policies, as well as national intermodal pilot programs, to promote efficient and green multimodal freight transport. In
response, local governments were accelerating the planning of, and investment in, intermodal freight hubs and logistics
parks.
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China: GEF Efficient and Green Freight Transport Project (P159883)
5. There was an urgent need for a national freight flow model to support data-informed policy analysis and decision
making. China had identified several national and international freight and logistics corridors to support the new trade
routes and industrial development locations. However, the corridor plans were basic, and detailed development
strategies and investment plans needed to be developed based on a review of the major impediments in policies,
regulations, infrastructure, and operations.
6. Urban freight demand was rapidly increasing, driven in large part by booming e-commerce but approaches to
last mile urban distribution were inefficient. The unit cost of last-mile delivery was reported to be twice that of long-haul
transportation in China, and urban freight was a major source of air pollution, GHG emissions and traffic congestion. While
cities had taken steps to promote public transport and manage travel demand for passenger transport, relatively little
had been done to facilitate the flow of goods in urban areas and to reduce the adverse impacts of urban freight transport.
7. The trucking industry had great potential to reduce CO2 emissions. Although heavy duty trucks accounted for 10
percent of the on-road vehicle fleet in China, they used about 50 percent of the on-road fuel because of higher per-vehicle
fuel consumption. The trucking industry in China was of low concentration, with many small companies owning less than
10 trucks. Due to lack of proper regulations, trucks with poor facilities, old age and illegal modifications were not closely
regulated and had become a major source of air pollutants and GHG emissions. Meanwhile, with 20,000 types of freight
vehicles manufactured in China and less than 20 percent of them containerized, there was CO2 emissions reductions that
were waiting to be realized by upgrading the existing truck fleet to larger, more efficient, and standardized trucks.
8. The private sector was gradually increasing the use of big data and internet-of-things approaches to improve
logistics efficiency and service quality and reduce emissions. However, information was fragmented and owned by
individual companies. The public sector therefore had an important role to play in creating an open platform with
standardized protocols, so that information may be shared among all stakeholders so that the data could be used by the
public sector to support their decision making to make logistics greener and more efficient.
Theory of Change (Results Chain)
9. The following theory of change diagram illustrates the causal link between the project’s activities, outputs,
intermediate outcomes, and outcomes at appraisal.
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China: GEF Efficient and Green Freight Transport Project (P159883)
Project Development Objectives (PDOs)
10. The PDO, as stated both in the Loan Agreement and the PAD was (i) improve the Recipient’s institutional capacity
to formulate and evaluate policies and strategies to promote green freight transport systems; and (ii) pilot innovative
carbon emission reduction measures in the freight transport sector in selected provinces.
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China: GEF Efficient and Green Freight Transport Project (P159883)
Key Expected Outcomes and Outcome Indicators
11. The PDO indicators at appraisal were:
• Number of analytical tools adopted by MOT for implementation in national planning and policy development.
• Number of national plans adopted by MOT for implementation.
• Number of guidelines on improving urban freight transport issued by MOT for implementation; and
• Total CO2 emission reduction.
Components
12. The project supported the development of policy, strategy, analytical tools, and technical standards at the
national level to improve the efficiency and environmental sustainability of China’s freight transport sector, focusing on
two priority areas, i.e., promotion of multimodal freight transportation system and optimization of urban freight
distribution. It also funded piloting of key policy, strategy, and analytical tools at the local levels in five selected cities and
provinces. The Ministry of Transport (MOT) selected the pilots based on whether they were (i) in the strategic priority
areas of intermodal transport and urban distribution; (ii) innovative and representative of sector challenges for piloting
and scale-up; (iii) had greater potential in GHG emission reduction, and (iv) the financial and technical capacity of the
implementing entities. Lessons learned from the implementation experience of the pilots, polices, and analytical tools
were to be systematically documented and disseminated within China and in other World Bank client countries seeking
to develop green freight transport systems.
13. Component 1: National Technical Assistance (TA) and Policy Development (Total estimated cost at appraisal
US$4.85 million, GEF US$3.15 million). Provision of technical and analytical support to:
(a) The development of national policies, plans, strategies and standards for a low carbon multimodal
freight transportation system, including, inter alia: (i) a structural carbon emission reduction strategy
for the freight transport sector, including a national freight flow model; (ii) an action plan for efficient
and green freight transport corridors; and (iii) guidelines on multimodal freight transport development
for the economic belt of Yangtze River.
(b) The development of national policies and guidelines for green urban freight distribution, including,
inter alia: (i) guidelines for green and efficient urban freight transport development; and (ii) guidelines
and solutions for an e-commerce based urban freight distribution system.
(c) The development of an abatement cost analytical tool for freight transport carbon emission reduction.
14. Component 2: Subnational Technical Assistance (TA) and Pilots (Total estimated cost at appraisal US$3.05
million, GEF US$3.05 million). Provision of technical and analytical support to:
(a) Selected activities related to multimodal transport across the Bohai Gulf, including, inter alia: (i)
developing policies and incentives to attract freight traffic; (ii) evaluating the performance of local
logistics operators; (iii) developing solutions to improve the efficiency of freight transport; and (iv)
monitoring and evaluating carbon emission reduction.
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China: GEF Efficient and Green Freight Transport Project (P159883)
(b) Selected activities related to urban freight distribution in Weifang, including, inter alia: (i) collecting
urban freight data and installing emission monitoring sensors on sample trucks; (ii) developing
recommendations to improve the efficiency of urban freight distribution; and (iii) carrying out training
for truck drivers and campaigns on green urban freight distribution schemes.
(c) Selected activities related to sea-rail intermodal transport in the port of Xiamen, including, inter alia:
(i) the development of a multimodal transport information platform for sea-rail-road orders; and (ii)
the development of an optimization plan for multimodal freight transport operations.
(d) Selected activities related integrated urban-rural distribution in Guangdong, including, inter alia: (i)
the development of a transport organization plan for urban-rural integrated distribution; (ii) the
development of a common module for integrated urban-rural distribution and application of the
module in the existing logistics platform; (iii) monitoring and evaluation activities; and (iv) carrying out
training and campaigns on urban-rural integrated distribution.
(e) Selected activities related to the integrated development of the inland waterway of the Han River,
including, inter alia: (i) the development of strategic plan for the integrated development of the inland
waterway of Han River; and (ii) the purchase and installation of solar-powered navigation lights along
selected pilot segments of Han River.
15. Component 3: Capacity Building, Monitoring and Evaluation, and Project Management (Total estimated cost
at appraisal US$5.77 million, GEF US$2.05 million). Provision of:
(a) Technical assistance support for, inter alia: (i) knowledge and capacity building on multimodal freight
transport and urban freight distribution; (ii) dissemination activities; and (iii) eco-driving professional
standard development and training courses for truck drivers.
(b) Monitoring and evaluation activities.
(c) Project management activities.
B. SIGNIFICANT CHANGES DURING IMPLEMENTATION (IF APPLICABLE)
16. The project underwent a Level 2 restructuring on December 1, 2022. The following changes were made: (i)
extension of the closing date by 12 months to December 31, 2023; (ii) cancellation of the Xiamen pilot and reallocation
of US$700,000 from Xiamen to Hubei to support new pilot activities; (iii) reallocation of US$500,000 from Component 3
to Component 1 to support new TAs; and (iv) revision to the Results Framework.
Revised PDOs and Outcome Targets
17. No change in the PDO.
Revised PDO Indicators
18. The target for PDO indicator 2, “Number of national plans adopted by MOT”, was increased from 2 to 3.
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China: GEF Efficient and Green Freight Transport Project (P159883)
Other Changes
19. Xiamen pilot cancelled and replaced with another Hubei pilot (Component 2). Due to the low commitment of
Xiamen to implementing the pilot, the MOT proposed to cancel the Xiamen pilot under this project and reallocate the
US$700,000 grant to another pilot in Hubei. Hubei had made good progress in implementing the pilot and had expressed
interest in using such funds. Hubei planned to develop a data collection and analysis platform for Yangtze River cargo ships
and implement emission reduction measures for selected cargo ships on the Yangtze River. The new proposal
supplemented Hubei's TA system for promoting inland waterway transportation and contributes to the achievement of
PDO.
20. Changes to Component 1 and 3. Due to COVID-19 restrictions on field research, most workshops were conducted
online, and international field trips had to be cancelled. Additionally, the eco-driving training initially proposed to be funded
by GEF grant was completed with other funding. The total savings from these changes to Component 3 was estimated at
approximately US$650,000. To fully utilize the GEF grant, capacity-building activities for the private sector was added under
Component 3; and remaining funds were allocated to Component 1 to support three new national-level assistance
projects.
Rationale for Changes and Their Implication on the Original Theory of Change
21. Impact on PDO achievement. The above changes were approved through restructuring in 2022. With the
extension of the project and the addition of three national TAs, the project’s development impact on national transport
policy formulation was increased. Accordingly, the PDO-level indicator for the number of national plans to be adopted by
MOT was increased. Meanwhile, the new capacity building activity increased the number of project beneficiaries that
participate in national-level trainings and the end target was increased accordingly. Finally, by replacing the Xiamen pilot
with the Hubei pilot, the expected reduction in CO2 emissions associated with the project increased.
II. OUTCOME
A. RELEVANCE OF PDOs
Relevance to Higher Level Objectives
22. The project was consistent with the 2020-2025 Country Partnership Framework (CPF) for China issued in 2019
(Report No. 117875-CN) and consistent with the China five-year strategy 2020-2025, in which Engagement Area Two:
Promoting Greener Development is one of the main strategies and Promoting Low-Carbon Transport as one of objectives
for Greener Development. The project improved the efficiency of multimodal freight transportation, so that long-distance
freight shifted from roads to greener transport modes such as railways and waterways. The project also promoted green
urban logistics to reduce emissions. In this way, the project also remained aligned with the Government of China’s (GOC)
latest climate goals to achieve carbon emission peaking in 2030 and carbon neutrality by 2060. Similarly, the project
remained relevant to the national 14th Five-Year Plan for Modern Comprehensive Transport Development (2021-2025).
23. The project was aligned with the Climate Change Mitigation (CCM) goal of the GEF-6 program, i.e., to support
developing countries and economies in transition to make transformational shifts towards a low-emission, resilient
development path. In particular, it supported the CCM Program 1: Promote the timely development, demonstration, and
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China: GEF Efficient and Green Freight Transport Project (P159883)
financing of low-carbon technologies and mitigation options. The project supported five local pilot projects to
demonstrate innovative options for GHG emission mitigation in the freight transport sector, such as establishing a trucking
alliance to promote drop-and-pull and waterway-highway intermodal transport, using big data analytics to inform policy
making and scenario testing in urban freight management, and leveraging information technology to match freight
demand and supply.
24. Considering the above, Relevance is rated as Substantial.
B. ACHIEVEMENT OF PDOs (EFFICACY)
Assessment of Achievement of Each Objective/Outcome
25. The assessment of PDOs is organized around each objective or outcome indicated in the PDO statement.
Compound PDOs with multiple outcomes linked together in a single sentence is “unpacked” and each outcome assessed
separately. The two parts to the PDO are (i) improve the Recipient’s institutional capacity to formulate and evaluate
policies and strategies to promote green freight transport systems; and (ii) pilot innovative carbon emission reduction
measures in the freight transport sector in selected provinces. The two PDOs were assessed based on the results
framework and data obtained through interviews with project stakeholders, World Bank preparation and supervision
team staff, and review of technical assistance reports produced under the project.
PDO (i) Improve the Recipient’s institutional capacity to formulate and evaluate policies and strategies
to promote green freight transport systems
26. The project met the revised end targets for all PDO-level and intermediate-level indicators related to this element
of the PDO.
Table 1 Summary of outputs and outcomes related to PDO (i)
Measure End result Indicator type Achievement compared
with end target1
Number of analytical tools adopted by MOT 2 PDO Achieved
for implementation in national planning and
policy development
Details: MOT adopted the Marginal Abatement Cost Analysis Tool2 and the National Freight Model for
Freight Emissions Reduction3.
Number of national plans adopted by MOT 3 PDO Achieved
for implementation (Number)
Details: Adopted plans informed by the project TAs include:
1End target in place after the restructuring. Refer to Annex 1 for details on baseline values, board approval stage and
restructuring stage end targets.
2 Link to published document:《交通运输部 国家铁路局 中国民用航空局 国家邮政局贯彻落实<中共中央 国务院关于完整
准确全面贯彻新发展理念做好碳达峰碳中和工作的意见>的实施意见》（交规划发〔2022〕56号）
https://xxgk.mot.gov.cn/2020/jigou/zhghs/202206/t20220624_3659984.html
3Link to published document:《推进多式联运发展优化调整运输结构工作方案（2021-2025）》（国办发〔2021〕54 号
http://www.gov.cn/zhengce/content/2022-01/07/content_5666914.htm#
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China: GEF Efficient and Green Freight Transport Project (P159883)
Measure End result Indicator typeAchievement compared
with end target1
1. Action Plan to Promote the Development of Multimodal Transport and Optimize and Adjust the
Transport Structure (2021-2025)4
2. The 14th Five-Year Plan for Comprehensive Transportation Services5
3. The 14th Five-Year Plan for Modern Integrated Transportation Hub Systems6
Number of guidelines on improving urban 1 PDO Achieved
freight transport issued by MOT for
Implementation
Details: The project produced the "Urban Distribution Path Optimization and Intelligent Scheduling", which
was approved by the Guangdong-Hong Kong SAR, China-Macao SAR, China Greater Bay Area Standards
Innovation Alliance.
Number of national TAs completed 15 Intermediate Achieved
Details: The fifteen completed TA projects are named below. A summary of the findings of each of the
studies is provided in paragraphs 27-41 below.
1. Research on China's Freight Structural Emission Reduction Strategy.
2. Research on China’s National Freight Model.
3. Action Plan for Efficient and Green Development of China’s Main Freight Channels.
4. Research on the development of multimodal transport in the Yangtze River Economic Belt YREB).
5. Research on the development of railway multimodal transport in the Yangtze River Economic Belt.
6. Research on green and efficient urban freight development and management policies.
7. Research on the construction and effect evaluation of urban green freight indicator system.
8. Research on urban freight standard system under new technology conditions.
9. Research on urban distribution route optimization and intelligent dispatch technology
10. Case study report on international inland waterway multimodal transport.
11. Research on the Efficient and Green Transformation Pathway of Modern Transportation and
Logistics Systems.
12. Research on the impact of China’s demographic change trend on green freight and
countermeasures.
13. Research on the impact of resource constraints and economical intensive utilization on freight
transport and countermeasures
14. Research on the impact and countermeasures of domestic and foreign economic development on
freight transportation.
15. Research on the construction and development of China’s port collection and distribution system
Number of national TAs informed by citizen 5 Intermediate Achieved
engagement
4Link to published document:《推进多式联运发展优化调整运输结构工作方案（2021-2025）》（国办发〔2021〕54 号
http://www.gov.cn/zhengce/content/2022-01/07/content_5666914.htm#
5Link to announcement:《综合运输服务“十四五”发展规划》http://www.gov.cn/zhengce/zhengceku/2021-
11/18/content_5651656.htm
6Link to announcement:《现代综合交通枢纽体系“十四五”发展规划》
https://www.mot.gov.cn/zhuanti/shisiwujtysfzgh/202201/t20220129_3639070.html
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China: GEF Efficient and Green Freight Transport Project (P159883)
Measure End result Indicator type Achievement compared
with end target1
Details: There were five TAs that showed clear evidence of citizen engagement. These TAs included
requirements for citizen engagement (gathering opinions of the general public) in their Terms of
Reference. The five TAs were:
1. Research of China’s Freight Structural Emission Reduction Strategy. This TA built the first domestic
industry-level framework for a public information platform for multimodal transport in China.
2. Action Plan for Efficient and Green Development of China’s Main Freight Channels.
3. Research on the development of multimodal transport in the Yangtze River Economic Belt YREB).
4. Research on the construction and effect evaluation of urban green freight indicator system.
5. Research on the Efficient and Green Transformation Pathway of Modern Transportation and
Logistics Systems.
MOT adopts the action plan for multimodal Yes Intermediate Achieved
freight transport development
Details: Research results were applied in:
1. The 14th Five-Year Plan for Comprehensive Transportation Services
2. Action Plan to Promote the Development of Multimodal Transport and Optimize and Adjust the
Transport Structure (2021-2025)7
MOT adopts the E-commerce based urban Yes Intermediate Achieved
freight distribution solution
Details: The project carried out discussions with four urban distribution companies, Cainiao, JD.com,
Suning, and SF Express, conducted a survey on the urban distribution situation in two provinces and one
city in the Yangtze River Delta (Suzhou, Zhejiang, and Shanghai). The research results were recognized by
the Planning Department of the MOT.
National freight flow model completed Yes Intermediate Achieved
Details: The completed model was based on the consideration of three aspects: the operating
characteristics of China's freight transportation industry, the socio-economic operating characteristics, and
the freight transportation connections between regions, with the goal of optimizing the allocation of
transportation system resources at the national or regional level.
Further details on the completed national TAs:
27. Research on China's Freight Structural Emission Reduction Strategy. This TA determined an overall
approach to structural emission reduction in China's freight industry based on the innovative development of
multimodal transport of goods and proposed a strategic and implementable roadmap for the development of
multimodal transport. Secondly, it established a framework and indicator system for evaluating freight emission
reduction policies, focusing on the two outcome elements of reducing emissions and reducing costs, and
constructed a cost-effectiveness assessment tool for China's freight emission reduction policies, laying a solid
foundation for follow-up research on emission reduction in China's freight industry. Thirdly, it built the first
domestic industry-level framework for a public information platform for multimodal transport in China. The TA
has informed key adopted policy documents including the (i) "Work Plan for Promoting the Development of
Multimodal Transport and Optimizing the Transportation Structure (2021-2025)" (Guo Ban Fa [2021] No. 54), (ii)
the "14th Five-Year Development Plan for Comprehensive Transportation Services" (Jiao Yun Fa [2021] No. 111),
7Link to published document:《推进多式联运发展优化调整运输结构工作方案（2021-2025）》（国办发〔2021〕54 号
http://www.gov.cn/zhengce/content/2022-01/07/content_5666914.htm#
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and (iii) the "Implementation Opinions of the Ministry of Transport, National Railway Administration, Civil Aviation
Administration of China, and State Post Bureau on Carrying Out the 'Opinions of the Central Committee of the
Communist Party of China and the State Council on Fully, Accurately, and Comprehensively Implementing the New
Development Concept and Doing a Good Job in Achieving Carbon Peak and Carbon Neutrality'" (Jiao Gui Hua Fa
[2022] No. 56).
28. Research on China’s National Freight Model. The TA made three major achievements. Firstly, it
constructed an origin-destination matrix database based on open multi-source data, building a transportation
demand matrix database for 26 cargo categories across 329 cities. This lays the foundation for the analysis and
optimization of the freight transportation system at the national and regional scales. Secondly, it constructed a
multi-modal intermodal generation and evaluation model to design and optimize China's comprehensive freight
system based on efficiency, cost, reliability, and optimal carbon emissions. The TA created a multi-modal
intermodal route planning model set that can optimize multi-objective optimization between the 329 prefecture-
level cities, as well do data analysis and assessment of the importance of particular transportation channels and
nodes. Finally, using this research the TA developed a national freight multi-modal intermodal “Data Analysis and
Decision Support Platform”. The Platform solves the issue of a lack of analytical tools at the macro level of national
freight transportation systems. The TA has informed key adopted policy documents including the (i) "Promoting
Intermodal Transport Development and Optimizing Transportation Structure Work Plan (2021-2025)" (State
Council Bulletin No. [2021] No. 54), "Comprehensive Transportation Service Development Plan (2021-2025)"
(Transportation Ministry Bulletin No. [2021] No. 111), and (ii) the "Guangdong Province Comprehensive
Transportation Service Development Plan (2021-2025)".
29. Action Plan for Efficient and Green Development of China’s Main Freight Channels. This TA analyzed
the layout of the main freight channels, predicted future demand scenarios, and proposed the main projects and
policy reforms needed to improve transportation efficiency, and reduce energy consumption and greenhouse gas
emissions. The findings from this TA were used by the MOT to prepare the "The 14th Five-Year Plan for
Comprehensive Transportation Services", and "The 14th Five-Year Plan for Modern Integrated Transportation Hub
Systems".
30. Research on the development of multimodal transport in the Yangtze River Economic Belt YREB).
This TA assessed the status and future needs of intermodal freight transport development along the YREB for nine
provinces and two cities. The assessment considered infrastructure, equipment, information technology systems,
transportation organization methods, and price drivers. Based on this research, the TA proposed the overall
development goals of intermodal freight transport in the YREB, formulated an action plan of key projects and
policy reforms. The results have supported the joint issuance by the State Council for the "Work Plan for Promoting
Intermodal Freight Transport Development and Optimizing and Adjusting Transportation Structure (2021-2025)."
31. Research on the development of railway multimodal transport in the Yangtze River Economic Belt.
This TA evaluated the status of railway multimodal transportation in the YREB. The study predicts the scale of
railway multimodal transportation demands in the YREB in 2025, 2030 and 2035, and then proposed key tasks for
formulating development strategies of railway multimodal transportation in the YREB in terms of railway network
layout, technical equipment, information systems and business models. The TA was utilized by the China Railway
Corporation to formulate policies related to railway-waterway combined transportation and promoted the
construction of relevant dedicated railway lines for railway-waterway combined transportation.
32. Research on green and efficient urban freight development and management policies. This TA
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assessed new national macro-policies, new technologies, and the development of new business formats.
Considering the causes of existing problems, the TA put forward policy recommendations to promote the green
and efficient development of urban freight in China.
33. Research on the construction and effect evaluation of urban green freight indicator system. This TA
analyzed the current methods used to monitor urban freight environmental performance in typical cities,
reviewed the global literature for index systems in use, and designed an original Urban Green Freight Evaluation
Index System.
34. Research on urban freight standard system under new technology conditions. This TA made
recommendations on ways to improve the efficiency and environmental sustainability of urban freight systems,
as well as the interconnections between long-distance freight and urban freight distribution. The TA analyzed
various delivery modes and made recommendations on what should be included in the technical guidelines for
delivery vehicles (including electric vehicles for last-mile delivery) and delivery systems (including the introduction
of co-delivery systems and automated parcel collection lockers). In addition, the TA set up feasible information
and resource sharing mechanisms for logistics companies. The TA conducted discussions with four major urban
distribution companies, namely, Cainiao, JD.com, Suning, and SF Express, conducted a survey on the urban
distribution situation in Shanghai, Zhejiang and Suzhou in the Yangtze River Delta.
35. Research on urban distribution route optimization and intelligent dispatch technology. This TA
analyzed the development trends of the urban distribution business sector, and new technology applications. The
TA developed technical solutions for urban distribution route optimization, applied and promoted them in non
GEF-6 pilot cities. Finally, it developed a draft national standard for urban distribution route optimization and
intelligent dispatch information technology, statistical analysis, and service management.
36. Case study report on international inland waterway multimodal transport. This TA analyzed the
typical practices of foreign inland waterways, and made recommendations on technologies, infrastructure, and
policies to adopt in China.
37. Research on the Efficient and Green Transformation Pathway of Modern Transportation and
Logistics Systems. This TA analyzed the market size, organizational models, equipment used, energy consumption,
and emissions in the field of transportation and logistics. The TA suggested opportunities for efficiency
improvement, energy supply adjustment, and service substitution in different logistics market segments. The TA
studies the barriers to achieving carbon peaking in the transportation and logistics system and provided policy
recommendations. The MOT utilized these findings when formulating the "Guiding Opinions on Accelerating the
Construction of a Modern Transportation and Logistics System (Draft)".
38. Research on the impact of China’s demographic change trend on green freight and countermeasures.
This TA did in-depth analysis of the impact of current and future population changes on green freight logistics
development (including both positive and negative impacts) with the aim to proactively reduce the costs of reform
and transformation. It also analyzed the impact of population development trends on the decarbonization of
logistics, proposed key implementation points and strategic measures for building a modern green freight logistics
system that adapts to population development.
39. Research on the impact of resource constraints and economical intensive utilization on freight
transport and countermeasures. This TA investigated feasible conservation and intensive strategies and analyzes
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their impact on the supply and demand of green freight logistics systems.
40. Research on the impact and countermeasures of domestic and foreign economic development on
freight transportation. This TA analyzed the industrial development trends of major economies around the world
and their relationships with China and identified various possible scenarios for China's future economic
development. The TA constructed a framework for the relationship between national economic development and
green freight logistics and validated the key impact paths through empirical research. The TA proposed overall
requirements, key tasks, policy suggestions, safeguard measures, environmental and social risk assessments, and
countermeasures for the coordinated development of green freight logistics with the economy.
41. Research on the construction and development of China’s port collection and distribution system.
This wide-ranging TA assessed current status of the construction and development of China’s port logistics system,
including linkages between the ports and the railway, road and water logistics infrastructure, transportation
volume structure organizational methods, operation processes, and functional layout. It analyzed the typical
practices of foreign ports and combine the national macro-strategy and market orientation to judge the future of
the Chinese industry.
PDO (ii) Pilot innovative carbon emission reduction measures in the freight transport sector in
selected provinces
42. The project met the revised end targets for all PDO-level and intermediate-level indicators related to
this element of the PDO.
Table 2 Summary of CO 2 reductions associated with PDO-level indicator “ Total CO2 emission
reduction (Ton, cumulative in project life cycle)”
Carbon emission reduction reporting is split into direct reduction from pilots and indirect scale-amplified
reduction. Scale-amplified reduction values are used for assessing completion of the PDO indicator as per
the PAD Results Framework, but the direct reduction estimate is included as well for transparency.
Indicator Direct carbon Indirect scale Achievement
reduction amplified carbon compared with end
projected to reduction target11
2031 (tons)8, 9 (tons)10
Total CO2 emission reduction 2,822,612 33,164,175 +112%
(cumulative)
Bohai Bay Highway-Waterway 1,739,062 17,390,62512 +58%
8 The evaluation period for carbon emission reduction was set at 2020-2030 at project appraisal but was extended to 2031 as a
result of the 1-year project closing date extension.
9 Details on calculation assumptions included in Annex 5.
10 Details on calculation assumptions included in Annex 5.
11 End target in place after the restructuring. Refer to Annex 1 for details on baseline values, board approval stage and
restructuring stage end targets.
12 Amplification effect assumed to be 10x direct project CO2 reduction effect, which is consistent with board approval stage
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Multimodal Transport Project in Yantai
Integrated Urban-Rural Distribution 770,000 15,400,00013 +235%
Project in Guangdong
Solar integrated navigation light 357,347 357,347（No Not applicable (not
construction and waterway upgrade scale effect） counted in PAD)
project in Hubei
Weifang Green Freight Demonstration 16,203 16,203（No Not applicable (not
Project scale effect） in original PAD)
Details: The CO2 emission reduction benefits of the project come from two aspects (i) direct GHG
emission reductions from the pilot projects in Yantai, Guangdong, Hubei, and Weifang and (ii) indirect
CO2 emission reductions from the replication of the successful pilots in Yantai and Guangdong
because of policy incentives and capacity-building activities. Direct GHG emission reductions (a) in
Yantai come from modal shift from road transport to waterways, (b) in Guangdong come from
reduction in empty freight truck trips, (c) in Hubei come from improvements to the capacity of the
Han River corridor, and installation of solar integrated navigation lights, and (d) in Weifang come from
freight consolidation, off‐peak delivery, and utilization of clean energy vehicles. Details on calculation
assumptions included in Annex 5.
Table 3 Summary of intermediate indicators related to PDO (ii)
Indicator End Achievement
Indicator
result compared
type
with end
target14
Percentage of Bohai Gulf ferry traffic that is drop-and-pull 10.16 Intermediate +1.6%
Details: The project successfully increased drop-and-pull (DnP) traffic by (i) unified technical standards
regarding DnP trucks, (ii) advocated for ‘one bill of lading’ operated by third-party logistics operators
through established ICT platforms so that information can be shared among stakeholders, and (iii)
added facilities at the port like a lounge for truck drivers to make seamless multimodal transport
possible. The project participated in the third China Transportation Service Model Selection
Conference, and there was comprehensive publicity and promotion on the project results by China
Transportation News Network.
Weifang adopts the proposal for improving urban freight Yes Intermediate Achieved
transport efficiency
PAD assumption. 10x replication assumption made based on the fact that China had made commitment to accelerate the
development of multimodal transport at 63 major ports across the country and it was assumed that at least some of them
would be influenced by the learnings derived from this pilot.
13 Amplification effect assumed to be 20x direct project CO2 reduction effect, which is consistent with board approval stage
PAD assumption. As of July 2023, the Ministry of Transport announced 118 counties (cities, districts), as the third batch of
urban and rural transportation integration demonstration counties. Of these, at there are 74 counties that have characteristics
(distribution scope, population size, and freight volume) that mean they are suitable for replication of the measures done in the
Guangdong pilot.
14 End target in place after the restructuring. Refer to Annex 1 for details on baseline values, board approval stage and
restructuring stage end targets.
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Indicator End Indicator Achievement
result type compared
with end
target14
Details: Before the project, the mainstream distribution mode in Weifang City was self-operated
distribution by suppliers of large-scale supermarket chains. The project intended to meet the
requirement of logistics cost reduction and efficiency improvement and form a more advanced urban
distribution mode. During the project implementation, 140 emission monitoring sensors were
installed into sample trucks, and relevant data were sent to Weifang Transportation Energy
Consumption Platform and Emergency Command Center Platform for further analysis. The project also
formulated a bunch of research, including the "Weifang City Logistics Vehicle Sample Configuration
Plan" and "Weifang City Logistics Vehicle Access Plan". Part of the recommendations from the latter
document was applied in the "Weifang City People's Congress Standing Committee's Decision on
Strengthening the Management of Limited-time Free Parking in Public Places", thus meeting the
indicator requirement.
Hubei Department of Transport adopts the Han River Yes Intermediate Achieved
inland waterway integrated development plan
Details: Project research results have been published in the "14th Five-Year Plan for Comprehensive
Transportation Development in Hubei Province", "14th Five-Year Plan for Water Transport
Development in Hubei Province", "Inland Waterway Planning of Hubei Province (2035)" and "14th Five
Year Plan for Integrated Transportation Services”. Additionally, in accordance with the Han River
inland waterway integrated development plan, 20 solar-powered navigation lights were installed
along the Han River.
Percentage of empty trucks on the return trip from rural 79.1% Intermediate Achieved
villages to urban centers in Guangdong
Details: The project supported the creation of three smartphone applications “Yue Cheng Pei”, “Huo
Hao Hao Yun” and “Qing Cheng Pei” by pilot companies “Zhong Xiang”, “Mei Tu” and “Ka Che Ren”,
respectively. The platforms help match drivers with cargo source to reduce the percentage of empty
trucks, as well as reducing driver waiting time and corresponding expenses. By the end of 2023, Zhong
Xiang’s "Yue Cheng Pei" APP had a total of 3,744 registered drivers, a total of 1,201 registered cargo
owner companies, a total of 36,672 matched orders, a total matched freight volume of 202,935 tons.
Mei Tu's "Huo hao hao yun" app had 576 registered users, 8,316 matching orders, and 16,049
transported tons. As a result, the percentage empty trucks of the project improved from 95% to
79.1%, exceeding the final target.
Villagers trained under the Guangdong integrated urban- 233 Intermediate +16%
rural distribution system pilot, cumulative
Details: 4 publicity activities and 3 training activities were held. The cumulative number of villagers
trained in person was 233 persons, among which 134 were female villagers. In addition, 36,600
received training virtually.
Female villagers trained under the Guangdong integrated 134 Intermediate +34%
urban-rural distribution system pilot, cumulative
Details: The cumulative number of villagers trained in person was 233 persons, among which 134 were
female villagers.
Number of Yangtze River cargo ships enrolled in the 3 Intermediate Achieved
carbon reduction technology pilot
Details: 3 vessels, including two different types of bulk carriers were involved as the measurement
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Indicator End Indicator Achievement
result type compared
with end
target14
objects to analyze the carbon reduction effect under the adoption of clean energy technology and
operational energy consumption optimization technology.
To supplement the evidence for the efficacy of the project that is presented above, the following
paragraphs provide an overview of the main findings from each of the sub-national pilots.
43. Bohai Bay Highway-Waterway Multimodal Transport Pilot. The main factors affecting the
development of drop and pull transportation are (i) inconsistent technical standards for drop and pull vehicles, (ii)
low level of information digitalization, and (iii) the unbalanced supply of drop and pull goods on routes. The pilot
investigated solutions to promote the development of drop-and-pull transportation, such as promoting
information networking, improving the construction of logistics parks, upgrading relevant cargo roll-on-roll-off
transport ships, further optimizing regional docking work, and forming a logistics alliance.
44. Weifang Urban Freight Joint Distribution Pilot. The TA identified the importance of constructing a
joint distribution logistics network system, optimizing, and improving urban freight distribution vehicle traffic
control policies, accelerating the update and transformation of standardized new energy freight distribution
vehicles, and promoting the exchange and sharing of information throughout the urban freight distribution chain.
45. Guangdong Integrated Urban-Rural Distribution Pilot. Using the TA, the Guangdong Transport Bureau
developed an urban‐rural freight distribution APP module to be used by freight companies and cargo owners to
match the freight demand and supply. The base APP software was provided open source and then freight
companies have since modified the software to create their own proprietary APPs. These APPs reduced the
amount of empty truck kilometers travelled between urban and rural areas in Guangdong province.
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Figure 1 APP interface of “Yue cheng pei”, “Huo hao hao yun”, and “Qing cheng pei”
46. Hubei Integrated Development of the Han River Waterway Pilot. The TA did an in-depth study of the
Yangtze River's complex navigation environment and ship type characteristics, new energy technologies for ships,
and energy efficiency improvement technologies for ship operations. The TA also analyzed the socio-economic
conditions and development plans along the Han River, cargo transportation conditions and demands, as well as
the influencing factors and degrees of influence on ports, waterways, maritime safety, shipping services, the main
factors restricting the development of shipping, drawing on the development experience of inland shipping in
China and abroad, and put forward suggestions and countermeasures for sustainable development of the
waterway.
47. Hubei Freight Vessel Emission Reduction Pilot. This TA built a carbon emission data analysis software
system for Yangtze River cargo ships based on the complex navigation environment and ship types in the Yangtze
River. Three representative vessels were installed with the emission monitoring equipment and the data was
being used to learn how to minimize carbon emissions through operational and technological changes.
Other benefits
48. The project substantially exceeded all the intermediate-level indicators related to capacity building.
Table 4 Evidence of capacity building done by the project
Indicator End result Indicator Achievement
type compared with
end target15
15End target in place after the restructuring. Refer to Annex 1 for details on baseline values, board approval stage and
restructuring stage end targets.
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Truck drivers trained at national green truck driver 6,458 Intermediate Achieved 21x
trainings, cumulative the target
Details: NPMO provided green driving-related trainings for truck drivers through National Road Continuing
Education Network Platform for Freight Driver on Professional Qualification Network of Transport. 4,201
people trained in 2020, 977 in 2020, 500 in 2021 and 780 in 2022.
Persons trained in national-level trainings and workshops, 1153 Intermediate +130%
cumulative
Details: A total of 15 training and meetings have been organized, including 1 training meeting on finance
and procurement, as well as topic review meetings to promote the implementation of various project
activities.
International freight conferences held under TransFORM 4 Intermediate Achieved
The four cited freight conferences were:
1. "China's Emergency Transportation Experience under COVID-19" online seminar, held on May 6,
2020.
2. "China Transportation's Experience and Enlightenment in anti-COVID-19" online seminar, held on
May 18, 2020.
3. The green logistics demonstration case exchange meeting with the theme of "Energy saving and
carbon reduction, held on November 29, 2023.
4. The Green logistics demonstration case promotion meeting in Miluo City of Hunan Province from
December 1 to 2, 2023.
Materials published on TransFORM website Not Not Not applicable
applicable applicable
Details: TransFORM website published 40 Chinese language case studies, 20 English language case studies,
20 Chinese language reports, and 10 English language reports. In addition, the News section of the website
was updated with a total of 607 Chinese language news items and 602 English language news items.
49. The project met the revised end targets for all PDO-level and intermediate-level indicators. Considering
the evidence presented above, Efficacy is rated as Substantial.
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C. EFFICIENCY
Assessment of Efficiency and Rating
50. The project achieved substantially more CO2 emission reduction at a lower cost per ton than envisaged at
appraisal. The CO2 emission reduction forecast due to the project is 33.16 million tons, an over achievement of 112
percent. The project substantially surpassed the ratio of incremental costs versus environmental benefits at appraisal. In
accordance with the guidelines of the Global Environment Facility (GEF), an incremental cost analysis was conducted
during the project design stage to assess the incremental costs and environmental benefits of the project scenario
compared to the BAU. The incremental costs of the project mainly refer to the funds used to support national-level
technical assistance to improve the efficiency of intermodal freight systems, and to provide support for local pilot
projects, as well as capacity building. The environmental benefits brought by the project mainly include direct and
indirect carbon dioxide emission reduction benefits. Direct carbon dioxide emission reduction benefits mainly come from
the implementation of two local pilot projects, (the Bohai Bay Highway-Waterway Multimodal Transport Project in
Yantai, and the Integrated Urban-Rural Distribution Project in Guangdong only). Indirect GHG emission reduction
benefits mainly stem from promoting national and subnational CO2 emission reduction policies and strategies and
establishing emission analysis tools in the freight sector, which has the replication potential to promote and disseminate
findings of the project further.
51. The cost per carbon emission reduced is now estimated at US$0.667 per ton, which is 23 percent more efficient
that the US$0.876 per ton estimated at appraisal. Note that an economic internal rate of return analysis was not done
at project appraisal and is not required for this ICR. For further details on the efficiency analysis refer to Annex 4.
52. If the project had not been extended by 12 months, it would have been even more economically efficient. The
extension was however necessary as it gave the project more time to achieve the PDO and environmental benefits, which
was behind which was lagged by the slower creation of designated account and movement restrictions affected by
COVID-19 pandemic.
53.Considering the above, Efficiency is rated as Substantial.
D. JUSTIFICATION OF OVERALL OUTCOME RATING
54. Based on the evidence set out in the preceding paragraphs, the Overall Outcome Rating is Satisfactory.
E. OTHER OUTCOMES AND IMPACTS (IF ANY)
Other Unintended Outcomes and Impacts
Gender
55. In the Bohai Bay Highway-Waterway Multimodal Transport Project in Yantai, it was identified that combined
male-female transport lounges were making it inconvenient for female practitioners to rest. The demonstration
enterprise, Shenbo Logistics Technology, listened to suggestions to meet the needs of female drivers, strengthened the
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management of passenger ship lounges, and set up separate male and female lounges to avoid the inconvenience of
resting and waiting for female practitioners, improving the employment experience of female practitioners.
56. The Guangdong Integrated Urban-Rural Distribution Pilot increased employment opportunities and income of
rural women. As an illustrative example, one of the blueberry farms “Foshan Lishui” signed up to the "Yue cheng pei"
APP to distribute its blueberries to market. Because blueberry crops are highly economical and profitable, the wages and
stability of pickers are higher than those of other casual workers, encouraging surrounding farmers to engage in
blueberry picking work, and the vast majority of blueberry pickers are female workers. From February to May 2023, there
were 525 people with 498 women employed in blueberry picking at the company, accounting for 95% of the workforce.
The APP facilitated an average of 200 deliveries per month, totaling 1,030 tons. Based on a conservative calculation of a
picking wage of 8,000 yuan/month, from February to May 2023, the project helped increase the income of rural women
in Foshan by a total of 15.94 million yuan (US$2.24 million).
III. KEY FACTORS THAT AFFECTED IMPLEMENTATION AND OUTCOME
A. KEY FACTORS DURING PREPARATION
57. The project set clear and achievable objectives that were aligned with the country's needs and priorities. The
project had a well-structured design with clearly defined components, and activities were appropriately timed and
sequenced. The approach of combining national-level TA with pilot city demonstrations confirmed the demonstration
effects and replication potentials of successful pilot projects, as well as facilitating knowledge dissemination. The project
engaged a wide range of stakeholders, including government agencies, civil society organizations, and private sector
entities. The selection of these stakeholders was appropriate and ensured their active involvement and ownership of
project activities. A national Project Steering Group (PSG) was established for overseeing overall project preparation
and implementation and exercising high‐level coordination among various stakeholders.
58. Key risks identified and mitigation measures implemented. The NPMO and three of the local PMOs were new
to World Bank operations and did not have experience with World Bank procurement or financial management. In
addition, previous GEF projects indicated that the staffing of these PMOs would change frequently. To mitigate these
risks, the NPMO hired experienced consultants to assist the NPMO and the local PMOs on procurement and financial
management. In addition, World Bank provided extensive training to fiduciary staff throughout project implementation.
Finally, at the national level, a technical committee was established for (i) conducting quality control of the TA Terms of
Reference (TOR) and bid documents, (ii) bid evaluation, and (iii) TA output review and management.
59. It was more than two years between the pre-identification mission in April 2016 and project approval in
December 2018. This slow preparation timeline was mainly a result of having to comply with both World Bank and GEF
project preparation procedures.
B. KEY FACTORS DURING IMPLEMENTATION
60. Impacts of COVID-19. The project was affected by the outbreak of the COVID-19 epidemic and associated travel
restrictions from 2020 onwards, resulting in the failure to carry out research, training, seminars, symposiums, and other
work related to the project as scheduled.
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61. Delay in establishment of Designated Account (DA), which resulted in a one-year delay against the schedule
planned at board approval. This delay was caused internal procedures at MOF which limit the number of DAs open at
any one time.
62. Good performance of national technical assistance encouraged more counterpart financing. At appraisal it was
envisaged that US$1.7 million would be provided to Component 1: National Technical Assistance and Policy
Development. However, US$8.91 million in counterpart financing was provided due to strong buy-in from the
counterpart to the efficient and green freight policy agenda. Therefore, the GEF grant funding leverage successfully
leveraged 524 percent of the counterpart financing than was originally estimated. With more funding provided, deeper
and wider research could be done to benefit the quality of the analytical tools, national plans and guidelines informed
by the project.
IV. BANK PERFORMANCE, COMPLIANCE ISSUES, AND RISK TO DEVELOPMENT OUTCOME
A. QUALITY OF MONITORING AND EVALUATION (M&E)
M&E Design
63. The project selected appropriate indicators to measure progress. The project was designed to achieve two
project development objectives, which were measured through 4 PDO indicators and 12 intermediate results
indicators. The indicators were all linked with PDO and were entirely attributable to the project before and after the
restructuring. The indicators were indicators specific, measurable, achievable, relevant, and time-bound, and
baselines and targets were available for all indicators. The Results Framework defines the methodology, data source,
frequency, and responsible agencies for data collection to monitor the progress.
M&E Implementation
64. The MOT PMO and Guangdong, Hubei, Yantai, and Weifang PMOs diligently collected the data required for
the indicators. Indicators were largely calculated following the methodology set ex-ante, however there were updates
made to some assumptions based on more recent and accurate data. Data used was reliable and of good quality. The
current status of each indicator was updated at each mission and reported in the Implementation Status and Results
Reports. M&E functions and processes are not likely to be sustained after project closing as the indicators were
designed specifically for the purposes of monitoring the outputs and outcomes of the project TAs which are now all
completed.
M&E Utilization
65. The Results Framework was used by the task team, national PMO and sub-national PMOs to monitor the
project progress. As noted earlier, the indicators were well targeted to the project activities and relatively
straightforward to measure. M&E findings were disseminated and used to inform the direction of the project. Several
Results Framework indicators were updated at the project restructuring. These factors likely led to the high utilization
of the Results Framework.
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Justification of Overall Rating of Quality of M&E
66. Based on the evidence set out in the preceding paragraphs, the Overall M&E Quality Rating is Substantial.
B. ENVIRONMENTAL, SOCIAL, AND FIDUCIARY COMPLIANCE
Environmental and Social Safeguards
67. The Project supported TA activities focused on green freight transport that were designed with the inherent
objectives of environmental protection in terms of energy saving, pollution and GHG emission reduction and
contribution to environment and social substantiable development.
68. The project was Categorized as a Category B project. Environmental Assessment (OP4.01) was triggered under
the Project. An Environmental and Social Management Framework (ESMF) was disclosed disclosed on local
government websites and the TransFORM website in both Chinese and English on February 22, 2018. It was also
disclosed on the World Bank’s website on March 7, 2018. National PMO assigned an environmental and social focal
point to manage the project environmental and social performance, and an Environmental and a Social consultant
was contracted separately to assist the approved ESMF implementation. The environmental and social capacity
building and training workshops to PMOs or contractors were conducted at least once a year. An effective working
mechanism/ procedure for environmental and social assessment was established between PMOs and contractors.
Since the outcomes of TA support may have some environmental and social implications going forward, entailing risks,
and potentially inducing adverse impacts, TORs on environmental and social assessment were prepared and
incorporated into the proposed scope of TA studies or platform development; and environment and social risks were
identified, and the corresponding measures were put forward. The ESMF performance was monitored and reviewed
by both national PMO and the World Bank through the regular missions and progress reports. Existing Grievance
Redress Service (GRS) were used to collect suggestions or complains related to the proposed TA studies and any
downstream investments. Overall, the ESMF was well implemented, the project environmental and social
performance is satisfactory.
69. The Involuntary Resettlement (OP4.12), Natural Habitats (OP4.04), and Indigenous Peoples (OP4.10) were
triggered during the appraisal due to precautionary considerations. These policies were not applicable during the
implementation of the project since the environment and social impacts screening concluded that no TA contract was
to support the preparation of feasibility studies of infrastructure investment, technical designs or other activities
directly linked to future investment project (whether or not funded by the World Bank).
70. Stakeholder participation and public information disclosure were also conducted throughout the TA process.
Meaningful consultation and participation mechanism was conducted throughout the TA studies. Key stakeholders
were identified, mainly including logistics enterprises, relevant government agencies, experts, drivers, farmers, and
women. Their options and suggestions were taken into consideration during the TA studies.
Financial Management
71. Project audit reports for the fiscal years from 2019 to 2022 were furnished to the World Bank on time with
acceptable quality and unmodified (clean) audit opinion. No significant FM issues were disclosed in the audit reports.
Most of the interim financial reports (IFRs) were also submitted to the World Bank in a timely manner, with a couple
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China: GEF Efficient and Green Freight Transport Project (P159883)
of them having a very short delay. The IFRs were found to be of acceptable quality. Financial Management was rated
Satisfactory.
Procurement
72. The MOT PMO and Guangdong, Hubei, Yantai, and Weifang PMOs carried out procurement activities in line with
the legal covenants and the World Bank’s procurement guidelines. In total 37 contracts (35 Consulting Services and 2
Goods) were procured. By the project closing date, all contracts were completed and accepted, the total amount of
all contracts were paid to the consultants and suppliers. The designated procurement staff attended procurement
training provided by the Bank team during project preparation and attended additional trainings organized by the
World Bank and Tsinghua University during project implementation. In addition, MOT PMO arranged continuous
capacity building events on procurement and contract management for staff members of MOT PMO and the four
provincial and city PMOs. Procurement was rated Satisfactory.
C. BANK PERFORMANCE
Quality at Entry
73. The project components were carefully considered, well designed, and key risks were well identified. The
PAD provides evidence of a thorough project design at appraisal, and in particular, the technical assistance activities
had been designed with acute consideration of how they would contribute to the PDO. The technical assistance activities
were highly relevant to the China’s ambitions to reduce emissions from the transport sector and the lack of research that
had been done on how to do this in the logistics sector (relative to the passenger transportation sectors). The
procurement strategy was also appropriate. Project implementation phase task team members mentioned in interviews
that they found the project to be well designed by the preparation phase task team.
Quality of Supervision
74. The World Bank task team remained responsive to the counterpart and World Bank management during
implementation. The task team gave extensive technical guidance to the implementing agencies on all aspects of the
project, including but not limited to the overall project management approach and strategic study outputs. The World
Bank team worked closely with the implementing agencies to manage challenges like the delayed Designated Account
setup, and the COVID-19 disruption. The World Bank provided regularly training to the implementing agencies, and the
Beijing-based team were able to provide swift and just-in-time support to the counterparts. Finally, the project was
restructured promptly after the Mid Term Review.
75. US$ 665,497.86 of the GEF grant was cancelled and returned to GEF at project closing . The savings were
identified in November 2023, and were mainly due to currency change and the cancelled international study tours. The
team considered extending the grant to utilize all the savings, but since the PDO level indicators were already achieved,
the team decided to not spend the savings and let them go back to GEF for reuse in other GEF funded projects.
Justification of Overall Rating of Bank Performance
76. Based on the evidence set out in the preceding paragraphs, the Bank Performance Rating is Satisfactory.
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D. RISK TO DEVELOPMENT OUTCOME
77. While indications are positive, it is still yet to be seen whether the carbon reduction initiatives piloted under
Component 2 will be scaled up to other cities, thus amplifying the development impact of the project. The GEF grant
criteria required the project to make assumptions about to what extent the innovations piloted under the project would
be replicated in China. The project assumes that the measures implemented in the Bohai Bay Highway-Waterway
Multimodal Transport Project in Yantai will be replicated in at least 10 other locations. So far, it is promising that this
target will be met since MOT had made commitment to accelerate the development of multimodal transport at least
63 major ports across the country and it was assumed that at least some of them would be influenced by the learnings
derived from this pilot. Meanwhile, the project assumed that the measures implemented in the Integrated Urban-Rural
Distribution Project in Guangdong would be replicated in at least 20 other locations. As of July 2023, the MOT
announced 118 counties as the third batch of urban and rural transportation integration demonstration counties. Of
these, there are 74 counties that have characteristics (distribution scope, population size, and freight volume) that
mean they are suitable for replication of the measures done in the Guangdong pilot. In sum, based on the information
available at the closing of the project, it appears promising that the project innovations will be replicated unless there
is a dramatic change in government policy.
V. LESSONS AND RECOMMENDATIONS
78. Aligning Project Design with National Strategic Needs is Crucial for Success . The project's success was
significantly influenced by its close alignment with China's national strategic needs, particularly in the areas of energy
conservation and carbon emission reduction. This lesson highlights the importance of conducting thorough research
and engaging with stakeholders to understand national priorities and ensure that project interventions are relevant
and impactful. By focusing on key leverage points within the transportation sector, the project was able to maximize
performance benefits with minimal capital investment, demonstrating the effectiveness of targeted interventions.
79. Continuous Capacity Building and Knowledge Sharing are Crucial for Sustainable Impact. The project's success
in promoting green freight practices was significantly influenced by its capacity building activities, which included
training programs, seminars, and knowledge sharing platforms. This lesson highlights the importance of investing in
long-term capacity building initiatives to ensure that project outcomes are sustained beyond the project's completion.
In particular, by equipping companies with the knowledge and tools to measure their carbon footprints, set low-carbon
goals, and develop sustainable roadmaps, the project has fostered a culture of environmental responsibility within the
industry. The project's use of professional media platforms to publicize project results and promote the concept of
green freight further amplified its impact and contributed to the long-term sustainability of its outcomes.
80. Multimodal Transport is a Powerful Tool for Emission Reduction. The project demonstrates the effectiveness
of promoting multimodal transport, particularly rail-water intermodal transport, in reducing carbon emissions and
energy consumption. By shifting freight from road to rail and water, the project showed it is possible to significantly
reduce transportation distance, leading to substantial reductions in fuel consumption and greenhouse gas emissions.
This lesson underscores the importance of prioritizing multimodal transport strategies in future projects aimed at
achieving sustainable freight transportation.
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81. Digital Platforms are Essential for Optimizing Freight Efficiency. The project's success in implementing digital
platforms for freight matching, route optimization, and logistics information sharing highlights the crucial role of
technology in improving freight efficiency and reducing costs. These platforms facilitated seamless connections,
optimized vehicle loading rates, and reduced waiting times for truck drivers, ultimately contributing to a more efficient
and cost-effective freight system. Furthermore, data standardization with platforms across modes, to share data helps
to smoothen multi-modal operations, enable shorter connections times between different modes and better route
planning/optimization This lesson emphasizes the need for incorporating digital solutions in future projects to enhance
freight logistics and promote sustainable practices.
82. Green Freight Initiatives Can Drive Inclusive Economic Development. The project's focus on promoting green
freight practices has not only yielded environmental benefits but also contributed to inclusive economic development.
By creating employment opportunities in the green logistics sector, particularly for women and low-income groups, the
project has fostered economic empowerment and social inclusion. This lesson highlights the potential of green freight
initiatives to drive sustainable and equitable economic growth.
83. Data Collection and Monitoring Require Further Refinement. While the project has made significant strides in
collecting data on carbon emissions and other environmental indicators, the data collection and monitoring systems
require further refinement. The project highlights the need for standardized data collection methodologies and robust
monitoring systems to ensure accurate and reliable data for evaluating project impact and informing future
interventions. This lesson emphasizes the importance of investing in data infrastructure and strengthening data
management practices to effectively track progress and measure the effectiveness of green freight initiatives.
84. More can be done to share to disseminate the lessons learnt from this project to audiences outside China.
The project made significant effort to record learnings from the project on TransFORM website with many case studies,
reports and news articles uploaded in Chinese and English. With the TransFORM website revamp completed in 2024, a
concerted effort should be made by World Bank to direct audiences outside China to review the TransFORM content.
This could be done using the World Bank Transport for Development blog site and doing some World Bank Transport
Global Practice webinars during 2024. As green and efficient freight technologies and practices evolve rapidly, World
Bank Transport management should move fast to disseminate the learnings from the project while they are still current
and relevant.
.
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ANNEX 1. RESULTS FRAMEWORK AND KEY OUTPUTS
A. RESULTS INDICATORS
A.1 PDO Indicators
Objective/Outcome: Improve the GoC's institutional capacity to formulate and evaluate policies and strategies
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
1. Number of analytical tools Number 0.00 2.00 2.00 2.00
adopted by MOT for
implementation in national 13-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
planning and policy
development
Comments (achievements against targets):
The target of this indicator was met from a baseline value of 0 to actuals of 2, the original target was not revised except matching the closing date after
restructuring.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
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2. Number of national plans Number 0.00 2.00 3.00 3.00
adopted by MOT for
implementation 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
The formally revised target after restructuring was met, the additional TA was to provide information for the development of a guidance note on modern
logistics system development.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
3. Number of guidelines on Number 0.00 1.00 1.00 1.00
improving urban freight
transport issued by MOT for 13-Aug-2018 31-Dec-2022 31-Dec-2023 24-Aug-2023
implementation
Comments (achievements against targets):
This indicator met the target with no change except matching a later closing date after restructuring.
Objective/Outcome: Pilot innovative carbon emission reduction measures in selected provinces
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
4. Total CO2 emission Number 0.00 15,600,000.00 15,600,000.00 33,164,175.00
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reduction (Tone, cumulative 13-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
in project life cycle)
Comments (achievements against targets):
The actual values for this indicator substantially surpassed the original target which was not changed except matching the revised closing date. The CO2
emission reduction benefits of the project come from two aspects (i) direct GHG emission reductions from the pilot projects in Yantai, Guangdong, Hubei
and Weifang and (ii) indirect CO2 emission reductions from the replication of the successful pilots in Yantai and Guangdong because of policy incentives and
capacity-building activities.
A.2 Intermediate Results Indicators
Component: Component 1: National Technical Assistance and Policy Development
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Number of national TAs Number 0.00 6.00 9.00 15.00
completed
24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Number of national TAs Number 0.00 5.00 5.00 5.00
informed by citizen
engagement
Comments (achievements against targets):
At restructuring, the original target was increased as three new national TA projects were added to utilize savings from Component 3 affected by COVID 19.
15 TAs were completed rather than the 9 envisaged at the restructuring because some of the TAs were split into multiple smaller TAs to improve the
procurement approach.
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Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
MOT adopts the action plan Yes/No No Yes Yes Yes
for multimodal freight
transport development 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Target achieved, indicator name revised from "MOT adopts the medium‐to‐long term multimodal freight transport plan" to "MOT adopts the action plan
for multimodal freight transport development".
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
MOT adopts the E-commerce Yes/No No Yes Yes Yes
based urban freight
distribution solution 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Target achieved. No change made at restructuring except to match target date with new closing date of project.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
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National freight flow model Yes/No No Yes Yes Yes
completed
24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Target achieved. No change made at the restructuring except to match target completion date with project closing date.
Component: Component 2: Subnational Technical Assistance and Pilots
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Percentage of Bohai Gulf Percentage 2.10 10.00 10.00 10.16
ferry traffic that is drop-and-
pull 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Target exceeded. No change made at restructuring except to extend target completion date to match closing date.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Weifang adopts the proposal Yes/No No Yes Yes Yes
for improving urban freight
transport efficiency 09-Jul-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
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Comments (achievements against targets):
Target achieved. No change made at restructuring except to match target completion date with project closing date.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Hubei Department of Yes/No No Yes Yes Yes
Transport adopts the Han
River inland waterway 09-Jul-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
integrated development plan
Comments (achievements against targets):
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Percentage of empty trucks Percentage 95.00 80.00 80.00 79.10
on the return trip from rural
villages to urban centers in 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Guangdong
Comments (achievements against targets):
Target achieved. No change made at restructuring except to match target completion date with project completion date.
Indicator Name Unit of Measure Baseline Original Target Formally Revised Actual Achieved at
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Target Completion
Villagers trained under the Number 0.00 200.00 200.00 233.00
Guangdong integrated
urban-rural distribution 24-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
system pilot, cumulative
Female villagers trained Number 0.00 100.00 100.00 134.00
under the Guangdong
integrated urban-rural 23-Aug-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
distribution system pilot,
cumulative
Comments (achievements against targets):
Target exceeded by 16%. No change made at restructuring except to match target completion date with project closing date.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Number of Yangtze River Number 0.00 3.00 3.00 3.00
cargo vessels enrolled in the
Hubei pilot (Number) 01-Nov-2022 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
This indicator was newly added at the restructuring due to the new pilot activities in Hubei Province.
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Component: Component 3: Capacity Building, M&E, and Project Management
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Truck drivers trained at Number 0.00 300.00 300.00 6,458.00
national green truck driver
trainings, cumulative 09-Jul-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
NPMO provided green driving-related trainings for truck drivers through National Road Continuing Education Network Platform for Freight Driver on
Professional Qualification Network of Transport. 4,201 people trained in 2020, 977 in 2020, 500 in 2021 and 780 in 2022.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
Persons trained in national- Number 0.00 500.00 500.00 1,153.00
level trainings and
workshops, cumulative 31-Dec-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Target is increased from 400 to 500 because of the new capacity building activity at the national level.
Formally Revised Actual Achieved at
Indicator Name Unit of Measure Baseline Original Target
Target Completion
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International freight Number 0.00 2.00 4.00 4.00
transport conferences held
under TransFORM 31-Dec-2018 31-Dec-2022 01-Dec-2022 31-Dec-2023
Comments (achievements against targets):
Restructuring: Target increased because the same budget could support more workshops and conferences as they were being conducted online during
COVID-19 restriction period.
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B. KEY OUTPUTS BY COMPONENT
Objective/Outcome 1 Improvement of GoC's institutional capacity to formulate and evaluate policies and strategies
1.Number of analytical tools adopted by MOT for implementation in national planning and policy
development - 2
Outcome Indicators 2. Number of national plans adopted by MOT for implementation (Number) - 3
3. Number of guidelines on improving urban freight transport issued by MOT for implementation
(Number) - 3
1. Number of national TAs completed, and national TAs informed by citizen engagement (Number) – 15,
and 5
2. MOT adopts the action plan for multimodal freight transport development (Yes/No) - Yes
3. MOT adopts the E-commerce based urban freight distribution solution (Yes/No) - Yes
Intermediate Results Indicators
4. National freight flow model completed - Yes
5. Truck drivers trained at national green truck driver trainings, cumulative (Number) – 6,458
6. Persons trained in national-level trainings and workshops, cumulative (Number) - 1153
7. International freight transport conferences held under TransFORM (Number) - 4
Objective/Outcome 2 Carbon emission reduction in selected provinces
Outcome Indicators 1. Total CO2 emission reduction (Tone, cumulative in project life cycle) (Number) – 33,164,175
1. Percentage of Bohai Gulf ferry traffic that is drop-and-pull (Percentage) – 10.16%
2. Weifang adopts the proposal for improving urban freight transport efficiency (Yes/No) - Yes
3. Hubei Department of Transport adopts the Han River inland waterway integrated development plan
(Yes/No) - Yes
Intermediate Results Indicators 4. Percentage of empty trucks on the return trip from rural villages to urban centers in Guangdong
(Percentage) – 79.1%
5. Villagers trained under the Guangdong integrated urban-rural distribution system pilot, cumulative and
villagers trained by the pilot-female (Number) – 233, of which 134 (57%) females
6. Number of Yangtze River cargo vessels enrolled in the Hubei pilot (Number) - 3
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China: GEF Efficient and Green Freight Transport Project (P159883)
ANNEX 2. BANK LENDING AND IMPLEMENTATION SUPPORT/SUPERVISION
A. TASK TEAM MEMBERS
Name Role
Preparation
Hua Tan Task Team Leader(s)
Hua Xu Procurement Specialist(s)
Yi Geng Financial Management Specialist
Huijing Deng Team Member
Tong Zhu Team Member
Yumeng Zhu Team Member
Ninan Oommen Biju Team Member
Yin Yin Lam Team Member
Yi Yang Team Member
Bernard Aritua Team Member
Aristeidis Panou Counsel
Ning Yang Environmental Specialist
Alejandro Alcala Gerez Counsel
Randeep Sudan Team Member
Songling Yao Social Specialist
Garo J. Batmanian Team Member
Maria Luisa G. Juico Team Member
Rajagopal S. Iyer Team Member
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Teresita Ortega Team Member
Supervision/ICR
Mengling Shen Task Team Leader(s)
Yuan Wang Procurement Specialist(s)
Haixia Li Financial Management Specialist
Songling Yao Social Specialist
Yan Zhang Procurement Team
Yiren Feng Environmental Specialist
Aristeidis Panou Counsel
Yi Yang Team Member
Mingyang Hao Team Member
Zhaoyuan Wang Team Member
B. STAFF TIME AND COST
Staff Time and Cost
Stage of Project Cycle
No. of staff weeks US$ (including travel and consultant costs)
Preparation
FY16 4.227 18,825.63
FY17 0 7,987.91
FY18 15.198 145,040.45
FY19 17.204 132,870.52
FY20 9.070 29,779.18
FY21 0 75.54
FY22 0 776.49
FY24 0 2,130.49
Total 45.70 337,486.21
Supervision/ICR
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FY20 0 15,733.83
FY21 5.050 41,485.33
FY22 11.647 69,067.75
FY23 12.075 89,344.08
FY24 18.940 129,711.86
Total 47.71 345,342.85
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ANNEX 3. PROJECT COST BY COMPONENT
Table 3.1 Project Cost by Component (inclusive of both GEF grant and Counterpart financing)
Amount Actual at
Amount at
at Project
Components Restructuring
Approval Closing
(US$)
(US$) (US$)
Component 1: National TA and Policy 4,850,000 5,350,000 11,940,722
Development
Component 2: Local TA and Pilot 3,050,000 3,050,000 2,773,477
Projects
Component 3: Capacity Building, M&E, 5,766,095 5,266,095 6,495,707
and Project Management
Total Project Cost 13,666,095 13,666,095 21,209,906
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ANNEX 4. EFFICIENCY ANALYSIS
1. The project substantially surpassed the ratio of incremental costs versus environmental benefits at
appraisal. In accordance with the guidelines of the Global Environment Facility (GEF), an incremental cost
analysis was conducted during the project design stage to assess the incremental costs and environmental
benefits of the project scenario compared to the BAU. The incremental costs of the project mainly refer to
the funds used to support national-level technical assistance to improve the efficiency of intermodal freight
systems, and to provide support for local pilot projects, as well as capacity building. The environmental
benefits brought by the project mainly include direct and indirect carbon dioxide emission reduction benefits.
Direct carbon dioxide emission reduction benefits mainly come from the implementation of two local pilot
projects, (the Bohai Bay Highway-Waterway Multimodal Transport Project in Yantai, and the Integrated
Urban-Rural Distribution Project in Guangdong only). Indirect GHG emission reduction benefits mainly stem
from promoting national and subnational CO2 emission reduction policies and strategies and establishing
emission analysis tools in the freight sector, which has the replication potential to promote and disseminate
findings of the project further.
2. The incremental cost at appraisal was approximately US$13.67 million (including the GEF grant of
US$8.25 million and counterpart funds of US$5.42 million), and the total environmental benefits estimated
were approximately 15.6 million tons. Therefore, the expected cost per unit of carbon dioxide emission
reduction was US$ 0.876 per ton at appraisal. Meanwhile, at project closing the expected emission reduction
has been recalculated and the CO2 emission reduction forecast due to the project is 33.16 million tons, an
over achievement of 112 percent of the PDO indicator target. As the counterpart funds materialized at the
closing reached at about US$13.66 million, the incremental cost is US$21.85 million and achieved the carbon
emission reduction cost of about US$0.667 per ton, which is lower than the US$0.876 per ton at appraisal.
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ANNEX 5. CARBON EMISSION REDUCTION CALCULATION
1. The CO2 emission reduction benefits of the project is made up of two aspects: (i) direct GHG emission
reductions from the pilot projects, such as modal shift from road transport to waterways, reduction in urban
distribution trips due to integration, reduction in empty freight trips, etc. and (ii) indirect GHG emission
reductions from the replication of the successful pilots as a result of policy incentives and capacity-building
activities.
Bohai Bay Highway-Waterway Multimodal Transport Project in Yantai
2. In this project, the emission reduction is through “shift”, i.e. attracting more traffic from road to sea
transport. In the BAU scenario, it was assumed that the number of trucks (both in roll-on-roll-off (RoRo) and
drop-and-pull (DnP) mode) was increasing at the same rate (5%) annually, which is derived from the historic
seaway transport data in the past 10 years. In the GEF scenario, the number of trucks in RoRo mode remains
the same as BAU, while the share of DnP is expected to level up at the targeted growth rate.
3. In the BAU scenario, with the most recent and actual number of trucks by seaway in year 2021, 2022
and 2023, and with the normal growth rate (5%), the total number of trucks by seaway in the studied years
(2024-2031) could be estimated. With the same methodology, annual BAU ratio of DnP/total trucks is
calculated as 2.1%, thus number of DnP trucks can be calculated as well.
Total trucks by seaway (BAU) = Baseline number of trucks by seaway × 1.05n
Number of DnP (BAU) = Total trucks by seaway (BAU) × BAU ratio
Number of RoRo (BAU) = Total trucks by seaway (BAU) × (1- BAU ratio)
* where n denotes the number of years after the baseline year
* Total trucks by seaway and Numbers of RoRo (BAU) in year 2021-2023 are actual
number counted by Yantai PMO.
* Total trucks by seaway and Numbers of RoRo (BAU) in year 2024-2031, and Numbers of
DnP(BAU) are calculated through above formulas.
4. In the GEF scenario, the number of trucks in RoRo mode remains the same as BAU. The increasing ratio
of DnP over total sea transport in 2024-2031, and the number of RoRo trucks, the number of DnP trucks in
2024-2031 can be estimated. Thus, the total number of trucks by seaway can be estimated.
Number of DnP (GEF) = Number of RoRo (BAU)×(increasing ratio/1-increasing ratio)
Total trucks by seaway (GEF) = Number of RoRo (BAU) + Number of DnP (GEF)
* where increasing ratio is the mean difference value of actual DnP/Total in 2021-2023,
which is calculated to be 1.6%.
5. The impact of GEF intervention is the increase of trucks using sea transport.
Number of increased trucks by seaway = Total trucks by seaway (GEF) – Total trucks by
seaway (BAU)
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6. The increased trucks by seaway were assumed to travel from Yantai to Dalian by road transport under
the BAU scenario. The direct emission reduction resulted from the GEF intervention is thus evaluated by
calculated the difference of emission factor between the road transport and seaway transport for trucks,
which is 1.34tCO2/truck, this factor was analyzed and determined in “Quantitative Analysis Report on
Environmental and Economic Benefits of Shandong-Liaoning Public Water Ro-Ro Intermodal Transport”
carried out by the Yantai PMO.
Direct emission reduction from road = Number of increased trucks by seaway× Emission
factor for trucks
7. As more trucks are transported by seaway, number of ship trips may increase, leading to additional
emissions. Based on the operator’s information, one freight ship can carry 300 trucks per trip. The number
of ship trips per day can thus be calculated and all numbers are rounded up.
Number of ship trips per day (BAU or GEF) = Total trucks by seaway (BAU or GEF) / 365 /
300
Increased ship trips per day = Number of ship trips per day (BAU) - Number of ship trips
per day (GEF)
* There are 12 ships travel from Yantai to Dalian at present, and the full capacity of ships
is not fully used now, it can be guaranteed that no extra ship is needed before 2031 to
meet the increasing seaway transport demand.
8. Given the emission factor for ship fuel use is 3150 kg CO2/ ton, and the fuel use per ship per trip is 18
tons oil, thus, the increased CO2 by ship per year can be calculated.
Increased CO2 by ship per year = Increased ship trips per day × Oil use per ship per trip ×
Emission factor for ships × 365
9. Each year the CO2 reduction is the difference between CO2 emission saved from road and CO2
emission increased from ship.
Direct CO2 reduction per year = Direct emission reduction from road – Increased CO2 by
ship per year
Total CO2 reduction = ∑������
������ ������������������������������������ ������������������ ������������������������������������������������������ ������������������ ������������������������
* where n indicates years of GEF project
10. With more traffic from road to sea transport, and a higher percentage of drop-and-pull in Bohai Gulf
ferry traffic, it is estimated that the carbon emission reduction of 142,895 tons was achieved by the end of
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the project (end of 2023), and a total of 1,739,062.58 tons of carbon emission reduction will be achieved in
the life cycle of the project (end of 2031), which is much higher than the designed goal of Yantai CO2
reduction in the PAD. What is more, if the ratio of DnP/Total stays 13% and unchanged after 2025 ( as
designed in PAD), a total of 1,136,419.75 tons of carbon emission reduction will be achieved and will still be
higher than the designed goal.
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Table A5.1 Calculation and forecast of CO2 emission reduction for Yantai Pilot
（Emission reduction estimated by 2022, projected emission reduction estimated by 2031 ）
Annual number of trucks
2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031
(*104)
Roll on n roll off 61.43 55.56 63.79 73.98 77.68 81.57 85.65 89.93 94.42 99.15 104.10
DnP/Total 2.10% 2.10% 2.10% 2.10% 2.10% 2.10% 2.10% 2.10% 2.10% 2.10% 2.10%
BAU Drop n pull 1.37 1.28 1.49 1.59 1.67 1.75 1.84 1.93 2.03 2.13 2.23
Total trucks by
62.80 56.84 65.28 75.57 79.35 83.32 87.48 91.86 96.45 101.27 106.34
seaway
Roll on n roll off 61.43 55.56 63.79 73.98 77.68 81.57 85.65 89.93 94.42 99.15 104.10
DnP/Total 6.98% 8.97% 10.16% 11.76% 13.36% 14.96% 16.56% 18.16% 19.76% 21.36% 22.96%
GEF Drop n pull 4.54 5.48 7.21 9.86 11.98 14.35 17.00 19.95 23.25 26.93 31.03
Total trucks by
65.08 61.04 71.01 83.84 89.66 95.92 102.64 109.88 117.68 126.08 135.13
seaway
Number of increased trucks
2.28 4.20 5.73 8.27 10.31 12.60 15.16 18.03 21.23 24.80 28.79
by seaway
Emission factor for trucks (t
1.34
CO2/truck)
Direct emission reduction
30596 56229 76766 110859 138188 168833 203153 241545 284451 332361 385819
from road (ton)
Number of ship trips per day
6 6 6 7 8 8 8 9 9 10 10
(BAU)
Number of ship trips per day
6 6 7 8 9 9 10 11 11 12 12
(GEF)
Increased ship trips per day 0 0 1 1 1 1 2 2 2 2 2
Emission factor for ships (ton
3.15
CO2/ton oil)
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Fuel use per trip for ship (ton
18
oil)
Increased CO2 by ship per
0 0 20696 20696 20696 20696 41391 41391 41391 41391 41391
year (ton)
Total direct CO2 reduction per
30596 56229 56070 90164 117492 148137 161762 200154 243060 290970 344428
year (ton)
Total direct CO2 reduction
(ton) 1,739,062.58
Average yearly CO2 reduction
(ton) 158,096.60
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Integrated Urban-Rural Distribution Project in Guangdong
11. Using the public module of the "Yue cheng pei" APP platform, the pilot project was assumed to achieve
emission reduction through reducing the percentage of empty trucks on the return trip from rural villages to
urban centers in Guangdong. Based on the delivery fuel consumption, average transportation distance,
delivery times and other operating indicators of 30 sample vehicles, comparative analysis method between
“the base period “(three months before the platform is officially launched, that is, April-June 2022) and “the
demonstration period “(the date of the platform is officially launched, namely July 1 , 2022-October 2023)
was adopted. Through the fuel consumption savings generated by the return delivery of sample vehicles in
the base period and the demonstration period, the actual emission reductions, and the expected emission
reductions of the pilot project until 2031, are calculated.
12. In the baseline scenario, the empty loaded rate of return trucks remains a slow decrease each year.
The empty loaded rate is expected to decrease by 1% per year from 2022, namely from 94.6% of the sample
vehicles monitored before the platform launched, to the end of 2031 with 85.6%.
13. With the GEF intervention, the empty loaded rate of return trucks was expected to decrease rapidly.
The direct emission reduction resulted from the increased delivery times of the return trip from rural villages
to urban centers, which in the baseline scenario, is conducted by the same type of vehicle with an additional
round-trip instead of per time of return trip. As of October 2023, a total of 7,318 vehicles have been
registered on "Yue cheng pei" platform.
14. Based on (i) the delivery times from urban centers to rural villages, and (ii) delivery times of the return
trip of the sample and platform vehicles in the base period and the demonstration period, the reduction on
the empty loaded rate of return trucks can be calculated.
The empty loaded rate of return trip = 1－Delivery times of the return trip/Delivery times
from urban centers to rural villages
The reduction on the empty loaded rate of the sample or platform vehicles=Average
empty loaded rate of return trip of sample vehicles in the base period－Average empty
loaded rate of return trip of the sample or platform vehicles in the demonstration period
15. Through the platform, the increased delivery times of the return trip from rural villages to urban
centers of the sample and platform vehicles, which in the baseline scenario, is conducted by the same type
of vehicle with an additional round-trip instead of per time of return trip. The saved delivery distance is 2
times of the delivery distance increment of the return trip. The delivery distance increment of return trip can
be calculated by the reduction on the empty loaded rate, delivery times from urban centers to rural villages
and the average delivery distance of return trip.
Saved delivery distance = The delivery distance increment of return trip×2=The reduction
on the empty loaded rate×Delivery times from urban centers to rural villages×The average
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delivery distance of return trip×2
16. Diesel fuel saving can be calculated by saved delivery distance of the sample or platform vehicles, and
fuel consumption per 100 kilometers of the sample vehicles. Since the fuel consumption per 100 kilometers
of a delivery vehicle loaded is slightly greater than that of a delivery vehicle without load. To simplify the
calculation, the vehicle's fuel consumption per 100 kilometers without load is calculated based on the
average fuel consumption per 100 kilometers of sample vehicles.
Diesel fuel saving=Fuel consumption per 100 kilometers of the sample vehicles in base
period×Saved delivery distance of the sample or platform vehicles/100
In which, Fuel consumption per 100 kilometers of the sample vehicles in base
period=Diesel fuel consumption of the sample vehicles in base period×100/Driven
distance of the sample vehicles in base period
17. The emission reduction of the pilot project can be estimated by the diesel fuel saving and its emission
factor.
Direct CO2 reduction of the sample or platform vehicles=Diesel fuel saving × emission
factor of diesel fuel
In which, Emission factor of diesel fuel is 2.67kg/L
18. The calculation (see Table A5.2) shows that by the end of the project, the average annual emission
reduction of 30 sample vehicles in Guangdong pilot project is predicted to be 317.63 tons; and over the full
life cycle of the project (end of 2031), the emission reduction of sample vehicles is predicted to be 3,176.27
tons.
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Table A5.2 Calculation and forecast of CO 2 emission reduction of 30 sample vehicles in Guangdong pilot project
（Emission reduction estimated by October 2023, projected emission reduction estimated by 2031 ）
Calculation Unit 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031
Parameter
Average empty % 94.65% 93.65% 92.65% 91.65% 90.65% 89.65% 88.65% 87.65% 86.65% 85.65%
loaded rate of
return trip of
sample
vehicles in the
base period
Average empty % 92.31% 83.53% 72.45% 62.84% 54.50% 47.27% 41.00% 35.56% 30.84% 26.75%
loaded rate of
return trip of
the sample
vehicles in the
demonstration
period
The reduction % 2.33% 10.12% 20.20% 28.81% 36.15% 42.38% 47.65% 52.09% 55.81% 58.90%
on the empty
loaded rate
Delivery times times 7,888 12,553 15,064 15,064 15,064 15,064 15,064 15,064 15,064 15,064
from urban
centers to rural
villages per
year
The average Km 65.13 53.54 97.00 97.00 97.00 97.00 97.00 97.00 97.00 97.00
delivery /per trip
distance of
return trip
Saved delivery km 23,991.34 135,986.75 590,299.46 841,960.55 1,056,356.56 1,238,431.47 1,392,473.34 1,522,201.31 1,630,841.14 1,721,190.58
distance
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Diesel fuel L 2,810.84 15,932.26 69,159.73 98,644.45 123,763.17 145,095.14 163,142.75 178,341.73 191,070.02 201,655.40
saving
Fuel L/100km 11.72
consumption
per 100
kilometers of
the sample
vehicles in
base period
Emission factor kg/L 2.67
of diesel fuel
Direct CO2 t CO2 7.50 42.54 184.66 263.38 330.45 387.40 435.59 476.17 510.16 538.42
reduction per
year
Average t CO2 317.63
annual CO2
emission
reduction
Total CO2 t CO2 3,176.27
reduction
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19. For comparing the empty loaded rate of return trip of the sample vehicles in the demonstration period, two
comparable time periods, "July to October 2023" and "July to October 2022", were used to calculate the year-on-year
decrease rate of the empty loaded rate, which is as the average annual decrease of the empty loaded rate and is used to
predict the empty loaded rate level in subsequent years of the project.
20. The annual number of deliveries from urban centers to rural villages after 2024 is assumed to be 15,064, which is
converted based on the average monthly delivery times in 2023, without considering vehicle growth factors. The average
delivery distance of return trip adopts 97km of the average transportation distance between Guangzhou and Qingyuan.
21. As of October 2023, a total of 7,318 vehicles were registered on the "Yue cheng pei" platform. Scale conversion
shows that the average annual emission reduction of Guangdong pilot project is about 77,000 tons, and the emission
reduction during the entire project cycle (2022~2031) is about 770,000 tons.
22. The scale effect amplification of Guangdong pilot project depends on the number and planning demonstration
situation of the similar projects in China. The Ministry of Transport announced 118 counties (cities, districts) in July 2023,
as the third batch of urban and rural transportation integration demonstration counties16. Guangdong pilot project is
centered in Guangzhou and radiates to Qingyuan, Zhongshan and Foshan. Comprehensively considering the factors, such
as the distribution scope, population size, and freight volume level, there are 74 counties (cities, districts) with the similar
scale as Guangdong pilot project selected from the list of counties announced, which are shown in the figure below. As
a result, the emission reduction of scale effect amplification of Guangdong pilot project is evaluated to be 15,400,000
tons.
Figure A5.1 Distribution and number of similar demonstration projects in China
16
Notice on the establishment of the third batch of urban and rural transportation integration demonstration counties from
MOT. https://xxgk.mot.gov.cn/2020/jigou/ysfws/202307/t20230728_3875391.html
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CO2 reduction calculation on solar integrated navigation light construction, waterway upgradation
project, improvement on port shore power coverage, deep carbon reduction technology and
construction of analyzing software of carbon emissions for inland cargo ships in Yangtze river in Hubei
province
23. In this pilot, emission reduction was to be achieved through the solar integrated navigation light demonstration
project and the waterway modernization promoted by policies, enhancing the shipping efficiency. The modernization of
waterway was to focus on and realize the standardization of waterway improvement and maintenance in the upper,
middle, and lower reaches of Han River, namely building standardized and modernized waterway.
A. CO2 reduction calculation of navigation light demonstration
24. Based on 20 MWHB90A10 solar integrated navigation lights, the amount of electricity that can be saved in a year
is calculated, thereby reducing the amount of carbon emission.
The average power of one light is 1.5W, and the converted daily power consumption is：:
QC1=1.5*10-3kW*24h=0.036kWh
Electricity saved by 20 lights in one year is：
QE=0.036kWh*20*365=262.8kWh
According to the electric energy conversion coefficient, 1kWh electricity
consumption=0.997kg CO2 emission, the carbon emissions that can be reduced by solar
lights in one year are：
QC=262.8kWh*0.997kg=262kg=0.262 ton
25. Therefore, the solar navigation light demonstration project can reduce carbon emissions by 0.262 tons in one year,
and the project is expected to achieve a carbon reduction of 0.786 tons from 2021 to the end of the project (end of
2023). The total carbon reductions over the full life cycle (end of 2031) of the project are 2.9 tons.
CO2 reduction calculation of waterway upgradation
26. According to the "14th Five-Year Plan for Water Transportation Development in Hubei Province", the upgrading
project of Han River waterway will be completed in the "14th Five-Year Plan" period. Therefore, it is predicted that the
carbon emission reduction benefits from the waterway upgrading will start from 2025 at the end of the "14th Five-Year
Plan" period.
27. After the completion of the waterway improvement and upgrading project, the ship class matches the scale of the
waterway, and the upgrading of the waterway will inevitably bring about the upgrading of the ship class and bring about
a corresponding change in the mode of transportation from the highway to the waterway. Due to the large-scale ship
and the enhancement of ship cargo load rate, the loading capacity of a single ship has increased significantly. Therefore,
the number of ship voyages can be reduced under the same total cargo turnover, saving the ship fuel consumption, and
producing the benefit of carbon emission reduction. Utilizing data of 2020 in the existing statistical yearbook and the
cargo demand of each port, based on different ship models, freight speeds, fuel consumption and cargo class etc., the
study establishes the carbon emission reduction calculation under the replacement mode of ship model.
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①CO2 reduction calculation of 2,000-tonne waterway improvement project from Xinglong to Caidian
28. 2,000-tonne waterway improvement project from Xinglong to Caidian: 233 kilometers of waterway are improved
according to the standard of Grade II, mainly involving water transport in Qianjiang City, Tianmen City and Wuhan City.
According to the existing ships in BAU scenario, The Cargo tonnage of ship in Qianjiang-Tianmen-Wuhan is 1,000-tonne,
and the total volume of cargo ship includes water transportation volume in Qianjiang, Tianmen and Wuhan (10%).
Total ship volume (BAU) =Water transportation volume/ship tonnage
=（58+136.2+2,390.8）/0.1=25,850 ships
Total fuel consumption (BAU) = Total ship volume (BAU) ×Total distance×Fuel
consumption/kM
=25,850*233*4.9 =29,522,945kg
29. Under GEF scenario, after the implementation of 2,000-tonne waterway improvement project from Xinglong to
Caidian, the waterway transport ships will be upgraded to 2,000 tons, and the total volume of cargo ship includes water
transportation volume in Qianjiang, Tianmen and Wuhan (10%).
Total ship volume (GEF) =Water transportation volume/ship tonnage
=（58+136.2+2,390.8）/0.2=12,925 ships
Total fuel consumption (GEF) = Total ship volume (GEF) ×Total distance×Fuel
consumption/kM
=12,825*233*5.2 =15,659,930kg
Under the conversion of BAU-GEF scenario, the carbon emission reductions from Xinglong
to Caidian are:
CO2 Reduction=（Total fuel consumption(BAU)-Total fuel consumption(GEF)）×Carbon
emission coefficient
=（Total fuel consumption(BAU)-Total fuel consumption(GEF)）
*3.206=4,441,2766.1kg=44,412.8 tons
*where Carbon emission coefficient is from the United Nations Intergovernmental Panel
on Climate Change and provided by Hubei PMO.
②CO2 reduction calculation of 1,000-tonne waterway improvement project from Danjiangkou to
Xiangyang
30. The waterway improvement project from Danjiangkou to Xiangyang, is from the shiplift downstream of the
approach channel of Danjiangkou hub to Cuijiaying hub, with a total length of 125 kilometers, covering Shiyan city and
Xiangyang City. It is constructed according to the standard of 1000-tonne waterway.
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31. Under BAU scenario, the shipping capacity of Danjiangkou-Xiangyang section is 700 tons, and the total volume of
cargo ship includes water transportation volume in Shiyan and Wuhan(90%).
Total ship volume (BAU) =Water transportation volume/ship tonnage
=（1,067.62+509）/0.07=22,524 ships
Total fuel consumption (BAU) = Total ship volume (BAU) ×Total distance×Fuel
consumption/kM
=314,669*125*4.1 =11,543,110.71kg
Under GEF scenario, the shipping capacity of Danjiangkou-Xiangyang section is 1000 tons,
and the total volume of cargo ship includes water transportation volume in Shiyan and
Xiangyang.
Total ship volume (GEF) =Water transportation volume/ship tonnage
=（1,067.62+509）/0.1=15,767 ships
Total fuel consumption (GEF) = Total ship volume (GEF) ×Total distance×Fuel
consumption/kM
=220,268.3*125*4.9 =9,656,797.5kg
Under the conversion of BAU-GEF scenario, the carbon emission reductions from
Danjiangkou to Xiangyang are:
CO2 Reduction=（Total fuel consumption(BAU)-Total fuel consumption(GEF)）×Carbon
emission coefficient
=（Total fuel consumption(BAU)-Total fuel consumption(GEF)）*3.206
=6,047,520.165kg=6,047.5 tons
Table A5.3 CO 2 reduction calculation on waterway upgradation project
Qianjiang-Tianmen-Wuhan Danjiangkou-Xiangyang
Wuhan（
Qianjiang Tianmen Xiangyang Shiyan
10%）
Annual total volume（104ton） 58 136.2 2,390.8 1,067.62 509
Annual total distance（km） 233 125
tonnage（104ton
0.1 0.07
）
Fuel
BAU consumption/kM 4.9 4.1
(Annually) （kg）
Total ship volume 25,850 22,523.14286
Total fuel
29,512,945 11,543,110.71
consumption（kg
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）
tonnage（104ton
0.2 0.1
）
Fuel
consumption/kM 5.2 4.9
GEF （kg）
(Annually)
Total ship volume 12,925 15,766.2
Total fuel
consumption（kg 15,659,930 9,656,797.5
）
Carbon emission coefficient 3.206 3.206
Annual CO2 Reduction（kg） 4,441,2766.1 6,047,520.2
Annual CO2 Reduction（ton） 44,412.8 6,047.5
Annual CO2 Reduction（ton） 50,460.3
Total CO2 Reduction during the full
353,222.1
life cycle of the project（ton）
32. According to the "14th Five-Year Plan for Water Transportation Development in Hubei Province", the upgrading
project of Han River waterway will be completed in the "14th Five-Year Plan" period. Therefore, it is predicted that the
carbon emission reduction benefits from the waterway upgrading will start from 2025 at the end of the "14th Five-Year
Plan" period. It is estimated that the project's full life cycle (2031) will reduce 353,222.1 tons of carbon emissions.
C. CO2 Reduction of Comprehensive development of Hanjiang inland waterway in Hubei Province-Port
shore power
33. The purpose of this pilot is to improve shore power coverage in docks and anchorages, eliminate old ships, develop
electric ships, and achieve carbon and emission reductions by implementing clean energy substitution in ship power
systems.
34. The calculation is based on the annual operating days of each berth: 330 days, the average ship shore power usage
of 6 hours per day, and the shore power consumption capacity of 90kW.
35. The annual electricity consumption port shore power=power consumption of the shore power of a single berth×
daily usage time of the ship’s shore power of a single berth×the number of operating days of the berth×the number of
berths =90×6×330×2= 356,400 kWh.
36. According to the fuel consumption rate of marine diesel generator, take 250g/kWh, provided by Hubei PMO.
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Fuel Consumption reduced corresponds to usage of port power
=Annual electricity consumption×Fuel consumption rate
= 35.64×10,000×0.25=89,100kg
Saving 1L of diesel = 2.63kg CO2 emission reduction, and 1L of heavy diesel = 0.92kg.，
CO2 reduction of using port power =（Fuel consumption reduced/0.92）×2.63
=（89,100/0.92）×2.63=254.71t。
Therefore, port shore power can reduce carbon emissions by 254.71 tons per year,
achieving a total carbon emission reduction of 2,547.1 tons in 10 years.
D. CO2 Reduction of Deep Carbon Reduction Technology and Construction of Analyzing Software of
Carbon Emissions for Inland Cargo Ships in Yangtze River
37. The demonstration and application vessels of this project, Changhang Freight 002 and Changhang Freight 001, are
used as the measurement objects to analyze the carbon reduction effect of the two types of bulk carriers under the
adoption of clean energy technology and operational energy consumption optimization technology.
The carbon emission calculation formula is as follows:
������������ = C ∙ ∑ ������
������
Where, ������������ is the annual CO2 emission from the ship, t.
������ is the emission conversion factor, according to GB/T 21404-2008, diesel takes 3.206,
LNG takes 2.75.
������ is the energy consumption of the ship for a single voyage.
������ is the annual volume of vessel trips, tons.
①Deep Carbon Reduction Technology: Long-haul cargo ship 002 was selected for comparison with a
demonstration comparison ship with a similar deadweight tonnage and similar sailing route.
Energy Annual energy
Annual carbon Annual carbon
Ship Fuel consumption per consumption（t
emission（t） reduction（t）
voyage（t） ）
Demonstrated
Diesel 8.09 242.7 778.1
ship
168.4
Changhang
LNG 7.39 221.7 609.7
Freight 002
38. From the above table, it can be seen that the annual carbon emission of the demonstration ship is about 778.1
tons, and the annual carbon emission of the ship 002 is about 609.7 tons, and the annual carbon reduction is about 168.4
tons, achieving a total carbon emission reduction of 1,178.8 tons by the end of 2031.
②Construction of Analyzing Software: The navigation data of CCA Cargo 001 before and after the
operation optimization were selected for comparison.
Annual energy Annual carbon Annual carbon
Reconstruction time Fuel
consumption（t） emission（t） reduction（t）
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Before 24.2 290.4 931.02
56.55
After 22.73 272.76 874.47
39. It can be seen from the analysis of the above table that: after the transformation of Changhang Cargo 001, the
annual fuel consumption of Changhang Cargo 001 is about 272.76t, and the annual carbon emission is about 874.47t.
Compared with the annual carbon reduction before the transformation, the annual carbon reduction effect is about
56.55t, achieving a total carbon emission reduction of 395.85 tons by the end of 2031.
40. In summary, the implementation of the project will promote CO2 emission reduction in terms of both navigation
light and waterway upgradation.
(a) ① The implementation of the replacement of solar navigation light in Han River waterways is
expected to reduce carbon emissions by 0.262 tons per year, and by the end of the project (end
of 2023), it is expected to achieve CO2 emission reduction of 0.786 tons. The total CO2 emission
reduction in the whole life cycle of the project (end of 2031) are 2.9 tons.
(b) ② After the completion of the Han River waterway upgrading project, it is predicted that a total
of 353,222.1 tons of CO2 emission reduction will be achieved over the project full life cycle
(2031).
(c) ③ Port shore power can reduce carbon emissions by 254.71 tons per year, achieving a total
carbon emission reduction of 2,547.1 tons in 10 years.
(d) ④CO2 Reduction of Deep Carbon Reduction Technology and Construction of Analyzing Software
of Carbon Emissions for Inland Cargo Ships in Yangtze River is 1574.65 tons by the end of 2031.
The overall CO2 reduction of Hubei pilot project is 357,346.75 tons.
41. In addition, the TA consultant of Hubei PMO evaluated the carbon reduction effect of application and promotion
of project research results. Combining the high demand and low demand scenarios of the Yangtze River's comprehensive
freight turnover, the carbon emissions of Yangtze River freight ships will increase rapidly from 2022 to 2050 when no
carbon reduction technical measures are taken. When three carbon reduction technical measures (green transportation
organization model, clean energy technology, operational energy consumption optimization) are adopted, carbon
emissions would grow with a show trend at first and then a steady downward trend. Carbon emissions peak in 2030 and
then decrease year by year. In which:
(a) Under the scenario of high demand for freight growth, the overall carbon reduction of Yangtze
River cargo ships is expected to reach 2.518 million tons in 2030;
(b) Under the low demand scenario of freight growth, the overall carbon reduction of Yangtze River
cargo ships is expected to reach 1.1489 million tons in 2030.
CO2 emission reduction potential analysis of Weifang Green Freight Demonstration Project
A. Calculation of emission reductions from the promotion of new energy transportation equipment
42. At project appraisal, the number of new energy distribution vehicles in Weifang was less than a hundred. Through
the demonstration and the implementation of related policies, it is expected that by 2025, 200 new energy distribution
vehicles would be added in Weifang.
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As data shown on the transportation energy consumption monitoring and statistical
platform in Weifang, the average annual cargo transportation distance of distribution
vehicles is 87,300 tons∙kilometers.
The diesel vehicle energy consumption and carbon emission intensity are 4.79 kgce/100
tons∙kilometers and 9.30 kg CO2/100 tons∙kilometers respectively.
The pure electric vehicle energy consumption and carbon emission intensity are 2.01
kgce/100 tons∙kilometers and 3.48 kg CO2/100 tons∙kilometers respectively. T
The energy saving and carbon emission due to the promotion of new energy transport
equipment are calculated as follows:
Annual energy saving = (energy consumption intensity
of diesel vehicles - energy consumption intensity
of pure electric vehicles) * cargo transportation turnover * 100 * number of vehicles
/1000
=（4.79-2.01）*8.73* 100*200/1,000
=485.39（tons of standard coal）
Annual emission reduction = (carbon emission intensity of diesel vehicles - carbon
emission intensity of pure electric vehicles) * cargo transportation turnover * 100 *
number of vehicles /1000
=（9.30-3.48）*8.73* 100*200/1,000
= 1016.17（tCO2）
B. Calculation of emission reductions due to improved energy use efficiency of transportation equipment
43. According to the pilot results, based on the calculation on the decline of 10% of the energy intensity of freight
transport units by 2025 compared to 2020 in Weifang, the energy consumption intensity of urban distribution in Weifang
in 2020 was 3.26 kgce/100 tons∙kilometers, and the carbon intensity was 7.04 kgCO2/100 tons∙kilometers. Then, the
energy consumption intensity and carbon intensity will be 2.93 kgce/100 tons∙kilometers and 6.34 kgCO2/100
tons∙kilometers in 2025. The predicted demand for urban freight transportation in Weifang in 2025 is 86.3 million
tons∙kilometers, and the annual energy saving and emission reduction formed by the improvement of energy use
efficiency are calculated as follows:
Annual energy saving = ( 2020 energy consumption intensity - 2025 energy consumption
intensity) * 2025 cargo transportation turnover * 100/1000
=（3.26-2.93）*8,630*100/1,000
=284.79（tons of standard coal）
Annual emission reduction = ( 2020 carbon emission intensity - 2025 carbon emission
intensity) * 2025 cargo transportation turnover * 100/1,000
=（7.04-6.34）*8,630*100/1,000
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China: GEF Efficient and Green Freight Transport Project (P159883)
=604.10（tCO2）
Summary of Carbon Emission Reduction Calculation Results
44. By the carbon emissions calculation of green freight projects, the carbon reduction benefits of each project are as
follows:
(a) The local pilot Guangdong project is expected to reduce the percentage of empty trucks on the
return trip from rural villages to urban centers by means of the e-commerce platform and is
expected to achieve a total carbon emission reduction of 770,000 tons in the full life cycle of the
project.
(b) The local pilot Yantai project is expected to achieve a total carbon emission reduction of
1,739,062.58 tons in the full life cycle of the project, by attracting more transport volume to shift
from the highway to the sea and raising the percentage of drop-and-pull.
(c) The local pilot Hubei project, with the replacement of solar-powered navigation lights ， the
completion of the Han River waterway upgrading project, improvement on port shore power
coverage, and deep carbon reduction technology and construction of analyzing software of
carbon emissions for inland cargo ships, is expected to achieve a total of 357,346.75 tons of
carbon emission reductions over the project's life cycle.
(d) The local pilot Weifang project is expected to achieve a total of 16,202.7 tons of carbon emission
reduction over the project's life cycle.
45. In short, the emission reductions of projects over the life cycle and scale effect amplification have achieved the
PDO indicator end target in PAD, and the details are shown as following table.
Table A5.4 Summary of carbon reduction projections and
for green freight transport project, and comparison with designed target in PAD
Project Carbon reduction projections Scale effect Designed Completion
over the project's lifecycle（ amplification target in PAD of Indicator
tons）
Bohai Bay Highway-Waterway 1,739,062.58 17,390,625.80
Multimodal Transport Project （10 times scale
in Yantai
effect）17 1,100,000 Achieved
17China has unveiled guidelines on developing comprehensive transport network, with the aim of developing a modern, high-
quality, and comprehensive national transport network. It proposes innovative multimodal transport models, accelerates the
development of multimodal transport, and plans to lay out 63 major ports across the country, including 27 major coastal ports
and 36 major inland river ports. It is reasonable to continue to use the 10x scale effect in PAD.
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China: GEF Efficient and Green Freight Transport Project (P159883)
Integrated Urban-Rural 770,000 15,400,000.00
Distribution Project in （20 times scale
Guangdong
effect）18 230,000 Achieved
Solar integrated navigation 357,346.75 357,346.75
light construction and
（No scale
waterway upgradation project Extra
etc. in Hubei province effect） N/A achievement
Weifang Green Freight 16,202.7 16,202.7
Demonstration Project （No scale
Extra
effect） N/A achievement
Total 2,882,612.03 15,600,000
33,164,175.25 (Scale effect) Achieved
18The Ministry of Transport announced 118 counties (cities, districts) in July 2023, as the third batch of urban and rural
transportation integration demonstration counties. Guangdong pilot project is centered in Guangzhou and radiates to
Qingyuan, Zhongshan and Foshan. Comprehensively considering the factors, such as the distribution scope, population size,
freight volume level, etc., there are 74 counties (cities, districts) with the similar scale as Guangdong pilot project selected from
the list of counties announced. It is reasonable to continue to use the 20x scale effect in PAD.
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China: GEF Efficient and Green Freight Transport Project (P159883)
ANNEX 6. BORROWER, CO-FINANCIER AND OTHER PARTNER/STAKEHOLDER COMMENTS
Comments received August 14, 2024. Machine translated from Mandarin Chinese.
The PMO has no comment on the report and thanks the World Bank project teams for their
guidance and assistance in project management, procurement, finance, and social
environment since the implementation of the project in the past five years.
The report comprehensively reflects the overall implementation of the project from the
aspects of the completion of the project PDO and intermediate indicators, finance,
procurement, project impact and other aspects, focuses on the realization of the project
objectives, as well as the experience of project implementation, and also introduces the
problems faced during the project preparation period and the key measures taken in the
implementation process. The project objectives and project design content are highly
consistent with the national industry development strategic objectives and policy
requirements, and the project research results provide intellectual support for the green and
efficient development of the national freight industry, especially some of the achievements
have been implemented, effectively guiding, and solving the practical problems and needs in
the development of the industry.
The World Bank has provided very professional and sufficient guidance during the project
initiation, implementation, and completion phases, and has been actively communicating
with all parties involved in the project implementation and solving difficulties.
During the implementation of the project, due to the impact of the epidemic, the relevant
research work of some sub-projects has lagged behind. In addition, due to personnel
changes and other factors, some local project agencies have changed greatly in project
handling personnel, which has an impact on the continuity and efficiency of project
management.
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