International Multilateral Public Climate Finance Dataset from 2000 to 2023

International multilateral public climate finance plays a key role in the global climate financing landscape, yet the availability of a comprehensive, publicly accessible, and transparent database remains inadequate. This study establishes an international multilateral public climate finance database covering the period from 2000 to 2023. The primary objective is to identify and track climate-related projects and their funding flows supported by major multilateral development finance institutions (MDFIs) and multilateral climate funds (MCFs). Using a machine learning model MLCF-BERT (Multilateral Climate Finance BERT), we extracted and classified climate mitigation and adaptation-related projects from project-level data, creating a climate finance database containing detailed information on funding sources, institutions, project types, recipient countries, financing amounts, and financing types. This database provides valuable insights into the distribution and trends of international climate finance, offering data support for climate finance policies and decision-making.

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Publication Details

Journal
Scientific Data
Published
2025-06-06
DOI
https://doi.org/10.1038/s41597-025-05308-x
Citations
3
Primary Topic
Climate Change Policy and Economics
Type
article
Field-Weighted Citation Impact
9.39

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International Multilateral Public Climate Finance Dataset from 2000 to 2023

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Scientific Data
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International Multilateral Public Climate Finance Dataset from 2000 to 2023

S. G. Fan, Kangxin An, Haiwang Zhong, Can Wang, Xinyang Dong
article en
3 citations

Abstract

International multilateral public climate finance plays a key role in the global climate financing landscape, yet the availability of a comprehensive, publicly accessible, and transparent database remains inadequate. This study establishes an international multilateral public climate finance database covering the period from 2000 to 2023. The primary objective is to identify and track climate-related projects and their funding flows supported by major multilateral development finance institutions (MDFIs) and multilateral climate funds (MCFs). Using a machine learning model MLCF-BERT (Multilateral Climate Finance BERT), we extracted and classified climate mitigation and adaptation-related projects from project-level data, creating a climate finance database containing detailed information on funding sources, institutions, project types, recipient countries, financing amounts, and financing types. This database provides valuable insights into the distribution and trends of international climate finance, offering data support for climate finance policies and decision-making.

Scientific DataVol. 12(1)
State Key Joint Laboratory of Environment Simulation and Pollution Control (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 3%
Climate Change Policy and Economics
9.39
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