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ClimActor 2.0: A spatialized database of subnational climate pledges and emissions data
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  • Published: 02 May 2026

ClimActor 2.0: A spatialized database of subnational climate pledges and emissions data

  • Diego Manya1,
  • Katherine Burley Farr1,2,
  • Elizabeth Brown1,2,
  • Andrew Martin1 &
  • …
  • Angel Hsu1,2 

Scientific Data (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

ClimActor 2.0 is an open, spatialized database that compiles climate targets, action plans, and self-reported emission inventories from subnational governments, including cities, municipalities, states and regions, worldwide. The dataset provides standardized administrative boundaries for each entity, enabling direct linkage to geospatial data such as population, GDP, land cover, and other globally-gridded datasets. Each record is anchored to a unique identifier that connects decision-making authorities to their corresponding geometries. The database integrates information from 14 major climate disclosure platforms and reporting initiatives, complemented with a few national-level datasets. In total, ClimActor includes over 15,000 entities that participate in a national or transnational climate initiative, of which more than 10,000 of these entities have adopted either a climate mitigation target or plan. In addition to the harmonized spatial boundaries, ClimActor 2.0 provides four harmonized core datasets: aggregated emissions, sectoral emissions, climate targets, and climate plans, in addition to network participation data. Users can utilize the data as a standalone dataset or as an open-source R statistical computing software package, which includes a set of cleaning and matching functions that allow users to easily combine other datasets with ClimActor 2.0 for a wide range of subnational climate action analyses.

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Acknowledgements

We want to thank Izzy Bukovnik, Emma Holmes, Cameron Kaplinger, Ying Yu and Xuewei Wang for their contributions in data collection and matching for selected countries This work was supported by a grant from the IKEA Foundation and the National Science Foundation (Grant 2216592) both to A. Hsu.

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Authors and Affiliations

  1. Data-Driven EnviroLab, UNC Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27516, USA

    Diego Manya, Katherine Burley Farr, Elizabeth Brown, Andrew Martin & Angel Hsu

  2. Department of Public Policy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27516, USA

    Katherine Burley Farr, Elizabeth Brown & Angel Hsu

Authors
  1. Diego Manya
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  2. Katherine Burley Farr
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  3. Elizabeth Brown
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  4. Andrew Martin
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  5. Angel Hsu
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Corresponding author

Correspondence to Angel Hsu.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Manya, D., Burley Farr, K., Brown, E. et al. ClimActor 2.0: A spatialized database of subnational climate pledges and emissions data. Sci Data (2026). https://doi.org/10.1038/s41597-026-07288-y

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  • Received: 30 October 2025

  • Accepted: 15 April 2026

  • Published: 02 May 2026

  • DOI: https://doi.org/10.1038/s41597-026-07288-y

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