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Synergistic action on mitigation and adaptation pilot policies to enhance low-carbon resilience of Chinese cities

Nature Cities volume 2, pages 812–824 (2025)Cite this article

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Abstract

Mitigation and adaptation strategies are recognized as effective means to enhance urban resilience against climate change; however, their combined effects at the urban level are less studied. Here we investigate the synergistic impacts of low-carbon and climate-resilient pilot policies on urban resilience, using panel data from 286 Chinese cities (2005–2022). The findings indicate that dual-pilot policies significantly enhance the low-carbon resilience of pilot cities, outperforming single-pilot policies. The effectiveness of these policies exhibits variation across different city categories: cities subjected to extreme weather and high disaster risks demonstrate more pronounced benefits, whereas medium ecological and economic low-carbon resilience, high social low-carbon resilience and medium institutional low-carbon resilience (MMHM) cities show consistent effects and low ecological, economic, social and institutional low-carbon resilience (LLLL) cities exhibit varied responses. Furthermore, green technology innovation, human capital development and communication infrastructure are critical to improving policy effectiveness. The diversity and integration of policy instruments, along with the multidimensionality and synergy of policy objectives, are essential for effective climate action. It is recommended that cities integrate both mitigation and adaptation strategies to optimize synergies and bolster urban resilience.

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Fig. 1: A coordinated analysis framework for urban climate change mitigation and adaptation.
Fig. 2: Analytical map of policy implications of climate resilience in different dual-pilot cities and their climate mitigation and adaptation policies.
Fig. 3: Climate mitigation and adaptation policy analysis of dual and single-pilot cities.

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Data availability

The economic, social and ecological data for Chinese cities were initially sourced from the following: (1) The China Urban Statistical Yearbook, China Urban Construction Statistical Yearbook, China Regional Economic Statistical Yearbook and China Meteorological Disaster Yearbook from various years. These yearbooks are available on the China Economic and Social Big Data Research Platform (https://data.cnki.net/). (2) The statistical yearbooks of various provinces and cities in China, as well as the official websites of city governments in China. These can be accessed through the official websites of the statistical bureaus and governments of the respective provinces and cities in China. (3) The weather data for Chinese cities were initially obtained from the National Qinghai-Tibet Plateau Science Data Center (https://data.tpdc.ac.cn/home) and the Resources and Environment Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/). The result table includes the extended dataset Source Data Figure 2, and Table 1 and Table 2 in the main text. Other data can be provided by the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

The algorithm version used for performing DML analysis is available via GitHub at https://github.com/py-why/EconML.

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Acknowledgements

This work was supported by the Humanities and Social Sciences Youth Foundation, Ministry of Education (no. 22YJC790120 to D.W.) and the National Social Science Fund of China (no. 22VMG016 to D.W.).

Author information

Authors and Affiliations

  1. School of Government, Peking University, Beijing, China

    Di Wang

  2. Institute of Public Governance, Peking University, Beijing, China

    Di Wang

  3. School of Management, Beijing Institute of Technology, Beijing, China

    Shiwei Chen

Authors
  1. Di Wang
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  2. Shiwei Chen
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Contributions

Conceptualization: D.W. Resources: D.W. Project administration: D.W. Methodology: D.W. and S.C. Writing—original draft: S.C. Visualization: S.C. Writing—review and editing: D.W. and S.C. Supervision: D.W. Funding acquisition: D.W.

Corresponding authors

Correspondence to Di Wang or Shiwei Chen.

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The authors declare no competing interests.

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Peer review information

Nature Cities thanks Bin Su and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–7, Discussion and Tables 1–4.

Reporting Summary

Source data

Source Data Fig. 2

The policy effects of the dual-pilot policy.

Source Data Table 1

The detailed results of the policy regression.

Source Data Table 2

The detailed results of the moderating effects.

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Wang, D., Chen, S. Synergistic action on mitigation and adaptation pilot policies to enhance low-carbon resilience of Chinese cities. Nat Cities 2, 812–824 (2025). https://doi.org/10.1038/s44284-025-00303-0

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