Chinese cities show different trend toward carbon peak
Science of The Total Environment, ISSN: 0048-9697, Vol: 934, Page: 173156
2024
- 6Citations
- 1Captures
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Article Description
Understanding the disparities in carbon emission trend among cities is critical for achieving carbon peak goal. However, the status and trends of carbon peaking and reduction in various city types are still unclear. Therefore, this study classified 315 Chinese cities according to their economic and industrial structure by SOM-K-means, aiming to evaluate the trends and dynamic drivers of carbon peaking progress in different city types. The findings reveal a decline in carbon emissions in 110 cities (34.9 %) since 2020. Notably, all city types show potential for carbon reduction and achieving carbon peaking. Specifically, resource-based cities and high-end service cities have the most effect on reducing emissions, with 48.4 % and 42.1 % of the cities declining in carbon emissions. Energy-based and heavy industrial cities face heightened pressure to reduce carbon emissions. Additionally, in high-end service cities, energy efficiency and investment intensity contribute to emission reduction, while industrial structure adjustment decrease carbon emissions in resource-based cities. Furthermore, enhancing energy efficiency effects and R&D intensity are effective ways to significantly reduce carbon emissions in heavy industrial cities. We conclude that differentiating carbon reduction pathways for different cities should constitute be a breakthrough in achieving the goal of carbon peaking. These insights provide recommendations for cities that have yet to reach their carbon peak for both China and other developing countries.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0048969724033035; http://dx.doi.org/10.1016/j.scitotenv.2024.173156; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85193528687&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/38763197; https://linkinghub.elsevier.com/retrieve/pii/S0048969724033035; https://dx.doi.org/10.1016/j.scitotenv.2024.173156
Elsevier BV
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