Can China Achieve Its Carbon Emission Peak Target? Empirical Evidence from City-Scale Driving Factors and Emission Reduction Strategies

Yuxue Zhang, Rui Wang (), Xingyuan Yang and He Zhang
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Yuxue Zhang: Department of Urban Planning, School of Architecture, Tianjin University, Tianjin 300072, China
Rui Wang: Department of Urban Planning, School of Architecture, Tianjin University, Tianjin 300072, China
Xingyuan Yang: Department of Urban Planning, School of Architecture, Tianjin University, Tianjin 300072, China
He Zhang: Department of Urban Planning, School of Architecture, Tianjin University, Tianjin 300072, China

Land, 2023, vol. 12, issue 6, 1-21

Abstract: The development of differentiated emission reduction strategies plays an important role in achieving carbon compliance targets. Each city should adopt carbon reduction strategies according to its carbon emission characteristics. China is a vast country, and there are significant differences between cities. Therefore, this study classifies 340 Chinese cities according to their carbon emission characteristics since 2020 and proposes differentiated emission reduction strategies accordingly. The results of the research show that Chinese cities can be divided into four categories, and they can strive to achieve their carbon peak targets by adopting differentiated emission reduction strategies. In the baseline scenario, Chinese cities will not be able to meet the peak carbon target by 2030. In the differentiated scenario, eco-agricultural cities, industry-led cities, and high-resource-availability cities will be able to achieve peak carbon by 2030. Unfortunately, resource-poor cities will not reach their peak. However, the extent to which their total carbon emissions contribute to the achievement of national goals is low, and their carbon emissions can be traded off for economic development by appropriately relaxing the constraints on carbon emissions. Therefore, in order to achieve China’s peak carbon goal, this study proposes emission reduction recommendations that should be adopted by different types of cities to form differentiated emission reduction strategies.

Keywords: STIRPAT model; k-means clustering algorithm; carbon peak; differentiated scenario setting; policy tool (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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