Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China

This study first attempts to use the parameterized quadratic directional distance function (DDF) approach to calculate China’s provincial carbon abatement cost and carbon reduction potential (CRP) under different scenarios from 2000 to 2017. Afterward, considering three different scenarios, we analy...

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Veröffentlicht in:Environmental science and pollution research international 2021-11, Vol.28 (42), p.59925-59944
Hauptverfasser: Li, Zhangwen, Zhang, Caijiang, Zhou, Yu
Format: Artikel
Sprache:eng
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Zusammenfassung:This study first attempts to use the parameterized quadratic directional distance function (DDF) approach to calculate China’s provincial carbon abatement cost and carbon reduction potential (CRP) under different scenarios from 2000 to 2017. Afterward, considering three different scenarios, we analyze the spatio-temporal characteristics and the dynamic evolution pattern of CRP. We also employ spatial Durbin model (SDM) to investigate the influencing factors of CRP. The results are obtained as follows: (1) CRP across the three scenarios varies considerably across provinces and different-located groups. CRP higher areas are mainly located in the economically developed eastern coastal regions, while most provinces with low CRP are concentrated in the western region. (2) Provinces with a similar CRP showed a significant geographic agglomeration, and the agglomeration effect was strengthened first and then weakened. Simultaneously, the local spatial distribution of moderation carbon reduction potential (MCRP), fairness carbon reduction potential (FCRP), and efficiency carbon reduction potential (ECRP) shows a slight spatial polarization feature. (3) Through the SDM analysis and spillover effect decomposition, we find that improvement of regional CRP not only depends on economic development, industrial structure adjustment, and energy efficiency elevation, but also involves energy structure optimization, low-carbon innovation, and population. The low-carbon innovation provides critical support for local CRP under the efficiency scenario but restrains the local CRP under the fairness scenario. Therefore, the central government should emphasize local conditions and the ex-ante scenario assessment, strengthen regional interactive governance, optimize energy efficiency, and promote the application of clean energy to enhance CRP.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-021-14913-3