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Analysis of provincial CO2 emission peaking in China: Insights from production and consumption

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  • Guo, Xuepeng
  • Pang, Jun

Abstract

China has pledged to peak its carbon dioxide emissions by 2030, and the provincial governments have a common but differentiated responsibility for cutting emissions, depending on their conditions. Requiring all provinces to peak CO2 production-based emissions by 2030 may harm some regional economies because of the different industrial divisions in each Chinese province. In addition to production-based accounting (PBA), the study on the peaking of carbon emissions on consumption-based accounting (CBA) is a beneficial supplement to the research of PBA to comprehensively understand the basic situation and possible future paths of carbon emissions in all provinces in China. This research uses scenario analysis and the Monte Carlo simulation to simulate the CO2 path of Chinese provinces on production- and consumption-based accounting, which is based on China’s multi-regional input–output (MRIO) table in 2017 from the Chinese Emissions Accounts and DataSets (CEADs). This study finds that the provincial peaking time of CBA is 4–5 years later than that of PBA on average. Carbon transfer is the source of the difference in carbon emissions between PBA and CBA in different regions. We suggest that the government should pay attention to PBA and CBA when formulating policies. The region where PBA CO2 emissions reach peaking first should pay attention to the situation of CBA CO2 emissions, and the region where CBA CO2 emissions peak first should pay attention to the decline of PBA CO2 intensity. Finally, the government should encourage some developed net carbon import regions to provide transfer assistance of capital, technology, and talents to their carbon import regions to promote the scientific, fair, and efficient peaking of carbon emissions in provinces and the whole country.

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  • Guo, Xuepeng & Pang, Jun, 2023. "Analysis of provincial CO2 emission peaking in China: Insights from production and consumption," Applied Energy, Elsevier, vol. 331(C).
  • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922017032
    DOI: 10.1016/j.apenergy.2022.120446
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    1. Ding, Song & Zhang, Huahan, 2023. "Forecasting Chinese provincial CO2 emissions: A universal and robust new-information-based grey model," Energy Economics, Elsevier, vol. 121(C).

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