4.7 Article

Coal power demand and paths to peak carbon emissions in China: A provincial scenario analysis oriented by CO2-related health co-benefits

期刊

ENERGY
卷 282, 期 -, 页码 -

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2023.128830

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Coal power demand; Carbon peaking; Health co-benefits; CO2 emissions; Coal-fired power generation

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This study dynamically simulates the coal power demand and CO2 emissions in China's 29 provinces and evaluates the health co-benefits and economic losses related to CO2. The results show that coal power demand and CO2 emissions are continuously increasing, with the highest emissions in the eastern region. Emission reduction brings significant health co-benefits.
Coal power sector plays a significant role in achieving carbon peaking in China. Due to the regional heterogeneity of socioeconomic level, peaking carbon emissions in coal power sector depends on the performances of China's provinces. This study aims to dynamically simulate the coal power demand and subsequent CO2 emissions in China's 29 provinces during 2020-2035, and evaluate CO2-related health co-benefits in life and economic loss. It is quantitatively found that the total coal power demand kept rising by 5.19% per year during 2009-2019. And the projection demand would still increase, ranging from 4687.26 +/- 357.15 to 8897.13 +/- 326.28 billion kW.h at the baseline. CO2 emissions under the rapid development scenario are less than in the other two scenarios, valuing 76.96 billion tons during the projection period. Results of spatial heterogeneity show that East China contributes to the most significant CO2 emissions, valuing 149.47, 156.11, and 190.21 mg/m(3) of CO2 concentrations for 2020-2025, 2026-2030, and 2031-2035. Further, life and economic losses of CO2-related health impacts suggest significant health co-benefits of emission reduction. Our findings could provide a deeper understanding of potential peaking paths in coal power sector by provinces and assist policymakers in better establishing emissions reduction targets from a top-down perspective.

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