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作者:

Li, Yunyan (Li, Yunyan.) | Dai, Jian (Dai, Jian.) | Zhao, Han (Zhao, Han.)

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Scopus SCIE

摘要:

The Chinese government has explicitly promised to peak carbon dioxide emissions by 2030 and strive to become carbon neutral by 2060. As the capital of China, Beijing should play a pilot role in reducing carbon emissions. Researching on the synergistic effect of air pollutants and carbon dioxide emissions reduction can be conducive to the reduction of carbon and pollution, and ultimately promote economic growth and enhance environmental management. Based on the extended Kaya identity and the gray correlation model, this study analyzes the correlation degree of the influencing factors of collaborative emission reduction. The Logarithmic Mean Divisia Index method (LMDI model) is conducted to decompose the driving effects and quantify the collaborative emission reduction effects of main air pollutants and carbon dioxide in Beijing. The results showed a strong correlation (correlation coefficient > 0.6) between carbon dioxide and major air pollution. The energy intensity and energy structure are the main factors to promote the major air pollutants emission reduction in Beijing, while the economic output and population size increase the air pollutant emissions. The average CO2 contribution rate to SO2, NOx, and PM10 from 2010 to 2019 was 9.60, 5.99 and 9.06%, respectively. In general, there is a significant connection between CO2 emissions and the main air pollutants. However, the synergistic emission reduction effect of CO2 and SO2 is greater than that of CO2 and NOx, and CO2 and PM10. Finally, this paper proposes several countermeasures and suggestions for front-end prevention, middle-end control, and collaborative emission reduction based on the findings. [GRAPHICS]

关键词:

Kaya identity Carbon neutral LMDI model Air pollutions Carbon dioxide emissions

作者机构:

  • [ 1 ] [Li, Yunyan]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 2 ] [Dai, Jian]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 3 ] [Zhao, Han]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China

通讯作者信息:

  • [Dai, Jian]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China;;

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来源 :

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY

ISSN: 1618-954X

年份: 2023

4 . 3 0 0

JCR@2022

ESI学科: ENVIRONMENT/ECOLOGY;

ESI高被引阀值:17

被引次数:

WoS核心集被引频次:

SCOPUS被引频次: 9

ESI高被引论文在榜: 0 展开所有

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