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Accounting and Characteristics Analysis of CO2 Emissions in Chinese Cities

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  • Xingmin WANG

    (Institutes of Science and Development, Chinese Academy of Sciences, No. 15, ZhongGuanCun BeiYiTiao, Beijing 100190, China†University of Chinese Academy of Sciences, No. 19(A), Yuquan Road, Shijingshan District, Beijing 100049, China)

  • Jing WU

    (Institutes of Science and Development, Chinese Academy of Sciences, No. 15, ZhongGuanCun BeiYiTiao, Beijing 100190, China†University of Chinese Academy of Sciences, No. 19(A), Yuquan Road, Shijingshan District, Beijing 100049, China)

  • Zheng WANG

    (Institutes of Science and Development, Chinese Academy of Sciences, No. 15, ZhongGuanCun BeiYiTiao, Beijing 100190, China†University of Chinese Academy of Sciences, No. 19(A), Yuquan Road, Shijingshan District, Beijing 100049, China§Key Laboratory of Geographic Information Science, East China Normal University, NO. 500, Dongchuan Road, Minhang District, Shanghai 200062, P. R. China)

  • Xiaoting JIA

    (#x2020;University of Chinese Academy of Sciences, No. 19(A), Yuquan Road, Shijingshan District, Beijing 100049, China‡Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, No. 818, South Beijing Road, Urumqi Xinjiang 830011, China)

  • Bing BAI

    (Institutes of Science and Development, Chinese Academy of Sciences, No. 15, ZhongGuanCun BeiYiTiao, Beijing 100190, China†University of Chinese Academy of Sciences, No. 19(A), Yuquan Road, Shijingshan District, Beijing 100049, China)

Abstract

Accurate estimation of CO2 emissions is a prerequisite for scientific low-carbon emission policymaking. Based on 20 types of energy consumption data at the prefecture level in China, this paper re-estimates the CO2 emissions of 198 prefecture-level cities in 2016 by using the method of carbon emission coefficient. The spatial pattern and scale characteristics are analyzed, and the conclusions are as follows: (1) Overall, China’s urban CO2 emissions show a certain degree of spatial separation in terms of the total amount, per capita emissions, and emission intensity. Cities with the highest CO2 emissions in China are mainly concentrated in North China, East China and Chongqing, while cities with the highest per capita CO2 emissions and emission intensity are mainly concentrated in Northwest and North China. (2) Different types of cities have different CO2 emission characteristics. Resource-based cities have a higher total amount and emission intensity; tourism and underdeveloped cities both have lower values; while super-large-sized cities and many very-large-sized cities have higher CO2 emissions, but their emission intensities are usually lower; and no obvious rules are found in other cities. (3) Spatial analysis shows that cities with higher CO2 emissions are clustered. The Beijing–Tianjin–Hebei region, the Yangtze River Delta region, Shandong Province, and Shanxi–Henan–Anhui resource-producing areas are the agglomeration areas of high-emission cities. (4) Scale analysis shows that the characteristics of CO2 emissions at different scales are different. Provincial-level research can help to identify the environmental impact and total effect of carbon emissions, while urban-scale research is helpful to explore the diversity and phases of cities. Finally, based on the main conclusions of this study, the corresponding urban low-carbon policy implications are drawn.

Suggested Citation

  • Xingmin WANG & Jing WU & Zheng WANG & Xiaoting JIA & Bing BAI, 2020. "Accounting and Characteristics Analysis of CO2 Emissions in Chinese Cities," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-17, March.
  • Handle: RePEc:wsi:cjuesx:v:08:y:2020:i:01:n:s2345748120500049
    DOI: 10.1142/S2345748120500049
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    Citations

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    Cited by:

    1. Ye Duan & Juanjuan Zhong & Hongye Wang & Caizhi Sun, 2023. "Analysis of the Spatial and Temporal Evolution of Energy-Related CO 2 Emissions in China’s Coastal Areas and the Drivers of Industrial Enterprises above Designated Size—The Case of 82 Cities," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    2. Yajing Liu & Shuai Zhou & Ge Zhang, 2023. "Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(10), pages 1-24, May.

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