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Spatial and Temporal Distribution and the Driving Factors of Carbon Emissions from Urban Production Energy Consumption

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  • Liyuan Fu

    (School of Economics, Liaoning University, Shenyang 110036, China)

  • Qing Wang

    (School of Economics, Liaoning University, Shenyang 110036, China)

Abstract

Urban production energy consumption produces a large amount of carbon emissions, which is an important source of global warming. This study measures the quantity and intensity of carbon emissions in 30 provinces of China based on urban production energy consumption from 2005–2019, and uses the Dagum Gini coefficient, kernel density estimation, carbon emission classification and spatial econometric model to analyze the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions from China and regional production energy consumption. It was found that the growth rate of carbon emission quantity and carbon emission intensity of production energy consumption decreased year by year in each province during the study period. The imbalance of carbon emission was strong, with different degrees of increase and decrease, and there were big differences between eastern and western regions. The classification of carbon emissions differed among provinces and there was heterogeneity among regions. The quantity and intensity of carbon emissions of production energy consumption qwre affected by multiple factors, such as industrial structure. This study provides an in-depth comparison of the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions of production energy consumption across the country and regions, and provides targeted policies for carbon emission reduction across the country and regions, so as to help achieve China’s “double carbon” target quickly and effectively.

Suggested Citation

  • Liyuan Fu & Qing Wang, 2022. "Spatial and Temporal Distribution and the Driving Factors of Carbon Emissions from Urban Production Energy Consumption," IJERPH, MDPI, vol. 19(19), pages 1-29, September.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12441-:d:929475
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    as
    1. Zhifu Mi & Jiali Zheng & Jing Meng & Jiamin Ou & Klaus Hubacek & Zhu Liu & D’Maris Coffman & Nicholas Stern & Sai Liang & Yi-Ming Wei, 2020. "Economic development and converging household carbon footprints in China," Nature Sustainability, Nature, vol. 3(7), pages 529-537, July.
    2. Qin Tang & Zhi-An Ren & Kang-Feng Zhu & Nai-Ru Xu & Shaohui Wang, 2021. "Research on the Impact of Chinese Total Factor Productivity on the Modern Economic System Based on the Spatial Dubin Model," Complexity, Hindawi, vol. 2021, pages 1-14, August.
    3. Wang, Zheng & Zhu, Yanshuo & Zhu, Yongbin & Shi, Ying, 2016. "Energy structure change and carbon emission trends in China," Energy, Elsevier, vol. 115(P1), pages 369-377.
    4. Huang, Junbing & Xiang, Shiqi & Wang, Yajun & Chen, Xiang, 2021. "Energy-saving R&D and carbon intensity in China," Energy Economics, Elsevier, vol. 98(C).
    5. Linna Chen & Shiyi Chen, 2015. "The Estimation of Environmental Kuznets Curve in China: Nonparametric Panel Approach," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 405-420, October.
    6. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    7. Wang, Qiang & Wu, Shi-dai & Zeng, Yue-e & Wu, Bo-wei, 2016. "Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1563-1579.
    8. Dingbang, Cang & Cang, Chen & Qing, Chen & Lili, Sui & Caiyun, Cui, 2021. "Does new energy consumption conducive to controlling fossil energy consumption and carbon emissions?-Evidence from China," Resources Policy, Elsevier, vol. 74(C).
    9. Ruimin Yin & Zhanqi Wang & Ji Chai & Yunxiao Gao & Feng Xu, 2022. "The Evolution and Response of Space Utilization Efficiency and Carbon Emissions: A Comparative Analysis of Spaces and Regions," Land, MDPI, vol. 11(3), pages 1-21, March.
    10. Xu, Bin & Lin, Boqiang, 2015. "How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models," Energy Economics, Elsevier, vol. 48(C), pages 188-202.
    11. Shi, Huiting & Chai, Jian & Lu, Quanying & Zheng, Jiali & Wang, Shouyang, 2022. "The impact of China's low-carbon transition on economy, society and energy in 2030 based on CO2 emissions drivers," Energy, Elsevier, vol. 239(PD).
    12. Zhixiong Tan & Mansoor Ahmed Koondhar & Kishwar Nawaz & Muhammad Nasir Malik & Zaid Ashiq Khan & Masroor Ali Koondhar, 2021. "Foreign direct investment, financial development, energy consumption, and air quality: A way for carbon neutrality in China," Post-Print hal-03558093, HAL.
    13. Huiqiang Ma & Jiale Liu & Jianchao Xi, 2022. "Decoupling and decomposition analysis of carbon emissions in Beijing’s tourism traffic," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5258-5274, April.
    14. Duan, Haiyan & Chen, Siyan & Song, Junnian, 2022. "Characterizing regional building energy consumption under joint climatic and socioeconomic impacts," Energy, Elsevier, vol. 245(C).
    15. Tang, Xu & Snowden, Simon & McLellan, Benjamin C. & Höök, Mikael, 2015. "Clean coal use in China: Challenges and policy implications," Energy Policy, Elsevier, vol. 87(C), pages 517-523.
    16. Wen Guo & Tao Sun & Hongjun Dai, 2016. "Effect of Population Structure Change on Carbon Emission in China," Sustainability, MDPI, vol. 8(3), pages 1-20, March.
    17. Pengnan Xiao & Yuan Zhang & Peng Qian & Mengyao Lu & Zupeng Yu & Jie Xu & Chong Zhao & Huilin Qian, 2022. "Spatiotemporal Characteristics, Decoupling Effect and Driving Factors of Carbon Emission from Cultivated Land Utilization in Hubei Province," IJERPH, MDPI, vol. 19(15), pages 1-32, July.
    18. Liangen Zeng & Chengming Li & Zhongqi Liang & Xuhai Zhao & Haoyu Hu & Xiao Wang & Dandan Yuan & Zhao Yu & Tingzhang Yang & Jingming Lu & Qi Huang & Fuyao Qu, 2022. "The Carbon Emission Intensity of Industrial Land in China: Spatiotemporal Characteristics and Driving Factors," Land, MDPI, vol. 11(8), pages 1-19, July.
    19. Wang, Shaojian & Fang, Chuanglin & Wang, Yang, 2016. "Spatiotemporal variations of energy-related CO2 emissions in China and its influencing factors: An empirical analysis based on provincial panel data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 505-515.
    20. Donglan, Zha & Dequn, Zhou & Peng, Zhou, 2010. "Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis," Energy Policy, Elsevier, vol. 38(7), pages 3377-3383, July.
    21. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2018. "Industrial structure, technical progress and carbon intensity in China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2935-2946.
    22. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    23. Tang, Bao-Jun & Li, Ru & Li, Xiao-Yi & Chen, Hao, 2017. "An optimal production planning model of coal-fired power industry in China: Considering the process of closing down inefficient units and developing CCS technologies," Applied Energy, Elsevier, vol. 206(C), pages 519-530.
    24. He, Weijun & Chen, Hao, 2022. "Will China's provincial per capita energy consumption converge to a common level over 1990–2017? Evidence from a club convergence approach," Energy, Elsevier, vol. 249(C).
    25. Liu, Yisheng & Yang, Meng & Cheng, Feiyu & Tian, Jinzhao & Du, Zhuoqun & Song, Pengbo, 2022. "Analysis of regional differences and decomposition of carbon emissions in China based on generalized divisia index method," Energy, Elsevier, vol. 256(C).
    26. Li, Wei & Sun, Wen & Li, Guomin & Jin, Baihui & Wu, Wen & Cui, Pengfei & Zhao, Guohao, 2018. "Transmission mechanism between energy prices and carbon emissions using geographically weighted regression," Energy Policy, Elsevier, vol. 115(C), pages 434-442.
    27. Tian Ma & Yisheng Liu & Meng Yang, 2022. "Spatial-Temporal Heterogeneity for Commercial Building Carbon Emissions in China: Based the Dagum Gini Coefficient," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    28. Jiancheng Qin & Lei Gao & Weihu Tu & Jing He & Jingzhe Tang & Shuying Ma & Xiaoyang Zhao & Xingzhe Zhu & Karthikeyan Brindha & Hui Tao, 2022. "Decomposition and Decoupling Analysis of Carbon Emissions in Xinjiang Energy Base, China," Energies, MDPI, vol. 15(15), pages 1-18, July.
    29. Chao-Qun Ma & Jiang-Long Liu & Yi-Shuai Ren & Yong Jiang, 2019. "The Impact of Economic Growth, FDI and Energy Intensity on China’s Manufacturing Industry’s CO 2 Emissions: An Empirical Study Based on the Fixed-Effect Panel Quantile Regression Model," Energies, MDPI, vol. 12(24), pages 1-16, December.
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    Cited by:

    1. Heping Li & Tao Lin, 2022. "Do Land Use Structure Changes Impact Regional Carbon Emissions? A Spatial Econometric Study in Sichuan Basin, China," IJERPH, MDPI, vol. 19(20), pages 1-17, October.
    2. Dan Wang & Yan Liu & Yu Cheng, 2023. "Effects and Spatial Spillover of Manufacturing Agglomeration on Carbon Emissions in the Yellow River Basin, China," Sustainability, MDPI, vol. 15(12), pages 1-18, June.

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