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Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model

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  • Xu, Bin
  • Lin, Boqiang

Abstract

China is now the world's largest carbon dioxide (CO2) emitter, and the government is under tremendous pressure to reduce CO2 emissions. The heavy industry sector is the largest contributor to the growth of CO2 emissions. Investigating the driving factors of this industry's CO2 emissions has important practical value. This paper applies the geographically weighted regression model to survey this industry's CO2 emissions. Empirical results show that urbanization exerts a heterogeneous impact on CO2 emissions across provinces and regions. This is mainly due to the differences in urban real estate and transportation infrastructure investments. Economic growth drives CO2 emissions, and this effect varies significantly by region and province on account of the differences in fixed-asset investment. It is more reasonable for local governments to develop emerging economies based on their specific conditions. Energy efficiency has the highest impact on CO2 emissions in the eastern region, because of the differences in R&D personnel investment and the number of patents granted. The energy consumption structure has the largest impact on CO2 emissions in the eastern region since it consumes more coal. Environmental regulations have a greater impact on CO2 emissions in the western region due to the differences in investment for industrial pollution control.

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  • Xu, Bin & Lin, Boqiang, 2021. "Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model," Energy Policy, Elsevier, vol. 149(C).
  • Handle: RePEc:eee:enepol:v:149:y:2021:i:c:s0301421520307229
    DOI: 10.1016/j.enpol.2020.112011
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    as
    1. Inglesi-Lotz, Roula, 2017. "Social rate of return to R&D on various energy technologies: Where should we invest more? A study of G7 countries," Energy Policy, Elsevier, vol. 101(C), pages 521-525.
    2. Kung, Chih-Chun & Zhang, Ning & Choi, Yongrok & Xiong, Kai & Yu, Jiangli, 2019. "Effectiveness of crop residuals in ethanol and pyrolysis-based electricity production: A stochastic analysis under uncertain climate impacts," Energy Policy, Elsevier, vol. 125(C), pages 267-276.
    3. Lin, Boqiang & Xu, Bin, 2018. "How to promote the growth of new energy industry at different stages?," Energy Policy, Elsevier, vol. 118(C), pages 390-403.
    4. Zhang, Chuanguo & Nian, Jiang, 2013. "Panel estimation for transport sector CO2 emissions and its affecting factors: A regional analysis in China," Energy Policy, Elsevier, vol. 63(C), pages 918-926.
    5. Liu, Kui & Bai, Hongkun & Yin, Shuo & Lin, Boqiang, 2018. "Factor substitution and decomposition of carbon intensity in China's heavy industry," Energy, Elsevier, vol. 145(C), pages 582-591.
    6. Zeng, Jingjing & Liu, Ting & Feiock, Richard & Li, Fei, 2019. "The impacts of China's provincial energy policies on major air pollutants: A spatial econometric analysis," Energy Policy, Elsevier, vol. 132(C), pages 392-403.
    7. Hui Li & Xianchun Tan & Jianxin Guo & Kaiwei Zhu & Chen Huang, 2019. "Study on an Implementation Scheme of Synergistic Emission Reduction of CO 2 and Air Pollutants in China’s Steel Industry," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    8. Xu, Bin & Lin, Boqiang, 2016. "Reducing CO2 emissions in China's manufacturing industry: Evidence from nonparametric additive regression models," Energy, Elsevier, vol. 101(C), pages 161-173.
    9. Zhang, Chuanguo & Lin, Yan, 2012. "Panel estimation for urbanization, energy consumption and CO2 emissions: A regional analysis in China," Energy Policy, Elsevier, vol. 49(C), pages 488-498.
    10. Cai, Wenjia & Wang, Can & Wang, Ke & Zhang, Ying & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's electricity sector," Energy Policy, Elsevier, vol. 35(12), pages 6445-6456, December.
    11. Zhao, Xiaoli & Ma, Qian & Yang, Rui, 2013. "Factors influencing CO2 emissions in China's power industry: Co-integration analysis," Energy Policy, Elsevier, vol. 57(C), pages 89-98.
    12. Cui, Lianbiao & Li, Rongjing & Song, Malin & Zhu, Lei, 2019. "Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments?," Energy Economics, Elsevier, vol. 83(C), pages 61-73.
    13. Song, Yi & Huang, Jian-Bai & Feng, Chao, 2018. "Decomposition of energy-related CO2 emissions in China's iron and steel industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 59(C), pages 103-116.
    14. Griffin, Paul W. & Hammond, Geoffrey P., 2019. "Industrial energy use and carbon emissions reduction in the iron and steel sector: A UK perspective," Applied Energy, Elsevier, vol. 249(C), pages 109-125.
    15. Lin, Boqiang & Xu, Mengmeng, 2018. "Regional differences on CO2 emission efficiency in metallurgical industry of China," Energy Policy, Elsevier, vol. 120(C), pages 302-311.
    16. Chang, Yen-Chiang & Wang, Nannan, 2010. "Environmental regulations and emissions trading in China," Energy Policy, Elsevier, vol. 38(7), pages 3356-3364, July.
    17. 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.
    18. Chen, Z.M. & Chen, G.Q., 2011. "Embodied carbon dioxide emission at supra-national scale: A coalition analysis for G7, BRIC, and the rest of the world," Energy Policy, Elsevier, vol. 39(5), pages 2899-2909, May.
    19. Li, Aijun & Zhang, Aizhen & Huang, Huijie & Yao, Xin, 2018. "Measuring unified efficiency of fossil fuel power plants across provinces in China: An analysis based on non-radial directional distance functions," Energy, Elsevier, vol. 152(C), pages 549-561.
    20. Chang, Chun-Ping & Wen, Jun & Dong, Minyi & Hao, Yu, 2018. "Does government ideology affect environmental pollutions? New evidence from instrumental variable quantile regression estimations," Energy Policy, Elsevier, vol. 113(C), pages 386-400.
    21. Ji, Qiang & Zhang, Dayong, 2019. "How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?," Energy Policy, Elsevier, vol. 128(C), pages 114-124.
    22. Lin, Boqiang & Xu, Bin, 2019. "How to effectively stabilize China's commodity price fluctuations?," Energy Economics, Elsevier, vol. 84(C).
    23. Wu, Haitao & Hao, Yu & Weng, Jia-Hsi, 2019. "How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models," Energy Policy, Elsevier, vol. 127(C), pages 24-38.
    24. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    25. Shang, Yizi & Hei, Pengfei & Lu, Shibao & Shang, Ling & Li, Xiaofei & Wei, Yongping & Jia, Dongdong & Jiang, Dong & Ye, Yuntao & Gong, Jiaguo & Lei, Xiaohui & Hao, Mengmeng & Qiu, Yaqin & Liu, Jiahong, 2018. "China’s energy-water nexus: Assessing water conservation synergies of the total coal consumption cap strategy until 2050," Applied Energy, Elsevier, vol. 210(C), pages 643-660.
    26. Xu, Bin & Lin, Boqiang, 2017. "Assessing CO2 emissions in China's iron and steel industry: A nonparametric additive regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 325-337.
    27. Wang, Shaojian & Zeng, Jingyuan & Liu, Xiaoping, 2019. "Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 140-150.
    28. Kung, Chih-Chun, 2019. "A stochastic evaluation of economic and environmental effects of Taiwan's biofuel development under climate change," Energy, Elsevier, vol. 167(C), pages 1051-1064.
    29. Zhu, Bangzhu & Jiang, Mingxing & He, Kaijian & Chevallier, Julien & Xie, Rui, 2018. "Allocating CO2 allowances to emitters in China: A multi-objective decision approach," Energy Policy, Elsevier, vol. 121(C), pages 441-451.
    30. Wang, Ke & Wang, Can & Lu, Xuedu & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's iron and steel industry," Energy Policy, Elsevier, vol. 35(4), pages 2320-2335, April.
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    9. Tianyi Zeng & Hong Jin & Zhifei Geng & Zihang Kang & Zichen Zhang, 2022. "The Effect of Urban Shrinkage on Carbon Dioxide Emissions Efficiency in Northeast China," IJERPH, MDPI, vol. 19(9), pages 1-18, May.
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    11. Xu, Bin & Luo, Yuemei & Xu, Renjing & Chen, Jianbao, 2021. "Exploring the driving forces of distributed energy resources in China: Using a semiparametric regression model," Energy, Elsevier, vol. 236(C).
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