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Regional disparity and cost-effective SO2 pollution control in China: A case study in 5 mega-cities

Author

Listed:
  • Kanada, Momoe
  • Dong, Liang
  • Fujita, Tsuyoshi
  • Fujii, Minoru
  • Inoue, Tsuyoshi
  • Hirano, Yujiro
  • Togawa, Takuya
  • Geng, Yong

Abstract

With rapid development, increasing sulfur dioxide (SO2) emission becomes a key environmental issue in China. To respond to this challenge, the Chinese government established a top-down scheme to reduce its SO2 emissions. However, regional disparity and the associated cost differences brought uncertainties to the policy effectiveness and efficiency. Few studies focus on this field. Therefore, this study tries to fill such a gap by investigating the differences of SO2 emissions, reduction potential, and cost-effectiveness through use of the GAINS-China model in five mega-cities in China, namely, Beijing, Shanghai, Tianjin, Chongqing, and Hong Kong. A scenario analysis approach is employed, focusing on two technologies named flue gas desulfurization (FGD) and limestone injection (LINJ). Results demonstrated that a large SO2 reduction potential exists, as well as a great disparity, among the five mega-cities. Chongqing had the largest reduction potential with lowest unit cost, while Beijng and Hong Kong showed the lowest reduction potential with higher unit cost. In Beijing and Shanghai, FGD and LINJ in the power generation sector had the larger reduction potential with the highest cost-effectiveness. However, in Chongqing, the industry sectors also had large reduction potentials. Finally, appropriate SO2 control strategies and policies are raised by considering the local realities.

Suggested Citation

  • Kanada, Momoe & Dong, Liang & Fujita, Tsuyoshi & Fujii, Minoru & Inoue, Tsuyoshi & Hirano, Yujiro & Togawa, Takuya & Geng, Yong, 2013. "Regional disparity and cost-effective SO2 pollution control in China: A case study in 5 mega-cities," Energy Policy, Elsevier, vol. 61(C), pages 1322-1331.
  • Handle: RePEc:eee:enepol:v:61:y:2013:i:c:p:1322-1331
    DOI: 10.1016/j.enpol.2013.05.105
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    References listed on IDEAS

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    7. Tan, Feifei & Lu, Zhaohua, 2015. "Current status and future choices of regional sectors-energy-related CO2 emissions: The third economic growth pole of China," Applied Energy, Elsevier, vol. 159(C), pages 237-251.
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    9. Zhang, Bo & Qiao, H. & Chen, B., 2015. "Embodied energy uses by China’s four municipalities: A study based on multi-regional input–output model," Ecological Modelling, Elsevier, vol. 318(C), pages 138-149.
    10. Tian, Xu & Geng, Yong & Viglia, Silvio & Bleischwitz, Raimund & Buonocore, Elvira & Ulgiati, Sergio, 2017. "Regional disparities in the Chinese economy. An emergy evaluation of provincial international trade," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 1-11.
    11. Yang, Hang & Zhang, Yongxin & Zheng, Chenghang & Wu, Xuecheng & Chen, Linghong & Fu, Joshua S. & Gao, Xiang, 2018. "Cost estimate of the multi-pollutant abatement in coal-fired power sector in China," Energy, Elsevier, vol. 161(C), pages 523-535.
    12. Zeng, Shihong & Jiang, Xue & Su, Bin & Nan, Xin, 2018. "China's SO2 shadow prices and environmental technical efficiency at the province level," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 86-102.
    13. Yue, Hui & Worrell, Ernst & Crijns-Graus, Wina, 2021. "Impacts of regional industrial electricity savings on the development of future coal capacity per electricity grid and related air pollution emissions – A case study for China," Applied Energy, Elsevier, vol. 282(PB).
    14. Liu, Chang & Hong, Tao & Li, Huaifeng & Wang, Lili, 2018. "From club convergence of per capita industrial pollutant emissions to industrial transfer effects: An empirical study across 285 cities in China," Energy Policy, Elsevier, vol. 121(C), pages 300-313.
    15. Jie Zhang & Zhencheng Xing & Jigan Wang, 2016. "Analysis of CO 2 Emission Performance and Abatement Potential for Municipal Industrial Sectors in Jiangsu, China," Sustainability, MDPI, vol. 8(7), pages 1-15, July.

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