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Spatial Pattern and Spillover of Abatement Effect of Chinese Environmental Protection Tax Law on PM 2.5 Pollution

Author

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  • Fei Han

    (School of Economics, Shanxi University of Finance and Economics, 696 Wucheng Road, Taiyuan 030006, China)

  • Junming Li

    (School of Statistics, Shanxi University of Finance and Economics, 696 Wucheng Road, Taiyuan 030006, China)

Abstract

Particulate matter ( P M 2.5 ) pollution is a threat to public health, and environmental taxation is an important regulatory mode controlling P M 2.5 pollution. In 2018, China implemented the Environmental Protection Tax Law (EPTL) targeting P M 2.5 pollution. Based on in-situ monitoring and emission inventory data, a Bayesian hierarchical spatiotemporal model combining a two-period trends difference method was employed to measure the abatement effects of China’s EPTL on P M 2.5 pollution (AEEPTLPM). On this basis, a spatial spillover index (SSI) of the AEEPTLPM is proposed. Applying this index, we calculated the spatial spillover characteristics of the AEEPTLPM in mainland China at a provincial scale in 2018–2019. The results show that the EPTL has had significant abatement effects on both in-situ-monitored P M 2.5 concentrations and local total industrial P M 2.5 emissions. Additionally, the two types of AEEPTLPM display distinct spatial heterogeneity. A correlation between the AEEPTLPM and the degree of P M 2.5 pollution was observed; areas with serious P M 2.5 pollution have higher AEEPTLPM levels, and vice versa. The SSI indicates that the AEEPTLPM exhibits significant spatial spillover characteristics, and spatial heterogeneity is also present.

Suggested Citation

  • Fei Han & Junming Li, 2022. "Spatial Pattern and Spillover of Abatement Effect of Chinese Environmental Protection Tax Law on PM 2.5 Pollution," IJERPH, MDPI, vol. 19(3), pages 1-16, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1440-:d:736127
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    1. Hongbin Dai & Guangqiu Huang & Jingjing Wang & Huibin Zeng & Fangyu Zhou, 2022. "Spatio-Temporal Characteristics of PM 2.5 Concentrations in China Based on Multiple Sources of Data and LUR-GBM during 2016–2021," IJERPH, MDPI, vol. 19(10), pages 1-20, May.

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