Sulfur dioxide (SO2) emission reduction and its spatial spillover effect in high-tech industries: based on panel data from 30 provinces in China

Abstract

Industrial sulfur dioxide (SO2) has become an important source of environmental pollution in China, and the regional SO2 emission reduction capacity is a comprehensive reflection of cleaner production capacity, environmental regulation, and economic development. It is obvious that high-tech industries play a crucial role in promoting the cleaner production capacity of the whole industry. Simultaneously, only considering the regional emission and the development of high-tech industry in isolation may deviate from actual economic characteristics. Therefore, by using the panel data of 30 provinces in China from 2005 to 2016, this paper adopts spatial autoregression model (SAR), spatial error model (SEM), and spatial Durbin model (SDM) to analyze the effect of the high-tech industry development on SO2 emission reduction under the spatial adjacency matrix (W1), geographic distance matrix (W2), and economic distance matrix (W3). In addition, this paper selects three indicators, which is SO2 removal rate, SO2 emission, and SO2 removal quantity, as explanatory variables, and R&D investment and number of enterprises in high-tech industry are selected to represent the industrial development level. The major conclusions are as follows: (1) The ability of SO2 emission reduction in the local province is significantly affected by the surrounding provinces, showing the agglomeration characteristics of “high-high” or “low-low.” (2) The R&D investment of high-tech industry has a negative impact on SO2 removal rate and SO2 removal quantity, but a positive effect on the SO2 emissions for the local province, and has a positive effect on the emission reduction of surrounding provinces. (3) The expansion of high-tech industry has significantly improved the SO2 emission reduction capacity of the local province and its surrounding provinces. The robustness test supports the empirical conclusions of this paper. Finally, this paper puts forward some policy suggestions for government in environmental governance, such as “joint prevention and control” and the promotion of cleaner production.

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Data availability

The data that support the findings of this study are available from [www.cnki.net] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [www.cnki.net].

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Funding

Financial support was provided by the “Young Innovative Talents” program of Harbin University of Commerce [2019CX16] and the graduate innovation project of Harbin University of Commerce [YJSCX2020-647HSD].

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Authors

Contributions

LYL provides the research route, theoretical analysis, and important contribute for the subsequent revision and language of the manuscript. JL is mainly responsible for data collection and collation, empirical analysis, and writing of the first draft of the manuscript. SZ provides software operation guidance and manuscript modification. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shen Zhong.

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This study involves the macro data of human economy and society. All the data are from the official statistical yearbook. The data collection process is in line with the ethical and moral standards. The research method of this study is spatial econometric method, and there is no need for ethical approval and animal experiment content. The author guarantees that the process, content and conclusion of this study do not violate the theory and moral principles.

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Highlights

1. Adopts three indicators to comprehensively reflect the regional SO2 emission reduction capacity, namely, SO2 emissions, SO2 removal quantity, and SO2 removal rate.

2. R&D of high-tech shows negative influence on SO2 emission reduction of the province but a positive spillover effect on SO2 emission

3. Expansion of high-tech shows positive influence on SO2 emission reduction both the province and surrounding areas.

Responsible editor: Philippe Garrigues

Appendix

Appendix

Table 10 Regression results under SAR
Table 11 Regression results under SEM
Table 12 Direct, indirect, and total effect under W1 and W2

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Lou, L., Li, J. & Zhong, S. Sulfur dioxide (SO2) emission reduction and its spatial spillover effect in high-tech industries: based on panel data from 30 provinces in China. Environ Sci Pollut Res (2021). https://doi.org/10.1007/s11356-021-12755-7

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Keywords

  • Sulfur dioxide emission reduction
  • High-tech industry
  • Spatial econometric model
  • China