PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism

Chen, Jibo; Chen, Keyao; Wang, Guizhi; Wu, Lingyan; Liu, Xiaodong; Wei, Guo

Abstract

In this paper, a vector autoregression (VAR) model has been constructed in order to analyze a two-way mechanism between PM2.5 pollution and industry development in Beijing via the combination of an impulse response function and variance decomposition. According to the results, long-term equilibrium interconnection was found between PM2.5 pollution and the development of primary, secondary, and tertiary industries. One-way Granger causalities were found in the three types of industries shown to contribute to PM2.5 pollution, though the three industries showed different scales of influences on the PM2.5 pollution that varied for about 1–2 years. The development of the primary and secondary industries increased the emission of PM2.5, but the tertiary industry had an inhibitory effect. In addition, PM2.5 pollution had a certain inhibitory effect on the development of the primary and secondary industries, but the inhibition of the tertiary industry was not significant. Therefore, the development of the tertiary industry can contribute the most to the reduction of PM2.5 pollution. Based on these findings, policy-making recommendations can be proposed regarding upcoming pollution prevention strategies.

Citation

Chen, J., Chen, K., Wang, G., Wu, L., Liu, X., & Wei, G. (2019). PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism. International Journal of Environmental Research and Public Health, 16(7), Article 1159. https://doi.org/10.3390/ijerph16071159

• Journal Article Type: Article
• Acceptance Date: Mar 28, 2019
• Online Publication Date: Mar 31, 2019
• Publication Date: Mar 31, 2019
• Deposit Date: May 31, 2019
• Publicly Available Date: Jun 7, 2019
• Journal: International Journal of Environmental Research and Public Health
• Electronic ISSN: 1660-4601
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 7
• Article Number: 1159
• DOI: https://doi.org/10.3390/ijerph16071159
• Keywords: Haze pollution; vector autoregression model; impulse response function; variance decomposition; industry development
• Public URL: http://researchrepository.napier.ac.uk/Output/1843259
• Contract Date: May 31, 2019