Environmental Kuznets curve for PM2.5 emissions in Beijing, China: What role can natural gas consumption play?

Kangyin Dong*, Renjin Sun, Cong Dong, Hui Li, Xiangang Zeng, Guohua Ni

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    75 Citations (Scopus)

    Abstract

    Beijing has been the fastest-growing megacity in China, however it faced severe air pollution in recent years, particularly the notorious fine particulate matter (PM2.5). In response, Beijing increased the use of natural gas since 2008; therefore, natural gas consumption (NGC) soared rapidly, accounting for over 30% of total energy need in 2016. This study explores the long- and short-run effects of NGC on PM2.5 emissions within the framework of the environmental Kuznets curve (EKC) in Beijing by employing the autoregressive distributed lag (ARDL) approach. To do this, the long-term and monthly PM2.5 data based on ground monitoring are used for the period of April 2008 through December 2016 (2008 M04-2016 M12). The empirical results suggest, in the long run, an inverted U-shaped EKC link exists between PM2.5 emissions and per capita gross domestic product (GDP); with 16,973 yuan for per capita monthly GDP, the EKC will reach its peak. Although the NGC in Beijing can mitigate PM2.5 emissions in both the long run and short run, its mitigation effect would be weakened over time. Furthermore, increasing vehicle quantity would lead to higher concentrations of PM2.5, whereas the proportion of tertiary industry exerts a negative effect on PM2.5 in Beijing. At the end of the article, several key policy implications are highlighted both for mitigating PM2.5 and for promoting growth in natural gas industry in Beijing.

    Original languageEnglish
    Pages (from-to)591-601
    Number of pages11
    JournalEcological Indicators
    Volume93
    DOIs
    Publication statusPublished - Oct 2018

    Keywords

    • Beijing
    • Driving forces
    • Environmental Kuznets curve
    • Natural gas consumption
    • PM emissions

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