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Do anthropogenic and natural factors elevate the haze pollution in the South Asian countries? Evidence from long-term cointegration and VECM causality estimation

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Abstract

Anthropogenic and natural factors lead to substantial environmental degradation. This shift is aligned with the country's overall development, resulting in high demand for energy resources and a dramatic shift in human activities that contribute to haze pollution. Some of the countries in the South Asian region are ranked between one and twenty on the list of countries with the highest levels of PM2.5 pollution. The member countries have taken many steps to tackle global warming, but concern about haze pollution was found limited. Moreover, very little research was conducted on haze pollution, which led us to conduct this research in this region. This study used the panel data from 1998 to 2018 and a set of econometric models like long-term cointegrating relationship, fully modified ordinary least squares, and vector error-correction model Granger causality tests to examine the major drivers like anthropogenic and natural factors that might elevate haze pollution. Furthermore, our empirical results depict that (1) there is a long-term cointegrating relation between haze and the factors studied. (2) Energy consumption, urbanisation, and economic growth are the primary drivers of environmental degradation. (3) Rainfall has the most substantial influence on reducing haze pollution. The study concluded that (a) if the countries continue to develop at the same pace, all factors studied will continue to drive haze pollution to rise. (b) A decrease in PM2.5 pollution requires improvements in regional rainfall through vegetation, reducing reliance on fossil fuel-based energy sources, and increasing environmental education. (c) Slowing down the drive for urbanisation would not be cost-effective in reducing haze pollution in the region in the short run. Thus, reducing haze by adjusting the factors studied would not be easy in the short run and require the careful adoption of long-term policies.

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Data availability

The [monthly average temperature, total monthly rainfall] data that support the findings of this study are available at [WorldClim database], [https://www.worldclim.org/data/monthlywth.html]; the [yearly average PM2.5 concentration] data that support the findings of this study are availed from [Atmospheric Composition Analysis Group (ACA)], [http://fizz.phys.dal.ca/~atmos/martin/?page_ id = 140]; the other variable [economic growth, energy consumption, urbanisation, and education] data are available at [World Development Indicators], [https://databank.worldbank.org/reports.aspx?source=world-development-indicators].

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Funding

This study is supported by the Chinese Ministry of Education’s Humanities and Social Sciences program entitled “Research on the synergistic effect of carbon market mechanism design on carbon emission reduction and smog control.” [Grant No. 20YJA790082]; the National Social Science Foundation of China’s flagship program “Research on the maturity of China’s carbon market and environmental regulation policy” [grant number 14AZD051]; the National Natural Science Foundation of China “Modelling Carbon Price Drivers with Optimised Smart Methods” [grant number 71101133]; the Program for New Century Excellent Talents in University “Carbon finance innovation Research on the price formation mechanism of international carbon market” [grant number NCET-11–0725].

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Authors and Affiliations

  1. International Business School, Shaanxi Normal University, Xi’an, 710119, China

    Mohammad Musa, Lan Yi, Preethu Rahman, Muhammad Abu Sufyan Ali & Li Yang

  2. Jinhe Center for Economic Research, Xi’an Jiaotong University, Xi’an, 710049, China

    Lan Yi

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  1. Mohammad Musa
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  2. Lan Yi
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  3. Preethu Rahman
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  4. Muhammad Abu Sufyan Ali
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  5. Li Yang
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Contributions

MM: conceptualisation, methodology, software, data curation, writing—original draft, formal analysis visualisation. LY: supervision, guidance, writing—review and editing, project administration, resources, funding acquisition. PR: literature, data curation, and visualisation. MASA: review, editing and visualisation. LY: methodology, software and validation.

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Correspondence to Lan Yi.

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Table 7.

Table 7 Variance decomposition of seven variables for the panel
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Musa, M., Yi, L., Rahman, P. et al. Do anthropogenic and natural factors elevate the haze pollution in the South Asian countries? Evidence from long-term cointegration and VECM causality estimation. Environ Sci Pollut Res 29, 87361–87379 (2022). https://doi.org/10.1007/s11356-022-21759-w

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