The Impact of Socioeconomic and Meteorological Factors on PM2.5 Concentrations in the United States: An ARDL Bounds Testing Approach

Document Type : Research Paper

Authors

1 Department of Economics and quantitative methods, Institut Supérieur de Gestion, Université de Tunis, Tunisia

2 Department of Economics and quantitative methods, Institut Supérieur de Gestion, Université de Tunis, Tunisia.

3 Faculty of Economics and Management in Nabeul, University of Carthage, Carthage 1054, Tunisia.

10.22059/ier.2023.358646.1007705

Abstract

The threat of air pollution in the form of fine particulate matter (PM2.5) has been increasingly becoming serious around the world. To address this problem, an accurate understanding of its determinants is needed. This study investigates the impact of both natural and socioeconomic factors on PM2.5 concentrations in the United States (US). To this end, we apply an ARDL bounds testing approach using monthly data over the period from 2000 to 2021. Our findings support the existence of long-run relationship among the variables. Further, the results suggest that, in both the long and short term, energy consumption worsened PM2.5 pollution. However, there exists an inverse relationship between economic growth and PM2.5 concentrations only in the long term, which contrasts with what was found in the short term. Besides, industrialization exerts a negative impact on PM2.5 concentrations only in the short term. Regarding the natural factors, the results provide significant evidence that wind speed mitigates PM2.5 concentration contrary to temperature. However, no significant impact exists for precipitation and relative humidity. The results of Toda-Yamamoto causality test indicate the presence of a unidirectional causality running from economic growth and energy consumption to PM2.5 concentration at 5% significance level, and from industrialization and wind speed to PM2.5 at the 10% significance level. In light of these findings, some policy implications are recommended for U.S. policymakers.

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