The dynamics of industrial activity, urbanization, and PM2.5 pollution in central Asian countries: A panel CS-ARDL analysis

Type of the article: Research ArticleAbstractThis study examines the long-term and short-term dynamic interactions between PM2.5 pollution and its anthropogenic determinants, namely industrial activity, urbanization, economic growth, total energy use, and renewable energy utilization, across five Central Asian countries (Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan) from 1992 to 2023. Preliminary tests validate pronounced cross-sectional dependence and notable slope heterogeneity, substantiating the application of the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model. The Westerlund cointegration results demonstrate a strong long-term equilibrium relationship. The long-term CS-ARDL estimations indicate that industrial activity is the primary driver of PM2.5 pollution, followed by total energy consumption. The analysis reveals evidence supporting the upward-sloping segment of the Environmental Kuznets Curve (EKC), as economic growth significantly elevates PM2.5 levels. In contrast, the squared GDP term is insignificant, suggesting the absence of a turning point in pollution reduction. Renewable energy consumption has a negligible moderating effect. The Error Correction Term is negative and statistically significant, indicating that approximately 24.5% of deviations from the long-term equilibrium are corrected each year. The findings indicate that environmental stability in Central Asia necessitates a strategic transformation of industrial and energy policy, underscoring the importance of coordinated regional initiatives to modernize grids and promote green industrial practices to decouple economic expansion from particulate pollution.