Revisiting the impact of vehicle emissions and other contributors to air pollution in urban built-up areas: A dynamic spatial econometric analysis

Abstract

Whether vehicle emissions are the primary source of PM2.5 in urban China remains controversial, which may be attributable to the insufficient consideration of the spatial autocorrelation and the spatial spillover effects of PM2.5. We employ data from built-up areas of 285 prefecture-level cities in China spanned 2001–2016 and dynamic spatial panel data analysis to resolve this controversy. Our results show that the direct and indirect effects of vehicles on PM2.5 concentration (annual mean and spatial variation within the city) in urban China are not significant in the short- and long-term. Alternatively, SO2 emission directly increases the mean and spatial variation of PM2.5 within the city in the short- and long-term. Short-term direct and indirect positive association and long-term indirect positive association are found relative to economic growth and PM2.5. Population density increases PM2.5 directly and indirectly in the short-term and yet, directly decreases and indirectly increases PM2.5 in the long-term. In the short- and long-term, the spatial spillover effect of secondary industry increases PM2.5, and industry also directly increases the spatial variation of PM2.5 within the city. Although real estate investment directly increases PM2.5 in the long-term, the spatial spillover effect of investment reduces PM2.5 in the short- and long-term. Our results show that other factors, rather than vehicle emissions, are the major contributors to PM2.5 in urban China. Furthermore, the Environmental Kuznets Curve hypothesis does not apply to the relationship between economic growth and PM2.5 proliferation in urban China. When tackling air pollution, owing to the significant spatial spillover of PM2.5 that is driven by multiple contributing factors, short- and long-term inter-regional coordination is required to achieve an effective positive outcome.