Underlying Dynamics of PM2.5 Concentrations in China: Evidence Based on ARDL Approach

Abstract

Abstract This study investigates the underlying dynamics of air pollution utilizing time series data from China over the period 2000–2020. In the empirical setting, air pollution is represented by particulate matter 2.5 (PM2.5) concentrations known as the most detrimental ambient pollutant. The empirical model of the study includes several socioeconomic potential determinants of PM2.5 concentrations. The main motivation behind the study is the downward tendency of PM2.5 concentrations in China as of the second decade of the 2000s. At this point, although it is commonly accepted that the Air Pollution Prevention and Control Action Plan implemented by the Chinese State Council has been effective, the underlying specific dynamics of reducing PM2.5 concentrations are not clear. From this motivation, the study unveiled the driving forces of PM2.5 concentrations in the framework of the autoregressive distributed lag model approach. Empirical results put forward the positive impact of economic growth, industrialization, and foreign direct investment inflows on PM2.5 concentrations, while medium- and high-tech exports, and coal rents are found negatively associated with them. In this respect, overall results particularly emphasize the lowering effect of an increase in medium- and high-tech product exports on the PM2.5 concentrations. In this context, to improve the air quality further, the study suggests that China should transform its industrialization structure toward specialization in medium- and high-tech products, and promote foreign direct investment inflows specialized in these types of products. The study provides additional policy recommendations for Chinese policymakers.