The contributions of socioeconomic indicators to global PM based on the hybrid method of spatial econometric model and geographical and temporal weighted regression.

PM pollution poses a negative effect on human health and economic growth. However, the major socioeconomic driving forces of global PM pollution during a long-term period remained unclear. In this study, we explored the potential association between socioeconomic indicators and the PM level worldwide using a spatial econometric model coupled with a geographical and temporal weighted regression (GTWR). The results suggested that renewable energy consumption ratio, per capita gross domestic production (GDP), per capita CO emission, urban population ratio, and fossil fuel consumption ratio were major factors responsible for the global PM pollution. The impacts of socioeconomic indicators on the PM level varied with the income-level and time. Fossil fuel consumption ratio, per capita CO emission, urban population ratio were major contributors for severe PM pollution in the developing countries (e.g., China and India). Further, these impacts have become more remarkable in recent years. Per capita GDP still played a crucial role on the PM pollution in India, indicating that energy-intensive industries were major contributors to its economic growth, thereby leading to the higher PM concentration in India. However, China has strode across the inflection of Environmental Kuznets Curve (EKC) as a whole and decreased the reliance on the secondary industries. Compared with the developing countries, the impacts of socioeconomic indicators on PM pollution in most of the developed countries remained relatively stable and weak, implicating that fossil fuel consumption and urbanization were not major contributors for local PM level. The findings of this study clarified major contributors for PM pollution, and provided scientific basis for mitigating the PM pollution.