Increasing attention has been given to the impact of PM2.5 concentration on human health. Exploring the influential factors of PM2.5 is conducive to improving air quality. Most existing studies explore the factors that influence the PM2.5 concentration from the perspective of cities or urban agglomerations, while few studies are conducted from the perspective of climate zones. We used the standard deviation ellipse and spatial autocorrelation analysis to explore the spatial-temporal evolution of the PM2.5 concentration in different climate zones in China during 2000-2018. We used differentiated EKC to construct panel regression models to explore the differences in the influential factors of the PM2.5 concentration in three climate zones. The number of cities with PM2.5 concentration less than 35 μg/m3 increased in the different climate zones. The center of gravity of the PM2.5 concentration has remained at the junction of the temperate and subtropical monsoon climate zones. The PM2.5 concentration had a high positive spatial autocorrelation in the different climate zones. The high-high clustering areas were located in the south of the temperate monsoon climate zone and the north of the subtropical monsoon climate zone. There was an inverted "U-shaped" curve between the PM2.5 concentration and economic development in China that varied in different climate zones. Identifying the differences in the influential factors of PM2.5 concentration in different climate zones will help to accelerate the implementation of the EKC inflection point.
Keywords: China; Climate zone; Environmental Kuznets curve; PM2.5 concentration; Spatial-temporal evolution.
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