High concentrations of PM2.5 are a primary cause of haze in the lower atmosphere. A better understanding of the spatial heterogeneity and driving factors of PM2.5 concentrations is important for effective regional prevention and control. In this study, we carried out remote sensing inversion of PM2.5 concentration data over a long time series and used spatial statistical analyses and a geographical detector model to reveal the spatial distribution and variation characteristics of PM2.5 and the main influencing factors in the Yangtze River Delta from 2005 to 2015. Our results show that (1) The average annual PM2.5 concentration in the Yangtze River Delta prior to 2007 displayed an increasing trend, followed by a decreasing trend after 2007 which eventually stabilized; and (2) climate regionalization and geomorphology were the dominant natural factors driving PM2.5 concentration diffusion, while total carbon dioxide emissions and population density were the dominant socioeconomic factors affecting the formation of PM2.5. Natural factors and socioeconomic factors together lead to PM2.5 pollution. These findings provide an interpretation of PM2.5 spatial distribution and the mechanisms influencing PM2.5 pollution, which can help the Chinese government develop effective abatement strategies.

Under the concept of green development, accurately mapping ecological carrying capacity to effectively evaluate regional sustainability has already become an important issue in China. This study introduced ecological carrying capacity intensity (ECintensity) based on the revised three-dimensional ecological footprint (3DEF) model to describe the temporal–spatial patterns of three-dimensional ecological carrying capacity (EC3D) in Inner Mongolia in 2010–2016 and to explore factors affecting socioeconomic sustainable development. The results showed that ecological footprint size (EFsize) differed between cities/leagues but changed little during the study period. Ecological footprint depth (EFdepth) far exceeded the original value of 1.00. Ecological carrying capacity (EC) varied in cities/leagues, while ECintensity increased slowly with stronger potential for regional development. Three-dimensional ecological deficits (ED3D) of cities/leagues were divided into five categories: Hohhot, Hulunbuir and Banyannur were in larger ecological surplus; Hinggan was in slight surplus; Baotou, Chifeng, Tongliao, Ulanqab, Xilin Gol and Erdos were in slight deficit; Wuhai was in stronger deficit; and Alxa was in severely intense deficit. Woodland of cities/leagues was continuously in slight ecological surplus, while cropland and grassland had crucial impacts on deficit. There was a significant positive linear correlation between gross domestic product (GDP) and footprint, while a negative correlation was seen with deficit. These results would help coordinate resource utilization and industrial structure adjustment in Inner Mongolia.