Non-Linear Response of PM 2.5 Pollution to Land Use Change in China.

Land use change has an important influence on the spatial and temporal distribution of PM_2.5 concentration. Therefore, based on the particulate matter (PM_2.5) data from remote sensing instruments and land use change data in long time series, the Getis-Ord Gi* statistic and SP-SDM are employed to analyze the spatial distribution pattern of PM_2.5 and its response to land use change in China. It is found that the average PM_2.5 increased from 25.49 μg/m³ to 31.23 μg/m³ during 2000-2016, showing an annual average growth rate of 0.97%. It is still greater than 35 μg/m³ in nearly half of all cities. The spatial distribution pattern of PM_2.5 presents the characteristics of concentrated regional convergence. PM_2.5 is positively correlated with urban land and farmland, negatively correlated with forest land, grassland, and unused land. Furthermore, the average PM_2.5 concentrations show the highest values for urban land and decrease in the order of farmland > unused land > water body > forest > grassland. The impact of land use change on PM_2.5 is a non-linear process, and there are obvious differences and spillover effects for different land types. Thus, reasonably controlling the scale of urban land and farmland, optimizing the spatial distribution pattern and development intensity, and expanding forest land and grassland are conducive to curbing PM_2.5 pollution. The research conclusions provide a theoretical basis for the management of PM_2.5 pollution from the perspective of optimizing land use. [ABSTRACT FROM AUTHOR]