四川盆地PM2.5浓度时空变化特征遥感监测与影响因子分析

四川盆地因其独特的地形地貌、静风和高湿等气象条件，导致盆地内部大气污染物扩散难度大，随着城市化与工业化进程加快，区内PM_2.5污染日益加重，四川盆地已成为国家大气污染防治的重点地区之一.基于PM_2.5浓度遥感反演产品，采用空间自相关分析与灰色关联分析方法，研究了四川盆地PM_2.5浓度的时空分布特征及其影响因素.结果表明，四川盆地PM_2.5浓度具有显著的空间聚集性，高-高聚集类型分布集中，低-低聚集类型分布较为分散；针叶林对PM_2.5的吸收抑制作用明显高于灌丛和草地等其他植被类型.研究认为，影响四川盆地PM_2.5浓度的主要气象因子是风速和气温，人口密度与经济规模则是影响四川盆地PM_2.5浓度的主要人类活动因子，产业结构及其规模变化对四川盆地PM_2.5浓度也产生一定影响.

Spatio-temporal Variation Characteristics Monitored by Remotely Sensed Technique of PM2.5 Concentration and Its Influencing Factor Analysis in Sichuan Basin, China

The spread of atmospheric pollutants in the Sichuan Basin is difficult because of its unique topography, static wind, high humidity, and other meteorological conditions. Owing to the acceleration of urbanization and industrialization, PM_2.5 pollution in the region is becoming increasingly severe, and the Sichuan Basin has become one of the key areas of national air pollution prevention and control. In this study, based on the remote sensing inversion product of PM_2.5 concentration, spatial autocorrelation and gray correlation analyses are used to evaluate the spatial and temporal distribution characteristics and influencing factors of PM_2.5 concentration in the Sichuan Basin. The results show that PM_2.5 concentration has significant spatial aggregation; the high-high aggregation types are concentrated, low-low aggregation types are more dispersed, and coniferous forest has a significantly higher inhibitory effect on the absorption of PM_2.5 than the shrub, grassland, and other vegetation types. The main meteorological factors affecting PM_2.5 concentration in the Sichuan Basin are wind speed and temperature; population density and economic scale are the main human-activity factors affecting PM_2.5 concentration in the Sichuan Basin, and the change in the industrial structure and scale also has a certain influence on the PM_2.5 concentration.