摘要
Abstract
Based on PM2.5 and population grid data,an exposure risk assessment model was employed,and the spatiotemporal evolution of population exposure risks to PM2.5 in China from 2000 to 2020 was investigated.In addition,the population exposure risks to PM2.5 in China was evaluated.According to land use data,this paper calculated landscape pattern indexes on the basis of the optimal moving window and employed Pearson correlation analysis to reveal the relationship among landscape patterns,PM2.5 concentrations,and population exposure risks.The population exposure risks to PM2.5 in China show a trend of an initial increase followed by a decrease.There is significant variation in the population exposure risks to PM2.5 between the eastern and western sides of the Heihe-Tengchong Line.Spatially,regions with high population exposure risks to PM2.5 in China are predominantly located in the Beijing-Tianjin-Hebei region,Yangtze River Delta,and Central China.The study finds that edge density(ED)and landscape shape index(LSI)can help mitigate population exposure risks to PM2.5.Lower ED,LSI,and edge shape complexity can effectively reduce population exposure risks to PM2.5,while highly fragmented landscape types can further weaken the reduction of population exposure risks to PM2.5.关键词
暴露风险评价/景观指数/评价模型/高精度/PM2.5Key words
exposure risk assessment/landscape index/assessment model/high precision/PM2.5分类
天文与地球科学
