Spatial distribution stimulation and population exposure of PM2.5 based on Land Use Regression——a case study of Hubei Province
SONG Wanying， YANG Zhen， WANG Pingping， DING Qiyan， LI Xingming
1.College of Urban and Environmental Sciences， Central China Normal University， Wuhan 430079， China；2.Research Institute of Sustainable Development， Central China Normal University， Wuhan 430079， China；3.Academy of Wuhan Metropolitan Area， Hubei Development and Reform Commission & Central China Normal University， Wuhan 430079， China
Abstract：Atmospheric fine particulate matter is one of the major pollutants that threatens human health seriously. Taking Hubei Province as an example， in this paper LUR (land use regression) model is applied in spatializing the PM2.5 concentration data of each monitoring station， and the spatial variation of population exposure intensity is investigated on top of that， so as to provide reference for the prevention and control of pollution regionally. The results show as follows. 1) The concentration of 60 monitoring sites differ a lot and the average PM2.5 concentration of sites exceeds the second level of the national ambient air quality standard. The concentration is significantly affected by four factors， namely temperature， wind velocity， altitude and area of green space in buffer with 3 km radius. The rise of temperature will be contributed to increase the value of PM2.5， while other factors are opposite. 2) The spatial distribution simulation of PM2.5 based on LUR shows obvious gradient differences of PM2.5 concentration， which are high in the middle region， low in the east， and the lowest in the west on a provincial scale. Generally， the pollution in Wuhan Metropolitan， Jianghan Plain and part of Xiangyang are more severe than the western parts relatively. 3) Taking population density into consideration， the study of PM2.5 exposure intensity index built exhibits a high spatial correlation between the exposure intensity and population density. The majority of population and land in the province is in low exposure intensity. The highly exposed areas are comparatively dispersed， mainly distributed in the middle and east of Hubei centered in Wuhan metropolitan.
宋万营,杨 振,王平平,丁启燕,李星明. 基于LUR模型的大气PM2.5浓度分布模拟与人口暴露研究——以湖北省为例[J]. 华中师范大学学报(自然科学版), 2019, 53(3): 451-458.
SONG Wanying,YANG Zhen,WANG Pingping,DING Qiyan,LI Xingming. Spatial distribution stimulation and population exposure of PM2.5 based on Land Use Regression——a case study of Hubei Province. journal1, 2019, 53(3): 451-458.
2019, Vol. 53 
