Abstract:Land use regression (LUR) model was employed to simulate the spatial distribution of PM10 and NO2 based on environmental air quality monitoring data and Arcgis. LUR predictor variables included density of population, wind index, distance to sea shore, as well as 2 buffer indices: total length of road and areas of 5 different land use patterns within a buffer. Radii of buffer area were chosen of 1, 2, 3, 4 km, respectively. The PM10 and NO2 annual average data from 7 national ambient air quality monitoring sites were chosen as dependent variables, data from another 3 sites were chosen for LUR model validation. PM10 and NO2 were highly correlated with total length of road within a buffer of 1km (R2=0.560) and population density (R2=0.414), respectively. Top five predictor variables without wind index were chosen based on the correlation coefficients for PM10 and for NO2, respectively. The 2 multi linear regression equations were established based on above five predictor variables with wind index for PM10 (R2=0.980) and NO2 (R2=0.849), respectively. Grid was established by 5 km ′ 5 km in Tianjin central districts. Concentrations of PM10 and NO2 at intersection points were calculated using 2 equations, respectively. The spatial concentration distribution of PM10 and NO2 were interpolated by Kriging approach and showed: PM10 concentration is highest in center of the studying area, and decreased gradually from center to surrounding area; while NO2 concentration is lowest in center of the studying area, and increased gradually to surround area. The final models predicted well at study area.
陈莉, 白志鹏, 苏笛, 游燕, 李华敏, 刘全. 利用LUR模型模拟天津市大气污染物浓度的空间分布[J]. 中国环境科学, 2009, 29(7): 685-691.
CHEN Li, BAI Zhi-Peng, SU Di, YOU Yan, LI Hua-Min, LIU Quan. Application of land use regression to simulate ambient air PM10 and NO2 concentration in Tianjin City. . CHINA ENVIRONMENTAL SCIENCECE, 2009, 29(7): 685-691.