中文摘要：

基于稀疏监测点的监测数据无法直接获取城市内部空气污染的高分辨率空间分布。以武汉市为例，研究了基于土地利用回归（1and use regression，LUR）模型的大气PM25浓度高分辨率空间分布模拟。采用双变量相关分析识别出与PMz。浓度相关性最高的4个影响因子，分别是1000m缓冲区内道路长度，500m缓冲区内水域面积，500ITI缓冲区内建设用地面积以及工业污染影响。采用PM2.5月平均浓度和识别出的影响因子连同气象条件（月平均温度和月降水量）进行多元线性回归分析，相关系数R2达到0．905，调整后的Rz为0．885。在研究区建立均匀格网（2km×2km），利用得到的LuR方程计算格点PM2.5浓度值，应用空间插值制成武汉市主城区夏季PMzs浓度空间分布模拟图。模拟结果显示，主城区有三个PM2.5浓度高值中心，分别为青山工业区、江北工业区和汉口汉西建材市场区域。汉阳南部、武昌南部的大型湖泊和水域面积比例较大的区域表现为两个PM2.5浓度低值中心。

英文摘要：

It is difficult to acquire small-scale spatial variation of intra-urban air pollutants from sparsely distributed monitoring sites; therefore, a land use regression model was used to generate a high-resolution map of summertime PM2.5 concentrations in Wuhan. Four spatial factors had high lev- els of correlation to PM2.5 average concentrations were identified using a bivariate correlation analysis; road length in buffers with 1000m radius （x2）, area of waters in buffers with 500m radius （x5）, area of construction land in buffers with 500m radius （xg） and point sources （x18）. These four spatial fac- tors together with meteorological data （monthly average temperature and monthly precipitation） were used as independent variables to build a multiple linear regression （MLR） model with PM2.smonthly average concentration as the dependent variable. The R2 of the regression was 0. 905, and the adjusted R2was 0. 885. We then built a grid at a resolution of 2 km× 2 km. The PM2.5 concentration for each cell of the grid was estimated using the MLR equation. A high resolution map of PM2.5 concentration of Wuhan in summer was generated based on this grid and spatial interpolation results showing the high-resolution distribution of PM2.5concentration. There were three high-value centers of PM2.5 con- centration, the Qingshan industrial zone, the north industrial zone, and Hanxi building material mar- kets area in Hankou. There were two low-value centers located at large lakes or in areas with large percentage of water in south Hanyang and south Wuchang.