京津冀地区夏冬两季PM2.5浓度空间分布研究

摘要

In order to make up the problem of lacking the study of surveying the spatial distribution of seasonal PM2.5 according to the related surveying and mapping results,PM2.5 concentration characters of summer and winter in Beijing-Tianjin-Hebei Region in 2013 are simulated by using land use regression model.Surface coverage classification,dust surfaces,polluting industries are identified having correlation to PM2.5 by using a bivariate correlation analysis.They are used as independent variables to build a multiple linear regression model with seasonal PM2.5 as the dependent variable,and R2 of PM2.5 in winter and summer is 0.743 and 0.866,respectively.According to the land use regression equation,the concentration of encryption points are calculated and a more accurate PM2.5 concentration spatial distribution map of two seasons is obtained by inverse-distance weighting method (IDW).The results show that the pollutant concentration is bounded by Taihang-Yanshan Mountain borders in both seasons.The east and south regions are heavily polluted while the west and north regions are relatively in good condition.Furthermore,the pollution in winter is heavier than that in summer,and the variation trend of PM2.5 concentration characters of both cities in summer and winter is basically consistent.%为弥补结合相关测绘成果研究季节性PM2.5空间分布相对不足的问题,以京津冀为例,基于土地利用回归(Land Use Regression,LUR)模型对研究区2013年典型季节的PM2.5浓度进行模拟.采用双变量相关分析识别出与PM2.5浓度相关的影响因子,主要包括地表覆盖分类、扬尘地表及污染企业在内的监测成果等因素,分别对夏冬两季PM2.5浓度和与之对应的影响因子进行多元线性回归分析,判定系数R2分别为0.743和0.866.根据LUR方程计算加密点浓度值,通过反距离加权插值得到较为精细的PM2.5浓度空间分布图.结果显示,研究区两季污染物浓度都呈现出以太行山-燕山山脉为界,东部、南部地区污染严重,西部、北部地区污染较轻的态势.冬季整体的污染程度高于夏季,各城市两季PM2.5浓度变化趋势基本一致.