利用MO DIS资料监测京津冀地区近地面PM2.5方法研究

摘要

Base on meteorological data from a numerical weather prediction model during January to March of 2013,MODIS Deep Blue AOD products were corrected with respect to relative humidity(RH)and vertical heights, and their correlation relationships with ground PM2.5 concentration were analyzed in order to establish a surface fine particulate concentration monitoring model in Jing-Jin-Ji regions.The results indicate that the Aqua MODIS DB algorithm AOD products are more suitable for establishing an AOD-PM2.5 linear correlative model in winter, and the R2 reaches 0.33 .Height of planetary boundary layer and RH extracted from the meteorological model are used to substitute for vertical correction factor.Besides,according to the aerosol hygroscopic characteristic from IMPROVE,relative humidity correction is developed to estimate surface PM2.5 concentration in different RH ran-ges,which could improve precision of AOD-PM2.5 model.Thus,an optimum model of winter remote sensing inver-sion PM2.5 concentration is established.Finally,the R2 between estimated and observed PM2.5 cocentration reaches 0.5 1 .Based on the above model,monthly average surface PM2.5 concentration is calculated.It suggests that month-ly average surface PM2.5 concentration is higher in Janurary,while air quality reaches a severe pollution level in the southern part of Jing-Jin-Ji regions.%为了建立京津冀地区冬季近地面细颗粒物浓度监测方法的模型，利用气象模式资料对2013年1-3月MODIS的AOD二级深蓝算法产品进行湿度和垂直订正，与同期观测的地面细颗粒物PM2.5资料进行相关分析。结果表明：AQUA的MODIS深蓝算法AOD产品更适用于建立冬季AOD-PM2.5遥感监测模型，其R2为0.33；以气象模式资料中边界层高度代替气溶胶标高对MODIS的AOD进行垂直订正，并结合IMPROVE观测的气溶胶吸湿增长特征构建分区湿度订正方法，可以提高AOD-PM2.5模型结果的精度，建立较理想的京津冀地区冬季遥感反演综合模型，模型模拟结果与地面监测结果R2达0.50以上。根据建立的模型计算了2013年1-3月京津冀地区PM2.5月平均浓度，京津冀地区1月PM2.5浓度较高，南部大部分地区空气质量已达到重度污染水平。