徐州市气溶胶光学厚度与PM2.5相关性及年周期特征

基于徐州市2014～2017年气溶胶光学厚度(AOD)、地面监测站PM_(2.5)浓度及气象数据,构建经标高订正的AOD(AOD/H)与经湿度订正的PM_(2.5)(PM_(2.5)×f_((RH)))之间的5种不同类型的拟合模型,分析两者在不同季节的相关性;同时利用经验模态分解对AOD/H与PM_(2.5)×f_((RH))进行周期变化分析。结果表明:AOD与PM_(2.5)浓度直接相关程度较低,经过订正后两者的相关程度显著提高;选取乘幂模型为最优拟合模型,利用乘幂模型估计得到的PM_(2.5)浓度与地面监测的经湿度订正的PM_(2.5)浓度呈显著正相关,相关系数在四季分别达到0.752、0.650、0.808和0.942;利用经验模态分解分析得到AOD/H与PM_(2.5)×f_((RH))具有显著的年周期变化特征,均在冬季出现高值,后逐渐降低,在6月前后出现极小值,到秋季又逐渐增大;AOD/H与PM_(2.5)×f_((RH))年变化特征表现出很高的一致性(r=0.888),表明在徐州地区AOD/H对PM_(2.5)×f_((RH))在年周期尺度变化特征研究中能起到良好的指示作用。

Correlation Analysis and Annual Cycle Characteristics of Aerosol Optical Depth and PM2.5 Concentrations in the Xuzhou City

The relationship model of PM_2.5 concentration and AOD (aerosol optical depth) was constructed, the annual changes of vertical corrected AOD (AOD/H) and moisture corrected PM_2.5 concentration (PM_2.5×f_(RH)) and their correlation, which could be used as a reference for air quality evaluation, in the Xuzhou city were analyzed. The correlations between AODs and PM_2.5 concentrations in different seasons were investigated on the basis of MODIS AOD, PM_2.5 concentration dataset and related meteorological data from 2014 to 2017, and five different fitting methods were applied to explore correlations of AOD/H and PM_2.5×f_(RH) in different seasons. The empirical mode decomposition was used to analyze periodic variations of AOD/H and PM_2.5×f_(RH). The results showed that no correlation was found between original AODs and PM_2.5 concentration data, but AOD/H and PM_2.5×f_(RH) correlated notably. The power model was the optimal fitting model for predicting PM_2.5 concentrations based on monitored data of PM_2.5×f_(RH) in Xuzhou, the correlation coefficients were 0.752, 0.650, 0.808 and 0.942 for the four seasons, respectively. The annual trends of AOD/H and PM_2.5×f_(RH) were highly covaried with r=0.888, and their highest values were showed in winter, and gradually decreased to the minimum values around June in summer, and then gradually increased throughout autumn. In summary, this study demonstrated that AOD is an effective proxy to estimate the concentration of PM_2.5 and that AOD/H is a good index for describing the annual changes of PM_2.5×f_(RH) in the Xuzhou city.