Study On Several Issues Concerning PM_2.5 Remote Sensing In China From MODIS

Due to the limited distribution of the conventional ground-based PM_2.5?particulate matter with diameter less than 2.5 ?m?monitoring sites,it is difficult to accurately elucidate the spatial distribution and transmission path of the aerosol pollutants.However,satellite remote sensing can only retrieave aerosol optical depth?AOD?,which is generally accompanied by large uncertainties caused by factors such as the vertical distribution of aerosol and the hygroscopic growth of aerosol particles.In general,AOD is affected by cloud cover,relative humidity,vertical distribution of aerosol particles and hygroscopic growth etc.Domestic and abroad scholars have done a lot of research on how to improve the correlation between PM_2.5 and AOD,but few studies have attempted to figure out the diurnal cycle of PM_2.5 and its impact on the correlation between PM_2.5 and AOD.In this work,we investigated the diurnal cycle of PM_2.5 in China based on ground-based PM measurements obtained at 226 sites of China Atmosphere Watch Network during the period of January 2013 to December 2015.Results showed that nearly half of the sites witnessed a PM_2.5 maximum in the morning,in contrast to the least frequent occurrence?5%?in the afternoon when strong solar radiation received at the surface resulst in rapid vertical diffusion of aerosols and thus lower mass concentration.PM_2.5 tends to peak equally in the morning and evening in North China Plain?NCP?with an amplitude of nearly twice or three times that in the Pearl River Delta?PRD?,whereas the morning PM_2.5 peak dominates in Yangtze River Delta?YRD?with a magnitude lying between those of NCP and PRD.The gridded correlation maps reveal varying correlations around each PM_2.5 site,depending on the locations and seasons.Concerning the impact of aerosol diurnal variation on the correlation,the averaging schemes of PM_2.5 using 3-h,5-h and 24-h time windows tend to have larger R biases,compared with the scheme of 1-h time window,indicating diurnal variation of aerosols plays a significant role in the establishment of explicit correlation between PM_2.5 and AOD.In addition,high cloud fraction and relative humidity tend to weaken the correlation,regardless of geographical location.Therefore,the impact of meteorology could be one of the most plausible alternatives in explaining the varying R values observed,due to its non-negligible effect on MODIS AOD retrievals.Our findings have implications for PM_2.5 remote sensing,as long as the aerosol diurnal cycle,along with meteorology,are explicitly considered in the future.Furthermore,based on the above work,we using the humidity,cloud cover,10km×10km MODIS AOD and Boundary layer height as the impact factors,a seasonal quantitative statistical model is constructed with nonlinear fitting scheme.The fitted result is pretty good in NCP,YRD and PRD.The estimated seasonal 10km×10km PM_2.5 retrievals can serve a effective indicator for the actual surface PM_2.5 concentration in China.The good agreement between the PM_2.5 retrievals and the observations indicates the potential of the promising PM_2.5 remote sensing method in operational monitoring of ground-based aerosol particles in China.Last but not least,some unresolved problems are discussed as well.