The Daily And Seasonal Changes Of AOD And PM_2.5 In North China

North China is one of the highly polluted areas in Asia.A large number of anthropogenic pollution emissions and natural dust transport have caused the spatial and temporal changes of aerosols in North China to be very complex.It is great scientific significance to study the temporal and spatial distribution characteristics of aerosols in North China based on various detection methods.This paper uses the hourly concentration of PM_2.5?aerodynamic diameter less than or equal to 2.5?m fine particles?of 124 atmospheric environmental monitoring stations in North China provided by China Environmental Monitoring Center,and the aerosol chemical composition analysis data measured by Beijing Laboratory in winter 2014,China Aerosol Research Network?CARSNET?7 stations in North China,aerosol optical thickness?AOD?data,medium resolution imaging spectrometer?MODIS?secondary AOD products and research and application analysis,modern reanalysis,second edition data?MERRA-2?,carried out data analysis research on data sampling rate problem of satellite remote sensing PM_2.5.5 in North China and MERRA-2 reanalysis PM_2.5.5 precision problem,and focused on the daily variation of PM_2.5.5 in North China.The main conclusions are as follows:In the case of clouds or snow cover on the surface,satellites cannot provide AOD products.Even under high pollution conditions,satellite cloud detection algorithms often misjudge high pollution as clouds.Therefore,the satellite AOD product observation data acquisition rate has very obvious time and space.Changes are particularly evident in North China.The results show that the average sampling rate of the North American winter MODIS dark surface algorithm?DT?AOD product is only 4%,and the other season is about 30%.The MODIS Deep Blue?DB?algorithm can effectively supplement the DT sampling deficiency,especially in winter,making DT AOD sampling rate with DB is more than 30%in all seasons in North China.The analysis results show that there are certain differences in PM2.5concentration under the conditions of MODIS/AOD and no AOD,especially the heavy pollution zone in the North China before the Taihang Mountains.The difference between the two in autumn and winter can reach 8.5-11.2?g/m-3.The PM_2.5.5 difference at individual sites even exceeded 20?g/m-3.The above results indicate that the AOD sampling rate problem needs to be carefully considered,otherwise there will be systematic bias in the PM_2.5.5 seasonal average concentration based on satellite remote sensing.The spatial and temporal changes of aerosols and their components in North China provide a good test platform for verification model simulation data.In this paper,the independent ground-based stations and remote sensing products are used to evaluate the applicability of Modern Reanalysis Data 2nd Edition?MERRA-2?AOD and PM_2.5.5 products in North China.The MERRA-2 aerosol components are also analyzed in individual cases.An assessment was made.Although MERRA-2assimilated several satellite and solar photometer AOD products,the MERRA-2AOD system is smaller than the independent solar photometer measurement data.The underestimation ranged from 0.09?13%?in summer to 0.17?33%?in spring,with little spatial dependence.Although the AOD of MERRA-2 is relatively low,it can reproduce the daytime variation of AOD.Except for summer,MERRA-2 has a lower PM_2.5.5 concentration than ground measurements in all seasons,with an underestimation of maximum in winter?44?gm-3?.However,MERRA-2 cannot reproduce the daytime changes of PM_2.5.Evaluation of the MERRA-2 aerosol component in the winter of 2014 showed that MERRA-2 was difficult to reproduce the daily variation of aerosols and their constituents.This may be due to the lack of MERRA-2 deficiency in nitrate aerosols(20%of PM_2.5.5 concentrations in severely polluted weather)and the inadequacy of Goddard's chemistry,aerosol radiation and transport mode?GOCART?.The AOD variation in North China is moderate,with an average regional average of 0.29-0.52.However,the daytime variation of PM_2.5.5 showed significant fluctuations.The specific performance was that PM_2.5.5 began to decline after sunrise,and began to rise after sunset.At 9:00 am and the lowest value appeared in the afternoon.