Abstract: Atmospheric quality is closely related to human living environment. Atmospheric pollutants, especially fine particulate matter, directly and indirectly endanger human health. Therefore, many cities put the monitoring of fine particulate concentration at an important position. We analyzed the correlation between MODIS highresolution aerosol products (aerosol optical depth, AOD) and PM_2.5 concentration monitoring data in Guanzhong area in spring 2017 and constructed a direct fitting model. A multiple regression model containing meteorological elements was established by combining meteorological observation data. Those two models were compared. The results showed that the multivariate regression model with meteorological factors had better fitting degree for the spatial distribution of PM_2.5 in Guanzhong area (r²=0.768,P<0.01). In the spring of 2017, the spatial distribution of PM_2.5 (AOD) in Guanzhong area showed a trend of being high in the east region and low in the west region. The highest value appeared in Xi’an, Weinan and Xianyang, being 1.019, 0.911, and 0.124, respectively. Results from the principal component analysis of a typical polluted weather and simulation of its potential transmission path based on HYSPLIT backward trajectory model showed that atmospheric quality in Guanzhong area in spring 2017 was affected by multipollutants, multipollutant sources and multichannel combined pollution, and the air mass mainly came from southwestern Mongolia. Our results provide reference for the prevention and control of air pollution and ecological environment protection in Guanzhong area.

Key words: soil colloidal phosphorus, speciation, transference, analysis technology.