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Study On Source Contribution Of Particulate Matter Concentration In Yumen City Based On WRF-Chem Simulation

Posted on:2021-03-31Degree:MasterType:Thesis
Country:ChinaCandidate:H ZhangFull Text:PDF
GTID:2381330611451854Subject:Atmospheric Science
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Yumen City is located in the northwest of Gansu Province,the west of the Hexi Corridor,the mountains in the south and north,and the desert belt in the east and west.It is affected by sand and dust weather all year round;For polluting enterprises,anthropogenic sources emit a large amount.The results of environmental quality monitoring in 2018 show that the particulate matter in this area exceeds the standard.This paper analyzes the spatial and temporal distribution characteristics of atmospheric pollutant concentration changes in Yumen City using ambient air quality monitoring data;using the rotating principal component analysis method to study the relationship between major atmospheric pollutants and meteorological factors,revealing the causes of polluted meteorology;using WRF-Chem values Model,simulate the concentration of PM100 and PM2.5.5 in Yumen City in January,April,July and October 2018,and compare with the monitoring concentration of the two monitoring points to quantitatively evaluate the simulation efficiency of the model and analyze Yumen City Spatial distribution characteristics of particulate matter;quantify the contribution rate of power sources,industrial sources,external sources and dust transportation to the concentration of particulate matter in Yumen City through a sensitivity test;Finally,the backward trajectory method is used to analyze the transmission path of air mass around Yumen City.The research conclusion has important reference value for scientific prevention and control of particulate matter pollution in Yumen City.?1?The analysis results of ambient air quality and meteorological monitoring data show that:the main pollutant in Yumen City is particulate matter,especially in winter and spring;the variation characteristics of particulate matter at different stations in Yumen City are basically the same;Up to 4.2m/s.?2?The rotating principal component analysis results show that:Yumen City site has extracted four main factors,The main factor1 is characterized by the effect of temperature and surface pressure on ozone generation;the main factor2 characterizes the effect of wind speed on the diffusion of particulate matter;the main factor3reflects the wind speed The influence of CO and NO2 concentration;the main factor4characterizes the influence of temperature on the concentration of SO2 and CO.The cumulative explanatory variance is 73.24%.?3?The WRF-Chem model compares and analyzes the monitoring values of PM2.5.5 and PM100 simulated in four season months of Yumen City with the two environmental quality monitoring stations,the correlation coefficients are all above0.6,the absolute error is 13?g/m3,and the relative error At 11%-27%,the root mean square error is 9?g/m3.The model is better for the simulation of particulate matter in Yumen City and Yumen East Town,and the simulation results are reliable.?4?The simulation results of the sensitivity test show that the contribution of external sources,power sources and industrial sources to the overall PM10 and PM2.5of Yumen City is less than 1%.The contribution of the transportation of sand and dust sources to PM100 and PM2.5.5 accounts for 95.0%and 88.6%,respectively.Sand and dust sources are the main sources of pollution that affect the environmental particulate matter concentration in Yumen City.?5?The HYSPLIT trajectory model results show that the main air masses that control Yumen City throughout the year are the wester airflow?Talimu Basin?,the easter airflow?Tengger Desert and Badain Jaran Desert?,northwest Airflow?Northern Xinjiang?,these three airflows all transport the sand and dust generated in the sand and dust source area to Yumen City,which is the main reason for affecting the particulate matter in Yumen City.
Keywords/Search Tags:WRF-Chem, Yumen City, principal component analysis, particulate matter, source contribution rate, backward trajectory method
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