| This paper studies the correlation between air pollutants and meteorological factors in xi'an city in recent years,focusing on the annual and quarterly variation characteristics analysis of various monitoring indicators?PM2.5,PM10,SO2,NO2,CO,O3?related to air quality index AQI and meteorological factors such as temperature,humidity and wind grade.As well as fitting analysis of regression equations between primary pollutants and meteorological factors in different seasons in key years,the following conclusions are obtained:After 2015,the air quality structure of xi'an city changed significantly,the number of days with good air quality decreased significantly,and the number of days with heavy pollution and serious pollution increased significantly.From 2016 to 2018,the main part of air quality is good and light pollution,so the main work to improve the air quality of xi'an is to solve the air quality is good and light pollution weather.Take 2017 as an example to study the change characteristics of pollutants in different seasons in xi'an and find that the most important pollutant that affects the upper limit of air quality is NO2.In spring,the air quality index has two peaks,which are influenced by a variety of pollutants.PM10 is the primary pollutant in severe air quality pollution and severe pollution weather.The change of pollutants is relatively stable in summer,and the main pollutant affecting air quality is O3.The air quality in autumn and winter are the best and worst seasons of the year respectively,and the air quality index has multiple peaks.The most important pollutant affecting the air quality in autumn and winter is PM2.5,and the second major pollutant is PM10.By analyzing the mass concentration changes of PM2.5 and PM10 during the Spring Festival from 2015 to 2018,it is found that the air quality during the Spring Festival from2015 to 2017 becomes worse year by year due to the impact of fireworks discharge.The mass concentration of PM2.5 and PM10 decreases with the increase of relative humidity,and the decrease trend shows a certain lag.The greater the change range of relative humidity,the greater the change of pollutant mass concentration.The change trend of mass concentration of PM2.5 and PM10 with large temperature difference?2015?was significantly greater than that of small temperature difference?2018?,and the mass concentration decreased with the sharp drop in temperature and increased with the sharp increase,while the influence of small temperature difference was weak.SPSS software was used to analyze the correlation between meteorological parameters and various pollutant indicators in different seasons in 2017.It was found that temperature,humidity and wind level in spring were significantly correlated with at least two pollutants at the 0.01 level except PM10.Summer humidity has significant correlation with various pollutants,while temperature has significant correlation with PM2.5,PM10and O3.In autumn,temperature and wind level are significantly correlated with various pollutants,while humidity has the largest correlation with SO2,which is 0.453.In winter,temperature has a weak correlation with pollutants,humidity has a maximum correlation with PM2.5 of 0.506,and wind level has a significant correlation with other pollutants except O3.SPSS was used for stepwise regression of primary pollutants in different seasons in2017,and stepwise regression equations of various primary pollutants in different seasons were obtained.The results showed that spring regression analysis was greatly affected by temperature and wind level,and the overall error was controlled within 35%.The regression analysis in summer is greatly affected by relative humidity,and the overall error is controlled within 25%.The regression analysis in autumn and winter is greatly affected by temperature,and the overall error is controlled at 20%and 30%respectively.Therefore,the stepwise regression analysis method used in this study has certain theoretical basis for the prediction of air pollutant concentration. |
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