Study On Influencing Factors And Forecast Of Meteorological Haze In Xi’an

Novel coronavirus pneumonia is a new research area in Xi’an.The data collected from the past three years are used as the basic data to study the outdoor air quality change trend in Xi’an.The relationship between meteorological factors and the main pollutants causing Xi’an’s pollution weather is analyzed.The relationship between the primary pollutants and meteorological factors during the outbreak of the new crown pneumonia is established.PM2.5 and PM are established.10.Based on the model with high prediction accuracy,the user interface of the prediction system is designed.The main conclusions are as follows:The main conclusions of the study are as follows:（1）The outdoor air quality in Xi’an has been continuously improved from 2017 to2019.The spatial distribution of outdoor air quality in Xi’an is low in the east.,high in the west,low in the north,high in the south,low in suburbs and high in urban areas.（2）Analyzing the temporal and spatial distribution characteristics of PM2.5,PM10,and O₃,it was found that the main pollutant that caused Xi’an’s summer air pollution in 2018was O₃,and the relationship between the concentrations of each season was:summer>spring>autumn>winter;The relationship between the mean value of PM_2.5and PM₁₀ is the same,both are winter>spring>autumn>summer.（3）According to the relationship between the primary pollutants and meteorological factors in 2018,temperature has the highest impact on various pollutants,and air pressure has the second highest impact on pollutants.Humidity and wind speed have lower effects on pollutants than temperature and air pressure.O₃concentration is most susceptible to meteorological factors.（4）In the continuous process of heavy pollution weather in Xi’an,there are often meteorological conditions with high humidity,low wind speed,temperature and atmospheric pressure fluctuations.The main reason for heavy pollution weather in Xi’an is the influence of warm and humid air flow to the south,while the strong cold air impact on the wind speed is the favorable condition for the diffusion of pollutants in Xi’an.（5）During the Novel coronavirus pneumonia epidemic,the air quality in Xi’an was better than the same period in previous years.During the Novel coronavirus pneumonia epidemic control period.It also has a strong impact.Air pressure and wind speed have a strong negative correlation with PM_2.5,the impact of precipitation on PM_2.5 appeared in The sudden drop of PM_2.5 concentration in the air during precipitation,the effect of wind direction on PM_2.5 is reflected in the area where the PM_2.5 concentration is higher in the area of the upper air outlet than in the area of the lower air outlet.（6）When PM_2.5,PM₁₀,O₃prediction models are made based on meteorological factors,the prediction effect of BP neural network prediction model on pollutant concentration is better than the multiple linear regression prediction model.The fitting degree and prediction accuracy of PM_2.5,PM₁₀,O₃and meteorological factors are from high to low:O₃>PM_2.5>PM₁₀.（7）Finally,a complete pollutant concentration prediction system was established based on the BP neural network prediction model.Because previous studies mostly stopped with the establishment of prediction models,without considering the practicality of the study,this article uses meteorological factors（barometric pressure,temperature,wind speed,and humidity）to predict the concentration of pollutants,the functions that can be implemented in the system are:importing different sample data to train specific BP neural network prediction models,the system can intuitively show the training process of BP neural networks,and predict the changes in pollutant concentrations Trend,users only need to collect meteorological factor data to predict the concentration of pollutants through a series of simple operations.There are 41 figures,18 tables,54 references in this article.