Simulation Of PM2.5 Air Pollution Diffusion Based On GIS

Frequent outbreaks of haze have seriously affected people's lives and threatened people's health,causing widespread concern from the government and the broad masses.The diffusion of PM2.5 is simulated and predicted.When a sudden air pollution accident occurs,people can take corresponding measures to prevent and treat it by simulating and predicting in advance,thus reducing the harm of the accident.In air quality research,gaussian plume model,gaussian smoke cloud model,box model and other atmospheric diffusion models have been developed to quantitatively predict air pollution diffusion.At the same time,many scholars also combined GIS with the air pollution model,and analyzed the spatial and temporal distribution rules of air pollution diffusion and its impact on cities by combining the meteorological factors that affect the diffusion of air pollution with the spatial and geographical factors such as topography,building density and land use type.Such cross-studies not only expand and apply GIS technology,but also enhance the research methods of air pollution diffusion simulation.The research results have certain practical guiding significance to the environmental planning and design of government departments and to the effective control and reduction of emergent environmental pollution emergency plan.This paper takes the study on PM2.5 diffusion in shuangliu district of chengdu city as an example.Firstly,the diffusion path of PM2.5 and the factors affecting the diffusion are analyzed.The main influencing factors(mainly mete orological factors,such as wind speed,temperature and pressure)are selected to establish a regression equation to analyze the correlation between PM2.5 concentration and PM2.5.Starting with gaussian diffusion model,meteorological factors were introduced to modify the diffusion coefficient.Python script function in ArcGIS was used to write the code of gaussian plume model and establish the diffusion model.Shuangliu area of point source pollution data(X,Y coor dinates and emissions)as the basic data into the diffusion model,considering(wind)in different wind speed,temperature and pressure,the research on PM2.5 pollutants to simulate the diffusion in the study area,to simulate the diffusion results are obtained,and after simulated diffusion concentration of kriging interpolation to get concentration changes of time and space,to analyze its change law.The concentration obtained from the interpolation of PM2.5 ground mon itoring station data at the same time was compared with the diffusion interpola tion results simulated by the gaussian model.The deviation between the two values was calculated and the error in the model was calculated to obtain the diffusion accuracy simulated by the gaussian model,and the reason for the deviation in the simulated diffusion was analyzed.The main research results of this paper are as follows:(1)PM2.5 concentration diffusion is affected by many factors,and meteor ological factors are one of the main factors.The correlation between meteorological factors and PM2.5 concentration was first analyzed in the study.By establishing the one-dimensional regression equation of meteorological impact factors and PM2.5 concentration,the goodness of fit between temperature and PM2.5was 0.72,the goodness of fit between wind speed and PM2.5 was 0.79,and the goodness of fit between pressure and PM2.5 was 0.77.The results show that there is a strong correlation between meteorological factors and PM2.5,and meteorological factors have a great influence on PM2.5 diffusion.Meteorological factor parameters must be considered in the establishment of PM2.5 concentration diffusion simulation model.(2)Choose gaussian plume model in the study area under certain assumptions for pollution diffusion simulation research,and based on ArcGIS Python scripts in the function of gaussian plume model code,considering the temperature,wind speed,wind direction),the pressure conditions,the diffusion coefficient,diffusion model is established and simulated emissions to the atmosphere pollutant diffusion distribution along the downwind diffusion.Gaussian model was used to obtain the simulated diffusion results of PM2.5 atmospheric pollutants based on the pollution point source data(X,Y coordinates and emissions).(3)Based on the analysis of spatial-temporal variation characteristics of PM2.5 diffusion concentration,it can be concluded that in terms of time series,PM2.5 concentration increases with the change of seasons due to the influence of temperature and wind speed.The simulated PM2.5 concentration values in the three seasons from the largest to the smallest are: > in winter,> in autumn and > in summer.Spatially,there is a certain relationship between the regional concentration and the number of pollution point sources.Due to the influence of wind speed and direction,the concentration variation law of the three seasons is consistent,and the concentration value decreases successively from the northwest region to the southeast region.(4)Consistency comparison and correlation analysis were conducted between the model diffusion results and the PM2.5 concentration monitoring value interpolation results of the monitoring station,and it was found that the change rule trend of the two was highly consistent,with a goodness of fit of 0.72,and the calculated model error was 33.7592.The reason of deviation may be from the error caused by meteorological factor measurement and the error caused by other factors not considered in the model.Through analysis,it is found that the land use factor not considered is correlated with PM2.5 concentration diffusion,and the land use factor should be added in the subsequent improvement of the model to improve the simulation accuracy.