Spatial And Temporal Distribution Of PM2.5 In Hangzhou From 2015 To 2019

In recent years,with the further advancement of China's industrialization and urbanization,the problem of air pollution has become increasingly prominent.Among them,PM2.5(fine particulate matter)pollution has attracted much attention.PM2.5 is the main pollutant in the atmosphere of Chinese cities and an important part of Hangzhou's air pollution.With the continuous strengthening of air pollution control in Hangzhou,the air quality has been greatly improved.However,the PM2.5 concentration has not yet reached the second level of the national ambient air quality standard,which needs our attention.It should be noted that there are still some deficiencies in the monitoring of PM2.5 concentration.The monitoring of PM2.5 mainly relies on the real-time monitoring of ground monitoring stations.Although the monitoring accuracy of the ground monitoring station is high,in the face of complex urban surface types and large-scale monitoring of PM2.5,the ground monitoring data is slightly weak.Corresponding to this,the spatial distribution of PM2.5 in the whole area can be obtained by remote sensing monitoring methods,which is of great help to the prevention and control of atmospheric pollution and the optimization and layout of the land-use structure.Based on the data of Hangzhou's air quality monitoring stations,this study analyzed the temporal and spatial changes of PM2.5 in Hangzhou for five consecutive years from 2015 to 2019 from multiple perspectives.In this study,remote sensing image MODIS L1 B was used for inversion to obtain the spatial distribution map of PM2.5 concentration in Hangzhou from March 2017 to February 2018.The spatial and temporal distribution characteristics of PM2.5 concentration in four seasons in Hangzhou were analyzed.And the relationship between PM2.5 and ground cover type and vegetation coverage was analyzed.The main research contents and results are as follows:(1)Based on hour-by-hour monitoring data from 11 air quality monitoring stations in Hangzhou from 2015 to 2019,this article analyzed the change rules and pollution status of PM2.5 in Hangzhou in terms of year,season,month and week.The results showed that the annual average concentration,seasonal average concentration and monthly average concentration of PM2.5 in Hangzhou decreased year by year from 2015 to 2019,while the monthly average concentration of PM2.5 changed periodically with the scale of year by year and presented a u-shaped distribution.When the weekly variation analysis was conducted,taking 2017 as an example,it was found that the PM2.5 concentration on the weekend was higher than the annual average concentration in Hangzhou city.And the PM2.5 concentration value on the weekend was higher than the average of the working day almost all day.In addition,this paper attempts to use PM2.5 site data to interpolate and obtain the spatial distribution maps of PM2.5 in Hangzhou in 2015 and 2019.(2)In this article,the MODIS L1 B data was remotely retrieved based on the V5.2algorithm,and finally the AOD spatial distribution map of Hangzhou was obtained.The AOD inversion results were verified by combining the MODIS aerosol product MYD04?3K.The decision coefficient value between AOD and MYD04?3K data reaches 0.8702.The overall inversion accuracy is high,which proves the reliability of the AOD inversion results.The AOD inversion results can be used in the next research work.(3)In this article,SPSS software was used to analyze the correlation between the concentration of PM2.5 and the AOD before and after correction in Hangzhou.The results show that after the correction of AOD,the correlation between AOD and PM2.5 is significantly higher than before the correction of AOD.The correlation was highest in winter and slightly lower in autumn.In this paper,a variety of regression models were established based on the relationship between AOD and PM2.5 concentration,and it was found that the univariate quadratic model between AOD and PM2.5 concentration had the best fitting effect in four seasons.The test accuracy of the unitary quadratic model in spring,summer,autumn and winter was relatively high.The prediction coefficients of the quadratic model of spring,summer,autumn and winter in Hangzhou were 0.6294,0.6636,0.5486 and 0.6846,respectively.(4)In this article,according to the correlation between AOD and PM2.5concentration and the optimal fitting model,the spatial distribution map of PM2.5 concentration was obtained through inversion and other treatments in main urban area of Hangzhou in four seasons.The relationship between PM2.5 and land cover type and vegetation coverage was discussed.By analyzing the spatial and temporal distribution characteristics of PM2.5 within the main urban area of Hangzhou,it was found that the PM2.5 concentration in space was relatively high in the central and eastern areas of the main urban area of Hangzhou,and relatively low in the western and southern areas.The influence of land cover type on PM2.5 concentration distribution is obvious.It was found that the PM2.5 concentration showed seasonal changes in different land cover types.The PM2.5 concentration showed the characteristics of artificial surface> water body> cultivated land> forest land on different land cover types.PM2.5 concentration has a negative correlation with vegetation coverage in all seasons.The coefficients of determination between PM2.5 and vegetation coverage in spring,summer,autumn,and winter were 0.886,0.6066,0.8403,and 0.9643,respectively.