Research On The Spatial And Temporal Distribution Pattern Of Urban Air Pollutants And Lts Influencing Factors

While urbanization drives economic growth,it also brings environmental pollution problems,which directly affects regional sustainable development,and urban air pollution has become a hot issue of concern for scholars at home and abroad.Urban air pollution is influenced by multiple factors such as the distribution of pollution sources,meteorological conditions,industrial and agricultural production and urban spatial structure.Based on the perspective of urban planning,this thesis mainly studies the spatial and temporal patterns of urban gaseous pollutants and the influence of urban spatial structure on their distribution.Buildings are the main constituents of urban spatial structure,and their three-dimensional spatial pattern affects the meteorological conditions and thus the spatial distribution of urban air pollutant（PM10,PM2.5,SO₂,NO₂,CO,O₃）concentrations.This thesis takes the central urban area of Jinan as the study area,constructs the urban spatial structure index system based on DEM,urban road network and building big data,and uses the daily average air pollutant values recorded at 74 environmental monitoring stations in the central urban area of Jinan in 2020 to draw box line diagrams to explore the spatial and temporal distribution characteristics of air pollutants;uses one-way ANOVA and multi-way ANOVA methods to investigate the effects of single and multiple indicators on the spatial structure of the city,respectively.The spatial regression models,such as spatial lag,spatial error,spatial Durbin and geographically weighted regression,were used to study the influence of urban spatial structure indicators on the distribution of gaseous pollutant concentrations and their spatial heterogeneity.The results show that:（1）the monthly average of PM2.5,CO,and SO₂ concentrations in the central city of Jinan shows a"U-shaped"trend,with serious pollution in winter and light pollution in summer;the monthly average of O₃ concentration shows an inverted"V-shaped"trend,with serious pollution in summer and light pollution in winter;the concentrations of the six pollutants have certain weekly variation characteristics,and O₃ concentration is subject to relatively large weekly variation.The concentration of six pollutants has certain weekly variation characteristics,O₃ concentration is subject to relatively large weekly variation,and the four pollutants PM10,PM2.5,CO,and NO₂ have the lowest concentration on Tuesday of a week;there are obvious spatial and temporal differences in the concentration of pollutants in the central city of Jinan,with a complex uneven distribution.（2）The influence of urban spatial structure indicators on the concentration distribution of six gaseous pollutants is significant,and most of the single-factor spatial structure indicators reach a significance level of 0.001 on pollutant concentrations,which is extremely significant;the interaction between topographic elevation and other urban spatial distribution indicators is an important factor affecting the distribution of gaseous pollutant concentrations,and most of its two-factor ANOVA results reach a significance level of 0.05 The interaction of DEM mean,building height means and building volume standard deviation on PM10,NO₂,and O₃ concentration distribution is significant,all of them reach 0.01level of significance,while the interaction of the other three factors has no significant effect on the concentration distribution of the six pollutants.（3）In terms of global correlation,the correlation between urban spatial structure indicators and different air pollutant concentrations has strong significance;in terms of local correlation,the correlation between urban spatial structure indicators and pollutant concentrations in different months are all different and have obvious seasonality,with the strongest effect of urban spatial structure indicators on pollutant concentrations in winter and the weakest in summer.The 1D height index is an important indicator affecting PM2.5,SO₂,and NO₂ concentrations,and the 1D height index and 3D spatial index are important indicators affecting PM10,CO,and O₃ concentrations;the concentrations of five pollutants,PM10,PM2.5,SO₂,NO₂,and CO,are negatively correlated with each urban spatial structure index in each month of 2020,while O₃ concentrations are positively correlated,in contrast to O₃ is positively correlated with the other five pollutants.（4）The spatial distribution of PM10,PM2.5,and CO concentrations are mainly influenced by the indicators of urban spatial distribution in this study unit,and the influence between PM10,PM2.5,and CO concentrations in neighboring study units is the result of the action of stochastic factors,while SO₂,NO₂,and O₃ concentrations are influenced by the indicators of urban spatial distribution in this study unit,the same indicators in neighboring areas and the concentrations of SO₂,NO₂,and O₃.（5）There is spatial heterogeneity in the effects of urban spatial structure indicators on the concentrations of different pollutants.the GWR models of PM10,PM2.5,NO₂,and O₃ concentrations and urban spatial structure indicators fit well globally and locally;the regression coefficients of each urban structure indicator in the GWR models constructed for PM10,PM2.5,and NO₂ concentrations differ,and the overall trend distribution is roughly the same.The positive and negative regression coefficients of each urban spatial distribution index for O₃ concentration are opposite to the other three pollutants,and the urban spatial distribution indexes have different effects on different pollutant concentrations.The results of this study can provide a reference for mitigating air pollutant concentrations by optimizing urban spatial structure,and provide a reference basis for preventing air pollution and improving the urban ecological environment.