Analysis The Spatial Distribution Of PM2.5 Of Waterfront District Based On LUR And The Correlation With The Penetration Capability Of River Wind

The pollution produced by the production of society and urban traffic will have adverse effects on the lives and health of residents.The study of the spatial distribution of pollutants in the district or the core of the city will help reduce the level of pollutant exposure of residents,improve the air quality,and provide reference for urban planning and architectural design.On the other hand,previous studies found that the clean air brought by river wind can alleviate the traffic pollution of waterfront blocks block,but it is often limited to the micro environment of the block,and the relationship between the river wind infiltration and the land use properties,development intensity and function of the block is not studied.At present,the research on the spatial distribution of pollutants mainly focuses on two scales,the macro scale research on the overall level of the city or the micro scale research on the street canyon level,that is,to simulate the spatial distribution of pollutants based on the land use regression model(LUR)and other methods on the regional or urban macro scale or the micro scale research on the street canyon based on CFD.Further research is needed to explore the mesoscale range of the region and the applicability of the method.In this study,the concentrations of CO and PM2.5 were monitored by portable monitoring instruments in Wuhan along the waterfront blocks and inland areas by fixed route from 9:30 to 11:30 a.m.and 16:30-18:30 p.m.Based on the measured data,the difference of pollutants concentration in waterfront blocks and inland is compared,and the LUR model of PM2.5 and CO in waterfront blocks and inland is established.The distribution characteristics of concentration in waterfront blocks are analyzed,and the influencing factors of pollutant concentration and the penetration of river wind are summarized.In the modeling process,the measured data are considered as dependent variables,and the factors that may affect the distribution of pollutants such as land use,meteorology,population and traffic intensity are used as prediction variables.Through the establishment of buffer zone,the main factors influencing pollutant concentration are selected.Finally,the unknown point concentration is predicted based on LUR model,and the spatial distribution of pollutant is simulated by Kriging of Arc GIS,and the spatial distribution of population exposure intensity is obtained by combining with population weighting model.In different periods of waterfront blocks and inland area,the LUR models of PM2.5and CO are established respectively.Finally,eight optimal LUR models are selected,which have good fitting degree.Among them,the R~2 of the model of PM2.5 in the morning and afternoon in the waterfront blocks area is 0.617 and 0.713 respectively,and the R~2of CO is0.577 and 0.631 respectively.Based on the analysis of the measured data,the influence range of river wind penetration is about 500m to 700m.Combined with the LUR model,it can be found that the main factors influencing the spatial distribution of PM2.5 are the spatial shape,street width,building height,public transportation and commercial land,and CO distribution is mainly related to real-time traffic flow.According to the distribution of population exposure space,the paper puts forward feasible suggestions for resident trip and urban planning,and puts forward improvement strategies for high-risk areas from the perspective of promoting river wind penetration,and designs the reconstruction of building forms and blocks,and makes the best use of the penetration effect of river wind to improve the exposure risk of high-risk areas in some parts of the city.In addition,the feasibility of establishing mesoscale LUR model by mobile monitoring is also confirmed.