The Influence Of Urban Green Landscape Pattern On PM_2.5 And PM₁₀

This paper is based on the 2018 meteorological data of Xuzhou City,PM_2.5and PM₁₀data of 7 national monitoring stations,and draws a buffer zone within a radius of 1km,2km,and 3km centered on 7 monitoring points.The remote sensing images in the buffer zone are imported into Arc GIS.To obtain land use information in the buffer zone by visual interpretation,the land use types are divided into:urban green land,agricultural land,construction land,transportation land,water area and unused land.Fragstats software was used to calculate the greenland landscape pattern index（PLAND,LPI,SHAPE＿AM,DIVISION）at each scale.Combined with EXCEL and SPSS software,the temporal and spatial distribution characteristics of PM_2.5and PM₁₀,their relationship with meteorological factors,and the correlation between urban green space landscape patterns at different scales and the concentrations of PM_2.5and PM₁₀were analyzed.The results show:（1）The concentrations of PM_2.5and PM₁₀in the main urban area of Xuzhou city vary greatly throughout the year,and the concentrations of both are the lowest in summer and the highest in winter.The concentration values of the two according to seasons are:winter>spring>autumn>summer.The main reason for this is that the high temperature and rain in summer are conducive to the diffusion of atmospheric pollutants,and the cold and dry in winter slows the diffusion of atmospheric particulate matter.（2）The concentrations of PM_2.5and PM₁₀fluctuate due to changes in meteorological factors.When the temperature and wind speed increase,the concentrations of PM_2.5and PM₁₀decrease accordingly,mainly because the atmospheric structure is unstable due to temperature rise Conducive to the diffusion of atmospheric pollutants,the increase in wind speed also accelerates the transfer and dilution of particulate matter.When the air pressure increases,the concentrations of PM_2.5and PM₁₀also increase.When the air pressure increases,the temperature decreases,the atmospheric structure becomes stable,the wind speed near the ground becomes smaller,and the atmospheric pollutants enter and leave less.PM_2.5and PM₁₀concentrations remained high.（3）The concentrations of PM_2.5and PM₁₀are more sensitive to the type of land use.Greenland,agricultural land,and water areas as the"sink landscape"of PM_2.5can reduce the concentration of PM_2.5."Source landscape"of PM_2.5,their area will also increase PM_2.5concentration.There is a seasonal difference between the concentration of agricultural land and PM₁₀.In winter and spring,agricultural land will reduce the concentration of PM₁₀,and in summer and autumn will increase the concentration of PM₁₀.Burning will increase regional PM₁₀concentration（4）There are seasonal and scale differences in the response of PM_2.5and PM₁₀concentrations to the landscape pattern of greenland.Generally speaking,the landscape area ratio（PLAND）,greenland maximum patch index（LPI）,and area weighting of greenfield patches The average plaque shape index（SHAPE＿AM）has a significant negative correlation with PM_2.5and PM₁₀,and a significant positive correlation with the landscape segmentation index（DIVISION）.Increasing the landscape area ratio of green patches and the area of?green patches can effectively reduce the concentration of fine particles in the area.The smaller the size of the green patch,the more complex the shape,and the stronger its ability to hold dust.The higher the connectivity of greenfield patches,the more favorable it is to form ventilation corridors and the faster it is to accelerate the diffusion of particulate matter.（5）Multivariate stepwise regression method was used to obtain the optimal regression model affecting the changes in PM_2.5and PM₁₀concentrations.The results showed that the PLAND and LPI indexes had the greatest influence on the changes of PM_2.5concentrations,and LPI and DIVISION had the greatest influence on the changes of PM₁₀concentrations.