Variation and influencing factors of PM2.5 concentration during the heating period in Shenyang
With the continuous industrialization,hazy weather has occurred more and more frequently in major developed regions,which leads to the deterioration of atmospheric environment and seriously affects people's daily life and health.Based on the recorded data of PM2.5 concentration at the state controlled environmental air quality monitoring points in urban areas of Shenyang and meteorological data during the heating period of 2020-2021,we explored the spatial patterns and temporal dynamics of PM2.5 at different environmental scales in Shenyang,as well as the influence of different meteorological factors and land use types on the variations of PM2.5 concentration.The results showed that PM2.5 concentrations in the urban areas displayed a spatial pattern of low in the north and high in the south.PM2.5 concentrations during the heating period were in a decreasing order of March 2021＞January 2021＞February 2021＞December 2020＞November 2020.Temperature and relative humidity were significantly and positively correlated with PM2.5 concentrations,and wind speed was significantly negatively correlated with PM2.5 concentrations.At three different buffers,green space and water bodies were significantly negatively correla-ted with PM2.5 concentrations,squares were significantly negatively correlated with PM2.5 concentrations at 500 m and 1000 m buffer scales,and significantly negatively correlated with PM2.5 concentrations at 2000 m buffer scale.The results of hierarchical regression analysis showed that temperature,relative humidity,and green space contrib-uted the most to PM2.5 concentration,which indicates that haze weather in Shenyang during the heating period is mainly affected by temperature and humidity,and that urban green space,water body,square and wind can signifi-cantly reduce PM2.5 concentration.This study provides a reference for urban haze weather management and urban planning in Shenyang.
heating periodPM2.5meteorological factorland use typeShenyang
国家科技期刊平台
NSTL
万方数据
