沈阳市采暖期PM_(2.5)浓度变化规律及其影响因素

Variation and influencing factors of PM_(2.5) concentration during the heating period in Shenyang

随着工业化的不断发展,主要经济发达地区的雾霾天气频发,导致大气环境日益恶化,严重影响了人们的日常生活和身体健康。本研究基于2020-2021年沈阳市城区采暖期国控环境空气质量监测点的PM_(2.5)浓度和同步的气象数据,探讨沈阳市不同环境尺度下的PM_(2.5)空间分布、时间变化规律,以及各气象因子和不同土地利用类型对PM_(2.5)浓度变化的影响。结果表明:沈阳市城区PM_(2.5)浓度呈现北低南高的空间分布;城区在采暖期间PM_(2.5)平均浓度大小依次为2021年3月>2021年1月>2021年2月>2020年12月>2020年11月;温度、相对湿度与PM_(2.5)浓度呈极显著正相关,风速与PM_(2.5)浓度呈显著负相关;在3种不同缓冲区下,绿地、水体与PM_(2.5)浓度均呈极显著负相关,广场在500m和1000m缓冲区与PM_(2.5)浓度均呈显著负相关,在2000m缓冲区呈极显著负相关;层次回归分析结果表明,温度、相对湿度和绿地对PM_(2.5)浓度的贡献度最大,这说明采暖期沈阳市雾霾天气主要受大气温湿度的影响,城市绿地、水体、广场和风可以显著降低PM_(2.5)浓度。本研究为城市雾霾天气的管理和城市规划提供了参考。

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 PM_(2.5) 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 PM_(2.5) at different environmental scales in Shenyang,as well as the influence of different meteorological factors and land use types on the variations of PM_(2.5) concentration.The results showed that PM_(2.5) concentrations in the urban areas displayed a spatial pattern of low in the north and high in the south.PM_(2.5) 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 PM_(2.5) concentrations,and wind speed was significantly negatively correlated with PM_(2.5) 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 PM_(2.5) concentrations at 500 m and 1000 m buffer scales,and significantly negatively correlated with PM_(2.5) 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 PM_(2.5) 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 PM_(2.5) concentration.This study provides a reference for urban haze weather management and urban planning in Shenyang.