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Dynamic prediction of PM2.5 diffusion in urban residential areas in severely cold regions based on an improved urban canopy model
Sustainable Cities and Society ( IF 10.5 ) Pub Date : 2020-06-24 , DOI: 10.1016/j.scs.2020.102352
Ye Xiao , Jianjian Zhao , Huan Liu , Lina Wang , Mingzhou Yu , Jing Liu

Problems related to air pollution have become more serious over the past few years, and air particulates have attracted attention as one of the most significant air pollutants. The air quality in residential areas is closely related to human health, as urban residents spend most of their time here. Because of the unique climatic characteristics of cities in severely cold regions, their urban energy structure, underlying surface, and architectural form are different from other cities to a certain degree, which causes distinctive particulate pollution characteristics. This study establishes a urban local-scale particle diffusion model for cities in severely cold regions and investigates the particle diffusion process and vertical concentration distribution in a residential area through simulation. The simulation results show that the near-ground PM2.5 mass concentrations are significantly affected by traffic flow. The vertical distribution of PM2.5 mass concentrations in residential areas demonstrates a decreasing trend with an increase in height owing to the effect of vehicle emissions and fugitive road dust. This study systematically studies the vertical distribution of particulate matter in urban settlements in severely cold regions and provides a theoretical basis and technical support for further improving the air quality of such urban settlements.



中文翻译:

基于改进的城市冠层模型的重寒地区城市居民区PM 2.5扩散动态预测

在过去的几年中,与空气污染有关的问题变得更加严重,并且空气颗粒作为最重要的空气污染物之一已引起人们的关注。由于城市居民大部分时间都在这里居住,因此居住区的空气质量与人类健康密切相关。由于严寒地区城市的独特气候特征,其城市能源结构,下垫面和建筑形式在一定程度上与其他城市不同,造成了独特的颗粒物污染特征。本研究为重度寒冷地区的城市建立了城市局部尺度的颗粒扩散模型,并通过模拟研究了居民区的颗粒扩散过程和垂直浓度分布。仿真结果表明,近地面PM2.5质量浓度受交通流量的影响很大。居民区PM 2.5质量浓度的垂直分布显示出下降趋势,随着车辆排放和逃逸的道路扬尘的影响,高度增加。该研究系统地研究了严寒地区城市居民点颗粒物的垂直分布,为进一步改善城市居民点的空气质量提供了理论基础和技术支持。

更新日期:2020-06-24
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