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Impacts of wind fields on the distribution patterns of traffic emitted particles in urban residential areas

机译:风场对城市居民区交通排放颗粒物分布格局的影响

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摘要

Traffic emissions are a major contributor to urban atmospheric pollution. The wind fields also play an important role in the dispersion of air pollutants from the traffic emissions. However, the effects of different regional wind fields on the diffusion patterns of traffic-emitted fine particulate matter (PM2.5) in urban areas are still unclear and lack quantified measurements. To provide guidance to urban planning and design, as well as urban governance and management, it is especially important to identify the extent to which wind fields affect the diffusion of traffic emitted particles. To understand the effect, field measurements and numerical simulations were conducted in this study. The field measurements mainly focused on collecting three-dimensional (3D) distributions of concentrations of traffic-emitted particles in a student dormitory zone at a university using instrumented unmanned aerial vehicles (UAVs). The collected PM2.5 measurements were used to verify and calibrate numerical models. Then, computational fluid dynamics (CFD) simulations were used to track the progress of pollutant dispersion and evaluate its relationship to urban forms. The effects of different wind directions (northwest and southeast) on the distribution and deposition of the traffic-emitted particles in the residential area were studied under different wind velocity conditions (1 m s(-1), 5 m s(-1) and 20 m s(-1)). As efficient observation platforms, the UAVs employed in the study allowed the capture of the 3D variations in the distributions of atmospheric pollutants in urban areas. The result provides a better understanding of the dispersion of atmospheric pollutants in a specific urban built environment under different wind fields, which can support urban governance and planning and design practice leading to effective mitigation of traffic-induced air pollution in urban areas.
机译:交通排放是造成城市大气污染的主要因素。风场在交通排放中的空气污染物扩散中也起着重要作用。但是,不同区域风场对城市地区交通排放的细颗粒物(PM2.5)扩散模式的影响仍不清楚,也缺乏量化的测量方法。为了为城市规划和设计以及城市治理和管理提供指导,特别重要的是确定风场在多大程度上影响交通排放颗粒的扩散。为了了解效果,在这项研究中进行了现场测量和数值模拟。现场测量主要集中在使用无人飞行器(UAV)收集大学学生宿舍区域内交通排放颗粒浓度的三维(3D)分布。收集到的PM2.5测量值用于验证和校准数值模型。然后,使用计算流体动力学(CFD)模拟来跟踪污染物扩散的进程并评估其与城市形态的关系。研究了在不同风速条件下(1 ms(-1),5 ms(-1)和20 ms),不同风向(西北和东南)对居民区交通排放颗粒的分布和沉积的影响。 (-1))。作为有效的观测平台,研究中使用的无人机可以捕获城市地区大气污染物分布的3D变化。结果更好地了解了不同风场下特定城市建筑环境中大气污染物的扩散,这可以支持城市治理以及规划和设计实践,从而有效缓解城市地区交通引起的空气污染。

著录项

  • 来源
    《Transportation Research》 |2019年第3期|122-136|共15页
  • 作者单位

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China|Shanghai Univ Finance & Econ, Sch Publ Econ & Adm, Shanghai 200240, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China|Shanghai Jiao Tong Univ, China Inst Urban Governance, Shanghai 200240, Peoples R China|Univ Florida, Int Ctr Adaptat Planning & Design, Sch Landscape Architecture & Planning, Coll Design Construct & Planning, POB 115706, Gainesville, FL 32611 USA;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China|Fujian Agr & Forestry Univ, Coll Transportat & Civil Engn, Fuzhou 350108, Fujian, Peoples R China;

    Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, State Key Lab Ocean Engn, Ctr Intelligent Transportat Syst & Unmanned Aeria, Shanghai 200240, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Traffic emission; Wind; Three-dimensional distribution; CFD; Urban air quality; UAV;

    机译:交通排放;风;三维分布;CFD;城市空气质量;UAV;
  • 入库时间 2022-08-18 04:23:16

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