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首页> 外文学位 >Regional Scale Dispersion Modeling and Analysis of Directly Emitted Fine Particulate Matter from Mobile Source Pollutants Using AERMOD.
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Regional Scale Dispersion Modeling and Analysis of Directly Emitted Fine Particulate Matter from Mobile Source Pollutants Using AERMOD.

机译：使用AERMOD对移动源污染物直接排放的细颗粒物进行区域尺度扩散建模和分析。

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摘要

A large and growing body of literature associates proximity to major roadways with increased risk of many negative health outcomes and suggests that exposure to fine particulate matter may be a substantial factor. Directly emitted and non-reactive mobile source air pollutants such as directly emitted fine particulate matter can form large spatial concentration gradients along major roadways, in addition to causing significantly large temporal and seasonal variation in air pollutant concentrations within urban areas. Current modeling and regulatory approaches for minimizing exposure have limited spatial resolution and do not fully exploit the available data.;The objective is to establish a methodology for quantifying fine particulate matter concentration gradients due to mobile source pollutants and to estimate the resulting population exposure at a regional scale. A novel air dispersion modeling framework is proposed using the Environmental Protection Agency's regulatory model AERMOD with data from a regional travel demand model that can produce a high resolution concentration surface for a considerably large metropolitan area; in our case, Los Angeles County, California.;We find that PM2.5 concentrations are highest and most widespread during the morning and evening commutes, particularly during the winter months. This is likely caused by a combination of stable atmospheric conditions during the early morning and after sunset in the evening and higher traffic volumes during the morning and evening commutes. During the midday hours concentrations are at their lowest even though traffic volumes are still much higher than during the evening. This is likely the result of heating during the day time which leads to unstable atmospheric conditions that cause more vertical mixing and lateral dispersion, reducing ground level PM2.5 concentrations by transport and dilution. With respect to roadway centerlines, PM2.5 concentrations drop off quickly, reaching relatively low concentrations between 150m to 200m from the center line of high volume roads. However, during stable atmospheric conditions (e.g., nighttime & winter season) concentrations remain elevated at distances up to 1,000m from roadway centerlines. We will demonstrate the feasibility of our methodology and how integrating the dispersion modeling framework into the travel demand modeling process routinely performed when developing and analyzing regional transportation improvement initiatives can lead to more environmentally and financially sustainable transportation plans. Regional strategies that minimize exposure, rather than inventories, could be established, environmental justice concerns are easily identified, and projects likely to cause local pollution "hotspots" can be proactively screened out, saving time and money for the transportation agency.
机译：大量且不断增长的文献将接近主要道路与许多负面健康后果的风险增加联系起来，并表明接触细颗粒物可能是一个重要因素。直接排放的和非反应性移动源空气污染物（例如直接排放的细颗粒物）会在主要道路上形成较大的空间浓度梯度，此外还会导致市区内空气污染物浓度的明显时空变化。当前用于使暴露最小化的建模和管理方法空间分辨率有限，不能充分利用现有数据。目标是建立一种量化由于移动源污染物引起的细颗粒物浓度梯度的方法，并估计由此导致的人口暴露。区域规模。使用环境保护局的管制模型AERMOD，结合区域旅行需求模型的数据，提出了一个新颖的空气扩散模型框架，该模型可以为相当大的都市区域产生高分辨率的浓度表面；在我们的案例中，是加利福尼亚州的洛杉矶县。；我们发现PM2.5浓度在上下班通勤期间最高，分布最广，尤其是在冬季。这可能是由于清晨和傍晚日落之后的稳定大气条件以及早晚上下班的交通流量的综合原因。在中午时段，尽管交通量仍然比晚上高得多，但浓度仍处于最低水平。这很可能是白天加热导致的结果，导致不稳定的大气条件，导致更多的垂直混合和横向分散，通过运输和稀释降低了地面PM2.5浓度。就道路中心线而言，PM2.5浓度迅速下降，距大容量道路中心线150m至200m之间的浓度相对较低。但是，在稳定的大气条件下（例如夜间和冬季），距道路中心线的最大距离为1000m时，浓度仍会升高。我们将论证我们方法论的可行性，以及在开发和分析区域交通改善计划时将色散建模框架整合到例行执行的旅行需求建模过程中，从而可以制定出更具环境和财务可持续性的运输计划。可以建立将暴露量最小化而不是清单最小化的区域策略，可以轻松地识别环境正义问题，并可以主动筛选出可能造成局部污染“热点”的项目，从而为运输机构节省时间和金钱。

著录项

  • 作者

    Contreras, Seth Daniel.;

  • 作者单位

    University of California, Irvine.;

  • 授予单位 University of California, Irvine.;
  • 学科 Transportation.;Climate Change.;Health Sciences Public Health.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 130 p.
  • 总页数 130
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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