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首页> 外文期刊>Environmental Science & Technology >Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffìc-Related Ultrafine Particles
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Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffìc-Related Ultrafine Particles

机译：评估与城市交通有关的超细颗粒的多种分散和土地利用回归模型的适用性

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摘要

Comparative evaluations are needed to assess the suitability of near-road air pollution models for traffic-related ultrafne particle number concentration (PNC). Our goal was to evaluate the ability of dispersion (CALINE4, AERMOD, R-LINE, and Q.UIC) and regression models to predict PNC in a residential neighborhood (Somerville) and an urban center (Chinatown) near highways in and near Boston, Massachusetts. PNC was measured in each area, and models were compared to each other and measurements for hot (>18 °C) and cold (<10 °C) hours with wind directions parallel to and perpendicular downwind from highways. In Somerville, correlation and error statistics were typically acceptable, and all models predicted conœntration gradients extending ～100 m from the highway. In contrast, in Chinatown, PNC trends differed among models, and predictions were poorly correlated with measurements likely due to effects of street canyons and nonhighway particle sources. Our results demonstrate the importance of selecting PNC models that align with study area characteristics (e.g., dominant sources and building geometry). We applied widely available models to typical urban study areas； therefore, our resuilts should be generalizable to models of hourly averaged PNC in similar urban areas.
机译：需要进行比较评估，以评估近路空气污染模型对与交通有关的超微粒子浓度（PNC）的适用性。我们的目标是评估色散能力（CALINE4，AERMOD，R-LINE和Q.UIC）和回归模型，以预测波士顿附近及附近高速公路附近的居民区（Somerville）和城市中心（唐人街）的PNC，马萨诸塞州。在每个区域对PNC进行了测量，并将模型进行了比较，并测量了在炎热（> 18°C）和寒冷（<10°C）小时下的风向与高速公路平行且垂直于顺风。在萨默维尔，相关性和误差统计量通常是可以接受的，并且所有模型都预测从高速公路延伸约100 m的构造梯度。相比之下，在唐人街，PNC趋势在模型之间有所不同，并且预测与测量的相关性很差，这可能是由于街道峡谷和非高速公路粒子源的影响。我们的结果证明了选择与研究区域特征（例如主要来源和建筑物几何形状）相符的PNC模型的重要性。我们将广泛可用的模型应用于典型的城市研究区域；因此，我们的研究结果应该可以推广到类似城市地区的每小时平均PNC模型。

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  • 来源
    《Environmental Science & Technology》 |2017年第1期|384-392|共9页
  • 作者

    Allison P. Patton; Chad Milando; John L. Durant; Prashant Kumar;

  • 作者单位

    EnvironmentaI and Occupational Health Sciences Institute, Rutgers University, Piscataway, New Jersey 08901, United States,Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States;

    Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States,Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States;

    Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts 02155, United States;

    Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences (FEPS), University of Surrey, Guildford GU2 7XH, Surrey United Kingdom,Environmental Flow (EnFlo) Research Centre, FEPS, University of Surrey, Guildford GU2 7XH, United Kingdom;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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