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1.14 Comparing Models/Methods for Estimating Multi-pollutant Fine-Scale Air Quality Concentrations

机译:1.14比较模型/方法估算多污染物细尺空气质量浓度

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摘要

Photochemical models are commonly used in regulatory and policy assessments to estimate pollutant concentrations and deposition of both inert and chemically reactive pollutants over large spatial scales. These models are generally run for horizontal grid resolutions of 36 and 12 km. However, several recent assessments have revealed the need for air quality predictions at resolutions finer than 12 km to resolve important local-scale gradients in pollutant concentrations. Given this need, we are undertaking a study to investigate several methods that can be used to obtain local-scale air quality concentrations. This study looks at the application and evaluation of a variety of models including CMAQ, CAMx and AERMOD. In addition, we will also evaluate the use of a new method called the Multiplicative Approach to the Hybrid Method (MAHM), which combines CMAQ and AERMOD predicted concentrations to generate local-scale air quality predictions. To do this, these models/methods are applied at ≤ 4 km resolution for both a winter and summer month in the same local area: Detroit, MI. The study looks at model/method performance of PM_(2.5), O_3, and several toxic pollutants by comparing modeled versus ambient measured concentrations. Resources for implementation of each model/method are also evaluated.
机译:光化学模型通常用于监管和政策评估,以估算污染物浓度,并在大型空间尺度上估算惰性和化学反应性污染物。这些模型通常为36和12公里的水平网格分辨率运行。然而,最近的几项评估揭示了在污染物浓度的重要局部级别梯度中达到12公里的决议,以确定污染物浓度的重要型梯度需要空气质量预测的需求。鉴于这种需要,我们正在进行一项研究以调查几种可用于获得本地尺度空气质量浓度的方法。本研究介绍了各种型号的应用和评估,包括CMAQ,CAMX和AERMOD。此外,我们还将评估使用称为乘法方法(MAHM)的乘法方法的新方法(MAHM),其结合了CMAQ和Aermod预测浓度来产生局部尺度的空气质量预测。为此,这些模型/方法适用于同一地区冬季和夏季的≤4公里分辨率:底特律,MI。该研究通过比较建模与环境测量浓度,看了PM_(2.5),O_3和几种有毒污染物的模型/方法性能。还评估了用于实现每个型号/方法的资源。

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