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Application and evaluation of two model fusion approaches to obtain ambient air pollutant concentrations at a fine spatial resolution (250m) in Atlanta
Environmental Modelling & Software ( IF 4.9 ) Pub Date : 2018-06-14 , DOI: 10.1016/j.envsoft.2018.06.008
Josephine T. Bates , Audrey Flak Pennington , Xinxin Zhai , Mariel D. Friberg , Francesca Metcalf , Lyndsey Darrow , Matthew Strickland , James Mulholland , Armistead Russell

Epidemiologic studies rely on accurately characterizing spatiotemporal variation in air pollutant concentrations. This work presents two model fusion approaches that use publicly available chemical transport simulations, dispersion model simulations, and observations to estimate air pollutant concentrations at a neighborhood-level spatial resolution while incorporating comprehensive chemistry and emissions sources. The first method is additive and the alternative method is multiplicative. These approaches are applied to Atlanta, GA at a 250 m grid resolution to obtain daily 24-hr averaged PM2.5 and 1-hr max CO and NOx concentrations during the years 2003–2008 for use in health studies. The modeled concentrations provide comprehensive estimates with steep spatial gradients near roadways, secondary formation and loss, and effects of regional sources that can influence daily variation in ambient pollutant concentrations. Results show high temporal and spatial correlation and low biases across monitors, providing accurate pollutant concentration estimates for epidemiologic analyses.



中文翻译:

在亚特兰大以精细空间分辨率(250m)获得大气污染物浓度的两种模型融合方法的应用和评估

流行病学研究依赖于准确表征空气污染物浓度的时空变化。这项工作提出了两种模型融合方法,这些方法使用公开可用的化学迁移模拟,扩散模型模拟和观测值,以邻域级的空间分辨率估算空气污染物的浓度,同时结合了全面的化学和排放源。第一种方法是加法,另一种方法是乘法。这些方法以250 m的网格分辨率应用于佐治亚州亚特兰大,以获取每日24小时平均PM 2.5以及在2003-2008年间用于健康研究的一小时最大CO和NOx浓度。建模浓度提供了巷道附近陡峭的空间梯度,二次形成和损失以及可能影响环境污染物浓度每日变化的区域源的影响的综合估计。结果表明,各个监测器之间的时间和空间相关性很高,偏差也很低,为流行病学分析提供了准确的污染物浓度估算。

更新日期:2018-06-14
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