Intercomparison of Six National Empirical Models for PM2.5 Air Pollution in the Contiguous US

Findings Pub Date : 2023-11-16 DOI:10.32866/001c.89423
M. Bechle, M. Bell, Daniel L. Goldberg, S. Hankey, Tianjun Lu, A. Presto, Allen L. Robinson, Joel Schwartz, Liuhua Shi, Yang Zhang, Julian D. Marshall
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Abstract

Empirical models aim to predict spatial variability in concentrations of outdoor air pollution. For year-2010 concentrations of PM2.5 in the US, we intercompared six national-scale empirical models, each generated by a different research group. Despite differences in methods and independent variables for the models, we find a relatively high degree of agreement among model predictions (e.g., correlations of 0.84 to 0.92, RMSD (root-mean-square-difference; units: μg/m3) of 0.8 to 1.4, or on average ~12% of the average concentration; many best-fit lines are near the 1:1 line).
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美国毗连地区 PM2.5 空气污染六种国家经验模型的相互比较
经验模型旨在预测室外空气污染浓度的空间变化。针对美国 2010 年 PM2.5 的浓度,我们比较了六个全国范围的经验模型,每个模型由不同的研究小组生成。尽管模型的方法和自变量不同,但我们发现模型预测之间的一致性相对较高(例如,相关性为 0.84 至 0.92,RMSD(均方根差;单位:μg/m3)为 0.8 至 1.4,或平均浓度的约 12%;许多最佳拟合线接近 1:1 线)。
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