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