Estimating population exposure to ambient polycyclic aromatic hydrocarbon in the United States - Part I: Model development and evaluation.
2017 Feb
Journal Article
Authors:
Zhang, J.;
Li, J.;
Wang, P.;
Chen, G.;
Mendola, P.;
Sherman, S.;
Ying, Q.
Secondary:
Environ Int
Volume:
99
Pagination:
263-274
PMID:
27988136
DOI:
10.1016/j.envint.2016.12.002
Keywords:
Air Pollutants; Air pollution; Environmental Exposure; Environmental Monitoring; Humans; Models, Theoretical; Polycyclic Aromatic Hydrocarbons; Seasons; United States
Abstract:
PAHs (polycyclic aromatic hydrocarbons) in the environment are of significant concern due to their negative impact on human health. PAH measurements at the air toxics monitoring network stations alone are not sufficient to provide a complete picture of ambient PAH levels or to allow accurate assessment of public exposure in the United States. In this study, speciation profiles for PAHs were prepared using data assembled from existing emission profile data bases, and the Sparse Matrix Operator Kernel Emissions (SMOKE) model was used to generate the gridded national emissions of 16 priority PAHs in the US. The estimated emissions were applied to simulate ambient concentration of PAHs for January, April, July and October 2011, using a modified Community Multiscale Air Quality (CMAQ) model (v5.0.1) that treats the gas and particle phase partitioning of PAHs and their reactions in the gas phase and on particle surface. Predicted daily PAH concentrations at 61 air toxics monitoring sites generally agreed with observations, and averaging the predictions over a month reduced the overall error. The best model performance was obtained at rural sites, with an average mean fractional bias (MFB) of -0.03 and mean fractional error (MFE) of 0.70. Concentrations at suburban and urban sites were underestimated with overall MFB=-0.57 and MFE=0.89. Predicted PAH concentrations were highest in January with better model performance (MFB=0.12, MFE=0.69; including all sites), and lowest in July with worse model performance (MFB=-0.90, MFE=1.08). Including heterogeneous reactions of several PAHs with O on particle surface reduced the over-prediction bias in winter, although significant uncertainties were expected due to relative simple treatment of the heterogeneous reactions in the current model.
