Estimating population exposure to ambient polycyclic aromatic hydrocarbon in the United States - Part I: Model development and evaluation.
Estimating population exposure to ambient polycyclic aromatic hydrocarbon in the United States - Part I: Model development and evaluation.
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DOI：
10.1016/j.envint.2016.12.002
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发表时间：
2017-03
影响因子：
11.8
通讯作者：
Ying Q
中科院分区：
文献类型：
--
作者：
Zhang J;Li J;Wang P;Chen G;Mendola P;Sherman S;Ying Q
环境中的 PAH（多环芳烃）因其对人类健康的负面影响而备受关注。仅靠空气毒物监测网络站的 PAH 测量不足以提供环境 PAH 水平的完整情况，也不足以准确评估美国公众的暴露情况。在这项研究中，使用从现有排放概况数据库中收集的数据来准备 PAH 的形态概况，并使用稀疏矩阵算子核排放 (SMOKE) 模型生成美国 16 种优先 PAH 的网格化国家排放量。估算的排放量用于模拟 2011 年 1 月、4 月、7 月和 10 月的 PAH 环境浓度，使用修改后的社区多尺度空气质量 (CMAQ) 模型 (v5.0.1)，该模型处理 PAH 的气相和颗粒相分配及其在气相和颗粒表面的反应。 61 个空气毒物监测点的每日多环芳烃浓度预测与观测结果基本一致，对一个月的预测进行平均可以减少总体误差。最佳模型性能是在农村地区获得的，平均分数偏差 (MFB) 为 -0.03，平均分数误差 (MFE) 为 0.70。郊区和城市地点的浓度被低估，总体 MFB = -0.57，MFE = 0.89。预测的 PAH 浓度在 1 月份最高，模型性能较好（MFB = 0.12，MFE = 0.69；包括所有地点），7 月份最低，模型性能较差（MFB = -0.90，MFE = 1.08）。尽管由于当前模型中对非均相反应的处理相对简单，预计会存在显着的不确定性，但将几种 PAH 与 O3 在颗粒表面上的非均相反应纳入在内，可以减少冬季的过度预测偏差。
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 O3 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.
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影响因子：
3
作者：
Aulinger, Armin;Matthias, Volker;Quante, Markus
通讯作者：
Quante, Markus
影响因子：
5
作者：
Kahan, T. F.;Kwamena, N. -O. A.;Donaldson, D. J.
通讯作者：
Donaldson, D. J.
影响因子：
2.4
作者：
Banceu, CE;Mihele, C;Bunce, NJ
通讯作者：
Bunce, NJ
影响因子：
2.9
作者：
Bieser, Johannes;Aulinger, Armin;Quante, Markus
通讯作者：
Quante, Markus
影响因子：
4.3
作者：
ATKINSON, R;BAULCH, DL;TROE, J
通讯作者：
TROE, J