Validation of a Novel Air Toxic Risk Model with Air Monitoring
Validation of a Novel Air Toxic Risk Model with Air Monitoring
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DOI：
10.1111/j.1539-6924.2011.01640.x
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发表时间：
2012-01-01
期刊：
影响因子：
3.8
通讯作者：
The, Jesse
中科院分区：
文献类型：
--
作者：
Pratt, Gregory C.;Dymond, Mary;The, Jesse
三个建模系统被用来估计空气污染对人类健康的风险：两个版本的MNRiskS（明尼苏达州风险筛查）和美国环保局国家空气毒性评估（NATA）。MNRiskS是一个独特的累积风险建模系统，用于评估当地到全州范围内多种空气毒物、来源和途径的风险。此外，环境室外空气监测数据可用于估计风险和与空气浓度的模拟估计值进行比较。最高的空气浓度和估计的风险通常出现在明尼阿波利斯-圣保罗大都市地区，最低的风险出现在不发达的农村地区。来自移动的和区域（非点源）源的排放比来自点源的排放产生更大的估计风险。最高的癌症风险是通过摄入途径接触二恶英和相关化合物。柴油颗粒、丙烯醛和甲醛对人体健康的影响最大。模型估计的空气浓度一般最高的NATA和最低的AERMOD版本的MNRiskS。该验证研究表明，现有的测量和模型预测之间的合理协议，虽然结果不同的污染物，预测往往低于测量。研究结果增加了识别污染物、途径、地理区域、来源和潜在关注受体的信心，从而为污染减排战略提供了依据，并将工作重点放在特定污染物（柴油颗粒、丙烯醛和甲醛）、地理区域（城市中心）和来源类别（非点源）上。这一结果加剧了人们对食物链暴露于二恶英和多环芳烃的风险的担忧。风险估计对处理排放、扩散、沉积、接触和毒性的方法的变化很敏感。
Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity.