A comparison of exposure metrics for traffic-related air pollutants: application to epidemiology studies in Detroit, Michigan.
A comparison of exposure metrics for traffic-related air pollutants: application to epidemiology studies in Detroit, Michigan.
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DOI：
10.3390/ijerph110909553
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发表时间：
2014-09-15
影响因子：
--
通讯作者：
Robins T
中科院分区：
文献类型：
--
作者：
Batterman S;Burke J;Isakov V;Lewis T;Mukherjee B;Robins T
车辆是空气污染物排放的主要来源，居住在大马路附近的个人承受着与交通有关的空气污染物的高暴露和健康风险。空气污染流行病学、健康风险、环境正义和交通规划研究都将受益于更好地了解评估暴露所需的关键信息和指标，以及替代暴露指标的优势和局限性。本研究开发并评估了在底特律（美国密歇根州）进行的NEXUS流行病学研究参与者的218个居住地暴露于交通相关空气污染物的几个指标。暴露指标包括靠近主要道路、交通量、车辆组合、交通密度、车辆废气排放密度和分散模型预测的污染物浓度。每个指标的结果包括暴露分布、空间变异性、类内相关性、一致性和不一致性率以及总体优势和局限性的比较。虽然显示出一些一致性，但简单的分类和接近性分类（例如，高柴油/低柴油交通道路和与主要道路的距离）并不能反映其他指标中所见的暴露范围和重叠。交通密度指标（定义为每个家庭周围300米缓冲区内每天行驶的公里数（VKT））提供的信息与更复杂的指标相当一致。分散模型提供了空间和时间分辨的浓度，以及分离由交通排放和其他来源引起的浓度的分摊。虽然几种暴露指标显示出广泛的一致性，包括交通密度、排放密度和模拟浓度，但这些替代方案仍然产生了很大一部分研究参与者的暴露分类，例如，根据指标，从20%到50%的家庭将被错误地分为“低”、“中”或“高”交通暴露等级。这些和其他结果表明可能存在暴露错误分类，需要改进和验证暴露指标。虽然交通排放分散建模的数据和计算需求是非常重要的问题，但一旦建立，分散建模系统可以为道路上和道路附近的环境提供暴露信息，这将有利于未来的交通相关评估。
Vehicles are major sources of air pollutant emissions, and individuals living near large roads endure high exposures and health risks associated with traffic-related air pollutants. Air pollution epidemiology, health risk, environmental justice, and transportation planning studies would all benefit from an improved understanding of the key information and metrics needed to assess exposures, as well as the strengths and limitations of alternate exposure metrics. This study develops and evaluates several metrics for characterizing exposure to traffic-related air pollutants for the 218 residential locations of participants in the NEXUS epidemiology study conducted in Detroit (MI, USA). Exposure metrics included proximity to major roads, traffic volume, vehicle mix, traffic density, vehicle exhaust emissions density, and pollutant concentrations predicted by dispersion models. Results presented for each metric include comparisons of exposure distributions, spatial variability, intraclass correlation, concordance and discordance rates, and overall strengths and limitations. While showing some agreement, the simple categorical and proximity classifications (e.g., high diesel/low diesel traffic roads and distance from major roads) do not reflect the range and overlap of exposures seen in the other metrics. Information provided by the traffic density metric, defined as the number of kilometers traveled (VKT) per day within a 300 m buffer around each home, was reasonably consistent with the more sophisticated metrics. Dispersion modeling provided spatially- and temporally-resolved concentrations, along with apportionments that separated concentrations due to traffic emissions and other sources. While several of the exposure metrics showed broad agreement, including traffic density, emissions density and modeled concentrations, these alternatives still produced exposure classifications that differed for a substantial fraction of study participants, e.g., from 20% to 50% of homes, depending on the metric, would be incorrectly classified into “low”, “medium” or “high” traffic exposure classes. These and other results suggest the potential for exposure misclassification and the need for refined and validated exposure metrics. While data and computational demands for dispersion modeling of traffic emissions are non-trivial concerns, once established, dispersion modeling systems can provide exposure information for both on- and near-road environments that would benefit future traffic-related assessments.
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DOI：
10.1038/sj.jea.7500074
发表时间：
2000-01-01
期刊：
JOURNAL OF EXPOSURE ANALYSIS AND ENVIRONMENTAL EPIDEMIOLOGY
影响因子：
--
作者：
Huang, YL;Batterman, S
通讯作者：
Batterman, S
DOI：
10.3155/1047-3289.58.3.451
发表时间：
2008-03-01
影响因子：
2.7
作者：
Cook, Rich;Isakov, Vlad;Ensley, Darrell
通讯作者：
Ensley, Darrell
影响因子：
5
作者：
Allen, Ryan W.;Amram, Ofer;Brauer, Michael
通讯作者：
Brauer, Michael
影响因子：
11.4
作者：
Apte, Joshua S.;Bombrun, Emilie;Marshall, Julian D.;Nazaroff, William W.
通讯作者：
Nazaroff, William W.
DOI：
10.3155/1047-3289.58.7.865
发表时间：
2008-07-01
影响因子：
2.7
作者：
Baldauf, Richard;Thoma, Eben;Bang, John
通讯作者：
Bang, John