National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA.
J Expo Sci Environ Epidemiol. 2013 Nov-Dec;23(6):581-92. doi: 10.1038/jes.2013.59. Epub 2013 Sep 25.
Measurements from central site (CS) monitors are often used as estimates of exposure in air pollution epidemiological studies. As these measurements are typically limited in their spatiotemporal resolution, true exposure variability within a population is often obscured, leading to potential measurement errors. To fully examine this limitation, we developed a set of alternative daily exposure metrics for each of the 169 ZIP codes in the Atlanta, GA, metropolitan area, from 1999 to 2002, for PM(2.5) and its components (elemental carbon (EC), SO(4)), O(3), carbon monoxide (CO), and nitrogen oxides (NOx). Metrics were applied in a study investigating the respiratory health effects of these pollutants. The metrics included: (i) CS measurements (one CS per pollutant); (ii) air quality model results for regional background pollution; (iii) local-scale AERMOD air quality model results; (iv) hybrid air quality model estimates (a combination of (ii) and (iii)); and (iv) population exposure model predictions (SHEDS and APEX). Differences in estimated spatial and temporal variability were compared by exposure metric and pollutant. Comparisons showed that: (i) both hybrid and exposure model estimates exhibited high spatial variability for traffic-related pollutants (CO, NO(x), and EC), but little spatial variability among ZIP code centroids for regional pollutants (PM(2.5), SO(4), and O(3)); (ii) for all pollutants except NO(x), temporal variability was consistent across metrics; (iii) daily hybrid-to-exposure model correlations were strong (r>0.82) for all pollutants, suggesting that when temporal variability of pollutant concentrations is of main interest in an epidemiological application, the use of estimates from either model may yield similar results; (iv) exposure models incorporating infiltration parameters, time-location-activity budgets, and other exposure factors affect the magnitude and spatiotemporal distribution of exposure, especially for local pollutants. The results of this analysis can inform the development of more appropriate exposure metrics for future epidemiological studies of the short-term effects of particulate and gaseous ambient pollutant exposure in a community.
中心站点（CS）监测器的测量值通常被用作空气污染流行病学研究中暴露的估计值。由于这些测量值在时空分辨率上通常受到限制，因此人群内的真实暴露变异性通常被掩盖，导致潜在的测量误差。为了充分研究这种局限性，我们为佐治亚州亚特兰大市 169 个邮政编码中的每一个，从 1999 年到 2002 年，开发了一套替代的每日 PM（2.5）及其成分（元素碳（EC）、硫酸盐（SO4））、O3、一氧化碳（CO）和氮氧化物（NOx）的暴露度量标准。这些度量标准应用于一项研究中，该研究调查了这些污染物对呼吸健康的影响。这些度量标准包括：（i）CS 测量值（每个污染物一个 CS）；（ii）区域背景污染空气质量模型结果；（iii）局部尺度 AERMOD 空气质量模型结果；（iv）混合空气质量模型估计值（（ii）和（iii）的组合）；和（iv）人口暴露模型预测（SHEDS 和 APEX）。通过暴露度量标准和污染物比较了估计的空间和时间变异性的差异。比较表明：（i）对于与交通相关的污染物（CO、NOx 和 EC），混合模型和暴露模型估计值都表现出高空间变异性，但对于区域污染物（PM（2.5）、SO4 和 O3），在邮政编码中心之间几乎没有空间变异性；（ii）除了 NOx 之外，对于所有污染物，度量标准之间的时间变异性是一致的；（iii）对于所有污染物，每日混合到暴露模型的相关性都很强（r>0.82），这表明当污染物浓度的时间变异性是流行病学应用中的主要关注点时，使用这两种模型中的任何一种估计值都可能产生相似的结果；（iv）纳入渗透参数、时间-位置-活动预算和其他暴露因素的暴露模型会影响暴露的大小和时空分布，特别是对于局部污染物。这项分析的结果可以为未来社区中短期颗粒物和气态环境污染物暴露的短期效应的流行病学研究提供更合适的暴露度量标准。
