Lupo Philip J, Symanski Elaine
Division of Epidemiology and Disease Control, The University of Texas School of Public Health, Houston, TX 77030, USA.
J Air Waste Manag Assoc. 2009 Nov;59(11):1278-86. doi: 10.3155/1047-3289.59.11.1278.
Often, in studies evaluating the health effects of hazardous air pollutants (HAPs), researchers rely on ambient air levels to estimate exposure. Two potential data sources are modeled estimates from the U.S. Environmental Protection Agency (EPA) Assessment System for Population Exposure Nationwide (ASPEN) and ambient air pollutant measurements from monitoring networks. The goal was to conduct comparisons of modeled and monitored estimates of HAP levels in the state of Texas using traditional approaches and a previously unexploited method, concordance correlation analysis, to better inform decisions regarding agreement. Census tract-level ASPEN estimates and monitoring data for all HAPs throughout Texas, available from the EPA Air Quality System, were obtained for 1990, 1996, and 1999. Monitoring sites were mapped to census tracts using U.S. Census data. Exclusions were applied to restrict the monitored data to measurements collected using a common sampling strategy with minimal missing values over time. Comparisons were made for 28 HAPs in 38 census tracts located primarily in urban areas throughout Texas. For each pollutant and by year of assessment, modeled and monitored air pollutant annual levels were compared using standard methods (i.e., ratios of model-to-monitor annual levels). Concordance correlation analysis was also used, which assesses linearity and agreement while providing a formal method of statistical inference. Forty-eight percent of the median model-to-monitor values fell between 0.5 and 2, whereas only 17% of concordance correlation coefficients were significant and greater than 0.5. On the basis of concordance correlation analysis, the findings indicate there is poorer agreement when compared with the previously applied ad hoc methods to assess comparability between modeled and monitored levels of ambient HAPs.
在评估有害空气污染物（HAPs）对健康的影响的研究中，研究人员通常依靠环境空气水平来估计暴露情况。两个潜在的数据源是美国环境保护局（EPA）全国人口暴露评估系统（ASPEN）的模型估计值和监测网络的环境空气污染物测量值。目标是使用传统方法和一种以前未被利用的方法——一致性相关性分析，对德克萨斯州HAPs水平的模型估计值和监测估计值进行比较，以便更好地为有关一致性的决策提供信息。从EPA空气质量系统获得了1990年、1996年和1999年德克萨斯州所有HAPs的普查区层面的ASPEN估计值和监测数据。利用美国人口普查数据将监测点映射到普查区。进行了排除，将监测数据限制为使用共同采样策略收集的测量值，且随着时间推移缺失值最少。对主要位于德克萨斯州城市地区的38个普查区中的28种HAPs进行了比较。对于每种污染物和每年的评估，使用标准方法（即模型年度水平与监测年度水平的比率）比较模型和监测的空气污染物年度水平。还使用了一致性相关性分析，该分析评估线性和一致性，同时提供一种正式的统计推断方法。模型与监测值中位数的48%落在0.5至2之间，而只有17%的一致性相关系数显著且大于0.5。基于一致性相关性分析，研究结果表明，与之前用于评估环境HAPs模型水平和监测水平之间可比性的临时方法相比，一致性较差。
