Breen Michael, Chang Shih Ying, Breen Miyuki, Xu Yadong, Isakov Vlad, Arunachalam Sarav, Carraway Martha Sue, Devlin Robert
Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA.
Atmosphere (Basel). 2020 Jan 3;11(1):1-65. doi: 10.3390/atmos11010065.
Air pollution epidemiological studies often use outdoor concentrations from central-site monitors as exposure surrogates, which can induce measurement error. The goal of this study was to improve exposure assessments of ambient fine particulate matter (PM), elemental carbon (EC), nitrogen oxides (NO), and carbon monoxide (CO) for a repeated measurements study with 15 individuals with coronary artery disease in central North Carolina called the Coronary Artery Disease and Environmental Exposure (CADEE) Study. We developed a fine-scale exposure modeling approach to determine five tiers of individual-level exposure metrics for PM, EC, NO, CO using outdoor concentrations, on-road vehicle emissions, weather, home building characteristics, time-locations, and time-activities. We linked an urban-scale air quality model, residential air exchange rate model, building infiltration model, global positioning system (GPS)-based microenvironment model, and accelerometer-based inhaled ventilation model to determine residential outdoor concentrations (C, Tier 1), residential indoor concentrations (C, Tier 2), personal outdoor concentrations (C, Tier 3), exposures (E, Tier 4), and inhaled doses (D, Tier 5). We applied the fine-scale exposure model to determine daily 24-h average PM, EC, NO, CO exposure metrics (Tiers 1-5) for 720 participant-days across the 25 months of CADEE. Daily modeled metrics showed considerable temporal and home-to-home variability of C and C (Tiers 1-2) and person-to-person variability of C, E, and D (Tiers 3-5). Our study demonstrates the ability to apply an urban-scale air quality model with an individual-level exposure model to determine multiple tiers of exposure metrics for an epidemiological study, in support of improving health risk assessments.
空气污染流行病学研究通常将中心站点监测器的室外浓度用作暴露替代指标，这可能会导致测量误差。本研究的目的是改进对北卡罗来纳州中部15名冠心病患者进行的重复测量研究中环境细颗粒物（PM）、元素碳（EC）、氮氧化物（NO）和一氧化碳（CO）的暴露评估，该研究称为冠心病与环境暴露（CADEE）研究。我们开发了一种精细尺度的暴露建模方法，以使用室外浓度、道路上的车辆排放、天气、房屋建筑特征、时间地点和时间活动来确定PM、EC、NO、CO的五个层级的个体水平暴露指标。我们将城市尺度空气质量模型、住宅空气交换率模型、建筑物渗透模型、基于全球定位系统（GPS）的微环境模型和基于加速度计的吸入通风模型相链接，以确定住宅室外浓度（C，第1层级）、住宅室内浓度（C，第2层级）、个人室外浓度（C，第3层级）、暴露量（E，第4层级）和吸入剂量（D，第5层级）。我们应用精细尺度暴露模型来确定CADEE研究25个月期间720个参与者日的每日24小时平均PM、EC、NO、CO暴露指标（第1 - 5层级）。每日建模指标显示，C和C（第1 - 2层级）在时间和家庭之间存在相当大的变异性，而C、E和D（第3 - 5层级）在人与人之间存在变异性。我们的研究证明了将城市尺度空气质量模型与个体水平暴露模型相结合以确定流行病学研究中多个层级暴露指标的能力，有助于改进健康风险评估。
