Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina

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• 作者：Michael S. Breen ; Thomas C. Long ; Bradley D. Schultz ; Ronald W. Williams ; Jennifer Richmond-Bryant ; Miyuki Breen ; John E. Langstaff ; Robert B. Devlin ; Alexandra Schneider ; Janet M. Burke ; Stuart A. Batterman ; Qing Yu Meng
• 刊名：Environmental Science & Technology
• 出版年：2015
• 出版时间：December 15, 2015
• 年：2015
• 卷：49
• 期：24
• 页码：14184-14194
• 全文大小：570K
• ISSN：1520-5851

文摘

Air pollution health studies of fine particulate matter (diameter 鈮?.5 渭m, PM_2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM_2.5 and time indoors can induce exposure errors. We developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM_2.5 using outdoor concentrations, questionnaires, weather, and time-location information. We linked a mechanistic air exchange rate (AER) model to a mass-balance PM_2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), personal exposure factors (Tier 4), and personal exposures (Tier 5) for ambient PM_2.5. Using cross-validation, individual predictions were compared to 591 daily measurements from 31 homes (Tiers 1鈥?) and participants (Tiers 4鈥?) in central North Carolina. Median absolute differences were 39% (0.17 h^鈥?) for Tier 1, 18% (0.10) for Tier 2, 20% (2.0 渭g/m³) for Tier 3, 18% (0.10) for Tier 4, and 20% (1.8 渭g/m³) for Tier 5. The capability of EMI could help reduce the uncertainty of ambient PM_2.5 exposure metrics used in health studies.