Natasha Hodas

Publications (2)5.86 Total impact

• Article: Influence of human activity patterns, particle composition, and residential air exchange rates on modeled distributions of PM(2.5) exposure compared with central-site monitoring data.

  Lisa K Baxter, Janet Burke, Melissa Lunden, Barbara J Turpin, David Q Rich, Kelly Thevenet-Morrison, Natasha Hodas, Halûk Ozkaynak
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  ABSTRACT: Central-site monitors do not account for factors such as outdoor-to-indoor transport and human activity patterns that influence personal exposures to ambient fine-particulate matter (PM(2.5)). We describe and compare different ambient PM(2.5) exposure estimation approaches that incorporate human activity patterns and time-resolved location-specific particle penetration and persistence indoors. Four approaches were used to estimate exposures to ambient PM(2.5) for application to the New Jersey Triggering of Myocardial Infarction Study. These include: Tier 1, central-site PM(2.5) mass; Tier 2A, the Stochastic Human Exposure and Dose Simulation (SHEDS) model using literature-based air exchange rates (AERs); Tier 2B, the Lawrence Berkeley National Laboratory (LBNL) Aerosol Penetration and Persistence (APP) and Infiltration models; and Tier 3, the SHEDS model where AERs were estimated using the LBNL Infiltration model. Mean exposure estimates from Tier 2A, 2B, and 3 exposure modeling approaches were lower than Tier 1 central-site PM(2.5) mass. Tier 2A estimates differed by season but not across the seven monitoring areas. Tier 2B and 3 geographical patterns appeared to be driven by AERs, while seasonal patterns appeared to be due to variations in PM composition and time activity patterns. These model results demonstrate heterogeneity in exposures that are not captured by the central-site monitor.Journal of Exposure Science and Environmental Epidemiology advance online publication, 16 January 2013; doi:10.1038/jes.2012.118.
  Journal of Exposure Science and Environmental Epidemiology 01/2013; · 2.93 Impact Factor
• Article: Variability in the fraction of ambient fine particulate matter found indoors and observed heterogeneity in health effect estimates.

  Natasha Hodas, Qingyu Meng, Melissa M Lunden, David Q Rich, Halûk Ozkaynak, Lisa K Baxter, Qi Zhang, Barbara J Turpin
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  ABSTRACT: Exposure to ambient (outdoor-generated) fine particulate matter (PM(2.5)) occurs predominantly indoors. The variable efficiency with which ambient PM(2.5) penetrates and persists indoors is a source of exposure error in air pollution epidemiology and could contribute to observed temporal and spatial heterogeneity in health effect estimates. We used a mass balance approach to model F for several scenarios across which heterogeneity in effect estimates has been observed: with geographic location of residence, residential roadway proximity, socioeconomic status, and central air-conditioning use. We found F is higher in close proximity to primary combustion sources (e.g. proximity to traffic) and for lower income homes. F is lower when PM(2.5) is enriched in nitrate and with central air-conditioning use. As a result, exposure error resulting from variability in F will be greatest when these factors have high temporal and/or spatial variability. The circumstances for which F is lower in our calculations correspond to circumstances for which lower effect estimates have been observed in epidemiological studies and higher F values correspond to higher effect estimates. Our results suggest that variability in exposure misclassification resulting from variability in F is a possible contributor to heterogeneity in PM-mediated health effect estimates.
  Journal of Exposure Science and Environmental Epidemiology 05/2012; 22(5):448-54. · 2.93 Impact Factor