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Integration of Air Quality & Exposure Models for Health Studies
Citation:
Breen, M. Integration of Air Quality & Exposure Models for Health Studies. UK-US meeting on Air-Quality Modelling & Exposure Science, Kings College, London, UK, September 29 - 30, 2016.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Description:
The presentation describes a new community-scale tool called exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM using outdoor concentrations, questionnaires, weather, and time-location information. In this modeling approach, we linked an air exchange rate (AER) model to a PM 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). The EMI model was applied to predict daily exposure metrics (Tiers 1-5) for each participant in a cohort health study in central North Carolina. Using EMI, spatial and temporal variability of indoor infiltration, and participant’s time spent indoors information is used for exposure assessment to help improve risk estimates. The presentation also discuss the linkage between the exposure model and the Community-Scale Modeling Tools (C-TOOLS) by adding a residential infiltration model to C-Tools.