Modeling of the Penetration of Ambient PM2.5 to Indoor Residential Microenvironment

Epidemiologic studies have demonstrated a positive relationship between ambient fine particulate matter (PM2.5) and adverse health effects. Past research indicates that the indoor residential PM2.5 exposure has the highest influence on total PM2.5 exposure compared to other microenvironments. Hence the characterization of the penetration of ambient PM2.5 into the indoor residential microenvironment and indoor sources of PM2.5, is critical for PM2.5 exposure assessment. The Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model developed by the U. S. Environmental Protection Agency is a probabilistic tool to estimate the population distribution of PM2.5 exposures. This study provides a critical assessment of the data and methodology used in SHEDS-PM to estimate indoor residential PM2.5 exposure. The SHEDS-PM algorithms are evaluated and compared to best practices. The default input data are reviewed and more recent and comprehensive data are identified in order to represent regional and seasonal variations. A sensitivity analysis of the SHEDS-PM residential indoor model indicates that air exchange rate, deposition rate and penetration factor affect indoor PM2.5 concentration strongly, whereas indoor volume is less sensitive. The mass balance approach in SHEDS-PM for estimating indoor residential PM2.5 concentration is based on the assumption that an entire residence is a single, well-mixed compartment. This assumption is evaluated by applying an indoor air quality model, RISK to compare ambient PM2.5 penetration for singlecompartment and multi-compartment scenarios, and to consider sensitivity of results for indoor emission sources such as cooking and smoking. Emissions from smoking increased the indoor PM2.5 significantly, compared to cooking. In case of no indoor sources, the difference between single and multi-compartment PM2.5 concentration was less significant. Recommendations are made regarding the methodology and data that should be used for planned SHEDS-PM case studies for variety of geographic areas and seasons.