Development and assessment of a physics-based simulation model to investigate residential PM2.5 infiltration across the US housing stock

• Developed model for estimating PM2.5 concentrations in the US housing stock.
• Compared modeled and measured regional estimates of PM2.5 infiltration.
• Model results compared reasonably well to measured.
• Data on time-varying air exchange rates in homes would help improve model.
• Model is a powerful tool for developing energy-efficient PM2.5 controls.

The Lawrence Berkeley National Laboratory Population Impact Assessment Modeling Framework (PIAMF) was expanded to enable determination of indoor PM2.5 concentrations and exposures in a set of 50,000 homes representing the US housing stock. A mass-balance model is used to calculate time-dependent pollutant concentrations within each home. The model includes size- and species-dependent removal mechanisms. The particle model was applied to the housing samples of the Relationship of Indoor, Outdoor, and Personal Air (RIOPA) and The Detroit Exposure and Aerosol Research Study (DEARS) studies to compare model- and measurement-based estimates of indoor PM2.5 of outdoor origin. Model-derived distributions of infiltration factors (ratio of indoor PM2.5 of outdoor origin to outdoor PM2.5) are compared to measurement-based distributions obtained in studies conducted in 11 US cities.