Development of a modeling approach to estimate indoor-to-outdoor sulfur ratios and predict indoor PM and black carbon concentrations for Eastern Massachusetts households.

The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (S/S) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates S/S for individual households that can be incorporated into models to predict indoor PM and black carbon (BC) concentrations. Overall, our model adequately estimated S/S with an out-of-sample by home-season R of 0.89. Estimated S/S reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM and BC with high precision, with out-of-sample R values of 0.79 and 0.76, respectively.