Identifying housing and meteorological conditions influencing residential air exchange rates in the DEARS and RIOPA studies: development of distributions for human exposure modeling

Abstract

Appropriate prediction of residential air exchange rate (AER) is important for estimating human exposures in the residential microenvironment, as AER drives the infiltration of outdoor-generated air pollutants indoors. AER differences among homes may result from a number of factors, including housing characteristics and meteorological conditions. Residential AER data collected in the Detroit Exposure and Aerosol Research Study (DEARS) and the Relationships of Indoor, Outdoor and Personal Air (RIOPA) study were analyzed to determine whether the influence of a number of housing and meteorological conditions on AER were consistent across four cities in different regions of the United States (Detroit MI, Elizabeth NJ, Houston TX, Los Angeles, CA). Influential factors were identified and used as binning variables for deriving final AER distributions for the use in exposure modeling. In addition, both between-home and within-home variance in AER in DEARS were quantified with the goal of identifying reasonable AER resampling frequencies for use in longitudinal exposure modeling efforts. The results of this analysis indicate that residential AER is depended on ambient temperature, the presence (or not) of central air conditioning, and the age of the home. Furthermore, between-home variability in AER accounted for the majority (67%) of the total variance in AER for Detroit homes, indicating lower within-home variability. These findings are compared with other previously published AER distributions, and the implications for exposure modeling are discussed.