Citation:

Rosofsky, A., J. Levy, M. Breen, A. Zanobetti, AND P. Fabian. The impact of air exchange rate on ambient air pollution exposure and inequalities across all residential parcels in Massachusetts. Journal of Exposure Science and Environmental Epidemiology . Nature Publishing Group, London, Uk, 29(4):520-530, (2019). https://doi.org/10.1038/s41370-018-0068-3

Impact/Purpose:

Examining disparities across Massachusetts by comparing modeled home air exchange rates, modeled outdoor-home PM2.5 air pollution concentrations, and census block-level demographics. This approach can be applied in epidemiological studies to develop potential exposure modifiers, or to characterize exposure inequalities that are not solely based on ambient concentrations. This work additionally highlights the importance of considering both neighborhood- and housing-level factors as drivers of inequitable ambient air pollutant exposure.

Description:

Individual housing characteristics can modify outdoor ambient air pollution infiltration through air exchange rate (AER). Time and labor-intensive methods needed to measure AER has hindered characterization of AER distributions across large geographic areas. Using publicly-available data and regression models associating AER with housing characteristics, we estimated AER for all Massachusetts residential parcels. We conducted an exposure disparities analysis, considering ambient PM2.5 concentrations and residential AERs. Median AERs (h−1) with closed windows for winter and summer were 0.74 (IQR: 0.47–1.09) and 0.36 (IQR: 0.23–0.57), respectively, with lower AERs for single family homes. Across residential parcels, variability of indoor PM2.5 concentrations of ambient origin was twice that of ambient PM2.5 concentrations. Housing parcels above the 90th percentile of both AER and ambient PM2.5 (i.e., the leakiest homes in areas of highest ambient PM2.5)—vs. below the 10 percentile—were located in neighborhoods with higher proportions of Hispanics (20.0% vs. 2.0%), households with an annual income of less than $20,000 (26.0% vs. 7.5%), and individuals with less than a high school degree (23.2% vs. 5.8%). Our approach can be applied in epidemiological studies to estimate exposure modifiers or to characterize exposure disparities that are not solely based on ambient concentrations.

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