Predicting Personal Nitrogen Dioxide Exposure in an Elderly Population: Integrating Residential Indoor and Outdoor Measurements, Fixed-Site Ambient Pollution Concentrations, Modeled Pollutant Levels, and Time–Activity Patterns

Abstract

Predicting chronic exposure to air pollution at the intra-urban scale has been recognized as a priority area of research for environmental epidemiology. Exposure assessment models attempt to predict and proxy for individuals' personal exposure to ambient air pollution, and there are no studies to date that explicitly attempt to compare and cross-validate personal exposure concentrations with pollutants modeled at the intra-urban level using methods such as interpolated surfaces and land-use regression (LUR) models. This study aimed to identify how well personal exposure to NO₂ (nitrogen dioxide) can be predicted from ambient exposure measurements and intra-urban exposure estimates using LUR and what other factors contribute to predicting variations in personal exposure beyond measured pollutant levels within home. Personal, indoor and outdoor NO₂ were measured in a population of older adults (>65 yr old) living in Hamilton, Canada. Our results show that personal NO₂ was most strongly associated with contemporaneously collected indoor and outdoor concentrations of NO₂. Predicted NO₂ exposures from intra-urban LUR models were not associated with personal NO₂, whereas interpolated surfaces of particulates and ozone were modestly associated. Combinations of variables that best predicted personal NO₂ variability were derived from time–activity diaries, interpolated surfaces of ambient particulate pollutants, and a citywide temporally matched average of NO₂. The nonsignificant associations between personal NO₂ and the modeled ambient NO₂ concentrations suggest that observed associations between NO₂ generated by LUR models and health effects are probably not produced by NO₂, but by other pollutants that follow a similar spatial pattern.

Acknowledgements

We acknowledge and thank the participants of this study who generously donated their time. This study was funded in part by the Canadian Institute of Health Research (CIHR) Interdisciplinary Research Team (IHRT) grant. We thank Zev Ross for assistance with statistical analyses. We acknowledge Richard Petrella, Bernardo Beckerman, and Valorie Crooks for their assistance with the fieldwork; Sandy Woodhouse for NO₂ filter analysis; and Stephanie Smith and the IHRT nurses for initial participant recruitment.