An analysis of factors that influence personal exposure to nitrogen oxides in residents of Richmond, Virginia.

Autor: Zipprich JL; Center for Environmental Studies, Virginia Commonwealth University, Richmond, Virginia 23248, USA., Harris SA, Fox JC, Borzelleca JF
Jazyk: angličtina
Zdroj: Journal of exposure analysis and environmental epidemiology [J Expo Anal Environ Epidemiol] 2002 Jul; Vol. 12 (4), pp. 273-85.
DOI: 10.1038/sj.jea.7500226
Abstrakt: Nitrogen oxides (NO(x)) are ubiquitous pollutants in outdoor and indoor air. However, epidemiologic studies that evaluate health effects associated with NO(x) commonly rely upon outdoor concentrations of NO(x), nitrogen dioxide (NO(2)), or residence characteristics as surrogates for personal exposure. In this study, personal exposures (48 h) and corresponding indoor and outdoor concentrations of nitric oxide (NO), NO(2), and NO(x) were measured (July-September) in 39 adults and 9 children from 23 households in Richmond, Virginia, using Ogawa passive NO(x) monitors. Demographic, time-activity patterns, and household data were collected by questionnaire and used to develop exposure prediction models. Adults had higher NO(2), NO, and NO(x) exposures (means: 16, 63, and 79 ppb, respectively) than children (13, 49, and 62 ppb). Measurements taken in bedrooms (18, 57, and 75 ppb) and living rooms (19, 65, and 84 ppb) surpassed measurements taken outdoors (15, 21, and 36 ppb). In indoor locations, NO(x) concentrations were influenced largely by NO, and consequently, personal exposure prediction models for NO(x) were reflective of models for NO. Statistical models that best predicted personal exposures included indoor measurements; outdoor measurements contributed relatively little to personal exposure. Close to 70% of the variation in personal NO(2) and NO(x) exposure was explained by two variable models (bedroom NO(2) and time spent in other indoor locations; bedroom NO(x) and time spent in kitchen). Given appropriate resources, measurement error in epidemiologic studies can be reduced significantly with the use of personal exposure measurements or prediction models developed from indoor measurements and survey data.
Databáze: MEDLINE