Predicting NO2 levels in residences based upon sources and source use: A multivariate model |
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| Institution: | 1. Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America;2. Unidad de Vinculación Científica de la Facultad de Medicina, Universidad Nacional Autónoma de México en el Instituto Nacional de Medicina Genómica, Mexico City, Mexico;3. Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America;4. Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America;5. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America;1. Swiss Tropical and Public Health Institute, Basel, Switzerland;2. University of Basel, Basel, Switzerland;3. Dept. of Environmental and Occupational Health Sciences, University of Washington, Seattle, USA;1. School of Environment, Tsinghua University, Beijing 100084, China;2. Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;3. Mailman school of Public Health, Columbia University in the City of New York, New York, USA |
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| Abstract: | In a field study of 302 residences, the indoor air contaminant concentrations associated with the use of unvented kerosene space heaters and gas cooking stoves were measured. For each residence, 2-week average NO2 levels were recorded outdoors and in three rooms using diffusion-type passive monitors. Data were obtained on NO2 sources, the level of use of these sources and on building characteristics from an initial questionnaire, a bi-weekly telephone interview, daily diaries and from assessors' records. The methodology employed in the field study is evaluated in terms of a multivariate model which predicts variations in NO2 levels in the residences as a function of the existence and reported use of sources. The source use parameters were found to explain over 60 % of the variation in residential indoor NO2 levels. The levels of specification needed for other independent variables (infiltration, removal rates, etc.) and the source use terms in the predictive model are presented and discussed. |
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