Record Display for the EPA National Library Catalog
RECORD NUMBER: 2 OF 2Main Title | Two indoor air exposure modeling studies : CONTAM modeling results, and serial correlation effects / | |||||||||||
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Author | Stogner, Ronald E. ; Irwin, J. S. ; Petersen, W. B. ; Aissa, M. ; Lansari, A. | |||||||||||
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CORP Author | Computer Sciences Corp., Research Triangle Park, NC.;Environmental Protection Agency, Research Triangle Park, NC. Atmospheric Research and Exposure Assessment Lab. | |||||||||||
Publisher | United States Environmental Protection Agency, Office of Research and Development, Atmospheric Research and Exposure Assessment Laboratory, | |||||||||||
Year Published | 1991 | |||||||||||
Report Number | EPA/600/3-91/013; EPA-68-01-7365 | |||||||||||
Stock Number | PB91-159707 | |||||||||||
Subjects | Indoor air pollution | |||||||||||
Additional Subjects | Emission factors ; Indoor air pollution ; Computerized simulation ; Air quality ; Time series analysis ; Concentration(Composition) ; Ozone ; Statistical analysis ; Sulfur dioxide ; Mass balance ; Ventilation ; Environmental engineering ; Buildings ; Air infiltration ; CONTAM87 model ; CONTAM88 model | |||||||||||
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Collation | 42 pages ; 28 cm | |||||||||||
Abstract | Two studies are reported on factors influencing indoor pollution levels. In the first, two mass balance computer models, CONTAM87 and CONTAM88, were used to estimate indoor pollution levels for a hypothetical four story building exposed to measured outdoor ozone (O3) concentrations for a 24-hour period. The building contained 50 rooms; exterior rooms contained windows, interior rooms did not. Modeled indoor concentrations indicated that ozone levels generally decreased along a partial cross section from peripheral rooms actually experience lower ozone concentrations than interior rooms. CONTAM88 analysis also revealed that simple actions such as opening interior office doors could significantly change indoor ozone distribution. In the second, a sensitivity study was conducted to quantify the factors affecting serial correlation in the time series of indoor pollution levels. Further, the authors investigated in a very preliminary way the use of personal exposure monitoring data to infer the values of variables needed to estimate indoor concentrations, such as the rates of air exchange, pollutant removal, and pollutant generation. |
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Notes | "John S. Irwin, project officer." Caption title. "January 1991." Microfiche., |
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Contents Notes | EPA/600/3-91/013. |