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Development of IAQ Model Input Databases: Volatile Organic Compound Source Emission Rates.


pdf icon Development of IAQ Model Input Databases: Volatile Organic Compound Source Emission Rates. (688 K)
Howard-Reed, C.; Polidoro, B.; Dols, W. S.

Development of IAQ Model Input Databases: Volatile Organic Compound Source Emission Rates. Air and Waste Management Association Conference. Proceedings. July 21-23, 2003, Research Triangle Park, NC, 1-14 pp, 2003.

Keywords:

indoor air quality; databases; volatile organic compounds; emission rates

Abstract:

Indoor air quality (IAQ) models can be used to predict airflows, contaminant concentrations and personal exposures for a given indoor environment. In order to generate such results, these models require the user to provide a wide range of input data including envelope leakage information, weather, ventilation system characteristics, contaminant source emission rates, sink removal rates, occupant schedules, and air cleaner removal rates. Many of the required data are available in the literature; however, this information has generally not been compiled in a convenient form for use in an IAQ model. As a result, finding appropriate model data can be a repetitive and laborious process for the user. To make this effort more efficient, the National Institute of Standards and Technology (NIST) has begun an effort to compile model input data needs into searchable databases. The process involves collecting data from the literature, designing a database format to standardize data entry, entering the information into the database, and developing a computer program to search the database for specific records to use in an IAQ model. This process has been completed for airflow leakage elements, wind pressure coefficients, and ventilation system schedules and is currently underway for VOC source emission rates. With these databases, CONTAMW users and other modelers will be able to simulate a wide range of exposure scenarios in different types of buildings as well as simulate the impacts of potential control strategies. In addition, as a result of this work, it will be possible to identify important gaps in the data.