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[null,"1.","Record Nr.",null,"UNINA9910714188703321"]
[null,null,"Autore",null,"Howard-Reed Cynthia"]
[null,null,"Titolo",null,"Database tools for modeling emissions and control of air pollutants from consumer products, cooking, and combustion / / Cynthia Howard Reed, Brian Polidoro"]
[null,null,"Pubbl/distr/stampa",null,"[Gaithersburg, MD] : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , [2006]"]
[null,null,"Descrizione fisica",null,"1 online resource (64 pages) : illustrations"]
[null,null,"Collana",null,"NISTIR ; ; 7364"]
[null,null,"Soggetti",null,"Indoor air pollution - Computer simulation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"November 2006.\""]
[{"$nulls":4},"Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes."]
[{"$nulls":4},"Title from page [1], viewed March 5, 2007."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (pages 19-24)."]
[null,null,null,"Sommario/riassunto","In order to estimate building contaminant concentrations and associated occupant exposures, indoor air quality (IAQ) model users require data related to source strengths and other contaminant transport mechanisms (e.g. sinks, filters). Much of this information exists in the literature; however, it is not readily accessible, thereby requiring users to expend significant efforts in searching for this information. To support the modeling process, the National Institute of Standards and Technology (NIST) has created a series of model input databases for use in its multizone IAQ and ventilation model CONTAM. As part of this effort, a standard data entry format was developed, as well as a computer program to search the database for specific records and build a CONTAM input library. These databases and tools can serve as a basis for building an extensive collection of model input parameters, assessing the quality and completeness of existing data sets, and allow for identification of significant data gaps."]