Development of IAQ Model Input Databases: Volatile Organic Compound Source Emission Rates.
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.
Building and Fire Research Laboratory
National Institute of Standards and Technology
Gaithersburg, MD 20899