Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures
Abstract
This paper presents two models for volatile organic compound (VOC) emissions from carpet. One is a numerical model using the computational fluid dynamics (CFD) technique for short-term predictions, the other an analytical model for long-term predictions. The numerical model can (1) deal with carpets that are not new, (2) calculate the time-dependent VOC distributions in a test chamber or room, and (3) consider the temperature effect on VOC emissions. Based on small-scale chamber data, both models were used to examine the VOC emissions under different temperatures from polypropene styrene-butadiene rubber (SBR) bitumen-backed carpet. The short-term predictions show that the VOC emissions under different temperatures can be modeled solely by changing the carpet diffusion coefficients. A formulation of the Arrhenius relation was used to correlate the dependence of carpet diffusion coefficient with temperature. The long-term predictions show that it would take several years to bake out the VOCs, and temperature would have a major impact on the bake-out time.
- Authors:
-
- Massachusetts Inst. of Tech., Cambridge, MA (United States). Building Technology Program
- TNO Building and Construction Research, Delft (Netherlands)
- Publication Date:
- Sponsoring Org.:
- National Science Foundation, Washington, DC (United States)
- OSTI Identifier:
- 687687
- Report Number(s):
- CONF-980650-
Journal ID: ISSN 0001-2505; TRN: IM9944%%352
- Resource Type:
- Book
- Resource Relation:
- Conference: 1998 ASHRAE summer annual meeting, Toronto (Canada), 20 Jun 1998; Other Information: PBD: 1998; Related Information: Is Part Of ASHRAE transactions 1998: Technical and symposium papers. Volume 104, Part 2; PB: 1511 p.
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; FLOORS; COVERINGS; VOLATILE MATTER; ORGANIC COMPOUNDS; EMISSION; INDOOR AIR POLLUTION; MATHEMATICAL MODELS; TEMPERATURE DEPENDENCE; THEORETICAL DATA
Citation Formats
Yang, S, Chen, Q, and Bluyssen, P M. Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures. United States: N. p., 1998.
Web.
Yang, S, Chen, Q, & Bluyssen, P M. Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures. United States.
Yang, S, Chen, Q, and Bluyssen, P M. 1998.
"Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures". United States.
@article{osti_687687,
title = {Prediction of short-term and long-term VOC emissions from SBR bitumen-backed carpet under different temperatures},
author = {Yang, S and Chen, Q and Bluyssen, P M},
abstractNote = {This paper presents two models for volatile organic compound (VOC) emissions from carpet. One is a numerical model using the computational fluid dynamics (CFD) technique for short-term predictions, the other an analytical model for long-term predictions. The numerical model can (1) deal with carpets that are not new, (2) calculate the time-dependent VOC distributions in a test chamber or room, and (3) consider the temperature effect on VOC emissions. Based on small-scale chamber data, both models were used to examine the VOC emissions under different temperatures from polypropene styrene-butadiene rubber (SBR) bitumen-backed carpet. The short-term predictions show that the VOC emissions under different temperatures can be modeled solely by changing the carpet diffusion coefficients. A formulation of the Arrhenius relation was used to correlate the dependence of carpet diffusion coefficient with temperature. The long-term predictions show that it would take several years to bake out the VOCs, and temperature would have a major impact on the bake-out time.},
doi = {},
url = {https://www.osti.gov/biblio/687687},
journal = {},
issn = {0001-2505},
number = ,
volume = ,
place = {United States},
year = {Thu Dec 31 00:00:00 EST 1998},
month = {Thu Dec 31 00:00:00 EST 1998}
}