Modeling of volatile organic compounds emissions and sinks from building materials.

摘要

Volatile Organic Compounds (VOC) emitted from building materials have been recognized as major problems affecting human comfort, health and productivity. Building materials not only are main VOC sources but also are main VOC sinks in buildings. Therefore, accurate modeling of building material VOC emissions and sinks is important for predicting contaminant concentrations, occupant exposures and design of mechanical ventilation systems.; This thesis describes three new modeling approaches to predict building material VOC emissions and sinks. First, a numerical and an analytical VOC emission model have been developed to predict VOC emission rates of a single-layer dry building material and VOC concentrations in a well-mixed room. Second, an integrated IAQ model has been developed to predict VOC emission rates of a multi-layer material, VOC sink rates of a material, VOC concentrations in a well mixed room with both VOC source and sink materials. Third, a zonal model has been integrated with air jet and material VOC emission/sink models to predict the transient VOC distribution in a ventilated room. In addition, a systematic parametric study has been carried out to study the impacts of model input parameters and their interactions on VOC emissions from building materials. These three models have been validated with available experimental results and/or CFD simulation results. The comparisons with the experimental results and the predictions of the CFD models indicate that there are generally good agreements between the proposed model predictions, the experimental results and the CFD results.; Moreover, these three models have been applied to analyze building material VOC emission/sink behaviors and to examine ventilation system efficiency. Results show that the developed models can provide useful information for building owners or designers in selecting proper building materials, designing efficient ventilation systems and assessing indoor air quality.