A multistage fractal-like tree network model to predict VOC diffusion characteristic of indoor fabrics

Abstract

Understanding the coupling mechanism between multi-material pollution sources and sinks is key to predicting the pollution load. Indoor fabric materials strongly adsorb volatile organic compounds (VOCs) owing to their high loading rates and large specific surface areas. The secondary source effects generated by their desorption easily aggravates indoor air pollution and prolongs the pollution period. The existing research conclusions on the VOC mass-transfer properties of building materials are difficult to apply directly to fabrics due to their multilayered anisotropic fiber-interlaced structure. In this study, the triple porous structure of the fabrics was characterized, and the mass-transfer network were analyzed. Moreover, a multistage fractal-like tree network model was proposed to characterize the fabric's pore structure and establish a theoretical prediction model of the VOC diffusion coefficient. Subsequently, the mass-transfer characteristic parameters of the fabrics were measured at different ambient temperatures through loading and emission experiments of formaldehyde, benzene, toluene, ethylbenzene, and xylene (BTEX) on typical indoor fabrics. A comparison of the experimentally determined and theoretically predicted values revealed that the proposed model could accurately predict the diffusion coefficient of fabrics. This study can help understand the dynamic source and sink characteristics of fabrics in an indoor environment.