A long-term dynamic model for predicting the concentration of semivolatile organic compounds in indoor environments: Application to phthalates

Abstract

Semivolatile organic compounds (SVOCs) in indoor environments can partition into the gas phase, airborne particles, and settled dust and onto available surfaces. A long-term dynamic model was developed to predict the hourly concentrations of SVOCs over a year in the gas phase, airborne particles, and settled dust and on each sink surface. The model takes into account mass transfer mechanisms, the reactivity of SVOCs with oxidants indoors, and the influence of four indoor environmental factors (the air temperature, relative humidity, concentration of indoor airborne particles, and air exchange rate) on the mass transfer parameters. The model was validated for DEHP (di-2-ethylhexyl phthalate) and BBzP (butyl benzyl phthalate) by comparing the predicted concentrations in all the phases with the measured concentrations obtained in an environmental chamber and a test house. The model was then used to predict the hourly averaged concentration of BBzP in all the phases under real environmental conditions over a year. More than 52% of the variance in the BBzP concentration was found to be associated with the covariance of the environmental factors. The air exchange rate contributed to 16% of the variance in the concentration. In addition, the indoor air temperature and relative humidity contributed 9% of the variance in the gas-phase concentration of BBzP and 7% of the variance in the settled dust concentration of BBzP. The variance in the concentration of the total suspended particles contributed 10% of the variance in the BBzP concentration on the walls and windows.

Temporal variability of indoor dust concentrations of semivolatile organic compounds

“…However, several studies observed different degrees of temporal variability of SVOC dust concentrations across chemical classes or within the same chemical class 18,31‐33 . Episodic occupant activities (eg, cooking, vacuuming, and ventilation) and environmental factors (eg, temperature, relative humidity, and airborne particulate matter concentration) are also known to affect SVOC air and/or dust concentrations during a short period of time 34,35 . Seasonal factors (eg, different product use pattern and ventilation frequency) may also play a role in temporal variability in measured dust concentrations 36 .…”

“…18,[31][32][33] Episodic occupant activities (eg, cooking, vacuuming, and ventilation) and environmental factors (eg, temperature, relative humidity, and airborne particulate matter concentration) are also known to affect SVOC air and/or dust concentrations during a short period of time. 34,35 Seasonal factors (eg, different product use pattern and ventilation frequency) may also play a role in temporal variability in measured dust concentrations. 36 Thus, further studies are needed to extensively examine temporal variability of dust concentrations for a wide range of SVOCs detected in household dust and other determinants (eg, chemical properties, seasonal difference in use patterns, or emission sources) of the temporal variability of dust concentrations.…”

Prediction of phthalates concentration in household dust based on back propagation neural network

“…The higher temperature could increase the emission rate of plasticizer, so higher PAEs concentrations in dust have also been attributed to electronic devices, cosmetics and personal care products. 39,40 Therefore, putting the computer in children's room and using mosquito-repellent incense were also important factors for BP neural network establishment. The association analysis can also provide a reference for reducing indoor PAEs concentration.…”

Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework

“…If it is assumed that a linear equilibrium relationship exists between the settled dust and the gas layer directly adjacent to the source material (SI Section 3), the critical parameters for modeling emission into dust are y 0 , h m (SI Section IV), the dust/air partition coefficient K dust (SI Section VI), the particle deposition velocity v d , and the concentration of airborne particles, which is usually given as total suspended particles, TSP. ,,, Instead of TSP, other particle concentration ranges such as PM 2.5 can be used, depending on the research question. , …”