Abstract

Semi-volatile organic compounds (SVOCs) are widely used in building materials, personal consumer products, and furnishings. These compounds can have an interaction with ubiquitous particulate matters (PM) by particle-gas partitioning processes. This plays a critical role in human inhalation exposure; however, the influence of key indoor parameters such as ventilation rate (residence time), particle size, and competitive adsorption has been poorly documented.
The objective of this research is to systematically quantify the particle–gas partitioning of phthalates under controlled indoor conditions. Specifically, this study (i) evaluates the influence of ventilation rate (residence time), (ii) determines size-resolved partitioning behavior using monodisperse NaCl particles, and (iii) examines competitive adsorption between co-existing phthalates. Sodium chloride (NaCl) as a model inorganic particle and four phthalates covering a wide range of vapor pressure were selected. A mixing chamber was used to combine particles and phthalates under isolated conditions. Moreover, the performance of the existing particle-gas partitioning model (adsorption) was evaluated, highlighting its limitations when applied to indoor environments. The results showed that residence time (ventilation rate) can alter particle-gas partitioning (even for adsorption process), which was suggested to occur for only absorption
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process (organic particles- or coated-particle). This can stem from higher interaction time between these two pollutants and might come from multilayer adsorption for longer interactions. For particles having size of 337 nm, 650 nm, and 1007 nm, results indicated that smaller particles tend to adsorb more SVOCs (in this case phthalates) on their surfaces. Furthermore, results showed that competitive adsorption in mixtures reduces individual compound uptake.
Not only do findings enhance the scientific understanding of SVOC partitioning behavior in indoor air, but also it offers new empirical insights that can refine predictive adsorption models. Besides, this study provides new methodological approaches for generating gaseous phthalates (including heavier species) which can be used for future works. Results have direct implication in exposure assessment, indoor air quality management, and the design of air remediation strategies. Lastly, this work supports the development of healthier indoor environments by providing data and modeling approaches better suited to real-world conditions.