Semivolatile organic compounds in French schools: Partitioning between the gas phase, airborne particles and settled dust.

The indoor environmental quality in classrooms can largely affect children's daily exposure to indoor chemicals in schools. To date, there has not been a comprehensive study of the concentrations of semivolatile organic compounds (SVOCs) in French schools. Therefore, the French Observatory for Indoor Air Quality (OQAI) performed a field study of SVOCs in 308 nurseries and elementary schools between June 2013 and June 2017. The concentrations of 52 SVOCs, including phthalates, polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), synthetic musks, and pesticides, were measured in air and settled dust (40 SVOCs in both air and dust, 12 in either air or dust). The results showed that phthalates had the highest concentrations among the SVOCs in both the air and dust. Other SVOCs, including tributyl phosphate, fluorene, phenanthrene, gamma-hexachlorocyclohexane (gamma-HCH, lindane), galaxolide, and tonalide, also showed high concentrations in both the air and dust. Theoretical equations were developed to estimate the SVOC partitioning between the air and settled dust from either the octanol/air partition coefficient or the boiling point of the SVOCs. The regression constants of the equations were determined using the data set of the present study for phthalates and PAHs.

Machine learning and statistical models for predicting indoor air quality.

Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mostly used in unoccupied or scenario-based environments, statistical models have great potential to explore IAQ captured in large measurement campaigns or in real occupied environments. The present study carried out the first literature review of the use of statistical models to predict IAQ. The most commonly used statistical modeling methods were reviewed and their strengths and weaknesses discussed. Thirty-seven publications, in which statistical models were applied to predict IAQ, were identified. These studies were all published in the past decade, indicating the emergence of the awareness and application of machine learning and statistical modeling in the field of IAQ. The concentrations of indoor particulate matter (PM2.5 and PM10 ) were the most frequently studied parameters, followed by carbon dioxide and radon. The most popular statistical models applied to IAQ were artificial neural networks, multiple linear regression, partial least squares, and decision trees.

Relationships between socioeconomic and lifestyle factors and indoor air quality in French dwellings.

BACKGROUND: To date, few studies have analyzed the relationships between socioeconomic status (SES) and indoor air quality (IAQ). OBJECTIVE: The aim of this study was to examine the relationships between socioeconomic and other factors and indoor air pollutant levels in French homes. METHODS: The indoor air concentrations of thirty chemical, biological and physical parameters were measured over one week in a sample of 567 dwellings representative of the French housing stock between September 2003 and December 2005. Information on SES (household structure, educational attainment, income, and occupation), building characteristics, and occupants' habits and activities (smoking, cooking, cleaning, etc.) were collected through administered questionnaires. Separate stepwise linear regression models were fitted to log-transformed concentrations on SES and other factors. Logistic regression was performed on fungal contamination data. RESULTS: Households with lower income were more likely to have higher indoor concentrations of formaldehyde, but lower perchloroethylene indoor concentrations. Formaldehyde indoor concentrations were also associated with newly built buildings. Smoking was associated with increasing acetaldehyde and PM2.5 levels and the risk of a positive fungal contamination index. BTEX levels were also associated with occupant density and having an attached garage. The major predictors for fungal contamination were dampness and absolute humidity. CONCLUSION: These results, obtained from a large sample of dwellings, show for the first time in France the relationships between SES factors and indoor air pollutants, and believe they should be considered alongside occupant activities and building characteristics when study IAQ in homes.

Semivolatile organic compounds in indoor air and settled dust in 30 French dwellings.

Semivolatile organic compounds (SVOCs) are ubiquitous contaminants in indoor environments, emanating from different sources and partitioning among several compartments, including the gas phase, airborne particles, and settled dust. Nevertheless, simultaneous measurements in the three compartments are rarely reported. In this study, we investigated indoor concentrations of a wide range of SVOCs in 30 French dwellings. In settled dust, 40 out of 57 target compounds were detected. The highest median concentrations were measured for phthalates and to a lesser extent for bisphenol A, synthetic musks, some pesticides, and PAHs. Di(2-ethylhexyl)phthalate (DEHP) and diisononyl phthalate (DINP) were the most abundant compounds. A total of 34 target compounds were detected both in the gas phase and airborne particles. The highest concentrations were measured for diisobutyl phthalate (DiBP), diethyl phthalate (DEP), dibutyl phthalate (DBP), and synthetic musks in the gas phase and for DEHP, DiBP, DBP, and DINP in the airborne particles. This is the first study on the indoor concentrations of a wide range of SVOCs in settled dust, gas phase, and airborne particles collected simultaneously in each dwelling.

Indoor exposure to ultrafine particles related to domestic activities: A systematic review and meta-analysis.

Ultrafine particles (< 100 nm) are of increasing concern because of their toxicological potential. Emission processes suggest their presence in all environments, including at home, where particularly at-risk populations may be exposed. However, knowledge of their impact on health is still limited, due to difficulties in properly assessing exposure in epidemiological studies. In this context, the objective of this study was to provide a complete summary of indoor exposure to ultrafine particles in highly industrialised countries by examining the domestic activities that influence such exposure. We conducted a systematic review, according to PRISMA guidelines using PubMed, Web of Science and Scopus up to and including 2021. We carried out a qualitative and quantitative analysis of the selected studies with a standardised template. Exposure circumstances, measurement methods, and results were analysed. Finally, a meta-analysis of the measured concentrations was performed to study exposure levels during domestic activities. The review included 69 studies resulting in the analysis of 346 exposure situations. Nine main groups of activities were identified: cooking, which was the most studied, smoking, the use of air-fresheners, cleaning, heating, personal care, printing, do-it-yourself activities, and others. Over 50 different processes were involved in these activities. Based on available particle number concentrations, the highest average of mean concentrations was associated with grilling (14,400 × 103 cm-3), and the lowest with wood stove (18 × 103 cm-3). The highest average of peak concentrations was that for the use of hair dryers (695 × 103 cm-3), and the lowest for the use of air cleaners (11 × 103 cm-3). A hierarchy of domestic activities and related processes leading to ultrafine particle exposure is provided, along with average exposure concentrations at home. However, more extensive measurement campaigns are needed under real-life conditions to improve assessments of indoor exposure to ultrafine particles.

Modeling Primary Emissions of Chemicals from Liquid Products Applied on Indoor Surfaces.

Liquid products applied on material surfaces and human skin, including many household cleaning products and personal care products, can lead to intermittent emissions of chemicals and peak concentrations in indoor air. The existing case-based models do not allow inter-comparison of different use scenarios and emission mechanisms. In this context, the present work developed a mechanistic model based on mass transfer theories, which allowed emissions into the air from the liquid product to be characterized. It also allowed for diffusion into the applied surface during product use and re-emission from the applied surface after the depletion of the liquid product. The model was validated using literature data on chemical emissions following floor cleaning and personal care product use. A sensitivity analysis of the model was then conducted. The percentage of the chemical mass emitted from the liquid to the air varied from 45% (applied on porous material) to 99% (applied on human skin), and the rest was absorbed into the applied material/skin. The peak gas-phase concentration, the time to reach the peak concentration, and the percentage of the liquid-to-air emission depended significantly on the chemical's octanol/gas and material/gas partition coefficients and the diffusion coefficient of the chemical in the applied material/skin.

Modeling the bioaccessibility of inhaled semivolatile organic compounds in the human respiratory tract.

The bioaccessibility of semivolatile organic compounds (SVOCs) via inhalation has rarely been studied, as indicated by the literature. There is no model to calculate the SVOC bioaccessibility following inhalation, and measurement data have focused on only a few polycyclic aromatic hydrocarbons (PAHs) in the particle phase. The present work developed a mechanistic model to address the mass transfer of inhaled SVOCs among the gas, particle and mucus phases in the human respiratory tract. The model considers (1) the SVOC partitioning between the gas and particle phases as well as between the gas and mucus phases and (2) the deposition of gas- and particle-phase SVOCs in the mucus of the respiratory tract. Based on the model, the inhalation bioaccessibility for 72 SVOCs was calculated. The SVOCs were measured in French dwellings at the nationwide scale, and their median concentrations in both the gas and particle phases were used for the bioaccessibility calculations. The results show that the inhalation bioaccessibility varies considerably from one compound to another, e.g., between 0.62 and 1.00 for phthalates, between 0.71 and 0.79 for polybrominated diphenyl ethers (PBDEs), between 0.48 and 0.56 for polychlorinated biphenyls (PCBs), between 0.48 and 1.00 for different chemical families of pesticides and between 0.48 and 0.90 for PAHs.

Predicting the rate constants of semivolatile organic compounds with hydroxyl radicals and ozone in indoor air.

Semivolatile organic compounds (SVOCs) in air can react with hydroxyl radicals (OH), nitrate radicals (NO3) and ozone (O3). Two questions regarding SVOC reactivity with OH, NO3 and O3 in the gas and particle phases remain to be addressed: according to the existing measurements in the literature, which are the most reactive SVOCs in air, and how can the SVOC reactivity in the gas and particle phases be predicted? In the present study, a literature review of the second-order rate constant (k) was carried out to determine the SVOC reactivity with OH, NO3 and O3 in the gas and particle phases in ambient and indoor air at room temperature. Measured k values were available in the literature for 90 polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organophosphates, dioxins, di(2-ethylhexyl)phthalate (DEHP) and pesticides including pyrifenox, carbamates and terbuthylazine. PAHs and organophosphates were found to be more reactive than dioxins and PCBs. Based on the obtained data, quantitative structure-activity relationship (QSAR) models were developed to predict the k value using quantum chemical, molecular, physical property and environmental descriptors. Eight linear and nonlinear statistical models were employed, including regression models, bagging, random forest and gradient boosting. QSAR models were developed for SVOC/OH reactions in the gas and particle phases and SVOC/O3 reactions in the particle phase. Models for SVOC/NO3 and SVOC/O3 reactions in the gas phase could not be developed due to the lack of measured k values for model training. The least absolute shrinkage and selection operator (LASSO) regression and random forest models were identified as the most effective models for SVOC reactivity prediction according to a comparison of model performance metrics.

Semi-volatile organic compounds in French dwellings: An estimation of concentrations in the gas phase and particulate phase from settled dust.

Semi-volatile organic compounds (SVOCs) are present in the gas phase, particulate phase and settled dust in the indoor environment, resulting in human exposure through different pathways. Sometimes, SVOCs are only measured in a single phase because of practical and/or financial constraints. A probabilistic method proposed by Wei et al. for the prediction of the SVOC concentration in the gas phase from the SVOC concentration in the particulate phase was extended to model the equilibrium SVOC concentrations in both the gas and particulate phases from the SVOC concentration measured in settled dust. This approach, based on the theory of SVOC partitioning among the gas phase, particulate phase, and settled dust incorporating Monte Carlo simulation, was validated using measured data from the literature and applied to the prediction of the concentrations of 48 SVOCs in both the gas and particulate phases in 3.6 million French dwellings where at least one child aged 6 months to 6 years lived. The median gas-phase concentration of 15 SVOCs, i.e., 5 phthalates, 2 organochlorine pesticides, 4 polycyclic aromatic hydrocarbons (PAHs), 2 synthetic musks, dichlorvos, and tributyl phosphate, was found to be higher than 1 ng/m3. The median concentration of 5 phthalates in the particulate phase was higher than 1 ng/m3. The impacts of some physical parameters, such as the molar mass and boiling point, on the SVOC partitioning among the different phases were quantified. The partitioning depends on the activity coefficient, vapor pressure at the boiling point, entropy of evaporation of the SVOCs, and the fraction of organic matter in particles. Thus, the partitioning may differ from one chemical family to another. The empirical equations based on regressions allow quick estimation of SVOC partitioning among the gas phase, particulate phase, and settled dust from the molar mass and boiling point.

Detection of fungal development in a closed environment through the identification of specific VOC: demonstration of a specific VOC fingerprint for fungal development.

The occurrence of disease amongst the occupants of "mouldy" environments has been widely described in the literature. However, the detection of such moulds in closed environments remains difficult, particularly in the event of recent (before the first deterioration) or masked contamination (behind a material). In this context, the present study aimed to determine a specific chemical fingerprint for fungal development detectable in closed environments (dwellings, office, museum...). To achieve this, chemical emissions from sterile and artificially contaminated by moulds materials were analyzed and compared using a descriptive statistical method. Principal Component Analysis is thus chosen to analyze the results. PCA generated optimum and similar graphical representations of the scatterplot representing the data matrix. This statistical approach made it possible to identify an emission fingerprint without applying any preconception as to the type of emitted compound. Statistical analysis of the data then enabled confirmation of the impact of moulds on total VOC emissions. This emission of specific compounds resulted in obtaining a signature for the presence of fungal development in an environment, defined by specific ions. This analysis, and use of these ions applied to dwellings, made it possible to distinguish those with proven fungal development from those with no sign of mould or with a context favorable to fungal development, thus demonstrating that a chemical fingerprint specific to fungal development could be detected in indoor environments.

Detection of fungal development in closed spaces through the determination of specific chemical targets.

In addition to the biodegradation problems encountered in buildings, exposure of their occupants to moulds is responsible for numerous diseases: infections (invasive nosocomial aspergillosis), immediate or delayed allergies, food-borne infections and different types of irritation. In this context, the aim of our work has been to determine specific chemical tracers for fungal development on construction materials. More generally, by detecting a specific chemical fingerprint of fungal development, our objective was to propose a microbiological alert system which could control systems and/or procedures for the microbiological treatment of indoor areas. We therefore characterized the chemical emissions from six types of construction material contaminated artificially by moulds. Chemical fingerprints were established for 19 compounds arising specifically from fungal metabolism: 2-ethylhexanoic acid methyl ester, 1-octen-3-ol, 3-heptanol, 3-methyl-1-butanol, 2-methyl-1-butanol, 1,3-octadiene, 2-(5H)-furanone, 2-heptene, alpha-pinene, 2-methylisoborneol, 4-heptanone, 2-methylfuran, 3-methylfuran, dimethyldisulfide, methoxybenzene, a terpenoid and three sesquiterpenes. Determining the origin of these compounds and their specific links with a growth substrate or fungal species made it possible to judge the pertinence of choosing these compounds as tracers. Thus the detecting specific volatile organic compounds emitted as from the second day of fungal growth demonstrated that this approach had the advantage of detecting fungal development both reliably and rapidly before any visible signs of contamination could be detected.

Influence of indoor environmental factors on mass transfer parameters and concentrations of semi-volatile organic compounds.

Semi-volatile organic compounds (SVOCs) in indoor environments can partition among the gas phase, airborne particles, settled dust, and available surfaces. The mass transfer parameters of SVOCs, such as the mass transfer coefficient and the partition coefficient, are influenced by indoor environmental factors. Subsequently, indoor SVOC concentrations and thus occupant exposure can vary depending on environmental factors. In this review, the influence of six environmental factors, i.e., indoor temperature, humidity, ventilation, airborne particle concentration, source loading factor, and reactive chemistry, on the mass transfer parameters and indoor concentrations of SVOCs was analyzed and tentatively quantified. The results show that all mass transfer parameters vary depending on environmental factors. These variations are mostly characterized by empirical equations, particularly for humidity. Theoretical calculations of these parameters based on mass transfer mechanisms are available only for the emission of SVOCs from source surfaces when airborne particles are not present. All mass transfer parameters depend on the temperature. Humidity influences the partition of SVOCs among different phases and is associated with phthalate hydrolysis. Ventilation has a combined effect with the airborne particle concentration on SVOC emission and their mass transfer among different phases. Indoor chemical reactions can produce or eliminate SVOCs slowly. To better model the dynamic SVOC concentration indoors, the present review suggests studying the combined effect of environmental factors in real indoor environments. Moreover, interactions between indoor environmental factors and human activities and their influence on SVOC mass transfer processes should be considered.

Bioaccessibility and bioavailability of environmental semi-volatile organic compounds via inhalation: A review of methods and models.

Semi-volatile organic compounds (SVOCs) present in indoor environments are known to cause adverse health effects through multiple routes of exposure. To assess the aggregate exposure, the bioaccessibility and bioavailability of SVOCs need to be determined. In this review, we discussed measurements of the bioaccessibility and bioavailability of SVOCs after inhalation. Published literature related to this issue is available for 2,3,7,8-tetrachlorodibenzo-p-dioxin and a few polycyclic aromatic hydrocarbons, such as benzo[a]pyrene and phenanthrene. Then, we reviewed common modeling approaches for the characterization of the gas- and particle-phase partitioning of SVOCs during inhalation. The models are based on mass transfer mechanisms as well as the structure of the respiratory system, using common computational techniques, such as computational fluid dynamics. However, the existing models are restricted to special conditions and cannot predict SVOC bioaccessibility and bioavailability in the whole respiratory system. The present review notes two main challenges for the estimation of SVOC bioaccessibility and bioavailability via inhalation in humans. First, in vitro and in vivo methods need to be developed and validated for a wide range of SVOCs. The in vitro methods should be validated with in vivo tests to evaluate human exposures to SVOCs in airborne particles. Second, modeling approaches for SVOCs need to consider the whole respiratory system. Alterations of the respiratory cycle period and human biological variability may be considered in future studies.

Chemical-by-chemical and cumulative risk assessment of residential indoor exposure to semivolatile organic compounds in France.

BACKGROUND: The toxic effects of environmental exposure to chemicals are increasingly being studied and confirmed, notably for semivolatile organic compounds (SVOCs). These are found in many products and housing materials, from which they are emitted to indoor air, settled dust and other surfaces. OBJECTIVES: The objective of this work is to assess the human health risk posed by residential indoor exposure to 32 SVOCs, assessed in previous nationwide studies. METHODS: A chemical-by-chemical risk assessment, using a hazard quotient (HQ) or excess risk (ER) method, was supplemented by a cumulative risk assessment (CRA). For CRA, a hazard index (HI) method, as well as higher tier approaches using relative potency factors (RPFs) or toxic equivalency factors (TEFs) were used for the following endpoints: neurotoxicity, reproductive toxicity, genotoxicity and immunotoxicity. RESULTS: HQs were above 1 for 50% of French children from birth to 2 years for BDE 47, and for 5% of children for lindane and dibutyl phthalate (DBP). Corresponding hazards are reprotoxic for BDE 47 and DBP, and immunotoxic for lindane. The CRA approach provided additional information of reprotoxic risks (HI > 1) that may occur for 95% of children and for 5% of the offspring for pregnant women's exposure. The SVOCs contributing most to these risks were PCB 101 and 118, BDE 47, and DBP. The higher tier CRA approaches showed that exposure to dwellings' SVOC mixtures were of concern for 95% of children for neurotoxic compounds having effects linked with neuronal death. To a lesser extent, effects mediated by the aryl hydrocarbon receptor (AhR) or by a decrease in testosterone levels may concern 5% of children and adults. Lastly, unacceptable immunotoxic risk related to exposure to 8 indoor PCBs was also observed for 5% of children. CONCLUSIONS: In view of uncertainties related to compounds' toxicity for humans, these results justify the implementation of preventive measures, as well as the production of more standardized and comprehensive toxicological data for some compounds.

Dermal absorption of semivolatile organic compounds from the gas phase: Sensitivity of exposure assessment by steady state modeling to key parameters.

Recent research has demonstrated the importance of dermal exposure for some semivolatile organic compounds (SVOCs) present in the gas phase of indoor air. Though models for estimating dermal intake from gaseous SVOCs exist, their predictions can be subject to variations in input parameters, which can lead to large variation in exposure estimations. In this sensitivity analysis for a steady state model, we aimed to assess these variations and their determinants using probabilistic Monte Carlo sampling for 8 SVOCs from different chemical families: phthalates, bisphenols, polycyclic aromatic hydrocarbons (PAHs), organophosphorus (OPs), organochlorines (OCs), synthetic musks, polychlorinated biphenyls (PCBs) and polybromodiphenylethers (PBDEs). Indoor SVOC concentrations were found to be the most influential parameters. Both Henry's law constant (H) and octanol/water partition coefficient (Kow) uncertainty also had significant influence. While exposure media properties such as volume fraction of organic matter in the particle phase (fom-part), particle density (ρpart), concentration ([TSP]) and transport coefficient (É£d) had a slight influence for some compounds, human parameters such as body weight (W), body surface area (A) and daily exposure (t) make a marginal or null contribution to the variance of dermal intake for a given age group. Inclusion of a parameter sensitivity analysis appears essential to reporting uncertainties in dermal exposure assessment.

Predicting the gas-phase concentration of semi-volatile organic compounds from airborne particles: Application to a French nationwide survey.

Semi-volatile organic compounds (SVOCs) partition indoors between the gas phase, airborne particles, settled dust, and other surfaces. Unknown concentrations of SVOCs in the gas phase (Cg) can be predicted from their measured concentrations in airborne particles. In previous studies, the prediction of Cg depended largely on choosing a specific equation for the calculation of the particle/gas partition coefficient. Moreover, the prediction of Cg is frequently performed at a reference temperature rather than the real indoor temperature. In this paper, a probabilistic approach based on Monte Carlo simulation was developed to predict the distribution of SVOCs' Cg from their concentrations in airborne particles at the target indoor temperature. Moreover, the distribution of the particle/gas partition coefficient of each SVOC at the target temperature was used. The approach was validated using two measured datasets in the literature: the predicted Cg from concentrations measured in airborne particles and the measured Cg were generally of the same order of magnitude. The distributions of the Cg of 66 SVOCs in the French housing stock were then predicted. The SVOCs with the highest median Cg, ranging from 1ng/m3 to >100ng/m3, included 8 phthalates (DEP, DiBP, DBP, DEHP, BBP, DMP, DiNP, and DMEP), 4 polycyclic aromatic hydrocarbons (fluorene, phenanthrene, fluoranthene, and anthracene), 2 alkylphenols (4-tert-butylphenol and 4-tert-octylphenol), 2 synthetic musks (galaxolide and tonalide), tributyl phosphate, and heptachlor. The nationwide, representative, predicted Cg values of SVOCs are frequently of the same order of magnitude in Europe and North America, whereas these Cg values in Chinese and Indian dwellings and the Cg of polybrominated diphenyl ethers in U.S. dwellings are generally higher.

Indoor residential exposure to semivolatile organic compounds in France.

Multiple chemicals are emitted in residential accommodation. Aggregate Daily Doses (ADD) (ng/kg-bw/d) were estimated for 32 semivolatile organic compounds (SVOCs) of different chemical families that are frequently detected in French dwellings in both air and settled dust. Daily doses were determined using steady-state models for the population, categorized into 11 age groups covering birth to age 30. Three routes of exposure were taken into account: dust ingestion, inhalation (gaseous and particulate phases) and dermal contact with the gaseous phase of air. Contamination levels were preferentially retrieved from large, nationwide representative datasets. A two-dimensional probabilistic approach was used to assess parametric uncertainty and identify the most influential factors. For children aged 2 to 3years, ADD estimates spanned orders of magnitude, with median values ranging from 8.7pg/kg-bw/d for 2,2',3,4,4'-pentabromodiphenylether (BDE 85) to 1.3µg/kg-bw/d for di-isobutyl phthalate (DiBP). Inhalation, ingestion and dermal pathway contributed at varying levels, and depending on compound, air was the dominant medium for 28 of the 32 compounds (either by inhalation or dermal contact). Indoor exposure estimate variance was mainly driven by indoor contamination variability, and secondarily by uncertainty in physical and chemical parameters. These findings lend support to the call for cumulative risk assessment of indoor SVOCs.

Distributions of the particle/gas and dust/gas partition coefficients for seventy-two semi-volatile organic compounds in indoor environment.

Particle/gas and dust/gas partition coefficients (Kp and Kd) are two key parameters that address the partitioning of semi-volatile organic compounds (SVOCs) between gas-phase, airborne particles, and settled dust in indoor environment. A number of empirical equations to calculate the values of Kp and Kd have been reported in the literature. Therefore, the difficulty lies in the selection of a specific empirical equation in a given situation. In this study, we retrieved from the literature 38 empirical equations for calculating Kp and Kd values from the SVOC saturation vapor pressure and octanol/air partition coefficient. These values were calculated for 72 SVOCs: 9 phthalates, 9 polybrominated diphenyl ethers (PBDEs), 11 polychlorinated biphenyls (PCBs), 22 biocides, 14 polycyclic aromatic hydrocarbons (PAHs), 3 alkylphenols, 2 synthetic musks, tributylphosphate, and bisphenol A. The mean and median values of log10Kp or log10Kd for most SVOCs were of the same order of magnitude. The distribution of log10Kp values was fitted to either a normal distribution (for 27 SVOCs) or a log-normal distribution (for 45 SVOCs). This work provides a reference distribution of the log10Kp for 72 SVOCs, and its use may reduce the bias associated with the selection of a specific value or equation.

Temperature dependence of the particle/gas partition coefficient: An application to predict indoor gas-phase concentrations of semi-volatile organic compounds.

The indoor gas-phase concentrations of semi-volatile organic compounds (SVOCs) can be predicted from their respective concentrations in airborne particles by applying the particle/gas partitioning equilibrium. The temperature used for partitioning is often set to 25°C. However, indoor temperatures frequently differ from this reference value. This assumption may result in errors in the predicted equilibrium gas-phase SVOC concentrations. To improve the prediction model, the temperature dependence of the particle/gas partition coefficient must be addressed. In this paper, a theoretical relationship between the particle/gas partition coefficient and temperature was developed based on the SVOC absorptive mechanism. The SVOC particle/gas partition coefficients predicted by employing the derived theoretical relationship agree well with the experimental data retrieved from the literature (R>0.93). The influence of temperature on the equilibrium gas-phase SVOC concentration was quantified by a dimensionless analysis of the derived relationship between the SVOC particle/gas partition coefficient and temperature. The predicted equilibrium gas-phase SVOC concentration decreased by between 31% and 53% when the temperature was lowered by 6°C, while it increased by up to 750% when the indoor temperature increased from 15°C to 30°C.

Optimization of FLEC-SPME for field passive sampling of VOCs emitted from solid building materials.

The FLEC-SPME sampler, described in a previous paper, consists of an emission cell coupled with solid phase microextraction (SPME) for passive sampling of VOCs emitted from building materials. It represents an interesting alternative to standard dynamic sampling protocol as it is easier to implement. If standard dynamic sampling determines emission rates, passive FLEC-SPME aims to the determination of the concentration in air at the material surface. That could be assumed provided that material/air equilibrium is reached. Thus, VOCs emission kinetics were studied for 3 different materials (pine wood panel, carpet and PVC floor) to determine equilibrium times. Then, the relevance of the method has been assessed using new materials through a 3-day emission test. Qualitative results were compared to those obtained from the standard method to check the ability of FLEC-SPME to detect the most toxic compounds, named "VOCs of interest" and listed in the French regulation. Minor differences were observed, so this methodology seems promising, especially for field studies aiming in the identification of VOCs sources in buildings. Moreover, the concentration at the material surface combined to emission modeling could be used to predict indoor VOCs concentrations helping in indoor air quality diagnostic.