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Squalene can react with indoor ozone to generate a series of volatile and semi-volatile organic compounds, some of which may be skin or respiratory irritants, causing adverse health effects. Better understanding of the ozone/squalene reaction and product transport characteristics is thus important. In this study, we developed a physical-chemical coupling model to describe the behavior of ozone/squalene reaction products, that is, 6-methyl-5-hepten-2-one (6-MHO) and 4-oxopentanal (4-OPA) in the gas phase and skin, by considering the chemical reaction and physical transport processes (external convection, internal diffusion, and surface uptake). Experiments without intervention were performed in a single-family house in California utilizing time- and space-resolved measurements. The key parameters in the model were extracted from 5 day data and then used to predict the behaviors in some other days. Predictions from the present model can reproduce the concentration profiles of the three compounds (ozone, 6-MHO, and 4-OPA) well (R2 = 0.82-0.89), indicating high accuracy of the model. Exposure analysis shows that the total amount of 6-MHO and 4-OPA entering the blood capillaries in 4 days can reach 14.6 and 30.1 μg, respectively. The contribution of different sinks to ozone removal in the tested realistic indoor environment was also analyzed.

Volatile organic compounds (VOCs) emitted from furniture severely influence indoor air quality. Prior studies have mainly focused on the emissions from building materials and vehicle cabin materials, but rarely refer to indoor furniture. Considering the complex internal structure of furniture, this study presents a two-layer numerical model to describe the emission behaviors of VOCs from wooden furniture. A multi-parameter regression method was then proposed to determine the key parameters in the furniture, i.e., the initial emittable concentration, the diffusion coefficient and the partition coefficient. Experiments were conducted in a 1 m3 environmental chamber for VOC emissions from two kinds of wooden furniture (panel furniture and solid wood furniture). The agreement between model predictions and test data (R2 = 0.97–0.99) demonstrated the effectiveness of the model and measured key parameters. Compared with the traditional single-layer model, the two-layer numerical model can characterize the whole emission process from furniture better. In addition, the impact of temperature on the key parameters for furniture emissions was explored. With an increase in temperature from 23 °C to 35 °C, the diffusion coefficients for different VOCs from different wooden furniture, increase by 200%–2993%, while partition coefficients decrease by 41%–94%. This pattern conforms with that of VOC emissions from building materials. The present study should be helpful for source characterization of furniture and the associated exposure assessment.

The fate and transport of semi-volatile organic compounds (SVOCs) in residential environments is significantly influenced by emission and sorption processes, which can be characterized by three key parameters: the gas-phase SVOC concentration adjacent to the material surface (y0); the diffusion coefficient (Dm); and the partition coefficient (K). Accurate determination of these three key parameters is critical for investigating SVOC mass transfer principles, and for assessing human health risks. Based on the mass transfer process of phthalates in a ventilated chamber, a novel method is developed to simultaneously measure Dm and K (key sorption parameters) in sink materials. The Dm and K of four target phthalates in a common T-shirt (sink material) are determined, and compared with those reported in literature. Results demonstrate that the measured parameters are in good agreement with those previously reported (relative deviation

Semi-volatile organic compounds (SVOCs) are widely used in materials employed in vehicle interiors, causing poor in-cabin air quality. The emission characteristics of SVOCs from vehicle cabin materials can be characterized by two key parameters: the gas-phase SVOC concentration adjacent to the material surface (y0) and the convective mass transfer coefficient across the material surface (hm). Accurate determination of y0 and hm is fundamental in investigating SVOC emission principles and health risks. Considering that the steady state SVOC concentration (y) in a ventilated chamber changes with the ventilation rate (Q), we developed a varied ventilation rate (VVR) method to simultaneously measure y0 and hm for typical vehicle cabin materials. Experimental results for di(2-ethylhexyl)phthalate (DEHP) emissions from test materials indicated that the VVR method has the merits of simple operation, short testing time, and high accuracy. We also examined the influence of temperature (T) on y0 and hm, and found that both y0 and hm increase with increasing temperature. A theoretical correlation between y0 and T was then derived, indicating that the logarithm of y0T is linearly related to 1/T. Analysis based on the data from this study and from the literature validates the effectiveness of the derived correlation. Moreover, preliminary exposure analysis was performed to assess the health risk of DEHP in a vehicular environment.

Volatile organic chemicals are produced from reactions of ozone with squalene in human skin oil. Both primary and secondary reaction products, i.e., 6-methyl-5-hepten-2-one (6-MHO) and 4-oxopentanal (4-OPA), have been reported in indoor occupied spaces. However, the abundance of these products indoors is a function of many variables, including the amount of ozone and occupants present as well as indoor removal processes. In this study, we develop a time-dependent kinetic model describing the behavior of ozone/squalene reaction products indoors, including the reaction process and physical adsorption process of products on indoor surfaces. The key parameters in the model were obtained by fitting time-resolved concentrations of 6-MHO, 4-OPA, and ozone in a university classroom on 1 day with multiple class sessions. The model predictions were subsequently tested against observations from four additional measurement days in the same classroom. Model predictions and experimental data agreed well (R2 = 0.87–0.92...

We investigate source characteristics and emission dynamics of volatile organic compounds (VOCs) in a single-family house in California utilizing time- and space-resolved measurements. About 200 VOC signals, corresponding to more than 200 species, were measured during eight weeks in summer and five in winter. Spatially resolved measurements, along with tracer data, reveal that VOCs in the living space were mainly emitted directly into that space, with minor contributions from the crawlspace, attic or outdoors. Time-resolved measurements in the living space exhibited baseline levels far above outdoor levels for most VOCs; many compounds also displayed patterns of intermittent short-term enhancements (spikes) well above the indoor baseline. Compounds were categorized as "high-baseline" or "spike-dominated" based on indoor-to-outdoor concentration ratio and indoor mean-to-median ratio. Short-term spikes were associated with occupants and their activities, especially cooking. High-baseline compounds indicate continuous indoor emissions from building materials and furnishings. Indoor emission rates for high-baseline species, quantified with 2-h resolution, exhibited strong temperature dependence and were affected by air-change rates. Decomposition of wooden building materials is suggested as a major source for acetic acid, formic acid, and methanol, which together accounted for ~75% of the total continuous indoor emissions of high-baseline species. This article is protected by copyright. All rights reserved.

The emissions of volatile organic compounds (VOCs) from indoor furniture contribute significantly to poor indoor air quality. We have taken a typical machine learning approach using an artificial neural network (ANN), to predict the emission behaviors of VOCs from furniture. The gas-phase VOC concentrations from four kinds of furniture (solid wood furniture, panel furniture, soft leather furniture, soft cloth furniture) were measured in a 1 m3 chamber at different temperatures, relative humidity and ventilation rates. We then used these VOC concentration data as input for training. The trained ANN model could then be used to predict VOC concentrations at other emission time. We selected a back-propagation neural network, with 3 hidden layers, and a learning rate of 0.01. Pearson correlation analysis demonstrates that there is a strong correlation between the input datasets. We used relative deviation (RD) and mean absolute percentage error (MAPE) as the criteria for evaluating the performance of the ANN. For all of the tested VOCs from different types of furniture, the RDs between the predictions and experimental data at 150 h, are less than 15%. The MAPE values of the ANN model are within 10%. These indicate that the trained ANN model has excellent capability in predicting the VOC concentrations from furniture. The main merit of the ANN is that it doesn't need to solve the challenging problem of obtaining the key parameters when using physical models for prediction, and will thus be very useful for indoor source characterization, as well as for exposure assessment.

Among many environments, the motor vehicle cabin microenvironment has been of particular public concern. Although commuters typically spend only 5.5% of their time in vehicles, the emissions from various interior components of motor vehicles as well as emissions from exhaust fumes carried by ventilation supply air are significant sources of harmful air pollutants that could lead to unhealthy human exposure due to their high concentrations inside vehicles' cabins. This review summarizes significant findings in the literature on air quality inside vehicle cabins, including chemical species, related sources, measurement methodologies and control measures. More than 90 relevant studies performed across over 10 countries were carefully reviewed. These comprised more than 2000 individual road trips, where concentrations of numerous air pollutants were determined. Ultrafine particles, aromatic hydrocarbons, carbonyls, semi-volatile organic compounds and microbes have been identified as the primary air pollutants inside vehicle cabins. Air recirculation with high-efficiency air filter has been reported as the most effective measure to lower air pollutant concentrations. Future work should focus on investigating the health risks of exposure to various air pollutants inside different vehicles and further developing advanced air filter to improve the in-cabin air quality.

Background Recent studies have found that particulate matter (PM) attached radioactivity was associated with certain adverse health effects including increased blood pressure and lung dysfunction. However, there has been no investigation on the direct effect of PM radioactivity on mortality. Methods Exposures to ambient PM gamma activities were determined using U.S. EPA RadNet data. Data on daily deaths were obtained from individual state Departments of Public Health. We used a generalized additive quasi-Poisson model to estimate the associations between two-day average ambient PM gamma activities (gamma2 through gamma9) with all-cause non-accidental and cardiovascular daily deaths for each of 18 US cities, for each season, adjusting for two-day average PM2.5 exposure, temperature, relative humidity, day of week and long-term trends. Subsequently, we used random-effects meta-analysis to estimate the overall effect in the 18 cities for each season. Results We found that all-cause non-accidental daily mortality in spring season was positively associated with two-day average ambient PM gamma activities in spring, with significant results for gamma2, gamma5 and gamma6. Similarly, cardiovascular daily mortality was positively associated with two-day average ambient PM gamma activities, with significant results for gamma2, gamma4, gamma5, gamma6, gamma7 and gamma9. For the spring season, each interquartile range (IQR) increase of two-day averaged ambient PM gamma activity was associated with increase in all-cause daily deaths, ranging from 0.15% (95% Confidence Interval (CI): −0.36%, 0.65%) to 1.03 (95%CI: 0.18%, 1.89%). Each IQR was also associated with increase in cardiovascular daily deaths, ranging from 0.01% (95%CI: −0.89, 0.92) to 2.95% (95%CI: 1.33, 4.59). For other seasons overall we found statistically insignificant associations of PM radioactivity with mortality. Conclusions Our findings suggest that there are potential systemic toxic effects of inhalation of radionuclides attached to ambient air particles.

Emissions of volatile organic compounds (VOCs) from building materials/furniture can be characterized by three key parameters: the initial emittable concentration (C0), the diffusion coefficient (Dm), and the partition coefficient (K). These parameters provide the basis for realizing effective source control, as well as for evaluating health risks. In this study, we propose a general regression method to accurately and rapidly measure the three key parameters of VOC emissions from building materials/furniture in a ventilated chamber. This method firstly establishes the relationship between the three key parameters and the first root of the analytical solution describing VOC emissions, and this root is then determined by curve regression. Compared with previous regression methods which need to fit two or three parameters simultaneously, the main merit of the present method lies in that it just needs to fit one parameter and thus can get a unique solution. We tested panel furniture in a ventilated chamber to measure the three key parameters of some common VOCs. Results indicate that the model predictions based on the parameters determined via this new method agree well with experimental data, which validates the reliability of this proposed method. Analyzing data from the literature further demonstrates the accuracy of this method. The present method involves chamber testing under ventilated conditions only, which is consistent with the testing conditions for many standards, thus will benefit routine laboratory testing.

© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Residences represent an important site for bioaerosol exposure. We studied bioaerosol concentrations, emissions, and exposures in a single-family residence in northern California with 2 occupants using real-time instrumentation during 2 monitoring campaigns (8 weeks during August-October 2016 and 5 weeks during January-March 2017). Time- and size-resolved fluorescent biological aerosol particles (FBAP) and total airborne particles were measured in real time in the kitchen using an ultraviolet aerodynamic particle sizer (UVAPS). Time-resolved occupancy status, household activity data, air-change rates, and spatial distribution of size-resolved particles were also determined throughout the house. Occupant activities strongly influenced indoor FBAP levels. Indoor FBAP concentrations were an order of magnitude higher when the house was occupied than when the house was vacant. Applying an integral material-balance approach, geometric mean of total FBAP emissions from human activities observed to perturb indoor levels were in the range of 10-50 million particles per event. During the summer and winter campaigns, occupants spent an average of 10 and 8.5 hours per day, respectively, awake and at home. During these hours, the geometric mean daily-averaged FBAP exposure concentration (1-10 μm diameter) was similar for each subject at 40 particles/L for summer and 29 particles/L for winter.

Characterization of indoor emissions of cyclic volatile methylsiloxanes (cVMS) due to the use of personal care products is important for elucidating indoor air composition and associated health risks. This manuscript describes a mass transfer model to characterize the emission behaviors of decamethylcyclopentasiloxane (D5, the most abundant indoor cVMS) from skin lipids. A C-history method is introduced to determine the key parameters in the model, i.e., the initial concentration and diffusion coefficient of D5 inside the skin lipids. Experiments were conducted in a university classroom to examine the D5 emission behaviors by using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS). Data from the first class session of two typical days was applied to obtain the key parameters, which were subsequently used for predicting D5 concentrations in other class sessions. Good agreement between model predictions and experiments demonstrates the effectiveness of the model and parameter determination method. With the model, we found that the reuse of personal care products has a significant impact on the D5 emissions. In addition, the time-dependent emission rate and remaining amount of D5 inside the skin can also be calculated. These results indicate a fast decay pattern during the initial emission period, which is consistent with prior experimental studies.

The accurate and rapid determination of the emission parameters of semi-volatile organic compounds (SVOCs) from indoor materials is of great importance for estimating and controlling indoor exposure. By virtue of a simplified mass transfer model we derived, a new method called the early stage C-history method, has been developed to measure the key emission parameters: the gas phase SVOC concentration adjacent to the material surface (y0) and the convective mass transfer coefficient (hm). We validate this model using experimental data found in the literature. When compared with established methods, the new method has the following salient features: (1) rapid (the experimental time is reduced from several months to several days); (2) accurate (R2 in the range of 0.92–0.97). Further analysis shows that both features can be further improved if the test system has a smaller chamber wall/air partition coefficient. The new method is also extended to measure the key parameters of SVOCs from sorption materials. This method should prove useful for screening SVOC emission characteristics and for assessing exposure, as well as for chamber and test design.

Mass transfer is key to understanding and controlling indoor airborne organic chemical contaminants (e.g., VVOCs, VOCs, and SVOCs). In this study, we first introduce the fundamentals of mass transfer and then present a series of representative works from the past two decades, focusing on the most recent years. These works cover: (i) predicting and controlling emissions from indoor sources, (ii) determining concentrations of indoor air pollutants, (iii) estimating dermal exposure for some indoor gas-phase SVOCs, and (iv) optimizing air-purifying approaches. The mass transfer analysis spans the micro-, meso-, and macroscales and includes normal mass transfer modeling, inverse problem solving, and dimensionless analysis. These representative works have reported some novel approaches to mass transfer. Additionally, new dimensionless parameters such as the Little number and the normalized volume of clean air being completely cleaned in a given time period were proposed to better describe the general process characteristics in emissions and control of airborne organic compounds in the indoor environment. Finally, important problems that need further study are presented, reflecting the authors' perspective on the research opportunities in this area.

Emissions of formaldehyde from building materials and furniture can cause adverse health effects. Traditional models generally only consider emissions as a physical process that can be characterized by three key parameters: the initial emittable concentration, the diffusion coefficient and the partition coefficient. However, the physical-based model causes discrepancy in predicting long-term formaldehyde emissions for the cases where chemical reaction (i.e., hydrolysis) occurs over time. In this study, an improved mechanism-based model was developed by combining the chemical reaction process with a physical mass transfer process to more accurately predict the long-term emission behaviors. The chamber testing data of formaldehyde emissions from exposed edges and seams of a laminate flooring product made with composite wood core for about 1.5 year was used to validate the model. Results indicate that the mechanism-based model characterizes well the long-term formaldehyde emissions from the tested material. Predictions of different models further demonstrate the advantages of this improved model compared with the physical model or with empirical models. This study is the first attempt to check the feasibility of including the chemical reaction term in emission modeling and to quantitatively explore the importance of its contribution to long-term formaldehyde emissions, which includes most of the indoor emissions from materials and furniture. Keywords: Building material, Formaldehyde, Mechanism-based model, Long-term emission, Indoor air quality

The emissions of volatile organic compounds (VOCs) from furniture contribute significantly to indoor air pollution. The majority of studies focus on the emission behaviors of building materials, and seldom consider furniture. This study develops a novel prediction-correction method to determine the three key parameters characterizing VOC emissions from furniture: the initial emittable concentration, the diffusion coefficient, and the partition coefficient. In addition, a simplified model is proposed to simulate the VOC emission behaviors, which owns the merits of simple form and high accuracy. Experiments investigating VOC emissions from two kinds of composite wood furniture under ventilated conditions were conducted to determine the key parameters. The calculated gas-phase concentrations based on these parameters and the simplified model agree well with experimental data from the ventilated chamber, demonstrating the effectiveness of the proposed measurement method and the simplified model. The application range of the model is then obtained through dimensionless analysis, and the model is further extended to evaluate VOC emissions for other loading ratios. This study is the first attempt to simultaneously and rapidly measure the three key parameters for furniture-VOC combinations under ventilated conditions, and should be helpful for enriching the database, and for the rapid screening of VOC emissions from furniture.

Solid-phase microextraction (SPME) is regarded as a nonexhaustive sampling technique with a smaller extraction volume and a shorter extraction time than traditional sampling techniques and is hence widely used. The SPME sampling process is affected by the convection or diffusion effect along the coating surface, but this factor has seldom been studied. This paper derives an analytical model to characterize SPME sampling for semivolatile organic compounds (SVOCs) as well as for volatile organic compounds (VOCs) by considering the surface mass transfer process. Using this model, the chemical concentrations in a sample matrix can be conveniently calculated. In addition, the model can be used to determine the characteristic parameters (partition coefficient and diffusion coefficient) for typical SPME chemical samplings (SPME calibration). Experiments using SPME samplings of two typical SVOCs, dibutyl phthalate (DBP) in sealed chamber and di(2-ethylhexyl) phthalate (DEHP) in ventilated chamber, were performed to measure the two characteristic parameters. The experimental results demonstrated the effectiveness of the model and calibration method. Experimental data from the literature (VOCs sampled by SPME) were used to further validate the model. This study should prove useful for relatively rapid quantification of concentrations of different chemicals in various circumstances with SPME.

Temperature and relative humidity can simultaneously change in indoor environment, which significantly affect the emission rate of formaldehyde and volatile organic compounds (VOCs) from building materials. Prior studies generally focus on the single effect of temperature or relative humidity, and the combined effect is not considered. This paper investigates the comprehensive influence of temperature and relative humidity on the emission rate of pollutants from building materials. Correlation between the emission rate and the combined environmental factors is derived theoretically. Data in literature are applied to validate the effectiveness of the correlation. With the correlation, the indoor formaldehyde concentration in summer is predicted to be 1.63 times of that in winter in Beijing, which is approximately consistent with surveyed data. In addition, a novel approach is proposed to assess the human health impact due to pollutants emitted from building materials at varied temperature and relative humidity. An association between the human carcinogenic potential (HCP) and the environmental factors is obtained. By introducing a reference room model developed previously, it is calculated that the HCP of bedroom at high relative humidity (70%, 25°C) for formaldehyde exceeds 10-4 cases, meaning high cancer health risk. This study should prove useful for evaluating the emission behaviors and the associated exposure of pollutants from building materials at varied environmental conditions.

Humidity is one of the main environmental factors affecting the emission rate and key parameters of formaldehyde and volatile organic compounds (VOCs) from building materials. Meanwhile, the initial emittable concentration (Cm,0) is proved to be the most sensitive key parameter to the emission behaviours. However, there is no report on the relationship between humidity and Cm,0. In this paper, Cm,0 of formaldehyde and hexaldehyde from a type of medium density fiberboard in absolute humidity (AH) range of 4.6–19.6 g/m3 at 25 °C were tested by virtue of a C-history method. Experimental results indicate that Cm,0 is dramatically dependent on AH, increased by 10 and 2 times for formaldehyde and hexaldehyde when AH rising from 4.6 g/m3 to 19.6 g/m3. A linear relationship between the logarithm of Cm,0 and AH is obtained based on the measured results. In addition, a correlation characterizing the association of emission rate and AH is derived. The effectiveness of the correlation is verified with our experimental results as well as data from literature. With the correlations, the Cm,0 or emission rate different from the test AH conditions can be conveniently obtained. This study should be useful for predicting the emission characteristics of humidity changing scenarios and for source control.