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The emissions of volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) from indoor building and vehicle cabin materials can adversely affect human health. Many mechanistic models to predict the VOC/SVOC emission characteristics have been proposed. Nowadays, the main obstacle to accurate model prediction is the availability and reliability of the physical parameters used in the model, such as the initial emittable concentration, the diffusion coefficient, the partition coefficient, and the gas-phase SVOC concentration adjacent to the material surface. The purpose of this work is to review the existing methods for measuring the key parameters of VOCs/SVOCs from materials in both indoor and vehicular environments. The pros and cons of these methods are analyzed, and the available datasets found in the literature are summarized. Some methods can determine one single key parameter, while other methods can determine two or three key parameters simultaneously. The impacts of multiple factors (temperature, relative humidity, loading ratio, and air change rate) on VOC/SVOC emission behaviors are discussed. The existing measurement methods span very large spatial and time scales: the spatial scale varies from micro to macro dimensions; and the time scale in chamber tests varies from several hours to one month for VOCs, and may even span years for SVOCs. Based on the key parameters, a pre-assessment approach for indoor and vehicular air quality is introduced in this review. The approach uses the key parameters for different material combinations to pre-assess the VOC/SVOC concentrations or human exposure levels during the design stage of buildings or vehicles, which can assist designers to select appropriate materials and achieve effective source control.

The emissions of volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) from indoor materials pose an adverse effect on people’s health. In this study, a new analytical model was developed to simulate the emission behaviors for both VOCs and SVOCs under ventilated conditions. Based on this model, we further introduced a hybrid optimization method to accurately determine the key parameters in the model: the initial emittable concentration, the diffusion coefficient, the material/air partition coefficient, and the chamber surface/air partition coefficient (for SVOCs). Experiments for VOC emissions from solid wood furniture were performed to determine the key parameters. We also evaluated the hybrid optimization method with the data of flame retardant emissions from polyisocyanurate rigid foam and VOC emissions from a panel furniture in the literature. The correlation coefficients are high during the fitting process (R2 = 0.92–0.99), demonstrating effectiveness of this method. In addition, we observed that chemical properties could transfer from SVOC-type to VOC-type with the increase of temperature. The transition temperatures from SVOC-type to VOC-type for the emissions of tris(2-chloroethyl) phosphate (TCEP) and tris(1-chloro-2-propyl) phosphate (TCIPP) were determined to be about 45 ℃ and 35 ℃, respectively. The present study provides a unified modelling and methodology analysis for both VOCs and SVOCs, which should be very useful for source/sink characterization and control.

Volatile organic compounds (VOCs) emitted from building and vehicle cabin materials seriously affect indoor and in-cabin air quality, as well as human health. Previous studies revealed that some VOCs from building materials could react with ozone to affect the concentration levels of the indoor environment, but seldom refers to vehicle cabin materials. In this study, we performed experimental investigation for two kinds of vehicle cabin materials (car carpet, sealing strip) and one furniture material (medium-density fiberboard) by conducting small-scale chamber tests under two different conditions, with ozone (about 110 μg/m3) and without ozone (about 10 μg/m3), to explore the effect of in-cabin chemistry on VOC emissions. We observed the VOC concentration changes in the two scenarios and found that ozone had a significant impact on the concentrations of aldehydes and ketones while having little impact on the concentrations of benzene series. We introduced a gain ratio to quantitatively reflect the concentration changes in the presence of ozone. The gain ratio for aldehydes and ketones is greater than one, while that for the benzene series is basically around one with a small fluctuation range. This study demonstrates that ozone can react with VOCs containing unsaturated carbon–carbon bonds or carbon–oxygen bonds emitted from varied materials to produce aldehydes and ketones, which will further reduce indoor and in-cabin air quality.

This study investigates the contribution of formaldehyde from residential building materials to ambient air in mainland China. Based on 265 indoor field tests in 9 provinces, we estimate that indoor residential sources are responsible for 6.66% of the total anthropogenic formaldehyde in China’s ambient air (range for 31 provinces: 1.88–18.79%). Residential building materials rank 6th among 81 anthropogenic sources (range: 2nd–10th for 31 provinces). Emission intensities show large spatial variability between and within regions due to different residential densities, emission characteristics of building materials, and indoor thermal conditions. Our findings indicate that formaldehyde from the indoor environment is a significant source of ambient formaldehyde, especially in urban areas. This study will help to more accurately evaluate exposure to ambient formaldehyde and its related pollutants, and will assist in formulating policies to protect air quality and public health.

To avoid a sharp rise in temperature in the cabin of parked vehicles exposed to solar radiation, experienced drivers leave some windows partly open when the vehicle is parked in the sunlight to achieve cooling through natural ventilation. However, the effectiveness of this measure to reduce the temperature under different weather conditions has not been verified. To this end, this study investigates the effect of open windows on the thermal environment of a vehicle under different environmental conditions. A field measurement, in which two identical vehicles with and without window gaps were used, was carried out in Daxing District, Beijing. The measurements were conducted for 15 days under different window gaps and ambient conditions. The results revealed that open windows resulted in a maximum temperature reduction of 6.7 °C in cabin air temperature under high temperature and high solar radiation, while only 0.6 °C can be reduced under low temperature and low solar radiation. The results also showed that when window gaps effectively reduce the air temperature, lower air temperature can be obtained with larger open-window areas.

Volatile organic compounds (VOCs) emitted from vehicle parts and interior materials can seriously affect in-cabin air quality. Prior studies mainly focused on indoor material emissions, while studies of emissions in-cabins were relatively scarce. The emission behaviors of VOCs from vehicle cabin materials can be characterized by three key emission parameters: the initial emittable concentration (C0), diffusion coefficient (Dm), and partition coefficient (K). Based on a C-history method, we have performed a series of tests with a 30 L small-scale chamber to determine these three key emission parameters for six VOCs, benzene, toluene, ethylbenzene, xylene, formaldehyde, and acetaldehyde, from typical vehicle cabin materials, car roof upholstery, carpet, and seat. We found that acetaldehyde had the highest level in the gas-phase concentration and C0, which differs from residential indoor environments where formaldehyde is usually the most prevalent pollutant. The influence of temperature on the key emission parameters was also investigated. When the temperature rose from 25 °C to 65 °C, C0 increased by 40–640%, Dm increased by 40–170%, but K decreased by 38–71% for different material-VOC combinations. We then performed an independent validation to demonstrate the accuracy of the measured key emission parameters. Furthermore, considering that in reality, several materials coexist in vehicle cabins, we made a first attempt at applying a multi-source model to predict VOC emission behaviors in a simulated 3 m3 vehicle cabin, using the key emission parameters obtained from the small-scale chamber tests. The good agreement between the predictions and experiments (R2 = 0.82–0.99) demonstrated that the three key emission parameters measured via chamber tests can be scaled to estimate emission scenarios in realistic vehicle cabin environments. A pollution contribution analysis for the tested materials indicated that the car seat could significantly contribute to the total emissions.

Material emission and ventilation are two aspects influencing indoor air quality. In this study, a model predictive control (MPC) strategy is proposed for intermittent ventilation system in office buildings, to achieve a healthy indoor environment. The strategy is based on a dynamic model for predicting emissions of volatile organic compounds (VOCs) from materials. The key parameters of formaldehyde from panel furniture in the model are obtained by an improved C-history method and large-scale chamber experiments. The effectiveness of the determined key parameters is validated, which are then used to predict the formaldehyde concentration variation and the pre-ventilation time in a typical office room. In addition, the influence of some main factors (i.e., vacant time, loading ratio, air change rate) on the pre-ventilation time is analyzed. Results indicate that the pre-ventilation time of the intermittent ventilation system ranges from several minutes to several hours. The pre-ventilation time decreases exponentially with the increase in the vacant time, the air change rate, and with the decrease in the loading ratio. When the loading ratio of the furniture is 0.30 m2/m3 and the vacant time is 100 days, the required pre-ventilation time approaches zero. Results further reveal that an air change rate of 2 h−1 is the most effective means for rapid removal of indoor formaldehyde for the cases studied. The proposed strategy should be helpful for achieving effective indoor pollution control.

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 steady state VOC concentration in automobile cabin is taken as a good indicator to characterize the material emission behaviors and evaluate the vehicular air quality. Most studies in this field focus on experimental investigation while theoretical analysis is lacking. In this paper we firstly develop a simplified physical model to describe the VOC emission from automobile materials, and then derive a theoretical correlation between the steady state cabin VOC concentration (Ca) and temperature (T), which indicates that the logarithm of Ca/T0.75 is in a linear relationship with 1/T. Experiments of chemical emissions in three car cabins at different temperatures (24°C, 29°C, 35°C) were conducted. Eight VOCs specified in the Chinese National Standard GB/T 27630-2011 were taken for analysis. The good agreement between the correlation and experimental results from our tests, as well as the data taken from literature demonstrates the effectiveness of the derived correlation. Further study indicates that the slope and intercept of the correlation follows linear association. With the derived correlation, the steady state cabin VOC concentration different from the test conditions can be conveniently obtained. This study should be helpful for analyzing temperature-dependent emission phenomena in automobiles and predicting associated health risks.

Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs) and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0), the diffusion coefficient (D), and the partition coefficient (K), can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

The diffusion coefficient (D(m)) and material/air partition coefficient (K) are two key parameters characterizing the formaldehyde and volatile organic compounds (VOC) sorption behavior in building materials. By virtue of the sorption process in airtight chamber, this paper proposes a novel method to measure the two key parameters, as well as the convective mass transfer coefficient (h(m)). Compared to traditional methods, it has the following merits: (1) the K, D(m) and h(m) can be simultaneously obtained, thus is convenient to use; (2) it is time-saving, just one sorption process in airtight chamber is required; (3) the determination of h(m) is based on the formaldehyde and VOC concentration data in the test chamber rather than the generally used empirical correlations obtained from the heat and mass transfer analogy, thus is more accurate and can be regarded as a significant improvement. The present method is applied to measure the three parameters by treating the experimental data in the literature, and good results are obtained, which validates the effectiveness of the method. Our new method also provides a potential pathway for measuring h(m) of semi-volatile organic compounds (SVOC) by using that of VOC.

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. [ABSTRACT FROM AUTHOR]

The initial emittable concentration (Cm,0) is a key parameter characterizing the emission behaviors of formaldehyde from building materials, which is highly dependent on temperature but has seldom been studied. Our previous study found that Cm,0 is much less than the total concentration (C0,total, used for labeling material in many standards) of formaldehyde. Because Cm,0 and not C0,total directly determines the actual emission behaviors, we need to determine the relationship between Cm,0 and C0,total so as to use Cm,0 as a more appropriate labeling index. By applying statistical physics theory, this paper derives a novel correlation between the emittable ratio (Cm,0/C0,total) and temperature. This correlation shows that the logarithm of the emittable ratio multiplied by power of 0.5 of temperature is linearly related to the reciprocal of temperature. Emissions tests for formaldehyde from a type of medium density fiberboard over the temperature range of 25.0-80.0 °C were performed to validate the correlation. Experimental results indicated that Cm,0 (or emittable ratio) increased significantly with increasing temperature, this increase being 14-fold from 25.0 to 80.0 °C. The correlation prediction agreed well with experiments, demonstrating its effectiveness in characterizing physical emissions. This study will be helpful for predicting/controlling the emission characteristics of pollutants at various temperatures. [ABSTRACT FROM AUTHOR]

The emission rate is considered to be a good indicator of the emission characteristics of formaldehyde and volatile organic compounds (VOCs) from building materials. In contrast to the traditional approach that focused on an experimental study, this paper uses a theoretical approach to derive a new correlation to characterize the relationship between the emission rate and temperature for formaldehyde emission. This correlation shows that the logarithm of the emission rate by a power of 0.25 of the temperature is linearly related to the reciprocal of the temperature. Experimental data from the literature were used to validate the derived correlation. The good agreement between the correlation and experimental results demonstrates its reliability and effectiveness. Using the derived correlation, the emission rate at temperatures other than the test condition can be obtained, greatly facilitating engineering applications. Further analysis indicates that the temperature-related emission rate of other scenarios, i.e., the standard emission reference and semi-volatile organic compounds (SVOCs), also conforms to the same correlation as that of formaldehyde. The molecular dynamics theory is introduced to preliminarily understand this phenomenon. Our new correlation should prove useful for estimating the emission characteristics of chemicals from materials that are subject to changes in temperature. [ABSTRACT FROM AUTHOR]

The initial emittable formaldehyde and VOC concentration in building materials (C0) is a key parameter for characterizing and classifying these materials. Various methods have been developed to measure this parameter, but these generally require a long test time. In this paper we develop a convenient and rapid method, the variable volume loading (VVL) method, to simultaneously measure C0 and the material/air partition coefficient (K). This method has the following features: (a) it requires a relatively short experimental time (less than 24 h for the cases studied); and (b) is convenient for routine measurement. Using this method, we determined C0 and K of formaldehyde, propanal and hexanal in one kind of medium density fiberboard, and repeated experiments were performed to reduce measurement error. In addition, an extended-C-history method is proposed to determine the diffusion coefficient and the convective mass transfer coefficient. The VVL method is validated by comparing model predicted results based on the determined parameters with experimental data. The determined C0 of formaldehyde obtained via this method is less than 10% of the total concentration using the perforator method recommended by the Chinese National Standard, suggesting that the total concentration may not be appropriate to predict emission characteristics, nor for material classification. [ABSTRACT FROM AUTHOR]

The initial emittable concentration (cm.0), the diffusion coefficient (Dm), and the material/air partition coefficient (K) are the three characteristic parameters influencing emissions of formaldehyde and volatile organic compounds (VOCs) from building materials or furniture. It is necessary to determine these parameters to understand emission characteristics and how to control them. In this paper we develop a new method, the C-history method for a closed chamber, to measure these three parameters. Compared to the available methods of determining the three parameters described in the literature, our approach has the following salient features, (1) the three parameters can be simultaneously obtained; (2) it is time-saving generally taking less than 3 days for the cases studied (the available methods tend to need 7-28 days); (3) the maximum relative standard deviations of the measured Cm,0 Dm and K are 8.5%, 7.7%, and 9.8%, respectively, which are acceptable for engineering applications. The new method was validated by using the characteristic parameters determined in the dosed chamber experiment to predict the observed emissions in a ventilated flail scale chamber experiment, proving that the approach is reliable and convincing. Our new C-history method should prove useful for rapidly determining the parameters required to predict formaldehyde and VOC emissions from building materials as well as for furniture labeling. [ABSTRACT FROM AUTHOR]

This paper first derives an analytical solution based on Laplace transformation for describing the volatile organic compounds (VOCs) and formaldehyde emission characteristics from building materials in a static chamber; the modelling method is then validated by application using previously reported experimental data. Based on the analytical solution and normalised analysis, the VOC emission characteristics can be advantageously deduced by scaling in dimensionless forms. The findings of this study shows that the dimensionless emission rate is a function of three dimensionless parameters: the ratio of the mass transfer Biot number to the partition coefficient; the mass transfer Fourier number; and the ratio of the VOC mass in the building material to that measured in the chamber at equilibrium. A group of dimensionless correlations for predicting the dimensionless emission rate were obtained through numerical simulation and characteristic parameter regression, and this was verified by experimental data. The dimensionless correlations are simple to use, and would allow scaling of the emission characteristics obtained from the static chamber to the more realistic conditions of a building and this would be useful for design engineer to minimize emissions of VOCs and formaldehyde in building environments. [ABSTRACT FROM AUTHOR]