Formaldehyde emission behavior of building materials: on-site measurements and modeling approach to predict indoor air pollution

Insight into the effect of exposed crystal facets of anatase TiO2 on HCHO catalytic oxidation of Mn-Ce/TiO2

Indoor formaldehyde pollution seriously jeopardizes human health. The development of efficient and stable non-precious metal catalysts for low-temperature catalytic degradation of formaldehyde is a promising approach. In this study, TiO2 {001} and {101} supports were loaded with different ratios of Mn and Ce active components, and the effects of the ratios of the active components on the catalytic activity were investigated. The elemental oxidation states, redox capacities, active oxygen mobilities and acid site distributions of the catalysts were determined using characterization techniques such as XPS, H2-TPR, O2-TPD, and NH3-TPD. In situ infrared spectroscopy was utilized to reveal the differences in the two-step dehydrogenation reactions of dioxymethylene (DOM) in 5Mn1Ce/Ti-NS and 5Mn1Ce/Ti-NP. Density-functional theory was used to investigate the differences in the catalytic steps and maximum energy barriers of Mn-Ce/Ti-NS and Mn-Ce/Ti-NP for HCHO. The differences in catalytic activity due to the influence of the manganese and cerium active components on the {001} and {101} crystal faces of anatase titanium dioxide are comprehensively revealed. Exposure of the supported crystalline surfaces alters the catalytic activity centers and reaction pathways at the molecular level. This study provides experimental and theoretical guidance for the selection of exposed crystalline surfaces for loaded catalysts.

Density functional theory-based screening of Ti4C3O2-loaded single atoms for efficient selective catalytic oxidation of formaldehyde

Indoor formaldehyde (HCHO) pollution poses a major risk to human health. Low-temperature catalytic oxidation is an effective method for HCHO removal. The high activity and selectivity of single atomic catalysts provide a possibility for the development of efficient non-precious metal catalysts. In this study, the most stable single-atom catalyst Ti-Ti4C3O2 was screened by density functional theory among many single atomic catalysts with two-dimensional (2D) monolayer Ti4C3O2 as the support. The computational results show that Ti-Ti4C3O2 is highly selective to HCHO and O2 in complex environments. The HCHO oxidation reaction pathways are proposed based on the Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) mechanisms. According to the reaction energy and energy span models, the E-R mechanism has a lower maximum energy barrier and higher catalytic efficiency than the L-H mechanism. In addition, the stability of the Ti-Ti4C3O2 structure and active center was verified by diffusion energy barrier and ab initio molecular dynamics simulations. The above results indicate that Ti-Ti4C3O2 is a promising non-precious metal catalyst. The present study provides detailed theoretical insights into the catalytic oxidation of HCHO by Ti-Ti4C3O2, as well as an idea for the development of efficient non-precious metal catalysts based on 2D materials.

A Review of Artificial Neural Network Models Applied to Predict Indoor Air Quality in Schools

BACKGROUND

Indoor air quality (IAQ) in schools can affect the performance and health of occupants, especially young children. Increased public attention on IAQ during the COVID-19 pandemic and bushfires have boosted the development and application of data-driven models, such as artificial neural networks (ANNs) that can be used to predict levels of pollutants and indoor exposures.

METHODS

This review summarises the types and sources of indoor air pollutants (IAP) and the indicators of IAQ. This is followed by a systematic evaluation of ANNs as predictive models of IAQ in schools, including predictive neural network algorithms and modelling processes. The methods for article selection and inclusion followed a systematic, four-step process: identification, screening, eligibility, and inclusion.

RESULTS

After screening and selection, nine predictive papers were included in this review. Traditional ANNs were used most frequently, while recurrent neural networks (RNNs) models analysed time-series issues such as IAQ better. Meanwhile, current prediction research mainly focused on using indoor PM2.5 and CO2 concentrations as output variables in schools and did not cover common air pollutants. Although studies have highlighted the impact of school building parameters and occupancy parameters on IAQ, it is difficult to incorporate them in predictive models.

CONCLUSIONS

This review presents the current state of IAQ predictive models and identifies the limitations and future research directions for schools.

Microchamber Extraction and Analytical Pyrolysis to Explore Volatile Organic Compounds from Compression-Cooking Wood Materials Obtained under Different Conditions

Volatile organic compounds are species of concern for indoor air quality. They are emitted from a wide range of indoor sources and in particular from construction materials. Industrialized wood-based panels made from various types of wood bonded with thermosetting adhesive resins have been shown to emit volatile organic compounds over months or even years mostly due to the petrochemical binders. Some studies have been conducted on binderless panels, but they mainly focused on the pressing parameters to be applied to optimize the panel characteristics. The aim of this research is to document the emissions from binderless panels and to access the volatile composition of wood processing through the molding of materials. For this purpose, binderless boards were manufactured from hardwoods, known to emit less than softwoods with different thermopressing temperatures and times. Emissions were studied by placing the materials in microchambers. Volatile organic compounds were then sampled and analyzed by various chromatographic methods. On the other hand, materials were pyrolyzed and then analyzed by gas chromatography and mass spectrometry. The implemented protocols proved suitable for the determination of more than 40 organic compounds, among which are aldehydes, aromatics, furans and derivatives, and carboxylic acids.

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.

A Time-Varying Model for Predicting Formaldehyde Emission Rates in Homes

Recent studies have succeeded in relating emissions of various volatile organic compounds to material mass diffusion transfer using detailed empirical characteristics of each of the individual emitting materials. While significant, the resulting models are often scenario specific and/or require a host of individual component parameters to estimate emission rates. This study developed an approach to estimate aggregated emissions rates based on a wide number of field measurements. We used a multi-parameter regression model based on previous mass transfer models to predict formaldehyde emission rate for a whole dwelling using field-measured, time-resolved formaldehyde concentrations, air exchange rates, and indoor environmental parameters in 63 California single-family houses built between 2011 and 2017. The resulting model provides time-varying formaldehyde emission rates, normalized by floor area, for each study home, assuming a well-mixed mass balance transport model of the home, and a well-mixed layer transport model of indoor surfaces. The surface layer model asserts an equilibrium concentration within the surface layer of the emitted materials that is a function of temperature and RH; the dwelling ventilation rate serves as a surrogate for indoor concentration. We also developed a more generic emission model that is suitable for broad prediction of emission for a population of buildings. This model is also based on measurements aggregated from 27 homes from the same study. We showed that errors in predicting household formaldehyde concentrations using this approach were substantially less than those using a traditional constant emission rate model, despite requiring less unique building information.

Probabilistic Prediction Models and Influence Factors of Indoor Formaldehyde and VOC Levels in Newly Renovated Houses

Rapid urbanization has promoted house renovations and refurbishment in urban and rural cities. Indoor pollutants emitted through renovations and refurbishment processes have raised public concerns owing to their adverse effects on human health. In the present study, the sources of formaldehyde and specific volatile organic compounds (VOCs) are used to model the health effects associated with exposure to formaldehyde and specific VOCs and the loading factors of building materials for newly renovated homes. The present study is carried out to identify the sources of formaldehyde and specific VOCs in newly renovated houses and develop probabilistic prediction models of the health effects to explore the health risks of residents and the potential contributions of multilayer wood materials responsible for indoor pollutants. In living rooms and bedrooms, the average concentrations of formaldehyde and TVOCs in closed window conditions were higher than those in opened window conditions. Multi-layer wooden structures were a significant predictor of indoor VOC concentrations in houses. The 95 percentile values of Monte Carlo simulations (MCS P95) of the hazard index and cancer risk were lower and slightly higher than the acceptable level, respectively. Prediction models for the concentrations of formaldehyde and selected VOCs in newly renovated houses were first established using probabilistic and sensitive approaches. The multi-layer wood materials, including the wooden floor, cold paint multi-layer wooden materials, and multi-layer materials for system furniture, were responsible for the contribution of these levels of formaldehyde and selected VOCs in the newly renovated houses. Our results provide a strategy for eliminating indoor pollutants emitted from construction and building/furnishing materials.

Suspension of pheromone microcapsules on vine leaves acting as passive dispensers against pests

Pheromones are increasingly used as alternatives to pesticides to protect vineyards against L. botrana, a key grape pest. To diffuse (7E,9Z)-7,9-dodecadien-1-ylacetate, the L. botrana pheromone, passive, or aerosol dispensers are commonly applied. This paper deals with another method based on spraying an aqueous formulation, Lobesia Pro Spray, containing the pheromone encapsulated in a resin. The objectives were to assess the ability of vine leaves to act as pheromone dispensers and to check that encapsulation protects the plant from pheromone penetration. Laboratory testing based on an emission cell combined with airborne pheromone measurements by active sampling on sorbent tubes followed by ATD-GC-MS analysis was developed to accurately characterise the release of the pheromone into the air. Release kinetics analysis performed on the vine leaves showed a high pheromone release (about 30% of the sprayed quantity) the first day of the test. The release rate then decreased rapidly to reach about 650 mg/day/ha after 4 days. Kinetic modelling showed that it would be possible to maintain an effective airborne concentration of pheromone for approximately 12 days. Release tests were also carried out on glass, PVC and blotting paper. The results obtained showed that the vine leaves behaved as a non-absorbent material, implying that the pheromone used in the Lobesia Pro Spray formulation did not penetrate the plant. These first results prove the feasibility of using vine leaves as pheromone dispensers for a sprayed formulation and the ability to optimise the treatment conditions (dose and frequency) through laboratory testing.

Challenges of a Healthy Built Environment: Air Pollution in Construction Industry

Air pollution is a global concern, especially in cities and urban areas, and has many implications for human health and for the environment. In common with other industrial sectors, the construction industry emits air pollutants. In scientific literature, the contribution the construction industry makes to air pollution is underexposed. This systematic literature review (SLR) paper gives an overview of the current literature regarding air pollution within the construction industry. Air pollution is discussed focusing mainly on three levels: (i) buildings and their building life cycle stages, (ii) construction processes and components, and (iii) building material and interior. The final sample of the SLR comprises 161 scientific articles addressing different aspects of the construction industry. The results show that most articles address the use stage of a building. Particulate matter in different sizes is the most frequently examined air pollutant within the SLR. Moreover, about a third of the articles refer to indoor air pollution, which shows the relevance of the topic. The construction industry can help to develop a healthier built environment and support the achievement of cleaner air within various life cycle stages, e.g., with optimized construction processes and healthier materials. International agreements and policies such as the Sustainable Development Goals (SDGs) can support the sustainable development of the construction industry.

Hierarchical nanostructures self-assembled from δ-MnO2 ultrathin nanosheets and Mn3O4 octahedrons for efficient room-temperature HCHO oxidation

Self-assembling ultrathin active δ-MnO₂ nanosheets and Mn₃O₄ octahedrons into hierarchical texture enhances room-temperature formaldehyde oxidation at a low-level of Pt.

Comparative analysis of formaldehyde and toluene sorption on indoor floorings and consequence on Indoor Air Quality

Indoor surfaces may be adsorptive sinks with the potential to change Indoor Air Quality. To estimate this effect, the sorption parameters of formaldehyde and toluene were assessed on five floorings by an experimental method using solid-phase microextraction in an airtight emission cell. Adsorption rate constants ranged from 0.003 to 0.075 m·h^-1 , desorption rate constants from 0.019 to 0.51 h^-1 , and the partition coefficient from 0.005 to 3.9 m, and these parameters vary greatly from one volatile organic compound/material couple to another indicating contrasted sorption behaviors. A rubber was identified as a sink of formaldehyde characterized by a very low desorption constant close to 0. For these sorbent floorings identified, the adsorption rates of formaldehyde are from 2 to 4 times higher than those of toluene. Two models were used to evaluate the sink effects of floorings on indoor pollutant concentrations in one room from different realistic conditions. The scenarios tested came to the conclusion that the formaldehyde sorption on one rubber (identified as a sink) has a maximum contribution from 15% to 21% for the conditions of low air exchange rate. For other floorings, the sorption has a minor contribution less than or equal to 5%, regardless of the air exchange rate.

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 (PM_2.5 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.

Indoor and outdoor concentrations of BTEX and formaldehyde in Tehran, Iran: effects of building characteristics and health risk assessment

BTEX (benzene, toluene, ethylbenzene, xylene) and formaldehyde are toxic compounds that can induce adverse health effect in humans. This study measured in-home and ambient concentrations of BTEX and formaldehyde across Tehran, Iran. These pollutants were sampled from the indoor and adjacent outdoor air of 45 houses (9 in each city zone) during the winter of 2015. Sampling was repeated three times for each house. The analyses were performed according to NIOSH procedures. The effect of flooring material, wall covering, ventilation system, heating system, height above ground, presence of attached garages, and distance from highways was evaluated. In addition, carcinogenic and non-carcinogenic risks of these compounds were assessed. The average indoor concentrations of benzene, toluene, ethylbenzene, xylene, and formaldehyde were 53.2, 21.5, 14.4, 21.1, and 17.9 μg/m³, respectively. The average outdoor concentrations of benzene, toluene, ethylbenzene, xylene, and formaldehyde were 43.5, 26.2, 10.0, 19.1, and 6.9 μg/m³, respectively. Separate regression models showed that wall coating, ventilation system, heating system, flat level, and distance from highways explained 29, 60, 16, 60, and 59% of the BTEX concentrations, respectively. Houses with oil painted walls and parquet flooring had higher concentrations of BTEX and formaldehyde, respectively. The health risk assessment found that the carcinogenic risks of benzene and formaldehyde exceeded 1 × 10^-4 and represent a definite risk. New buildings can be designed based on the results of this study to use better materials and optimum building designs to reduce exposure to these toxic air pollutants.

The Use of Sensory Analysis Techniques to Assess the Quality of Indoor Air

The quality of indoor air is one of the significant elements that influences people's well-being and health inside buildings. Emissions of pollutants, which may cause odor nuisance, are the main reason for people's complaints regarding the quality of indoor air. As a result, it is necessary to perform tests aimed at identifying the sources of odors inside buildings. The article contains basic information on the characteristics of the sources of indoor air pollution and the influence of the odor detection threshold on people's health and comfort. An attempt was also made to classify and use sensory analysis techniques to perform tests of the quality of indoor air, which would enable identification of sensory experience and would allow for indication of the degree of their intensity.

High-surface area mesoporous Pt/TiO₂ hollow chains for efficient formaldehyde decomposition at ambient temperature

Room-temperature catalytic decomposition of formaldehyde (HCHO) is considered as one of the most main methods for the removal of indoor HCHO due to its facile reaction conditions. Herein, high-surface area mesoporous Pt/TiO2 hollow chains were synthesized in high yield by using a simple microwave-hydrothermal route, followed by a combined NaOH-assisted NaBH4-reduction deposition of Pt nanoparticles on the as-obtained TiO2 surface. The catalytic activity for HCHO decomposition was evaluated at room temperature. The prepared Pt/TiO2 hollow chains with an optimal Pt loading of 0.5 wt.% exhibited high catalytic activity and recyclability. The apparent reaction rate constant of HCHO oxidation over this catalyst was approximately 1.42×10(-3) ppm(-1) min(-1), exceeding that of the commercial Degussa P25 TiO2 with equal Pt content (k=5.36×10(-4) ppm(-1) min(-1)) by a factor of approximately 2.65. The high catalytic activity of the Pt/TiO2 hollow chains could be mainly attributed to the hollow chain-like structure, high specific surface area, numerous mesopores, and high pore volume of TiO2 support. Consequently, the catalysts exhibited high adsorption capacity for HCHO, fast diffusion and transport of gas molecules, and good contact between gases and active sites. These characteristics enhanced the catalytic activity.

The microcapsule-type formaldehyde scavenger: the preparation and the application in urea-formaldehyde adhesives

The limitation and regulation of formaldehyde emissions (FE) now shows great importance in wood-based materials such as plywood and particle board manufactured for building and furnishing materials. The widely used formaldehyde-based adhesives are one of the main sources of FE from the wood products. In this work, a new kind of long-term effective formaldehyde scavenger in the microcapsule form was prepared by using an intra-liquid desiccation method. The characterizations of the capsule (UC) were performed including the morphologies, the yields, the loading efficiency as well as its sustained-release of urea in aqueous conditions. The prepared UC could be integrated in urea-formaldehyde resins by simply physical blending, and the mixtures were available to be applied as the adhesives for the manufacture of plywood. The bonding strength (BS) and the FE of the bonded plywood in both short (3h) and long (12 week) period were evaluated in detail. It was found that the FE profile of the plywood behaved following a duple exponential law within 12 week. The addition of UC in the adhesive can effectively depress the FE of the plywood not only in a short period after preparation but also in a long-term period during its practical application. The slow released urea would continuously suppress the emission of toxic formaldehyde in a sustained manner without obviously deteriorating on the BS of the adhesives.