Thermal discomfort is one of the main triggers for occupants’ interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses.

The study was conducted to investigate thermal adaptation and the impact of individual differences on developing thermal tolerance when the outdoor temperature falls below 10°C. The applicability of the predicted mean vote (PMV) model was investigated, too. The concept of occupant’s ‘Temperament’ was evaluated as a psychological-adaptation factor. Two main hypotheses were: (a) people with different temperaments would experience different thermal sensations and (b) the classic PMV- predicted percentage dissatisfied (PPD) model is capable of predicting the neutral sensation in heated buildings under cold outdoor temperatures. There was a direct relationship between individual temperament and clothing level as well as thermal sensation. The occupants who were assessed to have cold temperament tend to wear thicker clothes and were more sensitive to variations in indoor air temperature than others. Females with a cold temperament were more than twice as likely to be affected by indoor air temperature as those with a warm temperament. The PMV-PPD model was able to predict the mean neutral temperature in the heated buildings even when the outdoor temperature fell below 10°C. However, when occupants were able to control high indoor temperature, the percentage of true prediction of actual mean votes by the adaptive thermal heat balance model was more than that by the classic PMV model.

Introduction: Wood panels, commonly used in cold climates like the Nordic countries for their aesthetic surface and availability, emit volatile organic compounds (VOCs) that can impact indoor air quality and may contribute to health risks, especially with repeated or prolonged exposure. While research has primarily focused on untreated fresh wood, little attention has been given to the VOC emissions from commercial wood panels. This study aims to investigate the VOC emission pattern, intensity, and profile of nine commercially untreated and treated wood panels commonly used in indoor environments, focusing on how wood type and surface treatments influence emission characteristics.Methods: The study utilizes Proton Transfer Reaction Time-of-Flight Mass Spectrometry combined with passive sampling, offering a more comprehensive analysis of volatile organic compounds, including both volatile and very volatile compounds, which traditional gas chromatography cannot capture. Advanced statistical methods, such as Bayesian posterior, principal component analysis, and hierarchical clustering analysis, were employed to identify key emission contributors and classify emission patterns.Results: The findings reveal that emission intensity and profiles are influenced by wood type and surface treatments. Pine and oak emitted higher proportions of VOCs, while spruce primarily emitted VVOCs. Glazing, staining, and painting significantly affect emission intensity, with glazing reducing pine total emissions by 81% and increasing them in spruce by 65%. Staining pine reduced VOC emissions by 74% but increased VVOC emissions by 63%, shifting the emission profile. Despite high emission intensity from untreated pine, painting reduced TVOC emissions by 93%, aligning its profile with lower-emission woods like aspen and spruce, making it more suitable for indoor use.Discussion: The right treatment can transform high-emission woods into materials resembling low-emission species, offering a practical means to mitigate indoor VOC loads.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Selecting interior wood materials requires balancing functional and aesthetic demands with indoor air quality, as wood can emit volatile organic compounds (VOCs) and very volatile organic compounds (VVOCs) that either peak shortly after installation or persist over time. This study investigated time-resolved VOC and VVOC accumulation concentrations from untreated pine, spruce, aspen, and oak, representing wood species commonly used in Norway. Concentrations of VOCs and VVOCs were monitored for 25–28 days under low-ventilation, worst-case chamber conditions using Proton Transfer Reaction–Time-of-Flight Mass Spectrometry (PTR-TOF-MS). Emission behaviour was assessed using peak concentration, decay rate, half-time, stabilised concentration, cumulative exposure (AUC₂₈), and available health-based thresholds. Clear species-dependent differences were observed. Pine was the dominant VOC source, with the highest peak concentration, stabilised concentration, and AUC₂₈, mainly due to monoterpenes, which remained above the health-based threshold throughout the test period. Oak showed the second-highest VOC burden and a distinct acetate-dominated profile, with acetic acid showing the longest predicted exceedance duration. Aspen and spruce had lower VOC burdens, but their cumulative VVOC exposure exceeded VOC exposure. VVOCs generally peaked earlier than VOCs, although persistence varied by species. Overall, the concentration of VOCs and VVOCs was controlled by species, compound chemistry, volatility, and internal transport, supporting species- and compound-specific ventilation and material-selection strategies.