In this study, a grey box (GB) model for simulating internal air temperatures in a naturally ventilated nearly zero energy building (nZEB) was developed and calibrated, using multiple data configurations for model parameter selection and an automatic calibration algorithm. The GB model was compared to a white box (WB) model for the same application using identical calibration and validation datasets. Calibrating the GB model using only one week of data produced very accurate results for the calibration periods but led to inconsistent and typically inaccurate results for the validation periods (root mean squared error (RMSE) in validation periods was 229% larger than the RMSE in calibration periods). Using three weeks of data from varying seasons for calibration reduced the model accuracy in the calibration period but substantially increased the model accuracy and generalisation abilities for the validation period, reducing the mean RMSE by over 160%. The use of one week of data increased the standard deviation in parameter selections by over 40% when compared with the three-week calibration datasets. Utilising data from multiple seasons for calibration purposes was found to substantially improve generalisation abilities. When compared to the WB model, the GB model produced slightly less accurate results (mean RMSE of the GB model was 1.5% higher). However, the authors found that employing GB modelling with an automatic model calibration technique reduced the human labour input for simulating internal air temperature of a naturally ventilated nZEB by approximately 90%, relative to WB modelling using a manually calibrated approach.

The aim of the article is to analyze the perceived thermal comfort and indoor air quality of occupants and establish associations between these responses and the building-related, occupant-related characteristics, and environmental parameters of residential buildings (a total of 38 variables). The analysis is focused on the Swedish building stock as investigated during the latest national survey in 2008. The analysis covers 1035 residential buildings (multifamily and single-family dwellings). Analytical statistical analysis has been conducted, and logistic regression models have also been developed for the identification of statistically significant covariates. The analysis showed that users in this study demonstrated a significantly positive response to perceived thermal comfort and indoor air quality conditions. Perceived ratings were also highly correlated with each other. As the regression models indicated, the majority of the significant variables were related to the buildings. Nevertheless, this study also underscores the significance of contextual occupant attributes and behaviors as a crucial element influencing the subjective perception of indoor environments. Policymakers, guided by these insights, are encouraged to integrate considerations of occupant attributes into design and urban planning.

The global COVID-19 pandemic has resulted in significant and accelerated developments in ventilation practises, where the need to ventilate buildings has been put centre stage. Longer-term ventilation approaches are now more likely to utilise hybrid ventilation strategies to address the challenge of ensuring resilient indoor thermal environments that are carbon neutral while also minimising the risk of long-range airborne infectious spread of viral pathogens. In the short term, there are many existing buildings which may not undergo retrofit for some time, and consequently, risk mitigation strategies have been implemented in these buildings by utilising existing systems. This paper will present an indoor environmental quality evaluation of ten university lecture rooms both before, during and after changes in ventilation management behaviour and systems that were accelerated due to the COVID-19 pandemic. The results indicate a mean reduction in internal carbon dioxide levels of between 46% and 67% when pre-COVID-19 and COVID-19 datasets are compared and between 11% and 62% when pre-COVID-19 and post-COVID-19 datasets are compared. Changes in behaviour and systems have reduced the time spent above thresholds conducive to virus growth by between 8% and 54%, depending on the lecture room. Despite this, a “rebound” can be observed in many rooms, with CO₂ levels appearing to be trending toward pre-pandemic levels. This work indicates the effect of behavioural and system changes on ventilation and the potential risk for virus spread. The results indicate a need to retrofit existing lecture rooms with more advanced natural or mechanical systems to ensure consistent indoor environmental quality.

In the face of increasing global temperatures, this study aims to explore ventilation strategies that could provide passive cooling to mitigate overheating in studied low-energy school buildings, in particular those that use ventilative cooling. This study utilises building modelling calibrated with field data to tackle the challenge of maintaining indoor thermal comfort and cognitive performance levels during increasingly warm seasons. The calibrated building model is used to evaluate the vulnerability of classrooms, identifying and addressing risks based on standardised overheating and resilience criteria. Two primary school classrooms were simulated in three main cities across Ireland to assess the possibility of natural ventilative cooling for maintaining indoor thermal conditions without sacrificing energy efficiency. The study highlights the critical need to enhance natural ventilation strategies to protect against projected future overheating, with peak indoor temperatures reaching 29 °C to 31 °C during May, June, and September. Implementing a maximum natural ventilation strategy during occupied times, with a 9.6% opening-to-floor area ratio, can reduce peak indoor temperatures by up to 2.5 °C. Findings show Irish classrooms in low-energy buildings equipped with hybrid ventilative cooling can act as potential climate shelters during July and August under extreme weather conditions, underlining their capacity to provide a comfortable environment for vulnerable people during heatwaves and reduce overheating risk by 42–48% compared to natural ventilation. Additionally, projections show that cognitive performance loss in students may rise to 23% by 2071 due to raised indoor temperatures; however, this can be reduced to below 10% in 2021 and 2041 with maximum natural ventilation. The novelty of this work lies in its systematic evaluation of ventilative cooling resilience under future climate scenarios across multiple Irish city contexts, providing a robust evidence base for designing climate-resilient, energy-efficient learning environments.