Buildings are one of the largest contributors to energy consumption and greenhouse gas emissions (GHG) in the world. There is an increased interest in building performance evaluation as an essential practice to design a sustainable building. Building performance is influenced by various terms, for example, designs, construction-related factors such as building envelope and airtightness, and energy technologies with or without micro-generations. How well a building performs thermally is key to determining the level of energy demand and GHG emissions. Building standards and regulations, in combination with assessments (e.g., energy modeling tools) and certifications, provide sets of supports, guidelines and instructions for designers and building engineers to ensure users’ health and well-being, consistency in construction practices and environmental protection. This paper reviews, evaluates and suggests a sequence of building performance methods from the UK perspective. It shows the relationships between such methods, their evolutions and related tools, and further highlights the importance of post-occupancy analysis and how crucial such assessments could be for efficient buildings.

The impacts and benefits of thermal insulations on saving operational energy have been widely investigated and well-documented. Recently, many studies have shifted their focus to comparing the environmental impacts and CO₂ emission-related policies of these materials, which are mostly the Embodied Energy (EE) and Global Warming Potential (GWP). In this paper, machine learning techniques were used to analyse the untapped aspect of these environmental impacts. A collection of over 120 datasets from reliable open-source databases including Okobaudat and Ecoinvent, as well as from the scientific literature containing data from the Environmental Product Declarations (EPD), was compiled and analysed. Comparisons of Multiple Linear Regression (MLR), Support Vector Regression (SVR), Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Extreme Gradient Boosting (XGBoost) regression methods were completed for the prediction task. The experimental results revealed that MLR, SVR, and LASSO methods outperformed the XGBoost method according to both the K-Fold and Monte-Carlo cross-validation techniques. MLR, SVR, and LASSO achieved 0.85/0.73, 0.82/0.72, and 0.85/0.71 scores according to the R² measure for the Monte-Carlo/K-Fold cross-validations, respectively, and the XGBoost overfitted the training set, showing it to be less reliable for this task. Overall, the results of this task will contribute to the selection of effective yet low-energy-intensive thermal insulation, thus mitigating environmental impacts.

Climate change and its consequences are of a great concern and the likely increasing temperature would add more dilemmas for the choice of passive design options. The performance of building envelopes is one of the key determinants of energy use and thermal comfort. This research presents an evaluation of commonly used construction systems (lightweight and heavyweight) with different levels of thermal mass. The performance of different construction combinations is quantified on the basis of their impact on thermal comfort and energy consumption for current and future time slices in London, UK where climate change impact is expected to be extreme. A flat model is examined as a case study to model the performance of the construction systems with low, medium and high level of thermal mass. The dynamic thermal simulation software used was DesignBuilder, which employs EnergyPlus as its calculation engine. In essence, this study establishes a new approach for assessing the performance of well-insulated contemporary construction systems on the basis of overall annual thermal comfort hours and energy consumption. Results indicate limited advantage of heavyweight construction systems in a changing climate.

Recent intergovernmental panel on climate change reports have once again emphasised the effective measures to reduce greenhouse gas emissions and the importance of the built environment. Historically, passive and active solutions are known for their potential to make the built environment more environmentally friendly. Recently, a significant number of studies covered the effectiveness of such solutions under distinct current and different future climate and emission predictions. Through the PRISMA framework, this paper presents a comprehensive state-of-the-art review of such studies within the last 10 years (2013–2023) to understand their impact, their tangible applications, and their empirical evidence. Local ecosystems, weather patterns, geographical and cultural challenges dictate the solutions for a warmer future. Among the solutions, as expected, passive solutions remain most effective even though a combination with active ones is necessary regardless of the context. The review in this paper is expandable beyond the effective reported solutions and it highlights the most effective solutions under different climate zones.

The likely increasing temperature predicted by UK Climate Impacts Program (UKCIP) underlines the risk of overheating and potential increase in cooling loads in most of UK dwellings. This could also increase the possibility of failure in building performance evaluation methods and add even more uncertainty to the decision-making process in a low-carbon building design process. This paper uses a 55-unit residential unit project in Cardiff, UK as a case study to evaluate the potential of thermal simulations to identify risk in the early design stage. Overheating, increase in energy loads, carbon emissions, and thermal bridges are considered as potential risks in this study. DesignBuilder (DesignBuilder Software Ltd., Stroud, UK) was the dynamic thermal simulation software used in this research. Simulations compare results in the present, 2050, and 2080 time slices and quantifies the overall cooling and heating loads required to keep the operative temperature within the comfort zone. Overall carbon emissions are also calculated and a considerable reduction in the future is predicted. Further analysis was taken by THERM (Lawrence Berkeley National Laboratory, Berkeley, CA, USA) and Psi THERM (Passivate, London, UK) to evaluate the thermal bridge risk in most common junctions of the case study and the results reveal the potential of thermal assessment methods to improve design details before the start of construction stage.

A holistic understanding of the correlations between supply and demand in buildings forms the basis for their performance assessment. This paper aims to reinterpret a set of Key Performance Indicators (KPIs) that influence users’ satisfaction from different perspectives. Fieldwork was carried out in an office building following a detailed review on KPIs by conducting user surveys. This study highlights the need to organize specific indicators to focus on the usability of workplaces and, where and when required, through an iterative process, understand the user perception of performance indicators in usage conditions. This methodology is applicable for organizations to understand the main existing in-service problems, and could improve the building’s performance over time. Survey results showed that hygiene was the most recognizable influence on users’ satisfaction and indoor air quality was the less well-known in the assessment results. User perception results can be compared to other office buildings results to benchmark good practices and should also be investigated for the post-COVID-19 period.