This article provides the first comprehensive assessment of methods for the creation of weather variables for use in building simulation. We undertake a critical analysis of the fundamental issues and limitations of each methodology and discusses new challenges, such as how to deal with uncertainty, the urban heat island, climate change and extreme events. Proposals for the next generation of weather files for building simulation are made based on this analysis. A seven-point list of requirements for weather files is introduced and the state-of-the-art compared to this via a mapping exercise. It is found that there are various issues with all current and suggested approaches, but the two areas most requiring attention are the production of weather files for the urban landscape and files specifically designed to test buildings against the criteria of morbidity, mortality and building services system failure. Practical applications: Robust weather files are key to the design of sustainable, healthy and comfortable buildings. This article provides the first comprehensive assessment of their technical requirements to ensure buildings perform well in both current and future climates.

Buildings generate nearly 30% of global carbon emissions, primarily due to the need to heat or cool them to meet acceptable indoor temperatures. In the last 20 years, the empirically derived adaptive model of thermal comfort has emerged as a powerful alternative to fixed set point driven design. However, current adaptive standards offer a simple linear relationship between the outdoor temperature and the indoor comfort temperature, assumed to sufficiently explain the effect of all other variables, e.g. relative humidity (RH) and air velocity. The lack of a signal for RH, is particularly surprising given its well-known impact on comfort. Attempts in the literature to either explain the lack of such a signal or demonstrate its existence, remain scattered, unsubstantiated and localised. In this paper we demonstrate, for the first time, that a humidity signal exists in adaptive thermal comfort using global data to form two separate lines of evidence: a meta-analysis of summary data from 63 field studies and detailed field data from 39 naturally ventilated buildings over 8 climate types. We implicate method selection in previous work as the likely cause of failure to detect this signal, by demonstrating that our chosen method has a 56% lower error rate. We derive a new designer-friendly RH-inclusive adaptive model that significantly extends the range of Highlights • The influence of relative humidity on adaptive thermal comfort explained. • A new adaptive thermal comfort model which considers the effect of relative humidity introduced. • The current model is shown to overestimate overheating by 30% over 13 global locations.

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Globally, a primary concern is whether green office buildings perform as promised in terms of providing better indoor environment quality (IEQ) for employees, which may affect their satisfaction and work performance. In the Middle East, although there has been renewed interest in green building design, post occupancy evaluation of performance has never been conducted to-date, and evidence of actual occupant perception in green and non-green buildings is still ambiguous. Hence, we present the first study on IEQ performance in the Middle East. We show that Jordan can be taken as a representative example and systematically compare five "green" office buildings (representing 71% of all green-certified office buildings) against eight comparable conventional office buildings (CBs). Detailed bi-lingual survey data on perceived IEQ (n = 502) and work performance are accompanied by high-resolution continuous physical measurements of air temperature + relative humidity (n = 83) and CO2 concentrations (n = 21) with periodic measurements of mean radiant temperature and air speed, covering two typical summers and one typical winter. Results show both buildings types comply with design standards for indoor CO2 levels, while thermal comfort in green buildings is better than in CBs. However, CBs have a higher overall occupant satisfaction of IEQ. Work performance measured as absolute and relative absenteeism was slightly higher in CBs, with no significant differences in relative and absolute presenteeism between the two buildings types. These findings challenge the notion that green buildings improve occupant satisfaction and work performance over CBs and suggest the need for a better understanding of the performance-satisfaction gap.

There are more than six million refugees living in camps globally, primarily in places with severe climates. While camps are planned to be temporary, they can be in use for decades. This "planned temporariness", despite their potential longevity, together with the pressures of rapidly emerging situations, means the construction and monitoring of demonstrators is not a primary concern for their developers. This lack of iterative design improvement results in shelters with thermal environments far from ideal and a risk of increased morbidity. Here we propose a cyclical process for improving such shelters involving the thermal monitoring of pre-existing shelters to construct validated baseline simulation models of similar shelters in other areas of emerging crisis. These models can then be evolved and improved within an optimisation cycle before massconstruction and field testing. Here we demonstrate the method for the case of Azraq camp in Jordan. Starting from an analysis of field survey data which exposes a high incidence of heat-stress experienced in the shelters, a series of architectural strategies are applied to the design, resulting in significant reductions in overheating. This work suggests that the proposed cyclical approach can lead to significant improvement in conditions currently experienced in refugee camp shelters.

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Adaptive thermal comfort theory has become the bedrock of much thinking about how to judge if a free-running environment is suitable for human occupation. In design work, the conditions predicted by a thermal model, when the model is presented with one possible annual weather time series (a reference year), are compared to the limits of human comfort. If the temperatures are within the comfort limits, the building is judged to be suitable. However, the weather in many locations can vary year-on-year by a considerable margin, and this begs the question, how robust are the predictions of adaptive comfort theory likely to be over the many years a building might be in use? We answer this question using weather data recorded for up to 30 years for locations within each of the five major Köppen climate classifications.We find that the variation in the annual time series is so great that the predicted comfort temperature frequently lies outside the acceptable range given by the reference year. Return periods for the excursions of the time series are calculated for each location. The results for one location are then validated using the world's longest temperature record. These results suggest that industry and academia would be best advised to move to a probabilistic methodology, like the proposed one, when using adaptive comfort theory to judge the likely conditions within a building. Extra pertinence is provided by concerns over increases in mortality and morbidity in buildings due to a rapidly warming climate. • A new probabilistic adaptive comfort theory introduced.• New comfort equations for resilient building design presented.