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Traditional buildings constitute a large proportion of the building stock in many countries worldwide; around 40% of the UK's housing stock was built before 1940 and was primarily made with solid masonry walls. Only 11% of UK solid-walled dwellings had insulation installed, suggesting the high potential of the low-carbon retrofit of traditional buildings. However, there is evidence of the occurrence of unintended consequences, often associated with excess moisture. A method is presented for moisture risk management that includes the development of a process and a framework. These tools are then integrated into a novel framework for the combined energy and moisture performance retrofit of traditional buildings. An example of the framework's practical application is provided, with a focus on retrofit measures for solid-wall insulation. The proposed systematic approach demonstrates the interconnected nature of energy and moisture. It harmonises the principles needed to support organisations in the delivery of robust retrofit of traditional buildings through the integration of pre-retrofit building assessment and post-retrofit monitoring in the process. The risk-management process and framework presented can be valuable tools to support designers in providing robust and scalable retrofit measures and strategies. [ABSTRACT FROM AUTHOR]

The assumedU-values of solid walls represent a significant source of uncertainty when estimating the energy performance of dwellings. The typicalU-value for UK solid walls used for stock-level energy demand estimates and energy certification is 2.1 Wm−2 K−1. A re-analysis (based on 40 brick solid walls and 18 stone walls) using a lumped thermal mass and inverse parameter estimation technique gives a mean value of 1.3 ± 0.4 Wm−2 K−1for both solid wall types. Among the many implications for policy, this suggests that standard UK solid-wallU-values may be inappropriate for energy certification or for evaluating the investment economics of solid-wall insulation. For stock-level energy modelling, changing the assumedU-value for solid walls reduces the estimated mean annual space heating demand by 16%, and causes a proportion of the stock to change Energy Performance Certification (EPC) band. The analysis shows that the diversity of energy use in domestic buildings may be as much influenced by heterogeneity in the physical characteristics of individual building components as it is by variation in occupant behaviour. Policy assessment and guidance material needs to acknowledge and account for this variation in physical building characteristics through regular grounding in empirical field data. [ABSTRACT FROM PUBLISHER]

Abstract: The aim of this research is to investigate the thermophysical behaviour of building envelope multi-layer components and assess the whole building–plant response. The investigation was carried out in two different phases. The first phase concerned the study of the dynamic response of building envelope multi-layer components, by providing an improved implementation of the present European Standard UNI EN ISO 13786:2008. The proposed method allows one to determine the transient thermophysical performance of opaque building components that are associated with a thermal zone maintained at constant or variable air temperature. The variable internal air temperature can be associated with experimental data. The second phase consisted of a transient analysis of the above thermal zone with a conditioning plant working. The building plant simulations were carried out by EnergyPlus software. The method proposed, based on European standards, is particularly useful in the perspective of the Certification of the Energy Performance of the building–plant system, required by the European Union. It can provide a useful tool for developing an abacus of different envelope multi-layer component performances in order to support design choices. [Copyright &y& Elsevier]

Historic, listed, or unlisted, buildings account for 30% of the European building stock. Since they are complex systems of cultural, architectural, and identity value, they need particular attention to ensure that they are preserved, used, and managed over time in a sustainable way. This implies a demand for retrofit solutions able to improve indoor thermal conditions while reducing the use of energy sources and preserving the heritage significance. Often, however, the choice and implementation of retrofit solutions in historic buildings is limited by socio-technical barriers (regulations, lack of knowledge on the hygrothermal behaviour of built heritage, economic viability, etc.). This paper presents the approach devised in the IEA-SHC Task 59 project (Renovating Historic Buildings Towards Zero Energy) to support decision makers in selecting retrofit solutions, in accordance with the provision of the EN 16883:2017 standard. In particular, the method followed by the project partners to gather and assess compatible solutions for historic buildings retrofitting is presented. It focuses on best practices for walls, windows, HVAC systems, and solar technologies. This work demonstrates that well-balanced retrofit solutions can exist and can be evaluated case-by-case through detailed assessment criteria. As a main result, the paper encourages decision makers to opt for tailored energy retrofit to solve the conflict between conservation and energy performance requirements. [ABSTRACT FROM AUTHOR]

Buildings of heritage significance due to their historical, architectural, or cultural value, here called historic buildings, constitute a large proportion of the building stock in many countries around the world. Improving the performance of such buildings is necessary to lower the carbon emissions of the stock, which generates around 40% of the overall emissions worldwide. In historic buildings, it is estimated that heat loss through external walls contributes significantly to the overall energy consumption, and is associated with poor thermal comfort and indoor air quality. Measures to improve the performance of walls of historic buildings require a balance between energy performance, indoor environmental quality, heritage significance, and technical compatibility. Appropriate wall measures are available, but the correct selection and implementation require an integrated process throughout assessment (planning), design, construction, and use. Despite the available knowledge, decision-makers often have limited access to robust information on tested retrofit measures, hindering the implementation of deep renovation. This paper provides an evidence-based approach on the steps required during assessment, design, and construction, and after retrofitting through a literature review. Moreover, it provides a review of possible measures for wall retrofit within the deep renovation of historic buildings, including their advantages and disadvantages and the required considerations based on context. [ABSTRACT FROM AUTHOR]

• HTC estimated using grey-box, dynamic models is consistent with coheating test. • The thermal performance of occupied dwellings was reliably characterised year round. • The best models, selected by model comparison, are building and weather specific. • Addressing solar radiation, both direct and diffuse, is essential for such models. • Models and solar apertures provide insight into house characteristics and shading. The accurate determination of the in-use heat transfer coefficient (HTC) of a dwelling can support efficiency improvements and understanding of energy costs, potentially addressing the performance gap. This paper introduces a dynamic grey-box framework combining Bayesian methods and lumped thermal capacitance models for the estimation of the performance of in-use buildings. It focuses on methods to account for solar gains, a significant contributor to the heat transfer. Six simple first-order lumped models of occupied homes are presented, which explicitly include gains from solar radiation with varying complexity. Specifically, the models use solar radiation as a single heat input, divided by façade according to the angle of the sun, and including diffuse radiation. Two case study houses in the UK, monitored over two different seasons, were used to illustrate the models' performance. Bayesian model comparison was used, in conjunction with other methods, to determine the most suitable model for each sub-dataset analysed; this indicates that the most appropriate model is both season and case-study dependent, highlighting the importance of local topography and weather experienced. For each case study, the models selected provided HTC estimates within 15% of each other, including during the summer, using only 5–10 days of data. Such techniques have the potential to estimate the thermal performance of dwellings year-round, with minimum disturbance to the occupants and could be developed to improve quality assurance processes for new build and retrofit, identify opportunities for targeted retrofit, and close the performance gap. [ABSTRACT FROM AUTHOR]

A correction to the article "Bayesian Dynamic Method to Estimate the Thermophysical Properties of Building Elements in All Seasons, Orientations and with Reduced Error" that was published in a previous issue is presented.

The performance gap between the expected and actual energy performance of buildings and elements has stimulated interest in in-situ measurements. Most research has employed quasi-static analysis methods that estimate heat loss metrics such as U-values, without taking advantage of the rich time series data that is often recorded. This paper presents a dynamic Bayesian-based method to estimate the thermophysical properties of building elements from in-situ measurements. The analysis includes Markov chain Monte Carlo (MCMC) estimation, priors, uncertainty analysis, and model comparison to select the most appropriate model. Data from two case study dwellings is used to illustrate model performance; U-value estimates from the dynamic and static methods are within error estimates, with the dynamic model generally requiring much shorter time series than the static model. The dynamic model produced robust results at all times of year, including when the average indoor-to-outdoor temperature difference was low, when external temperatures had large daily variation, and measurements were subjected to direct solar radiation. Further, the probability distributions of parameters may provide insights into the thermal performance of elements. Dynamic methods such as that presented herein may enable wider characterisation of the performance of building elements as built, supporting work to reduce the performance gap. [ABSTRACT FROM AUTHOR]