Uncertainty-based optimal energy retrofit methodology for building heat electrification with enhanced energy flexibility and climate adaptability

To reach net zero emissions by 2050, the UK government relies heavily on heat degasification in buildings by using heat pump technology. However, existing buildings may have terminal radiators that require a higher operating temperature than what heat pumps typically provide. Increasing the size of radiators and thermally insulating building envelopes could be a potential solution, but the feasibility of these practices is uncertain due to space constraints and high retrofit costs. This study investigates the feasibility and potential benefits of incorporating air-source heat pumps into existing gas boiler heating systems to meet heating demands. The proposed probabilistic optimal air-source heat pump design method enhances energy flexibility and climate adaptability, taking into account a wide range of uncertainty sources and multiple flexibility services (e.g., energy and ancillary services). Heating systems of three educational buildings at the University of Cambridge are used as a testbed to assess and validate the effectiveness of the proposed method, under future climate scenarios and projected decreases in heating demand due to climate change. Results indicate that the best retrofit alternative of the hybrid heating system reduces carbon emissions by 88%, total costs by 54% over its lifespan, and has an average payback period of around 3 years. Air-source heat pumps can meet the majority of the heating demand (around 80%) with gas boilers used for “top-up” heating during high demand. Furthermore, air-source heat pumps' design capacity can fulfil future cooling demand even if retrofit optimization is initially focused on meeting heating needs

Retrofit solutions for solid wall dwellings in England: the impact of uncertainty upon the energy performance gap

This study seeks to evaluate the impact of uncertainty in the pre-retrofit thermal performance of solid walls of English dwellings on post-retrofit energy use. Five dwelling archetypes, broadly representative of English solid wall properties, were modelled pre- and post-retrofit, under different wall insulation scenarios, using dynamic thermal simulation. Findings indicate that whilst solid wall insulation could result in a significant reduction of space heating demand, uncertainties in the pre-retrofit solid wall U-value could lead to a gap between the anticipated and actual energy performance. Specifically, results show that if the current U-value assumption of 2.1 W/m2K is indeed an overestimation of the in-situ U-value of solid walls, then the anticipated carbon savings could be significantly reduced by up to 65%. Practical application: The performance gap observed in this study revealed that the actual carbon savings arising from the retrofit of solid wall properties could be significantly lower than predicted. This will not only affect UK Government carbon reduction targets but it can also result in a lack of confidence amongst stakeholders who may consequently doubt the effectiveness of energy retrofit measures, thus reducing their uptake. Uncertainties regarding solid wall U-values may necessitate the re-examination of the carbon targets set for the retrofit of solid wall dwellings and the exploration of alternative ways to further reduce their carbon emissions, e.g. by specifying higher insulation thicknesses

Phylogenetic analysis of strains of Orf virus isolated from two outbreaks of the disease in sheep in Greece

<p>Abstract</p> <p>Background</p> <p>Although orf is endemic around the world, there are few descriptions of <it>Orf virus </it>strains and comparisons of these strains. We report the sequence and phylogenetic analysis of the partial B2L gene of <it>Orf virus </it>from two outbreaks of the disease in Greece. The first was an outbreak of genital form of the disease in a flock imported from France, whilst the second was an outbreak of the disease in the udder skin of ewes and around the mouth of lambs in an indigenous flock.</p> <p>Results</p> <p>Phylogenetic analysis was performed on a part (498 bp) of the B2L gene of 35 <it>Parapoxvirus </it>isolates, including the two <it>Orf virus </it>isolates recovered from each of the two outbreaks in the present study. This analysis revealed that the maximum nucleotide and amino-acid variation amongst <it>Orf virus </it>strains worldwide (n = 33) was 8.1% and 9.6%, respectively. The homology of the nucleotide and amino-acid sequences between the two Greek isolates was 99.0% and 98.8%, respectively. The two Greek isolates clustered only with <it>Orf virus </it>strains.</p> <p>Conclusions</p> <p>We suggest that there can be differences between strains based on their geographical origin. However, differences in the origin of strains or in the clinical presentation of the disease may not be associated with their pathogenicity. More work is required to determine if differing clinical presentations are linked to viral strain differences or if other factors, e.g., flock immunity, method of exposure or genetic susceptibility, are more important to determine the clinical presentation of the infection.</p

Housing as a modifier of air contaminant and temperature exposure in Great Britain: A modelling framework

This paper presents the development of a modelling framework that quantifies the modifying effect of dwelling characteristics on exposure to indoor air pollution and excess temperature. A georeferenced domestic building stock model of Great Britain was created using national housing surveys, historical weather, and local terrain data. Dynamic building performance simulation was applied to estimate indoor air pollution and overheating risk metrics at the individual building level. These metrics were then aggregated at various geographic units and mapped across Britain within a Geographic Information System (GIS) environment to compare spatial trends. Results indicate that flats and newly built properties are characterised by lower indoor air pollution from outdoor sources, but higher air pollution from indoor sources. Flats, bungalows and newly built, more airtight dwellings are found to be more prone to overheating. Consequently, urban populations may experience higher levels of pollution from indoor sources and overheating resulting from the higher prevalence of flats in cities

Modelling Long-Term Urban Temperatures with Less Training Data: A Comparative Study Using Neural Networks in the City of Madrid

In the last decades, urban climate researchers have highlighted the need for a reliable provision of meteorological data in the local urban context. Several efforts have been made in this direction using Artificial Neural Networks (ANN), demonstrating that they are an accurate alternative to numerical approaches when modelling large time series. However, existing approaches are varied, and it is unclear how much data are needed to train them. This study explores whether the need for training data can be reduced without overly compromising model accuracy, and if model reliability can be increased by selecting the UHI intensity as the main model output instead of air temperature. These two approaches were compared using a common ANN configuration and under different data availability scenarios. Results show that reducing the training dataset from 12 to 9 or even 6 months would still produce reliable results, particularly if the UHI intensity is used. The latter proved to be more effective than the temperature approach under most training scenarios, with an average RMSE improvement of 16.4% when using only 3 months of data. These findings have important implications for urban climate research as they can potentially reduce the duration and cost of field measurement campaigns