A Statistical Analysis of the Energy Performance Characteristics for the Residential Building Stock in Jordan

The residential sector is responsible for the consumption of 46% of the building’s total primary energy consumption in Jordan. The Jordanian housing stock will need to be significantly improved to meet the government’s commitment to reduce national emissions by 2050. This research aims to examine the available statistical data on residential buildings, to help better understand the current state of housing stock in Jordan and pave the way to generate a national housing stock model, as well as to identify opportunities in improving the energy efficiency of these buildings. The study synthesised data from the Department of Statistics housing survey and the Jordan Green Building Council survey to investigate the Jordanian national housing stock. The aggregated data was examined using a descriptive statistical analysis method. The data was then merged to provide aggregated datasets with detailed building characteristics. The study successfully characterized residential buildings archetypes and identified a range of typical thermal performance-related building characteristics (e.g., envelope properties, HVAC systems, lighting systems, etc.). The findings of the statistical analysis can be useful for policymakers in Jordan to gain insights into the current state of the housing stock, identify trends and patterns, and make informed decisions and initiatives such as the improvement of regulatory building code requirements for energy efficiency

A Review of the Methodology Developed to Investigate CO₂ Emissions of the Housing Stock in Jordan

The dwellings make up 72% of buildings and consume around 40% of the primary energy in Jordan. Consequently, reducing carbon emissions from existing residential buildings is crucial. However, there are no mandatory and explicit terms in the building codes concerning carbon emissions. This paper aims to present a methodology suggesting refurbishment strategies to assess the feasibility of achieving Net-Zero carbon performance in the Jordanian housing stock. It can constitute a theoretical framework to identify intervention measures

Evaluation of energy performance of the most prevalent housing archetypes in Jordan

The residential sector is responsible for the consumption of 46% of the building’s total primary energy consumption in Jordan. Despite the Jordanian government’s commitment to significantly reduce national emissions by 2050, building Operational Carbon (OC) has been under-researched in the Jordanian context. This study aims to present the development of an archetypes-based housing stock model. The model is then used to evaluate the impact of a series of suggested refurbishment scenarios, to reduce the stock’s operational carbon impact. First, the most prevalent dwellings are identified and categorized into ‘archetypes’ based on the analysis of a housing survey database on Jordanian dwellings. Subsequently, the performance of these archetypes is evaluated in terms of OC. Finally, the improvement scenarios are investigated, and their impact on OC is evaluated

Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes

Tail-biting convolutional codes extend the classical zero-termination convolutional codes: Both encoding schemes force the equality of start and end states, but under the tail-biting each state is a valid termination. This paper proposes a machine-learning approach to improve the state-of-the-art decoding of tail-biting codes, focusing on the widely employed short length regime as in the LTE standard. This standard also includes a CRC code. First, we parameterize the circular Viterbi algorithm, a baseline decoder that exploits the circular nature of the underlying trellis. An ensemble combines multiple such weighted decoders, each decoder specializes in decoding words from a specific region of the channel words' distribution. A region corresponds to a subset of termination states; the ensemble covers the entire states space. A non-learnable gating satisfies two goals: it filters easily decoded words and mitigates the overhead of executing multiple weighted decoders. The CRC criterion is employed to choose only a subset of experts for decoding purpose. Our method achieves FER improvement of up to 0.75dB over the CVA in the waterfall region for multiple code lengths, adding negligible computational complexity compared to the circular Viterbi algorithm in high SNRs

An Integrated Thermal Simulation & Generative Design Decision Support Framework for the Refurbishment or Replacement of Buildings: A Life Cycle Performance Optimisation Approach

The environmental performance of existing buildings can have a major role in achieving the CO2 reduction targets, set out by the UK government. In the UK, new buildings account for around 1% of the total building stock (annually), and predictions show that around 75% of the housing stock that will still remain in 2050 has already been built. Furthermore, while current building performance improvement efforts focus mainly on the operational performance of buildings, the environmental impact of the built environment is the result of processes that occur throughout their whole life-cycle (construction, usage and demolition). To achieve significant CO2 emission reductions in the built environment in an economically viable way, this thesis adopted the Life Cycle Carbon Footprint (LCCF) and Life Cycle Cost (LCC) analysis approaches, to enable a cross-comparison between multiple design alternatives and to identify the preferable design solution: the refurbishment of existing buildings or their replacement by new ones. In particular, this thesis has developed, tested and validated a computational framework that integrates life cycle performance protocols (EN 15978:2011 and BS ISO 15686-5), thermal simulation tools (EnergyPlus), mathematical optimisation (NSGA-II) and a designated building generative design programming (PLOOTO - Parametric Lay-Out Organisation generator) into a single computer application. The investigation was carried out using a comparative analysis of simulated case study buildings: a terrace-house, a bungalow and a block of flats. Results show that under the considered assumptions, the optimal refurbishment case studies achieved lower LCCF and LCC values than the replacements: The LCCF of the refurbishment scenarios was between 1,100-1,500 kgCO2e/m2 and their LCC 440-680 £/m2, compared to those of the replacements scenarios, who achieved between 1,220-1,850 kgCO2e/m2 and 550-890 £/m2. Furthermore, this research has found that optimising the performance of a typical London-based terrace house using a life cycle carbon approach reached 10% more savings in CO2 throughout its life, compared to targeting operational CO2 only. This means that complying with current UK regulations – which is currently only focused on the improvement of operational efficiencies – may result in buildings with poorer performance, in terms of their overall life cycle carbon footprint. This is associated to the difference in the analysis scope: while operational efficiencies only examine emissions due to heating and lighting within the building, the Life Cycle approach accounts for emissions that occur in other stages in the building’s life, e.g., emissions that are embodied within its structure, emissions during construction, maintenance and more. An important conclusion of this research is, therefore, that to reach significant reductions in emissions rates – a life-cycle approach should be adopted. More specifically, to achieve immediate reductions (on a 20-year scale) - refurbishments are generally preferable over replacements. It can, therefore, be concluded that there is a greater importance in incentivising re-use to achieve quicker emissions reductions. The research has shown that the integration of the various research tools in the proposed computational framework was successful in automating the analysis process. The comparative analysis approach was found to be useful in identifying the preferable design solution – the refurbishment of existing buildings or their replacement. Finally, the research sets out an extensive discussion in regard to the proposed computational framework, life cycle performance analysis and the potential benefits of refurbishments or replacements of existing buildings, in the context of the UK

The impact of climate change on cognitive performance of children in English school stock: A simulation study

Children in England spend around 30% of their time in schools to gain knowledge and skills. Climate change could impact schools' thermal environments and children's learning performance by impairing their cognitive ability. This study presents an evaluation approach to investigating and quantifying climate change's impact on the cognitive performance of children across English school stocks. The study also evaluates the potential of possible strategies for mitigating the impacts of climate change. The results show that future climates are projected to increase cognitive performance loss of children in school archetypes representative of school stocks, with variations based on regional climate characteristics. Increasing ventilation rates proves to be an effective means of reducing cognitive performance loss, while its effectiveness diminishes as outdoor temperatures rise in the future. Thus, the introduction of air conditioning becomes a potentially more beneficial strategy, despite the associated increase in cooling energy demand. Moreover, higher ventilation rates in air-conditioned classrooms can further improve children's cognitive performance. The use of cognitive performance loss as a Key Performance Indicator (KPI) allows for better communication and understanding of climate change risks faced by schools among building and non-building experts. The proposed evaluation approach remains adjustable and can be continuously updated and enhanced as new insights from psychological research emerge

London School Building Stock Model for Cognitive Performance Assessment

Climate change is one of the biggest challenges facing humankind in the 21st century. In the building sector, a warming climate will significantly affect building heating and cooling loads, as well as building occupant health, comfort and wellbeing. School buildings in the UK, in particular, might face additional challenges, such as indoor overheating risks due to high internal gains in classrooms, and their current reliance on natural ventilation, which might offer limited cooling capacity in the future. This paper presents a secondary school building stock indoor environment modelling framework for London. The aim of the present study is to explore the impacts of ongoing and future climate change on schoolchildren’s cognitive performance levels. Using the PDSP (Property Data Survey Programme) dataset and a basic set of school building archetypes for London, a parametric stock modelling framework was developed. Weather files based on existing Test Reference Years (TRY) incorporating the UK Climate Projections 2009 scenarios were used. This study provides a detailed assessment of school building stock indoor thermal performance and students’ cognitive performance. It was found that building thermal properties and ventilation rates can function as reliable predictors of students’ cognitive performance, and their impacts were quantified in this study. A sensitivity analysis aiming to identify the relative importance of these factors will be conducted as part of ongoing research

Energy retrofit and passive cooling: overheating and air quality in primary schools

While building stock modelling has been used previously to investigate the space heating demand implications of national energy efficiency retrofitting, there are also implications for indoor overheating and air quality, particularly in schools, with highly intermittent occupancy patterns. This paper assesses indoor overheating risk and air quality within an English classroom stock model containing 111 archetypes, based on the analysis of the nationwide Property Data Survey Programme (PDSP) containing 9629 primary school buildings in England. Metrics for indoor temperatures, heating demand and concentrations of three contaminants (CO_{2}, NO_{2}, PM_{2.5}) were estimated in naturally ventilated classrooms, while exploring future climate projections, retrofit and overheating mitigation scenarios to analyse school stock resilience. Classrooms with a south-east orientation experience around four to six times the overheating-hours compared with those with a northern orientation. Post-1976 archetypes are most susceptible to overheating, indicative of the conflict between better insulated and airtight classrooms and overheating prevention. A range of retrofit and passive cooling measures can mitigate against overheating alone, although mechanically driven cooling and filtration may be required towards the 2080s. While no single measure predicted universally positive effects for building performance, night ventilation and overhangs were found to be particularly effective passive overheating mitigation methods across the school stock

Climatic, energy retro-fit and IEQ mitigation scenario modelling of the English classroom stock model

Health and cognitive performance in UK school classrooms is dependent on building fabric performance as well as heating and ventilation system operation in maintaining Indoor Environmental Quality (IEQ), comprising thermal comfort and air quality. While archetype models can be used to simulate IEQ for different stock-wide location and construction eras, a predictive approach also necessitates the use of longitudinal scenarios. As a key component of the UK’s decarbonisation strategy, these scenarios should account for fabric retro-fit adaptations to reduce carbon emissions, and changes in operation of the building for overheating mitigation as well as changes in external climatic conditions. The IEQ of three representative classroom archetypes, representing the stock of 18,000 English schools, have been analysed for 24 pair-wise retro-fit and operational scenarios across three climatic scenarios. Retro-fitting, while effective in reducing energy demand, may risk compromising indoor air by requiring ventilation at times of the day when external conditions are least conducive to air quality and overheating. Additionally, while North facing classrooms can tackle overheating through single effective IEQ mitigation measures, South facing and 2080 climates will necessitate cumulative effects of multiple measures to be realised. Future work involves incorporating educational and construction stakeholder preferences through multi-criteria decision analysis, to derive suitable metrics