ABSTRACT. Energy retrofits in residential buildings are often assessed with a narrow focus on energy savings, while the broader social dimension of energy poverty remains underexplored. This research investigates the role of air-to-air heat pump performance in reducing energy consumption and carbon emissions while improving thermal comfort in low-income households. Two single-family houses serve as case studies: one currently operates with a low-quality heat pump, and another is undergoing renovation with a high-efficiency system. Preliminary assessments indicate that the existing system contributes to high energy demand, elevated emissions, and considerable costs for occupants, whereas the renovated system is expected to deliver significant improvements in these areas. Financial constraints prevent these households from investing in extensive retrofits toward net-zero energy and carbon-neutral standards, underscoring the need for affordable and accessible solutions. The objectives are to (i) compare the energy performance and carbon emissions of low- and high-efficiency systems, (ii) assess the impact of heat pump retrofits on thermal comfort, and (iii) evaluate their role in alleviating energy poverty. The methodology combines on-site measurement and monitoring with dynamic simulations in DesignBuilder to test different retrofit scenarios. The expected outcome is a framework for quantifying both energy and non-energy benefits of cost-effective retrofit measures, thereby supporting decision-making that integrates technical performance with social equity in building decarbonization.

ABSTRACT. Solar thermal greenhouse systems remain constrained by limited thermal storage capacity, as conventional storage configurations are often insufficient to maintain stable indoor temperatures during prolonged nighttime periods. This limitation leads to continued reliance on auxiliary energy, increasing both heating costs and greenhouse gas emissions. To address this challenge, a dual thermal storage system combining a conventional heat transfer fluid and wheat straw as an additional thermal mass was developed and implemented in a single-slope greenhouse equipped with a roof-integrated solar heating system. The objective was to enhance nocturnal heat retention, improve energy efficiency, and promote passive solar greenhouse heating. Comparative experiments were conducted against a conventional fluid-only storage system under identical conditions. The transferred energy was comparable in both systems, with an average efficiency of approximately 62%. However, the dual storage system exhibited significantly improved nighttime performance, releasing 13.04 kWh of stored heat compared to 7.59 kWh for the single storage system. This resulted in an increase in heating demand coverage from 48.8% to 83.89%, along with a rise of approximately 3°C in nighttime indoor temperature. The improved performance is associated with the combined contribution of the heat transfer fluid and wheat straw, which enhance heat storage capacity and reduce thermal losses during nocturnal periods. In particular, wheat straw improves heat retention due to its bio-based thermal properties. These results demonstrate that integrating agricultural residues into thermal storage systems offers an effective and economically viable strategy for reducing the carbon intensity of greenhouse production while enhancing system sustainability.

ABSTRACT. Conventional vapor compression air-conditioning systems have the drawbacks of wasting energy and fostering mold growth. Liquid desiccant air-conditioning systems (LDAS) overcome these two drawbacks through controlling independent temperature and humidity. However, traditional liquid desiccants have highly corrosivity towards metals which increase maintenance cost of systems. The advantages of deep eutectic solvents (DESs) as liquid desiccants are their low vapor pressure, cost and corrosiveness. Thus, a novel DES composed of a mixture of L-proline and ethylene glycol in a 1:6 molar ratio was proposed to replace halide solutions for commercial applications in LDAS. The effect of hydration on hydrogen bond network was investigated utilizing molecular dynamics simulations. The electrochemical workstation was adopted to test the corrosion rates of DES towards metals such as copper, iron and steel. Meanwhile, the corrosion mechanisms of DESs were elucidated based on based on an analysis of the surface microstructure of metals immersed in DES for half year. Compared with a lithium bromide (LiBr) solution with 60% concentration, DES offers a similar vapor pressure while reducing costs and corrosion rates by nearly 60% and 90%, respectively.

ABSTRACT. CoolST aims to shed light into the cooling market of South Tyrol (ST), providing evidence on the amount of cooling units installed, per type, per sector (residential, tertiary, industry, and transport/mobility) - quantifying actual energy consumptions, being able to generate projections for upcoming years (2040), so to clarify future energy needs and set ground on how to face them best. CoolST provides a Knowledge Hub, an online open source repository of assembled and quality controlled data and information about ST’s cooling market, and a Tool transforming these data/information into knowledge easily understandable (i.e. graphs). Since households play a more and more crucial role in this context, CoolST focuses on the residential sector. The focus is on generating missing primary data by a number of bottom-up approaches. A detailed market analysis identifies the supply chain structure, assessing market shares of manufacturers, sellers, and resellers at the provincial level for direct data retrieval. Moreover, parametric simulations have been carried out, based on local climatic datasets, social clusters, and archetypes etc. Outcomes have been compared, evaluated by experts, and counterposed to the few available results of reliable/scientific sources. CoolST adopts an interdisciplinary approach, intersecting the areas of engineering, architecture, economics, user-behaviour, ecology, health, and policies. We gathered data/information about the cooling market in ST, providing a comprehensive investigation on the status quo and future developments. First results display the cooling consumption in ST to be approximately 400 GWh/y with the transport/mobility sectors most consuming, followed by industry, tertiary and the residential sector.

ABSTRACT. This study investigates the real-world performance of a gravity-driven loop heat pipe multistage cooling system in an operating data center. The system integrates high- and low-temperature loops across three operating modes: free cooling, composite cooling, and mechanical refrigeration. By optimizing the temperature matching between the hot IT exhaust and the cooling me-dium, the system effectively minimizes irreversible heat exchange losses. Consequently, compared to traditional single-stage architectures, this two-stage system utilizes free cooling sources much more efficiently, yielding significant energy savings. To validate this technology, a partial retrofit was conducted in an operational data center in Zhangjiakou, China, supporting a total IT load of 24 kW. Field measurements revealed that across an outdoor temperature range of -9.4°C to 35.9°C, the system's Cooling Load Factor (CLF) fluctuated between 0.017 and 0.259. Furthermore, simulations utiliz-ing local Typical Meteorological Year (TMY) data indicate an annual average CLF of 0.068 and an equivalent Power Usage Effectiveness (PUE) as low as 1.140. This exceptional efficiency successfully meets the Grade 1 energy ef-ficiency standard, establishing a robust technical reference for retrofitting ex-isting air-cooled facilities and laying a crucial foundation for the realization of future zero-carbon data centers.

ABSTRACT. Energy consumption in public institutional buildings is strongly influenced by occupancy patterns and the diversity of uses, particularly in historical buildings adapted to contemporary functions. This paper presents the results of an energy audit carried out in Las Naves, a protected public building located in the city of Valencia and currently used as a multipurpose facility hosting offices, co-working spaces and cultural events. The audit was conducted in accordance with the Spanish Royal Decree 56/2016 and the UNE-EN 16247 standard. Electricity consumption data from utility bills covering a specific operational period were analysed to assess energy use, tariff structure, contracted power and possible penalties. In addition, indoor environmental data obtained from an existing monitoring system and on-site measurements were used to identify heating and cooling setpoints, operating schedules and non-productive energy consumption outside occupancy hours. An inventory of the main energy-consuming systems, including lighting, office equipment and HVAC installations, was carried out, together with an assessment of on-site photovoltaic electricity generation. The analysis allowed the characterization of energy demand by end use, the identification of parasitic loads and the calculation of key performance indicators such as energy consumption per square metre and associated CO₂ emissions. Based on the results, a set of energy efficiency improvement measures is proposed, including operational, technological and monitoring actions, aimed at reducing energy consumption, improving self-consumption and supporting the transition of the building towards an active prosumer role.

ABSTRACT. Energy efficiency in buildings is a fundamental pillar for decarbonization goals, with Heating, Ventilation, and Air Conditioning (HVAC) systems representing a major source of energy consumption in commercial buildings. Accurate indoor temperature forecasting is a key enabler for optimizing setpoints and reducing energy consumption, directly contributing to a zero-carbon built environment. This study aims to review and evaluate the performance of optimization-based linear models for short-term indoor temperature prediction, serving as a foundation for future optimal control strategies. The methodology formulates parameter estimation for autoregressive models with exogenous inputs as an optimisation problem, allowing the incorporation of physical constraints and regularisation to improve robustness compared with traditional methods. The models were trained and validated using one year of hourly data from a large commercial building in northern Portugal, analysing how model coefficients vary under different seasonal and operational conditions. Results demonstrate high predictive accuracy, with R² values consistently above 0.96 and RMSE below 0.23 °C, confirming that simple and cost-effective linear models can accurately capture thermal dynamics. It is concluded that this optimisation-based framework provides a natural pathway for implementing advanced Model Predictive Control (MPC) strategies and the development of Mixed-Integer Linear Programming (MILP) formulations. Furthermore, the significant variation observed in model coefficients (e.g., HVAC signal inversion) highlights the need for adaptive control approaches, such as gain scheduling, which adjusts controller parameters based on seasonal or operational changes, to effectively manage building energy flexibility throughout the year.

ABSTRACT. The energy transition has fostered decentralized configurations such as Renewable Energy Communities (RECs), in which prosumers aggregate to maximize collective self-consumption of renewable generation. Adoption dynamics remain poorly investigated, especially in terms of how technical, economic and social factors influence decision-making. This study develops an agent-based model to simulate the spatial-temporal enrolment of buildings in a REC at the district scale over a 20-year horizon. The model is applied to a mixed-use neighborhood in Bari (Italy) with rooftop photovoltaic systems. Each building is an agent characterized by a multi-criteria utility function integrating financial, energy, environmental, and peer-influence components. The relative weights of these criteria evolve dynamically according to contextual variables and local social interactions and are calibrated using observed regional photovoltaic adoption data. At each monthly step, agents first evaluate the feasibility of photovoltaic investment through discounted payback-time and, if viable, choose between remaining individual prosumers or joining a REC via a probabilistic decision rule. Results from 20 simulation runs show that REC membership grows mainly between years 1 and 5, reaching up to 39 buildings (about 33% of agents), and then stabilizes. Non-residential buildings consistently benefit from REC participation due to higher surplus generation, while only 14–32% of residential buildings enroll, as individual prosumer configurations often remain more attractive under the current Italian REC scheme. Financial and energy motivations dominate early adoption, whereas peer influence becomes increasingly relevant over time. Despite assumptions, the framework supports the design of targeted incentives to enhance urban energy transition policies.

ABSTRACT. To achieve carbon neutrality in the building sector, an objective energy performance evaluation approach that reflects end-use energy consumption characteristics is required. Accordingly, this study aims to analyze Energy Use Intensity (EUI) and Carbon Emission Intensity (CEI) characteristics of office buildings in South Korea using national big data and assess the applicability of a peer group-based assessment framework. For this, the building register data and the monthly utility billing data of office buildings were utilized. Peer groups were defined based on gross floor area, permit year, and climate zone, and annual energy consumption was disaggregated into end uses using the Simplified Energy Disaggregation (SED) and the Change Point Method (CPM). Then, the characteristics of total, cooling, heating, and baseload EUIs were compared among peer groups. The results showed that the average total EUI was 135.6 kWh/m²·yr, and EUIs generally increased with building size. By climate zone, the proportion of heating EUI was relatively higher in the Central region, whereas the Southern and Jeju regions showed relatively higher proportions of cooling and baseload EUI. In addition, the Y87 group showed the highest EUI, while baseload EUIs did not show any significant difference by permit year. The average total CEI was 55.7 kCO₂/m²·yr. CEI patterns by peer group were generally similar to those observed in the EUI analysis. However, heating CEIs tended to remain constant or decrease as heating EUIs increased. This peer group-based framework can serve as a baseline for future nationwide energy performance evaluation of office buildings in South Korea.

ABSTRACT. The World Green Building Council states that 1% of all building construction has reached net-zero status. As the push for sustainability intensifies to meet global agendas, more data on high-performance, energy-efficient buildings is essential to accelerate progress toward net-zero buildings. The zero-energy office in Singapore was retrofitted to feature advanced building systems for indoor cooling and lighting, intelligent controls, and smart sensors. It features a hybrid cooling system, a daylight-harvesting system, and occupancy motion sensors that regulate electric lighting. This current work syntheses work we have previously published. These systems can reduce cooling and lighting energy use, without compromising thermal and visual comfort or productivity. These innovative systems are integrated with Internet-of-Things sensors, enabling us to analyse and understand the performance of the zero-energy office. A hybrid cooling system allows the setpoint to be increased to 26.5°C when used with ceiling and desk fans, saving energy while ensuring thermal comfort. The daylight harvesting system allows workspace sensors to dim dedicated artificial lights, reducing energy consumption while keeping the work surface lit at a minimum of 500 lx. Occupancy motion sensors dim lights in areas that require constant illumination for safety but aren’t frequently occupied, such as corridors. This approach maximises energy savings by reducing unnecessary lighting in spaces without specific ownership. Since the zero-energy building exemplifies a unique integration of smart technologies, it offers a valuable opportunity to scale these solutions through retrofitting in other spaces. This could lead to the proliferation of net-zero construction within the built environment.

ABSTRACT. The global energy landscape is undergoing an accelerating transition toward renewables, with solar photovoltaics (PV) expected to constitute nearly 80% of the total expansion in power capacity by 2030. In this context, accurate very short-term solar forecasting (VSTSF) is important for real-time grid stability and optimal power dispatch. However, current multi-site forecasting models often employ sequential architectures that decouple spatial and temporal feature extraction, limiting their ability to characterize rapid irradiance fluctuations driven by cloud advection. This study proposes a multi-site VSTSF approach based on a Spatiotemporal Graph Convolutional Network (STGCN) to simultaneously aggregate spatiotemporal information. The model utilizes a sandwich structure of temporal gated convolutions and spatial graph convolutions, implemented with 1-minute resolution data from seven monitoring sites in Nottingham, UK. Results indicate that the STGCN outperforms both single-site LSTM and sequential CNN-LSTM models, achieving a global Root Mean Square Error (RMSE) of 100.57 W/m^2 and a forecasting skill of 5.36%. Furthermore, typical day analysis confirms the model’s superior tracking capability during high fluctuate GHI condition, effectively reducing temporal misalignment. This work provides a robust and accurate solution that offers essential support for the real-time operation and optimal dispatch of modern power systems.

ABSTRACT. With solar energy growing rapidly worldwide, electrical grids are increasingly required to accommodate its variable power output due to the intermittent nature of the sun. Solar forecasting is a crucial tool for mitigating these challenges, particularly for short-term prediction of ramp events that impact grid operations. This is especially important in climates dominated by variable cloud cover, such as in Northern Europe, where integration requires models capable of predicting ramp events quickly and accurately. Artificial Intelligence models, particularly Artificial Neural Networks, have attracted significant interest in this context. However, the “black box” nature of these models has led researchers to adopt heuristic classifications scheme that split data based on predefined categories to improve both accuracy and interpretability. In this study, we use purely meteorological data to evaluate the effectiveness of different classification schemes based on season, Clear Sky Index and wind speed in a relatively cloudy and variable environment, specifically the UK.

ABSTRACT. With the rapid increase in Photovoltaic (PV) installation worldwide, PV systems are becoming one of the main renewable energy technologies for electricity generation. However, variations in cloud and sky conditions lead to fluctuations in solar irradiance. As a result, PV generation becomes intermittent, causing variability in power output that poses significant challenges to the stability and reliability of electricity grids. Solar forecasting is one of the key approaches to addressing these challenges. To improve the accuracy of PV output predictions, three main approaches have been adopted: physical models for PV output prediction, machine learning models for PV output prediction, and hybrid models combining both machine learning irradiance modelling and physical calculations. While purely physical models rely on simplified assumptions that hinder their ability to represent nonlinear and uncertain behaviours, purely data-driven machine learning models are constrained by data dependency and limited interpretability, leading to reduced robustness and generalization. Although each method has its own strengths and limitations, hybrid models have gained popularity due to their higher predictive accuracy and has the potential to be applied across different regions through transfer learning, with only minor adjustments to a small number of model coefficients. This study proposes a new approach by incorporating a Long Short-Term Memory (LSTM) network for solar radiation forecasting with a single-diode model for PV output prediction. To reduce the model complexity, single diode mode is the most common and easiest physical model used to describe PV cell. The method systematically investigates the effects of different input features and evaluates the prediction accuracy of the machine learning model. The results demonstrate that the proposed approach significantly improves PV output forecasting, providing stronger support for grid management.

ABSTRACT. Smart Home Energy and Comfort Management(HECM) Systems face a critical bottleneck: balancing energy efficiency and user comfort while providing transparent, explainable control logic to ensure user trust. Traditional black-box models and standard accuracy metrics fail in real-world physical deployments. This report proposes a Thinking-Enhanced Low-Rank Adaptation (LoRA) method for Small Language Models (SLMs) on edge devices. Evaluated via a novel Six-Dimensional Framework, the proposed model achieved an overall policy score of 0.8237 (approximating the human benchmark of 0.8254), guaranteed explainability (0.7160 score, 98.2% coverage), completely resolved the "Mode Collapse" issue typical in standard LLM fine-tuning, and improved comfort by 15.6%.

ABSTRACT. Accurate electricity load forecasting is essential for reliable and efficient power system operation under increasing uncertainty and complex load dynamics. However, existing forecasting approaches often struggle to simultaneously capture global patterns and uncertainty characteristics. To address this problem, this paper proposes a hybrid probabilistic forecasting framework based on Seasonal–Trend decomposition using Loess (STL). The original load series is decomposed into trend–seasonal and remainder components, where a multilayer perceptron (MLP) learns deterministic patterns and a Bayesian neural network (BNN) models remainder components with uncertainty quantification. Experimental results demonstrate that the proposed MLP–BNN framework achieves improved forecasting accuracy, increased calibrated prediction intervals, and reduced probabilistic forecasting loss compared with the conventional BNN model. At the daily level, the proposed method reduces the mean absolute error (MAE) by 18.92%. This performance improvement mainly results from enhanced global load profile modelling capability, which enables more effective learning of load dynamics and uncertainty representation. Consequently, the proposed framework provides a reliable probabilistic forecasting solution that supports informed decision-making in power system operation and energy management.

ABSTRACT. Climate change is intensifying summer cooling demand in buildings, particularly in Mediterranean climates, and poses new challenges for data-driven energy management systems that should remain reliable under increasingly variable thermal conditions. This work presents PINODE, a two-phase Physics-Informed Neural Ordinary Differential Equation framework for building thermal prediction designed as a differentiable model for integration in Model Predictive Control (MPC) loops. Phase 1 trains on BESTEST 600FF free-floating data to learn zone temperature dynamics via a Temporal Convolutional Network encoder and a physics-corrected ODEFunc integrated with RK4. Phase 2 uses Phase 1 output to estimate cooling power through a gated dual-head network on BESTEST 600 conditioned data. Physics-informed loss functions embed the zone energy balance as a soft constraint with auto-balanced weights. It is valuated at four prediction horizons (+1 h, +24 h, +72 h, +168 h) on the standardised BESTEST benchmark, PINODE achieves RMSE = 0.392°C and R² = 0.998 for operative temperature at +72 h, and RMSE = 0.152 kW and R² = 0.985 for cooling power at +168 h. The characteristic improvement from the single-step horizon to multi-day horizons, a signature of the RK4 trajectory integrator, confirms that PINODE naturally operates at the timescales required by MPC optimisation windows, while its fully differentiable latent space enables direct integration into gradient-based receding-horizon controllers without surrogate models. The framework provides a physically consistent and reproducible baseline for building energy prediction, with a direct pathway toward SSM-DPC integration for HVAC optimisation under climate change scenarios.

ABSTRACT. Abstract. Wood Plastic Composite (WPC) materials are increasingly adopted in building applications due to their durability, low maintenance requirements, and aesthetic versatility. Beyond their architectural appeal, recent laboratory investigations have shown that certain WPC formulations can exhibit exceptionally low thermal conductivity, in some cases below 0.01 W/m·K, indicating a strong potential for thermal insulation applications. In this study, a low-thermal-conductivity WPC sample with dimensions 10 cm × 10 cm × 1 cm was installed on the external wall of a portable test cabin exposed to real climatic conditions. Type-K thermocouples were deployed on the WPC surface, the underlying wall surface, and reference locations to experimentally quantify the impact of the WPC layer on surface temperature evolution. The results demonstrate a measurable attenuation of external surface temperature fluctuations and a reduction in heat transfer to the wall substrate, confirming the insulating effectiveness of the low-k WPC under hot-climate conditions. The findings suggest that WPC materials with ultra-low thermal conductivity can serve not only as exterior cladding solutions that enhance building aesthetics, but also as functional insulation layers, particularly suitable for hot and arid climates. Furthermore, based on our recent studies indicating superior building-envelope performance of low-thermal-conductivity phase change materials (PCMs), this work opens new opportunities for developing WPC–PCM doped composites that combine thermal insulation with latent heat energy storage for next-generation sustainable building envelopes.

ABSTRACT. Retrofitting residential buildings in Hong Kong’s hot-humid climate requires balancing energy performance, indoor comfort, and daylight availability. Building-integrated photovoltaics (BIPV) smart windows can both regulate solar radiation and generate on-site electricity, but their operation involves inherent trade-offs among these objectives. This study proposes an occupancy-based, climate-responsive control strategy for three-state BIPV smart windows and applies multi-objective optimization to identify Pareto-optimal solutions across net energy use intensity (NEUI), thermal comfort, and useful daylight illuminance (UDI). Using a representative Hong Kong residential prototype, integrated simulations are performed with EnergyPlus, Radiance, and PV generation models. Results indicate that dynamic control reduces NEUI while maintaining high thermal comfort and acceptable daylight performance compared with static window operation, and simultaneously increases PV electricity generation. Evaluation under future climate scenarios further shows that the control strategy optimized for present climate conditions remains robust under projected future climates.

ABSTRACT. With the increasing impact of climate change, the importance of investigating the effect of occupants’ comfort on the energy consumption and environmental impacts becomes vital. For these different procedures to be included, the usage of one platform for database integration, information interoperability, geometry manipulation and flexibility, and performance simulation is critical. This research develops a parametric BIM-based life cycle assessment framework using visual programming through Grasshopper to achieve this flexible approach. The developed framework assesses the effects of external roller shading and glazing on indoor environmental quality, energy consumption, and environmental impacts by developing different passive retrofit scenarios. These indoor environmental quality factors constitute thermal and visual comfort. Different software tools and plug-ins are used constituting Rhino-Inside-Revit, Ladybug, Honeybee, and GhPython. These tools are used for the quantification of cooling, heating, and lighting loads, thermal comfort percentage, average daylight factor, and global warming potential. The performance simulation is done on a 3D laser-scanned one-story building. The developed framework investigates the trade-off relationships among these performance indicators, serving as a starting point for a unified methodology and framework for future analyses. These future analyses will consider interactive occupant behavior and multi-objective optimization to develop optimal retrofit passive solutions.

ABSTRACT. This study investigates the seasonal thermal performance of a double-skin façade (DSF) integrated with multi-layer microencapsulated phase change material (MPCM) blinds. To address the leakage risk and limited temperature adaptability of conventional PCM blinds, two MPCMs with nominal phase change temperatures of 40 °C and 12 °C were incorporated into a layered blind structure for high- and low-temperature seasonal conditions. A two-dimensional heat transfer model was established and validated through comparative experiments using conventional aluminum alloy blinds, single-layer PCM blinds and the proposed multi-layer MPCM blinds. The results show that the multi-layer MPCM blinds effectively improved the thermal stability of the DSF cavity and indoor environment. During the high-temperature season, the system reduced the peak cavity and indoor temperatures by 5.3 °C and 5.0 °C, respectively, and decreased the total indoor heat gain by 25.6% compared with the aluminum blind system. During the low-temperature season, latent heat release increased the night-time cavity temperature by 3.9 °C and reduced the cumulative undercooling discomfort from 241.9 h·°C to 201.9 h·°C. These findings indicate that multi-layer MPCM blinds can enhance the seasonal adaptability and energy performance of DSF systems.

ABSTRACT. The modulation of solar spectrum and long-wave thermal emissivity (ε) in window systems play a critical role in building energy conservation. However, research on the combined mechanism of thermotropic (TT) material with dynamic ε modulation remains limited. This study proposed a novel Rotatable Thermotropic Radiative-Adaptive Window (RTRAW) for solar spectrum regulation and seasonal ε modulation which was constructed by sandwiching a PNIPAm TT layer between two glass panes with different ε. Furthermore, this study initially investigated the energy performance of the building applying the RTRAW by employing EnergyPlus. The results indicate that, compared with the building equipped with conventional low long-wave thermal emissivity (Low-E) windows and PNIPAm TT windows, the proposed RTRAW system can effectively reduce building energy demand by 8.52% and 4.89%, respectively. Meanwhile, the RARTW demonstrates greater energy efficiency and better adaptability in lager WWR exterior wall compared to conventional Low-E windows and PNIPAm TT windows. Additionally, the optimal performance parameters of the RARTW were investigated. For example, the building applying the RARTW can achieve a minimum energy demand at a WWR of 0.5. And at a phase transition temperature of 24°C for PNIPAm TT material, the building achieves a minimum energy demand. These findings highlight the potential of the RTRAW system as a promising strategy for energy-efficient and adaptive window technologies.

ABSTRACT. Abstract: The thermotropic (TT) window, due to its temperature response, can reduce solar transmittance to block solar radiation to reduce cooling loads in cooling seasons, and remain transparent in heating seasons to enhance passive solar heat gains. Most current studies predicted the dynamic thermal response of TT windows by average surface temperature, neglecting the temperature distribution impact on transmission uniformity of the TT window. This study investigates the temperature distribution and spatial thermal response characteristics of TT windows applied in an office building. The impacts of indoor thermal factors on the window surface temperature, including temperature distribution from different supply air velocity and different air supply modes, were evaluated by using a numerical simulation tool, computational fluid dynamics (CFD). The results indicate that different ventilation modes have a significant impact on the temperature distribution of the TT window. The ceiling-supply and ceiling-return ventilation mode has the least influence on the temperature distribution of the TT window. Furthermore, with increasing air supply velocity, the uniformity of the TT window surface temperature deteriorates under the ceiling-supply and ceiling-return ventilation mode, whereas it improves under the other two ventilation modes. Under the three ventilation modes, the predicted average transmittance of the TT window obtained from EnergyPlus and Ansys Fluent does not always show perfect agreement. At certain moments, the window may even exhibit opposite trends between the two models. These discrepancies may influence the accuracy of predicting the indoor thermal and daylighting environments.

ABSTRACT. Achieving a zero-carbon built environment requires assessment frameworks that move beyond building-level energy metrics to capture neighbourhood-scale interactions, social dynamics, and regeneration processes. This paper presents the Impact Model (IM) developed within the Horizon Europe–funded WeGenerate project as a compact and flexible KPI framework designed to support people-centred, sustainable urban regeneration in European neighbourhoods. The WeGenerate IM aims to address four critical challenges in contemporary assessment practice: (i) limited and heterogeneous data availability, (ii) meaningful citizen participation, (iii) holistic evaluation of neighbourhood metabolism, and (iv) operational and transferable assessment schemes. The model comprises 20 core KPIs, complemented by a set of context-specific optional indicators, structured into six balanced thematic categories addressing: energy and environmental performance, mobility, integrated urban regeneration, digitalisation, social inclusion and citizen participation, and socio-economic aspects. This structure supports a robust assessment of the decarbonisation pathways while explicitly recognising social inclusion, behaviour change, and quality of public space as key factors for a zero-carbon transition. The framework has been designed and is being tested across four European demonstrators using harmonised data collection tools, participatory workshops, and cross-site validation. Early testing indicates that the compact KPI set improves operability and comparability in contrast to extensive reference frameworks, while maintaining sufficient pliability to reflect local priorities and alignment with the major European frameworks. Overall, the strong people-centred focus of the WeGenerate IM enhances citizen engagement and supports an integrated, single evaluation of environmental and socio-economic impacts within an operational, adaptable, and transferable assessment model for neighbourhood-scale zero-carbon regeneration.

ABSTRACT. Energy poverty is a multidimensional phenomenon shaped by socioeconomic vulnerability, behavioural patterns, and the physical condition of the built environment and remains a persistent challenge across Europe, particularly in Southern countries where income inequality, inefficient housing stock, and rising energy costs disproportionately affect low-income households. In Portugal, these challenges are visible at the local level, including in the municipality of Cascais, where marked socioeconomic disparities coexist with high living costs. This study develops a multidisciplinary assessment of energy poverty in Cascais, undertaken within the WeGenerate - Co-creating People-Centric Sustainable Neighbourhoods through Urban Regeneration project, which proposes to establish an inclusive energy community to support social housing residents. The underlying research combines social science, energy economics, and engineering to generate an integrated diagnosis of local energy vulnerability and to estimate the potential welfare impact of community energy solutions in deprived neighborhoods. A structured survey was administered to three population groups, with a total sample of 558 respondents: (1) residents of Bairro the Alcabideche, the primary intervention site; (2) residents of the remaining social housing neighbourhoods in Alcabideche; and (3) users of public buildings, predominantly middle-income households, connected to the photovoltaic infrastructure of the energy community. The survey captures expenditure-based indicators of energy burden and affordability, alongside perception-based measures of thermal comfort, vulnerability, and quality of life. The findings are benchmarked against national-level indicators to contextualize local disparities. In parallel, engineering and infrastructure data are integrated into the analysis to identify structural determinants of energy poverty and quantify technical constraints. Finally, the study employs scenario modelling by combining the survey-based energy indicators with technical assumptions on energy cost reductions and building performance improvements to estimate potential impacts in energy poverty prevalence following the implementation of the project. The results indicate substantial differences in energy vulnerability within Alcabideche and suggest that investments in inclusive energy communities, when combined with building refurbishments, have significant potential to reduce energy bills, improve comfort, and reduce energy-related inequalities in social housing contexts. The study contributes evidence to support locally tailored policies and equitable energy transitions in Portugal and other Southern European settings.

ABSTRACT. Urban Digital Twins (UDTs) have rapidly emerged as a prominent instrument within urban digitalisation agendas, promising data-driven decision-making, real-time optimisation, and enhanced urban sustainability. Recent literature, however, indicates that while the technical capacity to develop sophisticated city-scale digital models is largely established, their effective use in municipal decision-making and governance remains limited. This limitation is primarily attributed to the absence of a shared understanding of UDT models, leading to misapplication and mismatched expectations, as well as challenges in integrating UDTs into existing municipal workflows and a lack of capacity cross the stakeholder chain to translate technical outputs into actionable policy decisions. This paper presents a systematic and critical review of contemporary UDT applications and research, with particular attention to their contributions and shortcomings in advancing sustainable and inclusive urban development.

A preliminary analysis highlights a significant ambition–reality gap. Despite narratives portraying UDTs as enablers of real-time urban management and transformative decision-making, many existing implementations function primarily as advanced visualisation platforms or isolated technical prototypes. Moreover, a persistent tension exists between technological ambition and participatory practice. Most UDT initiatives remain top-down and infrastructure-centric, focusing on efficiency gains in domains such as buildings, energy systems, and mobility, while human-centred outcomes, including community participation, social inclusion, and public acceptance, are only marginally addressed.

Building on these insights, the paper synthesises key research gaps across five interrelated dimensions: foundational semantic models of UDTs, linkages between digital and physical urban systems, support for decision-making processes, mechanisms for community awareness and engagement, and socio-technical integration within municipal workflows. The paper argues for reframing UDTs as components of broader municipal digital ecosystems rather than standalone technologies. In doing so, it contributes to ongoing debates on how UDTs can move beyond technological experimentation to meaningfully support carbon-neutral and people-centred urban development. This study is conducted within the framework of the WeGenerate project, which addresses sustainable and inclusive urban regeneration, including a focus on better understanding the role of digital technologies.

ABSTRACT. The acceleration of climate change and the decarbonisation of the built environment call for approaches that go beyond technological solutions, recognising the role of citizens in shaping energy-related decisions and practices. Within this debate, the concept of energy citizenship has emerged as a useful lens to understand how participation, responsibility and agency can be redistributed across urban energy systems. This paper draws on the energy citizenship framework to reflect on a methodological tool developed within the WeGenerate and the GRETA projects, designed to support urban practitioners and operative staff working within local authorities. The tool takes the form of an Engagement Strategy Guideline structured as a checklist-based canvas, intended to assist practitioners in the practical design of citizen engagement strategies for climate and energy action. The guideline addresses the inherent complexity of urban energy and environmental transitions by bringing together technological, behavioural, social and governance perspectives. It supports users in identifying key stakeholder groups, clarifying engagement objectives, selecting appropriate participatory formats, and aligning engagement activities with policy frameworks and local implementation constraints. Particular attention is given to the links between building-related energy interventions, neighbourhood-scale actions and wider urban climate strategies. By translating energy citizenship from a conceptual notion into an operational support tool, this contribution offers a practice-oriented framework that can be further tested, refined and evaluated through application in different urban contexts, opening up future research on its effectiveness, transferability and impact on long-term decarbonisation pathways.

ABSTRACT. Urban regeneration presents unique opportunities to revitalise disadvantaged areas and turn them into vibrant, inclusive, and sustainable neighbourhoods where people want to live and put down roots. Although urban regeneration is a place-based process, where effective strategies and actions are shaped by specific local context, strengths and weaknesses, successful projects do share some key commonalities.

Due to the multiple domains and diverse needs, the urban regeneration model should be designed as an integrated framework, ensuring interconnectivity between innovations, process-oriented implementation, and replicability. Within the context of a European project, four demonstration neighbourhoods have expressed the ambition to transform and regenerate their urban context bringing together interconnected domains as spatial planning, environmental and energy performance, mobility, social innovation, and governance mechanisms into a coherent approach that is adaptable to a variety of urban contexts.

A neighbourhood regeneration model is proposed in this study, considering an integrated design approach capable of coordinating energy transition, spatial transformation, social innovation, and mobility in a structured and operational manner. The model includes an operational, stepwise process that supports decision-making throughout the regeneration lifecycle and facilitates successful replication. Its validity will be tested in the four demonstration neighbourhoods.

ABSTRACT. The INA-Casa Vigne block in Cesena, Italy—a 1960s social housing neighbourhood—exemplifies the retrofitting challenges of modern heritage building stock in the transition toward climate neutrality. This paper presents the methodology developed within the EU WeGenerate project to design an Urban Digital Twin (UDT) workflow as a decision-support tool for multi-layered, neighbourhood-scale retrofit strategies grounded in the concept of Positive Energy Districts (PEDs). The workflow constructs GIS-based 3D models of INA-Casa blocks according to the CityGML standard, enabling semantically rich representations and interoperability with IoT and BIM domains, including geometry, land-use characterisation, and energy performance data from Energy Performance Certificates (EPCs). Collected datasets are organised in a 3DCityDB geospatial database structured around CityGML and its thematic modules, ensuring consistent data management and advanced querying. Key steps include assembling a geospatial database from open data sources, automated attribute mapping supported by Large Language Models (LLMs), geometric refinement through FOSS tools (e.g. 3DCityDB, QGIS, Blender), and bidirectional data flows to support Urban Building Energy Modelling (UBEM) simulations of retrofit scenarios such as envelope insulation, HVAC electrification, passive solar measures, and on-site renewables. Validated on mixed-use analogue districts, i.e. Rome’s Ostiense and Civitavecchia’s San Liborio, the approach demonstrates interoperability, scalability, and replicability for large-scale housing regeneration. By coupling advanced 3D city modelling with collaborative knowledge co-design and local regulatory plan directives, the UDT methodology supports climate-neutral urban planning pathways, operationalisation of PED concepts, and strengthened collaboration among municipalities, utilities, and community stakeholders.

ABSTRACT. Urban regeneration is a transformation process that encompasses multiple strategies and interventions to enhance physical, digital, economic, social, and ecological aspects of urban areas to improve quality of life and create functional and sustainable urban environments. As cities undergo rapid transformation processes, a holistic integration of these transitions becomes an important discussion subject. This study adopts a bibliometric-systematic literature review methodology to explore the current research landscape of urban regeneration. First, 3142 research articles published since 2015, were retrieved from Scopus and Web of Science databases and analyzed using bibliometrix and VOSviewer software to identify the main contributors, most frequent keywords, thematic clusters, and emerging trends. Then, 46 articles were selected for a systematic review to identify synergies, conflicts and crit-ical gaps in the interplay between the digital, built, mobility and social transi-tions through a co-creation lens. The bibliometric analysis revealed 5 themat-ic clusters covering built, environment, digital, planning, mobility, govern-ance, cultural, social and economic aspects, highlighting the complexity of the field. The in-depth review showed that co-creation operated urban regen-eration through these clusters as a critical integrative mechanism, balancing synergies (mainly between social, built-environment-digital and planning-mobility clusters to improve both environmental and social outcomes) and conflicts (lack of digital literacy, institutional fragmentation, and trade-offs between energy efficiency, cultural identity and community needs). By syn-thesizing existing knowledge and exposing how co-creation can support more integrated and people-centered urban regeneration, this study helps to guide future research on urban transitions.

ABSTRACT. This paper investigates Renewable Energy Communities (RECs) as innovative instruments for urban regeneration, focusing on their dual role in ad-vancing decarbonisation and mitigating energy poverty. Cascais Municipality, aligned with EU climate neutrality objectives, launched a pilot in Alcabideche integrating technical deployment with social engagement. The intervention in-cluded photovoltaic (PV) systems on five public buildings and five social hous-ing blocks, complemented by three electric vehicle chargers. Preliminary moni-toring indicates reductions in household electricity bills of up to 30%, contrib-uting directly to alleviating energy poverty. To complement the technical im-plementation, structured surveys and focus groups were conducted with resi-dents and local stakeholders. Findings reveal high levels of interest in partici-pating in RECs, though concerns remain regarding information accessibility, trust in governance structures, and long-term benefits. Citizen engagement ac-tivities proved essential in overcoming these barriers, reinforcing social ac-ceptance and community ownership. The initiative is supported by the WeGen-erate project, which provides frameworks for replicating REC models across Europe, linking technological innovation with participatory governance. Results demonstrate that socially inclusive RECs can simultaneously enhance energy efficiency, reduce carbon emissions, and strengthen social cohesion, positioning them as critical enablers of equitable and resilient urban regeneration.

ABSTRACT. The continuous rise in sewage sludge (SS) production—driven by population growth, urbanization, industrial expansion, and stricter wastewater treatment regulations—has intensified the need for sustainable management strategies, particularly for mechanically dewatered SS that is still largely landfilled. Landfilling involves high costs and long-term environmental concerns, while thermochemical routes such as gasification offer energy recovery potential but are hindered by high moisture content and the lack of integrated, site-specific techno-economic assessments. This study presents, for the first time, a comprehensive Aspen Plus–based simulation coupled with a techno-economic evaluation of an integrated drying–gasification–combustion system for mechanically dewatered SS. The model incorporates thermal drying, air-blown gasification, and syngas combustion with internal heat recovery, and compares the proposed configuration with conventional landfilling for a real wastewater treatment plant (WWTP) in southern Italy using Net Present Value (NPV), Simple Payback Period (SPB), and Profitability Index (PI). A drying model was created to lower the moisture of mechanically dewatered SS to below 10 wt.% for gasification, incorporating mass and energy balances and drying kinetics. The gasification stage assesses air-based conversion of dried SS into syngas, estimating its composition, heating value, cold gas efficiency, and carbon conversion efficiency across various conditions. The produced syngas is then combusted in a boiler to supply heat back to the dryer, reducing reliance on external fuels. Operating factors such as drying and gasification temperatures, equivalence ratio, and excess air are optimized in Aspen Plus to enhance both energy and economic performance. Findings show that this integrated approach can cut SS management costs compared with landfilling while yielding positive NPV, reasonable payback time, and PI above one under practical scenarios. The work offers a structured tool to support wastewater treatment facilities and decision-makers in shifting from disposal-based practices to energy recovery strategies.

ABSTRACT. The global construction industry accounts for approximately half of annual carbon emissions, resource depletion, and environmental degradation, making the transition to net zero carbon-built environments imperative. Digitalisation and innovative construction methods offer the potential to expedite this shift. This study investigates the role of Building Information Modelling (BIM) and Modular Integrated Construction (MIC) in enhancing building sustainability and supporting net zero carbon objectives. 50 valid responses were analysed to evaluate the sustainability benefits and challenges associated with BIM and MIC implementation. Sustainability performance was assessed across environmental, economic, and social dimensions, with focusing on carbon reduction, material efficiency, productivity, and waste minimisation. Descriptive statistics, regression analysis, and hypothesis testing were employed to examine the relationships between BIM and MIC benefits, implementation challenges, and overall sustainability outcomes. Results reveal a strong positive relationship between BIM and MIC implementation and sustainable construction performance (R²=0.917). BIM benefits demonstrate a statistically significant positive impact on sustainability (β = 0.461, p = 0.001) through improved design coordination, reduced errors and rework, and enhanced lifecycle-based decision-making. MIC benefits also show a significant positive contribution (β=0.244, p=0.030), with reduced material waste, improved quality control, enhanced site safety, and shorter construction durations. However, MIC-related challenges exhibit significant negative influence on sustainability outcomes (β=−0.374, p< 0.001), highlighting barriers including high initial costs, limited technical expertise, and coordination constraints. The findings demonstrate the complementary role of BIM and MIC as enablers of net zero carbon construction, providing evidence-based insights to support industry stakeholders and policymakers in advancing sustainable built environment strategies.

ABSTRACT. Climate change education in secondary schools often struggles to convey complex concepts such as embodied energy, operational energy, and life cycle assessment (LCA) in ways that engage students and promote deep understanding. This study explores the effectiveness of immersive virtual reality (VR) as a pedagogical tool for teaching building energy performance and environmental sustainability concepts to high school students. We developed an interactive VR environment featuring a single-family residential home with pre-simulated operational and embodied energy results. Students could manipulate key building parameters including window-to-wall ratio (WWR), building orientation, and insulation levels, with real-time visualization of energy impacts through volumetric cubes, temperature cut planes, and graphical representations of operational and embodied energy. This hands-on approach allowed students to explore cause-and-effect relationships between design decisions and environmental outcomes. Using a pre-post survey design, we assessed changes in students' confidence levels across multiple sustainability domains including climate change, greenhouse gas effects, carbon emissions, LCA, energy efficiency, and carbon neutrality. The survey also measured shifts in attitudes toward professional responsibility, environmental stewardship, and willingness to apply life cycle thinking in future careers. Knowledge gains were evaluated through multiple-choice questions covering greenhouse gases, LCA indicators, and building energy fundamentals. Preliminary observations suggest strong student engagement with the VR platform and positive reception of the visualization techniques. Complete analysis of pre-post survey data is currently underway and will provide quantitative evidence of learning gains and attitudinal shifts. This study contributes to the growing body of research on immersive technologies in STEM education and offers insights for construction management and engineering educators seeking innovative approaches to sustainability instruction.

ABSTRACT. Climate change adaptation in the built environment increasingly demands data-driven design tools that can balance resilience, energy performance, and material sustainability. The interaction between building form, construction materials, and the environment such as ground heat exchange, solar exposure, and air temperature dynamics presents both challenges and opportunities for reducing the life cycle impacts of buildings. Harnessing these interactions through systematic design exploration can play a pivotal role in reducing the energy demand and carbon footprint of future construction. This study introduces an inverse optimization framework as a novel decision-support tool for building systems. The framework determines optimal combinations of building envelope materials, window-to-wall ratio, and orientation based on target performance indicators for operational and embodied impacts. By defining desired carbon outcomes, the inverse process works backward to identify feasible design configurations that satisfy those goals. The approach is applied to representative buildings across climatic contexts to evaluate its potential for adaptation and mitigation. Results demonstrate that inverse optimization can reveal design strategies that minimize both operational and embodied carbon while adapting to local climatic conditions. In hot climates, optimization favors increased insulation, and orientation strategies that reduce solar gains. In cold climates, the framework emphasizes thermal mass utilization and low-carbon structural assemblies. These outcomes illustrate how design parameters can be systematically tuned to support and reduce lifecycle carbon footprints, and enhance climate resilience. The outcomes of this study can inform multiple stakeholders involved in shaping the sustainable built environment. Architects and design engineers can use the framework as a decision-support tool to identify material and configuration choices that achieve specific carbon targets early in the design process. Policy-makers and regulators can draw on the results to establish evidence-based performance benchmarks and guide the integration of life cycle thinking into building codes. Construction professionals and material manufacturers can leverage the findings to align product development and construction practices with evolving climate and energy contexts. Finally, researchers and educators can employ the framework to advance interdisciplinary studies connecting material science, building physics, and environmental performance.

ABSTRACT. The transition towards a circular and low carbon-built environment requires enhanced transparency, traceability, and structured environmental information across product life cycles. Digital product passports (DPPs) are emerging within the European regulatory landscape as key instruments to support sustainable product policies. However, their operationalization in the construction sector, particularly for complex and long-life building envelope systems, remains insufficiently defined, and specifically studied. The aim of this study is to develop a conceptual integration framework for DPPs tailored to building envelope systems, structured around life cycle assessment (LCA) logic and key technical and circularity attributes. A literature review is combined with regulatory mapping and data requirement analysis to identify interoperability gaps between DPPs data structures and environmental product declarations (EPDs). The proposed framework includes a functional data-layer model, life-cycle information flows, and interoperability requirements necessary to enable dynamic environmental performance tracking. The results clarify the role of DPPs as integrative instruments bridging product-level data, building-scale assessment, and circular economy objectives. The framework could provide a foundation for a standardized DPP data requirements for envelope systems and support the development and consistent integration of product information into building level-level LCA and circularity assessment in the construction sector.

ABSTRACT. The transition towards more sustainable and efficient demolition practices has led to increasing interest in digital deconstruction approaches. While academic research has explored a wide range of digital technologies, including Building Information Modelling (BIM), scan-to-BIM workflows, 4D simulation, and digital twins, their practical implementation within industry workflows remains limited. This study aims to bridge the gap between research and practice by integrating real-world demolition workflows with digital deconstruction methods identified in the literature. A qualitative investigation was conducted through interviews with project managers and industry practitioners to capture the current demolition workflow within a leading demolition company. The findings reveal that existing practices are largely experienced-driven, with limited use of structured digital data and minimal integration of advanced digital tools beyond basic planning and documentation. In parallel, a comprehensive literature review was undertaken to examine state-of-the-art digital technologies applied in demolition and deconstruction, focusing on data acquisition, BIM-based modelling, sequencing, and material recovery methods. By comparing industry workflows with academic approaches, the study identifies key gaps, including the lack of standardised data structures, limited integration between modelling and sequencing tools, and insufficient support for material recovery and circular economy strategies. To address these challenges, a data-driven digital deconstruction workflow is proposed, integrating Revit-based BIM models with COBie-compliant datasets to enable structured information management, improved decision-making, and enhanced linkage to 4D simulation and material recovery processes. The proposed framework demonstrates how combining geometric modelling with structured asset data can support more efficient, safe, and sustainable demolition planning. This research contributes to the advancement of digital deconstruction by providing a practical pathway for aligning academic innovations with industry needs.

ABSTRACT. China currently ranks first globally in total carbon emissions, and the construction industry is a major contributor to this footprint. Public buildings, in particular, have high energy consumption per unit area while holding substantial energy-saving potential. Previous research on their low-carbon development has mostly focused on specific aspects like building materials and equipment systems, failing to comprehensively explore low-carbon pathways from a whole life cycle perspective.This paper conducts a comparative analysis of domestic and international studies on low-carbon energy efficiency in public buildings. It categorizes key issues in developing their life-cycle low-carbon pathways into three main areas: policy, materials and equipment, and building operation and management. The study also clarifies the current status and deficiencies of China’s research on public building low-carbon development at different stages. Based on literature review, the paper aiming to provide theoretical support for future low-carbon pathway research and help the construction industry achieve carbon peaking and neutrality goals.

ABSTRACT. Cities are the largest consumers of energy in the European Union (EU) and responsible for a significant share of GHG emissions, playing a decisive role as both the causes and solutions of energy transitions. In turn, strengthening urban efficiency and sustainability requires integrated, data‑driven approaches to support informed local level decision‑making. Under this remit, two complementary projects under the Portuguese Energy Transition Alliance (ATE) contribute with two tools to support municipalities in decision-making and managing local assets. The first, POEM, develops an online integrated Platform for Municipal Energy Optimization designed to assist cities in efficiently managing energy. Particularly, it builds on design-tailored machine‑learning algorithms to forecast both PV production and energy consumption, and detecting anomalies in the PV systems or excessive consumption levels. The platform provides a user-friendly interface, showcasing interactive dashboards and alerts, and targeted user recommendations. It has been piloted in the municipality of Águeda, representing a useful tool supporting local action. Complementarily, EDEn develops a municipal Energy Performance Label. It considers a comprehensive set of indicators, capturing both drivers of local energy performance (e.g. buildings, transport…) and underlying context factors, which should not benefit nor penalize municipalities with diverse backgrounds. Machine-learning algorithms are employed to identify performance levels for the performance label. This provides municipalities, decision-makers, and citizens at large with a transparent and objective tool informing strategic energy decisions at local level, also driving municipal attractiveness and competitivity. Altogether, POEM and EDEn equip municipalities with both operational tools and strategic guidance to accelerate local energy transition.

ABSTRACT. This study investigates the integration of a Phase Change Material (PCM) ceiling with a Variable Refrigerant Volume (VRV) system in a Guangzhou office building, aiming to optimize the peak shaving and valley filling capabilities of the integrated system. Theoretical models, validated by field measurements, were established to conduct dynamic simulations using EnergyPlus software. Baseline analysis revealed a cooling energy peak-to-valley ratio of 2:1 with distinct dual peak periods, highlighting substantial potential for load shifting. Comparative results indicate that a medium-temperature PCM (25~35°C) outperforms other ranges, achieving a 6.19% energy reduction and enhancing indoor thermal stability. Furthermore, an optimized control strategy utilizing one-hour pre-cooling at 23°C under Time-of-Use (TOU) tariffs was proposed. This approach effectively takes the advantage of the latent heat storage of PCM, achieving a peak load transfer rate of 59.1%. Consequently, the strategy reduces both cooling energy consumption and carbon emissions by 16%, decreases electricity costs by 27.4%, while maintaining occupant thermal comfort of indoor environment. These findings demonstrate the viability of PCM-integrated active systems for low-carbon building operations.

ABSTRACT. With the rapid growth of high-density AI data centers, efficient and reliable cooling systems have become essential. This study investigates the thermal feasibility and energy performance of immersion cooling under elevated coolant supply temperatures. CFD simulations were performed to evaluate thermal behavior using various dielectric fluids, and Fluorinert FC-40 was se-lected as a representative coolant due to its superior thermal stability under high-temperature conditions. Based on the validated thermal performance, a system-level energy analysis was conducted for a 30 MW data center across ASHRAE S-class conditions (S30-S50). The results show that increasing the coolant supply temperature enables a transition from chiller-based cooling to free-cooling operation. In particular, cooling energy was reduced by up to 81% when shifting from S30 to S40. Although higher temperature operation increases pumping energy and slightly reduces cooling efficiency when using dry coolers at S50, it significantly reduces water consumption. The findings demonstrate that high-temperature immersion cooling provides an effective pathway toward energy-efficient and sustainable data center operation, contributing to both energy savings and carbon emission reduction.

ABSTRACT. Residential buildings across the Mediterranean are experiencing rapid growth in cooling demand, driven by climate change and increasing pressure on electricity grid. At the same time, time-varying electricity prices and peak-related constraints motivate control strategies that can provide demand flexibility without compromising indoor comfort. Achieving this balance requires careful attention to both temperature and humidity, which are critical determinants of thermal comfort and indoor air quality. This paper develops a humidity-aware economic model predictive control (MPC) approach for a cooling-only direct-expansion (DX) split system. The economic objective is defined using total electrical power consumption, and comfort is handled through temperature bounds together with moisture-related constraints. The supervisory MPC is implemented in a TRNSYS–MATLAB co-simulation framework with equipment behavior represented by performance-map data. An evaluation protocol is introduced to quantify trade-offs between flexibility and comfort using electricity cost, peak electrical demand, temperature and humidity deviations, and control-activity indicators. To isolate the effect of moisture handling, a temperature-only economic MPC formulation is compared with the humidity-aware formulation under identical boundary conditions and comfort requirements. The resulting framework supports reproducible finding of predictive control strategies for residential cooling and can be extended to additional flexibility objectives and indoor air-quality considerations.

ABSTRACT. Energy-efficiency retrofits of existing buildings at the urban-block scale require coordinated trade-offs among energy-saving performance, carbon-reduction benefits, and economic feasibility. This study uses a mixed-use block in Nanjing’s old city as a case study, developing an Urban Building Energy Model (UBEM) to simulate district building energy use and evaluate retrofit impacts. Focusing on passive envelope upgrade strategies suitable for historic urban areas, discrete technical options are defined for roofs, exterior walls, and windows and combined to generate a library of 343 building-level retrofit packages. Using Python-based multithreaded batch simulations, the annual Energy Use Intensity (EUI) and energy-saving potential of each building under different retrofit scenarios are efficiently obtained, while carbon emissions and life-cycle cost (LCC) are calculated over a 30-year service life. At the block level, allowing different retrofit packages for different building use groups, NSGA-II is applied for multi-objective optimization (minimizing total block energy use, total carbon emissions, and total LCC), yielding a Pareto-optimal solution set. Results indicate an overall block-level energy-saving potential of approximately 33.26%–37.70% and a carbon-reduction potential of approximately 93.02%–96.85%. The study demonstrates that the UBEM-driven workflow can efficiently identify retrofit strategies that balance energy efficiency, carbon reduction, and cost in a vast solution space, reveal differences in energy- and carbon-saving potentials across building use types, and provide quantitative support for typology-based retrofit planning and decision-making in mixed-use historic districts.

ABSTRACT. Thermal comfort assessment methods and models have been extensively developed, calibrated and validated based on large datasets, predominantly collected in non-residential environments such as offices, educational buildings and other mechanically conditioned spaces. These models have played a key role in defining design criteria, operational strategies and performance benchmarks for indoor environmental quality. However, transferability to residential buildings remains debated since key assumptions derived from non-residential datasets may not hold under typical residential occupancy and adaptation patterns. This paper provides a critical review of the most widely used thermal comfort assessment models, including steady-state and adaptive approaches, with a focus on their original scope, underlying assumptions and typical fields of application. The analysis highlights key differences between residential and non-residential buildings in terms of occupancy patterns, activity levels, conditioning strategies and the relationship between thermal neutrality and perceived performance. Beyond temperature-based criteria, the review emphasises behavioural, psychological and physiological adaptation mechanisms that shape thermal comfort preferences in residential environments. By comparing these building typologies from the perspective of occupant adaptability and comfort perception, the paper discusses the extent to which existing assessment methods can be transferred across contexts without compromising their validity. Particular attention is given to the identification of methodological limitations and adaptation thresholds that influence comfort evaluation in residential buildings. The findings underline the need for a more nuanced and context-sensitive use of thermal comfort models, especially in the assessment and renovation of existing residential buildings and support a more consistent methodological interpretation of thermal comfort assessment in relation to energy performance and occupant-centred design objectives.

ABSTRACT. Visual fatigue and visual comfort are key indicators of photopic visual system function, influencing visual performance, cognitive efficiency, and physiological responses. Short-wavelength spectral stimulation of short-wavelength-sensitive cones (S-cones) in the retina is considered an important physiological factor affecting visual comfort and fatigue. However, conventional approaches to lighting research typically characterise lighting conditions using Correlated Colour Temperature (CCT) and illuminance, which are insufficient to accurately quantify differences in effective S-cone stimulation under varying spectral power distributions. To address this limitation, this study adopts the CIE α-opic equivalent daylight illuminance (EDI) framework and constructs three artificial lighting conditions with different spectral distributions under identical CCT (6000 K) and desktop illuminance (300 lx), corresponding to high, low, and medium S-cone-opic EDI levels, with peak wavelengths at 447 nm, 539 nm, and a multi-peak spectrum, respectively. Subjective questionnaires, critical flicker fusion frequency (CFF) tests, and heart rate variability (HRV) measurements are integrated to evaluate visual fatigue, visual comfort, and overall mental fatigue. This study contributes to exploring the quantitative relationship between S-cone-specific photic stimulation and visual fatigue and comfort from a spectral physiological perspective, providing a scientific basis for understanding human visual responses under spectral modulation and supporting the development of health-oriented artificial lighting systems and visual comfort optimisation.

ABSTRACT. Indoor environmental quality plays an important role in cognitive performance, yet evidence remains unclear when focus to working memory (WM). Lighting and acoustic conditions are both common indoor exposures, but their effects on WM have not been systematically compared within a single review. This focused review examined whether indoor lighting and acoustic conditions have detectable effects on objective WM performance in healthy adults. Relevant studies were identified through PubMed, Scopus, and Web of Science, and the final review included 14 studies. The available evidence suggests that lighting effects on WM are generally weak and condition dependent. Changes in illuminance and correlated colour temperature within common indoor ranges do not consistently improve WM. By contrast, the available acoustic studies suggest a clearer pattern, with disruptive sounds, especially speech-related and traffic-like noise, being more likely to impair WM. Evidence on combined light-sound conditions remains limited, and current studies do not yet support a stable interaction pattern. Overall, current evidence does not support a unified optimal light-sound condition for WM, and reducing disruptive noise appears to be a more practical priority for indoor settings that rely on WM.

ABSTRACT. The building sector accounts for a substantial share of global energy consumption and associated carbon emissions, highlighting an urgent need for advanced efficiency technologies in existing infrastructures. Solar photovoltaic Vacuum Glazing (SPVG) represents an effective solution by integrating vacuum glazing with photovoltaic technology to achieve superior thermal insulation, clean electricity generation, and glare mitigation. This study investigates a novel SPVG retrofit strategy whereby the SPVG unit is mounted onto existing windows, forming an additional air cavity between the retrofit glazing and the original window. The proposed configuration substantially increases the overall thermal resistance of the fenestration system while reducing retrofit complexity and labor requirements. To quantify the energy-saving potential, an experimental rig was constructed, and a comprehensive numerical model was developed and validated against experimental measurements. The system was further optimized with respect to low-emissivity coating placement, air-gap thickness, and photovoltaic coverage ratio. Experimental results demonstrate that the SPVG retrofit achieved a maximum reduction in conductive heat flux through the entire window of up to 53 W/m2 compared with the original window, corresponding to a relative reduction of 71%. In addition, simulation results show that, in the cooling-dominated climate of Hong Kong, the optimized SPVG configuration reduces cooling energy demand by over 80% relative to non-retrofitted windows, while simultaneously enhancing indoor thermal comfort. Overall, this study demonstrates the effectiveness of the proposed retrofit strategy and provides practical technical guidelines for expanding building-integrated photovoltaic (BIPV) applications, thereby supporting the transition toward carbon-neutral buildings.

ABSTRACT. The rapid growth of urbanization has generated large volumes of Construction and Demolition Waste (CDW), while effective strategies to reintegrate irregular waste materials into new building lifecycles remain limited. The geometric heterogeneity and material variability of CDW prevent conventional standardization, resulting in low-value downcycling and missed opportunities to reduce embodied carbon in the built environment. This paper presents Semantic Aggregate, a closed-loop computational upcycling framework that integrates Vision-Language Models (VLM), generative design, and Mixed Reality (MR) to transform irregular construction waste into standardized architectural modules aligned with circular construction and net-zero carbon objectives. The proposed Scan–Compute–Cast workflow begins with LiDAR-based semantic digitization, in which a VLM generates digital material passports by interpreting the geometry, material type, and condition of waste fragments. A discrete generative packing algorithm then computes mold-specific digital recipes that optimize material arrangement according to functional and aesthetic constraints. Finally, MR-based holographic guidance enables accurate physical assembly by non-specialist labor, reducing cognitive and technical barriers to reuse. The framework was validated through the fabrication of post-material modules assembled into a prototype wall demonstrating a controlled material gradient from dense structural aggregates to lightweight translucent components. The results indicate that digitally guided upcycling can achieve repeatable fabrication, design flexibility, and scalable reuse of heterogeneous CDW. By embedding circular intelligence into the construction workflow, this approach offers a practical pathway to reduce lifecycle environmental impacts and embodied carbon in the transition toward net-zero built environments.

ABSTRACT. The construction sector is seeking effective approaches to reduce energy demand and environmental impacts of the built environment rapidly and significantly in EU by 2050, pushing on deep energy renovation. Research and innovation in this context are increasingly focusing on Off-Site Construction (OSC) solutions due to their potential to reduce costs and construction time, improve material control (reducing construction and demolition waste), and ensure more reliable technical performances with a smaller gap between design and actual results. However, nowadays most of the attention is devoted to the production and construction phases, while more accurate quantification of benefits is needed to assess medium-term impacts of such solutions to effectively return their potential. Since sustainability assessment must consider the full life cycle, analysing the sustainability and circularity potential of existing and emerging OSC solutions is crucial to define best practices and guide the construction sector towards the adoption of more durable circular products. The study explores the circularity potential of OSC solutions for building retrofitting available in the Italian market, with a focus on façade thermal insulation, by defining a set of evaluation criteria about service life retrieved from the state of the art, assessment tools and international standards. These are applied to a selection of relevant solutions from the market to evaluate their performances and thereafter to propose enhancement towards durability, ease of disassembly, ease of replacement and end-of-life management scenarios. Results offer policymakers a perspective on how to effectively support market uptake and foster the adoption of innovative prefabricated solutions.

ABSTRACT. Sustainability assessment in Meetings, Incentives, Conferences and Exhibi-tions (MICE) tourism has traditionally relied on indicators such as carbon footprint, mainly focused on emissions from transport, accommodation and venue operation. However, these approaches only partially capture the physi-cal transformations associated with event-related activity. This paper propos-es a conceptual and methodological framework to analyze MICE tourism from a thermodynamic perspective, using entropy as an indicator of the deg-radation of the useful potential of energy and materials within the host ur-ban system. Building on exergy analysis and life cycle assessment data, the study develops a relative entropy approach that enables comparison between MICE event configurations rather than attempting an absolute thermody-namic quantification. The framework distinguishes between a business-as-usual conference scenario, and an improved scenario structured around sec-toral programmes on energy, matter, and information and legacy. In addition to identifying the most dissipative components of the event system—such as transport, accommodation, food, materials and energy use—the paper intro-duces the concept of negentropy to capture the positive systemic contribu-tions of MICE events, including knowledge exchange, institutional collabo-ration, social legacy and regenerative urban actions. The proposed methodol-ogy is currently being validated through the case of HERITAGE2025 in Va-lencia. The study contributes a more systemic basis for evaluating MICE sustainability and supports the design of circular and regenerative event strategies in urban destinations.

ABSTRACT. As the Meetings, Incentives, Conferences and Exhibitions (MICE) sector continues to grow and shape urban economies, its environmental and social footprint is becoming increasingly relevant to assess. Assessing progress towards low-carbon, high-impact events requires more than reporting single indicators (energy use or emissions). In the Zentropy MICE project, we op-erationalize an urban entropy approach by measuring exchange flows of en-ergy, matter and information generated by conference tourism, linking on-site event operations and off-site tourist activities of attendees with the host city. These flows are integrated into an entropy calculator designed to support urban decision-making. This paper focuses on a critical enabling component: how data collection and integration can be organized under real conditions, where data are distributed across multiple actors and appears in heterogeneous formats. Using the València pilot as a reference, we propose a practical framework based on three layers: (1) an entropy library that trans-lates diverse measurements into a common structure of energy, matter and information flows; (2) a governance and minimum dataset approach that clarifies ownership, access, frequency and quality requirements across the València Conference Centre, local government, destination organizations and attendees; and (3) a traceable processing pipeline that standardizes, validates and harmonizes inputs to produce calculator-ready datasets. We dis-cuss typical bottlenecks (missing values, inconsistent granularity, privacy constraints and timing mismatches) and present mitigation strategies. The main contribution is a transferable, step-by-step method that lowers the barrier for cities to start with “good enough” data, improve over time, and generate comparable results to evaluate business-as-usual versus interventiondriven events.

ABSTRACT. This paper provides a systematic review of LCA research focused on residential energy-efficient retrofitting, focusing on methodological inconsistencies and the trade-off between renovation depth and environmental performance. The results indicate that increasing renovation depth generally reduces operational energy use and emissions but leads to higher upfront embodied carbon due to additional materials and system upgrades. As a result, the relationship between renovation depth and environmental performance is non-linear, with diminishing marginal benefits beyond a certain level of intervention. As energy grids increasingly decarbonize, the marginal benefits of operational energy savings are progressively attenuated, shifting the environmental focus toward the material level.

ABSTRACT. Reducing embodied carbon in the built environment requires structural materials that combine renewable sourcing with reliable long-term performance under realistic service conditions. Although wood is widely recognized as a carbon-storing and sustainable material, its broader application in building systems is often constrained by mechanical limitations, moisture-induced dimensional instability, and uncertainties regarding long-term environmental durability. Expanding the structural role of wood in low-carbon construction therefore depends on improving both its mechanical efficiency and environmental stability. This study examines densified wood as a performance-enhanced material intended for integration into carbon-conscious building systems. The material was assessed in terms of mechanical reliability and resistance to environmentally induced degradation under representative moisture-related exposure conditions relevant to building service environments. The evaluation focused on overall structural performance and environmental adaptability within practical building contexts. The results demonstrate that densification significantly enhances stiffness and load-bearing capacity while reducing moisture-driven dimensional variation compared to conventional wood. The densification process consolidates the internal cellular structure, decreases porosity, and improves structural integrity, contributing to stable behavior under fluctuating environmental conditions. The enhanced structural efficiency and environmental resistance of densified wood indicate its potential contribution to embodied carbon reduction through material optimization, increased durability, and partial substitution of high-emission construction materials. These findings provide performance-based evidence supporting the strategic use of densified wood in sustainable and low-carbon building design and construction practices.

ABSTRACT. This study presents a combined environmental and energetic assessment of three flat-plate photovoltaic-thermal (PVT) collector configurations: a reference collector without latent heat storage (Configuration O), a collector incorporating a paraffin-based phase change material (PCM) layer (Configuration B), and a collector integrating a PCM-metal foam (PCM-MF) composite layer (Configuration C). The environmental performance was evaluated through cradle-to-grave life cycle assessment using global warming potential over 100 years (GWP100) and cumulative energy demand (CED), while the energetic analysis considered thermal, electrical, and global performance under representative operating conditions. The results show that integrating PCM and PCM-MF improves the energetic behaviour of the collector, with the PCM-MF configuration exhibiting the highest thermal and electrical outputs in all representative months. For the climatic conditions of Naples, and assuming the total annual solar radiation of 1900 kWh/m², the annual energy output increased from 474.22 to 569.05 and 845.69 kWh/year, respectively, corresponding to gains of 20% and 79%, respectively. However, these benefits are accompanied by higher life-cycle impacts. The total GWP100 increased from 402.20 kg CO2-eq for the configuration O to 504.15 and 538.70 kg CO2-eq for the B and C configurations, respectively, while CED rose from 5.06 to 6.39 and 6.81 GJ. Overall, despite exhibiting the highest life-cycle environmental impacts, Configuration C achieves the greatest annual thermal and electrical energy gains, which may offset the additional environmental burden associated with the incorporation of PCM and metal foam.

ABSTRACT. This article presents a technical and economic assessment of comprehensive renovation measures for two representative apartment buildings in Slovakia using life-cycle cost (LCC) analysis. The study evaluates energy-efficiency impacts, investment costs, and economic viability in the context of European energy and climate objectives and the need to reduce energy demand in the residential building stock. The methodology combines measured operational energy consumption, calculated energy performance assessment, and dynamic simulation models developed in EnergyPlus. Individual energy-efficiency measures and their combinations were designed as renovation variants and evaluated for both buildings. The results showed that additional thermal insulation of external building envelopes has the most significant impact on reducing primary energy demand, with individual measures achieving reductions in the range of 20–35%. By appropriately combining renovation measures, total energy demand reductions of up to 60–62% can be achieved, which are both technically feasible and economically justified. The cost-optimal level of renovation is close to the energy performance requirements for new or low-energy apartment buildings. However, high initial investment costs, ranging approximately from 170 to 280 €/m², remain a major barrier to the implementation of deep and comprehensive renovations. The article provides a methodological framework and practical recommendations to support decision-making processes related to apartment building renovation, contributing to sustainable development in the building sector.

ABSTRACT. Urban regeneration projects increasingly require quantitative evidence on how design choices affect local microclimate, ventilation, and exposure to traffic-related pollutants. This paper presents a numerical study using ENVI-met to assess airflow patterns and outdoor thermal comfort at the WeGenerate project Bucharest demo-site, located in District 2. A high-resolution 3D model is developed from urban morphology data and supplemented with field measurements to parameterise surface materials, vegetation cover, and representative emission sources. A preliminary simulation (Simulation 0) establishes the baseline performance of the model domain under typical summer conditions. A validation simulation (Simulation 1) cross-checks model outputs against one week of sensor data. Scenario simulations (Simulation 2 / Simulation 3) then evaluate nature-based and layout interventions in terms of changes to wind speed and direction, air temperature, mean radiant temperature, and comfort indices (UTCI, PET, PMV). Results reveal severe thermal stress (UTCI 43-48°C, PET >54-60°C) in wind-stagnation zones (<0.1 m/s) driven by canyon geometry and easterly winds, with interventions achieving substantial comfort improvements through radiative mitigation (Fig. 4). The replicable workflow supports evidence-based urban regeneration across European demo-sites.

ABSTRACT. Abstract Glazed surfaces are critical components in energy-efficient building envelopes, mediating thermal performance through both solar gains and transmission losses. As Romania transitions toward nearly Zero-Energy Building (nZEB) standards and prepares for future Zero-Emission Building (ZEB) objectives, this study investigates the role of façade transparency in shaping heating energy demand in office buildings. Building upon a reference case previously defined, the analysis uses it as a baseline for comparative simulations across all five Romanian climate zones. Applying the Mc001-2022 methodology with a monthly energy balance approach, the study evaluates multiple façade configurations by varying the glazed-to-opaque surface ratio per orientation. Thermal envelope characteristics, internal gains, and climate-specific data are integrated to assess seasonal demand patterns. Rather than reaffirming known correlations, the research contextualizes the interaction between transparent surface design and climate-responsive energy behaviour. Results indicate that optimal glazing configurations differ by climatic zone, influencing a building’s ability to comply with national energy efficiency regulations. This study contributes a climate-sensitive and parametric design framework that supports envelope optimization under current Romanian standards while remaining adaptable to future European policy shifts. Emphasizing early-stage assessment and zone-specific strategies, the findings offer transferable insights into adaptive façade design for low-carbon office buildings operating under diverse climatic conditions.

ABSTRACT. The transition to carbon-neutral and low-energy buildings necessitates a sharp reduction in cooling energy demand, which is particularly acute in hot, humid climates. As a primary contributor to building heat gain, the roof presents a critical intervention point for improving thermal performance. This study provides a comprehensive, climate-responsive evaluation of two leading passive roof cooling technologies: radiative sky cooling roofs and vegetated green roofs. Through detailed EnergyPlus simulation across four distinct climate zones (very hot humid, hot humid, hot dry, warm humid), we quantify their comparative thermal behavior and energy savings. Our findings reveal a distinct performance trade-off: super-cool roofs achieve sub-ambient surface temperatures and superior cooling energy savings (8.2%-11.2% relative to the baseline) in warm climates due to exceptional solar reflectance and thermal emissivity. Green roofs, in contrast, offer more moderate cooling (2.9%-5.4% relative to the baseline) but provide additional benefits including thermal mass buffering, evapotranspiration, and potential heating season advantages. Building on these insights, we determine the rooftop cooling strategies that enables stakeholders to prioritize energy efficiency for maximizing annual building cooling electricity savings for each climate zone. This work delivers an actionable, evidence-based guide for architects, engineers, and policymakers to select and optimize region-specific roof cooling strategies, advancing the development of low-energy buildings.

ABSTRACT. The building sector accounts for a significant share of global energy consumption, with cooling demands contributing substantially to greenhouse gas emissions and climate change. In this context, passive radiative cooling has emerged as a promising strategy to mitigate overheating and reduce cooling energy needs. Among the available solutions, selective coatings for building envelopes have attracted increasing attention due to their ability to combine low solar absorptance with high long-wave infrared emittance, particularly within the 8–13 μm atmospheric window. This paper reviews recent advances in radiative cooling coatings for building envelope applications, synthesizing evidence from both experimental and numerical studies. The review examines their optical and thermal characteristics, reported cooling performance, and potential impact on building energy demand. The literature indicates that optimized coatings can achieve surface temperatures below ambient air temperature, even under direct solar irradiation, and can contribute to cooling energy savings, particularly in hot and temperate climates. However, evidence from full-scale applications under real operating conditions remains limited. From this perspective, the Mediterranean region constitutes a particularly relevant context for assessing the practical applicability of these solutions. Further research is needed to validate predicted energy benefits, evaluate long-term durability, and support their integration into building design under Mediterranean climatic conditions.

ABSTRACT. Glazed office buildings in high-irradiance climates face severe solar control challenges, with cooling energy exceeding 90% of annual site consumption. Electrochromic (EC) windows adapt optical transmittance in real time, yet effectiveness depends entirely on the signal triggering state transitions, a variable that has not been systematically optimized. This study evaluates four candidate signals for EC control in a south-facing Abu Dhabi office: global horizontal illuminance (GHI), outside solar irradiance on the facade (OSI), outdoor air temperature (OAT), and solar altitude angle (SAA). Each signal is characterized using interquartile-range thresholds then optimized with NSGA-III against three simultaneous objectives: total energy, PMV-based thermal discomfort, and useful daylight illuminance (UDI). GHI and SAA deliver the strongest standalone results, cutting total site energy by 44% and thermal discomfort by 70% relative to an uncontrolled clear-glass baseline. A co-optimized signal-fusion controller extends the non-dominated frontier beyond any individual signal, with the best daylight-oriented solution achieving 99.3% UDI. GHI functions as the dominant driver; OAT adds thermal context; SAA provides a geometric correction; OSI is largely suppressed.

ABSTRACT. During the heating season in Portugal, when the outdoor air temperature is significantly lower, the windows in classrooms in Higher Educational Institutions (HEI) Buildings are kept closed during activities. In the absence of HVAC systems, the ventilation rates (air changes per hour) are very low with potential negative consequences on the occupant attentiveness and productivity. This study aims to assess the indoor quality of two classrooms in a HEI building using Internet-of-Things (IoT) sensors that measure CO2 concentration. This will allow to quantify the conditions of the classrooms during and after classes. Furthermore, this study also aims to evaluate and quantify the effectiveness of opening windows during periods between classes (e.g., lunches or at nighttime). The advantage of using a fully integrated wireless and wireline network of IoT sensors, lies in the fact that the measured data is transmitted in real time to the building maintenance system for advanced processing, intelligent analysis, and storage. This approach not only allows it to act promptly but also supports the future development of a digital twin of the building.

ABSTRACT. Ground Source Heat Pumps (GSHPs) are a promising solution for reducing the carbon footprint of residential buildings; however, their performance is highly dependent on the design of the Borehole Heat Exchanger (BHE) field. Within the framework of the GROUNDFLEX project this paper presents a detailed numerical analysis of vertical boreholes serving a multifamily residential building located in the city of Turin, Italy. A high-resolution finite-element model is developed in COMSOL Multiphysics to simulate the heat transfer processes between the circulating fluid, borehole components and the surrounding ground. The model explicitly accounts for ground thermal inertia, axial heat transfer and mutual thermal interference among multiple boreholes, enabling an accurate assessment of both short-term and seasonal effects. Simulations are performed under heating and cooling operating modes, reflecting the real operating conditions of the GSHP system. A parametric study is carried out by varying borehole diameter, inlet fluid velocity and number of boreholes, while maintaining a constant nominal thermal capacity of the system. The influence of borehole configuration on thermal performance and ground temperature evolution is systematically investigated, highlighting the role of the ground as a thermal storage medium. Key energy performance indicators, including inlet-outlet temperature jumps on the borehole, exchanged thermal power, linear heat extraction/injection rates and borehole thermal resistance, are analysed and compared. The results provide practical insights into the optimal design of borehole fields for the GSHP application to a multi-family residential house, supporting the development of energy-efficient and low-carbon building solutions.

ABSTRACT. Older adults spend most of their time indoors, but most heat-health systems still assess risk using outdoor thresholds alone. This study quantifies housing-related heat vulnerability among U.S. older-adult households and uses those findings to inform ClimaSafe, a mobile decision-support prototype. We analyzed 20,587 households with a householder aged 60 or older in the 2023 American Housing Survey, representing 51.4 million occupied U.S. homes. Survey-weighted logistic regression examined associations between three housing deficiency domains and three health-related outcomes. Structural housing problems were most strongly associated with heat discomfort (OR 2.90, 95% CI 2.41–3.49), followed by moisture or mold problems (OR 1.97, 95% CI 1.60–2.43) and pest infestation signs (OR 1.69, 95% CI 1.44–1.99). Moisture or mold (OR 1.43, 95% CI 1.07–1.91) and pest infestation (OR 1.40, 95% CI 1.14–1.71) were associated with household asthma. Among households with asthma, renter status nearly doubled the odds of asthma-related emergency department use (OR 1.94, 95% CI 1.16–3.24). Secondary descriptive analyses showed substantial cooling and outage vulnerability. These included poor passive cooling (29.16%), limited shade (46.60%), recent power outages (26.45%), and lack of generator backup among households with electricity-dependent medical devices (68.58%). These findings are translated into a housing-aware app architecture that combines intake-based risk profiling, real-time environmental monitoring, and urgency-ranked recommendations, applying the Fogg Behavior Model with age-appropriate interface principles.

ABSTRACT. Wood-based interior remodeling is increasingly recognized for its biogenic carbon storage potential; however, concerns remain regarding biogenic volatile organic compound (BVOC) emissions and their implications for indoor air quality (IAQ). This study evaluates the environmental performance of wood-based remodeling through integrated IAQ monitoring and life-cycle global warming potential (GWP) assessment. A full-scale wood mock-up test identified monoterpene hydrocarbons, particularly α-pinene, as the dominant BVOCs, while oxygenated monoterpenes were detected only at trace levels. Field measurements were conducted before remodeling, 24 h after remodeling, and four weeks after remodeling, assessing formaldehyde (HCHO), anthropogenic VOCs (AVOCs), BVOCs, particulate matter (PM), and total airborne bacteria (TAB). Results demonstrated distinct temporal emission patterns. BVOCs increased sharply immediately after remodeling, driven primarily by α-pinene emissions, and their persistence was strongly influenced by ventilation conditions. In well-ventilated conditions, most VOCs, PM, and TAB decreased or stabilized within four weeks. Under limited ventilation, however, BVOCs accumulated substantially, with α-pinene reaching 1713.6 μg/m3 after four weeks. Life-cycle GWP analysis based on the EN 15978 framework revealed that although wood exhibited comparable production-phase emissions to gypsum board and paint, biogenic carbon storage significantly reduced net emissions. Net GWP decreased to 37.7 kgCO2eq in the high wood-application scenario, representing an order-of-magnitude reduction compared with non-wood materials. These findings indicate that wood-based remodeling offers meaningful carbon mitigation benefits while maintaining acceptable IAQ, provided that adequate ventilation and post-construction management strategies are implemented.

ABSTRACT. Geopolitical issues and climate-related problems have reduced the vitality of urban food systems in the UK, intensifying nutritional inequality and food shortages, particularly among low-income residents. Existing research has largely concentrated on specialised technologies to increase yields in large-scale commercial greenhouses, which do not resolve the socially produced inequities. Therefore, this study develops a replicable community greenhouse model in the Midlands city of Nottingham to strengthen local food security and advance food equity. By enabling participation from community groups, the project spreads relevant knowledge through community engagement. Using low-cost, low-carbon materials, the prototype explores practical pathways that can support community cultivation as well as household-scale growing. Within a community-embedded living-lab greenhouse, passive design strategies are integrated to improve airtightness, insulation measures, and ventilation pathways, thereby enhancing enclosure performance. Thermal energy storage using different materials is incorporated to buffer temperature fluctuations and stabilise night-time conditions. In addition, solar renewable energy is used to support greenhouse climate monitoring and operational control, providing a data-driven basis for evaluating interventions and performance outcomes. Results show that the integrated strategy improves ventilation, insulation, and thermal buffering efficiency: under peak summer conditions, the optimised greenhouse reduces peak indoor temperature by approximately 30 °C relative to worst-case scenarios, while in winter the optimised scenarios increase night-time indoor temperature by up to 10 °C. These findings demonstrate a feasible pathway toward low-energy, low-emission operation with year-round growing potential, enhancing the prospects for proactive, low-carbon, climate-adaptive communities.

ABSTRACT. The decarbonization of the built environment—encompassing buildings, urban infrastructure, and local energy systems—represents a central challenge for achieving net-zero objectives. Beyond technological efficiency, transforming the built environment requires governance frameworks capable of integrating urban planning, energy regulation, and social participation. In Latin America, where energy poverty and climate vulnerability remain structural challenges, energy communities are emerging as a strategic mechanism to connect distributed generation, urban resilience, and collective local action. This study presents a critical and conceptual review of academic literature, regulatory frameworks, and institutional reports on energy communities in Latin America, aiming to identify governance gaps that constrain their effective integration within the built environment. The analysis is structured around three key dimensions: (i) the articulation between urban policy and energy policy, (ii) institutional design and multi-level coordination, and (iii) mechanisms of inclusion and distributive justice in vulnerable urban contexts. The findings indicate that, despite regulatory advances and policy narratives aligned with energy transition goals, significant fragmentation persists between urban planning and energy systems, alongside limited local institutional capacity and insufficient integration of equity criteria in implementation processes. These governance gaps reduce the transformative potential of energy communities within the built environment. The paper concludes that advancing a just transition in the Latin American built environment requires stronger coherence between urban and energy governance, promoting integrated frameworks that recognize the built environment as a strategic arena for decarbonization, social inclusion, and territorial resilience.

ABSTRACT. Renewable Energy Communities (RECs) are increasingly framed as key instruments for a just energy transition. Yet evidence on their impact on households’ energy behaviour is limited. This study focuses on the Agra do Amial REC, a deprived neighbourhood in Porto, the second largest city in Portugal, assessing its impact on electricity consumption and expenditures. Using high-frequency (hourly/daily) data and a forecast-based counterfactual approach, the causal effect of REC participation is estimated. Results show an increase of electricity consumption and a net reduction in energy bills, consistent with improved access to essential energy services. Policy-relevant insights can be derived for designing just/inclusive community-based energy models in Portugal.

ABSTRACT. Wind tunnel experiments are widely used in architectural wind engineering to characterize flow fields around buildings and to provide validation data for CFD simulations. However, the same building-mounted photovoltaic system may be tested in different wind tunnels to address distinct experimental objectives, such as aerodynamic performance or dust deposition, even when the geometric scale is nominally identical. Although the scale factor for the two tests may remain the same, the physical size of the PV panels used in each wind tunnel would be different. This study investigates the influence of wind tunnel size on incoming boundary layer characteristics and the resulting flow field around geometrically similar building models with rooftop-mounted PV panels at a 1:3 size ratio. A direct comparison of the nondimensional velocity profiles demonstrates systematic deviations between the two wind tunnels one with a size of 3.1 m×2.4 m×1.9 m (L×W×H) and the other one is in a size of 1.2 m×0.8 m×0.8 m (L×W×H). These deviations are primarily attributed to differences in boundary layer development, as indicated by the measured velocity profiles, though other factors such as free-stream uniformity and tunnel contraction may also contribute. A height-dependent mapping function was derived empirically by fitting the nondimensional velocity profiles measured across the full test-section height in the two wind tunnels, enabling consistent interpretation of flow characteristics across different facilities. The results highlight the importance of considering wind tunnel size when interpreting experimental flow data and when validating CFD models against multiple wind tunnel measurements.

ABSTRACT. Sorting and recycling of construction and demolition waste (CDW) is a pivotal link in mitigating carbon emissions from virgin building material extraction. However, CDW’s intrinsic properties—high humidity, proneness to entanglement and agglomeration—cause insufficient screening efficiency and excessive screen adhesion, leading to resource wastage and incremental carbon costs. To address these issues, an MBD-DEM coupled model for the bar-assembled circular vibrating screen was developed based on multi-body dynamics (MBD) theory and the discrete element method (DEM). This study focuses on the strong coupling between screen efficient and screen motion parameters, while establishing a quantitative method for material-screen impact force and analyzing its time-frequence distribution. Targeting rational adhesion control and local impact minimization. This research provides theoretical and technical support for the screen structural optimization, motion parameter matching and the advancement of resource-efficient CDW sorting technologies.

ABSTRACT. Urban areas account for the largest share of global energy use and GHG emissions, largely driven by the building and transport sectors. Despite urban decarbonization efforts focus on energy use, it is as relevant to consider material stocks of buildings and mobility infrastructure, alongside their embodied energy and emissions. The way that cities are planned and structured impacts both resources dimensions, reinforcing the need to address energy and materials jointly, as interdependent urban components. Still, research remains fragmented, typically analysing energy and materials separately, seldom capturing trade-offs or synergies across buildings and mobility. To address this, the “Spatial urban energy and materials model” (SUE2M) constitutes a spatially-explicit framework enabling to jointly assess energy and material demand across these two sectors. SUE2M builds on machine-learning techniques (ANN), modelling high-resolution urban data at block level. By integrating urban form, socio-economic and behavioural drivers of energy and materials demand, it enables the analysis of cross-sectoral and spatial patterns. It has been applied in two cities, Porto and Berlin, allowing to estimate the relative importance of different drivers, and analysing different urban circularity pathways until 2050. The results show the extent to which different circularity pathways can be pursued in two distinct urban realities. Urban form plays a central role in shaping energy and material demand in both cases. Density emerges among the most important drivers, with other relevant ones being building types, urban diversity and household characteristics. The findings reveal synergies between energy and materials, supporting the need for integrated urban planning strategies.

ABSTRACT. Heatwave (HW) thermal amplification in cities depends on both synoptic forcing and urban building geometry and morphology, yet the relative contribution of urban form and whether it varies with HW intensity is rarely quantified directly. This study isolates geometry's role by comparing Bari, Italy and Athens, Greece, two cities sharing LCZ 2–3 dominance and flat-roof reinforced concrete building stock but differing sharply in HW intensity. Two Random Forest models are trained per city on Landsat 8/9 HW-period LST combined with 2 m air temperature, ERA5-Land meteorology, and OpenStreetMap building morphology on a 100 m grid: a Full model (10 predictors) and a Geometry-only model, while spatially stratified regression is used to analyze the HW thermal anomaly (ΔT). The Full Random Forest models achieved high predictive performance for HW-period LST (R² = 0.949 for Bari and 0.936 for Athens), while Geometry-only models retained substantial explanatory power (R² = 0.486 and 0.439), corresponding to Geometry Contribution Index (GCI) values of 51.2% and 46.9%, respectively. For heatwave thermal amplification (ΔT), the Full models achieved R² values of 0.831 for Bari and 0.766 for Athens, while the Geometry-only models yielded GCI values of 20.7% and 33.0%. Event-matched non-HW baseline analysis revealed greater thermal amplification in Bari (13.93°C) than in Athens (6.24°C), with a stronger Compact–Natural ΔT contrast (3.89°C vs. −0.26°C), although both cities exhibited similar SUHI values (≈15°C). Partial dependence and Spatial Grid OLS analyses show that urban geometry modifies the spatial distribution of HW-period LST, while synoptic forcing controls the overall magnitude of heatwave temperatures, supporting spatially targeted adaptation strategies for Mediterranean cities.

ABSTRACT. Rapid urbanization creates complex atmospheric microclimates where traditional, low-resolution monitoring fails to capture the heterogeneity of personal exposure risks. Furthermore, the correlation between acoustic comfort and chemical air quality is often intuitively assumed but rarely quantified at the neighborhood scale. This study investigates the spatiotemporal divergence between traffic arteries and sheltered residential zones using a high-density network of 20 IoT multi-parameter sensors deployed in a dense district of Bucharest, Romania. Analyzing a representative week characterized by meteorological duality (stability vs. instability), it was identified a critical "Nocturnal Paradox" in urban exposure. Results demonstrate that the built environment functions as a dynamic barrier rather than a static shield. While the residential layout reduces Particulate Matter (PM2.5) exposure by up to 47% during diurnal convective regimes, this shielding capacity collapses to negligible levels (<5%) under nocturnal atmospheric stability. Also, the study reveals a distinct decoupling between noise and oxidative pollutants. While nighttime noise levels dropped systematically by 10–15 dBA in residential zones, NOx concentrations exhibited an inverse accumulation trend, frequently exceeding roadside levels due to the urban canyon effect. These findings challenge the utility of "acoustic quietness" as a reliable proxy for environmental quality, demonstrating that silence often masks a latent chemical exposure risk driven by the stagnation of traffic-generated quasi-gaseous aerosols during sleep hours.

ABSTRACT. Urban overheating and Urban Heat Island (UHI) effects are intensifying heat-related risks in high-rise, high-density subtropical cities such as Hong Kong. This study develops a UAV and digital twin-empowered framework for pedestrian-level urban heat risk monitoring and management. Low-altitude unmanned aerial vehicle (UAV)-based thermal and multispectral observations are synchronized with Internet of Things (IoT)-based ground meteorological sensing to support high-resolution land surface temperature (LST) retrieval and spatio-temporal heat risk analytics. An urban heat digital twin system is developed to integrate multi-source data, generate dynamic heat risk maps, issue real-time alerts, and support UAV patrol decision-making for hotspot verification. In a neighborhood-scale case study in Hong Kong, the proposed pipeline achieved an absolute LST re-trieval deviation within 2 °C against in-situ measurements, while corrected prod-ucts reduced bias relative to raw thermal readings and enabled clearer discrimina-tion of pedestrian-relevant hotspots. Results further indicate that adjacent effect-induced temperature differences are substantial over low-emissivity surfaces but relatively minor over high-emissivity materials, highlighting the need for emissiv-ity- and context-aware correction in heterogeneous urban environments. The de-veloped platform demonstrates practical value for evidence-based planning and operational assessment of urban heat resilience interventions.

ABSTRACT. Climate change poses a significant risk to the built environment, driving shifts in building design, energy use patterns, and climate-related morbidity. To mitigate these impacts, it is crucial to quantify the expected changes in the passive and active climate-related performance of the building stock. This research evaluates future climate resilience of residential buildings by assessing bioclimatic potential—the inherent capacity of a building's design to maintain comfort primarily through climate adaptation. The study employs the BcChart methodology to conduct a detailed bioclimatic potential analysis for representative locations within each EUCRA (European Climate Risk Assessment) region. The evaluation compares a contemporary baseline (2007–2021) against future projections across two IPCC Shared Socioeconomic Pathways (SSP1-2.6 and SSP3-7.0) for two distinct timeframes: mid-century (2036–2065) and late-century (2066–2095). Using hourly time steps and standard residential occupancy schedules, the analysis determines the magnitude of change in bioclimatic potential relative to the current climate. Future resilience is quantified by shifts in passive adaptation potential (e.g., passive heating and cooling) and required mechanical interventions, such as air conditioning and conventional heating. The results highlight how these requirements differ across SSP scenarios at varying levels of global warming. By identifying the projected potential for passive and active adaptation, the findings provide a critical overview of the implications for residential building design. By doing so, this research informs strategic planning for the technical and policy actions needed to strengthen the climate resilience of the European residential building stock.

ABSTRACT. Climate change is increasingly expressed not only as a long-term warming trend but also as enhanced climate variability, posing challenges to the stability and resilience of the built environment. Most existing studies focus on long-term climate impacts on average building energy demand, while the interaction between evolving climate backgrounds and large-scale climate variability remains less examined, particularly from an operational perspective. Based on urban temperature records from 2004 to 2024, several Chinese cities show indications of climate and thermal zoning shifts, suggesting that assumptions of climatic stationarity may no longer hold. In this context, Shenzhen, Wenzhou, and Xi’an were selected to represent contrasting coastal and inland climatic conditions and different sensitivities of the built environment to thermal stress. Building energy simulations were conducted using a unified building prototype for six representative years (2004, 2014, 2015, 2019, 2021, and 2024), covering different climate stages and El Niño–Southern Oscillation (ENSO) phases. Results show that warming progressively shifts load structure toward cooling dominance and increases peak sensitivity, whereas ENSO induces substantial interannual deviations, particularly in heating-dominated and transitional climates. Even without formal zoning change, resilience metrics reveal rising operational stress within existing classifications. These findings highlight that built-environment resilience requires accommodating both sustained warming and episodic climate oscillations beyond climate thermal zoning assumptions.

ABSTRACT. Climate change represents one of the main challenges for European cities, with significant impacts in the densely built-up urban contexts of southern Europe. Among these, the Urban Heat Island (UHI) effect emerges as a critical phenomenon, with significant health, socio-economic and environmental implications. Rome, due to its high population density and average temperature increase of +1.7 °C over the last fifty years, with peaks of up to +2.3 °C, is an emblematic case study, particularly due to the fragmentation of available information and the lack of integrated analyses to support mitigation of the phenomenon. For this reason, in 2023 Rome launched its climate adaptation strategy, requesting the support of DG REFORM to draw up a UHI risk profile and develop mitigation measures for some pilot areas. Starting from the correlation between extreme temperatures and mortality due to summer heat stress, this paper proposes the methodological workflow and some of the results of the scientific contribution provided to the project by the Department of Architecture of Roma Tre University, through the use of predictive microclimate simulation tools which made it possible to test the effectiveness of the strategies by measuring the results. Starting from a territorial analysis and the design of mitigation strategies, a phase of microclimatic modelling and simulation of intervention scenarios was carried out using ENVI-met software. The results of UTCI and PET, compared between pre- and post-intervention, provided guidance to the Municipality of Rome on prioritising project interventions, offering meta-project guidelines that can be applied in similar contexts, supporting planners.

ABSTRACT. In light of the current state of the art, which increasingly highlights emergency scenarios associated with climate change and the growing frequency of extreme events, there is a need to strengthen analytical and control processes, methods, and criteria. Within this framework, research efforts on indicators understood as advanced tools for analyzing and managing complex climate dynamics are particularly critical. This contribution focuses on the application of indicators to complex climate dynamics, directing outcomes toward supporting strategic actions within climate adaptation plans. New families of indicators are conceived as reliable, measurable, and certifiable tools, capable of describing individual phenomena and interpreting the interactions and synergies they generate. The role of testing processes in real and scalable contexts is emphasized as a primary domain for verifying predictive tools to be integrated with cognitive sciences and artificial intelligence to enhance the analysis and prediction of complex climate dynamics. In particular, the study investigates technical systems capable of providing measurable and verifiable responses, supporting the development of innovative equipment to reproduce extreme climatic phenomena within controlled and standardized environments. Such systems enable the acquisition and processing of performance responses and certifiable metrics, suitable for studying dynamics and synergies affecting the environment and urban systems undergoing high-impact transformative processes. Finally, the indicators shall be used to define representative urban configurations by identifying a repertoire of recurring layouts capable of triggering or amplifying climate-related phenomena to be reproduced in a new Testing Laboratory (TCLAB Envelope Testing) according to standardized procedures, allowing objective and comparable performance assessment.