Search Results (344)

Saudi Arabia is a water-stressed nation and meets much of its daily demand through desalination, an energy-intensive process with a significant carbon footprint. As a Muslim-majority country, residents perform ablution before five daily prayers, making this activity a substantial yet under-quantified component of residential water use. This study focuses on household-level ablution water savings across 13 regions for both Saudi and non-Saudi households by replacing standard taps with a flow rate of 5.7 L/min with a proposed Saudi Standards, Metrology and Quality Organization (SASO)-compliant ultra-low-flow tap (1.9 L/min). Moreover, this study evaluates this ultra-low-flow tap as an environmental technology capable of reducing ablution water consumption and found that per capita savings are identical for both demographic segments, but the total household savings differ because Saudi households are larger, supporting sustainable water management. Results show that under the stated assumptions, full national adoption of the proposed tap would reduce monthly ablution water use from 27 million m³ to 9 million m³, conserving 212.14 million m³ annually with 67% efficiency and offsetting 702,198 tonnes of desalination-related carbon emissions. This highlights the effectiveness of deploying a simple water-saving technology in a water-stressed environment. Conservation potential is concentrated in Riyadh, Makkah, and the Eastern Province due to their high household counts. A four-year phased implementation roadmap is proposed, beginning with 25% adoption in year one (53.01 million m³ annual savings), expanding to moderate-impact regions in year two, and reaching 75–100% adoption nationwide by years three and four. The findings demonstrate how simple and commercially available water-efficient technology can contribute to sustainable resource management by simultaneously reducing water demand, energy consumption associated with desalination, and related greenhouse gas emissions. This study supports Saudi Arabia’s Vision 2030 water strategy and can potentially support UN-SDGs 6, 7, and 13 by demonstrating the substantial water, carbon, and economic benefits of a simple, commercially available tap of 400 SAR. In addition, the study develops a regionally prioritized technology deployment framework that can support decision makers in planning large-scale implementation. The analysis assumes that household members perform ablution five times daily for approximately one minute, based on field measurements, and they require validation of projected gains through actual implementation. Full article

Due to an increase in the demand for water and the limited availability of real time monitoring technologies, efficient management of residential water resources poses a unique problem. This study describes the development of an inexpensive Internet of Things (IoT)-based electronic system capable of providing real time monitoring and artificial intelligence (AI)-driven analysis of residential water consumption. The electronic system consists of the use of a YF-DN50 flow sensor connected to an ESP32 microcontroller allowing for continuous data acquisition. The data collected is stored in a cloud-based spreadsheet on Google Colab for processing and analysis, where an unsupervised Long Short-Term Memory (LSTM) Autoencoder model was developed for anomaly detection. The developed model produced a final training loss value of 0.038 and a validation loss value of 0.045, with the threshold for anomaly detection determined to be mean + 3 standard deviations above the reconstruction error. During the observation period, the system detected a total of 7 anomalous events as well as detecting an overall 85.7% of the detected known events and having a 33% reduction in false negative detections compared to a simple fixed threshold baseline. The results of this study demonstrate that the combination of IoT sensors with LSTM Autoencoder analysis of water consumption allows for the monitoring of water consumption patterns and early detection of anomalies, thus providing a means to achieve a reduction in average monthly household water consumption from approximately 21 m³ to 18 m³. Full article

This study presents a technical assessment of solar energy systems for integrated agricultural use and rural electrification. A model village comprising 30 households was considered, and high-resolution hourly load profiles were developed to characterize consumption dynamics, including peak demand and sectoral distribution across residential, agricultural, public, healthcare, and commercial users. A 60 kW photovoltaic (PV) system was designed in conjunction with an independent solar thermal installation for hot water supply. The system configuration was established through component sizing and numerical modeling, incorporating heat transfer mechanisms and operational constraints. Time-dependent simulations performed in MATLAB (R2022b) evaluated PV power output, battery storage cycling, and thermal system performance over a 24-h horizon. A comparative analysis of standalone PV, hybrid PV/T, and decoupled PV–thermal configurations was conducted based on performance and operational criteria. The results indicate that separated electrical and thermal subsystems achieve improved cost-effectiveness, enhanced reliability, and reduced maintenance requirements. The proposed approach demonstrates the technical viability of solar-based energy systems for rural applications, supporting energy autonomy, reduced fossil fuel dependence, and sustainable agricultural development. Full article

Rooftop rainwater harvesting (RWH) offers a practical adaptation option for Mediterranean cities where water scarcity is amplified by seasonal rainfall and climate variability. This study reports early findings from a simplified monthly water balance screening model for a typical residential building, driven by ERA5-Land monthly precipitation for Antalya and İzmir (Türkiye). Scenarios cover roof areas of 250–3000 m² and practical tank capacities of 2–100 m³ under a fixed non-potable demand of 0.20 m³/day. The model tracks monthly storage dynamics and supply demand in order to compute demand coverage and monthly reliability (i.e., fraction of months in which full demand is met). Reliability-based storage thresholds (≥0.80) are derived for four evaluation windows (1996–2010, 2011–2025, 1996–2025, 1950–2025) to explore climate sensitivity. In parallel, a guideline-style sizing which is consistent with the Turkish rainwater harvesting guideline is implemented using a three-day storage rule based on the wettest month potential. To enable a like-for-like comparison, the collection losses are harmonized by setting loss to 0.10 in the simulation and efficiency to 0.90 in the guideline method. The results show stable thresholds for Antalya but stronger period sensitivity in İzmir. They also quantify cases where guideline sizing does not achieve the target reliability under dry season constraints. This approach supports the rapid, climate-aware pre-design of small- to medium-scale urban RWH systems. Full article

This study addresses the technical, environmental, economic, and systemic role of multi-apartment residential buildings as hydrogen consumption nodes within urban energy systems. A representative five-story building comprising 30 apartments and 2400–2800 m² of heated floor area, located in a cold European climate, was modelled with an annual heat demand of approximately 185,000 kWh. Four heating configurations were assessed: a conventional natural gas/biomethane boiler (baseline), a hydrogen boiler, a hydrogen-fuel-cell combined heat and power (CHP) system, and a hybrid heat-pump–hydrogen solution. Dynamic simulations indicate that all hydrogen-based systems can fully satisfy space heating and domestic hot water demand without modifications to the internal hydronic distribution network. The fuel cell CHP achieved an overall efficiency of 93%. It generated approximately 54,000 kWh/year of on-site electricity, while the hybrid configuration reached a seasonal efficiency of 108% and the highest primary energy reduction (46%). Operational CO₂ emissions decreased from 37,800 kg/year (gas baseline) to 1900 kg/year (green hydrogen boiler), 1200 kg/year (fuel cell CHP), and 900 kg/year (hybrid system), corresponding to reductions of up to 98%. Peak-load analysis demonstrated improved operational stability in CHP and hybrid systems, characterised by reduced cycling frequency and enhanced thermal resilience through hydrogen storage integration. Capital expenditure (CAPEX) ranged from 41,000 EUR (gas baseline) to 101,000 EUR (fuel cell CHP), reflecting additional storage, safety, and control requirements. Over a 20-year lifecycle (5% discount rate), the hybrid system achieved the lowest levelized cost of heat (0.076 EUR/kWh), followed by fuel cell CHP (0.081 EUR/kWh), compared to 0.087 EUR/kWh for gas. Payback periods ranged between 9 and 13 years, depending on configuration and hydrogen pricing assumptions. Sensitivity analysis identified a break-even hydrogen price of approximately 0.085 EUR/kWh, while carbon pricing above 100 EUR/t CO₂ significantly improves economic competitiveness. District-scale aggregation modelling suggests that hydrogen-equipped multi-apartment buildings can reduce grid electricity imports by 30–40% through on-site generation and seasonal storage. The findings confirm that multi-apartment buildings offer structural and economic advantages for early hydrogen deployment compared to dispersed housing typologies. By combining high demand density, centralised infrastructure, and compatibility with sector-coupling strategies, such buildings can function as distributed energy hubs within decarbonized urban systems. Full article

The building sector accounts for nearly 30% of global energy use and 28% of CO₂ emissions, with residential buildings in Canada contributing about 17% of national energy demand. In cold regions such as Labrador, approximately 82% of this consumption is associated with space heating and domestic hot water, making heating the dominant residential load, while fossil-fuel furnaces and electric baseboard heaters remain common. These conditions highlight the need for efficient and sustainable heating alternatives for cold-climate residential buildings. This study examines the design and performance of a hybrid solar photovoltaic (PV) and geothermal heat pump (GTHP) system for a typical detached home in L’Anse-au-Loup, Labrador, Newfoundland and Labrador, Canada (51.52° N, 56.84° W), with the goal of improving energy efficiency and reducing dependence on the electrical grid. Heating and cooling loads were developed using the Hourly Analysis Program (HAP 6.1), while system operation and economic performance were assessed through the Hybrid Optimization Model for Electric Renewables (HOMER Pro 3.18.3). The proposed design combines a rooftop PV array, a ground-source heat pump, and second-life lithium-ion batteries repurposed from retired electric vehicles to lower costs and support short-term energy storage. The system is modelled under grid-connected conditions to reflect realistic operation for northern households. Results show that the hybrid system can meet annual electrical and thermal needs while reducing grid consumption by more than half. Annual carbon emissions decrease by roughly 4–5 tonnes, and repurposed batteries offer a cost-effective alternative to new storage. Overall, the study demonstrates that PV–GTHP systems can provide reliable, efficient, and practical energy solutions for cold-climate homes. Full article

The decarbonisation of the building sector represents a key challenge for the European energy transition, particularly in the heating segment, which is still largely dependent on fossil fuels. In this context, data centres (DCs) offer a promising opportunity as local sources of recoverable waste heat. This study investigates the use of data centre waste heat for building heating through a comparative annual energy analysis applied to two building typologies in a Mediterranean climate (Italy): a residential building and a school. Three scenarios are considered: non-integrated scenario S0 (data centre with its own cooling system and buildings with gas-fired boilers), non-integrated scenario S1 (data centre with its own cooling system and buildings with air-to-water heat pumps), and integrated scenario S2 (data centre cooling system coupled with the buildings through waste heat recovery and heat pump technology). A theoretical 300 kW data centre was considered as the waste heat source. The integrated scenario significantly improves system performance. In the residential case, the seasonal COP increases from 2.15 to 4.50, reducing electricity consumption from 289.5 MWh to 128.9 MWh. In the school case, the COP increases from 2.51 to 8.00, with electricity consumption decreasing from 161.3 MWh to 49.1 MWh. These improvements lead to reductions in non-renewable primary energy demand of up to 63% and 79% for the residential and school buildings, respectively, compared to the baseline scenario. The results demonstrate that data centres can act as decentralised thermal sources, supporting the transition towards low-carbon and Nearly Zero-Energy Buildings. Full article

The growing penetration of residential photovoltaic systems increases the need for effective demand-side management strategies that improve on-site electricity utilization without battery storage. This study investigates the impact of different electric water heater control strategies on the energy and economic performance of a residential PV system. A simulation-based analysis was performed in the PV*SOL Premium environment using a 5.4 kWp household PV installation and an electric water heater as a flexible thermal load. Five operating modes with different levels of control granularity, ranging from uncontrolled operation to continuous power modulation, were evaluated under climatic conditions representative of Dunajská Streda, Slovakia. The analyzed indicators included the self-consumption ratio, self-sufficiency ratio, electricity import and export, and total variable electricity costs. Compared to the reference mode, continuous control increased the self-consumption ratio from 38.73% to 66.43% and reduced electricity export from 3340 kWh/year to 1830 kWh/year. Total variable electricity costs decreased by 31.86%, from €725.53 to €494.44 per year. The results confirm a saturation effect, where increasing control complexity provides only marginal additional benefits. Moderately complex multi-level control, therefore, represents an effective and economically attractive solution for residential PV systems without battery storage. Full article

The building sector is a major contributor to global energy consumption and greenhouse gas emissions, and multi-family residential buildings play an important role in urban decarbonization and the transition toward sustainable cities and societies. This study proposes decarbonization-oriented case studies for selecting heating, ventilation, and domestic hot water systems by integrating environmental, economic, and social criteria aligned with the Sustainable Development Goals (SDGs), particularly SDG 7 and SDG 11. This research compares selected conventional and low-carbon building-level heating, ventilation, and domestic hot water systems, including gas boilers and heat pumps integrated with renewable energy and heat recovery. The evaluation is based on a calculation-based energy performance assessment using a quasi-static monthly heat balance approach, economic indicator analysis, and environmental assessment based on primary, final, and useful energy demand and CO₂ emissions. Cooling energy demand was not included in the assessment because the analyzed scenarios were limited to heating, ventilation, and domestic hot water preparation. Furthermore, the social implications are examined, considering energy affordability, long-term operating costs, and the potential to mitigate energy poverty. The results indicate that low-carbon HVAC systems, particularly heat pump systems integrated with renewable energy sources, significantly reduce CO₂ emissions and primary energy consumption compared to conventional solutions. Although they require a higher initial investment, they can achieve lower life cycle costs over the building’s lifetime. The study concludes that holistic, decarbonization-oriented technologies can support cost-effective, socially responsible pathways toward low-carbon, energy-efficient multi-family residential buildings and sustainable urban development. Full article

The environmental performance of residential buildings depends not only on envelope quality but also on the choice of heating, domestic hot water, and ventilation systems. This study presents a comparative assessment of eight technology packages for a reference single-family house located in Warsaw, Poland, using a harmonised framework under Polish EPC calculation assumptions, with identical building parameters, system boundaries, and functional assumptions for all variants. Operational performance was evaluated using Energy Performance Certificate indicators, including useful energy, final energy, non-renewable primary energy, operational CO₂ emissions, and the share of renewable energy sources. In addition, a comparative 50-year scenario of operational CO₂ emissions was developed, and a screening life-cycle carbon assessment of the reference building fabric and major building components was performed to provide a material and construction-related carbon context for the operational comparison. The embodied impacts of package-specific technical systems were excluded from the LCA scope. The results showed that fossil-dominated packages generated the highest primary energy demand and operational emissions, whereas renewable-supported and hybrid configurations substantially improved environmental performance. Under the adopted EPC-based accounting assumptions, the fully renewable packages achieved the lowest operational indicators; however, these variants should be interpreted as upper-bound theoretical scenarios rather than as demonstrated real-life zero-emission solutions. Therefore, they were not used as the main basis for the practical ranking. Among the practically comparable mixed configurations, the most favourable operational results were obtained for renewable-supported heat-pump-based packages. The screening life-cycle assessment indicated that a substantial part of the total environmental burden was associated with the product and construction stages of the reference building. The results confirm that the interpretation of residential technical packages depends strongly on the adopted assessment perspective and that operational indicators should be considered together with at least a screening-level carbon context for the building fabric. According to the calculation results, the EP value ranges from 0 to 90.8 kWh/(m²·year), depending on the technology package. Full article

Conventional clustering techniques for urban water consumption profiling treat each household as an independent entity, thereby disregarding the spatial, socioeconomic, and infrastructural contexts that jointly govern demand behavior. This structural limitation prevents the extraction of contextually coherent consumption profiles—a critical shortcoming for utility managers who must design spatially targeted conservation interventions. To overcome this, we propose Simple GLAC, a novel graph clustering framework that leverages graph neural networks with an adaptive attention mechanism to dynamically model these complex interdependencies. The model’s end-to-end training jointly optimizes a latent representation for cluster cohesion, separation, and spatial homogeneity, where each household’s multi-month consumption record serves as the node feature vector encoding temporal consumption patterns. Evaluated on a large-scale real-world dataset of 4590 residential households across four distinct graph topologies, Simple GLAC consistently achieves superior multi-metric performance over both traditional and graph-based benchmarks, yielding interpretable and operationally actionable consumption profiles aligned with the spatial, administrative, socioeconomic, and infrastructural dimensions of urban water governance in the studied context. This work provides a data-driven tool for utility managers to deploy targeted water conservation strategies, with findings grounded in a Colombian mid-sized city and generalization to broader urban settings identified as a priority direction for future work. Full article

In Brazil, more than 80% of households rely on electricity for water heating, representing approximately 13% of residential electricity consumption and significantly contributing to peak grid demand. As a prominent alternative for supplying household thermal energy and reducing grid stress, this study experimentally evaluates, under tropical climate conditions, the performance of a modular water-based photovoltaic–thermal (PVT) system and compares it with a conventional photovoltaic (PV) system operating simultaneously under identical environmental conditions. The PVT system, based on commercial PV modules coupled to roll-bond heat exchangers, a storage tank, and a shower outlet, was tested under three hydraulic regimes: natural thermosiphon, closed-loop, and Forced circulation. A dedicated ESP32-based data acquisition system, integrated with a cloud platform, continuously monitors electrical, thermal, and meteorological variables. Results show that PVT modules exhibit a small electrical efficiency reduction due to increased cell temperatures, which is largely compensated by the simultaneous thermal generation, yielding overall efficiency gains of 74.04%, 76.53%, and 7.62% over the reference PV system for Normal, Forced, and Closed circulation, respectively. The comparative analysis identifies Forced-circulation scheduling and the matching between thermal generation and consumption as key factors for performance optimization. The findings provide practical guidelines for deploying PVT systems to replace electric showers in tropical regions, reducing residential electricity consumption and mitigating peak-demand stress on the grid. Full article

Urban heat island (UHI) mitigation is essential for improving urban sustainability by reducing heat stress, energy demand, and climate-related health risks. This study evaluates three rooftop measures—highly reflective roofs (HR), green roofs (GR), and rooftop water sprinkling (WR)—in Osaka Prefecture, Japan, using an integrated assessment framework. Temperature changes induced by each measure were simulated using the Weather Research and Forecasting (WRF) model and linked to energy consumption and health impacts through temperature sensitivity coefficients. Health impacts were quantified using disability-adjusted life years (DALYs), and all impacts were monetized for cost–benefit analysis. All measures reduced summer outdoor air temperatures, although their temporal and seasonal effects differed. HR and WR mainly produced daytime cooling, whereas GR provided stronger nighttime cooling. HR and GR increased residential energy consumption due to higher winter heating demand, while WR avoided this penalty through seasonal operation. All measures reduced office and commercial energy consumption and improved health impacts, with GR and WR producing larger benefits than HR. WR achieved the highest benefit–cost ratio, followed by GR and HR. These findings emphasize temporal characteristics, seasonal trade-offs, and spatial targeting in UHI policy. Full article

Household rainwater tanks (HRWTs) have re-emerged globally as a decentralised strategy to address water scarcity, climate variability, and increasing urban water demand. In several jurisdictions, including New South Wales, Australia, rainwater tanks have been chosen to meet the mandatory potable water reduction target in new residential developments for nearly two decades; however, growing evidence indicates persistent underutilisation and variable performance in practice. Despite their recognised benefits in reducing potable water demand, mitigating stormwater runoff, and enhancing urban resilience, the global HRWT research landscape remains fragmented across disciplinary and thematic boundaries. This paper presents a multifaceted review, defined here as an approach that synthesises multiple perspectives on the topic. It integrates systematic mapping of peer-reviewed literature with a critical thematic analysis across four dominant research domains: technological and design innovation, policy and governance frameworks, environmental performance, and social–behavioural dimensions. The findings reveal a strong research focus on technical optimisation, while policy effectiveness, environmental trade-offs, and household-level behavioural factors receive comparatively uneven attention. Regulatory and incentive-based instruments are shown to produce inconsistent outcomes, shaped by local institutional capacity to design, implement, enforce, and sustain programs, as well as by climatic context and household acceptance. Environmental assessments identify both benefits and burdens, including energy use, treatment requirements, and operational complexity. Social and behavioural studies indicate growing acceptance of household rainwater tank (HRWT) systems. However, financial constraints, local conditions, and ongoing maintenance demands continue to influence adoption and performance. A key insight from this review is the limited attention given to households’ lived experiences, particularly how users adopt, adapt, operate, and maintain HRWT systems over time. This gap constrains progress across technical, policy, environmental, and social dimensions and risks cycles of early policy uptake followed by stagnation. The review highlights the need to integrate household perspectives into future research, policy design, and industry practice to improve system performance, user experience, and the long-term contribution of HRWTs to sustainable urban water management. Full article

Accurate forecasting of water demand enables optimized peak-load management, alleviating pressure during high-demand periods and improving the operational efficiency of urban secondary water supply systems—a critical component in the energy-efficient and sustainable operation of buildings. However, existing water demand prediction methods in some regions suffer from low accuracy and excessively long prediction cycles, posing challenges for real-time water scheduling in building-scale systems. To address these challenges, this study develops a hybrid predictive framework that integrates a BP neural network with the Gray Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO) algorithms for enhanced parameter optimization. Using hourly water consumption data from a representative residential district, the proposed model is compared against standalone machine learning models—Extreme Learning Machines (ELM), Support Vector Machines (SVM), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). Model performance is rigorously evaluated using the coefficient of determination, mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Nash–Sutcliffe efficiency coefficient (NSE). The PSO-GWO-BP hybrid model achieves a predictive accuracy of 97.06%, yielding the lowest MAE, MSE, RMSE, and MAPE, as well as the highest R among all models considered, thereby significantly outperforming the benchmark standalone models. Furthermore, the high-precision short-term prediction outputs enable dynamic regulation of secondary water tank refill thresholds, facilitating refined water allocation and enhanced operational management of building water supply systems. These findings demonstrate the considerable application potential of the proposed hybrid model in enhancing both water resource efficiency and energy utilization performance in the daily operation of green buildings, providing reliable technical support for intelligent and low-carbon building water supply management. Full article