Search Results (1,226)

Reasonable carbon allowance allocation for power transmission and transformation projects is critical for regional emission reduction, yet existing methods rarely address spatial heterogeneity or the fairness-efficiency trade-off at the city level. This study proposes a framework integrating entropy weighting with Zero-Sum Gains Data Envelopment Analysis (ZSG-DEA), applied to cities in Liaoning, China, to achieve objective initial distribution and efficiency-driven adjustments under a binding carbon cap. Empirical results reveal that regional quota levels are shaped not by economic scale or historical emissions alone, but by grid hub functions, load intensity, new energy transmission demand, and network density. The integrated approach avoids subjective bias and optimizes allocation efficiency, offering a replicable pathway for carbon quota allocation in similar contexts. Full article

The building envelope is a key lever for reducing energy demand and carbon emissions in the built environment. However, conventional envelope systems remain largely static and are unable to respond effectively to changing climatic conditions. Biomimetics has emerged as a promising approach for the development of climate-adaptive envelope solutions. Nevertheless, research in this field remains fragmented across disciplines, and its evolution and technological maturity have not yet been systematically assessed. This study proposes an integrated analytical framework combining a bibliometric analysis of 2.007 Scopus-indexed documents, based on a VOSviewer keyword co-occurrence network, with a cluster-guided state of the art review, and a Technology Readiness Level (TRL) assessment of selected biomimetic envelope solutions. The TRL assessment is conducted using explicit operational criteria. The analysis identifies three main research clusters: (C1) environmental-performative, focusing on energy efficiency and envelope optimisation; (C2) material-experimental, addressing biomimetic composites and innovative materials; and (C3) technological fabrication, centred on digital fabrication, smart materials, and 4D printing. Temporal trends reveal a shift after 2018 from materials science-oriented studies towards computational design and adaptive manufacturing, providing quantitative evidence of a transition previously described mainly in qualitative terms. The review highlights a strong focus on solar-shading applications, while energy harvesting and passive thermoregulation remain comparatively underexplored. The TRL assessment shows that more than 80% of the analysed solutions are concentrated at TRL 3, indicating an early stage of technological development. The main barriers include limited material durability, non-standardised production costs, and regulatory constraints. The findings suggest that future progress will depend less on the identification of new biological inspirations and more on advancing the technological maturity and industrial scalability of existing concepts. This will require integrated developments in materials, parametric design, life-cycle assessment, and regulatory frameworks. Full article

Residential buildings are central to decarbonisation because existing dwellings combine long service lives, high heating demand and heterogeneous constraints for retrofitting. This study investigates some retrofit strategies for a terraced house in Oxford, UK, to achieve the winter indoor air temperature set-point while reducing energy use, costs and CO₂ emissions. A calibrated dynamic simulation model was developed from on-site inspections, monitored temperatures, occupant schedules and energy-bill data. The analysis compares baseline configuration with scenarios including radiator power upgrading, envelope insulation, increased internal thermal mass and replacement of the condensing boiler with a high-temperature ground-source heat pump (GSHP). The results show that radiator upgrading enables the most critical rooms to reach the 20 °C set-point, while envelope insulation reduces heating energy and costs. Increased thermal mass improves night-time temperature stability, although its effect on annual energy demand is limited. The GSHP provides the largest primary energy reduction, lowering operational primary energy by 66.3% compared to the reference case and by 70.4% when combined with envelope and thermal-mass measures. Operational CO₂ emissions are reduced by 35.0–84.3%. The study highlights the need to evaluate the capacity of heat emitters, building envelope performance, thermal inertia and heat generator efficiency within a dynamic framework. Full article

Building-integrated photovoltaics (BIPVs) can expand the available photovoltaic area on buildings, especially in dense urban contexts with limited roof surfaces. For transparent-envelope applications, such as photovoltaic shading devices (PVSDs) and semi-transparent photovoltaic glazing (STPV), PV-yield assessment is particularly challenging because PV elements also function as part of the building envelope. Their energy yield depends on multiple interacting factors: irradiation, orientation, shading, incidence-angle effects, operating temperature, and, for STPV, glazing thermal behavior. In early-stage building design, however, these effects must be assessed while system characteristics are still evolving, and detailed product or module data are often unavailable. To address this gap, this study develops and evaluates an EnergyPlus-based approach for PV-yield assessments for transparent-envelope BIPV applications. The approach replaces fixed PV efficiency with a time-dependent effective efficiency that accounts for incidence-angle reflection and temperature-related efficiency losses. It is evaluated through a cross-tool comparison with established PV-yield assessment tools. For PVSD, the comparison separates unshaded conditions, louver self-shading, and urban-context shading. For STPV, it includes an analysis of the PV cell-temperature estimation and the link between electricity generation and glazing heat balance. Results show that PVSD yield differences are mainly governed by shading representation, while STPV results are more sensitive to cell-temperature assessment than to thermal coupling effects. Overall, the approach provides a consistent basis for comparing PVSD and STPV yield under early-stage input constraints, while including selected AOI- and temperature-related efficiency effects. Full article

High renewable penetration, distributed energy resources, and fast-varying electric loads are shifting smart-grid planning from energy-balance simulation toward quality-aware operational assessment. Full-unit benchmark models (FULL) preserve unit commitment, ramping memory, and reserve feasibility but are expensive for repeated annual studies, whereas conventional equivalent aggregation (EQ) can overstate the realizable flexibility of heterogeneous units. This paper proposes quality-aware flexibility-envelope aggregation (QFEA), which separates units by inherited boundary state, ranks them by renewable-following flexibility, constructs conservative cluster envelopes, and couples reduced optimization with feasible disaggregation and state write-back. The model coordinates renewable curtailment, reserve sufficiency, tie-line ramping, and a normalized quality-stress proxy without claiming to replace detailed power-flow, harmonic, or electromagnetic studies. In the nominal single-region case, QFEA reduces the number of commitment objects by 46.2% and computation time by 63.7%, while limiting total-cost deviation to 1.1% and renewable-curtailment deviation to 0.2 percentage points. In 20 matched 24-h stress scenarios, its mean quality-stress index is 2.56%, compared with 2.58% for FULL and 6.57% for EQ. A separate 13–104-unit simplified scaling test keeps inverse-mapping closure error below 5.2 × 10⁻⁹ MWh and disaggregation below 1.3% of measured end-to-end time. The results identify QFEA as a traceable intermediate model for renewable-integration screening when annual computational efficiency and implementable unit trajectories are both required. Full article

Three-dimensional concrete printing (3DCP) enables the fabrication of wall sections with internal cavities that are impractical to form with conventional methods. Although individual studies demonstrate that cavity geometry influences thermal resistance, the magnitude of this effect has not been quantified on a common basis across the literature. This paper introduces the Thermal Effectiveness Index (TEI), defined as the ratio of the theoretical U-value of a solid concrete wall (calculated using the material’s actual thermal conductivity) to the reported U-value, in order to isolate the purely geometric contribution to thermal performance. A structured extraction from 24 Scopus-indexed articles yielded an analysis dataset of 255 variants from 23 articles (after the exclusion of one study whose composite mix made the geometric effect inseparable from material substitution), spanning 17 typology categories. Results show that standard rectangular air cavities perform worse than solid printed counterparts of the same material (median TEI $=0.56$ versus $1.00$ for solid walls) due to internal convection and thermal bridging, whereas sinusoidal infills with post-printed insulation reach a median TEI of 8.9 (18 variants from a single study, so the magnitude requires independent replication). These patterns are descriptive; an article-level sensitivity check indicates that the number of independent studies per wall-type group is not yet sufficient for confirmatory statistical inference. A compliance analysis against five building energy codes showed that only 22% of variants meet the $0.30$ $\mathrm{W}$/($\mathrm{m}$² $\mathrm{K}$) threshold, in line with the component-based U-value criteria specified in the Passive House Institute’s EnerPHit Standard for building retrofits and warm-climate classifications, as opposed to the more stringent $\le 0.15 \mathrm{W}/({\mathrm{m}}^2 \mathrm{K})$ requirement applicable to new construction in temperate climates. Full article

Increasingly stringent regulations regarding climate policy and the sustainable development paradigm determine the transformation of contemporary multi-family housing typology, manifested by a growing share of single-aspect micro-apartments (units with exterior exposure on only one facade). This article identifies the phenomenon of the energy-efficiency paradox, wherein highly insulated buildings successfully trap winter heat but inadvertently escalate summer cooling demands. Consequently, the primary operational challenge becomes limiting excessive solar heat gains in summer, which directly translates into high cooling energy demand, rather than solely mitigating heat losses in winter. Sustainable construction requires moving beyond the narrowly defined reduction of envelope thermal transmittance towards holistic adaptation to climate change and ensuring adequate indoor environmental quality. The methodology is based on a coupled energy-economic analysis, evaluating thermal balances and their direct financial implications for end-users. The variant analysis of solar heat gains conducted for a reference 30 m² dwelling in Warsaw proves that architectural optimization should not be determined solely by short-term investment profit maximization. Effective engineering optimization in construction requires the implementation of a full building life cycle perspective. Unfavorable glazing orientation and the lack of cross-ventilation necessitate the use of energy-intensive air-conditioning systems, which directly increases the building’s carbon footprint and generates hidden operating costs (differences reaching over 145 PLN annually for heating and approximately 70 PLN for cooling). The findings highlight the necessity for a critical reevaluation of design priorities for compact apartments, integrating social justice (by reducing information asymmetry in the real estate market, where buyers are often unaware of these future cooling burdens) with long-term economic rationality and the resilience of the built environment to extreme weather events. Full article

Space cooling is one of the fastest-growing end uses in the building sector, and reflective (“cool”) coatings have emerged as a low-cost passive strategy to limit solar heat gain through the envelope. This study evaluates the summer thermal behaviour of three building-envelope materials commonly used in flat roofing—self-protected asphalt sheet, steel sheet, and ceramic tile—under outdoor conditions in Valencia, Spain. Sealed cubic prototypes were monitored to compare uncoated reference specimens with specimens coated with a conventional high-performance white acrylic paint produced by SOETAM and with an advanced reflective coating based on a laminar TiO₂ nanostructure produced by Q+TERMIK. External surface temperatures were assessed by infrared thermography and internal air temperatures by autonomous data loggers. External white coatings significantly reduced surface temperatures across all substrates, with the effect most pronounced in low-thermal-inertia materials: the advanced reflective coating achieved peak surface-temperature reductions of 21.0 °C (33.2%) for asphalt and 17.4 °C (28.8%) for steel, outperforming the high-performance coating, with corresponding internal reductions of up to 9.7 °C (22.0%) and 8.1 °C (18.6%). The results indicate that the advanced reflective coating produced greater thermal mitigation than the conventional coating under the tested outdoor conditions, despite both coatings being applied with similar thicknesses. The advanced reflective coating generally produced the greatest thermal mitigation, particularly for low-thermal-inertia substrates, while the ceramic tile exhibited a different internal thermal response, highlighting the influence of substrate properties on coating performance. Full article

Spent water-based drilling fluids generated during technological-well drilling for uranium production are high-solid, chemically heterogeneous suspensions whose treatment is constrained by water scarcity, waste-handling requirements, reagent demand and electrical-energy consumption. This study evaluated a recirculating flow-through disperser that converts pressure-driven flow into controlled nominal velocity gradients and localized contact zones. The laboratory-pilot dataset comprised five high-solid water-based spent-fluid samples, 120 hydrodynamic treatment runs, 216 particle-size-bin observations corresponding to 12 complete distributions, nine mechanical-mixing baseline tests and ten repeated-cycle runs. The investigated range covered nominal Camp–Stein-equivalent velocity gradients of 500–1500 s⁻¹, treatment times of 60–180 s and flocculant dosages of 0–100 g/t dry solids. A 50 L batch was recirculated through a disperser with a cylindrical geometric envelope of approximately 4.75 L. The maximum separation efficiency was 94.20%. The recommended compromise condition (G = 1300 s⁻¹, τ = 150 s and 50 g/t dry solids) achieved 92.15 ± 1.81% separation efficiency, residual aqueous-phase TSS of 125.2 ± 30.0 mg/L, water recovery of 83.84 ± 0.28%, sludge-volume reduction of 59.02 ± 2.11% and wall-plug specific energy consumption of 0.1227 ± 0.0062 kWh/m³. A separate ten-cycle series yielded 0.1245 ± 0.0065 kWh/m³, consistent with the triplicate compromise-mode result. Two-factor response-surface models reproduced the measured G–τ trends and provided prediction intervals for operating-window screening within the investigated fluid class. The findings support coupled energy–separation optimization, rather than selection of the maximum nominal mixing intensity. Full article

Decarbonizing industrial heating in cold climates remains challenging due to high thermal demand and strong seasonal variability. While the existing literature predominantly relies on steady-state or isolated component analyses, this study introduces a novel, multi-scale dynamic modeling framework. This framework evaluates the annual transient performance of an integrated renewable architecture. The proposed system couples a building-envelope Transpired Solar Collector (TSC) with a series-connected Photovoltaic Thermal/Solar Thermal (PVT-ST) array. Computational Fluid Dynamics (CFD) is employed to resolve the localized convective heat transfer within the TSC. Subsequently, a data-driven clustering methodology scales these transient results into a comprehensive annual system-level simulation featuring sensible Thermal Energy Storage (TES). The results demonstrate robust performance under Canadian winter conditions. The TSC maintains stable thermal efficiencies between 50% and 60%, peaking at over 64%. Annually, the integrated dual-source system delivers 229.7 MWh of useful thermal energy to offset primary fossil fuel consumption. Furthermore, the analysis identifies 128.76 MWh of seasonal surplus capacity. This underscores the critical necessity of dynamic TES integration. Ultimately, this framework establishes a highly defensible, predictive methodology for designing and implementing synergistic solar thermal networks for industrial decarbonization. Full article

Airtightness is a critical determinant of energy efficiency and hygrothermal performance in ultra-low-energy buildings, yet empirical data regarding lightweight timber construction under local practices in China’s cold climates remain limited. To bridge this gap, this study investigated 18 lightweight timber buildings in cold regions through comprehensive field measurements, aiming to quantify airtightness levels, identify leakage pathways, and develop a rapid prediction model. Blower door tests revealed that the air change rate at 50 Pa ranged from 3.43–7.89 h⁻¹ (mean: 4.83 h⁻¹), with an average air leakage rate per unit envelope area of 6.102 m³/(m²·h). Leakage detection identified openable (20.0%) and fixed (18.4%) fenestration frames, alongside service penetrations (9.9%), as the primary leakage pathways, while unaccounted airflow was traced to diffuse infiltration at structural junctions. Furthermore, Spearman correlation analysis showed significant associations between leakage rates and geometric determinants like building volume and envelope area, which enabled the development of a highly accurate rapid prediction model via backward elimination regression (R² = 0.932). These findings establish a vital empirical reference for designing and simulating lightweight timber buildings while providing a practical optimization tool for enhancing energy efficiency in cold climates. Full article

This study examines the technical and operational efficiency of publicly listed energy companies operating in Europe, the United States, and Canada during the 2017–2024 energy transition period. The sample includes both traditional electricity utilities and renewable energy producers. Technical efficiency was estimated using output-oriented Data Envelopment Analysis (DEA), specifically the Charnes–Cooper–Rhodes (CCR) and Banker–Charnes–Cooper (BCC) models. Panel-data models were subsequently applied to identify the financial, organisational, regional, and environmental, social, and governance (ESG) factors associated with firm-level efficiency. The results indicate a moderate average level of technical efficiency, with a substantial share of inefficiency attributable to an inappropriate operating scale. Contrary to the initial hypothesis, renewable energy companies were, on average, less technically efficient than traditional utilities, despite achieving higher ESG and environmental scores. European companies exhibited higher efficiency than firms located in the United States and Canada, suggesting that long-term exposure to climate-policy and regulatory pressures may encourage more effective resource use. The panel-model results did not provide robust evidence that ESG performance directly improves technical efficiency. By contrast, profitability, leverage, and firm size were significantly associated with efficiency outcomes. These findings show that the energy transition depends on more than the expansion of renewable energy capacity. Effective resource allocation, financial resilience, organisational adjustment, and an appropriate operating scale are equally important. The study provides relevant implications for corporate managers, investors, and policymakers involved in energy-sector transformation. Full article

Rigid polyurethane foams are used in impact-attenuation systems due to their tunable cellular structure and energy dissipation capacity. However, expanded polystyrene (EPS), commonly used for impact protection, presents limitations related to impact attenuation performance and limited design flexibility. This study evaluates the impact performance of rigid polyurethane foams modified with diethanolamine and assesses formulation efficiency using Data Envelopment Analysis (DEA). Rigid PU foam formulations containing 0–3 wt% DEOA were synthesized and characterized by impact testing, apparent density measurements, Scanning Electron Microscopy, Fourier Transform Infrared Spectroscopy, and Thermogravimetric Analysis/Derivative Thermogravimetry. DEA was applied to correlate diethanolamine content with impact absorption efficiency. Excessive crosslinking and reduced energy dissipation were observed above 2 wt%, while concentrations below 0.5 wt% resulted in poorly structured foams. The formulation containing 1 wt% DEOA was identified as the most efficient among the investigated formulations, exhibiting the best overall performance, reducing transmitted peak acceleration by 13.8% compared with neat PU foam, while exhibiting an approximately 48% increase in apparent density, more complete consumption of NCO groups, a more uniform cellular structure, and only modest changes in thermal degradation behavior. These findings indicate that the improved impact performance is associated with the combined effects of increased apparent density, modified cellular morphology, and changes in the polyurethane network promoted by DEOA, underscore the promise of diethanolamine-modified rigid polyurethane (PU) foams for protective applications. Full article

Water pumping stations are critical components of water transmission systems, particularly in the Gulf region, where potable water supply is heavily dependent on energy-intensive desalination processes. Despite their importance, pumping station efficiency is often assessed using single-dimensional indicators that fail to capture operational complexity, scale effects, and environmental impacts. This study develops a Data Envelopment Analysis (DEA) framework to evaluate the performance of 16 water pumping stations in Dubai, each treated as a decision-making unit (DMU), by incorporating both operational and sustainability dimensions. A multi-model approach was applied, integrating input-oriented Charnes, Cooper, and Rhodes (CCR) and Banker, Charnes, and Cooper (BCC) models with Slack-Based Measure (SBM) models that treat energy consumption as an undesirable output. The results reveal substantial variation in efficiency, with average scores of 0.73 under CCR, 0.95 under BCC, 0.62 under SBM Constant Returns to Scale (CRS), and 0.86 under SBM Variable Returns to Scale (VRS). The gap between CCR and BCC results indicates that inefficiencies are primarily driven by scale rather than managerial performance, while the lower SBM scores highlight the significant impact of energy consumption on overall efficiency. Peer analysis confirms the robustness of the findings, identifying Decision-Making Unit (DMU) 16 as the primary benchmark, appearing 37 times across the models. Slack analysis further reveals critical inefficiencies, particularly in DMU 03 and DMU 06. Full article

Electric vehicle (EV) charging has a large, spatially clustered, schedulable load whose vehicle-to-grid flexibility can be sold back to the power system. That flexibility has grid value only when the committed quantity can be reliably delivered under uncertainty. Open forecasting benchmarks operators rely on report-only point predictions. The dispatch models that turn forecasts into firm commitments assume a constant round-trip efficiency, so the committed flexibility is systematically over-scheduled. This study contributes two complementary modules, validated separately on public data. The first is a calibrated probabilistic charging forecaster that provides, to our knowledge, the first prediction intervals with reported empirical coverage on the UrbanEV benchmark. It is a gradient-boosted quantile-regression model that combines each zone’s own-history lags with adjacency-weighted neighbor-mean features and exogenous price and calendar inputs. It is calibrated by conformalized quantile regression and scored over thirty zones across a 120-day hourly window. The second is a deliverable-flexibility envelope whose returnable-energy bounds are set by measured, state-of-charge- and rate-dependent vehicle-to-grid (V2G) discharge efficiency rather than a constant round-trip number. These bounds are fit to the measured discharge traces of three V2G-capable vehicles in the Esser bidirectional-charging dataset. Chosen as a lightweight, reproducible baseline, the forecaster keeps its prediction intervals within a five-percentage-point coverage tolerance at both the 80% and 90% nominal levels. Measured coverage is 0.823 and 0.911. It also improves on the continuous ranked probability score of its conformalized-point counterpart at matched point accuracy. This calibration holds across the hyperparameter neighborhood and under data deficiency. On the delivery side, a leave-one-vehicle oracle shows the efficiency-aware envelope short-delivers less than the constant-average-efficiency aggregator on held-out vehicles. Its residual shortfall is 1.21% against the aggregator’s 2.03% at the conservative operating point. The margin widens as commitments grow more aggressive and discharges reach the lowest states of charge. Each of these two measured properties, calibrated demand-side uncertainty and state-dependent discharge physics, imposes a material, separately validated constraint on how much contracted EV flexibility can be delivered, a constraint the point-forecasting frontier leaves unaddressed. Full article