Search Results (4,074)

Harvesting remains one of the main bottlenecks in microalgae-based technologies. Although microalgae hold great promise for industrial biotechnology, their growth in dilute suspensions makes biomass recovery challenging. Conventional harvesting methods are often energy-intensive and costly, limiting large-scale implementation. This study applies a life cycle assessment (LCA) to evaluate the environmental performance of a laboratory-scale magnetic harvesting process of Chlorella vulgaris (C. vulgaris) using Fe₃O₄ microparticles in combination with polyaluminum chloride (PAC) and polyacrylamide (PAM), followed by magnetic oscillation for particle detachment and subsequent reuse. Electricity consumption was identified as the dominant environmental hotspot across most impact categories, with the detachment step accounting for nearly two-thirds of the total energy demand, a step often overlooked in previous LCA studies. The global warming potential (GWP) is consistent with typical laboratory-scale assessments and is mainly driven by energy inefficiencies associated with small processing volumes. The values obtained and the scale-up literature indicate that further optimization and future industrial-scale production will decrease these values into a realistic and competitive range. Sensitivity analysis showed that replacing grid electricity with photovoltaic power significantly reduces environmental impacts. The use of NaOH as a reagent also contributed substantially to environmental impacts. Reusing magnetic particles (4 cycles) reduced material resource depletion by up to fourfold, which is a very relevant result bearing in mind the principles of sustainability and circularity. Full article

The construction sector is undergoing a rapid transition toward more resilient, sustainable, and digitally connected systems, creating increasing demand for materials capable of providing functions beyond conventional structural performance. In this context, smart materials have emerged as promising solutions due to their ability to respond to mechanical, thermal, chemical, or electromagnetic stimuli through adaptive behaviors such as self-healing, structural sensing, energy regulation, vibration control, and reversible deformation. Despite growing scientific interest, available knowledge remains fragmented across specific material families and isolated application domains. Therefore, this study presents a PRISMA-based systematic review of smart materials in construction using peer-reviewed journal literature indexed in Scopus during the 2021–2026 period. The review examines the principal smart material families currently applied in construction, including self-healing concretes, self-sensing cementitious systems, Shape Memory Alloys (SMA), piezoelectric materials, phase change materials, adaptive coatings, conductive nanocomposites, and multifunctional geopolymers. Their engineering functions, structural and architectural applications, reported performance characteristics, sustainability contributions, digital integration potential, and implementation barriers are comparatively discussed and qualitatively synthesized based on the reviewed literature. The findings indicate that smart materials can improve durability, structural health monitoring, seismic resilience, thermal efficiency, lifecycle performance, and carbon reduction when properly integrated into buildings and infrastructure. However, large-scale adoption remains constrained by high initial costs, manufacturing scalability, regulatory uncertainty, long-term durability validation, and limited market confidence. The review further shows that the greatest future potential lies in combining material intelligence with IoT platforms, artificial intelligence, BIM environments, and digital twins. Overall, smart materials are positioned as strategic enablers of next-generation low-carbon, adaptive, and intelligent construction systems. Full article

As tunnel engineering continues to advance toward deeper, longer, and more complex projects, the risks encountered during the construction phase have evolved into a combination of various disaster types and the accumulation of multiple contributing factors. Traditional empirical and semi-empirical risk management methods are increasingly revealing shortcomings in terms of timeliness, accuracy, and the ability to process multi-source data. In recent years, driven by advancements in computing power and sensor technology, artificial intelligence algorithms (AI algorithms) such as machine learning and deep learning have been rapidly adopted in tunnel construction risk management. This paper retrieved relevant literature from the Web of Science database covering the period from 2010 to 2025. After rigorous screening, 96 highly relevant papers were selected for bibliometric analysis. This paper systematically reviews research progress from two perspectives: algorithmic models and engineering applications. The review indicates that, in terms of algorithmic models, traditional machine learning, convolutional neural network, recurrent neural network, generative adversarial network, Transformer, and graph neural network constitute a multi-level technical framework encompassing feature representation, risk perception, and intelligent decision-making. In terms of applications, AI algorithms have been widely integrated into typical scenarios such as geological hazard identification and prediction, surrounding rock stability and deformation prediction, rock burst assessment and early warning, lining defect detection and structural safety assessment, construction-induced ground settlement prediction, and tunnel gas and fire hazard prediction, significantly enhancing risk identification and early warning capabilities. However, several challenges remain, including the scarcity of high-quality datasets, the prevalence of noisy, incomplete, and heterogeneous monitoring data, insufficient coupling between model interpretability and engineering mechanisms, limited cross-project transferability, and the lack of integrated management systems for multi-hazard lifecycle control. Based on this, this paper proposes future research directions in areas such as data infrastructure development, integration of mechanism constraints, and multi-hazard collaborative modeling, aiming to provide guidance for the further development of intelligent risk management in tunnel construction. Full article

Waste-to-energy (WtE) systems are frequently proposed as complementary waste-management strategies; however, their climate performance depends on the interaction between thermodynamic efficiency, material circularity, and electricity-system characteristics. Existing life-cycle assessments generally provide static comparisons between landfill and WtE but rarely identify the operating conditions under which WtE remains environmentally competitive. To address this gap, a parametric life cycle–energy framework was developed by integrating attributional LCA with an analytical energy model capable of evaluating critical efficiency thresholds under varying recovery rates and electricity-grid conditions. Four representative thermoplastics (PET, HDPE, PP, and LDPE) were evaluated using ReCiPe 2016 Midpoint (H) in SimaPro under Mexican electricity conditions ($E{F}_{\mathrm{grid}}=0.444$ kg CO₂eq/kWh). Results indicate that total life-cycle climate impacts are dominated by upstream polymer production, whereas end-of-life management contributes only marginally to overall GWP. Critical-efficiency analysis revealed strong sensitivity to both recovery rate and electricity-grid carbon intensity. For PET, the minimum efficiency required for WtE to outperform landfill increased from 13.1% to 73.5% across the evaluated scenarios, whereas HDPE remained competitive at efficiencies below 1.3%. Monte Carlo simulations (10,000 realizations) further demonstrated that avoided emissions decline systematically with increasing recovery rates, with LDPE exhibiting the highest mean avoided emissions (1735 kg CO₂eq) and PET the lowest (811 kg CO₂eq). These results demonstrate that WtE climate performance is governed primarily by residual waste availability and electricity-system evolution rather than thermodynamic efficiency alone. Consequently, WtE should be interpreted as a transitional residual-waste management strategy whose long-term climate relevance decreases as material circularity and electricity-grid decarbonization advance. Full article

Energy storage systems (ESSs) installed alongside traditional photovoltaic (PV) power plants are primarily used to track planned output, which often results in low utilization rates and extended payback periods. Moreover, existing research inadequately addresses actual grid frequency fluctuation characteristics and lacks multi-timescale optimization frameworks. To address these issues, this paper proposes a day-ahead and intraday multi-market coordinated rolling optimization strategy that integrates energy market trading with Automatic Generation Control (AGC) frequency regulation services through a zone-based frequency regulation control strategy. The strategy first defines distinct regulation zones based on regional control deviations, enabling a dynamic power allocation approach for the energy storage system. Recognizing that conventional constant power control can lead to battery overcharging, over-discharging, and reduced cycle life, the strategy introduces state of charge (SOC)-based variable power charging and discharging constraint coefficients. These constraints ensure the battery operates safely within its optimal range. Furthermore, an electrochemical energy storage life decay model is developed to quantify battery degradation. To accommodate the uncertainty in PV output, Latin hypercube sampling is employed. A day-ahead dispatch model is established to maximize the system’s total daily operating revenue, and rolling optimization is applied during the intraday phase to correct deviations from the day-ahead forecast. Finally, simulation studies using actual data from a PV power plant demonstrate that the proposed strategy achieves a total daily revenue of 107,477 ¥, representing a 24.6% improvement over energy market-only participation; battery aging costs are reduced by 11.1% compared to the scenario without zone-based frequency regulation control. Results indicate that the proposed strategy effectively balances battery life degradation against market revenue, significantly improving the overall operational efficiency and economic viability of PV-storage hybrid systems. Full article

Steel bridge deck pavements in coastal hot–humid regions are often exposed to the combined effects of moisture, salt, and temperature, which can accelerate material deterioration and shorten service life. To clarify the durability behavior of typical paving materials under such conditions, a comparative study was conducted on three asphalt mixtures used for steel bridge deck pavements: epoxy asphalt mixture (EA-10), dense-graded asphalt mixture (AC-13), and stone mastic asphalt mixture (SMA-10). The mixtures were subjected to hygrothermal salt-water cycling using a mixed chloride-sulfate solution, and their durability was evaluated through air void content, indirect tensile strength, and four-point bending fatigue tests. The results showed varying degrees of deterioration. The air void content of AC-13 increased by about 41.4% after 28 d at 60 °C, suggesting greater susceptibility to internal void damage under severe conditioning. The indirect tensile strength also decreased with wet–dry cycling; at 60 °C and 28 d, the strength retention of EA-10 remained 76.9%, higher than those of AC-13 and SMA-10. After conditioning at 60 °C, the fitted slope of fatigue life for SMA-10 reached −0.0052, compared with −0.0044 for AC-13 and 0.0027 for EA-10, indicating that SMA-10 was the most sensitive to hygrothermal salt attack, whereas EA-10 was the least affected. Overall, the resistance to hygrothermal salt-water damage followed the order EA-10 > AC-13 > SMA-10. The findings help clarify the durability behavior of steel bridge deck paving materials in coastal environments and provide support for durability-oriented material selection. Full article

This study presents a numerical investigation of biogas–natural gas co-firing for greenhouse heating, integrating lumped-parameter energy balance, multi-objective optimization, and life cycle assessment (LCA) for a Syrian coast case study (48 dairy cows, 100 m² greenhouse). Five blends (0–100% biogas) were evaluated using a zero-dimensional model implemented in MATLAB R2024a (The MathWorks, Inc., Natick, MA, USA) and verified with Python (version 3.11, Python Software Foundation, Beaverton, OR, USA). The 70% biogas–30% natural gas blend exhibited the most favorable trade-off among conditionally feasible scenarios (requiring external biogas sourcing) with a model-predicted system thermal efficiency of 84.5% (LHV basis) and a model-estimated thermal NOx reduction of 75–85%, which represents a mathematical extrapolation beyond the experimentally validated range of 0–50% biogas and excludes prompt NOx (5–20% of total) and should be interpreted as an indicative trend requiring experimental confirmation. For self-sufficient operation using only on-site biogas production (24 m³ day⁻¹), the maximum achievable blend is 32% biogas, offering a 13.8% cost reduction and a 13.5% GWP reduction. Pure biogas achieves a 41.5% GWP reduction and 48.5% lower daily operating costs under the assumption of expanded on-site production capacity but requires 3.3 times the current production volume. Multi-objective optimization reveals stakeholder-specific optima ranging from 50% to 91% biogas, with a robust compromise region of 65–75%. All predictions for NOx emissions above 50% biogas are mathematical extrapolations requiring experimental validation. For farms without access to external biogas markets, the 32% blend (self-sufficient optimum) is the currently implementable solution, offering a 13.8% cost reduction. For farms with access to regional biogas markets, the 70% blend represents the conditional techno-economic optimum, achieving a 15.3% cost reduction but requiring 29.12 m³ day⁻¹ of external biogas procurement. Full article

Habitat alteration and biological invasions are two main drivers of biodiversity loss at the global scale. Eutrophication and invasive fish greatly disturb freshwater native communities. This is of particular conservation concern in the Iberian Peninsula (Portugal and Spain), where fish fauna display a high level of endemism. For this eco-region, there is a dearth of information on the interactions among water quality, physical condition and parasites of invasive fishes. Consequently, the aim of this study was to assess the effect of nutrient enrichment on health status and parasitological traits in the invasive mosquitofish Gambusia holbrooki inhabiting an Iberian river. Water (n = 18 replicates, three per site) and fish (n = 400 individuals, 33–34 ind. per site and year) samples were collected in September 2024 and 2025 along the River Bullaque (central Spain). Sampling effort was standardised among sites, with the following parameters consistent: seine and pond nets were used, deployed by wading; 10:00 solar time; 1.5 h duration; personnel (the same seven trained researchers); and weather/environmental conditions; ensuring methodological consistency and data comparability. Laboratory procedures were carried out near the sampling sites to minimise both fish stress and distortions to parasite communities. Morphological and parasitological parameters were compared between mesotrophic and eutrophic reaches (six sampling sites, three per reach). Body condition and health assessment index* were greater under eutrophic conditions. Fluctuating asymmetry (a measure of developmental instability) was significantly higher for eye diameter in the mesotrophic reach. Parasite taxonomic composition differed between reaches, with more digeneans and cestodes in the mesotrophic sites, whereas ciliates and monogeneans were more abundant in mosquitofish from the eutrophic reach. Parasite prevalence, abundance and index of life-cycle complexity (heteroxenous species) were lower in the eutrophic reach. These results strongly suggest that eutrophication can facilitate mosquitofish invasiveness. This is reflected in a variety of morphological and parasitological traits, such as better body condition, health status, developmental stability, parasite resistance and tolerance. Overall, these parameters indicate that mosquitofish is taking advantage of anthropogenic impacts to improve their level of establishment and subsequent spread throughout Iberian fresh waters. Full article

Anaerobic co-digestion (AcoD) is increasingly applied in sewage-sludge management and organic-waste treatment because it can improve methane recovery, stabilize mixed substrates, and reduce life-cycle greenhouse-gas emissions under appropriate feedstock and operating conditions. However, existing reviews still focus mainly on feedstock types or isolated enhancement measures and less often connect synergistic mechanisms with engineering implementation and carbon outcomes. The specific novelty of this review is to connect functional feedstock classification, mechanism boundaries, engineering controls, and carbon-performance evaluation within one sludge-centered AcoD framework. This review synthesizes recent progress in AcoD of sewage sludge, food waste, livestock manure, crop residues, and industrial organic streams through a chain from feedstock traits to substrate interactions, microbial responses, engineering performance, and carbon benefits. Feedstocks are reorganized by function rather than by waste name, highlighting how carbon-to-nitrogen contrast, buffering capacity, hydrolysis recalcitrance, and inhibitor profiles jointly define synergy potential. Key mechanisms, including C/N balancing, hydrolysis complementarity, inhibitor mitigation, and direct interspecies electron transfer (DIET), are discussed together with their applicability limits. Representative evidence shows methane-yield or methane-production increases of about 41–55% for selected food-waste–manure blends, approximately 45% for rice–straw–pig manure systems after cellulolytic pretreatment, and approximately 16–55% for selected additive strategies; these values are illustrative rather than directly comparable because the underlying studies differ in substrates, baselines, reactor configurations, pretreatment conditions, and operating parameters. The review then translates mechanism into practice through pretreatment, reactor-selection templates, operating windows, additive reinforcement, and artificial-intelligence-assisted monitoring. Representative cases and life-cycle evidence indicate that AcoD can improve methane productivity while lowering greenhouse-gas emissions relative to landfill or mono-digestion pathways when energy substitution and nutrient recycling are credibly counted. Remaining bottlenecks include incomplete kinetic integration, limited DIET quantification, insufficient reporting of quantitative operating ranges and additive dosages, and weak coupling of carbon, economics, and regional feedstock dynamics. The revised review therefore treats AcoD as a sludge-centered mechanism-to-engineering framework and highlights two transferability gaps that require stronger standardization: biodegradation/toxicity testing and local co-substrate logistics. Full article

The rapid expansion of solar photovoltaic (PV) deployment has led to increasing concerns regarding end-of-life module management and the sustainability of material supply chains, where waste volumes are projected to reach 3.3–5.6 million tons by 2045. This study evaluates the environmental and economic impact of advanced photovoltaic recycling in Germany, focusing on high-value material recovery from crystalline silicon modules. A Full Recovery of End-of-Life Photovoltaics (FRELP) pathway is developed, integrating light-pulse delamination and molten salt etching, and a comparative life cycle assessment and economic assessment framework is applied. The results indicate that advanced recycling achieves high recovery rates for silicon, silver, aluminum, copper and low-iron glass, yielding around €1174.88 per ton of panels recycled. Economic analysis shows that manufacturing PV modules from recycled materials reduces costs by approximately 60–77% compared to virgin material production, mainly due to avoided energy-intensive upstream processes. From an environmental perspective, the recycling-based pathway yields net benefits across impact categories, as avoided impacts from primary material extraction outweigh additional burdens associated with recycling. Overall, PV recycling in Europe is shown to be environmentally and economically favorable; however, technological maturity and policy constraints remain key barriers to large-scale implementation and a holistic overall recycling process, indicating the need for targeted policy support. Full article

Climate change adaptation in buildings is an expanding field, yet methodological approaches remain diverse and fragmented, with no widely adopted unified assessment framework. This study aims to identify and synthesize existing methods and frameworks used to assess climate change adaptation in buildings. A scoping review was conducted to map key concepts, methodological trends, and knowledge gaps in the literature. Following database screening and study selection, 50 articles published between 2010 and 2026 (including one online-first paper with a nominal publication year 2026) were analysed according to assessment methods, frameworks, hazards, building typologies, life-cycle stages, and climate zones. The findings indicate a strong reliance on simulation-based and indicator-based approaches. Heatwaves are the most frequently examined hazard, while thermal comfort is the most commonly assessed adaptation-related outcome; comprehensive multi-hazard assessments remain relatively scarce. Established sustainability certification schemes and technical standards are often adapted for this purpose, whereas dedicated climate adaptation assessment frameworks remain limited. Overall, the field is characterized by considerable methodological fragmentation, highlighting the need for integrated multi-criteria evaluation frameworks that better connect building-scale technical assessment with broader climate policy objectives. Full article

The tower with an attached vent stack is a special arrangement in chemical tower structures. Flow-induced vibration of this configuration directly affects the safe operation and structural fatigue life of the equipment. This paper investigates the vortex-induced vibration (VIV) characteristics of a two-cylinder system consisting of a tower and its attached vent stack. Through fluid–structure interaction (FSI) simulations of two unequally sized cylinders in a bundled arrangement, the vibration responses under first and second-mode critical wind speeds with a flow direction of 0° are analyzed. The analysis examines lift and drag coefficients, vibration displacements, and wake flow evolution to reveal the vibration response pattern under multi-parameter coupling. When the lift forces obtained from FSI are applied in a static calculation, the static results for both the first and second-mode critical wind speeds are approximately 250% larger than the FSI results, indicating a significant discrepancy. Further analysis shows that in the FSI simulations, a notable phase difference exists between the fluid excitation and the structural response, causing the lift force to do negative work during part of the vibration cycle, thereby limiting the net energy input. Under the second-mode critical wind speed, the lift distribution along the tower height is significantly non-uniform. The conventional static calculation method neglects both the phase difference and the non-uniform lift distribution along the height, leading to overly conservative predictions. Full article

The prevention and control of forest fires are of vital importance for ecological security. The efficiency and environmental friendliness of fire-extinguishing agents remain the core focus of current research. This paper reviews the research progress and fire extinguishing mechanisms of three types of forest-fire-extinguishing agents, namely, foam extinguishing agents, gel extinguishing agents, and fire-resistant barrier materials. These three types of extinguishing agents work together to extinguish fires through three principles: isolating combustibles, reducing the oxygen concentration, and lowering the temperature. This paper systematically summarizes the performance evaluation methods, covering the cooling rate, fire extinguishing time, and re-ignition rate, and combines numerical simulation and field experiments to build a multi-scale verification system. The environmental assessment focuses on biodegradability, the ecological toxicity to soil and water systems, and the impact on plant germination and biodiversity. It clearly indicates that degradability, low toxicity, and low residue are key development directions. The current research still needs to further deepen in aspects such as long-term stability, adaptability to complex terrains, and ecological risk assessment during the life cycle. In the future, priority should be given to promoting green, multi-functional, and precise application technologies to provide solid support for scientific forest fire prevention and ecological protection. Full article

To explore the life-cycle carbon emission characteristics of zero-carbon buildings and the economic feasibility of carbon reduction strategies, this study takes the Life Cycle Assessment (LCA) method as the core and constructs a full life-cycle carbon emission accounting system for buildings covering building material production, transportation, construction, operation and demolition in accordance with the standards. Taking the Jinan Zero-Carbon Operation Center Project as a case, this paper systematically calculates its carbon emissions at all stages of the life cycle, identifies the key carbon emission stages and core influencing factors, and comparatively analyzes the economic efficiency of two carbon offset strategies, namely increasing photovoltaic power generation and purchasing green electricity, for the two goals of zero carbon in the operation stage and zero carbon in the full life cycle by using the equivalent annual cost (EAC) method. The results show that the total life-cycle carbon emissions of the case project reach 149,974.04 tCO₂e, with the operation stage and building material production stage being the core carbon emission stages, accounting for 75.50% and 24.19% respectively, while the carbon emissions in the transportation, construction and demolition stages account for a negligible proportion. The economic analysis indicates that although the increase in photovoltaic power generation systems involves a high initial investment, its equivalent annual cost is significantly lower than that of the green electricity purchase strategy. Comparative analysis using equivalent annual costs shows that adding a photovoltaic system achieves equivalent annual costs of $206,589.58 and $273,630.84 for operation stage and life-cycle zero-carbon targets, respectively. In contrast, purchasing green power certificates annually to achieve the same goals incurs equivalent annual costs of $316,223.13 and $317,096.45, representing annual savings of 34.67% and 13.71%. The carbon emission accounting method constructed in this study can provide a reference for the life-cycle carbon quantification of zero-carbon buildings, and the conclusions on the economic efficiency of carbon reduction strategies can serve as an economic decision-making basis for the planning, design and carbon reduction scheme selection of zero-carbon buildings. Full article

Senecavirus A (SVA) is a newly emerging picornavirus associated with porcine idiopathic vesicular disease and sudden death in newborn piglets. Currently, no specific vaccines or drugs are available against SVA, highlighting the importance of investigating the immunological characteristics of its key proteins. The VP1 protein of SVA exhibits strong immunogenicity and high sequence conservation, and it is indispensable to the viral life cycle. In the present study, a monoclonal antibody (mAb) against VP1 was generated. A series of truncated VP1 proteins was then expressed to precisely map the epitope recognized by this mAb. The minimal reactive unit was identified as ¹⁶DTDFSGELA²⁴. Homology analysis further revealed that this epitope is conserved among different SVA isolates deposited in GenBank. Moreover, AlphaFold prediction, along with PyMOL (Version 3.0.3) and GETAREA analyses, reveals that this epitope resides in the α-helix and loop regions of the three-dimensional structure of the VP1 protein and is surface-exposed. Collectively, these findings indicate that the mAb and its recognized epitope represent valuable tools for investigating SVA etiology and VP1 protein function. Full article