Search Results (1,117)

Cosmetic wastewater is increasingly recognized not only as a disposal problem but also as a potential source of recoverable water and formulation-derived compounds. This review critically examines the relationship between cosmetic formulation chemistry, wastewater composition, pollutant removal mechanisms, membrane separation, fouling behaviour, and reuse-oriented treatment design. Cosmetic wastewater shows high compositional variability, with reported COD values ranging from approximately 2400 mg O₂/L to more than 100,000 mg O₂/L, depending on product type, cleaning practices, and raw material losses. Surfactants, emulsifiers, oils, polymeric thickeners, preservatives, fragrances, UV filters, dyes, and microplastics contribute differently to organic load, emulsion stability, toxicity, and treatment resistance. Conventional treatment processes reduce coarse, suspended, emulsified, and biodegradable fractions, but they are limited by low biodegradability, sludge generation, inhibitory compounds, and incomplete removal of persistent micropollutants. Advanced oxidation, adsorption, electrochemical processes, and hybrid systems can improve the transformation, phase transfer, retention, and polishing of recalcitrant compounds, with AOPs typically achieving COD removal of approximately 55–85% and hybrid systems improving overall performance by about 10–25% compared with biological treatment alone. Membrane technologies are evaluated as selective barriers enabling clarification, polishing, water reuse, and resource recovery. MBRs can remove more than 90–95% of COD and BOD₅, while NF/RO polishing may reject more than 90–95% of selected recalcitrant organics and microcontaminants. The novelty of this review lies in shifting the discussion from end-of-pipe wastewater treatment toward source-oriented recovery, integrated treatment trains, and mechanism-based selection of technologies before cosmetic wastewater becomes diluted, mixed, and difficult to reuse. Full article

Operational risk assessment in complex industrial systems like mineral processing plants is hindered by inherent uncertainty and incomplete information. This study presents an integrated grey system theory-based framework to address this challenge. Combining Grey Multi-Criteria Decision-Making (GST-MCDM) and Grey Relational Analysis (GRA), the methodology enables a systemic analysis that prioritizes risks, quantifies interdependencies, and measures cumulative burden across four key objectives: time, cost, quality, and safety. Applied to a case study at the Gohar Zamin iron ore processing plant (Iran), the model analyzed 26 operational risks, classifying them into Critical (8 risks), Significant (9), and Controllable (9) tiers. Electrical power shortage (RPS: 0.19) and raw material supply delay (RPS: 0.21) were identified as the most critical risks. The analysis quantified that the safety objective bears the highest cumulative risk burden at 32%, primarily due to human factor vulnerabilities, while cyber-physical threats ranked among the top 8 critical risks. Strong interdependencies were revealed, notably a quality cascade (relational grade: 0.84) between poor consumable materials and final product failure. Sensitivity analysis confirmed high model robustness (Spearman’s p = 0.91). The framework provides managers with an actionable tool for strategic, cluster-based mitigation and evidence-based resource allocation, emphasizing investment in human capital as a core risk reduction strategy. This research contributes a replicable, quantitative methodology for enhancing operational resilience under uncertainty in capital-intensive industries. Full article

Financial statement fraud inflicts large and recurring losses on capital markets, yet the dominant detection paradigm still relies on single, black-box classifiers (e.g., RUSBoost) trained on structured accounting ratios alone. Two limitations follow: (i) the rich, unstructured Management Discussion and Analysis (MD&A) narrative of the 10-K filing is discarded, and (ii) the resulting scores are difficult for auditors to trust because they carry no transparent, standards-aligned rationale. Recent large language model (LLM) systems have shown that multi-agent collaboration is more robust than a single LLM for anomaly detection, but no study has systematically transferred this paradigm to listed-company statement fraud. We propose FraudDebate-Agent, a four-role multi-agent system in which a Quantitative Analyst agent scores 28 raw accounting items and 14 ratios with gradient-boosted and tabular attention models, a Narrative Auditor agent quantifies tone, linguistic uncertainty, and year-over-year textual novelty of the MD&A with FinBERT, and an Industry Peer agent uses retrieval-augmented generation to measure industry-relative anomaly. A Critic–Debate agent then orchestrates a pair-wise Evidence-based Multi-Agent Debate (EMAD) that reconciles disagreement across modalities and arbitrates a reconciled fraud-risk assessment, which is aggregated over a tri-modal evidence graph. Our contributions are as follows: (1) the first use of an evidence-grounded debate mechanism for accounting fraud, which materially reduces LLM hallucination; (2) a numerical–textual–peer evidence graph that fuses heterogeneous signals; and (3) an explainable report aligned with the PCAOB AS 2401 fraud-risk taxonomy. On AAER-labelled firm-years linked across a SEC financial dataset and EDGAR-CORPUS, FraudDebate-Agent improves the area under the ROC curve and the rare-event ranking metric NDCG@k over the strongest single-modality and single-LLM baselines while producing substantially more faithful explanations. We frame the system as a fraud-risk screening and risk-ranking tool for AAER-labelled misstatement risk rather than a determination of fraudulent intent. We report results over multiple seeds to reflect real-world stochasticity and discuss limitations and cross-domain applications. Full article

Ukraine’s energy strategy under martial law necessitates decentralized local energy systems to counter electricity shortages and systemic infrastructure failures. The study develops and validates an optimization model for designing the architecture of decentralized “energy islands” based on circular bioenergy models for agricultural waste use. Empirical verification was conducted using data from the Vinnytsia region in Ukraine. The model accounts for a multi-level structure that separates micro/small generation (0.1–2.0 MW) from medium generation (1–20 MW) based on the logistical radius for raw material collection. The model incorporated the Value of Lost Load (VLL), enabling the monetization of avoided socio-economic losses from energy shortages. In addition, the coefficient of energy island sustainability (I_sred) was introduced to quantitatively assess the effectiveness of investments in terms of replacing external resources. The modeling revealed the nonlinear nature of the total cost function, enabling us to determine an optimal energy-autonomy range of 40% to 50% for communities. At this threshold, the total construction and logistics costs are minimized. The potential socio-economic losses from blackouts are effectively mitigated, as confirmed by the calculated sustainability coefficient (I_sred), which ranges from 0.78 to 0.94 across the studied communities. The resource potential assessment confirms that the region’s total potential is approaching 30 million tons of oil equivalent, driven by solid biofuels, agricultural residues, and energy crops (miscanthus, switchgrass). The classification of biomass supply chains shows that exceeding the transportation radius by more than 70 km at the meso level, or deviating from the optimal logistics lever by 20%, reduces the profitability of projects below the critical limit of 15%, which justifies strict localization within raw-material clusters. This enables local communities to eliminate natural gas consumption, reduce energy supply operating costs by 15%, and ensure the autonomous and stable operation of critical infrastructure facilities during prolonged disruptions to the national power grid. Full article

Arachidonic acid (ARA) is an essential long-chain polyunsaturated fatty acid for infant growth and development, commonly added to infant formula and supplementary foods as ARA oil or ARA powder. Since December 2025, infant formula products have been recalled in several countries due to cereulide contamination in ARA ingredients. Cereulide, a heat-resistant emetic toxin produced by Bacillus cereus, presents a serious threat to infant health. However, specific analytical methods for cereulide detection in ARA raw materials remain scarce, hindering effective quality control and source prevention of food safety hazards. This study developed and validated a rapid ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) method for the quantitative determination of cereulide in ARA oil and powder. Sample pretreatment was optimized according to matrix characteristics: for microencapsulated ARA powder, water dissolution was performed to release cereulide before acetonitrile extraction, whereas direct extraction was applied to ARA oil. Subsequent HLB-P pass-through solid-phase extraction effectively eliminated matrix interference in both matrices. The method exhibited excellent linearity (R² > 0.999) from 0.1 to 20 μg·L⁻¹, with an LOD of 0.03 μg·kg⁻¹ and an LOQ of 0.1 μg·kg⁻¹, respectively. Spike recoveries reached 90.7–107.0% for ARA oil (RSDs ≤ 6.5%) and 88.5–107.9% for ARA powder (RSDs ≤ 7.0%). This rapid and reliable method provides a critical analytical tool to monitor cereulide in ARA raw materials and mitigate infant safety hazards at the source. Full article

The depletion of high-grade manganese ore reserves, accompanied by the progressive decline in ore quality, has intensified concerns regarding the supply of suitable manganese raw materials for Kazakhstan’s ferroalloy industry. Under these conditions, the development of efficient processing technologies for iron manganese ores characterized by low Mn/Fe ratios and complex mineralogical compositions has become increasingly important. This review examines current pyrometallurgical approaches for the processing of iron manganese ores, including carbothermic reduction roasting followed by magnetic separation, reduction smelting for the production of rich manganese slag, and hydrogen-based selective reduction followed by magnetic separation. Particular attention is given to the mineralogical and chemical characteristics of Kazakhstan’s iron manganese ores, which significantly limit their direct utilization in conventional ferromanganese production processes. The advantages and limitations of these technologies are critically evaluated in terms of metal recovery, Mn/Fe upgrading efficiency, energy requirements, environmental performance, and industrial applicability. The comparative analysis identifies reduction smelting as the most suitable route for Kazakhstan’s iron manganese ores under current technological conditions. This conclusion is primarily supported by the low Mn/Fe ratios, elevated iron contents, and complex mineralogical associations characteristic of the major Kazakhstan deposits, which limit the efficiency of solid-state reduction followed by magnetic separation. During smelting, the original mineral structure is destroyed, and iron and manganese are separated directly between the liquid metal and slag phases. Published studies report iron recoveries exceeding 95%, MnO recovery to the slag of approximately 94.6%, and Mn/Fe ratios above 15 in the resulting rich manganese slag. In addition, the process produces two potentially marketable products-cast iron and rich manganese slag-and can be integrated more readily into Kazakhstan’s existing ferroalloy production infrastructure. Therefore, reduction smelting currently represents the most technologically mature and practically feasible route for the comprehensive utilization of Kazakhstan’s iron manganese resources. Full article

The growing demand for electric traction batteries, together with their high content of Critical Raw Materials (CRMs), necessitates comprehensive life cycle environmental assessments. Limited attention in the literature has been devoted to explicitly disentangling the role of individual CRMs in shaping both environmental burdens and potential end-of-life benefits. This study presents a “cradle-to-grave” life cycle assessment (LCA) of a Lithium Iron Phosphate battery for electric vehicle applications, aiming to identify the contributions of individual life cycle phases and quantify the role of CRMs. The life cycle inventory was developed using data from the literature and the Ecoinvent database, with impacts assessed using the ReCiPe 2016 midpoint hierarchist (H) method. LCA results indicate that the material manufacturing phase dominates most impact categories. A gravity analysis demonstrates that a limited set of CRMs (aluminium, copper, and lithium) structurally governs both environmental burdens and recycling benefits. Monte Carlo analysis indicates low uncertainty for most impact categories. A first sensitivity analysis reveals that improvements in round-trip efficiency exert the strongest influence on environmental performance. A second sensitivity analysis assesses the effect of different energy mixes used to model electricity consumption during the use phase. Full article

The firing of traditional gray pottery relies on complex physicochemical reactions governing its color, dimensional accuracy, and structural stability. Unclear kiln-transformation mechanisms restrict standardized and digital production of this Chinese intangible cultural heritage. Herein, direct ink writing (DIW) was used to fabricate Hejin gray pottery green bodies from local ternary raw materials. Thermodynamic calculations, TG–DTG/DSC, XRD, XRF, and atmosphere-controlled firing tests were combined to reveal coupled phase evolution and reduction color-forming mechanisms during sintering. Two interrelated kiln-transformation processes were identified. First, sequential mineral reconstruction occurs at four critical temperatures: free water loss at 119.8 °C, two-stage dehydroxylation of hydrous silicates at 270.5 °C and 767.9 °C, and CaCO₃ decomposition at 547.9 °C. Uneven shrinkage and gas release at these temperatures induce cracking, blistering, and deformation of printed bodies. Micron-sized CaCO₃ (equivalent radius ≈ 1.31 μm) exhibits high surface energy and significantly reduces its decomposition temperature, consistent with experimental observations. Second, reducing atmospheres trigger competitive phase formation. Distinct from the conventional Fe₂O₃ → Fe₃O₄ → FeO reduction pathway, Fe oxides preferentially react with abundant Al₂O₃ to form thermodynamically stable FeAl₂O₄ spinel, yielding uniform celadon-gray tones. The final color is nearly independent of 20–90 vol% CO, and air-isolated cooling below 600 °C is mandatory to prevent secondary oxidation and reddening. This work establishes a thermodynamic framework for DIW-printed Hejin gray pottery kiln transformation, clarifies microscale defect and color-evolution mechanisms, and offers theoretical guidance for atmosphere-controlled firing and digital mass production of heritage ceramics. Full article

Contemporary research on ecological building materials focuses on the use of industrial waste as an alternative to traditional raw materials. Utilizing byproducts such as fly ash, slag, and plastic waste not only solves the problem of landfill but often improves the technical parameters of the finished products. Contemporary research on sustainable building materials focuses on the use of industrial waste as an alternative to traditional raw materials. This review article, which opens this Special Issue, provides a comprehensive conceptual framework for sustainable materials and introduces clear criteria for selecting the main global waste streams. Besides systematizing the existing literature, the work critically addresses the most pressing challenges in the sector, such as the upcoming shortage of traditional fly ash resulting from the European energy transition and the volumetric instability of steel slag. Looking ahead, as an opening article, it outlines key avenues for further analysis—including advanced chemical surface modifications and supply chain regionalization—necessary to reduce embodied carbon footprints and combat urban heat islands. Ultimately, the work highlights the systemic possibilities of multi-stream waste upcycling, defining ecological and methodological benchmarks that justify and guide further academic research and industrial implementation in sustainable construction. Full article

Circularity in the aluminium manufacturing and use industries has attracted increasing attention in recent years. This is partly due to the criticality of the raw material and the drive for a more sustainable, greener society through the EU Green Deal and subsequent legislation/frameworks. Several stakeholders regard post-consumer scrap (PCS) as a panacea for this transition to circularity. Obtaining an appropriate, recycling-friendly post-consumer scrap alloy for a product is challenging, thereby intensifying competition in the PCS alloy market. Furthermore, manufacturers in the aluminium industry must conduct accurate and transparent assessments of their products. Life Cycle Assessment is the primary method used today. While several modelling approaches exist within LCA, the EU recommends using either the product environmental footprint (PEF) (50:50) or the Circular Footprint Formula (CFF) approach. This paper highlights the limitations of these modelling approaches and compares them with the net-scrap approach for LCA of high-voltage aluminium cables. The strength of the net-scrap approach lies in its robustness, particularly in demand-heavy PCS markets. It promotes the use of recycled inputs and end-of-life recyclability and allows for the inclusion of metal quality parameters. These are key levers for achieving high circularity (i.e., over 70%) in open-loop recycling of aluminium alloys. Full article

Under the “dual carbon” goals (carbon peak and carbon neutrality), the new energy vehicle (NEV) industry has become a strategic focus of great-power competition, and the resilience of its international supply chain is critical to industrial security and development initiatives. As a traditional automobile manufacturing hub in China, Hubei Province faces increasingly prominent global risks in its supply chain during the transition to NEVs; scientifically evaluating and enhancing its international supply chain resilience is therefore of great practical significance. Drawing on supply chain resilience theory, this paper constructs an evaluation index system comprising 18 specific indicators across four dimensions: robustness, redundancy, agility, and innovativeness. To overcome the limitations of a single weighting method, a combined subjective and objective weighting approach that integrates the Analytic Hierarchy Process (AHP) and the entropy weight method was employed to determine indicator weights. Subsequently, the TOPSIS model was applied to measure the supply chain resilience level of Hubei Province from 2018 to 2025, with horizontal comparisons conducted against Shanghai and Guangdong. Finally, an obstacle degree model was introduced to quantitatively diagnose the key factors constraining resilience improvement. The results indicate that the international supply chain resilience of Hubei’s NEV industry has shown a continuous upward trend. By 2025, it ranks in the first tier alongside Guangdong (with closeness coefficients of 0.8180 and 0.8181, respectively), approaching the level of Shanghai. Weaknesses are concentrated primarily in the agility dimension, while upstream resource dependence remains a salient issue within the robustness dimension. “External dependence on key raw materials,” “average recovery time from logistics disruptions,” and “level of supply chain information sharing” are still the top three obstacle factors. Fuzzy-set qualitative comparative analysis (fsQCA) further reveals that low resource autonomy and slow logistics recovery are core conditions leading to low resilience, and the coupling of multiple obstacle factors amplifies the risk transmission effect. Based on this, this study proposes optimization recommendations focusing on foundation strengthening and chain consolidation, digital chain connectivity, and innovation–chain integration, in order to enhance the resilience of the international supply chain for new energy vehicles in Hubei. This research provides a methodological reference for evaluating the supply chain resilience of regionally distinctive industries and offers a quantitative basis for Hubei Province and related enterprises to formulate targeted improvement strategies. Full article

Carnot batteries (CBs) offer an appealing alternative to saturated pumped-hydro facilities and electrochemical batteries dependent on critical raw materials. A concept recently highlighted in the literature is that of coupled CBs, in which the discharge cycle of a CB interacts directly with the power cycle of a thermal power plant. Such configurations show promising gains in performance, cost, and responsiveness. However, their dynamic behavior remains insufficiently characterised, restricting assessment of the grid services they could realistically deliver. This work examines an innovative architecture in which a nuclear Rankine cycle is coupled to a CB to enhance operational flexibility. Following the preliminary system sizing, a detailed numerical analysis is performed using the CATHARE-3 thermal–hydraulic code to characterize the overall steady-state performance and transient behavior during CB discharge. The results show that the high-pressure turbine acts as an effective filter, absorbing most disturbances introduced by the CB. A refined breakdown of inertial contributions within both the Rankine cycle and the CB enables the identification of the most sensitive components. Finally, under these preliminary sizing assumptions, the coupled system exhibits high performance and would be capable of meeting the primary frequency control requirements during discharge operation, suggesting that coupled CBs constitutes a promising solution for providing fast frequency-regulation services to the electrical grid. Full article

Color is a critical sensory attribute of foods that strongly influences consumer perception, acceptance, and purchasing decisions. As health-oriented consumption increases, natural pigments are progressively replacing synthetic colorants. Red algal phycobiliproteins (PBPs) have gained attention in related industries for their vivid water-soluble colors and potential health-promoting properties. Phycoerythrin (PE), phycocyanin (PC), and allophycocyanin (APC) are key pigment proteins responsible for their characteristic coloration. However, variations in algal species, season, and cultivation environments make PBP composition, yield, and quality difficult to standardize. This review summarizes red algal PBPs, covering algal sources, extraction and purification, physicochemical properties, biological functions, regulatory frameworks, and future directions. Major red seaweed sources, PBP types, and extraction strategies are compared, with cyanobacterial PBP studies incorporated where direct red algal evidence is limited. Evidence suggests that red algal PBPs are promising for clean-label, water-based, and mildly processed foods, including beverages, dairy products, confectionery, and meat alternatives, but their application is constrained by sensitivity to heat, light, oxygen, and pH. Beyond coloration, PBPs exhibit antioxidant, anti-inflammatory, anticancer, antibacterial, and metabolic health-promoting activities. Overall, red algal PBPs have considerable potential as dual-function ingredients, although commercialization requires advances in raw material standardization, stability-enhancement strategies, process optimization, clinical validation, and regulatory harmonization. Full article

Malodorous gases such as ammonia (NH₃) and hydrogen sulfide (H₂S) emitted from pig intestines and excrement have become critical environmental bottlenecks restricting the green transformation of the swine industry. Therefore, identifying sustainable protein feed alternatives with odor-reducing potential has become increasingly important. This study evaluated the effects of replacing soybean meal with four distiller’s grains-derived protein raw materials (DGPRMs), including Baijiu DDGS, Sorghum DDGS, Corn DDGS, and Cassava DDGS, using an in vitro fermentation system simulating the intestinal environment of six fattening pigs. After 24 h of fermentation, odor-related gas production, short-chain fatty acid (SCFA) concentrations, and microbial community composition were analyzed to assess the odor-mitigation potential of these alternative protein sources. Results demonstrated that Baijiu distiller’s grains, sorghum distiller’s grains, and corn distiller’s grains significantly reduced the yields of NH₃ and H₂S under the in vitro fermentation system (p < 0.05). Meanwhile, they reshaped the intestinal microbial community structure by inhibiting the growth and reproduction of odor-producing genera (e.g., Ligilactobacillus) and promoting the enrichment of beneficial genera (e.g., Limosilactobacillus) that were significantly negatively correlated with malodor indicators. Notably, among all tested DGPRMs, Baijiu DDGS exhibited the strongest odor-reducing effect, markedly decreasing NH₃, H₂S, and volatile sulfur compounds while enriching beneficial bacterial taxa associated with reduced odor generation. These findings suggest that selected DGPRMs, particularly Baijiu DDGS, may serve as promising alternative protein ingredients for mitigating odor emissions in pig production systems. Full article

The stainless steelmaking process generates substantial volumes of metal hydroxide sludge during neutralization after pickling. The sludge contains valuable materials, including fluorspar (CaF₂) and alloy-containing compounds. So far, life cycle assessment (LCA) of resource recovery and reuse pathways for pickling sludge remains absent in the literature. This study conducted a comprehensive LCA of a real-world Swedish case study in which the sludge is thermally processed into a usable product (Hydrofluss) and utilized in the argon oxygen decarburization (AOD) process in stainless steelmaking. Using the Product Environmental Footprint (PEF) 3.1 method and ecoinvent v3.11 in SimaPro v10.3.01, the results showed that using 1 ton of Hydrofluss can reduce the total life-cycle climate change impact by 91.6 kg CO₂eq, corresponding to a 6% reduction compared with a reference scenario relying on natural fluorspar and primary ferroalloys. The sensitivity analysis indicated that replacing fossil heating oils with renewable HVO100 in the Hydrofluss recovery process could substantially enhance the climate benefit of the studied system, resulting in a six-fold (540.3 kg) CO₂eq emission reduction. Beyond climate change, this study highlights the need for multi-impact LCAs to provide a more holistic understanding of the environmental implications of resource recovery and utilization systems. In a broader context, the findings can contribute to the development of more sustainable and circular resource flows and associated business models for stainless steelmaking. Full article