Search Results (1,708)

Rising carbon emissions from international road freight transport in the EU—increasing from 29.4% in 2023 to 31.4% in 2025 under the With Existing Measures (WEM) Road Transport scenario—necessitate the implementation of additional measures within the framework of the EU Carbon Border Adjustment Mechanism (CBAM). For Ukraine, operating under martial law and pursuing a post-war green recovery of its transport and trade sectors, the adoption of EU experience in distributed generation (DG) from renewable energy sources (RESs) is particularly critical. This study evaluates the synergy between energy-efficient and low-carbon management in logistics chains for road freight transportation in Ukraine, drawing on EU evidence of DG based on RESs. To this end, a decoupling analysis was conducted to identify the factors influencing low-carbon and energy-efficient management of logistics chains in Ukraine’s freight transport sector. Under wartime conditions, the EU practice of utilising electric vehicles (EVs) as an auxiliary source of renewable energy for distributed electricity generation within microgrids—through Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) technologies—was modelled. The results confirm the relevance of RES-based DG and the integration of EVs as a means of enhancing energy resilience in resource-constrained and conflict-affected regions. The scientific novelty of this research lies in identifying the conditions for achieving energy-efficient and low-carbon effects in the design of logistics chains through RES-based distributed generation, grounded in circular and inclusive economic development. The practical significance of the findings lies in formulating a replicable model for diversifying low-carbon fuel sources via the development of distributed generation of electricity based on renewable resources, providing a scalable paradigm for energy-limited and conflict-affected areas. Future research should focus on developing innovative logistics chain models that integrate DG and renewable energy use into Ukraine’s transport system. Full article

To achieve a complete circular economy for used electric vehicle batteries, it is essential to implement a disassembly step. Given the significant diversity of battery geometries and designs, a high degree of flexibility is required for automated disassembly processes. The incorporation of human–robot interaction provides a valuable degree of flexibility in the process workflow. However, human behavior is characterized by unpredictable timing and variable task durations, which add considerable complexity to process planning. Therefore, it is crucial to develop a robust strategy for coordinating human and robotic tasks to manage the scheduling of production activities efficiently. This study proposes a global optimization approach to the scheduling of production activities, which employs a genetic algorithm with the objective of minimizing the total production time while simultaneously reducing the idle time of both the human operator and robot. The proposed approach is concerned with optimizing the sequencing of disassembly tasks, considering both temporal and exclusion constraints, to guarantee that tasks deemed hazardous are not executed in the presence of a human. This approach is based on a two-level adaptation framework developed in RoboDK (Robot Development Kit, v5.4.3.22231, 2022, RoboDK Inc., Montréal, (Québec,) Canada). At the first level, offline optimization is performed using a genetic algorithm to determine the optimal task sequencing strategy. This stage anticipates human behavior by proposing disassembly sequences aligned with expected human availability. At the second level, an online reactive adjustment refines the plan in real time, adapting it to actual human interventions and compensating for deviations from initial forecasts. The effectiveness of this global optimization strategy is evaluated against a non-global approach, in which the problem is partitioned into independent subproblems solved separately and then integrated. The results demonstrate the efficacy of the proposed approach in comparison with a non-global approach, particularly in scenarios where humans arrive earlier than anticipated. Full article

This study explores a conceptual framework for integrating Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems, emphasising its transformative potential in highly automated industrial environments, often referred to as ‘dark factories’, where operations are carried out with minimal human intervention using robotics, AI, and IoT. These lights-out manufacturing environments demand intelligent, autonomous systems that go beyond traditional ERP functionalities to deliver sustainable enterprise operations and supply chain management. Drawing from secondary data and a comprehensive review of existing literature, the study identifies significant gaps in current AI-ERP research and practice, namely, the absence of a unified adoption framework, limited focus on AI-specific implementation challenges, and a lack of structured post-adoption evaluation metrics. In response, this paper proposes a novel integrated conceptual framework that combines the Technology–Organisation–Environment (TOE) framework, the Technology Acceptance Model (TAM), and the Information Systems (IS) Success Model. The model incorporates industry-specific dark factors, such as AI autonomy, human–machine collaboration, operational agility, and sustainability, by optimising resource efficiency, enabling predictive maintenance, enhancing supply chain resilience, and supporting circular economy practices. The primary research aim of the current study is to provide a theoretical foundation for further empirical research on the input of AI-ERP systems into autonomous industry settings. The framework provides a robust theoretical foundation and actionable guidance for researchers, technology leaders, and policy-makers navigating the integration of AI and ERP in sustainable enterprise operations and supply chain management. Full article

The mechanical vapor compression (MVC) is an appealing technology for Zero Liquid Discharge (ZLD) processes, particularly in the context of the increasing global demand for freshwater and the protection of the natural environment. This approach supports the development of circular emerging technologies aligned with the Sustainable Development Goals. In this framework, an extended analysis is conducted to evaluate the performance of the MVC system under various operating conditions, with the objective of assessing the impact on energy consumption and distillate production. Reducing the consumption ratio is essential for enhancing process efficiency and advancing a more sustainable process. For this purpose, the paper examines how fluctuations in compressor boundary conditions affect temperatures and pressures. Moreover, feed brine concentration salinity is varied and related to the distillate flow. In the paper, a real ZLD process case study is provided, with experimental data collected. The real data correspond to four different operating conditions (scenarios), verifying that higher evaporation temperatures and lower compression ratio enhance the performance of such systems and lead to increased distillate production. In addition, the energy analysis reveals a consumption range of 165–214 kWh/m³ feed. Incoming electrical conductivities of up to 100 mS/cm are acceptable without scaling, with periodic HNO₃ cleanings recommended. The proposed operating ranges can also be applied to other mechanical evaporation systems for wastewater treatment, desalination processes and ZLD technologies, or transferred to other locations. Full article

Second-life electric vehicle batteries (SLBs) represent a promising asset for enhancing grid flexibility and advancing circular economy objectives in the power sector. This paper proposes a conceptual trigger-based PDCA (Plan–Do–Check–Act) framework for the sustainable grid integration of SLBs, enabling adaptive operational control across diverse application scenarios. The framework combines lifecycle KPI monitoring, degradation and performance tracking, and economic feasibility assessment with trigger-driven dispatch logic. Technical, financial, and environmental indicators are systematically integrated into the four PDCA phases, providing a structured basis for adaptive management. To illustrate applicability, indicative KPI calculations are presented for three representative scenarios (HV Backup, RES Smoothing, and Frequency Regulation). These examples demonstrate how the framework supports scenario-based planning, performance evaluation, and decision-making under uncertainty. Compared with existing state-of-the-art approaches, which typically analyse technical or economic aspects in isolation, the proposed framework introduces a modular, multi-model architecture that aligns operational triggers with long-term sustainability goals. By embedding reuse-oriented strategies into an adaptive PDCA cycle, the study offers a clear and practical methodology for maximising SLB value while minimising degradation and environmental impacts. The framework provides a valuable reference framework for structured SLB deployment, supporting more resilient, cost-effective, and low-carbon energy systems. Full article

For large-scale measurement of microbubble parameters on the ocean surface beneath breaking waves, a buoy-type bubble sensor (BBS) is proposed. This sensor integrates a panoramic bubble imaging sub-sensor with a circular array fiber-optic sub-sensor. The sensitive unit of the latter sub-sensor is designed via theoretical modeling and experimental validation. Theoretical calculations indicate that the optimal cone angle for a quartz fiber-optic-based sensitive unit ranges from 45.2° to 92°. A prototype array element with a cone angle of 90° was fabricated and used as the core component for feasibility experiments in static and dynamic two-phase (gas and liquid) identification. During static identification, the reflected optical power differs by an order of magnitude between the two phases. For dynamic sensing of multiple microbubble positions, the reflected optical power varies from 13.4 nW to 29.3 nW, which is within the operating range of the array element’s photodetector. In theory, assembling conical quartz fiber-based sensitive units into fiber-optic probes and configuring them as arrays could overcome the resolution limitations of the panoramic bubble imaging sub-sensor. Further discussion of this approach will be presented in a subsequent paper. Full article

Conventional wastewater treatment methods typically achieve 70–90% removal efficiency for organic pollutants. However, the global wastewater crisis—with 80% of wastewater discharged untreated—demands innovative solutions to overcome persistent challenges in nutrient removal and resource recovery. This review presents the first systematic analysis of technology integration strategies for algal wastewater treatment, examining synergistic combinations of biofilm reactors, nano-enhancement, artificial intelligence, and 3D printing technologies. Individual technologies demonstrate distinct performance characteristics: algal biofilm reactors achieve 60–90% removal efficiency with biomass productivity up to 50 g/m²/day; nano-enhanced systems reach 70–99% pollutant removal; AI optimization provides 15–35% efficiency improvements with 25–35% energy reductions; and 3D-printed architectures achieve 70–90% removal efficiency. The novel integration framework reveals that technology combinations achieve 85–95% overall efficiency compared to 60–80% for individual approaches. Critical challenges include nanomaterial toxicity (silver nanoparticles effective at 10 mg/L), high costs (U.S. Dollar (USD) 50–300 per m² for 3D components, USD 1500+ per kg for nanomaterials), and limited technological maturity (TRL 4–5 for AI and 3D printing). Priority development needs include standardized evaluation metrics, comprehensive risk assessment, and economic optimization strategies. The integration framework provides technology selection guidance based on pollutant characteristics and operational constraints, while implementation strategies address regional adaptation requirements. Findings support integrated algal systems’ potential for superior treatment performance and circular economy contributions through resource recovery. Full article

The recovery of copper from metallurgical effluents is critical for advancing sustainable mining and circular economy practices. This study evaluated a hybrid process combining copper sulfide precipitation with clarification using polymeric polyvinylidene fluoride (PVDF) microfiltration membranes. Laboratory-scale experiments were performed under controlled cyanide conditions (100 mg/L free CN⁻, 1800 mg/L Cu²⁺), focusing on permeate flux behavior, fouling mechanisms, and cleaning strategies. Optimal performance was achieved at moderate transmembrane pressures (<2.0 bar) and higher flow rates, which provided a balance between productivity and fouling control. Flux decline was attributed to a combination of pore blocking and cake layer formation, confirming the multifactorial nature of fouling dynamics. Cleaning tests revealed that oxidizing solutions (HCl + H₂O₂) restored up to 96% of the initial permeability, while combined treatments with NaCN achieved complete recovery (>100%), albeit with potential risks of membrane aging under prolonged exposure. A techno-economic assessment comparing polymeric and ceramic membranes revealed similar capital and operational costs, with polymeric membranes offering slight reductions in CAPEX (10%) and OPEX (2.3%). Overall, the findings demonstrate the technical feasibility and economic competitiveness of polymeric membranes for copper sulfide clarification, while emphasizing the need to improve long-term chemical resistance to ensure reliable industrial-scale implementation. Full article

The Line Balancing Problem (LBP) is a classic optimization topic in production management, aiming to improve efficiency through task allocation. With the transformation of the manufacturing industry towards intelligence, customization, and sustainability, its research scope has been significantly expanded. This study systematically reviews the recent research progress and proposes the C|H|V|E framework to analyze the LBP in four dimensions: (i) extension of the core line problem; (ii) horizontal integration with shop-floor decision-making; (iii) vertical coordination with enterprise-level operations; and (iv) extension of the value from efficiency improvement to sustainability and resilience enhancement. The review focuses on emerging trends, including artificial intelligence and data-driven approaches, digital twin-based optimization, flexible human-machine collaboration, and system integration across the lifecycle and circular economy. This paper provides a systematic overview of the current state of LBP research and explains how it continues to expand its boundaries by incorporating knowledge from new fields. Full article

The rapid growth of electric vehicle (EV) adoption in Malaysia is projected to generate substantial volumes of end-of-life lithium-ion batteries, creating both environmental challenges and opportunities for repurposing into second-life batteries (SLBs). This study investigates the technical, economic, and regulatory feasibility of deploying SLBs for photovoltaic (PV) energy storage in petrol stations, an application aligned with the nation’s energy transition goals. Laboratory testing of Nissan Leaf ZE0 battery modules over a 120-day operation period demonstrated stable cycling performance with approximately 7% capacity fade, maintaining state-of-health (SOH) above 47%. A case study of a 12 kWp PV–SLB hybrid system for a typical Malaysian petrol station shows 45 kWh of usable storage, capable of offsetting a daily electricity demand of 45 kWh, reducing capital cost by 30–50% compared to new lithium-ion systems, and achieving 70–80% lifecycle CO₂ emission reductions. The proposed architecture leverages SLBs’ suitability for slower, steady discharge to provide reliable nighttime operation and grid load relief, particularly in semi-urban and rural stations. Beyond technical validation, the paper evaluates economic benefits, environmental impacts, and Malaysia’s regulatory readiness, identifying gaps in certification standards, reverse logistics, and workforce skills. Strategic recommendations are proposed to enable large-scale SLB deployment and integration into hybrid PV–petrol station systems. Findings indicate that SLBs can serve as a cost-effective, sustainable energy storage solution, supporting Malaysia’s National Energy Transition Roadmap (NETR), advancing circular economy practices, and positioning the country as a potential ASEAN leader in battery repurposing. Full article

The automotive industry is at a critical juncture, facing increasing pressure from stringent environmental regulations, resource scarcity, and global supply chain disruptions. This study aims to identify, model, and prioritize the key factors influencing the adoption of circular economy principles in the automotive sector. The Decision-Making Trial and Evaluation Laboratory method was applied to analyze the interdependencies among ten critical factors. Based on a contribution from a panel of six experts from a European automotive distributor with its main operating points in France and Romania, the study reveals a clear cause-and-effect relationship among the factors. Causal factors such as organizational culture, internal integration, regulatory policies, circular business models, and R&D capacity were identified as key drivers. Conversely, factors like top management commitment, stakeholder engagement, technological capability, sustainable materials management, and ecodesign were classified as effect factors, meaning they are influenced by other variables. The key practical contribution of this research is a strategic prioritization framework for decision-makers, offering guidance on how to effectively boost key factors, either directly or indirectly, to achieve a more efficient alignment with circular economy principles. By strategically leveraging these interdependencies, organizations can trigger a positive chain reaction, leading to improved performance in the dependent effect factors and ultimately accelerating the transition to a circular economy. Full article

This study investigates the capacity of green and brown algae to sustainably remove oxyanions from contaminated waters, highlighting their cost-effectiveness. Often considered biomass waste and contributors to organic contamination, these algae can be used as effective biosorbents, aligning with circular economy principles and sustainable waste management. Various pre-treatments were tested to enhance adsorption capacity, with mixed results regarding their effectiveness. The focus then shifted to the use of Cladophora sericea algae for the uptake and removal of selenium species, specifically selenite (Se(IV)) and selenate (Se(VI)). The effects of different operational parameters on oxyanion uptake by algae were studied in batch mode. The assessments were conducted on a single-component and a multi-component synthetic matrix. The results indicate that pH significantly impacts biosorption, with equilibrium achieved in 90 min. Both pseudo-first-order and pseudo-second-order models provided a good fit to the experimental data. The algae’s retention capacity for selenium remained largely unaffected by the presence of other anions, a key advantage for application in complex real effluent matrices. Kinetic studies performed under different values of initial pollutant concentration and biosorbent mass indicate a biosorbed amount at an equilibrium of 570 µg g⁻¹. Full article

Drought is a leading constraint on plant productivity and will intensify with climate change. Plant acclimation emerges from a multilayered regulatory system that integrates signaling, transcriptional reprogramming, RNA-based control, and chromatin dynamics. Within this hierarchy, non-coding RNAs (ncRNAs) provide a unifying regulatory layer; microRNAs (miRNAs) modulate abscisic acid and auxin circuits, oxidative stress defenses, and root architecture. This balances growth with survival under water-deficient conditions. Small interfering RNAs (siRNAs) include 24-nucleotide heterochromatic populations that operate through RNA-directed DNA methylation, which positions ncRNA control at the transcription–chromatin interface. Long non-coding RNAs (lncRNAs) act in cis and trans, interact with small RNA pathways, and can serve as chromatin-associated scaffolds. Circular RNAs (circRNAs) are increasingly being detected as responsive to drought. Functional studies in Arabidopsis and maize (e.g., ath-circ032768 and circMED16) underscore their regulatory potential. This review consolidates ncRNA biogenesis and function, catalogs drought-responsive modules across model and crop species, especially cereals, and outlines methodological priorities, such as long-read support for isoforms and back-splice junctions, stringent validation, and integrative multiomics. The evidence suggests that ncRNAs are tractable entry points for enhancing drought resilience while managing growth–stress trade-offs. Full article

Logistics and warehouse operations experience an increasing pressure to adopt sustainable practices. The logistics industry generates substantial material waste, with cardboard being the primary packaging material. Adopting Circular Economy (CE) principles to control this waste is important for enhancing sustainability. However, there is a lack of studies on transforming warehouses into more sustainable operations. This paper studies the ability to transform the linear supply chain of a distribution warehouse into a circular supply chain by applying lean manufacturing principles to eliminate cardboard waste. A structured framework is presented to outline the project’s methodology and illustrate the steps taken to apply the concept of CE. The paper also tests the capability to simulate warehouse operations with engineering software using limited available data to generate various scenarios. This study contributes by showing how discrete-event simulation combined with VSM and 6R principles can provide operational insights under data-constrained conditions. Bridging the gap between theory and practice. Multiple operational scenarios were modelled and run, including peak and off-peak demand periods, as well as a sensitivity analysis for recycling durations. A comparative evaluation is shown to demonstrate the effectiveness of each alternative and determine the most feasible solution. Results indicate that introducing recycling activities created some bottlenecks in the system and reduced its efficiency. Furthermore, suggestions for future improvements are presented, ensuring that on-site actions are grounded in a simulation that reflects reality. Full article

Steel structures that support machines and industrial process installations should ideally be flexible, adaptable, and easily reconfigurable. However, in current practice, new profiles are frequently used and discarded whenever layout modifications are required, leading to considerable material waste, increased costs, and environmental burdens. Such practices conflict with the principles of the circular economy, in which reusability is preferable to recycling. This paper presents a life cycle sustainability assessment (life cycle cost, LCC, and life cycle assessment, LCA) applied to six structural typologies: (a) welded IPE profiles, (b) bolted IPE profiles, (c) welded tubular profiles, (d) bolted tubular profiles, (e) clamped IPE profiles with demountable joints, and (f) flanged tubular profiles with demountable joints. The assessment integrates structural calculations with an updatable database of costs, operation times, and service lives, providing a systematic framework for evaluating both economic and environmental performance in medium-load industrial structures (0.5–9.8 kN/m²). Application to nine representative case studies demonstrated that demountable clamped and flanged joints become economically competitive after three life cycles, and after only two life cycles under high-load conditions (9.8 kN/m²). The findings indicate relative cost savings of up to 75% in optimized configurations and carbon-footprint reductions of approximately 50% after three cycles. These results provide quantitative evidence of the long-term advantages of demountable and reconfigurable steel structures. Their capacity for repeated reuse without loss of performance supports sustainable design strategies, reduces environmental impacts, and advances circular economy principles, making them an attractive option for modern industrial facilities subject to frequent modifications. Full article