Search Results (3,328)

In cold climates, mine air conditioning systems are essential for preventing liners and shaft components from freezing. Traditionally, fossil fuel burners are used to heat intake air, resulting in high energy consumption and significant greenhouse gas emissions. As part of efforts to reduce both environmental impacts and energy use, mining companies are increasingly adopting innovative solutions, such as heat recovery systems. These systems offer a promising approach to significantly reduce energy demand for underground mine heating. This study evaluates several heat recovery technologies including exhaust air, water, hybrid exhaust air–water, diesel exhaust, jacket water, and hybrid diesel exhaust–jacket-water systems, through numerical modeling. Two case studies are presented: a grid-connected mine in British Columbia with moderately cold conditions, and an off-grid mine in the Northwest Territories, which experiences Arctic climate extremes. Results show that heat recovery can reduce heating costs by up to 89% in British Columbia and as much as 90% in the Northwest Territories, depending on the system applied. The findings also demonstrate substantial associated carbon emission reductions. Furthermore, a comprehensive feasibility analysis was carried out to evaluate the thermodynamic performance, financial savings, and carbon emission reductions of these systems across various mining operations, offering a preliminary assessment of their potential for mining settings. Full article

Despite significant research interest, the understanding of how to systematically implement Lean practices in supply chains remains limited. Therefore, this study analyzes the impact of blockchain technology on implementing Lean principles within supply chain networks. A theoretical model was developed based on a comprehensive literature review, utilizing innovation diffusion theory, agency theory, and transaction cost economics. The LDA topic modeling, based on big data from the past decade, was employed to explore key areas and essential industry practices related to blockchain technology. By cross-validating big data analysis and survey results, we also developed reliable metrics that can be used to study blockchain utilization in SCM. The hypotheses were empirically tested using survey data from 219 US enterprises that have adopted blockchain technology. The empirical results revealed that blockchain adoption significantly improved Lean management practices within supply chain networks. Furthermore, research has shown that blockchain can significantly enhance operational performance, including cost reduction, quality improvement, delivery capacity, and greater flexibility. These compelling results suggest that blockchain has the potential to serve as a powerful platform for systematically integrating and orchestrating Lean management practices across the entire supply chain network, thereby achieving operational excellence. An in-depth discussion of the study’s practical implications and theoretical contributions is presented. Full article

Container multimodal transport faces many uncertainties in practice. To improve operational efficiency and reduce carbon emissions in freight transport, this study develops a multi-objective optimization model for container multimodal routes that incorporates demand and time uncertainties as well as carbon emissions. The proximal policy optimization (PPO) algorithm identifies robust transport paths facing uncertainty and assesses the model’s sensitivity to price fluctuations and carbon tax rates. Empirical results for the Chongqing–Singapore container route demonstrate the strong applicability of the PPO algorithm. Compared with traditional routing methods, the algorithm yields a lower late-arrival rate and delivers clear advantages in risk avoidance and cost control, thereby effectively reducing carbon emissions in line with carbon-reduction policies and offering practical guidance for logistics firms. The model operates under the assumptions of indivisible cargo and single-visit constraints at nodes, which impose certain limitations. In addition, the current model requires substantial computational resources, which may limit its applicability for smaller companies. With continued optimization, however, the approach advances the industry toward data-driven, intelligent decision-making. Full article

Dynamic social and legal transformations drive technological innovation and the transition of energy and heating sectors toward renewable sources and higher efficiency. Ensuring the reliable operation of these systems requires regular inspections, fault detection, and infrastructure maintenance. Unmanned Aerial Vehicles (UAVs) are increasingly being used for monitoring and diagnostics of photovoltaic and wind farms, power transmission lines, and urban heating networks. Based on literature from 2015 to 2025 (Scopus database), this review compares UAV platforms, sensors, and inspection methods, including thermal, RGB/multispectral, LiDAR, and acoustic, highlighting current challenges. The analysis of legal regulations and resulting operational limitations for UAVs, based on the frameworks of the EU, the US, and China, is also presented. UAVs offer high-resolution data, rapid coverage, and cost reduction compared to conventional approaches. However, they face limitations related to flight endurance, weather sensitivity, regulatory restrictions, and data processing. Key trends include multi-sensor integration, coordinated multi-UAV missions, on-board edge-AI analytics, digital twin integration, and predictive maintenance. The study highlights the need to develop standardised data models, interoperable sensor systems, and legal frameworks that enable autonomous operations to advance UAV implementation in energy and heating infrastructure management. Full article

This study examines the adoption of a low-cost model to support digital transformation in small- and medium-sized industrial enterprises (SMEs) within the context of Industry 4.0. In light of the need to increase operational efficiency while simultaneously reducing expenditure, it becomes a priority to employ innovative and cost-effective solutions. To evaluate this impact, the research applies the PICO (Population, Intervention, Comparison, Outcome) methodology, systematically assessing how the proposed model influences digital transformation and operational efficiency. Drawing on a case study, the findings demonstrate that implementing the low-cost model leads to significant cost reductions, gains in operational efficiency, and an acceleration of digital transformation in industrial organizations. The results indicate that the approach not only optimizes internal processes but also contributes to lowering the organization’s overall costs. The conclusions confirm the hypotheses, showing that the model achieves a balance between technological advancement and economic efficiency. The study provides relevant insights into the potential of technologies to simultaneously drive operational efficiency and digital transformation within the framework of Industry 4.0, offering an innovative pathway for companies seeking to digitalize while controlling costs. This research strengthens the existing body of knowledge on the synergy between digital transformation, cost efficiency, and operational performance in industrial settings. Full article

Direct Air Capture (DAC) technology plays a crucial role in reducing atmospheric CO₂, but large-scale deployment faces challenges such as high energy consumption, operational costs, and slow material development. This study provides a comprehensive review of DAC principles, including chemical and solid adsorption methods, with a focus on emerging technologies like Metal–Organic Frameworks (MOFs) and graphene aerogels. MOFs have achieved adsorption capacities up to 1.5 mmol/g, while modified graphene aerogels reach 1.3 mmol/g. Other advancing approaches include DAC with Methanation (DACM), variable-humidity adsorption, photo-induced swing adsorption, and biosorption. The study also examines global industrialization trends, noting a significant rise in DAC projects since 2020, particularly in the U.S., China, and Europe. The integration of DAC with renewable energy sources, such as photovoltaic/electrochemical regeneration, offers significant cost-reduction potential and can cut reliance on conventional heat by 30%. This study focuses on the integration of Artificial Intelligence (AI) for accelerating material design and system optimization. AI and Machine Learning (ML) are accelerating DAC R&D: high-throughput screening shortens material design cycles by 60%, while AI-driven control systems optimize temperature, humidity, and adsorption dynamics in real time, improving CO₂ capture efficiency by 15–20%. The study emphasizes DAC’s future role in achieving carbon neutrality through enhanced material efficiency, integration with renewable energy, and expanded CO₂ utilization pathways, providing a roadmap for scaling DAC technology in the coming years. Full article

This study examines the economic performance of residential photovoltaic systems combined with battery storage (PV-BESS) under Poland’s net-billing regime for a single-family household without subsidy support in 10-year operational horizon. These insights extend existing European evidence by demonstrating how net-billing fundamentally alters investment incentives. The analysis incorporates real production data from selected locations and realistic household consumption profiles. Results demonstrate that optimal system configuration (6 kWp PV with 15 kWh storage) achieves 64.3% reduction in grid electricity consumption and positive economic performance with NPV of EUR 599, IRR of 5.32%, B/C ratio of 1.124 and discounted payback period of 9.0 years. The optimized system can cover electricity demand in the summer half-year by over 90% and reduce local network stress by shifting surplus solar generation away from midday peaks. Residential PV-BESS systems can achieve economic efficiency in Polish conditions when properly optimized, though marginal profitability requires careful risk assessment regarding component costs, durability and electricity market conditions. For Polish energy policy, the findings indicate that net-billing creates strong incentives for regulatory instruments that promote higher self-consumption, which would enhance the economic role of residential storage. Full article

Traditional path planning methods primarily optimize distance or time, without fully considering the impact of slope gradients in park road networks, variations in vehicle load capacity, and braking energy recovery characteristics on the energy consumption of pure electric commercial vehicles. To address these issues, this paper proposes a globally optimized path planning method based on energy consumption minimization. The proposed method introduces a multi-factor coupled energy consumption model for pure electric commercial vehicles, integrating slope gradients, load capacity, motor efficiency, and energy recovery. Using this vehicle energy consumption model and the park road network topology map, an energy consumption topology map representing energy consumption between any two nodes is constructed. An energy-optimized improved ant colony optimization algorithm (E-IACO) is proposed. By introducing an exponential energy consumption heuristic factor and an enhanced pheromone update mechanism, it prioritizes energy-saving path exploration, thereby effectively identifying the optimal energy consumption path within the constructed energy consumption topology map. Simulation results demonstrate that in typical three-dimensional industrial park scenarios, the proposed energy-optimized path planning method achieves maximum reductions of 10.57% and 4.90% compared to the A* algorithm and ant colony optimization (ACO), respectively, with average reductions of 5.14% and 1.97%. It exhibits excellent stability and effectiveness across varying load capacities. This research provides a reliable theoretical framework and technical support for reducing logistics operational costs in industrial parks and enhancing the economic efficiency of pure electric commercial vehicles. Full article

Decarbonizing building energy use requires efficient heat pumps and low-impact geothermal exchangers. A novel standalone TRNSYS Type was developed for a patented shallow horizontal ground heat exchanger (HGHE), called flat-panel (FP), designed at the University of Ferrara. Beyond simulating the FP in isolation, the Type enables coupling with other components within heat-pump configurations, allowing performance assessments that reflect realistic operating conditions. The Type was implemented in TRNSYS models of a ground-source heat pump (GSHP) and of a dual air and ground source heat pump (DSHP) to verify Type reliability and evaluate potential DSHP advantages over GSHP in terms of efficiency and ground-loop downsizing. The performance of the system was analyzed under varying HGHE lengths and DSHP control strategies, which were based on onset temperature differential $DT$. The results highlighted that shorter HGHE lines yielded higher specific HGHE performance, while higher $DT$ reduced HGHE operating time. Concurrently, the total energy extracted from the ground decreased with increasing $DT$ and reduced length, thus supporting long-term thermal preservation and allowing HGHE to operate under more favorable conditions. Exploiting air as an alternative or supplemental source to the ground allows significant reduction of the HGHE length and the related installation costs, without compromising the system performance. Full article

The growing share of variable renewable energy sources in power systems is increasing the need for short-term operational flexibility—particularly from large industrial electricity consumers. This study proposes a practical, two-stage optimization framework to unlock this flexibility in cement manufacturing and support participation in electricity balancing markets. In Stage 1, a mixed-integer linear programming model minimizes electricity procurement costs by optimally scheduling the raw milling subsystem, subject to technical and operational constraints. In Stage 2, a flexibility assessment model identifies and evaluates profitable deviations from this baseline, targeting participation in Spain’s manual Frequency Restoration Reserve market. The methodology is validated through a real-world case study at a Spanish cement plant, incorporating photovoltaic (PV) generation and battery energy storage systems (BESS). The results show that flexibility services can yield monthly revenues of up to €800, with limited disruption to production processes. Additionally, combined PV + BESS configurations achieve electricity cost reductions and investment paybacks as short as six years. The proposed framework offers a replicable pathway for integrating demand-side flexibility into energy-intensive industries—enhancing grid resilience, economic performance, and decarbonization efforts. Full article

Aircraft turnaround efficiency is a key determinant of the sustainability of air transport systems. Each stage of ground handling—passenger disembarkation, baggage handling, refuelling, and ancillary services—contributes to the total turnaround time, with direct implications for airport capacity, operating costs, and environmental performance. Using empirical records from ground operations, the study characterizes the duration and variability of individual activities and identifies the main process bottlenecks. Building on this evidence, a comparative PERT-COST protocol with explicit threshold rules (quantized billing steps for selected resources) is developed and applied across predefined scenarios (remote versus gate, day versus night, low versus high fuel uplift, with versus without a second baggage team) under both linear and threshold cost models. The protocol aligns with ITS-enabled decision support by mapping stochastic activity times to cost-of-crashing functions and by providing harmonized performance metrics: final time T, total cost ∑ΔC, and efficiency η (EUR/min). The results show that moderate time reductions are attainable at reasonable cost, whereas aggressive targets that lie below the structural minimum are infeasible under current constraints; gate stands reduce the attainable minimum time but increase the marginal price near the minimum, and night operations raise costs without improving that minimum. These findings delineate the most productive intervention range and inform operational choices consistent with sustainability objectives. Full article

Residential photovoltaic and battery energy storage systems (PV/BESS systems) are gaining attention as a measure against natural disasters and rising electricity prices. This paper aims to propose an operational strategy that balances electricity cost reductions, battery lifespans, and outage mitigation for the residential PV/BESS system. The optimization model considering battery degradation determines normal operations with balancing cost reductions and degradation. Additionally, a rule-based approach simulates system performance during various outages and evaluates supply continuity using a resilience metric: the percent continuous supply hour. Outage mitigation benefits are quantified by considering the distribution of residential values of lost load (VoLLs). Results show that the operation considering degradation maintains a high state of charge (SoC) at all times. For 25.7% of households with large demand, electricity cost reductions exceed equipment costs. Outage simulations demonstrate that the mean energy supplied during a 48-h outage ranges from 14 kWh to $26.7$ kWh. Furthermore, the proposed operation increases the resilience metric from 20% to 30% under severe and unpredictable outages. Finally, incorporating outage mitigation benefits increases the proportion of households adopting PV/BESS systems by 21.5% points. Full article

Rechargeable zinc–air batteries (ZABs) are promising candidates for sustainable energy storage owing to their high theoretical energy density, safety, and environmental compatibility. However, their practical application is hindered by sluggish oxygen evolution reaction (OER) kinetics and the high charging voltage required, which reduce energy efficiency and accelerate electrode degradation. Here, we report for the first time the beneficial role of potassium iodide (KI) as a reaction modifier in ZABs employing manganese dioxide (MnO₂) as a bifunctional catalyst. MnO₂ not only exhibits remarkable electrocatalytic activity toward the oxygen reduction reaction (ORR) but also catalyzes the iodide oxidation reaction (IOR), which proceeds at significantly lower potentials than the OER. As a result, KI-modified MnO₂ ZABs achieve a remarkably low charging voltage of ≈1.8 V and an energy efficiency of 69.9% at 5 mA/cm². Although the IOR is not fully reversible in alkaline media and its effectiveness depends on the iodide concentration in the electrolyte—which may decrease upon repeated discharge–charge cycling—the suppression of electrode degradation enables stable operation for more than 200 charge–discharge cycles. These findings demonstrate the synergistic effect of KI and MnO₂ in enabling an efficient ORR/IOR pathway, providing a sustainable and cost-effective alternative to noble metal catalysts and opening new perspectives for the practical development of high-performance ZABs. Full article

Decarbonizing heavy-duty freight transport is essential for achieving climate neutrality targets. Although internal combustion engine (ICE) trucks currently dominate logistics, they contribute substantially to greenhouse gas emissions. Zero-emission alternatives, such as battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (H2), provide different decarbonization pathways; however, their relative roles remain contested, particularly in small economies. While BEVs benefit from technological maturity and declining costs, hydrogen offers advantages for high-payload, long-haul operations, especially within energy-intensive cold supply chains. The aim of this paper is to examine the gradual transition from ICE trucks to hydrogen-powered vehicles with a specific focus on cold-chain logistics, where reliability and energy intensity are critical. The hypothesis is that applying a system dynamics forecasting approach, incorporating investment costs, infrastructure coverage, government support, and technological progress, can more effectively guide transition planning than traditional linear methods. To address this, the study develops a system dynamics economic model tailored to the structural characteristics of a small economy, using a European case context. Small markets face distinct constraints: limited fleet sizes reduce economies of scale, infrastructure deployment is disproportionately costly, and fiscal capacity to support subsidies is restricted. These conditions increase the risk of technology lock-in and emphasize the need for coordinated, adaptive policy design. The model integrates acquisition and maintenance costs, fuel consumption, infrastructure rollout, subsidy schemes, industrial hydrogen demand, and technology learning rates. It incorporates subsystems for fleet renewal, hydrogen refueling network expansion, operating costs, industrial demand linkages, and attractiveness functions weighted by operator decision preferences. Reinforcing and balancing feedback loops capture the dynamic interactions between fleet adoption and infrastructure availability. Inputs combine fixed baseline parameters with variable policy levers such as subsidies, elasticity values, and hydrogen cost reduction rates. Results indicate that BEVs are structurally more favorable in small economies due to lower entry costs and simpler infrastructure requirements. Hydrogen adoption becomes viable only under scenarios with strong, sustained subsidies, accelerated station deployment, and sufficient cross-sectoral demand. Under favorable conditions, hydrogen can approach cost and attractiveness parity with BEVs. Overall, market forces alone are insufficient to ensure a balanced zero-emission transition in small markets; proactive and continuous government intervention is required for hydrogen to complement rather than remain secondary to BEV uptake. The novelty of this study lies in the development of a system dynamics model specifically designed for small-economy conditions, integrating industrial hydrogen demand, policy elasticity, and infrastructure coverage limitations, factors largely absent from the existing literature. Unlike models focused on large markets or single-sector applications, this approach captures cross-sector synergies, small-scale cost dynamics, and subsidy-driven points, offering a more realistic framework for hydrogen truck deployment in small-country environments. The model highlights key leverage points for policymakers and provides a transferable tool for guiding freight decarbonization strategies in comparable small-market contexts. Full article

Poly(vinyl chloride) (PVC) is one of the most widely used polymers due to its strength, low cost, and light weight. Industrial production is mainly conducted by suspension polymerization, which facilitates the control of the emissions of vinyl chloride monomer (VCM), a known carcinogen. However, the process consumes large amounts of water and energy and generates residual compounds such as polyvinyl alcohol (PVA) and polymerization initiators, which must be properly managed to mitigate environmental impacts. To improve sustainability, this study applied mass- and energy-integration strategies together with a zero-liquid-discharge (ZLD) water-regeneration system that uses sequential aerobic and anaerobic reactors to recirculate process water with reduced PVA. Although these measures reduce resource consumption, they can displace or intensify other impacts; therefore, a comprehensive evaluation of the system is necessary. Accordingly, the objective of this study is to quantify and compare the potential environmental impacts (PEIs) of the improved PVC production process through a scenario-based assessment using a waste reduction algorithm (WAR). This is applied to four operating scenarios in order to identify the stages and flows that contribute most to the environmental burden. According to our literature review, there is limited published evidence that simultaneously combines mass/energy integration and a ZLD system in PVC processes; thus, this work provides an integrated assessment useful for industrial design. The environmental performance of the improved process was evaluated using WAR GUI software (v 1.0.17, which quantifies PEIs in categories such as toxicity, climate change, and acidification. Four scenarios were compared: Case 1 (excluding both product and energy), Case 2 (product only), Case 3 (energy only), and Case 4 (product and energy). The total PEI increased from 2.46 PEI/day in Case 1 to 6230 PEI/day in Case 4, with the largest contributions from acidification (5140 PEI/day) and global warming (496 PEI/day), mainly due to natural gas consumption (5184 GJ/day). In contrast, Cases 1 and 2 showed negative PEI values (−3160 and −2660 PEI/day), indicating that converting the toxic VCM (LD₅₀: 500 mg/kg; ATP: 26 mg/L) into PVC (LD₅₀: 2000 mg/kg; ATP: 100 mg/L) can reduce the environmental burden in certain respects. In addition, the ZLD system contributed to maintaining low aquatic toxicity in Case 4 (90.70 PEI/day). Full article