Search Results (709)

The cold chain sector is responsible for approximately 4% of global GHG–greenhouse gas emissions. Its passive thermal packaging, which has historically been dominated by expanded polystyrene (EPS), is both a crucial functional component and a significant environmental liability. Regulation (EU) 2025/40 on packaging and packaging waste (PPWR), along with the Single-Use Plastics Directive, the Ecodesign for Sustainable Products Regulation, and the Digital Product Passport, creates cumulative regulatory pressure on EPS and opens the market to alternative passive solutions. This systematic literature review, conducted according to the PRISMA 2020 protocol, addresses three research questions regarding the maturity of EPS alternatives such as phase change materials, vacuum insulated panels, mycelium composites, moulded pulp, dry-moulded fibre, and reusable pooled systems. It examines the cumulative effects of the EU regulatory framework and the systemic interventions needed for a circular transition, interpreted through the ten-R hierarchy. The review introduces the Cold Chain Packaging Circular Transition Framework (CCP-CTF), which is articulated across four dimensions and implemented as a composite indicator across five transition regimes, in addition to a residual EPS scenario. This framework is visualised as a Cold Chain Sustainability Thermometer—a calibrated assessment tool for researchers, policymakers, and industry operators navigating the 2026–2040 PPWR implementation timeline. The review identifies key knowledge gaps, including limited integration of decarbonisation accounting at the packaging-logistics interface, fragmentation of Extended Producer Responsibility schemes in the pharmaceutical sector, and the lack of harmonised eco-modulation criteria for cold chain packaging at the European Union level. Full article

The study uses a case study (Parliament House, Ghana) to identify a sustainable energy pathway for public institutions in emerging economies, from technical and economic viewpoints, towards the net-zero agenda. Technically, the study uses GIS (Google Earth Pro, v7.3.7) mapping and Python (Jupyter notebook from Anaconda, v4.20) simulation to assess rooftop/carport solar PV–grid integration and explore green hydrogen and ammonia productions. It combines a GIS rooftop solar resources assessment with a forward/backward sweep hosting-capacity analysis and a cascaded economic comparison of grid, hydrogen (H₂), and ammonia (NH₃) to inform decisions about RE investment scenarios in Ghana. The economic assessment uses net present value (NPV), internal rate of return (IRR), profitability index (PI), discounted payback period (DPP), and levelized cost of energy (LCOE, LCOH, and LCOA). A 6.3 MW (10,569 MWh) solar electricity system is proposed to meet the 2.56 MW (7554 MWh) demand with 3014 MWh excess. Hydrogen and ammonia production stood at 60.3 tons and 343,579 kg from excess electricity, respectively. The facility’s CO₂ contribution in 25 years period with the grid supply is 160,539 tons, while with PV deployment, it can save 211,611 tons. A total of GHS 58,558,962 (GHS 36,306,556 for local demand and GHS 22,252,405 for grid sales), GHS 12,328,785, and GHS 43,805,636 are required to set up the solar PV, hydrogen, and ammonia plants, respectively. Results from 100% local consumption and grid sales scenarios indicate an NPV of GHS 106.91, an IRR of 75%, a payback period of 3 years, a profitability index of 3.1, and an LCOE of GHS 0.68. An NPV of GHS 84.57 million, IRR of 56%, PI of 3.8, DPP of 4 years, and LCOE of GHS 1.06/kWh were recorded for the grid sales. Hydrogen sales had a negative NPV of GHS 16.78 million, a PI of 0.7, and an LCOH of GHS 87.2 per kg. Similarly, a negative NPV of GHS 70.72 million, a PI of 0.27, and an LCOA of GHS 29,419.55 per ton were recorded for the ammonia sales. The Parliament House can save 106.91 million GHS over 25 years if it chooses to go solar after meeting its local requirements. Results from the Python simulation show a 5.6% reduction in bus voltage for the system without PV, while the configuration with PV injections saw a voltage increase of up to 11.4%. The system loss increased 113.3 kW in case 1 to 1659.2 kW in case 2. Solar-to-grid is the recommended pathway, while H2/NH3 are not competitive under present costs. The sensitivity analysis shows that changes in key input variables (CAPEX, electricity input cost, and selling price) affect the prospective H₂/NH₃ sales under current market conditions in Ghana. Therefore, policymakers should make conscious efforts to lower these parameters (CAPEX and electricity input cost) to boost green hydrogen and ammonia penetration in the transition agenda. A new law is required to encourage consumers to sell to the grid rather than rely on the current net metering scheme, which limits prosumers’ generation to 500 kW and forbids grid sales. Full article

Sustainable reservoir-system management requires coordinated operation to balance economic benefits, sediment regulation, and ecological requirements while maintaining equitable and durable cooperation among participating reservoirs. Focusing on the Wanjiazhai, Sanmenxia, and Xiaolangdi reservoirs in the middle and lower Yellow River Basin, this study develops an integrated framework that links multi-objective reservoir operation, coordination-oriented scheme selection, and compensation allocation under representative dry, normal, and wet hydrological conditions. NSGA-II is used to identify Pareto trade-offs among sediment transport, electricity production, and ecological water-deficit control, while the coupling-coordination degree model is applied to select schemes with balanced overall performance. CRITIC-TOPSIS is then used to allocate compensation by integrating static engineering attributes with operation-induced dynamic responses. The results show that the maximum coupling-coordination degrees reach 0.81, 0.88, and 0.90 under dry, normal, and wet conditions, respectively. Compared with actual operation, the recommended schemes increase total electricity production while reflecting hydrologically dependent trade-offs in sediment transport and ecological water-deficit control. Xiaolangdi Reservoir consistently receives the largest compensation share, followed by Wanjiazhai Reservoir and Sanmenxia Reservoir, and this ranking remains consistent across alternative allocation methods. By linking operational trade-offs with reservoir-specific contributions and compensation priorities, the framework supports more adaptive and equitable joint operation and provides a quantitative decision-support approach for improving the long-term environmental, economic, and institutional sustainability of reservoir-system management in the Yellow River Basin. Full article

Within the framework of the United Nations Sustainable Development Goals (SDGs), the transition toward green and low-carbon development has achieved broad international consensus. Blockchain technology offers an effective instrument for surmounting the trust bottleneck in low-carbon products; however, its substantial costs and market uncertainty constrain firm adoption. By developing a decision model for blockchain traceability investment and pricing of low-carbon products under various combinations of manufacturer risk preferences and government subsidies in a dual-channel supply chain, this study investigates the composite mechanisms through which government subsidies, channel structure, and risk aversion preferences jointly shape traceability investment and pricing decisions. The principal findings are as follows. The manufacturer’s traceability investment is synergistically promoted by consumer trust and the direct channel proportion through a “market pull–channel push” mechanism, yet is suppressed by risk aversion; furthermore, excessive risk aversion attenuates the incentive effect of consumer trust. The optimal design of government subsidies must be calibrated to the direct-channel share and risk preference characteristics, with higher subsidies warranted under “low direct-channel share–high risk aversion” conditions. Bilateral risk aversion intensifies the conservative strategic orientation across the supply chain, necessitating adaptive adjustments to subsidy levels by the government. This study furnishes theoretical underpinnings for corporate decision-making regarding blockchain traceability investments in low-carbon products and for the design of differentiated government subsidy schemes, thereby holding positive implications for advancing digital technology deployment in low-carbon product supply chains and fostering sustainable consumption. Full article

Drought is one of the most damaging abiotic stresses affecting global crop productivity, and its frequency and severity are projected to increase under ongoing climate change. Silicon (Si), although not classified as an essential nutrient, is increasingly regarded as a “quasi-essential” beneficial element that improves crop performance under water-limited conditions. This review summarises the physiological mechanisms of Si-induced drought tolerance, based mainly on literature published in the past five years. Rather than presenting these mechanisms as an inventory of separate physiological effects, the review reframes them as a coordinated stress-tolerance network linked by shared transcriptional regulation, and it organises the evaluation around three conceptual tensions that remain unresolved in the literature: the opposite direction of Si’s effect on transpiration, the extent to which Si-accumulating grasses and Si-excluding dicots rely on equivalent mechanisms, and the non-linearity of dose responses. Si uptake and transport via Lsi1, Lsi2, and Lsi6, and the resulting difference between Si-accumulating and Si-excluding species, are discussed together with the enhancement of root growth and aquaporin-mediated hydraulic conductance; stomatal and photosynthetic regulation; osmotic adjustment through compatible solute accumulation; enzymatic and non-enzymatic antioxidant defence; hormonal signalling involving abscisic acid, jasmonic acid, ethylene, and auxin; reinforcement of cell walls and vascular tissue; and the transcriptional networks coordinating these responses. Si’s influence on rhizosphere nutrient dynamics and the dependence of its efficacy on genotype, dose, and application method are also considered. A consolidated mechanistic scheme is presented, showing how these pathways converge on a drought-tolerant phenotype characterised by sustained growth, improved water-use efficiency, and faster recovery. Future research priorities, including field validation, standardisation of application protocols, multi-omics integration, and Si–microbiome interactions, are outlined to support the translation of these mechanistic insights into practical drought-management strategies. Full article

Hydrogen is acknowledged as a clean and sustainable energy source due to the increasing demand for renewable energy sources. Photoelectrochemical (PEC) water splitting presents a viable approach for directly producing hydrogen from solar energy with negligible implications for the environment. However, regardless of the intensive studies over several years, a major hurdle to translating impressive laboratory-scale efficiency into robust, dependable, large-scale production of hydrogen is increasing competition from quickly advancing photovoltaic (PV)–based electrolysis technology. In parallel, Z-scheme or S-scheme artificial leaf catalyst systems mimicking photosynthesis are gaining ground in the research community. The performance and reliability of photo-electrocatalytic large-scale hydrogen production should be evaluated via pilot-scale and field studies, along with life cycle and economic studies. In the present manuscript, a comprehensive overview of technologies related to scalability is presented, with a focus on semiconductor materials and reactor design. In conclusion, problems and opportunities for future research on large-scale production technologies are presented. Full article

Rwanda’s sustainable green economy agenda has placed irrigation and input-support schemes at the centre of efforts to raise tropical fruit productivity in the Mugesera region, yet the econometric analysis presented, in a Cobb–Douglas production function estimated by panel OLS and a Nerlove partial-adjustment model of agricultural supply response required the analyst to pre-specify a log-linear, constant-elasticity functional form. This paper asks whether machine learning methods that learn input–output relationships directly from data can cross-check those findings, and presents a documented Python version 3.10.12 pipeline for doing so. Using a synthetic panel dataset (six regions, 2009–2018, N = 346 farm-year observations) calibrated to match the elasticity magnitudes reported in the original Cobb–Douglas estimation, three models—multiple linear regression, random forest, and gradient boosting—are trained on land, fertilizer, seed, lagged price, and lagged output features, and are evaluated on held-out data. All three models explain a substantial share of variation in output (R² between 0.72 and 0.75 under a random split; for results under panel-aware validation), with tuned gradient boosting achieving the best accuracy under the random split (R² = 0.751, RMSE = 0.268). Permutation feature importance recovers the same relative ranking of input variables as the original regression—fertilizer, then seeds, then land area—without the model being given the Cobb–Douglas functional form in advance. Because the synthetic data were explicitly generated to reproduce these elasticities, this recovery demonstrates that the modelling pipeline behaves as intended; it is a calibrated methodological demonstration and not an independent empirical validation of the original findings. The results are consistent with lagged price and output operating mainly through farmers’ input decisions rather than as direct predictors of output once input quantities are known, although we present this as a hypothesis for future testing rather than a demonstrated finding. Re-running the identical pipeline on real Mugesera farm-level survey microdata is the necessary next step before these results can be treated as genuine empirical findings; this caveat applies to every quantitative result reported below, not only to the conclusion. Full article

The transition to sustainable energy is critical for addressing global climate change. Hydrogen production, particularly via electrolysis, has emerged as a key solution, offering the potential for low-carbon energy across various sectors. This paper conducts a spatiotemporal life cycle analysis of electrolytic hydrogen production in Australia under time-varying CO₂ management schemes. Three scenarios are studied. The baseline scenario studies hydrogen production at a fixed rate of 20 kg/h, resulting in monthly carbon emissions of 30–500 metric tons of CO₂, depending on the Australian state and chosen month. Variable production scenario 1 reduces hydrogen production in a tiered fashion as the grid’s carbon intensity increases, resulting in monthly carbon emissions of 30–110 metric tons of CO₂, depending on the Australian state and chosen month. Finally, variable production scenario 2 restricts hydrogen production to periods when the life cycle carbon intensity (LCA CO₂eq) of electricity falls below a predefined threshold of 0.6 kg CO₂ per kg H₂, thereby qualifying for hydrogen tax credits and resulting in monthly carbon emissions of 0.1–0.6 metric tons of CO₂ in Tasmania. Leveraging real-time data from the Electricity Mapping database and real-time electricity cost data from the AEMO database, the three scenarios study the effect of dynamically adjusting hydrogen output to reduce both emissions and production costs. Furthermore, the integration of hydrogen tax credits significantly enhances cost-effectiveness, offering a viable pathway for widespread adoption. This study concludes that dynamic, real-time operation, coupled with financial incentives, offers a promising approach to enhancing the sustainability and economic viability of hydrogen production. Full article

The occurrence characteristics of impurities and the precise technologies used for their removal are the main factors limiting the high-end applications of quartz sand. To simultaneously achieve ultrahigh purity and a high yield while incorporating a sustainable waste acid treatment strategy, quartz sand (SP1) from India was selected as the research material. A stepwise experimental scheme involving single-acid and mixed-acid treatments was adopted to optimize the purification conditions, incorporating a complete process of pretreatment, acid leaching, and post-treatment along with a defined waste liquid management method. The raw SP1 quartz samples and samples treated under the optimal acid-washing conditions were characterized through qualitative and quantitative analyses, including X-ray diffraction, Raman spectroscopy, scanning electron microscopy, and inductively coupled plasma mass spectrometry. The optimal result for the single-acid system was obtained by treating quartz sand with 70 mL of hydrofluoric acid at 120 °C for 2 h, resulting in a purity of 99.9963%. For the mixed-acid system, the volume ratio of hydrofluoric acid, hydrochloric acid, and nitric acid was maintained at 1:6:2, and acid leaching was performed at a constant temperature of 120 °C for 5 h. Under these conditions, the aluminum and iron contents were reduced to 15.23 and 0.15 μg/g, respectively, while the purity and production yield of the acid-washed quartz sand reached 99.9964% and 82.11%, respectively. Based on comprehensive consideration of the purification effectiveness and process economy, an HF:HCl:HNO₃ volume ratio of 1:6:2 and an acid-washing reaction time of 5 h were selected, providing a stable purity exceeding 99.996%. This study provides a theoretical and technical basis for the standardized and sustainable production of high-purity quartz sand. Full article

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation. Full article

This research proposes an approach based on a circular economy principle for the integral valorization of Sargassum from the Mexican Caribbean. The biomass was characterized through proximal and elemental analyses, and then an oxidative pretreatment was carried out to enhance a sequential processing scheme to extract sodium alginate and use the solid waste as a substrate for biogas production via anaerobic digestion. The oxidative pretreatment successfully reduces the recalcitrant content and the concentration of heavy metals. The sodium alginate extracted from treated biomass achieves a yield higher than 20%; the characterization of the polymer via nuclear magnetic resonance showed that the mannuronic-to-guluronic ratio was between 0.34 and 0.62, indicating the potential for its use for environmental and biomedical applications. The highest yield in methane production was 328 mL CH₄/g of volatile solids, with a purity of 90%, and was achieved using the waste from alginate extraction with an inoculum-to-substrate ratio of 1:1. The experimental data presented an excellent fit to a Gompertz model (R² > 0.99). The proposed valorization pathway improves the sustainability of Sargassum management, prioritizing the recovery of high-value compounds before energy production. This circular approach provides a framework for converting environmental challenges into opportunities in the Caribbean. Full article

Existing industrial buildings represent a critical but under-addressed field for operational carbon emission reduction, as retrofit decisions are constrained by production continuity, limited investment capacity, and heterogeneous technical options. This study developed a decision support framework integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to evaluate and prioritize operational phase decarbonization retrofit schemes for existing industrial buildings. The framework was applied to the Thyssenkrupp S Plant in eastern China, where ten candidate schemes were identified through an energy audit, on-site investigation, and expert consultation. The results show that heating, ventilation, and air conditioning (HVAC) operational control and temperature set-point optimization ranked first, followed by lighting operational management and automatic control. These management-based measures offer strong near-term applicability because of their low investment, short payback periods, limited implementation disturbance, and immediate emission reduction benefits. Their sustained effectiveness, however, requires standardized procedures, staff education, energy monitoring, and appropriate automation. Rooftop photovoltaics provide the largest annual carbon reduction but have a lower short-term priority because of their high upfront investment. Expert-consistency testing and sensitivity analyses, including criterion weight perturbation, preference scenarios, and Monte Carlo simulation, support the robustness of the leading ranking pattern. The findings support staged retrofit planning that prioritizes durable management measures in the short term, equipment-level efficiency improvements in the medium term, and renewable energy deployment in the long term. Full article

This study assessed the current status of irrigation systems and water management practices in Rwanda’s irrigated agricultural zones, focusing on the Nasho Government-Funded Irrigation (GFI) scheme in Kirehe District and the Kagitumba Irrigation Scheme in Nyagatare District. A mixed descriptive approach was used, combining field observations with structured questionnaires administered via KoboToolbox to 224 respondents in Nasho and 188 in Kagitumba. Field observations were used to evaluate the physical condition and functionality of irrigation infrastructure, while questionnaires captured stakeholder perceptions, water management practices, institutional arrangements, and operational challenges. Results show that both irrigation schemes are operational but function below optimal efficiency due to multiple constraints. In Nasho, irrigation performance is primarily affected by sedimentation in canals and reservoirs, pump inefficiencies, and inadequate maintenance practices, resulting in unreliable water delivery. In Kagitumba, despite the use of modern center pivot systems, performance is constrained by pipeline corrosion, pressure losses, sediment-laden water, and uneven water distribution. Across both schemes, more than 80% of respondents reported frequent system failures, while over 95% indicated the absence of formal irrigation scheduling practices. Water management remains largely reactive, with limited preventive maintenance and weak technical capacity among users and institutions. The study concludes that improving irrigation efficiency in Rwanda requires integrated interventions that combine infrastructure rehabilitation, strengthened maintenance systems, improved water governance, and farmer capacity development to enhance sustainable water use and agricultural productivity. Full article

Urban and peri-urban regions increasingly face climate-related pressures, competing land-use demands, and the need to expand renewable-energy infrastructure while maintaining agricultural land and landscape functions. Agrivoltaics, which combines photovoltaic energy generation with agricultural production, represents a potentially multifunctional approach to land use; however, regional GIS assessments often stop at environmental suitability surfaces without translating those results into planning-relevant cadastral inventories. This study develops and applies a planning-oriented Geographic Information System (GIS) framework for preliminary statewide agrivoltaic screening in Connecticut. Annual global solar radiation and terrain slope were integrated through a weighted suitability model, while incompatible land-cover classes were treated as hard exclusions through a binary land-cover mask. The workflow subsequently excluded protected and open-space lands, associated suitable areas with cadastral parcels, normalized and dissolved parcel identifiers using ParcelKey, and a recalculated suitable area from the resulting unique parcel geometries and then applied a minimum requirement of 1 ha of cumulative suitable area per retained parcel. The final baseline inventory contained 3497 normalized unique cadastral parcels encompassing 16,366.49 ha of GIS-identified suitable area, with suitable land representing an average of 42.46% of total parcel area. Peri-urban contexts accounted for the largest share of the final suitable area, containing 2497 parcels and 73.16% of the total, compared with 476 urban and 524 rural parcels. Sensitivity analysis indicated strong stability under alternative weighting schemes, with spatial overlap exceeding 99% relative to the baseline. Reducing the suitability-score threshold from 3.0 to 2.5 produced only minor changes, whereas increasing it to 3.5 reduced the inventory to 3095 parcels and 13,712.89 ha. From a sustainability perspective, the framework provides a spatial decision-support approach for coordinating renewable-energy planning with agricultural land stewardship, conservation constraints, and more efficient use of already fragmented land resources. By making the effects of exclusions, parcel thresholds, and analytical assumptions explicit, the approach supports more transparent and reproducible evaluation of land-use trade-offs relevant to sustainable development. The resulting inventory is intended as a first-stage planning resource rather than a determination of project feasibility or site-level sustainability performance. Full article

Recent advances in numerical modelling, remote sensing, and artificial intelligence are bringing a transformation in our ability to assess sediment transport. Nevertheless, climate change is fundamentally altering sediment production, transport, and deposition through intensifying hydrological extremes, sea-level rise, changing storm regimes, cryosphere degradation, and increasing human modification of sediment pathways. These interacting drivers challenge conventional sediment transport assessment, which has largely evolved within separate fluvial, estuarine, coastal, and marine disciplines and often lacks an integrated perspective capable of representing source-to-sink sediment connectivity under non-stationary environmental conditions. Although significant advances have been made in process-based numerical modelling, Earth observation, and artificial intelligence (AI), these approaches are commonly reviewed independently, limiting their collective application to regional climate-responsive sediment assessment. This review examines state-of-the-art process-based numerical models, observational tools, and machine-learning approaches for sediment transport from source-to-sink. A transparent benchmarking scheme is used to compare leading modelling systems (e.g., AdH, SRH-2D, FLO-2D, HEC-RAS, TELEMAC, Delft3D, EFDC, SCHISM, XBeach, ROMS), highlighting differences in dimensionality, sediment-process representation, computational demands, and climate-scenario readiness. Remote sensing (optical, SAR, LiDAR, UAV) and AI/ML/DL methods (e.g., random forests) are reviewed as complementary tools that enhance model parametrization, improve validation, and address uncertainty in data-limited regions. A reproducible bibliometric synthesis based on Dimensions.ai records (2000–2026) reveals accelerating growth in sediment-transport research, with strong recent expansion in coastal, estuarine, and data-driven modelling applications. Major challenges include cohesive sediment physics, cross-environment coupling, limited long-term validation datasets, and the need for scalable workflows compatible with climate-model forcing. In this manuscript, we analyse and propose a future roadmap for near-term integration of satellite–field data streams, medium-term development of hybrid physics–AI models, and long-term coupling of sediment modules within Earth-system and regional climate frameworks. Collectively, this review provides a foundation for next-generation, climate-responsive sediment transport assessment supporting sustainable river basin and coastal management. Full article