Search Results (472)

This study is an economic evaluation of a composting facility in southeastern Spain (applying Life Cycle Costing), a key region in European horticulture with a significant availability of agricultural biomass. Composting helps reduce dependence on inorganic fertilizers, aligning with European policies that promote the transition toward organic fertilization practices. In addition, compost enhances soil health, increases soil organic carbon, and supports climate change mitigation. Despite its agronomic and environmental benefits, and the large availability of biomass in this region, there is a notable lack of literature addressing the economic costs of composting, which is the first step in assessing the sustainability of a production process. The proposed facility (production: 9000 tonnes of compost per year) utilizes pruning residues and manure to produce high-quality organic amendments. The analysis includes infrastructure, equipment, and every operational input. Likewise, the analysis also provides socio-economic indicators such as employment generation and contribution to the regional economy. Three scenarios were evaluated based on the pruning–shredding location: at the plant, at the farm with mobile equipment, and at the farm with conventional machinery. The most cost-effective option was shredding at the farm using mobile equipment, reducing the unit cost to EUR 65.19 per tonne due to the transport of a smaller volume of prunings and, therefore, lower fuel consumption. The plant also demonstrates high productivity per square metre and generates stable employment in rural areas. Overall, the findings highlight composting as a viable and competitive strategy within circular and low-carbon agricultural systems. Full article

Gas injection is a well-established method for enhancing oil recovery by improving oil mobility, primarily through viscosity reduction. While its application in heavy oil reservoirs is extensively studied, the specific impact of carbon dioxide (CO₂) injection pressure on fluid viscosity reduction and the ultimate recovery factor from light oil reservoirs has not been fully investigated. To address this gap, this experimental study systematically explores the effects of CO₂ injection pressure and reservoir permeability on light oil recovery. This study conducted miscible, near-miscible, and immiscible gas injection experiments on two core samples with distinct permeabilities (13.4 md and 28 md), each saturated with light oil. CO₂ was injected at five different pressures, including conditions ranging from immiscible to initial reservoir pressure. The primary metrics for evaluation were the recovery factor (measured at gas breakthrough, end of injection, and abandonment pressure) and the viscosity reduction of the produced oil. The results conclusively demonstrate that CO₂ injection significantly enhances light oil production. A direct proportional relationship was established between both the injection pressure and the recovery factor and between permeability and overall oil production at the gas breakthrough. However, a key finding was the inverse relationship observed between permeability and viscosity reduction: the lower-permeability sample (13.4 md) consistently exhibited a greater percentage of viscosity reduction across all injection pressures than the higher-permeability sample (28 md). This unexpected trend is aligned with the inverse relationship between the permeability and the recovery factor after the gas breakthrough. This outcome suggests that enhanced CO₂ solubility, driven by higher confinement pressures within the nanopores of the lower-permeability rock, promotes a localized, near-miscible state. This effect was even evident during immiscible injection, where the low-permeability sample showed a noticeable viscosity reduction and superior long-term production. These findings highlight the critical role of pore-scale confinement in governing CO₂ miscibility and its associated viscosity reduction, which should be incorporated into enhanced oil recovery design for unconventional reservoirs. Full article

The accelerating global transition to electric mobility demands data-driven infrastructure planning that balances technical, economic, and spatial considerations. This study develops a scenario-based demand and economic modeling framework to estimate electric vehicle (EV) charging infrastructure needs across Abu Dhabi’s urban and rural regions through 2050. Two adoption pathways, Progressive and Thriving, were constructed to capture contrasting policy and technological trajectories consistent with the UAE’s Net Zero 2050 targets. The model integrates regional travel behavior, energy consumption (0.23–0.26 kWh/km), and differentiated charging patterns to project EV penetration, charging demand, and economic feasibility. Results indicate that EV stocks may reach 750,000 (Progressive) and 1.1 million (Thriving) by 2050. The Thriving scenario, while demanding greater capital investment (≈108 million AED), yields higher utilization, improved spatial equity (Gini = 0.27), and stronger long-term returns compared to the Progressive case. Only 17.6% of communities currently meet infrastructure readiness thresholds, emphasizing the need for coordinated grid expansion and equitable deployment strategies. Findings provide a quantitative basis for balancing economic efficiency, spatial equity, and policy ambition in the design of sustainable EV charging networks for emerging low-carbon cities. Full article

Zinc (Zn) in excess is very toxic for plants and can limit agriculture. Carbon-based engineered nanomaterials with high electron mobility and electron-accepting capability may be essential for mitigating heavy metal stress. In the present study, the protective role of some fullerene C₆₀ derivatives (fullerenol [C₆₀(OH)_22–24] and the arginine C₆₀ [C₆₀(C₆H₁₃N₄O₂)₈H₈]) were tested for the first time against Zn toxicity in Cucumis sativus L. (cucumber). Plants were grown hydroponically at three concentrations of fullerenes (0, 2, and 10 mg L⁻¹) without or with 40 µM Zn for 17 days. Plant growth, leaf chlorosis, and nutritional imbalances in combination with a metabolomics approach were analyzed. The Zn-treated plants show chlorotic leaves, the retarded growth of shoots (−20%), and roots (−49%) and nutrient imbalance. Addition of fullerene C₆₀ derivatives suppressed loss in the dry biomass of leaves (15%) and roots (40%; fullerenol only) induced by high Zn. However, they did not alter leaf chlorophyll, shoot dry biomass, and elemental composition, including leaf Zn. Moreover, the Zn of xylem sup from roots remained unchanged by fullerenes. In an adsorption experiment, the amounts of Zn adsorbed by tested C₆₀ were below the detection limits. The addition of C₆₀ derivatives slightly changed the metabolite profiling in stressed plants. Nevertheless, in fullerene-treated plants, the abundance of some Zn-responsible metabolites tended to be altered in the opposite direction as compared with the metabolic responses to excessive Zn alone. There were several up-regulated metabolites protecting plants under oxidative stress. We speculate that fullerene C₆₀ derivatives have the ability to increase antioxidant non-enzyme activity at least, improving some growth parameters. However, fullerenes did not reduce Zn transport from the root to the shoots. We concluded that the low capacity of these compounds to buffer Zn in the root zone might limit the efficiency of fullerene derivatives against Zn toxicity. Our results provide new evidence for the crucial role of Zn–fullerene interactions in the amelioration of Zn toxicity in plants. Full article

Against the backdrop of rising global carbon emissions, promoting active transportation modes such as walking and cycling has become a key strategy for countries worldwide to meet carbon reduction targets and advance the goals of sustainable development. In China, the concept of low-carbon mobility has gained rapid traction, leading to a significant increase in public demand for non-motorized travel options like walking and cycling. From the perspective of inclusive urban development, gender imbalances in sample representation during design and evaluation processes have contributed to homogenization and a lack of diversity in urban slow-traffic environments. To address this issue, this study adopts a problem-oriented approach. First, we collect street scene images of slow-traffic environments through self-conducted field surveys. Concurrently, we gather satisfaction survey responses from 511 urban residents regarding existing slow-traffic streets, identifying three key environmental evaluation indicators: safety, liveliness, and beauty. Second, an experimental analysis is conducted to compare machine-generated assessments based on self-collected street view data with manual evaluations performed by 27 female participants. The findings reveal significant perceptual differences between genders in the assessment of slow-moving environments, particularly regarding attention to environmental elements, challenges in utilizing non-motorized lanes, and overall environmental satisfaction. Moreover, notable discrepancies are observed between machine scores and manual assessments performed by women. Based on these findings, this study investigates the underlying causes of such perceptual disparities and the mechanisms influencing them. Finally, it proposes female-inclusive strategies aimed at enhancing the quality of slow-traffic environments, thereby addressing the current absence of gender considerations in their design. This research seeks to provide a robust female perspective and empirical evidence to support improvements in the quality of slow-moving environments and to inform strategic advancements in their design. The findings of this study can provide a theoretical and empirical basis for the optimization of gender-inclusive non-motorized transportation environment design, policy formulation, and subsequent interdisciplinary research. Full article

This paper presents a theoretical and empirical analysis of how banks apply artificial intelligence (AI) in digital and mobile banking to implement and communicate ESG (Environmental, Social, and Governance) strategies, with particular emphasis on environmental dimensions of sustainable finance. The study adopts a mixed methodological approach combining desk research, encompassing a synthesis of academic studies, industry reports, and European regulatory frameworks on AI and ESG, and case study analysis of selected banks implementing AI-based sustainability solutions. The findings reveal that AI supports ESG strategy implementation primarily through green investment recommendations, carbon footprint analytics, automated sustainability reporting, and ethical communication with clients. AI-driven tools enhance the operational efficiency, transparency, and customer engagement of financial institutions while simultaneously fostering low-carbon financial behaviors. However, the study also highlights ethical and governance challenges related to algorithmic transparency, data bias, and responsible AI oversight. The paper contributes to the growing body of literature on AI-driven digital transformation and sustainable finance by identifying research gaps and outlining future directions for exploring the role of AI in accelerating the transition of the banking sector. Full article

This study presents a systematic approach for converting low-grade carbon derived from mining waste into functional carbon–zeolite composites with enhanced adsorption performance. To promote carbon deposition within and around zeolite frameworks, four industrially relevant zeolites, including zeolite socony mobil-5 (ZSM-5), Faujasite-type zeolite (Zeolite-Y), beta zeolite (Zeolite-β), and mordenite (MOR), were mechanically mixed with low-grade carbon under controlled stirring conditions (24 h at 250 rpm) and subsequently pyrolyzed at 800 °C. These treatments enabled a detailed assessment of structural stability and carbon–zeolite interactions. Scanning electron microscopy revealed pronounced modifications in surface morphology and carbon distribution after carbon treatment, while X-ray diffraction confirmed that the crystalline zeolite frameworks remained structurally intact despite the deposition of amorphous carbon. The adsorption performance of the resulting composites was evaluated through CO₂ adsorption measurements under controlled temperature and pressure conditions, demonstrating a clear enhancement relative to the pristine zeolites. Overall, this work highlights an effective strategy for valorizing low-grade carbon waste into high-performance carbon–zeolite hybrid adsorbents and provides new mechanistic insights into framework stability, selective atom removal, and carbon–zeolite interactions in high-temperature and acidic environments. Full article

Sustainable transport innovation often faces funding gaps, as traditional public and private sources rarely support early-stage or high-risk initiatives. Crowdfunding, enabled by digital transformation, is emerging as a complementary financing mechanism for this sector. This study presents a literature review combined with bibliometric mapping to examine the evolving research landscape on crowdfunding in transport. Three research questions guide the analysis: RQ1—What are the dominant research areas at the intersection of crowdfunding and transport? RQ2—What types of transport projects are financed via crowdfunding? RQ3—What research gaps and future directions emerge for transport innovation financing? Findings reveal three core research areas: (1) Sustainability and finance, (2) Fintech and blockchain, and (3) Management and consumer behavior. We propose a typology of crowdfunded transport projects comprising five categories: (1) Large-scale transport infrastructure, (2) Sustainable local mobility, (3) Innovative start-ups, (4) New business models, and (5) Advanced systems and technologies. This demonstrates crowdfunding’s versatility beyond traditional infrastructure, supporting high-risk innovations critical for decarbonization and technological transformation. The study highlights domain-specific challenges—such as integrating PPP models with digital finance and ensuring investor protection—and emphasizes crowdfunding’s role as an enabler of low-carbon transition aligned with global climate strategies (EU Green Deal, SDGs). Despite its potential, investor safety remains a major concern. Policy implications include sandbox regulation, standardized risk assessment, and operationalizing PPP–crowdfunding hybrids to unlock large-scale and innovative transport projects. Full article

Road transport systems are central to sustainable mobility and the energy transition because they account for a large share of final energy use and remain heavily dependent on fossil fuels. With more than 90% of transport energy still supplied by petroleum-based fuels, improving energy efficiency and reducing emissions in road networks has become a strategic priority. This review compares Australia, Hong Kong, and the United Kingdom to examine how road-design standards and emerging digital technologies can improve energy performance across planning, design, operations, and maintenance. Using Australia’s Austroads Guide to Road Design, Hong Kong’s Transport Planning and Design Manual (TPDM), and the UK’s Design Manual for Roads and Bridges (DMRB) as core reference frameworks, we apply a rubric-based document analysis that codes provisions by mechanism type (direct, indirect, or emergent), life-cycle stage, and energy relevance. The findings show that energy-relevant outcomes are embedded through different pathways: TPDM most strongly supports urban operational efficiency via coordinated/adaptive signal control and public-transport prioritization; DMRB emphasizes strategic-network flow stability and whole-life carbon governance through managed motorway operations and life-cycle assessment requirements; and Austroads provides context-sensitive, performance-based guidance that supports smoother operations and active travel, with implementation varying by jurisdiction. Building on these results, the paper proposes an AI-enabled benchmarking overlay that links manual provisions to comparable energy and carbon indicators to support cross-jurisdictional learning, investment prioritization, and future manual revisions toward safer, more efficient, and low-carbon road transport systems. Full article

E-bikes are emerging as a competitive alternative to private cars in both urban and suburban contexts, enhancing accessibility to daily amenities and aligning with the proximity-oriented principles of X-minute city development. However, empirical knowledge remains limited regarding e-bike adopter profiles, trip purposes, influencing factors, and modal substitution patterns, particularly in urban Global South contexts. This exploratory pilot study employs correlation analysis and exploratory factor analysis to examine the sociodemographic characteristics of e-bike users in Surabaya, identify trip behavior patterns, and uncover potential determinants associated with e-bike usage within the X-minute city framework. Based on a sample of 71 e-bike users, the preliminary findings reveal notable socioeconomic patterns in e-bike adoption, with lower-income inner-city residents, particularly women in informal employment, emerging as early adopters. Additionally, two potential influence dimensions are identified: utilitarian trip chaining and active mobility infrastructure. While these findings require validation through larger-scale studies, they suggest potential for e-bikes to expand feasible X-minute city catchments and support low-carbon mobility transitions in similar Global South contexts. Full article

On-demand public transport systems are increasingly adopted to improve service flexibility, reduce operating costs, and meet emerging mobility needs. Evaluating their performance under realistic demand and operational conditions, however, remains a complex challenge. This study presents a hybrid simulation framework that integrates deep learning-based demand forecasting, behavioural survey data, and agent-based simulation to assess system performance. A BiLSTM neural network trained on real-world smartcard data forecasts short-term passenger demand, which is embedded into an agent-based model simulating vehicle dispatch, routing, and passenger interactions. The framework is applied to a case study in Melbourne, Australia, comparing a baseline fixed-route service with two on-demand scenarios. Results show that the most flexible scenario reduces the average passenger trip time by 32%, decreases the average wait time by 34%, increases vehicle occupancy from 12.1 to 18.6 passengers per vehicle, lowers emissions per passenger trip by 72%, and cuts the service cost per trip from AUD 6.82 to AUD 4.73. These findings demonstrate the potential of hybrid on-demand services to improve operational efficiency, passenger experience, and environmental outcomes. The study presents a novel, integrated methodology for scenario-based evaluation of on-demand public transportation using real-world transportation data. Full article

Hazardous galvanic sludge waste (GSW) from the electroplating industry, produced at 100,000–150,000 tonnes/year in the EU and containing high concentrations of Cr and Ni was successfully treated using metakaolin-based geopolymers via Stabilization/Solidification (S/S). The experimental design incorporated chelating (sodium diethyl dithio carbamate, C₅H₁₀NS₂Na, DTC), reducing (sodium sulfide, Na₂S), and adsorbing (hydroxyapatite, Ca₅(PO₄)₃(OH), Hap) agents separately to improve heavy metal immobilization. The results demonstrated that Na₂S drastically decreased Cr release by −98.7% by reducing mobile Cr(VI) to insoluble Cr(III). DTC reduced Ni leaching by −93.4%, forming sparingly soluble Ni(II)(DTC)₂ complexes that precipitated within the matrix. Hap enhanced Ni retention by 55.5% via cation exchange but was ineffective for Cr due to electrostatic repulsion with the anion Cr(VI)O₄²⁻ at the geopolymer’s high pH. This work is the first to apply geopolymerization coupled with these chemical agents for S/S of as-received galvanic waste, offering a highly efficient, low-carbon strategy to manage this hazardous industrial residue. Full article

Accurate and efficient forest inventory methods are crucial for monitoring forest ecosystems, assessing carbon stocks, and supporting sustainable forest management. Traditional field-based techniques, which rely on manual measurements such as diameter at breast height (DBH) and tree height (TH), remain labour-intensive and time-consuming. In this study, we introduce and validate a fully open-source, low-cost terrestrial laser scanning system (LCA-TLS) built from commercially available components and based on the Livox Avia sensor. With a total cost of €2050, the system responds to recent technological developments that have significantly reduced hardware expenses while retaining high data quality. This trend has created new opportunities for broadening access to high-resolution 3D data in ecological research. The performance of the LCA-TLS was assessed under controlled and field conditions and benchmarked against three reference devices: the RIEGL VZ-1000 terrestrial laser scanner, the Stonex X120GO handheld mobile laser scanner, and the iPhone 15 Pro Max structured-light device. The LCA-TLS achieved high accuracy for estimating DBH (RMSE: 1.50 cm) and TH (RMSE: 0.99 m), outperforming the iPhone and yielding results statistically comparable to the Stonex X120GO (DBH RMSE: 1.32 cm; p > 0.05), despite the latter being roughly ten times more expensive. While the RIEGL system produced the most accurate measurements, its cost exceeded that of the LCA-TLS by a factor of about 30. The hardware design, control software, and processing workflow of the LCA-TLS are fully open-source, allowing users worldwide to build, modify, and apply the system with minimal resources. The proposed solution thus represents a practical, cost-effective, and accessible alternative for 3D forest inventory and LiDAR-based ecosystem monitoring. Full article

How to economically and effectively mobilize remaining oil and achieve carbon sequestration after water flooding in low-permeability, high-water-cut reservoirs is an urgent challenge. This study, focusing on Block Y of the Daqing Oilfield, employs numerical simulation to systematically reveal the synergistic influencing mechanisms of CO₂ flooding and geological storage. A three-dimensional compositional model characterizing this reservoir was constructed, with a focus on analyzing the controlling effects of key geological (depth, heterogeneity, physical properties) and engineering (gas injection rate, gas injection volume, bottom-hole flowing pressure) parameters on the displacement and storage processes. Simulation results indicate that the low-permeability characteristics of Block Y effectively suppress gas channeling, enabling a CO₂ flooding enhanced oil recovery (EOR) increment of 15.65%. Increasing reservoir depth significantly improves both oil recovery and storage efficiency by improving the mobility ratio and enhancing gravity segregation. Parameter optimization is key to achieving synergistic benefits: the optimal gas injection rate is 700–900 m³/d, the economically reasonable gas injection volume is 0.4–0.5 PV, and the optimal bottom-hole flowing pressure is 9–10 MPa. This study confirms that for Block Y and similar high-water-cut, low-permeability reservoirs, CO₂ flooding is a highly promising replacement technology; through optimized design, it can simultaneously achieve significant crude oil production increase and efficient CO₂ storage. Full article

Electrifying port horizontal transportation is constrained by downtime and deadheading from fixed charging/swapping systems, large battery sizes, and the lack of integrated decision tools for life-cycle emissions. This study develops a carbon-efficiency-centered bi-objective optimization framework benchmarking Mobile Charging Stations (MCSs) against Fixed Charging Stations (FCSs) and Battery Swapping Stations (BSWSs). The framework integrates operational parameters such as charging power, range, dispatch, and non-operational mileage, along with grid carbon intensity, battery embodied emissions, and carbon-market factors. It generates Pareto fronts using the NSGA-II algorithm with real port data. Port horizontal transportation refers to the movement of goods within the port area, typically involving the use of specialized vehicles to transport containers short distances across the terminal. Results show that MCSs can reuse idle windows to reduce deadheading and infrastructure demand, yielding significant economic improvements. The trade-off between emissions and profitability is context-dependent: at low-to-moderate reuse levels, low-carbon and profitable solutions coexist; beyond a threshold of approximately 0.5–0.75, the Pareto fronts shift to high emissions and high profits, highlighting the context-specific advantages of MCSs for port-infrastructure planning. MCSs thus provide context-dependent advantages over FCSs and BSWSs, offering practical guidance for port infrastructure planning and carbon-informed policy design. Full article