Recycling aluminum-rich drinking water treatment sludge into ceramic membranes: Fabrication process and environmental impact assessment

The recovery of valuable metals from e-waste leachates is essential for advancing circular economy strategies and reducing environmental risks. This study examined Low Density Concrete (LDC), a waste material, as a sustainable adsorbent for the recovery of Ni 2+ , Mn 2+ , Zn 2+ , and Fe 2+ /Fe 3+ . This is the first study that evaluated the performance of LDC in metal recovery from a real leachate produced by the anaerobic digestion of alkaline batteries and municipal solid waste. The one-factorial method was employed to find the effect of the pH and adsorbent mass on results. The adsorption behavior was then studied using three different isothermal models: Freundlich, Langmuir, and Temkin. The findings indicated that pH significantly influenced metal removal, with ion exchange predominating in acidic conditions (pH < 5) and adsorption-precipitation mechanisms becoming more significant near neutral pH. Optimal performance was achieved at pH = 7 and an adsorbent dosage of 0.10 g. The most significant parameter influencing metal removal efficiency was pH, as determined by ANOVA. To enhance process prediction, both Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models were developed. ANN had a better predictive accuracy ( r > 0.98) than RSM. Material characterization such as FTIR, SEM-EDS, and TGA, confirmed metal uptake and associated surface and structural changes. Finally, an environmental impact assessment using the Leopold Matrix indicated that LDC exhibits lower environmental impacts compared to conventional adsorbents. These findings support the potential of LDC as a green, low-cost material for metal recovery from complex e-waste leachates. • Recovered Ni 2+ , Mn 2+ , Zn 2+ , Fe 2+ /Fe 3+ ions from e-waste leachate using concrete waste. • LDC showed dual adsorption–ion exchange behavior under varying pH conditions. • ANN predicted adsorption capacity with r > 0.98, surpassing RSM performance. • Freundlich model confirmed multilayer adsorption on heterogeneous LDC surface. • EIA proved LDC greener than GO regarding water, energy, and human health impact.

Shipboard carbon capture and storage (SCCS) is a viable retrofit for maritime decarbonisation, yet its environmental and techno-economic performance remains under-quantified. This study links life-cycle assessment with life-cycle costing to evaluate SCCS across four fuel configurations comprising very low sulphur fuel oil (VLSFO), marine gas oil (MGO), liquefied natural gas (LNG), and methanol, analysed with/without capture. Fuel system boundaries follow International Maritime Organization guidance. The SCCS boundary covers post-combustion monoethanolamine (MEA) absorption, compression/liquefaction and onboard liquid CO 2 storage; one-off manufacture/transport/installation and periodic maintenance are included, whereas port offloading and downstream transport, storage or utilisation are excluded. To enhance generalisability, conservative settings are adopted, assuming post-combustion monoethanolamine at 1.5 kg/t CO 2 , 58% capture efficiency, 3.7 GJ/t CO 2 energy use, and a 30-year service life with 5-year maintenance. Under these settings, installing SCCS lowers well-to-propeller greenhouse-gas emissions by 48.8–49.5% across all fuels after including 8.5–9.2% SCCS self-emissions. These net reductions support technical feasibility through policy alignment, with attained Energy Efficiency Existing Ship Index decreasing and Carbon Intensity Indicator improving by up to two grades for representative container, bulk-carrier, and tanker vessels. MGO with SCCS attains decarbonisation comparable to methanol, hence the economic comparison focuses on these two pathways. Over 30 years, MGO with SCCS is 7.1% less costly, with fuel prices the primary driver. Probabilistic analysis indicates SCCS on MGO is the lower-cost option in 69.8% of cases. Overall, within the stated boundary, the findings demonstrate the significance and effectiveness of SCCS for ship decarbonisation. • Study links life cycle assessment and costing for ship carbon capture and storage. • Shipboard carbon capture cuts well-to-propeller emissions by 48.7% to 49.5%. • Carbon capture on ships helps meet 2030 International Maritime Organization rules. • Marine gas oil with carbon capture costs 7.4% less than that of methanol conversion. • Shipboard carbon capture is the lower-cost option in 81.7% of cases studied.

The construction industry produces a large amount of carbon emissions, with a significant portion attributed to embodied carbon (EC). Prefabrication has the potential to reduce EC through streamlined workflows and controlled production environments. However, inefficiencies such as rework, material waste, excessive labor input, and quality issues can offset these benefits, necessitating a flexible digital technology approach. This study proposes the integration of mixed reality (MR) into prefabrication workflows to mitigate these issues and reduce EC emissions. A hybrid input-output (I-O) life cycle assessment (LCA) model combined with Monte Carlo (MC) simulation was employed to evaluate EC emission under uncertainty. Four prefabrication scenarios representing increasing levels of MR integration, ranging from conventional methods to high-level digitalization, were analyzed across several life cycle stages. Results emphasize that EC emissions were reduced by 8.5%, 14.9%, and 21.2% in the Lower, Medium, and Higher MR scenarios, respectively, due to significant reductions in rework, rejections, labor hours, and energy use. MC simulation confirmed the robustness of the results, showing decreased variability and tighter confidence intervals with higher levels of MR integration. While the experimental context focuses on precast panel production, the proposed approach is generalizable to broader prefabrication systems with appropriate adaptations to the MR model. This study contributes to the body of knowledge by introducing a novel integration of MR with hybrid I-O LCA for EC accounting in prefabrication and by demonstrating how MC simulation enhances the reliability of environmental impact assessments under uncertainty. The proposed hybrid I-O LCA approach offers a replicable and data-driven method for sustainable decision-making in construction engineering and management.

Marine nematodes, the most abundant meiofauna in benthic ecosystems, drive critical nutrient cycling and carbon sequestration, yet accurate biomass estimation remains challenging due to morphological variability and reliance on simplistic geometric models like Andrássy's formula, which introduced systematic biases across taxa. This study developed RAH NemaCalc, an open-source Python-based tool with Tkinter GUI and OpenCV integration, that semi-automates morphometric analysis by segmenting nematodes into 5–20 conical frustums based on length-diameter ratios, calculating lateral surface area with morphology-specific correction factors (ktotal and frustum geometry factor f), and converting to biomass using an empirically determined density of 1.08 g/cm 3 derived from sucrose gradient centrifugation of 50 genera. The tool processed high-resolution images of 187 specimens from diverse habitats- 50 from Lakshadweep Islands, 87 from Clarion-Clipperton Zone abyssal sediments, and 50 from the Nemys database yielding processing times of 1.8–2.1 s/image with manual contour verification. Key results showed the frustum method produced significantly different biomass estimates from Andrássy (Wilcoxon p < 0.0001 across datasets), with median volume reductions of 20–28% in coastal/abyssal samples but up to 260% higher biomass in large tapered genera like Linhomoeus and Halichoanolaimus ; Bland-Altman analysis confirmed morphology- and size-dependent bias, while 10–20 segments optimized accuracy for tapered forms. RAH NemaCalc thus established a precise, high-throughput standard for nematode biomass quantification, enabling reliable monitoring of anthropogenic impacts like deep-sea mining on ecosystem functions and informing conservation baselines. • Automated, morphology-sensitive biomass estimation using a novel conical-frustum segmentation model. • Validated across multiple marine habitats with 187 specimens, ensuring broad applicability. • High-throughput, non-destructive analysis (~2 s per specimen) for scalable studies. • Open-source, user-friendly tool with an intuitive interface for ecological monitoring. • Directly supports environmental impact assessment in vulnerable marine ecosystems.

Life cycle and net environmental impact assessment of a shared e-bike service: application to the case of Madrid

Hybrid energy storage through the passive connection of a Vanadium Redox Flow Battery and a supercapacitor: An experimental, modelling, economic and environmental impact assessment study

The release of heavy metals from commercial deep-sea mining is likely to be a long-term process lasting decade, and therefore fish communities are actually exposed to a chronic, ongoing stressor. However, toxicity assessment data for marine fishes related to heavy metals have predominantly been derived from acute toxicity experiments to date. To evaluate this potential risk, this study selected four heavy metals (Cu2+, Cd2+, Mn2+, VO4³-) and with potential for release from deep-sea mining and determined their 14-day median lethal concentration (LC50) for embryos and 96 hour (96 hr) LC50 for newly hatched larvae of marine medaka. Subsequently, a 60-day low-concentration, long-term exposure experiment was conducted based on the 96 hr LC50 of Cu2 + and Cd2 + for larvae. This experiment measured parental reproductive indices, such as spawning output and fertilization rate, and offspring developmental parameters, including hatching rate, malformation rate, hatching delay rate, and egg diameter, under stress from Cu2 + and Cd2 + at concentrations of 1/25 or 1/5 of 96 hr LC50. The results indicated that at long-term exposure concentrations even as low as 1/25 of 96 hr LC50 (Cu2+: 0.36 mg L-1, Cd2+: 0.25 mg L-1), both parental reproductive capacity and offspring development were significantly inhibited. This was manifested by an approximately 20% decrease in parental spawning output, a 5-14% reduction in offspring hatching rate, a 12-29% increase in hatching delay rate, alongside significant elevations in malformation rate and heart rate. In contrast, the impact on fertilization rate was relatively minor. These findings demonstrate that marine medaka are more sensitive to the long-term stress induced by heavy metals compared to short-term acute exposure, particularly regarding key indicators related to population recruitment such as parental reproductive fitness and offspring development. This study provides long-term toxicological data under stress conditions, so far largely lacking, for establishing environmental impact assessment thresholds for deep-sea mining activities.

Since the 1960s, waste generated by power plants has been a major environmental concern. In Chile, the regulation of emissions from the power industry remains limited, leading to significant negative impacts on both the environment and public health. International organizations have developed models and software to monitor emissions, yet their accuracy in assessing the true impact of pollutants remains unsatisfactory, as they rely solely on past observations to simulate pollutant concentrations without incorporating learning from historical behavior. This study explores key concepts related to air quality, atmospheric emission modeling, and the critical parameters involved in pollutant dispersion analysis. The objective of this work is to evaluate the efficacy of a feedforward-backpropagation neural network (NN) as an alternative to CALPUFF for predicting SO 2 concentrations in environmental impact assessments. Emission, meteorological, and stack data were collected from official, private, and public sources. We compare the performance of the CALPUFF/CALPOST workflow with a neural-network-based approach for predicting SO 2 concentrations in the Industrial Bay of Mejillones, Chile. The NN substantially reduces prediction error at the training site (Ferrocarriles (FFEE); Root Mean Square Error (RMSE) 4.75 and Mean Absolute Error (MAE) 2.90) compared with CALPOST (RMSE 14.74 and MAE 12.76). However, transfer to an independent station (Cactus Gaviotín (CV)) remains more challenging (NN RMSE 6.76 and MAE 5.57), highlighting both the potential and limitations of data-driven surrogates in environmental impact assessment contexts.

Pineapple chips are a snack from sliced pineapples that are deep-fried and contain permitted food additives. The production activities of pineapple chip agroindustry have the potential to cause environmental impacts. Therefore, a comprehensive assessment of emissions generated throughout the life cycle of pineapple chip production is necessary using the Life Cycle Assessment (LCA) approach. This study aims to calculate the environmental emission potentials from the life cycle of pineapple chips, covering stages from cultivation to distribution. The research stages include goal and scope definition, inventory analysis using the mass balance method, impact assessment using the Open LCA software, and interpretation. The life cycle of the pineapple chips begins with land preparation for cultivation, including nursery, maintenance, and harvesting. The harvested pineapples are then transported to the processing facility, where they are transformed into packaged pineapple chips and distributed to souvenir centres. The results of the environmental impact assessment for a functional unit of 100 grams of pineapple chips show emissions of 7.04E-01 kg CO₂-eq for global warming potential (GWP), 2.29E-03 kg SO₂-eq for acidification potential (AP), 1.42E-02 kg PO₄-eq for eutrophication potential (EP), and 1.08E-08 kg CFC-11 eq for ozone depletion potential (ODP). The life cycle analysis reveals that the production stage is the main contributor to emissions, with eutrophication potential (EP) identified as the hotspot. To reduce the environmental burden, three improvement scenarios are proposed: substitution of chemical fertilizers with compost, conversion of gasoline to gas fuel, and replacement of palm oil with coconut oil. Keywords: environmental emissions, life cycle assessment, pineapple chips

ABSTRACT Minerals and energy have for many years been an important part of the political game in Greenland with a strong wish of becoming economically independent of Denmark. Although Greenland in some periods received significant income, later years have demonstrated a modest level of activities and low interest from investors. Since Greenland took over the mineral administration in 1998 and the full legislation in 2010, a total of 14 exploitation licences has been granted. Four small mines have been active in short periods of time. Several licences have been relinquished or revoked without the start of mining. This paper gives a historical overview of exploitation licences and describes well-established procedures with requested resource estimates, feasibility studies and public hearings about environmental and social impact assessments. Many of these requirements have been dropped after legal and administrative changes within the last few years. Exploitation licences now look like extended exploration, both in terms of areas and time frame. This has caused a lot of confusion in business, less transparency for society, uncertainty when hearings will take place, and how the concept of exploitation licences should be understood in the future. The author has worked with research, advice and promotion of Greenland petroleum and mineral resources since the mid-1980s, and always in close dialogue with authorities and industry. This background knowledge is used for discussing the inexplicable changes that seem to be the result of direct dialogue between a few licence holders and politicians without serious analysis.

Following China’s completion of the removal of provincial boundary toll stations and expressway network integration reform, a large number of electronic toll collection (ETC) gantries were deployed along expressway mainlines nationwide, transforming these facilities from dedicated toll terminals into pervasive traffic-sensing infrastructure covering the entire road network. However, the data value and technological potential embedded in this major infrastructure transformation have not yet been systematically reviewed. This paper adopts a narrative review methodology, incorporating 71 publications identified through multi-database systematic searches. The review is organized along the functional upgrade path of ETC gantries, covering the progression from toll terminals to traffic sensing nodes, multi-source fusion hubs, and finally vehicle–road–cloud cooperative control nodes, and synthesizes research progress in expressway traffic sensing, multi-source data fusion, safety operations, and emerging applications. The review reveals that ETC data have enabled a diverse methodological repertoire spanning travel time estimation, traffic flow prediction, origin–destination (OD) matrix inference, toll plaza safety analysis, dynamic pricing strategies, and environmental impact assessment. Nevertheless, a single ETC data source suffers from inherent limitations: spatial–temporal resolution constrained by gantry spacing and real-time capability limited by transmission latency. This fundamental contradiction constitutes the core driving force behind multi-source data fusion and vehicle–road–cloud integration technologies. The paper further argues that establishing a closed-loop pipeline integrating sensing, fusion, decision, and control and anchored on ETC gantry nodes represents the key direction for realizing intelligent expressway transformation.

This work focuses on the pultrusion of pre-consolidated tapes made of virgin polypropylene reinforced with glass fiber. A specially designed laboratory-scale pultrusion line was used, consisting of a heating/forming mold, a cooling mold, and the pulling system. A life cycle assessment was conducted to evaluate the environmental impact of producing a pultruded composite material with a constant cross-section of 100 mm² and a length of one meter. The cradle-to-gate approach was chosen to model the pultrusion process, which involves the three stages mentioned above. The analysis was performed using the CML 2016 method in the LCA for Experts (Sphera) software. The data used in this work to model the cradle-to-gate scenario are mainly derived from experimental measurements taken during the pultrusion process using sensors and from the literature. The specific Energy Consumption (SEC) was calculated for both operational conditions (1.41 MJ/m at v120 to 0.905 MJ/m at v180). Despite the defects found, the samples taken from the pultruded profile showed significant interlaminar shear strength (120 mm/min of 83.7 ± 9.6 MPa compared to 63.5 ± 17.3 MPa at 180 mm/min).

Municipal solid waste (MSW) continues to generate polluted gases, toxic leachate, and thermal emissions even after landfill closure. This study evaluates long-term bio-hazard, thermal, and moisture impacts of MSW using 9 years of satellite observations for the functional phase (FP) and post-functional phase (PFP) of a dumping site in Multan, Pakistan. The average annual radius of bio, thermal, and moisture influence zones during FP was 1097 m, 1454 m, and 1248 m, respectively, increasing to 1249 m, 1504 m, and 1470 m in PFP. Seasonal analysis showed rising trends during FP and declining trends in PFP. The novelty of this study lies in combining the multi-index remote sensing, zonal proximity, and trend-detection techniques to distinguish environmental reactions between FP and PFP. The findings provide evidence-based spatial hazard thresholds and demonstrate the long-term value of remote sensing in characterizing persistent landfill impacts. Mann-Kendall and innovative trend analysis were applied to detect temporal trend variations. Overall, this work offers a cost-effective, scalable, and reliable approach for monitoring environmental risks from MSW and supports improved landfill management strategies. This study significantly offers a cost-effective, scalable, and reliable approach for monitoring environmental risks from MSW and supports improved landfill management strategies.

As the global population continues to grow exponentially, the demand for renewable energy sources is more critical than ever. Bioethanol, derived from lignocellulosic biomass, has emerged as a promising alternative to fossil fuels. This study focuses on optimizing bioethanol production using a supply chain model that incorporates corn stover, sugarcane bagasse, and miscanthus as feedstocks. To minimize overall supply chain costs, a mixed-integer linear programming (MILP) model is developed, considering key cost factors such as feedstock procurement, bioethanol production, transportation, and facility installation. Traditional optimization methods are replaced with the Social Group Optimization (SGO) algorithm to enhance computational efficiency and solution quality. The results demonstrate that SGO achieves lower total costs with faster convergence, making it an effective optimization approach. Sensitivity analysis reveals that feedstock procurement has the highest impact on total supply chain costs, while production costs show moderate sensitivity, and installation costs have also sensitive effect. These findings emphasize the importance of strategic feedstock sourcing and production planning for economically viable bioethanol supply chains. The proposed SGO-based framework offers a practical solution for industry practitioners seeking cost-effective and sustainable bioethanol production. Future research could explore uncertainty modeling, environmental impact assessments, and hybrid metaheuristic approaches to further enhance sustainable supply chain decision-making.

RSM based optimization and environmental impact assessment of a ternary blended one part alkali activated binder with enhanced mechanical performance.

ABSTRACT The offshore wind energy sector is rapidly expanding globally, with dozens of new projects being proposed. As a consequence, the volume of Environmental Impact Assessment (EIA) documents prepared and stored in public repositories is increasing. To ensure transparency and support meaningful stakeholder participation, these documents must be available and accessible. This paper analyzes the current state of the availability and accessibility of EIA documents of the offshore wind sector in public repositories in the United Kingdom, the United States, Australia, and Brazil. A review framework was applied, drawing on key references on access to environmental information and the disclosure of EIA documents. Good practices were found across availability and accessibility in the countries analysed, including organization by project stage, search tools, filters, and complete EIA documentation. All four countries provide official online repositories, although their level of open access and user accessibility differs. Public repositories are not merely administrative tools for the disclosure of documents, but also an instrument for operationalizing the right of access to environmental information. The design of public repositories is not only a technical or communication task, but a core responsibility of EIA practice. Future research and policy efforts should establish minimum standards for digital repositories.

ABSTRACT This article examines the Environmental Impact Assessment (EIA) framework in the Draft Regulations on Exploitation developed by the International Seabed Authority (ISA), identifying deficiencies and constraints in promoting sustainable governance of the Area recognised as the ‘common heritage of mankind’. This study explores the legal foundations of EIA within the context of international law, focusing on customary international law, the precautionary principle, and the framework established by the United Nations Convention on the Law of the Sea (UNCLOS). This paper reviews exemplary approaches to EIA by referencing international and regional best practices, specifically focusing on the EIA process, baseline studies, uncertainty, transparency, stakeholder engagement, public participation, and the precautionary approach as outlined in the Draft Regulations on Exploitation. This research suggests that insights gained from global practices may enhance the legitimacy, accountability, and environmental protections of the ISA, thereby facilitating a more coherent, equitable, and sustainable governance framework for deep seabed mining activities.

Abstract- With the pressure of sustainability needs growing in the world, corporations are under increasing pressure to balance profitability and environmental responsibility. However, most organizations, especially the small and medium-sized enterprises (SMEs) do not have available tools to measure the financial and environmental implications of embracing green practice before committing capital. This paper introduces a web-based decision support system (DSS), which is the Green Business Strategy Simulator and allows the user to model sustainable business configurations and calculate energy consumption, as well as, the analysis of return on investment (ROI) and important sustainability indicators. The parameters are set usefully by the users such as operational area, equipment inventory and energy sources. The system calculates Key Performance Indicators (KPIs) which include monthly energy usage, Green Score, total investment cost, estimate savings and payback period. Simulated financial analytics module gathers past simulation data to produce business intelligence comprising of average ROI, sustainability trend projections and twelve-month ROI projections. A smart intelligence dashboard also uses simulation logs to create actionable advice to improve energy efficiency and sustainability. The suggested platform is placed as a decision support tool to students, researchers and SMEs in order to strictly evaluate green strategies prior to the full deployment. Keywords- Green Business Simulator, Sustainable Business Planning, Financial Analytics, Sustainability Metrics, Decision Support System, Environmental Impact Assessment.

The rapid accumulation of marble stone waste has created significant environmental concerns and disposal issues. At the same time, the construction sector is actively exploring sustainable material alternatives to reduce dependence on conventional resources. Pervious concrete, widely recognized for its ability to allow water infiltration and manage stormwater, provides a promising solution for incorporating industrial by-products without affecting its core functionality. This research focuses on evaluating the durability and environmental benefits of pervious concrete prepared using black marble stone waste as a partial substitute for natural coarse aggregates. Different concrete mixes were developed by varying the proportion of marble waste, and their performance was studied through a series of laboratory tests. Durability characteristics were examined using abrasion resistance, freeze–thaw resistance, water absorption, and chemical resistance tests. In addition, key properties such as permeability and void ratio were measured to ensure that the essential drainage capability of pervious concrete was preserved. The environmental impact assessment included analysis of resource conservation, efficiency in waste utilization, and reduction in the use of natural aggregates. The findings reveal that incorporating black marble waste enhances certain durability properties, especially abrasion resistance and long-term performance, while still maintaining sufficient permeability. Although minor changes in mechanical behavior were noticed with higher replacement levels, the results remained within acceptable limits for pervious pavement applications. From an environmental standpoint, the use of marble waste contributes to reducing landfill burden and supports efficient utilization of industrial by-products. Overall, the study demonstrates that black marble stone waste can serve as a viable and eco-friendly alternative to conventional aggregates in pervious concrete, promoting sustainable construction and responsible infrastructure development. Key word:- Pervious concrete, Marble Dust, landfill disposal