Granular activated carbon (GAC) is widely used in advanced surface water treatment, but long-term operation depletes its adsorption capacity and necessitates bed replacement or regeneration. This study evaluated regeneration of WG-12 GAC after five years of operation in three full-scale municipal water treatment plants supplied with surface water. Samples were thermally regenerated in steam at 600–850°C for 20 min and subsequently demineralized with 1.75% HCl. Performance was assessed using iodine number (IN), specific surface area (SBET), bulk density (ρ), mechanical strength (MS), regeneration mass yield (ηR), and the adsorption–mechanical compromise index (ISM), supported by SEM and FTIR analyses. The most favorable results were obtained at 800°C followed by HCl demineralization. For the Warsaw Water Treatment Plant sample, IN reached 909.0 mg/g and SBET reached 891.0 m2/g, corresponding to 95.68% and 99.00% of the reference specification values for virgin WG-12, respectively. Increasing the temperature to 850°C did not improve adsorption properties and caused greater mass loss. Across the three plants, the 800°C + HCl treatment provided the best balance between adsorption recovery and mechanical stability, while the thermal stage maintained a more favorable material balance than treatment at 850°C. These results support further pilot-scale evaluation of regenerated WG-12 as a circular adsorbent management strategy for full-scale water treatment systems.
The valorization of industrial wastewater through biotechnological approaches represents a promising strategy for sustainable, cost-effective bioproduction and environmental pollution control. Three industrial wastewaters from a pasta manufacturing plant, specifically the complex industrial process effluent (M1), the final treated effluent (M2), and the extrusion die rinsing wastewater (M3), were evaluated as sustainable feedstocks for Bacillus thuringiensis (Bt) isolation and production. Interestingly, a newly Bt kurstaki strain, designated Bt1, was isolated from these effluents. The use of nutrient-rich medium M1 for Bt1 cultivation led to a nearly seven-fold increase in toxin yield compared to the glucose-based medium, reaching 109 mg 10-10 spores instead of 15.69 mg 10-10 spores. Furthermore, Bt1 cells grown in M1 exhibited the highest insecticidal activity against Ephestia kuehniella and Ectomyelois ceratoniae, outperforming both the reference strain HD1 and the commercial formulation DELFIN.Cultivation of the newly isolated strain Bt1 under non-sterile conditions further demonstrated the suitability of the alternative medium M1 for biopesticide production and bioremediation, achieving a δ-endotoxin concentration of 420.15 mg L-1 and removal efficiencies of 92.66% for Zn2+, 64.28% for Fe2+, 59% for Cu2+, and 100% for Mn2+. Genomic annotation proved evidence of the presence of multiple cry genes, as well as genes encoding hydrolytic enzymes, virulence factors, and pathways related to organic matter degradation, persistence, host interaction, and heavy metals uptake, highlighting the Bt1 efficiency as a prominent agent for eco-friendly, sustainable agriculture, and bioremediation in line with circular economy principles.
There are wastes produced during the production of alkyd resin that pose organic pollutants, causing environmental hazards. The current research examined the feasibility of dielectric barrier discharge (DBD) plasma treatment with and without lime pre-treatment as a sustainable, novel method to treat alkyd resin wastewater. Lime pre-treatment prior to DBD plasma treatment substantially enhanced both the magnitude and persistence of COD reduction compared to plasma treatment alone. Nevertheless, it caused a rise in EC and TDS following prolonged plasma treatment. Notably, during plasma treatment, the wastewater color shifted to yellow-orange. The analysis of the data obtained by UV-Vis spectroscopy and FTIR data demonstrated the hypothesis that the reactive species formed by the plasma not only oxidize organic compounds but also cause the residual precursors to undergo polymerization. The spectral features revealed in the FTIR data of the treated wastewater, with a band at 1728 cm−1, were also closely comparable to the fingerprint of a synthesized alkyd resin reference. This implies that the reactions of reactive species produced by the plasma may facilitate the reaction of esterification and condensation, which causes repolymerization. The results emphasize a two-step degradation and repolymerization process, indicating that careful process control is necessary to optimize the production of alkyd resin and reuse, as well as the mineralization of other organic waste components.
This study compares two practical fluoride-removal variants for a small food and beverage production facility using low-mineralized groundwater with slight fluoride exceedance: full-flow electrocoagulation (EC) and partial-flow nanofiltration (NF) followed by blending. Life cycle assessment was performed in SimaPro using ReCiPe 2016 Midpoint (H) and Endpoint (H), with 1 m3 of final water meeting the fluoride limit as the functional unit. The analysis was first conducted for a basic gate-to-gate model ending at the generation of process-specific residual streams and was then extended to include downstream residual-stream management.In the basic model, both technologies showed comparable environmental performance. EC achieved a slightly lower endpoint single score than NF, 62.2 and 64.9 mPt/FU, respectively, corresponding to a 4.3% higher aggregated burden for NF. After inclusion of downstream residual-stream management, the difference increased, with endpoint scores of 60.6 mPt/FU for EC and 70.8 mPt/FU for NF. This was mainly associated with NF concentrate treatment and transport, as well as backwash wastewater treatment. Human health dominated the endpoint results in both modelling variants. Midpoint results confirmed that neither technology was preferable in all impact categories, although NF was more sensitive to residual-stream management assumptions. A simplified multi-criteria decision assessment slightly favoured EC, with total weighted scores of 4.05 for EC and 3.95 for NF.The results show that fluoride-removal technology selection should consider not only removal efficiency, but also treatment intensity, blending strategy, residual-stream management and site-specific operating conditions.
Mismanagement of antibiotics is a global problem affecting environmental and human health. In the present study, soya stalks (SS) derived biochars were prepared using thermochemical method for the effective removal of ciprofloxacin from water. The synthesized adsorbents succeeded in removing ciprofloxacin (CIP) in the range of 50-98% with maximum removal efficiency of ∼98% using biochar synthesized at 900°C. Notably no chemical treatment was given for biochar synthesis. The linear and non-linear isotherm models were studied, revealing the dominance of chemisorption. The presence of -oxy functional groups, hydrogen bonding, π-π interaction, and electrostatic interaction were considered responsible for this. No considerable difference was observed upon incorporating different agitation mechanisms for SS900 biochar, further substantiating the robustness of the prepared adsorbent. Another fascinating finding was that presence of various contaminants in water, such as nitrate, alkalinity, total organic carbon, and total dissolved solids, did not influence the adsorption of CIP using the synthesized adsorbent, retaining the removal efficiency in the range of 94-98%. This study has the potential to utilize agricultural waste and reduce carbon footprint by avoiding the open burning of soya stalks. Furthermore, this contribution approaches towards achieving the Sustainable Development Goals of ‘Good Health and Well-being (SDG #3) and ‘Clean Water and Sanitation (SDG #6), along with the circular economy.
This study investigates the performance of an aerobic Moving Bed Biofilm Reactor (MBBR) for the treatment of sulfate-rich wastewater under varying influent sulfate concentrations. Response Surface Methodology (RSM) was applied using synthetic wastewater to evaluate the effects of hydraulic retention time (HRT), influent sulfate concentration, and carrier filling ratio on chemical oxygen demand (COD) and sulfate removal efficiencies. Laboratory-scale experiments demonstrated that biofilm development on K3 carriers significantly enhanced treatment performance, under fully aerobic conditions (with dissolved oxygen levels maintained at approximately 3–3.5 mg/L throughout the operational phase). Under optimized parameters (HRT = 8 h and 50% carrier filling ratio), the system achieved a stable COD removal efficiency exceeding 90% and maximum sulfate removal of 80–87%.Quadratic models accurately described process behavior (R2 > 0.97), identifying carrier filling ratio and influent sulfate concentration as the most influential variables, while HRT played a complementary role. Overall, the results demonstrate that aerobic MBBRs offer a compact, robust, and sustainable solution for the treatment of sulfate-rich wastewater. Careful optimization of HRT and carrier filling ratio, together with control of influent sulfate levels, are essential to preserve biofilm integrity and ensure stable reactor performance, providing practical guidance for wastewater treatment plant design and operation under sulfate-related challenges.
On-site treatment and recycling of denim wastewater represent an important opportunity to advance resource efficiency and reduce environmental burden of textile production. Because emerging treatment technologies can shift impact across the value chain, their evaluation requires a comprehensive life-cycle perspective. This study applies life cycle assessment to a pilot-scale water recycling system developed for denim manufacturing, integrating advanced oxidation processes, membrane treatment and photovoltaic-powered operation. Using data from the technology developers and modelled baseline scenarios, several optimisation pathways were explored. Results show that, relative to conventional wastewater treatment systems, the recycling system achieves lower impacts in water use and freshwater ecotoxicity categories by factors 5 and 50 respectively when recovering brine and operating solely on solar-derived electricity. Key contributing processes to the other assessed impacts are the consumption of chemicals during the operation stage and the manufacture of photovoltaic and battery components. The use of recyclable materials in energy components enhances overall system performance, allowing the system to counteract its impact on climate change and on nearly all the remaining impact categories. The findings highlight the importance of integrating resource recovery, renewable energy, and designfor-recycling principles to maximise the sustainability benefits of decentralised industrial water recycling systems.
Non-residential water consumption can represent a significant share of urban water demand, making the characterization of users belonging to the service industry (SI) pivotal for urban water management. However, the relationship between water consumption and SI user categories remains underexplored, limiting accurate modeling and the reliability of leakage assessments. This study aims to fill this gap by analysing hourly water-consumption data collected through smart meters over a one-year period for 44 labelled SI users located in Northern Italy and grouped into six categories: shops, catering services, offices, wellness services, recreational and training activities and police stations. The methodological framework relies on four phases: (i) data preprocessing, including the removal of periods affected by long-term closure or post-meter leakages; (ii) characterization of daily water consumption for each user; (iii) derivation of seasonal and annual average daily consumption profiles; and (iv) profile clustering based on the application of K-means and Gaussian Mixture Models (GMMs) and clustering performance evaluation by adopting the Adjusted Rand Index (ARI) and the Normalized Mutual Information (NMI). Results reveal substantial variability in both daily consumption and profiles, even among users belonging to the same SI category. Moreover, user categories do not closely correspond to the obtained clusters (ARI approximate to 0.10 - 0.20 and NMI approximate to 0.30 - 0.40), suggesting that user category alone may not be sufficient to describe actual water-consumption behaviours. The dataset is provided as an open-access library, supporting applications such as preliminary water-demand estimations, water-balance assessments, or modelling applications in contexts where detailed consumption data are unavailable.
Tannery effluents, distinguished by the substantial presence of polymeric finishing chemicals and additives, have become a global environmental issue which is becoming more worse by the fact that microplastics (MPs) are found in many other types of industrial waste. This research concentrates on the advancement and refinement of a sustainable hybrid treatment method that combines Fenton oxidation with Electrocoagulation-Electroflocculation (EC-EF). The objective is to get effective elimination of MPs found in tannery wastewater. Batch tests employed using aluminum electrodes as the primary sacrificial material for systematic parametric optimization like varying current densities, pH, inter-electrode distances, and agitation rates to carefully investigate the influence of each functional parameter on microplastic elimination. While zinc electrodes additionally evaluated for comparative energy efficiency assessment. The hybrid system demonstrated a maximum microplastic removal efficiency of 98.9% from synthetic wastewater and 95.1% from real tannery wastewater when conditions were optimized (current density 3 mA cm-2, pH 7.2, IED 0.5 cm, 450 rpm). FT-IR and XRD provided confirmation of oxidation-induced potential fragmentation and the surface modification and loss of polymer crystallinity, while SEM illustrated the surface erosion and aggregation of the degraded particles. The kinetic analysis followed a pseudo-first-order model (R2 = 0.9989), which indicates surface-controlled adsorption and flocculation mechanisms. The specific energy consumption was low (0.66-0.69 kWh m-3), indicating that the developed process could be a cost-effective for MPs removal. Therefore, this work establishes a novel resource-efficient hybrid electrochemical system for the remediation of MP from industrial wastewater. The process ensures high removal and elimination of MPs with a practical pathway for scaling up toward circular economy of leather industry and other polymer industries.
Efficient use of water and energy resources is increasingly important for sustaining agricultural production under growing food demand and climate change pressures. This study evaluated the effects of irrigation technology on energy performance, input-related carbon footprint, and water scarcity footprint in irrigated silage maize production. Field-based data were collected over three consecutive growing seasons (2022-2024) from a large commercial farm in Ankara Province, Central Anatolia, T & uuml;rkiye, where silage maize was produced under sprinkler and center pivot irrigation systems. Energy performance was quantified using an input-output energy analysis framework, input-related carbon footprint was estimated using emission factors associated with agricultural inputs and field operations, and water scarcity footprint was assessed using the AWARE characterization factor for T & uuml;rkiye. Based on three-year mean values, center pivot irrigation increased dry matter yield by 1.48%, energy use efficiency by 16.89%, energy productivity by 16.88%, and net energy by 3.27%, while reducing specific energy by 14.38% compared with sprinkler irrigation. The input-related carbon footprint per unit of dry matter yield decreased by 22.22% under center pivot irrigation. In contrast, the mean water scarcity footprint was identical between the two systems, and its pattern varied by year: sprinkler irrigation showed lower values in 2022 and 2023, whereas center pivot irrigation showed a lower value in 2024. Overall, center pivot irrigation improved energy performance and reduced input-related carbon footprint under the evaluated commercial farm conditions, while water scarcity footprint was mainly governed by irrigation water volume and the regional AWARE factor rather than irrigation technology alone. These findings provide field-based evidence for irrigation planning and resource-use assessment in semi-arid silage maize production systems.
Synthetic dyes in textile wastewater pose severe environmental risks due to their toxicity and resistance to biodegradation. This study investigates a multi-faceted rotating arc discharge (MFRAD) plasma system for dye-contaminated wastewater treatment, focusing on performance, energy efficiency, energy cost estimation, and degradation mechanisms. Methyl Orange (MO) and Crystal Violet (CV), including their binary mixture, were selected as representative pollutants commonly found in textile effluents. Rapid decolorization was achieved, with removal efficiencies of 95.8% for CV, 97.6% for MO, and 88.5% for the mixed solution within 60 min. Total organic carbon reduction of up to 90-95% confirmed substantial mineralization. The maximum energy efficiency reached 16.45 g/kWh, corresponding to the lowest energy cost of 0.255 $/m3 for CV at 15 min. Across all tested conditions, the electrical energy cost ranged from 0.255 to 1.036 $/m3 of treated wastewater. Reactive species analysis using scavengers demonstrated the dominant roles of ozone and hydroxyl radicals in CV and mixed dye degradation, while hydrogen peroxide contributed significantly to MO removal. High-Performance Liquid Chromatography-Mass Spectrometry (HPLC-MS) analysis identified key intermediates and revealed degradation pathways involving demethylation, hydroxylation, azo bond cleavage, and aromatic ring opening. Plasma treatment also resulted in increased conductivity and decreased pH due to the formation of nitrate and nitrite species, reflecting the contribution of reactive nitrogen pathways. The results demonstrate that MFRAD plasma provides an effective, energy-efficient approach for recalcitrant dye removal, with promising potential for industrial wastewater treatment, particularly for complex dye mixtures.
Investigation of UASB-reactors is complicated at laboratory-scale and operating many biological replicates to draw statistically significant conclusions is challenging. A simple syringe reactor system using off-the-shelf components was developed for the investigation of wastewater treatments with anaerobic granular sludge. As a proof of concept, the effect of hydrogen addition (in situ biomethanation) on the process performance and methane production was investigated with real wastewater of a paper company. The biogas production was highly reproducible and the removal of short-chain fatty acids and alcohols were easy to follow. Addition of H2 gas as electron donor to upgrade biogas was easily implemented and after three cycles a significant negative effect on process performance was observed. Molecular community analysis revealed the predominance of both strict acetotrophic (Methanothrix) and hydrogenotrophic methanogens (Methanobacterium) as well as bacteria typically found in anaerobic wastewater systems including syntrophic microorganisms affiliated to the classes Clostridia, Syntrophobacteria and Syntrophia. H2-addition had most probably negatively affected the syntrophic interactions due to thermodynamic constraints. The developed syringe reactor system was easy to use and very affordable lowering the barrier for widespread investigation of the process performance and microbial ecology of wastewater treatment based on anaerobic granular sludge.
The increased use of ionic liquids (ILs) in many industries in recent years has made the development of methods for recovering them from aqueous solutions and wastewater extremely important. This study investigates the application of electrodialysis for the recovery of 1-methyl-3-octylimidazolium chloride ([Omim]Cl, IL) from aqueous solutions. The effects of the initial IL concentration, applied voltage, linear flow velocity, and ion-exchange membranes were examined to identify the conditions that lead to the effective recovery of IL and by the proposed method, with no degradative by-products in the concentrate solution. Based on the investigated conditions, the most favorable electrodialysis conditions were determined: an initial IL concentration of 0.2 mol/L, an applied potential of 10 V (2 V per membrane pair), and a linear flow velocity of 2 cm/s. Under these conditions, the [Omim]Cl recovery reached 86% along with an IL concentration factor of 2 at a minimum direct current consumption of 16.6 kWh/m3. It was observed that the tested ion-exchange membranes, after five cycles of electrodialysis, exhibit good stability, and 1H NMR analysis confirmed the absence of IL degradation products in the concentrate solution.
Environmental contamination (EC) poses significant risk to surface water resources. Particularly, EC by potentially toxic elements (PTEs) have received greater attention due to their bioaccumulation and biomagnification capabilities. However, existing tools for assessing EC by PTEs lack reliability due to uncertain outcomes. Therefore, this research utilized PTEs data including Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Manganese (Mn), Nicket (Ni), Lead (Pb) and Zinc (Zn), collected from different rivers and estuaries within the Sundarbans estuarine ecosystem of Bangladesh and developed the novel “Environmental Contamination Index (ECI)” model for rating EC in aquatic bodies. The ECI model's architecture consist of four components, including (i) indicator selection technique for selecting crucial environmental contaminants; (ii) a linear interpolation based sub-index (SI) function for normalizing the various environmental contaminants' information; (iii) arithmetic mean-based aggregation function for computing the ECI score; and (iv) score classification scheme for assessing the state of EC. Additionally, for the purposes of evaluating the model's performance in terms of sensitivity, uncertainty and efficiency, this study employed ten machine learning and artificial intelligence techniques. Furthermore, five hyperparameter optimization techniques were compared for assessing the influence of hyperparameters on the model performance and efficiency. To assess the generalization capability of the model(s), the research utilized an independent dataset for validation purposes. The computed ECI scores demonstrated the “fair” and “marginal” EC by PTEs in different sampling sites of the study domain. Among the ML-AI technique, the gradient boosting regression (GBR) model with the Bayesian optimizer (BO) hyperparameter optimization technique demonstrated exceptional superiority for predicting ECI score with training (Root mean squared error-RMSE = 1.08, Mean squared error-MSE = 1.18, Mean absolute error-MAE = 0.847, and Percentage of absolute bias error-PABE = 1.30), testing (RMSE = 4.12, MSE = 17.0, MAE = 3.08 and PABE = 4.62) and validation (RMSE = 3.91, MSE = 15.3, MAE = 3.15 and PABE = 5.51) datasets. Additionally, the ECI model demonstrated good generalization sensitivity (R2 = 0.71) and less than 5 % uncertainty level with the independent dataset for rating PTEs contamination. Further comparison between the ECI model and the heavy metal pollution index (HPI) model revealed that the ECI model is able to accurately rate the scenario of EC by PTEs depending on the number of PTEs breached the threshold limit suggested for the PTEs in water bodies. Cumulatively, the outcomes from this research implied that the ECI model could be an effective tool for monitoring EC by PTEs in water bodies. Although the ECI model is developed using the PTEs data, the model could be utilized for assessing EC from different environmental contaminants. Finally, the findings from this research have significant implication for protecting aquatic ecosystem from EC by accelerating rapid decision-making process.
Optimizing organic loading rate (OLR) and hydraulic retention time (HRT) in granular-bed anaerobic reactors treating poultry slaughterhouse wastewater requires an explicit understanding of the causal relationships between operational decisions and chemical oxygen demand (COD) removal. A Bayesian causal framework was developed to estimate dose-response functions, quantify uncertainty, and derive risk-minimizing operating policies across three reactor configurations (SGBR, DEGBR, and EGSB). Hierarchical Bayesian additive spline models, informed by an explicit causal structure represented as a directed acyclic graph, were applied to 59 observations spanning OLRs of 0.7-38.9 g COD L- 1 d- 1 and HRTs of 0.6-4.5 days. The results reveal structurally stable dose-response relationships across start-up, steady-state, and high-load operating phases. Pareto-optimal policies at OLRs of 7.5-9 g COD L- 1 d- 1 and HRTs of 2.6-3.2 days achieved mean COD removals exceeding 95.7%, with less than an 8.6% probability of falling below 90%. Causal effects were highly transportable across reactor configurations, with prediction errors below 3%, enabling robust generalization of operating guidelines. Compared with conventional kinetic models, the Bayesian causal model improved predictive performance by expected log predictive density (ELPD) units while providing decision-relevant uncertainty quantification. This study demonstrates how explicit causal reasoning combined with Bayesian inference can convert correlational reactor data into actionable and uncertainty-aware operating policies.
In this work, innovative polyaniline (PANI)-coated polymeric membranes were tested in long-term (>100 days) operated microbial fuel cells (PANI-MFC) to treat - besides acetate - various volatile fatty acid (VFA)-type feeds, including model and real, food waste-derived C-2-C-5 mixtures. Current generation was assessed in comparison to MFCs using Nadir ultrafiltration membrane (Nadir-MFC), the neat counterpart of PANI-coated membrane. PANI-MFCs showed good reproducibility and increasing trend in peak current densities (180-250 mA m(-2)). Simulated progress curves based on the modified Gompertz-model revealed significant differences in charge generation kinetics between PANI-MFCs and Nadir-MFCs. in relation to membrane oxygen (k(O)) and acetate (k(S)) mass transfer coefficients. While k(O) values were similar (7.45 +/- 0.94 vs. 6.08 +/- 1.79 & times; 10(-3) cm s(-1)), the PANI-coated membrane exhibited a significantly lower (40%) kS (1.48 +/- 0.29 vs. 2.40 +/- 0.33 & times; 10(-5) cm s(-1)). After >140 days, biofouling analyses and contact angle measurements indicated improved hydrophilicity and anti-biofouling potential of the PANI-coated membrane (66.6 +/- 3.1 vs. 73.9 +/- 2.0 deg).
Wastewater from explosives manufacturing poses significant treatment challenges due to extreme pollutant concentrations and complex contaminant matrices. This work addresses wastewater-related problems at an initiating explosives production facility, where lead azide, lead styphnate, and pyrotechnic compositions are manufactured. The pollutant concentrations substantially exceed regulatory limits: lead reaching up to 653 mg/L (exceedance factor >1300), nitrates up to 3840 mg/L (exceedance 128×), sodium up to 4490 mg/L, and COD up to 9700 mg/L. The batch-based nature of production results in significant temporal and spatial variability in wastewater quality, with discharge intervals ranging from days to over 150 days depending on the production schedule. Additionally, the diversity of pollutants-heavy metals, nitrates, and organic compound requires fundamentally different treatment approaches (reduction vs. oxidation), complicating process design. BOD5/COD ratio 0 and high lead concentration exclude biological treatment. Regulatory requirements were analyzed, including Polish legislation, EU directives, BAT reference documents, and HELCOM recommendations. Despite extensive research on industrial wastewater treatment, comprehensive case studies using real wastewater from European explosives facilities remain scarce, with most of the literature focusing on synthetic wastewater. A critical review of applicable treatment methods is provided, including precipitation, coagulation, advanced oxidation processes, nano zero-valent iron, electroreduction, ion exchange, adsorption, and membrane filtration. The results indicate that hybrid multi-stage treatment configurations are essential to achieve the required 99% removal efficiency, with retention tanks being a key element for load equalization.
Seawater desalination powered by renewable energy is a promising solution to simultaneously address water scarcity and climate challenges. However, achieving net-zero and resilient desalination remains limited by the intermittency of renewable sources and the complexities of managing energy and water interdependencies. While hybrid battery and green hydrogen storage systems offer short- and long-term balancing potential, existing studies oversimplify the water-energy interactions by neglecting electrolyzer and cooling water quality and quantity requirements and pressure differentials in hydrogen production and storage infrastructure. This research addresses these gaps by developing an integrated, high-resolution model that couples renewable-powered desalination with a hybrid battery–green hydrogen storage system, explicitly capturing the bidirectional water-energy interdependencies. The proposed system includes detailed modelling of water treatment systems comprising pre- (coarse screening and media filtration), main (Reverse Osmosis) and post-treatment (electro-deionization) stages to meet local potable water and green hydrogen production systems. The developed model is a Mixed Integer Linear Programming (MILP), solvable by current off-the-shelf solver packages, considering the quality and quantity needs of the electrolysis process and electrolyzer cooling. The model also considers hydrogen compression differences between production and above-ground high-pressure storage tanks. The proposed framework is implemented using real-world data from Al-Ahmadi Port, Kuwait, and evaluated under various operational scenarios. Simulations demonstrate that integrating the proposed green hydrogen model enhances system independence and storage scalability while significantly accounting for real-life water-energy interactions. This research demonstrates a scalable and practical pathway for deploying climate-resilient desalination infrastructure in arid and resource-constrained environments by explicitly modelling the hydrogen-for-water and water-for-hydrogen nexus.
This study examines how water use propagates through Poland's economy by linking the 2020 national Input-Output (IO) accounts with sectoral withdrawal data from Statistics Poland, establishing a consistent, Environmentally Extended Input-Output framework. Direct and indirect water-use are calculated from the Leontief model, and three complementary IO linkages - total, size-adjusted, and net - are derived, each with backward (upstream) and forward (downstream) components. This yields a final sector classification into key, backward-oriented, forward-oriented, or weak. The results indicate extreme concentration: Electricity, gas, steam and air-conditioning (D), Chemicals (C20), and Paper (C17) withdraw 5171.7 hm3, 313.1 hm3, and 102.6 hm3, accounting for 94.2% of industrial withdrawals, while indirect effects constitute 65.3% of the economy-wide total. The dominance of direct vs. indirect effects splits 32 vs. 27 sectors, respectively. The linkages reveal systemic roles that headline withdrawals mask - for example, I56 (Food and beverage service activities) shows strong size-adjusted backward reach, and M71 (architectural and engineering) exhibits very high bidirectional linkages, whereas 62 of 77 sectors fall into the weak category. Value added consists of three elements: an economy-wide decomposition that combines IO linkages with concentration metrics to identify policy leverage points; a size-adjusted indicator set that separates size effects from systemic reach, enabling fair cross-sector comparisons; and a majority-rule classification that turns complex IO outputs into a practical framework for targeting supplier-focused, buyer-standards-based, or dual interventions. Ultimately, this study demonstrates how water-intensive industries must transition from isolated facility-level efficiency to comprehensive value-chain management, providing actionable insights for sustainable water strategies.
