Hasil untuk "Water supply for domestic and industrial purposes"

Punit Kumar, Priti Saxena

Plasma activated water (PAW) offers a sustainable, nonthermal solution for degrading persistent organic pollutants in industrial effluents. This study employed a gliding arc plasma system to generate PAW for treating diluted waste water containing dyes, pesticides, and pharmaceuticals. Experimental parameters such as exposure time, dilution ratio, and pollutant concentration were varied, with analysis conducted using UV Vis spectroscopy, HPLC, TOC, and COD. Results showed high degradation efficiencies, up to 90% for dyes, 85% for pesticides, and 80% for pharmaceuticals following pseudo first order kinetics driven by hydroxyl and nitrate or nitrite radicals. The findings demonstrate PAWs potential as a green, scalable wastewater treatment strategy that minimizes chemical use, supports water reuse, and enhances environmental safety, with future scope for pilot scale applications.

Keerththanan Vickneswaran, Mariangel Garcia Andarcia, Hugo Retief et al.

Sustainable water resource management in transboundary river basins is challenged by fragmented data, limited real-time access, and the complexity of integrating diverse information sources. This paper presents WaterCopilot-an AI-driven virtual assistant developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research for the Limpopo River Basin (LRB) to bridge these gaps through a unified, interactive platform. Built on Retrieval-Augmented Generation (RAG) and tool-calling architectures, WaterCopilot integrates static policy documents and real-time hydrological data via two custom plugins: the iwmi-doc-plugin, which enables semantic search over indexed documents using Azure AI Search, and the iwmi-api-plugin, which queries live databases to deliver dynamic insights such as environmental-flow alerts, rainfall trends, reservoir levels, water accounting, and irrigation data. The system features guided multilingual interactions (English, Portuguese, French), transparent source referencing, automated calculations, and visualization capabilities. Evaluated using the RAGAS framework, WaterCopilot achieves an overall score of 0.8043, with high answer relevancy (0.8571) and context precision (0.8009). Key innovations include automated threshold-based alerts, integration with the LRB Digital Twin, and a scalable deployment pipeline hosted on AWS. While limitations in processing non-English technical documents and API latency remain, WaterCopilot establishes a replicable AI-augmented framework for enhancing water governance in data-scarce, transboundary contexts. The study demonstrates the potential of this AI assistant to support informed, timely decision-making and strengthen water security in complex river basins.

Elaheh Ilkhas, Laleh Roomiani, Ali Akbar Babaei et al.

The purpose of this experimental study was to impact the influencing parameters on the elimination of photocatalytic antibiotic florfenicol from shrimp ponds using Cu-doped ZnO. The research variables included the initial pH (3, 5, 7, 9, 11), the primary concentration of florfenicol (5, 10, 15, 20 mg/L), the photocatalyst dose (0.075, 0.15, 0.3, 0.6 g/L), and reaction time (0, 15, 30, 45, 60, 90 min). Kinetic and isotherm of absorption were performed. Nanoparticle identification tests were reviewed using SEM, XRD, XPS, UV-VIS, and PL spectrum and nano-photocatalyst in optimal conditions. The results showed that copper doping effectively confirmed the optimized dioxide strip structure and SEM images, with pure nanoparticles and Cu-doped ZnO having smooth surfaces. The elements were confirmed by XRD analysis and the chemical composition of nanoparticles via XPS. The results showed that with the increase in pH and the initial concentration of florfenicol, the elimination efficiency decreased. Within 120 minutes, the performance of the photocatalytic process increased (75.2%) and then decreased by increasing the dose of nanoparticles to 0.3 g/L. The absorption kinetics followed the second-degree quasi -high -grade isotherm model. This study could be a reference for practical application of photocatalytic analysis of antibiotics.

Sarah Mariska, Zhang Jin-Wei, Hoang Huu Chien et al.

Abstract This research examines the efficacy of layered double hydroxides (LDHs) in removing phosphate and nitrate from wastewater, enhanced by the memory effect and in situsynthesis techniques. LDHs were synthesized hydrothermally, initially creating carbonate-based CO₃–LDHs, which were then converted to chloride-based Cl–LDHs through anion exchange. These LDHs underwent calcination at 300 °C, 400 °C, and 500 °C to optimize their structure for enhanced adsorption capabilities. The synthesized LDHs were thoroughly characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET) surface area analysis, and X-ray diffraction (XRD). Adsorption experiments in solutions with pH values between 5, 7, and 9 revealed the adsorption capacities of phosphate and nitrate on the CO₃–LDHs and Cl–LDH, respectively. The results indicated that LDHs calcined at 500 °C showed the highest adsorption performance, achieving maximum capacities of 184 mg/g for phosphate and 70.1 mg/g for nitrate. Kinetic studies confirmed that the adsorption process followed a pseudo-second-order model, demonstrating the effectiveness of the memory effect in enhancing ion exchange. The in situ synthesis of LDHs under controlled conditions significantly improved the removal rates of these anionic contaminants from wastewater, proving the potential of this method for the realistic wastewater treatment.

T. Moustapha Mai, C. Azzaro-Pantel, M. Chin Choi et al.

This study investigates the potential of hydrogen as a sustainable energy carrier for mobility applications in island territories, which are traditionally dependent on fossil fuel imports. Green hydrogen is identified as a key component of the energy transition. A Mixed Integer Linear Programming (MILP) model with a multi-period, multi-objective framework is used to optimize the hydrogen supply chain based on system costs, greenhouse gas (GHG) emissions, and a risk index. The model incorporates critical island-specific factors such as water resource availability, renewable energy sources, tourism flow, and geographic constraints. A multi-criteria decision making tool based on a modified version of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) aids the identification of optimal solutions. Results suggest a decentralized Hydrogen Supply Chains (HSC) structure with minimized transport. The levelized cost of hydrogen (LCOH) is estimated at 6.54 ___/kg, and GHG emissions range from 1.32 to 1.75 kgCO 2 e/kg H 2. This study highlights the impact of tourism on energy demand and the crucial role of water resources, offering a novel approach to optimizing island-specific HSC.

Ke Zhang, Shenyi Lu, Mingyang Jiang et al.

Abstract Nanocomposites based on inorganic/graphene nanoparticles have gained remarkable interest as a novel class of hybrid materials. Scientific community attention towards these substances has been increasing, because of their peculiar characteristics in combining anticipated features of building constructs for specified applications. Graphene oxide (GO) and metal nanoparticles (MNPs) are using separately in different applications due to their specific limitations. Researchers continue to explore ways to overcome these challenges and create functional nanomaterials for various fields by combining unique advantages of GO and MNPs. Here, we used a facile one-step method for the synthesis of reduced graphene oxide–palladium composite (RGO/Pd). Environmental-friendly biofabricated palladium nanoparticles adhered to Polyscias scutellaria (PS) leaf extract mediated RGO/Pd have been presented in the current investigation. The biofabricated nanohybrid (RGO/Pd) was analysed utilizing several microscopic and spectroscopic techniques. Further, we have also examined the catalytic function for the reduction of 2-nitroaniline (2-NA) in detail. Primarily, we observed that the synthesized nanocomposite can catalyse simultaneous reduction of 2-NA. Furthermore, an added advantage of the as prepared RGO/Pd nanocomposite is its antimicrobial and antifungal ability. Further, we exhibited that the mesenchymal stem cells of adult goat were viable in the presence of RGO/Pd of 0.1 mg/mL concentration and their properties of stem cells were retained. The outcomes displayed that the nanocomposites exhibited outstanding functioning in the killing of dangerous microbial and fungal pathogens. All these results strengthen the RGO/Pd composite applicability in future for potential therapy in bone tissue engineering applications.

Latif Ahmad, Assmaa Abd-Elmonem, Saleem Javed et al.

Abstract Encountering of entropy generation is meaningful while investigating the energy loss during the operational mechanical system. In particular, the flow of fluid experiencing friction drag and due to which a significant amount of heat transfer occurred. Thus, the thermodynamic system energy conversion is one of the measures of the lost available work and is known as irreversibility. Avoiding of such energy loss can be minimized by introducing the concept of hybridization during the liquid dynamics. This work is initiated to formally characterize and address the significance of irreversible process during the typical Homann flow of viscoelastic liquid. The flow with heat and mass balance aspects are further characterize with the inclusion of thermophoretic and Brownian motion factors. The flow configuration is interpreted in terms of gravitationally affected vertical cylindrical disk, for a better understanding of the impact of irreversible processes, more physical effects in terms of heating source/sink, chemical reaction and solar thermal radiation. New physical impacts are described numerically in terms of flow speed temperatures, nanoparticle volume fraction, displacement thicknesses and entropy generation. Perturbation method is utilized for the reduction of the fourth-order mathematical equation for reducing the problem in to well-posed from ill-posed status. The numerical analysis is carried out by applying one of the built-in commands while using MATLAB software. The buoyancy force factor enhanced the liquid speed, and the concentration of the liquid was determined with uplifted conduct for higher values of chemical reaction parameters. The overall entropy rate is reduced as the Brinkman number and magnetic parameter are increased. The heat transfer flow is increased by internal heat generation. Higher Prandtl and Schmidt numbers significantly affected the isotherms and volume fraction contours.

Maryna Strokal, Mengru Wang, Ilaria Micella et al.

Abstract Validating large-scale water quality models is challenging because of the variety of water quality constituents, and scales for which observations are limited. Here, in this perspective, we propose 13 alternative strategies to build trust in large-scale water quality models beyond validation and discuss their strengths and weaknesses regarding their validity, reliability, and applicability. Our alternative strategies aim to evaluate separately model inputs (Strategies 1–4), outputs (Strategies 5–6) and structures (Strategy 7) as well as these aspects together (Strategies 8–13). This is done via methods such as comparisons (Strategies 1–3, 6–8, 12–13), sensitivity analysis (Strategy 5), use of innovations (Strategy 9), expert knowledge (Strategy 11) and local models (Strategy 13). The proposed strategies vary in their validity, reliability, and applicability. Validation is an important starting point but should be used in combination with other strategies. Our proposed list opens the discussion to improve methods to evaluate global water quality models.

Yi-Han Cao, Wen-Jun Cai, Xi-Wei He et al.

Abstract Biofilms pose significant challenges due to their role in biological contamination and water quality damage. This review explores physical/chemical strategies for controlling biofilms, emphasizing the potential of nanomaterials to enhance antibiofilm performance. Popular characterization methods in biofilm studies are summarized in two aspects, bactericidal monitoring, and anti-adhesion monitoring, which serve as a toolbox for future studies. The insights provided are crucial for advancing biofilm management in various fields.

Hazem Ghassan Abdo, Dinesh Kumar Vishwakarma, Karam Alsafadi et al.

Abstract In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km2 (10.87%); low, 52.45 km2 (26.65%); moderate, 65.64 km2 (33.35%); high, 40.45 km2 (20.55%) and very high, 16.90 km2 (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

Dan Lehman, Tim J. Schoonbeek, Shao-Hsuan Hung et al.

Recognizing errors in assembly and maintenance procedures is valuable for industrial applications, since it can increase worker efficiency and prevent unplanned down-time. Although assembly state recognition is gaining attention, none of the current works investigate assembly error localization. Therefore, we propose StateDiffNet, which localizes assembly errors based on detecting the differences between a (correct) intended assembly state and a test image from a similar viewpoint. StateDiffNet is trained on synthetically generated image pairs, providing full control over the type of meaningful change that should be detected. The proposed approach is the first to correctly localize assembly errors taken from real ego-centric video data for both states and error types that are never presented during training. Furthermore, the deployment of change detection to this industrial application provides valuable insights and considerations into the mechanisms of state-of-the-art change detection algorithms. The code and data generation pipeline are publicly available at: https://timschoonbeek.github.io/error_seg.

Petro Karungamye, Anita Rugaika, Kelvin Mtei et al.

Considering the health effects of antibiotics in the environment, effective monitoring and treatment technologies are needed to mitigate social and environmental impacts. The present study was carried out to investigate the efficiency of the constructed wetland (CW) on the removal of Ciprofloxacin (CIP) from aqueous samples. Experiments were conducted in pilot scale CWs planted with single plants of Cyperus alternifolius, Canna indica and one planted with both plant species. Analysis of CIP concentrations in the influent and effluent samples was done using Cary 60 UV–Vis spectrophotometer, while physical-chemical parameters were monitored for the influent and effluent samples. The removal efficiency of physico-chemical parameters was ˃70% for Nitrate, ˃60% for Phosphate, ˃70% for BOD and ˃77% for COD. The maximum removal of CIP (77.1%) was observed in CW planted with Cyperus alternifolius during a 7 days hydraulic retention time (HRT). The results of this study show superior performance of Cyperus alternifolius than Canna indica. There was no significance difference (p > 0.05) produced by mixing the two plants in a CW. However, mixing of plants especially ornamental plants in CWs brings good visual impression of the systems while treating the wastewater. This study demonstrate that CW can remove antibiotics from wastewater. The best performance depends on best selection and best combination of the plants.

Ameneh Mianabadi, Mojdeh Salimifard, Maryam Salajegheh

IntroductionEvapotranspiration is one of the key components of water balance and irrigation planning. Thus, the accurate estimation of this component and the water consumption of plants can improve the management of water use and increase the efficiency of water consumption. Due to the limitation of tools for measuring evaporation-transpiration, remote sensing methods can be used for this purpose. There are several remote sensing algorithms for actual evaporation estimation including SEBAL, SEBS, Metric, etc. In this study we used the triangle method which only was used by Salimifard et al. (2022) in Mashhad Plain. They evaluated the results for the agricultural products, i.e., wheat and maize. The aim of this study is to evaluate the triangle method for a horticultural crop, i.e., pistachio in Kerman Plain. MethodologyThe study area is Kerman Plain in which pistachio is one of the most important agricultural products. Due to water scarcity in this plain, determining the water requirement of the crops is crucial for agricultural activities. Accordingly, it is important to have an appropriate estimation of actual evapotranspiration in the plain. In this paper, the triangular algorithm was used to estimate actual evapotranspiration in the Kerman Plain in the growing seasons of 2020 (1399) and 2021 (1400). For this purpose, the Landsat 8 satellite images with less than 10% cloudiness were used. The variables such as NDVI, LST, etc., were calculated by using the JAVA programming language in the Google Earth Engine code (GEE) system environment. The required meteorological data of Kerman station were acquired from IRIMO. The triangular algorithm is based on the two-dimensional spatial plot of normalized LST and normalized NDVI, which were calculated using bands 10, 5, and 4 of the Landsat 8 in the GEE. Estimation of the wet and dry edges was conducted by MATLAB code. the actual evapotranspiration obtained using the triangular method for a pistachio orchard, which was under irrigation management, was compared to the values obtained by the FAO-56 method. The results were evaluated by correlation coefficient (r), Root Mean Square Error (RMSE), and Mean Error (ME).Results and discussionThe results showed that the amount of evapotranspiration for pistachio was estimated with acceptable accuracy (r= 0.73 and RMSE=1.8, nRMSE=0.4, ME=-1.6). However, the NSE less than zero (-1.3) shows that the observed (FAO-56) mean is a better predictor than the Triangle algorithm. The values obtained from the triangular algorithm were lower than the values of FAO 56, which was in line with the results of the previous studies for both Agricultural and horticultural crops. This underestimation could be due to the uncertainty of the algorithm, uncertainty in the measured data, or due to the time difference between the date of the selected images and the date of irrigation. Moreover, inappropriate quality of water and soil in Kerman Plain and the uncertainty of plant coefficients used are among the factors that can underestimate evapotranspiration values by the algorithm. ConclusionsIn this study, the triangular algorithm was used to estimate actual evapotranspiration in Kerman plain using remote sensing data. Actual evapotranspiration values obtained from the triangular algorithm were lower than FAO 56 values, which might be due to the uncertainty of the algorithm, uncertainty in the measured data, uncertainty of plant coefficients, or due to the time difference between the date of the selected images and the date of irrigation. To have a better evaluation of the remote sensing algorithms, it can be suggested to develop and apply a micro lysimeter in the farms and orchards, or to use the soil water balance of the farms and orchards. These may help to choose the more appropriate algorithm for the given study area, leading to providing the more proper and applicable advices for the farmers for managing the shortage of the water resources. Furthermore, it may help to update the crop coefficients which may lead to better estimation of evapotranspiration.

Christos Anagnostopoulos, Georgios Mylonas, Apostolos P. Fournaris et al.

Virtual and augmented reality are currently enjoying a great deal of attention from the research community and the industry towards their adoption within industrial spaces and processes. However, the current design and implementation landscape is still very fluid, while the community as a whole has not yet consolidated into concrete design directions, other than basic patterns. Other open issues include the choice over a cloud or edge-based architecture when designing such systems. Within this work, we present our approach for a monitoring intervention inside a factory space utilizing both VR and AR, based primarily on edge computing, while also utilizing the cloud. We discuss its main design directions, as well as a basic ontology to aid in simple description of factory assets. In order to highlight the design aspects of our approach, we present a prototype implementation, based on a use case scenario in a factory site, within the context of the ENERMAN H2020 project.

Eduard Hirsch, Simon Hoher, Stefan Huber

Industry 4.0 factories are complex and data-driven. Data is yielded from many sources, including sensors, PLCs, and other devices, but also from IT, like ERP or CRM systems. We ask how to collect and process this data in a way, such that it includes metadata and can be used for industrial analytics or to derive intelligent support systems. This paper describes a new, query model based approach, which uses a big data architecture to capture data from various sources using OPC UA as a foundation. It buffers and preprocesses the information for the purpose of harmonizing and providing a holistic state space of a factory, as well as mappings to the current state of a production site. That information can be made available to multiple processing sinks, decoupled from the data sources, which enables them to work with the information without interfering with devices of the production, disturbing the network devices they are working in, or influencing the production process negatively. Metadata and connected semantic information is kept throughout the process, allowing to feed algorithms with meaningful data, so that it can be accessed in its entirety to perform time series analysis, machine learning or similar evaluations as well as replaying the data from the buffer for repeatable simulations.

Sicong Xie, Binbin Hu, Fengze Li et al.

Aiming at helping users locally discovery retail services (e.g., entertainment and dinning), Online to Offline (O2O) service platforms have become popular in recent years, which greatly challenge current recommender systems. With the real data in Alipay, a feeds-like scenario for O2O services, we find that recurrence based temporal patterns and position biases commonly exist in our scenarios, which seriously threaten the recommendation effectiveness. To this end, we propose COUPA, an industrial system targeting for characterizing user preference with following two considerations: (1) Time aware preference: we employ the continuous time aware point process equipped with an attention mechanism to fully capture temporal patterns for recommendation. (2) Position aware preference: a position selector component equipped with a position personalization module is elaborately designed to mitigate position bias in a personalized manner. Finally, we carefully implement and deploy COUPA on Alipay with a cooperation of edge, streaming and batch computing, as well as a two-stage online serving mode, to support several popular recommendation scenarios. We conduct extensive experiments to demonstrate that COUPA consistently achieves superior performance and has potential to provide intuitive evidences for recommendation

Fikret Basic, Christian Steger, Christian Seifert et al.

With the advent of clean energy awareness and systems that rely on extensive battery usage, the community has seen an increased interest in the development of more complex and secure Battery Management Systems (BMS). In particular, the inclusion of BMS in modern complex systems like electric vehicles and power grids has presented a new set of security-related challenges. A concern is shown when BMS are intended to extend their communication with external system networks, as their interaction can leave many backdoors open that potential attackers could exploit. Hence, it is highly desirable to find a general design that can be used for BMS and its system inclusion. In this work, a security architecture solution is proposed intended for the communication between BMS and other system devices. The aim of the proposed architecture is to be easily applicable in different industrial settings and systems, while at the same time keeping the design lightweight in nature.

Geetanjali Rathee, Farhan Ahmad, Naveen Jaglan et al.

Industrial Internet-of-Things (IIoT) is a powerful IoT application which remodels the growth of industries by ensuring transparent communication among various entities such as hubs, manufacturing places and packaging units. Introducing data science techniques within the IIoT improves the ability to analyze the collected data in a more efficient manner, which current IIoT architectures lack due to their distributed nature. From a security perspective, network anomalies/attackers pose high security risk in IIoT. In this paper, we have addressed this problem, where a coordinator IoT device is elected to compute the trust of IoT devices to prevent the malicious devices to be part of network. Further, the transparency of the data is ensured by integrating a blockchain-based data model. The performance of the proposed framework is validated extensively and rigorously via MATLAB against various security metrics such as attack strength, message alteration, and probability of false authentication. The simulation results suggest that the proposed solution increases IIoT network security by efficiently detecting malicious attacks in the network.

Maria Cairoli, André van den Doel, Berber Postma et al.

A comprehensive approach to protect river water quality is needed within the European Water Framework Directive. Non-target screening of a complete chemical fingerprint of the aquatic ecosystem is essential, to identify chemicals of emerging concern and to reveal their suspicious dynamic patterns in river water. This requires a new combination of two measurement paradigms: the path of potential pollution should be traced through the river network, while there may be many compounds that make up this chemical composition - both known and unknown. Dedicated data processing of ongoing GC-MS measurements at 9 sites along the Rhine using PARAFAC2 for non-target screening, combined with spatiotemporal modelling of these sites within the river network using path modelling (Process PLS), provided a new integrated approach to track chemicals through the Rhine catchment, and tentatively identify known and as-yet unknown potential pollutants based on non-target screening and spatiotemporal behaviour.

Andrew Ako Ako, Coretta T. Nzali, Lydia Likowo Lifongo et al.

Abstract This research is aimed at assessing the possibility of using a rainwater harvesting (RWH) system to supplement domestic water supply in the Mvog-Betsi neighbourhood of Yaoundé. The research made use of a 63-year long data series on the amount of rainfall available in the study area, an analysis of rainwater quality and an estimate of the population's monthly water demand in relation to the monthly harvestable rainwater supply. Rainwater supply for the months of September, October and November is 53.05 m3 which is considerably greater than the households' water demand of 25.56 m3 during the long dry season. This led to the design of a 27 m3 ferrocement tank as minimum storage requirement. Furthermore, a rainwater quality analysis showed that all tested parameters conform to water quality standards except for microbiological quality. The rainwater needs to be disinfected before consumption as potable water. Finally, cost estimates for installing RWH systems for low ($419), medium ($549) and high standard ($668) habitations were calculated. RWH can effectively serve as a water supply supplement in the Mvog-Betsi neighbourhood.