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Access to clean and safe drinking water remains a critical challenge in many rural and low-resource communities across Nigeria, particularly in regions such as Achalla community in Ibusa, Delta state, where reliance on untreated surface water sources exposes residents to significant health risks. This project presents the design and evaluation of a self-healing intelligent biofilter for sustainable water purification — an innovative system that integrates biological filtration, smart monitoring, and adaptive regeneration mechanisms to provide safe, affordable, and reliable potable water.

The study addresses the persistent issue of waterborne diseases linked to contaminated water sources, including streams such as Atakpo in Achalla, which serve as a primary water supply for domestic use. These sources are often polluted with microbial pathogens, suspended solids, and organic contaminants due to poor sanitation practices and environmental factors. Conventional water treatment systems are either too expensive, energy-intensive, or technically complex for development in such communities. Therefore, this research proposes a decentralized, low-cost, and environmentally sustainable solution.

The developed system utilizes a biofilter medium embedded with active biofilm layers, consisting of naturally occurring microorganisms capable of degrading organic pollutants and trapping harmful pathogens. The self-healing capability of the system is achieved through an intelligent feedback mechanism that monitors key water quality parameters such as turbidity, pH and microbial load in real time. When performance decline is detected, the system automatically initiates regeneration processes, including controlled backwashing and microbial reactivation, thereby maintaining optimal filtration efficiency without frequent manual intervention.

A case study approach was adopted in Achalla community, Ibusa, Delta state, Nigeria, to evaluate the practical applicability and performance of the system. Field data were collected on water quality before and after treatment, focusing on parameters such as turbidity, total dissolved solids (TDS), biochemical oxygen demand (BOD), and Coliform count. Results indicate a significant improvement in water quality, with turbidity reduction exceeding 90%, microbial removal efficiency above 95%, and overall compliance with recommended drinking water standards. The system demonstrated consistent performance under varying environmental conditions and user demand levels.

Furthermore, the integration of solar-powered sensors and a simple user interface enhances the system’s usability and data logging, enabling both users and local stakeholders to track water quality and system performance effectively. This feature is particularly beneficial in rural settings, where technical expertise and maintenance resources are limited.

The economic analysis of the system reveals that it is cost-effective compared to conventional treatment technologies, with low operational and maintenance costs. Its modular design allows for scalability, making it suitable for individual households as well as community-level development. Additionally, the use of locally available material in construction promotes affordability and encourages community participation in system implementation and maintenance.

In conclusion, the self-healing intelligent biofilter represents a novel and sustainable approach to water purification in underserved communities. By combining biological treatment processes with smart technology, the system not only improves water quality but also ensures long-term reliability through its adaptive self-maintenance capabilities. The successful application of this system in Achalla community highlights its potential for wider adoption across similar rural areas in Nigeria and other developing regions facing water scarcity and contamination challenges. This research contributes to ongoing efforts toward achieving universal access to clean water and supports global sustainability goals related to public health and environmental protection.

Volcanic eruptions can cause not only pyroclastic flows and the ejection of volcanic rocks, but also landslides and tsunamis. Worldwide, more than 1,500 active volcanoes have the potential to produce such hazards, and about one billion
people live in at-risk areas.

To help reduce the impact of volcanic disasters, we attempted to predict eruptions
at Sakurajima Volcano. Before an eruption, changes in volcanic activity can cause
gases released from magma to dissolve into nearby groundwater and hot spring
water. We therefore investigated whether hot spring water chemistry could be used
as an indicator of impending eruptions.

We analyzed chemical components related to volcanic gases—CO₂ and SO₂,which can increase when magma intrudes beneath Sakurajima, and HCl and HF, which are expected to be released from the magma system shortly before an eruption. We detected compositional changes that preceded the continuous eruption sequence in May 2025. To make monitoring feasible in the field, we developed and improved (i) a simple, low-cost, rapid method to measure total  carbonate concentration without expensive or time-consuming instruments, and (ii) a hot spring water analysis method using a homemade spectrophotometer. Our results suggest a two-step chemical warning system: an increase in the molar [Cl]/[Na] ratio about 3–4 months in advance as a first warning sign, followed by an
increase in F⁻ concentration about one month in advance as a second warning sign. These indicators may help support future eruption forecasting and disaster preparedness.

The project stems from the desire to realise a fundamental right of every individual: access to clean water. The results obtained indicate that the answer to this global challenge lies in the integration of natural resources and sustainable technology.
Precise data has emerged from the experiments carried out:
• laboratory analysis: tests on standardised samples recorded a 99% reduction in bacterial load and an 82% reduction in PFAS (PFOA, PFOS, HFBA). These results demonstrate the effectiveness of Moringa oleifera not only as a coagulant, but also as a bio-adsorbent for complex chemical pollutants;
• field trial: the prototype, assembled using reused components, demonstrated a bacterial load reduction capacity comparable to that of the laboratory tests, proving suitable for meeting the daily needs of a small household. In addition to its proven technical efficiency, our proposal meets criteria of sustainability,  replicability and social impact, making it a practical solution for the local area.
• Sustainability: the project is cost-effective as the cost of the filter material is low or nonexistent and the system requires no electricity, operating solely by gravity. The use of recycled materials eliminates the need for costly investments.
• Scalability: the kit is designed to be built using common components; its simple operation requires no special skills, allowing for rapid deployment in rural centresor outlying settlements.
• Social Impact: ensuring access to purified water reduces exposure to bacteria and contaminants responsible for serious diseases. The system thus enables the
population to manage a vital resource such as water independently.

Nitrate contamination in UK agricultural watercourses remains a major issue, but existing monitoring methods are often too costly for farm-scale use. This project introduces NitroGauge, a £190 manometric nitrate monitor, alongside BioFix, a biochar-based remediation column. Tested across three sites over sixteen visits, NitroGauge identified rainfall-lag patterns suggesting different subsurface flow pathways. BioFix improved through successive designs, with removal increasing from 12.5–36.5% using raw biochar to 63.5–66.5% with FeCl₃ modification and 81.2–84.0% using a two-zone biological system. The prototype costs over 99% less than commercial sensors, and future designs will enable autonomous deployment. Findings remain preliminary due to the limited sample size.

JointGuard is a passive proof-of-concept system designed to make hidden drinking  water pipe joint leakage visible by guiding leaked water through a tube to an absorbent  indicator. This project addresses the problem of non-revenue water and the limitations  of existing leak detection methods, which often depend on electronics, acoustic  equipment, or pressure monitoring. A simplified laboratory prototype was built using a plastic pipe section, a 2 L bottle leak capture collar, hot glue, tape, cotton, food colouring, and reusable drinking straws. Our prototype was tested at indicator heights  of 10 cm, 15 cm, and 20 cm, with three repeated trials at each height. Mean response  time increased from 89.0 seconds at 10 cm to 113.8 seconds at 15cm and finally 134.2 seconds at 20 cm, showing that the greater vertical transport height slowed the  detection time, although a visible indicator was achieved at all tested heights. These  results provide preliminary evidence that pressure-driven transport can be used to move leaked water from a pipe joint to an accessible visual indicator under controlled laboratory conditions.

Coastal plastic settling on the seabed fragments into microplastics that persist in sediments for decades, degrading benthic habitat and water quality. This study quantifies how early removal of submerged macroplastic prevents long-term accumulation. Physics-based stability analysis, field tests in Malta, and worldwide surveys confirm technical and social feasibility of DIVE&CLEAN, a low-cost diver-assisted seabed bin deployed at recreational dive routes. Each bin also serves as a fixed sampling station for microplastic research. The model predicts >96% prevention when intervention starts in the first five years (across all tested fragmentation rates), but only 76% if delayed to year 20.

Water resources are a fundamental factor essential for livelihoods and driving the global economy, with “watershed forests” in mountainous region serving as an ecological water allocation process. They absorb and store rainwater in the soil pore space before gradually releasing it into tributary streams to sustain agricultural areas and communities. This research aims to develop Bio-Seed Balls, a biological material to enhance water absorption for seed germination and survival in watershed forest restoration.

The research was conducted by determining the ratio of Bio-Seed Balls, using a Tapioca starch paste mixed with coconut coir dried vetiver grass leaves and vermicompost, encapsulating the desired plant seeds, and comparing them with Traditional Seed Balls made from clay mixed with coconut coir and vermicompost. Experiment, analyses, and comparisons of Seed Ball performance were carried out.

The study of the physical characteristics of Seed balls, using the CU Smart Lens for material structure inspection, revealed that the Bio-Seed Balls formula has a fibrous and porous structure distributed throughout the ball, which aids in water retention and gas diffusion within the Seed balls. This differs from the traditional formula, which has a fine and dense texture.

The water absorption test showed that Bio-Seed Balls absorbed 107.6% of their dry weight. The traditional formula absorbed 22.2% of its dry weight. Regarding moisture loss, Bio-Seed Balls had a moisture loss of 44.55% and a moisture loss rate of 1.40 grams per hour, which is faster and higher than the traditional Seed balls formula, which had a moisture loss of 11.14% and a moisture loss rate of 0.40 grams per hour.

Germination tests on five wild tree species showed that Bio-Seed Balls had higher germination rates than traditional Seed Balls for all species. Specifically, False koa (Leucaena leucocephala (Lam.) de Wit) the highest germination rate at 75.00%, followed by Yang (Dipterocarpus alatus Roxb. ex G.Don) at 55.56%, Burma padauk (Pterocarpus macrocarpus Kurz) at 44.44%, Black rosewood (Afzelia xylocarpa (Kurz) Craib) 41.67%, and Wild Himalayan Cherry (Prunus cerasoides Buch.-Ham. ex D.Don) at 30.00%. All of which are native species. Therefore, the results of this study indicate that Bio-Seed Balls can enhance seed germination more effectively than traditional formula.

For the firing range test, it was found that the 4 cm diameter Bio-Seed Balls achieved an average maximum distance of 31.9 meters. Their greater mass generates higher momentum and inertia, which helps resist air resistance and allows them to travel farther horizontally. Regarding structural integrity after ground impact, all balls remained intact.

After evaluating Bio-Seed Balls effectiveness and user experience satisfaction through a questionnaire by 94 people in community, the satisfaction level with the Bio-Seed Balls were rated “Excellent” in all aspects with lower cost only 0.8 USD/100 units. This confirms that this innovation makes reforestation simple and truly accessible, giving the community confidence and willingness to participate sustainably in restoring ecosystems and water resources.

The innovative product also supports SDGs 6, 13, 14 and 15 and slogan “Protect the watershed forests, nurture the trees and conserve the water”.

When plastic containers degrade, they can release microplastics and endocrine disrupting chemicals into their contents. This project investigated whether an engineered silicone-based elastomeric barrier coating could reduce microplastic release from plastic containers under simulated environmental stress conditions.
Identical 500 ml polyethylene terephthalate (PET) bottles were used, with some coated internally and others left uncoated. Glass containers served as a control to establish baseline contamination levels. Testing was conducted under two environmental  stressors: ultraviolet (UV) exposure and thermal stress. Water samples were subsequently filtered using a vacuum filtration apparatus onto membrane filter papers  and analyzed under a compound light microscope.

Background-corrected results show that coated bottles released 100% fewer microplastics than uncoated bottles under UV conditions, and 76.9% fewer under heat conditions. Both fibers and fragments were identified, with uncoated samples producing predominantly larger and longer fibers, while coated samples produced shorter, finer particles — suggesting the coating interrupts surface fragmentation in addition to reducing particle count.

These results are considered minimum estimates due to limitations including short trial duration, inconsistent experimental conditions, 40× magnification limiting detection to larger particles, and incomplete sample filtration. Despite these limitations, a clear and consistent pattern emerged across both conditions. The coating shows significant potential as a practical solution to reduce microplastic contamination from plastic containers, with further research under more rigorous conditions recommended to fully quantify its effectiveness.

Every rainstorm turns a small urban creek into a conveyor belt of plastic that rides the current to the sea. Cities want to catch it, but the engineering studies that pick a single boom location routinely cost six figures and take most of a year.

We built GRIME to shrink that gap: a free browser tool that scores every meter of any stream a user draws on a map. It runs a D8 flow model on USGS 3DEP ten-meter elevation data, then blends 27 parameters spanning litter generation, hydrologic transport, downstream ecological and environmental-justice impact, and deployment feasibility into a two-level weighted score, cross-checked against Manning’s equation and stress-tested with a 10,000-iteration Dirichlet Monte-Carlo run.

Applied to Ellerbe Creek, GRIME flagged 8 of 10 debris hotspots a local group had logged over a decade (80% sensitivity; 95% Wilson CI 49–94%) and cut estimated planning cost by more than 95%.

On an independent statewide test against 27 anthropogenic litter-trap sites documented by Waterkeepers Carolina, it recovered 22 (81.5%).

A bridge-anchored boom, sized to the sites GRIME picks, completes the pipeline from pixel to hardware.

Microplastics are an increasing contaminant in coastal marine environments, yet their effects on primary producers and the consequences for food-web stability remain poorly quantified. This study combines laboratory bioassays with computational modelling to investigate how microplastic exposure affects the green macroalga Ulva lactuca and how these disruptions propagate to higher trophic levels, offering a replicable framework for ecosystem-level risk assessment. Algae were cultivated at eight microplastic concentrations (0–580 ppm) for 28 days, with cellular and structural traits quantified via digital image analysis. Cell density declined significantly and monotonically with increasing concentration (F(7, 23) = 74.2, p < 0.001, η 2 = 0.96 across 24 digitized image-analysis replicates),
falling by 46%, while net dry biomass stabilized above 120 ppm, revealing a stress-induced
cellular-to-mass decoupling.

These empirical relationships directly parameterized amodified Rosenzweig-MacArthur food-chain model, where the laboratory-derived cell density decay determined the algal growth rate r(M) and the cell-to-biomass ratio defined trophic conversion efficiencyE1(M). The model identifies a critical bifurcation threshold at 35.6 ppm, beyond which apex predators undergo a catastrophic bottom-up collapse due to energetic starvation. To map the systemic vulnerabilities of this framework, a comprehensive sensitivity analysis was conducted via a Tornado chart. This analysis isolated the key biological parameters driving the system’s volatility, demonstrating how minor shifts in lower-trophic efficiencies can accelerate or buffer ecosystem-wide collapse. These findings demonstrate that conventional biomass monitoring severely underestimates microplastic stress, and that our integrated framework provides a scalable, early-warning diagnostic tool for global coastal water management.

This project presents an intelligent, data-driven irrigation framework designed to regulate severe water
scarcity in football field management, with a specific focus on the extreme water-stressed climate of  Cyprus. Our system transitions traditional experience-based watering habits into a precise, automated  decision-support system. The architecture integrates multi-level technology: ground-based capacitive  soil moisture and AHT10 temperature and humidity sensor managed by a Kypruino UNO+ microcontroller,
remote sensing data from the ESA Sentinel-2 mission, and cloud-based machine learning analytics. While initial deployment between January to March 2026 required manual data logging due to localized ESP8266  Wi-Fi connectivity limitations, an app was fully coded and optimized between April to June 2026. Our
model using Ridge Regression and XGBoost models established a high-accuracy correlation between  environmental variables and grass vitality, achieving a remarkably low Mean Absolute Error 0.0356. Our app splits the football pitch into eight separate irrigation zones showing real-time soil, meteorological, and satellite inputs against predefined system data. The app delivers zone-specific recommendations and features a sustainability dashboard demonstrating reduction in water consumption, reduction in required  maintenance labor, and sprinkles operated duration.

Per- and polyfluoroalkyl substances (PFAS), often called “forever chemicals,” are highly persistent compounds widely used in industrial and consumer products. Their resistance to degradation, caused by the strong carbon–fluorine bond, enables accumulation in the environment and living organisms, raising concerns about ecological and human health impacts. Consequently, effective PFAS remediation technologies are increasingly needed. The ultimate goal is to develop a cost-effective and practical technique to remove these chemicals that could be used widely and integrate into the existing treatment techniques. This study evaluated three PFAS remediation approaches: coated sand filtration, biological treatment using sewage sludge, and chemical solvent treatment. The aim was to assess their effectiveness and identify the underlying removal mechanisms. Batch adsorption experiments showed that sand coated with cationic polymers, particularly chitosan and polyDADMAC, enhanced PFAS removal compared to uncoated sand, especially for long-chain compounds such as PFOS and PFOA. However, a subsequent column filtration experiment demonstrated limited removal under continuous-flow conditions. Biological treatment with aerobic and anaerobic sewage sludge resulted in substantial PFAS removal, particularly for longer-chain PFAS. Comparisons between active and
inactive sludge indicated that adsorption was the primary removal mechanism, although anaerobic microorganisms may also have contributed to PFAS uptake. Chemical treatment using acetonitrile (ACN) and ethanol (EtOH) was largely ineffective, reflecting the high stability of PFAS. An exception was GenX, which showed a notable concentration decrease in ACN, suggesting that some PFAS structures may be more
susceptible to chemical modification. Overall, adsorption-based methods, particularly coated sand and sewage sludge treatment, showed the greatest potential for PFAS removal, while chemical degradation remained challenging. The results highlight the importance of contact time, PFAS chain length, and treatment conditions in determining removal efficiency. Future research should focus on optimizing filtration systems, clarifying microbial contributions to PFAS remediation, and distinguishing degradation from adsorption processes.

This study aimed to determine whether a distributed, non-focusing solar-thermal system could deliver weed-lethal temperatures to floating aquatic weeds without chemicals or sediment disturbance. The SunRays Aqua System uses a bank-mounted array of flat-mirror heliostats to project a broad, non-focusing thermal field onto a receiver, carried either by a screw-pontoon platform that lifts and partially dewaters the weed mat to overcome the water’s heat-sink effect, or by a drone for otherwise inaccessible sites. The prototype was evaluated through thermal calibration trials and mesocosm experiments on Azolla filiculoides. Calibration confirmed 20 heliostats as the minimum to reliably exceed 60 °C, and high-dose treatment reduced dry biomass to 17% of control at day 14, outperforming both mechanical removal (72%) and low-dose treatment (54%). SunRays Aqua is a viable proof-of-concept for chemical-free aquatic weed control in sensitive wetlands, with future work needed on field-scale trials, repeated treatments to manage regrowth, and biomass management to address post treatment nutrient release.

Water security is one of the greatest challenges faced by semi-arid regions, where a single rainy season can determine food production, water availability, and even impact the global economy. To address this challenge, a low-cost and highly accessible hybrid tool was developed, combining meteorological records with the ancestral knowledge of Rain Prophets, local observers of natural signs, and AI, transforming traditional wisdom into practical solutions for the future. The system achieved 95% precision and predicted seasonal rainfall volume with only a 5.7% error rate. This innovative integration of science and traditional knowledge can contribute to building a more sustainable and resilient future.

Plastic pollution threatens global ecosystems; aquatic plastic debris can fragment into smaller particles, be ingested by organisms, and transport associated chemicals through trophic levels. If aquatic plastic contamination is not stringently mitigated, both marine biodiversity and public health face significant, systemic risks. Existing remediation methods like nets, trawlers and filters often harm biological life and heavily rely on manual labour, maintenance and intervention. Plastic pollution cleanup needs to be selective and autonomous.

This project investigates whether an AI (Artificial Intelligence)-guided ferrofluid-assisted collection system can selectively remove plastic debris from water bodies. A new ferrofluid and magnetic drum system, which selectively remediates plastics, was created, and a plastic-targeting AI pilot was trained using a handmade dataset.

For validation, a controlled proof-of-concept study was done in a pool environment against multiple plastic polymers of varying sizes. After 9 trials, the robot had 51.85% removal efficiency and could collect 1.73 pieces of plastic per minute. The system outperformed a preliminary sieve-based baseline for microplastic-scale particles, illustrating the pass-through limitation of coarse mechanical screening.

The prototype demonstrates the viability of combining AI with ferrofluid-assisted remediation to clean up aquatic plastic contamination, while also identifying limitations that future iterations must overcome.

Access to quality drinking water remains a major challenge in several rural communities in Benin, where people continue to rely on traditional wells vulnerable to physicochemical and microbiological contamination. In response to this situation, the SMART-BIOFILTER BENIN project offers an innovative solution combining water treatment, agricultural waste valorization, and intelligent water quality monitoring.

The study was conducted using water from a rural well located in the village of Akpali (Zè commune). A site vulnerability assessment and a physicochemical characterization of the water confirmed the need for treatment before consumption. To address this need, several local agricultural waste products were studied for their potential for transformation into biochar, with particular attention paid to coconut shells.

Experimental tests have demonstrated the effectiveness of coconut shell biochar, with reductions of 87.23% in turbidity, 89.86% in phosphates, 98.29% in potassium and 51.88% in conductivity, while improving the pH from 6.20 to 7.2. These results confirm its potential as a low-cost local filter material.

The project also incorporates an intelligent sensor-based system to monitor several water quality parameters in real time and estimate filter wear in order to alert the user when maintenance becomes necessary.

By combining frugal innovation, circular economy and accessible technologies, SMART-BIOFILTER BENIN constitutes a sustainable and reproducible solution to improve water safety in rural communities in Benin and other regions facing similar problems.

Abalone farming in the municipality of Caldera (Atacama Region) is concentrated in landbased systems for the cultivation of red abalone (Haliotis rufescens) and Japanese abalone (Haliotis discus hannai). In the same coastal environment, natural banks of clams (Gari solida) and surf clams (Mesodesma donacium) coexist, which are filter feeding mollusks of high economic and cultural value for local artisanal fishing.
However, overexploitation has brought the surf clam close to extinction in sectors such
as Bahía Inglesa, making the protection of its habitat urgent in the face of environmental
impacts.

This research presents a comprehensive assessment of water quality and microbial
diversity in a college stream impacted by anthropogenic pollution. Five sites were sampled (including an upstream control site and four downstream sites having different levels of pollution exposure) to gather the required water samples. Physicochemical parameters (pH, dissolved oxygen, turbidity, bio-chemical oxygen demand, nutrient levels), microbial indicators (total coliforms, fecal coliforms, Escherichia coli, heterotrophic plate counts and fungal diversity) were measured on the basis of the standard EPA and APHA methods. Results demonstrated significant deterioration in water quality at polluted sites compared to the control: fecal coliform concentrations reached 180 CFU/100 mL (Site 3: garbage accumulation), compared to 0 CFU/100 mL at the control site. Dissolved oxygen levels declined from 8.3 mg/L (control) to 2.1 mg/L (most impacted site). Algal cells increased from 8.5 × 10³ cells/mL (control) to 72.8 × 10³ cells/mL (most impacted site), indicating nutrient enrichment. The microbial test revealed the presence of the species of Euglena and Aspergillus species as the dominant organism in contaminated areas, and a high concentration of fecal indicator bacteria. It was partially recovered at the downstream site indicating that it had some ability to self-purify. Such results highlight the urgency to manage sources of pollution and introduce programs of integrated monitoring of water quality and restoration of an ecosystem.

In 2026, global water scarcity has been on the rise with regions such as Northern Africa and India have been experiencing a critical water deficit. This paper seeks to provide a feasible and sustainable solution to global water scarcity by developing a Hybrid AWG, which combines the benefits of solar energy and micro wind turbine technology to provide a constant 24h cycle of clean water production. This is achieved using a dual mode condensation architecture utilising compressor driven condensation technology and active electrostatic precipitation mechanism to extract water from the air, followed by a rigorous filtration and mineralization process. The results of our research have revealed that in tropical regions such as India and dry regions such as Northern Africa, the hybrid AWG is capable of producing a constant supply of drinking water that meets World Health Organization and Bureau of Indian Standards IS 10500:2012 specifications, thereby eliminating the need to rely on depleting groundwater resources.

Floods are becoming a common threat to all regions of Kazakhstan, especially during
the springtime, when snow melts rapidly and leads to rapid increases in river levels for
which there is not enough time to act quickly. In order to solve this problem, we have
designed an inexpensive and independent Early Flood Warning System, which monitors
the environment and sends instant warnings before hazardous water levels occur.
The system is able to measure the water level with the help of two different sensors – an
ultrasonic sensor and a resistive water level sensor. Additional information about
temperature, humidity, atmospheric pressure, and soil moisture provides data about
conditions for a possible flood occurrence. The data received from all sensors is
transmitted to the Arduino/ESP32 microcontroller, where all data is analyzed and
warnings are sent if danger occurs.
After installing this system, its work is fully automated, it collects all necessary data,
processes it and instantly notifies about danger via the Telegram Bot. No special
knowledge is required during installation; an easy-to-follow guide will explain
everything. Additionally, in order to get a bigger map of all possible threats to the
country, NASA satellite data are used for monitoring of snow cover, precipitation, and
rivers.

The “AquaVision AI” project is dedicated to creating an accessible system for the early detection of environmental issues in water bodies using multispectral imaging and artificial intelligence. The author developed an optical system with interchangeable light filters, image analysis software, and trained the YOLOv26m model to detect signs of pollution, eutrophication, and debris accumulation based on changes in the spectral characteristics of the water.

The technology operates in several stages: first, the AI analyzes photos and videos from open sources and surveillance cameras; then, suspicious areas are photographed again using multispectral cameras or drones. The system can automatically detect anomalies, determine the coordinates of problem areas, generate PDF and JSON reports, and transmit data to environmental agencies.

The main advantage of the system is its combination of high accuracy, autonomous AI processing, and low cost – about $445 per monitoring module-making it accessible to communities, environmental activists, and local water body monitoring initiatives.

This research investigates the presence of heavy metals that cause contamination in untreated wastewater that is used for crop irrigation in Al-Nassariya, Jeftlek, and Jordan Valley, in the main breadbasket farming area, northeast of Nablus city in the West Bank, Palestine. The valley is considered the main source of fruits, vegetables, and grains for the people of Nablus, because of its heavy production for the local market. This makes the water quality in this area a direct concern for public health and food safety.

Water samples were collected from three areas: a clean groundwater stream, a polluted wastewater stream carrying untreated sewage and industrial discharge from Nablus city, and a mixed stream where both combine. Samples were collected during two seasons (winter rainy season and summer season) and they were analysed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) at An-Najah National University. Results were compared against FAO international standards for safe irrigation water.

During winter, most toxic heavy metals were found to be within safe limits. However, during summer, six heavy metals, that are: arsenic, chromium, cadmium, copper, nickel, and iron, were tested as exceeding safe FAO limits. This confirms that the water causes a serious risk to the quality of crops harvested from there, and human health during the summer season.

To provide a solution for this water problem, we developed an activated carbon filter made from coffee waste to function as an affordable and sustainable solution. The filter has proven to have reduced toxic heavy metal contaminants closer to the safe FAO limits, with removal rates between 55% and 90%.

This demonstrates that the coffee-waste activated carbon filter alternative developed by the researchers, is a sustainable and cheap alternative for contaminated irrigation water that farmers use in that area.

Oil pollution in aquatic ecosystems poses a threat to biodiversity, water quality, and economic activities associated with these environments. This project developed a sustainable alternative for  removing surface oil using human hair and palm fiber, two low-cost and widely Oil pollution in aquatic ecosystems poses a threat to biodiversity, water quality, and economic activities associated with these environments. This project developed a sustainable alternative for removing surface oil using human hair and palm fiber, two low-cost and widely available organic waste materials. The methodology involved evaluating different proportions of both materials to determine their hydrocarbon adsorption capacity and selecting the most efficient combination for prototype design. The results showed that the mixture of human hair and palm fiber achieved 85% oil adsorption with low water retention, confirming its potential as an adsorbent. In addition to contributing to the reduction of pollution in aquatic ecosystems, the proposal promotes the circular economy by repurposing materials considered waste and offers scalability potential for application in ports, vessels, coastal areas, and other bodies of water affected by hydrocarbons. Due to its innovative, accessible, and sustainable nature, this alternative can contribute to environmental protection and the development of replicable solutions in different regions of the world.available organic waste  materials. The methodology involved evaluating different proportions of both materials to determine  their hydrocarbon adsorption capacity and selecting the most efficient combination for prototype design. The results showed that the mixture of human hair and palm fiber achieved 85% oil adsorption  with low water retention, confirming its potential as an adsorbent. In addition to contributing to the  reduction of pollution in aquatic ecosystems, the proposal promotes the circular economy by  repurposing materials considered waste and offers scalability potential for application in ports,  vessels, coastal areas, and other bodies of water affected by hydrocarbons. Due to its innovative,  accessible, and sustainable nature, this alternative can contribute to environmental protection and the  development of replicable solutions in different regions of the world.

Access to clean drinking water remains a challenge in many rural areas of Laos, particularly during the rainy season when rivers, ponds, and wells become contaminated with sediments, microorganisms, and organic matter. This capstone project designs and evaluates a low-cost water filtration system using locally available materials including rocks, pebbles, sand, and charcoal, followed by ultraviolet (UV) light disinfection. The filtration system removes suspended solids, reduces turbidity, improves water quality, and the UV stage destroys harmful microorganisms such as bacteria, viruses, and protozoa. The project aims to provide an affordable, sustainable, and easy-to-maintain solution suitable for rural households, schools, and community centers in Laos.

Project Calypso addresses critical data gaps in water quality monitoring and Harmful
Algal Bloom (HAB) forecasting by engineering a low-cost, modular, open-source
environmental monitoring ecosystem. The framework utilizes a cost-effective, DIY
approach pairing custom 3D-printed components with a dual-controller hardware
architecture:

• High resolution remote sensing: A Raspberry Pi 5 single-board computer pairs
with a specialized camera module to execute localized multispectral imaging and
real-time machine learning inference.

• Geospatial In Situ Data Logging: A Raspberry Pi Pico microcontroller interfaces
with an in situ water quality sensor suite and a GNSS/GPS module for precise
geospatial telemetry.

• Autonomous Robotic Monitoring Platforms: Custom-built Unmanned Surface
Vehicle (USV) and multirotor Unmanned Aerial Vehicle (UAV) platforms
dynamically deploy these payloads across targeted aquatic environments.

• AI Predictive Data Fusion: Machine learning workflows process both localized
physical sensor telemetry and optical imagery to detect and forecast HABs.

To date, the core hardware and software architectures have been validated through
successful laboratory testing of sensor integration, image acquisition, and initial
predictive machine learning evaluations. The project is currently transitioning into multi environment field validation across integrated USV, drone, and static buoy
deployments. Ongoing research through September 2026 will expand the sensor array, optimize edge-connectivity, and train predictive forecasting models on expanded environmental datasets.

This project examines how deglobalisation affects the prosperity of water- and trade-dependent communities. Comparing the British fishing industry and the Bangladeshi textile industry, it explores how changes in global trade influence employment, economic security and access to water and sanitation. The findings show that the impacts of deglobalisation also depend on the economic structures linking communities to global markets. Deglobalisation reveals unequal levels of resilience rooted in the global economy itself. The study argues that water-related vulnerability is shaped not only by environmental or technological factors, but also by trade structures, economic resilience and the unequal distribution of risks, benefits and costs.

This study investigates an enhanced Microbial Fuel Cell (MFC) system for simultaneous  wastewater treatment and bioenergy generation. A Microbial Fuel Cell (MFC) is a system that uses naturally occurring microorganisms to treat wastewater while converting organic pollutants into electrical energy. The system utilizes agricultural waste materials, where rice and corn straw are converted into activated carbon for electrode modification. This approach enhances the structural properties of the electrodes, increasing porosity and surface area, which improves microbial attachment and facilitates efficient electron transfer during wastewater treatment. As a result, an initial power density of 226 mW/m² was achieved proving reduction in Chemical Oxygen Demand (COD), indicating effective pollutant removal. To further improve wastewater treatment efficiency and energy recovery, tea-leaves-derived nanomaterials were integrated onto the electrodes to enhance microbial adhesion and system stability within the water environment. In addition, microbial activity was stimulated using glucose-enriched sludge to optimize the degradation of organic pollutants and increase electron production.

The optimized system demonstrated a significant improvement in performance, reaching a power density of 390 mW/m² which indicates an expected and improved efficiency in Chemical Oxygen Demand (COD) removal. Expected to improve wastewater purification alongside higher bioenergy generation. This project presents a cost-effective and scalable solution for wastewater treatment by transforming agricultural waste into functional electrode materials, offering a sustainable approach for improving water quality and energy recovery in resource-limited regions.

Industrial activities, rapid industrialization, uncontrolled population growth, and climate change have led to a significant increase in the amount of toxic waste discharged into water resources. Consequently, monitoring water pollution has become a critical necessity to ensure the sustainability of aquatic ecosystems and public health. Traditional monitoring methods currently in use, such as manual sampling by divers and fixed-station systems, generally fall short due to depth limitations, high operational costs, severe safety risks, and a lack of continuous spatial
data. This project aims to overcome these operational, technical, and economic barriers. To this end, an innovative, multi-purpose Remotely Operated Underwater Vehicle (ROV) with a modular architecture has been designed and developed to perform observation, measurement, and sampling tasks in both freshwater and saltwater environments.

The developed vehicle features a highly modular architecture, allowing it to be easily modified according to the specific requirements of various underwater research tasks. It is equipped with specialized mechanisms capable of safely collecting physical samples from both the water column and bottom sediment at targeted depths in a sterile manner. Simultaneously, an array of high-resolution onboard sensors allows for the real-time measurement of critical water quality parameters, including temperature, pressure, dissolved oxygen, pH, electrical conductivity, and oxidation-reduction
potential.

A dual-camera system integrated into the vehicle provides a detailed inspection of the underwater environment and significantly increases the pilot’s control. By processing the images obtained from the front camera using AI algorithms—specifically YOLOv8—advanced analyses such as assessing the health and density of reefs, identifying macroscopic water pollutants, and detecting and counting marine life populations are made possible.

Thanks to the hydrodynamic hull design, which was meticulously optimized through Computational Fluid Dynamics (CFD) analyses, the vehicle can successfully complete its missions with high stability and energy efficiency, even in challenging aquatic flows. The vehicle’s Six Degrees of Freedom (6DOF) movement capability guarantees precise positioning under demanding conditions. Comprehensive
computer-aided structural analyses and real-world field tests have thoroughly validated the vehicle’s operational competencies, including its pressure resistance, waterproofing capabilities, and thrust performance. The results demonstrate that the developed system is a cost-effective, field-applicable, and highly reliable technological solution that minimizes human risk in water quality monitoring and sanitation processes.

Wastewater often contains harmful heavy metal compounds that pose risks to both
human health and ecological balance. This study explores an environmentally friendly and cost-effective alternative for removing heavy metals, specifically copper Cu(II) ions, from wastewater using the biomass of the broadleaf cattail (Typha latifolia) and its associated microorganisms. The research also examines promising methods for heavy metal Cu(II) desorption, allowing the biomass to be reused, safely and responsibly disposed of, and enabling the recovery of a concentrated metal ion solution. The data obtained summarizesheavy metal Cu(II) absorption and desorption efficiencies at different copper ion concentrations. From the obtained absorption efficiency results, it can be concluded that the stems and roots of broadleaf cattail (Typha latifolia), together with the naturally occurring microorganisms present in them, are suitable biosorbents for water purification
from Cu(II) ions, with an efficiency of up to 100%. The tested desorption methods showed relatively low efficiencies compared to similar studies

Remote islands often face chronic freshwater shortages due to the lack of natural
freshwater resources, limited infrastructure, and vulnerability to extreme weather
events. Although existing desalination technologies can effectively produce freshwater,
they typically rely on substantial energy input, complex equipment, and centralized
facilities, limiting their applicability in small and remote island settings.
In this study, discarded polyvinyl chloride (PVC) waste was transformed into a
photothermal gel evaporator through a simple solvothermal process. During the
reaction, conjugated structures and hydrophilic functional groups were  simultaneously generated, endowing the material with efficient solar-energy  harvesting and water-transport capabilities. The resulting evaporator exhibited a high evaporation rate of 1.489 kg m-2 h-1 under one-sun irradiation, with a solar-to-vapor efficiency of 93.6%. By adopting a three-dimensional (3D) architecture with an enlarged evaporation area, the evaporation rate was further increased to 1.976 kg m-2 h-1.

Desalination tests using natural seawater demonstrated excellent salt rejection, reducing the concentrations of major ions (Na+, Mg2+, Ca2+, K+, and Cl-) to levels well  below international drinking-water guidelines. Outdoor experiments further confirmed stable freshwater production under natural sunlight and concentrated solar conditions. With optimized condictions, a 1 m2 evaporator can generate 6 L of potable freshwater within 3 h, sufficient to meet the emergency drinking-water needs of a small family.
By integrating plastic-waste upcycling with solar desalination, this project provides a low-cost, portable, and decentralized freshwater solution for remote islands and emergency water-supply scenarios. Beyond addressing freshwater shortages, the proposed approach offers a sustainable pathway for converting waste PVC into a value-added material with practical environmental and societal benefits.

Air pollution is a serious environmental problem mainly caused by the high amounts of CO₂ emission. According to the Worldometer Tunisia’s CO₂ emissions hover near 32 million tons annually, with recent figures indicating a roughly 3% year-over-year increase.
Therefore this project’s aim is to decrease the volume of this gas in the air.

In fact, our system is designed to reduce the atmospheric CO₂ through a biological carbon capture while producing oxygen via a chemical reaction called photosynthesis of cyanobacteria whose role is to absorb CO₂ from the atmosphere and produce oxygen. We will optimize the results of this reaction since we manipulate many physical variables such as humidity, temperature, light intensity and exposure, pH level, liquid concentration and nutrients availability using solar energy.

This IOT approach will collect the real time data through its sensors, analyze it, then send it to the user’s application and provide the user with real-time information of the CO₂ volume reduced by litre and alert him in case of abnormal activity.

This device will be extremely practical since it is a multifunctional outdoor table in cafes equipped with charging ports using solar energy in order to sustain the environment and promote a cleaner urban space with an accuracy of oxygen production of 73%

This study aims to evaluate the catalytic activity of manganese oxide (MnO2) in advanced oxidation processes (AOPs) based on the generation of sulfate radicals  (SO4•-) on an activated carbon (AC) substrate. This research demonstrates dual
degradation mechanism, based on ‘bait, hook and destroy’ theory (Alvarez et al. 2018), while the AC can attract organic pollutants close to its surface, thereby enabling the SO4•- to degrade them efficiently. The objective of this work was to determine which conditions are optimal for producing a stable and efficient and robust MnO2@AC catalyst, as well as the effect the synthesis procedure on
catalytic performance. A comparison of two different coating methods showed that a two-step coating method is more efficient. In addition, a thermal post treatment was examined and proved to have only a negligible influence on the catalytic activity performance. If implemented in the water purification industry, this method can prove to be more cost and time effective, but more research is required.

Across water-stressed farming systems, much irrigation water is lost before crops can use it. This project tested whether microbial biofilms, stimulated with aerobically brewed vermicompost tea, could improve soil water retention. In a controlled column experiment, biofilm-enhanced soil retained water 117% longer than microbially-reduced soil andreduced immediate surface runoff by 71.3%. The treatment hierarchy — biofilm-enhanced outperforming natural soil, which outperformed sterilized soil — confirms the role of native microbial communities in water management. At approximately 800 BDT per hectare, less than 2% of conventional drip irrigation costs, this zero-waste approach offers accessible drought resilience for 500 million smallholder farms worldwide.

The study evaluates the ability of bacterial biofilms to adsorb microplastics, a potential solution for this emergent contaminant. It involved cultivating native biofilms under laboratory conditions and comparing their retention capacity against control surfaces without biofilm. The results showed a significant increase of approximately 3.8-fold in microplastic adsorption in the presence of biofilm.

The project focuses on developing a cost‑effective, efficient, pocket-sized filtration system that removes microbiological contaminants from surface water, making it safe for human consumption. The use of Chitosan – a naturally derived and biodegradable biopolymer – not only enables effective filtration but also supports an eco‑friendly design, allowing clean drinking water to be produced without compromising ecological responsibility.