And the winners are…

paPECo is an innovative system designed to treat phenolic compounds in industrial wastewater using photoelectrocatalysis. It works by catalyzing a semiconductor immobilized on an electrode with light and an electrical potential. The optimized FTO/WO₃/BiVO₄ electrode induces a continuous oxidation reaction, effectively decomposing phenolic compounds into carbon dioxide. This system offers rapid treatment within one hour, operates at a low energy consumption of 2.5 V, and reduces CO₂ emissions. In the context of fossil fuel-based electricity, paPECo promotes sustainable economic growth and while ensuring environmental responsibility, especially in water management. It aligns with SDG 6, 13, and 14, supporting global sustainability efforts.

The project offers an innovative solution for lobster fishing by utilizing mesquite wood, an invasive species prevalent in the semi-arid region of northeastern Brazil. Unlike polluting materials like tires, barrels, and contaminated items that capture juvenile lobsters, the proposed device is biodegradable, eco-friendly, and respects the species’ reproductive cycle. After 6 to 10 months of use, it transforms into a substrate for coral reefs and contributes to the fertilization of marine soil. Interviews with fishermen, technical evaluations, and validations from environmental agencies have already been conducted, confirming its feasibility and local acceptance. The initiative combats overfishing, preserves marine ecosystems, and values artisanal fishing. With global potential, the project aims to shift fishing practices by uniting innovation, sustainability, and marine regeneration.

A possible solution to the increasingly urgent protein deficiency could be green biorefining, which is a process to get edible proteins out of plants. But one of the produced by-products called brown juice is harmful to the environment in large quantities, for example, it can cause eutrophication. In my research we wanted to get advantage of this situation by using the brown juice as an additive in the growing media of microalgae to increase the production and the nutritional value of the harvested biomass. Recycling brown juice this way helps to fight with protein deficiency because the harvested biomass contains high amount of protein, suitable for human or animal consumption.

As water scarcity worsens due to climate change, atmospheric water harvesting is emerging as a sustainable solution for freshwater supply in regions with limited access. This study presents an energy-efficient atmospheric water harvesting device based on metal–organic frameworks (MOFs). Unlike existing systems that operate only once daily using temperature differences between day and night or require electricity, the proposed device collects water multiple times daily without external power. Integrating MOFs with manual vacuum pump and low-temperature sources like soil accelerated water collection up to fourfold compared to non-vacuum conditions. Incorporating MOFs into a porous sponge shaped into beads or films enhanced water uptake efficiency and portability. This approach offers a promising strategy for freshwater production across diverse climate conditions.

AquaWise is a smart, automated irrigation system designed to optimize water use through customizable schedules – start/stop times, duration, flow rate, and total volume. It connects to the irrigation network and adjusts water distribution based on real-time data and plant’s production. The system integrates weather forecasts, environmental conditions (humidity, rainfall, wind, temperature, light), and local soil moisture sensor input to improve efficiency and reduce water waste. AquaWise is scalable for use in gardens, farms, or large agricultural setups and it includes machine learning. It requires basic hardware: affordable soil moisture sensors and a Raspberry Pi programmed in C++. The system controls a hydraulic valve and, if required, a pump. A pilot version is currently implemented in a school garden.  

This research explores using natural sulphurous waters for various chemical applications. It focuses on precipitating heavy metal ions, eliminating free radicals, and recovering sulphur.

Key findings include successful H₂S detection, and sulphur recovery through oxidation with hydrogen peroxide. H₂S effectively precipitated several heavy metals (except chromium) and neutralized free radicals. The study demonstrates that sulphurous water is valuable for chemical reductions, metal precipitation, organic synthesis, and radical scavenging, suggesting it could be a sustainable source for sulphur recovery, reducing reliance on less healthy extraction methods.

Climate change, a major challenge of the 21st century, profoundly affects societies and biodiversity. In the Swiss Alps, it causes glacier melting, intensifies natural hazards, and threatens the local economy dependent on winter tourism. This study analyzes its impact in the Fribourg Prealps, specifically on the Tissiniva alpine pasture, where water resources are particularly fragile. The reduction in snowfall, earlier snowmelt, and periods of drought complicate water supply, forcing the alpine pasture to adapt. By combining field observations, long-term meteorological data, and local testimonies, this research aims to better understand climate evolution in mountain regions and its environmental, economic, and social consequences.

We created a compact, low-energy system that treats and makes kitchen greywater safe to reuse by combining electrocoagulation, UV light, and multi-stage filtration. It fits under the sink and automatically operates with an Arduino Mega board, reducing water use by up to 83%. In our hometown, Belén, Catamarca — a region affected by water scarcity and poor water quality — kitchens consume around one billion liters of water each year. Our system could recover up to 900 million liters annually, offering a sustainable and affordable way to improve water use, reduce the demand for clean drinking water, and minimize pollution.

Waver is an innovative aquatic drone designed to restore and monitor dead zones in aquatic environments by generating artificial waves and collecting real-time environmental data. Equipped with smart sensors, solar panels, and GPS, Waver operates autonomously while monitoring key parameters such as temperature, pH, and oxygen levels. It integrates three AI models specialized in detecting plastic waste, oil leaks, and marine life, supported by a robust dataset for high accuracy. A user-friendly online platform displays live data and alerts, enabling informed decision-making for environmental management. Waver aims to support biodiversity recovery, promote sustainability, and offer a scalable solution to one of the most pressing ecological issues aquatic ecosystem degradation.

In our project, we present a novel method for detecting volatile organic compounds (VOCs) in water using a Needle Trap Device (NTD) filled with a recently developed metal-organic framework sorbent (MOF), ZnMOF-74. VOCs, even at low concentrations, pose serious health and environmental risks. Omnipresent in rivers, near factories, and in tap water, exposure may lead to liver complications, lung disease, and cancer. The ZnMOF-74 sorbent demonstrated high reusability, sensitivity, and reproducibility in capturing VOCs such as isoprene, acetone, benzene, and p-xylene. Compared to conventional methods, this approach offers improved detection limits and environmental compatibility. The findings highlight the potential of MOFs as sorbent materials for the extraction of harmful chemicals and contribute to creating a safer aquatic environment.

Ameland is an island with unique challenges and opportunities in drinking water production. An increasing demand for drinking water due to growing tourism and a growing permanent population creates challenges. The current drinking water supply largely relies on freshwater bubbles under the island and water brought in from the mainland via pipes. However, this approach is fragile and not fully sustainable. Therefore, this paper investigated whether electrodialysis metathesis (EDM) could contribute to a self-sufficient and future-proof drinking water system for Ameland. The study concludes that EDM is a promising technique for producing drinking water from seawater on Ameland. The road to a self-sufficient drinking water system is still long and has many obstacles, but this research shows that with the right innovations and knowledge, it is possible.

The project aims to develop a system that detects water loss using sound signal processing algorithms via a single sensor placed in a commonly used sink area and enables prompt intervention by a responsible staff member.  The developed water sound recognition algorithm was tested in different sinks; the experiments demonstrated that it achieved an accuracy rate of 77.3% and could prevent 15.25 liters of water waste in 135 minutes in a single restroom. Additionally, we trained an AI model to classify the sound, and our AI algorithm achieved a classification accuracy of 95%. Using a contactless approach, this system provides a low-cost, fast-deploying, and actionable solution that ensures water conservation and sustainability.