The impact of PFAS on the public health and safety of future food supply in Europe: Challenges and AI technologies solutions of environmental sustainability DOI Open Access
Ioannis Adamopoulos, Antonios Valamontes,

John T. Karantonis

et al.

European Journal of Sustainable Development Research, Journal Year: 2025, Volume and Issue: 9(2), P. em0288 - em0288

Published: April 23, 2025

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants extensively used in industrial consumer applications. Their accumulation European agricultural soils through discharges, biosolid applications, contaminated irrigation water poses an unprecedented threat to food security, soil health, quality. Despite extensive laboratory research, no full-scale, long-term validated PFAS remediation study exists, leaving critical gaps mitigation strategies. Existing approaches–including mobilization, immobilization, degradation techniques–have demonstrated effectiveness controlled environments but lack real-world validation dynamic settings. This proposes artificial intelligence (AI)-driven framework that integrates real-time detection tools, predictive modeling, adaptive technologies overcome these challenges. Unlike static strategies, the proposed AI-assisted system dynamically optimizes interventions based on contamination patterns, composition, environmental conditions. Machine learning algorithms statistical models enable precise tracking, migration automated decision-making, offering a scalable responsive solution for sustainable management. underscores urgent need large-scale, policy-backed field trials validate AI-driven technologies, bridging gap between scientific advancements implementation. By transitioning from theory adaptive, field-deployable framework, this research ensures solutions resilience, public health protection.

Language: Английский

Supramolecular Gels Based on C3-Symmetric Amides: Application in Anion-Sensing and Removal of Dyes from Water DOI Creative Commons
Geethanjali Kuppadakkath, Sreejith Sudhakaran Jayabhavan, Krishna K. Damodaran

et al.

Molecules, Journal Year: 2024, Volume and Issue: 29(9), P. 2149 - 2149

Published: May 5, 2024

We modified C3-symmetric benzene-1,3,5-tris-amide (BTA) by introducing flexible linkers in order to generate an N-centered BTA (N-BTA) molecule. The N-BTA compound formed gels alcohols and aqueous mixtures of high-polar solvents. Rheological studies showed that the DMSO/water (1:1, v/v) were mechanically stronger compared other gels, a similar trend was observed for thermal stability. Powder X-ray analysis xerogel obtained from various revealed packing modes gelators these systems similar. stimuli-responsive properties towards sodium/potassium salts indicated gel network collapsed presence more nucleophilic anions such as cyanide, fluoride, chloride at MGC, but intact when contact with nitrate, sulphate, acetate, bromide, iodide salts, indicating anion-responsive gels. Anion-induced formation less below MGC N-BTA. ability act adsorbent hazardous anionic cationic dyes water evaluated. results ethanolic successfully absorbed methylene blue methyl orange water. This work demonstrates potential gelator material promising candidate purification.

Language: Английский

Citations

4
The impact of PFAS on the public health and safety of future food supply in Europe: Challenges and AI technologies solutions of environmental sustainability DOI Open Access
Ioannis Adamopoulos, Antonios Valamontes,

John T. Karantonis

et al.

European Journal of Sustainable Development Research, Journal Year: 2025, Volume and Issue: 9(2), P. em0288 - em0288

Published: April 23, 2025

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants extensively used in industrial consumer applications. Their accumulation European agricultural soils through discharges, biosolid applications, contaminated irrigation water poses an unprecedented threat to food security, soil health, quality. Despite extensive laboratory research, no full-scale, long-term validated PFAS remediation study exists, leaving critical gaps mitigation strategies. Existing approaches–including mobilization, immobilization, degradation techniques–have demonstrated effectiveness controlled environments but lack real-world validation dynamic settings. This proposes artificial intelligence (AI)-driven framework that integrates real-time detection tools, predictive modeling, adaptive technologies overcome these challenges. Unlike static strategies, the proposed AI-assisted system dynamically optimizes interventions based on contamination patterns, composition, environmental conditions. Machine learning algorithms statistical models enable precise tracking, migration automated decision-making, offering a scalable responsive solution for sustainable management. underscores urgent need large-scale, policy-backed field trials validate AI-driven technologies, bridging gap between scientific advancements implementation. By transitioning from theory adaptive, field-deployable framework, this research ensures solutions resilience, public health protection.

Language: Английский

Citations

0