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

Oil spills at sea pose risks to the marine environment and to the economy of many nations. Marine ecosystems are very vulnerable and precious as producers of oxygen and as regulators of climate. Therefore, their protection and preservation are necessary. In the event of an oil spill, anthropogenic clean-up activities and natural weathering processes can minimize the negative effects on marine organisms, and the marine environment in general. The target of this study was to investigate the status of the sea along the coastline of the Saronic Gulf, Greece, a year after the sinking of the Agia Zoni II oil tanker. Seawater samples from 15 sampling locations from Phlisvos coast to Anavissos, an area easily approached by bathers with recreational interest, were collected and analysed for total petroleum hydrocarbons. Concentrations up to a maximum of 56.6 μg/L were detected. Despite the large extent of the initial hydrocarbon pollution, the immediate clean-up operations and natural weathering and/or sorption processes have reduced the impact of the spill on surface waters.

Management of sediments from coastal areas, contaminated with heavy metals and organic substances, is a very critical issue. Management decisions are usually based on total pollutant concentrations and various guidelines that are used by different countries. Heavy metals can be mobilized from polluted sediments if they are exposed to changing environmental conditions that occur during excavation, disposal at sea, or disposal in confined facilities. This paper examines the changes in heavy metals partitioning to binding phases in contaminated marine sediments and the release of metals to the environment. Environmental conditions are simulated by submitting sediments to a modified elutriation test with oxygenated and deoxygenated seawater. A sequential extraction procedure is used to determine the binding fractions of heavy metals in the sediments. Fractionation analysis of excavated marine sediments from the port of Piraeus, Greece showed that copper is primarily associated with organic matter, whereas lead and zinc are primarily associated with iron oxides. Under anoxic conditions, the metals bound to the various binding fractions remain practically stable. On the other hand, under oxic conditions, an increase in the concentration of metals associated with carbonates and a decrease in the concentration of metals associated with organic matter and iron oxides were observed. Both under oxic and anoxic conditions, actual metal mobility was very low and less than 0.5 % of total metal mass was found in the dissolved phase.