Role of Artificial Intelligence & Remote Sensing (AIRS) to develop Sequestration techniques to Control Marine Pollution due to micro- plastics and save Marine ecosystems through Physicochemical Processes

Abstract

The present study applies artificial intelligence and remote sensing tech-nologies to develop advanced sequestration techniques for controlling oceanic pollution, particularly microplastics, which severely threaten marine life and human health. Microplastic contamination kills nearly one-third of fish consumed by humans and impacts over a billion people annually through exposure to polluted seawater. With global cleanup costs estimated at $500 million per year, the study focuses on economical and innovative physicochemical solutions supported by AI-driven deep-sea monitoring to address the 46,000 plastic pieces found per square mile of ocean and pollution intensified by storms and extreme weather. Further research will integrate aquatic toxicology, air-sea CO2 exchange, and ocean-energy interactions to monitor water quality and link it with climate variability. Spectroscopic and physicochemical methods will be developed to mitigate pollution and protect marine and atmospheric ecosystems. Technologies such as The Seabin, which filters plastics, detergents, and oil from harbour waters, will be evaluated alongside methods for managing hydrosphere and cryosphere pollution related to global warming and climate change. The study also aims to analyse atmospheric aerosols, organic compounds, biomolecules, toxins, and greenhouse gases using spatial and temporal modelling. Detoxification processes for marine pollutants will be explored through transition metal oxide catalysts, High-Affinity Toxin Receptors (HART), and computational modelling of physicochemical properties (e.g., magnetic susceptibility, surface area, chemisorption, DTA) to predict catalytic behaviour and redox reaction kinetics.