(31s) Climate Change Impacts on Surface Seawater in Contest to CO2 Solubility: A Comprehensive Thermodynamic Investigation

The escalating global climate crisis necessitates a profound understanding of oceanic transformations, particularly the intricate relationship between temperature variations and natural seawater properties. This presentation investigates the thermodynamic characteristics of Arabian Sea surface natural seawater, focusing on the critical interplay between rising temperatures, molecular dynamics, and CO₂ solubility. By experimentally measuring ultrasonic velocity and density at varying temperature and salinity, we provide novel insights into the fundamental physical changes occurring in marine environments. This research addresses a critical knowledge gap by using contemporary experimental data on ultrasonic velocity and density in surface natural seawater in derivation of some of the highly important thermoacoustic parameters including non-linearity parameter, Gruneisen Parameter and Solubility Parameter, which are investigated for the first time for seawater. The results offer crucial information for policymakers, highlighting the mechanical and thermodynamic changes driven by climate change and underscoring the urgent need for comprehensive environmental strategies. Employing advanced machine learning techniques including Random Forest (RF), Gradient Booster (GB), Stacked Ensemble Machine Learning (SEML), and AdaBoost (AB) we have developed predictive models to analyze natural seawater property variations. The Stacked Ensemble Machine Learning approach demonstrated exceptional predictive accuracy, exceeding 99%, with AdaBoost achieving a robust 95% accuracy. Our findings reveal significant molecular-level transformations: increased kinetic energy leads to expanded intermolecular interactions, reduced density, and enhanced CO2 solubility, creating a potentially amplifying feedback mechanism in climate warming.