Abstract

The fast development of aluminium production in Saudi Arabia has led to proportionally increased amounts of industrial waste that present both environmental risks and potential chances for resource recovery. The hydrolysis of waste aluminium slag through seawater to create green hydrogen along with aluminium hydroxide is presented in this work as a potential to improve waste management through the conversion of aluminium waste into marketable products, thereby reducing greenhouse gas emissions and creating financial opportunities that promote sustainable resource management and green energy solutions, supporting the kingdom’s Vision 2030 energy transition plans. This case study utilises the XGBoost machine learning algorithm to forecast aluminium production growth in Saudi Arabia and estimate future aluminium slag availability and the production of hydrogen and aluminium hydroxide. Economic growth and industrial demand served as the basis for these estimates. The model achieved a Mean Absolute Percentage Error (MAPE) of 6.9%, and analysis shows that aluminium production is projected to increase from 784.88 Kt in 2025 to 1,058.42 Kt in 2041, with slag generation rising from 156.98 to 211.68 Kt and enabling up to 6.83 million kilograms of green hydrogen and 176.2 Kt of aluminium hydroxide annually by 2041. The economic analysis indicated that the process relies strongly on the dual-value stream generated by hydrogen and aluminium hydroxide, supporting the commercial attractiveness of aluminium slag valorisation. The economic viability, carbon mitigation advantages, and industrial growth potential outcomes of this approach contribute to sustainable energy research by integrating AI-driven forecasting with circular waste-to-hydrogen valorisation for decarbonising the aluminium sector in the region.