State-of-the-Art Decarbonization in Sludge Thermal Treatments for Electrical Power Generation Considering Sensors and the Application of Artificial Intelligence

Abstract

This study explores innovative strategies for decarbonizing sludge thermal treatments used in electrical power generation, with a focus on integrating sensor technologies and artificial intelligence. Sludge, a carbon-intensive byproduct of wastewater treatment, presents both environmental challenges and opportunities for energy recovery. The paper provides a comprehensive analysis of thermal processes such as pyrolysis, gasification, co-combustion, and emerging methods, including hydrothermal carbonization and supercritical water gasification. It evaluates their carbon mitigation potential, energy efficiency, and economic feasibility, emphasizing the importance of catalyst selection, carbon dioxide capture techniques, and reactor optimization. The role of real-time monitoring via sensors and predictive modeling through artificial intelligence (AI) is highlighted as critical for enhancing process control and sustainability. Case studies and recent advances are discussed to outline future pathways for integrating thermal treatment with circular economy principles. This work contributes to sustainable waste-to-energy practices, supporting global decarbonization efforts and advancing the energy transition.