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

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.

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Publication Details

Journal
Water
Published
2025-06-29
DOI
https://doi.org/10.3390/w17131946
Citations
1
Primary Topic
Electrokinetic Soil Remediation Techniques
Type
article
Field-Weighted Citation Impact
0.73

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article

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

Rodolfo Cardoso, Ademir Nied, Gabriel Villarrubia González, Carlos Frederico de Oliveira Barros et al.
1 citations
Water
Electrokinetic Soil Remediation Techniques
0.73
article

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

Rodolfo Cardoso, Ademir Nied, Gabriel Villarrubia González, Carlos Frederico de Oliveira Barros, Rafael Ninno Muniz, William Gouvêa Buratto
article en
1 citations

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.

WaterVol. 17(13)
Universidade Federal Fluminense (BR), Universidade do Estado de Santa Catarina (BR), Universidad de Salamanca (ES)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Agencia Estatal de Investigación
Openalex Percentile: Top 26%
Electrokinetic Soil Remediation Techniques
0.73
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