PORTO @ 
Archivio Istituzionale della Ricerca
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThis study is part of a multi-objective, integrated approach to analyze various possibilities for increasing energy efficiency of the largest Italian wastewater treatment plant (WWTP) at Castiglione Torinese, NW Italy. The final goal of this study was evaluating the optimization interventions on the sludge treatment process in terms of mass, energy and greenhouse gas (GHG) emission balance. An optimization scenario of sludge digestion was simulated and compared the present operating situation. In the optimized scenario, a hybrid thermo-chemical pre-treatment of the waste activated sludge (WAS) entering the digestion process was considered. The biogas produced was upgraded to biomethane with a process working with selective membranes. Full scale simulation of the whole sewage sludge treatment line was performed with the screening model MCBioCH4, developed by the Authors. The results showed that the optimization interventions would provide two important positive impacts. Firstly, a reduction of the sludge volume entering into the digestion process. Secondly, biomethane production would be around 20% higher than the methane fraction contained in the biogas actually produced. The energy saving and the increased specific biomethane production would improve the overall GHG balance of the system.
Optimizing Sewage Sludge Digestion in Wastewater Treatment Plants: a Case Study from the Largest WWTP in Italy / Borzooei, S.; Campo, G.; Cerutti, A.; Meucci, L.; Panepinto, D.; Ravina, M.; Riggio, V.; Ruffino, B.; Scibilia, G.; Zanetti, M.. - (2020), pp. 311-316. ((Intervento presentato al convegno 28th European BiomassConference..
| Titolo: | Optimizing Sewage Sludge Digestion in Wastewater Treatment Plants: a Case Study from the Largest WWTP in Italy |
| Autori: | |
| Data di pubblicazione: | 2020 |
| Abstract: | This study is part of a multi-objective, integrated approach to analyze various possibilities for... increasing energy efficiency of the largest Italian wastewater treatment plant (WWTP) at Castiglione Torinese, NW Italy. The final goal of this study was evaluating the optimization interventions on the sludge treatment process in terms of mass, energy and greenhouse gas (GHG) emission balance. An optimization scenario of sludge digestion was simulated and compared the present operating situation. In the optimized scenario, a hybrid thermo-chemical pre-treatment of the waste activated sludge (WAS) entering the digestion process was considered. The biogas produced was upgraded to biomethane with a process working with selective membranes. Full scale simulation of the whole sewage sludge treatment line was performed with the screening model MCBioCH4, developed by the Authors. The results showed that the optimization interventions would provide two important positive impacts. Firstly, a reduction of the sludge volume entering into the digestion process. Secondly, biomethane production would be around 20% higher than the methane fraction contained in the biogas actually produced. The energy saving and the increased specific biomethane production would improve the overall GHG balance of the system. |
| ISBN: | 978-88-89407-20-2 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 2020Optimizing2CO.5.2_paper_28th_2020.pdf | 2a Post-print versione editoriale / Version of Record | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri | |
| 2020OptimizingSlide2CO.5.2_presentation_28th_2020.pdf | 2a Post-print versione editoriale / Version of Record | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2846654
Copyright © 2021