Dr Shivaprasad Vijayalakshmi shivaprasad.k.vijayalakshmi@durham.ac.uk
Assistant Professor (Research)
Hydrogen rich syngas production through sewage sludge pyrolysis: A comprehensive experimental investigation and performance optimisation using statistical analysis
Shivaprasad, Kumar Vijayalakshmi; Heslop, Jonathan; Roy, Dibyendu; Malik, Abdullah; Wang, Yaodong; Roskilly, Anthony Paul; Bao, Huashan
Authors
Jonathan Heslop jonathan.heslop@durham.ac.uk
Senior Technician
Dr Dibyendu Roy dibyendu.roy@durham.ac.uk
Post Doctoral Research Associate
Dr Abdullah Malik abdullah.a.malik@durham.ac.uk
Assistant Professor
Dr Yaodong Wang yaodong.wang@durham.ac.uk
Professor
Professor Tony Roskilly anthony.p.roskilly@durham.ac.uk
Professor
Dr Huashan Bao huashan.bao@durham.ac.uk
Associate Professor
Abstract
Bioenergy is anticipated to play a significant role in the United Kingdom’s Net Zero 2050 scenario. This study aims to explore the possibility of producing hydrogen-rich syngas using sewage sludge from a wastewater treatment plant located in England, United Kingdom. The primary objective of this study is to experimentally produce hydrogen-rich syngas from sewage sludge through pre-treatment, drying, and pyrolysis. Furthermore, statistical methods have been employed to optimise the performance of the pyrolyser. The individual desirability scores for lower heating value (LHV) and cold gas efficiency (CGE) were estimated to be 0.83902 and 0.85307, respectively. Combining these scores, the overall desirability of the model reached 0.8460, indicating favourable predictive performance. The optimal operational conditions are reported to be a feed rate of 3.0488 revolutions per minute (rpm) and an operational temperature of 800°C. Under these conditions, the highest calculated CGE of 66.31% and the peak LHV value of 18.36 MJ/ m^3 were achieved.
Citation
Shivaprasad, K. V., Heslop, J., Roy, D., Malik, A., Wang, Y., Roskilly, A. P., & Bao, H. (2024). Hydrogen rich syngas production through sewage sludge pyrolysis: A comprehensive experimental investigation and performance optimisation using statistical analysis. Process Safety and Environmental Protection, 187, 270-278. https://doi.org/10.1016/j.psep.2024.04.071
| Journal Article Type | Article |
|---|---|
| Acceptance Date | Apr 14, 2024 |
| Online Publication Date | Apr 16, 2024 |
| Publication Date | 2024-07 |
| Deposit Date | May 17, 2024 |
| Publicly Available Date | May 17, 2024 |
| Journal | Process Safety and Environmental Protection |
| Print ISSN | 0957-5820 |
| Publisher | Elsevier |
| Peer Reviewed | Peer Reviewed |
| Volume | 187 |
| Pages | 270-278 |
| DOI | https://doi.org/10.1016/j.psep.2024.04.071 |
| Public URL | https://durham-repository.worktribe.com/output/2442767 |
Files
Published Journal Article
(4.1 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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