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http://bura.brunel.ac.uk/handle/2438/27008Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Porro, J | - |
| dc.contributor.author | Vasilaki, V | - |
| dc.contributor.author | Bellandi, G | - |
| dc.contributor.author | Katsou, E | - |
| dc.contributor.editor | Liu, Y | - |
| dc.contributor.editor | Porro, J | - |
| dc.contributor.editor | Nopens, I | - |
| dc.date.accessioned | 2023-08-21T09:14:31Z | - |
| dc.date.available | 2023-08-21T09:14:31Z | - |
| dc.date.issued | 2022-04-15 | - |
| dc.identifier | ORCID iD: Evina Katsou https://orcid.org/0000-0002-2638-7579 | - |
| dc.identifier | 10 | - |
| dc.identifier.citation | Porro, A. et al. (2022) 'Knowledge-based and data-driven approaches for assessing greenhouse gas emissions from wastewater systems', in Ye, L.; Porro, J.; Nopens, I. (eds.) Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems: A report from the IWA Task Group on GHG. London: IWA Publishing, pp. 229 - 244. doi: 10.2166/9781789060461_229. | en_US |
| dc.identifier.issn | 978-1-78906-045-4 (pbk) | - |
| dc.identifier.issn | 978-1-78906-046-1 (ebk) | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27008 | - |
| dc.description | Chapter ten of the Open Access book, 'Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems', published by IWA Publishing, is available online at https://iwaponline.com/ebooks/book/844/Quantification-and-Modelling-of-Fugitive . | en_US |
| dc.description.abstract | Copyright © 2022 The Authors and Editors. This chapter provides an overview of modelling approaches other than the mechanistic activated sludge model (ASM) framework for assessing greenhouse gas (GHG) emissions from urban wastewater systems. Examples include knowledge-based artificial intelligence, integrating mechanistic modelling and computational fluid dynamics (CFD) with artificial intelligence (AI), and data-driven and machine learning (ML) methods for assessing and mitigating nitrous oxide (N2 O) emissions from wastewater treatment. | en_US |
| dc.description.sponsorship | The research work of J. Porro on the N2 O Risk Model was financed by People Program (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007–2013, 579 under REA agreement 289193 (SANITAS). This research of E. Katsou and V. Vasilaki was supported by the Horizon 2020 research and innovation program SMART-Plant (grant agreement No 690323). | en_US |
| dc.format.extent | 229 - 244 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language | English | - |
| dc.language.iso | en | en_US |
| dc.publisher | IWA Publishing | en_US |
| dc.rights | Copyright © 2022 The Authors and Editors. This is an Open Access book chapter distributed under a Creative Commons Attribution Non Commercial 4.0 International License (CCBY-NC 4.0), (https://creativecommons.org/licenses/by-nc-nd/4.0/). The chapter is from the book Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems, Liu Ye, Jose Porro and Ingmar Nopens (Eds.). | - |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
| dc.subject | artificial intelligence | en_US |
| dc.subject | knowledge-based systems | en_US |
| dc.subject | machine learning | en_US |
| dc.subject | nitrous oxide | en_US |
| dc.subject | principal component analysis | en_US |
| dc.subject | support vector machines | en_US |
| dc.title | Knowledge-based and data-driven approaches for assessing greenhouse gas emissions from wastewater systems | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.2166/9781789060461_229 | - |
| dc.relation.isPartOf | Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems: A report from the IWA Task Group on GHG | - |
| pubs.place-of-publication | London | - |
| pubs.publication-status | Published | - |
| dc.rights.holder | The Authors and Editors | - |
| Appears in Collections: | Dept of Civil and Environmental Engineering Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2022 The Authors and Editors. This is an Open Access book chapter distributed under a Creative Commons Attribution Non Commercial 4.0 International License (CCBY-NC 4.0), (https://creativecommons.org/licenses/by-nc-nd/4.0/). The chapter is from the book Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems, Liu Ye, Jose Porro and Ingmar Nopens (Eds.). | 17.81 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License
