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http://bura.brunel.ac.uk/handle/2438/27008| Title: | Knowledge-based and data-driven approaches for assessing greenhouse gas emissions from wastewater systems |
| Authors: | Porro, J Vasilaki, V Bellandi, G Katsou, E |
| Keywords: | artificial intelligence;knowledge-based systems;machine learning;nitrous oxide;principal component analysis;support vector machines |
| Issue Date: | 15-Apr-2022 |
| Publisher: | IWA Publishing |
| 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. |
| 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. |
| 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 . |
| URI: | https://bura.brunel.ac.uk/handle/2438/27008 |
| DOI: | https://doi.org/10.2166/9781789060461_229 |
| ISSN: | 978-1-78906-045-4 (pbk) 978-1-78906-046-1 (ebk) |
| Other Identifiers: | ORCID iD: Evina Katsou https://orcid.org/0000-0002-2638-7579 10 |
| 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 |
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