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The future of WRRF modelling : outlook and challenges

Pusker Regmi, Heather Stewart, Youri Amerlinck (UGent) , Magnus Arnell, Pau Juan García, Bruce Johnson, Thomas Maere, Ivan Miletić, Mark Miller, Leiv Rieger, et al.
(2019) WATER SCIENCE AND TECHNOLOGY. 79(1). p.3-14
Author
Organization
Abstract
The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources - e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis - keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.
Keywords
activated sludge model, big-data, computational fluid dynamics, dynamic simulation, modelling, wastewater, WASTE-WATER TREATMENT, PRINCIPAL COMPONENT ANALYSIS, BIOLOGICAL NITROGEN REMOVAL, CHEMICAL OXYGEN-DEMAND, ACTIVATED-SLUDGE, DATA RECONCILIATION, SIZE DISTRIBUTION, PARAMETERS, SYSTEMS, PERSPECTIVE

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Citation

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MLA
Regmi, Pusker, et al. “The Future of WRRF Modelling : Outlook and Challenges.” WATER SCIENCE AND TECHNOLOGY, vol. 79, no. 1, 2019, pp. 3–14, doi:10.2166/wst.2018.498.
APA
Regmi, P., Stewart, H., Amerlinck, Y., Arnell, M., García, P. J., Johnson, B., … Rosso, D. (2019). The future of WRRF modelling : outlook and challenges. WATER SCIENCE AND TECHNOLOGY, 79(1), 3–14. https://doi.org/10.2166/wst.2018.498
Chicago author-date
Regmi, Pusker, Heather Stewart, Youri Amerlinck, Magnus Arnell, Pau Juan García, Bruce Johnson, Thomas Maere, et al. 2019. “The Future of WRRF Modelling : Outlook and Challenges.” WATER SCIENCE AND TECHNOLOGY 79 (1): 3–14. https://doi.org/10.2166/wst.2018.498.
Chicago author-date (all authors)
Regmi, Pusker, Heather Stewart, Youri Amerlinck, Magnus Arnell, Pau Juan García, Bruce Johnson, Thomas Maere, Ivan Miletić, Mark Miller, Leiv Rieger, Randal Samstag, Domenico Santoro, Oliver Schraa, Spencer Snowling, Imre Takács, Elena Torfs, Mark CM van Loosdrecht, Peter A Vanrolleghem, Kris Villez, Eveline Volcke, Stefan Weijers, Paloma Grau, José Jimenez, and Diego Rosso. 2019. “The Future of WRRF Modelling : Outlook and Challenges.” WATER SCIENCE AND TECHNOLOGY 79 (1): 3–14. doi:10.2166/wst.2018.498.
Vancouver
1.
Regmi P, Stewart H, Amerlinck Y, Arnell M, García PJ, Johnson B, et al. The future of WRRF modelling : outlook and challenges. WATER SCIENCE AND TECHNOLOGY. 2019;79(1):3–14.
IEEE
[1]
P. Regmi et al., “The future of WRRF modelling : outlook and challenges,” WATER SCIENCE AND TECHNOLOGY, vol. 79, no. 1, pp. 3–14, 2019.
@article{8614114,
  abstract     = {{The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources - e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis - keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.}},
  author       = {{Regmi, Pusker and Stewart, Heather and Amerlinck, Youri and Arnell, Magnus and García, Pau Juan and Johnson, Bruce and Maere, Thomas and Miletić, Ivan and Miller, Mark and Rieger, Leiv and Samstag, Randal and Santoro, Domenico and Schraa, Oliver and Snowling, Spencer and Takács, Imre and Torfs, Elena and van Loosdrecht, Mark CM and Vanrolleghem, Peter A and Villez, Kris and Volcke, Eveline and Weijers, Stefan and Grau, Paloma and Jimenez, José and Rosso, Diego}},
  issn         = {{0273-1223}},
  journal      = {{WATER SCIENCE AND TECHNOLOGY}},
  keywords     = {{activated sludge model,big-data,computational fluid dynamics,dynamic simulation,modelling,wastewater,WASTE-WATER TREATMENT,PRINCIPAL COMPONENT ANALYSIS,BIOLOGICAL NITROGEN REMOVAL,CHEMICAL OXYGEN-DEMAND,ACTIVATED-SLUDGE,DATA RECONCILIATION,SIZE DISTRIBUTION,PARAMETERS,SYSTEMS,PERSPECTIVE}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{3--14}},
  title        = {{The future of WRRF modelling : outlook and challenges}},
  url          = {{http://dx.doi.org/10.2166/wst.2018.498}},
  volume       = {{79}},
  year         = {{2019}},
}
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