Advanced search
1 file | 1.73 MB Add to list

Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques

Author
Organization
Abstract
Emission of N2O represents an increasing concern in wastewater treatment, in particular for its large contribution to the plant's carbon footprint (CFP). In view of the potential introduction of more stringent regulations regarding wastewater treatment plants' CFP, there is a growing need for advanced monitoring with online implementation of mitigation strategies for N2O emissions. Mechanistic kinetic modelling in full-scale applications, are often represented by a very detailed representation of the biological mechanisms resulting in an elevated uncertainty on the many parameters used while limited by a poor representation of hydrodynamics. This is particularly true for current N2O kinetic models. In this paper, a possible full-scale implementation of a data mining approach linking plant-specific dynamics to N2O production is proposed. A data mining approach was tested on full-scale data along with different clustering techniques to identify process criticalities. The algorithm was designed to provide an applicable solution for full-scale plants' control logics aimed at online N2O emission mitigation. Results show the ability of the algorithm to isolate specific N2O emission pathways, and highlight possible solutions towards emission control.
Keywords
BIOMATH, Greenhouse gas, Nitrous oxide, Wastewater treatment, PCA, Carbon footprint, Control, WASTE-WATER TREATMENT, AMMONIA-OXIDIZING BACTERIA, NITROUS-OXIDE EMISSIONS, DISSOLVED-OXYGEN, NITRIC-OXIDE, DYNAMICS

Downloads

  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.73 MB

Citation

Please use this url to cite or link to this publication:

MLA
Bellandi, Giacomo, et al. “Towards an Online Mitigation Strategy for N2O Emissions through Principal Components Analysis and Clustering Techniques.” JOURNAL OF ENVIRONMENTAL MANAGEMENT, vol. 261, 2020, doi:10.1016/j.jenvman.2020.110219.
APA
Bellandi, G., Weijers, S., Gori, R., & Nopens, I. (2020). Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 261. https://doi.org/10.1016/j.jenvman.2020.110219
Chicago author-date
Bellandi, Giacomo, Stefan Weijers, Riccardo Gori, and Ingmar Nopens. 2020. “Towards an Online Mitigation Strategy for N2O Emissions through Principal Components Analysis and Clustering Techniques.” JOURNAL OF ENVIRONMENTAL MANAGEMENT 261. https://doi.org/10.1016/j.jenvman.2020.110219.
Chicago author-date (all authors)
Bellandi, Giacomo, Stefan Weijers, Riccardo Gori, and Ingmar Nopens. 2020. “Towards an Online Mitigation Strategy for N2O Emissions through Principal Components Analysis and Clustering Techniques.” JOURNAL OF ENVIRONMENTAL MANAGEMENT 261. doi:10.1016/j.jenvman.2020.110219.
Vancouver
1.
Bellandi G, Weijers S, Gori R, Nopens I. Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques. JOURNAL OF ENVIRONMENTAL MANAGEMENT. 2020;261.
IEEE
[1]
G. Bellandi, S. Weijers, R. Gori, and I. Nopens, “Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques,” JOURNAL OF ENVIRONMENTAL MANAGEMENT, vol. 261, 2020.
@article{8659685,
  abstract     = {{Emission of N2O represents an increasing concern in wastewater treatment, in particular for its large contribution to the plant's carbon footprint (CFP). In view of the potential introduction of more stringent regulations regarding wastewater treatment plants' CFP, there is a growing need for advanced monitoring with online implementation of mitigation strategies for N2O emissions. Mechanistic kinetic modelling in full-scale applications, are often represented by a very detailed representation of the biological mechanisms resulting in an elevated uncertainty on the many parameters used while limited by a poor representation of hydrodynamics. This is particularly true for current N2O kinetic models. In this paper, a possible full-scale implementation of a data mining approach linking plant-specific dynamics to N2O production is proposed. A data mining approach was tested on full-scale data along with different clustering techniques to identify process criticalities. The algorithm was designed to provide an applicable solution for full-scale plants' control logics aimed at online N2O emission mitigation. Results show the ability of the algorithm to isolate specific N2O emission pathways, and highlight possible solutions towards emission control.}},
  articleno    = {{110219}},
  author       = {{Bellandi, Giacomo and Weijers, Stefan and Gori, Riccardo and Nopens, Ingmar}},
  issn         = {{0301-4797}},
  journal      = {{JOURNAL OF ENVIRONMENTAL MANAGEMENT}},
  keywords     = {{BIOMATH,Greenhouse gas,Nitrous oxide,Wastewater treatment,PCA,Carbon footprint,Control,WASTE-WATER TREATMENT,AMMONIA-OXIDIZING BACTERIA,NITROUS-OXIDE EMISSIONS,DISSOLVED-OXYGEN,NITRIC-OXIDE,DYNAMICS}},
  language     = {{eng}},
  pages        = {{8}},
  title        = {{Towards an online mitigation strategy for N2O emissions through principal components analysis and clustering techniques}},
  url          = {{http://dx.doi.org/10.1016/j.jenvman.2020.110219}},
  volume       = {{261}},
  year         = {{2020}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: