A benchmark simulation model, which includes a wastewater treatment plant (WWTP)-wide model and a rising main sewer model, is proposed for testing mitigation strategies to reduce the system's greenhouse gas (GHG) emissions. The sewer model was run to predict methane emissions, and its output was used as the WWTP model input. An activated sludge model for GHG (ASMG) was used to describe nitrous oxide (N2O) generation and release in activated sludge process. N2O production through both heterotrophic and autotrophic pathways was included. Other GHG emissions were estimated using empirical relationships. Different scenarios were evaluated comparing GHG emissions, effluent quality and energy consumption. Aeration control played a clear role in N2O emissions, through concentrations and distributions of dissolved oxygen (DO) along the length of the bioreactor. The average value of N2O emission under dynamic influent cannot be simulated by a steady-state model subjected to a similar influent quality, stressing the importance of dynamic simulation and control. As the GHG models have yet to be validated, these results carry a degree of uncertainty; however, they fulfilled the objective of this study, i.e. to demonstrate the potential of a dynamic system-wide modelling and benchmarking approach for balancing water quality, operational costs and GHG emissions.
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Research Article|
December 01 2012
Towards a benchmarking tool for minimizing wastewater utility greenhouse gas footprints
L. Guo
;
1
modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1065 av. de la Médecine, Quebec, QC, Canada G1V 0A6
E-mail: lisha.guo.1@ulaval.ca
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J. Porro
;
J. Porro
2
Malcolm Pirnie (now The Water Division of ARCADIS), 27-01 Queens Plaza North, Ste. 800, Long Island City, NY 11101, USA3
BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium
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K. R. Sharma
;
K. R. Sharma
4
Advanced Water Management Center (AWMC), The University of Queensland, Brisbane, QLD 4072, Australia
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Y. Amerlinck
;
Y. Amerlinck
3
BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium
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L. Benedetti
;
L. Benedetti
5
WATERWAYS srl, Via del Ferrone 88, 50023 Impruneta (FI), Italy
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I. Nopens
;
I. Nopens
3
BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium
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A. Shaw
;
A. Shaw
6
Black & Veatch, 8400 Ward Parkway, Kansas City, MO 64114, USA and Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA
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S. W. H. Van Hulle
;
S. W. H. Van Hulle
3
BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium7
EnBiChem, University College West Flanders, Graaf Karel de Goedelaan 5, 8500 Kortrijk, Belgium
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Z. Yuan
;
Z. Yuan
4
Advanced Water Management Center (AWMC), The University of Queensland, Brisbane, QLD 4072, Australia
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P. A. Vanrolleghem
P. A. Vanrolleghem
1
modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1065 av. de la Médecine, Quebec, QC, Canada G1V 0A6
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Water Sci Technol (2012) 66 (11): 2483-2495.
Article history
Received:
February 24 2012
Accepted:
July 11 2012
Citation
L. Guo, J. Porro, K. R. Sharma, Y. Amerlinck, L. Benedetti, I. Nopens, A. Shaw, S. W. H. Van Hulle, Z. Yuan, P. A. Vanrolleghem; Towards a benchmarking tool for minimizing wastewater utility greenhouse gas footprints. Water Sci Technol 1 December 2012; 66 (11): 2483–2495. doi: https://doi.org/10.2166/wst.2012.495
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L. Guo, J. Porro, K. R. Sharma, Y. Amerlinck, L. Benedetti, I. Nopens, A. Shaw, S. W. H. Van Hulle, Z. Yuan, P. A. Vanrolleghem; Towards a benchmarking tool for minimizing wastewater utility greenhouse gas footprints. Water Sci Technol 1 December 2012; 66 (11): 2483–2495. doi: https://doi.org/10.2166/wst.2012.495
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