TY - JOUR
T1 - Systematic calibration of N2O emissions from a full-scale WWTP including a tracer test and a global sensitivity approach
AU - Solís, Borja
AU - Guisasola, Albert
AU - Pijuan, Maite
AU - Corominas, Lluís
AU - Baeza, Juan Antonio
N1 - Funding Information:
Borja Sol?s is grateful for the PIF PhD grant funded by Universitat Aut?noma de Barcelona. Borja Sol?s, Albert Guisasola and Juan Antonio Baeza are members of the GENOCOV research group (Grup de Recerca Consolidat de la Generalitat de Catalunya, 2017 SGR 1175, www.genocov.com) and were supported by the European Union's Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie C-FOOT-CTRL project (grant agreement No 645769). M. Pijuan and Ll. Corominas acknowledge the support from the Economy and Knowledge Department of the Catalan Government through a Consolidated Research Group (ICRA-TECH - 2017 SGR 1318) - Catalan Institute for Water Research. A special thanks to Ms. Cristina Pujol and Mr. Llu?s Ayach from TRARGISA, the company responsible for the operation of the WWTP for all the help during the monitoring campaign. We acknowledge the contribution of Dr. Ayla Kiser (www.aylakiser.com) in the design and execution of the tracer test.
Funding Information:
Borja Solís is grateful for the PIF PhD grant funded by Universitat Autònoma de Barcelona. Borja Solís, Albert Guisasola and Juan Antonio Baeza are members of the GENOCOV research group (Grup de Recerca Consolidat de la Generalitat de Catalunya, 2017 SGR 1175, www.genocov.com ) and were supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie C-FOOT-CTRL project (grant agreement No 645769). M. Pijuan and Ll. Corominas acknowledge the support from the Economy and Knowledge Department of the Catalan Government through a Consolidated Research Group (ICRA-TECH - 2017 SGR 1318) - Catalan Institute for Water Research. A special thanks to Ms. Cristina Pujol and Mr. Lluís Ayach from TRARGISA, the company responsible for the operation of the WWTP for all the help during the monitoring campaign. We acknowledge the contribution of Dr. Ayla Kiser ( www.aylakiser.com ) in the design and execution of the tracer test.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/5/1
Y1 - 2022/5/1
N2 - Nitrous oxide (N2O) is a greenhouse gas (GHG) emitted during biological nitrogen removal from wastewater treatment plants (WWTPs). Some modelling tools have been proposed to predict N2O emissions during the design and operation of WWTPs. In this study, the novel ASM2d-N2O model, which accounts for the production of N2O in nutrient removal WWTPs, was used to study the associated emissions from a full-scale WWTP with two independent lines. Firstly, the hydraulics of the WWTP was characterized by a residence time distribution test, showing the flow was equally divided into the two treatment lines (49.3 vs. 50.7%), that each reactor worked as an ideal continuous stirred tank reactor and the secondary settler model flux was similar to a plug-flow reactor. The ASM2d-N2O model was then calibrated using experimental data obtained under dynamic conditions. A global sensitivity analysis was used to select, among 59 model parameters, five candidates that resulted to be related to nitrifying organisms. Different parameter subsets up to four parameters were evaluated, being the subset [µNOB, qAOB_AMO, KO2_NOB, KNO2_NOB] the best, achieving 53.3% reduction of the calibration cost function. The model fit obtained provided a reasonably description of nutrients and N2O emission trends, considering the inherent operational variability suffered in full-scale WWTPs. Finally, a simulation-based study showed that, for the given WWTP and operational conditions, an unbalanced distribution of flow-rate between the two treatment lines did not result in a significant increase on N2O emissions. The results obtained show that this model can be a suitable tool for predicting N2O emissions in full-scale WWTPs, and can therefore be used to find operational conditions that help to minimise these emissions.
AB - Nitrous oxide (N2O) is a greenhouse gas (GHG) emitted during biological nitrogen removal from wastewater treatment plants (WWTPs). Some modelling tools have been proposed to predict N2O emissions during the design and operation of WWTPs. In this study, the novel ASM2d-N2O model, which accounts for the production of N2O in nutrient removal WWTPs, was used to study the associated emissions from a full-scale WWTP with two independent lines. Firstly, the hydraulics of the WWTP was characterized by a residence time distribution test, showing the flow was equally divided into the two treatment lines (49.3 vs. 50.7%), that each reactor worked as an ideal continuous stirred tank reactor and the secondary settler model flux was similar to a plug-flow reactor. The ASM2d-N2O model was then calibrated using experimental data obtained under dynamic conditions. A global sensitivity analysis was used to select, among 59 model parameters, five candidates that resulted to be related to nitrifying organisms. Different parameter subsets up to four parameters were evaluated, being the subset [µNOB, qAOB_AMO, KO2_NOB, KNO2_NOB] the best, achieving 53.3% reduction of the calibration cost function. The model fit obtained provided a reasonably description of nutrients and N2O emission trends, considering the inherent operational variability suffered in full-scale WWTPs. Finally, a simulation-based study showed that, for the given WWTP and operational conditions, an unbalanced distribution of flow-rate between the two treatment lines did not result in a significant increase on N2O emissions. The results obtained show that this model can be a suitable tool for predicting N2O emissions in full-scale WWTPs, and can therefore be used to find operational conditions that help to minimise these emissions.
KW - Dynamic calibration
KW - Global sensitivity analysis
KW - Nitrous oxide
KW - WWTP modelling
UR - http://www.scopus.com/inward/record.url?scp=85123622609&partnerID=8YFLogxK
U2 - 10.1016/j.cej.2022.134733
DO - 10.1016/j.cej.2022.134733
M3 - Article
AN - SCOPUS:85123622609
VL - 435
JO - Chemical Engineering Journal
JF - Chemical Engineering Journal
SN - 1385-8947
M1 - 134733
ER -