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Main Authors: Domingo-Félez, Carlos, Smets, Barth F.
Format: Preprint
Published: 2018
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Online Access:https://arxiv.org/abs/1811.00004
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author Domingo-Félez, Carlos
Smets, Barth F.
author_facet Domingo-Félez, Carlos
Smets, Barth F.
contents Nitrous oxide (N2O) is a potent greenhouse gas emitted during biological wastewater treatment. A pseudo-mechanistic model describing three biological pathways for nitric oxide (NO) and N2O production was calibrated for mixed culture biomass from an activated sludge process using laboratory-scale experiments. The model (NDHA) comprehensively describes N2O producing pathways by both autotrophic ammonium oxidizing bacteria and heterotrophic bacteria. Extant respirometric assays and anaerobic batch experiments were designed to calibrate endogenous and exogenous processes (heterotrophic denitrification and autotrophic ammonium/nitrite oxidation) together with the associated net N2O production. Ten parameters describing heterotrophic processes and seven for autotrophic processes were accurately estimated (variance/mean < 25%). The model predicted NO and N2O dynamics at varying dissolved oxygen, ammonium and nitrite levels and was validated against an independent set of experiments with the same biomass. Aerobic ammonium oxidation experiments at two oxygen levels used for model evaluation (2 and 0.5 mg/L) indicated that both the nitrifier denitrification (42, 64%) and heterotrophic denitrification (7, 17%) pathways increased and dominated N2O production at high nitrite and low oxygen concentrations; while the nitrifier nitrification pathway showed the largest contribution at high dissolved oxygen levels (51, 19%). The uncertainty of the biological parameter estimates was propagated to N2O model outputs via Monte Carlo simulations as 95% confidence intervals. The accuracy of the estimated parameters resulted in a low uncertainty of the N2O emission factors (4.6 +- 0.6% and 1.2 +- 0.1%).
format Preprint
id arxiv_https___arxiv_org_abs_1811_00004
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle Modelling N2O dynamics of activated sludge biomass under nitrifying and denitrifying conditions: pathway contributions and uncertainty analysis
Domingo-Félez, Carlos
Smets, Barth F.
Quantitative Methods
Nitrous oxide (N2O) is a potent greenhouse gas emitted during biological wastewater treatment. A pseudo-mechanistic model describing three biological pathways for nitric oxide (NO) and N2O production was calibrated for mixed culture biomass from an activated sludge process using laboratory-scale experiments. The model (NDHA) comprehensively describes N2O producing pathways by both autotrophic ammonium oxidizing bacteria and heterotrophic bacteria. Extant respirometric assays and anaerobic batch experiments were designed to calibrate endogenous and exogenous processes (heterotrophic denitrification and autotrophic ammonium/nitrite oxidation) together with the associated net N2O production. Ten parameters describing heterotrophic processes and seven for autotrophic processes were accurately estimated (variance/mean < 25%). The model predicted NO and N2O dynamics at varying dissolved oxygen, ammonium and nitrite levels and was validated against an independent set of experiments with the same biomass. Aerobic ammonium oxidation experiments at two oxygen levels used for model evaluation (2 and 0.5 mg/L) indicated that both the nitrifier denitrification (42, 64%) and heterotrophic denitrification (7, 17%) pathways increased and dominated N2O production at high nitrite and low oxygen concentrations; while the nitrifier nitrification pathway showed the largest contribution at high dissolved oxygen levels (51, 19%). The uncertainty of the biological parameter estimates was propagated to N2O model outputs via Monte Carlo simulations as 95% confidence intervals. The accuracy of the estimated parameters resulted in a low uncertainty of the N2O emission factors (4.6 +- 0.6% and 1.2 +- 0.1%).
title Modelling N2O dynamics of activated sludge biomass under nitrifying and denitrifying conditions: pathway contributions and uncertainty analysis
topic Quantitative Methods
url https://arxiv.org/abs/1811.00004