Optimizing Nitrate Dosing Strategies for Sulfide Control Using Kinetic Modeling, Variance‐Based Sensitivity Analysis, and Laboratory‐Scale Sewer Reactors

Sulfide and methane production in sewer systems poses significant operational and environmental challenges, including odor, corrosion, and greenhouse gas emissions. This study investigates the optimization of nitrate dosing strategies to mitigate sulfide generation using a laboratory-scale sewer reactor system combined with mathematical modeling. An extended kinetic model was developed, based on the Wastewater Aerobic/Anaerobic Transformations in Sewers (WATS) model, to simulate sulfide and methane dynamics, incorporating key microbial processes and nitrate-based oxidation pathways. The model was calibrated and validated using experimental data with and without nitrate dosing. A variance-based global sensitivity analysis was performed to identify influential parameters affecting model predictions. Results show that dosing location and rate substantially influence sulfide removal efficiency and residual nitrate levels. Among the tested strategies, nitrate dosing in the third reactor (out of four) at 14.5 mgNO₃-N/L offered optimal trade-offs, achieving sulfide concentrations below 0.5 mgS/L while maintaining effluent nitrate levels at 0.9 mgNO₃-N/L, representing a 42% reduction in dosing costs compared to upstream dosing. These findings provide a quantitative foundation for improving nitrate dosing strategies in sewer networks.

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Publication Details

Journal
Water Environment Research
Published
2025-12-01
DOI
https://doi.org/10.1002/wer.70226
Primary Topic
Odor and Emission Control Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing Nitrate Dosing Strategies for Sulfide Control Using Kinetic Modeling, Variance‐Based Sensitivity Analysis, and Laboratory‐Scale Sewer Reactors

Damien J. Batstone, Domenico Santoro, Christopher T. DeGroot, A. Elsawy Khalil et al.
Water Environment Research
Odor and Emission Control Technologies
article

Optimizing Nitrate Dosing Strategies for Sulfide Control Using Kinetic Modeling, Variance‐Based Sensitivity Analysis, and Laboratory‐Scale Sewer Reactors

Damien J. Batstone, Domenico Santoro, Christopher T. DeGroot, A. Elsawy Khalil, Bassem Haroun
article en

Abstract

Sulfide and methane production in sewer systems poses significant operational and environmental challenges, including odor, corrosion, and greenhouse gas emissions. This study investigates the optimization of nitrate dosing strategies to mitigate sulfide generation using a laboratory-scale sewer reactor system combined with mathematical modeling. An extended kinetic model was developed, based on the Wastewater Aerobic/Anaerobic Transformations in Sewers (WATS) model, to simulate sulfide and methane dynamics, incorporating key microbial processes and nitrate-based oxidation pathways. The model was calibrated and validated using experimental data with and without nitrate dosing. A variance-based global sensitivity analysis was performed to identify influential parameters affecting model predictions. Results show that dosing location and rate substantially influence sulfide removal efficiency and residual nitrate levels. Among the tested strategies, nitrate dosing in the third reactor (out of four) at 14.5 mgNO₃-N/L offered optimal trade-offs, achieving sulfide concentrations below 0.5 mgS/L while maintaining effluent nitrate levels at 0.9 mgNO₃-N/L, representing a 42% reduction in dosing costs compared to upstream dosing. These findings provide a quantitative foundation for improving nitrate dosing strategies in sewer networks.

Water Environment ResearchVol. 97(12)
Western University (CA), The University of Queensland (AU), USP Technologies (United Kingdom) (GB)
Mitacs, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 69%
Odor and Emission Control Technologies
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Optimizing Nitrate Dosing Strategies for Sulfide Control Using Kinetic Modeling, Variance‐Based Sensitivity Analysis, and Laboratory‐Scale Sewer Reactors — Damien J. Batstone, Domenico Santoro, et al. · Water Environment Research (2025) | TGRS Research Map | TGRS