Abstract
Reliable modelling of sulfide and methane production in sewer systems is required for efficient sewer emission management. Wastewater compositions affect sulfide and methane production kinetics through both its short-term variation influencing the substrate availability to sewer biofilms, and its long-term variation affecting the sewer biofilm structure. While the short-term effect is well considered in existing sewer models with the use of Monod or half-order equations, the long-term effect has not been explicitly considered in current sewer models suitable for network modelling. In this study, the long-term effect of wastewater compositions on sulfide and methane production activities in rising main sewers was investigated. A detailed biofilm model was firstly developed, and then calibrated and validated using experimental data measured during the entire biofilm development period of a laboratory sewer reactor. Based on scenario simulations using the detailed biofilm model, empirical equations describing the long-term effect of sulfate and sCOD (soluble chemical oxygen demand) concentrations on kH2S (the maximum sulfide production rate of sewer biofilm) and kCH4 (the maximum methane production rate of sewer biofilm) were proposed. These equations require further verification in future studies before their potential integration into network-wide sewer models. © 2017 Elsevier Ltd
| Original language | English |
|---|---|
| Pages (from-to) | 58-65 |
| Journal | Water Research |
| Volume | 129 |
| DOIs | |
| Publication status | Published - 1 Feb 2018 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This research was funded by the CRC for Water Sensitive Cities through Project 3.1. Jing Sun acknowledges the support of National Natural Science Foundation of China (No. 51608374) and the Program for Young Excellent Talents in Tongji University. Bing-Jie Ni acknowledges the support of Australian Research Council Future Fellowship (FT160100195). Qilin Wang acknowledges the support of Australia Research Discovery Early Career Research Awards (DE160100667).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Research Keywords
- Mathematical model
- Maximum production rate
- Methane
- Sewer biofilm
- Sulfide
- Wastewater compositions
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