Using computational fluid dynamics to describe H2S mass transfer across the water–air interface in sewers

Abstract

For the past 70 years, researchers have dealt with the investigation of odour in sewer systems caused by hydrogen sulphide formations and the development of approaches to describe it. The state-of-the-art models are one-dimensional. At the same time, flow and transport phenomena in sewers can be three-dimensional, for example the air flow velocities in circular pipes or flow velocities of water and air in the reach of drop structures. Within the past years, increasing computational capabilities enabled the development of more complex models. This paper uses a three-dimensional two-phase computational fluid dynamics model to describe mass transfer phenomena between the two phases: water and air. The solver has been extended to be capable of accounting account for temperature dependency, the influence of pH value and a conversion to describe simulated air phase concentrations as partial pressure. Its capabilities are being explored in different application examples and its advantages compared to existing models are demonstrated in a highly complex three-dimensional test case. The resulting interH2SFoam solver is a significant step in the direction of describing and analysing H2S emissions in sewers.

Experimental determination of the H2S mass transfer coefficient across the liquid–gas interface in gravity sewers

“…The saturation concentration at equilibrium is influenced by Henrýs constant and therefore, by its temperature dependency. This effect was considered using the vant Hoff equation (Equation ( 18) as described in (Sander 2015;Teuber et al 2019).…”

Water quality modeling in sewer networks: Review and future research directions

“…For example, as shown in this table, when considering sulfide as the quality parameter, two main processes have been modelled. These are the production of sulfide within the SNs under different environmental conditions or impacted by different covariates (e.g., temperature, chemical dosage, Jiang et al, 2010, Alani et al, 2014 and the mass transfer (e.g., H2S) between the wastewater in SNs and the air under various air velocities (Matias et al, 2018, Teuber et al, 2019. For the regression models of sulfides, the covariates (i.e., inputs) can vary ranging from sewer structure and seasons to wastewater characteristics and chemical dosages, and the model outputs can be H2S emission hotspots (Zuo et al, 2019) or sulfide concentrations (Jiang et al, 2011).…”

“…As observed from Figure 5, empirical process-driven models have been employed more frequently than kinetic process-driven models for all modelling purposes. This is because the dynamic biochemical behaviours of many water quality parameters can be significantly affected by environmental conditions (e.g., flow velocities, Teuber et al 2019) and hence it is necessary to account for such environmental factors within the modelling process with the aid of empirical processdriven models (Verdaguer et al 2014). For prediction, the number of data-driven model applications is significantly larger compared to those developed to enable understanding and control, as shown in Figure 5.…”

Design and implementation of verification device for dissolved oxygen tester

“…Through the diffusion of oxygen in the gas to the electrolyte immediately occurs reduction reaction on the cathode, oxidation reaction on the anode, the current generated by the reaction is proportional to the concentration of oxygen, by measuring the size of the current in the electrode can be calculated the concentration of dissolved oxygen. The oxygen electrode method is able to detect the concentration of dissolved oxygen online while avoiding the effects of wastewater chroma, turbidity, iron ions in the wastewater, and other impurity ions that can interact with iodine [9][10][11][12] . The verification effort also requires manual manipulation, which is less efficient and inevitably introduces human error, so it is particularly necessary to develop an integrated verification device with a high level of automation.…”