Development of a model for activated sludge aeration systems: linking air supply, distribution, and demand

Abstract

During the design of a water resource recovery facility, it is becoming industry practice to use simulation software to assist with process design. Aeration is one of the key components of the activated sludge process, and is one of the most important aspects of modelling wastewater treatment systems. However, aeration systems are typically not modelled in detail in most wastewater treatment process modelling studies. A comprehensive dynamic aeration system model has been developed that captures both air supply and demand. The model includes sub-models for blowers, pipes, fittings, and valves. An extended diffuser model predicts both oxygen transfer efficiency within an aeration basin and pressure drop across the diffusers. The aeration system model allows engineers to analyse aeration systems as a whole to determine biological air requirements, blower performance, air distribution, control valve impacts, controller design and tuning, and energy costs. This enables engineers to trouble-shoot the entire aeration system including process, equipment and controls. It also allows much more realistic design of these highly complex systems.

A Novel Method to Determine Blower Capacity of Wastewater Treatment Plants for Dry and Wet Weather Conditions

“…3E-H) and the peak of the overall oxygen demand concentration was expressed as the mean of the daily maximum, Site #1 had about 278 mg-O 2 /L of the oxygen demand whilst Site #2 and Site #3 had 402 mgO 2 /L and 592 mg-O 2 /L respectively. Since these concentrations were scattered over the 3 sites, use of default values for oxygen demand might not be an attractive option to perform precise plant design, unlike the research by Schraa et al (2017) and USEPA [3]. Indeed, the ratio of the maximum value of the daily maximum to the mean value of the daily average were also distinct over the three sites.…”

“…For the air supply system and the oxygen transfer, the topics have been intensively studied. For instance, with respect to model-ling the aeration system and its energy consumption, Schraa et al (2017) developed a fully dynamic model around the aeration header network to simulate the air distribution, and evaluated its limitations with various optimisation options and influent loadings [3]. Juan-Garcia et al (2018) modified their study to the plant controlling systems by integrating a biokinetic model having oxygen uptake phenomena [4].…”

“…The above-mentioned guidelines only provide default design-daily-average concentrations of BOD 5 and Total Kjeldahl Nitrogen (TKN) with thumb rules to adapt the parameters to the plant design. For example, Schraa et al (2017) and US Environmental Protection Agency (USEPA) selected 150~200 mg-BOD/L and 30~40 mg-N/L as the default BOD 5 concentration and total TKN concentration respectively [3]. With respect to the oxygen demand in design-daily-maximum, the guidelines suggest calculating the load in proportion to the inflow rate of the design-dailyaverage.…”

Hydrodynamics and parametric study of an activated sludge process using residence time distribution technique

“…The intensity of mixing leads to enhanced mass exchange in the AT, hence directly influencing the concentration of residual polluting matter in the effluent. The knowledge of actual reactor MRT can prevent incomplete biochemical reactions in ASP and help in growth of desirable microorganisms [14,23,33]. With the optimal combination of operating parameters, optimized ASP performance can be achieved that result in minimum BOD and COD of the treated effluent [34].…”

“…Several RTD studies performed on ASP shows that the AT acts as a complete mixing tank and excessive air supply is needed to ensure the aerobic condition, provided by air diffusion systems or surface aerators. The rate of aeration often leads to high circulation rates and back-mixing, and affect the sludge particle size and its distribution in the reactor [14][15][16]. These reactors have been often represented with one parameters and two parameters RTD models [17,18].…”