Modeling and optimization of granulation process of activated sludge in sequencing batch reactors

Abstract

Aerobic granulation is a promising process for wastewater treatment, but this granulation process is very complicated and is affected by many factors. Thus, a mathematical model to quantitatively describe such a granulation process is highly desired. In this work, by taking into account all of key steps including biomass growth, increase in particle size and density, detachment, breakage and sedimentation, an one-dimensional mathematic model was developed to simulate the granulation process of activated sludge in a sequencing batch reactor (SBR). Discretization methodology was applied by dividing operational time, sedimentation process, size fractions and slices into discretized calculation elements. Model verification and prediction for aerobic granulation process were conducted under four different conditions. Four parameters indicative of granulation progression, including mean radius, biomass discharge ratio, total number, and bioparticle size distribution, were predicted well with the model. An optimum controlling strategy, automatically adjusted of settling time, was also proposed based on this model. Moreover, aerobic granules with a density higher than 120 g VSS/L and radius in a range of 0.4-1.0 mm were predicted to have both high settling velocity and substrate utilization rate, and the corresponding optimum operating conditions were be determined. Experimental results demonstrate that the developed model is appropriate for simulating the formation of aerobic granules in SBRs. These results are useful for designing and optimizing the cultivation and operation of aerobic granule process.

Effects of Wash-Out Dynamics on Nitrifying Bacteria in Aerobic Granular Sludge During Start-Up at Gradually Decreased Settling Time

“…According to their model simulations, the optimal control strategy would be to keep the biomass discharge ratio between 0.01 and 0.05. This is in good agreement with the discharge ratio in R1 in our investigation, which hereby confirms experimentally that the control strategy proposed by Su et al [20] is indeed successful. Although R2 was operated with twice as high biomass discharge ratios during start-up (first 28 days), this approach was still effective in retaining biomass (Figure 2) while facilitating granulation.…”

“…Therefore, to prevent severe biomass wash-out, or the formation of well-settling flocs instead of granules, a balanced strategy for decreasing the settling time is required during the start-up of granular sludge reactors. Su et al [20] suggested that a stepwise decrease of the settling time based on the biomass discharge ratio could be a successful strategy for achieving fast and effective granulation. According to their model simulations, the optimal control strategy would be to keep the biomass discharge ratio between 0.01 and 0.05.…”

“…Rapid changes in the microbial population have also been documented during start-up [17,18]; however, very few studies have examined the abundance and dynamics of the nitrifying community during granulation [19]. Based on a modeling approach, Su et al [20] suggested that a stepwise decrease of settling time can be an effective method for optimizing biomass discharge during start-up, but their study did not investigate the nutrient removal during granulation.…”

Performance and kinetics of ANAMMOX granular sludge with pH shock in a sequencing batch reactor

“…Decreasing size of granular sludge resulted in the decrease of settling velocity. Our results also agreed with Su et al (2013). In general, the granular sludge became fragile at pH 9.0 and a slight pH increase would lead to further damage on ANAMMOX system.…”

A novel control strategy for enhancing biological N-removal in a granular sequencing batch reactor: A model-based study

“…Vazquez-Padín et al [27] showed that the biomass characteristics could be successfully described if a porosity profile across the granules depth was taken into account. Later, Su et al [28] modeled the variations in size and density of granules due to growth, detachment or breakage, to optimize the size and density of granules.…”