Validation of linear and non-linear kinetic modeling of saline wastewater treatment by sequencing batch reactor with adapted and non-adapted consortiums

Sequential batch membrane bio-reactor for wastewater treatment: The effect of increased salinity

“…Only a slight decrease in the heterotrophic yield coefficient (Y H ) and the maximum heterotrophic growth rate (l H,max ) were observed during the experiment. This result might suggest that variations in the biokinetic coefficients may be related to the existence of biochemical mechanisms within the bacterial cell for adaptation to a saline environment, which is in agreement with what was found in previous studies (Amin et al, 2014). Nevertheless, the similarity of the biokinetic parameters determined for the present study with the typical ones observed in CAS processes (Table 3) highlights the fact that a good acclimation level was reached at the end of the experiment.…”

“…Ye et al (2009) found that the salinity exerted a significant impact on nitrifying bacteria in a SBR. Moreover, the bacterial wash-out due to salinity may promote an increase in the effluent turbidity (Amin et al, 2014). During the last decades, new approaches to designing and operating SBRs have been explored to achieve very high effluent qualities when treating non domestic wastewater (e.g., multiple tanks and innovative technologies such as membrane bioreactors -MBR, etc.).…”

“…Sequential Batch Reactors (SBRs), set up to treat industrial and civil wastewater in a single biological reactor and operated according to five discrete periods (fill, react, settle, draw and idle), were also investigated to treat saline wastewater (Artan and Orhon, 2005;Campos et al, 2002;Rene et al, 2008). Amin et al (2014) recently found that treating saline wastewater in an SBR resulted in substrate consumption that is better described by a secondorder kinetic rather than the Monod first order kinetic. Ye et al (2009) found that the salinity exerted a significant impact on nitrifying bacteria in a SBR.…”

Modeling microbial growth and dynamics

“…With few exceptions (e.g., Amin et al 2014), the bulk of WWT models simulates the microbial growth process by the use of the well-established hyperbolic Monod function μ = μ 0 S/(K S + S), where the microbial growth rate μ is modeled as a function of a maximum (biologically limited) growth rate μ 0 , the substrate concentration S, and a halfsaturation constant K S that gives the substrate concentration at which μ takes half the value of μ 0 (Monod 1949). This growth model assumes that microbial growth is modulated and limited by only one specific substrate.…”

“…Wastewater treatment systems are thus usually open systems with, heuristically speaking, an influx of fresh wastewater and an efflux of a mixture of bulk fluid and microbial biomass. The microbial community is in part a function of the composition of the available substrate, e.g., sewage (Henze et al 2000;Makinia 2010) or industrial wastewater (Debik and Coskun 2009;Tekerlekopoulou et al 2013;Amin et al 2014), which in turn depends on the composition and activity of the microbial community. Consequently, the management of wastewater treatment processes, such as the activated sludge process (Ardern and Lockett 1914), membrane bioreactors (Brindle and Stephenson 1996), or membrane-aerated biofilm reactors (Casey et al 1999), is often closely related to the management of microbial communities and activities by providing optimal growth conditions for a target community.…”