Sensitivity analysis for an elemental sulfur-based two-step denitrification model

Modelling of hydrogenotrophic denitrification process in a venturi-integrated membrane bioreactor

The aim of this study is to model a hydrogenotrophic denitrification process in a venturi-integrated submerged membrane bioreactor (MBR) system. The MBR was operated in batch mode using feed concentrations of 100 and 150 mg NO3-N/L. In contrast to most of the denitrification process models that represent the mixed culture with one composite biomass parameter, the biomass was subdivided into two main categories in this modelling study: mainly nitrate-reducing biomass and mainly nitrite-reducing biomass. The determination coefficients (r2) in the range of 0.97-0.99 indicate that the model successfully simulates the concentrations of nitrate- and nitrite-nitrogen in the bioreactor. The maximum specific growth rate of nitrite-reducing biomass (0.06 h-1) was found to be higher than that of nitrate-reducing biomass (0.0002 h-1). Similarly, the growth yield coefficient of nitrite-reducing biomass was higher than that of nitrate-reducing biomass (0.44 vs. 0.31 g biomass/g substrate). The kinetic and stoichiometric coefficients obtained from this modelling study suggest that the limiting step determining the overall conversion rate of hydrogenotrophic denitrification process is the conversion of nitrite to nitrogen gas.

Modelling the effect of SMP production and external carbon addition on S-driven autotrophic denitrification

The aim of this study was to develop a mathematical model to assess the effect of soluble microbial products production and external carbon source addition on the performance of a sulfur-driven autotrophic denitrification (SdAD) process. During SdAD, the growth of autotrophic biomass (AUT) was accompanied by the proliferation of heterotrophic biomass mainly consisting of heterotrophic denitrifiers (HD) and sulfate-reducing bacteria (SRB), which are able to grow on both the SMP derived from the microbial activities and on an external carbon source. The process was supposed to occur in a sequencing batch reactor to investigate the effects of the COD injection on both heterotrophic species and to enhance the production and consumption of SMP. The mathematical model was built on mass balance considerations and consists of a system of nonlinear impulsive differential equations, which have been solved numerically. Different simulation scenarios have been investigated by varying the main operational parameters: cycle duration, day of COD injection and quantity of COD injected. For cycle durations of more than 15 days and a COD injection after the half-cycle duration, SdAD represents the prevailing process and the SRB represent the main heterotrophic family. For shorter cycle duration and COD injections earlier than the middle of the cycle, the same performance can be achieved increasing the quantity of COD added, which results in an increased activity of HD. In all the performed simulation even in the case of COD addition, AUT remain the prevailing microbial family in the reactor.

Advances in elemental sulfur-driven bioprocesses for wastewater treatment: From metabolic study to application

Elemental sulfur (S0) is known to be an abundant, non-toxic material with a wide range of redox states (-2 to +6) and may serve as an excellent electron carrier in wastewater treatment. In turn, S0-driven bioprocesses, which employ S0 as electron donor or acceptor, have recently established themselves as cost-effective therefore attractive solutions for wastewater treatment. Numerous related processes have, to date, been developed from laboratory experiments into full-scale applications, including S0-driven autotrophic denitrification for nitrate removal and S0-reducing organic removal. Compared to the conventional activated sludge process, these bioprocesses require only a small amount of organic matter and produce very little sludge. There have been great efforts to characterize chemical and biogenic S0 and related functional microorganisms in order to identify the biochemical pathways, upgrade the bioprocesses, and assess the impact of the operating factors on process performance, ultimately aiming to better understand and to optimize the processes. This paper is therefore a comprehensive overview of emerging S0-driven biotechnologies, including the development of S0-driven autotrophic denitrification and S0-based sulfidogenesis, as well as the associated microbiology and biochemistry. Also reviewed here are the physicochemical characteristics of S0 and the effects that environmental factors such as pH, influent sulfur/nitrate ratio, temperature, S0 particle size and reactor configurations have on the process. Research gaps, challenges of process applications and potential areas for future research are further proposed and discussed.

Biofilm carrier type affects biogenic sulfur-driven denitrification performance and microbial community dynamics in moving-bed biofilm reactors

Autotrophic denitrification with biosulfur (ADBIOS) provides a sustainable technological solution for biological nitrogen removal from wastewater driven by biogenic S⁰, derived from biogas desulfurization. In this study, the effect of different biofilm carriers (conventional AnoxK™ 1 and Z-200 with a pre-defined maximum biofilm thickness) on ADBIOS performance and microbiomics was investigated in duplicate moving bed-biofilm reactors (MBBRs). The MBBRs were operated parallelly in continuous mode for 309 days, whilst gradually decreasing the hydraulic retention time (HRT) from 72 to 21 h, and biosulfur was either pumped in suspension (days 92-223) or supplied in powder form. Highest nitrate removal rates were approximately 225 (±11) mg/L·d and 180 (±7) mg NO₃^--N/L·d in the MBBRs operated with K1 and Z-200 carriers, respectively. Despite having the same protected surface area for biofilm development in each MBBR, the biomass attached onto the K1 carrier was 4.8-fold more than that on the Z-200 carrier, with part of the biogenic S⁰ kept in the biofilm. The microbial communities of K1 and Z-200 biofilms could also be considered similar at cDNA level in terms of abundance (R = 0.953 with p = 0.042). A relatively stable microbial community was formed on K1 carriers, while the active portion of the microbial community varied significantly over time in the MBBRs using Z-200 carriers.

Modeling of the effect of zeolite concentration on the biological nitrification process in the presence of sulfide and organic matter

The evaluation of the nitrification kinetics in the simultaneous presence of sulfide and organic matter using zeolite as improver was the main goal of this work. According to the sensitivity and collinearity analyses, five parameters were the most sensitive in the model, whose calibrated values were: μ _{max, AOB} = 0.02642 ± 0.002 h^-1; μ _{max, NOB} = 0.3307 ± 0.416 h^-1; K _S,NOB = 1.65·10^-6 ± 2.85·10^-6 mgHNO₂-N/L; k _S2 = 0.8213 ± 0.076 and n = 0.6537 ± 0.030. A good fit between the experimental data and the model's results including the effect of zeolite on the kinetic parameters was obtained, with Theil inequality coefficient values between 0.109 and 0.007 for all the variables studied, with all of these values lower than 0.3. Thus, the model proposed is robust and can simulate the nitrification process in the presence of sulfide and organic matter when zeolite was used as improver.

Elemental sulfur-based autotrophic denitrification in stoichiometric S0/N ratio: Calibration and validation of a kinetic model

The inclusion of S⁰ hydrolysis in a kinetic model of autotrophic denitrification has been recently proposed; however the model has not been calibrated or validated yet. Thus, a new methodology was developed and applied to calibrate and validate this kinetic model for the first time. An inoculum adapted from a poultry wastewater treatment plant at stoichiometric S⁰/NO₃^- ratio was used. The model was calibrated with batch data (initial nitrate concentrations of 50 and 6.25 mg NO₃^--N/L) at an S⁰/N ratio = 2.29 mg S/mg N and validated with seven different batch data. The sensitivity analysis showed that the most sensitive parameters are related to S⁰ hydrolysis. The kinetic model was successfully calibrated with the new methodology and validated, with Theil inequality coefficient values lower than 0.21. Thus, the proposed model and methodology were proved to be well suited for the simulation of elemental sulfur-based autotrophic denitrification in batch systems.