Lai Peng

Approach of describing dynamic production of volatile fatty acids from sludge alkaline fermentation.

In this work, a mathematical model was developed to describe the dynamics of fermentation products in sludge alkaline fermentation systems for the first time. In this model, the impacts of alkaline fermentation on sludge disintegration, hydrolysis, acidogenesis, acetogenesis, and methanogenesis processes are specifically considered for describing the high-level formation of fermentation products. The model proposed successfully reproduced the experimental data obtained from five independent sludge alkaline fermentation studies. The modeling results showed that alkaline fermentation largely facilitated the disintegration, acidogenesis, and acetogenesis processes and severely inhibited methanogenesis process. With the pH increase from 7.0 to 10.0, the disintegration, acidogenesis, and acetogenesis processes respectively increased by 53%, 1030%, and 30% while methane production decreased by 3800%. However, no substantial effect on hydrolysis process was found. The model also indicated that the pathway of acetoclastic methanogenesis was more severely inhibited by alkaline condition than that of hydrogentrophic methanogenesis.

Effect of diclofenac on the production of volatile fatty acids from anaerobic fermentation of waste activated sludge

In this study, the impact of diclofenac (DCF), an antiinflammatory drug being extensively used in human health care and veterinary treatment, on the production of volatile fatty acids (VFAs) from anaerobic fermentation of waste activated sludge (WAS) was investigated for the first time. Experimental results showed that when DCF concentration increased from 2.5 to 25u202fmg/kg total suspended solid (TSS), the maximum production of VFAs increased from 599 to 1113u202fmgu202fCOD/L, but further increase of DCF to 47.5u202fmg/kg TSS decreased VFAs yield to 896u202fmgu202fCOD/L. The mechanism investigation revealed that DCF had no effect on the hydrolysis process, promoted the process of acidogenesis, acetogenesis, and homoacetogenesis, but severely inhibited methanogenesis, leading to the accumulation of VFAs. Microbial community analysis showed that the addition of DCF could promote the relative abundance of VFAs (especially acetic acid) producers, which was well consistent with the results obtained above.

Model-based assessment of estrogen removal by nitrifying activated sludge

Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non-growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for E1, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations.

Kinetic assessment of simultaneous removal of arsenite, chlorate and nitrate under autotrophic and mixotrophic conditions

In this work, a kinetic model was proposed to evaluate the simultaneous removal of arsenite (As (III)), chlorate (ClO3-) and nitrate (NO3-) in a granule-based mixotrophic As (III) oxidizing bioreactor for the first time. The autotrophic kinetics related to growth-linked As (III) oxidation and ClO3- reduction by As (III) oxidizing bacteria (AsOB) were calibrated and validated based on experimental data from batch test and long-term reactor operation under autotrophic conditions. The heterotrophic kinetics related to non-growth linked As (III) oxidation and ClO3- reduction by heterotrophic bacteria (HB) were evaluated based on the batch experimental data under heterotrophic conditions. The existing kinetics related to As (III) oxidation with NO3- as the electron acceptor together with heterotrophic denitrification were incorporated into the model framework to assess the bioreactor performance in treatment of the three co-occurring contaminants. The results revealed that under autotrophic conditions As (III) was completely oxidized by AsOB (over 99%), while ClO3- and NO3- were poorly removed. Under mixotrophic conditions, the simultaneous removal of the three contaminants was achieved with As (III) oxidized mostly by AsOB and ClO3- and NO3- removed mostly by HB. Both hydraulic retention time (HRT) and influent organic matter (COD) concentration significantly affected the removal efficiency. Above 90% of As (III), ClO3- and NO3- were removed in the mixotrophic bioreactor under optimal operational conditions of HRT and influent COD.

Modeling Electron Competition among Nitrogen Oxides Reduction and N2O Accumulation in Hydrogenotrophic Denitrification

Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors

A comprehensive mathematical model was constructed to evaluate the complex substrate and microbial interaction in algal-bacterial photo sequencing batch reactors (PSBR). The kinetics of metabolite, growth and endogenous respiration of ammonia oxidizing bacteria, nitrite oxidizing bacteria and heterotrophic bacteria were coupled to those of microalgae and then embedded into widely-used activated sludge model series. The impact of light intensity was considered for microalgae growth, while the effect of inorganic carbon was considered for each microorganism. The integrated model framework was assessed using experimental data from algal-bacterial consortia performing sidestream nitritation/denitritation. The validity of the model was further evaluated based on dataset from PSBR performing mainstream nitrification. The developed model could satisfactorily capture the dynamics of microbial populations and substrates under different operational conditions (i.e. feeding, carbon dosing and illuminating mode, light intensity, influent ammonium concentration), which might serve as a powerful tool for optimizing the novel algal-bacterial nitrogen removal processes.

Modeling aerobic biotransformation of vinyl chloride by vinyl chloride-assimilating bacteria, methanotrophs and ethenotrophs.

Recent studies have investigated the potential of enhanced groundwater Vinyl Chloride (VC) remediation in the presence of methane and ethene through the interactions of VC-assimilating bacteria, methanotrophs and ethenotrophs. In this study, a mathematical model was developed to describe aerobic biotransformation of VC in the presence of methane and ethene for the first time. It examines the metabolism of VC by VC-assimilating bacteria as well as cometabolism of VC by both methanotrophs and ethenotrophs, using methane and ethene respectively, under aerobic conditions. The developed model was successfully calibrated and validated using experimental data from microcosms with different experimental conditions. The model satisfactorily describes VC, methane and ethene dynamics in all microcosms tested. Modeling results describe that methanotrophic cometabolism of ethene promotes ethenotrophic VC cometabolism, which significantly enhances aerobic VC degradation in the presence of methane and ethene. This model is expected to be a useful tool to support effective and efficient processes for groundwater VC remediation.