Abstract: 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 El, 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. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: 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.

Abstract: Electroporation is a non-thermal electromagnetic phenomenon widely used in medical diseases treatment. Different mathematical models of electroporation have been proposed in literature to study pore evolution in biological membranes. This paper presents a nonlinear dispersive multiphysic model of electroporation in irregular shaped biological cells in which the spatial and temporal evolution of the pores size is taken into account. The model solves Maxwell and asymptotic Smoluchowski equations and it describes the dielectric dispersion of cell media using a Debye-based relationship. Furthermore, the irregular cell shape has been modeled using the Gielis superformula. Taking into account the cell in mitosis phase, the electroporation process has been studied comparing the numerical results pertaining the model with variable pore radius with those in which the pore radius is supposed constant. The numerical analysis has been performed exposing the biological cell to a rectangular electric pulse having duration of 10 μs. The obtained numerical results highlight considerable differences between the two different models underling the need to include into the numerical algorithm the differential equation modeling the spatial and time evolution of the pores size.

Abstract: In this paper, a new fouling measurement method is presented as a pragmatic approach to determine a mixed liquor's fouling propensity. The MBR-VFM (VITO Fouling Measurement) uses a specific measurement protocol consisting of alternating filtration and physical cleaning steps, which enables the calculation of both the reversible and the irreversible fouling resistances. The MBR-VFM principle, set-up and measurement protocol are described as well as the evaluation of the fouling measurement method. Finally, the MBR-VFM was validated by comparing the fouling propensity measured on-line by the MBR-VFM in a lab-scale MBR with the fouling of the MBR membranes themselves. Our experiments indicated that the MBR-VFM can accurately measure fouling and that it can even be detected earlier than can be seen from the on-line filtration data of the lab-scale system itself. Furthermore, the differences measured in reversible and irreversible fouling seemed to be related to the observed impact of physical and chemical cleaning respectively. Therefore, the application of the MBR-VFM as an on-line sensor in an advanced control system, enabling the deployment of the measured fouling data for the control of membrane cleaning, seems feasible and will be tested in the near future.

Abstract: Urine contains the majority of nutrients in urban wastewaters and is an ideal nutrient recovery target. In this study, stabilization of real undiluted urine through nitrification and subsequent microalgae cultivation were explored as strategy for biological nutrient recovery. A nitrifying inoculum screening revealed a commercial aquaculture inoculum to have the highest halotolerance. This inoculum was compared with municipal activated sludge for the start-up of two nitrification membrane bioreactors. Complete nitrification of undiluted urine was achieved in both systems at a conductivity of 75 mS cm−1 and loading rate above 450 mg N L−1 d−1. The halotolerant inoculum shortened the start-up time with 54%. Nitrite oxidizers showed faster salt adaptation and Nitrobacter spp. became the dominant nitrite oxidizers. Nitrified urine as growth medium for Arthrospira platensis demonstrated superior growth compared to untreated urine and resulted in a high protein content of 62%. This two-stage strategy is therefore a promising approach for biological nutrient recovery.

Abstract: Long-term human Space missions depend on regenerative life support systems (RLSS) to produce food, water and oxygen from waste and metabolic products. Microbial biotechnology is efficient for nitrogen conversion, with nitrate or nitrogen gas as desirable products. A prerequisite to bioreactor operation in Space is the feasibility to reactivate cells exposed to microgravity and radiation. In this study, microorganisms capable of essential nitrogen cycle conversions were sent on a 44-days FOTON-M4 flight to Low Earth Orbit (LEO) and exposed to 10(-3)-10(-4) g (gravitational constant) and 687 +/- 170 mu Gy (Gray) d(-1) (20 +/- 4 degrees C), about the double of the radiation prevailing in the International Space Station (ISS). After return to Earth, axenic cultures, defined and reactor communities of ureolytic bacteria, ammonia oxidizing archaea and bacteria, nitrite oxidizing bacteria, denitrifiers and anammox bacteria could all be reactivated. Space exposure generally yielded similar or even higher nitrogen conversion rates as terrestrial preservation at a similar temperature, while terrestrial storage at 4 degrees C mostly resulted in the highest rates. Refrigerated Space exposure is proposed as a strategy to maximize the reactivation potential. For the first time, the combined potential of ureolysis, nitritation, nitratation, denitrification (nitrate reducing activity) and anammox is demonstrated as key enabler for resource recovery in human Space exploration.

Abstract: Sustainable wastewater treatment has been attracting increasing attentions over the past decades. However, the production of nitrous oxide (N2O), a potent GHG, from the energy-efficient granule-based autotrophic nitrogen removal is largely unknown. This study applied a previously established N2O model, which incorporated two N2O production pathways by ammonia-oxidizing bacteria (AOB) (AOB denitrification and the hydroxylamine (NH2OH) oxidation). The two-pathway model was used to describe N2O production from a granule-based partial nitritation (PN) reactor and provide insights into the N2O distribution inside granules. The model was evaluated by comparing simulation results with N2O monitoring profiles as well as isotopic measurement data from the PN reactor. The model demonstrated its good predictive ability against N2O dynamics and provided useful information about the shift of N2O production pathways inside granules for the first time. The simulation results indicated that the increase of oxygen concentration and granule size would significantly enhance N2O production. The results further revealed a linear relationship between N2O production and ammonia oxidation rate (AOR) (R-2 = 0.99) under the conditions of varying oxygen levels and granule diameters, suggesting that bulk oxygen and granule size may exert an indirect effect on N2O production by causing a change in AOR.

Abstract: We generalize the Gielis Superformula by extending the R. Chacon approach, but avoiding the use of Jacobi elliptic functions. The obtained results are extended to the three-dimensional case. Several new shapes are derived by using the computer algebra system Mathematica(C).

Abstract: Aim of this chapter is analytical representation of one wide class of geometric figures (lines, surfaces and bodies) and their complicated displacements. The accurate estimation of physical characteristics (such as volume, surface area, length, or other specific parameters) relevant to human organs is of fundamental importance in medicine. One central idea of this article is, in this respect, to provide a general methodology for the evaluation, as a function of time, of the volume and center of gravity featured by moving of one class of bodies used of describe different human organs.

Abstract: The filtration process within a membrane bioreactor (MBR) is mostly controlled in a classic way through typical set-points such as aeration flow rate, filtration duration, backwash frequency or relaxation duration. The values of these filtration set-points result from experience and remain often unchanged during the installations operational lifetime. Filtration is dictated considerably by membrane fouling phenomena. The fouling potential of the mixed liquor however can significantly fluctuate, even daily, from changing influent characteristics. Fixed set-point values thus may represent sub-optimal filtration conditions. Consequently, a supervising advanced control system, being able to continuously adapt the set-points values would be beneficial regarding the MBR filtration process optimization. Such optimization could reduce the corresponding MBR energy consumption, e.g. linked to the filtration related membrane aeration. An Advanced Control System (ACS) based on Fuzzy Set Logic (FSL) is introduced here, enabling to supervise an existing classic membrane filtration control system. Such ACS is able to daily (or even more frequent) optimize the set-points of the underlying classic control system, from the input of various sensor and process parameter values. The theoretical background and practical implementation of the FSL based ACS concept is explained.

Abstract: Nitrate contamination of groundwater has been recognized as a significant environmental problem world widely. Sulfur-driven mixotrophic denitrification has been demonstrated as a promising groundwater treatment process, which though plays an important role in nitrous oxide (N2O) emissions, significantly contributing to the overall carbon footprint of the system. However, the current process optimizations only focus on nitrate removal and excess sulfate control, with the N2O emission being ignored. In this work, an integrated mathematical model was proposed to evaluate the N2O emission as well as the excess sulfate production and carbon source utilization in sulfur-driven mixotrophic denitrification process. In this model, autotrophic and heterotrophic denitrifiers use their corresponding electron donors (sulfur and organic matter, respectively) to reduce nitrate to nitrogen gas, with each modeled as three-step denitrification (NO3 to N-2 via NO2 and N2O) driven by sulfur or organic matter to describe all potential N2O accumulation steps. The developed model, employing model parameters previously reported in literature, was successfully validated using N2O and sulfate data from two mixotrophic denitrification systems with different initial conditions. Modeling results revealed substantial N2O accumulation due to the relatively low autotrophic N2O reduction activity as compared to heterotrophic N2O reduction activity, explaining the observation that higher carbon source addition resulted in lower N2O accumulation in sulfur-driven mixotrophic denitrifying system. Based on the validated model, optimizations of the overall system performance were carried out. Application of the model to simulate long-term operations of sulfur-driven mixotrophic denitrification process indicates that longer sludge retention time reduces N2O emission due to better retention of active biomass. High-level total nitrogen removal with significant N2O emission mitigation, appropriate excess sulfate control and maximized COD utilization can be achieved simultaneously through controlling the influent nitrate and COD concentrations. (C) 2017 Elsevier Ltd. All rights reserved.