Numerical model estimation of biomethane production using an anaerobic CSTR: model formulation, parameter estimation and uncertainty/sensitivity analysis

Global climate change is becoming of increasing concern. Transportation makes up a large part of carbon gasses, which affects climate change and air quality. As transportation is a big part of carbon emissions, everybody can contribute to reducing emissions through transportation. One way for people to contribute is to start choosing greener transportation. Nuding is a tool that can be used to get people to choose greener transportation. It's function is to help guide people's behavior. For this project, the nudging goal is to nudge people towards healthier and greener transportation options than already in use. An example of a nudge is to provide reminders of bus departure times for a trip to an event. In order to nudge people gathering information relevant for traveling is necessary. In this thesis, relevant information for green transportation nudges is researched. Other studies on green transportation nudges are applied to discover relevant information topics and sources. Microservices architecture is proposed as the architecture for designing nudges, where the system is divided into smaller interconnected services that work together. Demonstrators of information collection microservices are designed and implemented. The demonstrators handle data for different information topics relevant to green transportation nudges. There are demonstrators for collecting weather data, routing data, public transportation data, rental bikes and scooters data, calendar data, and location data. The thesis also discusses how the data collected can be used to form transportation nudges

Fate of selected drugs in the wastewater treatment plants (WWTPs) for domestic sewage

The wide diffusion of Emerging Organic Micropollutants (EOMs) in the environment is receiving increasing attention due to their potential toxicological effects on living organisms. So far, the Wastewater Treatment Plants (WWTPs) have not been designed with the purpose to remove these contaminants; therefore, they can represent the major source of release into the environment both through the effluent and the wasted sludge. The fate of EOMs in the WWTPs is still not completely known; further investigations are therefore needed to assess if it is possible to exploit the existing treatment units to reduce EOM concentrations or which processes must be implemented to this purpose. Among the wide class of EOMs, the present study focused on the following drugs of abuse: amphetamine (AM), methamphetamine (MET), 11-nor-Δ9-THC-9carboxy (THC-COOH) and benzoylecgonine (BEG). Presence and removal efficiency of these drugs in the activated sludge tank of a WWTP for domestic sewage was investigated through analyses at both full-scale and laboratory scale. Determinations conducted in the full-scale WWTP highlighted that, among the searched drugs, AM was found to be the most abundant in the influent and effluent of the biological oxidation tank, while 11-nor-Δ9-THC-9carboxy was present at the lowest concentration. Some removal took place in the units prior to the oxidation tank, although the main reduction was observed to occur in the biological oxidation reactor. All the drugs showed a wide variability of the measured concentrations during the week and the day. Taking into account results from both full-scale observations and batch tests, removals in the biological reactor were found within the following ranges: 33–84% for AM, 33–97% for MET, 33–57% for BEG and 29–83% for THC-COOH. These removals were due to a combination of adsorption and biodegradation mainly, while volatilization did not play a significant role. Other processes, e.g. hydrolysis, were likely to occur. © 2017 Springer-Verlag Berlin Heidelber

Modelling of submerged membrane bioreactor: Conceptual study about link between activated slugde biokinetics, aeration and fouling process

A mathematical model was developed to simulate filtration process and aeration influence on Submerged Membrane Bioreactor (SMBR) in aerobic conditions. The biological kinetics and the dynamic effect of the sludge attachment and detachment from the membrane, in relation to the filtration and a strong intermittent aeration, were included in the model. The model was established considering soluble microbial products (SMP) formation-degradation. The fouling components responsible of pore clogging, sludge cake growth, and temporal sludge film coverage were considered during calculation of the total membrane fouling resistance. The influence of SMP, trans-membrane pressure, and mixed liquor suspended solids on specific filtration resistance of the sludge cake was also included. With this model, the membrane fouling under different SMBR operational conditions can be simulated. The influence of a larger number of very important process variables on fouling development can be well quantified. The model was developed for evaluating the influence on fouling control of an intermittent aeration of bubbles synchronized or not with the filtration cycles, taking into account the effects of shear intensity on sludge cake removal

CO-PrOx over nano-Au/TiO2: Monolithic catalyst performance and empirical kinetic model fitting

In this work, the performance of ceramic monoliths washcoated with Au/TiO2 is studied on CO preferential oxidation (CO-PrOx) reaction in H2-rich environments under a wide range of operating conditions of practical interest. The parameter estimation of a nonlinear kinetic empirical model representing this system is made via genetic algorithms by fitting the model predictions against our laboratory observations. Parameter uncertainty leading to inaccurate predictions is often present when kinetic models with nonlinear rate equations are considered. Here, after the fitting was concluded, a statistical study was conducted to determine the accuracy of the parameter estimation. Activation energies of ca. 30 kJ/mol and 55 kJ/mol were adjusted for CO and H2 oxidations, respectively. The catalyst showed appropriate activity and selectivity values on the CO oxidation on a H2-rich environment. After ca. 45 h on stream the catalyst showed no deactivation. Results show that the model is suitable for reproducing the behavior of the CO-PrOx reactions and it can be used in the design of reactors for hydrogen purification.Peer ReviewedPostprint (author's final draft

Design of experiments for microbiological models

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Deactivation of TEM-1 beta-Lactamase investigated by isothermal batch and non-isothermal continuous enzyme membrane reactor methods

The thermal deactivation of TEM-1 β-lactamase was examined using two experimental techniques: a series of isothermal batch assays and a single, continuous, non-isothermal assay in an enzyme membrane reactor (EMR). The isothermal batch-mode technique was coupled with the three-state Equilibrium Model of enzyme deactivation, while the results of the EMR experiment were fitted to a four-state molten globule model . The two methods both led to the conclusions that the thermal deactivation of TEM-1 β -lactamase does not follow the Lumry-Eyring model and that the Teq of the enzyme (the point at which active and inactive states are present in equal amounts due to thermodynamic equilibrium) is at least 10 °C from the Tm (melting temperature), contrary to the idea that the true temperature optimum of a biocatalyst is necessarily close to the melting temperature

Efficient Finite Difference Method for Computing Sensitivities of Biochemical Reactions

Sensitivity analysis of biochemical reactions aims at quantifying the dependence of the reaction dynamics on the reaction rates. The computation of the parameter sensitivities, however, poses many computational challenges when taking stochastic noise into account. This paper proposes a new finite difference method for efficiently computing sensitivities of biochemical reactions. We employ propensity bounds of reactions to couple the simulation of the nominal and perturbed processes. The exactness of the simulation is reserved by applying the rejection-based mechanism. For each simulation step, the nominal and perturbed processes under our coupling strategy are synchronized and often jump together, increasing their positive correlation and hence reducing the variance of the estimator. The distinctive feature of our approach in comparison with existing coupling approaches is that it only needs to maintain a single data structure storing propensity bounds of reactions during the simulation of the nominal and perturbed processes. Our approach allows to computing sensitivities of many reaction rates simultaneously. Moreover, the data structure does not require to be updated frequently, hence improving the computational cost. This feature is especially useful when applied to large reaction networks. We benchmark our method on biological reaction models to prove its applicability and efficiency.Comment: 29 pages with 6 figures, 2 table