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Anaerobic Reactors
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  1. Anaerobic reactors | Condorchem Envitech
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Reaction compartment of expanded bed. The IC reactor was inoculated with methanogenic granule sludge from a full-scale IC anaerobic reactor that treats pulp and papermaking wastewater Guangzhou City, China. Residence time distribution RTD research based on the tracing technique is a common method of studying the mixing pattern of bio-chemical reactors By using an injector, a solution containing 2.

Samples were collected from the effluent pipe every 0. Samples were centrifuged and filtered before analysis The lithium-ion concentration was detected by an inductive coupled plasma emission spectrometer ICP, PerkinElmer-Optima , US at a wavelength of Effluent water COD was determined using the potassium dichromate method The concentration of volatile fatty acids VFA was measured by a gas chromatograph external standard method. To inhibit the adsorption of organic acids by using a chromatographic column, all of the effluent samples were pre-treated by using a high-speed refrigerated centrifuge and a microporous membrane filtrate.

The curves were obtained from tracer studies. Theoretically, when the back-mixing in the reactor is weak, the axial dispersion plug flow PF model can be applied to simulate the hydrodynamic of the reactor. Pe can be estimated as follows:. As a non-ideal flow, the hydrodynamics of the anaerobic reactor can be well described by the multi-CSTRs continuous stirred tank reactor tank-in-series model 25 , The previous research studies have illustrated that the distribution of the substrates and intermediates along the axis of the reactor were far different, and the increasing-size CSTRs model ISC would perform better at simulating the performance of the reactor 30 , The ISC model can be expressed by an equation set as below 19 :.

The biological degradation processes are described by substrate uptake Monod-type kinetics equations, while other extracellular processes e. Using a CSTR model with a single input and output stream and constant liquid volume, the IWA Task Group has provided the differential equation of the mass balance for each state component in the liquid phase, as follows 15 :.

Despite all parameters in the equations theoretically affecting the outcome of the model, the sensitivity degree of the parameters was far different.

In particular, most of the parameters have low sensitivity. A sensitivity analysis was used to identify the dominant parameters, which was conducted by employing the absolute-relative sensitivity function supported by AQUASIM2.

The function is calculated as follows 32 :. Their units do not depend on the unit of the parameter, which makes quantitative comparisons of the effect of different parameters p on the same variable y possible. The model parameters that are represented by constant variables can be estimated by minimizing the sum of the squares of the weighted deviations between the measurements and calculating the results of the model as follows:.

Schematic diagram of the tracer concentration at time t C t -t curve. In each diagram, the black dot plot depicts the C t -t curve under blank operation without sludge, and the red dot depicts the C t -t curve under normal operation with sludge. These results illustrated that: the reactor structure fundamentally determined the RTD of the substrates; the sludge can detain the substrates, which showed apparently at the short HRT; nevertheless, the sludge detaining effect would degrade along with the extension of HRT, which might be attributed to the perturbation effect of generating bubbles in the reactor.

Back-mixing refers to the mixing degree of substrates in the reactor, which exerts an important effect on pollutant removal From Eq. According to Tomlinson et al. The Run5—8 were carried out without sludge, and the N values were 2. Therefore, the dispersion of the reactor was large and the back-mixing was strong.

Anaerobic reactors | Condorchem Envitech

The Run1—4 were executed under normal conditions with sludge , and the N values were 2. The result illustrated that the configuration of the reactor mainly determines the mixing pattern. Within the biomass, the granule sludge and the generation of bubbles produce a coaction to stimulate the mixing pattern to be PF. This effect was obvious under a short HRT.

Theoretically, the pollutant removal rate in the absolute PF pattern is higher than the rate in the absolute CSTR pattern. The calculated tank number N values under the normal experiment were from 2. Generally, when the reactor is dominated under Monod or first-order biological kinetics, a PF pattern will be more effective Consequently, if the anaerobic bioreactor has an absolute PF pattern, the production of VFAs will accumulate at the bottom layer and the pH will descend there; at the same time, the methane production occurs at only the top layer and the pH value will ascend It should be noted that methanogenic bacteria may be inhibited by a low pH, when the pH of the reaction is less than 6.

This adverse result can break down the methane production reaction. In contrast, moderate back-mixing can produce a continuous stirring between the liquid-solid phases, which not only enhances the transfer action on pollutants and granule sludge but also increases the balance of substrates, the pH, and nutrients in the reactor.

Therefore, the moderate back-mixing effect may be beneficial for the highly efficient degradation capacity of IC reactor. It is easy to find that the accuracy of the ISC model is higher than that of the other two models. This finding agreed with the research results of Dai et al. Therefore, exploiting the ISC model would easily improve the simulation results. Schematic diagram of three kinds of tank-in-series TIS models of the simulation result. ADM1 involves 19 biochemical processes and 26 component variables All of the biochemical process rates are described by Monod uptake equations or by first-order kinetic equations Despite the fact that all of the parameters in the equations theoretically affect the output of the model, the sensitivity degree of the parameters may be far different from one to another, and many parameters have little impact.

Lecture 36:Anaerobic Treatment of Wastewater: UASB Reactor

It is necessary to analyse and distinguish the important parameters which have the significant impact on the model calculation. Chen et al.


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Barrera et al. As the most sensitive parameters, k m parameters of propionate, acetate, hydrogen, and Yield of hydrogen were used for calibration in the anaerobic digestion with sulphate reduction of cane-molasses vinasse. The sensitivity analysis was a useful method to identify the dominant parameters, to reduce the model complexity and to determine the main processes 40 , In the research, lab synthetic wastewater was used, and the glucose was the only substrate in the influent. Glucose, as a simple monosaccharide, undergoes easy uptake by sugar degraders X su and will be decomposed directly into VFAs butyrate, propionate, and acetate, etc.

Thus, to accurately predict the COD eff , the kinetic parameters of the uptake process rates of butyrate, propionate and acetate were used in the calculation. The absolute-relative sensitivity analysis of the k m parameter specific Monod maximum uptake rate and the K s parameter Monod half saturation constant relating to these ingredients are shown in Fig. The sensitivity of k m in the process rate equation is higher than that of K s in the same process rate equation. The k m and K s values of the uptake process in the acetate and propionate uptake processes showed higher sensitivity than their counterparts in the butyrate and sugar uptake processes, especially in the k m value of the acetate uptake process.

Therefore, these four parameters were used for parameter adjustments, which would be considered in the next step of the mathematical simulation. The sensitivity curves of both k m and K s parameters for acetate and propionate are shown in Fig. Relative model parameters of the sensitivity analysis accounting for COD eff. The absolute-relative sensitivity analysis of the k m parameter specific Monod maximum uptake rate and the K s parameter Monod half saturation constant relating to sugar, butyrate, propionate, and acetate degrading are depicted.

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Anaerobic reactor system was sensitive to influent fluctuation, such as high organic loading shock, hydraulic shock, and even toxic wastes shock etc. The disturbances might adversely affect the quality of effluent what should be monitored and predicted earlier. Consequently, to validate the mathematical model in wastewater COD eff prediction, both the stable running test and overloading shock test were carried out in our experiments. Other parameters were adopted from the recommended values of the IWA task group After adjusting the maximum uptake rate and the half saturation constant, the simulation COD effluent agreed with the experimental effluent COD.

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The blue dotted-line represents the simulation result with the original parameter, and the black line represents the simulation with the adjusting maximum uptake rate and half saturation constant. Short-time overloading, such as a huge pollutant influent or water flow shock, are common in industrial wastewater treatments 42 , Based on regular loading simulation, we further simulated the over-organic and over-hydraulic shock tests. As shown in Fig. Three kinds of tank-in-series models were used to simulate the hydrodynamics of this reactor, and the gradually increasing-size CSTRs model ISC model was more suitable to fit the hydraulic character than the other two models.


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  • We chose the medium ratio value of the ISC model to simulate the hydraulic dynamic of this reactor. Both stable running and overloading shock tests were executed, and the simulation results agreed with the experimental data. The proposed model in this research might be valuable to monitor reactor effluent effectively and to supply a useful tool to design and operate a full-scale anaerobic reactor.

    Li, S. Hydraulic characteristics and performance modeling of a modified anaerobic baffled reactor MABR. Chemical Engineering Journal , 85—92 Tao, B. Enhancement of microbial density and methane production in advanced anaerobic digestion of secondary sewage sludge by continuous removal of ammonia. Kamali, M. Anaerobic digestion of pulp and paper mill wastes—An overview of the developments and improvement opportunities.

    Chemical Engineering Journal , — Macarie, H. Strategy to identify the causes and to solve a sludge granulation problem in methanogenic reactors: application to a full-scale plant treating cheese wastewater. Wang, Y. Mao, C. Review on research achievements of biogas from anaerobic digestion. Renewable and Sustainable Energy Reviews 45 , — Karadag, D.

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    Journal of Water Process Engineering 10 , — Batstone, D. Mathematical modelling of anaerobic digestion processes: applications and future needs. Dai, R. Dispersion characteristics of a spiral symmetry stream anaerobic bio-reactor. Biochemical Engineering Journal , 27—34 Ji, J. Hydraulic characteristics and their effects on working performance of compartmentalized anaerobic reactor. Qi, W. Hydraulic characteristics simulation of an innovative self-agitation anaerobic baffled reactor SA-ABR. Sarathai, Y. Hydraulic characteristics of an anaerobic baffled reactor as onsite wastewater treatment system.

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    Anaerobic reactors

    Mathematical modeling in anaerobic digestion AD. Journal of Bioremediation and Biodegradation 5 Delrue, F. Modelling a full scale membrane bioreactor using Activated Sludge Model No.