In the second part of the project, stationary and dynamic simulation models for anaerobic conversion for Fischer-Tropsch reaction water were developed. From the pilot work, alkalinity requirements were identified as the main limitations in the applicability of AD-FTRW.
Introduction
Furthermore, anaerobic digestion of the SCFAs in FTRW is estimated to occur rapidly, resulting in low Hydraulic Retention Times (HTRs) of < 24 hours for a production-scale anaerobic reactor. If the first part of the hypothesis is met, the AnMBR performance will be evaluated against a laboratory-scale Anaerobic Packed Bed Reactor (AnPBR) which is also being evaluated for the treatment of FTRW.
Literature Review
Sasol’s Coal to Synthetic Polymer Processes
In the first part of the process, 46 Mton/j of coal is converted into synthesis gas (or production gas), a combination of carbon monoxide and hydrogen. The cleaner nature of the methane feed (compared to coal) favors the use of highly active catalysts to improve the conversion process.
Introduction to Anaerobic Digestion
- Trophic Group Functionality and Characteristics
- pH and Alkalinity
- Inhibitors and Toxicity
The most prominent species in the reactor will be the acetoclastic methanogens and acetogenic organisms. A detailed discussion of the parameters influencing pH in the anaerobic digestion of FTRW is presented in Chapter 5.
Development of Anaerobic Bio-Reactors
- Dispersed Biomass Reactors
- High Rate Immobilized Biomass Reactors
In the clarigester design, the secondary settling tank (SST) is mounted on top of the anaerobic digester (Figure 2.6B). This large amount of "dead" space in the reactor volume is the primary disadvantage of AnFBR.
Anaerobic Membrane Bioreactors
- Membrane Separation
- Membrane Fouling
- Membrane Cleaning
- Membranes and Anaerobic Technology
- Anaerobic Membrane Bio-reactor Designs
- Critical Flux
- Economic Considerations
- Future Prospects of AnMBRs
In this thesis, critical current will refer to the "weak definition" of the term. The economic viability of membranes is limited by the achievable permeate flow rate, the frequency of cleaning and the lifetime of the membrane modules.
Closure
The membranes provide a positive solid-liquid separation barrier that holds the biomass in the reactor while allowing the wastewater to pass through. In another configuration, the membranes are immersed in a mixed liquid and recycled biogas is used to clean the membrane. AnMBR technology is still in its infancy, but the past 3 years have seen a 10-fold increase in research output in this area, demonstrating that major wastewater research groups around the world are considering AnMBR as an effective treatment method for full-scale use . scale, despite the currently high (but falling) cost of membranes and the more complex reactor designs and control schemes required to operate these systems.
Materials and Methods
AnMBR: Design
- Flat Panel Kubota Membranes
- Reactor Shell and Membrane Housing
- Biogas: Recycling & Trans Membrane Pressure Control
- AnMBR On-line Control System
As the gas bubbles are more hydrophobic than the biomass itself, it continuously 'scrapes' the biomass from the hydrophobic membrane surface. It was therefore decided to develop an on-line control system to increase the robustness of the AnMBR. A detailed discussion of the design and operation of the online control system is presented in Appendix 3.2.
Anaerobic Packed Bed Reactor (AnPBR): Design
As a result, influent distributor tubes and perforated plates and wall baffles were mounted on the inside of the reactor shell. Liquid flows downwards through the reactor and is recycled by the recovery pump (C) and reintroduced into the top. In this way, the liquid volume in the reactor can be maintained in such a way that efficient wetting by immersion of all the packing is ensured.
Experimental Methods
According to Ripley et al. (1986) the alkalinity must be at least 3 times higher than the SCFA concentration to protect the anaerobic system from pH fluctuations. Sludge age (Rs) determines the mass of biomass recovered from the reactor as a fraction of the total sludge mass in the system. Since the majority of COD (>95%) comes out of the anaerobic process in the form of methane, the composition of the biogas is also necessary.
Operation
Also, the analysis of trace metals in the sludge mass was done to evaluate the C:H:O:N:P:S:Fe ratio of the sludge. Therefore, the first VHIs to be recorded in the membrane reactor are the mixed volume of liquor and foam. It was observed experimentally that a head of foam in the mixed liquor would appear when NaOH dosing and membrane cleaning began.
Feedstock
Under stable operating conditions the foam volume is about 10% of the mixed liquid volume (in the current design), but if more NaOH is dosed than normal (due to high SCFAs) the foam level rises (experimental observation). Most of the metals in the macro and micronutrients are added as sulfate salts and so the pH of the mixture must be lowered below 3 to allow these salts to dissolve. Due to the high SCFA concentrations and the low pH, no growth occurs in the feed container and influent lines.
Closure
So the feed is filled into 200 L tanks and stirred continuously to ensure that the nutrients remain in solution. Both reactors are then fed from the same feed tank to ensure exactly the same feed conditions. To make the results obtained from the system as comparable as possible, environmental conditions such as temperature were kept the same in both systems with temperature controllers (37 oC) and both systems were fed with the same feed and nutrient mixture because they were fed from the same. source.
Results & Discussion
Commissioning & Start-up
- Inoccullum & Seeding
- Start-up Problems
A considerable amount of time (100 days) was spent on the mechanical optimization of the AnMBR before its start-up could begin. Air leaks in the AnMBR caused a significant problem due to the inhibitory effect of oxygen on the anaerobic biomass. Heating of the AnMBR to 37 oC is necessary to ensure optimal growth rates of the anaerobic biomass.
AnMBR Start-up
The time between the final nutrient turnover and the system reaching an OLR of 15 kgCOD/m3Vr/d is represented in the square in Figure 4.1 and is considered the actual start-up period. The OLR increase was continued and it was proven that AnMBR can operate at OLRs up to 30 kgCOD/m3Vr/d if adequately controlled. From this evaluation, it was proven that municipal anaerobic digester sludge can adapt to the AnMBR and FTRW environment.
Nutrient Optimization
In contrast to other nutrients, anaerobic biomass does contain a significant amount (~10 %) of nitrogen (N) and sludge age has a significant effect on the AD-FTRW system's N requirements. If the 'Du Preez nutrients' are compared with the nutrient requirements optimized for the ADMBR, it can be noted that the optimized nutrients are significantly lower in all cases. Even at µg/L levels, nickel (Ni) appears to have no effect on reactor performance.
Mixed Liquor: Operational Concentrations and Characteristics
The long sludge age is due to the very low net biomass yield of the acetoclastic methanogens, the most abundant trophic group in the system. The sludge settleability in terms of the diluted sludge volume index (DSVI) of the sludge mass was approximately 3000 mL/g. One of the most important questions about the AnMBR performance that required attention was how the membrane flux and TMP relationship responded to a change in MLSS concentration.
Membrane Performance
- Membrane Fouling
- Critical Flux
- Membrane Life Span & Permanent Fouling
No chemical cleaning was performed on the membranes to restore the TMP to < 50 mmH2O. The biomass was pumped out of the AnMBR and the membranes were cleaned with a 5% hypochlorite solution. The second permanent fouling test was performed on day 530, when biofouling was observed on the membranes (Figure 4.5, 3).
AnMBR Steady State Performance Evaluation
- Effluent Quality
- Alkalinity Requirements
- Shock Loading Responses
COD, the removal efficiency (RE) of the AnMBR is significantly higher (by 9 %) than that of the AnPBR. For this reason, the steady state alkalinity consumption of the AnMBR and AnPBR was evaluated. In the AnPBR (day 372 to day 374), the overload only became apparent after 48 hours and the feed was stopped immediately (Day 374).
Closure
AnPBR can withstand significantly higher shock loads than AnMBR (3 times higher) and also shows a 30% shorter recovery period before full recovery (low effluent SCFA concentration). From an operational perspective, AnPBR was also found to be much easier to operate and control than AnMBR. The AnMBR study showed that a steady-state design loading rate of 25 kgCOD/m3/d can be maintained compared to 8 kgCOD/m3/d for AnPBR.
Steady State Modeling
Steady State Model Development
- Kinetic Part
- Stoichiometry
- Weak Acid Base Aqueous Chemistry
- Statistical Methods
From Cf. 5.8 it can be noted that the proportion of dissociated SCFAs (F), the urea dose (b) and of course the hydroxide dose (d) all generate alkalinity (HCO3-. ) which helps to control the pH of the reactor. The F value is determined by the pH of the influent FTRW and the dissociation constant of the SCFAs (pKax), viz. Due to the nature of the data to which the model will be fitted, i.e.
Model Calibration
The YAR was then varied and predicted carbon leaving the system as (i) biogas, (ii) biomass and (iii) bicarbonate (HCO3-) in the effluent relative to the actual measured carbon leaving the experimental system and was compared via Eq. 5.17 (Figure 5.4 A, where Figure 5.4 B is an enlargement of the square in Figure A). It is clear that the OH dose is the major contributor (Figure 5.7 Alk-OH), but the influent alkalinity (Alk-AD) despite the pH being 3.77 is not insignificant and cannot be ignored to determine the pH of the predict reactor correctly. Comparing Figure 5.9A and B shows that – for a constant OLR (in this case 15 kgCOD/m3Vr/d) – the MLSS of the reactor is directly proportional to the sludge age.
Model Sensitivity Analysis
- Sludge Age Sensitivity
- Representative Organism Yield (Y AR ) Sensitivity
Error in sludge age is therefore not a cause for model predictions deviating from the measured results for PCO2 and gas production. Again, error in sludge age is not a cause for model predictions deviating from the measured results for alkalinity and reactor pH. Error in sludge age is therefore a cause for model predictions deviating from the measured results for sludge production and by direct link also the MLSS concentration.
![Figure 5.10, Model Sensitivity to Variation in Sludge Age for P CO2 [A] and Gas Production [B]](https://thumb-ap.123doks.com/thumbv2/pubpdfnet/10370257.0/135.892.135.753.338.705/figure-model-sensitivity-variation-sludge-age-co2-production.webp)
Model Validation
Alkalinity is slightly under-predicted for both the AnMBR and AnPBR systems, the P90 of the AnMBR = 3%, showing a strong correlation between the predicted and the actual values. In this case, both the AnMBR and AnPBR show a strong correlation with the experimentally measured pH values (P90AnMBR . = 1.5% and P90AnPBR = 0.16%). This correlates closely with an MLSS expected for the AnMBR operating at a similar OLR and sludge age.
Closure
Experimental sludge age and MLSS concentrations were found to play a crucial role in the model performance. From this, the AnMBR was found to operate at a theoretical MLSS of ~25 gTSS/L and a sludge age of ~32 days - an order of magnitude shorter than the AnMBR for the same OLR (~15 kgCOD/m3Vr/d). Since nutrients tend to accumulate in the biomass, the short sludge age may explain the 50% higher nutrient requirements for the AnPBR.
Dynamic Modeling
Model Development
- Stoichiometry
- Process Rates
- Microbial Inhibition
- Assembling the dynamic AD-FTRW model
Two different forms of the Monod expression will be applied to the AD-FTRW dynamic model. The non-degradable fraction is part of the endogenous mass (Ze) which contributes to the sludge mass (MLSS) in the system. From Figure 6.5 it can be observed that three pH inhibition functions describe all FOGs in the dynamic model.
Model Verification and Calibration
- Steady State Calibration
- Batch Test Calibration
So the steady state parameter optimization was only done on the stoichiometric yield (Ymetabolic) values for each of the FOGs. This is because acetic acid is produced in the oxidation of all the higher SCFAs. From Table 6.4, the growth rates of all the functional groups considered are quite similar, as expected.
Model Validation
For the CO2 partial pressure, the dynamic model (PCO2-dyn) also correlates well with the experimentally observed values (P90 = 7%), provided the CO2 partial pressure data (PCO2-exp) is corrected (PCO2-exp(adj)) after determining the COD balance as discussed in Chapter 5 (Figure 6.15B). In the dynamic model, much less variance in the effluent COD and SCFA concentrations is observed than in the experimental data (Figure 6.16). The effluent substrate is also plotted as a breakdown of the total effluent COD in Figure 6.19.
![Figure 6.14 [A] and [B]: pH and Alkalinity; Experimental vs. Dynamic Model](https://thumb-ap.123doks.com/thumbv2/pubpdfnet/10370257.0/181.892.130.764.205.484/figure-14-b-ph-alkalinity-experimental-dynamic-model.webp)
Modeling Reactor Failure
As expected, acidogens (Zad) contribute only a small fraction (<4%) of total VSS because the rate of endogenous respiration is so low. Of the total biogas production, 3.8% is the result of the metabolism of biodegradable organic matter (Sbp) in biomass, which is important, since only 1% of the inflow COD becomes discarded biomass, the observed efficiency (Yobs = net production of sludge) amounts to only about a quarter of the production of metabolic mud. Since FTRW is nitrogen deficient and urea is dosed only as a nutrient, its concentration and consequent effect on pH and inhibition will be negligible compared to other compounds evaluated.
Reactor Failure Due to OH - Dosing
- System Failure Due to Temperature Fluctuation
- System Failure Due to Overloading
- System Failure from Too Low Sludge Age
In the next simulation, the aim was to lower the reactor pH to 6.7 (Figure 6.21 – OHin). Even a gradual 5 oC temperature reduction (over 4 days) still leads to catastrophic failure of the biomass (Figure 6.24). To observe how effluent quality and MLSS change with sludge age at a constant OLR, Figure 6.28 was constructed.
Closure
During the experimental part of the project it was discovered that the AnMBR is prone to inhibition which can lead to system failure. As this was not specifically investigated in the experimental part of the project, a literature survey was conducted to find the required inhibition functions for mesophilic anaerobic digestion. It can also be noted that, if the H2(aq) recovers, the system also recovers from the inhibition of a shock charge.
Conclusions & Recommendations
Conclusions
- Literature Review
- Feasibility Study
- Performance Evaluation
- Steady State AD-FTRW Modeling
- Dynamic AD-FTRW Modeling
The specific NaOH utilization of the AnMBR is affected by three parameters, (i) the feed flow rate through the reactor, (ii) the reactor pH, and (iii) the SCFA concentration of the effluent. For the first 650 days of the study, the membranes were operated at 1 to 10% of their capacity. In the last 50 days of the experimental phase, an effluent recycle was included in the AnMBR design to simulate the effects of an increased flux on the membranes.
Recommendations
- Membrane Performance: Evaluation & Enhancement
- Automated Control
- AD-FTRW Modeling
- Scaling up from Lab to Pilot Plant
