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Analysis of nutrient requirements for the anaerobic digestion of Fischer-Tropsch reaction water.

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84 Figure 21: Dissolved phase ion concentration for Mn (in mg/l x10-4) and Zn (in mg/l x10-8) and their changes with each successive cycle modeled for Reactor II. 164 Figure 36: Dissolved phase ion concentration for Co2+ and HS-1 (μg/l), and their changes with each successive cycle modeled for Reactor II.

Introduction

Background and motivation

This includes interactions within the aqueous phase, with the microorganisms and other solid phases in the digester and even with the construction materials of the digester itself. Sequential extraction procedures are often hampered by problems with the determination of trace metal concentrations, due to the small concentrations of the trace metals also found in the sequential extraction process, which leads to further dilution of the metals which are sometimes below detection limits.

Background into the Field

Historically, speciation and thus bioavailability have been determined analytically (Aquino and Stuckey, 2007, van Hullebusch et al., 2005, Fermoso, 2008). There are only a few cases of dynamic metal speciation modeling that incorporate metal precipitation (Musvoto et al., 2000).

Aims and objectives

Literature Review

Source and Properties of Reaction water

FTRW currently accounts for 23% of the activated sludge plant stream, but contributes 77% of the total organic load, thereby contributing significantly to the high oxygen, electricity, and treatment costs associated with the plant. As a solution to these problems, anaerobic digestion of FTRW has been proposed as an alternative to the aerobic activated sludge system.

Anaerobic Digestion

  • Favourable Conditions for Anaerobic Processing
  • Parameters used to determine efficiency of anaerobic digestion

The second means of inhibition is through sulfide toxicity of anaerobic bacteria (Colleran et al., 1995). The parameter should reflect the actual metabolic status of the microorganisms in the process (Bjornsson et al., 1997).

Table 1: Reported toxic concentrations of metals and their effects on various systems
Table 1: Reported toxic concentrations of metals and their effects on various systems

Importance of nutrients in anaerobic digestion

  • Treatment of Industrial Streams
  • Growth and functioning of Microorganisms
  • Settleability of the sludge

This results in an increase in the hydraulic residence time of the influent, as more time is required for the breakdown of the complex material (Burgess et al., 1999). This is due to the ability of the microorganisms to synthesize some vitamins (Lemmer et al., 1994).

Table 2: Reported stimulatory/optimum concentrations of metals added for various systems
Table 2: Reported stimulatory/optimum concentrations of metals added for various systems

Bioavailability of Metals

If the binding capacity is high, this could reduce the bioavailability of the metal (Fermoso et al., 2010). Other variables affecting metal bioavailability are pH (Burgess et al., 1999) and age of granular sludge (Fermoso et al. 2009).

Figure 3: Fate of micro-metals when added to a reactor
Figure 3: Fate of micro-metals when added to a reactor

Precipitation Chemistry

The presence of sulfide, carbonate and phosphate anions in the bioreactor greatly affects the bioavailability of metals due to the formation of trace metal precipitates (Speece, 1996). The solubility product, Ksp, is the product of the activity of metal and carbonate ions in the aqueous phase.

Methods to determine Bioavailability in a system

  • Analytical Approach
  • Chemical Speciation Modelling

The use of ammonium salt of the modified Tessier scheme rather than potassium nitrate in the Stover scheme is therefore preferable (Filgeuras et al., 2002). Other problems associated with sequential extractions are the inability of reagents to selectively extract metals in a given phase and the influence of operating conditions (pH, temperature, particle size, etc.) (Filgeuras et al., 2002).

Table 7: Outline of Stover and Modified Tessier extraction schemes
Table 7: Outline of Stover and Modified Tessier extraction schemes

Uptake of metals by the microorganisms

36 Transport of metal ions largely depends on the properties of the transport system (Braun et al., 1998, cited in Chen et al., 2008). Another factor is the changing number of microbial carriers in response to changes in the environment (Worms et al., 2006).

Micronutrient dosing

  • Dosing Strategy
  • Recipes Used

Another highlight is that the wastewater treated by Sasol has a very high COD (18 g/l) compared to the substrates of other systems. In the case of the macronutrients N, P, K and S, the recipe used by Sasol in most cases uses higher concentrations compared to the dose concentrations of the other listed systems.

Table 8: Nutrient recipe used by Sasol for their anaerobic digestion of FTRW
Table 8: Nutrient recipe used by Sasol for their anaerobic digestion of FTRW

Anaerobic Sequencing batch reactors

  • Sequencing Batch Reactor operation
  • Advantages and Disadvantages

The length of the reaction step depends on the properties of the substrate and requirements for waste water quality. There is an improved retention of the biological solids, and the process control is more advanced.

Research Methodology

Experiment A

  • Experimental setup
  • Reactor Operation
  • Influent Composition
  • Sampling and Analytical Techniques

The preparation of the standard solutions used for calibration, as well as sample preparation, was performed in-house. After ICP-AES analysis of the samples, the concentrations found were used to determine the mass of metals in the sludge based on the sludge volume.

Figure 5: Experimental setup of one reactor for Experiment A.
Figure 5: Experimental setup of one reactor for Experiment A.

Experiment B

  • Experimental Setup
  • Seed sludge source
  • Initial operation
  • Stable Operation
  • Washout Experiment
  • Reactor Operation
  • Sampling and Analytical Techniques

To provide an indication of the degree of leaching from the solid phase with each cycle. Before sampling, the sludge in the reactors was mixed using the pumps and samples were taken from the bottom of the reactor. This gave an indication of the total amount of metals in the reactor before and after a certain cycle.

Figure 7: Experiment B reactor setup
Figure 7: Experiment B reactor setup

Mass Balance-Chemical Speciation Modelling

  • Rationale
  • Model Development
  • Assumptions

Tables containing the initial conditions for the models of both experiments A and B are contained in Appendix D. For each run, a VM process was first performed for speciation modeling in which no solids were allowed to precipitate. For the setup of experiment B, the partial pressures of CH4 and CO2 used corresponded to the average values ​​determined experimentally.

Table 16: Precipitates likely to form under Experimental Conditions.
Table 16: Precipitates likely to form under Experimental Conditions.

Results

Experiment A Results

  • Metals Mass Balance
  • Sequential Extraction of Sludge
  • Comparison between Acid Digestion and Sequential Extraction
  • Mass Balance-Speciation Modelling Results- Experiment A

Looking at the figure above, the contribution of the metals in the feed and decanting is small compared to the amounts present in the sludge. The main difference between the results for the two reactors is the higher total metals in the sequential extraction for Reactor II, Cycle (i) initial sludge(1) for Al, Zn and Fe. The following graph shows the changes in the amount of ions in the precipitation with each modeled cycle.

Figure 9: Metals mass balance (range 100-2000 mg) for Cycle (i) Reactor I and II.
Figure 9: Metals mass balance (range 100-2000 mg) for Cycle (i) Reactor I and II.

Experiment B Results

  • Mass Balance-Speciation Modelling Results- Experiment B
  • Supernatant Metal Analysis
  • Sludge Metal Analysis
  • Bioprocess Results Calculation and Summary
  • Biogas production, methane activity and methane recovery
  • pH Control
  • Biogas production comparison to alkalinity dosage

From the beginning of the leaching experiment, both Mg and Ca experience a decrease in soluble concentrations. The following graph shows the mud metal concentrations as a percentage of maximum concentration (% C/Cmax) for Al, Ca, Co, Cr, Cu, Fe, Mg, Mn and Zn. The maximum methane production rate was determined from the maximum slope of the cumulative methane production curve.

Figure 18: Model prediction of the concentrations of different precipitates formed and their changes with each  cycle modelled
Figure 18: Model prediction of the concentrations of different precipitates formed and their changes with each cycle modelled

Discussion

Experiment A Discussion

  • Metals Mass Balance
  • Sequential Extraction of Sludge
  • Comparison between Acid Digestion and Sequential Extraction
  • Mass Balance-Speciation Modelling Discussion- Experiment A

103 this metal phase compared to the seven other phases, the organically bound phase contributes between 30 and 68% of the total metal ions in the sludge. The fraction of metal ions in the precipitate phases (carbonate and sulfide combined) varies between 15 and 50% for all the metals in Figure 11. Therefore, the soluble concentration of a metal in the reactor at equilibrium will dictate the amount of metal ions that will be adsorbed ( according to some adsorption equilibrium isotherm), the amount of metal ions that will be organically bound and the amount that will be precipitated (according to the Ksp for that precipitate, assuming that the required concentration of the counterion is present) .

Experiment B Discussion

  • Mass Balance-Speciation Modelling Discussion- Experiment B
  • Supernatant Metal Analysis
  • Sludge Metal Analysis
  • Biogas production, methane activity and methane recovery
  • pH Control
  • Biogas production comparison to alkalinity dosage
  • Biogas production comparison to soluble metal concentration
  • Validity of Model Assumptions
  • Dosing Strategy

In Figure 19, prior to the metal leaching experiment, almost all of the metals present in the system are predicted to occur 100% in precipitates. Due to the complexity of the chemical speciation system, the approach used in developing the model was a stepwise approach. For Mg, the model and the experimental analysis show that the majority of the ions are in the soluble phase (Figures 19 and 20).

Figure 33: Comparison of biogas production data with the experimental soluble metal concentration for Mg, Ca  and Fe and the model predicted cycle at which metal soluble concentration starts to decrease (in green boxes)
Figure 33: Comparison of biogas production data with the experimental soluble metal concentration for Mg, Ca and Fe and the model predicted cycle at which metal soluble concentration starts to decrease (in green boxes)

Conclusions and Recommendations

Because soluble concentrations were higher than those predicted by the model, the deviations were most likely due to kinetic effects in the system that prevented complete precipitation. Furthermore, the incorporation of other phases, such as the organically bound phase, may result in a slower reduction in soluble concentration than predicted by the model. A decrease in one or a combination of these metals most likely led to the second decrease in biogas production.

Effect of trace metals on the anaerobic degradation of volatile fatty acids in molasses silt. Dynamic modeling of anaerobic digestion of Fischer-Tropsch reaction water: different approaches to physicochemical modeling. Dynamic modeling of anaerobic digestion of Fischer-Tropsch reaction water: Different approaches to physiochemical modeling.

Appendix A-List of Micro-nutrient recipes from Literature

Appendix B: Analytical Methods

ICP-AES Analysis

  • Sample Preparation
  • Standard Solutions preparation
  • Quality Control

The distilled water used in preparing the standards was used as a blank reagent for analysis. Element concentrations were determined at one or two wavelengths, with no more than one element determined per wavelength.

Table A2: Standard Solutions used for ICP-AES calibration
Table A2: Standard Solutions used for ICP-AES calibration

Acid Digestion of Sludge

  • Apparatus and Reagents
  • Method
  • Obtaining the sludge samples for acid digestion
  • Calculating the total amount of metals in the reactor

Mass of sample (g) Volume of sample (ml). calculated using the inside diameter of the reactor and height of the sludge). Average ICP concentration of blank samples (mg/l) 0.32. the 0.1 above is the final volume of the sample after acid digestion is complete). Average ICP concentration of blank samples (mg/l) 0.12. the 0.1 above is the final volume of the sample after acid digestion is complete).

Sequential Extraction

  • Apparatus and Reagents
  • Method

Take a sample of sludge of known volume and measure the mass of the sample. If necessary, use some of the reagent for the next step to recover all solids. The concentration determined from the ICP-AES analysis should be converted to mass/mass of sample units (mg/kg sample) using the mass of the sample and the final volume of the diluted sample.

Table 20: Reagent Scheme for the sequential extraction procedure
Table 20: Reagent Scheme for the sequential extraction procedure

Appendix C: Initial Conditions for Mass Balance-Speciation Modelling

Appendix D: Illustration of the Mass balance in the Mass balance-Speciation model

Mass balance for Experiment A

Mass balance for Experiment B

Residual volume (volume after decanting) = working volume – volume of decanted supernatant – volume of sludge lost during decanting.

Appendix E: Mass balance-Speciation Modelling for Experiment A, Reactor II

Soluble Concentration Changes

The following figure shows the predicted solute ion concentrations for species in the μg/l range and their changes with each successive run modeled. 165 The graph below shows the concentrations of dissolved ions for the ionic species Co2+ and HS-1, in the μg/l range, as well as their changes with the modeling of each successive cycle. For cobalt, the feed concentration was 37 µg/l and was not detected experimentally, probably because the concentration in the soluble phase was below the detection limit.

Figure 35: Concentration of ions in the dissolved phase for Mn, Cu and Zn ions (µg/l), and their changes with each  successive cycle modelled for Reactor II, including comparisons to experimental values for Cu and Zn
Figure 35: Concentration of ions in the dissolved phase for Mn, Cu and Zn ions (µg/l), and their changes with each successive cycle modelled for Reactor II, including comparisons to experimental values for Cu and Zn

Precipitate Formation

This suggests that, like hydrogen sulfide, a significant portion of this ion is predicted to occur in phases other than the soluble phase. An important result from the graph above is that the model predicts that certain metals are completely present in precipitation from the start of the experiment. For Mg2+, K+ and Ca2+, the model predicts that these metals only occur in the soluble phase.

Figure 37: Percentage of ions that are within precipitates as predicted for each successive cycle modelled
Figure 37: Percentage of ions that are within precipitates as predicted for each successive cycle modelled

Appendix F: Experiment B results for Reactor I

  • Results Summary
  • Biogas Production, methane activity and methane recovery
  • pH Control
  • Biogas production comparison to alkalinity dosage
  • Supernatant Metal Analysis

In the following graph, the alkalinity dosage and the total biogas production are compared together with the maximum estimated CO2 composition. In the first region, the alkalinity dosage remains the same, but the total biogas production decreases. For the sludge samples, when comparing the amount of metal in the sludge with the amount that was dosed in the feed, the percentage of retained metal is obtained.

Figure 38: The Total biogas production and % methane recovery on the left axis and maximum methane activity  for pre-metal washout cycles -3 to -1 and post-metal washout cycles 0 to 15 on the right axis for Reactor I
Figure 38: The Total biogas production and % methane recovery on the left axis and maximum methane activity for pre-metal washout cycles -3 to -1 and post-metal washout cycles 0 to 15 on the right axis for Reactor I

Gambar

Figure 1: Source of FTRW in the Sasol Oil-from-coal process
Table 1: Reported toxic concentrations of metals and their effects on various systems
Table 2: Reported stimulatory/optimum concentrations of metals added for various systems
Figure 2: The series metabolism for the anaerobic digestion of synthetic compounds
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