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278855

HyTIME

Low temperature hydrogen production from second generation biomass

Deliverable 5.1 – Mass and energy balances of process steps

Due date of deliverable: Month 15 (31-03-13) Actual submission date: Month 15 (29-04-13)

Start date of project: 01/01/2012 Duration: 36 months

Lead contractors for this deliverable: Vienna University of Technology (TUW) Version 29.04.2013

Project co-funded by the Fuel cell and hydrogen joint undertaking Dissemination Level

PU Public X PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services)

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Completed by: Adela Drljo (TUW) Date: 25.4.2013 Evaluated by: Walter Wukovits (TUW) Date: 29.4.2013

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Content 1. INTRODUCTION ........................................................................................................................................ 4

2. SOFTWARE UPGRADING, MODEL UPDATE AND PROPERTY VALIDATION .......................... 4

3. FEEDSTOCK PRETREATMENT ............................................................................................................. 6 3.1. PRETREATMENT OF GRASS..................................................................................................................... 6 3.2. PRETREATMENT OF WHEAT STRAW ....................................................................................................... 8

4. THERMOPHILIC FERMENTATION .................................................................................................... 10 4.1. BASIC FERMENTER BALANCES ............................................................................................................. 10 4.2. INCREASE OF ACETATE TOLERANCE .................................................................................................... 12

5. GAS-UPGRADING .................................................................................................................................... 13 5.1. REDUCTION OF H2 PARTIAL PRESSURE / H2 CONCENTRATION IN THE LIQUID ........................................ 13 5.2. H2-REMOVAL FROM LIQUID VIA MEMBRANES – BASIC SIMULATION STUDY .......................................... 15

6. ANAEROBIC DIGESTION ...................................................................................................................... 17 6.1. MODEL OF BIOGAS FORMATION ........................................................................................................... 17 6.2. MODEL FOR BIOGAS UTILIZATION ........................................................................................................ 20

7. SUMMARY AND OUTLOOK .................................................................................................................. 21

REFERENCES ..................................................................................................................................................... 22 APPENDIX A – SELECTED STREAM RESULTS FOR PROCESS STEPS ............................................... 23

APPENDIX B – CALCULATOR CODE FOR SIMULATION MODEL ...................................................... 26

APPENDIX C – REWORKED COMPONENT LIST ...................................................................................... 27

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1. Introduction One of the main goals of WP5 is to calculate mass- and energy-balances of the different process steps and integrate these steps (components, heat) to a feasible overall process route by minimizing chemical, heat and utility demand. Deliverable 5.1 summarizes first activities in Task 5.1 and presents first mass and energy balances for selected process steps in HyTime process. First activities in Task 5.1 comprised model care (existing models and databanks) and model development (anaerobic digestion). Model architecture, component list as well as available models from preceding project Hyvolution have been critically reviewed and improved for the use in calculation of mass- and energy-balance in HyTime project. Existing models have been divided into simplified single process steps and revised in terms of eliminating unnecessary steps (photo-fermentation) and to combine with new models in form of a hierarchical structure. New models have been developed (anaerobic digestion, biogas utilization), other have been reworked to fit the changed feedstock situation and pretreatment conditions. Beforehand the calculation of balances for process steps, basic equilibrium calculations were performed to understand gas solubility and thus the concentration of H2 and CO2 in the liquid phase as well as obtainable raw gas composition under different process conditions. This is especially of importance for WP4 – Gas upgrading as well as WP3 – Thermophilic hydrogen fermentation to find options to avoid inert gas stripping of the fermenter. Finally, after an inventory of available data including feedstock composition, known or estimated stream composition and process parameters - based on actual research work in WP2-WP4 as well as on preceding work in project Hyvolution first mass- and energy-balances of process steps are calculated and presented in this deliverable. Process steps are scaled to obtain 10 kg H2/day.

2. Software upgrading, model update and property validation Model care – as mentioned above – included a critical review of implemented components and their properties. This was tightly connected with a migration from Aspen Plus software version 7.1 (Hyvolution models/balances) to version 7.3.2 (HyTime models/balances). In the course of software upgrade, the used property databanks are changed from the old AspenTech databank language systems (text files with special compilation procedure) to the new SQL-server based databank system, enabling an easy update and extension of user defined components and property parameters via direct access of the data set combined with an easy and quick installation procedure. Due to the complex update and installation procedure in Hyvolution project some of the added components were not included in the user database, but defined directly in the flowsheets, providing – at this stage of development – a higher flexibility in component implementation and model exchange. 2.1. Acetic acid dissociation in Aspen Plus To obtain accurate and trust worth results in process simulation, it is crucial to critically check involved components properties. According to the AspenTech Knowledge Base (Solution ID: 130014), there is some uncertainty in the Aspen Plus calculations of acetic acid dissociation constant K, compared to the literature. It is recommended to force Aspen Plus to calculate K via Gibbs energy of formation and not using the build in equations describing K as a function of temperature. Following this information, calculation procedures in Aspen Plus have been checked and validated with the literature data (Figure 1).

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Figure 1: Comparison of data for acetic acid dissociation from literature and Aspen Plus calculations

However Aspen Plus calculation of K, via Gibbs formation energy, gives very poor results compared to literature as it is obvious from Fig. 1. Therefore, following Eq. 1 it was tried to describe dissociation constant K as a function of temperature to obtain results that are in better accordance with literature. ln K = A + B/T + C*lnT + D*T (Eq. 1) Coefficients A, B, C and D have been calculated via multiple linear regression (MLR) in external statistical software Unscrambler v9.0. Regression results are given in Table 1. Implementation of new coefficients give good accordance with dissociation data from literature as shown in Fig. 1. Table 1: Regressed coefficient for calculation of K via Eq. 1

Coefficient Eq. 1 Regression (MLR) A 52,55497 B -3897 C -7,918 D -0,01784

2.2. Component list Besides the check of selected properties, the component list used in Hyvolution was critically evaluated in terms of duplicates, components not reported experimentally, new components to be included in modeling (inhibitors, anaerobic digestions) and the availability of new components in the Aspen Plus databanks. All model components are listed in Appendix C (Table C.1), with component ID, real formula, alias component name in Aspen Plus and reference, where the consideration of the component in modeling is recommended. Components are listed under the headings:

• Basic components (water, gaseous components, acetic acid)

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*Source: CRC Handbook ofChemistry and Physics, R.C. Weast,Ph.D., M.J: Astle, Ph.D, 59th edition,1978-1979*Source: Electrolyte data collection,A. Apelblat, R. Neueder, J. Barthel,Chemistry data series, Vol. XII, Part4a*Source:Lange's handbook ofchemistry, J.A. Dean, 15th edition

Aspen via dG

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• Sugar components (monomers, oligomers, olymers) • By-products and inhibitors • Biomass components (eg. following from Weender Analysis) • Cell mass and enzyme • Other components (mainly inorganic chemicals)

Final goal is to keep models closer to the experimental results as well as to have better overview on the balancing results by avoiding extensive rows of zero flow rates due to model components not determined experimentally. The list will be introduced and discussed with partners in terms of:

• How is feedstock characterized (Weender, detailed sugar analysis ...) • Which components are determined experimentally • Important inhibitors to be monitored • Potential access of components difficult to determine/follow experimentally • Additional needs in Anaerobe Digestion (AD) step

3. Feedstock pretreatment According to the basic experimental data available from the project partners in WP2 (DLO-FBR and Envipark), some preliminary models have been adapted/developed for the different pretreatment procedures. While DLO-FBR at the moment is focusing on the pretreatment of fresh grass for use in biohydrogen fermentation, partner Envipark develops pretreatment procedures for straw and domestic residuals. Developed models are based on data and parameters provided by partners (periodic reports, presentations, personal communication) as well as existing models and experience from preceding project Hyvolution. Feedstock composition has been provided partially from the partners. For undefined or unknown feedstock (components), some additional databanks have been employed (TU Wien internal database BioBib as well as Phyllis Database for biomass and waste).

3.1. Pretreatment of Grass Based on the data from project partner DLO-FBR, a basic model for pretreatment of grass for the use in thermophilic hydrogen fermentation was developed, through including the following process steps: • Mechanical treatment and solid/liquid separation via single screw pressing

(2 pressing steps) or via twin screw co-rotating extrusion • Lime (alkali) treatment • Washing of solids • Enzymatic hydrolysis Purpose of mechanical treatment of the grass is to press out liquids, which are separated from the solids. Figures 3a and 3b illustrate this process step in form of a scheme including balance data presented in WP2 progress report (month 1-6/2012). After the mechanical treatment step, lime pretreatment follows under the following conditions (DLO-FBR): • Consistency of biomass: 10% w/w dry matter • T=85-100°C • Concentration of Ca(OH)2 = 7,5% based on the biomass dry matter (7,5 g of solid lime for 100 g dry matter) • Pretreatment time 4 hours, cooling and washing after 16 hours

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After the lime treatment, the stream is washed 3 times (industrial scale: counter-current washing step). Depending on the demand of enzymatic hydrolysis / fermentation, acid is added to neutralize added alkaline and adjust an appropriate pH.

Figure 3a: Balance of mechanical treatment via single screw pressing

Figure 3b: Balance of mechanical treatment via extruder A preliminary Aspen Plus flowsheet for the two stage pressing option including lime pretreatment and washing is presented in Figure 4. The pH adjustment step is not implemented yet due to the missing data. Based on the available experimental data simulation and balancing is not possible. Necessary update of input data and process parameters must include grass composition (average/model composition, moisture content), conversion reactions and factors for lime pretreatment and enzymatic hydrolysis as well as optimized washing conditions and pH regulation.

Figure 4: Preliminary Aspen Plus model for lime pretreatment of grass (2 stage pressing)

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3.2. Pretreatment of Wheat straw Treatment of wheat straw to release fermentable sugar is developed by partner Envipark. A process scheme including a basic mass balance used for model development is illustrated in Figure 5. A mixture of sulphuric acid and water was added to the dried straw and the whole mixture is treated at high temperature for 2,5 hours. After the treatment with acid, some sugars are released in the liquid and separated from the undissolved solid phase. The solid stream is washed and mixed with enzymes that released undissolved sugars and make them available for thermophilic fermentation. pH is regulated to the value of approx. 4,5.

Figure 5: Scheme of acid pretreatment of wheat straw (Envipark) According to the pretreatment scheme at Fig. 5, an Aspen Plus model of the pretreatment procedure has been developed (Figure 6). Dried straw is mixed with acidified water, that contains H2SO4 (0,5-1N). At laboratory scale, 1 kg of dry straw is mixed with 10 L of the acid solution. In the simulation, the whole system is scaled up to produce 10 kg/day of hydrogen. Preliminary straw characterisation (see Table 2 for straw composition) includes only cellulose, hemicellulose and lignin. Since no detailed characterisation data are available, undefined components are assumed as a Rest. The liquid stream (stream D in Fig. 5) is not further used for hydrogen production during lab-scale pretreatment, but contains some sugars that are lost. During simulation stream D is considered for use in biohydrogen production or anaerobic digestion. Simulation results for both options will be presented later in this report, with detailed information on stream D utilization and advantages/disadvantages that it causes in the system.

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Table 2: Characterisation of dried wheat straw (Envipark)

Wheat straw components (g/100g dry matter) Cellulose 38,26 Hemicellulose 27,90 Lignin 6,64 Rest 27,20

Figure 6: Aspen Plus model of the straw pretreatment Mass and energy balance given in this report should be considered as PRELIMINARY result, considering only main components in the component balance and giving an estimate for necessary material and heat input for each process step. More detailed results will be presented after availability of more precise pretreatment data based on ongoing experimental research. More detailed data are expected for straw composition (e.g. ash, proteins…), optimized temperatures and treatment time and process data on intermediate process steps (solid-liquid separation, washing step). Table 3 represents the preliminary mass balance for the pretreatment step. Pretreatment as well as whole process is scaled up and balance is calculated for the hydrogen production of 10 kg/day. Table 3 summarizes feedstock demand, necessary water input as well as chemical and heat demand. Chemical demand is related mostly to the amount of sulfuric acid added in the pretreatment procedure. Amount of enzyme solution in enzymatic hydrolysis is not considered yet. Steam result for out-going streams are given in Appendix A – Table A.1. Table 3: Feedstock and utility demand for acid pretreatment of wheat straw

PTR Feedstock demand (dry), kg/h 33 Water demand, kg/h 1311,92 Heat demand, kW 38,27 Chemical demand, kg/h 8,08

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4. Thermophilic Fermentation The simulation model for thermophilic fermentation (THF) was mainly originating the Hyvolution process. The model slightly simplified to make basic calculations fast and reliable. Modifications mainly concern heat integration in the sense that detailed heat exchanger models are replaced by simple heater models to avoid undesired temperature cross-over during parameter change in basic balances. Full heat integration will be considered at a later process stage. The flowsheet of THF is represented at Figure 7.

Figure 7: Thermophilic fermentation (Hyvolution) Reaction considered in the thermophilic reactor are as follows: (1) 2.17145 O2 + Glucose + 0.62134 NH3 --> 3.65494 Cells + 2.34506 CO2 + 3.71566 H2O (2) Glucose + 2 H2O --> 4 H2 + 2 CO2 + 2 Acetic acid (3) 0.6 Xylose + H2O --> 2 H2 + CO2 + Acetic acid (4) 1.8095 O2 + Xylose + 0.51778 NH3 --> 3.04578 Cells+ 1.95422 CO2 + 3.09638 H2O Due to missing continuous fermentation results based on new feedstock options, it is assumed that 80% of sugars have been converted to hydrogen (reactions 2 and 3) and 15% sugars are converted to biomass (reactions 2 and 4), giving a total substrate consumption of 95%. Data are taken from Hyvolution Deliverable 5.43 (dated 24.1.2011) and are comparable with results obtained in HyTime in small scale batch fermentations.

4.1. Basic fermenter balances Two scenarios have been considered for calculating basic balances for thermohilic fermentation step:

• V1: pretreatment stream D is not used for biohydrogen production, but considered in anaerobic digestion (Figure 8) – basic configuration

• V2: pretreatment stream D is considered in biohydrogen production (Figure 9) Calculations of balances are scaled to obtain 10 kg H2/day. Substrate concentration at the reactor inlet is 10 g/l monomeric sugar.

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Figure 8: Process setup for V1 including pretreatment (PTR) and thermophilic fermentation THF)

Figure 9: Process setup for V2 including pretreatment (PTR) and thermophilic fermentation (THF) Table 4 summarizes utility demand and obtained osmolality in the thermophilic fermentation step for scenario 1 and 2. Results show a slightly reduced water demand, but increased heat demand for scenario V2. It has to be considered that the calculated heat demand includes already basic considerations towards heat integration. The feed stream of thermophilic fermenter is preheated using the reactor effluent. However, only obtainable heat streams, but not temperature level and minimum temperature differences for heat exchange are considered yet. The difference in chemical demand is related to the amount of KOH needed to regulate pH value in THF. More alkaline is needed for pH adjustment in scenario 2 since with the use of liquid effluent from pretreatment (stream D) also main amount of sulphuric acid used in pretreatment is entering THF. This fact is also visible in the increase of osmolality in THF from 2,2 to 3,4 osmol/kg violating the limit of 0,3 osmol/kg defined in Hyvolution process (Foglia et al.,2011). Steam result for out-going streams are given in Appendix A for scenario V1 and V2 (Tables A.2 and A.3).

D stream

D stream

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Table 4: Utility demand and osmolality for THF at 10 g/l feed concentration

THF V1 THF V2 Water demand , kg/h 386,03 375,77 Heat demand, kW 3,09 3,53 Chemical demand, kg/h 7,07 17,4 Osmolality after THF, osmol/kg H2O 0,216 0,340

4.2. Increase of Acetate Tolerance WP3 is working on the development of acetate tolerant organisms, which might enable the increase of substrate concentration in THF. Based on the assumptions in scenario V1 a case study was performed in increasing the substrate concentration in the feed stream. Results are presented in Table 5 in terms of water demand, reactor volume and osmolality. Table 5: Results of case study on substrate concentrations

Substrate concentration, g/l sugars 10 15 50 100 Total water demand (PTR+THF) , kg/h 1697 1318,87 756,00 634,74 Osmolality after THF, osmol/kg H2O 0,216 0,313 1,101 2,613

Results show a considerable reduction in water demand. However, it has to be considered that from pretreatment a maximum sugar concentration in feed stream of approx. 15 g/l can be obtained at the used process conditions. A further increase of substrate concentration needs also reduction of water demand in pretreatment. Due to the considered basic heat integration measures in thermophilic fermentation step (see above) heat demand (not reported in Table 5) only changes slightly. However, changing pretreatment conditions to increase sugar concentration in the hydrolysate might influence overall heat demand of the process. As obvious from table besides an increased acetate tolerance an increased tolerance of osmolality of used microorganisms is necessary, to run the process at higher substrate concentrations.

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5. Gas-Upgrading Due to the ongoing research on gas upgrading technologies within HyTime no overall balances, but basic studies on the influence of partial pressure reduction of H2 on gas composition and a parameter study on insitu H2 removal via membranes, is presented in this section. Calculated gas solubilites as a function of pH (not presented here) formed the basis for estimating gas composition as presented in D4.1. Furthermore, it could be shown, that up to a pressure 20 bar the use of activity coefficient models is sufficient, whereas at high pressure non-ideal behaviour in the gas phase has to be considered with a combination of activity coefficient models and equation of state (EOS). Calculation of H2 and CO2 solubility in acetic acid-water mixtures at different pH conditions discovered, that at a pH lower or equal to 6,5, solubility of H2 and CO2 and thus gas composition obtained from thermophilic fermentation do not change a lot. Once the pH goes higher than 6,5, solubility of H2 and CO2 seems to increase. Reason for this behaviour is that CO2 dissolves better at the higher pH. Thus, partial pressure of CO2 in the gas phase decreases, whereas partial pressure of H2 increases, finally giving also a higher H2 solubility in the liquid phase.

5.1. Reduction of H2 partial pressure / H2 concentration in the liquid The influence of the (partial) pressure on H2 and CO2 solubility was investigated in the total pressure range from 0,4 bar until 2 bar. Figure 10 shows that when a higher pressure is applied in the system, gas solubility in the liquid stream is higher. The minimum pressure that could be reached in the system is 0,4 bar due to the liquid’s boiling point. Green points in the Figure 10 represent the value for osmolality calculated in the system. Calculated values are much lower than the critical value. Furthermore, an increased CO2 solubility due to changes in pressure / partial pressure only contributes slightly to the osmolality. Main contribution to osmolality is based on formed acetic acid in THF as well as added alkaline (KOH) to control pH (see also results in section 3). Lower osmolalities compared to results presented in section 3 can be explained by the absence of H2SO4 residues from pretreatment in the calculation results presented here.

Figure 10: Gas solubility and osmolality results at different pressure values

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Figure 11 presents some basic consideration towards gas stripping. In general, stripping gas is introduced in order to remove hydrogen from the liquid stream and to avoid hydrogen inhibition. Stripping is usually done by applying N2. Due to the results presented in Figure 10, also CO2 can be used without compromising osmolality of fermentation broth. Besides gas stripping, applying vacuum to the THF would decrease H2 partial pressure and thus, H2 concentration in the liquid. Figure 11 illustrates the amount of stripping gas to be introduced to obtain the same H2 concentration in liquid, as reached under certain vacuum conditions. For example, if the goal is to be under 2,0E-06 mole fraction hydrogen in the liquid, it is necessary to apply a vacuum of around 0,4 bar or to introduce approx. 90 kmol/h of the stripping gas. All calculations are based on the assumption of an established equilibrium between gas and liquid phase.

Figure 11: Stripping at different conditions (product gas flow = 20kmol/h) However, while applying vacuum reduces hydrogen concentration in the liquid without changing the product gas composition (approx. 66 vol% hydrogen in dry gas stream from THF), the introduction of stripping gas may lower the hydrogen concentration in the product gas considerably as obvious from Figure 12. Scientific investigations use ratios between product gas and stripping gas of 1:8-14 (de Vrije, 2012), resulting in a hydrogen concentration below 10 vol%. For establishing the same liquid concentration when applying a vacuum of 0,55 bar (Aspen Plus calculations in Hyvolution project) a ratio of approximately 1:2 is necessary, reducing the hydrogen concentration in THF product gas to 22 vol%. During Hyvolution project, partner Profactor was able to operate the THF at an experimental ratio of 3 parts of produced gas and one part of stripping gas (de Vrije, 2012), resulting in 50% hydrogen purity in the gas stream. In a following national project the ratio was 10:1 (Profactor, 2012) finally resulting in a hydrogen concentration in the product gas of more than 60 vol% (extrapolated from Figure 12). In can be summarized, that dissolved CO2 only slightly increases osmolality. Vacuum stripping does not change the product gas composition in THF, but gas-stripping decreases H2 content in the product gas. At a stripping ratio of 3:1 (product gas : stripping gas) the H2

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content is reduced from approx. 0,66 to 0,5 mol/mol. A stripping ratio of 10:1 as used by Profactor in late experiments would rarely influence product gas composition.

Figure 12: Influence of ration between product gas and stripping gas on hydrogen purity

5.2. H2-removal from liquid via membranes – basic simulation study To reduce hydrogen content in the THF fermentation broth, WP3 suggested the application of membranes to remove gases from the liquid as a possible alternative to vacuum- or gas-stripping. Basic calculations in Aspen Plus try to analyse the feasibility of this suggestion. All calculations are based on the assumption of an established equilibrium between gas- and liquid phase. The flowsheet of the setup is shown in Figure 13. THF is represented by a simple flash, where liquid (fermentation broth, recycle from membrane unit) and gas streams are mixed. THF is operated at 1 bar, 70°C and pH 6,5, adjusted with KOH. The liquid stream leaving the flash is saturated with product gas. Part of this liquid stream is by-passed over the membrane unit (represented by a component split); the rest of the liquid leaves the system. Liquid flow through the membrane (0,1-15*Feed to “THF”) unit is adjusted via a stream split. In the membrane unit, part of the dissolved gases are removed from the liquid. The following scenarios have been investigated:

• Removal of 75% H2 + 75% CO2 (Case 1) • Removal of 75% H2 + 0% CO2 (Case 2, selective membrane) • Removal of 75% H2 + 25% CO2 (Case 3) – not shown in Figures 13 and 14

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Figure 13: Flowsheet of setup for gas removal from liquid phase via membrane unit In case 1 it is assumed, that H2 and CO2 are removed in the same manner. This results in the fact, that H2 concentration in the liquid increases (Figure 14), since in absolute numbers more CO2 is removed than H2 due to the higher solubility of CO2. Thus the mole fraction/partial pressure of CO2 in the gas phase decreases, partial pressure of hydrogen increases (Figure 15), resulting in a higher H2 content in the liquid phase. Case 3 shows a comparable behaviour. However, concentration increase of H2 in liquid phase is less than in case 1. With increasing liquid flow rate over the membrane unit more and more product gas is leaving the system via the membrane instead via the vapour phase leaving the THF. In case 2 (only H2 passes the membrane = selective membrane) a slightly reduction of H2 concentration in the fermentation broth can be observed. However, the change in H2 content of the liquid is negligible.

Figure 14: Gas content in liquid phase as a function of liquid flow rate over the membrane unit

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Figure 15: Gas content in gas phase and mole flow product gas removed via the

membrane unit as a function of liquid flow rate over the membrane unit Based on these simulation results it is difficult decide on the effectiveness of the proposed setup to reduce hydrogen concentration in the liquid phase. Calculations show a slightly decrease of H2 content, in case only H2 is able to pass the membrane. Due to the low equilibrium solubility of H2, the amount of removed H2 is low. Assuming “oversaturation” of formed H2 in the liquid, this excess H2 might be removed. Necessary liquid flow rate over the membrane module as well as membrane area must be investigated and determined experimentally. Under the assumption that both gases pass the membrane, simulation results predict an increase in concentration of H2 in the liquid phase. Real system behaviour has to be evaluated experimentally applying vacuum or a sweep gas on permeate side of the membrane unit. A potential advantage of the membrane unit could be seen in the fact that a larger „liquid surface“ is exposed to applied vacuum. However, surface should be also large in using the trickle bed compartment compared to the use of a stirred tank reactor!

6. Anaerobic Digestion Due to thermodynamic limitations during thermophilic fermentation carbohydrates cannot be converted completely to H2 and CO2. In the best case sugars are degraded to acetic acid, giving a maximum H2 yield. However, residues from thermophilic fermentation as well as from other process steps can be further converted to biogas (CH4 + CO2) via anaerobic digestion. Biogas could be used to cover the demand of heat and power of HyTime process.

6.1. Model of biogas formation Based on an extensive literature study the following options for modeling anaerobic digestion have been identified:

1. Chemical oxygen demand (COD) – Calculation of amount of methane, but not of the composition of biogas

2. Elemental composition / (Extended) Buswell formula – Calculation of amount and composition of biogas, but only for an overall stream not considering the degradability of involved components

3. Stoichiometric reactions with fractional conversion factors – Calculation of amount and composition of biogas by definition of fractional conversion factors for different components

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4. Anaerobic digestion model no. 1 (ADM1) – rigorous modeling of biogas formation based on kinetic reactions including the effect of inhibitors

It was finally decided to implement options 1-3 into an Aspen Plus model to be used in HyTime project. Option 4 was omitted due to the need of detailed experimental data to adjust the model parameters to the used substrate.

Figure 16: Models of biogas production routes in Aspen Plus Figure 16 illustrates the basic flowsheet of the anaerobic digestion model in Aspen Plus enabling the calculation of all selected calculation routes in parallel. As it is shown in Figure 16, the same input stream is used in all 3 routes. For this purpose, a triplicate unit from Aspen Plus unit operation library is used. After triplication, all 3 streams have the same composition and mass flow. One stream is connected to the Buswell route, the other one to Stoichiometric route and the third one to COD route. For accurate results with Buswell and COD model, it was necessary to distinguish between degradable and non-degradable components in the system. In Buswell and COD calculations non-degradable components are split off before calculating the biogas formation. In the stoichiometric reactor only the defined reactions take place based on the given fractional conversion, thus the non-degradable don’t have to be split off. However, both models – based on COD and Buswell – can be used for analyses of the theoretical biogas potential of every process stream of interest with the full component set. Biogas via Chemical Oxygen Demand (COD) Since the exact chemical composition of the substrate is often not known, the methane production is calculated via COD reduction. Aspen Plus provides a property set called CODMX (chemical oxygen demand of a mixture) which calculates the theoretical oxygen demand (equal to the chemical oxygen demand) of a chemical substance CcHhClclNnNanaOoPpSs with molecular weight MW of a stream with a defined composition (Solution ID 122047, AspenTech Knowledge Base, 2013).

(Eq. 2)

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Based on the obtained COD, the amount of CH4 can be easily obtained via a FORTRAN code implemented in a calculator block. The calculator block can be connected to any process stream to analyze its biogas potential. The COD represents an unspecific measure, not considering whether components can be really degraded to CH4. For example a high salt (NaCl) or alkaline content (NaOH) would contribute to the COD, but give no methane. Therefore, the model should include a split unit to separate degradable components contributing to biogas formation and non-degradable components which are by-passed. Disadvantage of the model is the fact, that only the amount of CH4 but not the composition of biogas is accessible. Biogas via Buswell If the chemical composition of organic matter is known, the biogas yield can be calculated via Buswell formula. Original Buswell formula only considers elements C, H and O for biogas formation, whereas Extended Buswell formula also includes elements N and S. The formula assumes that components CcHhOoNnSs and H2O react to CO2, CH4, NH3 and H2S (Buswell and Mueller 1952; Boyle, 1977). Thus, besides amount of produced CH4, Buswell formula also gives the composition of the produced biogas. However, still the definition of degradable and non-degradable components is necessary. Based on the substrate/biomass composition the amount of generated biogas is given by Eq. 3 (Jördening and Winter, 2005): CcHhOoNnSs + ¼ (4c-h-2o+3n+2s) H2O ⅛ (4c-h+2o+3n+2s) CO2 + ⅛ (4c+h-2o-3n-2s) CH4 + nNH3 + sH2S (Eq. 3) The difficulty of the application of Buswell formula is to create a fictional chemical formula (CcHhOoNnSs) out of individual mole fractions of real components (glucose, sucrose, acetic-acid, cellulose ...). The elemental coefficients c, h, o, n, and s have to be interpreted as mole fractions referring to 1 mole of the fictional chemical substrate formula. Thus, the mole fractions of elemental builders of biomass are not necessarily equal to elemental coefficients in the biomass structural formula. Again a split-unit is implemented in the Aspen Plus model (Figure 16a), to separate degradable and non-degradable components from input stream. H2O has to be also separated, because H2O represents a non-degradable component. However, since Buswell’s equation includes H2O as reactant, H2O has to be added again before calculation of biogas potential and composition via extended Buswell equation. In order to implement all these theoretical considerations about the transformation of the mole fractions into elemental coefficients, in Aspen Plus, a calculator block was implemented in the flowsheet. This calculator block calculates the coefficient for chemical formula out of empirical formula. Biogas via stoichiometric reactions A third option for modelling anaerobic digestion is based on the definition of degradation reactions for each component in the system contributing to the formation of biogas. For each component a fractional conversion factor (literature, experience, and experiment) must be defined to account for the degradability of the component. Example implementations of this concept in Aspen Plus are for example available from NREL (Humbird et al., 2011) and Lassmann, 2012 (extended NREL model based on Barta et al., 2010). In the Aspen Plus flowsheet, shown in Figure 16, stoichiometric route for biogas production is the central one (b). It consists of one reactor (RStoic reactor from Aspen Plus unit operation models) and one flash to separate gas and liquid stream. The fractional conversion factors of

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the reactions are at the moment 1, but they will be adapted according to the experimental results or adequate literature source. Biogas formation using stoichiometric reactions is the preferred route for modelling anaerobic digestion in Aspen Plus, since it completely follows the component based modelling approach of the other process steps.

6.2. Model for biogas utilization For the purpose of biogas utilization in a first step a gas engine is foreseen producing electric power and process heat. However, other utilization options can be implemented in the flow sheet (Figure 17). As feed flow for biogas utilization step the raw biogas stream from stoichiometric biogas calculations is used. In the first step H2S is removed (process not specified yet) because sulphur would harm the engine. In the next step a flash model is implemented to adjust an appropriate biogas dew point. After the pretreatment of the biogas, the stream is multiplied in order to calculate three optional utilization pathways: combined heat and power generation (CHP) via gas engine (Figure 17a), combustion (up till now: combustion of the biogas at adiabatic flame temperature) (Figure 17b), and biogas upgrading (e.g. pressurized water scrubbing or upgrading via gas-permeation – not yet implemented in the flowsheet) (Figure 19c).

Figure 17: Model of biogas utilization in Aspen Plus Results presented below are based on biogas utilisation in a gas engine to produce heat and power. A gas engine is an internal combustion engine and works on the principle of the Otto Cycle. The process is described by the following cyclic steps also represented in the Aspen Plus model

• Process 1-2 isentropic compression COMP • Process 2-3 isochoric supply of heat (combustion) CHP-reactor (RGIBBS) • Process 3-4 isentropic expansion EXP • Process 4-1 isochoric heat removal (heat exchange) CHPHEAT (stream)

Composition of flue gas leaving the gas engine and enthalpy balance of combustion is calculated via Gibbs-minimization in the CHP-reactor. Power output and heat output are obtained from heat and power output of CHP-reactor via efficiencies (ETHAEL, ETHTH). Bothe, efficiencies and typical flue gas temperature are taken from datasheets of IWK & Jenbacher gas engines. A screen-shot of input-/output-variables and the FORTRAN code of the gas engine model is depicted in Figure B.1 in Appendix B.

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Biogas results for V1 and V2 The anaerobic digestion model in combination with themodel for biogas utilization (gas engine) was used to analyse the biogas potential as well as obtained heat and power from residual streams of wheat straw pretreatment (section 3) and thermophilic fermentation (section 4). Results for process scenarios V1 and V2 (see Figures 8 and 9) are summarized in Tables 10 and 11. Table 12 opposes heat demand of process steps with heat obtained from biogas utilisation showing a considerable deficit of process heat. However, no heat integration measures are introduced in the pretreatment step, yet. Results concerning obtained amount and composition of biogas reflect theoretical values giving a glance on the amount of process heat to be covered, since no conversion factors are implemented in the model. Reliable results are expected after full validation of the anaerobic digestion model with plant data from process partners as well as comparison of experimental biogas yields from process residues. Table 10: Biogas potential for acid pretreatment of wheat straw and THF scenario V1 Total produced biogas, kg /h

Biogas composition, mole fraction Heat from biogas utilisation, kW

Power from biogas utilisation, kW

CH4 CO2 H2O NH3 H2S 21,6 0,440 0,440 0,104 0,0001 0 33,51 30,84

Table 11: Biogas potential for acid pretreatment of wheat straw and THF scenario V2 Total produced biogas, kg /h

Biogas composition, mole fraction Heat from biogas utilisation, kW

Power from biogas utilisation, kW

CH4 CO2 H2O NH3 H2S 18,0 0,435 0,439 0,108 0,0002 0 31,7 29,1

Table 12: Heat summary for process scenarios V1 and V2

Heat input/output, kW Process model PTR input THF input Total input Biogas output Deficit/Surplus

V1 38,27 3,09 41,36 33,51 -7,85 V2 38,27 3,53 41,80 31,7 -10,1

7. Summary and Outlook Deliverable 5.1 summarizes the features of the implemented models of process steps and presents basic mass- and energy balances. Results represent a rough estimate, since all process steps are still under experimental investigation. Nevertheless, results will be critically discussed with partners from WP2 to WP4 and in this way contribute to experimental planning. Available models will be updated with upcoming experimental data giving more precise balancing results for the process steps as well as for the overall process. Next steps will include the validation of anaerobic digestion models and models for biogas utilization with real data from biogas plants (provided by partners Envipark and AWITE). Afterwards the models will be combined to represent the overall process. This step will also enable the implementation of further heat integration steps.

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References AspenTech Knowledge Base, http://support.aspentech.com, 2013

Barta, Z., Reczey, K., and Zacchi, G., Techno-economic evaluation of stillage treatment with anaerobic digestion in a softwood-to-ethanol process, Biotechnology for Biofuels, 3, 21, 2010

Batstone D.J., J. Keller, Angelidaki I., Kalyuzhnyi S.V., Paviastathis S.G., Rozzi A., Sanders, W.T.M., Siegrist H., Vavilin V.A.; Anaerobic Digestion Model No.1 (ADM1) - IWA task group for modelling of anaerobic digestion processes; IWA Publishing, 2002

BioBib- A Database for biofuels http://www.vt.tuwien.ac.at/biobib/

Boyle W.C., Energy recovery from sanitary landfills – a review, in Microbial Energy conversion; Pergamon Press, 1977

Buswell A.M. and Mueller H.F., Mechanism of Methane Fermentation; Industrial and Engineering Chemistry 44 (1952) 550-552

De Vrije, internal communication, 2012

Foglia, D., Wukovits, W., Friedl, A., Ljunggren, M., Zacchi, G., Urbaniec, K. and Markowski, M., Effects of feedstocks on the process integration of biohydrogen production., Clean Technologies and Environmental Policy, 13, 547-558, 2011

Humbird et al., Process Design and Economic for Biochemical Conversion of Lignocellulosic Biomass to Ethanol; NREL, 2011

Hyvolution Deliverable report D5.43-“Amendment to basic plant design - simulation, integration and engineering”, 24.1.2011

Jördening H.J. and Winter J., Environmental Biotechnology- Concepts and Applications. Weinheim: Wiley-VCH Verlag GmbH & Co. KGaA, 2005

Lassmann, T., Downstream processing in the ethanol production from lignocellulosic biomass - A process simulation with ASPEN PLUS including an energy analysis, Master Thesis, Vienna University of Technology, 2012

Phyllis database for biomass and waste, http://www.ecn.nl/phyllis2/

Profactor, private communication, 2012

Unscrambler V9.0, Oslo: CAMO software

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Appendix A – Selected stream results for process steps Table A.1: Preliminary mass balance for acid pretreatment of wheat straw

PTR ACIDH20 PT-WTDRY PTR-LIQ TO-THF Substream: Liquid (water+acid) (dry wheat straw) (liquid stream) (stream to THF) Mass flow kg/hr H2 - - - - O2 - - - - CO2 - - - - N2 - - - - H2S - - - - SO2 - - - - H2O 321,92 - 286,09 774,27 Glucose - - 0,32 10,88 Xylose - - 3,39 0,93 NH3 - - - - Acetic acid - - - - KOH - - - H2SO4 8,09 - 7,20 0,28 HCl - - - - Total flow kg/hr 330,00 297,00 786,36 Substream: Solid Mass flow kg/hr Cellulose - 12,63 - 2,51 Hemicellulose - 9,21 - 5,15 Lignin - 2,19 - 2,19 Cell Mass - - - - Rest - 8,98 - 8,98 Total flow kg/hr - 33,00 - 18,84 Total stream flow, kg/hr 330,00 33,00 297,00 80,52

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Table A.2: Preliminary mass balance for THF in scenario V1 at 10 g/l feed concentration

THF TH-FEED TH-GOUT TH-TO-AD

Substream: Liquid (hydrogen stream) (stream to anaerobic digestion) Mass flow kg/hr H2 0,42 - O2 0,03 - CO2 6,19 0,42 N2 - - H2S - - SO2 - - H2O 774,27 0,44 1159,08 Glucose 10,88 - 0,54 Xylose 0,93 - 0,05 NH3 0,00 - 0,01 Acetic acid 0,00 - 6,30 KOH 0,00 - 7,07 H2SO4 0,28 - 0,28 HCl 0,00 - 0,25 Total flow kg/hr 786,36 7,09 1174,89 Substream: Solid Mass flow kg/hr Cellulose 2,51 - 2,51 Hemicellulose 5,15 - 5,15 Lignin 2,19 - 2,19 Yeast - - 0,89 Rest 8,98 - 8,98 Total flow kg/hr 18,84 - 19,72 Total stream flow, kg/hr 80,52 1194,61

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Table A.3: Preliminary mass balance for THF in scenario V2 at 10 g/l feed concentration

THF PTR-LIQ TH-FEED TH-GOUT TH-TO-AD Substream:Liquid (hydrogen stream) (stream to anaerobic digestion) Mass Flow kg/hr H2 - - 0,56 - O2 - - 0,07 - CO2 - -- 7,78 0,60 H2O 286,09 1436,48 0,57 1434,31 Glucose 0,32 11,21 - 0,56 Xylose 3,39 4,32 - 0,22 NH3 - - 0,01 0,02 Acetic acid - - - 8,28 KOH - 17,40 - 17,40 H2SO4 7,20 7,48 - 7,48 HCl - 0,25 - 0,25 Total liquid flow kg/hr 297,00 1478,04 8,98 1470,02 Substream: Solid Mass flow kg/hr Cellulose - 2,51 - 2,51 Hemicellulose - 5,15 - 5,15 Lignin - 2,19 - 2,19 Cell-mass - 0,00 - 1,16 Rest - 8,98 - 8,98 Total solid flow kg/hr - 18,84 - 20,00 Total stream flow, kg/hr 297,00 1496,88 8,98 1490,02

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Appendix B – Variables and Fortran code for simulation model of gas engine (calculator block)

Figure B.1: Gas engine calculator block

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Appendix C – Reworked component list

Table C.1. Extended component list based on Hyvolution simulation model

Component ID Type Real Formula (Alias) Component Aspen Keep? Basic Components

H2 CONV H2 HYDROGEN Yes O2 CONV O2 OXYGEN Yes CO2 CONV CO2 CARBON-DIOXIDE Yes N2 CONV N2 NITROGEN Yes H2S CONV H2S HYDROGEN-SULFIDE Yes NH3 CONV H3N AMMONIA Yes SO2 CONV O2S SULFUR-DIOXIDE Yes H2O CONV H2O WATER Yes HAC CONV C2H4O2 ACETIC-ACID Yes

Component ID Type Real Formula (Alias) Component Aspen Keep?

Sugar-Components SUCROSE CONV C12H22O11 SUCROSE Yes GLUCOSE, C6 CONV C6H12O6 GLUCOSE Yes XYLOSE, C5 CONV C5H10O5 XYLOSE Yes GALACTOS CONV C6H12O6 GLUCOSE Partner MANNOS CONV C6H12O6 GLUCOSE Partner ARABINOS CONV C5H10O5 XYLOSE Partner OLIG-GLU CONV C6H12O6 GLUCOSE Partner OLIG-XYL CONV C5H10O5 XYLOSE Partner OLIG-GAL CONV C6H12O6 GLUCOSE Partner OLIG-MAN CONV C6H12O6 GLUCOSE Partner OLIG-ARA CONV C5H10O5 XYLOSE Partner

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Component ID Type Real Formula (Alias) Component Aspen Keep? Biomass Components

GLUCAN SOLID C6H10O5 CELLULOS Yes XYLAN SOLID C5H8O4 XYLAN Yes MANNAN SOLID C6H10O5 CELLULOS Partner GALACTAN SOLID C6H10O5 CELLULOS Partner ARABINAN SOLID C5H8O4 XYLAN Partner LIGNIN SOLID C7,3H13,9O1,3 LIGNIN Yes STARCH SOLID C6H10O5 CELLULOS Yes PECTINE SOLID C6H10O5 CELLULOS Partner PROTEIN SOLID CELLULAS CELLULAS Partner ASH CaO/SiO2 Yes Cellulose SOLID C6H10O5 CELLULOS Yes Hemicellulose SOLID

XYLAN Yes

Oil/Fat

Partner Cellobiose as C12H22O11 as Sucrose - H2O Partner

Component ID Type Real Formula (Alias) Component Aspen Keep? Bacteria/Cell Mass

ENZYME SOLID CH1,57N0,29O0,31S0,007 Cellulase ??? CH4Bacteria CH1,64N0,23O0,39S0,0035 BIOMASS Yes H2Bacteria

CH1,64N0,23O0,39S0,0035 BIOMASS Yes

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Component ID Type Real Formula (Alias) Component Aspen Keep? By-Products / Inhibitors

ETHANOL CONV C2H6O-2 ETHANOL Partner FURFURAL CONV C5H4O2 FURFURAL Yes HMF CONV C6H6O3

Yes

FORMIC CONV CH2O2 FORMIC-ACID Partner LACTIC-A CONV C3H6O3-D1 LACTIC-ACID Yes Proprionic Acid CONV C3H6O2-1 Partner SUCCINAT CONV C4H6O4-2 SUCCINIC-ACID Partner LEVULIN CONV C5H8O3-D1 LEVULINIC-ACID Partner Phenol(s) CONV C6H6O PHENOL Partner Coumaric acid CONV C9H8O3-N2 P-HYDROXYCINNAMIC-ACID Partner Syringaldehyd CONV Partner Ferulic acid CONV C10H10O4-N1 4-HYDROXY-3-METHOXYCINNAMIC-ACID Partner Coniferylaldehyd CONV Partner p-Cresol CONV C7H8O-5 4-Cresol Partner XYLITOL CONV Partner GLYCEROL CONV C3H8O3 GLYCEROL Partner FURFALKO CONV C5H6O2 FURFURYL-ALCOHOL Partner Acetaldehyd CONV C2H4O-1 Partner

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Component ID Type Real Formula (Alias) Component Aspen Keep? Other chemicals

KOH CONV KOH POTASSIUM-HYDROXIDE Partner NAOH CONV NAOH SODIUM-HYDROXIDE Partner HCL CONV HCL HYDROGEN-CHLORIDE Partner H2SO4 CONV H2SO4 SULFURIC-ACID Yes H2SO3 CONV H2SO3

???

Ca(OH)2 CONV Ca(OH)2

Partner K2HPO4 CONV K2HPO4 DIPOTASSIUM-PHOSPHATE Partner KH2PO4 CONV KH2PO4 POTASSIUM-DIHYDROGEN-PHOSPHATE Partner H3PO4 CONV H3PO4 ORTHOPHOSPHORIC-ACID ??? (NH3)2HPO4

Partner

NH4Acetate

Partner NH4SO4

Partner

P2O5, Na2O, HX ??? Check importance / use / definition (as other compound) Not included in Hyvolution