Inorganic compounds, such as Cl and S-containing material, HCN, COS, and am­monia, can be removed by means of physical and chemical washing techniques. Removal of ammonia from biomass is necessary in many situations since they are converted to NOX when gas is burned. Ammonia can be removed by catalytic destruc­tion using catalysts similar to those used for tar cracking and also by wet scrubbing where low temperature product gases are acceptable. Catalysts, such as dolomite, nickel-based steam reforming catalysts, and iron-based catalysts, have been used for ammonia removal with > 99 % efficiency. Catalytic removal is economically an attractive option since it has the potential to remove tar and ammonia from product gas while keeping its heat [60].

In systems where product gas is first cooled, ammonia can be removed by wet scrubbing. The ammonia recovered from the scrubber is reinjected into the gasifier to reduce ammonia production through equilibrium.

H2S can be removed by different sorptions, such as metal oxides, Cu- and Ca-based sorbents. For example, the Selexol process uses dimethyl ethers of polyethylene glycol and the Rectisol process employs methanol as a solvent to remove H2S and COS and simultaneously remove CO2 from syngas [61].

In these models, a feedstock first reacts to yield volatiles and intermediate solid products (Fig. 11.2c). The following steps then depend on the feedstock and the
model. In most models, the volatiles undergo thermal cracking while the intermediate solid products further decompose into other final and/or intermediate products and so on. For highly heterogeneous materials, where the notion of ‘pseudo-component’ loses its physical meaning, this conceptualization appears more realistic. However, the main disadvantage of this type of model is the high number of parameters and the difficulty to segregate the different reactions experimentally to clearly estimate their kinetics parameters. Considering all the possibilities for the different reactions under various conditions, this family of models will lead to a myriad of different models.

Table 11.2 lists the kinetics parameters of several models available in the scientific literature along with their range of validity. Note that the parameters reported in Ta­ble 11.2 were all obtained from static thermogravimetric experiments. Furthermore, some of these models assumed an order of reaction, while pyrolysis reactions are in reality characterized by multiple elemental reactions with their specific reaction order. Moreover, it has been demonstrated that the product yield during biomass pyrolysis is strongly dependent on the temperature, while all the models listed in Ta­ble 11.2 assume that the product yields follow the non-isothermal or isothermal TGA temperature profile used to evaluate the kinetics. Therefore, none of these models can confidently reproduce the variability of products yields with respect to temperature. Also, there is significant uncertainty as to whether these kinetic expressions will be accurate when extrapolated to industrial pyrolysis conditions. To model industrial scale pyrolysis processes, it is critical to develop reliable and robust pyrolysis models based on experimental data obtained at representative conditions.

In the late 1990s of the 20th century, interest to gasification technologies of solid fuels has renewed against the background of fossil resources price rising. IEE RAS started researching in this field as it is one of perspective implementations of low-temperature plasma systems. The experimental installation for investigation of plasma gasification process (Fig. 12.6) has been created [91].

The reactor is the key element of this installation. This is a fixed bed downdraft apparatus gasifier. Solid fuel is loaded into the reactor from above (Fig. 12.6, zone I).

After that it is gradually moved downwards to a zone of slag discharge (VII) by grav­ity and due to fuel gasification in the lower layers of the reactor. The raw materials consistently pass a zone of evaporation (II), pyrolysis (III), oxidation (IV), and re­duction (V); as a result, the organic mass and water are converted into the syngas. These processes are initiated and supported in the reactor by plasma streams gener­ated by plasma torches. Gasifier has the loading device which allows portion loading of feedstock during the experiment (Fig. 12.6, pos. 5).

The reactor has three oxidant injection points along the shaft length. The first (top) point is meant for supplying the oxidizer of the moderate temperature (no more than ~400-500 °C), the second and the third points are used to supply the low-temperature plasma. Plasma can be supplied in each these two points from two plasma torches simultaneously. High-voltage AC air plasma torches with power up to 50 kW or a combination of air and steam (or CO2) plasma torches are used on the installation.

Syngas is removed from the bottom part of the reactor. In addition, the possibility to supply plasma or other oxidant for the accelerated heating at the first stage of experiment is provided in this zone.

The created gasifier is designed for working under a pressure close to the atmo­spheric. The gas flow in the gasifier shaft is induced by pressure 0.3 ± 0.2 kPa below an atmospheric pressure created in the outlet branch (Fig. 12.6, pos. 7) by the exhaust fan positioned at the end of the processing chain (Fig. 12.6, pos. 15).

The bottom part of the reactor is equipped with a revolving grate (Fig. 12.6, pos. 6) for the slag removal. Below the revolving grate, the water valve is arranged which has two functions: the reaction chamber closure and explosive valve function.

The installation is designed to investigate the composition of syngas and process characteristics. Gas samples for the analysis are taken at the gasifier outlet (Fig. 12.6, pos. 7).

There are two sampling systems. The first one utilizes two sampling lines in automatic mode. Gas, pumped out from gas duct by the vacuum pump, passes the hot filter, the cyclone, the cooler, the fine gas cleaning filter, and then is analyzed by a time-of-flight mass spectrometer EMG-20-1 (Mettek, Russia).

The second system is designed for separation and measuring of water and tars of syngas. The first element in the system after sampling probe is the hot filter. Two methods of water content measurements based on condensation and absorption are realized. The volume of liquid condensed from the syngas stream during its cooling is measured along with the gas-flow rate and its temperature in the condensation method. In the absorption method, water and steam are completely absorbed from the syngas stream at constant flow rate and measured by the milligram scale. The dried gas sample is pumped to the quadrupole mass-spectrometer MKS Cirrus-300 (MKS Instruments, USA) for composition analysis. Condensed liquid is investigated on tar content.

Mass-spectrometers allow performing the continuous analysis of synthesis gas composition for both the macro — and micro-concentrations. The plasma gasification mode is corrected using these data along with the information about temperatures in the reactor and plasma flow rates. These data are recorded and subsequently analyzed to determine the mass and energy streams of processes and other parameters.

Control over the mass streams, temperatures, and pressures in the reactor and in other elements of the experimental installation allows the installation operation mode regulating. These parameters are continuously measured and recorded. The changing of oxidant flow rate and plasma torch power are the basic leverages of the process.

The produced syngas after samples are taken in branch pipe is subjected to com­bustion. The afterburner serves for this purpose. In the afterburner, the syngas is mixed with the required amount of air and burns out. The device for forced ignition is installed for flame stabilization and prevention of explosion risk. A single-phase high-voltage plasma torch of low power is used as such a device.

The exhaust gases from the afterburner pass through the gas treatment system to the stack and into the atmosphere. Wet method of cleaning is used. It comprises two consecutive devices: spray and packed bed scrubbers.

Chemical catalytic systems with liquid acids have the difficulty in separating the homogeneous catalysts from product solutions. Solid acid catalysts have many ad­vantages over liquid catalysts. They are widely studied as direct replacements for liquid acids to reduce pollutants and operating costs. A solid acid catalyst is defined as solid that can donate protons (Brpnsted, B acid) or accept electrons during re­actions (Lewis, L acid). The catalytic function for a solid acid catalyst is derived from its acidic centers, existing mainly on its surface. Accordingly, solid acids with B acid sites can catalyze biomass hydrolysis. Because L acid catalysis of cellulose conversion was reviewed [24], this section focuses on B acid catalysis.

The mechanistic route of cellulose hydrolysis by solid acid catalysts consists of the following steps: (1) crystalline cellulose dissolves in some chemical agents, such as ILs; (2) the soluble polysaccharide diffuses onto the surface of the solid acid catalysts; (3) the polysaccharide undergoes hydrolysis over the acid sites; (4) some hydrolysis oligosaccharides diffuse into the internal pores of solid acid catalysts; (5) the poly-oligosaccharides undergo hydrolysis over the surface and internal acid sites; (6) the hydrolysis products, mainly glucose, diffuse into the reaction medium. Therefore, the properties of solid B acid catalysts, such as acid site density, acid strength, structure of supports, acid site distribution, and tolerance to water, have great influence on their activities and selectivities. Under ordinary circumstances, acid strengths and catalytic activities of solid acid catalysts decrease in the presence of water. Moreover, most solid acids do not function effectively for cellulose hydrolysis because the surfaces of these solids do not have strong acid sites or cannot allow their close contact to |5-1,4-glucans. Therefore, it is a challenge to develop hydrothermal catalytic hydrolysis processes with solid acid catalysts. It is important to acquaint with the properties of solid B acid catalysts considerably.

In current scenario to utilize the lignocellulosic material for green energy, the pre­treatment is an unavoidable step in biorefinery with the cost as high as 30 cents/gallon ethanol produced [10]. Approximately, pretreatment alone costs around 30 % to the

total processing cost in the conversion oflignocellulosics into ethanol [29]. Perfor­mance of pretreatment methods and the incurred cost on bioconversion process was comprehensively analyzed by Eggeman and Elander [72]. The ideal pretreatment process needs to be highly efficient with imposing low operational and capital cost with less pollution [10, 16, 73]. Recovery of maximum sugars after pretreatment, less chemical load, usage of by-products, faster kinetics, and less process complexity are the important criteria to determine the overall impact of pretreatment methods [11, 16, 17]. All these features determine the cost on downstream processing steps and the trade-off with operational cost, capital cost, and biomass cost [10, 68, 73]. Table 16.5 analyzes the environment and economic impact of various pretreatment

methods applied to SB/SL. Critical features like upstream and downstream process­ing cost, capital investment, chemical recycling, usage of by-products, and waste treatment systems makes the comparison and evaluation of pretreatment methods difficult [74]. Net impact of each pretreatment method concerning the economics and environmental impact shows that chemical-based pretreatment methods have strong impact on economics of overall biomass conversion along with considerable environmental pollution burden (Table 16.5).

Pure chemical based pretreatment methods require significant amount of chemi­cals for biomass destruction with the significant amount of by-products generation [14, 17]. However, these methods are highly effective toward either lignin re­moval or hemicellulose degradation from lignocelluloses in short reaction times. Physico-chemical methods (dilute acid hydrolysis, AFEX, steam explosion, etc) have considerable effect on economics and environmental concerns [14, 17]. These methods are more specific toward hemicellulose or lignin degradation leaving cel — lulignin and holocellulose together but in disorganized manner amenable for better cellulases action. In comparison to alkaline methods, physic-chemical methods need less chemical load for the hemicellulose degradation. Biological, physical and LHW pretreatment methods do not require chemicals and are generally considered as mod­erate. Biological methods are generally safe but take longer time periods for lignin removal from the substrates.

Application of lignin generated during alkaline pretreatment has been found im­portant in many products of commercial significance such as resins, adhesives and coatings. Many industries are aiming forward to commercialize the lignin derived products [73]. Pretreatment like dilute acid hydrolysis, auto-hydrolysis and LHW degrade hemicellulose fraction of cell wall into varieties of sugars (xylose, arabi- nose, glucose, mannose and galactose) are used for the production of value-added products like D-xylitol, ethanol, lactic acid, single cell protein etc [2].

A detail economic analysis of each pretreatment strategy considering all the in­volving factors will help to direct research and development efforts in the success of commercialization of bioconversion processes [72, 73]. The renewed interest in sus­tainable development and environment friendly based practices, biotransformation processes are generally preferred over the conventional chemical conversion process. Unfortunately, most pretreatment protocols involve either strong chemicals or harsh physical conditions except bio-delignification. Pretreatment methods autohydrolysis, LHW, steam explosion do not deal with corrosive chemicals however strong physical parameters (high temperature and pressure) are the matter of concern [10]. Biolog­ical pretreatment are the least environmental pollution causing methods but their slow reaction time and loss of significant amount of carbohydrates are the important concerns while selecting them as pretreatment method of choice [13,16]. Biological pretreatment methods have important benefits in a life cycle context also [68].

The raw and pretreated pine sawdust samples were hydrolyzed using enzymes to produce sugar for biofermentation. Effects of reaction time and enzyme dose on the glucose yield, total sugar yield, and weight loss of the raw and pretreated pine sawdust were systematically studied. The results of enzymatic hydrolysis are presented as follows.

Figure 19.2 shows the effect of reaction time on the glucose yield under two differ­ent enzyme doses. The general trends observed in Fig. 19.2a (7.67 FPU) are similar to those in Fig. 19.2b (11.76 FPU). In the first 12 h of operation, the glucose yield increased significantly with time for all samples. After that, the glucose yield leveled off for 12-48 h of reaction. This could be explained by the fact that the enzymatic hydrolysis rate, especially the initial hydrolysis rate, strongly depends on the initial extent of enzyme adsorption and the effectiveness of the adsorbed enzymes [54]. At the beginning of the hydrolysis reaction, there were ideally a maximum number of ac­tive binding sites on the surface of the substrate, and enzymes could be fully absorbed onto the area. At this time, the hydrolysis rate could be considered the fastest. After a certain period of time, the process of enzymes adsorption and desorption reached a saturation point. Additionally, the production of cellobiose and glucose, which have been considered inhibitory to enzymatic hydrolysis, might be accumulated and inhibited enzymatic hydrolysis. As shown in Fig. 19.2, there are obvious differences in the glucose yield among pine sawdust samples pretreated using different methods. From Fig. 19.2, it is clear that the glucose yield increased with an increase in the enzyme dose (Fig. 19.2a vs. b). The raw pine sawdust (untreated) only had 5-6 % glucose yield while pine sawdust treated with (organosolv + ultrasound + NaOH) contributed to nearly 16-18 % glucose yield (Fig. 19.2b), which is more than three times the yield obtained with the raw pine sawdust sample. This can be explained by that the pretreatment removed lignin, loosened the cellulose crystalline structures and increased its accessibility to enzyme. The order of glucose yield positively cor­related to the order of PE and DE, as shown in Fig. 19.4. In other words, a higher PE and DE led to a higher glucose yield. The results suggest that pretreatment did play an important role in enzymatic hydrolysis [50, 55].

Reaction time (h)

Reaction time (h)

Fig. 19.2 Glucose yield from various pretreated pine sawdust samples at 50 °C in sodium citrate solution, pH 4.8 and 100 rpm shaking speed: a 7.67 FPU; b 11.76 FPU

Admittedly, the maximum glucose yield from this work was lower than those reported in some other studies, for example by Sannigrahi et al. [50] and Palonen et al. [55] using different pretreatment methods. Sannigrahi et al. [50] obtained a nearly 70 % of sugar yield when 65 % ethanol/water solution containing 1.1 % sulfuric acid was used as the pretreatment reagent. The addition of acid could lead to

a higher pretreatment efficiency not only for lignin but also for hemicellulose. The higher lignin and hemicellulose removal efficiency led to the higher glucose yield.

The glucose yields achieved in this study for Jack pine sawdust pretreated with the combination of (organosolv + ultrasound + NaOH) methods are lower than those

reported in the work of Zhu et al. [4-6] where very high percentage of cellulose conversion (up to 90 %) was reported for hardwood and softwood samples with combined pretreatment methods of dilute acid and sulfite and disk milling [4-6]. However, compared with the disk milling pretreatment, a mechanical pretreatment approach, the organosolv-based pretreatment approaches may be advantageous in terms of pretreatment energy costs and the overall economics of the process. An acid-free organosolv process can overcome the problems caused by acid-catalyzed pretreatment. It shall be noted that the effect of the organosolv-based pretreatment on cellulose conversion can be greatly improved by combining it with dilute acid pretreatment, as demonstrated by Sannigrahi et al. [50]. Moreover, one of the striking advantages of the organosolv-based pretreatment approaches is that lignin of high purity is generated as a byproduct from the organosolv-based pretreatment processes, which can be utilized as a highly valuable feedstock for the production of phenolic resins and adhesives and biophenols [56].

Figure 19.3a and 19.3b shows the total sugar yield as the function of hydrolysis reaction time. Similar to the results obtained for glucose yield as dicussed above, for the sample pretreated with organo + ultrasound + NaOH, the total sugar yield increased to approximately 27 % in the initial 24 h and then reached the maximum yield of about 30 %. In the next 24 h, there was no significant increase in total sugar yield. The total sugar yields of other pretreated pine sawdust samples were lower but followed the same trend. Interestingly, in contrast to the glucose yield, a higher PE and DE led to a lower total sugar yield (Fig. 19.4). This was probably due to the fact that the higher removal efficiency of hemicellulose at a higher PE resulted in a lower content of hemicellulose in the solid residues, which decreased the formation of non-glucose carbohydrates (such as xylose). From the Fig. 19.4, the effects of enzyme dose on the total sugar yield are less significant (with approximately 5 % differecne in the yield).

19.4 Conclusions

1. Various pretreatment methods (organosolv extraction, followed by ultrasonic and/or NaOH treatment) resulted in a significant removal of lignin and hemi — cellulose.

2. The observations from SEM, FTIR, and XRD clearly demonstrate that the pre­treatment led to disordered cell wall, twisted and exposed inner structure, reduced lignin and hemicelluloses contents, accompanied by increased cellulose content in the solid residues after treatment.

3. Pretreatment of pine sawdust samples had a significant impact on the glucose yield and total sugar yield. The treatment with different methods produced two — tothree-fold increase in the glucose and total sugar yields. The maximum glu­cose and total sugar yields were 5.8 % and 7.1 %, respectively for the raw pine sample, but they were increased to 9.6 % and 30.1 % with organosolv pretreat­ment, 10.7 % and 24.1 % with organosolv + ultrasound pretreatment, 13.6 %

and 26.8 % with organosolv + NaOH pretreatment, and 19.3 % and 22.4 % with organosolv + ultrasound + NaOH pretreatment.

4. In enzymatic hydrolysis of the pretreated pine sawdust, increasing PE and DE led to an increase in glucose yield, but a decrease in total sugar yield.

Acknowledgments The authors are grateful for the financial support from the Ontario Ministry of Energy and Ontario Centers of Excellence (OCE) through the Atikokan Bioenergy Research Center (ABRC) program. The authors would also like to acknowledge Natural Sciences and Engineering Research Council of Canada (NSERC) for the Discovery Grants.

[1] Panwar NL (2011) Biomass for domestic and agro industrial application. Nova Science Pub­lishers, New York

[2] Vassilev V, Baxter D (2012) An overview of the organic and inorganic phase composition of bio-mass. Fuel 94:1

[3] SkoulouV, KantarelisE, Arvelakis S, YangW, ZabaniotouA (2009) Effect of biomass leaching on H2 production, ash and tar behavior during high tem-perature steam gasification (HTSG) process. Int J Hy-drogen Energy 34(14):5666-5673

[4] Kobayashi N, Guilin P, Kobayashi J, Hatano S, Itaya Y, Mori S (2008) A new pulverized biomass utilization technology. Powder Technol 180:272-283

[5] Bergman PCA, Boersma AR, Kiel JHA, Prins MJ, Ptasinski KJ, Janssen FJJG (2004) Torre— faction for entrained flow gasification of biomass. Second world biomass conference. ETA — Florence and WIP-Munich, Rome, pp 679-682

[6] Pels JR, Bergman PCA (2006) proof of prin-ciples—Phase 1, Report ECN, Petten, (NL) ECN-E-06-021

[7] Prins MJ, Ptasinski KJ, Janssen FJJG (2006) More efficient biomass gasification via torrefac — tion. Energy 31:3458-3470

[8] Xiao R, Chen X, Wang F, Yu G (2010) Py-rolysis treatment of biomass for entrained-flow gasifi-cation. Appl Energy 78:1

[9] Okumura Y, Hanaoka T, Sakanishi K (2009) Effect of pyrolysis conditions on gasification reactivity of woody biomass-derived char. Proc Combust Inst 32(2):2013-2020

[10] Rezaiyan J, Nicholas P (2005) Gasifica-tion technologies: a primer for engineers and scien­tists. CRC Press, Boca Raton

[11] Van Den Aarsen F, Beenackers A, Swaaij WV (1985) Wood pyrolysis and carbon dioxide char gasification kinetics in a fluidized bed. Fundamentals of biomass thermochemical conversion. Elsevier, London

[12] Using 500 ^m square wood particles showing average properties with nitrogen as a fluidization medium operating at atmospheric pressure and 773°K. Heating rate estimated at 250° K temperature difference between the gas and particle with the lumped-capacitance method.

[13]Net impact of pretreatment methods can be defined as the overall impact of each pretreatment technology encompassing economics, environmental assessment, and efficiency to improve sugars recovery after enzymatic hydrolysis; +: moderate, ++: considerable, + + +: strong; IL: Ionic liquids, ISMD: in-situ microbial delignification

Mania Abdollahi-Neisiani, Jean-Philippe Laviolette, Rouzbeh Jafari and Jamal Chaouki

Abstract Bioreflnery is the object of significant research and development efforts due to the scarcity of economically viable crude oil, renewable energy source, and its environmental benefits. This has prompted chemical corpo-rations to look for alternative sources of carbon and hydrogen to produce chemicals, biologics, and other products such as biomass and waste matter. Two main reaction pathways are currently explored for biorefinery: thermochemical and biochemical. The thermo­chemical pathway proposes significantly higher reaction rates compared to current biological processes that use non-genetically modified organisms. One of the thermo­chemical pathways for biomass conversion is gasification which is a decomposition of solid fuels at high temperatures and oxygen-lean atmosphere. The successful development of biomass gasification processes requires addressing several critical technical difficulties including biomass diversity, feedstock treatment, gasification mechanism and reactions, gasifier types, and their performances. This chapter re­views key features of biomass gasification as a pretreatment for biorefining which can be used as a practical guide for gasification process. This chapter consists of six sections that include types of biomass for gasification, their properties, and pretreat­ment steps; gasification mechanism and reactions; syngas cleaning and conditioning; different gasifier, their characteristics, and modeling.

Keywords Biomass gasification ■ Pretreatment ■ Gasifier ■ Gas cleaning ■ Tar removal ■ Catalytic gasification

J. Chaouki (H) ■ M. Abdollahi-Neisiani ■ J.-P. Laviolette ■ R. Jafari Department of Chemical Engineering, Ecole Polytechnique de Montreal, C. P. 6079, succ. Centre Ville, Montreal, H3C 3A7, Canada e-mail: jamal. chaouki@polymtl. ca

M. Abdollahi-Neisiani

e-mail: mania. abdollahineisiani@polymtl. ca

J.-P. Laviolette

e-mail: jean-philippe. laviolette@polymtl. ca R. Jafari

e-mail: rouzbeh. jafari@polymtl. ca

Z. Fang (ed.), Pretreatment Techniques for Biofuels and Biorefineries,

Green Energy and Technology,

DOI 10.1007/978-3-642-32735-3_10, © Springer-Verlag Berlin Heidelberg 2013

10.1 Introduction

The beginning of industrial civilization has triggered the frantic use of non-renewable fossil-fuel resources (coal first, followed by oil and gas), which has grown worldwide ever since. Today, the price of fossil fuels is increasing due to depleting “conven­tional” resources, rising demands from developing countries and the establishment of a low-carbon economy. In this context, significant investments and research are focusing on the development of new processes to extract energy and goods from renewable resources, such as biomass.

Biomass is a carbonaceous matter, known as a renewable energy source from living or recently living organisms. Examples include forest residue, agricultural wastes, and even, municipal solid waste. To convert biomass, two main reaction pathways are currently considered: biochemical and thermochemical. Gasification is a thermo-chemical pathway, which transfers the combustion value of the solid fuel to the gas phase whose composition maximizes its chemical energy rather than sensible heat. Syngas, a mixture of CO and H2, is one of the products of the gasification process, which could be used as a fuel or building block for many hydrocarbons. The products derived from syngas can be divided into three categories: (1) chemicals, such as ammonia and methanol; (2) transportation fuels, such as synthetic natural gas and synthetic diesel; (3) and energy feedstock, such as methane. Currently, syngas is produced mainly from fossil fuels; however, there is a growing interest in generating “green chemicals” and “green fuels” from the gasification process.

To successfully design an industrial gasification process, a thorough knowledge of biomass pretreatment, gasification reaction kinetics, and reactor technologies is essential. This chapter discusses the subject of biomass gasification through a detailed review of the scientific and industrial literature.

The equilibrium model predicts the maximum yield when the reactants are in contact for an infinite time without taking into account the reactor type and size [76]. In reality, the products leave the reactor before having the opportunity to reach equilibrium so this type of model only provides the ideal yield. For practical applications, therefore, the use of the kinetic model is more realistic. At higher temperatures (>1,500 K), however, the use of the equilibrium model is more effective. There are two types of equilibrium modeling approaches: (1) stoichiometric or the use of the equilibrium constant; (2) non-stoichiometric or the minimization of Gibbs free energy method. In the stoichiometric model, all the chemical reactions and species involved are considered. For a known reaction mechanism this method predicts the maximum yield of all the products and the possible limiting behavior of the reactor. In the

‘

and Mahinpey developed a model capable of predicting the performance of an at­mospheric fluidized-bed gasifier [83]. They used both built-in Aspen Plus reactor models and external FORTRAN subroutines for hydrodynamics and kinetics to sim­ulate the gasification process. Other authors have worked with Aspen Plus to model the gasification process for coal and biomass. Yan and Rudolph developed a model for a compartmented fluidised-bed coal gasifier process [86], Sudiro et al. modeled the gasification process to obtain synthetic natural gas from petcoke [87]. Abdeloua — hed proposed a compressive model for dual fluidized bed gasifier modeling with ASPEN Plus [88]. A comprehensive review on Biomass gasification simulation also provided by Puig-Arnavat et al. [90] (Fig. 10.3)

The fluidization gas acts as a heating media and promotes mass and heat transfer by inducing a movement on the solids particles as well as removing the volatile from the bed. The BFB can be divided into three phases: (1) the bubble phase (dilute phase—low solids fraction), (2) the emulsion phase (dense phase—high solids fraction) and (3) the cloud phase. The cloud phase is at the interface between the bubble and emulsion phases such that the local solids fraction is between dilute and dense [48]. Several gas-phase (1-phase, multiple-phase, multiple regions etc.) and solid-phase (counter-current back mixing etc.) hydrodynamic models are available

in the scientific literature [49]. These models can be coupled with pyrolysis kinetics (reviewed in Sect. 11.3) to estimate the yield of products. These models have been reviewed in detail in several publications [49].

When designing a BFB pyrolysis system, one could desire to minimize the flu­idization gas flow to facilitate post-pyrolysis separation of the products. However, the superficial gas velocity also affects the reaction rates since it influences the heat and mass transfer. When temperature is sufficiently high, the pyrolysis reaction char­acteristic time becomes shorter than the heating characteristic time, such that heat transfer is the limiting step. In this case, the particles reaction rate (and residence time) is determined by the convection heat transfer to the biomass particles in the fluidized bed; and the convection coefficient can be calculated from the following correlation [52]:

NUbed = = 0.033 Rep 133 for 0.1 < Rep < 100 (11.3)

kg

In Eq. (11.3), the overall fluidized bed Nusselt number (Nubed) is a function of the particle Reynolds number (Rep):

The convection coefficient from Eq. (11.3) is averaged over the bed of particles and it is shown to increase with increasing slip velocity (U-Up). As demonstrated by Avidan and Yerushalmi [53], the slip velocity (U-Up) for BFBs is equal to the superficial gas velocity. This is the case because the average particle velocity is zero: solids circulate within the bed (negligible or limited entrainment) and particles flow co-current or counter-current with the gas. Therefore, the fluidization gas velocity should be sufficiently high to maximize reaction rates and the yield in volatiles: there is therefore a trade-off associated with the selection of the fluidization velocity.

Note that Eq. (11.3) has been shown to yield a more accurate estimation of the convection coefficient than the typical correlations involving the Prandtl number [54]. Furthermore, Eqs. (11.3) and (11.4) should be used by considering the inert (sand) fluidization media, in which case the use of the inert material properties is generally sufficiently accurate (the biomass particles are highly diluted in the inert media). Basic heat transfer estimations with Eq. (11.3) and (11.4)[12] suggest that operating a fluidized bed in the bubbling regime widely promotes fast pyrolysis rather than conventional pyrolysis.

To model biomass pyrolysis in a BFB, less importance is generally given to the bubble characterization since the fluidization gas is inert. The modelling is therefore focused on the dense emulsion phase, which contains the solid biomass particles. If the fluidized bed temperature is uniform and the inert (sand) particles do not leave
the bed, the inert particles temperature can be assumed equal to the gas temperature. In this case, the heat balance strictly involves the biomass particles.

13.4.1 Estimate of Energy Consumption by CNG Vehicles during Crop Production Activities at Model Farm

Based on the results obtained from onsite field testing, we selected Town A and established a regional utilization model that revolved around the BGUS. We evaluated the model’s energy and environment aspects. We used the calculation of the process potential in terms of GHG reduction per year for the environmental assessment.

For our model, we selected a farm in Town A that has a plot with an area of 75 ha. The crop activity was cultivation of pasture grass (cut twice yearly). In this farm’s system of cultivating mid-moisture grass silage, trucks are used for laying fertilizer, harvesting grass, and spreading soil improvement materials. The trucks’ distance of movement were measured and collected using a geographic information system (GIS). The total distance of 4-t trucks involved in the production of pasture grass at the farm was 3,513 km/yr. The amount of diesel fuel consumed was 462.2 L/yr, and the amount of refined biogas consumed was 462.2 Nm3/yr.

13.4.2 Players in Regional Utilization Model Revolving around BGUS

The players that are studied in the utilization model (subjects playing roles) are: (1) the farmer with the biogas plant installation, (2) the biogas vendor, and (3) con­sumers of the refined biogas. The farmer with biogas plant installation manages the biogas plant and is responsible for the refining of surplus gas and compression; that is, he is responsible up to the point of storing the refined gas in storage canisters. The biogas vendor is responsible for filling cylinders with refined biogas, deliver­ing, installing, and recovering the cylinders, as well as modifying residential gas equipment. Consumers consume the gas.

The utilization model is centered on equipment that can be easily modified and introduced; this equipment was tested by onsite field testing.

The areas of use were established as “inside the farm production system” and “adjacent area and residence of the farm production system”. The equipment “inside the farm production system” that consumed the refined biogas produced by the RCF facility included the farmer’s residence as well as the farm operations. Otherwise, the gas vendor delivered cylinders filled with refined gas to the customers. The routes utilized the existing infrastructure.