Lignocellulosic ethanol: Technology design and its impact on process efficiency Leona Paulov´a, Petra Pat´akov´a, Barbora Bransk´a, Mojm´ır Rychtera, Karel Melzoch PII: DOI: Reference:
S0734-9750(14)00189-X doi: 10.1016/j.biotechadv.2014.12.002 JBA 6872
To appear in:
Biotechnology Advances
Please cite this article as: Paulov´ a Leona, Pat´ akov´a Petra, Bransk´a Barbora, Rychtera Mojm´ır, Melzoch Karel, Lignocellulosic ethanol: Technology design and its impact on process efficiency, Biotechnology Advances (2014), doi: 10.1016/j.biotechadv.2014.12.002
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ACCEPTED MANUSCRIPT Lignocellulosic ethanol: technology design and its impact on process efficiency
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Leona Paulová*, Petra Patáková, Barbora Branská, Mojmír Rychtera and Karel Melzoch Department of Biotechnology, Institute of Chemical Technology Prague, Technicka 5, CZ16628 Prague 6, Czech Republic
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* Corresponding author at: Institute of Chemical Technology Prague, Technicka 5, CZ16628 Prague 6, Czech Republic. Tel.: +420220445022, fax: +420224311082 E-mail address: [email protected]
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Abstract This review provides current information on the production of ethanol from lignocellulosic biomass, with the main focus on relationships between process design and efficiency, expressed as ethanol concentration, yield and productivity. In spite of unquestionable advantages of lignocellulosic biomass as a feedstock for ethanol production (availability, price, non-competitiveness with food, waste material), many technological bottlenecks hinder its wide industrial application and competitiveness with 1st generation ethanol production. Among the main technological challenges are the recalcitrant structure of the material, and thus the need for extensive pretreatment (usually physico-chemical followed by enzymatic hydrolysis) to yield fermentable sugars, and a relatively low concentration of monosaccharides in the medium that hinder the achievement of ethanol concentrations comparable with those obtained using 1st generation feedstocks (e.g. corn or molasses). The presence of both pentose and hexose sugars in the fermentation broth, the price of cellulolytic enzymes, and the presence of toxic compounds that can inhibit cellulolytic enzymes and microbial producers of ethanol are major issues. In this review, different process configurations of the main technological steps (enzymatic hydrolysis, fermentation of hexose/and or pentose sugars) are discussed and their efficiencies are compared. The main features, benefits and drawbacks of simultaneous saccharification and fermentation (SSF), simultaneous saccharification and fermentation with delayed inoculation (dSSF), consolidated bioprocesses (CBP) combining production of cellulolytic enzymes, hydrolysis of biomass and fermentation into one step, together with an approach combining utilization of both pentose and hexose sugars are discussed and compared with separate hydrolysis and fermentation (SHF) processes. The impact of individual technological steps on final process efficiency is emphasized and the potential for use of immobilized biocatalysts is considered. Keywords: lignocellulose, ethanol, pretreatment, enzymatic hydrolysis, fermentation, process configuration, SHF, SSF, CBP, pentose, hexose, immobilization, yield, productivity Content 1. Introduction 2. Process configuration and its impact on ethanol yield and productivity 2.1 Separated hydrolysis and fermentation 2.2 Simultaneous saccharification and fermentation 2.3 Simultaneous saccharification with delayed inoculation 2.4 Co-fermentation of hexose and pentose sugars 2.4.1. Glucose and xylose co-fermentation 2.4.2. Co-fermentation of different saccharide mixtures 2.4.3. Microbial co-culture and sequential fermentation of saccharides
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Consolidated bioprocessing Use of immobilized biocatalysts (enzymes and cells) Immobilization of cellulolytic enzymes Immobilization of microbial cells Conclusion Acknowledgement References
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2.5 2.6 2.6.1. 2.6.2. 3. 4. 5.
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1. Introduction Although production of ethanol from lignocellulosic materials (e.g. wood, agricultural residues, energy crops, herbaceous plants etc.) has many advantages (e.g. availability, low price if not transported long distances, non-competitiveness with the food chain, often regarded as waste material) the process (2nd generation ethanol) is more complicated compared with 1st generation ethanol production and involves many technical and economic challenges; it is therefore only carried out on pilot/demonstration scales in Europe and most commercial plants have been built during the last decade (Larsen et al., 2012). In 2009, a cellulosic ethanol plant using Ibicon technology was constructed in Kaundborg, Denmark, to produce 5 400 m3 of ethanol per year. In 2013 the plant was rebuilt to provide mixed fermentation of hexose and pentose sugars originating from wheat straw (Dong Energy, 2014). In 2010, a plant producing ethanol from various biomasses, particularly from straw and bagasse, was opened in Oulu, Finland (Commercial cellulosic ethanol projects, 2014). In June 2013, the Abengoa demonstration plant was inaugurated in Salamanca, Spain, with an annual capacity of 15 000 m3 of bioethanol made from municipal solid waste. Currently the world´s largest 2nd generation biofuel production plant, with an annual capacity of 75 000 m3 of bioethanol produced from wheat and rice straw, was opened in October 2013, in Italy (Cellulosic ethanol (CE), 2014). Although many combinations of individual technological steps have been tested, the principle of producing ethanol from lignocellulosic feedstock is the same and fundamental steps should be followed to enable successful conversion of cellulose (and/or hemicellulose) to ethanol (Cardona and Sánchez, 2007; Gupta et al., 2009; Lin and Tanaka, 2006; Paulová et al., 2013 ). Generally, the process of producing 2nd generation ethanol consists of the following operations: reduction of particle size (usually by milling or cutting), liberation of cellulose and hemicellulose from the lignin-protected complex, carried out by different pretreatment methods (usually a combination of high pressure, temperature and the addition of chemicals, although some innovative methods such as treatment with ionic liquids have been tested) , the release of monomeric sugars from cellulosic and hemicellulosic polymeric chains, and their fermentation into ethanol (Fig. 1). These operations can be carried out consecutively, as in case of separate hydrolysis and fermentation (SHF) processes, fully or partly simultaneously, as in case of simple simultaneous (SSF) processes or simultaneous processes with delayed inoculation (dSSF), or fully consolidated as in the case of the consolidated bioprocessing (CBP) design. These will be discussed in the following chapters. Regardless of process design, one of the main drawbacks of these technologies is the low ethanol concentration produced from lignocellulose. This is caused mainly by the low concentration of sugars available for fermentation because the character of this feedstock does not practically allow for an increase in fermentable solids in batch to levels that would provide similar sugar concentrations as used for 1st generation feedstocks (e.g. corn or molasses). Many technical problems (high viscosity, low amount of free water due to its absorption into the biomass, high content of inhibitors, problems with mixing, nutrient levels, heat, mass transport, etc.) contribute to this (Modenbach and Nokes 2013).
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Second generation ethanol technologies are complicated (Eggert and Greaker, 2014; Lin and Tanaka; 2006; Taherzadeh and Karimi, 2007; Viikari et al., 2012) and their efficiencies can be influenced by many factors such as the type of lignocellulosic feedstock, pretreatment methods, use of or omission of a detoxification step, the type and amount of cellulolytic enzymes, the microorganisms used and their robustness (including compatibility with enzymatic cocktails in simultaneous processes), cultivation conditions (configuration, temperature, pH, concentration of solids, type and amount of nutrient addition etc.), and type of bioreactor (principle of mixing, type of operation). Therefore to find an optimum combination of all variables for a particular feedstock is challenging. To obtain optimum values of all parameters, different optimization approaches such as response surface methodology are often used (for an example, see Jaisamut et al., 2013). In this review, the main features, advantages and drawbacks of the common process configurations such as SHF, SSF, dSSF and CBP are discussed and compared with processes in which utilization of both hexose and pentose sugars are combined. Technologies exploiting immobilized biocatalysts are also described. Individual process designs are compared regarding parameters that play important roles in process efficiency such as final ethanol concentration, its yield from substrate and productivity. All process configurations have some advantages and drawbacks (which are sometimes contradictory), therefore several aspects must be considered in order to select the best combination of unit operations that will lead to efficient production of ethanol, complete use of feedstock and reasonable utilization of coproducts and wastes to ensure an economically acceptable technology for any particular feedstock.
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2.1. Separate hydrolysis and fermentation Separate hydrolysis and fermentation, (SHF) is a process consisting of two consecutive operations; firstly, cellulose, contained in a solid phase of pretreated lignocellulosic material, is hydrolysed to glucose using cellulolytic enzymes (usually in combination with other sugars released from hemicellulose). Released glucose (which is usually in a mixture with other hexose and/or pentose sugars, depending on the method of pretreatment and medium preparation) is then converted into ethanol by a selected microbial strain in the following fermentation steps (Fig. 2). Both processes (i.e. enzymatic hydrolysis and fermentation) can be carried out under optimal conditions (temperature, pH, nutrient composition, solid loading), which is probably the main advantage of this configuration because the temperature optimum of each process differs considerably. The optimum temperature for most cellulolytic enzymes is usually around 50 °C while most microbial strains employed for ethanol production (traditional large scale ethanol producers are the yeast Saccharomyces cerevisiae and the bacterium Zymomonas mobilis, although many other strains have been employed in different processes, as described later), produce ethanol most efficiently at 28-37 °C. Moreover, the performance of cellulolytic enzymes is not influenced by the presence of ethanol, as is the case for simultaneous process arrangements, and medium viscosity is considerably reduced prior to fermentation, having positive effects on microbial strain viability, efficient mixing, and nutrient and heat transfers; this is advantageous mainly for processes carried out with a high solid content. On the other hand, inhibition of cellulolytic enzyme activity by increasing concentrations of released glucose (or cellobiose), (end product inhibition), slows the rate of cellulose hydrolysis and is usually described as the main drawback of this process configuration (Ask et al., 2012; Gupta et al., 2009; Tomás-Pejó et al., 2009). Although this effect can be partly minimized by supplementation of enzymatic cocktails with ß-glucosidase to increase the rate of cellobiose decomposition, it remains as the main problem of SHF. Moreover, for high xylan content feedstocks, further inhibition of cellulolytic enzymes by xylan degradation products is problematic (Qing et al., 2010).
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Many authors also emphasize the increased investment needed for SHF due to the use of more than one vessel (e.g. Ask et al., 2012), although it is not always necessary because in batch mode, both processes can be carried out consecutively in one bioreactor. Many processes employing SHF for ethanol production have been reported over the last few decades (Chen Y. et al., 2014; Gupta et al., 2009; Hansen et al., 2014), however, to improve competitiveness of 2nd generation ethanol production, ethanol concentrations around 100 g/l are required; this can be achieved by increased substrate loading. However, the amount of solid in the broth considerably affects both enzymatic hydrolysis and fermentation (Chen et al., 2007), and thus the outcome of the process. As shown by Lopéz-Lináres et al. (2014), the main drawback of SHF performed under high solid loading is reduced activity of cellulolytic enzymes, while with simultaneous processes (as discussed later), low microbial strain viability becomes a problem. For high solid SHF processes, typically higher concentrations of glucose are released during enzymatic hydrolysis (which is desired) but the cellulose hydrolysis rate and ethanol yield are usually lower compared to processes performed with a lower solid content (Uppugundla et al., 2014). As demonstrated by Lopéz-Lináres et al. (2014) for enzymatic hydrolysis of acid pretreated rapeseed straw in SHF, the glucose concentration increased roughly linearly with increasing solid content but both cellulose hydrolysis rate and its conversion into glucose were reduced. The authors attributed this effect to lower enzyme binding capacities caused by diffusional limitations in medium containing a high proportion of solids rather than to the loss of enzymatic activity due to endproduct inhibition. Some authors (e.g. Hoyer et al., 2010) recommend the continuous or intermittent feeding of cellulolytic enzymes, together with substrate, to improve the conversion of cellulose in high solid operations and to compensate for the non-productive binding of enzymes. However, the economics of such an approach should be carefully considered before being implemented. The use of various surfactants (e.g. Tweens, polyethene glycols or ionic liquids) to reduce enzyme attachment to lignin is another approach for improving the rate of cellulose hydrolysis and has been reported in many papers with varying successes (Gupta et al., 2009; Zhang et al., 2013), probably because the efficiency of this method greatly depends on the type of biomass and pretreatment methods prior to enzymatic hydrolysis. On the other hand, microbial strain performance in the fermentation phase of high solid SHF is almost unaffected by high solid medium, particularly because the initial broth viscosity is considerably reduced by the previous enzymatic step (Lópéz-Linares et al., 2014; Stenberg et al., 2000). The sensitivity of yeast cells to inhibition is thus often described as being lower in SHF processes compared to those combining enzymatic hydrolysis and fermentation in one step. Among the many factors that can affect a process result is also the composition of the enzyme cocktail used for cellulose hydrolysis. As reported by Canella and Jorgensen (2014), with the new generation of cellulolytic enzymes, high solid SHF processes are superior to simultaneous ones regarding ethanol yield while the converse is true for older enzyme cocktails. Moreover, as demonstrated by Uppungundla et al. (2014), the optimum composition of enzyme cocktails and dosing regime differs for various types of biomass and even for the same type of biomass pretreated using different methods. The same is true for supplementation of culture broth with nutrients; medium prepared from hydrolysates originating from the same biomass but pretreated using different methods require different nutrient supplementation because of differential nutrient loss during pretreatment and subsequent washing. There are many examples of SHF processes carried out either with low solid or high solid content media prepared from various types of biomass that were pretreated using numerous methods. A brief overview of selected SHF processes reported mainly over the last two years
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is shown in Tab. I in order to compare ethanol yield, final ethanol concentration and productivity with other processes that are described later in this review. Although the ethanol yield from glucose is often very high and close to theoretical, the final concentration of ethanol is far below the values achieved with 1st generation substrates (last row of Tab. IV), mainly due to the lower yield of glucose from cellulose, which is especially true for high solid processes. An exception is that reported by Canella and Jorgensen (2014), where almost 95% conversion of cellulose was achieved and about 60 g/l of ethanol was obtained from hydrothermally pretreated wheat straw.
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2.2. Simultaneous saccharification and fermentation The simultaneous saccharification and fermentation (SSF) process represents one of several modifications of the classical SHF process for production of cellulosic ethanol. This concept was first described in a patent by Gauss et al. (1976) and the term simultaneous saccharification and fermentation was first used in 1977 by the same working group (Takagi et al., 1977). The SSF process integrates enzymatic hydrolysis of pretreated (mechanically, physico-chemically, etc) lignocellulosic material with fermentation of released glucose into one step, carried out at the same time in one vessel (Fig. 3). Since the glucose released from cellulose in the enzymatic reaction is immediately and rapidly consumed by the microbial strain producing ethanol (and thus does not accumulate in the culture broth), elimination of end-product inhibition of cellulolytic enzymes are reported as the main advantages of this process configuration. The influence of glucose accumulation on the performance of cellulolytic enzymes was demonstrated in the model developed by Oh et al. (2000), who found that the initial cellulose hydrolysis rate decreased by 20 and 60% due to enzyme inhibition at glucose concentrations of 5 and 20 g/l, respectively. Elimination of glucose accumulation thus enhances the rate of cellulose hydrolysis and therefore shortens the process time (Cardona and Sánchez, 2007; Olofsson et al., 2008). A reduction in investment costs (both processes run in the same vessel) and a lower risk of contamination (glucose is released in the presence of ethanol) are frequently described as other positive attributes of this process (e.g. Hasunuma and Kondo, 2012), although the effect of ethanol on the activities of cellulolytic enzymes is usually neglected in many papers. According to Oh et al. (2000), inhibition of cellulases by ethanol is less than that caused by glucose (or cellobiose), although this statement was not supported by data. In addition to the potential sensitivity of enzymes to released ethanol, low ethanol productivity in the early stages of SSF, caused by carbon limitation due to glucose deficiency, is another problem associated with this process (Paulová et al., 2014). However, the main drawback of SSF is difference between the temperature optimum of cellulolytic enzymes (usually 45-50 °C) and that of the fermenting microorganisms (mostly 28-37 °C), which affects the efficiency of both processes. This discrepancy is usually solved by lowering the temperature of hydrolysis to be compatible with the temperature optimum for the fermenting microorganism. Alternatively, a compromise between the optimal temperatures of both processes, which is usually around 37 °C, is applied. Unfortunately, the first approach affects the rate of glucose release from cellulose and can cause carbon limitation for fermentation, while the second approach affects the activity of cellulolytic enzymes and slows down the metabolism of the microbial strain; both approaches result in reduced productivity and often a lower final concentration of ethanol. As reported elsewhere, both cellulose hydrolysis rate and conversion into glucose are considerably affected by temperatures below the enzyme optimum; the rate of hydrolysis of pure cellulose was reduced by 60% if the temperature was lowered from 50 °C to 30 °C (Oh et al., 2000), while conversion of cellulose from acid pretreated wheat straw dropped by 40% if the process was carried out at 30°C instead of at 45 °C (Paulová et al., 2014). On the other hand, work at lower temperatures often means a higher
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tolerance of microorganisms to inhibitors (Olofsson et al., 2008) and ethanol (Cardona and Sánchez, 2007). Therefore, SSF carried out at enzyme suboptimal temperatures eliminates enzyme inhibition by glucose but slows the hydrolysis rate. Therefore, careful optimization of process conditions must be done to reach a compromise between the advantages and disadvantages of this process configuration. Another approach is ethanol production at elevated temperatures by employing thermotolerant ethanol producing microbial strains. Reduced demands for cooling and partial continuous removal of ethanol from the fermentation broth by evaporation, in addition to faster enzymatic hydrolysis carried out at (or close to) the optimum for cellulolytic enzymes, are described as benefits of this approach (Hansunuma and Kondo, 2012). Among wild species, Kluyveromyces marxianus is a good candidate for an SSF process carried out at an elevated temperature because many strains can efficiently produce ethanol at 38-45 °C and are also able to utilize arabinose, galactose, mannose or xylose, i.e. sugars present in the lignocellulosic medium. Strain IMB, isolated from a distillery in India, is reported (Suryawati et al., 2008) to be promising due to its ability to grow at temperatures up to 50 °C and with an ethanol tolerance of up to 9.5%. However, in practice, only small differences in ethanol concentration and productivity were observed between this strain and S. cerevisiae in an SSF process carried out at 45°C and 37 °C, respectively. This was probably due to the combined effects of high temperature, ethanol concentration and decreasing pH, which affected cell viability. Other authors (Kádár et al., 2004) did not observe any significant difference between S. cerevisiae and K. marxianus regarding ethanol yield in an SSF process, both values being in the range of 0.31-0.34 g/g. Some thermotolerant strains of S. cerevisiae that can be exploited for cellulosic ethanol production e.g. a high-temperature growth phenotype (Htg+) exhibiting increased resistance to temperature, ethanol and osmotic pressure, have been recently isolated and characterized (Shahsavarani et al., 2012). Some genetically engineered strains of Hansenula polymorpha or Candida glabrata also have potential for SSF carried out at higher temperatures. Unfortunately, although a good ethanol yield is usually achieved in SSF, the final ethanol concentration and productivity is still low compared with starch- or sugar-based processes, caused mainly by the lower initial concentration of fermentable sugars in the broth. In contrast to media prepared from corn or molasses, the pre-concentration of pretreated lignocellulosic material is more complicated due to the character of this substrate. High substrate loadings, which are inevitable for achieving ethanol concentrations similar to that of 1st generation processes, are hardly achievable due to mixing and pumping problems and mass transfer limitations caused by the high viscosity of the medium and its toxicity due to the preconcentration of inhibitors. With increasing substrate loading (usually above 7- 10% of WIS – water insoluble solids), ethanol yields tend to decrease (Kim et al., 2013; Olofsson et al., 2008; Paulová et al., 2014; Tomás-Pejó et al., 2009). Total inhibition of yeast caused by a combination of high osmotic pressure, low water content and above optimum temperature occurred at 20% solids using acid pretreated rapeseed straw (López-Linares et al., 2014). Although glucose inhibition of cellulases in low solid SSF processes is usually eliminated, at high solids content, enzyme activity is also affected by the high concentration of inhibitors (this is mainly true for acid pretreated materials); as reported by Lopéz-Linares et al. (2014) the conversion of cellulose to glucose was reduced from 71 to 61% if the solid content of acid pretreated rapeseed straw increased from 7.5 to 20%. On the other hand, a high solid content is inevitable for process economy; 40 g/l ethanol is considered as the lower limit for economic distillation (Wingren et al., 2003) and a solid content of 16-20% is needed, assuming an average cellulose content of 40-50% w/v. Integration of a detoxification step (usually washing with water or other solvents) enables an increased solid content in fermentation because washing removes inhibitors, but is counter-productive for glucose content (glucose released in
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prehydrolysis is also washed out). However, recently published data on an SSF process using formalin-pretreated oil palm empty fruit bunches, subsequently treated with lime and washed several times showed very good results. The ethanol concentration increased from 23.0 to 83.6 g/l along with increasing solid content from 5 to 20% (Cui et al., 2014); moreover the yield was only slightly affected by high solid loading. Although the ethanol concentration achieved was close to that for sugar- or starch-based processes, this result is unique, as seen in Tab.II. Fed-batch addition of pretreated material is another approach to increase sugar concentrations in the process. It allows the dose of substrate to be spread over a longer time period and thus to stepwise decrease viscosity in the bioreactor compared to batch mode. The initial batch is liquefied by the action of cellulolytic enzymes until the next addition of substrate and the concentration of inhibitors is kept low due to their microbial transformation to less harmful compounds during fermentation and by dilution. Many feeding strategies have been reported for SSF processes, some of them based on dynamic or fuzzy models (Chen and Qiu, 2010), in order to define an optimal feeding rate. As shown by Ruiz et al. (2006), the result of SSF is influenced not only by process arrangement and solid loading, but also by the method of lignocellulose pretreatment – for olive tree wood, steam explosion followed by hot alkaline peroxide treatment yielded increased ethanol with elevated pretreatment temperature, however the enzymatic hydrolysis yield and ethanol concentration dropped if the temperature exceeded 220 °C. The result of SSF (i.e. ethanol concentration) is also influenced by the amount of enzyme used. As demonstrated by Kim et al. (2013), higher enzyme concentrations can increase the conversion of cellulose into glucose, and consequently, the concentration of ethanol, but process economics should be kept in mind when calculating enzyme dose and process configuration. Fed-batch SSF using a combined feed of substrate, enzymes and yeast adapted to inhibitors enhanced cell viability in a high solids process (20% WIS) and achieve 40 g/l ethanol (Koopram and Olsson, 2014), although the economic balance of cost of additional operations (continuous yeast propagation, high amount of enzymes fed into the process) was not provided. The performance of cellulolytic enzymes can be also enhanced by addition of polyethylene glycol, which helps to reduce the adsorption of enzymes to lignin. However, as noted by Canella and Jorgensen (2014), the economic feasibility of this approach is doubtful. Mathematical modelling and computer simulation can be exploited to maximize ethanol production in SSF, as demonstrated by Oh et al. (2000), or by Mutturi and Lidén (2014) who developed the nonisothermal SSF process following a changing temperature profile during SSF. However, the final ethanol concentration remained low (14.87 g/l and 13.6 g/l, respectively). This indicates that several parameters (optimal pretreatment, fed-batch operation, optimum (as high as possible) substrate loading, appropriate enzyme dosing, suitable microorganism, optimum cultivation condition,…) should be combined to achieve higher ethanol concentrations at a reasonable process price. As seen from Tab. II, where results published within the last two years, together with selected processes published previously are compared (only SSF working with natural substrates are listed while papers dealing with carboxymethylcellulose, Avicel or filter paper are omitted), the yield of ethanol was usually lower compared to SHF processes and the concentration of ethanol achieved was usually below 40 g/l, which is at the limit for economic distillation. The exceptional and promising result with formalin pretreated oil palm empty bunches in an SSF process, where almost 85 g/l of ethanol were achieved and productivity was acceptible, warrants further research. 2.3. Simultaneous saccharification with delayed inoculation
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Several of the problems of SSF can be eliminated, or at least reduced, by integration of a prehydrolysis step into the SSF process. Although different names of this process have been used, e.g. semi-simultaneous saccharification and fermentation, abbreviated as SSSF or S-SSF (Goncalves et al., 2014; Zhang et al., 2014; Li et al., 2014), prehydrolysis and simultaneous saccharification and fermentation, PSSF (Lopéz-Linares et al., 2014), presaccharification of simultaneous saccharification and fermentation, P-SSF (Tan et al., 2013), simultaneous saccharification and fermentation with delayed inoculation, dSSF (Paulová et al., 2014), liquefaction plus simultaneous saccharification and fermentation, L+SSF (Castro et al., 2014) or non-isothermal simultaneous saccharification and fermentation, NSSF (Mutturi and Lidén, 2014), the principle is essentially the same: the broth prepared from chemically or physically pretreated biomass is firstly prehydrolysed with cellulases at the optimum temperature (4555°C depending on the enzyme mixture) then cooled to the temperature meeting the SSF condition, and immediately inoculated without enzymes being inactivated. The main purpose of this process is to overcome the discrepancy in the temperature optima for enzymes and microorganisms and thus increase the rate of cellulose hydrolysis and its conversion into glucose in the early stages of the process, to eliminate glucose limitation at the beginning of SSF (and thus increase the rate of ethanol production), and decrease the viscosity of material prior to inoculation (which is advantageous mainly for processes with high solid loadings). Theoretically, this method combines the advantages of both SHF and SSF processes – the rate of enzymatic hydrolysis is not reduced by a suboptimal temperature, released glucose does not accumulate above the critical value that would entrain end product inhibition, and the rate of ethanol production is not limited by a low concentration of carbon source. Although many papers using this method have been published recently, the results are hard to compare (Tab. III) because the success rate is affected by many factors such as type of material, method of pretreatment, composition of enzyme cocktail and dose, solids content, conditions for the subsequent SSF process (temperature, pH, type of microorganism and its sensitivity to toxic compounds), its configuration (batch, fed-batch) and especially in this case, by the length of prehydrolysis. Although the duration of prehydrolysis is a factor that affects yield, productivity and final ethanol concentration, and thus consequently the final evaluation of the process, it is rarely optimized, as seen from many studies where 24 h of prehydrolysis were applied without any clear relationship with the main process parameters (Tab. III). Because of this (and also other effects such as type of material, enzymatic mixture, etc.), some studies (e.g. Mesa et al., 2011; Huang et al., 2014; Zhang et al., 2014) showed that SSF with delayed inoculation was superior to SSF and SHF, while others (e.g. Lopéz-Linares et al. 2014) did not see any improvement. As reported by Paulová et al. (2014), the duration of the presaccharification period considerably influences productivity of the process; although ethanol yield and its final concentration did not differ, 12 h presaccharification resulted in 2.3 times increased productivity of ethanol from acid pretreated wheat straw compared to SSF (because the length of the process was shortened by 60%) whereas lengthening the presaccharification period to 24 h (which is the time used in most studies) resulted in a 25% loss in productivity and SHF was, in this case, superior to dSSF. Although other authors have also reported that ethanol yields in SSF with presaccharification did not dramatically change compared to SSF alone (Manzares et al., 2011), Hoyer et al. (2014), reported that the prehydrolysis period especially influenced ethanol yield, with 32.6%, 32.7% and 58.3% of theoretical being achieved for 4, 8 and 22 h prehydrolysis, respectively; all yields were superior to the simple SSF process. As shown in Table III, the presaccharification period cannot be generalized because it differs for each combination of substrates, their concentrations, the type of pretreatment and the microbial strain. As discussed for other process configurations, ethanol concentrations exceeding the limit of 40 g/l are rather exceptional and are achieved mainly on easily manipulated substrates such as
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waste paper or paper sludge dissolved in buffer. An ethanol concentration of 91.5 g/l, which is comparable with 1st generation bioethanol, was achieved by a combination of 12 h presaccharification and 2h of sequential addition of both paper sludge and enzymes in a fedbatch SSF process lasting for more than 400 h (Elliston et al., 2013). Although a high concentration of ethanol was achieved, the profitability of this process due to repeated enzyme addition is doubtful and the productivity was low due to the length of the process. Generally, productivity of SSF with delayed inoculation, as reported in the literature, is often overestimated because it is calculated from the second part of the process (SSF) and the presaccharification period is omitted. Data presented in Table III has thus been recalculated to include the real duration of the process. Similarly to other processes discussed in this review, the amount of substrate should be carefully calculated because it can considerably influence process efficiency due to the “solid effect”, where the conversion of cellulose and the ethanol concentration decrease as the solid content increases (Kristensen et al., 2009); e.g. as shown by Lopéz-Linares et al. (2014), increased solid content from 7.5 to 15% achieved 85% more glucose in the 24 h presaccharification step and the final ethanol concentration was increased by 80%, while further solid addition (20% WIS) negatively affected both the conversion of cellulose and the ethanol yield, and practically did not improve the volume of ethanol produced. Similarly, Huang et al. (2014) reported a significant decrease in ethanol yield if the substrate (hydrothermally pretreated pomelo peel) was preconcentrated in batch from 5 to 14% WIS, although despite the worsened yield, they more than doubled the final concentration of ethanol (9.3 g/l and 20.8 g/l for 5 and 14% WIS, respectively). As described by Xiros and Olsson (2014), in the case of a process with a high solid content, many parameters must be combined and optimized for any particular configuration to achieve an optimum result; in SSF with a 24 h presaccharification step, the best results were achieved when detoxification with a reducing agent was applied prior to the process, while in SHF, nutrient supplementation worked better than detoxification. Among modifications of the classical SSF, the process of employing simultaneous saccharification, filtration and fermentation (SSFF) should be mentioned (Ishola et al., 2013). In this process, enzymatic hydrolysis is carried out under optimum enzyme conditions. Broth is then pumped through a membrane into the bioreactor where fermentation takes place and is then recycled back to the hydrolysis vessel while yeast cells are retained in the bioreactor. This permits reuse of the yeast and at the same time achieves comparable results to SSF, although the main problem with this process is clogging of the cross-flow membrane. A similar concept was demonstrated by Viola et al. (2013), who used a two chamber bioreactor to combine the advantages of SHF and SSF processes. In individual parts of the bioreactor, divided by a porous barrier, enzymatic hydrolysis and fermentation are carried out under optimal conditions, enabling a 20% increase in ethanol yield compared to classical SSF and keeps lignin separated from the fermentation broth. However, the final concentration of ethanol achieved in this process is far below the 40 g/l that is considered a lower limit for economic distillation (Tab. III). 3.4 Co-fermentation of hexose and pentose sugars Lignocellulose decomposition/digestion, independent of the material origins and method of degradation, results in a mixture of hexoses (mainly glucose) and pentoses (mostly xylose but also arabinose). An example of such a mixture of saccharides is spent sulfite liquor (SSL), a common waste stream from sulfite wood processing to pulp. SSL, which can usually be included in several modified processes, contains a mixture of fermentable saccharides originating from cellulose and hemicellulose i.e. glucose, galactose, mannose, xylose and arabinose, where the total saccharide concentration does not exceed 50 g/l. In addition, SSL
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contains acids, alcohols and free and bound sulfur dioxide, which can hamper its use. Therefore SSL is often detoxified by different methods such as overliming, SO2 stripping with steam, or precipitation of sulfates. When S.cerevisiae was used for SSL fermentation (Novy et al., 2013), the final ethanol concentration, maximum theoretical yield and productivity, were 20 g/l, 86% and 0.1 g/l/h, respectively. These values, with the exception of productivity, are very similar to those (20 g/l, 88% and 0.44 g/l/h) obtained using Pichia stipitis (Nigam 2001) and probably represent the maximum achievable values considering the initial saccharide concentration of the SSL. More detailed information on ethanol produced from SSL can be found in a recent review (Pereira et al., 2013).
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3.4.1 Glucose and xylose co-fermentation The xylose content in lignocellulose hydrolysates varies according to the condition and origin of the material (a high xylose content can be found especially in birch wood). Traditional ethanol producers, S. cerevisiae and Z. mobilis prefer hexose saccharides and most of their strains do not consume pentoses at all. Efficient adaptation or modification of S.cerevisiae for xylose fermentation includes the following steps: (1) xylose uptake and prevention of carbon catabolite repression (CCR) caused by glucose If genes for xylose metabolism are incorporated into either S. cerevisiae or Z. mobilis, both microorganisms still more rapidly consume glucose from a mixture of glucose and xylose because of the absence/low affinity of a xylose transporter protein in the cells (Kim et al., 2010). To overcome this problem and to achieve simultaneous consumption of hexose and pentose saccharides, it is desirable to keep the glucose concentration low by maintaining a controlled level of cellulases in the SSF system (Olofsson et al., 2010). Another approach is to insert and express the gene for P. stipitis xylose transporter SUT1 in a genetically modified, xylose-assimilating strain of S. cerevisiae. This approach resulted in successful cofermentation of a glucose/xylose mixture (50 + 50 g/l) and an ethanol concentration of 41 g/l, productivity of 0.7 g/l/h and 82% of maximum theoretical yield were achieved (Katahira et al., 2008). However, this is probably a rare example of successful glucose/xylose cofermentation to ethanol because in other cases, where different xylose transporters or different yeast strains were used (Runquist et al., 2010; Moon et al., 2013; Tanino et al., 2012), a maximum ethanol concentration of 10 g/l was obtained. (2) expression of xylose isomerase or biotransformation of xylose to xylulose The first step in xylose metabolism by xylose-utilizing yeasts is the gradual transformation of xylose to xylulose through xylitol, by xylose reductase and xylitol dehydrogenase. However, these enzymes are normally absent in S.cerevisiae and the main issue preventing use of these enzymes in a genetically modified yeast is that they both function under aerobic conditions due to the formation of NADH, which is continuously removed by oxidation. Modification of S.cerevisiae by transformation and expression of xylose isomerase from the anaerobic fungus Piromyces sp. has therefore become standard , resulting in anaerobic xylose utilization (Kuyper et al., 2004; Kuyper et al., 2005). In addition, xylose can be transformed to xylulose in vitro by addition of xylose isomerase. This process was proposed in 1981 (Gong et al., 1981a) and achieved 20 g/l of ethanol from 120 g/l of xylose, which was partially converted to xylulose by addition of Sweetzyme Q. However, a portion of xylose was transformed to xylitol (this is more likely under oxidative conditions but can occur even during fermentation). This method has been modified recently (Yuan et al., 2011) when the authors used commercially available S.cerevisiae strains in high loads (up to 200 g/l of yeast biomass) for fermentation of glucose/xylulose mixtures, with the addition of sodium azide as a respiratory inhibitor. In this way, up to 73 g/l of ethanol with 81% theoretical yield was obtained. Nevertheless, such a high yeast dose is not applicable in a scaled-up process.
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In addition to genetic modification, further progress with modified S.cerevisiae strains can be achieved by evolution or adaptation techniques (Novy et al., 2013; Novy et al., 2014). An effective way to modify Z. mobilis for glucose/xylose utilization was demonstrated by Zhang et al. (1995), who combined the original Entner-Doudoroff pathway with the non oxidative part of the pentose phosphate pathway. By this method, 25 g/l of ethanol with a productivity of 0.8 g/l/h and 95% of theoretical maximum yield was achieved from a glucose /xylose (1:1) mixture. Different adaptation approaches (Agrawal et al., 2011; Mohagheghi et al., 2014), in which Z. mobilis was gradually accustomed to increasing xylose concentration, gave similar results. Escherichia coli, which can utilize both glucose and xylose naturally, may be modified to produce ethanol in high quantities. This approach was chosen by Ohta et al. (1991) who inserted pyruvate decarboxylase and alcohol dehydrogenase genes originating from Z. mobilis into E. coli and were able to ferment solutions containing 10% glucose or 8% xylose, but glucose/xylose mixtures were not tested. To achieve simultaneous utilization of glucose/xylose mixtures it is necessary to eliminate CCR, to control transport into the cell and to balance the metabolic pathways for both saccharides. Successful demonstration of this approach is described by Chiang et al. (2013) who achieved about 30 g/l of ethanol with a productivity 1.9 g/l/h and 97% of theoretical yield from a glucose/xylose (1:1) mixture.
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3.4.2 Co-fermentation of different saccharide mixtures To overcome glucose CCR and prevent diauxic growth on different substrates, S.cerevisiae can be engineered to utilize cellobiose instead of glucose. Ha et al. (2011a) modified the yeast to utilize cellobiose and xylose, resulting in an improvement in ethanol productivity (from 0.27 to 0.65 g/l/h) compared to utilization of xylose as a sole carbon source. An ethanol concentration of 48 g/l, with a productivity of 0.79 g/l/h was reached if 130 g/l of a sugar mixture containing glucose, cellobiose and xylose was used. For marine biomass, S.cerevisiae was modified to simultaneously consume cellobiose and galactose, resulting in an ethanol concentration of up to 27 g/l and productivity of 0.75 g/l/h (Ha et al., 2011b). In addition to traditional ethanol producers, other microorganisms such as P. stipitis can be used but their common main disadvantage is a low tolerance of ethanol and lower productivity compared with S.cerevisiae (Agbogbo and Coward-Kelly, 2008). In addition, selected bacteria, e.g. lactobacilli (Kim et al., 2009; Kim et al. 2010) or clostridia (Patakova et al., 2013), and even some yeasts such as Candida shehatae (Kim et al., 2010) are characterized as CCR-negative and can utilize hexose and pentose saccharides simultaneously, which is more convenient regarding process productivity in lignocellulose fermentation. However utilization of these microorganisms for ethanol production requires further research. It has recently been published that the basidiomycete Trametes versicolor can utilize glucose, mannose, fructose, xylose, cellobiose and maltose for ethanol production, with yields ranging from 0.44 to 0.49 g/g of saccharide (Okamoto et al., 2014). The adapted ascomycete Spathaspora passalidarum can also produce up to 39 g/l ethanol (with a productivity of 0.8 g/l/h and 74% of the maximum theoretical yield) by co-fermentation of glucose, xylose and cellobiose contained in a hardwood hydrolysate (Long et al., 2012). 3.4.3 Microbial co-culture and sequential fermentation of saccharides The ethanol producers, S. cerevisiae or Z. mobilis can be used together with a pentoseutilizing microorganism for fermentation of saccharide mixtures. The most common solution is to use P. stipitis as the second member of the microbial community (for recent review of glucose/xylose mixtures used for ethanol co-fermentation see Chen 2011) but usually the ethanol yield did not exceed 25 g/l (Fu et al., 2009; Gupta et al., 2009; Yadav et al., 2011).
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Theoretically, it is possible to consider the sequential use of different microorganisms where S. cerevisiae will first consume glucose for ethanol production and then other microorganisms will utilize the remaining pentoses. This approach was applied to chemically pre-treated rice straw (Li et al., 2011) when, after glucose consumption, S.cerevisiae was inactivated by heat and subsequently P. stipitis was inoculated for xylose fermentation. The final ethanol concentration in this experiment was 21.1 g/l with 73% of maximum theoretical yield and productivity of 0.2 g/l/h.
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3.5 Consolidated bioprocessing Consolidated bioprocessing (CBP) can be defined as a one-step process in which a feedstock is directly converted into a desired product by a special microorganism or microbial consortium without requiring pre-treatment of the feedstock (Fig. 4). The term can be applied to any raw material and any product, but is usually associated with lignocellulosic biomass and ethanol. The most challenging task with CBP is selection or design of a suitable microorganism/microbial consortium that must express appropriate hydrolytic enzymes matching the lignocellulosic feedstock, and produce ethanol. Strictly speaking, the raw material for CBP should not require any special physical, chemical or enzyme pre-treatment and particle size reduction should be sufficient. However, a number of authors label their processes as CBP even if they add saccharifying enzymes or use chemical pre-treatment of the feedstock. Although these approaches can improve process parameters they also increase the processing cost. Microorganisms to be used in lignocellulosic CBP can be categorized into two groups: cellulase producers (category I CBP producers) or ethanol producers (category II CBP producers). The difficulty is that microorganisms from either category cannot be used directly as wild type strains and require strain evolution involving adaptation, mutation, metabolic engineering, targeted or random modifications, or a combination of these approaches. The most common category I CBP producers include cellulolytic thermophilic bacteria such as Clostridium thermocellum (Lynd et al., 2005), Geobacillus thermoglucosidans, Thermoanaerobacterium saccharolyticum or Thermoanaerobacter mathranii (Taylor et al., 2009) and cellulolytic fungi (Amore and Faraco, 2012) such as Trichoderma reesei (Huang et al., 2014) or Paecilomyces variotii (Zerva et al., 2014). Other organisms such as the mushroom Flammulina velutipes (Kaneko et al., 2012; Maehara et al., 2013), or anaerobic filamentous fungi (Youseef et al., 2013) have some potential for CBP but until now, ethanol yields using these organisms are very low and therefore additional intensive research is required. Nevertheless, it cannot be excluded that further promising category I CBP producers will be isolated from natural sources in future. Category II CBP producers consist of engineered traditional ethanol producers such as S. cerevisiae (den Haan et al., 2013; Hasunuma and Kondo, 2012; Khramtsov et al. 2011; Wen et al. 2010), Z. mobilis (He et al., 2014; Linger et al., 2010) and also Kluyveromyces marxianus (Chang et al., 2013; Hong et al., 2007). Naturally occuring and designed microbial consortia combining category I and II CBP producers, were also tested. Using a consortium consisting of T. reesei, S. cerevisiae and Scheffersomyces stipitis (Brethauer and Studer, 2014), up to 67% of maximum theoretical ethanol yield was achieved from an acid pretreated wheat straw slurry, but the maximum ethanol concentration was about 7 g/l. Another consortium comprised of Clostridium phytofermentans and yeast (Zuruf et al., 2013) could convert cellulose to ethanol with 50% efficiency, reaching an ethanol concentration of up to 22 g/l, but with very low productivity. Selected results obtained using both categories of CBP producers, microbial consortia and two step sequential processes (the use of microbial consortia can also approach a sequential, twostep process using two microorganisms with cellulolytic and ethanologenic capabilities) are
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presented in Table IV. Only results where the concentration of ethanol reached at least 1 g/l are shown in Table IV, while processes where the final ethanol concentration was below this value were not included. Despite the exponentially increasing number of papers dealing with lignocellulosic ethanol production, including CBP, it is surprisingly difficult to find papers presenting „hard data“ on ethanol concentrations, yields and productivity values. Looking at Table IV, it is evident that some very good results (Christakopoulos et al., 1989; Gong et al., 1981b; Hahn-Hägerdahl and Häggström, 1985; ), comparable with current data (Argyros et al., 2011; Xu et al., 2010), were achieved in the 1980s, during the previous wave of interest in utilization of lignocellulosic materials for ethanol production. What seems to link current results with older significant data are good luck (and patience) with strain isolation/acquisition and once more good luck in strain improvement using both traditional and advanced techniques. Nevertheless, both then and now, the competitiveness of the CBP and its variants with traditional S. cerevisiae ethanol production is far too low, especially regarding process productivity. Current standard values obtained in distilleries during ethanol production using saccharose- or starch- containing crop fermentation by S. cerevisiae are also given for comparison in Table IV.
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2.6. Use of immobilized biocatalysts (enzymes and cells) Other approaches to decrease expenses associated with converting the rigid recalcitrant structure of lignocellulose to a valuable product such as ethanol include reducing input costs, particularly of cellulolytic enzymes and the production strain. Both can be efficiently immobilized to allow their separation and subsequent reuse in consecutive processes. The potential and advantages, together with drawbacks, of an immobilized system, in comparison with a suspension configuration are discussed in the following paragraphs.
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2.6.1. Immobilization of cellulolytic enzymes Traditional enzyme immobilization is based either on attachment on/in solid particles and/or enzyme cross-linking. Various suggestions for biocalyst immobilization have been reported for both individual cellulolytic enzymes (Verma et al., 2013; Wei et al., 2013) and a multicomponent enzyme complex (Abraham et al., 2014; Ince et al., 2012). To design an enzyme immobilization system, the nature and complexity of raw lignocellulosic material must be considered, and although pretreated, it is still a suspension of insoluble materials that exclude the use of conventional separation techniques such as filtration and centrifugation (Battacharya and Pletschke, 2014). The main immobilization methods, such as entrapment in a polymer matrix (Ortega et al., 1998; Ungurean et al., 2013), adsorption onto a solid carrier (Khoshnevisan et al., 2011; Sinegani and Sinegani, 2013), covalent linking to a solid support (Su et al., 2012; Verma et al., 2013), affinity interactions (Alftrén et al., 2013) and cross-linking of enzyme aggregates (CLEAs) or their combination (Sutarlie and Yang, 2013) were reported recently. In addition to facilitated separation, immobilization can lead to beneficial changes in enzyme characteristics (Mateo et al., 2007), e.g. increased stability is often mentioned together with changes in pH optima (Shimizu and Ishihara, 1987) and thermal characteristics (Tab. V), as well as changes in selectivity (Cao, 2005). In particular, an increase in thermal stability extends application possibilities, and the majority of authors agree that although the temperature optimum remains constant or varies slightly, at higher temperatures immobilized enzymes retain their activity for a longer period. A comparison of thermal properties of free and immobilized cellulolytic enzymes from some very recent experiments is summarized in Table V. Higher stability of immobilized enzymes may apply not only to hydrolysis at higher temperatures but also in the case of processes run under non-optimal conditions, e.g. SSF
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(ethanol, temperature) where several fold higher yields (up to 2.3) compared with soluble cellulases can be achieved (Lupoi and Smith, 2011). Abraham et al. (2014) achieved 93% and 89% saccharification of hemp hurd biomass after 48 h, employing cellulase bound on magnetic nanoparticles and free enzymes, respectively. Unfortunately, in most cases, a reduction in specific enzyme activity occurs after immobilization to an insoluble carrier (Chim-anage et al., 1986; Sutarlie and Yang, 2013; Tébéka et al., 2009; Wang et al., 2013). Reduction in activity of an immobilized enzyme could be caused by folding of cross-linked structures, diffusional difficulties of the large substrate (Shimizu and Ishihara, 1987), alterations in enzyme conformation (Tébéka et al., 2009; Yu et al., 2012) together with changes in the accessibility of the catalytic domain (Sutarlie and Yang 2013) or could be induced by steric hindrance of the matrix that prevents binding of a high molecular weight substrate to the enzyme. The latter can be avoided by introduction of a spacer arm that places the enzyme at some distance from the matrix (Chimanage et al., 1986). On the other hand exceptions can be found, e.g. Bhattacharya and Pletschke (2014) reported 1.35 fold higher activity compared to free enzyme for calcium magnetic cross-linked xylanase. The biggest advantage of immobilized enzymes is their ability to be recovered and reused, but from the reported data it is evident that enzyme activity of both free and immobilized biocatalysts more or less decrease with increasing time of saccharification, temperature and the number of cycles. This effect is a result of a variety of factors with different degrees of impact on final activity, including, in particular, enzyme detachment, protein denaturation and loss of matter during passage (Alftrén and Hobley, 2013). The greatest influence on the loss of activity would probably be temperature of hydrolysis and time of delay. Whereas Shimizu and Ishihara (1987) reported an appreciable activity of immobilized Trichoderma and Aspergillus cellulases after 60 days at 40°C, from Table V it is obvious that enzyme activity falls rapidly, in the order of hours, with increased temperature of hydrolysis, although more slowly than that of free enzyme. A certain degree of leakage of enzyme from binding structures in an immobilized system also occurs (Liang and Cao, 2012). Moreover, cellulolytic systems are more complicated because endoglucanases and cellobiohydrolases contain cellulose binding domains next to the catalytic core (Alftrén and Hobley, 2014; Gokhale and Lee, 2012; Linder et al., 1995), with a cellulose affinity that can be higher than that of the enzyme-support. For the same reason, recycling of cellulases should involve a desorption step (Lindedam et al., 2013). Objective evaluation of the recycling of cellulases immobilized by different methods is almost impossible due to differences in time, temperature and substrate used in each experiment. For example Verma et al. (2013) achieved 80% retention of enzymatic activity for β-glucosidase after 8 cycles and 50% activity after 16 cycles, whereas Alftrén and Hobley (2013) reported approx. 50% reduction of β-glucosidase activity after 4 cycles. At first sight this is an appreciably lower number but on close inspection, the duration of each cycle in the first example (using a synthetic substrate) was 10 minutes, while in the second case one cycle lasted for 24 h and a natural substrate was used. Similarly, for evaluation of loss of enzyme activity, approximately 20% loss of activity was detected by Su et al. (2012) after 11 cycles, but after only 5 cycles by Liang and Cao (2012), the first experiment was run for only 20 minutes per cycle with carboxy-methyl-cellulose (CMC) whereas the second was cycled for 1 hour each using a natural substrate. It can be generalized that recyclability decreases with increasing temperature and time of reaction, and varies noticeably with the type of substrate; a synthetic substrate such as CMC or Avicel provides significantly better results than crude lignocellulolytic biomass. As demonstrated by Sutarlie and Yang (2013) with cross-linked cellulase aggregates adsorbed on silica, the effect of substrate is significant; when synthetic
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substrate (CMC) was used, activity was similar to that of free enzyme but was significantly (~ 70%) decreased with a natural substrate (palm oil fibres). Another consideration is that the catalytic part of an immobilized enzyme scarcely reaches more than 10% of the total mass, leading to dilution of volumetric activity. In practice, actual values for cellulolytic enzymes vary a lot, with most well below this value, reaching approximately 10-30 mg/g (Alftren and Hobley, 2013; Khoshnevisan et al., 2011; Shimizu and Ishihara 1987). Very high immobilization capacities for cellulases have also been reported, reaching 112.3 mg/g immobilized on Fe3O4-chitosan (Zang et al., 2014) or even 225.5 mg/g attached to Fe3O4@SiO2 microspheres anchored with Cu2+ (Li et al., 2013). To enhance volumetric activity, higher payloads (mass of immobilized enzyme/ mass of carrier) or cross-linked enzyme aggregates (CLEAs) should be applied (Cao, 2005). Employing CLEAs without carrier is hardly feasible for lignocellulose due to the small particle size, whereas the use of CLEAs adsorbed to different carriers was successful (Nguyen and Yang, 2014; Sutarlie and Yang, 2013). Another approach to promote higher payloads is to increase the specific carrier surface area; smaller particles generally possess a larger surface area but there must be a balance between the available surface and separability of smaller particles; in this regard, the use of magnetic nanoparticles is beneficial (Khoshnevisan et al., 2011) due to the magnetism of their inorganic core, where simple concentration of nanoparticles can be achieved by an external magnetic field (Alahakoon et al., 2012; Cho et al., 2012). For porous carriers with a larger surface area and a higher enzyme loading capacity, the increase in specific area is inevitably connected with a decrease in pore size (Cao, 2005) that leads to diffusional limitations. Realistic assessments of glucose yield produced by immobilized enzymes compared with a suspension system is complicated because the vast majority of articles present data in relative percentages related to different variables; even though these percentages seem promising, specific data indicating real values on glucose release (concentration per time) are often omitted. A few available values correlate with one of the main drawbacks of lignocellulose biomass utilization - a very low concentration of reducing sugars even if synthetic (CMC, Avicel, filter paper) substrates are used. Tébéka et al. (2008) achieved 2.35 g/l of glucose after hydrolysis of Avicel using cellulases adsorbed on Si wafers. Alftrén and Hobley (2014) has reported the highest bead activity of 2.8 g/kg/min (reducing sugars per bead mass per time) for microcrystalline cellulose digested by cellulases immobilized on magnetic particles activated by cyanuric chloride. Better results were reported for enzyme retention in a membrane reactor (Yang et al., 2009) where a 200% increase in the conversion of pretreated corn stalk compared to a traditional arrangement, has been achieved; but even under these conditions (100 g/l dry weight, D=0.65 1/h) the concentration of reducing sugars was less than 10 g/l and during the process continued to decline, to a stable concentration of 2 g/l. 2.6.2. Immobilization of microbial cells Compared to the cost of enzymatic hydrolysis, expenses associated with microbial transformation of glucose to ethanol are significantly lower, but still must be taken into account. Ethanol producing yeast or bacterial cells can be immobilized similarly to cellulolytic enzymes, leading to savings in both time and the cost of cell cultivation. The commonly used immobilization techniques for microbial cells are attachment or adsorption onto a solid surface, entrapment within a porous matrix, mechanical containment behind a barrier or self-aggregation of cells by flocculation (Mussatto et al., 2010). A widely exploited immobilization strategy is the encapsulation of microorganisms in alginate beads, where the concentration of CaCl2 can influence the rate of ethanol production via altered matrix permeabilities for substrate as well as for product (Franco et al., 2011). As reported for yeasts encapsulated in 3.5 and 8% calcium alginate, the glucose utilization rate
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(50 g/l, synthetic medium) halved while the ethanol yield was 10% higher (64% and 74% of theoretical values, respectively). A higher tolerance to toxic compounds present in hydrolysates due to a lower diffusion rate into the matrix core, mitigation of inhibitory effects by absorption to the carrier matrix, or by the activity of outer cells is often reported for immobilized cells. Due to this effect, immobilized cells can be applied in processes where free cells fail to grow, as reported by Yamashita et al., 2008 for Z. mobilis immobilized in alginate and grown on paper sludge. Unfortunately, a noticeable decline in productivity after repeated batch fermentation was observed in this case. The main drawback of alginate beads seems to be their stability, fragmentation, cell leakage or even complete dissolution (Mathew et al., 2013 Singh et al., 2013). On the other hand some authors have reported relatively good reusability, e.g. Wirawan et al., 2012 successfully repeated five 10 h cycles on 20 g/l glucose without any apparent change in ethanol yield or productivity, and Zhao and Xia (2010) reported that agar immobilized S. cerevisiae ZU-10 cells were maintained after six 24 h cycles with 100% conversion of glucose and 93% conversion of xylose. In addition to alginate, other materials can be used for cell entrapment such as the more mechanically stable Lenticats® (Mathew et al., 2013), polyvinyl alcohol (PVA) (Wirawan et al., 2012) or agar-agar (Lebeau et al., 2007; Singh et al., 2013). Apart from encapsulation, traditional immobilization of microorganisms on solid supports can be used, including a variety of natural materials such as spent grains (Mathew et al., 2013), or sugarcane bagasse (Singh et al., 2013). However, cells immobilized on this type of substrate cannot be employed in simultaneous processes where cellulolytic enzymes are present due to the risk of support dissolution. An advantageous method of immobilization appears to be self-flocculation of yeast, where cells form flocs with an appropriate size range that can be effectively separated by sedimentation. There is no extra consumption of supporting material and simultaneously effective ethanol production can be achieved by maintaining the cell concentration at the required level with little affect on cell growth (Bai et al., 2008). Brandberg et al. (2007) demonstrated that separation of S. cerevisiae cells in a settler was the most efficient system compared with immobilization in calcium alginate, and cell recirculation by filtration, achieveing 98% hexose utilization and a volumetric ethanol production rate of 2.58 g/l/h at D=0.10 1/h for acid lignocellulose hydrolyzate supplemented with enzymatically hydrolyzed wheat flour. Under these conditions, cell number was 32 times higher in the bioreactor than in the outflow. Nevertheless wheat particles and cells were distributed in the settler inhomogenously due to the faster sedimentation of wheat, resulting in a reduced reflux of cells back to the reactor, which contributed to rapid wash out at D=0.20 1/h. Some new approaches have also been proposed for the effective utilization of cellulose, e.g., expression of endo-glucanase gene egX in S. cerevisiae and its display on the cell surface by fusion with aga2 encoding the binding subunit of the cell wall protein α-agglutinin (Yang et al., 2013). The highest cellulase activity and bioethanol concentration achieved on CMC were 2.36 U/g (dry weight of cells) and 3.92 g/l, respectively. Another system was introduced by Liu et al. (2012), where three different microorganisms were co-immobilized in a specially constructed bioreactor with separated aerobic and anaerobic chambers for consecutive hydrolysis and ethanol production, but the final values on CMC were quite poor, with only 11.2% conversion to reducing sugar and an ethanol concentration of only 0.56 g/l. Apparently, cell immobilization gives more encouraging results than immobilization of cellulases; while cell immobilization leads mainly to improvements in ethanol production through resistance to toxic compounds present in lignocellulosic hydrolyzates, the opposite, a decrease in enzymatic activity, occurs after cellulase immobilization, together with difficulties in separation from the lignocellulosic matter. However, considering the price of cellulases, and recirculation possibilities, active research in this field may result in a future prospective
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3. Conclusion The configuration of individual technological steps plays an important role in the efficiency of a lignocellulosic ethanol production process. Although the recent trend is for consolidation of unit operations, to propose a generally valid optimal design suitable for many substrates is not feasible because all process configurations have advantages and disadvantages. In the case of separate hydrolysis and fermentation (SHF), high ethanol yields (usually exceeding 80% of theoretical value) are often achieved and even yields approaching maximum are not exceptional, especially for substrates containing lower amounts (less than 10%) of water insoluble solids. This is logical because the substrate is liquefied before fermentation and therefore the inoculum (usually yeast) is not exposed to harsh conditions (high viscosity, lack of free water, problems with mass transfer) as in simultaneous processes. Since the conversion of cellulose into glucose is influenced by many factors (type of substrate, composition of enzyme cocktail, dosing, WIS) the results are hard to compare and differ for different substrates and SHF conditions, although yields of glucose approaching maximum have been reported for substrates with lower WIS. On the other hand, the yield of ethanol achieved in simultaneous processes (SSF) is lower than SHF (values exceeding 80% of theoretical yield are exceptional) but cellulose conversion is probably more efficient due to elimination of end product inhibition of cellulolytic enzymes (since all processes are combined, and released glucose is immediately consumed, this value cannot be calculated properly). Similarly to SHF, SSF processes usually suffer from low productivity that can be partly improved by integration of a presaccharification step (as in case of dSSF processes), but the duration should be carefully calculated. Consolidated bioprocesses employed for ethanol production are difficult to evaluate since their design and combination of microbial strains differ. Although the ethanol yield can approach theoretical values, the final ethanol concentration and productivity are usually lower than SHF, SSF and dSSF when natural substrates (rather than pure cellulose) are used. Despite enormous progress that has been achieved in 2nd generation ethanol technologies, as shown in this review, it is clear that the factory price of lignocellulosic ethanol is higher than the price of 1st generation ethanol. This is partly due to additional technological steps (and thus higher energy demands), higher dosing of enzymes (and their price), and partly by the character of the substrate not allowing an increased concentration of sugars comparable with substrates originating from starch or molasses. In contrast, with 1st generation raw materials, the price of waste lignocellulosic materials is much lower and this could partly contribute to reducing the difference in bioethanol prices. On the other hand, the problem of 2nd generation ethanol cannot be assessed only in terms of price. In order to fulfil ambitious political targets of Directive 2009/28/EC, it has been estimated that 40 million hectares will be needed to grow biomass for bioenergy (De Wit and Faaij, 2010), meaning that large amounts of currently arable land would need to be moved from food to biofuel production. Diversification of biofuel feedstocks, including inedible ones, is thus necessary to maintain food independency of EU countries (Simon et al., 2010). A transition to cellulosic ethanol, exploiting agriculture wastes, energy crops grown on pastures, and currently unused land is the next step (Eggert and Greaker, 2014). In addition, it was reported that reductions in emissions from cellulosic ethanol could be almost 100%, which is an improvement over most first generation ethanols, with the exception of sugarcane ethanol produced in Brazil (Eggert and Greaker, 2014). Thus, governmental interventions with production subsidies, or the
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5. Acknowledgement This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic, projects Kontakt ME10146 and project Nol MSM 6046137305.
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Chang JJ, Ho FJ, Ho CY, Wu YC, Hou YH, Huang CC , Shih MC, Li WH. Assembling a cellulase cocktail and a cellodextrin transporter into a yeast host for CBP ethanol production. Biotechnol Biofuels 2013;6:19.
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Cui X, Zhao X, Zeng J, Loh SK, Choo YM, Lui D. Robust enzymatic hydrolysis of formilinepretreated oil palm empty fruit bunches (EFB) for efficient conversion of polysaccharide to sugars and ethanol. Bioresour Technol 2014;166:584-91.
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Ha S-J, Wei Q, Kim SR, Galazka JM, Cate J, Jin YS. Cofermentation of cellobiose and galactose by an engineered Saccharomyces cerevisiae strain. Appl Environ Microbiol 2011b; 77:5822-5.
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Jin M, Gunawan C, Balan V, Dale BE. Consolidated bioprocessing (CBP) of AFEX™pretreated corn stover for ethanol production using Clostridium phytofermentans at a high solids loading. Biotechnol Bioeng 2012;109:1929-36. Kádár Z., Szengyel Z., Réczey K. Simultaneous saccharification and fermentation (SSF) of industrial wastes for the production of ethanol Ind Crops Prod 2004;20:103-10.
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Lopéz-Linares JC, Romero I, Cara C, Ruiz E, Moya M, Castro E. Bioethanol production from rapeseed straw at high solids loading with different process configurations. Fuel 2014; 122:112-8. Lu J, Li X, Zhao J, Qu Y. Enzymatic saccharification and ethanol fermentation of reed pretreated with liquid hot water. J Biomedicine Biotechnol 2012;2012: 276278.
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Moon J, Liu ZL, Ma M, Slininger PJ. New genotypes of industrial yeast Saccharomyces cerevisiae engineered with YXI and heterologous xylose transporters improve xylose utilization and ethanol production. Biocat Agr Biotechnol 2013;2:247-54.
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Wirawan F, Cheng C-L, Kao W-C, Lee D-J, Chang J-S. Cellulosic ethanol production performance with SSF and SHF processes using immobilized Zymomonas mobilis. Appl Energy 2012;100:19-26. Xiros C, Christakopoulos P. Enhanced ethanol production from brewer's spent grain by a Fusarium oxysporum consolidated system. Biotechnol Biofuels 2009;2:4. Xiros Ch, Olsson L. Comparison of strategies to overcome the inhibitory effects in highgravity fermentation of lignocellulosic hydrolysates. Biomass Bioenergy 2014;65:79-90. Xu C, Qin Y, Li Y, Ji Y, Huang J, Song H, Xu J. Factors influencing cellulosome activity in consolidated bioprocessing of cellulosic ethanol. Biores Technol 2010;101:9560-9. Yadav KS, Naseeruddin S, Prashanthi GS, Sateesh L, Rao LV. Bioethanol fermentation of concentrated rice straw hydrolysate using co-culture of Saccharomyces cerevisiae and Pichia stipitis. Biores Technol 2011;102:6473-8. Yamashita Y, Kurosumi A, Sasaki C, Nakamura Y. Ethanol production from paper sludge by immobilized Zymomonas mobilis. Biochem Eng J 2008;42(3):314-9.
ACCEPTED MANUSCRIPT Yang J, Dang H, Lu JR. Improving genetic immobilization of cellulase on yeast cell surface for bioethanol production using cellulose. J Basic Microbiol 2013;53:381-9.
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Yang S, Ding W, Chen H. Enzymatic hydrolysis of corn stalk in a hollow fiber ultrafiltration membrane reactor. Biomass Bioenergy 2009;33(2):332-6.
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Youssef NH, Couger MB, Struchtemeyer CG, Liggenstofer AS, Prade RA, Najar FZ, Atiyeh HK, Wilkins MR, Elshahed MS. The genome of the anaerobic fungus Orpinomyces sp. strain C1A reveals the unique evolutionary history of a remarkable plant biomass degrader. Appl Environ Microbiol 2013;79:4620-34.
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Yu Y, Yuan J, Wang Q, Fan X, Wang P. Covalent immobilization of cellulases onto a watersoluble-insoluble reversible polymer. Appl Biochem Biotechnol 2012;166:1433-41.
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Yuan D, Rao K, Relue P, Varanasi S. Fermentation of biomass sugars to ethanol using native industrial yeast strains. Biores Technol 2011;102:3246-53. Zang L, Qui J, Wu X, Zhang W, Sakai E, Wei Y. Preparation of magnetic chitosan nanoparticles as support for cellulase immobilization. Ind Eng Chem Res 2014;53:3448-54.
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Zhang L, You T, Zhang L, Yang H, Xu F. Enhanced fermentability of poplar by combination of alkaline peroxide pretreatment and semi-simultaneous saccharification and fermentation. Bioresour Technol 2014;164:292-8.
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Zhang M, Eddy C, Deanda K, Finkelstein M, Picataggio S. Metabolic engineering of a pentose metabolic pathway in ethanologenic Zymomonas mobilis. Science 1995;267:240-3. Zhang M, Ouyang J, Liu B, Yu H, Jiang T, Cai C, Li X. Comparison of hydrolysis efficiency and enzyme adsorption of three different cellulosic materials in the presence of poly(ethylene glycol). Bioenerg Res 2013;6:1252-9. Zhao J, Xia L. Bioconversion of corn stover hydrolysate to ethanol by a recombinant yeast strain. Fuel Process Technol 2010;91(12):1807-11. Zuruff TR, Xiques SB, Curtis WR. Consortia-mediated bioprocessing of cellulose to ethanol with a symbiotic Clostridium phytofermentans/yeast co-culture. Biotechnol Biofuels 2013; 6:59. Internet resources: Cellulosic Ethanol (CE). (n.d.). Retrieved November 21, 2014, from http://www.biofuelstp.eu/cellulosic-ethanol.html Commercial Cellulosic Ethanol Projects: Brazil and Europe. (n.d.). Retrieved November 21, 2014, from http://dglassassociates.wordpress.com/2013/02/25/commercial-cellulosic-ethanolprojects-brazil-and-europe/
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Dong Energy, 2014: Dong Energy and DSM prove cellulosic bio-ethanol fermentation on industrial scale with 40% higher yield. Retrieved November 21, 2014, from http://www.dongenergy.com/EN/Media/Newsroom/News/Pages/DONGEnergyandDSMprove cellulosicbio-ethanolfermentationonindustrialscalewith40higheryield.aspx,
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Fig. 1 Overview of unit operations of lignocellulosic ethanol production Fig. 2 Unit operations of separate hydrolysis and fermentation (SHF) process design Fig. 3 Unit operations of simultaneous hydrolysis and fermentation (SSF) process design Fig. 4 Unit operations of co-fermentation of hexose and pentose sugars process design Fig. 5 Unit operations of consolidated (CBP) process design
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Figure 1
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Figure 2
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Figure 3
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Rapeseed straw, acid pretreated
S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Rapeseed straw, acid pretreated
S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Rapeseed straw, acid pretreated
S. cerevisiae, 34°C, 96 h
Wheat straw, hydrothermally pretreated
S. cerevisiae, recombinant , 120 h
Corn pretreated dilute acid
71.0
Productivity (g/l/h)
Reference
15.5
84.0
0.16
López-Linares et al., 2014
65.7
30.5
87.8
0.32
López-Linares et al., 2014
64.5
39.9
91.6
0.42
López-Linares et al., 2014
~95
NP
~ 60
73.1
~0.36
Canella and Jorgensen, 2014
stover with
65.0
88
30.0
93.0
0.16
Uppugundla al., 2014
et
S. cerevisiae, recombinant 120 h
Corn stover ionic liquid pretreated
72.0
100
~40
90.0
~0.21
Uppugundla al., 2014
et
S. cerevisiae, recombinant 120 h
Corn stover AFEX pretreated
60.0
79
~40
98.0
~0.21
Uppugundla al., 2014
et
AC
Max. ethanol concentration (g/l)
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S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Conversion of cellulose into glucose (%) 70
CR
Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 7% WIS Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 15% WIS Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 20% WIS Cellic CTech 2, addition of polyethyleneglycol, 50°C, 72 h, 30% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C, 72 h, 18% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C, 72 h, 10% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C,
Glucose concentration after enzymatic hydrolysis (g/l) 38.0
MA N
Feedstock
TE D
Fermentation
88.0
CE P
Enzymatic hydrolysis
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Theoretical Yield* (%)
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Table I Comparison of efficiency of selected SHF processes
S. cerevisiae, 30°C, 16 h
Cellulast 1.5L and Novozyme 188, 45 °C, 72 h, 10% WIS
recombinant xylose consuming S. cerevisiae, 32 °C, 90 h S. cerevisiae, 36°C, 72 h
58.6
37.5
NP
~30
7.13
76.5
0.12
Gupta 2009
et
al.,
18.5
96.1
0.36
Gupta 2009
et
al.,
18.5
49.1
NP
Ask et al., 2012
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18.2
CR
Commercial cellulose and ßglucosidase, 50°C, 36 h, surfactant addition
Prosopis juliflora wood, acid pretreated and delignified by sodium sulphate and sodium chlorite Prosopis juliflora wood, acid pretreated and delignified by sodium sulphate and sodium chlorite Arundo donax steam-exploded
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P. stipitis, 30°C, 24 h
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72 h, 13% WIS Commercial cellulose and ßglucosidase, 50°C, 36 h, 5% WIS surfactant addition
MA N
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54 62
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Commercial Reed, liquid hot 32.1 ~100 19.0 99.5 0.13 Lu et al. 2012 water pretreated cellulose, 50°C, 72 h, 5% WIS * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. WIS – Water insoluble solids ~ data were obtained from graph NP-not provided
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Table II Comparison of efficiency of selected SSF processes
42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS
S. cerevisiae
S. cerevisiae M. indicus R. oryzae S. cerevisiae
30°C, 6% WIS 3-stage fed-batch SSF 42 °C, 72 h, fed-batch SSF, 14% WIS 38 °C, 5% WIS 38 °C, 5% WIS 38 °C, 5% WIS 30 °C, 4% WIS, 48 h
P. stipitis
30 °C, 4% WIS, 48 h
Z. mobilis
30 °C, 4% WIS, 48 h
S. cerevisiae
37-38°C, 20% WIS, 48 h
S. cerevisiae
40°C, 7.5% WIS, 72 h
S. cerevisiae
40°C, 15 % WIS, 72 h
S. cerevisiae
40°C, 15 % WIS, 72 h
S. cerevisiae
35°C, 20 % WIS, fed-
39.9
0.84
Alfani et al., 2000
71.2 62.5 62.5 60.9
0.26 0.24 0.25 0.23
Ballesteros et al., 2004 Ballesteros et al., 2004 Ballesteros et al., 2004 Ballesteros et al., 2004
81.7
0.67
Kim et al., 2013
54
0.44
Tomás-Pejó, 2009
68
30.2
Rice straw Rice straw Rice straw Mature coconut fibre, alkali pretreated Mature coconut fibre, alkali pretreated Mature coconut fibre, alkali pretreated Oil palm empty fruit bunches formiline pretreated Rapeseed straw, acid pretreated Rapeseed straw, acid pretreated Rapeseed straw, acid pretreated Spruce slurry
10.2 11.4 21.5 8.4
60.8 67.6 75.9 84.6
0.20 0.23 0.43 0.18
Karimi et al., 2006 Karimi et al., 2006 Karimi et al., 2006 Goncalves et al., 2014
9.1
79.3
0.40
Goncalves et al., 2014
8.3
81.7
0.17
Goncalves et al., 2014
83.6
85.2
1.74
Cui et al., 2014
17.0
66.0
0.24
32.0
62.1
0.44
34.0
49.5
0.47
40.0
53%
0.42
López-Linares et al., 2014 López-Linares et al., 2014 López-Linares et al., 2014 Koopram and Olsson,
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Wheat straw
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K. marxianus
19.0 17.0 18.1 16.2
Reference
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K. marxianus K. marxianus K. marxianus K. marxianus
Wheat straw, steam exploded+washed NaOH Poplar Eucalyptus Wheat straw Sweet sorghum bagasse Saw dust
Productivity (g/l/h)
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37°C, 50 h, 10% WIS
Theoretical Yield* (%)
CR
S. cerevisiae
Max. ethanol concentration (g/l) ~30
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Feedstock
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SSF condition
TE D
Microorganism
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15.8
68.1
14.0
60.3
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Kanlow switchgrass pretreated with hydrothermolysis Kanlow switchgrass pretreated with hydrothermolysis Arundo donax steam-exploded
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37°C, ~7% WIS, 72 h
2014
CR
S. cerevisiae
commercially pretreated
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K. marxianus
batch addition of substrate, enzymes and yeasts, 96 h 45°, ~7% WIS, 72 h
0.22
Suryawati et al., 2008
0.19
Suryawati et al., 2008
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TE D
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S. cerevisiae 32 °C, 96 h 17.0 41.2 0.18 Ask et al., 2012 recombinant, xylose consuming * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. WIS – Water insoluble solids
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50 °C, 24h 50 °C, 24h 50 °C, 10h
50 °C, 10h
S. cerevisiae, 30 °C, 48 h, 25% WIS, fed-batch
50 °C, 24h
S. cerevisiae, 30°C, 96 h, 20% WIS S. cerevisiae, 40 °C, 28 h S. cerevisiae, 30 °C, 396 h, fed-batch
50 °C, 24h 50 °C, 12h with addition of substrate and enzymes 50 °C, 18h, 10% WIS 50 °C, 24h, 1012% WIS,
Reference
0.47
31.5
31.5
61.1
0.44
32.4
47.1
0.45
17.4
88.4
0.24
Lopéz-Linares et al., 2014 Lopéz-Linares et al., 2014 Lopéz-Linares et al., 2014 Huang et al., 2014
36.6
73.5
0.51
Huang et al., 2014
34.0
NP
58.8
NP
NP
9.9
63.1
0.19
Xiros and Olsson, 2014 Zhang et al., 2014
30.5
91.5
54
0.02
Elliston et al., 2013
32.0 38.4
NP
Reed, liquid hot water NP 39.4 79.1 0.44 Lu et al., 2012 pretreatment Spruce chips, SO2 49.4 31.1 85.0 0.26 Ishola et al., 2013 impregnated, pretreated at elevated temperature and pressure 45°C, 5 days, 7% S. cerevisiae, 30°C, 4 Wheat straw steam NP 22 49 ~0.23 Viola et al., 2013 WIS, cycles exploded, extracted with alkaline solution * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. ** Process productivity has been recalculated to include the duration of both the presaccharification period and SSF WIS – Water insoluble solids NP-not provided
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S. cerevisiae, 36 °C, 72 h, fed-batch S. cerevisiae, 96 h saccharification with filtration
Productivity** (g/l/h)
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Rapeseed straw acid pretreated Rapeseed straw acid pretreated Rapeseed straw acid pretreated Pomelo peel, hydrothermally pretreated Pomelo peel, hydrothermally pretreated Spruce wood chips acid pretreated Sacrau poplar, peroxide pretreatment a Copier paper
Theoretical Yield* (%) 65.5
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S. cerevisiae, 40 °C, 7.5%WIS, 72 h S. cerevisiae, 40 °C, 48 h, 15 %WIS, S. cerevisiae, 40 °C, 48 h, 20 %WIS, S. cerevisiae, 30 °C, 48 h, 10% WIS
Max. ethanol concentration (g/l) 17.4
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50 °C, 24h
Glucose in presaccharification (g/l) 17.0
MA N
Feedstock
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SSF condition
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Presaccharificati on
CR
Table III Comparison of efficiency of selected SSF processes with delayed inoculation
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Table IV Comparison of efficiency of selected CBP processes
Trichoderma reesei Fusarium oxysporum
Paecilomyces variotii Trametes versicolor
Category II CBP engineered S.cerevisiae engineered S. cerevisiae Consortia C. thermocellum Thermoanaerobacter ethanolicus C.thermocellum Thermoanaerobacterium saccharolyticum C.phytofermentans, S.cerevisiae T.reesei, S.cerevisiae T.reesei, S.cerevisiae,
Cellulose (unspecified) Cellulose (unspecified) AFEX treated corn stover Avicel Solka-Floc Sugar cane bagasse Cellulose Alkali treated brewer`s spent grain Wheat bran Crystalline cellulose Wheat bran rice straw
2.8
40
23.0
-
Reference
0.02
Rani et al., 1997
0.06
Xu et al., 2010
63
0.03
Jin et al., 2012
60 70 20
0.05 0.07 0.03
Gong et al., 1981b Gong et al., 1981b Huang et al., 2014
14.5 10
53 60
0.1 0.1
Christakopoulos et al., 1989 Xiros and Christakopoulos, 2009
1.2 4.7
18 47
0.2 0.05
Zerva et al., 2014 Okamoto et al., 2014
5.0 4.8
92 91
0.05 0.05
Okamoto et al., 2014 Okamoto et al., 2014
Avicel Acid pre-treated wheat straw
1.8 26
36 63
0.03 0.27
Wen et al., 2010 Khramtsov et al., 2011
Alkali treated banana waste Avicel
22
29
NP
Reddy et al., 2010
38
90
0.3
Argyros et al., 2011
α-cellulose (added endoglucanase) Avicel Dilute acid
22
43
NP
Zuroff et al., 2013
7.0 9.8
70 69
0.04 0.07
Brethauer and Studer, 2014 Brethauer and Studer, 2014
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7 13 16 3.0
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Productivity (g/l/h)
MA N
Monilia sp.
Theoretical Yield* (%)
TE D
Clostridium phytofermentans
Max. ethanol concentration (g/l)
CE P
category I CBP Clostridium thermocellum
Feedstock
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CBP microorganism(s)
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wheat
40
83
Corn, sugar beet, molasses
100-120
95-98
0.2
Hahn-Hägerdahl Häggström, 1985
2.8-4.0
average data from Czech distilleries
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Solka-Floc
CR
Two step processes T. reesei S. cerevisiae Standard process using 1st generation feedstock S. cerevisiae
pretreated straw
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Scheffersomyces stipitis
and
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Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. NP-not provided
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Table V Optimal temperature and thermal stability of free and immobilised enzymes under increased temperature. Optimal temperature
49°C
non-porous magnetic particles
65°C
70°C
β-glucosidase (Novozyme)
mercaptopropyl functionalyzed mesoporous TiO2 Fe3O4-chitosan
60°C
60°C
50°C
Xylanases (Bacillus gelatini ABBP-1)
Ca-mag- CLEA
-
Cellulase (T. resei ATCC 26921)
CLEAs on silica gel (XCa-Si)
Biotinylated glucosidase
Loss of activity
initial
Referenc e
NP
-28%
immobili zed -14%
1h
-26%
-60%
60°C
4h
- ~30%
50°C
60°C
5h
~80 % -47%
-
50°C
32h
-20%
not changed
50°C
50°C
70°C
1h
-73%
-25%
streptavidin coated magnetic particles
45°C
45°C
50C
3h
100 %
- 43%
iron oxide nanoparticles
60°C
60°C
70°C
2h
96%
-21%
co-immobilized gold nanoparticles
-
-
80°C
48h
- ~20%
Cho et al., 2012
co-immobilized gold-doped magnetic silica nanoparticles polyamidoamine dendrimer grafted silica chitosan
-
-
80°C
48h
~11 % ~11 %
- ~8%
Cho et al., 2012
50°C
60°C
70°C
3h
- ~47%
Wang et al., 2013
40°C
50°C
60°C
2h
~75 % -39%
-14%
55°C
60°C
80°C
2h
-73%
-50%
Cellulase (Suhong B989N)
reversible watersoluble polyacrylate copolymer reversibly soluble Eudragit S-100
Su et al., 2012 Liang and Cao, 2012
50°C
50°C
70°C
1h
- ~30%
Yu et al., 2012
Cellulase viride)
polyaniline coated microspheres
40°C
50°C
75°C
2h
~47 % ´100 %
-22%
Ince et al., 2012
D
AC
β-glucosidase (Aspergillus niger) Endo-glucanase Exo-glucanase Beta-glucosidase Endo-glucanase Exo-glucanase Beta-glucosidase
TE
β-
CE P
Cellulase (Meiji Seika Pharma)
Cellulase viride)
(T.
Cellulase Cellulase (Novozyme)
(T.
60°C
SC R
CLEAs on silica gel
Tim e
free
65°C
NU
Cellulase (T. resei) SigmaAldrich β-glucosidase (Megazyme)
immobil ized 51°C
MA
free
Increase d tempera ture
T
Immobilization method
IP
Enzyme
-41%
Sutarlie and Yang, 2013 Alftrén and Hobley, 2013 Wei et al., 2013 Zang et al., 2014 Battachar ya and Pletschke , 2014 Nguyen and Yang, 2014 Alftrén et al., 2013 J Verma et al., 2013
ACCEPTED MANUSCRIPT Cellulase viride)
(T.
Cellulase resei)
(T.
polyaniline coated microspheres, crosslinked enzyme magnetic nanoparticles
40°C
50°C
75°C
2h
50°C
60°C
80°C
2h
AC
CE P
TE
D
MA
NU
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T
~ data were obtained from graph NP – not provided
100 % 100 %
- 37%
Ince et al., 2012
- ~35%
Abraham
et 2014
al.,
ACCEPTED MANUSCRIPT Highlights Process design for production of 2nd generation ethanol is reviewed.
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Efficiency of processes (ethanol concentration, yield, productivity) is compared.
S0734-9750(14)00189-X doi: 10.1016/j.biotechadv.2014.12.002 JBA 6872
To appear in:
Biotechnology Advances
Please cite this article as: Paulov´ a Leona, Pat´ akov´a Petra, Bransk´a Barbora, Rychtera Mojm´ır, Melzoch Karel, Lignocellulosic ethanol: Technology design and its impact on process efficiency, Biotechnology Advances (2014), doi: 10.1016/j.biotechadv.2014.12.002
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ACCEPTED MANUSCRIPT Lignocellulosic ethanol: technology design and its impact on process efficiency
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Leona Paulová*, Petra Patáková, Barbora Branská, Mojmír Rychtera and Karel Melzoch Department of Biotechnology, Institute of Chemical Technology Prague, Technicka 5, CZ16628 Prague 6, Czech Republic
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* Corresponding author at: Institute of Chemical Technology Prague, Technicka 5, CZ16628 Prague 6, Czech Republic. Tel.: +420220445022, fax: +420224311082 E-mail address: [email protected]
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Abstract This review provides current information on the production of ethanol from lignocellulosic biomass, with the main focus on relationships between process design and efficiency, expressed as ethanol concentration, yield and productivity. In spite of unquestionable advantages of lignocellulosic biomass as a feedstock for ethanol production (availability, price, non-competitiveness with food, waste material), many technological bottlenecks hinder its wide industrial application and competitiveness with 1st generation ethanol production. Among the main technological challenges are the recalcitrant structure of the material, and thus the need for extensive pretreatment (usually physico-chemical followed by enzymatic hydrolysis) to yield fermentable sugars, and a relatively low concentration of monosaccharides in the medium that hinder the achievement of ethanol concentrations comparable with those obtained using 1st generation feedstocks (e.g. corn or molasses). The presence of both pentose and hexose sugars in the fermentation broth, the price of cellulolytic enzymes, and the presence of toxic compounds that can inhibit cellulolytic enzymes and microbial producers of ethanol are major issues. In this review, different process configurations of the main technological steps (enzymatic hydrolysis, fermentation of hexose/and or pentose sugars) are discussed and their efficiencies are compared. The main features, benefits and drawbacks of simultaneous saccharification and fermentation (SSF), simultaneous saccharification and fermentation with delayed inoculation (dSSF), consolidated bioprocesses (CBP) combining production of cellulolytic enzymes, hydrolysis of biomass and fermentation into one step, together with an approach combining utilization of both pentose and hexose sugars are discussed and compared with separate hydrolysis and fermentation (SHF) processes. The impact of individual technological steps on final process efficiency is emphasized and the potential for use of immobilized biocatalysts is considered. Keywords: lignocellulose, ethanol, pretreatment, enzymatic hydrolysis, fermentation, process configuration, SHF, SSF, CBP, pentose, hexose, immobilization, yield, productivity Content 1. Introduction 2. Process configuration and its impact on ethanol yield and productivity 2.1 Separated hydrolysis and fermentation 2.2 Simultaneous saccharification and fermentation 2.3 Simultaneous saccharification with delayed inoculation 2.4 Co-fermentation of hexose and pentose sugars 2.4.1. Glucose and xylose co-fermentation 2.4.2. Co-fermentation of different saccharide mixtures 2.4.3. Microbial co-culture and sequential fermentation of saccharides
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Consolidated bioprocessing Use of immobilized biocatalysts (enzymes and cells) Immobilization of cellulolytic enzymes Immobilization of microbial cells Conclusion Acknowledgement References
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2.5 2.6 2.6.1. 2.6.2. 3. 4. 5.
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1. Introduction Although production of ethanol from lignocellulosic materials (e.g. wood, agricultural residues, energy crops, herbaceous plants etc.) has many advantages (e.g. availability, low price if not transported long distances, non-competitiveness with the food chain, often regarded as waste material) the process (2nd generation ethanol) is more complicated compared with 1st generation ethanol production and involves many technical and economic challenges; it is therefore only carried out on pilot/demonstration scales in Europe and most commercial plants have been built during the last decade (Larsen et al., 2012). In 2009, a cellulosic ethanol plant using Ibicon technology was constructed in Kaundborg, Denmark, to produce 5 400 m3 of ethanol per year. In 2013 the plant was rebuilt to provide mixed fermentation of hexose and pentose sugars originating from wheat straw (Dong Energy, 2014). In 2010, a plant producing ethanol from various biomasses, particularly from straw and bagasse, was opened in Oulu, Finland (Commercial cellulosic ethanol projects, 2014). In June 2013, the Abengoa demonstration plant was inaugurated in Salamanca, Spain, with an annual capacity of 15 000 m3 of bioethanol made from municipal solid waste. Currently the world´s largest 2nd generation biofuel production plant, with an annual capacity of 75 000 m3 of bioethanol produced from wheat and rice straw, was opened in October 2013, in Italy (Cellulosic ethanol (CE), 2014). Although many combinations of individual technological steps have been tested, the principle of producing ethanol from lignocellulosic feedstock is the same and fundamental steps should be followed to enable successful conversion of cellulose (and/or hemicellulose) to ethanol (Cardona and Sánchez, 2007; Gupta et al., 2009; Lin and Tanaka, 2006; Paulová et al., 2013 ). Generally, the process of producing 2nd generation ethanol consists of the following operations: reduction of particle size (usually by milling or cutting), liberation of cellulose and hemicellulose from the lignin-protected complex, carried out by different pretreatment methods (usually a combination of high pressure, temperature and the addition of chemicals, although some innovative methods such as treatment with ionic liquids have been tested) , the release of monomeric sugars from cellulosic and hemicellulosic polymeric chains, and their fermentation into ethanol (Fig. 1). These operations can be carried out consecutively, as in case of separate hydrolysis and fermentation (SHF) processes, fully or partly simultaneously, as in case of simple simultaneous (SSF) processes or simultaneous processes with delayed inoculation (dSSF), or fully consolidated as in the case of the consolidated bioprocessing (CBP) design. These will be discussed in the following chapters. Regardless of process design, one of the main drawbacks of these technologies is the low ethanol concentration produced from lignocellulose. This is caused mainly by the low concentration of sugars available for fermentation because the character of this feedstock does not practically allow for an increase in fermentable solids in batch to levels that would provide similar sugar concentrations as used for 1st generation feedstocks (e.g. corn or molasses). Many technical problems (high viscosity, low amount of free water due to its absorption into the biomass, high content of inhibitors, problems with mixing, nutrient levels, heat, mass transport, etc.) contribute to this (Modenbach and Nokes 2013).
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Second generation ethanol technologies are complicated (Eggert and Greaker, 2014; Lin and Tanaka; 2006; Taherzadeh and Karimi, 2007; Viikari et al., 2012) and their efficiencies can be influenced by many factors such as the type of lignocellulosic feedstock, pretreatment methods, use of or omission of a detoxification step, the type and amount of cellulolytic enzymes, the microorganisms used and their robustness (including compatibility with enzymatic cocktails in simultaneous processes), cultivation conditions (configuration, temperature, pH, concentration of solids, type and amount of nutrient addition etc.), and type of bioreactor (principle of mixing, type of operation). Therefore to find an optimum combination of all variables for a particular feedstock is challenging. To obtain optimum values of all parameters, different optimization approaches such as response surface methodology are often used (for an example, see Jaisamut et al., 2013). In this review, the main features, advantages and drawbacks of the common process configurations such as SHF, SSF, dSSF and CBP are discussed and compared with processes in which utilization of both hexose and pentose sugars are combined. Technologies exploiting immobilized biocatalysts are also described. Individual process designs are compared regarding parameters that play important roles in process efficiency such as final ethanol concentration, its yield from substrate and productivity. All process configurations have some advantages and drawbacks (which are sometimes contradictory), therefore several aspects must be considered in order to select the best combination of unit operations that will lead to efficient production of ethanol, complete use of feedstock and reasonable utilization of coproducts and wastes to ensure an economically acceptable technology for any particular feedstock.
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2.1. Separate hydrolysis and fermentation Separate hydrolysis and fermentation, (SHF) is a process consisting of two consecutive operations; firstly, cellulose, contained in a solid phase of pretreated lignocellulosic material, is hydrolysed to glucose using cellulolytic enzymes (usually in combination with other sugars released from hemicellulose). Released glucose (which is usually in a mixture with other hexose and/or pentose sugars, depending on the method of pretreatment and medium preparation) is then converted into ethanol by a selected microbial strain in the following fermentation steps (Fig. 2). Both processes (i.e. enzymatic hydrolysis and fermentation) can be carried out under optimal conditions (temperature, pH, nutrient composition, solid loading), which is probably the main advantage of this configuration because the temperature optimum of each process differs considerably. The optimum temperature for most cellulolytic enzymes is usually around 50 °C while most microbial strains employed for ethanol production (traditional large scale ethanol producers are the yeast Saccharomyces cerevisiae and the bacterium Zymomonas mobilis, although many other strains have been employed in different processes, as described later), produce ethanol most efficiently at 28-37 °C. Moreover, the performance of cellulolytic enzymes is not influenced by the presence of ethanol, as is the case for simultaneous process arrangements, and medium viscosity is considerably reduced prior to fermentation, having positive effects on microbial strain viability, efficient mixing, and nutrient and heat transfers; this is advantageous mainly for processes carried out with a high solid content. On the other hand, inhibition of cellulolytic enzyme activity by increasing concentrations of released glucose (or cellobiose), (end product inhibition), slows the rate of cellulose hydrolysis and is usually described as the main drawback of this process configuration (Ask et al., 2012; Gupta et al., 2009; Tomás-Pejó et al., 2009). Although this effect can be partly minimized by supplementation of enzymatic cocktails with ß-glucosidase to increase the rate of cellobiose decomposition, it remains as the main problem of SHF. Moreover, for high xylan content feedstocks, further inhibition of cellulolytic enzymes by xylan degradation products is problematic (Qing et al., 2010).
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Many authors also emphasize the increased investment needed for SHF due to the use of more than one vessel (e.g. Ask et al., 2012), although it is not always necessary because in batch mode, both processes can be carried out consecutively in one bioreactor. Many processes employing SHF for ethanol production have been reported over the last few decades (Chen Y. et al., 2014; Gupta et al., 2009; Hansen et al., 2014), however, to improve competitiveness of 2nd generation ethanol production, ethanol concentrations around 100 g/l are required; this can be achieved by increased substrate loading. However, the amount of solid in the broth considerably affects both enzymatic hydrolysis and fermentation (Chen et al., 2007), and thus the outcome of the process. As shown by Lopéz-Lináres et al. (2014), the main drawback of SHF performed under high solid loading is reduced activity of cellulolytic enzymes, while with simultaneous processes (as discussed later), low microbial strain viability becomes a problem. For high solid SHF processes, typically higher concentrations of glucose are released during enzymatic hydrolysis (which is desired) but the cellulose hydrolysis rate and ethanol yield are usually lower compared to processes performed with a lower solid content (Uppugundla et al., 2014). As demonstrated by Lopéz-Lináres et al. (2014) for enzymatic hydrolysis of acid pretreated rapeseed straw in SHF, the glucose concentration increased roughly linearly with increasing solid content but both cellulose hydrolysis rate and its conversion into glucose were reduced. The authors attributed this effect to lower enzyme binding capacities caused by diffusional limitations in medium containing a high proportion of solids rather than to the loss of enzymatic activity due to endproduct inhibition. Some authors (e.g. Hoyer et al., 2010) recommend the continuous or intermittent feeding of cellulolytic enzymes, together with substrate, to improve the conversion of cellulose in high solid operations and to compensate for the non-productive binding of enzymes. However, the economics of such an approach should be carefully considered before being implemented. The use of various surfactants (e.g. Tweens, polyethene glycols or ionic liquids) to reduce enzyme attachment to lignin is another approach for improving the rate of cellulose hydrolysis and has been reported in many papers with varying successes (Gupta et al., 2009; Zhang et al., 2013), probably because the efficiency of this method greatly depends on the type of biomass and pretreatment methods prior to enzymatic hydrolysis. On the other hand, microbial strain performance in the fermentation phase of high solid SHF is almost unaffected by high solid medium, particularly because the initial broth viscosity is considerably reduced by the previous enzymatic step (Lópéz-Linares et al., 2014; Stenberg et al., 2000). The sensitivity of yeast cells to inhibition is thus often described as being lower in SHF processes compared to those combining enzymatic hydrolysis and fermentation in one step. Among the many factors that can affect a process result is also the composition of the enzyme cocktail used for cellulose hydrolysis. As reported by Canella and Jorgensen (2014), with the new generation of cellulolytic enzymes, high solid SHF processes are superior to simultaneous ones regarding ethanol yield while the converse is true for older enzyme cocktails. Moreover, as demonstrated by Uppungundla et al. (2014), the optimum composition of enzyme cocktails and dosing regime differs for various types of biomass and even for the same type of biomass pretreated using different methods. The same is true for supplementation of culture broth with nutrients; medium prepared from hydrolysates originating from the same biomass but pretreated using different methods require different nutrient supplementation because of differential nutrient loss during pretreatment and subsequent washing. There are many examples of SHF processes carried out either with low solid or high solid content media prepared from various types of biomass that were pretreated using numerous methods. A brief overview of selected SHF processes reported mainly over the last two years
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is shown in Tab. I in order to compare ethanol yield, final ethanol concentration and productivity with other processes that are described later in this review. Although the ethanol yield from glucose is often very high and close to theoretical, the final concentration of ethanol is far below the values achieved with 1st generation substrates (last row of Tab. IV), mainly due to the lower yield of glucose from cellulose, which is especially true for high solid processes. An exception is that reported by Canella and Jorgensen (2014), where almost 95% conversion of cellulose was achieved and about 60 g/l of ethanol was obtained from hydrothermally pretreated wheat straw.
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2.2. Simultaneous saccharification and fermentation The simultaneous saccharification and fermentation (SSF) process represents one of several modifications of the classical SHF process for production of cellulosic ethanol. This concept was first described in a patent by Gauss et al. (1976) and the term simultaneous saccharification and fermentation was first used in 1977 by the same working group (Takagi et al., 1977). The SSF process integrates enzymatic hydrolysis of pretreated (mechanically, physico-chemically, etc) lignocellulosic material with fermentation of released glucose into one step, carried out at the same time in one vessel (Fig. 3). Since the glucose released from cellulose in the enzymatic reaction is immediately and rapidly consumed by the microbial strain producing ethanol (and thus does not accumulate in the culture broth), elimination of end-product inhibition of cellulolytic enzymes are reported as the main advantages of this process configuration. The influence of glucose accumulation on the performance of cellulolytic enzymes was demonstrated in the model developed by Oh et al. (2000), who found that the initial cellulose hydrolysis rate decreased by 20 and 60% due to enzyme inhibition at glucose concentrations of 5 and 20 g/l, respectively. Elimination of glucose accumulation thus enhances the rate of cellulose hydrolysis and therefore shortens the process time (Cardona and Sánchez, 2007; Olofsson et al., 2008). A reduction in investment costs (both processes run in the same vessel) and a lower risk of contamination (glucose is released in the presence of ethanol) are frequently described as other positive attributes of this process (e.g. Hasunuma and Kondo, 2012), although the effect of ethanol on the activities of cellulolytic enzymes is usually neglected in many papers. According to Oh et al. (2000), inhibition of cellulases by ethanol is less than that caused by glucose (or cellobiose), although this statement was not supported by data. In addition to the potential sensitivity of enzymes to released ethanol, low ethanol productivity in the early stages of SSF, caused by carbon limitation due to glucose deficiency, is another problem associated with this process (Paulová et al., 2014). However, the main drawback of SSF is difference between the temperature optimum of cellulolytic enzymes (usually 45-50 °C) and that of the fermenting microorganisms (mostly 28-37 °C), which affects the efficiency of both processes. This discrepancy is usually solved by lowering the temperature of hydrolysis to be compatible with the temperature optimum for the fermenting microorganism. Alternatively, a compromise between the optimal temperatures of both processes, which is usually around 37 °C, is applied. Unfortunately, the first approach affects the rate of glucose release from cellulose and can cause carbon limitation for fermentation, while the second approach affects the activity of cellulolytic enzymes and slows down the metabolism of the microbial strain; both approaches result in reduced productivity and often a lower final concentration of ethanol. As reported elsewhere, both cellulose hydrolysis rate and conversion into glucose are considerably affected by temperatures below the enzyme optimum; the rate of hydrolysis of pure cellulose was reduced by 60% if the temperature was lowered from 50 °C to 30 °C (Oh et al., 2000), while conversion of cellulose from acid pretreated wheat straw dropped by 40% if the process was carried out at 30°C instead of at 45 °C (Paulová et al., 2014). On the other hand, work at lower temperatures often means a higher
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tolerance of microorganisms to inhibitors (Olofsson et al., 2008) and ethanol (Cardona and Sánchez, 2007). Therefore, SSF carried out at enzyme suboptimal temperatures eliminates enzyme inhibition by glucose but slows the hydrolysis rate. Therefore, careful optimization of process conditions must be done to reach a compromise between the advantages and disadvantages of this process configuration. Another approach is ethanol production at elevated temperatures by employing thermotolerant ethanol producing microbial strains. Reduced demands for cooling and partial continuous removal of ethanol from the fermentation broth by evaporation, in addition to faster enzymatic hydrolysis carried out at (or close to) the optimum for cellulolytic enzymes, are described as benefits of this approach (Hansunuma and Kondo, 2012). Among wild species, Kluyveromyces marxianus is a good candidate for an SSF process carried out at an elevated temperature because many strains can efficiently produce ethanol at 38-45 °C and are also able to utilize arabinose, galactose, mannose or xylose, i.e. sugars present in the lignocellulosic medium. Strain IMB, isolated from a distillery in India, is reported (Suryawati et al., 2008) to be promising due to its ability to grow at temperatures up to 50 °C and with an ethanol tolerance of up to 9.5%. However, in practice, only small differences in ethanol concentration and productivity were observed between this strain and S. cerevisiae in an SSF process carried out at 45°C and 37 °C, respectively. This was probably due to the combined effects of high temperature, ethanol concentration and decreasing pH, which affected cell viability. Other authors (Kádár et al., 2004) did not observe any significant difference between S. cerevisiae and K. marxianus regarding ethanol yield in an SSF process, both values being in the range of 0.31-0.34 g/g. Some thermotolerant strains of S. cerevisiae that can be exploited for cellulosic ethanol production e.g. a high-temperature growth phenotype (Htg+) exhibiting increased resistance to temperature, ethanol and osmotic pressure, have been recently isolated and characterized (Shahsavarani et al., 2012). Some genetically engineered strains of Hansenula polymorpha or Candida glabrata also have potential for SSF carried out at higher temperatures. Unfortunately, although a good ethanol yield is usually achieved in SSF, the final ethanol concentration and productivity is still low compared with starch- or sugar-based processes, caused mainly by the lower initial concentration of fermentable sugars in the broth. In contrast to media prepared from corn or molasses, the pre-concentration of pretreated lignocellulosic material is more complicated due to the character of this substrate. High substrate loadings, which are inevitable for achieving ethanol concentrations similar to that of 1st generation processes, are hardly achievable due to mixing and pumping problems and mass transfer limitations caused by the high viscosity of the medium and its toxicity due to the preconcentration of inhibitors. With increasing substrate loading (usually above 7- 10% of WIS – water insoluble solids), ethanol yields tend to decrease (Kim et al., 2013; Olofsson et al., 2008; Paulová et al., 2014; Tomás-Pejó et al., 2009). Total inhibition of yeast caused by a combination of high osmotic pressure, low water content and above optimum temperature occurred at 20% solids using acid pretreated rapeseed straw (López-Linares et al., 2014). Although glucose inhibition of cellulases in low solid SSF processes is usually eliminated, at high solids content, enzyme activity is also affected by the high concentration of inhibitors (this is mainly true for acid pretreated materials); as reported by Lopéz-Linares et al. (2014) the conversion of cellulose to glucose was reduced from 71 to 61% if the solid content of acid pretreated rapeseed straw increased from 7.5 to 20%. On the other hand, a high solid content is inevitable for process economy; 40 g/l ethanol is considered as the lower limit for economic distillation (Wingren et al., 2003) and a solid content of 16-20% is needed, assuming an average cellulose content of 40-50% w/v. Integration of a detoxification step (usually washing with water or other solvents) enables an increased solid content in fermentation because washing removes inhibitors, but is counter-productive for glucose content (glucose released in
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prehydrolysis is also washed out). However, recently published data on an SSF process using formalin-pretreated oil palm empty fruit bunches, subsequently treated with lime and washed several times showed very good results. The ethanol concentration increased from 23.0 to 83.6 g/l along with increasing solid content from 5 to 20% (Cui et al., 2014); moreover the yield was only slightly affected by high solid loading. Although the ethanol concentration achieved was close to that for sugar- or starch-based processes, this result is unique, as seen in Tab.II. Fed-batch addition of pretreated material is another approach to increase sugar concentrations in the process. It allows the dose of substrate to be spread over a longer time period and thus to stepwise decrease viscosity in the bioreactor compared to batch mode. The initial batch is liquefied by the action of cellulolytic enzymes until the next addition of substrate and the concentration of inhibitors is kept low due to their microbial transformation to less harmful compounds during fermentation and by dilution. Many feeding strategies have been reported for SSF processes, some of them based on dynamic or fuzzy models (Chen and Qiu, 2010), in order to define an optimal feeding rate. As shown by Ruiz et al. (2006), the result of SSF is influenced not only by process arrangement and solid loading, but also by the method of lignocellulose pretreatment – for olive tree wood, steam explosion followed by hot alkaline peroxide treatment yielded increased ethanol with elevated pretreatment temperature, however the enzymatic hydrolysis yield and ethanol concentration dropped if the temperature exceeded 220 °C. The result of SSF (i.e. ethanol concentration) is also influenced by the amount of enzyme used. As demonstrated by Kim et al. (2013), higher enzyme concentrations can increase the conversion of cellulose into glucose, and consequently, the concentration of ethanol, but process economics should be kept in mind when calculating enzyme dose and process configuration. Fed-batch SSF using a combined feed of substrate, enzymes and yeast adapted to inhibitors enhanced cell viability in a high solids process (20% WIS) and achieve 40 g/l ethanol (Koopram and Olsson, 2014), although the economic balance of cost of additional operations (continuous yeast propagation, high amount of enzymes fed into the process) was not provided. The performance of cellulolytic enzymes can be also enhanced by addition of polyethylene glycol, which helps to reduce the adsorption of enzymes to lignin. However, as noted by Canella and Jorgensen (2014), the economic feasibility of this approach is doubtful. Mathematical modelling and computer simulation can be exploited to maximize ethanol production in SSF, as demonstrated by Oh et al. (2000), or by Mutturi and Lidén (2014) who developed the nonisothermal SSF process following a changing temperature profile during SSF. However, the final ethanol concentration remained low (14.87 g/l and 13.6 g/l, respectively). This indicates that several parameters (optimal pretreatment, fed-batch operation, optimum (as high as possible) substrate loading, appropriate enzyme dosing, suitable microorganism, optimum cultivation condition,…) should be combined to achieve higher ethanol concentrations at a reasonable process price. As seen from Tab. II, where results published within the last two years, together with selected processes published previously are compared (only SSF working with natural substrates are listed while papers dealing with carboxymethylcellulose, Avicel or filter paper are omitted), the yield of ethanol was usually lower compared to SHF processes and the concentration of ethanol achieved was usually below 40 g/l, which is at the limit for economic distillation. The exceptional and promising result with formalin pretreated oil palm empty bunches in an SSF process, where almost 85 g/l of ethanol were achieved and productivity was acceptible, warrants further research. 2.3. Simultaneous saccharification with delayed inoculation
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Several of the problems of SSF can be eliminated, or at least reduced, by integration of a prehydrolysis step into the SSF process. Although different names of this process have been used, e.g. semi-simultaneous saccharification and fermentation, abbreviated as SSSF or S-SSF (Goncalves et al., 2014; Zhang et al., 2014; Li et al., 2014), prehydrolysis and simultaneous saccharification and fermentation, PSSF (Lopéz-Linares et al., 2014), presaccharification of simultaneous saccharification and fermentation, P-SSF (Tan et al., 2013), simultaneous saccharification and fermentation with delayed inoculation, dSSF (Paulová et al., 2014), liquefaction plus simultaneous saccharification and fermentation, L+SSF (Castro et al., 2014) or non-isothermal simultaneous saccharification and fermentation, NSSF (Mutturi and Lidén, 2014), the principle is essentially the same: the broth prepared from chemically or physically pretreated biomass is firstly prehydrolysed with cellulases at the optimum temperature (4555°C depending on the enzyme mixture) then cooled to the temperature meeting the SSF condition, and immediately inoculated without enzymes being inactivated. The main purpose of this process is to overcome the discrepancy in the temperature optima for enzymes and microorganisms and thus increase the rate of cellulose hydrolysis and its conversion into glucose in the early stages of the process, to eliminate glucose limitation at the beginning of SSF (and thus increase the rate of ethanol production), and decrease the viscosity of material prior to inoculation (which is advantageous mainly for processes with high solid loadings). Theoretically, this method combines the advantages of both SHF and SSF processes – the rate of enzymatic hydrolysis is not reduced by a suboptimal temperature, released glucose does not accumulate above the critical value that would entrain end product inhibition, and the rate of ethanol production is not limited by a low concentration of carbon source. Although many papers using this method have been published recently, the results are hard to compare (Tab. III) because the success rate is affected by many factors such as type of material, method of pretreatment, composition of enzyme cocktail and dose, solids content, conditions for the subsequent SSF process (temperature, pH, type of microorganism and its sensitivity to toxic compounds), its configuration (batch, fed-batch) and especially in this case, by the length of prehydrolysis. Although the duration of prehydrolysis is a factor that affects yield, productivity and final ethanol concentration, and thus consequently the final evaluation of the process, it is rarely optimized, as seen from many studies where 24 h of prehydrolysis were applied without any clear relationship with the main process parameters (Tab. III). Because of this (and also other effects such as type of material, enzymatic mixture, etc.), some studies (e.g. Mesa et al., 2011; Huang et al., 2014; Zhang et al., 2014) showed that SSF with delayed inoculation was superior to SSF and SHF, while others (e.g. Lopéz-Linares et al. 2014) did not see any improvement. As reported by Paulová et al. (2014), the duration of the presaccharification period considerably influences productivity of the process; although ethanol yield and its final concentration did not differ, 12 h presaccharification resulted in 2.3 times increased productivity of ethanol from acid pretreated wheat straw compared to SSF (because the length of the process was shortened by 60%) whereas lengthening the presaccharification period to 24 h (which is the time used in most studies) resulted in a 25% loss in productivity and SHF was, in this case, superior to dSSF. Although other authors have also reported that ethanol yields in SSF with presaccharification did not dramatically change compared to SSF alone (Manzares et al., 2011), Hoyer et al. (2014), reported that the prehydrolysis period especially influenced ethanol yield, with 32.6%, 32.7% and 58.3% of theoretical being achieved for 4, 8 and 22 h prehydrolysis, respectively; all yields were superior to the simple SSF process. As shown in Table III, the presaccharification period cannot be generalized because it differs for each combination of substrates, their concentrations, the type of pretreatment and the microbial strain. As discussed for other process configurations, ethanol concentrations exceeding the limit of 40 g/l are rather exceptional and are achieved mainly on easily manipulated substrates such as
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waste paper or paper sludge dissolved in buffer. An ethanol concentration of 91.5 g/l, which is comparable with 1st generation bioethanol, was achieved by a combination of 12 h presaccharification and 2h of sequential addition of both paper sludge and enzymes in a fedbatch SSF process lasting for more than 400 h (Elliston et al., 2013). Although a high concentration of ethanol was achieved, the profitability of this process due to repeated enzyme addition is doubtful and the productivity was low due to the length of the process. Generally, productivity of SSF with delayed inoculation, as reported in the literature, is often overestimated because it is calculated from the second part of the process (SSF) and the presaccharification period is omitted. Data presented in Table III has thus been recalculated to include the real duration of the process. Similarly to other processes discussed in this review, the amount of substrate should be carefully calculated because it can considerably influence process efficiency due to the “solid effect”, where the conversion of cellulose and the ethanol concentration decrease as the solid content increases (Kristensen et al., 2009); e.g. as shown by Lopéz-Linares et al. (2014), increased solid content from 7.5 to 15% achieved 85% more glucose in the 24 h presaccharification step and the final ethanol concentration was increased by 80%, while further solid addition (20% WIS) negatively affected both the conversion of cellulose and the ethanol yield, and practically did not improve the volume of ethanol produced. Similarly, Huang et al. (2014) reported a significant decrease in ethanol yield if the substrate (hydrothermally pretreated pomelo peel) was preconcentrated in batch from 5 to 14% WIS, although despite the worsened yield, they more than doubled the final concentration of ethanol (9.3 g/l and 20.8 g/l for 5 and 14% WIS, respectively). As described by Xiros and Olsson (2014), in the case of a process with a high solid content, many parameters must be combined and optimized for any particular configuration to achieve an optimum result; in SSF with a 24 h presaccharification step, the best results were achieved when detoxification with a reducing agent was applied prior to the process, while in SHF, nutrient supplementation worked better than detoxification. Among modifications of the classical SSF, the process of employing simultaneous saccharification, filtration and fermentation (SSFF) should be mentioned (Ishola et al., 2013). In this process, enzymatic hydrolysis is carried out under optimum enzyme conditions. Broth is then pumped through a membrane into the bioreactor where fermentation takes place and is then recycled back to the hydrolysis vessel while yeast cells are retained in the bioreactor. This permits reuse of the yeast and at the same time achieves comparable results to SSF, although the main problem with this process is clogging of the cross-flow membrane. A similar concept was demonstrated by Viola et al. (2013), who used a two chamber bioreactor to combine the advantages of SHF and SSF processes. In individual parts of the bioreactor, divided by a porous barrier, enzymatic hydrolysis and fermentation are carried out under optimal conditions, enabling a 20% increase in ethanol yield compared to classical SSF and keeps lignin separated from the fermentation broth. However, the final concentration of ethanol achieved in this process is far below the 40 g/l that is considered a lower limit for economic distillation (Tab. III). 3.4 Co-fermentation of hexose and pentose sugars Lignocellulose decomposition/digestion, independent of the material origins and method of degradation, results in a mixture of hexoses (mainly glucose) and pentoses (mostly xylose but also arabinose). An example of such a mixture of saccharides is spent sulfite liquor (SSL), a common waste stream from sulfite wood processing to pulp. SSL, which can usually be included in several modified processes, contains a mixture of fermentable saccharides originating from cellulose and hemicellulose i.e. glucose, galactose, mannose, xylose and arabinose, where the total saccharide concentration does not exceed 50 g/l. In addition, SSL
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contains acids, alcohols and free and bound sulfur dioxide, which can hamper its use. Therefore SSL is often detoxified by different methods such as overliming, SO2 stripping with steam, or precipitation of sulfates. When S.cerevisiae was used for SSL fermentation (Novy et al., 2013), the final ethanol concentration, maximum theoretical yield and productivity, were 20 g/l, 86% and 0.1 g/l/h, respectively. These values, with the exception of productivity, are very similar to those (20 g/l, 88% and 0.44 g/l/h) obtained using Pichia stipitis (Nigam 2001) and probably represent the maximum achievable values considering the initial saccharide concentration of the SSL. More detailed information on ethanol produced from SSL can be found in a recent review (Pereira et al., 2013).
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3.4.1 Glucose and xylose co-fermentation The xylose content in lignocellulose hydrolysates varies according to the condition and origin of the material (a high xylose content can be found especially in birch wood). Traditional ethanol producers, S. cerevisiae and Z. mobilis prefer hexose saccharides and most of their strains do not consume pentoses at all. Efficient adaptation or modification of S.cerevisiae for xylose fermentation includes the following steps: (1) xylose uptake and prevention of carbon catabolite repression (CCR) caused by glucose If genes for xylose metabolism are incorporated into either S. cerevisiae or Z. mobilis, both microorganisms still more rapidly consume glucose from a mixture of glucose and xylose because of the absence/low affinity of a xylose transporter protein in the cells (Kim et al., 2010). To overcome this problem and to achieve simultaneous consumption of hexose and pentose saccharides, it is desirable to keep the glucose concentration low by maintaining a controlled level of cellulases in the SSF system (Olofsson et al., 2010). Another approach is to insert and express the gene for P. stipitis xylose transporter SUT1 in a genetically modified, xylose-assimilating strain of S. cerevisiae. This approach resulted in successful cofermentation of a glucose/xylose mixture (50 + 50 g/l) and an ethanol concentration of 41 g/l, productivity of 0.7 g/l/h and 82% of maximum theoretical yield were achieved (Katahira et al., 2008). However, this is probably a rare example of successful glucose/xylose cofermentation to ethanol because in other cases, where different xylose transporters or different yeast strains were used (Runquist et al., 2010; Moon et al., 2013; Tanino et al., 2012), a maximum ethanol concentration of 10 g/l was obtained. (2) expression of xylose isomerase or biotransformation of xylose to xylulose The first step in xylose metabolism by xylose-utilizing yeasts is the gradual transformation of xylose to xylulose through xylitol, by xylose reductase and xylitol dehydrogenase. However, these enzymes are normally absent in S.cerevisiae and the main issue preventing use of these enzymes in a genetically modified yeast is that they both function under aerobic conditions due to the formation of NADH, which is continuously removed by oxidation. Modification of S.cerevisiae by transformation and expression of xylose isomerase from the anaerobic fungus Piromyces sp. has therefore become standard , resulting in anaerobic xylose utilization (Kuyper et al., 2004; Kuyper et al., 2005). In addition, xylose can be transformed to xylulose in vitro by addition of xylose isomerase. This process was proposed in 1981 (Gong et al., 1981a) and achieved 20 g/l of ethanol from 120 g/l of xylose, which was partially converted to xylulose by addition of Sweetzyme Q. However, a portion of xylose was transformed to xylitol (this is more likely under oxidative conditions but can occur even during fermentation). This method has been modified recently (Yuan et al., 2011) when the authors used commercially available S.cerevisiae strains in high loads (up to 200 g/l of yeast biomass) for fermentation of glucose/xylulose mixtures, with the addition of sodium azide as a respiratory inhibitor. In this way, up to 73 g/l of ethanol with 81% theoretical yield was obtained. Nevertheless, such a high yeast dose is not applicable in a scaled-up process.
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In addition to genetic modification, further progress with modified S.cerevisiae strains can be achieved by evolution or adaptation techniques (Novy et al., 2013; Novy et al., 2014). An effective way to modify Z. mobilis for glucose/xylose utilization was demonstrated by Zhang et al. (1995), who combined the original Entner-Doudoroff pathway with the non oxidative part of the pentose phosphate pathway. By this method, 25 g/l of ethanol with a productivity of 0.8 g/l/h and 95% of theoretical maximum yield was achieved from a glucose /xylose (1:1) mixture. Different adaptation approaches (Agrawal et al., 2011; Mohagheghi et al., 2014), in which Z. mobilis was gradually accustomed to increasing xylose concentration, gave similar results. Escherichia coli, which can utilize both glucose and xylose naturally, may be modified to produce ethanol in high quantities. This approach was chosen by Ohta et al. (1991) who inserted pyruvate decarboxylase and alcohol dehydrogenase genes originating from Z. mobilis into E. coli and were able to ferment solutions containing 10% glucose or 8% xylose, but glucose/xylose mixtures were not tested. To achieve simultaneous utilization of glucose/xylose mixtures it is necessary to eliminate CCR, to control transport into the cell and to balance the metabolic pathways for both saccharides. Successful demonstration of this approach is described by Chiang et al. (2013) who achieved about 30 g/l of ethanol with a productivity 1.9 g/l/h and 97% of theoretical yield from a glucose/xylose (1:1) mixture.
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3.4.2 Co-fermentation of different saccharide mixtures To overcome glucose CCR and prevent diauxic growth on different substrates, S.cerevisiae can be engineered to utilize cellobiose instead of glucose. Ha et al. (2011a) modified the yeast to utilize cellobiose and xylose, resulting in an improvement in ethanol productivity (from 0.27 to 0.65 g/l/h) compared to utilization of xylose as a sole carbon source. An ethanol concentration of 48 g/l, with a productivity of 0.79 g/l/h was reached if 130 g/l of a sugar mixture containing glucose, cellobiose and xylose was used. For marine biomass, S.cerevisiae was modified to simultaneously consume cellobiose and galactose, resulting in an ethanol concentration of up to 27 g/l and productivity of 0.75 g/l/h (Ha et al., 2011b). In addition to traditional ethanol producers, other microorganisms such as P. stipitis can be used but their common main disadvantage is a low tolerance of ethanol and lower productivity compared with S.cerevisiae (Agbogbo and Coward-Kelly, 2008). In addition, selected bacteria, e.g. lactobacilli (Kim et al., 2009; Kim et al. 2010) or clostridia (Patakova et al., 2013), and even some yeasts such as Candida shehatae (Kim et al., 2010) are characterized as CCR-negative and can utilize hexose and pentose saccharides simultaneously, which is more convenient regarding process productivity in lignocellulose fermentation. However utilization of these microorganisms for ethanol production requires further research. It has recently been published that the basidiomycete Trametes versicolor can utilize glucose, mannose, fructose, xylose, cellobiose and maltose for ethanol production, with yields ranging from 0.44 to 0.49 g/g of saccharide (Okamoto et al., 2014). The adapted ascomycete Spathaspora passalidarum can also produce up to 39 g/l ethanol (with a productivity of 0.8 g/l/h and 74% of the maximum theoretical yield) by co-fermentation of glucose, xylose and cellobiose contained in a hardwood hydrolysate (Long et al., 2012). 3.4.3 Microbial co-culture and sequential fermentation of saccharides The ethanol producers, S. cerevisiae or Z. mobilis can be used together with a pentoseutilizing microorganism for fermentation of saccharide mixtures. The most common solution is to use P. stipitis as the second member of the microbial community (for recent review of glucose/xylose mixtures used for ethanol co-fermentation see Chen 2011) but usually the ethanol yield did not exceed 25 g/l (Fu et al., 2009; Gupta et al., 2009; Yadav et al., 2011).
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Theoretically, it is possible to consider the sequential use of different microorganisms where S. cerevisiae will first consume glucose for ethanol production and then other microorganisms will utilize the remaining pentoses. This approach was applied to chemically pre-treated rice straw (Li et al., 2011) when, after glucose consumption, S.cerevisiae was inactivated by heat and subsequently P. stipitis was inoculated for xylose fermentation. The final ethanol concentration in this experiment was 21.1 g/l with 73% of maximum theoretical yield and productivity of 0.2 g/l/h.
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3.5 Consolidated bioprocessing Consolidated bioprocessing (CBP) can be defined as a one-step process in which a feedstock is directly converted into a desired product by a special microorganism or microbial consortium without requiring pre-treatment of the feedstock (Fig. 4). The term can be applied to any raw material and any product, but is usually associated with lignocellulosic biomass and ethanol. The most challenging task with CBP is selection or design of a suitable microorganism/microbial consortium that must express appropriate hydrolytic enzymes matching the lignocellulosic feedstock, and produce ethanol. Strictly speaking, the raw material for CBP should not require any special physical, chemical or enzyme pre-treatment and particle size reduction should be sufficient. However, a number of authors label their processes as CBP even if they add saccharifying enzymes or use chemical pre-treatment of the feedstock. Although these approaches can improve process parameters they also increase the processing cost. Microorganisms to be used in lignocellulosic CBP can be categorized into two groups: cellulase producers (category I CBP producers) or ethanol producers (category II CBP producers). The difficulty is that microorganisms from either category cannot be used directly as wild type strains and require strain evolution involving adaptation, mutation, metabolic engineering, targeted or random modifications, or a combination of these approaches. The most common category I CBP producers include cellulolytic thermophilic bacteria such as Clostridium thermocellum (Lynd et al., 2005), Geobacillus thermoglucosidans, Thermoanaerobacterium saccharolyticum or Thermoanaerobacter mathranii (Taylor et al., 2009) and cellulolytic fungi (Amore and Faraco, 2012) such as Trichoderma reesei (Huang et al., 2014) or Paecilomyces variotii (Zerva et al., 2014). Other organisms such as the mushroom Flammulina velutipes (Kaneko et al., 2012; Maehara et al., 2013), or anaerobic filamentous fungi (Youseef et al., 2013) have some potential for CBP but until now, ethanol yields using these organisms are very low and therefore additional intensive research is required. Nevertheless, it cannot be excluded that further promising category I CBP producers will be isolated from natural sources in future. Category II CBP producers consist of engineered traditional ethanol producers such as S. cerevisiae (den Haan et al., 2013; Hasunuma and Kondo, 2012; Khramtsov et al. 2011; Wen et al. 2010), Z. mobilis (He et al., 2014; Linger et al., 2010) and also Kluyveromyces marxianus (Chang et al., 2013; Hong et al., 2007). Naturally occuring and designed microbial consortia combining category I and II CBP producers, were also tested. Using a consortium consisting of T. reesei, S. cerevisiae and Scheffersomyces stipitis (Brethauer and Studer, 2014), up to 67% of maximum theoretical ethanol yield was achieved from an acid pretreated wheat straw slurry, but the maximum ethanol concentration was about 7 g/l. Another consortium comprised of Clostridium phytofermentans and yeast (Zuruf et al., 2013) could convert cellulose to ethanol with 50% efficiency, reaching an ethanol concentration of up to 22 g/l, but with very low productivity. Selected results obtained using both categories of CBP producers, microbial consortia and two step sequential processes (the use of microbial consortia can also approach a sequential, twostep process using two microorganisms with cellulolytic and ethanologenic capabilities) are
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presented in Table IV. Only results where the concentration of ethanol reached at least 1 g/l are shown in Table IV, while processes where the final ethanol concentration was below this value were not included. Despite the exponentially increasing number of papers dealing with lignocellulosic ethanol production, including CBP, it is surprisingly difficult to find papers presenting „hard data“ on ethanol concentrations, yields and productivity values. Looking at Table IV, it is evident that some very good results (Christakopoulos et al., 1989; Gong et al., 1981b; Hahn-Hägerdahl and Häggström, 1985; ), comparable with current data (Argyros et al., 2011; Xu et al., 2010), were achieved in the 1980s, during the previous wave of interest in utilization of lignocellulosic materials for ethanol production. What seems to link current results with older significant data are good luck (and patience) with strain isolation/acquisition and once more good luck in strain improvement using both traditional and advanced techniques. Nevertheless, both then and now, the competitiveness of the CBP and its variants with traditional S. cerevisiae ethanol production is far too low, especially regarding process productivity. Current standard values obtained in distilleries during ethanol production using saccharose- or starch- containing crop fermentation by S. cerevisiae are also given for comparison in Table IV.
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2.6. Use of immobilized biocatalysts (enzymes and cells) Other approaches to decrease expenses associated with converting the rigid recalcitrant structure of lignocellulose to a valuable product such as ethanol include reducing input costs, particularly of cellulolytic enzymes and the production strain. Both can be efficiently immobilized to allow their separation and subsequent reuse in consecutive processes. The potential and advantages, together with drawbacks, of an immobilized system, in comparison with a suspension configuration are discussed in the following paragraphs.
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2.6.1. Immobilization of cellulolytic enzymes Traditional enzyme immobilization is based either on attachment on/in solid particles and/or enzyme cross-linking. Various suggestions for biocalyst immobilization have been reported for both individual cellulolytic enzymes (Verma et al., 2013; Wei et al., 2013) and a multicomponent enzyme complex (Abraham et al., 2014; Ince et al., 2012). To design an enzyme immobilization system, the nature and complexity of raw lignocellulosic material must be considered, and although pretreated, it is still a suspension of insoluble materials that exclude the use of conventional separation techniques such as filtration and centrifugation (Battacharya and Pletschke, 2014). The main immobilization methods, such as entrapment in a polymer matrix (Ortega et al., 1998; Ungurean et al., 2013), adsorption onto a solid carrier (Khoshnevisan et al., 2011; Sinegani and Sinegani, 2013), covalent linking to a solid support (Su et al., 2012; Verma et al., 2013), affinity interactions (Alftrén et al., 2013) and cross-linking of enzyme aggregates (CLEAs) or their combination (Sutarlie and Yang, 2013) were reported recently. In addition to facilitated separation, immobilization can lead to beneficial changes in enzyme characteristics (Mateo et al., 2007), e.g. increased stability is often mentioned together with changes in pH optima (Shimizu and Ishihara, 1987) and thermal characteristics (Tab. V), as well as changes in selectivity (Cao, 2005). In particular, an increase in thermal stability extends application possibilities, and the majority of authors agree that although the temperature optimum remains constant or varies slightly, at higher temperatures immobilized enzymes retain their activity for a longer period. A comparison of thermal properties of free and immobilized cellulolytic enzymes from some very recent experiments is summarized in Table V. Higher stability of immobilized enzymes may apply not only to hydrolysis at higher temperatures but also in the case of processes run under non-optimal conditions, e.g. SSF
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(ethanol, temperature) where several fold higher yields (up to 2.3) compared with soluble cellulases can be achieved (Lupoi and Smith, 2011). Abraham et al. (2014) achieved 93% and 89% saccharification of hemp hurd biomass after 48 h, employing cellulase bound on magnetic nanoparticles and free enzymes, respectively. Unfortunately, in most cases, a reduction in specific enzyme activity occurs after immobilization to an insoluble carrier (Chim-anage et al., 1986; Sutarlie and Yang, 2013; Tébéka et al., 2009; Wang et al., 2013). Reduction in activity of an immobilized enzyme could be caused by folding of cross-linked structures, diffusional difficulties of the large substrate (Shimizu and Ishihara, 1987), alterations in enzyme conformation (Tébéka et al., 2009; Yu et al., 2012) together with changes in the accessibility of the catalytic domain (Sutarlie and Yang 2013) or could be induced by steric hindrance of the matrix that prevents binding of a high molecular weight substrate to the enzyme. The latter can be avoided by introduction of a spacer arm that places the enzyme at some distance from the matrix (Chimanage et al., 1986). On the other hand exceptions can be found, e.g. Bhattacharya and Pletschke (2014) reported 1.35 fold higher activity compared to free enzyme for calcium magnetic cross-linked xylanase. The biggest advantage of immobilized enzymes is their ability to be recovered and reused, but from the reported data it is evident that enzyme activity of both free and immobilized biocatalysts more or less decrease with increasing time of saccharification, temperature and the number of cycles. This effect is a result of a variety of factors with different degrees of impact on final activity, including, in particular, enzyme detachment, protein denaturation and loss of matter during passage (Alftrén and Hobley, 2013). The greatest influence on the loss of activity would probably be temperature of hydrolysis and time of delay. Whereas Shimizu and Ishihara (1987) reported an appreciable activity of immobilized Trichoderma and Aspergillus cellulases after 60 days at 40°C, from Table V it is obvious that enzyme activity falls rapidly, in the order of hours, with increased temperature of hydrolysis, although more slowly than that of free enzyme. A certain degree of leakage of enzyme from binding structures in an immobilized system also occurs (Liang and Cao, 2012). Moreover, cellulolytic systems are more complicated because endoglucanases and cellobiohydrolases contain cellulose binding domains next to the catalytic core (Alftrén and Hobley, 2014; Gokhale and Lee, 2012; Linder et al., 1995), with a cellulose affinity that can be higher than that of the enzyme-support. For the same reason, recycling of cellulases should involve a desorption step (Lindedam et al., 2013). Objective evaluation of the recycling of cellulases immobilized by different methods is almost impossible due to differences in time, temperature and substrate used in each experiment. For example Verma et al. (2013) achieved 80% retention of enzymatic activity for β-glucosidase after 8 cycles and 50% activity after 16 cycles, whereas Alftrén and Hobley (2013) reported approx. 50% reduction of β-glucosidase activity after 4 cycles. At first sight this is an appreciably lower number but on close inspection, the duration of each cycle in the first example (using a synthetic substrate) was 10 minutes, while in the second case one cycle lasted for 24 h and a natural substrate was used. Similarly, for evaluation of loss of enzyme activity, approximately 20% loss of activity was detected by Su et al. (2012) after 11 cycles, but after only 5 cycles by Liang and Cao (2012), the first experiment was run for only 20 minutes per cycle with carboxy-methyl-cellulose (CMC) whereas the second was cycled for 1 hour each using a natural substrate. It can be generalized that recyclability decreases with increasing temperature and time of reaction, and varies noticeably with the type of substrate; a synthetic substrate such as CMC or Avicel provides significantly better results than crude lignocellulolytic biomass. As demonstrated by Sutarlie and Yang (2013) with cross-linked cellulase aggregates adsorbed on silica, the effect of substrate is significant; when synthetic
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substrate (CMC) was used, activity was similar to that of free enzyme but was significantly (~ 70%) decreased with a natural substrate (palm oil fibres). Another consideration is that the catalytic part of an immobilized enzyme scarcely reaches more than 10% of the total mass, leading to dilution of volumetric activity. In practice, actual values for cellulolytic enzymes vary a lot, with most well below this value, reaching approximately 10-30 mg/g (Alftren and Hobley, 2013; Khoshnevisan et al., 2011; Shimizu and Ishihara 1987). Very high immobilization capacities for cellulases have also been reported, reaching 112.3 mg/g immobilized on Fe3O4-chitosan (Zang et al., 2014) or even 225.5 mg/g attached to Fe3O4@SiO2 microspheres anchored with Cu2+ (Li et al., 2013). To enhance volumetric activity, higher payloads (mass of immobilized enzyme/ mass of carrier) or cross-linked enzyme aggregates (CLEAs) should be applied (Cao, 2005). Employing CLEAs without carrier is hardly feasible for lignocellulose due to the small particle size, whereas the use of CLEAs adsorbed to different carriers was successful (Nguyen and Yang, 2014; Sutarlie and Yang, 2013). Another approach to promote higher payloads is to increase the specific carrier surface area; smaller particles generally possess a larger surface area but there must be a balance between the available surface and separability of smaller particles; in this regard, the use of magnetic nanoparticles is beneficial (Khoshnevisan et al., 2011) due to the magnetism of their inorganic core, where simple concentration of nanoparticles can be achieved by an external magnetic field (Alahakoon et al., 2012; Cho et al., 2012). For porous carriers with a larger surface area and a higher enzyme loading capacity, the increase in specific area is inevitably connected with a decrease in pore size (Cao, 2005) that leads to diffusional limitations. Realistic assessments of glucose yield produced by immobilized enzymes compared with a suspension system is complicated because the vast majority of articles present data in relative percentages related to different variables; even though these percentages seem promising, specific data indicating real values on glucose release (concentration per time) are often omitted. A few available values correlate with one of the main drawbacks of lignocellulose biomass utilization - a very low concentration of reducing sugars even if synthetic (CMC, Avicel, filter paper) substrates are used. Tébéka et al. (2008) achieved 2.35 g/l of glucose after hydrolysis of Avicel using cellulases adsorbed on Si wafers. Alftrén and Hobley (2014) has reported the highest bead activity of 2.8 g/kg/min (reducing sugars per bead mass per time) for microcrystalline cellulose digested by cellulases immobilized on magnetic particles activated by cyanuric chloride. Better results were reported for enzyme retention in a membrane reactor (Yang et al., 2009) where a 200% increase in the conversion of pretreated corn stalk compared to a traditional arrangement, has been achieved; but even under these conditions (100 g/l dry weight, D=0.65 1/h) the concentration of reducing sugars was less than 10 g/l and during the process continued to decline, to a stable concentration of 2 g/l. 2.6.2. Immobilization of microbial cells Compared to the cost of enzymatic hydrolysis, expenses associated with microbial transformation of glucose to ethanol are significantly lower, but still must be taken into account. Ethanol producing yeast or bacterial cells can be immobilized similarly to cellulolytic enzymes, leading to savings in both time and the cost of cell cultivation. The commonly used immobilization techniques for microbial cells are attachment or adsorption onto a solid surface, entrapment within a porous matrix, mechanical containment behind a barrier or self-aggregation of cells by flocculation (Mussatto et al., 2010). A widely exploited immobilization strategy is the encapsulation of microorganisms in alginate beads, where the concentration of CaCl2 can influence the rate of ethanol production via altered matrix permeabilities for substrate as well as for product (Franco et al., 2011). As reported for yeasts encapsulated in 3.5 and 8% calcium alginate, the glucose utilization rate
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(50 g/l, synthetic medium) halved while the ethanol yield was 10% higher (64% and 74% of theoretical values, respectively). A higher tolerance to toxic compounds present in hydrolysates due to a lower diffusion rate into the matrix core, mitigation of inhibitory effects by absorption to the carrier matrix, or by the activity of outer cells is often reported for immobilized cells. Due to this effect, immobilized cells can be applied in processes where free cells fail to grow, as reported by Yamashita et al., 2008 for Z. mobilis immobilized in alginate and grown on paper sludge. Unfortunately, a noticeable decline in productivity after repeated batch fermentation was observed in this case. The main drawback of alginate beads seems to be their stability, fragmentation, cell leakage or even complete dissolution (Mathew et al., 2013 Singh et al., 2013). On the other hand some authors have reported relatively good reusability, e.g. Wirawan et al., 2012 successfully repeated five 10 h cycles on 20 g/l glucose without any apparent change in ethanol yield or productivity, and Zhao and Xia (2010) reported that agar immobilized S. cerevisiae ZU-10 cells were maintained after six 24 h cycles with 100% conversion of glucose and 93% conversion of xylose. In addition to alginate, other materials can be used for cell entrapment such as the more mechanically stable Lenticats® (Mathew et al., 2013), polyvinyl alcohol (PVA) (Wirawan et al., 2012) or agar-agar (Lebeau et al., 2007; Singh et al., 2013). Apart from encapsulation, traditional immobilization of microorganisms on solid supports can be used, including a variety of natural materials such as spent grains (Mathew et al., 2013), or sugarcane bagasse (Singh et al., 2013). However, cells immobilized on this type of substrate cannot be employed in simultaneous processes where cellulolytic enzymes are present due to the risk of support dissolution. An advantageous method of immobilization appears to be self-flocculation of yeast, where cells form flocs with an appropriate size range that can be effectively separated by sedimentation. There is no extra consumption of supporting material and simultaneously effective ethanol production can be achieved by maintaining the cell concentration at the required level with little affect on cell growth (Bai et al., 2008). Brandberg et al. (2007) demonstrated that separation of S. cerevisiae cells in a settler was the most efficient system compared with immobilization in calcium alginate, and cell recirculation by filtration, achieveing 98% hexose utilization and a volumetric ethanol production rate of 2.58 g/l/h at D=0.10 1/h for acid lignocellulose hydrolyzate supplemented with enzymatically hydrolyzed wheat flour. Under these conditions, cell number was 32 times higher in the bioreactor than in the outflow. Nevertheless wheat particles and cells were distributed in the settler inhomogenously due to the faster sedimentation of wheat, resulting in a reduced reflux of cells back to the reactor, which contributed to rapid wash out at D=0.20 1/h. Some new approaches have also been proposed for the effective utilization of cellulose, e.g., expression of endo-glucanase gene egX in S. cerevisiae and its display on the cell surface by fusion with aga2 encoding the binding subunit of the cell wall protein α-agglutinin (Yang et al., 2013). The highest cellulase activity and bioethanol concentration achieved on CMC were 2.36 U/g (dry weight of cells) and 3.92 g/l, respectively. Another system was introduced by Liu et al. (2012), where three different microorganisms were co-immobilized in a specially constructed bioreactor with separated aerobic and anaerobic chambers for consecutive hydrolysis and ethanol production, but the final values on CMC were quite poor, with only 11.2% conversion to reducing sugar and an ethanol concentration of only 0.56 g/l. Apparently, cell immobilization gives more encouraging results than immobilization of cellulases; while cell immobilization leads mainly to improvements in ethanol production through resistance to toxic compounds present in lignocellulosic hydrolyzates, the opposite, a decrease in enzymatic activity, occurs after cellulase immobilization, together with difficulties in separation from the lignocellulosic matter. However, considering the price of cellulases, and recirculation possibilities, active research in this field may result in a future prospective
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3. Conclusion The configuration of individual technological steps plays an important role in the efficiency of a lignocellulosic ethanol production process. Although the recent trend is for consolidation of unit operations, to propose a generally valid optimal design suitable for many substrates is not feasible because all process configurations have advantages and disadvantages. In the case of separate hydrolysis and fermentation (SHF), high ethanol yields (usually exceeding 80% of theoretical value) are often achieved and even yields approaching maximum are not exceptional, especially for substrates containing lower amounts (less than 10%) of water insoluble solids. This is logical because the substrate is liquefied before fermentation and therefore the inoculum (usually yeast) is not exposed to harsh conditions (high viscosity, lack of free water, problems with mass transfer) as in simultaneous processes. Since the conversion of cellulose into glucose is influenced by many factors (type of substrate, composition of enzyme cocktail, dosing, WIS) the results are hard to compare and differ for different substrates and SHF conditions, although yields of glucose approaching maximum have been reported for substrates with lower WIS. On the other hand, the yield of ethanol achieved in simultaneous processes (SSF) is lower than SHF (values exceeding 80% of theoretical yield are exceptional) but cellulose conversion is probably more efficient due to elimination of end product inhibition of cellulolytic enzymes (since all processes are combined, and released glucose is immediately consumed, this value cannot be calculated properly). Similarly to SHF, SSF processes usually suffer from low productivity that can be partly improved by integration of a presaccharification step (as in case of dSSF processes), but the duration should be carefully calculated. Consolidated bioprocesses employed for ethanol production are difficult to evaluate since their design and combination of microbial strains differ. Although the ethanol yield can approach theoretical values, the final ethanol concentration and productivity are usually lower than SHF, SSF and dSSF when natural substrates (rather than pure cellulose) are used. Despite enormous progress that has been achieved in 2nd generation ethanol technologies, as shown in this review, it is clear that the factory price of lignocellulosic ethanol is higher than the price of 1st generation ethanol. This is partly due to additional technological steps (and thus higher energy demands), higher dosing of enzymes (and their price), and partly by the character of the substrate not allowing an increased concentration of sugars comparable with substrates originating from starch or molasses. In contrast, with 1st generation raw materials, the price of waste lignocellulosic materials is much lower and this could partly contribute to reducing the difference in bioethanol prices. On the other hand, the problem of 2nd generation ethanol cannot be assessed only in terms of price. In order to fulfil ambitious political targets of Directive 2009/28/EC, it has been estimated that 40 million hectares will be needed to grow biomass for bioenergy (De Wit and Faaij, 2010), meaning that large amounts of currently arable land would need to be moved from food to biofuel production. Diversification of biofuel feedstocks, including inedible ones, is thus necessary to maintain food independency of EU countries (Simon et al., 2010). A transition to cellulosic ethanol, exploiting agriculture wastes, energy crops grown on pastures, and currently unused land is the next step (Eggert and Greaker, 2014). In addition, it was reported that reductions in emissions from cellulosic ethanol could be almost 100%, which is an improvement over most first generation ethanols, with the exception of sugarcane ethanol produced in Brazil (Eggert and Greaker, 2014). Thus, governmental interventions with production subsidies, or the
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5. Acknowledgement This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic, projects Kontakt ME10146 and project Nol MSM 6046137305.
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Fig. 1 Overview of unit operations of lignocellulosic ethanol production Fig. 2 Unit operations of separate hydrolysis and fermentation (SHF) process design Fig. 3 Unit operations of simultaneous hydrolysis and fermentation (SSF) process design Fig. 4 Unit operations of co-fermentation of hexose and pentose sugars process design Fig. 5 Unit operations of consolidated (CBP) process design
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SC R
Figure 1
MA
NU
SC R
IP
T
ACCEPTED MANUSCRIPT
AC
CE P
TE
D
Figure 2
MA
NU
SC R
IP
T
ACCEPTED MANUSCRIPT
AC
CE P
TE
D
Figure 3
MA
NU
SC R
IP
T
ACCEPTED MANUSCRIPT
AC
CE P
TE
D
Figure 4
D
MA
NU
SC R
IP
T
ACCEPTED MANUSCRIPT
AC
CE P
TE
Figure 5
ACCEPTED MANUSCRIPT
Rapeseed straw, acid pretreated
S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Rapeseed straw, acid pretreated
S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Rapeseed straw, acid pretreated
S. cerevisiae, 34°C, 96 h
Wheat straw, hydrothermally pretreated
S. cerevisiae, recombinant , 120 h
Corn pretreated dilute acid
71.0
Productivity (g/l/h)
Reference
15.5
84.0
0.16
López-Linares et al., 2014
65.7
30.5
87.8
0.32
López-Linares et al., 2014
64.5
39.9
91.6
0.42
López-Linares et al., 2014
~95
NP
~ 60
73.1
~0.36
Canella and Jorgensen, 2014
stover with
65.0
88
30.0
93.0
0.16
Uppugundla al., 2014
et
S. cerevisiae, recombinant 120 h
Corn stover ionic liquid pretreated
72.0
100
~40
90.0
~0.21
Uppugundla al., 2014
et
S. cerevisiae, recombinant 120 h
Corn stover AFEX pretreated
60.0
79
~40
98.0
~0.21
Uppugundla al., 2014
et
AC
Max. ethanol concentration (g/l)
IP
S. cerevisiae, 35°C, 24 h, centrifugation prior the fermentation
Conversion of cellulose into glucose (%) 70
CR
Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 7% WIS Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 15% WIS Cellic CTec3 supplemented with ßglucosidase and Tween, 50°C, 72 h, batch 20% WIS Cellic CTech 2, addition of polyethyleneglycol, 50°C, 72 h, 30% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C, 72 h, 18% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C, 72 h, 10% WIS Cellic CTec2+Htec2+Miltif ect Pectinase, 50°C,
Glucose concentration after enzymatic hydrolysis (g/l) 38.0
MA N
Feedstock
TE D
Fermentation
88.0
CE P
Enzymatic hydrolysis
T
Theoretical Yield* (%)
US
Table I Comparison of efficiency of selected SHF processes
S. cerevisiae, 30°C, 16 h
Cellulast 1.5L and Novozyme 188, 45 °C, 72 h, 10% WIS
recombinant xylose consuming S. cerevisiae, 32 °C, 90 h S. cerevisiae, 36°C, 72 h
58.6
37.5
NP
~30
7.13
76.5
0.12
Gupta 2009
et
al.,
18.5
96.1
0.36
Gupta 2009
et
al.,
18.5
49.1
NP
Ask et al., 2012
IP
T
18.2
CR
Commercial cellulose and ßglucosidase, 50°C, 36 h, surfactant addition
Prosopis juliflora wood, acid pretreated and delignified by sodium sulphate and sodium chlorite Prosopis juliflora wood, acid pretreated and delignified by sodium sulphate and sodium chlorite Arundo donax steam-exploded
US
P. stipitis, 30°C, 24 h
TE D
72 h, 13% WIS Commercial cellulose and ßglucosidase, 50°C, 36 h, 5% WIS surfactant addition
MA N
ACCEPTED MANUSCRIPT
54 62
AC
CE P
Commercial Reed, liquid hot 32.1 ~100 19.0 99.5 0.13 Lu et al. 2012 water pretreated cellulose, 50°C, 72 h, 5% WIS * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. WIS – Water insoluble solids ~ data were obtained from graph NP-not provided
ACCEPTED MANUSCRIPT
Table II Comparison of efficiency of selected SSF processes
42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS 42 °C, 160 h, 10% WIS
S. cerevisiae
S. cerevisiae M. indicus R. oryzae S. cerevisiae
30°C, 6% WIS 3-stage fed-batch SSF 42 °C, 72 h, fed-batch SSF, 14% WIS 38 °C, 5% WIS 38 °C, 5% WIS 38 °C, 5% WIS 30 °C, 4% WIS, 48 h
P. stipitis
30 °C, 4% WIS, 48 h
Z. mobilis
30 °C, 4% WIS, 48 h
S. cerevisiae
37-38°C, 20% WIS, 48 h
S. cerevisiae
40°C, 7.5% WIS, 72 h
S. cerevisiae
40°C, 15 % WIS, 72 h
S. cerevisiae
40°C, 15 % WIS, 72 h
S. cerevisiae
35°C, 20 % WIS, fed-
39.9
0.84
Alfani et al., 2000
71.2 62.5 62.5 60.9
0.26 0.24 0.25 0.23
Ballesteros et al., 2004 Ballesteros et al., 2004 Ballesteros et al., 2004 Ballesteros et al., 2004
81.7
0.67
Kim et al., 2013
54
0.44
Tomás-Pejó, 2009
68
30.2
Rice straw Rice straw Rice straw Mature coconut fibre, alkali pretreated Mature coconut fibre, alkali pretreated Mature coconut fibre, alkali pretreated Oil palm empty fruit bunches formiline pretreated Rapeseed straw, acid pretreated Rapeseed straw, acid pretreated Rapeseed straw, acid pretreated Spruce slurry
10.2 11.4 21.5 8.4
60.8 67.6 75.9 84.6
0.20 0.23 0.43 0.18
Karimi et al., 2006 Karimi et al., 2006 Karimi et al., 2006 Goncalves et al., 2014
9.1
79.3
0.40
Goncalves et al., 2014
8.3
81.7
0.17
Goncalves et al., 2014
83.6
85.2
1.74
Cui et al., 2014
17.0
66.0
0.24
32.0
62.1
0.44
34.0
49.5
0.47
40.0
53%
0.42
López-Linares et al., 2014 López-Linares et al., 2014 López-Linares et al., 2014 Koopram and Olsson,
CE P
Wheat straw
AC
K. marxianus
19.0 17.0 18.1 16.2
Reference
T
K. marxianus K. marxianus K. marxianus K. marxianus
Wheat straw, steam exploded+washed NaOH Poplar Eucalyptus Wheat straw Sweet sorghum bagasse Saw dust
Productivity (g/l/h)
IP
37°C, 50 h, 10% WIS
Theoretical Yield* (%)
CR
S. cerevisiae
Max. ethanol concentration (g/l) ~30
US
Feedstock
MA N
SSF condition
TE D
Microorganism
ACCEPTED MANUSCRIPT
15.8
68.1
14.0
60.3
T
Kanlow switchgrass pretreated with hydrothermolysis Kanlow switchgrass pretreated with hydrothermolysis Arundo donax steam-exploded
IP
37°C, ~7% WIS, 72 h
2014
CR
S. cerevisiae
commercially pretreated
US
K. marxianus
batch addition of substrate, enzymes and yeasts, 96 h 45°, ~7% WIS, 72 h
0.22
Suryawati et al., 2008
0.19
Suryawati et al., 2008
AC
CE P
TE D
MA N
S. cerevisiae 32 °C, 96 h 17.0 41.2 0.18 Ask et al., 2012 recombinant, xylose consuming * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. WIS – Water insoluble solids
ACCEPTED MANUSCRIPT
50 °C, 24h 50 °C, 24h 50 °C, 10h
50 °C, 10h
S. cerevisiae, 30 °C, 48 h, 25% WIS, fed-batch
50 °C, 24h
S. cerevisiae, 30°C, 96 h, 20% WIS S. cerevisiae, 40 °C, 28 h S. cerevisiae, 30 °C, 396 h, fed-batch
50 °C, 24h 50 °C, 12h with addition of substrate and enzymes 50 °C, 18h, 10% WIS 50 °C, 24h, 1012% WIS,
Reference
0.47
31.5
31.5
61.1
0.44
32.4
47.1
0.45
17.4
88.4
0.24
Lopéz-Linares et al., 2014 Lopéz-Linares et al., 2014 Lopéz-Linares et al., 2014 Huang et al., 2014
36.6
73.5
0.51
Huang et al., 2014
34.0
NP
58.8
NP
NP
9.9
63.1
0.19
Xiros and Olsson, 2014 Zhang et al., 2014
30.5
91.5
54
0.02
Elliston et al., 2013
32.0 38.4
NP
Reed, liquid hot water NP 39.4 79.1 0.44 Lu et al., 2012 pretreatment Spruce chips, SO2 49.4 31.1 85.0 0.26 Ishola et al., 2013 impregnated, pretreated at elevated temperature and pressure 45°C, 5 days, 7% S. cerevisiae, 30°C, 4 Wheat straw steam NP 22 49 ~0.23 Viola et al., 2013 WIS, cycles exploded, extracted with alkaline solution * Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. ** Process productivity has been recalculated to include the duration of both the presaccharification period and SSF WIS – Water insoluble solids NP-not provided
AC
S. cerevisiae, 36 °C, 72 h, fed-batch S. cerevisiae, 96 h saccharification with filtration
Productivity** (g/l/h)
T
Rapeseed straw acid pretreated Rapeseed straw acid pretreated Rapeseed straw acid pretreated Pomelo peel, hydrothermally pretreated Pomelo peel, hydrothermally pretreated Spruce wood chips acid pretreated Sacrau poplar, peroxide pretreatment a Copier paper
Theoretical Yield* (%) 65.5
IP
S. cerevisiae, 40 °C, 7.5%WIS, 72 h S. cerevisiae, 40 °C, 48 h, 15 %WIS, S. cerevisiae, 40 °C, 48 h, 20 %WIS, S. cerevisiae, 30 °C, 48 h, 10% WIS
Max. ethanol concentration (g/l) 17.4
US
50 °C, 24h
Glucose in presaccharification (g/l) 17.0
MA N
Feedstock
TE D
SSF condition
CE P
Presaccharificati on
CR
Table III Comparison of efficiency of selected SSF processes with delayed inoculation
ACCEPTED MANUSCRIPT
Table IV Comparison of efficiency of selected CBP processes
Trichoderma reesei Fusarium oxysporum
Paecilomyces variotii Trametes versicolor
Category II CBP engineered S.cerevisiae engineered S. cerevisiae Consortia C. thermocellum Thermoanaerobacter ethanolicus C.thermocellum Thermoanaerobacterium saccharolyticum C.phytofermentans, S.cerevisiae T.reesei, S.cerevisiae T.reesei, S.cerevisiae,
Cellulose (unspecified) Cellulose (unspecified) AFEX treated corn stover Avicel Solka-Floc Sugar cane bagasse Cellulose Alkali treated brewer`s spent grain Wheat bran Crystalline cellulose Wheat bran rice straw
2.8
40
23.0
-
Reference
0.02
Rani et al., 1997
0.06
Xu et al., 2010
63
0.03
Jin et al., 2012
60 70 20
0.05 0.07 0.03
Gong et al., 1981b Gong et al., 1981b Huang et al., 2014
14.5 10
53 60
0.1 0.1
Christakopoulos et al., 1989 Xiros and Christakopoulos, 2009
1.2 4.7
18 47
0.2 0.05
Zerva et al., 2014 Okamoto et al., 2014
5.0 4.8
92 91
0.05 0.05
Okamoto et al., 2014 Okamoto et al., 2014
Avicel Acid pre-treated wheat straw
1.8 26
36 63
0.03 0.27
Wen et al., 2010 Khramtsov et al., 2011
Alkali treated banana waste Avicel
22
29
NP
Reddy et al., 2010
38
90
0.3
Argyros et al., 2011
α-cellulose (added endoglucanase) Avicel Dilute acid
22
43
NP
Zuroff et al., 2013
7.0 9.8
70 69
0.04 0.07
Brethauer and Studer, 2014 Brethauer and Studer, 2014
IP CR
US
7 13 16 3.0
T
Productivity (g/l/h)
MA N
Monilia sp.
Theoretical Yield* (%)
TE D
Clostridium phytofermentans
Max. ethanol concentration (g/l)
CE P
category I CBP Clostridium thermocellum
Feedstock
AC
CBP microorganism(s)
ACCEPTED MANUSCRIPT
T
wheat
40
83
Corn, sugar beet, molasses
100-120
95-98
0.2
Hahn-Hägerdahl Häggström, 1985
2.8-4.0
average data from Czech distilleries
IP
Solka-Floc
CR
Two step processes T. reesei S. cerevisiae Standard process using 1st generation feedstock S. cerevisiae
pretreated straw
US
Scheffersomyces stipitis
and
AC
CE P
TE D
MA N
Theoretical ethanol yield (0.51 g/g), which is taken as 100%, is the yield that can be theoretically achieved by Saccharomyces cerevisiae during ethanol fermentation of glucose if yeast maintenance requirements and the formation of fermentation by-products are not considered. NP-not provided
ACCEPTED MANUSCRIPT
Table V Optimal temperature and thermal stability of free and immobilised enzymes under increased temperature. Optimal temperature
49°C
non-porous magnetic particles
65°C
70°C
β-glucosidase (Novozyme)
mercaptopropyl functionalyzed mesoporous TiO2 Fe3O4-chitosan
60°C
60°C
50°C
Xylanases (Bacillus gelatini ABBP-1)
Ca-mag- CLEA
-
Cellulase (T. resei ATCC 26921)
CLEAs on silica gel (XCa-Si)
Biotinylated glucosidase
Loss of activity
initial
Referenc e
NP
-28%
immobili zed -14%
1h
-26%
-60%
60°C
4h
- ~30%
50°C
60°C
5h
~80 % -47%
-
50°C
32h
-20%
not changed
50°C
50°C
70°C
1h
-73%
-25%
streptavidin coated magnetic particles
45°C
45°C
50C
3h
100 %
- 43%
iron oxide nanoparticles
60°C
60°C
70°C
2h
96%
-21%
co-immobilized gold nanoparticles
-
-
80°C
48h
- ~20%
Cho et al., 2012
co-immobilized gold-doped magnetic silica nanoparticles polyamidoamine dendrimer grafted silica chitosan
-
-
80°C
48h
~11 % ~11 %
- ~8%
Cho et al., 2012
50°C
60°C
70°C
3h
- ~47%
Wang et al., 2013
40°C
50°C
60°C
2h
~75 % -39%
-14%
55°C
60°C
80°C
2h
-73%
-50%
Cellulase (Suhong B989N)
reversible watersoluble polyacrylate copolymer reversibly soluble Eudragit S-100
Su et al., 2012 Liang and Cao, 2012
50°C
50°C
70°C
1h
- ~30%
Yu et al., 2012
Cellulase viride)
polyaniline coated microspheres
40°C
50°C
75°C
2h
~47 % ´100 %
-22%
Ince et al., 2012
D
AC
β-glucosidase (Aspergillus niger) Endo-glucanase Exo-glucanase Beta-glucosidase Endo-glucanase Exo-glucanase Beta-glucosidase
TE
β-
CE P
Cellulase (Meiji Seika Pharma)
Cellulase viride)
(T.
Cellulase Cellulase (Novozyme)
(T.
60°C
SC R
CLEAs on silica gel
Tim e
free
65°C
NU
Cellulase (T. resei) SigmaAldrich β-glucosidase (Megazyme)
immobil ized 51°C
MA
free
Increase d tempera ture
T
Immobilization method
IP
Enzyme
-41%
Sutarlie and Yang, 2013 Alftrén and Hobley, 2013 Wei et al., 2013 Zang et al., 2014 Battachar ya and Pletschke , 2014 Nguyen and Yang, 2014 Alftrén et al., 2013 J Verma et al., 2013
ACCEPTED MANUSCRIPT Cellulase viride)
(T.
Cellulase resei)
(T.
polyaniline coated microspheres, crosslinked enzyme magnetic nanoparticles
40°C
50°C
75°C
2h
50°C
60°C
80°C
2h
AC
CE P
TE
D
MA
NU
SC R
IP
T
~ data were obtained from graph NP – not provided
100 % 100 %
- 37%
Ince et al., 2012
- ~35%
Abraham
et 2014
al.,
ACCEPTED MANUSCRIPT Highlights Process design for production of 2nd generation ethanol is reviewed.
IP
T
Features, benefits and drawbacks of process configuration are discussed.
AC
CE P
TE
D
MA
NU
SC R
Efficiency of processes (ethanol concentration, yield, productivity) is compared.
