Bioresource Technology 173 (2014) 42–51
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Ethanol production from cotton gin trash using optimised dilute acid pretreatment and whole slurry fermentation processes S. McIntosh, T. Vancov ⇑, J. Palmer, S. Morris NSW Department of Primary Industries, Wollongbar Primary Industries Institute, NSW, Australia
h i g h l i g h t s Pretreatment of cotton gin trash with sulfuric acid was investigated. Response surface modelling described the optimal pretreatment conditions. Enzymatic glucose conversion of 89% was achieved. Industrial yeast rapidly and efficiently fermented recovered glucose.
a r t i c l e
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Article history: Received 29 July 2014 Received in revised form 11 September 2014 Accepted 14 September 2014 Available online 22 September 2014 Keywords: Cotton gin trash Pretreatment optimisation Ethanol fermentations
a b s t r a c t Cotton ginning trash (CGT) collected from Australian cotton gins was evaluated for bioethanol production. CGT composition varied between ginning operations and contained high levels of extractives (26–28%), acid-insoluble material (17–22%) and holocellulose (42–50%). Pretreatment conditions of time (4–20 min), temperature (160–220 °C) and sulfuric acid concentration (0–2%) were optimised using a central composite design. Response surface modelling revealed that CGT fibre pretreated at 180 °C in 0.8% H2SO4 for 12 min was optimal for maximising enzymatic glucose recoveries and achieved yields of 89% theoretical, whilst the total accumulated levels of furans and acetic acid remained relatively low at <1 and 2 g/L respectively. Response surface modelling also estimated maximum xylose recovery in pretreated liquors (87% theoretical) under the set conditions of 150 °C in 1.9% H2SO4 for 23.8 min. Yeast fermentations yielded high ethanol titres of 85%, 88% and 70% theoretical from glucose generated from: (a) enzymatic hydrolysis of washed pretreated fibres, (b) enzymatic hydrolysis of whole pretreated slurries and (c) simultaneous saccharification fermentations, respectively. Crown Copyright Ó 2014 Published by Elsevier Ltd. All rights reserved.
1. Introduction Cotton is the principal source of natural fibres for textile industries, and thus one of the most abundant sources of agro-industrial biomass. Globally, more than 12 million hectares of cotton is planted across 80 countries producing approximately 26 million tonnes of refined cotton according to the latest production figures for 2012–13 (Anon., 2013). The high level of cotton cultivation also equates to high production of cotton gin wastes and residues. In the US alone it is estimated that the cotton industry produces about 2.26 million tonnes of cotton gin waste annually (Jeoh and Agblevor, 2001). In Australia, cotton production is also a significant broadacre crop with more than half a million hectares currently under cultivation. It has been estimated that the ginning process ⇑ Corresponding author at: Industry & Investment NSW, 1243 Bruxner Highway, Wollongbar, 2477 NSW, Australia. Tel.: +61 2 6626 1359; fax: +61 2 6628 3264. E-mail address:
[email protected] (T. Vancov). http://dx.doi.org/10.1016/j.biortech.2014.09.063 0960-8524/Crown Copyright Ó 2014 Published by Elsevier Ltd. All rights reserved.
utilised in Australia generates anywhere from 25 to 60 kg of CGT per bale of cotton. Therefore, based on the production data for 2011 to 2012, up to 300,000 tonnes of CGT was produced (Hassall and Associates, 2005; Kovac and Scott, 2012). Although these volumes are less significant than those generated by the sugar, cereal grains and forestry production systems, it is recognised that a second generation biofuel plants will use multiple feedstocks within close proximity to reduce transportation costs and ensure economic viability. Cotton in Australia is generally grown in the same region as broadacre gain crops (ABARE, 2012). In Australia the high volume of CGT produced poses a significant burden to the industry. Since the conventional practice of burning trash has ceased, many cotton ginneries are still developing suitable management practices. Current practices for managing CGT vary greatly across the industry but for most handling, storage, transport and disposal options add considerable cost to the cotton ginning process. According to a 2005 report (Hassall and
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Associates, 2005) on waste management, the current methods for disposal of CGT as a ‘solid waste’ include: dumping and landfilling, composting for ground cover/mulch and spreading on uncropped lands. These management practices not only require large areas of land (approximately 50 hectares per ginnery) but have an estimated annual cost of $3.40 million per year (Hassall and Associates, 2005). Compounding the CGT disposal issue is the potential classification of the trash as ‘hazardous waste’ on the grounds of residual pesticide contamination. Under this restrictive classification, the annual disposal cost increases to $64.55 million per year (Hassall and Associates, 2005). To provide a solution to these disposal problems and to potentially add value, cotton growing nations have been investigating alternative uses for CGT. Cotton trash has been investigated in numerous studies as an exploitable biomass resource, particularly as a renewable feedstock in supporting commercial bioenergy applications (Agblevor et al., 2007, 2003; Akpinar et al., 2011; Isci and Demirer, 2007; Jeoh and Agblevor, 2001; Sharma-Shivappa and Chen, 2008; Silverstein et al., 2007). CGT is well suited as a biorefinery feedstock for several reasons. It has promising compositional attributes for effective and scalable conversion to biofuels relative to other candidate biomass resources. For biochemical conversion based approaches, these include high polysaccharide content (up to 50%). Sugars generated from CGT processing have been shown to support ethanol fermentations (Agblevor et al., 2003; Beck and Clements, 1982; Brink, 1981; Jeoh and Agblevor, 2001). Moreover, CGT is an ideal feedstock because unlike most lignocellulosic feedstocks, CGT is concentrated at processing sites and current infrastructure therefore harvesting and transportation costs would be considerably less than those for other agroforestry residues and dedicated biomass feedstocks. The efficient conversion of CGT to sugars for ethanol fermentations generally requires pretreatment to remove structural barriers (lignin and hemicellulose) and enzymatic hydrolysis of composite carbohydrates to simple sugars. Although CGT has a high carbohydrate content (up to 50%), especially pure cellulose from cotton fibre, investigations into ethanol production and process optimisation is relatively modest in comparison to other notable agricultural residues (corn stover, sugarcane bagasse, straws, etc.). In the first reported study on CGT, Jeoh and coworkers (2001) focussed on pretreating CGT using steam explosion under varying conditions. Although they observed improvements in enzyme hydrolysis of cellulose fraction (from 42% to 67%), xylan losses owing to degradation under severer conditions were prevalent. Agblevor et al., 2003 expanded upon this work and investigated the production of ethanol from CGT, based on feedstock origin, composition and steam explosion severity. They found that CGT composition varied considerably between locations and storage regimes, and that harsher pretreatment conditions (severity) tended to create more inhibitory compounds, resulting in low ethanol yields (120 L/t). Besides steam explosion, the only other notable study on alternative pretreatment approaches for CGT was investigated by Plácido and co-workers (2013). They reported that although a combination of ultrasonication, liquid hot water and ligninolytic enzymes were comparatively effective in modifying the structure and composition of CGT, the ensuing sugar (25%) and ethanol yields were relatively modest. This study examines and reports on the effectiveness of acid catalysed pretreatment and enzymatic hydrolysis options for processing CGT from Australian ginning operations into sugars and subsequently ethanol. The effects of varying key pretreatment parameters (acid strength, temperature and residence time) on cellulose hydrolysis were investigated and the optimal conditions for maximal sugar recoveries are described by means of Response Surface Methodology (RSM). The ethanol fermentation potential of
ensuing sugar hydrolysates were also evaluated using an industrial Saccharomyces cerevisiae strain. 2. Methods 2.1. Materials CGT was kindly supplied by AusCot (Narrabri, NSW) and Namoi Cotton Co-operative (Yarraman Gin, NSW). All material was airdried at 50 °C for 48 h and ground in a rotary mill (Gelder & Co., NSW, Australia) fitted with a No. 5 sieve (ASTM.). To achieve better uniformity and further size reduction, samples were subject to a 60 s pulse in a pulveriser (Labtechnics Pulveriser, WA, Australia). Milled material was stored at room temperature in air-tight containers. All chemicals including acid, bases, salts and analytical standards were of reagent grade or higher and purchased from Sigma Chemical Co. (St. Louis, MO). The cellulase blend CellicÒ CTec 2 was kindly supplied by Novozymes (Denmark). For ethanol fermentations the S. cerevisiae strain ThermosaccÒ Dry was kindly supplied by Lallemand (WI, USA) as an active dry preparation; yeast extract and peptone were purchased from AMYL Media (VIC, Australia). 2.2. Optimisation of dilute acid pretreatment Generally, for pretreatment reactions 100 g of ground CGT was mixed with 1 L of sulfuric acid solution in a 2 L stirred Parr reactor (Parr Instruments, USA) and allowed to pre-soaked at 50 °C for 30 min prior to initiating the pretreatment to ensure thorough wetting of solids. Pretreatments were performed at temperatures of 160–220 °C, with residence times of 4–20 min and sulfuric acid concentrations of 0–2% (v/v) according to experimental plan described below. The Parr reactor was heated by an external aluminium block heater and water cooled through the heating blocks internal cooling coil. For pretreatment experiments, the heating controller was set on maximum output and reaction material was stirred at 60 rpm. Water was pushed through the cooling coil using the maximum water valve opening to rapidly cool the system (about 15 min). When reaction material reached 90 °C the slurries were immediately decanted and the insoluble fractions (solids) were recovered by vacuum filtration using a Büchner funnel and WhatmanÒ glass microfiber GF/A filters. Solids were water washed until a neutral pH was achieved. Recovered solids were sampled and dried at 50 °C and stored at room temperature until further compositional analysis. Recovered soluble fractions were sampled, filtered (0.45 lm MinisartÒ syringe filter, Sartorius) and stored at 20 °C until further compositional analysis. In the case where solids were not separated post-pretreatment, the whole slurries were pH adjusted to 5.0 with NaOH. For pretreatment reaction conditions a central composite design (CCD) incorporating variables of temperature, time and acid concentration was employed to define the optimum pretreatment process. Each independent variable was assessed at five coded levels (2, 1, 0, 1, 2) (Table 1). The range of each variable was based on preliminary single factor pretreatment experiments. Twenty combinations of time, temperature and acid were selected according to the CCD
Table 1 Coded levels of the three variables in the dilute acid pretreatments. Variable
Time Temperature H2SO4
Symbol
x1 x2 x3
Units
min °C % (v/v)
Coded levels 2
1
0
1
2
4 160 0
8 175 0.5
12 190 1
16 205 1.5
20 220 2
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which included eight tests for factorial design, six tests for axial points and 6 tests for replication of the central point (Table 3). A second order polynomial response surface was fitted using the methods and tools described by Lenth (Lenth, 2009). The response surface model has the form:
y ¼ a0 þ a1 x1 þ a2 x2 þ a3 x3 þ a4 x1 x2 þ a5 x1 x3 þ a6 x2 x3 þ a7 x21 þ a8 x22 þ a9 x23
ð1Þ
where y is the response of interest and x1, x2, x3 represent time, temperature and acid level respectively but with values coded as units from the centre (2, 1, 0, 1, 2). The statistical importance of each variable was tested by change in model likelihood after deletion and terms were dropped from the model when the change was not significant (p > 0.10). The values of time, temperature and acid concentration at the stationary point for each response surface were calculated and used to predict the yield arising from the system at that point. 2.3. Enzyme hydrolysis. CellicÒ CTec 2 cellulase blend was used for all enzymatic hydrolysis studies and loads are quoted as FPU (Filter Paper Units)/g dry material (DM). Generally, enzymatic hydrolysis of solid substrates was performed in 50 mM citrate buffer pH 5.0 containing 0.02% sodium azide with a substrate loading of 10% (w/v) and incubated for up to 96 h at 50 °C. To identity significant pretreatment variables and interactive effects, enzymatic hydrolysis of pretreated fibres were conducted under controlled isodosing conditions using a fixed CellicÒ CTec 2 cellulase loading of 20 FPU/g DM. This cellulase loading was selected based on results from preliminary experiments in which CGT fibres pretreated under midpoint conditions for temperature, time and acid concentration (as described in Table 1) were subjected to an enzyme dose response using cellulase loadings of 5.0, 12.5, 20 and 30 FPU/g DM. To evaluate maximum glucose release, pretreated materials were subject to higher enzyme dose response condition using CellicÒ CTec 2 cellulase loading of 30, 40, 60 and 80 FPU/g DM. For enzymatic hydrolysis of whole pretreated slurries (including both insoluble fibre and soluble fractions), the entire slurry was adjusted to pH 5.0 with NaOH prior to addition of 0.02% sodium azide and appropriately diluted enzyme. No buffering agents were used in enzymatic hydrolysis of whole pretreated slurries. Hydrolysates were sampled at time points specified in the text, boiled for 10 min and centrifuged at 8000g for 5 min, syringe filtered with a 0.45 lm MinisartÒ (Sartorius, Germany) and stored at 20 °C for further HPLC analysis. 2.4. Ethanol fermentation Active, dry S. cerevisiae (ThermosaccÒDry, Lallemand, WI, USA) was used in accordance with manufactures instructions for fermentation studies. To evaluate fermentation of CGT sugar hydrolysates three approaches were selected. In approach (1) sugar hydrolysates were prepared from water washed recovered fibre pretreated under optimised conditions (0.8% H2SO4 at 180 °C for 12 min), followed by enzymatic hydrolysis (80 FPU/g DM, pH 5.0, 48 h) and recovered sugars were subject to fermentation. Approach (2), sugar hydrolysates were produced by pretreating CGT under the same optimised conditions (0.8% H2SO4 at 180 °C for 12 min) with subsequent cellulase hydrolysis (80 FPU/g DM, pH 5.0, 48 h) of pH adjusted whole pretreated slurries (described in Section 2.2 above) and recovered sugars were subject to fermentation. For approaches 1 and 2, the liquid hydrolysates following enzymatic hydrolysis were separated from residual solids by vacuum filtration using a Büchner funnel and WhatmanÒ glass microfiber GF/ A filters and referred to as WF and WS hydrolysates. The yeast fer-
mentation media consisted of filter sterilised hydrolysate (0.22 lm, nylon filter, Millipore, MA, USA) containing 2 g/L KH2PO4, 5 g/L yeast extract, 10 g/L peptone and 1 g/L MgSO4 and were inoculation directly with dried yeast at 5 g/L to initiate fermentation. Approach 3 was a simultaneous saccharification/ hydrolysis fermentation (SSF) where CGT was pretreated under the same described conditions (0.8% H2SO4 at 180 °C for 12 min) and whole slurries were pH adjusted to 5.0 using NaOH. Whole slurries were supplemented with 2 g/L KH2PO4, 5 g/L yeast extract, 10 g/L peptone and 1 g/L MgSO4 and re-sterilised by autoclaving at 121 °C for 15 min. When the temperature had reached approximately 30 °C, 80 FPU/g DM and 5 g/L dry yeast were directly added to initiate SSF. Fermentations were conducted in a 2 L computer controlled Bioflo 110 fermentors (New Brunswick Scientific, CT, USA) with a working volume of 1 L, and were incubated at 30 °C (±3 °C) with agitation (50 rpm). Samples were taken at regular time intervals, centrifuged at 8000 g for 5 min, syringe filtered with a 0.45 lm MinisartÒ (Sartorius, Germany) and stored at 20 °C for further analysis. Sugars and ethanol were quantified by HPLC. The maximum ethanol volumetric productivity (g/L/h) is calculated from Dp/Dt where Dp is the change in the ethanol concentrations over the time period Dt. The theoretical ethanol yields from glucose were calculated according to the following equation:
%Theoretical ethanol yield Y E ¼ ½E=ð0:51 ½GÞ 100
ð2Þ
where [E] is the final ethanol concentration and [G] is the initial glucose concentration. 2.5. Analytical methods Specific carbohydrate and lignin contents of untreated and treated materials were determined following concentrated acid hydrolysis as described by NREL (Sluiter et al., 2008a). CGT biomass extractives were determined by sequential water and ethanol extraction using a Dionex ASE system according to the NREL automatic extraction methods (Sluiter et al., 2008b). The carbohydrate, furan, ethanol and carboxylic acid compositions were determined using high performance liquid chromatography (HPLC). The HPLC separation system consisted of a solvent delivery system (Controller 600, Waters, MA, USA) equipped with an auto sampler (717, Waters) and a refractive index detector (412 differential refractometer, Waters, MA, USA) managed by the Waters EmpowerÒ software program. Sugars and degradation products (furans and carboxylic acids) were analysed using either the RHM or RPM-Monosaccharide column (7.8 mm 300 mm, Rezex™, Phenomenex Inc., CA, USA), fitted with a Carbo-H or Carbo-Pb (Rezex™, Phenomenex Inc., CA, USA) guard column cartridge respectively. The RHMMonosaccharide column was maintained at 60 °C and compounds were eluted with an isocratic mobile phase consisting of degassed Milli-Q water containing 0.005 N H2SO4 at a flow rate of 0.5 mL/ min. The RPM-Monosaccharide column was maintained at 70 °C and compounds were eluted with an isocratic mobile phase consisting of degassed Milli-Q water at a flow rate of 0.6 mL/min. The refractive index detector was maintained at 50 °C for all applications. Peaks detected by the refractive index detector were identified by retention times matching, and quantified by comparison, with analytical standards analysed within each batch. 3. Results and discussion 3.1. Composition of cotton gin trash CGT is uniquely different in composition to most other agricultural residues in that it consists of a heterogeneous mixture of
S. McIntosh et al. / Bioresource Technology 173 (2014) 42–51
different plant components mainly, cotton stems, leaves, motes, burrs, lint and seeds. The proportion of these may vary substantially and primarily depend on the ginning operation, time of cotton harvest and whether cotton seed components are removed for other uses. To evaluate CGT compositions, samples were obtained from two of Australia’s leading cotton processors and are identified herein as CGT1, and CGT2. A visual inspection revealed that the major fraction of CGT1 and CGT2 were comparable although CGT2 had slightly more lint. Neither samples contained cotton seed. A composite sample, identified herein as just CGT, was constructed by pooling CGT1 and CGT2 (50:50) and was used in all further pretreatment, enzymatic hydrolysis and fermentation experiments. The extractives, acid-insoluble lignins, and ash contents of CGT1, CGT2 and CGT are presented on an original starting material basis in Table 2. The total ash content was similar for both samples and recorded at 8–13%. Soil contamination during harvesting and storage is most likely responsible for this elevated ash content. Samples were sequentially extracted with water and ethanol to remove the extractives fractions whilst the recovered solids represented total fibre. The total extractives component was relatively high at 26–28% compared to other herbaceous crops like wheat straw (18%) and corn stover (10%) (Vancov and McIntosh, 2011a,b; Weiss et al., 2010). The water soluble fractions were brownish in appearance with a faint sweet aroma and represent about 15–17%. HPLC analysis of this fraction failed to reveal detectible levels of monomeric sugars. CGT1 contained more ethanol extractives than CGT2; 12.5% and 9.3% respectively, which is presumably due to the higher proportion of non-lint material in the former sample. Both CGT samples were found to contain a relatively high acidinsoluble lignin content of 22.8% and 17.9% for CGT1 and CGT2, respectively (Table 2). On an extractives free basis, the lignin content equates to about 26–28% which is substantially higher than those reported for other herbaceous biomass and are more comparable to hardwoods like eucalyptus (McIntosh et al., 2012). The total carbohydrate content varied among ginning samples and ranged from 41% to 51% for CGT1 and CGT2 respectively (Table 2), which is relatively low compared to woody or herbaceous biomass (McIntosh et al., 2012; Pronyk and Mazza, 2012; Vancov and McIntosh, 2011a,b). Similarly, the xylan content was comparatively low for an agricultural residue contributing 10–14% for CGT2 and CGT1 respectively. Glucan, which is derived from both the cotton fibre and the cell wall of the lignocellulose, represented the largest fraction of the CGT samples. Glucan content varied from
Table 2 Chemical composition of untreated CGT. Composition percentages are on an original starting material basis and standard errors are shown in parenthesis. Component (%)
CGT1
CGT2
CGTa
Glucan
23.9 (1.02) 13.9 (0.48) 2.2 (0.12) 2.4 (0.13) 22.8 (0.88) 15.6 (0.31) 12.5 (0.39) 13.1 (0.11)
36.5 (1.2) 10.7 (0.34) 1.7 (0.16) 1.3 (0.08) 17.9 (0.43) 17.0 (0.22) 9.3 (0.19) 8.0 (0.17)
31.0 (0.71) 12.2 (0.14) 2.0 (0.15) 2.0 (0.17) 20.1 (0.76) 16.1 (0.34) 10.2 (0.26) 10.5 (0.12)
Xylan Arabinan Galactan Acid Insoluble Lignin Extractives (H2O) Extractives (ethanol) Ash a
CGT is a composite sample of CGT1 and CGT2 (50:50).
45
c.a. 24% to 36% and correlated well with total cotton fibre content. Minor sugars including arabinan and galactan were similar in both samples and contributed only about 2%. These compositional estimates reveal that CGT is unique and different from other biomass feedstocks in that its characteristics lie between those of herbaceous crop residues (like cereal straws) and woody type feedstocks. A review of available literature indicates that the composition of CGT samples used in this study are comparable to values reported for other CGT feedstocks (Agblevor et al., 2003; Jeoh and Agblevor, 2001). 3.2. Optimisation of dilute H2SO4 pretreatment of CGT and cellulose digestibility The use of dilute acid at elevated temperature is a well documented pretreatment method for recovering high amounts of fermentable sugars from lignocellulosic substrates (Brodeur et al., 2011; da Costa Sousa et al., 2009; Hendriks and Zeeman, 2009). Previous processing studies of agroforestry biomass have established that pretreatment variables such as temperature, acid concentration and residence time play a critical role in dictating hemicellulose solubilisation, persistence of polymerised sugars within the fibres and the efficiency of subsequent enzymatic hydrolysis of cellulose (McIntosh et al., 2012; Mosier et al., 2005; Vancov and McIntosh, 2012). In this study, RSM incorporating variables of temperature, time and acid concentration was used to define optimum pretreatment process parameters for maximum enzymatic conversion of cellulose to glucose. Following pretreatments, solid residues (fibre) were quantitatively recovered and initially subject to compositional analysis. The recovered fibre ranged from 72% in the absence on any acid catalyst to as little as 33% under very harsh pretreatment conditions (Table 3). CGT fibre losses correlated well with pretreatment severity. Degradation and solubilisation of hemicellulose fractions and the apparent depolymerisation of cellulose in conjunction with a high soluble extractive content may account for the excessive loss of material following pretreatment. The composition of recovered pretreated fibre had undergone significant changes and for the most part was completely devoid of hemicellulose sugars (Table 3). Likewise, all minor hemicellulose components (arabinan and galactan) were also completely solubilised during pretreatments (data not shown). The cellulose content modestly increased from 31% (untreated CGT) to a maximum of 46%, however, based on prior experiences with crop residues a greater enrichment in cellulose was anticipated (Vancov and McIntosh, 2011a,b). In fact, under the most extreme conditions tested (e.g. run 1 and 8) a decline to 28% in cellulose content when compared to the original CGT biomass was observed. This decrease in ascribed to the solubilisation and ensuing partial degradation of glucose to hydroxymethylfurfural (HMF). Although not a typical response, Jeoh and Agblevor (2001) also reported severe depolymerisation and solubilisation of glucan in steam exploded CGT. They attributed the unique composition of CGT and the high proportion of naked cotton fibre as being completely exposed, thereby rendering the cellulose more susceptible to depolymerisation than other lignocellulosic feedstocks. The effects of pretreatment conditions on glucan digestibility were determined by cellulase hydrolysis of pretreated fibre under standardised cellulase isodosing conditions of 20 FPU/g and 48 h duration. These enzymatic strategies were not intended to maximise sugar recoveries but to augment and draw out those parameters critical to the success of the pretreatment process. The glucose recoveries summarised in Table 3 reveal maximum enzyme catalysed glucose recoveries reach 280 mg/g pretreated fibre (or 61% theoretical), representing a 2.07-fold increase over yields from untreated CGT under the same enzymatic conditions.
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Table 3 Experimental matrix and quantitative recovery data for pretreated fibre, composition and glucose yields following enzymatic hydrolysis of pretreated fibre. Run No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Gmax a b
Time (min)
Temperature (°C)
H2SO4 (% v/v)
Pretreated fibre
x1
x2
x3
Fibre recovered (%)
12 8 12 12 16 12 8 16 12 20 16 4 12 8 12 12 12 8 12 16 12
220 205 190 190 175 190 205 205 190 190 205 190 190 175 160 190 190 175 190 175 185
1 0.5 0 2 1.5 1 1.5 1.5 1 1 0.5 1 1 1.5 1 1 1 0.5 1 0.5 0.8
33.6 50.7 72.2 36.8 41.3 46.8 36.6 34.6 44.1 44.1 51.3 44.1 42.3 43.4 51.4 44.6 45.6 56.1 43.6 54.3 47.8
Glucan digestibility a
b
Glucan (%)
Xylan (%)
28.4 44.0 34.3 36.7 44.5 45.9 33.4 28.1 46.4 44.1 46.1 45.7 44.0 45.3 40.5 45.8 45.8 43.1 44.7 45.1 46.0
0.0 1.6 7.8 0.0 1.0 0.9 0.0 0.0 1.0 0.0 1.3 1.2 1.0 1.2 3.5 0.9 1.0 4.8 0.9 4.3 1.5
b
Glucose (mg/g)b
Glucose (%)b
152.2 222.9 206.0 157.9 246.8 265.0 188.4 134.3 266.5 272.0 280.8 244.8 265.3 222.9 220.7 264.1 264.3 263.0 267.6 272.2 278.8
54.5 50.6 60.1 42.6 54.3 58.0 56.4 47.8 58.3 61.7 60.8 52.0 58.0 49.2 54.4 57.8 57.8 59.3 58.5 59.5 60.6
Based on original dried material. Based on dry pretreated material. Gmax is the optimal pretreatment condition and responses as described by the RSM for maximising glucose release.
Table 4 Summary of t-test and parameter estimates for glucose recovery from enzymatic hydrolysis of pretreated CGT fibre (G) and xylose recovery from pretreatment liquors (X). Coefficient
ao a1 a2 a3 a4 a5 a6 a7 a8 a9 a
Term
Intercept x1 x2 x3 x1x2 x1x3 x2x3 x21 x22 x23
Estimate
Standard error
t value
G
X
G
X
G
265.47 NS 19.09 22.04 NSa NS 15.69 NS 18.87 19.99
88.26 2.7 9.29 6.07 3.31 NS 21.78 NS 10.99 16.27
6.99
1.61 1.01 1.01 1.01 1.43
37.95
5.34 5.34
3.57 4.13
Pr(>|t|) X 54.75 2.67 9.2 6.01 2.32
G
X
0.001
0.001 0.020 0.001 0.001 0.040
0.001 0.001
7.55
1.43
2.08
15.24
0.060
0.001
4.16 4.16
0.81 0.81
4.53 4.8
13.64 20.18
0.001 0.001
0.001 0.001
NS – not significant.
The glucose yields in response to varying pretreatment conditions were modelled using RSM and a second order polynomial response surface was fitted (based on Eq. (1)) (Lenth, 2009). A summary of the estimated coefficients is shown in Table 4, with p-values greater than 0.10 indicating that model terms are not significant. Based on the regression model of total glucose recoveries, coefficients of the variables x2, x3, x22 and x23 were all found to be significant (p < 0.001). Likewise, the term x2x3 with a p-value of 0.06 indicated a significant interaction effect between temperature and acid concentration. Conversely, the model asserts that the total glucose recoveries from enzymatic hydrolysis were not significantly changed by pretreatment time (x1) within the boundaries of the CCD. The fit of the model illustrates good correlation to the data sets, with total glucose recoveries displaying an R2 value of 84%. The model for pretreatment parameters and enzymatic glucose yields for CGT can be described by the following equation:
Glucoseðmg=gÞ; Y ¼ 265:47 19:09x2 22:04x3 15:69x2 x3 18:87x22 19:99x23 where Y is the glucose recovered (mg/g) after enzymatic hydrolysis and x2, x3 represent temperature (°C) and H2SO4 concentration
(% v/v) respectively, but with values coded as units from the centre (2, 1, 0, 1, 2). Predictions generated from the quadratic equation to describe the effect of pretreatment temperature and acid concentration on glucose recoveries following enzymatic hydrolysis are shown in Fig. 1. It is evident that at low acid concentrations glucose recovery increases significantly with an increase in temperature and then follows a smooth decline at higher temperature settings. Similarly, increasing acid concentrations significantly influenced enzyme catalysed glucose recoveries. The response surfaces exhibit similar sensitivities to both temperature and acid concentrations and the terms x2 and x3 displayed similarly weighted coefficient values of 19.09 and 22.04 respectively (Table 4). In related optimisation studies, enzymatic hydrolysis of pretreated eucalyptus wood was significantly influenced by increasing pretreatment temperature followed by acid strength and to a lesser degree reaction holding times (McIntosh et al., 2012). Avci et al. (2013) used a similar composite design when pretreating corn stover with phosphoric acid and reported that glucose yields were largely sensitive to increasing pretreatment temperature, more so than acid loadings. Residence times can and do influence the enzymatic release of glucose particularly under very mild and extreme pretreatment conditions. Typically, extending residence times tends to decreases
) lease (mg/g Glucose re
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47
partly to the degradation compounds formed during pretreatment, both of which are documented to impact on cellulase effectiveness (Duarte et al., 2012; Kim et al., 2011). Thus the use of dilute acid pretreatment shows improvements in cellulose digestibility over those obtained for CGT by microbial pretreatment (18%) (Shi et al., 2008) or ultrasonication coupled with hot water and enzyme pretreatment (23%) (Plácido et al., 2013). Likewise, values achieved in this study are slightly higher than those reported for steam exploded CGT with a conversion of 67% (Jeoh and Agblevor, 2001). This difference in yield is largely attributed to a slightly greater enzyme dosage (70 FPU/g vs 80 FPU in this work) and the disparity in CGT composition (particularly the amount of cotton lint present).
250 200 150 100 50 0 220 210 200 190
2.0 1.5 1.0
180
0.5
170
Temperature (°C)
160 0.0
H2SO4 (%)
Fig. 1. Response surface modelling of the effects of pretreatment temperature and acid concentration at middle time (12 min) on glucose yields after enzymatic hydrolysis of pretreated CGT fibre.
glucose yields under harsh conditions (as evident between pretreatment run 7 and 8 in Table 3) whereas, studies by Pedersen et al. (2011) describe an increased hydrolysis of cellulose under mild acidic conditions. According to the predictive model, a maximum glucose release of 273 mg/g pretreated CGT was estimated at conditions comprising of 0.8% H2SO4 at 180 °C with holding times of between 4 and 20 min. Based on fibre composition this represents a glucose yield of approximately 60% for the pretreated substrate. Several experimental pretreatment runs at the described acid and temperature setting with times of 4, 12 and 20 min were undertaken to validate forecasted maximum glucose levels. Actual glucose yields of 274.5, 278.8 and 276.8 mg/g at above respective times, confirmed the accuracy of the model to predict hydrolysis yields from variable pretreatment conditions (see quantitative recovery data for optimised pretreatment Gmax in Table 3). To further investigate cellulase’s accessibility to the cellulose fraction, recovered fibre from the optimised pretreatment regime (180 °C/0.8% H2SO4/12 min) were subjected to cellulase dose response conditions of 30, 40, 60 and 80 FPU/g pretreated substrate. The enzymatic glucose release increased significantly with increased enzyme dosage with near theoretical yields (94%) achievable over the time course (Fig. 2A). However, the summative mass of recovered glucose from the original CGT biomass (including glucose present in pretreatment liquors) indicated that even at the enzyme load of 80 FPU/g, up to 20% of the theoretical glucose was unaccountable. Therefore, enzymatic hydrolysis trials were undertaken on whole pretreated slurries (including both insoluble fibre and soluble liquid fractions). Enzyme dose response trials (Fig. 2B) confirmed that for each enzyme dose, total glucose recoveries were appreciably enhanced with a maximum yield of 89% theoretical glucose (based on ODM composition) evident with 80 FPU/g. In this approach it was possible to capture a significant fraction of glucan oligosaccharides which were present in pretreatment liquors. This result highlights the sensitivity of CGT cellulose to depolymerisation during pretreatment and dictates that enzymatic hydrolysis on whole pretreated slurries as a requisite for maximum glucose recovery. A relatively high enzyme concentration was required to deliver high hydrolysis rates and yields, owing in part to the elevated AIR fraction (46.5%) of the substrate and
3.3. Effects of sulfuric acid pretreatment and composition of pretreatment hydrolysates In addition to cellulose depolymerisation, acid catalysed pretreatments of CGT have lead to near total hemicellulose solubilisation as well as biomass degradation products. The pentose sugars represent a significant fraction that can either contribute to ethanol fermentations or be exploited for conversion to other products like xylitol or furfural in a biorefinery setting. Likewise, biomass degradation products can impact on both cellulase effectiveness and fermentation productivities and must be minimised as part of the process optimisation (Palmqvist and Hahn-Hägerdal, 2000; Panagiotou and Olsson, 2007). Therefore the investigation was expanded to quantify sugar solubilisation and degradation reaction products during the pretreatment phase. Furthermore, from recovered fibre compositions (Table 3) it is evident that hemicellulose fractions were completely solubilised, indicating pretreatment conditions for maximising xylose recovery may also be described within the CCD experimental matrix. Quantities of soluble sugars (xylose and glucose) and the main biomass degradation products, acetic acid, furfural and hydroxymethylfurfural (HMF) in pretreatment liquors are presented in Table 5. Galactans and arabinans were detected in some prehydrolysate liquors at low levels; presumably because they were mostly degraded to their corresponding furans. The xylose yields in response to varying pretreatment conditions were modelled using RSM and a second order polynomial response surface was fitted (based on Eq. (1)). A statistical analysis of the terms is shown in Table 4. The high R2 (99%) for xylose implies the model predictions correlate well with the data. The model terms x1, x2, x3, x1x2, x2x3, x22 and x23 all had a significant (p < 0.05) effect on xylose recovery. The model for pretreatment parameters and xylose yield for CGT could be represented by the following equation:
Xyloseðmg=gÞ; Y ¼ 88:28 2:70x1 9:29x2 þ 6:07x3 3:31x1 x2 21:78x2 x3 10:99x22 16:27x23 where Y is xylose recovered (mg/g ODM) after pretreatment and x1 (time, min), x2 (temperature, °C) and x3 (H2SO4, %) are the independent variables. Fitting of the surface response curves reveals that xylose recovery is most sensitive to pretreatment temperature followed by acid strengths. However, the stationary point of the surface extrapolated in the time direction extended beyond the CCD boundaries to 23.8 min due to the ridge shape of the fitted surface (Fig. 3). The response surfaces also reveal a decreasing sensitivity to temperature as the acid levels increased. The optimum pretreatment conditions for maximum hemicellulose solubilisation and xylose release were predicted to be 23.8 min at 150 °C with 1.9% H2SO4. This presents a recovery yield of 85% theoretical (102 mg/g ODM) which is significantly higher than reported yields from steam exploded CGT (10.4%) (Jeoh and Agblevor, 2001). Predicted optimal
48
S. McIntosh et al. / Bioresource Technology 173 (2014) 42–51 100
A
90 80
Glucose yield (%)
70 60 50 40 30 20 FPU 30 FPU 40 FPU 60 FPU 80 FPU
20 10 0
0
10
20
30
40
50
60
70
Time (h) 100
B
90 80
Glucose yield (%)
70 60 50 40 30 20 FPU 30 FPU 40 FPU 60 FPU 80 FPU
20 10 0
0
10
20
30
40
50
60
70
Time (h)
Fig. 2. Time course of glucose release from enzymatic hydrolysis of pretreated (185 °C/0.8% H2SO4/12 min) CGT using increasing cellulase dosages. Substrates are recovered washed fibre only (A) and whole pretreated slurries including both insoluble fibre and soluble fractions (B). Glucose releases are presented as percent theoretical maximal yield based on pretreated fibre composition (A) and original starting material composition (B).
pretreatment conditions for xylose recovery were empirically confirmed with data indicating a mean xylose yield of 104 mg/g ODM or 87% theoretical (see Xmax in Table 5). At pretreatment conditions described above for maximal enzymatic glucose release (0.8% H2SO4 at 180 °C for 12 min), xylose recoveries declined to 67% (see Gmax in Table 5). The presence of glucose in pretreatment liquors was relatively low across most test conditions at about 12% or less (Table 5) and correlated well with increasing pretreatment severities. Only under extreme pretreatment conditions (high temperature and acid levels) did yields approach 25% theoretical. Although relatively high, these values still fall short of fulfilling the summative mass closure for glucose recoveries following cellulase digestion. As noted in the preceding section, a substantial proportion of this glucose persists as soluble glucan oligosaccharides and degradation compounds (discussed below) in pretreatment liquors. These observations are consistent with reported findings on steam exploded CGT (Jeoh and Agblevor, 2001). It is evident that the formation and accumulation of biomass degradation products in pretreatment liquors occur predominantly
at higher acid and temperature combinations (Table 5). Of the three representative degradation products (acetic acid, furfural and HMF), acetic acid resulting from the hydrolysis of hemicellulose acetyl groups was the most abundant with levels approaching 21 mg/g (or 2.1 g/L based on 10% solid load). For the most part, acetic acid levels remained fairly constant over the experimental trials with midpoint treatments (1.0% H2SO4 at 190 °C for 12 min) producing about 19 mg/g. Acetic acid levels were substantially reduced at low temperature and acid combinations and correlated well with poor hemicellulose solubilisation. Furfural levels ranged between undetected (in the absence of an acid catalyst) and 25 mg/ g, whilst HMF levels were relatively low (c.a. 6 7 mg/g). Surface response curves for product furans (furfural and HMF) in relation to pretreatment variables revealed that levels continued to increase with pretreatment severity, which is consistent with correlating declining C5/C6 sugars yields and the creation of degradation products (Fig. 4). Under described conditions for optimal enzymatic glucose recoveries, total accumulated levels of furans and acetic acid remained relatively low at <1 and 2 g/L, respectively, based on 10% solid loads. These vales were slightly higher
49
S. McIntosh et al. / Bioresource Technology 173 (2014) 42–51 Table 5 Experimental matrix and quantitative recovery data for solubilised sugars, acetic acid and furans following pretreatment of CGT. Run No.
Xylose (mg/g)
Xylose (%)a
Glucose (mg/g)
Glucose (%)a
Furfural (mg/g)
HMF (mg/g)
Acetic acid (mg/g)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Xmax Gmax
24.1 73.3 12.6 37.8 90.4 89.9 40.2 30.0 86.7 82.3 60.5 94.1 88.4 96.8 68.5 89.4 89.8 33.4 88.6 43.3 104.4 80.3
20.1 61.1 10.5 31.5 75.3 75.0 33.5 25.0 72.3 68.6 50.4 78.4 73.7 80.7 57.1 74.5 74.8 27.8 73.8 36.1 87.0 66.9
67.3 20.7 3.1 47.8 38.0 39.0 78.8 79.7 38.6 38.9 20.5 34.5 39.5 36.9 16.2 39.7 38.1 8.3 38.4 10.6 24.5 28.8
21.9 6.7 1.0 15.5 12.3 12.7 25.6 25.9 12.6 12.7 6.7 11.2 12.9 12.0 5.3 12.9 12.4 2.7 12.5 3.4 7.9 9.3
21.8 9.7 0.0 15.1 7.7 11.2 25.4 22.8 10.3 12.8 9.9 6.4 11.0 5.1 0.4 11.3 10.6 0.6 9.9 1.0 1.3 6.1
7.2 2.1 0.2 1.6 0.9 1.4 4.2 4.4 1.3 1.8 1.9 1.1 1.4 0.8 0.2 1.5 1.5 0.3 1.4 0.4 0.3 1.0
20.1 14.5 8.0 13.7 17.9 19.2 20.8 20.3 18.8 18.9 16.1 17.6 19.1 18.5 11.9 19.1 18.8 4.4 18.4 5.6 17.8 19.7
ase (mg/g)
100 40
Furan rele
0
Xylose rele
ase (mg/g)
a Based on original dried material; Gmax and Xmax represent optimal pretreatment condition as described by the RSM for maximising glucose (from enzymatic hydrolysis) and xylose release, respectively.
−100
−200
220
2.0
200
1.5
180
1.0
160
Temperature (°C)
140
0.5 0.0
H2SO4 (%)
30 20 10 0 −10 −20 220
2.0
200
1.5
180
1.0
160
Temperature (°C)
140
0.5 0.0
H2SO4 (%)
Fig. 3. Response surface modelling of the effects of pretreatment temperature and acid concentration with time fixed at 23.8 min on xylose yields in pretreatment liquors.
Fig. 4. Response surface modelling of the effects of pretreatment temperature and acid concentration at middle time (12 min) on furan (furfural and HMF) release in pretreatment liquors.
than those reported for steam explosion of CGT but fall well within the tolerance range for yeast fermentations (Jeoh and Agblevor, 2001; Liu et al., 2004).
lead to an unfavourable environment for microbial growth resulting in low ethanol titres and productivities, and potentially require removal via an expensive detoxification step (Palmqvist and HahnHägerdal, 2000). In the first two approaches a separate enzymatic hydrolysis followed by fermentation was employed, where fermentation hydrolysates were produced from either recovered washed pretreated fibres (termed WF) or whole pretreated slurries (termed WS). The differences between the two hydrolysates being those from WS contain a complex mixture of sugars and compounds from CGT biomass and degradation reactions. In both approaches glucose was rapidly and completely metabolised by the yeast with the production of high ethanol titres (Table 6).
3.4. Ethanol fermentations The ethanol fermentation potential of C6 sugar hydrolysates were performed using the industrial S. cerevisiae ThermosaccÒ Dry .Three different yeast fermentation approaches were trialled to establish ethanol production and to investigate the effects of biomass degradation compounds generated during pretreatment and those naturally present in CGT. These compounds generally
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S. McIntosh et al. / Bioresource Technology 173 (2014) 42–51
Table 6 Time course of ethanol production and theoretical yields by S. cerevisiae ThermosaccÒ Dry from dilute acid pretreated and enzymatically hydrolysed CGT. Source
WF WS SSFa
YE
YE
YE
YE
YE
(%) 2h
(g/L)
(%) 4h
(g/L)
(%) 6h
(g/L)
(%) 9h
(g/L)
22.4 14.9 3.7
4.2 2.4 0.7
52.5 42.0 15.6
9.9 6.7 2.8
82.7 75.8 40.2
15.6 12.1 7.3
85.0 88.1
16.0 14.1
YE
YE
YE
(%) 24 h
(g/L)
(%) 48 h
(g/L)
(%) 72 h
(g/L)
(%) 96 h
(g/L)
62.2
11.3
68.5
12.4
69.3
12.6
70.9
12.8
YE stands for theoretical yield of ethanol (%) as calculated in Eq. (2); WF stands for hydrolysates derived from washed pretreated fibre; WS stands for hydrolysates derived from whole pretreated slurries; SSF stands for simultaneous hydrolysis (saccharification) fermentation. a YE is based on theoretical glucose content of both insoluble and soluble fractions following pretreatment.
The efficient fermentation of sugar hydrolysate produced from WF, which is essentially free of any inhibitory compounds, provides benchmarking data for fermentation of CGT C6 sugars by ThermosaccÒ Dry. Under these circumstances, fermentations were completed within 6–7 h yielding 16 g/L ethanol with an overall maximum ethanol volumetric productivity of 2.28 g/L/h. This corresponds to an ethanol yield of 85% theoretical and is consistent with reported ethanol yields from pretreated CGT feedstocks (Agblevor et al., 2003; Jeoh and Agblevor, 2001). The rapid metabolism of glucose from WS sugar hydrolysates was completed within 8 h, however; the metabolism of some minor C6 sugars (galactose) required an addition 2 h to reach completion. A slightly higher maximum ethanol yield of 88% theoretical is attributed to the utilisation of these minor sugars. The maximum volumetric productivity was 1.8 g/L/h demonstrating that the level of inhibitory compounds produced during the pretreatment phase is within the yeast’s tolerance level. In the third approach, SSF of whole CGT slurries achieved a final ethanol titre of 12.88 g/L (or 70.9% theoretical) within a 96 h period. The slower rate of ethanol production is attributed to reduced cellulases hydrolysis efficiencies encountered by suboptimal working temperatures (33 °C in this case). However, the productivity rates show that ethanol production was virtually completed by about 48 h. Although this is considerably longer than fermentation times observed for the separate hydrolysis and fermentations, if the duration of enzymatic hydrolysis (48 h in this study) is included than the overall time required to complete ethanol production is comparable between the two approaches. Based on glucose recovery data from optimised pretreatment conditions, calculated ethanol fermentation yields for the three processing options are 101, 149 and 142 L ethanol per metric tonne of original CGT for WF, WS and SSF respectively. From an economic and logistical perspective, the SSF approach would be more favourable in an industrial setting. Although process efficiencies described herein are similar to those reported by Jeoh and Agblevor (2001), their estimated potential ethanol yield at 270 L/ t was greater because of the higher sugar content in their CGT biomass, and the potential yields of ethanol from pentose sugars. On the basis of this latter premise, conversion of released pentose sugars (122 kg of xylose/t) would yield an additional 79 L/metric tonne.
4. Conclusion This study demonstrates using dilute sulfuric acid at elevated temperatures is an exemplary pretreatment method for CGT feedstocks, achieving glucose conversions of 89%. The susceptibility of cotton fibre cellulose to solubilisation during pretreatment dictates enzymatic hydrolysis of whole slurries is necessary to maximise glucose recoveries. Utilising the full complement of C5 and C6 sugars for ethanol production along with a consolidated whole slurry SSF approach has the potential to improve the profitability and
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