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Economic and environmental assessment of syrup production. Colombian case
Bioresource Technology 161 (2014) 84–90
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Economic and environmental assessment of syrup production. Colombian case Javier A. Dávila a, Valentina Hernández a, Eulogio Castro b, Carlos A. Cardona a,⇑ a b
Instituto de Biotecnología y Agroindustria, Departamento de Ingeniería Química, Universidad Nacional de Colombia sede Manizales, Cra. 27 No. 64-60, Manizales, Colombia Departamento de Ingeniería Química, Ambiental y de los Materiales, Universidad de Jaen, Campus Las Lagunillas, Spain
h i g h l i g h t s Six Colombian agroindustrial wastes were used for glucose syrup production. A techno-economic analysis for glucose syrup production was made. An environmental analysis of glucose syrup production was made. Energy cost is an important factor for the total production cost of syrups. Heat integration strategy is suggested for syrup production.
a r t i c l e
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Article history: Received 3 December 2013 Received in revised form 25 February 2014 Accepted 27 February 2014 Available online 12 March 2014 Keywords: Agroindustrial wastes Syrup Techno-economic analysis Environmental analysis
a b s t r a c t This work presents a techno-economic and environmental assessment of the glucose syrups production from sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs. According to the economic analysis, the corncob had both, the lowest production cost (2.48 USD/kg syrup) and the highest yield (0.61 kg of sugars/kg of wet agroindustrial waste) due to its high content in cellulose and hemicellulose. This analysis also revealed that a heat integration strategy is necessary since the utilities consumption represent an important factor in the production cost. According to the results, the pretreatment section requires more energy in the syrup production in comparison with the requirements of other sections such as production and sugar concentration. The environmental assessment revealed that the solid wastes such as furfural and hydroxymethylfurfural affected the environmental development of the process for all the agroindustrial wastes, being the rice husk the residue with the lowest environmental impact. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction One of the main issues in the management of agroindustrial chains in Colombia is related to the final disposal of the generated residues. Residues from fruits, vegetables, corn, wood and other industries based on biomass are obtained in large quantities. This fact is due to the low efficiencies in different processing steps such as cultivation, transportation, cooling chain and distribution, among others. The potential chemical composition of the agroindustrial wastes allows using them as source to obtain value added products under modern biomass utilization technologies (Quintero et al., 2011). Different agroindustrial residues have been used to produce compounds with high value in the market. Ethanol has been ⇑ Corresponding author. Tel.: +57 6 8879300x50417; fax: +57 6 8859300x50199. E-mail address: [email protected] (C.A. Cardona). http://dx.doi.org/10.1016/j.biortech.2014.02.131 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
produced from empty fruit bunches reaching yields of 59.6% after hydrolysis (Piarpuzán et al., 2011) also; fuel ethanol has been produced from lignocellulosic biomass with an energy consumption of 41.96 MJ/l of ethanol (Cardona and Sánchez, 2006). Rice husk has been used as substrate for microalgae growth to produce oil reaching a yield of 0.37 kg of oil/kg of dry microalgae with a production cost of 0.56 USD/kg of oil (Jaramillo et al., 2012). In the case of fruits, compounds as essential oils, pectin, flavonoids, phenolic compounds and anthocyanins, among others can be obtained from their residues (Yepes et al., 2008). On the other hand, residues such as sugarcane bagasse and corncobs are considered important lignocellulosic residues, because of its large quantities and its potential application in ethanol production. Some important agroindustrial wastes in Colombia are related to the residues generated from Plantain (Musa sapientum), Cassava (Manihot esculenta), Mango (Manguifera Indica L.), Rice (Oryza sativa) and Corn (Zea mays) processing. For 2011, Colombia had a
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production of 2.82, 1.87, 2.24, 23.18, 1.07 and 0.22 millions of tonnes of plantains, cassava, rice, sugarcane, corn and mango, respectively (MADS, 2012). The agroindustrial chains of the crops above mentioned have not only high losses due to the low efficiencies in several production steps but also large quantities of generated residues. For instance, in the case of plantain approximately 20% to 30% of the total biomass is utilized while the remaining is used as fertilizer and as animal supplement food (Botero and Mazzeo, 2009). In the cassava processing approximately 96.2% of the total wastes correspond to solids which have an inadequate management causing negative impact over the environment (Marmolejo et al., 2008). In the pulping process of mango, approximately 55% of the residues are obtained as solids wastes (Mejía et al., 2007). In the case of rice, 400,000 tonnes of husk are produced per year (Piñeros et al., 2011). In the corn processing, the corncobs production is approximately 532,000 tonnes per year. Finally, taking into account that the sugarcane production in 2011 was 23.18 millions of tonnes (MADS, 2012) and that this crop generates approximately 280 kg of bagasse per tonne of sugarcane then, 6.49 millions of tonnes of sugarcane bagasse were produced. The agroindustrial wastes above mentioned have low or no cost throughout the year, besides its availability and its important composition in cellulose and hemicellulose are characteristics that allow considering these wastes as adequate substrates for sugar production (Mejía et al., 2007; Piñeros et al., 2011). Moreover, some of these agroindustrial wastes can also be considered as potential feedstocks for ethanol production in Colombia (Quintero et al., 2008). Considering the above mentioned, this work presents a technoeconomic and environmental assessment for the glucose syrup production in the Colombian context using sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs as feedstocks. Computer-aided process engineering tools are used as a promising alternative to evaluate this kind of processes. In order to carry out the techno-economic and environmental assessment, operational conditions, yields and relevant data from experimental works reported in the literature are used.
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global atmospheric impacts and regional atmospheric impacts). These impacts are calculated according to parameter values such as Lethal Dose (LD50) which eliminates the 50% of the population (e.g. rats), Limit Concentration (LC50) which eliminates the 50% of the population and Permissible Exposure Limit (PEL) for a substance or compound. The steps one and two using Aspen Plus software were performed following a sequence of calculations from the information given by the user. Once the flow diagram and compounds are defined, the thermodynamic models are selected according to the characteristics of each compound and units as well as operational conditions. After, the simulation is run to obtain the mass and energy balances of the process. Thus, the economic analysis is made extracting the information about mass and energy balances, flows, temperatures, pressures and number of units from Aspen Plus. This information is combined with the economic parameters given by the user such as economic life of the project, tax rate, desired rate of return, utilities, costs (raw materials, reagents, products, electricity, potable water and fuel), operating cost (operator, supervisor) and depreciation method to carry out the economic evaluation. Once all of this information is provided, it is used to calculate the raw materials and utilities costs and the depreciation expensive as well as the operating, general and administrative, plant overhead and charge costs. Thus, it is possible to calculate the total production cost and energy requirements of the process. 2.1. Raw material Table 1 shows the chemical composition of sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs, which were the selected agroindustrial wastes (Baah et al., 1999; Dagnino et al., 2013; Guo and Rockstraw, 2007; Happi et al., 2007; Hoareau et al., 2004; López et al., 2013; Mansilla et al., 1998; Marmolejo et al., 2008; Mejía et al., 2007; Miura et al., 2004; Pandey et al., 2000). 2.2. Process simulation description
2. Methods The methodology employed in this work consists on three steps using different computational tools. The first step corresponds to the process simulation to obtain the mass and energy balances of the process using Aspen Plus V8.0 (AspenTech: Cambridge, MA). The physicochemical properties of all the involved compounds in the simulation were obtained from the National Institute of Standards of Technology (NIST, 2012). To calculate the properties in the liquid and vapor phases, the Non Random Two Liquids (NRTL) model and the Hayden O’Conell (HOC) equation were used, respectively. NRTL model was used to estimate the activity coefficients of all the compounds from its mole fractions in the liquid phase. The HOC equation provides a method for predicting a second virial coefficient for multi-compounds vapor mixtures. These methods are used to calculate successfully phase equilibria in the type of mixtures with non-conventional compounds (Cardona and Sánchez, 2006; Jaramillo et al., 2012; Quintero et al., 2008). The second step corresponds to the economic analysis using Aspen Process Economic Analyzer (AspenTech: Cambridge, MA). This evaluation was developed for the six proposed agroindustrial wastes used as raw materials. The final step corresponds to the environmental analysis where the Waste Algorithm Reduction Software (WAR GUI) developed by the U.S. Environmental Protection Agency (EPA) was employed. This software uses a method of direct data sum based on the mass and energy streams of the process and the environmental impact that these streams can have over four principal categories (Human toxicity, ecological toxicity,
Fig. 1 shows the glucose syrup production scheme, which is the same for all the selected raw materials. The process begins drying the feedstock with air to remove the moisture. Then, the dried material was milled to obtain particles with sizes smaller than 0.45 mm. In order to improve the cellulose accessibility, a diluted acid hydrolysis using sulfuric acid (2% v/v) at 121 °C was carried out. Diluted acid hydrolysis was selected not only because it is the most commonly employed chemical pretreatment but also because it permits to enhance biomass digestibility obtaining good cellulose accessibility. Besides, this pretreatment allows achieving high reaction rates and producing lower quantities of fermentation inhibitors that could reduce the syrup quality (Agbor et al., 2011; Dagnino et al., 2013; Haghighi et al., 2013). Other pretreatment methods such as ionic liquids and organosolv present higher costs because of the solvent recovery. In the case of Ammonia Fiber Explosion (AFEX), costs increase because of the ammonia (Haghighi et al., 2013). Other methods such as concentrated acid hydrolysis and steam explosion produce appreciable amounts of toxic compounds, affecting the quality of the syrup. On the other hand, alkaline methods require long pretreatment resident time (Agbor et al., 2011; Haghighi et al., 2013). From this pretreatment, traces of furfural and hydroxymethylfurfural (HMF) were obtained. After, the liquid phase was sent to a xylose recovery process while the solid phase was used to produce glucose through an enzymatic hydrolysis at 50 °C (Sindhu et al., 2011). Once the stream containing xylose is separated, the remaining water is evaporated. Additionally, a detoxification process with
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Table 1 Chemical composition for the selected Colombian agroindustrial wastes. Sugarcane bagasse (SCB), plantain husk (PH), cassava husk (CH), mango peel (MP), rice husk (RH), corncob (CC). Component
Cellulose Hemicellulose Lignin Sugar Ash Protein Water Total
SCB (%)
PH (%)
CH (%)
MP (%)
RH (%)
CC (%)
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
24.86 18.40 6.46 0.89 0.47 0.88 48.04 100
47.84 35.41 12.44 1.72 0.90 1.69
1.48 1.66 1.57 0.24 0.91 2.25 91.88 100
18.22 20.45 19.34 2.96 11.22 27.71
7.43 10.37 1.78 5.68 0.37 3.72 70.65 100
25.32 35.33 6.06 19.35 1.27 12.67
5.76 4.10 5.21 6.39 0.01 2.06 76.46 100
24.47 17.44 22.14 27.15 0.04 8.76
38.02 16.57 20.38 1.46 14.62 3.37 5.57 100
40.26 17.55 21,58 1.55 15.48 3.57
34.07 33.88 13.63 1.75 1.93 5.93 8.81 100
37.36 37.15 14.95 1.92 2.12 6.50
100
100
100
100
100
100
Fig. 1. Scheme of glucose syrup production from Colombian agroindustrial wastes.
Ca(OH)2 was carried out at 60 °C to remove furfural and HMF traces, which are trapped in the resulting gypsum (Millati et al., 2002). Thus, a stream rich in xylose is obtained. On the other hand, the glucose obtained from the enzymatic hydrolysis was separated from the remaining solids, which correspond to lignin. Finally, the streams rich in xylose and glucose are mixed obtaining the final syrup. The purpose, assumptions, conditions and methods used for the principal units in the simulation are summarized in Table 2. 2.3. Economic analysis The economic analysis was made calculating the production cost per kg of syrup. The total production cost considers the total raw material, utilities, operating, labor and maintenance costs as well as the operating charges, plant overhead and general and administrative costs. Additionally, tax and interest rates were taken according to the laws in Colombia as 25% and 17%, respectively. Table 3 shows the economic parameters taken for economic analysis. Finally, the raw material cost was 0.021 USD/kg (Calculated to a distance of 140 km with a truck of three axles).
2.4. Environmental analysis The environmental analysis evaluates eight environmental impact categories which are: Human Toxicity Potential by Ingestion (HTPI), Human Toxicity Potential by Dermal and Inhalation Exposure (HTPE), Terrestrial Toxicity Potential (TTP), Aquatic Toxicity Potential (ATP), Global Warming Potential (GWP), Ozone Depletion Potential (ODP), Photochemical Oxidation Potential (PCOP) and Acidification Potential (AP). The Potential Environmental Impact (PEI) of the process was calculated per kilogram of product (syrup). Natural Gas was used as fuel to cover the heat requirements in the syrup production. 3. Results and discussion 3.1. Process simulation Total energy and chemical requirements as well as out streams of the process for each raw material are showed in Table 4. Total energy consumption is very similar for all the raw materials used.
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J.A. Dávila et al. / Bioresource Technology 161 (2014) 84–90 Table 2 Purposes, conditions, methods and assumptions for the principal units used in the simulation. Unit
Purpose
Conditions and unit specifications
Method
Assumptions
Dryer
Remove part of the water (Up to 20%) Improve the accessibility of the cellulose and xylose production
80 °C, 1 bar Atmospheric tray dryer 121 °C, 1 bar, (2% v/v of H2SO4) Agitated tank enclosed Cellulose + water = Glucose (Conversion = 1%) Hemicellulose + water = xylose (Conversion = 93%) Glucose = HMF + 3 water (Conversion = 1%) HMF + 2 water = L.A + F.A. (Conversion = 1%) Xylose = 3 water + Furfural (Conversion = 20%) 111 °C, 1 bar for both xylose and glucose Standard tube vertical evaporator, one effect 60 °C, 1 bar Ca(OH)2 + H2SO4 = CaSO4⁄2H2O (Conversion = 99%) Agitated tank enclosed 50 °C, 1 bar, 7% (wt) biomass/ enzyme Aagitated tank enclosed
NRTL
No
NRTL
Low production of glucose, HMF and acids (Levunilic and formic) Haghighi Mood et al. (2013)
NRTL-HOC
No
NRTL
All furfural and HMF are trapped in the gypsum Millati et al. (2002)
User model (Yields from literature)
Yield of 0.6 g/g from Sindhu et al. (2011)
Acid hydrolysis
Evaporators
Remove part of the water (60% for both xylose and glucose)
Detoxification
Remove furfural and HMF
Enzymatic hydrolysis
Glucose production
Table 3 Economic parameters taken for economic analysis.
a b c d e
Item
Price
Unit
Operatora Supervisora Electricitya Potable Watera Fuelb Raw materialc Sulfuric acidd Calcium hydroxided Enzymee
2.14 4.29 0.10 1.25 7.21 0.021 0.094 0.056 3
(USD/h) (USD/h) (USD/KWh) (USD/m3) (USD/MMBTU) (USD/kg) (USD/kg) (USD/kg) (USD/kg)
Typical prices in Colombia. Estimated cost of gas to a period range of 2015 – 2035 (NME, 2013). Calculated to a distance of 140 km with a truck of three axles. Taken from ICIS Prices (ICIS, 2013). Taken from Alibaba International prices (ALIBABA, 2013).
This because of the volume for acid hydrolysis was the same for all the agroindustrial wastes. Thus, the subsequent units operated with similar flows and conditions. This reveals that in average (taking sugarcane bagasse as base case) for 1 tonne of raw material, 30, 0.6, 0.45 and 0.041 tonnes of water, sulfuric acid (the same for all the raw materials), calcium hydroxide and enzymes respectively, are required. On the other hand, 29.7 tonnes of residual water are obtained and the total solid wastes (Gypsum) ranges from 1.4 to 2.1 tonnes/tonne of agroindustrial waste depending on the raw material used. Gypsum with traces of furfural and HMF was produced from xylose concentration step, while the
solids with high lignin content were obtained from glucose production step. Table 5 shows flows, sugar content and yields obtained for each one of the raw materials. Here, it is found that both yield and sugar concentration, are highest and lower for corncobs and plantain husk, respectively. These results are totally explained for the original content of cellulose and hemicellulose because a high content of these compounds improve the hydrolysis and the final yields (Latif and Rajoka, 2001). In the same way, rice husk had a good yield, reason for which it is considered a good raw material for the glucose production (Arezoo et al., 2011).
3.2. Economic analysis Table 6 shows both, cost and its corresponding share in the syrup production for each agroindustrial waste used. The economic analysis showed a similar distribution in all the economic parameters for all the raw materials considered and the differences are due to the variations on initial chemical composition because of variations on moisture, cellulose and hemicellulose can define the cost associated for both, units (drying, evaporation, fermentation, among others) and reagents (enzymes, water, among other). Total utilities cost represent approximately 80% of the total project cost in all the cases while, general and administrative, total raw material and depreciation expensive costs are between 4% and 8% approximately. This is in agreement with the fact that the two most important parameters in the glucose syrup production are raw materials and utilities (Shewale, 2008).
Table 4 Total energy, chemical requirements and out streams of each raw material. Raw material
Total Energy (kJ/kg)
Water (kg/h)
Enzyme (kg/h)
Ca(OH)2 (kg/h)
Residual water (kg/h)
Solids (kg/h)
Gypsum (kg/h)
Sugarcane bagasse Plantain husk Cassava husk Mango peel Rice husk Corncobs
2548 2543 2548 2543 2543 2558
30,000 29,562 29,774 29,716 34,247 33,923
41 2.44 12.25 9.50 62.70 56.19
450 40.59 253.61 100.27 405.24 828.58
29,700 29,266 29,476 29,418 33,904 33,583
517 539 541 512 654 725
1874 1400 1623 1496 1757 2100
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Table 5 Flow, sugar content and yields of the glucose syrups obtained of each raw material. Raw material
Flow (kg/h)
Total sugars (%)
Yielda
Sugarcane bagasse Plantain husk Cassava husk Mango peel Rice husk Corncobs
692.65 286.29 418.47 360.71 784.04 909.40
62.21 20.11 40.91 35.13 66.66 67.12
0.43 0.06 0.17 0.12 0.52 0.61
a
Yield is in kg of total sugars per kg of wet agroindustrial waste.
The energy requirements are the main factors that contribute with a high total production cost (80% as was mentioned above) because the pretreatment of these kinds of raw materials involves the major energy consumption in these processes. According to Fig. 1, drying, milling and the acid hydrolysis compose the pretreatment section while processes such as evaporation, detoxification and enzymatic hydrolysis compose the section of production and concentration of sugars. In this sense, the energy analysis showed that are required 12, 1089 and 1017 kJ/kg of syrup for drying, acid hydrolysis and evaporation respectively. Thus, the diluted acid hydrolysis in the pretreatment section has the major energy consumption even more than the energy requirements in the evaporation to concentrate both, xylose and glucose. Pretreatment is among the most costly steps in the biochemical conversion of lignocellulosic biomass and represents a high percentage of the total production cost (Njoku et al., 2012). Specially, the dilute acid hydrolysis as pretreatment is more expensive that other physicochemical pretreatments methods (Agbor et al., 2011). However, according to (Haghighi et al., 2013) if other pretreatment methods are used, the hemicellulose removal and solubilization could be affected. This is the case of physical methods, alkaline methods, ionic liquids usage, ozonolysis, AFEX method and biological methods for which the final effect on hemicellulose removal and solubilization is lower than that reached with diluted acid hydrolysis. On the other hand, other pretreatments such as organosolv, CO2 explosion, wet oxidation, concentrated acid hydrolysis and liquid hot water method have a low effect to avoid fermentation inhibitors formation, which is very important for syrup production. From these two important characteristics, other pretreatment methods could not be as efficient as the most typically diluted acid hydrolysis. Besides, other pretreatment methods also could have other economic implications based on high pressures or temperatures, solvent costs and its recycle and long pretreatment resident times, among others. Anyway, it is evident that the pretreatment section for these kinds of raw
materials needs further inputs in terms of research and development (Pandey et al., 2000). In order to reduce the utility consumption and thus, the heat and cooling requirements it is necessary to add a heat integration strategy (Sánchez and Cardona, 2012). From the economic analysis, corncob and plantain husk had the lowest and highest production cost with 2.48 and 7.88 USD/kg of syrup, respectively. The prices of syrups in the market depend on the Dextrose Equivalent (DE) measured, which represents the total content of the reducing sugars. For a syrup with a DE between 40 and 60, the typically sale price ranges from 0.48 to 0.6 USD/kg of syrup. Fig. 2 shows the production cost per kg of syrup for all raw materials used which are compared with the sale price found in the market according to the wholesale list prices for glucose syrups published by Milling & Baking (News, 2013), with a sale price of 0.64 USD/kg of syrup. Despite the low production cost in the case of corncobs (2.48 USD/kg of syrup) this cost is higher that the typical sale prices in the market. This means that the syrups from Colombian agroindustrial wastes are not well established yet and it suggests that is necessary to refine the biotechnological production routes and concentration processes. This agrees with the results obtained in Ghana where a reduction in the prices of glucose syrups only are achieved if the quality of the syrup is reduced (FAO, 2013). According to the economic analysis, it can be seen that the corncobs are the most suggested raw material between the six Colombian agroindustrial wastes evaluated to produce syrups. Although, it is necessary to improve the biotechnological process by mean of refining different steps in the production scheme such as the pretreatment and concentration methods.
Fig. 2. Production cost per kg of syrup.
Table 6 Distribution of the total project costs. Sugarcane bagasse (SCB), plantain husk (PH), cassava husk (CH), mango peel (MP), rice husk (RH), corncob (CC). Item
a
Depreciation expense Total raw materials cost Total utilities cost Operating labor cost Maintenance cost Operating charges Plant overhead b G and A Cost Total project cost a b
SCB
PH
CH
MP
RH
CC
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
0.77
4.31
0.77
4.36
0.77
4.36
0.77
4.31
0.77
4.31
0.77
4.31
1.19
6.64
1.02
5.76
1.03
5.76
1.20
6.64
1.20
6.64
1.20
6.64
14.4 0.12
80.1 0.67
14.4 0.12
80.9 0.67
14.4 0.12
80.9 0.67
14.4 0.12
80.1 0.67
14.4 0.12
80.1 0.67
14.4 0.12
80.1 0.67
0.08 0.03
0.46 0.17
0.08 0.03
0.47 0.17
0.08 0.03
0.47 0.17
0.08 0.03
0.46 0.17
0.08 0.03
0.46 0.17
0.08 0.03
0.46 0.17
0.10 1.27 18.03
0.56 7.1 100
0.10 1.26 17.85
0.57 7.08 100
0.10 1.26 17.85
0.57 7.08 100
0.10 1.28 18.03
0.56 7.09 100
0.10 1.28 18.03
0.56 7.09 100
0.10 1.28 18.03
0.56 7.09 100
Depreciation expensive was calculated using the straight-line method. G and A is referrer to general and administrative costs.
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Fig. 3. Leaving Potential Environmental Impact (PEI) of the process.
3.3. Environmental analysis Fig. 3 shows the leaving Potential Environmental Impact (PEI), which demonstrates that the total PEI cannot be mitigated. The environmental categories HTPI, HTPE and TTP are the most affected due to the compounds as lignin and the compounds trapped by the gypsum (furfural and HMF), which are presented in the solid outlet streams. On the other hand, AP environmental category is affected due to the H2SO4 used in the pretreatment process. Rice husk, sugarcane bagasse and corncobs presented the lowest total PEI, this is agreeing with the fact that the highest yields correspond to these raw materials whereby compounds such as furfural and HMF are formed in low quantities when the yield of xylose is high. Because mass integration was not considered in the production scheme, the flows of residual water obtained from the concentration of sugars, contribute to the PEI of the process because this water contains acid (H2SO4), which was not separated and affects considerably the environmental development. 4. Conclusions All the selected raw materials are promising feedstocks, however corncob is the most attractive of them to produce syrup. The production cost suggests that, it is necessary to improve the yields and energy consumption in the pretreatment, even if another pretreatment method is used. This to assures hemicellulose removal and solubilization as well as low fermentation inhibitors formation. The agroindustrial wastes with highest yields presented the lowest total PEI. However, it is necessary to reduce solid wastes. Heat integration strategy is suggested to reduce the utilities consumption, which are the most important economic factor in the syrup production. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2014.02. 131. References Agbor, V.B., Cicek, N., Sparling, R., Berlin, A., Levin, D.B., 2011. Biomass pretreatment: fundamentals toward application. Biotechnol. Adv. 29 (6), 675– 685. ALIBABA, 2013. International Prices. Available in: (accessed 25.07.2013). Arezoo, G., Soleiman, M., Rabeah, M. 2011. Management of Glucose Production Process from Rice Husk by Solid State Fermentation Method. International Conference on Biotechnology and Environment Management IPCBEE vol.18. Available in: (accessed 25.07.2013). Baah, J., Tait, R.M., Tuah, A.K., 1999. The effect of supplementation with ficus leaves on the utilization of cassava peels by sheep. Bioresour. Technol. 67 (1), 47–51.
Botero, L.J.D., Mazzeo, M.M.H., 2009. Obtainment of rachis flour from Dominico harton plantain, and its quality evaluation with industrialization purposes. Vector 4 (1), 83–94. Cardona, C.A., Sánchez, O.J., 2006. Energy consumption analysis of integrated flowsheets for production of fuel ethanol from lignocellulosic biomass. Energy 31 (13), 2447–2459. Dagnino, E.P., Chamorro, E.R., Romano, S.D., Felissia, F.E., Area, M.C., 2013. Optimization of the acid pretreatment of rice hulls to obtain fermentable sugars for bioethanol production. Ind. Crop. Prod. 42, 363–368. FAO. 2013. Production of glucose syrup from high quality cassava flour. Available in (accessed 04.07.2013). Guo, Y., Rockstraw, D.A., 2007. Activated carbons prepared from rice hull by onestep phosphoric acid activation. Microporous Mesoporous Mater. 100 (1–3), 12–19. Haghighi, M.S., Hossein Golfeshan, A., Tabatabaei, M., Salehi Jouzani, G., Najafi, G.H., Gholami, M., Ardjmand, M., 2013. Lignocellulosic biomass to bioethanol, a comprehensive review with a focus on pretreatment. Renew. Sust. Energ. Rev. 27, 77–93. Happi, E.T., Andrianaivo, R.H., Wathelet, B., Tchango, J.T., Paquot, M., 2007. Effects of the stage of maturation and varieties on the chemical composition of banana and plantain peels. Food Chem. 103 (2), 590–600. Hoareau, W., Trindade, W.G., Siegmund, B., Castellan, A., Frollini, E., 2004. Sugar cane bagasse and curaua lignins oxidized by chlorine dioxide and reacted with furfuryl alcohol: characterization and stability. Polym. Degrad. Stab. 86 (3), 567–576. ICIS., 2013. Indicative Chemical Prices A–Z. Available in: (accessed 14.07.2013). Mansilla, H.D., Baeza, J., Urzúa, S., Maturana, G., Villaseñor, J., Durán, N., 1998. Acidcatalysed hydrolysis of rice hull: evaluation of furfural production. Bioresour. Technol. 66 (3), 189–193. Marmolejo, L.F., Pérez, A., Torres, P., Cajigas, A.A., Cruz, C.H. 2008. Utilization of the solid wastes generated in small scale cassava starch production. Livestock Research for Rural Development 20(7), Available in (accessed 17.06.2013). Mejía, G.L.F., Martínez, C.H.A., Betancourt, G.J.E., Castrillón, C.C.E., 2007. Usage of the common mango agroindustrial waste (mangifera indica L.) in the destraction of fermentables sugars. Revista Ingeniería y Ciencia 3 (6), 41–62. Millati, R., Niklasson, C., Taherzadeh, M.J., 2002. Effect of pH, time and temperature of overliming on detoxification of dilute-acid hydrolyzates for fermentation by Saccharomyces cerevisiae. Process Biochem. 38 (4), 515–522. Miura, S., Arimura, T., Itoda, N., Dwiarti, L., Feng, J.B., Bin, C.H., Okabe, M., 2004. Production of l-lactic acid from corncob. J. Biosci. Bioeng. 97 (3), 153–157. News, M.B. 2013. Table 7 – U.S. wholesale list price for glucose syrup, Midwest markets, monthly, quarterly, and by calendar and fiscal year 1. Available in: (accessed 06.07.2013). NIST, N.I.o.S.a.T.V. 2012. Gaithersburg, MD. Available from
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Pandey, A., Soccol, C.R., Nigam, P., Soccol, V.T., Vandenberghe, L.P.S., Mohan, R., 2000. Biotechnological potential of agro-industrial residues. II: cassava bagasse. Bioresour. Technol. 74 (1), 81–87. Piarpuzán, D., Quintero, J.A., Cardona, C.A., 2011. Empty fruit bunches from oil palm as a potential raw material for fuel ethanol production. Biomass Bioenergy 35 (3), 1130–1137. Piñeros, C.Y., Velasco, G.A., Proaños, J., Cortes, W., Ballesteros, I., 2011. Production of fermentables sugars by enzymatic hydrolysis of steam-exploded rice husks, vol. 24. Revista Ion, No. 2. Quintero, J.A., Montoya, M.I., Sanchez, O.J., Giraldo, O.H., Cardona, C.A., 2008. Fuel ethanol production from sugarcane and corn: comparative analysis for a Colombian case. Energy 33 (3), 385–399. Quintero, J.A., Rincon, L.E., Cardona, C.A., 2011. Chapter 11. Production of Bioethanol from Agroindustrial residues as feedstocks. Biofuels, 251–285.
Sánchez, Ó.J., Cardona, C.A., 2012. Conceptual design of cost-effective and environmentally-friendly configurations for fuel ethanol production from sugarcane by knowledge-based process synthesis. Bioresour. Technol. 104, 305–314. Shewale, S.D. 2008. Studies in the Enzymatic depolymerisation of natural polysaccharides (Ph.D. thesis). University of Mumbai, India. Available in: (accessed 29.08.2013). Sindhu, R., Kuttiraja, M., Binod, P., Janu, K.U., Sukumaran, R.K., Pandey, A., 2011. Dilute acid pretreatment and enzymatic saccharification of sugarcane tops for bioethanol production. Bioresour. Technol. 102 (23), 10915–10921. Yepes, S.M., Montoya, N.L.J., Orozco, S.F., 2008. Agroindustrial waste valorization – fruits – in Medellín and the south of Valle de Aburrá, Colombia. Fac. Nal. Agr. Medellìn 61 (1), 4422–4431.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Economic and environmental assessment of syrup production. Colombian case Javier A. Dávila a, Valentina Hernández a, Eulogio Castro b, Carlos A. Cardona a,⇑ a b
Instituto de Biotecnología y Agroindustria, Departamento de Ingeniería Química, Universidad Nacional de Colombia sede Manizales, Cra. 27 No. 64-60, Manizales, Colombia Departamento de Ingeniería Química, Ambiental y de los Materiales, Universidad de Jaen, Campus Las Lagunillas, Spain
h i g h l i g h t s Six Colombian agroindustrial wastes were used for glucose syrup production. A techno-economic analysis for glucose syrup production was made. An environmental analysis of glucose syrup production was made. Energy cost is an important factor for the total production cost of syrups. Heat integration strategy is suggested for syrup production.
a r t i c l e
i n f o
Article history: Received 3 December 2013 Received in revised form 25 February 2014 Accepted 27 February 2014 Available online 12 March 2014 Keywords: Agroindustrial wastes Syrup Techno-economic analysis Environmental analysis
a b s t r a c t This work presents a techno-economic and environmental assessment of the glucose syrups production from sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs. According to the economic analysis, the corncob had both, the lowest production cost (2.48 USD/kg syrup) and the highest yield (0.61 kg of sugars/kg of wet agroindustrial waste) due to its high content in cellulose and hemicellulose. This analysis also revealed that a heat integration strategy is necessary since the utilities consumption represent an important factor in the production cost. According to the results, the pretreatment section requires more energy in the syrup production in comparison with the requirements of other sections such as production and sugar concentration. The environmental assessment revealed that the solid wastes such as furfural and hydroxymethylfurfural affected the environmental development of the process for all the agroindustrial wastes, being the rice husk the residue with the lowest environmental impact. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction One of the main issues in the management of agroindustrial chains in Colombia is related to the final disposal of the generated residues. Residues from fruits, vegetables, corn, wood and other industries based on biomass are obtained in large quantities. This fact is due to the low efficiencies in different processing steps such as cultivation, transportation, cooling chain and distribution, among others. The potential chemical composition of the agroindustrial wastes allows using them as source to obtain value added products under modern biomass utilization technologies (Quintero et al., 2011). Different agroindustrial residues have been used to produce compounds with high value in the market. Ethanol has been ⇑ Corresponding author. Tel.: +57 6 8879300x50417; fax: +57 6 8859300x50199. E-mail address: [email protected] (C.A. Cardona). http://dx.doi.org/10.1016/j.biortech.2014.02.131 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
produced from empty fruit bunches reaching yields of 59.6% after hydrolysis (Piarpuzán et al., 2011) also; fuel ethanol has been produced from lignocellulosic biomass with an energy consumption of 41.96 MJ/l of ethanol (Cardona and Sánchez, 2006). Rice husk has been used as substrate for microalgae growth to produce oil reaching a yield of 0.37 kg of oil/kg of dry microalgae with a production cost of 0.56 USD/kg of oil (Jaramillo et al., 2012). In the case of fruits, compounds as essential oils, pectin, flavonoids, phenolic compounds and anthocyanins, among others can be obtained from their residues (Yepes et al., 2008). On the other hand, residues such as sugarcane bagasse and corncobs are considered important lignocellulosic residues, because of its large quantities and its potential application in ethanol production. Some important agroindustrial wastes in Colombia are related to the residues generated from Plantain (Musa sapientum), Cassava (Manihot esculenta), Mango (Manguifera Indica L.), Rice (Oryza sativa) and Corn (Zea mays) processing. For 2011, Colombia had a
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production of 2.82, 1.87, 2.24, 23.18, 1.07 and 0.22 millions of tonnes of plantains, cassava, rice, sugarcane, corn and mango, respectively (MADS, 2012). The agroindustrial chains of the crops above mentioned have not only high losses due to the low efficiencies in several production steps but also large quantities of generated residues. For instance, in the case of plantain approximately 20% to 30% of the total biomass is utilized while the remaining is used as fertilizer and as animal supplement food (Botero and Mazzeo, 2009). In the cassava processing approximately 96.2% of the total wastes correspond to solids which have an inadequate management causing negative impact over the environment (Marmolejo et al., 2008). In the pulping process of mango, approximately 55% of the residues are obtained as solids wastes (Mejía et al., 2007). In the case of rice, 400,000 tonnes of husk are produced per year (Piñeros et al., 2011). In the corn processing, the corncobs production is approximately 532,000 tonnes per year. Finally, taking into account that the sugarcane production in 2011 was 23.18 millions of tonnes (MADS, 2012) and that this crop generates approximately 280 kg of bagasse per tonne of sugarcane then, 6.49 millions of tonnes of sugarcane bagasse were produced. The agroindustrial wastes above mentioned have low or no cost throughout the year, besides its availability and its important composition in cellulose and hemicellulose are characteristics that allow considering these wastes as adequate substrates for sugar production (Mejía et al., 2007; Piñeros et al., 2011). Moreover, some of these agroindustrial wastes can also be considered as potential feedstocks for ethanol production in Colombia (Quintero et al., 2008). Considering the above mentioned, this work presents a technoeconomic and environmental assessment for the glucose syrup production in the Colombian context using sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs as feedstocks. Computer-aided process engineering tools are used as a promising alternative to evaluate this kind of processes. In order to carry out the techno-economic and environmental assessment, operational conditions, yields and relevant data from experimental works reported in the literature are used.
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global atmospheric impacts and regional atmospheric impacts). These impacts are calculated according to parameter values such as Lethal Dose (LD50) which eliminates the 50% of the population (e.g. rats), Limit Concentration (LC50) which eliminates the 50% of the population and Permissible Exposure Limit (PEL) for a substance or compound. The steps one and two using Aspen Plus software were performed following a sequence of calculations from the information given by the user. Once the flow diagram and compounds are defined, the thermodynamic models are selected according to the characteristics of each compound and units as well as operational conditions. After, the simulation is run to obtain the mass and energy balances of the process. Thus, the economic analysis is made extracting the information about mass and energy balances, flows, temperatures, pressures and number of units from Aspen Plus. This information is combined with the economic parameters given by the user such as economic life of the project, tax rate, desired rate of return, utilities, costs (raw materials, reagents, products, electricity, potable water and fuel), operating cost (operator, supervisor) and depreciation method to carry out the economic evaluation. Once all of this information is provided, it is used to calculate the raw materials and utilities costs and the depreciation expensive as well as the operating, general and administrative, plant overhead and charge costs. Thus, it is possible to calculate the total production cost and energy requirements of the process. 2.1. Raw material Table 1 shows the chemical composition of sugarcane bagasse, plantain husk, cassava husk, mango peel, rice husk and corncobs, which were the selected agroindustrial wastes (Baah et al., 1999; Dagnino et al., 2013; Guo and Rockstraw, 2007; Happi et al., 2007; Hoareau et al., 2004; López et al., 2013; Mansilla et al., 1998; Marmolejo et al., 2008; Mejía et al., 2007; Miura et al., 2004; Pandey et al., 2000). 2.2. Process simulation description
2. Methods The methodology employed in this work consists on three steps using different computational tools. The first step corresponds to the process simulation to obtain the mass and energy balances of the process using Aspen Plus V8.0 (AspenTech: Cambridge, MA). The physicochemical properties of all the involved compounds in the simulation were obtained from the National Institute of Standards of Technology (NIST, 2012). To calculate the properties in the liquid and vapor phases, the Non Random Two Liquids (NRTL) model and the Hayden O’Conell (HOC) equation were used, respectively. NRTL model was used to estimate the activity coefficients of all the compounds from its mole fractions in the liquid phase. The HOC equation provides a method for predicting a second virial coefficient for multi-compounds vapor mixtures. These methods are used to calculate successfully phase equilibria in the type of mixtures with non-conventional compounds (Cardona and Sánchez, 2006; Jaramillo et al., 2012; Quintero et al., 2008). The second step corresponds to the economic analysis using Aspen Process Economic Analyzer (AspenTech: Cambridge, MA). This evaluation was developed for the six proposed agroindustrial wastes used as raw materials. The final step corresponds to the environmental analysis where the Waste Algorithm Reduction Software (WAR GUI) developed by the U.S. Environmental Protection Agency (EPA) was employed. This software uses a method of direct data sum based on the mass and energy streams of the process and the environmental impact that these streams can have over four principal categories (Human toxicity, ecological toxicity,
Fig. 1 shows the glucose syrup production scheme, which is the same for all the selected raw materials. The process begins drying the feedstock with air to remove the moisture. Then, the dried material was milled to obtain particles with sizes smaller than 0.45 mm. In order to improve the cellulose accessibility, a diluted acid hydrolysis using sulfuric acid (2% v/v) at 121 °C was carried out. Diluted acid hydrolysis was selected not only because it is the most commonly employed chemical pretreatment but also because it permits to enhance biomass digestibility obtaining good cellulose accessibility. Besides, this pretreatment allows achieving high reaction rates and producing lower quantities of fermentation inhibitors that could reduce the syrup quality (Agbor et al., 2011; Dagnino et al., 2013; Haghighi et al., 2013). Other pretreatment methods such as ionic liquids and organosolv present higher costs because of the solvent recovery. In the case of Ammonia Fiber Explosion (AFEX), costs increase because of the ammonia (Haghighi et al., 2013). Other methods such as concentrated acid hydrolysis and steam explosion produce appreciable amounts of toxic compounds, affecting the quality of the syrup. On the other hand, alkaline methods require long pretreatment resident time (Agbor et al., 2011; Haghighi et al., 2013). From this pretreatment, traces of furfural and hydroxymethylfurfural (HMF) were obtained. After, the liquid phase was sent to a xylose recovery process while the solid phase was used to produce glucose through an enzymatic hydrolysis at 50 °C (Sindhu et al., 2011). Once the stream containing xylose is separated, the remaining water is evaporated. Additionally, a detoxification process with
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Table 1 Chemical composition for the selected Colombian agroindustrial wastes. Sugarcane bagasse (SCB), plantain husk (PH), cassava husk (CH), mango peel (MP), rice husk (RH), corncob (CC). Component
Cellulose Hemicellulose Lignin Sugar Ash Protein Water Total
SCB (%)
PH (%)
CH (%)
MP (%)
RH (%)
CC (%)
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
Wet basis
Dry basis
24.86 18.40 6.46 0.89 0.47 0.88 48.04 100
47.84 35.41 12.44 1.72 0.90 1.69
1.48 1.66 1.57 0.24 0.91 2.25 91.88 100
18.22 20.45 19.34 2.96 11.22 27.71
7.43 10.37 1.78 5.68 0.37 3.72 70.65 100
25.32 35.33 6.06 19.35 1.27 12.67
5.76 4.10 5.21 6.39 0.01 2.06 76.46 100
24.47 17.44 22.14 27.15 0.04 8.76
38.02 16.57 20.38 1.46 14.62 3.37 5.57 100
40.26 17.55 21,58 1.55 15.48 3.57
34.07 33.88 13.63 1.75 1.93 5.93 8.81 100
37.36 37.15 14.95 1.92 2.12 6.50
100
100
100
100
100
100
Fig. 1. Scheme of glucose syrup production from Colombian agroindustrial wastes.
Ca(OH)2 was carried out at 60 °C to remove furfural and HMF traces, which are trapped in the resulting gypsum (Millati et al., 2002). Thus, a stream rich in xylose is obtained. On the other hand, the glucose obtained from the enzymatic hydrolysis was separated from the remaining solids, which correspond to lignin. Finally, the streams rich in xylose and glucose are mixed obtaining the final syrup. The purpose, assumptions, conditions and methods used for the principal units in the simulation are summarized in Table 2. 2.3. Economic analysis The economic analysis was made calculating the production cost per kg of syrup. The total production cost considers the total raw material, utilities, operating, labor and maintenance costs as well as the operating charges, plant overhead and general and administrative costs. Additionally, tax and interest rates were taken according to the laws in Colombia as 25% and 17%, respectively. Table 3 shows the economic parameters taken for economic analysis. Finally, the raw material cost was 0.021 USD/kg (Calculated to a distance of 140 km with a truck of three axles).
2.4. Environmental analysis The environmental analysis evaluates eight environmental impact categories which are: Human Toxicity Potential by Ingestion (HTPI), Human Toxicity Potential by Dermal and Inhalation Exposure (HTPE), Terrestrial Toxicity Potential (TTP), Aquatic Toxicity Potential (ATP), Global Warming Potential (GWP), Ozone Depletion Potential (ODP), Photochemical Oxidation Potential (PCOP) and Acidification Potential (AP). The Potential Environmental Impact (PEI) of the process was calculated per kilogram of product (syrup). Natural Gas was used as fuel to cover the heat requirements in the syrup production. 3. Results and discussion 3.1. Process simulation Total energy and chemical requirements as well as out streams of the process for each raw material are showed in Table 4. Total energy consumption is very similar for all the raw materials used.
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J.A. Dávila et al. / Bioresource Technology 161 (2014) 84–90 Table 2 Purposes, conditions, methods and assumptions for the principal units used in the simulation. Unit
Purpose
Conditions and unit specifications
Method
Assumptions
Dryer
Remove part of the water (Up to 20%) Improve the accessibility of the cellulose and xylose production
80 °C, 1 bar Atmospheric tray dryer 121 °C, 1 bar, (2% v/v of H2SO4) Agitated tank enclosed Cellulose + water = Glucose (Conversion = 1%) Hemicellulose + water = xylose (Conversion = 93%) Glucose = HMF + 3 water (Conversion = 1%) HMF + 2 water = L.A + F.A. (Conversion = 1%) Xylose = 3 water + Furfural (Conversion = 20%) 111 °C, 1 bar for both xylose and glucose Standard tube vertical evaporator, one effect 60 °C, 1 bar Ca(OH)2 + H2SO4 = CaSO4⁄2H2O (Conversion = 99%) Agitated tank enclosed 50 °C, 1 bar, 7% (wt) biomass/ enzyme Aagitated tank enclosed
NRTL
No
NRTL
Low production of glucose, HMF and acids (Levunilic and formic) Haghighi Mood et al. (2013)
NRTL-HOC
No
NRTL
All furfural and HMF are trapped in the gypsum Millati et al. (2002)
User model (Yields from literature)
Yield of 0.6 g/g from Sindhu et al. (2011)
Acid hydrolysis
Evaporators
Remove part of the water (60% for both xylose and glucose)
Detoxification
Remove furfural and HMF
Enzymatic hydrolysis
Glucose production
Table 3 Economic parameters taken for economic analysis.
a b c d e
Item
Price
Unit
Operatora Supervisora Electricitya Potable Watera Fuelb Raw materialc Sulfuric acidd Calcium hydroxided Enzymee
2.14 4.29 0.10 1.25 7.21 0.021 0.094 0.056 3
(USD/h) (USD/h) (USD/KWh) (USD/m3) (USD/MMBTU) (USD/kg) (USD/kg) (USD/kg) (USD/kg)
Typical prices in Colombia. Estimated cost of gas to a period range of 2015 – 2035 (NME, 2013). Calculated to a distance of 140 km with a truck of three axles. Taken from ICIS Prices (ICIS, 2013). Taken from Alibaba International prices (ALIBABA, 2013).
This because of the volume for acid hydrolysis was the same for all the agroindustrial wastes. Thus, the subsequent units operated with similar flows and conditions. This reveals that in average (taking sugarcane bagasse as base case) for 1 tonne of raw material, 30, 0.6, 0.45 and 0.041 tonnes of water, sulfuric acid (the same for all the raw materials), calcium hydroxide and enzymes respectively, are required. On the other hand, 29.7 tonnes of residual water are obtained and the total solid wastes (Gypsum) ranges from 1.4 to 2.1 tonnes/tonne of agroindustrial waste depending on the raw material used. Gypsum with traces of furfural and HMF was produced from xylose concentration step, while the
solids with high lignin content were obtained from glucose production step. Table 5 shows flows, sugar content and yields obtained for each one of the raw materials. Here, it is found that both yield and sugar concentration, are highest and lower for corncobs and plantain husk, respectively. These results are totally explained for the original content of cellulose and hemicellulose because a high content of these compounds improve the hydrolysis and the final yields (Latif and Rajoka, 2001). In the same way, rice husk had a good yield, reason for which it is considered a good raw material for the glucose production (Arezoo et al., 2011).
3.2. Economic analysis Table 6 shows both, cost and its corresponding share in the syrup production for each agroindustrial waste used. The economic analysis showed a similar distribution in all the economic parameters for all the raw materials considered and the differences are due to the variations on initial chemical composition because of variations on moisture, cellulose and hemicellulose can define the cost associated for both, units (drying, evaporation, fermentation, among others) and reagents (enzymes, water, among other). Total utilities cost represent approximately 80% of the total project cost in all the cases while, general and administrative, total raw material and depreciation expensive costs are between 4% and 8% approximately. This is in agreement with the fact that the two most important parameters in the glucose syrup production are raw materials and utilities (Shewale, 2008).
Table 4 Total energy, chemical requirements and out streams of each raw material. Raw material
Total Energy (kJ/kg)
Water (kg/h)
Enzyme (kg/h)
Ca(OH)2 (kg/h)
Residual water (kg/h)
Solids (kg/h)
Gypsum (kg/h)
Sugarcane bagasse Plantain husk Cassava husk Mango peel Rice husk Corncobs
2548 2543 2548 2543 2543 2558
30,000 29,562 29,774 29,716 34,247 33,923
41 2.44 12.25 9.50 62.70 56.19
450 40.59 253.61 100.27 405.24 828.58
29,700 29,266 29,476 29,418 33,904 33,583
517 539 541 512 654 725
1874 1400 1623 1496 1757 2100
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Table 5 Flow, sugar content and yields of the glucose syrups obtained of each raw material. Raw material
Flow (kg/h)
Total sugars (%)
Yielda
Sugarcane bagasse Plantain husk Cassava husk Mango peel Rice husk Corncobs
692.65 286.29 418.47 360.71 784.04 909.40
62.21 20.11 40.91 35.13 66.66 67.12
0.43 0.06 0.17 0.12 0.52 0.61
a
Yield is in kg of total sugars per kg of wet agroindustrial waste.
The energy requirements are the main factors that contribute with a high total production cost (80% as was mentioned above) because the pretreatment of these kinds of raw materials involves the major energy consumption in these processes. According to Fig. 1, drying, milling and the acid hydrolysis compose the pretreatment section while processes such as evaporation, detoxification and enzymatic hydrolysis compose the section of production and concentration of sugars. In this sense, the energy analysis showed that are required 12, 1089 and 1017 kJ/kg of syrup for drying, acid hydrolysis and evaporation respectively. Thus, the diluted acid hydrolysis in the pretreatment section has the major energy consumption even more than the energy requirements in the evaporation to concentrate both, xylose and glucose. Pretreatment is among the most costly steps in the biochemical conversion of lignocellulosic biomass and represents a high percentage of the total production cost (Njoku et al., 2012). Specially, the dilute acid hydrolysis as pretreatment is more expensive that other physicochemical pretreatments methods (Agbor et al., 2011). However, according to (Haghighi et al., 2013) if other pretreatment methods are used, the hemicellulose removal and solubilization could be affected. This is the case of physical methods, alkaline methods, ionic liquids usage, ozonolysis, AFEX method and biological methods for which the final effect on hemicellulose removal and solubilization is lower than that reached with diluted acid hydrolysis. On the other hand, other pretreatments such as organosolv, CO2 explosion, wet oxidation, concentrated acid hydrolysis and liquid hot water method have a low effect to avoid fermentation inhibitors formation, which is very important for syrup production. From these two important characteristics, other pretreatment methods could not be as efficient as the most typically diluted acid hydrolysis. Besides, other pretreatment methods also could have other economic implications based on high pressures or temperatures, solvent costs and its recycle and long pretreatment resident times, among others. Anyway, it is evident that the pretreatment section for these kinds of raw
materials needs further inputs in terms of research and development (Pandey et al., 2000). In order to reduce the utility consumption and thus, the heat and cooling requirements it is necessary to add a heat integration strategy (Sánchez and Cardona, 2012). From the economic analysis, corncob and plantain husk had the lowest and highest production cost with 2.48 and 7.88 USD/kg of syrup, respectively. The prices of syrups in the market depend on the Dextrose Equivalent (DE) measured, which represents the total content of the reducing sugars. For a syrup with a DE between 40 and 60, the typically sale price ranges from 0.48 to 0.6 USD/kg of syrup. Fig. 2 shows the production cost per kg of syrup for all raw materials used which are compared with the sale price found in the market according to the wholesale list prices for glucose syrups published by Milling & Baking (News, 2013), with a sale price of 0.64 USD/kg of syrup. Despite the low production cost in the case of corncobs (2.48 USD/kg of syrup) this cost is higher that the typical sale prices in the market. This means that the syrups from Colombian agroindustrial wastes are not well established yet and it suggests that is necessary to refine the biotechnological production routes and concentration processes. This agrees with the results obtained in Ghana where a reduction in the prices of glucose syrups only are achieved if the quality of the syrup is reduced (FAO, 2013). According to the economic analysis, it can be seen that the corncobs are the most suggested raw material between the six Colombian agroindustrial wastes evaluated to produce syrups. Although, it is necessary to improve the biotechnological process by mean of refining different steps in the production scheme such as the pretreatment and concentration methods.
Fig. 2. Production cost per kg of syrup.
Table 6 Distribution of the total project costs. Sugarcane bagasse (SCB), plantain husk (PH), cassava husk (CH), mango peel (MP), rice husk (RH), corncob (CC). Item
a
Depreciation expense Total raw materials cost Total utilities cost Operating labor cost Maintenance cost Operating charges Plant overhead b G and A Cost Total project cost a b
SCB
PH
CH
MP
RH
CC
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
Cost USD (106)
Share (%)
0.77
4.31
0.77
4.36
0.77
4.36
0.77
4.31
0.77
4.31
0.77
4.31
1.19
6.64
1.02
5.76
1.03
5.76
1.20
6.64
1.20
6.64
1.20
6.64
14.4 0.12
80.1 0.67
14.4 0.12
80.9 0.67
14.4 0.12
80.9 0.67
14.4 0.12
80.1 0.67
14.4 0.12
80.1 0.67
14.4 0.12
80.1 0.67
0.08 0.03
0.46 0.17
0.08 0.03
0.47 0.17
0.08 0.03
0.47 0.17
0.08 0.03
0.46 0.17
0.08 0.03
0.46 0.17
0.08 0.03
0.46 0.17
0.10 1.27 18.03
0.56 7.1 100
0.10 1.26 17.85
0.57 7.08 100
0.10 1.26 17.85
0.57 7.08 100
0.10 1.28 18.03
0.56 7.09 100
0.10 1.28 18.03
0.56 7.09 100
0.10 1.28 18.03
0.56 7.09 100
Depreciation expensive was calculated using the straight-line method. G and A is referrer to general and administrative costs.
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Fig. 3. Leaving Potential Environmental Impact (PEI) of the process.
3.3. Environmental analysis Fig. 3 shows the leaving Potential Environmental Impact (PEI), which demonstrates that the total PEI cannot be mitigated. The environmental categories HTPI, HTPE and TTP are the most affected due to the compounds as lignin and the compounds trapped by the gypsum (furfural and HMF), which are presented in the solid outlet streams. On the other hand, AP environmental category is affected due to the H2SO4 used in the pretreatment process. Rice husk, sugarcane bagasse and corncobs presented the lowest total PEI, this is agreeing with the fact that the highest yields correspond to these raw materials whereby compounds such as furfural and HMF are formed in low quantities when the yield of xylose is high. Because mass integration was not considered in the production scheme, the flows of residual water obtained from the concentration of sugars, contribute to the PEI of the process because this water contains acid (H2SO4), which was not separated and affects considerably the environmental development. 4. Conclusions All the selected raw materials are promising feedstocks, however corncob is the most attractive of them to produce syrup. The production cost suggests that, it is necessary to improve the yields and energy consumption in the pretreatment, even if another pretreatment method is used. This to assures hemicellulose removal and solubilization as well as low fermentation inhibitors formation. The agroindustrial wastes with highest yields presented the lowest total PEI. However, it is necessary to reduce solid wastes. Heat integration strategy is suggested to reduce the utilities consumption, which are the most important economic factor in the syrup production. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.biortech.2014.02. 131. References Agbor, V.B., Cicek, N., Sparling, R., Berlin, A., Levin, D.B., 2011. Biomass pretreatment: fundamentals toward application. Biotechnol. Adv. 29 (6), 675– 685. ALIBABA, 2013. International Prices. Available in:
Botero, L.J.D., Mazzeo, M.M.H., 2009. Obtainment of rachis flour from Dominico harton plantain, and its quality evaluation with industrialization purposes. Vector 4 (1), 83–94. Cardona, C.A., Sánchez, O.J., 2006. Energy consumption analysis of integrated flowsheets for production of fuel ethanol from lignocellulosic biomass. Energy 31 (13), 2447–2459. Dagnino, E.P., Chamorro, E.R., Romano, S.D., Felissia, F.E., Area, M.C., 2013. Optimization of the acid pretreatment of rice hulls to obtain fermentable sugars for bioethanol production. Ind. Crop. Prod. 42, 363–368. FAO. 2013. Production of glucose syrup from high quality cassava flour. Available in
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