Article-Conceptual Design of Cost Effec Environ Configu for EtOHprdn

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Conceptual design of cost-effective and environmentally-friendly configurationsfor fuel ethanol production from sugarcane by knowledge-based process synthesis

scar J. Snchez a, Carlos A. Cardona b,

a Institute of Agricultural Biotechnology, University of Caldas, Calle 65, No. 26-10, Manizales, Colombiab Institute of Biotechnology and Agro-industry, National University of Colombia at Manizales, Cra. 27, No. 64-60, Manizales, Colombia

a r t i c l e i n f o

Article history:Received 20 May 2011Received in revised form 30 August 2011Accepted 31 August 2011Available online 8 September 2011

Keywords:Fuel ethanolProcess synthesisConceptual designProcess simulationSugarcane

a b s t r a c t

In this work, the hierarchical decomposition methodology was used to conceptually design the produc-tion of fuel ethanol from sugarcane. The decomposition of the process into six levels of analysis was car-ried out. Several options of technological configurations were assessed in each level consideringeconomic and environmental criteria. The most promising alternatives were chosen rejecting the oneswith a least favorable performance. Aspen Plus was employed for simulation of each one of the techno-logical configurations studied. Aspen Icarus was used for economic evaluation of each configuration, andWAR algorithm was utilized for calculation of the environmental criterion. The results obtained showedthat the most suitable synthesized flowsheet involves the continuous cultivation ofZymomonas mobiliswith cane juice as substrate and including cell recycling and the ethanol dehydration by molecular sieves.The proposed strategy demonstrated to be a powerful tool for conceptual design of biotechnological pro-cesses considering both techno-economic and environmental indicators.

2011 Elsevier Ltd. All rights reserved.

1. Introduction

Process systems engineering deals withthe development of pro-cedures, techniques, and tools to undertakethe generic problems ofdesign, operation, andcontrol for productive systems related to dif-ferent sectors ofthe processand chemicalindustries (Perkins,2002).As part of process systems engineering, process design plays animportant role when developing more cost-efficient and environ-mentally friendly technologies for manufacturing different prod-ucts. In this way, its main objective consists in the selection anddefinition of a processconfigurationthat makes possible the conver-sion of the raw materials into end products meeting the requiredspecifications and improving the overall process performance(Cardona et al., 2010). The task of defining an appropriate processconfiguration requires the generation and evaluation of many tech-nological schemes (processflowsheets) in order to findthose exhib-iting better performance indicators. This task is called processsynthesis. To undertake it, a series of solving strategies have beenproposed being classified into two large groups: knowledge-basedprocess synthesis and optimization-based process synthesis. Thesecondgroup ofstrategies is orientedto theformulation ofa synthe-sisproblemin theform of an optimization problem. In turn, thefirstgroup of strategies is concentrated on the representation of thedesign problem as well as the organization of the knowledge

requiredby this problem (Li and Kraslawski, 2004), i.e., it isorientedto the development of a representation that is rich enough to allowall the alternatives to be included, and smart enough to automat-ically ignore illogical options.

The hierarchical heuristic method is an extension of the purelyheuristic approach and combines heuristics with an evolutionarystrategy for process design (Li and Kraslawski, 2004). Douglas(1988) has proposed a method in which any process can be decom-posed into five levels of analysis for its design. This strategy has ahierarchical sequential character considering that in each level dif-ferent decisions are made based on heuristic rules. This allows thegeneration of different alternatives, which are evaluated from aneconomic viewpoint using short-cut methods. According to thisauthor, hierarchical decomposition comprises the analysis of theprocess in the following levels: (i) Batch vs. continuous, (ii)inputoutput structure of the flowsheet, (iii) recycle structure ofthe flowsheet, (iv) separation system synthesis, and (v) heatrecovery network. A slightly different hierarchical decompositionscheme corresponds to the onion diagram (Smith, 2005), whichincludes the heating and cooling utilities, and wastewater andeffluent treatment. The hierarchical heuristic method emphasizesthe strategy of decomposition and screening. It allows the quicklocation of flowsheet structures that are often near optimum solu-tions. This methodology has been mostly applied to chemical andpetro-chemical processes. Nevertheless, the utilization of theseprocedures and design schemes is less frequent in the case ofbiotechnological processes. To the authors knowledge, there isno published works on the application of the hierarchical

0960-8524/$ - see front matter 2011 Elsevier Ltd. All rights reserved.doi:10.1016/j.biortech.2011.08.125

Corresponding author. Tel.: +57 6 8879300x50417; fax: +57 6 8879300x50452.

E-mail address:[email protected](C.A. Cardona).

Bioresource Technology 104 (2012) 305314

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decomposition approach to the conceptual design of fuel ethanolproduction processes.

Fuel ethanol has become an important commodity in the globalenergy market, especially in the transport sector. Ethyl alcohol canbe used as a sole fuel for spark ignition engines or as an additive toelevate the oxygen content of gasoline (oxygenate) allowing thereduction of polluting gases (mostly CO and aromatic hydrocar-bons) through a better combustion of the fuel. The fuel ethanolcan be obtained from energy crops and lignocellulosic biomass.The complexity of the production process depends on the feed-stock. In this way, the spectrum of designed and implementedtechnologies goes from the simple conversion of sugars by fermen-tation, to the multi-stage conversion of lignocellulosic biomass intoethanol (Snchez et al., 2009). The big diversity of technologicalalternatives requires the analysis of the global process along withthe design and development of each one of the involved opera-tions. Among the new research trends in this field, process integra-tion has the key for reducing costs in ethanol industry andincreasing bioethanol competitiveness related to gasoline (Cardonaand Snchez, 2007). The objective of this work is to apply a hierar-chical decomposition method to accomplish the process synthesisfor fuel ethanol production from sugarcane. The application of thismethodology to this relatively known biotechnological processusing process simulation tools allowed a more systematic proce-dure to generate process alternatives with a better technical, eco-nomic and environmental performance. This is very relevantconsidering the need of lowering the fuel ethanol production costsin the new production facilities projected worldwide in an environ-mentally friendly way. Aspen Plus and Aspen Icarus Process Evalu-ator (IPE), the main simulation and evaluation tools used in thiswork, have demonstrated their usefulness and suitability duringthe assessment of different flowsheets for production of liquidand gaseous biofuels (Shafiei et al., 2011).

2. Process synthesis procedure

2.1. General procedure

In this paper, the hierarchical decomposition method wasapplied to the fuel ethanol production from sugarcane accordingtoDouglas (1988)with elements of the onion-based decomposi-tion model (Smith, 2005). Therefore, the system decompositionin six levels of analysis was carried out (batch vs. continuous,

inputoutput structure of the flowsheet, reaction system synthesis,separation system synthesis, effluent treatment, and heat recoverynetwork). The evaluation of each level of analysis was accom-plished with a synthesis tree that allowed the systematic genera-tion and evaluation of the alternatives by the branch and boundmethod (Biegler et al., 1997; Seider et al., 1999). The breadth-firststrategy was the branch and bound option used in this work. Theaim of this strategy consists in the selection of the process alterna-tive with the best evaluation criterion within each decision level,with the subsequent assessment of the alternatives at the nextlevel of the hierarchical decomposition. Thus, at each design level,a base case was defined and other alternatives were selected. Basedon the evaluation results, the most promising alternatives werechosen and the ones showing a least favorable performance wererejected. Alternatives generated through some algorithmic meth-ods as the synthesis of distillation trains and the second law anal-ysis (Seider et al., 1999) were considered as well. For this, specialsoftware like Aspen Split (Aspen Technology, Inc., USA) wasemployed.

The process simulator Aspen Plus (Aspen Technology, Inc., USA)was used as the main tool to specify and evaluate the mass andenergy balances of the configurations studied. The data requiredfor the simulation of the different technological schemes, espe-cially the physicalchemical properties of the involved substances,and the design and operation parameters of each unit operation,were obtained from secondary sources (articles, technical reports,data bases, patents and others). The general approach for simula-tion by using Aspen Plus has been described elsewhere (Quinteroet al., 2008).

The detail level of the flowsheets was improved through therigorous simulation of the most relevant unit operations. Thisrequired the utilization of kinetic models for some of the transfor-mation processes, particularly for biological transformations. Asthe Aspen Plus reaction modules do not contemplate the introduc-tion of specific kinetic relationships related to the fermentationand enzymatic processes, an Aspen PlusExcel interface was used

for considering the particularities of the biological transformation.Kinetic models were included in a spreadsheet and then integratedto the simulator. A significant amount of kinetic models werereviewed in order to select the most appropriate description of fer-mentation using the assimilable sugars released during the condi-tioning of sugarcane juice. From all the models reviewed, a reducedgroup was pre-selected (see Table 1) in order to evaluate their

Table 1

Kinetic models preselected for describing specific cell growth rate during alcoholic fermentations employing glucose-based media.

No. Growth rate model tf, ha X, g/Lb P, g/Lb Remarks References

1.l lmax

S

KS Sek1P

11.04 16.64 52.51 S. cerevisiae,k1changesfor continuous cultures

Aiba et al. (1968)

2.

l lmaxS

KS S1 KPXP

23.31 5.13 66.81 S. cerevisiaeimmobilized

in alginate, P10% sugars

Birol et al. (1998)

3.

l lmaxS

KS S 1

P

Pm

a 30.00 16.14 93.08 S. cerevisiae, someconstants taken fromBirol et al. (1998),P10% sugars

Luong (1985)

4.

l lmaxS

KS S 1

P

Pm

13.68 10.00 56.26 S. cerevisiae, modeltaken fromLee et al. (1983)

Tsuji et al. (1986)

5.

l lmaxS

KS S 1

P

Pm

n 6.98 2.27 73.20 Z. mobilis, model takenfromGarro et al. (1995)

da silva Henriques et al. (1999)

6.

l

lmax 1 PPma

ah i 1 PP0b

PmbP0b

b S

Km SSSSiKiSi

6.50 3.90 72.76 Z. mobilis, modification tothe model ofVeeramalluand Agrawal (1990)

da silva Henriques et al. (1999)

X, cell biomass concentration; P, ethanol concentration; S, substrate concentration; l, specific growthrate; Pm, maximum ethanol concentration; KS, substrate semi-saturationconstant;Ki, substrate inhibition constant;a,b,n,KPX,Pma,Pmb,P0b,Si, kinetic constants.

a

Length of the batch process for a fermentation time (tf) corresponding to the total substrate consumption (S= 0).b The values were obtained from calculations for the end of fermentations with an initial concentration of substrate of 150 g/L.

306 .J. Snchez, C.A. Cardona/ Bioresource Technology 104 (2012) 305314


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applicability to continuous cultures. With the help of the softwareMatlab version 7.0 (MathWorks, Inc., USA), the time profiles of the

corresponding batch fermentation processes were obtained con-sidering initial glucose and biomass concentrations of 150 and1 g/L, respectively. The time when occurs the total substrate con-sumption (tf) was also determined. The substrate consumptionand ethanol production rates are not included inTable 1becauseof space reasons, but both expressions depend on either the cellgrowth rate or cell biomass concentration. The selection of theproper model to be employed during the subsequent steps of thesynthesis procedure was carried out based on the above-men-tioned information and experimental data reported in the litera-ture. In some cases, accessible information from existingindustrial processes was used.

2.2. Evaluation of process alternatives

At the upper levels of the hierarchical decomposition procedure(1 and 2), the different alternative technological configurationswere evaluated using a simplified Economic Potential criterion(seeDouglas, 1988). At lower levels of the hierarchical decomposi-tion procedure (36), where the degree of detail is higher, a morerigorous evaluation of the different alternatives was accomplishedaccording to technical, economic and environmental criteria. TheNet Present Value (NPV) was selected as the techno-economic cri-terion since it considers the technical efficiency of the process bycalculating the production costs. In addition, NPV considers thetime value of money by evaluating the system as an investmentproject that may or may not be profitable. For economic assess-

ment of the technological schemes, the software Aspen IPE (AspenTechnology, Inc., USA) was used. The description of the approach

used for the economic evaluation was disclosed in a previous work(Quintero et al., 2008).

The environmental assessment of the different alternatives wasaccomplished by using the concept of the Potential EnvironmentalImpact (PEI) of a process. The PEI of a given quantity of material orenergy is considered as the effect that this material or energywould have on the environment if it was to be emitted into theenvironment. The potential environmental impacts of a processare caused by the energy and materials that the process acquiresor emits into the environment (Cardona et al., 2004; Young andCabezas, 1999). PEI was calculated by the WAR algorithm includedinto the WAR GUI software (Environmental Protection Agency,USA). The impact categories that WAR algorithm evaluates fall intotwo general areas: global atmospheric and local toxicological (seethe caption ofFig. 2a). The values of these categories were aggre-gated into a single indicator of environmental performance through

the weighted sum of the PEI of each category. In this paper, the fourlocal toxicological impact categories had the largest weight (10.0)compared to the remaining four atmospheric categories whoseweighting factors were set to 2.5. Thus, greater importance was gi-vento thedirect effectthatanethanolproductionfacility couldhaveon the surrounding land, nearby natural water streams, staff work-ingin thefacility, andwildlifethatcould have some contact with theplant. The two most important output indexes calculated by theWAR algorithmare thetotal rate of impact output (expressed as im-pactpotential per time unit), and thetotal impactoutput per mass ofproducts. The smaller the value of the indexes, the more environ-mentally efficient is the process. Considering that the total rate ofimpact output depends on the plant capacity, the total impact out-put per mass of product (PEI/kg) is used in this paper.

Once both economic and environmental indexes were calcu-lated for each process alternative, a combined techno-economic

Fig. 1. Schematicflowsheetshowing the different technological options in each stepof the overall fuel ethanolproduction process fromsugarcane. Process units: (1) Washingstep. (2) Sugarcane mill with liquid recycle to the washing step. (3) Storage tank for raw juice. (4) Heater. (5) Mixer for adding acid and other chemicals used for juiceclarification. (6) Clarifying tank. (7) Rotary-drum vacuum filter for press mud removal. (8) Storage tank for clarified juice. (9) Heater. (10) Heat exchanger for sterilization ofclarified juice. (11) Juice cooler. (12) Continuous stirred-tank bioreactors. (13) Centrifuge for cell separation. (14) Bioreactor for extractive fermentation. (15) Decanter forphase splitting. (16) Column for solvent regeneration. (17) Concentration column. (18) Rectification column. (19) Columns for extractive distillation. (20) Adsorption beds(molecular sieves). (21) Pervaporation modules. (22) Stillage evaporation train. (23) Anaerobic digestion system. (24) Incinerator. (25) Burner/boiler. (26) Turbogenerator.

.J. Snchez, C.A. Cardona / Bioresource Technology 104 (2012) 305314 307


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and environmental index (including the NPV and PEI) wasemployed to select the most appropriate configuration at eachdesign level. This combination was done by following the proce-dure exposed byChen et al. (2002)where the economic and envi-ronmental criteria were aggregated into a single objective functionusing the Analytic Hierarchy Process approach. The AHP is one var-iant of multi-criteria analysis that uses a number of pairwise com-parisons between quantitative or qualitative criteria to assess therelative importance of each criterion. These comparisons can be

arranged in a hierarchical manner to form sets of attributes, andqualities (levels) within these attributes (Hussain et al., 2006).The indexes (NPV and PEI) for each configuration were normalized,so that they could be compared at the same scale and did notexceed a normalization value, and converted to quantitative scores.The AHP score of a process design represents the sum of the prod-ucts of the average process score for a given attribute and theweighting for that attribute, that is:

AHP PEcn weight PEnv weight 1

where PEcn is thenormalized economicscore calculatedfromtheNPVof the analyzed process, and PEnv is the normalized environmentalscore resulting from the PEI values of the process. The qualitativeweightings of economic and environmental attributes were taken

as 0.82 and 0.18, respectively. These values are suggested byChenet al. (2002) who applied themto several chemical processes.

The normalization of the NPV data to determine the economicscore took into account all the NPV values obtained during the syn-thesis procedure throughout all the hierarchical levels. Thus, theeconomic score for a given configuration was calculated as follows:

PEcn NPV NPVworstNPVbest NPVworst

2

where NPV is the net present value of the configuration, NPVworstisthe NPV of the configuration with the worst economic performance,

and NPVbest is the NPV of the best configuration according to thissame criterion. Thus, all the values of the normalized economicscore were in the range between 0 and 1. The configurations withhigher PEcnhad better economic performance. The normalized envi-ronmental scores for each configuration were calculated in a similarway. In this case, the PEI normalization for the different alternativeswas performed in such a way that processes with improved envi-ronmental performance (less PEI values) had a higher value of theenvironmental scorePEnv.

3. Results and discussion

3.1. Levels 1 and 2 of the synthesis procedure

The process synthesis procedure was developed based on thedecomposition of the process for fuel ethanol production from sug-

Fig. 2. Level 4 of the synthesis procedure (separation system). (a) Output potential environmental impact per mass of product (anhydrous ethanol) of five configurations forfuelethanol production according to the different impact categories. Local toxicological categories: HTPI, human toxicity potential by ingestion, HTPE, human toxicity potential

by inhalationor dermalexposure; TTP, terrestrial toxicity potential; ATP, aquatic toxicity potential. Global atmospheric categories: GWP, global warming potential; ODP, ozonedepletion potential; PCOP, photochemical oxidation potential; AP, acidification potential. A brief description of the alternatives is shown in the footnote of Table 3.(b) Configuration with the best performance at level 4. The conditioning of sugarcane has been simplified in the diagram. (1) Washing step. (2) Mill. (3) Clarifier. (4) Rotarydrum vacuum filter. (5) Fermentation system (three CSTR in series). (6) Centrifuge. (7) Scrubber. (8) Concentration column (52% wt. ethanol). (9) Rectification column (91%wt. ethanol). (10) Molecular sieves. (11) Product tank.



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arcane. Sixlevelsof decision were studied inorderto choosethe bestconfigurationaccording to techno-economicand environmental cri-teria. The raw material entering the ethanol production plant is thesugarcane stalks. This implies the conceptual design of a standalonefacility. Ethanol production capacity was fixed in 250,000 L/day,considering the conditions of Colombia, for which the case studywas developed. First hierarchical level of the decomposition proce-durecomprisesthe selectionof thetimeregimeof thewhole process(batch or continuous). Continuous processes for ethanol productionexhibit higher productivities that batch ones, so this regime wasselected. Saccharomyces cerevisiae yeasts were preliminarily chosenas the process microorganisms. At this first level of analysis, thegross profit was used as the evaluation indicator (i.e. the economicpotential). For this, the final product price was set to US$0.59/Lanhydrous ethanol (average price according to the official regulatedquotation in Colombia) and a sugarcane price of US$0.0124/L(averageprice obtainedfromthe sugar sector). Gross profit obtainedwas US$35,389,286/year considering an ethanol yield of 77 L/ton ofsugarcane for a 250,000 L/day plant.

The second level of the synthesis procedure corresponds to theoutputinput structure. To describe the structure, it is necessary todefine the need of purifying the feed streams before the biologictransformation step. Sugarcane contains many impurities mainlycoming from soil residues incorporated during its cutting. Canebagasse is generatedduring the milling. Afterthis operation, the ob-tainedsugarcane juice hasto be conditioned for its subsequent sub-merged fermentation. The base case defined at this analysis levelconsidered a thermal treatment of the juice using sulfuric acid andother chemicals required for juice clarification and pH adjustment.These operations favor the sucrose hydrolysis into its fermentablesugars (glucoseand fructose). Other materialobtained fromthe clar-ificationstep is the filter cake (press mud). The alternative option isnot to process the impurities, but it is discarded because the impu-rities negatively affect the metabolism of the microorganisms.

3.2. Level 3: reaction system synthesis

Reaction system corresponds to the recycle structure accordingto the original Douglas terminology. Precisely, stream recyclinghas a direct influence on the reaction step. The base case selectedat this level involved the conditioning of the feedstock: sugar canemilling, clarification of sugarcane juice, and sterilization (see firstprocess units inFig. 1). In addition, the base case considered thecontinuous fermentation in one single bioreactor. The fermentedbroth, sugarcane bagasse and press mud are obtained as outputstreams. These last two materials are considered as process wastesat this hierarchical level. For the fermentation analysis, the modelspresented inTable 1were assessed. All these pre-selected modelstake into account the substrate limitation, which is represented inmost expressions through Monod-type equations. Likewise, allmodels include expressions describing the growth rate inhibitionby the ethanol formed. The expression developed by Lee et al.(1983) for S. cerevisiae strains (model No. 4) was chosen as the

most suitable model to describe the ethanologenic fermentationfrom glucose. In particular, it has also been used for studying thecontinuous fermentation as reported byTsuji et al. (1986).

The process simulator allowed the generation of the dataneeded for assessing the base case and the alternative configura-tions. The first process alternative considered at this hierarchicallevel involved the recirculation of the yeast biomass, a practicecommonly used in distilleries to raise the cell concentrations insidethe bioreactor during continuous fermentation. To avoid an artifi-cial growth of the biomass concentration in the bioreactor duringthe calculations due to the recirculation, a term representing thecell recycling should be introduced in the model of Lee et al.(1983). Other issue to be considered is the substrate inhibition ofthe growth rate that limits the utilization of very concentrated cul-ture media due to factors as the catabolic repression and osmoticpressure. Therefore, the model employed to describe the yeast spe-cific growth rate (rX), in g/(L h), is as follows:

rX lmaxS

KS S

KiKi S

1

P

Pm

1

X

Xm

X 3

whereXmis the maximum allowable cell concentration during cell

recycling; the notation of the remaining symbols is presented in thefootnote ofTable 1. The remaining alternative configurations arebriefly described in the footnote ofTable 2. The fourth alternativeis basedon thecultivation ofZymomonas mobilis bacteria as the eth-anol-producing microorganisms. This option is relevant consideringthat the ethanol yield from Z. mobilis is higher than that from S.cerevisiae. In addition, research efforts are being made worldwideintended to the adaptation ofZ. mobilis strains to the industrial con-ditions, especially on media containing fructose (Cardona et al.,2010). The kinetic model chosen in this case was based on thatdeveloped byGarro et al. (1995)(model No. 5 in Table 1) sincethe structured model proposed byVeeramallu and Agrawal (1990)(model No. 6) offers quite similar results but with a higher complex-ity in the kinetic expressions. To consider the cultivation of this bac-

terium in sugarcane juice, the growth rate expression from fructosewas slightly modified with the aim of describing a different rate ofconsumption of this monosaccharide compared to glucose. In thisway, the kinetic description comprised a model of co-fermentationof glucose and fructose that approaches to the actual growing pro-cess from sugarcane juice. In fact, this approximation was alsoemployed for previous alternatives using S. cerevisiae yeasts. Allthe configurations considered at this level of the synthesis proce-dure are schematically depicted inFig. 1.

Obtained data from simulation of the base case show that thethermal energy required for sugarcane conditioning, juice clarifica-tion, and sterilization reaches 37,051 MJ/h. Ethanol concentrationin the fermenter effluent was 66.91 g/L for a residence time of24 h. The results of the mass and energy balances from the simula-tor were the starting point for the techno-economic evaluationusing Aspen IPE. The process NPV reached US$55,118,007 that inturn was the base to calculate the normalized economic criterionPEcn, which attained a value of 0.074 (Table 2). The base case

Table 2

Technical, economic and environmental comparison of different configurations for fuel ethanol production from sugarcane at level 3 of the synthesis procedure (reaction system).

Configuration Productivity, g/(L h) NPV, US$ PEcn PEI, PEI/kg PEnv AHP

Base case 2.78 55,118,007 0.074 4.083 0.000 0.06040Alternative 1 5.45 57,361,215 0.139 4.070 0.003 0.11471Alternative 2 7.42 57,279,410 0.137 4.067 0.004 0.11289Alternative 3 6.69 58,516,779 0.173 4.024 0.015 0.14452Alternative 4 9.41 77,231,975 0.719 3.682 0.104 0.60851

Base case:sugar cane milling, juice conditioning, juice clarification, juice sterilization, one continuous bioreactor, S. cerevisiae.Alternative 1:base case but with yeast recycle

(purge fraction of cells: 0.3).Alternative 2:two CSTR in series with yeast recycle.Alternative 3:three CSTR in series with yeast recycle.Alternative 4:based on alternative 2 butusingZ. mobilisas the process microorganism.



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implies the handling of a large broth volume leading to the employof two parallel fermenters, each one with a capacity of 1560 m3.These large capacities increase the capital costs, decreasing theNPV. The volumetric productivity (used as the technical criterion)reached 2.78 g/(L h) is near to the productivity of conventionaland batch processes (Snchez and Cardona, 2008).

The synthesis tree at level 3 starts with the evaluation of thebase case and all the alternative configurations. All process config-urations whose evaluations are presented in Table 2ensure theprocessing of 146,308 kg/h sugarcane enough for producing atleast 250,000 L/day fuel ethanol. Final ethanol production varieddepending on the efficiency of each alternative. As expected foralternative 1, cell concentration in the culture broth was increasedby yeast recycling. According to a preliminary sensitivity analysis,the purge fraction of cells was set to 0.3, i.e., the 70% of the cell bio-mass stream is recycled back to the continuous bioreactor. Thisalternative showed the possibility of reducing the residence timein the bioreactor down to 12 h, reaching a cell concentration of10.7 g/L and an ethanol concentration similar to that obtained forthe base case. In addition, ethanol productivity can be increased al-most twice. This method for increasing ethanol productivity hasbeen reported in different sources including patents (Hojo et al.,1999; Rogers and Tribe, 1984; Tsuji et al., 1986). The productivityincrease implied that the fermenters size can be reduced and,therefore, the capital and operating costs may also be reduced.

Taking into account that the cell recycling showed a better per-formance than the base case, the recirculation of the cell biomass(with a purge fraction of 0.3) was also considered in the alternative2, which involves two CSTR in series. In a system of several serialCSTR, ethanol concentration in the first tank is less than in the fol-lowing tanks, which favors the cell reproduction and diminishesthe end-product inhibition. Only in the last fermenter, ethanol con-centration is relatively high, but sugars concentration is minimalmeaning more complete utilization of the substrate. The obtainedresults showed the possibility of reaching satisfactory cell concen-trations with lower residence times. If the behavior predicted by

the kinetic expressions used is verified in practice, it is possibleto decrease the residence time in each reactor down to 4.5 h,implying a global productivity of the fermentation system of7.42 g/(L h) ethanol and increasing the NPV (see Table 2). The thirdalternative allowed reducing the residence time in each one of thethree reactors in series down to 3.3 h, which led to a lower produc-tivity than alternative 2. However, economic evaluation showed abetter performance by the combined effect of slightly higher etha-nol concentrations and lower fermenters size.

In the case of alternative 4, it was assumed that the Z. mobilisstrain presents no disadvantages regarding the cultivation of thesebacteria under industrial conditions in fructose-rich media. Thefeasibility of recycling these bacteria during continuous alcoholicfermentations was reported by Rogers and Tribe (1984), which

however did not report the cell purge fraction. The simulation

results showed, as expected, that the ethanol concentration washigher than for the process using yeasts (seeTable 1). This alsomakes higher the economic and financial performance of a projectbased on this configuration as presented in Table 2. Dueto the larg-est amount of ethanol produced in the process based on alternative4 as a result of using Z. mobilis, the indicator per unit of product issmaller, which identifies this configuration as the most environ-mentally friendly.

The selection of the process configuration with the best com-bined techno-economic and environmental performance was madeby calculating the AHP according to the Eq. (1). At this synthesislevel, the alternative 4 was chosen as the configuration with thebest performance (seeTable 2). Therefore, this configuration wasselected as the base case for the following hierarchical level con-sidering the breadth-first strategy of the synthesis tree.

3.3. Level 4: separation system synthesis

The following hierarchical level comprises the definition of theseparation system. Culture broth has suspended solids includingmicrobial cells. Outlet gases formed during fermentation containcarbon dioxide, volatilized ethanol, and water vapor, among others.Valuable compounds from these streams must be recovered orrecycled. Thus, centrifuges were considered for yeast recoveryand removal of solids from stillage. Distillation columns allowedthe separation of anhydrous ethanol from water, which is recov-ered from stillage evaporation as well. In addition, a scrubberwas used for recovering ethanol from fermentation gases avoidingsignificant product losses.

At this level of the synthesis procedure, five separation schemeswere proposed. The base case was based on the alternative 4 of theprevious level of analysis with a separation system that includedtwo distillation columns (the first one for concentration of theaqueous solution of ethanol leaving the fermenters, and the secondone for rectification of the concentrated ethanol solution), onescrubber to recover entrapped ethanol from fermentation gases,

and a dehydration step by adsorption with molecular sieves. Thistype of configuration employing two distillation columns insteadof three or more was also chosen in other works dealing with sep-aration and concentration of ethanol-containing streams from cul-tivation systems (Quintero et al., 2008; Shafiei et al., 2011). Thealternative configurations proposed are indicated in the footnoteofTable 3. To define alternative 4, the concept of reaction-separa-tion integration was applied by using an extractive fermentationprocess with n-dodecanol as the solvent and using molecularsieves as the dehydration method. This last separation schemewas included during the decomposition procedure taking intoaccount that a more concentrated ethanol stream could beobtained leading to a potential reduction in energy costs duringethanol dehydration. In this way, ethanol is removed from the cul-

ture broth during the fermentation by using a selective solvent

Table 3

Technical, economic and environmental comparison of different configurations for fuel ethanol production from sugarcane at level 4 of the synthesis procedure (separationsystem).

Configuration Energy consumption, MJ/h NPV, US$ PEcn PEI, PEI/kg PEnv AHP

Base case 271,538 76,276,642 0.691 3.742 0.088 0.58284Alternative 1 270,821 82,148,494 0.863 3.642 0.114 0.72808Alternative 2 342,498 78,864,065 0.767 3.804 0.072 0.64190Alternative 3 282,331 52,594,895 0.000 3.580 0.130 0.02345Alternative 4 341,414 67,297,041 0.429 3.871 0.055 0.36186

Base case:sugar cane milling, juice conditioning, juice clarification, juice sterilization, two CSTR in series with cell recycling (purge fraction of cells: 0.3),Z. mobilisas theprocess microorganism, distillation for ethanol concentration and rectification, and adsorption with molecular sieves as the dehydration method.Alternative 1:base case butwith three CSTR steps in series. Alternative 2: based on alternative 1 with extractive distillation using ethylene glycol as the dehydration method.Alternative 3:based on

alternative 1 with dehydration by pervaporation.Alternative 4: based on alternative 1 but with an extractive fermentation process for in situ ethanol removal andincluding anadditional distillation column for solvent recovery (n-dodecanol).



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offering the possibility of improving both the fermentation andseparation steps (Bruce and Daugulis, 1992; Cardona and Snchez,2007; Snchez et al., 2006). All the alternatives for separation sys-tem are depicted inFig. 1.

The results of the configurations studied are shown inTable 3.At this level, the thermal energy consumption (steam) of each con-figuration was used as the technical indicator to compare the alter-natives. In general, the extractive distillation (alternative 2) as thedehydration method showed a higher energy consumption. Thepervaporation (alternative 3) exhibited satisfactory results regard-ing thermal energy, but no outstanding results in terms of eco-nomic performance due to the high amount of heat exchangersand pervaporation modules needed, and to the electricity con-sumption for ensuring deep vacuum conditions (0.001 bar). Thenumber of pervaporation modules required to achieve 99.6% etha-nol purity reached 28 under the operating conditions consideredduring the simulations. Actually, a reduced amount of commercialethanol dehydration plants employing pervaporation have beenreported (Baker, 2004). The extractive fermentation (alternative4) showed reduced energy and capital costs during the ethanoldehydration, but the need of recovering the n-dodecanol added sig-nificant expenditures to the overall process. In fact, this configura-tion had one of the highest energy consumption. This integratedprocess is currently under development and more research isneeded for its industrial implementation, but employing otherthann-dodecanol more selective solvents.

Environmental performance of the alternatives by impact cate-gory and total environmental indicator is shown inFig. 2a. If com-paring the base case to the alternative 1, the usage of an additionalCSTR during the fermentation stage led to a more complete conver-sionof feedstocks and, therefore, toa decreased amountofwastewa-ter. This explainsthe more reduced value of thePEI foralternative 1.The use of an additional substancein alternative 2 (ethyleneglycol)involvesthe reductionof the environmental performance. Similarly,the alternative 4 represents a poor environmental performance dueto theutilization of a solvent potentially toxic forhuman and terres-

triallife. In contrast, the environmental performance of the configu-ration involvingpervaporationwas the bestone amongthe differentseparation options because of the absence of third components likeentrainers or solvents. The alternative 1 was the best technologicalconfiguration when the combined techno-economic and environ-mental indicator was assessed. This can be explained consideringthat the molecular sieves have low operating costs compared tothe other options analyzed and that no solvents or entrainers areemployed during the ethanol dehydration improving the environ-mental indicators. The bestsynthesized configurationat this hierar-chical level is illustrated in Fig. 2b.

3.4. Level 5: synthesis of the effluent treatment system

At this level, the effluent treatment scheme for the flowsheetsynthesized at the last hierarchical level was defined. The effluents

of such configuration are the outlet gases from the scrubber usedfor recovering the ethanol vapors (see Fig. 2b), stillage leavingthe bottoms of the concentration column, aqueous stream fromthe bottoms of the rectification column, and a small purge fromthe adsorption devices filled with molecular sieves. In addition,this process flowsheet generates solid wastes like sugarcanebagasse and press mud. The latter is used in the composting pro-cess for producing organic fertilizer or as a component for animalfeed. Therefore, it was considered as a product during the environ-mental evaluation by using the WAR algorithm. Sugarcane bagassewas analyzed as a waste at this hierarchical level. To continue thesynthesis tree, the base case chosen at level 5 was the best config-uration of the level 4 considering the partial stillage recycling tothe milling step as an option for wastewater minimization. In thisway, almost all fresh water used in juice extraction can be replacedas suggested byNavarro et al. (2000). However, only 30% of thestillage generated can be recycled, implying a remaining non-treated effluent stream. The alternatives proposed are brieflydescribed in the footnote of Table 4. All the configurationsanalyzed are schematically depicted inFig. 1.

The results of the economic and environmental evaluationobtained for the base case and its alternatives are reported in Table4. The option with the best economic performance was to partiallyrecycle the stillage and not to apply any treatment to the remain-ing liquid effluent (the base case), due to the low investmentrequired. However, this configuration is not acceptable from theenvironmental viewpoint, therefore it was discarded. The bestoption was the alternative 1 in which a value added co-productis obtained (stillage concentrated up to 55% wt. solids) withoutcausing negative environmental impacts. This co-product is com-mercialized in countries like Colombia as assessed in a previouswork (Quintero et al., 2008). All the alternatives consideredshowed similar economic indicators.

The environmental assessment of the configurations proposed(seeFig. 3a) represents a great interest. The best alternative corre-sponded to the evaporation of the whole stillage. Partial stillage

recycling without any additional treatment decreased the gener-ated stillage, but the direct discharge into the environment is notavoided generating an unacceptable high impact. The partial recy-cling of the stillage combined with the evaporation of the remain-ing stillage stream (alternative 2) had a lower environmentalperformance than the evaporation of the whole stillage since theother liquid effluents increased their organic matter load due tothe recycling. The incinerationof the stillage concentrated by evap-oration (alternative 3) implied the emission of polluting gases thatcan generate a significant impact. For instance, note the higher va-lue of the acidification potential (AP) of this alternative in Fig. 3a.On the other hand, although the anaerobic digestion (alternative4) decreased the organic matter content and generated an impor-tant co-product (biogas), the effluent of this step still contained

between 5% and 10% of the original organic load from stillage.Hence, the environmental performance of this configuration is

Table 4

Technical, economic and environmental comparison of different configurations for fuel ethanol production from sugarcane at level 5 of the synthesis procedure (effluenttreatment).

Configuration Energy consumption, MJ/h NPV, US$ PEcn PEI, PEI/kg PEnv AHP

Base case 267,319 86,846,643 1.000 1.385 0.699 0.94576Alternative 1 336,126 77,779,077 0.735 1.097 0.773 0.74210Alternative 2 309,616 76,885,043 0.709 1.139 0.762 0.71874Alternative 3 336,149 75,852,973 0.679 1.435 0.686 0.68023Alternative 4 239,750 77,020,451 0.713 1.430 0.687 0.70842

Base case:sugar cane milling, juice conditioning, juice clarification, juice sterilization, three CSTR in series with cell recycling (purge fraction of cells: 0.3), Z. mobilisas theprocess microorganism, distillation for ethanol concentration and rectification, adsorption with molecular sieves as the dehydration method, and partial recycling of stillageto the milling step (30% wt. stillage).Alternative 1: base case but with concentration of the whole stillage stream up to 55% (wt.) solids.Alternative 2: base case with partial

stillage recycling (30% wt.) and concentration by evaporation of the remaining stillage stream. Alternative 3: based on alternative 1 but with the incineration of theconcentrated stillage.Alternative 4: base case but with anaerobic digestion of the whole stillage stream.



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not suitable if it is not complemented with other wastewatertreatment methods as the aerobic digestion. Other attractive alter-natives using anaerobic digesters can be proposed to diminish theorganic matter content of the effluent generating other valuablebiofuels at the same time as shown byJuang et al. (2011). Theseauthors evaluated a two-stage treatment where the wastewatergenerated during ethanol production from tapioca starch was fedto a bioreactor for hydrogen production; the effluent from this bio-reactor was fed to a reactor for methane production. Considering

the combined criterion AHP, the alternative 1 was the best config-uration at this hierarchical level (seeFig. 3b).

3.5. Level 6: heat integration

At this hierarchical level, energy flows of the process wereanalyzed (in particular, thermal ones) to determine the require-ments of steam, cooling water and electricity. The application ofPinch Analysis and the assessment of possibilities for cogenera-tion (combined steam and electricity production) within the pro-cess are valuable tools to undertake this task as demonstrated byDias et al. (2011) in the case of fuel ethanol production fromsugarcane. In the present work, a cogeneration system usingthe sugarcane bagasse as a solid fuel with production of high

pressure steam was simulated and considered in all the alterna-tive configurations generated at this hierarchical level (see the

footnote of Table 5). Base case represented the configurationwhich did not include energy integration possibilities betweenstreams and corresponded to the best alternative obtained at le-vel 5. The third case does not represent itself an alternative con-figuration, but took into account the alternative 2 withoutcalculating the carbon dioxide emissions released during bagassecombustion. This consideration is made to highlight the fact that,throughout the life cycle of the overall process at the currenttime scale, the CO2 released to the atmosphere was previously

fixed by the plantations during the growth of sugarcane (net bal-ance of CO2 equal to zero). In contrast, the usage of fossil fuelslike natural gas, oil or coal, releases into the atmosphere theCO2 fixed by the plants mainly during the Carboniferous period(299350 million years ago).

Theresults from the hierarchicallevel 6 are presentedin Table 5.The outcomes obtained show how the high investment requiredfor a cogeneration system decreased the NPV of alternative 1 re-lated to the base case. However, when considering the sale of theelectricity surplus (this possibility is allowed by the legislation ofsome countries like Colombia and Brazil), in addition to the saleof ethanol, concentrated stillage and press mud, the NPV can beimproved significantly. In this case, it was assumed that 60% ofthe electric energy produced was consumed within the plantremaining a 40% that can be commercialized in the grid. The ba-gasse moisture has an important influence on the amount of heat

Fig. 3. Level 5 of the synthesis procedure (effluent treatment). (a) Output potential environmental impact per mass of products (anhydrous ethanol and press mud) of fiveconfigurations for fuel ethanol production according to the different impact categories. The nomenclature of impact categories is indicated in the caption ofFig. 2. A briefdescription of the alternatives is shown in the footnote ofTable 4. (b) Configuration with the best performance at level 5. The conditioning of sugarcanehas been simplifiedinthe diagram. (1) Washing step, (2) Mill, (3) Clarifier, (4) Rotary drum vacuum filter, (5) Fermentation system (three CSTR in series), (6) Centrifuge, (7) Scrubber, (8)Concentration column (52% wt. ethanol), (9) Rectification column (91% wt. ethanol), (10) Molecular sieves, (11) Product tank and (12) Stillage evaporation train.



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released during its combustion as confirmed by simulation in aprevious work (Quintero et al., 2008). Thus, the use of not pre-heated wet bagasse (50% humidity) led to a 7.3% reduction in theamount of steam produced (with a pressure of 84.9 atm) comparedto the drying of bagasse up to 40% humidity, which was the config-uration selected as the one with the best performance for thecogeneration system. This very high-pressure steam can be usedto generate electricity in the turbines. In contrast, when usinglow-pressure boilers (29 atm), the reduction of the available steam

would be 13.18%. This decrease is also indicated in theMaranhaospatent (1982). In this way, the total amount of steam extractedfrom the turbines covers most of the thermal energy required forethanol production. This fact dramatically improved the economicperformance of the overall process.

The environmental performance per categories of the configura-tions studied at this level is shown in Fig. 4a. This figure reflects thelarge environmental benefit the implementation of a cogenerationunit has in an ethanol production facility employing sugarcane.

Table 5

Technical, economic and environmental comparison of different configurations for fuel ethanol production from sugarcane at level 6 of the synthesis procedure (heat integration).

Configuration Energy consumption, MJ/h NPV, US$ Pecn PEI, PEI/kg Penv AHP

Base case 336,126 77,779,077 0.735 1.097 0.773 0.74210Alternative 1 117,115 65,918,088 0.389 0.734 0.867 0.47508Alternative 2 117,115 82,579,762 0.875 0.734 0.867 0.87397Alternative 2A 117,115 82,579,762 0.875 0.221 1.000 0.89785

Base case:sugar cane milling, juice conditioning, juice clarification, juice sterilization, three CSTR in series with cell recycling (purge fraction of cells: 0.3), Z. mobilisas theprocess microorganism, distillation for ethanol concentration and rectification, adsorption with molecular sieves as the dehydration method, stillage evaporation.Alternative1: base case but with a cogeneration system using bagasse as the renewable fuel. Alternative 2: based on alternative 1 but selling the 40% of the electricity generated.

Alternative 2A:consideration of the life cycle of CO2released into the atmosphere during the bagasse combustion (net carbon dioxide emission equal to zero).

Fig. 4. Level 6 of the synthesis procedure (heat integration network). (a) Output potential environmental impact per mass of products (anhydrous ethanol, press mud andconcentrated stillage) for four configurations for fuel ethanol production according to the different impact categories. The nomenclature of impact categories is indicated inthe caption ofFig. 2.A brief description of the alternatives is shown in footnote of the Table 5. (b) Simplified technological flowsheet for fuel ethanol production fromsugarcane synthesized through the hierarchical decomposition described in this work (after completion of level 6 of synthesis procedure). The conditioning of sugarcane hasbeen simplified in the diagram. (1) Washing step. (2) Mill. (3) Clarifier. (4) Rotary drum vacuum filter. (5) Fermentation system (three CSTR in series). (6) Centrifuge. (7)

Scrubber. (8) Concentrationcolumn (52%wt. ethanol). (9) Rectificationcolumn (91%wt. ethanol). (10) Molecularsieves. (11) Product tank. (12) Stillage evaporation train. (13)Burner/boiler. (14) Turbogenerators.



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The consideration of the net emissions of CO2during cogenerationshowed a dramatic improvement of the PEI per kg of products and,therefore, in the combined techno-economic and environmentalindicator (seeTable 5).

The final technological configuration for fuel ethanol productionfrom sugarcane synthesized after six hierarchical levels by apply-ing the decomposition approach presented in this work is depictedinFig. 4b. It clearly exhibited a high technical, economic and envi-ronmental performance. This configuration allows a high degree ofintegration since, besides the anhydrous ethanol produced, thepress mud can be sold as a co-product intended for fertilization,the stillage concentrated up to 55% solids can be commercializedas a fertilizer as well, and the electricity surplus can be sold tothe electric network.

During the simulation of different technological alternativesproposed, the results were compared to the experimental datapublishedin the literature along with non-publisheddata from realethanol production facilities. This helped to get a sufficient degreeof confidence on the assumptions made during the simulations re-quired by the synthesis procedure.

4. Conclusions

The strategy of knowledge-based process synthesis to concep-tually design a process for fuel ethanol production from sugarcanewas implemented by employing a hierarchical decomposition pro-cedure into six levels. The best option considering both techno-economic and environmental criteria was properly identified. Thisconfiguration has a high degree of integration and included thesales of the press mud, concentrated stillage and electricity sur-plus. During the procedure, process modeling and simulationplayed a crucial role during the assessment of each alternative con-figuration as the synthesis tree was evolving towards the (near)optimal configuration. The proposed strategy is the basis for fur-ther process optimization.

Acknowledgements

The authors express their acknowledgments to the ColombianAdministrative Department of Science, Technology and Innovation(Colciencias), the Government of Caldas Province, the National Uni-versity of Colombia at Manizales, and the University of Caldas, fortheir financial and material support.

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