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Application of stochastic analytic hierarchy process for evaluating algal cultivation systems for sustainable biofuel production

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Abstract

Algal biomass is considered as a promising source of alternative fuel energy given its high yield per land area and other potential benefits. Categorized as an advanced generation biofuel feedstock, microalgae are grown in non-conventional ways through different cultivation systems. A preference of a cultivation system may vary depending on a given scenario and its inherent configuration (strength and weakness). Hence, the usage of a specific cultivation system to sustainably produce algal biofuels depends on various factors. Thus, a multi-criteria approach based on analytic hierarchy process (AHP) is proposed for evaluating alternative cultivation systems for sustainable production of algal biofuels. The main criteria considered to evaluate the alternatives based on consultation with a panel of expert and from literature are environmental impact, energy consumption, economic viability, social acceptability, and system robustness. Sub-criteria were identified under each main criterion to further qualify the analysis into relevant sub-factors in the sustainable production of algal biofuels. Three cultivations systems were used as an example to demonstrate the developed decision model using qualitative data and quantitative data. Probabilistic scenarios were analyzed using stochastic approach via Monte Carlo simulation. The results of the stochastic-based AHP showed which cultivation system is preferred for conservative (risk-averse) and optimistic (risk-inclined) scenarios.

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Abbreviations

a ij :

Pairwise comparison rating coefficient for element i and element j

a′ ij :

Stochastic pairwise comparison rating coefficient for element i and element j

A :

Positive reciprocal matrix

A′:

Stochastic positive reciprocal matrix

M :

Set of criteria

M′:

Set of sub-criteria

N :

Set of alternatives

n :

Matrix order

q :

Members of the set of criteria

q’ :

Members of the set of sub-criteria

Q :

Maximum number members of the set of criteria

Q′:

Maximum number members of the set of sub-criteria

r :

Members of the set of criteria

R :

Maximum number members of the set of alternatives

w i :

Row weights in the pairwise comparison rating coefficient

w j :

Column weights in the pairwise comparison rating coefficient

W i :

Normalized row weights of the pairwise comparison rating coefficient

i :

Elements in the row

j :

Elements in the column

References

  • Aguilar JEA, Ortega JMP, Campos JBG, González MS, El-Halwagi MM (2014) Optimal planning and site selection for distributed multiproduct biorefineries involving economic, environmental and social objectives. J Clean Prod 65(2):270–294

    Article  Google Scholar 

  • Aikins GP, Heath A, Mentzer RA, Mannan MS, Rogers WJ, El-Halwagi MM (2010a) A Multi-criteria approach to screening alternatives for converting sewage sludge to biodiesel. J. Loss Prev Process Ind 23(3):412–420

    Article  Google Scholar 

  • Aikins GP, Nadim A, Mahalec V, El-Halwagi MM (2010b) Design and analysis of biodiesel production from algae grown through carbon sequestration. Clean Technol Environ Policy 12:239–254

    Article  Google Scholar 

  • Arbel A, Vargas L (1993) Preference simulation and preference programming: robustness issues in priority derivation. Eur J Oper Res 69:200–209

    Article  Google Scholar 

  • Arriaga CG, González MS, Ortega JMP, El-Halwagi MM (2014) Sustainable integration of algal biodiesel production with steam electric-power plants for greenhouse gas mitigation. ACS Sustain Chem Eng 2(6):1388–1403

    Article  Google Scholar 

  • Bañuelas R, Antony J (2006) Application of stochastic process within a domestic appliance manufacturer. J Oper Res Soc 58:29–38

    Article  Google Scholar 

  • Berrittella M, La Franca L, Zito P (2009) An analytic hierarchy process for ranking operating costs of low cost and full service airlines. J Air Transp Manag 15(5):249–255

    Article  Google Scholar 

  • Bowling IM, Ortega JMP, El-Halwagi MM (2011) Facility location and supply chain optimization for a biorefinery. Ind Eng Chem Res 50(10):6276–6286

    Article  CAS  Google Scholar 

  • Carrera DG, Mack A (2010) Sustainability assessment of energy technologies via social indicators: results of a survey among European energy experts. Energy Policy 38(2):1030–1039

    Article  Google Scholar 

  • Castelazo ES, Azapagic A (2014) Sustainability assessment of energy systems: integrating environmental, economic and social aspects. J Clean Prod 80:119–138

    Article  Google Scholar 

  • Chiang SY, Wei CC, Chiang TH, Chen WL (2011) How can electronics industries become green manufacturers in Taiwan and Japan. Clean Technol Environ Policy 13(1):37–47

    Article  Google Scholar 

  • Chisti Y (2007) Biodiesel from microalgae. Biotechnol Adv 25:294–306

    Article  CAS  Google Scholar 

  • Cinelli M, Coles SR, Jørgensen A, Zamagni A, Fernando C, Kirwan K (2013) Workshop on life cycle sustainability assessment: the state of the art and research needs—November 26, Copenhagen, Denmark. Int. J. Life Cycle Assess 18:1421–1424

    Article  Google Scholar 

  • Cinelli M, Coles SR, Kirwan K (2014) Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment. Ecol Ind 46:138–148

    Article  Google Scholar 

  • Čuček L, Klemeš JJ, Kravanja Z (2012) A review of footprint analysis tools for monitoring impacts on sustainability. J Clean Prod 34:9–20

    Article  Google Scholar 

  • Čuček L, Klemeš JJ, Varbanov PS, Kravanja Z (2013) Dealing with high-dimensionality of criteria in multi-objective optimization of biomass energy supply network. Ind Eng Chem Res 52:7223–7239

    Article  Google Scholar 

  • Čuček L, Klemeš JJ, Kravanja Z (2014) Objective dimensionality reduction method within multi-objective optimisation considering total footprints. J Clean Prod 71:75–86

    Article  Google Scholar 

  • Čuček L, Klemeš JJ, Varbanov PS, Kravanja Z (2015) Significance of environmental footprints for evaluating sustainability and security of development. Clean Technol Environ Policy. doi:10.1007/s10098-015-0972-3

    Google Scholar 

  • Daroch M, Geng S, Wang G (2013) Recent advances in liquid biofuel production from algal feedstocks. Appl Energy 102:1371–1381

    Article  Google Scholar 

  • De Benedetto L, Klemeš J (2009) The Environmental Performance Strategy Map: an integrated LCA approach to support the strategic decision-making process. J Clean Prod 17:900–906

    Article  Google Scholar 

  • de Luca S (2014) Public engagement in strategic transportation planning: an analytic hierarchy process based approach. Transp Policy 33:110–124

    Article  Google Scholar 

  • Durbach I, Lahdelma R, Salminen P (2014) The analytic hierarchy process with stochastic judgements. Eur J Oper Res 238:552–559

    Article  Google Scholar 

  • El-Halwagi AM, Rosas C, Ponce-Ortega JM, Jiménez-Gutiérrez A, Mannan MS, El-Halwagi MM (2013) Multi-objective optimization of biorefineries with economic and safety objectives. AIChE J 59(7):2427–2434

    Article  CAS  Google Scholar 

  • Evans A, Strezov V, Evans TJ (2009) Assessment of sustainability indicators for renewable energy technologies. Renew Sustain Energy Rev 13(5):1082–1088

    Article  Google Scholar 

  • Frikha A, Moalla H (2015) Analytic hierarchy process for multi-sensor data fusion based on belief function theory. Eur J Oper Res 241(1):133–147

    Article  Google Scholar 

  • Gomez JM, Montero OB, Ortega JMP, Rivera FN, González MS, El-Halwagi MM (2013) On the environmental, economic and safety optimization of distributed treatment systems for industrial effluents discharged to watersheds. J Loss Prev Process Ind 26:908–923

    Article  Google Scholar 

  • Greenhalgh C, Azapagic A (2009) Review of drivers and barriers for nuclear power in the UK. Environ Sci Policy 12(7):1052–1067

    Article  Google Scholar 

  • Grima EM (1999) Microalgae, mass culture methods. In: Flickinger MC, Drew SW (eds) Encyclopedia of bioprocess technology: fermentation, biocatalysis and bioseparation, vol 3. Wiley, New York, pp 1753–1769

    Google Scholar 

  • Hahn ED (2006) Link function selection in stochastic multicriteria decision making models. Eur J Oper Res 172:86–100

    Article  Google Scholar 

  • Hauschild M, Wenzel H (1998) Environmental assessment of products. Volume 2: scientific background. Chapman and Hall, London. ISBN 0 412 80810 2

  • Hauser D, Tadikamalla P (1996) The analytic hierarchy process in an uncertain environment: a simulation approach. Eur J Oper Res 91:27–37

    Article  Google Scholar 

  • Huesemann M, Benemann JR (2009) Biofuels from microalgae: review of products, process and potential, with special focus on Dunaliella sp. In: BenAmotz A, Polle JEW, Subba Rao VD (eds) The alga Dunaliella: biodiversity, physiology, genomics and biotechnology. Science Publishers, New Hampshire

  • Hsueh JT, Lin CY (2015) Constructing a network model to rank the optimal strategy for implementing the sorting process in reverse logistics: case study of photovoltaic industry. Clean Technol Environ Policy 17(1):155–174

    Article  Google Scholar 

  • Huang IB, Keisler J, Linkov I (2011) Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Sci Total Environ 409:3578–3594

    Article  CAS  Google Scholar 

  • Ishizaka A, Labib A (2011) Review of the main developments in the analytic hierarchy process. Expert Syst Appl 38:14336–14345

    Article  Google Scholar 

  • Jacobson MZ (2009) Review of solutions to global warming, air pollution, and energy security. Energy Environ Sci 2(2):148–173

    Article  CAS  Google Scholar 

  • Jalao ER, Wu T, Shunk D (2014) A stochastic AHP decision making methodology for imprecise preferences. Inf Sci 270:192–203

    Article  Google Scholar 

  • Jorquera O, Kiperstok A, Sales EA, Embirucu M, Ghirardi ML (2010) Comparative energy life-cycle analyses of microalgal biomass production in open ponds and photobioreactors. Bioresour Technol 101:1406–1413

    Article  CAS  Google Scholar 

  • Kim CJ, Yoo WS, Lee UK, Song KJ, Kang KI, Cho H (2010) An experience curve-based decision support model for prioritizing restoration needs of cultural heritage. J Cultur Herit 11:430–437

    Article  Google Scholar 

  • Lokey E (2009) Barriers to clean development mechanism renewable energy projects in Mexico. Renew Energy 34(3):504–508

    Article  Google Scholar 

  • Mata TM, Martins AA, Caetano NS (2010) Microalgae for biodiesel production and other applications: a review. Renew Sustain Energy Rev 14:217–232

    Article  CAS  Google Scholar 

  • Mata TM, Martins AA, Sikdar SK, Costa CAV (2011) Sustainability considerations of biodiesel based on supply chain analysis. Clean Technol Environ Policy 13(5):655–671

    Article  Google Scholar 

  • Mohan T, El-Halwagi MM (2007) An algebraic targeting approach for effective utilization of biomass in cogeneration systems through process integration. J Clean Technol Environ Policy 9(1):13–25

    Article  Google Scholar 

  • Moheimani NR, Borowitzka MA (2006) The long-term culture of the coccolithophore Pleurochrysis carterae (Haptophyta) in outdoor raceway ponds. J Appl Phycol 18:703–712

    Article  Google Scholar 

  • National Research Council (NRC) (2012) Sustainable development of algal biofuels in the United States. The National Academies Press, Washington DC

    Google Scholar 

  • Norsker NH, Barbosa MJ, Vermuë MH, Wijfells RH (2011) Microalgal production—a close look at the economics. Biotechnol Adv 29:24–27

    Article  CAS  Google Scholar 

  • Ojha A, Das B, Mondal S, Maiti M (2010) A stochastic discounted multi-objective solid transportation problem for breakable items using analytical hierarchy process. Appl Math Model 34:2256–2271

    Article  Google Scholar 

  • Onat N, Bayar H (2010) The sustainability indicators of power production systems. Renew Sustain Energy Rev 14(9):3108–3115

  • Perera ATD, Attalage RA, Perera KKCK, Dassanayake VPC (2013) A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems. Appl Energy 107:412–425

    Article  Google Scholar 

  • Pohekar SD, Ramachandran M (2004) Application of multi-criteria decision making to sustainable energy planning—a review. Renew Sustain Energy Rev 81:365–381

    Article  Google Scholar 

  • Prado-Lopez V, Seager TP, Chester M, Laurin L, Bernardo M, Tylock S (2014) Stochastic multi-attribute analysis (SMAA) as an interpretation method for comparative life-cycle assessment (LCA). Int J Life Cycle Assess 19(2):405–416

    Article  Google Scholar 

  • Promentilla MA, Aviso KB, Tan RR (2015) A fuzzy analytic hierarchy process (FAHP) approach for optimal selection of low-carbon energy technologies. Chem Eng Trans 45:1141–1146

    Google Scholar 

  • Razon LF (2015) Is nitrogen fixation (once again) “vital to the progress of civilized humanity”? Clean Technol Environ Policy 17(2):301–307

    Article  CAS  Google Scholar 

  • Razon LF, Tan RR (2011) Net energy analysis of the production of biodiesel and biogas from the microalgae: haematococcus pluvialis and Nannochloropsis. Appl Energy 88:3507–3514

    Article  CAS  Google Scholar 

  • Richmond A, Wu ZC (2001) Optimization of a plate glass reactor for mass production of Nannochloropsis sp. outdoors. J Biotechnol 85:259–269

    Article  CAS  Google Scholar 

  • Rippka R, Deruelles J, Waterbury JB, Herdman M, Stanier RY (1979) Generic assignment, strain histories and properties of pure cultures of cyanobacteria. J Gen Microbiol 111:1–61

    Google Scholar 

  • Rockström J, Steffen W, Noone K, Persson Å, Chapin FS, Lambin EF, Lenton TM, Scheffer M, Folke C, Schellnhuber HJ, Nykvist B, De Wit CA, Hughes T, Van Der Leeuw S, Rodhe H, Sörlin S, Snyder PK, Costanza R, Svedin U, Falkenmark M, Karlberg L, Corell RW, Fabry VJ, Hansen J, Walker B, Liverman D, Richardson K, Crutzen P, Foley JA (2009) A safe operating space for humanity. Nature 461:472–475

    Article  Google Scholar 

  • Rodolfi L, Chini Zittelli G, Bassi N, Padovani G, Biondi N, Bonini G, Tredici M (2009) Microalgae for oil: strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnol Bioeng 102:100–112

    Article  CAS  Google Scholar 

  • Rosenbloom ES (1996) A probabilistic interpretation of the final rankings in AHP. Eur J Oper Res 95:371–378

    Google Scholar 

  • Ruoning X, Xiaoyan Z (1992) Extensions of the analytic hierarchy process in fuzzy environment. Fuzzy Sets Syst 52:251–257

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw-Hill Inc, New York, p 287

    Google Scholar 

  • Saaty TL, Vargas LG (1987) Uncertainty and rank order in the analytic hierarchy process. Eur J Oper Res 32:107–117

    Article  Google Scholar 

  • Subhadra BG (2011) Water management policies for the algal biofuel sector in the Southwestern United States. Appl Energy 88:3492–3498

    Article  Google Scholar 

  • Tan RR, Promentilla MAB (2013) A methodology for augmenting sparse pairwise comparison matrices in AHP: applications to energy systems. Clean Technol Environ Policy 15(4):713–719

    Article  Google Scholar 

  • Tan RR, Culaba AB, Purvis MRI (2004) POLCAGE 1.0—a possibilistic life-cycle assessment model for evaluating alternative transportation fuels. Environ Model Softw 19:907–918

    Article  Google Scholar 

  • Tan RR, Ballacillo JAB, Aviso KB, Culaba AB (2009) A fuzzy multiple-objective approach to the optimization of bioenergy system footprints. Chem Eng Res Des 87:1162–1170

    Article  CAS  Google Scholar 

  • Tan RR, Aviso KB, Huelgas A, Promentilla MAB (2014) Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects. Process Saf Environ Prot 92(5):467–475

    Article  CAS  Google Scholar 

  • Tan J, Low KY, Sulaiman NMN, Tan RR, Promentilla MAB (2015) Fuzzy analytical hierarchy process (AHP) for multi-criteria selection in drying and harvesting process of microalgae system. Chem Eng Trans 45:829–834

    Google Scholar 

  • Tang Y, Sun H, Yao Q, Wang Y (2014) The selection of key technologies by the silicon photovoltaic industry based on the Delphi method and AHP (analytic hierarchy process): case study of China. Energy 75:474–482

    Article  CAS  Google Scholar 

  • Terry KL, Raymond LP (1985) System design for the autotrophic production of microalgae. Enzyme Microb Technol 7:474–488

    Article  Google Scholar 

  • Tong O, Shao S, Zhang Y, Chen Y, Liu SL, Zhang SS (2012) An AHP-based water-conservation and waste-reduction indicator system for cleaner production of textile-printing industry in China and technique integration. Clean Technol Environ Policy 14(5):857–868

    Article  Google Scholar 

  • Tredici MR (1999) Bioreactors, photo. In: Flickinger MC, Drew SW (eds) Encyclopedia of bioprocess technology: fermentation, biocatalysis and bioseparation. Wiley, New York, pp 395–419

    Google Scholar 

  • Tseng ML, Lin YH, Chiu ASF, Liao JCH (2008) Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer, Taiwan. Clean Technol Environ Policy 10(1):17–29

    Article  Google Scholar 

  • Turcksin L, Bernardini A, Macharis C (2011) A combined AHP-PROMETHEE approach for selecting the most appropriate policy scenario to stimulate a clean vehicle fleet. Proced Soc Behav Sci 20:954–965

    Article  Google Scholar 

  • Ubando A (2014) Development of a fuzzy optimization methodology for the systematic design of a microalgal multifunctional bioenergy system. De La Salle University, Manila, Dissertation, Chapter 4

  • Ubando A, Cuello J, Culaba AB, Promentilla MAB, Tan RR (2014a) Multi-criterion evaluation of cultivation systems for sustainable algal biofuel production using analytic hierarchy process and Monte Carlo simulation. Energy Proced 61:389–392

    Article  Google Scholar 

  • Ubando AT, Cuello JL, Culaba AB, El-Halwagi MM, Tan RR, (2014b). Multi-regional multi-objective optimization of an algal biofuel polygeneration supply chain with fuzzy mathematical programming. In: American Society of Mechanical Engineers (ASME) Digital Collection: ASME 2014 8th international conference on energy sustainability, Boston. June 30-July 2, 2014. Paper no. IMECE2013-66236, pp. V012T13A045. doi:10.1115/IMECE2013-66236, ISBN: 978-0-7918-5641-3

  • Ubando A, Felix CB, Promentilla MAB, Culaba AB (2015) Strategic site selection of microalgae industry in the Philippines using analytic hierarchy process. Chem Eng Tran 45 (in press)

  • Vaidya OS, Kumar S (2006) Analytic hierarch process: an overview of applications. Eur J Oper Res 169:1–29

    Article  Google Scholar 

  • Valencia BJH, Lira LF, Ortega JMP, González MS, El-Halwagi MM (2014) Multi-objective design of inter-plant trigeneration systems. AIChE J 60(1):213–236

    Article  Google Scholar 

  • Van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241

    Article  Google Scholar 

  • Vargas LD (1990) An overview of the analytic hierarchy process and its applications. Eur J Oper Res 48:2–8

    Article  Google Scholar 

  • Wenzel H, Hauschild M, Alting L (1997) Environmental assessment of products. Volume 1: methodology, tools and case studies in product development. Chapman and Hall, London. ISBN 0 412 80800 5

  • Wu ZC, Zmora O, Kopel R, Richmond A (2001) An industrial-size flate plate glass reactor for mass production of Nannochloropsis sp. (Eustigmatophyceae). Aquaculture 195:35–49

    Article  Google Scholar 

  • Yang IT, Wang WC, Yang TI (2012) Automatic repair of inconsistent pairwise weighting matrices in analytic hierarchy process. Autom Constr 22:290–297

    Article  Google Scholar 

  • Yang X, Yan L, Zeng L (2013) How to handle uncertainties in AHP: the Cloud Delphi hierarchical analysis. Inf Sci 222:384–404

    Article  Google Scholar 

  • Zamagni A, Buttol P, Buonamici P, Masoni P, Guine'e JB, Huppes G, Heijungs R, Van der Voet E, Ekvall T, Rydberg T (2009) D20 blue paper on life cycle sustainability analysis. Institute of Environmental Sciences, Leiden University (CML). CALCAS Project, http://www.calcasproject.net/default.asp?site=calcas&-page_id=E2669B0F-9DB7-4D1E-95B0-407BC7949030

  • Zhu B, Xu Z (2014) Analytic hierarchy process-hesitant group decision making. Eur J Oper Res 239:794–801

    Article  Google Scholar 

  • Zittelli GC, Lavista F, Bastianini A, Rodolfi L, Vicenzini M, Tredici MR (1999) Production of eicosapentaenoic acid by Nannochloropsis sp. cultures in outdoor tubular photobioreactors. J Biotechnol 70:299–312

    Article  Google Scholar 

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Acknowledgments

The financial support of the Fulbright Philippine Agriculture Scholarship Program through the Philippine-American Educational Foundation, the Philippine Commission on Higher Education through the PHERNet program, and the Faculty Development Program of De La Salle University for the Ph.D. studies of the first author is gratefully acknowledged. Mr. Louie Moran is highly appreciated for his assistance in the schematic diagrams.

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Authors and Affiliations

  1. Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, NCR, Philippines

    Aristotle T. Ubando & Alvin B. Culaba

  2. Department of Agricultural and Biosystems Engineering, The University of Arizona, 1177 E. 4th Street, Shantz Building, Tucson, AZ, 85721-0038, USA

    Joel L. Cuello

  3. The Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU Room 200, College Station, TX, 77843-3122, USA

    Mahmoud M. El-Halwagi

  4. Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, NCR, Philippines

    Michael Angelo B. Promentilla & Raymond R. Tan

  5. Center for Engineering and Sustainable Development Research (CESDR), De La Salle University, 2401 Taft Avenue, 0922 Manila, NCR, Philippines

    Aristotle T. Ubando, Alvin B. Culaba, Michael Angelo B. Promentilla & Raymond R. Tan

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  1. Aristotle T. Ubando
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  2. Joel L. Cuello
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Correspondence to Aristotle T. Ubando.

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Ubando, A.T., Cuello, J.L., El-Halwagi, M.M. et al. Application of stochastic analytic hierarchy process for evaluating algal cultivation systems for sustainable biofuel production. Clean Techn Environ Policy 18, 1281–1294 (2016). https://doi.org/10.1007/s10098-015-1073-z

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