Skip to main content

Advertisement

SpringerLink
Log in

A Data Envelopment Analysis Method for Location Optimization of Microalgae Cultivation: A Case Study

  • Original Paper
  • Published:
Waste and Biomass Valorization Aims and scope Submit manuscript

Abstract

Environmental issues and depletion of fossil energy resources have triggered a sense among and practitioners to seek the ways of substituting fossil energy resources with renewable ones. Biodiesel is a green fuel which is produced from different oleaginous biomass. Nevertheless, producing biodiesel from edible feedstock is strongly criticized by Food and Agriculture Organization. Recently, microalgae have been identified as a source that can be the purification factor of wastewater and appropriate feedstock for biodiesel production. The high potential of microalgae to produce biodiesel and low-cost recovery in large-scale production encourage investors to utilize microalgae for biodiesel production. Accordingly, selecting the best locations for microalgae cultivation has a great impact on the economic viability of biodiesel production from microalgae. This paper studies application of a data envelopment analysis (DEA) approach in selecting the best locations for microalgae cultivation through ecological and economic factors. The DEA method is applied to a real case in Iran. Moreover, the well-known principal component analysis and numerical taxonomy methods are used for verification and validation of the applied DEA approach. The results confirm the applicability of the DEA approach in selecting suitable locations for microalgae cultivation areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Rawat, I., Kumar, R.R., Mutanda, T., Bux, F.: Dual role of microalgae: phyco remediation of domestic waste water and biomass production for sustainable biofuels production. Appl. Energy 88, 3411–3424 (2011)

    Google Scholar 

  2. Leite, G.B., Abdelaziz, A.E., Hallenbeck, P.C.: Algal biofuels: challenges and opportunities. Bioresour. Technol. 145, 134–141 (2013)

    Google Scholar 

  3. Kamur, A., Sharma, S.: Potential non-edible oil resources as biodiesel feedstock: an Indian perspective. Renew. Sustain. Energy Rev. 15, 1791–1800 (2011)

    Google Scholar 

  4. Spolaore, P., Joannis-Cassan, C., Duran, E., Isambert, A.: Commercial applications of microalgae. J. Biosci. Bioeng. 101, 87–96 (2006)

    Google Scholar 

  5. Banerjee, A., Sharma, R., Chisti, Y., Banerjee, U.C.: Botryococcus braunii: a renewable source of hydrocarbons and other chemicals. Crit. Rev. Biotechnol. 22, 245–278 (2002)

    Google Scholar 

  6. Chisti, Y.: Biodiesel from microalgae. Biotechnology Adv 25(3), 294–306 (2007)

    Google Scholar 

  7. Hu, Q.: Progress and perspectives on microalgal mass culture. Algal Res. 4, 1 (2014)

    Google Scholar 

  8. Hu, Q., Sommerfeld, M., Jarvis, E., Ghirardi, M., Posewitz, M., Seibert, M.Darzins, A.: Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances. Plant J. 54(4), 621–639 (2008)

    Google Scholar 

  9. Rios, S.D., Torres, C.M., Torras, C., Salvadó, J., Mateo-Sanz, J.M., Jiménez, L.: Microalgae-based biodiesel: economic analysis of downstream process realistic scenarios. Bioresour. Technol. 136, 617–625 (2013)

    Google Scholar 

  10. Kargbo, D.M.: Biodiesel production from municipal sewage sludges. Energy Fuels 24, 2791–2794 (2010)

    Google Scholar 

  11. Roberts, G.W., Fortier, M.P., Sturm, B.S.M., Stagg-Williams, S.M.: Promising pathway for algal biofuels through waste water cultivation and hydrothermal conversion. Energy Fuels. 27, 857–867 (2013)

    Google Scholar 

  12. Chisti, Y.: Constraints to commercialization of algal fuels. J. Biotechnol. 167, 201–214 (2013)

    Google Scholar 

  13. Lam, M.K., Lee, K.T.: Microalgae biofuels: a critical review of issues, problems and the way forward. Biotechnol. Adv. 30, 673–690 (2012)

    Google Scholar 

  14. Lam, M.K., Lee, K.T.: Renewable and sustainable bioenergies production from palm oil mill effluent (POME): win–win strategies toward better environmental protection. Biotechnol. Adv. 29, 124–141 (2011)

    Google Scholar 

  15. Dalrymple, O.K., Halfhide, T., Udom, I., Gilles, B., Wolan, J., Zhang, Q.: Wastewater use in algae production for generation of renewable resources: a review and preliminary results. Aquat. Biosyst. 9, 1–11 (2013)

    Google Scholar 

  16. Molina Grima, E., Acién Fernández, F.G., García Camacho, F., Chisti, Y.: Photobioreactors: light regime, mass transfer, and scaleup. J. Biotechnol. 70, 231–247 (1999)

    Google Scholar 

  17. Yun, Y.S., Lee, S.B., Park, J.M., Lee, C.I., Yang, J.W.: Carbon dioxide fixation by algal cultivation using wastewater nutrients. J. Chem. Technol. Biotechnol. 69, 451–455 (1997)

    Google Scholar 

  18. Maxwell, E.L., Folger, A.G., Hogg, S.E.: Resource Evaluation and Site Selection for Microalgae Production Systems. SERI/TR-215-2484. Solar Energy Research Institute, Golden, CO (1985)

    Google Scholar 

  19. Darzins, A., Pienkos, P., Edye, L.: Current status and potential for algal biofuels production: a report to IEA bioenergy task 39. Report T39-T2 (2010)

  20. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444 (1978)

    MathSciNet  MATH  Google Scholar 

  21. Azadeh, A., Ghaderi, S.F., Nasrollahi, M.R.: Location optimization of wind plants in Iran by an integrated hierarchical data envelopment analysis. Renew. Energy 36, 1621–1631 (2011)

    Google Scholar 

  22. Omid, M., Ghojabeige, F., Delshad, M., Ahmadi, H.: Energy use pattern and benchmarking of selected greenhouses in Iran using data envelopment analysis. Energy Convers. Manag. 52, 153–162 (2011)

    Google Scholar 

  23. Cooper, W.W., Seiford, L.M., Tone, K.: Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, 2nd edn. Springer, New York (2007)

    MATH  Google Scholar 

  24. Azadeh, A., Sheikhalishahi, M., Asadzadeh, S.M.: A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity. Renew. Energy 36, 3394–3401 (2011)

    Google Scholar 

  25. Babazadeh, R., Razmi, J., Pishvaee, M.S., Rabbani, M.: A non-radial DEA model for location optimization of Jatropha curcas L. cultivation. Ind. Crops Prod. 69, 197–203 (2015)

    Google Scholar 

  26. Amin, G.R., Toloo, M., Sohrabi, B.: An improved MCDM DEA model for technology selection. Int. J. Prod. Res. 44(13), 2681–2686 (2006)

    MATH  Google Scholar 

  27. Karsak, E.E., Ahiska, S.S.: Improved common weight MCDM model for technology selection. Int. J. Prod. Res. 46(24), 6933–6944 (2008)

    Google Scholar 

  28. Amin, G.R., Gattoufi, S., Rezaee Seraji, E.: A maximum discrimination DEA method for ranking association rules in data mining. Int, J. Comput. Math. 88(11), 2233–2245 (2011)

    MATH  Google Scholar 

  29. Toloo, M., Sohrabi, B., Nalchigar, S.: A new method for ranking discovered rules from data mining by DEA. Expert. Syst. Appl. 36(4), 8503–8508 (2009)

    Google Scholar 

  30. Toloo, M., Kresta, A.: Finding the best asset financing alternative: a DEA-WEO approach. Measurement 55, 288–294 (2014)

    Google Scholar 

  31. Toloo, M.: The most efficient unit without explicit inputs: an extended MILP-DEA model. Measurement 46, 3628–3634 (2013)

    Google Scholar 

  32. Toloo, M., Tavana, M.: A novel method for selecting a single efficient unit in data envelopment analysis without explicit inputs/outputs. Ann. Oper. Res. 253(1), 657–681 (2017)

    MathSciNet  MATH  Google Scholar 

  33. Sueyoshi, T., Goto, M.: Measurement of returns to scale and damages to scale for DEA-based operational and environmental assessment: how to manage desirable (good) and undesirable (bad) outputs? Eur. J. Oper. Res. 211, 76–89 (2011)

    MathSciNet  MATH  Google Scholar 

  34. Abdel-Raouf, N., Al-Homaidan, A.A., Ibraheem, I.B.M.: Microalgae and wastewater treatment. Saudi J. Biol. Sci. 19, 257 – 275 (2012)

    Google Scholar 

  35. Kligerman, D.C., Bouwer, E.J.: Prospects for biodiesel production from algae-based wastewater treatment in Brazil: A review. Renew. Sustain. Energy Rev. 52, 1834–1846 (2015)

    Google Scholar 

  36. Demirbas, M.F.: Biofuels from algae for sustainable development. Appl. Energy 88, 3473–3480 (2011)

    Google Scholar 

  37. Quinn, J.C., Smith, T.G., Downes, C.M., Quinn, C.: Microalgae to biofuels lifecycle assessment—multiple pathway evaluation. Algal Res. 4, 116–122 (2013)

    Google Scholar 

  38. Weyer, K., Bush, D., Darzins, A., Willson, B.: Theoretical maximum algal oil production. Bioenergy Res. 3, 204–213 (2009)

    Google Scholar 

  39. Udom, I., Zaribaf, B., Halfhide, T., Gillie, B., Dalrymple, O., Zhang, Q., Ergas, S.: Harvesting microalgae grown on wastewater. Bioresour. Technol. 139, 101–106 (2013)

    Google Scholar 

  40. Lyon, S.R., Ahmadzadeh, H., Murry, M.: Algae-Based Wastewater Treatment for Biofuel Production: Processes, Species, and Extraction Methods. vol. 2, pp. 95–115. Springer, New York (2015)

    Google Scholar 

  41. Sueyoshi, T., Goto, M.: Efficiency-based rank assessment for electric power industry: a combined use of data envelopment analysis (DEA) and DEA discriminant analysis (DA). Energy Econ. 34(3), 634–644 (2012)

    Google Scholar 

  42. Ren, J., Tan, S., Dong, L., Mazzi, A., Scipioni, A., Sovacool, B.K.: Determining the life cycle energy efficiency of six biofuel systems in China: A Data Envelopment Analysis. Bioresour. Technol. 162, 1–7 (2014)

    Google Scholar 

  43. Chen, C.M.: A critique of non-parametric efficiency analysis in energy economics studies. Energy Econ. 38, 146–152 (2013)

    Google Scholar 

  44. Zografidou, E., Petridis, K., Arabatzis, G., Kumar, P.: Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis. Comput. Oper. Res. 66, 313–326 (2016)

    MathSciNet  MATH  Google Scholar 

  45. Fraser, I., Cordina, D.: An application of data envelopment analysis to irrigated dairy farms in Northern Victoria, Australia. Agric. Syst. 59(3), 267–282 (1999)

    Google Scholar 

  46. Nassiri, S.M., Singh, S.: Study on energy use for paddy crop using envelopment analysis (DEA) technique. Appl. Energy 86, 1320–1325 (2009)

    Google Scholar 

  47. Mousavi-Avval, S.H., Rafiee, S., Mohammadi, A.: Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis. Energy 36, 909–916 (2011)

    Google Scholar 

  48. Babazadeh, R., Razmi, J., Pishvaee, M.S.: Sustainable cultivation location optimization of the Jatropha curcas L. under uncertainty: A unified fuzzy data envelopment analysis approach. Measurement 89, 252–260 (2016)

    Google Scholar 

  49. Zhang, F., Wang, J., Liu, S., Zhang, S., Sutherland, J.W.: Integrating GIS with optimization method for a biofuel feedstock supply chain. Biomass Bioenerg. 98, 194–205 (2017)

    Google Scholar 

  50. Singh, R.P., Nachtnebel, H.P.: Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal. Renew. Sustain. Energy Rev. 55, 43–58 (2016)

    Google Scholar 

  51. Marler, R.T., Arora, J.S.: The weighted sum method for multi-objective optimization: new insights. Struct. Multidiscip. Optim. 41(6), 853–862 (2010)

    MathSciNet  MATH  Google Scholar 

  52. Cook, W.D., Tone, K., Zhu, J.: Data envelopment analysis: prior to choosing a model. Omega 44, 1–4 (2014)

    Google Scholar 

  53. Sherman, H.D., Zhu, J.: Analyzing performance in service organizations. Sloan Manag. Rev. 54, 37–42 (2013)

    Google Scholar 

  54. Lovell, C.A.L., Schmidt, P.: A comparison of alternative approaches to the measurement of productive efficiency. In: Dogramaci, A., Färe, R. (eds.) Applications of Modern Production Theory: Efficiency and Productivity, pp. 3–32. Kluwer, Boston (1998)

    Google Scholar 

  55. Tofallis, C.: Combining two approaches to efficiency assessment. J. Oper. Res. Soc. 52, 1225–1231 (2001)

    MATH  Google Scholar 

  56. Färe, R., Grosskopf, S., Noh, D.-W., Weber, W.: Characteristics of a polluting technology: theory and practice. J. Econ. 26, 343–352 (2005)

    MathSciNet  MATH  Google Scholar 

  57. Liu, W.B., Meng, W., Li, X.X., Zhang, D.Q.: DEA models with undesirable inputs and outputs. Ann. Oper. Res. 173, 177–194 (2010)

    MathSciNet  MATH  Google Scholar 

  58. Azadeh, A., Moghaddam, M., Asadzadeh, S.M., Negahban, A.: An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: The case of injection process with ambiguous data. Eur. J. Oper. Res. 214, 768–779 (2011)

    MathSciNet  MATH  Google Scholar 

  59. Watanabe, M., Tanaka, K.: Efficiency analysis of Chinese industry: a directional distance function approach. Energy Policy 35, 6323–6331 (2007)

    Google Scholar 

  60. Mandal, S.K., Madheswaran, S.: Environmental efficiency of the Indian cement industry: an interstate analysis. Energy Policy 38, 1108–1118 (2010)

    Google Scholar 

  61. Toloo, M.: Data Envelopment Analysis with selected models and applications, vol. 30. SAEL, Ostrava. Ostrava: VSB-TU Ostrava (2014)

    MATH  Google Scholar 

  62. Sheskin, D.: Handbook of Parametric and Nonparametric Statistical Procedures. CRC Press, Florida (2000)

    MATH  Google Scholar 

  63. Toloo, M., Nalchigar, S., Sohrabi, B.: Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach. Cent. Eur. J. Oper. Res. https://doi.org/10.1007/s10100-018-0549-4 (2018)

    Article  MATH  Google Scholar 

Download references

Acknowledgements

Mehdi Toloo was supported by the Czech Science Foundation (GAČR 16-17810S).

Author information

Authors and Affiliations

  1. Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran

    Reza Babazadeh & Mohammad Khalili

  2. Department of Systems Engineering, Faculty of Economics, VŠB-Technical University of Ostrava, Sokolska třída 33, 702 00, Ostrava, Czech Republic

    Mehdi Toloo

Authors
  1. Reza Babazadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammad Khalili
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mehdi Toloo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Reza Babazadeh.

Appendix A (Mathematical Programming Code with GAMS)

Appendix A (Mathematical Programming Code with GAMS)

figure a
figure b

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Babazadeh, R., Khalili, M. & Toloo, M. A Data Envelopment Analysis Method for Location Optimization of Microalgae Cultivation: A Case Study. Waste Biomass Valor 11, 173–186 (2020). https://doi.org/10.1007/s12649-018-0371-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12649-018-0371-1

Keywords

Search

Navigation