Clean Technologies and Environmental Policy

, Volume 17, Issue 6, pp 1585–1595 | Cite as

A design of experiments (DOE) approach to data uncertainty in LCA: application to nanotechnology evaluation

Original Paper
First Online:
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Accepted:

Abstract

A limitation of any reported environmental performance is the considerable uncertainties present in the analysis. A methodology based on design of experiments techniques, coupled with life cycle assessment, was implemented to investigate the influence of inventory uncertainties on the predicted environmental impact. A case study on nanomanufacturing is presented. Results showed that mass data variability does not have a significant effect on the predicted environmental impacts. Material profiles for input materials did have a highly significant effect on the overall impact. Energy consumption and material characterization were identified as two areas where additional research is needed in order to obtain more accurate and precise predictions of the overall impact of nanomaterials. The methodology facilitates impact assessment of material selection for life cycle assessment, allows the establishment of a predictive model, and makes possible the identification of significant process variables as well as their interdependency.

Keywords

Emerging technologies Life cycle assessment Uncertainties Data variability Nanotechnology 

List of symbols

y

Test response

x

Independent variable

\(\hat{y}\)

Predicted response

\(\sigma ^2_y\)

Variance of the response

\(\sigma ^2_i\)

Variance of the ith independent variable

\(\mu _y\)

Mean test response

\(\mu _i\)

Mean of the ith independent variable

Y

Model response with uncertainty

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Notes

Acknowledgments

The authors gratefully acknowledge the funding provided by the Sustainable Futures IGERT Project sponsored by the U.S. National Science Foundation (Grant # DGE 033401), and the Richard and Elizabeth Henes Endowment. Special thanks to Dr. David Shonnard for his assistance with the LCA methodology.

Supplementary material

10098_2014_890_MOESM1_ESM.doc (356 kb)
Supplementary material 1 (doc 356 KB)

References

  1. Arena M, Azzone G, Conte A (2013) A streamlined LCA framework to support early decision making in vehicle development. J Clean Prod 41:105–113. doi: 10.1016/j.jclepro.2012.09.031 CrossRefGoogle Scholar
  2. Bare J (2014) Development of impact assessment methodologies for environmental sustainability. Clean Technol Environ Policy 16(4):681–690CrossRefGoogle Scholar
  3. Beard J, Sutherland J (1993) Robust suspension system design. Adv Des Autom 65:387–395Google Scholar
  4. Cherubini F, Guest G, Strømman A (2013) Application of probability distributions to the modeling of biogenic CO\(_2\) fluxes in life cycle assessment. GCB Bioenergy 4(4):784–798. doi: 10.1111/j.1757-1707.2011.01156.x Google Scholar
  5. Chiang I, Brinson B, Smalley R, Margrave J, Hauge R (2001) Purification and characterization of single-wall carbon nanotubes. J Phys Chem B 105(6):1157–1161CrossRefGoogle Scholar
  6. Clavreul J, Guyonnet D, Tonini D, Christensen T (2013) Stochastic and epistemic uncertainty propagation in LCA. Int J Life Cycle Assess 18(7):1393–1403. doi: 10.1007/s11367-013-0572-6 CrossRefGoogle Scholar
  7. DeVor R, Chang T, Sutherland J (2007) Statistical quality design and control, 2nd edn. Pearson Prentice Hall, New JerseyGoogle Scholar
  8. Dorini G, Kapelan Z, Azapagic A (2011) Managing uncertainty in multiple-criteria decision making related to sustainability assessment. Clean Technol Environ Policy 13(1):133–139. doi: 10.1007/s10098-010-0291-7 CrossRefGoogle Scholar
  9. Finnveden G, Lindfors LG (1998) Data quality of life cycle inventory datarules of thumb. Int J Life Cycle Assess 3(2):65–66. doi: 10.1007/BF02978486 CrossRefGoogle Scholar
  10. Gavankar S, Anderson S, Keller AA (2014) Critical components of uncertainty communication in life cycle assessments of emerging technologies. J Ind Ecol. doi: 10.1111/jiec.12183
  11. Goedkoop M, Spriensma R (2000) The Ecoindicator-99: A damage oriented method for life-cycle assessment, methodology report. Pré ConsultantsGoogle Scholar
  12. Gonzalez R (2009) Data analysis for experimental design. The Guilford Press, New YorkGoogle Scholar
  13. Healy M, Dahlben L, Isaacs J (2008) Environmental assessment of single-walled carbon nanotube processes. J Ind Ecol 12(3):376–393CrossRefGoogle Scholar
  14. Heijungs R, Huijbregts M (2004) A review of approaches to treat uncertainty in LCA. Proceedings of the IEMSS conferenceGoogle Scholar
  15. Hetherington A, Borrion A, Griffiths O, McManus M (2014) Use of LCA as a development tool within early research: challenges and issues across different sectors. Int J Life Cycle Assess 19(1):130–143. doi: 10.1007/s11367-013-0627-8 CrossRefGoogle Scholar
  16. Huijbregts M, Norris G, Bretz R, Ciroth A, Maurice B, von Bahr B, Weidema B, de Beaufort A (2001) Framework for modelling data uncertainty in life cycle inventories. Int J Life Cycle Assess 6(3):127–132. doi: 10.1007/BF02978728 CrossRefGoogle Scholar
  17. Huijbregts M, Gilijamse W, Ragas A, Reijnders L (2003) Evaluating uncertainty in environmental life-cycle assessment. a case study comparing two insulation options for a Dutch one-family dwelling. Environ Sci Technol 37(11):2600–2608. doi: 10.1021/es020971+ CrossRefGoogle Scholar
  18. ISO (1998) Environmental management standard, life cycle assessment, principles and framework (ISO 14040:2006). International Organization for StandardizationGoogle Scholar
  19. Kivimaa P, Mickwitz P (2006) The challenge of greening technologies—environmental policy integration in finnish technology policies. Res Policy 35(5):729–744CrossRefGoogle Scholar
  20. Klöppfer W, Curran M, Frankl P, Heijungs R, Köhler A, Olsen S (2007) Nanotechnology and life cycle assessment: a systems approach to nanotechnology and the environment. European Commission (EC) and the Project on Emerging NanotechnologiesGoogle Scholar
  21. Lloyd S, Ries R (2007) Characterizing, propagating, and analyzing uncertainty in life-cycle assessment: a survey of quantitative approaches. J Ind Ecol 11(1):161–179CrossRefGoogle Scholar
  22. Lo S, Ma H, Lo S (2005) Quantifying and reducing uncertainty in life cycle assessment using the Bayesian Monte Carlo method. Sci Total Environ 340(1):23–33. doi: 10.1016/j.scitotenv.2004.08.020 CrossRefGoogle Scholar
  23. McLellan B, Corder G (2013) Risk reduction through early assessment and integration of sustainability in design in the minerals industry. J Clean Prod 53:37–46CrossRefGoogle Scholar
  24. Mery Y, Tiruta-Barna L, Baudin I, Benetto E, Igos E (2014) Formalization of a technical procedure for process ecodesign dedicated to drinking water treatment plants. J Clean Prod 68:16–24CrossRefGoogle Scholar
  25. Meyer D, Upadhyayula V (2014) The use of life cycle tools to support decision making for sustainable nanotechnologies. Clean Technol Environ Policy 16(4):757–772. doi: 10.1007/s10098-013-0686-3 CrossRefGoogle Scholar
  26. Moign A, Vardelle A, Themelis N, Legoux J (2010) Life cycle assessment of using powder and liquid precursors in plasma spraying: the case of yttria-stabilized zirconia. Surf Coat Technol 205(2):668–673. doi: 10.1016/j.surfcoat.2010.07.015 CrossRefGoogle Scholar
  27. Roduner E (2006) Size matters: why nanomaterials are different. Chem Soc Rev 35(7):583–592. doi: 10.1039/B502142C CrossRefGoogle Scholar
  28. Roelant G, Kemppainen A, Shonnard D (2004) Assessment of the automobile assembly paint process for energy, environmental, and economic improvement. J Ind Ecol 8(1–2):173–191. doi: 10.1162/1088198041269355 Google Scholar
  29. Ross S, Evans D, Webber M (2002) How LCA studies deal with uncertainty. Int J Life Cycle Assess 7(1):47–52CrossRefGoogle Scholar
  30. Seager TP, Linkov I (2009) Uncertainty in life cycle assessment of nanomaterials. In: Linkov I, Steevens J (eds) Nanomaterials: risks and benefits., NATO science for peace and security series C: environmental securitySpringer, Dordrecht, pp 423–436. doi: 10.1007/978-1-4020-9491-0-33 CrossRefGoogle Scholar
  31. Sonnemann G, Schuhmacher M, Castells F (2003) Uncertainty assessment by a Monte Carlo simulation in a life cycle inventory of electricity produced by a waste incinerator. J Clean Prod 11(3):279–292. doi: 10.1016/S0959-6526(02)00028-8 CrossRefGoogle Scholar
  32. Steen B (1997) On uncertainty and sensitivity of LCA-based priority setting. J Clean Prod 5(4):255–262CrossRefGoogle Scholar
  33. Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes. The Organization, TokyoGoogle Scholar
  34. Tan R (2008) Using fuzzy numbers to propagate uncertainty in matrix-based LCI. Int J Life Cycle Assess 13(7):585–592CrossRefGoogle Scholar
  35. Tischner U, Deutschland U (2000) How to do EcoDesign?: a guide for environmentally and economically sound design. Verlag formGoogle Scholar
  36. van Zelm R, Huijbregts M (2013) Quantifying the trade-off between parameter and model structure uncertainty in life cycle impact assessment. Environ Sci Technol 47(16):9274–9280. doi: 10.1021/es305107s CrossRefGoogle Scholar
  37. Wardak A, Gorman M, Swami N, Deshpande S (2008) Identification of risks in the life cycle of nanotechnology-based products. J Ind Ecol 12(3):435–448CrossRefGoogle Scholar
  38. Wender B, Foley R, Prado-Lopez V, Eisenberg D, Ravikumar D, Hottle T, Sadowski J, Flanagan W, Fisher A, Laurin L, Bates M, Linkov I, Seager T, Matthew P, Guston D (2014) Illustrating anticipatory life cycle assessment for emerging photovoltaic technologies. Environ Sci Technol 48(18):10531–10538CrossRefGoogle Scholar
  39. Wiesner MR, Lowry GV, Jones KL, Hochella JMF, Giulio RTD, Casman E, Bernhardt ES (2009) Decreasing uncertainties in assessing environmental exposure, risk, and ecological implications of nanomaterials. Environ Sci Technol 43(17):6458–6462CrossRefGoogle Scholar
  40. Williams E, Weber C, Hawkins T (2009) Hybrid framework for managing uncertainty in life cycle inventories. J Ind Ecol 13(6):928–944. doi: 10.1111/j.1530-9290.2009.00170.x CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Mechanical Engineering-Engineering MechanicsMichigan Technological UniversityHoughtonUSA
  2. 2.Research Centre for Environmental Studies and Sustainability (CREIDD), Institute Charles DelaunayTroyes University of TechnologyTroyesFrance
  3. 3.Environmental and Ecological EngineeringPurdue UniversityWest LafayetteUSA

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