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A novel approach for uncertainty propagation applied to two different bio-waste management options

  • UNCERTAINTIES IN LCA
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Abstract

Purpose

A novel approach was used for quantifying uncertainty propagation in life cycle assessment (LCA). The approach was designed to be efficient and applicable in practice. The model was applied to a specific case study concerning alternative strategies for managing bio-waste: incineration versus anaerobic digestion followed by composting.

Methods

The uncertainty of each impact category was calculated starting from the variance (σ2) and geometric mean (μ) of the lognormal distribution of each input data. A procedure consisting of three mandatory steps and one facultative step was developed. Mandatory steps were calculation of the associated normal distribution for each input, calculation of the percentile curve for each input, and calculation of the percentile curve of the impact categories. The facultative step consisted in calculating the lognormal distribution of the impact categories if all the values of the percentile curve were >0.

Results and discussion

The uncertainty associated with the results of the anaerobic digestion and composting scenario was significantly higher than those associated with the incineration scenario. These results were confirmed by those obtained by Monte Carlo simulations. Environmental gains calculated for the scenario with incineration concerning acidification, global warming, terrestrial eutrophication, and photochemical ozone creation had a high level of probability (i.e., >90 %). On the contrary, the impact categories of the scenario with anaerobic digestion and composting had higher uncertainties.

Conclusions

The source of uncertainty in LCA analysis can be due to multiple factors. Among these, the variability of the values of the LCI can have a significant influence on the results of the study. LCA analysis based on the exploitation of geometric means and/or average values of inputs reported in LCI can lead to results affected by a low level of reliability. In particular, this aspect can play a relevant role for LCA-based decisions when different scenarios and options are compared. As in the case study reported in this work, neglecting the propagation of uncertainty can result in a relevant bias for obtaining a full informative impression of the problem analyzed.

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References

  • Bjorklund AE (2002) Survey of approaches to improve reliability in LCA. Int J Life Cycle Assess 7:64–72

    Article  Google Scholar 

  • Blengini GA (2008) Using LCA to evaluate impacts and resource conservation potential of composting: a case study of the Asti District in Italy. Resour Conserv Recycl 52:1373–1381

    Article  Google Scholar 

  • Bolzonella D, Pavan P, Mace S, Cecchi P (2006) Dry anaerobic digestion of different sorted organic municipal solid waste: a full scale experience. Water Sci Technol 53:23–32

    Article  CAS  Google Scholar 

  • Ciroth A, Fleischer G, Steinbach J (2004) Uncertainty calculation in life cycle assessment. Int J Life Cycle Assess 9:216–226

    Article  Google Scholar 

  • CML (2001) Bureau B&G, School of Systems Engineering, Policy Analysis and Management – Delft University of Technology, 2001. Life cycle assessment: an operational guide to the ISO standards. http://media.leidenuniv.nl/legacy/new-dutch-lca-guide-part-1.pdf. Accessed Mar 2016

  • Di Maria F, Micale C (2014) A holistic life cycle analysis of waste management scenarios at increasing source segregation intensity: the case of an Italian urban area. Waste Manag 34:2382–2392

    Article  Google Scholar 

  • Di Maria F, Micale C (2015) Life cycle analysis of management options for organic waste collected in urban area. Environ Sci Pollut Res 22:248–263

    Article  Google Scholar 

  • Di Maria F, Sordi A, Micale C (2013) Experimental and life cycle analysis of gas emissions from mechanically-biologically pretreated waste in landfill with energy recovery. Waste Manag 33:2557–2567

    Article  Google Scholar 

  • European Commission (2008) Joint Research Centre - Institute for Environment and Sustainability and DG Environment - Directorate G. 2008: European Reference Life Cycle Database, version 2.0. http://eplca.jrc.ec.europa.eu/. Accessed May 26, 2014

  • European Commission (2010) (EC) – Joint Research Centre – Institute for Environment and Sustainability. International Reference Life Cycle Data System (ILCD) Handbook – General guide for Life Cycle Assessment – Detailed guidance. First edition March 2010. EUR 24708 EN. Publications Office of the European Union. Luxembourg, LU

  • Heijungs R, Suh S (2002) The computational structure of life cycle assessment. Kluwer Academy Publisher, Dordrecht

    Book  Google Scholar 

  • Hischier R, Weidema B, Althaus HJ, Bauer C, Doka G, Dones R, Frischknecht R, Hellweg S, Humbert S, Jungbluth N, Hong J, Shaked S, Rosenbaum RK, Joillet O (2010) Analytical uncertainty propagation in life cycle inventory and impact assessment. Application to an automobile front panel. Int J Life Cycle Assess 15:499–510

    Article  Google Scholar 

  • Imbeault-Tetreault H, Jolliet O, Deschenes L, Rosenbaum RK (2013) Analytical propagation of uncertainty in life cycle assessment using matrix formulation. J Ind Ecol 17:485–492

    Article  Google Scholar 

  • ISO 14040 (2006) Environmental management: life cycle assessment, principles and guidelines. International Organization of Standardization, Geneva

    Google Scholar 

  • ISPRA (2013) Rapporto rifiuti urbani. Roma, Italy. ISBN 978-88-448-0596-8

  • Khoo HH, Lim TZ, Tan RBH (2010) Food waste conversion options in Singapore: environmental impacts based on an LCA perspective. Sci Total Environ 408:1367–1373

    Article  CAS  Google Scholar 

  • Lanzuela NE, Sanchis FJR, Sener AR, Polo GC, Vidla AP, Pellicer NS (2015) Uncertainty analysis in the environmental assessment of an integrated management system for restaurant and catering waste in Spain. Int J Life Cycle Asess 20:244–262

    Article  Google Scholar 

  • Laurent A, Bakas I, Clevereul J, Bernstad A, Niero M, Gentil E, Hauschild MZ, Christensen TH (2014a) Review of LCA studies of solid waste management systems – Part II: methodological guidance. Waste Manag 34:589–606

    Article  Google Scholar 

  • Laurent A, Bakas I, Clevereul J, Bernstad A, Niero M, Gentil E, Hauschild MZ, Christensen TH (2014b) Review of LCA studies of solid waste management systems – Part I: lesson learned and perspective. Waste Manag 34:573–588

    Article  Google Scholar 

  • Lloyd MS, Ries R (2007) Characterizing, propagating, and analyzing uncertainty in life cycle assessment. J Ind Ecol 11:161–179

    Article  Google Scholar 

  • MacLeod S, Faset A, Mackay D (2002) Evaluating and expressing the propagation of uncertainty in chemical fare and bioaccumulation models. Environ Toxicol Chem 21:700–709

    Article  CAS  Google Scholar 

  • Maurice B, Frischknecht R, Coelho-Schwirtz V, Hungerbuhler K (2000) Uncertainty analysis in life cycle inventory. Application to the production of electricity with French coal power plants. J Clean Prod 8:95–108

    Article  Google Scholar 

  • Prè Consultants (2013) SimaPro 8 Prè Consultants BV, Amersfoort, The Netherlands; 2013. Available on line at <www.pre-sustainability.com/download/All-About-SimaPro8-oct-2013.pdf> (last access January 2014)

  • Rico C, Rico JL, Tejero I, Munoz N, Gomex B (2011) Anaerobic digestion of the liquid fraction of dairy manure in pilot plant for biogas production: residual methane yield of digestate. Waste Manag 31:2167–2173

    Article  CAS  Google Scholar 

  • Rigamonti L, Falbo A, Grosso M (2013) Improvement actions in waste management systems at the provincial scale based on a life cycle assessment evaluation. Waste Manag 33:2568–2578

    Article  CAS  Google Scholar 

  • Ross S, Evans D, Webber M (2002) How LCA studies deal with uncertainty. Int J Life Cycle Assess 7:47–52

    Article  Google Scholar 

  • Sills DL, Paramita V, Franke MJ, Jhonson MC, Akabas TM, Greene CH, Tester JW (2012) Quantitative uncertainty analysis of life cycle assessment for algal biofuel production. Environ Sci Technol 47:687–694

    Article  Google Scholar 

  • Sonesson U, Bjorklund A, Carlsson M, Dalemo M (2000) Environmental and economic analysis of management systems for biodegradable waste. Resour Conserv Recycl 28:29–53

    Article  Google Scholar 

  • TERNA (2013) Dati statistici sull’energia elettrica in Italia; 2013. Available on line at http://www.terna.it/LinkClick.aspx?fileticket=8fzKlKgsmzY%3D&tabid=418&mid=2501 (last access June 2014)

  • Tillmann DA (1991) The combustion of solid fuels and waste. Academic Press, San Diego, CA 1991. ISBN 0-12-691255-6

  • US-EPA (1989) Exposure factors handbook. EPA, Washington

    Google Scholar 

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Correspondence to Francesco Di Maria.

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Responsible editor: Roland Hischier

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Di Maria, F., Micale, C. & Contini, S. A novel approach for uncertainty propagation applied to two different bio-waste management options. Int J Life Cycle Assess 21, 1529–1537 (2016). https://doi.org/10.1007/s11367-016-1101-1

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  • DOI: https://doi.org/10.1007/s11367-016-1101-1

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