Analysis of water use impact assessment methods (part A): evaluation of modeling choices based on a quantitative comparison of scarcity and human health indicators

  • Anne-Marie Boulay
  • Masaharu Motoshita
  • Stephan Pfister
  • Cécile Bulle
  • Ivan Muñoz
  • Helen Franceschini
  • Manuele Margni
WATER USE IN LCA

Abstract

Purpose

In the past decade, several methods have emerged to quantify water scarcity, water availability and the human health impacts of water use. It was recommended that a quantitative comparison of methods should be performed to describe similar impact pathways, namely water scarcity and human health impacts from water deprivation. This is precisely the goal of this paper, which aims to (1) identify the key relevant modeling choices that explain the main differences between characterization models leading to the same impact indicators; (2) quantify the significance of the differences between methods, and (3) discuss the main methodological choices in order to guide method development and harmonization efforts.

Methods

The modeling choices are analysed for similarity of results (using mean relative difference) and model response consistency (through rank correlation coefficient). Uncertainty data associated with the choice of model are provided for each of the models analysed, and an average value is provided as a tool for sensitivity analyses.

Results

The results determined the modeling choices that significantly influence the indicators and should be further analysed and harmonised, such as the regional scale at which the scarcity indicator is calculated, the sources of underlying input data and the function adopted to describe the relationship between modeled scarcity indicators and the original withdrawal-to-availability or consumption-to-availability ratios. The inclusion or exclusion of impacts from domestic user deprivation and the inclusion or exclusion of trade effects both strongly influence human health impacts. At both midpoint and endpoint, the comparison showed that considering reduced water availability due to degradation in water quality, in addition to a reduction in water quantity, greatly influences results. Other choices are less significant in most regions of the world. Maps are provided to identify the regions in which such choices are relevant.

Conclusions

This paper provides useful insights to better understand scarcity, availability and human health impact models for water use and identifies the key relevant modeling choices and differences, making it possible to quantify model uncertainty and the significance of these choices in a specific regional context. Maps of regions where these specific choices are of importance were generated to guide practitioners in identifying locations for sensitivity analyses in water footprint studies. Finally, deconstructing the existing models and highlighting the differences and similarities has helped to determine building blocks to support the development of a consensual method.

Keywords

Impact modeling Life cycle assessment Model comparison Water deprivation Water footprint 

Supplementary material

11367_2014_814_MOESM1_ESM.docx (1.5 mb)
ESM 1(DOCX 1530 kb)

References

  1. Aguilar-Manjarrez J (2006) WRI Major watersheds of the world delineation. FAO-Aquaculture Management and Conservation ServiceGoogle Scholar
  2. Alcamo J, Henrichs T, Rosch T (2000) World water in 2025—global modeling and scenario analysis for the World Commission on Water for the 21st century. Kassel World Water seriesGoogle Scholar
  3. Alcamo J, Doll P, Henrichs T, Kaspar F, Lehner B et al (2003a) Development and testing of the WaterGAP 2 global model of water use and availability. Hydrol Sci J 48(3):317–337CrossRefGoogle Scholar
  4. Alcamo J, Doll P, Henrichs T, Kaspar F, Lehner B et al (2003b) Global estimates of water withdrawals and availability under current and future “business-as-usual” conditions. Hydrol Sci J 48(3):339–348CrossRefGoogle Scholar
  5. Bauer C, Zapp P (2005) Towards generic factors for land Use and water consumption. In: Dubreuil A (ed) Life cycle assessment of metals: issues and research directions. SETAC - USA, Pensacola, USAGoogle Scholar
  6. Bayart J-B et al (2010) Framework for assessment of off-stream freshwater use within LCA. Int J Life Cycle Assess 15(5):439CrossRefGoogle Scholar
  7. Bayart J-B et al (2014) The Water Impact Index: a simplified single-indicator approach for water footprinting. Int J Life Cycle Assess 19(6):1336–1344CrossRefGoogle Scholar
  8. Berger M, Finkbeiner M (2013) Methodological challenges in volumetric and impact-oriented water footprints. J Ind Ecol 17(1):79–89CrossRefGoogle Scholar
  9. Boulay A-M, Bouchard C et al (2011a) Categorizing water for LCA inventory. Int J Life Cycle Assess 16(7):639–651CrossRefGoogle Scholar
  10. Boulay A-M, Bulle C et al (2011b) Regional characterization of freshwater use in LCA: modeling direct impacts on human health. Environ Sci Technol 45(20):8948–8957CrossRefGoogle Scholar
  11. Bourgault G, Lesage P, Margni M, Bulle C, Boulay A-M, Samson, R (2012) Quantification of uncertainty of characterisation factors due to spatial variability. SETAC Europe 22nd Annual Meeting / 6th SETAC World Congress, Berlin.Google Scholar
  12. Brent AC (2004) A life cycle impact assessment procedure with resource groups as areas of protection. Int J Life Cycle Assess 9(3):172–179CrossRefGoogle Scholar
  13. Bulle C, Humbert S, Jolliet O, Rosenbaum R, Margni M (2012) IMPACT World+: A new global regionalized life cycle impact assessment method, LCA XII, United States, Washington, Tacoma.Google Scholar
  14. Fekete B, Vörösmarty C, Grabs W (2002) High-resolution fields of global runoff combining observed river discharge and simulated water balances. Global Biogeochem Cy 16(3):15.1-15-10Google Scholar
  15. Fenner K et al (2005) Comparing estimates of persistence and long-range transport potential among multimedia models. Environ Sci Technol 39(7):1932–1942CrossRefGoogle Scholar
  16. Food and Agriculture Organization of the United Nations (nd.) AQUASTAT-FAO’s information system on water and agriculture. Available at: http://www.fao.org/NR/WATER/AQUASTAT/main/index.stm
  17. Frischknecht R et al. (2008) Swiss ecological scarcity method: the new version 2006Google Scholar
  18. Hertwich EG, McKone TE, Pease WS (1999) Parameter uncertainty and variability in evaluative fate and exposure models. Risk Anal 19(6):1193–1204Google Scholar
  19. Hoekstra AY et al (2012) Global monthly water scarcity: blue water footprints versus blue water availability. PLoS ONE 7(2):e32688. doi:10.1371/journal.pone.0032688 CrossRefGoogle Scholar
  20. Initiative, U.-S.L.C (2012) http://www.wulca-waterlca.org/
  21. ISO 14046 (2014) Water footprint—principles, requirements and guidelinesGoogle Scholar
  22. Kounina A et al (2013) Review of methods addressing freshwater use in life cycle inventory and impact assessment. Int J Life Cycle Assess 18:707–721CrossRefGoogle Scholar
  23. Mekonnen MM, Hoekstra AY (2011) National water footprint accounts: the green, blue and grey water footprint of production and consumption. UNESCO-IHE, Delft, The NetherlandsGoogle Scholar
  24. Motoshita M, Itsubo N, Inaba A (2010a) Damage assessment of water scarcity for agricultural use 1. In: Proceedings of 9th international conference on EcoBalance. National Institute of Advanced Industrial Science and Technology (AIST), pp 3–6Google Scholar
  25. Motoshita M, Itsubo N, Inaba A (2010b) Development of impact factors on damage to health by infectious diseases caused by domestic water scarcity. Int J Life Cycle Assess 16(1):65–73CrossRefGoogle Scholar
  26. Owens JW (2002) Water resources in life-cycle impact assessment: considerations in choosing category indicators. J Ind Ecol 5(2):37–54CrossRefGoogle Scholar
  27. Perry C (2007) Efficient irrigation; inefficient communication; flawed recommendations. Irrig Drain 56:367–378CrossRefGoogle Scholar
  28. Pfister S, Bayer P (2013) Monthly water stress: spatially and temporally explicit consumptive water footprint of global crop production. J Clean Prod. Available at: http://www.ifu.ethz.ch/ESD/downloads/reports/Monthly_WSI_LCA_FOOD.pdf
  29. Pfister S, Koehler A, Hellweg S (2009) Assessing the environmental impacts of freshwater consumption in LCA. Environ Sci Technol 43(11):4098–4104CrossRefGoogle Scholar
  30. Pfister S, Hellweg S (2011) Surface water use – human health impacts. Report of the LC-IMPACT project (EC: FP7) (p. http://www.ifu.ethz.ch/ESD/downloads/Uncertainty_w). Retrieved from http://www.ifu.ethz.ch/ESD/downloads/Uncertainty_water_LCIA.pdf
  31. Ridoutt BG, Pfister S (2010) A revised approach to water footprinting to make transparent the impacts of consumption and production on global freshwater scarcity. Glob Environ Chang 20(1):113–120CrossRefGoogle Scholar
  32. Ridoutt BG, Pfister S (2013) A new water footprint calculation method integrating consumptive and degradative water use into a single stand-alone weighted indicator. Int J Life Cycle Assess 18:204–207CrossRefGoogle Scholar
  33. Rodell M et al (2004) The global land data assimilation system. Bull Am Meteorol Soc 85(3):381–394CrossRefGoogle Scholar
  34. Rosenbaum R et al (2008) USEtox—the UNEP-SETAC toxicity model: recommended characterisation factors for human toxicity and freshwater ecotoxicity in life cycle impact assessment. Int J Life Cycle Assess 13(7):532–546CrossRefGoogle Scholar
  35. Shiklomanov IA, Rodda JC (2003) World water resources at the beginning of the 21st century. Cambridge University Press, Cambridge, UKGoogle Scholar
  36. UNEP Global Environment Monitoring System (GEMS) Water programme (2009) GEMStatGoogle Scholar
  37. Vorosmarty CJ et al (2000) Global water resources: vulnerability from climate change and population growth. Science 289(5477):284–288CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Anne-Marie Boulay
    • 1
  • Masaharu Motoshita
    • 2
    • 5
  • Stephan Pfister
    • 3
  • Cécile Bulle
    • 1
  • Ivan Muñoz
    • 4
  • Helen Franceschini
    • 4
  • Manuele Margni
    • 1
  1. 1.CIRAIG, Ecole Polytechnique of MontrealMontrealCanada
  2. 2.National Institute of Advanced Industrial Science and TechnologyTsukubaJapan
  3. 3.Institute for Environmental Engineering, ETH ZurichZurichSwitzerland
  4. 4.Safety and Environmental Assurance Centre, UnileverColworthUK
  5. 5.Department of Environmental TechnologyTechnical University of BerlinBerlinGermany

Personalised recommendations