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Parameterization in Life Cycle Assessment inventory data: review of current use and the representation of uncertainty

  • Uncertainties in LCA
  • Published:
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Abstract

Purpose

Parameterization refers to the practice of presenting Life Cycle Assessment (LCA) data using raw data and formulas instead of computed numbers in unit process datasets within databases. This paper reviews parameterization methods in the European Reference Life Cycle Data System (ELCD), ecoinvent v3, and the US Department of Agriculture's Digital Commons with the intent of providing a basis for continued methodological and coding advances.

Methods

Parameterized data are reviewed and categorized with respect to the type (raw data and formulas) and what is being represented (e.g., consumption and emission rates and factors, physical or thermodynamic properties, process efficiencies, etc.). Parameterization of engineering relationships and uncertainty distributions using Smirnov transforms (a.k.a. inverse transform sampling), and ensuring uncertain individual fractions (e.g., market shares) sum to the total value of interest are presented.

Results

Seventeen categories of parameters (raw data and formulas) are identified. Thirteen ELCD unit process datasets use 975 parameters in 12 categories, with 124 as raw data points and 851 as formulas, and emission factors as the most common category of parameter. Five additional parameter categories are identified in the Digital Commons for the presentation and analysis of data with uncertainty information, through 146 parameters, of which 53 represent raw data and 93 are formulas with most being uncertainty parameters, percentages, and consumption parameters.

Conclusions

Parameterization is a powerful way to ensure transparency, usability, and transferability of LCI data. Its use is expected to increase in frequency, the categories of parameters used, and the types of computational methods employed.

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Notes

  1. Available at http://lca.jrc.ec.europa.eu/lcainfohub/datasetArea.vm.

  2. Available at http://www.ecoinvent.ch/.

  3. From http://www.ecoinvent.org/ecoinvent-v3/ecospold-v2/.

  4. See http://www.lcacommons.gov/.

  5. See http://lca.jrc.ec.europa.eu/lcainfohub/datasetArea.vm.

  6. Based on personal communication with Michael Srocka of Green Delta TC (http://greendeltatc.com/index.html) on June 10, 2011.

  7. Data are available at http://www.ers.usda.gov/Data/ARMS/.

  8. Personal communication, March 16, 2011.

  9. Specifically, for a continuous variable x with a cumulative distribution function of F(x), the random variable y = F(x) has a uniform distribution on [0, 1]. Thus, by passing random numbers on the unit interval through the quantile, a sample of a random variable governed by the cumulative distribution function is obtained.

  10. Note that ILCD supports the random() function for the generation of a uniform distribution on [0,1] which could be used instead of explicitly specifying the uniform distribution. However, it is not clear if EcoSpold v2 will also support random() and, either way, it must be ensured that the distribution is consistently applied within each estimation of z p .

  11. These data are available at http://www.ers.usda.gov/Data/FertilizerUse/, and note that geographic specificity is national, thus a larger area than is intended to be represented by the Washington State unit process data, and thus having lower data quality for geographic representativeness.

  12. These data are available in Section 9 of 22 (9e—Nitrogen Fertilizer Guide) at http://www.nm.nrcs.usda.gov/technical/handbooks/iwm/NM_IWM_Field_Manual/Section09/9e-Nitrogen_Fertilizer_Guide.pdf and assuming “nitrogen solutions” can be represented as “mixtures of urea and ammonium nitrate in aqueous or ammoniacal solution” (URAN) as inferred from the Harmonized Tariff Schedule code at http://www.ers.usda.gov/Data/FertilizerTrade/documentation.htm.

  13. See http://www.openlca.org/documentation/index.php/Advanced_functions.

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Acknowledgments

This research was funded by the United States Department of Agriculture National Agricultural Library (agreement number 58-8201-0-149).

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Authors and Affiliations

  1. Design for Environment Laboratory, University of Washington, Box 352700, Seattle, WA, 98195-2600, USA

    Joyce Smith Cooper, Michael Noon & Ezra Kahn

Authors
  1. Joyce Smith Cooper
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  2. Michael Noon
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  3. Ezra Kahn
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Correspondence to Joyce Smith Cooper.

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Responsible editor: Berlan Rodriguez Perez

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Cooper, J.S., Noon, M. & Kahn, E. Parameterization in Life Cycle Assessment inventory data: review of current use and the representation of uncertainty. Int J Life Cycle Assess 17, 689–695 (2012). https://doi.org/10.1007/s11367-012-0411-1

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  • DOI: https://doi.org/10.1007/s11367-012-0411-1

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