Background, aim, and scopeA new trend driven by climate change concerns is the interest to label consumer products with a carbon footprint (CF) number. Here, we present a study that examines the uncertainty in the estimated CFs of a liquid and a compact powder detergent and how the uncertainty varies with the type of comparison one wishes to make.Materials and methodsA simplified CF model for detergents, encompassing all life cycle stages, has been used for the calculation of CFs. The CFs for the two detergents were compared under three different cases: (1) a situation where most of life cycle assessment (LCA) system is similar, (2) a situation where the LCA background systems may be different but certain choices with regard to system boundaries are standardized, and (3) a situation where the LCA background system, choices of system boundaries, and foreground system may also be different. Uncertainty in the CFs was calculated for each of the three comparison situations using a stepwise sensitivity/uncertainty analysis approach.ResultsThe stepwise approach makes it possible to obtain reliable uncertainty estimates without the need to have very good uncertainty descriptions for every input parameter. Only a few input parameters were found to drive the uncertainty of the CF values. For case 1, the uncertainties in the difference between the CF of the ultraliquid and compact powder products are very small. The CF of compact powder is always larger than that of the ultraliquid product. In case 3, the uncertainties become much larger, such that in 23% of the cases, a CF comparison would wrongly indicate that the compact powder product has a lower CF than the ultraliquid product. Case 2 falls between the extremes of cases 1 and 3.DiscussionOne of the challenges of developing user-friendly CF methods based on the ISO 14040 framework is to ensure a high level of comparability of CF values, such that misleading or oversimplified conclusions can be avoided. Our analysis shows how the uncertainty margins around the calculation of a CF for a set of given products will broaden as the assessment moves from an “internal” comparison to a comparison with data from third parties where there is no specific information how these data have been obtained. CF calculations based on internal comparisons can lead to very clear distinctions between products and illustrate the utility of a CF tool to optimize the environmental performance of products using difference analysis.ConclusionsCF calculations for products can only provide a fair comparison if the LCA background system used for the two products is the same and exactly the same choices in the foreground system are made. In practice, this would require consultation and agreement on specific product category rules.Recommendations and outlookSimplification is needed for a wider adoption of uncertainty analysis in CF and LCA. This article introduces some first steps towards such simplification, but more work is needed both on the theoretical and practical aspects of simplified uncertainty analyses.
[1]
Hans-Jürgen Dr. Klüppel,et al.
The Revision of ISO Standards 14040-3 - ISO 14040: Environmental management Life cycle assessment Principles and framework - ISO 14044: Environmental management Life cycle assessment Requirements and guidelines
,
2005
.
[2]
G. Psacharopoulos.
Overview and methodology
,
1991
.
[3]
Reinout Heijungs,et al.
Calculating the influence of alternative allocation scenarios in fossil fuel chains
,
2007
.
[4]
Stefano Tarantola,et al.
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
,
2004
.
[5]
A. Saltelli,et al.
Sensitivity Anaysis as an Ingredient of Modeling
,
2000
.
[6]
Erwan Saouter,et al.
A database for the life-cycle assessment of procter & gamble laundry detergents
,
2002
.
[7]
Reinout Heijungs,et al.
A review of approaches to treat uncertainty in LCA
,
2004
.
[8]
J. Houghton,et al.
Climate change 2001 : the scientific basis
,
2001
.
[9]
H. S. Matthews,et al.
The importance of carbon footprint estimation boundaries.
,
2008,
Environmental science & technology.
[10]
Stefano Tarantola,et al.
Sensitivity Analysis in Practice
,
2002
.
[11]
J. Bongaarts,et al.
Global Environment Outlook
,
1998
.
[12]
Matthias Fawer,et al.
Life cycle inventories for the production of detergent ingredients
,
1999
.
[13]
Rana Pant,et al.
Standardisation efforts to measure greenhouse gases and ‘carbon footprinting’ for products
,
2008
.
[14]
B Efron,et al.
Statistical Data Analysis in the Computer Age
,
1991,
Science.
[15]
M. Huijbregts,et al.
Evaluating uncertainty in environmental life-cycle assessment. A case study comparing two insulation options for a Dutch one-family dwelling.
,
2003,
Environmental science & technology.
[16]
Robert Ries,et al.
Characterizing, Propagating, and Analyzing Uncertainty in Life‐Cycle Assessment: A Survey of Quantitative Approaches
,
2007
.
[17]
Stefano Tarantola,et al.
Sensitivity Analysis as an Ingredient of Modeling
,
2000
.
[18]
M. Franke,et al.
Okobilanzierung — Sachbilanz für die Waschmittel-Konfektionierung/ Life-Cycle-Assessment — Life-Cycle Inventory for Detergent Manufacturing
,
1995
.
[19]
Janet Ann ranganathan,et al.
Greenhouse Gas Protocol
,
2004
.
[20]
Eric Johnson,et al.
Disagreement over carbon footprints : A comparison of electric and LPG forklifts
,
2008
.
[21]
J. Konz,et al.
Exposure factors handbook
,
1989
.