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line running so the facility level data already re fl ected just that line, not a line average.

Table 3 Relative paper facility fl ow amounts from IPSA procedure as % of facility level mass allocation.

Albany

Box Elder

5. Discussion and conclusions

Inputs Pulp

86% 86% 86% 86% 89% 94% 93% 86% 39% 84% 61% 86% 87% 68% 86% 86%

102% 102% 100% 100% 100% 102% 102% 102% 102% 102% 102% 102% 102% 102% 102% 102%

LCA studies can vary in quality due to data, methodologies, allocations, assumptions, modeling choices, etc. (Bousquin et al., 2012; Subramanian et al., 2011). Extra care is needed to use the best data and methodologies possible so that sustainability goals and strategies are based on robust science. This study used innovative and technically strong approaches to fortifying data (pulp, manufacturing, electricity), allocation (IPSA), and modeling (openLCA, WARM). The iterative nature of the LCA resulted in a recognition of the need to improve the quality of pulp and elec- tricity LCI, making the results for these important contributors more accurate. Pulp production LCI speci fi c to the most important pulp sources for Bounty production were developed, providing results that appear to differ signi fi cantly from use of average US pulp data. New electricity LCI data were developed, which better re fl ects the technologies currently in use in the US. This is important in the paper towel life cycle, particularly for facilities that draw from a regional electricity grid with a much different mix than the national average. The data allocation at the complex, multi-line manufacturing facility is superior to previous methods of simple mass or economic allocation, since actual line metrics were utilized in the new IPSA methodology to avoid arbitrary allocation. This is particularly important in providing line-level inventory and distinguishing many lines of varying performance at a facility. Additional functionality was added to openLCA software that provided a more straightforward and consistent means of performing sensitivity analysis for LCA that will be of

Chemicals (average)

Fuels (average)

Water

Electricity

Outputs PM 10

PM 2.5

SO 2 NO X VOC

Lead NH 3

CO 2

Wastewater Water loss

Tables 4 and 5 show the results of the sensitivity analyses for Albany and Box Elder, respectively, for the impact categories of most signi fi cance. For Albany, the IPSA procedure had a signi fi cant impact on results, since the line showed different performance than other lines in that facility when compared to the facility-level mass allocation. Having accurate numbers for forest yield and supply chain speci fi c pulp data would also in fl uence results for that facility. Results for Box Elder were similar, except the IPSA method was not as signi fi cant; this is due to only having the one

Table 4 Relative changes to full life cycle impact indicator results for Albany from the sensitivity analyses of allocation method, distribution distance, pulp, electricity, forest yield and water used in forestry.

Scenario

Fossil fuel depletion Climate change Ag. land occupation Particulate matter Energy demand Water consumption

67%

High forest yield Low forest yield

100% 100%

133%

High water loss for pulp Low water loss for pulp National average pulp vs

NA NA

NA NA NA

NA NA

99%

101%

166%

84%

113%

160%

supply chain speci fi c data

76%

National average electricity vs regional

98%

103% 120% 104%

100% 116% 100% 100%

99%

114% 104%

114% 102%

115% 104%

115% 100% 100%

Mass allocation vs IPSA Long distribution distance Short distribution distance Alternate material for WARM

98%

98% 82%

99%

98%

100%

Note: Bolded values indicate sensitivities of 10% or higher.

Table 5 Relative changes to full life cycle results for Box Elder from sensitivity analysis of allocation method, distribution distance, pulp, electricity, forest yield and water used in forestry.

Scenario

Fossil fuel depletion Climate change Ag. land occupation Particulate matter Energy demand Water consumption

67%

High forest yield Low forest yield

100% 100%

133%

High water loss for pulp Low water loss for pulp National average pulp vs

NA NA

NA NA NA

NA NA

92%

104%

211%

85%

127%

201%

supply chain speci fi c data

125% 100% 106%

111%

36% 99%

National average electricity vs regional

105%

100%

107%

Mass allocation vs IPSA Long distribution distance Short distribution distance Alternate material for WARM

99%

98%

99%

107%

100% 100%

103%

107%

100% 100%

96%

97% 80%

99%

97%

100%

Note: Bolded values indicate sensitivities of 10% or higher.

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