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indicators at the inventory analysis, midpoint, and endpoint are chosen along with normalization factors when available. Indicators from TRACI 2.1 (Bare, 2012) and ReCiPe 1.08 (Goedkoop et al., 2012) were chosen to represent potential environmental and human health effects at the midpoint level. TRACI models for these impacts are based on US conditions, where the majority of life cycle activ- ities occur. ReCiPe was used to provide endpoint indicators for the same and additional impact categories and provide external normalization using global normalization factors (Sleeswijk et al., 2008; Van Hoof et al., 2013). Normalization is an optional approach in the ISO 14044 standards (ISO, 2006) that can be used to view indicator scores in respect to a comparable reference point to aid in interpretation. P & G uses this approach to prioritize impact indicators without using additional subjective weighting values; this interpretation implicitly implies an equal weighting value for all impact categories in the study. As a global consumer products company serving consumers with the variety of perspectives on which environmental issues are most critical, this approach is used as a way to narrow the indicators that are considered for further analysis, but not used as a reason for suggesting that other in- dicators are not important (Van Hoof et al., 2013). Where midpoint factors for resource depletion are not well developed in TRACI, methods were adopted from ReCiPe as well. The ReCiPe method- ology is used in application to other P & G products and provides consistency across applications of LCA to different P & G products. The use of similar impact indicators from multiple LCIA method- ologies provides a sensitivity check to help understand how results might differ across impact methods. Neither TRACI nor ReCiPe include indicators of energy use or solid waste generation. The Swiss Center for Life Cycle Inventories method for non-renewable energy demand was used (Frischknecht et al., 2007). To track wa- ter consumption, all evaporative losses as de fi ned by the Water Footprint Network as blue water were tracked and aggregated by volume (WFN, 2009). Human health and ecotoxicity indicators were not used in this study due to lack of high quality data on toxics release to air and water across the entire life cycle, and due to manufacturing and consumer related releases that undergo detailed risk assessment, which is separate from LCA modeling.
to be identical to the existing pulp datasets to hold other factors constant. In the second scenario, the use of the new regionalized electricity LCI in the paper facility was replaced with the equivalent Ecoinvent 2.2 process for average US electricity at an industrial facility, which is ‘ electricity, medium voltage, at grid/US ’ . Additional scenarios were developed to understand the impor- tance of speci fi c data accuracy on results; we systematically altered one or more of the key data points. Following initial model runs, key data points with inherent uncertainty were identi fi ed of particular potential importance to model results. Primary data provided by papermaking facilities were of high quality in all as- pects (ISO, 2006). Data of lesser quality and therefore with less certainty included data representing forestry and pulp operations (e.g. forestry yield, water use), product distribution, and end-of-life. For these points, values were doubled or halved. Ten scenarios were developed and applied to each line for a total of 20 scenarios run in the sensitivity analysis. New functionality was developed in openLCA 1.4 in collaboration with GreenDelta in order to conduct the sensitivity analyses. Within an openLCA 1.4 “ Project, ” which is where different product systems can be compared, functionality to track variants of one or more systems were added. “ Variants ” were created with many variations of the baseline product system with a single change in one of the aforementioned key variables. Addi- tional “ variants ” were created that used different product systems (or models) where unique unit processes have been substituted in the process network. This approach was taken to model the alter- native facility allocation approach, and the scenarios with the substitution of the datasets, including the use of national average pulp and national average electricity datasets in place of the spe- ci fi c datasets used in the baseline case. The LCA results were then calculated simultaneously for each of these system variants.
2.2. Impact assessment
Impact categories were chosen based on known impacts of concern, ability to contextualize impacts, availability of data to accurately represent potential impacts, and appropriateness of available impact methodologies. The selected categories are pre- sented in Table 2 along with indicators to represent them. Impact
Table 2 Impact indicators used in this study, organized according to Bare and Gloria (2008). Impact categories names are those described in TRACI 2.1, except for categories which did not exist there, in which case names from ReCiPe or the other referenced methods are used.
Normalized? c
Area of protection
Impact category
Material fl ux Indicator units
Midpoint indicator units
Endpoint indicators, units b
a , kg PM
b
Human health effects Particulate matter
kg PM 2.5 eq
10 eq
DALY DALY DALY
Yes Yes Yes Yes Yes Yes Yes
kg CFC11-eq a,b
Ozone depletion Smog formation Global climate Ionizing radiation
a , kg NMVOC-eq b
kgO 3 -eq kg CO 2 -eq
a,b
DALY, species yr g
kgU 235 -eq b kg oil-eq b kg Fe-eq b
DALY
Natural resources
Fossil fuel depletion
$ $
Metal depletion
m 3d
Water consumption/depletion
No No
Cumulative energy demand, non-renewable MJ e
m 2 yr f
Agricultural land, m 2 yr b
Land occupation/transformation
Agricultural land, species yr
Yes Yes
Urban land, m 2 yr b
Urban land, species yr
Land transformation, m 2b
Land transformation, species yr Yes
kgN-eq a , kg P-eq b
species yr species yr species yr
Yes Yes Yes
Environmental quality Freshwater eutrophication
kgN-eq b kg SO 2 -eq
Marine eutrophication
a,b
Acidi fi cation
a TRACI 2.1 (Bare, 2012). b ReCiPe 1.08 with Hierarchist Perspective (Goedkoop et al., 2012). c Normalization factor used were for Endpoint normalization factors in world per person impact. d Water consumption is non-rainwater (bluewater) evaporative losses. e Frischknecht et al. (2007). f Total land occupation. g Global climate is normalized to both human health and environmental quality endpoints.
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