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Abstract
Life Cycle Assessments are cradle-to-grave systems studies that are created from a variety of inputs that include the process of defining the study goals, scope and boundaries, data input sources and quality requirements, methodologies and assumptions, and allocation methods and cut off points. All these inputs have degrees of uncertainty related to them.
Traditional life cycle modeling uses process flow level data obtained from life cycle databases that produce global and regional level general averaged input data parameters. It is also acceptable to use primary data as inputs for modeling. The type of data and the methodology used to complete the LCA study should agree with the goal and scope as determined during the initial phase of the study. This study hypothesized that custom modeled unit flow level data that reflected process flow inputs at a sub-process production level from a textile manufacturing operation would decrease the inherent uncertainty in an LCA model by at least 50%. The study also considered the effect of variations in the scope, boundaries, and functional unit definitions on the LCA outputs.
The study found that uncertainty varied only an average of 10% between a base level and a unit flow level LCA model when evaluated using uncertainty analysis techniques. However, temporal, geographical, and technological data quality scores improved by approximately 50% when evaluated with a pedigree matrix.
The most significant variations in the end point impact values occurred in the categories of Water Impact, Damage to Ecosystems and Damage to Human Health. Increase water consumption was the impact that was associated most closely with the changes in water usage in the production phase. The methodological variations that had notable impacts on the outcomes of the LCA models included the application of cut off points at the production gate, modification of the functional unit to meet Product Category Rule criteria, and changes to system boundaries that allowed for allocation of additional impacts associated with fiber recycling.
The study concluded that it is important that the LCA commissioner determine the purpose of an LCA at the onset of a study. This will dictate the methodologies that will be followed and data sets that will be selected for use by the LCA practitioner. Traditional LCA datasets provide sufficient information for LCA models to provide generalized information; however, if the LCA commissioner wishes to have actionable outcome information, site specific unit flow level inputs are needed.
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