Many presentations during the conference touched on the importance and complexity of assessing uncertainty in LCA. On the second day of the conference, as a part of the ACLCA education committee’s work to expand understanding of uncertainty, Sinistore joined Laurie Wright, Lise Laurin, and Sangwon Suh for a presentation on “The Wild Wild West: Teaching Uncertainty in LCA.”
The session focused on how to explain the often-nebulous topic of uncertainty to students, practitioners, the public and clients, and stimulated debate on methods to teach and communicate the usefulness of uncertainty analysis as a part of LCA.
Wright led an activity called “The Mystery Box,” in which attendees broke into small groups and tried to diagram what the inside of a 3D-printed box with a small ball bearing in it looked like, based only on what they could feel by manipulating it. After each group sketched their ideas, the groups shared their ideas with each other to gain consensus on the internal geometry of the box. When the box was opened it revealed that each group had come close to mapping its internal structure, but no group was exactly right.
The activity perfectly illustrated some fundamentals of LCA. Processes and models are often treated as a “black box” in which there is some certainty about what goes in and what comes out, but often uncertainty about what happens inside the box. Also, different LCA practitioners will produce different results even if they start with the same information.
Suh’s presentation on published methods for quantifying and dealing with uncertainty highlighted the potential consequences of incorrect communication. He noted a headline about an incorrect claim by the Intergovernmental Panel on Climate Change (IPCC) that Himalayan glaciers could melt by 2035, which was rooted in an inconsistent treatment of uncertainty in calculation, as well as miscommunication of this uncertainty.
Sinistore followed with a description of the policy implications of uncertainty in the modeled GHG emissions from soils when calculating the total carbon impact of cellulosic ethanol. According to the Renewable Fuels Standard (RFS2), for a fuel to qualify as an advanced biofuel it must reduce GHG emissions by 60 percent when compared to a 2006 gasoline baseline. Where the feedstock is grown (i.e., the location’s soil properties and regional climate) determines the emissions from feedstock production and can be the deciding factor if the fuel passes or fails this emissions reduction test.
Laurin illustrated the power of uncertainty analysis in LCA to reduce the burdens of data collection. Her first example was to determine if the precision of transportation data has a substantive effect on the results of a product LCA. As she put it, “uncertainty is your friend!”
Even still, uncertainty is a concept that is difficult to grasp and may represent a key barrier to understanding and communicating LCAs effectively.
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