LCA results can have high uncertainties because
of the large amounts of measured and simulated
data and the simplified modeling of complex en-
vironmental cause-effect chains. Recent studies
have highlighted the contribution that system as-
sumptions and value choices can also make to
overall uncertainty (36, 37). A number of quantita-
tive uncertainty assessments are available (38) butare rarely used in practice. One of the key questions
is, how much uncertainty is acceptable, depending
on the application? In some cases, rough estimates
of input values can be enough to identify supply-
chain hotspots (39), but for other applications,
such as product comparisons (37), the demands
for more accurate values are higher. For some im-
pact categories such as toxicity, very large differ-
ences in inventory results are needed to statistically
differentiate product systems, whereas for other
categories, differences of a factor of two or less
may be enough (40). LCA practitioners should al-
ways attempt to manage the decision-maker’s
expectations and clarify that LCA is not always a
tool to provide a single answer, but rather one
that permits comprehensive understanding of a
problem and its possible solutions.
LCA results can have high uncertainties because of the large amounts of measured and simulated data and the simplified modeling of complex en- vironmental cause-effect chains. Recent studies have highlighted the contribution that system as- sumptions and value choices can also make to overall uncertainty (36, 37). A number of quantita- tive uncertainty assessments are available (38) butare rarely used in practice. One of the key questions is, how much uncertainty is acceptable, depending on the application? In some cases, rough estimates of input values can be enough to identify supply- chain hotspots (39), but for other applications, such as product comparisons (37), the demands for more accurate values are higher. For some im- pact categories such as toxicity, very large differ- ences in inventory results are needed to statistically differentiate product systems, whereas for other categories, differences of a factor of two or less may be enough (40). LCA practitioners should al- ways attempt to manage the decision-maker’s expectations and clarify that LCA is not always a tool to provide a single answer, but rather one that permits comprehensive understanding of a problem and its possible solutions.
Linking to my comment replying to the exact same comment you made elsewhere. This is really funny.
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