it is not compelling, because the LCA references explicitly say that they cannot be combined with other LCA studies. poore-nemecek ignores this guidance and draws hyperbolic conclusions.
This is the FUD I was referring to. I’ve asked you before to point to even a single paper responding to this extremely high-profile meta-analysis with something even resembling this vague concern; you haven’t been able to turn one up. This should be trivial, because an LCA is an ISO standard, and thus failure to comply with it would be unambiguous for the hundreds if not thousands of scientists familiar with LCAs who have surely read and even cited this paper. I’ve even pointed out that the animal agriculture industry would be champing at the bit to refute a paper like this and has millions of dollars and teams of scientists to throw at the problem. But you can’t, because one doesn’t exist.
Your entire argument boils down to “Um, actually, meta-analyses are bad science”, which is completely hilarious. Hell, assuming Poore & Nemecek, the peer reviewers, and the entire scientific community ignored this alleged basic oversight, I’ve pointed out to you multiple times that you yourself could author a paper rebutting this and get it published if what you’re saying is even remotely credible. But it isn’t. Because you have no idea what you’re talking about regarding this paper except to the extent that you’re lying.
Edit: I’ve asked you this before: please, learn how to edit your comments so you don’t have to respond to this one with three separate comments.
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.
I’ve asked you before to point to even a single paper responding to this extremely high-profile meta-analysis with something even resembling this vague concern;
So what I’m hearing here is that despite this being an ISO standard, thereby rendering this trivially obvious even to someone with zero background in this field:
Poore & Nemecek saw and see no issue with it.
The peer reviewers for one of the world’s top academic journals see no issue with it.
None of the 100+ authors of the 40 papers cited see any issue with it.
Having read this, none of the hundreds upon hundreds of environmental scientists for whom this is their life’s work and who are orders of magnitude more informed on this than you or I see no issue with it.
The animal agriculture industry – which again, absolutely has the means and the overwhelming financial motive to refute this – sees no issue with it.
I’m sorry for “appealing to authority” when all you have to offer is the same flimsy, nonsensical vagary over and over again. If you’ll recall, I even asked you last time to point to one of the references calling what Poore & Nemecek did here unjustified, and you refused, likely because you’ve never actually read a single one of the 40 referenced papers in your life.
it is not compelling, because the LCA references explicitly say that they cannot be combined with other LCA studies. poore-nemecek ignores this guidance and draws hyperbolic conclusions.
This is the FUD I was referring to. I’ve asked you before to point to even a single paper responding to this extremely high-profile meta-analysis with something even resembling this vague concern; you haven’t been able to turn one up. This should be trivial, because an LCA is an ISO standard, and thus failure to comply with it would be unambiguous for the hundreds if not thousands of scientists familiar with LCAs who have surely read and even cited this paper. I’ve even pointed out that the animal agriculture industry would be champing at the bit to refute a paper like this and has millions of dollars and teams of scientists to throw at the problem. But you can’t, because one doesn’t exist.
Your entire argument boils down to “Um, actually, meta-analyses are bad science”, which is completely hilarious. Hell, assuming Poore & Nemecek, the peer reviewers, and the entire scientific community ignored this alleged basic oversight, I’ve pointed out to you multiple times that you yourself could author a paper rebutting this and get it published if what you’re saying is even remotely credible. But it isn’t. Because you have no idea what you’re talking about regarding this paper except to the extent that you’re lying.
Edit: I’ve asked you this before: please, learn how to edit your comments so you don’t have to respond to this one with three separate comments.
calling me a liar and appealing to authority doesn’t change the truth of what I’m saying.
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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the references themselves say this explicitly.
So what I’m hearing here is that despite this being an ISO standard, thereby rendering this trivially obvious even to someone with zero background in this field:
I’m sorry for “appealing to authority” when all you have to offer is the same flimsy, nonsensical vagary over and over again. If you’ll recall, I even asked you last time to point to one of the references calling what Poore & Nemecek did here unjustified, and you refused, likely because you’ve never actually read a single one of the 40 referenced papers in your life.
your characterization of my expertise is bare ad hominem. what I’m saying is true or false regardless of your opinion of me and my expertise.