To clarify what this user is referring to, Poore & Nemecek 2018 is a recent, widely cited meta-analysis covering over 1530 studies assessing the environmental impacts of food. It’s published in one of the world’s top academic journals – Science – and authored by Dr. Joseph Poore, the director of the University of Oxford’s food sustainability program, and Dr. Tomas Nemecek, an expert on agroecology and life cycle assessments from the Zurich University of Applied Sciences.
They somehow constantly appear like a spectre whenever this study gets brought up to try to spread FUD about it through vague and unsubstantiated nonsense. They do this because it’s extremely compelling, effectively unambiguous evidence that many animal products such as dairy are abysmal for the climate (“because it’s devastating to my case!”). I highly encourage anyone interested to read it for themselves. The article is paywalled, but Dr. Poore hosts it for free through their personal website, so you don’t have to take either of our words for it.
Edit: the paper they quote (but conspicuously don’t link to) below to try to refute this methodology is itself a meta-analysis of 369 LCA studies in the same vein as Poore & Nemecek. I can’t; my sides are in orbit. Edit 2: For anyone wanting to read it in full, Lancaster University hosts Clune, Crossin & Verghese 2015 legally and for free as well, so again, you don’t have to take either of our words for it.
First, it is often cited that LCA results should not be compared (Desjardins et al., 2012; Foster et al., 2006; McAuliffe et al., 2016; Röös et al., 2013) due to variation in methodology choices, functional units, as well as temporal and regional differences2. Second, no single comprehensive review was identified that adequately covers the breadth of fresh foods available to consumers and caterers. As Helle et al. (2013, p.12643) state ‘data availability and quality remain primary obstacles in diet-level environmental impact assessment’, while Pulkkinen et al. (2015) calls for the creation of a database that communicates data quality, uncertainty and variability to reliably differentiate between the GWP of food types. Previous studies have compiled LCA data to compare different foods (e.g. Audsley et al., 2009; Berners-Lee et al., 2012; Bradbear and Friel, 2011; de Vries and de Boer, 2010; Foster et al., 2006; Nijdam et al., 2012; Sonesson et al., 2010; Roy et al., 2009). While these are useful attempts, the identified studies are inadequate in the coverage of fresh foods available. Environmental Product Declarations (EPDs) attempt to inform consumers of the environmental impacts (carbon, water and ecological footprint) of specific foods, however they also fall short in breadth of items covered at present. The most comprehensive attempt at carbon footprint labelling was performed by Tesco (2012), however failed to label key categories such as fresh fish, pork, lamb or beef before finishing in 2012 due to the scale of the labelling scheme and a lack of participation from other retailers (Head et al., 2013). Third, studies that do compare results may often present singular figures. Peters et al. (2010) and Röös et al. (2011) argue that a range of impacts should be reported from LCA’s to better represent the variety of environmental impacts, as opposed to a singular figure. Finally, there is a lack of synthesised open access LCA data in the public domain available to consumers to inform decision-making.
It’s exceptionally funny to me that you didn’t link to the study you’re quoting, because if you did, people would find out that you’re quoting a systematic review & meta-analysis of 369 LCA studies in the same vein as Poore & Nemecek 2018 did with 1530 LCA studies.
The ENTIRE POINT of the study you just quoted was that “there is a lack of synthesised open access LCA data in the public domain available to consumers to inform decision-making. Therefore this paper presents a systematic literature review and meta-analysis of food LCA studies in the last 15 years to assess the GWP of fresh food.” Thus, they appropriately synthesized the data using a meta-analysis. You’ve literally just disproven your own point. I hope you don’t actually believe that people reading this comment will fall for this.
I’m not trying to taunt you, rather I’m being completely serious: did you read the study you just linked beyond what you quoted?
they were honest enough to acknowledge that these studies varied so widely in methodology that combining them would be bad science, but went on to do it anyway. poore-nemecek doesn’t even acknowledge their faux pas.
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;
the references themselves say this explicitly.
