Climate metrics and the carbon footprint of livestock products: where’s the beef?
Open accessAbstract
The livestock sector is estimated to account for 15% of global greenhouse gas (GHG) emissions, 80% of which originate from ruminant animal systems due to high emissions of methane (CH 4 ) from enteric fermentation and manure management. However, recent analyses have argued that the carbon footprint (CF) of ruminant meat and dairy products are substantially reduced if one adopts alternative metrics for comparing emissions of GHGs—e.g., the 100 year global temperature change potential (GTP 100 ), instead of the commonly used 100 year global warming potential (GWP 100 )—due to a lower valuation of CH 4 emissions. This raises the question of which metric to use. Ideally, the choice of metric should be related to a climate policy goal. Here, we argue that basing current GHG metrics solely on temperature impact 100 years into the future is inconsistent with the current global climate goal of limiting warming to 2 °C, a limit that is likely to be reached well within 100 years. A reasonable GTP value for CH 4 , accounting for current projections for when 2 °C warming will be reached, is about 18, leading to a current CF of 19 kg CO 2 -eq. per kilo beef (carcass weight, average European system), 20% lower than if evaluated using GWP 100 . Further, we show that an application of the GTP metric consistent with a 2 °C climate limit leads to the valuation of CH 4 increasing rapidly over time as the temperature ceiling is approached. This means that the CF for beef would rise by around 2.5% per year in the coming decades, surpassing the GWP based footprint in only ten years. Consequently, the impact on the livestock sector of substituting GTPs for GWPs would be modest in the near term, but could potentially be very large in the future due to a much higher (>50%) and rapidly appreciating CF.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Equal CO2-eq for different GHGs implies equal integrated radiative forcing of one emission pulse over a certain timeframe, but says little about the contribution of the emission pulse to radiative forcing and temperature change at a certain point in time.
“Equal CO2-eq for different GHGs implies equal integrated radiative forcing of one emission pulse over a certain timeframe, but it says little about the contribution of the emission pulse of a gas to radiative forcing - and temperature change - at a certain point in time17,18.”
From Risk to rely on soil carbon sequestration to offset global ruminant emissions (2023) · cites this paper as [17]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredCH4 has a much higher impact on radiative forcing than CO2 and a much shorter perturbation lifetime.
“Comparing the impact behaviors of the same amount of CH4 and CO2, for example, CH4 has a much higher impact on radiative forcing than CO2 (i.e., approximate 120 times higher in the first year after the emission) and a much shorter perturbation lifetime (11.8 years for CH4 and millennia for CO2)17,23.”
From Risk to rely on soil carbon sequestration to offset global ruminant emissions (2023) · cites this paper as [17]
The Background–GHG metrics section says that methane is much shorter-lived than CO2 and compares the radiative forcing of equal-mass emissions, supporting the qualitative claim. Our copy does not give the citing sentence’s specific figures of approximately 120 times greater forcing in the first year or lifetimes of 11.8 years and millennia. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 35
- Garnett T 2013 Food sustainability: problems, perspectives and solutions Proc. Nutrition Soc. 72 29-39 · DOI
- Myhre G et al 2013 Anthropogenic and natural radiative forcing Climate change 2013: The Physical Science Basis. Contribution of Working Group 1st to the 5th Assessment Report of the Intergovernmental Panel on Climate Change ed T F Stocker et al (Cambridge, UK & New York: Cambridge University Press) pp 658-740
- Reisinger A et al 2013 Implications of alternative metrics for global mitigation costs and greenhouse gas emissions from agriculture Clim. Change 117 677-90 · DOI
- Reisinger A and Ledgard S 2013 Impact of greenhouse gas metrics on the quantification of agricultural emissions and farm-scale mitigation strategies: a New Zealand case study Environ. Res. Lett. 8 025019 · DOI
- Picasso V D et al 2014 Sustainability of meat production beyond carbon footprint: a synthesis of case studies from grazing systems in Uruguay Meat Sci. 98 346-54 · DOI · Paper page
- Tol R S et al 2012 A unifying framework for metrics for aggregating the climate effect of different emissions Environ. Res. Lett. 7 044006 · DOI
- Houghton J T, Jenkins G J and Ephraums J J (ed) 1990 Climate Change: The IPCC Scientific Assessment (Cambridge: Cam- bridge University Press)
- Shine K P 2009 The global warming potential-the need for an interdisciplinary retrial Clim. Change 96 467-72 · DOI
- Peters G P et al 2011 The integrated global temperature change potential (iGTP) and relationships between emission metrics Environ. Res. Lett. 6 044021 · DOI
- Geoffroy O et al 2013 Transient climate response in a two-layer energy-balance model: I. Analytical solution and parameter calibration using CMIP5 AOGCM experiments J. Clim. 26 1841-57 · DOI · Paper page
- Tanaka K et al 2013 Emission metrics under the 2 °C climate stabilization target Clim. Change 117 933-41 · DOI
- Reisinger A, Meinshausen M and Manning M 2011 Future changes in global warming potentials under representative concentration pathways Environ. Res. Lett. 6 024020 · DOI
- Tanaka K, Peters G P and Fuglestvedt J S 2010 Policy update: multicomponent climate policy: Why do emission metrics matter? Carbon Manage. 1 191-7 · DOI
- Manne A S and Richels R G 2001 An alternative approach to establishing trade-offs among greenhouse gases Nature 410 675-7 · DOI
- Shine K P et al 2007 Comparing the climate effect of emissions of short-and long-lived climate agents Phil. Trans. R. Soc. A 365 1903-14 · DOI
- Ekholm T, Lindroos T J and Savolainen I 2013 Robustness of climate metrics under climate policy ambiguity Environ. Sci. Policy 31 44-52 · DOI
- Johansson D J, Persson U M and Azar C 2006 The cost of using global warming potentials: analysing the trade off between CO 2 , CH 4 and N 2 O Clim. Change 77 291-309 · DOI
- Johansson D A 2012 Economics-and physical-based metrics for comparing greenhouse gases Clim. Change 110 123-41 · DOI
- Azar C and Johansson D J 2012 On the relationship between metrics to compare greenhouse gases-the case of IGTP, GWP and SGTP Earth Syst. Dyn. Discuss. 3 113-41 · DOI
- Joshi M et al 2011 Projections of when temperature change will exceed 2 °C above pre-industrial levels Nat. Clim. Change 1 407-12 · DOI
- Azar C, Johansson D J and Mattsson N 2013 Meeting global temperature targets-the role of bioenergy with carbon capture and storage Environ. Res. Lett. 8 034004 · DOI
- Clarke L and Jiang K 2014 Assessing Transformation Pathways Climate Change 2013: Mitigation of Climate Change Contribu- tion of Working Group 3rd to the 5th Assessment Report of the Intergovernmental Panel on Climate Change ed O Edenhofer et al (Cambridge, UK & New York: Cambridge University Press) pp 658-740
- Rogelj J et al 2013 Probabilistic cost estimates for climate change mitigation Nature 493 79-83 · DOI · Paper page
- Johansson D J, Persson U M and Azar C 2008 Uncertainty and learning: implications for the trade-off between short-lived and long-lived greenhouse gases Clim. Change 88 293-308 · DOI
- Lesschen J et al 2011 Greenhouse gas emission profiles of European livestock sectors Animal Feed Sci. Technol. 166 16-28 · DOI
- Weiss F and Leip A 2012 Greenhouse gas emissions from the EU livestock sector: a life cycle assessment carried out with the CAPRI model Agric. Ecosystems Environ. 149 124-34 · DOI
- Wirsenius S, Azar C and Berndes G 2010 How much land is needed for global food production under scenarios of dietary changes and livestock productivity increases in 2030? Agric. Syst. 103 621-38 · DOI · Paper page
- Bajželj B et al 2014 Importance of food-demand management for climate mitigation Nat. Clim. Change 4 924-9 · DOI
- Hedenus F, Wirsenius S and Johansson D J 2014 The importance of reduced meat and dairy consumption for meeting stringent climate change targets Clim. Change 124 79-91 · DOI
- Cieslak A et al 2013 Plant components with specific activities against rumen methanogens Animal 7 253-65 · DOI
- Petersen S O et al 2013 Manure management for greenhouse gas mitigation Animal 7 266-82 · DOI
- Wirsenius S, Hedenus F and Mohlin K 2011 Greenhouse gas taxes on animal food products: rationale, tax scheme and climate mitigation effects Clim. Change 108 159-84 · DOI
- Cederberg C et al 2013 Trends in greenhouse gas emissions from consumption and production of animal food products- implications for long-term climate targets Animal 7 330-40 · DOI
- Smith P et al 2014 Agriculture, forestry and other land use (AFOLU) Climate Change 2014: Mitigation of Climate Change Working Group 3rd Contribution to the IPCC 5th Assessment Report ed O Edenhofer et al (Cambridge, UK and New York: Cambridge University Press)
- Strefler J et al 2014 Economic impacts of alternative green- house gas emission metrics: a model-based assessment Clim. Change 125 319-31 · DOI
Cited by
Sorted by citations
Risk to rely on soil carbon sequestration to offset global ruminant emissions
Wang, Y., de Boer, I. J. M., Persson, U. M., Ripoll-Bosch, R., Cederberg, C., Gerber, P. J., Smith, P., & van Middelaar, C. E. (2023) · Nature Communications · doi:10.1038/s41467-023-43452-3 · Cited by 39 · see citing works
Self-citation
- Authors
- Persson, U. M., Johansson, D. J. A., Cederberg, C., Hedenus, F., & Bryngelsson, D.
- Affiliations
- Chalmers University of Technology (SE)
- Corresponding author
- Persson, U Martin
- Venue
- Environmental Research Letters
- Publisher
- IOP Publishing
- Published
- 2015-03-01
- Volume
- 10
- Issue
- 3
- Pages
- 034005
- ISSN
- 1748-9326 (ISSN-L)
- OpenAlex
- W2086482153
- Cited by
- 47
- References
- 0
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 4 · 2023: 2 · 2022: 3 · 2021: 8 · 2020: 2 · 2019: 8 · 2018: 6 · 2017: 6 · 2016: 1 · 2015: 1
- FWCI
- 4.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Environmental Research Letters (publishedVersion, cc-by)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- NordForsk
- Adlerbertska Stiftelserna
- E.ON Sweden
- Energimyndigheten
- Topics
- Physical Sciences › Environmental Science › Ecology › Agriculture Sustainability and Environmental Impact
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
- Keywords
- carbon footprint, climate metrics, global warming potential, global temperature change potential, methane emissions, ruminant livestock, beef, dairy products, 2 °C warming limit, enteric fermentation, manure management, climate policy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review