Carbon footprint and ammonia emissions of California beef production systems1
Abstract
Beef production is a recognized source of greenhouse gas (GHG) and ammonia (NH(3)) emissions; however, little information exists on the net emissions from beef production systems. A partial life cycle assessment (LCA) was conducted using the Integrated Farm System Model (IFSM) to estimate GHG and NH(3) emissions from representative beef production systems in California. The IFSM is a process-level farm model that simulates crop growth, feed production and use, animal growth, and the return of manure nutrients back to the land to predict the environmental impacts and economics of production systems. Ammonia emissions are determined by summing the emissions from animal housing facilities, manure storage, field applied manure, and direct deposits of manure on pasture and rangeland. All important sources and sinks of methane, nitrous oxide, and carbon dioxide are predicted from primary and secondary emission sources. Primary sources include enteric fermentation, manure, cropland used in feed production, and fuel combustion. Secondary emissions occur during the production of resources used on the farm, which include fuel, electricity, machinery, fertilizer, and purchased animals. The carbon footprint is the net exchange of all GHG in carbon dioxide equivalent (CO(2)e) units per kg of HCW produced. Simulated beef production systems included cow-calf, stocker, and feedlot phases for the traditional British beef breeds and calf ranch and feedlot phases for Holstein steers. An evaluat…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
GHG emissions (per kg CW) were within the range of those reported in other studies for the Northern Great Plains, Upper Midwest, and California within the U.S.
“Generally, GHG emissions (per kg CW) were within the range of those reported in other studies for the Northern Great Plains (Lupo et al., 2013), Upper Midwest (Pelletier et al., 2010), andCalifornia (Stackhouse-Lawson et al., 2012) within the U.S.”
From Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems (2018) · cites this paper as Stackhouse-Lawson et al., 2012
This overestimation has also been reported in other studies and reflects the uncertainty embedded in the use of IPCC methodology to represent a wide variety of diets and different management strategies in beef finishing systems.
“This overestimation has also been reported in other studies (Rowntree et al., 2016;Stackhouse-Lawson et al., 2012) and reflects the uncertainty embedded in the use of IPCC methodology to represent a wide variety of diets and different management strategies in beef finishing systems.”
From Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems (2018) · cites this paper as Stackhouse-Lawson et al., 2012
The cow-calf phase contributes the most to beef GHG emissions due to its year-round duration on lower quality forages, reproductive inefficiencies, and large cattle numbers.
“The cow-calf phase contributes the most due to its year-round duration on lower quality forages, reproductive inefficiencies, and large cattle numbers (Stackhouse-Lawson et al., 2012).”
From Impact of 10 years of adaptive multi-paddock grazing on soil carbon and beef's greenhouse gas footprint in the US Upper Midwest (2026) · cites this paper as Stackhouse-Lawson et al., 2012
We quantified uncertainties in farm-level GHG emissions following procedures previously used, applying ±20% uncertainty for enteric and manure-derived CH4, ±50% for N2O, and ±20% for non-animal direct GHGs, with overall uncertainty calculated as the square root of the sum of squares.
“We quantified uncertainties in farm-level GHG emissions following procedures previously used (Rotz et al., 2019;Stackhouse-Lawson et al., 2012), where uncertainty percentages were assigned to each source following IPCC (2006) based on expert opinion for their Tier 2 methodologies.We applied ±20% uncertainty for enteric and manurederived CH 4 , ±50% for N 2 O, and ± 20% for non-animal direct GHGs (”
From Impact of 10 years of adaptive multi-paddock grazing on soil carbon and beef's greenhouse gas footprint in the US Upper Midwest (2026) · cites this paper as Stackhouse-Lawson et al., 2012
Cites
Johnson, K. A., & Johnson, D. E. (1995) · Journal of Animal Science · doi:10.2527/1995.7382483x · Cited by 2,714 · see citing works
Beauchemin, K. A., Henry Janzen, H., Little, S. M., McAllister, T. A., & McGinn, S. M. (2010) · Agricultural Systems · doi:10.1016/j.agsy.2010.03.008 · Cited by 397 · see citing works
STEWART, A. A., LITTLE, S. M., OMINSKI, K. H., WITTENBERG, K. M., & JANZEN, H. H. (2009) · The Journal of Agricultural Science · doi:10.1017/s0021859609008764 · Cited by 42 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Comparing environmental impacts of beef production systems: a review of life cycle assessments
de Vries, M., van Middelaar, C. E., & de Boer, I. J. M. (2015) · Livestock Science · doi:10.1016/j.livsci.2015.06.020 · Cited by 276 · see citing works
Stanley, P. L., Rowntree, J. E., Beede, D. K., DeLonge, M. S., & Hamm, M. W. (2018) · Agricultural Systems · doi:10.1016/j.agsy.2018.02.003 · Cited by 266 · see citing works
“Generally, GHG emissions (per kg CW) were within the range of those reported in other studies for the Northern Great Plains (Lupo et al., 2013), Upper Midwest (Pelletier et al., 2010), and California (Stackhouse-Lawson et al., 2012) within the U.S. Compared to results of the grass-finishing model of Pelletier et al. (…”
BackgroundMethodResultInfluentialInvited Review: Methane Sources, Quantification, and Mitigation in Grazing Beef Systems
Thompson, L. R., & Rowntree, J. E. (2020) · Applied Animal Science · doi:10.15232/aas.2019-01951 · Cited by 112 · see citing works
Stewart, E. K., Beauchemin, K. A., Dai, X., MacAdam, J. W., Christensen, R. G., & Villalba, J. J. (2019) · Journal of Animal Science · doi:10.1093/jas/skz206 · Cited by 78 · see citing works
Garcia, L., Stanley, P. L., Sacramento, J. P., Dillon, J. A., Thorbecke, M., Thompson, L. R., Ambike, V., Sharma, P., Xu, S., Chiavegato, M. B., et al. (2026) · Agricultural Systems · doi:10.1016/j.agsy.2026.104879 · Cited by 1 · see citing works
- Authors
- Stackhouse-Lawson, K. R., Rotz, C. A., Oltjen, J. W., & Mitloehner, F. M.
- Affiliations
- University of California, Davis (US)
- Agricultural Research Service (US)
- Corresponding author
- Mitloehner, F. M.
- Venue
- Journal of Animal Science
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-12-01
- Volume
- 90
- Issue
- 12
- Pages
- 4641-4655
- ISSN
- 0021-8812 (ISSN-L)
- 1525-3163
- OpenAlex
- W2130626806
- Cited by
- 103
- References
- 3
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 6 · 2023: 14 · 2022: 6 · 2021: 10 · 2020: 11 · 2019: 7 · 2018: 10 · 2017: 6 · 2016: 5 · 2015: 6 · 2014: 9 · 2013: 4 · 2012: 1
- FWCI
- 5.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Animal Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Ecology › Agriculture Sustainability and Environmental Impact
- Physical Sciences › Environmental Science › Environmental Chemistry › Sustainable Agricultural Systems Analysis
- Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
- Keywords
- beef production, carbon footprint, ammonia emissions, greenhouse gas emissions, Integrated Farm System Model, cow-calf systems, feedlot, Holstein steers, enteric methane, nitrous oxide, manure management
- MeSH terms
- Ammonia, Animals, Animal Husbandry, California, Carbon Dioxide, Cattle, Computer Simulation, Meat, Models, Biological, Greenhouse Effect, Carbon Footprint
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
