Mitigation of greenhouse gas emissions from beef production in western Canada – Evaluation using farm-based life cycle assessment

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Livestock are by far the greatest contributor to Australian agricultural greenhouse gas (GHG) emissions and are projected to account for 72% of total agricultural emissions by 2020. This necessitates the development of GHG mitigation strategies from the livestock sector. Currently there are many research streams investigating the efficacy of GHG mitigation technologies, though most are at the individual animal level. Here we examine the effect of a promising animal-scale intervention - increasing ewe fecundity - on GHG emissions at the whole farm scale. This approach accounts for seasonal climatic influences on farm productivity and the dynamic interactions between variables. The study used a biophysical model and was based on real data from a property in south-eastern Australia that currently runs a self-replacing prime lamb enterprise. The breeding flock was a composite cross-bred genotype segregating for the FecB gene (after the 'fecundity Booroola' trait observed in Australian Merinos), with typical lambing rates of 150-200% lambs per ewe. Lambs were born in mid-winter (July) and were weaned and sold at 18 weeks of age at the beginning of summer (December). Livestock continuously grazed pastures of phalaris, cocksfoot and subterranean clover and were supplied with barley grain as supplementary feed in seasons when pasture biomass availability was low. Biophysical variables including pasture phenology and flock dynamics were simulated on a daily time-step using the model GrassGro with historical weather data from 1970 to 2012. Whole farm GHG emissions were computed with GrassGro outputs and methodology from the Australian National Greenhouse Accounts Inventory (DCCEE, 2012). Increasing ewe fecundity from 1.0 lamb per ewe at birth (equivalent to scanning rates at pregnancy of 80% of ewes with single lambs, 17% with twins and 3% empty) to 1.5 (scanning rates of 20% ewes with singles, 51% with twins, 26% with triplets and 3% empty as observed at the property) reduced mean emissions intensity from 9.3 to 7.3 t CO2-equivalents/t animal product and GHG emissions per animal sold by 32%. Increasing fecundity reduced average lamb sale liveweight from 42 to 40 kg, but this was offset by an increase in annual sheep sales from 8 to 12 head/ha and an increase in average annual meat production from 410 to 540 kg liveweight/ha. A key benefit associated with increasing sheep fecundity is the ability to increase enterprise productivity whilst remaining environmentally sustainable. For the same long-term average annual stocking rate as an enterprise running genotypes with lower fecundity, it was shown that genotypes with high fecundity such as those on the property could either increase meat and wool productivity from 449 to 571 kg/ha (clean fleece weight plus liveweight at sale) with little change in net GHG emissions, or reduce net GHG emissions from 4.1 to 3.2 t CO2-equivalents/ha for similar average annual farm productivity. In either case, GHG emissions intensity was reduced by about 2.1 t CO2-equivalents/t animal product. From a methodological perspective, this study revealed that differences in computing the relative effect of increased fecundity on total farm production, GHG emissions or emissions intensity either within or across years were relatively small. For example, the mean difference in emissions intensity of an enterprise obtaining 1.5 lambs per ewe relative to an enterprise obtaining 1.0 lamb per ewe computed within years was -25%, whereas the relative difference in mean emissions intensity across years was -27%. Such findings justify the traditional approach of previous GHG mitigation studies which compare differences (e.g. abatement potential) between values averaged across multiple-year simulation runs, as opposed to the method of computing the differences between intervention strategies within years then comparing the average difference.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

The development of beneficial management practices is a key strategy to reduce greenhouse gas (GHG) emissions from animal agriculture. The objective of the present study was to evaluate the impact of time and amount of hog manure application on farm productivity and GHG emissions from a cow–calf production system using two whole-farm models. Detailed model inputs (climate, soil and manure properties, farm operation data) were collected from a 3-year field study that evaluated the following three treatments: no application of hog manure on grassland (baseline); a single application of hog manure on grassland in spring (single); and two applications of hog manure as fall and spring (split). All three treatments were simulated in a representative cow–calf production system at the farm-gate using the following whole-farm models: a Coupled Components Model (CCM) that used existing farm component models and the Integrated Farm System Model (IFSM). Annual GHG intensities for the baseline scenario were 17.7 kg CO2-eq/kg liveweight for CCM and 18.1 kg CO2-eq/kg liveweight for IFSM. Of the total farm GHG emissions, 73–77% were from enteric methane production. The application of hog manure on grassland showed a mean emission increase of 7.8 and 8.4 kg CO2-eq/kg liveweight above the baseline for the single and split scenarios, respectively. For the manured scenarios, farm GHG emissions were mainly from enteric methane (47–54%) and soil nitrous oxide (33–41%). Emission estimates from the different GHG sources in the farm varied between models for the single and split application scenarios. Although farm productivity was 3–4% higher in the split than in single application (0.14 t liveweight/ha), the environmental advantage of applying manure in a single or split application was not consistent between models for farm emission intensity. Further component and whole-farm assessments are required to fully understand the impact of timing and the amount of livestock manure application on GHG emissions from beef production systems.

The objective of this work is to characterize regionally representative beef farm systems that represent dominant or typical surveyed management practices for 11 beef-producing regions across Canada. This work fulfills two further purposes 1) to improve and expand the Holos model interface; and 2) to facilitate the estimation of greenhouse gas (GHG) emissions and soil carbon (C) changes on beef farms in different regions of Canada. Holos version 4 is the whole-farm model of Agriculture and Agri-Food Canada’s to estimate GHG emissions and changes in soil C on Canadian farms in response to shifts in management practices. Holos can be implemented in all 10 Canadian provinces and accounts for GHG emissions from crop and livestock production [enteric and manure methane (CH4), manure and soil N2O emissions], farm machines and infrastructure [on-farm energy carbon dioxide (CO2) emissions], as well as from the upstream production of some farm inputs (synthetic fertilizer and pesticides). The model is designed to utilize data readily available on the farm to answer, ‘What if?’ scenarios, whereby the user can test the effect of changing management practices on their whole-farm GHG budget. To reduce the data input burden on the user, Holos V4 has built-in model livestock systems for beef, dairy, swine and poultry production that characterize the dominant features of these operations in Canada at the national scale based on relevant literature/data and expert opinion. Regarding beef production, we have characterized regionally specific model beef farms for incorporation into Holos, one for each of 11 Canadian beef-producing regions. General characteristics and management practices for each farm were based on the 2011 Beef Farm Survey (Sheppard et al., 2015), which summarizes management information from 1,009 Canadian beef farms, combined with data from the Canadian Cow-Calf Cost of Production Network (Canfax 2023). Each regional farm includes cow-calf, backgrounding in confinement, backgrounding on pasture and finishing components, and considers all the specific feed (e.g., forage, grains, by-products) required for each stage of the beef cycle. These 11 model farms are simulated within the current Holos V4 model to explore the impacts of variation in beef management practices on farm GHG emissions across Canada and on soil C stocks on lands used to produce feed and graze cattle. An overview of the national-level dairy, swine and poultry components in Holos will be presented along with a more detailed perspective of whole-farm GHG budget and multi-decadal soil C dynamics in regionalized beef farms. The impact of management and environmental factors that lead to differences in GHG emissions and soil C stocks in beef farms will also be explored.

Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway

Life cycle assessment of greenhouse gas emissions from beef production in western Canada: A case study

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Mitigation of greenhouse gas emissions in pasture-based dairy-beef production systems

The potential for mitigating greenhouse gas emissions and minimizing yield losses using the negative pressure irrigation system

Whole-farm systems modelling of greenhouse gas emissions from pastoral suckler beef cow production systems

Agriculture produces an estimated 14.5% of global anthropogenic greenhouse gases, with livestock emissions being the largest source of enteric methane. Reducing greenhouse gas (GHG) emissions from production and processing of beef cattle will become increasingly important with time, particularly in line with global efforts to mitigate rising GHG emissions. The present study compared several GHG emission scenarios from beef cattle grazing on irrigated Leucaena leucocephala (Lam.) de Wit cv. Cunningham (leucaena) in Queensland, Australia. Animals began grazing the leucaena paddocks when they were 16 months old and continued until ~240 days, before being sold to market. Three scenarios were modelled with cattle grazing leucaena and the resulting GHG emissions calculated, representing (1) the current leucaena paddock (current leucaena scenario), (2) clearing native vegetation and extending the leucaena paddock (extended leucaena scenario) and (3) extending the leucaena paddock onto previously cleared paddocks (alternative leucaena scenario). These were compared with a pre-scenario baseline, where the steers grazed on native vegetation until the time of sale. Herd GHG emission intensities (EI) were reduced in comparison with the baseline (EI of 8.4 tCO2-e/t liveweight sold) for all the leucaena scenarios, where reductions were modelled for the current, extended and alternative leucaena scenarios, which had an EI of 3.9, 3.7 and 3.6 tCO2-e/ t liveweight sold, respectively. Reductions were attributed to the higher growth rates of the steers on leucaena and the anti-methanogenic potential of leucaena. Where leucaena was planted on previously cleared paddocks, carbon stocks (t C/ha) nearly doubled a decade following planting, with most carbon sequestered in the soil. However, total carbon stocks on the property reduced over the modelled period (112 years), where native vegetation, e.g. eucalyptus woodland, was cleared for leucaena planting, but soil carbon yield increased. The combined sequestration of leucaena and the reduction of GHG emission intensities resulted in overall net reductions of GHG emissions for the three leucaena scenarios compared with the baseline. These results demonstrated that the use of leucaena for grazing can be an effective means for farmers to reduce the GHG emissions and increase productivity of their herds. The study also demonstrated that it would take 9 years of reduced emissions to compensate for the carbon lost as emissions from clearing the eucalyptus woodland, suggesting that farmers should use other methods of intensifying production from existing leucaena paddocks if their sole purpose is short-term emissions abatement.

Climate-smart livestock production at landscape level in Kenya

Balancing crop production and greenhouse gas (GHG) emissions from agriculture soil requires a better understanding and quantification of crop GHG emissions intensity, a measure of GHG emissions per unit crop production. Here we conduct a state-of-the-art estimate of the spatial-temporal variability of GHG emissions intensities for wheat, maize, and rice in China from 1949 to 2012 using an improved agricultural ecosystem model (Dynamic Land Ecosystem Model-Agriculture Version 2.0) and meta-analysis covering 172 field-GHG emissions experiments. The results show that the GHG emissions intensities of these croplands from 1949 to 2012, on average, were 0.10-1.31kgCO2 -eq/kg, with a significant increase rate of 1.84-3.58×10-3 kgCO2 -eqkg-1 year-1 . Nitrogen fertilizer was the dominant factor contributing to the increase in GHG emissions intensity in northern China and increased its impact in southern China in the 2000s. Increasing GHG emissions intensity implies that excessive fertilizer failed to markedly stimulate crop yield increase in China but still exacerbated soil GHG emissions. This study found that overfertilization of more than 60% was mainly located in the winter wheat-summer maize rotation systems in the North China Plain, the winter wheat-rice rotation systems in the middle and lower reaches of the Yangtze River and southwest China, and most of the double rice systems in the South. Our simulations suggest that roughly a one-third reduction in the current N fertilizer application level over these "overfertilization" regions would not significantly influence crop yield but decrease soil GHG emissions by 29.60%-32.50% and GHG emissions intensity by 0.13-0.25kgCO2 -eq/kg. This reduction is about 29% and 5% of total agricultural soil GHG emissions in China and the world, respectively. This study suggests that improving nitrogen use efficiency would be an effective strategy to mitigate GHG emissions and sustain China's food security.

In their article discussing the impacts of farm animal production on climate change, Koneswaran and Nierenberg (2008) called for “immediate and far-reaching changes in current animal agriculture practices” to mitigate greenhouse gas (GHG) emissions. One of their recommendations was to switch to organic livestock production, stating that Raising cattle for beef organically on grass, in contrast to fattening confined cattle on concentrated feed, may emit 40% less GHGs and consume 85% less energy than conventionally produced beef. These claims are terribly misleading. Koneswaran and Nierenberg (2008) compared organic beef produced in Sweden (22.3 kg of carbon dioxide-equivalent GHG emissions per kilogram of beef) with unusual and resource-intensive Kobe beef production in Japan (36.4 kg of CO2-equivalent GHG emissions per kilogram) (Cederberg and Stadig 2003; Ogino et al. 2007). To achieve the ultra-high fat levels in meat preferred by Japanese consumers, Japan’s wagyu cattle are raised and fattened for more than twice as long as typical U.S. beef cattle (Cattle Marketing Information Service Inc. 2007; Ogino et al. 2007). Moreover, all of the feed and forage for the Japanese animals (from birth through slaughter) must be shipped especially long distances—> 18,000 miles in the example cited. Hence, this beef has ultra-high GHG emissions and energy requirements. According to several analyses, typical nonorganic beef production in the United States results in only 22 kg of CO2-equivalent GHG emissions per kilogram of beef, which is 0.3 kg less than the Swedish organic beef system (Johnson et al. 2003; Subak 1999). These comprehensive life cycle analyses, which examined all aspects of beef production and all GHG emissions, seem to definitively rule out significant reductions in GHG emissions by switching to organic beef production. In fact, if nitrous oxide and other emissions from land conversion are included in the analysis, a large-scale shift to organic, grass-based extensive livestock production methods would increase overall GHG emissions by nearly 60% per pound of beef produced. According to Searchinger et al. (2008), each acre of cleared land results in 10,400 lb/acre/year of CO2-equivalent GHG (over a 30-year period, based on estimated emissions from a proportion of each land type converted to cultivation in the 1990s). Our own analysis (Avery and Avery 2007) using conservative beef production parameters from Iowa State University’s Leopold Center for Sustainable Agriculture shows that grain-finishing cattle is at least three times more land efficient per pound of finished beef compared to grass-finishing. Cattle industry statistics [U.S. Department of Agriculture (USDA) 2008] show that, in 2007, the United States used 2 billion bushels of corn to produce 22.16 billion lb finished grain-fed beef (17.3 million head steers and 10.2 million head heifers at average dressed weights of 830.2 and 764.8 lb, respectively). At 150 bushels/acre corn, this means we used 13.3 million acres to produce the feed grains. Converting all beef production to grass-based finishing would require at least an additional 26.6 million acres of pasture/grass to produce 2007 U.S. beef output. Using the 22 lb of CO2-equivalent GHG per pound of grain-fed beef from Johnson et al. (2003) and the 22.3 lb CO2-equivalent GHG per pound of beef for organic grass of Cederberg and Stadig (2003), each system producing 22.16 billion lb of beef would directly and indirectly result in 487.5 and 494.2 billion lb of CO2-equivalent GHG emissions, respectively. However, adding the “carbon debt” resulting from the additional cleared land required by the two-thirds less efficient grass finishing process (26.6 million acres × 10,400 lb/acre/year, or 276.6 billion lb/year) results in the organic system totaling 770 billion lb of CO2-equivalent GHG emissions; or 58% higher than the conventional system’s total of 487.5 billion lb.