Abstract
Life Cycle Assessment (LCA) of livestock production systems is often based on inventory data for farms typical of a study region. As information on individual animals is often unavailable, livestock data may already be aggregated at the time of inventory analysis, both across individual animals and across seasons. Even though various computational tools exist to consider the effect of genetic and seasonal variabilities in livestock-originated emissions intensity, the degree to which these methods can address the bias suffered by representative animal approaches is not well-understood. Using detailed on-farm data collected on the North Wyke Farm Platform (NWFP) in Devon, UK, this paper proposes a novel approach of life cycle impact assessment that complements the existing LCA methodology. Field data, such as forage quality and animal performance, were measured at high spatial and temporal resolutions and directly transferred into LCA processes. This approach has enabled derivation of emissions intensity for each individual animal and, by extension, its intra-farm distribution, providing a step towards reducing uncertainty related to agricultural production inherent in LCA studies for food. Depending on pasture management strategies, the total emissions intensity estimated by the proposed method was higher than the equivalent value recalculated using a representative animal approach by 0.9-1.7 kg CO2-eq/kg liveweight gain, or up to 10% of system-wide emissions. This finding suggests that emissions intensity values derived by the latter technique may be underestimated due to insufficient consideration given to poorly performing animals, whose emissions becomes exponentially greater as average daily gain decreases. Strategies to mitigate life-cycle environmental impacts of pasture-based beef productions systems are also discussed.
Generated Summary
This research presents a life cycle assessment (LCA) of pasture-based beef cattle production systems, focusing on the environmental impact of emissions intensity for individual beef cattle. The study, conducted at the North Wyke Farm Platform (NWFP) in Devon, UK, employs a novel approach that uses high-resolution, on-farm data to assess individual animal performance and emissions intensity. The methodology involves measuring field data such as forage quality and animal performance, directly integrating them into LCA processes to derive emissions intensity for each animal. The aim is to reduce uncertainty in LCA studies by accounting for heterogeneity in animal performance, and thus, the study examines and compares emissions intensity under different pasture management strategies, specifically permanent pasture (PP), white clover/high sugar grass mix (WC), and high sugar grass monoculture (HS). The functional unit is “1 kg of liveweight gain (LWG)”. This approach provides a detailed analysis of environmental hotspots and a basis for assessing the impact of different pasture management strategies on emissions intensity, using both a representative animal approach and an individual animal approach.
Key Findings & Statistics
- The study was conducted at the North Wyke Farm Platform (NWFP) in Devon, UK.
- The study period followed emissions intensity of 90 cattle (30 per farmlet) born in spring 2014, from weaning to slaughterhouse in December 2015.
- The functional unit was set as “1 kg of liveweight gain (LWG)”.
- The total global meat production generates 7.1 Gt CO2-eq of greenhouse gases (GHG) each year, with cattle contributing 65%.
- The NWFP consists of three small-scale (21 ha) livestock farms known as “farmlets”.
- The average emissions intensity for WC was 16.0 kg CO2-eq/kg LWG, PP was 18.5 kg CO2-eq/kg LWG, and HS was 20.2 kg CO2-eq/kg LWG.
- There were significant differences across the three treatments (p < 0.001).
- Emissions intensity for WC was significantly lower than PP (p < 0.001) and HS (p < 0.001), while PP was significantly lower than HS (p < 0.001).
- The relationship between average daily gain (ADG) and emissions intensity: WC (r = -0.86), PP (r = -0.84), and HS (r = -0.77; all p < 0.001).
- The PP system showed higher ADG (0.76 kg/d) than WC (0.68 kg/d) and HS (0.70 kg/d) (p < 0.01).
- The study found that the average emissions intensity of the pre-averaged animals approach underestimates the emissions intensity by 0.9-1.7 kg CO2-eq/kg LWG, representing up to 10% of the system-wide emissions.
- The study showed that, on average across the three systems, emissions assigned to cattle were 78% under economic allocation and 72% under mass allocation.
- The study indicated that emissions intensity for WC, PP, and HS decreased by 2%, 3%, and 4% respectively, under mass allocation of pasture.
Other Important Findings
- The study found that the WC system had the lowest average emission intensity across all animals.
- Emissions from livestock were not the primary drivers of relative emissions intensity amongst different farmlets.
- Individual animal heterogeneity played a key role in distributions of emissions intensity within each farming system.
- Steers from the WC farmlet had a significantly lower emissions intensity than WC heifers (difference in means = 1.4 kg CO2-eq/kg LWG; p = 0.020).
- HS males had a significantly lower emissions intensity than HS females (1.7 kg CO2-eq/kg LWG; p = 0.027).
- While the study found no significant differences in ADG between the sexes, male cattle had a higher total LWG than females for both WC and HS systems (p = 0.033 and p = 0.037).
- The study suggests that the use of pre-averaged data may result in underestimation of emission intensities, both in terms of point estimates and the width of confidential intervals.
Limitations Noted in the Document
- The study focused only on the post-weaning (finishing) stage of the cattle lifecycle, thus, it is not a full carbon footprint analysis.
- The study excluded the cow-calf operations, as well as land use and land use change.
- Uncertainties exist in the LCA framework.
- The study did not account for the potential effect of changes in soil carbon stock on emissions intensity.
- The results may not be straightforwardly applicable at regional and national scales.
Conclusion
This study provides a detailed analysis of the environmental impacts of pasture-based beef production systems. The results highlight the importance of accounting for heterogeneity in animal performance and its impact on emissions intensity. The study’s findings suggest that pre-averaged data may underestimate emissions, emphasizing the need for more precise and nuanced methodologies in LCA studies. The study’s comparison of different pasture management strategies reveals variations in emissions intensity, with the white clover/high sugar grass mix showing the lowest average emissions intensity. The research underscores the potential for improving the environmental performance of pasture-based beef production systems through innovative strategies such as the use of legumes, low-carbon inputs, and animal selection based on genetics and performance. The study also points to the need to consider broader aspects of beef production, including competition for land resources and the nutritional value of meat. These findings have implications for policy and farm management practices, suggesting that the adoption of more detailed and evidence-based approaches can enhance the environmental benefits of beef production. Overall, the research advocates for integrating high-resolution data and a clear methodology to better understand the environmental consequences and provide more reliable assessments of emissions intensity in livestock production. Further research is required before drawing any conclusion regarding the optimal interlinkages between beef systems and dairy systems, which is beyond the remit of the present study.