Distributions of emissions intensity for individual beef cattle reared on pasture-based production systems

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. •Estimates emissions intensity (EI) for each individual cattle on farm.•Integrates high-resolution data into the life cycle assessment (LCA) framework.•Proposes an original “uncertainty analysis” based on actual distributions of EI.•Demonstrates that EI derived by representative animal models may be underestimated.