Abstract
The UK livestock industry urgently needs to reduce greenhouse gas (GHG) emissions to contribute to ambitious climate change policy commitments. Achieving this requires an improved understanding of emission sources across a range of production systems to lower the burden associated with livestock products. Life cycle assessment (LCA) methods are used in this study to model milk production from two genetic merits of Holstein Friesian cows managed in two novel and two conventional UK dairy systems. Select merit cows sired by bulls with high predicted transmission for fat plus protein yield are compared with Control merit animals sired from UK average merit bulls. Cows were managed in conventional housed and grazed dairy systems with novel Byproduct and Homegrown feeding regimes. A LCA was used to quantify the effect of allocation and management of feed components on the carbon footprint of milk production. Natural variation in nutritional quality of dairy system rations was investigated to quantify uncertainty in the carbon footprint results. Novel production system data are used to assess the effect of introducing home grown legumes and co-product feeds. Control merit footprints across each of the management regimes were significantly higher (p<0.001) in comparison with a high production Select merit, on average by 15%. Livestock emissions (enteric, manure management and deposition) and embedded emissions (purchased feeds, fertiliser, and pesticides) were also significantly higher from control merit cows (p<0.01). Mass and economic allocation methods, and land use functional units, resulted in differences in performance ranking of the dairy systems, with larger footprints resulting from mass allocation. Pairwise comparisons showed GHG's from the systems to be significantly different in total and source category emissions, with significant differences in mean embedded emissions found between most management systems (p<0.05). Monte Carlo simulated system footprints considering the effect of variation in feed digestibility and crude protein also differed significantly from system footprints using standard methods (p < 0.001). Dairy system carbon footprint results should be expressed using multiple units and where possible calculations should incorporate variation in diet digestibility and crude protein content.
Highlights
The UK government is committed to reducing greenhouse gas (GHG) emissions to net zero by 2050 with an even more ambitious target date of 2045 in Scotland (Committe on Climate Change, 2019)
UK GHG emissions from agriculture have declined by ∼14% since 1990, and reductions have largely arisen from a change to the Common Agriculture Policy (CAP), which ended a link between subsidy amounts and animal numbers (DBEIS, 2019, AHDB, 2014)
Post hoc comparisons using the Tukey test showed mean Select and Control merit GHG totals to be significantly different (p < 0.05) in low forage (LF), BP and high forage (HF) feed types but no significant difference was found between the home grown (HG) and HF diet
Summary
The UK government is committed to reducing GHG emissions to net zero by 2050 with an even more ambitious target date of 2045 in Scotland (Committe on Climate Change, 2019). Agriculture is estimated to be responsible for 10–12% of global anthropogenic greenhouse gas (GHG) emissions (Smith et al, 2014). Emissions stemming from milk production in developed dairy regions such as the UK are estimated at between 1.2 and 1.4 kg CO2e/kg, respectively, which is lower than the global average of 2.5 kg CO2e/kg of fat and protein corrected milk (FPCM) (FAO, 2019). GHG emissions from livestock need to be reduced at a time when global demand for these commodities is increasing (Opio et al, 2013; FAO, 2019). UK GHG emissions from agriculture have declined by ∼14% since 1990, and reductions have largely arisen from a change to the Common Agriculture Policy (CAP), which ended a link between subsidy amounts and animal numbers (DBEIS, 2019, AHDB, 2014). Formulating policies to enable further emission reductions on dairy farms will require an understanding of mitigation measures appropriate for specific production systems
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