Applying life cycle assessment to sparse historical data from pig systems

Feed inputs account for a large part of environmental impact from pig systems. However, within life cycle assessment (LCA), genetics and management of crop production systems are also considered as important determinants of the environmental impact of livestock systems. As such, for rigorous comparisons of livestock production systems from different eras with respect to environmental impact, a robust method is needed to estimate diet composition based on animal requirements. The objective of this study was to compare the environmental impacts of British indoor and outdoor bred pigs based on growth rates, feed intake and of sow reproductive performance from 2003 and 2017 systems. Animal daily requirements were estimated by modelling the need for energy and protein based on equations for conservation of mass, energy and protein. To accommodate lactation nutrient dynamics, a sow growth model modified to impose conservation of protein was implemented to estimate sow requirements. Least cost diets, based on historical prices of feed ingredients, were formulated to meet the estimated energy, amino acids and mineral requirements of all life stages. Storage and spreading of manure were modelled based on excreted nutrients, and artificial fertilizers were replaced with typical ratios reported in literature. Global Warming Potential (GWP), Terrestrial Acidification Potential (TAP), Land use (LU) and Fossil Resource Scarcity (FRS) were calculated with SimaPro, linking the sow reproductive cycle to the grower pig via piglet production. We found that impacts changes per functional unit of 1 kg of live pig at farm gate from 2003 to 2017 respectively for indoor and outdoor systems were 8.8 and 5.0% lower for GWP, 2.1% higher and 6.1% lower for TAP, 13.2 and 16.6% lower for land use, and 86.9 and 83.7% higher for FRS. The major increase in FRS are accounted for by higher inclusion of artificial amino acids in 2017 and higher fertilizer replacement in 2003. This method can be applied to all systems where basic industry data are available, and thus is a promising tool for estimating the implications of industrial development for the sustainability of livestock systems.