a b s t r a c tThe carbon footprint (CF) of beef production is one of the most widely discussed environmental issues within the current agricultural community due to its association with climate change. Because of these relevant and serious concerns, the beef cattle industry is under increasing pressure to reduce production or implement technological changes with significant consequences in terms of beef marketing. The goals of this study were to evaluate the CF per 1 kg of live weight gain (LWG) at the farm gate for different beef production systems in the southern part of Brazil. Aberdeen Angus beef-bred cattle were assigned to one of seven categories: natural grass; improved natural grass; natural grass plus ryegrass; improved natural grass plus sorghum; cultivated ryegrass and sorghum; natural grass supplemented with protein mineralised salt; and natural grass supplemented with protein-energetic mineralised salt. Monte Carlo analysis was employed to analyse the effect of variations of dry matter intake digestibility (DMID), total digestible nutrients (TDN) and crude protein (CP) parameters in methane (CH 4 ) enteric, CH 4 manure, nitrous oxide (N 2 O) manure and N 2 O N-fertiliser. The method used was a comparative life cycle assessment (LCA) centred on the CF. The CF varied from 18.3 kg CO 2 equivalent/kg LWG for the ryegrass and sorghum pasture system to 42.6 kg CO 2 equivalent/kg LWG for the natural grass system, including the contributions of cows, calves and steers. Among all grassland-based cattle farms, production systems with DMID from 52 to 59% achieved the lowest CO 2 emissions and the highest feed conversion rate, thereby generating lower CH 4 and N 2 O emissions per production system. Because the feed intake and feed conversion rate are one of the most important production parameters in beef cattle production with an obvious risk of data uncertainty, accurate feed data, which include quantity and quality, are important in estimates of CF for LWG. The choice of adequate feeding strategies to mitigate greenhouse gas (GHG) emissions may result in better environmental advantages.

Purpose Livestock production is a recognized source of environmental impact, and this sector indirectly involves approximately 5 million people in Brazil. Livestock production includes nearly 1.5 million milk producers that use several different production systems. We chose the southern region of Brazil to evaluate the carbon footprint (CF) per 1 kg of energy-corrected milk (ECM) at the farm gate for different dairy production systems with the use of a good level of technology. Methods The dairy production systems were confined feedlot system, semi-confined feedlot system (including some grazing), and pasture-based grazing system. A sensitivity analysis of the dry matter intake (DMI) in each farming system and an uncertainty analysis based on a Monte Carlo (MC) simulation were performed to complement the discussion. The standards ISO 14040: 2006 and ISO 14044: 2006 were used for the comparative life cycle assessment (LCA) focused on the CF. The LCA software tool SimaPro 7.3.3 was used. Sensitivity analyses were conducted on input data for total digestible nutrients (TDN) and crude protein (CP) based on values from the literature. Results and discussion The comparative LCA showed that the confined feedlot system had a lower CF than the other systems studied. Total greenhouse gas emissions were 0.535 kg CO 2 e kg ECM −1 for the confined feedlot system, 0.778 kg CO 2 e kg ECM −1 for the semi-confined feedlot system, and 0.738 kg CO 2 e kg ECM −1 for the pasture-based system without considering the impact from direct land use change (dLUC). When considering these emissions, the CFs for grain and cottonseed production showed CF increases of 45.0, 36.9, and 37.3 % for the confined feedlot, semi-confined feedlot, and pasture-based systems, respectively. The results from the MC simulations showed low uncertainty through variations in TDN and CP. The coefficient of variation was 1.1 % for the confined feedlot, 0.7 % for the semi-confined feedlot, and 1.0 % for the pasture systems. Conclusions The uncertainties were due mainly to variations in N 2 O emissions from manure for the three systems. The CF in Brazilian systems was lower than almost all the results found in the literature, even when impacts from the dLUC were considered. The lowest CF in this case study was due mainly to the emission factor used for enteric fermentation.

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