Carbon footprint, non-renewable energy and land use of dual-purpose cattle systems in Colombia using a life cycle assessment approach

Abstract

Dual-purpose cattle systems (DPS) include more than 75% of all dairy cows in Latin America and produce 40% of total milk production. Colombia has the fourth largest cattle herd in Latin America, and DPS account for 39% of the cattle population, and 58% of national milk production. Therefore, focusing on reducing the carbon footprint (CF) of DPS can have a huge contribution on mitigating the environmental impacts of the cattle farming sector. The present study aimed to estimate, based on a farm gate life cycle assessment (LCA) approach, the environmental impact of 1313 dual-purpose farms in Colombia. The study also aimed at identifying the main hotspots of negative environmental impacts and proposing possible mitigation options and their cost-effectiveness. The impact categories such as CF, non-renewable energy use, and land use were estimated using the 2019 Refinement to 2006 IPCC, databases, and locally estimated emission factors. Three methods of allocating environmental burdens to meat and milk products were applied. A principal component multivariate analysis (PCA) and a Hierarchical Clustering on Principal Components (HCPC) were performed. The largest source of greenhouse gas (GHG) in dual-purpose cattle systems comes directly from enteric fermentation, and manure deposited on pasture. The proportion of environmental burdens allocated to meat differed, with the economic method assigning the greater burden (36%), followed by energy content (30%) and mass production (13%). Four farms clusters and two production strategies were identified, a more intensive strategy with high proportion of improved pastures and higher fertilizer application rates (Clusters 1 and 2), and a more extensive with low input of fertilizers and grazing on natural pastures (Clusters 3 and 4). The CF values ranged between 2.1 and 4.2 CO2-eq per kg fat and protein corrected milk (FPCM) and between 9.0 and 18.3 CO2-eq per kg meat among clusters. CF, land use, and non-renewable energy use were lowest for clusters 1 and 3. Concerning cost-effectiveness, the adoption of improved pastures is a negative-cost measure and a promising climate change mitigation option. Overall, the CF could be reduced by around 25 to 48% for milk and meat. Therefore, our results suggest that it is possible to reduce GHG emissions by adopting improved pastures, better agricultural management practices, efficient fertilizer usage, and using the optimal stocking rate. It is expected that these reductions can be achieved with at negative costs.