Dynamic estimation of greenhouse gas emissions from bovine livestock of Valle del Cauca, Colombia

Abstract

The contribution of Colombia to global emissions of greenhouse gases (GHGs) is low (0.37%); from this percentage, 38% is attributed to agriculture. There are few studies on GHGs emissions at the regional level for agriculture. Therefore, the aim of this research is to estimate dynamically GHG and carbon footprint produced by cattle in the department of Valle del Cauca, Colombia. GHG estimates were established as follows: Tier II of IPCC methodology (2006), and population trends, which were simulated using dynamic system. According to the departmental livestock inventory in recent years (2009-2015), average emissions were 673 million of CO2eq. year-1, with emissions intensity (EI) of 5.58 kgCO2eq.kg.milk-1 and 3.54 kgCO2eq.kgmeat-1. Simulating the behavior of the bovine population (2016-2035), based on historical trends, the number of animals and emissions tended to reduce. The simulated EI was in 4.1 - 4.2 kgCO2eq.kg.milk-1 and 3.7 – 3.9 kgCO2eq.kg.meat-1. Increasing birth rates (83 to 90%), lower age at first birth (34 to 30 months), increased milk production per cow per day (5.33 to 10 kg), increased production of milk and meat in 100 and 4 million kg per year, respectively; with decrease in EI of 1.4 for milk and 2 units for meat. This study showed selecting efficient animals (productively and reproductively), can produce more animal protein with less carbon footprint.