Abstract
The United Nations Food and Agriculture Organization (FAO) has developed the Global Livestock Environmental Model (GLEAM), a spatial data framework for estimating greenhouse gas (GHG) emissions from the livestock sector. In addition to livestock distribution data, GLEAM incorporates five spatially distributed variables associated with nitrogen and methane conversion factors. These variables include maximum methane production capacity from manure, climate zones, temperature, and losses due to leaching from solid and liquid manure management. All based on the 2019 and 2006 guidelines from the Intergovernmental Panel on Climate Change (IPCC). GLEAM has been used by several countries to estimate the impact of GHG mitigation actions and report these as part of their Nationally Determined Contributions. This process necessitates the development of a country-level data collection plan, which requires significant financial and planning resources. This study examines the impact of variability in spatial parameters on direct emission estimates by developing a sensitivity index at global and country scales. The results highlight the value of incorporating sensitivity analysis when designing data collection efforts, to reduce associated costs.