Development of Rwanda country-specific greenhouse gas emission factors for livestock

National greenhouse gas (GHG) emission inventories have consistently highlighted the significant contribution of livestock. In Rwanda, livestock contributed 43.5% to national emissions in 2018. Most of non-annex 1 countries, including Rwanda, have relied on default Tier 1 emission factors from IPCC for livestock due to the lack of country-specific data. This study aimed to improve Rwanda-specific methods for livestock feed intake, diet composition, volatile solids, nitrogen excretion and manure management systems (MMS) to facilitate Tier 2 GHG emission calculations in future inventories. Literature review and farm survey have been conducted. The country-wide survey generated data missing from literature review: population structure; production system types and their respective proportions; live weight and daily feed intake; volatile solids; nitrogen excretion; types and proportions of MMS for cattle, sheep, goats, swine, rabbits and poultry. The population-weighted methane (CH4) emission factors for enteric fermentation were 62.5 kg/head per year for cattle and 8.6 kg/head per year for sheep. These values were higher than the default values stipulated in the Tier 1 IPCC guidelines but fell below the values previously used in Rwanda national inventories. The data collected did not allow full Tier-2 emission factor calculations for goats, swine, poultry and rabbits. With respect to MMS, the reported emission factors for CH4 were 1.2–1.9 times lower for dairy cattle, sheep, goats and swine and 2.8–18 times higher for poultry and rabbits as compared to the IPCC 2019 default values, and nitrous oxide were notably greater, ranging from 3 to 26 times greater than the default values set forth in the IPCC 2006 guidelines for Africa and used in Rwanda BUR-1. This disparity may be attributed to Rwanda’s zero-grazing policy implementation and predominantly inadequate MMS, with 46% of these facilities being open pits. This study was the first to systematically survey MMS in Rwanda against the IPCC categorization related to GHG emission characteristics. The datasets and methods demonstrated here to calculate the parameters could be adopted for the compilation of the next Rwanda agricultural GHG inventory.