Multiple mitigation strategies can lead to GHG emissions reduction in Kenyan dairy systems

Merbold, L., Graham, M.W., Arndt, C., González-Quintero, R., Korir, D., Leitner, S., Ndung’u, P.W., Notenbaert, A. and Özk, S. 2023. Multiple mitigation strategies can lead to GHG emissions reduction in Kenyan dairy systems. Presented at the 3rd one-day symposium of the Animal Task Force and the EEAP Commission on Livestock Farming Systems, Lyon, 28 August 2023. Nairobi, Kenya: ILRI.

Livestock systems are an important source of livelihoods in Africa, but are also a large source of anthropogenic greenhouse gas (GHG) emissions (i.e. CH4 from enteric fermentation; CH4 and N2O from manure) in most African countries. Many African countries, such as Kenya, have prioritized livestock emissions in their Nationally Determined Contributions under the Paris Agreement. However, there are limited data available on GHG emissions from livestock systems in Africa. Scaled livestock emissions in Africa have been estimated using modelling approaches and were not necessarily based on locally appropriate data. To bridge this gap between limited local data and modelling, we used datasets collected from representative smallholder mixed dairy cattle systems in Kenya to up-scale GHG emissions using the Global Livestock Environmental Assessment Model – interactive (GLEAM-i). We evaluated effects of the following previously evaluated mitigation interventions on milk emission intensities (EI) to compare against baseline data: reduced age at first calving; increased fertility rate; sweet potato vine silage (SPVS) supplementation; dairy concentrate feeding; increased feeding level; all interventions combined. EIs for milk were lower than the baseline for all individual intervention scenarios (-3.6 to -11.0%), and the combined scenario reduced EIs additively by 36%. Individual interventions with the highest overall impact on milk EIs were supplementation with SPVS (-11.0%), increased fertility rate (-10.3%), and increasing feeding level (-10.1%). These results indicate the ‘many little hammers’ approach to interventions can lead to additive reductions in EIs when combined. Further, we demonstrate that data based mitigation interventions can be captured by the GLEAM-i model. Future work should focus on filling existing data gaps for emissions from livestock in East Africa to allow further upscaling, particularly for pastoralist systems, small ruminants, and manure.