Calculation of new enteric methane emission factors for small ruminants in western Kenya highlights the heterogeneity of smallholder production systems

Abstract

Context African livestock play a critical role in food security and the wider economy, while accounting for >70% of African agricultural greenhouse gas emissions. Accurate estimates of greenhouse gas emissions from livestock are required for inventory purposes and to assess the efficacy of mitigation measures. While there is an increasing number of studies assessing methane (CH4) emissions of cattle, little attention has been paid to small ruminants (SR). Aims Enteric CH4 emissions were assessed from 1345 SR in three counties of western Kenya to develop more accurate emission factors (EF) for enteric CH4 from sheep and goats. Methods Using on-farm animal activity data, feed samples were also analysed to produce estimates of feed digestibility by season and region. The combined data were also used to estimate daily CH4 production by season, location and class of animal to produce new EF for annual enteric CH4 production of SR. Key results Mean dry-matter digestibility of the feed basket was in the range of 58–64%, depending on region and season (~10% greater than Tier I estimates). EF were similar for sheep (4.4 vs 5 kg CH4/year), but lower for goats (3.7 vs 5 kg CH4/year) than those given for SR in developing countries in Intergovernmental Panel on Climate Change (Tier I) estimates. Conclusions Published estimates of EF for SR range widely across Africa. In smallholder systems in western Kenya, SR appear to be managed differently from cattle, and EF appear to be driven by different management considerations. Implications The findings highlighted the heterogenous nature of SR enteric emissions in East Africa, but also suggested that emissions from SR are quantitatively less important than other estimates suggest compared with cattle.

A simplified approach for producing Tier 2 enteric-methane emission factors based on East African smallholder farm data

“…The accuracy of estimating enteric CH 4 emissions by using models has been a key interest with numerous studies (du Toit et al 2013;Ndung'u et al 2019;Goopy et al 2021;Ndao 2021). These studies largely agree on two conclusions, namely that (1) appropriate assumptions need to be made that reflect the conditions of the livestock system under investigation, and (2) data inputs to be used by the model need to have sufficient accuracy to derive reliable estimates of the actual emission situation.…”

“…Such information is largely missing for most livestock production systems in SSA countries, and many countries are facing challenges such as inadequate knowledge of key sources of GHG emissions and missing reliable accounting systems (Merbold et al 2021). This is specifically true for methane emissions from ruminants as the lack of accurate and reliable animal-activity data for local agricultural systems (Goopy et al 2018a(Goopy et al , 2021 hampers the development of accurate national GHG inventories. So as to close this knowledge gap, low-cost and simplified approaches to estimate GHG emissions from livestock production are the key.…”

“…Yet, inventories created using the Tier 1 system have been demonstrated to be considerably less representative of the actual case than are those using EFs generated through detailed investigations of enteric CH 4 emissions associated with livestock production in the Global South that take into account local conditions (e.g. seasonal fluctuations of quantity and quality of feeds, animal phenotype husbandry practices and management; du Toit et al 2013;Goopy et al 2018aGoopy et al , 2021.…”

“…Recently, several field studies have been undertaken in western Kenya, which collected detailed on-farm information on seasonal liveweight change, milk production, and feed composition and quality, and used this information to create spatially explicit EFs for different production systems in the region (Goopy et al 2018a(Goopy et al , 2021Ndung'u et al 2019Ndung'u et al , 2021. More studies using the same approach are underway by a team led by the International Livestock Research Institute for Tanzania, Uganda, and Ethiopia, so that more detailed information on CH 4 emissions from the livestock sector in East Africa will become available soon (Merbold et al 2021).…”

Livestock, methane, and climate change: The politics of global assessments

“…In part, this is because such animals are smaller, but also because they are physiologically adapted and feed selectively on natural range under particular feeding regimes. As a result, such animals produce far fewer emissions than usually assumed in standard models (Goopy et al, 2021;ILRI, 2018;Ndung'u et al, 2019). While estimated emissions factors may be necessary while improved data emerges from such local studies, much caution must be applied to the results, since life-cycle analyses may be substantially off the mark due to this chain of compounding uncertainties.…”