Abstract. National greenhouse-gas (GHG) inventories in most developing countries, and in countries in Sub-Saharan Africa in particular, use default (Tier I) GHG emission factors (EFs) provided by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric methane (CH 4 ) emissions from livestock. Because these EFs are based on data primarily from developed countries, there is a high degree of uncertainty associated with CH 4 emission estimates from African livestock systems. Accurate Tier II GHG emission reporting from developing countries becomes particularly important following the Paris Climate agreement made at COP21, which encourages countries to mitigate GHG emissions from agricultural sources. In light of this, the present study provides improved enteric CH 4 emission estimates for cattle in Nandi County, Western Kenya, representing a common livestock production system found in East Africa. Using the data from measurements of liveweight and liveweight change, milk production and locomotion collected from 1143 cattle in 127 households across 36 villages over three major agro-ecological zones covering a full year, we estimated total metabolic energy requirements. From this and assessments of digestibility from seasonally available feeds, we estimated feed intake and used this to calculate daily CH 4 production by season, and, subsequently, created new EFs. Mean EFs were 50.6, 45.5, 28.5, 33.2 and 29.0 kg CH 4 /head.year for females (>2 years), males (>2 years), heifers (1-2 years), young males (1-2 years) and calves (<1 year) respectively, and were lower than the IPCC Tier I estimates for unspecified African adult cattle, but higher for calves and young males. Thus, using IPCC Tier 1 EFs may overestimate current enteric CH 4 emissions in some African livestock systems.

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Context African livestock play a critical role in food security and the wider economy, while accounting for &gt;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.

Livestock are an important source of livelihoods in agricultural systems in sub-Saharan Africa (SSA), while also being the largest source of national greenhouse gas (GHG) emissions in most African countries. As a consequence, there is a critical need for data on livestock GHG sources and sinks to develop national inventories, as well as conduct baseline measurements and intervention testing to mitigate GHG emissions and meet ambitious national climate goals. Our objective was to review studies on GHG emissions from livestock systems in SSA, as well as soil carbon storage in livestock-dominated systems (i.e., grasslands and rangelands), to evaluate best current data and suggest future research priorities. To this end, we compiled studies from SSA that determined emission factors (EFs) for enteric methane and manure emissions, along with studies on soil organic carbon (SOC) stocks in SSA. We found that there has been limited research on livestock GHG emissions and SOC relative to national ambitions for climate change mitigation in SSA. Enteric methane emission factors (EFs) in low productivity cattle systems may be lower than IPCC Tier 1 default EFs, whereas small ruminants (i.e. sheep and goats) had higher EFs compared to IPCC Tier 1 EFs. Manure EFs were equal to or lower than IPCC Tier 1 EFs for deposited manure (while grazing), manure applied as fertilizer, and manure management. SOC stocks for grasslands and rangelands in SSA show broad agreement with IPCC estimates, but there was a strong geographic bias and many studies did not report soil type, bulk density, or SOC stocks at &gt;30 cm depth. In general, the largest data gaps included information for manure (quantity, quality, management), small ruminants, agropastoral/pastoralist systems, and in general from West Africa. Future research should focus on filling major data gaps on locally appropriate mitigation interventions and improving livestock activity data for developing Tier 2 GHG inventories in SSA. At the science-policy interface, all parties would benefit from enhanced coordination within the research community and between researchers and African governments to improve Tier 2 inventories and harmonize measurement for mitigation in livestock systems in SSA.

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The output can be accessed at: https://repository.rothamsted.ac.uk/item/98q05/asimplified-approach-for-producing-tier-2-enteric-methane-emission-factors-based-oneast-african-smallholder-farm-data.

Most Sub-Saharan countries still rely on the basic Intergovernmental Panel on Climate Change's (IPCC) Tier 1 methodology for reporting greenhouse gas (GHG) emissions from their livestock sector. This approach is, however, associated with high uncertainty and cannot detect changes in GHG emissions resulting from mitigation interventions. The present study aimed to quantify the effect of replacing the IPCC Tier 1 methodology with Tier 2 approaches in assessing total farmgate GHG emissions and products' emission intensities (EIs) in smallholder cattle production in Western Kenya. Additionally, the study assessed the effect of using locally measured methane yield (MY) instead of regional defaults in Tier 2 estimations. A partial life cycle assessment (LCA) was conducted using aggregated activity data from two contrasting study sites, one with moderately performing and another with low-performing cattle production systems. The total farmgate GHG emissions were allocated to the co-products, namely milk and live weight gain, using the novel energy expenditure allocation method, in comparison to the traditionally used protein mass allocation. Compared Tier 1 methodology, the use of Tier 2 approaches resulted in 18-44% lower total farmgate GHG emissions and milk EIs across the two study sites. When the IPCC regional MY default was substituted with locally measured MY, the total GHG emissions and milk EI increased by 19-25%. These findings suggest that the continued use of IPCC Tier 1 methodology or Tier 2 MY defaults by East African countries are resulting in considerable uncertainty in their livestock GHG inventory reporting. There is therefore a need for these developing nations to adopt higher-tier methodologies as well as measure and utilize locally relevant MY for more accurate inventory reporting and to be able to assess suitable GHG mitigation strategies for local cattle production systems. Additionally, the study found that the energy expenditure allocation method apportioned a lower proportion of GHG emissions to milk production compared to live weight gain, reflecting the greater nutrient use efficiency by cattle in producing milk than gaining weight. As developing countries are faced with the double challenge of increasing animal-sourced food to feed the growing population and a need to reduce GHG emissions associated with food production, it is sensible for these countries to report changes in product EIs rather than absolute emissions. It is, therefore, imperative to continually refine LCA methodology for more relevance in multifunctional smallholder systems for unbiased measurement of products' EIs from such systems.

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