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

Context: Accurate livestock greenhouse gas (GHG) emissions reporting is important in developing effective mitigation strategies, but the cost and labor requirements associated with on-farm data collection often prevent this effort in low-and-middle-income countries. Aim: The aim of this study was to investigate the precision and accuracy of simplified activity data collection protocols in African smallholder livestock farms for country-specific enteric methane emission factors. Method: Activity data such as live weight (LW), feed quality, milk yield, and milk composition were collected from 257 smallholder farms with a total herd of 1,035 heads of cattle in Nandi and Bomet counties in Western Kenya. The data collection protocol was then altered by substituting actual LW measurements with algorithm LW (ALG), feed quality (FQ) data sourced from the Feedipedia database, reducing the need for daily milk yield records to a single seasonal milk measurement (MiY), and using a default energy content of milk (MiE). Daily methane production (DMP) was calculated using these simplified protocols and the estimates under individual and combined protocols were compared with values derived from the published (PUBL) estimation protocol. Key results: Employing the algorithm LW showed good agreement in DMP with only a small negative bias (7%) and almost no change in variance. Calculating DMP based on Feedipedia FQ, by contrast, resulted in a 27% increase in variation and a 27% positive bias for DMP compared to PUBL. The substitutions of milk (MiY and MiE) showed a modest change in variance and almost no bias in DMP. Conclusion: It is feasible to use a simplified data collection protocol by using algorithm LW, default energy content of milk value, seasonal single milk yield data, but full sampling and analysis of feed resources is required to produce reliable Tier 2 enteric methane emission factors. Implications: Reducing enteric methane emissions from the livestock is a promising pathway to reduce the effects of climate change hence the need to produce accurate emissions estimates as benchmark to measure the effectiveness of mitigation options. However, it is expensive to produce accurate emission estimates especially in developing countries, hence important and feasible to simplify on-farm data collection.