Analysis of Inputs Parameters Used to Estimate Enteric Methane Emission Factors Applying a Tier 2 Model: Case Study of Native Cattle in Senegal

Abstract

In the context of the Paris Agreement, and considering the importance of methane emissions from cattle in West Africa, application of a Tier 2 method to estimate enteric methane emission factors is clearly pertinent. The current study has two purposes. Firstly, it aims to detect how much each input parameter contributes to the overall uncertainty of enteric methane emission factors for cattle. Secondly, it aims to identify which input parameters require additional research efforts for strengthening the evidence base, thus reducing the uncertainty of methane enteric emission factors. Uncertainty and sensitivity analysis methodologies were applied to input parameters in the calculation of enteric methane emission factors for lactating cows and adult male Senegalese native cattle using the IPCC Tier 2 model. The results show that the IPCC default input parameters, such as the coefficient for calculating net energy for maintenance (Cfi), digestible energy (DE) and the methane conversion rate (Ym) are the first, second and third most important input parameters, respectively, in terms of their contribution to uncertainty of the enteric methane emission factor. Sensitivity analysis demonstrated that future research in Senegal should prioritize the development of Ym, Cfi and DE in order to estimate enteric methane emission factors more accurately and to reduce the uncertainty of the national agricultural greenhouse gas inventory.

Review of Sources of Uncertainty and Techniques Used in Uncertainty Quantification and Sensitivity Analysis to Estimate Greenhouse Gas Emissions from Ruminants

“…This intricate web of elements contributes to the difficulties in accurately estimating emissions [29,74,75]. The identified uncertainties in animal parameters highlight the urgency of addressing the challenges to refine emission models and devise effective mitigation strategies [48,68,75]. The present study underscores the significance of improv-ing precision in data collection, advancing modeling techniques, and cultivating a holistic understanding of the diverse factors influencing emissions [74].…”

“…Utilizing both top-down and bottom-up methods, as highlighted by Kumari et al [71] and Vechi et al [73], introduces complexities and uncertainties in assessing methane emissions. Additionally, the impact of assumptions in LCA and default parameters in IPCC Tier 2 methodology, emphasized by Xu et al [63] and Ndao et al [68], further contributes to the overall uncertainty in emission factor accuracy. Hempel et al [70] draw attention to the limitations of livestock population databases and the potential overestimation of emissions using default factors, underscoring the need for improved data coverage and parameter refinement.…”

“…Ndao et al [68] applied uncertainty analysis to enteric methane emission factors, determining the importance of each input parameter. Marklein et al [7] employed a novel approach for facility-scale manure emissions, extending sensitivity analysis to the state level.…”

Research Progress on Greenhouse Gas Emissions From Livestock in Sub-Saharan Africa Falls Short of National Inventory Ambitions

“…The Tier 1 method uses fixed, default emission factors (EFs) (19) to compute emissions per head of livestock. Tier 1 EFs for SSA are based on modeling studies, and more recent in situ research has shown that IPCC Tier 1 EFs may not be appropriate for livestock in SSA (20)(21)(22)(23)(24)(25). Moreover, because it relies on fixed EFs, the Tier 1 approach cannot capture trends in emissions over time due to changes in management or other factors (26) and is therefore not suitable for measurement, reporting, and verification (MRV) purposes and tracking progress toward mitigation goals outlined in NDCs.…”