Harmonizing soil carbon simulation models, emission factors and direct measurements used in LCA of agricultural systems

CONTEXT: The increasing demand for animal products, coupled with the need to reduce greenhouse gas (GHG) emissions from livestock production, highlights the urgency for effective mitigation strategies for livestock systems, including the cropping systems. Soil organic carbon (SOC) sequestration, a crucial approach for reducing atmospheric GHG concentrations, is often underrepresented in Life Cycle Assessments (LCA) of agricultural systems, largely due to methodological challenges in accurately accounting for soil carbon dynamics. OBJECTIVE: The objective of this study was to evaluate soil carbon simulation models, emission factors and direct measurements used in LCA, with the aim of developing a harmonized approach for including soil carbon change in agricultural LCAs. The goals were to: i) assess soil carbon simulation models, emissions factors and direct measurements used in LCAs of agricultural systems; ii) evaluate the strengths and weaknesses of these models; iii) provide recommendations for LCA practitioners; and iv) identify areas for future methodological improvements. METHODS: A systematic review of soil carbon simulation models, emission factors and direct measurements used in LCAs of agricultural systems was conducted, obtaining 263 relevant articles from an initial pool of 29,151. In addition to direct measurements, fifteen soil carbon simulation models and three methods based on emission factors were identified and categorized into three tiers based on complexity and data requirements. A modified Delphi participatory process was used to evaluate each method against established criteria through expert workshops. RESULTS AND CONCLUSIONS: The results showed an inverse relationship between applicability and accuracy of methods, making the choice of methodology critical to achieving high-quality LCA results. Recommendations emphasize selecting methods based on objectives and data availability, while being aware of the effect of the initial soil carbon level and the assessment time period when using soil carbon simulation models. In addition, this study identified current methodological challenges in assessing soil C dynamics in LCA of agricultural systems. SIGNIFICANCE: This research provides a foundation for improving LCA practices and supports better decision-making in mitigating climate impacts of agricultural systems.