Purpose: Life cycle assessment (LCA) studies have overlooked the potential range of biochar’s effects on agricultural soils. Only several of the numerous soil effects reported in empirical studies have been included in LCA models. This study aims to establish a consistent lifecycle inventory (LCI) approach to include biochar’s soil effects in LCA and assess the conceptual applicability of LCA to model soil effects. Methods: To exemplify this approach, a case study was conducted, which also provides insight into the environmental implications of biochar’s soil effects and whether LCA results can help guide biochar optimization for greater environmental benefits. For soil effects that met all inclusion criteria, empirical data was selected based on controlling factors and translated into inventory data. The LCI approach was applied to a case study in Aguascalientes, a semi-arid state in central Mexico that suffers from droughts. Results: The combined soil effects have a substantial overall impact across all impact categories, mostly dwarfing upstream biochar production and treatment impacts. This is driven by the persistent soil effects; the transient soil effects contribute far less. Biochar primarily leads to a net environmental benefit in an impact category, strongly depending on the soil effect literature data that is selected. While some soil effects have been researched sufficiently to produce sensible meta-analyses (e.g. crop yield increase), others have only been quantified a handful of times or solely qualitatively assessed (e.g. fire hazard increase). Most soil effects have a non-intermediate impact and can be modelled as intervention or economic flow in some form, with some missing appropriate characterization models. Biochar’s soil effects have a substantial environmental effect and cannot be ignored. A highly accurate inclusion of soil effects in LCA is hindered by several conceptual (non-linearity of soil effect expression, missing characterization models, focus on environmental impact) but mostly data-related (availability of long-term empirical field data) constraints. Conclusion: Although the results varied across scenarios due to differences in model assumptions and uncertainties, they provided in order of magnitude trends that still allowed for informed conclusions on how to tailor biochar in Aguascalientes to maximize environmental benefits while minimizing associated risks (e.g. increasing pyrolysis temperature to reduce PAH content).