Quantifying spatially explicit LCA midpoint characterization factors to assess the impact of specific farming practices on ecosystem services

Abstract

The Life Cycle Assessment (LCA) methodology is a scientifically sound tool, endorsed by the European Commission, for conducting environmental assessments. Despite its standardized approach, certain areas require improvement, particularly concerning impacts on ecosystem structure, function, and associated ecosystem services. Given the significant pressure of agriculture on global ecosystems, research has attempted to establish characterization factors (CFs) that reflect the impact of agricultural practices on ecosystem services. However, the current CFs lack precision and are unable to differentiate between the various types and intensities of agricultural management. This study aims to contribute to the evolving LCA field by introducing novel CFs that allow for the assessment of the impacts and benefits of growing wheat under different agricultural practices on three ecosystem services: water purification, soil erosion control, and carbon sequestration. Spatially explicit, nonlinear models (InVEST and RothC) were used, with the Galician region of northwestern Spain as the spatial setting. The quantified CFs indicated that wheat cultivated with conventional tillage, straw removal and without cover crop exhibited the least favorable outcomes in terms of ecosystem service supply, specifically water purification (13.29 kg N·ha⁻¹·y^-1), soil erosion control (11.71 t soil·ha⁻¹·y^-1), and carbon sequestration (45.41 t C·ha⁻¹·y^-1). In contrast, the combination of conservation tillage, straw return and cover crop resulted in the highest ecosystem services gains (−0.46 kg N·ha⁻¹·y^-1, 2.64 t soil·ha⁻¹·y^-1, 7.05 t C·ha⁻¹·y^-1, respectively). The geographical specificity of the CFs presented here, combined with the detailed classification of agricultural land use, offers essential insights into the potential gains and losses of ecosystem services resulting from various farming practices. This information can assist industry stakeholders and policymakers in making well-informed agricultural management decisions, and in developing strategies that prevent unintended environmental burden shifting.