Soybean is a major vegetable protein crop often considered to be a sustainable alternative to animal products. Assessments of soybean sustainability often resort to Life Cycle Assessments (LCAs), which are difficult to compare due to methodological inconsistencies. This study carried out an innovative method for harmonized comparisons of soybean production between farms assessed in different studies. Rather than collecting LCA results, we collected Life Cycle Inventories (LCIs) and then calculated the global warming potential (GWP) and land use impacts of each farm. For this, we carried out a systematic review following the PRISMA methodology to collect LCI data from 19 studies representing 126 farms in six countries. A comparable analysis of the farms showed a higher variability in GWP (0.27–1.53 kg CO2e/kg of soybean) than previous reviews, but within a range similar to the results of original studies. As the same LCA method and data were used for all cases, this range can be explained by differences between production systems and locations, with a minimum contribution from methodological variability. Farms in Iran and the United States exhibited the highest emissions, primarily driven by synthetic fertilizer use, irrigation, and energy use. Using results from original studies, farms in Iran showed a substantially lower GWP. Farms in Brazil showed lower non-biogenic greenhouse gas emissions but the highest soil biotic capacity loss due to land occupation, while Italian farms demonstrated minimal land use impacts. These findings underscore the need for region-specific mitigation strategies, despite being limited by data gaps on residue management, the global representativity of the sample of farms, and a lack of detail in fertilizer and irrigation data. There is a pressing need for more complete reporting of LCA study results.
A systems-level understanding of livestock production and its environmental consequences is essential for informing sustainability transitions and evidence-based policy in Europe. While life cycle assessment (LCA) is widely applied in this context, the use of consequential LCA (CLCA), which aims to capture market-mediated and structural system responses, remains comparatively limited. This study provides a critical synthesis of CLCA applications in European livestock systems through a PRISMA-guided systematic literature review complemented by an expert workshop. Twenty-three studies met the inclusion criteria, spanning multiple livestock groups, regions, and modelling approaches. Scenario development was dominated by technical or management-oriented adjustments, with limited use of optimisation-based, narrative, or policy-driven frameworks capable of exploring transformative system changes. Inventory construction typically relied on Ecoinvent, supplemented where necessary by experimental datasets, expert elicitation, survey data, or outputs from economic models. Most studies focused on midpoint indicators, and although uncertainty analysis was commonly included, its implementation was inconsistent across studies. Overall, most of the reviewed CLCA applications remain focused on incremental improvements within existing systems, limiting their ability to assess the consequences of more profound system transitions. Key limitations include both methodological challenges (particularly in scenario formulation and the representation of system-wide responses) and data gaps, notably the limited availability of regionally specific inventory data for marginal processes and endpoint characterisation factors. We recommend that future CLCAs adopt more structured and forward-looking scenario development approaches, strengthen inventory construction through updated and localised datasets, and consider the incorporation of both midpoint and endpoint indicators, while clearly acknowledging the limitations of both approaches. In addition, the systematic application of sensitivity and scenario-based uncertainty analysis is essential for assessing robustness. Addressing these practical and methodological dimensions will enhance the contribution of CLCA to analysing sustainability transitions of European livestock systems.
About Me
Doctoral candidate in Environmental Engineering @ Instituto Superior Técnico, Universidade de Lisboa.
Doctoral candidate in Environmental Engineering @ Instituto Superior Técnico, Universidade de Lisboa.