A parametric LCA platform for modelling environmental impacts in plant protein processing: Application to pea, soy, and wheat protein isolates and concentrates

The central dietary role of proteins and the high environmental burden of animal-based food require a transition to more sustainable protein sources. Plant protein extracts are the primary commercial alternatives, yet their environmental impacts remain poorly quantified. We present the first regionalized life cycle assessment of soy, pea, and wheat proteins, based on a harmonized modelling platform to evaluate 19 global value chains supplying the European market. The model relies on fully parameterized foreground inventories to assess the uncertainty and model sensitivity related to variable process efficiencies, methodological choices (e.g., economic allocation), and transport distances through Monte-Carlo analysis. Water stress, health impacts through particulate matter emissions, and land-use-related biodiversity loss were quantified based on country-specific characterization factors along with global warming impacts. Resulting environmental impacts vary by up to three orders of magnitude. These wide ranges underscore how regional factors like energy systems and climatic conditions critically determine environmental footprints, necessitating transparency for downstream manufacturers. Additionally, results for single value chains varied by a factor of 1.5 to 3, highlighting the relevance of efficient process design for minimizing environmental impacts. A global sensitivity analysis reveals that protein content in raw materials, extraction yields, renewable energy, and transport are the primary leverage points for reducing impacts across all value chains. Our publicly available modelling platform and dataset can readily be applied to other plant protein value chains to optimize protein processing in the future.