This analysis finds variations in greenhouse gas emission multipliers for machinery in South Korea, suggesting inconsistencies in LCA and EEIO models.
Environmental impact assessments of machinery and equipment (ME) are constrained by process-based life cycle assessment (LCA) with limited system coverage and by aggregated top-down models with reduced representativeness. Lack of knowledge about consistency across these approaches hampers the understanding of ME impacts and policy making. This study quantifies greenhouse gas emission multipliers (cradle-to-gate emissions per unit production) of ME using data from process LCA (ecoinvent), national environmentally extended input-output (EEIO) models, and a multiregional EEIO model (EXIOBASE) for the United States, China, Japan, and South Korea, assessing variations, reliability, and compatibility. While EXIOBASE (seven ME sectors) and national EEIO data (32-102 sectors) broadly align, national EEIO models differ more in production technologies, with deviations from 100-fold lower to 3.7-fold higher than EXIOBASE results. Ecoinvent offers broad ME product-level coverage (∼390 sectors), especially for general and electrical ME, but with uneven representation and limited geographic differentiation. Its multipliers vary widely and often exceed EXIOBASE values, challenging the assumption that process-based LCA underestimates impacts due to truncation. Overall, our results reveal cross-model variation, confirm the relative reliability of EEIO data, point to limitations in ecoinvent, and underscore the need to link technical detail with global trade representation in ME modeling.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: