In response to Japan’s national goal of a 46% reduction in greenhouse gas (GHG) emissions from the 2013 level by 2030, the deployment of renewable electricity and electric vehicles is accelerating. Consequently, power-conditioning devices such as inverters are now expected to minimize their life-cycle impacts. In the life cycle assessment (LCA) of electronic products, the principal contributors are the use stage (Category 11, CAT11) and Purchased goods and services during manufacturing (Category 1, CAT1) defined by the GHG Protocol. While CAT11 emissions are expected to decrease with the increased share of renewable energy sources in the electricity mix, reducing CAT1 emissions requires eco-design guided by dynamic LCA that reflects future shifts in the electricity generation mix. CAT1 accounting assigns a static cradle-to-gate emission factor to each bill of materials (BOM) item. However, emission factors are derived from multilayered tree structures encompassing components, materials, and manufacturing electricity, so when emission coefficients change, recalculating the entire tree becomes computationally intensive. We therefore propose a graph-based model in which BOM items, emission factors, and the electricity coefficient are represented as nodes linked by directed edges, enabling efficient propagation and automatic recalculation of emission changes. Applying the model to a 200 V industrial inverter with Japan’s projected 2030 electricity mix revealed a 24% shortfall relative to the reduction target. Based on the emission analysis, attention was focused on the housing and cooling components whose modification is expected to exert only minor influence on power-system control. Replacing 60% of the virgin material in these parts with recycled material closes the gap and brings the inverter into line with the national 2030 GHG objective. The proposed framework therefore presents a practical, data-driven pathway for eco-design under dynamic LCA conditions.
Kobayashi et al. (Thu,) studied this question.