Analyzing Temporal Variability in Inventory Data for Life Cycle Assessment: Implications in the Context of Circular Economy

Sustainability

FarazeeM. A. Asif¹  Malvina Roci¹  Amir Rashid¹  Niloufar Salehi¹  Sayyed Shoaib-ul-Hasan¹ 

[1] Department of Production Engineering, KTH Royal Institute of Technology, Brinellvägen 68, 100 44 Stockholm, Sweden;

关键词: life cycle assessment;    circular economy;    multiple product life cycles;    temporal variability;    life cycle inventory;    emission intensity;   

DOI  :  10.3390/su13010344

来源: DOAJ

【 摘 要 】

Life cycle assessment (LCA) is used frequently as a decision support tool for evaluating different design choices for products based on their environmental impacts. A life cycle usually comprises several phases of varying timespans. The amount of emissions generated from different life cycle phases of a product could be significantly different from one another. In conventional LCA, the emissions generated from the life cycle phases of a product are aggregated at the inventory analysis stage, which is then used as an input for life cycle impact assessment. However, when the emissions are aggregated, the temporal variability of inventory data is ignored, which may result in inaccurate environmental impact assessment. Besides, the conventional LCA does not consider the environmental impact of circular products with multiple use cycles. It poses difficulties in identifying the hotspots of emission-intensive activities with the potential to mislead conclusions and implications for both practice and policy. To address this issue and to analyze the embedded temporal variations in inventory data in a CE context, the paper proposes calculating the emission intensity for each life cycle phase. It is argued that calculating and comparing emission intensity, based on the timespan and amount of emissions for individual life cycle phases, at the inventory analysis stage of LCA offers a complementary approach to the traditional aggregate emission-based LCA approach. In a circular scenario, it helps to identify significant issues during different life cycle phases and the relevant environmental performance improvement opportunities through product, business model, and supply chain design.

【 授权许可】

Unknown