转化式学习
托换
生命周期评估
意外后果
新兴技术
风险分析(工程)
比例(比率)
管理科学
过程管理
计算机科学
工程类
业务
心理学
政治学
经济
生产(经济)
教育学
土木工程
物理
量子力学
人工智能
法学
宏观经济学
作者
Shelie A. Miller,Gregory A. Keoleian
摘要
Emerging products and technologies pose unique challenges for the life cycle assessment (LCA) community, given the lack of data and inherent uncertainties regarding their development. An emerging technology that has the potential to be transformative and effect broad-scale change within society, as well as the underpinning assumptions associated with its life cycle, is particularly difficult to analyze. Despite the associated challenges, LCA methods must be developed for transformative technologies. The greatest improvement potential occurs at the early phases of technology development; therefore, prospective LCA results can be used to anticipate potential unintended consequences and develop design pathways that lead to preferential outcomes. This paper identifies and categorizes ten factors that influence the LCA results of transformative technologies in order to provide a formal structure for determining appropriate factors for inclusion within an LCA. Appropriate factors for an analysis should be selected according to the overall research questions of the study and are applicable to both attributional and consequential approaches to LCA.
科研通智能强力驱动
Strongly Powered by AbleSci AI