在生命周期库存数据系统中进行基本的流量映射:在全球生命周期评估数据访问 (GLAD) 倡议下的数据互操作性的案例研究
Antonio Valente1, Carl Vadenbo2, Simone Fazio1
1European Commission, Joint Research Centre, Directorate D-Sustainable Resources, 21027 Ispra (VA), Italy.
概括
全球生命周期评估数据访问 (GLAD) 网络开发了一种高效的映射程序,以改善生命周期评估 (LCA) 数据的可访问性. 这一过程实现了主要分类系统之间的90%以上的映射覆盖率,为LCA从业者增强了数据互操作性.
科学领域:
- 环境科学 环境科学
- 数据科学数据科学数据科学
- 可持续发展 可持续发展 可持续发展
背景情况:
- 生命周期评估 (LCA) 数据的有限可用性和互操作性阻碍了其广泛采用.
- 全球LCA数据访问 (GLAD) 网络旨在通过改善LCA数据可访问性来应对这些挑战.
- 规范命名对于一致和可靠的LCA数据至关重要.
研究的目的:
- 介绍GLAD编号工作组 (NWG) 开发的用于绘制基本流动的方法方法.
- 提高LCA数据在不同命名体系中的可访问性和互操作性.
- 为了促进对LCA数据管理的更统一的方法.
主要方法:
- 开发了一种多步骤的映射程序,包括与双边审查相匹配的流量和隔间.
- 使用了由欧洲委员会开发的免费软件"GLAD Mapper Tool".
- 绘制了四个主要的命名系统:ecoinvent,环境足迹,IDEA和美国联邦LCA Commons.
主要成果:
- 在几次代后,在命名系统之间实现了超过90%的映射覆盖率.
- 该程序被证明对LCA从业者来说是有效的,这是由独特的物质识别和隔间颗粒度驱动的.
- 由于缺乏完美的流量等价性,需要近似匹配 (代理匹配).
结论:
- GLAD映射方法为影响评估方法和数据集的中央枢纽提供了基础.
- 增强的数据可访问性和互操作性有助于更统一的LCA命名体系.
- 开放和透明的方法促进了LCA社区内的可追溯性和协作.
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