Deriving life cycle assessment coefficients for application in integrated assessment modelling
Deriving life cycle assessment coefficients for application in integrated assessment modelling
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DOI：
10.1016/j.envsoft.2017.09.010
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发表时间：
2018-01-01
影响因子：
4.9
通讯作者：
Hertwich, Edgar G.
中科院分区：
文献类型：
--
作者：
Arvesen, Anders;Luderer, Gunnar;Hertwich, Edgar G.
今天，生命周期评估和综合评估建模领域在评估宏观层面的转型途径方面具有类似的兴趣，并对环境问题有着广泛的看法。流行的IA模型缺乏生命周期的观点，而LCA传统上是静态的和面向微观的。我们开发了一种通用的方法，用于从详细的，自下而上的LCA适用于IA模型中的应用系数，从而使IA分析师探索技术和方案的替代品的生命周期的影响。该方法将LCA系数分解为生命周期阶段和各行业的能源载体使用情况，从而便于将生命周期影响归因于适当年份，并在将LCA系数应用于IA情景建模时，一致和全面地使用IA模型特定情景数据。我们演示了该方法的应用，全球电力供应到2050年，并提供数值结果（作为补充材料），供IA分析师未来使用。(C)2017爱思唯尔有限公司版权所有
The fields of life cycle assessment (LCA) and integrated assessment (IA) modelling today have similar interests in assessing macro-level transformation pathways with a broad view of environmental concerns. Prevailing IA models lack a life cycle perspective, while LCA has traditionally been static-and micro-oriented. We develop a general method for deriving coefficients from detailed, bottom-up LCA suitable for application in IA models, thus allowing IA analysts to explore the life cycle impacts of technology and scenario alternatives. The method decomposes LCA coefficients into life cycle phases and energy carrier use by industries, thus facilitating attribution of life cycle effects to appropriate years, and consistent and comprehensive use of IA model-specific scenario data when the LCA coefficients are applied in IA scenario modelling. We demonstrate the application of the method for global electricity supply to 2050 and provide numerical results (as supplementary material) for future use by IA analysts. (C) 2017 Elsevier Ltd. All rights reserved.