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Three Strategies to Overcome the Limitations of Life‐Cycle Assessment
Author(s) -
Haes Helias A. Udo,
Heijungs Reinout,
Suh Sangwon,
Huppes Gjalt
Publication year - 2004
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1162/1088198042442351
Subject(s) - toolbox , industrial ecology , computer science , flexibility (engineering) , life cycle assessment , scope (computer science) , risk analysis (engineering) , resource (disambiguation) , relation (database) , consistency (knowledge bases) , data science , management science , systems engineering , sustainability , data mining , artificial intelligence , production (economics) , engineering , ecology , business , computer network , statistics , mathematics , macroeconomics , economics , biology , programming language
Summary Many research efforts aim at an extension of life‐cycle assessment (LCA) in order to increase its spatial or temporal detail or to enlarge its scope. This is an important contribution to industrial ecology as a scientific discipline, but from the application viewpoint other options are available to obtain more detailed information, or to obtain information over a broader range of impacts in a life‐cycle perspective. This article discusses three different strategies to reach these aims: (1) extension of LCA—one consistent model; (2) use of a toolbox—separate models used in combination; and (3) hybrid analysis—combination of models with data flows between them. Extension of LCA offers the most consistent solution. Developments in LCA are moving toward greater spatial detail and temporal resolution and the inclusion of social issues. Creating a supertool with too many data and resource requirements is, however, a risk. Moreover, a number of social issues are not easily modeled in relation to a functional unit. The development of a toolbox offers the most flexibility regarding spatial and temporal information and regarding the inclusion of other types of impacts. The rigid structure of LCA no longer sets limits; every aspect can be dealt with according to the logic of the relevant tool. The results lack consistency, however, preventing further formal integration. The third strategy, hybrid analysis, takes up an intermediate position between the other two. This strategy is more flexible than extension of LCA and more consistent than a toolbox. Hybrid analysis thus has the potential to combine the strong points of the other two strategies. It offers an interesting path for further discovery, broader than the already well‐known combination of process‐LCA and input‐output‐LCA. We present a number of examples of hybrid analysis to illustrate the potentials of this strategy. Developments in the field of a toolbox or of hybrid analysis may become fully consistent with LCA, and then in fact become part of the first solution, extension of LCA.