Partial ordering of life cycle inventory databases

PurposeLife cycle inventory (LCI) databases provide information of fundamental importance to the mainstream practice of life cycle assessment (LCA). Development and management of LCI data resources is a tremendous task. This paper seeks to develop design principles for organizing efforts around distributed database management by considering the structure of inventory networks.MethodsA number of LCI databases in wide use are placed into a partial ordering using graph theoretic techniques. First, strongly connected components, which indicate cyclic dependencies, are identified in each network. Then, those components are collapsed to single nodes, rendering the graphs acyclic. The acyclic graphs are then ordered topologically.Results and discussionLarge databases were found to contain a single large strongly connected component, designated the background, that satisfied dependencies of other processes in the database. Processes with a lower position in the ordering than the background, designated the foreground, depended on inputs from the background in order to operate, but no background processes required inputs from any foreground processes. Processes higher in the order than the background, designated the downstream, satisfied dependencies in the background but did not themselves require the background. Databases sharing a common set of product flows could be compared on the basis of their foreground, background, and downstream segments.Making a distinction between an acyclic foreground and a strongly connected background has computational utility because the foreground and background databases can be managed independently. Describing LCA studies on the basis of their dependence on background product flows would allow them to be easily moved among distinct databases that provide the same products and would also facilitate critical review. Background databases themselves can be broken up by scope into mutually dependent systems that can be independently maintained.ConclusionsLCI database maintainers should consider maintaining the foreground and background components of their databases separately because of the differing implications of modeling decisions made in each of the two cases. A framework for database-independent enumeration of intermediate flows would advance distributed data management.

[1]  Robert E. Tarjan,et al.  Depth-First Search and Linear Graph Algorithms , 1972, SIAM J. Comput..

[2]  Pascal Lesage,et al.  Systematic disaggregation: a hybrid LCI computation algorithm enhancing interpretation phase in LCA , 2012, The International Journal of Life Cycle Assessment.

[3]  Reinout Heijungs,et al.  The computational structure of life cycle assessment , 2002 .

[4]  Gary Moore,et al.  A new data architecture for advancing life cycle assessment , 2015, The International Journal of Life Cycle Assessment.

[5]  T. Nemecek,et al.  Overview and methodology: Data quality guideline for the ecoinvent database version 3 , 2013 .

[6]  Oliver Kusche,et al.  Managing LCI Data from Different Workgroups within the same Instance of an LCA Database , 2012, EnviroInfo.

[7]  Glen P. Peters,et al.  Efficient algorithms for Life Cycle Assessment, Input-Output Analysis, and Monte-Carlo Analysis , 2007 .

[8]  A. B. Kahn,et al.  Topological sorting of large networks , 1962, CACM.

[9]  C. Davis,et al.  Industrial Ecology 2.0 , 2010 .

[10]  Steven B. Young,et al.  Critical review: a summary of the current state-of-practice , 2014, The International Journal of Life Cycle Assessment.

[11]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[12]  Anne-Marie Tillman,et al.  Significance of decision-making for LCA methodology , 2000 .

[13]  Edrisi Muñoz,et al.  Considering environmental assessment in an ontological framework for enterprise sustainability , 2013 .

[14]  Robert E. Tarjan,et al.  Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance , 2011, ACM Trans. Algorithms.

[15]  Sangwon Suh,et al.  Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization , 2013, Soc. Networks.

[16]  John K. Reid,et al.  An Implementation of Tarjan's Algorithm for the Block Triangularization of a Matrix , 1978, TOMS.

[17]  John W. Sutherland,et al.  LCA-oriented semantic representation for the product life cycle , 2015 .

[18]  Reinout Heijungs Topological network theory and its application to LCA and related industrial ecology tools , 2015 .

[19]  Oliver Kusche,et al.  Creating LCA Data Exchange Networks , 2012, EnviroInfo.

[20]  Sangwon Suh,et al.  Generalized Make and Use Framework for Allocation in Life Cycle Assessment , 2010 .

[21]  Christian Leroy Provision of LCI data in the European aluminium industry Methods and examples , 2009 .

[22]  Vasile-Marian Scuturici,et al.  A semantic approach to life cycle assessment applied on energy environmental impact data management , 2012, EDBT-ICDT '12.

[23]  Rainer Zah,et al.  Using non-local databases for the environmental assessment of industrial activities: The case of Latin America , 2010 .

[24]  Bruce Vigon,et al.  Global guidance principles for life cycle assessment databases: development of training material and other implementation activities on the publication , 2013, The International Journal of Life Cycle Assessment.

[25]  Ronald L. Rivest,et al.  Introduction to Algorithms, third edition , 2009 .