Contribution-based prioritization of LCI database improvements: the most important unit processes in ecoinvent

Purpose Improving the quality and quantity of unit process datasets in Life Cycle Inventory (LCI) databases affects every LCA they are used in. However, improvements in data quality and quantity are so far rather directed by the external supply of data and situation-driven requirements instead of sy...

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Veröffentlicht in:The international journal of life cycle assessment 2019-10, Vol.24 (10), p.1778-1792
Hauptverfasser: Reinhard, Juergen, Wernet, Gregor, Zah, Rainer, Heijungs, Reinout, Hilty, Lorenz M.
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container_end_page 1792
container_issue 10
container_start_page 1778
container_title The international journal of life cycle assessment
container_volume 24
creator Reinhard, Juergen
Wernet, Gregor
Zah, Rainer
Heijungs, Reinout
Hilty, Lorenz M.
description Purpose Improving the quality and quantity of unit process datasets in Life Cycle Inventory (LCI) databases affects every LCA they are used in. However, improvements in data quality and quantity are so far rather directed by the external supply of data and situation-driven requirements instead of systematic choices guided by structural dependencies in the data. Overall, the impact of current data updates on the quality of the LCI database remains unclear and maintenance efforts might be ineffective. This article analyzes how a contribution-based prioritization approach can direct LCI update efforts to datasets of key importance. Methods A contribution-based prioritization method has been applied to version 3 of the ecoinvent database. We identified the relevance of unit processes on the basis of their relative contributions throughout each product system with respect to a broad range of Life Cycle Impact Assessment (LCIA) indicators. A novel ranking algorithm enabled the ranking of unit processes according to their impact on the LCIA results. Finally, we identified the most relevant unit processes for different sectors and geographies. Results and discussion The study shows that a relatively large proportion of the overall database quality is dependent on a small set of key processes. Processes related to electricity generation, waste treatment activities, and energy carrier provision (petroleum and hard coal) consistently cause large environmental impacts on all product systems. Overall, 300 datasets are causing 60% of the environmental impacts across all LCIA indicators, while only 3 datasets are causing 11% of all climate change impacts. In addition, our analysis highlights the presence and importance of central hubs, i.e., sensitive intersections in the database network, whose modification can affect a large proportion of database quality. Conclusions Our study suggests that contribution-based prioritization offers important insights into the systematic and effective improvement of LCI databases. The presented list of key processes in ecoinvent version 3.1 adds a new perspective to database improvements as it allows the allocation of available resources according to the structural dependencies in the data.
doi_str_mv 10.1007/s11367-019-01602-0
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However, improvements in data quality and quantity are so far rather directed by the external supply of data and situation-driven requirements instead of systematic choices guided by structural dependencies in the data. Overall, the impact of current data updates on the quality of the LCI database remains unclear and maintenance efforts might be ineffective. This article analyzes how a contribution-based prioritization approach can direct LCI update efforts to datasets of key importance. Methods A contribution-based prioritization method has been applied to version 3 of the ecoinvent database. We identified the relevance of unit processes on the basis of their relative contributions throughout each product system with respect to a broad range of Life Cycle Impact Assessment (LCIA) indicators. A novel ranking algorithm enabled the ranking of unit processes according to their impact on the LCIA results. Finally, we identified the most relevant unit processes for different sectors and geographies. Results and discussion The study shows that a relatively large proportion of the overall database quality is dependent on a small set of key processes. Processes related to electricity generation, waste treatment activities, and energy carrier provision (petroleum and hard coal) consistently cause large environmental impacts on all product systems. Overall, 300 datasets are causing 60% of the environmental impacts across all LCIA indicators, while only 3 datasets are causing 11% of all climate change impacts. In addition, our analysis highlights the presence and importance of central hubs, i.e., sensitive intersections in the database network, whose modification can affect a large proportion of database quality. Conclusions Our study suggests that contribution-based prioritization offers important insights into the systematic and effective improvement of LCI databases. 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The presented list of key processes in ecoinvent version 3.1 adds a new perspective to database improvements as it allows the allocation of available resources according to the structural dependencies in the data.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s11367-019-01602-0</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record>
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subjects Algorithms
Climate change
Data Availability
Data Quality
Datasets
Earth and Environmental Science
Environment
Environmental Chemistry
Environmental Economics
Environmental Engineering/Biotechnology
Environmental impact
Indicators
Intersections
Life cycle assessment
Life cycles
Meta-analysis
Quality
Ranking
Waste treatment
title Contribution-based prioritization of LCI database improvements: the most important unit processes in ecoinvent
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