Rethinking the area of protection "natural resources" in life cycle assessment.

Life cycle impact assessment (LCIA) in classical life cycle assessment (LCA) aims at analyzing potential impacts of products and services typically on three so-called areas of protection (AoPs): Natural Environment, Human Health, and Natural Resources. This paper proposes an elaboration of the AoP Natural Resources. It starts with analyzing different perspectives on Natural Resources as they are somehow sandwiched in between the Natural Environment (their cradle) and the human-industrial environment (their application). Reflecting different viewpoints, five perspectives are developed with the suggestion to select three in function of classical LCA. They result in three safeguard subjects: the Asset of Natural Resources, their Provisioning Capacity, and their role in Global Functions. Whereas the Provisioning Capacity is fully in function of humans, the global functions go beyond provisioning as they include nonprovisioning functions for humans and regulating and maintenance services for the globe as a whole, following the ecosystem services framework. A fourth and fifth safeguard subject has been identified: recognizing the role Natural Resources for human welfare, either specifically as building block in supply chains of products and services as such, either with or without their functions beyond provisioning. But as these are far broader as they in principle should include characterization of mechanisms within the human industrial society, they are considered as subjects for an integrated sustainability assessment (LCSA: life cycle sustainability assessment), that is, incorporating social, economic and environmental issues.

Background qualitative analysis of the European Reference Life Cycle Database (ELCD) energy datasets - part I: fuel datasets.

INTRODUCTION: The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. CASE DESCRIPTION: The revision is based on the data quality indicators described by the ILCD Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. DISCUSSION AND EVALUATION: Results show that ELCD fuel datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the fuel-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. CONCLUSIONS: Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD fuel datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall DQR of databases.

Method applied to the background analysis of energy data to be considered for the European Reference Life Cycle Database (ELCD).

Under the framework of the European Platform on Life Cycle Assessment, the European Reference Life-Cycle Database (ELCD - developed by the Joint Research Centre of the European Commission), provides core Life Cycle Inventory (LCI) data from front-running EU-level business associations and other sources. The ELCD contains energy-related data on power and fuels. This study describes the methods to be used for the quality analysis of energy data for European markets (available in third-party LC databases and from authoritative sources) that are, or could be, used in the context of the ELCD. The methodology was developed and tested on the energy datasets most relevant for the EU context, derived from GaBi (the reference database used to derive datasets for the ELCD), Ecoinvent, E3 and Gemis. The criteria for the database selection were based on the availability of EU-related data, the inclusion of comprehensive datasets on energy products and services, and the general approval of the LCA community. The proposed approach was based on the quality indicators developed within the International Reference Life Cycle Data System (ILCD) Handbook, further refined to facilitate their use in the analysis of energy systems. The overall Data Quality Rating (DQR) of the energy datasets can be calculated by summing up the quality rating (ranging from 1 to 5, where 1 represents very good, and 5 very poor quality) of each of the quality criteria indicators, divided by the total number of indicators considered. The quality of each dataset can be estimated for each indicator, and then compared with the different databases/sources. The results can be used to highlight the weaknesses of each dataset and can be used to guide further improvements to enhance the data quality with regard to the established criteria. This paper describes the application of the methodology to two exemplary datasets, in order to show the potential of the methodological approach. The analysis helps LCA practitioners to evaluate the usefulness of the ELCD datasets for their purposes, and dataset developers and reviewers to derive information that will help improve the overall DQR of databases.

Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.