Abiotic resource use in life cycle impact assessment : part I : towards a common perspective

At the beginning of the SUPRIM project, there was no global consensus on the assessment of impacts from the use of abiotic resources (minerals and metals), in life cycle impact assessment (LCIA). Unlike with other impact categories such as global warming, there is not just one single, explicitly agreed-upon problem arising from the use of abiotic resources. The topic is complex and new methods are still being developed, all with different perspectives and views on resource use. For this reason, the SUPRIM project initiated a consensus process together with members from the research and mining communities, with the aim to obtain an understanding of different stakeholders’ views and concerns regarding potential issues resulting from the use of resources. This paper reports on this consensus process and its outcomes. Insights from this process are twofold: First, the outcome of the process is a clear definition of the perspectives on abiotic resources which form the starting point to further refine or develop LCIA methods on abiotic resource use. Second, the process itself has been a challenging but valuable exercise, which can inspire the evolution of other complex issues in life cycle impact assessment, where research communities face similar issues as experienced with abiotic resources (e.g. water and land use, social LCA, etc.)

Abiotic resource use in life cycle impact assessment : part II : Linking perspectives and modelling concepts

Starting from a lack of consensus on how to consistently assess abiotic resource use in life cycle assessment, a structured approach was developed to enable a classification of perspectives on resource use, based on the socalled role of resources. Using this classification, this paper focusses on analysing links between perspectives and modelling concepts, i.e. the conceptual implementation. To analyse the modelling concepts for a selection of existing LCIA methods and other modelling approaches, the concept of the system model is introduced. It defines the relevant inventory flows to be assessed by the LCIA method, and, at the same time, to be considered in the characterization model, and how the flows and stocks of resources used to calculate the characterization factors are positioned in relation to environment (nature) and economy (technosphere). For consistency, they should be aligned with the position of inventory flows and, at the same time, reflect the perspective on resources taken by the method. Using this concept, we critically review a selection of methods and other modelling approaches for consistency with the perspectives on resource use, as well as for their internal consistency. As a result of the analysis, we highlight inconsistencies and discuss ways to improve links between perspectives and modelling concepts. To achieve this, the new framework can be used for the development or improvement of LCIA methods on resource use

Bringing science and pragmatism together a tiered approach for modelling toxicological impacts in LCA

Goal, Scope and Background: The EU 5th framework project OMNIITOX will develop models calculating characterisation factors for assessing the potential toxic impacts of chemicals within the framework of LCA. These models will become accessible through a web-based information system. The key objective of the OMNIITOX project is to increase the coverage of substances by such models. In order to reach this objective, simpler models which need less but available data, will have to be developed while maintaining scientific quality. Methods. Experience within the OMNIITOX project has taught that data availability and quality are crucial issues for calculating characterisation factors. Data availability determines whether calculating characterisation factors is possible at all, whereas data quality determines to what extent the resulting characterisation factors are reliable. Today, there is insufficient knowledge and/or resources to have high data availability as well as high data quality and high model quality at the same time. Results: The OMNIITOX project is developing two inter-related models in order to be able to provide LCA impact assessment characterisation factors for toxic releases for as broad a range of chemicals as possible: 1) A base model representing a state-of-the-art multimedia model and 2) a simple model derived from the base model using statistical tools. Discussion. A preliminary decision tree for using the OMNIITOX information system (IS) is presented. The decision tree aims to illustrate how the OMNIITOX IS can assist an LCA practitioner in finding or deriving characterisation factors for use in life cycle impact assessment of toxic releases. Conclusions and Outlook: Data availability and quality are crucial issues when calculating characterisation factors for the toxicity impact categories. The OMNIITOX project is developing a tiered model approach for this. It is foreseen that a first version of the base model will be ready in late summer of 2004, whereas a first version of the simple base model is expected a few months late

Characterisation model approach for LCA to estimate land use impacts on pollinator abundance and illustrative characterisation factors

This study presents the first approach to characterise relative land use impacts on pollinator abundance for life cycle assessment (LCA). Pollinators make an essential contribution to global crop production and in recent years evidence of declines has raised concerns on how land use, among other factors, affects pollinators. Our novel method assesses land use impacts on pollinator abundance and proposes a new impact category that is compatible with the current framework of life cycle impact assessment (LCIA). While a systematic literature research showed the existence of multiple models that could assess pollinator abundance impacts, their parameterization is too complicated for applications in LCA. Therefore, a simplified method based on expert knowledge is presented. The practical application of the method is illustrated through the connection to, and characterisation of, relevant land use types derived from the widely used LCA database, ecoinvent. The illustrative characterisation factors demonstrate that key differences among land use types can be reflected through the proposed approach. Further development of robust characterisation factors through a larger sample of pollinator abundance estimates, and improvements to the model, such as considerations of spatial differentiation, will contribute to the identification of impacts of agricultural practices in LCA studies, helping prevent further pollinator abundance decline

Correction to: Waste is not a service

The original version of this article unfortunately contained a mistake which was missed during typesetting. In both Figs. 1 and 2 several lines were missing arrowheads. The correct versions of Figs. 1 and 2 are given below. The original article has been corrected