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Abstract. On May 25-26, 2000 in Brighton (England), the third in a series of international workshops was held under the umbrella of UNEP addressing issues in Life Cycle Impact Assessment (LCIA). The workshop provided a forum for experts to discuss midpoint vs. endpoint modeling. Midpoints are considered to be links in the cause-effect chain (environmental mechanism) of an impact category, prior to the endpoints, at which characterization factors or indicators can be derived to reflect the relative importance of emissions or extractions. Common examples of midpoint characterization factors include ozone depletion potentials, global warming potentials, and photochemical ozone (smog) creation potentials. Recently, however, some methodologies have adopted characterization factors at an endpoint level in the cause-effect chain for all categories of impact (e.g., human health impadts in terms of disability adjusted life years for carcinogenicity, climate change, ozone depletion, photochemical ozone creation; or impacts in terms of changes in biodiversity, etc.). The topics addressed at this workshop included the implications of midpoint versus endpoint indicators with respect to uncertainty (parameter, model and scenario), transparency and the ability to subsequently resolve trade-offs across impact categories using weighting techniques. The workshop closed with a consensus that both midpoint and endpoint methodologies provide useful information to the decision maker, prompting the call for tools that include both in a consistent framework.

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Conclusions and Outlook.The present framework will offer the practitioner the choice to use either midpoint or damage indicators, depending on modelling uncertainty and increase in results interpretability. Due to the collaboration of acknowledged specialists in environmental processes and LCIA around the globe, it is expected that -after a few years of effort -the task forces of the Life Cycle Initiative will provide consistent and operational sets of methods and factors for LCIA in the future. and damage-oriented methods aiming at more easily interpretable results in the form of damage indicators at the level of the ultimate societal concern (e.g. human health damage). The Life Cycle Initiative, a joint project between UNEP 1 and SETAC 2 , proposes a comprehensive LCA framework to combine these families of methods. The new framework takes a world-wide perspective, so that LCA will progress towards a tool meeting the needs of both developing and developed countries. By a more precise and broadly agreed description of main framework elements, the Life Cycle Initiative expects to provide a common basis for the further development of mutually consistent impact assessment methods.

Purpose The ISO 14044 standard for life cycle assessment (LCA) provides the reference decision hierarchy for dealing with multi-functional processes. We observe that, in practice, the consistent implementation of this hierarchy by LCA practitioners and LCA guidance document developers may be limited. In an attempt to explain this observation, and to offer suggestions as to how consistency in LCA practice might be improved, we identify and compare the rationales for (and limitations of) different common approaches to solving multifunctionality problems in LCA. Methods The different prevalent understandings of specific approaches for dealing with multi-functional processes were identified, and their respective rationales were analyzed. This takes into account identifying the implicit underlying assumptions regarding the nature and purpose of LCA that support each approach. Results and discussion We identified what we believe to be three internally consistent but mutually exclusive schools of thought amongst LCA practitioners, which differ in subtle but important ways in terms of their understanding of the nature and purpose of LCA, and the multi-functionality solutions necessary to support them. These three divisions follow two demarcations. The first is between consequential and attributional data modeling approaches. The second is between adherence to a natural science-based approach (privileging physical allocation solutions) and a socioeconomic approach (favoring economic allocation solutions) in attributional data modeling. Conclusions We conclude that the ISO 14044 multifunctionality hierarchy should explicitly differentiate between attributional and consequential data modeling applications. We question the feasibility and practical utility of system expansion (currently privileged in the ISO hierarchy) in attributional data modeling applications. We suggest that ISO 14044 should also make explicit its rationale for privileging natural science-based approaches to solving multifunctionality problems and to more clearly differentiate between natural science and social science-based approaches. We also call for the formulation of additional guidance for solving multi-functionality problems, in particular for justifying the use of lower-tier solutions from the ISO hierarchy when these are applied in LCA studies. We suggest that this additional guidance and clarity in ISO 14044 will contribute to increased consistency in LCA practice and also increase the potential for users of information from LCA studies to make informed decisions as to their relevance within the context of specific intended applications.

Multimedia fate and multipathway human exposure models are widely adopted in assessments of toxicological risks of chemical emissions at the regional scale. This paper addresses the question of how much spatial detail is necessary in such models when estimating the intake by the entire population in large, heterogeneous regions such as Europe. The paper presents a spatially resolved multimedia fate and multipathway exposure model for Western Europe, available as IMPACT 2002. This model accounts for relationships between the location of food production and drinking water extraction as well as where population cohorts live relative to where chemical emissions occur. The model facilitates estimation of environmental concentration distributions, related levels of contaminants in foods, and the fraction of a chemical release that will be taken in by the entire human population (the intake fraction) at the regional scale. To evaluate the necessary spatial resolution, the paper compares estimates of environmental concentrations and the intake fraction from the spatially resolved model with the results of a consistent clone without spatial resolution. An evaluation for disperse emissions of PeCDF (2,3,4,7,8-pentachlorodibenzofuran, CAS# 5120731-4) suggests reasonable agreement with monitoring data for most impact pathways with both versions of the model, but that the generic vegetation models for estimating contaminant concentrations in agricultural produce require improvement. A broader comparison for a range of organic chemicals demonstrates that the nonspatial models are likely to be appropriate in general for assessing dispersed sources of emissions. However, it is necessary to include generic compartments in such nonspatial models to account separately for emissions that enter lakes with long residence times versus rivers that feed directly into seas. For assessing an emission source in a specific location, using models that are not spatially resolved can result in underestimation, or overestimation, of the population's intake by at least 3 orders of magnitude for some chemicals.