Günter Fleischer

Framework for scenario development in LCA

This article is based on the work of the SETAC-Europe LCA Working Group ‘Scenario Development in LCA’, which has started its work in April 1998. The goal of the Working Group is to focus on the use of scenarios in Life Cycle Assessment (LCA). This article presents the results of the first phase of the Working Group. The previous definitions of scenarios include three common basic elements: the definition of alternative future circumstances, the path from the present to the future, and the inclusion of uncertainty in the concept. We define a scenario in LCA as “a description of a possible future situation relevant for specific LCA applications, based on specific assumptions about the future, and (when relevant) also including the presentation of the development from the present to the future.’On the basis of the scenario definition we distinguish between two basic approaches for scenario development in LCA studies: What-if scenarios and Cornerstone scenarios. What-if scenarios are used to gain operational information and to compare two or more alternatives in a well-known situation with a short time horizon where the researcher is familiar with the decision problem and can set defined hypothesis on the basis of existing data. The Cornerstone scenario approach offers strategic information for long term planning, new ways of seeing the world, and also guidelines in the field of study. Results of a study using the Cornerstone scenario approach often serve as a basis for further, more specific research where the scenarios can be defined according to What-if scenarios.The frames of the scenarios are defined in the first phase of LCA, the goal and scope definition. Scenario development does, however, influence all of the following phases of LCA. The frames of the scenarios form the basis for modelling product systems and environmental impacts associated with products and services, which are not exactly known due to lacking information on parts of the life cycle.

Sustainability in manufacturing: Recovery of resources in product and material cycles

Global Framework.- Life Cycle Engineering and Management.- Product Development.- Processes and Tools for Disassembly.- Planning for Remanufacturing and Recycling.- Enabling for Sustainability in Engineering.- Roadmap.

Uncertainty calculation in life cycle assessments

Goal and BackgroundUncertainty is commonly not taken into account in LCA studies, which downgrades their usability for decision support. One often stated reason is a lack of method. The aim of this paper is to develop a method for calculating the uncertainty propagation in LCAs in a fast and reliable manner.ApproachThe method is developed in a model that reflects the calculation of an LCA. For calculating the uncertainty, the model combines approximation formulas and Monte Carlo Simulation. It is based on virtual data that distinguishes true values and random errors or uncertainty, and that hence allows one to compare the performance of error propagation formulas and simulation results. The model is developed for a linear chain of processes, but extensions for covering also branched and looped product systems are made and described.ResultsThe paper proposes a combined use of approximation formulas and Monte Carlo simulation for calculating uncertainty in LCAs, developed primarily for the sequential approach. During the calculation, a parameter observation controls the performance of the approximation formulas. Quantitative threshold values are given in the paper. The combination thus transcends drawbacks of simulation and approximation.Conclusions and OutlookThe uncertainty question is a true jigsaw puzzle for LCAs and the method presented in this paper may serve as one piece in solving it. It may thus foster a sound use of uncertainty assessment in LCAs. Analysing a proper management of the input uncertainty, taking into account suitable sampling and estimation techniques; using the approach for real case studies, implementing it in LCA software for automatically applying the proposed combined uncertainty model and, on the other hand, investigating about how people do decide, and should decide, when their decision relies on explicitly uncertain LCA outcomes-these all are neighbouring puzzle pieces inviting to further work.

Iterative screening LCA in an eco-design tool

A screening and simplified LCA method, is essential necessary to include environmental aspects in the stage of Research and Development (R&D) of products and processes. An interactive, iterative and integrative eco-design tool using the top-down approach in the identification of advanced materials is being developed in a joint project performed by six research institutes. The principles and methods as well as some examples for the validation of the screening LCA as well as its application in eco-design in case studies are presented in this article.

Geographical and technological differences in life cycle inventories shown by the use of process models for waste incinerators part I. technological and geographical differences

Goal and BackgroundGeographical and technological differences in Life Cycle Inventory data are an important source for uncertainty in the result of Life Cycle Assessments. Knowledge on their impact on the result of an LCA is scarce, and also knowledge on how to manage them in an LCA case study.ObjectiveGoal of this paper is to explore these differences for municipal solid waste incinerator plants, and to develop recommendations for managing technological and geographical differences.MethodologyThe paper provides a definition of technological and geographical differences, and analyses their possible impacts. In a case study, the differences are caused intentionally in ‘games’, by virtually transplanting incineration plants to a different location and by changing parameters such as the composition of the waste input incinerated. The games are performed by using a modular model for municipal solid waste incinerator plants. In each case, an LCA including an Impact Assessment is calculated to trace the impact of these changes, and the results are compared.ConclusionsThe conclusions of the paper are two-fold: (1) reduce the differences in inventory data where their impact on the result is high; where it is possible reducing them to a great extent, and the effort for performing the change acceptable; in the case of incineration plants: Adapt the flue gas treatment, especially a possible DeNOx step, to the real conditions; (2) make use of modular process models that allow adapting plant parameters to better meet real conditions, but be aware of possible modelling errors. The paper invites the scientific community to validate the model used for a waste incinerator plant, and suggest putting up similar models for other processes, preferably those of similar relevance for Life Cycle Inventories.

Functional unit for systems using natural raw materials

The necessity of a functional unit, which considers the equality of all benefits, is underlined especially for systems using such natural raw materials as wood.The example of identifying the ecological optimal extent of paper recycling is therefore examined by using the data of 11ASA [1]. It can be shown that the calculated quantity of the ecological optima particularly depend on the selected model of the comparison. In general, a functional unit of LCA should be based on a model which considers all benefits of the compared systems. The additional benefits of forests have to be taken into account as well. Otherwise, no statement concerning the ecological optima is possible.

A semi-quantitative method for the impact assessment of emissions within a simplified life cycle assessment

Intention, Goal and Scope: Dealing with data gaps, data asymmetries, and inconsistencies in life cycle inventories (LCI) is a general prohlem in Life Cycle Assessment (LCA) studies. An approach to deal with these difficulties is the simplification of LCA. A methodology that lowers the requirements for data quality (accuracy) for process emissions within a simplified LCA is introduced in this article. Background: Simplification is essential for applying LCA in the context of design for environment (DfE). The tool euroMat is a comprehensive DfE software tool that is based on a specific, simplified LCA approach, the Iterative Screening LCA (IS-LCA). Within the scope of the IS-LCA, there is a quantitative assessment of energy-related processes, as well as a semi-quantitative assessment of non-energy related emissions which supplement each other. Objectives: The semi-quantitative assessment, which is in the focus of this article, aims at lowering the requirements for the quality of non-energy related emissions data through combined use of qualitative and quantitative inventory data. Methods: Potential environmental impacts are assessed based on ABC-categories for qualities (harmfulness) of emissions and XYZ-categories for quantities of emitted substances. Employing statistical methods assignment rules for the ABC/XYZ-categories were derived from literature data and databases on emissions to air, water, and soil. Statistical tests as well as a DfE case study (comparing the materials aluminum and carbon fiber reinforced epoxy for a lightweight container to be used in an aerospace application) were conducted in order to evaluate the level of confidence and practicality of the proposed, simplified impact assessment. Results: Statistical and technical consistency checks show that the method bears a high level of confidence. Results obtained by the simplified assessment correlate to those of a detailed quantitative LCA. Conclusions: Therefore, the application of the ABC/XYZ-categories (together with the cumulative energy demand) can be considered a practical and consistent approach for determining the environmental significance of products when only incomplete emission data is available. Future Prospects: The statistical base of the method is expanded continuously since it is an integral part of the DfE software tool euroMat, which is currently being further developed. That should foster the application of the method. Outside DfE, the method should also be capable of facilitating simplified LCAs in general.

Geographical and technological differences in Life Cycle Inventories shown by the use of process models for waste incinerators

Goal and BackgroundGeographical and technological differences in Life Cycle Inventory data are an important source for uncertainty in the result of Life Cycle Assessments. Knowledge on their impact on the result of an LCA is scarce, and also knowledge on how to manage them in an LCA case study.ObjectiveGoal of this paper is to explore these differences for municipal solid waste incinerator plants, and to develop recommendations for managing technological and geographical differences.MethodologyThe paper provides a definition of technological and geographical differences, and analyses their possible impacts. In a case study, the differences are caused intentionally in ‘games’, by virtually transplanting incineration plants to a different location and by changing parameters such as the composition of the waste input incinerated. The games are performed by using a modular model for municipal solid waste incinerator plants. In each case, an LCA including an Impact Assessment is calculated to trace the impact of these changes, and the results are compared.ConclusionsThe conclusions of the paper are two-fold: (1) reduce the differences in inventory data where their impact on the result is high; where it is possible reducing them to a great extent, and the effort for performing the change acceptable; in the case of incineration plants: Adapt the flue gas treatment, especially a possible DeNOx step, to the real conditions; (2) make use of modular process models that allow adapting plant parameters to better meet real conditions, but be aware of possible modelling errors. We invite the scientific community to validate the model used for a waste incinerator plant, and suggest putting up similar models for other processes, preferably those of similar relevance for Life Cycle Inventories.

euroMat ‘97 - Tool for Environmental Life Cycle Design and Life Cycle Costing

Common design approaches use a bottom-up methodology for materials selection as well as environmental checklists. In euroMat ‘97 a top-down materials selection approach is operationalized, in such a way that it enables the designer to find the best materials (combinations) for a product. An integrative life cycle approach is used instead of environmental checklists. Principles, methods, and examples for the implementation of the top-down, iterative, interactive, and integrative (t3i) materials selection are presented.

A new approach for a modular valuation of LCAs

Goal Scope and BackgroundQualitative valuation methods carefully try to avoid an aggregation across impact categories. However, such an aggregation often helps in obtaining a clear result for the valuation (which product scores better?). This article presents a new valuation method that uses an iterative approach. The application is demonstrated by the help of a case study for electric motors in trains.Methods / Main FeaturesThe approach combines two existing, unique valuation methods described earlier in literature, which both are of a rather non-aggregating nature, in line with ISO requirements, and were designed to be performed by LCA experts. The method is implemented in a computer software. Besides constants used within the method, the software needs as input solely indicator values from the Impact Assessment.Results and DiscussionThe iterative nature of these methods itself, and especially the combination of these methods, helps in achieving a valuation result for the LCA with not more subjective and aggregating elements than necessary. Subjective elements are clearly separated from others. The algorithm seems highly sensitive to changes in impact categories regarded as important ones. The implementation in software greatly eases the application of the method by transferring routine work from LCA experts to a machine. It ensures a reproducible result and prevents erroneous steps in a rather complicated valuation procedure. It further helps in hiding the complexity of the method from the user.ConclusionThe approach of combining valuation methods in LCAs seems a fruitful one, and shows benefits when implemented in computer software, in terms of usability, and in terms of a more reproducible application. Care has to be taken to make sure users know what they do when performing an automated valuation procedure.OutlookWe see three ways for extending the approach, namely: (i) become part of a toolbox of different valuation procedures; (ii) explicitly cope with uncertainty, and (iii) include different values for normalisation, in different regions worldwide. The software will be made available also in a stand alone version.