This guideline provides a procedural description to identify the relevant granularity of product groups, through the definition of functional units that express the obligatory product properties in the market segment where the products are sold.
This guideline has been produced as a complement to the PEF guidance (European Commission 2013, 2016).
The guideline is applicable for Product Life Cycle Assessments in general, also beyond the Product Environmental Footprint (PEF) scheme.
This report was a contribution to Nordic PEF seminar at Nordic Council of Ministers.
Three consistency problems are identified that arise when partitioning a product system with joint production according to an allocation key, such as revenue or mass of the joint products, namely: lacking consistency of rationales and procedures; lacking consistency of monetary, mass, and energy balances in the partitioned product systems; and lacking consistency of results across model resolution and classification of the intermediate flows. Different solutions to these consistency problems are described, including the attempt of ecoinvent to solve the third consistency problem with a system model that uses revenue allocation at the point of substitution. The problems with the different practical implementations are described. For each of the three consistency problems, a solution is proposed and combined into a single consistent solution. The consistency of rationales and procedures is ensured by asking only one question at a time and performing a separate allocation and calculation for each question. The problem of maintaining monetary, mass, and energy balances is solved by a generalized allocation correction. The identified problem with consistency of results across model resolution and classification is solved by redefining the point of substitution. It is described what consequences the solutions will have if their results are misused for decision making that will shift demand between products.
A systematic comparison is made of attributional and consequential results for the same products using the same unit process database, thus isolating the effect of the two system models. An analysis of this nature has only recently been made possible due to the ecoinvent database version 3 providing an access to both unallocated and unlinked unit process datasets as well as both attributional and consequential models based on these datasets. The analysis is therefore limited to the system models provided by ecoinvent.
For both system models, the analysis was made on the life cycle inventory analysis (LCIA) results as published by ecoinvent (692 impact categories from different methods, for 11,650 product/activity combinations). The comparison was made on the absolute difference relative to the smallest absolute value.
The comparison provides quantified results showing that the consequential modelling provides large differences in results when the unconstrained (marginal) suppliers have much more/less impact than the average, when analysing the by-products, and when analysing determining products from activities with important amounts of other coproducts.
The analysis confirms that for consequential studies, attributional background datasets are not appropriate as a substitute for consequential background. The overall error will of course depend on the extent to which attributional modelling is used as part of the overall system model. While the identified causes of differences between the attributional and consequential models are of general nature, the identified sizes of the errors are specific to the way the two models are implemented in ecoinvent.
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Building on the rhetoric question “quo vadis?” (literally “Where are you going?”), this article critically investigates the state of the art of normalisation and weighting approaches within life cycle assessment. It aims at identifying purposes, current practises, pros and cons, as well as research gaps in normalisation and weighting. Based on this information, the article wants to provide guidance to developers and practitioners. The underlying work was conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative, Task Force on Cross-Cutting issues in life cycle impact assessment (LCIA).
The empirical work consisted in (i) an online survey to investigate the perception of the LCA community regarding the scientific quality and current practice concerning normalisation and weighting; (ii) a classification followed by systematic expert-based assessment of existing methods for normalisation and weighting according to a set of five criteria: scientific robustness, documentation, coverage, uncertainty and complexity.
The survey results showed that normalised results and weighting scores are perceived as relevant for decision-making, but further development is needed to improve uncertainty and robustness. The classification and systematic assessment of methods allowed for the identification of specific advantages and limitations.
Based on the results, recommendations are provided to practitioners that desire to apply normalisation and weighting as well as to developers of the underlying methods.
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The practicality of social footprinting is currently hampered by an excessive data requirement, a lack of focus on materiality of the impacts, and a lack of understanding of the main impact pathways (cause-effect relationships) for social and economic impacts. We propose a “streamlined” method to overcome these barriers without loss of comprehensiveness.
The method combines a top-down approach using input-output data to focus the data collection effort on processes with high value added or a high number of work hours with a streamlined impact assessment that limits the inventory data requirement and the need for detailed impact pathway descriptions, by focusing on the macro-scale impacts of income redistribution and productivity impacts of missing governance, both of which can be classified as non-production-specific impacts, i.e., unrelated to enterprise-specific actions and choice of technology, and therefore quantifiable from national statistics without need to access detailed technology- or enterprise-specific data. The method is open for further refinement and detail in areas of specific interest for a particular product or project.
We show that non-production-specific impacts constitute the vast majority of social and economic impacts and how important income inequality is for the impact assessment. We apply a novel way of combining impacts on productivity and impacts on human well-being and show that inequality implies that an intervention that changes the amount of QALY (quality-adjusted life years) for a population group will always give a larger change in well-being than an intervention of the same monetary value that only affects the level of consumption of the same population group. Throughout the article, we apply and illustrate the method with an example from the clothing industry.
The presented method allows comprehensive assessments of social footprints of products at much lower efforts than seen so far. The potential credits for positive action is by far the largest in countries with missing governance, thus providing a compelling argument for placing activities in countries with missing governance, provided that it allows the enterprise to follow an active strategy to create shared value.
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As companies try to embrace life cycle thinking, Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) have proven to be powerful tools. In this paper, an Environmental Input-Output model is used for analysis as it enables an LCA using the same economic input data as LCC. This approach helps align LCA and LCC while avoiding cut-offs in the LCA. The efficacy of the method is illustrated by a real case study of a tanker ship.
As economies in the European Union are ultimately driven by the final consumption of citizens, policy makers need proper indicators to monitor the environmental impacts associated with this consumption. These indicators can be constructed using two different approaches, each having their strengths and limitations. The top-down approach is based on environmentally extended input–output analysis and quantifies the environmental impacts of product groups and services provided by industrial sectors. The bottom-up approach is based on Life Cycle Assessment and quantifies the environmental impacts of a selection of representative products. The bottom-up approach has already been used by the European Commission's Joint Research Centre to calculate the impacts of the final consumption per capita in the European Union in 2006. In this paper, we calculated these impacts through a top-down approach, using the Exiobase database. The covered household activities are food, consumer goods, mobility, shelter and services. The goal was to calculate all the impact categories recommended by the International Reference Life Cycle Data handbook, and compare both approaches. However, the categories ionizing radiation, toxicity and abiotic resource depletion could not be included, as some relevant emissions and resources are not available in Exiobase. To study more profoundly the impact on natural resources, we added the Cumulative Exergy Extraction From the Natural Environment to the impact assessment. When comparing both approaches, it can be concluded that there is a considerable shift in the results. This means that the information obtained by a top-down approach could supplement the information base for policy support.
The fifth assessment report by the IPCC includes methane oxidation as an additional indirect effect in the global warming potential (GWP) and global temperature potential (GTP) values for methane. An analysis of the figures provided by the IPCC reveals they lead to different outcomes measured in CO2-eq., depending on whether or not biogenic CO2 emissions are considered neutral. In this article, we discuss this inconsistency and propose a correction.
We propose a simple framework to account for methane oxidation in GWP and GTP in a way that is independent on the accounting rules for biogenic carbon. An equation with three components is provided to calculate metric values, and its application is tested, together with the original IPCC figures, in a hypothetical example focusing on GWP100.
The hypothetical example shows that the only set of GWP100 values consistently leading to the same outcome, regardless of how we account for biogenic carbon, is the one proposed in this article. Using the methane GWP100 values from the IPCC report results in conflicting net GHG emissions, thus pointing to an inconsistency.
In order to consistently discriminate between biogenic and fossil methane sources, a difference of 2.75 kg CO2-eq. is needed, which corresponds to the ratio of the molecular weights of CO2 and methane (44/16). We propose to correct the GWP and GTP values for methane accordingly.
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Life Cycle Assessment (LCA) is a state-of-the art method for conducting environmental assessments of systems, whether these consist of goods or services, or a combination of the two. However, current LCA guidelines focus on assessing tangible products and lack specific attention to more complex systems, such as Product/Service-Systems (PSS), which also consist of intangible elements. PSS imply a shift in business paradigm from selling specific products to delivering a function, through a mix of products and services, thereby incentivising resource efficiency as well as user satisfaction. Despite their potential to reduce environmental impacts, PSS are not by default more environmentally benign compared to conventional systems, and quantifications of their environmental performance are called for. This paper contributes by showing that specific challenges need to be addressed when using LCA to evaluate the environmental performance of PSS. We identify a set of PSS characteristics that can challenge an LCA study. Three relevant scopes are distinguished, where LCA may be applied: (1) evaluating options within the PSS itself; (2) comparing a PSS with an alternative; and (3) modelling the actual contextual changes caused by the PSS. We derive three pronounced challenges when conducting LCA within the three scopes: (i) identifying and defining the reference system; (ii) defining the functional unit; and (iii) setting system boundaries. We elaborate on how these challenges are discussed in current literature. Recommended future work includes developing adapted guidelines and further empirical case studies that quantify the environmental changes and impacts caused by introducing PSS.
Purpose
This discussion article aims to highlight two problematic aspects in the International Reference Life Cycle Data System (ILCD) Handbook: its guidance to the choice between attributional and consequential modeling and to the choice between average and marginal data as input to the life cycle inventory (LCI) analysis.
Methods
We analyze the ILCD guidance by comparing different statements in the handbook with each other and with previous research in this area.
Results and discussion
We find that the ILCD handbook is internally inconsistent when it comes to recommendations on how to choose between attributional and consequential modeling. We also find that the handbook is inconsistent with much of previous research in this matter, and also in the recommendations on how to choose between average and marginal data in the LCI.
Conclusions
Because of the inconsistencies in the ILCD handbook, we recommend that the handbook be revised.
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