In a life-cycle assessment (LCA) involving only one of several products from the same process, how are the resource consumption and the emissions associated with this process to be partitioned and distributed over these co-products? This is the central question in co-product allocation, which has been one of the most controversial issues in the development of the methodology for life-cycle assessment, as it may significantly influence or even determine the result of the assessments. In this article, it is shown that in prospective life-cycle assessments, co-product allocation can always be avoided by system expansion. Through a number of examples, it is demonstrated how system expansion is performed, with special emphasis on issues that earlier have been a focus of the allocation debate, such as joint production (e.g., of chlorine and sodium hydroxide, zinc and heavy metals, and electricity and heat), the handling of “near-to-waste” by-products, processes simultaneously supplying services to multiple product systems, and credits for material recycling and downcycling. It is shown that all the different co-product situations can be covered by the same theoretical model and the same practical procedure, and that it is also possible to include the traditional co-product allocation as a special case of the presented procedure. The uncertainty aspects of the presented procedure are discussed. A comparison is made with the procedure of ISO 14041, “Life-cycle assessment—Goal and scope definition and inventory analysis,” the international standard.
Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs.
What is a life cycle assessment worth? How much should one spend on an LCA, and what are the expected returns from undertaking one? The value of an LCA ought to be readily estimable by anyone proposing to fund an LCA, or by anyone seeking funds for undertaking an LCA. Assessing the value of a potential LCA as a function of its uncertainty and scope and the characteristics of the decision should be part of goal and scope definition. The present paper proposes and illustrates a framework for estimating the value of LCAs as a function of these and other parameters. We begin by describing two different perspectives for characterizing an LCA’s value: private and public. Next, we suggest which characteristics of the decision context and the LCA results are most influential in determining the value of the LCA. We then construct a basic model of the value of an LCA, which incorporates these characteristics as floating parameters, and use this model to draw some general and qualitative conclusions about how the value of an LCA depends on these characteristics. Finally we demonstrate application of the method and model to a case study.
Environmental Product Declarations (EPDs) on electricity and nitrogen fertiliser are used to illustrate how a declaration or labelling[1] based on data from the current supply chain can be misleading when the production capacity in the supply chain is constrained. Three ways of avoiding such misleading declarations are suggested.
A modified scheme of areas of protection (also known as safeguard subjects) by Udo de Haes & Lindeijer (2000) has opened up a debate in the SETAC-Europe Working Group on impact assessment. This paper should be seen as a contribution to this debate, providing some basic concepts and structures for the debate.
This is the final report from the sub-project “Quantitative environmental assessment of land use in relation to the product life cycle” of the EUREKA project EU-1296 entitled “Development and application of major missing elements in the existing detailed Life Cycle Assessment methodology (LCAGAPS),” which was funded by the Danish EUREKA- secretariat at the Danish Agency for Industry and Trade. Through the Danish funding it was possible to involve a Dutch expert in the field, Erwin Lindeijer, to participate in the work.
The original concepts upon which this report is based were presented to the international scientific community in 1996 (Weidema & Mortensen 1996, Blonk et al. 1996), and within the field of biodiversity assessment some key ideas were developed in the report by Schmidt (1997). Several of the scientific topics related to environmental assessment of land use have been in rapid development during the scheduled period of the LCAGAPS project, especially in the fields of assessment of biodiversity and biogeochemical substance cycles. The finalisation of the project was postponed to take advantage of this concurrent and still ongoing development, and in the following years we focused on contributing to the conceptual development, especially in the SETAC working group on impact assessment (as documented e.g. in Lindeijer et al. 1998). In view of the rapid advancement in modelling and data availability, we have placed emphasis on assessment indicators that can function at the current level of available information, while being amenable for refinement as more data become available. For the same reason, not all aspects of the topic have been treated in equal detail. The final results of the project are presented with the present report.
LCA has traditionally been performed as a bottom-up process analysis, based on linking the specific processes in a supply chain. Exceptions to this approach may be found, especially in the early LCA work in Japan, which was often based on IOA. The process-based method is explained in more detail by Marianne Wesnæs in Chapter 3, who also points out its capability for detail as a significant advantage of this approach. However, a major problem in process-based LCA is the likelihood that important parts of the product systems are left out of the analysis, simply because it is a very difficult task to follow the entire supply chain in detail. As pointed out by Manfred Lenzen in Chapter 4, up to 50% of the environmental exchanges related to a product can be left out, thus possibly leading to erroneous conclusions.
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E-commerce is often cited as offering the potential to reduce wholesale and retail burdens within product life cycles; however its potential impacts upon transport may be positive or negative. But the relative environmental importance of wholesale and retail trade and their intervening transportation links within product life cycles has not been generally characterized. The objective of this research was to assess the upstream (preusage) life-cycle energy burden shares associated with retail trade and wholesale trade using input-output life-cycle assessment (IO LCA) with a special focus on the electronic computers sector.
According to our results, the physical transfers of products within the distribution phase play a minor role in terms of energy consumption compared with wholesaling and retailing. On the other hand, the supply chains of the wholesale and retail trade sectors can lead to energy consumption that is a significant share of the total preconsumer energy consumption for many products. Thus, where e-commerce circumvents wholesale and/or retail trade, it can have a major impact on total preconsumer energy consumption.
As an example, for the electronic computers sector, retailing and wholesaling as a portion of distribution are responsible for 38% of the total energy consumption from production until purchase (cradle to gate), whereas transportation within the distribution phase corresponds to only 9%. Our analysis of more than 400 commodities in the United States showed that for the large majority of them, retailing and wholesaling account for appreciable shares of the total preconsumer energy burdens. Wholesaling and retailing should be included in LCA, and IO LCA is an effective tool for doing so.
Input-Output Analysis (IOA) has recently been introduced to Life Cycle Assessment (LCA). In applying IOA to LCA studies, however, it is important to note that there are both advantages and disadvantages.
This paper aims to provide a better understanding of the advantages and disadvantages of adopting IOA in LCA, and introduces the methodology and principles of the Missing Inventory Estimation Tool (MIET) as one of the approaches to combine the strengths of process-specific LCA and IOA. Additionairy, we try to identify a number of possible errors in the use of IOA for LCA purposes, due to confusion between industry output and commodity, consumer’s price and producer’s price.
MIET utilises the 1996 US input-output table and various environmental statistics. It is based on an explicit distinction between commodity and industry output.
MIET is a self-contained, publicly available database which can be applied directly in LCA studies to estimate missing processes.
By adopting MILT results in existing, process-based, life-cycle inventory (LCI), LCA practitioners can fully utilise the process-specific information while expanding the system boundary.
MIET will be continuously updated to reflect both methodological developments and newly available data sources. For supporting information sec http:// wwwJeidenuniv.nl/cml/ssp/softwarc/miet.
