Life Cycle Assessment

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1 12 Life Cycle Assessment Mikkel Thrane and Jannick H Schmidt The aim of this chapter is to introduce life cycle assessment (LCA) and its application according to the ISO (2006) and ISO (2006) standards. The chapter provides the basis for carrying out an LCA and includes tables that can be used as a checklist. The level of sophistication represented by the checklist corresponds to a screening or detailed LCA. Compared to other methods for environmental assessment, e.g. Environmental Impact Assessment (see chapter 19), the most important characteristics of LCA are that it applies the life cycle perspective and that the inputs and outputs are translated into potential environmental impacts. The life cycle perspective means that LCA considers the entire life cycle of a product including raw material extraction, processing, distribution (transport), use and final disposal. Apart from providing an overview of the products entire life cycle, it may contribute to avoiding potential burden shifting between different stages of product life cycle (ISO p. 6). Potential environmental impacts may include the contribution to impact categories such as global warming, ozone depletion, nutrient enrichment, and acidification etc. LCA does typically not include social and economical impacts (ISO p. Vii) but methods are being developed to address these two important dimensions of sustainability as well (Weidema 2006, Norris 2006). This chapter will only address the environmental dimension, but an integrated or separate assessment of the other dimensions is relevant to avoid burden shifting in this dimension as well. If we consider an LCA of a single product, LCA makes it possible to elucidate where the environmental impacts occur in the lifecycle, how important they are, and which processes or substances they are related to. But LCA can also be used to compare the environmental impact potential from two or more products. LCAs of single products and comparative studies are

2 206 Life Cycle Assessment both relevant for development of cleaner products (and services). As an example, car designers can use LCA to compare the environmental impact from alternative design solutions such as the use of light weight (but energy intensive) materials versus heavier (but less energy intensive) materials. Introduction to LCA History The roots of LCA go back to the late 1960s and early 1970s where environmental studies applying the life cycle perspective were used to estimate the environmental burden for beverage containers by the Coca Cola Company. A British researcher, Ian Bousted, used similar approaches in the 1970s to estimate the total energy used to produce a number of different packaging materials. Still, it was not until the late 1980s that LCA gained momentum (Jensen et al. 1997). The first guidelines for LCA were published in The guidelines were termed the Code of Practice and developed by a working group in the Society of Environmental Toxicology and Chemistry (SETAC). The guideline has been replaced with standards developed by the International Organization for Standardization in the period 1997 to 2000 (ISO ). The standards have been revised in 2006, and reduced to two documents ISO (principles) and ISO (requirements and guidelines). Hence, the ISO standards have replaced guidelines from SETAC and are much more detailed partly to reduce the risk of misuse but the Code of Practice was actually more ambitious with respect to improvement assessment, which is not included as a requirement in the ISO standards. Key concepts and definitions In short, LCA is a tool used to assess the potential environmental impacts from a product (or a service) from raw material extraction to final disposal (ISO p. 3). The following definitions are based on ISO (2006). Unit processes, exchanges, and elementary flows The assessment is based on a compilation of the elementary flows related to inputs (e.g. materials, energy, transport, chemicals, and other exchanges such as land use) and outputs (e.g. emissions to air and water or solid waste) from the unit processes that compose the product system being analysed.

3 Thrane and Schmidt 207 A unit process is the smallest portion of a product system for which input and output data are collected (e.g. a process line or a factory). A product system is a collection of unit processes (with elementary and product flows) that perform one or more defined functions, that models the life cycle of a product. Elementary flows are material or energy flows from or to the environment without any previous (or further) human transformation. An example of an elementary flow entering the system could be coal from a coal mine. An example of an elementary flow leaving the system could be emissions of SO 2 from a coal fired power plant. Figure 1 provides a conceptual overview of a product system including unit processes, inputs, outputs, and elementary flows. Each of the boxes (grey and white) may be composed by several unit processes. System Boundary Input flows (exchange) Extraction of raw materials Output flows (exchange) Elementary flow from nature (Environmental exchange) Materials Energy and transport Chemicals Other (e.g. land) Manufacturing/ Processing Distribution Use Air emissions Water emissions Solid emissions Other exchanges (e.g. radiation) Waste treatment Reuse or recycling Elementary flow To nature (Environmental exchange) Disposal Intermediate product flows Figure 1: Conceptual overview of a product system, unit processes, inputs and outputs and elementary flows. Inspired by ISO (2006 p. 10). Apart from inputs and outputs (exchanges) that are directly related to the immediate product chain (shaded boxes), data should be obtained for inputs and outputs for other unit processes illustrated with white boxes. This includes production of various materials, energy, transport and chemicals as well as possible recycling/reuse processes and waste or wastewater treatment. Databases can be usefull for this purpose, but this will be elaborated later.

4 208 Life Cycle Assessment LCIA and the impact chain Based on the inventory of exchanges and ultimately elementary flows, it is possible to assess the potential environmental impact through calculations carried out as part of the phase life cycle impact assessment in short LCIA. The result of the LCIA is a number of category indicator results e.g. an indicator for the contribution to global warming, eutrophication, and acidification. This is further elaborated in the section Life cycle Impact Assessment later in this chapter. Hence, in ISO language LCA is:..a compilation and evaluation of the input, outputs and the potential environmental impacts of a product system throughout its life cycle (ISO p. 2). As it appears from the definition, LCA cannot measure the absolute or precise impacts, but only potential impacts. The reason is that the impacts that eventually materialize depend on variables such as the level of exposure, and sensitivity of the receiving environment (ecosystems, humans etc.) in the area affected. In other words, there are a number of physical, chemical, and biological processes that links the results from the inventory to the category indicator or the category endpoints. This is also termed the environmental mechanism, see figure 2. Environmental Exchange Mid-point End-point Emission Fate Exposure Sensitivity of recieving environment Damage to human health, ecosystems or resources. Figure 2: The environmental mechanism from elementary flows (environmental exchange) to damage on end-point level, inspired by Hauschild and Potting (2003 p. 19) The environmental mechanism links an environmental exchange to category indicators (midpoints) and category end-points. An example of an environmental mechanism where human health is involved could be the emission of CFC gases, which causes a depletion of the ozone layer in the stratosphere (mid-point). Later this will cause increased levels of radiation (also midpoint) that eventually results in a certain number of people being affected by skin diseases (end-point). The amount of CFC that enters the atmosphere depends on the fate of the substance. The number of affected people depend on their exposure to the sun, and the seriousness eventually depend on peoples sensitivity to ultra violet radiation (dark versus light skin colour, amount of sun block etc.).

5 Thrane and Schmidt 209 LCA methodologies are being developed to include more variables, but LCA will always be a model of the world (Udo de Haes et al. 2002). In relation to figure 3, it is worth mentioning that the level of uncertainty in the models tends to increase going from left to right (towards the end-point level), while the level of uncertainty in interpretation will decrease (Hauschild and Potting 2003). Tools To be able to carry out an LCA it is necessary or at least convenient to have certain tools within reach. First of all, it is necessary to have the ISO 14040:2006 and ISO 14044:2006 standards. They serve as the overall framework for carrying out the LCA, the cookbook. Secondly, it is a good idea to have a database with information about inputs and outputs for a large number of standard processes, materials, energy products, and chemicals. Thirdly, it is necessary to choose a method for the LCIA, which transforms the input and output data to environmental impact potentials. There exist several LCIA methods that are often developed in a national context, but UNEP is now in the process of developing an international LCIA method. Finally, it is convenient with a PC software tool to handle the calculations. In PC tools such as SimaPro or Gabi, the user can choose between a variety of databases and LCIA methods, and the software can help analyzing the results. So there are four important tools the ISO standard, a method (or several methods) for impact assessment (LCIA), a database, and a PC software tool, see figure 3. Figure 3: Four important tools to carry out an LCA.

6 210 Life Cycle Assessment The LCIA calculations in chapter 13 are based on the Danish EDIP method (Environmental Design of Industrial Products). The applied PC software is the Dutch Simapro 7 and the applied databases include ETH, Buwal and LCAfood. The LCA method and the databases are both available in the PC software. Methodological overview This section provides a quick overview of the four phases of an LCA and discusses how different levels of detail can be applied. The content of the four phases will be elaborated further in the remaining part of the chapter. Framework According to the ISO standard a LCA study includes four phases, as illustrated in figure 4 (ISO ). Life Cycle Assessment framework Application areas 1) Goal and scope definition Product development and improvement 2) Inventory analysis (LCI) 3) Impact Assessment (LCIA) 4) Interpretation Strategic planning Marketing Public policy-making Other Figure 4: Phases in a LCA and examples of application areas. Inspired by ISO (2006). In the goal and scope phase, the LCA-practitioner formulates and specifies the goal and scope of study in relation to the intended application. The object of study is described in terms of a functional unit (explained later). An overview of relevant processes and the methodology applied is also described here. The system boundary, and therefore also the results, depends on the purpose of the LCA study.

7 Thrane and Schmidt 211 The Inventory involves modelling of the product system, data collection, as well as description and verification of data. The data must be related to the functional unit defined in the goal and scope definition. Data can be presented in tables and some interpretations can be made already at this stage. The results of the inventory is an LCI which provides information about all inputs and outputs in the form of elementary flow to and from the environment from all the unit processes involved in the study. The impact assessment phase is aimed at evaluating the contribution to impact categories such as global warming, acidification etc. The first step is termed characterization. Here, impact potentials are calculated based on the LCI results. The next steps are normalization and weighting, but these are both voluntary. Normalization provides a basis for comparing different types of environmental impact categories (all impacts get the same unit). Weighting implies assigning a weighting factor to each impact category depending on the relative importance. The methodology will be further elaborated later. The Interpretation is basically the conclusion on the study, but besides a presentation of the key results it must also include a critical reflection about the study, uncertainty, sensitivity and methodological choices. An iterative process The double arrows in figure 4 illustrate that LCA is an iterative process, where changes in various choices at different phases occur continuously as the LCA practitioner gradually becomes wiser and more focused. For example, it may appear that the impact category land use turns out to be much more important after the impact assessment phase than initially assumed. This may lead to inclusion of this impact category in the Goal and scope phase, and a reconsideration of the data collection in the Inventory phase where new and better data for land use aspects might be required. Another example would be the appearance of new processes during the LCI, which require that the practitioner returns to the Goal and scope phase and includes these new processes in the scope. Finally, one could also imagine a situation where the LCI and the LCIA phases provide completely new knowledge about production patterns and production restrictions, in a way that undermines the whole purpose of the study, which then has to be reconsidered. Application areas As indicated in the right side of figure 4, LCA has many application areas. The standard highlights product development and improvement, strategic planning, marketing, and public policy making. This seems to highlight the

8 212 Life Cycle Assessment application at company and policy level, but it can also be applied at sector level, by NGOs, consumer organizations etc. Specific versus generic purposes When LCA is used at company level it is often for specific products (e.g. product documentation or development), while the application at societal level often has a more generic character (e.g. criteria for eco-labelling or societal action plans and legislation). The distinction between specific and generic purposes is important for two reasons. First of all, the potential social and economical consequences increase when the purpose becomes more generic (e.g. societal action plans and legislation opposed to product development). This means that the demands to certainty, transparency and documentation tend to increase when the purpose has a generic character (opposite to an LCA specific product from a specific company). Secondly, the consequences of e.g. political decisions tend to influence industrial systems many years ahead opposed to purposes of a more specific character. This means that requirements to projections and future scenarios in generic LCAs tend to increase. Documentation versus strategic purposes Another important distinction is whether the intended application is for, - documentation (e.g. hot-spot identification or product declaration) for example as response to actual or potential demands or acusations from customers, competitors, NGOs, authorities etc, or - for strategic purposes (strategy for product innovation, or environmental policies). Again, the requirements to sophistication and future scenarios become larger when the purpose is strategic opposite to purposes of a more operational character such as documentation. Historical or current data are often enough for the latter, while the LCA should reflect future technologies and future markets in situations where the purpose of the LCA is strategic and has consequences for the next years. Basically, data and methods applied in the LCA should reflect the type of decision as well as the decision horizon. Conceptual, screening, and detailed LCA As mentioned, different ambition levels can be chosen when carrying an LCA. The simplest approach is a conceptual LCA, which is a qualitative assessment of the environmental aspects from cradle to grave. Besides basic

9 Thrane and Schmidt 213 environmental knowledge, this method does not require knowledge about LCA methodology and can be performed in a matter of hours. Chapter 14 on EcoDesign includes several examples of assessment tools that can be used for a conceptual LCA, e.g. the ABC scheme. See also Wenzel (1998). A screening LCA require quantitative data, and the practitioner must have knowledge about LCA methodology. It can be performed in a matter of days or months, and is often characterized by the use of existing data (e.g. from literature sources and databases). It is also possible to limit the data collection to energy consumption - while the impact assessment may be limited to address only a few impact categories (e.g. only global warming). The detailed LCA includes a comprehensive data collection, a high level of data quality and a larger number of impact categories. In addition, the detailed LCA must include an analysis of the uncertainty, sensitivity and consistency of the analysis. These definitions are based on Jerlang et al. (2001), but it is often difficult to make a clear distinction between a screening and detailed LCA in practise. Considering the number of justifications and considerations that are required in the ISO standard, an LCA made according the requirements in the standard often have a character of detailed LCA, in practise. The LCA technique can also be applied in studies that only addresses parts of the life cycle e.g. the first stages in the life cycle from raw material acquisition to processing (cradle-to-gate), a single life cycle stage such as processing (gate-to-gate) or studies which only addresses e.g. waste management systems or components of a product. The ISO standard points out that such studies shouldn t be referred to as LCAs, but instead studies that apply the LCA technique (ISO ). Level of sophistication and purpose of study As explained in the previous section about specific versus generic purposes, there is a relationship between the intended application and the level of sophistication. Generally, the requirements to sophistication (e.g. certainty, transparency and documentation), must be higher when the purpose is to support decision with large social and economical consequences (Wenzel 1998). It is also worth to distinguish between situations where the LCA only is intended to be used internally and situations where the results are to be communicated externally (to a third party). In the first case, there are no specific requirements to the level of sophistication while the requirements are equivalent to a screening or detailed LCA for studies that are to be communicated externally. The latter requires a level of sophistication equivalent to a screening or detailed LCA. Specific requirements to the study report for

10 214 Life Cycle Assessment LCA that are communicated externally are described in the ISO standard (ISO p. 36). A number of additional requirement apply to comparative assertion that are intended to be disclosed to the public. A comparative assertion is an environmental claim about the superiority of one product versus a competing product that performs the same function (ISO 14044, 2006 p. 8). Examples of additional requirements are a detailed description of data quality requirements, obtained data quality, critical review process, evaluation of the completeness of the LCIA, and results of the uncertainty and sensitivity analysis. This level is equivalent to a detailed LCA. Further details about requirements and content of study report are described in ISO (2006 p. 38). Phase 1: Goal and scope The main elements of the Goal and Scope phase are illustrated in table 1. Unless other references are specifically mentioned the main reference used throughout the following sections is ISO (2006). Phase one: Goal and scope definition Goal of the study: Intended application Stakeholders Product/service alternatives LCIA methodology (scope): Impact categories Method for impact assessment Key assumptions and exceptions Scope: Functional unit System boundary Cut-off criteria Co-product allocation Data collection and treatment (scope): Demands to data quality Plans for critical review Table 1: The main elements of the goal and scope phase according to the ISO standard. It is worth noticing that the ISO standard mainly serves to provide an overview of LCA, while ISO contains specific requirements to those carrying out an LCA. The word shall only appears one time in the ISO standard, namely in the phrase where it is stated that - when performing an LCA the requirements of the ISO standard shall apply. The different elements of the goal and scope phase will be elaborated in the following.

11 Thrane and Schmidt 215 Goal of the study Intended application As mentioned earlier, LCA can be applied for documentation purposes or purposes of a more strategic character such as product development or improvement. The need for documentation can be a respond to demands from customers or authorities, but it can also be a part of a more proactive greenmarketing effort. The latter may include eco-labelling (e.g. environmental product declaration) or LCA information used to show customers that certain products or technologies represent an environmental benefit (e.g. LCA documentation of wind turbines) LCA has the largest potential to contribute to environmental improvements when it is used proactively and strategically. As mentioned earlier this ideally requires that the LCA include future scenarios as strategic decisions may have consequences that materializes 5, 10 or maybe 20 years from now (Wenzel 1998, Weidema 2003). Stakeholders It is important to describe the context in which the LCA is performed. Relevant questions to answer are: who are the target audience? Who is the commissioner? Who has paid for the study? What are the most important stakeholders? To whom are the LCA results to be communicated? This type of information should not be omitted as it prevents that is used in the wrong contexts or misuse in other ways. Also, it generally improves the transparency and credibility of the study. Product alternatives It is possible to distinguish between two types of LCA studies, a single product and a comparative LCA. The first is used to perform an environmental assessment of a single product and is also known as a hot-spot assessment. It is called a hot-spot assessment because it is used to determine where in the product s life cycle the impact potentials are most significant. At company level this can be important knowledge in the search for ecofriendly suppliers, but also the search for improvement options, and for environmental action plans (that minimize the risk of sub-optimization or shift of burden problems). A comparative LCA is used to compare the environmental performance of two or more products. This is especially relevant in product development, where the new and greener products often are compared to a reference product. It is difficult to determine if something is truly greener without a reference product, and comparative LCA studies are therefore often an essential part of a continuous improvement cycle. One of the advantages of compara-

12 216 Life Cycle Assessment tive studies is that it is possible to disregard life cycle stages or processes that are similar for the products being compared. A number of special requirements should be fulfilled, if the LCA is used for a comparative assertion intended to be disclosed to the public. Scope Functional unit The object of the study must also be carefully described in terms of a functional especially in comparative studies. A functional unit is defined as a quantified performance of a product system used as a reference unit in a LCA. The functional unit may reflect: - A quantity (amount, volume or size) - A duration period - Qualitative characteristics. If an LCA practitioner wants to compare two types of wall paint (paint A versus paint B) it is important to know how much the two buckets contain (quantity), how much time the two types of paint can last without fading or flaking off (duration period), and to which an extend they are comparable with respect to gloss, repellent qualities etc. (qualitative aspects). In certain cases it is also relevant to consider if the two products are comparable with respect to non-market relevant qualities as well. This could be the heat delivered from electronic equipment, which may substitute other heat sources or which may increase the need for cooling depending on the context. Based on the considerations of quantity, duration period and qualitative aspects, it is possible to establish the reference flow which is used as the basis for all calculations. In the paint example, the reference flow could be 1½ bucket of paint A versus 2 buckets of paint B. This reflects that paint A is a more durable paint. The focus on function ensures fair comparisons, but it may also be an eye-opener in the search for product alternatives. The purpose of the functional unit is to ensure a fair comparison of product alternatives. However, it also serves the purpose to address functionality and instead of merely a physical products, which in itself may promote creative thinking and smarter ways of providing the function. System boundaries (two different approaches) Apart from describing the functional unit, the goal and scope, should address the overall approach used to establish the system boundaries.

13 Thrane and Schmidt 217 The system boundary determines which unit processes that are included in the LCA, and must reflect the goal of the study. In recent years, two approaches to system delimitation have emerged. These are often referred to as consequential modelling and attributional modelling. Economic causalities versus biophysical flows: The main differences is that consequential modelling uses a market oriented approach to identify the affected processes, while the attributional modelling identifies processes to be included by analysing the bio-physical flows in the (current) supply chain. This is best illustrated by an example: In a study of the environmental impact from consumption of 1 litre of milk in EU, attributional modelling would suggest the inclusion of the producers in the current supply of milk, ending up with the agriculture stage (the cow). At first, this seems to the most logical solution. However, quota or other production constrains exists in many product chains, and these limitations should always be considered according to the consequential approach. In EU, milk production is limited by quota. Hence, an extra demand of milk doesn t result in additional production of milk. In practise, less milk becomes available for milk powder production. Therefore, the cow must be excluded from the product system. Instead, the production of milk powder should be included. In consequential modelling, the cow should only be included to illustrate the impact in a scenario where milk quotas are removed - or in a comparative LCA that shows the environmental consequences of choosing e.g. organic instead of conventional milk (Weidema 2003). This shows a close link between the purpose of the study and the modelling of the product system. Average versus actually affected technologies: Another difference between the two approaches concerns the use of average data. In attributional modelling electricity consumption is typically modelled as a mix (average) of existing producers of electricity in proportion with their current supply. But, in consequential modelling, it is sought to model the technologies most likely to be affected by a change in demand of electricity. In the case of Denmark this is most likely coal or gas. The argument is that windmills and other renewable energy sources can be disregarded because their production is independent of small scale changes in demand. Electricity consumption is not the only example of this. Many products are traded on markets with no specific ties to producers, and while attributional modelling often suggest averages as default, consequential modelling suggest identification of the processes that are most likely to be affected. The latter requires more information about functioning of markets but Weidema (2003) provides a list of default assumption that makes this job relatively easy (Weidema 2003). Use of system expansion: There are a few other differences between attributional and consequential modelling e.g. in relation to handling of co-

14 218 Life Cycle Assessment product allocation where allocation by arbitrary parameters is systematically avoided in consequential LCA, but this requires further explanations, and is therefore treated separately later in this chapter. Choice of approach: The remaining question is what modelling approach that is most correct? The ISO standard is somewhat imprecise in its recommendations, but annex 2 stresses that: the products and processes studied in an LCA are those affected by the decision that the LCA intends to support. Some applications may not appear to immediately address improvements, such as LCA to be used for education or information about the product life cycle. However, as soon as such information is applied in practice, it is used in an improvement context. Therefore, special care is necessary to ensure that the information is applicable to the context in which it is likely to be applied (ISO ). This formulation seems to advocate for consequential modelling, but part of the LCA community (especially in other countries than Denmark) currently interprets is as an argument for attributional LCA, as well (Christiansen 2007). In Denmark, consequential modelling has been chosen as the officially preferred method (Hansen 2004), and hence the following descriptions will therefore reflect consequential modelling. It should be noted that the number of advocates for attributional modelling is decreasing, also internationally (Christensen 2007). System boundaries (consequential modelling how?) According to Weidema (2003) the fundamental rule that should be applied to all methodological choices in LCA is: that the data used must reflect as far as possible the processes actually affected as a consequence of the decision that the specific life cycle assessment is intended to support (Weidema 2003). The decision always include alternatives e.g. whether to produce product A or B, whether to buy product A or B, alternative ways to produce energy or alternative ways to collect and treat waste - at company or societal level. There are many possibilities but we always investigate the environmental consequences of a potential change - even in a study of a single product (a hot-spots assessment). Here, we compare a situation where we produce product A with a situation where we don t produce product A. The point of departure of any modelling is the decision that we try to model. In a company perspective, the affected processes could be upstream as well as down stream in the product chain. For upstream processes, it must

15 Thrane and Schmidt 219 be established who are affected by a change in demand (for intermediate products, materials, energy, chemicals etc). If there are specific ties to a certain supplier, and if the given supplier is able to respond to a change in demand (unconstrained supplier), the supplier will be affected. Eco-labelling schemes may in some cases establish such ties to certain suppliers. However, if the supplier is constrained by quota or other restrictions, it is other suppliers on the market that will be affected. The challenge here is to identify the suppliers that are most likely to be affected on the given market. Also, for some product categories, specific ties between producers and customers, seldom exists. One example is electricity as decribed above, but it can also be food products such as coffee, sugar, soy meal etc. In this case, we have the same problem - who is affected? Weidema (2003) presents a procedure for identification of the affected or marginal suppliers. First it has to be established whether a local, regional or even global market is affected. However, we also have to consider which type of suppliers that are affected on these markets. For small-scale changes, which often occur at company level LCAs, the method suggests that the most competitive producers (presumably high level of technology) are affected on expanding markets, because they are most able to respond to a change in demand. The opposite happens if the market is in regress, because the company then affects the capacity that is being taken out of the market. Information about market trends and the regional scope of markets for a number of products is available in Weidema (2003) together with a number of default assumptions that can be used for these kinds of assessments. This may appear a little confusing, but it is a pivotal part of the LCA which should not be underestimated. Cut-off criteria As part of the system delimitation it is also necessary to consider and describe the level of detail which is applied in the data collection. There should obviously be a limit to how detailed the data collection should be and to how many tiers back we should track each flows. This can be handled through cut-off criteria. One possibility is to use mass as a criterion. All inputs could be included that cumulatively contribute to more than a certain percentage of the total mass input to the product system. Similar for energy, it is possible to define a percentage of the accumulated energy input to the system. However, for chemicals it is important to consider the environmental significance as well. Apart from these considerations, the practitioner should decide whether to include capital goods (equipment) which typically include buildings, machines, roads and other types of infrastructure. In an LCA of milk products capital goods could be construction of farm buildings and construction of

16 220 Life Cycle Assessment machines used to pump process and store the milk, roads used for distribution etc. The ISO standard suggests that capital goods are treated as an integrated part of the product system and that the same cut-off criteria should apply for capital goods as any other process. More recent databases e.g. Ecoinvent, include capital goods, but separate estimates should still be obtained for processes where databases are not used. Due to time limitations this is often omitted in practise, but some researchers argue that LCAs may give false results if capital goods are omitted (Frischknecht et al. 2007). Hence, it is a good idea to make some kind of estimates or to make separate qualitative or semi qualitative assessments. Generally, it should be sought to use data that reflect the same level of detail in all life cycle stages and product types investigated. PC tools such as SimaPro include a function termed cut-off which can be adjusted at any level. If the cut-off function is set to 0.1% the software leaves out (graphically) all processes that have a smaller contribution to the impact potential than 0.1%. This function can be used to avoid that a more detailed data collection for some products or some life cycle stages result in a biased result. It should be mentioned that so-called IO LCA databases makes it possible to avoid that parts of the product system are excluded. Hence, by using IO LCA databases (separately or in combination with the process LCA) it is possible to avoid cut-off entirely. IO LCA databases are not the focus on the present chapter, but are briefly discussed in the section Inventory. Co-product allocation Processes often yield more than one product. In other words, we typically have one (or several) determining products (main products) and one or several dependent products (co-products) leaving a unit process or a product system. The challenge is to allocate the inputs and outputs to the different products. The method used to handle this should be clearly stated and explained. Phase 1 (Goal and scope) should include the overall principles, but as the actual allocation takes place in the inventory phase, this subject is further explained in the following section (phase 2: Inventory). Methodology (scope) Apart from the system boundaries and cut-off criteria, the ISO standard requires that the choice of impact categories and impact assessment method is described in the goal and scope phase. The following provides a brief introduction to some of the choice that should be made.

17 Thrane and Schmidt 221 Types of impacts The ISO requirements to the choice of impact types (or categories) are that: The selection of impact categories shall reflect a comprehensive set of environmental issues related to the product system being studied, taking the goal and scope into consideration (ISO ). Hence, the practitioner shall make a conscious choice of relevant impact categories not just chose a default list of impact types or a list of impact categories that promotes good or bad characteristics of a given product. The impact categories included in the EDIP 97 method (black) are listed in table 2, together with a list of examples of other impact categories that also could be considered (grey): Globa Environmental impact Resources consumption Other related impacts Global warming (GWP) Ozone depletion (ODP) Depletion of non-renewable resources Regional Photoch. ozone formation Acidification Nutrient enrichment Ecological toxicity Human toxicity Depletion of renewable resources at regional scale Radiation Local Ecological toxicity (acute) Human toxicity (acute) Waste Damage to the seabed Land use As above but local scale Occupational H&S Animal welfare Noise Odour Accidents Aesthetics Radiation Table 2: Environmental impact categories included in the EDIP 97 method (black) and examples of other relevant impact categories of which some are included in other LCIA methods. Separate qualitative (or semi-quantitative assessments) can be carried out for impacts that are not included in the standard LCIA methods, but which are considered potentially important. This could be land use, seafloor impacts, occupational health and safety, animal welfare etc. Social and economical aspects are not addressed by table 2 (apart from OH&S). Method for LCIA In practise LCA practitioners often choose a method for LCIA, which is developed in the country where the LCA is carried out. In Denmark we tend to use the Danish EDIP method, where the latest version is termed EDIP

18 222 Life Cycle Assessment However, it can be an advantage to use several methods for verification purposes and to cover more impact categories. Methods for LCIA are categorised in two groups. The first group uses a so- called midpoint approach as these methods stop somewhere in the environmental mechanism between environmental exchanges and endpoints (see figure 3). The other group uses a so-called end-point approach as they model the potential damage on value items such as trees etc. The Danish EDIP method represents a mid-point approach, which models the first part of the environmental mechanism (from left to right in figure 3). The first method known as EDIP 97 considered some aspects of fate, but did not model exposure and sensitivity of the receiving environment. A more recent version EDIP 2003 does take exposure and sensitivity into account (at least to some degree) and distinguishes between emissions occurring in different geographical regions (spatial differentiation). Another method that applies the mid-point method is the Dutch CML II baseline developed at the Leiden University see Guinée et al. (2001). An example of a method applying the end-point approach is the Dutch EcoIndicator 99 (Goodkoep and Spriensma 2000). This method models the influence on the end-points and goes one step further as it aggregates the end-points in three categories termed areas of protection (AoP). The three AoP areas express damage to ecosystems, human health and resources. Ecoindicator 99 uses a top-down approach. This implies that epidemiological data (such as the number of people that die or get sick from particle pollution per year) are used to estimate the harmfulness of various emissions. More recently methods have been developed which combines the advantages of previous mid-point and end-point methods, namely Impact and the Stepwise 2006 (Humbert et al. 2005, Weidema et al. 2007). The rest of the chapter focuses on the midpoint approach - in particular EDIP 97, which is also applied in the following case chapter. Key assumptions and exceptions In the goal and scope phase, it can also be a good idea to explicitly mention key assumptions and exceptions. This can be related to certain methods for co-product allocation, the system delimitation in general, exemption of certain life cycle stages or impact categories, representativeness of data etc. Data quality requirements (scope) Finally, phase 1 (Goal and scope) should include a description of data types, data sources and requirements to data quality. The data quality goals can be reduced to five key parameters according to Weidema (1998). The first three are:

19 Thrane and Schmidt Temporal scope - Geographical scope - Technological scope The temporal scope concerns the age of the data as well as the period for which data have been collected. Geographical scope concern the area for which data should be collected to satisfy the goal of the study, and the technological scope deals with the type of technology that should be addressed. The latter may concern the level of technology (old, average or cutting edge) but also concern the question of whether the data should reflect a mix of technologies or specific technologies e.g. the marginal technology. Both the geographical and technological scope will depend on the result of the system delimitation and which processes that is included in the product system being analyzed. The temporal scope strongly depends on the goal of study. Studies that concerns decisions with future implication should reflect this by using updated data and future scenarios. The two last parameters are: - Reliability - Completeness. Reliability concerns how the data have been obtained and verified. Measured data are better than estimated data and verification by mass and energy balances is always a good idea to ensure high data quality. Completeness concerns if parts of the data are missing as well as the statistical representativeness of the data. Depending on the goal of scope it is important that the data cover a sufficient number of sites and for adequate time periods. It should be emphasized that the ISO standard uses some of these terms slightly differently. The assessment of obtained data quality in the inventory should be made in the context of the initial quality requirements described in the goal and scope phase. Hence, it is only possible to assess the obtained data quality later in the study e.g. during inventory. Data quality assessment can not be made absolute - it will always be relative to the requirements and the degree of accordance with these. Demands to verification of results The last part of the goal and scope definition is to state the requirements to verification of the LCA. For a comparative study, it is necessary that the equivalence of the systems being compared is evaluated before the interpretation. The systems being compared must have the same functional unit and similar methodological considerations concerning performance, system boundaries, data

20 224 Life Cycle Assessment quality, allocation procedures, and impact assessment etc. Important differences should be reported (ISO ). Studies that are intended to be used for a comparative assertion intended to be disclosed to the public, must be evaluated through a critical review with the participation of interested parties. Under all circumstances, it should be mentioned if a critical review should be conducted and how. A critical review is basically a process intended to ensure consistency between an LCA and the recommendations and requirements in the ISO and standards (ISO ). Phase 2: Life Cycle Inventory The second phase Life cycle inventory analysis (LCI) is probably the most time consuming phase. The main elements of the Inventory are data collection, calculations and finally handling of co-product allocation - see table 3. Phase two: Life Cycle Inventory analysis (LCI) Data collection: Process descriptions Collection of quantitative and qualitative data Calculations and co-product allocation: Relate data to the functional unit (or reference flow) Data quality assessment Presentation and discussion of results (optional) Handling of co-product allocation Table 3: The main elements of the second phase Life Cycle Inventory. The different elements of this phase will be elaborated in the following. Data collection A good point of departure for the data collection is a process diagram, which shows the included unit processes and their interrelationships. The data collection may involve the collection of both quantitative and qualitative data. The data sources can be empirical studies, literature references, databases, expert judgement etc. In countries like Denmark, possible references are also environmental approvals and green accounts. The data can be actual measured data, which is often the most accurate, but can also be based on mass and energy balances, estimates, etc. It is always a good idea to verify the accuracy of the data (including qualitative data) by comparing different data sources. This is also termed data triangulation, and ensures a higher degree of certainty.

21 Thrane and Schmidt 225 The present chapter focuses on so called process LCA where data are collected for a number of specific processes that compose a specific product system. This can also be perceived as a bottom up approach to LCA. But another approach has emerged, which represent a top-down approach, namely the so-called input output LCA or just IO LCA. Apart from a brief description, this approach will not be elaborated in this chapter, but IO LCA should be mentioned because data from IO databases can be used in process LCAs as well. This is briefly discussed in the following. Input output databases for LCA Environmental Input-Output (IO) databases are based on national economical and environmental statistics. IO LCA has the advantage compared to process LCA that it covers the entire economy. It is therefore not necessary to apply cut-off in IO LCA (Weidema et al. 2005). IO LCA data express the environmental impact for a number of product categories in specific countries or regions of the world. This type of data is more aggregated compared to traditional process LCA data, and even in the most detailed IO database (for US) there are only around 500 product categories. Hence, it is not possible (without modifications) to make an LCA of a very specific type of product. In the context of process LCA, IO LCA data are useful for a number of purposes e.g.: - verify LCA results, - fill out data gaps - provide an estimate of hot-spots and where to focus in data collection - provide an estimate of the significance and type of processes that are omitted in a process LCAs IO LCA, and hybrid LCA that seeks to combine the advantages of IO and process LCA will not be further explained here, but there exist several articles and books on the subject, e.g. Rebitzer et al (2004). An environmental IO study of the Danish economy is available in Weidema et al. (2005). Explanations are also available on the homepage Calculations After the data have been collected, they should be validated and related to the functional unit. The validation should ideally take place during the data collection and must ensure that the data quality requirements are meet. Validation can be performed by mass balances, energy balances, or other types of checks such as comparisons with data from similar processes.

22 226 Life Cycle Assessment After this, the data must be related to the functional unit or the reference flow which expresses the functional unit. If the raw data are expressed as flows per year, and if the reference flow is 1 kg of product A, it is obviously necessary to divide the total exchange for the whole year with the amount of product A that is produced in the same period measured in kg. If the functional unit is 1 kg consumed product at the use stage, it can be necessary to include considerations of product losses along the product chain and the result may be that the functional unit at the start of the life cycle is considerably larger than 1 kg (sometime you need 3 kg caught fish to product 1 kg of fish filet). Still, it is a good idea to relate the exchanges to the same product quantity e.g. 1 kg at each life cycle stage, and then compensate for product losses later. Data quality assessment The inventory could also include a data quality assessment where the obtained data are compared to the initial data quality requirements. Important variations from the data quality goals should be reported. In a LCA screening, this will typically only include a brief description and assessment of the most problematic data sets. A detailed pedigree diagram procedure for data quality assessment for detailed LCA is available in Weidema (1998). In the data collection, there will often be a significant number of exchanges that are not expressed as elementary flows. An example is energy flows where the units often are kwh or MJ instead of inputs of coal and outputs of various emissions such as CO 2, SO 2 etc. In most PC tools applied today there are a number of databases that can be used to determine the elementary flows for a significant number of processes and products. Still, there are specific products and processes that are not available and here it is up to the LCA practitioner to collect data further back in the life cycle and express the flows as elementary flows. In cases where this is omitted for various reasons, it should be reported and discussed to which extend this omission is believed to influence the results. This can be done in the Interpretation phase. The result of the LCI is a complete inventory of elementary flows, which is used as the input for the LCIA phase. Data which are not expressed as elementary flows (environmental exchanges) will not be treated at the LCIA step. Presentation and discussion of results at LCI level It is important to mention that it possible to make a separate presentation and discussion of the results from the inventory as a supplement to the LCIA. This has several advantages. It becomes easier to reproduce the LCIA, it shows the results on a very early stage with the least possible amount of data

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