Additional starting points for the Interpretation phase in this Guide include the following. Interpretation does not replace an external interactive critical review. A full error analysis is not feasible for LCA. Even a partial Monte-Carlo analysis is currently unachievable for simplified or detailed LCA, and is only mentioned as an extension. 5.3 Recipe 5.3.1 Procedures Topic The procedural organisation must ensure the common treatment of general and specific subjects that the parties involved want to discuss during the Interpretation phase. The following procedural issues should be taken into account. The choice of assumptions and data to be checked or analysed in the Interpretation phase, especially product specification and system specifications, methodological choices, and the data and calculation models used. Execution of sensitivity analysis and uncertainty analysis. Part 2a: Guide 5


Execution of sensitivity analysis and uncertainty analysis. Part 2a: Guide 5. Interpretation Recipe Procedures Consistency check Completeness check Contribution analysis Perturbation analysis Sensitivity and uncertainty analysis Conclusions and recommendations Page

Guinée et al., Handbook on LCA: Operational Guide to the ISO Standards (2002)


Part 2a: Guide Quantification of the accuracy of the calculated LCA results, including imprecision due to disregarding and the use of cut-off criteria, data uncertainties and uncertainties arising from deviations in the process situation being analysed. Determination of the bandwidth of the LCA results, in relation to the quantification of the accuracy of these results and the adequacy, quality and results of sensitivity analysis. Effects of the bandwidth conclusions with respect to possible implications of conclusions based on LCA results, possible adjustment of the goal of the LCA study and possible revision of further progress of the process. Intentions with respect to a possible iterative approach to the phases (in terms of allocation and weighting). Further process planning and process management. Main choices In the course of this LCA phase, the supervisory process should be arranged so as to preserve the authoritativeness of the results


Further process planning and process management. Main choices In the course of this LCA phase, the supervisory process should be arranged so as to preserve the authoritativeness of the results. The potential input from stakeholders should also be used to improve the quality of the LCA. In this situation of ‘mandated science’ this implies that, depending on the specific process context, there should be room for interaction between the parties involved on topics that are relevant to the selection of topics to be included in consistency checks, sensitivity analyses, final conclusions and so on. Guidelines Guidelines for simplified and detailed LCA and optional extensions Determine the competencies and responsibilities of the LCA research scientists, any critical reviewers, the LCA clients and other interested parties using Table 5.3.1. Address potential bottlenecks in the LCA process by making arrangements in line with Table 5.3.2 to ensure the orderly progress of the project.


Part 2a: Guide Table 5.3.1. Overview of the competencies of the various actors during the LCA process for the different process contexts


Item 1a 1b 2a 2b 3a 3b Description First instructions with respect to fulfilment of LCA assignment First instructions with respect to fulfilment of assignment of critical reviewer Written response to instruction on LCA assignment Written response to instructions on assignment of critical reviewer1 Possible revision of the first instructions on LCA assignment Possible report on incompatible opinions on LCA assignment Presentation of draft interim report (= draft text of Interpretation) Written response to draft interim report on Interpretation Possible revision of draft report on Interpretation Possible report on incompatible opinions arising during the Interpretation Final opinion on final interim report on Interpretation Process context I C – L – C L L C L L C II C or S CorS L + R R C or S L L + R C or S L + R L C or S III S S L + R R S L L + R S L + R L S Legend Process context I = few diverging interests, potentially strong impact Process context II = many diverging interests,


C or S L L + R C or S L + R L C or S III S S L + R R S L L + R S L + R L S Legend Process context I = few diverging interests, potentially strong impact Process context II = many diverging interests, potentially weak impact Process context III = many diverging interests, potentially strong impact C = first LCA client(s) S = stakeholders (including C) L = LCA research scientists R = critical reviewer Table 5.3.2 Overview of the arrangements that can be made between the various actors for the different process contexts


Item Description Process context I II III a b c d e Widening/supplementation of the study (on request) Validation by an independent expert (on request) Binding advice on decision points by the critical reviewer Final decision-making by the largest possible majority, arbitration or another previously determined procedure Quantification of the influence of incompatible opinions in the final report o o o o o r r r o r r r r r r 1 The actual implementation of all guidelines in this Guide should be checked in a critical review.


Part 2a: Guide Legend Process context I = few diverging interests, potentially strong impact Process context II = many diverging interests, potentially weak impact Process context III = many diverging interests, potentially strong impact r = recommended o = option Example (case history) “The first Dutch Packaging Covenant stipulated LCA studies for a number of product groups. According to this covenant, disposable packaging systems had to be replaced by refillable packaging systems in all cases where refillable systems produce “clearly less environmental damage”. As a result, an extensive project was organised between 1992 and 1994, to manage the implementation of the LCAs needed and to manage an accompanying process. The covenant partners did not define the phrase ‘clearly less environmental damage’, nor did they establish which environmental aspects were to be taken into account


The covenant partners did not define the phrase ‘clearly less environmental damage’, nor did they establish which environmental aspects were to be taken into account. The LCA project was organised by a steering group involving many stakeholders (several business organisations and Dutch consumers' organisations; the environmentalist movement was not willing to participate). At the end of the project, the steering group concluded: “In general, there are no great differences in environmental aspects between disposable and refillable packaging systems, with the exception of the waste aspect.” However, this first conclusion had no consequences: the commission that had to check the implementation of the covenant concluded that the interpretation of the LCA results in terms of “clearly less environmental damage” had not been unambiguously defined, and formulated criteria themselves. However, the commission concluded that further study was required with respect to a number of comparisons


However, the commission concluded that further study was required with respect to a number of comparisons. A good example of this is the comparison between milk in cartons and milk in a refillable polycarbonate bottles. The representatives of the consumers' organisations felt that the LCA had proved the PC-bottle packaging system to be environmentally preferable. The business organisations involved did not endorse to this. In their view, this was not a question of “clearly less environmental damage” because a changeover from cartons to PC bottles would only achieve waste reduction and possibly some reduction of eutrophication.” 5.3.2 Consistency check Topic The objective of the consistency check is to determine whether the assumptions, methods, models and data are consistent with the goal and scope of the study, both over a product’s life cycle and across various options. As discussed above, we place this issue at the very start of the Interpretation phase, contrary to ISO 14043


As discussed above, we place this issue at the very start of the Interpretation phase, contrary to ISO 14043. All other analyses of the results and sensitivity analyses are futile if the assumptions and models used in the LCA are inconsistent with the goal and scope of the study, or inconsistent across the various options. Main choices Only those included in ISO 14043.


Part 2a: Guide Guidelines Guidelines for simplified and detailed LCA and optional extensions Conduct a consistency check to determine whether the assumptions, methods, models and data are consistent with the goal and scope of the study. Check for unexpected results based on expert knowledge, and if possible, based on a comparison between the results of the study and results of previous studies on related subjects. In the case of comparisons in particular, check for differences between the options being compared as regards data sources, data accuracy, technical level, temporal aspects, geographical representativeness and functions. If inconsistencies are found: justify them, if they are justifiable; assess their validity and influence; if possible and necessary, reiterate previous steps in the methodology and adapt the study results by removing the inconsistencies found; report any remaining inconsistencies explicitly and justify these together with the results of the study


In addition to a data-oriented consistency check, analyse and discuss the consistency of the procedures followed. Example (hypothetical) “In this example, it has been decided to develop a checklist that will be used to determine whether the model and data choices made in the study are equivalent either within a product’s life cycle or across the various options. The checklist includes the following. Differences in data sources. For instance, the information on the production of ethylene may be based on the literature, while the information on PE production is based on primary data. Differences in data accuracy. For instance, a highly detailed modularisation might be available for option A, while option B is described as an accumulated black box system. Differences in technical level


For instance, a highly detailed modularisation might be available for option A, while option B is described as an accumulated black box system. Differences in technical level. For instance, data on chemical waste incineration may be based on an experimental process (e.g., a new installation with higher process efficiency at pilot plant level) while electricity production data are based on existing large-scale technology. Temporal differences. For example, data on PE production may refer to recently developed technology, while the refining process is described for a mixture of technologies, including recently built and old plants. Differences in data age. For instance, data for option A are five-year-old primary data, whereas data for Option B have been recently collected


Differences in data age. For instance, data for option A are five-year-old primary data, whereas data for Option B have been recently collected. Differences in geographical representativeness; data for option A might represent a mixture of European technologies, while option B is representative of one EU country with a high level of environmental protection or one single plant. Differences in the functions performed by the two products or options. A detailed report on the discrepancies found has been added as an appendix to the LCA report. The overall findings suggest that no serious consistency problems were present.”


Part 2a: Guide 5.3.3 Completeness check Topic The completeness check ensures that all relevant information and data needed for the Interpretation phase are available and complete. In the error check, the study is checked for false assumptions, model choices and data. Having an expert look at the results of the LCA and how they were generated can uncover errors and incomplete data. An LCA expert could check the methodology used in the different phases of the project and the results and conclusions of the analysis in relation to the goal and scope of the study. Technical experts could also look at the parameters describing the product system and the data used. Main choices Only those included in ISO 14043


Technical experts could also look at the parameters describing the product system and the data used. Main choices Only those included in ISO 14043. Guidelines Guidelines for simplified and detailed LCA and optional extensions Conduct a completeness check based on the knowledge of one or more internal or external LCA experts and/or technical expert(s), and, if possible, based on a comparison between the results of the study and results of previous studies on related subjects. Refer to the “Interventions for which characterisation factors are lacking” and the “Economic flows not followed to system boundary” If errors or gaps are found: justify them, if they are justifiable; assess their validity and influence; if possible and necessary, reiterate the previous step in the methodology and adapt the study results by correcting the errors or gaps found; report any remaining issues explicitly and justify these together with the results of the study


Special attention should be given to comparisons. If the completeness of the data differs between alternative systems, the influence of this difference should be estimated (e.g., by way of a contribution analysis, a perturbation analysis or a sensitivity analysis; see the next sections). In addition to a data-oriented completeness check, analyse and discuss, if necessary, the completeness of the procedures followed. Example (hypothetical) “A technical expert has assessed the qualitative and quantitative validity of the system, looking at the following questions. Is the structure of the process tree correct? Are any processes missing? Are any economic inputs or outputs missing? Are any emissions or extractions missing? Is the magnitude of the emission correct? Do the mass balances add up to zero? A detailed report by the technical expert has been added as an annex. The expert did not find any major problems with the validity of the data and the system.”


Part 2a: Guide 5.3.4 Contribution analysis Topic The contribution analysis calculates the overall contribution to the results of the various factors. The contributions are usually expressed as percentages of the total. Contribution analysis answers questions about the contribution of specific environmental flows, processes or impacts to a given environmental score. Main choices Only those included in ISO 14043


Contribution analysis answers questions about the contribution of specific environmental flows, processes or impacts to a given environmental score. Main choices Only those included in ISO 14043. Guidelines Guidelines for simplified and detailed LCA and optional extensions Conduct several contribution analyses by calculating the contributions to the results of: individual processes within the overall process (e.g., pasteurising as a phase within the production of 1000 I of milk); a group of processes within the overall process (e.g., various conservation measures as a phase within the production of 1000 I of milk); a life-cycle stage within the overall process (e.g., the agricultural production of 1000 I of milk); the packaging phase within the overall process (e.g., the bottles used to package 1000 I of milk); an environmental flow within the overall process (e.g., flow in the production of 1000 I of milk); specific product properties, e.g., the energy requirement of a refrigerator


Do this, when applicable, at the level of: the inventory results, e.g., emissions or extractions of (groups of) substances; the environmental profile; the normalised environmental profile; the weighting results. For a description of calculation techniques, see Part 2b, Section 5.5. Pay special attention to processes and process data whose data quality gives reason for concern (see Section 3.3.5 on data quality) or processes for which the data are based on estimations (see Section 3.3.6 on data collection and Section 3.3.8 on data estimation). If the contribution analysis shows that the contributions of these processes or flows may be substantial, this may be a reason to return to the data collection step to collect more data, or data of a better quality. Pay special attention to differences in completeness between alternative systems


Pay special attention to differences in completeness between alternative systems. Are the data missing in one alternative very important contributors in another? Report and justify the levels (inventory table, environmental profile, etc.; processes, lifecycle phases, elementary flows, etc.) chosen for the contribution analyses. Compare, if possible, the results of a contribution analysis with those of contribution analyses reported in previous studies on related products. Report results of the contribution analysis as tables and, if useful, as graphs. Example (hypothetical) “A contribution analysis for the emission of cadmium to fresh water yields the following list of contributing processes.


Part 2a: Guide Process Electricity production Refining; allocated to naphtha Incineration of chemical waste Contribution 56% 25% 19% Thus, a large part (56%) of the emission of cadmium to surface water is caused by electricity production. Note that the 25% contribution made by the refining process is only the part that is allocated to naphtha production, and that this excludes the production of fuel oil and other co-products. If the emission of cadmium to surface water is a major concern in the study, it is clear that the process data for the electricity production must be checked carefully.” 5.3.5 Perturbation analysis Topic Perturbation analysis involves the study of the effects of small changes within the system on the results of an LCA.1 The effects of these small changes are calculated simultaneously for all flows within the system, including economic flows


The analysis can be conducted at different levels of aggregation: inventory table, indicator results, normalised indicator results or weighting results. The main difference between the contribution analysis and the perturbation analysis lies in the fact that it takes into account not only environmental flows but also economic flows between unit processes. This is important, because multipliers of economic flows can exceed unit when internal loops (see also Section 3.3.10) are present. The perturbation analysis may be very important in an improvement analysis and in a sensitivity analysis aimed at identifying important points and refining the LCA study. Main choices Perturbation analysis is a potentially useful addition to the methods mentioned in ISO 14043. Guidelines Guidelines for simplified and detailed LCA Perturbation analysis requires dedicated software routines which are not generally available. Therefore, it may be skipped in many cases


Guidelines Guidelines for simplified and detailed LCA Perturbation analysis requires dedicated software routines which are not generally available. Therefore, it may be skipped in many cases. One might consider, however, to use specialised software including a perturbation analysis in selected cases. Guidelines for optional extensions Conduct perturbation analyses at the level of: the inventory table; the environmental profile; the normalised environmental profile; the weighting results. For a description of calculation techniques, see Part 2b, Section 5.6. Pay special attention to processes and process data whose data quality gives reason for concern (see Section 3.3.5 on data quality) or processes whose data were based on 1 In the perturbation analysis, all system parameters (process data, characterisation factors, etc.) are successively changed marginally (e.g. 1%), and the resulting change in a system output (emission, category indicator result, etc.) is observed


1%), and the resulting change in a system output (emission, category indicator result, etc.) is observed. The ratio between these is the multiplier. Hence, if a 1% decrease in the fuel input of a production process leads to a 3% decrease in the emission of the multiplier is said to be 3.


Part 2a: Guide estimations (see Section 3.3.6 on data collection and Section 3.3.8 on data estimation). If the perturbation analysis shows that small changes in these processes or flows can have relatively large effects on the results, this may be a reason to go back to the data collection step to collect more data, or data of a better quality. Pay special attention to differences in completeness between alternative systems. Are the results very sensitive to small changes in the data missing in one alternative? Report and justify the level (inventory table, environmental profile, etc.) at which perturbation analyses have been conducted. If possible, compare the results of a perturbation analysis with results of perturbation analyses reported in previous studies on related products; Report the results of the perturbation analysis as tables and, if useful, as graphs


Example (hypothetical) “A perturbation analysis for the emission of benzene to fresh water yields the following: Process production of ethylene production of PE production of PE production of plastic bags production of plastic bags packaging a loaf refining production of ethylene packaging a loaf rest (19 items) Flow output of ethylene input of ethylene output of PE input of PE output of plastic bags output of loaves packaged output of naphtha input of naphtha input of plastic bags Multiplier –1.15 0.92 0.92 0.92 0.92 0.92 0.90 0.90 0.70 <0.1 These results should be interpreted as follows: if the output of ethylene from the production of ethylene is increased by one per cent, the emission of benzene to fresh water will decrease by 1.15 per cent. This means, among other things, that the output of ethylene from the process of production of ethylene should be known fairly accurately for a reliable result on emissions of benzene to fresh water


This means, among other things, that the output of ethylene from the process of production of ethylene should be known fairly accurately for a reliable result on emissions of benzene to fresh water. It also means that a technological improvement affecting this coefficient leads to a large reduction in the emission of benzene to fresh water. Finally, it shows that most of the coefficients (19 out of 28) have a negligible influence on this emission.” 5.3.6 Sensitivity and uncertainty analysis Topic In order to use LCA as a tool for decision-making, information is needed on the robustness of the results. This element of the Interpretation phase assesses the influence on the results of variations in process data, model choices and other variables. In the sensitivity analysis, these changes are deliberately introduced in order to determine the robustness of the results with regard to these variations


In the sensitivity analysis, these changes are deliberately introduced in order to determine the robustness of the results with regard to these variations. The uncertainty analysis uses empirical data on the uncertainty ranges of specific data to calculate the total error range of the results. Main choices Since the required data are often lacking and since most LCA software does not include the possibility to conduct a full sensitivity and uncertainty analysis, such analyses can not be made obligatory. However, it is good practice to implement at least partial sensitivity and uncertainty analyses.


Part 2a: Guide Guidelines Guidelines for simplified LCA Select and justify a limited set of issues for sensitivity analysis, based on the results of contribution analysis, perturbation analysis and the subjects identified as issues for Interpretation in the various steps (e.g., influence of future scenarios, effect of data quality, key data sensitivity, possible contribution of missing processes) See Part 2b, Section 5.7 for a checklist of issues for simplified LCA. Conduct sensitivity analyses on the issues selected, at the level of: the inventory table; the environmental profile; the normalised environmental profile; the weighting results. Report the issues identified for sensitivity analyses. Report the results of the sensitivity analyses and possible uncertainty analyses conducted in table and, if useful, in graphic format. If possible, compare the results of a sensitivity and uncertainty analysis with results of such analyses reported in previous studies on related products


If possible, compare the results of a sensitivity and uncertainty analysis with results of such analyses reported in previous studies on related products. Pay special attention to processes and process data whose data quality gives reason for concern (see Section 3.3.5 on data quality) or processes whose data were based on estimations (see Section 3.3.6 on data collection and Section 3.3.8 on data estimation). If the sensitivity analysis shows that changes in these processes or flows can have important effects on the results of the LCA, this may be a reason to go back to the data collection step to collect more data, or data of a better quality Pay special attention to differences in completeness between alternative systems


Are the results very sensitive to changes in the data missing in one alternative? Guidelines for detailed LCA All guidelines provided above for simplified studies apply here, but the selection of issues in the first guideline should now be comprehensive instead of limited. Guidelines for optional extensions All guidelines provided above for detailed studies apply here. In addition the following guideline is given: Conduct more detailed sensitivity analyses or, if possible, conduct partial uncertainty analysis on the issues selected and on parameters for which uncertainty ranges are known, for instance by Monte Carlo simulations. Example (hypothetical) “Since the example LCA is a simplified LCA, the uncertainty analysis is skipped and the sensitivity analysis is confined to an ISO-based checklist, including: rules for allocation; characterisation method; weighting method and data; cut-off criteria; boundary setting and system definition; data; normalisation data


With regard to data uncertainties in a simplified LCA, the focus is on the most important processes and flows in the contribution and/or perturbation analyses. The data for these processes and flows have been checked and a sensitivity analysis on this data has been conducted for data variations.


Part 2a: Guide With regard to allocation rules, a sensitivity analysis has been conducted by comparing the results of economic allocation with those of allocation on the basis of energy content. Results are presented as an appendix to the report. There is no major difference with economic allocation.” 5.3.7 Conclusions and recommendations Topic In this last step of the Interpretation phase, conclusions are drawn and recommendations are made for the intended audience of the study, based on the information gathered in the previous phases of the LCA and combined with the results of the previous steps of the Interpretation phase. Main choices For the sake of transparency, it is good to separate analysis and opinion, and therefore, to have a separate step in which final conclusions are drawn and recommendations are made


Main choices For the sake of transparency, it is good to separate analysis and opinion, and therefore, to have a separate step in which final conclusions are drawn and recommendations are made. Guidelines Guidelines for simplified and detailed LCA and optional extensions Formulate conclusions and recommendations transparently and unambiguously by: giving a summary of key issues; justifying conclusions drawn by means of materials presented in the report and on the basis of the entire report. Formulate conclusions and recommendations in line with the goal and scope of the study and the results found. Take the results of the consistency and completeness checks and the sensitivity and uncertainty analyses on data and models into account in formulating conclusions and recommendations. Inconsistencies, incompleteness and errors must either be corrected or incorporated in the conclusions of the study


Inconsistencies, incompleteness and errors must either be corrected or incorporated in the conclusions of the study. Data and parameters to which the conclusions of the study are most sensitive must be mentioned. Check and report whether the limitations of LCA as a tool and the limitations of the models used allow for the conclusions and recommendations intended. If possible and relevant, discuss the results of the study in relation to earlier, related studies. In the case of a comparison, report and justify the significance of the differences in results. Check the concomitant statement made on this in the Goal and scope definition and indicate whether the differences in results are large enough to allow the conclusion that a certain product alternative is more environmentally sound than another alternative. In the case of a comparison, give a summary of key issues. For example, product system A is substantially better with respect to acidification than product system B


In the case of a comparison, give a summary of key issues. For example, product system A is substantially better with respect to acidification than product system B. Example (hypothetical) “Although there a number of data gaps, for instance relating to ancillary inputs, capital equipment, and toxicity parameters for dioxins, it seems that a fairly complete picture of the bread packaging systems has been obtained. The most important results are presented in


Part 2a: Guide the tables and figures below. Important contributions are made by several emissions, mainly on impact categories that relate to toxicity, photo-oxidant formation, and acidification; see the table. As the goal was formulated in terms of finding options for product and process improvement, the results of the analysis cannot be used for comparison with alternative packaging systems.” 5.4 Results of Interpretation The results of the Interpretation phase are two-fold. First, there are the results of all forms of consistency and uncertainty analysis, leading to a number of judgements relating to the quality and the robustness of the findings of the Inventory analysis and Impact assessment. Second, there is a description of the final conclusions and recommendations, for instance as to product choice or improvement.


Part 2a: Guide Appendix A: Terms, definitions and abbreviations This glossary provides definitions of the key terms and abbreviations used in this Guide. Terms marked with an asterisk (*) are defined in accordance with the definitions given in the ISO 1404X series of standards, although not necessarily according to the letter. For reasons explained in the text, several definitions adopted here deviate substantively from those of ISO. In this Glossary these are marked as "adapted from ISO". Cross-references, indicated by an arrow point to the preferred terms used in this Guide. Terms abiotic resource a natural resource (including energy resources) regarded as non-living, e.g. zinc ore, crude oil, wind energy allocation multifunctionality and allocation alternative one of a set of product systems studied in a particular LCA, e.g. for comparison (note: some LCA steps are carried out for all alternatives together (e.g


for comparison (note: some LCA steps are carried out for all alternatives together (e.g. selection of impact categories), while others are repeated for each alternative (e.g. characterisation) area of protection a cluster of category endpoints of recognisable value to society, viz. human health, natural resources, natural environment and man-made environment average modeling proportional modeling background system/process a system or process for which secondary data, viz. databases, public references, estimated data based on input-output analysis, are used in an LCA baseline method (model, impact category, LCA, etc.) a method (etc.) recommended in this Guide for operationalising an LCA or methodological step biotic resource a natural resource (including energy resources) regarded as living, e.g. rainforests, elephants casualty human injury or death due to direct, physical cause, e.g. explosion or traffic collision (but not indirect casualties, e.g


rainforests, elephants casualty human injury or death due to direct, physical cause, e.g. explosion or traffic collision (but not indirect casualties, e.g. due to toxics) category endpoint * an attribute or aspect of the natural environment, human health, natural resources or the man-made environment identifying an issue of concern, e.g. loss of coral reefs or crops, damage to buildings category indicator * a quantifiable representation of an impact category, e.g. infrared radiative forcing for climate change category indicator result * indicator result cause-effect network environmental mechanism change-oriented LCA a type of LCA focusing on the environmental changes resulting from a switch to or from a particular product system or an extra functional unit of a particular product system


Part 2a: Guide characterisation * a step of Impact assessment, in which the environmental interventions assigned qualitatively to a particular impact category (in classification) are quantified in terms of a common unit for that category, allowing aggregation into a single score: the indicator result; these scores together constitute the environmental profile characterisation factor * a factor derived from a characterisation model for expressing a particular environmental intervention in terms of the common unit of the category indicator, e.g


(photochemical ozone creation potential of methanol) characterisation method a method for quantifying the impact of environmental interventions with respect to a particular impact category; it comprises a category indicator, a characterisation model and characterisation factors derived from the model characterisation model a mathematical model of the impact of environmental interventions with respect to a particular category indicator characterisation result environmental profile classification * a step of Impact assessment, in which environmental interventions are assigned to predefined impact categories on a purely qualitative basis closed loop recycling * recycling of material within one and the same product system combined waste processing a method of waste processing in which more than one form of waste is processed simultaneously comparative assertion * an environmental claim regarding the superiority or equivalence of one product relative to a competing product performing the


one form of waste is processed simultaneously comparative assertion * an environmental claim regarding the superiority or equivalence of one product relative to a competing product performing the same function; particular requirements are set by ISO on comparative assertions disclosed to the public completeness check * a step of the Interpretation phase to verify whether the information yielded by the preceding phases is adequate for drawing conclusions in accordance with the Goal and scope definition consistency check * a step of the Interpretation phase to verify whether assumptions, methods and data have been applied consistently throughout the study and in accordance with the Goal and scope definition contribution analysis * a step of the Interpretation phase to assess the contributions of individual life cycle stages, (groups of) processes, environmental interventions and indicator results to the overall LCA result (e.g


as a percentage) co-product * any of two or more functional flows from a co-production process co-production process a unit process having more than one functional flow, e.g. crude oil refining critical review * an expert (internal or external) review of an LCA, designed to ensure validity, consistency, transparency and credibility of results damage approach definition of category indicators close to areas of protection


Part 2a: Guide data category * a heading for classifying data in an LCA, e.g


energy inputs, raw material inputs, ancillary inputs, other physical inputs, products, emissions to air, emissions to water, emissions to land, other environmental aspects data quality * a data characteristic relevant for the capacity of the data to satisfy stated requirements data quality requirements * specification, in general terms, of the quality criteria to be satisfied by the data used in an LCA depletion a decrease in the stock of a biotic or abiotic resource due to extraction thereof descriptive LCA a type of LCA focusing on the contribution of a particular way of fulfilling a certain function to the entire spectrum of environmental problems as they currently exist or are being created detailed LCA the baseline LCA elaborated in this Guide, complying with the ISO 1404X standards and representative of studies typically requiring between 20 and 200 person-days of work difference analysis a type of LCA focusing on the differences between two alternative product systems, thus


and representative of studies typically requiring between 20 and 200 person-days of work difference analysis a type of LCA focusing on the differences between two alternative product systems, thus ignoring those unit processes that are qualitatively and quantitatively identical economic flow a flow of goods, materials, services, energy or waste from one unit process to another; with either a positive (e.g


steel, transportation) or zero/negative (e.g. waste) economic value economic process unit process economy-environment boundary see also: system boundary elementary flow * matter or energy entering or leaving the product system under study that has been extracted from the environment without previous human transformation (e.g. timber, water, iron ore, coal) or is emitted or discarded into the environment without subsequent human transformation (e.g


timber, water, iron ore, coal) or is emitted or discarded into the environment without subsequent human transformation (e.g. or noise emissions, wastes discarded in nature) see also: environmental intervention emission a chemical or physical discharge (of a substance, heat, noise, etc.) into the environment, considered as an environmental intervention endpoint category endpoint endpoint approach damage approach environment system the natural environment and its constituent processes environmental effect environmental impact environmental impact a consequence of an environmental intervention in the environment system environmental intervention a human intervention in the environment, either physical, chemical or biological; in particular resource extraction, emissions (incl. noise and heat) and land use; the term is thus broader than (‘elementary flow’ environmental life cycle assessment * life cycle assessment


Part 2a: Guide environmental mechanism * for a given impact category, the chain of environmental processes linking interventions to impacts; modeled in LCA (usually only partially) to one or more category endpoints by means of a characterisation model environmental process a physical, chemical or biological process in the environment system that is identified as part of the causal chain linking a particular environmental intervention to a particular impact, e.g


pollution leaching or bioaccumulation; for a given impact category, the environmental processes together form the environmental mechanism environmental profile the overall result of the characterisation step: a table showing the indicator results for all the predefined impact categories, supplemented by any other relevant information environmental relevance * the degree of linkage between a category indicator and category endpoint expert review * critical review extraction withdrawal of a biotic or abiotic resource from the environment in a unit process, considered as an environmental intervention final product a product requiring no additional transformation prior to use flow diagram a graphic representation of the interlinked unit processes comprising the product system foreground system/process a system or process for which primary, site-specific data are used in an LCA, for whatever reason format a structured framework for representing and possibly processing unit process data as


a system or process for which primary, site-specific data are used in an LCA, for whatever reason format a structured framework for representing and possibly processing unit process data as well as any relevant remarks function a service provided by a product system or unit process functional flow any of the flows of a unit process that constitute its goal, viz


the product outflows of a production process and the waste inflows of a waste treatment process functional unit * the quantified function provided by the product system(s) under study, for use as a reference basis in an LCA, e.g


1000 hours of light (adapted from ISO) goal and scope definition * the first phase of an LCA, establishing the aim of the intended study, the functional unit, the reference flow, the product system(s) under study and the breadth and depth of the study in relation to this aim grouping * a step of Impact assessment in which impact categories are aggregated in one or more sets defined in the Goal and scope definition phase; it may take the form of sorting and/or ranking impact assessment * the third phase of an LCA, concerned with understanding and evaluating the magnitude and significance of the potential environmental impacts of the product system(s) under study impact category * a class representing environmental issues of concern to which environmental interventions are assigned, e.g. climate change, loss of biodiversity impact score indicator result


Part 2a: Guide indicator result * the numerical result of the characterisation step for a particular impact category, e.g. 12 kg for climate change inflow input input a product (goods, materials, energy and services), waste for treatment or environmental intervention (including resource extraction, land use, etc.) modeled as ‘entering’ a unit process (adapted from ISO) interested party stakeholder intermediate product * an input or output from a unit process which undergoes further transformation before consumptive use interpretation * the fourth phase of an LCA, in which the results of the Inventory analysis and/or Impact assessment are interpreted in the light of the Goal and scope definition (e.g


by means of contribution, perturbation and uncertainty analysis, comparison with other studies) in order to draw up conclusions and recommendations intervention environmental intervention inventory analysis * the second phase of an LCA, in which the relevant inputs and outputs of the product system(s) under study throughout the life cycle are, as far as possible, compiled and quantified inventory table the result of the Inventory analysis phase: a table showing all the environmental interventions associated with a product system, supplemented by any other relevant information (adapted from ISO) land occupation the unavailability of a given plot of land for alternative uses for a certain period of time land transformation the change in the quality of a given plot of land due to a particular mode of human use, measured in terms of changes in biodiversity and life support functions LCA process the integral series of exchanges among the individuals and organisations participating in an


mode of human use, measured in terms of changes in biodiversity and life support functions LCA process the integral series of exchanges among the individuals and organisations participating in an LCA project, from project initiation and guidance through to interpretation and discussion of the results LCA project a project that seeks to obtain particular results by means of an LCA study and LCA process; besides commissioning parties and practitioners, it may also involve other organizations and individuals, in the capacity of data supplier, peer reviewer or interest group, for example LCA study an environmental study in which LCA methodology is employed, performed by practitioners who may or may not be affiliated to the party or parties commissioning the study life cycle * the consecutive, interlinked stages of a product system, from raw materials acquisition or natural resource extraction through to final waste disposal life cycle assessment (LCA) compilation and evaluation of the


interlinked stages of a product system, from raw materials acquisition or natural resource extraction through to final waste disposal life cycle assessment (LCA) compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle; the term may refer to either a procedural method or a specific study


Part 2a: Guide life cycle impact assessment * impact assessment life cycle impact category indicator * category indicator life cycle interpretation * interpretation life cycle inventory analysis * inventory analysis life cycle inventory analysis result * inventory table life support functions the ecological structures and processes that sustain the productivity, adaptability and capacity for renewal of lands, water and/or the biosphere as a whole marginal modeling a type of modeling whereby changes in inputs and outputs are modeled on a marginal basis (e.g. full attribution to one additional train passenger of the extra power consumption required for transporting that passenger). Note: use of the word marginal is sometimes ambiguous; see section 1.2.3.4 of Part 3 for more details midpoint approach problem-oriented approach multifunctional process a unit process yielding more than one functional flow, e.g


co-production, combined waste processing, recycling multifunctionality and allocation * a step of the Inventory analysis in which the inventory model is refined and the input and output flows of multifunctional processes are partitioned to the functional flows of those processes natural resource a biotic or abiotic resource that can be extracted from the environment in a unit process non-functional flow any of the flows of a unit process that are not the goal of that process, viz. product inflows, waste outflows and environmental interventions normalisation * a step of Impact assessment in which the indicator results are expressed relative to welldefined reference information, e.g


relative to the indicator results for global interventions in 1995 normalisation factor the reciprocal of the indicator result for a particular impact category and reference system; used in the normalisation step normalisation result normalised environmental profile normalised environmental profile the result of the normalisation step: a table showing the normalised indicator results for all the selected impact categories, supplemented by any other relevant information normalised indicator result the numerical result of normalisation for a particular impact category, e.g. 0.02 yr for climate change open loop recycling * recycling of material generated in one product system in a different product system optional extension an option for enhancing the quality of a detailed LCA to address any obvious shortcomings outflow output


Part 2a: Guide output an economic flow (e.g. energy, waste for treatment) or environmental intervention (e.g. pollutant or noise emission) modeled as ‘leaving’ a unit process (adapted from ISO) perturbation analysis a step of the Interpretation phase to identify any process data in which minor changes may significantly alter the inventory table, the (normalised) environmental profile or the weighting result, to identify efficient options for product improvement or to focus attention on sensitive items phase any of the four basic elements of an LCA, viz


Goal and scope definition, Inventory analysis, Impact assessment and Interpretation pollution a change in the state of the environment due to emissions practitioner * an individual group or organisation conducting an LCA primary function the main function delivered by the product system under study problem-oriented approach definition of category indicators close to environmental interventions procedure the rules and arrangements adopted to manage an LCA study process unit process see also: environmental process product a positively valued economic flow of goods, materials, energy or services produced in a unit process and possibly serving as an input to another unit process product system * a set of unit processes interlinked by material, energy, product, waste or service flows and performing one or more defined functions proportional modeling a type of modeling whereby changes in inputs and outputs are modeled proportionally (e.g


equal attribution to all passengers of the increase in power consumption needed for transporting one additional passenger). Note: use of the word proportional (and average) is sometimes ambiguous; see section 1.2.3.4 of Part 3 for more details prospective LCA change-oriented LCA ranking * a grouping method whereby impact categories are hierarchically ranked (e.g. high, medium, and low priority), applying value choices recycling a unit process, or set of processes, for collecting and/or treating waste from a unit process for useful application in the same or in a different product system (closed and open loop recycling, respectively) reference flow quantified flow generally connected to the use phase of a product system and representing one way (i.e. by a specific product alternative) of obtaining the functional unit release emission retrospective LCA descriptive LCA


Part 2a: Guide sensitivity and uncertainty analysis a step of the Interpretation phase to assess the robustness of the overall LCA results with respect to variations and uncertainties in the methods and data used sensitivity check * an ISO step included in this Guide as part of sensitivity and uncertainty analysis simplified LCA a simplified variety of detailed LCA conducted according to guidelines not in full compliance with the ISO 1404X standards and representative of studies typically requiring from 1 to 20 person-days of work sorting * a grouping method whereby impact categories are sorted on a nominal basis, e.g. by characteristics such as emissions and resource use, or global, regional and local spatial scales stakeholder * an individual group or organisation concerned about or affected by the environmental performance of a product system or the outcome of an LCA


Note: the LCA commissioner is also a stakeholder step a discrete element of any of the four phases of an LCA; some steps (e.g. data format, calculation method) are areas of concern rather than actions subcategory a subdivision of an impact category, e.g


data format, calculation method) are areas of concern rather than actions subcategory a subdivision of an impact category, e.g. freshwater aquatic ecotoxicity as a subcategory of ecotoxicity system boundary * the interface between a product system and the environment system or other product systems third party * a critical reviewer or a stakeholder other than the LCA commissioner or practitioner transparency * open, comprehensive and understandable presentation of information unit process * the smallest portion of a product system for which data are collected in an LCA use process a unit process in which the final product is consumed, thereby delivering the function under study waste (for treatment) an economic flow with a zero or negative value produced in a unit process and serving as an input to another unit process (note: materials such as waste paper and scrap metals with a positive economic, i.e


market value are thus not wastes but products) (adapted from ISO) weighting * a step of Impact assessment in which the (normalised) indicator results for each impact category assessed are assigned numerical factors according to their relative importance, multiplied by these factors and possibly aggregated; weighting is based on valuechoices (e.g. monetary values, standards, expert panel) weighting factor a factor obtained with a weighting method and used to express a particular (normalised) indicator result in terms of the common unit of the weighting result weighting profile * the result of the weighting step: a table showing all the weighting results, supplemented by any other relevant information


Part 2a: Guide weighting result the numerical part of the result of weighting and aggregation of all (normalised) indicator results, e.g. 0.08 yr (note: the result may be expressed as more than one numerical value) Explanatory figures

Part 2a: Guide


Part 2a: Guide Abbreviations ADI ADP ALI AP BDP BUWAL CBA CFC CML CMLCA DALY DCB DGM EBIR EDIP El 99 EIA EIOLCA EP EPS ETH FAETP FNPP FSETP GWP HTP IOA IPCC ISO LCA LCI LCIA LSS MAETP MCA MIET MIR MOIR MRPI MSETP MTC MTR MVOC NOEC NPP ODP OP OTV acceptable daily intake abiotic depletion potential annual limit of intake acidification potential biotic depletion potential Bundesamt für Umwelt, Wald und Landschaft SAEFL) cost-benefit analysis chlorofluorocarbon Centre of Environmental Science - Leiden University chain management by life cycle assessment disability adjusted life years dichlorobenzene Netherlands Directorate-General of Environmental Management (part of VROM) equal benefit incremental reactivity environmental design of industrial products Eco-indicator 99 environmental impact assessment economic input-output life cycle assessment eutrophication potential environmental priority strategy Eidgenössische Technische Hochschule (Zürich) freshwater aquatic ecotoxicity potential


assessment economic input-output life cycle assessment eutrophication potential environmental priority strategy Eidgenössische Technische Hochschule (Zürich) freshwater aquatic ecotoxicity potential free net primary production freshwater sediment ecotoxicity potential global warming potential human toxicity potential input-output analysis Intergovernmental Panel on Climate Change International Organization for Standardization life cycle assessment life cycle inventory analysis (note: this abbreviation sometimes also includes the Goal and scope definition) life cycle impact assessment life support system marine aquatic ecotoxicity potential multi-criteria analysis missing inventory estimation tool maximum incremental reactivity maximum ozone incremental reactivity milieurelevante product informatie (environmentally relevant product information) marine sediment ecotoxicity potential maximum tolerable concentration maximum tolerable risk non-methane volatile organic compound no observed


(environmentally relevant product information) marine sediment ecotoxicity potential maximum tolerable concentration maximum tolerable risk non-methane volatile organic compound no observed effect concentration net primary production ozone depletion potential odour potential odour threshold value


Part 2a: Guide P.M


PAF PBT PEC PNEC POCP RA RAINS SAEFL SETAC SFA SI SPEP SPINE SPOLD TETP UNEP USES-LCA VOC VROM WIA WMO WRI pro memoria (as a reminder) potentially affected fraction persistence, bioaccumulation, toxicity predicted environmental concentration predicted no-effect concentration photochemical ozone creation potential risk assessment regional acidification information and simulation Swiss Agency for the Environment, Forests and Landscape BUWAL) Society for Environmental Toxicology and Chemistry substance flow analysis Systèms International des Unités species-pool effect potential Sustainable Product Information Network for the Environment Society for the Promotion of Life-cycle assessment Development terrestrial ecotoxicity potential United Nations Environment Programme Uniform System for the Evaluation of Substances, adapted for LCA volatile organic compound Netherlands Ministry of Housing, Spatial Planning and the Environment SETAC-Europe Working Group on Impact Assessment World


for the Evaluation of Substances, adapted for LCA volatile organic compound Netherlands Ministry of Housing, Spatial Planning and the Environment SETAC-Europe Working Group on Impact Assessment World Meteorological Organisation World Resources Institute


PART 2B OPERATIONAL ANNEX


Contents of Part 2b List of tables Reading guidance 1. Management of LCA projects: procedures 1.1 1.2 1.3 1.4 1.5 Designing an LCA project Context of an LCA project Process management in LCA Organisation and assignment Reporting on an LCA project 2. Goal and scope definition 2.1 2.2 2.3 2.4 Procedures Goal definition Scope definition Function, functional unit, alternatives and reference flows 3


Goal and scope definition 2.1 2.2 2.3 2.4 Procedures Goal definition Scope definition Function, functional unit, alternatives and reference flows 3. Inventory analysis 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 Procedures Economy-environment system boundary Flow diagram Format and data categories Data quality Data collection and relating data to unit processes Data validation Cut-off and data estimation Multifunctionality and allocation 3.9.1 3.9.2 Economic allocation Solving problems of missing and distorted market prices for step da1 3.9.3 Quantified example of economic allocation and symmetrical substitution 3.9.3.1 3.9.3.2 Economic allocation of simplified hypothetical refinery (SHR) process151 Symmetrical substitution of simplified hypothetical refinery (SHR) process 3.10 Calculation method 4


Impact assessment 4.1 4.2 4.3 Procedures Selection of impact categories Selection of characterisation methods: category indicators, characterisation models and factors 4.3.1 4.3.2 4.3.3 Depletion of abiotic resources Depletion of biotic resources Impacts of land use 4.3.3.1 4.3.3.2 Land competition Loss of biodiversity and life support function 4.3.4 4.3.5 4.3.6 4.3.7 4.3.8 4.3.9 Desiccation Climate change Stratospheric ozone depletion Human toxicity Ecotoxicity Photo-oxidant formation Acidification Eutrophication Waste heat 4.3.10 4.3.11 4.3.12


4.3.13 Odour 4.3.13.1 4.3.13.2 Malodorous air 4.3.14 4.3.15 4.3.16 4.3.17 4.3.18 Malodorous water Noise Impacts of ionising radiation Casualties Interventions for which characterisation factors are lacking Economic flows not followed to system boundary 4.4 4.5 4.6 4.7 4.8 Classification Characterisation Normalisation Grouping Weighting 5. Interpretation 5.1 5.2 5.3 5.4 5.5 5.6 5.7 Procedures Consistency check Completeness check Contribution analysis Perturbation analysis Sensitivity analysis and uncertainty analysis Conclusions and recommendations 6. References


SI and derived units often used in LCA studies Units with conversion factors to SI Prefixes used in presenting quantitative numbers. Composite units often used in LCA studies. Overview of data categories for collecting and reporting the data of unit processes Adapted version of the so-called pedigree matrix Estimation factors for converting NMVOC group emissions into individual compounds Estimation factors for converting group emissions into individual compounds. Overview of preferred units for collecting and reporting the data of unit processes Prices of products with missing or distorted markets. Proceeds from sales and allocation factors for goods and services from an SHR Calculation of selected environmental exchanges to be attributed to waste hydrocarbons from wood preservation (per kton waste hydrocarbon input to the refinery)


Calculation of selected environmental exchanges to be attributed to kerosene (per kton kerosene output from the refinery) Default list of impact categories Requirements for documenting and justifying new impact categories. Impact categories in the Eco-indicator ’99 approach Eco-indicator ’99 damage factors. Environmental Load Units (ELUs) for natural resources. Environmental Load Units (ELUs) for emissions. Requirements for documenting and justifying new impact categories ADP factors for characterising abiotic resources based on ultimate reserves and extraction rates Values for reserve and de-accumulation rates that can be used to calculate alternative reserve and de-accumulation rate based ADPs Factors for characterising abiotic resources based on exergy content (Finnveden, 1996b) Factors for characterising abiotic resources based on exergy content (Ayres et al., Upper (and middle) heating values


factors for characterising climate gases and factors for characterising climate gases Upper and lower limits of the uncertainty range of net GWPs for a few ozone depleting gases factors for characterising ozone depleting gases Time-dependent ODP factors for characterising ozone depleting gases HTP factors for characterising human toxic releases, for infinite and 100-year time horizons and global scale. Alternative HTP factors for characterising human toxic releases, for 20- and 500-year time horizons and global scale, and for infinite time horizon and continental scale. FAETP, MAETP, FSETP, MSETP and TETP factors for characterising ecotoxic releases, for infinite time horizon and global scale. Alternative FAETP, MAETP, FSETP, MSETP and TETP factors for characterising ecotoxic releases, for 100-year time horizon and global scale Alternative FAETP, MAETP, FSETP, MSETP and TETP factors for characterising ecotoxic releases, for 20-year time horizon and global scale


Alternative FAETP, MAETP, FSETP, MSETP and TETP factors for characterising ecotoxic releases, for 500-year time horizon and global scale Alternative MAETP, MSETP and TETP factors for characterising ecotoxic releases, for infinite time horizon and continental scale. Table 2.4.1: Table 2.4.2: Table 2.4.3: Table 2.4.4: Table 3.4.1: Table 3.5.1: Table 3.6.1: Table 3.6.2: Table 3.6.3: Table 3.9.2.1: Table 3.9.3.1.1: Table 3.9.3.2.1: Table 3.9.3.2.2: Table 4.2.1: Table 4.2.2: Table 4.2.3: Table 4.3.1: Table 4.3.2: Table 4.3.3: Table 4.3.4: Table 4.3.1.1: Table 4.3.1.2: Table 4.3.1.3: Table 4.3.1.4: Table 4.3.1.5: Table 4.3.5.1: Table 4.3.5.2: Table 4.3.5.3: Table 4.3.6.1: Table 4.3.6.2: Table 4.3.7.1: Table 4.3.7.2: Table 4.3.8.1: Table 4.3.8.2: Table 4.3.8.3: Table 4.3.8.4: Table 4.3.8.5: List of tables 1996).


High POCPs for background concentrations for characterising photooxidant forming releases to the air. Alternative MIRs, MOIRs and EBIRs for characterising photo-oxidant forming releases to the air Alternative low POCPs for characterising photo-oxidant forming releases to the air Average European AP factors for characterising acidifying releases to the air. Alternative generic AP factors for characterising acidifying releases to the air. Additional region- (or site-) dependent AP factors for characterising acidifying releases to the air Generic EP factors for characterising eutrophying releases to air, water and soil Alternative average and additional region- (site-) dependent European EP factors for characterising eutrophying releases to the air


Inverse OTV factors for characterising odour releases to air Damage factors for characterising radioactive releases Screening factors for characterising radioactive releases (level I) All interventions for which baseline characterisation factors are available Factors for normalisation with the annual extent of the baseline impact categories and characterisation methods for different reference regions Factors for normalisation with the annual per-capita extent of the baseline impact categories and characterisation methods for different reference regions Table 4.3.9.1: Table 4.3.9.2: Table 4.3.9.3: Table 4.3.10.1: Table 4.3.10.2: Table 4.3.10.3: Table 4.3.11.1: Table 4.3.11.2: Table 4.3.13.1: Table 4.3.15.1: Table 4.3.15.2: Table 4.4.1: Table 4.6.1: Table 4.6.2:


Part 2b: Operational annex Reading guidance This is Part 2b of the publication entitled “Handbook on life cycle assessment: An operational guide to the ISO standards”. The entire publication consists of three parts: Part 1 (“LCA in perspective”) is a short introduction describing in broad terms the purpose, role, applications and limitations of life cycle assessment. Its main intended readership consists of people who have to commission the execution of LCAs and who will use the results of such analyses. Part 2 consists of two parts: 2a (“Guide”) and 2b (“Operational annex”). Its target audience is those concerned with the actual execution of LCAs. Depending on the context and the complexity, this may be one person or an entire research team with diverging backgrounds, such as process technology, product design, end-of-pipe solutions, ecotoxicology and so on


Part 3 (“Scientific background”) provides the foundations and arguments for certain methodological choices, the alternative options available, and much more. It is intended to stimulate scientific debate and progress and to function as a reference book for those who wish to learn more about the rationale behind the Guide’s rules. Part 2b adds operational models and data to the Guidelines formulated in Part 2a. The operational models and data published in this part have been carefully selected on the basis of a set of criteria, including scientific and technical validity, environmental relevance, etc. (see Part 3). In addition to these criteria, the operational data and models had to be publicly accessible. The operational models and data are published in a separate document in order to allow them to be regularly updated without updating the other parts of this LCA Guide


The operational models and data are published in a separate document in order to allow them to be regularly updated without updating the other parts of this LCA Guide. In principle, operational models or data can be provided for each methodological step for which guidelines have been provided in Part 2a. In this edition of the Handbook, however, it has not been possible to provide guidelines for each step. More emphasis has been placed here on the impact assessment steps (providing lists of characterisation factors etc.). It is our intention to address the other steps in a similar way should a subsequent updated edition of the Handbook be realised sometime in the future. The steps which have not been addressed in this edition are labelled "to be inserted"


The steps which have not been addressed in this edition are labelled "to be inserted". The latest updates of Part 2b, including the models and data referred to in this part, can be found on and downloaded from the following website: http://www.leidenuniv.nl/cml/lca2/index.html We would encourage the reader to check this site regularly.


Part 2b: Operational annex 1. Management of LCA projects: procedures 1.1 Designing an LCA project To be inserted 1.2 Context of an LCA project To be inserted 1.3 Process management in LCA To be inserted 1.4 Organisation and assignment To be inserted 1.5 Reporting on an LCA project To be inserted


Part 2b: Operational annex 2. Goal and scope definition 2.1 Procedures To be inserted 2.2 Goal definition To be inserted 2.3 Scope definition To be inserted 2.4 Function, functional unit, alternatives and reference flows SI UNITS Table 2.4.1: Quantity distance, length energy mass radioactivity temperature time volume work SI and derived units often used in LCA studies. Unit meter joule kilogram becquerel kelvin second cubic meter joule Symbol m J = N m kg K s J = N m Table 2.4.2: unit are day hour kilowattuur litre minute (time) tonne year Units with conversion factors to SI. symbol a d h kWh I min t a, y in SI-units 60 s Table 2.4.3: factor Prefixes used in presenting quantitative numbers. name kilo mega giga tera peta centi milli micro nano pico symbol k M G T P c m n p


Part 2b: Operational annex Table 2.4.4: quantity transport functional units Composite units often used in LCA studies units ton km year; lumen year; etc. For the conversion of other units to SI units (or SI-based or SI-derived units), see also: http://www.df.lth.se/~thanisa/recept/units js.html


Part 2b: Operational annex 3. Inventory analysis 3.1 Procedures To be inserted 3.2 Economy-environment system boundary To be inserted 3.3 Flow diagram To be inserted 3.4 Format and data categories THE SPOLD AND SPINE DATA FORMATS FOR LCI DATA Spold format can be found on: http://www.spold.org/ Spine format can be found on: http://deville.tep.chalmers.se/SPINE_ElM/iso.html CHOICE OF DATA CATEGORIES Table 3.4.1 : Overview of data categories for collecting and reporting the data of unit processes. main category data category economic flows inputs and outputs of goods inputs and outputs of services (including transport) inputs and outputs of materials inputs and outputs of energy inputs and outputs of waste (for treatment) environmental interventions extractions of abiotic resources (including gas) extractions of biotic resources land transformation land occupation emissions of chemicals (including radionuclides) emissions of sound emissions of waste heat casualties


Part 2b: Operational annex 3.5 Data quality EXAMPLE OF PEDIGREE MATRIX Table 3.5.1 : Adapted version of the so-called pedigree matrix. pedigree reliability verified data based on measured data verified data based partly on assumptions, or non-verified data based on measurements non-verified data partly based on assumptions qualified estimate (e.g


by industrial expert) non-qualified estimate completeness representative data from a sufficient sample of sites over an adequate period to even out normal fluctuations representative data from a smaller number of sites but for adequate periods representative data from an adequate number of sites but for shorter periods representative data but from a smaller number of sites, for shorter periods, or incomplete data for an adequate number of sites and periods representativeness unknown, or incomplete data from a smaller number of sites and/or for shorter periods temporal correlation less than 3 years of difference from the year of study less than 6 years of difference less than 10 years of difference less than 15 years of difference age of data unknown, or more than 15 years of difference geographical correlation data from area under study average data from larger area that includes area under study data from area with similar production conditions data from area with slightly similar


geographical correlation data from area under study average data from larger area that includes area under study data from area with similar production conditions data from area with slightly similar production conditions data from unknown area or area with very different production conditions further technical correlation data from enterprises, processes and materials under study data on processes and materials under study but from different enterprises data on processes and materials under study but with different technology data on related processes or materials but with same technology data on related processes materials but with different technology 3.6 Data collection and relating data to unit processes BACKGROUND PROCESS DATA The inventory analysis requires data on the physical inputs and outputs of the processes of the product system, regarding product flows as well as elementary flows


Such data are mostly collected on a caseby-case basis, with the help of the companies involved. In addition, there are a number of public data bases which are used more generally: the ETH database for energy production processes (Frischknecht et al., 1993/1995/1996), the APME database for plastics (Boustead, 1994), the BUWAL/SAEFL database for packaging materials (SAEFL, 1998) and the SIMAPRO database containing data from the above databases and additional data (Pré Consultants, 1997). As stated above, the inventory analysis requires extensive data, and the availability and quality of the data may largely determine the outcome of the study. Therefore there is a great need for more standardised data, particularly about background processes, i.e., proceses which are not specific for the given product system. Source: UNEP, 1999. Source: Weidema, 1998b


Part 2b: Operational annex GENERIC CONVERSION FACTORS FOR BREAKING DOWN GROUP PARAMETERS INTO THEIR INDIVIDUAL CONSTITUENTS NOTE that these data are only ESTIMATES ! Table 3.6.1: Estimation factors for converting NMVOC group emissions into individual compounds


Name Ethane Propane n-butane i-butane n-pentane i-pentane n-hexane 2-methylpentane 3-methylpentane 2,2-dimethylbutane 2,3-dimethylbutane n-heptane 2-methylhexane 3-methylhexane n-octane 2-methylheptane n-nonane 2-methyloctane n-decane 2-methylnonane n-undecane dodecane cyclohexane methylcyclohexane ethylene propylene 1-butene 2-butene butylene 1-pentene 2-pentene 2-methylbut–1 -ene 3-methylbut–1-ene 2-methylbut–2-ene styrene acetylene benzene toluene o-xylene m-xylene p-xylene ethylbenzene n-propylbenzene i-propylbenzene 1,2,3-trimethylbenzene 1,2,4-trimethylbenzene 1,3,5-trimethylbenzene o-ethyltoluene Mass fraction in the UK NMVOC emission inventory 0.016821 0.005324 0.064891 0.042643 0.020604 0.034201 0.013661 0.011779 0.008001 0.002695 0.003601 0.003503 0.005425 0.004652 0.002905 0.016173 0.010857 0.012271 0.010938 0.011402 0.012351 0.003342 0.000013 0.002054 0.037958 0.016409 0.004922 0.009375 0.002279 0.003206 0.006196 0.001243 0.001644 0.002713 0.003603 0.016869 0.022817


0.016173 0.010857 0.012271 0.010938 0.011402 0.012351 0.003342 0.000013 0.002054 0.037958 0.016409 0.004922 0.009375 0.002279 0.003206 0.006196 0.001243 0.001644 0.002713 0.003603 0.016869 0.022817 0.069846 0.026428 0.030537 0.030476 0.013297 0.004994 0.004111 0.005409 0.012314 0.006074 0.005673


Part 2b: Operational annex Name m-ethyltoluene p-ethyltoluene 3,5-dimethylethylbenzene 3,5-diethyltoluene formaldehyde acetaldehyde propionaldehyde butyraldehyde i-butyraldehyde valeraldehyde benzaldehyde acetone methylethylketone methyl-i-butylketone cyclohexanone methanol ethanol i-propanol n-butanol i-butanol s-butanol t-butanol cyclohexanol diacetone alcohol dimethyl ether methyl-t-butylether methoxypropanol butylglycol methylacetate ethylacetate n-propylacetate i-propylacetate n-butylacetate s-butylacetate formic acid acetic acid propionic acid methyl chloride methylene chloride methyl chloroform tetrachloroethylene trichloroethylene 1,1-dichloroethylene cis 1,2-dichloroethylene trans dichloroethylene vinylchloride Mass fraction in the UK NMVOC emission inventory 0.007223 0.007223 0.0049 0.0049 0.007788 0.001468 0.001647 0.00102 0.000901 0.000159 0.000726 0.008934 0.007959 0.014137 0.005441 0.000173 0.042804 0.004108 0.014342 0.010091 0.00872 0.000013 0.002054 0.00872 0.000013


0.0049 0.0049 0.007788 0.001468 0.001647 0.00102 0.000901 0.000159 0.000726 0.008934 0.007959 0.014137 0.005441 0.000173 0.042804 0.004108 0.014342 0.010091 0.00872 0.000013 0.002054 0.00872 0.000013 0.000013 0.00227 0.008576 0.000018 0.007261 0.000013 0.000027 0.004396 0.004396 0.000021 0.000021 0.000013 0.000389 0.003999 0.011243 0.007927 0.010883 0.000013 0.000013 0.000013 0.002378 Source: Derwent et al., 1996.


Part 2b: Operational annex Table 3.6.2: Estimation factors for converting group emissions into individual compounds. See table on: http://www.leidenuniv.nl/interfac/cml/lca2/index.html NOTE: this table might be regularly updated and only provides rough estimates of the actual contents of emission groups ! Source: VROM, Dept. Monitoring and Information Management Description (in Dutch) : Omstoffentabel registratiejaar 1996 CONVERSION OF BQ INTO KG AND OF KG INTO BQ The relation between radiation and mass m is given by and that between mass m and radiation by where is the radiation in Bq, while m is the mass in kg, is the half life in s, M is the molecular mass in and is Avogadro’s number in . Tables with values of molecular mass M and half life for a large number of isotopes have been published in, e.g., The Handbook of Chemistry and Physics. For an explanation of the background argumentation, see text box:


Part 2b: Operational annex Normally, amounts of material are expressed in terms of mass, that is in kg. The amount of a radioactive substance, however, is sometimes expressed in radiation terms, that is, in Bq. The two can be converted into each other. Below is a description of the conversion process. The equation for radioactive decay is given by where N(t) is the number of atoms present at time t and the decay constant. This differential equation can be solved for N(t): and also gives an expression for the amount of radiation namely the number of decays dN in the time interval dt: This can be elaborated to yield The decay constant K is related to the half life T via so that The amount of radiation is thus given by It only makes sense to refer to an amount of radiation if this amount is constant over a reasonable time frame


This leads to the assumption that The amount originally present N(0) can thus be written as N, and we have: Switching to mass units m (in kg) only requires the application of the molecular mass M (in and Avogadro’s number (in Furthermore, a factor 1000 is needed to convert the molecular mass to CONVERSION OF DB INTO Sound is calculated as a linear additive expression by conversion to an energy-related quantity. For a unit process, producing an annual amount of material of M kg/yr, of which an amount of m kg is needed, the inventory entry for sound in is found by where p is the sound pressure level in dB of the unit process. The constant has an implicit dimension. For an explanation of the background argumentation, see Heijungs et al. (1992; Backgrounds, p.37).


Part 2b: Operational annex CALCULATION OF OCCUPATION AND TRANSFORMATION IN RELATION TO LAND USE A unit process which occupies a of land and keeps it in state B, with the land being in state A before the activity and in state C after the activity, leads to two inventory entries: one for occupation (o) and one for transformation (t). If the unit process produces an annual amount of material of M kg/yr, while m kg is required, the two inventory entries are: for occupation in of state B, and fortransformationin from state A to state C. The constant 1 has an implicit dimension


The constant 1 has an implicit dimension. UNITS IN RELATION TO DATA CATEGORIES kg MJ _ 3.7 Data validation To be inserted 3.8 Cut-off and data estimation AVOIDING CUT-OFF BY USING INPUT-OUTPUT MODELING TO ESTIMATE FLOWS FOR WHICH SPECIFIC DATA ARE LACKING A hybrid analysis combining a process-based foreground system with an input-output-based background system can be used to simulate full interactions between foreground and background systems (Suh & Huppes, 2000a). Alternatively, a default estimate derived by environmentally extended input-output analysis (envlOA) can be used directly for the missing flows. The text frame below drafts a stepwise procedure for working with a default US inventory estimation model based on input-outpout tables, called MIET (Missing Inventory Estimation Tool; available online through http://www.leidenuniv.nl/interfac/cml/lca2/index.html)


This spreadsheet provides default inventory estimates based on inpout-output tables, using various data sources, including the 1996 US input-output table and the 1998 US TRI data. Table 3.6.3: Overview of preferred units for collecting and reporting the data of unit processes. data category inputs and outputs of goods inputs and outputs of services (excluding transport) inputs and outputs of transport inputs and outputs of materials inputs and outputs of energy inputs and outputs of waste (for treatment) extractions of abiotic resources (including gas) extractions of biotic resources land occupation land transformation emissions of chemicals (including radioactive iostopes) emissions of waste heat casualties sound preferred unit – hr, –, etc. tonne×km, person×km, etc. kg MJ or kWh kg kg _


Part 2b: Operational annex 1. 2. 3. 4. 5. 6. Establish prices for the inputs to be estimated by environmental IOA. Deflate the prices to the base year 1996. Convert the price into US $. Select an appropriate sector from the Bureau of Economic Analysis (BEA) Classification (SIC) code description. Enter the result of 3 into the corresponding cell in MIET (either producer’s price). Include this result in the corresponding process in your LCA. or Standard Industry price or purchaser’s Each flow for which process data are lacking must be quantified in money terms, i.e., in US dollars. This can either be done directly by means of company purchasing statistics or expenditure records for the flow at stake (in $ needed for the functional unit being analysed), or indirectly by means of physical data on the flow at stake (in terms of kg, etc. needed for the functional unit being analysed) and price data per physical unit


needed for the functional unit being analysed) and price data per physical unit. Make sure that the converted money value and the unit of l/O-based inventory are compatible. That is, if the calculated price is the purchaser’s price, as is true in most cases, then it is also the purchaser’s price which should be used in the I/O account. In most cases, I/O accounts are calculated using the producer's price. The producer’s price must then be converted into the consumer’s price by adding the retail, wholesale and transportation margins provided with the supply (U) table of input-output accounts. MIET automatically converts consumer’s prices into producer’s prices. Detailed information can be found in Suh and Huppes (2000a, 2000b). The consumption of durable capital goods can be converted accordingly, using the annual depreciation of capital goods


Detailed information can be found in Suh and Huppes (2000a, 2000b). The consumption of durable capital goods can be converted accordingly, using the annual depreciation of capital goods. Note that if the flow in question is capital-intensive, goods or services lOA-based models will yield underestimated data, since the use of capital goods is not regarded as an input in input-output convention. In this case, try to collect more specific data for the flow, or add the proportion of capital goods in the flow using annual depreciation and the corresponding capital goods column in Suh & Huppes (2000b). It should also be recognised that input-output based inventory cannot provide reliable information if the flow in question refers to an aggregated sector such as 020503: Miscellaneous crops, 110900: Other construction, 570300: Other electronic components, etc. (Suh & Huppes, 2000a)


(Suh & Huppes, 2000a). With the growth of e-commerce, price information for most commodities is available by searching on the World Wide Web. Current prices should be converted to US$ values for 1996 by using an appropriate economic index. A good source of price indices is the Statistical Abstract of the United States, available online(http://www.census.gov/prod/www/statistical-abstract-us.html; section 15). If prices are obtained in Euros, Dutch guilders or any other non-US dollar rate, they have to be converted into US dollars using the following exchange rates (d.d. 2000.11.13). 1 Dfl=0.389 US $ 1 Euro=0.857 US $ Etc. Please keep these factors up-to-date, as exchange rates change over time (e.g., consult: http://www.xe.net/ucc/). SIC and BEA code descriptions can be found from the websites http://www.osha.gov/cgi-bin/sic/sicser5 and http://www.bea.doc.gov/bea/dn2/i-o.htm, respectively


SIC and BEA code descriptions can be found from the websites http://www.osha.gov/cgi-bin/sic/sicser5 and http://www.bea.doc.gov/bea/dn2/i-o.htm, respectively. The estimates made on the basis of IOA have to be evaluated carefully afterwards: After entering the results as an inventory process in the LCA, it is useful to conduct a contribution and perturbation analysis (see Section 5.4 and 5.5) to assess the significance of the flow in question for the overall results of the study. Based on these analyses, decide whether it is still important to collect specific process data for that flow or not. A rule of thumb could be that if a single flow for which data are lacking contributes more than 5% to the indicator result of the product system analysed, specific process data should be collected for that flow


Estimating process data by comparison with similar processes for which data are known Most of the options currently known (see Part 3) for "Estimating process data by comparison with similar processes for which data are known" are practical solutions applied by some practitioners, without further documentation. This implies that there is no standard working procedure for this method. Hence, if such – –


Part 2b: Operational annex an option is applied, the procedure followed for the particular case study must be documented and justified, and the uncertainties related to the approach must be discussed. However, for the capital good approach developed by Lindeijer (1998), a working procedure has been drafted, for each level of sophistication distinguished (see text box). The environmental profile of capital goods can be estimated at three levels of sophistication: Based on an average environmental profile per building volume, and the ground surface and height of the facility (or the total building volume) and the annual production of the company. Based on the environmental profiles for different construction parts, the ground surface, the height, the annual production and the pavement surface of the facility


Based on the environmental profiles for different construction parts, the ground surface, the height, the annual production and the pavement surface of the facility. Based on the environmental profiles for different construction parts, and: the total quantity of flooring surface the total quantity of building surface the total building volume the estimated mass of machines and equipment (kg); the quality (brick, concrete, asphalt) and the total quantity of surface pavement the expected lifetime of the building; the annual energy use, if possible; and the annual production of the company. See Lindeijer (1998) for a detailed description of this procedure. The goal of Lindeijer’s study was to provide environmental profiles of the most important parts of capital goods for an average production facility. The study was aimed at buildings and did not include machinery


The study was aimed at buildings and did not include machinery. These environmental profiles allowed a first estimate of the importance of the environmental effects of capital goods to be made, with the aid of only a very limited amount of data such as surface area, height, annual production, lifetime. The result of the study was a relatively simple, three-level method providing a rough indication of the environmental effects of capital goods. In the first-level method, the environmental effects are calculated on the basis of the volume of the building (V), the annual production (P) and the environmental effect per (E). CUT-OFF BASED ON PREDEFINED CRITERIA If the estimation methods discussed above are not applicable, for instance in the use phase and the waste management phase, or if the input data for the estimation methods cannot be obtained, the inputs or outputs for which further data are lacking will have to be cut off after all


However, before the cut-off is actually made, it is recommended to assess the possible significance of the flow cut-off quantitatively and qualitatively. With respect to quantitative assessment, the following options are available if all process flows are known in either mass or monetary terms, but specific data on preceding processes are lacking for some flows: If a flow contributes less than X % (mass/mass) to the total mass inflow of a specific process – or in ISO 14041/14049 terms, if all materials have been included that have a cumulative total of more than 100-X % of the total mass inputs of that process - the flow may be removed from further analysis (see example in ISO 14049; to be included here later). If an input contributes less than X % to the total purchase costs of a specific process - or if all materials have been included that represent the cumulative total of more than 100-X % of the total purchase costs of that process - the flow may be removed from further analysis


Both options may have their own problems. The first option has the problem that it is often impossible to determine what is 100%, since not all flows are known in mass terms. The second option does not have this problem, as the total purchase costs are generally known based on business administration1. However, this method has not yet been elaborated and applied in practice and possible drawbacks are as yet unknown. Before this method can be recommended, therefore, it should be investigated in more detail and the definition of purchase costs (e.g., whether it should include pure costs of labour or not) should be established in scientific debate. 1 One could even consider using the average environmental burdens per unit of costs of the flows for which process data are known as an indicator of the flows for which such data are lacking. This would make the method an estimation method as well. – –


Part 2b: Operational annex Both quantitative assessment options discussed above should be combined with a qualitative assessment of the resource extractions and emissions that may be expected from the flow for which data are lacking (see also ISO 14041). This assessment can again be made by looking at similar flows (see above under the heading “Estimating process data by comparison with similar processes for which data are known”) and discussing the likelihood of, e.g., hazardous emissions occurring somewhere in the lifecycle of that flow. Finally, the outcomes of the quantitative and the qualitative assessment must be combined, and the choice of whether the use of cut-offs is reasonable or whether specific process data should be gathered after all must be justified and reported


If both options to assess the quantitative and/or qualitative significance of flows for which process data are lacking fail to work, there is no sensible advice left and an arbitrary choice will have to be made on whether to use cut-offs or not. If a cut-off is made, this has to be reported clearly and it has to be justified that all other options to prevent a cut-off failed to work. EXAMPLE In the example system (see Part 2a), several inputs have been cut off. The cut-offs being made include all production buildings, facilities and machines, and it is assumed that a chemical catalyst input in the refinery process has also been cut off, since specific process data for that catalyst are lacking. As an example we now estimate the potential contribution of the refinery facility and a catalyst, e.g., platinum


As an example we now estimate the potential contribution of the refinery facility and a catalyst, e.g., platinum. At least the following data for the facility are needed to estimate the facility impacts by IO analysis: – the original investment in terms of total facility (or specified per material needed for the facility, e.g., concrete, steel, aluminium etc.; a more precise IOA is possible but finding these data will take a lot of time !), corrected if necessary by a correction factor (C) based on the price index rate between 199? and the base year 1996; – the expected economic lifetime of the facility (after how many years is the facility expected to be actually substituted?); – annual average maintenance costs of the facility corrected if necessary by a correction factor (C) based on the price index rate between 199? and the base year 1996; and – the annual production of the facility (in terms of the flow analysed, i.e., naphtha)


As the facility is a multi-function facility, the allocation factor for the flow analysed in the example system, i.e., naphtha (allocation factor A = 0.31; see Section 3.9.1), needs to be known too, but this is produced by the allocation for the impacts of the process itself anyway. So, only the bulleted data above are additional to what was already known. The original investment and maintenance costs in monetary terms to be allocated to the 10 kg of naphtha output in the example system can be calculated by: In this example, the following hypothetical values have been assumed for the refinery facility: Original investment: Euro 2,400,000 (1996) Write-off period: 20 years; Average annual maintenance cost: Euro 120 per year (at 2000 price level); Annual production: 9 kton of naphtha per year


10 kg of naphtha is necessary for the production of 1000 PE disposable bags (= the functional unit) The maintenance costs (1997 price index) need to be corrected for the base year 1996 by applying a factor of 0.907986 (based on the consumer price index (CPI) for August 2000 and the 1996 annual CPI), but the original investment costs do not need to be corrected for the 1996 base year. This implies that the 1 As the allocation factor depends on the allocation method applied, a sensitivity analysis could be conducted on other possible allocation factors for naphta. However, this sensitivity analysis is only useful if the allocation factors differ significantly between the different allocation methods, and if the estimated contribution of the facility appears to be potentially significant for the overall results. – – – – –


– – – Part 2b: Operational annex original investment and maintenance costs of the refinery facility that should be allocated to the naphtha flow amount to: {(2,400,000/20) * 0.3 * (10/9,000,000)}=Euro 0.040 (US$ 0.047); and {(120 * 0.907986) * 0.3 * 10/9,000,000}=Euro 3.6319E–05 (US$ 4.238E–05). For the catalyst, the quantity of the input in the refinery process needs to be known in mass terms or in monetary terms. In this example, the following (hypothetical) values have been assumed for platinum: Annual input of platinum catalyst into the refinery: 10 kg/year. Current platinum price: about $140,000 per kg. Annual production: 6 kg of naphtha per year. The platinum price (1999 price index) needs to be corrected for the base year 1996 by applying a factor of 0.964120 (based on the 1999 and 1996 annual CPI). This implies that the platinum that should be allocated to the naphtha flow amounts to: {14000 * 10 * 0.964120 * 0.3 * (10/9,000,000)}= US $ 0.045


This implies that the platinum that should be allocated to the naphtha flow amounts to: {14000 * 10 * 0.964120 * 0.3 * (10/9,000,000)}= US $ 0.045. These monetary values can now be entered into the MIET spreadsheet. Users must specify whether producer’s prices or consumer’s prices are used. If the price data have been gathered from purchasing records, then the prices will be consumer’s prices. Before entering the value, the sectors to which each missing flow belongs must be determined. For the refinery installation, this turns out to be the “SIC 3559 Special Industry Machinery, Not Elsewhere Classified”, while platinum belongs to “2819 Industrial Inorganic Chemicals, Not Elsewhere Classified”. After the calculated value has been entered, MIET calculates inventory estimates based on the 1996 US input-output table and environmental data including TRI 98 data. The results of the calculation are shown in Part 2a


The results of the calculation are shown in Part 2a. 3.9 Multifunctionality and allocation 3.9.1 Economic allocation ECONOMIC VALUE SHARES OF THE DIFFERENT CO-PRODUCTS AS ALLOCATION FACTORS For each multiple process, the economic values produced are to be expressed in one monetary unit, like Euros or Dollars, as the proceeds of each type of product sold, As ultimately only shares in proceeds are used, not the absolute values, the monetary units may be local ones, avoiding the transformation steps into one common monetary unit for all processes. Hence, the base year for the currency used is not very relevant either. For economic allocation, only a transformation into one common monetary unit is necessary, while different units may be used in different processes. The share of the sales of one product in the total proceeds of the sales of all products is the allocation factor (see Figure 3.9.1 below)


The share of the sales of one product in the total proceeds of the sales of all products is the allocation factor (see Figure 3.9.1 below). This factor is dimensionless and does not depend on the monetary units used; it is also independent of inflation. The allocation factor applies to all non-function inputs and outputs represented by flow V. These include resource extractions, emissions, inflows of products and outflows of waste with negative value. Thus, if a certain amount of flow V enters or leaves the multifunctional (combined/joint) process, we allocate to product 1 and to product 2. In cases where economic value shares are not known because of missing or distorted markets, the methods specified in Section 3.9.2 may be applied.


Part 2b: Operational annex With all allocation factors established, each multiple process in the product system can be split up into single-function processes. Since allocation factors have been set up as product shares in total (adjusted) proceeds, the 100% rule holds at the process level. The system as a whole, as quantified with these made-single processes, will therefore be a single function system as well. The allocation method applies not only to the situation of co-production but also to situations of recycling and combined waste management, that is, to all situations where the value creation in a process involves more than one good or service. For instance, processing chlorinated solvent wastes from the plating industry is a waste management service to the plating industry and at the same time part of PVC production and metals production


For instance, processing chlorinated solvent wastes from the plating industry is a waste management service to the plating industry and at the same time part of PVC production and metals production. The process can then be allocated on the basis of the prices the plating industry pays for spent solvent processing, the price the PVC producers pay for the chlorine, and the price that metal producers pay for the metals regenerated. Allocation occurs in the unit process in which the chlorine and metals are stripped from the organic compounds. Simplification In many instances, proceeds are known at the level of the entire firm, rather than for the multi-functional process within the firm. There is a method available to derive the values at this multi-functional process level, viz., the gross sales value method (see below)