Search

Purpose: The mining industry plays a critical role in the global economy by providing raw materials and metals for various sectors, but it is also associated with environmental and social impacts. This paper presents a comparison of the findings from social life cycle assessment (S-LCA) with those obtained from a stakeholders' risk perception analysis. The goal is to provide a multifaceted view on the challenges faced by the mining industry in achieving sustainable practices. Methods: This research reports the results of S-LCA and stakeholders' risk perception analysis used to evaluate the social dimension of sustainability in two different European Horizon 2020 projects: (i) recovery of secondary metals and minerals from mining residues through bioleaching and chemical precipitation (project NEMO with a demonstration site in Finland), and (ii) recycling of wastewater and valorization of tailings from mining activities to create geopolymers through chemical activation (project ITERAMS with a demonstration site in Portugal). Results: The S-LCA conducted in NEMO reveals that fair salary is the social category presenting the highest risk (22% of the total). This risk is unequally shared between foreground activities (4%) and background activities (18%), and it occurs mostly in Finland. The S-LCA in ITERAMS shows that the low percentage of employees organized in trade unions accounts for the highest social risk (14%), occurring mostly with the background activities (8.5% out of the 14%). The risk perception analysis conducted among involved stakeholders for both projects highlighted that the analysis performed using only S-LCA databases overestimated some social issues (e.g., access to biomass, trade unionism) that were not relevant for local stakeholders while underestimating, or even ignoring, other social issues that are considered important by the same stakeholders (e.g., health and safety, housing prices). Conclusions: The two case studies show the critical need to integrate locally gathered data from stakeholders directly involved in the projects with the broader insights offered by sector-level S-LCA. Local analysis can capture site-specific dynamics and social risk perceptions, while S-LCA can extend the analysis to the entire supply chain. Both analyses highlighted that one of the main limitations of the current S-LCA framework is the omission of the positive environmental, social and economic effects resulting from the proposed projects. Ultimately, these case studies provided valuable insights for the stakeholders involved in both projects, facilitating information sharing concerning the primary social risks associated with the development and implementation of the technologies proposed by the projects. This empowers decision-makers with the information required to formulate strategies that can enhance the sustainability of the bioleaching and geopolymer technologies used to valorize mining residues. [ABSTRACT FROM AUTHOR]

Purpose: A review of LCA process datasets is an important element of quality assurance for databases and for other systems to provide LCA datasets. Somewhat surprisingly, a broadly accepted and applicable set of criteria for a review of LCA process datasets was lacking so far. Different LCA databases and frameworks are proposing and using different criteria for reviewing datasets. To close this gap, a set of criteria for reviewing LCA dataset has been developed within the Life Cycle Initiative. Methods: Previous contributions to LCA dataset review have been analysed for a start, from ISO and various LCA databases. To avoid somewhat arbitrary review criteria, four basic rules are proposed which are to be fulfilled by any dataset. Further, concepts for assessing representativeness and relevance are introduced into the criteria set from established practices in statistics and materiality. To better structure the criteria and to ease their application, they are grouped into clusters. A first version of the developed review criteria was presented in two workshops with database providers and users on different levels of experience, and draft versions of the criteria were shared within the initiative. The current version of the criteria reflects feedback received from various stakeholders and has been applied and tested in a review for newly developed datasets in Brazil, Malaysia and Thailand. Results and discussion: Overall, 14 criteria are proposed, which are organised in clusters. The clusters are goal, model, value, relevance and procedure. For several criteria, a more science-based definition and evaluation is proposed in comparison to 'traditional' LCA. While most of the criteria depend on the goal and scope of dataset development, a core set of criteria are seen as essential and independent from specific LCA modelling. For all the criteria, value scales are developed, typically using an ordinal scale, following the pedigree approach. Conclusions: Review criteria for LCI datasets are now defined based on a stringent approach. They aim to be globally acceptable, considering also database interoperability and database management aspects, as well as feedback received from various stakeholders, and thus close an important gap in LCA dataset quality assurance. The criteria take many elements of already existing criteria but are the first to fully reflect the implications of the ISO data quality definition, and add new concepts for representativeness and relevance with the idea to better reflect scientific practice outside of the LCA domain. A first application in a review showed to be feasible, with a level of effort similar to applying other review criteria. Aspects not addressed yet are the review procedure and the mutual recognition of dataset reviews, and their application for a very high number of datasets. [ABSTRACT FROM AUTHOR]

Purpose: Access, affordability and sustainability of raw material supply chains are crucial to the sustainable development of the European Union (EU) for both society and economy. The study investigates whether and how the social life cycle assessment (S-LCA) methodology can support responsible sourcing of raw materials in Europe. The potential of social indicators already available in an S-LCA database is tested for the development of new metrics to monitor social risks in raw material industries at EU policy level. Methods: The Product Social Impact Life Cycle Assessment (PSILCA) database was identified as a data and indicators source to assess social risks in raw material industries in EU-28 and extra-EU countries. Six raw material country sectors in the scope of the European policy on raw materials were identified and aggregated among those available in PSILCA. The selection of indicators for the assessment was based on the RACER (Relevance, Acceptance, Credibility, Ease, Robustness) analysis, leading to the proposal of 9 social impact categories. An S-LCA of the selected raw material industries was, thus, performed for the EU-28 region, followed by a contribution analysis to detect direct and indirect impacts and investigate related supply chains. Finally, the social performance of raw material sectors in EU-28 was compared with that of six extra-EU countries. Results and discussion: Considering the overall social risks in raw material industries, "Corruption", "Fair salary", "Health and safety" and "Freedom of association and collective bargaining" emerged as the most significant categories both in EU and extra-EU. EU-28 shows an above-average performance where the only exception is represented by the mining and quarrying sector. An investigation of the most contributing processes to social impact categories for EU-28 led to the identification of important risks originating in the supply chain and in extra-EU areas. Therefore, the S-LCA methodology confirmed the potential of a life cycle perspective to detect burdens shifting and trade-offs. However, only a limited view on the sectoral social performance could be obtained from the research due to a lack of social data. Conclusions: The S-LCA methodology and indicators appear appropriate to perform an initial social sustainability screening, thus enabling the identification of hotspots in raw material supply chains and the prioritization of areas of action in EU policies. Further methodological developments in the S-LCA field are necessary to make the approach proposed in the paper fully adequate to support EU policies on raw materials. [ABSTRACT FROM AUTHOR]

The decentralized wastewater treatment systems including collection, treatment, and recycling of treated wastewater are an efficient integrated water management solution to overcome the shortage of freshwater and to reduce pollutant emissions. In this study, life cycle assessment was performed in order to evaluate a decentralized alternative allowing the recycling of treated greywater (TGW) in a multi-family dwelling. The adopted treatment system is the moving bed biofilm reactor (MBBR). The biological treatment with MBBRs was found the main contributor to the majority of the investigated impact categories. The integration of the tertiary treatment led to an increase in the environmental load ranging between 6 and 30.4% depending on the impact category in comparison with the scenario integrating only the biological treatment. However, the final environmental profile of both scenarios presented a minor difference. Moreover, the recycling of the TGW allowed a reduction ranging between 3.9 and 17% on five impact categories compared to the no recycling scenario. It is concluded that the decentralized approach for greywater treatment and recycling is beneficial for the environment as the distribution system and the tertiary treatment didn't increase drastically the environmental load of the plant allowing water saving. Moreover, it is recommended to use renewable energy to reduce the environmental impact associated with the energy requirement for the biological treatment which affects the global warming potential and the acidification impact categories and to substitute the polyvinylchloride pipes with polyethylene pipes to reduce emissions related to the human toxicity impact category. [ABSTRACT FROM AUTHOR]

Purpose: In response to a need for interoperable LCA databases of adequate quality, a review of 40 datasets from emerging economies has been conducted with UNEP support by independent LCA experts, with the purpose to encourage improvements, either prior to publication or as part of a continuous improvement cycle. We discuss the lessons learned during this reviewing process. Methods: The review effort had to be delivered in a set and limited timeline of 9 months and covered 20 datasets from Malaysia, ten from Brazil, and ten from Thailand. The developed review process consisted in, among others, (i) developing a set of review criteria for this specific effort, (ii) pairing a local sector reviewer with an international LCA expert to enhance capacity development, (iii) establishing a legal relationship via a non-disclosure agreement (NDA) between the data provider and the data reviewers, and (iv) providing a review report for each dataset that assesses the presence and magnitude of gaps or deficiencies relative to the criteria, as well as their implications for qualifying usage. Results and discussion: The reviews provided solid recommendations for improvement to the majority of the datasets submitted by the three countries. This review exercise has been conducted in the given timeframe for the majority of the datasets. Many challenges have been faced along the way; among them agreeing on an NDA, the need for sufficient information, and the question of the confidentiality of the data. The developed set of criteria for this exercise have not been presented or discussed outside of the narrow review exercise and therefore can be seen as a starting point for further debates and improvements that should involve the broad LCA community. Conclusions: This hands-on exercise provided some valuable insights into the road towards global consensus and guidance on data review. Beyond this time-constrained effort, a broader discussion and consensus at international level on the review of datasets and a continuous effort in reviewing datasets is desirable. Four key aspects were identified as necessary to consider: review criteria, review process, reviewers' selection criteria, and development of a legal basis which protects the confidentiality of the data, as well as the position of the reviewers. This last aspect is sensitive as, in LCA datasets reviews, companies and/or countries might disclose some information with high stakes regarding competition and trade. [ABSTRACT FROM AUTHOR]

Purpose: Environmental life-cycle assessment (LCA) is broadly applied and recently social and economic LCA have emerged. However, the development of a general framework for social LCA is still at an early stage of development. The aims of this paper are to systematically discuss general considerations regarding social LCA, to build a consistent and operationalized framework for a number of indicators and to test the framework through application on a case study. Methods: The first step was to define the scope of the framework starting from a comprehensive review of concepts of social sustainability and social well-being, focusing on the conditions potentially affected by large-scale introduction of novel technologies. Secondly, main areas of concern for social well-being were defined. This resulted in the identification of four main areas of concern. The third step was to make an inventory of potential social indicators and select a number of indicators that could make the framework operational. Additionally, factors for weighting and normalization were developed. Results and discussion: The framework developed in this paper is based on four categories and 11 indicators and follows a life-cycle perspective. Six of the indicators are quantitative and are assessed using an input-output model linked to databases from the International Labour Organization. The remaining five indicators are qualitative indicators which are mapped using expert elicitation and a literature review. Identified concerns regarding the qualitative indicators are 'flagged' and provided alongside the results of the quantitative assessment, which are aggregated into one single score by means of a weighted and normalized arithmetical mean. The paper illustrates the application of the methodology in a case study examining the deployment of carbon capture and storage technologies in Europe. Conclusions: The paper presents a framework that can be used to explore potential impacts on social well-being resulting from the large-scale implementation of novel technologies. The selection of a limited number of indicators (11) keeps the methodology simple and transparent. Although the framework provides a useful approach in allowing both quantitative or qualitative identification of potential areas of concern, the results remain highly explorative in nature. The inherent value-laden and context specific nature of social aspects remains one of the key challenges for developing a general applicable framework. [ABSTRACT FROM AUTHOR]

Purpose: Ecoinvent applies a method for estimation of default standard deviations for flow data from characteristics of these flows and the respective processes that are turned into uncertainty factors in a pedigree matrix, starting from qualitative assessments. The uncertainty factors are aggregated to the standard deviation. This approach allows calculating uncertainties for all flows in the ecoinvent database. In ecoinvent 2 the uncertainty factors were provided based on expert judgment, without (documented) empirical foundation. This paper presents (1) a procedure to obtain an empirical foundation for the uncertainty factors that are used in the pedigree approach and (2) a proposal for new uncertainty factors, received by applying the developed procedure. Both the factors and the procedure are a result of a first phase of an ecoinvent project to refine the pedigree matrix approach. A separate paper in the same edition, also the result of the aforementioned project, deals with extending the developed approach to other probability distributions than lognormal (Muller et al.). Methods: Uncertainty is defined here simply as geometric standard deviation (GSD) of intermediate and elementary exchanges at the unit process level. This fits to the lognormal probability distribution that is assumed as default in ecoinvent 2, and helps to overcome scaling effects in the analysed data. In order to provide the required empirical basis, a broad portfolio of data sources is analysed; it is especially important to consider sources outside of the ecoinvent database to avoid circular reasoning. The ecoinvent pedigree matrix from version 2 is taken as a starting point, skipping the indicator 'sample size' since it will not be used in ecoinvent 3. This leads to a pedigree matrix with five data quality indicators, each having five score values. The analysis is conducted as follows: for each matrix indicator and for each data source, indicator scores are set in relation to data sets, building groups of data sets that represent the different data quality indicator scores in the pedigree matrix. The uncertainty in each of the groups is calculated. The uncertainty obtained for the group with the ideal indicator score is set as a reference, and uncertainties for the other groups are set in relation to this reference uncertainty. The obtained ratio will be different from 1, it represents the unexplained uncertainty, additional uncertainty due to a lower data quality, and can be directly used as uncertainty factor candidates. Results and discussion: The developed approach was able to derive empirically based uncertainty factor candidates for the pedigree matrix in ecoinvent. Uncertainty factors were obtained for all data quality indicators and for almost all indicator scores in the matrix. The factors are the result of the first analysis of several data sources, further analyses and discussions should be used to strengthen their empirical basis. As a consequence, the provided uncertainty factors can change in future. Finally, a few of the qualitative score descriptions in the pedigree matrix left room for interpretation, making their application not ambiguous. Conclusions and perspectives: An empirical foundation for the uncertainty factors in the pedigree matrix overcomes one main argument against their use, which in turn strengthens the whole pedigree approach for quantitative uncertainty assessment in ecoinvent. This paper provides an approach to obtain an empirical basis for the uncertainty factors, and it provides also empirically based uncertainty factors, for indicator scores in the pedigree matrix. Basic uncertainty factors are not provided, it is recommended to use the factors from ecoinvent 2 for the time being. In the developed procedure, using GSD as the uncertainty measure is essential to overcome scaling effects; it should therefore also be used if the analysed data do not follow a lognormal distribution. As a consequence, uncertainty factors obtained as GSD ratios need to be translated to range estimators relevant for these other distributions. Formulas for this step are provided in a separate paper (Muller et al.). The work presented in this paper could be the starting point for a much broader study to provide a better basis for input uncertainty in LCA, not only in ecoinvent. [ABSTRACT FROM AUTHOR]

Purpose: Data used in life cycle inventories are uncertain (Ciroth et al. Int J Life Cycle Assess 9(4):216-226, 2004). The ecoinvent LCI database considers uncertainty on exchange values. The default approach applied to quantify uncertainty in ecoinvent is a semi-quantitative approach based on the use of a pedigree matrix; it considers two types of uncertainties: the basic uncertainty (the epistemic error) and the additional uncertainty (the uncertainty due to using imperfect data). This approach as implemented in ecoinvent v2 has several weaknesses or limitations, one being that uncertainty is always considered as following a lognormal distribution. The aim of this paper is to show how ecoinvent v3 will apply this approach to all types of distributions allowed by the ecoSpold v2 data format. Methods: A new methodology was developed to apply the semi-quantitative approach to distributions other than the lognormal. This methodology and the consequent formulas were based on (1) how the basic and the additional uncertainties are combined for the lognormal distribution and on (2) the links between the lognormal and the normal distributions. These two points are summarized in four principles. In order to test the robustness of the proposed approach, the resulting parameters for all probability density functions (PDFs) are tested with those obtained through a Monte Carlo simulation. This comparison will validate the proposed approach. Results and discussion: In order to combine the basic and the additional uncertainties for the considered distributions, the coefficient of variation (CV) is used as a relative measure of dispersion. Formulas to express the definition parameters for each distribution modeling a flow with its total uncertainty are given. The obtained results are illustrated with default values; they agree with the results obtained through the Monte Carlo simulation. Some limitations of the proposed approach are cited. Conclusions: Providing formulas to apply the semi-quantitative pedigree approach to distributions other than the lognormal will allow the life cycle assessment (LCA) practitioner to select the appropriate distribution to model a datum with its total uncertainty. These data variability definition technique can be applied on all flow exchanges and also on parameters which play an important role in ecoinvent v3. [ABSTRACT FROM AUTHOR]

Purpose: In May 2009, the Guidelines for Social Life Cycle Assessment of Products (the Guidelines) were launched at the occasion of the International Organization for Standardization (ISO) 26000 (Social Responsibility) meeting in Quebec City, Canada. Developed by a United Nations Environment Programme/Society of Environmental Toxicology and Chemistry ('UNEP/SETAC') Life Cycle Initiative project group on Social Life Cycle Assessment (S-LCA), the Guidelines provide a framework to assess social impacts across product life cycles. A year later, the Methodological Sheets for the Subcategories of Social LCA ('the Methodological Sheets') are being made available to support practitioners engaging in the field. The Methodological Sheets provide practical guidance for conducting S-LCA case studies by offering consistent, yet flexible assistance. Aim and scope: A Methodological Sheet was developed for each of the 31 subcategories of assessment outlined in the Guidelines. Each sheet includes a subcategory definition tailored to S-LCA, an explanation of how the subcategory relates to sustainable development, information on data assessment, including examples of inventory indicators, units of measurement, and data sources, along with a reference section that points the user to further information. The data assessment section is intended to provide adaptable guidance to LCA practitioners by offering examples and does not prescribe comprehensive procedures. The Methodological Sheets do not provide guidance on aggregating subcategory indicators or characterization models, nor do they discuss interpretation of results. The sheets are focused on the inventory analysis phase of S-LCA. This article will detail the development process of this unique resource, its content and future development, and how it compares to other types of documents, such as the GRI G3, ISO 26000 guidelines on Social Responsibility and the Global Social Compliance reference code. Conclusions: The Methodological Sheets support the framework of S-LCA offered in the UNEP/SETAC Guidelines. They provide consistent guidance to assist LCA practitioners in case studies. At the same time, they have been designed to encourage context-specific application. Content of the Methodological Sheets will continue to evolve. Over time, and when relevant, characterization and interpretation models will be added to the Methodological Sheets. The Methodological Sheets are currently under public review and available on the Life Cycle Initiative website. A finalized version will be available in 2011, integrating comments from the review process. [ABSTRACT FROM AUTHOR]

Purpose: There is a need to assess social impacts of products along the full life cycle, not only to be able to address the 'social dimension' in sustainability, but also for potentially improving the circumstances of affected stakeholders. This paper presents a case study for a social life cycle assessment (S-LCA) based on the recently published 'Guidelines for Social Life Cycle Assessment of Products' developed by the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) working group. General aim is to 'try out' the proposed method. The case study itself compares the impacts of rose production in Ecuador with the Netherlands. Furthermore, the objective is to identify differences and similarities in environmental and social life cycle modelling and both social and environmental hot spots in each of the life cycles. Methods: The study considers the production of rose blossoms and the cutting and packaging process in two fictitious companies in Ecuador and the Netherlands. Both rose bouquets are delivered to the European market and auctioned in Aalsmeer, the Netherlands. The social assessment is based on the UNEP/SETAC guidelines for S-LCA. Data are mainly obtained from governmental and non-governmental organisations. For the calculation of the environmental burden, a screening-type LCA is conducted, including midpoint impact assessment. Results and discussion: This paper asserts that rose production in Ecuador is associated with many negative social effects, e.g. child labour, unfair salary, or bad impairment to health. The rose production in the Netherlands has no obvious negative social impacts but rather ecological consequences. Responsible for this is the high-energy consumption of the greenhouses. Conclusions: Application of the UNEP/SETAC guidelines in case studies can be encouraged based on results of this case study. The consideration of different stakeholder groups with corresponding, very diverse themes allows a comprehensive analysis of the actual conditions. However, finding suitable indicators to measure the status of the subcategories may be challenging. Moreover, the case study shows that results can be completely different for the environmental and for the social dimension, so that it often will be needed to perform both assessments if a complete picture is required. Recommendations and perspectives: It will be interesting to apply the UNEP/SETAC approach of S-LCA to other products; products with a more complex life cycle will be a special challenge. As with any new method, getting experience on data collection and evaluation, building a data stock, integrating the method in software, and finding ways for effective communication of results are important steps until integrating S-LCA in routine, recognized decision support. [ABSTRACT FROM AUTHOR]

Purpose: The paper presents a discussion on the possibilities of using LCA in identification and assessment of environmental aspects in environmental management systems based on the requirements of the international ISO14001 standard and the European Union EMAS regulation. Some modifications of LCA methodology are proposed in Part 1 while the results of a review of environmental aspects for 36 organisations with implemented EMS are presented in Part 2 of the article. Materials and methods: The scope of the systems analysed in EMS and in LCA is different. This comes as the result of the fact that both ISO 14001 and EMAS are focused on an organisation on contrary to ISO14040x which are focused on a product life cycle. For the present work, this resulted in a need of adjusting the LCA methodology to EMS specificity and vice versa. Some suggestions of such modifications are presented and discussed in the paper. Results: A preliminary analysis was carried out on 36 organisations which have environmental management systems compliant with the ISO14001 or EMAS regulations. A certain disproportion between input and output related environmental aspects included in most of the analysed registers was found. The probable reasons for such disproportion could be the fact that the output related environmental aspects are easier to manage by organisation and are often regulated by laws. Legal requirements are a significant criterion in the environmental aspects assessment. Discussion: Based on the assessments carried out and the observations made, some conclusions have been drawn with regard to weaknesses and strengths and usefulness of LCA, as a result of a comparison to the traditional approaches used in EMS in the discussed area. LCA has evident advantages like: standardised methodology, possibility of inclusion of the quantitative information, presence of some methodological steps enabling the verification of the collected data, and ability to generate of reproducible results. At the same time, the following potential weak points can be observed: a complexity of the procedure, higher time, and cost requirements (especially related to an inventory phase); difficulties with assessing of environmental aspects with the qualitative character and these related to emergency situations; and limitation related to the lack of relevant characterisation factors in the currently used life cycle impact assessment methods. Conclusions: LCA ought to be considered as a tool used for identification and assessment of environmental aspects in environmental management systems. The listed limitations do not disqualify its suitability to be used. After certain simplifications, LCA seems to be a valuable alternative to the methodologies currently in use. [ABSTRACT FROM AUTHOR]

Purpose Authors of different sustainability journals, including authors of articles in past issues of the International Journal of Life Cycle Assessment have acknowledged the rising interest and the pressing need for a social and socioeconomic life cycle assessment methodology and identified challenges in its development and implementation. Social life cycle assessment (LCA) allows identification of key issues, assessing, and telling the story of social conditions in the production, use, and disposal of products. In this article, the United Nations Environment Programme/The Society of Environmental Toxicology and Chemistry Guidelines for Social Life Cycle Assessment of Products will be presented. Aim and scope The guidelines demystifies the assessment of product life cycle social impacts and presents an effective framework representing the consensus of an international group of experts leading research in this field. The guidelines complement those for environmental life cycle assessment and life cycle costing, and by doing so contribute to the full assessment of goods and services within the context of sustainable development. They enable a larger group of stakeholders to engage. Key aspects of the framework and the research needs identified in the guidelines will be summarized. Conclusions In a globalized world where transparency and information occupies a predominant place and where consumers and companies reach out to shed light on both the brightest and the darkest side of the economy and, when applicable, transform its condition, social LCA brings strong value. At a moment where major companies and initiatives are going forward with using LCA and are trying to track and communicate about the social impacts of their products they are increasingly held accountable for the guidelines for social life cycle assessment arrive just in time to inform their efforts. [ABSTRACT FROM AUTHOR]

Background, Aim and Scope. Quite often there is need for precise and representative parameters in LCA studies. Probably the most relevant have direct influence on the functional unit, whose definition is crucial in the conduct of any LCA. Changes in the functional Unit show directly in LCI and LCIA results. In comparative assertions, a bias in the functional unit may lead to a bias in the overall conclusions. Since quantitative data for the functional unit, such as geometric dimensions and specific weight, often vary, the question arises how to determine the functional unit, especially if a comparative assertion shall be representative for a region or market. Aim and scope of the study is to develop and apply methods for obtaining precise and representative estimates for the functional unit as one important parameter in an LCA study. Materials and Methods. Statistical sampling is applied in order to get empirical estimates for the weight of yoghurt cups, as a typical parameter for the functional unit. We used a two-stage sampling design, with stratified sampling in the first stage and three different sampling designs in the second stage, namely stratified, clustered, and a posteriori sampling. Sampling designs are motivated and de- scribed. In a case study, they are each used to determine a representative weight for 150 g yoghurt cups in Berlin, at the point of sale and within a specific time. In the first sampling stage, food markets are randomly selected, while in the second stage, yoghurt cups in these food markets are sampled. The sampling methods are applicable due to newly available internet data. These data sources and their shortcomings are described. Results. The random sampling procedure yields representative estimates, which are compared to figures for market leaders, i.e. yoghurt cups with very high occurrence in the supermarkets. While single types of yoghurt cups showed moderate uncertainty, representative estimates were highly precise. Discussion results show, for one, the performance of the applied statistical estimation procedures, and they show further that adding more information in the estimation procedure (on the shape of the cup, on the type of plastic, on the specific brand) helps reducing uncertainty. Conclusions. As conclusions, estimates and their uncertainty depend on the measurement procedure in a sensitive manner; any uncertainty information should be coupled with information on the measurement procedure, and it is recommended to use statistical sampling in order to reduce uncertainty for important parameters of an LCA study. Recommendations and Perspectives. Results for market leaders differed considerably from representative estimates. This implies to not use market leader data, or data with a high market share, as substitute for representative data in LCA studies. Statistical sampling has been barely used for Life Cycle Assessment. It turned out to be a feasible means for obtaining highly precise and representative estimates for the weight of yoghurt cups in the case study, based on empirical analysis. Further research is recommended in order to detect which parameters should best be investigated in LCA case studies; which data sources are available and recommended, and which sampling designs are appropriate for different application cases. [ABSTRACT FROM AUTHOR]

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

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

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

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

Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs. [ABSTRACT FROM AUTHOR]

The author reflects on the code of practice established by the Society of Environmental Toxicology and Chemistry (SETAC) for environmental life-cycle costing (LCC). He mentions that this code of practice is in line with the standards formulated by the International Organization for Standardization (ISO). An overview on the use of LCC and life-cycle assessment (LCA) in initiating product sustainability assessment is offered. The author suggests that manufacturers must examine their products.

In a recent letter to the editor, Jørgensen et al. questioned that life cycle costing (LCC) is relevant in life cycle-based sustainability assessment (LCSA). They hold the opinion that environmental and social aspects are sufficient. We argue that sustainability has three dimensions: environment, economy, and social aspects in accordance with the well-accepted 'three pillar interpretation' of sustainability, although this is not verbally stated in the Brundtland report (WCED 1987). An analysis of the historical development of the term 'sustainability' shows that the economic and social component have been present from the beginning and conclude that LCSA of product systems can be approximated by LCSA = (environmental) LCA + (environmental) LCC + S-LCA where S-LCA stands for social LCA. The 'environmental' LCC is fully compatible with life cycle assessment (LCA), the internationally standardized (ISO 14040 + 14044) method for environmental product assessment. For LCC, a SETAC 'Code of Practice' is now available and guidelines for S-LCA have been published by UNEP/SETAC. First examples for the use of these guidelines have been published. An important practical argument for using LCC from the customers' point of view is that environmentally preferable products often have higher purchasing costs, whereas the LCC may be much lower (examples: energy saving light bulbs, low energy houses, and cars). Also, since LCC allows an assessment for different actor perspectives, the producers may try to keep the total costs from their perspective below those of a conventional product: otherwise, it will not succeed at the market, unless highly subsidized. Those are practical aspects whichfinally decide about success or failure of 'sustainable' products. Whether or not an analysis using all three aspects is necessary will depend on the exact question. However, if real money flows are important in sustainability analysis of product systems, inclusion of LCC is advisable. [ABSTRACT FROM AUTHOR]

The author talks about the significance of validation in the improvement and quality of Life Cycle Assessment (LCA) model. Validation is the process of examining the behavior of the model in contrast with the real system, to assess its quality. He states that building an LCA model needs a critical examination to assure its effectiveness and quality. Accordingly, the author believes that the quality and effectiveness of the model are best achieve when validation is made.

In recent years, increased interest and actions have been taken to better understand, and mitigate, sustainability impacts of mining activities, by both industry and policy. The present work reports on a sustainability hotspots screening performed for the EU Horizon 2020 "Integrated Mineral Technologies for More Sustainable Raw Material Supply" (ITERAMS) project, which foresees a more efficient water recycling, tailings valorization, and minimization of environmental footprint. The focus of this paper is on social and environmental issues in mining. Different methodologies were explored, starting from a qualitative causal loop modelling. Afterwards, an environmental and social LCA screening was performed using well-accepted databases and methods, thus completing results with a literature research. The main findings related to the importance of the supply chain, the vulnerability of local communities, and the toxic emissions from tailings offer a starting point to reflect on the specific social, socio-economic, and environmental context which may influence these issues. A better understanding of the environmental and social pressures associated with mining is not only crucial to orient the sustainability assessment foreseen for the ITERAMS project, but also to contribute in terms of methodology to the challenges tackled by policy and research worldwide towards a more sustainable mining. [ABSTRACT FROM AUTHOR]

This paper is a two-fold introduction. For one, it introduces a new, open source, LCA software. Second, it is to establish a new section in Int J LCA named ‘LCA Software’. Herewith, the editors of the journal recognise the growing possibilities and the impact of software, meaning both databases and calculation as well as modelling software, for practical applications as well as for the scientific development in LCA. This section is designed to house a broad variety of papers to be LCA focused and related to ICT (Information and Communication Technology). In this sense, announcements (as this one), conference reports, but also peer-reviewed papers on methodology and case studies, are most welcome. [ABSTRACT FROM AUTHOR]

The author reflects on the activities during the Editors Meeting of the Scientific Journals in Porto, Portugal, May 19, 2007. General issues relevant for all journals were discussed. Topics including the roles of the Submission Editors and Referees, the referee data base and how to improve it, the quality of the review process, and the impact factor are discussed.