Establishing Life Cycle Inventories of Chemicals Based on Differing Data Availability (9 pp)

Goal, Scope and Background In contrast to inventory data of energy and transport processes, public inventory data of chemicals are rather scarce. Chemicals are important to consider in LCA, because they are used in the production of many, if not all, products. Moreover, they may cause considerable environmental impacts. For these reasons, it was one goal of the new ecoinvent database to provide LCI data on chemicals. In this paper, the methods and procedures used for establishing LCIs of chemicals in ecoinvent are presented.Methods Three different approaches are suggested for situations of differing data availability. First, in the case of good data availability, the general quality guidelines of ecoinvent can be followed. Second, a procedure is proposed for the translation of aggregated inventory data (cumulative LCI results) from industry into the ecoinvent format. This approach was used, if adequate unit process data was not available. Third, a procedure is put forward for estimating inventory data using stoichiometric equations from technical literature as a main information source. This latter method was used if no other information was available. The application of each of the three procedures is illustrated with the help of a case study.Results and Conclusion When sufficient information is available to follow the general guidelines of ecoinvent, the resulting dataset is characterized by a high degree of detail, and it is thus of high quality. For chemicals, however, the application of the standard procedure is possible in only a few cases. When using industrial data, the main drawback is the fact that those data are often available only as aggregated data, thus being out of tune with the quality guidelines of ecoinvent and its main aim, the harmonization of LCI data. As a third approach, the use of the stoichiometric reaction equation is used for the compilation of LCI datasets of chemicals. This approach represents an alternative to neglecting chemicals completely, but it contains a high risk to not consider important aspects of the life cycle of the respective substance.Outlook Further work in the area of chemicals should focus on an improvement of datasets, so far established by either of the two estimation procedures (APME method; estimation based on technical literature) described. Besides the improvement of already established inventories, the compilation of further harmonized inventories of specific types of chemicals (e.g. solvents) or of chemicals for new industrial sectors (e.g. electronics industry) are in discussion.     

Framework for modelling data uncertainty in life cycle inventories

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

What distribution function do life cycle inventories follow?

Purpose

Life cycle inventory (LCI) results are often assumed to follow a lognormal distribution, while a systematic study that identifies the distribution function that best describes LCIs has been lacking. This paper aims to find the distribution function that best describes LCIs using Ecoinvent v3.1 database using a statistical approach, called overlapping coefficient analysis.

Methods

Monte Carlo simulation is applied to characterize the distribution of aggregate LCIs. One thousand times of simulated LCI results are generated based on the unit process-level parametric uncertainty information, from each of which 1000 randomly chosen data points are extracted. The 1 million data points extracted undergo statistical analyses including Shapiro-Wilk normality test and the overlapping coefficient analysis. The overlapping coefficient is a measure used to determine the shared area between the distribution of the simulated LCI results and three possible distribution functions that can potentially be used to describe them including lognormal, gamma, and Weibull distributions.

Results and discussion

Shapiro-Wilk normality test for 1000 samples shows that average p value of log-transformed LCI results is 0.18 at 95 % confidence level, accepting the null hypothesis that LCI results are lognormally distributed. The overlapping coefficient analysis shows that lognormal distribution best describes the distribution of LCI results. The average of overlapping coefficient (OVL) for lognormal distribution is 95 %, while that for gamma and Weibull distributions are 92 and 86 %, respectively.

Conclusions

This study represents the first attempt to calculate the stochastic distributions of the aggregate LCIs covering the entire Ecoinvent 3.1 database. This study empirically shows that LCIs of Ecoinvent 3.1 database indeed follow a lognormal distribution. This finding can facilitate more efficient storage and use of uncertainty information in LCIs and can reduce the demand for computational power to run Monte Carlo simulation, which currently relies on unit process-level uncertainty data.

     

Life cycle inventory analysis of granite production from cradle to gate

Purpose

Granite is a traditional high-quality material that is widely used in construction. A key strategy that is increasingly promoted to highlight the competitiveness of materials is life cycle environmental performance. Due to the lack of comprehensive life cycle inventories (LCIs), the environmental characterisation of granite products has received little attention in scientific literature. In this paper, a complete LCI of the production chain of intermediate and finished granite products is provided and analysed.

Methods

The Spanish granite production industry, which is the second major European producer and the seventh worldwide, is examined. The reference unit is defined as 1 m² of finished granite tiles with dimensions 60?×?40?×?2 cm used for indoor and outdoor applications. Input and output data were collected through the distribution of technical data collection surveys to quarries and processing facilities and via on-site visits. During data calculation and validation, technical support was provided by technicians from the Spanish Cluster of Granite Producers. The LCI data describe the industrial activity in baseline year 2010 that corresponds to a total production volume of 48,052 m³ of quarried granite and a net of 881,406 m² of processed granite.

Results and discussion

The production of 1 m² of polished granite tiles requires 28 kWh of electricity, 23 MJ of diesel, 103 l of water, and 7 kg of ancillary materials. Sandblasted, flamed or bush-hammered finishes applied to granite tiles have a minimal effect on their total energy and material requirements but significantly affect their water consumption. Electrical energy, cooling water and steel are the major industrial requirements in which granite sawing is the most demanding process. The resource efficiency of the production chain is 0.31. Approximately 117 kg of granite are wasted per square meter of granite tiles that are produced (53 kg). Seventy-four percent of granite waste is composed of granite scrap, which becomes a marketable by-product. The predominant source of granite waste is the sawdust that is generated during stone-cutting operations.

Conclusions

LCIs provide the relevant information required to characterise the environmental performance of granite production and products. LCI data can be easily managed by users due to the disaggregation into unit processes. LCI data can be used to analyse the environmental burden associated with intermediary granite products, such as granite blocks, sawn granite slabs and finished granite slabs, and to analyse the environmental burden of finished granite tiles according to the corresponding net production volumes.

Recommendations

LCI dataset of granite production should be extended to include alternative production technologies, such as diamond multiwire machines for sawing granite, which is an increasingly competitive production technology with interesting properties for cleaner production. Strong competitive granite industries, such as the industries in China, India and Brazil, should also provide LCIs of granite products to transparently compare different product chains, identify environmental strategies on the sector level, and promote the green procurement of granite products.     

Data representativeness in LCA: A framework for the systematic assessment of data quality relative to technology characteristics

A shortcoming in current data quality assessment schemes is that the data quality information is not used systematically to identify the critical data in a life cycle inventory (LCI) model. In addition, existing criteria employed to evaluate representativeness lack relevance to the specific context of a study. A novel framework is proposed herein for the evaluation of the representativeness of LCI data, including an analysis of the importance of the data and a modification of quality criteria based on unit process characteristics. Temporal characteristics are analyzed by identifying the technology shift, because data generated before this time are considered outdated. Geographical and technological characteristics are analyzed by defining a “related area” and a “related technology,” which is done by identifying a number of relevant geographical and technical factors, and then comparing the collected data with these factors. The framework was illustrated in a case study on household waste incineration in Denmark. The results demonstrated the applicability of the method in practice, and they provided data quality criteria unique to waste incineration unit processes, for example, different time intervals to evaluate temporal representativeness. However, the proposed method is time demanding, and thus sector‐level characteristic analyses are feasible instead of the user having to do the analyses.     

The virtual ecologist approach: simulating data and observers

Ecologists carry a well‐stocked toolbox with a great variety of sampling methods, statistical analyses and modelling tools, and new methods are constantly appearing. Evaluation and optimisation of these methods is crucial to guide methodological choices. Simulating error‐free data or taking high‐quality data to qualify methods is common practice. Here, we emphasise the methodology of the ‘virtual ecologist’ (VE) approach where simulated data and observer models are used to mimic real species and how they are ‘virtually’ observed. This virtual data is then subjected to statistical analyses and modelling, and the results are evaluated against the ‘true’ simulated data. The VE approach is an intuitive and powerful evaluation framework that allows a quality assessment of sampling protocols, analyses and modelling tools. It works under controlled conditions as well as under consideration of confounding factors such as animal movement and biased observer behaviour. In this review, we promote the approach as a rigorous research tool, and demonstrate its capabilities and practical relevance. We explore past uses of VE in different ecological research fields, where it mainly has been used to test and improve sampling regimes as well as for testing and comparing models, for example species distribution models. We discuss its benefits as well as potential limitations, and provide some practical considerations for designing VE studies. Finally, research fields are identified for which the approach could be useful in the future. We conclude that VE could foster the integration of theoretical and empirical work and stimulate work that goes far beyond sampling methods, leading to new questions, theories, and better mechanistic understanding of ecological systems.     

Input‐Output‐based Life Cycle Inventory

An input‐output‐based life cycle inventory (IO‐based LCI) is grounded on economic environmental input‐output analysis (IO analysis). It is a fast and low‐budget method for generating LCI data sets, and is used to close data gaps in life cycle assessment (LCA). Due to the fact that its methodological basis differs from that of process‐based inventory, its application in LCA is a matter of controversy. We developed a German IO‐based approach to derive IO‐based LCI data sets that is based on the German IO accounts and on the German environmental accounts, which provide data for the sector‐specific direct emissions of seven airborne compounds. The method to calculate German IO‐based LCI data sets for building products is explained in detail. The appropriateness of employing IO‐based LCI for German buildings is analyzed by using process‐based LCI data from the Swiss Ecoinvent database to validate the calculated IO‐based LCI data. The extent of the deviations between process‐based LCI and IO‐based LCI varies considerably for the airborne emissions we investigated. We carried out a systematic evaluation of the possible reasons for this deviation. This analysis shows that the sector‐specific effects (aggregation of sectors) and the quality of primary data for emissions from national inventory reporting (NIR) are the main reasons for the deviations. As a rule, IO‐based LCI data sets seem to underestimate specific emissions while overestimating sector‐specific aspects.     

Provision of LCI data in the European aluminium industry Methods and examples

Background, aim, and scope

The development of robust and up-to-date generic life cycle inventory data for materials is absolutely crucial for the LCA community since many LCA studies rely on these generic data about materials. LCA databases and software usually include within their package such generic LCI datasets. However, in many cases, the quality of these data is poor while the methodology and the models used for their development are rarely accessible or transparent. This paper presents the development of robust European LCI datasets for the production of primary and recycled aluminium ingots and for the transformation of aluminium ingot into semi-finished products, i.e. sheet, foil and extrusion.

Materials and methods

The environmental data have been collected through an extensive environmental survey, organised among the European aluminium industry, focusing on the year 2005 and covering EU27 countries as well as EFTA countries (Norway, Iceland and Switzerland). From this survey, European averages, i.e. foreground data, have been calculated for the direct inputs and outputs of the various aluminium processes. Using the GaBi software, the foreground data have been combined within LCI models integrating background LCI data on energy supply systems, ancillary processes and materials. For the primary aluminium production (smelters), a specific model for the electricity production has been developed. The methodology for the data consolidation and for the development of the various models is explained as well as the main differences between the new modelling approach and LCI models used in the past. An independent expert has critically reviewed the entire LCI project including data collection, models development, calculation of LCI data and associated environmental indicators.

Results

As confirmed by the critical review, the new LCI datasets for aluminium ingot production and transformation into semi-finished products have been developed though a robust methodology in full accordance with ISO 14040 and 14044. Most significant environmental data and LCI results are reported in this paper with an emphasis on energy use and the major emissions to air. The full environmental report, including the critical review report and the calculation of environmental indicators for a pre-set of impact categories, is available on the website of the European Aluminium Association (EAA 2008). Whenever possible, the updated European averages and the new LCI data are compared with previous results developed from two past European surveys covering respectively the years 2002 and 1998. For the aluminium processes related to primary production, European averages are also benchmarked against global averages calculated from two worldwide surveys covering the years 2000 and 2005.

Discussion

While some data evolutions are directly attributed to the variation of foreground data, e.g. raw materials consumption or energy use within the aluminium processes, modifications related to the system boundaries, the background data and the modelling hypotheses can also influence significantly the LCI results. For primary aluminium production, the evolution of the foreground data is dominated by the strong decrease of PFC (perfluorocarbon) emissions (about 70% since 1998). In addition, the electricity structure calculated from the refined electricity model shows significant differences compared to previous models. In the 2005 electricity model, the hydropower share reaches 58% while coal contributes to 15% only of the electricity production. In 1998, the respective share of coal-based and hydro-electricity were respectively calculated to 25% and 52%. As a result, the electricity background LCI data are then significantly affected and influence also positively the environmental profile of primary aluminium in Europe. For the semi-production processes, the reduction of process scrap production, especially for extrusion and foil, demonstrates the increase of process efficiency from 1998. In parallel, a significant reduction of energy use is observed between 1998 and 2005. However, this positive trend is not fully reflected within LCI data due to the significant contribution of the background electricity data. The choice of the electricity model plays also a critical role for these transformation processes since electricity production contributes to about 2/3 of the consumption of the non-renewable energy and to about the same level of the air emissions. In such a case, the move from the UCPTE electricity model used in the past towards the EU25 electricity model used for the development of the updated LCI data has a detrimental effect on the environmental profile of the three LCI datasets respectively related to sheet, foil and extrusion. In addition to energy and process scrap reduction, the reduction of the VOC (volatile organic compounds) emission is also a major trend in foil production. Finally, for old aluminium scrap recycling, the new LCI data show a dramatic improvement regarding energy efficiency, reinforcing the environmental soundness of promoting and supporting aluminium recycling within the aluminium product life cycles.

Conclusions

This paper shows the development of generic LCI data about aluminium production and transformation processes which are based on robust data, methodologies and models in full accordance with ISO 14040 and 14044 standards, as confirmed by the critical review. The publishing of these LCI datasets definitely shows the commitment of the European aluminium industry to contribute in a transparent, fair and scientifically sound manner to product sustainability in a life cycle thinking perspective.

Recommendations and perspectives

Software houses and LCA practitioners are invited to update their generic European data on aluminium with the herewith datasets. Even if the quality and the completeness of these LCI data reach a high standard, some areas for data improvements have been identified, as described within the review report. Land use, water use and solid waste treatment appear as three priority areas for data refining and improvement. The land use dimension, particularly meaningful for bauxite mining, is not covered in the current LCI data while it is now integrated within many LCA studies. Up to now, the reporting of meaningful and robust data on water origins and use have not been possible due to the huge discrepancies between the surveyed sites combined with the difficulty to report coherent input and output water mass flows. The development of water data, only focussing on water-stressed areas, will most probably make more sense in the future. Finally, collecting more qualitative information about solid waste processing and treatment will help to include such operations within the system boundaries and to model their associated air, water and soil emissions.

     

Methodology for developing gate-to-gate Life cycle inventory information

Life Cycle Assessment (LCA) methodology evaluates holistically the environmental consequences of a product system or activity, by quantifying the energy and materials used, the wastes released to the environment, and assessing the environmental impacts of those energy, materials and wastes. Despite the international focus on environmental impact and LCA, the quality of the underlying life cycle inventory data is at least as, if not more, important than the more qualitative LCA process. This work presents an option to generate gate-to-gate life cycle information of chemical substances, based on a transparent methodology of chemical engineering process design (an ab initio approach). In the broader concept of a Life Cycle Inventory (LCI), the information of each gate-to-gate module can be linked accordingly in a production chain, including the extraction of raw materials, transportation, disposal, reuse, etc. to provide a full cradle to gate evaluation. The goal of this article is to explain the methodology rather than to provide a tutorial on the techniques used. This methodology aims to help the LCA practitioner to obtain a fair and transparent estimate of LCI data when the information is not readily available from industry or literature. Results of gate-to-gate life cycle information generated using the cited methodology are presented as a case study. It has been our experience that both LCI and LCA information provide valuable means of understanding the net environmental consequence of any technology. The LCI information from this methodology can be used more directly in exploring engineering and chemistry changes to improve manufacturing processes. The LCA information can be used to set broader policy and to look at more macro improvements for the environment.     

Assessment of ecological status in U.K. rivers using diatoms

1. The European Union's Water Framework Directive requires all water bodies to achieve ‘good ecological status’ by 2015 and this paper describes a rationale for defining ‘good ecological status’ based on diatoms, a significant component of the biological quality element ‘macrophyte and phytobenthos’. 2. A database of benthic diatom samples collected over the past 20 years was assembled. New sampling, specifically for this project, was undertaken during 2004 to supplement these data. In total 1051 samples were included in the database with matching environmental data. 3. ‘Reference sites’, relatively unimpacted by human activity, were selected from this database by a series of screening steps and these sites were used to develop a site‐specific reference typology. 4. Environmental variables not related to the pressure gradient were used to predict the ‘expected’ Trophic Diatom Index (TDI) values at each site. Site‐specific TDI predictions were used to generate ecological quality ratios (EQRs) ranging from ≥1, where the diatom assemblage showed no impact, to (theoretically) 0, when the diatom assemblage was indicative of major anthropogenic activities. 5. The boundary between ‘high’ and ‘good’ status was defined as the 25th percentile of EQRs of all reference sites. The boundary between ‘good’ and ‘moderate’ status was set at the point at which nutrient‐sensitive and nutrient‐tolerant taxa were present in equal relative abundance. An ecological rationale for this threshold is outlined in the paper.     

Ambiguities in decision-oriented Life Cycle Inventories The Role of mental models

If the complexity of real, socio-economic systems is acknowledged, life cycle inventory analysis (LCI) in life cycle assessment (LCA) cannot be considered as unambiguous, objective, and as an exclusively data and science based attribution of material and energy flows to a product. The paper thus suggests a set of criteria for LCI derived from different scientific disciplines, practice of product design and modelling characteristics of LCI and LCA. A product system with its respective LCI supporting the process of effective and efficient decision-making should ideally be: a) complete, operational, decomposable, non-redundant, minimal, and comparable; b) efficient, i.e., as simple, manageable, transparent, cheap, quick, but still as ‘adequate’ as possible under a functionalistic perspective which takes given economic constraints, material and market characteristics, and the goal and scope of the study into account; c) actor-based when reflecting the decision-makers’ action space, risk-level, values, and knowledge (i.e. mental model) in view of the management rules of sustainable development; d) as site- and case-specific as possible, i.e. uses as much site-specific information as possible. This rationale stresses the significance of considering both (i) material and energy flows within the technosphere with regard to the sustainable management rules; (ii) environmental consequences of the environmental interventions on ecosphere. Further, the marginal cost of collecting and computing more and better information about environmental impacts must not exceed the marginal benefits of information for the natural environment. The ratio of environmental benefits to the economic cost of the tool must be efficient compared to other investment options. As a conclusion, in comparative LCAs, the application of equal allocation procedures does not lead to LCA-results on which products made from different materials can be compared in an adequate way. Each product and material must be modelled according to its specific material and market characteristics as well as to its particular management rules for their sustainable use. A generic LCA-methodology including preferences on methodological options is not definable.     

Thai national life cycle inventory readiness for product environmental footprint

Purpose

In the near future, the products of Thai industries and companies mainly producing parts and products for export to the European Union (EU) will require the Product Environmental Footprint (PEF) to assess the environmental performance and resource efficiency of products by using a life cycle perspective. The potential generic (often used interchangeably with background data) data have to be modified and improved for mandatory use in the product-specific and country-specific PEF database.

Methods

PEF is used as a tool for assessing the environmental burden of products and services for export to the EU. It requires both specific data from primary sources and generic data to fulfill assessment requirement. Accordingly, the Thai national life cycle inventory (LCI) database plays a key role in generic data that was used to evaluate the environmental performance of products. This paper presents the perspective of Thai data readiness for PEF in which the quality of LCI is the main issue of concern. The current situation of the Thai national LCI database was reviewed. Then, the gaps of data were addressed, and the gaps were also filled. Non-representative data and untreated waste are the selected issues that were presented in this paper.

Results and discussion

Many gaps were revealed for the Thai national LCI database because this database was developed based on ISO 14040/44, which may not be compliant with the PEF guide. The issues that have been selected for improvement are non-representative data and untreated waste because these gaps can offer inaccuracy concerning the environmental burden of products potentially leading to the reliability of products for export to the EU. However, the Thai national LCI database has not achieved the data quality aspects of the PEF, continuously improving the quality of data to meet the requirements of the PEF.

Conclusions

The lessons learned from the real-world situation of data quality development based on PEF requirements were extracted. The practical procedure and recommendations were transparent for drivers and researchers who would like to start with data quality issues and prepare for the EU single market.

     

German network on life cycle inventory data

Reliability of Life Cycle Assessment (LCA) results depends on the availability and quality of Life Cycle Inventory (LCI) data. In order to provide high-quality LCI data for background systems in LCA and to make it applicable to a wider range of fields, harmonization strategies for already existing datasets and databases are required. In view of the high significance of LCI data as a basis of major fields of action within a sustainability strategy, the German Helmholtz Association (HGF), under the leadership of the Forschungszentrum Karlsruhe (FZK) has taken up this issue in its research programme. In 2002, the FZK conducted a preliminary study on ‘Quality Assurance and User-oriented Supply of a Life Cycle Inventory Data’ funded by the Federal Ministry of Education and Research (BMBF). Within the framework of this study, a long-term concept for improving the scientific fundamentals and practical use of LCI data was developed in association with external experts. The focus is on establishing a permanent German ‘Network on Life Cycle Inventory Data’ which will serve as the German information and cooperation platform for all scientific and non-scientific actors in the field of life cycle analysis. This network will integrate expertise on LCA in Germany, harmonise methodology and data, and use the comprehensive expert panel as an efficient basis for further scientific development and practical use of LCA. At the same time, this network will serve as a platform for cooperation on an international level. Current developments address methodological definitions for the initial information infrastructure. As a novel element, user needs are differentiated in parallel according to the broad application fields of LCI-data from product declaration to process design. Case studies will be used to define tailored interfaces for the database, since different data quality levels will be encountered.     

Moving towards an Egyptian national life cycle inventory database

Purpose

Life cycle inventory (LCI) data are region-specific because energy fuel mixtures and methods of production often differ from region to region. LCI database examples include US LCI, Ecoinvent v.2, and NIST, each of which is country-specific. Thus, the main aim of this study is to show that Egypt is in need of an Egyptian National LCI (ENLCI) database and to focus on the means of developing a database specific to Egypt.

Methods

Arab countries have thus far engaged in virtually no life cycle assessment (LCA) studies, and a significant neglect of this matter is in evidence for the continent of Africa and, in particular, Egypt. Thus, this study suggests an organizational and managerial framework for the development of a national LCI database and sheds light on the required LCI database categories and data quality for practical solutions reflecting who is equipped to do what in order to keep pace with the world.

Results

The results from this review are useful to standardize the study of the life cycle assessment concept in Egypt; to form a foundation for development of an Egyptian database for facilitating a cleaner environment; to encourage stakeholders, such as the environmental agencies, Egyptian Housing and Building Research Center, and the Ministry of Industry; to propose an organizational framework in which they play a central role; and to provide investment to initiate development.

Conclusions

The analysis indicates that the development of a LCI database specific to Egypt is difficult because Egypt has various technical and organizational challenges, but a roadmap of actions to be taken to move ahead is provided. The success of this roadmap depends on the capacity for developing the necessary technical and financial support and on strong partnerships with industry, government, LCA professionals, and academia.     

A framework for increasing the availability of life cycle inventory data based on the role of multinational companies

Purpose

The aim of the paper is to assess the role and effectiveness of a proposed novel strategy for Life Cycle Inventory (LCI) data collection in the food sector and associated supply chains. The study represents one of the first of its type and provides answers to some of the key questions regarding the data collection process developed, managed and implemented by a multinational food company across the supply chain.

Methods

An integrated LCI data collection process for confectionery products was developed and implemented by Nestlé, a multinational food company. Some of the key features includes (1) management and implementation by a multinational food company; (2) types of roles to manage, provide and facilitate data exchange; (3) procedures to identify key products, suppliers and customers; (4) LCI questionnaire and cover letter and (5) data quality management based on the pedigree matrix. Overall, the combined features in an integrated framework provide a new way of thinking about the collection of LCI data from the perspective of a multinational food company.

Results and discussion

The integrated LCI collection framework spanned across 5 months and resulted in 87 new LCI datasets for confectionery products from raw material, primary resource use, emission and waste release data collected from suppliers across 19 countries. The data collected was found to be of medium to high quality compared with secondary data. However, for retailers and waste service companies, only partially completed questionnaires were returned. Some of the key challenges encountered during the collection and creation of data included lack of experience, identifying key actors, communication and technical language, commercial compromise, confidentiality protection and complexity of multi-tiered supplier systems. A range of recommendations are proposed to reconcile these challenges which include standardisation of environmental data from suppliers, concise and targeted LCI questionnaires and visualising complexity through drawings.

Conclusions

The integrated LCI data collection process and strategy has demonstrated the potential role of a multinational company to quickly engage and act as a strong enabler to unlock latent data for various aspects of the confectionery supply chain. Overall, it is recommended that the research findings serve as the foundations to transition towards a standardised procedure which can practically guide other multinational companies to considerably increase the availability of LCI data.

     

International Molybdenum Association (IMOA) life cycle assessment program and perspectives on the LCA harmonization effort

Purpose

In 2001, the International Molybdenum Association (IMOA) initiated their life cycle assessment (LCA) program performing cradle-to-gate life cycle inventories (LCIs) of three molybdenum metallurgical products, followed by LCIs of eight molybdenum chemicals and an update to the metallurgical LCIs. From 2012 to 2014, IMOA participated in a multi-metal industry initiative to harmonize the methodological approach to metal-related LCAs. This paper describes some of IMOA’s conclusions formed from its program and, coupled with its involvement in the multi-metal initiative, provides some lessons learned.

Methods

For this paper, IMOA evaluated the benefits of its LCI program, including its ability to communicate effectively with member companies and stakeholders on the development, use, and application of life cycle data. Likewise, IMOA developed the competence to recognize and provide input on potentially inappropriate use of LCA. IMOA performed a literature review to highlight some of the scientific research using the molybdenum LCI data. IMOA also reviewed the metal industry’s guidance document to provide its perspective on it, including similarities, differences, and substantiation of elements of the four topic areas.

Results and discussion

The metal industry’s guidance document identified four topic areas as essential for alignment with respect to metal-related LCAs: (1) system boundaries, (2) coproduct modelling, (3) life cycle impact assessment (LCIA), and (4) metals recycling modelling. IMOA is largely in agreement with the approaches described in the document. The paper provides examples of how these have been applied to LCAs on Mo-bearing products as well as examples of how some LCA work can benefit from the guidance document.

Conclusions

Having taken part in the harmonization effort, IMOA is poised to educate its member companies and stakeholders about some of the challenging issues encountered in LCA and will continue to lead through active industry participation. IMOA supplies its LCI data via a formal request process which enables open dialogue with stakeholders and LCA practitioners while providing IMOA with insights into how its products fit into the broader lifecycle context and facilitating stakeholders’ awareness of LCA and metals.

     

Spatial and temporal response of multiple trait-based indices to natural- and anthropogenic seafloor disturbance (effluents)

To support ecosystem-based management and achieve the Good Environmental Status (GES) of marine waters it is important to better comprehend the relationships between biodiversity and environmental disturbance (anthropogenic and natural). Biotic indices are widely used in studies to help understanding these relationships and to assess the environmental status of waters. In recent years, trait-based indices rapidly emerged as an alternative ‘functional’ approach to serve this purpose. In this study, we analysed how two indices based upon the mean (community-weighted mean trait value–CWM) and the diversity of multiple traits (Rao’s quadratic entropy–Rao) in a macroinvertebrate community respond to natural- and anthropogenic seafloor disturbance (effluents) and we compared their performance with the widely used AMBI and M-AMBI. Our results demonstrate that CWM and Rao were not effective in indicating anthropogenic disturbance in the Basque coast, Bay of Biscay. The main reason was probably that many traits did not have a strong link with this type of disturbance. Besides, the mechanistic links between certain traits and their response to anthropogenic seafloor disturbance in marine environments is currently not well understood. From a management perspective: the CWM does not provide a single value indicating a quality status, which makes it a difficult tool to use and interpret. This index is probably more useful for scientists who want to explore and understand different aspects of community functioning. On the other hand, Rao and other indices expressing trait diversity do provide a single value of functioning; therefore they could potentially be effectively used for management purposes. However, to improve its performance, detailed and accurate trait data is required, which is currently lacking for many marine species.     

Strategy tool trial for office furniture

Purpose

A strategic product development tool combining REACH and environmental and financial factors was previously developed for a coatings company. This paper presents results from refining this tool for an office furniture company, using life cycle assessment (LCA)-based environmental information, addressing the research questions: ? Is it possible to combine information from REACH with the LCA approach to provide useful information for a furniture producer in their environmental product development process? ? Does the approach developed for substances in mixtures need to be adapted for articles? ? Is there a correlation between energy consumption and the environmental impacts analysed? ? Will product designers get the same information independent of the environmental impact category used? ?C Will the strategy tool indicate the same ranking of products for all environmental impacts? ?C Does REACH information indicate the same set of priorities as those arising from LCA environmental data alone? (Do they agree, or is there a conflict?) ? Will strategic decisions differ if different environmental indicators are in focus? The strategy tool??s purpose is to analyse company product portfolios, identifying products that need redevelopment or redesign because of issues concerning hazardous substances, or environmental performance.

Methods

The LCA data used is cradle-to-gate data from type III environmental declarations for 11 seating solutions. REACH Complexity, health hazard and environmental class indicators (based on risk phrases) are combined with financial data and LCA-based indicators. Correlations between energy consumption and environmental impact factors for these specific furniture products are investigated. Establishing any such correlations serves to simplify subsequent analysis in the product development process, by effectively reducing the number of indicators that need to be taken into consideration.

Results

Correlations between energy consumption and the environmental impacts global warming, acidification, eutrophication and heavy metals are presented. Strategy tool figures are shown for energy consumption, ozone depletion potential and photochemical oxidation potential. The results for office chairs and conference/visitor chairs are presented separately, as the two types of chairs fulfil different functions.

Conclusions

The correlation between energy consumption and certain environmental impact indicators affords a simplification of the product development process, since energy consumption can be used as a reasonable proxy for these indicators in this specific case. The results support acknowledged principles of Ecodesign. Energy and materials minimization improves environmental performance??higher recycled material content and proportion of renewable energy resources are also beneficial. Designers have to consider multiple aspects in parallel and the strategy tool is useful for this purpose; the furniture producer has gained useful product development insight. The tool is applicable for strategic choice of products for development or redesign that can be useful across many business sectors.