Comparative evaluation of Life Cycle Impact assessment methods with a South African case study

Goal and Background  LCIA procedures that have been used in the South Africa manufacturing industry include the CML, Ecopoints, EPS and Eco-indicators 95 and 99 procedures. The aim of this paper is to evaluate and compare the applicability of these European LCIA procedures within the South African context, using a case study. Methods  The five European methods have been evaluated based on the applicability of the respective classification, characterisation, normalization and weighting approaches for the South African situation. Impact categories have been grouped into air, water, land and mined abiotic resources for evaluation purposes. The evaluation and comparison is further based on a cradle-to-gate Screening Life Cycle Assessment (SLCA) case study of the production of dyed two-fold wool yarn in South Africa. Results and Discussion  Where land is considered as a separate category (CML, Eco-indicator 99 and EPS), the case study highlights this inventory constituent as the most important. Similarly, water usage is shown as the second most important in one LCIA procedure (EPS) where it is taken into account. However, the impact assessment modelling for these categories may not be applicable for the variance in South African ecosystems. If land and water is excluded from the interpretation, air emissions, coal usage, ash disposal, pesticides and chrome emissions to water are the important constituents in the South African wool industry. Conclusions  In most cases impact categories and procedures defined in the LCIA methods for air pollution, human health and mined abiotic resources are applicable in South Africa. However, the relevance of the methods is reduced where categories are used that impact ecosystem quality, as ecosystems differ significantly between South Africa and the European continent. The methods are especially limited with respect to water and land resources. Normalisation and weighting procedures may also be difficult to adapt to South African conditions, due to the lack of background information and social, cultural and political differences. Recommendations and Outlook  Further research is underway to develop a framework for a South African LCIA procedure, which will be adapted from the available European procedures. The wool SLCA must be revisited to evaluate and compare the proposed framework with the existing LCIA procedures.     

A life cycle impact assessment procedure with resource groups as areas of protection

Goal and Background  Current Life Cycle Impact Assessment (LCIA) procedures have demonstrated certain limitations in the South African manufacturing industry context. The aim of this paper is to propose a modified LCIA procedure, which is based on the protection of resource groups. Methods  A LCIA framework is introduced that applies the characterisation procedure of available midpoint categories, with the exception of land use. Characterisation factors for land occupation and transformation is suggested for South Africa. A distanceto-target approach is used for the normalisation of midpoint categories, which focuses on the ambient quality and quantity objectives for four resource groups: Air, Water, Land and Mined Abiotic Resources. The quality and quantity objectives are determined for defined South African Life Cycle Assessment (SALCA) Regions and take into account endpoint or damage targets. Following the precautionary approach, a Resource Impact Indicator (RII) is calculated for the resource groups. Subjective weighting values for the resource groups are also proposed, based on survey results from the manufacturing industry sector and the expenditure trends of the South African national government. The subjective weighting values are used to calculate overall Environmental Performance Resource Impact Indicators (EPRIIs) when comparing life cycle systems with each other. The proposed approaches are evaluated with a known wool case study. Results and Discussion  The calculation of a RJI ensures that all natural resources that are important from a South African perspective are duly considered in a LCIA. The results of a LCIA are consequently not reliant on a detailed Life Cycle Inventory (LCI) and the number of midpoint categories that converge on a single resource group. The case study establishes the importance of region-specificity, for LCIs and LCIAs. Conclusions  The proposed LCIA procedure demonstrates reasonable ease of communication of LCIA results. It further allows for the inclusion of additional midpoint categories and is adaptable for specific regions. Recommendations and Outlook  The acceptance of the LCIA procedure must be evaluated for different industry and government sectors. Also, the adequate incorporation of Environmental Performance Resource Impact Indicators (EPRIIs) into decision-making for Life Cycle Management purposes must be researched further. Specifically, the application of the procedures for supply chain management will be investigated.     

The Environmental Importance of Energy Use in Chemical Production

In many cases, policy makers and laymen perceive harmful emissions from chemical plants as the most important source of environmental impacts in chemical production. As a result, regulations and environmental efforts have tended to focus on this area. Concerns about energy use and greenhouse gas emissions, however, are increasing in all industrial sectors. Using a life cycle assessment (LCA) approach, we analyzed the full environmental impacts of producing 99 chemical products in Western Europe from cradle to factory gate. We applied several life cycle impact assessment (LCIA) methods to cover various impact areas. Our analysis shows that for both organic and inorganic chemical production in industrial countries, energy‐related impacts often represent more than half and sometimes up to 80% of the total impacts, according to a range of LCIA methods. Resource use for material feedstock is also important, whereas direct emissions from chemical plants may make up only 5% to 10% of the total environmental impacts. Additionally, the energy‐related impacts of organic chemical production increase with the complexity of the chemicals. The results of this study offer important information for policy makers and sustainability experts in the chemical industry striving to reduce environmental impacts. We identify more sustainable energy production and use as an important option for improvements in the environmental profile of chemical production in industrial countries, especially for the production of advanced organic and fine chemicals.     

Life Cycle Assessment Software: Selection Can Impact Results

When software is used to facilitate life cycle assessments (LCAs), the implicit assumption is that the results obtained are not a function of the choice of software used. LCAs were done in both SimaPro and GaBi for simplified systems of creation and disposal of 1 kilogram each of four basic materials (aluminum, corrugated board, glass, and polyethylene terephthalate) to determine whether there were significant differences in the results. Data files and impact assessment methodologies (Impact 2002, ReCiPe, and TRACI 2) were ostensibly identical (although there were minor variations in the available ReCiPe version between the programs that were investigated). Differences in reported impacts of greater than 20% for at least one of the four materials were found for 9 of the 15 categories in Impact 2002+, 7 of the 18 categories in ReCiPe, and four of the nine categories in TRACI. In some cases, these differences resulted in changes in the relative rankings of the four materials. The causes of the differences for 14 combinations of materials and impact categories were examined by tracing the results back to the life cycle inventory data and the characterization factors in the life cycle impact assessment (LCIA) methods. In all cases examined, a difference in the characterization factors used by the two programs was the cause of the differing results. As a result, when these software programs are used to inform choices, the result can be different conclusions about relative environmental preference that are functions purely of the software implementation of LCIA methods, rather than of the underlying data.     

Efficient information visualization in LCA: approach and examples

Aim, Scope and Background  The data-intensive nature of life cycle assessment (LCA), even for non-complex products, quickly leads to the utilization of various methods of representing the data in forms other than written characters. Up until now, traditional representations of life cycle inventory (LCI) data and environmental impact analysis (EIA) results have usually been based on 2D and 3D variants of simple tables, bar charts, pie charts and x/y graphs. However, these representation methods do not sufficiently address aspects such as representation of life cycle inventory information at a glance, filtering out data while summarizing the filtered data (so as to reduce the information load), and representation of data errors and uncertainty. Main Features  This new information representation approach with its glyph-based visualization method addresses the specific problems outlined above, encountered when analyzing LCA and EIA related information. In particular, support for multi-dimensional information representation, reduction of information load, and explicit data feature propagation are provided on an interactive, computer-aided basis. Results  Three-dimensional, interactive geometric objects, so called OM-glyphs, were used in the visualization method introduced, to represent LCA-related information in a multi-dimensional information space. This representation is defined by control parameters, which in turn represent spatial, geometric and retinal properties of glyphs and glyph formations. All relevant analysis scenarios allowed and valid can be visualized. These consist of combinations of items for the material and energy inventories, environmental items, life cycle phases and products, or their parts and components. Individual visualization scenarios, once computed and rendered on a computer screen, can then interactively be modified in terms of visual viewpoint, size, spatial location and detail of data represented, as needed. This helps to increase speed, efficiency and quality of the assessment performance, while at the same time considerably reducing mental load due to the more structured manner in which information is represented to the human expert. Conclusions  The previous paper in this series discussed the motivation for a new approach to efficient information visualization in LCA and introduced the essential basic principles. This second paper offers more insight into and discussion on technical details and the framework developed. To provide a means for better understanding the visualization method presented, examples have been given. The main purpose of the examples, as already indicated, is to demonstrate and make transparent the mapping of LCA related data and their contexts to glyph parameters. Those glyph parameters, in turn, are used to generate a novel form of sophisticated information representation which is transparent, clear and compact, features which cannot be achieved with any traditional representation scheme. Outlook  Final technical details of this approach and its framework will be presented and discussed in the next paper. Theoretical and practical issues related to the application of this visualization method to the computed life cycle inventory data of an actual industrial product will also be discussed in this next paper.     

Characterisation and Normalisation Factors for Life Cycle Impact Assessment Mined Abiotic Resources Categories in South Africa: The manufacturing of catalytic converter exhaust systems as a case study (10 pp)

Goal and Background Current Life Cycle Impact Assessment (LCIA) procedures have demonstrated certain limitations in the South African manufacturing industry. The aim of this paper is to propose new characterisation and normalisation factors for classified mined abiotic resource depletion categories in the South African context. These factors should reflect the importance of mined resources as they relate to region-specific resource depletion. The method can also be applied to determine global factors. Methods The reserve base (as in 2001) of the most commonly produced minerals in South Africa is used as basis to determine characterisation factors for a non-renewable mineral resources category. The average production of these minerals from 1991 to 2000 is compared to economically Demonstrated and Demonstrated Marginal Reserves (and not ultimate reserves) to obtain the characterisation factors in equivalence units, with platinum as the reference mineral. Similarly, for a non-renewable energy resources category, coal is used in South Africa as equivalent unit as it is the most important fossil fuel for the country. Crude oil and natural gas resources are currently obtained from reserves elsewhere in the world and characterisation factors are therefore determined using global resources and production levels. The normalisation factors are based on the total economic reserves of key South African minerals and world non-renewable energy resources respectively. A case study of the manufacturing of an exhaust system for a standard sedan is used to compare LCIA results for mined abiotic resource categories that are based on current LCIA factors and the new South African factors. Results and Discussion The South African LCIA procedure differs from current methods in that it shows the importance of other mined resources, i.e. iron ore and crude oil, relative to PGMs and coal for the manufacturing life cycle of the exhaust system. With respect to PGMs, the current characterisation factors are based on the concentrations of the metals in the ores and the ultimate reserves, which are erroneous with respect to the actual availability of the mineral resources and the depletion burden placed on these minerals is consequently too high. Conclusions The South African LCIA procedure for mined abiotic resources depletion shows the significance of choosing a method, which is inline with the current situation in the mining industry and its limitations. Recommendations and Outlook It is proposed to similarly investigate the impacts of the use of other natural resource groups. Water, specifically, must receive attention in the characterisation phase of LCIAs in South African LCAs.     

Country-dependent Characterisation Factors for Acidification and Terrestrial Eutrophication Based on Accumulated Exceedance as an Impact Category Indicator (14 pp)

Background, Aims and Scope Several authors have shown that spatially derived characterisation factors used in life cycle impact assessment (LCIA) can differ widely between different countries in the context of regional impact categories such as acidification or terrestrial eutrophication. Previous methodology studies in Europe have produced country-dependent characterisation factors for acidification and terrestrial eutrophication by using the results of the EMEP and RAINS models and critical loads for Europe. The unprotected ecosystem area (UA) is commonly used as a category indicator in the determination of characterisation factors in those studies. However, the UA indicator is only suitable for large emission changes and it does not result in environmental benefits in terms of characterisation factors if deposition after the emission reduction is still higher than the critical load. For this reason, there is a need to search for a new category indicator type for acidification and terrestrial eutrophying in order to calculate site-dependent characterisation factors. The aim of this study is to explore new site-dependent characterisation factors for European acidifying and eutrophying emissions based on accumulated exceedance (AE) as the category indicator, which integrates both the exceeded area and amount of exceedance. In addition, the results obtained for the AE and UA indicators are compared with each other. Methods The chosen category indicator, accumulated exceedance (AE), was computed according to the calculation methods developed in the work under the United Nations Economic Commission for Europe (UNECE) Convention on Long-range Transboundary Air Pollution (LRTAP). Sulphur and nitrogen depositions to 150x150 km2 grid cells over Europe were calculated by source-receptor matrices derived from the EMEP Lagrangian model of long-range transport of air pollution in Europe. Using the latest critical load data of Europe, the site-dependent characterisation factors for acidification and terrestrial eutrophication were calculated for 35 European countries and 5 sea areas for 2002 emissions and emissions predicted for 2010. In the determination of characterisation factors, the emissions of each country/area were reduced by various amounts in order to find stable characterisation factors. In addition, characterisation errors were calculated for the AE-based characterisation factors. For the comparison, the results based on the use of UA indicator were calculated by 10% and 50% reductions of emissions that corresponded to the common practice used in the previous studies. Results and Discussion The characterisation factors based on the AE indicator were shown to be largely independent of the reduction percentage used to calculate them.. Small changes in emissions (≤100 t) produced the most stable characterisation factors in the case of the AE indicator. The characterisation errors of those characterisation factors were practically zero. This means that the characterisation factors can describe the effects of small changes in national emissions that are mostly looked at in LCAs. The comparison between country-dependent characterisation factors calculated by the AE and UA indicators showed that these two approaches produce differences between characterisation factors for many countries/areas in Europe. The differences were mostly related to the Central and Northern European countries. They were greater for terrestrial eutrophication because the contribution of ammonia emission differ remarkably between the two approaches. The characterisation factors of the AE indicator calculated by the emissions of 2002 were greater than the factors calculated by the predicted emissions for 2010 in almost all countries/sea areas, due to the presumed decrease of acidifying and eutrophying emissions in Europe. Conclusions and Recommendations. In this study, accumulated exceedance was shown to be an appropriate category indicator in LCIA applications for the determination of site-dependent characterisation factors for acidification and terrestrial eutrophication in the context of integrated assessment modelling. In the future, it would be useful to calculate characterisation factors for emissions of separate parts of large countries and sea areas in Europe. In addition, it would also be useful to compare the approach based on the AE indicator with the method of the hazard index, as recommended in the latest CML guidebook.     

Quantifying system uncertainty of life cycle assessment based on Monte Carlo simulation

Background, aim, and scope

Many studies evaluate the results of applying different life cycle impact assessment (LCIA) methods to the same life cycle inventory (LCI) data and demonstrate that the assessment results would be different with different LICA methods used. Although the importance of uncertainty is recognized, most studies focus on individual stages of LCA, such as LCI and normalization and weighting stages of LCIA. However, an important question has not been answered in previous studies: Which part of the LCA processes will lead to the primary uncertainty? The understanding of the uncertainty contributions of each of the LCA components will facilitate the improvement of the credibility of LCA.

Methodology

A methodology is proposed to systematically analyze the uncertainties involved in the entire procedure of LCA. The Monte Carlo simulation is used to analyze the uncertainties associated with LCI, LCIA, and the normalization and weighting processes. Five LCIA methods are considered in this study, i.e., Eco-indicator 99, EDIP, EPS, IMPACT 2002+, and LIME. The uncertainty of the environmental performance for individual impact categories (e.g., global warming, ecotoxicity, acidification, eutrophication, photochemical smog, human health) is also calculated and compared. The LCA of municipal solid waste management strategies in Taiwan is used as a case study to illustrate the proposed methodology.

Results

The primary uncertainty source in the case study is the LCI stage under a given LCIA method. In comparison with various LCIA methods, EDIP has the highest uncertainty and Eco-indicator 99 the lowest uncertainty. Setting aside the uncertainty caused by LCI, the weighting step has higher uncertainty than the normalization step when Eco-indicator 99 is used. Comparing the uncertainty of various impact categories, the lowest is global warming, followed by eutrophication. Ecotoxicity, human health, and photochemical smog have higher uncertainty.

Discussion

In this case study of municipal waste management, it is confirmed that different LCIA methods would generate different assessment results. In other words, selection of LCIA methods is an important source of uncertainty. In this study, the impacts of human health, ecotoxicity, and photochemical smog can vary a lot when the uncertainties of LCI and LCIA procedures are considered. For the purpose of reducing the errors of impact estimation because of geographic differences, it is important to determine whether and which modifications of assessment of impact categories based on local conditions are necessary.

Conclusions

This study develops a methodology of systematically evaluating the uncertainties involved in the entire LCA procedure to identify the contributions of different assessment stages to the overall uncertainty. Which modifications of the assessment of impact categories are needed can be determined based on the comparison of uncertainty of impact categories.

Recommendations and perspectives

Such an assessment of the system uncertainty of LCA will facilitate the improvement of LCA. If the main source of uncertainty is the LCI stage, the researchers should focus on the data quality of the LCI data. If the primary source of uncertainty is the LCIA stage, direct application of LCIA to non-LCIA software developing nations should be avoided.     

Applying cumulative exergy demand (CExD) indicators to the ecoinvent database

Goal, Scope and Background Exergy has been put forward as an indicator for the energetic quality of resources. The exergy of a resource accounts for the minimal work necessary to form the resource or for the maximally obtainable amount of work when bringing the resource’s components to their most common state in the natural environment. Exergy measures are traditionally applied to assess energy efficiency, regarding the exergy losses in a process system. However, the measure can be utilised as an indicator of resource quality demand when considering the specific resources that contain the exergy. Such an exergy measure indicates the required resources and assesses the total exergy removal from nature in order to provide a product, process or service. In the current work, the exergy concept is combined with a large number of life cycle inventory datasets available with ecoinvent data v1.2. The goal was, first, to provide an additional impact category indicator to Life-Cycle Assessment practitioners. Second, this work aims at making a large source of exergy scores available to scientific communities that apply exergy as a primary indicator for energy efficiency and resource quality demand. Methods The indicator Cumulative Exergy Demand (CExD) is introduced to depict total exergy removal from nature to provide a product, summing up the exergy of all resources required. CExD assesses the quality of energy demand and includes the exergy of energy carriers as well as of non-energetic materials. In the current paper, the exergy concept was applied to the resources contained in the ecoinvent database, considering chemical, kinetic, hydro-potential, nuclear, solar-radiative and thermal exergies. The impact category indicator is grouped into the eight resource categories fossil, nuclear, hydropower, biomass, other renewables, water, minerals, and metals. Exergy characterization factors for 112 different resources were included in the calculations. Results CExD was calculated for 2630 ecoinvent product and process systems. The results are presented as average values and for 26 specific groups containing 1197 products, processes and infrastructure units. Depending on the process/product group considered, energetic resources make up between 9% and 100% of the total CExD, with an average contribution of 88%. The exergy of water contributes on the average to 8% the total exergy demand, but to more than 90% in specific process groups. The average contribution of minerals and metal ores is 4%, but shows an average value as high as 38% and 13%, in metallic products and in building materials, respectively. Looking at individual processes, the contribution of the resource categories varies substantially from these average product group values. In comparison to Cumulative Energy Demand (CED) and the abiotic-resource-depletion category of CML 2001 (CML’01), non-energetic resources tend to be weighted more strongly by the CExD method. Discussion Energy and matter used in a society are not destroyed but only transformed. What is consumed and eventually depleted is usable energy and usable matter. Exergy is a measure of such useful energy. Therefore, CExD is a suitable energy based indicator for the quality of resources that are removed from nature. Similar to CED, CExD assesses energy use, but regards the quality of the energy and incorporates non-energetic materials like minerals and metals. However, it can be observed for non-renewable energy-intensive products that CExD is very similar to CED. Since CExD considers energetic and non-energetic resources on the basis of exhaustible exergy, the measure is comparable to resource indicators like the resource use category of Eco-indicator 99 and the resource depletion category of CML 2001. An advantage of CExD in comparison to these methods is that exergy is an inherent property of the resource. Therefore less assumptions and subjective choices need to be made in setting up characterization factors. However, CExD does not coversocietal demand (distinguishing between basic demand and luxury), availability or scarcity of the resource. As a consequence of the different weighting approach, CExD may differ considerably from the resource category indicators in Eco-indicator 99 and CML 2001. Conclusions The current work shows that the exergy concept can be operationalised in product life cycle assessments. CExD is a suitable indicator to assess energy and resource demand. Due to the consideration of the quality of energy and the integration of non-energetic resources, CExD is a more comprehensive indicator than the widely used CED. All of the eight CExD categories proposed are significant contributors to Cumulative Exergy Demand in at least one of the product groups analysed. In product or service assessments and comparative assertions, a careful and concious selection of the appropriate CExD-categories is required based on the energy and resource quality demand concept to be expressed by CExD. Recommendations and Perspectives A differentiation between the exergy of fossil, nuclear, hydro-potential, biomass, other renewables, water and mineral/metal resources is recommended in order to obtain a more detailed picture of resource quality demand and to recognise trade-offs between resource use, for instance energetic and non-energetic raw materials, or nonrenewable and renewable energies. ESS-Submission Editor: Dr. Gerald Rebitzer (Gerald.Rebitzer@alcan.com)     

农业生命周期评价研究进展

作为评价产品系统全链条环境影响的有效工具,生命周期评价（LCA）方法已广泛用于工业领域。农业领域也面临着高强度的资源和环境压力,LCA在农业领域的应用应运而生。旨在综述已有农业LCA研究的基础上,鉴别农业LCA应用存在的问题,并为农业LCA未来的发展提出建议。目前农业LCA存在系统边界和功能单位界定不明晰、缺少区域清单数据库、生命周期环境影响评价模型（LCIA）不能准确反映农业系统环境影响、结果解释存在误区等方面的问题。为了科学准确地衡量农业系统的环境影响,促进农业系统的可持续发展,文章认为农业LCA应该从以下几个方面加强研究,即科学界定评价的参照系、系统边界的扩大及功能单位的合理选取、区域异质性数据库构建与LCIA模型开发、基于组织农业LCA的开发以及对于利益相关者行为的研究。     

Efficient information visualization in LCA: Application and practice

Aim, Scope and Background  Acquisition and analysis of huge amounts of data still pose a challenge, with few options available for solutions and support. Life cycle assessment (LCA) experts face such problems on a daily basis. However, data do not become useful until some of the information they carry is extracted, and most important, represented in a way humans can both recognize efficiently and understand and interpret as quickly as possible. Unfortunately, information representation techniques as used in this field are still based on traditional low-dimensional information spaces, featuring only a few basic choices to represent life cycle (LC) related data. We must part from those traditional techniques and shift to visual representations that are easier for us to understand due to the human capability for detecting spatial structures and shapes represented in different colors and textures. Then all the advantages of modern, advanced information visualization can be applied and exploited. Main Features  With the introduction of a new glyph-based information representation and visualization approach to LCA, current issues of representing LC-related information efficiently at a glance are being tackled. These new techniques support reduction of information load by providing tools to select and summarize data, assist in making explicit and transparent data feature propagation, and provide a means of representing data errors and uncertainty. In this approach the human perceptual capability for easily and quickly recognizing and understanding graphical objects in different colors and textures is exploited for the design and application of highly structured and advanced forms of multi-dimensional information representation. Results  Now in the example presented in this paper, OM-glyphs were used to represent LCA-related information for an industrial product and its compiled life cycle inventory under conditions normal for LCA. To demonstrate the application and benefits of the approach introduced, several different visualization scenarios were computed and presented. These were illustrated with a selection of generated glyph-based displays containing spherical glyph clusters for environmental items such as air pollutants and water pollutants, and inventory glyph matrices related to components and to LC phases. Where appropriate, to further aid understanding and clarity, displays were additionally shown with various orientations and in enlarged form. This is a functional feature of interactive 3D OM-glyph based information visualization that can be used in practice to efficiently navigate through displays while at the same time adjusting rendered scenes to the needs of the user at any given time. Due to the huge amount of data acquired and compiled, only a small fraction of the glyph-based displays could be shown, and, in consequence, only a fraction of the data properties, patterns and features available could be discussed in detail. However, it is believed that the basic principles and methods of this approach, as shown in a real application, could be clearly conveyed, and, most important, that the benefits and potential could be displayed in a convincing manner. This technology will support a marked increase in efficiency, speed and quality in LC information analysis. Conclusions  This paper concludes our short series on efficient information visualization in LCA. A new approach to efficient information visualization has been introduced, together with its basic principles. This background was enriched with discussions on and further insights into technical details of the approach and the framework developed. The first practical examples were provided in the previous paper, demonstrating the mapping of LCA-related data and their contexts to glyph parameters. In this paper the application of the approach was presented using data for an actual industrial product. During the discussions, and with the various glyph-based displays shown, it could be convincingly demonstrated that all data features, trends, patterns, relationships, and data imperfections detected and examined, and sometimes traced, could be quickly and efficiently recognized in a short time. Even basic data features, such as small gaps in the data propagation of related values, could be easily seen using OM-glyphs. In the case of traditional data representation, using for example LCI tables, this would require the identification and comparison of several thousand numerical entries. As is the case with all new technology, however, it is still difficult to obtain the interest of the experts, and to convince them that such new ideas will eventually change the face of industry. Outlook  A new, advanced and efficient information representation and visualization approach has been introduced to the LCA community. Hopefully, through this small series of papers, some interest will have been generated in the field of advanced information visualization. For the first time this area has been related to LCA, and some seeds for interdisciplinary research may have been sown. Now it is up to individuals, the experts in the various fields elated to those issues, to respond. The desired results will be stimulating discussions, an exchange of ideas, further initiated multilateral, interdisciplinary efforts, and improved collaboration between partners from academia and industry. At that point, efficient information visualization will finally have arrived at, and received, its deserved place within LCA.     

No Matter – How?: Dealing with Matter‐less Stressors in LCA of Wind Energy Systems

The portfolio of impacts that are quantified in life cycle assessment (LCA) has grown to include rather different stressors than those that were the focus of early LCAs. Some of the newest life cycle impact assessment (LCIA) models are still in an early phase of development and have not yet been included in any LCA study. This is the case for sound emissions and noise impacts, which have been only recently modeled. Sound emissions are matter‐less, time dependent, and bound to the physical properties of waves. The way sound emissions and the relative noise impacts are modeled in LCA can show how new or existing matter‐less impacts can be addressed. In this study, we analyze, through the example of sound emissions, the specific features of a matter‐less impact that does not stem from the use of a kilogram of matter, nor is related to the emission of a kilogram of matter. We take as a case study the production of energy by means of wind turbines, contradicting the commonly held assumption that windmills have no emissions during use. We show how to account for sound emissions in the life cycle inventory phase of the life cycle of a wind turbine and then calculate the relative impacts using a noise LCIA model.     

The Design of a Sustainability Assessment Standard Using Life Cycle Information

Sustainability assessment standards are currently being developed for a range of building products. This activity has been stimulated through the considerable success of the U.S. Green Building Council's (USGBC) LEED? standard. Transparent life cycle–based standards can guide manufacturers to design products that have reduced environmental impact. The use of a sustainability standard can certify performance and avoid green washing. In this article we present a logical framework for designing a sustainability assessment standard through the creation of tables that award points in the standard to be consistent with life cycle information. Certain minimum principles of consistency are articulated. In the case that the life cycle impact assessment method maps the life cycle inventory to impact through a linear weighting, two design approaches—impact category and activity substitution—are constructed to be consistent with these principles. The approach is illustrated in a case study of a partial redesign of a carpet sustainability assessment standard (NSF/ANSI‐140).     

Ecological Toxicity Methods and Metals. An examination of two case studies (8 pp + 1)

Goal, Scope and Background The Apeldoorn Workshop (April 15th, 2004, Apeldoorn, NL) brought together specialists in LCA and Risk Assessment to discuss current practices and complications of the life cycle impact assessment (LCIA) ecological toxicity (ecotox) methodologies for metals. The consensus was that the LCIA methods currently available do not appropriately characterize impacts of metals due to lack of fundamental metals chemistry in the models. A review of five methods available to perform ecotox impact assessment for metals has been prepared to provide Life Cycle Assessment (LCA) practitioners with a better understanding of the current state of the science and potential biases related to metals. The intent is to provide awareness on issues related to ecotox impact assessment. Methods In this paper two case studies, one a copper based product (copper tube), the other a zinc-based product (gutter systems), were selected and examined by applying freshwater ecological toxicity impact models – USES-LCA, Eco-indicator 99 (EI 99), IMPACT 2002, EDIP 97, and CalTOX-ETP. Both studies are recent, comprehensive, cradle-to-gate, and peer-reviewed. The objective is to review the LCIA results in the context of the practical concerns identified by the Apeldoorn Declaration, in particular illustrating any inconsistencies such as chemical characterization coverage, species specificity, and relative contribution to impact results. Results and Discussion The results obtained from all five of the LCIA methods for the copper tube LCI pointed to the same substance as being the most important – copper. This result was obtained despite major fundamental differences between the LCIA methods applied. However, variations of results were found when examining the freshwater ecological toxicity potential of zinc gutter systems. Procedural difficulties and inconsistencies were observed. In part this was due to basic differences in model nomenclature and differences in coverage (IMPACT 2002+ and EDIP 97 contained characterization factors for aluminium that resulted in 90% and 22% contribution to burden respectively, the other three methods did not). Differences were also observed relative to the emissions source compartment. In the case of zinc, air emissions were found to be substantial for some ecotox models, whereas, water emissions results were found to be of issue for others. Conclusions This investigation illustrates the need to proceed with caution when applying LCIA ecotox methodologies to life cycle studies that include metals. Until further improvements are made, the deficiencies should be clearly communicated as part of LCIA reporting. Business or policy decisions should not without further discussion be based solely on the results of the currently available methods for assessing ecotoxicity in LCIA. Outlook The outlook to remedy deficiencies in the ecological toxicity methods is promising. Recently, the LCIA Toxic Impacts Task Force of the UNEP/SETAC Life Cycle Initiative has formed a subgroup to address specific issues and guide the work towards establishment of sound characterization factors for metals. Although some measure of precision of estimation of potential impact has been observed, such as in the case of copper, accuracy is also a major concern and should be addressed. Further investigation through controlled experimentation is needed, particularly LCIs composed of a variety of inorganics as well as organics constituents. Support for this activity has come from the scientific community and industry as well. Broader aspects of structure and nomenclature are being collectively addressed by the UNEP/SETAC Life Cycle Initiative. These efforts will bring practical solutions to issues of naming conventions and LCI to LCIA flow assignments.     

A life cycle method for assessment of a colliery’s eco-indicator

Global Scope and Background  The study was aimed at presenting the methodology of the process eco-indicator, in relation to hard coal mines, and thereby making evaluation of the impact of the mine’s coal extraction process on the environment. The life cycle of a mine is made up of three phases: opening and developing the mine’s deposit, extraction of the mine’s deposit, closing the mine. Methods  The assessment of environmental influence of mining operation of a colliery was executed on a basis of the life cycle analysis, in accordance with the standard series PN-EN 14040. The environmental loads caused by individual unit processes were calculated by means of the aforementioned methodology with division into the basic influence categories: human health, ecosystem quality and natural resources. The obtained values of eco-indicators for the individual unit processes made it possible to compare the unit-process-caused environmental loads. Mean values of the eco-indicators of the individual unit processes were calculated by means of the inventory analysis covering 38 collieries. Next, these indicators were used to compare environmental load values by each similar process in a colliery. A total eco-indicator was calculated for colliery by summing up the eco-indicators of the individual unit processes. The eco-indicators, structured as above, were calculated for the phase of opening out a deposit and for the phase of extraction. Results and Discussion  The model mine in the phase of extraction of a deposit causes a total environmental load which expressed in points of the eco-indicator 99 amounts to 23.9 [MEw]. In the ‘human health’ category losses amount to 8.4 per cent, in the ‘quality of ecosystem’ 0.6 per cent and in the ‘resourses’ category 91 per cent. The greatest losses in all categories are caused by the process of getting body of coal and the next greatest ones are:

Geographical and technological differences in life cycle inventories shown by the use of process models for waste incinerators part I. technological and geographical differences

Goal and Background  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. Objective  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. Methodology  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. Conclusions  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.     

Integration of life cycle assessment in the environmental information system

Background, aim, and scope  As the sustainability improvement becomes an essential business task of industry, a number of companies are adopting IT-based environmental information systems (EIS). Life cycle assessment (LCA), a tool to improve environmental friendliness of a product, can also be systemized as a part of the EIS. This paper presents a case of an environmental information system which is integrated with online LCA tool to produce sets of hybrid life cycle inventory and examine its usefulness in the field application of the environmental management. Main features  Samsung SDI Ltd., the producer of display panels, has launched an EIS called Sustainability Management Initiative System (SMIS). The system comprised modules of functions such as environmental management system (EMS), green procurement (GP), customer relation (e-VOC), eco-design, and LCA. The LCA module adopted the hybrid LCA methodology in the sense that it combines process LCA for the site processes and input–output (IO) LCA for upstream processes to produce cradle-to-gate LCA results. LCA results from the module are compared with results of other LCA studies made by the application of different methodologies. The advantages and application of the LCA system are also discussed in light of the electronics industry. Results and discussion  LCA can play a vital role in sustainability management by finding environmental burden of products in their life cycle. It is especially true in the case of the electronics industry, since the electronic products have some critical public concerns in the use and end-of-life phase. SMIS shows a method for hybrid LCA through online data communication with EMS and GP module. The integration of IT-based hybrid LCA in environmental information system was set to begin in January 2006. The advantage of the comparing and regular monitoring of the LCA value is that it improves the system completeness and increases the reliability of LCA. By comparing the hybrid LCA and process LCA in the cradle-to-gate stage, the gap between both methods of the 42-in. standard definition plasma display panel (PDP) ranges from 1% (acidification impact category) to −282% (abiotic resource depletion impact category), with an average gap of 68.63%. The gaps of the impact categories of acidification (AP), eutrophication (EP), and global warming (GWP) are relatively low (less than 10%). In the result of the comparative analysis, the strength of correlation of three impact categories (AP, EP, GWP) shows that it is reliable to use the hybrid LCA when assessing the environmental impacts of the PDP module. Hybrid LCA has its own risk on data accuracy. However, the risk is affordable when it comes to the comparative LCA among different models of similar product line of a company. In the results of 2 years of monitoring of 42-in. Standard definition PDP, the hybrid LCA score has been decreased by 30%. The system also efficiently shortens man-days for LCA study per product. This fact can facilitate the eco-design of the products and can give quick response to the customer's inquiry on the product's eco-profile. Even though there is the necessity for improvement of process data currently available, the hybrid LCA provides insight into the assessments of the eco-efficiency of the manufacturing process and the environmental impacts of a product. Conclusions and recommendations  As the environmental concerns of the industries increase, the need for environmental data management also increases. LCA shall be a core part of the environmental information system by which the environmental performances of products can be controlled. Hybrid type of LCA is effective in controlling the usual eco-profile of the products in a company. For an industry, in particular electronics, which imports a broad band of raw material and parts, hybrid LCA is more practicable than the classic LCA. Continuous efforts are needed to align input data and keep conformity, which reduces data uncertainty of the system.