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.     

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.     

Screening stochastic Life Cycle assessment inventory models

A screening methodology is presented that utilizes the linear structure within the deterministic life cycle inventory (LCI) model. The methodology ranks each input data element based upon the amount it contributes toward the final output. The identified data elements along with their position in the deterministic model are then sorted into descending order based upon their individual contributions. This enables practitioners and model users to identify those input data elements that contribute the most in the inventory stage. Percentages of the top ranked data elements are then selected, and their corresponding data quality index (DQI) value is upgraded in the stochastic LCI model. Monte Carlo computer simulations are obtained and used to compare the output variance of the original stochastic model with modified stochastic model. The methodology is applied to four real-world beverage delivery system LCA inventory models for verification. This research assists LCA practitioners by streamlining the conversion process when converting a deterministic LCI model to a stochastic model form. Model users and decision-makers can benefit from the reduction in output variance and the increase in ability to discriminate between product system alternatives.     

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.     

Parameterised inventories for life cycle assessment

Background and Objective  

Life cycle assessment (LCA) is a highly data intensive undertaking, where collecting the life cycle inventory (LCI) data is the most labour intensive part. The aim of this paper is to show a method for representing the LCI in a simplified manner which not only allows an estimative, quantitative LCA, but also the application of advanced analysis methods to 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.     

A Framework for Social Life Cycle Impact Assessment (10 pp)

Goal, Scope and Background To enhance the use of life cycle assessment (LCA) as a tool in business decision-making, a methodology for Social life cycle impact assessment (LCIA) is being developed. Social LCA aims at facilitating companies to conduct business in a socially responsible manner by providing information about the potential social impacts on people caused by the activities in the life cycle of their product. The development of the methodology has been guided by a business perspective accepting that companies, on the one hand, have responsibility for the people affected by their business activities, but, on the other hand, must also be able to compete and make profit in order to survive in the marketplace. Methods A combined, bottom-up and top-down approach has been taken in the development of the Social LCIA. Universal consensus documents regarding social issues as well as consideration for the specific business context of companies has guided the determination of damage categories, impact categories and category indicators. Results Discussion, and Conclusion. The main results are the following: (1) Impacts on people are naturally related to the conduct of the companies engaged in the life cycle rather than to the individual industrial processes, as is the case in Environmental LCA. Inventory analysis is therefore focused on the conduct of the companies engaged in the life cycle. A consequence of this view is that a key must be determined for relating the social profiles of the companies along the life cycle to the product. This need is not present in Environmental LCA, where we base the connection on the physical link which exists between process and product. (2) Boundaries of the product system are determined with respect to the influence that the product manufacturer exerts over the activities in the product chain. (3) A two-layer Social LCA method with an optional and an obligatory set of impact categories is suggested to ensure both societal and company relevance of the method. The obligatory set of impact categories encompasses the minimum expectations to a company conducting responsible business. (4) A new area of protection, Human dignity and Well-being, is defined and used to guide the modelling of impact chains. (5) The Universal Declaration of Human Rights serves as normative basis for Social LCA, together with local or country norms based on socio-economic development goals of individual countries. The International Labour Organisation's Conventions and Recommendations, and the Tripartite Declaration of Principles concerning Multinational Enterprises and Social Policy, support development of the impact pathway top-down, starting from the normative basis. (6) The obligatory part of Social LCA addresses the main stakeholder groups, employees, local community and society. Recommendations and Outlook Social LCA is still in its infancy and a number of further research tasks within this new area are identified.     

Applying Leontief's Price Model to Estimate Missing Elements in Hybrid Life Cycle Inventories

This article presents an approach to estimate missing elements in hybrid life cycle inventories. Its development is motivated by a desire to rationalize inventory compilation while maintaining the quality of the data. The approach builds on a hybrid framework, that is, a combination of process‐ and input–output‐based life cycle assessment (LCA) methodology. The application of Leontief's price model is central in the proposed procedure. Through the application of this approach, an inventory with no cutoff with respect to costs can be obtained. The formal framework is presented and discussed. A numerical example is provided in Supplementary Appendix S1 on the Web.     

An Approach to Integrating Occupational Safety and Health into Life Cycle Assessment: Development and Application of Work Environment Characterization Factors

Integrating occupational safety and health (OSH) into life cycle assessment (LCA) may provide decision makers with insights and opportunities to prevent burden shifting of human health impacts between the nonwork environment and the work environment. We propose an integration approach that uses industry‐level work environment characterization factors (WE‐CFs) to convert industry activity into damage to human health attributable to the work environment, assessed as disability‐adjusted life years (DALYs). WE‐CFs are ratios of work‐related fatal and nonfatal injuries and illnesses occurring in the U.S. worker population to the amount of physical output from U.S. industries; they represent workplace hazards and exposures and are compatible with the life cycle inventory (LCI) structure common to process‐based LCA. A proof of concept demonstrates application of the WE‐CFs in an LCA of municipal solid waste landfill and incineration systems. Results from the proof of concept indicate that estimates of DALYs attributable to the work environment are comparable in magnitude to DALYs attributable to environmental emissions. Construction and infrastructure‐related work processes contributed the most to the work environment DALYs. A sensitivity analysis revealed that uncertainty in the physical output from industries had the most effect on the WE‐CFs. The results encourage implementation of WE‐CFs in future LCA studies, additional refinement of LCI processes to accurately capture industry outputs, and inclusion of infrastructure‐related processes in LCAs that evaluate OSH impacts.     

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.     

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。     

Enhancing the Adoption of Life Cycle Assessment by Small and Medium Enterprises Grouped in an Industrial Cluster: A Case Study of the Tanning Cluster in Tuscany (Italy)

Greenhouse gas emissions from small and medium enterprises (SMEs) account for 70% of the industrial pollution in the European Union. Owing to limited economic and human resources, only a few SMEs start procedures to evaluate the environmental impact of processes and products through life cycle assessment (LCA). In this work, a cluster life cycle assessment (Cluster‐LCA) is proposed as an instrument for the diffusion and realization of LCA analysis in clustered SMEs. This methodology is illustrated with a case study in the tanning cluster in Tuscany. The different characteristics of the methodology are analyzed by identifying the intrinsic strengths, weaknesses, opportunities, and threats. The application of this methodology in a particular cluster is then discussed in order to gather some helpful insight for the application of this methodology in different clusters.     

Traffic noise in LCA

Background, aim, and scope  

An inclusion of traffic noise effects could change considerably the overall results of many life cycle assessment (LCA) studies. However, at present, noise effects are usually not considered in LCA studies, mainly because the existing methods for their inclusion do not fulfill the requirement profile. Two methods proposed so far seem suitable for inclusion in generic life cycle inventory (LCI) databases, and a third allows for inter-modal comparison. The aim of this investigation is an in-depth analysis of the existing methods and the proposition of a framework for modeling road transport noise emissions in LCI in accordance to the requirement profile postulated in part 1.     

Integration of working environment into life cycle assessment framework

Background, aim, and scope  Life cycle assessment (LCA) has been considered one of the tools for supporting decision-making related to the environmental aspects of a product system. It has mainly been used to evaluate the potential impacts associated with relevant inputs and outputs to/from a given product system throughout its life cycle. In most cases, LCA has not considered the impacts on the internal environment, i.e. working environment, but only the external environment. Recently, it has been recognized that the consideration of the impacts on the working environment as well as on the external environment, is needed in order to assess all aspects of the effects on human well-being. To this end, this study has developed a total environmental assessment methodology which enables one to integrate both the working environment and the external environment into the conventional LCA framework. Materials and methods  In general, the characteristics of the impacts on the external environment are different from those on the working environment. In order to properly integrate the two types into total environmental impacts, it is necessary to define identical system boundaries and select impact category indicators at the same level. In order to define the identical system boundary and reduce the uncertainties of LCI results, the hybrid IOA (input–output analysis) method, which integrates the advantages between conventional LCI method and IOA method, is introduced to collect input and output data throughout the entire life cycle of a given product. For the impact category indicators at the endpoint level, LWD (Lost Work Days) is employed to evaluate the damage to human health and safety in the working environment, while DALY (disability-adjusted life years) and PAF (Potentially Affected Fraction) are selected to evaluate the damage to human health and eco-system quality in the external environment, respectively. Results and discussion  The environmental intervention factors (EIFs) are developed not only for the data categories of resource use, air emissions, and water emissions, but also for occupational health and safety to complete a life cycle inventory table. For the development of the EIFs on occupational health and safety, in particular, the number of workers affected by i hazardous items and the number of workers affected at the i magnitude of disability are collected. For the characterization of the impact categories in the working environment, such as occupational health and safety, the exposure factors, effect factors, and damage factors are developed to calculate the LWD of each category. For normalization, the normalization reference is defined as the total LWD divided by the total number of workers. A case study is presented to illustrate the applicability of the proposed method for the integration of the working environment into the conventional LCA framework. Conclusions  This study is intended to develop a methodology which enables one to integrate the working environmental module into the conventional LCA framework. The hybrid IOA method is utilized to extend the system boundary of both the working environment module and the external environment module to the entire life cycle of a product system. In this study, characterization models and category indicators for occupational health and safety are proposed, respectively, while the methodology of Eco-indicator 99 is used for the external environment. In addition to aid further understanding on the results of this method, this study introduced and developed the category indicators such as DALY, and LWD, which can be expressed as a function of time, and introduced PAF, which can be expressed as a probability. Recommendations and perspectives  The consideration of the impacts not only on the external environment, but also on the working environment, is very important, because the best solution for the external environment may not necessarily be the best solution for the working environment. It is expected that the integration of occupational health and safety matters into the conventional LCA framework can bring many benefits to individuals, as well as industrial companies, by avoiding duplicated measures and false optimization.     

Efficient Information Visualization in LCA

Background, Goal and Scope  A complete life cycle assessment (LCA) always requires several itemizations of goal/scope definitions, inventory analysis and impact analysis. This requires the retrieval and collection of inventory information on all processes with which a product or any part of it comes into either direct or indirect contact. As a result, the data required for LCA is vast, uncertain and, therefore, complex. Up until now, unfortunately, and as far as the authors are aware, there has not been much computer-assisted aid available from any of the systems currently used in either academia or industry to support any life cycle (LC) related data representation, other than the traditional methods of tables, xy-graphs, bar charts, pie charts and various 3-D variants of those which are difficult for humans to interpret. Main Features  Benefiting from the synergy of latest developments in both visualization techniques and computer technology, the authors are able to introduce a new information representation approach based on glyphs. These exploit the human perceptual capability for distinguishing spatial structures and shapes presented in different colors and textures. Within this approach, issues of representing life cycle related information at a glance, filtering out data so as to reduce the information load, and representation of data features, such as uncertainty and estimated errors, are targeted. Results  Advanced information visualization, the process which transforms and maps data to a visual representation, employs the glyphs rendered here to create abstract representations of multi-dimensional data sets. Different parameters describing spatial, geometrical and retinal properties of such glyphs, and defining their position, orientation, shape, color, etc., can be used to encode more information in a comprehensible format, thus allowing multiple values to be encoded in those glyph parameters. The natural function of glyphs, linking (mapped) data within a known context with the attributes that in turn control their visualization, is believed capable of providing sufficient functionality to interactively support designers and LCA experts performing life cycle inventory (LCI) information analysis so that they can operate faster and more efficiently than at present. Conclusions  Within this paper, the first of a small series on efficient information visualization in LCA, the motivation for and essential basic principles of the approach are introduced and discussed. With this technique, the essential characteristics of data, relationships, patterns, trends, etc. can be represented in a much better structured and compact manner, thus rendering them clearer and more meaningful. It is hoped that a continuing interest in this work combined with an improved collaboration with industrial partners will eventually provide the grounds for translating this novel approach into an efficient and reliable tool enhancing applied LCA in practice on a broader base. Outlook  More technical details of the approach and its implementation will be introduced and discussed in the following papers, and examples will be offered demonstrating its application and first experimental translation into practice.     

Life cycle assessment of the selective catalytic reduction process for power plants

The overall reduction of the environmental impact by the use of selective catalytic reduction (SCR) of nitrogen oxide emissions in power plants was determined by strict application of ISO 14040 and ISO/DIS 14041. Special emphasis was placed on the implementation of the total product life cycle (PLC) of ammonium molybdate as a key input material. The environmental impact was generated by application of the life cycle assessment (LCA) concept of “ecoscarcity” and integrated in the life cycle inventory analysis (LCI) of SCR systems. The LCI was used to generate the life cycle impact assessment (LC1A) by use of different quantitative valuation methods. Under consideration of the overall LCIA results and the environmental protection costs of the SCR variants, the Ecological Effectiveness of the SCR alternatives was determined. The results enable plausible conclusions with regard to the ecological advantages of the use of deNOx catalysts in the SCR used in hard-coal fired power plants.     

Life-Cycle based methods for sustainable product development

Sustainability-a term originating from silviculture, which was adopted by UNEP as the main political goal for the future development of humankind-is also the ultimate aim of product development. It comprises three components: environment, economy and social aspects which have to be properly assessed and balanced if a new product is to be designed or an existing one is to be improved. The responsibility of the researchers involved in the assessment is to provide appropriate and reliable instruments. For the environmental part there is already an internationally standardized tool: Life Cycle Assessment (LCA). Life Cycle Costing (LCC) is the logical counterpart of LCA for the economic assessment. LCC surpasses the purely economic cost calculation by taking into account hidden costs and potentially external costs over the life cycle of the product. It is a very important point that different life-cycle based methods (including Social Life Cycle Assessment) for sustainablity assessment use the same system boundaries.     

Life cycle inventory analysis - A case study of steel used in Brazilian automobiles

Data acquisition to perform LCA is time and capital consuming. There is already international data about environmental aspects in several processes. This study aims to verify the possibility of adapting international data to Brazilian conditions. Therefore, a Life Cycle Inventory was conducted to compare the use of national and international data for steel used in automobiles. This was done in three steps: objective and scope definition, inventory analysis and interpretation. LCI is a simplification of Life Cycle Assessment (LCA) as impact assessment is not taken into account. Even so, LCI takes into account all life cycle stages of a product, that is, from its extraction through its deposition. In this study, three phases of the life cycle were considered: steel manufacturing, automobile use and disposal. In the case studied, the amount of steel evaluated was 263 kg, which would be possible to be replaced by other materials in a 1,300 kg automobile. Resources and energy consumption, atmospheric emissions and solid residues production were taken into account within the analysis done. Results show that automobile use and materials manufacturing are responsible for the bulk of energy and resources consumption. Solid residues occur mainly in the discard phase, due to the low level of recycling. Several differences were also achieved between national and international data, which implies the need of environmental databases development.     

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.