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.     

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.     

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.     

LiSET: A Framework for Early‐Stage Life Cycle Screening of Emerging Technologies

While life cycle assessment (LCA) is a tool often used to evaluate the environmental impacts of products and technologies, the amount of data required to perform such studies make the evaluation of emerging technologies using the conventional LCA approach challenging. The development paradox is such that the inputs from a comprehensive environmental assessment has the greatest effect early in the development phase, and yet the data required to perform such an assessment are generally lacking until it is too late. Previous attempts to formalize strategies for performing streamlined or screening LCAs were made in the late 1990s and early 2000s, mostly to rapidly compare the environmental performance of product design candidates. These strategies lack the transparency and consistency required for the environmental screening of large numbers of early‐development candidates, for which data are even sparser. We propose the Lifecycle Screening of Emerging Technologies method (LiSET). LiSET is an adaptable screening‐to‐LCA method that uses the available data to systematically and transparently evaluate the environmental performance of technologies at low readiness levels. Iterations follow technological development and allow a progression to a full LCA if desired. In early iterations, LiSET presents results in a matrix structure combined with a “traffic light” color grading system. This format inherently communicates the high uncertainty of analysis at this stage and presents numerous environmental aspects assessed. LiSET takes advantage of a decomposition analysis and data not traditionally used in LCAs to gain insight to the life cycle impacts and ensure that the most environmentally sustainable technologies are adopted.     

Hybrid Framework for Managing Uncertainty in Life Cycle Inventories

Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input–output (I‐O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom‐up process model can be estimated via a top‐down approach such as the economic I‐O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long‐term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method.     

Linking Data Choices and Context Specificity in Life Cycle Assessment of Waste Treatment Technologies: A Landfill Case Study

To generate meaningful results, life cycle assessments (LCAs) require accurate technology data that are consistent with the goal and scope of the analysis. While literature data are available for many products and processes, finding representative data for highly site‐specific technologies, such as waste treatment processes, remains a challenge. This study investigated representative life cycle inventory (LCI) modeling of waste treatment technologies in consideration of variations in technological level and climate. The objectives were to demonstrate the importance of representative LCI modeling as a function of the specificity of the study, and to illustrate the necessity of iteratively refining the goal and scope of the study as data are developed. A landfill case study was performed where 52 discrete landfill data sets were built and grouped to represent different technology options and geographical sites, potential impacts were calculated, and minimum/maximum (min‐max) intervals were generated for each group. The results showed decreasing min‐max intervals with increasing specificity of the scope of study, which indicates that compatibility between the scope of study and LCI model is critical. Hereby, this study quantitatively demonstrates the influence of representative modeling on LCA results. The results indicate that technology variations and site‐specific conditions (e.g., the influence of precipitation and cover permeability on landfill gas generation and collection) should be carefully addressed by a systematic analysis of the key process parameters. Therefore, a thorough understanding of the targeted waste treatment technologies is necessary to ensure that appropriate data choices are made within the boundaries of the defined scope of the study.     

Using GaBi 3 to perform life cycle assessment and life cycle engineering

The growing availability of software tools has increased the speed of generating LCA studies. Databases and visual tools for constructing material balance modules greatly facilitate the process of analyzing the environmental aspects of product systems over their life cycle. A robust software tool, containing a large LCI dataset and functions for performing LCIA and sensitivity analysis will allow companies and LCA practitioners to conduct systems analyses efficiently and reliably. This paper discusses how the GaBi 3 software tool can be used to perform LCA and Life Cycle Engineering (LCE), a methodology that combines life cycle economic, environmental, and technology assessment. The paper highlights important attributes of LCA software tools, including high quality, well-documented data, transparency in modeling, and data analysis functionality. An example of a regional power grid mix model is used to illustrate the versatility of GaBi 3.     

Assessing freshwater use impacts in LCA: Part I—inventory modelling and characterisation factors for the main impact pathways

Background, aim and scope

Freshwater is a basic resource for humans; however, its link to human health is seldom related to lack of physical access to sufficient freshwater, but rather to poor distribution and access to safe water supplies. On the other hand, freshwater availability for aquatic ecosystems is often reduced due to competition with human uses, potentially leading to impacts on ecosystem quality. This paper summarises how this specific resource use can be dealt with in life cycle analysis (LCA).

Main features

The main quantifiable impact pathways linking freshwater use to the available supply are identified, leading to definition of the flows requiring quantification in the life cycle inventory (LCI).

Results

The LCI needs to distinguish between and quantify evaporative and non-evaporative uses of ‘blue’ and ‘green’ water, along with land use changes leading to changes in the availability of freshwater. Suitable indicators are suggested for the two main impact pathways [namely freshwater ecosystem impact (FEI) and freshwater depletion (FD)], and operational characterisation factors are provided for a range of countries and situations. For FEI, indicators relating current freshwater use to the available freshwater resources (with and without specific consideration of water ecosystem requirements) are suggested. For FD, the parameters required for evaluation of the commonly used abiotic depletion potentials are explored.

Discussion

An important value judgement when dealing with water use impacts is the omission or consideration of non-evaporative uses of water as impacting ecosystems. We suggest considering only evaporative uses as a default procedure, although more precautionary approaches (e.g. an ‘Egalitarian’ approach) may also include non-evaporative uses. Variation in seasonal river flows is not captured in the approach suggested for FEI, even though abstractions during droughts may have dramatic consequences for ecosystems; this has been considered beyond the scope of LCA.

Conclusions

The approach suggested here improves the representation of impacts associated with freshwater use in LCA. The information required by the approach is generally available to LCA practitioners

Recommendations and perspectives

The widespread use of the approach suggested here will require some development (and consensus) by LCI database developers. Linking the suggested midpoint indicators for FEI to a damage approach will require further analysis of the relationship between FEI indicators and ecosystem health.     

A semi-quantitative method for the impact assessment of emissions within a simplified life cycle assessment

Intention, Goal and Scope: Dealing with data gaps, data asymmetries, and inconsistencies in life cycle inventories (LCI) is a general prohlem in Life Cycle Assessment (LCA) studies. An approach to deal with these difficulties is the simplification of LCA. A methodology that lowers the requirements for data quality (accuracy) for process emissions within a simplified LCA is introduced in this article. Background: Simplification is essential for applying LCA in the context of design for environment (DfE). The tool euroMat is a comprehensive DfE software tool that is based on a specific, simplified LCA approach, the Iterative Screening LCA (IS-LCA). Within the scope of the IS-LCA, there is a quantitative assessment of energy-related processes, as well as a semi-quantitative assessment of non-energy related emissions which supplement each other. Objectives: The semi-quantitative assessment, which is in the focus of this article, aims at lowering the requirements for the quality of non-energy related emissions data through combined use of qualitative and quantitative inventory data. Methods: Potential environmental impacts are assessed based on ABC-categories for qualities (harmfulness) of emissions and XYZ-categories for quantities of emitted substances. Employing statistical methods assignment rules for the ABC/XYZ-categories were derived from literature data and databases on emissions to air, water, and soil. Statistical tests as well as a DfE case study (comparing the materials aluminum and carbon fiber reinforced epoxy for a lightweight container to be used in an aerospace application) were conducted in order to evaluate the level of confidence and practicality of the proposed, simplified impact assessment. Results: Statistical and technical consistency checks show that the method bears a high level of confidence. Results obtained by the simplified assessment correlate to those of a detailed quantitative LCA. Conclusions: Therefore, the application of the ABC/XYZ-categories (together with the cumulative energy demand) can be considered a practical and consistent approach for determining the environmental significance of products when only incomplete emission data is available. Future Prospects: The statistical base of the method is expanded continuously since it is an integral part of the DfE software tool euroMat, which is currently being further developed. That should foster the application of the method. Outside DfE, the method should also be capable of facilitating simplified LCAs in general.     

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.     

Ecosystem Services in Life Cycle Assessment while Encouraging Techno‐Ecological Synergies

Life cycle assessment (LCA) has enabled consideration of environmental impacts beyond the narrow boundary of traditional engineering methods. This reduces the chance of shifting impacts outside the system boundary. However, sustainability also requires that supporting ecosystems are not adversely affected and remain capable of providing goods and services for supporting human activities. Conventional LCA does not account for this role of nature, and its metrics are best for comparing alternatives. These relative metrics do not provide information about absolute environmental sustainability, which requires comparison between the demand and supply of ecosystem services (ES). Techno‐ecological synergy (TES) is a framework to account for ES, and has been demonstrated by application to systems such as buildings and manufacturing activities that have narrow system boundaries. This article develops an approach for techno‐ecological synergy in life cycle assessment (TES‐LCA) by expanding the steps in conventional LCA to incorporate the demand and supply of ecosystem goods and services at multiple spatial scales. This enables calculation of absolute environmental sustainability metrics, and helps identify opportunities for improving a life cycle not just by reducing impacts, but also by restoring and protecting ecosystems. TES‐LCA of a biofuel life cycle demonstrates this approach by considering the ES of carbon sequestration, air quality regulation, and water provisioning. Results show that for the carbon sequestration ecosystem service, farming can be locally sustainable but unsustainable at the global or serviceshed scale. Air quality regulation is unsustainable at all scales, while water provisioning is sustainable at all scales for this study in the eastern part of the United States.     

The life cycle assessment management tool for technologies in eastern Europe: why and how

The knowledge and use of western-based environmental management tools like LCA (life cycle assessment) in Eastern Europe is very low. Discussions about introducing environmental management systems and taking care of environmental consequences of producing processes are very relevant now in Eastern European countries that want to become members of the European Union and to introduce their goods onto the international market. In this paper, the problems connected to introducing LCA based environmental management systems and Eco-Labeling in Eastern European countries are described. The poor financial condition of national sciences in Estonia does not appear to be the main problem. A brief overview of the development and current status of LCA research in Denmark, Finland and Japan is presented. Solutions to current problems are discussed, and experiences gained during conducting LCA research on oil shale energy production in Estonia are presented.     

Evaluation of Long-Term Impacts in LCA

When looking at a product’s life cycle, emissions and resource uses, as well as the resulting impacts, usually occur at different points in time. For instance, construction materials are often ‘stored’ in buildings for many decades before they are recycled or disposed of. The goal of the LCA Discussion Forum 22 was to present and discuss arguments pro and contra a temporally differentiated weighting of impacts. The discussion forum started with three talks that illustrated the importance of temporal aspects in LCI and LCIA. The following two presentations discussed the economical principles of discounting, the adequacy of this concept within LCA, and the ethical questions involved. After one further short presentation, three groups were formed that discussed questions about temporally-differentiated weighting, and consequences for LCI as well as LCIA (damage assessment and final weighting). The discussion forum ended with the following conclusions: (a) long-term impacts should be considered in LCA, and (b) long-term emissions should be inventoried separately from short-term emissions. There was no consensus on whether short-term and long-term impacts should be weighted equally. Some prefer to weigh short-term emissions higher, because they are considered to be closer. Consistent and approved forecasts should be used when considering future changes in environmental conditions in LCI and LCIA.     

可持续消费的内涵及研究进展——产业生态学视角

生产和消费是产生诸多环境问题的根本原因,而可持续生产和消费则是实现可持续发展的根本途径。基于产业生态学视角,界定了可持续消费的定义及内涵,认为可持续消费首先须符合代内公平、代际公平和资源能源永续合理利用等可持续理念;其次辨识了可持续消费研究依次经历关注消费者行为直接环境影响、关注产品和服务生命周期环境影响到关注消费者责任3个阶段;最后结合我国城市化、工业化背景,提出我国可持续消费研究应该以城市居民为重点、加强生命周期数据库建设和内注重可持续生产等建议。     

Post-consumer waste wood in attributive product LCA

Background  

In product life cycle assessment (LCA), the attribution of environmental interventions to a product under study is an ambiguous task. This is due to a) the simplistic modeling characteristics in the life cycle inventory step (LCI) of LCA in view of the complexity of our techno-economic system, and b) to the nontangible theoretical nature of the product system as a representation of the processes ‘causally’ linked to a product. Ambiguous methodological decisions during the setup of an LCI include the modeling of end-of-life scenarios or the choice of an allocation factor for the allocation of joint co-production processes. An important criterion for methodological decisions — besides the conformity with the relevant series of standards ISO 14 040 — is if the improvement options, which can be deduced from the LCI, are perceived by the decision-maker as to redirect the material flows at stake into more sustainable paths.     

Societal LCA Methodology and Case Study (12 pp)

Background, Aim and Scope Societal assessment is advocated as one of the three pillars in the evaluation of, and movement toward, sustainability. As is the case with the well established LCA, and the emerging LCC, societal life cycle assessment should be developed in such as way as to permit relative product comparisons, rather than absolute analyses. The development of societal life cycle assessment is in its infancy, and important concepts require clarification including the handling of the more than two hundred social indicators. Therefore, any societal life cycle assessment methodology must explain why it is midpoint- or endpoint-based as well as its reasons to be complimentary with, or included within, life cycle assessment. Materials and Methods: A geographically specific midpoint based societal life cycle assessment methodology, which employs labour hours as an intermediate variable in the calculation has been developed and evaluated against an existing LCA comparing two detergents. The methodology is based on using an existing life cycle inventory and, therefore, has identical system boundaries and functional units to LCA. The societal life cycle assessment methodology, much like LCA, passes from inventory, through characterisation factors, to provide an ultimate result. In analogy to economics and cost estimation, societal life cycle assessment combines, into its statistics, both data as well as estimates, some of which are correlated to elements of the LCI. It focuses on the work hours required to meet basic needs.A geographically specific midpoint based societal life cycle assessment methodology, which employs labour hours as an intermediate variable in the calculation has been developed and evaluated against an existing LCA comparing two detergents. The methodology is based on using an existing life cycle inventory and, therefore, has identical system boundaries and functional units to LCA. The societal life cycle assessment methodology, much like LCA, passes from inventory, through characterisation factors, to provide an ultimate result. In analogy to economics and cost estimation, societal life cycle assessment combines, into its statistics, both data as well as estimates, some of which are correlated to elements of the LCI. It focuses on the work hours required to meet basic needs. Results: The societal life cycle assessment of an appended case study indicates that Detergent 2 generates, relative Detergent 1, approximately 20% less employment in Russia, 35% less in France, and approximately five times more in Canada and South Africa, the latter derived from its higher aluminium content. There is essentially no difference in the employment in the use country (Switzerland) nor in Morocco, where some of the waste disposal was assumed to take place. Discussion: Given that housing is more affordable, in terms of shelter units per labour hour, in South Africa, compared to Europe, it is, therefore, of no surprise that Detergent 2 provides a societal benefit in terms of housing. Detergent 2 does, however, result in dematerialization, in that its environmental impact is lower (LCI). Therefore, as less resources are employed and labour required, in extraction, production and transport, the societal benefits in health care, education and necessities, a grouped variable, are lower for Detergent 2. This is despite the employment shift away from Europe and to less 'developed' regions. Conclusions: The assessment of societal impacts involves several hundred specific indicators. Therefore, aggregation is, if not impossible, at least heavily value laden and, therefore, not recommended. The impact of a societal action, derived from a product purchase or otherwise, is also highly local. Given this, societal life cycle assessment, carried through to the midpoints, and based on an existing LCI, has been developed as a methodology. The results, for an existing LCA-detergent case, illustrate that societal life cycle assessment provides a means to investigate how policy and policy makers can be linked to sustainable development. The sensitivity analyses also clarify the decisions in regards to product improvement. Recommendations and Perspectives: The goal of societal life cycle assessment is not to make decisions, but rather to point out tradeoffs to decision- or policy-makers. This case, and the methodology that it is based on, permit such a comparison. Substituting Detergent 2 for Detergent 1 reduces resource use at the expense of an increase in atmospheric and terrestrial emissions. Access to housing is improved, though at the expense of education, health care and necessities. As a recommendation, one would look at the fact that the majority of indicators are superior for Detergent 2 relative to Detergent 1and seek to improve the aqueous emissions in Detergent 2 via a change in the formulation. An energy or fossil fuel substitution at the site of production could also improve the societal benefits in terms of education and health care. While societal life cycle assessment remains in its infancy, a methodology does exist. The field can, therefore, be viewed in a similar way to LCA in the early 1990s, with a need to validate, consolidate and, ultimately, built toward a standard. The contribution is aimed at contributing to such a discussion and therefore proposes that a societal life cycle assessment be LCI-derived, geographically specific, based on mid-points, and use employment as an intermediate variable.     

On the Complexity of Life Cycle Inventory Networks: Role of Life Cycle Processes with Network Analysis

Determining the relevance and importance of a technosphere process or a cluster of processes in relation to the rest of the industrial network can provide insights into the sustainability of supply chains: those that need to be optimized or controlled/safeguarded. Network analysis (NA) can offer a broad framework of indicators to tackle this problem. In this article, we present a detailed analysis of a life cycle inventory (LCI) model from an NA perspective. Specifically, the network is represented as a directed graph and the “emergy” numeraire is used as the weight associated with the arcs of the network. The case study of a technological system for drinking water production is presented. We investigate the topological and structural characteristics of the network representation of this system and compare properties of its weighted and unweighted network, as well as the importance of nodes (i.e., life cycle unit processes). By identifying a number of advantages and limitations linked to the modeling complexity of such emergy‐LCI networks, we classify the LCI technosphere network of our case study as a complex network belonging to the scale‐free network family. The salient feature of this network family is represented by the presence of “hubs”: nodes that connect with many other nodes. Hub failures may imply relevant changes, decreases, or even breaks in the connectedness with other smaller hubs and nodes of the network. Hence, by identifying node centralities, we can rank and interpret the relevance of each node for its special role in the life cycle network.     

Method for Setting Environmental Targets in Product Development: Incorporating Use‐Phase Impact by Subsystem

In order to address environmental aspects during redesign, the product specification must include related targets that are reachable and challenging. To do so, this article presents a stepwise approach for combining benchmarking information and component impact, out of life cycle assessment (LCA) scaling. This approach requires allocating environmental impacts to each subsystem, which is not commonly done for some life cycle phases in LCAs, most particularly for use phases. This article includes a methodology for allocating such impacts. The underlying criterion is avoiding complex calculations, to make the method more agile. This methodology is presented in a full case study of a complex product: a knuckle boom crane. The case study results in the percentage of impact reduction needed to meet the market average or best competitors. In particular, the results show that the cylinders of the crane have a high contribution to environmental impact, not only because of their weight, but also because of the active power consumed to activate them.