The EcoSpold 2 format—why a new format?

Purpose

This paper introduces the new EcoSpold data format for life cycle inventory (LCI).

Methods

A short historical retrospect on data formats in the life cycle assessment (LCA) field is given. The guiding principles for the revision and implementation are explained. Some technical basics of the data format are described, and changes to the previous data format are explained.

Results

The EcoSpold 2 data format caters for new requirements that have arisen in the LCA field in recent years.

Conclusions

The new data format is the basis for the Ecoinvent v3 database, but since it is an open data format, it is expected to be adopted by other LCI databases. Several new concepts used in the new EcoSpold 2 data format open the way for new possibilities for the LCA practitioners and to expand the application of the datasets in other fields beyond LCA (e.g., Material Flow Analysis, Energy Balancing).

     

Notions on the Design and Use of an Ideal Regional or Global LCA Database

Goal, Scope and Background

More and more national and regional life cycle assessment (LCA) databases are being established satisfying the increasing demand on LCA in policy making (e.g. Integrated Product Policy, IPP) and in industry. In order to create harmonised datasets in such unified databases, a common understanding and common rules are required. This paper describes major requirements on the way towards an ideal national background LCA database in terms of co-operation, but also in terms of life cycle inventory analysis (LCI) and impact assessment (LCIA) methodology.

Methods

A classification of disputed methodological issues is made according to their consensus potential. In LCI, three main areas of dissent are identified where consensus seems hardly possible, namely system modelling (consequential versus attributional), allocation (including recycling) and reporting (transparency and progressiveness). In LCIA the time aspect is added to the well-known value judgements of the weighting step.

Results and Discussions

It is concluded that LCA methodology should rather allow for plurality than to urge harmonisation in any case. A series of questions is proposed to identify the most appropriate content of the LCA background database or the most appropriate LCI dataset. The questions help to identify the best suited approach in modelling the product system in general and multioutput and recycling processes in particular. They additionally help to clarify the position with regard to time preferences in LCIA. Intentionally, the answers to these questions are not attributed to particular goal and scope definitions, although some recommendations and clarifying explanations are provided.

Recommendations and Perspective

It is concluded that there is not one single ideal background database content. Value judgements are also present in LCI modelling and require pluralistic solutions; solutions possibly based on the same primary data. It is recommended to focus the methodological discussion on aspects where consensus is within reach, sensible and of added value for all parties.

     

A generalized computational structure for regional life-cycle assessment

Purpose

Regional life-cycle assessment (LCA) is gaining an increasing attention among LCA scholars and practitioners. Here, we present a generalized computational structure for regional LCA, discuss in-depth the major challenges facing the field, and point to a direction in which we believe regional LCA should be headed.

Methods

Using an example, we first demonstrate that when there is regional heterogeneity (be it due to environmental conditions or technologies), average data would be inadequate for estimating the life-cycle impacts of a product produced in a specific region or even that of an average product produced in many regions. And when there is such regional heterogeneity, an understanding of how regions are connected through commodity flows is important to the accuracy of regional LCA estimates. Then, we present a generalized computational structure for regional LCA that takes into account interregional commodity flows, can evaluate various cases of regional differentiation, and can account for multiple impact categories simultaneously. In so doing, we show what kinds of data are required for this generalized framework of regional LCA.

Results and discussion

We discuss the major challenges facing regional LCA in terms of data requirements and computational complexity, and their implications for the choice of an optimal regional scale (i.e., the number of regions delineated within the geographic boundary studied).

Conclusions

We strongly recommend scholars from LCI and LCIA to work together and choose a spatial scale that not only adequately captures environmental characteristics but also allows inventory data to be reasonably compiled or estimated.

     

Bridge processes: a solution for LCI datasets independent of background databases

Introduction

New platforms are emerging that enable more data providers to publish life cycle inventory data.

Background

Providing datasets that are not complete LCA models results in fragments that are difficult for practitioners to integrate and use for LCA modeling. Additionally, when proxies are used to provide a technosphere input to a process that was not originally intended by the process authors, in most LCA software, this requires modifying the original process.

Results

The use of a bridge process, which is a process created to link two existing processes, is proposed as a solution.

Discussion

Benefits to bridge processes include increasing model transparency, facilitating dataset sharing and integration without compromising original dataset integrity and independence, providing a structure with which to make the data quality associated with process linkages explicit, and increasing model flexibility in the case that multiple bridges are provided. A drawback is that they add additional processes to existing LCA models which will increase their size.

Conclusions

Bridge processes can be an enabler in allowing users to integrate new datasets without modifying them to link to background databases or other processes they have available. They may not be the ideal long-term solution but provide a solution that works within the existing LCA data model.

     

The ecoinvent database version 3 (part I): overview and methodology

Purpose

Good background data are an important requirement in LCA. Practitioners generally make use of LCI databases for such data, and the ecoinvent database is the largest transparent unit-process LCI database worldwide. Since its first release in 2003, it has been continuously updated, and version 3 was published in 2013. The release of version 3 introduced several significant methodological and technological improvements, besides a large number of new and updated datasets. The aim was to expand the content of the database, set the foundation for a truly global database, support regionalized LCIA, offer multiple system models, allow for easier integration of data from different regions, and reduce maintenance efforts. This article describes the methodological developments.

Methods

Modeling choices and raw data were separated in version 3, which enables the application of different sets of modeling choices, or system models, to the same raw data with little effort. This includes one system model for Consequential LCA. Flow properties were added to all exchanges in the database, giving more information on the inventory and allowing a fast calculation of mass and other balances. With version 3.1, the database is generally water-balanced, and water use and consumption can be determined. Consumption mixes called market datasets were consistently added to the database, and global background data was added, often as an extrapolation from regional data.

Results and discussion

In combination with hundreds of new unit processes from regions outside Europe, these changes lead to an improved modeling of global supply chains, and a more realistic distribution of impacts in regionalized LCIA. The new mixes also facilitate further regionalization due to the availability of background data for all regions.

Conclusions

With version 3, the ecoinvent database substantially expands the goals and scopes of LCA studies it can support. The new system models allow new, different studies to be performed. Global supply chains and market datasets significantly increase the relevance of the database outside of Europe, and regionalized LCA is supported by the data. Datasets are more transparent, include more information, and support, e.g., water balances. The developments also support easier collaboration with other database initiatives, as demonstrated by a first successful collaboration with a data project in Québec. Version 3 has set the foundation for expanding ecoinvent from a mostly regional into a truly global database and offers many new insights beyond the thousands of new and updated datasets it also introduced.

     

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

Purpose

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

Methods

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

Results and discussion

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

Conclusions

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

     

A flexible parametric model for a balanced account of forest carbon fluxes in LCA

Purpose

Despite a mature debate on the importance of a time-dependent account of carbon fluxes in life cycle assessments (LCA) of forestry products, static accounts of fluxes are still common. Time-explicit inventory of carbon fluxes is not available to LCA practitioners, since the most commonly used life cycle inventory (LCI) databases use a static approach. Existing forest models are typically applied to specific study fields for which the detailed input parameters required are available. This paper presents a simplified parametric model to obtain a time-explicit balanced account of the carbon fluxes in a forest for use in LCA. The model was applied to the case of spruce as an example.

Methods

The model calculated endogenous and exogenous carbon fluxes in tons of carbon per hectare. It was designed to allow users to choose (a) the carbon pools to be included in the analysis (aboveground and belowground carbon pools, only aboveground carbon or only carbon in stem); (b) a linear or sigmoidal dynamic function describing biomass growth; (c) a sigmoidal, negative exponential or linear dynamic function describing independently the decomposition of aboveground and belowground biomass; and (d) the forest management features such as stand type, rotation time, thinning frequency and intensity.

Results and discussion

The parametric model provides a time-dependent LCI of forest carbon fluxes per unit of product, taking into account the typically limited data available to LCA practitioners, while providing consistent and robust outcomes. The results obtained for the case study were validated with the more complex CO2FIX. The model ensures carbon balance within spatial and time delimitation defined by the user by accounting for the annual biomass degradation and production in each carbon pool. The inventory can be used in LCA studies and coupled with classic indicators (e.g. global warming potential) to accurately determine the climate impacts over time. The model is applicable globally and to any forest management practice.

Conclusions

This paper proposes a simplified and flexible forest model, which facilitates the implementation in LCA of time-dependent assessments of bio-based products.

     

Uncertainty analysis in LCA using precalculated aggregated datasets

Purpose

Some LCA software tools use precalculated aggregated datasets because they make LCA calculations much quicker. However, these datasets pose problems for uncertainty analysis. Even when aggregated dataset parameters are expressed as probability distributions, each dataset is sampled independently. This paper explores why independent sampling is incorrect and proposes two techniques to account for dependence in uncertainty analysis. The first is based on an analytical approach, while the other uses precalculated results sampled dependently.

Methods

The algorithm for generating arrays of dependently presampled aggregated inventories and their LCA scores is described. These arrays are used to calculate the correlation across all pairs of aggregated datasets in two ecoinvent LCI databases (2.2, 3.3 cutoff). The arrays are also used in the dependently presampled approach. The uncertainty of LCA results is calculated under different assumptions and using four different techniques and compared for two case studies: a simple water bottle LCA and an LCA of burger recipes.

Results and discussion

The meta-analysis of two LCI databases shows that there is no single correct approximation of correlation between aggregated datasets. The case studies show that the uncertainty of single-product LCA using aggregated datasets is usually underestimated when the correlation across datasets is ignored and that the magnitude of the underestimation is dependent on the system being analysed and the LCIA method chosen. Comparative LCA results show that independent sampling of aggregated datasets drastically overestimates the uncertainty of comparative metrics. The approach based on dependently presampled results yields results functionally identical to those obtained by Monte Carlo analysis using unit process datasets with a negligible computation time.

Conclusions

Independent sampling should not be used for comparative LCA. Moreover, the use of a one-size-fits-all correction factor to correct the calculated variability under independent sampling, as proposed elsewhere, is generally inadequate. The proposed approximate analytical approach is useful to estimate the importance of the covariance of aggregated datasets but not for comparative LCA. The approach based on dependently presampled results provides quick and correct results and has been implemented in EcodEX, a streamlined LCA software used by Nestlé. Dependently presampled results can be used for streamlined LCA software tools. Both presampling and analytical solutions require a preliminary one-time calculation of dependent samples for all aggregated datasets, which could be centrally done by database providers. The dependent presampling approach can be applied to other aspects of the LCA calculation chain.

     

Geographic variability of agriculture requires sector-specific uncertainty characterization

Purpose

Regionalization in life cycle assessment (LCA) has focused on spatially differentiated environmental variables for regional impact assessment models. Relatively less attention has been paid to spatial disparities in intermediate flows for life cycle inventory (LCI).

Methods

First, we compiled state-specific LCIs for four major crops in the USA and evaluated their geographic variability in the characterized results due to the differences in intermediate inputs. Second, we evaluated the consequence of choosing average or region-specific LCIs in understanding the life cycle environmental implications of land use change from cotton to corn or soybean. Finally, we analyzed the implications of our findings in characterizing the uncertainties associated with geographic variability under the conventional pedigree approach.

Results and discussion

Our results show that spatial disparities in LCI alone lead to two to fourfold differences in characterized results for most impact categories. The differences, however, increase to over an order of magnitude for freshwater ecotoxicity and human health non-cancer. Among the crops analyzed, winter wheat shows higher variability partly due to a larger difference in yield. As a result, the use of national average data derived from top corn and soybean producing states significantly underestimates the characterized impacts of corn and soybean in the states where land conversion from cotton to corn or soybean actually took place. The results also show that the conventional pedigree approach to uncertainty characterization in LCA substantially underestimates uncertainties arising from geographic variability of agriculture. Compared to the highest geometric standard deviation (GSD) value of 1.11 under the pedigree approach, the GSDs that we derived are as high as 7.1, with the median around 1.9.

Conclusions

The results highlight the importance of building regional life cycle inventory for understanding the environmental impacts of crops at the regional level. The high geographic variability of crops also indicates the need for sector-specific approaches to uncertainty characterization. Our results also suggest that the uncertainty values in the existing LCI databases might have been signficantly underestimated especially for those products with high geographic variability, demanding a cautious interpretation of the results derived from them. 

     

Life cycle assessment of construction and renovation of sewer systems using a detailed inventory tool

Purpose

The objective was to provide comprehensive life cycle inventories for the construction and renovation of sewers. A detailed inventory was provided with multiple options of pipe materials, diameters and site-specific characteristics, and was embedded into the Excel^®-based tool SewerLCA. The tool allows for life cycle evaluation of different sewers. It was applied to determine the most important phases, processes, and related parameters involved in the construction and renovation of sewers from an environmental and economical perspective.

Methods

Comprehensive life cycle inventories (LCIs) for sewers construction and renovation were obtained by first identifying all processes involved after interviewing construction experts and reviewing sewer construction budgets from a Catalan company; and second transforming the processes into masses of materials and energy usage using construction databases. In order to run the life cycle impact assessment (LCIA) the materials and energy typologies from the inventories were matched to their corresponding equivalents into available LCI databases. Afterwards the potential impacts were calculated through the use of LCIA characterization factors from ReCiPe. Life cycle assessment (LCA) was run several times to assess the construction of a 1-km-long sewer with varying pipe materials, life spans for each material, diameters, transport distances, site-specific characteristics, and pipe deposition options.

Results and discussion

The environmental impacts generated by construction and renovation of a 1 km Polyvinylchloride (PVC) pipe with a diameter of 40 cm are mainly associated with pipe laying and backfilling of the trench. The evaluation of several pipe materials and diameters shows that the exclusion of renovation would underestimate the impacts by 38 to 82 % depending on the pipe materials and diameters. Including end-of-life phase for plastic pipe materials increases climate change (up to an extra 71 %) and human toxicity (up to an extra 147 %) impacts (among all diameters). The preferred pipe materials from an environmental point of view are precast concrete and High-Density Polyethylene (HDPE). Site-specific characteristics (specially the presence of rocky soil and asphalt placement) and material life span have a high influence on the overall environmental profile, whereas changes in transport distances have only a minor impact (<4 %).

Conclusions

Environmental impacts during the construction and renovation of sewers are subject to differences in material type, site-specific characteristics and material life span. Renovation of sewers has a large influence on all potential environmental impacts and costs and, hence, should not be omitted in LCA studies. The treatment and disposal processes of plastic pipes at the end of their life has to be accounted in LCA studies.

     

Attributional and consequential LCA in the ILCD handbook

Purpose

This discussion article aims to highlight two problematic aspects in the International Reference Life Cycle Data System (ILCD) Handbook: its guidance to the choice between attributional and consequential modeling and to the choice between average and marginal data as input to the life cycle inventory (LCI) analysis.

Methods

We analyze the ILCD guidance by comparing different statements in the handbook with each other and with previous research in this area.

Results and discussion

We find that the ILCD handbook is internally inconsistent when it comes to recommendations on how to choose between attributional and consequential modeling. We also find that the handbook is inconsistent with much of previous research in this matter, and also in the recommendations on how to choose between average and marginal data in the LCI.

Conclusions

Because of the inconsistencies in the ILCD handbook, we recommend that the handbook be revised.

     

Experiences with the critical review process of aluminium LCI data

Background, aim, and scope

This paper summarises the critical review process according to ISO 14040/44 performed for the European Aluminium Association (EAA), Brussels. Scope of the review was a life cycle inventory (LCI) project, aiming at providing the life cycle assessment (LCA) community with reliable generic data relevant for the European aluminium market, including the production of aluminium ingot either from primary aluminium or from recycled aluminium and the fabrication of semi-finished products, i.e. sheet, foil or extrusion fabrication from aluminium ingots.

Main features

Critical reviewing according to ISO 14040 and 14044, although described formally in the standards, evolved essentially via ‘learning by doing’. This special review has been conducted as a critical review by one external expert. Since no comparative assertions are to be expected from the results obtained, a critical review according to the panel method (at least three reviewers) was deemed not to be necessary. The review process was interactive and took about a year (March 2007 to April 2008). The full review report is printed in full length at the end of the published LCI data report.

Results

The report continues the tradition of the former reports but offers new aspects. The main change refers to the use of new software for data handling (GaBi 4.0 replacing the formerly used LCA-2 based on BUWAL data), including generic data for ancillary processes and inputs for the energy model. The LCI results, therefore, cannot be compared exactly with the data of the previous reports. There is no disconnection, however, so that trends can be observed and discussed with some precaution. The main trend with respect to energy and emissions is one of slow but steady improvement. A main methodological improvement with regard to the former projects is the new energy model, especially with regard to imported primary aluminium.

Discussion

There was some discussion about the term ‘waste’ when it is put outside the system boundary together with the resulting emissions. According to the author’s opinion, there are at least three types of waste: (1) waste to be reused or recycled—this waste stays within the technosphere and, thus, within the system boundaries of a typical LCA; (2) waste to be collected and removed legally by incineration, controlled landfilling or composting—this waste stays within the technosphere, too; only the emissions of the waste removal processes (CO₂, CH₄, organic contaminants to ground water, leached metal ions to ground water, etc.) escape into the environment if not collected properly; (3) waste thrown away, e.g. by littering, illegal dumping, burning, etc.; this waste ends up in the environment if not collected. There was a time when solid waste in LCA (if landfilled) was considered as an ‘emission into soil’. This is only true for illegal, uncontrolled land filling. Controlled landfilling is a kind of process and belongs to the technosphere as long as it is controlled. EAA envisages to include appropriate data in future updates (incineration is already included).

Conclusions

According to ISO 14040, “The critical review process shall ensure that: the methods used to carry out the LCA are consistent with the international Standard; the methods used to carry out the LCA are scientifically and technically valid, the data used are appropriate and reasonable in relation to the goal of the study; the interpretations reflect the limitations identified and the goal of the study; the study report is transparent and consistent.” These five points can be confirmed with a few restrictions. With regard to the first item, consistency with ISO 14040/44, there is a formal lack of a section ‘interpretation’. It was also discussed that the study is not a full LCA, but the standard allows for LCI studies. As such, the study conforms to ISO. The methods used in data collection and modelling are described clearly and correspond to the state of the art. They should be published and become standard for generic data collection.

Perspectives

It is assumed and recommended that the process of continuous improvement (both technological and relating to data collection and modelling) will continue in the following years. However, since raw aluminium production is faced with thermodynamic limits, it is proposed to rethink the whole aluminium system, which is based on a century-old technology and to conceive bold new routes, especially aiming at a further increase of renewable energy use and further improving recycling in countries with deficient waste collecting systems. The use of heavy fuel oil in alumina production should be discouraged.

     

Criteria for the evaluation of life cycle assessment software packages and life cycle inventory data with application to concrete

Purpose

Life cycle assessment (LCA) software packages have proliferated and evolved as LCA has developed and grown. There are now a multitude of LCA software packages that must be critically evaluated by users. Prior to conducting a comparative LCA study on different concrete materials, it is necessary to examine a variety of software packages for this specific purpose. The paper evaluates five LCA tools in the context of the LCA of seven concrete mix designs (conventional concrete, concrete with fly ash, slag, silica fume or limestone as cement replacement, recycled aggregate concrete, and photocatalytic concrete).

Methods

Three key evaluation criteria required to assess the quality of analysis are adequate flexibility, sophistication and complexity of analysis, and usefulness of outputs. The quality of life cycle inventory (LCI) data included in each software package is also assessed for its reliability, completeness, and correlation to the scope of LCA of concrete products in Canada. A questionnaire is developed for evaluating LCA software packages and is applied to five LCA tools.

Results and discussion

The result is the selection of a software package for the specific context of LCA of concrete materials in Canada, which will be used to complete a full LCA study. The software package with the highest score is software package C (SP-C), with 44 out of a possible 48 points. Its main advantage is that it allows for the user to have a high level of control over the system being modeled and the calculation methods used.

Conclusions

This comparative study highlights the importance of selecting a software package that is appropriate for a specific research project. The ability to accurately model the chosen functional unit and system boundary is an important selection criterion. This study demonstrates a method to enable a critical and rigorous comparison without excessive and redundant duplication of efforts.

     

Life cycle assessment of a steam thermolysis process to recover carbon fibers from carbon fiber-reinforced polymer waste

Purpose

Carbon fibers have been widely used in composite materials, such as carbon fiber-reinforced polymer (CFRP). Therefore, a considerable amount of CFRP waste has been generated. Different recycling technologies have been proposed to treat the CFRP waste and recover carbon fibers for reuse in other applications. This study aims to perform a life cycle assessment (LCA) to evaluate the environmental impacts of recycling carbon fibers from CFRP waste by steam thermolysis, which is a recycling process developed in France.

Methods

The LCA is performed by comparing a scenario where the CFRP waste is recycled by steam-thermolysis with other where the CFRP waste is directly disposed in landfill and incineration. The functional unit set for this study is 2 kg of composite. The inventory analysis is established for the different phases of the two scenarios considered in the study, such as the manufacturing phase, the recycling phase, and the end-of-life phase. The input and output flows associated with each elementary process are standardized to the functional unit. The life cycle impact assessment (LCIA) is performed using the SimaPro software and the Ecoinvent 3 database by the implementation of the CML-IA baseline LCIA method and the ILCD 2011 midpoint LCIA method.

Results and discussion

Despite that the addition of recycling phase produces non-negligible environmental impacts, the impact assessment shows that, overall, the scenario with recycling is less impactful on the environment than the scenario without recycling. The recycling of CFRP waste reduces between 25 and 30% of the impacts and requires about 25% less energy. The two LCIA methods used, CML-IA baseline and ILCD 2011 midpoint, lead to similar results, allowing the verification of the robustness and reliability of the LCIA results.

Conclusions

The recycling of composite materials with recovery of carbon fibers brings evident advantages from an environmental point of view. Although this study presents some limitations, the LCA conducted allows the evaluation of potential environmental impacts of steam thermolysis recycling process in comparison with a scenario where the composites are directly sent to final disposal. The proposed approach can be scaled up to be used in other life cycle assessments, such as in industrial scales, and furthermore to compare the steam thermolysis to other recycling processes.

     

A scalable life cycle inventory of an electrical automotive traction machine—Part I: design and composition

Purpose

A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models’ mass estimations.

Methods

Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines’ maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20–200 kW and 48–477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands.

Results and discussion

The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models’ mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96–97%.

Conclusions

The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking.

     

Pesticide emission modelling and freshwater ecotoxicity assessment for Grapevine LCA: adaptation of PestLCI 2.0 to viticulture

Purpose

Consumption of high quantities of pesticides in viticulture emphasizes the importance of including pesticide emissions and impacts hereof in viticulture LCAs. This paper addresses the lack of inventory models and characterization factors suited for the quantification of emissions and ecotoxicological impacts of pesticides applied to viticulture. The paper presents (i) a tailored version of PestLCI 2.0, (ii) corresponding characterization factors for freshwater ecotoxicity characterization and (iii) result comparison with other inventory approaches. The purpose of this paper is hence to present a viticulture customized version of PestLCI 2.0 and illustrate the application of this customized version on a viticulture case study.

Methods

The customization of the PestLCI 2.0 model for viticulture includes (i) addition of 29 pesticide active ingredients commonly used in vineyards, (ii) addition of 9 viticulture type specific spraying equipment and accounting the number of rows treated in one pass, and (iii) accounting for mixed canopy (vine/cover crop) pesticide interception. Applying USEtox?, the PestLCI 2.0 customization is further supported by the calculation of freshwater ecotoxicity characterization factors for active ingredients relevant for viticulture. Case studies on three different vineyard technical management routes illustrate the application of the inventory model. The inventory and freshwater ecotoxicity results are compared to two existing simplified emission modelling approaches.

Results and discussion

The assessment results show considerably different emission fractions, quantities emitted and freshwater ecotoxicity impacts between the different active ingredient applications. Three out of 21 active ingredients dominate the overall freshwater ecotoxicity: Aclonifen, Fluopicolide and Cymoxanil. The comparison with two simplified emission modelling approaches, considering field soil and air as part of the ecosphere, shows that PestLCI 2.0 yields considerable lower emissions and, consequently, lower freshwater ecotoxicity. The sensitivity analyses reveal the importance of soil and climate characteristics, canopies (vine and cover crop) development and sprayer type on the emission results. These parameters should therefore be obtained with site-specific data, while literature or generic data that are acceptable inputs for parameters whose uncertainties have less influence on the result.

Conclusions

Important specificities of viticulture have been added to the state-of-the-art inventory model PestLCI 2.0. They cover vertically trained vineyards, the most common vineyard training form; they are relevant for other perennial or bush crops provided equipment, shape of the canopy and pesticide active ingredients stay in the range of available options. A similar and compatible model is needed for inorganic pesticide active ingredients emission quantification, especially for organic viticulture impacts accounting.

     

Life cycle inventories of electricity generation and power supply in version 3 of the ecoinvent database—part I: electricity generation

Purpose

Life cycle inventories (LCI) of electricity generation and supply are among the main determining factors regarding life cycle assessment (LCA) results. Therefore, consistency and representativeness of these data are crucial. The electricity sector has been updated and substantially extended for ecoinvent version 3 (v3). This article provides an overview of the electricity production datasets and insights into key aspects of these v3 inventories, highlights changes and describes new features.

Methods

Methods involved extraction of data and analysis from several publically accessible databases and statistics, as well as from the LCA literature. Depending on the power generation technology, either plant-specific or region-specific average data have been used for creating the new power generation inventories representing specific geographies. Whenever possible, the parent–child relationship was used between global and local activities. All datasets include a specific technology level in order to support marginal mixes used in the consequential version of ecoinvent. The use of parameters, variables and mathematical relations enhances transparency. The article focuses on documentation of LCI data on the unlinked unit process level and presents direct emission data of the electricity-generating activities.

Results and discussion

Datasets for electricity production in 71 geographic regions (geographies) covering 50 countries are available in ecoinvent v3. The number of geographies exceeds the number of countries due to partitioning of power generation in the USA and Canada into several regions. All important technologies representing fossil, renewable and nuclear power are modelled for all geographies. The new inventory data show significant geography-specific variations: thermal power plant efficiencies, direct air pollutant emissions as well as annual yields of photovoltaic and wind power plants will have significant impacts on cumulative inventories. In general, the power plants operating in the 18 newly implemented countries (compared to ecoinvent v2) are on a lower technology level with lower efficiencies and higher emissions. The importance of local datasets is once more highlighted.

Conclusions

Inventories for average technology-specific electricity production in all globally important economies are now available with geography-specific technology datasets. This improved coverage of power generation representing 83 % of global electricity production in 2008 will increase the quality of and reduce uncertainties in LCA studies worldwide and contribute to a more accurate estimation of environmental burdens from global production chains. Future work on LCI of electricity production should focus on updates of the fuel chain and infrastructure datasets, on including new technologies as well as on refining of the local data.

     

Towards harmonizing natural resources as an area of protection in life cycle impact assessment

Purpose

In this paper, we summarize the discussion and present the findings of an expert group effort under the umbrella of the United Nations Environment Programme (UNEP)/Society of Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative proposing natural resources as an Area of Protection (AoP) in Life Cycle Impact Assessment (LCIA).

Methods

As a first step, natural resources have been defined for the LCA context with reference to the overall UNEP/SETAC Life Cycle Impact Assessment (LCIA) framework. Second, existing LCIA methods have been reviewed and discussed. The reviewed methods have been evaluated according to the considered type of natural resources and their underlying principles followed (use-to-availability ratios, backup technology approaches, or thermodynamic accounting methods).

Results and discussion

There is currently no single LCIA method available that addresses impacts for all natural resource categories, nor do existing methods and models addressing different natural resource categories do so in a consistent way across categories. Exceptions are exergy and solar energy-related methods, which cover the widest range of resource categories. However, these methods do not link exergy consumption to changes in availability or provisioning capacity of a specific natural resource (e.g., mineral, water, land etc.). So far, there is no agreement in the scientific community on the most relevant type of future resource indicators (depletion, increased energy use or cost due to resource extraction, etc.). To address this challenge, a framework based on the concept of stock/fund/flow resources is proposed to identify, across natural resource categories, whether depletion/dissipation (of stocks and funds) or competition (for flows) is the main relevant aspect.

Conclusions

An LCIA method—or a set of methods—that consistently address all natural resource categories is needed in order to avoid burden shifting from the impact associated with one resource to the impact associated with another resource. This paper is an important basis for a step forward in the direction of consistently integrating the various natural resources as an Area of Protection into LCA.