Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.     

A simple methodology for elaborating the life cycle inventory of agricultural products

Goal, Scope and Background  A methodological approach for representing agricultural products in terms of life cycle inventory is suggested in this paper. This approach was developed during the conduction of an LCA study for two perennial crops of important Brazilian exportation products: green coffee and orange juice, which included tillage cultivation by commercial farms, harvest, as well as product processing when pertinent. The published papers on agricultural products LCA usually discuss the final results in terms of LCIA, being not very clear what methodology or principles were applied on the LCI phase. The aim of this paper is to present a simple methodology that would be employed by different stakeholders as farmers, environment managers and decision makers for evaluating the environmental performance of their products. In recent years, many researchers have tried to make a worldwide effort in order to reach comparable results of LCA studies developed in different countries. So, the proposed methodology has also the aim of isolating the site-dependency of the results that are not strictly related to the agricultural production. The time coverage suggested is the period can be considered as an average for the specific tillage under evaluation, usually two crops, since there is a large variation on the inputs in every other crop, including the higher and subsequent lower productive periods. Method  The functional unit recommended is 1,000 kg of the specific product, being recommended to distinguish the energy used for the cultivation from that used by the processing stage. There are several specific considerations to transform the data collected through the questionnaires in an inventory data set of fertilizers (macro and micro nutrients), correctives, fillers and pesticides further detailed. Water used for chemicals preparation, in the cleaning and processing stages of the harvested crop is also considered. Land use refers to the area used land for cultivation divided by the medium life period of the tillage. The stoichiometric balance is performed based on the elementary composition of the products. An average carbohydrate formula is established for the products considering the relationship among the carbon, hydrogen and oxygen contents of them. The carbohydrate formula (output) is balanced with carbon dioxide and water (inputs) according to the basic principles of the photosynthesis reaction. The differences among the mineral composition of the products and the total content of these elements (N, P, K, Ca, Mg and micronutrients elements) for all the crop inputs (fertilizers, pesticides, correctives) are allocated as outputs of the system. The pesticides is counted in two forms: grouped in classes (herbicide, fungicide, acaricide, bactericide and inseticide) and specified by the chemical name of the active ingredient. Results and Discussion  A simplified inventory useful for different purposes is generated with the principles described in this paper. The exact fate of each pesticide, fertilizer or corrective or assumptions can be further associated to impact categories as nutriphication, human health, natural resources depletion, ecological toxicity, etc. In this approach the mass balance was focused in the grain or fruit growth and not in the plant or tree as a whole, considering basically the elementary composition of the product and the photosynthesis principle. Despite agricultural LCAs performed in different countries have been published, neither of them considers the carbon capture by the agricultural products during their growth. Conclusions  This method is based on well accepted universal principles of stoichiometry applied to the grain or fruit growth. Minimum estimations were introduced in this approach, which produces ‘clean inventories’, with comparable results between different studies. The generated inventory can be gradually improved as the understanding about each emission fate is known, producing a valid methodology for actual and future knowledge about the fate of tillage emissions. The inventory results of this method can be employed by different stakeholders as farmers, environment managers, decision makers and traders, with valuable environmental parameters for evaluating the environmental performance of their products and also for introducing improvements on their systems, without however to exhibit any particular data.     

Cradle-to-gate life cycle inventory and assessment of pharmaceutical compounds

Background, Goal and Scope  The research presented here represents one part of GlaxoSmithKline’s (GSK) efforts to identify and improve the life cycle impact profile of pharmaceutical products. The main goal of this work was to identify and analyze the cradle-to-gate environmental impacts in the synthesis of a typical Active Pharmaceutical Ingredient (API). A cradle-to-gate life cycle assessment of a commercial pharmaceutical product is presented as a case study. Methods  Life cycle inventory data were obtained using a modular gate-to-gate methodology developed in partnership with North Carolina State University (NCSU) while the impact assessment was performed utilizing GSK’s sustainability metrics methodology. Results and Discussion  Major contributors to the environmental footprint of a typical pharmaceutical product were identified. The results of this study indicate that solvent use accounts for a majority of the potential cradle-to-gate impacts associated with the manufacture of the commercial pharmaceutical product under study. If spent solvent is incinerated instead of recovered the life-cycle profile and impacts are considerably increased. Conclusions  This case study provided GSK with key insights into the life-cycle impacts of pharmaceutical products. It also helped to establish a well-documented approach to using life cycle within GSK and fostered the development of a practical methodology that is applicable to strategic decision making, internal business processes and other processes and tools.     

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。     

Life cycle inventory of medium density fibreboard

Goal, Scope and Background Wood is the most important renewable material. The management of wood appears to be a key action to optimise the use of resources and to reduce the environmental impact associated with mankind’s activities. Wood-based products must be analysed considering the two-fold nature of wood, commonly used as a renewable material or regenerative fuel. Relevant, up-to-date environmental data are needed to allow the analysis of wood-based products. The main focus of this study is to provide comprehensive data of one key wood board industry such as the Medium Density Fibreboard (MDF). Moreover, the influence of factors with strong geographical dependence, such as the electricity profile and final transport of the product, is analysed. In this work, International Organization for Standardization standards (ISO 14040-43) and Ecoindicator 99 methodology have been considered to quantify the potential environmental impact associated to the system under study. Three factories, considered representative of the ‘state of art’, were selected to study the process in detail: two Spanish factories and a Chilean one, with a process production of around 150,000 m³ per year. The system boundaries included all the activities taking place into the factory as well as the activities linked to the production of the main chemicals used in the process, energy inputs and transport. All the data related to the inputs and outputs of the process were obtained by on-site measurements during a one-year period. A sensitive analysis was carried out taking into account the influence of the final transport of the product and the dependence on the electricity generation profile. Life Cycle Inventory Analysis LCI methodology has been used for the quantification of the impacts of the MDF manufacture. The process chain can be subdivided in three main subsystems: wood preparation, board shaping and board finishing. The final transport of the product was studied as a different subsystem, considering scenarios from local to transoceanic distribution and three scenarios of electricity generation profile were assessed. The system was characterised with Ecoindicator 99 methodology (hierarchic version) in order to identify the ‘hot spots’. Damage to Human Health, Ecosystem Quality and Resources are mainly produced by the subsystem of Wood Preparation (91.1%, 94.8% and 94.1%, respectively). The contribution of the subsystem of Board Finishing is considerably lower, but also significant, standing for the 5.8% of the damage to HH and 5.5% of the damage to Resources. Condusions With the final aim of creating a database of wood board manufacture, this work was focused in the identification and characterisation of one of the most important wood-based products: Medium Density Fibreboard. Special attention has been paid in the inventory analysis stage of the MDF industry. The results of the sensitive analysis showed a significant influence of both the final transport of the product and the electricity generation profile. Thus, the location of MDF process is of paramount importance, as both aspects have considerable site-dependence. Recommendations and Perspectives Research continues to be conducted to identify the environmental burdens associated to the materials of extended use. In this sense, future work can be focused on the comparison of different materials for specific applications.     

Life cycle assessment of emerging technologies at the lab scale: The case of nanowire‐based solar cells

Nanomaterials are expected to play an important role in the development of sustainable products. The use of nanomaterials in solar cells has the potential to increase their conversion efficiency. In this study, we performed a life cycle assessment (LCA) for an emerging nanowire‐based solar technology. Two lab‐scale manufacturing routes for the production of nanowire‐based solar cells have been compared—the direct growth of GaInP nanowires on silicon substrate and the growth of InP nanowires on native substrate, peel off, and transfer to silicon substrate. The analysis revealed critical raw materials and processes of the current lab‐scale manufacturing routes such as the use of trifluoromethane (CHF₃), gold, and an InP wafer and a stamp, which are used and discarded. The environmental performance of the two production routes under different scenarios has been assessed. The scenarios include the use of an alternative process to reduce the gold requirements—electroplating instead of metallization, recovery of gold, and reuse of the InP wafer and the stamp. A number of suggestions, based on the LCA results—including minimization of the use of gold and further exploration for upscaling of the electroplating process, the increase in the lifetimes of the wafer and the stamp, and the use of fluorine‐free etching materials—have been communicated to the researchers in order to improve the environmental performance of the technology. Finally, the usefulness and limitations of lab‐scale LCA as a tool to guide the sustainable development of emerging technologies are discussed.     

生命周期管理研究述评

生命周期管理起源于生命周期思想,它是生命周期思想在实践中的具体应用,是面向可持续生产和消费,对产品、工艺和服务的全生命周期环境影响进行的综合管理,是解决复合生态系统中结构无序、效率不高和代谢冗余的有效途径,是基于生命周期评价原则与框架的一种环境管理手段或环境管理体系。全面回顾了生命周期管理的起源与内涵,阐述了生命周期管理与生命周期评价的区别与联系,梳理了生命周期管理与环境管理体系的关系。对生命周期管理在产品、企业、行业及城市等层次上的具体应用进行了总结与述评,并对其今后需深入研究的方向进行了展望。     

Uncertainty calculation in life cycle assessments

Goal and Background  Uncertainty is commonly not taken into account in LCA studies, which downgrades their usability for decision support. One often stated reason is a lack of method. The aim of this paper is to develop a method for calculating the uncertainty propagation in LCAs in a fast and reliable manner. Approach  The method is developed in a model that reflects the calculation of an LCA. For calculating the uncertainty, the model combines approximation formulas and Monte Carlo Simulation. It is based on virtual data that distinguishes true values and random errors or uncertainty, and that hence allows one to compare the performance of error propagation formulas and simulation results. The model is developed for a linear chain of processes, but extensions for covering also branched and looped product systems are made and described. Results  The paper proposes a combined use of approximation formulas and Monte Carlo simulation for calculating uncertainty in LCAs, developed primarily for the sequential approach. During the calculation, a parameter observation controls the performance of the approximation formulas. Quantitative threshold values are given in the paper. The combination thus transcends drawbacks of simulation and approximation. Conclusions and Outlook  The uncertainty question is a true jigsaw puzzle for LCAs and the method presented in this paper may serve as one piece in solving it. It may thus foster a sound use of uncertainty assessment in LCAs. Analysing a proper management of the input uncertainty, taking into account suitable sampling and estimation techniques; using the approach for real case studies, implementing it in LCA software for automatically applying the proposed combined uncertainty model and, on the other hand, investigating about how people do decide, and should decide, when their decision relies on explicitly uncertain LCA outcomes-these all are neighbouring puzzle pieces inviting to further work.     

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.     

Framework for modelling data uncertainty in life cycle inventories

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

Life cycle inventory for electricity generation in China

Background, Goal and Scope The objective of this study was to produce detailed a life cycle inventory (LCI) for the provision of 1 kWh of electricity to consumers in China in 2002 in order to identify areas of improvement in the industry. The system boundaries were processes in power stations, and the construction and operation of infrastructure were not included. The scope of this study was the consumption of fossil fuels and the emissions of air pollutants, water pollutants and solid wastes, which are listed as follows: (1) consumption of fossil fuels, including general fuels, such as raw coal, crude oil and natural gas, and the uranium used for nuclear power; (2) emissions of air pollutants from thermal power, hydropower and nuclear power plants; (3) emissions of water pollutants, including general water waste from fuel electric plants and radioactive waste fluid from nuclear power plants; (4) emissions of solid wastes, including fly ash and slag from thermal power plants and radioactive solid wastes from nuclear power plants. Methods Data were collected regarding the amount of fuel, properties of fuel and the technical parameters of the power plants. The emissions of CO₂, SO₂, NO_x, CH₄, CO, non-methane volatile organic compound (NMVOC), dust and heavy metals (As, Cd, Cr, Hg, Ni, Pb, V, Zn) from thermal power plants as well as fuel production and distribution were estimated. The emissions of CO₂ and CH₄ from hydropower plants and radioactive emissions from nuclear power plants were also investigated. Finally, the life cycle inventory for China’s electricity industry was calculated and analyzed. Results Related to 1 kWh of usable electricity in China in 2002, the consumption of coal, oil, gas and enriched uranium were 4.57E-01, 8.88E-03, 7.95E-03 and 9.03E-08 kg; the emissions of CO₂, SO₂, NO_x, CO, CH₄, NMVOC, dust, As, Cd, Cr, Hg, Ni, Pb, V, and Zn were 8.77E-01, 8.04E-03, 5.23E-03, 1.25E-03, 2.65E-03, 3.95E-04, 1.63E-02, 1.62E-06, 1.03E-08, 1.37E-07, 7.11E-08, 2.03E-07, 1.42E-06, 2.33E-06, and 1.94E-06 kg; the emissions of waste water, COD, coal fly ash, and slag were 1.31, 6.02E-05, 8.34E-02, and 1.87E-02 kg; and the emissions of inactive gas, halogen and gasoloid, tritium, non-tritium, and radioactive solid waste were 3.74E+01 Bq, 1.61E-01 Bq, 4.22E+01 Bq, 4.06E-02 Bq, and 2.68E-10 m³ respectively. Conclusions The comparison result between the LCI data of China’s electricity industry and that of Japan showed that most emission intensities of China’s electricity industry were higher than that of Japan except for NMVOC. Compared with emission intensities of the electricity industry in Japan, the emission intensities of CO₂ and Ni in China were about double; the emission intensities of NO_x, Cd, CO, Cr, Hg and SO₂ in China were more than 10 times that of Japan; and the emission intensities of CH₄, V, Pb, Zn, As and dust were more than 20 times. The reasons for such disparities were also analyzed. Recommendations and Perspectives To get better LCI for the electricity industry in China, it is important to estimate the life cycle emissions during fuel production and transportation for China. Another future improvement could be the development of LCIs for construction and operation of infrastructure such as factory buildings and dams. It would also be important to add the information about land use for hydropower.     

Driving forces for data exchange

The subgroup ‘Driving Forces for Data Exchange’ as part of the SETAC LCA Workgroup on Data Availability and Quality is finishing its final report with recommendations and guidelines to stimulate availability and exchange of LCI data. Activities in the past three years involved a literature review, interviews with LCI data publishers and stakeholder discussions. The final report will be part of a SETAC ‘Code of Life Cycle Inventory Practice’, dealing with LCI data availability and quality aspects in a broader sense.     

Life Cycle Assessment Software: Selection Can Impact Results

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

Implementing a Dynamic Life Cycle Assessment Methodology with a Case Study on Domestic Hot Water Production

This work contributes to the development of a dynamic life cycle assessment (DLCA) methodology by providing a methodological framework to link a dynamic system modeling method with a time‐dependent impact assessment method. This three‐step methodology starts by modeling systems where flows are described by temporal distributions. Then, a temporally differentiated life cycle inventory (TDLCI) is calculated to present the environmental exchanges through time. Finally, time‐dependent characterization factors are applied to the TDLCI to evaluate climate‐change impacts through time. The implementation of this new framework is illustrated by comparing systems producing domestic hot water (DHW) over an 80‐year period. Electricity is used to heat water in the first system, whereas the second system uses a combination of solar energy and gas to heat an equivalent amount of DHW at the same temperature. This comparison shows that using a different temporal precision (i.e., monthly vs. annual) to describe process flows can reverse conclusions regarding which case has the best environmental performance. Results also show that considering the timing of greenhouse gas (GHG) emissions reduces the absolute values of carbon footprint in the short‐term when compared with results from the static life cycle assessment. This pragmatic framework for the implementation of time in DLCA studies is proposed to help in the development of the methodology. It is not yet a fully operational scheme, and efforts are still required before DLCA can become state of practice.     

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.     

Comparative Environmental Life Cycle Assessment of Conventional and Electric Vehicles

Electric vehicles (EVs) coupled with low‐carbon electricity sources offer the potential for reducing greenhouse gas emissions and exposure to tailpipe emissions from personal transportation. In considering these benefits, it is important to address concerns of problem‐shifting. In addition, while many studies have focused on the use phase in comparing transportation options, vehicle production is also significant when comparing conventional and EVs. We develop and provide a transparent life cycle inventory of conventional and electric vehicles and apply our inventory to assess conventional and EVs over a range of impact categories. We find that EVs powered by the present European electricity mix offer a 10% to 24% decrease in global warming potential (GWP) relative to conventional diesel or gasoline vehicles assuming lifetimes of 150,000 km. However, EVs exhibit the potential for significant increases in human toxicity, freshwater eco‐toxicity, freshwater eutrophication, and metal depletion impacts, largely emanating from the vehicle supply chain. Results are sensitive to assumptions regarding electricity source, use phase energy consumption, vehicle lifetime, and battery replacement schedules. Because production impacts are more significant for EVs than conventional vehicles, assuming a vehicle lifetime of 200,000 km exaggerates the GWP benefits of EVs to 27% to 29% relative to gasoline vehicles or 17% to 20% relative to diesel. An assumption of 100,000 km decreases the benefit of EVs to 9% to 14% with respect to gasoline vehicles and results in impacts indistinguishable from those of a diesel vehicle. Improving the environmental profile of EVs requires engagement around reducing vehicle production supply chain impacts and promoting clean electricity sources in decision making regarding electricity infrastructure.     

Comparative LCA of industrial objects

Goal, Scope and Background  This paper is the second part of the publication which is devoted to comparative LCA analysis of the industrial pumps. The previous paper deals with the methodological aspects concerning quality assessment and forms an independent work. This paper uses practically only the methodological suggestions made there. The main aim of the presented study is to make a comparison between the industrial pumps which are based on two different technologies. The Life Cycle Assessment method is used to check whether the differences of the manufacturing processes influence the level of the potential environmental impact during the whole life cycle of the analysed products. Methods  The Life Cycle Assessment is carried out using the Ecoindicator99 method. Additionally, an extensive quality analysis of the LCA study is made (Part I). To make the process of an identification of the data easier and faster, they are assigned to a special data documentation form. To ensure the credibility of the LCA results different methods of interpretation are used. Results and Discussion  The LCA analysis shows clear superiority of the pumps manufactured using modern technology. It seems that this superiority results not only from the differences in the emissions, but also from different characteristics of effectiveness in the usage stage. Thanks to the uncertainty analysis, each LCA result is provided with the range of uncertainty. Conclusions  The LCA results are supported by different techniques of interpretation: the sensitivity-, the contribution-, the comparative-, the discernability- and the uncertainty analysis. There is strong evidence of the superiority of the pumps based on the modern technology. Recommendations and Outlook  The main source of the environmental impact in the case of pumps is the usage stage and the consumption of energy. That is why it should be the main area to improve. The LCA results show that actions taken in the usage stage and energy consumption can lead to a considerable reduction of the environmental impacts.     

Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The model is based on a process‐level approach, accounting for all significant materials by their transformation processes (aluminum castings, polyethylene blow molding; etc.) and plant operation activities (painting; heating, ventilation, and air conditioning [HVAC], etc.) germane to VMA. Using quantitative results for these material/transformation process pairings, a percent‐by‐weight material/transformation distribution (MTD) function was developed that permits the model to be applied to a range of vehicles, both conventional and advanced (e.g., hybrid electric, light weight, aluminum intensive). Upon consolidation of all inputs, the model reduces to two terms: one proportional to vehicle mass and a plant overhead per vehicle term. When the model is applied to a materially well‐characterized conventional vehicle, reliable estimates of cumulative energy consumption (34 gigajoules/vehicle) and carbon dioxide (CO₂) emissions (2 tonnes/vehicle) with coefficients of variation are computed for the VMA life cycle stage. Due to the more comprehensive coverage of manufacturing operations, our energy estimates are on the higher end of previously published values. Nonetheless, they are still somewhat underestimated due to a lack of data on overhead operations in part manufacturing facilities and transportation of parts and materials between suppliers and vehicle manufacturing operations. For advanced vehicles, the material/transformation process distribution developed above needs some adjusting for different materials and components. Overall, energy use and CO₂ emissions from the VMA stage are about 3.5% to 4.5% of total life cycle values for vehicles.     

Economic Allocation in Life Cycle Assessment

This article examines methods for analyzing allocation in life cycle assessment (LCA); it focuses on comparisons of economic allocation with other feasible alternatives. The International Organization for Standardization's (ISO) guideline 14044 indicates that economic allocation should only be used as a last resort, when other methods are not suitable. However, the LCA literature reports several examples of the use of economic allocation. This is due partly to its simplicity and partly to its ability to illustrate the properties of complex systems. Sometimes a price summarizes complex attributes of product or service quality that cannot be easily measured by physical criteria. On the other hand, economic allocation does have limitations arising, for example, from the variability of prices and the low correlation between prices and physical flows. This article presents the state of the debate on the topic and some hypothetical examples for illustration. A general conclusion is that it is not possible to determine one “best” allocation method. The allocation procedure has to be selected on a case‐by‐case basis and no single approach is suitable for every situation. Despite its limitations, economic allocation has certain qualities that make it flexible and potentially suitable for different contexts. In some situations, economic allocation should not be the last methodological resort. The option of economic allocation should be considered, for example, whenever the prices of coproducts and coservices differ widely.