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.     

Establishing Life Cycle Inventories of Chemicals Based on Differing Data Availability (9 pp)

Goal, Scope and Background In contrast to inventory data of energy and transport processes, public inventory data of chemicals are rather scarce. Chemicals are important to consider in LCA, because they are used in the production of many, if not all, products. Moreover, they may cause considerable environmental impacts. For these reasons, it was one goal of the new ecoinvent database to provide LCI data on chemicals. In this paper, the methods and procedures used for establishing LCIs of chemicals in ecoinvent are presented.Methods Three different approaches are suggested for situations of differing data availability. First, in the case of good data availability, the general quality guidelines of ecoinvent can be followed. Second, a procedure is proposed for the translation of aggregated inventory data (cumulative LCI results) from industry into the ecoinvent format. This approach was used, if adequate unit process data was not available. Third, a procedure is put forward for estimating inventory data using stoichiometric equations from technical literature as a main information source. This latter method was used if no other information was available. The application of each of the three procedures is illustrated with the help of a case study.Results and Conclusion When sufficient information is available to follow the general guidelines of ecoinvent, the resulting dataset is characterized by a high degree of detail, and it is thus of high quality. For chemicals, however, the application of the standard procedure is possible in only a few cases. When using industrial data, the main drawback is the fact that those data are often available only as aggregated data, thus being out of tune with the quality guidelines of ecoinvent and its main aim, the harmonization of LCI data. As a third approach, the use of the stoichiometric reaction equation is used for the compilation of LCI datasets of chemicals. This approach represents an alternative to neglecting chemicals completely, but it contains a high risk to not consider important aspects of the life cycle of the respective substance.Outlook Further work in the area of chemicals should focus on an improvement of datasets, so far established by either of the two estimation procedures (APME method; estimation based on technical literature) described. Besides the improvement of already established inventories, the compilation of further harmonized inventories of specific types of chemicals (e.g. solvents) or of chemicals for new industrial sectors (e.g. electronics industry) are in discussion.     

Ambiguities in decision-oriented Life Cycle Inventories The Role of mental models

If the complexity of real, socio-economic systems is acknowledged, life cycle inventory analysis (LCI) in life cycle assessment (LCA) cannot be considered as unambiguous, objective, and as an exclusively data and science based attribution of material and energy flows to a product. The paper thus suggests a set of criteria for LCI derived from different scientific disciplines, practice of product design and modelling characteristics of LCI and LCA. A product system with its respective LCI supporting the process of effective and efficient decision-making should ideally be: a) complete, operational, decomposable, non-redundant, minimal, and comparable; b) efficient, i.e., as simple, manageable, transparent, cheap, quick, but still as ‘adequate’ as possible under a functionalistic perspective which takes given economic constraints, material and market characteristics, and the goal and scope of the study into account; c) actor-based when reflecting the decision-makers’ action space, risk-level, values, and knowledge (i.e. mental model) in view of the management rules of sustainable development; d) as site- and case-specific as possible, i.e. uses as much site-specific information as possible. This rationale stresses the significance of considering both (i) material and energy flows within the technosphere with regard to the sustainable management rules; (ii) environmental consequences of the environmental interventions on ecosphere. Further, the marginal cost of collecting and computing more and better information about environmental impacts must not exceed the marginal benefits of information for the natural environment. The ratio of environmental benefits to the economic cost of the tool must be efficient compared to other investment options. As a conclusion, in comparative LCAs, the application of equal allocation procedures does not lead to LCA-results on which products made from different materials can be compared in an adequate way. Each product and material must be modelled according to its specific material and market characteristics as well as to its particular management rules for their sustainable use. A generic LCA-methodology including preferences on methodological options is not definable.     

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.     

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.     

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.     

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.     

Life Cycle Inventory of Particleboard: A Case Study in the Wood Sector (8 pp)

Goal, Scope and Background Wood has many applications and it is often in competition with other materials. Chipboard is the most common item of wood-based materials and it has attained the highest economical development in recent years. Relevant up-to-date environmental data are needed to allow the environmental comparison of wood with other materials. There are several examples of Life Cycle Assessment (LCA) evaluations of some wood products and forest-technology systems, but no comprehensive Life Cycle Inventory (LCI) data for particleboard manufacture is available in the literature. The main focus of this study is to generate a comprehensive LCI database for the manufacture of resin-bonded wood particleboards. Methods In this work, International Organization for Standardization (ISO) standards and Ecoindicator 99 methodology were considered to quantify the potential environmental impact associated to the system under study. A Spanish factory considered representative of the 'state of art' was studied in detail. The system boundaries included all the activities taking place inside the factory as well as the activities associated with 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. Results and Discussion LCI methodology was used for the quantification of the impacts of the particleboard manufacture. The inventory data of the three defined subsystems are described: - Wood preparation: a comprehensive inventory of data including storage, debarking, particle production, storage and measurement of particles, drying and combustion of the bark for energy purposes. - Board shaping: data related to particle classification, resin mixing, mattress formation and the pressing stage. - Board finishing: cooling data, finishing, storage and distribution of the final product. The system was characterised with Ecoindicator 99 methodology (hierarchic version) in order to identify the 'hot spots'. Damage to Human Health was mainly produced by the subsystem of Board finishing. The subsystem of Board shaping was the most significant contributor to damage to the Ecosystem Quality and Resources. Conclusions With the final aim of creating a database to identify and characterise the manufacture of particleboard, special attention was paid to the inventory analysis stage of the particleboard industry. A multicriteria approach was applied in order to define the most adequate use of wood wastes. Environmental, economic and social considerations strengthen the hypothesis that the use of forest residues in particleboard manufacture is more sustainable than their use as fuel. Recommendations and Outlook In this work, particleboard was the product analysed, as it is one of the most common wood-based materials. Future work will focus on the study of another key wood board: Medium Density Fibreboard (MDF). Moreover, factors with strong geographical dependence, such as the electricity profile and final transport of the product, will be analysed. In addition, the definition of widespread functional unit to study the use of wood wastes at the end-of-life stage may be another issue of outstanding interest.     

The effect of compact formulations on the environmental profile of Northern European granular laundry detergents Part II: Life Cycle assessment

The environmental profile of laundry detergents at three time points (1988, 1992, and 1998) were compared on the basis of two distinct, complementary approaches: Environmental Risk Assessment (ERA) and Life-Cycle Assessment (LCA). The results are presented in this paper and its accompanying paper in this issue (Part I: Product Environmental Risk Assessment). Life-Cycle Inventory (LCI) data from The Netherlands and Sweden were used for this retrospective analysis. The chosen time period studied (1988 - 1998) spans significant, multiple formulation and process change in laundry detergents, including the introduction of compact, then super-compact, granular detergents. Cradle-to-Gate LCAs based on 1 kg of finished product (from raw material supply to packaged finished product leaving the suppliers site) revealed no significant differences between the products themselves, as manufactured between 1988, 1992 and 1998. Cradle-to-Grave LCAs based on 1000 wash cycles (from raw material supply to disposal of used product) indicated that the consumption of raw materials and energy, as well as environmental emissions (air, water and solid waste), decreased after the introduction of compact detergents in 1988. The LCAs revealed that a number of category indicator values decreased (for acidification, aquatic toxicity greenhouse effects, eutrophication, toxicity, ozone depletion and smog). Furthermore, the results of the LCAs support the conclusion that the differences between The Netherlands and Sweden are due to (1) differences in electrical generation between the countries, (2) differences in energy consumption during consumer use, (3) differences in detergent dosage per wash and (4) differences in the wastewater treatment infrastructure.     

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

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

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.     

Efficient information visualization in LCA: Application and practice

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

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

Goal and Background  Geographical and technological differences in Life Cycle Inventory data are an important source for uncertainty in the result of Life Cycle Assessments. Knowledge on their impact on the result of an LCA is scarce, and also knowledge on how to manage them in an LCA case study. Objective  Goal of this paper is to explore these differences for municipal solid waste incinerator plants, and to develop recommendations for managing technological and geographical differences. Methodology  The paper provides a definition of technological and geographical differences, and analyses their possible impacts. In a case study, the differences are caused intentionally in ‘games’, by virtually transplanting incineration plants to a different location and by changing parameters such as the composition of the waste input incinerated. The games are performed by using a modular model for municipal solid waste incinerator plants. In each case, an LCA including an Impact Assessment is calculated to trace the impact of these changes, and the results are compared. Conclusions  The conclusions of the paper are two-fold: (1) reduce the differences in inventory data where their impact on the result is high; where it is possible reducing them to a great extent, and the effort for performing the change acceptable; in the case of incineration plants: Adapt the flue gas treatment, especially a possible DeNOx step, to the real conditions; (2) make use of modular process models that allow adapting plant parameters to better meet real conditions, but be aware of possible modelling errors. The paper invites the scientific community to validate the model used for a waste incinerator plant, and suggest putting up similar models for other processes, preferably those of similar relevance for Life Cycle Inventories.     

Evaluation of two simplified Life Cycle assessment methods

Goal, Scope and Background  Two methods of simplified LCA were evaluated and compared to the results of a quantitative LCA. These are the Environmentally responsible product assessment matrix developed by Graedel and Allenby and the MECO-method developed in Denmark. Methods  We used these in a case study and compared the results with the results from a quantitative LCA. The evaluation also included other criteria, such as the field of application and the level of arbitrariness. Results and Discussion  The MECO-method has some positive qualities compared to the Environmentally responsible product assessment matrix. Examples of this are that it generates information complementary to the quantitative LCA and provides the possibility to consider quantitative information when such is available. Some of the drawbacks with the Environmentally responsible product assessment matrix are that it does not include the whole lifecycle and that it allows some arbitrariness. Conclusions  Our study shows that a simplified and semi-quantitative LCA (such as the MECO-method) can provide information that is complementary to a quantitative LCA. In this case the method generates more information on toxic substances and other impacts, than the quantitative LCA. We suggest that a simplified LCA can be used both as a pre-study to a quantitative LCA and as a parallel assessment, which is used together with the quantitative LCA in the interpretation. Recommendations and Outlook  A general problem with qualitative analyses is how to compare different aspects. Life cycle assessments are comparative. The lack of a quantitative dimension hinders the comparison and can thereby hinder the usefulness of the qualitative method. There are different approaches suggested to semiquantify simplified methods in order to make quantitative comparisons possible. We think that the use of fabricated scoring systems should be avoided. If quantitative information is needed, one should consider performing a simplified quantitative LCA instead.     

Using monte carlo simulation in life cycle assessment for electric and internal combustion vehicles

1 Background

The U.S. Government has encouraged shifting from internal combustion engine vehicles (ICEVs) to alternatively fueled vehicles such as electric vehicles (EVs) for three primary reasons: reducing oil dependence, reducing greenhouse gas emissions, and reducing Clean Air Act criteria pollutant emissions. In comparing these vehicles, there is uncertainty and variability in emission factors and performance variables, which cause wide variation in reported outputs.

2 Objectives

A model was developed to demonstrate the use of Monte Carlo simulation to predict life cycle emissions and energy consumption differences between the ICEV versus the EV on a per kilometer (km) traveled basis. Three EV technologies are considered: lead-acid, nickel-cadmium, and nickel metal hydride batteries.

3 Methods

Variables were identified to build life cycle inventories between the EVs and ICEV. Distributions were selected for each of the variables and input to Monte Carlo Simulation soft-ware called Crystal Ball 2000®.

4 Results and Discussion

All three EV options reduce U.S. oil dependence by shifting to domestic coal. The life cycle energy consumption per kilometer (km) driven for the EVs is comparable to the ICEV; however, there is wide variation in predicted energy values. The model predicts that all three EV technologies will likely increase oxides of sulfur and nitrogen as well as particulate matter emissions on a per km driven basis. The model shows a high probability that volatile organic compounds and carbon monoxide emissions are reduced with the use of EVs. Lead emissions are also predicted to increase for lead-acid battery EVs. The EV will not reduce greenhouse gas emissions substantially and may even increase them based on the current U.S. reliance on coal for electricity generation. The EV may benefit public health by relocating air pollutants from urban centers, where traffic is concentrated, to rural areas where electricity generation and mining generally occur. The use of Monte Carlo simulation in life cycle analysis is demonstrated to be an effective tool to provide further insight on the likelihood of emission outputs and energy consumption.     

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.     

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.     

Life Cycle Inventory Information of the United States Electricity System (11/17 pp)

Goal and Scope This study estimates the life cycle inventory (LCI) of the electricity system in the United States, including the 10 NERC (North American Electric Reliability Council) regions, Alaska, Hawaii, off-grid non-utility plants and the US average figures. The greenhouse gas emissions associated with the United States electricity system are also estimated. Methods The fuel mix of the electricity system based on year 2000 data is used. The environmental burdens associated with raw material extraction, petroleum oil production and transportation for petroleum oil and natural gas to power plants are adopted from the DEAMTM LCA database. Coal transportation from a mining site to a power plant is specified with the data from the Energy Information Administration (EIA), which includes the mode of transportation as well as the distance traveled. The gate-to-gate environmental burdens associated with generating electricity from a fossil-fired power plant are obtained from the DEAMTM LCA database and the eGRID model developed by the United States Environmental Protection Agency. For nuclear power plants and hydroelectric power plants, the data from the DEAMTM LCA database are used.Results and Discussion Selected environmental profiles of the US electricity system are presented in the paper version, while the on-line version presents the whole LCI data. The overall US electricity system in the year 2000 released about 2,654 Tg CO2 eq. of greenhouse gas emissions based on 100-year global warming potentials with 193 g CO2 eq. MJe–1 as an weighted average emission rate per one MJ electricity generated. Most greenhouse gases are released during combusting fossil fuels, accounting for 78–95% of the total. The greenhouse gas emissions released from coal-fired power plants account for 81% of the total greenhouse gas emissions associated with electricity generation, and natural gas-fired power plants contribute about 16% of the total. The most significant regions for the total greenhouse gas emissions are the SERC (Southeastern Electric Reliability Council) and ECAR (East Central Area Reliability Coordination Agreement) regions, which account for 22% and 21% of the total, respectively. A sensitivity analysis on the generation and consumption based calculations indicates that the environmental profiles of electricity based on consumption are more uncertain than those based on generation unless exchange data from the same year are available because the exchange rates (region to region import and export of electricity) vary significantly from year to year.Conclusions and Outlook Those who are interested in the LCI data of the US electricity system can refer to the on-line version. When the inventory data presented in the on-line version are used in a life cycle assessment study, the distribution and transmission losses should be taken into account, which is about 9.5% of the net generation [1]. The comprehensive technical information presented in this study can be used in estimating the environmental burdens when new information on the regional fuel mix or the upstream processes is available. The exchange rates presented in this study also offer useful information in consequential LCI studies.