Bo Pedersen Weidema

System Boundaries and Input Data in Consequential Life Cycle Inventory Analysis

Goal, Scope and BackgroundA consequential life cycle assessment (LCA) is designed to generate information on the consequences of decisions. This paper includes a comprehensive presentation of the consequential approach to system boundaries, allocation and data selection. It is based on a text produced within the SETAC-Europe working group on scenarios in LCA. For most of the methodological problems, we describe ideal methodological solutions as well as simplifications intended to make the method feasible in practice.MethodWe compile, summarize and refine descriptions of consequential methodology elements that have been presented in separate papers, in addition to methodological elements and general conclusions that have not previously been published.Results and ConclusionsA consequential LCA ideally includes activities within and outside the life cycle that are affected by a change within the life cycle of the product under investigation. In many cases this implies the use of marginal data and that allocation is typically avoided through system expansion. The model resulting from a consequential life cycle inventory (LCI) also includes the alternative use of constrained production factors as well as the marginal supply and demand on affected markets. As a result, the consequential LCI model does not resemble the traditional LCI model, where the main material flows are described from raw material extraction to waste management. Instead, it is a model of causal relationships originating at the decision at hand or the decision-maker that the LCI is intended to inform.

Data quality management for life cycle inventories - An example of using data quality indicators

Abstract A formal procedure for data quality management in life cycle inventory is described. The procedure is applied to the example of an energy inventory for 1 kg rye bread. Five independent data quality indicators are suggested as necessary and sufficient to describe those aspects of data quality which influence the reliability of the result. Listing these data quality indicators for all data gives an improved understanding of the typical data quality problems of a particular study. This may subsequently be used for improving the data collection strategy during a life cycle study. To give an assessment of the reliability of the overall result of a life cycle inventory, the data quality indicators are transformed into estimates of the additional uncertainty due to the insufficient data quality. It is shown how a low data quality can both increase the uncertainty and change the mean value. After assigning additional uncertainties to all data in the study, a calculation of the uncertainty of the overall result is made by the use of simulations. The use of default estimates of additional uncertainties is suggested as a way to both simplify and improve the procedure.

Avoiding Co-Product Allocation in Life-Cycle Assessment

Abstract: In a life-cycle assessment (LCA) involving only one of several products from the same process, how are the resource consumption and the emissions associated with this process to be partitioned and distributed over these co-products? This is the central question in co-product allocation, which has been one of the most controversial issues in the development of the methodology for life-cycle assessment, as it may significantly influence or even determine the result of the assessments. In this article, it is shown that in prospective life-cycle assessments, co-product allocation can always be avoided by system expansion. Through a number of examples, it is demonstrated how system expansion is performed, with special emphasis on issues that earlier have been a focus of the allocation debate, such as joint production (e.g., of chlorine and sodium hydroxide, zinc and heavy metals, and electricity and heat), the handling of “near-to-waste” by-products, processes simultaneously supplying services to multiple product systems, and credits for material recycling and downcycling. It is shown that all the different co-product situations can be covered by the same theoretical model and the same practical procedure, and that it is also possible to include the traditional co-product allocation as a special case of the presented procedure. The uncertainty aspects of the presented procedure are discussed. A comparison is made with the procedure of ISO 14041, “Life-cycle assessment—Goal and scope definition and inventory analysis,” the international standard.

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

PurposeGood 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.MethodsModeling 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 discussionIn 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.ConclusionsWith 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.

The LCIA midpoint-damage framework of the UNEP/SETAC life cycle initiative

Background, Aims and ScopeLife Cycle Impact Assessment (LCIA) methods can be grouped into two families: classical methods determining impact category indicators at an intermediate position of the impact pathways (e.g. ozone depletion potentials) and damage-oriented methods aiming at more easily interpretable results in the form of damage indicators at the level of the ultimate societal concern (e.g. human health damage). The Life Cycle Initiative, a joint project between UNEP1 and SETAC2, proposes a comprehensive LCA framework to combine these families of methods. The new framework takes a world-wide perspective, so that LCA will progress towards a tool meeting the needs of both developing and developed countries. By a more precise and broadly agreed description of main framework elements, the Life Cycle Initiative expects to provide a common basis for the further development of mutually consistent impact assessment methods.Main FeaturesInputs to the LCIA midpoint-damage framework are results of Life Cycle Inventory analyses (LCI). Impact pathways connect the LCI results to the midpoint impact categories with the corresponding indicators, as well as to the damage categories at the level of damages to human health, natural environment, natural resources and man-made environment, via damage indicators. Mid-point impact categories simplify the quantification of these impact pathways where various types of emissions or extractions can be aggregated due to their comparable impact mechanisms. Depending on the available scientific information, impact pathways may be further described up to the level of damage categories by quantitative models, observed pathways or merely by qualitative statements. In the latter case, quantitative modelling may stop at mid-point. A given type of emission may exert damaging effects on multiple damage categories, so that a corresponding number of impact pathways is required. Correspondingly, a given damage category may be affected jointly by various types of emissions or extractions. It is therefore an important task of the Life Cycle Initiative to carefully select damage indicators. The content of the midpoint and of the damage categories is clearly defined, and proposals are made on how to express the extent of environmental damage by suitable indicator quantities.Conclusions and OutlookThe present framework will offer the practitioner the choice to use either midpoint or damage indicators, depending on modelling uncertainty and increase in results interpretability. Due to the collaboration of acknowledged specialists in environmental processes and LCIA around the globe, it is expected that - after a few years of effort - the task forces of the Life Cycle Initiative will provide consistent and operational sets of methods and factors for LCIA in the future.

Marginal production technologies for life cycle inventories

Marginal technologies are defined as the technologies actually affected by the small changes in demand typically studied in prospective, comparative life cycle assessments. Using data on marginal technologies thus give the best reflection of the actual consequences of a decision. Furthermore, data on marginal technologies are easier to collect, more precise, and more stable in time than data on average technologies. A 5-step procedure is suggested to identify the marginal technologies. The step-wise procedure first clarifies the situation in which the marginal should apply, and then identifies what specific technology is marginal in this situation. The procedure is illustrated in two examples: European electricity production and pulp and paper production.

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.

Key issues and options in accounting for carbon sequestration and temporary storage in life cycle assessment and carbon footprinting

PurposeBiological sequestration can increase the carbon stocks of non-atmospheric reservoirs (e.g. land and land-based products). Since this contained carbon is sequestered from, and retained outside, the atmosphere for a period of time, the concentration of CO2 in the atmosphere is temporarily reduced and some radiative forcing is avoided. Carbon removal from the atmosphere and storage in the biosphere or anthroposphere, therefore, has the potential to mitigate climate change, even if the carbon storage and associated benefits might be temporary. Life cycle assessment (LCA) and carbon footprinting (CF) are increasingly popular tools for the environmental assessment of products, that take into account their entire life cycle. There have been significant efforts to develop robust methods to account for the benefits, if any, of sequestration and temporary storage and release of biogenic carbon. However, there is still no overall consensus on the most appropriate ways of considering and quantifying it.MethodThis paper reviews and discusses six available methods for accounting for the potential climate impacts of carbon sequestration and temporary storage or release of biogenic carbon in LCA and CF. Several viewpoints and approaches are presented in a structured manner to help decision-makers in their selection of an option from competing approaches for dealing with timing issues, including delayed emissions of fossil carbon.ResultsKey issues identified are that the benefits of temporary carbon removals depend on the time horizon adopted when assessing climate change impacts and are therefore not purely science-based but include value judgments. We therefore did not recommend a preferred option out of the six alternatives presented here.ConclusionsFurther work is needed to combine aspects of scientific and socio-economic understanding with value judgements and ethical considerations.

C balance, carbon dioxide emissions and global warming potentials in LCA-modelling of waste management systems

Global warming potential (GWP) is an important impact category in life-cycle-assessment modelling of waste management systems. However, accounting of biogenic CO2 emissions and sequestered biogenic carbon in landfills and in soils, amended with compost, is carried out in different ways in reported studies. A simplified model of carbon flows is presented for the waste management system and the surrounding industries, represented by the pulp and paper manufacturing industry, the forestry industry and the energy industry. The model calculated the load of C to the atmosphere, under ideal conditions, for 14 different waste management scenarios under a range of system boundary conditions and a constant consumption of C-product (here assumed to be paper) and energy production within the combined system. Five sets of criteria for assigning GWP indices to waste management systems were applied to the same 14 scenarios and tested for their ability to rank the waste management alternatives reflecting the resulting CO2 load to the atmosphere. Two complete criteria sets were identified yielding fully consistent results; one set considers biogenic CO2 as neutral, the other one did not. The results showed that criteria for assigning global warming contributions are partly linked to the system boundary conditions. While the boundary to the paper industry and the energy industry usually is specified in LCA studies, the boundary to the forestry industry and the interaction between forestry and the energy industry should also be specified and accounted for.

Environmental improvement potentials of meat and dairy products

The report is a scientific contribution to the European Commissions Integrated Product Policy framework, which seeks to minimise the environmental degradation caused throughout the life cycle of products. This report first presents a systematic overview of the life cycle of meat and dairy products and their environmental impacts, covering the full food chain. It goes on to provide a comprehensive analysis of the improvement options that allow reducing the environmental impacts throughout the life cycle. Finally, the report assesses the different options regarding their feasibility as well as their potential environmental and socioeconomic benefits and costs. The report shows that meat and dairy products contribute on average 24% to the environmental impacts from the total final consumption in EU-27, while constituting only 6% of the economic value. The main improvement options were identified in agricultural production, in food management by households (avoidance of food wastage), and related to power savings. When all environmental improvement potentials are taken together, the aggregated environmental impacts (external costs) of meat and dairy products may be reduced by about 20%. How to obtain EU publications Our priced publications are available from EU Bookshop (http://bookshop.europa.eu), where you can place an order with the sales agent of your choice. The Publications Office has a worldwide network of sales agents. You can obtain their contact details by sending a fax to (352) 29 29-42758.