• Energy Research

Life Cycle Assessment is a tool to assess the environmental impacts and resources used throughout a product's life cycle, i.e., from raw material acquisition, via production and use phases, to waste management. The methodological development in LCA has been strong, and LCA is broadly applied in practice. The aim of this paper is to provide a review of recent developments of LCA methods. The focus is on some areas where there has been an intense methodological development during the last years. We also highlight some of the emerging issues. In relation to the Goal and Scope definition we especially discuss the distinction between attributional and consequential LCA. For the Inventory Analysis, this distinction is relevant when discussing system boundaries, data collection, and allocation. Also highlighted are developments concerning databases and Input-Output and hybrid LCA. In the sections on Life Cycle Impact Assessment we discuss the characteristics of the modelling as well as some recent developments for specific impact categories and weighting. In relation to the Interpretation the focus is on uncertainty analysis. Finally, we discuss recent developments in relation to some of the strengths and weaknesses of LCA.

Three mutually dependent elements are required for the application of life cycle assessment: methodology, data and software. Obviously, the design of software is determined by the methodology and the type of data available. Conversely, the development of software dictates the way in which data should be collected and recorded, and improves the theoretical framework, as it forces one to state the principles clearly and unambiguously. The influence of the development of software on both data and methodology is addressed and illustrated by examples, with reference to two key terms: transparency and explicitness. Three types of influence are distinguished: the design of a protocol, the formulation in terms of recipes, and the presentation of data.

A key source of uncertainty in the environmental assessment of emerging technologies is the unpredictable manufacturing, use, and end-of-life pathways a technology can take as it progresses from lab to industrial scale. This uncertainty has sometimes been addressed in life cycle assessment (LCA) by performing scenario analysis. However, the scenario-based approach can be misleading if the probabilities of occurrence of each scenario are not incorporated. It also brings about a practical problem; considering all possible pathways, the number of scenarios can quickly become unmanageable. We present a modelling approach in which all possible pathways are modelled as a single product system with uncertain processes. These processes may or may not be selected once the technology reaches industrial scale according to given probabilities. An uncertainty analysis of such a system provides a single probability distribution for each impact score. This distribution accounts for uncertainty about the product system's final configuration along with other sources of uncertainty. Furthermore, a global sensitivity analysis can identify whether the future selection of certain pathways over others will be of importance for the variance of the impact score. We illustrate the method with a case study of an emerging technology for front-side metallization of photovoltaic cells.

Purpose: The increasing concern for adverse effects of climate change has spurred the search for alternatives for conventional energy sources. Life cycle assessment (LCA) has increasingly been used to assess the potential of these alternatives to reduce greenhouse gas emissions. The popularity of LCA in the policy context puts its methodological issues into another perspective. This paper discusses how bio-electricity directives deal with the issue of allocation and shows its repercussions in the policy field. Methods: Multifunctionality has been a well-known problem since the early development of LCA and several methods have been suggested to deal with multifunctional processes. This paper starts with a discussion of the most common allocation methods. This discussion is followed by a description of bio-energy policy directives. The description shows the increasing importance of LCA in the policy context as well as the lack of consensus in the application of allocation methods. Methodological differences between bio-energy directives possibly lead to different assessments of bio-energy chains. To assess the differences due to methodological choices in bio-energy directives, this paper applies three different allocation methods to the same bio-electricity generation system. The differences in outcomes indicate the importance of solving the allocation issue for policy decision making. Results and discussion: The case study focuses on bio-electricity from rapeseed oil. To assess the influence of the choice of allocation in a policy directive, three allocation methods are applied: economic partitioning (on the basis of proceeds), physical partitioning (on the basis of energy content), and substitution (under two scenarios). The outcomes show that the climate change score is assessed quite differently; ranging from 0.293 kg to 0.604 kg CO 2 eq/kWh. It is argued that this uncertainty hampers the optimal use of LCA in the policy context. The aim of policy LCAs is different from the aim of LCAs for analysis. Therefore, it is argued that LCAs in the policy context will benefit from a new guideline based on robustness. Conclusions: The case study confirms that the choice of allocation method in policy directives has large influence on the outcomes of an LCA. With the growing popularity of LCA in policy directives, this paper recommends a new guideline for policy LCAs. The high priority of robustness in the policy context makes it an ideal starting point of this guideline. An accompanying dialog between practitioners and commissioners should further strengthen the use of LCA in policy directives.

Environmental life cycle assessment (LCA) has developed fast over the last three decades. Whereas LCA developed from merely energy analysis to a comprehensive environmental burden analysis in the 1970s, full-fledged life cycle impact assessment and life cycle costing models were introduced in the 1980s and 1990 s, and social-LCA and particularly consequential LCA gained ground in the first decade of the 21st century. Many of the more recent developments were initiated to broaden traditional environmental LCA to a more comprehensive Life Cycle Sustainability Analysis (LCSA). Recently, a framework for LCSA was suggested linking life cycle sustainability questions to knowledge needed for addressing them, identifying available knowledge and related models, knowledge gaps, and defining research programs to fill these gaps. LCA is evolving into LCSA, which is a transdisciplinary integration framework of models rather than a model in itself. LCSA works with a plethora of disciplinary models and guides selecting the proper ones, given a specific sustainability question. Structuring, selecting, and making the plethora of disciplinary models practically available in relation to different types of life cycle sustainability questions is the main challenge.

Background, aim, and scope: The expectations with respect to biomass as a resource for sustainable energy are sky-high. Many industrialized countries have adopted ambitious policy targets and have introduced financial measures to stimulate the production or use of bioenergy. Meanwhile, the side-effects and associated risks have been pointed out as well. To be able to make a well-informed decision, the Dutch government has expressed the intention to include sustainability criteria into relevant policy instruments. Main features: Among other criteria, it has been proposed to calculate a so-called life-cycle-based greenhouse gas (GHG) indicator, which expresses the reduction of GHG emissions of a bio-based fuel chain in comparison with a fossil-based fuel chain. Life-cycle-based biofuel studies persistently have problems with the handling of biogenic carbon balances and with the treatment of coproducts and recycling. In life-cycle assessments (LCAs) of agricultural products, a distinction between "negative" and "positive" emissions may be relevant. In particular, carbon dioxide, as a naturally occurring compound or an anthropogenic emission, takes part in the so-called geochemical carbon cycle. The most appropriate way to treat carbon cycles is to view them as genuine cycles and, thus, at the systems level, subtract the fixation of CO 2 during tree growth from the CO2 emitted during waste treatment of discarded wood and to quantify the CH4 emitted. In solving the multifunctionality problem, two steps may be distinguished. The first concerns the modeling of the product system studied in the inventory analysis. In this step, system boundaries are set, processes are described, and process flows are quantified. Multifunctionality problems can be identified and the model of the product system is drafted. The second step concerns solving the remaining multifunctionality problems. For this step, various ways of solving the multifunctionality problem have been proposed and applied, on the basis of mass, energy, economic value, avoided burdens, etc. As the GHG indicator may constitute the basis for granting subsidies to stimulate the use of bioenergy, for example, and as the method for the GHG indicator provides no guidelines on the handling of biogenic CO2 and guidelines for solving multifunctionality problems such as with coproducts and recycling that leave room for various choices, this study analyzed whether the current GHG indicator provides results that are a robust basis for granting such subsidies. Results: For the robustness check, a hypothetical case study on wood residue-based electricity was set up in order to illustrate what the effects of different solutions and choices for the two steps mentioned may be. The case dealt with the production of wood pellets (residues of the wood industry) that are cofired in a coal-fired power plant. The functional unit is 1 kWh of electricity. Three possibilities for the places of the multifunctional process, two possibilities for whether or not to include biogenic CO2, and four possibilities for the allocation method were distinguished and calculated. Varying the options for these three choices in this way appears to have a huge effect on the GHG indicator, while no clear pattern seems to emerge. Discussion: The results found for this hypothetical case indicate that there are several methodological choices that have not sufficiently been fixed by the presently available standards and guidelines for LCA and GHG assessment of bioenergy systems. In particular, we have focused on issues related to biogenic CO2 and allocation, two issues that play a prominent role in the assessment of bioenergy systems. Moreover, we have demonstrated with a small hypothetical case study that these are not only issues that might theoretically show up, but that they play a decisive role in practice. Conclusions: The present (Dutch) GHG indicator lacks robustness, which will raise problems for providing a sound basis for granting subsidies. This situation can, however, be improved by reducing the freedom of choices for the handling of biogenic CO2 and allocation to an absolute minimum. Recommendations and perspectives: Even then, however, differences could appear due to different definitions, data sources, and method interpretations. It thus appears that two kinds of guidance are needed: (1) the LCA methodology itself should be expanded with guidelines for those issues that follow from science, logic, or consensus; (2) in the policy regulation that demands LCA to be the basis of the decision, additional guidelines should be specified that perhaps do not (yet) have the status of being scientifically proven or generally agreed upon, but that serve as a set of temporary extra guidelines.

In a previous article about life cycle assessment (LCA), a methodological framework was proposed and two components of this framework were discussed in more detail: the goal definition and the inventory. In this second article, the other components of the framework are discussed in detail: the classification, the valuation and the improvement analysis. In the classification, resource extractions and emissions associated with the life cycle of a product are translated into contributions to a number of environmental problem types, such as resource depletion, global warming, ozone depletion, acidification, etc. For this, each extraction and emission is multiplied with a so-called classification factor and the multiplication results are aggregated per problem type. Classification factors are proposed for a number of environmental problem types. The valuation includes both a valuation of the different environmental problem types and an assessment of the reliability and validity of the results. For the valuation of the environmental problem types, qualitative or quantitative multicriterion analysis could be applied. Given a standard list of weighting factors the quantitative multicriterion analysis seems preferable, because of its low costs and its simplicity. The main problem, however, is to get a broadly supported standard list. In studies so far little attention is paid to the assessment of the reliability and the validity of the results. To improve this situation methods which could support this assessment are proposed. In the improvement analysis potential options to improve the product(s) studied are identified. Combined with expertise in other fields, such as costs and technological feasibility, the improvement analysis may yield a number of serious options for the redesign of a product. Two complementary techniques for the identification of the potential options are discussed. With these techniques and the active participation of process technologists and designers, LCA might become an analytic tool for eco-design supporting a continuous environmental improvement of products.

Abstract Life cycle assessment (LCA) is a method that has been applied on numerous different types of product systems. Most of these LCA studies concern full-market existing systems. In our common search for a more sustainable society, new technology systems are proposed of which the environmental sustainability still needs to be proven. These emerging technologies often only function at lab- or pilot-scale, and process data are also only available at these scales, and not at observed full-market scales. Performing LCAs of emerging technology systems poses challenges because relevant observations are lacking with regards to the projected final system, projected unit process data, projected characterization factors of new chemicals, etc. These challenges are increasingly recognized and addressed by the LCA community. In this contribution we discuss these challenges, with a special focus on ongoing research and recent developments.