• Energy Research

Purpose Consequential LCA (CLCA) is becoming widely used in the scientific community as a modelling technique which describes the consequences of a decision. However, despite the increasing number of case studies published, a proper systematization of the approach has not yet been achieved. This paper investigates the methodological implications of CLCA and the extent to which the applications are in line with the theoretical dictates. Moreover, the predictive and explorative nature of CLCA is discussed, highlighting the role of scenario modelling in further structuring the methodology. Methods An extensive literature review was performed, involving around 60 articles published over a period of approximately 18 years, and addressing both methodological issues and applications. The information was elaborated according to two main aspects: What for (questions and modes of LCA) and what (methodological implications of CLCA), with focus on the nature of modelling and on the identification of the affected processes. Results and discussion The analysis points out that since the modelling principles of attributional LCA (ALCA) and CLCA are the same, what distinguishes the two modes of LCA is the choice of the processes to be included in the system (i.e. in CLCA, those that are affected by the market dynamics). However, the identification of those processes is often done inconsistently, using different arguments, which leads to different results. We suggest the use of scenario modelling as a way to support CLCA in providing a scientifically sound basis to model specific product-related futures with respect to technology development, market shift, and other variables. Conclusions The CLCA is a sophisticated modelling technique that provides a way to assess the environmental consequences of an action/decision by including market mechanisms into the analysis. There is still room for improvements of the method and for further research, especially in relation to the following aspects: Clarifying when and which market information is important and necessary; understanding the role of scenario modelling within CLCA; and developing a procedure to support the framing of questions to better link questions to models. Moreover, we suggest that the logic of mechanisms could be the reading guide for overcoming the dispute between ALCA and CLCA. Going further, this logic could also be extended, considering CLCA as an approach-rather than as a modelling principle with defined rules-To deepen LCA,providing the conceptual basis for including more mechanisms than just the market ones.

The UN's 17 Sustainable Development Goals (SDGs) aim to improve the lives of people, increase prosperity, and protect the planet. Given the large number of goals, interactions are inevitable. We analyse the interaction between two social goals (related to SDG1 Poverty and SDG10 Inequality) and three environmental goals (related to SDG13 Carbon, SDG15 Land, and SDG6 Water). We use a trade-linked, consumption-based approach to assess interactions in 166 nations, each subdivided into four income groups. We find that pursuing social goals is, generally, associated with higher environmental impacts. However, interactions differ greatly among countries and depend on the specific goals. In both interactions, carbon experiences smaller changes than land and water. Although efforts by high- and low-income groups are needed, the rich have a greater leverage to reduce humanity's footprints. Given the importance of both social and environmental sustainability, it is crucial that quantitative interactions between SDGs be well understood so that, where needed, integrative policies can be developed.

Nanotechnology is an emerging technology with the potential to contribute towards sustainability. However, there are growing concerns about the potential environmental and human health impacts of nanomaterials. Clearly, nanomaterials have advantages and disadvantages, and a balanced view is needed to assess the overall benefit. The current “green and clean” claims of proponents of nanomaterials across different sectors of the economy are evaluated in this review study. Focusing on carbon emissions and energy use, we have reviewed 18 life cycle assessment studies on nanomaterials in the solar, energy, polymer, medical and food sectors. We find that the “green and clean” claims are not supported for the majority of the reviewed studies in the energy sector. In the solar sector, only specific technologies tend to support the “green and clean” claims. In the polymer sector, only some applications support the “green and clean” claims. The main findings show that nanomaterials have high cradle-to-gate energy demand that result in high carbon emissions. Synthesis of nanomaterials is the main contributor of carbon emissions in the majority of the studies. Future improvements in reducing parameter uncertainties and in the energy efficiency of the synthesis processes of nanomaterials might improve the environmental performance of nanotechnologies.

A recent paper in this journal points out that the ISO standards for LCA ignore the situation of internally recurring unit process in life cycle inventories. The paper also presents a way to solve this problem, using a set of simultaneous equations with one equation for each unit process and one variable for each product. The authors appear to be unaware of existing approaches towards this problem in which a set of simultaneous equations is used, but with a reverse set-up: one equation for each product and one variable for each unit process. This paper reviews the existing literature and contrasts it with the newly proposed method. It is concluded that the presentation of the new method is unclear in certain parts, and that its realm of application is probably restricted to product systems with mono-functional processes.

To assess the potential environmental impact of human/industrial systems, life cycle assessment (LCA) is a very common method. There are two prominent types of LCA, namely attributional (ALCA) and consequential (CLCA). A lot of literature covers these approaches, but a general consensus on what they represent and an overview of all their differences seems lacking, nor has every prominent feature been fully explored. The two main objectives of this article are: (1) to argue for and select definitions for each concept and (2) specify all conceptual characteristics (including translation into modelling restrictions), re-evaluating and going beyond findings in the state of the art. For the first objective, mainly because the validity of interpretation of a term is also a matter of consensus, we argue the selection of definitions present in the 2011 UNEP-SETAC report. ALCA attributes a share of the potential environmental impact of the world to a product life cycle, while CLCA assesses the environmental consequences of a decision (e.g., increase of product demand). Regarding the second objective, the product system in ALCA constitutes all processes that are linked by physical, energy flows or services. Because of the requirement of additivity for ALCA, a double-counting check needs to be executed, modelling is restricted (e.g., guaranteed through linearity) and partitioning of multifunctional processes is systematically needed (for evaluation per single product). The latter matters also hold in a similar manner for the impact assessment, which is commonly overlooked. CLCA, is completely consequential and there is no limitation regarding what a modelling framework should entail, with the coverage of co-products through substitution being just one approach and not the only one (e.g., additional consumption is possible). Both ALCA and CLCA can be considered over any time span (past, present & future) and either using a reference environment or different scenarios. Furthermore, both ALCA and CLCA could be specific for average or marginal (small) products or decisions, and further datasets. These findings also hold for life cycle sustainability assessment.

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.

Ecodesign — Carbon Footprint — Life Cycle Assessment — Life Cycle Sustainability Analysis. A Flexible Framework for a Continuum of Tools Life cycle assessment (LCA) is a tool for answering questions related to environmental impacts of products. It is a comprehensive tool, addressing the entire life cycle, and addressing the full spectrum of environmental impacts. There are two opposite movements occurring: LCA is getting smaller, and it is getting broader. This presentation presents the general framework for a broader life cycle sustainability analysis (LCSA), and shows how the practical work related to doing an LCA, a carbon footprint, or an analysis for ecodesign, can be seen as special cases.

In economics, opportunity cost is defined as the benefit foregone by choosing another course of action. Considering opportunity costs enables the improved handling of trade-offs to better support strategic decision-making. We introduce the concept of opportunity cost into life cycle assessment (LCA). In our framework, opportunity cost extends the system expansion paradigm to support better alignment with a circular economy (CE). Opportunity cost thinking is considered to be most useful for the efficient allocation of scarce economic capital for the creation of economic value. In the environmental domain, we use such thinking to account for the implications of ‘wasting waste’. In this paper, we consider a case of treated wastewater sludge being used as a source of nutrients as a vehicle to study the points at which LCA can support a CE. Our conclusions, however, have wider repercussions because there are many more situations in which product systems are analytically demarcated from the web of connections in which they are embedded.