In this paper, we discuss practical challenges in ex-ante life cycle assessment (LCA) of emerging technologies, i.e., barriers to hands-on implementation, as opposed to the conceptual challenges... Show moreIn this paper, we discuss practical challenges in ex-ante life cycle assessment (LCA) of emerging technologies, i.e., barriers to hands-on implementation, as opposed to the conceptual challenges that recent contributions to the literature have been focusing on (see Giesen et al., 2020; Thonemann et al., 2020; Villares et al., 2017). We will illustrate the discussion with the case of emerging photovoltaics (PV), namely multijunction III-V/silicon tandem cell (III-V/Si). This case application helps structure the ex-ante LCA exercise and highlights the challenges of applying LCA early on in technology development, while providing sufficient general elements that apply to other emerging technologies.Written from the perspective of LCA analysts, the paper is organized around the LCA method. LCAs can be conducted at various stages of a technology development process, requiring different types of information at the various stages. By illustrating with the case study of emerging photovoltaics, the paper explores the importance of product performance optimization during technological development, and how it is directly linked to environmental performance during the use phase. It also demonstrates how the design and manufacturing choices that technology developers are confronted with can greatly influence environmental performance over the future product’s life cycle. The approach that emerges is one in which the LCA method remains flexible throughout the technology development process to accommodate its dynamic nature and the numerous uncertainties inherent in it. Show less
Purpose In 1995, the original method for assessing the impact category abiotic resource depletion using abiotic depletion potentials (ADPs) was published. The ADP of a resource was defined as the... Show morePurpose In 1995, the original method for assessing the impact category abiotic resource depletion using abiotic depletion potentials (ADPs) was published. The ADP of a resource was defined as the ratio of the annual production and the square of the ultimate (crustal content based) reserve for the resource divided by the same ratio for a reference resource (antimony (Sb)). In 2002, ADPs were updated based on the most recent USGS annual production data. In addition, the impact category was sub-divided into two categories, using two sets of ADPs: the ADP for fossil fuels and the ADP for elements; in this article, we focus on the ADP for elements. Since then, ADP values have not been updated anymore despite the availability of updates of annual production data and also updates of crustal content data that constitute the basis of the ultimate reserves. Moreover, it was known that the coverage of elements by ADPs was incomplete. These three aspects together can affect relative ranking of abiotic resources based on the ADP. Furthermore, dealing with annually changing production data might have to be revisited by proposing new calculation procedures. Finally, category totals to calculate normalized indicator results have to be updated as well, because incomplete coverage of elements can lead to biased results. Methods We used updated reserve estimates and time series of production data from authoritative sources to calculate ADPs for different years. We also explored the use of several variations: moving averages and cumulative production data. We analyzed the patterns in ADP over time and the contribution by different elements in the category total. Furthermore, two case studies are carried out applying two different normalization reference areas (the EU 27 as normalization reference area and the world) for 2010. Results and discussion We present the results of the data updates and improved coverage. On top of this, new calculation procedures are proposed for ADPs, dealing with the annually changing production data. The case studies show that the improvements of data and calculation procedures will change the normalized indicator results of many case studies considerably, making ADP less sensitive for fluctuating production data in the future. Conclusions The update of ultimate reserve and production data and the revision of calculation procedures of ADPs and category totals have resulted in an improved, up-to-date, and more complete set of ADPs and a category total that better reflects the total resource depletion magnitude than before. An ADP based on the cumulative production overall years is most in line with the intent of the original ADP method. We further recommend to only use category totals based on production data for the same year as is used for the other (emission-based) impact categories. Show less
Oers, L.F.C.M. van; Guinée, J.B.; Heijungs, R. 2019
Purpose Despite efforts to treat uncertainty due to methodological choices in life cycle assessment (LCA) such as standardization, one-at-a-time (OAT) sensitivity analysis, and analytical and... Show morePurpose Despite efforts to treat uncertainty due to methodological choices in life cycle assessment (LCA) such as standardization, one-at-a-time (OAT) sensitivity analysis, and analytical and statistical methods, no method exists that propagate this source of uncertainty for all relevant processes simultaneously with data uncertainty through LCA. This study aims to develop, implement, and test such a method, for the particular example of the choice of partitioning methods for allocation in LCA, to be used in LCA calculations and software. Methods Monte Carlo simulations were used jointly with the CMLCA software for propagating into distributions of LCA results, uncertainty due to the choice of allocation method together with uncertainty of unit process data. In this study, a methodological preference is assigned to each partitioning method, applicable to multi-functional processes in the system. The allocation methods are sampled per process according to these preferences. A case study on rapeseed oil focusing on three greenhouse gas (GHG) emissions and their global warming impacts is presented to illustrate the method developed. The results of the developed method are compared with those for the same case similarly quantifying uncertainty of unit process data but accompanied by separate scenarios for the different partitioning choices. Results and discussion The median of the inventory flows (emissions) for separate scenarios varies due to the partitioning choices and unit process data uncertainties. Inventory variations are reflected in the global warming results. Results for the approach of this study vary with the methodological preference assigned to the different allocation methods per multi-functional process and with the continuous distribution of unit process data. The method proved feasible and implementable. However, absolute uncertainties only further increased. Therefore, it should be further researched to reflect relative uncertainties, more relevant for comparative LCAs. Conclusions Propagation of uncertainties due to the choice of partitioning methods and to unit process data into LCA results is enabled by the proposed method, while capturing variability due to both sources. It is a practical proposal to tackle unresolved debates about partitioning choices increasing robustness and transparency of LCA results. Assigning a methodological preference to each allocation method of multi-functional processes in the system enables pseudo-statistical propagation of uncertainty due to allocation. Involving stakeholders in determining these methodological preferences allows for participatory approaches. Eventually, this method could be expanded to also cover other ways of dealing with allocation and to other methodological choices in LCA. Show less
