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PurposeIn 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.MethodsWe 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 discussionWe 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.ConclusionsThe 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.

Risk assessment and life cycle assessment are both needed in the environmental evaluation of engineered nanomaterials. Scientists from both fields should collaborate intensively to deal with mutual challenges to achieve a complete and comprehensive assessment. Although technological and environmental benefits are important stimuli for nanotechnology development, these technologies have been contested from an environmental point of view. The steady growth of applications of engineered nanomaterials has heated up the debate on quantifying the environmental repercussions. The two main scientific methods to address these environmental repercussions are risk assessment and life-cycle assessment. The strengths and weaknesses of each of these methods, and the relation between them, have been a topic of debate in the world of traditional chemistry for over two decades. Here we review recent developments in this debate in general and for the emerging field of nanomaterials specifically. We discuss the pros and cons of four schools of thought for combining and integrating risk assessment and life-cycle assessment and conclude with a plea for action.

In traditional research, repeated measurements lead to a sample of results, and inferential statistics can be used to not only estimate parameters, but also to test statistical hypotheses concerning these parameters. In many cases, the standard error of the estimates decreases (asymptotically) with the square root of the sample size, which provides a stimulus to probe large samples. In simulation models, the situation is entirely different. When probability distribution functions for model features are specified, the probability distribution function of the model output can be approached using numerical techniques, such as bootstrapping or Monte Carlo sampling. Given the computational power of most PCs today, the sample size can be increased almost without bounds. The result is that standard errors of parameters are vanishingly small, and that almost all significance tests will lead to a rejected null hypothesis. Clearly, another approach to statistical significance is needed. This paper analyzes the situation and connects the discussion to other domains in which the null hypothesis significance test (NHST) paradigm is challenged. In particular, the notions of effect size and Cohen’s d provide promising alternatives for the establishment of a new indicator of statistical significance. This indicator attempts to cover significance (precision) and effect size (relevance) in one measure. Although in the end more fundamental changes are called for, our approach has the attractiveness of requiring only a minimal change to the practice of statistics. The analysis is not only relevant for artificial samples, but also for present-day huge samples, associated with the availability of big data.

Goal, Scope and BackgroundIn the recently published (Dutch) Handbook on LCA, economic allocation is advised as baseline method for most allocation situations in a detailed LCA. Although the Handbook on LCA aimed to provide a ‘cookbook’ with operational guidelines for conducting each step of an LCA, this was not completely achieved for the allocation step. The guidelines for allocation largely remained at the level of principles. This restricted elaboration of economic allocation may hamper application in practice. Therefore, this paper elaborates some examples applying economic allocation.MethodTwo concepts are of particular importance when applying economic allocation: functional flow and multi-functional process. The definitions of these concepts are presented and discussed. The basic principle of economic allocation is that having determined the various functional flows of a multi-functional process, all other flows need to be allocated to these functional flows according to their shares in the total proceeds. Proceeds are based on prices and these are not always easy to determine for a process. A summary of possible solutions for different problems when determining prices is given.Results and DiscussionThe examples presented focus on co-production and various recycling situations. All examples are hypothetical in order to avoid discussions on the data. The examples show that the prices of the functional flows determine the allocation results. It is of importance to have correct information on the relative prices of the functional flows at stake, especially whether they are negative or positive. Learning from these examples, we establish a decision tree for economic allocation. The decision tree is meant for identifying and handling multi-functionality situations starting from a defined (product) system. This decision tree is with minor adaptations also applicable to other allocation methods and has a more general value than for the economic allocation method only.Conclusions and perspectiveThe examples have helped us to establish a decision tree for handling the multi-functionality problem by economic allocation. The examples can be broadened to other materials and allocation situations. We would encourage others to provide other examples and experiences as we expect that these will help to further improve and refine the guidelines and decision tree for economic allocation in future.

Purpose and contextThis paper aims to establish principles for the increased application and use of life cycle sustainability assessment (LCSA). Sustainable development (SD) encompassing resilient economies and social stability of the global system is growingly important for decision-makers from business and governments. The “17 SDGs” emerge as a high-level shared blueprint for peace, abundance, and prosperity for people and the planet, and “sustainability” for supporting improvements of products and organizations. A “sustainability” interpretation—successful in aligning stakeholders’ understanding—subdivides the impacts according to a triple bottom line or three pillars: economic, social, and environmental impacts. These context and urgent needs inspired the LCSA framework. This entails a sustainability assessment of products and organizations in accordance with the three pillars, while adopting a life cycle perspective.MethodsThe Life Cycle Initiative promotes since 2011 a pragmatic LCSA framework based on the three techniques: LCSA = environmental life cycle assessment (LCA) + life cycle costing (LCC) + social life cycle assessment (S-LCA). This is the focus of the paper, while acknowledging previous developments. Identified and reviewed literature shows challenges of addressing the three pillars in the LCSA framework implementation like considering only two pillars; not being fully aligned with ISO 14040; lacking interconnectedness among the three pillars; not having clear criteria for results’ weighting nor clear results’ interpretation; and not following cause-effect chains and mechanisms leading to an endpoint. Agreement building among LCSA experts and reviewing processes strengthened the consensus on this paper. Broad support and outreach are ensured by publishing this as position paper.ResultsFor harmonizing practical LCSA applications, easing interpretation, and increasing usefulness, consensed ten LCSA principles (10P) are established: understanding the areas of protection, alignment with ISO 14040, completeness, stakeholders’ and product utility considerations, materiality of system boundaries, transparency, consistency, explicit trade-offs’ communication, and caution when compensating impacts. Examples were provided based on a fictional plastic water bottleConclusionsIn spite of increasing needs for and interest in SD and sustainability supporting tools, LCSA is at an early application stage of application. The 10P aim to promote more and better LCSA applications by ensuring alignment with ISO 14040, completeness and clear interpretation of integrated results, among others. For consolidating its use, however, more consensus-building is needed (e.g., on value-laden ethical aspects of LCSA, interdependencies and interconnectedness among the three dimensions, and harmonization and integration of the three techniques) and technical and policy recommendations for application.

In response to growing awareness of climate change, requests to establish product carbon footprints have been increasing. Product carbon footprints are life cycle assessments restricted to just one impact category, global warming. Product carbon footprint studies generate life cycle inventory results, listing the environmental emissions of greenhouse gases from a product's lifecycle, and characterize these by their global warming potentials, producing product carbon footprints that are commonly communicated as point values. In the present research we show that the uncertainties surrounding these point values necessitate more sophisticated ways of communicating product carbon footprints, using different sizes of catfish (Pangasius spp.) farms in Vietnam as a case study. As most product carbon footprint studies only have a comparative meaning, we used dependent sampling to produce relative results in order to increase the power for identifying environmentally superior products. We therefore argue that product carbon footprints, supported by quantitative uncertainty estimates, should be used to test hypotheses, rather than to provide point value estimates or plain confidence intervals of products' environmental performance.

PurposeThe methods for assessing the impact of using abiotic resources in life cycle assessment (LCA) have always been heavily debated. One of the main reasons for this is the lack of a common understanding of the problem related to resource use. This article reports the results of an effort to reach such common understanding between different stakeholder groups and the LCA community. For this, a top-down approach was applied.MethodsTo guide the process, a four-level top-down framework was used to (1) demarcate the problem that needs to be assessed, (2) translate this into a modeling concept, (3) derive mathematical equations and fill these with data necessary to calculate the characterization factors, and (4) align the system boundaries and assumptions that are made in the life cycle impact assessment (LCIA) model and the life cycle inventory (LCI) model.ResultsWe started from the following definition of the problem of using resources: the decrease of accessibility on a global level of primary and/or secondary elements over the very long term or short term due to the net result of compromising actions. The system model distinguishes accessible and inaccessible stocks in both the environment and the technosphere. Human actions can compromise the accessible stock through environmental dissipation, technosphere hibernation, and occupation in use or through exploration. As a basis for impact assessment, we propose two parameters: the global change in accessible stock as a net result of the compromising actions and the global amount of the accessible stock. We propose three impact categories for the use of elements: environmental dissipation, technosphere hibernation, and occupation in use, with associated characterization equations for two different time horizons. Finally, preliminary characterization factors are derived and applied in a simple illustrative case study for environmental dissipation.ConclusionsDue to data constraints, at this moment, only characterization factors for “dissipation to the environment” over a very-long-term time horizon could be elaborated. The case study shows that the calculation of impact scores might be hampered by insufficient LCI data. Most presently available LCI databases are far from complete in registering the flows necessary to assess the impacts on the accessibility of elements. While applying the framework, various choices are made that could plausibly be made differently. We invite our peers to also use this top-down framework when challenging our choices and elaborate that into a consistent set of choices and assumptions when developing LCIA methods.

PurposeThis study focuses on the environmental assessment of European copper production. Life cycle assessment is applied to analyse copper cathode production in Sweden, including its mining (an open-pit mine) and refining (pyrometallurgy), and using two combinations of software and databases: SimaPro software with ecoinvent database and GaBi software with GaBi database. The results are compared with results from other case studies from literature.MethodsA cradle-to-gate LCA was conducted considering 1 tonne of copper as functional unit. The inventory for the foreground system was elaborated using primary data gathered by the staff from the mine, the concentrator and the smelter. For the background data, LCA databases are used considering datasets for the Swedish market whenever possible. As the smelter has multiple useful outputs, economic allocation was applied at the inventory level. The calculation method CML-IA baseline 3.5 was considered for both combinations of software and database, reporting all the impact categories of the method plus the Cumulative Energy Demand.Results and discussionThe inventory of the system and the main environmental hotspots were presented, such as the explosives for blasting (due to their supply chain) or the electricity used in the concentrator. The results obtained with the two combinations of LCA software and databases yield large differences for categories such as abiotic depletion (7.5 times higher for SimaPro and ecoinvent), possibly due to differences in the system boundaries of the databases and the characterisation factors of the method. Although the case study has a relatively high cumulative energy demand (140/168 kMJ/tonne Cu) compared to other mines, its performance in global warming (3.5/4.7 tonne CO2eq/tonne Cu) is much better due to the low greenhouse gas emissions from electricity, which shows that the electricity mix is a key aspect.ConclusionsThe environmental performance of mining depends partially on the specific conditions of the deposit, e.g., the ore grade and the mining type. LCA practitioners should consider the potential different results that can be obtained using different combinations of software and database and exert caution when comparing cases, especially for abiotic depletion, human toxicity and ecotoxicity categories. Finally, the use of renewable energies can be key to improve the environmental sustainability of copper production.

Purpose When resources are extracted and used by society, they are not necessarily lost for future generations. Therefore, recent publications on impact assessment of abiotic resource use in life cycle assessment focus on a decreased accessibility of resources due to dissipation, rather than depletion. In a previous study, dissipation was defined as a function of the global change in accessible stock due to human actions, and the global amount of the accessible stock, assuming a very long-term time perspective (more than 500 years). In this paper, a short-term time perspective (25 years) is adopted. Methods The same generic characterization model is used, but different choices are outlined to derive characterization factors for a short-term perspective (25 years). To illustrate how the short term might be approached, a preliminary set of characterization factors is developed, based on assumptions and estimates. Results The problem of resource use is defined as follows: the decrease of accessibility on a global level of primary and/or secondary elements over the short term due to the net result of compromising actions (i.e., emissions, dissipation in the technosphere, occupation in use, and exploration for new stocks). Characterization factors are derived based on assumptions, like the following: the accessible stock is based on present estimates of accessible stocks in the environment and the technosphere; estimates of accessible stocks in the technosphere are based on past extractions and generic recycling rates; all flows that are presently not recycled are assumed to be inaccessible. Finally, weighting between elements and the functions they have for the present society is based on the added value of the economic sector that is affected due to the decreased accessibility. Discussion and conclusion A preliminary set of characterization factors is proposed for 55 elements. They assess the impact of the present use of resources on the decreased accessibility in the short term due to emissions and dissipation in the technosphere. However, calculation of impact category scores is still hampered by a lack of appropriate data for dissipative flows in life cycle inventory databases. The presented calculations are based on several simplifications and proxies. A more detailed distinction of dissipative flows and estimates of stocks in the technosphere may be possible based on (dynamic) SFA modelling of elements in different applications. To derive a more mature set of characterization factors, it is recommended to use the presented model as a basis and further elaborate or replace the proxies.