Purpose The 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... Show morePurpose The 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. Methods To 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. Results We started from the followingdefinition of the problemof 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 thenetresult of compromising actions. Thesystem modeldistinguishes 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 abasis 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. Conclusions Due 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. Show less
A brief historic overview and analysis is presented of the almost 9000 scientific articles that have appeared in the Journal of Inorganic Biochemistry (JIB) and its predecessor (Bioinorganic... Show moreA brief historic overview and analysis is presented of the almost 9000 scientific articles that have appeared in the Journal of Inorganic Biochemistry (JIB) and its predecessor (Bioinorganic Chemistry), since 1973. This overview has a focus on the different topics, in particular on the different elements of the Periodic Table and on papers that have received very large numbers of citations. Over the whole period, copper has been the element occurring in most publications (almost 1800, which is 20%), followed by iron which occurs in some 12% of all papers. Other favorite elements are zinc, platinum and ruthenium. The worldwide origin of papers published in JIB has been analyzed as well, showing a quite evenly worldwide distribution, with just a few exceptions. Trends in selected scientific topics over time (first 10 years; last 25 years, last 10 years) are also discussed. Also authors and institutes with the largest number of papers published in JIB have been detected. The numerical information is based on an analysis of the Web of Science with a cutoff date around July 1, 2020. Show less
Schulze, R.; Guinée, J.B.; Oers, L. van; Alvarenga, R.; Dewulf, J.; Drielsma, J. 2019
At the beginning of the SUPRIM project, there was no global consensus on the assessment of impacts from the use of abiotic resources (minerals and metals), in life cycle impact assessment (LCIA).... Show moreAt the beginning of the SUPRIM project, there was no global consensus on the assessment of impacts from the use of abiotic resources (minerals and metals), in life cycle impact assessment (LCIA). Unlike with other impact categories such as global warming, there is not just one single, explicitly agreed-upon problem arising from the use of abiotic resources. The topic is complex and new methods are still being developed, all with different perspectives and views on resource use. For this reason, the SUPRIM project initiated a consensus process together with members from the research and mining communities, with the aim to obtain an understanding of different stakeholders’ views and concerns regarding potential issues resulting from the use of resources. This paper reports on this consensus process and its outcomes. Insights from this process are twofold: First, the outcome of the process is a clear definition of the perspectives on abiotic resources which form the starting point to further refine or develop LCIA methods on abiotic resource use. Second, the process itself has been a challenging but valuable exercise, which can inspire the evolution of other complex issues in life cycle impact assessment, where research communities face similar issues as experienced with abiotic resources (e.g. water and land use, social LCA, etc.). Show less
Our study emphasizes the importance of two toxicity-modifying factors (the composition of the surrounding exposure media and mixture effects) in the assessment of toxic effects of metals and... Show more Our study emphasizes the importance of two toxicity-modifying factors (the composition of the surrounding exposure media and mixture effects) in the assessment of toxic effects of metals and metal-based NPs on higher plants. Based on the affinity of metals for binding sites on the biotic ligand at the water-organism interface, the mechanistic models we developed provide better links with the toxicity of metal mixtures. We also recommend that finding a statistically significant deviation from additivity can be the starting point for further mechanistic research concerning toxicologically relevant interactions between substances, instead of the endpoint of research used so far. As an extension of the research discussed in the third chapter of this thesis, the commonly known model for the toxicity of mixtures was proven to be suitable for preliminarily assessing the effects of metal-based NPs on terrestrial organisms. The experimental design of nested combinations helps establish a more realistic exposure scenario for the environment and makes it possible to identify where and how chemical-chemical interactions occur with metal-based NPs. Consequently, our findings enrich the rapidly evolving field of toxicology regarding metals and metal-based NPs. Show less
There are only a limited number of studies that have developed appropriate models which incorporate bioavailability to estimate mixture toxicity. Here, we explored the applicability of the extended... Show moreThere are only a limited number of studies that have developed appropriate models which incorporate bioavailability to estimate mixture toxicity. Here, we explored the applicability of the extended biotic ligand model (BLM) and the WHAM-F tox approach for predicting and interpreting mixture toxicity, with the assumption that interactions between metal ions obey the BLM theory. Seedlings of lettuce Lactuca sativa were exposed to metal mixtures (Cu-Ni, Cu-Cd, and Ni-Cd) contained in hydroponic solutions for 4 days. Inhibition to root elongation was the endpoint used to quantify the toxic response. Assuming that metal ions compete with each other for binding at a single biotic ligand, the extended BLM succeeded in predicting toxicity of three mixtures to lettuce, with more than 82 % of toxicity variation explained. There were no significant differences in the values of f mix50 (i.e., the overall amounts of metal ions bound to the biotic ligand inducing 50 % effect) for the three mixture combinations, showing the possibility of extrapolating these values to other binary metal combinations. The WHAM-F tox approach showed a similar level of precision in estimating mixture toxicity while requiring fewer parameters than the BLM-f mix model. External validation of the WHAM-F tox approach using literature data showed its applicability for other species and other mixtures. The WHAM-F tox model is suitable for delineating mixture effects where the extended BLM also applies. Therefore, in case of lower data availability, we recommend the lower parameterized WHAM-F tox as an effective approach to incorporate bioavailability in quantifying mixture toxicity. Show less