The life cycle impact for platinum group metals and lithium to 2070 via surplus cost potential.

PURPOSE: A surplus cost potential (SCP) indicator has been developed as a measure of resource scarcity in the life cycle impact assessment (LCIA) context. To date, quality SCP estimates for other minerals than fossils are either not yet available or suffer methodological and data limitations. This paper overcomes these limitations and demonstrate how SCP estimates for metals can be calculated without the utilisation of ore grade function and by collecting primary economic and geological data. METHODS: Data were collected in line with the geographical distribution, mine type, deposit type and production volumes and total production costs in order to construct cost-cumulative availability curves for platinum group metals (PGMs) and lithium. These curves capture the total amount of known mineral resources that can be recovered profitably at various prices from different types of mineral deposits under current conditions (this is, current technology, prevailing labour and other input prices). They served as a basis for modelling the marginal cost increase, a necessary parameter for estimating the SCP indicator. Surplus costs were calculated for different scenario projections for future mineral production considering future market dynamics, recyclability rates, demand-side technological developments and economic growth and by applying declining social discount rate. RESULTS AND DISCUSSION: Surplus costs were calculated for three mineral production scenarios, ranging from (US$2014/kg) 6545-8354 for platinum, 3583-4573 for palladium, 8281-10,569 for rhodium, 513-655 for ruthenium, 3201-4086 for iridium and 1.70-5.80 for lithium. Compared with the current production costs, the results indicate that problematic price increases of lithium are unlikely if the latest technological trends in the automotive sector will continue up to 2070. Surplus costs for PGMs are approximately one-third of the current production costs in all scenarios; hence, a threat of their price increases by 2070 will largely depend on the discovery of new deposits and the ability of new technologies to push these costs down over time. This also applies to lithium if the increasing electrification of road transport will continue up to 2070. CONCLUSIONS: This study provides useful insight into the availability of PGMs and lithium up to 2070. It proves that if time and resources permit, reliable surplus cost estimates can be calculated, at least in the short-run, based on the construction of one's own curves with the level of quality comparable to expert-driven consulting services. Modelling and incorporating unknown deposits and potential future mineral production costs into these curves is the subject of future work.

Co-constructive development of a green chemistry-based model for the assessment of nanoparticles synthesis.

Nanomaterials (materials at the nanoscale, 10-9m) are extensively used in several industry sectors due to the improved properties they empower commercial products with. There is a pressing need to produce these materials more sustainably. This paper proposes a MCDA approach to assess the implementation of green chemistry principles as applied to the protocols for nanoparticles synthesis. In the presence of multiple green and environmentally oriented criteria, decision aiding is performed with a synergy of ordinal regression methods; preference information in the form of desired assignment for a subset of reference protocols is accepted. The classification models, indirectly derived from such information, are composed of an additive value function and a vector of thresholds separating the pre-defined and ordered classes. The method delivers a single representative model that is used to assess the relative importance of the criteria, identify the possible gains with improvement of the protocol's evaluations and classify the non-reference protocols. Such precise recommendation is validated against the outcomes of robustness analysis exploiting the sets of all classification models compatible with all maximal subsets of consistent assignment examples. The introduced approach is used with real-world data concerning silver nanoparticles. It is proven to effectively resolve inconsistency in the assignment examples, tolerate ordinal and cardinal measurement scales, differentiate between inter- and intra-criteria attractiveness and deliver easily interpretable scores and class assignments. This work thoroughly discusses the learning insights that MCDA provided during the co-constructive development of the classification model, distinguishing between problem structuring, preference elicitation, learning, modeling and problem-solving stages.

Phytoremediation-biorefinery tandem for effective clean-up of metal contaminated soil and biomass valorisation.

During the last few decades, phytoremediation process has attracted much attention because of the growing concerns about the deteriorating quality of soil caused by anthropogenic activities. Here, a tandem phytoremediation/biorefinery process was proposed as a way to turn phytoremediation into a viable commercial method by producing valuable chemicals in addition to cleaned soil. Two agricultural plants (Sinapis alba and Helianthus annuus) were grown in moderately contaminated soil with ca. 100 ppm of Ni and further degraded by a fungal lignin degrader-Phanerochaete chrysosporium. Several parameters have been studied, including the viability of plants, biomass yield, and their accumulating and remediating potentials. Further, downstream processing showed that up to 80% of Ni can be easily extracted from contaminated biomass by aqueous extraction at mild conditions. Finally, it was demonstrated that the growth of plants on the contaminated soil could be degraded by P. chrysosporium, and the effect of nickel and biomass pretreatment on the solid-state fermentation was studied. The proposed and studied methodology in this work could pave the way for successful commercialization of the phytoremediation process in the near future.

Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes.

This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier developed model for the same purpose to investigate concordance between the models and potential decision support synergies. A three-phase procedure was adopted to achieve the research objectives. Firstly, an ordinal ranking of the evaluation criteria used to characterize the implementation of green chemistry principles was identified through relative ranking analysis. Secondly, a structured selection process for an MCDA classification method was conducted, which ensued in the identification of Stochastic Multi-Criteria Acceptability Analysis (SMAA). Lastly, the agreement of the classifications by the two MCDA models and the resulting synergistic role of decision recommendations were studied. This comparison showed that the results of the two models agree between 76% and 93% of the simulation set-ups and it confirmed that different MCDA models provide a more inclusive and transparent set of recommendations. This integrative research confirmed the beneficial complementary use of MCDA methods to aid responsible development of nanosynthesis, by accounting for multiple objectives and helping communication of complex information in a comprehensive and traceable format, suitable for stakeholders and/or decision-makers with diverse backgrounds.

Interlayer Hybridization of Virgin Carbon, Recycled Carbon and Natural Fiber Laminates.

To meet sustainability objectives in the transport sector, natural fiber (NF) and recycled carbon fiber (RCF) have been developed, although they have been typically limited to low to medium performance components. This work has considered the effect of interlayer hybridization of woven NF and non-woven RCF with woven virgin carbon fibers (VCF) on the mechanical and damping performance of hybrid laminates, produced using double bag vacuum infusion (DBVI). The mean damping ratio of the pure laminates showed a trend of NF>RCF>VCF, which was inversely proportional to their modulus. The tensile, flexural and damping properties of hybrid laminates were dominated by the outermost ply. The VCF-RCF and VCF-NF hybrid laminates showed a comparatively greater mean damping ratio. The results of this work demonstrate a method for the uptake of alternative materials with a minimal impact on the mechanical properties and improved damping performance.

Improved hydrogen gas production in microbial electrolysis cells using inexpensive recycled carbon fibre fabrics.

Growing energy demands of wastewater treatment have made it vital for water companies to develop less energy intensive processes for treating wastewater if net zero emissions are to be achieved by 2050. Microbial electrolysis cells (MECs) have the potential to do this by treating water and producing renewable hydrogen gas as a product, but capital and operational costs have slowed their deployment. By using recycled carbon fibre mats, commercially viable MECs can brought closer to reality, where recycled carbon fibre anode MECs treating real wastewater (normalised ~3100 L d-1) were producing 66.77 L H2 d-1 while graphite felt anode MECs produced 3.65 L H2 d-1 per 1 m3 reactor, anodes costing £5.53 m-2 and £88.36 m-2 respectively, resulting in a total anode cost saving of 93%. This could incentivise the development of larger pilot systems, opening the door for generating greater value and a more sustainable wastewater treatment industry.

Synthetic mimicking of plant oils and comparison with naturally grown products in polyurethane synthesis.

The use of plant oils as industrial feedstocks can often be hampered by their lack of optimization towards a particular process, as well as their development being risky; growing suitable volumes of crops to test can take up to five years. To circumvent this, we aimed to discover a method that would mimic plant oil profiles in the laboratory, and show that they exhibited similar properties to the naturally grown plant oils in a given process. Using the synthesis of polyurethanes as an example, we have synthesized six different polymers and demonstrated that plant oils will produce polymers with similar physical properties to those oils mimicked in the laboratory. The use of this mimicking process can be extended to other types of polymers to obtain a method for predicting the properties of a given material based on the plant oil composition of a crop before it is grown in bulk.