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In this research, how environmental impacts of products can be tracked through complex production networks based on semantic data and environmental impact calculations is demonstrated. It focuses on the example of secondary copper production and the subsequent production of copper alloys, namely bronze and brass. The adopted methodology and ontology can however be generalized to other products and environmental impact categories. In this study, HSC Sim and FactSage software are employed to model and simulate the copper alloy production process from copper scrap (CuScrap) and waste‐printed circuit boards (WPCBs) and an ontology to represent the results for individual process parts is developed in a way that impact assessment is possible for all materials in a complex process network. Life cycle assessment (LCA), focused on greenhouse gas emissions (global warming potential [GWP]), is conducted using OpenLCA software and the ecoinvent 3.8 database to evaluate the environmental impacts comprehensively. In the GWP results, variations across all the studied cases are indicated, with bronze production generally exhibiting higher impacts, i.e., 33.46%, 32.33%, and 32.41% for Scrap, Mix, and printed circuit board cases, respectively, as compared to brass production due to the presence of tin (in bronze) which exhibits 3.7 times higher emissions than zinc (present in brass).
In this research, how environmental impacts of products can be tracked through complex production networks based on semantic data and environmental impact calculations is demonstrated. It focuses on the example of secondary copper production and the subsequent production of copper alloys, namely bronze and brass. The adopted methodology and ontology can however be generalized to other products and environmental impact categories. In this study, HSC Sim and FactSage software are employed to model and simulate the copper alloy production process from copper scrap (CuScrap) and waste‐printed circuit boards (WPCBs) and an ontology to represent the results for individual process parts is developed in a way that impact assessment is possible for all materials in a complex process network. Life cycle assessment (LCA), focused on greenhouse gas emissions (global warming potential [GWP]), is conducted using OpenLCA software and the ecoinvent 3.8 database to evaluate the environmental impacts comprehensively. In the GWP results, variations across all the studied cases are indicated, with bronze production generally exhibiting higher impacts, i.e., 33.46%, 32.33%, and 32.41% for Scrap, Mix, and printed circuit board cases, respectively, as compared to brass production due to the presence of tin (in bronze) which exhibits 3.7 times higher emissions than zinc (present in brass).
Furnace slags are potential new sources of critical metals. We undertook a micron- to nanoscale study that addresses speciation, distribution and associations of phases in flash furnace (FF, oxidised) and electric furnace (EF, reduced) slags from the Olympic Dam mining-smelting-refinery operation. Results enable understanding of the behaviour and partitioning of critical metals between melt and cooling crystalline phases in a controlled smelter environment that mimics Fe-Si-rich systems in Nature. Melts at ~1300 °C result in slags that differ in the relative proportions of component phases. Both FF and EF slags comprise major magnetite and two, compositionally distinct Si-Fe-rich glasses (glass-1 and -2); fayalite is a main component of EF slag. Glass-1 is rich in REE+Y (4.5–5.4 wt%, Ce2O3+La2O3) and contains dendritic monazite-(Ce). The EF slag crystallization sequence is: magnetite→fayalite+glass-1→monazite→glass-2. Immiscibility of REE in Si-Fe-rich melt is inferred from amorphous ‘monazite-like’ droplets. Chondrite-normalised fractionation patterns are defined by downwards-sloping LREE segments in both glasses. Partition coefficients are calculated for magnetite and fayalite relative to glasses. DREY for HREE exceeds those for LREE in all phases and fayalite has an order of magnetite higher DHREE than co-existing EF magnetite. Applying lattice strain models to experimental values show excellent fits for DHREE-model trends, even if lattice strain is not the sole factor controlling partitioning. Melt polymerisation, variable/unpredictable oxidation states, and constraints from specific crystallographic sites, also impact on observed trends. This study demonstrates that clues to element behaviour in the deep Earth are available from metallurgical plants.
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