Rosie Blannin is a geologist and resource engineer with a strong basis in fieldwork, sampling, characterisation, geometallurgy and geostatistical modelling of mine waste deposits. Rosie graduated with a BSc in Geology from the Imperial College London (2016) and an MSc from the EMerald Erasmus Mundus Masters (2018), a program focused on characterisation, processing and modelling in georesources engineering and undertaken at research institutions across Belgium, France, Sweden and Germany. After completing her MSc, Rosie undertook her PhD at Helmholtz Institute Freiberg as part of the SULTAN European Training Network for the Remediation and Reprocessing of Sulfidic Mining Waste Sites. In particular, Rosie has developed a method to assess the optimum sampling density and configuration for resource assessment of tailings deposits. Additionally, she has implemented geostatistical modelling methods to improve the quality of grade-tonnage estimates for tailings deposits and has performed geometallurgical modelling to evaluate recoverable metal contents as well as the potential for acid mine drainage.
Currently, Rosie is working as a Research Officer at the W.H. Bryan Mining and Geology Research Centre, SMI. She is involved in projects focused on sampling, characterisation and modelling of mine waste deposits across Australia.
Journal Article: A study on the desulfurization of sulfidic mine tailings for the production of a sulfur-poor residue
de Carvalho, Ana Luiza Coelho Braga, de Carvalho, Victor Albuquerque, Blannin, Rosie, Escobar, Alexandra Gomez, Frenzel, Max, Rudolph, Martin, Silva, André Carlos and Goldmann, Daniel (2023). A study on the desulfurization of sulfidic mine tailings for the production of a sulfur-poor residue. Minerals Engineering, 202 108285, 108285. doi: 10.1016/j.mineng.2023.108285
Journal Article: 3D geostatistical modelling of a tailings storage facility: resource potential and environmental implications
Blannin, Rosie, Frenzel, Max, Tolosana-Delgado, Raimon, Büttner, Philipp and Gutzmer, Jens (2023). 3D geostatistical modelling of a tailings storage facility: resource potential and environmental implications. Ore Geology Reviews, 154 105337. doi: 10.1016/j.oregeorev.2023.105337
Journal Article: Bioleaching of metal(loid)s from sulfidic mine tailings and waste rock from the Neves Corvo mine, Portugal, by an acidophilic consortium
Opara, Chiamaka Belsonia, Blannin, Rosie, Ebert, Doreen, Frenzel, Max, Pollmann, Katrin and Kutschke, Sabine (2022). Bioleaching of metal(loid)s from sulfidic mine tailings and waste rock from the Neves Corvo mine, Portugal, by an acidophilic consortium. Minerals Engineering, 188 107831, 1-21. doi: 10.1016/j.mineng.2022.107831
Geometallurgical characterisation of tailings - from sampling to metal extraction
(2023–2024) Regeneration Enterprises, Inc
MIM Tailings Reprocessing Study Initiation
(2023) Glencore Australia Holdings Pty Limited
A study on the desulfurization of sulfidic mine tailings for the production of a sulfur-poor residue
de Carvalho, Ana Luiza Coelho Braga, de Carvalho, Victor Albuquerque, Blannin, Rosie, Escobar, Alexandra Gomez, Frenzel, Max, Rudolph, Martin, Silva, André Carlos and Goldmann, Daniel (2023). A study on the desulfurization of sulfidic mine tailings for the production of a sulfur-poor residue. Minerals Engineering, 202 108285, 108285. doi: 10.1016/j.mineng.2023.108285
Blannin, Rosie, Frenzel, Max, Tolosana-Delgado, Raimon, Büttner, Philipp and Gutzmer, Jens (2023). 3D geostatistical modelling of a tailings storage facility: resource potential and environmental implications. Ore Geology Reviews, 154 105337. doi: 10.1016/j.oregeorev.2023.105337
Opara, Chiamaka Belsonia, Blannin, Rosie, Ebert, Doreen, Frenzel, Max, Pollmann, Katrin and Kutschke, Sabine (2022). Bioleaching of metal(loid)s from sulfidic mine tailings and waste rock from the Neves Corvo mine, Portugal, by an acidophilic consortium. Minerals Engineering, 188 107831, 1-21. doi: 10.1016/j.mineng.2022.107831
Metal deportment in Pb-Zn mine wastes from a historic tailings pond, Plombières, East Belgium
Bevandić, Srećko, Blannin, Rosie, Gomez Escobar, Alexandra, Bachmann, Kai, Frenzel, Max, Pinto, Álvaro, Relvas, Jorge M.R.S. and Muchez, Philippe (2022). Metal deportment in Pb-Zn mine wastes from a historic tailings pond, Plombières, East Belgium. Minerals Engineering, 184 107628, 1-14. doi: 10.1016/j.mineng.2022.107628
Kamariah, Nor, Kalebic, Demian, Xanthopoulos, Panagiotis, Blannin, Rosie, Araujo, Fernando P., Koelewijn, Steven-Friso, Dehaen, Wim, Binnemans, Koen and Spooren, Jeroen (2022). Conventional versus microwave-assisted roasting of sulfidic tailings: Mineralogical transformation and metal leaching behavior. Minerals Engineering, 183 107587, 1-11. doi: 10.1016/j.mineng.2022.107587
Blannin, Rosie, Frenzel, Max, Tolosana-Delgado, Raimon and Gutzmer, Jens (2022). Towards a sampling protocol for the resource assessment of critical raw materials in tailings storage facilities. Journal of Geochemical Exploration, 236 106974, 1-16. doi: 10.1016/j.gexplo.2022.106974
Vanderbruggen, Anna, Gugala, Eligiusz, Blannin, Rosie, Bachmann, Kai, Serna-Guerrero, Rodrigo and Rudolph, Martin (2021). Automated mineralogy as a novel approach for the compositional and textural characterization of spent lithium-ion batteries. Minerals Engineering, 169 106924, 1-14. doi: 10.1016/j.mineng.2021.106924
Blannin, Rosie, Frenzel, Max, Tuşa, Laura, Birtel, Sandra, Ivăşcanu, Paul, Baker, Tim and Gutzmer, Jens (2021). Uncertainties in quantitative mineralogical studies using scanning electron microscope-based image analysis. Minerals Engineering, 167 106836, 1-33. doi: 10.1016/j.mineng.2021.106836
Bevandić, Srećko, Blannin, Rosie, Auwera, Jacqueline Vander, Delmelle, Nicolas, Caterina, David, Nguyen, Frederic and Muchez, Philippe (2021). Geochemical and mineralogical characterisation of historic zn–pb mine waste, plombières, East Belgium. Minerals, 11 (1) 28, 1-27. doi: 10.3390/min11010028
Tuşa, L., Kern, M., Khodadadzadeh, M., Blannin, R., Gloaguen, R. and Gutzmer, J. (2020). Evaluating the performance of hyperspectral short-wave infrared sensors for the pre-sorting of complex ores using machine learning methods. Minerals Engineering, 146 106150, 1-10. doi: 10.1016/j.mineng.2019.106150
Predictive modelling of mineralogical and textural properties of tailings using geochemical data
Blannin, Rosie, Frenzel, Max and Gutzmer, Jens (2022). Predictive modelling of mineralogical and textural properties of tailings using geochemical data. 16th SGA Biennial Meeting 2022 , Rotorua, New Zealand, 28-31 March 2022.
Blannin, Rosie, Tusa, Laura, Birtel, Sandra, Gilbricht, Sabine, Ivascanu, Paul and Gutzmer, Jens (2019). Metal deportment and ore variability of the Bolcana porphyry Au-Cu system (Apuseni Mts, Romania) - Implications for ore processing. 15th Biennial Meeting of the Society for Geology Applied to Mineral Deposits, Glasgow, Scotland, Great Britain, 27-30 August 2019.
Geometallurgical characterisation of tailings - from sampling to metal extraction
(2023–2024) Regeneration Enterprises, Inc
MIM Tailings Reprocessing Study Initiation
(2023) Glencore Australia Holdings Pty Limited