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Sulfur analyses and mineralogical data in the preliminary mine waste characterization
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering. Circular Economy Solutions, Geological Survey of Finland, Neulaniementie 5, FI-70211 Kuopio, Finland.ORCID iD: 0000-0001-9034-3880
Circular Economy Solutions, Geological Survey of Finland, Neulaniementie 5, FI-70211 Kuopio, Finland.
Circular Economy Solutions, Geological Survey of Finland, Vuorimiehentie 2, FI-02151 Espoo, Finland.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.ORCID iD: 0000-0001-7291-8505
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2022 (English)In: Environmental Monitoring & Assessment, ISSN 0167-6369, E-ISSN 1573-2959, Vol. 194, article id 437Article in journal (Refereed) Published
Abstract [en]

The objective of this study was to investigate the use of the acid production potential (AP) calculation factor and seven different S analysis methods in the preliminary mine waste characterization by analyzing and comparing 48 Finnish mine waste samples. Special attention was paid on mineralogical aspects and data produced in the exploration phase of a mining project.

According to our results, the abundance of sulfide species other than pyrite in Finnish mine waste suggests that the factor to calculate the AP should be considered based on mineralogy and would often be below 31.25. Therefore, the mineralogy-based determination of S should be preferred. However, the determination of S based on scanning electron microscope (SEM) mineralogy includes some uncertainties. Underestimation of S content may appear if not all S-bearing mineral particles have been detected, or if the amount of S is low in general. This uncertainty appears to be especially related to the samples containing elevated (> 9 wt%) amounts of serpentine, diopside, augite, and/or hornblende. Risk of overestimating AP is related to samples containing high amounts (> 4.13 wt%) of S-bearing minerals. These uncertainties can be reduced by inspecting that the SEM mineralogy-based S concentrations are in line with the energy dispersive X-ray spectrometer data. The aqua regia extractable S concentrations, which are often available in the exploration phase, appeared to be usable in the preliminary waste rock AP assessment and often comparable with the analytical total S values in the Finnish waste rock samples, especially when the samples did not contain any sulfate minerals. In contrast, the analytical sulfide S and the X-ray fluorescence methods may lead to an underestimation of AP.

Place, publisher, year, edition, pages
Springer, 2022. Vol. 194, article id 437
Keywords [en]
Acid mine drainage, mineralogy, sulfide minerals, aqua regia, SEM, EDS spectra, Sulfur analysis
National Category
Geochemistry
Research subject
Applied Geochemistry
Identifiers
URN: urn:nbn:se:ltu:diva-89216DOI: 10.1007/s10661-022-10094-9ISI: 000797510400001PubMedID: 35583831Scopus ID: 2-s2.0-85130272289OAI: oai:DiVA.org:ltu-89216DiVA, id: diva2:1636858
Note

Validerad;2022;Nivå 2;2022-05-31 (joosat);

Funder: K.H Renlunds stiftelse

Available from: 2022-02-11 Created: 2022-02-11 Last updated: 2023-10-11Bibliographically approved
In thesis
1. Geochemical and Mineralogical Characterization of Waste Rocks for Preliminary Mine Drainage Quality Prediction
Open this publication in new window or tab >>Geochemical and Mineralogical Characterization of Waste Rocks for Preliminary Mine Drainage Quality Prediction
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Acid or neutral rock drainage (ARD or NRD) with its attendant elevated concentrations of harmful elements presents one of the main challenges related to the management of waste rocks. Low-quality drainage is a particular issue with respect to mineral deposits containing sulfide minerals, of which pyrite and pyrrhotite are especially prone to produce acidic drainage when exposed to oxygen and water. The generation of low-quality drainage depends primarily on the composition of mine waste, in particular the proportions of acid-producing and neutralizing minerals, as well as the abundance of harmful elements bound to leachable mineral phases. To mitigate adverse environmental impacts, it is important to characterize waste rocks at an early phase of any given mining project. Early-phase characterization is needed in designing appropriate waste facilities, water treatment and closure techniques, and to investigate the potential possibilities for utilization of waste material. Several methods have been developed for characterizing waste rocks and for predicting their potential for generating low-quality drainage. These methods include static and kinetic testing, geochemical extractions, geochemical modelling, and the use of analogs from similar, older, mine waste sites. Geochemical extractions and static tests, such as acid-base accounting (ABA) and net acid-generation (NAG) tests, are commonly used for preliminary screening, and in selecting suitable samples for further testing. The assortment of these preliminary characterization methods should be expanded and their performance in ARD and element mobility prediction investigated further, to improve the accuracy of drainage quality prediction.

The objective of this study has been to enhance waste rock management by developing tools for preliminary waste rock characterization and drainage quality prediction. An additional objective has been to improve the capacity for using geochemical and mineralogical data that have already been obtained during early phases of a mining project, and to provide general information about Finnish waste rock characteristics, so as to highlight the need for regional scale waste rock management and investigations. Accordingly, this study is based on waste rock and drainage samples collected from 19 Finnish active and closed mine sites, with the aim of assessing and comparing the performance of different methods for the preliminary prediction of drainage quality. The investigated acid potential (AP) methods included the ABA test in accordance with the established standard EN 15875, the single-addition NAG test as presented in the AMIRA guidebook, and an additional calculation based on SEM mineralogy. Furthermore, the suitability of seven different sulfur analytical methods for AP assessment was evaluated. The assessed methods for element mobility prediction included single-addition NAG test leachate analysis, as well as aqua regia (AR) and hydrogen peroxide ammonium citrate (HA) extractions, which are commonly used in mineral exploration to determine the concentrations of valuable elements bound to sulfide minerals.

Based on the results, pyrrhotite was found to be the main sulfide mineral contributing to AP in the waste rocks at the investigated sites, with pyrite being the next in importance. The abundance of sulfide species other than pyrite in the waste rocks led to the realization suggested that the appropriate factor for defining the AP, based on multiplying the S content, should instead take into consideration the dominant sulfide species, rather than assume that all S is pyritic. Silicate minerals, especially biotite, were found to be important contributors to the neutralization potential (NP). The results suggested that the AP and NP calculations based on the SEM mineralogy serve as a useful tool in the ARD prediction, as they also reveal the source minerals for AP and NP. However, it is recommended to make use of EDS spectral data to verify that the S concentration calculated by modal mineralogy is in accord with total S based on the EDS sum spectra. The AR-extractable S concentration appeared to be a useful discriminant for determining the S concentration for the AP calculation, as it does not leach baryte, thus more accurately representing the S-content in sulfide.

The most abundant harmful elements in the investigated waste rocks were Co, Ni, Cu, and Cr, whereas in the waste rock pile drainages the most prominent elements were  Ni, Co, Zn and Cu. Results indicated that the use of the Finnish PIMA values (the threshold values defined in the Government Decree 214/2007 on the Assessment of Soil Contamination and Remediation Needs) in the waste rock characterization should be reassessed, especially for Cr, for which concentrations often exceeded the PIMA threshold values, even though they were not elevated in the corresponding drainage waters. Based on the measured drainage water concentrations, the AR and HA extraction methods appeared to be effective in the prediction of preliminary ARD quality. The AR extraction realistically reflected the abundances of elements that are likely to occur in elevated concentrations in the waste rock drainage water. However, this method overestimates contaminant mobilities in some circumneutral drainage cases, and the mobility of Cr in general. The HA extraction also performed well in the prediction of harmful element mobilities, with the exception of Al mobility in acidic drainage systems. The HA extraction appeared to be a more sulfide specific method compared with AR, which is evident for example, in better prediction of Cr mobility. The single-addition NAG test leachate analysis performed well in assessing the mobility of harmful elements, but only when the test leachate was acidic, as the elements appeared to co-precipitate when the NAG test leachate pH rises above 3-6.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2022
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Mine waste characterisation, mine drainage water, ARD, NRD, aqua regia extraction, ABA test, NAG test, SEM mineralogy, sulfide minerals, risk assessment
National Category
Geochemistry
Research subject
Applied Geochemistry
Identifiers
urn:nbn:se:ltu:diva-89217 (URN)978-91-8048-028-4 (ISBN)978-91-8048-029-1 (ISBN)
Public defence
2022-04-13, F1031, Luleå, 09:00 (English)
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Supervisors
Available from: 2022-02-11 Created: 2022-02-11 Last updated: 2022-03-22Bibliographically approved

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Karlsson, TeemuAlakangas, Lena

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