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Rare Earth and Critical Element Chemistry of the Volcanic Ash-fall Parting in the Fire Clay Coal, Eastern Kentucky, USA

Published online by Cambridge University Press:  01 January 2024

Jingjing Liu*
Affiliation:
School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China
Shifeng Dai*
Affiliation:
College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Debora Berti*
Affiliation:
Department of Oceanography, Texas A&M University, College Station, TX 77843-3146, USA
Cortland F. Eble*
Affiliation:
Kentucky Geological Survey, University of Kentucky, Lexington, KY 40506, USA
Mengjun Dong*
Affiliation:
College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Yan Gao*
Affiliation:
College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
James C. Hower*
Affiliation:
Center for Applied Energy Research, University of Kentucky, 2540 Research Park Drive, Lexington, KY 40511, USA Department of Earth & Environmental Sciences, University of Kentucky, Lexington, KY 40506, USA
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Abstract

In the search for rare earth and other critical elements in coal measures, the coals are emphasized with lesser consideration for the accompanying rocks. In this investigation, the focus is on a lanthanide-rich, 315–317 Ma (after Machlus et al., Chemical Geology, 539, art. no. 119485, 2020) volcanic ash-fall trachyandesite to trachyte tonstein which occurs in association with the Middle Pennsylvanian Duckmantian-age Fire Clay coal in eastern Kentucky. The tonstein was deposited largely during peat accumulation, although it is known to occur at the base of the coal or within the underclay. The mineralogy is dominated by kaolinite with illite and quartz as minor to major minerals. A number of accessory minerals, as detected by X-ray diffraction + Siroquant XRD software and scanning and transmission electron microscopy (S/TEM), include REE-bearing phosphates (apatite, crandallite, florencite, monazite), and Y-bearing zircon. The highest rare earth element + Y concentrations occur in the weathered tonsteins, probably due to the concentration of these minerals after weathering of kaolinite from the rock.

Information

Type
Original Paper
Copyright
Copyright © The Author(s), under exclusive licence to The Clay Minerals Society 2023
Figure 0

Fig. 1 Locations of the tonstein and other sample sites within central eastern Kentucky, USA

Figure 1

Table 1 Sample, sample type, location (7½ˈ quadrangle, county, north latitude, west longitude), thickness (cm) for samples analyzed in the present study

Figure 2

Fig. 2 a Lithologic profile of a coal seam surrounding tonstein sample 4712. b Hand specimen of tonstein (sample 4712), the underlying illitic clay (sample 4713 in Hower et al., 1999), and a portion of the lowermost lithotype of the coal (sample 4714 in Hower et al., 1999). Note centimeter scale to the right of hand specimen. c Polished block corresponding to coal sample 41010. The coal encases kaolinite lenses (K) and a thin tonstein lens (t). The tonstein was present at the top of the polished coal section. Note centimeter scale to the left of polished block

Figure 3

Table 2 Mineral percentages as determined by XRD and Siroquant (%)

Figure 4

Fig. 3 Al2O3–SiO2–K2O chemistry of the rock and coal samples. The floor samples (4703, 4898, 4880, and 4912) and the weathered tonsteins (4962 and 4969) are identified

Figure 5

Fig. 4 TEM images of the FIB section. a Monazite (mz) and kaolinite (Kln); the black ribbon is a platinum (Pt) protective layer placed on the surface of the sample; b kaolinite; c selected area electron diffraction pattern (SAED) of the region within the white circle in b. The pattern symmetry and d spacing correspond to kaolinite viewed along 11¯0. The inset shows the kinematic simulation computed with the software SingleCrystal®4, using the kaolinite structure by Bish and Von Dreele (1989) which confirms the identification (from Hower et al., 2018)

Figure 6

Fig. 5 SEM back-scattered electron images of kaolinite, sanidine, and apatite in tonstein samples: a vermicular kaolinite and a matrix kaolinite in sample 4673; b sanidine in a kaolinite matrix in sample 4673; c sanidine in a kaolinite matrix in sample 4777; d sanidine in a kaolinite matrix in sample 4673; e and f apatite in a kaolinite matrix. Key: Kln, kaolinite; Sa, sanidine; Ap, apatite

Figure 7

Fig. 6 SEM back-scattered electron images of zircon in sample 4673

Figure 8

Fig. 7 SEM back-scattered electron images of Ti oxides (rutile or anatase): a Ti oxide distributed in vermicular kaolinite in sample 4673; b authigenic Ti oxide distributed in a kaolinite matrix in sample 4673; c Ti oxides subjected to corrosion and filled with authigenic quartz in sample 4777; d Ti oxides subjected to corrosion and filled with kaolinite in sample 4777. Key: Kln, kaolinite; Qtz, quartz

Figure 9

Fig. 8 SEM back-scattered electron images of trace minerals in sample 4673: a apatite distributed in a kaolinite matrix; b ilmenite in kaolinite; c crandallite and pyrite in kaolinite; d florencite in kaolinite; e euhedral pyrite in kaolinite; f galena. Key: Kln, kaolinite; Ap, apatite; Ilm, ilmenite; Crd, crandallite; Flr, florencite; Py, pyrite; Gn, galena

Figure 10

Fig. 9 SEM back-scattered electron images of siderite and goethite in sample 4673: a well crystallized siderite; b and c siderite subjected to corrosion; d goethite with a bell-emulsion shape. Key: Sd, siderite; Kln, kaolinite; Gt, goethite

Figure 11

Table 3 a Sample; as-determined moisture, ash, and total S; ash-basis major oxides determined at CAER. b Sample, ash-basis (%) major oxides determined at CUMT

Figure 12

Table 4 Sample; ash basis (µg/g) minor elements from Li through Nb; World coal average (ash basis), 2 × World coal average, and 5 × World coal average at bottom of table (after Ketris & Yudovich, 2009).

Figure 13

Table 5 Sample; ash basis (µg/g) minor elements from Mo through U; World coal average (ash basis), 2 × World coal average, and 5 × World coal average at bottom of table (after Ketris & Yudovich, 2009).

Figure 14

Table 6 Sample; ash basis (µg/g) REE plus Sc and Y; World coal average (ash basis), 2 × World coal average, and 5 × World coal average at bottom of table (after Ketris & Yudovich, 2009)

Figure 15

Table 7 Sample; UCC-normalized REE values (after Taylor & McLennan, 1985)

Figure 16

Table 8 Sample; Light (L) vs. Heavy (H) distribution, EuN/EuN*, CeN/CeN*, GdN/GdN*, total REE, REE + Y (REY), REY + Sc (REYSc, Light REE/Heavy REE (LREE/HREE)

Figure 17

Fig. 10 Upper continental crust-normalized REE distributions for all of the studied samples. Normalization after Taylor & McLennan (1985)

Figure 18

Fig. 11 Upper continental crust-normalized REE distributions for the samples with the highest normalized Lu. Normalization after Taylor & McLennan (1985)

Figure 19

Fig. 12 GdN/GdN* vs. CeN/CeN* distribution showing the locations of coal data from Hower et al. (1999)

Figure 20

Fig. 13 a Principal components analysis (PCA) distribution for selected variables for all of the samples. Note that the vectors for LREE/HREE and GdN/GdN* overlap at this scale. b Outlier distribution for all samples

Figure 21

Table 9 Principal components analysis parameters for the analysis of all samples

Figure 22

Fig. 14 a Principal components analysis (PCA) distribution for selected variables for the tonstein samples. Note that the vectors for LREE/HREE and GdN/GdN* overlap at this scale. b Outlier distribution for all samples

Figure 23

Table 10 Principal components analysis parameters for analysis of the tonstein

Figure 24

Fig. 15 REE vs. Zr + Nb (ppm; ash basis) for all samples

Figure 25

Fig. 16 Al2O3/TiO2 vs. Zr + Nb (ppm; ash basis) for all samples

Figure 26

Fig. 17 Zr vs. Y (both ppm; ash basis) for all samples

Figure 27

Fig. 18 Nb vs. Ta (both ppm; ash basis) for tonstein, weathered tonstein, floor, and coal

Figure 28

Fig. 19 Rock classification based on Nb/Y vs. Zr/TiO2 after Winchester and Floyd (1977) and Vergunov et al. (2022)