Occurrence Of Elements In Coal Research Articles

Advocating the Use of Bayesian Network in Analyzing the Modes of Occurrence of Elements in Coal.

Modes of occurrence of elements in coal are important because they can be used not only to understand the origin of inorganic components in coal but also to determine the impact on the environment and human health and the deposition process of coal seams as well. Statistical analysis is one of the commonly used indirect methods used to analyze the modes of occurrence of elements in coal, among which hierarchical clustering is widely used. However, hierarchical clustering may lead to misleading results due to its limitation that it focuses on the clusters of elements rather than a single element. To tackle this issue, we use the first part of a well-known Bayesian network structure learning algorithm, i.e., Peter-Clark (PC) algorithm, to explore the relationships of the coal elemental data and then infer modes of occurrence of elements in coal. A data set containing 95 Late Paleozoic coal samples from the Datanhao and Adaohai mines in Inner Mongolia, China, is used for the performance evaluation. Analytical results show that many instructive and surprising insights can be concluded from the first part of the PC algorithm. Compared with the hierarchical clustering algorithm, the first part of the PC algorithm demonstrates superiority in analyzing the modes of occurrence of elements in coal.

Application of self-organizing maps to coal elemental data

Understanding the modes of occurrence of elements in coal is important, not only to help properly evaluate the impacts of potentially toxic elements on the environment and human health but also to provide technical guidance for recovering critical elements from coal ash. Statistical and multivariate data analysis methods have widely been used, together with physical and chemical methods, to determine the modes of occurrence of elements in coal. However, some of the statistical methods, e.g., average linkage hierarchical clustering algorithm have some disadvantages (e.g., statistical errors and poor visualization). A self-organizing map is an unsupervised artificial neural network, and it is known for its high data mining capability and excellent data visualization. In contrast to the average linkage hierarchical clustering algorithm that is commonly used for analyzing the modes of occurrence of elements in coal, the self-organizing map algorithm can provide a topological relationship among elements instead of merely providing the groups to which the elements belong. This paper focuses on the application of self-organizing map to coal elemental data for analyzing the modes of occurrence of elements in coal. Samples used in this study are from the Adaohai, Hailiushu, and Datanhao mines, all located in the Daqingshan Coalfield, Inner Mongolia, China. The results obtained from the self-organizing map algorithm are compared with those produced by average linkage hierarchical clustering algorithm. Based on the previous investigations (mainly direct methods) and further analysis, it can be concluded that the results from the self-organizing map algorithm in this investigation are more consistent with the geochemical nature and previous investigations by direct methods than those from average linkage hierarchical clustering algorithm. Consequently, the self-organizing map algorithm is a new reliable and intuitive method for analyzing the modes of occurrence of elements in coal.

Modes of occurrence of elements in high-germanium coals using correlation analysis algorithm

Modes of occurrence of elements in Ge-rich coals are important because they provide an understanding of Ge mineralization and insight into Ge behavior during coal combustion and the modes of occurrence for Ge in the resulting combustion products. Previous researchers showed that the leaching of granite by N2 – CO2 mixed hydrothermal solutions in the Lincang coal in southwest China led to the enrichment of Ge. Elevated Ge concentrations from leaching of granite by hydrothermal solutions have been established in the nearby Lincang Ge ore deposit; however, the influence of hydrothermal solutions, especially mixed hydrothermal solutions, on the modes of occurrence of elements in coal have not been quantitatively analyzed. In this paper, we focus on the quantitative analysis of the influence of mixed hydrothermal solutions on the modes of occurrence of elements in coal. Samples used in this study were collected from the Dazhai Mine, located in the Lincang Ge ore deposit, Yunnan Province, southwestern China. The correlation coefficients between pyrite, ash yield, Al2O3, and SiO2 versus elemental concentrations in coal are processed with the correlation analysis algorithm. The results show that a distinct break in pyrite content of ∼16.8 wt% as a threshold for different elemental modes of occurrence of elements as a result of hydrothermal fluids. The modes of occurrence of As and Hg changes from an organic-inorganic mixed affinity to predominantly in pyrite by the influence of volcanic hydrothermal fluids when the content of pyrite is higher than 16.8 wt%.

Coal elemental (compositional) data analysis with hierarchical clustering algorithms

The modes of occurrence for elements in coal are extremely important for deciphering geological process of coal formation and for anticipating the technological behavior and environmental and health impacts derived from coal utilization. Hierarchical clustering algorithm has been widely adopted to investigate the modes of occurrence of elements in coal. The traditional statistics (e.g., Pearson correlation, Euclidean distance) for the elemental data of coal may lead to misinterpretation because the elemental data of coal are of compositional nature and follow the rules of Aitchison geometry. This work applied log-ratio transformations in order to overcome this problem. Different hierarchical clustering algorithms with various data transformations can infer modes of occurrence for coal elements, but which algorithm is optimum deserves to be investigated. In this paper, we discuss four commonly used hierarchical clustering algorithms utilizing pivot coordinates and weighted symmetric pivot coordinates (WSPC), two types of log-ratio transformations, to infer modes of occurrence of elements in coal, based on published coal elemental data. Results showed that the Pearson correlation produces more meaningful results than the Euclidean distance in clustering rare earth elements and Y. WSPC produces more interpretable results than those from pivot coordinates transformed data for these coal elemental data. Compared with the single, complete, and centroid, the average-linkage algorithm is indeed the optimum.

Average Linkage Hierarchical Clustering Algorithm for Determining the Relationships between Elements in Coal.

The modes of occurrence of elements in coal are important not only because they can provide insights into the sources of mineral matter in coal but also because they are vital in determining the behavior of their environmental and human health impacts. Besides a number of physical and chemical analyses for determining the modes of occurrence in coal, some statistical methods have been commonly adopted to investigate elements in coal. Among many statistical methods, the hierarchy clustering algorithm is the most common method for deducing modes of occurrence of elements in coal. However, different hierarchical clustering algorithms with a number of similarity measures sometimes result in different modes of occurrence of elements in coal, and subsequently in some cases, such results could be confusing. Therefore, which algorithm is more effective in determining the modes of occurrence in coal deserves to be investigated. In this paper, the data sets of coals from the Adaohai coal mine in Inner Mongolia, China, are used for this performance evaluation. From the analytical results with the average linkage hierarchical clustering algorithm on Adaohai coal samples, many instructive and surprising insights can be concluded. For example, selenium, Be, and Tl do not appear to be in agreement with geochemical principles, that is, substituting for P, associated with rare earth elements, and occurring in Fe-sulfides, respectively. In conclusion, the average linkage hierarchical clustering algorithm with correlation similarity is much better in the analysis of the geological processes than the previous statistical method used in Adaohai coal samples, that is, centroid linkage hierarchical clustering algorithm with Pearson correlation similarity.

Spatial Macroscale Variability of the Role of Mineral Matter in Concentrating Some Trace Elements in Bituminous Coal in a Coal Basin—A Case Study from the Upper Silesian Coal Basin in Poland

As there are numerous claims that the mode of occurrence of trace elements in coal influences the quality of the substrates as well as the course and results of the coal preparation processes, it is necessary to analyse the differences in the mode of occurrence of the elements in coal within a coal basin or a coal deposit. With the use of concentration distribution functions and the Pearson correlation coefficient, it was concluded that (1) mineral matter plays a significant and nearly constant or constant role in concentrating V, Cr, Co, As, Rb, Sr, Ba, and Pb in coal; (2) organic matter plays a stable role in concentrating Sn; and (3) there are significant differences in the role of organic and mineral matter in concentrating Mn, Ni, Cu, Zn, Mo, Cd, and Sb in coal throughout the USCB (Upper Silesian Coal Basin). Moreover, there was observed a difference in the mode of occurrence of Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Sn, and Sb in coal in the vertical profile of the USCB. At the same time, there were observed no differences and a stable significant role of mineral matter in concentrating V, As, Rb, Sr, Ba, and Pb in coal, while the role of the petrographic groups of the coal components in concentrating the elements in raw coal was differentiated. It is believed that the difference in the mode of occurrence of the trace elements in coal within coal seams and coal deposits is a geochemical regularity.

What do coal geochemistry statistics really mean?

Modes of occurrence of elements in coal have been widely investigated using different methods, including statistical methods, which, however, in some cases resulted in misleading interpretations. In order to verify this potential problem and find an effective solution, we selected a data set which contained comprehensive analyses of 27 coal bench samples with ash yields ranging from 3.66% to 46.56% in a single Paleozoic coal seam from the Haerwusu Surface Mine, Inner Mongolia, China. The correlation coefficients between the elemental concentrations versus ash yields were progressively calculated based on variations of ash yields (from the lowest to the highest). The elements were classified using k-means clustering algorithm and the Goldschmidt’s geochemical classification. The distinct break of ash yields of ~9%, in this case, has been determined for different modes of occurrence of elements in coals with ash yields lower and higher than this break. However, using traditional statistical methods for coal geochemistry analysis, i.e., using the full dataset without separating ash yields, it would not be possible to reach the rational interpretations of the elements modes of occurrence and sources but would result in misinterpretations.

Mineralogical and geochemical characteristics of the Permian coal from the Qinshui Basin, northern China, with emphasis on lithium enrichment

Comprehensive information about the concentrations, distribution, and modes of occurrence of elements in coal are important from the environmental and economic point of view. Although a great number of previous studies have investigated the geology of coalbed methane in the Qinshui Basin, only a few studies focused on the inorganic constituents in coal. More specifically, the mode of occurrences of valuable element Li in the No. 3 Coal is still unclear, although Li was found enriched. In this study, we present mineral characteristics, as well as multi-element data on the Permian No. 3 Coal from the Sucun and Gaohe Mines, Changzhi City, southern Qinshui Basin. The studied coals are characterized by low- to medium-ash yield (Ad = 5.72%- 28.18%, 12.34% on average), low volatile matter yield (Vdaf = 8.49–15.17%, 10.96% on average), suggesting a low volatile bituminous coal to semi-anthracite. NH4-illite and kaolinite are the main minerals in the coals detected by XRD, and trace amount of minerals calcite, dolomite, quartz, pyrite and diaspore can also be found. The major elements of the studied No. 3 coals are dominated by SiO2 and Al2O3, ranging 2.49–16.45 wt% and 2.13–12.9 wt% (on a whole-coal basis), respectively. Li is enriched in the No. 3 coals (5 < CC < 10). Li in the studied coals is positively correlated with Al2O3, SiO2 and ash yield, with the correlation coefficients (r) of 0.86, 0.8, and 0.78, respectively. The sequential leaching results show that 96.6%–99.4% of Li in the coals was removed by HF. The proportion of Li present as the ion-exchange form and water soluble form accounts for <1.1% and < 0.29% of the total Li respectively in the coals. Li in the studied coals are probably bound to clay minerals kaolinite and illite, residing mainly in non-exchangeable positions, either in the octahedral or pseudo-hexagonal sites.

Distribution of As, Hg and other trace elements in different size and density fractions of the Reshuihe high-sulfur coal, Yunnan Province, China

A Lopingian coal from the Reshuihe Mine in southwestern China contains high pyritic sulfur (5.2%) and trace elements including As (10.8μg/g), Hg (0.81μg/g), V (98.9μg/g), Co (15.7μg/g), Cu (47.5μg/g), Se (4.8μg/g) and Th (7.2μg/g). The variation of trace elements in coal samples of different size and density were investigated. The results showed that the vertical variation of As and Hg through the seam section is the result of hydrothermal activity. Arsenic and Hg are highly concentrated in coal layers far from the parting, roof and floor in vertical section. For example, the highest concentrations of As (44.3μg/g) and Hg (2.8μg/g) occur in ply 6, which is 40-cm vertically away from partings. Elements As, Hg, Co, Ni, Se, Sb and Tl occur mainly in pyrite; Be, F, Cs, Th and U are evenly distributed in clay minerals and organic components; V and Cr mainly occur in the organic portions of the coal. The As and Hg content generally increases with greater particle size and density, with content in the light fractions as low as 1.1 and 0.14μg/g, respectively, and as high as 75.8 and 3.8μg/g, respectively, in heavy fractions. Co, Ni, Se, Sb and Tl exhibit similar density dependence. Vanadium and Cr are more concentrated in lower-density fractions.The genetic type and mode of occurrence of elements in coal both exert a great impact on their removability; epigenetic and coarse minerals may be readily liberated by gravity separation. Elements associated with pyrite (e.g., As, Hg, Co, Ni, Cu, Se, Sb and Tl) demonstrate high removability; F, Th, U, V and Cr, which mainly occur in clay minerals and/or organic components of the coal, show a relatively low removability. Trace elements in particle size fractions 6–13mm and <0.5mm are most easily removed by gravity separation. In order to fully remove toxic elements from coal, it is suggested fractions with particle sizes of 3–6mm and 0.5–3mm be reduced in size to <0.5mm prior to gravity separation.

Assessment of aldosterone synthase (CYP11B2), mineralocorticoid receptor expression and markers of fetal cardiac gene reprogramming in rats exposed to fine particles

A Lopingian coal from the Reshuihe Mine in southwestern China contains high pyritic sulfur (5.2%) and trace elements including As (10.8 μg/g), Hg (0.81 μg/g), V (98.9 μg/g), Co (15.7 μg/g), Cu (47.5 μg/g), Se (4.8 μg/g) and Th (7.2 μg/g). The variation of trace elements in coal samples of different size and density were investigated. The results showed that the vertical variation of As and Hg through the seam section is the result of hydrothermal activity. Arsenic and Hg are highly concentrated in coal layers far from the parting, roof and floor in vertical section. For example, the highest concentrations of As (44.3 μg/g) and Hg (2.8 μg/g) occur in ply 6, which is 40-cm vertically away from partings. Elements As, Hg, Co, Ni, Se, Sb and Tl occur mainly in pyrite; Be, F, Cs, Th and U are evenly distributed in clay minerals and organic components; V and Cr mainly occur in the organic portions of the coal. The As and Hg content generally increases with greater particle size and density, with content in the light fractions as low as 1.1 and 0.14 μg/g, respectively, and as high as 75.8 and 3.8 μg/g, respectively, in heavy fractions. Co, Ni, Se, Sb and Tl exhibit similar density dependence. Vanadium and Cr are more concentrated in lower-density fractions.The genetic type and mode of occurrence of elements in coal both exert a great impact on their removability; epigenetic and coarse minerals may be readily liberated by gravity separation. Elements associated with pyrite (e.g., As, Hg, Co, Ni, Cu, Se, Sb and Tl) demonstrate high removability; F, Th, U, V and Cr, which mainly occur in clay minerals and/or organic components of the coal, show a relatively low removability. Trace elements in particle size fractions 6–13 mm and < 0.5 mm are most easily removed by gravity separation. In order to fully remove toxic elements from coal, it is suggested fractions with particle sizes of 3–6 mm and 0.5–3 mm be reduced in size to < 0.5 mm prior to gravity separation.

00/00015 The use of sequential leaching to quantify the modes of occurrence of elements in coal

Sequential leaching can be used to rapidly and accurately quantify the modes of occurrence of inorganic elements in coal. Nine as-mined coals and seven commercially cleaned coals from major coal producing areas (Appalachian, Eastern Interior and the Powder River basins) were sequentially leached with 1 N ammonium acetate, 2N HCl, 48% HF and 2N HNO{sub 3}. The reproducibility of the technique is about {+-}5 to 10% absolute. The resulting mass balances from the multi-technique analyses of both the leachates and the residual solids provide a high degree of confidence in the procedure. Modes of occurrence were quantified for 15 environmentally sensitive elements. Generally more than 50 percent of the As and Fe are leached by HNO{sub 3} indicating an association with pyrite. With few exceptions, more than 50% of the Be and 40% of the Cr was leached by HF indicating an association with the aluminosilicates. Se and Hg are associated with disulfides in most coals but as much as 95% of the Se and 70% of the Hg in some cases remained unleached by any solvent indicating an organic association. Co, Ni, Sb, Th and U have multiple modes of occurrence in each coal. Mn is primarily associated withmore » the carbonates. Pb, Zn and Cd are primarily associated with mono- and di-sulfides but also have a significant organic association.« less

00/00008 Mode of occurrence of minor elements in coal

00/00008 Mode of occurrence of minor elements in coal

96/04626 Modes of occurrence of trace elements in coal: Geochemical constraints from XAFS and PIXE spectroscopic analysis of advanced coal cleaning tests

96/04626 Modes of occurrence of trace elements in coal: Geochemical constraints from XAFS and PIXE spectroscopic analysis of advanced coal cleaning tests

95/01156 Modes of occurrence of trace elements in coal from XAFS spectroscopy

95/01156 Modes of occurrence of trace elements in coal from XAFS spectroscopy

95/01165 Reliability and reproductibility of leaching procedures to estimate the modes of occurrence of trace elements in coal

95/01165 Reliability and reproductibility of leaching procedures to estimate the modes of occurrence of trace elements in coal

The geochemistry of the halogens

Coal, containing all the elements that are present in nature and more than 200 minerals, has a complex chemical structure, making it one of the most complex geological materials. Inorganic matter in coal includes minerals (in which element concentration may vary from trace to major), non-crystalline mineraloids, and elements with non-mineral associations such as those occurring in pore waters, organically bound, or in an organic association. Understanding the modes of occurrence of elements in coal is important because, theoretically, they provide useful information on peat deposition, diagenesis and epigenesis of coal, coal-hosted basin formation, and the regional geological background or evolution. Practically, the modes of occurrence of elements play a significant role in affecting coal mining, coal preparation, coal combustion, and coal utilization, and in exerting adverse effects on both the environment and human health. The modes of occurrence of critical elements in coal and coal ash are key factors for designing the method and technology required for extracting critical metals from coal or coal ash. In this paper, the following aspects are reviewed, including the modes of occurrence of 73 elements and rare gases that occur in coal (with the exceptions of organically associated C, H, O, and N), the definition of modes of occurrence and their practical and academic significance, analytical methods for determining modes of occurrence of elements in coal and their advantages and limitations, and reported modes of occurrence of elements in coal and their likely associations.Overall, the modes of occurrence of elements in coal are classified into inorganic, organic, and intimate organic associations. Although there are common modes of occurrence of many elements in coal, there are many exceptions and most, if not all, elements have multiple modes of occurrence. Each mode of occurrence of an element may also show different levels of confidence, namely, certain, probable, possible, doubtful, unlikely, and may occur in coal with different frequencies, namely abundant, common, uncommon, rare, and unlikely. For each element, the authors present concluding comments viewpoints on the modes of occurrence of almost each element in coal that is listed in the old literature.The different modes of occurrence for each element in different coals depend on the geological conditions of coal formation, and do not necessarily indicate inconsistency in the reported results. However, due to limitations of the analytical methods used, some data relating the modes of occurrence of elements in coal are not convincing, and in some cases are invalid or even misleading. Overall, while precisely determining the concentrations of many elements in coal is not difficult, determination of the modes of occurrence of some elements, particularly those with low concentrations and high volatility, is still a challenge. Although analytical methods certainly play critical roles in determining the modes of occurrence of elements in coal, in-depth understanding of the nature of the coal and host-rocks and the geological background of coal formation is very useful in investigating when and how these modes of occurrence of elements were formed.