In Situ Lung Dust Analysis by Automated Field Emission Scanning Electron Microscopy With Energy Dispersive X-ray Spectroscopy: A Method for Assessing Inorganic Particles in Lung Tissue From Coal Miners.

CONTEXT.­: Overexposure to respirable coal mine dust can cause severe lung disease including progressive massive fibrosis (PMF). Field emission scanning electron microscopy with energy dispersive x-ray spectroscopy (FESEM-EDS) has been used for in situ lung dust particle analysis for evaluation of disease etiology. Automating such work can reduce time, costs, and user bias. OBJECTIVE.­: To develop and test an automated FESEM-EDS method for in situ analysis of inorganic particles in coal miner lung tissue. DESIGN.­: We programmed an automated FESEM-EDS procedure to collect particle size and elemental data, using lung tissue from 10 underground coal miners with PMF and 4 control cases. A statistical clustering approach was used to establish classification criteria based on particle chemistry. Data were correlated to PMF/non-PMF areas of the tissue, using corresponding brightfield microscopy images. Results for each miner case were compared with a separate corresponding analysis of particles recovered following tissue digestion. RESULTS.­: In situ analysis of miner tissues showed higher particle number densities than controls and densities were generally higher in PMF than non-PMF areas. Particle counts were typically dominated by aluminum silicates with varying percentages of silica. Compared to digestion results for the miner tissues, in situ results indicated lower density of particles (number per tissue volume), larger size, and a lower ratio of silica to total silicates-probably due to frequent particle clustering in situ. CONCLUSIONS.­: Automated FESEM-EDS analysis of lung dust is feasible in situ and could be applied to a larger set of mineral dust-exposed lung tissues to investigate specific histologic features of PMF and other dust-related occupational diseases.

Characterizing Lung Particulates Using Quantitative Microscopy in Coal Miners With Severe Pneumoconiosis.

CONTEXT.­: Current approaches for characterizing retained lung dust using pathologists' qualitative assessment or scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) have limitations. OBJECTIVE.­: To explore polarized light microscopy coupled with image-processing software, termed quantitative microscopy-particulate matter (QM-PM), as a tool to characterize in situ dust in lung tissue of US coal miners with progressive massive fibrosis. DESIGN.­: We developed a standardized protocol using microscopy images to characterize the in situ burden of birefringent crystalline silica/silicate particles (mineral density) and carbonaceous particles (pigment fraction). Mineral density and pigment fraction were compared with pathologists' qualitative assessments and SEM/EDS analyses. Particle features were compared between historical (born before 1930) and contemporary coal miners, who likely had different exposures following changes in mining technology. RESULTS.­: Lung tissue samples from 85 coal miners (62 historical and 23 contemporary) and 10 healthy controls were analyzed using QM-PM. Mineral density and pigment fraction measurements with QM-PM were comparable to consensus pathologists' scoring and SEM/EDS analyses. Contemporary miners had greater mineral density than historical miners (186 456 versus 63 727/mm3; P = .02) and controls (4542/mm3), consistent with higher amounts of silica/silicate dust. Contemporary and historical miners had similar particle sizes (median area, 1.00 versus 1.14 µm2; P = .46) and birefringence under polarized light (median grayscale brightness: 80.9 versus 87.6; P = .29). CONCLUSIONS.­: QM-PM reliably characterizes in situ silica/silicate and carbonaceous particles in a reproducible, automated, accessible, and time/cost/labor-efficient manner, and shows promise as a tool for understanding occupational lung pathology and targeting exposure controls.

Respirable silica particles in coal mine dust: An image library dataset collected using scanning electron microscopy with energy dispersive X-ray spectroscopy.

This dataset comprises an image library of 282 respirable silica particles. The particles were identified in samples of respirable coal mine dust (RCMD) collected in numerous US underground mines, and samples of lab-generated respirable dust that were created using the primary dust source materials (e.g., raw coal and rock) obtained from those mines. (A limited number of particles were also identified in samples generated from silica-containing reference materials.) Silica particle identification was done by scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), and then each particle was imaged and analyzed at both low (5 kV) and high (20 kV) accelerating voltage. SEM micrographs were captured at high magnification (i.e., 5000-20,000 ×) and overlaid with elemental maps to visually indicate relative Si and Al content; spectra were also collected to determine Si and Al % in each particle. This dataset can inform the understanding of real respirable silica particles in coal mine environments, which may differ from idealized (i.e., pure, independent) silica particles. The dataset therefore provides valuable context for the design and interpretation of research related to: respirable silica exposure studies, sample analysis and monitoring techniques, or dust control.

Historical shift in pathological type of progressive massive fibrosis among coal miners in the USA.

BACKGROUND: Pneumoconiosis among coal miners in the USA has been resurgent over the past two decades, despite modern dust controls and regulatory standards. Previously published studies have suggested that respirable crystalline silica (RCS) is a contributor to this disease resurgence. However, evidence has been primarily indirect, in the form of radiographic features. METHODS: We obtained lung tissue specimens and data from the National Coal Workers' Autopsy Study. We evaluated specimens for the presence of progressive massive fibrosis (PMF) and used histopathological classifications to type these specimens into coal-type, mixed-type and silica-type PMF. Rates of each were compared by birth cohort. Logistic regression was used to assess demographic and mining characteristics associated with silica-type PMF. RESULTS: Of 322 cases found to have PMF, study pathologists characterised 138 (43%) as coal-type, 129 (40%) as mixed-type and 55 (17%) as silica-type PMF. Among earlier birth cohorts, coal-type and mixed-type PMF were more common than silica-type PMF, but their rates declined in later birth cohorts. In contrast, the rate of silica-type PMF did not decline in cases from more recent birth cohorts. More recent year of birth was significantly associated with silica-type PMF. CONCLUSIONS: Our findings demonstrate a shift in PMF types among US coal miners, from a predominance of coal- and mixed-type PMF to a more commonly encountered silica-type PMF. These results are further evidence of the prominent role of RCS in the pathogenesis of pneumoconiosis among contemporary US coal miners.

Mining Tenure and Job Duties Differ Among Contemporary and Historic Underground Coal Miners With Progressive Massive Fibrosis.

OBJECTIVE: To characterize differences in mining jobs and tenure between contemporary (born 1930+, working primarily with modern mining technologies) and historic coal miners with progressive massive fibrosis (PMF). METHODS: We classified jobs as designated occupations (DOs) and non-DOs based on regulatory sampling requirements. Demographic, occupational characteristics, and histopathological PMF type were compared between groups. RESULTS: Contemporary miners ( n = 33) had significantly shorter mean total (30.4 years vs 37.1 years, P = 0.0006) and underground (28.8 years vs 35.8 years, P = 0.001) mining tenure compared with historic miners ( n = 289). Silica-type PMF was significantly more common among miners in non-DOs (30.1% vs 15.8%, P = 0.03) and contemporary miners (58.1% vs 15.2%, P < 0.0001). CONCLUSIONS: Primary jobs changed over time with the introduction of modern mining technologies and likely changed exposures for workers. Elevated crystalline silica exposures are likely in non-DOs and require attention.

Thermogravimetric analysis of respirable coal mine dust for simple source apportionment.

Resurgence of coal mine dust lung diseases in the central Appalachian region of the United States and elsewhere has spurred a range of efforts to better understand respirable coal mine dust (RCMD) exposures and sources. Thermogravimetric analysis (TGA) of RCMD samples can enable the dust mass to be fractionated into three main components: coal, non-carbonate minerals, and carbonates. These are expected to approximate, respectively, the three primary dust sources in many underground mines: the coal seam being mined, the surrounding rock strata (i.e., typically dominated by non-carbonate minerals) being drilled or mined along with the coal, and the rock dust products (i.e., typically made from carbonate-rich limestone or dolostone) being applied in the mine to mitigate explosibility hazards. As proof of concept, TGA was applied to respirable dust samples that were laboratory-generated from real source materials representing 15 mines. Except in the case of two mines, compositional results were generally consistent with expectations. TGA was also applied to RCMD samples collected in standard locations of 23 mines (including the 15 mines represented by the dust source materials). Results showed significantly different compositions with respect to sampling location and geographic region (i.e., within and outside of central Appalachia). To further interpret the RCMD results, a simple source apportionment model was built using the dust compositions yielded from the source materials analysis. Model results indicated that, on average, about twice as much dust was sourced from mining into rock strata than from mining the target coal seam. This finding is particularly important for mines extracting relatively large amounts of rock along with the coal or for mines that frequently encounter high-silica rock strata.

Updating "Characteristics of respirable dust in eight Appalachian coal mines: A dataset including particle size and mineralogy distributions, and metal and trace element mass concentrations" with expanded data to cover a total of 25 US mines.

A total of 171 sets respirable dust samples were collected from 25 underground coal mines in several regions of the United States. One sample from each set was analyzed by scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) to determine particle size and mineralogy distributions. Results from the first eight mines were presented in the original dataset (Sarver et al., 2019). Here, the dataset is updated to include results from all 25 mines and to further subclassify particle mineralogy using improved SEM-EDX routines. The current article presents particle mineralogy binned by size between about 100-10,000 nm on a per sample basis, and data is also available on a per particle basis. Discussion of the SEM-EDX data is included in a parallel research article "Particle size and mineralogy distributions in respirable dust samples from 25 US underground coal mines" (Sarver et al., 2021). Moreover, sequential digestions and analysis of the digestates by inductively coupled plasma-mass spectroscopy (ICP-MS) were used to estimate mass concentrations of potentially bioaccessible and total-acid soluble metals and trace elements in the respirable dust samples. Results are included here for a total of 76 samples representing 15 mines; results from first eight mines were presented in the original dataset (Sarver et al., 2019) and discussed in an earlier research article (Sarver et al., 2019).

Pathology and Mineralogy Demonstrate Respirable Crystalline Silica Is a Major Cause of Severe Pneumoconiosis in U.S. Coal Miners.

Rationale: The reasons for resurgent coal workers' pneumoconiosis and its most severe forms, rapidly progressive pneumoconiosis and progressive massive fibrosis (PMF), in the United States are not yet fully understood. Objectives: To compare the pathologic and mineralogic features of contemporary coal miners with severe pneumoconiosis with those of their historical counterparts. Methods: Lung pathology specimens from 85 coal miners with PMF were included for evaluation and analysis. We compared the proportion of cases with pathologic and mineralogic findings in miners born between 1910 and 1930 (historical) with those in miners born in or after 1930 (contemporary). Results: We found a significantly higher proportion of silica-type PMF (57% vs. 18%; P < 0.001) among contemporary miners compared with their historical counterparts. Mineral dust alveolar proteinosis was also more common in contemporary miners compared with their historical counterparts (70% vs. 37%; P < 0.01). In situ mineralogic analysis showed that the percentage (26.1% vs. 17.8%; P < 0.01) and concentration (47.3 × 108 vs. 25.8 × 108 particles/cm3; P = 0.036) of silica particles were significantly greater in specimens from contemporary miners compared with their historical counterparts. The concentration of silica particles was significantly greater when silica-type PMF, mineral dust alveolar proteinosis, silicotic nodules, or immature silicotic nodules were present (P < 0.05). Conclusions: Exposure to respirable crystalline silica appears causal in the unexpected surge of severe disease in contemporary miners. Our findings underscore the importance of controlling workplace silica exposure to prevent the disabling and untreatable adverse health effects afflicting U.S. coal miners.

A thermogravimetric analysis application to determine coal, carbonate, and non-carbonate minerals mass fractions in respirable mine dust.

Occupational lung diseases such as coal worker's pneumoconiosis, often called black lung, are caused by exposures to respirable coal mine dust. Dust composition is increasingly understood as an important disease factor, and it can vary significantly depending on dust source materials and generation processes. For regulatory compliance purposes, the mass concentration and quartz percentage of respirable dust are monitored in U.S. coal mines, but the whole composition is not typically determined. Previous work has indicated that thermogravimetric analysis (TGA) can be used to apportion the respirable dust mass to three important component fractions (i.e., coal, non-carbonate minerals, and carbonate), which should generally correlate with three different dust sources (i.e., coal strata, rock strata, and limestone rock dusting products being applied in the mine). However, a primary shortcoming of that previous work was use of fibrous sampling filters, which limited dust recovery and thus analytical accuracy. Here, an improved TGA application is presented using smooth polycarbonate filters. Based on experiments with laboratory-generated dust samples (masses ranging between 95-1,319 µg), the TGA-derived mass fractions (reported as percentage values) for all three components were found to generally be within ±10% of expected values.

Characteristics of respirable dust in eight appalachian coal mines: A dataset including particle size and mineralogy distributions, and metal and trace element mass concentrations.

Respirable dust samples were collected in several key locations of eight underground coal mines in central and northern Appalachia. In total, there were 76 unique sampling events (i.e., specific location in a specific mine). Here, we present data from each event describing particle size and mineralogy class distributions across the ∼100-10,000nm size range, which were determined using SEM-EDX; and estimated mass concentrations of potentially bioaccessible and total acid-soluble metals and trace elements, which were determined using sequential digestions with digestate analysis by ICP-MS. Discussion of this dataset is included in a companion research article "Beyond conventional metrics: Comprehensive characterization of respirable coal mine dust" Sarver et al., 2019.

A field study on the possible attachment of DPM and respirable dust in mining environments.

Typcial monitoring procedures for diesel particulate matter (DPM) in mines include the collection of filter samples using particle size selectors. The size selectors are meant to separate the DPM, which is generally considered to occur in the submicron range (i.e., < 0.8 µm), from larger dust particles that could present analytical interferences. However, previous studies have demonstrated that this approach can sometimes result in undersampling, therefore, excluding significant fractions of the DPM mass. The excluded fraction may represent oversized DPM particles, but another possibility is that submicron DPM attaches to supramicron dust particles such that it is effectively oversized. To gain insights into this possibility, a field study was conducted in an underground stone mine. Submicron, respirable, and total airborne particulate filter samples were collected in three locations to determine elemental carbon (EC) and total carbon (TC), which are commonly used as analytical surrogates for DPM. Concurrent with the collection of the filter samples, a low-flow sampler with an electrostatic precipitator was also used to collect airborne particulates onto 400-mesh copper grids for analysis by transmission electron microscope (TEM). Results indicated that, while typical submicron sampling did account for the majority of DPM mass in the study mine, DPM-dust attachment can indeed occur. The effect of exposure to such attached particulates has not been widely investigated.

Interactive effects of water quality, physical habitat, and watershed anthropogenic activities on stream ecosystem health.

Ecological degradation of streams remains a major environmental concern worldwide. While stream restoration has received considerable attention, mitigation efforts focused on the improvement of physical habitat have not proven completely effective. Several small-scale studies have emphasized that effective restoration strategies require a more holistic understanding of the variables at play, although the generalization of the findings based on the small-scale studies remains unclear. Using a comprehensive statewide stream monitoring database from West Virginia (WV), a detailed landscape dataset, and a machine learning algorithm, this study explores the interactive impacts of water quality and physical habitat on stream ecosystem health as indicated by benthic macroinvertebrate scores. Given the long history of energy extraction in this region (i.e., coal mining and oil/gas production), investigation of energy extraction influences is highlighted. Our results demonstrate that a combination of good habitat and low specific conductance is generally associated with favorable benthic macroinvertebrate scores, whereas poor habitat combined with water quality conditions typically indicative of high ionic strength are associated with impaired stream status. In addition, streams impacted by both energy extraction and residential development had a higher percentage of impairment compared to those impacted predominantly by energy extraction or residential development alone. While water quality played a more important role in the ecosystem health of streams impacted primarily by energy extraction activities, habitat seems to be more influential in streams impacted by residential development. Together, these findings emphasize that stream restoration strategies should consider interactive effects of multiple environmental stressors tailored to specific sites or site types - as opposed to considering a single stressor or multiple stressors separately.

Tracking the downstream impacts of inadequate sanitation in central Appalachia.

Poor sanitation in rural infrastructure is often associated with high levels of fecal contamination in adjacent surface waters, which presents a community health risk. Although microbial source tracking techniques have been widely applied to identify primary remediation needs in urban and/or recreational waters, use of human-specific markers has been more limited in rural watersheds. This study quantified the human source tracking marker Bacteroides-HF183, along with more general fecal indicators (i.e. culturable Escherichia coli and a molecular Enterococcus marker), in two Appalachian streams above and below known discharges of untreated household waste. Although E. coli and Enterococcus were consistently recovered in samples collected from both streams, Bacteroides-HF183 was only detected sporadically in one stream. Multiple linear regression analysis demonstrated a positive correlation between the concentration of E. coli and the proximity and number of known waste discharge points upstream; this correlation was not significant with respect to Bacteroides-HF183, likely due to the low number of quantifiable samples. These findings suggest that, while the application of more advanced source targeting strategies can be useful in confirming the influence of substandard sanitation on surface waters to justify infrastructure improvements, they may be of limited use without concurrent traditional monitoring targets and on-the-ground sanitation surveys.

4-MCHM sorption to and desorption from granular activated carbon and raw coal.

4-Methylcyclohexanemethanol (4-MCHM) is a saturated higher alicyclic primary alcohol that is used in the froth flotation process for cleaning coal. In early 2014, a large spill of crude chemical (containing primarily 4-MCHM) to the Elk River near Charleston, WV contaminated the local water supply. Carbon filters at the affected water treatment facility quickly became saturated, and the contaminated water was distributed to nearby homes and businesses. Sorption of 4-MCHM to granular activated carbon (GAC) was studied in the laboratory using head space (HS) analysis via gas chromatography with a flame ionization detector (GC-FID). Sorption to raw coal was also investigated, since this material may be of interest as a sorbent in the case of an on-site spill. As expected, sorption to both materials increased with decreased particle size and with increased exposure time; although exposure time proved to be much more important in the case of GAC than for coal. Under similar conditions, GAC sorbed more 4-MCHM than raw coal (e.g., 84.9 vs. 63.1 mg/g, respectively, for 20 × 30 mesh particles exposed to 860 mg/L 4-MCHM solution for 24 h). Desorption from both materials was additionally evaluated. Interestingly, desorption of 4-MCHM on a mass per mass basis was also higher for GAC than for raw coal. Overall, results indicated that GAC readily sorbs 4-MCHM but can also readily release a portion of the chemical, whereas coal sorbs somewhat less 4-MCHM but holds it tightly.