Last data update: Jul 11, 2025. (Total: 49561 publications since 2009)
Records 1-6 (of 6 Records) |
Query Trace: Parks DA[original query] |
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Applying finite mixture models to quantify respirable dust mass in coal and metal-nonmetal mines using fourier transform infrared spectroscopy
Weakley AT , Parks DA , Miller AL . Appl Spectrosc 2024 37028241296158 Respirable dust mass is a prevalent occupational health hazard to the mining workforce. Mineral matrices observed in the mine environment are complex, time varying, and heterogeneous. This poses a challenge to assessing dust exposure using Fourier transform infrared (FT-IR) spectrometry as calibrations for constituent dust species (e.g., crystalline silica) have historically been trained using homogeneous standards or simple mixtures therein. Investigations have considered direct-on-filter analysis, which collects FT-IR spectra directly from sampling filters for calibration, as an alternative. Direct-on-filter analysis using a partial least squares (PLS) method has gained particular interest recently due to the potential to rapidly quantify multiple species from a single filter at the mine site. By design, heterogeneity, and its presumed impact on method accuracy, cannot be addressed in the laboratory when using a direct-on-filter approach motivating the need for more advanced calibration approaches. When heterogeneity is present, mixture of experts (MoE) finite mixture models offer a promising and novel alternative to PLS direct-on-filter analysis as MoE incorporates cluster discovery, regression, and outlier identification into model fitting. Three MoE models of increasing complexity were tasked with determining respirable dust mass in 243 field samples from thirteen active coal, limestone, sandstone, and silver mines. All MoE models, including those using only "expert" spectroscopic predictors or a combination of expert and categorical "gate" variables (e.g., mine type), significantly outperform PLS in terms of accuracy (α = 0.05). Decomposing bias by mine type shows that accuracy generally improves across all types considered when MoE models are not overfitted. The MoE method's effectiveness was linked to its ability to endogenously classify outliers as well as possibly to the use of an additional cluster model for mass predictions. Overall, MoE methods appear as a capable and novel tool to addressing problems of heterogeneity for direct-on-filter quantitative analysis. |
Reducing dust and respirable crystalline silica near conveyors using a hybrid dust control system
Parks DA , King GW , Koski BD , Bierie GS , Sunderman CB , Wilson SE , Miller AL . Min Metall & Explor 2024 Occupational exposures to respirable dusts and respirable crystalline silica (RCS) is well established as a health hazard in many industries including mining, construction, and oil and gas extraction. The U.S. National Institute for Occupational Safety and Health (NIOSH) is researching methods of controlling fugitive dust emissions at outdoor mining operations. In this study, a prototype engineering control system to control fugitive dust emissions was developed combining passive subsystems for dust settling with active dust filtration and spray-surfactant dust suppression comprising a hybrid system. The hybrid system was installed at an aggregate production facility to evaluate the effectiveness of controlling fugitive dust emissions generated from two cone crushers and belt conveyors that transport crushed materials. To evaluate effectiveness of the system, area air measurements (n = 14 on each day for a total of 42 samples) for respirable dust were collected by NIOSH before, during, and after the installation of the dust control system in the immediate vicinity of the crushers and the nearby conveyor transfer point. Compared to pre-intervention samples, over short periods of time, geometric mean concentrations of airborne respirable dust were reduced by 37% using passive controls (p = 0.34) but significantly reduced by 93% (p < 0.0001) when the full hybrid system was installed. This proof-of-concept project demonstrated that the combined use of active and passive dust controls along with a spray surfactant can be highly effective in controlling fugitive dust emissions even with minimal use of water, which is desirable for many remote mining applications. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024. |
Evaluation of a non-dispersive infrared spectrometer for quantifying organic and elemental carbon in diesel particulate matter
Parks DA , Zhao Y , Griffiths PR , Miller AL . Aerosol Sci Technol 2024 Diesel particulate matter (DPM) is a common and well-known health hazard in the mining environment. The regulatory method for monitoring both the organic and elemental carbon (OC, EC) portions of DPM is a laboratory-based thermal-optical method with a typical turnaround time of one week. In order to evaluate exposure levels and take corrective action prior to overexposure, a portable real-time device capable of quantifying both OC and EC is needed. To that end, researchers from the National Institute for Occupational Safety and Health (NIOSH) designed and tested the feasibility of a device based on bandpass optical filters that target key infrared wavelengths associated with DPM and its spectroscopic baseline. The resulting device, referred to here as a non-dispersive infrared (NDIR) spectrometer could serve as the basis of a cost-effective, field-portable alternative to the laboratory thermal-optical method. The limits of quantification (LOD) indicate that the NDIR spectrometer can quantify EC, OC, and TC provided they are present at 20, 37, and 46 μg/m3 or more, respectively. In the event that the NDIR spectrometer is integrated with a sampler and filter tape the LOD is estimated to be reduced to 13, 7, and 10 μg/m3 for EC, OC, and TC, respectively. These LOD estimates assume a face velocity of 59 cm/s and a sampling time of 30 min. ©, This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 USC. 105, no copyright protection is available for such works under US Law. |
Quantifying elemental and organic carbon in diesel particulate matter by mid-infrared spectrometry
Parks DA , Griffiths PR , Weakley AT , Miller AL . Aerosol Sci Technol 2021 55 (9) [Epub ahead of print] A method for the quantification of airborne organic carbon (OC) and elemental carbon (EC) within aerosolized diesel particulate matter (DPM) is described in this article. DPM is a known carcinogen encountered in many industrial workplaces (notably mining) and in the ambient atmosphere. The method described here collects DPM particles onto a quartz fiber filter, after which reflection-mode infrared spectra are measured on a mid-infrared Fourier transform (FT-IR) spectrometer. Several infrared absorption bands are investigated for their efficacy in quantifying OC and EC. The thermo-optical (T-O) method is used to calibrate a linear regression model to predict OC and EC from the infrared spectra. The calibrated model, generated from laboratory DPM samples, is then utilized to quantify OC and EC in mine samples obtained from two metal mine locations under a variety of operating conditions. The feasibility of further improving these results by partial least squares (PLS) regression was investigated. A single calibration that is broadly applicable would be considered an improvement over currently available portable instruments, which require aerosol-specific calibration. |
A predictive model for elemental carbon, organic carbon and total carbon based on laser induced breakdown spectroscopy measurements of filter-collected diesel particulate matter
McLaughlin RP , Parks DA , Grubb AI , Mason GS , Miller AL . Spectrochim Acta Part B At Spectrosc 2020 168 105871 Diesel particulate matter (DPM) produced from vehicle and equipment diesel exhaust (DE) is a common industrial inhalation hazard, particularly in underground mines. The sub-micron particles of DPM (< 800 nm) are composed of a carbonaceous core operationally defined as elemental carbon (EC), which are irregularly arranged graphitic- like "spherule" structures, and a wide-variety of adsorbed, semivolatile organic carbon compounds (OC). In addition to associating chronic exposure to DPM with immunological, respiratory and cardiovascular health issues, the International Agency for Research on Cancer (IARC) categorizes this material as carcinogenic to humans, with workers regularly exposed to it demonstrating an elevated risk for lung cancer. Given the long-term health risks associated with repeated and prolonged exposure to DPM, efforts are being directed at reducing the exposure of miners and other workers who may encounter high levels of DPM over the course of a typical working day. |
Towards a field-portable real-time organic and elemental carbon monitor
Parks DA , Raj KV , Berry CA , Weakley AT , Griffiths PR , Miller AL . Min Metall Explor 2019 36 (4) 765-772 Diesel particulate matter (DPM) has been classified as a carcinogen to humans by the International Agency for Research on Cancer. As a result of its potential carcinogenic nature, DPM exposure is regulated by the Mine Safety and Health Administration. Currently, diesel emissions in the workplace are monitored by collecting the aerosol onto filters, which are then sent to a laboratory for thermal-optical analysis using the NIOSH method 5040. This process can take days or even weeks, and workers can potentially be exposed to excessive levels of DPM before the problem is identified. Moreover, the delay involved in getting the loaded filter to the lab inevitably means the loss of some of the more volatile organic carbon. To remedy this delay, researchers from the National Institute for Occupational Safety and Health are seeking to develop a field-portable, real-time method for measuring elemental and organic carbons in DPM aerosols. In the current study, the use of mid-infrared spectrometry was investigated. It is believed that mid-infrared spectroscopy is more suitable for use in a real-time field-portable device than thermo-optical analysis methods. This article presents a method for measuring organic carbon (OC) and elemental carbon (EC) in DPM for a broad range of OC/EC ratios. The method has been successfully applied to laboratory-generated and mine samples. |
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