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Particle size distribution from biomass combustion is an important parameter as it affects air quality, climate modelling and health effects. To date, particle size distributions reported from prior studies vary not only due to difference in fuels but also difference in experimental conditions. This study aims to report characteristics of particle size distributions in well controlled repeatable lab scale biomass fires for southwestern United States fuels with focus on chaparral. The combustion laboratory at the United States Department of Agriculture-Forest Service's Fire Science Laboratory (USDA-FSL), Missoula, MT provided a repeatable combustion and dilution environment ideal for measurements. For a variety of fuels tested the major mode of particle size distribution was in the range of 29 to 52 nm, which is attributable to dilution of the fresh smoke. Comparing mass size distribution from FMPS and APS measurement 51–68% of particle mass was attributable to the particles ranging from 0.5 to 10 μm for PM₁₀. Geometric mean diameter rapidly increased during flaming and gradually decreased during mixed and smoldering phase combustion. Most fuels produced a unimodal distribution during flaming phase and strong biomodal distribution during smoldering phase. The mode of combustion (flaming, mixed and smoldering) could be better distinguished using the slopes in MCE (Modified Combustion Efficiency) vs. geometric mean diameter than only using MCE values

Miners face a variety of respiratory hazards while on the job, including exposure to silica dust which can lead to silicosis, a potentially fatal lung disease. Currently, field-collected filter samples of silica are sent for laboratory analysis and the results take weeks to be reported. Since the mining workplace is constantly moving into new and often different geological strata with changing silica levels, more timely data on silica levels in mining workplaces could help reduce exposures. Improvements in infrared (IR) spectroscopy open the prospect for end-of-shift silica measurements at mine sites. Two field-portable IR spectrometers were evaluated for their ability to quantify the mass of silica on filter samples loaded with known amounts of either silica or silica-bearing coal dust (silica content ranging from 10-200 µg/ filter). Analyses included a scheme to correct for the presence of kaolin, which is a confounder for IR analysis of silica. IR measurements of the samples were compared to parallel measurements derived using the laboratory-based U.S. Mine Safety and Health Administration P7 analytical method. Linear correlations between Fourier transform infrared (FTIR) and P7 data yielded slopes in the range of 0.90-0.97 with minimal bias. Data from a variable filter array spectrometer did not correlate as well, mainly due to poor wavelength resolution compared to the FTIR instrument. This work has shown that FTIR spectrometry has the potential to reasonably estimate the silica exposure of miners if employed in an end-of-shift method.

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Researchers at NIOSH are developing methods for characterizing ultrafine aerosols in workplaces. One method includes the detailed analysis of collected particles using electron microscopy (EM). In order to collect samples for EM at remote workplaces including mining and manufacturing facilities, researchers have developed a handheld electrostatic precipitator (ESP) particle sampler capable of collecting airborne particles including nanoscale materials, for subsequent EM analysis. The handheld ESP has been tested in the laboratory and is currently undergoing beta testing in the field. Gross collection efficiencies were measured with a CPC and net efficiencies by EM analysis of collected samples. Using laboratory-generated NaCl aerosols in the 30-400 nm size range at a flow rate of 55 cc/min and ESP operating voltages between 5.6-6.8 kV, both gross and net efficiencies were measured and showed a similar correlation with voltage, with maximum efficiency of approximately 86% at 6.4 kV. EM images from samples were also used to estimate particle size distributions of the original aerosols and the size-dependent deposition was evaluated for upstream versus downstream locations on the sample media. Results suggest that the number concentration and particle size distribution of sampled aerosols may potentially be estimated from a single ESP sample, but that the accuracy and repeatability of such quantification need to be investigated and refined. NIOSH is planning to license the ESP sampler for commercial manufacturing.

Recent studies suggest that trace metals emitted by internal combustion engines are derived mainly from combustion of lubrication oil. This hypothesis was examined by investigation of the formation of particulate matter emitted from an internal combustion engine in the absence of fuel-derived soot. Emissions from a modified CAT 3304 diesel engine fueled with hydrogen gas were characterized. The role of organic carbon and metals from lubrication oil on particle formation was investigated under selected engine conditions. The engine produced exhaust aerosol with log normal-size distributions and particle concentrations between 10 5 and 10 7 cm -3 with geometric mean diameters from 18 to 31 nm. The particles contained organic carbon, little or no elemental carbon, and a much larger percentage of metals than particles from diesel engines. The maximum total carbon emission rate was estimated at 1.08 g h -1 , which is much lower than the emission rate of the original diesel engine. There was also evidence that less volatile elements, such as iron, self-nucleated to form nanoparticles, some of which survive the coagulation process.

The feasibility of measuring airborne crystalline silica (α-quartz) in noncoal mine dusts using a direct-on-filter method of analysis is demonstrated. Respirable α-quartz was quantified by applying a partial least squares (PLS) regression to the infrared transmission spectra of mine-dust samples deposited on porous polymeric filters. This direct-on-filter method deviates from the current regulatory determination of respirable α-quartz by refraining from ashing the sampling filter and redepositing the analyte prior to quantification using either infrared spectrometry for coal mines or x-ray diffraction (XRD) from noncoal mines. Since XRD is not field portable, this study evaluated the efficacy of Fourier transform infrared spectrometry for silica determination in noncoal mine dusts. PLS regressions were performed using select regions of the spectra from nonashed samples with important wavenumbers selected using a novel modification to the Monte Carlo unimportant variable elimination procedure. Wavenumber selection helped to improve PLS prediction, reduce the number of required PLS factors, and identify additional silica bands distinct from those currently used in regulatory enforcement. PLS regression appeared robust against the influence of residual filter and extraneous mineral absorptions while outperforming ordinary least squares calibration. These results support the quantification of respirable silica in noncoal mines using field-portable infrared spectrometers.

The exposure to respirable crystalline silica (RCS) in the mining industry is a recognized occupational hazard. The assessment and monitoring of the exposure to RCS is limited by two main factors: (1) variability of the silica percent in the mining dust and (2) lengthy off-site laboratory analysis of collected samples. The monitoring of respirable dust via traditional or real-time techniques is not adequate. A solution for on-site quantification of RCS in dust samples is being investigated by the Office of Mine Safety and Health Research, a division of the National Institute for Occupational Safety and Health. The use of portable Fourier transform infrared analyzers in conjunction with a direct-on-filter analysis approach is proposed. The progress made so far, the necessary steps in progress, and the application of the monitoring solution to a small data set is presented. When developed, the solution will allow operators to estimate RCS immediately after sampling, resulting in timelier monitoring of RCS for self-assessment of compliance at the end of the shift, more effective engineering monitoring, and better evaluation of control technologies.