Measurements of the particle size distribution at the outlets of six coal-fired utility boilers showed a peak at a particle diameter near 0.1 micrometer. This submicrometer mode appears to be a general feature of coal combustion that results from a volatilization-condensation process in the boiler. At the boilers tested, the submicrometer mode contained 0.2 to 2.2 percent of the total fly ash mass. The importance of this mode is greater than its small quantity suggests because particles in the submicrometer size range are often much more difficult to collect with conventional particulate control devices than larger particles. Thus, the submicrometer mode may significantly influence the design and selection of future power plant emission controls. The particle mass in the submicrometer mode was correlated with the nitric oxide concentration in the flue gas. This correlation suggests that control of nitric oxide by modification of the combustion conditions may reduce the generation and emission of submicrometer particles.

The filtration efficiency of ventilation air cleaners is highly particle‐size dependent over the 0.01 to 3 μm diameter size range. Current standardized test methods, which determine only overall efficiencies for ambient aerosol or other test aerosols, provide data of limited utility. Because particles in this range are respirable and can remain airborne for prolonged time periods, measurement of air cleaner fractional efficiency is required for application to indoor air quality issues. The objectives of this work have been to 1) develop a test apparatus and procedure to quantify the fractional filtration efficiency of air cleaners over the 0.01 to 3 μm diameter size range and 2) quantify the fractional efficiency of several induct air cleaners typical of those used in residential and office ventilation systems. Results show that efficiency is highly dependent on particle size, flow rate, and dust load present on the air cleaner. A minimum in efficiency was often observed in the 0.1 to 0.5 μm diameter size range. The presence of a dust load frequently increased an air cleaner's efficiency; however, some air cleaners showed little change or a decrease in efficiency with dust loading. The common furnace filter had fractional efficiency values of less than 10% over much of the measurement size range.

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This paper reports an interlaboratory comparison that evaluated a protocol for measuring and analysing the particle size distribution of discrete, metallic, spheroidal nanoparticles using transmission electron microscopy (TEM). The study was focused on automated image capture and automated particle analysis. NIST RM8012 gold nanoparticles (30 nm nominal diameter) were measured for area-equivalent diameter distributions by eight laboratories. Statistical analysis was used to (1) assess the data quality without using size distribution reference models, (2) determine reference model parameters for different size distribution reference models and non-linear regression fitting methods and (3) assess the measurement uncertainty of a size distribution parameter by using its coefficient of variation. The interlaboratory area-equivalent diameter mean, 27.6 nm ± 2.4 nm (computed based on a normal distribution), was quite similar to the area-equivalent diameter, 27.6 nm, assigned to NIST RM8012. The lognormal reference model was the preferred choice for these particle size distributions as, for all laboratories, its parameters had lower relative standard errors (RSEs) than the other size distribution reference models tested (normal, Weibull and Rosin–Rammler–Bennett). The RSEs for the fitted standard deviations were two orders of magnitude higher than those for the fitted means, suggesting that most of the parameter estimate errors were associated with estimating the breadth of the distributions. The coefficients of variation for the interlaboratory statistics also confirmed the lognormal reference model as the preferred choice. From quasi-linear plots, the typical range for good fits between the model and cumulative number-based distributions was 1.9 fitted standard deviations less than the mean to 2.3 fitted standard deviations above the mean. Automated image capture, automated particle analysis and statistical evaluation of the data and fitting coefficients provide a framework for assessing nanoparticle size distributions using TEM for image acquisition.

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