Different particle size silicas from water glass.

Non-crystalline silica was obtained with different particle sizes. Samples were prepared from soluble sodium silicate (water glass) and sulfuric acid solutions. Dialysis was performed for sodium sulfate elimination. Products were dried in a microwave oven, milled and characterized by X-ray powder diffraction, infrared spectrum and sedigraphic analysis. Products milled for more than 120 minutes showed uniform particle size distribution with average silica particle size of 4.5 mu m.

Multifractal characterization of saprolite particle-size distributions after topsoil removal

Multifractal analysis is now increasingly used to characterize soil properties as it may provide more information than a single fractal model. During the building of a large reservoir on the Parana River (Brazil), a highly weathered soil profile was excavated to a depth between 5 and 8 m. Excavation resulted in an abandoned area with saprolite materials and, in this area, an experimental field was established to assess the effectiveness of different soil rehabilitation treatments. The experimental design consisted of randomized blocks. The aim of this work was to characterize particle-size distributions of the saprolite material and use the information obtained to assess between-block variability. Particle-size distributions of the experimental plots were characterized by multifractal techniques. Ninety-six soil samples were analyzed routinely for particle-size distribution by laser diffractometry in a range of scales, varying from 0.390 to 2000 mu m. Six different textural classes (USDA) were identified with a clay content ranging from 16.9% to 58.4%. Multifractal models described reasonably well the scaling properties of particle-size distributions of the saprolite material. This material exhibits a high entropy dimension, D-1. Parameters derived from the left side (q > 0) of the f(alpha) spectra, D-1, the correlation dimension (D-2) and the range (alpha(0)-alpha(q+)), as well as the total width of the spectra (alpha(max) - alpha(min)) all showed dependence on the clay content. Sand, silt and clay contents were significantly different among treatments as a consequence of soil intrinsic variability. The D, and the Holder exponent of order zero, alpha(0), were not significantly different between treatments; in contrast, D-2 and several fractal attributes describing the width of the f(alpha) spectra were significantly different between treatments. The only parameter showing significant differences between sampling depths was (alpha(0) - alpha(q+)). Scale independent fractal attributes may be useful for characterizing intrinsic particle-size distribution variability. (c) 2006 Elsevier B.V. All rights reserved.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Size-resolved particle distribution and gaseous concentrations by real-world road tunnel measurement

Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5～87.5nm, geometric standard deviations were 1.89～1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21～24 nm, geometric standard deviations were 1.27～1.31.

Influential parameters on particle concentration and size distribution in the mainstream of e-cigarettes

Electronic cigarette-generated mainstream aerosols were characterized in terms of particle number concentrations and size distributions through a Condensation Particle Counter and a Fast Mobility Particle Sizer spectrometer, respectively. A thermodilution system was also used to properly sample and dilute the mainstream aerosol. Different types of electronic cigarettes, liquid flavors, liquid nicotine contents, as well as different puffing times were tested. Conventional tobacco cigarettes were also investigated. The total particle number concentration peak (for 2-s puff), averaged across the different electronic cigarette types and liquids, was measured equal to 4.39 ± 0.42 × 109 part. cm−3, then comparable to the conventional cigarette one (3.14 ± 0.61 × 109 part. cm−3). Puffing times and nicotine contents were found to influence the particle concentration, whereas no significant differences were recognized in terms of flavors and types of cigarettes used. Particle number distribution modes of the electronic cigarette-generated aerosol were in the 120–165 nm range, then similar to the conventional cigarette one.

Mass and size distribution measurement of particulates from a gas turbine combustor using modern mobility analyzer and particle sizer

SMPS and DMS500 analysers were used to measure particulate size distributions in the exhaust of a fully annular aero gas turbine engine at two operating conditions to compare and analyse sources of discrepancy. A number of different dilution ratio values were utilised for the comparative analysis, and a Dekati hot diluter operating at a temperature of 623°K was also utilised to remove volatile PM prior to measurements being made. Additional work focused on observing the effect of varying the sample line temperatures to ascertain the impact. Explanations are offered for most of the trends observed, although a new, repeatable event identified in the range from 417°K to 423°K – where there was a three order of magnitude increase in the nucleation mode of the sample – requires further study.

Exploring the enzymatic landscape: distribution and kinetics of hydrolytic enzymes in soil particle-size fractions

The location of extracellular enzymes within the soil architecture and their association with the various soil components affects their catalytic potential. A soil fractionation study was carried out to investigate: (a) the distribution of a range of hydrolytic enzymes involved in C, N and P transformations, (b) the effect of the location on their respective kinetics, (c) the effect of long-term N fertilizer management on enzyme distribution and kinetic parameters. Soil (silty clay loam) from grassland which had received 0 or 200 kg N ha(-1) yr(-1) was fractionated, and four particle-size fractions (> 200, 200-63, 63-2 and 0. 1-2 mum) were obtained by a combination of wet-sieving and centrifugation, after low-energy ultrasonication. All fractions were assayed for four carbohydrases (beta-cellobiohydrolase, N-acetyl-beta-glucosammidase, beta-glucosidase and beta-xylosidase), acid phosphatase and leucine-aminopeptidase using a microplate fluorimetric assay based on MUB-substrates. Enzyme kinetics (V-max and K-m) were estimated in three particle-size fractions and the unfractionated soil. The results showed that not all particle-size fractions were equally enzymatically active and that the distribution of enzymes between fractions depended on the enzyme. Carbohydrases predominated in the coarser fractions while phosphatase and leucine-aminopeptidase were predominant in the clay-size fraction. The Michaelis constant (K.) varied among fractions, indicating that the association of the same enzyme with different particle-size fractions affected its substrate affinity. The same values of Km were found in the same fractions from the soil under two contrasting fertilizer management regimes, indicating that the Michaelis constant was unaffected by soil changes caused by N fertilizer management. (C) 2004 Elsevier Ltd. All rights reserved.

Particle concentration and size distribution in the NGRIP ice core

A novel laser microparticle detector used in conjunction with continuous sample melting has provided a more than 1500 m long record of particle concentration and size distribution of the NGRIP ice core, covering continuously the period approximately from 9.5-100 kyr before present; measurements were at 1.65 m depth resolution, corresponding to approximately 35-200 yr. Particle concentration increased by a factor of 100 in the Last Glacial Maximum (LGM) compared to the Preboreal, and sharp variations of concentration occurred synchronously with rapid changes in the delta18O temperature proxy. The lognormal mode µ of the volume distribution shows clear systematic variations with smaller modes during warmer climates and coarser modes during colder periods. We find µ ~ 1.7 µm diameter during LGM and µ ~ 1.3 µm during the Preboreal. On timescales below several 100 years µ and the particle concentration exhibit a certain degree of independence present especially during warm periods, when µ generally is more variable. Using highly simplifying considerations for atmospheric transport and deposition of particles we infer that (1) the observed changes of µ in the ice largely reflect changes in the size of airborne particles above the ice sheet and (2) changes of µ are indicative of changes in long range atmospheric transport time. From the observed size changes we estimate shorter transit times by roughly 25% during LGM compared to the Preboreal. The associated particle concentration increase from more efficient long range transport is estimated to less than one order of magnitude.

Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution

A 2D computer simulation method of random packings is applied to sets of particles generated by a self-similar uniparametric model for particle size distributions (PSDs) in granular media. The parameter p which controls the model is the proportion of mass of particles corresponding to the left half of the normalized size interval [0,1]. First the influence on the total porosity of the parameter p is analyzed and interpreted. It is shown that such parameter, and the fractal exponent of the associated power scaling, are efficient packing parameters, but this last one is not in the way predicted in a former published work addressing an analogous research in artificial granular materials. The total porosity reaches the minimum value for p = 0.6. Limited information on the pore size distribution is obtained from the packing simulations and by means of morphological analysis methods. Results show that the range of pore sizes increases for decreasing values of p showing also different shape in the volume pore size distribution. Further research including simulations with a greater number of particles and image resolution are required to obtain finer results on the hierarchical structure of pore space.

Validating SMPS-measured size distribution of double-mode spherical Silica nanoparticles by Transmission Electron Microscope (TEM)

A nanoparticles size is one of their key physical characteristics that can affect their fate in a human’s respiratory tract (in case of inhalation) and also in the environment. Hence, measuring the size distribution of nanoparticles is absolutely essential and contributes greatly to their characterization. For years, Scanning Mobility Particle Sizers (SMPS), which rely on measuring the electrical mobility diameter of particles, have been used as one of the most reliable real-time instruments for the size distribution measurement of nanoparticles. Despite its benefits, this instrument has some drawbacks, including equivalency problems for non-spherical particles (i.e. assuming a non-spherical particle is equal to a spherical particle of diameter d due to the same electrical mobility), as well as limitations in terms of its use in workplaces, because of its large size and the complexity of its operation...

What are the driving factors influencing the size distribution of airborne synthetic clay particles emitted from a jet milling process?

In the field of workplace air quality, measuring and analyzing the size distribution of airborne particles to identify their sources and apportion their contribution has become widely accepted, however, the driving factors that influence this parameter, particularly for nanoparticles (< 100 nm), have not been thoroughly determined. Identification of driving factors, and in turn, general trends in size distribution of emitted particles would facilitate the prediction of nanoparticles’ emission behavior and significantly contribute to their exposure assessment. In this study, a comprehensive analysis of the particle number size distribution data, with a particular focus on the ultrafine size range of synthetic clay particles emitted from a jet milling machine was conducted using the multi-lognormal fitting method. The results showed relatively high contribution of nanoparticles to the emissions in many of the tested cases, and also, that both surface treatment and feed rate of the machine are significant factors influencing the size distribution of the emitted particles of this size. In particular, applying surface treatments and increasing the machine feed rate have the similar effect of reducing the size of the particles, however, no general trend was found in variations of size distribution across different surface treatments and feed rates. The findings of our study demonstrate that for this process and other activities, where no general trend is found in the size distribution of the emitted airborne particles due to dissimilar effects of the driving factors, each case must be treated separately in terms of workplace exposure assessment and regulations.