Assessment of emissions and exposure in 3D printing workplaces in Taiwan.

Three-dimensional (3D) printing is an emerging and booming industry in Taiwan. Compared to traditional manufacturing, 3D printing has various advantages, such as advanced customization, additive manufacturing, reduced mold opening time, and reduced consumption of precursors. In this study, the real-time monitoring of particulate matter (PM) and total volatile organic compound (TVOC) emissions from various filaments is investigated using fused deposition modeling with material extrusion technology, a liquid-crystal display, a stereolithography apparatus based on vat photopolymerization technology, and binder jetting for occupational settings. An exposure assessment for nearby workers using the 3D printing process was performed, and improvement measures were recommended. Nine 3D printing fields were measured. The generation rate of ultrafine particles ranged from 1.19 × 1010 to 4.90 × 1012 #/min, and the geometric mean particle size ranged from 30.91 to 55.50 nm. The average concentration of ultrafine particles ranged from 2.31 × 103 to 7.36 × 104 #/cm3, and the PM2.5 and PM10 concentrations in each field ranged from 0.74 ± 0.27 to 12.46 ± 5.61 µg/m3 and from 2.39 ± 0.60 to 30.65 ± 21.26 µg/m3, respectively. The TVOC concentration ranged from 0.127 ± 0.012 to 1.567 ± 0.172 ppm. The respiratory deposition (RDUFPs) dose ranged from 2.02 × 1013 to 5.54 × 1014 nm2/day. Depending on the operating conditions, appropriate control and protective measures should be employed to protect workers' health.

Photochemical oxidation of VOCs and their source impact assessment on ozone under de-weather conditions in Western Taiwan.

The application of statistical models has excellent potential to provide crucial information for mitigating the challenging issue of ozone (O3) pollution by capturing its associations with explanatory variables, including reactive precursors (VOCs and NOX) and meteorology. Considering the large contribution of O3 in degrading the air quality of western Taiwan, three-year (2019-2021) hourly concentration data of VOC, NOX and O3 from 4 monitoring stations of western Taiwan: Tucheng (TC), Zhongming (ZM), Taixi (TX) and Xiaogang (XG), was evaluated to identify the effect of anthropogenic emissions on O3 formation. Owing to the high-ambient reactivity of VOCs on the underestimation of sources, photochemical oxidation was assessed to calculate the consumed VOC (VOCcons) which was followed by the source identification of their initial concentrations. VOCcons was observed to be highest in the summer season (16.7 and 22.7 ppbC) at north (TC and ZM) and in the autumn season (17.8 and 11.4 ppbC) in southward-located stations (TX and XG, respectively). Results showed that VOCs from solvents (25-27%) were the major source at northward stations whereas VOCs-industrial emissions (30%) dominated in south. Furthermore, machine learning (ML): eXtreme Gradient Boost (XGBoost) model based de-weather analysis identified that meteorological factors favor to reduce ambient O3 levels at TC, ZM and XG stations (-67%, -47% and -21%, respectively) but they have a major role in accumulating the O3 (+38%) at the TX station which is primarily transported from the upwind region of south-central Taiwan. Crucial insights using ML outputs showed that the finding of the study can be utilized for region-specific data-driven control of emission from VOCs-sources and prioritized to limit the O3-pollution at the study location-ns as well as their accumulation in distant regions.

Characterization of spatial-temporal distribution and microenvironment source contribution of PM2.5 concentrations using a low-cost sensor network with artificial neural network/kriging techniques.

Low-cost sensors (LCS) network is widely used to improve the resolution of spatial-temporal distribution of air pollutant concentrations in urban areas. However, studies on air pollution sources contribution to the microenvironment, especially in industrial and mix-used housing areas, still need to be completed. This study investigated the spatial-temporal distribution and source contributions of PM2.5 in the urban area based on 6-month of the LCS network datasets. The Artificial Neural Network (ANN) was used to calibrate the measured PM2.5 by the LCS network. The calibrated PM2.5 were shown to agree with reference PM2.5 measured by the BAM-1020 with R2 of 0.85, MNE of 30.91%, and RMSE of 3.73 µg/m3, which meet the criteria for hotspot identification and personal exposure study purposes. The Kriging method was further used to establish the spatial-temporal distribution of PM2.5 concentrations in the urban area. Results showed that the highest average PM2.5 concentration occurred during autumn and winter due to monsoon and topographic effects. From a diurnal perspective, the highest level of PM2.5 concentration was observed during the daytime due to heavy traffic emissions and industrial production. Based on the present ANN-based microenvironment source contribution assessment model, temples, fried chicken shops, traffic emissions in shopping and residential zones, and industrial activities such as the mechanical manufacturing and precision metal machining were identified as the sources of PM2.5. The numerical algorithm coupled with the LCS network presented in this study is a practical framework for PM2.5 hotspots and source identification, aiding decision-makers in reducing atmospheric PM2.5 concentrations and formulating regional air pollution control strategies.

Source-apportionment and spatial distribution analysis of VOCs and their role in ozone formation using machine learning in central-west Taiwan.

This study assessed the machine learning based sensitivity analysis coupled with source-apportionment of volatile organic carbons (VOCs) to look into new insights of O3 pollution in Yunlin County located in central-west region of Taiwan. One-year (Jan 1 to Dec 31, 2021) hourly mass concentrations data of 54 VOCs, NOX, and O3 from 10 photochemical assessment monitoring stations (PAMs) in and around the Yunlin County were analyzed. The novelty of the study lies in the utilization of artificial neural network (ANN) to evaluate the contribution of VOCs sources in O3 pollution in the region. Firstly, the station specific source-apportionment of VOCs were carried out using positive matrix factorization (PMF)-resolving six sources viz. AAM: aged air mass, CM: chemical manufacturing, IC: Industrial combustion, PP: petrochemical plants, SU: solvent use and VE: vehicular emissions. AAM, SU, and VE constituted cumulatively more than 65% of the total emission of VOCs across all 10 PAMs. Diurnal and spatial variability of source-segregated VOCs showed large variations across 10 PAMs, suggesting for distinctly different impact of contributing sources, photo-chemical reactivity, and/or dispersion due to land-sea breezes at the monitoring stations. Secondly, to understand the contribution of controllable factors governing the O3 pollution, the output of VOCs source-contributions from PMF model along with mass concentrations of NOX were standardized and first time used as input variables to ANN, a supervised machine learning algorithm. ANN analysis revealed following order of sensitivity in factors governing the O3 pollution: VOCs from IC > AAM > VE ≈ CM ≈ SU > PP ≈ NOX. The results indicated that VOCs associated with IC (VOCs-IC) being the most sensitive factor which need to be regulated more efficiently to quickly mitigate the O3 pollution across the Yunlin County.

The influence of COVID-19 pandemic on PM2.5 air quality in Northern Taiwan from Q1 2020 to Q2 2021.

The study aimed to investigate the PM2.5 variations in different periods of COVID-19 control measures in Northern Taiwan from Quarter 1 (Q1) 2020 to Quarter 2 (Q2) 2021. PM2.5 sources were classified based on long-range transport (LRT) or local pollution (LP) in three study periods: one China lockdown (P1), and two restrictions in Taiwan (P2 and P3). During P1 the average PM2.5 concentrations from LRT (LRT-PM2.5-P1) were higher at Fuguei background station by 27.9% and in the range of 4.9-24.3% at other inland stations compared to before P1. The PM2.5 from LRT/LP mix or pure LP (Mix/LP-PM2.5-P1) was also higher by 14.2-39.9%. This increase was due to higher secondary particle formation represented by the increase in secondary ions (SI) and organic matter in PM2.5-P1 with the largest proportion of 42.17% in PM2.5 from positive matrix factorization (PMF) analysis. A similar increasing trend of Mix/LP-PM2.5 was found in P2 when China was still locked down and Taiwan was under an early control period but the rapidly increasing infected cases were confirmed. The shift of transportation patterns from public to private to avoid virus infection explicated the high correlation of the increasing infected cases with the increasing PM2.5. In contrast, the decreasing trend of LP-PM2.5-P3 was observed in P3 with the PM2.5 biases of ∼45% at all the stations when China was not locked down but Taiwan implemented a semi-lockdown. The contribution of gasoline vehicle sources in PM2.5 was reduced from 20.3% before P3 to 10% in P3 by chemical signatures and source identification using PMF implying the strong impact of strict control measures on vehicle emissions. In summary, PM2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions.

Getting insight into the influence of coexisting airborne nanoparticles on gas adsorption performance over porous materials.

Adsorption as one of the most important air cleaning methods has been extensively applied during which the coexisting airborne nanoparticles (NPs) with sizes close to adsorbent pore sizes could inevitably influence gas adsorption processes. In this work, the influence of sub-20 nm NPs on toluene adsorption on ZSM-5 zeolites exchanged with different cations (Li+, Na+ and K+) were studied based on gas-and-particle coexisting adsorption/filtration tests. Affinities for both toluene and NPs on adsorbents follow Li-ZSM-5 > Na-ZSM-5 > K-ZSM-5 regarding the orders of charge density, pore size, and internal and external specific surface areas. The toluene adsorption was shown to be impaired by coexisting NPs from perspectives of thermodynamics and kinetics. For Li-ZSM-5, Na-ZSM-5 and K-ZSM-5, significant relative reductions of 10.4 %, 10.5 % and 16.0 % in toluene adsorption capacity at the lower feed concentration, and of 20.3 %, 15.2 % and 2.3 % in mass transfer coefficient at the higher feed concentration were observed, respectively. The influential mechanisms regarding competitiveness between toluene and NPs in interaction with cationic and porous surfaces were accordingly proposed, which are of practical significance for selecting robust adsorbents under realistic harsh air conditions.

Development of a Novel Shallow Liquid Interface Exposure System for MWCNT Toxicity Assessment.

Increasing applications of multiwalled carbon nanotubes (MWCNT) lead to significant occupational exposure and potential health concerns. Toxicity of MWCNT should be carefully elucidated since the conventional (CON) method with fully immersed condition fails to mimic the air-liquid interface (ALI) in airways. Additionally, quantification of MWCNT in cells was a real challenge. Currently available ALI exposure devices are costly, posing problems to conducting in vitro evaluations for emerging nanomaterials. A novel system, consisting of a shaker fluidized-bed atomizer (SFA) and electrostatic shallow liquid interface (ESLI) exposure chamber, has been developed for investigating nanotoxicity of well-dispersed pristine-MWCNT (pMWCNT) and carboxylized-MWCNT (cMWCNT). After 24-h exposure, LDH, MCP-1, IL-1ß, IL-6, and TNF-α releases were determined, and cell uptakes were quantified according to the molybdenum content in cells. Biological responses triggered by SLI exposure are obviously more sensitive compared with those caused by CON exposure at equivalent doses. Exposure dose-dependent release of LDH and IL-6 was highlighted in A549 cells, indicating higher cytotoxicity and inflammatory responses of cMWCNT attributed to its shorter length, smaller size, and higher cell uptake. Cell-associated dose-dependent release of LDH and IL-6 was highlighted in RAW264.7 cells, revealing the higher adverse health risk of pMWCNT due to frustrated phagocytosis and its much higher molybdenum content. These results suggest that inherent characteristics of cells and distinct physicochemical properties of pMWCNT and cMWCNT lead to either exposure dose-dependent or cell-associated dose-dependent responses. Notably, the SLI is superior to the CON exposure method and well suited for nanotoxicity assessment of different MWCNTs.

Detection of Particulate Matter of Size 2.5 µm with a Surface-Acoustic-Wave Sensor Combined with a Cyclone Separator.

A device to monitor particulate matter of size 2.5 µm (PM2.5) that has been designed and developed includes a surface-acoustic-wave sensor operating in a shear horizontal mode (SH-SAW) combined with a cyclone separator. In our tests, aerosols generated as incense smoke were first separated and sampled inside a designed cyclone separator; the sampled PM2.5 was then introduced into the sensing area of an SH-SAW sensor for detection. The use of microcentrifuge tubes as a cyclone separator effectively decreases the size and power consumption of the device; the SAW sensor in a well design and operating at 122 MHz was fabricated with MEMS techniques. After an explanation of the design of the cyclone separator, a simulation of the efficiency and the SAW sensor detection are discussed. A microcentrifuge tube (volume 0.2 mL, inlet and outlet diameters 0.5 mm) as a separator has separation cutoff diameters 50% (d50) at 2.5 µm; the required rate of volumetric flow at the inlet is 0.125 LPM, according to simulation with computational fluid dynamics (CFD) software; the surface-acoustic-wave (SAW) sensor exhibits sensitivity approximately 9 Hz/ng; an experiment for PM2.5 detection conducted with the combined device shows a strong positive linear correlation with a commercial aerosol monitor. The limit of detection (LOD) is 11 µg/m³ with sample time 160 s and total detection duration about 5 min.

A review on recent progress in observations, sources, classification and regulations of PM2.5 in Asian environments.

Natural and human activities generate a significant amount of PM2.5 (particles ≤2.5 µm in aerodynamic diameter) into the surrounding atmospheric environments. Because of their small size, they can remain suspended for a relatively longer time in the air than coarse particles and thus can travel long distances in the atmosphere. PM2.5 is one of the key indicators of pollution and known to cause numerous types of respiratory and lung-related diseases. Due to poor implementation of regulations and a time lag in introducing the vehicle technology, levels of PM2.5 in most Asian cities are much worse than those in European environments. Dedicated reviews on understanding the characteristics of PM2.5 in Asian urban environments are currently missing but much needed. In order to fill the existing gaps in the literature, the aim of this review article is to describe dominating sources and their classification, followed by current status and health impact of PM2.5, in Asian countries. Further objectives include a critical synthesis of the topics such as secondary and tertiary aerosol formation, chemical composition, monitoring and modelling methods, source apportionment, emissions and exposure impacts. The review concludes with the synthesis of regulatory guidelines and future perspectives for PM2.5 in Asian countries. A critical synthesis of literature suggests a lack of exposure and monitoring studies to inform personal exposure in the household and rural areas of Asian environments.

The rural carbonaceous aerosols in coarse, fine, and ultrafine particles during haze pollution in northwestern China.

The carbonaceous aerosol concentrations in coarse particle (PM10: Dp ≤ 10 µm, particulate matter with an aerodynamic diameter less than 10 µm), fine particle (PM2.5: Dp ≤ 2.5 µm), and ultrafine particle (PM0.133: Dp ≤ 0.133 µm) carbon fractions in a rural area were investigated during haze events in northwestern China. The results indicated that PM2.5 contributed a large fraction in PM10. OC (organic carbon) accounted for 33, 41, and 62 % of PM10, PM2.5, and PM0.133, and those were 2, 2.4, and 0.4 % for EC (elemental carbon) in a rural area, respectively. OC3 was more abundant than other organic carbon fractions in three PMs, and char dominated EC in PM10 and PM2.5 while soot dominated EC in PM0.133. The present study inferred that K(+), OP, and OC3 are good biomass burning tracers for rural PM10 and PM2.5, but not for PM0.133 during haze pollution. Our results suggest that biomass burning is likely to be an important contributor to rural PMs in northwestern China. It is necessary to establish biomass burning control policies for the mitigation of severe haze pollution in a rural area.

Novel Wire-on-Plate Electrostatic Precipitator (WOP-EP) for Controlling Fine Particle and Nanoparticle Pollution.

A new wire-on-plate electrostatic precipitator (WOP-EP), where discharge wires are attached directly on the surface of a dielectric plate, was developed to ease the installation of the wires, minimize particle deposition on the wires, and lower ozone emission while maintaining a high particle collection efficiency. For a lab-scale WOP-EP (width, 50 mm; height, 20 mm; length, 180 mm) tested at the applied voltage of 18 kV, experimental total particle collection efficiencies were found as high as 90.9-99.7 and 98.8-99.9% in the particle size range of 30-1870 nm at the average air velocities of 0.50 m/s (flow rate, 30 L/min; residence time, 0.36 s) and 0.25 m/s (flow rate, 15 L/min; residence time, 0.72 s), respectively. Particle collection efficiencies calculated by numerical models agreed well with the experimental results. The comparison to the traditional wire-in-plate EP showed that, at the same applied voltage, the current WOP-EP emitted 1-2 orders of magnitude lower ozone concentration, had cleaner discharge wires after heavy particle loading in the EP, and recovered high particle collection efficiency after the grounded collection plate was cleaned. It is expected that the current WOP-EP can be scaled up as an efficient air-cleaning device to control fine particle and nanoparticle pollution.

Evaluation of a novel personal nanoparticle sampler.

This work investigated the performance in terms of collection efficiency and aspiration efficiency of a personal sampler capable of collecting ultrafine particles (nanoparticles) in the occupational environment. This sampler consists of a cyclone for respirable particle classification, micro-orifice impactor stages with an acceleration nozzle to achieve nanoparticle classification and a backup filter to collect nanoparticles. Collection efficiencies of the cyclone and impactor stages were determined using monodisperse polystyrene latex and silver particles, respectively. Calibration of the cyclone and impactor stages showed 50% cut-off diameters of 3.95 µm and 94.7 nm meeting the design requirements. Aspiration efficiencies of the sampler were tested in a wind tunnel with wind speeds of 0.5, 1.0, and 1.5 m s(-1). The test samplers were mounted on a full size mannequin with three orientations toward the wind direction (0°, 90°, and 180°). Monodisperse oleic acid aerosols tagged with sodium fluorescein in the size range of 2 to 10 µm were used in the test. For particles smaller than 2 µm, the fluorescent polystyrene latex particles were generated by using nebulizers. For comparison of the aspiration efficiency, a NIOSH two-stage personal bioaerosol sampler was also tested. Results showed that the orientation-averaged aspiration efficiency for both samplers was close to the inhalable fraction curve. However, the direction of wind strongly affected the aspiration efficiency. The results also showed that the aspiration efficiency was not affected by the ratio of free-stream velocity to the velocity through the sampler orifice. Our evaluation showed that the current design of the personal sampler met the designed criteria for collecting nanoparticles ≤100 nm in occupational environments.

Comparison and implications of PM2.5 carbon fractions in different environments.

The concentrations of PM2.5 carbon fractions in rural, urban, tunnel and remote environments were measured using the IMPROVE thermal optical reflectance (TOR) method. The highest OC1 and EC1 concentrations were found for tunnel samples, while the highest OC2, OC3, and OC4 concentrations were observed for urban winter samples, respectively. The lowest levels of most carbon fractions were found for remote samples. The percentage contributions of carbon fractions to total carbon (TC) were characterized by one peak (at rural and remote sites) and two peaks (at urban and tunnel sites) with different carbon fractions, respectively. The abundance of char in tunnel and urban environments was observed, which might partly be due to traffic-related tire-wear. Various percentages of optically scattering OC and absorbing EC fractions to TC were found in the four different environments. In addition, the contribution of heating carbon fractions (char and soot) indicated various warming effects per unit mass of TC. The ratios of OC/EC and char/soot at the sites were shown to be source indicators. The investigation of carbon fractions at different sites may provide some information for improving model parameters in estimating their radiative effects.

Novel active personal nanoparticle sampler for the exposure assessment of nanoparticles in workplaces.

A novel active personal nanoparticle sampler (PENS), which enables the collection of both respirable particulate mass (RPM) and nanoparticles (NPs) simultaneously, was developed to meet the critical demand for personal sampling of engineered nanomaterials (ENMs) in workplaces. The PENS consists of a respirable cyclone and a micro-orifice impactor with the cutoff aerodynamic diameter (d(pa50)) of 4 µm and 100 nm, respectively. The micro-orifice impactor has a fixed micro-orifice plate (137 nozzles of 55 µm in the inner diameter) and a rotating, silicone oil-coated Teflon filter substrate at 1 rpm to achieve a uniform particle deposition and avoid solid particle bounce. A final filter is used after the impactor to collect the NPs. Calibration results show that the d(pa50) of the respirable cyclone and the micro-orifice impactor are 3.92 ± 0.22 µm and 101.4 ± 0.1 nm, respectively. The d(pa50) at the loaded micro-Al(2)O(3) mass of 0.36-3.18 mg is shifted to 102.9-101.2 nm, respectively, while it is shifted to 98.9-97.8 nm at the loaded nano-TiO(2) mass of 0.92-1.78 mg, respectively. That is, the shift of d(pa50) due to solid particle loading is small if the PENS is not overloaded. Both NPs and RPM concentrations were found to agree well with those of the IOSH respirable cyclone and MOUDI. By using the present PENS, the collected samples can be further analyzed for chemical species concentrations besides gravimetric analysis to determine the actual exposure concentrations of ENMs in both RPM and NPs fractions in workplaces, which are often influenced by the background or incident pollution sources.

Concentrations of ultrafine particles at a highway toll collection booth and exposure implications for toll collectors.

Research regarding the magnitude of ultrafine particle levels at highway toll stations is limited. This study measured ambient concentrations of ultrafine particles at a highway toll station from October 30 to November 1 and November 5 to November 6, 2008. A scanning mobility particle sizer was used to measure ultrafine particle concentrations at a ticket/cash tollbooth. Levels of hourly average ultrafine particles at the tollbooth were about 3-6 times higher than those in urban backgrounds, indicating that a considerable amount of ultrafine particles are exhausted from passing vehicles. A bi-modal size distribution pattern with a dominant mode at about <6 nm and a minor mode at about 40 nm was observed at the tollbooth. The high amounts of nanoparticles in this study can be attributed to gas-to-particle reactions in fresh fumes emitted directly from vehicles. The influences of traffic volume, wind speed, and relative humidity on ultrafine particle concentrations were also determined. High ambient concentrations of ultrafine particles existed under low wind speed, low relative humidity, and high traffic volume. Although different factors account for high ambient concentrations of ultrafine particles at the tollbooth, measurements indicate that toll collectors who work close to traffic emission sources have a high exposure risk.

Measurements of respirable dust and nanoparticle concentrations in a titanium dioxide pigment production factory.

This study compared respirable dust and nanoparticle concentrations measured by different sampling devices at a titanium dioxide pigment factory. Respirable particle mass concentrations, nanoparticle concentrations, particle size distribution and particle metallic content were measured at different sampling locations. The sampling results of the Multi-orifice Uniform Deposit Impactor (MOUDI) showed that the particle size distribution at this titanium dioxide production factory fell in the range of 1-10 mu m. Generally, the higher levels of the respirable particle mass concentrations and nanoparticle number concentrations were near the packing site of the pigment titanium dioxide production factory. Metal analysis results revealed that the titanium dioxide concentrations in respirable dust and nanoparticles were within the limits specified by National Institute for Occupational Safety and Health (NIOSH). During sampling, particle metallic content analysis is essential for identifying the source of particles and for measuring respirable dust and nanoparticle concentrations.

Copper loaded on sol-gel-derived alumina adsorbents for phosphine removal.

The hydride gas of phosphine (PH3) is commonly used for semiconductor and optoelectronic industries. The local scrubbers must immediately abate it because of its high toxicity. In this study, copper (Cu) loaded on the sol-gel-derived gamma-alumina (Al2O3) adsorbents are prepared and tested to investigate the possibility of PH3 removal and sorbent regeneration. Test results showed that during the breakthrough time of over 99% PH3 removal efficiency, the maximum adsorption capacity of Cu loaded on the sol-gel-derived gamma-Al2O3 adsorbent is 18 mg-PH3/g-adsorbent. This is much higher than that of Cu loaded on the commercial gamma-Al2O3 adsorbent--8.6 mg-PH3/g-adsorbent. The high specific surface area, narrow pore size distribution, and well dispersion of Cu loaded on the sol-gel-derived gamma-Al2O3 could be the reasons for its high PH3 adsorption capacity. The regeneration test shows that Cu loaded on the sol-gel-derived gamma-Al2O3 adsorbent can be regenerated after a simple air purging procedure. The cumulative adsorption capacity for five regeneration cycles is 65 mg-PH3/g-adsorbent, which is approximately double that of the Cu/zeolite adsorbent demonstrated in the literature.

Measurements of ultrafine particle concentrations and size distribution in an iron foundry.

The number and surface area concentration of ultrafine particles in an iron foundry is of interest as freshly generated ultrafine particles are produced by metal melting, pouring and molding processes. This study measured the number and surface area concentrations of ultrafine particles and their size distributions in an iron foundry using a scanning mobility particle sizer (SMPS). The 10-100 nm ultrafine particle number concentrations (NC(0.01-0.1)) and surface area concentrations (SC(0.01-0.1)) measured at the iron foundry were 2.07 x 10(4) to 2.82 x 10(5)particles cm(-3) and 67.56 to 2.13 x 10(3)microm(2)cm(-3), respectively. The concentrations changed dramatically depending on on-site manufacturing conditions. The NC(0.01-0.1) levels in the iron foundry were approximately 4.5 times higher on average compared with those in the outdoor ambient environment. These measurement results indicate that the presence of extra particles in the workplace air is within the ultrafine range. Additionally, the analytical results suggest that the number mode diameter can be used to estimate the SC(0.01-0.1) levels using the NC(0.01-0.1) levels. Moreover, the ultrafine particle number mode diameter was found to be about 46.1 nm in the iron foundry.

Study of an axial flow cyclone to remove nanoparticles in vacuum.

An axial flow cyclone for removing nanoparticles was tested for collection efficiency. Data were validated numerically in vacuum conditions of several Torrs, with flow rates of 0.35-0.57 slpm. The experimental cutoff aerodynamic diameter of the cyclone ranged from 21.7 to 49.8 nm. A 3-D numerical simulation was conducted first to calculate detailed flow and pressure fields, then a Brownian Dynamics simulation was done to determine the collection efficiency of nanoparticles. Both centrifugal force and Brownian diffusion were taken into account. The simulated results for both pressure drop and cutoff aerodynamic diameter are in good agreement with the experimental data. In comparison, previous theories using simplified tangential flow field assumption are not able to predict collection efficiencies accurately. The numerical model developed in this study can facilitate cyclone design to classify valuable nanopowders below a certain diameter, or to remove toxic nanoparticles from the vacuum exhaust of process chambers commonly used in high-tech industries.

Silane removal at ambient temperature by using alumina-supported metal oxide adsorbents.

Copper, zinc, and cerium oxide adsorbents supported on alumina were used to remove silane gas (SiH4). The adsorbents were prepared using a coprecipitation method and characterized by the inductively coupled plasma mass spectrometry, X-ray powder diffractometer, and Brunauer-Emmett-Teller method (BET). The silane removal efficiency and adsorption capacity of the adsorbents were investigated in this study. Test results showed that the adsorbents containing active species had a removal efficiency >99.9% for SiH4 before breakthrough. Adsorbents containing mixed oxides (CuO-CeO2/ Al2O3 and CuO-ZnO/Al2O3), which showed well-dispersed active species and high BET surface areas, had a greater adsorption capacity than the adsorbents containing single metal oxide. However, when the CuO-ZnO/ Al2O3 adsorbents contain >40 wt% of active metal oxides, the increase of active species lowered the BET surface area leading to a decrease of the adsorption capacity. Additionally, when the content of the active metal oxides was between 20% and 40%, the CuO-ZnO/Al2O3 adsorbents demonstrated higher adsorption capacity.