The determination of the collection efficiency (CE) of particles during transport, vaporization, and ionization in the aerosol mass spectrometer (AMS), which uses vaporizer to evaporate non-refractory particles with subsequent ionization, is important for accurately quantifying the concentrations of chemical constituents. Particle bounce in the vaporizer can be considered as one of the most important parameters influencing the CE of particles. Substrates with various shapes (flat, cylindrical, reverse-conical, cup, trapezoidal, and reverse-T), materials (stainless steel, copper, tungsten, and molybdenum), pores with average sizes of 0.2, 1, 5, 20, and 100 mm, and mesh with a size of 79 mm, which can be a possible candidate for the vaporizer in the AMS, were constructed. Bounce fractions of sub-micrometer particles (polystyrene latex, oleic acid, and dioctyl phthalate) were determined using the differential mobility analyzer (DMA)-impactor technique under a constant impact velocity. For the porous substrate, the particle bounce fraction significantly decreased with increasing pore size and porosity, but there was an upper limit for the pore size above which the particle bounce fraction no longer decreased significantly (i.e., the rebounded particles successfully escaped from the pores). The mesh substrate also had a lower particle bounce fraction than the flat substrate. Among the tested materials, the copper substrate having the lowest hardness and elasticity had the lowest particle bounce fraction. In addition, the reverse-T shape substrate having more available surfaces for particle entrapment led to the reduction of particle bounce fraction. In terms of phase, the liquid particles had lower particle bounce fractions than the solid particles. Our results suggest that the vaporizer in the AMS should provide traps for multiple collisions of the rebounding particles with an appropriate porosity or mesh and should be made of lowhardness materials to minimize particle bounce.

The destruction study of NF3 gas emitted from the semiconductor industry is performed with electron-beam technology.Absorbed dose (kGy) and current ranged from 0 (0) to 400 kGy (20 mA). The concentration of NF3 gas ranged from 500 to 2,000 ppm. In order to assess the effect of a residence time on DRE (Destruction and Removal Efficiency, %), experiments also conducted at different irridiation times of 5 sec, 10 sec, 15 sec and 20 sec respectively. As absorbed dose and current increased, DRE of NF3 was also increased. However, DRE (%) of NF3 decreased with increasing the concentration of NF3 gas. The DRE of NF3 was about 90% at an absorbed dose of 400 kGy.

A single-particle mass spectrometer (SPMS) with laser ionization was constructed to determine the chemical composition of single particles in real time. The technique was evaluated using various polystyrene latex particles with different sizes (125 nm, 300 nm, 700 nm, and 1000 nm); NaCl, KCl, MgCO3, CaCO3, and Al2O3 particles with different chemical compositions; an internal mixture of NaCl and KCl; and an internal mixture of NaCl, KCl, and MgCl2 with different mixing states. The results show that the SPMS can be useful for the determination of chemical characteristics and mixing states of single particles in real time. The SPMS was then applied to obtain the chemical signatures of various combustion aerosols (diesel engine exhaust, biomass burning (rice straw), coal burning, and cooking (pork)) based on their single-particle mass spectra. Elemental carbon (EC)-rich and EC-organic carbon (OC) particles were the predominant particle types identified in diesel engine exhaust, while K-rich and EC-OC-K particles were observed among rice straw burning emissions. Only one particle type (ash-rich particles) was detected among coal burning emissions. EC-rich and EC-OC particles were observed among pork burning particles. The single-particle mass spectra of the EC or OC types of particles differed among various combustion sources. The observed chemical signatures could be useful for rapidly identifying sources of atmospheric fine particles. In addition, the detected chemical signatures of the fine particles may be used to estimate their toxicity and to better understand their effects on human health.

No abstract