Application of Single-Particle Mass Spectrometer to Obtain Chemical Signatures of Various Combustion Aerosols
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, MgCO&l...
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Autores principales: | , , , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/6caa57e7ca2a452b83ebeb0b7d534aa4 |
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Sumario: | 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, MgCO<sub>3</sub>, CaCO<sub>3</sub>, and Al<sub>2</sub>O<sub>3</sub> particles with different chemical compositions; an internal mixture of NaCl and KCl; and an internal mixture of NaCl, KCl, and MgCl<sub>2</sub> 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. |
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