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Optimization of the Efficient Extraction of Organic Components in Atmospheric Particulate Matter by Accelerated Solvent Extraction Technique and Its Application.

Authors :
Zhang, Hao
Ren, Yanqin
Wei, Jie
Ji, Yuanyuan
Bai, Xurong
Shao, Yanqiu
Li, Hong
Gao, Rui
Wu, Zhenhai
Peng, Zhijian
Xue, Feng
Source :
Atmosphere; May2022, Vol. 13 Issue 5, p818, 14p
Publication Year :
2022

Abstract

Organic components in atmospheric fine particulate matter have attracted much attention and several scientific studies have been performed, although most of the sample extraction methods are time consuming and laborious. Accelerated solvent extraction (ASE) is a new sample extraction method offering number of advantages, such as low extraction cost, reduced solvent and time consumption, and simplified extraction protocols. In order to optimize ASE methods to determine the concentrations of organic compounds in atmospheric fine particulate matter, different parameters were set out for the experiment, and the optimal method was selected according to the recoveries of the standard (i.e., n−alkanes and polycyclic aromatic hydrocarbons (PAHs)). This study also involves a comparison of the optimal method with the traditional method of ultrasonic extraction (USE). In addition, the optimized method was applied to measure the mass concentrations of organic compounds (n−alkanes and PAHs) in fine particulate matter samples collected in Beijing. The findings showed that the average recovery of target compounds using ASE was 96%, with the majority of compounds falling within the confidence levels, and the ASE recoveries and precision were consistent with the USE method tested. Furthermore, ASE combines the advantages of high extraction efficiency, automation, and reduced solvent use. In conclusion, the optimal ASE methods can be used to extract organic components in atmospheric particulate matter and serve as a point of reference for the development of analytical methodologies for assessing organic compounds in atmospheric particulate matter in China. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734433
Volume :
13
Issue :
5
Database :
Complementary Index
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
157129212
Full Text :
https://doi.org/10.3390/atmos13050818