Issue 7, 2016

Quantitative analysis of aliphatic amines in urban aerosols based on online derivatization and high performance liquid chromatography

Abstract

A method combining online derivatization with high performance liquid chromatography/fluorescence detection was developed for the determination of seven aliphatic amines (ethanolamine, methylamine, ethylamine, propylamine, butylamine, pentylamine and hexylamine) in urban aerosols. The collected amines were online derivatized with o-phthalaldehyde to form highly fluorescent sulfonatoisoindole derivatives. The derivatives were completely separated in 13 min through gradient elution and detected by fluorescence detection at an excitation wavelength of 334 nm and an emission wavelength of 443 nm. Under the optimized conditions, the relative standard derivations (RSDs) of all detected amines were 0.02–2.03% and 1.04–1.52% for the retention time and peak area, respectively. Excellent linearity was achieved for each analyte, ranging from 5 μg L−1 to 1000 μg L−1 (R2 > 0.99). The detection limits for all analytes were below 1.1 μg L−1. The proposed method was used to analyze aliphatic amines in 35 samples of urban PM2.5 collected in Shanghai and was found to be suitable for the determination of particulate aliphatic amines at ng m−3 levels in ambient air. Based on our measurements, ethanolamine and methylamine were the most abundant species on average in Shanghai during dry and wet seasons. The highest concentration was 15.3 ng m−3 for ethanolamine and 13.2 ng m−3 for methylamine.

Graphical abstract: Quantitative analysis of aliphatic amines in urban aerosols based on online derivatization and high performance liquid chromatography

Article information

Article type
Paper
Submitted
25 Mar 2016
Accepted
24 May 2016
First published
25 May 2016

Environ. Sci.: Processes Impacts, 2016,18, 796-801

Quantitative analysis of aliphatic amines in urban aerosols based on online derivatization and high performance liquid chromatography

X. Huang, C. Deng, G. Zhuang, J. Lin and M. Xiao, Environ. Sci.: Processes Impacts, 2016, 18, 796 DOI: 10.1039/C6EM00197A

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