Issue 8, 2017, Issue in Progress

Polycyclic aromatic hydrocarbons in traditional Chinese medicines: an analytical method based on different medicinal parts, levels, distribution, and sources

Abstract

Herein, we describe a rapid, easy, and cost-effective high-performance liquid chromatography method using UV and fluorescence detectors for the simultaneous analysis of 16 polycyclic aromatic hydrocarbons (PAHs) in traditional Chinese medicines (TCMs). Pretreatment involved different extraction methods depending on the different medicinal parts, and was followed by silica gel purification. The method was validated and used to assess PAHs contamination in 32 TCMs. In the samples analyzed, all 16 PAHs were present. Their total contents ranged from 19.5 to 1614.1 μg kg−1. Among all PAHs studied, phenanthrene was the most common and serious contaminant, followed by fluorene and fluoranthene. Leaves had the highest levels of the 16 PAHs, followed by roots and stems, seeds, flowers, and fruits. The diagnostic ratios and principle component analysis showed that the main sources of PAHs in TCMs were both pyrogenic and petrogenic. Furthermore, PAHs in roots and stems primarily originated from wood or coal combustion, as reported for the first time. Our results suggest that PAHs contamination in TCMs is widespread, and that the proposed method may be a useful tool for quality control of PAHs in TCMs, and for determining their potential health risks.

Graphical abstract: Polycyclic aromatic hydrocarbons in traditional Chinese medicines: an analytical method based on different medicinal parts, levels, distribution, and sources

Supplementary files

Article information

Article type
Paper
Submitted
03 Oct 2016
Accepted
28 Nov 2016
First published
16 Jan 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 4671-4680

Polycyclic aromatic hydrocarbons in traditional Chinese medicines: an analytical method based on different medicinal parts, levels, distribution, and sources

B. Yu, D. Zhang, L. Tan, S. Zhao, J. Wang, L. Yao and W. Cao, RSC Adv., 2017, 7, 4671 DOI: 10.1039/C6RA24682F

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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