Issue 11, 2021

Microcystin in source water: pollution characteristics and human health risk assessment

Abstract

Frequent cyanobacterial blooms in eutrophic waters produce a variety of toxins such as microcystins (MCs), which are seriously harmful to waterbodies and human health. The spatiotemporal distribution characteristics of the MC-LR concentration in drinking water sources in seven river basins in China were investigated in this study. The removal rate of MC-LR in the purification process of water treatment plants and the human health risk of MC-LR in drinking water are also discussed. The results show that the detection frequency of MC-LR in source water was 55.46% and its concentration ranged from 0.06 × 10−3 to 52 × 10−3 μg L−1 (mean of 12.47 × 10−3 μg L−1), which are both below China's drinking water quality standard for algal toxins. The MC-LR concentration in lakes and reservoirs was higher than that in rivers, and exhibited an obvious spatiotemporal variation. The mean removal rate of MC-LR varied with river basin, and was also slightly higher for the advanced water treatment process (97.46%) in comparison to that of the conventional process (96.74%). The concentration of MC-LR in 8.26% of treated water samples was higher than that of raw water, thus indicating that MC-LR may be further released during the purification process. The risk index of MC-LR in treated water samples ranged from 2.29 × 10−3 to 8.40 × 10−3 (mean of 4.73 × 10−3), which corresponded to an extremely low level of risk. However, intensive monitoring should still be carried out in some high-concentration watersheds during the summer to ensure the safety of public drinking water.

Graphical abstract: Microcystin in source water: pollution characteristics and human health risk assessment

Article information

Article type
Paper
Submitted
22 Oct 2020
Accepted
18 Jan 2021
First published
04 Feb 2021
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2021,11, 6415-6422

Microcystin in source water: pollution characteristics and human health risk assessment

S. Ge, X. Qiao, X. Zhao, X. Li and Y. Liu, RSC Adv., 2021, 11, 6415 DOI: 10.1039/D0RA08983D

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