Issue 3, 2020

Summation of disinfection by-product CHO cell relative toxicity indices: sampling bias, uncertainty, and a path forward

Abstract

The cyto- and genotoxic potencies of disinfection by-products (DBPs) have been evaluated in published literature by measuring the response of exposed Chinese hamster ovary cells. In recent publications, DBP concentrations divided by their individual toxicity indices are summed to predict the relative toxicity of a water sample. We hypothesized that the omission or inclusion of certain DBPs over others is equivalent to statistical sampling bias and may result in biased conclusions. To test this hypothesis, we removed or added actual or simulated DBP measurements to that of published studies which evaluated granular activated carbon as a treatment to reduce the relative toxicity of the effluent. In several examples, it was possible to overturn the conclusions (i.e., activated carbon is detrimental or beneficial in reducing toxicity) by preferentially including specific DBPs. In one example, removing measured haloacetaldehydes caused the predicted cytotoxicity of a treated sample to decrease by up to 47%, reversing the initial conclusion that activated carbon increased the toxicity of the water. We also discuss measurements of statistical error, which are rarely included in publications related to predicted toxicity, but strongly influence the outcomes. Finally, we discuss future research needs in the light of these and other concerns.

Graphical abstract: Summation of disinfection by-product CHO cell relative toxicity indices: sampling bias, uncertainty, and a path forward

Supplementary files

Article information

Article type
Paper
Submitted
15 Okt. 2019
Accepted
12 Dec. 2019
First published
13 Dec. 2019

Environ. Sci.: Processes Impacts, 2020,22, 708-718

Author version available

Summation of disinfection by-product CHO cell relative toxicity indices: sampling bias, uncertainty, and a path forward

E. McKenna, K. A. Thompson, L. Taylor-Edmonds, D. L. McCurry and D. Hanigan, Environ. Sci.: Processes Impacts, 2020, 22, 708 DOI: 10.1039/C9EM00468H

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