Estimating the combined toxicity by two-step prediction model on the complicated chemical mixtures from wastewater treatment plant effluents

• Published in: Environmental toxicology and chemistry 2006-08, Vol.25 (8), p.2107-2113
• Main Authors: Ra, Jin Sung, Lee, Byoung Cheun, Chang, Nam Ik, Kim, Sang Don
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Animals; Applied ecology; Applied sciences; Biological and medical sciences; Chemicals; Daphnia - drug effects; Daphnia magna; Ecotoxicology, biological effects of pollution; Effluents; Environmental management; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects; Industrial Waste; Mass spectrometry; Methods; Mixture toxicity; Models, Theoretical; Pollution; Prediction models; Predictions; Seedlings; Toxicity; Two-step predictions; Wastewater treatment plant effluents; Wastewater treatment plants; Wastewaters; Water Pollutants, Chemical - toxicity; Water treatment; Water treatment and pollution
• ISSN: 0730-7268; 1552-8618
• DOI: 10.1897/05-484R.1

The toxicities of chemical mixtures containing 10 compounds, detected in wastewater treatment plant (WWTP) effluents, were investigated using Daphnia magna in a two‐step prediction (TSP) model. The 10 chemicals determined by gas chromatography/mass spectrometry in WWTP effluents included three groups: Three acetylcholinesterase inhibitors, six narcosis inhibitors, and one seedling root inhibitor. In the first step, a concentration addition (CA) model was used to predict the mixture toxicities for the three component groups with similar modes of action; in the second step, an independent action (IA) model was used for the newly developed concentration–response curves from the three CA predictions. The CA predictions did not show a statistically significant difference from the observed results with respect to the three groups of chemicals, whereas the IA model did not conform to the experimental results. Therefore, the concentration–response curves obtained from the mixture toxicity tests in each group was considered as a single curve and applied in the next step of the mixture toxicity prediction. However, the observed toxicity of the 10‐chemical mixture showed large differences from the results of the IA and CA model predictions, whereas the TSP model predicted the toxicity well and with statistical significance (p = 0.0501, n = 17). This suggests that the TSP model would provide a valid prediction for a randomly selected chemical mixture having various modes of action if the concentration–response function for an individual component is obtained.