Development and use of interspecies correlation estimation models in China for potential application in water quality criteria

Establishment of numerical water quality criteria (WQC) has brought increasing interest in China. However, toxicity data to develop robust WQC values (number of toxicity data >= 8) of contaminants based solely on endemic and indigenous species are insufficient. In this study, interspecies correlation estimation (ICE) models were developed using a combination of North American ICE models supplemented with China-specific species to resolve this problem. A total of 207 significant surrogate-predicted models (p < 0.05, F-test) were derived: 119, 66 and 22 models for vertebrates, invertebrates and plant surrogate species, respectively. Model cross-validation success rate (>= 80%), mean square error (MSE, <= 0.54), R-2 (>= 0.78) and taxonomic distance (<= 4, within the same class) were selected as guiding criteria to screen the resulted ICE models. The differences of 5th percentile hazard concentrations (HC5s) for 6 chemicals (2,4-dichlorophenol, triclosan, tetrabromobisphenol A, nitrobenzene, perfluorooctane sulfonate and octabromodiphenyl ether) calculated from ICE-based and measured toxicity-based SSDs were within 3-fold among models. Although the number of derived ICE models was not comprehensive and continues to be improved, they can already be used in the development of WQC targeting protection of aquatic life and environmental risk assessments for chemicals lacking toxicity data. (C) 2019 Elsevier Ltd. All rights reserved.