Original and improved interspecies correlation estimation models in China for potential application in water quality criteria.

Environ Sci Pollut Res Int

Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, 100124, China.

Published: February 2023

Fluoranthene (FLU) has gained much attention in recent years because of its continuous discharge in natural waters and toxicity to aquatic ecosystems. However, it is difficult to control and manage FLU pollution because of the lack of a rational and scientific water quality criteria (WQC) of FLU. To solve these data gaps, the US EPA established an interspecies correlation estimation (ICE) model, which can be utilized to develop the SSD and HC (hazardous concentration, 5th percentile). Moreover, an improved model was developed using a combination of North American ICE models supplemented with China-specific species. In this study, to verify the applicability of the two ICE models, measured acute toxicity data for FLU were obtained from 9 acute toxicity tests using indigenous Chinese aquatic species from different taxonomic levels. Original and improved ICE-based SSD curves, which were generated using 3 surrogate species (Daphnia magna, Oncorhynchus mykiss, and Lepomis macrochirus), were compared with SSD curves based on measured data. The results showed that HC was 1.838, 1.062, and 0.570 mg/L for the original ICE, improved ICE, and measured data, respectively. The improved ICE-based HC value for FLU was within twofold of the HC value based on measure data, while the original ICE-based HC value was threefold higher than the HC value based on measure data. This indicated that the improved ICE had better predictability in extrapolating data with acceptable deviation than the original ICE. Furthermore, their differences between HC derived from two SSD curves were not significant. Generally, the improved ICE model was verified as a valid approach for generating SSDs with limited toxicity data and for deriving WQC for FLU.

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http://dx.doi.org/10.1007/s11356-022-23612-6DOI Listing

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