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The quality of chemical management depends more or less on practical procedures used to assess chemicals. This study quantitatively assessed the efficacy of a derivation procedure for calculating no‐effect concentrations for screening assessment of environmental hazards under the Chemical Substance Control Law in Japan. We first evaluated the derivation procedure by applying a series of test ecotoxicity datasets to the procedure and calculating the resulting misclassification rates of the hazardous class of chemicals. In this study, a chemical was deemed to have been misclassified if its classification differed from its classification based on the full dataset (chronic toxicity data for three trophic levels), which was defined as the correct assignment. We also calculated the effects of additional uncertainty factors to decrease the variance (i.e., to improve the consistency) of the misclassification rates among cases with different data availability in the derivation procedure. The results showed that the derivation procedure resulted in very high rates of misclassification when only particular sets of ecotoxicity data were available (e.g., only chronic toxicity data of algae were available). Our analyses also showed that the use of additional uncertainty factors improved the consistency of the misclassification rates within the derivation procedure. Our study presents a broadly applicable calculation framework for quantifying error rates in assessment procedures and serves as a case study for future development and reforms of chemical assessment processes and policies, while additional analyses using more extensive ecotoxicity data with various modes of actions are needed in the future. [ABSTRACT FROM AUTHOR]

Field surveys provide valuable empirical information about the effects of heavy metals on the biological integrity of river ecosystems. To evaluate the effect of nickel (Ni) on aquatic organisms, we conducted field surveys of benthic invertebrates and Ni concentrations at 45 sites in 19 rivers in Japan. We examined the relationships between 11 structural or functional measures of benthic invertebrate communities and free Ni ion concentrations with a 90th quantile regression model. Among the measures, Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, total wet biomass of all invertebrates, and total abundance of filter feeders were negatively associated with free Ni ion concentrations. The total abundance of mud burrowers and their percentage contribution to the abundance of all invertebrates as well as the total abundances of collector‐gatherers and predators were positively associated with the Ni ion concentrations. The free ion concentrations of Ni associated with a 5% reduction of one of the 3 measures from its 90th quantile value at reference sites (EC5) were estimated to be 0.2 to 7.6 µg/L. The point estimates of EC5 were similar in order of magnitude to the environmental quality standard for Ni in the European Union. However, the usefulness of simple point estimates of effective concentrations based on quantile regression lines should be carefully examined because the uncertainties in our EC5 values were large. Environ Toxicol Chem 2019;38:1728–1737. © 2019 SETAC [ABSTRACT FROM AUTHOR]

Application of herbicides to paddy fields in Japan has strong seasonality, and their environmental concentrations exhibit clear spatiotemporal variation. The authors developed an approach that combines a multimedia environmental exposure model (Grid- Catchment Integrated Modeling System) and density dynamics models for algae. This approach enabled assessment of ecological risk when the exposure concentration shows spatiotemporal variation. First, risk maps of 5 herbicides (pretilachlor, butachlor, simetryn, mefenacet, and esprocarb) were created from the spatial predictions of environmental concentrations and 50% inhibitory concentrations of the herbicides. Simulations of algal density dynamics at high-risk sites were then conducted by incorporating the predicted temporal dynamics of the environmental concentration of each herbicide at the sites. The results suggested that the risk of pretilachlor was clearly the highest of the 5 herbicides, in terms of both the spatial distributions and the temporal durations. The present study highlights the importance of integrating exposure models and effect models to clarify spatial and temporal risk and to develop management plans for chemical exposure that shows high spatiotemporal variation. [ABSTRACT FROM AUTHOR]