Validation of AIST‐SHANEL Model Based on Spatiotemporally Extensive Monitoring Data of Linear Alkylbenzene Sulfonate in Japan: Toward a Better Strategy on Deriving Predicted Environmental Concentrations

ABSTRACT Strategies for deriving predicted environmental concentrations (PECs) using environmental exposure models have become increasingly important in the environmental risk assessment of chemical substances. However, many strategies are not fully developed owing to uncertainties in the derivation of PECs across spatially extensive areas. Here, we used 3‐year environmental monitoring data (river: 11 702 points; lake: 1867 points; sea: 12 points) on linear alkylbenzene sulfonate (LAS) in Japan to evaluate the ability of the National Institute of Advanced Industrial Science and Technology (AIST)‐Standardized Hydrology‐Based Assessment Tool for the Chemical Exposure Load (SHANEL) model developed to predict chemical concentrations in major Japanese rivers. The results indicate that the estimation ability of the AIST‐SHANEL model conforms more closely to the actual measured values in rivers than it does for lakes and seas (correlation coefficient: 0.46; proportion within the 10× factor range: 82%). In addition, the 95th percentile, 90th percentile, 50th percentile, and mean values of the distributions of the measured values (14 µg/L, 8.2 µg/L, 0.88 µg/L, and 3.4 µg/L, respectively) and estimated values (19 µg/L, 13 µg/L, 1.4 µg/L, and 4.2 µg/L, respectively) showed high concordance. The results suggest that AIST‐SHANEL may be useful in estimating summary statistics (e.g., 95th and 90th percentiles) of chemical concentrations in major rivers throughout Japan. Given its practical use and high accuracy, these environmental risk assessments are suitable for a wide range of regions and can be conducted using representative estimated values, such as the 95th percentile. Integr Environ Assess Manag 2019;15:750–759. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points The performance of an environmental exposure model, AIST–SHANEL, for estimating chemical concentration in rivers was evaluated using comprehensive measurement data from major rivers throughout Japan. The estimated spatiotemporal LAS concentrations, especially the 95th and 90th percentiles, were in good agreement with the measured concentrations. Using representative estimated values, e.g., 95th percentile, AIST–SHANEL can precisely estimate chemical concentrations in major rivers throughout Japan, and can contribute to high–accuracy environmental risk assessments.