Abstract
ABSTRACTStrategies 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).
Highlights
Since the adoption of the Strategic Approach to International Chemicals Management (SAICM) framework at the International Conference on Chemicals Management in 2006, risk assessments for the management of chemicals have been actively conducted worldwide (Hase and Kitano 2012)
The 50th to 95th percentiles showed high agreement (e.g., 95th percentile, 90th percentile, 50th percentile: total measured = 13 μg/L, 7.2 μg/L, and 0.8 μg/L, respectively; total estimated = 18 μg/L, 12 μg/L, and 1.2 μg/L, respectively). These results show that AIST‐SHANEL has high accuracy for mid to high concentrations, especially for river data
Concentrations in river water based on nationwide environmental monitoring data, and showed that the model can be useful for performing spatiotemporal exposure assessments within a wide region
Summary
Since the adoption of the Strategic Approach to International Chemicals Management (SAICM) framework at the International Conference on Chemicals Management in 2006, risk assessments for the management of chemicals have been actively conducted worldwide (Hase and Kitano 2012). Environmental risk assessments for various chemicals are ongoing because understanding exposure situations in rivers across a wide range of regional conditions is important. Even for chemicals that have been monitored, the study duration and study area are often limited. A highly or at least reasonably accurate exposure assessment model is needed to estimate spatiotemporal exposure levels for a wide range of regions. Exposure assessment models for chemicals are being developed worldwide. In Europe and North America, different models have been developed based on the Uniform Substance Evaluation System (USES), including the European Union System for the Evaluation of Substances (EUSES; Vermeire et al 1997), a level III fugacity (i.e., non‐ equilibrium, steady state with advection) dynamic predictive simulation model, and the Risk Assessment, Identification
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