Globally applicable water quality simulation model for river basin chemical risk assessment

Abstract

Abstract Many companies around the world need to assess water environmental risks in accordance with sustainable development goals (SDGs) set by the United Nations, environmental, social, and governance (ESG) investment, the Carbon Disclosure Project (CDP) water program, and also their corporate social responsibility (CSR) activities. Although companies have been requested to voluntarily evaluate their water risks and provide information thereon, the water quality risk in river basins is difficult to assess owing to insufficient monitoring information. This paper proposes the National Institute of Advanced Industrial Science and Technology - Standardized Hydrology-based AssessmeNt tool for chemical Exposure Load (AIST-SHANEL) model as a river water quality simulation model that can be employed for chemical risk assessment and evaluation of the effects of use of a company's consumer products on river basins. AIST-SHANEL is the only unsteady analysis model that estimates spatial and temporal chemical concentrations and assesses water quality within river basins by point/non-point emission of chemical substances. To evaluate the efficacy of AIST-SHANEL, a case study focused on the surfactant linear alkylbenzene sulfonate (LAS), found in the detergents of widely used health care products, was conducted. The water risk assessment was performed in three Japanese river basins with different watershed characteristics: Tama River in urban Tokyo with high sewerage penetration rate, Nikko River in urban Nagoya with a low sewerage penetration rate, and the nonurban None River with no sewerage. In Tama River, the LAS river water concentrations were found to be strongly influenced by seasonal variations as well as the flow rate associated with dilution and temperature-induced biodegradation. Their concentrations in Nikko River were strongly affected by flooding, indicating that the influence on their transport through the drainage channel was due more to low sewage levels than temperature-induced biodegradation. In None River, the LAS river water concentrations were only slightly affected by dilution. The river sediment concentrations of LAS in the three river basins showed mild seasonal variations. The 95th percentile of river water concentrations, predicted environmental concentration (PEC), at the most downstream and maximum concentration grids in the three river basins were 4.5 and 51.2 mg/m3 for Tama River, 30 and 58.6 mg/m3 for Nikko River, and 0.15 mg/m3 for None River. Neither of the PECs nor maximum values at these grids exceeded the predicted no-effect concentration (PNEC) of LAS (270 mg/m3), suggesting minimal ecological risk in these river basins over the year for all target river basins due to LAS. Furthermore, we analyzed a scenario in which LAS was substituted with the highly biodegradable alcohol ethoxylates (AE) for corporate self-management measures in Nikko River with only a few sewers, and therefore only a low risk. The AIST-SHANEL model has useful and widespread application with no need for monitoring by companies; as long as the relevant watershed characteristics can be obtained, water risk assessments of chemical substances can be performed for any river basin in the world.