Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore.
NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore.
Water Res. 2021 Jul 15;200:117298. doi: 10.1016/j.watres.2021.117298. Epub 2021 May 28.
We developed a comprehensive integrated water quality modeling approach towards a better understanding of the fate and transport of emerging contaminants and comprehensive assessment of their potential risks in a tropical reservoir. Two representative emerging contaminants, namely Bisphenol A (BPA) and N, N-diethyltoluamide (DEET), were selected for this study. Unlike the traditional water quality modeling approach, the target emerging contaminants were modelled in four multi-compartments and coupled to a 3D-dimensional eutrophication model to investigate their interactions with other water quality state variables. First, the integrated model was calibrated and validated in four multi-compartments against an observed dataset in 2014. Subsequently, the correlation analysis between emerging contaminants and general water quality parameters were conducted. The potential ecological risks in this reservoir were also assessed via the trophic state index (TSI) and coupled to a species sensitivity distribution (SSD)-Risk Quotient (RQ) method. Finally, the model was applied to describe the dynamics of the two emerging contaminants and examine the direct and indirect influences of other environmental factors on their multi-compartment distributions in the aquatic environment. The comprehensive approach provides new insights into dynamic modeling of the fate and transport of emerging contaminants, their interactions with other state variables as well as an assessment of their potential risks in aquatic ecosystems.
我们开发了一种全面的综合水质建模方法,以更好地了解新兴污染物的归宿和迁移,并综合评估它们在热带水库中的潜在风险。本研究选择了两种代表性的新兴污染物,即双酚 A(BPA)和 N,N-二乙基间甲苯酰胺(DEET)。与传统的水质建模方法不同,该目标新兴污染物在四个多组分中建模,并与三维富营养化模型耦合,以研究它们与其他水质状态变量的相互作用。首先,综合模型在四个多组分中针对 2014 年的观测数据集进行了校准和验证。随后,对新兴污染物与一般水质参数之间的相关性进行了分析。还通过营养状态指数(TSI)并结合物种敏感性分布(SSD)-风险商(RQ)方法评估了该水库的潜在生态风险。最后,该模型用于描述两种新兴污染物的动态,并检查其他环境因素对其在水生环境中多组分分布的直接和间接影响。这种综合方法为新兴污染物的归宿和迁移的动态建模、它们与其他状态变量的相互作用以及对水生生态系统中它们的潜在风险的评估提供了新的见解。