Advancing prediction of emerging contaminants in a tropical reservoir with general water quality indicators based on a hybrid process and data-driven approach-Reference-Cited by-同舟云学术

Advancing prediction of emerging contaminants in a tropical reservoir with general water quality indicators based on a hybrid process and data-driven approach

Published:2022-05 Issue: Volume:430 Page:128492
ISSN:0304-3894
Container-title:Journal of Hazardous Materials
language:en
Short-container-title:Journal of Hazardous Materials

Author:

Tong Xuneng,You Luhua,Zhang Jingjie,He Yiliang,Gin Karina Yew-Hoong

Funder

National Natural Science Foundation of China National Outstanding Youth Science Fund Project

Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology

National Research Foundation of Singapore

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference61 articles.

1. Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models;Allen;J. Mar. Syst.,2007

2. Simulation of the fate of selected pharmaceuticals and personal care products in a highly impacted reach of a Canadian watershed;Arlos;Sci. Total Environ.,2014

3. Position Paper A general framework for dynamic emulation modelling in environmental problems;Castelletti;Q. Environ. Model. Softw.,2012

4. Extended suspect screening to identify contaminants of emerging concern in riverine and coastal ecosystems and assessment of environmental risks;Čelić;J. Hazard. Mater.,2021

5. Modeling water quality in an urban river using hydrological factors e Data driven approaches;Chang;J. Environ. Manag.,2015

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Characterizing PFASs in aquatic ecosystems with 3D hydrodynamic and water quality models;Environmental Science and Ecotechnology;2024-11

2. Recent progress in ceramic membrane technology for the removal of emerging contaminant from wastewater: a critical review;Chemical Engineering Communications;2024-09-13

3. A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments;Water Research;2024-09

4. Predicting Antibiotic Resistance and Assessing the Risk Burden from Antibiotics: A Holistic Modeling Framework in a Tropical Reservoir;Environmental Science & Technology;2024-04-01

5. A study on identifying synergistic prevention and control regions for PM2.5 and O3 and exploring their spatiotemporal dynamic in China;Environmental Pollution;2024-01