Keyword search (4,164 papers available)

"river" Keyword-tagged Publications:

Title Authors PubMed ID
1 Organic chemicals of Arctic concern in Russian coastal seas Min XZ; Zhang X; Xie ZY; Nikolaev A; Vorkamp K; Ma JM; Reiersen LO; Li L; Cai MH; Ren NQ; Li YF; Zhang ZF; Kallenborn R; Muir D; 41571477
CHEMBIOCHEM
2 A DiffeRential Evolution Adaptive Metropolis (DREAM)-based inverse model for continuous release source identification in river pollution incidents: Quantitative evaluation and sensitivity analysis Zhu Y; Cao H; Gao Z; Chen Z; 38309421
ENCS
3 Facilitation strength across environmental and beneficiary trait gradients in stream communities Tumolo BB; Albertson LK; Daniels MD; Cross WF; Sklar LL; 37555442
CONCORDIA
4 Development of a DREAM-based inverse model for multi-point source identification in river pollution incidents: Model testing and uncertainty analysis Zhu Y; Chen Z; 36191500
ENCS
5 Survey of Cooperative Advanced Driver Assistance Systems: From a Holistic and Systemic Vision González-Saavedra JF; Figueroa M; Céspedes S; Montejo-Sánchez S; 35459025
ENCS
6 A regional numerical environmental multimedia modeling approach to assess spatial Eco-Environmental exposure risk of perfluorooctane sulfonate (PFOS) in the Pearl river basin Chen Z; Dong J; Asif Z; 35121494
ENCS
7 Identification of point source emission in river pollution incidents based on Bayesian inference and genetic algorithm: Inverse modeling, sensitivity, and uncertainty analysis Zhu Y; Chen Z; Asif Z; 34380214
ENCS
8 A comprehensive investigation of industrial plastic pellets on beaches across the Laurentian Great Lakes and the factors governing their distribution. Corcoran PL, de Haan Ward J, Arturo IA, Belontz SL, Moore T, Hill-Svehla CM, Robertson K, Wood K, Jazvac K 32781316
CONCORDIA

 

Title:A regional numerical environmental multimedia modeling approach to assess spatial Eco-Environmental exposure risk of perfluorooctane sulfonate (PFOS) in the Pearl river basin
Authors:Chen ZDong JAsif Z
Link:https://pubmed.ncbi.nlm.nih.gov/35121494/
DOI:10.1016/j.envint.2022.107101
Publication:Environment international
Keywords:Environmental multimedia modelHealth riskNumerical analysisPFOSRiver basinSpatiotemporal resolution
PMID:35121494 Category: Date Added:2022-02-05
Dept Affiliation: ENCS
1 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal H3G 1M8, Canada. Electronic address: zhichen@bcee.concordia.ca.
2 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal H3G 1M8, Canada.

Description:

This paper presents a novel numerical environmental multimedia modeling system (RNEMM) for assessing the environmental fate of emerging organic contaminants and their relative health risk at a regional scale. The RNEMM is developed based on an integrated numerical algorithm that comprises four sub-models: a river network simulation module, a gaseous phase simulation module, a mass balance based simulation module for soil compartment, and a food web analysis module. This RNEMM has been applied to simulate the spatial distribution of PFOS and assess the consequent health risks for a central water basin region of the Pearl River in China. The study region includes the urban areas of Guangzhou, Foshan, and Dongguan Cities with emission sources of PFOS, which was detected in local water, sediments, and air environment. The spatial concentration distributions of PFOS in water, sediment, air, soil, and various fish species are examined based on RNEMM and compared with the measured data. With a focus on water environment, it shows that the simulated results essentially agree well with measured concentrations. Comparing the simulated results and the measured data collected in 2013, the relative errors are mostly less than 40 % in the surface water and sediment zones for this regional scale field study. Whereas the relative error in the atmosphere zone is less than 5%. In addition, the health risk assessment for children and adults is conducted based on the RNEMM approach. The hazard quotient (HQ) values for the 95th percentile in most subareas of the study region are higher than 0.1, showing a low-risk level for the study period. The results indicate that the RNEMM is a useful modeling tool to manage the environmental and health risks associated with emerging contaminants on regional air, water, soil, and ecosystem at an adequate spatial-temporal resolution.





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