Transport and fate of metal contamination in estuaries: Using a model network to predict the contributions of physical and chemical factors

Larissa Schneider; William A. Maher; John Floyd; Jaimie Potts; Graeme E. Batley; Bernd Gruber

doi:10.1016/j.chemosphere.2016.03.019

Transport and fate of metal contamination in estuaries: Using a model network to predict the contributions of physical and chemical factors

Larissa Schneider^*, William A. Maher, John Floyd, Jaimie Potts, Graeme E. Batley, Bernd Gruber

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Original language	English
Pages (from-to)	227-236
Number of pages	10
Journal	Chemosphere
Volume	153
DOIs	https://doi.org/10.1016/j.chemosphere.2016.03.019
Publication status	Published - 1 Jun 2016

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10.1016/j.chemosphere.2016.03.019

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title = "Transport and fate of metal contamination in estuaries: Using a model network to predict the contributions of physical and chemical factors",

keywords = "Coal-fired power station, Hydrodynamic model, Lake, Lake Macquarie, Sediment",

author = "Larissa Schneider and Maher, \{William A.\} and John Floyd and Jaimie Potts and Batley, \{Graeme E.\} and Bernd Gruber",

year = "2016",

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doi = "10.1016/j.chemosphere.2016.03.019",

language = "English",

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T1 - Transport and fate of metal contamination in estuaries

T2 - Using a model network to predict the contributions of physical and chemical factors

AU - Schneider, Larissa

AU - Maher, William A.

AU - Floyd, John

AU - Potts, Jaimie

AU - Batley, Graeme E.

AU - Gruber, Bernd

PY - 2016/6/1

Y1 - 2016/6/1

KW - Coal-fired power station

KW - Hydrodynamic model

KW - Lake

KW - Lake Macquarie

KW - Sediment

UR - https://www.scopus.com/pages/publications/84961782808

U2 - 10.1016/j.chemosphere.2016.03.019

DO - 10.1016/j.chemosphere.2016.03.019

M3 - Article

SN - 0045-6535

VL - 153

SP - 227

EP - 236

JO - Chemosphere

JF - Chemosphere

ER -

Transport and fate of metal contamination in estuaries: Using a model network to predict the contributions of physical and chemical factors

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