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Evaluation of potential relationships between chemical contaminants in sediments and aquatic organisms from the lower Passaic River, New Jersey, USA.

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Title: Evaluation of potential relationships between chemical contaminants in sediments and aquatic organisms from the lower Passaic River, New Jersey, USA.
Authors: Iannuzzi, Jacqueline1 jackie.iannuzzi@arcadis-us.com, Butcher, Matthew2, Iannuzzi, Timothy1
Source: Environmental Toxicology & Chemistry. Jul2011, Vol. 30 Issue 7, p1721-1728. 8p.
Subjects: Polycyclic aromatic hydrocarbons, Toxicology of water pollution, Biosensors, Immunoassay, Monoclonal antibodies, Gas chromatography/Mass spectrometry (GC-MS)
Abstract: The lower Passaic River, New Jersey, USA, a tidal tributary to Newark Bay and part of the New York and New Jersey Harbor Estuary, is contaminated with a variety of persistent organic pollutants (POPs) due to nearly two centuries of heavy industrialization and urbanization. Resident aquatic organisms are exposed to, and can bioaccumulate, a variety of chemical contaminants from sediments, water and other organisms. In the present study, the relationships between selected POPs detected in both surface sediments and aquatic organisms are examined statistically along with the efficacy of using empirical biota-sediment accumulation factors (BSAFs) to describe such relationships. Regression analyses were conducted on synoptic surface sediment POP data (0 to 15 cm in depth) and whole-body tissue POP data for three prominent organisms that reside in the river and which are important components of the food web: mummichog ( Fundulus heteroclitus), blue crab ( Callinectes sapidus), and white perch ( Morone americana). Per the equilibrium partitioning theory on which the BSAF model is based, surface sediment data were normalized to total organic carbon and tissue data were normalized to lipid content for each organism. Normalized surface sediment concentrations were generally poorly correlated with normalized biota tissue concentrations. The BSAF model was not found to be a reliable means to predict concentrations of POPs in select lower Passaic River organisms, using surface sediment chemistry data. Environ. Toxicol. Chem. 2011; 30:1721-1728. © 2011 SETAC [ABSTRACT FROM AUTHOR]
Copyright of Environmental Toxicology & Chemistry is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Evaluation of potential relationships between chemical contaminants in sediments and aquatic organisms from the lower Passaic River, New Jersey, USA.
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  Data: <searchLink fieldCode="AR" term="%22Iannuzzi%2C+Jacqueline%22">Iannuzzi, Jacqueline</searchLink><relatesTo>1</relatesTo><i> jackie.iannuzzi@arcadis-us.com</i><br /><searchLink fieldCode="AR" term="%22Butcher%2C+Matthew%22">Butcher, Matthew</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Iannuzzi%2C+Timothy%22">Iannuzzi, Timothy</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Toxicology+%26+Chemistry%22">Environmental Toxicology & Chemistry</searchLink>. Jul2011, Vol. 30 Issue 7, p1721-1728. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Polycyclic+aromatic+hydrocarbons%22">Polycyclic aromatic hydrocarbons</searchLink><br /><searchLink fieldCode="DE" term="%22Toxicology+of+water+pollution%22">Toxicology of water pollution</searchLink><br /><searchLink fieldCode="DE" term="%22Biosensors%22">Biosensors</searchLink><br /><searchLink fieldCode="DE" term="%22Immunoassay%22">Immunoassay</searchLink><br /><searchLink fieldCode="DE" term="%22Monoclonal+antibodies%22">Monoclonal antibodies</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+chromatography%2FMass+spectrometry+%28GC-MS%29%22">Gas chromatography/Mass spectrometry (GC-MS)</searchLink>
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  Data: The lower Passaic River, New Jersey, USA, a tidal tributary to Newark Bay and part of the New York and New Jersey Harbor Estuary, is contaminated with a variety of persistent organic pollutants (POPs) due to nearly two centuries of heavy industrialization and urbanization. Resident aquatic organisms are exposed to, and can bioaccumulate, a variety of chemical contaminants from sediments, water and other organisms. In the present study, the relationships between selected POPs detected in both surface sediments and aquatic organisms are examined statistically along with the efficacy of using empirical biota-sediment accumulation factors (BSAFs) to describe such relationships. Regression analyses were conducted on synoptic surface sediment POP data (0 to 15 cm in depth) and whole-body tissue POP data for three prominent organisms that reside in the river and which are important components of the food web: mummichog ( Fundulus heteroclitus), blue crab ( Callinectes sapidus), and white perch ( Morone americana). Per the equilibrium partitioning theory on which the BSAF model is based, surface sediment data were normalized to total organic carbon and tissue data were normalized to lipid content for each organism. Normalized surface sediment concentrations were generally poorly correlated with normalized biota tissue concentrations. The BSAF model was not found to be a reliable means to predict concentrations of POPs in select lower Passaic River organisms, using surface sediment chemistry data. Environ. Toxicol. Chem. 2011; 30:1721-1728. © 2011 SETAC [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Environmental Toxicology & Chemistry is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jul2011
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