TY - JOUR
T1 - Predicting organic loading in natural water using spectral fluorescent signatures
AU - Bengraïne, Karim
AU - Marhaba, Taha F.
N1 - Funding Information:
This work has been funded by New Jersey Department of Environmental Protection under the A-280 Act, and by New Jersey Institute of Technology. The authors thank Dr. R. Lee Lippincott for his significant contributions and Jaime Arago for maintaining the databases and routine data for calibration analyses.
PY - 2004/5/20
Y1 - 2004/5/20
N2 - Spectral fluorescent signature (SFS) is a rapid, reagent free and inexpensive technique, which has great potential for environmental monitoring of aqueous systems, especially for predicting dissolved organic carbon (DOC) along natural waters. This technical note aimed to examine the possibility to use SFS associated with partial least squares regression (PLS) to assess the organic loading in natural water. A model was built using samples of water collected between October 1999 and February 2002 on the Passaic River at Little Falls, NJ, USA. A correlation was established between measured DOC, SFS, and the corresponding daily registered flow from United States Geological Survey (USGS) New Jersey's streamflow database. The methodology presented herein looks promising in making use of the significant organic characteristics information contained in a SFS for application and use in spatial and temporal water quality management and treatment.
AB - Spectral fluorescent signature (SFS) is a rapid, reagent free and inexpensive technique, which has great potential for environmental monitoring of aqueous systems, especially for predicting dissolved organic carbon (DOC) along natural waters. This technical note aimed to examine the possibility to use SFS associated with partial least squares regression (PLS) to assess the organic loading in natural water. A model was built using samples of water collected between October 1999 and February 2002 on the Passaic River at Little Falls, NJ, USA. A correlation was established between measured DOC, SFS, and the corresponding daily registered flow from United States Geological Survey (USGS) New Jersey's streamflow database. The methodology presented herein looks promising in making use of the significant organic characteristics information contained in a SFS for application and use in spatial and temporal water quality management and treatment.
KW - Dissolved organic carbon (DOC)
KW - Loading
KW - New Jersey
KW - Partial least square regression (PLS)
KW - Spectrofluorescence signature (SFS)
KW - Streamflow
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U2 - 10.1016/j.jhazmat.2003.12.002
DO - 10.1016/j.jhazmat.2003.12.002
M3 - Article
C2 - 15120874
AN - SCOPUS:2142812899
SN - 0304-3894
VL - 108
SP - 207
EP - 211
JO - Journal of Hazardous Materials
JF - Journal of Hazardous Materials
IS - 3
ER -