Feasibility Study on Ultrasound-Assisted Emulsification Microextraction-Near Infrared Spectroscopy Technique for the Determination of Traces of Nonylphenol in Water Samples
Restricted accessResearch articleFirst published online December, 2012
Feasibility Study on Ultrasound-Assisted Emulsification Microextraction-Near Infrared Spectroscopy Technique for the Determination of Traces of Nonylphenol in Water Samples
An ultrasound-assisted emulsification microextraction-near infrared spectroscopy (USAEME-NIR) technique was applied for quantitative analysis of traces of nonylphenol in water samples. Development of the USAEME procedure included optimisation of some important parameters such as extracting temperature, time for ultrasonic-assisted emulsification and the ionic strength. Under optimised conditions, 200 μL carbon tetrachloride was injected into a 20 mL water sample and ultrasonically emulsified for 15 min. The organic phase was taken for NIR analysis after centrifuging. Using a least squares-support vector machine regression (LS-SVMR) model, the linearity and accuracy were satisfactory in the range of 600–6000 μgL−1. Promising results, with r2 = 0.99, RMSEP=44.8 μgL−1 and RPD=8.9, were achieved when the model was used to analyse for nonylphenol in water samples from local factories and sewage treatment works. The results showed that rapid determination of trace contaminants in water samples by NIR is feasible using the USAEME-NIR technique.
CevascoA.UrbatzkaR.BotteroS.MassariA.PedemonteF.KloasW. and MandichA., “Endocrine disrupting chemicals (EDC) with (anti)estrogenic and(anti)androgenic modes of action affecting reproductive biology of Xenopus laevis: II. Effects on gonad histomorphology”, Comp. Biochem. Physiol. C: Pharmacol. Toxicol.147, 241–251 (2008). doi: 10.1016/j.cbpc.2007.10.001
2.
KumarA. and XagorarakiI., “Pharmaceuticals, personal care products and endocrine-disrupting chemicals in U.S. surface and finished drinking waters: A proposed ranking system”, Sci. Total Environ.408, 5972–5989 (2010). doi: 10.1016/j.scitotenv.2010.08.048
3.
JinY.ChenR.LiuW. and FuZ., “Effect of endocrine disrupting chemicals on the transcription of genes related to the innate immune system in the early developmental stage of zebrafish (Danio rerio)”, Fish Shellfish Immun.28, 854–861 (2010). doi: 10.1016/j.fsi.2010.02.009
4.
MunckeJ., “Endocrine disrupting chemicals and other substances of concern in food contact materials: An updated review of exposure, effect and risk assessment”, J. Steroid Biochem. Mol. Biol.127, 118–127 (2010). doi: 10.1016/j.jsbmb.2010.10.004
5.
HuW.-Y.ShiG.-B.HuD.-P.NellesJ.L. and PrinsG.S., “Actions of estrogens and endocrine disrupting chemicals on human prostatestem/progenitor cells and prostate cancer risk”, Mol. Cell. Endocrinol.354, 63 (2012). doi: 10.1016/j.mce.2011.08.032
6.
VincentM.D. and SneddonJ., “Nonylphenol: An overview and its determination in oysters and wastewaters and preliminary degradation results from laboratory experiments”, Microchem. J.92, 112–118 (2009). doi: 10.1016/j.microc.2009.02.005
7.
Zgoła-GrześkowiakA.GrześkowiakT.RydlichowskiR. and ŁukaszewskiZ., “Determination of nonylphenol and short-chained nonylphenol ethoxylates in drain water from an agricultural area”, Chemosphere75, 513–518 (2009). doi: 10.1016/j.chemosphere.2008.12.022
8.
NairP.M.G. and ChoiJ., “Modulation in the mRNA expression of ecdysone receptor gene in aquatic midge, Chironomus riparius upon exposure to nonylphenol and silver nanoparticles”, Environ. Toxicol. Pharmacol.33, 98 (2012). doi: 10.1016/j.etap.2011.09.006
9.
HaoR.-X.ZhouY.-W.ChengS.-Y.LiJ.-B.ZhaoM.ChenX. and YaoN., “The accumulation of nonylphenol in a wastewater recycling process”, Chemosphere70, 783–790 (2008). doi: 10.1016/j.chemosphere.2007.07.007
10.
The European Parliament and the Council of the European Union, “Directive 2003/53/EC of the European Parliament and of the Council of 18 June 2003”, Official Journal of the European UnionL178/24–L178/26 (2003).
11.
RodilR.QuintanaJ.B.López-MahíaP.Muniategui-LorenzoS. and Prada-RodríguezD., “Multi-residue analytical method for the determination of emerging pollutants in water by solid-phase extraction and liquid chromatography-tandem mass spectrometry”, J. Chromatogr. A1216, 2958–2969 (2009). doi: 10.1016/j.chroma.2008.09.041
12.
PrietoA.SchraderS. and MoederM., “Determination of organic priority pollutants and emerging com-pounds in wastewater and snow samples using multi-residue protocols on the basis of microextraction by packed sorbents coupled to large volume injection gas chromatography–mass spectrometry analysis”, J. Chromatogr. A1217, 6002–6011 (2010). doi: 10.1016/j.chroma.2010.07.070
13.
Zgoła-Grze'skowiakA., “Dispersive liquid–liquid micro-extraction applied to isolation and concentration of alkylphenols and their short-chained ethoxylates in water samples”, J. Chromatogr. A1217, 1761–1766 (2010). doi: 10.1016/j.chroma.2010.01.054
14.
LimaK.M.G.RaimundoI.M.Jr and PimentelM.F., “Improving the detection limits of near infrared spectroscopy in the determination of aromatic hydrocarbons in water employing a silicone sensing phase”, Sens. Actuators, B125, 229–233 (2007). doi: 10.1016/j.snb.2007.02.008
15.
ZhangM.GengY. and XiangB., “Identification of dimethoate-containing water using partitioned dispersive liquid-liquid microextraction coupled with near-infrared spectroscopy”, Yakugaku Zasshi131, 977–983 (2011). doi: 10.1248/yakushi.131.977
16.
RegueiroJ.LlompartM.Garcia-JaresC.Garcia-MonteagudoJ. C. and CelaR., “Ultrasound-assisted emulsification–microextraction of emergent contaminants and pesticides in environmental waters”, J. Chromatogr. A1190, 27–38 (2008). doi: 10.1016/j.chroma.2008.02.091
17.
FontanaA.R.WuilloudR.G.MartínezL.D. and AltamiranoJ.C., “Simple approach based on ultrasound-assisted emulsification-microextraction for determination of polibrominated flame retardants in water samples by gas chromatography–mass spectrometry”, J. Chromatogr A1216, 147–153 (2009). doi: 10.1016/j.chroma.2008.11.034
18.
WuJ.XiangB. and XiaJ., “Application of ultrasound-assisted emulsification-microextraction combined with high performance liquid chromatography to the determination of propoxur in environmental and beverage samples”, Microchim Acta166, 157–162 (2009). doi: 10.1007/s00604-009-0179-6
19.
VinasP.Martínez-CastilloN.CampilloN. and Hernandez-CórdobaM., “Liquid–liquid microextraction methods based on ultrasound-assisted emulsification and single-drop coupled to gas chromatography–mass spectrometry for determining strobilurin and oxazole fungicides in juices and fruits”, J. Chromatogr. A1217, 6569–6577 (2010). doi: 10.1016/j.chroma.2010.08.046
GeladiP.MacDougallD. and MartensH., “Linearization and scatter-correction for near-infrared reflectance spectra of meat”, Appl. Spectrosc.39, 491–500 (1985). doi: 10.1366/0003702854248656
22.
BarnesR.J.DhanoaM.S. and ListerS.J., “Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra”, Appl. Spectrosc.43, 772–777 (1989). doi: 10.1366/0003702894202201
23.
FrenichA.G.GaleraM.M.VidalJ.L.M. and GarciaM.D.G., “Partial least-squares and principal component regression of multi-analyte high-performance liquid chromatography with diode-array detection”, J. Chromatogr. A727, 27–38 (1996). doi: 10.1016/0021-9673(95)01150-1
24.
WoldS.SjöströmM. and ErikssonL., “PLS-regression: A basic tool of chemometrics”, Chemometr. Intell. Lab. Syst.58, 109–130 (2001). doi: 10.1016/S0169-7439(01)00155-1
25.
LiJ.SunJ. and HeZ., “Quantitative structure-retention relationship studies with immobilized artificial membrane chromatography II: Partial least squares regression”, J. Chromatogr A1140, 174–179 (2007). doi: 10.1016/j.chroma.2006.11.091
26.
ForinaM.LanteriS. and CasaleM., “Multivariate calibration”, J. Chromatogr A1158, 61–93 (2007). doi: 10.1016/j.chroma.2007.03.082
27.
LiY.ShaoX. and CaiW., “A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples”, Talanta72, 217–222 (2007). doi: 10.1016/j.talanta.2006.10.022
28.
NiaziA.Jameh-BozorghiS. and Nori-SharghD., “Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines”, J. Hazard. Mater.151, 603–609 (2008). doi: 10.1016/j.jhazmat.2007.06.030
29.
NiaziA.SharifiS. and AmjadiE., “Least-squares support vector machines for simultaneous voltammetric determination of lead and tin: A comparison between LS-SVM and PLS in voltammetric data”, J. Electroanal. Chem.623, 86–92 (2008). doi: 10.1016/j.jelechem.2008.06.021
30.
ZhiweiG. and GuangchenB., “Application of least squares support vector machine for regression to reliability analysis”, Chin. J. Aeronaut.22, 160–166 (2009). doi: 10.1016/S1000-9361(08)60082-5
31.
XiaJ.XiangB. and ZhangW., “Determination of meta-crate in water samples using dispersive liquid–liquid microextraction and HPLC with the aid of response surface methodology and experimental design”, Anal. Chim. Acta625, 28–34 (2008). doi: 10.1016/j.aca.2008.07.020
32.
OuD.L. and SeddonA.B., “Near- and mid-infrared spectroscopy of sol–gel derived ormosils: Vinyl and phenyl silicates”, J. Non-Cryst. Solids210, 187–203 (1997). doi: 10.1016/S0022-3093(96)00585-6
33.
LuC.XiangB.HaoG.XuJ.WangZ. and ChenC., “Rapid detection of melamine in milk powder by near infrared spectroscopy”, J. Near Infrared Spectrosc.17, 59–67 (2009). doi: 10.1255/jnirs.829
