title: [Investigation of quantitative detection of water quality using spectral fluorescence signature].
abstract: A method of spectral analysis, which can simultaneously detect dissolved organic matter (DOM) and chlorophyll a (Chl-a) in natural water, was developed in the present paper with the intention of monitoring water quality fast and quantitatively. Firstly, the total luminescence spectra (TLS) of water sample from East Lake in Wuhan city were measured by the use of laser (532 nm) induced fluorescence (LIF). There were obvious peaks of relative intensity at the wavelength value of 580, 651 and 687 nm in the TLS of the sample, which correspond respectively to spectra of DOM, and the Raman scattering of water and Chl-a in the water. Then the spectral fluorescence signature (SFS) technique was adopted to analyze and distinguish spectral characteristics of DOM and Chl-a in natural water. The calibration curves and function expressions, which indicate the relation between the normalized fluorescence intensities of DOM and Chl-a in water and their concentrations, were obtained respectively under the condition of low concentration(< 40 mg x L(-1))by using normalization of Raman scattering spectrum of water. The curves have a high linearity. When the concentration of the solution with humic acid is large (> 40 mg x L(-1)), the Raman scattering signal is totally absorbed by the molecules of humic acid being on the ground state, so the normalization technique can not be adopted. However the function expression between the concentration of the solution with humic acid and its relative fluorescence peak intensity can be acquired directly with the aid of experiment of fluorescence spectrum. It is concluded that although the expression is non-linearity as a whole, there is a excellent linear relation between the fluorescence intensity and concentration of DOM when the concentration is less than 200 mg x L(-1). The method of measurement based on spectral fluorescence signature technique and the calibration curves gained will have prospects of broad application. It can recognize fast what pollutants are and detect quantitatively their contents in water. It is realizable to monitor the quality of natural water with real time, dynamics and inlarge area.
authors.affiliation: The School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China.
authors.forename: Jun-hua
authors.initials: JH
authors.lastname: He
authors.forename: Yong-jin
authors.initials: YJ
authors.lastname: Cheng
authors.forename: Yan-ling
authors.initials: YL
authors.lastname: Han
authors.forename: Hao
authors.initials: H
authors.lastname: Zhang
authors.forename: Tao
authors.initials: T
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D002734:Chlorophyll / Q000032:analysis* / Q000737:chemistry; D004784:Environmental Monitoring / Q000379:methods; D005618:Fresh Water / Q000032:analysis* / Q000737:chemistry / Q000382:microbiology; D009930:Organic Chemicals / Q000032:analysis*; D045483:Rivers / Q000737:chemistry / Q000382:microbiology; D013050:Spectrometry, Fluorescence; D014871:Water Microbiology; D014876:Water Pollution / Q000032:analysis*
chemical_list: D009930:Organic Chemicals; D002734:Chlorophyll