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FLUORESCENCE AS A TOOL FOR THE CHARACTERIZATION OF WATER AquaLife 2010 Martin Wagner, Technologiezentrum Wasser (TZW) Außenstelle Dresden.

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Presentation on theme: "FLUORESCENCE AS A TOOL FOR THE CHARACTERIZATION OF WATER AquaLife 2010 Martin Wagner, Technologiezentrum Wasser (TZW) Außenstelle Dresden."— Presentation transcript:

1 FLUORESCENCE AS A TOOL FOR THE CHARACTERIZATION OF WATER AquaLife 2010 Martin Wagner, Technologiezentrum Wasser (TZW) Außenstelle Dresden

2 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Outline Principles of fluorescence spectroscopy Characterization of DOC Problems in quantification of fluorescence signals

3 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Measurement of fluorescence Design of a fluorescence spectrometer I. Principles of fluorescence spectroscopy

4 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Measurement of fluorescence Emission spectrum: λ Ex = const., λ Em I. Principles of fluorescence spectroscopy

5 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Measurement of fluorescence Variation of λ Ex produces an excitation-emission- matrix, called EEM I. Principles of fluorescence spectroscopy λ Emission λ Excitation Intensity

6 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Characterization of water II. Characterization of DOC Chl AChlorophyll A PCPhycocyanin PEPhycoerythrin FCFucoxanthin TyrTyrosine TrpTryptophane PhePhenylalanine EPSextracellular polymeric substances FSfulvic acid like HShumic acid like Q-oQuinone (oxidized) Q-sSemiquinone Q-hHydroquinone Bakbacteria like fluorescence HS Chl a PC PE Tyr Trp EPS Q-o Q-s Q-s/h FS FC Bak Biopolymers Humic substances Algae pigments Phe

7 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Characterization by LC-OCD Most parameters used to describe DOC are sum parameters (like BOD, COD, UV 254, UV 436 ) LC-OCD (Liquid chromatography – Organic carbon detection) and fluorescence allow the characterization of DOC LC-OCD separates DOC by molecular weight Fluorescence separates DOC by chemical structure or rather chemical properties II. Characterization of DOC

8 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Quantification of fluorescence Fluorescence is easy to use and is appropriated for the characterization of the DOC The quantification isnt easy, because of Influence of stray light Inner – Filter - Effects Quenching of fluorescence signals Portability: standardization between different spectrometers Spectral overlapping of signals III. Problems in quantification of fluorescence signals

9 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Stray light Caused by scattering of exciting light in sample Differentiation between Rayleigh- and Ramanscattering Rayleigh: elastic scattering without loss of energy Appears at excitation wavelength Raman: inelastic scattering with loss of energy Appears at longer wavelengths III. Problems in quantification of fluorescence signals

10 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Stray light III. Problems in quantification of fluorescence signals

11 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Stray light III. Problems in quantification of fluorescence signals

12 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of stray light problem Best method is the use of cutoff filters III. Problems in quantification of fluorescence signals

13 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of stray light problem Best method is the use of cutoff filters III. Problems in quantification of fluorescence signals

14 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Inner – Filter – Effects (IFE) Primary IFE: absorption of excitating light by sample Secondary IFE: absorption of emitted light III. Problems in quantification of fluorescence signals

15 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of the IFE-Problem Generally there are two methods: Additionally measurement of absorption spectrum of sample Correction via stray light peaks of the sample (Raman peak) Absorption wavelength [nm] absorption III. Problems in quantification of fluorescence signals L AKOWICZ (2006):

16 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of the IFE-Problem III. Problems in quantification of fluorescence signals

17 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of the IFE-Problem Result of IFE-correction is a linear relationship III. Problems in quantification of fluorescence signals

18 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Quenching Is also a decrease of fluorescence intensity Results from contact between fluorophor and quenching molecule Dynamic Quenching: collision between molecules in excited state High temperatures and high concentrations increase the probability of collisions Static Quenching: formation of complex between fluorophore and quencher Fluorophore isnt able to fluoresce any more III. Problems in quantification of fluorescence signals

19 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Quenching: an example III. Problems in quantification of fluorescence signals

20 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of Quenching-Problem Relationship between fluorophore and Quencher can be described by the Stern-Volmer-Law III. Problems in quantification of fluorescence signals

21 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of Quenching-Problem Definition of the most important Quenchers in respect of raw and drinking water O 2, Cl -, NO 3 - (surface- and groundwater) Fulvic acid Humic acid Methodical laboratory tests to derive the single quenchingconstants for every fluorophore-quencher- pair III. Problems in quantification of fluorescence signals

22 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Portability III. Problems in quantification of fluorescence signals Proteinfluorescence at two spectrometers emission wavelength [nm] fluorescence intensity [a.u.] LS50LS55

23 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Portability The reason for the differences is the missing reference photomultiplier for the emission channel III. Problems in quantification of fluorescence signals

24 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of Portability-Problem Standardization in three steps: Correction of exciting light: is included in all spectrometers (reference photomultiplier) Correction of deformed peaks: via derivation of correction-function with the use of reference dyes Normalization of signals via external standard (sealed pure water cuvette) III. Problems in quantification of fluorescence signals

25 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of Portability-Problem Correction of deformed peaks via reference dyes III. Problems in quantification of fluorescence signals L AKOWICZ (2006)

26 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Solution of Portability-Problem III. Problems in quantification of fluorescence signals before standardizationafter standardization LS50 LS55

27 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Short summary We have learned How a spectrometer does work How the DOC is characterized by Fluorescence LC-OCD method How a quantification is complicated by Stray light Inner – Filter – Effects Quenching Portability III. Problems in quantification of fluorescence signals

28 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Spectral overlapping III. Problems in quantification of fluorescence signals

29 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Spectral overlapping Existing multivariate methods are: Principal components regression (PCR) Parallel factor analysis (PARAFAC) III. Problems in quantification of fluorescence signals

30 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Principal components regression (PCR) Need for set of EEMs for decomposition DOC: 1,2 mg/LDOC: 0,4 mg/LDOC: 0,6 mg/L ……… training dataset Collection of samples about one year New matrix Quantification of the new matrix III. Problems in quantification of fluorescence signals

31 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Principal components regression (PCR) Comparison between classical calibration and calibration using principal components Principal components are difficult to interpret Appropriate for quantification of well known waters, not for characterization III. Problems in quantification of fluorescence signals LC-OCD- fraction R² (classical) R² (PC-Regression) Number of principal components TOC0,860,954 Biopolymers0,000,7310 Humic Substances 0,780,914

32 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Parallel factor analysis (PARAFAC) Some kind of extended principal components analysis III. Problems in quantification of fluorescence signals 20 to ~ 200

33 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Multivariate analysis Lack of interpretation (PCA/PCR) No universal application possible New calibration for every location or water necessary High number of samples necessary PCR mainly applied in process-monitoring (e.g. brewery), where water always has the same defined composition and may only exhibits fluctuation of concentration III. Problems in quantification of fluorescence signals

34 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Approach of TZW to solve the problem Target is decomposition based on one EEM Extended curve fitting approach is used Allows to remove stray light, if cutoff filters werent able to remove them III. Problems in quantification of fluorescence signals Tryptophan fitted with an asymmetric curve and stray light with symmetric curves

35 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Approach of TZW to solve the problem Main problem is finding the truth, because several solutions are possible III. Problems in quantification of fluorescence signals

36 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Approach of TZW to solve the problem Principle of fluoresence: λ em = constant Usage of pattern recognition (DTW) III. Problems in quantification of fluorescence signals

37 Technologiezentrum Wasser (TZW) – Außenstelle Dresden Summary Advantages Quick Little sample preparation Very sensitive Disadvantages Complexity of data evaluation and interpretation

38 Technologiezentrum Wasser (TZW) – Außenstelle Dresden The End Thank you for your attention


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