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

FLUORESCENCE AS A TOOL FOR THE CHARACTERIZATION OF WATER

AquaLife 2010Martin Wagner,

Technologiezentrum Wasser (TZW)Außenstelle Dresden

Technologiezentrum Wasser (TZW) – Außenstelle Dresden

Outline

Principles of fluorescence spectroscopy

Characterization of DOC

Problems in quantification of fluorescence signals


Measurement of fluorescence

Design of a fluorescence spectrometer

I. Principles of fluorescence spectroscopy



Emission spectrum: λEx = const., λEm


0

50

100

150

200

250

240 340 440 540 640

Flu

ores

cenc

e in

tens

ity [

a.u.

]

Emission wavelength [nm]



Variation of λEx produces an excitation-emission-

matrix, called EEM


λEmission λExcitation

Intensity


Characterization of water

II. Characterization of DOC

Chl A Chlorophyll APC PhycocyaninPE PhycoerythrinFC FucoxanthinTyr TyrosineTrp TryptophanePhe PhenylalanineEPS extracellular

polymericsubstances

FS fulvic acidlike

HS humic acidlike

Q-o Quinone (oxidized)Q-s SemiquinoneQ-h HydroquinoneBak bacteria like

fluorescence

HS

Chl a

Chl a

Chl a

PC

PE

Tyr

Tyr

Trp

Trp

EPS

EPSQ-oQ-o

Q-s

Q-s

Q-s

Q-s/h

Q-s/hFS

FC

FC

Bak

Biopolymers

Humic substances

Algae pigments

Phe


Characterization by LC-OCD

Most parameters used to describe DOC are sum parameters (like BOD, COD, UV254, UV436)

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

0

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120

10 30 50 70 90Retention time [min]

OC

D [

rela

tive

hei

gh

t o

f si

gn

al]

low molecular compounds

Polysaccharides

Humic Substances

Building Blocks


Quantification of fluorescence

Fluorescence is easy to use and is appropriated for the

characterization of the DOC

The quantification isn’t 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


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



Stray light


stray light in pure water

0

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260 360 460 560 660

emission wavelength [nm]

fluor

esce

nce

inte

nsity

[a.u

.]

Rayleigh peaks

Raman peaks


Stray light



Solution of stray light problem

Best method is the use of cutoff filters


0

20

40

60

80

100

120

200 300 400 500 600 700

T [%

]

wavelength [nm]

Cutoff filter


Solution of stray light problem

Best method is the use of cutoff filters


0

0,2

0,4

0,6

0,8

1

1,2

300 350 400 450 500

norm

aliz

ed in

tens

ity [-

]

emission wavelength

Quinine sulfate without filterQuninine sulfate with cutoff filter (290 nm)


Inner – Filter – Effects (IFE)

Primary IFE: absorption of excitating light by

sample

Secondary IFE: absorption of emitted light


Calibration

020406080

100120140160180

0 2 4 6 8 10 12

Concentration [mg/L]

fluor

esce

nce

inte

nsity

[a.u

.]


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

0

0.5

1

1.5

2

2.5

3

200 300 400 500 600 700

wavelength [nm]

ab

sorp

tion


LAKOWICZ (2006):




correction of Inner-Filter-Effects by ratio between raman peak of pure water and sample

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100

200

300

400

500

600

240 290 340 390 440 490 540 590 640 690


flu

ore

scen

ce in

ten

sity

[a.

u.]

pure water sample



Result of IFE-correction is a linear relationship


Calibration

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100

200

300

400

500

0 2 4 6 8 10 12

Concentration [mg/L]

fluor

esce

nce

inte

nsit

y [a

.u.]


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 isn‘t able to fluoresce any more



Quenching: an example



Solution of Quenching-Problem

Relationship between fluorophore and Quencher

can be described by the Stern-Volmer-Law



Solution of Quenching-Problem

Definition of the most important Quenchers in respect

of raw and drinking water

O2, Cl-, NO3- (surface- and groundwater)

Fulvic acid

Humic acid

Methodical laboratory tests to derive the single

quenchingconstants for every fluorophore-quencher-

pair



Portability


Proteinfluorescence at two spectrometers

0

50

100

150

200

250

300

350

400

240 340 440 540 640emission wavelength [nm]

fluore

scence

inte

nsi

ty [

a.u

.]

LS50 LS55


Portability

The reason for the differences is the missing

reference photomultiplier for the emission channel



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)




Correction of deformed peaks via reference dyes


LAKOWICZ (2006)




before standardization after standardization

LS50

LS55


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



Spectral overlapping


Component I

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100.00

150.00

200.00

250.00

220.0 320.0 420.0 520.0 620.0


fluor

esce

nce

inte

nsity

[a.

u.]

Component II

0.00

50.00

100.00

150.00

200.00

250.00

220.0 320.0 420.0 520.0 620.0


fluor

esce

nce

inte

nsity

[a.u

.]

Mix of both Components

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250.00

220.0 320.0 420.0 520.0 620.0


fluor

esce

nce

inte

nsity

[a.

u.] Component I Component II Mix


Spectral overlapping

Existing multivariate methods are:

Principal components regression (PCR)

Parallel factor analysis (PARAFAC)




Need for set of EEM‘s 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




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


LC-OCD-fraction

R²

(classical)

R²(PC-Regression)

Number of principal

components

TOC 0,86 0,95 4

Biopolymers 0,00 0,73 10

Humic Substances

0,78 0,91 4


Parallel factor analysis (PARAFAC)

Some kind of „extended“ principal components analysis


20 to ~ 200


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



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 weren‘t able to

remove them

III. Problems in quantification of fluorescence signalsTryptophan fitted with an asymmetric curve and stray light with symmetric curves



Main problem is finding the truth, because several

solutions are possible




Principle of fluoresence: λem = constant

Usage of pattern recognition (DTW)



Summary

Advantages

Quick

Little sample preparation

Very sensitive

Disadvantages

Complexity of data evaluation and interpretation


The End

Thank you for your attention

Documents

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