Transcript Fluorescence as a tool for the characterization of water

FLUORESCENCE AS A TOOL
FOR THE CHARACTERIZATION
OF WATER
AquaLife 2010
Martin Wagner,
Technologiezentrum Wasser (TZW)
Außenstelle Dresden
Outline

Principles of fluorescence spectroscopy

Characterization of DOC

Problems in quantification of fluorescence signals
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Measurement of fluorescence

Design of a fluorescence spectrometer
I. Principles of fluorescence spectroscopy
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Measurement of fluorescence
Emission spectrum: λEx = const., λEm
Fluorescence intensity [a.u.]

250
200
150
100
50
0
240
340
440
540
640
Emission wavelength [nm]
I. Principles of fluorescence spectroscopy
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Measurement of fluorescence

Variation of λEx produces an excitation-emissionmatrix, called EEM
Intensity
λEmission
I. Principles of fluorescence spectroscopy
λExcitation
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Characterization of water
Chl A
PC
PE
FC
Tyr
Trp
Phe
EPS
FS
HS
Q-o
Q-s
Q-h
Bak
Chlorophyll A
Phycocyanin
Phycoerythrin
Fucoxanthin
Tyrosine
Tryptophane
Phenylalanine
extracellular
polymeric
substances
fulvic acid
like
humic acid
like
Quinone (oxidized)
Semiquinone
Hydroquinone
bacteria like
fluorescence
II. Characterization of DOC
Chl a
PC
PE
FC
Humic substances
Chl a
FC
Biopolymers
EPS
Q-s/h
EPS
Chl a
Q-s
HS
Q-s
Trp
Tyr
Q-s/h Q-s
Q-o Q-o FS
Tyr Trp
Algae pigments
Bak
Phe
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
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
OCD [relative height of signal]

120
Humic Substances
100
Building Blocks
80
60 Polysaccharides
40
20
0
10
II. Characterization of DOC
low molecular
compounds
30
50
70
Retention time [min]
90
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
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 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
 Raman:
excitation wavelength
inelastic scattering with loss of energy
 Appears at
longer wavelengths
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Stray light
stray light in pure water
fluorescence intensity [a.u.]
300
250
Rayleigh peaks
200
150
100
Raman peaks
50
0
260
360
460
560
660
emission wavelength [nm]
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Stray light
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of stray light problem

Best method is the use of cutoff filters
Cutoff filter
120
100
T [%]
80
60
40
20
0
200
300
400
500
600
700
wavelength [nm]
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of stray light problem

Best method is the use of cutoff filters
normalized intensity [-]
1,2
Quinine sulfate without
filter
Quninine sulfate with
cutoff filter (290 nm)
1
0,8
0,6
0,4
0,2
0
300
350
400
emission wavelength
450
500
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Inner – Filter – Effects (IFE)

Primary IFE: absorption of excitating light by
sample

Secondary IFE: absorption of emitted light
fluorescence intensity [a.u.]
Calibration
180
160
140
120
100
80
60
40
20
0
0
2
4
6
8
10
12
Concentration [mg/L]
III. Problems in quantification of fluorescence signals 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
3
2.5
absorption
2
1.5
1
LAKOWICZ (2006):
0.5
0
200
300
400
500
600
700
wavelength [nm]
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of the IFE-Problem
correction of Inner-Filter-Effects by ratio between raman peak of pure water and sample
600
fluorescence intensity [a.u.]
500
400
300
200
100
0
240
290
340
390
440
490
540
590
640
690
emission wavelength [nm]
pure water
sample
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of the IFE-Problem

Result of IFE-correction is a linear relationship
fluorescence intensity
[a.u.]
Calibration
500
400
300
200
100
0
0
2
4
6
8
10
12
Concentration [mg/L]
III. Problems in quantification of fluorescence signals 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 isn‘t able to fluoresce any more
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Quenching: an example
III. Problems in quantification of fluorescence signals 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 Technologiezentrum Wasser (TZW) – Außenstelle Dresden
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-quencherpair
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Portability
Proteinfluorescence at two spectrometers
400
fluorescence intensity [a.u.]
350
LS50
LS55
300
250
200
150
100
50
0
240
340
440
540
emission wavelength [nm]
640
III. Problems in quantification of fluorescence signals 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 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 Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of Portability-Problem

Correction of deformed peaks via reference dyes
LAKOWICZ (2006)
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Solution of Portability-Problem
before standardization
after standardization
LS50
LS55
III. Problems in quantification of fluorescence signals 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 Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Spectral overlapping
Component II
Component I
250.00
fluorescence intensity [a.u.]
fluorescence intensity [a.u.]
250.00
200.00
150.00
100.00
50.00
0.00
220.0
320.0
420.0
520.0
200.00
150.00
100.00
50.00
0.00
220.0
620.0
320.0
emission wavelength [nm]
420.0
520.0
emission wavelength [nm]
620.0
Mix of both Components
250.00
fluorescence intensity [a.u.]
Component I
Component II
Mix
200.00
150.00
100.00
50.00
0.00
220.0
320.0
420.0
520.0
620.0
emission wavelength [nm]
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Spectral overlapping

Existing multivariate methods are:
 Principal
 Parallel
components regression (PCR)
factor analysis (PARAFAC)
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Principal components regression (PCR)

Need for set of EEM‘s for decomposition
training dataset
DOC: 1,2 mg/L
…
New matrix
DOC: 0,4 mg/L DOC: 0,6 mg/L
…
…
Collection of samples about one year
Quantification of the new matrix
III. Problems in quantification of fluorescence signals 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
LC-OCDfraction
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
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Parallel factor analysis (PARAFAC)

Some kind of „extended“ principal components analysis
20 to ~ 200
III. Problems in quantification of fluorescence signals 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 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 weren‘t able to
remove them
Tryptophan fitted with an asymmetric curve and stray light with symmetric curves
III. Problems in quantification of fluorescence signals 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 Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Approach of TZW to solve the problem

Principle of fluoresence: λem = constant

Usage of pattern recognition (DTW)
III. Problems in quantification of fluorescence signals Technologiezentrum Wasser (TZW) – Außenstelle Dresden
Summary

Advantages
 Quick
 Little
 Very

sample preparation
sensitive
Disadvantages
 Complexity
of data evaluation and interpretation
Technologiezentrum Wasser (TZW) – Außenstelle Dresden
The End
Thank you for your attention
Technologiezentrum Wasser (TZW) – Außenstelle Dresden