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Aquatic Organic Matter Fluorescence – from phenomenon to applicationsDr Darren Reynolds - Associate Professor in Bio-Sensing ResearchUniversity of the West of England
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Institute of Bio-Sensing Technology
biology for sensors and sensors for biology
Aquatic Organic Fluorescence
from phenomenon to applications
Darren Reynolds
biology for sensors and sensors for biology
17th and 18th Centuries – intellectual
movement - ‘Enlightenment’ the ‘Age
of Reason’.
Newtonian science exerted its greatest
impact on the world
biology for sensors and sensors for biology
Maxwell de Broglie Born
Thompson Wein Rutherford
Faraday Hertz Schrödinger
Stokes Einstein Pauli
Bohr Planck Lewis
Becquerel Crookes Heisenberg
biology for sensors and sensors for biology
Defined as the emission of light by a
substance, where the emitted light
cannot be attributed to incandescence,
i.e. thermal radiation.
biology for sensors and sensors for biology
Sir G. G. Stokes
(1852)
biology for sensors and sensors for biology
biology for sensors and sensors for biology
Observed the fluorescence properties of
humic and fulvic substances and organic
matter in natural waters........... ‘Gelbstoff’
Humic, fulvic, DOC, DOM, CDOM
(Vodacek, Mopper, Blough, Coble)
biology for sensors and sensors for biology
we have and are experiencing a
technological revolution largely driven
by breathtaking advances in;
Applied electro optics
Improvements in data processing and
data handling....
biology for sensors and sensors for biology
Optical Space
www.turnerdesigns.com
biology for sensors and sensors for biology
Optical Space
Wastewater fluorescence
biology for sensors and sensors for biology
Optical Space
Wastewater fluorescence
biology for sensors and sensors for biology
Optical Space
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
biology for sensors and sensors for biology
Optical Space a)
b)
c)
d)
e)
f)
biology for sensors and sensors for biology
T1
Energy
S2
S0
Ground state
λ2
S1
λ2 λ 1 λ 3 λ 4
Fluorescence Absorption Internal
and External
Conversion
Phosphorescence
Vibrational Relaxation
Triplet Excited State
Singlet Excited States
Intersystem Crossing
Internal Conversion
biology for sensors and sensors for biology
biology for sensors and sensors for biology
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
Whitening Agents
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
Fluorescent Dyes
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
Chlorophyll fluorescence
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
Humic/Fulvic Material
biology for sensors and sensors for biology
Chlorophyll
300 400 500 600 7000
200
400
600
800
1000
Wavelength (nm)
Inte
nsity (
a.u
.)
Wa
ve
le
ng
th
(
nm
)
W a v e l e n g t h ( n m )
2 0 0 . 0 0
2 5 0 . 0 0
3 0 0 . 0 0
3 5 0 . 0 0
4 0 0 . 0 0
4 5 0 . 0 0
5 0 0 . 0 0
5 5 0 . 0 0
6 0 0 . 0 0
3 0 0 .0 0 3 5 0 .0 0 4 0 0 .0 0 4 5 0 .0 0 5 0 0 .0 0 5 5 0 .0 0 6 0 0 .0 0 6 5 0 .0 0 7 0 0 .0 0
9 6 2 . 0 0
8 8 6 . 0 0
8 1 0 . 0 0
7 3 4 . 0 1
6 5 8 . 0 1
5 8 2 . 0 1
5 0 6 . 0 1
4 3 0 . 0 1
3 5 4 . 0 2
2 7 8 . 0 2
2 0 2 . 0 2
1 2 6 . 0 2
5 0 . 0 2
- 2 5 . 9 7
Microbial Processes
biology for sensors and sensors for biology
biology for sensors and sensors for biology
Autochthonous material is created in-situ
through microbial activity – a reflection of the
phys/chem/biol processes
This provides a recycling mechanism for
allochthonous DOM (dissolved organic carbon
fed into the hydrological system from outside).
biology for sensors and sensors for biology
Bacterial origin.
Shelley et al., (1980),
Dalterio et al. (1986)
Determann et al., (1998) Cammack
et al., (2004) and Elliott et al., (2006)
biology for sensors and sensors for biology
Laboratory Field
Num
ber
P
ublis
hed
P
apers
Marine ‘optical map’
(Coble, 1993, Mar.Sci.)
Fresh/waste ‘optical map’
(Baker, 2001, ES&T)
Rapid Technological
improvements
Aquatic Fluorescence Research
Wastewater
Fluorescence
biology for sensors and sensors for biology
– Water recycling/nano filtration
– Drinking water treatment processes -
chlorination
– Urban watersheds quality monitoring
– Catchment water quality monitoring
– Wastewater quality monitoring
biology for sensors and sensors for biology
Real-time monitoring of water and
wastewater quality using a fluorescence
technique
Optical Spectroscopy in the Aquatic
Environment
Elsholt Works, Yorkshire Water (May,1998)
biology for sensors and sensors for biology
biology for sensors and sensors for biology
The characterisation of sewage using
fluorescence
Effluent and Sewage Network Management
Inst. Mech. Engineers (February 2000)
biology for sensors and sensors for biology
biology for sensors and sensors for biology
Field based fluorescence devices for
urban/fresh/drinking/waste water
systems have been limited;
– Low knowledge base
– Technological challenges
– Lack of appropriate field trails
biology for sensors and sensors for biology
Real-time monitoring of river water quality
using in-line continuous acquisition of
fluorescence excitation and emission
matrices.
Future Water Sensing Technologies
Warrington, (February, 2010)
biology for sensors and sensors for biology
biology for sensors and sensors for biology
Samples Correlation (peak/parameter/Pearson's r
unless stated)
References
Raw settled/treated sewage from 3 different treatment works
(n=129)
T1 BOD5 0.960
0.970
0.960
Reynolds & Ahmad (1997)
Raw settled/treated sewage (n=25) T1–T2 BOD5 0.980 Ahmad & Reynolds (1999)
Synthetic sewage treated via a rotating bio-disc contactor (n =45)
FTotal = Total fluorescence intensity
Settled and treated sewage samples over a 3 month period (n=56)
FTotal = Total fluorescence intensity
FTotal
T1
FTotal–T1
FTotal
T1
FTotal–T1
BOD5
COD
TOC
BOD5
COD
TOC
COD-BOD
BOD5
COD
TOC
BOD5
COD
TOC
COD-BOD
0.890
0.920
0.910
0.980
0.980
0.980
0.840
0.790
0.820
0.800
0.930
0.940
0.930
0.710
Reynolds (2002)
Filtered raw sewage T1 COD
TOC
Nk
NH4-N
COD
TOC
Nk
NH4-N
0.420
0.410
0.690
0.650
0.560a
0.530a
0.760a
0.840a
Vasel & Praet (2002)
Treated effluent samples (over a 3 month period) T1 COD 0.900 Lee and Ahn (2004)
Wastewater samples (96 in total) using CODDissolved values T1 CODDissolved.
COD
0.370
0.510
Wu et al., (2006)
Sewage effluents (n=16) C1 DOC 0.140 Cumberland & Baker (2007)
Wastewater effluents (223 samples - sewage, trade and pollution
incidents)
T1
T2
C2
A
BOD5
TOC
BOD5
TOC
BOD5
TOC
BOD5
TOC
0.906b
0.876b
0.848b
0.802b
0.771b
0.870b
0.720b
0.808b
Hudson et al., (2008)
biology for sensors and sensors for biology
a)
b)
c)
d)
e)
f)
I
II
III
IV
V
VI
VII
biology for sensors and sensors for biology
A concerted effort to tackle the
approaching data Tsunami is necessary
Application driven technology needs to be
developed, tested and evaluated in the
field
biology for sensors and sensors for biology
Fluoro-sensor Development
Tryptophan-like fluorescence
Laboratory assessment
Field deployment
biology for sensors and sensors for biology
Preliminary Field Trials
biology for sensors and sensors for biology
• Aquatic fluorescence is not new
• Fluorescence sensing has history
• Technology Readiness Level is high
• Clear Identified Applications
biology for sensors and sensors for biology
• Application-led field studies/trials
– Sensor performance
– Generation of data sets for evaluation
– Development of appropriate data
management tools (application driven)
biology for sensors and sensors for biology
Hudson, N., Baker, A., and Reynolds,
D. (2007). Fluorescence analysis of
dissolved organic matter in natural,
waste and polluted waters – a review.
River Research Applications, 23, 631-
649.
biology for sensors and sensors for biology
Henderson, R.K. et al. (2009).
Fluorescence as a potential
monitoring tool for recycled water
systems: A review. Water Research,
43, 863-881.
biology for sensors and sensors for biology
Paula G. Coble, Andy Baker, Jamie
Lead, Robert M. Spencer, Darren M.
Reynolds.
2013 Cambridge University Press
biology for sensors and sensors for biology
John Attridge
Chelsea Technologies Group, UK.
Robin Thorn & Gareth Robinson
Centre for Research in Biosciences, UWE, UK.
Elfrida Carstea
National Institute of R&D for Optoelectronics, Romania.
Andy Baker
Water Research Centre, UNSW, Australia.
biology for sensors and sensors for biology
darren.reynolds@uwe.ac.uk
http://www.biosensingtech.co.uk/
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