Stephan J. KÖHLER 1,2 , Elin E. LAVONEN 2 , Phillipe SCMITT-KOPPLIN 3 , Alexander KEUCKEN 4 , Norbert HERTKORN 3 , M HARIR 3 , Tom SPANJER 5 , Kenneth PERSSON 6 , Per ERICSSON 2 Jose L.J. LEDESMA 1 , Chris EVANS 1 , Salar VALINIA 1 , Johan TEMNERUD 1 , Julia HYTTEBORN 1 and Martyn FUTTER 1 1 SLU, Department of Aquatic Sciences and Assessment P.O. Box 7050 Uppsala, Sweden, +46 18 68 3826., [email protected], 2 NORRVATTEN, Skogsbacken 6, 172 41 Sundbyberg; Sweden, [email protected], [email protected], [email protected]3 HELMHOLTZ CENTRUM München, Allemagne, [email protected],[email protected], [email protected]4 VIVAB AB, Varberg, Sweden, [email protected]5 PENTAIR, Enschede, Holland [email protected]6 SYDVATTEN AB,Hyllie Stationstorg 21, 215 32 Malmö, Sweden, [email protected]Current challenges of trea0ng raw waters rich in natural organic ma4er (NOM) in Sweden
Transcript
Stephan J. KÖHLER1,2, Elin E. LAVONEN 2, Phillipe SCMITT-KOPPLIN3, Alexander KEUCKEN4, Norbert HERTKORN 3, M HARIR 3, Tom SPANJER 5, Kenneth PERSSON 6, Per ERICSSON 2
Current challenges of trea0ng raw waters rich in natural organic ma4er (NOM) in Sweden
climate change related challenges in nordic countries
Increase in color èBrowning as a result of increased iron and NOM mobilisa9on Increased weather extremes with floodings and dry spells, earlier ice break up and longer autumns èmore algal blooms, higher varia9on in water quality
Increasing color (A420_5cm; light brown) and TOC (dark brown) in Lyckebyån between 1965 9ll 2012
Varia9on in color ((A420_5cm; light brown) and TOC (dark brown) at the outlet of Mälaren between 1996 and 2012
stream
lake
intro trends lake Mälaren adapta0on synthesis
Recovery from acidifica9on is one apparent driver of changes in DOC and color
DOC
SO42-‐
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Comparing modelled trends in lakes and streams change in DOC mg L-‐1 year-‐1
Predicted trend for lakes n = 1200 (Valinia et al. 2015 ES&T)
Predicted trend in streams n = 215 (Temnerud et al. 2014 Ambio)
-0.5-0.4-0.3-0.2-0.10
0.10.20.30.40.5
-0.5-0.4-0.3-0.2-0.10
0.10.20.30.40.5
Regional model (offset, S deposi9on, area, lake size)
Site specific parameters (offset, temp, flow, trend)
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Trends in DOC over 0me
• Trends are slowing • TOC, color and Fe trends are not always consistent
• Temporal variability has increased substan9ally
• Main drivers are – Recovery from acid arin – Varia9on and trends in flow and temperature
– Effect of increased forest growth – Local land management (ditching, land conversion, replanta9on)
è site specific studies are needed
to beaer understand
local changes and
local drivers
in DOC quan9ty and quality!
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Lake Mälaren
� Lovö
Görväln
Lovö
< 5 <10 >15
DOC content [mg L-‐1]
Changes in DOC in large lake
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Changes in NOM character in large lake
Increasing residence 9me
In-‐Lake Processes Offset Increased Terrestrial Inputs of Dissolved Organic Carbon and Color to Lakes Köhler et al 2013 PlosOne
β/α DOC
A420 Feorg
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Characterisa9on of NOM
method parameter references
absorbance SUVA, UV Lavonen et al. 2015
Fluorescence β/α, HIX, FI Lavonen et al. 2015
FT-‐ICR-‐MS COS, C/H, C/O ; size, van Krevelen plots
Lavonen et al. 2015
LC-‐OCD Humic acids, size, LMW Huber et al. 2011 Köhler et al. 2016
1H-‐RMN NOM structure and fucn9onality
Diamar et al,. 2008
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Macroscopic parameters may be connected to molecular proper9es
How turnover ?me affects dissolved organic maAer composi?on -‐ tracking lake organic carbon processing with op?cal and molecular level tools Lavonen et al. ( in prep)
intro trends lake Mälaren adapta0on synthesis
This can be used to understand …and benchmark treatment processes
1. entrée
3. pompe
4. rajout ALG coagula9on (COAG)
5. flocula9on
9. Filtre à charbon ac9f (GAC)
8. pompe 6. décanta9on 7. Filtre à sable (FAS)
10. UV
11. Ca(OH)2 et rajout monochloramine
12. Stockage de l´eau traitée
13. pompe
2. microfiltre
Al2(SO4)3
Treatment Parameters scale References
1. Coag/SF/GAC coagula9on/SF/GAC pilot Lavonen et al. 2015 Köhler et al. 2016
intro trends lake Mälaren adapta0on synthesis
This can be used to understand …and benchmark treatment processes
Treatment Parameters scale References
1. Coag/SF/GAC coagula9on/filter/GAC large Lavonen et al. 2015 Köhler et al. 2016
2. Coag/SF/SF slow coagula9on/filter/ slow sand Large Lavonen et al. 2015
3. Coag/SF/NF coagula9on/filt/NF Pilot Köhler et al. 2016
4. MIEX Ion exchange Pilot Lavonen al. 2015
5. NF Nanofiltra9on Pilot Keucken et al. 2016
6. SIX/Ceramac/O3 Ion exchange, ozone and ceramic filtra9on Pilot Star9ng 2017
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Changement du caractère du COD PROCÈS
COAG
PROCÈS
MIEXNF
CERAMAC
β/α < 0.5 HSfrac =0.85COD = 12
β/α > 0.7Hsfrac = 0.7COD = 9
β/α > 0.7HSfrac > 0.3COD = 4
β/α > 0.9HSfrac < 0.2COD < 2
β/α SUVACOD
Biopoly = 350 Biopoly = 150 Biopoly 5-‐250 ppb
A420
This can be used to understand …and benchmark treatment processes
Process
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100%
100%
35%
Dosing chemical [mg L-‐1]
High NOM
Coagula9on has limits in low SUVA waters
Reduced barrier func9on against organic polluants (PFAS)
Specific challenges with increasing NOM
intro trends lake Mälaren adapta0on synthesis
…but NOM is just one of a mul9tude of challenges
• Climate change • More than 70% of raw water used is surface water
• Improved microbial barriers are needed • More algal blooms and algal toxins • Improved Chemical barriers and POPs are needed • Renewal and increase of the distribu9on network • Popula9on growth leads to capacity problems
è Many WTPs are from 1970s…
intro trends lake Mälaren adapta0on synthesis
Adap9ng and exploring • Improving current processes – Using sensors to op9mize coagula9on online
– Coagula9on with Fe instead of Al (Helsinki)
– Pretretament prior to ar9ficial infiltra9on (Gävle, Uppsala)
• Installa9on of new processes – COAG/UF Göteborg (done) , Varberg (in progress)
– NF Östersund (in progress) – NF, IEX or Ceramac/IEX/O3 Stockholm (in progress)
• Joint reserach projects – NOMiNOR (NOM research consor9um) – DomQua (NOM research consor9um) – MemiNOR (Membrane research consor9um) – Coopera9on between WTP (DRICKS) network – DW has been li{ed in the Na9onal research agenda
References can be viewed and downloaded at h4ps://www.researchgate.net/profile/S_Koehler
effort è
HSlabile
HSstable
DOCstable
DOClabile
DOC removal techniques (no oxida9on)
Empirical models for lake DOC (Valinia et al. 2015)
Observed and predicted TOC levels in 2010 TOC Trends are driven by lake area, catchment area and S deposi0on Study is limited to weakly buffered acid sensi0ve lakes
Upgrading coagula?on with hollow-‐fibre nanofiltra?on for improved organic maAer removal during surface water treatment. Köhler et al 2016 Water Research Vol 89
Görväln
Köhler et al. PloSOne 2013
Aλ-‐Modelled = a * DOCimport + b * Fecoll + c * DOCauto
Predic9ng color A420 and and A254 from EEM and Fe data
ForWater Jose Ledesma, PhD (INCA-‐C modelling
Ledesma et al. Sci of the tot Environ. 2012
Using MERIS to predict DOC from satelite images in Mälaren
-‐ DOC, TOC -‐ EEM flourescence -‐ FT-‐ICR-‐MS -‐ NMR -‐ è follow changes in DOC character -‐ è couple molecular and specroscopic data
Elin Lavonen, PhD
Tracking changes in the op0cal proper0es and molecular composi0on of dissolved organic ma4er during drinking water produc0on Lavonen et al 2015 Water Research 85:286-‐294
