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Removal of

Natural

Organic

Matter

fractions by

anion exchange

Impact on drinking water treatment

processes and biological stability

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Removal of Natural Organic Matter Fractions by Anion

Exchange

Impact on drinking water treatment processes and biological stability

Proefschrift

ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,

op gezag van de Rector Magnificus prof. ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties,

in het openbaar te verdedigen op vrijdag 29 november 2013 om 10.00 uur door Anke GREFTE

civiel ingenieur geboren te Enschede

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Dit proefschrift is goedgekeurd door de promotor: Prof. dr. ir. L.C. Rietveld

Samenstelling promotiecommissie:

Rector Magnificus voorzitter

Prof. dr. ir. L.C. Rietveld Technische Universiteit Delft, promotor

Prof. dr.-Ing. W. Uhl Technische Universit¨at Dresden, Germany

Prof. dr. J. Haarhoff University of Johannesburg, South Africa

Prof. dr. P. M. Huck, P. Eng. University of Waterloo, Canada

Prof. dr. ir. J.P. van der Hoek Technische Universiteit Delft/ Waternet

Dr. M. Dignum Waternet

Dr. E.R. Cornelissen KWR water research institute

Prof. dr. ir. W.G.J van der Meer Technische Universiteit Delft/ Oasen, reservelid

The research reported in this thesis is supported by the collaborative IS NOM re-search project Breakthrough in biological stability of drinking water, funded by Sen-terNovem agency of the Dutch Ministry of Economic Affairs together with KWR water research institute, UNESCO-IHE Institute for Water Education, Delft Uni-versity of Technology and the water supply companies of Vitens and Waternet.

ISBN: 978-94-6186-239-6 c

2013 Anke Grefte

Printed by: Gildeprint Drukkerijen

All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilised in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without the prior permission of the author.

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.

It always seems impossible until it is done

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Contents

1 Introduction 1

1.1 Drinking water in the Netherlands . . . 1

1.2 Importance of NOM removal . . . 2

1.3 Methods to measure NOM . . . 3

1.4 Anion exchange for NOM removal . . . 4

1.5 This thesis . . . 4

2 Determination of low molecular weight acids by LC-OCD used in drinking water treatment 9 2.1 Introduction . . . 10

2.2 Materials and methods . . . 11

2.2.1 Experimental setup . . . 11

2.2.2 Analyses . . . 12

2.2.3 Pilot plant experiment . . . 13

2.3 Results and discussion . . . 14

2.3.1 Reliability of LC-OCD NOM fraction determination . . . 14

2.3.2 Determination of NOM fractions . . . 15

2.3.3 The use of LC-OCD in practice . . . 20

2.3.4 Relation between NOM fractions and AOC . . . 23

2.4 Conclusions . . . 24

3 Multi-component modelling of natural organic matter fractions re-moval by ion exchange 27 3.1 Introduction . . . 28

3.2 Materials and methods . . . 29

3.2.1 Modelling . . . 29

3.2.2 Modelling approach . . . 31

3.2.3 Experimental setup . . . 32

3.2.4 Analyses . . . 33

3.3 Results and discussion . . . 34

3.3.1 Breakthrough of DOC by ion exchange . . . 34

3.3.2 Breakthrough of NOM compounds by ion exchange . . . 37

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3.3.4 Discussion on NOM compounds and exchangeability . . . 41

3.4 Conclusions . . . 42

4 Natural organic matter removal by ion exchange at different posi-tions in the drinking water treatment lane 43 4.1 Introduction . . . 44

4.2 Materials and methods . . . 45

4.2.1 Treatment scheme . . . 45

4.2.2 Analyses . . . 46

4.2.3 Cost comparison and environmental impact . . . 47

4.3 Results and discussion . . . 49

4.3.1 NOM removal by MIEX R and FIX . . . 49

4.3.2 Biological stability . . . 50

4.3.3 IEX cost comparison . . . 54

4.3.4 Expected costs savings on subsequent treatment processes . . 54

4.3.5 Environmental impact . . . 56

4.4 Conclusions . . . 57

5 The influence of the removal of specific NOM compounds by an-ion exchange on ozone demand, disinfectan-ion capacity and bromate formation 59 5.1 Introduction . . . 60

5.2 Materials and methods . . . 61

5.2.1 Treatment scheme . . . 61

5.2.2 Experimental set-up . . . 62

5.2.3 Analyses . . . 62

5.3 Results and discussion . . . 63

5.3.1 Change in NOM composition . . . 63

5.3.2 Determination of Ct . . . 65

5.3.3 Ozone demand and disinfection capacity . . . 70

5.3.4 Bromate formation . . . 70

5.4 Conclusions . . . 72

6 Improving the biological stability of drinking water by ion ex-change 75 6.1 Introduction . . . 76

6.2 Materials and methods . . . 76

6.2.1 Experimental setup . . . 76

6.2.2 Analysis . . . 78

6.3 Results and discussion . . . 78

6.4 Conclusions . . . 81

7 Conclusions 83 7.1 NOM properties . . . 83

7.2 Water treatment processes . . . 84

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7.4 Final conclusion . . . 86 7.5 Recommendations . . . 86 Bibliography 87 List of symbols 97 Summary 99 Samenvatting 103 Dankwoord 107 Publications 111 Curriculum vitae 115

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Chapter 1

Introduction

1.1

Drinking water in the Netherlands

In the Netherlands, the three main sources for the production of drinking water are groundwater, artificial groundwater and surface water (de Moel et al., 2006). Groundwater is the preferred source, because it is free from pathogenic organisms, it has a consistent good quality and the temperature is constant. Approximately two third of the Dutch drinking water is produced from protected groundwater sources. In the western part of the Netherlands the groundwater is brackish and the popula-tion density is high. Previously, water of good quality was abstracted from aquifers in the dunes, along the North Sea coast. When this source became brackish, the water companies started to infiltrate (pre-treated) surface water into these aquifers. Approximately 20% of the Dutch drinking water is made of artificially recharged groundwater abstracted from the dunes. Drinking water in the Netherlands is also directly produced from surface water. The treatment always includes filtration sys-tems, like rapid and slow sand filtration, activated carbon filtration or membrane filtration. The water is disinfected by ozone or UV-radiation, occasionally com-bined with hydrogen peroxide. If necessary, the hardness of the water is reduced by a softening process. After this extensive treatment, the water is hygienically safe and therefore no chlorine is needed for the distribution of drinking water to the consumer. However, without chlorine residual, biofilm formation, growth of micro invertebrates (van der Kooij et al., 1999a) and deposit formation in the drinking water distribution system may occur, causing deterioration of the drinking water quality (Vreeburg et al., 2008).

Pre-treatment plant Loenderveen and production plant Weesperkarspel (WPK) of Waternet, the water cycle company of Amsterdam and surrounding areas, were used for the experimental research described in this thesis. Therefore, these treatment plants are described in more detail.

The production of WPK is approximately 30 Mm3

drinking water per year, which is distributed to households and industries in (the vicinity of) Amsterdam. Only the eastern part of Amsterdam is supplied by WPK, the other parts of

Amster-dam (approximately 60 Mm3

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treatment plant Leiduin. In the beginning of the last century only water from the Amsterdam water supply dunes was used as source for drinking water. Because the demand for reliable drinking water grew the water supply company started to use seepage water from the Bethune polder as a source for the pre-treatment plant Loenderveen in 1930. The first treatment step at Loenderveen is coagulation with ferric chloride, which incorporates the suspended particles in the water, forming flocs that settle to the bottom of large, two stage, basins. Not only suspended matter is removed by coagulation but also organic substances, bacteria, viruses, and heavy metals are partly removed from the water. However, the main purpose of coagu-lation in Loenderveen is the removal of phosphate. This is necessary because the second treatment step is natural purification in an artificial lake. By removing phos-phate before this lake, algae growth can be reduced. The residence time in the lake is approximately three months, in which ammonia, bacteria and viruses are removed. From the lake, the water is pumped to 24 rapid sand filters for the removal of the last suspended matter. The filter beds of the rapid sand filters carry bacteria which convert substances such as ammonia. The filtered water is collected in a filtra-tion reservoir and then pumped to the producfiltra-tion plant WPK. After transportafiltra-tion through two parallel 10 kilometre transport mains the water flows in reservoirs where the water is pumped to the ozonation chambers. Here, ozone is added to the water and about 20 minutes contact time is realised. Ozonation is used for disinfection and oxidation of NOM and ozonation provides the water with a better taste, odour and colour. Calcium is removed in softening reactors, which are filled with a fluidised bed of garnet sand. By adding caustic soda, crystallisation of calcium carbonate occurs on the sand grains, resulting in marble-like pellets and reducing the water hardness to 1.5 mmol/L. After softening, the pH is corrected using hydrochloric acid. Organic compounds are removed by biological activated carbon filtration. Caustic soda is added to the filtrate to correct the pH. As a final treatment step, the water passes through slow sand filters (SSF) for the removal of pathogenic micro-organisms and for lowering the AOC concentration. The produced drinking water is stored in two drinking water reservoirs, from where it is transported to the customers.

1.2

Importance of NOM removal

Living and growing matter throughout the ecosystem, such as humans, animals, plants, and microorganisms, contains organic components. After dying, the or-ganic matter decomposes into NOM, and also the excretions of living matter are broken down through a reactive process into NOM. NOM is a complex mixture of various organic substances with different molecular weights, charge densities and hydrophobicities. Humic materials are the main component of NOM but also bi-opolymers such as polysaccharides, proteins, lipids and amino sugars are part of NOM. NOM can vary greatly, depending on its origin, transformation mode, age, and existing environment (Krdel et al., 1997).

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NOM is present in almost all types of natural (untreated or raw) water. NOM can cause various problems in drinking water treatment, such as high coagulant dose in coagulation processes (Edzwald, 1993), high ozone demand during ozon-ation (van der Helm et al., 2009), shorter run times of granular activated carbon filters (Heijman et al., 2007), high chlorine doses for disinfection (Campos and Har-mant, 2002), as well as disinfection by-products (DBP) formation (Kitis et al., 2001). Besides problems in drinking water treatment, NOM can be a source of nutrients for bacteria present in the distribution system (Wricke et al., 2002), which can cause regrowth (van der Kooij et al., 1982). Specifically, small organic acids can cause bacterial activity in the distribution system and biofilm formation in pipelines can occur. Microbial regrowth can deteriorate the taste and odour of the drinking water and it can even lead to potential health hazards.

1.3

Methods to measure NOM

NOM is a complex mixture of of compounds with various molecular weights and structures. Most commonly applied methods to indicate the NOM concentration present in the water are total organic carbon (TOC), dissolved organic carbon (DOC) and ultra-violet absorbance at a wavelength of 254 nm (UV254), which also provides an indication of the amount of unsaturated bonds present in NOM. These methods are bulk parameters, while NOM consists of various compounds with different molecular weights, charge densities and hydrophobicities. Therefore, addi-tional NOM characterisation methods are being developed. The aromaticity of NOM is determined by the specific UV254 absorbance (SUVA=UV254/DOC) (Edzwald et al., 1985). SUVA can also give an indication of hydrophobicity (Crou´e, 2004; Singer, 1999), knowledge of the hydrophobicity of NOM fractions can be extended by preparative DOC fractionation, this divides NOM in hydrophilic and hydrophobic bases, neutrals and acids (Leenheer, 1981). Different types and sources of NOM in natural water, can be distinguished by three-dimensional excitation emission matrix (EEM) spectroscopy, resulting in five fluorescence EEM regions (Chen et al., 2003). Common methods used for the quantification of small organic acids or low molecular weight (LMW) NOM influencing the biological stability are the assimilable organic carbon (AOC) method and the biodegradable organic carbon (BDOC) method. The AOC test is used to assess the concentration of growth-promoting organic com-pounds present in water (van der Kooij et al., 1982), while the decrease of DOC by microbial activity is measured by the BDOC method (Joret and Levi, 1986). To determine the biofilm-formation rate (BFR) of drinking water, the biofilm monitor can be used (van der Kooij et al., 1995). Because these methods are not stand-ardised, and labour and time consuming, they are not commonly used as a routine parameter in drinking water treatment.

In this research liquid chromatography (LC) with organic carbon detection (OCD) and ultra violet detection (UVD) is used for NOM characterisation, including

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LMW-NOM compounds. LC-OCD is a rapid and sensitive method, pre-extraction is not needed and the equipment is not too sophisticated or expensive (Matilainen et al., 2011). LC-OCD separates chromatographable organic carbon (CDOC) into frac-tions of different molecular weights, although hydrophobic interacfrac-tions (Specht and Frimmel, 2000) as well as functional groups (Ruhl and Jekel, 2012) have an effect on the fractionation. It is assumed that hydrophobic organic carbon (HOC) remains on the column due to the hydrophobic interaction with the column. HOC is the difference between DOC and CDOC. Particulate organic carbon (POC) is the dif-ference between TOC and DOC which both are measured in a bypass of the column. CDOC is fractionated into (a) biopolymers (BP); (b) humic substances (HS); (c) building blocks (BB); (d) low-molecular weight (LMW) acids and (e) low-molecular weight neutrals (Huber and Frimmel, 1996; Huber et al., 2011).

1.4

Anion exchange for NOM removal

NOM in surface water can be removed by anion exchange (IEX), because the main part of NOM, humic, fulvic and organic acids, is negatively charged (Bolto et al., 2002b; Cornelissen et al., 2008). IEX is a promising method for NOM removal, because empty bed contact times can be small and run times of IEX columns can be up to several weeks (van der Helm et al., 2009). IEX is relatively cost effective, easy to operate and a compact installation can be used due to the short contact times (Cornelissen et al., 2009). The efficiency of NOM removal by IEX depends on i.a. NOM concentration, NOM composition, type of IEX resin, empty bed contact time and configuration of the IEX installation. IEX can be operated as a packed

bed or in a fluidised mode, like Magnetic IEX (MIEX R

) (Drikas et al., 2002), Fluid-ised IEX (FIX) (Cornelissen et al., 2009) or suspended IEX (SIX) (Galjaard et al., 2011). When the resin is exhausted, a 10% sodium chloride solution can be used for regeneration; the NOM ions are exchanged for chloride ions. The residual or waste of IEX regeneration consists of water, salt (NaCl) and humic substances. The waste can be discharged to the sewer or directly to the wastewater treatment plant. However, humic substances are not readily biodegradable and will remain in the effluent of the wastewater treatment plant. Additionally, high salt solutions could give problems during wastewater treatment. To limit the residual, the brine can be reused (Schippers et al., 2004). Separating the salt from the humic substances is possible by membrane filtration. In that way the salt can be reused and only the higher concentration of humic substances is discharged to the sewer (Schippers et al., 2004; Kabsch-Korbutowicz et al., 2011).

1.5

This thesis

This thesis focuses on improving drinking water quality, specifically the biological stability of the produced drinking water. The biological stability of the treated wa-ter is negatively influenced by the presence of certain NOM fractions. Therefore,

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specific NOM fractions should be removed from the source water to improve bio-logical stability. It is known that NOM can be removed by anion exchange resins. However, the removal and conversion of specific NOM fractions is not well under-stood. Therefore, knowledge about NOM fractions as well as their behaviour in water treatment processes is essential.

This thesis aimed to answer the question:

How can the additional removal of specific NOM fractions by anion ex-change improve treatment processes as well as the biological stability of the produced drinking water?

To answer this question, LC-OCD was used as NOM characterisation method, IEX was used to remove NOM from the water and the pilot plant of drinking water treat-ment plant WPK was used to execute the research. LC-OCD provides insight in the composition of NOM, without determining the exact nature of it. NOM fractions determined by LC-OCD using FIFFIKUS software are BP, HS, BB, LMW-acids and neutrals. The produced water of WPK had a DOC concentration of approximately 6 mg C/L, which may be a source for regrowth in the distribution system.

The pilot plant of WPK consisted of 2 lanes of the same treatment processes, i.e. ozone dosage and contact columns, a pellet reactor, biological activated carbon (BAC) filtration columns and a slow sand filter (SSF). These processes were op-erated with similar contact times as in the full-scale treatment plant on a scale of approximately 1:200 compared to the full-scale treatment plant. The maximum flow

in the pilot plant was 7 m3

/h for each lane. For this research one of the lanes in the pilot plant was extended with IEX columns operated in fluidised mode. The IEX treatment step could produce water with different NOM concentrations and NOM compositions. These different water qualities were used for the research on NOM fractions. The conducted research existed of: lab research (Chapter 2), pilot plant research (Chapter 2 to 6), modelling (Chapter 3) and desktop calculations (Chapter 4).

The specific research questions are:

1. How is the LMW-acids concentration determined in the LC-OCD analysis using FIFFIKUS?

2. Is it possible to correlate different NOM fractions to the AOC concentration, the traditional measurement for biostability?

3. How to predict the removal of different NOM fractions by IEX?

4. What is the best position to place an IEX process in the treatment lane accord-ing to water quality as well as costs? (Case study: Waternet, Weesperkarspel) 5. How does the NOM composition in water change due to ozonation?

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6. What is the effect of NOM composition and ozone dose on the ozone demand, disinfection capacity and bromate formation?

7. How will the biological stability be improved by incorporating IEX in the treatment lane?

These research questions are answered in the following chapters:

In Chapter 2 research questions 1 and 2 are answered. To investigate the determina-tion of LMW-acids concentradetermina-tion by LC-OCD analysis using FIFFIKUS, laboratory experiments were executed. To answer this question, three different water types were chosen. Known concentrations of acetic acid and oxalic acids were added to the three different water types and the concentrations as determined by FIFFIKUS were evaluated. A pilot plant at WPK was used for AOC and LMW-acids data col-lection. In this chapter the relation between AOC and LMW-acids concentrations is investigated, because, LMW-acids and AOC both represent small organic carbon molecules.

In Chapter 3 research question 3 is answered. By batch experiments the Freundlich and kinetic parameters for DOC removal by IEX are determined. An IEX pilot column was used to collect data of the breakthrough of different NOM fractions as determined by LC-OCD. Based on these results a multi-component model is formu-lated to predict the removal of different NOM fractions by IEX.

In Chapter 4 research question 4 is answered. NOM can be removed by anion ex-change resins. To determine the best position of IEX in the treatment lane based on costs, the pre-treatment plant at Loenderveen and production plant Weesperkarspel of Waternet are used as a case study. Different placement positions of IEX in the treatment lane (IEX positioned before coagulation, before ozonation or after slow

sand filtration) and two IEX configurations (MIEX R and fluidised IEX (FIX)) are

compared on costs and water quality.

In Chapter 5 research questions 5 and 6 are answered. The pilot plant was used to study the reaction of ozone with NOM. For this part of the research three wa-ter qualities with different DOC concentrations and NOM compositions, obtained after several stages of an anion exchange process, were used. The change of NOM composition due to ozonation of the water as well as the effect of NOM removal by IEX on ozone demand, bromate formation and disinfection capacity are investigated. In Chapter 6 the last research question, question 7, is answered. To measure the effect of NOM removal by IEX on the biological stability of drinking water two treatment lanes are compared in biological stability of the produced water. IEX was used as pre-treatment in one lane and removed 50% of DOC, the other lane was used as reference. Biologically stable water is determined in terms of AOC, BFR and DOC.

In Chapter 7 conclusions are drawn by dividing the research question ”How can the additional removal of specific NOM fractions by anion exchange improve treatment

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processes as well as the biological stability of the produced drinking water?” into three subjects: 1) NOM properties; 2) Drinking water treatment processes and 3) Biological stability. The findings of every individual chapter are placed in a broader perspective for each subject, including recommendations for further research.

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Chapter 2

Determination of low molecular

weight acids by LC-OCD used in

drinking water treatment

Liquid chromatography with online organic carbon (OC) detection (LC-OCD) provides insight into the composition of natural organic matter (NOM), without determining the exact nature of it. The determination of the low molecular weight (LMW) acid concentration by LC-OCD was investigated for three water types with different NOM compositions. The NOM fraction concentrations were calculated on the basis of the humic substances (HS) concentration; the prediction of the different NOM fraction concentrations, specifically the LMW-acids and HS concentration, improved when the HS/DOC (dissolved organic carbon) ratio increases. To calculate a reliable concen-tration of LMW-acids, correction for LMW-HS by the software program FIFFIKUS should not be used. Not correcting for LMW-HS made it possible to investigate the effect of treatment steps on the LMW-acids concentration and, although water spe-cific and only for average assimilable organic carbon (AOC) concentrations, a linear relationship between the LMW-acids concentration determined by LC-OCD without correction for LMW-HS and the AOC concentration existed.

.

This chapter is in preparation for publication: Grefte, A., Dignum, M., Kroesbergen, J. and Rietveld, L.C. Determination of low molecular weight acids by LC-OCD used in drinking water treatment.

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2.1

Introduction

Many source waters for the production of drinking water contain natural organic matter (NOM) which may cause problems during drinking water treatment. Be-sides this, NOM can be a source for regrowth in the distribution system (van der Kooij et al., 1982). Specifically the low molecular weight (LMW) organic acids can be readily available as carbon and energy source in the distribution system and stim-ulate biofilm formation in pipelines, deteriorating the taste and odour of the drinking water. The presence of substances that enhance microbial growth are quantified by methods such as assimilable organic carbon (AOC) (van der Kooij et al., 1982), biofilm formation rate (BFR) (van der Kooij et al., 1995) or biodegradable organic carbon (BDOC) (Joret and Levi, 1986).

The most common methods to measure NOM are total organic carbon (TOC), dis-solved organic carbon (DOC) and ultra-violet absorbance at a wavelength of 254 nm (UV254), which provides an indication of the presence of unsaturated bonds present in NOM. These methods are bulk parameters, but NOM consists of compounds with different molecular weights, charge densities and hydrophobicities. Liquid chroma-tography (LC) with ultra violet absorbance (UV) and online organic carbon (OC) detection (UVD and OCD, respectively) can be used for NOM characterisation. For data acquisition and data processing of the LC-OCD data a customised software program FIFFIKUS (DOC-LABOR) can be used. This program calculates the con-centration of different NOM compounds by determining the area below the different peaks in the chromatograms based on curve deconvolution. However, it seems that specifically the LMW-acids are underestimated. Different researches found a peak in the chromatogram at the LMW-acids and HS region, but LMW-acids concen-tration was not calculated (Baghoth et al., 2009; Henderson et al., 2010; Kennedy et al., 2008). Huber et al. (2011) explained that a small proportion of HS, which is called the LMW-HS, is trapped in the LMW-acids zone. To distinguish between LMW-acids and LMW-HS the UV/OC ratio of HS is used to determine the concen-tration of LMW-HS, by assuming the same UV/OC ratio for LMW-HS as for HS. The concentration of LMW-acids is calculated by subtracting the concentration of LMW-HS from the total surface of the peak LMW-HS and LMW-acids. Because the UV/OC ratio of the HS fraction is used, the HS concentration and composition influences the LMW-acids concentration.

From 2006 onwards, NOM fractionation was done by LC-OCD in water from the treatment plant and the pilot plant at Weesperkarspel (WPK). Results showed an expected increase in AOC concentration after ozonation (Baghoth et al., 2009), without a significant increase in LMW-acids concentration, as determined by LC-OCD and FIFFIKUS, as was expected (Hammes et al., 2006; Myllykangas et al., 2002; Nissinen et al., 2001). Although the chromatograms showed a peak at the retention time were the LMW-acids and HS peak occurred, no LMW-acids con-centration was calculated by FIFFIKUS. Lankes et al. (2009) showed that the de-termination of the biopolymers peak and concentration were underestimated, while

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Ruhl and Jekel (2012) showed that the elution behaviour of LMW-compounds was determined by functional groups rather than by molecular weight.

In conclusion, from literature and previous experiments at WPK, LMW-acids and other natural organic carbon compounds are an important factor for the microbi-ological stability of drinking water. LC-OCD provides insight in the composition of NOM, without determining the exact nature of it. Questions were raised about the correctness of the quantification of NOM compounds measured by LC-OCD and their practical interpretation.

The focus of this chapter is on the determination of the LMW-acids concentration. The first research question was: What is the effect of the HS concentration on the determination of the LMW-acids concentration in the LC-OCD analysis using FIF-FIKUS? To answer this question, three different water types were chosen: 1) Feed water of WPK with a high HS concentration, 2) Feed water of WPK treated by ion exchange (IEX), which removed specifically HS and, 3) Nordic reservoir NOM (IHSS), which is a standard NOM with a low concentration of LMW-acids, neutrals and BB. Known concentrations of acetic acid and oxalic acids were added to the three different water types and the concentrations as determined by FIFFIKUS were evaluated.

The second research question was: How can LMW-acids as determined by LC-OCD be used in practice?

The third research question was: Is it possible to correlate different NOM fractions to the AOC concentration, the traditional measurement for biostability? This relation was investigated, because, LMW-acids and AOC both represent small organic carbon molecules. These last two questions were answered by analysing data obtained from a pilot plant experiment at Weesperkarspel (WPK) treatment plant. Samples were taken for i.a. DOC, LC-OCD and AOC analyses. In total 90 samples were analysed for LC-OCD and 64 samples were analysed for AOC.

2.2

Materials and methods

2.2.1

Experimental setup

Three water types were spiked with LMW organic acids: acetic acid and oxalic acid. First, water with a high HS concentration, which was WPK-feed water with a DOC concentration of approximately 5.6 mg C/L and a HS concentration of approxim-ately 60% of the DOC concentration. Second, water with a low HS concentration, which was feed water of WPK treated by anion exchange in fluidised form (FIX) as described by Cornelissen et al. (2009), for approximately 15,000 bed volumes with a DOC concentration of approximately 2.6 mg C/L and the HS concentration was ap-proximately 17% of the DOC concentration. Third, Nordic reservoir NOM (IHSS), which is a standard NOM with a low concentration of LMW-acids, neutrals and BB

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0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB

LMW-acids (and HS)

WPK feed FIX Nordic reservoir NOM

Figure 2.1: OCD chromatograms of WPK-feed water, FIX-treated water and Nordic reservoir NOM

(together LMW-NOM). The DOC concentration of the used Nordic reservoir NOM solution was 1.6 mg C/L. The main part (67%) of the standard NOM was HS. In Figure 2.1 the OCD-chromatograms of the different water types are shown.

Water was collected at WPK treatment plant in AOC-free glassware and transported to the laboratory of Het Waterlaboratorium, Haarlem, the Netherlands. Different solutions of both acids were made in Milli-Q water, namely 100, 200 and 500 µg C/L. To determine the reliability, 200 µg/L acetic or oxalic acid was added to Milli-Q water, and to WPK feed and FIX treated water, analysis of the samples was repeated eight and five times, respectively. The standard deviation (STD) was de-termined using Microsoft Excel. Pearson correlation coefficients between AOC and NOM fraction concentrations were determined using Microsoft Excel.

2.2.2

Analyses

Analyses were carried out at Het Waterlaboratorium, Haarlem, The Netherlands. After filtration through a 0.45 µm cellulose acetate filter, DOC was analysed on a Shimadzu TOC Analyser. NOM characterisation was performed by LC-OCD/UVD (manufacturer DOC-LABOR Dr. Huber, Karlsruhe, Germany) as described by Huber et al. (2011). Water samples were analysed after filtration through 0.45 µm filters. The used size exclusion chromatography column was a TSK HW-50S (GROM Ana-lytik+HPLC GmbH, Herrenberg, Germany). The separated compounds were

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de-tected by UV absorption at 254nm (WellChrom fixed wavelength detector K-200, Knauer, Berlin, Germany). In order to eliminate inorganic carbon, phosphoric acid was added after the UV detector. Then the organic carbon was oxidised in a Gr¨antzel thfilm reactor. The produced carbon dioxide was detected by non-dispersive in-frared absorption with an Ultramat 6 from Siemens, Munich, Germany (Huber and Frimmel, 1991). Before the LC-OCD separation a small amount of the sample was analysed for carbon on the Gr¨antzel reactor, bypassing the column. This was done without filtration for the TOC analysis and after filtration over a 0.45 µm filter to measure DOC.

FIFFIKUS (DOC-LABOR) software was used for the determination of the concen-trations of different NOM compounds. Most peaks in the chromatograms are poorly separated, therefor deconvolution is used to obtain Gaussian curves, where the HS peak is used as reference. From these Gaussian curves, the peak area is determ-ined and converted into a concentration using a calibration of the detector with potassium hydrogen phthalate. In Huber et al. (2011) it was explained that a small proportion of HS, the LMW-HS, is trapped in the LMW-acids zone. To distinguish between LMW-acids and LMW-HS the UV/OC ratio of HS is used to determine the concentration of LMW-HS, by assuming the same UV/OC ratio for LMW-HS as for HS. The concentration of LMW-acids is calculated by subtracting the con-centration of LMW-HS from the total surface of the peak LMW-HS and LMW-acids. In this study the HS concentration and the LMW-acids concentration were

determ-ined in two ways: with (HScor and LMW-Acidscor) and without (HS and LMW-acids)

correction for LMW-HS. The calculated concentrations of the NOM fractions were compared to the added acid concentrations and to the concentration of the different fractions which were already in the water. The determination level of fractions is 50 µg/L. Calculated concentrations below 50 µg/L were considered as unreliable. The concentration of AOC was determined, with growth measurements in water samples of 600 mL. Two pure cultures of bacteria were used by applying the simul-taneous incubation of strains Pseudomonas fluorescens (strain P17), which is cap-able of utilising a wide range of low-molecular-weight compounds at very low concen-trations and Spirillum sp (strain NOX), which utilises only carboxylic acids. The AOC concentration was calculated from the obtained maximum colony counts of these strains, using their yield values for acetate (van der Kooij et al., 1982; van der Kooij and Hijnen, 1984; van der Kooij, 1992). AOC was measured in duplicate and the average was taken.

2.2.3

Pilot plant experiment

In order to measure the effect of NOM fractions in treatment processes, a pilot plant experiment was conducted as described in Chapter 6. In short, the pilot plant of

WPK was operated in two lanes, each treating 7 m3

/h. Both lanes consisted of ozone dosage and contact columns, a pellet softening reactor, BAC filtration columns and

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a SSF. One lane was pre-treated with ion exchange filters operated in fluidised mode (FIX-lane), the other lane was the reference-lane (ref-lane). The experiment lasted for four months and every other week after every treatment step samples were taken for i.a. DOC, LC-OCD and AOC analyses. In total 90 samples were analysed for LC-OCD and 77 samples were analysed for AOC. Before ozonation the AOC levels were low. To investigate the relation between different NOM fractions and AOC, only data after ozonation were taken. For every treatment step (8 steps in total divided over 2 treatment lanes) 8 samples in time were taken and analysed, in total 64 measurements.

2.3

Results and discussion

2.3.1

Reliability of LC-OCD NOM fraction determination

Different amounts of acetic acid and oxalic acid were added to three types of wa-ter. These acids were chosen because of their relation with the AOC concentration. Acetate is well-degradable and is used for the calibration of AOC (in acetate equi-valents) (van der Kooij et al., 1982), oxalate is formed during ozonation (Hammes et al., 2007) and is specifically used by the Spirillum sp. strain NOX in the AOC test. Of each acid (oxalic and acetic acid) 200 µg C/L was added to milli-q water. The LC-OCD analysis was done eight times, the average calculated oxalic acid concentra-tion was 203 µg C/L and the standard deviaconcentra-tion was 1.3 µg C/L (the measurement error was 0.6%). The average acetic acid concentration was 176 µg C/L and the standard deviation was 1.1 µg C/L (the measurement error was 0.6%). The oxalic acid concentration determined by LC-OCD was within the expected measurement error, the recovery was 102%. The recovery of acetic acid was approximately 88% of the added concentration.

Next, 200 µg C/L oxalic acid or acetic acid was added to FIX-treated water and to WPK-feed water, this was repeated five times. In order to determine the reliability of the measurements, the averages of the measurements, the standard deviations and measurement errors are given in Table 2.1. Especially, POC and HOC gave a high measurement errors varying from 18.9% to 37.0%. Both parameters are derived and not measured directly. Because of the high measurement error, conclusions can not be drawn from these two parameters. The measurement error of the parameters other than POC and HOC were below 5% (see Table 2.1). Ciputra et al. (2010) found a measurement error of less than 1%, a value we only found for milli-q water. The DOC concentration of WPK water as measured by LC-OCD was 90% of the DOC concentration measured by the Shimadzu analyser (comparison of 99 samples through the treatment lane). This was in accordance with Lankes et al. (2009), who showed that large amounts of carbon were not measurable by LC-OCD, specifically the BP were underestimated.

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Table 2.1: Averages, standard deviations and measurement error for addition of 200 µg C/L acetic acid or 200 µg C/L oxalic acid to WPK-feed water and

FIX-treated water (n=5). HScor is corrected for LMW-HS, while HS are not corrected

for LMW-HS; same for LMW-acids

FIX-treated water Acetic SD Uncertainty Oxalic SD Uncertainty

(µg C/L) (%) (µg C/L) (%) TOC 3046 56 1.8 2954 14 0.5 DOC 2915 24 0.8 2893 46 1.6 POC 132 49 37.0 61 39 63.5 HOC 250 24 9.4 203 46 22.6 CDOC 2665 24 0.9 2690 32 1.2 BP 129 5 3.7 132 4 2.8 HScor 921 13 1.5 766 12 1.6 HS 495 13 2.7 512 8 1.6 BB 1141 24 2.1 1295 18 1.4 Neutrals 474 11 2.2 497 23 4.7 LMW-Acidscor 0 0 - 0 0 -LMW-Acids 426 12 2.7 253 7 2.8

WPK-feed water Acetic SD Uncertainty Oxalic SD Uncertainty

(µg C/L) (%) (µg C/L) (%) TOC 6271 94 1.5 6223 48 0.8 DOC 6191 103 1.7 6076 34 0.6 POC 80 16 20.0 146 43 29.6 HOC 290 100 34.7 178 33 18.9 CDOC 5901 15 0.3 5899 18 0.3 BP 95 3 3.3 93 2 2.7 HScor 3933 56 1.4 3968 93 2.4 HS 3595 41 1.2 3693 83 2.2 BB 1176 43 3.7 1227 59 4.8 Neutrals 581 19 3.2 611 25 4.0 LMW-Acidscor 116 8 6.6 0 0 -LMW-Acids 454 12 2.6 276 11 4.1

2.3.2

Determination of NOM fractions

Chromatograms

Acetic acid, which is a monocarboxylic acid, elutes in the HS and LMW-acids peak, while oxalic acid, which is a dicarboxylic acid, elutes in the BB peak as shown in Figure 2.2. This is in accordance with research of Tercero Espinoza et al. (2009); Huber et al. (2011); Meylan et al. (2007). In Figure 2.2a the chromatograms

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for additions of 100, 200 and 500 µg C/L acetic acid and in Figure 2.2b the chro-matograms for additions of 100, 200 and 500 µg C/L oxalic acid are shown. The figures show the increasing heights of the peaks for the different additions. From these chromatograms it is expected that when acetic acid is added the calculated concentration for solely the LMW-acids fraction will increase and when oxalic acid is added solely the calculated BB concentration will increase, this will be discussed in the next sections. As expected, the additions did not have an effect on the UVD chromatograms, because there are no unsaturated bonds in acetic and oxalic acid.

Water with high HS concentration

In Figure 2.3 the difference between the fraction concentrations calculated for water with addition of acids and water without addition of acids to WPK-feed water is

shown. A significant increase in LMW-acidscor was observed when 200 µg C/L

acetic acid or more was added. When the correction for LMW-HS was not used the increase in LMW-acids was 75-79% of the added amount, which was higher than when the correction for LMW-HS was used (10-60% of the added amount).

Addition of oxalic acid caused an increase in the BB fraction, but the increase in the BB fraction was only 52-79% of the added amount. However, there was also an increase shown in the HS fraction (32-44% of the added amount). This can be explained by the fact that the elution time of the HS fraction and BB fraction are partly the same. Increasing the BB fraction can cause a shift in the Gaussian curves as determined by FIFFIKUS, which causes an increase in both the determined HS and BB concentration. The correction for LMW-HS did not affect the amount of oxalic acid attribution to the HS fraction.

Water with low HS concentration

The HS peak is taken as a starting point for the calculation of the concentration of the different fractions (Huber et al., 2011). For that reason the same experiments have been done with water that contained less HS. In FIX-treated water approxim-ately 17% of the DOC concentration consisted of HS. In Figure 2.4 the difference in fraction concentrations after addition of 100, 200 and 500 µg C/L acetic or ox-alic acid to FIX-treated water is given. When using the correction for LMW-HS, addition of acetic acid did not increase the LMW-acids (only a small increase after addition of 500 µg C/L acetic acid, this value is lower than the determination level of 50 µg C/L), although, the HS concentration increased (68-78% of added amount). The LMW-acid concentration increased (77-81% of the added amount) when the correction for LMW-HS was not used. Addition of acetic acid not only caused an increase in HS concentration or LMW-acids concentration, also the BB concentra-tion increased (14-37% of the added amount). Addiconcentra-tion of oxalic acid caused, as expected, an increase in the BB concentration (83-125% of the added amount), the correction for LMW-HS did not influence these results.

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0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB LMW-acids (and HS) WPK 100 acetic acid 200 acetic acid 500 acetic acid

(a) Addition of 100, 200 and 500 µg C/L acetic acid

0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB LMW-acids (and HS) WPK 100 oxalic acid 200 oxalic acid 500 oxalic acid

(b) Addition of 100, 200 and 500 µg C/L oxalic acid

Figure 2.2: LC-OCD chromatograms after additions of acetic acid or oxalic acid to WPK-feed water

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-50 0 50 100 150 200 250 300 350 400 Acids Acidscor BB HS HScor Change in OC concentration ( µ g C/L) Fraction 100 µg/L acetic acid 200 µg/L acetic acid 500 µg/L acetic acid 100 µg/L oxalic acid 200 µg/L oxalic acid 500 µg/L oxalic acid

Figure 2.3: Difference in fraction concentrations after additions of 100, 200 and 500 µg C/L acetic and oxalic acid to WPK-feed water

-50 0 50 100 150 200 250 300 350 400 450 Acids Acidscor BB HS HScor Change in OC concentration ( µ g C/L) Fraction 100 µg/L acetic acid 200 µg/L acetic acid 500 µg/L acetic acid 100 µg/L oxalic acid 200 µg/L oxalic acid 500 µg/L oxalic acid

Figure 2.4: Difference in fraction concentrations after additions of 100, 200 and 500 µg C/L acetic and oxalic acid to FIX-treated water

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0 100 200 300 400 500 600 Acids Acidscor BB HS HScor Change in OC concentration ( µ g C/L) Fraction

Nordic reservoir NOM WPK feed water FIX treated water

Figure 2.5: Difference in fraction concentrations after additions of 500 µg C/L acetic acid and oxalic acid to WPK-feed water, FIX-treated water and Nordic reservoir NOM

Comparison of fraction concentration calculation for three water types with different HS concentrations

In addition to FIX-treated water with a low HS concentration and WPK-feed water with a high HS concentration, also Nordic reservoir NOM was used. The proportion HS to DOC was the highest for Nordic reservoir NOM (67%), followed by

WPK-feed water (63%) and FIX-treated water (31%) (all % calculated for HScor). To

all three water qualities 500 µg C/L acetic acid together with 500 µg C/L oxalic acid was added. In Figure 2.5 is shown that the increase in BB concentration is approximately 500 µg C/L, independent of water type. The standard way of calculating the fraction concentration is with correction for LMW-HS. The addition

of acids caused an increase in HScor (42% of the added amount), no increase in

acidscor was determined for FIX-treated water with a low HS concentration. The

higher the proportion HS, the more LMW-acidscor were calculated (0, 23, 35% of the

added amount) and less HScor (42, 28, 5% of the added amount), which shows that

the HS concentration influences the calculation of specifically the HScor and

LMW-acidscor concentration. When correction for LMW-HS was not used, the LMW-acids

concentration increased with the same amount for all water types (36-39% of the added amount).

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2.3.3

The use of LC-OCD in practice

Ozonation

In Figure 2.6a and 2.6b the LC-OCD chromatograms before and after ozonation for WPK-feed water (ref-lane) and FIX-treated WPK (FIX-lane) water are shown. Usually, ozonation causes a degradation of larger molecules into smaller molecules, which can be observed from the LC-OCD chromatograms of WPK-feed water (Fig-ure 2.6a). After ozonation of WPK-feed water the HS peak decreased and the BB peak increased. The increase in BB peak is assumed to be due to the formation of de-gradation products, of which oxalic acid is an important one (Hammes et al., 2006). The concentrations of the fractions calculated by the software program ”FIFFIKUS”

are shown in Figure 2.6c. HScor concentration of WPK-feed water decreased due to

ozonation, while the BB concentration did not change. The neutrals concentration

decreased, and the LMW-acidscor concentration increased (although 38 µg C/L is

below the determination level of 50 µg C/L). When correction for LMW-HS was not used, the LMW-acids showed a small increase (Figure 2.6c).

There is a discrepancy between the chromatogram, which showed an increase in the BB fraction, and the calculated concentrations, which showed an increase in LMW-acids concentration and not in BB concentration. Correction for LMW-HS did not affect the calculation for BB concentration, so it can be concluded that the discrep-ancy between chromatogram and calculations was not a result of the correction for LMW-HS, but it was caused by the fact that the HS peak is used as a reference for the calculation of the other fraction concentrations by FIFFIKUS, as explained in Section 2.2.2.

In Figure 2.6b the LC-OCD chromatogram after ozonation of FIX-treated WPK wa-ter is shown. Here an increase in the HS peak is present, while the lower MW-NOM (after a retention time of 55 minutes) decreased (see also Chapter 5. Figure 2.6c

gives an increase in the HScor and HS concentrations after ozonation of FIX-treated

WPK water. The BB concentration decreased, as well as the concentration of

neut-rals. With correction for LMW-HS, no LMW-acidscor concentration was calculated.

Without correction for LMW-HS, LMW-acids concentrations were calculated and showed a small decrease due to ozonation.

Biological activated carbon filtration

From the chromatograms (Figure 2.7a and 2.7b), it appeared that in the reference-lane (which is the treatment reference-lane without FIX treatment, before BAC the water was treated by ozonation and softening), all NOM fractions were partly removed by BAC. For water in the FIX-lane (FIX, ozonation, softening followed by BAC) BAC caused a small increase in the larger HS fraction, while the other fractions were decreasing.

The calculated concentrations by FIFFIKUS in Figure 2.7c shows for BAC in the reference-lane a decrease in all fractions, which is in accordance with the

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0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB

LMW-acids (and HS)

Ref. lane; before ozonation Ref. lane; after ozonation

(a) WPK-feed water

0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB

LMW-acids (and HS)

FIX-lane; before ozonation FIX-lane; after ozonation

(b) FIX-treated water 0 1000 2000 3000 4000 5000 6000 Acids Acidscor Neu BB HS HScor BP CDOC DOC TOC OC concentration ( µ g C/L) Fraction

Ref. lane; before ozonation Ref. lane; after ozonation FIX-lane; before ozonation FIX-lane; after ozonation

(c) Quantified results of WPK-feed water and and FIX-treated WPK water before and after ozonation (in µg C/L)

Figure 2.6: Effect of ozonation on NOM composition of WPK-feed water and FIX-treated water

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0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB

LMW-acids (and HS)

Ref. lane; before BAC Ref. lane; after BAC

(a) Reference-lane 0 2 4 6 8 10 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB

LMW-acids (and HS)

FIX-lane; before BAC FIX-lane; after BAC

(b) FIX-lane 0 1000 2000 3000 4000 5000 6000 Acids Acidscor Neu BB HS HScor BP CDOC DOC TOC OC concentration ( µ g C/L) Fraction

Ref. lane; before BAC Ref. lane; after BAC FIX-lane; before BAC FIX-lane; after BAC

(c) Quantified results before and after biological activated car-bon filtration (in µg C/L)

Figure 2.7: Effect of biological activated carbon filtration on NOM composition of WPK-feed water and FIX-treated water

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grams. In both treatment lanes BAC caused a decrease in LMW-acids concentration which remained unnoticed when correction for LMW-HS was used, because in that case no acids were found at all. In the FIX-lane the small increase in HS fraction shown in Figure 2.7b could not be calculated significantly, only when the correc-tion for LMW-HS was not used the average values showed an increase in HS. Not correcting for LMW-HS gave calculated concentrations of the fractions, which were in accordance with the chromatograms, not only for water with high HS concentra-tions, but also for water with a low HS concentration.

2.3.4

Relation between NOM fractions and AOC

In Table 2.2 the Pearson correlation coefficients are given for data from both treat-ment lanes (all data), for data only from the reference-lane and for data only from the FIX-lane. A correlation coefficient above 0.80 is considered as a strong linear relation (John Sall and Lehman, 2007). Only a strong relation was found between AOC and the accumulated concentration of HS, BB, neutrals and LMW-acids in the FIX lane, where the concentration of LMW-NOM is relatively high and the HS concentration is low. A correlation of more than 0.70 was found between AOC and several NOM fractions and combinations of NOM fractions. There is not one spe-cific NOM fraction that attributed to AOC. This is as expected because addition of oxalic acid influenced the concentration of BB and HS, while oxalic acid is important for the determination of the AOC concentration.

The same result was found by other researchers. Hammes et al. (2007) showed that during ozonation of phytoplankton BB, LMW-acids and neutrals were formed as well as AOC, but it was not possible to designate one certain fraction that contrib-uted dominantly to the AOC concentration. They suggested that a combination of all three fractions correspond to the measured AOC concentration. Meylan et al. (2007) were looking for a relation between AOC and any particular NOM fraction, but did not found any relation. They also did not find a relation between LMW-organics, which is the same as LMW-acids without correction for LMW-HS in our

Table 2.2: Pearson correlation coefficients between AOC and NOM fractions All data FIX-lane Ref.-lane

AOC AOC AOC

HS 0.57 0.45 0.43 LMW-Acids 0.67 0.74 0.73 BB 0.65 0.36 0.64 Neutrals 0.74 0.74 0.66 LMW-Acids+BB 0.69 0.47 0.68 Neutrals+LMW-Acids 0.75 0.75 0.70 LMW-acids+BB+Neutrals 0.72 0.57 0.69 HS+LMW-acids+BB+Neutrals 0.65 0.85 0.57

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research, and AOC. Besides the LMW-NOM fractions, also HS can contribute to biological regrowth and may possibly relate to AOC (Camper, 2004).

LMW-acids and AOC should both give an indication of the biological stability of the drinking water. Therefore a linear relation between AOC en the LMW-acids de-termined by LC-OCD is to be expected. The Pearson correlation coefficient between LMW-acids and AOC for the reference-lane was 0.73, for the FIX-lane this coeffi-cient was 0.74, see Table 2.2. When the data of the two treatment lanes were taken together the Pearson correlation coefficient decreased to 0.67. In Figure 2.8 this relation is shown for the two treatment lanes, for all measurements in the treatment lane after ozonation. In Figure 2.8a all measurement are shown. In Figure 2.8b the averages of eight samples in time and the standard deviations of the analyses after every treatment step are given. It is shown that, although there is a poor correla-tion between all LMW-acid and AOC concentracorrela-tions, the averages after the different treatment steps show a clear relation between LMW-acids and AOC concentrations. The standard deviation for LMW-acids varied between 7 and 19 µg C/L and the measurement error varied between 3% and 12%. The standard deviation for AOC varied between 12 µg C/L and 55 µg C/L and the measurement error decreased from 50% to 34%. The standard deviations and measurement errors were lower for LMW-acids concentration than for AOC concentrations. It can be stated that measuring the LMW-acids by LC-OCD is more precise than measuring the AOC concentration.

The high measurement errors of specifically the AOC concentration caused a weak relation between individual AOC concentrations and LMW-acids concentrations. Taking the averages showed a water specific linear relation between the LMW-acids concentration determined by LC-OCD without correction for LMW-HS, and the AOC concentration.

2.4

Conclusions

The focus of this chapter was on the determination of the LMW-acid concentration in the LC-OCD analysis using FIFFIKUS. In this chapter three research questions were proposed and the conclusions are given:

1. What is the effect of the HS concentration on the determination of the LMW-acids concentration by LC-OCD?

• The NOM fraction concentrations were calculated on the basis of the HS

concentration; the calculation of the different NOM fraction concentra-tions, specifically the LMW-acids and HS concentration, improved when the HS/DOC ratio in the water increased. When correction for LMW-HS was not used, the increase in calculated LMW-acids concentration due to the addition of acids was independent of the HS concentration in the sample.

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-50 0 50 100 150 200 250 0 50 100 150 200 250 300 350 AOC ( µ g C/L) LMW-Acids (µg C/L) y=0.58*x-37.6; R2=0.534 y=0.35*x-31.5; R2=0.552 FIX-lane Ref.-lane

(a) All data

-50 0 50 100 150 200 0 50 100 150 200 250 300 350 AOC ( µ g C/L) LMW-Acids (µg C/L) y=0.58*x-37.5; R2=0.989 y=0.36*x-33.7; R2=0.978 Ozonation Ozonation softening Softening BAC BAC SSF SSF FIX-lane Ref.-lane

(b) Averages after treatment steps

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• To calculate a reliable concentration of acids, correction for LMW-HS should not be used. Even not when there are LMW-HS in the water. The assumption that the correction for LMW-HS is based on, creates more uncertainties, than without this correction.

2. How can LMW-acids as determined by LC-OCD be used in practice?

• Not correcting for LMW-HS made it possible to investigate the effect

of the treatment steps ozonation and activated carbon filtration on the LMW-acids concentration.

3. Is it possible to correlate different NOM fractions to AOC?

• AOC corresponds to a combination of fractions, which was water type

specific.

• Measuring LMW-acids concentration was more precise than measuring

AOC concentration.

• Although water specific and only for average AOC concentrations, a

lin-ear relationship between the LMW-acids concentration determined by LC-OCD without correction for LMW-HS and the AOC concentration existed.

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Chapter 3

Multi-component modelling of

natural organic matter fractions

removal by ion exchange

In this chapter a multi-component model was formulated to predict the removal of different NOM fractions by IEX. By batch experiments the Freundlich and kinetic parameters for DOC were determined. An IEX pilot column was used to collect data of the breakthrough of different NOM fractions as determined by LC-OCD. NOM breakthrough was modelled using an overall advection-dispersion equation for trans-port, the Freundlich isotherm describing the adsorption of NOM fractions onto the IEX resin and the linear driving force (LDF) model to describe intra-particle mass transfer.

Breakthrough of DOC could not be described by the used single-component adsorp-tion model with the Freundlich and kinetic parameters determined from batch exper-iments. Five NOM fractions were determined, HS, BB, LMW-acids, neutrals and non-exchangeable NOM. The main NOM fraction in WPK water was HS (60%), this fraction was also the best removed fraction by IEX. HS had the highest affinity for this resin, which was shown by a higher Freundlich K value for HS than for other NOM fractions. By the summation of the five modelled breakthrough curves, the breakthrough of DOC was predicted. From this research, it turned out that a com-plex theory as ideal adsorbed solution theory (IAST) seemed not necessary because the NOM fractions measured by LC-OCD were already measured in competition. However, as every water source is different, the determination of the Freundlich parameters should be done for every NOM fraction as determined by LC-OCD, as well as for every water source. It is expected that by doing simple batch experiments the breakthrough of the different NOM compounds as determined by LC-OCD can be predicted. .

This chapter is in preparation for publication: Grefte, A., Dignum, M., Cornelis-sen, E.R. and Rietveld, L.C. Multi-component modelling of natural organic matter fractions removal by ion exchange

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3.1

Introduction

Natural organic matter (NOM) is present in almost all types of natural (untreated or raw) water. For example in lakes, rivers and reservoirs. The presence of nat-ural organic matter (NOM) can cause problems during treatment, as well as during distribution of drinking water. NOM in surface water can be removed by anion exchange (IEX), because the main part of NOM, humic, fulvic and organic acids, is negatively charged (Bolto et al., 2002b; Cornelissen et al., 2008). The efficiency of NOM removal by IEX depends on e.g. NOM concentration, NOM composition, type of IEX resin, empty bed contact time and configuration of the IEX installation. NOM fractions of low and high molecular weight (MW) are known to be removed by IEX (Crou´e et al., 1999; Bolto et al., 2002b; Allpike et al., 2005; Boyer and Singer, 2005; Humbert et al., 2005). Weak base resins do not remove NOM as efficiently as strong base resins (Crou´e et al., 1999) and bead size of the resin, water retention and capacity of the resin, and functional groups on the resin (Cornelissen et al., 2008) will also influence the removal efficiency.

Both adsorption and ion exchange are sorption processes by which one substance becomes attached to another. The difference between the two processes is that ion exchange is a stoichiometric process, for NOM removal this is described by Boyer and Singer (2008). Ions from the IEX resin are replaced by an equivalent amount of ions from the water. This process is reversible and selective, i.e. some ions are pref-erentially exchanged. In adsorption a compound is adsorbed without being replaced by another compound. Ion exchange is essentially a diffusion process and has little, if any, relation to chemical reaction kinetics in the usual sense (Helfferich, 1995). The removal of NOM by IEX is based on the exchange of negatively charged NOM compounds for chloride ions (Mergen et al., 2009). Different isotherms are used to describe the sorption removal of dissolved NOM by IEX. Langmuir and Wiegner-Jenny and Summers-Roberts equations (these last two are related to but different from the Freundlich equation) were used (Qi et al., 2012), as well as the Freundlich equation (Heijman et al., 1999).

DOC removal by IEX in a completely mixed flow reactor was modelled by Boyer et al. (2008a, 2010), that is based on a two-scale mathematical model that couples the microscale removal of DOC by IEX with the macroscale transport of aqueous and solid phases. The microscale model describes IEX as a pore diffusion process with local equilibrium at the resin surface. The DOC was classified into two fractions: a fraction that was removable by IEX and a fraction that was non-removable. It was assumed that the removable fraction of DOC could be treated as a single solute. The ideal adsorbed solution theory (IAST) is used in sorption processes to predict multi-component equilibria using their respective isotherm parameters. Crittenden et al. (1985) combined IAST, the Freundlich isotherm equation and the mass bal-ance, for modelling the adsorption of six volatile organic chemicals in competition on activated carbon, into one formula. Using this formula for different NOM

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com-pounds requires data about the individual NOM comcom-pounds. Measuring isolated NOM compounds is possible by preparative DOC fractionating (Leenheer, 1981), however, the obtained isolated NOM compound differs in time and place. NOM in water can also be characterised by liquid chromatography (LC) with online organic carbon detection (OCD) and ultra violet absorbance detection (UVD).

The objective of this chapter was to formulate a multi-component model that de-scribes the removal of different NOM fractions by IEX. The breakthrough curve of different NOM fractions were measured by LC-OCD and modelled using an overall advection-dispersion equation for transport, the Freundlich isotherm describing the adsorption of NOM fractions onto the IEX resin and the linear driving force (LDF) model to describe intra-particle mass transfer.

3.2

Materials and methods

3.2.1

Modelling

The ion exchange process for NOM removal takes place in five distinct steps (In-amuddin and Luqman, 2012). First, the NOM is brought to the surface of the resin by the water flow, which can be described by a transportation model. Second, NOM needs to diffuse through a liquid film surrounding the particle. Third, the ions dif-fuse across the film-particle interface and fourth, the ions difdif-fuse inside the particle. Finally, the ions exchange on the active sites in the resin particle. The advection-dispersion model was used to describe the transport of NOM in water through a reactor. In this model the diffusion term is neglected because the large scale mixing due to turbulence is dominant. The turbulent dispersion is described by Fick’s law. Under these assumptions the uniform flow in x-direction, with a constant dispersion

coefficient Dx and neglecting decay of NOM, can be written as (Rietveld and de Vet,

2009): ∂c ∂t = Dx ∂2 c ∂x2 − u ǫ ∂c ∂x − ρr ǫ ∂q ∂t (3.1) Where:

u = velocity of water through the reactor (m/s)

c = concentration of NOM in water (g/m3

)

Dx = dispersion coefficient in water (m2/s)

q = load on resin (g NOM/kg IEX resin)

ρr = bulk density of the resin (kg/m3)

ǫ = porosity (-)

Dx∂

2c

∂x2 = dispersion term due to the turbulence of the water and velocity shear

u ǫ

∂c

∂x = advection term due to the movement of water

ρr

ǫ ∂q

∂t = transfer function of NOM from water

x = position (m) t = time (s)

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During step 5, the charge differences between the bound ionic functional groups on the surface of the ion exchange material and free ion in the solution cause the exchange. The electro neutrality determines the quantity of counter ions that will enter the resin; their total number of charge equivalents must equal the resin

capa-city. A simplistic explanation is that when an anion Bb− in solution is exchanged

for an anion Aa−on the resin the reaction will be (Wachinski, 2006; Inamuddin and

Luqman, 2012):

bAa−+ aBb− ⇐⇒aBb−+ bAa− (3.2)

Where:

Aa− = anion A bound to the resin

Bb− = anion B bound to the resin

Aa− = anion A in solution

Bb− = anion A in solution

The equilibrium equation for this reaction that can be obtained for different con-centrations is:

KB/A =

(Bb−)a(Aa−)b

(Aa−)b(Bb−)a (3.3)

Where:

KB/A is the selectivity coefficient

For a treatment system with a specific type of resin and a known substance to be exchanged, there is a relationship between the amount of adsorbed matter per unit weight of resin and the equilibrium concentration in the water, when temperature is held constant. This relation is called a sorption isotherm. The shape of the isotherm can be described in various mathematical ways (linear isotherm, Freundlich isotherm, the Langmuir isotherm), here, the Freundlich adsorption isotherm is used and given by the expression:

q = Kc1/n (3.4)

Where:

K = Freundlich parameter (g/kg / (mg/L)n)

1/n = Freundlich parameter (-)

The NOM transfer rate in the resin is a function of the difference between the actual adsorbed amount and the adsorbed amount in equilibrium, and a kinetic rate

con-stant k2 (Heijman et al., 1999), called the linear driving force model (LDF-model):

∂q

∂t = k2(qeq−qt) (3.5)

Where:

qeq = equilibrium exchange capacity of resin (g/kg)

qt = exchange capacity of resin at time t(g/kg)

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The LDF-constant k2 and the Freundlich parameters K and 1/n can be

determ-ined by batch equilibrium experiments. From bottles filled with water and a certain amount of resin, after a certain contact time, the corresponding surface loadings, Freundlich parameters and mass transfer coefficient were calculated from the follow-ing mass balances on isotherm bottles:

q = (c0−c)V /M (3.6) and qeq = K(ceq−cnon) 1/n (3.7) and q0−qeq qt−qeq = k2t (3.8) Where:

q0 = initial exchange capacity of resin (g NOM/kg IEX resin)

c0 = initial concentration of NOM in the water phase (g/m3)

cnon = concentration of the non-exchangeable NOM fraction (g/m3)

V = volume of batch (m3

) M = mass of resin (kg)

From the equations described, general equations for transport and exchange of NOM to ion exchange resin, can be formulated (Rietveld, 2005):

∂c ∂t = Dx ∂2 c ∂x2 − u ǫ ∂c ∂x − ρr ǫ ∂q ∂t = Dx ∂2 c ∂x2 − Q ATǫ ∂c ∂x −k2(Kc 1/n −q) (3.9) ∂q ∂t = − u ρp ∂c ∂x = Q ATρp ∂c ∂x (3.10) Where: dp = particle diameter (m)

q = average exchange capacity of resin (g NOM/kg IEX resin)

Q = water flow (m3

/s)

AT = Total surface area of the reactor (m2)

ρp = density of the particle (kg/m3)

3.2.2

Modelling approach

When a certain effluent quality is required, the determination of a so-called break-through curve is important. The breakbreak-through curve is obtained by plotting the effluent concentration as a function of time or bed volumes (BV). With the determ-ined Freundlich parameters and the process conditions, like column dimensions, flow, NOM concentration of the influent, it is possible to predict a breakthrough curve in the IEX column. For modelling the breakthrough of NOM by ion exchange the Stimela platform (van der Helm and Rietveld, 2002) is used, based on the equa-tions described earlier. In order to be able to solve the partial differential equation

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numerically with Matlab/SimulinkT M, they are transferred to a set of ordinary

dif-ferential equations. This is done by discretising the reactor in space, using unit elements. The more unit elements the better a plug flow is approached, in this re-search five completely mixed unit elements were used. The basic discrete equations of a treatment process, neglecting degradation in the water phase and transport and degradation in the solid phase, are then given in the following ordinary differential equations (ODEs)(based on Euler) (Rietveld, 2005):

dcef f dt = − u ǫ cef f −cinf ∆x −k2(K(cef f) 1/nq) (3.11) dq dt = − u ρp cef f −cinf ∆x (3.12) Where:

∆x = height of the unit element (m)

cinf = influent concentration (g/m3)

cef f = effluent concentration (g/m3)

3.2.3

Experimental setup

Water quality

Raw water samples were collected from the treatment plant Weesperkarspel (WPK) of Waternet, water cycle company for Amsterdam and surrounding areas. WPK water is surface water that is pre-treated by coagulation, self-purification in a lake with a residence time of 100 days, and rapid sand filtration. The pH of the water was 7.6. The DOC concentration of WPK water was approximately 5.7 mg C/L and the HS concentration, as determined by LC-OCD, was approximately 60% of the DOC concentration. The LC-OCD chromatogram is shown in Figure 3.1. The determined concentration of the different compounds was: HS 3.4 mg C/L; BB 1.1 mg C/L; Neutrals 0.6 mg C/L and LMW acids 0.2 mg C/L.

Ion exchange resin

The IEX resin used in this research was Lewatit VP OC 1071 type resin, which is a strong-base gel resin with an acrylic (type 1) structure. This resin was the best performing resin for WPK feed water, according to a selection study on bench scale (Cornelissen et al., 2008). The total IEX capacity of the resin is 1.25 eq/L.

Batch experiments

Before using the new Lewatit VP OC 1071 resin for batch experiments, the resin was regenerated overnight with 10% NaCL and 2% NaOH solution. After regeneration the resin was rinsed with demineralised water.

The exchange kinetics of the resin was determined at a concentration of 160 mg resin/L. Over two weeks time, eight water samples were taken and analysed. In

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-1 0 1 2 3 4 5 6 7 8 9 30 40 50 60 70 80

rel. Signal Response

Retention time (minutes)

BP HS BB LMW acids WPK

Figure 3.1: LC-OCD chromatogram of raw WPK water

addition, different amounts of each resin were used (i.e 10, 20, 40, 80, 160, 320, 640 and 1280 mg) in beakers filled with 1 litre of the same WPK water each, for determining the exchange isotherms. Also a blank of WPK water without resin (control) was tested.

The water was stirred by magnetic stirrers at a constant temperature of 16oC. After

2 weeks of contact time, the characteristics of the NOM remaining in the water after treatment were analysed.

Pilot plant experiment

The FIX pilot, as described by Cornelissen et al. (2009) contained Lewatit VP OC

1071 type resin. The flow through the pilot was 4 m3

/h. The fixed bed height of the ion exchange bed was approximately 0.5 meter, when fluidised it was approximately

1 meter. The surface area was 0.3 m2

, the column was filled with 150 litre of resin and the empty bed contact time was approximately 2.3 minutes. The column was in operation for approximately 1 year and regenerated every three weeks, after a run time of 15,000 bed volumes, with a 10% NaCl solution. Before the IEX column was brought back in operation the resin was rinsed with tap water.

3.2.4

Analyses

The water samples were analysed for general physicochemical characteristics such as UV254, pH and temperature, which were determined using standard procedures

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