AN ADD-ON FILTER TECHNIQUE TO IMPROVE MICROPOLLUTANT REMOVAL AND WATER QUALITY IN ON-SITE SEWAGE TREATMENT FACILITIES

Wen Zhang

September 2018

TRITA-ABE-DLT-1821 ISBN: 978-91-7729-936-3 Wen Zhang TRITA-ABE-DLT-1821

© Wen Zhang 2018 Phd thesis Division of Water and Environmental Engineering Department of Sustainable Development, Environmental Science and Engineering School of Architecture and the Built Environment KTH Royal Institute of Technology SE-100 44 STOCKHOLM, Sweden Reference to this publication should be written as: Zhang, W (2018) “An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities” TRITA-ABE-DLT-1821

ii An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

SUMMARY IN SWEDISH

Småskaliga (enskilda) avloppsreningsanläggningar i Sverige och på många håll i världen släpper på grund av ofullständig rening betydande mängder kväve (N) och fosfor (P) till grundvatten och ytvatten. Mikroföroreningar (MP) har också hittats i både ytvatten och grundvatten, vilket indikerar otillräckligt avlägsnande av MP i dessa anläggningar. Det övergripande syftet med denna avhandling var att undersöka olika typer av organiska och oorganiska filtermaterial (sorbent) för att identifiera en lämplig typ eller kombination av typer med hög kapacitet att ta bort en mängd MP från avloppsvatten i småskaliga anläggningar. Samtidigt har konventionella parametrar och ämnen (t ex N, P) i avloppsvattnet studerats för att undersöka om studerade sorbent även samtidigt kan avskilja dessa. Två kolonnförsök i laboratorieskala, följt av ett fältförsök, utfördes för att studera avskiljningen av en uppsättning organiska MPs genom filtrering med organiska och oorganiska sorbent. Uppsättningen MPs som tillsattes avloppsvattnet omfattade olika produktkategorier, t.ex. ett artificiellt sötningsmedel, organofosfater, parabener, personliga hygienprodukter, perfluoralkylsubstanser (PFAS), bekämpningsmedel, läkemedel, en mjukgörare, en bisfenol, stimulanter och ytaktiva ämnen.

Vardera fem organiska och oorganiska sorbenter som testades visade att kolbaserade organiska sorbenter avskiljde MPs i genomsnitt 20% bättre än naturliga fibermaterial och oorganiska sorbent. Organiska sorbent med bra prestanda vid avlägsnande av MP och en konventionell sandbädd visade emellertid begränsad förmåga att avlägsna P, medan kalciumrika sorbent ökade P- avlägsnandet mycket. Fem sorbent valdes för ett långsiktigt kolonnexperiment som undersökte 31 målmikroföroreningar. De kemiska och fysikaliska egenskaperna hos de valda organiska och oorganiska filtermaterialen varierade mycket, vilket hade signifikanta effekter på deras förmåga att avlägsna målämnena från avloppsvatten. Stor specifik yta och en varierad fördelning av makroporer och mikroporer var viktiga för avlägsnande av MP, såsom demonstrerades av granulerat aktivt kol (GAC).

Relativt hydrofoba MPs (log Kow ≥3) avlägsnades väl av alla organiska sorbenter. Enbart hydrofobicitet kunde emellertid inte förklara adsorptionen av MP. Negativt laddade MPs adsorberade till lignit (som var ett av testade sorbent) befanns lätt frigöras över tid från sin negativt laddade yta. För PFAS befanns molekylvikt och tillgänglig yta vara starkt positivt korrelerad med förmågan att avskilja ämnet hos materialen lignit, Xylit och sand. För andra grupper av MP var apolär och polär ytarea och förhållandet mellan dessa positivt korrelerade med avskiljningen av MP hos lignit och Xylit. Slutsatsen är att de kemiska och fysikaliska egenskaperna hos en uppsättning filtermaterial måste beaktas noga när det väljs för ett tilläggsfilter för små avloppsteknik.

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Markbäddar och infiltrationslösningar är mycket vanliga i Sverige. Resultaten från denna undersökning visar att de avskiljer MP men för att uppnå effektiv behandling måste ytterligare tekniker tillämpas. Två sorbent, GAC och Xylit (xyloid lignit) testades i 24 veckor som ett tillsatsfilter i utflödet från en markbädd. Båda filtermaterialen befanns avsevärt förbättra avlägsnandet av MP. En utbytbar tilläggsenhet föreslås därför om avskiljningen av MP från små avlopp ska kunna förbättras. I denna undersökning har GAC och Xylit visat sig vara bra material som kan ingå i ett filter. Dessa material kan dock inte minska koncentrationerna av fosfor och kväve i avloppsvatten till en nivå som uppfyller svenska lagstadgade utsläppsgränser utan andra metoder måste läggas till i reningssystemet.

iv An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

ACKNOWLEDGEMENTS

First and foremost, I would like to express my sincere gratitude to my main supervisor, Professor Gunno Renman, for his guidance in the research and great support in the laboratory and in the field. I appreciate his professional ideas in discussions and the rich practical experiences he shared during field studies. My gratitude also to my co-supervisor, Dr. Erik Kärrman, for great support and encouragement during the whole study. I would like to thank the professors and all the scientists with whom I collaborated in the RedMic project group: Berndt Björlenius, Patrik Andersson, Karin Wiberg, Peter Haglund, Lutz Ahrens, Kristin Blum, Pablo Gago Ferrero, Qiuju Gao, Meritxell Gros, Henrik Jernstedt, Ande Rostvall and Shiromini Gamage. Thank you all for the deep and invaluable discussions, support during the experiments and suggestions for data analysis.

I am grateful to Dr. Agnieszka Renman for her enthusiastic help in the laboratory. Special thanks to Dr. Heléne Ejhed for being my mid-term exam reviewer, and Professor Elzbieta Plaza, for quality control of my thesis. Warm thanks for all the help from Aira Sarrelainen and Britt Aguggiaro regarding administrative issues. Many thanks are due to Dr. Mary McAfee for her help with English grammar.

Thanks to my friends and colleagues, Ezekiel Kholoma and Raúl Rodriguez Gómez, who helped me to build my columns and taught me to be an engineer. Thanks to Anqi Li and Aibin Zhang for their assistance in my laboratory work. My sincere thanks go to Yuanying Chen, Minyu Zuo, Guillaume Vigouroux, Romain Goldenberg and Liangchao Zou, for all your kindness, friendship and the enjoyable times we shared. Extra thanks to Xi Pang and Ziyi Wang for every happy lunch time we spent together during my last year.

Great thanks to my parents, Shoufeng Zhang and Huaiying Cui, for their unconditional baking and love. I would like to thank my beloved husband, Anders Larsson, and the best mother-in-law, Ingrid Larsson, for their understanding and great support during my PhD study. Thanks to my dearest son, Jack Zhang Larsson, who disturbed me every five minutes when I tried to work at home, reminding me that I have a family to take care of.

Finally, thanks to the Swedish Research Council FORMAS for funding part of my work in the project RedMic (Reduction of diffuse emissions of micropollutants from on-site sewage facilities, 216-2012-2101).

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vi An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

TABLE OF CONTENT Summary ...... iii Acknowledgements ...... v Table of Content ...... vii List of appended papers ...... ix List of abbreviations...... xi Abstract ...... 1 1. Introduction ...... 1 1.1. Aims and objectives 2 2. Background ...... 3 2.1. On-site sewage treatment technologies 3 2.2. Micropollutant removal from domestic wastewater 5 2.3. Factors affecting micropollutant removal 6 2.3.1. Physical properties and chemical structure of the sorbent 6 2.3.2. Physicochemical properties of micropollutants 8 2.3.3. Adsorption process 8 2.3.4. Effect of biofilm 8 3. Materials and methods ...... 9 3.1. Filter media 9 3.2. Target chemicals 11 3.3. Screening experiment (Paper I) 11 3.4. Long-term column experiment (Papers II and III) 14 3.5. Field study (Paper IV) 16 3.6. Analytical methodology for micropollutant analysis (see also Papers I-III) 17 3.7. Determination of surface functional groups on the sorbents 18 3.8. Determination of point of zero charge (pHpzc) of the sorbents 18 3.9. Prediction of phosphorus removal 18 3.10. Calculations and statistical analysis 19 3.11. Quality assurance and quality control 20 4. Results and discussion ...... 21 4.1. Removal of conventional contaminants (Papers I, II and IV) 21 4.1.1. Dissolved organic carbon and chemical oxygen demand 21 4.1.2. Ammonium-nitrogen 23 4.1.3. Phosphorus 25 4.2. Removal of micropollutants 27 4.2.1. Comparison of sorbent performance in micropollutant removal (Papers I and II) 27 4.2.2. Removal of target micropollutants (Papers I and II) 30 4.2.3. Removal of micropollutants over time (Paper II) 31 4.3. Sorbent characterisation (Paper II) 32 4.3.1. Surface charge on sorbents and chemicals 32 4.3.2. Characterisation of surface functional groups on virgin and used sorbents 32

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4.4. Possible removal mechanism of micropollutants (Papers I-III) 34 4.4.1. Impact of pore size and surface area on compound removal 34 4.4.2. Hydrophobic effects 36 4.4.3. Impact of surface functional groups 37 4.4.4. Relationship between removal efficiency and physicochemical properties of micropollutants (Paper III) 38 4.4.5. Impact of biofilm 39 4.5. The add-on filter technology in the field 40 5. Conclusion and future perspectives ...... 43 6. References ...... 45

viii An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

LIST OF APPENDED PAPERS This thesis is based on the following papers, which are referred to in the text by their Roman numerals I. Zhang W., Blum K., Gros M., Ahrens L., Jernstedt H., Wiberg K., Andersson P.L., Björlenius B. & Renman G. 2018. Removal of micropollutants and nutrients in household wastewater using organic and inorganic sorbents. Desalination and Water Treatment, in press, doi:10.5004/dwt.2018.22836 II. Zhang W., Gago-Ferrero P., Gao Q., Ahrens L., Blum K., Rostvall A., Björlenius B., Andersson P.L., Wiberg K., Haglund P. & Renman G. 2018. Removal of 31 organic micropollutants and phosphorus by filter media in a column experiment using household wastewater. Journal of Environmental Management, submitted. III. Rostvall A., Zhang W., Dürig W., Renman G., Wiberg K., Ahrens L. & Gago-Ferrero P. 2018. Removal of pharmaceuticals, perfluoroalkyl substances and other micropollutants from wastewater using lignite, Xylit, sand, granular activated carbon (GAC) and GAC+Polonite® in column tests – Role of physicochemical properties. Water Research 137: 99-106. IV. Zhang W., Gago-Ferrero P., Gao Q., Björlenius B., Ahrens L., Andersson P.L., Wiberg K., Kärrman E. & Renman G. 2018. Wastewater purification and removal of micropollutants in a soil treatment system and by subsequent filtration through activated carbon and xyloid lignite – a field experiment. Manuscript.

Reprints are published with the kind permission of the journals concerned.

Publications not included in the thesis: Zhang W. & Renman G., Screening of different types of on-site sewage facilities - treatment function and potential for removing micropollutants, 2016. 13th IWA specialist conference on small water and wastewater systems, Athens, Greece. Kholoma E., Renman G., Zhang W. & Renman A. 2018. Leachability and plant-availability of phosphorus in post-sorption wastewater filters fortified with biochar. Environmental Technology 12: 1-11.

AUTHOR’S CONTRIBUTIONS TO PAPER I-IV

I. Designed and planned the experiment with guidance from supervisors and discussion with the co-authors, conducted the experiments, analysed the general wastewater quality parameters, interpreted both general wastewater quality parameters and micropollutants data, and wrote, submitted and revised the paper for publication.

II. Designed and planned the experiment with guidance from supervisors and discussion with the co-authors, conducted the experiments,

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analysed the general wastewater quality parameters, interpreted both general wastewater quality parameters and micropollutants data, and wrote and submitted the paper.

III. Designed and planned the experiment with guidance from supervisors and discussion with the co-authors, conducted the experiments, interpreted part of the micropollutants data, and took a large part in writing and revising the paper for publication.

IV. Designed and planned the experiment with guidance from supervisors, conducted the field experiments together with the main supervisor, performed field sampling, analyzed the general wastewater parameters, interpreted both general wastewater parameters and micropollutants data, and wrote the paper.

x An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

LIST OF ABBREVIATIONS Abbreviation Description AB Aromatic bonds BOD Biochemical oxygen demand COD Chemical oxygen demand DOC Dissolved organic carbon FTIR Fourier transform infrared GAC Granular activated carbon HRT Hydraulik retention time KBr Potassium bromide

Kow Octanol-water partition coefficient Log D Distribution coefficient between octanol and water LSD Least significant difference MP Micropollutant MW Molecular weight

Ntot Total nitrogen

NH4-N Ammonium nitrogen OSSF On-site sewage facility PAC Powdered activated carbon PCA Principal component analysis pKa Acid dissociation constant Total phosphorus Ptot PTS Package treatment system PZC Point of zero charge S Solvent-accessible surface area

Sw Water solubility SA Apolar suface area SA/SP Ratio between apolar and polar surface area SEPA Swedish Environmental Protection Agency SFG Surface functional group SMED Swedish Environmental Emissions Data SP Polar surface area SSA Specific surface area STS Soil treatment system WWTP Wastewater treatment plant

Chemical names Abbreviation Description AHTN Tonalide APAP Acetaminophen BPA Bisphenol A BPH Benzophenone BTEX Benzene, toluene, ethyl-benzene and m-,p-,o-xylenes

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CBZ Carbamazepine CF Caffeine DEET N,N-diethyl-m-toluamide DF Diclofenac FOSA Perfluorooctanesulfonamide HCB Hexachlorobenzene HHCB Galaxolide IP Ibuprofen LAT Lamotrigine LOT Losartan MEP Metoprolol MK Musk ketone MTBE methyl tertiary butyl ether MTBT 2-(methylthio)-benzothiazole MX Musk xylene NBBS N-butylbenzenesulfonamide OC Octocrylene OP Oxazepam PFAS Perfluoroalkyl substances PFBS Perfluorobutanesulfonate PFOS Perfluorooctanesulfonate PP Propylparaben SL Sucralose TAME Tertiary amyl methyl ether TBEP Tris(2-butoxyethyl)phosphate TBP Tributylphosphate TBT Terbutryn TCEP Tris(2-chloro-ethyl)phosphate TCS Triclosan TDCPP Tris-(1,3-dichloro-2-propyl)phosphate TMDD 2,4,7,9-tetramethyl-5-decyn-4,7-diol TPP Triphenylphosphate α-TPA α-Tocopheryl acetate

xii An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

ABSTRACT

Onsite sewage treatment facilities (OSSFs) in Sweden currently release significant amounts of nitrogen (N) and phosphorus (P) into groundwater or/and receiving water bodies. Micropollutants (MPs) have been found in both surface water and groundwater, indicating insufficient removal of MPs by OSSFs. Two laboratory-scale column experiments, followed by a field experiment, were performed to study removal of a set of organic MPs by organic and inorganic sorbents. The set covered different product categories, e.g. an artificial sweetener, organophosphates, parabens, personal care products, perfluoroalkyl substances (PFASs), pesticides, pharmaceuticals, a plasticiser, a polymer impurity, stimulants and surfactants. An experiment using five organic and five inorganic sorbents showed that coal-based organic sorbents performed better than natural fibre and inorganic sorbents in removal of MPs, with 20% higher removal efficiency on average. Five sorbents were selected for a long-term column experiment examining 31 MPs. Physical properties and chemical structure of the sorbents, namely pore structure and surface functional groups, were found to be correlated to their capacity for removal of MPs. Molecular weight, solvent-accessible area, octanol-water partition coefficient and distribution-coefficient of PFASs were found to be strongly positively correlated with their removal by some sorbents. Organic sorbents with good performance in removal of MPs and a conventional sand bed showed limited ability to remove P, while calcium-rich sorbents increased P removal greatly. Two sorbents, granulated activated carbon (GAC) and xyloid lignite (Xylit), were tested for 24 weeks in an add-on filter for effluent from a soil treatment system and found to significantly improve removal of MPs. A replaceable add-on unit for removal of MPs from OSSF effluent is recommended and should contain an organic sorbent such as GAC or Xylit.

Key words: micropollutant, on-site sewage facilities, physicochemical properties, pore structure, sorbents, surface functional group

1. INTRODUCTION

On-site sewage facilities (OSSFs) are commonly used in rural and semi-urban areas to treat wastewater. In Sweden, around one million people, representing 10% of the population, are connected to such on-site treatment plants. However, theoretical calculations show that, after treatment, these systems still release 295 tons of phosphorus and 3066 tons of nitrogen per year in their effluent (Olshammar et al., 2015). The main reason for eutrophication of lakes and rivers in Sweden is phosphorus and nitrogen emissions from land-based activities and OSSFs are a substantial source of

emissions, accounting for 15% of the total phosphorus (Ptot) load and 5% of the total nitrogen (Ntot) load (Ek et al., 2009).

Insufficient wastewater treatment by OSSFs has been reported by different studies, which have found that the water discharged often cannot meet the quality levels recommended by the Swedish Environmental Protection Agency (SEPA) (Olshammar et al.,

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2015; Eveborn et al., 2012a; Hubinette, 2009). In particular, the removal of nutrients by soil-based systems shows high variation. Overall, it has been found that phosphorus and nitrogen cannot be well removed by conventional soil-based systems, so wastewater treatment in such systems therefore needs to be enhanced by other technologies (Kholoma et al., 2016; Kauppinen et al., 2014). Recent studies have also shown that effluent from OSSFs contains a wide range of micropollutants (MPs). Several MPs, such as pesticides (i.e. dichlorobenzamide) and organophosphorus flame retardants (i.e. tributylphosphate and tris(2-chloro- ethyl)phosphate), have been found to be poorly removed by conventional soil-based wastewater treatment systems (Blum et al., 2017; Gros et al., 2017). Therefore, studying the removal of MPs and improving the quality of the water discharged from OSSFs is an important research area.

Any anthropogenic chemicals present in low concentrations in water, although above a natural background level in the environment, can be defined as micropollutants (MPs) (Stamm et al., 2016). These chemicals derive from a vast array of commonly used products, such as pharmaceuticals, personal care products, pesticides and industrial chemicals. They can have toxic, persistent and bioaccumulative properties, causing negative effects on the environment and/or organisms. A wide range of MPs have been identified at different concentrations in recipient waters for both central wastewater treatment plants (WWTPs) and OSSFs (Tröger et al., 2018; Gago-Ferrero et al., 2017; Fisher et al., 2016). They have even been found in groundwater (Kreuzinger et al., 2004) which may threaten ecosystem health in areas where groundwater is used as a drinking water source (Tröger et al., 2018). Wastewater treatment techniques are traditionally optimised to remove macroorganic pollutants, phosphorus, nitrogen and pathogens, whereas MPs may be poorly or insignificantly treated. Advanced treatment methods to remove MPs are being developed for WWTPs world-wide (Guerra et al., 2014; Kårelid et al., 2017; Pan et al., 2016; Petrovic et al., 2003), but less attention has been devoted to developing corresponding techniques for OSSFs.

Since OSSFs are commonly based on passive filtration of wastewater in soil systems, this thesis focused on development of a technique that could be easily fitted to soil-based systems, but also adapted for other types of small-scale wastewater treatment systems. Filters are interesting in this context since their active components can be manufactured from many different materials, so-called sorbents, that can eliminate the contaminant of concern. 1.1. Aims and objectives

The overall aim of this thesis was to investigate different kinds of organic and inorganic sorbents, in order to identify a suitable type, or combination of types, with high capacity to remove a multitude of MPs from wastewater treated by OSSFs, while simultaneously

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improving other water quality parameters such as phosphorus concentration. In order to approach this research aim, the following objectives were established:

 Evaluate candidate organic and inorganic sorbents in terms of their capacity for removing multiple MPs and nutrients in a short-term screening experiment. Select a few promising sorbents for further studies (Paper I)

 Determine the properties of chosen sorbents, investigate the removal mechanisms of MPs and identify relationships between physicochemical properties of the MPs and the removal efficiency in a long-term column experiment (Papers II and III)

 Investigate the feasibility of an add-on filter, while testing two selected sorbents, for removal of MPs from OSSF effluent in field conditions (Paper IV). 2. BACKGROUND This chapter reviews current knowledge regarding on-site sewage treatment and micropollutant removal technologies.

2.1. On-site sewage treatment technologies

In order for treated wastewater to comply with human health and environmental considerations, the SEPA has established two recommended protection levels (normal, high) as guidelines for OSSF operators (Table 1). The degree of protection required at each level is based on environmental conditions in the particular geographical area.

Different treatment technologies have been developed for OSSF, for example the soil treatment system (STS), the source separation system and the package treatment system (PTS). According to an investigation conducted by Swedish Environmental Emissions Data, around 40% of the OSSFs in Sweden use STS technology (Olshammar, 2015). The most common type of STS comprises a sludge separation tank, followed by either a soil bed or an infiltration bed (Eveborn, 2012b). The difference between these bed types is that the constructed soil bed can have an impermeable bottom layer and effluent can therefore be controlled and monitored, while the infiltration bed only has a distribution layer of permeable gravel or sand, conducting the wastewater below the trench to the natural soil. Thus there is a greater risk of wastewater from infiltration beds entering the groundwater before it is well treated (Figure 1). The removal of nutrients by soil treatment systems shows large variations (e.g. Kholoma et al., 2016; Kauppinen et al., 2014). Phosphorus, which is an important cause of eutrophication of surface waters, cannot be well removed by conventional STS and therefore treatment needs to be improved

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by other technologies (Kholoma et al., 2016). Therefore, nutrient removal by STS should also be taken into consideration when seeking to improve removal of MPs.

The PTS has become more popular in recent years, but a very small proportion (<2%) of OSSFs are using the PTS as yet. The PTS process varies with different suppliers, but usually includes chemical dosing, aeration, precipitation and purification. In 2009, the County Administration Boards in Sweden carried out a study on 24 different types of PTS in which effluent water samples from 115 PTS were taken for chemical and biological analysis. The

results showed that the average biological oxygen demand (BOD7) value was just within the normal threshold set by the SEPA, but

that the concentration of Ptot exceeded the limit (Hubinette, 2009).

A substantial proportion of households in Sweden (serving 125 000 person-equivalents (PE)) have a source separation sewage

Table 1. Normal and high protection thresholds for biological oxygen demand

(BOD), total phosphorus (Ptot) and total nitrogen (Ntot) concentrations in effluent from on-site sewage facilities (OSSFs), according to SEPA (2018) Normal protection level High protection level

-1 -1 BOD7 90% reduction / 30 mg L 90% reduction / 30 mg L

-1 -1 Ptot 70% reduction / 3 mg L 90% reduction / 1 mg L

-1 Ntot - 50% reduction / 40 mg L

Figure 1. Schematic diagram of a soil-based system for on-site treatment of wastewater. (A) Soil bed and (B) infiltration bed. (1 = distribution conduit, 2 = distribution layer, 3 = sand, 4 = drainage conduit, 5 = drainage layer, 6 = impermeable bottom layer).

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treatment system where blackwater and greywater are collected separately (Olshammar, 2015). The septic tank is emptied periodically and the contents are transported to a municipal WWTP. Greywater is discharged directly to ditches and ends up in natural surface waters, or is discharged to soil infiltration beds. Further installation of other methods, such as treatment with only a de-sludging tank or a septic tank (22% and 9%, respectively), has been illegal since the 1960s. Existing facilities of this type are decreasing in numbers as property owners more or less voluntarily upgrade their sewage treatment solution or are required to do so by the local authority.

2.2. Micropollutant removal from domestic wastewater

Many technologies have been studied for the removal of MPs from wastewater, including membrane bioreactors (Abegglen et al., 2009; Clara et al., 2005; Sipma et al., 2010), activated sludge systems (Sipma et al., 2010), ultraviolet oxidation (Li et al., 2017), ozonation (Katsoyiannis et al., 2011), slow sand filtration (D’Alessio et al., 2015), plant uptake in constructed wetland (Matamoros et al., 2017; Lv et al., 2016) and adsorption by a sorbent such as activated carbon (Kårelid et al., 2017). However, for practical and economic reasons some of these technologies are not suitable or are difficult to apply in OSSFs. Ecotoxicological hazards when using reactive treatments have also been reported, e.g. ozonation may generate toxic transformation products that increase the genotoxic and mutagenic potential of MPs in wastewater (Petala et al., 2008; Stalter et al., 2010).

Organic sorbents, such as activated carbon in both granular (GAC) and powdered form (PAC), have been widely tested for removal of MPs. The granular form is considered more suitable for OSSFs than the powdered form, since the granules can be used as a filter medium with less risk of clogging. In fact, GAC has been found to be one of the most effective organic sorbents in the removal of MPs. Its efficacy has been tested for a variety of MPs, such as pharmaceuticals (Ek et al., 2014; Kårelid et al., 2017; Serrano et al., 2011), cholorophenoxy pesticides (Derylo-Marczewska et al., 2017) and per- and polyfluoroalkyl substances (McCleaf et al., 2017; Ochoa-Herrera et al., 2008). However, the adsorption capacity can differ between different types of GAC (Kårelid et al., 2017; Wei et al., 2016). Moreover, GAC is generally expensive, so an alternative sorbent with lower costs is desirable. Other organic sorbents, such as lignite (often referred to as brown coal), have been studied for their efficacy in adsorption of different substances, including MPs, and good removal efficiencies have been observed (Aivalioti et al., 2012; Kleineidam et al., 2002; Redding & Cannon, 2009; Rossner et al., 2009). However, the treatment effect has only been studied for a few types of individual MPs, so more research is needed to investigate the treatment efficiency when large numbers of different MPs are present in the wastewater.

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Most inorganic sorbents are used for removal of nutrients and regular wastewater contaminants, while only a few studies have reported their efficiency in removal of MPs. For example, clay materials show promising adsorption potential for removal of a few pharmaceuticals and personal care products from aqueous solution (Dordio et al., 2017; Styszko et al., 2015; Sotelo et al., 2013). Zeolite, which has a porous uniform structure, shows good removal of specific MPs, such as methyl tert-butyl ether (MTBE) (Rossner et al., 2009; Rossner et al., 2008).

Sand, the most common inorganic filter media, is capable of removing some MPs, while a number of other MPs are poorly removed (D’Alessio et al., 2015; Teerlink et al., 2012). In a study examining the fate of a few pharmaceuticals in a slow sand filtration system, the removal efficiency was found to be between 11 and 100%, depending on the pharmaceutical (D’Alessio et al., 2015). Similarly, a sand column experiment using different loading rates found that sand was capable of removing some organic chemicals, but that other chemicals were poorly removed (<20%) (Teerlink et al., 2012).

A combination of organic and inorganic sorbents could be feasible to simultaneously remove a broader spectrum of MPs and conventional wastewater contaminants. For example, Bester and Schäfer (2009) combined peat and two sands in three layers and found high removal rates for MPs, while also reporting long-term stability for this system.

Overall, the reported performance of most sorbents has been confined to a limited number of individual MPs. Thus, further research including a broader range of MPs, as well as nutrients, and their removal by alternative filter materials with better adsorption capacities is needed in order to improve wastewater treatment in OSSFs.

2.3. Factors affecting micropollutant removal

2.3.1. Physical properties and chemical structure of the sorbent

Pore structure and specific surface area

The pore structure of sorbents plays an important role in determining their sorption capacity for various MPs. According to the International Union of Pure and Applied Chemistry, pore size is classified, based on the width of the pores, into macropores (>50 nm), mesopores (2-50 nm), micropores (<2 nm), supermicropores (0.7-2 nm) and ultramicropores (<0.7 nm). The smaller micropore classes are important for the removal of organic MPs from aqueous solution, since the adsorption strength increases with decreasing pore size (Li et al., 2002). Most of the sorption takes place in the micropores (<2 nm), while mesopores and macropores serve as passages for the sorbate to reach

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micropores (Mohamed et al., 2011; Paredes et al., 2016; Swapna Priya & Radha, 2017). However, if pores are too small, size exclusion limits the adsorption of MPs of a given size and shape (Li et al., 2002). For instance, in one study a coal-based activated carbon achieved a slightly better adsorption rate than a coconut- based carbon with smaller pores, an effect attributed to a larger volume of mesopores in the coal-based activated carbon (Choi et al., 2008). Besides, multilayer adsorption has been found to take place only in meso- and macropores (Mohamed, 2011).

The specific surface area (SSA) (measured by the Brunauer- Emmett-Teller (BET) method) may also have an important influence on the adsorption capacity. A larger SSA and a varied surface (pores of different sizes) contribute to higher sorption rate (Swapna Priya & Radha, 2017; Brigante & Schulz, 2011). In a study by Aivalioti et al. (2012), the adsorption of the compounds BTEX, MTBE and TAME by raw lignite was enhanced when the SSA of the lignite was increased by 835% by thermal treatment. Besides, a large SSA provides more surface functional groups (SFGs), which are involved in the interactions with MPs, and the adsorption rate of MPs can therefore be improved.

Surface functional groups

The presence of SFGs and the surface charge are important factors affecting the adsorption capacity and the removal mechanism of MPs (Vargas et al., 2011). Micropollutants in solution can interact electrostatically or chemically with SFGs and are thus adsorbed onto the sorbent surface. For instance, sorbents such as cashew nut shell, sawdust and raw and modified mango seed can bind with methylene blue in aqueous solution, due to the presence of several active functional groups on the surface of the sorbent (Senthil Kumar et al., 2014; Senthil Kumar, 2011a). Moreover, in a study on methylene blue in aqueous solution comparing virgin sorbent with used sorbent, a few shifted peaks and new peaks were observed, which indicates adsorption of the methylene blue (Suganya et al., 2017).

The surface charge of a sorbent will appear positively or negatively charged depending on the solution pH and the point of zero

charge (pHpzc) of the sorbent. When the solution pH is lower than the sorbent pHpzc, then the surface charge on the sorbent is on average positive, and vice versa. Some MPs will also appear as charged ions depending on the pH in the solution. When the pH of the solution is higher than the acid dissociation constant (pKa) of the compound, it will mostly be in anionic form and can easily be adsorbed by a positively charged surface, and vice versa.

The pHpzc on GAC can range from acidic to basic, depending on its physicochemical properties and the treatment method used

during modification. Some types of GACs with higher pHpzc (>8)

7 Wen Zhang TRITA-ABE-DLT-1821

exhibit higher adsorption capacity (Di Natale et al., 2013; Mahmudov & Huang, 2010; Órfão et al., 2006).

2.3.2. Physicochemical properties of micropollutants

The physicochemical properties of MPs have important effects on the adsorption. Apart from the properties of the sorbents, the adsorption capacity and removal rate also depend on the nature of the adsorbed molecule (Ania et al., 2008). Because the molecular dimension and molecular conformation controls the accessbibility to the pores, and the solubility determines the hydrophobic interactions (Kose, 2010). It has also been found that chemicals

with octanol-water partition coefficient (log Kow) value > 4 have high sorption potential to solids and can thus be efficiently removed from solution (Luo et al., 2014), which was confirmed by a few studies that compounds with high hydrophobicity and low solubility show a stronger tendency to be adsorbed and retained on sorbent surfaces (Derylo-Marczewska et al., 2004; Kumar et al., 2007; Moreno-Castilla, 2004). Other physicochemical properties on adsorption have been studied in previous research as well. For example, it has been shown that the chain length and functional group of per- and polyfluoroalkyl substances (PFAS) have a great influence on their removal rate using GAC and anion exchange resins (McCleaf et al., 2017; Zaggia et al., 2016).

2.3.3. Adsorption process

Adsorption mechanisms can be divided into electrostatic interactions, hydrogen bond formation, electron donor-acceptor interactions and π-π dispersion interactions (Tong et al., 2016; Vargas et al., 2011). The anions/cations in functional groups on the surfaces of sorbents can interact electrostatically with the oppositely charged ions of MPs, and thus adsorb MPs onto their surface. As shown in a study by Tong et al. (2016), the hydrogen atoms of the organic pollutants can bond with oxygen atoms of the functional groups on surfaces in activated carbon. The basic sites on the sorbent can also act as electron donors, while aromatic rings on the MP act as electron acceptors (Mohamed, 2011b; Mattson et al., 1969). For instance, the hydrogen atoms of surface functional groups can bond with nitrogen and oxygen atoms of organic pollutants (Tong et al., 2016). The π-π dispersion mechanism is one of the most widely accepted mechanisms to explain the adsorption of aromatic compounds (Tong et al., 2016; Mohamed, 2011b; Rivera-Utrilla & Sanchez-Polo, 2002). This assumes that the aromatic structure of the sorbent interacts with the aromatic ring of the micropollutant.

2.3.4. Effect of biofilm

In a soil treatment system, biofilm develops due to the biological activities in soils. Hence biodegradation could be a significant removal mechanism for certain chemicals. For instance, some

8 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

biocides and biocide metabolites, including 2-(methylthio)- benzothiazole (MTBT), are well removed in activated soil biofilters with biodegradation as the main removal mechanism, showing average removal efficiencies of between 82 and 100 % (Bester et al., 2011). A study by Valix et al. (2006) has indicated that both adsorption and biodegradation contribute to the removal of carbamazepine (CBZ) in biochar filter. It has also been shown that a biologically activated carbon filter which combines biodegradation with physical adsorption can achieve removal of a wider range of MPs (Kalkan et al., 2011; Zhang et al., 2010). 3. MATERIALS AND METHODS

The work presented in this thesis was divided into three phases (Figure 2). In phase 1, a screening experiment was performed, based on a literature study, where 10 sorbents with different properties were selected to test their capacity on a broad range of MPs (n = 19) (Paper I). Based on the results from the screening experiment, five sorbents were selected for a continuous study (long-term experiment) in phase 2 of the work (Papers II and III). In this long-term study, an even broader range of MPs (n = 31) was tested. The removal mechanisms of MPs were further studied to identify the correlation between MP removal and physicochemical properties of the MPs and the sorbents. In phase 3, two sorbents with the best performance in removal of MPS from water were chosen to test add-on filter technology in the field during a period of six months (Paper IV). Wastewater quality was analysed in all these studies.

3.1. Filter media

Ten different sorbents covering materials with different physicochemical properties and application purposes were selected

Figure 2. Schematic diagram showing the three research phases in this thesis work.

9 Wen Zhang TRITA-ABE-DLT-1821

for the initial study (Table 2, Figure 3). They were selected based on literature studies, current applications in treatment systems and cost benefit. In tests, GAC and lignite showed promising removal for several types of MPs, and therefore two kinds of GAC with different particle sizes and a raw lignite product were chosen for the studies. Also Xyloid lignite (Xylit) was included and this material is carbonised wood fibre derived from lignite. The raw lignite was crushed and sieved to 2-4 mm before being used as a filter material in the experiments.

The five inorganic sorbents studied in phase 1 are in commercial use for different treatment purposes in OSSFs. Filtralite ® P,

Table 2. Filter materials used in the screening experiment in this thesis, along with supplier, particle size, surface area, pore volume and average pore size (Paper I) Particle Surface Pore Average Filter medium Material Supplier sizea areab volumeb pore size b (mm) (m2 g-1) (cm3 g-1) (nm) Organic materials GAC: agglomerated Chemviron Carbon AB, Filtrasorb® 300 0.6-2.4 783.5 0.519 2.7 bituminous coal Sweden EnvirocarbTM Chemviron Carbon AB, GAC: bituminous coal 3-4 914.4 0.507 2.2 207EA Sweden Mátrai Erömü, Lignite Brown coal 2-4 5.3 0.020 14.7 Bükkábrány, Hungary Nature wood fibres Xylit Eloy Water, Belgium Fibres 2.5 0.010 16.7 derived from lignite Zugol® Swedish pine bark Zugol AB, Sweden Fibres 2.5 0.017 26.4

Inorganic materials Sand: Quartz and Rådasand Rådasand AB, Sweden 0.7-1.0 0.6 0.002 17.0 feldspar Tobermorite (autoclaved Ecofiltration Nordic AB, Sorbulite® 2-4 20.4 0.092 18.1 aerated concrete) Sweden Zeolite (clinoptilolite and Filtra® N Nordkalk AB, Sweden 1-4 19.0 0.067 14.1 mordenite) Ecofiltration Nordic AB, Polonite® Calcium silicate bedrock 2-6 3.8 0.022 23.1 Sweden Saint-Gobain Byggevarer Filtralite® P Expanded clay aggregate 0.5-4 0.5 0.003 24.2 AS, Norway aProvided by supplier; bThe specific surface area, pore volume and average pore size of the sorbents was determined by Brunauer-Emmett-Teller (BET) analysis using a Tristar surface area analyzer.

Figure 3. Appearance of the 10 filter media selected for the screening study (Paper I).

10 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Polonite® and Sorbulite® are used for phosphorus removal, while Filtra® N is intended to remove nitrogen. Sorbulite® and Filtra® N are quite porous compared with other inorganic sorbents, thereby providing a large adsorptive surface area and increasing the possibility for removal of MPs. The sand used in the study was a natural sand excavated from the Råda esker in south-west Sweden. It is considered the standard test sand in Sweden.

3.2. Target chemicals

A total of 31 target compounds were evaluated in the study in this thesis and selected based on their environmental significance and their occurrence in OSSF effluent, as reported in previous studies by Blum et al. (2017) and Gros et al. (2017). They comprised: an artificial sweetener, biocide/pesticides (n = 2), fragrances (n = 4), organophosphates (n = 5), perfluoroalkyl substances (PFASs) (n = 3), pharmaceuticals (n = 9), a plasticiser, a polymer impurity, a preservative, a rubber additive, a surfactant and ultraviolet stabilisers (n = 2). The selected compounds cover a wide range of chemical classes (Table 3) and physico-chemical properties (see Table 3).

3.3. Screening experiment (Paper I)

The screening experiment was carried out for two weeks. Wastewater was taken from the effluent of a soil treatment system (STS) serving 13 households located in the municipality Ekerö near Stockholm, Sweden. Two standard mixtures, consisting of 19 case chemicals, were added to the feed water in the laboratory. Standard Mixture 1 contained HCB, TCS, α-TPA, HHCB, TBP, TDCPP, TPP, n-BBSA, MTBT, OC and TMDD (for abbreviations, see Table 3). Standard Mixture 2 contained BAM, TBT, CBZ, OP, MEP, DF, LOT and CF. The feed solution was prepared by adding 3 mL of Standard Mixture 1 and 5 mL of Standard Mixture 2 to the wastewater in a 2-L volumetric flask. The mixture was mixed thoroughly with a magnetic stirrer and then added to 8 L of wastewater in a 10-L flask, which resulted in a spiking concentration of 0.55 µg L-1 to 35 µg L-1 for individual MPs (for details see Table S2 in Paper I). The concentrations of the selected MPs were measured after spiking (Table S3 in Paper I). The feed solution was prepared freshly at the beginning of each week.

Eleven columns were constructed from polypropylene tubes with internal diameter 4.82 cm (Figure 4). Ten filter columns were filled with a 10-cm layer of one of the test filter media. One empty reference column was used to determine background levels of the MPs in the un-spiked wastewater. Two multichannel pumps were used to apply the feed water to each column and the pumping rate

11 Wen Zhang TRITA-ABE-DLT-1821

Table 3. Chemical class, name, abbreviation, chemical formula, log Kow and pKa of the 31 MPs analysed in this thesis

Class Analyte Abbreviation Formula log Kow pKa

Artificial sweetener Sucralose SL C12H19Cl3O8 -1.0ᵃ 11.8ᵃ

Biocides/pesticides Hexachlorobenzene HCB C6Cl6 5.9ᵇ N/A

N,N-diethyl-m-toluamide DEET C12H17NO 2.3ᵃ 0.67ᵃ

Fragrances Galaxolide HHCB C18H26O 6.3ᵇ N/A

Musk xylene MX C12H15N3O6 4.5ᵇ N/A

Musk ketone MK C14H18N2O5 4.3ᵇ N/A

Tonalide AHTN C18H26O 6.3ᵇ N/A

Organophosphates Tributylphosphate TBP C12H27O4P 3.8ᵇ N/A

Tris-(1,3-dichloro-2-propyl)phosphate TDCPP C9H15Cl6O4P 3.6ᵇ N/A

Triphenylphosphate TPP C18H15O4P 4.7ᵇ N/A

Tris(2-butoxyethyl)phosphate TBEP C18H39O7P 3.0ᵇ N/A

Tris(2-chloro-ethyl)phosphate TCEP C9H18Cl3O4P 1.6ᵇ N/A

Perfluoroalkyl Perfluorooctanesulfonate PFOS C8HF17O3S 7.0ᵃ -3.27ᵃ

substances Perfluorooctanesulfonamide FOSA C8H2F17NO2S 7.6ᵃ 6.52ᵃ

(PFAS) Perfluorobutanesulfonate PFBS C4HF9O3S 2.4ᵃ 0.14ᵃ

Pharmaceuticals Acetaminophen APAP C8H9NO2 0.46ᵃ 9.40ᵃ

and stimulants Caffeine CF C8H10N4O2 -0.07ᵃ 10.40ᵃ

Carbamazepine CBZ C15H12N2O 2.3ᵃ 4.17ᵃ

Diclofenac DF C14H11Cl2NO2 4.0ᵃ 4.20ᵃ

Ibuprofen IP C13H18O2 3.8ᵃ 4.40ᵃ

Lamotrigine LAT C9H7Cl2N5 1.0ᵃ 5.70ᵃ 4.10ᵃ Losartan LOT C22H23ClN6O 4.0ᵃ

Metoprolol MEP C15H25NO3 1.7ᵃ 9.70ᵃ

Oxazepam OP C15H11ClN2O2 3.3ᵃ 1.70ᵃ

Plasticiser N-butylbenzenesulfonamide NBBS C10H15NO2S 2.3ᵇ N/A

Polymer impurity Bisphenol A BPA C15H16O2 3.6ᵇ 9.6ᶜ

Preservative Propylparaben PP C10H12O3 3.0ᵃ 8.4ᵃ

Rubber additive 2-(methylthio)-benzothiazole MTBT C8H7NS2 3.2ᵇ N/A

d Surfactant 2,4,7,9-tetramethyl-5-decyn-4,7-diol TMDD C14H26O2 3.6ᵇ 13.5

UV stabilisers Benzophenone BPH C13H10O 3.1ᵇ N/A

Octocrylene OC C24H27NO2 6.9ᵇ N/A aObtained from Rostvall et al. (2018). bObtained from the U.S. Environmental Protection Agency’s EPISuite 4.1 (Blum., 2018) cObtained from Zeng G et al. (2006) dMarvin was used for drawing, displaying and characterising chemical structures, substructures and reactions, Marvin 17.21.0, ChemAxon (https://www.chemaxon.com) N/A: These compounds are not ionisable.

was adjusted to 1.14 mL min-1 (Figure 5), resulting a surface load of 75 L m-2 d-1. To simulate realistic wastewater flows in on-site systems, the pumps were run three times per day, from 7:00 to 7:30 h, 12:00 to 13:00 h, and 18:00 to 18:30 h.

The feed water was pumped onto the top of each column. Effluent pipes were curved to form a ‘U’ shape and raised 10 cm

12 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

above the column base to ensure saturated flow during the experiment (Figure 4). Effluent water from each column was collected separately in glass bottles, transferred daily to sample glass bottles for respective weekly samples, and stored in a refrigerator at 4 °C. At the end of the experiment, 26 samples, comprising two unspiked influent samples, two spiked influent samples, 20 effluent samples from filter columns and two effluent samples from the reference column, were analysed for concentration of 19 MPs and for conventional wastewater

parameters (e.g. dissolved organic carbon (DOC), Ptot, ammonium nitrogen (NH4-N), pH, conductivity, turbidity and oxygen concentrations). The analytical methods used for conventional wastewater parameters are presented in Paper I.

Figure 4. The screening column experiment in operation.

Figure 5. Schematic flowchart of the column experiment (note: not to scale). The sorbents were: (A) Filtrasorb® 300, (B) sand, (C) Xylit, (D) Filtra® N, (E) lignite, (F) Filtralite® P, (G) Zugol®, (H) Sorbulite®, (I) Envirocarb™ 207EA, (J) Polonite® (Paper I).

13 Wen Zhang TRITA-ABE-DLT-1821

3.4. Long-term column experiment (Papers II and III)

Based on the results from the screening experiment, five sorbents were selected for the long-term column experiment. These were: GAC, Xylit, lignite, sand and Polonite® (Paper II). The experiment was conducted in darkness in a temperature-conditioned room kept at 15 ± 3 °C over a 12-week period. The feed water was taken from the outlet of a septic tank system in Brottby, located 35 km north of Stockholm, Sweden, to which five households are connected (for more information, see Kholoma et al., 2016). A 22- L batch of wastewater was spiked with 1 mL of a standard mixture containing (for abbreviations, see Table 3): AHTN, BPA, BPH, HCB, HHCB, MK, MTBT, MX, NBBS, OC, TBEP, TBP, TCEP, TDCPP, TMDD and TPP and 3.7 mL of a standard mixture containing APAP, CBZ, CF, DEET, DF, FOSA, IP, LAT, LOT, MEP, OP, PFBS, PFOS, PP and SL. The spiking concentration for individual MPs was between 0.19 µg L-1 and 3.4 µg L-1 (for details, see Table S2 in Paper II). The feed solution was prepared freshly at the beginning of each week. The spiked water was kept in the refrigerator at 4 °C, from where it was pumped during the whole experimental period.

Five stainless steel columns (diameter 5 cm) were filled with a 50cm layer of each kind of sorbent. The base of the columns was fitted with stainless steel grids (1 mm mesh). Feed solution was pumped (pump 1) to the GAC, Xylit, lignite and sand columns and the effluent was collected through funnels into aluminium foil- covered glass bottles to prevent photolytic degradation (Figures 6 and 7). A dual layer system was also tested in the study, by pumping half the treated water from the GAC column to the Polonite® column (pump 2). An empty reference column receiving distilled water was applied to control background levels of MPs. This column was tilted to ensure water contact with the inner wall of the column.

The total pumping time per 24-hour period was 10.5 hours for pump 1 and 5.25 hours for pump 2 (for pumping schedule, see Table S3 in Paper II). The feed water bottle was stirred slowly by an agitator during the pumping period. The pumping rate was adjusted to 1.14 mL min-1 and the intended surface load was around 364 L m-2 day-1.

In order to monitor potential changes, the feed solution was sampled twice a week, first directly after the spiking process (day 0) and then from the remaining water in the feed water container at the end of each week (day 7). Effluent samples were collected three times per week, stored at 4 °C, and pooled to a weekly composite sample for each of the six types of columns (five sorbents plus control) at the end of each week.

14 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Feed water and effluent water samples from the 12 weeks of

column operation were analysed every week for DOC, Ptot, NH4- N, pH, conductivity, turbidity and oxygen concentrations (see Paper II for details of analytical methods). In addition, water samples from week 1, week 2, week 4, week 8 and week 12 were analysed for MP concentrations. The mean concentrations of MPs, DOC and total phosphorus at day 0 and day 7 (feedwater) were used for calculating the weekly removal efficiency.

Figure 6. Schematic diagram of the column experiment (note: not to scale). The sorbents were: (A) sand, (B) lignite, (C) Xylit, (D) GAC (E) Polonite® (Papers II and III).

Figure 7. The long-term column experiment in operation.

15 Wen Zhang TRITA-ABE-DLT-1821

Figure 8. Flowchart of the field column experiment and the sampling points (note: not to scale). A, B, C and D are the sampling points (Paper IV).

3.5. Field study (Paper IV)

Two sorbents were selected for a 24-week column experiment to test the feasibility of add-on filters in field OSSFs. The pilot set-up consisted of two columns which were placed in the effluent well at an OSSF serving 13 households located in Ekerö municipality near Stockholm. The diameter of the columns was 15.5 cm and one column filled to 80 cm depth with GAC and the other with Xylit. The OSSF in question is a soil bed-based system consisting of a three-chamber septic tank followed by a soil bed (Figure 8). A collecting container was placed in the effluent well receiving effluent water from the STS (Figure 9). A volume of 44 L of water was then pumped to each column in the up-flow direction at a pumping rate of around 80 mL min-1 and 9.25 hours every day, corresponding to a surface load at 2350 L m-2 day-1. To simulate realistic wastewater flows, the pumping time was adjusted according to Figure 10.

Figure 9. The field experiment in operation (the opening was covered with a wooden lid during the experiment).

16 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Figure 10. Schedule applied in each 24-h period for pumping water to the filters (Paper IV).

Grab samples were taken fortnightly from the influent to the soil bed (Figure 8, point A), effluent from the filter bed (Figure 8, point B) and effluent from GAC and Xylit filters (Figure 8, points C and D). Influent and effluent samples from the soil bed were collected from week 1, whereas effluent samples from GAC and Xylit columns were collected from week 6. Analysis of chemical

oxygen demand (COD), Ptot and NH4-N was carried out for all fortnightly samples, while MPs analysis was performed for monthly samples.

3.6. Analytical methodology for micropollutant analysis (see also Papers I-III)

In the screening experiment (Paper I), HCB, TCS, α-TPA, HHCB, TBP, TDCPP, TPP, n-BBSA, MTBT, OC and TMDD were extracted and analysed according to Blum et al. (2017). In brief, the wastewater samples were filtered, extracted by automated solid phase extraction with OASIS HLB cartridges (200 mg, 6 mL,

Waters, Milford, MA, USA) and filtered through Na2SO4 columns, before gas chromatography mass spectrometry (GC-MS) analysis (Pegasus 4D HRT, Leco Corp., St.Joseph, MI, USA). The compounds BAM, TBT, CBZ, OP, MEP, DF, LOT and CF were analysed by off-line SPE, using Oasis HLB cartridges (500 mg, 6 mL, Waters Corporation, Milford, MA, USA), followed by ultra- high-performance-liquid chromatography (UHPLC) (Acquity UHPLC, Waters Corporation, Milford, MA, USA) coupled to quadrupole-time-of-flight mass spectrometry (QTOF) (Xevo G2S, Waters Corporation, Manchester, UK). Extracts were analysed in both positive and negative electrospray ionisation mode. Details of the analytical method can be found in Gros et al. (2017).

In the long-term column experiments and the field study (Papers II-IV), the concentrations of AHTN, BPA, BPH, HCB, HHCB, MK, MTBT, MX, NBBS, OC, TBEP, TBP, TCEP, TDCPP, TMDD and TPP were determined according to Blum et al. (2017). Prior to instrumental analysis, water samples were extracted by solid phase extraction following the procedures described in Blum

17 Wen Zhang TRITA-ABE-DLT-1821

et al. (2017). The analyses were then conducted using gas chromatography (Agilent Technologies, Palo Alto, CA) coupled to high resolution mass spectrometry (Autospec Ultima MS, Waters Corporation, Milford, MA) as described in Blum et al. (2018). For the analysis of APAP, CBZ, CF, DEET, DF, FOSA, IP, LAT, LOT, MEP, OP, PFBS, PFOS, PP and SL, samples were extracted by solid phase extraction and further analysed using a UHPLC system coupled to a triple quadrupole mass spectrometer (MS/MS) (TSQ Quantiva, Thermo Scientific, Waltham, MA, USA), as described in paper III.

3.7. Determination of surface functional groups on the sorbents

The surface functional groups (SFG) on lignite, Xylit, sand and Polonite® were determined by Fourier transform infrared (FTIR) spectrophotometry performed using a Spectrum 100 instrument (Perkin-Elmer, Shelton, USA). The potassium bromide (KBr) pellet method was used for both virgin and used sorbent samples. Samples of used sorbent were taken from middle part of the columns, between 20 cm and 30 cm below the top of the column. A 3 mg sample of dried sorbent was mixed with 300 mg KBr and pressed under 8 ton pressure for 60 s to create a pellet. The spectrometer was fitted with a single reflection (attenuated total reflection, ATR) Golden Gate accessory unit (Graseby Specac Ltd, Kent, England) and a triglycine sulphate detector. The spectra were obtained from 16 scans and 4.0 cm-1 resolution and were within the range 400-4000 cm-1. They were analysed using software from Perkin-Elmer.

Analysis of surface functional groups on GAC was performed using both the particle and KBr pellet method, but it was found that most infrared light was adsorbed by GAC and that the spectra were not valid. Therefore, GAC spectra from previous studies (Putra et al., 2009; Seredych et al., 2008; Moreno-Castilla, 2004) were used for comparison with data obtained for lignite, Xylit, sand and Polonite® in this thesis work.

3.8. Determination of point of zero charge (pHpzc) of the sorbents

The point of zero charge (pHpzc) of GAC, Xylit, lignite, sand and Polonite® was determined using a pH titration procedure (Putra et al., 2009). This involved placing 50 mL of NaCl (0.01 M) solution in Erlenmeyer flasks and adjusting the pH solution within each

flask to a value between 2 and 12 (pHinitial) by adding HCl (0.1M) or NaOH (0.1M). A 0.15 g sample of sorbent was then added to each

flask and the pH was measured after 48 h (pHfinal). The pH at which pHfinal was equal to pHinitial was defined as the pHpzc. 3.9. Prediction of phosphorus removal

The chemical equilibrium software Visual MINTEQ 3.1 (Gustafsson, 2013) was applied to determine possible precipitation

18 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

of phosphorus by GAC, lignite, sand and Polonite®. The saturation index was calculated using the default equilibrium constants for complexes and precipitates in the Visual MINTEQ

database. The predicted phosphate-phosphorus (PO4-P) removal was then compared with the actual experimental results, in order to find a reasonable explanation for phosphorus removal. Xylit has similar chemical composition to GAC, consisting mainly of carbon and oxygen, and was therefore not included in this analysis.

3.10. Calculations and statistical analysis

The removal efficiency (RE) was calculated for DOC, COD, Ptot and NH4-N according to:

RE = (1 – Ceff / Cin) × 100% (Eq. 1)

where Cin is the influent concentration and Ceff is the effluent concentration.

Removal efficiency of MPs in the long-term column experiments and the field study was also determined according to Eq. 1. In the screening experiment, release/adsorption of MPs from/onto the sorbents was assessed. The removal efficiency values obtained were corrected for potential levels of MPs in the system according to:

Cch = Cin – Ceff0 (Eq. 2)

where Cch is the change in concentration of the MP in the outflow from the reference column, Cin is the influent concentration of the MP, and Ceff0 is the effluent concentration of the MP in the reference column. The removal efficiency for MPs (REMPs) was then calculated according to:

REMPs = [1 – Ceff / (Cinsp – Cch)] × 100% (Eq. 3)

where Ceff is the concentration of the MP in the outflow from the column, Cinsp is the concentration of the MP in spiked influent wastewater.

Experimental results were statistically evaluated using SPSS (IBM Corp.). In the screening experiment (Paper I), principal component analysis (PCA) was performed to evaluate the variation in removal behaviour of the test chemicals by the 10 sorbents. Cronbach’s alpha was calculated to test the reliability of the extracted components. One-way ANOVA and Least Significant Difference (LSD) post-hoc test were performed to test whether the removal efficiency differed between sorbents and chemicals. Negative removal values were set as zero removal in the evaluation. The relationship between MP removal and pore size and surface area of the sorbents was tested using Spearman’s rank correlation.

19 Wen Zhang TRITA-ABE-DLT-1821

For the long-term column experiments (Papers II and III), grab samples from week 5, week 7 and week 9 were statistically evaluated against weekly samples using SPSS. Mann-Whitney U tests were performed to compare the variation in the

concentrations of DOC, PO4-P, total phosphorus, NH4-N and dissolved oxygen and in the values of pH, turbidity, conductivity and redox potential. One-way ANOVA and LSD post-hoc tests were performed to test whether the removal efficiency differed significantly between sorbents. Correlations between the various physicochemical properties and the removal efficiencies obtained with the different sorbent materials were investigated using Pearson correlation using the SIMCA 14.0 software package (Umetrics, Umeå, Sweden).

Experimental results from the field study (Paper IV) were statistically evaluated using one-way ANOVA and Bonferroni

post-hoc test to compare the removal of MPs, COD, Ptot and NH4-N by the soil bed and the add-on filters (GAC and Xylit). Pearson correlation was calculated to analyse the correlation between removal efficiency and octanol/water partition coefficient

(log Kow). 3.11. Quality assurance and quality control

Screening experiment (Paper I)

The experimental set-up contained some plastic and silicon materials, e.g. in pumping tubes, which could not be avoided. The manufacturing process for these materials was unknown, so there was a risk that they contained chemicals which could have contaminated the water samples. Therefore, the impact of chemicals from the experimental set-up was checked by measuring their concentration in the influent and effluent water of the reference column. According to the analytical results on MPs, a large amount of NBBS (n-butylbenzenesulfonamide) was released into the outflow from the experimental set-up, and therefore removal of NBBS was not considered in evaluation of the sorbents. Release and adsorption of other chemicals from the experimental fittings was minor (≤5%) compared with the spiked concentration. The removal efficiency was then calculated according to Eq. 2 and Eq. 3.

Long-term column experiment (Paper II, III)

To check the impact of the experimental set-up, influent and effluent samples from the reference column were analysed to determine the adsorption and release rate. A few chemicals were detected in both the influent and effluent distilled water samples, but at insignificant concentrations (<3%) compared with the spiked concentrations of target chemicals. Random grab samples (n = 15) were taken from the outflow of all columns in week 5, week 7 and week 9. A few regular wastewater parameters, such as

20 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

pH, turbidity and conductivity and levels of DOC, PO4-P and NH4-N, were analysed to compare against those obtained for the weekly samples, to check the representativeness of the weekly samples. No significant differences (p>0.05) were found between the grab samples and the weekly samples.

Field experiment (Paper IV)

The pumping time to the add-on filter simulated actual inflow to soil beds in practice, with peaks in the morning, at noon and in the evening (see Figure 10). Each sampling event was performed at different time points between 8:30 and 18:00 during the day. Conventional parameters such as pH, turbidity, conductivity, oxygen and redox were measured every two weeks to observe the change over time, instead of occasional snapshots of the situation.

Analysis of micropollutants (Papers I-IV)

Method validation results for the GC-MS analysis of AHTN, BPA, BPH, HCB, HHCB, MK, MTBT, MX, NBBS, OC, TBEP, TBP, TCEP, TDCPP, TMDD and TPP, including recovery experiments, linearity and precision, can be found in Blum et al. (2017). Laboratory blanks were extracted in parallel to the samples. For APAP, CBZ, CF, DEET, DF, FOSA, IP, LAT, LOT, MEP, OP, PFBS, PFOS, PP and SL, method performance parameters for the compounds analysed by UHPLC-QTOF also included recovery efficiencies, linearity, method precision, method detection (MDLs) and quantification limits (MQLs). For details, see Gros et al. (2017) and Paper III. 4. RESULTS AND DISCUSSION

4.1. Removal of conventional contaminants (Papers I, II and IV)

4.1.1. Dissolved organic carbon and chemical oxygen demand

The efficiency of the sorbents in removing organic carbon was investigated by measuring the DOC and COD concentrations in influent and effluent. Dissolved organic carbon removal was evaluated in the screening and long-term column experiment (Figure 11). The feedwater was taken from different sources for the two experiments, so the DOC concentration of the original feedwater in experiments 1 and 2 was quite different (10 mg L-1 and 68 ± 16 mg L-1), respectively. After spiking with the case chemicals, the DOC concentration increased to 440 and 145 ± 26 mg L-1, respectively. The additional DOC came from the solvent used in the MP spiking solution.

21 Wen Zhang TRITA-ABE-DLT-1821

Figure 11. A) Mean concentration and removal efficiency of dissolved organic carbon (DOC) by the 10 sorbents tested in the screening experiment (Paper I). B) Removal efficiency of DOC in the long-term experiment (Paper II).

The GAC sorbent achieved the best removal of DOC in both experiments, with an average removal efficiency above 95%. The next best sorbent was Xylit, which showed intermediate performance (52%) in the screening experiment and good DOC removal (89 ± 3%) in the long-term experiment. Lignite removed only 32% of DOC in the screening experiment (Figure 11A). However, better removal was observed in the long-term experiment before week 5 (79 ± 3%), after which the removal efficiency declined to around 31% between week 8 and week 12. Another organic sorbent, Zugol®, showed the lowest removal efficiency of all the sorbents tested (3.0% removal in the screening experiment). The lower DOC removal by Xylit and lignite in the screening experiment may be due competitive adsorption between DOC and MPs, since these two sorbents achieved high removal efficiency for MPs (see section 4.2.3). The poor removal of DOC by Zugol® may also be due to the sorbent releasing constituent carbon into the water.

22 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Figure 12. Concentration of chemical oxygen demand (COD) in influent and effluent of the soil bed and in effluent from the granulated activated carbon (GAC) and xyloid lignite (Xylit) filters (Paper IV).

The effluent concentrations of DOC were quite similar for all inorganic sorbents (230-312 mg L-1), corresponding to 32-49% removal efficiency (screening experiment). Sand was given extra attention in the study, since it represents the treatment capacity of STS. The lowest removal of DOC by sand was in week 4, and then the removal efficiency increased from week 5 (Figure 11B). That increase was probably due to growth of biofilm, which helped with biodegradation and/or adsorption of organic matter.

In the field study, the COD concentration was measured to evaluate the capacity of the soil bed and the two add-on filters to reduce the concentration of oxygen-demanding organic matter in the water. Chemical rather than biological oxygen demand (BOD) was chosen, because of its faster method of determination. The influent COD concentration to the soil bed was 458 ± 63 mg L-1 (Figure 12). The soil bed achieved 94 ± 3% removal, resulting in an average effluent concentration of 32 ± 15 mg L-1. The add-on GAC filter improved the COD removal by 5%, which was a significant increase (ANOVA, p<0.05, R2 = 0.59). No significant difference in COD removal from soil bed effluent was observed for the Xylit filter (ANOVA, p = 0.90).

4.1.2. Ammonium-nitrogen

In the screening experiment (Paper I), NH4-N removal by the 10 candidate sorbents was evaluated. The feedwater contained low -1 ® levels of NH4-N (3.8 mg L on average). Filtra N achieved the best removal (90%) among all sorbents (Figure 13). The reason for this excellent removal is that Filtra® N consists of zeolite, which is well known to remove ammonium from wastewater by ion exchange (Rahmani & Mahvi, 2006). Lignite, Polonite® and Filtralite® P had the lowest removal efficiency (50%, 71% and 74%

23 Wen Zhang TRITA-ABE-DLT-1821

Figure 13. Mean concentration and removal efficiency of

ammonium-nitrogen (NH4-N) by the 10 sorbents tested in the screening experiment (Paper I).

Figure 14. Concentration of ammonium-nitrogen (NH4-N) in influent and effluent of the soil bed and in effluent from the granulated activated carbon (GAC) and xyloid lignite (Xylit) filters (Paper IV).

respectively), because nitrification is pH-sensitive and the optimal pH value is between 7.5 and 8 (Metcalf & Eddy, 2003). The pH of the lignite was 4, while Polonite® and Filtralite® P had pH over 10, which can inhibit the nitrification process. Other sorbents had pH values between 7 and 9 and achieved an average removal rate of around 87%.

In the field study, the concentration of NH4-N in influent to the soil bed was 76 ± 6.3 mg L-1 (Figure 14) (Paper IV). An average removal efficiency of 85.5 ± 7 % was achieved by the soil bed. In

addition, lower NH4-N concentration was observed during summer in the effluent of the soil bed and the add-on filters, an effect probably associated with increased outdoor and wastewater

temperature and better removal of NH4-N by nitrification and

24 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

denitrification. The add-on filters did not improve the removal of

NH4-N, as no significant differences were observed between the soil bed effluent and the effluent from the GAC and Xylit filters (ANOVA, p=0.79).

4.1.3. Phosphorus

The inorganic sorbents Sorbulite®, Polonite® and Filtralite® P were

more effective in removing Ptot than other sorbents tested in the screening experiment (Paper I). The concentration of Ptot in the influent was 4.17 mg L-1. Sorbulite® and Polonite®, which contain 19% and 25% calcium, respectively (Nilsson et al., 2013), achieved the best removal rates (above 95%) (Figure 15A), as they were able to provide sufficient Ca2+ and OH- for the formation of calcium ® phosphate (Ca-PO4) precipitates (Zuo et al., 2015). Filtralite P has a high content of calcium and magnesium (Ádám et al., 2006) and ® it achieved 90% removal of Ptot. The two GACs, Filtrasorb 300 and EnvirocarbTM 207EA, achieved a 49% and 66% reduction in

Ptot, respectively, while Ptot was poorly removed by Xylit and sand (22% and 33%, respectively) (Figure 15A). Zugol® and lignite

removed a large proportion of Ptot (94% and 89%, respectively). Zugol® contains 20% calcium and lignite contains 14% iron (Gamage, 2017), which is beneficial for phosphorus precipitation.

The GAC sorbents, Xylit, Filtra® N, and sand were not able to precipitate phosphorus, so removal was probably due to adsorption or biological processes. To confirm the estimation of the removal mechanisms, Visual MINTEQ was used to calculate the saturation index and possible species formed in the wastewater in the continuous study.

The concentration of Ptot in the influent to the filters was around -1 7.4 ± 1.2 mg L in the long-term experiment (Paper II). The Ptot removal by GAC fluctuated widely, with an average removal efficiency of 12 ± 27%. The added Polonite® filter improved phosphorus removal greatly, while a dual filter (GAC + Polonite®)

achieved the best removal of Ptot among all three sorbents tested in this experiment (96 ± 2%) (Figure 15B). According to the saturation index calculated by Visual MINTEQ (Table S7 in Paper II), all phosphate-related minerals were undersaturated, so phosphorus was unable to precipitate in the GAC columns. Thus the removal of phosphorus was most likely by adsorption in the first four to six weeks and by biological processes after the formation of biofilm. Around 82% of the phosphorus in - ® wastewater may form CaPO4 with the calcium in Polonite and may precipitate as Ca3(PO4)2, Ca4H(PO4)3·3H2O and hydroxyapatite (Ca5(PO4)3OH) (Table S7 in Paper II) (Gustafsson et al., 2009).

The good removal achieved by lignite in the longterm experiment can be explained by the content of aluminium and iron in lignite

25 Wen Zhang TRITA-ABE-DLT-1821

Figure 15. A) Mean concentration and removal efficiency of

total phosphorus (Ptot) in the screening experiment (Paper I). B) Removal efficiency of Ptot in the long-term experiment (Paper II).

resulting in precipitation of AlPO4·1.5H2O, strengite ((FePO4·2H2O) and variscite (AlPO4·2H2O) (Table S7, Paper II). However, in the long-term experiment, similarly to DOC removal,

the highest removal efficiency of Ptot by lignite was observed in the first five weeks (85 ± 3%) and then removal decreased sharply (Figure 15B). Desorption may have caused the negative removal after week 9. The assumption can be made that lignite was exhausted after 5 weeks.

Sand and Xylit achieved similar removal of Ptot, with average removal efficiency of 16 ± 12% and 14 ± 15%, respectively. Sand contains small amounts of calcium, iron and aluminumthat may be

released into the water, leading to the formation of e.g. Ca3(PO4)2 , FePO4 andAlPO4, which may explain the better removal of Ptot in the first two weeks. The removal efficiency by sand stabilised at 14 ± 2 % after 5 weeks, i.e. after formation of bacterial organic matter was observed in the effluent. The removal mechanism probably shifted at that point from adsorption to biological processes (Campos et al., 2002)

26 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Figure 16. Concentration of total phosphorus (Ptot) in influent and effluent from the soil bed and in effluent from the granulated activated carbon (GAC) and xyloid lignite (Xylit) filters (Paper IV).

The influent concentration of Ptot to the soil bed in the field treatment system was 8.4 ± 0.7 mg L-1. The soil bed achieved average removal efficiency of 34 ± 6%, resulting in a concentration of about 5.5 ± 0.5 mg L-1 in the effluent (Figure 16). This value exceeds the suggested high protection threshold (1 mg -1 L ) for OSSFs set by SEPA (see Table 1). The improvement in Ptot removal achieved by the added GAC and Xylit filters was not significant (ANOVA, p = 0.80).

Based on the conventional pollutant removal results from the field study, the soil bed-based sewage treatment system at Ekerö is in good condition except for phosphorus, for which more advanced removal technology needs to be applied to reach the normal protection level set by SEPA (2006).

4.2. Removal of micropollutants

4.2.1. Comparison of sorbent performance in micropollutant removal (Papers I and II)

Principal component analysis was carried out to visualise and explore the variation in MP removal between different sorbents. Two main principal components (PC1 and PC2) were extracted and explained 50% and 24% of the variation, respectively (Figure 17). As shown in the score plot, the two GACs and lignite grouped together along PC2, while all five inorganic sorbents, plus the organic sorbents Xylit and Zugol®, grouped along PC1, demonstrating different removal behaviour for these different groups of sorbents.

In general, the organic sorbents achieved much better removal than the inorganic sorbents in the screening experiment. Removal efficiency varied considerably between MPs, depending on the

27 Wen Zhang TRITA-ABE-DLT-1821

Figure 17. A) Score plot and B) loading plot of micropollutant removal efficiency achieved by the five organic and five inorganic sorbents tested in the screening experiment (Paper I).

sorbent (Figure 18). The coal-based organic sorbents were significantly better at removing MPs than the natural fibre and inorganic sorbents, while Filtralite® P showed significantly lower removal efficiency than all other sorbents (ANOVA, p<0.05). The two GACs obtained the best removal of MPs, with an average removal efficiency of 97% for Filtrasorb® 300 and 95% for EnvirocarbTM 207EA. The removal efficiency of individual MPs by the GACs ranged from 88% to 100% except for α-TPA, was only 78% removed by EnvirocarbTM 207EA. Lignite and Xylit achieved good removal for most MPs, with average removal efficiency of 90% and 92%, respectively, except for DF, BAM and OC, which were moderately well removed. Compared with the coal-based sorbents, natural wood fibre (Zugol®) was less efficient in reducing MP levels (on average 74%), while the inorganic sorbents were even less efficient, with average overall removal efficiencies ranging from 53% to 73%.

Similar results were observed in the long-term column experiment (Paper II), where the GAC column achieved the highest removal, with an average removal efficiency of 97 ± 6% (Table 4). Over 90% removal was achieved for 29 of the 31 target MPs (Figure 19). Xylit showed great potential for removal of MPs, with average removal efficiency of 80 ± 28%, while it achieved more than 90% removal for 17 MPs. Unlike in the screening experiment, lignite was less efficient in removal of multiple MPs. The average removal efficiency of lignite was 68 ± 29 %, with 16 of the 31 MPs removed to more than 80%, while seven of the remaining MPs showed less than 50% removal (Figure 19, Table 4).

Among the inorganic sorbents, the removal of MPs by sand was significantly lower than that of other sorbents (ANOVA, p<0.05). Most MPs were poorly removed by sand, with 21 out of the 31 chemicals showing less than 50% removal, resulting in average removal efficiency of 43 ± 30 % (Figure 19, Table 4). The added Polonite® filter did not further improve the removal of other MPs,

28 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Figure 18. Average removal efficiency (%) of individual micropollutants (MPs) by the 10 sorbents tested in the screening experiment (Paper I). For MP abbreviations, see Table 3.

Table 4. Number of target micropollutants (MPs, n = 31) removed by the five different sorbents tested in the long-term column experiment, in total and in different removal efficiency classes ® Removal efficiency Lignite Xylit GAC GAC+Polonite Sand

> 90% 9 17 29 27 4 80% - 90% 7 5 1 1 1 50% - 80% 8 6 1 2 5 < 50% 7 3 0 1 21

Average removal efficiency (%) 68 ± 29 80 ± 28 97 ± 6 94 ± 12 43 ± 30

Figure 19. Twelve-week mean removal efficiency (n = 5) of the 31 target micropollutants by lignite, Xylit, GAC, GAC+Polonite® and sand in the long- term column experiment (Paper II).

29 Wen Zhang TRITA-ABE-DLT-1821

except OC which was improved by 8-24%. No significant difference was found between the GAC and the dual layer system (GAC+Polonite®(GAC+P)) (ANOVA, p>0.05). The average removal efficiency of the dual layer system was 94 ± 12%. However, the concentrations of MPs in the water treated by the GAC filter before entering the Polonite® filter were extremely low.

4.2.2. Removal of target micropollutants (Papers I and II)

In the screening experiment, the 19 MPs were removed to different levels by the sorbents (see Figure 17). According to the PCA loading plot (Figure 17B), the chemicals distributed along PC1 in the upper right corner, which included the biocides (HCB and TCS), organophosphorus flame retardants (TBP, TDCPP, TPP), a fragrance (HHCB), and a pesticide (TBT), were well removed by all sorbents. The average removal efficiency was 97%, which was significantly better than for the other target MPs (ANOVA, p<0.05). A few MPs located close to the intersection point, including a rubber additive (MTBT) and some pharmaceuticals (CBZ, OZP, MTP, LST), were better removed by GACs and lignite, with average removal efficiency of around 96%. Xylit and Zugol removed 85% of the MPs, while the inorganic sorbents could only remove 48%. A few compounds (OC, α-TPA, CF, TMDD, BAM and DF) lay outside the two groups of compounds which were more or less inefficiently removed by the inorganic sorbents. For instance, CF was poorly removed by Polonite® and Filtralite® P (15% and 0%, respectively), while DF and BAM (dichlorobenzamide) were significantly (ANOVA, p<0.05) less well removed by all inorganic sorbents, with an average removal efficiency of 4%.

In the long-term column experiment (Paper II), the MPs fell into three groups: i) MPs that were well removed by all organic sorbents, ii) MPs that were less efficiently removed by lignite and Xylit than by GAC, and iii) MPs what were poorly removed by lignite and Xylit. The first group included fragrances (HHCB, MX, MK, AHTN), a biocide (HCB), organophosphates (TBP, TBEP, TDCPP, TPP), pharmaceuticals (LAT, OP), a rubber additive (MTBT), PFASs (FOSA), an ultraviolet stabiliser (BPH) and a preservative (PP) (Figure 19) with average removal efficiency of 98 ± 2%, 90 ± 5% and 95 ± 4% by GAC, lignite and Xylit, respectively. The MPs that were less efficiently removed by lignite and Xylit included a plasticiser (NBBS), pharmaceuticals (APAP, CF, CBZ, LOT, MEP, IP), a pesticide (DEET), an ultraviolet stabiliser (OC), an organophosphate (TCEP) and a plasticiser (BPA). The GAC sorbent maintained high removal rates of these chemicals (95 ± 9 %), while Xylit and lignite achieved an average removal efficiency of 86 ± 9 % and 60 ± 13 %, respectively. The MPs that were poorly removed by lignite and Xylit included a surfactant (TMDD), a pharmaceutical (DF), PFASs (PFBS and PFOS) and an artificial sweetener (SL), with removal efficiency of 24-35% for lignite and 9-55% for Xylit. In fact, SL and PFBS were

30 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

found to be negatively removed, i.e. higher concentration found in the effluent than in the feedwater (Figure 19).

The performance of different sorbents in the removal of MPs was quite varied. The better performance of coal-based organic sorbents compared with natural fibre and inorganic materials could be explained by the pore structures and the surface chemistry of the sorbents (Putra et al., 2009). The varied removal efficiency for different types of MPs can due to the physicochemical properties of the chemical, such as hydrophobicity and solubility. The removal mechanisms are discussed in the following sections.

4.2.3. Removal of micropollutants over time (Paper II)

During the 12-week column experiment, the average removal efficiency of the 31 MPs remained comparatively steady for the GAC (96-98%) and GAC+P (91-97%) columns (Figure 20). Greater fluctuation in removal efficiency was observed for Xylit (73-85 %) and lignite (60-76 %). Sand had the most fluctuating removal curve, with the removal efficiency varying between 28% to 61%.

Slightly increased removal of MPs was observed for all sorbents in the first two to four weeks of operation, while a downward trend in DOC removal was observed in the GAC, lignite, Xylit and sand filters (see Figure 11B). The feedwater had a high DOC concentration (68 mg L-1 on average), which may lead to competitive adsorption between DOC and MPs (Mailler et al., 2015). Another possible reason for the increased removal of MPs in the first week is increased hydraulic retention time (HRT) (cf. Ejhed et al., 2018; Kim et al., 2016). Unsaturated flow was applied in the column experiment to mimic the flow of OSSFs, so the HRT in the five columns varied from 5 to 20 minutes during the first week. It then increased to 15-20 minutes in week 2 (Table S4, Paper II).

Figure 20. Average removal efficiency (%) of the 31 target micropollutants (MPs) achieved during the 12-week column experiment by granulated activated carbon (GAC), GAC + Polonite®, lignite, xyloid lignite (Xylit) and sand (Paper II)

31 Wen Zhang TRITA-ABE-DLT-1821

The average removal rate of MPs by lignite started to decrease after week 4. A similar reduction in removal of DOC and total phosphorus by lignite was observed at week 5 (Figure 11B, Figure 15B). The downward trend was caused by the reduced removal of APAP, DEET, LOT, OC and PFOS (a reduction of 6%, 7%, 19%, 15% and 66%, respectively) and negative removal of DF, IP and PFBS. The concentrations of DF, IP and PFBS found in the lignite effluent water samples eventually became higher than the inlet concentration, indicating that lignite probably exceeded its sorption capacity for these chemicals and released those adsorbed earlier (McCleaf et al., 2017).

4.3. Sorbent characterisation (Paper II)

4.3.1. Surface charge on sorbents and chemicals

During the long-term column experiment, the average pH value of

the spiked feed water was 7.5 ± 0.2. The pHpzc of GAC (10.35) and Polonite® (>12) was much higher than the pH of the feed water (Table 5), indicating an overall positive surface charge on their

surfaces. In contrast, the pHpzc for Xylit, lignite and sand, which was 5.93, 2.55 and 5.85, respectively, was lower than the feed water pH, indicating overall negatively charged surfaces. Some target compounds will appear as positively or negatively charged ions depending on the pH in the solution. The acid dissociation constant (pKa) was used to determine the charge of the compounds. For information on the pKa value of the 31 chemicals screened in this thesis, see Table 3.

4.3.2. Characterisation of surface functional groups on virgin and used sorbents

The peaks found in the FTIR spectra for virgin lignite and Xylit were quite similar and indicated the presence of several SFGs (Figure 21, Table 6). Similar SFGs have been identified in different types of GAC in previous studies (Gong et al., 2016; Putra et al., 2009; Seredych et al., 2008). For instance, the C=O stretching peak at 1700 cm-1 identified for a wood origin activated carbon by Seredych et al. (2008) was found at 1723 cm-1for lignite and 1707 cm-1 for Xylit in this thesis and the intense peaks near 1508-1609 cm-1 for Xylit and at 1624 cm-1 for lignite were attributed to C=C aromatic stretching (Putra et al., 2009). Overall, the FTIR spectra for the virgin lignite and Xylit indicated the presence of hydroxyl and carbonyl groups, which can potentially bind MPs in wastewater to their surfaces.

Table 5. Point of zero charge (pHpzc) of the five sorbents tested in the long-term column experiment. GAC = granulated activated carbon, Xylit = xyloid lignite ® GAC Xylit Lignite Sand Polonite

pHpzc 10.35 5.93 2.55 5.85 >12* ® *Initial and final pH did not meet for pHpzc of Polonite

32 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Table 6. Fourier transform infrared (FTIR) band position and corresponding surface functional groups for unused lignite, Xylit, sand and Polonite® ® Lignite Xylit Sand Polonite Corresponding functional groups N N 422 N SiH₂ rocking N N 465 476 Si-O vibration N N 536 N Si-Cl asym and sym strs, SiCl₃ 543 552 N N C-C=O in-plane deformation in aldehyde 602 609 N N C=C-H bending, terminal acetylene groups N N 648 649 Si-H rocking 663 661 N N C=C-H bending, terminal acetylene groups

702 695 705/726 711 C-H out-of -plan bending, cis -CH=CH-

N N N 796 Si-O stretching of silica and quartz N N N 876 C-H out-of -plane bending N N N 966 C-H out-of plane bending N N 1012/1030 N Si-O-C asymmetric stretch, Si-O-CH₃ N 1028 N N C-H in plan bending N 1052 N N C-O stretch in alcohol N N 1067/1086 N Si-O-C asymmetric stretch 1097/1129 1115 N N C-O-C symmetric stretch in ester C-O-C asymmetric stretch in ethers

N N 1112/1127 1100 O-Si-O vibration 1156 1162 N N C-O stretch in carboxylic acids, alcohol or ester N 1225/1265 N N C-O and C-H stretch 1387 1367/1418 1350/1384 1425 C-H rocking, aldehydes 1624 1508/1609 N N C=C aromatic stretch N N 1630 1630 H-O-H bending 1723 1707 N N C=O stretch, carboxylic acid

2860/2928 2853/2925 2858/2926 2855/2926 C-H stretch 3405 3388 3436 3430 O-H stretch, water of crystallization 3566/3619 N N N O-H stretch N: The peak was not presented in the FTIR spectra curve. (Socrates, 2001)

Different surface functional groups were observed for virgin sand and Polonite®. These were mostly attributable to silicon-containing groups. For example, peaks were detected near 1100, 650 and 470 cm-1 and are indicative of O-Si-O vibration, Si-H rocking and Si-O vibration, respectively (Atalay et al., 2001). However, several functional groups that exist on organic sorbent surfaces were lacking (e.g. C=O and C-O in carboxylic acid; C-O in alcohol and ester), suggesting that inorganic sorbents are less efficient in removal of MPs. Gustafsson et al. (2008) and Putra et al. (2009) identified similar functional groups on the surfaces of other mineral-based filter materials.

Compared with the virgin samples, in used lignite the intensity of a few peaks changed markedly. For example, the peaks close to 1100 cm-1 and 602 and 663 cm-1 were much weaker or even disappeared

33 Wen Zhang TRITA-ABE-DLT-1821

Figure 21. Fourier transform infrared (FTIR) spectra of virgin and used sorbents (ww = (wastewater): A) lignite, B) Xylit, C) sand and D) Polonite®.

in the used samples. The spectra of the used Xylit, sand and Polonite® resembled those for the virgin samples, but the intensity and position of peaks changed. Real wastewater was used in the experiment and reactions such as adsorption, degradation, oxidation and precipitation may have affected the results, which might be the reason for the spectra changes.

4.4. Possible removal mechanism of micropollutants (Papers I-III)

4.4.1. Impact of pore size and surface area on compound removal

The average pore size of the two GACs tested, Filtrasorb® 300 and EnvirocarbTM 207EA (2.7 nm and 2.2 nm, respectively), is much smaller than of lignite, Xylit and Zugol® (14.7, 16.7 and 26.4, respectively) (see Table 2). The smaller pore size of the GACs lies within the beneficial range for adsorption of MPs. Besides, the GACs have a significantly higher fraction of pore volume per mass unit (0.519 cm3 g-1 for Filtrasorb® 300 and 0.507 cm3 g-1 for EnvirocarbTM 207EA; Table 2), which is of critical importance for sorption.

A strong correlation was found between removal of MPs by organic sorbents and pore size with coefficient of determination (R2) = 0.8, while the coefficient of determination between removal of MPs by inorganic sorbents and pore size was very low (R2 = 0.1) (Figure 22A). As described in section 4.3.2, the functional groups on the surface differ between organic and inorganic sorbents, and thus the main removal mechanisms of the MPs also differs. Therefore, in the analysis in this thesis, the impact of pore size on the removal efficiency was considered separately for organic and inorganic sorbents.

34 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Figure 22. Relationship between average removal efficiency of the target micropollutants (MPs) (n =19) and A) sorbent pore size and B) specific surface area of the inorganic and organic sorbents tested (n =10) (Paper I).

With regard to the correlation between specific surface area (SSA) and removal of MPs from wastewater, a slight tendency was observed for increasing removal efficiency with increasing SSA for the organic sorbents (Figure 22B).

The GACs Filtrasorb® 300 and EnvirocarbTM 207EA had the largest SSA (780 m2 g-1 and 910 m2 g-1, respectively) and also showed the highest removal efficiencies. The impact of SSA on removal of MPs by other sorbents (for which SSA ranged from 0.5 m2 g-1 to 20 m2 g-1) was minor and inconsistent. For instance, Xylit had a smaller SSA (2.5 m2 g-1) but achieved higher removal efficiency than lignite (SSA 5.3 m2 g-1). For the inorganic sorbents, Filtra® N and Sorbulite®, which had SSA values of around 20 m2 g- 1, showed similar removal efficiency to Polonite® and sand (SSA 3.8 m2 g-1 and 0.6 m2 g-1, respectively). This can be attributed to the maximum adsorption capacity not being reached in this short-term experiment, so the sorbent SSA was not a strong factor affecting

35 Wen Zhang TRITA-ABE-DLT-1821

the removal of MPs. Statistical analysis confirmed that the correlation between removal efficiency and specific surface area

was not significant (Spearman’s rank correlation Rorganic=0.6, Rinorganic=0.1, p>0.05). However, the lifetime of sorbents can be influenced by the total surface area, since large surface area provides more functional groups in the interactions with MPs, which may yield a larger capacity and longer lifetime of the sorbent.

4.4.2. Hydrophobic effects

In both laboratory-scale column experiments, the hydrophobic effect played an important role in the removal of MPs. As shown in Figure 17B (PCA plot), seven MPs (HCB, TCS, TBP, TDCPP, TPP, HHCB and TBT) displayed an average removal efficiency of 97% for all sorbents. As mentioned in section 4.2.2, 15 MPs (HHCB, MX, MK, AHTN, HCB, TBP, TBEP, TDCPP, TPP, LAT, OP, MTBT, FOSA, BPH and PP) were well removed by GAC, lignite and Xylit, with an average removal efficiency of 98 ± 2%, 90 ± 5% and 95 ± 4%, respectively. The reason for the high removal efficiency was most likely the hydrophobicity of these chemicals, as all except LAT (lamotrigine) are relatively

hydrophobic (log Kow ≥3), which increases the possibility of adsorption. Although the hydrophobicity of LAT is low (log Kow = 1), the removal was still most likely due to adsorption, since this compound is quite persistent and poorly biodegradable (Bollmann et al., 2016).

The log Kow value of the MPs less efficiently removed (NBBS, APAP, CF, CBZ, LOT, MEP, IP, DEET, OC, TCEP and BPA)

by Xylit and lignite was in general slightly lower (1.6 ≤ log Kow ≤ 2.6) than that of the chemicals mentioned in the previous paragraph, except for the pharmaceuticals LOT (losartan) and IP

(ibuprofen) (log Kow = 4.01 and 3.79, respectively).

Regarding sand, a few MPs were well removed in the long-term experiment, including APAP, PP, MX, CF and HCB with a removal efficiency ranging from 88% to 100%. Three of the five well-removed MPs (PP, MX and HCB) are relatively hydrophobic

compounds, with log Kow > 3.

Table 7. Pearson correlation coefficient (R) between octanol-water partition coefficient (log Kow) and removal efficiency of micropollutants by granulated activated carbon (GAC), xyloid lignite (Xylit), lignite, sand and GAC+Polonite® (n = 31)

GAC Xylit Lignite Sand GAC+Polonite®

log Kow -0.267 0.132 0.41* 0.095 -0.03 * Correlation significant at p<0.05.

36 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Based on the observations, hydrophobic compounds adsorb more easily to filter material compared with hydrophilic compounds, which can be explained by the hydrophobic effect (Blum, 2018). Pearson correlation coefficient was therefore calculated to test the

correlation between the removal efficiency and log Kow of the MPs for GAC, Xylit, lignite, sand and GAC+P. The results are summarised in Table 7.

A moderate correlation (R = 0.41) at the 0.05 significant level was found when using lignite for MPs removal. The insignificant correlation found for GAC, GAC+P and Xylit was possibly due to the variations in removal efficiency values were in a very small range, namely 29, 27 and 17 out of 31 MPs were more than 90% removed by GAC and Xylit, respectively (Table 4).

4.4.3. Impact of surface functional groups

The presence of surface functional groups and the surface charge on the sorbent are important factors affecting the adsorption capacity and the removal mechanism of MPs (Vargas et al., 2011). The PFOSs and the pharmaceuticals DF and IP are usually negatively charged in wastewater (Anumol et al., 2015; Ávila et al., 2017; Zeng, 2015), but were found to be efficiently removed by the positively charged GAC, with average removal efficiency over 99%, while the removal was less efficient by the negatively charged Xylit and lignite (23-80%). The removal of DF and IP by lignite was between 60% and 100% in the first four weeks, but negative removal was observed for week 8 samples, indicating desorption, while some MPs still showed high removal rates. This can possibly be explained by the negatively charged lignite surface releasing negatively charged IP and DF from its surface more readily. Low adsorption of DF due to its negative charge has been found in other studies (Ejhed et al., 2018; Malmborg & Magnér, 2015).

Most of the target chemicals appeared to have neutral charge in wastewater (n = 14). The correlations between pKa of the ionisable MPs and their removal efficiency (n = 17) by different sorbents were not significant (Pearson correlation, p>0.05) in this thesis.

As mentioned in section 4.3.2, SFGs identified in GACs by several previous studies were also found in Xylit and lignite, but better removal of MPs was achieved by GAC. It can therefore be concluded that the large specific surface area of GAC and the varied distribution of macropores and micropores contribute to the high sorption rate for MPs on this material (Swapna Priya & Radha, 2017; Brigante et al., 2011; Li et al., 2002).

37 Wen Zhang TRITA-ABE-DLT-1821

4.4.4. Relationship between removal efficiency and physicochemical properties of micropollutants (Paper III)

Micropollutants with a wide range of physicochemical properties should be selected in evaluating the removal of MPs by different sorbents. In Paper III, Pearson correlation was calculated between 11 physicochemical properties and the removal efficiency of 54 MPs. The physicochemical properties were selected based on their potential to affect the sorption behaviour of MPs and based on the literature (Svahn & Björklund, 2015). They included molecular weight (MW), acid dissociation constant (pKa), Octanol-water

partition coefficient (log Kow), water solubility (Sw), distribution coefficient between octanol and water at pH 5.5 (log D (pH 5.5)) and at pH 7.4 (log D (pH 7.4)), solvent-accessible surface area (S), apolar surface area (SA), polar surface area (SP), the ratio between apolar and polar surface area (SA/SP) and number of aromatic bonds (AB). The physicochemical properties and behaviour of PFASs (Rostvall et al., 2018) were very different from those of the other MPs, and therefore they were evaluated separately.

In agreement with previous findings obtained for GAC and anion exchange resins (Appleman et al., 2014; Du et al., 2014; Eschauzier et al., 2012; McCleaf et al., 2017; Zaggia et al., 2016), MW and S were found to be strongly positively correlated with removal of PFASs for Xylit, lignite and sand (Table 8), which can be explained by the removal efficiency increasing with increasing

perfluorocarbon chain length. log Kow, log D (pH 5.5) and log D (pH 7.4) were also strongly positively correlated with the removal efficiencies of PFASs (p<0.05 for lignite, Xylit and sand). These physicochemical properties relate to the polarity of the molecule and PFASs with longer chain length are more hydrophobic, indicating that longer chain length results in better removal of PFASs. The negative correlation found for GAC was possibly due to variations in removal efficiency values in a very small range close to 100%, which created artificially strong negative correlations.

In contrast to the results obtained for PFASs, the molecular

weight, log Kow and log D (pH 5.5) did not show any significant effect on the removal efficiency of other MPs (p>0.05), suggesting that hydrophobicity alone is not the dominant attribute of MPs governing their sorption. In previous studies by Rattier et al. (2013, 2014), similar behaviour was observed, i.e. no correlation was found between these physicochemical properties and adsorption of MPs by anthracite and GAC.

SA, SP and SA/SP were positively correlated with removal of MPs by lignite and Xylit (Paper III). This is in agreement with results obtained in an earlier study, where the SA/SP ratio was found to positively affect retention of selected pharmaceuticals in sediments and sewage sludge (Svahn & Björklund, 2015). However, further

38 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Table 8. Pearson correlation coefficient (R value) for selected physicochemical properties (see text for abbreviations) and removal efficiency of all micropollutants (MPs) excluding per- and polyfluoroalkyl substances (PFASs)) (n =42) and of PFASs (n =12) using lignite, Xylit, GAC, GAC+P and sand columns All MPs excluding PFASs PFASs Lignite Xylit GAC+P GAC Sand Lignite Xylit GAC+P GAC Sand log MW 0.08 -0.03 -0.08 0.00 -0.26 0.87 0.88 -0.40 -0.60 0.85 Pka 0.12 0.31 -0.14 0.15 0.39 0.41 0.40 0.05 0.10 0.01 log Kow 0.28 0.05 -0.08 -0.12 -0.06 0.82 0.87 -0.49 -0.67 0.80 log (Sw+10) -0.11 0.01 0.03 0.05 0.17 0.08 0.01 0.32 0.25 0.26 log D pH5.5 0.19 0.06 0.02 0.02 -0.01 0.92 0.93 -0.35 -0.50 0.70 log D pH7.4 0.39 0.29 -0.03 0.04 0.21 0.91 0.92 -0.37 -0.52 0.70 log S 0.33 0.21 0.02 0.16 -0.06 0.87 0.90 -0.45 -0.64 0.87 log (SA+10) 0.43 0.35 -0.01 0.13 0.01 -0.24 -0.28 0.25 0.30 -0.03 log (SP+10) -0.37 -0.37 0.09 -0.02 -0.32 -0.01 -0.08 0.28 0.33 0.03 log (SA/SP+10) 0.38 0.33 -0.02 0.06 0.21 -0.33 -0.37 0.23 0.28 -0.06 log (AB+10) 0.18 0.07 -0.22 -0.09 -0.14 NC NC NC NC NC The significance of the correlation is shown with 95% confidence interval. No colour = p>0.05; light grey = p<0.05; dark grey = p<0.01; black = p<0.001. NC= not calculable

studies are needed to determine how SA/SP contributes to enhancing the removal efficiency. In the long-term column

experiment, the pKa and the MPs removal was not correlated when the 17 case chemicals were analysed (14 MPs were non-ionisable). However, when a larger group of MPs (n = 42) was employed in

the analysis, a correlation was found for pKa with Xylit and sand (0.31 and 0.39, respectively). A few other weaker correlations were found for log S and log D pH 7.4 with lignite and log (SP+10) with sand (Table 8), which need to be confirmed in further studies.

4.4.5. Impact of biofilm

Biofilm was possibly formed in GAC, lignite and sand columns after 30, 36 and 18 days of operation, as bacteria-derived organic matter was found in the effluent water and the colour of the effluent water changed over time. The removal of several MPs in the GAC, Xylit, lignite and sand columns increased at week 8 and week 12 compared with week 4 (Figure 20).

The average rate of removal of MPs in the sand column increased greatly at week 8, then decreased at week 12 (Figure 20). This large variation was due to the removal of BPH, MTBT, NBBS and TCEP, the concentration of which decreased on average from 66% to -30%, so they were excluded from the assessment of biofilm impacts. A few MPs (BPA, MK, TBP, TBEP TDCPP, TPP and TMDD) were found to be better removed at week 8 and week 12, with an average increase of 38%. The best improvement was observed for TBEP, TBP and TMDD (73%, 59% and 43%, respectively), while smaller improvements (15-28%) were observed for BPA, MK, TDCPP and TPP removal in the sand column.

In addition, the removal of TBP, TCEP, TDCPP, CBZ and OP by lignite increased by 12%, 23%, 8%, 12% and 13%, respectively, and the removal efficiency of TBP, BPH, HCB and OP slightly increased (by 2-4%) in the Xylit and GAC columns. The

39 Wen Zhang TRITA-ABE-DLT-1821

improvement achieved in the Xylit, GAC and lignite columns was not as significant as that observed in the sand column.

The improved removal of the MPs mentioned above may be due to adsorption onto the developing biofilm, since most of the

chemicals concerned are quite hydrophobic (log Kow > 3.1) and thus may be removed more easily by adsorption. Apart from adsorption onto the biofilm, it has been found that recalcitrant MPs in active sludge treatment, such as DF, can be biodegraded by biofilm reactors (slow sand filtration) (Escol Casas & Bester, 2015). In a biochar and sand filter study, ranitidine and caffeine have been found to be removed through adsorption, biodegradation and a combination of these in the biofilm active system (Dalahmeh et al., 2018).

The Polonite® filter assessed in Paper II received treated water from the GAC columns, and thus the concentrations of most MPs and of organic matter were quite low. Besides, the pH in the Polonite® columns was very high, which inhibits the formation of biofilm.

4.5. The add-on filter technology in the field

In the field study, wastewater samples were collected on six occasions over 24 weeks for analysis of MPs. In total, 86 compounds were identified in the influent wastewater samples. Of these, 58 compounds were further assessed in Paper IV, while 28 of the compounds with low detection frequency (n ≤ 1) in the influent samples were excluded from the presentation of results. The 58 MPs comprised artificial sweeteners (n = 2), organophosphates (n = 7), parabens (n = 3), personal care products (n = 7), pesticides (n = 2), perfluoroalkyl substances (PFAS) (n = 3), pharmaceuticals (n = 27), a plasticiser, a bisphenol, a rubber additive, stimulants (n = 3) and a surfactant. The category, concentration and the detection frequency are presented in Table S1 in Paper IV.

The MPs were detected over a wide range of concentrations (Table S1 in Paper IV). The highest concentration detected was 110 μg L-1 for APAP, which is an analgesic pharmaceutical commonly used as a pain reliever. In addition to APAP, six other MPs were found to be present at an average concentration above 5000 ng L-1, namely CF, metformin, nicotine, IP, SL and naproxen (Table S1 in Paper IV). The concentration for 50% of the detected MPs ranged from 59 ng L-1 to 1268 ng L-1. Fourteen compounds were present in concentrations lower than 50 ng L-1. The lowest detected concentration was 1.3 ng L-1 (ranitidine). Overall, the concentrations of MPs present in the on-site wastewater were within the range reported for conventional wastewater treatment facilities in previous studies (Luo et al., 2014).

40 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

Table 9. Number of micropollutants (MPs) detected in different concentration ranges and the median concentration in different components of the field treatment system studied in Paper IV. GAC = granulated activated carbon, Xylit = xyloid lignite Influent Soil bed GAC Xylit

>5000 7 0 0 0

Concentration 500 - 5000 15 15 0 6 ranges -1 (ng L ) 50 - 500 22 17 3 10

< 50 14 26 55 42 Median concentration (ng·L-1) 210 65 0.04 7.6

Low removal efficiencies of MPs have been reported previously for on-site sewage treatment systems using a soil bed (Blum et al., 2017; Gros et al., 2017). In this thesis, the median concentration of the 58 MPs decreased from 210 to 65 ng L-1 after the treatment by the soil bed system (Table 9). The concentrations of 26 MPs were found to be lower than 50 ng L-1. However, there were still 15 MPs present at concentrations over 500 ng L-1 in the treated water from the soil bed. These MPs comprised one artificial sweetener (sucralose), three organophosphates (TCIPP, TCEP and TBEP), three personal care products (BPH, OC and HHCB), four pharmaceuticals (metformin, fluconazole, metoprolol, IP), one plasticiser (NBBS), one rubber additive (MTBT), one stimulant (CF) and one surfactant (TMDD).

After enhanced treatment by the add-on filter columns containing GAC or Xylit, the median concentration of the MPs was reduced to 0.04 and 7.6 ng L-1, respectively (Figure 23). Among these, 42 MPs reached a concentration lower than 50 ng L-1 in the effluent of the Xylit filter, while the GAC filter achieved even better removal, as 55 MPs were found to have a concentration lower than 50 ng L-1. SL and TMDD were found in high concentrations in the Xylit effluent (3170 and 2220 ng L-1, respectively), while naproxen, CF, metformin and TCIPP were found in concentrations between 560 and 1180 ng L-1.

The average removal efficiency of the soil bed was 49 ± 56%. A total of 17 MPs were found to be over 90% removed, while 25 MPs were less than 50% removed (Figure 23A). Higher concentrations of some MPs was detected in the soil bed effluent, leading to negative removal values. One of the reasons for the negative removal is that the effluent water samples did not correspond directly to the influent water. Another explanation could be desorption of the MPs from the soil bed. After the added GAC filter, the average removal efficiency for MPs increased to 98 ± 6%, although a removal efficiency lower than 90% was found for a few MPs (Figure 23A). Xylit achieved very good removal,

41 Wen Zhang TRITA-ABE-DLT-1821

Figure 23. A) Average removal efficiencies of micropollutants (MPs) by the soil bed and enhanced removal efficiency after the granulated activated carbon (GAC) and xyloid lignite (Xylit) filter (outliers lower than -150% not shown). B) Removal of MPs over time by the soil bed and the GAC and Xylit filters (outliers lower than -40% not shown). Range (vertical lines) and 25% and 75% percentile values (boxes) are shown (Paper IV).

with an average removal efficiency of 87 ± 28%, while 75% of the studied MPs showed removal efficiency of over 90%. The add-on filters (GAC and Xylit) significantly improved the removal of MPs (n = 58) from wastewater treated by the soil bed (ANOVA, p<0.001), but no significant differences were found between GAC and Xylit (p = 0.273).

The median removal in the soil bed at the first two sampling events (April and May) was 48% and 43%, respectively (Figure 23B). After June, the median removal efficiency then increased to above 62%. The variation in removal in the add-on filters was small over the whole experimental period. The better removal achieved in the soil bed in summer months is due to the increasing ambient temperature, which contributes to the development and function of biofilm in soil, thus improving the capacity for biodegradation and adsorption of MPs by/on biofilms (Sbardella et al., 2018).

The mechanisms by which MPs are removed in a soil bed are complex and can be due to biodegradation in the biofilm and/or adsorption to sand particles. The physicochemical properties of the sand used in this thesis were not favourable for adsorption of MPs (see Table 2 and Table 6). Most MPs are poorly degradable and cannot be removed in conventional on-site sewage treatment systems (Ejhed et al., 2012).

A few MPs were found to be well removed in the soil bed-based treatment system used in Paper IV, for instance pharmaceuticals (such as APAP, citalopram and naproxen), parabens (such as propylparaben) and ultraviolet filter chemicals (such as

oxybenzone). These MPs are relatively hydrophobic (log Kow ≥ 3), and therefore the removal was most likely due to adsorption (Blum

42 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

et al., 2017; Stevens-Garmon et al., 2011). However, a few MPs

with low log Kow, such as caffeine (log Kow = -0.07) and nicotine (log Kow = 1.0), were also efficiently removed in the soil bed, displayed an average removal efficiency of over 95%. Their removal was probably due to biodegradation.

Some MPs were less well removed by Xylit than by GAC, including acesulfame, SL, TCIPP, TCEP, DEET, lidocaine, fluconazole, hydrochlorothiazide, DF and TMDD. Apart from DF and TMDD, these MPs are highly water-soluble, which may decrease their sorption potential. The surface characteristics of Xylit can also explain the less efficient removal than observed for GAC. The average pore size on the surface of Xylit particles is 16.7 nm (Table 2), indicating that the proportion of micropores is smaller than in GAC. Besides, the specific surface area of Xylit (2.5 m2 g-1) is much lower than that of GAC (950 m2 g-1), and therefore less surface area is available for adsorption (Zhang et al., 2018).

The total water volume treated by the add-on filters was about 7450 L per column, resulting in a water load/sorbent ratio of around 0.99 L g-1 for GAC and 1.55 L g-1 for Xylit. The removal efficiency of MPs by the add-on filters was promising after six months of operation and no breakthrough was observed. The add- on filters were actually operated for another two months after the last sampling occasion (August 2017) and regular wastewater quality parameters were checked over time. The results showed that the values remained at the same levels as reported for the earlier samples, indicating high potential longevity of the sorbents.

Technical development of add-on filter units should therefore commence and the types of GAC and Xylit tested in this thesis can be recommended as suitable sorbents. Under field conditions, the GAC material tested achieved overall better removal of MPs than the Xylit. However, Xylit is already being used in on-site sewage treatment systems to achieve both macro- and micropollutant removal. This soft material can be packed much more densely than was done in this thesis, which would probably increase its performance in removal of MPs. Thus further research is needed on these materials and their use in add-on filter units for on-site wastewater treatment.

5. CONCLUSION AND FUTURE PERSPECTIVES

The thesis examined the possibility of add-on technology for OSSFs to improve removal of MPs, possibly together with macro- pollutants and nutrients. A screening experiment identified suitable candidate sorbents for different treatment purposes. A following long-term column experiment studied the mechanism for removal of MPs, while a dual-layer system was tested for its performance in removal of both MPs and phosphorus. An add-on filter unit for OSSFs was then tested in the field as a practical solution. Based on

43 Wen Zhang TRITA-ABE-DLT-1821

the results presented in this thesis, the following conclusions can be drawn:

 The organic sorbents tested achieved good and consistent removal of organic carbon (measured as DOC or COD) and a large range of MPs, while the inorganic sorbents had on average 20% lower MPs removal capacity in the screening experiment. In all experiments performed, GAC was superior in MP removal. The removal of wastewater

compounds such as NH4-N and total P exhibited a different pattern, with the best performance achieved by the inorganic materials Filtralite® P, lignite and Polonite®.

However, these materials were unable to reduce NH4-N concentrations in wastewater to a level that meets Swedish statutory effluent limits. It can thus be concluded that the organic sorbents GAC and Xylit can be used in OSSFs for efficient removal of MPs, but efficient treatment of nitrogen and phosphorus has to be introduced before or after the MP filter.  The chemical and physical properties of the selected organic and inorganic sorbents varied greatly, which had significant effects on their ability to remove the target substances from wastewater. Large specific surface area and a varied distribution of macropores and micropores were important for the removal of MPs, as demonstrated by GAC. However, unprocessed carbonised material, represented by Xylit, also showed good performance. Sorbents with pH values which favour growth of bacteria that can form biofilm in the filters explained the improved removal of a few MPs by sand, lignite and Xylit. It can be concluded that many specific properties of sorbents and their ability to develop biofilm are of overall importance for the removal of MPs and that a wide range of organic contaminants cannot be removed to over 90% by a single sorbent.  Charge, molecular weight, solvent-accessible area, apolar and polar surface area and hydrophobicity of the MPs influenced their ability to be removed by the sorbents tested. Negatively charged MPs adsorbed to lignite were found to be easily released from its negatively charged surface over time. For PFASs, molecular weight and solvent-accessible area were found to be strongly positively correlated with removal by lignite, Xylit and sand. For MPs other than PFASs, apolar and polar surface area and the ratio between these were positively correlated with removal of MPs by lignite and Xylit. Relatively hydrophobic (log

Kow ≥3) MPs were well removed by all organic sorbents. However, hydrophobicity alone could not explain the adsorption of MPs. It can be concluded that the chemical and physical properties of MPs must be considered when a

44 An add-on filter technique to improve micropollutant removal and water quality in on-site sewage treatment facilities

certain or a set of sorbents is being selected for an add-on filter for OSSFs.  The studied add-on filter to a soil bed-based system showed good treatment capacity and was operated successfully. The soil bed itself removed MPs but, to achieve efficient treatment, additional techniques must be applied. Therefore, a replaceable add-on unit after the system is recommended and should preferably consist of an organic sorbent such as GAC or Xylit.

Emissions of MPs from OFFSs constitute a diffuse source of pollution and these persistent contaminants end up in the groundwater or reach surface water. There are many problems connected with small-scale wastewater treatment systems beside the emerging problem with MPs, such as insufficient P removal. Treatment plants can be costly to construct, operate and control for householders. Additional costs and management will arise if rules are introduced on removing MPs from sewage. Small-scale sewage treatment technology must therefore be carefully developed so it can be adapted to the conditions prevailing in the countryside. For example, any add-on filter should be replaceable, since the sorbent can be saturated and/or start to desorb the captured contaminants. More studies are needed to investigate the long-term performance of filter media and how they can be safely handled when spent.

This thesis identifed two candidate sorbents to be used in add-on filter systems, GAC and Xylit, of which the latter is studied for the first time as a sorbent for removal of MPs. The types of GAC tested showed superior performance, as expected from results in other studies. Xylit also achieved good removal efficiency and performed well in the field test. This material is already in use as a bio-carrier in package treatment plants, and hence has an additional function to remove MPs. The advantage of this material is that no costly processing is needed and that it is considered a by- product after coal mining. In this thesis, Xylit was not packed to the same density as GAC, which caused much lower surface area. Future investigations should test more compacted Xylit, which is possible due to the good hydraulic performance of this material. The possibility to reuse this material after every treatment cycle should also be investigated. For instance, heating it to temperatures around 300 oC could eliminate or immobilise the sorbed organic contaminants, after which the material could be reused at least one more time in a filter unit before final destruction.

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