Coagulation Process Characteristics and Pollutant Removal from Urban Runoff

LICENTIATE T H E SIS

Department of Civil, Environmental and Natural Resources Engineering Division of Architecture and Water Fredrik Nyström Coagulation Process Characteristics and Pollutant Nyström Coagulation ProcessFredrik Characteristics Removal from Urban Runoff

ISSN 1402-1757 Coagulation Process Characteristics and ISBN 978-91-7790-322-2 (print) ISBN 978-91-7790-323-9 (pdf) Pollutant Removal from Urban Runoff Luleå University of Technology 2019

M Z +  energy

Fredrik Nyström

Urban Water Engineering

Coagulation Process Characteristics and Pollutant Removal from Urban Runoff

Fredrik Nyström Luleå, 2019

Urban Water Engineering Division of Architecture and Water Department of Civil, Environmental and Natural Resources Engineering Luleå University of Technology

Printed by Luleå University of Technology, Graphic Production 2019 ISSN 1402-1757 ISBN 978-91-7790-322-2 (print) ISBN 978-91-7790-323-9 (pdf) Luleå 2019 www.ltu.se

Preface

The research of this thesis was carried out in the Urban Water Research Group at the department of Civil, Environmental and Natural Resources Engineering at the Luleå University of Technology. Financial support for the projects was provided by the Swe- dish Research Council Formas (project numbers 2015-00120, 2016-20075 and 2016- 01447), from Sweden’s Innvoation Agency Vinnova (UDI project GrönNano) and from the research cluster Stormwater & Sewers. The papers are based on laboratory work for which I received tremendous practical help from Kerstin Nordqvist. She made sure the experiments were running smoothly and as efficiently as possible and always made sure we had time for fika. For that help I am thoroughly grateful. I am thankful for all the help Gunnar Smith and Thomas Gustafsson from Kemira has provided for this thesis, including the jar-testing equipment, the coagulants and discussions. I would also like to extend my thanks to Liang Yu at the division for Chemical Technology, Lueå University of Technology, for all the assistance I got with the practical issues concerning the zeta-potential measurements. My deepest gratitude goes out to my academic supervisors Maria Viklander, Annelie Hedström and Inga Herrmann. Without their guidance this thesis would never have come to fruition. Although I have been barraged with an endless amount of comments during my experiments and in the drafting process of my papers, I have enjoyed the experience throughout. Thank you Maria, for the exuberant joy you are spreading and always giving me confidence in my scientific endeavors. Thank you Annelie for always challenging me to think one step further, and question things. And thank you for the end of the day office visits to your PhD students with a big smile on your face. Thank you Inga for unhurried and easy-going attitude, you seem to always see the positive in things and always find some encouraging words to say. Thank you everyone in our research group for the interesting scientific discussions. Thank you Heléne for always helping me with my tricky chemistry questions. Thank you Jiri, for the interesting and engaging discussions once a year during the retreat days. Thank you and apologies to my office friend Youen for being the first one to face the flurry of questions I might have regarding whatnot. A hearty thank you to all the colleagues and friends in the research group. You all help to make the days more fun and interesting. Thank you to my family down south, my father and my brother. Mikael and Johanna, I am sorry I could not be a good host when you were visiting. I was busy writing this thesis. Thank you Katharina for your patience and understanding throughout the writing of this thesis. Fredrik Nyström Luleå, March 2019

Abstract

Different stormwater control measures can be implemented in order to mitigate the effects of polluted stormwater flows into receiving water bodies. The treatment function of stormwater control measures is commonly based on the removal of particles by sedimentation, thereby also removing pollutants associated with particles. In recent years, more attention has been given to characterizing and understanding different particle size fractions and their associations with pollutants commonly found in stormwater. It has been shown that the smaller particles are very important pollutant transporters, and should be considered when designing and implementing stormwater control measures. How- ever, the settling velocities for smaller sized particles are very low, and may not be effectively removed using existing stormwater control measures. One treatment process in widespread use in water and wastewater treatment with a proven ability to enhance sedimentation is coagulation/flocculation; there are very few accounts of its use in a stormwater context, however. My aim in this thesis was to investigate the treatability of stormwater with a coagulation/flocculation process. This research included determining the operating conditions, the dominating coagulation mechanism(s), and the removal efficiencies for stormwater-related pollutants. The objectives of this thesis were achieved by laboratory experiments treating a snowmelt mixture and road runoff in a jar-testing procedure. An initial screening of primary coagulants and flocculant aids was conducted using an urban snowmelt mixture. Five of the chemicals were then selected for an extended testing regime in order to determine the necessary operating conditions for reaching maximum turbidity as measured in the pH, conductivity, alkalinity, and zeta potential of the tested doses for each coagulant. Criteria used for chemical selection included high turbidity reduction, low dose requirement and low pH/alkalinity impacts. An evaluation of the performance of the coagulation/flocculation process with regard to pollutant removal was conducted on a snowmelt mixture and also on collected road runoff. For the urban snowmelt mixture, charge reversal was observed at positive particle surface charge, measured as the zeta potential, indicating that the dominant coagulation mechanism was charge neutralization for all coagulants tested. For both the snowmelt mixture and the road runoff particles (measured as turbidity and total suspended solids), total organic carbon, total metals, and hydrocarbons were removed by >90%. For the snowmelt mixture and road runoff dissolved copper was removed by on average 40%, additionally for the road runoff, chromium and lead was removed by 40% on average. Dissolved zinc and nickel increased by up 300% using metal salt coagulants, presumably due to pH decrease that led to higher mobility. Chitosan reduced dissolved copper by 70% and dissolved zinc by 50%, but slightly less efficient for particle-associated pollutants (88% removal). Changes in the particle size distribution after coagulation/flocculation as compared to the sedimentation control indicated an effect on the size fraction corresponding to smaller particles.

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Sammanfattning

För att minska dagvattenpåverkan i recipienter kan dagvattenreningstekniker implemen- teras. Många av de existerande dagvattenreningsanläggningarna baseras på partikulär av- skiljning av föroreningar genom sedimenteringsprocesser. På senare tid har flera studier fokuserat på att karaktärisera och förstå hur olika dagvattenföroreningar är fördelade i olika partikelfraktioner. Det har påvisats att små partiklar är viktiga transportörer av för- oreningar, och bör avskiljas om fullgod dagvattenrening skall uppnås. Dock, så är sedi- menteringshastigheten för små partiklar alltför låg, och riskerar att inte avskiljas alls i existerande dagvattenreningsanläggningar. En behandlingsprocess som är vanlig inom dricks- vattenberedning och avloppsvattenbehandling är kemisk fällning. Kemisk fällning har en destabiliserande effekt på de små partiklarna och kan förbättra avskiljningen av dem. Ke- misk fällning är inte en vanlig reningsteknik i dagvattensammanhang, endast ett fåtal ve- tenskapliga studier finns publicerade på ämnet. Målet med den här uppsatsen är att un- dersöka hur processbaserad kemisk fällning kan användas för att rena förorenat dagvatten. Specifikt är syftena att undersöka de operativa betingelser som måste uppfyllas för att kemisk fällning skall fungera, vilken som är den dominerande fällningsmekanismen, samt vilka avskiljningseffekter som kan urskönjas för de vanligaste dagvattenföroreningarna. Målen uppfylldes genom laboratorietester där både en blandning av urban snö och väg- dagvatten behandlades i en flockulator i bänkskala. En screening-studie av olika fällningskemikalier genomfördes på snösmältmixen och utifrån resultaten så valdes fem fällningskemikalier för att vidare bestämma processparametrar såsom pH, konduktivitet, alkalinitet och zeta-potential. Urvalskriterierna var hög turbi- ditetsreduktion, låg dosering, och liten påverkan på pH och alkalinitet. Vidare så utvär- derades avskiljningseffekten för dagvattenföroreningar på både snösmältmixen och väg- dagvattnet. I snösmältmixen så observerades ytladdningsreversion hos partiklarna (mätt som zeta-potential), vilket är förknippat med laddningsneutralisering som fällningsmekanism. Ladd- ningsreversionen inträffade för alla fällningskemikalier som utvärderades. Kemisk fällning avskilde partiklar (mätt som turbiditet och suspenderat material), totalhalt organiskt kol, totalhalt metaller samt kolväten med över 90%. Vid kemisk fällning av både snösmält- mixen och vägdagvattnet avskildes löst koppar med 40% i genomsnitt, för vägdagvattnet avskildes även löst krom och bly med 40%. Dock ökade halten löst zink och nickel vid kemisk fällning med upp till 300% vid användningen av metallsaltskoagulanter, förmod- ligen på grund av ett lägre pH som ökade mobiliteten hos zink och nickel. Chitosan avskilde löst koppar till 70% och löst zink med 50%, men uppvisade något lägre avskilj- ningseffekt (88%) för partikelbundna förorening. Förändringar i partikelstorleksfördel- ningen visade på en destabiliserande effekt hos de allra minsta partiklarna som inte påvi- sades i sedimentationskontrollen.

Table of Contents

Preface ...... i Abstract ...... iii Sammanfattning ...... v List of papers ...... ix 1. Introduction ...... 1 1.1. Aim and research objectives ...... 2 1.2. Thesis structure ...... 2 2. Background ...... 5 2.1. Urban runoff quality and treatment ...... 5 2.2. Coagulation and flocculation ...... 6 2.2.1. Terminology ...... 6 2.2.2. Colloidal stability ...... 6 2.2.3. Coagulation mechanisms ...... 7 2.2.4. Flocculation ...... 7 2.3. Coagulation & flocculation processes for urban runoff ...... 8 3. Materials and methods ...... 13 3.1. Study Design ...... 13 3.2. Flocculation and sedimentation ...... 13 3.3. Experimental set-up ...... 13 3.4. Chemicals used as primary coagulants or flocculant aids ...... 16 3.5. Chemical and physical analyses of the water samples ...... 16 3.5.1. Determination of pollutant concentrations ...... 17 3.6. Description of the stormwater used for jar-testing ...... 18 3.6.1. Urban snowmelt mixture ...... 19 3.6.2. Road runoff ...... 19 3.6.3. Water quality parameters ...... 20 3.7. Statistical analyses ...... 22 4. Results ...... 25 4.1. Differentiating characteristics between snowmelt mixture and road runoff ...... 25 4.2. Screening of primary coagulants and flocculant aids ...... 26 4.3. Coagulation process characteristics ...... 26 4.4. Treatment performance ...... 29

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4.5. Particle content ...... 29 4.6. Pollutants ...... 30 4.7. Identification of important parameters in the coagulation process ...... 34 5. Discussion ...... 35 5.1. Flocculation and sedimentation ...... 35 5.2. Coagulation process characteristics ...... 35 5.3. Particulate removal as a result of destabilization by coagulation ...... 36 5.4. The effect of a coagulation process on the dissolved metal fraction ...... 37 5.5. Removal of organic compounds ...... 39 5.6. Coagulation process control parameters ...... 40 6. Conclusions ...... 43 References ...... 45 Appendices: Papers I-III

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List of papers

Paper I Nyström, F., Nordqvist, K., Herrmann, I., Hedström, A. and Viklander, M. Laboratory evaluation of coagulants for treatment of urban snowmelt. (Submitted to Chemosphere)

Paper II Nyström, F., Nordqvist, K., Herrmann, I., Hedström, A. and Viklander, M. Removal of metals and hydrocarbons from urban snowmelt using coagulation and flocculation (Submitted to Water Research)

Paper III Nyström, F., Nordqvist, K., Herrmann, I., Hedström, A. and Viklander, M. Treatment of road runoff using coagulation/flocculation and sedimentation. Water Science & Technology 79(3),527-534

Contribution to the above papers:

Publication process Data Development Research study Data Data Manuscript Paper processing and Responding to of idea design collection interpretation preparation for analysis reviewers submission Shared Shared I Contributed Responsible Responsible Responsible NA responsibility Responsibility Shared Shared Shared Shared II Responsible Responsible NA responsibility responsibility Responsibility Responsibility Shared Shared Shared III Responsible Responsible Responsible Responsible responsibility responsibility Responsibility

Responsible – Developed, consulted (where needed) and implemented a plan for completion of the task. Shared responsibility – Made essential contributions to the completion of the task in collaboration with other members of the research team Contributed – Worked on some aspects of completing the task No contribution – With valid reason, did not contribute to completing the task (e.g., joining the research project after task completion) NA – not applicable

1. Introduction

Stormwater flows such as road runoff or urban snowmelt contain numerous pollutant constituents (Westerlund et al., 2003; Westerlund and Viklander, 2011) that may contribute to the degradation of the receiving aquatic ecosystems. The sources of these pollutants are often anthropogenic and the result of traffic and wear and tear to urban infrastructure (Barbosa et al., 2012). Many pollutants have been shown to be strongly associated with particles, and the smaller particles in particular are regarded as significant pollutant transporters (Langmuir, 1997; McKenzie et al., 2008; Charters et al., 2015), even though larger particles are also impacting the pollutant transport (Borris et al., 2016). This can pose a problem for existing stormwater treatment infrastructure as these systems most often are designed to use sedimentation as their primary treatment process. The dimin- ishing returns of sedimentation increase as the particle sizes become smaller due to the effects of Stoke’s law and Brownian motion. Therefore, the capability of stormwater treatment systems to efficiently remove the smaller particle fractions becomes important in heavily polluted areas or sensitive receiving waters (Clark and Pitt, 2012; Trenouth and Gharabaghi, 2015). Coagulation and flocculation is an established water treatment technique that is commonly used for both drinking water production and wastewater treatment. The coagulation/flocculation process has been used relatively little in a stormwater treatment context, however. A coagulation/flocculation process can neutralize the negatively-charged electrostatic field found around naturally occurring suspended particles. This field pre- vents small particles from naturally aggregating and settling out of suspension. By chemically introducing counter-ions with a positive charge, this field can be compressed or neutralized, thereby enhancing both the aggregation and sedimentation (Bratby, 2016). There are a few studies in the scientific literature on coagulation/flocculation systems for stormwater treatment (Heinzmann, 1994; Harper et al., 1999; Trejo-Gaytan et al., 2006; Kang et al., 2007). In general, the results from these studies were promising, indicating that coagulation may be a viable and efficient treatment process for polluted stormwater. However, further studies and more information are needed regarding the process characteristics, the coagulation mechanisms, and the removal rates for a wider array of pollutants in order to understand the capabilities and limitations of the coagulation process technique in stormwater treatment.

1.1. Aim and research objectives The main aim in this thesis was to contribute to and expand the existing knowledge of the coagulation/flocculation process under optimal operating conditions as applied to stormwater. Particular attention was given to the characteristics of the coagulation process and its performance in removing stormwater pollutants.

The research objectives of this thesis were: 1. To determine the process conditions under which successful coagulation of an urban snowmelt mixture and road runoff occur, in particular dose requirements and pH 2. To perform an initial jar-testing screening evaluating a panel of common coagulants and flocculant aids with regard to turbidity reduction 3. To discern the underlying dominating coagulation mechanism and its operational implications 4. To evaluate the removal efficiency of the coagulation/flocculation process for suspended solids, dissolved and particulate metals as well as organic compounds 5. To elucidate important parameters governing successful coagulation using linear regression

1.2. Thesis structure The foundation for this thesis is three appended papers that investigate the effects of a coagulation treatment process on a snowmelt mixture and road runoff. Paper I mainly deals with coagulant selection and the process characteristics that govern a successful process. Paper II presents the treatment performance of the process with regard to stormwater pollutants and their removal. The studies in Papers I and II were performed using a snowmelt mixture as the stormwater sample. Paper III follows up on Paper II, but instead of using a snowmelt mixture, the coagulation treatment process is evaluated on road runoff generated from rain events. The relationship between the papers are illustrated in the synthesis figure (Figure 1), which highlights the most important aspects of a coagulation/flocculation process as applied to stormwater. This thesis is structured into six chapters. Chapter 1 briefly presents the research topic and the major objectives of the thesis. Chapter 2 provides background on the theory behind the coagulation process, and also a research overview of how it has been previously applied to treat stormwater. Chapter 3 describes the experimental setup of the jar- testing, the overall study design and the analyses that were performed. Chapter 4 presents some synthesized results from the papers focusing on the process characteristics and treatment performance. The results are later discussed in detail in Chapter 5. Finally, Chapter 6 presents the main conclusions of this thesis. All papers are appended at the end of the thesis.

Process characteristics and pollutant removal in a stormwater coagulation/flocculation treatment

Paper II Paper I Dose requirements Hydrocarbons pH and alkalinitty Particles Coagulation selection Coagulation Metals mechanism

Urban snowmelt mixture Paper III Road runoff

Figure 1 Synthesis of papers included in the thesis. Yellow circle contains parameters related to the coagulation process characteristics, red circle contains important stormwater pollutants, and green circle are the different stormwater used in the thesis.

2. Background

2.1. Urban runoff quality and treatment If pollutants found in urban runoff are not removed, they may contribute to the degradation of water bodies. In Europe, the status of water bodies is evaluated on various criteria, as mandated in the Water Framework Directive (European Parliament, 2000). Particular attention is focused on the compounds listed as priority substances, which include several metals and PAHs. In stormwater studies, typical metals of priority include cadmium, chromium, copper, nickel, lead and zinc (Eriksson et al., 2007). In the U.S., stormwater pollution discharge is regulated under the Clean Water Act via the National Pollution Discharge Elimination System (EPA, 2010) program, which issues permits reg- ulating discharge in order to minimize the effect on receiving water bodies. Early studies on the quality of urban runoff indicated associations between pollutants and particles (suspended solids), both in urban snow melt (Oliver et al., 1974; Viklander, 1999) and urban runoff (Herrmann, 1981; Hoffman et al., 1985). The pollutants in question are associated with different particle size fractions (Bryan Ellis and Revitt, 1982; Sansalone and Buchberger, 1997a), which has been examined in detail in several studies in which particle size distribution was analyzed in relation to pollutant concentrations, with the finding that as particle sizes decrease, the concentration of metals increases (Sansalone and Buchberger, 1997b; Lin et al., 2005; Zanders, 2005; Herngren et al., 2006; Li et al., 2006). Furthermore, some metals were enriched up to 100 times in the very fine particulate fraction (<0.5 um) (McKenzie et al., 2008). One explanation for this may be that the surface area exposed by particles increases as their size decreases, thereby offering more potential binding sites for pollutants (Langmuir, 1997). In addition, small particle size fractions are correlated with higher metal bioavailability and toxicity (Preciado and Li, 2006; Kayhanian et al., 2008). In studies in which street sediments were sampled, the association of pollutants with different size ranges seemed to vary on a site-by-site basis (German and Svensson, 2002; Lau and Stenstrom, 2005), and it has been demonstrated that during a rain event, coarser particles may break up into smaller constituents (Borris et al., 2016). There are multiple studies examining the efficiency of various stormwater control measures (SCMs) to remove small particles, with varying reports on performance. In conveyance SCMs, filter strips efficiently remove particles larger than 8 μm in diameter (Han et al., 2005), and grass swales particles larger than 13.5 μm (Bäckström, 2002). In the effluent from detention ponds, particles <10 μm were found (Pettersson, 1998), and efficient removal of particles >30 μm (Xanthopoulos and Augustin, 1992). Settling tanks may reduce the particle fraction between 2 μm and 10 μm by up to 45%, while efficiently removing all particles >40 μm (Li et al., 2006). Most likely, the removal efficiency varies based on site characteristics and SCM design. However, there is a consensus that smaller particles are removed less efficiently than coarser particles. Furthermore, it is likely that in retention facilities, the settling velocity or sedimentation rate of the smaller particles cannot be modeled using Stoke’s Law. Instead, the effects of electrostatic repulsion and 5 external environmental perturbation reduce the effectiveness of sedimentation in these systems (Gromaire-Mertz et al., 1999; Bäckström, 2002). Several studies have highlighted the importance of treatment systems that target small particle fractions in order to achieve high effluent quality (Sansalone and Buchberger, 1997b; Gromaire-Mertz et al., 1999; Meland, 2016). There are many different technologies that may efficiently remove small particle fractions and dissolved pollutants, e.g. chemically active filtration or coagulation, but they have yet to be thoroughly investigated (Clark and Pitt, 2012). 2.2. Coagulation and flocculation 2.2.1. Terminology Although coagulation and flocculation are defined as separate physicochemical processes, they are often mistakenly used interchangeably. The definition of coagulation, according to Bratby (2016), is “the process whereby destabilization of a given suspension or solution is effected. That is, the function of coagulation is to overcome those factors which pro- mote the stability of a given system.” The same author defines flocculation as “the process whereby destabilized particles, or particles formed as a result of destabilization, are induced to come together, make contact and thereby form large(r) agglomerates.” Both of these processes may happen naturally or be induced by external forces. A substance that induces coagulation is termed a primary coagulant, and a substance that speeds up the flocculation process, or increases floc stability, is termed a flocculant aid. Thus, it is the way the substance is used that defines the name: for example, a cationic polymer will both have a destabilization effect and bring aggregate particles together through bridging, and can therefore be used as either a primary coagulant or a flocculant aid. 2.2.2. Colloidal stability Colloid is the chemical term referring to a system of insoluble particles dispersed in a medium. The specific term for solids dispersed in a liquid is a sol. Different scientific fields use different cut-offs for sizes in their definition of colloidal particles; the Interna- tional Union of Pure and Applied Chemistry defines them as particles with a dimension <1 μm (IUPAC, 2007). There are several interactions between the particles that contribute to their stability in the water medium, but the dominant one is electrostatic repulsion (Mosley et al., 2003). In natural systems, such as stormwater, colloidal particles are negatively charged due to processes such as adsorption of molecules with negatively charged functional groups (e.g., carboxyl and phenolic-OH) (Hunter and Liss, 1979). The DLVO theory, named after its researchers (Verwey and Overbeek, 1946; Derjaguin and Landau, 1993), provides the prevailing explanation for the interaction between charged particles in a liquid medium. The theory assumes that two forces acting upon particles are independent of each other, and the total interaction energy is the sum of the two forces. There is an attractive force, van der Waals attraction, which is strong at very short distances and weak at long distances. The other force is the electrostatic force arising from an ionic double layer around the particle (the surface charge ions rand the charged

6 particles it attracts through Coulomb forces). The electrostatic force is stronger at a distance, and weaker than the van der Waals force at short distances. This forms an energy barrier that must be surpassed in order for particles to aggregate. The surface charge of the particles might therefore be an indication of the colloidal stability of a dispersion. However, it is not feasible to measure the surface charge directly; instead, another electric potential, the zeta potential, can be calculated using electropho- retic mobility measurements. The zeta potential is defined as the electric potential at the interface of the double layer and the bulk fluid (Hunter, 1981) 2.2.3. Coagulation mechanisms Although the first descriptions of the phenomenon date back almost 4,000 years, the chemical theory behind coagulation was formulated step by step in the 20th century via studies of colloid solutions and aqueous solutions of metal salts. Stumm and Morgan (1962) realized that pH was an important factor affecting coagulation, and observed a reversal of the effect for certain value ranges of coagulant concentration, colloid concentration and pH (Stumm and O’Melia, 1968). The authors conceptualized different zones, in some of which coagulation occurred. In a suspension with a sufficient colloid concentration, a stoichiometric reaction will occur between the negatively charged colloid particles and the coagulant species, leading to charge neutralization—i.e., coagulation—in which the cationic metal hydrolysis species neutralize the negatively charged colloids (Van Benschoten and Edzwald, 1990). The addition of more coagulant will result in charge reversal due to the formation of positively charged particles; in other words, charge reversal effectively nullifies the destabilization previously attained. Oversaturation of coagulant past the solubility level leads to the formation of insoluble amorphous metal hydroxides. However, the solubility levels increase with decreasing pH, so pH adjustment may be needed to form the metal hydroxide precipitates. This precipitation leads to coagulation by sweep flocs, like a blanket weighing down the particles in the suspension. In natural waters, the occurring coagulation processes are even more complex, with multiple different competing reactions, multiple hydrolysis products, complexation, and other ligand reactions interacting (Shin et al., 2008). In addition to the two coagulation mechanisms (charge neutralization through adsorption of hydrolysis species and sweep flocculation) mentioned above, there are two additional destabilization mechanisms. The distance at which the electrostatic forces between particles act can be reduced by increasing the ionic strength of the liquid medium, achieving coagulation by double-layer compression (Edzwald et al., 1974). This naturally occurring phenomenon happens when rivers meet the ocean. The final mechanism is creating inter- particle bridges using long polymer chains. 2.2.4. Flocculation Flocculation is the subsequent process, in which destabilized particles aggregate to form larger particles termed flocs. Typically, the flocculation process is subdivided into two steps: transport and attachment (Thomas et al., 1999). The transport step determines the collision frequency, and is impacted by the kinetic energy available; examples include

7 perikinetic flocculation (collisions caused by Brownian motion), orthokinetic flocculation (velocity gradients from mixing), and differential sedimentation. The attachment step determines the collision efficiency, and is affected by the destabilization processes previously outlined in the coagulation section. The Smoluchowski model (Smoluchowski, 1918) is the classical model describing the flocculation process, and it is still the foundation for current models. The model assumes that collision frequency and collision efficiency are independent, although later research has shown that this might not actually be the case (Lawler, 1993). Control of the flocculation process is achieved by adjusting factors such as mixing energy or sedimentation time, and enhanced by the addition of flocculant aids such as polymers. 2.3. Coagulation & flocculation processes for urban runoff The scholarly body of literature on coagulation as a general water and wastewater treatment process is extensive, and dates back to the beginning of the 20th century. However, there is little published data1 in peer-reviewed academic literature on the use of coagulation processes for treating stormwater from a storm sewer system, despite the fact that the concept of using coagulants and/or polymers to increase the settling velocity of stormwater particles is not new, with some of the earliest ideas and attempts dating back 40 years. In the 1980s, Bennet et al. (1981) conducted limited laboratory-scale treatment tests using both snowmelt and stormwater runoff, evaluating sedimentation, coagulation/sedimentation and filtration, with regard to reduction of turbidity, chemical oxygen demand (COD), and suspended solids. The coagulants and optimal dose used were as follows: alum (50 mg/L), ferric chloride (50 mg/L), and lime (100 mg/L). The authors concluded that for their evaluation criteria both coagulation/sedimentation and filtration perform much better than sedimentation alone. Tapp and Barfield (1986) attempted to improve the model predictability of particle settling in sedimentation ponds by examining natural flocculation with and without floccu- lating agents. The authors tried to improve old plug flow settling models by considering flocculation equations consisting of particle aggregation and particle breakup terms; the aggregation term included a variable describing collision efficiency. A number of pilot-scale coagulation experiments have been conducted. In an effort to mitigate deterioration of Berlin’s water bodies, Heinzmann (1994) built a pilot plant to treat stormwater after an initial laboratory selection of coagulant. The plant achieved a greater than 75% reduction of turbidity and filterable solids, with inflow concentrations of up to 140 FTU (formazin turbidity units) and 50 mg/L, respectively. The authors only reported the performance of the coagulant with the highest reduction, a product com- bining poly-aluminum chloride with a cationic polymer. They did not present reduction

1 A search on Scopus using the term coagulation AND (“stormwater” OR “runoff”) yields 135 document hits, fewer than 20 of which concern coagulation of urban runoff. The majority of the documents concern treatment of CSO, implications of diluted wastewater, rainwater-induced leachate from industries, tropical storms affecting raw water sources, or other phenomena related to coagulation in natural waters (e.g., lake remediation). 8 rates for metals, but stated that lead and copper were removed to a high degree, and zinc to a very low degree. A shorter economic analysis included investment costs, amortiza- tion, and capital costs, and estimated a 10%–40% higher cost than for the use of a settling tank. Bernard et al. (1995) set up a small stormwater treatment plant operating with a treatment scheme consisting of coagulation/flocculation followed by flotation. The plant treated runoff from the Chelles River catchment area in France during seven rain events, with land use split between residential and industrial. Fixed concentrations of the primary coagulant, alum (50 and 100 mg/L), and anionic flocculant aids (1 and 2 mg/L) were used, and the pilot system was evaluated in terms of the residual concentrations of suspended matter, COD, and total hydrocarbons. Reductions of up to 90% for suspended matter, 82% for COD, and 95% for total hydrocarbons were obtained. The authors also reported that the system was robust to varying pollutant concentrations in the inflow, and the outflow concentrations were consistent. In Florida, interestingly, coagulation/flocculation of stormwater seems to be common, and has been in use in full-scale facilities since the mid-1980s, with multiple installations built by one company (Harper, 2007). At that time, Lake Ella in Tallahassee was a hyper- eutrophic lake, receiving stormwater from a storm sewer system at multiple discharge points. The choice of a chemical treatment system arose from the need for an area-efficient system, as there was no land available to purchase for conventional SCMs. The system was based on a central facility with a coagulant dosing system connected to pumps and flow meters. Alum was dosed directly inline into the stormwater flow and relied on natural or artificially created turbulence in the sewer line. Since its inception at Lake Ella, more than 50 alum stormwater treatment systems have been constructed in Florida. Ac- cording to reports, the typical optimal dose of alum in these systems is 5-10 mg/L, and they consistently show a reduction of 90% of total phosphorus, a 50%–90% reduction of metals, and a greater than 99% reduction of total coliform. They also state that the pollutant mass removal for the alum stormwater treatment systems exceeds that of sedimentation ponds. In their life cycle cost analysis, the systems were cheaper per pollutant mass removed than the cost for sedimentation ponds. Ding et al. (2001) reported that very few stormwater treatment processes have an effect on colloidal particles, and using coagulation/flocculation requires long detention times and large tanks. In response, the authors sought to decrease the settling time drastically by employing and testing a microsand-ballasted coagulation process using a synthetic runoff made from parking lot sediment along with either alum or ferric chloride. They reduced the turbidity of the synthetic runoff from 74 NTU down to around 10 NTU without ballast, and below 2 NTU with ballast. The authors also observed a difference in the particle size distribution, which before treatment was dominated by particles >10 μm, and after treatment by particles below 1 μm. Lin et al. (2004) investigated the floc fractal dimension (describing the shape complexity) effect of a coagulation/flocculation process on particulate removal and particle size distribution using both jar-tests and a settling column. Water samples were taken from a catchment basin receiving runoff from a highway bridge in Baton Rouge, Louisiana. The

9 authors observed optimal removal at an alum dose of 120 mg/L, and enhanced particle removal with the use of a cationic polymer. Their main findings were that the stormwater particles were fractal, with complex shapes and drastically different settling velocities compared to ideal spherical particles, and that a coagulation/flocculation process increased the settling velocity. The California Department of Transportation (Caltrans) has been active in trying to find ways to efficiently treat stormwater runoff in order to meet discharge limits set by the State of California. The quality of Lake Tahoe was deteriorating, and the cause was mainly phosphorus and small particles. Trejo-Gaytan (2006) screened different coagulants to determine their ability to remove phosphorus and particles using low chemical doses in both synthetic and real stormwater. In laboratory tests, discharge limits could be met using sulfate or silica modified poly-aluminum chlorides and controlling the dose with streaming current detectors, aiming for a slightly negative charge (SCV ≤ 0 mV). How- ever, there were concerns regarding the toxicity of residual coagulants in the water body. In toxicity tests, the coagulant-treated stormwater increased algae and decreased fish mor- tality compared to untreated stormwater, but adversely affected zooplankton reproduc- tion (Lopus et al., 2009; P. A.M. Bachand et al., 2010); low dosages were therefore ad- vised. A feasibility study indicated that a coagulation/flocculation process had good potential for the treatment of stormwater (P. A. M. Bachand et al., 2010), clear benefits including increased treatment effect, and a low footprint. A coagulation/flocculation- retrofitted sedimentation pond or wetland would be able to service two to three times the original catchment area. Potential drawbacks of the coagulation/flocculation process were technical problems in accommodating the variation found in urban runoff, and costs (P.A.M. Bachand et al., 2010). In another project carried out by Caltrans, coagulation/flocculation of first-flush highway runoff in the Los Angeles area was investigated (Kang et al., 2007). The authors concluded that low doses of coagulant (alum or iron chloride) did not coagulate the runoff, but high doses to target the sweep floc mechanism reduced turbidity to below 5 NTU and dissolved metals up to 50%, but might require pH adjustment. The authors suggested that initial conductivity might be a useful parameter for controlling the dose, and that the main benefit to using a polymer is decreased mixing time. Zeta potential is a measurement of the surface charge of suspended particles, and its applicability for achieving charge neutralization is of interest for stormwater applications. Sansalone and Kim (2008) studied the zeta potential in coagulation/flocculation of stormwater. They observed an optimal interval between -15 to -10 mV at which maximal turbidity and suspended solids reduction occurred. The authors noted that the charge neutralization mechanism was susceptible to charge reversal at lower pH/higher doses, and that charge reversal not only caused the resuspension of particles, but also the creation of fine particulates and metal precipitates; control of such an operation is therefore important to ensure treatment efficiency. A study in Denmark looked at the possibility of amending wet detention ponds with sand filters and either dosed coagulant in the inflow, iron coagulant enriched sediment, or a 10 fixed-media sorption filter (Isteniç et al., 2012). The authors noted treatment performance improvements from the sand filters and the fixed-media sorption in terms of metal removal. However, the coagulant-amended ponds did not consistently improve the removal of metals. On the other hand, there was less algae growth, which was attributed to a reduction in bioavailable phosphorus.

3. Materials and methods

3.1. Study Design An initial jar-test screening study was conducted on an urban snowmelt mixture in which different combinations of the chemicals were evaluated as primary coagulants or flocculant aids in terms of turbidity reduction, total suspended solids (TSS) removal, and in- curred changes in pH (Paper I). Five coagulants were selected for a further extended jar- testing regime investigating the coagulation process characteristics and changes in particle size distribution (Paper I), as well as the removal effect of stormwater pollutants (Paper II). The extended jar-testing regime consisted of a set of three replicate jar-tests per coagulant in a completely randomized design. In the extended jar-testing regime, additional water quality measurements for zeta potential, conductivity, and alkalinity were performed, as well as determination of pollutant concentrations. The study design for the extended testing regime was repeated for the collected road runoff (Paper III). 3.2. Flocculation and sedimentation The treatment process investigated in these studies consisted of particle destabilization through coagulation via the addition of coagulants followed by particle aggregation in a flocculation process. The floc aggregates formed were subsequently separated from the water phase by sedimentation. Only parameters related to the coagulation process were studied in these papers. Param- eters governing both flocculation and sedimentation were constant throughout the studies, including mixing times with velocity gradients for the rapid and slow mix stages, sedimentation time and height (area if continuous with a hydraulic flow). No measurements were examined for these processes (e.g., settling velocity, floc steady-state size or floc fractal dimension). Sedimentation time was kept constant at 30 minutes, which was more than enough time for flocs to settle to the bottom. 3.3. Experimental set-up A portable jar-testing apparatus (Flocculator, provided by Kemira) was used in all the experiments conducted throughout the papers in this thesis (Figure 2). The apparatus consisted of a central control unit with six sets of individual dials controlling the different impeller rotational speeds, and a timer that beeped after a preset time. Six individual and detachable inserts with flat-bladed impellers were connected to the control unit. The inserts fit standard 1 L beakers.

Figure 2 Left: Control unit with individual dials to control settings for each connected beaker. Right: Beaker with the impeller insert.

Each jar-test had a protocol consisting of three phases: rapid mixing, slow mixing, and sedimentation. A standard protocol was followed and kept unchanged throughout all experiments, and was performed as follows (Lytle, 1995): 1. Rapid mixing phase 200 rpm corresponding to a velocity gradient of G = 190 s-1, mixing time of 60 seconds. 2. Slow mixing phase 30 rpm corresponding to a velocity gradient of G = 15 s-1, mixing time of 15 minutes. 3. Sedimentation phase No mixing. Sedimentation time of 30 minutes. Each impeller was started individually and in sequential order. The chemicals were added in the first one to two seconds during the rapid mixing phase. When a flocculant aid was used, it was added approximately 15 seconds after the primary coagulant. The kinetic energy added (velocity gradient) in the rapid mixing phase ensured total dispersion of the chemicals. During the rapid mixing phase, a 500 μL sample was extracted into a DTS1070 cuvette, and the zeta potential was measured on a Zetasizer Nano ZS Instrument (Mal- vern Instruments, Worcestershire, United Kingdom). The kinetic energy input in the slow mixing phase was lower, promoting floc aggregation and helping prevent floc dis- integration caused by shear forces (Figure 3).

Figure 3 Floc aggregation and growth was promoted through the addition of low kinetic energy in the slow mixing phase. Jar-testing experiment during the slow mixing phase (left), and a close up of the formed flocs (right).

The water in the container to be treated in the jar-testing experiments were thoroughly mixed by shaking the container before being poured into the jar-testing beakers. Two different jar-testing experiment setups were used: one for optimal dose determination, and one for analysis of pollutant removal. For optimal dose determination, the first beaker was the control and did not receive any chemicals, but was subjected to the entire jar- testing protocol. The next five beakers contained increasing doses of the chemical (Figure 4). A sample of 600 mL was decanted to measure water quality parameters (pH, turbidity, TSS, conductivity, and alkalinity).

Figure 4 After a jar-test for optimal dose determination. From the left: Beaker 1 was the control, Beaker 4 received the optimal dose, and Beaker 6 received a dose that was too high, resulting in a low degree of charge reversal.

To analyze pollutant removal, three control beakers and three beakers using the optimal dose were used. After the jar-test, 600 mL from each beaker was decanted. The three controls were mixed together, and the three beakers receiving the optimal dose were mixed together. This composite volume was then portioned to smaller volumes to analyze water quality parameters, as well as metals, TOC/DOC, and hydrocarbons.

3.4. Chemicals used as primary coagulants or flocculant aids Table 1 lists the chemicals that were evaluated using jar-tests throughout the studies in this thesis. PIX-111, PAX-215, PAX-XL100, PAX-XL360, Superfloc C491, Superfloc C494, Superfloc A110 HMW and Superfloc A130 HMW are water treatment products from Kemira (Helsinki, Finland). Limewater was prepared by dissolving 5 g of Ca(OH)2 (Kebo, Düsseldorf, Germany) in 100 mL of water and decanting to leave behind undis- solved Ca(OH)2. Alum was prepared by dissolving 5 g of Al2(SO4)3·16H2O (BDH, Lon- don, United Kingdom) in 100 mL of water. Chitosan was prepared by dissolving 5 g of chitosan (Acros Organics, Geel, Belgium) in 100 mL of 5% HCl. Drinking water sludge was obtained from the nearby water treatment plant, where they use PAX-XL60 in the treatment process. Table 1 All chemicals used as coagulants and/or flocculant aids in the jar-testing experiments.

Used in Chemical Used as Description papers PIX-111 Primary coagulant Iron(III) chloride I, II & III PAX-215 Primary coagulant Pre-hydrolyzed aluminum chloride, 30% I, II & III relative basicity PAX-XL100 Primary coagulant Pre-hydrolyzed aluminum chloride with I* sulfate, relative basicity 43% PAX-XL360 Primary coagulant Pre-hydrolyzed aluminum chloride and I & II organic polymer

Limewater Primary coagulant I* Alum Primary coagulant Aluminum sulfate I & II Drinking water sludge Primary coagulant Treated with PAX-XL60 I* Chitosan Primary coagulant and Cationic polysaccharide I & II flocculant aid Superfloc C491 Flocculant aid Cationic polyacrylamide (PAM), low relative I* charge (5%) Superfloc C494 Flocculant aid Cationic PAM, medium relative charge I* (20%) Superfloc A110 HMW Flocculant aid Anionic PAM, low relative charge (16%) I* Superfloc A130 HMW Flocculant aid Anionic PAM, medium relative charge (33%) I*

* Only evaluated in the coagulant screening study

Paper I describes the combinations of primary coagulants and flocculant aids that were evaluated in both the screening study and the extended testing regime. 3.5. Chemical and physical analyses of the water samples Chemical and physical analyses for water quality were performed on each of the urban snowmelt batches and the road runoff collected from each rain event. Samples of 600 mL were also taken from tested stormwater and from each beaker, after each jar-testing experiment. Conductivity was measured with a CDM210 device (Radiometer, Copenha- gen, Denmark), and pH was measured with a WTW pH 330 equipped with a WTW SenTix41 pH electrode (WTW, Weilheim, Germany), calibrated with standard solutions of pH 4 and 7 before each experiment. TSS was measured using glass fiber filtration with

16 a pore size of 1.6 μm (EN 872:2005), and turbidity measurements were taken on a Hach Turbidimeter 2100N (Hach, Loveland, Colorado) with the signal average and ratio con- figuration settings enabled. Particle size distribution measurements were performed using laser diffraction on a HORIBA LA-960 (HORIBA, Kyoto, Japan). Alkalinity was determined using end-point titration (EN ISO 9963-1:1994) with an ABU901 automatic bu- rette coupled to a TIM900 control module (Radiometer analytical, Lyon, France), and calculated as mg/L as CaCO3. 3.5.1. Determination of pollutant concentrations Organic compound removal was evaluated using multiple aggregate variables. The most general measurement, TOC/DOC, determined the amount of oxidizable organic carbon (both the total and dissolved fractions). The hydrocarbon oil index determined compounds that could be extracted in a non-polar solvent with a boiling point of 39-69˚C measured on a standard of linear alkanes (n-decane to n-tetracontane). The most specific measurements were the PAH analyses, covering 16 PAHs (Keith, 2015) identified by the U.S. EPA. These 16 PAHs have been the established standard for analysis for many years, but recent research has scrutinized this list and suggested an updated list for environmental purposes containing alkylated PAHs, larger compounds, and heterocyclic compounds (Andersson and Achten, 2015). Furthermore, there are indications that the alkylated PAHs are more dispersed due to an exchangeable nature by being partitioned into many different particle sizes, whereas their parent non-alkylated PAHs are mostly adsorbed onto soot particulates (Simo et al., 1997). This would indicate that in a sedimentation process the alkylated PAHs would exhibit different removal characteristics. The PAH analysis in this thesis did not possess sufficient selectivity to differentiate between alkylated and parent PAHs, and therefore removal efficiencies for these could not be assessed. Analyses for TOC, DOC, total (with acid digestions) and dissolved (without acid diges- tion) metals, hydrocarbon oil index (HOI), and polycyclic aromatic hydrocarbons (PAHs) were carried out by an accredited laboratory (ALS Scandinavia, SWEDAC Accreditation no: 2030), with extended uncertainty bounds (JCGM 100:2008, 2008). Samples for analysis of dissolved metals and DOC were passed through 0.45 μm polyethersulfone filters. Analysis techniques, standard methods and reporting limits are listed in Table 2. For calculations of removal efficiency, concentrations below the reporting limit were set to half the reporting limit.

Table 2 Analysis methods for different compounds and the corresponding reporting limits for each compound. The laboratory reported the concentrations for metals using ICP-SFMS, or ICP-AES when the metal concentrations were too high.

Reporting limit Compound Technique Total Dissolved Unit

Metals Cadmium ICP-SFMS1 0.05 0.05 μg/L

Chromium " 0.9 0.5 " Copper ICP-SFMS or ICP-AES2 1 1 "

Nickel ICP-SFMS 0.6 0.5 " Lead " 0.5 0.2 " Zinc ICP-SFMS or ICP-AES 4 2 "

TOC Oxidation and IR-spectrometry3 0.5 mg/L DOC " 0.5 "

Hydrocarbon oil index C10-C12 & C12-C16 GC-FID4 5 μg/L

C16-C35 " 30 " C35-C40 " 10 "

PAH GC-MS5

Naphtalene " 0.03 μg/L

Phenantrene " 0.02 "

Other PAHs " 0.01 "

1 ISO 17294:2016, 2 ISO 11885:2007, 3 CSN EN 1484 4 ISO 9377-2:2000, 5 ISO 6468:1996

3.6. Description of the stormwater used for jar-testing The experiments carried out for papers I and II took place during the spring of 2016, and were performed using an artificial urban snowmelt mixture. Reasons for that were two- fold. Firstly, snow banks accumulate pollutants over the entire winter seasons, which are mobilized during the thawing season and is often severely polluted (Westerlund and Viklander, 2011; Moghadas et al., 2015). Secondly, it was a practical decision since relatively equal quality of artificial run-off was expected to be achieved in this way. In paper III, the jar-testing experiments were performed on the first 25 L of road runoff generated from rain events. This was done in order to capture the highest concentration of pollutants if the runoff exhibited a first-flush effect (Deletic, 1998).

3.6.1. Urban snowmelt mixture An urban snowmelt mixture was produced by mixing equal volumes of traffic-impacted snow and pristine snow. In March 2016, traffic-impacted snow was collected from a snowbank along the side of a road in downtown Luleå, Sweden using a wheel loader. The annual average daily traffic for the entire road is approximately 20,000 vehicles. The pristine snow was collected from an undisturbed park area in Luleå without any direct contact to traffic. The snow was stored in plastic (high-density polyethylene) boxes (Fig- ure 5) and kept at -10˚C until used in the jar-testing experiments. Approximately 24 hours prior to each jar-testing experiment, one batch of traffic-impacted snow and one with pristine snow was removed from storage and allowed to thaw at room temperature. Once thawed, an urban snowmelt mixture of 25 L was made by mixing equal volumes of traffic impacted snowmelt and pristine snowmelt. The urban snowmelt mixture was mixed and allowed to settle for 1 hour before decantation. De- cantation was performed in order to achieve a water quality similar to meltwater entering the urban drainage system during the natural thawing season in terms of total suspended solids (TSS) and turbidity (Westerlund et al., 2003).

Figure 5 Snow impacted by traffic in cold storage.

3.6.2. Road runoff Road runoff was collected during four rain events in the autumn of 2017 in downtown Luleå, Sweden. To ensure collection of stormwater with a high pollutant content, the first 25 L of runoff generated were collected in a gully pot equipped with a stainless steel collector funnel (Figure 6). The funnel was rinsed with water before each rain event. The gully pot drains an approximately 300 m2 area from one lane of a two-lane road with annual average daily traffic (both directions) of approximately 17,800 vehicles. After collection, the road runoff was transported back to the laboratory, where jar-testing com- menced immediately.

Figure 6 Collection site for the road runoff. Insert: gully pot equipped with a funnel that leads to an easily accessible manhole on the vegetated traffic island. 3.6.3. Water quality parameters Samples were taken for analysis of water quality parameters prior to each jar-testing experiment; this includes both the urban snowmelt mixture samples (n = 15) from Papers I and II, and the road runoff (n = 7) from Paper III. For the parameters measured (Table 3), the road runoff exhibited a higher concentration of total suspended solids (TSS) compared to the snowmelt mixture. Likewise, the alkalinity was higher in general for the road runoff than the snowmelt mixture. The particles found in the snowmelt mixture presented a greater surface charge measured as the zeta potential. The particle content, measured as turbidity and TSS, varied considerably (Table 3). Alkalinity and pH are important parameters for the coagulation process; in water treatment guidance manuals, any alkalinity level below 60 mg/L as CaCO3 (USEPA, 1999) is generally considered low from a coagulation process perspective, and as such, the snowmelt mixture and road runoff used in this thesis would qualify as low alkalinity water.

Table 3 Water quality parameters (mean ± SD) for the snowmelt mixture samples (Papers I and II, n = 15) and the road runoff samples (Paper III, n = 7) used in the jar-testing experiments

Turbidity TSS Conductivity pH Alkalinity Zeta potential (mg/L as (NTU) (mg/L) (μS/cm) (mV) CaCO3) Urban snowmelt mixture 550 ± 260 484 ± 202 111 ± 20 7.3 ± 0.3 28.5 ± 14.4 -19.5 ± 9.4

Road runoff 650 ± 280 1140 ± 385 104 ± 26 7.6 ± 0.5 51.7 ± 13.8 -10.5 ± 4.7

Comparing the difference in total metal concentrations (Table 4) for the snowmelt mixture and the road runoff, the road runoff had higher concentrations of metals, but also quantifiable levels of dissolved metals. Copper and zinc were the only dissolved metals of

20 the typical stormwater pollutants that were present in quantifiable levels in the snowmelt mixture samples. A local report in Stockholm (Riktvärdesgruppen, 2009) included a proposal for discharge limits for selected stormwater pollutants. According to the guidelines of this proposal, both the snowmelt mixture and the road runoff exceeded the proposed limits for metals, and could be considered highly polluted. In particular, the road runoff had up to ten times the recommended concentration levels (for copper and zinc) for discharge directly into a water body. Cadmium was the only metal below the calculated exceedance levels for both the snowmelt mixture and the road runoff, and was also the only metal without quantifiable levels of the dissolved fraction. In terms of metals, the compositions of the snowmelt mixture and the road runoff were similar. However, the road runoff contained approximately two to three times the total metal concentrations, and six times the dissolved metal concentrations compared to the snowmelt mixture.

Table 4 Concentrations (mean ± SD) of typical stormwater-associated metals in the snowmelt mixture and road runoff samples. Exceedance percentages were calculated based on the concentrations (total/dissolved) and a proposal for discharge limits in Stockholm, Sweden.

Dissolved Dissolved as a Suggested discharge Metal Total Exceedance* (<0.45μm) fraction of total limits* (μg/L) (μg/L) (%) (μg/L) (%)

Snowmelt mixture Cd 0.133 ± 0.061 ND - 0.4 / 0.5 - 234 / 34 Cr 33.4 ± 12.0 ND - 10 / 25 447 / 146 Cu 98.5 ± 32.9 3.71 ± 1.03 4 18 / 40 - Ni 13.5 ± 4.79 ND - 15 / 30 83 / - Pb 14.6 ± 5.16 ND - 8 / 15 243 / 106 Zn 257 ± 91.6 5.09 ± 4.47 2 75 / 125 Road runoff Cd 0.377 ± 0.669 ND - 0.4 / 0.5 - Cr 61.6 ± 9.33 1.71 ± 1.7 3 10 / 25 516 / 146 Cu 182 ± 15.5 21.8 ± 4.71 12 18 / 40 900 / 355 Ni 30.3 ± 6.50 1.81 ± 2.16 6 15 / 30 102 / 1 Pb 36.6 ± 6.99 0.24 ± 0.71 1 8 / 15 358 / 144 Zn 802 ± 25.7 28.8 ± 5.21 4 75 / 125 969 / 542 * Discharge to: water body/separate storm sewer; ND, not detected; -, not calculated

Concentrations of TOC were approximately three times higher in the road runoff samples compared to the snowmelt mixture samples, and concentrations of DOC were approximately six times higher (Table 5). Specifically, there was roughly twice the concentration of hydrocarbons and PAHS in the road runoff, though the distribution of their constituent groups was similar. Apart from the different magnitude in pollutant concentrations, the differentiating feature was the higher levels of DOC in the road runoff.

Table 5 Concentrations of organic compounds (mean ± SD, fraction of total) in the snowmelt mixture and road runoff samples. Organic compounds were measured as organic carbon, hydrocarbon oil index and PAHs.

Snowmelt mixture Road runoff TOC (mg/L) 37.4 ± 13.3 101 ± 38.5 DOC 3.2 ± 1.7 (9%) 21.1 ± 6.3 (21%)

Hydrocarbon oil index C10-C40 (μg/L) 1060 ± 1200 2390 ± 1320

C10-C12 * -

C12-C16 5.3 ± 4.05 (1%) 26.9 ± 9.9 (1%)

C16-C35 770 ± 882 (73%) 1860 ± 990 (78%)

C35-C40 276 ± 315 (26%) 502 ± 340 (21%)

PAH (μg/L) 1.64 ± 0.95 2.87 ± 1.25 LMW 0.03 ± 0.02 (2%) 0.12 ± 0.07 (4%) MMW 0.98 ± 0.55 (60%) 1.6 ± 0.78 (56%) HMW 0.65 ± 0.39 (40%) 1.15 ± 0.46 (40%)

*,one measurement above reporting limit. -, below reporting limit.

3.7. Statistical analyses All data was stored in Microsoft Excel spreadsheets using the concept of tidy data, in which each variable is a column, and each observation a row (Wickham, 2014). All statistical tests (described below) were performed in R using a significance level of 0.05 (R Core Team, 2019). Graphical plots were produced using either base R plots or with the ggplot2 package (Wickham, 2016). A PCA analysis was performed to find differences between the snowmelt mixture and the road runoff. Prior to PCA analysis, zero variance observations (e.g. dissolved cadmium and PAH LMW) were removed since they could not be scaled. Near-zero variance observations (short-chain hydrocarbons, >C10-C12, had one value above reporting limit) were also pruned as they would contribute with almost no information to the analysis. The principal components were calculated using singular value decomposition. Principal components were chosen according to evaluation using the broken-stick model (Jackson, 1993). Confidence ellipses were calculated at a 95% level for the score groupings using a multivariate normal distribution. In order to test if there were differences between the sedimentation control and the coagulation treatments, a one-way ANOVA test was used. If the ANOVA indicated differences in treatment effect, a post-hoc pairwise t-test with Bonferroni correction was performed to compare the means between the different coagulant treatments. Multiple linear regression was performed in order to estimate a 95% confidence interval of the alkalinity consumption for all the coagulants. In order to understand the important parameters governing a successful coagulation/flocculation process on the snowmelt mixture and the road runoff, a naïve approach with 22 model selection was used. Data from all jar-tests were used to fit linear regression models using stepwise bidirectional elimination, adding or subtracting one parameter at the time. The response parameter used for the models was turbidity. Relative quality of the models were evaluated using the Akaike information criterion. The linear models were fitted to the jar-testing data that included turbidity, TSS, pH, alkalinity, and conductivity.

4. Results

4.1. Differentiating characteristics between snowmelt mixture and road runoff PCA analysis was performed to identify differentiating characteristics between the stormwater used. The biplot (Figure 7) presents the scores of the water samples reframed onto the two first principal components (explaining 65% of the total variance), together with the variables loading. A lot of pollutant loadings exhibited clear collinearity, and cluster variables out of these were created.

Figure 7 Biplot from PCA analysis of the pollutant concentrations in the snowmelt mixture and road runoff samples. The scores were represented as the circles and triangles, and variable loadings as arrows. Scores and loadings were plotted with the first and second principal components, which together account for 65% of the total variance. Confidence ellipses (95% level) as calculated from a multivariate normal distribution. Several of the metal variables exhibited collinearity, and were recalculated as total metal cluster and dissolved metal cluster, excluded metals were plotted on their own.

The first principal component explained ~45% of the variance, compared to ~20% for the second principal component. Therefore, the most differentiating characteristics were the loadings with the greatest magnitude as projected onto PC1. Specifically, sodium (both total and dissolved) correlated positively with the snowmelt mixture, and correlated negatively with dissolved metals. This indicated that higher concentrations of sodium were more likely to be found in the snowmelt mixture as compared to the road runoff,

25 and that a higher dissolved metal concentration in general was associated with a lower sodium concentration. Interestingly, dibenz[a,h]antracene stands out among the PAHs as uncorrelated with the compound PAH variables. Similar independency effects could be found for the metals manganese (dissolved), aluminum (dissolved) and cobalt. 4.2. Screening of primary coagulants and flocculant aids Twelve different chemicals were used in the screening study (Table 1). Eight of them were tested as primary coagulant and five were used as a flocculant aid together with a primary coagulant. They were evaluated in jar-tests based on the attained turbidity reduction and impact on the pH (Paper I). The flocculant aids were evaluated if their addition could increase the turbidity reduction or if the same turbidity reduction could be attained with a lower coagulant dose. None of the flocculant aids improved the turbidity reduction nor was it possible to lower the primary coagulant dose. Five chemicals were choosen for the extended testing regime. Alum was included as a baseline coagulant to compare against, as it is one of the most commonly used coagulants. PAX-215 and PAX-XL360 were chosen to represent pre-hydrolyzed aluminum coagulants. PIX-111 was the only iron chloride product tested and was chosen for the high turbidity reduction despite a higher pH impact. Lastly, chitosan was selected due to its low pH impact and cationic biopolymer nature. 4.3. Coagulation process characteristics The characteristics of the coagulation process in terms of coagulant dose requirements as well as changes in pH, alkalinity, zeta potential and conductivity were discussed in Paper I. In Figure 8, the dose ranges at which the different coagulants used in the studies reached optimal effect is outlined, along with the initial and final pH. According to the scientific literature and handbooks, the optimal pH range for alum is between 6 and 7, and for iron chloride 5.5 to 6.5, varying depending on water quality (USEPA, 1999; Bratby, 2016). As observed in Figure 8, the optimal dose and pH range coincided only for the road runoff treated with the iron coagulant, and, in one instance, when the snowmelt mixture was treated with PAX-215. In all other cases, the pH was above the theoretical optimal range. A higher coagulant dose would lower the pH, but for the concentrations used in these studies charge reversals were already observed in several cases. In practice, charge reversal means that sufficient cationic hydrolysis species were produced to turn the negative colloids positive. However, it is unknown if the optimal pH range from the literature corresponds to the optimal range for stormwater, since its properties differ from both raw water and wastewater. Therefore, it is uncertain if the treatment experiments would have benefited from adjusting the pH slightly with an acid in order to reach the theoretical optimal pH interval. Another interesting finding was that the road runoff required higher doses of coagulant, possibly due to both higher particle content and lower ionic strength (as inferred from the conductivity). Alkalinity consumption was calculated using the dose and alkalinity levels during the jar- testing experiments. Table 6 presents the theoretical alkalinity consumption (Bratby,

2016) for the coagulants, and the actual consumption in the jar- tests for both the snowmelt mixture and the road runoff. The theoretical consumptions are based on balanced chemical formulas and may not represent the true consumption in an environmental system. As shown in Table 6, the alkalinity consumption does not match the theory for several of the coagulants, and the linear relationship between dose and alkalinity was moderate.

Table 6 Calculated alkalinity consumption for the coagulants used in the jar-testing experiments. Cal- culated using multiple linear regression.

Calculated alkalinity consumption Theoretical consumption1 Snowmelt mixture Road runoff (mg/mg) Mean Confidence interval Mean Confidence interval R2 R2 (mg/mg) (95%) (mg/mg) (95%) Alum 5.56 0.59 (0.2, 0.98) 0.78 PAX-215 (30% basicity) 3.89 4.51 (1.39, 7.63) 0.40 3.48 (2.62, 4.35) 0.84 PAX-XL360) 3.17 2.12 (1.04, 3.21) 0.64 PIX-111 1.48 2.18 (1.31, 3.06) 0.76 2.00 (1.67, 2.33) 0.89 Chitosan 02 1.29 (-0.52, 3.1) 0.56

1 Recalculated as mg active substance / mg CaCO3 from Bratby (2016) 2 Does not undergo hydrolysis unlike the metal coagulants, however it is often prepared in an acid solution.

Zeta potential is an interesting parameter to use for the control of a coagulation process. It is the only measured parameter that estimates the destabilization effect on the particles in suspension. Typically, a zeta potential of between -10 and +5 mV indicates adequate destabilization in order to remove colloidal material (Sharp et al., 2005). Unfortunately, the set of zeta potential measurements performed during jar-testing of the road runoff was not robust enough, and data is only presented for the jar-tests using snowmelt mixture in Paper I. The zeta-potential measurements for the road runoff os- cillated wildly between dose increments, making it difficult to narrow down an interval in which the coagulation process was operating optimally. The reasons for this are two- fold: first, replicate samples should have been extracted for measurements from each jar in the jar-test to reduce the risk of spurious values; second, the measurements are time- sensitive, and should ideally be performed as soon as possible after sampling. The zeta potential measurements were conducted between 10 and 30 minutes after sampling for logistical reasons.

Figure 8 Dose ranges for the coagulants tested in the jar-tests for which turbidity was reduced by 90% or more. The pH values for the initial and final dose ranges are overlaid as numbers in the plot. End points marked with a star indicate observed charge reversal.

4.4. Treatment performance 4.5. Particle content The treatment performance in the jar-testing experiments in terms of particle content (measured as turbidity and TSS) is presented in Paper I for the snowmelt mixture, and Paper III for the road runoff. A table summarizing the findings from the papers is shown below (Table 7).

Table 7 Average and standard deviation for the removal of particle content (TSS and turbidity) in the snowmelt mixture and road runoff treated with the different coagulants.

Snowmelt mixture Road runoff

Sedimentation Coagulation Sedimentation Coagulation TSS 35 ± 13 % 94 ± 9 % 74 ± 20 % 99 ± 1 %

Turbidity 20 ± 18 % 93 ± 12 % 30 ± 10 % 98 ± 1 %

The coagulation process proved to be very efficient in removing particles. The treatment effect varied more in the snowmelt mixture as compared to the road runoff (Table 7), probably due to a higher initial particle content in the road runoff as compared to the snowmelt mixture. The performance of the sedimentation control was considerably lower than that of the coagulation treatment. However, due to the much higher TSS concentration in the road runoff, the sedimentation control removed on average 74% of TSS. Average cumulative particle size distributions with area and number as the distribution base are included in both Paper I and Paper II for the snowmelt mixture. For the road runoff, it is noteworthy that particles measuring less than 1 μm in diameter accounted for most of the surface area exposed by all particles (Figure 9). Sedimentation alone shifted the cumulative distribution toward smaller particle sizes in terms of total surface area and particle numbers. However, coagulation treatment (with the same sedimentation time) shifted the cumulative distribution back toward larger particle sizes, suggesting that the coagulation treatment had an effect on the smaller particles, in contrast to sedimentation only. This effect can also be seen when looking at the distribution (Figure 9). The distributions before treatment exhibited a bimodal appearance that nearly disappeared with sedimentation. It is worth noting that the particle size distribution did not provide information on the number of particles or surface area per unit volume, only their distribution by particle size.

Figure 9 Average particle size distribution for the untreated road runoff, and post-treatment (sedimentation and coagulation/sedimentation). The distributions for the left-hand panels are calculated using number as transformation basis and the right-hand panels distributions are calculated using surface area. Shaded regions demarcate one standard deviation around the mean.

4.6. Pollutants Typically, the pollutants associated with particles were removed at the same magnitude as TSS and turbidity. These results were similar for all the coagulants tested. The total metal fraction was reduced by 90% on average in both the snowmelt mixture (Paper II) and road runoff (Paper III). Similar removal efficiency was found for the PAHs and hydrocarbon oil index (Paper II for the snowmelt mixture, Figure 10 for the runoff). The TOC removal was smaller on average for the road runoff (71% for PIX-111 and 62% for PAX-215) compared to the snowmelt mixture (88% for PIX-111, 89% for PAX-215, and similar for the other coagulants tested in Paper II).

Figure 10 Mean treatment effect of hydrocarbon oil index and PAH sum 16, the compound variable summing 16 PAHs for the jar-testing experiments with road runoff. Solid line represents the coagulation and sedimentation treatment, and the dotted line represents the control treatment, sedimentation only.

The removal efficiencies for dissolved metals and DOC, however, were different compared to the particulate pollutants. In most of the treatment experiments little to no removal of DOC was achieved in the snowmelt mixture (Figure 11). PIX-111 was the only coagulant that caused a significant removal of DOC. A single experiment with PAX- 215 caused considerable removal, but not significant compared to sedimentation. PIX- 111 caused significant removal of DOC in the runoff, but the removal effect was only 26% on average. Using conventional coagulants, the removal efficiency for dissolved metals was generally low (Figure 12); the removal efficiency for dissolved copper was 40% on average for both the snowmelt mixture and road runoff. The road runoff contained quantifiable levels of dissolved chromium and lead, and a removal of between 30% and 60% was observed for these dissolved metals with the use of PIX-111 and PAX-215. An increase in dissolved zinc was observed after treatment with the conventional coagulants (Paper II and III). This increase was also found for dissolved nickel (Paper III). Comparing the final pH to speciation diagrams for both zinc and nickel, it can be surmised that the mobility of these metals increased due to a decrease in pH. Conversely, chitosan stood out compared to the conventional coagulants with a high removal capacity for dissolved metals (72% on average for copper, and 51% on average

31 for zinc) in Paper II. However, chitosan removed lower amounts of the particulate- bound pollutants, and was therefore not selected for evaluation with the road runoff.

Figure 11 Mean treatment effect for dissolved organic carbon (DOC) in the jar-testing experiment. The top row represents the snowmelt mixture experiments and the bottom row the runoff experiments. Solid lines represent the coagulation and sedimentation treatment, and the dotted line represents the control treatment, sedimentation only. Error bars cover two standard deviations from the mean as reported by the laboratory.

Figure 12 Mean treatment effect for dissolved metals in the jar-testing experiment. The top two rows represent the snowmelt mixture experiments and the two columns on the bottom right represent the runoff experiments. Solid lines represent the coagulation and sedimentation treatment, and the dotted line represents the control treatment, sedimentation only. Error bars cover two standard deviations from the mean as reported by the laboratory. Copper and zinc were the only metals with quantifiable concentration levels in the snowmelt mixture.

4.7. Identification of important parameters in the coagulation process Important parameters for the coagulation process were identified through stepwise linear regression using the data from the jar-tests in both the snowmelt mixture and road runoff studies. Prior studies have identified the starting values for certain parameters as important in the determination of optimal dose (Rathnaweera, 2010), therefore these were added to each observation used in the model.

Table 8 Resulting models fitted from stepwise linear regression using bidirectional elimination.

Model for Number of observations Included parameters R2

Alum 24 Conductivity, alkalinity, Initial turbidity 0.56

PAX-215 48 Alkalinity, initial conductivity, initial pH, Initial alkalinity 0.62 PAX-XL360 24 Alkalinity, initial TSS 0.67 PIX-111 55 Conductivity, pH, alkalinity, initial conductivity, initial alkalinity 0.72 Chitosan 22 Conductivity, pH, alkalinity, initial turbidity, initial TSS 0.44

Although the model fit was relatively low, some results are interesting. Different parameters were considered important for different coagulants for the reduction of turbidity, but the parameters conductivity and alkalinity seemed to be of importance for all coagulants. These two parameters are inter-related (Hill et al., 2018) and conductivity can be used to assess the ionic strength (McCleskey et al., 2012), which in part determines the electrostatic repulsion of the double layer. Initial particle content (turbidity or TSS) was only considered important in the models for PAX-XL360, alum and chitosan.

5. Discussion

5.1. Flocculation and sedimentation In screening study in paper I, the use of flocculant aids was briefly investigated via the addition of both cationic and anionic polymers. The use of flocculant aids was evaluated on the basis of whether they improved the removal of particles (measured as turbidity and TSS), or if the same removal rate could be maintained while lowering the coagulant dose. The results of both these evaluations were negative, and the use of a flocculant aid was not investigated further. It is possible, however, that use of a flocculant aid could affect other process parameters, such as decreasing the required mixing time, or producing shear-resistant flocs (Bratby, 2016). 5.2. Coagulation process characteristics One major concern for the coagulation process was the low alkalinity of the snowmelt mixture and road runoff, and whether enough coagulant could be added before pH sub- stantially decreased. The theoretical and calculated alkalinity consumptions are presented in Table 6. PAX-215 and PAX-XL360 are pre-hydrolyzed aluminum chlorides, often referred to as poly-aluminum chlorides, since the polymeric hydrolysis species have already been prepared by base titration. Basicity is a property of coagulants, defined as the ratio of [OH] to [Al3+] or [Fe3+], and is one factor determining the nature of polymeric species (Ye et al., 2007). The practical applicability means that the use of a pre-hydrolyzed coagulant will require a much lower dose and thus have a lower impact on the alkalinity and pH. Chitosan itself will not consume alkalinity in a hydrolysis reaction, however it is only soluble in acid, which may consume alkalinity (Renault et al., 2009). In this study, chitosan was diluted in 5% HCl, which may have had a slight impact on the alkalinity. PIX-111 consumed less alkalinity per active substance than the other metal coagulants, but required higher doses before an effect was achieved, in particular for the road runoff (Figure 8). Four different coagulation mechanisms were described in the background chapter: double- layer compression, adsorption destabilization through charge neutralization, enmesh- ment in sweep floc precipitation, and inter-particle bridging. In terms of the conventional metal salt coagulants (Alum, PAX-215, PAX-XL360 and PIX-111), the main coagulation mechanism observed in the jar-testing experiments was charge neutralization, as ev- idenced in the charge reversal at higher coagulant doses (Figure 8), and changes in zeta potential. The occurrence of charge reversals is indicative of a charge neutralization mechanism (Stumm and O’Melia, 1968), whereby the polymeric hydrolysis are adsorbed onto the negatively charged particles, lowering their electrostatic repulsion potential. It is possible that metal hydroxides were formed to some degree, but no amorphous flocs, typical of sweep flocculation, were observed. Both the snowmelt mixture and the road runoff were rich enough in particle content that coagulation by sweep floc (amorphous metal hydroxide precipitation) was unneeded, and would have required adjustment of the pH due to much higher coagulant doses. Treatment using chitosan affected the zeta potential, and overdosing also resulted in charge reversal, which is strongly indicative of

35 a charge neutralization mechanism. However, the possibility cannot be excluded that inter-particle bridging occurred with chitosan due to its cationic polymeric nature. This is in contrast with previous studies, in which the authors drew the conclusion that since the effect of pH change using coagulation of chitosan was insignificant, the mechanism could not be charge neutralization (Huang and Chen, 1996). Other studies of stormwater coagulation/flocculation processes have identified the observed coagulation mechanism as charge neutralization (Trejo-Gaytan et al., 2006; Harper, 2007; Sansalone and Kim, 2008). In one study, there was no effect for low coagulant dosing at all, but high coagulant dosing along with pH adjustment resulted in sweep flocculation with residual turbidity <5 NTU and 50% removal of dissolved metals (Kang et al., 2007). The rapid mixing stage has been found to be an important parameter for effective charge neutralization in order to ensure rapid and proper dispersal of the coagulant throughout the water, in contrast to a sweep flocculation mechanism (Rossini et al., 1999). In low turbidity drinking water applications, a sweep floc mechanism is usually considered safer, as suboptimal charge neutralization may lead to internal membrane clogging downstream as a result of the incomplete aggregation of colloidal material (Judd and Hillis, 2001). In the wastewater literature, descriptions of the dominant coagulation mechanism are rare. One explanation offered is that due to the competitive interplay between particle and phosphorus removal, the main mechanism seems to depend on the type of coagulant used, with low basicity coagulants giving rise to sweep floc, and high basicity coagulants bringing charge neutralization into effect (Ratnaweera et al., 1992). 5.3. Particulate removal as a result of destabilization by coagulation Throughout the studies, both turbidity and TSS decreased to a large degree. The treatment effect was over 90% for the snowmelt mixture, and over 98% for the road runoff. Both treatment effects were probably underestimated due to a slight disturbance in the settled particles during sample decantation for further analyses. The high removal rates were expected, since a coagulation destabilization process is believed to have a considerable effect on particle content (Duan and Gregory, 2003; Bratby, 2016). Moreover, similar removal efficiencies for particle content have been reported in stormwater coagulation with the use of a sweep floc mechanism (Kang et al., 2007), charge neutralization (Trejo-Gaytan et al., 2006; Harper, 2007; Sansalone and Kim, 2008), a nondescript coagulation mechanism (Bennett et al., 1981) and a microsand-ballasted nondescript coagulation mechanism (Ding et al., 2001). Slightly lower removal efficiencies were obtained via charge neutralization in a pilot plant (Heinzmann, 1994) and in a coagulation/flocculation/flotation pilot plant (Bernard et al., 1995). Metal particles and particulate-bound metals were also removed to a high degree. The removal efficiencies for total metals were over 90% for both the snowmelt mixture and road runoff. Taking into consideration that the measurements for total metals contain the dissolved fraction, the removal efficiencies for the metal particles alone and the particulate-bound metals are even higher. Relatively few scientific articles have examined metal

36 removal in a stormwater coagulation process. In a technical report describing the long- term performance of several alum stormwater treatment facilities in Florida (Harper, 2007), the author recorded metal removal of between 60% and 90%. Another previous study on coagulation/flocculation of stormwater presented removal rates for metals, but only for the dissolved phase (<0.45 μm), stating that “particulate-phase metals are not shown because they are expected to be removed as the turbidity and TSS are removed.” (Kang et al., 2007, p. 432). This statement is in accordance with the calculated removal efficiencies in this thesis. Analysis of particle size distribution was performed on the water phase before treatment, and after treatment (sedimentation control and coagulation treatment). Particle size distributions were analyzed to determine whether smaller silt-sized, clay-sized and colloidal particles were removed as a result of the coagulation process. In both studies presented in papers II and III, a leftward shift in the cumulative distributions using both number and surface area as basis occurred in the sedimentation control. This could be explained by coarser settleable particles being removed without the use of a coagulant. The coagulation treatment shifted these distributions rightward again, indicative of enhanced sedimentation of smaller particles. In the case of PIX-111 and the snowmelt mixture, the difference was very pronounced, although this may be due to the influence of a few leftover flocs as a result of decantation procedure. Almost identical observations were made from the analysis of the particle size distribution in the road runoff study (Figure 9), with the exception of the pronounced difference in rightward shift for PIX-111. The measurement range for the laser diffraction used was down to 0.01 μm, and compositional changes were observed down to 0.445 μm for the road runoff and down to 0.115 μm for the snowmelt mixture. Two other studies on a stormwater coagulation process investigated the changes in particle size distribution as a result of the process. Sansalone and Kim (2008) investigated changes in volume-basis particle size distribution from coagulation of retained stormwater using alum and ferric chloride. The authors used laser diffraction, and obtained particle size distributions down to a particle diameter of 1 μm. For particles <20 μm, the authors observed an effect from the coagulation process, which was absent in the sedimentation control. In addition, Sansalone and Kim observed resuspension of the clay-sized particle fraction (1-3 μm) during charge reversal. Kang et al. (2007) looked at the efficiency of polymer-mediated particle aggregation during rapid mixing, several hours of slow mixing, and finally sedimentation using optical scattering and extinction. The authors looked at the relative changes in number-basis distribution down to 0.5 μm in diameter, noting an increase in particle size during the slow mixing procedure indicative of particle aggregation, and further observed that particles larger than 30 μm settled out quickly. Together with the observations in this thesis, this corroborates that a coagulation treatment desta- bilizes smaller particles (<20 μm), including colloidal particles. 5.4. The effect of a coagulation process on the dissolved metal fraction The dissolved metal fraction was measured as everything capable of passing through a 0.45 μm filter. Consequently, the dissolved metal fraction contained particulates smaller 37 than 0.45 μm, as well as truly dissolved metals. This was evident in the particle size analysis, which showed that—especially for the snowmelt mixture—there was a considerable fraction of particulates smaller than 0.45 μm (Paper II). Therefore, any removal efficiency for the dissolved metal fractions in these studies will include both particulate matter smaller than 0.45 μm as well as the truly dissolved phase. Studies looking at particle size cut-offs below 0.45 μm found that copper and zinc especially, although to varying de- grees, were found in dissolved fractions passed through either 100 kDa or 10 kDa ultrafiltration membranes (Morrison et al., 1990; Tuccillo, 2006), or after ultracentrifugation (Grout et al., 1999), or by ultrafiltration and diffusive gradients (Lindfors et al., 2017). In these fractions, copper was typically found bound to dissolved organic matter (Morrison et al., 1990; Characklis and Wiesner, 2002; Karlsson et al., 2016), and zinc to carbonates (Karlsson et al., 2016). The metal salt coagulants removed on average 30% to 50% of chromium, copper and lead from the snowmelt mixture and road runoff. There was no significant difference in removal effect for chromium, copper and lead between the metal salt coagulants in the snowmelt mixture (Paper II). However, in the road runoff study (Paper III), PIX-11 performed significantly better than PAX-215 at removing copper. Treatment with the metal coagulants also exhibited adverse effects with an increased concentration of nickel and zinc in the dissolved fraction. The increases in nickel (Paper III) and zinc (Papers II and III), was most likely be attributed to the decrease in pH (Sauvé et al., 2000) resulting from the hydrolysis reactions caused by using metal salt coagulants. For the removal of the dissolved fractions (copper in Paper II, chromium, copper, and lead in Paper III), destabilization of colloidal particulates below 0.45 μm, or co-precipitation along with the coagulant hydroxides could be the possible chemical reactions. Kang et al. (2007) reported removal rates of up to 50% for dissolved arsenic, copper, chromium, cadmium, lead and zinc from Los Angeles highway runoff via a sweep floc mechanism at high coagulant doses (up to 250 mg/L of alum and iron chloride) along with a polymer, using pH adjustment. The authors did not observe any removal at low coagulant concentrations, leading to the conclusion that precipitation was the dominating removal mechanism for the metal and not the destabilization of particles <0.45 μm. The dissolved metal concentrations in the highway runoff were considerably greater than the concentrations in the road runoff from Paper III, but despite this, and the use of different coagulation mechanisms, the removal effect was similar. Overall, chitosan exhibited lower removal efficiency for both particle content and metals than the other tested coagulants. Conversely, for the dissolved metal fraction, the use of chitosan produced both the highest and most consistent rates of removal compared to the conventional coagulants tested. Chitosan is known to interact with metal cations in aqueous solutions via mechanisms such as ion exchange and chelation (Guibal, 2004). Metal ion removal using chitosan has been observed in many metal cations (Zhang et al., 2016), including copper(II) and zinc(II) ions. In this thesis, chitosan was evaluated solely as a primary coagulant (Papers I and II), and it may perhaps be possible to achieve high particle and dissolved metal removal with a combined use of a metal salt coagulant with chitosan as a flocculant aid. 38

In metal-laden industrial wastewater, metal ions are most commonly removed using chemical precipitation (Ku and Jung, 2001). Metal precipitates can be achieved either in alkaline conditions using CaO (quicklime) to form hydroxide precipitates, or in acidic conditions using sulfide precipitation (bubbling H2S or in situ generation from organic matter by sulfate-reducing bacteria) (Fu and Wang, 2011). Chelation, ion exchange, and adsorption are also used for this purpose (Fu and Wang, 2011). Limewater was evaluated in Paper I, but was not selected for further testing due to handling issues and high pH (11.8) after treatment, which could have consequences for receiving water bodies (Wendelaar Bonga, 1997). Ultimately, the dissolved metal fraction comprised only a small portion of the total metal concentration in the snowmelt mixture and road runoff investigated in this thesis. Copper was the metal most often found in the dissolved fraction, followed by nickel. Optimal selection of coagulant(s) in stormwater treatment will therefore depend on the stormwater pollutant fractionation. The pollutants in the snowmelt mixture and road runoff were mostly particulate-associated, and therefore effective treatment meant primarily removal of particulate matter. 5.5. Removal of organic compounds The coagulation/flocculation process studied removed organic compounds, measured as hydrocarbon oil index (HOI) and PAH, to a sizable extent. HOI removal for the snowmelt mixture was over 80% (Paper II), and for the road runoff 98% (Figure 10). PAH removal, measured as the aggregate sum of the 16 EPA PAHs, was over 74% for the snowmelt mixture (Paper II), and 97% for the road runoff (Figure 10). The road runoff contained roughly twice the concentrations of HOI and PAH as the snowmelt mixture. Alkanes and PAHs are hydrophobic, and previous studies have shown a strong particulate association for PAHs (Ligocki et al., 1967; Lau and Stenstrom, 2005; Hwang and Foster, 2006) and aliphatic hydrocarbons (Ligocki et al., 1967). Furthermore, this particle affinity becomes stronger as the particle size decreases, especially for particles smaller than 2 μm (Baek et al., 1991; Kaupp and McLachlan, 2000). In addition, smaller PAHs tend to be predominantly found in the dissolved phase, while the larger PAHs tend to be found in the particulate phase (Nielsen et al., 2015). The vast majority of the PAHs (>95%) in the snowmelt mixture and road runoff were medium to high molecular weight, but since filtration was not performed, their phase distributions remain unknown. Together, this suggests that efficient removal of PAHs and aliphatic hydrocarbons in stormwater control measures entails proper removal of the particulate fraction. Removal of organic compounds measured as PAHs in a coagulation/flocculation process has not previously been studied in the stormwater context. One study reported removal rates of up to 95% of total hydrocarbons in a coagulation/flocculation/flotation stormwater treatment plant using alum and anionic polymers (Bernard et al., 1995), but the process was minimally described. Typically, an electrocoagulation process is employed in industrial wastewater plants treating hydrocarbon-rich influent, such as from coking or from oil refining (Chen, 2004), since this process has emulsion-breaking properties (Asselin et al.,

2008). A traditional coagulation/flocculation/flotation process has also proved successful in removing petroleum products from industrial wastewater (Santo et al., 2012). TOC and DOC are bulk parameters encompassing all organic compounds, including the PAHs and hydrocarbon oil index discussed previously. Prior studies on coagulation/flocculation of stormwater have not examined removal of TOC/DOC. In this thesis, the removal efficiency for TOC was on average 89% for the snowmelt mixture, and slightly lower for the road runoff (67%). The removal rates for TOC in the snowmelt mixture were much more consistent than for the road runoff, possibly due to a different composition of organic compounds. In drinking water treatment, removal of TOC is important as residual organic matter may form harmful disinfection byproducts, when chlorine compounds are added downstream in the process (Edzwald and Tobiason, 1999). En- hanced coagulation is the term for coagulation processes optimized for the removal of TOC, and the TOC removal effects observed in this thesis would be compliant with U.S. regulation (50% minimum removal for waters with >8.0 mg/L TOC and <60 mg/L as CaCO3 alkalinity) (USEPA, 1999, pp. 2–5). PIX-111 was the only coagulant that removed DOC (although with high variability), with 30% removal for the snowmelt mixture and 26% for the road runoff. Low removal effects for DOC is a problem sometimes encountered in drinking water treatment plants, and is generally attributed to changes in composition of the DOC (Sharp et al., 2006), which are often poorly understood (Goslan et al., 2004). Hydrophillic organic matter is less effectively removed than hydrophobic (Fearing et al., 2004; Parsons et al., 2004), and ferric coagulants perform better than aluminum coagulants (Sharp et al., 2006). These findings are in agreement with the finding that PIX-111 was the only coagulant to remove any DOC from both the snowmelt mixture and the road runoff. The composition of the DOC in the snowmelt mixture and the road runoff seemed generally unamenable to removal using coagulation/flocculation. 5.6. Coagulation process control parameters In treatment plants, the most common way to control the dosing in the coagulation process is through flow-proportional injection with a pre-determined dose obtained from jar-tests (Ratnaweera and Fettig, 2015). More advanced systems may be based on feed- back/feedforward loops with online measurements of turbidity and mathematical control schemes. Online zeta-potential measurements have been also utilized for dose control (Sharp et al., 2005). Even more advanced control methods employing multivariate statis- tics, such as partial least squares regression (Manamperuma et al., 2017), fuzzy models (Chen and Hou, 2006) or artificial neural networks (Yu et al., 2000) have been tested. In this thesis a naïve model selection using linear regression with bidirectional parameter elimination was used not for prediction or control but to identify the parameters that were important for the reduction of turbidity in the jar-tests for the snowmelt mixture and road runoff. Alkalinity and conductivity were identified as important parameters common for all the coagulants in the model selection using stepwise linear regression (Table 8). Measured

40 alkalinity was significantly higher for the road runoff than the urban snowmelt mixture, whereas the snowmelt mixture had slightly higher conductivity (Table 3). In the PCA analysis, one of the differentiating characteristics between the snowmelt mixture and the road runoff was the dissolved sodium concentration (Figure 7). Together these results may suggest that the ionic strength of the snowmelt mixture was higher, which may be indicative for the 1.5 to 3 times higher coagulant dose required for road runoff compared to the snowmelt mixture.

6. Conclusions

Jar-test experiments were conducted using two different types of stormwater: an urban snowmelt mixture and road runoff. The stormwater used in these studies was weakly buffered, with a slightly basic pH. From a coagulation process perspective, the alkalinity would be considered low. From the coagulation screening it was concluded that for the stormwater used in this thesis, a coagulation process using a high basicity coagulant has a wider operating envelope and is more suitable, since the effect on the water pH level is minimized. Removal efficiency of upward of 90%–99% of particle content was observed both in terms of turbidity and total suspended solids. The iron chloride coagulant (PIX- 111) produced higher removal rates than the pre-hydrolyzed aluminum coagulants, but caused a greater decrease in water pH. No measurable effect in terms of increased removal efficiency or reduced coagulant use was observed with the addition of a flocculant aid. The use of zeta potential was investigated as an indicator for particle destabilization; in the snowmelt mixture, a maximum treatment effect was observed between -14 and +1 mV. However, the measurements were not robust enough for analysis when performed in the experimental setup with the road runoff, and no conclusions could be made from that experimental set. Charge reversal occurred at higher coagulant doses in both the snowmelt mixture and the road runoff. This observation, in conjunction with the snowmelt mixture zeta potential measurements, indicates that charge neutralization was the dominant coagulation mechanism. The treatment effect of a sweep floc mechanism was not investigated, and to achieve sweep floc coagulation and would likely require pH adjustment of the stormwater. Particulate or particle-associated pollutants were removed by over 90% on average from the snowmelt mixture as measured by total metal fraction (cadmium, chromium, copper, lead, nickel and zinc), polycyclic aromatic hydrocarbons, hydrocarbon oil index, and total organic carbon. Results were similar for road runoff, except total organic carbon was removed to a lesser degree (66% compared to 88% for the snowmelt mixture). Removal effects for the dissolved pollutants were lower than for the particulate and particle-associated pollutants. In the snowmelt mixture, fewer metals were quantifiable and with lower concentrations compared to the road runoff, although the removal efficiencies were similar. The dissolved fractions of chromium, copper and lead could be removed by an average of 40%, whereas the dissolved fractions for nickel and zinc increased with the use of metal salt coagulants as a result of decreased pH. Chitosan was the only coagulant that produced a treatment effect for all the metals investigated in the dissolved fraction. The iron chloride coagulant was the only evaluated coagulant that had a treatment effect on the dissolved organic fraction, reducing it by approximately 25%–30%. Analysis of particle size distributions using both surface area and number as the transformation basis indicated that the sedimentation control removed coarser particles and

43 shifted the mode of the distribution towards smaller particles (<1 μm). The coagulation/flocculation treatment did have an effect on this colloidal particle fraction and a clear shift towards larger particles was observed. In a naïve linear regression model, alkalinity and conductivity were found to be important parameters for the outcome of the coagulation process with regard to turbidity reduction. The PCA analysis defined dissolved sodium as one of that the differentiating characteristic of the snowmelt mixture as compared to the road runoff, and the conductivity of the snowmelt mixture was slightly higher than the road runoff. Both are related to the ionic strength and may be part of the explanation why the road runoff required 1.5 to 3 times the coagulant dose to treat, as the snowmelt mixture.

References

Andersson, J.T., Achten, C., 2015. Time to Say Goodbye to the 16 EPA PAHs? Toward an Up-to-Date Use of PACs for Environmental Purposes. Polycycl. Aromat. Compd. 35, 330–354. https://doi.org/10.1080/10406638.2014.991042 Asselin, M., Drogui, P., Brar, S.K., Benmoussa, H., Blais, J.-F., 2008. Organics removal in oily bilgewater by electrocoagulation process. J. Hazard. Mater. 151, 446–455. https://doi.org/10.1016/J.JHAZMAT.2007.06.008 Bachand, P.A.M., Bachand, S.M., Lopus, S.E., Heyvaert, A., Werner, I., 2010. Treatment with chemical coagulants at different dosing levels changes ecotoxicity of stormwater from the Tahoe basin, California, USA. J. Environ. Sci. Heal. Part A 45, 137–154. https://doi.org/10.1080/10934520903425459 Bachand, P.A.M., Heyvaert, A.C., Prentice, S.E., Delaney, T., 2010. Feasibility Study and Conceptual Design for Using Coagulants to Treat Runoff in the Tahoe Basin. J. Environ. Eng. 136, 1218–1230. https://doi.org/10.1061/(asce)ee.1943- 7870.0000261 Bäckström, M., 2002. Sediment transport in grassed swales during simulated runoff events. Water Sci. Technol. 45, 41–49. https://doi.org/10.2166/wst.2002.0115 Baek, S.O., Field, R.A., Goldstone, M.E., Kirk, P.W., Lester, J.N., Perry, R., 1991. A review of atmospheric polycyclic aromatic hydrocarbons: Sources, fate and behavior. Water. Air. Soil Pollut. 60, 279–300. https://doi.org/10.1007/BF00282628 Barbosa, A.E., Fernandes, J.N., David, L.M., 2012. Key issues for sustainable urban stormwater management. Water Res. 46, 6787–6798. https://doi.org/10.1016/j.watres.2012.05.029 Bennett, E.R., Linstedt, K.D., Nilsgard, V., Battaglia, G.M., Pontius, F.W., 1981. Urban Snowmelt-Characteristics and Treatment. J. Water Pollut. Control Fed. 53, 119– 125. https://doi.org/10.2307/25041025 Bernard, C., Herviou, P., Poujol, T., 1995. Stormwater treatment by dissolved air flotation: First results from a pilot project. Water Sci. Technol. https://doi.org/10.1016/0273-1223(95)00548-2 Borris, M., Österlund, H., Marsalek, J., Viklander, M., 2016. Contribution of coarse particles from road surfaces to dissolved and particle-bound heavy metal loads in runoff: A laboratory leaching study with synthetic stormwater. Sci. Total Environ. 573, 212–221. https://doi.org/10.1016/j.scitotenv.2016.08.062 Bratby, J., 2016. Coagulation and Flocculation in Water and Wastewater treatment, Third. ed. IWA Publishing, London. Bryan Ellis, J., Revitt, D.M., 1982. Incidence of heavy metals in street surface sediments: Solubility and grain size studies. Water. Air. Soil Pollut. 17, 87–100. https://doi.org/10.1007/BF00164094

Characklis, G.W., Wiesner, M.R., 2002. Particles, Metals, and Water Quality in Runoff from Large Urban Watershed. J. Environ. Eng. 123, 753–759. https://doi.org/10.1061/(asce)0733-9372(1997)123:8(753) Charters, F.J., Cochrane, T.A., O’Sullivan, A.D., 2015. Particle size distribution variance in untreated urban runoff and its implication on treatment selection. Water Res. 85, 337–345. https://doi.org/10.1016/j.watres.2015.08.029 Chen, C.-L., Hou, P.-L., 2006. Fuzzy model identification and control system design for coagulation chemical dosing of potable water. Water Sci. Technol. Water Supply 6, 97–104. https://doi.org/10.2166/ws.2006.782 Chen, G., 2004. Electrochemical technologies in wastewater treatment. Sep. Purif. Technol. 38, 11–41. https://doi.org/10.1016/j.seppur.2003.10.006 Clark, S.E., Pitt, R., 2012. Targeting treatment technologies to address specific stormwater pollutants and numeric discharge limits. Water Res. 46, 6715–6730. https://doi.org/10.1016/j.watres.2012.07.009 Deletic, A., 1998. The first flush load of urban surface runoff. Water Res. 32, 2462– 2470. https://doi.org/10.1016/S0043-1354(97)00470-3 Derjaguin, B., Landau, L., 1993. Theory of the stability of strongly charged lyophobic sols and of the adhesion of strongly charged particles in solutions of electrolytes. Prog. Surf. Sci. 43, 30–59. https://doi.org/10.1016/0079-6816(93)90013-L Ding, Y., Dresnack, R., Chan, P.C., 2001. Mechanism and feasibility of colloidal particle removal by a microcarrier process. Int. J. Environ. Stud. 58, 535–548. https://doi.org/10.1080/00207230108711349 Duan, J., Gregory, J., 2003. Coagulation by hydrolysing metal salts. Adv. Colloid Interface Sci. 100–102, 475–502. https://doi.org/10.1016/S0001-8686(02)00067-2 Edzwald, J.K., Tobiason, J.E., 1999. Enhanced coagulation: US requirements and a broader view. Water Sci. Technol. 40, 63–70. https://doi.org/10.1016/S0273- 1223(99)00641-1 Edzwald, J.K., Upchurch, J.B., O’Melia, C.R., 1974. Coagulation in estuaries. Environ. Sci. Technol. 8, 58–63. https://doi.org/10.1021/es60086a003 EPA, 2010. National Pollution Discharge Elimination System (NPDES) Permit Writers’ Manual. United States Environmental Protection Agency, Washington, D.C. Eriksson, E., Baun, A., Scholes, L., Ledin, A., Ahlman, S., Revitt, M., Noutsopoulos, C., Mikkelsen, P.S., 2007. Selected stormwater priority pollutants — a European perspective. Sci. Total Environ. 383, 41–51. https://doi.org/10.1016/J.SCITOTENV.2007.05.028 European Committee for Standardization. (1994). Water quality. Determination of alkalinity. Determination of total and composite alkalinity (EN Standard No. 9963). Brussels, Belgium.

European Committee for Standardization. (1997). Water analysis – Guidelines for the determination of total organic carbon (TOC) and dissolved organic carbon (DOC) (EN Standard No. 1484). Brussels, Belgium. European Committee for Standardization. (2005). Water quality – Determination of suspended solids. Method by filtration through glass fibre filters (EN Standard No. 872). Brus- sels, Belgium. European Parliament, C. of the E.U., 2000. Directive of the European Parliament and of the Council Establishing a Fraework for Community Action in the Field of Water Policy (2000/60/EC), 2000/60/EC. ed, Official Journal of the European Union. Fearing, D.A., Banks, J., Guyetand, S., Monfort Eroles, C., Jefferson, B., Wilson, D., Hillis, P., Campbell, A.T., Parsons, S.A., 2004. Combination of ferric and MIEX® for the treatment of a humic rich water. Water Res. 38, 2551–2558. https://doi.org/10.1016/J.WATRES.2004.02.020 Fu, F., Wang, Q., 2011. Removal of heavy metal ions from wastewaters: A review. J. Environ. Manage. 92, 407–418. https://doi.org/10.1016/j.jenvman.2010.11.011 German, J., Svensson, G., 2002. Metal content and particle size distribution of street sediments and street sweeping waste. Water Sci. Technol. 46, 191–198. https://doi.org/10.2166/wst.2002.0679 Goslan, E.H., Voros, S., Banks, J., Wilson, D., Hillis, P., Campbell, A.T., Parsons, S.A., 2004. A model for predicting dissolved organic carbon distribution in a reservoir water using fluorescence spectroscopy. Water Res. 38, 783–791. https://doi.org/10.1016/J.WATRES.2003.10.027 Gromaire-Mertz, M.C., Garnaud, S., Gonzalez, A., Chebbo, G., 1999. Characterisation of urban runoff pollution in Paris. Water Sci. Technol. 39, 1–8. https://doi.org/10.1016/S0273-1223(99)00002-5 Grout, H., Wiesner, M.R., Bottero, J.Y., 1999. Analysis of colloidal phases in urban stormwater runoff. Environ. Sci. Technol. 33, 831–839. https://doi.org/10.1021/es980195z Guibal, E., 2004. Interactions of metal ions with chitosan-based sorbents: A review. Sep. Purif. Technol. 38, 43–74. https://doi.org/10.1016/j.seppur.2003.10.004 Han, J., Wu, J.S., Allan, C., 2005. Suspended Sediment Removal by Vegetative Filter Strip Treating Highway Runoff. J. Environ. Sci. Heal. Part A 40, 1637–1649. https://doi.org/10.1081/ESE-200060683 Harper, H.H., 2007. Current Research and Trends in Alum Treatment of Stormwater Runoff, in: Proceedings of the 3rd Biennial Stormwater Management Research Symposiunm. Orlando, p. 14. Harper, H.H., D, P., Herr, J.L., Livingston, E.H., 1999. Alum treatment of stormwater runoff: An innovative BMP for urban runoff problems, in: National Conference on Retrofit Opportunities for Water Resource Protection in Urban Environments.

Heinzmann, B., 1994. Coagulation and flocculation of stormwater from a separate sewer system - a new possibility for enhanced treatment. Water Sci. Technol. 29, 267– 278. Herngren, L., Goonetilleke, A., Ayoko, G.A., 2006. Analysis of heavy metals in road- deposited sediments. Anal. Chim. Acta 571, 270–278. https://doi.org/10.1016/j.aca.2006.04.064 Herrmann, R., 1981. Transport of polycyclic aromatic hydrocarbons through a partly urbanized river basin. Water. Air. Soil Pollut. 16, 445–467. https://doi.org/10.1007/BF01048135 Hill, J.R., Bouwhuis, R.F., Kilgour, B.W., Francis, A.P., Proulx, C.L., 2018. Using a conductivity–alkalinity relationship as a tool to identify surface waters in reference condition across Canada. Water Qual. Res. J. 53, 231–240. https://doi.org/10.2166/wqrj.2018.030 Hoffman, E.J., Latimer, J.S., Hunt, C.D., Mills, G.L., Quinn, J.G., 1985. Stormwater runoff from highways. Water. Air. Soil Pollut. 25, 349–364. https://doi.org/10.1007/BF00283788 Huang, C., Chen, Y., 1996. Coagulation of Colloidal Particles in Water by Chitosan. J. Chem. Technol. Biotechnol. 66, 227–232. https://doi.org/10.1002/(SICI)1097- 4660(199607)66:3 Hunter, K.A., Liss, P.S., 1979. The surface charge of suspended particles in estuarine and coastal waters. Nature 282, 823–825. https://doi.org/10.1038/282823a0 Hunter, R.J., 1981. Zeta Potential in Colloid Science, 1st ed. Elsevier. https://doi.org/10.1016/C2013-0-07389-6 Hwang, H.-M., Foster, G.D., 2006. Characterization of polycyclic aromatic hydrocarbons in urban stormwater runoff flowing into the tidal Anacostia River, Washington, DC, USA. Environ. Pollut. 140, 416–426. https://doi.org/10.1016/J.ENVPOL.2005.08.003 International Organization for Standardization. (1996). Water Quality – Determination of certain organochlorine insecticides, polychlorinated biphenyls and chlorobenzenes – Gas chro- matographic method after liquid-liquid extraction (ISO Standard No. 6468). Geneva, Swit- zerland. International Organization for Standardization. (2000). Water quality – Determination of hydrocarbon oil index – Part 2: Method using solvent extraction and gas chromatography (ISO Standard No. 9377-2). Geneva, Switzerland. International Organization for Standardization. (2004). Water quality – Application of inductively coupled plasma mass spectrometry (ICP-MS) (ISO Standard No. 17294). Geneva, Switzerland. International Organization for Standardization. (2007). Water quality – Determination of selected elements by inductively coupled plasma optimal spectrometry (ICP-OES) (ISO Stand- ard No. 11885). Geneva, Switzerland.

Isteniç, D., Arias, C.A., Vollertsen, J., Nielsen, A.H., Wium-Andersen, T., Hvitved- Jacobsen, T., Brix, H., 2012. Improved urban stormwater treatment and pollutant removal pathways in amended wet detention ponds. J. Environ. Sci. Heal. - Part A Toxic/Hazardous Subst. Environ. Eng. 47, 1466–1477. https://doi.org/10.1080/10934529.2012.673306 IUPAC, 2007. Environmental Colloids and Particles, Environmental Colloids and Particles. John Wiley & Sons, Ltd, Chichester, UK. https://doi.org/10.1002/9780470024539 Jackson, D.A., 1993. Stopping rules in principal components analysis: A comparison of heuristical and statistical approaches. Ecology 74, 2204–2214. https://doi.org/10.2307/1939574 JCGM 100:2008, 2008. Evaluation of measurement data - Guide to the expression of uncertainty in measurement. Joint Committee for Guides in Metrology, Paris. Judd, S.J., Hillis, P., 2001. Optimisation of combined coagulation and microfiltration for water treatment. Water Res. 35, 2895–2904. https://doi.org/10.1016/S0043- 1354(00)00586-8 Kang, J.-H., Li, Y., Lau, S.-L., Kayhanian, M., Stenstrom, M.K., 2007. Particle destabilization in highway runoff to optimize pollutant removal. J. Environ. Eng. 133, 426–434. https://doi.org/10.1061/(ASCE)0733-9372(2007)133:4(426) Karlsson, K., Blecken, G.-T., Öhlander, B., Viklander, M., 2016. Environmental Risk Assessment of Sediments Deposited in Stormwater Treatment Facilities: Trace Metal Fractionation and Its Implication for Sediment Management. J. Environ. Eng. 142. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001122 Kaupp, H., McLachlan, M.S., 2000. Distribution of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polycyclic aromatic hydrocarbons (PAHs) within the full size range of atmospheric particles. Atmos. Environ. 34, 73–83. https://doi.org/10.1016/S1352-2310(99)00298-8 Kayhanian, M., Stransky, C., Bay, S., Lau, S.-L., Stenstrom, M.K., 2008. Toxicity of urban highway runoff with respect to storm duration. Sci. Total Environ. 389, 386– 406. https://doi.org/10.1016/j.scitotenv.2007.08.052 Keith, L.H., 2015. The Source of U.S. EPA’s Sixteen PAH Priority Pollutants. Polycycl. Aromat. Compd. 35, 147–160. https://doi.org/10.1080/10406638.2014.892886 Ku, Y., Jung, I.-L., 2001. Photocatalytic reduction of Cr(VI) in aqueous solutions by UV irradiation with the presence of titanium dioxide. Water Res. 35, 135–142. https://doi.org/10.1016/S0043-1354(00)00098-1 Langmuir, D., 1997. Aqueous environmental geochemistry. Prentice Hall, New Jersey. Lau, S.-L., Stenstrom, M.K., 2005. Metals and PAHs adsorbed to street particles. Water Res. 39, 4083–4092. https://doi.org/10.1016/J.WATRES.2005.08.002 Lawler, D.F., 1993. Physical Aspects of Flocculation: From Microscale to Macroscale. Water Sci. Technol. 27, 165–180. https://doi.org/10.2166/wst.1993.0226

Li, Y., Lau, S.-L., Kayhanian, M., Stenstrom, M.K., 2006. Dynamic Characteristics of Particle Size Distribution in Highway Runoff: Implications for Settling Tank Design. J. Environ. Eng. 132, 852–861. https://doi.org/10.1061/(ASCE)0733- 9372(2006)132:8(852) Ligocki, M.P., Leuenberger, C., Pankow, J.F., 1967. Trace organic compounds in rain— III. Particle scavenging of neutral organic compounds. Atmos. Environ. 19, 1619– 1626. https://doi.org/10.1016/0004-6981(85)90214-8 Lin, C.-C., Chen, S.-J., Huang, K.-L., Hwang, W.-I., Chang-Chien, G.-P., Lin, W.- Y., 2005. Characteristics of Metals in Nano/Ultrafine/Fine/Coarse Particles Collected Beside a Heavily Trafficked Road. Environ. Sci. Technol. 39, 8113–8122. https://doi.org/10.1021/es048182a Lin, H., Wall, L., Sansalone, J., 2004. Aggregation of Stormwater Particulates - Suspended Particle Gradations and Setting Column Analysis, in: Global Solutions for Urban Drainage. American Society of Civil Engineers, Reston, VA, pp. 1–15. https://doi.org/10.1061/40644(2002)208 Lindfors, S., Österlund, H., Viklander, M., 2017. Truly dissolved and labile Cu and Zn in urban runoff from a parking lot, an industrial area and copper and zinc roofs, in: 14th IWA/IAHR International Conference on Urban Drainage: Conference Proceedings, 2017, Prague, 2017, : Lopus, S.E., Bachand, P.A.M., Heyvaert, A.C., Werner, I., Teh, S.J., Reuter, J.E., 2009. Potential toxicity concerns from chemical coagulation treatment of stormwater in the Tahoe basin, California, USA. Ecotoxicol. Environ. Saf. 72, 1933–1941. https://doi.org/10.1016/j.ecoenv.2009.04.004 Lytle, D., 1995. How do I run a proper jar test procedure? U.S. Environmental Protection Agency, Washington, D.C. Manamperuma, L., Wei, L., Ratnaweera, H., 2017. Multi-parameter based coagulant dosing control. Water Sci. Technol. 75, 2157–2162. https://doi.org/10.2166/wst.2017.058 McCleskey, B.B., Nordstrom, K.K., Ryan, J.N., 2012. Comparison of electrical conductivity calculation methods for natural waters. Limnol. Oceanogr. Methods 10, 952–967. https://doi.org/10.4319/lom.2012.10.952 McKenzie, E.R., Wong, C.M., Green, P.G., Kayhanian, M., Young, T.M., 2008. Size dependent elemental composition of road-associated particles. Sci. Total Environ. 398, 145–153. https://doi.org/10.1016/j.scitotenv.2008.02.052 Meland, S., 2016. Management of contaminated runoff water : current practice and future research needs. Conference of European Directors of Roads, Brussels. Moghadas, S., Paus, K.H., Muthanna, T.M., Herrmann, I., Marsalek, J., Viklander, M., 2015. Accumulation of Traffic-Related Trace Metals in Urban Winter-Long Roadside Snowbanks. Water. Air. Soil Pollut. 226, 1–15. https://doi.org/10.1007/s11270-015-2660-7

Morrison, G.M.P., Revitt, D.M., Ellis, J.B., 1990. Metal Speciation in Separate Stormwater Systems. Water Sci. Technol. 22, 53–60. https://doi.org/10.2166/wst.1990.0288 Mosley, L.M., Hunter, K.A., Ducker, W.A., 2003. Forces between colloid particles in natural waters. Environ. Sci. Technol. 37, 3303–3308. https://doi.org/10.1021/es026216d Nielsen, K., Kalmykova, Y., Strömvall, A.M., Baun, A., Eriksson, E., 2015. Particle phase distribution of polycyclic aromatic hydrocarbons in stormwater - Using humic acid and iron nano-sized colloids as test particles. Sci. Total Environ. 532, 103–111. https://doi.org/10.1016/j.scitotenv.2015.05.093 Oliver, B.G., Milne, J.B., Labarre, N., 1974. Chloride and lead in urban snow. Water Pollut. Control Fed. 46, 766–771. https://doi.org/10.2307/25038190 Parsons, S.A., Jefferson, B., Goslan, E.H., Jarvis, P.R., Fearing, D.A., 2004. Natural organic matter – the relationship between character and treatability. Water Sci. Technol. Water Supply 4, 43–48. https://doi.org/10.2166/ws.2004.0091 Pettersson, T.J.R., 1998. Water quality improvement in a small stormwater detention pond. Water Sci. Technol. 38, 115–122. https://doi.org/10.1016/S0273- 1223(98)00740-9 Preciado, H.F., Li, L.Y., 2006. Evaluation of Metal Loadings and Bioavailability in Air, Water and Soil Along Two Highways of British Columbia, Canada. Water. Air. Soil Pollut. 172, 81–108. https://doi.org/10.1007/s11270-005-9063-0 R Core Team, 2019. R: A Language and Environment for Statistical Computing. Rathnaweera, S.S., 2010. Modelling and optimisation of wastewater coagulation process. Norwegian University of Life Sciences. Ratnaweera, H., Fettig, J., 2015. State of the art of online monitoring and control of the coagulation process. Water (Switzerland) 7, 6574–6597. https://doi.org/10.3390/w7116574 Ratnaweera, H., Ødegaard, H., Fettig, J., 1992. Coagulation with Prepolymerized Aluminium Salts and their Influence on Particle and Phosphate Removal. Water Sci. Technol. 26, 1229–1237. https://doi.org/10.2166/wst.1992.0565 Renault, F., Sancey, B., Badot, P.-M., Crini, G., 2009. Chitosan for coagulation/flocculation processes – An eco-friendly approach. Eur. Polym. J. 45, 1337–1348. https://doi.org/10.1016/J.EURPOLYMJ.2008.12.027 Riktvärdesgruppen, 2009. Förslag till riktvärden för dagvattenutsläpp [Proposal for stormwater discharge limits]. Regionplane- och trafikkontoret, Stockholm. Rossini, M., Garrido, J.G., Galluzzo, M., 1999. Optimization of the coagulation– flocculation treatment: influence of rapid mix parameters. Water Res. 33, 1817– 1826. https://doi.org/10.1016/S0043-1354(98)00367-4

Sansalone, J.J., Buchberger, S.G., 1997a. Partitioning and First Flush of Metals in Urban Roadway Storm Water. J. Environ. Eng. 123, 134–143. https://doi.org/10.1061/(ASCE)0733-9372(1997)123:2(134) Sansalone, J.J., Buchberger, S.G., 1997b. Characterization of solid and metal element distributions in urban highway stormwater. Water Sci. Technol. 36, 155–160. https://doi.org/10.2166/wst.1997.0659 Sansalone, J.J., Kim, J.Y., 2008. Suspended particle destabilization in retained urban stormwater as a function of coagulant dosage and redox conditions. Water Res. 42, 909–922. https://doi.org/10.1016/j.watres.2007.08.037 Santo, C.E., Vilar, V.J.P., Botelho, C.M.S., Bhatnagar, A., Kumar, E., Boaventura, R.A.R., 2012. Optimization of coagulation–flocculation and flotation parameters for the treatment of a petroleum refinery effluent from a Portuguese plant. Chem. Eng. J. 183, 117–123. https://doi.org/10.1016/J.CEJ.2011.12.041 Sauvé, S., Hendershot, W., Allen, H.E., 2000. Solid-solution partitioning of metals in contaminated soils: Dependence on pH, total metal burden, and organic matter. Environ. Sci. Technol. 34, 1125–1131. https://doi.org/10.1021/es9907764 Sharp, E.L., Banks, J., Billica, J.A., Gertig, K.R., Henderson, R., Parsons, S.A., Wilson, D., Jefferson, B., 2005. Application of zeta potential measurements for coagulation control: Pilot-plant experiences from UK and US waters with elevated organics. Water Sci. Technol. Water Supply 5, 49–56. Sharp, E.L., Parsons, S.A., Jefferson, B., 2006. Seasonal variations in natural organic matter and its impact on coagulation in water treatment. Sci. Total Environ. 363, 183–194. https://doi.org/10.1016/j.scitotenv.2005.05.032 Shin, J.Y., Spinette, R.F., O’Melia, C.R., 2008. Stoichiometry of Coagulation Revisited. Environ. Sci. Technol. 42, 2582–2589. https://doi.org/10.1021/es071536o Simo, R., Grimalt, J.O., Albaiges, J., 1997. Loss of unburned-fuel hydrocarbons from combustion aerosols during atmospheric transport. Environ. Sci. Technol. 31, 2697– 2700. https://doi.org/10.1021/es960994m Smoluchowski, M., 1918. Versuch einer mathematischen Theorie der Koagulationskinetik kolloider Lösungen [An attempt for a mathematical theory of coagulation kinetics of colloidal solutions]. Zeitschrift für Phys. Chemie 92, 129– 168. Stumm, W., Morgan, J., 1962. Chemical aspects of coagulation. J. Am. Water Work. Assoc. 54, 971–994. Stumm, W., O’Melia, C.R., 1968. Stoichiometry of Coagulation. J. Am. Water Work. Assoc. 60, 514–539. Tapp, J.S., Barfield, B.J., 1986. Modeling the Flocculation Process in Sediment Ponds. Trans. Am. Soc. Agric. Eng. 29, 741–747.

Thomas, D.N., Judd, S.J., Fawcett, N., 1999. Flocculation modelling: a review. Water Res. 33, 1579–1592. https://doi.org/10.1016/S0043-1354(98)00392-3 Trejo-Gaytan, J., Bachand, P., Darby, J., 2006. Treatment of urban runoff at Lake Tahoe: Low-intensity chemical dosing. Water Environ. Res. 78, 2487–2500. https://doi.org/10.2175/106143006X102042 Trenouth, W.R., Gharabaghi, B., 2015. Soil amendments for heavy metals removal from stormwater runoff discharging to environmentally sensitive areas. J. Hydrol. 529, 1478–1487. https://doi.org/10.1016/j.jhydrol.2015.08.034 Tuccillo, M.E., 2006. Size fractionation of metals in runoff from residential and highway storm sewers. Sci. Total Environ. 355, 288–300. https://doi.org/10.1016/j.scitotenv.2005.03.003 USEPA, 1999. Enhanced Coagulation and Enhanced Precipitative Softening Guidance Manual. Van Benschoten, J.E., Edzwald, J.K., 1990. Chemical aspects of coagulation using aluminum salts - I. Hydrolytic reactions of alum and polyaluminum chloride. Water Res. 24, 1519–1526. https://doi.org/10.1016/0043-1354(90)90086-L Verwey, E.J.W., Overbeek, J.T.G., 1946. Long distance forces acting between colloidal particles. Trans. Faraday Soc. 42, B117. https://doi.org/10.1039/tf946420b117 Viklander, M., 1999. Dissolved and particle-bound substances in urban snow. Water Sci. Technol. 39, 27–32. https://doi.org/10.2166/wst.1999.0525 Wendelaar Bonga, S.E., 1997. The stress response in fish. Physiol. Rev. 77, 591–625. https://doi.org/10.1152/physrev.1997.77.3.591 Westerlund, C., Viklander, M., 2011. Pollutant release from a disturbed urban snowpack in northern Sweden. Water Qual. Res. J. Canada 46, 98–109. https://doi.org/10.2166/wqrjc.2011.025 Westerlund, C., Viklander, M., Bäckström, M., 2003. Seasonal variations in road runoff quality in Lulea. Sweden Water Sci. Technol. 48, 93–101. 93–101. Wickham, H., 2016. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. Wickham, H., 2014. Tidy data. J. Stat. Softw. 59. Xanthopoulos, C., Augustin, A., 1992. Input and Characterization of Sediments in Urban Sewer Systems. Water Sci. Technol. 25, 21–28. https://doi.org/10.2166/wst.1992.0175 Ye, C., Wang, D., Shi, B., Yu, J., Qu, J., Edwards, M., Tang, H., 2007. Alkalinity effect of coagulation with polyaluminum chlorides: Role of electrostatic patch. Colloids Surfaces A Physicochem. Eng. Asp. 294, 163–173. https://doi.org/10.1016/j.colsurfa.2006.08.005

Yu, R.-F., Kang, S.-F., Liaw, S.-L., Chen, M. -c., 2000. Application of artificial neural network to control the coagulant dosing in water treatment plant. Water Sci. Technol. 42, 403–408. https://doi.org/10.2166/wst.2000.0410 Zanders, J.M., 2005. Road sediment: characterization and implications for the performance of vegetated strips for treating road run-off. Sci. Total Environ. 339, 41–47. https://doi.org/10.1016/j.scitotenv.2004.07.023 Zhang, L., Zeng, Y., Cheng, Z., 2016. Removal of heavy metal ions using chitosan and modified chitosan: A review. J. Mol. Liq. 214, 175–191. https://doi.org/10.1016/J.MOLLIQ.2015.12.013