LICENTIATE T H E S I S

ISSN 1402-1757ISBN 978-91-7790-697-1 (print)ISBN 978-91-7790-698-8 (pdf)

Luleå University of Technology 2020

Snežana Gavrić E

nhancement of storm

water quality in grass sw

ales

Department of Civil, Environmental and Natural Resources EngineeringDivision of Architecture and Water

Enhancement of stormwater

quality in grass swales:Removal and immobilisation of metals

Snežana Gavrić

Urban Water Engineering

131907-LTU-Gavric.indd Alla sidor131907-LTU-Gavric.indd Alla sidor 2020-11-13 10:092020-11-13 10:09

Enhancement of stormwater quality

in grass swales: Removal and immobilisation of metals

Snežana Gavrić

Luleå, 2020

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 2020

ISSN 1402-1757

ISBN: 978-91-7790-697-1 (print)

ISBN: 978-91-7790-698-8 (pdf)

Luleå 2020

www.ltu.se

i

Preface This licentiate thesis presents a summary of my research work carried out in the Urban

Water Engineering research group in the Department of Civil, Environmental and

Natural Resources Engineering at Luleå University of Technology. The work was carried

out as a part of a research cluster Stormwater&Sewers, a collaboration between Swedish

municipalities of Luleå, Skellefteå, Östersund, Boden, municipal water organisations

Vakin, MittSverige Vatten & Avfall, VASYD, the Swedish Water & Wastewater

Association, and the Urban Water Engineering research group. The research was

financed by the Swedish Research Council Formas (Grant no. 2015-778) and

DRIZZLE-Center for Stormwater management, funded by the Swedish Governmental

Agency for Innovation System (Vinnova), project 2016-05176.

First and foremost, I would like to express my great gratitude to my supervisors Maria

Viklander and Günther Leonhardt for their supervision, valuable feedback and

encouragement throughout the years. My great gratitude also goes to Jiri Marsalek and

Heléne Österlund. Thank you Jiri, for your scientific guidance at some pivotal moments

in my studies, for sharing your great knowledge with me and for all the feedback and

valuable comments. Heléne, thank you for your advice and support and help with both

practical and scientific questions. I also would like to thank Anna-Maria Perttu for her

help during my first months as a PhD student and Alexandra, for the help with Swedish

translations.

The field study would not be possible without the help of the staff from Luleå

municipality who helped me with logistics and provided me with information about the

studied catchments. I want to thank Peter Rosander for helping me to make my soil

sampler and solve all other practical issues. I want to thank Stefan Marklund for help in

contacting people from kommun and Kerstin Nordqvist for her help in the laboratory. I

also want to thank all my colleagues in the Urban Water Engineering research group for

providing friendly work environment.

Finally, I would like to thank all the people that made my time in Luleå pleasant: my

tango group for welcoming me in their community and my friends from other research

groups for fun times away from work. I want to thank all my family and friends in Serbia,

and especially my parents, Boško and Milica, thank you for all the love and support. To

Ivan, for being such a wonderful father, which enabled me to fully concentrate at work.

Thank you for believing in me and helping me manage everything at work and home.

To Luka, my wonderful boy, I love you dearly, thank you for being you.

Snežana Gavrić Luleå, November 2020

ii

iii

Abstract Grass swales are common elements of green drainage infrastructure used in urban

catchments to provide stormwater quantity and quality control. Concerning stormwater

quantity, swales convey runoff and attenuate stormwater volumes and peaks by enhancing

hydrological abstractions and providing dynamic storage. Furthermore, grass swales are

effective in treating stormwater runoff from trafficked surfaces. Swales are typically

designed as long shallow channels with dense grass and permeable soils, and thereby create

favourable conditions along the turf-stormwater interface for processes enhancing

stormwater quality and reducing pollutant concentrations in swale effluents.

The thesis aim is to advance the knowledge of short-term performance of grass swales in

removal of total metals, with respect to such influential factors as concentrations of metals

and solids (TSS) in the inflow, swale geometry, and grass-soil characteristics. The

literature reviewed showed that solids were the most frequently investigated parameter

and the enhancement of stormwater quality by settling gained most attention in the earlier

research. On the other hand, studies of swale performance in removal of other stormwater

pollutants, such as total and dissolved metals, were limited, as was the understanding of

the physical-chemical-biological processes facilitating the removal of other-than-solids

pollutants.

Since swales are generally recognized as being effective in removing metals from

stormwater through infiltration into swale soils, and the associated metal immobilisation

in soils, long-term operation of swales may lead to accumulation of pollutants in, and

contamination of, swale soils. Such conditions need to be remedied by relatively costly

swale maintenance. A field study was conducted to characterize the soil chemistry of

three swales, which serve for stormwater drainage and winter storage of snow cleared

from adjacent trafficked areas. The swales studied served three catchments with different

land use in the City of Luleå. Swales provided drainage of commercial, downtown, and

residential catchments and drained roads with various traffic intensities. The study

findings showed that the soil in the oldest swale, next to the road with the highest traffic

intensity, contained the highest concentrations of most of the investigated metals. For

example, the mean lead (Pb) concentration at this swale was ~70 mg/kg DW, compared

to

iv

v

Sammanfattning Svackdiken är ett vanligt inslag i grön infrastruktur, som i urbana områden används för

att kontrollera dagvattenflöden gällande både kvantitet och kvalitet. Svackdiken reglerar

dagvattenkvantitet genom att transportera avrinning och dämpa både dagvattenvolymer

och toppflöden via ökade hydrologiska abstraktioner och tillhandahållande av dynamisk

lagring. Dessutom är svackdiken effektiva för att rena dagvattenavrinning från trafikerade

ytor. Svackdiken utformas vanligtvis som långa, grunda, kanaler med tätt gräs och

permeabel jord och skapar därigenom gynnsamma förhållanden längs med gränssnittet

gräs-dagvatten för processer som förbättrar dagvattenkvalitet och reducerar

föroreningskoncentrationer i utsläpp från svackdiken.

Avhandlingens mål är att öka kunskapen om kortsiktig prestanda hos svackdiken avseende

avlägsnandet av metaller, med hänsyn till påverkande faktorer såsom koncentrationer av

metaller och partiklar (TSS) i inflödet, svackdikets geometri samt egenskaper hos gräs och

jord. Litteraturstudien visade att partiklar var den mest frekvent studerade parametern och

att förbättring av dagvattenkvaliteten genom sedimentation fick mest uppmärksamhet i

tidigare forskning. Å andra sidan var studier av svackdikens prestanda med avseende på

avlägsnande av andra dagvattenföroreningar, såsom totala och lösta metaller, begränsade,

liksom förståelsen av de fysikaliska-kemiska-biologiska processerna som främjar

avlägsnandet av andra föroreningar än partiklar.

Eftersom svackdiken allmänt anses vara effektiva för att avlägsna metaller från dagvatten

genom infiltration och associerad metallimmobilisering i jord, kan långsiktig användning

av svackdiken leda till ackumulation av föroreningar i, och kontamination av, svackdikens

jordar. Sådana förhållanden behöver åtgärdas med relativt kostsamt underhåll. En

fältstudie genomfördes för att karaktärisera markkemin i tre svackdiken som används för

dagvattenavledning och vinterförvaring av snö undanröjd från intilliggande

trafikområden. De studerade svackdikena, tjänade tre avrinningsområden med olika

markanvändning i Luleå. Svackdikena avleder avrinning från ett handelsområde,

innerstad och bostadsområde och med vägar av olika trafikintensitet. Resultaten från

studien visade att jorden i det äldsta svackdiket, bredvid vägen med högst trafikintensitet,

innehöll högst koncentrationer av de flesta undersökta metallerna. Till exempel var

medelkoncentrationen av bly (Pb) ~70 mg/kg DW (torrvikt), jämfört med

vi

vii

Table of Contents Preface ......................................................................................................................... i

Abstract ...................................................................................................................... iii

Sammanfattning ............................................................................................................ v

List of papers ............................................................................................................... ix

1. Introduction ......................................................................................................... 1

1.1. Aim and Objectives ......................................................................................... 2

1.2. Thesis structure ............................................................................................... 3

2. Background .............................................................................................................. 5

2.1. Swale design and characteristics ....................................................................... 5

2.2. Swale hydrological performance ...................................................................... 8

2.3. Swale performance in treating stormwater runoff ............................................. 8

2.4. Effect of stormwater infiltration on soil media quality .................................... 10

2.5. Conceptual models of grass swales ................................................................. 13

2.6. Knowledge gaps and future research ................................................................ 14

3. Methods ............................................................................................................. 15

3.1. The literature review ..................................................................................... 15

3.2. Study sites ..................................................................................................... 15

3.3. Soil sampling ................................................................................................. 16

3.4. Infiltration measurements .............................................................................. 18

3.5. Laboratory analysis ........................................................................................ 18

3.5.1. Soil parameters .................................................................................... 18

3.5.2. Analysis of total metal concentrations .................................................. 19

3.5.3. Sequential extraction analysis ............................................................... 19

3.6. Grit material applied during the winter road maintenance ............................. 20

3.7. Data analysis .................................................................................................. 21

3.8. Computation of the metal burdens in swale soils ........................................... 21

3.8.1. Background concentrations of metals in swale soils .............................. 23

3.9. Modelling methods (StormTac Web) ............................................................ 24

4. Results ................................................................................................................... 27

4.1. Physico-chemical characteristics of soils in the studied swales ........................... 27

4.2. Metal removal during runoff conveyance in grass swales .................................. 30

4.3. Metal burdens in swale soils ............................................................................. 34

viii

4.4. Total metal concentrations in swale soils .......................................................... 35

4.5. Metal mobility ................................................................................................. 40

4.6. Winter road maintenance ................................................................................ 42

5. Discussion .............................................................................................................. 43

5.1. Factors affecting the estimated metal burdens in swale soils .............................. 43

5.1.1. Metal sources ............................................................................................ 43

5.1.2 Mean metal Zn, Cu and Pb burdens in soil layers ...................................... 44

5.2. Selected factors influencing the removal of metals from stormwater transported

in grass swales ......................................................................................................... 46

5.2.1. Hydraulic functioning of various swales sections ....................................... 46

5.2.2. Swale soil properties: pH, LOI, EC and sorption capacity (CEC) .............. 48

5.3. Swale maintenance .......................................................................................... 50

6. Conclusions ............................................................................................................ 53

7. References ............................................................................................................. 55

ix

List of papers

Paper I Gavrić, S., Leonhardt, G., Marsalek, J., Viklander, M. (2019).

Processes improving urban stormwater quality in grass swales and filter strips: A

review of research findings.

Science of the Total Environment, 669, 431-447.

Paper II Gavrić, S., Larm, T., Österlund, H., Marsalek, J., Wahlsten, A., Viklander, M. (2019).

Measurement and conceptual modelling of retention of metals (Cu, Pb, Zn) in

soils of three grass swales

Journal of Hydrology, 574, 1053-1064.

Paper III Gavrić, S., Leonhardt, G., Österlund, H., Marsalek, J., Viklander, M. Metal enrichment of soils in three urban drainage grass swales used for seasonal

snow storage

Submitted to Science of the Total Environment

Assessment of contribution to the above papers

Paper

no.

Development

of idea

Research

study design

Data

collection

Data

processing

and analysis

Data

interpretation

Publication process

Manuscript

preparation

for

submission

Responding

to reviewers

I Contributed Shared

responsibility

Responsible Shared

responsibility

Shared

responsibility

Shared

responsibility

Shared

Responsible

II Contributed Shared

responsibility

Responsible Shared

responsibility

Shared

responsibility

Shared

Responsible

Shared

responsibility

III Shared

responsibility

Shared

responsibility

Responsible Shared

responsibility

Shared

responsibility

Shared

Responsible

N/A

Responsible – developed, consulted (where needed) and implemented a plan for

completion of the task.

Shared responsibility – made essential contributions towards the task completion in

collaboration with other members in the research team

Contributed – worked on some aspects of the task completion

No contribution – for valid reason, has not contributed to completing the task (e.g.

joining the research project after the task completion)

N/A – Not applicable

x

1

1. Introduction The goal of the EC Water Framework Directive (WFD) (Directive 2000/60/EC, 2000)

is to achieve good qualitative and quantitative status of all water bodies in member states,

and this goal is further supported by the Environmental Quality Standards Directive

(EQSD) (Directive 2008/105/EC, 2008) and the Groundwater Directive (GD)

(Directive 2006/118/EC, 2006). Meeting the WFD objectives is particularly challenging

in river basins with high concentration of urban areas, which are recognized for multiple

pollutant sources impacting on both surface waters and the groundwater. With respect

to urban drainage, which is addressed in this thesis, one of the promising pollution

prevention and remediation measures is incorporation of green infrastructure (GI)

elements into urban and suburban catchments, with the objective of providing local

control of polluted stormwater runoff generated mostly on impervious areas. Grass swales

represent common GI elements that can be advantageously used, instead of stormwater

pipes, to drain runoff from trafficked areas. In addition to runoff conveyance, swales also

attenuate stormwater flow volumes and peaks, and reduce pollutant concentrations

through the interaction of flow with grass-soil media (Schueler, 1987). In climates with

seasonal snow, swales also serve for storage of snow cleared from streets, roads and

sidewalks (Backstrom and Viklander, 2000).

Swales ability to remove pollutants during actual rainfall and snowmelt events and

irrigation experiments, when runoff is conveyed through the swale, can be referred to as

short-term performance. Usually such a performance is estimated by comparing the

quality of stormwater before it enters and after it leaves the swale. On the other hand,

the performance of swales, that have been operated for many years, in retaining

particulate pollutants can be estimated from their soil chemistry. Soil chemical quality is

the result of swale long-term operation, i.e., drainage of a series of many runoff/snowmelt

events, processes occurring between the events (e.g., evapotranspiration, plant uptake)

and even external actions (maintenance of swales, reconstruction). These effects are

accounted for in swale long-term performance in immobilizing pollutants in their soils.

Studies investigating short-term swale performance in pollutant removal focused mostly

on selected swale characteristics, such as the longitudinal slope, geometry (the length and

cross-section), and the grass species and density, in order to develop the “best” swale

designs for stormwater quality control. A general analysis of the database derived from 59

swale studies showed that swales were efficient in removing TSS and particulate metals

(Zn, Pb, Cd and Cu) from conveyed runoff flows (Fardel et al., 2019). The removal of

solids has been investigated extensively, which led to the development of computational

methods for the settling of discrete particles (Deletic, 2001; Deletic and Fletcher, 2006).

Long-term exposure to polluted stormwater runoff from roads and parking lots in turn

leads to an elevated content of traffic-related metals in roadside soils (Lind and Karro,

1995; Achleitner et al., 2007). Generally, the highest metal concentrations were observed

2

in the upper soil layers (typically 0-5 cm) near the point of runoff inflow into the swale

(Tedoldi et al., 2017a), from which the pollutant concentrations declined with distance

and increasing depth below the soil surface (Tedoldi et al., 2017b). Although the metal

enrichment in roadside soils was investigated in some earlier studies, there is a lack of data

for swales serving not just for runoff control in warm seasons, but also for snow storage

during the winter season.

In spite of a fair number of studies on the role of grass swales in stormwater management,

the research of swales is still ongoing, because of the needs to cover the variety of climatic

conditions, swale design characteristics and operating conditions in urban catchments.

Swales usually provide a link between impervious surfaces (e.g., highways, streets, parking

lots, roofs, etc.) generating stormwater runoff, which partly ingresses into swale soils and

partly is conveyed through the swale, and the separate sewer systems. In that sense, swales

can be viewed as transport links between the pollutant sources and the receiving

environments, including both groundwater aquifers and surface waters. Thus,

investigations of both short- and long-term environmental performance of swales are of

great importance for creating opportunities for implementing environmental protection

by, and establishing maintenance needs of, grass drainage swales.

1.1. Aim and Objectives The vast majority of literature references reported on the studies, in which grass swales

were exposed only to rain-generated runoff and the associated pollution. However, in a

climate with seasonal snow addressed in this thesis, swales are also exposed to snowmelt

from intermittent melts of fresh snow on trafficked pavements and the melts of polluted

snow stored in swales during the winter. Urban snowmelt is generally more polluted than

rain runoff, because of winter road maintenance involving salt and grit applications on

roads and seasonal activation of other pollution sources (Vijayan, 2020).

This thesis aims to investigate the short- and long-term operation of grass swales serving

for stormwater drainage and seasonal snow storage. The specific thesis objectives are as

follows:

1. To advance the knowledge of processes affecting total metal concentrations in

stormwater runoff passing through grass swales, with respect to influential factors,

including inflow pollutant concentrations, swale geometry, and characteristics of

grass-soil media (Paper I).

2. To estimate metal enrichment of, and metal burdens in, soils of three urban grass

swales serving for stormwater drainage and seasonal snow storage, on the basis of

soil chemistry data (Papers II and III).

Much of the discussion of swale environmental performance focuses on traffic-related

metals, because of their common occurrence in road runoff at toxic levels and potentially

acute effects on biota in the receiving waters.

3

1.2. Thesis structure The thesis includes three papers referred to as Papers I-III. Paper I is a review paper,

which synthesizes and critically reviews the findings of previous research on the processes

affecting pollutant transport with runoff in grass swales and on grass filter strips. Paper II

presents a method, which uses soil chemistry data and planning level modelling to

estimate the metal burdens in swale soils. Paper III is a field study examining vertical and

horizontal profiles of swale soils, in order to advance the understanding of metal

distribution and mobility in urban grass swales operated in the cold climate with seasonal

snow. A synthesis of these three papers is presented in Figure 1.

The thesis is divided into seven chapters. Chapter 1 introduces the topic of grass swales

and their importance in stormwater management, and finishes with the thesis aims and

objectives. Chapter 2 presents a background of swale quantity and quality performance

in stormwater control, with special focus on the consequences of long-term infiltration

of polluted stormwater and snowmelt into swale soils. The investigated field sites and the

methods used in the three papers are described in Chapter 3. In Chapter 4, the main

results of the licentiate thesis are presented and followed by the discussion of results in

Chapter 5. The main study conclusions are presented in Chapter 6. The list of references

cited is presented in Chapter 7. Finally, the thesis papers are appended at the end of the

thesis.

Figure 1: The relationship among the papers included in the thesis

4

5

2. Background This chapter describes the role of grass swales in green urban drainage infrastructure and

presents an overview of the state-of-the-art knowledge addressing: (i) swale hydrology

and design, (ii) swale performance in removing pollutants from conveyed stormwater

runoff, (iii) enrichment of swale soils with metals (or other pollutants) entering soils

through infiltration, and (iv) modelling stormwater quality processes in grass swales.

2.1. Swale design and characteristics Progressing urbanisation results in higher runoff peaks and volumes of stormwater of

impaired quality travelling faster from the catchment to the receiving waters. One

solution for attenuating these negative effects of urbanisation and restoring some measure

of balance between the “natural” and “urban” drainage is the incorporation of green

infrastructure (GI), such as grass swales, into the landscape of urban catchments. Swales

are vegetated shallow drainage channels commonly used along impervious surfaces, such

as highways, roads, and parking lots, in order to reduce stormwater runoff volumes and

peaks, and remove some stormwater pollutants during runoff conveyance through a dense

grass layer and filtration through swale soils. Swales typically fall into three main

categories: (i) standard swales, (ii) dry swales, and (iii) wet swales. Standard and dry swales

are similar in their appearance, however, the latter feature a filter bed of specially

processed soil (an engineered soil) and an under-drain pipe to enhance infiltration

(Woods Ballard et al., 2015). On the other hand, wet swales are designed to operate with

permanent standing water and wetland vegetation (Woods Ballard et al., 2015). Typically,

swales receive runoff through lateral inflows over side slopes, either freely without

obstructions or through regular brakes in the curbs, and/or longitudinal inflows from the

upstream sources, e.g., from a bridge or a roof. Moreover, swales can be constructed as a

part of a stormwater treatment train, in combination with e.g. permeable pavement

parking lots, grass filter strips, or bioretention cells, in order to provide sufficient

treatment for meeting environmental objectives (WSUD, 2006; Revitt et al., 2017).

Sometimes the swale designs include grass filter strips (GFS) and/or check-berms across

the swale bottom section. GFS are considered as pre-treatment devices of swales,

however, some studies compared swale performance with and without GFS and

concluded that the main pollutant removal still occurs along the bottom of the swale

channel (Stagge et al., 2012). Check-berms serve to enhance infiltration into the swale

bed by increasing the flow depth. Figure 2 shows typical operating conditions of standard

swales.

There are some general design recommendations for swales that may be further modified

to meet specific local conditions. Swales are usually constructed to treat stormwater runoff

from small catchments, up to 1-2 ha in size, in order that the generated flow depths and

velocities allow for stormwater quality processes to occur (WSUD, 2006). The

recommended swale cross-sections are trapezoidal or triangular, with a rounded bottom

section and a recommended bottom width of 0.5-2.0 m, to allow for easier maintenance

6

and prevention of concentrated flows (Woods Ballard et al., 2015). Longitudinal slopes

are recommended not to exceed 2%, and inclusion of check-berms is recommended for

slopes steeper than 4%, while side slopes should be less than 1:3 (33%) (USEPA, 1999).

To achieve stormwater quality control, swales should perform well in pollutant removal

for the majority of events occurring on an annual basis (Woods Ballard et al., 2015). For

example, a design event for water quality swales should generate flow depths below the

grass height, flow velocities < 0.3 m/s, and adequate times of travel of runoff along the

swale (Woods Ballard et al., 2015). Even for major design rain events, with return periods

50 – 100 years, flow velocities within swales should be

7

Table 1: Methods used for determining swale characteristics in the previous research

Swale characteristics Method Ambient environmental and operational

conditions: Swale surroundings; channel

erosion and the state of turf cover;

accumulations of debris (litter) and sediment;

maintenance access; functionality of the

drainage pipe, condition of the drop inlet,

etc.

Visual observations (during regular inspections)

Swale geometry

Manual measurement at repeated distances along the

swale (e.g., 5 m); RTK-GPS survey and building the

digital elevation model (DEM) (Rujner et al., 2018)

Grass characteristics

Grass type

Processing digital photographs of the grass area with

imaging software to estimate the dominant grass

species (Ming-Han et al., 2008)

Grass cover

[grass blade/cm2]: Counting the blades within 10 cm2

quadrants (Deletic and Fletcher, 2006);

[%]: Processing digital photographs of the grass area

with imaging software to estimate grass coverage

(Ming-Han et al., 2008; Pan and Shangguan, 2006);

Aerial photographs imported to AutoCAD to draw

polygons around areas with bare soils plus visual

estimation (Winston et al., 2012)

Grass blade width [cm] Measuring ≈ 50 random grass blades (Deletic and

Fletcher, 2006)

Above-ground biomass per unit area

(if herbs are more dominant than grasses)a

An open cylinder (diameter 0.12 m and height 0.1

m) is placed in the centre of two adjacent 0.25 m2

quadrants to harvest the contained above-ground

biomass, the collected material is oven-dried and

weighed (Mazer et al., 2001);

Three plants randomly taken from a 15 cm2 quadrant,

aerial parts of plants were cut and dried at 35 °C for

one week, after which the dry residue was weighed

(Leroy et al., 2017)

Soil physical characteristics

Infiltration capacity [cm/h] Double ring infiltrometer test (Deletic and Fletcher,

2006; Rujner et al., 2018; Young et al., 2018)

Soil texture

From wet sieving and hydrometer analysis of two 13

cm long soil cores to determine % clay, % silt and %

sand (García-Serrana et al., 2017);

From granulometry of a 30 cm soil layer to determine

% clay, % silt and % sand (Rujner et al., 2018)

Soil compaction

Cone penetrometer (soil was considered compacted

if the cone index exceeded 2,070 kPa in the upper

7.6 cm) (Winston et al., 2012) a Herbs may produce high above-ground biomass despite low plant density (Mazer et al., 2001)

8

2.2. Swale hydrological performance Draining trafficked areas requires fast removal of generated runoff from the impervious

surfaces, in order to maintain safe road conditions (e.g., avoidance of hydroplaning) and

passage of emergency vehicles. Since swales are typically located next to roads and

highways, their design needs to provide good hydrological performance, including

attenuation of stormwater runoff volumes and peaks, and safe runoff conveyance.

Research has shown that swales are very effective in controlling runoff from small rain

events by completely infiltrating the runoff into soils, and avoiding any outflow (Davis et

al., 2012, Purvis et al., 2018, Young et al., 2018). This is why some authors noted that

small storms did not generate enough runoff in swales to allow for stormwater sampling.

For moderate rain events, swales attenuate runoff volumes and peaks, while for large

events, their main function is flow conveyance (Davis et al., 2012).

Rushton (2001) reported a mean runoff volume reduction of 30% in a catchment with

swales, compared to a similar catchment without swales. Bäckström et al. (2002)

performed field experiments on seven swales (5-10 m long) by pumping water mixed

with sediments into the swale at the upstream end (inflow rate 0.5-1.5 L/s) and observed

inflow volume reductions of 33-66%. Lucke et al. (2014) studied four field swales (30-

35 m long) by feeding in water with pollutants (TSS, TP and TN) at the upstream end

(0.5-2.0 L/s) and observed mean runoff volume reduction of 52%, which depended on

the initial soil moisture content. Jiang et al. (2017) monitored two swale sections (5 m

long) and reported mean runoff volume reductions of 78-98% for five monitored actual

events. Young et al. (2018) studied two swales (210-230 m) draining highway runoff and

observed mean volume reduction of 87% for 65 rainfall events.

The swale grass layer further enhances the swale hydraulic function, compared to bare

soils. Dense grass increases surface roughness by slowing down the runoff and increasing

infiltrated runoff volumes (García-Serrana et al., 2017), which also limits the effect of

slope on infiltration rates (Morbidelli et al., 2016).

2.3. Swale performance in treating stormwater runoff Runoff generated on impervious surfaces of urban catchments contains a variety of

pollutants from numerous anthropogenic activities. Draining such a polluted runoff into

grass swales can provide local treatment in well-designed swales (e.g., with dense grass

turf, mild bottom slopes, good infiltration rates, etc.). Identification of swale

characteristics, which are beneficial for stormwater quality control, resulted from studies

addressing grass swale performance in enhancing stormwater quality. These studies can

be divided into three groups: (i) laboratory and field assessment of simulated inflows, (ii)

field assessment of actual rainfall events, and (iii) computer modelling studies.

The first group of studies often aimed to advance the understanding of small-scale

processes occurring in swales with respect to influential factors. Typical controlled

9

investigations supplied synthesized stormwater runoff at the swale upstream end (Deletic

1999; Bäckström 2002; Deletic and Fletcher 2006; Lucke et al., 2014), but less frequently

also over the swale side slopes (Fardel et al., 2020). Developed algorithms for fluxes of

pollutants of different types and characteristics, which resulted from such controlled

experiments, can be verified using the measured data from the second group of studies.

Field studies of swale short-term performance in pollutant removal during actual rainfall

events typically investigated swales next to highways (e.g. Barrett et al., 1998; Winston

et al., 2010) or urban roads (e.g. Bäckström et al., 2006), and less frequently parking lots

(Rushton, 2001). Moreover, studies of swale field performance for actual rainfall events

are very important for collecting high quality data for testing standard urban drainage

modelling packages (e.g. SWMM, Mike SHE) and for investigating swale performance

in larger-scale systems (i.e., incorporated into the drainage system).

Looking at larger-scale processes is important, because these processes affect the

generation and quality of runoff entering the swale. During dry periods,

evapotranspiration (ET) restores swale infiltration capacity (Deletic, 2000) and compared

to bare soils, evapotranspiration is enhanced by the grass cover (Hino et al., 1987). At the

same time, pollutants accumulate on the catchment surfaces (including the swale surface)

as a result of dry atmospheric deposition. Even in dry weather, the pollutants accumulated

on the contributing drainage surfaces may be transported into grass swales by vehicle

induced turbulence, wind, street sweeping and snow clearance from pavements. During

wet weather, the accumulated pollutants are washed into the swale via runoff and vehicle-

generated splash water (Werkenthin et al., 2014), and additional pollutants enter swales

through direct precipitation (i.e., wet atmospheric deposition). Leroy et al. (2016)

sampled infiltrated water from a swale section receiving only atmospheric deposition (wet

and dry) and compared it to a swale section receiving also road runoff. The authors

measured lower concentrations in the former section, but of the same order of magnitude,

concluding that atmospheric wet and dry deposition should not be neglected in the

conditions of their study (Leroy et al., 2016).

Moreover, specific catchment characteristics, such as, land use type (e.g., highway,

secondary road, residential area), percentage of imperviousness, slopes, etc., affect the

stormwater runoff pathway. Different pathways of stormwater before reaching the swale

will affect the stormwater quality (i.e., the pollutant inflow concentrations reaching the

swale). Studies have shown that pollutant removal in grass swales is affected by pollutant

inflow concentrations. For example, Stagge et al. (2012) suggested that swales can treat

total phosphorus (TP), if its concentration in the inflow exceeds 0.7 mg/L, while

Bäckström et al. (2006) suggested that inflow concentrations of TSS >40 mg/L are

needed to produce positive removals. Winston et al. (2011) observed that the largest

increases in total nitrogen (TN) and TP concentrations, after conveyance through GFS,

may be caused by low inflow concentrations. Also, Winston et al. (2010) investigated

two wet swales and two standard swales (with GFS) draining highways with asphalt

10

pavement with a porous friction course (PFC) overlay. The swale length was 30.5 m and

the GFS length was 8 m (Winston et al., 2010). TSS inflow concentrations, to the GFS,

were reduced by runoff passage over the PFC to concentrations in the range 10-31 mg/L

and negative removals of TSS were observed after conveyance over GFS (Winston et al.,

2010). The authors explained such a TSS export by the irreducible TSS concentrations

in the influent, ~10 mg/L (Winston et al., 2010). The irreducible concentrations are the

minimum (residual) outflow concentrations that cannot be further reduced by stormwater

management facilities (Schueler, 2000).

Abundance of solids in urban areas, their release throughout the urban catchments and

the role in transporting other pollutants (e.g., adsorbed metals) (Liu et al., 2015), all

contribute to the fact that solids are the most investigated quality parameter in studies of

grass swale inflows and outflows. In addition, total and dissolved metals, nutrients, traffic-

associated hydrocarbons and oxygen-demanding constituents are also often analysed,

compared to, e.g., chloride and faecal indicator bacteria, which are studied less frequently.

The pollutant type and characteristics are important to consider, because actual

stormwater quality processes causing pollutant removal in overland flow over grass

depend on these influential factors. For example, settling and infiltration processes, were

found important in removing solids (usually described as total suspended solids (TSS))

(Mendez et al., 1999; Barrett et al., 2004; Stagge et al., 2012), while plant uptake

contributed to retention of metals in the roots and the above ground biomass (Leroy et

al., 2017).

2.4. Effect of stormwater infiltration on soil media quality Filtration of stormwater through swale soils is an important process for enhancing

stormwater quality, as shown by sampling subsurface flow from a swale underdrain pipe

(Purvis et al., 2018; Fardel et al., 2020). Filtration of road runoff through swale soils

resulted in a significantly cleaner outflow in the underdrain pipe, compared to untreated

road runoff, with respect to TSS, total volatile suspended solids (VSS), enterococcus, E.

coli, and turbidity (Purvis et al., 2018). For example, concentration reductions in the

underdrain outflow were 88% (TSS) and 87% (VSS), while reductions in the overflow

were substantially lower, 10 and 21%, for TSS and VSS, respectively (Purvis et al., 2018).

Fardel et al., (2020) conducted controlled field experiments to examine Zn, pyrene,

phenanthrene and glyphosate removals through standard and filtration swales, and found

that chemical removal efficiencies were significantly higher in the subsurface outflow,

compared to the overflow. In the same study by Fardel et al. (2020), for all experiments,

mass removals of Zn, pyrene, phenanthrene and glyphosate were higher in the filtration

swale than in the standard swale. Moreover, Leroy et al. (2015) observed that filtration

through the dense root system of grass captured suspended solids (SS) with attached PAHs

and limited the transfer of PAHs into deeper soil layers.

11

The above discussed research studies acknowledged that, in a long term, filtering polluted

stormwater runoff from trafficked surfaces can pose some risk of contamination of swale

soils, with contaminants reaching deeper soil layers and even leaching into the

groundwater. Monitoring pollutant concentrations in the field can be used to

characterize pollutant concentrations, provide spatial or temporal summary of

environmental contamination, and demonstrate or enforce the compliance with standards

or guidelines (Gilbert, 1987), to name a few examples. Moreover, field and laboratory

studies can provide data for studying pollutant transport and quantifying the relationships

that control the levels and variability of pollutant concentrations in time and space

(Gilbert, 1987). Often, a composite sampling is performed in order to reduce the cost of

sample analyses, but at the risk of losing the individual sample information and dilution

of the samples (Mason, 1992).

The fate and transport of metals and PAHs in the soils of the infiltration-based Sustainable

Urban Drainage Systems (SUDS) has been reviewed by Tedoldi et al. (2016). Metals are

often reported in higher concentrations in the topsoil layer, and such concentrations

decrease with the soil depth (Tedoldi et al., 2016). The thickness of the “topsoil layer”

differs among the studies. In many studies, the topsoil layer was considered to be 5 cm

thick (Lind and Karro 1995; Norrström and Jacks 1998; Achleiter et al., 2007; Ingversten

et al., 2012; Rommel et al., 2019), but in other studies (Rushton 2001; Hjortenkrans et

al., 2006) a smaller depth was considered (0-3 cm). According to Mason (1992) airborne

pollutants and pollutants that are strongly bound to soil particles are found in the top

15 cm, while pollutants from long-term deposition are found in the layers deeper than

15 cm.

There are multiple traffic-related sources of metals, e.g. vehicle operation, tire and brake

wear, vehicle washing, and road abrasion that contribute to metal pollution in stormwater

runoff (Müller et al., 2020). In many studies, soils were sampled next to the roads with

various traffic intensities, in order to assess the contribution of traffic to the metal

pollution in roadside soils. Carrero et al. (2013) sampled soils next to: (i) an old secondary

road exposed to high traffic (>60 years of service), (ii) a newer highway road (20 years

old with 28,200 AADT), and (iii) two roundabouts (1 and 5 years old). PCA analysis

showed that samples from the old secondary road clearly differed from the remaining

samples by having higher concentrations of traffic related metals (Carrero et al., 2013).

For example, Pb concentrations of 630 mg/kg in the old road case far exceeded the

concentrations of Pb

12

sorption capacity can lead to migration of metals into the deeper layers (Tedoldi et al.,

2016). In another case, the high clay content (19.1%) provided high cation exchange

capacity enabling metal sorption (Leroy et al., 2016). Moreover, decrease in pH can result

in mobilisation of metals (Bäckström et al., 2004), but neutral pH 6-7 reduces the risk of

occurrence of metals in the dissolved fraction, as reviewed by Rieuwerts et al. (2015).

Bäckström et al. (2004) sampled the water draining through the soil at a depth of 50 cm

below the soil surface, at various distances from the road edge. The sampling was done

in the soils next to two roads in mid Sweden during one year and the analytical protocol

included pH, electrical conductivity (EC), inorganic carbon (IC), total organic carbon

(TOC), chloride, sulphate, and metals (Cd, Cu, Pb, Zn, Na, Ca, Mg, K, Fe and Al). The

authors found strong significant correlations between chloride and metals, and electrical

conductivity and metals (Bäckström et al., 2004).

Lastly, swales in cold climate regions with seasonal snow have an additional function, i.e.,

storage of snow cleared from roads and parking lots. This is a very useful swale function

for maintaining safe driving conditions during the winter, since snow can be quickly

cleared from roads into swales. Comparisons of different snow management scenarios

(i.e., transport of snow to, and storage in, central or local snow storage sites, with or

without the use of swales) showed that storage of snow in the swales had a favourable

impact on costs and long-term traffic-related pollution emissions (Reinosdotter et al.,

1998).

Lind and Karro (1995) sampled soils next to two roads (AADT = 11,400-34,000) in

southern Sweden, after the first eight years of operation. The authors observed that

drainage of stormwater contributed to a metal (Zn, Pb and Cu) enrichment of soils.

Norrström and Jacks (1998) sampled soil next to a 29-year old highway (40,000-50,000

AADT) in southern Sweden. The first 15 cm of soil were sampled by coring at 20

locations along two transect lines at 0.5 and 2.5 m distances from the pavement edge and

the cores were divided into 5 cm slices, which were composed for individual transects

(Norrström and Jacks, 1998). The authors measured the highest Pb concentration (542

mg/kg) in the top 5 cm at 0.5 m from the highway. Hjortenkrans et al. (2008) sampled

two swales draining about 20-year old highways (20,700-22,300 AADT) in the South of

Sweden and produced composite samples, comprising at least seven sub-samples, to

represent the metal concentrations at different depths and distances from the highway. At

one site the highest Pb concentration (200 mg/kg) was measured at the 0.4 m distance,

10 cm below the surface, with the upper layer concentrations being lower (Hjortenkrans

et al., 2008). The authors explained this by the annual depositions of sand used in winter

road maintenance and the phase-out of Pb from gasoline (Hjortenkrans et al., 2008). The

characterisation of soil pollution in cold climate swales is important, because of specific

operating conditions, including the drainage from roads serviced by applications of salt

and anti-skid materials, and the effects of melting of the stored snow during the winter.

13

2.5. Conceptual models of grass swales Computer modelling studies strive to cope with the complexity of urban drainage systems

and integration of a large number of drainage elements. Modelling studies of grass swales

can be divided in two groups, according to the nature of the models used: (i) Studies

based on research models, and (ii) Studies of applications of standard urban drainage

modelling packages (e.g., SWMM, Mike SHE, Music, and others).

The first group represents semi-empirical models for computing TSS removal from

stormwater flow over grass surfaces, e.g., the Kentucky Method (Tollner et al., 1976) and

the Aberdeen equation (Deletic, 2000), which resulted from controlled laboratory

experiments. This group of models still attracts a lot of research interest and efforts to

verify the original equations for other conditions than those, for which they were

developed. For example, the Aberdeen equation was recently tested to predict TSS

removal efficiencies in two swales and the modelling results for six rain events were

compared to the actual field data (Hunt et al., 2020). The modelled event removal

efficiency was a weighted average of the removal efficiencies of each particle size

(calculated using Aberdeen method) (Hunt et al., 2020). The maximum difference

between the modelled and actual removal efficiencies was 20% and the authors noted

that the smallest difference (1-6%) was observed for two events when the flow depth was

close to the nominal grass height. There is a research need for more data on other-than-

solids pollutant removals and transport in swales, in order to gain more knowledge on

influential factors and quantify processes other than settling in swales.

The models in the second group were originally developed for larger (catchment) scales

and are continually being refined, in order to simulate small stormwater control facilities,

such as grass swales, with sufficient accuracy. For example, Niaizi et al. (2017) reviewed

papers on SWMM applications and found only a small number of studies, out of 150

peer-reviewed papers, describing the use of SWMM for modelling stormwater pollutant

reductions by GI. One study (Jia et al., 2014) compared the following drainage scenarios:

(i) impervious areas, and (ii) impervious area reduced by incorporating GI features

(including a grass swale in a treatment train). However, the pollution reduction by the

swale and representation of the stormwater quality processes in the swale was not the

focus of the study. A number of recent studies focused on modelling runoff quantity

control by grass swales using standard urban drainage modelling packages, Mike SHE,

SWMM, and WinSLAMM (Flanagan et al., 2017; Xie et al., 2017; Rujner et al., 2018;

Young et al., 2018; Wadhwa and Kumar, 2020; Broekhuizen et al., 2020). This work is

relevant to the studies in this thesis, since reliable quantity simulations are needed to

model well the water quality. However, an even bigger obstacle in modelling pollutant

reductions in swales is the lack of understanding of physical, chemical and biological

processes taking place in grass swales.

14

2.6. Knowledge gaps and future research

There is a continual need to expand the existing knowledge of design and operation of

drainage swales into widely varying and previously unexplored conditions, and assess the

underlying limitations of the past research. This assessment was conducted at the start of

the thesis project and its findings are briefly summarized below. Recognizing the inherent

emphasis of the thesis project on producing new experimental data and physico-chemical

concepts, the modelling of swale operation was excluded from the above knowledge gap

analysis.

A brief overview of the state of knowledge of urban grass drainage swales in this chapter

indicates that the analysed studies were conducted mostly in the temperate climate,

without seasonal snow, with the exception of the pioneering work by Bäckström (2003).

To achieve a good control of experimental conditions, laboratory or field research studies

mostly considered well-defined but less-complex class of swale layouts:

(i) Land cover/use serviced by drainage swales: mostly adjacent to urban roads or

highways, very few studies addressed parking lots, or residential lands

(ii) Generation of runoff inflow – mostly by irrigation water, or by actual rain events;

rarely by snowmelt (from drained surfaces, or stored snow)

(iii) Runoff inflow into swales – in studies applying swale irrigation, the inflow entered

at the upstream end only, with a few exceptions of supplementing the longitudinal inflow

with lateral inflows as well; in studies of actual rainfall events, both longitudinal and lateral

inflows were considered; lateral inflow – typically from one side only

(iv) swale cross-sections – mostly trapezoidal or triangular; many studies addressed

treatment in the bottom section only, neglecting treatment/infiltration on side slopes

(v) swale surface – turf, natural or synthetic (the latter was used in lab studies); rarely bare

earth in lab studies comparing turf with bare earth

(vi) swale soils – investigated in some field studies, within some distance (0-5 m) from

the road pavement and typical depths (0-30 cm)

(vii) swale water quality process studied – a vast majority of studies focused on solids

settling as the most important quality enhancement process; relatively few studies pursued

stormwater filtration through swale turf and soils, or the resulting effects on soil chemistry

The licentiate phase of the planned PhD project should strive to reduce or close the

above knowledge gaps by focusing on stormwater quality enhancement in urban grass

swales providing drainage and snow storage for various land use (for comparative

purposes), conveying actual runoff and snowmelt entering the swale at the upstream end

as well as on one or both sides, and focusing on the treatment of stormwater by infiltration

into swale soils.

15

3. Methods

3.1. The literature review The aim of the critical review paper was to provide a systematic overview of the state-

of-the-art knowledge of processes that serve to remove pollutants from stormwater runoff

flowing over grass surfaces, with respect to influential factors. The primary sources of

information were laboratory, field and modelling studies of stormwater quality processes

occurring during stormwater runoff over standard and dry grass swales and grass filter

strips (GFS). Literature research focused on peer reviewed articles, academic theses,

conference proceeding papers, books, reports and design guidelines in Scopus, Web of

Science and Google Scholar databases. The references listed in the reviewed articles were

also examined. Searches included a variety of related keywords e.g. “grass swale”,

“vegetative swale”, “grass ditch”, “drainage swale”, “dry swale”, “grass filter strip”, etc.

3.2. Study sites In this thesis project, three grass swales serving for stormwater drainage and seasonal snow

storage were selected for study using such selection criteria as: (i) Well-functioning swales

with clearly delineated inflows (on one or both sides) and outflows, (b) Coverage of a

variety of sites with various soils, land use and traffic intensity, and (c) A general suitability

with respect to the site proximity, access and field crew safety. Three sites meeting these

conditions were selected in the City of Luleå, Sweden (Paper II and III). The climate at

the study location is a cool temperate climate, characterized by long winters, with the

snow season starting in October-November and snow remaining on the ground until

April. The mean annual temperature is 1.4 ºC. The studied sites represent different land

use types, i.e., a swale in a commercial catchment (swale L1), a swale next to the busiest

road in the city in the downtown area (swale L2), and a swale in the residential catchment

(swale L3). The first swale (L1) receives runoff from a parking lot (408 m2), a small part

of a building roof (5 m2), and a single-lane road (241 m2) with the average daily traffic

(ADT) of ~ 2,750. The second swale (L2) receives lateral stormwater runoff from a two-

lane road (728 m2) with the highest traffic intensity (ADT ~ 11,650) among the studied

locations. This swale receives road runoff only from one side, because the other side

features a continuous curb preventing any stormwater runoff discharge into the swale

(further called the no-runoff (NR) side). The third swale (L3) receives runoff from a

parking lot (287 m2), a roof (812 m2), a grassed area (726 m2), and a two-lane road (520

m2) with ADT ~ 2,500. The age of the three studied swales was estimated from the years

of construction of the roads next to the swales; thus, the swales years of operation at the

time of the soil sampling campaign was 57 years for swale L2, and 38 years for swales L1

and L3. There are uncertainties concerning the years of swale construction, which

depended on when the road was completed and possible swales modifications in the

following years, resulting from road reconstruction or other building activities in the

catchments. All the three swales are used for snow storage during winter road

16

maintenance, which includes the clearance of snow from the roads and parking lots

adjacent to the swales and applications of anti-skid materials (grit). Road salt (NaCl) is

applied only as an additive to grit material, to prevent its freezing and formation of clumps

in the grit material. Such a salt/grit mixture is applied only in early or late winter, when

temperatures are above -6° C and salt is effective in melting the ice layer formed on grit

particles. In early spring, after the winter season (end of April-beginning of May), the

residual grit is brushed off the roads and parking lots and collected for disposal. As an

example, Figure 2 shows swale L1 in the commercial catchment, before and after the

winter. It can be seen from Figure 2 that the stored snow may remain on the swale

ground even after the sweeping and removal of the residual grit from the roads and

parking lots.

Regular maintenance of the three studied swales includes: (i) regular mowing of grass in

the summer, and (ii) removal of gravel accumulations from the swales, which is done

once a year in early spring, after snow melted away and swales became dry, but before

the grass layer was established.

3.3. Soil sampling

In each swale studied, a 20 m long section was selected for soil sampling, which was done

in October 2017, using a stainless-steel core sampler with a 5 cm diameter and the length

of 30 cm. The section received only direct lateral runoff from the adjacent road and/or

parking lot, and the measured soil chemistry was used to examine if there were differences

in metal concentrations in soils draining different land covers. Because of soil

characteristics variation along the swale, samples were collected at three cross-sections 10

m apart to allow for statistical analysis. In order to investigate the metal concentrations

along the runoff flow path, at each cross-section, samples were collected at the distances

Figure 2: Swale L1 in the commercial catchment. The picture on the left side shows the swale before

the soil sampling campaign (September 2017) and the picture on the right shows the same swale after the winter (April 2018).

17

of 40 and 80 cm from the edge of the pavement and at the deepest point of the cross-

section, in the swale bottom section. Using a stainless-steel knife, each soil core was

divided into 5 cm slices representing individual samples, which were placed in a plastic

bag, refrigerated and kept in cold storage (up to 7 days) until analysed. At all three swales,

top three soil layer samples (0-5, 5-10 and 10-15 cm) and the deepest layer sample from

the swale bottom section were analysed, while for the swale sides there were some

exceptions:

(i) In swale L3, no soil samples could be collected from the swale side draining

the parking lot, because of the presence of gravel from the parking lot

construction.

(ii) Only the top layer (0-5 cm) samples from the side draining road (L3) and

parking lot (L1) were analysed, because some deeper soil layers, at a 40 cm

distance from the pavement edge, were highly compacted and did not allow

sample extraction.

(iii) In swale L2, only the top layer (0-5 cm) samples from the no-runoff side were

analysed.

Figure 3 shows an example of sample distribution at three cross-sections of swale L1;

the black coloured symbols identify, which samples were analysed. The same sampling

pattern was applied in swales L2 and L3, with minor exceptions listed above. In total,

96 individual soil samples were collected and analysed.

Figure 3: Distribution of 30 cm deep soil cores collected at the three studied swales (obtained from

Paper III). Black colour indicates, which samples were subject to the analysis at swale L1. All lengths are

in cm, unless indicated otherwise.

18

In order to investigate the swale topography and runoff contributing areas, location data

(x-y-z coordinates) were collected at numerous points along the swale using a real-time

kinematic-GPS device (model GeoMax Zenith35 Pro TAG) with the precision of 1.5

cm (for x and y) and 2 cm for z. The location data was used to build the TIN (Triangular

irregular networks) surface in AutoCAD Civil 3D software.

3.4. Infiltration measurements In order to investigate the swale infiltration capacity, field measurements were performed

in September 2018 using the Modified Phillip Dunne (MPD) infiltrometer (ASTM,

2018). Infiltration measurements were performed at undisturbed sites, which were

covered with turf, along the three sampled cross-sections (Figure 3), within ~ 30 cm of

the corresponding sampling points, and at two additional points at 120 and 200 cm

distances from the pavement edge. The saturated hydraulic conductivity was calculated

according to the method developed by Upstream Technology Co. following the ASTM

standard (ASTM, 2018). The best-fit values of saturated hydraulic conductivity (Kf,best_fit)

were calculated using the method developed by Weiss and Gulliver (2015):

Kf,bestfit = 0.32(Kf,arit) + 0.68 (Kf,geo) (1)

where,

Kf,arit and Kf,geo represent the arithmetic and geometric means of the saturated hydraulic conductivity, respectively.

The measured data was also compared to the literature data on infiltration capacities of

soils of various textures to inform about the soil texture of the studied sites.

3.5. Laboratory analysis

3.5.1. Soil parameters

Soil samples were prepared according to the standard ISO 11464 (2006) with minor

changes, and analysed for electrical conductivity (EC) and pH in the university

laboratory. The samples were air dried and dry sieved in the laboratory using a vibratory

sieve shaker (Retsch AS200) and a stainless sieve (mesh size of 2 mm). Soil lumps

remaining on the sieve were crushed using pestle and mixed with the < 2 mm fraction

(ISO 11464, 2006). The fraction > 2 mm, which generally included grass roots and

stones, was excluded from analyses. Measurements of EC were done according to the

standard ISO 11 265 (1994) using the CDM210 conductivity meter. Measurements of

pH (in a 1:5 suspension of soil in water) were done according to the standard ISO 10390

(2005), using the WTW pH 330 instrument. Chloride and loss on ignition (LOI) analyses

were done by an accredited commercial laboratory (ALS Scandinavia AB, Luleå).

Chloride analysis was done according to standard DIN EN ISO 12457–4 (2003). The

LOI analysis was determined at 1000°C and reported in % of sample dry weight (DW).

19

3.5.2. Analysis of total metal concentrations

Total concentrations of 13 metals have been examined in this thesis. The group consists

of common urban-related metals Zn, Cu, Pb, Cd, Cr, Cu, Ni and Co, all of which,

except Co, are considered stormwater priority pollutants (Eriksson et al., 2007). This

group was expanded to include W, Mn, Ti, V and Ba, which were all reported as traffic-

related elements, originating from such sources as e.g., asphalt, tire and brake wear, and

tire studs (Apeagyei et al., 2011; Mummullage et al., 2016; Huber et al., 2016). Zr was

also selected since it was validated as a tracer exhibiting a concentration deficit in sediment

accumulations in Sustainable Urban Drainage Systems (Tedoldi et al., 2018). This deficit

is caused by dilution of sediments containing Zr from anthropogenic sources by sediments

of mineral origin. Analyses of total metal concentrations were done by ALS Scandinavia

AB in Luleå. Metals Cd, Cu, Co, Ni, Pb and Zn were determined by digestion in a

heating block with nitric acid, while for the remaining metals (Cr, V, Ba, Mn, Ti, W

and Zr), 0.1 g of dried sample was fused with 0.4 g LiBO2 (lithium metaborate) and

subsequently dissolved in dilute nitric acid. The total metal concentrations were analysed

using Inductively Coupled Plasma Sector Field Mass Spectrometry (ICP-SFMS)

following SS EN ISO 17294-1, 2 and EPA-method 200.8. All metal concentrations were

reported in mg/kg DW except for Mn and Ti, which were reported as MnO and TiO2,

respectively, and converted to mg/kg DW. The laboratory performing the analysis

reported analytical uncertainties in concentrations of Cd, Co, Cu, Pb and Zn as 19-33%

of the reported values.

3.5.3. Sequential extraction analysis

Results of analyses of total metal concentrations were complemented by results from a

five-step sequential extraction analysis and the residue analysis. In this procedure,

extractants of increasing reactivity are sequentially applied, so that the successive fractions

exhibit lesser mobilities and lower risks of metal release due to changes in the ambient

environmental chemistry. Such changes may include the changes in pH and other factors

(Stone and Marsalek, 1996). A set of 11 soil samples from swale L2, which was noted for

the highest metal concentrations among the three swales studied, were selected for this

analysis. The selected samples included three top layer samples (0-5 cm) - two on the

road shoulder and one on the no-runoff side; and, eight samples from two soil cores from

the swale bottom section. Each core comprised samples from four layers of successively

increasing depths. The selected samples were analysed by ALS Scandinavia AB in Luleå

using a five-step sequential extraction analysis, and the residual analysis, following the

method adopted from Hall et al. (1996a, 1996b). The total metal concentrations were

analysed using ICP-SFMS following SS EN ISO 17294-1, 2 and EPA-method 200.8.

Analytical uncertainties in the reported concentrations of all metals in all steps were in

the range of 17-37% of the reported values, except for Zn in step 2, which had higher

uncertainty (range of the uncertainty for the 11 samples analysed was 48-62%). Samples

were ground prior to the first extraction step. Concentrations were reported in µg/L and

recalculated to mg/kg DW. The five extraction steps are listed below:

20

Step 1 (Fraction 1): Extraction of 1 g sample with 10 ml 1.0 M acetate buffer (pH 5)

by shaking for 6 h at room temperature to remove and measure adsorbed and

exchangeable metals and carbonates.

Step 2 (Fraction 2): Extraction of the solid residue from Step 1 with 50 ml 0.1 M

pyrophosphate solution (pH 9) by shaking for 1 h at room temperature to remove and

measure labile organic forms, which are the forms associated with reaction sites such

as those present in humic and fulvic substances (Hall et al. 1996b).

Step 3 (Fraction 3): Extraction of the solid residue from Step 2 with 10 ml 0.25 M

hydroxylamine hydrochloride for 4 h at 50°C to remove and measure amorphous

Fe/Mn oxides.

Step 4 (Fraction 4): Extraction of the solid residue from Step 3 with 15 ml 1 M

hydroxylamine hydrochloride in 25% acetic acid for 3 h at 90°C to remove and measure

crystalline Fe oxides.

Step 5 (Fraction 5): Removal and measurement of stable organic forms and

sulphides by adding 0.75 g potassium chlorate to the solid residue from Step 4 followed

by adding 15 ml 12 M hydrochloric acid for 30 min at room temperature and then 10

ml 4 M nitric acid for 20 min at 90°C.

Additionally, metal residuals were also determined. The residual content of Ba, V and

Cr, was determined according to ASTM D3682: 2013 and ASTM D4503: 2008 (fusion

with LiBO2). For obtaining the residual content of Cd, Ni, Pb, Zn, Cu, and Co, the

samples were digested with HNO3/HCl/HF according to SS EN 13656: 2003. The ICP-

SFMS analyses were carried out according to SS EN ISO 17294-2: 2016 and EPA-

method 200.8: 1994. The residual concentrations were reported in mg/kg DW.

Analytical uncertainties in the reported residual concentrations of metals were 14-34% of

the reported values.

3.6. Grit material applied during the winter road maintenance Three samples of stocked anti-skid grit materials were collected from the municipal

storage in April 2018:

- Material A (aggregate sizes 2-6 mm)

- Material B (aggregate sizes 4-8 mm)

- Material C (aggregate sizes 0-6mm) + salt

This material is applied on the roads, parking lots and bicycle paths throughout the winter

and, once applied, may be ground by vehicle tires.

A single sample of each material was analysed for total metal concentrations by the ALS

Scandinavia AB laboratory in Luleå. Prior to the analysis, the material was crushed and

the total metal content was analysed as described in section 3.5.2. Analytical uncertainties

21

in concentrations of Cd, Co, Cu, Pb and Zn were reported by the laboratory as 18-29%

of the reported values.

3.7. Data analysis The most data analysis was performed using Microsoft Excel. In Paper II, the proprietary

conceptual model StormTac Web was used, as explained in detail in section 3.10.

Statistical software MiniTab was used in Paper III to examine the normality of data (using

the Anderson-Darling normality test). Because some variables were not normally

distributed, the Spearman rho correlation coefficient (ρ) was calculated in MiniTab to

examine correlations among different metals and between metal concentrations and soil

properties. The correlation is considered strong if ρ≥0.60, and significant, if the p-value

is

22

The mean metal concentration (C) [mg/kg] and standard deviation (STDEV) were

calculated in each 5 cm layer using all the samples collected in that layer. In the case of

swale L2, which receives stormwater runoff only from one side, the no-runoff side

samples were excluded from calculations of metal burdens. Since no samples were

analysed in the layers 15-20 and 20-25 cm of swales L1 and L3, the mean metal

concentrations and STDEV for those layers were assumed equal to those in the layers 10-

15 and 25-30 cm, respectively.

During dry sieving of soil samples, each sample was split into two sub-samples with

particles 2 mm, and the corresponding sub-sample masses were recorded

for further use in calculating the mean total soil mass in the 5 cm slice (msample [g]) as well

as the fraction of the total sample material < 2 mm [%]. The volume of a 5 cm slice from

the soil corer equals the sample volume (Vsample [m3]), which can be calculated as the

volume of a cylinder with a 5 cm diameter and the height of 5 cm. Soil density (ρsoil

[kg/m3]) was then calculated from the total soil mass in the 5 cm slice and the sample

volume (equation 2):

ρ𝑠𝑜𝑖𝑙 [kg

𝑚3] =

𝑚𝑠𝑎𝑚𝑝𝑙𝑒[𝑔]

1000𝑉𝑠𝑎𝑚𝑝𝑙𝑒 [𝑚

3](2)

Each 5 cm swale soil layer volume (Vlayer) [m3] was calculated as a product of the swale

area [m2] and the layer thickness (5 cm). The area included an upstream swale section,

which was not sampled and, therefore, it was assumed that the soil chemistry data from

the sampled 20 m swale section was representative for the entire swale length.

The mass of soil in each 5 cm layer (Msoil,layer) [kg] was calculated as a product of the soil

density (ρsoil) and the layer volume (Vlayer). Since the metal concentrations were analysed

only in the sieved material (< 2 mm), the mass of soil < 2 mm in each 5 cm layer (M

23

3.8.1. Background concentrations of metals in swale soils

Because the metal content of swale soil samples is a result of both the soil background

(natural) content plus inputs from anthropogenic activities, the background soil metal

burden (Mback) [kg] was subtracted from that calculated from soil samples (as explained in

the previous section). The thought that the samples from the no-runoff side of swale L2

could be used to obtain the native soil chemistry was rejected, because only top soil

samples (0-5 cm) were analysed at that location, and furthermore, such samples could be

contaminated by polluted snow cleared from the road into the swale and also by

atmospheric deposition. Since all the three swales were built using native soils, the metal

concentrations in the deepest analysed layer (25-30 cm) were assumed to provide the best

estimates of the native soil metal content (Table 2).

Table 2: Mean metal concentrations and standard deviation (STDEV) in the deepest sampled layer

Cu [mg/kg DW] Pb [mg/kg DW] Zn [mg/kg DW]

L1 (25–30 cm) 5.7 ± 1.1 2.9 ± 0.8 16.6 ± 3.0

L2 (25–30 cm)1 19.3 ± 1.8 80.1 ± 11.1 61.4 ± 8.5

L3 (25–30 cm) 7.1 ± 0.7 4.4 ± 1.3 17.3 ± 4.5

1Because only two samples were collected from the deepest layer in swale L2, instead of the standard deviation, the

differences of the actual concentrations from the mean of the two samples available for the layer are shown in the

table.

Cumulative metal burden (Mtot) for the 30 cm thick soil layer was calculated as a sum of

metal masses in individual layers (Mmetal), reduced by the background metal burden in

each layer (Mback). Uncertainty of the cumulative metal burden (stot) was calculated by

considering the uncertainty of the mean metal concentrations in the layer (STDEV) using

the law of propagation of uncertainties (equation 4). In such calculations, the

uncertainties in estimating the mass of soil < 2 mm in each 5 cm layer (M< 2 mm) were not

accounted for.

𝑠𝑡𝑜𝑡 = √𝑠𝑚𝑒𝑡𝑎𝑙,12 + 𝑠𝑚𝑒𝑡𝑎𝑙,2

2 + … + 𝑠𝑚𝑒𝑡𝑎𝑙,62 + 𝑠𝑏𝑎𝑐𝑘,1

2 + 𝑠𝑏𝑎𝑐𝑘,22 + ⋯ + 𝑠𝑏𝑎𝑐𝑘,6

2 (4)

where,

smetal,i – uncertainty of the metal mass in the layer obtained by multiplying the standard

deviation of metal concentrations in the layer by the mass of soil material

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3.9. Modelling methods (StormTac Web) A proprietary source-based model StormTac Web was selected to simulate the annual

metal loads of Cu, Pb and Zn discharged into the studied swales and the annual metal

mass retained in their soils. This model was selected for the following reasons: (i) it is

widely used in Sweden for planning and design of stormwater treatment facilities (STFs)

and their maintenance, and (ii) it is a parsimonious model requiring little input data. The

input data included: (i) annual precipitation (rain + snow), (ii) the land use type, including

the corresponding runoff contributing area and the volumetric runoff coefficient, and (iii)

the StormTac Web database standard pollutant concentrations provided for each land use

(Larm, 2000).

The model estimates the annual stormwater pollutant load entering and leaving the swale

[kg/year] (Lin and Lout, respectively), from which the annual load retained in the swale is

determined using site-specific functions. StormTac Web database contains pollutant

reduction efficiencies [%] derived from flow-proportional input and output data for

specific STFs (e.g., swales, biofilters, etc.). The database also includes site-specific data of

the STFs, including the ratio of the STF area to the reduced watershed area (i.e. the

watershed area multiplied by the runoff coefficient). The model calculates regression

equations (RE [%]) for calculating the STF reduction efficiencies. The regression

equation for swales includes the ratio of the swale area to the reduced drainage area,

empirical field data of the pollutant removal by swale compiled in the StormTac Web

database, and additional site specific characteristics, such as inflow concentrations (Larm

and Alm, 2016). The annual load leaving the swale after treatment (Lout [kg/year]) is

calculated using equation 5:

𝐿𝑜𝑢𝑡 = 𝐿𝑖𝑛 −𝑅𝐸

100∗ 𝐿𝑖𝑛 (5)

The annual pollutant mass retained in the swale soil is calculated from the pollutant runoff

input loads minus the loads leaving the swale at the downstream end, after treatment (Lin-

Lout). The StormTac Web model calculates only the annual loads added to the soil from

the polluted stormwater and groundwater, without consideration of the native metal

mass. The retained annual metal loads calculated by the model were then multiplied by

the swale age to obtain the total metal loads to be compared to the loads estimated from

soil samples.

StormTac Web uses adjustment factors (F = 0-10) for each land use category, except the

roads, to calculate land use specific standard concentrations. A factor of 5 indicates

standard conditions of the land use, while factors < 5 and > 5 indicate that the

concentrations should be adjusted towards the minimum or maximum values,

respectively, in the model database. For the roads, the standard concentration is calculated

based on the road traffic intensity (ADT). Available historical ADT data for the three

studied sites were obtained from the Luleå municipality, in order to examine the

25

sensitivity of the calculated retained metal loads to the ADT values. Since the modelled

retained loads were little sensitive to historical variations in ADTs at the study sites, the

mean ADT was used for calculating the retained metal loads. Moreover, the default

options for the land use factor (F = 5) was used for other land covers as well (e.g., the

parking lot, roof etc.). This scenario was called a “standard scenario”.

In order to estimate the modelling uncertainty in calculating the yearly retained metal

mass in swale soils, two additional scenarios were developed for estimating the minimum

and the maximum annual metal loads retained in the swale. Two parameters were

adjusted to obtain those two scenarios, i.e., the land use input concentration and the

swale pollutant reduction efficiency, because these two parameters are directly related to

the modelling of stormwater quality. For the scenario serving to calculate the minimum

retained loads, the minimum traffic intensity from the available historical data was used,

and the minimum factor (F=0) was set for land uses other than roads to obtain the

minimum input concentrations (Cmin) and the associated minimum yearly metal loads

discharged into the swale. Moreover, the swale pollutant reduction efficiency was set to

the minimum values estimated from the StormTac Web database (REmin). For the

scenario estimating the maximum retained loads, the maximum factor (F=10) was set for

each land use and the maximum ADT from the available historical data for the study

location was used, in order to maximise the yearly metal loads into the swale. Also, the

maximum swale pollutant reduction efficiency (REmax) from the model database was set

for this scenario. Finally, the metal burdens calculated from model outputs from these

three scenarios (standard, min and max) were compared to the cumulative metal burdens

from soil samples (reduced by the native soil burdens).

26

27

4. Results This chapter presents synthesis of results in the following order:

(a) The soil characteristics that influence metal immobilisation in swales (infiltration

capacity, loss on ignition (LOI), pH and electrical conductivity (EC)) are presented

in Section 4.1. for the three swales studied,

(b) Short-term metal removal efficiencies of grass swales during runoff conveyance,

reported in previous research, are synthesized in Section 4.2.

(c) Metal burdens retained in swale soils, as a consequence of a long-term exposure to

stormwater runoff, are presented in Section 4.3.

(d) Total metal concentrations in the soils of the three studied swales are presented in

Section 4.4., and

(e) Metal content of the traction material used in the study area in winter road

maintenance is presented in Section 4.5.

4.1. Physico-chemical characteristics of soils in the studied swales

The critical review of grass swales and filter strips identified two main categories of

removal processes of pollutants, other than solids, in overland flow over grass swales and

grass filter strips. Firstly, removal of the particulate fraction (i.e., pollutants attached to

solids) by filtration through the grass and settling. Secondly, removal of the dissolved

fraction from stormwater runoff through infiltration into swale soils, where adsorption,

chemical precipitation, microbial degradation and plant uptake take place.

Thus, stormwater infiltration into swale soils, which can be estimated by measuring the

hydraulic conductivity (Kf), is particularly important for assessing swale operation. Best-

fit estimates of hydraulic conductivities (eq. 1 in Methods, section 3.5) for the three

studied swales, which were built using native soils (Paper III), are shown in Table 3.

Comparison of data from Table 3 to the recommended permeability values for swale

design (Kf > 1.3 cm/h; USEPA, 1999) and dry swales with engineered soils (Kf >3.6

cm/h; Ingvertsen et al. 2012) shows that all three studied swales meet or exceed the

recommended infiltration rates. Particularly, the swale side draining the parking lot next

to swale L3 exhibits significantly higher infiltration rates compared to other swale

sections. This can be explained by the presence of gravel leftover from the parking lot

construction, which also interfered with soil sample collection mentioned in Section 3.5.

28

Kf,best fit [cm/h]

Swale L1 L2 L3

R40 20.7 4.4 1.4

R80 11.2 4.8 4.9

R120 8.6

8.4

R200

21.4 4

Bottom 6.8 7.9 9.9

PL80 4.8

72.4

PL40 9.3

143.4

Examination of infiltration rates can provide an insight into the contact time between the

percolating stormwater and the soil media. High hydraulic conductivities enable

infiltration of significant stormwater volumes into the soil, but also accelerate transport

through the soil matrix. The contact time affects adsorption of the dissolved metals;

longer contact times result in more effective adsorption of metals, until an equilibrium

state is reached (Yousef et al., 1985; Scholes et al., 2008). For example, Pb is mostly

associated with the particulate fraction, while Cu and Zn may also occur in appreciable

quantities in the dissolved fraction (Huber et al., 2016). In order to examine whether

there is a relationship between the measured infiltration rates and the metal

concentrations in the soil, Kf,best fit was related to the mean Zn, Pb and Cu concentrations

(in all the layers) at a certain distance from the pavement edge, as shown in Table 4. No

relationship was observed between the hydraulic conductivity and the mean metal

concentrations (Zn, Pb, and Cu). Achleitner et al. (2007) also did not find any specific

relationship between the hydraulic conductivity and mean metal concentrations of Zn,

Cu, and Pb. When comparing hydraulic conductivities Kf, best fit for the bottom section of

the three studied swales (6.8-9.9 cm/h) against those reported by Rawls et al. (1982) for

soils of various textures, the calculated Kf, best fit corresponded to the soils classified as a

loamy sand (6.11 cm/h). Other soil properties, which may affect immobilisation of metals

in the soil matrix, i.e., LOI, pH and EC, are presented in Tables 5 and 6.

Table 3: Best-fit estimates of the saturated hydraulic conductivity Kf [