# Influence of Temperature and De-Icing Salt on the Sedimentation of Particulate Matter in Traffic Area Runoff

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Monitoring of Full-Scale Sedimentation Tank

^{3}. Runoff from 400 m

^{2}of a heavily trafficked road form the influent to the treatment plant. The annual average daily traffic (AADT) is approximately 24,000 vehicles per day on the attached road surface (46,000 vehicles per day including the separated opposing traffic). The cross-section of the road consists of two traffic lanes, one accelerating lane and one emergency lane with an asphalt surface.

^{−1}for longer than 1 min. Flow was measured by an electro-magnetic flow meter (Krohne Optiflux 1100 C, DN40, error of measurement <1.6% for q > 2.6 L s

^{−1}ha

^{−1}). At the end of the discharge events the sampling stopped. To prevent alteration of samples, they were kept in coolers at 4 ± 1 °C until transport to the lab. Analyses were performed within 72 h.

^{−1}) and SM 4500-H

^{+}, respectively [27]. Electric conductivity was used to verify the de-icing salt application, here sodium chloride (NaCl). Particulate matter was analyzed as total suspended solids (TSS), coarse suspended solids with a diameter greater than 63 μm (SS > 63 µm), and suspended solids between 0.45 µm and 63 µm (SS63). To determine the PM, one liter of sample was sieved by a 1000 µm sieve in the first step, followed by a 63 µm sieve as the second step. In the third step the sieved sample was filtrated under a vacuum over a 0.45 µm membrane filter (cellulose nitrate). Large constituents (>> 1 mm; e.g., leaves, cigarette stubs), which are not representative for the sample, were manually removed. All sieves and filters were dried at 105 °C ± 2 °C until constant mass was achieved. The fine suspended solids (SS63) are the fraction between 0.45 µm and 63 µm, found as residue on the membrane filter. The coarse suspended solids (SS > 63) are the fraction between 1000 µm and 63 µm, found on the 63 µm sieve. Total suspended solids was calculated by the sum of the residues on the 1000 µm and 63 µm sieves, and the 0.45 µm membrane filter after drying. The procedure was a modified method of Dierschke and Welker [28].

#### 2.2. Calculations

#### 2.2.1. Density

_{w}(kg m

^{−3}) were calculated with Equation (1) [25],

_{m}, in this case sodium chloride (NaCl) solutions, were calculated using the model of Laliberté and Cooper [25]. The model considers temperature and concentration of the solute. ρ

_{m}(kg m

^{−3}) was determined with the following Equations (2) and (3):

_{NaCl}= mass fraction of the NaCl in the solution (-) and ${\overline{v}}_{app,NaCl}$ = NaCl specific volume (m

^{3}kg

^{−1}). Equation (3) is valid for w

_{NaCl}> 0.00006 [25], therefore densities of pure water (without NaCl) were calculated with Equation (1).

^{−1}NaCl could be present in traffic area runoff [7,29,30]. Because of the thermal expansivity, this study used the mass fraction of solute NaCl (w

_{NaCl}) to describe the concentration of the solution. A w

_{NaCl}of 0.01 corresponds to 10 g L

^{−1}at 20 °C. To cover extrema, the calculations were conducted up to w

_{NaCl}= 0.02, unless otherwise stated.

#### 2.2.2. Viscosity

_{w}(kg m

^{−1}s

^{−1}) was calculated at temperature t (°C). Equation (4) is valid for t from 0 °C to 100 °C [26].

_{m}(kg m

^{−1}s

^{−1}) were calculated with Equation (5), based on the model of Laliberté [26]:

_{m}= dynamic viscosity of the NaCl solution (kg m

^{−1}s

^{−1}), η

_{w}= dynamic viscosity of water (kg m

^{−1}s

^{−1}), ${\mathrm{w}}_{{\mathrm{H}}_{2}\mathrm{O}}$ = mass fraction of water in the solution (−), w

_{NaCl}= mass fraction of NaCl in the solution (−) and t = temperature (°C). This formula is valid for t ranging from 5 °C to 154 °C and w

_{NaCl}up to 0.264 [26].

#### 2.2.3. Settling Velocity

_{t}(m s

^{−1}) of the particles [31],

^{−2}), η

_{m}= dynamic viscosity of the solution (kg m

^{−1}s

^{−1}), ρ

_{m}= density of the solution (kg m

^{−3}), ρ

_{s}= density of particles (kg m

^{−3}), and d = particle diameter (m).

^{2}s

^{−1}). Reported settling velocities fulfilled this condition, meaning laminar flow conditions were present.

_{s}(1.35 g cm

^{−3}) [34] and a high ρ

_{s}(2.25 g cm

^{−3}) [33] were used. Because fine SS63 are prevalent in traffic area runoff [30,35,36,37] and showed a significant worse settling behavior, this study focused on those particles <63 μm.

#### 2.2.4. Retention of Suspended Solids

_{In}and outflow Q

_{Eff}were assumed to be equal and constant over time as well as inflow TSS. Scouring of retained particles was neglected. In this model particles with a terminal settling velocity equal to or greater than the critical terminal settling velocity v

_{crit}were removed [19]. The v

_{crit}(m s

^{−1}) was equal to the overflow rate determined with Equation (8),

^{3}s

^{−1}) = flow rate and A (m

^{2}) = surface of the sedimentation basin.

_{crit}the critical particle diameter d

_{crit}(µm) was calculated for given conditions like solution temperature, viscosity, density, and particle density. The calculation was conducted with Excel Solver and the solving method GRG nonlinear. Because de-icing salt (NaCl) showed a neglectable effect on the settling velocity (cf. Section 3.2.3), in this step w

_{NaCl}was not considered (set to 0). The water temperature was altered in the range from 5 °C to 25 °C. Additionally, the effect of particle density was studied.

^{−1}ha

^{−1}and 15 L s

^{−1}ha

^{−1}were investigated. The upper value was chosen based on the knowledge that more intense design rain intensities lead to a minor increase in treatment efficiency [39].

_{50}from 6 to 75 μm, and κ was fixed to 0.84 [41].

_{crit}, which is derived from v

_{crit}following Equation (8). Preassigned λ and κ values were used.

## 3. Results and Discussion

#### 3.1. Monitoring of the Full-Scale Sedimentation Tank

_{s}< −0.68). Between SS63 removal and mean inflow q a weak correlation was observable(r

_{s}= −0.34), which induces that even longer residence times in the studied sedimentation tank do not improve the SS63 retention. In contrast, the retention of SS > 63 correlates considerably with q (r

_{s}= −0.71). Overall, this means that the used settling tank is only partially suitable for the retention of fine particulate matter. Only in recent years the SS63 parameter has become popular, and therefore settling tanks were mainly designed to separate the sand fraction (>63 µm). To achieve better settling, the geometry needs to be changed to achieve lower surface loadings, and thus, increased settling times.

_{s}| ≤ 0.40). Because q is increasing with t and decreasing with EC, it can be assumed that this is masking the expected effects. In addition, PSD was not constant (cf. Figure 3), and therefore removal efficiency of the PM was varying. The monitoring will proceed and with increasing data the trend may alter.

#### 3.2. Calculations

#### 3.2.1. Density

_{m}with different w

_{NaCl}at various temperatures. The solution with w

_{NaCl}= 0.00 equates to pure water. Density declines with increasing temperature and increases with increasing w

_{NaCl}. The density anomaly of water affected the NaCl solutions as well. While the highest density of pure water was found at 3.98 °C, in accordance with Kell [43], the density of the NaCl solutions peaked at lower temperatures: 1.58 °C with w

_{NaCl}= 0.02 and up to 3.38 °C with w

_{NaCl}= 0.005. Thereby a trend of shifting the maximum density point towards lower temperatures with increasing w

_{NaCl}was derivable. In Figure 5b, density is plotted as a function of w

_{NaCl}. A linear correlation between ρ

_{m}and w

_{NaCl}is observable. Density affects settling velocity linearly following Equation (6) (Section 2.2.2), causing colder temperatures and higher w

_{NaCl}to lead to a decrease of settling velocity and consequently worse PM retention. Assuming the particle density of ρ

_{s}= 1.35 g cm

^{−1}, the settling velocity at 5 °C and w

_{NaCl}= 0.02 is 5% less than at 20 °C and w

_{NaCl}= 0.00. Though, w

_{NaCl}is an extreme value in this example. Under more likely winter conditions (w

_{NaCl}= 0.01), the effect of density variation on settling velocity is <1%. Consequently, this effect is negligible and probably not measurable in full scale. Please refer the Supplementary Materials (S1) for the densities of NaCl solutions at various temperatures.

#### 3.2.2. Viscosity

_{NaCl}. NaCl showed a kosmotropic effect, meaning it acts as a structure maker and increases the viscosity of the solution compared to pure water [44]. The viscosity of pure water is depicted by the solution with w

_{NaCl}= 0.00.

_{NaCl}< 0.015 (15 g L

^{−1}at 5 to 25 °C) occur [7,30]. Consequently, the viscosity alteration by NaCl does not occur in the full magnitude, which Figure 6a indicates. To investigate the influence of the temperature, the viscosity calculation was carried out with solution temperatures t from 5 to 25 °C with increments of 5 °C following the method of Laliberté [26]. The minimal temperature covered by the model is 5 °C, thus the density peak (cf. Section 3.2.1) cannot be included in the viscosity calculation. Figure 6b shows the viscosity of solutions η

_{m}as a function of w

_{NaCl}at various temperatures. In the considered mass fraction range, a slightly positive linear relation between w

_{NaCl}and η

_{m}is observable. However, the influence of the solution temperature was significantly stronger. Thereby the solutions revealed a higher viscosity at lower temperatures. The settling velocity in a solution with w

_{NaCl}= 0.02 at 5 °C is 35% less than in a solution with w

_{NaCl}= 0.00 at 20 °C. Accordingly, viscosity is the main influencing factor on the settling velocity if particle density and size are constant. The viscosity variation was mainly caused by temperature alteration, not by de-icing salt (NaCl). Please refer the Supplementary Materials (S1) for the viscosities of NaCl solutions at various temperatures.

#### 3.2.3. Settling Velocity

_{NaCl}= 0.02 and summer conditions with t = 20 °C and w

_{NaCl}= 0.00. Figure 7 illustrates settling velocity v

_{t}as a function of particle diameter d. There was a severe difference observable between both scenarios. In winter, 38% lower settling velocities were determined.

_{NaCl}= 0.00. In this case, a 34% lower settling velocity was calculated for winter conditions without NaCl influence. This resulted in the temperature influencing the settling velocity at a bigger magnitude than the de-icing salt.

#### 3.2.4. Retention of Suspended Solids

_{crit}under varying boundary conditions (temperature, flow q, particle density) were determined. The critical particle diameter characterizes the lower limit of particle size, which can be separated in the sedimentation tank.

_{NaCl}from 0.00 to 0.02 was shown to decrease the TSS removal efficiency by less than 0.7%. Therefore, de-icing salt was classified as a negligible factor, which was not considered in the following ranking of the influencing factors.

_{s}, λ or d

_{50}and q) (Table 2). This allowed the influencing factors on the TSS removal efficiency to be ranked. The PSD, specified by d

_{50}or λ, showed the most distinct influence, followed by q and ρ

_{s}. t was classified as the least influencing factor. However, physical characteristics of particles (ρ

_{s}and d

_{50}/PSD) are regarded site-specific [45,46,47,48,49]. Thus, temperature needs to be considered in future SQID designs to improve treatment efficiency during the cold season. Because the applied model cannot represent effects of occurring density currents caused by temperature and de-icing salt, the effect could occur at bigger magnitudes.

_{s}> t of this study was affirmed by Spelman and Sansalone [24]. Additionally, they identified influent hydrograph unsteadiness as the most powerful influencing factor. The hydrograph unsteadiness describes the shape of the hydrograph. A highly unsteady hydrograph rises fast and drops fast after a short time. In comparison to this, a highly steady hydrograph rises slow and drops slow after a long time. Due to the stationary method used in this study, this factor was not assessed. Spelman and Sansalone [24] altered the flow rate q together with the unsteadiness of the influent hydrograph, and therefore, it is not determinable if q or the unsteadiness was the dominant factor. Furthermore, the minimum temperature was 10 °C [24], which is not adequate for the use in the temperate climate zone.

## 4. Conclusions

_{s}> t. The influence of de-icing salt (NaCl) on the sedimentation of PM was negligible. Since PSD and ρ

_{s}are assumed to be site-specific, low temperatures need to be considered to improve effluent quality of SQIDs in the cold season. Low temperatures (5 °C) revealed a decrease of up to 8% TSS removal efficiency compared to higher temperatures (20 °C). The simplified models can be extended in future studies by considering de-icing salt induced particle coagulation, stratification, alternated flow patterns, and non-spherical shape of particles.

## Supplementary Materials

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Abbreviations

A | Area |

AADT | Annual average daily traffic |

CDF | Cumulative distribution function |

d | Particle diameter |

d_{50} | Mass-median-diameter of particles |

DIBt | Deutsches Insitut für Bautechnik |

DWD | German Weather Service |

EC | Electric conductivity |

Eff | Effluent |

g | Gravitational acceleration |

Inf | Influent |

NaCl | Sodium chloride |

PM | Particulate matter |

PSD | Particle size distribution |

Q | Flow rate |

q | Discharge rate, mean inflow |

Q_{Eff} | Outflow |

Q_{In} | Inflow |

RE | Removal efficiency |

Re | Reynold’s number |

r_{s} | Spearman’s rank correlation coefficients |

SQID | Stormwater quality improvement device |

SS > 63 | Suspended solids with particle diameter >63 µm |

SS63 | Suspended solids with particle diameter between 0.45 µm and 63 µm |

SUDS | Sustainable urban drainage systems |

t | Temperature |

TSS | Total suspended solids |

${\overline{v}}_{app,NaCl}$ | NaCl specific volume |

v_{t} | Terminal settling velocity |

w_{H2O} | Mass fraction of water in the solution |

w_{NaCl} | Mass fraction of the NaCl in the solution |

η_{m} | Dynamic viscosity of the NaCl solution |

κ | Scale parameter of CDF |

λ | Shape parameter of CDF |

ν_{m} | Kinematic viscosity of the solution |

ρ_{s} | Particle density |

ρ_{w} | Water density |

ψ | Discharge coefficient |

## References

- Ball, J.E.; Jenks, R.; Aubourg, D. An assessment of the availability of pollutant constituents on road surfaces. Sci. Total Environ.
**1998**, 209, 243–254. [Google Scholar] [CrossRef] - Legret, M.; Pagotto, C. Evaluation of pollutant loadings in the runoff waters from a major rural highway. Sci. Total Environ.
**1999**, 235, 143–150. [Google Scholar] [CrossRef] - McKenzie, E.R.; Money, J.E.; Green, P.G.; Young, T.M. Metals associated with stormwater-relevant brake and tire samples. Sci. Total Environ.
**2009**, 407, 5855–5860. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Wik, A.; Dave, G. Occurrence and effects of tire wear particles in the environment—A critical review and an initial risk assessment. Environ. Pollut.
**2009**, 157, 1–11. [Google Scholar] [CrossRef] [PubMed] - Huber, M.; Welker, A.; Helmreich, B. Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning. Sci. Total Environ.
**2016**, 541, 895–919. [Google Scholar] [CrossRef] [PubMed] - Kayhanian, M.; Fruchtman, B.D.; Gulliver, J.S.; Montanaro, C.; Ranieri, E.; Wuertz, S. Review of highway runoff characteristics: Comparative analysis and universal implications. Water Res.
**2012**, 46, 6609–6624. [Google Scholar] [CrossRef] [PubMed] - Huber, M.; Welker, A.; Drewes, J.E.; Helmreich, B. Auftausalze im Straßenwinterdienst—Aufkommen und Bedeutung für dezentrale Behandlungsanlagen von Verkehrsflächenabflüssen zur Versickerung (De-icing salts in road maintenance—Occurrence and impact on decentralized systems treating traffic area runoff for infiltration). GWF Wasser/Abwasser
**2015**, 156, 1138–1152. [Google Scholar] - Fay, L.; Shi, X. Environmental impacts of chemicals for snow and ice control: State of the knowledge. Water Air Soil Pollut.
**2012**, 223, 2751–2770. [Google Scholar] [CrossRef] - Murray, D.C.; Ernst, U.F.W. An Economic Analysis of the Environmental Impact of Highway Deicing; USEPA 600/2-76-033; US EPA: Washington, DC, USA, 1976.
- Helmreich, B.; Hilliges, R.; Schriewer, A.; Horn, H. Runoff pollutants of a highly trafficked urban road—Correlation analysis and seasonal influences. Chemosphere
**2010**, 80, 991–997. [Google Scholar] [CrossRef] [PubMed] - Shi, X.; Akin, M.; Pan, T.; Fay, L.; Liu, Y.; Yang, Z. Deicer impacts on pavement materials: Introduction and recent developments. Open Civ. Eng. J.
**2009**, 3, 16–27. [Google Scholar] [CrossRef] - Dierkes, C.; Lucke, T.; Helmreich, B. General technical approvals for decentralised sustainable urban drainage systems (suds)—The current situation in germany. Sustainability
**2015**, 7, 3031–3051. [Google Scholar] [CrossRef] - Huber, M.; Helmreich, B.; Welker, A. Einführung in Die Dezentrale Niederschlagswasserbehandlung für Verkehrsflächen- und Metalldachabflüsse: Schacht-/Kompaktsysteme, Rinnensysteme, Straßeneinläufe und Flächenbeläge (Introduction on Decentralized Stormwater Treatment of Traffic Area and Metal Roof Runoff); Technische Universität München Garching: München, Germany, 2015; Volume 213, p. 96. ISSN 0942-914X. [Google Scholar]
- Rommel, S.H.; Helmreich, B. Feinpartikuläre Stoffe (AFS63) in Verkehrsflächenabflüssen—Vorkommen und Relevanz für Dezentrale Behandlungsanlagen (Fine Particulate Matter (SS63) in Traffic Area Runoff—Occurrence and Relevance for Decentralized Treatment Systems). In Proceedings of the Aqua Urbanica Trifft RegenwasserTage, Landau (Pfalz), Germany, 18–19 June 2018; Schmitt, T.G., Ed.; Technische Universität Kaiserslautern: Kaiserslautern, Germany, 2018; pp. 159–178. [Google Scholar]
- Semadeni–Davies, A. Winter performance of an urban stormwater pond in southern sweden. Hydrol. Process.
**2006**, 20, 165–182. [Google Scholar] [CrossRef] - Hendi, E.; Shamseldin, A.Y.; Melville, B.W.; Norris, S.E. Experimental investigation of the effect of temperature differentials on hydraulic performance and flow pattern of a sediment retention pond. Water Sci. Technol.
**2018**, 77, 2896–2906. [Google Scholar] [CrossRef] [PubMed] - Adamsson, Å.; Bergdahl, L. Simulation of temperature influence on flow pattern and residence time in a detention tank. Hydrol. Res.
**2006**, 37, 53–68. [Google Scholar] [CrossRef] - Marsalek, J.; Oberts, G.; Exall, K.; Viklander, M. Review of operation of urban drainage systems in cold weather: Water quality considerations. Water Sci. Technol.
**2003**, 48, 11–20. [Google Scholar] [CrossRef] [PubMed] - Tchobanoglous, G.; Burton, F.L.; Stensel, H.D. Wastewater Engineering: Treatment and Resource Recovery; McGraw-Hill Education: Berkshire, UK, 2014. [Google Scholar]
- Winkler, M.K.H.; Bassin, J.P.; Kleerebezem, R.; van der Lans, R.G.J.M.; van Loosdrecht, M.C.M. Temperature and salt effects on settling velocity in granular sludge technology. Water Res.
**2012**, 46, 5445–5451. [Google Scholar] [CrossRef] [PubMed] - Krishnappan, B.G.; Marsalek, J.; Watt, W.E.; Anderson, B.C. Seasonal size distributions of suspended solids in a stormwater management pond. Water Sci. Technol.
**1999**, 39, 127–134. [Google Scholar] [CrossRef] - Krishnappan, B.G.; Marsalek, J. Modelling of flocculation and transport of cohesive sediment from an on-stream stormwater detention pond. Water Res.
**2002**, 36, 3849–3859. [Google Scholar] [CrossRef] - Lau, Y.L. Temperature effect on settling velocity and deposition of cohesive sediments. J. Hydraul. Res.
**1994**, 32, 41–51. [Google Scholar] [CrossRef] - Spelman, D.; Sansalone, J.J. Is the treatment response of manufactured bmps to urban drainage pm loads portable? J. Environ. Eng.
**2018**, 144. [Google Scholar] [CrossRef] - Laliberté, M.; Cooper, W.E. Model for calculating the density of aqueous electrolyte solutions. J. Chem. Eng. Data
**2004**, 49, 1141–1151. [Google Scholar] [CrossRef] - Laliberté, M. Model for calculating the viscosity of aqueous solutions. J. Chem. Eng. Data
**2007**, 52, 321–335. [Google Scholar] [CrossRef] - Baird, R.; Eaton, A.D.; Rice, E.W.; Bridgewater, L.; American Public Health Association; American Water Works, Association; Water Environment Federation. Standard Methods for the Examination of Water and Wastewater; American Public Health Association, American Water Works Association, Water Environment Federation: Washington, DC, USA, 2017; ISBN 978-087553-287-5. [Google Scholar]
- Dierschke, M.; Welker, A. Bestimmung von Feststoffen in Niederschlagsabflüssen (Method for measuring suspended solids in runoffs). GWF Wasser/Abwasser
**2015**, 156, 440–446. [Google Scholar] - Sansalone, J.J.; Glenn, D.W. Accretion of pollutants in snow exposed to urban traffic and winter storm maintenance activities. I. J. Environ. Eng.
**2002**, 128, 151–166. [Google Scholar] [CrossRef] - Hilliges, R.; Endres, M.; Tiffert, A.; Brenner, E.; Marks, T. Characterization of road runoff with regard to seasonal variations, particle size distribution and the correlation of fine particles and pollutants. Water Sci. Technol.
**2017**, 75, 1169–1176. [Google Scholar] [CrossRef] [PubMed] - Sansalone, J.; Lin, H.; Ying, G. Experimental and field studies of type I settling for particulate matter transported by urban runoff. J. Environ. Eng.
**2009**, 135, 953–963. [Google Scholar] [CrossRef] - Sansalone, J.J.; Koran, J.M.; Smithson, J.A.; Buchberger, S.G. Physical characteristics of urban roadway solids transported during rain events. J. Environ. Eng.
**1998**, 124, 427–440. [Google Scholar] [CrossRef] - Kayhanian, M.; McKenzie, E.R.; Leatherbarrow, J.E.; Young, T.M. Characteristics of road sediment fractionated particles captured from paved surfaces, surface run-off and detention basins. Sci. Total Environ.
**2012**, 439, 172–186. [Google Scholar] [CrossRef] [PubMed] - Li, Y.; Kang, J.-H.; Lau, S.-L.; Kayhanian, M.; Stenstrom, M.K. Optimization of settling tank design to remove particles and metals. J. Environ. Eng.
**2008**, 134, 885–894. [Google Scholar] [CrossRef] - Li, Y.; Lau, S.; Kayhanian, M.; Stenstrom, M. Dynamic characteristics of particle size distribution in highway runoff: Implications for settling tank design. J. Environ. Eng.
**2006**, 132, 852–861. [Google Scholar] [CrossRef] - Gunawardana, C.; Egodawatta, P.; Goonetilleke, A. Role of particle size and composition in metal adsorption by solids deposited on urban road surfaces. Environ. Pollut.
**2014**, 184, 44–53. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Charters, F.J.; Cochrane, T.A.; O’Sullivan, A.D. Particle size distribution variance in untreated urban runoff and its implication on treatment selection. Water Res.
**2015**, 85, 337–345. [Google Scholar] [CrossRef] [PubMed] - DIBt. Teil 1: Anlagen zur dezentralen Behandlung des Abwassers von Kfz-Verkehrsflächen zur anschließenden Versickerung in Boden und Grundwasser (Devices treating traffic area runoff for percolation into soil and groundwater). In Zulassungsgrundsätze Niederschlagswasserbehandlungsanlagen (Approval Principles for Stormwater Quality Improvement Devices); Deutsches Insitut für Bautechnik: Berlin, Germany, 2017. [Google Scholar]
- DWA-A 102 (Draft). Grundsätze zur Bewirtschaftung und Behandlung von Regenwetterabflüssen zur Einleitung in Oberflächengewässer (Principles for Management and Treatment of Runoff for Discharge into Surface Waters); DWA Deutsche Vereinigung für Wasserwirtschaft, Abwasser und Abfall e. V.: Hennef, Germany, 2016. [Google Scholar]
- Selbig, W.R.; Fienen, M.N. Regression modeling of particle size distributions in urban storm water: Advancements through improved sample collection methods. J. Environ. Eng.
**2012**, 138, 1186–1193. [Google Scholar] [CrossRef] - Lee, D.H.; Min, K.S.; Kang, J.-H. Performance evaluation and a sizing method for hydrodynamic separators treating urban stormwater runoff. Water Sci.
**2014**, 69, 2122–2131. [Google Scholar] [CrossRef] [PubMed] - Bardin, J.P.; Barraud, S.; Chocat, B. Uncertainty in measuring the event pollutant removal performance of online detention tanks with permanent outflow. Urban Water
**2001**, 3, 91–106. [Google Scholar] [CrossRef] - Kell, G.S. Density, thermal expansivity, and compressibility of liquid water from 0 to 150 °C: Correlations and tables for atmospheric pressure and saturation reviewed and expressed on 1968 temperature scale. J. Chem. Eng. Data
**1975**, 20, 97–105. [Google Scholar] [CrossRef] - Corridoni, T.; Mancinelli, R.; Ricci, M.A.; Bruni, F. Viscosity of aqueous solutions and local microscopic structure. J. Phys. Chem. B
**2011**, 115, 14008–14013. [Google Scholar] [CrossRef] [PubMed] - Faram, M.G.; Iwugo, K.O.; Andoh, R.Y.G. Characteristics of urban run-off derived sediments captured by proprietary flow-through stormwater interceptors. Water Sci. Technol.
**2007**, 56, 21–27. [Google Scholar] [CrossRef] [PubMed] - Gunawardana, C.; Goonetilleke, A.; Egodawatta, P.; Dawes, L.; Kokot, S. Source characterisation of road dust based on chemical and mineralogical composition. Chemosphere
**2012**, 87, 163–170. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Gunawardena, J.M.A.; Liu, A.; Egodawatta, P.; Ayoko, G.A.; Goonetilleke, A. Influence of traffic and land use on pollutant transport pathways. In Influence of Traffic and Land Use on Urban Stormwater Quality: Implications for Urban Stormwater Treatment Design; Springer: Singapore, 2018; pp. 27–54. [Google Scholar]
- Ferreira, M.; Stenstrom, M.K. The importance of particle characterization in stormwater runoff. Water Environ. Res.
**2013**, 85, 833–842. [Google Scholar] [CrossRef] [PubMed] - Selbig, W.R.; Bannerman, R.T. Characterizing the Size Distribution of Particles in Urban Stormwater by Use of Fixed-Point Sample-Collection Methods; US Geological Survey: Reston, VA, USA, 2011.
- Li, Y.; Lau, S.; Kayhanian, M.; Stenstrom, M. Particle size distribution in highway runoff. J. Environ. Eng.
**2005**, 131, 1267–1276. [Google Scholar] [CrossRef] - Faltermaier, S.; Krause, S.; Günther, F.W. Einfluss von Streusalz auf die Flockung Partikulärer Stoffe in Regenbecken an Autobahnen (Influence of De-Icing Salt on the Flocculation of Particulate Matter in Stormwater Tanks on Motorways); Aqua Urbanica 2017; Muschalla, D., Gruber, G., Eds.; TU Graz, Institut für Siedlungswasserwirtschaft und Landschaftswasserbau: Graz, Austria, 2017. [Google Scholar]
- Portela, L.I.; Ramos, S.; Teixeira, A.T. Effect of salinity on the settling velocity of fine sediments of a harbour basin. J. Coast. Res.
**2013**, 65, 1188–1193. [Google Scholar] [CrossRef] - Sutherland, B.R.; Barrett, K.J.; Gingras, M.K. Clay settling in fresh and salt water. Environ. Fluid Mech.
**2015**, 15, 147–160. [Google Scholar] [CrossRef] - Duzgoren-Aydin, N.S.; Wong, C.S.C.; Song, Z.G.; Aydin, A.; Li, X.D.; You, M. Fate of heavy metal contaminants in road dusts and gully sediments in guangzhou, se china: A chemical and mineralogical assessment. Hum. Ecol. Risk Assess. Int. J.
**2006**, 12, 374–389. [Google Scholar] [CrossRef] - Bäckström, M. Sediment transport in grassed swales during simulated runoff events. Water Sci. Technol.
**2002**, 45, 41–49. [Google Scholar] [CrossRef] [PubMed]

**Figure 1.**(

**a**) Influent (

**left**) and effluent (

**right**) samples of a sedimentation tank for road runoff treatment withdrawn during the cold season. Minor difference can be seen in turbidity between the two samples. (

**b**) Diagram showing which influencing factors cause worse effluent quality and total suspended solids (TSS) retention of sedimentation tanks for treatment of road runoff during winter season; grey arrow indicates weaker influence (adapted from Semadeni–Davies [15]).

**Figure 2.**Annual course of TSS influent and effluent of the sedimentation tank and TSS retention; two successive data points of TSS retention were removed due to strong scouring of sediments of previous events (−185% and −365% TSS retention).

**Figure 3.**Fraction of fine particulate matter (PM) (SS63) in the TSS in the influent and effluent of the sedimentation tank as a function of temperature.

**Figure 4.**Correlation matrix of Spearman’s rank correlation coefficients r

_{s}of full-scale sedimentation tank monitoring; q = mean inflow (L s

^{−1}ha

^{−1}), t = water temperature in tank (°C), EC eff. = effluent electrical conductivity (μS cm

^{−1}), TSS in = influent TSS (mg L

^{−1}), TSS eff = effluent TSS (mg L

^{−1}), RE TSS = removal efficiency of TSS (%), RE SS63 = removal efficiency of SS63 (%), RE SS63 = removal efficiency of SS > 63 (%), n = 15 for SS63 and n = 23 for all other parameters.

**Figure 5.**(

**a**) Density of aqueous NaCl solutions as a function of temperature for various w

_{NaCl}; (

**b**) density of aqueous NaCl solutions as a function of w

_{NaCl}for t = 5 °C and t = 20 °C.

**Figure 6.**(

**a**) Viscosity of various aqueous NaCl solutions at 20 °C; (

**b**) viscosity of aqueous NaCl solutions at various temperatures.

**Figure 7.**Settling velocity as a function of particle diameter in two aqueous solutions at various temperatures and w

_{NaCl}simulating winter and summer conditions (extrema); both ρ

_{s}= 1.35 g cm

^{−1.}

**Figure 8.**Critical particle diameter d

_{crit}for settling, various water temperatures and particle densities.

**Figure 9.**(

**a**) TSS removal efficiency as a function of temperature; (

**b**) TSS removal efficiency as a function of w

_{NaCl}, λ = 60, d

_{50}= 39 μm; (

**a**,

**b**): ρ

_{s}= 1.35 g cm

^{−1}; q = 15 L s

^{−1}ha

^{−1}.

**Table 1.**Statistics of full-scale sedimentation tank monitoring: q = mean inflow; t = water temperature in sedimentation tank; TSS Inf. = influent TSS; SS63 Inf. = influent SS63; EC Eff. = electric conductivity in effluent.

Parameter | Unit | n | Min | 25th Percentile | Median | Mean | 75th Percentile | Max | SD |
---|---|---|---|---|---|---|---|---|---|

q | L s^{−1} ha^{−1} | 23 | 1.6 | 3.4 | 5.7 | 8.1 | 7.2 | 26.1 | 7.5 |

t | °C | 23 | 3.0 | 8.8 | 17.5 | 17.5 | 21.7 | 24.6 | 7.3 |

TSS Inf. | mg L^{−1} | 23 | 7 | 32 | 82 | 123 | 166 | 433 | 129 |

SS > 63 Inf. | mg L^{−1} | 15 | 3 | 18 | 26 | 35 | 46 | 122 | 30 |

SS63 Inf. | mg L^{−1} | 15 | 8 | 18 | 73.3 | 121 | 140 | 394 | 130 |

EC Eff. | µS cm^{−1} | 22 | 59 | 95 | 119 | 119 | 867 | 4790 | 1225 |

TSS retention | % | 21 | −365 | 22 | 44 | 18 | 68 | 95 | 105 |

SS > 63 retention | % | 15 | −4 | 65 | 83 | 71 | 93 | 100 | 31 |

SS63 retention | % | 15 | −49 | −1 | 37 | 25 | 57 | 80 | 40 |

**Table 2.**Pearson correlation coefficients between TSS removal efficiency, temperature t, particle density ρ

_{s}, median particle diameter d

_{50}and discharge rate q.

t | ρ_{s} | d_{50} | q | |
---|---|---|---|---|

TSS removal efficiency | 0.07 | 0.22 | 0.85 | −0.32 |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Rommel, S.H.; Helmreich, B.
Influence of Temperature and De-Icing Salt on the Sedimentation of Particulate Matter in Traffic Area Runoff. *Water* **2018**, *10*, 1738.
https://doi.org/10.3390/w10121738

**AMA Style**

Rommel SH, Helmreich B.
Influence of Temperature and De-Icing Salt on the Sedimentation of Particulate Matter in Traffic Area Runoff. *Water*. 2018; 10(12):1738.
https://doi.org/10.3390/w10121738

**Chicago/Turabian Style**

Rommel, Steffen H., and Brigitte Helmreich.
2018. "Influence of Temperature and De-Icing Salt on the Sedimentation of Particulate Matter in Traffic Area Runoff" *Water* 10, no. 12: 1738.
https://doi.org/10.3390/w10121738