Transformation Processes of Metals in Urban Road Dust: Implications for Stormwater Reuse [1st ed. 2020] 978-981-15-2077-8, 978-981-15-2078-5

Table of contents :
Front Matter ....Pages i-vi
Metals in the Urban Stormwater Environment (Ayomi Jayarathne, Buddhi Wijesiri, Prasanna Egodawatta, Godwin A Ayoko, Ashantha Goonetilleke)....Pages 1-10
Research Design for Investigating Metal Transformations on Urban Roads (Ayomi Jayarathne, Buddhi Wijesiri, Prasanna Egodawatta, Godwin A Ayoko, Ashantha Goonetilleke)....Pages 11-20
Metal Transformation and Stormwater Quality (Ayomi Jayarathne, Buddhi Wijesiri, Prasanna Egodawatta, Godwin A Ayoko, Ashantha Goonetilleke)....Pages 21-32
Assessment of Human Health Risks from Metals in Urban Stormwater Based on Geochemical Fractionation and Bioavailability (Ayomi Jayarathne, Buddhi Wijesiri, Prasanna Egodawatta, Godwin A Ayoko, Ashantha Goonetilleke)....Pages 33-43
Practical Implications and Recommendation for Future Research (Ayomi Jayarathne, Buddhi Wijesiri, Prasanna Egodawatta, Godwin A Ayoko, Ashantha Goonetilleke)....Pages 45-48
Back Matter ....Pages 49-50

Citation preview

SPRINGER BRIEFS IN WATER SCIENCE AND TECHNOLOGY

Ayomi Jayarathne · Buddhi Wijesiri · Prasanna Egodawatta · Godwin A Ayoko · Ashantha Goonetilleke

Transformation Processes of Metals in Urban Road Dust Implications for Stormwater Reuse 123

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SpringerBriefs in Water Science and Technology present concise summaries of cutting-edge research and practical applications. The series focuses on interdisciplinary research bridging between science, engineering applications and management aspects of water. Featuring compact volumes of 50 to 125 pages (approx. 20,000–70,000 words), the series covers a wide range of content from professional to academic such as: • • • • •

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Ayomi Jayarathne Buddhi Wijesiri Prasanna Egodawatta Godwin A Ayoko Ashantha Goonetilleke •

•

•

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Transformation Processes of Metals in Urban Road Dust Implications for Stormwater Reuse

123

Ayomi Jayarathne Science and Engineering Faculty Queensland University of Technology Brisbane, QLD, Australia

Buddhi Wijesiri Science and Engineering Faculty Queensland University of Technology Brisbane, QLD, Australia

Prasanna Egodawatta Science and Engineering Faculty Queensland University of Technology Brisbane, QLD, Australia

Godwin A Ayoko Science and Engineering Faculty Queensland University of Technology Brisbane, QLD, Australia

Ashantha Goonetilleke Science and Engineering Faculty Queensland University of Technology Brisbane, QLD, Australia

ISSN 2194-7244 ISSN 2194-7252 (electronic) SpringerBriefs in Water Science and Technology ISBN 978-981-15-2077-8 ISBN 978-981-15-2078-5 (eBook) https://doi.org/10.1007/978-981-15-2078-5 © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Contents

1 Metals in the Urban Stormwater Environment . . . . . . 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Metals in Urban Roads . . . . . . . . . . . . . . . . . . . . . 1.3 Understanding the Behavioural Changes of Metals and Potential Stormwater Quality Impacts . . . . . . . 1.3.1 Adsorption . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Surface Precipitation . . . . . . . . . . . . . . . . . 1.3.3 Oxidation-Reduction . . . . . . . . . . . . . . . . . 1.4 Factors Influencing Metal Transformation . . . . . . . 1.4.1 Physicochemical Properties of Road Dust . . 1.4.2 Environmental Factors . . . . . . . . . . . . . . . . 1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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2 Research Design for Investigating Metal Transformations on Urban Roads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Study Area and Study Sites . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Sample Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Study Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Road Dust Sample Collection . . . . . . . . . . . . . . . . . . 2.3.3 Sample Handling, Storage and Subsampling . . . . . . . 2.4 Laboratory Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Selection of Test Parameters . . . . . . . . . . . . . . . . . . . 2.4.2 Analysis of Metals . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3 Analysis of Physicochemical Properties of Road Dust 2.4.4 Quality Control and Quality Assurance . . . . . . . . . . . 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3 Metal Transformation and Stormwater Quality . . . . . . . . . 3.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Relationships Between Mobility and Bioavailability of Metals and Geochemical Fractions . . . . . . . . . . . . . . 3.3 Influence of Particle Size of Road Dust on Geochemical Behaviour of Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Time Dependent Metal Transformation . . . . . . . . . . . . . 3.4.1 Transformation of Zn . . . . . . . . . . . . . . . . . . . . . 3.4.2 Transformation of Cu . . . . . . . . . . . . . . . . . . . . . 3.4.3 Transformation of Pb . . . . . . . . . . . . . . . . . . . . . 3.4.4 Transformation of Cd . . . . . . . . . . . . . . . . . . . . . 3.5 Influence of Metal Transformation and Mobility on Stormwater Quality . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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4 Assessment of Human Health Risks from Metals in Urban Stormwater Based on Geochemical Fractionation and Bioavailability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Risk Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Human Health Risk Indices . . . . . . . . . . . . . . . . . . 4.2.2 Drawbacks in Classical Risk Indices . . . . . . . . . . . . 4.3 Assessing Metal Concentration in Stormwater Using Metal Build-Up Load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Human Health Risk Assessment . . . . . . . . . . . . . . . . . . . . 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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5 Practical Implications and Recommendation for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Implications of Research Outcomes . . . . . . . . . . . . . . . . 5.2.1 Implications Related to Transformation Processes of Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Implications Related to Human Health Risk Assessment of Metals in Stormwater . . . . . . . . . . 5.3 Recommendations for Future Research . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 1

Metals in the Urban Stormwater Environment

Abstract Stormwater reuse is one of the viable alternatives to overcome the growing water demand in urban areas. However, effective use of stormwater as an alternative water resource is constrained due to the presence of toxic pollutants generated by natural and anthropogenic processes. Stormwater quality is further impacted by the behavioural changes to pollutants, resulting from the transformation of their physical and chemical characteristics. The transformed pollutants can have different persistence, toxicity, mobility and bioavailability characteristics compared to their original form. Therefore, improving stormwater quality by understanding the behavioural changes of pollutants and quantification of the associated risks of transformed pollutants is essential to ensure the safe use of stormwater. This chapter discusses the potential transformation characteristics of metals associated with road dust, which is among the major toxic pollutants found in urban areas, and the factors influencing metal transformations and resulting stormwater quality impacts. Keywords Metals · Road dust · Transformations · Pollutant build-up · Stormwater quality · Stormwater pollution processes

1.1 Background The sustainable use of water resources has received significant attention in recent decades due to the increasing demand for water for potable purposes as a result of rapid population growth in urban areas together with improved living standards (Begum et al. 2008; Liu et al. 2015). On the other hand, the increasing impacts of climate change imposes a significant influence on water resources. As freshwater is a finite resource, seeking alternatives to meet the growing demand for water is important in order to ensure community well-being. In this context, stormwater has been identified as a viable water resource that can be utilised for a range of water demanding purposes (Begum et al. 2008; Liu et al. 2015; Nnadi et al. 2015). The concept of using stormwater of appropriate quality is referred to as ‘fit-for-purpose’ reuse. For example, reuse of untreated or minimally-treated stormwater would be suitable for low-quality water requirements such as for toilet flushing, gardening and construction and for high-quality water needs such as groundwater recharge. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5_1

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However, the effective use of stormwater originating from urban areas is a challenge since urban stormwater runoff commonly contains toxic pollutants such as metals and hydrocarbons. In urban areas, natural and anthropogenic processes result in the generation and deposition of pollutants on impervious surfaces such as roads, driveways and roofs. During rainfall events, these pollutants are mobilised and transported by stormwater runoff, resulting in the discharge of relatively high pollutant loads to receiving water environments. Consequently, stormwater runoff originating from impervious surfaces such as road surfaces is considered as a major non-point source of pollution to urban water environments that can cause physical, chemical and biological changes in water bodies. Stormwater quality is dependent on the characteristics of pollutants entrained into stormwater runoff. During dry weather periods, pollutants are subjected to dynamic changes, undergoing different physical and chemical transformations (Egodawatta et al. 2007; Gunawardana et al. 2015; Wijesiri et al. 2015). The transformed pollutants with variable persistence, mobility, bioavailability and toxicity characteristics can change the characteristics of stormwater. Therefore, improving stormwater quality by understanding behavioural changes of pollutants and resulting stormwater quality impacts is needed to ensure the safe use of stormwater. More importantly, human health risks associated with stormwater pollutants should also be undertaken by considering the various reuse purposes. A summary of the generic pathway to ‘fitfor-purpose’ stormwater reuse strategy is illustrated in Fig. 1.1. Low-quality water requirements

Stormwater reuse High-quality water requirements

Improving stormwater quality Human health risks assessment of stormwater pollutants Understanding potential stormwater quality impacts

Fig. 1.1 Conceptual representation of the generic pathway to ‘fit-for-purpose’ stormwater reuse

1.2 Metals in Urban Roads

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1.2 Metals in Urban Roads Metals are one of the hazardous pollutants commonly found on urban roads that can cause detrimental impacts on human and ecosystem health (Jayarathne et al. 2018a; Ma et al. 2017). Increased quantity of metals in receiving water environments can be toxic to aquatic organisms, while human exposure to metal contaminated soil and/or water can cause short-term and/or long-term health impacts such as skin irritations, breathing problems and carcinogenic effects (Martin and Griswold 2009; Shi et al. 2011). Although there are a diverse range of metal species present in urban environments, zinc (Zn), copper (Cu), lead (Pb), cadmium (Cd), chromium (Cr) and nickel (Ni) have received significant attention due to their acute and chronic toxic impacts. Traffic and land use related activities are the major sources of metals accumulated on urban roads (Huber et al. 2016; Liu et al. 2016; Mummullage et al. 2014). For example, Zn, Ni and Cd are the primary metals associated with tyre wear, whilst brake abrasion and brake dust commonly contain Cu. Furthermore, industrial activities such as metal smelting, gasworks, food processing and commercial incineration generate high amounts of metals (Brown and Peake 2006). Apart from these sources, natural sources of metals on urban roads include weathering and erosion of surrounding soils, and corrosion of metallic surfaces such as roofs, fences and gutters and other building components.

1.3 Understanding the Behavioural Changes of Metals and Potential Stormwater Quality Impacts Metals build-up on road surfaces are intrinsically associated with a complex mix of organic and inorganic constituents of road dust. During dry weather periods, metals associated with road dust are subjected to behavioural changes, resulting from the transformation of their original physical and chemical forms. These processes can be influenced by the physicochemical properties of road dust such as particle size, specific surface area and organic matter content, and prevailing environmental conditions such as residence time of pollutants on the urban surface and humidity (Gunawardana et al. 2015; Jayarathne et al. 2018b). As depicted in Fig. 1.2, the transformed metals can subsequently impact stormwater quality due to the characteristic changes to mobility, bioavailability and toxicity compared to their original form. Among different transformations, adsorption, surface precipitation and oxidationreduction can be identified as the key processes influencing the changes in physical and chemical characteristics of metals (Akpomie et al. 2015; Bradl 2004; Demirbas 2008; Ritter et al. 2002).

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Metals build-up

Physicochemical properties of road dust

Transformations

Environmental factors

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Transformed metals Mobility Bioavailability Toxicity Wash-off

Stormwater Quality Fig. 1.2 The relationship between metal transformation and stormwater quality

1.3.1 Adsorption Adsorption is a primary mechanism that determines the chemical interaction between metal species and road dust particles (Sparks 2003; Weber et al. 1991). Metal ions interact with chemically reactive surface functional groups on particle surfaces, creating either outer-sphere or inner-sphere adsorption complexes (Chen et al. 2013; Harrison 2007). The nature of the metal adsorption complexes depends on the type of interaction force created between metal ions and reactive charged sites. Inner-sphere metal complexes are relatively strong compared to the outer-sphere complexes due to the association of covalent or ionic interactions. Ion-exchange and chemisorption can be identified as two primary types of adsorption processes in relation to outer-sphere and inner-sphere complexation, respectively. In ion-exchange, metals interact with the particle surface by exchanging originally attached metal ions with the surface in a stoichiometric manner (Chorover and Brusseau 2008; Sparks 2003). Due to the weak metal-particulate attachment, ion-exchangeable metals have high mobility and bioavailability characteristics. As reported in past studies, the order of mobility based on metal enrichment in the exchangeable fraction are: Cd > Zn > Pb > Cu (Li et al. 2001), Cd > Zn > Pb > Cu > Ni (Duong and Lee 2009), Zn > Pb > Cd > Cu > Mn > Co > Ni > Cr > Fe (Zhang and Wang 2009), Cd > Mn > Zn > Cu > Ni > Pb > Cr > Co (Ozcan and Altundag 2013) and Cd > Zn > Cu > Pb > Mn > Ni > Cr (Jayarathne et al. 2017). Accordingly, the contamination of stormwater by metals such as Zn and Cd can influence stormwater quality due to their readily available nature.

1.3 Understanding the Behavioural Changes of Metals …

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In chemisorption, metals are firmly attached to the particle surface by exchanging electrons between metal ions and surface functional groups (Huang et al. 2011; Sposito 2008; Worch 2012). Organic and inorganic constituents of road dust contain a variety of chemically reactive surface functional groups such as hydroxyl, carboxyl, carbonyl and phenolic groups for chemisorption reactions. Protonation and deprotonation are the main mechanisms involved in the development of favourable charge sites on surface functional groups. Due to the firm chemical attachment, chemisorbed metals are barely desorbed from particle surfaces, thereby having low mobility and bioavailability.

1.3.2 Surface Precipitation Surface precipitation becomes a dominant chemical transformation process followed by adsorption when metal ion concentration exceeds a certain threshold limit. At high pH levels, metals react with anionic groups such as PO4 3− , CO3 2− and OH− , and tend to precipitate as a new solid phase. The common metal precipitates formed in alkaline conditions are carbonates and phosphates, whilst in acidic conditions, hydroxides are dominant (Pitt et al. 1999). Precipitated products are usually present as coatings on mineral surfaces, and due to their low solubility, the environmental impacts in terms of their mobility and bioavailability are low (Sparks 2003; Zhuang and Yu 2002). In relation to road surfaces, surface precipitation is not necessarily a prominent transformation process as the cationic and anionic concentrations in road dust are relatively low compared to that of surrounding soils (Gunawardana et al. 2012; Jayarathne et al. 2019a). However, due to the variability in metal build-up on roads, there is potential for surface precipitation to play a role particularly in places where there is relatively higher concentration pockets of metals. On the other hand, due to low specific surface area and internal pore development in road dust, some researchers have attributed surface precipitation as a primary transformation process influencing the interaction between metal ions and road dust particles, over adsorption (Djuki´c et al. 2016).

1.3.3 Oxidation-Reduction Metals undergo oxidation-reduction reactions as a result of the simultaneous loss and gain of electrons from the valence shells. Depending on the number of electrons removed or added, metals can have multiple oxidation-reduction products, which are either in cationic or anionic forms (Sparks 2003). The adsorption characteristics, bioavailability and toxicity of oxidised or reduced species can vary from one metal

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ion to another. For example, Cr (6+), one of the oxidation products of Cr, has low chemisorption ability compared to Cr (3+) (Violante et al. 2010). Due to its high bioavailability and toxicity characteristics, Cr (6+) is known as a carcinogenic metal species.

1.4 Factors Influencing Metal Transformation 1.4.1 Physicochemical Properties of Road Dust Physical and chemical properties of road dust such as particle size, specific surface area (SSA), cation exchange capacity (CEC) and mineralogy can significantly influence metal transformations, predominantly, adsorption (Jayarathne et al. 2019b). The variability in the particle size of road dust is an important physical property that determines the adsorption ability of metals. Metals preferentially adsorb to fine particles as they are enriched with surface functional groups and higher SSA compared to that of coarser particles (Ball et al. 1998; Bian and Zhu 2009; Sansalone and Ying 2008; Zhao et al. 2017). Furthermore, the number of cation exchangeable sites that a particle surface holds at a specific pH value (i.e. CEC) also determines the adsorption ability of metals in the form of exchangeable ions. Different minerals associated with road dust play a significant role in metal adsorption. Quartz, feldspars, clay minerals of chlorite and illite, carbonates of dolomite, calcite and siderite, metal oxides of magnetite, and gypsum are the dominant minerals associated with road ´ dust (Djuki´c et al. 2016; Gunawardana et al. 2012; Jayarathne et al. 2018b; Swietlik et al. 2015). Deprotonation of surface functional groups attached to mineral surfaces creates favourable charged sites for metal adsorption. On the other hand, metals can incorporate into the lattice structure of minerals through isomorphous substitution. Once metal ions are adsorbed to particles, their relative mobility depends on the mobility of associated particles. Compared to the coarser particles, fine particles have limited settling velocities, enabling transport over relatively longer distances in the atmosphere during dry weather periods and in stormwater runoff during wet weather periods.

1.4.2 Environmental Factors Residence time of metals is one of the important environmental factors that determines the fate and chemical behaviour of metals. This means that the environmental significance of metals can change depending on the time period in which the metals undergo transformation processes. For example, ion-exchange and chemisorption are rapid transformation processes that can continue up to several days, whilst the incorporation of metals into mineral structures occur over a relatively long time

1.4 Factors Influencing Metal Transformation

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period (Roberts et al. 2005). As such, mobility and bioavailability of metals decrease with increasing residence time due to the transformation of metals from less stable geochemical forms to relatively stable binding forms (Jalali and Khanlari 2008; Jayarathne et al. 2018c; Lu et al. 2005). Apart from the residence time, moisture content positively influences metal transformations. When the environment is saturated with moisture/water, metal ions can be hydrated by interacting with polarized water molecules. Metals with smaller hydrated radius generally consist of higher charge densities, and in turn, have a high tendency to undergo ion-exchange reactions (Bleam 2011; Bradl 2004; Filep 1999). Other than moisture content, temperature is also reported to affect metal adsorption (Akpomie et al. 2015; Sarı et al. 2007; Sharma 2008). Solar radiation is one of the main sources that controls the temperature of road surfaces. Negative charge sites developed on particle surfaces generally increase with increasing temperature, allowing metal ions to interact with opposite charges. Furthermore, at high temperature, pore sizes of particles change due to intra-particle diffusion, increasing the specific surface area and the adsorption ability of particles (Meena et al. 2008).

1.5 Summary A detailed understanding of the environmental fate of stormwater pollutants and associated stormwater quality impacts is required for the implementation of appropriate stormwater pollution mitigation strategies to ensure the safe reuse of stormwater in urban areas. This chapter has discussed the transformation characteristics of metals, one of the primary toxic pollutants associated with road dust, and the factors influencing metal transformations in order to highlight their potential stormwater quality impacts. The primary mechanisms of metal transformation on urban roads are ionexchange and chemisorption. Metal precipitation would not be a prominent process as the cationic/anionic concentration in road dust is relatively low. Transformation processes are strongly influenced by intrinsic properties of road dust such as particle size, specific surface area and cation exchange capacity, whilst environmental factors indirectly induce transformations. Depending on the residence time and the different transformation processes that metal undergo, the mobility, bioavailability and toxicity characteristics of metals can change. These changes in turn, will influence the degradation of stormwater quality when these pollutants are washed-off by stormwater runoff.

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Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2018a) Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability. Sci Total Environ 635:1609–1619. https://doi.org/10.1016/j.scitotenv.2018. 04.098 Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2018b) Intrinsic and extrinsic factors which influence metal adsorption to road dust. Sci Total Environ 618:236–242. https://doi.org/ 10.1016/j.scitotenv.2017.11.047 Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2018c) Role of residence time on the transformation of Zn, Cu, Pb and Cd attached to road dust in different land uses. Ecotoxicol Environ Saf 153:195–203. https://doi.org/10.1016/j.ecoenv.2018.02.007 Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2019a) Transformation processes of metals associated with urban road dust: a critical review. Crit Rev Environ Sci Technol 49:1675–1699 Jayarathne A, Wijesiri B, Egodawatta P, Ayoko GA, Goonetilleke A (2019b) Role of adsorption behavior on metal build-up in urban road dust. J Environ Sci 83:85–95. https://doi.org/10.1016/ j.jes.2019.03.023 Li X, Poon CS, Liu PS (2001) Heavy metal contamination of urban soils and street dusts in Hong Kong. Appl Geochem 16(11):1361–1368. https://doi.org/10.1016/S0883-2927(01)00045-2 Liu A, Gunawardana C, Gunawardena J, Egodawatta P, Ayoko GA, Goonetilleke A (2016) Taxonomy of factors which influence heavy metal build-up on urban road surfaces. J Hazard Mater 310:20–29. https://doi.org/10.1016/j.jhazmat.2016.02.026 Liu A, Liu L, Li D, Guan Y (2015) Characterizing heavy metal build-up on urban road surfaces: implication for stormwater reuse. Sci Total Environ 515–516:20–29. https://doi.org/10.1016/j. scitotenv.2015.02.026 Lu A, Zhang S, Shan XQ (2005) Time effect on the fractionation of heavy metals in soils. Geoderma 125(3–4):225–234. https://doi.org/10.1016/j.geoderma.2004.08.002 Ma Y, McGree J, Liu A, Deilami K, Egodawatta P, Goonetilleke A (2017) Catchment scale assessment of risk posed by traffic generated heavy metals and polycyclic aromatic hydrocarbons. Ecotoxicol Environ Saf 144:593–600. https://doi.org/10.1016/j.ecoenv.2017.06.073 Martin S, Griswold W (2009) Human health effects of heavy metals, vol 15. Center for Hazardous Substance Research (CHSR), Kansas State University, Manhattan, KS, pp 1–6 Meena AK, Kadirvelu K, Mishra GK, Rajagopal C, Nagar PN (2008) Adsorptive removal of heavy metals from aqueous solution by treated sawdust (Acacia arabica). J Hazard Mater 150(3):604– 611. https://doi.org/10.1016/j.jhazmat.2007.05.030 Mummullage S, Egodawatta P, Goonetilleke A, Ayoko GA (2014) Variability of metal composition and concentrations in road dust in the urban environment. Int J Environ Earth Sci Eng 8(2):54–59 Nnadi EO, Newman AP, Coupe SJ, Mbanaso FU (2015) Stormwater harvesting for irrigation purposes: an investigation of chemical quality of water recycled in pervious pavement system. J Environ Manag 147:246–256. https://doi.org/10.1016/j.jenvman.2014.08.020 Ozcan N, Altundag H (2013) Speciation of heavy metals in street dust samples from Sakarya I. Organized industrial district using the BCR sequential extraction procedure by ICP-OES. Bull Chem Soc Ethiopia 27(2):205–212 Pitt R, Clark S, Field R (1999) Groundwater contamination potential from stormwater infiltration practices. Urban Water 1(3):217–236 Ritter KS, Sibley P, Hall K, Keen P, Mattu G, Linton B, Len (2002) Sources, pathways, and relative risks of contaminants in surface water and groundwater: a perspective prepared for the Walkerton inquiry. J Toxicol Environ Health Part A 65(1):1–142 Roberts D, Nachtegaal M, Sparks DL (2005) Speciation of metals in soils. Chemical processes in soils (chemical process). SSSA, Madison, WI, pp 619–654 Sansalone J, Ying G (2008) Partitioning and granulometric distribution of metal leachate from urban traffic dry deposition particulate matter subject to acidic rainfall and runoff retention. Water Res 42(15):4146–4162. https://doi.org/10.1016/j.watres.2008.06.013 Sarı A, Tuzen M, Soylak M (2007) Adsorption of Pb(II) and Cr(III) from aqueous solution on Celtek clay. J Hazard Mater 144(1):41–46. https://doi.org/10.1016/j.jhazmat.2006.09.080

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Sharma YC (2008) Thermodynamics of removal of cadmium by adsorption on an indigenous clay. Chem Eng J 145(1):64–68. https://doi.org/10.1016/j.cej.2008.03.006 Shi G, Chen Z, Bi C, Wang L, Teng J, Li Y, Xu S (2011) A comparative study of health risk of potentially toxic metals in urban and suburban road dust in the most populated city of China. Atmos Environ 45(3):764–771. https://doi.org/10.1016/j.atmosenv.2010.08.039 Sparks DL (2003) Environmental soil chemistry. Elsevier Science, Amsterdam Sposito G (2008) The chemistry of soils. Oxford University Press, New York, NY ´ Swietlik R, Trojanowska M, Strzelecka M, Bocho-Janiszewska A (2015) Fractionation and mobility of Cu, Fe, Mn, Pb and Zn in the road dust retained on noise barriers along expressway—a potential tool for determining the effects of driving conditions on speciation of emitted particulate metals. Environ Pollut 196:404–413. https://doi.org/10.1016/j.envpol.2014.10.018 Violante A, Cozzolino V, Perelomov L, Caporale A, Pigna M (2010) Mobility and bioavailability of heavy metals and metalloids in soil environments. J Soil Sci Plant Nutr 10(3):268–292 Weber WJ, McGinley PM, Katz LE (1991) Sorption phenomena in subsurface systems: concepts, models and effects on contaminant fate and transport. Water Res 25(5):499–528 Wijesiri B, Egodawatta P, McGree J, Goonetilleke A (2015) Influence of pollutant build-up on variability in wash-off from urban road surfaces. Sci Total Environ 527–528:344–350. https:// doi.org/10.1016/j.scitotenv.2015.04.093 Worch E (2012) Adsorption technology in water treatment: fundamentals, processes, and modeling. Walter de Gruyter, Berlin Zhang M, Wang H (2009) Concentrations and chemical forms of potentially toxic metals in roaddeposited sediments from different zones of Hangzhou, China. J Environ Sci 21(5):625–631. https://doi.org/10.1016/S1001-0742(08)62317-7 Zhao H, Wang X, Li X (2017) Quantifying grain-size variability of metal pollutants in road-deposited sediments using the coefficient of variation. Int J Environ Res Public Health 14(8):850 Zhuang J, Yu G-R (2002) Effects of surface coatings on electrochemical properties and contaminant sorption of clay minerals. Chemosphere 49(6):619–628

Chapter 2

Research Design for Investigating Metal Transformations on Urban Roads

Abstract Investigations into the transformation characteristics of metals deposited on urban roads required a scientifically robust research design. Sample collection and laboratory analyses were two important steps in the overall research design. This chapter provides a detailed discussion on the methods adopted for road dust sample collection, sample handling and preservation, and laboratory experiments for the analysis of selected metals and key physicochemical parameters of road dust. Keywords Road dust · Dry and wet vacuuming · Sequential extraction · Antecedent dry days · Laboratory testing

2.1 Background Metals entrained in stormwater runoff can potentially influence stormwater quality due to their mobility, bioavailability and toxicity characteristics. The changes to the characteristics of metals primarily result from the transformation processes that metals undergo during dry weather periods. Such processes are further influenced by the physicochemical properties of road dust particles and environmental factors. This underlines the complexity of processes inherent to stormwater pollution. As such, prior to implementing stormwater pollution mitigation strategies, the potential transformation processes of metals and resulting stormwater quality impacts should be clearly understood. Accordingly, a robust research methodology was formulated to generate data sets on the concentration and characteristics of metals, and other influential parameters. This chapter outlines the important steps adopted in the research design. The outcomes of this chapter formed the key underpinning for the subsequent data analyses and interpretations discussed in the following chapters.

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5_2

11

12

2 Research Design for Investigating Metal Transformations …

2.2 Study Area and Study Sites Sampling sites were selected from Gold Coast, South East Queensland (SEQ), which is one of the fastest developing urban regions in Australia. This region consists of an integrated network of waterways, including five main rivers, creeks, lakes and canals. The city authorities are striving to maintain healthy waterways despite high pollutant generation in the area as a result of the rapid population growth together with associated anthropogenic activities. Six sampling sites were selected spread over two suburbs, Benowa and Nerang in the Gold Coast region. Among the selected sites, four sites were located within Benowa, while two sites were in Nerang. The selected sites consisted of different traffic and land use characteristics comprising of industrial, commercial and residential, which were expected to influence the variation in pollutant composition and build-up loads on the road surfaces. A detailed description of the study sites is given in Table 2.1.

2.3 Sample Collection 2.3.1 Study Plot As reported by Egodawatta and Goonetilleke (2006), the accumulation rate of pollutants on urban road surfaces is nearly 1–2 g/m2 /day and the total build-up asymptotes to a near-constant value with increasing antecedent dry days. Accordingly, a relatively large road surface area was needed to collect the required amount of samples for detailed laboratory analyses. Accordingly, study plots of 1.0 m width by the distance from the kerb to the road centreline were selected at each site for sample collection. Past research has found that other than traffic and land use characteristics, the load and composition of pollutants build-up at a specific site is influenced by the antecedent dry weather period. Consequently, samples were collected for a range of antecedent dry days, namely, 1, 4, 7 and 11 days to account for this variation.

2.3.2 Road Dust Sample Collection Road dust samples were collected using a dry and wet vacuum method which has been proven to have a high collection efficiency (Amato et al. 2010; Deletic and Orr 2005; Zhang et al. 2015). The dry and wet vacuum system consisted of a portable vacuum cleaner and a pressure controllable water sprayer. A detailed description of the sample collection method can be found in Gunawardena et al. (2017). In summary, dry vacuuming was initially conducted, followed by wet vacuuming after moistening the road surface (Fig. 2.1). The sample collection efficiency of the system was verified

Strathaird Road

Benowa

Mediterranean Drive

Site name

Suburb

Commercial

Land use type

Table 2.1 Characteristics of the study sites

Com-2

Com-1

Site identification

750

3500

Average daily traffic volume (DTV)

– Major access road to a school – Frequent vehicle parking

– Two lane access road – Commercial services such as vehicle service stations, warehouses, sports clubs and a food store

Characteristics of the study site

Reference image of the study site

(continued)

2.3 Sample Collection 13

Village High Road

Benowa

De Haviland Avenue

Site name

Suburb

Table 2.1 (continued)

Residential

Land use type

Res-2

Res-1

Site identification

500

750

Average daily traffic volume (DTV) – Medium and large scale detached family houses with well-maintained roadside lawns and gardens

Characteristics of the study site

Reference image of the study site

(continued)

14 2 Research Design for Investigating Metal Transformations …

Stevens Street

Nerang

Hilldon Court

Site name

Suburb

Table 2.1 (continued)

Industrial

Land use type

Ind-2

Ind-1

Site identification

3500

3500

Average daily traffic volume (DTV)

– Busy access road – Light industries such as a vehicle service station, plumbing and metal works

– Broad and steep-sloped access road – Different industries, such as aluminium and steel fabrication workshops, a welding workshop, furniture and cement mixing industries

Characteristics of the study site

Reference image of the study site

2.3 Sample Collection 15

16

2 Research Design for Investigating Metal Transformations …

Fig. 2.1 Road dust sample collection; a dry vacuuming, b water spraying prior to wet vacuuming

before commencing field work by selecting a bitumen road surface, which was similar in surface characteristics to the actual sampling sites. The collection efficiency was about 92%, which was considered satisfactory for field sampling. The field samples collected were then transferred into polyethylene containers and properly labelled with all the necessary information.

2.3.3 Sample Handling, Storage and Subsampling Field blanks were collected as part of the standard quality control procedures during sampling as recommended in Australia/New Zealand Standards for water quality and sampling (AS/NZS-5667.1:1998, 1998). Samples were transported to the laboratory on the same day and stored at 4 °C until further testing. Subsampling was carried out prior to the laboratory analyses. In this study, laboratory data were generated based on four different particle size ranges of road dust, namely, 0.45–75, 75–150, 150–300 and 300–425 µm to understand the sizedependent transformation characteristics of metals. This selection was based on the significance of pollutant distribution among different particle sizes of road dust (Gunawardana et al. 2015; Herngren et al. 2010; Zhang et al. 2015). Accordingly, the bulk sample was wet-filtered through a sieve set of 75, 150, 300 and 425 µm, the larger debris retained on the 425 µm sieve were removed and then the wet samples retained on the remaining sieves were air dried. The fine particles which passed through the 75 µm sieve was separated using 0.45 µm filter papers under suction filtering and followed by air drying. The Cu > Zn > Cd, which is inversely opposite to the order of their mobility. Based on the transformation rate and mobility order, metals such as Cd and Zn can adversely influence stormwater quality due to their readily available nature. Keywords Geochemical fractions · Mobility · Transformation rate · Antecedent dry days · Stormwater pollution processes · Stormwater quality

3.1 Background Stormwater pollution from toxic pollutants such as metals is a critical concern in relation to ecological and human health due to their mobility and bioavailability characteristics (Li et al. 2017; Ma et al. 2016; Zhang et al. 2017). The characteristic changes to mobility and bioavailability of metals are largely influenced by the transformation processes of metals whilst accumulated on roads. Transformed pollutants can eventually influence stormwater quality during pollutant wash-off process by stormwater runoff (Wijesiri et al. 2015). However, it is not well understood how the road deposited metals can transform during dry weather periods, changing their mobility and bioavailability characteristics. This could constrain scientifically robust interpretation of the potential stormwater quality impacts of metals. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5_3

21

22

3 Metal Transformation and Stormwater Quality

The chapter initially discusses the geochemical behaviour of metals deposited on roads and the relationships to mobility and bioavailability. Then, the transformation processes of metals are investigated as a function of varying dry weather periods in order to understand the potential stormwater quality impacts of transformed metals. The investigations described in this Chapter were based on the key laboratory outcomes generated by analysing metals associated with different particle size ranges of road dust as presented in Chap. 2.

3.2 Relationships Between Mobility and Bioavailability of Metals and Geochemical Fractions Identifying the bonding mechanisms of metals with road dust particles provides useful information in relation to their chemical behaviour and potential environmental impacts. Accordingly, the sequentially extracted metal concentrations were analysed. For this analysis, road dust samples collected from the three study sites; Strathaird Road, Village High Road and Steven Street, which consisted of commercial, residential and industrial land use, respectively, were selected. The percentage geochemical fractionation characteristics of metals for each land use is shown in Fig. 3.1. It is evident that metals show different affinities for the exchangeable (ion-exchangeable form), reducible (Fe–Mn oxides bound), oxidisable

Industrial

Ni

7.7

8.8

6.9

76.6

Cr 0.4 2.8 5.7

91.1

Cd 10.6

40.4

Cu

23.0

Residential

5.8

6.8

14.7 18.6 44.3

16.6

9.5

19.5

29.5

11.8

34.6 36.5

14.0

17.4 17.9

16.6 84.6

Cd

69.6 22.7

Cu

22.0

13.3 38.0

30%

Exchangeable

19.4 13.0

40%

50%

Reducible

60%

6.8 15.6

42.4

61.8 20%

10.3

23.7

16.2

Zn 10%

22.3

62.1

Cr 1.0 3.2 11.2 Pb

19.5

13.2

45.8

0%

15.7

72.7

42.5 7.9

Ni

11.6

89.2

Cd Cu

23.3 13.6

Cr 0.62.6 7.6 Pb

18.6 31.8

31.6

59.1

Zn

Commercial

16.4

17.2

22.0

Zn Ni

18.1

46.9

Pb

70%

Oxidisable

15.8 80%

Residual

Fig. 3.1 Geochemical fractionation characteristics of metals for different land uses

9.5 90%

100%

3.2 Relationships Between Mobility and Bioavailability of Metals …

23

(organic matter bound) and residual (bound to the mineral lattices) geochemical fractions. However, the distribution of metals in each of the geochemical fractions was comparatively similar for all land uses, in which the mean percentages of metals followed the order: exchangeable—Cd > Zn > Cu > Pb > Ni > Cr, reducible—Pb > Cu > Cd > Zn > Ni > Cr, oxidisable—Cu > Pb > Ni > Zn > Cr > Cd and residual—Cr > Ni > Cu > Pb > Zn > Cd. The exchangeable fraction of metals is commonly referred to as the ‘effective bioavailable or mobile fraction’, and the reducible and oxidisable fractions are considered as the ‘potentially bioavailable or mobilisable fraction’. The residual fraction is viewed as ‘non-bioavailable or immobile fraction’ (Alvarenga et al. 2013; Nannoni and Protano 2016). Accordingly, the abundance of Cd, Zn, Cu and Pb in the exchangeable, reducible and oxidisable fractions of road dust implies their potential mobility and bioavailability characteristics. Furthermore, the low desorption ability of Ni and Cr is evident from their characteristic enrichment in the stable residual fraction. Therefore, in order to minimise the stormwater quality impacts of metals, stormwater pollution mitigation strategies should be implemented in a way that the readily available metals are specifically targeted for removal.

3.3 Influence of Particle Size of Road Dust on Geochemical Behaviour of Metals The size dependentgeochemical fractionation patterns of metals are shown in Figs. 3.2 and 3.3. As depicted in Fig. 3.2, irrespective of land use, the exchangeable fraction of Zn is relatively high in the particle size ranges of 0.45–75 and 75–150 µm compared to that of the >150 µm size ranges. The distribution of Cu and Pb in the reducible and oxidisable fractions also follow a similar trend (Fig. 3.2). Furthermore, a higher enrichment of Cd in the exchangeable fraction and, Cr and Ni in the residual fraction of 0.45–75 and 75–150 µm size ranges is also evident from Fig. 3.3. However, a large difference in metal concentrations cannot be identified between 0.45–75 and 75–150 µm size ranges, and 150–300 and 300–425 µm size ranges. Therefore, the combined size ranges of 0.45–75 and 75–150 can be regarded as the fine particle size range that contains a relatively higher fraction of metals. The fine particles possess a significant specific surface area to interact with metals, resulting in high concentrations of metals in each geochemical fraction (Gunawardana et al. 2014). This highlights the need for implementing pollution mitigation measures specifically targeting the removal of fine road dust particles in order to minimise the potential stormwater quality impacts of metals.

24

3 Metal Transformation and Stormwater Quality

Fig. 3.2 Geochemical fractionation of Zn, Cu and Pb in different particle size ranges of road dust. Notes EXC—exchangeable, RED—reducible, OXI—oxidisable and RES—residual

Fig. 3.3 Geochemical fractionation of Cd, Cr and Ni in different particle size ranges of road dust. Notes EXC—exchangeable, RED—reducible, OXI—oxidisable and RES—residual

3.4 Time Dependent Metal Transformation

25

3.4 Time Dependent Metal Transformation The time that metals reside in the environment is an important factor that determines their environmental fate. The residence time of metals deposited on roads can be related to the antecedent dry days (ADDs). As evident from Sect. 3.3, metals undergo different adsorption processes when interacting with road dust particles, resulting in different geochemical affinities of metals. However, as the residence times increase, the chemical behavior of metals can change whilst undergoing continuous desorption and subsequent re-adsorption processes. This can lead to changes in the mobility and bioavailability characteristics of metals. The geochemical fractionation characteristics of Zn, Cu, Pb and Cd were investigated as a function of ADD based on data obtained from three study sites, namely, Mediterranean Drive (commercial land use—Com), De Haviland Avenue (residential land use—Res) and Hilldon Court (industrial land use—Ind). Considering the significance of metal adsorption ability of fine particles, particle size ranges of 0.45–75 and 75–150 µm were selected for this analysis. Prior to the analysis, metal concentrations for different dry days were normalised with respect to their total pollutant build-up loads in order to counteract any bias as a result of different build-up loads.

3.4.1 Transformation of Zn The geochemical fractionation characteristics of Zn in particle size ranges of 0.45– 75 µm (I) and 75–150 µm (II) as a function of ADD is shown in Fig. 3.4. Irrespective of particle size range, the ion-exchangeable Zn fraction decreases with ADD in commercial and residential study sites, whereas the corresponding reducible and the oxidisable Zn fractions increase with time. This behaviour is prominent during the initial dry period. There is no significant variation in the residual fraction of Zn with increasing dry days (0.6–1.0%). These observations imply that the exchangeable form of Zn transforms into other stable geochemical forms over time. As time increases, the unavailability of exchangeable sites on road dust particles can limit the interaction of Zn ions to the exchangeable fraction. However, at the industrial study site, Zn shows a significant affinity towards the exchangeable fraction over time, whilst the distribution of Zn in the oxidisable fraction is low. As evident from Table 3.1, among different land uses studied, the industrial study site of Hilldon Court generally had the lowest organic matter content (i.e. TOC). Due to the low organic matter content at the site, the interaction between Zn ions and favourable charge sites on organic matter could be limited.

26

3 Metal Transformation and Stormwater Quality

Fig. 3.4 Geochemical fractionation characteristics of Zn over dry days. Notes Com—commercial, Res—residential, Ind—industrial. The roman letters I and II symbolise particle size ranges of 0.45–75 µm and 75–150 µm, respectively (Jayarathne et al. 2018) Table 3.1 Physicochemical properties of road dust collected at different study sites Site name

Mediterranean Drive

De Haviland Avenue

Hilldon Court

land use type

Commercial

Residential

Industrial

Size range (µm)

TOC (g/L)

SSA (m2 /g)

TOC (g/L)

SSA (m2 /g)

TOC (g/L)

SSA (m2 /g)

1

0.633

18.8

0.771

76.8

0.524

23.7

4

0.543

19.6

1.194

29.4

0.492

16.8

0.45–75

75–150

ADD

7

0.612

40.5

0.791

43.7

0.420

24.5

11

0.681

36.4

1.455

53.0

0.523

18.2

1

0.134

19.6

0.368

37.7

0.182

11.2

4

0.246

17.5

0.451

29.2

0.142

10.5

7

0.299

23.8

0.426

51.4

0.188

16.8

11

0.216

14.0

0.520

40.2

0.250

11.9

ADD Antecedent dry day; TOC Total organic carbon; SSA Specific surface area

3.4 Time Dependent Metal Transformation

27

3.4.2 Transformation of Cu It is evident from Fig. 3.5, that irrespective of study sites and particle size ranges, the reducible and oxidisable fractions of Cu increase with increasing dry days, whilst the exchangeable fraction of Cu follows a decreasing trend. These observations suggest that Cu tends to transform into relatively firm chemical form/s when the residence time increases. It was noted that irrespective of particle size ranges of 0.45–75 µm (I) and 75–150 µm (II), the geochemical distribution of Cu in the oxidisable fraction is comparatively higher at the residential site (i.e. Res-I and Res-II). Among different land uses, road dust collected at the residential road site (i.e. De Haviland Avenue) exhibited high organic matter content (see Table 3.1). This implies that organic matter rich road dust can increase the distribution of Cu in the organically bound form. It has been reported that compared to any other divalent cation, Cu (2+) is firmly attached to organic matter leading to low mobility and bioavailability characteristics (Sparks 2003).

Fig. 3.5 Geochemical fractionation characteristics of Cu over dry days. Notes Com—commercial, Res—residential, Ind—industrial. The roman letters I and II symbolise particle size ranges of 0.45–75 µm and 75–150 µm, respectively (Jayarathne et al. 2018)

28

3 Metal Transformation and Stormwater Quality

3.4.3 Transformation of Pb The time-dependent transformation characteristics of Pb are shown in Fig. 3.6. In general, the geochemical distribution of Pb shows characteristics similar to Cu. Irrespective of particle size ranges of road dust, the oxidisable fraction of Pb at the commercial and residential sites increases with respect to the decreasing trends in the exchangeable and reducible fractions over time. At the industrial study site, even though the organically bound Pb fraction is generally low, there is a significant increase in the reducible fraction of Pb with respect to the decreasing trend in the exchangeable form, with ADD. The residual fraction of Pb generally remains constant over time. These observations imply that Pb in its exchangeable form gradually transforms into either Fe–Mn oxide or organic matter bound forms when residence time on road surfaces increases.

Fig. 3.6 Geochemical fractionation characteristics of Pb over dry days. Notes Com—commercial, Res—residential, Ind—industrial. The roman letters I and II symbolise particle size ranges of 0.45–75 µm and 75–150 µm, respectively (Jayarathne et al. 2018)

3.4 Time Dependent Metal Transformation

29

3.4.4 Transformation of Cd The time dependent geochemical fractionation characteristics of Cd are different from that of Zn, Cu and Pb. It was noted that during the initial dry period, the exchangeable fraction of Cd at the industrial and commercial study sites increases with ADD, showing a decreasing trend in the reducible and oxidisable fractions (Fig. 3.7). This implies that the geochemical affinity of Cd for ion-exchangeable sites present in road dust particles is high compared to the stable charge sites. However, it was noted that at the residential site with high organic matter content (see Table 3.1), the oxidisable fraction of Cd shows an increasing trend with time compared to the decreasing trend in the exchangeable and reducible fractions. This further confirms that organic matter rich road dust has a significant influence on the transformation of metals from mobile geochemical forms to less mobile forms.

Fig. 3.7 Geochemical fractionation characteristics of Cd over dry days. Notes Com—commercial, Res—residential, Ind—industrial. The roman letters I and II symbolise the particle size ranges of 0.45–75 µm and 75–150 µm, respectively (Jayarathne et al. 2018)

30

3 Metal Transformation and Stormwater Quality

3.5 Influence of Metal Transformation and Mobility on Stormwater Quality The analysis outcomes reported in Sect. 3.4 infer that metals in their unstable geochemical forms are likely to transform into relatively stable geochemical form/s with increasing residence time. The time dependent transformation rate for the metals in the exchangeable fraction was calculated using Eq. 3.1 (Lu et al. 2005). As evident from Fig. 3.8, except for Cd at the industrial and commercial study sites, the data related to other metals fit into the linear relationship with satisfactory regression coefficients (R2 ). log Cm = A + b t

(3.1)

where Cm t b A

Concentration of metals in the exchangeable fraction (mg/kg) Residence time (antecedent dry days) Transformation rate of a particular metal (mg/kg day) Constant accounts for the relationship between metals and particles.

Fig. 3.8 Plots representing the transformation rate of metals. Notes Com—commercial, Res— residential, Ind—industrial. The roman letters I and II symbolise particle size ranges of 0.45–75 µm and 75–150 µm, respectively (Jayarathne et al. 2018)

3.5 Influence of Metal Transformation and Mobility on Stormwater …

31

The gradient of the plots indicates that the transformation rate of metals (b) vary from 0.004 to −0.053 mg/kg day for Zn, 0.008 to −0.066 mg/kg day for Cu, −0.021 to −0.078 mg/kg day for Pb and −0.002 to −0.054 mg/kg day for Cd. Considering the mean values of b, the order of the transformation rate of metals is Pb (−0.044) > Cu (−0.030) > Zn (−0.029) > Cd (−0.024). This implies that compared to Pb and Cu in road dust, the time dependent transformation rate of Cd and Zn into stable geochemical forms is relatively low. Further, it is interesting to note that the transformation rate of metals shows an inverse relationship with the mobility sequence of metals in the exchangeable fraction (see Sect. 3.2). The order of mobility and the transformation rate of metals further highlight the potential stormwater quality impacts associated with Zn and Cd with increased duration of residence time on road surfaces. Therefore, pollution mitigation strategies should consider the time dependent transformation characteristics of pollutants on road surfaces.

3.6 Summary This chapter provides insights into the geochemical behaviour of metals bound to different particle size ranges of road dust and the time dependent metal transformation characteristics that can influence the mobility of metals, and in turn, the stormwater quality. The affinities of metals for different geochemical fractions of road dust such as exchangeable, reducible, oxidisable and residual vary among different metal species, resulting in variable mobility characteristics. Zn and Cd show higher affinity towards the less stable exchangeable fraction, thereby being more mobile and bioavailable. The association of Cr and Ni with the residual fraction underlines their low mobility characteristics. It was further noted that antecedent dry days and organic matter in road dust play a significant role in transforming metals in the less stable geochemical forms to more stable forms. The metal transformation rate follows the order: Pb > Cu > Zn > Cd. Compared to the other metals, Cd tends to associate with the ion-exchangeable form and barely transform into the stable geochemical forms with time, highlighting potential stormwater quality impacts associated with Cd.

References Alvarenga P, Laneiro C, Palma P, de Varennes A, Cunha-Queda C (2013) A study on As, Cu, Pb and Zn (bio)availability in an abandoned mine area (São Domingos, Portugal) using chemical and ecotoxicological tools. Environ Sci Pollut Res 20(9):6539–6550 Gunawardana C, Egodawatta P, Goonetilleke A (2014) Role of particle size and composition in metal adsorption by solids deposited on urban road surfaces. Environ Pollut 184:44–53. https:// doi.org/10.1016/j.envpol.2013.08.010 Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2018) Role of residence time on the transformation of Zn, Cu, Pb and Cd attached to road dust in different land uses. Ecotoxicol Environ Saf 153:195–203. https://doi.org/10.1016/j.ecoenv.2018.02.007

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3 Metal Transformation and Stormwater Quality

Li H-H, Chen L-J, Yu L, Guo Z-B, Shan C-Q, Lin J-Q, Cheng Z (2017) Pollution characteristics and risk assessment of human exposure to oral bioaccessibility of heavy metals via urban street dusts from different functional areas in Chengdu, China. Sci Total Environ 586:1076–1084. https://doi. org/10.1016/j.scitotenv.2017.02.092 Lu A, Zhang S, Shan X-Q (2005) Time effect on the fractionation of heavy metals in soils. Geoderma 125(3–4):225–234. https://doi.org/10.1016/j.geoderma.2004.08.002 Ma Y, Egodawatta P, McGree J, Liu A, Goonetilleke A (2016) Human health risk assessment of heavy metals in urban stormwater. Sci Total Environ 557–558:764–772. https://doi.org/10.1016/ j.scitotenv.2016.03.067 Nannoni F, Protano G (2016) Chemical and biological methods to evaluate the availability of heavy metals in soils of the Siena urban area (Italy). Sci Total Environ 568:1–10. https://doi.org/10. 1016/j.scitotenv.2016.05.208 Sparks DL (2003) Environmental soil chemistry. Elsevier Science, San Diego, CA Wijesiri B, Egodawatta P, McGree J, Goonetilleke A (2015) Influence of pollutant build-up on variability in wash-off from urban road surfaces. Sci Total Environ 527–528:344–350. https:// doi.org/10.1016/j.scitotenv.2015.04.093 Zhang J, Hua P, Krebs P (2017) Influences of land use and antecedent dry-weather period on pollution level and ecological risk of heavy metals in road-deposited sediment. Environ Pollut 228:158–168

Chapter 4

Assessment of Human Health Risks from Metals in Urban Stormwater Based on Geochemical Fractionation and Bioavailability

Abstract Risks posed by metals in stormwater is directly influenced by their geochemical fractionation and, in turn, the bioavailability. Therefore, accurate quantification of the risks from metals should be undertaken by considering these two key aspects. This chapter presents a novel approach to quantify the human health risks of metals, among the common stormwater pollutants found in urban areas, considering their geochemical fractionation and bioavailability characteristics. Stormwater quality and quantity modelling approaches were used to convert metal build-up loads to corresponding metal concentrations in stormwater. The results of the modified risk assessment discussed in this chapter highlights the drawbacks in using classical health risk indices and the importance of upgrading the risk assessment methods to avoid the over-estimation of risk posed by metals. Based on the modified hazard index, there is a low or no health risk from metals in stormwater runoff originating from the urban land uses investigated in this study. Keywords Metals · Geochemical behaviour · Bioavailability · Stormwater · Risk assessment · Hazard index · Non-cancer risk

4.1 Background Besides understanding the potential stormwater quality impacts of metals, the quantification of human health risks associated with stormwater pollutants is an essential step for implementing appropriate stormwater mitigation measures. Risk quantification will further inform the critical decisions in relation to stormwater management, ensuring the safe reuse of stormwater for high-quality water requirements in urban areas such as for recreational activities. Metals are one of the essential elements needed to maintain the various biochemical and physiological functions in living organisms. However, they can become toxic when certain threshold concentrations are exceeded, causing acute and chronic diseases such as skin irritations and cancers when people come into contact with polluted water (Jaishankar et al. 2014; Ma et al. 2016). The increasing significance of risks associated with metals is primarily due to the bioavailability and toxicity characteristics, which rely on the geochemical behaviour of metals attached to particles © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5_4

33

34

4 Assessment of Human Health Risks from Metals in Urban …

(Huang et al. 2016; Zhang et al. 2014). During storm events, particulate bound metals are entrained in the stormwater runoff, changing the characteristics of stormwater, and in turn the risk associated with stormwater. As such, the assessment of risks posed by metals should be undertaken in a way that the geochemical behaviour of metals is understood in-depth. Nevertheless, this is barely considered in most risk assessment studies, which can mislead interpretations (Acosta et al. 2009; Li et al. 2017; Man et al. 2010; Zhao and Li 2013). The objective of this chapter is to present a methodology to enhance the classical risk assessment, considering the geochemical behaviour and bioavailability characteristics of metals. Application of the improved risk assessment methodology presented is also evaluated in estimating human health risks of six metals in stormwater, namely, Zn, Cd, Cu, Pb, Cr and Ni. These metals are ubiquitous in the urban environment. The concentration of metals in stormwater runoff is primarily influenced by the concentration of metals built-up on urban surfaces such as roads, during dry weather periods. Therefore, prior to the assessment of risk posed by metals present in stormwater, the estimation of the concentrations of metal species present in stormwater is an essential step. The approach adopted for assessing metal concentration in stormwater runoff is also discussed in this Chapter. The information presented in this Chapter provides new insights into risk quantification in the context of stormwater pollution mitigation and stormwater reuse.

4.2 Risk Indices Risk indices are one of the quantitative approaches used for estimating and modelling the likelihood or probability that human and ecosystem health can be impacted due to the presence of pollutants or exposure to pollutants. As such, risk indexing can be considered as a composite of the likelihood and impacts that pollutants can cause.

4.2.1 Human Health Risk Indices In relation to human health, there are three different pathways of exposure to metal contaminated stormwater: ingestion of stormwater as drinking water; incidental ingestion of stormwater while swimming; and dermal contact with stormwater (Ma et al. 2016; USEPA 1989). The daily metal intake (D) by an individual through these routes can be evaluated as given in Eqs. 4.1–4.3 (USEPA 1989, 2001). The values for each parameter used in exposure pathways are selected according to the criteria specified in USEPA (1989). DW ater ingestion = C ×

I RW × E F × E D BW × 365 days/year × AT

(4.1)

4.2 Risk Indices

35

D Swimming ingestion = C × D Der mal contact = C ×

C R × E T D × E FD × E D BW × 365 days/year × AT

S A × PC × E TD × E FD × E D × C F . BW × 365 days/year × AT

(4.2) (4.3)

where DWater ingestion , DDermal contact C

DSwimming ingestion

I RW EF CR E TD E FD SA PC CF ED BW AT

and Daily metal intake through different exposure pathways (mg/kg day) Concentration of metals in stormwater (mg/L) Water ingestion rate (2 L/day) Exposure frequency (365 day/year) Contact rate (0.05 L/h) Exposure time while swimming (2.6 h/event) Exposure frequency for swimming (7 events/year) Skin surface area available for contact (18,000 cm2 ) Chemical-specific dermal permeability constant (0.7 cm/h) Volumetric conversion for water (1 L/1000 cm3 ) Exposure duration (30 years) Body weight of an adult (70 kg) Average time during exposure (70 years).

The potential non-cancer health risk of a particular metal ion can be evaluated through comparison between exposure levels of the metal via different pathways and a specific reference dose of the metal. The ratio of the comparison is called the hazard quotient (HQ) and is expressed as in Eqs. 4.4 and 4.5 (USEPA 1989). H Q iOral =

i i DW ater ingestion + D Swimming ingestion

H Q iDer mal =

R f D iOral

.

D iDer malcontact R f D iDer mal

where H Q iOral H Q iDer mal

Hazard quotient for ith metal through oral ingestion Hazard quotient for ith metal through dermal contact

(4.4) (4.5)

36

R f D iOral R f D iDer mal

4 Assessment of Human Health Risks from Metals in Urban …

Reference dose of ith metal through oral ingestion (Zn = 0.3, Cu = 0.04, Pb = 0.0035, Cd = 0.0005, Cr = 0.003 and Ni = 0.02 mg/kg day) Reference dose of ith metal through dermal contact (Zn = 0.06, Cu = 0.012, Pb = 0.000525, Cd = 0.00001, Cr = 0.00006 and Ni = 0.0054 mg/kg day).

The total non-cancer health risk from multiple metals can be evaluated using the Hazard Index (HI), which is the sum of different HQs for various metals through multiple exposure pathways (Eq. 4.6). HI > 1 and HI < 1 indicate the potential to cause non-cancer health risks and lower or no risks, respectively (USEPA 1989). HI =

n  i=1

H Q Oral +

n 

H Q Der mal

(4.6)

i=1

4.2.2 Drawbacks in Classical Risk Indices The environmental fate and bioavailability of metals primarily depend on how they are geochemically bound to different constituents of particles such as organic matter and minerals. Metals are primarily distributed among four geochemical fractions of particles: exchangeable (ion-exchangeable), reducible (Fe–Mn oxide bound), oxidisable (organically bound) and residual (mineral lattice structure bound), which have varying bioavailability characteristics (Jayarathne et al. 2017; Zhang et al. 2015). Considering the adsorption/desorption ability, and in turn the bioavailability of metals in each geochemical fraction, these are referred to as, effective bioavailable (i.e. exchangeable), potentially bioavailable (i.e. reducible and oxidisable) and nonbioavailable (i.e. residual) fractions (Jalali and Khanlari 2008; Nannoni and Protano 2016). Accordingly, it can be considered that the potential of metal ions to cause toxic impacts on human health is dependent on the effective and potentially bioavailable metal concentrations rather than the total metal concentration (i.e. summation of the bioavailable and non-bioavailable metal concentrations). However, in most risk assessments, metal concentrations used for risk indices are inaccurately defined without considering the geochemical behaviour and bioavailability of metals. Therefore, it is required to modify the classical risk indices for informed decision making in human health risk management. Accordingly, the metal concentrations (C) given in the classical health risk assessment process (see Eqs. 4.1–4.6) were modified, incorporating the effective bioavailable (i.e. exchangeable, C E−Bio ) and potentially bioavailable (i.e. reducible and oxidisable, C P−Bio ) metal concentrations as given in Eq. 4.7 C = C E−Bio + C P−Bio

(4.7)

4.3 Assessing Metal Concentration in Stormwater Using Metal …

37

4.3 Assessing Metal Concentration in Stormwater Using Metal Build-Up Load The risks associated with metals in stormwater depend on the pollutant concentration in stormwater runoff. The load and composition of pollutants entrained in stormwater runoff during rainfall events are directly influenced by the initially available pollutant build-up load on impervious surfaces. Considering the aforementioned facts, metal build-up loads in each of the geochemical fractions of road dust were converted to their corresponding stormwater concentrations. This was undertaken using hydrologic and stormwater quality modelling tools as described in Ma (2016). Essentially, metal concentrations in stormwater were determined in the form of event mean concentration of total particulates (i.e. total solid concentration of a rainfall-runoff event) as given in Eq. 4.8, assuming that geochemical fractionation characteristics of metals attached to particles in stormwater runoff are the same as that in build-up samples and the ratio of different particle size ranges of solids in stormwater runoff are the same as that in build-up samples. Ci = E MC T S × Bi × 10−6 f

f

(4.8)

where Ci

f

E MC T S f Bi

Geochemical fractionated metal concentration (i.e. exchangeable, reducible, oxidisable or residual) on ith particle size range in stormwater runoff (mg/L) Event mean concentration of total solids in stormwater runoff (mg/L) Geochemical fractionated metal build-up load (i.e. exchangeable, reducible, oxidisable or residual) on ith particle size range (mg/kg).

The method adopted for calculating EMC of total solids considering the year-long rainfall-runoff events (i.e. annual average EMC) is depicted in Fig. 4.1. A detailed description of the method can be found in Ma (2016). In summary, a representative year where the rainfall characteristics are similar for the study region was selected by considering the annual rainfall depth records from the Hinze Dam weather station (Station ID: 040584), which is the nearest to Stevens street (Ind-1) and Hilldon court (Ind-2) study sites, and rainfall records from the Gold Coast Seaway (Station ID: 040764), which is the nearest to Strathaird Road (Com-1), Mediterranean Drive (Com-2), Village High Road (Res-1) and De Haviland Av (Res-2) study sites, for the period 2006–2016. Accordingly, year 2008, for which continuous rainfall records were available, was selected as the representative year. The selected rainfall depths were converted to corresponding rainfall intensities and simulated using MIKE URBAN, a commonly used hydrologic model to obtain runoff volume for a given catchment area (MIKE URBAN 2008). In this study, an area of 100 m road length and appropriate width to cover the complete urban area beside the road was considered as the unit catchment. The total runoff volume for the selected year was obtained as a summation of the runoff volumes simulated for all rainfall events.

38

4 Assessment of Human Health Risks from Metals in Urban … Selection of rainfall data for a representative year

Hydrologic modelling Stormwater quality modelling Rainfall data Pollutant build-up load estimation Calculation of rainfall intensity

Pollutant wash-off load estimation

Hydrologic modelling

Total solids load

Total runoff volume

Annual average EMC = Total solids load / Total runoff volume Fig. 4.1 Calculation of event mean concentration (EMC) of solids in stormwater considering year-long rainfall records

Total solid loads in stormwater runoff for each rainfall event were calculated using the build-up load estimation (Egodawatta and Goonetilleke 2007) followed by wash-off load estimation (Egodawatta et al. 2007) as given in Eqs. 4.9 and 4.10. The summation of the wash-off loads of all the rainfall events was taken as the total solids load for the selected year. In this study, the estimation of build-up and washoff loads was only confined to urban road surfaces and pollutant loads from other impervious surfaces such as roofs were not taken into consideration. The values used for coefficients specified in Eqs. 4.9 and 4.10 are provided in Table 4.1 B = a Db where B Pollutant build-up load D Antecedent dry days a, b Coefficients.

(4.9)

4.3 Assessing Metal Concentration in Stormwater Using Metal …

39

Table 4.1 Values used in build-up and wash-off load estimation Build-up equation coefficientsa Study catchment

ID

a

b

Strathaird Rd

Com-1

6.74

0.26

Mediterranean Dr

Com-2

3.62

0.43

Village High Rd

Res-1

3.62

0.43

De Haviland Av

Res-2

4.2

0.26

Stevens St

Ind-1

6.47

0.26

Hilldon Ct

Ind-2

6.74

0.26

Wash-off equation

coefficientsb

Rainfall intensity (I)

5–40 mm/h

40–90 mm/h

90–1150 mm/h

Capacity factor (C F )

(0.008 × I) + 0.59

0.91

(0.0036 × I) + 0.59

Wash-off coefficient (k)

9.33 × 10−3

9.33 × 10−3

9.33 × 10−3

a According b According

to the values recommended by Gbeddy et al. (2018) to the values recommended by Egodawatta (2007)

Fw =

W = C F (1 − e−K I t ) Wo

(4.10)

where Fw W Wo CF K I

Wash-off fraction Weight of pollutants washed-off after time t Initial pollutant load on road surface Capacity factor Wash-off coefficient Rainfall intensity.

The estimated total solid loads for each study catchment were divided by the corresponding total runoff volumes in order to obtain the annual average EMC of total solids in stormwater (refer to Fig. 4.1). Based on the EMC values, metal concentrations in stormwater runoff were calculated as specified in Eq. 4.8.

4.4 Human Health Risk Assessment Non-cancer health risks from metals associated with different particle size ranges of road dust in stormwater runoff which originated from different study sites were evaluated using both, classical hazard risk index (HI) and modified hazard risk index (HI m ). As evident from Fig. 4.2, there is a significant difference between the health risks calculated from classical and modified risk indices for all study sites. As indicated by the classical hazard index, the non-cancer risks from metals are higher or closer to the safe level of 1 for most of the study sites, where the highest risk was

40

4 Assessment of Human Health Risks from Metals in Urban …

(a)

10.0

Classical Hazard index (HI)

9.0

0.45-75 m 75-150 m 150-300 m 300-425 m

8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0

HI = 1

0.0 Com - 1

Modified Hazard Index (HI m )

(b)

Com - 2

Res - 1

Res - 2

Ind - 1

Ind-2

Ind - 1

Ind-2

Study sites 1.0 0.45-75 m 75-150 m 150-300 m 300-425 m

0.8

0.6

0.4

0.2

0.0 Com - 1

Com - 2

Res - 1

Res - 2

Study sites

Fig. 4.2 Human health risk from metals associated with road dust in stormwater at different study sites of commercial (Com), residential (Res) and industrial (Ind) as indicated by the classical and modified hazard risk indices

reported at Ind-2 followed by Ind-1 sites (Fig. 4.2a). In terms of particle size ranges, the risks associated with the 150 µm size ranges at most of the study sites (i.e. Com-1, Com-2, Res-2 and Ind-2). It is noteworthy that the highest risk reported at Ind-1 and Ind-2 sites fall into the low risk category (i.e. HI < 1) when the risks were estimated using the modified hazard risk index (Fig. 4.2b). These observations imply that the classical risk assessment method over-estimates the risk posed by metals, which in effect can lead to the poor decision making in human health risk management. In terms of particle size ranges, the modified hazard index also indicates that the risk posed by

4.4 Human Health Risk Assessment

41

(a) 1.6 Classical Hazard Index (HI)

Zn Cu Pb

Cr Ni Cd

1.2 1.0

0.4

0.2

Classical Hazard Index (HI)

(b)

Ind - 1 Site 1.4

0.0

Ind - 2 Site

6.0

1.0

0.5

0.0

0.45-75

75-150

150-300

300-425

0.45-75

Size fraction ( m)

(c)

0.5

Zn Cu Pb

0.20

0.15

0.10

0.05

Cr Ni Cd

Modified Hazard Index (HIm )

Ind - 1 Site

75-150

150-300

300-425

Size fraction ( m)

(d)

0.25

Modified Hazard Index (HIm )

8.0

Ind - 2 Site

0.4

0.3

0.2

0.1

0.0

0.00

0.45-75

75-150

150-300

Size fraction ( m)

300-425

0.45-75

75-150

150-300

300-425

Size fraction ( m)

Fig. 4.3 Risk posed by individual metal ions at industrial study sites as indicated by classical and modified hazard index

metals associated with fine particles is considerably higher compared to the coarser particles at most of the study sites, implying the importance of accounting for the size fractionated risk characteristics of metals. Figure 4.3 shows the contribution from individual metal ions to the total risks reported at Ind-1 and Ind-2 sites. As shown by the classical hazard index in Fig. 4.3a and b, irrespective of particle size ranges of road dust, Cr poses a higher health risk (HI > 1) at both study sites. However, as indicated by modified hazard index, where the health risks were assessed by considering the effective and potentially bioavailable metal concentrations (i.e. exchangeable, reducible and oxidisable), the potential for Cr to pose non-cancer health risk is considerably low (HI < 1) (Fig. 4.3c and d). As evident from Sect. 3.2 in Chap. 3, Cr is largely enriched in the residual fraction of particles compared to the other geochemical fractions, and in turn, barely desorbed from particle surfaces, becoming a non-bioavailable form for humans. Accordingly, the over-estimated risk from Cr through the classical risk index can be ascribed to the risk contribution from the non-bioavailable Cr concentration. Other than Cr, as evident from Fig. 4.3c and d, the non-cancer health risk from Pb is significantly higher in all particle size ranges. This suggests that though leaded fuel is no longer in common use, Pb-contaminated soils from past usage of leaded fuel and Pb originating from the wear of vehicle components are entrained in stormwater runoff. Therefore, there is still a high potential for Pb to cause non-cancer health risks in the study area. As such, considering different land use characteristics, appropriate source control

42

4 Assessment of Human Health Risks from Metals in Urban …

measures would need to be implemented in order to minimize the influence of toxic metals on stormwater quality prior to enhance stormwater reuse.

4.5 Summary This chapter presents a robust methodology to assess human health risks of metals in stormwater considering the geochemical fractionation and bioavailability characteristics. Metal build-up loads in each geochemical fraction were converted to their corresponding concentrations in stormwater by using stormwater quality and hydrologic modelling approaches. The proposed modified risk assessment lays the foundation for accurate quantification of risks posed by metals in stormwater and the development of effective risk management strategies targeting stormwater reuse in urban areas. It was noted that the health risks from metals as quantified using the modified risk index procedure showed significantly lower risk levels compared to those given by the use of the classical risk index procedure. Further, the significance of particle sizes of road dust and land use characteristics also needs to be taken into consideration when determining the risks associated with metals, for accurate risk quantification.

References Acosta JA, Cano AF, Arocena JM, Debela F, Martínez-Martínez S (2009) Distribution of metals in soil particle size fractions and its implication to risk assessment of playgrounds in Murcia City (Spain). Geoderma 149(1):101–109. https://doi.org/10.1016/j.geoderma.2008.11.034 Egodawatta P (2007) Translation of small-plot scale pollutant build-up and washoff measurements to urban catchment scale. Ph.D., Queensland University of Technology, Australia Egodawatta P, Goonetilleke A (2007) Characteristics of pollution build-up on residential road surfaces Egodawatta P, Thomas E, Goonetilleke A (2007) Mathematical interpretation of pollutant wash-off from urban road surfaces using simulated rainfall. Water Res 41(13):3025–3031. https://doi.org/ 10.1016/j.watres.2007.03.037 Gbeddy G, Jayarathne A, Goonetilleke A, Ayoko GA, Egodawatta P (2018) Variability and uncertainty of particle build-up on urban road surfaces. Sci Total Environ 640–641:1432–1437. https:// doi.org/10.1016/j.scitotenv.2018.05.384 Huang J, Li F, Zeng G, Liu W, Huang X, Xiao Z, He Y (2016) Integrating hierarchical bioavailability and population distribution into potential eco-risk assessment of heavy metals in road dust: a case study in Xiandao District, Changsha city, China. Sci Total Environ 541:969–976. https://doi.org/ 10.1016/j.scitotenv.2015.09.139 Jaishankar M, Tseten T, Anbalagan N, Mathew BB, Beeregowda KN (2014) Toxicity, mechanism and health effects of some heavy metals. Interdiscip Toxicol 7(2):60–72 Jalali M, Khanlari ZV (2008) Effect of aging process on the fractionation of heavy metals in some calcareous soils of Iran. Geoderma 143(1):26–40. https://doi.org/10.1016/j.geoderma.2007. 10.002

References

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Jayarathne A, Egodawatta P, Ayoko GA, Goonetilleke A (2017) Geochemical phase and particle size relationships of metals in urban road dust. Environ Pollut 230:218–226. https://doi.org/10. 1016/j.envpol.2017.06.059 Li H-H, Chen L-J, Yu L, Guo Z-B, Shan C-Q, Lin J-Q, Cheng Z (2017) Pollution characteristics and risk assessment of human exposure to oral bioaccessibility of heavy metals via urban street dusts from different functional areas in Chengdu, China. Sci Total Environ 586:1076–1084. https://doi. org/10.1016/j.scitotenv.2017.02.092 Ma Y (2016) Human health risk of toxic chemical pollutants generated from traffic and land use activities. Ph.D., Queensland University of Technology Ma Y, Egodawatta P, McGree J, Liu A, Goonetilleke A (2016) Human health risk assessment of heavy metals in urban stormwater. Sci Total Environ 557–558:764–772. https://doi.org/10.1016/ j.scitotenv.2016.03.067 Man YB, Sun XL, Zhao YG, Lopez BN, Chung SS, Wu SC, Wong MH (2010) Health risk assessment of abandoned agricultural soils based on heavy metal contents in Hong Kong, the world’s most populated city. Environ Int 36(6):570–576. https://doi.org/10.1016/j.envint.2010.04.014 MIKEURBAN (2008) MIKE URBAN user’s manual. DHI Water Environment Health, Hørsholm, Denmark Nannoni F, Protano G (2016) Chemical and biological methods to evaluate the availability of heavy metals in soils of the Siena urban area (Italy). Sci Total Environ 568:1–10. https://doi.org/10. 1016/j.scitotenv.2016.05.208 USEPA (1989) Risk assessment guidance for superfund human health evaluation manual (Part A), vol 1. Office of Emergency and Remedial Response, US Environmental Protection Agency, Washington, DC USEPA (2001) Supplemental guidance for developing soil screening levels for superfund sites. Office of Emergency and Remedial Response, US Environmental Protection Agency, Washington, DC Zhang C, Yu Z-G, Zeng G-M, Jiang M, Yang Z-Z, Cui F, Hu L (2014) Effects of sediment geochemical properties on heavy metal bioavailability. Environ Int 73:270–281. https://doi.org/10. 1016/j.envint.2014.08.010 Zhang J, Hua P, Krebs P (2015) The build-up dynamic and chemical fractionation of Cu, Zn and Cd in road-deposited sediment. Sci Total Environ 532:723–732. https://doi.org/10.1016/j.scitotenv. 2015.06.074 Zhao H, Li X (2013) Risk assessment of metals in road-deposited sediment along an urban–rural gradient. Environ Pollut 174:297–304. https://doi.org/10.1016/j.envpol.2012.12.009

Chapter 5

Practical Implications and Recommendation for Future Research

Abstract This chapter summarises the key outcomes of the research study undertaken to investigate metal transformations on urban road surfaces and their potential impacts on stormwater quality. In particular, it discusses the practical implications of the research outcomes in relation to stormwater pollution mitigation in the context of stormwater reuse. Stormwater pollution mitigation strategies should be implemented such that they specifically address the impacts of fine road dust particles and more mobile metals such as Zn and Cd in stormwater runoff. Furthermore, it is important to enhance current risk assessment methods by taking into consideration the geochemical behaviour of metals for accurate risk quantification. The chapter further discusses the current knowledge gaps where further research is needed. These include, the investigation of transformation processes of other toxic pollutants and the influence of additional factors on metal transformation, and the need for integrating factors influencing metal transformation into stormwater quality models for developing effective stormwater pollution mitigation strategies. Keywords Metals · Transformations · Risk assessment · Stormwater quality · Stormwater reuse

5.1 Background The rapid urban population growth has increased the demand for water resources, creating the urgent need for sustainable use of water. In this context, stormwater is a valuable alternative water resource that can be used for a range of needs in the built environment. However, stormwater reuse can be challenging due to the presence of various toxic pollutants such as metals. Therefore, prior to stormwater reuse, the improvement in stormwater quality may be needed depending on the intended use in order to safeguard human and ecosystem health. Stormwater quality is significantly influenced by the transformations that pollutants undergo during dry weather periods prior to being entrained in stormwater runoff. This is because, the transformed pollutants may exhibit different characteristics in terms of their mobility, bioavailability and toxicity compared to their original form, exerting a significant influence on the quality of receiving waters. Therefore, a © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5_5

45

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5 Practical Implications and Recommendation for Future Research

comprehensive understanding of the behavioural changes of pollutants and associated water quality impacts is required as a prelude to stormwater reuse. Knowledge gained by investigating the behavioural changes of metals associated with road dust can be used for informed decision making in relation to treatment strategies and for implementing ‘fit-for-purpose’ stormwater reuse. This chapter summarises key outcomes of the research study undertaken and how these outcomes can be implemented targeting stormwater pollution mitigation. Further, recommendations for future research directions are provided by identifying current knowledge gaps.

5.2 Implications of Research Outcomes 5.2.1 Implications Related to Transformation Processes of Metals Metals build-up on road surfaces are intrinsically associated with road dust particles. Depending on the availability and selectivity of metal ions for surface charge sites on particles, the geochemical affinity of metals can vary, resulting in variable mobility and bioavailability characteristics. Metals attached to particles are primarily distributed among four geochemical fractions: exchangeable (ion-exchangeable), reducible (bound to Fe–Mn oxides), oxidisable (bound to organic matter) and residual (bound to mineral lattice structures). The exchangeable fraction of metals is mobile and bioavailable due to their weak geochemical attachment to the particle surface. The mobility characteristics of metals bound to the reducible and oxidisable fractions are relatively low as they specifically undergo inner-sphere adsorption complexation. Metals which are incorporated into the lattice structure of minerals are considered as immobile and non-bioavailable. In this context, a significant focus should be on metals which are associated with the exchangeable fraction of particles, due to their readily available nature. Zn shows the highest affinity towards the exchangeable fraction followed by the oxidisable and reducible fractions. Both, Cu and Pb are enriched in the reducible and oxidisable fractions compared to the exchangeable fraction. Similar to Zn, Cd shows a decreasing trend in its concentration in sequential geochemical fractions, where the highest percentage concentrations were found in the exchangeable fraction. For Cr and Ni, the highest percentage concentrations were found in association with the residual fraction, and the affinity for the exchangeable fraction was low. The following mobility order of metals was identified considering their characteristic enrichment in the exchangeable fraction of road dust: Cd > Zn > Cu > Pb > Ni > Cr. These observations highlight the requirement for the selection of suitable treatment methods that can efficiently remove more mobile metals in stormwater considering the geochemical affinity and mobility characteristics. The influence of antecedent dry days on the geochemical behaviour of metals was investigated to understand the transformation characteristics of metals, with residence

5.2 Implications of Research Outcomes

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time. The exchangeable form of Zn, Cu and Pb transforms into either reducible or oxidisable forms, with time. However, Cd tends to persist in the exchangeable form rather than transform into stable geochemical forms. The transformation rate of metals in the exchangeable fraction follows the order: Pb > Cu > Zn > Cd, which is inverse to the mobility order of metals. This further confirms that Cd and Zn have a high potential for being mobile and bioavailable compared to other metals. Further, the importance of the antecedent dry weather period when predicting metal pollution levels and associated risk in stormwater runoff is evident from the research outcomes. As such, pollution mitigation strategies should be implemented to systematically remove road dust particles, predominantly fine particle sizes accumulating over the dry weather periods in order to minimise potential stormwater quality impacts associated with toxic pollutants.

5.2.2 Implications Related to Human Health Risk Assessment of Metals in Stormwater The non-cancer health risks of six metals, namely, Zn, Cu, Pb, Cd, Cr and Ni were assessed based on the geochemical fractionation and potential bioavailability characteristics of metals by improving the classical risk indices. Metal build-up loads were converted to their corresponding concentrations in stormwater using the approach discussed in Ma (2016), as the risks associated with metals in stormwater is dependent on the metal concentration in stormwater runoff. A comparison between the classical and modified health risk indices clearly indicated that the classical risk index over-estimates the risk from metals in stormwater. As implied by the modified risk assessment method, the non-cancer risks posed by metals vary among different study sites based on the land use characteristics and particle size ranges of road dust. Even though the risks posed by metals at all the study sites and particle size ranges are below the safe threshold level, it was noted that industrial study sites and metals associated with fine particle size ranges of road dust pose the highest health risk. Furthermore, there is a high potential for Cr and Pb to create non-cancer health effects through incidental ingestion and/or dermal contact with metal contaminated stormwater. Therefore, the selection of appropriate source control measures to minimise the enrichment of toxic metals such as Cr and Pb in stormwater runoff which predominantly originates from industrial areas is essential, prior to stormwater reuse.

5.3 Recommendations for Future Research Based on the knowledge gaps identified, the following future research directions are proposed that can enhance the state-of-the-art-knowledge for developing effective stormwater pollution mitigation strategies and to ensure the safe reuse of stormwater.

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5 Practical Implications and Recommendation for Future Research

a. Not only metals This study was confined to the investigation of the transformation characteristics of metals, one of the toxic pollutant species commonly found in urban environments. However, the behavioural changes of other toxic pollutants such as hydrocarbons can also potentially influence stormwater quality and the human health risk associated with stormwater reuse. Therefore, further studies are required targeting other toxic pollutants present in the urban environment. b. Other influential factors Apart from the key influential factors investigated such as particle size of road dust, organic matter content and antecedent dry days, the investigation of the potential influence exerted by other physicochemical factors such as pH and dissolved organic carbon in rain water, on metal transformation is recommended. It has been noted that organic matter and pH could be important parameters enhancing the desorption of pollutants from the solid phase (Zhang et al. 2016). c. Mathematical modelling Factors influencing metal transformations need to be incorporated into metal build-up models for informed decision-making and thereby, the implementation of effective stormwater pollution mitigation strategies. Even though the relationship between metal build-up and influential factors such as antecedent dry days, traffic and land use parameters has been mathematically replicated (Egodawatta et al. 2013; Ma et al. 2016; Wijesiri et al. 2016), the influence of physicochemical properties of road dust such particle size, organic matter content and mineralogy has not been incorporated into models.

References Egodawatta P, Ziyath AM, Goonetilleke A (2013) Characterising metal build-up on urban road surfaces. Environ Pollut 176:87–91. https://doi.org/10.1016/j.envpol.2013.01.021 Ma Y (2016) Human health risk of toxic chemical pollutants generated from traffic and land use activities. Doctor of Philosophy, Queensland University of Technology Ma Y, Egodawatta P, McGree J, Liu A, Goonetilleke A (2016) Human health risk assessment of heavy metals in urban stormwater. Sci Total Environ 557–558:764–772. https://doi.org/10.1016/ j.scitotenv.2016.03.067 Wijesiri B, Egodawatta P, McGree J, Goonetilleke A (2016) Influence of uncertainty inherent to heavy metal build-up and wash-off on stormwater quality. Water Res 91:264–276. https://doi. org/10.1016/j.watres.2016.01.028 Zhang J, Hua P, Krebs P (2016) The influences of dissolved organic matter and surfactant on the desorption of Cu and Zn from road-deposited sediment. Chemosphere 150:63–70. https://doi. org/10.1016/j.chemosphere.2016.02.015

Index

A Adsorption, 3–7, 17, 25, 36, 46 Adsorption complexes, 4 Antecedent Dry Days (ADD), 12, 25, 26, 28–31, 38, 46, 48 Antecedent dry period, 12, 47 Anthropogenic, 1, 2, 12, 17

B Bioavailability, 1–7, 11, 21–23, 25, 27, 33, 34, 36, 42, 45–47 Build-up, 3, 5, 12, 25, 33, 37–39, 42, 46–48

C Cation exchange capacity, 6, 7 Chemisorption, 4–7

D Dermal contact, 34–36, 47 Desorption, 23, 25, 36, 48 Dry and wet vacuum, 12

E Event Mean Concentration (EMC), 37–39 Exchangeable, 4, 6, 17, 18, 21–25, 27–31, 36, 37, 41, 46, 47 Exposure pathways, 34–36

F Fe-Mn oxide, 17, 22, 28, 36, 46 Fit-for-purpose, 1, 2, 46

G Geochemical behaviour, 21–23, 31, 33, 34, 36, 45, 46 Geochemical binding forms, 17 Geochemical fraction, 21, 23, 31, 36, 37, 41, 42, 46

H Hazard index, 33, 36, 39–41 Hazard quotient, 35 Health risk, 2, 33, 34, 36, 39–42, 47, 48 Hydrologic modelling, 42

I Immobile, 23, 46 Impervious surfaces, 2, 37, 38 Ingestion, 34–36, 47 Ion-exchangeable, 4, 22, 25, 29, 31, 36, 46

L Land use, 3, 12–15, 19, 22, 23, 25–27, 33, 41, 42, 47, 48 Lattice structure, 6, 17, 36, 46

M Metals, 1–7, 11, 16–19, 21–23, 25, 29–31, 33–37, 39–42, 45–48 Minerals, 5, 6, 17, 23, 36, 46 Mobilisable, 23 Mobility, 1–7, 11, 21–23, 25, 27, 30, 31, 45–47

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 A. Jayarathne et al., Transformation Processes of Metals in Urban Road Dust, SpringerBriefs in Water Science and Technology, https://doi.org/10.1007/978-981-15-2078-5

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Index N Non-bioavailable, 23, 36, 41, 46 Non-cancer risk, 35, 36, 39, 41, 47

O Organically bound, 27, 28, 36 Organic matter, 3, 17, 23, 25, 27–29, 31, 36, 46, 48 Oxidisable, 18, 21–25, 27–29, 31, 36, 37, 41, 46, 47

P Particle size, 3, 6, 7, 16, 17, 22–31, 37, 39–41, 47, 48 Physicochemical properties, 3, 4, 6, 11, 17, 19, 26, 48 Pollution, 2, 11, 21, 23, 34, 45–47 Pollution mitigation strategies, 7, 11, 21, 23, 31, 45, 47, 48 Potentially bioavailable, 23, 36, 41

R Reducible, 18, 21–25, 27–29, 31, 36, 37, 41, 46, 47 Representative year, 37 Residence time, 3, 6, 7, 21, 25, 27, 28, 30, 31, 47 Residual, 18, 21, 23–25, 28, 31, 36, 37, 41, 46

Risk assessment, 33, 34, 36, 39, 40, 42, 45, 47 Road dust, 1, 3–7, 11, 12, 16–19, 21–29, 31, 37, 39–42, 45–48 Road surfaces, 2, 3, 5, 7, 12, 17, 28, 31, 38, 45, 46 Runoff volume, 37, 39

S Sample collection, 11, 12, 16, 19 Sequential extraction, 17, 18 Specific surface area, 3, 5–7, 17, 23, 26 Stormwater pollutants, 2, 7, 33 Stormwater quality, 1–4, 7, 11, 21–23, 30, 31, 33, 37, 42, 45, 47, 48 Stormwater quantity, 33 Stormwater reuse, 1, 2, 34, 42, 45–48 Stormwater runoff, 2, 6, 7, 11, 21, 33, 34, 37–39, 41, 45, 47 Surface functional groups, 4–6 Surface precipitation, 3, 5

T Total solids, 37–39 Transformation rate, 21, 30, 31, 47 Transformations, 1–7, 11, 16, 17, 21, 22, 25, 27–31, 45–48

W Wash-off, 21, 38, 39