Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability

STOTEN-26451; No of Pages 11 Science of the Total Environment xxx (2018) xxx–xxx

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Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability Ayomi Jayarathne, Prasanna Egodawatta, Godwin A. Ayoko, Ashantha Goonetilleke ⁎ Science and Engineering Faculty, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, 4001, Queensland, Australia

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Geochemical fractionation of metals influence their bioavailability characteristics. • Ecological and human health risk of metals assessed considering bioavailability. • Ecological risk of metals in different size fractions in road dust relatively low. • The non-cancer risk of metals in different size fractions was below the threshold. • The cancer risk of Cr in road dust was higher than the other carcinogenic metals.

a r t i c l e

i n f o

Article history: Received 16 January 2018 Received in revised form 6 April 2018 Accepted 6 April 2018 Available online xxxx Editor: D. Barcelo Keywords: Metals Road dust Sequential extraction Bioavailability Risk index

a b s t r a c t Metals are one of the primary pollutants in the urban environment that pose adverse ecological and human health impacts. Therefore, the accurate quantification of the risk posed by metals is essential for developing effective risk management strategies to safeguard the urban environment. This study assessed the ecological and human health risks of six metals, commonly present in road dust by improving the original risk indices based on their potential bioavailability characteristics. The bioavailability of metals was determined by considering their distribution between the different geochemical phases of exchangeable, reducible, oxidisable and residual. The results of the modified risk analysis indicated that the road dust poses a low ecological risk in most of the study sites. According to the present situation, the non-cancer risk of individual metals for both, children and adults followed the decreasing trend of Pb N Cu N Cr N Zn N Ni N Cd. This study also found that depending on the particle size ranges, the potential of multiple metals being able to cause non-cancer health risk was low at most study sites. In terms of cancer health risk, Cr present at most of the study sites was found to be within the cancer threshold limit, even though the Cr content and the bioavailable fractions were relatively low. © 2018 Elsevier B.V. All rights reserved.

1. Introduction Road dust, which consists of particles of natural (i.e. weathered or eroded soil and re-suspended particles) and anthropogenic (i.e. vehicular ⁎ Corresponding author. E-mail addresses: [email protected], (A. Jayarathne), [email protected], (P. Egodawatta), [email protected], (G.A. Ayoko), [email protected]. (A. Goonetilleke).

traffic emissions and construction and demolition materials) origin acts as the main adsorbent and mobile substrate for a diversity of pollutants deposited on road surfaces (Goonetilleke et al., 2005; Lau and Stenstrom, 2005). Among the diverse types of pollutants, the presence of metals is of great concern due to their persistence, bioavailability and toxicity characteristics that can cause harmful effects on both, human health and the environment. Metals in very low concentrations are essential for living organisms, particularly for the functioning of chemical and biological activities

https://doi.org/10.1016/j.scitotenv.2018.04.098 0048-9697/© 2018 Elsevier B.V. All rights reserved.

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

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(Nagajyoti et al., 2010; Singh et al., 2011). However, after exceeding a certain threshold limit, they can cause either short term or long term toxic impacts. For example, short term exposure to metals can cause skin irritations, breathing problems and vomiting, whilst with long term exposure, they can cause cancer in the skin, lungs and kidneys (Duruibe et al., 2007; Jaishankar et al., 2014; Martin and Griswold, 2009). Numerous research studies have been conducted in the area of metal pollution of road dust, including the identification of sources and pathways (Brown and Peake, 2006; Mahbub et al., 2010), assessment of metal pollution levels and evaluation of the ecological and human health risks posed by different metals in the urban environment (Li et al., 2017; Liao et al., 2017; Man et al., 2010). Furthermore, in recent years, risk assessment studies have been extended to incorporate different influential factors such as particle size of road dust and traffic and land use characteristics (Ma et al., 2016; Ma et al., 2017; Zhao and Li, 2013). However, in most studies, the risk posed by metals is either over-estimated or under-estimated, as their geochemical behaviour is not taken into consideration. Metals attached to solid constituents such as organic matter, metal oxides, and primary and secondary minerals are in different binding forms, resulting in either weak or strong metal-solid complexes (Gunawardana et al., 2015; Jayarathne et al., 2018). Consequently, the desorption characteristics and thereby the bioavailability of metals are primarily dependent on the geochemical interactions in the metal-solid complex. The geochemical behaviour of metals associated with road dust has been investigated by numerous researchers in recent years to evaluate their mobility, availability and persistence characteristics using different extraction methods (Świetlik et al., 2015; Tokalıoğlu and Kartal, 2006; Zhang et al., 2017). A well-known sequential extraction procedure, which was initially proposed by Tessier et al. (1979) and modified by a range of researchers, is one of the widely used analytical methods for characterising the geochemical interactions of metals. For example, using sequential extraction, Zhang and Wang (2009), Sutherland et al. (2012), Isen et al. (2013) and Jayarathne et al. (2017) studied the partitioning of metals in road dust over different geochemical fractions (also referred to as geochemical phases) and found that metals such as Zn and Cd are the most mobile and potentially bioavailable, whereas Cu, Pb, Mn, Co, Cr and Ni have medium to least risk of being mobilised and bioavailable. Zhang et al. (2015) further reported that geochemical fractionation of metals was strongly size-dependent. Moreover, Acosta et al. (2014) reported that metal distribution in different geochemical fractions is dependent on the type of land use. They found that Pb was mainly bound with primary and secondary minerals in natural land use areas, whereas in industrial road dust, it was mainly bound to the metal oxides of Fe and Mn, resulting in different desorption characteristics with land use. These findings highlight the importance of evaluating the risk posed by metals based on their geochemical fractionation, particle size ranges and land use. Accordingly, the objectives of this study were to: (1) improve the ecological and human health risk indices based on geochemical fractionation and bioavailability of metals; and (2) assess the ecological and human health risks posed by metals in different urban land use areas and particle size ranges of road dust using the improved risk indices. The generic outcomes of this study will contribute to the development of appropriate measures to mitigate metal pollution in urban areas. 2. Materials and methods 2.1. Study sites Six road surfaces in two suburbs, Benowa and Nerang, in Gold Coast, South East Queensland (QLD), Australia (Fig. 1) were selected for this study. The primary consideration in the study site selection was the differences in traffic volume and land use characteristics common to commercial (C), residential (R) and industrial (I) areas, ensuring the collection of metal build-up loads with a range of different characteristics

(Liu et al., 2016). Benowa can be characterised as a mixed-land-use suburb due to the presence of different commercial and residential activities, whereas Nerang is a region with light industries and commercial services. Accordingly, the two commercial sites of C-1 and C-2, and the residential sites of R-1 and R-2 were selected in Benowa, whilst the two industrial sites of I-1 and I-2 in Nerang were selected. The type of land use activities present at each study site and corresponding daily traffic volume (DTV) are shown in Fig. 1. 2.2. Sample collection and analytical methods The sample collection was carried out during the Southern Hemisphere spring and summer periods of September to December 2016. At each selected study site, four sampling campaigns were conducted, selecting four different antecedent dry days (dry days since the last substantial rainfall event), namely, one, four, seven and eleven. The primary consideration for the selection of different dry days for this study was the variability in metal build-up load with different dry periods (Egodawatta and Goonetilleke, 2006; Wicke et al., 2012). As reported by Egodawatta et al. (2013), metal build-up rate on road surfaces is high for the first few dry days after a storm event and decreases gradually to reach a near constant value after about 14 days. Accordingly, a total of 24 build-up samples was collected for analyses. Road dust samples were collected using a dry and wet vacuum system, which has been described in Jayarathne et al. (2017). A plot area of one metre width by the distance from the kerb to the road centreline was demarcated at each study site, ensuring the representative collection of solids distributed across the road surface. Collected samples were separated into four different size ranges; 0.45–75 μm, 75–150 μm, 150–300 μm and 300–425 μm using wet and dry sieving and allowing particles to air dry. These particle size ranges were selected in view of their significance in metal-solid adsorption, which gives rise to variable contamination levels (Gunawardana et al., 2014; Zhao et al., 2017). Therefore, different ecological and health risk characteristics of metals would be expected with different particle size ranges of solids. Dust samples were then analysed for six metals commonly found on urban road surfaces (Zn, Cu, Pb, Cr, Ni and Cd) according to the three-step sequential extraction procedure proposed by the European Community Bureau of Reference (BCR sequential extraction) and using the aqua regia digestion method, which had been published elsewhere (Jayarathne et al., 2017). These procedures are able to separate metals into geochemical phases of exchangeable (ion-exchange and carbonate bound), reducible (Fe-Mn bound), oxidisable (organically bound) and residual (primary silicate bound) fractions (Horvath et al., 2010; Ozcan and Altundag, 2013). Briefly, the following reagents and experimental conditions were used for the extraction: exchangeable-0.11 mol L−1 of acetic acid (40 mL, shaken for 16 h at room temperature), reducible0.1 mol L−1 hydroxylammonium chloride (40 mL, shaken for 16 h at room temperature), oxidisable-30% hydrogen peroxide (10 mL, digested for 1 h at room temperature followed by another 1 h at 85 °C) and 1.0 mol L−1 ammonium acetate (25 mL, shaken for 16 h at room temperature), and residual-aqua regia digestion. In addition, Al concentration (reference element) in each dust sample was analysed using the same method. Metal concentrations were determined using Agilent 8800 Triple Quadrupole Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and reported on a dry weight basis (mg kg−1). The accuracy and analytical precision of the metal extraction was determined by analysing the BCR-701 certified reference material (CRM) and triplicates of a randomly selected sample within each batch. The recovery values of CRM are provided in Table S1 in the Supplementary Information, showed satisfactory efficiency of the method. Moreover, the method accuracy was verified by comparing the sum of the metal concentration in sequential fractions and pseudo-total metal concentration (direct digestion of road dust samples using aqua-regia). The recovery values of all metals for the selected road dust samples ranged from 85%–120%, indicating good agreement between methods.

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

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Fig. 1. Study sites. Notes: Data from Gold Coast City Council, Queensland, Australia. DTV-daily traffic volume.

2.3. Ecological risk assessment methodology The likelihood of environmental impact due to the presence of metals is assessed using a variety of methods. These methods provide a quantitative approach in relation to the pollution level and the ecological risk posed by different metals which can be informative to decision makers in environmental risk management. The risk evaluation methods used in this study are enrichment factor, geo-accumulation index and modified ecological risk index. The modified ecological risk index was developed from the original ecological risk index by taking into consideration the geochemical behaviour and bioavailability characteristics of the metals. 2.3.1. Enrichment factor The enrichment factor (EF) described in Keshavarzi et al. (2015) was applied to assess the contamination level of metals in road dust using Eq. (1). This method facilitates the discrimination of the source

contribution of metals between natural and anthropogenic origin (Chen et al., 2007).
C i =C ref dust
EF ¼ ð1Þ Bi =Bref background where (Ci/Cref)dust and (Bi/Bref)background are the concentration ratio of the ith metal and the reference metal in the dust sample and the background, respectively. In this study, Al was used as the reference metal as it is the most commonly used normalising element in geochemical analysis (Brady et al., 2014; Duodu et al., 2017). The background metal concentrations are the investigation threshold of metals in Australian soils (ANZECC-NHMRC, 1992; Caritat and Cooper, 2011; DEC, 2010). 2.3.2. Geo-accumulation index The geo-accumulation index (Igeo) also evaluates the pollution level of metals in road dust by comparing the present concentration with

Table 1 Contamination categories of metals. EF valuea

Enrichment degree

Igeo valueb

Pollution degree

RI valuec

Risk degree

EF b 2 2 b EF b 5 5 b EF b 20 20 b EF b 40 40 b EF

Deficiency to minimum enrichment Moderate enrichment Significant enrichment Very high enrichment Extreme enrichment

Igeo ≤ 0 0 b Igeo b 1 1 b Igeo b 2 2 b Igeo b 3 3 b Igeo b 4 4 b Igeo b 5 5 b Igeo

Unpolluted Slightly polluted Moderately polluted Moderate to heavily polluted Heavily polluted Heavily to extremely polluted Extremely polluted

RI b 50 50 ≤ RI b 100 100 ≤ RI b 200 200 ≤ RI

Low risk Moderate risk Considerable risk Very high risk

a b c

Sutherland (2000). Müller (1969). Zhao and Li (2013).

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

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Table 2 Factors used for health risk assessment. Factor CIngR InhR EF ED CF BW PEF SA -

Metal concentration Dust ingestion rate Dust inhalation rate Exposure frequency Exposure duration Unit conversion factor Average body weight Particle emission factor Exposed skin area Skin adherence factor Dermal absorption factor Average exposure time for non-cancer risk Average exposure time for cancer risk

ABS AT -

Unit

Child

Adult

Reference

mg kg−1 mg/day m3/day day/year year kg mg−1 kg m3/kg cm2 mg/cm2/day unitless day day

200 7.6 180 6 10−6 15 1.36 ×109 2800 0.2 0.001 2190 25,550

100 20 180 24 10−6 70 1.36 ×109 5700 0.07 0.001 8760 25,550

USEPA (2001) Van den Berg (1994) Li et al. (2017) USEPA (2001) USEPA (1989) USEPA (2001) USEPA (2001) USEPA (2001) USEPA (2001) USEPA (2001) Li et al. (2017) Li et al. (2017)

pre-industrial levels. The Igeo index was calculated using Eq. (2) (Müller, 1969): Igeo ¼ log2

C id 1:5 

ð2Þ

C ibk

i are the concentrations of the ith metal in dust sample where Cdi and Cbk and background, respectively. The factor 1.5 was applied as the background matrix correction value (Ke et al., 2017).

2.3.3. Ecological risk index The potential risk posed by a particular metal cation is not solely dependent on its concentration, but also on the toxicological characteristics. Accordingly, the ecological risk index (RI), which was originally

proposed by Hakanson (1980) can be used to assess the risk of metals based on their toxicity response in the environment (Eqs. (3), (4)). n

RI ¼ ∑i¼1 T ir  C if

ð3Þ

C if ¼ C id =C ibk

ð4Þ

where RI is the sum of the potential ecological risk of metals; Tri is the toxic response factor of the ith metal and Cfi is the contamination factor i for the ith metal. Cdi and Cbk have the same meaning as in Eq. (2). The toxic response factors of metals are; Zn = 1, Cr = 2, Cu = Ni = Pb = 5 and Cd = 30 (Hakanson, 1980; Liu et al., 2015). The contamination categories for EF, Igeo and RI are given in Table 1.

Table 3 Enrichment factor (EF) of metals for different study sites (mean ± standard deviation). Site

Size range (μm)

Zn

Cu

Pb

Cr

Ni

Cd

BST

b75 75–150 150–300 300–425

23.3 ± 1.0 22.9 ± 2.6 23.9 ± 3.4 15.0 ± 4.6

19.7 ± 2.8 29.7 ± 5.5 38.0 ± 13.8 39.4 ± 23.8

3.1 ± 0.2 3.2 ± 0.2 3.9 ± 2.3 4.3 ± 2.2

6.1 ± 1.3 7.9 ± 1.5 6.1 ± 0.5 5.6 ± 1.4

3.1 ± 0.6 3.7 ± 0.6 2.8 ± 0.2 2.6 ± 0.7

1.1 ± 0.5 0.8 ± 0.1 0.7 ± 0.2 0.5 ± 0.2

EF rangea b75 75–150 150–300 300–425

Significant to very high 16.1 ± 9.6 13.1 ± 2.4 17.8 ± 6.8 18.8 ± 3.6

Significant to extreme 15.7 ± 10.7 12.9 ± 4.3 9.1 ± 0.6 9.4 ± 3.1

Moderate 0.7 ± 0.2 0.8 ± 0.6 0.6 ± 0.4 0.6 ± 0.4

Significant 3.0 ± 0.6 5.1 ± 3.1 6.1 ± 5.1 3.0 ± 1.6

Moderate 1.3 ± 0.2 2.0 ± 1.2 2.4 ± 0.9 1.2 ± 0.6

Deficient to minimum 0.2 ± 0.0 0.2 ± 0.0 0.2 ± 0.0 0.2 ± 0.0

EF range b75 75–150 150–300 300–425

Significant 7.4 ± 1.0 6.3 ± 0.8 5.9 ± 0.7 6.5 ± 1.5

Significant 9.0 ± 2.2 7.9 ± 1.7 10.4 ± 2.9 4.5 ± 1.4

Deficient to minimum 2.0 ± 0.2 1.7 ± 0.2 1.2 ± 0.3 1.3 ± 0.2

Moderate 4.4 ± 1.4 5.6 ± 1.7 3.8 ± 0.7 2.7 ± 0.4

Deficient to moderate 2.0 ± 0.5 2.0 ± 0.4 1.5 ± 0.2 1.3 ± 0.2

Deficient to minimum 0.2 ± 0.0 0.1 ± 0.0 0.1 ± 0.0 0.1 ± 0.0

EF range b75 75–150 150–300 300–425

Significant 11.7 ± 3.3 11.7 ± 2.4 10.5 ± 3.1 11.3 ± 3.2

Significant 13.6 ± 2.9 12.2 ± 2.9 7.4 ± 1.1 10.8 ± 7.3

Deficient to moderate 1.3 ± 0.4 1.4 ± 0.4 1.2 ± 0.5 1.3 ± 0.6

Moderate 4.1 ± 1.0 5.1 ± 2.0 2.9 ± 0.6 3.9 ± 1.9

Deficient to moderate 1.7 ± 0.5 2.1 ± 0.7 1.5 ± 0.5 1.9 ± 1.1

Deficient to minimum 0.3 ± 0.1 0.3 ± 0.1 0.3 ± 0.1 0.3 ± 0.1

EF range b75 75–150 150–300 300–425

Significant 14.7 ± 1.4 15.3 ± 1.7 15.3 ± 4.1 12.9 ± 4.1

Significant 10.7 ± 4.4 13.6 ± 5.6 30.0 ± 20.0 33.1 ± 15.4

Deficient to minimum 1.9 ± 0.3 1.6 ± 0.1 1.1 ± 0.1 1.1 ± 0.2

Moderate 5.3 ± 1.0 6.7 ± 1.4 8.1 ± 1.6 7.8 ± 3.5

Deficient to moderate 2.6 ± 0.3 3.0 ± 0.5 3.5 ± 1.5 3.6 ± 0.1

Deficient to minimum 0.5 ± 0.1 0.5 ± 0.1 0.4 ± 0.1 0.4 ± 0.1

EF range b75 75–150 150–300 300–425 EF range

Significant 24.4 ± 2.2 28.4 ± 3.4 29.3 ± 12.0 30.6 ± 12.3 Very high

Significant to very high 175.9 ± 85.8 64.8 ± 22.2 89.3 ± 20.2 57.2 ± 17.0 Extreme

Deficient to minimum 2.1 ± 0.1 2.6 ± 0.4 2.4 ± 1.0 2.0 ± 1.1 Moderate

Significant 21.2 ± 2.2 38.4 ± 9.0 40.7 ± 3.5 39.1 ± 22.6 Very high

Moderate 9.5 ± 0.8 14.9 ± 3.1 14.5 ± 5.1 12.1 ± 7.1 Significant

Deficient to minimum 0.8 ± 0.4 0.7 ± 0.1 0.5 ± 0.0 0.6 ± 0.4 Deficient to minimum

BMT

BVH

BDH

NSS

NHC

a

Elements

EF range is based on the criteria provided in Table 1.

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

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f3i and f4i are the exchangeable, reducible, oxidisable and residual phase metal concentrations, respectively, as a percentage of the total metal concentration. Accordingly, the original ecological risk index was modified as shown in Eqs. (8) and (9), incorporating the ‘effective’ and ‘potentially’ bioavailable fractions of metals in order to evaluate the ecological risk posed by metals based on their geochemical behaviour.

2.3.4. Modified ecological risk index based on the bioavailability characteristics of metals The behaviour and fate of metals in the environment are primarily dependent on the way that metals interact with solids. Consequently, different bioavailability characteristics and thereby potential environmental impacts can be assessed by identifying the geochemical fractions of metals (i.e. exchangeable, reducible, oxidisable and residual). The exchangeable fraction is often referred to as the ‘effective bioavailable or mobile fraction’, whereas the reducible and oxidisable fractions are collectively considered as the ‘potentially bioavailable or mobilisable fraction’ (Jayarathne et al., 2017; Nannoni and Protano, 2016). Metals which are bound to the residual fraction are considered immobile and “non-bioavailable” in nature as they are firmly attached to the interlayer crystalline structure of mineral lattices and may not be desorbed under natural conditions (Jalali and Khanlari, 2008; Keshavarzi et al., 2015; Lu et al., 2005). As described in Huang et al. (2016), the bioavailability of metals based on their geochemical fractions can be calculated using Eqs. (5)–(7). i

5

C imf ¼

C iBio C iBk

þ

C iP−Bio

ð8Þ

C iBk

n

RIm ¼ ∑i¼1 T ir  C imf

ð9Þ

i i is the modified contamination factor of the ith metal; CBio and where Cmf i CP−Bio are the concentrations of the effective bioavailable and potentially bioavailable fractions of the ith metal; RIm is the modified ecological risk index.

F iBio ¼ C i  f 1

ð5Þ

2.4. Modified human health risk assessment model

  i i F iP−Bio ¼ C i  f 2 þ f 3

ð6Þ

Similar to the ecological impacts, the presence of metals in urban road dust can cause potentially adverse human health impacts. The risk posed by metals to human health can be quantitatively assessed by understanding the relevant exposure scenarios (Shi et al., 2011). In this study, the original health risk assessment model was also modified considering the bioavailability characteristics of metals. The primary pathways of entry of metal contaminated road dust into the human body are; incidental ingestion via food and drink,

i

F iNon−Bio ¼ C i  f 4

ð7Þ

i i i where FBio , FP−Bio and FNon−Bio are the effective bioavailable, potentially bioavailable and non-bioavailable geo-chemical fractions of the ith metal, respectively; Ci is the concentration of the ith metal; f1i , f2i,

Table 4 Igeo index of metals at different study sites and particle size ranges of road dust (mean ± standard deviation).

Site

Size range (µm) <75 75–150 150–300 300–425

Elements Zn

Cu

1.96 ± 0 1.30 ± 0 0.37 ± 0 0.31 ± 1

1.71 ± 0 1.67 ± 0 0.23 ± 1 0.82 ± 1

0.97 ± 0 1.52 ± 0 3.20 ± 1 2.21 ± 1

0.00 ± 0 0.25 ± 0 2.34 ± 0 1.69 ± 1

0.97 ± 0 1.34 ± 0 3.44 ±0 2.80 ± 1

2.53 ± 1 3.49 ± 0 5.59 ± 1 5.30 ± 1

C-2

<75 75–150 150–300 300–425

0.60 ± 0 0.32 ± 0 0.06 ± 1 0.31 ± 0

0.51 ± 0 0.25 ± 0 0.97 ± 1 0.73 ± 1

3.86 ± 0 3.94 ± 1 5.18 ± 1 4.83 ± 1

1.69 ± 1 1.21 ± 1 1.86 ± 1 2.45 ± 1

2.93 ± 1 2.55 ± 1 3.22 ± 1 3.70 ± 1

5.54 ± 1 5.60 ± 0 6.62 ± 0 6.39 ± 0

R-1

<75 75–150 150–300 300–425

0.54 ± 0 0.06 ± 0 0.98 ± 0 0.45 ± 0

0.80 ± 0 0.38 ± 0 0.20 ± 0 1.01 ± 1

1.36 ± 0 1.82 ± 0 3.27 ± 1 2.78 ± 0

0.25 ± 0 0.14 ± 0 1.64 ± 0 1.73 ± 0

1.41 ± 0 1.63 ± 0 2.96 ± 0 2.73 ± 0

4.90 ± 0 5.61 ± 0 6.77 ± 1 6.17 ± 0

R-2

<75 75–150 150–300 300–425

0.08 ± 0 0.41 ± 0 1.48 ± 1 1.52 ± 1

0.15 ± 0 0.37 ± 0 1.93 ± 0 1.85 ± 1

3.23 ± 0 3.54 ± 0 4.63 ± 1 4.76 ± 1

1.59 ± 0 1.67 ± 0 3.28 ± 0 3.11 ± 1

2.84 ± 0 2.93 ± 0 4.32 ± 1 4.16 ± 1

5.14 ± 0 5.51 ± 0 6.58 ± 1 6.74 ± 1

0.61 ± 1 0.58 ± 1 0.95 ± 1 1.27 ± 1

1.76 ± 0 2.42 ± 0 3.64 ± 0 3.55 ± 1

0.28 ± 0 0.34 ± 0 0.76 ± 0 0.83 ± 1

1.27 ± 0 1.50 ± 0 2.02 ± 1 1.95 ± 1

3.70 ± 0 4.22 ± 0 5.29 ± 0 5.15 ± 0

C-1

I-1

I-2

<75 75–150 150–300 300–425

<75 75–150 150–300 300–425 Pollution level:

1.21 ± 0 0.86 ± 0 0.15 ± 0 0.00 ± 0

1.71 ± 0 4.43 ± 1 1.55 ± 0 2.67 ± 1 0.61 ± 0 2.26 ±0 1.00 ± 0 1.94 ± 0 - heavily to extremely - slightly

Pb

Cr

Ni

Cd

1.51 ± 0 0.35 ± 0 1.84 ± 0 3.27 ± 1 1.96 ± 0 0.60 ± 0 1.89 ± 0 3.85 ± 0 1.16 ± 0 3.00 ± 0 0.39 ± 1 5.31 ± 0 1.28 ± 1 3.04 ± 1 0.42 ± 1 4.68 ± 1 - moderately to heavily - moderately - unpolluted

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

Note: FBio – effective bioavailable (exchangeable fraction), FP−Bio – potentially bioavaiable (sum of the reducible and oxidisable fractions), FNon−Bio – non-bioavailable (residual fraction).

I-2 I-1

327.1 ± 48.3 134.5 ± 11.2 83.5 ± 3.6 0.11 ± 0.03 0.08 ± 0.01 0.05 ± 0.02 39.8 ± 10.0 86.5 ± 45.1 18.1 ± 9.2 10.2 ± 2.9 46.0 ± 3.4 28.0 ± 1.8 0.2 ± 0.0 4.5 ± 0.2 55.9 ± 13.8 2.5 ± 1.8 5.2 ± 1.0 24.4 ± 7.0 85.2 ± 6.8 118.9 ± 19.2 22.3 ± 1.6 0.03 ± 0.00 0.06 ± 0.01 0.01 ± 0.00 3.2 ± 1.0 58.1 ± 11.3 9.5 ± 2.0 0.6 ± 0.1 30.8 ± 5.7 7.8 ± 0.9 0.1 ± 0.0 4.4 ± 0.4 20.0 ± 7.2 0.9 ± 0.3 4.6 ± 0.8 6.6 ± 2.5

R-2 C-1

247.6 ± 58.8 210.6 ± 51.2 46.5 ± 6.4 0.04 ± 0.02 0.06 ± 0.03 0.01 ± 0.00 46.5 ± 6.4 71. ± 23.4 12. ± 3.1 1.0 ± 0.4 18.3 ± 4.0 12.1 ± 1.9 0.2 ± 0.1 4.8 ± 2.3 20.8 ± 10.4 1.4 ± 0.8 4.1 ± 2.0 7.0 ± 3.9

I-1

I-2

671.9 ± 15.8 389.6 ± 6.1 107.8 ± 6.8 0.55 ± 0.36 0.24 ± 0.03 0.05 ± 0.00 76.5 ± 13.9 178.9 ± 18.6 41.1 ± 1.3 28.3 ± 1.6 153.5 ± 9.1 48.8 ± 3.4 0.6 ± 0.0 13.3 ± 0.6 62.0 ± 13.2 3.9 ± 0.4 15.3 ± 1.4 27.0 ± 5.0 Ni

ð16Þ

Cr

CR ¼ LADD  SF

ð15Þ

Pb

  C  EF IngRchild  EDchild IngRadult  EDadult  þ AT  PEF BW child BW adult

Cu

LADD ¼

FE−Bio FP−Bio FNon−Bio FE−Bio FP−Bio FNon−Bio FE−Bio FP−Bio FNon−Bio FE−Bio FP−Bio FNon−Bio FE−Bio FP−Bio FNon−Bio FE−Bio FP−Bio FNon−Bio

where HQ iing, HQ iinh and HQ idermal are the hazard quotients for ingestion, inhalation and dermal contact of the ith metal, respectively; Diing, Diinh and Didermal are the daily intake of the ith metal via three exposure pathways; RfDiing, RfDiinh and RfDidermal are the specific reference doses of ith metal for ingestion, inhalation and dermal contact, respectively. The RfD value for metals is given in Table S2 in the Supplementary Information. The cancer risk (CR), which quantifies the likelihood to cause cancer over the lifetime as a result of exposure to carcinogenic metals was calculated considering the lifetime average daily exposure dose (LADD) of Cr, Ni and Cd using Eqs. (15) and (16) (USEPA, 1989). The parameters used in Eq. (15) is the same as in Eqs. (10) and (11). The slope factors (SF) for metals are given in Table S2 in Supplementary Information. The acceptable precautionary criterion for cancer risk is 1 × 10−6 (Shi et al., 2011).

Zn

n

75–150 μm

n

R-2

ð14Þ

n

R-1

HI ¼ ∑i¼1 HQ ing þ ∑i¼1 HQ inh þ ∑i¼1 HQ dermal

RfDdermal

C-2

Didermal

C-1

; HQ idermal ¼

ð13Þ

i RfDinh

0.45–75 μm

Diinh

Concentration in mg kg−1

; HQ iinh ¼

i

i RfDing

Geochemical fractions

Diing

HQ iing ¼

Elements

The potential health impacts of metals were then characterised as non-cancer and cancer health risk, based on the exposure assessment. The potential non-cancer risk can be evaluated using the Hazard Quotient (HQ) and the Hazard index (HI). Hazard Quotient is the ratio of the daily intake of a particular metal to its specific reference dose (RfD) (Ma et al., 2016; USEPA, 1989). Hazard index is equal to the sum of the HQs, which evaluates the total health risk posed by multiple metals via different exposure pathways (USEPA, 1989). HI N 1 indicates the likelihood to cause non-cancer health impacts, whereas HI b 1 indicates lower or no risk of noncancer impacts (USEPA, 1989). HQ and HI were separately calculated for an adult and child using Eqs. (13) and (14), considering the values given in Table 2.

C-2

ð12Þ

Cd

SA  AF  ABS  EF  ED  CF BW  AT

Table 5 Geochemical distribution of metals based on the bioavailability characteristics for 0.45–75 μm and 75–150 μm size ranges of road dust (mean ± SD in mg kg−1).

Ddermal ¼ C 

144.8 ± 17.2 92.6 ± 19.2 77.5 ± 5.1 0.05 ± 0.01 0.04 ± 0.00 0.03 ± 0.01 17.8 ± 2.3 79.2 ± 15.4 21.1 ± 1.3 12.6 ± 8.8 71.4 ± 8.4 44.6 ± 3.2 0.3 ± 0.0 5.3 ± 0.5 63.7 ± 15.8 1.2 ± 0.1 5.4 ± 0.9 22.7 ± 4.3

ð11Þ

R-1

InhR  EF  ED PEF  BW  AT

226.4 ± 71.5 212.3 ± 98.1 42.5 ± 7.5 0.03 ± 0.00 0.04 ± 0.01 0.02 ± 0.02 42.5 ± 7.5 56.6 ± 27.4 9.8 ± 1.6 0.8 ± 0.4 21.3 ± 16.9 18.1 ± 22.5 0.1 ± 0.0 4.1 ± 0.5 31.8 ± 20.0 1.0 ± 0.3 4.3 ± 1.9 11.7 ± 8.1

Dinh ¼ C 

601.3 ± 80.8 282.3 ± 22.0 103.9 ± 8.2 0.30 ± 0.20 0.14 ± 0.01 0.05 ± 0.00 69.1 ± 46.9 1040.1 ± 621.8 1014.3 ± 395.5 16.3 ± 1.9 86.2 ± 4.4 22.9 ± 0.8 0.6 ± 0.1 12.7 ± 0.7 202. ± 32.1 4.7 ± 0.9 18.1 ± 1.4 92. ± 14.9

ð10Þ

396.1 ± 58.9 190.3 ± 16.4 109.4 ± 6.9 0.17 ± 0.01 0.08 ± 0.01 0.01 ± 0.00 53.9 ± 22.8 76.5 ± 28.3 20.9 ± 11.4 12.2 ± 1.0 82.3 ± 8.2 38.8 ± 1.4 0.3 ± 0.1 6.9 ± 0.4 56.0 ± 15.1 2.6 ± 0.2 7.5 ± 1.0 27.5 ± 6.4

IngR  EF  ED  CF BW  AT

107.5 ± 14.2 151.4 ± 12.3 26.2 ± 3.5 0.04 ± 0.01 0.08 ± 0.01 0.01 ± 0.00 7.3 ± 1.3 80.1 ± 6.3 13.1 ± 4.5 0.8 ± 0.2 37.4 ± 3.4 9.8 ± 1.1 0.1 ± 0.0 6.1 ± 0.4 18.7 ± 1.8 1.1 ± 0.1 4.8 ± 0.6 6.7 ± 0.9

Ding ¼ C 

486.8 ± 24.7 188.3 ± 9.4 66.1 ± 2.8 0.39 ± 0.38 0.14 ± 0.02 0.06 ± 0.02 67.1 ± 7.3 183.3 ± 28.0 36.9 ± 7.0 32.0 ± 7.3 96.5 ± 10.0 28.9 ± 6.5 0.4 ± 0.0 7.5 ± 0.1 55.5 ± 6.7 4.2 ± 2.6 9.2 ± 2.0 22.1 ± 2.8

inhalation of vehicular exhaust or airborne particles and dermal contact with dust particles (Ferreira-Baptista and De Miguel, 2005; Megido et al., 2017; Shi et al., 2011). Accordingly, the daily intake of metals (mg kg−1 day−1) by adults and children via those three exposure pathways (i.e. Ding, Dinh and Ddermal) were determined using Eqs. (10)-(12) (USEPA, 1989, 2001). The sum of the exchangeable, reducible and oxidisable phase metal concentration was used in the risk evaluation (i. e. C = CiBio + CiP−Bio), considering that metals in those three geochemical phases are potentially available for exposure to humans. Metals in residual fraction are non-bioavailable in nature due to their form of attachment. The description of the parameters along with the values used in Eqs. (10)–(12) is provided in Table 2.

551.6 ± 71.2 228.4 ± 36.3 104.0 ± 6.3 0.15 ± 0.03 0.10 ± 0.01 0.07 ± 0.02 85.9 ± 15.0 307.2 ± 92.4 54.7 ± 26.7 22.6 ± 6.5 77.7 ± 13.0 22.3 ± 3.5 0.5 ± 0.1 11.2 ± 0.7 284.9 ± 56.2 4.3 ± 1.2 14.8 ± 4.8 119.0 ± 19.2

A. Jayarathne et al. / Science of the Total Environment xxx (2018) xxx–xxx

203.3 ± 27.6 143.8 ± 21.5 90.6 ± 15.3 0.08 ± 0.01 0.07 ± 0.00 0.03 ± 01 30.5 ± 12.6 102. ± 20.9 27.3 ± 6.1 10.3 ± 3.1 107.8. ± 14.5 58.8 ± 13.0 0.3 ± 0.0 7.6. ± 0.7 57. ± 17.6 2.2 ± 0.4 8.4 ± 1.3 23.9 ± 6.7

6

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

A. Jayarathne et al. / Science of the Total Environment xxx (2018) xxx–xxx

3.1. Contamination levels of metals in road dust The average metal concentrations of size-fractionated road dust corresponding to each study site are given in Table S3 in the Supplementary Information. It can be noted that in most study sites and particle size ranges, metal concentrations, except Pb and Cd are higher than the soil background values in Australia (ANZECC-NHMRC, 1992; DEC, 2010), implying that road dust is contaminated by metals derived from anthropogenic rather than geogenic sources. The enrichment factor (EF) for Zn, Cu, Pb, Cr, Ni and Cd associated with different particle size ranges collected during four different dry periods (i.e. the mean value of the homologous subsamples at a specific site) were calculated to identify the degree of metal contamination for different land uses. As evident from Table 3 and EF values presented in Table 1, Zn and Cu associated with different size ranges of road dust show significant to very high enrichment at all study sites, whilst an extreme enrichment of Cu was evident at I-2 site. Pb in different size ranges at site C-1 and site I-2 is moderately enriched, but at other sites, it shows insignificant enrichment. The very high enrichment of size-fractionated Cr was noted at I-2 site, whereas it was moderate to significant at other study sites. Ni is significantly enriched at I-2 site, while it was moderate at C-1 and I-1 sites. Cd enrichment levels for different size ranges of road dust were at a minimum for all study sites. Based on these observations, commercial site C-1 and industrial site I-2 can be considered as polluted sites. As evident in Table S3 in the Supplementary Information, the average metal concentrations in each size-fractionated road dust in C-1 and I-2 sites are also considerably high compared to the other sites. The high pollution levels and enrichments at these sites are attributed to the presence of metal related light industries (such as aluminium and steel fabrication) and commercial activities such as vehicle servicing (Fig. 1). On the other hand, due to the high traffic volume reported at these study sites (Fig. 1), pollutant sources common to vehicular traffic related activities such as wear of brake, tyre and vehicle components can significantly influence the build-up of high metal loads (Gunawardana et al., 2012; Liu et al., 2016; Mummullage et al., 2014). In summary, the mean EF values for metals at all study sites show the following decreasing trend: Cu N Zn N Cr N Ni N Pb N Cd. To further understand the degree of metal pollution at each site, the Igeo index for metals was calculated based on the different particle size ranges (Table 4). As evident from Table 4, the contamination levels vary depending on the particle sizes of road dust. The Igeo for most of the metals associated with the b150 μm size ranges is generally high compared to the that of the N150 μm size ranges. Based on the criteria for Igeo given in Table 1, the size fractionated Cu at I-2 site vary from ‘moderately’ to ‘heavily to extremely polluted’, whereas Cr belongs to ‘moderately polluted’ category. Zn associated with b150 μm of road dust at most of the study sites fall into the pollution level categories of ‘slightly polluted’ or ‘moderately polluted’. Furthermore, Igeo classified Pb, Cd and Ni as ‘unpolluted’ for all sites, except for Ni at I-2 site. These results confirmed that the road dust in industrial site I-2 was highly polluted by metals such as Zn, Cu and Cr, whereas the commercial site C-1 is slightly to moderately polluted by Zn and Cu. 3.2. Modified ecological risk assessment based on the bioavailability of metals The bioavailability characteristics of individual metals based on their distribution among the geochemical fractions for different particle size ranges were analysed. The average metal concentrations in the homologous subsamples for the 0.45–75 μm and 75–150 μm size ranges are given in Table 5, whereas the corresponding concentrations for the 150–300 μm and 300–425 μm size ranges are given in

the Supplementary Information, Table S4. As evident from Table 5 and Table S4, except for R-2 which showed more affinity towards the potentially bioavailable fraction, irrespective of particle size ranges, Zn is associated with the effective bioavailable fraction at all study sites, suggesting that it could cause significant adverse effects as a readily available metal. Cu and Pb are generally dominant in the potentially bioavailable fraction. Compared to the non-bioavailable fraction, the affinities of Ni and Cr for the effective and potentially bioavailable fractions are generally low. ANOVA (analysis of variance) analysis was employed to test the statistical difference between the mean concentrations of metals in different particle size ranges. The ANOVA results are given in Table S5. It is evident that there were no significant differences in the metal concentrations between the 0.45–75 μm and 75–150 μm particle size ranges, and 150–300 μm and 300–425 μm at 95% confidence level (P N 0.05). However, it was noted that the b150 μm size ranges for all geochemical fractions of Zn and the potentially bioavailable fraction of Cd, Pb, Cr and Ni are statistically different from the N150 μm size ranges in terms of their mean concentrations (P b 0.05) (Table S5). This emphasises the fact that the differences in the metal adsorption capacities of road dust are based on their particle sizes. The modified ecological risk index (RIm) was then calculated from the effective and potentially bioavailable metal concentrations. According to Fig. 2 and RI categories provided in Table 1, the RIm for the road dust indicates low risks from metals for all study sites, except at I-2, where the range varies from low to considerable risk. As evident from Table S6, the highest RIm at I-2 site was observed for the 0.45–75 μm size range. Therefore, it is essential to deploy appropriate solids removal practices targeting fine particles in order to minimise the potential environmental risk posed by metals associated with road dust. 3.3. Modified human health risk assessment Human exposure to metals in road dust via different exposure scenarios was determined considering the bioavailable metal fractions. Accordingly, the HQ for ingestion, inhalation and dermal contact of metals at different study sites were calculated to quantify the noncancer risk to children and adults. The HQ graphs for children and adults at different study sites are shown in Figs. 3 and 4, respectively. As shown in Figs. 3 and 4, the hazard index (HI = ΣHQ) for a given metal is lower than the safe level of 1, indicating that there is no potential for noncancer risk at the study sites. However, it should be noted that the potential of multiple metals being able to cause toxic effects is significantly higher than that of a single metal, predominantly at site C-1 (HI = 1.19) and site I-2 (HI = 1.13). 120

Considerable 100

Modified Eco-Risk Index (RIm)

3. Results and discussion

7

80

Moderate

60

40

Low

20

0 C-1

C-2

R-1

R-2

I-1

I-2

Study sites Fig. 2. Potential ecological risk from metals at different study sites.

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

8

A. Jayarathne et al. / Science of the Total Environment xxx (2018) xxx–xxx

C-1: Child

C-2: Child HQingestion HQinhalation

Cd

HQdermal

Ni Cr Pb Cu Zn

0.00

0.05

0.10

0.15 0.90

0.95

0.00

0.02

0.04

0.06

0.08

0.10

0.12

HQ value

R-1: Child

R-2: Child

Cd Ni Cr Pb Cu Zn

0.00

0.04

0.08

0.51

0.54

0.00

0.02

0.04

0.18

0.20

HQ value

I-1: Child

I-2: Child

Cd Ni Cr Pb Cu Zn

0.000

0.050

0.100

0.350

0.375

0.0

0.1

0.2

0.3

0.4

0.5

0.6

HQ value Fig. 3. Hazard Quotient (HQ) of metals in relation to children at different study sites.

Among the three different exposure pathways, the HQ for ingestion was found to be the highest, followed by dermal contact, while the HQ for inhalation of dust can be considered as negligible (Figs. 3 and 4). Accordingly, incidental ingestion is the main exposure pathway for metals in road dust that can cause the highest level of risk to human health. This result is consistent with previous research studies. For example, Li et al. (2017) reported that the contribution of HQIngestion to hazard index (HI) was the highest compared to HQ for dermal contact and inhalation for both, children (70.4%) and adults (62.1%). Moreover, Ferreira-Baptista and De Miguel (2005), Keshavarzi et al. (2015) and Megido et al. (2017) also reported the significance of ingestion of road dust in terms of

non-cancer health risk. As evident from Figs. 3 and 4, children are more vulnerable to non-cancer health effects compared to adults. This is possibly due to their low tolerance levels and unintentional exposure to road dust while consuming food or playing near roads (Acosta et al., 2009). Among the analysed metals, non-cancer health risk posed by Pb was the highest at all study sites for children and adults, while the other metals were in the decreasing order of Cu N Cr N Zn N Ni N Cd (Figs. 3 and 4). A similar risk characteristic for Pb has been reported in other studies (Li et al., 2017; Shi et al., 2011). Although the use of leaded fuel in automobiles is no longer allowed in Australia, it has been noted that the Pb is relatively

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

A. Jayarathne et al. / Science of the Total Environment xxx (2018) xxx–xxx

C-1: Adult

9

C-2: Adult HQingestion HQinhalation HQdermal

Cd Ni Cr Pb Cu Zn

0.000

0.005

0.010

0.015

0.090

0.100

0.110 0.000

0.003

0.006

0.009

0.012

0.015

HQ value

R-1: Adult

R-2: Adult

Cd Ni Cr Pb Cu Zn

0.0000

0.0050

0.0100

0.0550

0.0575

0.000

0.002

0.004

0.006

0.020

0.021

0.022

HQ value

I-1: Adult

I-2: Adult

Cd Ni Cr Pb Cu Zn

0.000

0.005

0.010

0.040

0.041

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

HQ value

Fig. 4. Hazard Quotient (HQ) of metals in relation to adults at different study sites.

enriched in road dust compared to roadside soil (Al-Chalabi and Hawker, 2000; Jayarathne et al., 2017). This is primarily attributed to the dispersion of Pb contaminated soils and the wear of vehicle components. The evaluation of cancer risk (CR) for the lifetime daily exposure to carcinogenic metals, Cr, Ni and Cd is shown in Fig. S1 in the Supplementary Information. It can be noted that CR for Cr is higher than that for the other metals. At C-2, R-2, I-1 and I-2 sites, CR for Cr is above the threshold limit of 1 × 10−6, where the highest was reported at I-2 (1.24 × 10−5). These observations confirm that even though the effective and potentially bioavailable fractions of Cr in road dust are relatively low, the possibility of cancer risk from Cr exists predominantly in industrial areas. However, in terms of Ni and Cd, the CR

levels are within the range of 10−7–10−9, indicating that there is no cancer risk. In order to evaluate the influence of size ranges of road dust on human health, the HI and CR indices were assessed for multiple metals at different study sites. According to the data given in Table 6, the HI in relation to children and adults are b1 for all size ranges, indicating that the individual size ranges of road dust would not cause non-cancer risk. However, the HI for children, the size ranges collectively is either exceeding (C-1 and I-2 sites) or close (R-1 and I-1) to the threshold limit of 1. In relation to the cancer effects, the CR index decreases with increasing particle sizes at most sites. Notably, at I-1, I-2, C-2 and R-2 sites, the CR indices for individual size ranges exceed the threshold limit, signifying a potential cancer risk in terms of different particle sizes of road dust.

Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098

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A. Jayarathne et al. / Science of the Total Environment xxx (2018) xxx–xxx

References

Table 6 Non-cancer and cancer risk indices for different particle size ranges. C-1

C-2

R-1

R-2

I-1

I-2

0.08 0.08 0.04 0.04

0.28 0.19 0.08 0.10

0.11 0.08 0.05 0.04

0.24 0.15 0.09 0.09

0.31 0.30 0.19 0.33

Modified HI index - Adult 0.45–75 0.05 0.01 75–150 0.04 0.01 150–300 0.02 0.00 300–425 0.03 0.00

0.03 0.02 0.01 0.01

0.01 0.01 0.01 0.00

0.03 0.02 0.01 0.01

0.03 0.03 0.02 0.04

Modified CR index 0.45–75 3.59e–07 75–150 2.06e-07 150–300 6.12e-08 300–425 8.61e-08

2.04e-07 1.43e-07 6.95e-08 8.45e-08

1.58e-06 1.14e-06 4.78e-07 5.40e-07

1.86e-06 1.22e-06 8.22e-07 1.14e-06

3.43e-06 3.02e-06 2.03e-06 4.29e-06

Modified HI index - Child 0.45–75 0.46 75–150 0.33 150–300 0.17 300–425 0.26

1.27e-06 1.07e-06 6.30e-07 7.77e-07

4. Conclusions This study evaluated the ecological and human health risks posed by six metals commonly present in urban road dust based on their geochemical fractionation. The approach adopted provides new insights into the risk assessment of metals based on their potential bioavailability characteristics. The use of modified risk indices would be valuable to decision makers in evaluating environmental risk, regulating stormwater harvesting and managing the safe use of stormwater for recreational use. As an initial proof-of-concept, only a relatively small data set was considered in the current work. However, further investigations are recommended to accurately quantify the risks posed by metals, particularly the human health impacts. The assessment of both, EF and Igeo indices indicated that the study sites, C-1 and I-2 are highly polluted with metals such as Zn and Cu, signifying contributions from anthropogenic activities. Even though the C-1 site is highly polluted, based on the proposed modified ecological risk index (RIm), the road dust in C-1 poses low ecological risk. According to the modified health risk indices determined, although some metals are highly enriched in road dust, the non-cancer risks from metals were found to be at a safe level. However, the cancer risk index for individual size ranges of road dust exceeded the cancer threshold limit, predominantly in some industrial and commercial sites, suggesting that there is potential carcinogenic health risk in the study area. However, further work is required to confirm this conclusion. The study outcomes highlight the importance of accounting for the influence of different particle sizes of solids and the land use characteristics in risk management strategies to minimise the risk posed by metals in urban areas.

Acknowledgements The first author would like to express her appreciation for the scholarship provided by the Queensland University of Technology to undertake this postgraduate research study. We also thank the Central Analytical Research Facility (CARF) operated by the Institute of Future Environments (QUT) where the data reported in this paper were obtained. Access to CARF is supported by generous funding from the Science and Engineering Faculty (QUT). This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2018.04.098.

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Please cite this article as: Jayarathne, A., et al., Assessment of ecological and human health risks of metals in urban road dust based on geochemical fractionation and potential bioavailability, Sci Total Environ (2018), https://doi.org/10.1016/j.scitotenv.2018.04.098