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Composition of selected heavy metals in road dust from Kuala Lumpur city centre

Abstract

This study was carried out in order to determine the concentration of heavy metals, e.g., lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn), iron (Fe), manganese (Mn), nickel (Ni) and chromium (Cr) in road dust in Kuala Lumpur’s city centre. Samples were collected from four sampling locations, each of which had four sampling points and three replications. Heavy metals from different fractions of particles separated by different diameter sizes: d < 63 μm (Fraction A), 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C) were analyzed using inductively coupled plasma mass spectrometry. The results from this study showed that concentration of heavy metals was dominated by the smallest particle size: <63 μm and that Fe was the most abundant heavy metal overall, followed by Cu > Mn > Zn > Pb > Ni > Cr > Cd. The fact that Cd had the highest enrichment factor value (EF) for all particle sizes indicates that anthropogenic activities contributed to the presence of this metal. There was also a higher EF value for heavy metals in small particle (Fraction A), compared to Fraction B and C, which suggests that fine particles were being produced through anthropogenic activities. Cluster analysis and principal component analysis demonstrated the likelihood of the heavy metals detected in the road dust, originating from road traffic and industrial activities.

Introduction

Urban areas throughout the world are experiencing rapid change as a result of urbanization and the accelerated development of the social economy (Oh et al. 2011; Latif and Saleh 2012). This in turn has led to a dramatic growth in both industrial and road traffic activity; the main causes of serious air pollution in urban areas. Urban surfaces are covered with a deposit originating from more or less remote sources through atmospheric transport as well as from local human activity (Christoforidis and Stamatis 2009). Motor vehicles are the principle source of urban surface pollution, often through the accumulation of related pollutants in the form of road dust on the roadside as result of exhaust emissions and tyre wear (Apeagyei et al. 2011).

Road dust, originating from the interaction of solid, liquid and gaseous materials, derived from different sources, for example, motor vehicles, significantly contributes to the level of pollution in urban environments (Lu et al. 2009; Faiz et al. 2009). The formation and composition of road dust alter depending on climate, the degree of human activity, as well as the composition of soil and rocks in the surrounding area (Lu et al. 2009; Karmacharya and Shakya 2012). A number of previous studies have indicated that heavy metals are the primary pollutants in road dust, in addition to organic materials (Lu et al. 2009; Christoforidis and Stamatis 2009; Zheng et al. 2010; Duong and Lee 2011). Heavy metals may accumulate in road dust through sedimentation, impaction and interception. The accumulation of heavy metals can also result from industrial discharge, the use of oil lubricants, automobile parts and corroding building-material asphalts, road paint and concrete (Li et al. 2001; Karmacharya and Shakya 2012). The environmental and health effects of toxic heavy metals in road dust have been shown to be dependent on their mobility and existence (Banerjee 2003; Duong and Lee 2009).

Cities in tropical urban areas such as Kuala Lumpur have been exposed to various types of dust as a result of traffic emissions, industrial activity, biomass burning, construction activities materials as well as from rapid degradation, resuspension and the evaporation of soil and road dust within the city areas (Abdullah et al. 2012; Sara et al. 2013). The high number of motor vehicles within Kuala Lumpur’s city centre (with traffic volume at about 2,90,772 vehicles in 16 h of traffic and 28,565 vehicles during the peak hour) (Ministry of Works 2010) contributes to a high level of particles and road dust containing a high amount of heavy metals and organic substances within Kuala Lumpur’s city centre (Rahman et al. 2011; Wahid et al. 2013). With respect to motor vehicles, two-stroke motorcycles, busses and heavy vehicles are the major sources of particulate matter and organic carbon (Faiz et al. 1996). Rapid development of the city centre leads to the resuspension and distribution of road dust which is usually influenced by blocks of buildings along the roadsides. Other types of sources (e.g. industrial activity, construction and biomass burning) in Kuala Lumpur are predominantly influenced by wind direction and seasonal activities (Azmi et al. 2010).

Yearly increases in the number of private motor vehicles on the roads in Kuala Lumpur’s city centre (around 8 % each year) (Mohamad and Kiggundu 2007), along with a low rate of enforcement on vehicle emissions is expected to contribute to the high level of toxic materials, including heavy metals, found in road dust within the city centre. Thus, the main objectives of this study were to determine the concentrations of selected heavy metals (Pb, Zn, Cd, Fe, Mn, Ni, Cr and Cu) in road dust at different stations (with different backgrounds) around Kuala Lumpur’s city centre and to compare these concentrations at different diameter sizes: d < 63 μm (Fraction A), 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C). The size fractions were chosen to represent the different dimensions of road dust particles which not only originate from various sources but also have different impacts on human health. The size fractions also consider the production of a small amount of road dust as a result of daily sweeping and cleaning activities. The smallest fraction of dust (Fraction A) is in fact considered the biggest health risk as it absorbs more pollutants compared to larger particles. The sources of heavy metals in road dust were determined through the use of cluster analysis (CA) and principle component analysis (PCA).

Materials and methods

Sampling sites

Road dust was collected from Kuala Lumpur’s city centre. Kuala Lumpur is both the federal capital and the most populous city in Malaysia with a population of 1.6 million. It is situated in the west of the Malaysian Peninsula. The city covers an area of 243 km2 and is among the fastest growing metropolitan regions in the country in terms of both population and economic growth. Kuala Lumpur has a wet tropical climate with a high level of rainfall and humidity throughout the year. The average annual temperature is 26.6 °C and the annual precipitation average is 2,366.2 mm (Malaysian Meteorological Department 2011). The samples for this study were collected from the roadway of several sampling stations with different backgrounds (Fig. 1), namely: Tunku Abdul Rahman Road (TAR), Bukit Bintang (BB), Tasik Perdana Park (TPP) and Kampung Baru (KB). Tunku Abdul Rahman Road (TAR) is in the most congested area in Kuala Lumpur due to being located in its commercial centre in the city centre. Bukit Bintang (BB) is located in another commercial area with heavy traffic. Kampung Baru (KB) is a traditional Malay village in the middle of Kuala Lumpur. It is situated in a residential area surrounded by busy motorways which experience heavy traffic. TPP is a recreational park with lake gardens, located in the centre of Kuala Lumpur. There are no major industrial sources around this study area and due to its strategic location with different attractive monuments and museums close by, this park is usually busy with tourists, particularly at the weekend. At each sampling stations, four sampling points were chosen for dust replication. The selection of sampling points was based on the availability of road dust in the sampling locations and the differing homogeneity of traffic along the roadside. The longitude and latitude of all sampling stations are summarized in Table 1.

Fig. 1
figure1

Location of study area and sampling sites (Inset shows location of Kuala Lumpur in the Malaysian Peninsular)

Table 1 Description of the sampling area

Dust sampling

Dust samples were collected using a soft paintbrush. They were obtained from the pavement on both sides of the roads in the sampling stations. All dust samples collected were stored in sealed polyethylene bags which were labeled and then transported to the laboratory. Any road dust with a diameter (d) > 2,000 μm was removed from the sample using a stainless steel sieve with a mesh diameter of 2,000 μm (Duong and Lee 2009). The road dust samples were then categorized into three groups based on particle size: d < 63 μm (Fraction A), 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C); this was achieved through the use of a laboratory test sieve. Three replicates of the dust samples (n = 3) were taken at each sampling site.

Sample digestion and heavy metal analysis

Each road dust sample (1 g) was dissolved in a mixture of 16 mL nitric and 4 mL perchloric acid (v/v, 16:4) on a hot plate at 85 °C for 1 h. Each sample solution was filtered using Whatman glass microfiber filter papers with a pore size of 0.45 μm and 47 mm diameter, and filtration apparatus linked to a vacuum pump. The filtered solution was diluted to 100 mL with deionised water in a volumetric flask and kept at 4 °C in a polyethylene bottle until analysis. The heavy metal concentrations in each solution were determined through the use of inductively coupled plasma mass spectrometry (ICP-MS, PerkinElmer ELAN 9000). The standard solution for heavy metals was prepared by diluting 1,000 mg/L stock solution of Pb, Cd, Cu, Zn, Fe, Mn, Ni and Cr with ultra pure water. The percentage recoveries of these elements ranged from 63 to 110 %, which are high percent recoveries demonstrating the accuracy of the methods employed.

Quality control

Quality control was practiced throughout the analysis to avoid any interference and to minimize the likelihood of error. Powderless gloves were used while performing all stages of the experiment, most notably when handling the road dust. Furthermore, all sample analysis was conducted in a fume cupboard. All the polyethylene bottles and glassware utilized for heavy metal analysis were pre-cleaned by being soaked over night and treated with nitric acid (20 %) before being rinsed with deionised water. Furthermore, all instruments involved in this analysis were calibrated before use. The instrumental detection limits were determined as 0.04 μg g−1 for Pb, 0.03 μg g−1 for Zn, 0.09 μg g−1 for Cd, 0.03 μg g−1 for Fe, 0.02 μg g−1 for Cr, 0.04 μg g−1 for Ni, 0.007 μg g−1 for Mn and 0.02 μg g−1 for Cu. Each solution was analyzed three times and the relative standard deviation (RSD) of the repeated analyses for each heavy metal was shown as being below 5 %. The difference between the heavy metal concentrations of the duplicate samplings was also under 5 %.

Statistical analysis

All statistical calculations were analyzed using the Statistical Package for Social Sciences (SPSS Version 20.0). The statistical significance of correlation among the measured heavy metals was analyzed using the one-way variance (ANOVA) test with a 95 % level of confidence after the data was found to be in normal distribution.

CA and PCA were performed using data from all fractions and XLSTAT 2012 software. These two methods are the most common multivariate statistical methods used in environmental studies (Tokalioğlu and Kartal 2006; Lu et al. 2010). In this study, CA analysis was undertaken so as to classify the elements which originate from different sources yet have similar characteristics and chemical properties (Yongming et al. 2006), while PCA analysis was performed to determine the contribution of various factors that can be used to identify the sources of the pollution (Banerjee 2003; Al-Khashman 2007).

Enrichment factor

The enrichment factor (EF) of each element in the samples studied was based on the standardization of the measured element against a reference element. The EF calculation is used to identify which metals derive from human activity and which from crustal elements, as well as the degree of the anthropogenic contribution (Yongming et al. 2006). The EF calculation is expressed below:

$${\text{EF }} = \frac{\left[ {C_{x} / \, C_{\text{ref}} } \right]_{\text{Sample}}}{\left[ {C_{x} / \, C_{\text{ref}} } \right]_{\text{Background}}}$$

where C x is the concentration of the element of interest and C ref is the concentration of the reference element for normalization (Lu et al. 2009; Taylor and McLennan 1985). In this study, Fe was used as the C ref for both the sample and background concentrations. Background data on all elements was taken from Taylor and McLennan (1985). Thus, if the EF value approached 1, it could be determined that the element was of crustal origin. EF <2 shows the deficiency to be of minimal enrichment, EF = 2–5 is moderate enrichment, EF = 5–20 is significant enrichment, while EF = 20–40 demonstrates an extremely high enrichment (Yongming et al. 2006; Lu et al. 2009). However, the explanation of the EF value can differ depending on the composition of a crustal element which does not necessarily remain static from one location to another due to the weathering fraction being variable (Joshi et al. 2009).

Results and discussion

Heavy metals in street dust

Overall concentrations of heavy metals in road dust are shown in Table 2. The concentration of each heavy metal determined was recorded at the highest concentration in the particle with the smallest particle size (d < 63 μm, Fraction A) followed by the particle with a diameter size: 63 < d < 125 μm (Fraction B) and 125 < d < 250 μm (Fraction C). The mean concentration of heavy metals in road dust was found to be dominated by Fe followed by Cu > Mn > Zn > Pb > Ni > Cr > Cd—this was the case for size fractions from all the sampling stations used. The concentration of Fe ranged between 3,757 and 19,545 μg g−1 with the highest concentration recorded in the particles with a diameter size, d < 63 μm (Fraction A) collected from TAR and the lowest concentration recorded in the particles with a diameter size: 125 < d < 250 μm (Fraction C) collected from BB. The lowest concentration determined among the selected heavy metals was Cd with a concentration range between 0.1 and 13.7 μg g−1. Almost all heavy metals, with the exception of Cu and Cd, were recorded at the highest concentrations in small particles (Fraction A) at the TAR station and at the lowest concentration at TPP. There were significant differences (p < 0.05) between almost all of the heavy metals (Cu, Zn, Ni, Cr, Cd) recorded at the different stations, particularly in relation to smaller particle size, d < 63 μm (Fraction A).

Table 2 Average and range concentration of heavy metals in road dust (μg g−1) for particle in different fractions

The dominance of heavy metal concentrations in the smaller particle size road dust has previously been recorded by several researchers (Charlesworth and Lees 1999; McKenzie et al. 2008; Duong and Lee 2011; Karmacharya and Shakya 2012). According to McKenzie et al. (2008) and Acosta et al. (2009), heavy metals tend to accumulate in fine particles mainly because of high surface areas and negative charges. Moreover, small particle road dust was found to consist of a higher amount of organic and clay mineral components, both of which are able to absorb metals easily (Beckwith et al. 1986; Duong and Lee 2011). Small-sized particles were also emitted from vehicle exhausts as a result of engine combustion. These would then float in the air and finally fall to the ground and accumulate as road dust along roadsides (Tanner et al. 2008).

A high Fe concentration, particularly for Fraction A, with a range between 11,186 and 19,545 μg g−1 recorded at TAR, 9,923 and 19,051 μg g−1 at BB, 12,841 and 17,459 μg g−1 at KB, and 5,273 and 10,811 μg g−1 at TPP sampling locations can be explained by the influence of crustal elements and soil-blown dust. According to Al-Khashman (2004) and Han et al. (2007), Fe usually originates from crustal sources and soil. The crustal material itself may originate from motor vehicles use outside the city centre, dust from unpaved roads along with dust brought in by wind from the surrounding areas—all of which accumulate as road dust. Moreover, Fe in road dust can also originate from anthropogenic activities, such as the use of vehicle brake pads which are constantly utilized to reduce vehicle acceleration in heavy traffic along with industrial activity (Al-Khashman 2007; Apeagyei et al. 2011). A high concentration of Zn (ranging between 58.4 and 617.0 μg g−1) and Cu (ranging between 4.3 and 317 μg g−1) particularly in particles <63 μm, as recorded in this study, may be due to a high level of motor vehicular pollution. According to Addo et al. (2012), the presence of Zn originates from its use as a galvanizing agent in vehicles while Cu is derived from the corrosion of metallic parts. Zn and Cu in road dust also can derive from tyre wear and the level of Cu present in diesel (Contini et al. 2012). The occurrence of Cu and Zn in road dust has been used as an indicator of pollution, particularly from car components and lubricants (Arslan 2001; Al-Khashman 2004; Rashed 2008; Lu et al. 2009).

Mn and Pb were also recorded at high concentrations in the road dust with a range between 92.1 and 497.7 μg g−1; and 7.1 and 422.8 μg g−1, respectively. This is predominantly a result of soil dust, industrial activity and long-accumulated dust from motor vehicles. According to Kabadayi and Cesur (2010), Mn is abundant in soil and Lu et al. (2009) also stated that the principle source of Mn and Pb in street dust is automotive emissions. Even though most vehicles now use unleaded petrol and gasoline, Pb in the leaded petrol previously used still remains in the environment, particularly at road sides which have been exposed to high levels of traffic (Jones et al. 1991; Akbar et al. 2006). Ahmed and Ishiga (2006) reported that Pb contamination of the environment can also derive from industrial activity, such as the manufacture of paint and batteries. From this study, Ni, Cu and Cd were all found to have a low-range concentration in road dust at 6.0–75.3 , 12.1–127.2 and 0.1–1.6 μg g−1, respectively, which demonstrates that these heavy metals were not produced by vehicle emissions at any significant level. The lowest levels or mass of Cd, when compared to the other elements focused on in this study, are consistent with the findings of Elik (2003) and Latif and Saleh (2012).

The Tunku Abdul Rahman Road (TAR) sampling area recorded the highest concentration of the five heavy metals (Zn, Mn, Pb, Ni and Cr) determined in this study. This result is most likely the result of high traffic congestion along the TAR road. Moreover, the sampling area’s location near a commercial centre with a shopping complex and rows of shops results in this area being busy with motor vehicles until midnight. Added to this, the TAR sampling area is surrounded by tall buildings, which in effect, trap suspended dust within the road sides. According to Duong and Lee (2011) an area with a high volume of traffic and tall buildings results in low air dispersion and the accumulation of heavy metals. In contrast, almost all heavy metals were recorded at a low concentration in the TPP sampling area. This was due to low traffic congestion and the existence of a very limited number of tall buildings to trap the pollutants.

The concentrations of heavy metals in the road dust in this study have been compared to those reported in previous studies undertaken in a number of other cities throughout the world (Table 3). The fact that Fe was found to have the highest concentration in this study was consistent with a study by Al-Khashman (2007) in a rural area where soil was found to have a high Fe content and another one by Al-Khashman (2013) in different areas of Ma’an, Jordan. Moreover, studies by Li et al. (2001), Duong and Lee (2011) and Al-Khashman (2013), which were all undertaken in urban areas, recorded Zn as having the highest concentration. This high Zn concentration was attributed to the use of tyres where Zn had been used as a vulcanization agent. Moreover, the Zn concentration in this study was found to be 2.5 times lower than that determined by Sezgin et al. (2003) while slightly higher than that determined Faiz et al. (2009). Both of their studies were undertaken in highway areas. The source of the Zn concentration in such locations was directly attributed to traffic activity. The Pb concentration in this study was nearly identical to the Pb concentration recorded by Al-Khashman (2013) in the urban area of Ma’an, Jordan, but far lower when compared to Christoforidis and Stamatis (2009) and Lu et al. (2010), whose studies were carried out in the cities of Kavala (Greece) and Baoji (China). The high Pb concentrations recorded in their studies were reportedly the result of leaded gasoline usage by motor vehicles.

Table 3 Heavy metals concentration (μg g−1) in road dust compared to other studies

Correlation matrix for heavy metals in street dust

The results of the Pearson correlation matrix for heavy metals in road dust (Fraction A, B and C) are shown in Table 4. All the heavy metals in the three fractions show positive correlations except for the correlation between Cd and Mn in Fraction B. A strong correlation between the heavy metals recorded suggests the possibility of these metals having originated from the same sources. For heavy metals in Fraction A (Table 4a), strong correlations (p < 0.01) are evident between Pb and Ni (r = 0.91), Pb and Cr (r = 0.83) and Ni and Cr (r = 0.85), while Cd recorded a good correlation (p < 0.01) between Cu, Zn and Fe. The relationships between Cu and Zn, Cu and Cr, Zn and Fe, Zn and Cr as well as Mn and Ni also show a good correlation at p < 0.01. There were also good correlations (p < 0.05) between Zn and Pb (r = 0.42), Cu and Fe (r = 0.42) and Fe and Ni [strong correlations (p < 0.01)].

Table 4 Correlation matrix for heavy metals concentration in road dust

Moreover, the influence of the particle size on the correlation between the heavy metals at (p < 0.01) is more obviously recorded in Fraction C (diameter size of 125 < d < 250 μm) as illustrated in Table 4c. For example, there were stronger positive correlations between Pb and Cr (r = 0.83) as well as Zn and Fe (r = 0.87) in Fraction C compared with Fraction B. And among the three fractions, Fraction C also shows that the relationship between Mn and Zn, and Fe and Cr were recorded as being stronger with the correlation coefficient, such that the r value was 0.76, 0.72 and 0.71, respectively. The correlation between Zn and Ni (r = 0.56), and Fe and Cr (r = 0.54) also recorded a stronger relationship in Fraction C.

Significant correlations between Zn and Cu, Pb, Fe, Mn and other metals suggest that these metals have two common sources, namely: motor vehicles and industrial activity (Yongming et al. 2006; Kabadayi and Cesur 2010). As determined by Manno et al. (2006), heavy metals such as Zn, Ni and Cu are highly abundant in urban areas and industrial sites. According to Amato et al. (2011), Zn, Ni, Cu and Cr can be derived from tyre and brake wear while Fe can be contributed by motor exhaust emissions and brake wear. The coagulation of small particles into coarse particles increases the mixture of heavy metals in the road dust and leads to a strong correlation between heavy metals, even in the particles with a diameter size of 125 < d < 250 μm (Fraction C).

Enrichment factor

The enrichment factor values for heavy metals in Fraction A, B and C are shown in Fig. 2. From the results obtained, it can be seen that the majority of the heavy metals had a higher EF value for particles with a diameter size, d < 63 μm (Fraction A) and that there was a minimal difference in EF values for each particle size apart from those for Cd. The EF values recorded for the heavy metals in all three fractions were: Cd > Pb > Zn > Cu > Cr > Ni > Mn > Fe. The highest EF value recorded for Cd was 19.8 for Fraction A (d < 63 μm) followed by 16.5 for Fraction B (63 < d < 125 μm) and 12.8 for Fraction A (125 < d < 250 μm). These results demonstrate that Cd originated predominantly as a result of anthropogenic activities, particularly in the case of the fine particle size. According to ATSDR (2012), Cd in the environment can be generated from mineral fertilizers, motor oil combustion and other products, such as pigments, batteries, metal coating cement and plastics. The higher concentration of Cd at TPP (Table 2) may indicate that mineral fertilizers are among the main sources of Cd in Kuala Lumpur. Other metals such as Pb, Cu, Zn, Ni and Cr were also noted as having the highest EF value for Fraction A which suggests that fine particles can be produced through anthropogenic activities. According to McKenzie et al. (2008), fine and very fine particles are mainly composed of non-crustal elements. According to Shi et al. (2008), the ability of particles to absorb metals is determined by a few factors; particularly surface properties and particle size. Fe, Mn, Ni and Cr (for all particle sizes) had an EF value in the range of 1–3, which suggests that these heavy metals were derived from crustal contribution and minimal anthropogenic influences. As the aforementioned metals occur naturally in soil, they can also be contributed by other metals (Yongming et al. 2006; Faiz et al. 2009). Moreover, the significant enrichment values given by Pb, Cu and Zn strongly suggest that these elements are derived from anthropogenic activities.

Fig. 2
figure2

Enrichment factor (EF) of heavy metals in road dust

Cluster analysis

Using the means of z-scores to standardize the concentrations of the heavy metals studied, data underwent cluster analysis during which Euclidean distances for similarities were calculated (Yongming et al. 2006; Lu et al. 2010). The cluster analysis of heavy metals in road dust is shown in Fig. 3. Three classes were distinguished, which are as three follows: Cluster 1 (Mn, Zn, Pb, Ni and Cr), Cluster 2 (Cd) and Cluster 3 (Fe and Cu). The classification of these heavy metals was predominantly influenced by their concentration, such that the concentration for each class had its own range. Cluster 3 recorded the highest concentration followed by Cluster 1, with the lowest being Cluster 2.

Fig. 3
figure3

Cluster analysis for heavy metals in road dust

Principal component analysis

The results for factor loading with varimax rotation are shown in Table 5. The varimax rotation resulted in two factors which accounted for 86.71 % of the cumulative variance. In this study, we considered Factor 2 as a significant factor which explained a high variability (9.93 %) of the dataset. Factor 1 itself shows strong positive loadings for Pb, Ni and Cr, which accounted for 76.78 % of the total variance (Table 5). Based on the enrichment factor for the heavy metals included in Factor 1 (Fig. 2), the EF values ranged from moderate to significant, which indicate that Factor 1 is greatly influenced by a variety of sources of crustal origin and moderately influenced by anthropogenic sources, for example, crustal elements, soil-blown dust as well as corrosion of vehicular parts and traffic emissions. The study area is located in an urban area surrounded by heavy traffic flow. Generally, the possible sources of the heavy metals named (Pb, Cr and Ni) are exhaust emissions, domestic and industrial combustion, paints and corrosion. A previous study by Thorpe and Harrison (2008) stated that Pb is also one of the elements utilized in the manufacture of tyres.

Table 5 Rotated component matrix for heavy metals in road dust (strong PCA loading >0.75 is shown in bold)

Moreover, Factor 2 with 9.93 % of the total variance shows a strong factor loading for the Cd, Zn and Fe elements (Table 5). For Fe, Zn and Cd, the possible sources are predominantly the surrounding soil as well as a result of wear and tear of vehicle parts, particularly brake pads. Heavy traffic, road intersections and traffic lights in the study area require drivers to often use their brakes and then subsequently to accelerate to continue on their journeys, at which point damage is potentially caused to their tyres, brake pads and brake linings. According to Adachia and Tainoshob (2004) and Apeagyei et al. (2011), serious wear and tear of tyres and the brake lining may produce a high concentration of heavy metals, such as Fe and Zn. The sources of Cd in Factor 2 are most likely to be from oil leakage from automobiles along with car abrasion and car lubricants (Akhter and Madany 1993). According to a study undertaken by Tamrakar and Shakya (2011), metal plating and metal-enforced tyres are considered the most likely and common anthropogenic sources of Cd in road dust through the burning of tyres and bad roads. This argument has been supported by the EF calculation for heavy metals (Fig. 2), which shows that both Cd and Zn recorded a significantly high enrichment value in the range of 10–20 , thus indicating that Factor 2 is significantly influenced by anthropogenic sources.

Conclusion

The results from this study demonstrate that elevated concentrations of heavy metals, including Fe, Cu, Mn, Zn, Pb, Ni, Cr and Cd, were identifiable in the road dust collected from the selected area. Overall, the concentrations of heavy metals determined in the road dust in this study are within those concentrations found in other cities. The highest concentration of heavy metal was Fe followed by Cu > Mn > Zn > Pb > Ni > Cr > and Cd. It was also found that the concentration of heavy metals increased as particle size decreased. As a result, the highest concentration of heavy metals in the road dust was for particles with a diameter, d < 63 μm (Fraction A). Enrichment factor analysis demonstrated that Cd had the greatest value compared to other metals. Cd was derived from anthropogenic activities while Fe, Mn, Ni and Cr originated from both anthropogenic and crustal sources. Cluster analysis classified all heavy metals (Pb, Cu, Cd, Ni, Cr, Zn and Mn) into three groups according to similar concentrations, as in Cluster 1 (Mn, Zn, Pb, Ni and Cr), Cluster 2 (Cd) and Cluster 3 (Fe and Cd). Further analysis, using PCA, clearly indicates that traffic activities (namely: exhaust emissions, brake and tyre wear) are the main sources of heavy metals in the road dust collected at selected areas in Kuala Lumpur city centre.

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Acknowledgments

The authors would like to thank Universiti Kebangsaan Malaysia for the Research University Grant (DIP-2012-020). We also would like to thank the Ministry of Education for its Fundamental Research Grant (FRGS/1/2013/STWN01/UKM/02/2). Special thanks to Ms K Alexander for proofreading this manuscript.

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Correspondence to Mohd Talib Latif.

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Han, N.M.M., Latif, M.T., Othman, M. et al. Composition of selected heavy metals in road dust from Kuala Lumpur city centre. Environ Earth Sci 72, 849–859 (2014). https://doi.org/10.1007/s12665-013-3008-5

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Keywords

  • Heavy metals
  • Road dust
  • Particle size
  • City centre
  • PCA