The Sources of Polycyclic Aromatic Hydrocarbons in Road Dust and Their Potential Hazard

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants (POPs) found in the environment, posing significant health concerns for the population. This research aimed to assess the PAH levels in road dust near bus stops, identify their sources, and evaluate potential health risks. The analysis involved the use of a gas chromatography–flame ionization detector (GC-FID) to measure PAHs and absolute principal component score-multiple linear regression (APCS-MLR) for source apportionment of PAHs. The results indicated that the measured PAHs concentrations in road dust ranged from 137.8 to 5813 ng g⁻¹, with Indeno[1,2,3-c,d]pyrene having the highest PAHs concentrations. The study identified three main sources of PAHs such as oil spills, fuel combustion, and coal burning, determined through APCS-MLR modeling. Further analysis revealed that the aggregate incremental lifetime cancer risk (ILCR) for children and adults were 2.16 × 10⁻⁶ and 2.08 × 10⁻⁶, respectively. Additionally, the hazard index (HI) for children exceeded that of adults, suggesting greater vulnerability to the potential health effects of PAH exposure. The findings indicate that long-term exposure to PAHs may negatively impact lung function and increase the risk of cancer and skin diseases. As a result, it is crucial for the local government to implement effective measures aimed at improving fuel quality and promoting green public transportation within the city. These initiatives may help mitigate PAH emissions and safeguard public health.

1. Introduction

Road dust is a matter of significant apprehension owing to its detrimental effects on human well-being. It can amass in the surroundings through diverse means, including natural, biogenic, and anthropogenic sources. Moreover, it comprises a blend of soil-derived substances and atmospheric particles emitted from both volcanic activities and human-induced factors [1,2]. Effective management of airborne particulate matter is of utmost importance as it can have adverse effects on human health. The presence of fine and coarse particles in the atmosphere is primarily linked to road traffic, arising from both exhaust and non-exhaust particle discharges. Notably, non-exhaust emissions, particularly those from road dust, are now recognized as a substantial source of particle concentrations in numerous countries, surpassing exhaust emissions. Nevertheless, analyzing road dust in the air presents considerable challenges [3]. Road dust contains numerous hazardous materials and semi-volatile organic compounds (SVOCs), including polycyclic aromatic hydrocarbons (PAHs) [4,5,6,7].

PAHs, which are recognized as significant environmental contaminants composed of multiple fused benzene rings arranged in various patterns such as linear, angular, and cluster, have been extensively studied [8]. These compounds exist mostly as colorless, white, or pale-yellow solids, exhibiting persistence with diverse structures and toxicity levels [9]. PAHs can originate from various processes, including biological activities, biomass forest fires, and incomplete combustion of fossil fuels, coal burning, agriculture straw, and smoking, making them ubiquitous in the environment [10,11,12].

Two well-known sources of PAHs are pyrogenic and petrogenic. Pyrogenic PAHs stem from traffic exhaust and the combustion of fossil fuels [13], while petrogenic PAHs result from oil spillage accidents [14]. Additionally, it is worth noting that various other sources, such as tire abrasion, wood emissions, asphalt, rubber tires, tailpipe drainage, industrial emissions, and waste burning, also contribute significantly to pyrogenic and petrogenic PAH levels [15,16]. PAHs concentrations in roadside dust are influenced by two primary sources: traffic volume and cleaning routine [17]. Moreover, a study by Khpalwak et al. [18] highlights vehicular exhaust, coal or wood combustion, and oil spills as the main sources of PAHs in road dust.

PAHs possess the characteristics of toxic, mutagenic, carcinogenic, as well as persistent pollutants. Overall, 16 PAHs have been nominated as “Highlighted pollutants” by the United States Environmental Protection Agency (USEPA) [19,20] as shown in Figure S1. PAHs in road dust affect the health of children and adults more frequently [21]. The International Agency for Research on Cancer (IARC) identified some of the PAHs (such as benzo[a]pyrene (BaP)) as carcinogenic pollutants. PAHs are absorbed via inhalation, ingestion, and dermal contact. The highly lipid-soluble properties readily absorbed from the human intestinal tract into human fat tissues and other tissues are likely to wander and stay within the human body fat. Tumor reproduction, development, and immunity are some of the adverse effects on humans [17,22,23]. Consequently, individuals residing in urban neighborhoods are at risk of experiencing prolonged chronic health effects, including lung cancer and skin-related diseases, as a result of metabolic reactions triggered by PAH exposure [24,25,26,27]. Notably, PAHs with higher molecular weights, such as Benzo[a]pyrene (BaP) and Dibenzo[a,h]anthracene (D[ah]A), pose significant cancer risks [18].

The rapid urbanization and industrialization in Malaysia has led to an increased demand for energy. Specifically, in Kuala Lumpur, there is a swift development of buildings and rails, which involves higher combustion of fossil fuels, resulting in the emission of hazardous air pollutants. The purpose of this study is to provide valuable insights for improving the public transportation system. By doing so, it aims to reduce the health risks faced by passers-by, users, and workers at bus stops. To achieve this, dust samples were collected from various bus stations around Kuala Lumpur, including the rail network, to identify the sources of PAH pollutants. The main objectives of the study are as follows: (a) to determine the concentration of PAHs and their composition in road dust near bus stations, (b) to identify the sources of PAHs using multivariate modeling techniques, and (c) to assess the potential health risk posed by PAHs in the studied areas. By accomplishing these objectives, the study aims to contribute valuable information to enhance public transportation systems and ensure the well-being of the general public, commuters, and workers in the vicinity of the bus stations.

2. Methodologies

2.1. Study Area along with Its Sampling Procedures

Between the 23rd, 26th, and the 29th of September 2019, dust samples were collected in Kuala Lumpur on sunny days. The average temperature during the study time over the sampling stations was recorded as 31.83 °C and humidity also observed at approximately 71% (https://world-weather.info, access date 10 August 2023). The collection took place at 20 different locations, with a focus on bus stations and public rail transportation. Kuala Lumpur serves as the capital city of Malaysia and is situated approximately 40 km from the coast, within the federal state of Selangor. Covering an area of 243 square kilometers, the city is home to around 1.8 million people in its central region. The public rail transportation system in Kuala Lumpur is well-developed, consisting of various networks such as the Monorail, Light Rail Transit (LRT), Mass Rapid Transit (MRT), and Keretapi Tanah Melayu (KTM) Commuter, all of which are integrated at the KL Sentral station. Additionally, each rail station is served by RapidKL feeder buses, with the main hub located at Pasar Seni, Kuala Lumpur. To conduct the study, a total of twenty (20) dust samples were collected. Street dust was carefully swept using a small brush and collected in a plastic dustpan. The collected dust was then placed in clean Ziploc bags. In the laboratory, the dust was sieved to achieve a uniform size of 53 μm, using a standard test sieve (8-inch diameter; 2-inch height, No. 270; Cole Parmer, Burlington Township, NJ, USA). The sieved dust was stored in another clean Ziploc bag and left to dry overnight in a desiccator. The dried dust samples were preserved for further analysis. The sampling location map is shown in Figure 1.

2.2. Analysis of the Water-Soluble Organic Carbon (WSOC) and PAHs Compositions

2.2.1. Determination of Water-Soluble Organic Carbon (WSOC) Analysis

WSOC was measured in mg/L as a water-soluble fraction of organic carbon (WSOC) using a TOC analyzer (Total Organic Carbon Analyser, Shimadzu, Japan). About 200.0 mg of dust sample was weighed and dissolved in 50.0 mL of distilled water. The solution was sonicated for 20 min and filtered by gravity to remove the insoluble dust sample. The instrument used to analyze the sample solution was TOC-L (Shimadzu Total Organic Carbon Analyser, Japan). The TOC from samples was subtracted from the blank samples [28,29,30].

2.2.2. Extraction and Chemical Analysis of PAHs

PAHs were extracted in dichloromethane solvent, and the clean-up process was followed using n-octyl-triethoxysilane Surface-modified Magnetic Iron Oxide Nanoparticles (C₈MNPs). The MNPs were synthesized based on a study conducted by Tay et al. [31]. A mixture of FeCl₂:FeCl₃ (in a molar ratio of 2:3) was dissolved in 50.0 mL deionized water. Then, 50.0 mL of 25% ammonium hydroxide was added into the mixture with vigorous stirring for 30 min. After 30 min, the MNPs settled at the bottom of the beaker and were collected using an external magnetic field. The collected MNPs were washed with deionized water followed by methanol. The MNPs collected were dried under vacuum at room temperature. The MNPs were modified to C₈MNPs due to the instability of MNPs under ambient conditions, being readily oxidized in air or dissolved in acidic medium [31]. Before modification, the apparatus used was dried by applying the flow of nitrogen throughout the set-up. The procedure to modify MNPs is as follows: 2.0 g of MNPs, 5.0 g of n-octyl-triethoxysilane, 0.1 mL of trimethylamine, and 25.0 mL of toluene was placed into a round-bottomed flask under nitrogen atmosphere for 10 min before refluxing. The mixture was refluxed for 24 h under nitrogen flow. The modified MNPs—C₈MNPs—were collected using an external magnetic field and washed with toluene followed by methanol. The collected C₈MNPs were dried under vacuum at room temperature.

Fourier-transform infrared spectroscopy (FTIR) analysis was conducted to confirm the modification of MNPs to C₈MNPS using n-octyl-triethoxysilane. The instrument that used was an FT-IR Spectrometer Frontier (PerkinElmer, Waltham, MA, USA). The analysis was performed using the dried KBr pellet method where the solid MNPs and C₈MNPs were ground together with KBr pellets in the ratio of 100:1 (KBr: Sample). Figure S2 shows both the FTIR spectrum of MNPs and C₈MNPs. In both spectrums, it was noticeable that there was a peak for Fe-O stretching vibration at 579 cm⁻¹. The peak at 1038 cm⁻¹ in the C₈MNPs spectrum shows the presence of Si-O bonding. The peak at 1635 cm⁻¹ can be seen in both spectra as it shows O-H deformation vibration while the peak at 2922 cm⁻¹ was the only presence on the C₈MNPs spectrum as it indicates C-H stretching vibration in n-octyl-triethoxysilane. In both MNPs and C8MNPs spectrums, the broad peak presence at 3409 cm⁻¹ indicates the O-H stretching vibration. The IR spectra obtained in this study are consistent with the previously reported article. The extraction method followed the method developed by Tay et al. [31], with slight modifications. About 500.0 mg of each sample was weighed and dissolved in 15.0 mL dichloromethane. The solution was sonicated for 10 min and about 20.0 mg of C₈MNPs was added into the solution immediately after. After the addition of C₈MNPs, the mixture was sonicated for 1 min and the magnetic nanoparticles were collected using an external magnetic field. The dichloromethane was decanted, and 5.0 mL dichloromethane was added into the magnetic nanoparticles with leftover dust sample and sonicated for 4 min. Dichloromethane was thrown away and 200.0 µL of n-hexane was added into the vial containing the magnetic nanoparticles. The mixture was sonicated for 1 min and the solution was transferred into an insert and placed into a GC-FID vial.

2.2.3. Analysis of PAHs Using Gas Chromatograph—Flame Ionisation Detector (GC-FID)

The instrument used in this analysis is a Gas Chromatograph coupled with Flame Ionized Detector (Agilent Technologies 7890A, GC System, USA). Regarding the GC system, the oven temperature at 40 °C was increased at 8 °C min⁻¹ to 150 °C, then 5 °C min⁻¹ to 310 °C and held for 10 min. The injector temperature was 270 °C with split-less mode and nitrogen as carrier gas with flow fixed at 1 mL min⁻¹ and pressure 170 kPa. The FID heater was at 320 °C with hydrogen gas flow at 30 mL min⁻¹. The capillary column used was a standard polysiloxane HP-5 column (30 m length; 0.320 mm diameter; 0.25 µm film) (Agilent, Santa Clara, CA, USA). The solvent used was n-hexane with an injection volume of 1µL. The sixteen PAHs that were analyzed based on the USEPA are naphthalene (NAP), acenaphthylene (ACY), acenaphthene (ACP), fluorene (FLR), phenanthrene (PHE), anthracene (ANT), fluoranthene (FLT), pyrene, benzo[a]anthracene (BaA), chrysene (CHY), benzo[b]fluoranthene (BbF), Benzo[k]fluoranthene (BkF), Benzo[a]pyrene (BaP), Indeno[1,2,3-c,d]pyrene (IcP), Dibenz[a,h]anthracene (D(a,h)A), and Benzo[g,h,i]perylene (BgP) stated their molecular structure in Figure S1.

2.2.4. Quality Assurance and Quality Control (QA/QC)

The QA/QC was conducted using a Certified Standard Reference Material by Sigma-Aldrich, USA (CRM47543, Polycyclic Aromatic Hydrocarbons Mix; 1 × 1 mL; 2000 µg mL⁻¹). The standard mixture was diluted to 200, 500, 1000, 2000, and 3000 µg L⁻¹ and treated as a standard solution and analyzed using GC-FID with the same temperature program as the sample. The calibration curve of each compound in the CRM detected was plotted and their retention time was used as a reference for the sample.

2.3. Source Apportionment and Health Risk Modeling

Data analysis, modeling, and health risk assessment are involved with diagnostic ratio (DR), APCS-MLR, and USEPA health risk models.

2.3.1. Source Apportionment Modeling

Diagnostic Ratio (DR)

The simplest source apportionment using receptor modeling is to calculate the DR. PAHs ratio was used to perform DR analysis to arbitrarily determine the unknown sources of pollutants [32,33,34,35]. Tables S4 and S5 shows the indicative sources of pollutants based on their DR as suggested by several researchers [35,36,37,38,39,40,41,42,43,44,45].

Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) Models

Absolute principal component score (APCS), an advanced version of PCA, was applied to evaluate the PAH source apportionment. The APCS procedures used in this study were based on methodologies previously reported in the works of Harrison et al. [46], Hopke [47], and Thurston and Spengler [48]. Before conducting the PCA, the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s Test were applied to assess the suitability of the concentration data for PCA analysis. The results of both the KMO and Bartlett’s Test were deemed acceptable, with values above 0.5, indicating that the data were suitable for PCA analysis. Moreover, the KMO test result, being close to 1, suggests that the data were highly suitable for PCA analysis, further supporting its appropriateness for this study [49]. To prepare the data for PCA analysis, the raw PAHs concentration data were normalized by subtracting the concentration (C) with the average mean ($\bar{\mathrm{C}}$) and dividing by the standard deviation (SD). This normalization process rendered the data unitless. The PCA analysis was then performed using the normalized data, and missing data were replaced with the geometric average means of each variable. The PCA procedure utilized covariance extraction with varimax rotation and linear regression. From the total variance data, the factors with more than 5.0% variance were selected. Subsequently, the principal component scores were corrected as suggested by Thurston and Spengler [48] to rescale them, yielding APCS. The APCS were then regressed using Multiple Linear Regression (MLR) against the total PM_2.5-bound PAHs. The high r² value of 0.97 obtained from the MLR indicates a reasonable fit of the regression to the data. This supports the appropriate application of MLR results to convert the APCS into mass concentration, as demonstrated in Figure 2. This methodology of using PCA and MLR for source apportionment has been previously successful, as evidenced by Khan et al. [50], who applied a similar procedure for source apportionment of metals from air suspended particles collected in various sites in Yokohama, Japan.

2.3.2. US EPA Health Risk Modeling

BaP_eq was calculated by multiplying the concentration of each compound, C, with the toxic equivalency factors (TEFs) of the respective compound, as shown in Equation (1).

$${\mathrm{B}\mathrm{a}\mathrm{P}}_{\mathrm{e}\mathrm{q}}=\mathrm{C}\times \mathrm{T}\mathrm{E}\mathrm{F}$$

(1)

The daily Intake Dosage (ID) and incremental lifetime cancer risk (ILCR) were calculated for non-carcinogenic and carcinogenic risk. This calculation was performed for three exposure pathways: inhalation, ingestion, and dermal. The equation of IDs and ILCR for the three intakes pathway is shown below. The calculation was evaluated for two age categories which are children and adults. The parameterization and related calculation for the entire risk assessment was adopted correctly from the published literature [51,52,53,54,55,56,57,58]. The reference values for RfD and CSF were obtained from Anh et al. [51]. Reference values and details for EF, ED, BW, and PEF including others are given in Table S7.

Non-carcinogenic assessment was made using the following Equations (2)–(5) [52].

$$\mathrm{D}\left(\mathrm{I}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)=\frac{\mathrm{C}\mathrm{S}\times \mathrm{I}\mathrm{R}\times \mathrm{E}\mathrm{T}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}\times \mathrm{P}\mathrm{E}\mathrm{F}}$$

(2)

$$\mathrm{I}\mathrm{D}\left(\mathrm{I}\mathrm{n}\mathrm{g}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)=\frac{\mathrm{C}\mathrm{S}\times \mathrm{I}\mathrm{R}\times \mathrm{F}\mathrm{I}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}\times \mathrm{C}\mathrm{F}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}}$$

(3)

$$\mathrm{I}\mathrm{D}\left(\mathrm{D}\mathrm{e}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{l}\right)=\frac{\mathrm{D}\mathrm{A}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}\times \mathrm{E}\mathrm{V}\times \mathrm{S}\mathrm{A}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}}$$

(4)

$$\mathrm{H}\mathrm{Q}=\frac{\mathrm{I}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{k}\mathrm{e}}{\mathrm{R}\mathrm{f}\mathrm{D}}$$

(5)

Carcinogenic assessment was performed using the following Equations (6)–(8) [54,56,57]

$$\mathrm{I}\mathrm{L}\mathrm{C}\mathrm{R}\left(\mathrm{I}\mathrm{n}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)=\frac{\mathrm{C}\mathrm{S}\times ({\mathrm{C}\mathrm{S}\mathrm{F}}_{\mathrm{i}\mathrm{n}\mathrm{h}}\times \sqrt[3]{\frac{\mathrm{B}\mathrm{W}}{70}})\times {\mathrm{I}\mathrm{R}}_{\mathrm{i}\mathrm{n}\mathrm{h}}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}\times \mathrm{P}\mathrm{E}\mathrm{F}}$$

(6)

$$\mathrm{I}\mathrm{L}\mathrm{C}\mathrm{R}\left(\mathrm{I}\mathrm{n}\mathrm{g}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\right)=\frac{\mathrm{C}\mathrm{S}\times ({\mathrm{C}\mathrm{S}\mathrm{F}}_{\mathrm{i}\mathrm{n}\mathrm{g}}\times \sqrt[3]{\frac{\mathrm{B}\mathrm{W}}{70}})\times {\mathrm{I}\mathrm{R}}_{\mathrm{i}\mathrm{n}\mathrm{g}}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}\times {10}^6}$$

(7)

$$\mathrm{I}\mathrm{L}\mathrm{C}\mathrm{R}\left(\mathrm{D}\mathrm{e}\mathrm{r}\mathrm{m}\mathrm{a}\mathrm{l}\right)=\frac{\mathrm{C}\mathrm{F}\times ({\mathrm{C}\mathrm{S}\mathrm{F}}_{\mathrm{d}\mathrm{e}\mathrm{r}}\times \sqrt[3]{\frac{\mathrm{B}\mathrm{W}}{70}})\times \mathrm{S}\mathrm{A}\times \mathrm{A}\mathrm{F}\times \mathrm{A}\mathrm{B}\mathrm{S}\times \mathrm{E}\mathrm{F}\times \mathrm{E}\mathrm{D}}{\mathrm{B}\mathrm{W}\times {\mathrm{A}\mathrm{T}}_{\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{c}}\times {10}^6}$$

(8)

3. Results

3.1. Level of Water-Soluble Organic Carbon (WSOC) in the Road Dust

WSOC for road dust near bus stations in Kuala Lumpur is 831.3 to 7886 ng g⁻¹ with a mean of 3026 ng g^−1, as shown in

Table 1. PAHs concentration (ng g⁻¹) in street dust.

Compound	Mean ± Std. Deviation	Median (Min–Max)
TOC	3026 ± 2104	2142 (831.3–7886)
ACY	69.80 ± 20.85	77.57 (37.07–90.24)
ACP	25.22	25.22 (25.22–25.22)
FLR	42.63 ± 11.82	48.23 (19.33–49.48)
PHE	61.99 ± 3.31	61.99 (59.66–63.34)
ANT	265.9 ± 168.5	271.3 (73.42–483.2)
PYR	348.5 ± 292.3	313.6 (22.15–746.0)
BaA	578.5 ± 348.5	589.6 (84.71–1023)
CHY	150.1 ± 47.14	158.9 (59.76–198.6)
BbF	491.3 ± 159.6	508.3 (208.2–674.4)
BkF	191.2 ± 76.58	199.8 (93.78–280.5)
BaP	249.6 ± 39.36	250.4 (122.8–374.8)
IcP	805.5 ± 304.1	917.5 (290.4–1094)
BgP	622.1 ± 227.9	710.7 (248.8–800.2)
Total PAHs	2458 ± 2251	1848 (137.8–5813)

. Table S2 shows the highest and lowest concentrations in sample locations such as KL location Bandar Tun Razak and KL 19 at KTM Angkasapuri, with a concentration of 7886 ng g⁻¹ and 831.3 ng g⁻¹, respectively. LRT Bandar Tun Razak is situated in the vicinity of high-rise flats and, thus, a common spot for familiar residents to park along the roadside. Taxi and bus drivers usually leave their engines running while waiting at the station, contributing to the emission of harmful air pollutants such as PAHs. KTM Angkasapuri has the lowest TOC as the buses here mostly only drop off passengers instead of waiting. As the buses only stop by along their trip, the emission of pollutants (PAHs) is less.

3.2. The Concentration of PAHs in Road Dust near Bus Stations

Based on the result obtained from GC-FID analysis, there are a few undetectable compounds which were naphthalene (NAP), fluoranthene (FLT), and dibenz[a,h]anthracene (D[a,h]A). Naphthalene has the lowest boiling point among the 16 compounds analyzed. Since the sampling was conducted on a sunny day, naphthalene is assumed to have been vaporized and cannot be detected.

Table 1 presents the concentration of PAHs in street dust samples collected from Kuala Lumpur. The total PAHs concentration was determined to be 2457.73 ± 2251.21 ng g⁻¹, with a range spanning from 137.76 to 5812.53 ng g⁻¹. Among the various PAHs analyzed, the highest concentration was found for Indeno[1,2,3-c,d]pyrene, a high molecular weight (HW) PAH, with a value of 805.47 ± 304.05 ng g⁻¹ and a range of 290.35 to 1094.37 ng g⁻¹. In contrast, the low molecular weight (LW) PAHs, which are lighter compounds, exhibited relatively lower concentrations. Acenaphthene, Fluorene, and Phenanthrene are examples of LW PAHs, and their respective concentrations were measured as 25.22, 42.63 ± 11.82, and 61.99 ± 3.31 ng g⁻¹. The concentration of total PAHs is considered moderate to highly contaminated. For single PAHs compound, it was noticeable that benzo[a]anthracene and indeno[1,2,3-c,d]pyrene concentrations are categorized as moderately contaminated as more than 1000 ng g⁻¹ were accumulated but not over 1500 ng g⁻¹. The rest of the PAHs are classified as low to moderately contaminated. Table 1 shows that Indeno[1,2,3-c,d]pyrene has the highest PAHs concentration, while acenaphthene has the lowest concentration with a value of 805.5 ng g⁻¹ and 25.22 ng g⁻¹, respectively. According to Chiu et al. [59], the concentration of PAHs below 1000 ng g⁻¹ is considered low to moderately contaminated, and concentration within 1000 ng g⁻¹ and 10,000 ng g⁻¹ is considered moderate to highly contaminated. Table S3 shows the comparison of PAHs in road dust and previous literature. Referring to a study by Omar et al. [60], the total concentration of road dust in Kuala Lumpur was 224 ng g⁻¹, with the range of PAHs compound concentration between 2 to 43 ng g⁻¹. Based on the results of this study, the concentration of PAHs has increased by about 9% over the past 17 years. Compared to the PAHs concentrations in Jeddah and Xi’an, the PAHs concentrations found in this study is far lower. This may be due to the increased PAHs emission from household heating, industrialization, and higher traffic intensity in larger populated cities such as Jeddah [37] and Xi’an [61]. The PAHs concentrations in this study are similar to those in Vietnam [51] and Ghana [62].

4. Discussion

4.1. Determination of Possible Unknown Sources of PAHs in Road Dust

4.1.1. Diagnostic Ratios (DRs)

From Table S4, the diagnostic ratio obtained for ANT/(ANT + PHE) in this study is 0.89 and 0.87 for the sampling sites of KL-13 and KL-14, respectively. Since the ratio is more than 0.1, it indicates that the PAHs came from pyrogenic sources [35,38,42]. The ratio of BaA/(BaA + CHY) obtained in this study was 0.793 to 0.889. According to Yunker et al. [35], Akyüz and Çabuk [36], and Manoli et al. [41], the ratio of BaA/(BaA + CHY) above 0.5 may have arisen from wood burning. However, in Malaysia, wood burning is not common. Biomass burning is more prevalent as some residents prefer to perform open burning of their rubbish and garden waste, which is also known as waste or biological waste [63]. The DR of IcP/(IcP + BgP) shows that the PAHs may come from exhaust emissions of heavy vehicles that use diesel as their energy source, as the ratio calculated in this study falls in the range of 0.35 to 0.70 [35,38,40,41]. The DR value of BaP/BgP was in the range of 0.644 to 0.994, which was more than 0.6. Previous work suggested that the PAHs ratio above 0.6 indicates that the PAHs originated from traffic sources [35,38]. The BgP/BaP calculated in this study lies in the range between 0.9 and 3.3, which shows that the PAHs are emitted from the combustion of diesel or car gasoline [37,43].

4.1.2. Multivariate Receptor Modeling Using PCA-MLR

PCA factor loadings and source apportionment by APCS-MLR of the PAHs are shown in

Table 2. PCA factor profiles and source apportionment of PAHs.

Variables	Factor 1	Factor 2	Factor 3
Acenapthylene	0.861	0.293	0.254
Fluorene	0.937	0.247	0.092
Anthracene	0.263	0.283	0.907
Pyrene	0.203	0.316	0.916
Benzo[a]anthracene	0.199	0.660	0.694
Chrysene	0.896	0.292	0.198
Benzo[b]fluoranthene	0.226	0.868	0.405
Benzo[k]fluoranthene	0.757	0.407	0.405
Benzo[a]pyrene	0.527	0.730	0.217
Indeno[1,2,3-c,d]pyrene	0.420	0.816	0.334
Benzo[g,h,i]perylene	0.460	0.791	0.314
Eigenvalues	8.035	1.513	0.747
Variance (%)	73.04	13.75	6.789
Cumulative (%)	73.04	86.79	93.58
PAHs Sources	Oil spills	Fuel combustion	Natural gas and coal burning

Bold values highlight the significant PCA factor loadings.

and Figure 2a,b.

Factor 1: Oil Spill

Factor 1 shows the loading of ACY, FLR, CHY, and BkF, with FLR predominant. NAP, ACY, ACP, and FLR mainly come from petroleum spills such as fresh or used crankcase oil, crude, and fuel oil [64,65,66]. Therefore, it can be deduced that Factor 1 is caused by oil spills. Studies revealed that FLR, PHE, FLT, and PYR are the main PAHs compound in diesel-powered vehicle emissions [67,68].

Based on the origin of the samples, it is assumed that the road dust was originally from gravel. The first justification is related to the components present in the rock that function as a sorbent to the PAHs. Road gravel usually comprises clay and bitumen [69]. The bitumen matrix is a decorous surface for the adsorption of organic components and incredibly aromatic hydrocarbons. In principle, lower molecular weight PAHs have lower aromaticity than higher molecular weight PAHs that identify with at least four aromatic rings. The series could suggest that the possible interactions between the bitumen matrix and PAHs might limit to dipole-dipole interactions (van der Waals) and pi stacking [70]. In this study, the identified compounds contain aromatic rings while two substances, ACP and FLR, partially contain saturated hydrocarbon. Lower molecular weight PAHs have fewer aromatic rings hence less chance to interact with the gravels. Higher molecular weight PAHs have a more significant number of aromatic rings that promote better dipole-dipole interaction and pi stacking between the PAHs and the bitumen. Related to the individual molecular weight of the PAHs, smaller PAHs consisted of fewer rings. The lower number of molecular interactions of the molecules also explains the higher volatility of the molecules. Therefore, the molecules are released into the atmosphere rather than remaining trapped in gravel or road dust. The third justification is from the content of the oil spillages. The oil spillages from the bus stations are obviously from the diesel engine that empowers the buses rather than less popular gasoline and hybrid engines. Diesel engines use higher-viscosity and -boiling-point lubricant oils [71,72]. The lubricant oils of this type consist of higher-molecular-weight petrogenic organic substances. If the spillages are from gasoline-type engines, the lubricants could be formulated mainly for lower viscosity to suit gasoline engines. The lubricant for diesel engines is also the source of higher-molecular-weight PAHs that are favorably adsorbed onto the road gravel and road dust. This is consistent with the findings from this study [73,74,75].

Factor 2: Fuel Combustion

It can be seen that BbF, BaP, IcP, and BgP show strong factor loadings in Factor 2. BaP, IcP, and BgP indicate the usage of heavy fuel. Based on existing literature, it has been referred that the BaP, IcP, DhA, and BgP are recognized as source markers for vehicles and gasoline emissions [65,76,77]. Benzo[a]pyrene indicates a stationary emission point that uses heavy oils as fuel, and high loadings of BaP, DhA, and BgP indicate vehicle engine emissions [65,77]. This factor has also been reported in several studies by Jamhari et al. [49] and Sulong et al. [78]. Like the first factor, the diesel engine is a potential emitter of PAH pollutants. The use of diesel as fuel combustion in a substantial amount in the area will release mainly higher-molecular-weight PAHs. The emission of diesel engines can be the main contributor to the existence of highly aromatic PAHs [74,75,79]. These molecules have better intermolecular interactions, particularly pi stacking, to form a larger cluster of dust. The molecules settle on the road and are adsorbed onto the organic component of the gravel and small particles with the help of dipole-dipole interaction [80]. This is consistent with the findings of considerable-molecular-weight PAHs, usually with five aromatic molecules.

Factor 3: Natural gas, biomass burning, and coal combustion

Factor 3 is strongly loaded with ANT, PYR, and BaA, whereby PYR and ANT dominate this factor. PHE, FLT, PYR, BaA, and CHR depict characteristics of natural gas and coal combustion [40,77,81,82,83]. It was found that BbF, BkF, PHE, FLT, PYR, BaA, and CHY are markers of coal combustion [46,66,84]. Meanwhile, FLT, FLR, PHE, ANT, and PYR are reported as oil combustion markers [17,46,77,85]. It can be concluded that the source of Factor 3 is natural gas and coal combustion. Coal as fuel in Malaysia is used to manufacture cement [86], and a cement plant is located in Kuala Lumpur. This power plant could also be the source of coal combustion as a coal-fired power plant is located in the Klang Kapar area, about 15 km from Kuala Lumpur. The aromaticity of the PAHs is also essential in describing this source profile. Those PAHs related to this factor profile are lower in the molecular weight [73]. The lower molecular weight of PAHs may have less pi-stacking interaction compared to the larger PAH molecules. They are relatively more volatile with weaker intermolecular pi-stacking interaction. This character allows the PAH molecules to travel longer distances from the source.

The APCS-MLR distribution in Figure 2a shows that Factor 1, Factor 2, and Factor 3 from PCA analysis contributed 7%, 15%, and 35%, respectively. The remaining 43% of the PAHs concentrations sources are undefined. The highest contribution, 35%, was caused by Factor 3, which was identified as natural gas and coal combustion. Factor 1, with a percentage of 7%, is caused by oil spills, and Factor 2, with a 15% contribution, is affected by vehicle fuel combustion. A correlation of the PAHs concentrations derived by APCS-MLR regression with the PAHs concentrations direction from GC-FID was demonstrated in Figure 2b. The coefficient of determination (r² = 0.97) suggests that the above model estimation shows a lower uncertainty to the PAHs apportionment.

4.2. Human Exposure of PAHs in Road Dust

4.2.1. Carcinogenic Assessment

Benzo[a]pyrene Equivalent Concentration (BaP_eq)

Table S6 explains that the total average of BaP_eq is 389.9 ng g⁻¹. The BaP_eq of the carcinogenic PAHs, benzo[a]pyrene (BaP), is the highest with 429.0 ng g^−1, followed by indeno[1,2,3-c,d]pyrene (IcP) with 80.55 ng g⁻¹ which was listed as one of the probable carcinogenic PAHs compounds. Benzo[a]anthracene (BaA) and benzo[b]fluoranthene, which is also listed as the potential carcinogenic PAHs compound, has quite significant BaP_eq concentration with 57.85 ng g⁻¹ and 49.13 ng g⁻¹ compared to other PAHs. Meanwhile, acenaphthene is listed as the lowest BaP_eq concentration, with 0.025 ng g⁻¹.

Incremental lifetime Cancer Risk (ILCR)

(a)

Incremental Lifetime Cancer Risk (ILCR) of the inhalation pathway

Tables S8 and S9 present the ILCR value for children and adults. From the calculated ILCR, it can be observed that the values are in the range of 10⁻¹⁵ to 10⁻¹¹ for both children and adults. ILCR values in this study were lower than in [62], which recorded the ILCR values for the inhalation pathway range between 10⁻¹⁰ to 10⁻⁹. In addition, Soltani et al. [58] also possess a higher ILCR value with the range of 10⁻⁹ to 10⁻⁸. The highest ILCR value for children is observed for benzo[a]pyrene, which was 2.58 × 10⁻¹¹ with an average of 2.05 × 10⁻¹¹. As for adults, benzo[a]pyrene shows the highest ILCR value of 8.04 × 10⁻¹¹ and a mean of 6.40 × 10⁻¹¹. According to EPA [52], an ILCR of less than 10⁻⁶ is not susceptible to health risk. Since the ILCR value of PAH exposure through inhalation is less than 10⁻⁶, there is no possible health risk.

(b)

Incremental Lifetime Cancer Risk (ILCR) through ingestion pathway

The ILCR data for the ingestion pathway are shown in Tables S10 and S11 for children and adults, respectively. Both children and adults have ILCR values ranging from 10⁻¹¹ to 10⁻⁶. The cancer risk is equal to the limit of 10⁻⁶, it is acceptable, and there is no possible human health risk. Compared to Soltani et al. [58], their average ILCR reached 10^−4, which needs to be considered a health risk. As observed in Table S11, the highest cancer risk value for children is 1.33 × 10⁻⁶, representing benzo[a]pyrene. The average ILCR for children is 9.60 × 10⁻⁷ with a maximum value of 2.11 × 10⁻⁶. For an adult, the average total ILCR is 7.49 × 10⁻⁷, and the maximum value is observed that acenaphthene has the lowest ILCR value for both children and adults compared to the other PAHs compound, with an average value of 6.21 × 10⁻¹¹ and 4.85 × 10⁻¹¹, respectively. It has been reported in the literature that BaP and DahA are of significant concern for possible cancer risks among people [18].

(c)

Incremental Lifetime Cancer Risk (ILCR) through dermal pathway

For the dermal pathway, the ILCR value ranges from 10⁻¹¹ to 10⁻⁶ for both children and adults, as shown in Tables S12 and S13, which is acceptable and has no potential human health risk. The mean total ILCR for children is 1.20 × 10⁻⁶; meanwhile, for adults, the value is 1.33 × 10⁻⁶. Compared to road dust in Afghanistan [18] and Xi’an, China [61], this study has higher ILCR but lower than those in Isfahan [58]. The compound with the highest ILCR is BaP, with an average value of 1.32 × 10⁻⁶ for children and 1.46 × 10⁻⁶ for adults. However, the total ILCR from inhalation, dermal and ingestion stated in

Table 3. Total ILCR, HQ, and HI of PAHs through inhalation, ingestion, and dermal pathways.

	Pathway	Children	Adult
ILCR	Inhalation	1.86 × 10−11	5.81 × 10−11
	Ingestion	9.60 × 10−7	7.49 × 10−7
	Dermal	1.20 × 10−6	1.33 × 10−6
	Total	2.16 × 10−6	2.08 × 10−6
HQ	Inhalation	1.617 × 10−6	1.386 × 10−6
	Ingestion	1.100 × 10−2	1.178 × 10−3
	Dermal	4.003 × 10−3	6.112 × 10−4
HI	Total	1.500 × 10−2	1.791 × 10−3

both for children and adults is higher than the guideline value (10⁻⁶).

4.2.2. Non-Carcinogenic Assessment

a.

Hazard Quotient (HQ) through Inhalation Pathway

The intake dosage (ID) for children and adults ranges between 10⁻¹¹ to 10⁻⁹ and 10⁻¹¹ to 10⁻¹⁰, respectively. The ID for children of total PAHs has a mean of 4.93 × 10⁻⁹ mg kg⁻¹ d⁻¹ and a maximum of 1.12 × 10⁻⁸ mg kg⁻¹ d⁻¹. For adults, the mean of total PAHs is 2.11 × 10⁻⁹ mg kg⁻¹ d⁻¹ with a maximum value of 4.82 × 10⁻⁹ mg kg⁻¹ d⁻¹. In both children and adults, the IcP that contributed the most was ACP. ID values of IcP for children and adults are 2.06 × 10⁻⁹ mg kg⁻¹ d⁻¹ and 8.82 × 10⁻¹⁰ mg kg⁻¹ d⁻¹, respectively. The HQ values for the inhalation pathway of children and adult are in the range of 10⁻¹⁰ to 10⁻⁸ with the mean of total HQ being 1.62 × 10⁻⁶ and 1.39 × 10⁻⁶ for children and adults, respectively, as shown in Tables S14 and S15. For road dust in Afghanistan, Khpalwak et al. [18] reported that the HQ value is in the range of 10⁻⁹. The contents of this study and of road dust in Afghanistan are pretty similar. The highest HQ can be observed for BaP for children and adults as 3.38 × 10⁻⁶ and 2.90 × 10⁻⁶. ACP sets the lowest HQ for children and adults as 7.90 × 10⁻¹⁰ and 6.78 × 10⁻¹⁰. Since the total HQ does not exceed 1, there is less probability of potential health risks in the PAHs [53].

b.

Hazard Quotient (HQ) through Ingestion Pathway

The ID ranges from 10⁻⁷ to 10⁻⁵ for children and 10⁻⁸ to 10⁻⁶ for adults. The highest ID values are 1.40 × 10⁻⁵ mg kg⁻¹ d⁻¹ for children and 1.50 × 10⁻⁶ mg kg⁻¹ d⁻¹ for adults, which is IcP representative among the PAHs showing a compound is ACP with 3.23 × 10⁻⁷ mg kg⁻¹ d⁻¹ for children and 3.46 × 10⁻⁸ mg kg⁻¹ d⁻¹ for adults. As observed, the intake dosage of children is higher than that of adults. The ranges of HQ for children and adults are 10⁻⁶ to 10⁻² and 10⁻⁷ to 10⁻⁴, respectively. The mean for total HQ of children and adults are 1.10 × 10⁻² and 1.18 × 10⁻³, as shown in Tables S16 and S17. Compared to a study by Khpalwak et al. [18], this study has a higher HQ value. The trend in this study and that of Khpalwak et al. [18] is the same, whereby children have a higher HQ than adults. It was noticed that BaP has the highest HQ value among the PAHs, with 2.30 × 10⁻² for children and 2.46 × 10⁻³ for adults. ACP has the lowest HQ, whereby values for children and adults are 5.38 × 10⁻⁶ and 5.76 × 10⁻⁷, respectively. According to EPA [53], the HQ of no more than 1 does not bring any potential health to humans. For this study, the HQ is below 1; therefore, there is no potential health risk.

c.

Hazard Quotient (HQ) through Dermal Pathway

As observed in Tables S18 and S19, the mean of total HQ for children and adults is 4.00 × 10⁻³ and 6.11 × 10⁻⁴, respectively. Children and adults have a total mean of 1.22 × 10⁻⁵ mg kg⁻¹ d⁻¹ and 1.86 × 10⁻⁶ mg kg⁻¹ d⁻¹ intake dosage, respectively. For children and adults, the highest ID is 5.09 × 10⁻⁶ and 7.78 × 10⁻⁷, respectively, representing the compound IcP. The range of ID value for this study is 10⁻⁷ to 10⁻⁶ for children and 10⁻⁸ to 10⁻⁷ for adults. The HQ ranges from 10⁻⁶ to 10⁻³ for children, while for adults, the HQ ranges from 10⁻⁷ to 10⁻³. Compared to the study of road dust in Afghanistan [18], the HQ agrees with this study which was 10⁻³ for children and 10⁻⁴ for adults. The lowest HQ can be seen at compound ACP, with a value of 1.96 × 10⁻⁶ and 2.99 × 10⁻⁷ for children and adults, respectively. The HQ in this study does not exceed the limit set by EPA [53], in which the value is not more than 1. Thus, the potential health risk is not a serious concern.

d.

Hazard Index (HI)

It can be deduced from Table S3 that there is no potential health risk to be a concern as the value of HI in this study does not exceed the limit of 1 (EPA, 2001b). The total HI values were also presented in Table 3 for children and adults which shows no potential non-carcinogenic risk. Compared with Khpalwak et al. [18], this study has a higher HI value as their HI is 10⁻³ for children and 10⁻⁴ for adults. A similar observation was reported in another study by Anh et al. [51]; however, their HI value is lower than this study, whereby their HI value for children and adults is in the range of 10⁻⁵ to 10⁻⁴ and 10⁻⁶ to 10⁻⁵, respectively.

5. Conclusions

The mean concentration of PAHs in road dust near bus stations is 2458 ng g⁻¹, ranging from 137.8 ng g⁻¹ to 5813 ng g⁻¹. Over the past 17 years, the PAHs concentrations has increased by approximately 9%. The source apportionment analysis revealed three significant factors: Factor 1 (indicative of oil spills), Factor 2 (indicative of fuel combustion), and Factor 3 (indicative of natural gas and coal combustion), contributing 25%, 24%, and 46%, respectively. However, 5% of sources of PAHs remain unidentified. In terms of carcinogenic health risk assessments, the Benzo[a]pyrene equivalent concentration (BaPeq) was determined, with the highest BaPeq being 429.0 ng g⁻¹ for Benzo[a]pyrene (BaP), a known carcinogenic PAH. Indeno[1,2,3-c,d]pyrene (IcP), listed as a probable carcinogenic PAH compound, had a BaPeq of 80.55 ng g⁻¹. The ILCR values for inhalation, ingestion, and dermal contact pathways were calculated for both children and adults. The ILCR values were found to be below the USEPA guideline value, indicating no potential health risk for all three pathways for both age groups. However, children were more vulnerable to BaP exposure through all routes. Furthermore, the Hazard Quotient (HQ) values for inhalation, ingestion, and dermal contact pathways were assessed. Again, all HQ values were below the USEPA threshold for non-carcinogenic health risk assessment, indicating no non-carcinogenic health risk. Nevertheless, the overall HI values were relatively high for both children (1.50 × 10⁻²) and adults (1.79 × 10⁻³), especially considering children’s lower immune system. Although the HI values are within the non-carcinogenic health risk range, they signify a significant health risk, particularly for children. The study recommends sharing the knowledge gained with government bodies to facilitate the implementation of new rules and policies for the public transportation sector, aiming for the betterment of society. Moreover, sharing this knowledge with citizens can increase awareness about the severity of this health issue and its potential impacts on public health.