Spatial distribution, contamination levels, source identification and human health risk assessment of potentially toxic elements in street dust in urban area in Libya

ABSTRACT Street dust samples were collected from 31 sampling sites which were classified into four different groups in Zawiya, Libya, covering different traffic, city center, junkyards, oil refinery, farming, and household activities. Since the potentially toxic elements (PTEs) in street dust have a non-negligible impact on health, the aim of this study is to investigate the sources, pollution level and human health risk of PTEs. In this study, wavelength distribution X-ray fluorescence device was used to determine the concentration of PTEs. The spatial distribution, contamination levels, sources, and human health risks of PTEs in road dust were evaluated. The PTEs content of the street dust were found as Cr>Mn>Zn>Pb>Cu>Ni>Co. The average concentration of most PTEs (Co, Cu, Mn, Ni and Zn) was higher in junkyards and heavily traffic areas than in other areas. Cobalt and Cu has the highest geo accumulation index (Igeo) values, and due to these values, the study area was evaluated as moderately to heavily contaminated. Enrichment factor (EF) values of Cr, Pb and Zn exhibited a significant enrichment, indicating that some sampling sites were affected by anthropogenic sources. There was no lifetime cancer risk for exposure to PTEs in street dust by inhalation in Zawiya. Each hazard quotient (HQ) and hazard index (HI) for all PTEs were less than 1, indicating that exposure to PTEs in street dust did not have significant non-carcinogenic risks for both adults and children. In conclusion, Zn, Pb, Cu, Mn, and Cr were represented by the largest portion of the total data variance in the principal component analysis (PCA), and they were positively correlated. It was seen that study area was influenced by anthropogenic sources rather than natural sources, but there was no health risk.

area. Therefore, in this study, the total concentrations of seven PTEs (e.g., Co, Cr, Cu, Mn, Ni, Pb and Zn) in street dusts were investigated in 4 different groups (junkyards, oil refinery (industrial), traffic, and agriculture activities) according to the characteristics of 31 sampling sites. The main objectives of this study were: (i) to determine the concentration of PTEs; (ii) to evaluate the contamination levels of PTEs by calculating enrichment factor (EF), geoaccumulation index (Igeo); (iii) to determine human health risk and (iv) to determine potential natural and anthropogenic sources of PTE by evaluating the concentration of PTEs in 4 different groups according to the characteristics of the sampling sites, interpreting the correlation coefficient analysis (CCA) and principal component analysis (PCA). In this study, results were obtained that will constitute a source for the plans for increasing the environmental quality in Zawiya.

Study area
Zawiya is located on the Mediterranean coastline, about 40 km west of Tripoli the capital city of Libya. Sustainable urban design elements are not enough in the city. The city has almost no gardens, and the streets seem to be designed only for cars. It is possible to feel the hot sun penetrating everywhere (Elbasha and Aysu 2019). Mediterranean climate with hot summers and mild winters prevails along the coast of Libya. While in the early summer months, with high humidity, the temperature may reach up to 30°C, in July and August, the temperature reaches to 40°C. In winter, the average temperature is 14°C. It rains along the coast from October to March. The wind, which generally flows from the northeast or north and hot in the summer and colder in the winter, is dominant in the coastal areas (Salem 2015). Zawiya is the third largest city in Libya (Badi, Ballem, and Shetwan 2018) and has one of the largest water desalination plants. Another important facility of Zawiya is the power plant (Fellah and Noba 2016;Shehada et al. 2021). An oil refining company is another vital facility operating in this city since 1974 (Gawedar and Ramakumar 2016).

Sample collection
Street dust samples were collected from 31 sampling sites in Zawiya on 8 June 2021 ( Figure 1). The sampling sites were classified into four groups according to their characteristics as follows: Group 1: traffic-city center, Group 2: junkyard-heavy traffic, Group 3: oil refineries and other factories-traffic, Group 4: intensive farming activities-less houses. Groups 2 and 3 also represent industrial activities. In order to best assess the effects of these activities on PTE pollution, great attention has been paid to the location of the sampling sites shown in Figure 1. Polyethylene brush and plastic hand shovels were used to collect approximately 1000 g of dust sample from the surface. While dust samples were collected gently, the dust accumulated on metal surfaces was not taken as a sample. The number of each sampling site was written and labeled on the polyethylene bag of each sample. Before the sieve analysis, larger pieces were taken from the samples. All samples were dried at room temperature for 24 hours after they were brought to the laboratory. In the literature, 10, 25, 60, 100, 140, 180 and 230 mesh sieves were used in the studies conducted by Victoria et al. (2014), Kara (2020), Aguilera et al. (2021), , Idris et al. (2020), Castillo-Nava et al. (2020) and Bartholomew et al. (2020), respectively. In this study, samples were sieved through a 100 mesh (154 micron) and stored in the laboratory to analyze.

Analytical procedures
Street dust samples collected and pre-treated in this study were analyzed by using Wavelength Dispersive X-Ray Fluorescence (WDXRF) device. The X-ray tube in the device has a power of 4 Kw and operates at 160 mA light current and 60 kV voltage. Rh anode (SST-mAX in model) X-Ray tube is used in the device. K β rays for arsenic (As); L α rays for Uranium (U), Bismuth (Bi), Neodymium (Nd), Lanthanum (La) and Barium (Ba); K α rays for Cerium (Ce), Thorium (Th) and Lead (Pb) and other elements are used. The same method was applied for the analysis of samples and reference material (WEPAL-970). 3 g of the samples were taken and mixed with 0.3 g of cellulose. It was tableted under 30 tons of pressure and analyzed. In order to check the accuracy of the analysis made within the scope of this study, PTEs analysis were performed under the same conditions as the reference material (WEPAL-970) analysis. The mean of repeated analysis, certification values and recovery values were shown in Table S1 for reference materials of PTEs.

Assessment of pollution level
Since the geoaccumulation index (Igeo) and the enrichment factor (EF) provide information about the contribution of a metal to the pollution status of the study area, it is performed to explain the pollution categories. In many studies (Al-Khashman 2013; Ferreira et al. 2022;Zhang et al. 2009) on street dust characterization and source, Igeo and EF have been used for pollution assessment and calculated by using Eq. S1 and S2, respectively). Mn, Al and Fe are among the most common reference elements in the earth's crust in EF calculation (Zhang et al. 2009). In this study, Mn was used as reference element (Huang et al. 2022;Idris et al. 2020).

Health risk assessment method
The United States Environmental Protection Agency (US EPA) developed a method to assess health risks from exposure to metals in dust deposition (USEPA 1996). Health risk assessment is used to estimate potential carcinogenic and non-carcinogenic adverse health effects now or in the future (USEPA 1989). People may be exposed to dust through direct ingestion, inhalation, and skin contact (USEPA 2002). Daily intakes by inhalation (D inh ), ingestion (D ing ) and dermal (D der ) pathways are calculated using Eq. S3-S5. The noncarcinogenic risks (hazard quotient (HQ) and hazard index (HI)) are estimated using Eq. S6-S7. The lifetime average daily dose (LADD inh ) is calculated by adding up the daily intakes of adults and children through inhalation exposure. The LADD inh is multiplied by the carcinogenic slope factor (SF), which represents the maximum probability of heavy metal-induced cancer risk, to estimate the potential carcinogenic risk (CR) using Eq. S8 (USEPA 1989). The descriptions of the parameters and values of reference dose (RfD), and slope factor (SF) of carcinogenic metals in the equations were given in Table S2, and Table  S3, respectively. For the possibility of non-carcinogenic effect of heavy metal in dusts, the HI must be greater than 1, but if it is less than 1, there may be no risk. In addition, a CR value in the range of 1.0E-6 to 1.0E-4 generally indicates an acceptable estimated level of cancer risk (USEPA 1998). In this study, health risk assessment was performed for Cr, Mn, Zn, Pb, Cu, Ni, Co. According to its physicochemical form, Cr may be both carcinogenic (Cr (VI)) and non-cancerogenic (Cr(III)). In this study, Cr was evaluated as a carcinogen, since no distinction was made according to its physicochemical forms.

Statistical analysis
Correlation coefficient analysis (CCA) and principal component analysis (PCA) are widely used to identify possible sources of contaminants as they categorize parameters statistically (Adewumi 2022;Mandal et al. 2016). CCA is used to determine the strength and direction of the relationship between PTEs. Thus, PTEs whose sources are probably similar can be grouped together. Since the data distribution is nonparametric, the Spearman correlation coefficient is preferred in this study. PCA is used to reduce the size of the dataset and organize it into groups (Cai and Li 2019). PCA can make the relationships between PTEs in street dusts simpler to understand.

Elemental concentration
The mean concentration of PTEs content of the street dust was in the decreasing order of Cr, Mn, Zn, Pb, Cu, Ni and Co (58.55,43.73,26.61,8.37,3.81, 2.51, 0.78 mg/kg), respectively. The concentration of all PTEs was below the reference values of the Composition of the Upper Continental Crust (CUCC) (Rudnick and Gao 2014). Although the Cr concentration was not above the reference value, it was the highest among the other elements. The highest of Cr value was determined at the sampling site closest to the oil refinery and on the road where the vehicle repair shops and junkyards. The highest Mn concentration in this study, the second dominant PTE, was determined at the sampling site close to the agricultural lands. The highest Ni concentration was also detected at this sampling site, while other higher concentrations were detected at sampling sites near heavy traffic. The concentration of Zn and Pb were detected at the highest level at sampling sites on the main streets. In addition, Cu had the highest concentration both at this sampling site and at the sampling site closest to the vehicle repair shops and junkyards. The highest Co concentration was also found at the sampling site closest to the vehicle repair shops and junkyards. The spatial distributions of PTEs in street dust samples of Zawiya were mapped using Surfer software. Spatial distributions also revealed that Mn and Ni concentrations are highest in agricultural areas, while others are in traffic-city center and junkyard-heavy traffic activity areas ( Figure 2).
The descriptive statistics such as the mean, median, minimum, maximum, standard deviations, coefficients of variation values for each element were summarized in Table 1 for the sampling sites in Zawiya, Libya.
The relatively high CV indicate the wide variation in concentrations in road dust (Wang et al. 2022). In the study by Huang et al. (2022), it was stated that PTEs species with a CV value higher than 0.9 may be strongly affected by anthropogenic sources (Huang et al. 2022). In the study conducted by Yang et al. (2015), CV was evaluated in three groups (CV<0.2, 0.2< CV<1, CV>1) (Yang et al. 2015). In another study by Soltani et al. (2015) the elements under investigation were grouped depending on whether they were greater or less than 0.4. For the sources of the elements, it can be said that natural sources dominate at a lower CV value, while anthropogenic sources dominate at a higher CV value. This evaluation applies to urban dusts as they are thoroughly mixed with the effects of both erosion and wind before they are deposited (Soltani et al. 2015;Yongming et al. 2006). Although a CV value higher than 0.9 and 1.0 was not obtained for PTEs in this study, the CV of Cu (71.2%) and Co (51.0%) was higher than 0.4, indicating the anthropogenic origin of the elements in street dust.
Since the urban area is affected by many sources, such as industrial, residential, and agricultural sources, the classification of the study area according to land usage may provide convenience for evaluations. Co was the highest mean concentration in Group 2 and the lowest mean concentration in Group 1 (Group 2> Group 3> Group 4> Group 1). It was seen that the mean concentrations of Mn and Zn, Cu and Pb as well as Cr and Pb were similarly distributed according to the classification of the sampling sites. Although Cr and Pb had the highest mean concentrations in Group 3, the lowest mean concentrations were observed in Group 4 (Group 3> Group 2> Group 1> Group 4). In addition, it was found that the highest mean concentrations for Mn and Ni were in the Group 2 and the lowest mean concentrations were in Group 3 (Group 2> Group 4> Group 1> Group 3). Moreover, Cu and Zn were highest in Group 2 and lowest in Group 4 (Group 2 > Group 3 > Group 1 > Group 4). Mean concentration of PTEs according to land uses in the study area were shown in Figure 3. When the activities that dominate the study area are evaluated in general, the activities at the sites where the pollutant parameters are determined at the highest concentration can be considered as a source of pollution. It is worth noting that while traffic has a significant impact on the first three groups (city center, junkyards, and oil refinery, respectively), agricultural activities dominate in the last group. Therefore, it can be considered that most of the PTEs (Co, Cu Mn, Ni and Zn) reached the dominant level in Group 2 due to junkyards and traffic effect. In Group 3, where oil refinery and traffic activities   were at the highest level, Cr and Pb were dominant. In Group 4, none of the PTEs were dominant. Here we can think that this may be due to the natural structure of agricultural activities and the distance from polluting sources at these sampling sites.
In the study by (Wang et al. 2022), it was determined that Cu, Ni and Pb concentrations were high in industrial areas. In addition, Cr, Cu and Zn concentrations were higher in cities with high traffic flow than in cities with low traffic flow. Moreover, it was determined that Cr, Ni, Pb, Cu, and Zn concentrations were higher in industrial and commercial areas. For example, Cr is a waste product found in large amounts in oil refining processes (Bhattacharyya and Shekdar 2003). For Co, Cr, Cu, Ni, Pb and Zn, the results obtained in this study were similar to those in the areas where industry and traffic activities are effective, as mentioned in these references. This may be resulted from the suspension of PTEs settling on the road surface due to various human activities and complex road conditions in commercial areas with high human and vehicle flow capacity (Wang et al. 2022). Natural sources, or a mix of natural and anthropic sources, can be considered a source of Mn in street dust (Moskovchenko et al. 2022). Although the highest Mn concentration was determined in the agricultural area in this study, higher concentrations were also detected in the traffic and junkyard areas. In this study, the highest Ni concentration was determined in the agricultural area and the higher concentrations were obtained in the traffic areas. Beside Cr is caused by animal manure and organic fertilizers (Sellami et al. 2022), and the possible contribution of transportation enabled the detection of high Cr and Pb concentrations on the main street (Issa and Alhanash 2020). Pb accumulation on the street is a result of multiple industrial activities (Mandal et al. 2016) and particulate vehicles (Phi et al. 2017). In the study conducted by (Sellami et al. 2022), it was determined that there is a relationship between the Pb and Zn concentrations at the sampling sites dominated by an uncontrolled domestic landfill and industrial wastes. As a result, both Pb and Zn originate from anthropogenic sources such as traffic, vehicle emissions, particulates from wear and tear on brakes and tires, and the local industrial groups. In addition, mining activities, local industrial pollution, fertilizers, pesticides, sewage sludge and car brake particles from car brakes are some of the main sources of Cu (Sellami et al. 2022). In the light of all this information, due to the effects of industries of oil  refinery and junkyards, the results of this study were in line with the previous literature. Moreover, the effect of traffic was clearly seen in this study for Pb, Ni and Cu. For all these reasons, considering all selected sampling sites, pollutants were dominant in the sampling sites representing traffic-city center and junkyard-heavy traffic activities. Concentration of PTEs determined in this study were compared with some studies conducted in countries neighboring Libya and in different cities in the worldwide (Table 2). Since the results obtained can be directly affected by the development level and geographical structure of the study area, it is an expected result that each study will have some differences and some similarities. The mean Co, Cu and Mn concentrations reported in this study were lower than that of those in all other countries. In addition, the mean Cr concentration was lower than concentrations in Jinhua, China, Busan, Korea, Khamees-Mushait, Saudi Arabia, Delta region, Egypt. Moreover, the mean Ni, Pb and Zn concentrations were higher than concentrations in only Bolgatanga, Ghana. Another comparison was also carried out according to the ratio of each PTE concentration to the total concentration of PTEs (TPTEs) for each study in countries. Accordingly, it was seen that the PTE/TPTEs slopes for each parameter had the same tendency in the studies conducted in Libya and Turkey. It was observed that PTE/TPTEs slopes were the same trend for each parameter except Cu for Mexico, China, Korea, Egypt; Co for Russia; Zn for Saudi Arabia; Cu and Zn for Algeria; Co, Cr and Cu for Nigeria; Co, Cu and Zn for Ghana. As mentioned before, it can be said that the reason for the different results is the differences in the development level and geographical structure of each study area. In the study areas, the social and economic situation, climatic conditions, traffic density, local polluting factors and the geochemical structure of the soil can be listed as the factors affecting the formation of street dust and the reasons for obtaining different results (Taşpınar and Bozkurt 2018).

Geo-accumulation Index (Igeo)
The loss of originality of the land structure makes it challenging to access background data (Verma, Kumar, and Yadav 2020), especially when considering junkyards and oil refinery activities. Therefore, minimum concentration of PTEs were used as background values in previous studies (Chan et al. 2001). The Igeo values for different land use showed different PTE contamination levels. The mean Igeo value of PTEs ranged from −0.13 (Mn) to 3.14 (Co) and displayed the decreasing order of Co>Cu>Cr≈Pb>Zn>Ni>Mn. The spatial distributions of Igeo values for each PTE were visualized in Figure 4. Igeo spatial distribution   Figure 5 revealed that the study area was uncontaminated with Mn. Furthermore, the index revealed that the study area was categorized as uncontaminated to moderately contaminated with Ni, Zn, Pb and Cr. Co and Cu had the highest Igeo values and due to these values, the study area was evaluated as moderately to heavily contaminated. It was observed that 50% of Co, and 40% of Cu data were moderately contaminated. In comparison, 0.71% of Pb, 0.68% of Zn, 0.65% of Ni 0.52% of Cr data were found in the category of contaminated to moderately contaminated. Only Mn had most of the data (77%) in the uncontaminated category. In this study, Igeo was also evaluated according to four sampling groups. Group 2 has the highest Igeo value calculated for PTEs excluding Cr and Pb in terms of 4 groups. For PTEs, Igeo values in Group 2 were above average values. In Group 3, except for Ni and Mn, PTEs Igeo values were above the average value. The calculated Igeo values for Co, Cu and Cr were below the mean in Group 1 and Group 4. Igeo values calculated for PTEs except Co, Ni and Mn were the lowest in Group 4. Briefly, Groups 2 and 3 represent the most geochemically contaminated sampling sites.

Enrichment Factor (EF)
Mn was used as a reference element in this study because it is one of the most suitable metals that can be accepted as a reference element due to its abundance on earth crust (Huang et al. 2022;Idris et al. 2020). The Composition of the Upper Continental Crust (CUCC) (Rudnick and Gao 2014) was used as the reference soil composition when calculating the EF value.
EF values for different land use indicated different PTE enrichment category. The mean EF value of PTEs ranges from 0.96 (Ni) to 11.71 (Cr) and shows the decreasing order of Cr>Pb>Zn>Cu>Co>Ni. Spatial distribution maps of EF values were prepared for each PTE Figure 6. EF spatial distribution maps show that Co and Ni have the highest EF values at sampling sites close to the agricultural area.
Although the EF values obtained in the study area were not at very high enrichment level, they were determined at significant enrichment, moderate enrichment and deficiently to minimal enrichment levels (Figure 7). EF values of Cr, Pb and Zn exhibited a significant enrichment (5≤ EF<20), indicating that some sampling sites were affected by anthropogenic sources. Although only EF value of Cu was found in the moderate enrichment category, significant enrichment was observed especially at the sampling sites close to area of traffic, commercial and gas stations. EF values of Co and Ni were in the category of deficiently to minimal enrichment. These results were in line with similar studies that emphasized the importance of anthropogenic sources (Kamani et al. 2015;Marjovvi et al. 2022).
The sampling sites were classified into 4 groups according to their characteristics. The EF interpretation above for each group is valid because it is in the same enrichment factor range. However, the difference between the EF values of the groups can be seen here even though they are in the same pollution definition range. For Cr and Pb EF values, Group 1 and 3 are above the average EF value. In addition, for the Zn and Cu EF values, Group 1, 2 and 3 are above the average EF value. Furthermore, Group 1, 2 and 4 were above the average EF value

Health risk assessment
In this study, possible cancer and non-cancer risks from exposure to PTEs in street dust were calculated using the US EPA human health risk assessment method for both children and adults. Calculations of the human health risk were given in Table 3 for both cancer and non-cancer categories.
Ni, Co, and Cr cancer risk values were calculated as 2.1E-10, 7.6E-10 and 2.5E-07 for the assessment of lifetime cancer risks by inhaling carcinogenic PTEs in street dust. In addition, the total cancer risk value was determined as 2.5E-07. Cr had the highest cancer risk value. While Co was in the second place, the lowest cancer risk value was calculated for Ni. These cancer risk values were lower than 10E-6, showing no lifetime cancer risk for exposure to PTEs in street dust by inhalation in Zawiya. However, considering the effects of oil refinery and traffic-related pollutants, it should not be concluded that PTEs do not pose a risk in the future.
HI values were determined between 8.1E-05 (Co) and 3.7E-02 (Cr) and ∑HI was 4.2E-02 in the determination of non-carcinogenic health risks for adults. HI values for children ranged from 1.6E-03 (Ni) to 2.9E-01 (Cr), and ∑HI was 3.3E-01. Since the ∑HI for adults and children were lower than 1, indicating no significant non-carcinogenic health risks to people. However, health risks for children were about eight times higher than those of adults. According to the routes of exposure, the health risk levels of children appear to be ingestion risk (2.9E-01) > dermal risk (3.6E-02) > inhalation risk (1.0E-02), respectively. However, although the highest health risk level for adults was determined for ingestion risk (3.1E-02), the inhalation risk (5.8E-03) was higher than the dermal risk (5.5E-03). The Cr health risk value was calculated as the highest of all exposure routes for both children and adults. Fortunately, each HQ and HI for all PTEs are less  than 1, indicating that exposure to PTEs in street dust has no significant non-carcinogenic risks for both adults and children.

Correlation coefficient and principal component analysis
Correlation coefficient analysis (CCA) was used to evaluate the relationship between PTEs. Figure 8 shows the correlation coefficients between concentrations of PTEs in the street dust samples. There were moderate and significant strong positive correlations between PTEs except for Co, indicating that they were derived from a similar source. Mn had a moderately positive significant relationship with Zn and Ni. In addition, Zn had a strong positive significant correlation with Cu and Pb, while Zn had a moderately positive significant correlation with Cr and Mn. Pb and Cu were moderately positive and significantly correlated.
In PCA, suppress small coefficients (absolute value: 0.30) option was selected and Varimax was used as the rotation method. PCA results showed that there were 3 eigenvalues greater than 1 and the 3 principal components represented a total 77.406% of the variance (Table 4). Principal component 1 (PC1) represented 36.700% of the total data variance. PC1 was heavily loaded with Zn, Pb and Cu, while it was moderately loaded with Mn and Cr (Table 4). In the Igeo and EF evaluations, it was observed that Cr, Pb and Zn were in the same pollution level category. The highest concentrations were determined for Zn, Pb and Cu at the Group 1 sampling site, while for Cr and Mn at the Group 3 and Group 4 sampling sites, respectively. Moreover, these five metals were positively correlated (P < .05) (Figure 8), showing similar sources. Representing 23.482% of the total data variance, PC2 was heavily loaded with Ni and Mn, which were in the same pollution level category. Furthermore, Ni and Mn, had their highest concentration at the Group 4 sampling site and they were positively correlated. For these reasons, it can be deduced that they may be affected by similar sources. PC3 constituted 17.224% of the total data variance. Although PC3 was heavily loaded with Co and Cr, they were not in the same pollution level category. The highest Co and Cr concentration values were detected in Group 2 and Group 3, which are very close to each other, respectively. However a significant correlation could not be found between them.

Conclusion
Street dust samples from Zawiya street dust, predominantly affected by agriculture, trade, traffic, junkyards and oil refinery activities, were collected to analyze PTEs and evaluate their contamination levels and environmental impacts. The PTE concentration of street dust was found as Cr (58.55 mg/kg), Mn (43.73 mg/kg), Zn (26.61 mg/kg), Pb (8.37 mg/kg), Cu (3.81 mg/kg), Ni (2.51 mg/kg), Co (0.78 mg/kg) in decreasing order. The following conclusions can be withdrawn from this study: • When the oil refinery and junkyards were considered as industries for this study, the results were in line with the literature. In addition, the effect of traffic was observed in this study. For all these reasons, considering all selected sampling sites, pollutants were dominant in the sampling sites representing traffic-city center and junkyard-heavy traffic activities. • Most of the PTEs (Co, Cu, Mn, Ni and Zn) reached the dominant level in Group 2 due to junkyards and traffic effect. • The detected PTE contents were not considerably high compared to other studies. The study results clearly showed that traffic and industrial activities strongly impact the environment in the urban area. • Co and Cu had the highest Igeo values, and due to these values, the study area was evaluated as moderately to heavily contaminated. Although the average Igeo values show moderately to heavily contaminated level, it was observed that it was at heavily contaminated levels at some sampling sites. • EF values of Cr, Pb and Zn exhibited a significant enrichment, indicating that some sampling sites were affected by anthropogenic sources. Therefore, it is necessary to take immediate measures to prevent the pollution level from increasing further. • There was no lifetime cancer risk for exposure to PTEs in street dust by inhalation in Zawiya. However, considering the effects of industries and traffic-related pollutants, it should not be concluded that PTEs do not pose a health risk in the future. • Cr were determined to be the highest risk PTEs via all exposure routes for both children and adults. Fortunately, each HQ and HI for all PTEs are less than 1, indicating that exposure to PTEs in street dust has no significant non-carcinogenic risks for both adults and children. • Zn, Pb, Cu, Mn and Cr were positively correlated, and also these five PTEs were represented in 36.70% of the total data variance in PCA analysis. The CCA and PCA indicated that these were associated with traffic and industrial activities in urban area. • Since street dust is affected by the geochemical structure of the soil, the social and economic situation of the region, climatic and meteorological conditions, traffic conditions and local polluting factors, the results obtained in each study are an essential environmental indicator for that region. Therefore, these results may be used in the planning of activities such as the determination of transport roads, residential, industrial, and green areas to improve the environmental and health management quality in the study areas.