Sources, Distribution, and Health Implications of Heavy Metals in Street Dust across Industrial, Capital City, and Peri-Urban Areas of Bangladesh

Abstract

Heavy metals in road dusts can directly pose significant health risks through ingestion, inhalation, and dermal contact. This study investigated the pollution, distribution, and health effect of heavy metals in street dust from industrial, capital city, and peri-urban areas of Bangladesh. Inductively coupled plasma mass spectrometry (ICP-MS) examined eight hazardous heavy metals such as Zn, Cu, Pb, Ni, Mn, Cr, Cd, and Co. Results revealed that industrial areas showed the highest metal concentrations, following the order Mn > Zn > Cr > Pb > Ni > Co > Cd, with an average level of 444.35, 299.25, 238.31, 54.22, 52.78, 45.66, and 2.73 mg/kg, respectively, for fine particles (≤20 μm). Conversely, multivariate statistical analyses were conducted to assess pollution levels and sources. Anthropogenic activities like traffic emissions, construction, and industrial processing were the main pollution sources. A pollution load index revealed that industrial areas had significantly higher pollution (PLI of 2.45), while the capital city and peri-urban areas experienced moderate pollution (PLI of 1.54 and 1.59). Hazard index values were below the safety level of 1, but health risk evaluations revealed increased non-carcinogenic risks for children, especially from Cr, Ni, Cd, and Pb where Cr poses the highest cancer risk via inhalation, with values reaching 1.13 × 10⁻⁴–5.96 × 10⁻⁴ falling within the threshold level (10⁻⁴ to 10⁻⁶). These results underline the need for continuous environmental monitoring and pollution control in order to lower health hazards.

1. Introduction

Environmental pollution is a global concern, causing human mortality 15 times higher than that from wars and other forms of violence [1,2]. Each year, an estimated 9 to 12 million deaths are linked to air pollution [3]. Another paper shows that air pollution resulting from burning fossil fuels is causing an alarming 5 million extra deaths per year, globally [4]. Air is being polluted through various means, including industrial emissions, transportation, household waste incineration, and biomass burning [5]. Industrial processes, transportation, and fuel combustion generate toxic elements, which can be suspended in street dust [6].

Suspended street dust causes significant toxic metal pollution in many industrial, city, and peri-urban areas; these metals are resistant to biodegradation and poisonous; a few of them are carcinogenic according to the International Agency for Research on Cancer [7]. Most toxic metals contaminate the environment and the atmosphere, posing severe hazards to humans as they become highly toxic when combined with water, soil, and air, by entering the food chain and exposing live entities [8]. Heavy metals like Cu, Zn, Ni, Cr, Mn, Cd, Co, and Pb released in nature are present in suspended street dust and create possible health problems to persons living near highways [9]. Trapping metals from many sources, this dust serves as a sink [10]. With its finer particle size and higher specific surface area relative to soils [11,12], street dust helps re-suspension of heavy metals (HMs), which may enter into the human body through ingestion, inhalation, and skin contact, thus posing health hazards to urban residents [13,14]. Moreover, vehicle exhaust runoff can dissolve a good amount of heavy metals from suspended street dust and distribute them to surrounding water bodies, thus creating different ecological hazards [15]. Wameq reported that Dhaka, Bangladesh, ranked as the second most polluted city in the world [16]. With regard to air quality, Bangladesh ranks among the lowest performing nations in the world [17]. Rapid urbanization, poor infrastructure, automobile pollution, and traffic congestion are major contributors to this problem [18]. The capital city has undergone rapid and unplanned urbanization over the past few decades [19]. Urbanization is still ongoing, with peri-urban areas expanding more rapidly than traditional city centers. This urban sprawl has led to an increase in soil and air pollution [20], which poses significant health risks [21]. High degrees of air pollution in Bangladesh greatly raise the risk of respiratory problems including coughing, lower respiratory infections, and mood disorders along with other health problems in urban and industrial areas [22]. The primary causes of this problem are element enrichment in suspended street dust due to poor transportation, unplanned industrial activities, and other anthropogenic factors [23,24]. Exhaust fumes from vehicles discharge toxic elements like heavy metal into the air; this is mainly due to poorly maintained vehicles, adulterated fuel, improper traffic and road management, and insufficient parking spaces [18]. Despite awareness of the health risks posed by heavy metal pollution in street dust, there has been limited action to mitigate these hazards [25]. Numerous studies on street dust in Dhaka, the capital city, have explored its metal composition and the related health risks [26,27,28,29,30,31]. However, there has been limited research on heavy metal pollution in street dust within Bangladesh’s industrial and peri-urban settings. Therefore, research needs to address heavy metal pollution in street dust for smaller particle sizes in peri-urban regions as well as industrial areas. Thus, this study intends (i) to investigate the distribution of toxic heavy metal in street dust across Dhaka and industrial, capital city, and peri-urban areas based on two particle sizes and (ii) to evaluate pollution levels and health hazards.

2. Materials and Methods

2.1. Study Site

The study was conducted in and around Dhaka, the capital city of Bangladesh (Figure 1). These locations were categorized into 3 distinct areas: industrial, capital city, and peri-urban areas. The industrial area included Madanpur bus stand in Narayanganj (S1), Gazipur Chowrasta (S2), Cheragali Tongi (S3), and Rajendrapur Gazipur (S4). The capital city areas encompassed Saidabad stand in Dhaka (S5), Mogbazar Chowrasta in Dhaka (S6), Gabtoli bus stand in Dhaka (S7), and Savar bus stand in Dhaka (S8). The peri-urban area covered the Golara bus stand in Manikganj (S9), Mymensingh Bypass (S10), Mymensingh Bridge Mor (S11), Bathuli in Manikganj Sadar (S12), Barera in Manikganj Sadar (S13), the Araihazar bus stand in Narayanganj (S14), and Nothullahban bus stand in Barishal (S15). The topography of this area is relatively flat, with an elevation ranging from 0.5 m to 12 m [32]. Bangladesh experiences a tropical monsoon climate, characterized by high temperatures, high humidity, and significant seasonal variations in rainfall. Despite these seasonal changes, the spatial variation in climate across the country is minimal. Bangladesh has four distinct seasons: the dry winter season (December to February), the hot pre-monsoon summer (March to May), the hot and humid monsoon summer season (June to September), and the post-monsoon autumn (October to November) [33]. During summer, the maximum temperatures typically range between 38 °C and 41 °C. As of 2022, the populations of Dhaka, Gazipur, Mymensingh, Narayanganj, and Barishal were approximately 10.22 million, 2.67 million, 0.58 million, 0.97 million, and 0.42 million, respectively [34]. Around 1.81 million vehicles operate within the capital city [35], and more than 80% of these vehicles in daily use on the streets of Dhaka city are defective and emit huge quantities of black smoke [36]. This area has experienced with unplanned growth, unregulated silt from buildings and constructions, and extensive roadworks during the rainy season [19].

2.2. Street Dust Sampling and Preparation

During the hot and humid monsoon summer season (June to September) of 2023, street dust samples were collected from 15 busy-traffic streets of Bangladesh. The sampling locations were categorized into three functional areas, namely industrial, capital city, and peri-urban areas. Dust samples were taken using a nylon brush and dustpan, sweeping both sides of the road. Approximately 500 g of street dust was collected from each test location by randomly sweeping a 1 m² area, including streets, pavements, and gutters [37]. At least five samples were collected at each location, combined into a bulk to make a representative dust sample, and placed in clearly marked plastic bags (Figure 2). These samples were sealed and sent to the laboratory for processing. Upon arrival at the Bangladesh Institute of Nuclear Agriculture (BINA) substation in Barishal, the samples were initially left to air dry for 1 week. They were subsequently passed through a 2.0 mm nylon mesh sieve to eliminate debris and small stones. Further sieving took place at the Saitama University Pollution Control Laboratory in Japan, where an AS 200 digit Retsch vibratory sieve shaker was employed. This device was set to an amplitude of 60 and shaken for 20 min, producing two distinct particle size fractions: ≤20 µm and 20–32 µm. These fine dust particles were then analyzed for the detection of toxic heavy metal presence.

2.3. Sample Processing and Determination Procedure

To measure metal concentrations, 50 mg samples of roadside dust, consisting of particles sizes of 20–32 μm and ≤20 μm, were first oven-dried. These samples were then transferred into 100 mL conical flasks. Subsequently, 20 mL aqua regia made up of 5 mL of 63% HNO₃ and 15 mL of 36% HCl was added to each flask. Samples were heated on a hot plate for 90 min at 150 °C, until the reddish-brown fumes no longer emerged (Figure 3). The resulting digests were then reduced to approximately 1 mL or until they were nearly dry. Once cooled to room temperature, the samples were diluted to a final volume of 20 mL with 2% nitric acid. Next, the samples were filtered using Whatman filter paper (5C, 110 mm diameter, 11 µm pore size) and kept in a refrigerator at 4 °C temperature until analysis. Aqua regia was prepared using analytical grade reagents (HNO₃ and HCl), and Type-1 (Milli-Q) water was utilized for the preparation of solution. Heavy metal analysis was conducted using inductively coupled plasma mass spectrometry (Perkin Elmer ICP-MS NexION 350 D) at the Center for Environmental Science in Saitama, Japan. The analysis was conducted under the following conditions: a plasma gas flow rate of 18.00 L/min, an auxiliary gas flow rate of 1.20 L/min, a nebulizer gas flow rate of 0.98 L/min, and with plasma power set to 1600 W. The procedure began with the dilution of the sample using 3% HNO₃, followed by the addition of an internal standard solution (Y). The ICP-MS was then turned on, and the instrument was tuned using a tuning standard solution to establish and fix the analytical conditions. Finally, the instrument’s condition was checked using the tuning standard solution. Calibration curves were created using multi-elemental standard XSTC-662 solutions (Spex certi Prep, Metuchen, NJ, USA). Curves with an R² value above 0.999 were deemed acceptable for calculating concentrations.

2.4. Quality Control/Quality Assurance (QC/QA)

QC/QA protocols were followed for metal estimation in roadside dust samples. Glassware utilized in the analyses was meticulously rinsed with deionized water after being acid-washed. Reagent blanks underwent the same digestion procedure as the samples, processed simultaneously. As part of quality control, the method’s percentage recovery was evaluated using a triplicate CRM (certified reference material), which were prepared and digested alongside the samples. Ensuring the relative standard deviation, each digested sample solution was analyzed 3 times and repeated measurements did not exceed 5%. Satisfactory elemental recoveries were achieved from the CRM, with values of 107% for Cu, 100% for Zn, 93% for Mn, 85% for Cr, 95% for Co, 86% for Pb, 97% for Cd, and 85% for Ni. Standards were recalibrated after every ten measurements. The limits of LOD for Mn, Cr, Cu, Ni, Co, Zn, Pb, and Cd were 0.041 ng/mL, 0.018 ng/mL, 0.048 ng/mL, 0.088 ng/mL, 0.009 ng/mL, 0.067 ng/mL, 0.085 ng/mL, and 0.001 ng/mL, respectively [23].

2.5. Methods of Estimating Pollution Indices

A variety of methods and indices were employed for a thorough assessment of toxic metal pollution in roadside dust. The most commonly used indices for this assessment are a geo-accumulation index (I_geo), pollution load index (PLI), and a pollution factor (CF). These indices are derived using the natural background values of metals present in sediments and soils. The evaluation of metal pollution indices in roadside dust is greatly influenced by the background values applied in this assessment. As there are no documented background values for metals in roadside dust specific to Dhaka city, we utilized global soil background values, which are a widely accepted geochemical background. The global soil background values for Cr, Mn, Ni, Zn, Cu, Pb, Co, and Cd are 59.5 mg/kg, 488 mg/kg, 29 mg/kg, 70 mg/kg, 38.9 mg/kg, 27 mg/kg, 11.3 mg/kg, and 0.2 mg/kg, respectively (Table 1). I_geo and CF are used to measure individual contaminants and indicate pollution levels. Unlike CF, I_geo incorporates a logarithmic function and includes a constant factor of 1.5 to account for lithogenic effects and variations in background values. PLI and Er are used to evaluate the combined effects of multiple pollutants on the environment. These indices are chosen for their simplicity in calculation and interpretation, and their comparability with global studies.

2.5.1. Geo-Accumulation Index (I_geo)

The I_geo is employed to measure the level of pollution by harmful element, categorizing it into 7 enrichment classes based on the index’s increasing numerical values shown in Table 2. The Igeo index served as a numerical gauge to evaluate the degree of heavy metal pollution in dust [38] compared with baseline levels of heavy metals on Earth crusts. It is expressed as follows:

$$I_{geo}={Log}_2\left[{\displaystyle \frac{C_n}{1.5\times B_n}}\right]$$

(1)

Here, $C_n$ denotes the heavy metal concentration in the tested samples, whereas $B_n$ denotes baseline levels of metals, derived from the soil background values.

Table 1. Global soil background value [39].

Heavy Metals	Global Soil Background Value (mg/kg)
Mn	488
Zn	70
Cu	38.9
Pb	27
Cr	59.5
Co	11.3
Ni	29
Cd	0.2

Table 1. Global soil background value [39].

Heavy Metals	Global Soil Background Value (mg/kg)
Mn	488
Zn	70
Cu	38.9
Pb	27
Cr	59.5
Co	11.3
Ni	29
Cd	0.2

Table 2. Geo-accumulation index classification for [40].

Igeo Value	Classes	Soil Condition
≤0	0	Uncontaminated
0–1	1	From uncontaminated to moderately contaminated
1–2	2	Moderately contaminated
2–3	3	Moderately to strongly contaminated
3–4	4	Strongly contaminated
4–5	5	Strongly to extremely contaminated
>6	6	Extremely contaminated

Table 2. Geo-accumulation index classification for [40].

Igeo Value	Classes	Soil Condition
≤0	0	Uncontaminated
0–1	1	From uncontaminated to moderately contaminated
1–2	2	Moderately contaminated
2–3	3	Moderately to strongly contaminated
3–4	4	Strongly contaminated
4–5	5	Strongly to extremely contaminated
>6	6	Extremely contaminated

2.5.2. Pollution Factor for Suspended Street Dust Heavy Metals

Pollution factor is usually denoted as CF, which is defined as the ratio of metal concentration present in suspended street dust to its concentration in the background soil. CF is determined using the following equation:

$$CF={\displaystyle \frac{C_n}{B_n}}$$

(2)

Here, C_n represents the toxic heavy metal concentration in suspended street dust, and B_n, denotes the background value of the heavy metals [41]. The CF classification is as follows: CF < 1 denotes ‘low pollution’, 1 < CF < 3 denotes ‘moderate pollution’, 3 < CF < 6 represents ‘considerable pollution’; and CF > 6 shows ‘very high pollution’ [42].

2.5.3. Pollution Load Index

The PLI offers a summary of the total pollution load from toxic metals at a site. It is calculated as the nth root of the product of the CF for the metals present. The PLI for a specific site was determined using the following formula:

$$PLI=({CF}_1\times {CF}_2\times {CF}_3.............{\times CF}_n{)}^{1/\mathrm{n}}$$

(3)

Here, CF denotes the pollution factor for single elements. PLI < 1 represents ‘no pollution’, PLI = 1 shows that only background levels of pollution are present; and PLI > 1 represents the deterioration of the site.

2.5.4. Ecological Risk for Suspended Street Dust Heavy Metals

To assess quantitatively the ecological risk (Er) of a contaminant in each specific site, the following equation is applied:

$$Er=Tr\times CF$$

(4)

Based on the accumulated values, the Tr values for the metals are as follows: Cr = 2, Mn = 1, Zn = 1, Pb = 1, Cu = 1, Co = 1, Ni = 1, and Cd = 30. Here, Tr denotes the level of toxicity that the metals pose to the environment, while CF represents the pollution factor [43]. According to the risk factors, the classification is as follows: Er < 40 is considered ‘low potential ecological risk’; 40 < Er < 80 is ‘moderate potential ecological risk’; 80 ≤ Er < 160 is ‘significant potential risk’; 160 ≤ Er < 320 is ‘high ecological potential risk’; and Er > 320 is ‘very high potential risk’ [44].

2.5.5. Principal Component Analysis (PCA)

PCA is a statistical method that reduces the dimensionality of a dataset while maintaining most of the data’s variability. This technique converts the original variables into new, uncorrelated variables known as principal components, which are ranked according to the amount of variance they capture from the data.

2.5.6. Pearson’s Correlation Analysis (CA)

CA is a statistical technique which is used to assess the intensity and trend in the direct correlation between two variables. In this research, CA has been applied to assess the relationships between various toxic elements found in street dust originated from industrial, capital city, and peri-urban areas.

2.5.7. Hierarchical Cluster Analysis (HCA)

HCA is a statistical analysis method using the average linkage (between groups) which acts to find clusters of heavy metals that might share common sources or behaviors in the urban environment. In this study, HCA has been conducted using SPSS 25 software, employing the average linkage method (between groups) and Euclidean distance as the measure of homogeneity. The resulting dendrogram gives a visual representation of the clustering process, illustrating the relationships among the heavy metals.

2.6. Health Risk Assessment for Suspended Street Dust Heavy Metals

The primary pathways for toxic metal exposure include inhalation and ingestion as well as dermal contact. This research investigates carcinogenic and non-carcinogenic risks, using risk characterization models developed by the US EPA [45,46]. Average daily doses (ADDs) of heavy metals from suspended street dust were estimated utilizing health risk assessment models, expressed as follows:

$${ADD}_{ing}=\mathrm{C} \times {\displaystyle \frac{IngR\times EF\times ED}{BW\times AT}}\times {10}^{-6}$$

(5)

$${ADD}_{inh}=C\times {\displaystyle \frac{I\mathrm{n}\mathrm{h}R\times EF\times ED}{PEF\times BW\times AT}}$$

(6)

$${ADD}_{dermal}=C\times {\displaystyle \frac{AF\times SA\times ABS\times EF\times ED}{BW\times AT}}\times {10}^{-6}$$

(7)

For lifetime average daily dose (LADD) calculation, the model (8)–(10) was employed for computing the lifetime average daily doses concerning Cd, Cr, and Ni, referencing studies [47] and US EPA reports [48,49]. The formulation is outlined below:

$${LADD}_{ing}={\displaystyle \frac{C\times EF}{AT}}\times \left({\displaystyle \frac{{IngR}_{child}\times {ED}_{child}}{{BW}_{child}}}\times {\displaystyle \frac{{IngR}_{adult}\times {ED}_{adult}}{{BW}_{adult}}}\right)\times {10}^{-6}$$

(8)

$${LADD}_{inh}={\displaystyle \frac{C\times EF}{AT\times PEF}}\times \left({\displaystyle \frac{{InhR}_{child}\times {ED}_{child}}{{BW}_{child}}}\times {\displaystyle \frac{{IngR}_{adult}\times {ED}_{adult}}{{BW}_{adult}}}\right)$$

(9)

$${LADD}_{dermal}={\displaystyle \frac{C\times EF\times ABS}{AT}}\times \left({\displaystyle \frac{{AF}_{child}\times {SA}_{child}\times {ED}_{child}}{{BW}_{child}}}\times {\displaystyle \frac{{AF}_{adult}\times {SA}_{adult}\times {ED}_{adult}}{{BW}_{adult}}}\right)\times {10}^{-6}$$

(10)

Here, C represents the heavy metal concentration under examination. The remaining parameters listed in

Table 3. Referenced population exposure factors for assessing human health risk.

Parameters	Description and Units	Value		Reference
		Child	Adult
PEF	Particle emission factor	1.36 × 109	1.36 × 109	[50]
IngR	Ingestion rate (mg/day)	200	100	[50]
SA	Exposed skin area (cm2)	2800	5700	[50]
InhR	Inhalation rate (m3/day)	7.63	12.8	[51]
ABS	Dermal absorption factor	0.001	0.001	[50,52]
AF	Skin adherence factor (mg/cm2)	0.2	0.07	[50]
ED	Duration of exposure (years)	6	24	[50]
EF	Frequency of exposure (days/year)	350	350	[53]
AT	Average time (days) for non-carcinogens	ED × 365	ED × 365	[54]
Atcan	Average time (days) for carcinogens	70 × 365	70 × 365	[54]
BW	Body weight average (kg)	15	70	[53,55,56]
C	Toxic metal concentration (mg/kg)	This study
CF	Conversion factor (kg/mg)	1 × 10−6		[51]

.

The Hazard Quotient (HQ), Carcinogenic Risk (CR), Hazard Index (HI), and Cumulative Carcinogenic Risk (CCR) for both children and adult were calculated using the following equations and parameters listed in

Table 4. The cancer lope factors (CSF) and reference dose (RfD) for 3 exposure pathways used in the health risk assessment model.

Heavy Metals	RfD (mg/(kg × d))			SF ((kg × d)/mg)
	Ingestion	Inhalation	Dermal Contact	Ingestion	Inhalation	Dermal Contact	Reference
Cr	3.00 × 10−3	2.86 × 10−5	6.00 × 10−5	8.50 × 10−3	4.20 × 101	n/a	[57,58]
Zn	3.00 × 10−1	3.00 × 10−1	6.00 × 10−2	n/a	n/a	n/a	[57]
Pb	3.50 × 10−3	3.52 × 10−3	5.2 × 10−4	8.50 × 10−3	n/a	n/a	[57,59]
Cd	1.00 × 10−3	1.00 × 10−5	1.00 × 10−5	6.1	6.30	n/a	[57,58]
Ni	2.00 × 10−2	2.06 × 10−2	5.40 × 10−3	n/a	8.4 × 10−1	n/a	[57]
Cu	4.00 × 10−2	4.02 × 10−2	1.20 × 10−2	n/a	n/a	n/a	[57]
Co	2.00 × 10−2	5.71 × 10−6	1.84 × 10−3	n/a	9.80	n/a	[60]
Mn	4.60 × 10−1	1.43 × 10−5	1.84 × 10−3	n/a	n/a	n/a	[61]

n/a, data not available.

. The HQ is determined by dividing ADD by the reference dose (RfD) for each heavy metal and exposure pathway. The hazard index (HI) is the total sum of the HQ for a heavy metal across three exposure pathways.

$$HQ={\displaystyle \frac{{ADD}_{ing}}{RfD}}$$

(11)

$$HQ={\displaystyle \frac{{ADD}_{inh}}{RfD}}$$

(12)

$$HQ={\displaystyle \frac{{ADD}_{dermal}}{RfD}}$$

(13)

$${HI=\sum HQ=\sum HQ}_{Ingestion}{+\sum HQ}_{Inhalation}{+\sum HQ}_{Dermal}$$

(14)

$$CR=L{ADD}_{ing}\times SF$$

(15)

$$CR=L{ADD}_{inh}\times SF$$

(16)

$$CR=L{ADD}_{dermal}\times SF$$

(17)

$${CCR=\sum CR=CR}_{Ingestion}{+CR}_{Inhalation}{+CR}_{Dermal}$$

(18)

2.7. Quantitative Analysis

Data processing, statistical analysis, and visualization was performed using SPSS 25 and ArcGISPro. Pearson’s correlation analysis was employed to examine the relationships among different heavy metals. Principal component analysis with varimax rotation and cluster analysis were employed to elucidate the relationships among various toxic metals and to identify their potential sources.

3. Result and Discussion

3.1. Heavy Metal Concentration in Street Dust

3.1.1. Heavy Metal Pollution in Industrial Area Suspended Street Dust

Data from

Table 5. Comparison of heavy metal levels in two sizes of suspended street dust, measured in mg/kg.

Heavy Metals	Study Areas	≤20 μm Particle Size			20–32 μm Particle Size
		Mean	Minimum	Maximum	Mean	Minimum	Maximum
Cr	Industrial areas	238.31	28.96	855.90	86.11	25.19	201.32
	Capital city areas	45.21	26.93	55.07	42.17	29.85	53.31
	Peri-urban areas	198.05	33.77	736.27	146.55	41.26	881.08
Mn	Industrial areas	444.35	233.16	1004.73	230.11	36.39	320.21
	Capital city areas	236.72	194.28	270.36	283.51	214.99	354.65
	Peri-urban areas	369.96	212.18	630.23	322.98	40.42	572.17
Co	Industrial areas	10.93	8.98	14.33	8.81	4.15	12.13
	Capital city areas	9.81	8.39	12.76	9.95	7.94	11.54
	Peri-urban areas	12.88	9.26	20.19	11.76	4.80	24.79
Ni	Industrial areas	45.66	21.71	63.17	36.27	ND	78.47
	Capital city areas	43.27	22.13	100.28	29.93	12.65	46.85
	Peri-urban areas	40.84	20.84	187.21	54.03	ND	606.03
Cu	Industrial areas	54.22	20.45	147.40	19.22	1.79	35.32
	Capital city areas	55.76	21.06	134.53	64.46	14.16	165.22
	Peri-urban areas	34.18	11.55	59.42	33.44	ND	69.79
Zn	Industrial areas	299.25	67.52	826.45	140.76	14.94	350.06
	Capital city areas	205.19	95.05	380.33	271.47	101.06	530.42
	Peri-urban areas	164.50	43.58	367.91	213.69	ND	1528.08
Cd	Industrial areas	2.73	ND	18.57	ND	ND	3.14
	Capital city areas	3.14	2.61	3.90	ND	ND	6.29
	Peri-urban areas	0.22	ND	12.25	ND	ND	3.08
Pb	Industrial areas	52.78	13.41	143.34	20.69	3.58	51.74
	Capital city areas	27.42	15.68	52.87	26.39	9.87	64.33
	Peri-urban areas	23.98	10.21	59.86	23.79	ND	68.13

ND—Non-detectable limit.

reveal that fine dust particles (≤20 μm) generally hold higher concentrations of most heavy metals compared to coarse particles (20–32 μm) across industrial, urban, and peri-urban areas. Fine particle fractions are particularly significant due to their higher mobility and increased concentrations of contaminants [62]. The average concentrations of Mn, Cr, Co, Ni, Cu, Zn, Cd, and Pb for fine particles (≤20 μm) were 444.35, 238.31, 10.93, 45.66, 54.22, 299.25, 2.73, and 52.78 mg/kg respectively. This indicates that finer particles are more prone to heavy metal accumulation in these areas, likely due to direct emissions from industrial processes such as metal smelting, manufacturing, and waste disposal. The large range between minimum and maximum values, particularly for Cr with a range of 28.96 to 855.90 mg/kg, suggests localized sources of contamination, such as specific industrial facilities or practices. The toxic element distribution order for industrial area suspended street dust is Mn > Zn > Cr > Cu > Pb > Ni > Co > Cd. In industrial area suspended street dust, Mn, Zn, and Cr concentration are very high because Mn and Zn come from industrial and traffic emissions [63] and Cr comes from the use of stainless steel alloys industry [64]. The high concentrations of Cr, Zn, Mn as well as other metals in industrial area suspended street dust are largely due to emissions from industrial activities, vehicular wear and tear, and atmospheric deposition. These metals pose significant health and environmental risks, emphasizing the need for effective pollution control and management strategies.

3.1.2. Heavy Metals in Capital City’s Street Dust

In urban areas, particularly in the megacity of Dhaka, the concentrations between the two sizes found were more balanced, whereas peri-urban areas exhibited variable trends depending on the specific metals. This reflects the influence of urban activities, such as vehicle emissions, construction, and the wear and tear of infrastructure, which contribute to the presence of metals like Pb, Zn, and Cu. The smaller variance between the minimum and maximum values in capital city areas (e.g., Pb: 15.68 to 52.87 mg/kg) suggests more uniform sources of pollution, possibly related to widespread urban traffic and commercial activities. Mean concentrations of Mn, Cr, Co, Ni, Cu, Zn, Cd, and Pb for fine particles (≤20 μm) were 236.72, 45.21, 9.81, 43.27, 55.76, 205.19, 3.14, and 27.14 mg/kg, respectively. This result supports the previous research result conducted in Dhaka city [27,28,30]. In their assessment of suspended street dust in Dhaka, they found that Cr, Zn, and Mn were dominant, with Cr concentrations between 100 and 700 mg/kg, Zn between 100 and 500 mg/kg, and Mn between 150 and 600 mg/kg. These values closely aligned with the concentrations found in this study, reinforcing the parallel urban influences on heavy metal distribution. Another study from Mexico City investigated the geographic distribution of heavy metals in roadside dust, concluding that urban form and proximity to industrial activities significantly influenced the levels of these toxic metals [65].

3.1.3. Heavy Metal in Peri-Urban Street Dust

Heavy metal concentrations in peri-urban areas showed variability, particularly in the 20–32 μm size range. This variability can be attributed to mixed land use, including agriculture, small-scale industries, and residential areas. For instance, Ni levels range from non-detectable (ND) to 606.03 mg/kg, indicating sporadic contamination sources such as localized industrial activities or the application of metal-containing fertilizers. For a fine particle size (≤20 μm), the mean concentration of the heavy metals Mn, Cr, Co, Ni, Cu, Zn, Pb, and Cd in peri-urban street dust was 369.96,198.05, 12.88, 40.84, 34.18, 164.50, 23.98, and 0.22, respectively. Ahole [66] found similar results. Cao [67] investigated heavy metal pollution in a peri-urban area soil of Laizhou, China, and identified high concentrations of Cd, Pb, and Hg. The ability of roadside dust to retain metals was influenced by the size of the dust particles. Generally, smaller particles tend to hold more heavy metals because of their high surface area [68]. Fine particles can remain suspended in the air for longer times, increasing the likelihood of adsorbing atmospheric heavy metals before settling on the ground.

3.2. Source Assessment

To conduct source assessment of toxic elements in street dust, principal component analysis (PCA), hierarchical cluster analysis (HCA), and Pearson’s correlation analysis (CA) were performed.

3.2.1. Principal Component Analysis

In this study, PCA was applied to assess the relationships among heavy metals present in city suspended street dust. Principal components were determined using eigenvalues > 1, with the total variations described in Table S1 and loading scores detailed in Table S2. Loading scores have been classified into three categories: ‘strong’ for values greater than 0.75, ‘moderate’ for values between 0.75 and 0.50, and ‘weak’ for values between 0.50 and 0.30 [69,70]. Figure 4 shows the principal component plots in rotated space for metals in the street dust.

(a)

Anthropogenic sources

The first principal component (PC₁) captures 47.9% of the variance, which is the highest variance in the dataset. The high loadings for Zn (0.911), Pb (.881), Cu (0.846), and Mn (0.863) indicate that these metals contribute significantly to PC₁. These loading values suggest that Zn, Pb, Cu, and Mn exhibit a strong correlation, indicating similar sources or behaviors in the urban environment. According to previously calculated pollution indexes, these four metals (Mn, Zn, Pb, and Cu) were the most polluting elements in the suspended street dust of Dhaka City, indicating that they likely originate from anthropogenic activities [65]. Mn, Pb, Zn, and Cu are known to be vehicle-related metals, as noted in the literature [71,72].

(b)

Industrial sources

The second principal component (PC₂), covering 21.0%, has significant loadings for Co (.757) and Ni (0.664). Cr (0.470) also contributes moderate correlation to this component. This indicates a different pattern of association, possibly related to specific industrial or vehicular sources. Lead chromate (PbCrO₄₎ in suspended street dust particles comes from yellow road paint, making it a major source of lead pollution in street dust [72]. However, the presence of Ni and Co are influenced by industrial activities, including the dust from mortar made with cement and lime, used in large buildings, expressways, flyovers, roads, and construction activities in Dhaka city [73].

(c)

Mixed sources

The third principal component (PC₃) is dominated by Cd (0.890) and Ni (0.340), covering only 13.2%, and so also contributes, but to a lesser extent. The weaker correlations for Cd and Ni suggest that these metals did not solely derive from traffic emissions. Instead, they likely originate from a mix of industrial activities, natural sources, and possibly long-range atmospheric transport. Cadmium’s presence in urban environments could be attributed to several sources besides traffic emissions. These include industrial processes such as electroplating, battery production, and waste incineration. Similarly, nickel’s sources are diverse, including emissions from industrial processes such as metal refining and alloy production, fossil fuel combustion, and the wear of nickel-containing materials in vehicles. The high loading of Cd suggests it has a distinct behavior or source compared to the other metals which mostly come from urban transportation and industrial activities [74].

3.2.2. Pearson’s Correlation Analysis (CA)

The elements analyzed include Mn, Cr, Cu, Co, Pb, Zn, Cd, and Ni. The correlation matrix of hazardous elements in street dust is presented in

Table 6. Correlation matrix of hazardous elements in suspended street dust.

Correlation Matrix
HMs	Cr	Mn	Co	Ni	Cu	Zn	Cd	Pb
Cr	1.0
Mn	0.670 ***	1.0
Co	0.569 ***	0.421 **	1.0
Ni	0.420 **	0.180	0.333 *	1.0
Cu	0.409 **	0.572 ***	0.124	0.010	1.0
Zn	0.453 **	0.689 ***	0.108	0.065	0.895 ***	1.0
Cd	0.182	0.057	−0.222	−0.007	0.236	0.156	1.0
Pb	0.442 **	0.715 ***	0.091	0.000	0.794 ***	0.927 ***	0.047	1.0

* indicates significant at p < 0.05, ** indicates significant at p < 0.01, and *** indicates significant at p < 0.001.

. The table includes Pearson correlation coefficients along with their significance levels.

Cu and Zn (r = 0.895 ***) show a very strong positive correlation, indicating that they are likely generated from similar sources, like vehicular emissions and industrial activities. Zn and Pb also show a strong positive correlation (r = 0.927 ***), suggesting common sources such as vehicle engine-related activities and industrial processes. Mn and Zn exhibit a strong positive relation (r = 0.689 ***), implying a possible shared source, possibly related to industrial activities. At the same time, Cr and Mn show a moderate positive correlation (r = 0.670 ***), indicating a likely shared source or similar environmental behavior. Cr and Co also have a moderate positive correlation (r = 0.569 ***), which may indicate industrial or vehicular sources. Cd shows weak or non-significant correlations with most of the other elements, suggesting distinct sources or behaviors. The only exception is a moderate positive correlation with Cu (r = 0.236), though it is not highly significant. Ni generally shows weak correlations with other elements, except for a medium correlation with Co (r = 0.333 *), indicating some degree of association. There is a weak negative correlation between Co and Cd (r = −0.222), which might imply that these elements are influenced by different sources or environmental processes. High and positive correlation coefficients point to common or similar sources for the elements found in suspended street dust, whereas negative correlations imply differing or less common sources [75].

The correlation analysis reveals several significant relationships among the heavy metals in roadside dust. Strong correlations among elements as Cu, Zn, and Pb suggest they are primarily influenced by traffic emissions and industrial activities. The moderate correlations involving Cr, Mn, and Co also point to industrial and vehicular sources. In contrast, the weaker correlations for Cd and Ni imply distinct sources or behaviors in the urban environment. The correlations of Ni with Cu, Zn, Cd, and Pb are particularly low (ranging from −0.007 to 0.065). These low correlations imply that Ni does not show a strong linear relationship with other metals, indicating different sources or factors influencing its concentration compared to the others. The correlations between Co and Cu, Zn, and Pb of 0.124, 0.108, and 0.091, respectively, are also weak. This suggests that Co might not be associated with the same pollution sources or environmental processes as Cu, Zn, and Pb. Cd shows weak correlations with most other metals, except for a slightly stronger relationship with Cu, with a value of 0.236. This could indicate that Cd has distinct sources or behaves differently in the environment compared to the other metals, such as specific industrial processes or emissions. Recent studies have also observed similar relationships between certain toxic elements in the dust of Dhaka [73,74,76,77].

3.2.3. Hierarchical Cluster Analysis (HCA)

The dendrogram illustrates the clustering of eight heavy metals found in industrial, capital city, and peri-urban suspended street dust (Figure 5). Co and Cd cluster together at the lowest rescaled distance, suggesting a strong similarity and potential common source. This could be attributed to industrial activities or vehicular emissions that simultaneously release both metals. Cu and Pb also form a cluster early on, indicating they might share similar sources, such as traffic emissions, brake wear, and tire abrasion. Ni joins the Cu-Pb cluster at a higher rescaled distance, indicating a moderate similarity. This clustering suggests that Ni, Cu, and Pb are possibly co-emitted by industrial processes or vehicular sources. Cr clusters with Zn and Mn at a higher distance level, indicating these metals might be produced from similar sources like construction activities, tear of metal structures, or industrial emissions. The initial cluster of Co and Cd merges with the Cu-Pb-Ni cluster, forming a larger group of metals that might be influenced by a combination of industrial and vehicular sources. Eventually, this large cluster merges with the Cr-Zn-Mn cluster, suggesting a broader similarity among all the metals, likely due to the mixed nature of urban pollution sources potentially originating from industrial activities and traffic-related sources such as tire wear, the use of lubricants, vehicular corrosion, fuel combustion, and engine oil [73]. At the highest distance level, all heavy metals form a single cluster, reflecting the complex and intertwined sources of urban pollution. The clustering pattern highlights that these metals often coexist in the environment, likely due to the multifaceted nature of urban activities. HCA of metals in industrial, capital city, and peri-urban suspended street dust reveals distinct groupings that suggest common sources or similar environmental behaviors.

3.3. Pollution Assessement

3.3.1. Geo-Accumulation Index (I_geo)

The I_geo values for Cr range from approximately 0.0 to 3.0 (Figure 6). Most values fall between 0.0 and 1.5, indicating varying degrees of pollution. Positive I_geo values indicate that the Cr concentrations are higher than the average natural background layers, suggesting moderate pollution. The industrial area (IA) exhibits higher concentrations of Cr, as indicated by the positive Igeo values. In contrast, the capital city area (CCA) and peri-urban area (PUA) show lower levels, with the PUA having the lowest values. This suggests that industrial activities might be the primary source of Cr pollution. The outlier, at around 3.0, suggests a specific site in the peri-urban area (Manikgonj) with notably higher Cr pollution. The I_geo values of Mn range from −2.0 to 1. Negative values indicate that Mn levels in the suspended street dust are generally lower than the natural background levels while a positive value indicates uncontaminated to moderately contaminated levels. Mn shows higher concentrations in IA and PUA compared to CCA. The elevated levels in IA could be attributed to industrial emissions, while the PUA’s levels might be influenced by vehicle emission and construction activities. The I_geo values for Co range from approximately −0.5 to 1. IA has higher Co concentrations compared to CCA and PUA, which indicates that industrial activities are likely contributing more to Co pollution. CCA and PUA show similar levels, suggesting that Co contamination in these areas may come from sources other than industry, such as traffic or localized soil composition. The I_geo values for Ni range from approximately −1.5 to 3.0, with a significant variation across sites. Ni levels are higher in IA, but the difference across regions is less pronounced compared to other elements. This might imply that industrial activities contribute to Ni pollution. The outlier, at around 3.0, indicates a peri-urban area (Manikgonj) site with a particularly high level of Ni pollution, which might be linked to specific industrial activities or heavy traffic in the area. The Cu value ranges from approximately −3.0 to 2.0. Most values are below zero, suggesting that the concentrations of Cu are close to or below natural background levels. The highest levels of Cu are observed in IA, followed by PUA, with CCA having the lowest concentrations. The significant levels in IA suggest industrial sources, while in PUA the presence of Cu might be related to agricultural activities or local industry.

The I_geo values for Zn range from approximately −2.0 to 2.0, indicating moderately polluted levels. Zn levels are relatively similar across the three regions, though IA and PUA have slightly higher concentrations. This suggests that Zn pollution may have multiple sources, including tire wear, industrial discharges, and galvanized materials. The I_geo values for Cd range from approximately 0.0 to 3.0, showing a wide variation in the peri-urban area. Cd levels are significantly higher in PUA compared to IA and CCA. The high Igeo values reflect significant anthropogenic influence, such as industrial emissions, battery waste, and vehicular pollution. The Igeo values for Pb range from approximately −4.0 to 1.0, indicating unpolluted to moderately polluted levels. Pb concentrations are relatively similar across all three regions, with slightly higher levels in IA and PUA.

Positive Igeo values indicate an increase in concentration relative to the natural background level, implying moderate to high pollution likely due to human activities such as vehicular activities and those of industries [74]. Outliers indicate specific locations with notably high pollution levels.

3.3.2. Pollution Factor (CF)

CF values are presented in

Table 7. Pollution factor (CF) of hazardous elements in street dust of industrial, urban, and peri-urban areas.

Heavy Metals	Industrial Area CF	Capital City Area CF	Peri-Urban Area CF
Cr	4	0.76	2.46
Mn	0.91	0.49	0.71
Co	0.97	0.87	1.12
Ni	1.57	1.49	1.18
Cu	1.39	1.43	0.88
Zn	4.28	2.93	2.36
Cd	20.5	15.7	9.15
Pb	1.95	1.02	0.94

to assess the pollution level of toxic elements in street dust samples relative to background values; the pollution factors were computed.

According to the CF classification [42], in industrial areas street dust exhibits substantial pollution for Cr (4.00), Zn (4.28), Cd (20.5), and Pb (1.95), suggesting it originates primarily from industrial activities. Moderate pollution can be observed for Ni, Cu, and Pb, while Mn and Co show low pollution levels. In the capital city area, suspended street dust shows a very high pollution for Cd (15.7). Moderate pollution can be observed for Ni, Cu, Zn, and Pb. Low pollution values are noted for Cr, Mn, and Co. The results suggest that urban activities, including traffic emissions, are major pollution sources. Cd (9.15) also displays very high pollution in peri-urban area suspended street dust. Moderate pollution can be observed for Cr, Co, Ni, and Zn. Low pollution can be noted for Pb, Mn, and Cu in this area.

3.3.3. Pollution Load Index (PLI)

PLI provides an indication of the total pollution load from the accumulation of toxic metals in street dust from industrial, capital city, and peri-urban areas. As shown in

Table 8. PLI of toxic elements in roadside dust from industrial, capital city, and peri-urban areas.

Area	Pollution Load Index (PLI)
Industrial area	2.45
Capital city area	1.54
Peri-urban area	1.59

, the PLI values in all areas under study were greater than 1, indicating a pollution of the site.

In industrial areas, the PLI of 2.45 indicates that the area is experiencing considerable pollution. In capital city and peri-urban area suspended street dust, the PLI values of 1.54 and 1.59 suggest moderate pollution. Previous research has also found high levels of toxic element pollution in dust samples from Dhaka city [74,77,78].

3.3.4. Ecological Risk (Er)

Er measures the potential risks posed by toxic metals in suspended street dust to ecological systems. The levels of potential ecological risk are categorized as follows: low risk for Er < 40, medium risk for 40 ≤ Er < 80, considerable risk for 80 ≤ Er < 160, high risk for 160 ≤ Er < 320, and very high risk for Er > 320.

The ecological risk (Er) values in

Table 9. Er of heavy metals in street dust from industrial, capital city, and peri-urban areas.

Heavy Metals	Industrial Area Er	Capital City Area Er	Peri-Urban Area Er
Cr	8	1.52	4.92
Mn	0.91	0.49	0.71
Co	0.97	0.87	1.12
Ni	1.57	1.49	1.18
Cu	1.39	1.43	0.88
Zn	4.28	2.93	2.36
Cd	615	471	274.5
Pb	1.95	1.02	0.94

values demonstrate that Cd poses a significantly higher risk compared to other heavy metals across all areas, with the highest risk in industrial areas (Er = 615), followed by capital city (Er = 471) and peri-urban areas (Er = 274.5). This result illustrates that Cd has a very high potential ecological risk, particularly in industrial and capital city areas, and a high risk in peri-urban areas. The elevated Er values for Cd indicate its substantial contribution to the overall ecological risk, likely due to its high toxicity and persistence in the environment. The Er values for Cr, Zn, Mn, Pb, Cu, Co, and Ni are less than 40, exhibiting a low potential ecological risk in all areas, as different from Cd [74].

3.4. Health Risk Assessment

3.4.1. Exposure Calculation

Humans are often exposed to non-carcinogenic risks from toxic elements in dust through inhalation, ingestion, and dermal contact. Exposure can occur through a single mechanism or multiple pathways.

Table 10. ADD (mg/kg/day) of heavy metals through ingestion, inhalation, and dermal pathways.

Heavy Metal	Pathways	Industrial Area		Capital City Area		Peri-Urban Area
		Child	Adult	Child	Adult	Child	Adult
	Ingestion	1.1 × 10−4	7.51 × 10−5	2.17 × 10−5	1.42 × 10−5	7.04 × 10−5	4.61 × 10−5
Cr	Inhalation	3.20 × 10−9	1.10 × 10−8	6.07 × 10−10	2.09 × 10−9	1.96 × 10−9	6.78 × 10−9
	Dermal	3.20 × 10−9	2.99 × 10−9	6.08 × 10−10	5.70 × 10−10	1.97 × 10−9	1.84 × 10−9
	Ingestion	2.70 × 10−3	3.54 × 10−4	1.44 × 10−3	1.88 × 10−4	2.11 × 10−3	2.76 × 10−4
Mn	Inhalation	7.56 × 10−8	5.21 × 10−8	4.02 × 10−8	2.77 × 10−8	5.89 × 10−8	4.06 × 10−8
	Dermal	7.57 × 10−8	1.41 × 10−8	4.03 × 10−8	7.54 × 10−9	5.90 × 10−8	1.10 × 10−8
	Ingestion	5.00 × 10−6	3.40 × 10−6	4.70 × 10−6	3.10 × 10−4	6.10 × 10−6	4.00 × 10−6
Co	Inhalation	1.5 × 10−10	5.10 × 10−10	1.32 × 10−10	4.50 × 10−10	1.70 × 10−10	5.86 × 10−10
	Dermal	1.47 × 10−10	1.37 × 10−10	1.32 × 10−10	1.20 × 10−10	1.70 × 10−10	1.59 × 10−10
	Ingestion	2.20 × 10−5	5.49 × 10−2	2.08 × 10−5	1.36 × 10−4	1.64 × 10−5	1.07 × 10−5
Ni	Inhalation	6.10 × 10−9	2.12 × 10−9	5.81 × 10−10	2.00 × 10−9	4.58 × 10−10	1.58 × 10−9
	Dermal	6.15 × 10−10	5.74 × 10−10	5.82 × 10−10	5.40 × 10−9	4.60 × 10−10	4.29 × 10−10
	Ingestion	3.30 × 10−4	4.33 × 10−5	3.39 × 10−4	4.45 × 10−4	2.07 × 10−4	2.72 × 10−5
Cu	Inhalation	9.22 × 10−9	6.36 × 10−9	9.48 × 10−10	6.54 × 10−9	5.79 × 10−9	3.99 × 10−9
	Dermal	9.24 × 10−9	1.72 × 10−9	9.50 × 10−9	1.78 × 10−9	5.81 × 10−9	1.08 × 10−9
	Ingestion	1.82 × 10−3	2.38 × 10−4	1.24 × 10−3	1.63 × 10−4	1.00 × 10−3	1.32 × 10−4
Zn	Inhalation	5.09 × 10−8	3.51 × 10−8	3.49 × 10−8	2.40 × 10−8	2.81 × 10−8	1.94 × 10−8
	Dermal	5.10 × 10−8	9.52 × 10−9	3.49 × 10−8	6.53 × 10−9	2.82 × 10−8	5.26 × 10−9
	Ingestion	2.00 × 10−6	4.93 × 10−3	1.50 × 10−6	1.00 × 10−6	9.00 × 10−7	6.00 × 10−7
Cd	Inhalation	6.00 × 10−11	1.90 × 10−10	4.20 × 10−11	1.50 × 10−10	2.50 × 10−11	8.50 × 10−11
	Dermal	5.50 × 10−11	5.20 × 10−11	4.20 × 10−11	4.00 × 10−11	2.00 × 10−11	2.30 × 10−11
	Ingestion	2.50 × 10−5	1.66 × 10−5	1.32 × 10−3	8.60 × 10−6	1.22 × 10−5	8.00 × 10−6
Pb	Inhalation	7.10 × 10−11	2.44 × 10−9	3.68 × 10−10	1.27 × 10−9	3.41 × 10−10	1.75 × 10−9
	Dermal	7.10 × 10−10	6.63 × 10−10	3.69 × 10−10	3.40 × 10−5	3.40 × 10−10	3.19 × 10−10

presents the calculated non-carcinogenic risk average daily dose (ADD) from atmospheric deposition exposure for both children and adults. In all areas, ingestion is the primary exposure route for all heavy metals. Industrial areas show higher values of heavy metal intake up to 2.70 × 10⁻³ mg/kg/day, indicating higher environmental pollution. Based on population comparison, children generally have higher intake values compared to adults, highlighting a greater vulnerability. This is because children are more likely to engage in hand-to-mouth activities, such as playing on the ground and putting objects in their mouths, which increases their exposure to contaminated dust. A similar study found that the daily intake of heavy metals in Shijiazhuang, China, follows the following order: hand-to-mouth intake > skin contact > respiratory inhalation, with children’s exposure being significantly greater than that observed in adults [79]. The findings underscore the potential health risks of heavy metal exposure, especially for children and those in industrial regions.

Ingestion is the primary exposure route for all heavy metals across all regions (

Table 11. Estimated LADD (mg/kg/day) of heavy metals through ingestion, inhalation, and dermal pathways.

Heavy Metal	Pathways	Industrial Area	Capital City Area	Peri-Urban Area
	Ingestion	1.89 × 10−4	2.17 × 10−5	1.16 × 10−4
Cr	Inhalation	1.42 × 10−5	2.70 × 10−6	8.75 × 10−6
	Dermal	5.28 × 10−6	1.00 × 10−6	3.24 × 10−6
	Ingestion	8.95 × 10−4	2.88 × 10−4	6.98 × 10−4
Mn	Inhalation	3.36 × 10−4	3.58 × 10−5	5.24 × 10−5
	Dermal	2.49 × 10−7	1.32 × 10−5	1.94 × 10−5
	Ingestion	8.68 × 10−6	4.71 × 10−6	1.00 × 10−5
Co	Inhalation	6.51 × 10−7	5.86 × 10−7	7.55 × 10−7
	Dermal	2.41 × 10−7	2.17 × 10−7	2.80 × 10−7
	Ingestion	3.36 × 10−5	2.07 × 10−5	2.71 × 10−5
Ni	Inhalation	2.72 × 10−6	2.58 × 10−6	2.03 × 10−6
	Dermal	1.01 × 10−6	9.58 × 10−7	7.56 × 10−7
	Ingestion	1.09 × 10−4	6.78 × 10−5	6.86 × 10−5
Cu	Inhalation	4.10 × 10−9	8.44 × 10−6	5.15 × 10−6
	Dermal	3.04 × 10−6	3.12 × 10−6	1.91 × 10−6
	Ingestion	6.03 × 10−4	2.49 × 10−4	3.33 × 10−4
Zn	Inhalation	2.26 × 10−4	3.10 × 10−5	2.50 × 10−5
	Dermal	1.67 × 10−5	1.15 × 10−5	9.28 × 10−6
	Ingestion	3.26 × 10−6	1.50 × 10−6	1.45 × 10−6
Cd	Inhalation	2.44 × 10−7	1.87 × 10−7	1.09 × 10−7
	Dermal	9.08 × 10−8	6.95 × 10−8	4.05 × 10−8
	Ingestion	4.19 × 10−5	1.31 × 10−5	2.01 × 10−5
Pb	Inhalation	3.15 × 10−6	1.63 × 10−6	1.51 × 10−6
	Dermal	1.16 × 10−6	6.07 × 10−7	5.62 × 10−7

). In Al-Akrasha, Egypt, and Madrid City, Spain, ingestion was also found to be the dominant pathway, markedly greater than dermal contact and inhalation [80,81]. Industrial areas show a higher LADD of heavy metal intake, indicating higher environmental pollution. Inhalation and dermal exposure pathways generally have lower values compared to ingestion across all areas. Across all areas, Mn has the highest estimated lifetime average daily dose, while Cd has the lowest.

3.4.2. Non-Carcinogenic Risk Assessment

HQ and HI values were calculated for both children and adults to evaluate non-carcinogenic health risks from exposure to heavy metals (Pb, Cr, Ni, Mn, Co, Cu, Zn, Cd) in three functional areas.

Table 12. HQ for heavy metals through ingestion, inhalation, and skin contact for children and adults.

Heavy Metal	Pathways	Industrial Area		Capital City Area		Peri-Urban Area
		Child	Adult	Child	Adult	Child	Adult
Cr	Ingestion	3.67 × 10−2	2.50 × 10−2	7.23 × 10−3	4.73 × 10−3	2.35 × 10−2	1.54 × 10−2
	Inhalation	1.12 × 10−1	3.85 × 10−1	2.12 × 10−2	7.31 × 10−2	6.85 × 10−2	2.37 × 10−1
	Dermal	5.33 × 10−2	4.98 × 10−2	1.01 × 10−2	9.50 × 10−3	3.28 × 10−2	3.07 × 10−2
Mn	Ingestion	5.87 × 10−3	7.70 × 10−4	3.13 × 10−3	4.09 × 10−4	4.59 × 10−3	6.00 × 10−4
	Inhalation	5.29 × 10−3	3.64 × 10−3	2.81 × 10−3	1.94 × 10−3	4.12 × 10−3	2.84 × 10−3
	Dermal	4.11 × 10−5	7.64 × 10−6	2.19 × 10−5	4.10 × 10−6	3.20 × 10−5	5.98 × 10−6
Co	Ingestion	2.50 × 10−4	1.70 × 10−4	2.35 × 10−4	1.55 × 10−4	3.05 × 10−4	2.00 × 10−4
	Inhalation	2.63 × 10−4	8.95 × 10−4	2.31 × 10−4	7.88 × 10−4	2.98 × 10−4	1.02 × 10−3
	Dermal	8.00 × 10−5	7.50 × 10−5	7.20 × 10−5	6.50 × 10−5	9.50 × 10−5	8.90 × 10−5
Ni	Ingestion	1.10 × 10−3	5.50 × 10−1	1.04 × 10−3	6.80 × 10−3	8.20 × 10−4	5.35 × 10−4
	Inhalation	2.96 × 10−4	1.03 × 10−4	2.82 × 10−5	9.67 × 10−5	2.29 × 10−5	7.92 × 10−5
	Dermal	2.96 × 10−5	2.77 × 10−5	2.91 × 10−5	2.70 × 10−5	2.30 × 10−5	2.14 × 10−5
Cu	Ingestion	3.30 × 10−4	4.33 × 10−5	3.39 × 10−4	4.45 × 10−4	2.07 × 10−4	2.72 × 10−5
	Inhalation	9.22 × 10−9	6.36 × 10−9	9.48 × 10−10	6.54 × 10−9	5.79 × 10−9	3.99 × 10−9
	Dermal	9.24 × 10−9	1.72 × 10−9	9.50 × 10−9	1.78 × 10−9	5.81 × 10−9	1.08 × 10−9
Zn	Ingestion	1.82 × 10−3	2.38 × 10−4	1.24 × 10−3	1.63 × 10−4	1.00 × 10−3	1.32 × 10−4
	Inhalation	5.09 × 10−8	3.51 × 10−8	3.49 × 10−8	2.40 × 10−8	2.81 × 10−8	1.94 × 10−8
	Dermal	5.10 × 10−8	9.52 × 10−9	3.49 × 10−8	6.53 × 10−9	2.82 × 10−8	5.26 × 10−9
Cd	Ingestion	2.50 × 10−2	1.66 × 10−2	1.32 × 10−1	8.60 × 10−3	1.22 × 10−2	8.00 × 10−3
	Inhalation	6.00 × 10−6	1.90 × 10−5	4.20 × 10−6	1.50 × 10−5	2.50 × 10−6	8.50 × 10−6
	Dermal	5.50 × 10−6	5.20 × 10−6	4.20 × 10−6	4.00 × 10−6	2.00 × 10−6	2.30 × 10−6
Pb	Ingestion	7.14 × 10−3	4.75 × 10−3	3.77 × 10−3	2.50 × 10−3	2.90 × 10−3	1.95 × 10−3
	Inhalation	3.19 × 10−3	1.10 × 10−1	1.65 × 10−2	5.71 × 10−2	1.42 × 10−2	4.87 × 10−2
	Dermal	2.21 × 10−2	2.06 × 10−2	1.15 × 10−2	1.07 × 10−2	1.05 × 10−2	9.87 × 10−3

presents the calculated HQ for various heavy metals, considering different exposure pathways and both children and adults across industrial, capital city, and peri-urban areas. The HQ values indicate potential health risks associated with each metal; values greater than 1 suggest a potential health risk, while values less than 1 are considered safe. The results highlight that certain heavy metals, like Pb and Cr, exhibit higher HQ values close to 1, indicating possible health risks in certain pathways and areas, especially for children in industrial regions.

Hazard index (HI) values presented in

Table 13. HI values of HMs in suspended street dust across industrial, capital city, and peri-urban areas.

Heavy Metals	Industrial Area		Capital City Area		Peri-Urban Area
	Child	Adult	Child	Adult	Child	Adult
Zn	0.00001	0.016	0.132	0.008	0.012	0.008
Mn	0.011	0.004	0.0059	0.002	0.008	0.0034
Cr	0.202	0.459	0.0385	0.087	0.125	0.283
Pb	0.032	0.135	0.0317	0.0703	0.028	0.061
Ni	0.001	0.550	0.001	0.006	0.0008	0.0006
Cu	0.0003	0.00004	0.0003	0.0004	0.0002	0.00003
Co	0.0006	0.001	0.0005	0.001	0.0006	0.0013
Cd	0.00001	0.017	0.132	0.008	0.012	0.008

for HMs were below the safety threshold of 1, but values for metals like Cr and Pb approach 1 across three exposure pathways in all areas. This indicates that these metals might present non-carcinogenic risks to residents if human activities continue to raise their pollution levels [82].

3.4.3. Carcinogenic Risk (CR)

CR denotes the probability of an individual developing cancer from continuous exposure to carcinogenic substance over a lifetime. This study evaluated carcinogenic risks for Cr, Ni, and Cd (established carcinogens) as well as Pb (probable carcinogens). Using the available slope factors, ingestion and inhalation were identified as exposure routes for these toxic metals. The CR values for exposure routes ranked as follows: ingestion > inhalation, aligning with non-carcinogenic exposure patterns across all locations (

Table 14. Carcinogenic risk of heavy metals for children and adults through ingestion and inhalation.

Heavy Metal	Pathways	Industrial Area	Capital City Area	Peri-Urban Area
	Ingestion	1.16 × 10−4	1.84 × 10−7	9.86 × 10−7
Cr	Inhalation	5.96 × 10−4	1.13 × 10−4	3.67 × 10−4
	Ingestion	n/a	n/a	n/a
Co	Inhalation	6.37 × 10−6	5.74 × 10−6	7.40 × 10−6
	Ingestion	n/a	n/a	n/a
Ni	Inhalation	2.28 × 10−6	2.16 × 10−6	1.70 × 10−6
	Ingestion	1.98 × 10−5	9.15 × 10−6	8.84 × 10−6
Cd	Inhalation	1.53 × 10−6	1.17 × 10−6	6.86 × 10−7
	Ingestion	3.56 × 10−7	1.11 × 10−7	1.70 × 10−7
Pb	Inhalation	n/a	n/a	n/a

n/a indicates that data are not available.

). For CR, the acceptable range is 10⁻⁶ to 10⁻⁴ [83,84,85].

Cr presented the highest carcinogenic risk through inhalation in all areas. Industrial areas showed the highest risk, with values reaching 1.16 × 10⁻⁴–5.96 × 10⁻⁴, which fell within the threshold level (10⁻⁴ to 10⁻⁶) [6,27]. The inhalation pathway (1.13 × 10⁻⁴) presents a higher risk than ingestion (1.84 × 10⁻⁷), indicating inhalation as the primary concern for Cr-related carcinogenic risk in capital city areas. Inhalation (3.67 × 10⁻⁴) presents a significantly higher risk than ingestion (9.86 × 10⁻⁷), making airborne Cr the major carcinogenic threat in peri-urban areas. Co and Ni showed relatively lower risks, predominantly through inhalation pathways. Cd posed significant risks via ingestion in the industrial area, highlighting the need for targeted interventions. Pb showed the lowest carcinogenic risk across all pathways and areas.

3.4.4. Cumulative Carcinogenic Risk (CCR)

CCR represents the total cancer risk from heavy metals through three exposure pathways, indicating the overall lifetime cancer risk (

Table 15. CCR of HMs in suspended street dust across industrial, capital city, and peri-urban areas.

Heavy Metals	Industrial Area	Capital City Area	Peri-Urban Area
Cr	7.12 × 10−4	1.132 × 10−4	3.68 × 10−4
Co	6.37 × 10−6	5.74 × 10−6	7.40 × 10−6
Ni	2.28 × 10−6	2.16 × 10−6	1.70 × 10−6
Cd	2.13 × 10−5	1.03 × 10−5	9.53 × 10−6
Pb	3.56 × 10−7	1.11 × 10−7	1.7 × 10−7

). The CSF values for Cr, Co, Ni, and Pb are provided in Table 4. The CCR values were highest for Cr (7.12 × 10⁻⁴), Cd (2.13 × 10⁻⁵), and Pb (3.56 × 10⁻⁷) in the industrial area, indicating that these heavy metals pose significant carcinogenic risks. The CCR values for heavy metals like Cr (1.132 × 10⁻⁴) and Cd (1.03 × 10⁻⁵) are lower in the capital city area compared to the industrial area but still present notable risks. The peri-urban area showed a higher CCR for Co (7.40 × 10⁻⁶) and moderate risks for Cr (3.68 × 10⁻⁴) and Cd (9.53 × 10⁻⁶). Co is near to the upper limit of the acceptable range and requires monitoring. The elevated CCR values for Cr and Cd necessitate immediate attention to address potential health risks.

4. Conclusions

In the present study, we investigated the distribution, pollution source, and health impact of toxic heavy metals in street dust across industrial, capital city, and peri-urban areas of Bangladesh. We identified eight heavy metals, namely Cr, Mn, Co, Ni, Cu, Zn, Cd, and Pb, with average concentrations of 238.31, 444.35, 10.93, 45.66, 54.22, 299.25, 2.73, and 52.78 mg/kg, respectively, for fine particles (≤20 μm) in industrial area street dust. Our results indicated that Pb, Cr, Cd, and Zn concentrations were higher in industrial zones compared to capital city and peri-urban areas, suggesting moderate to high pollution levels due to traffic emission and anthropogenic activities. The hazard index revealed potential non-carcinogenic health risks, particularly for children, from Cr, Ni, Cd, and Pb. Additionally, Cr was identified as the most carcinogenic heavy metal, with inhalation posing cancer risks ranging from 1.13 × 10⁻⁴ to 5.96 × 10⁻⁴, falling within the threshold level of 10⁻⁴ to 10⁻⁶. These findings provide crucial insights for policymakers to better understand the current situation and take immediate interventions like pertinent zoning to minimize heavy metal exposure and reduce associated health hazards.