Pollution characteristics and risk assessment of potentially toxic elements of fine street dust during COVID-19 lockdown in Bangladesh.

Due to the COVID-19 pandemic, Bangladesh government took the measure like partial lockdown (PL) and complete lockdown (CL) to curb the spread. These measures gave a chance for environmental restoration. In this study, street dust samples were collected during PL and CL from four main urban land use categories in Dhaka city, such as industrial area (IA), commercial area (CA), public facilities area (PFA), and residential area (RA). Ten potentially toxic elements (Cr, Mn, Zn, Fe, Pb, Cu, Co, Ni, As, and Cd) in fine street dust particles (diameter < 20 μm) were determined following aqua-regia digestion and measured by inductively coupled plasma mass spectrometry (ICP-MS) to evaluate distribution, pollution sources, and potential risks to ecological systems and human health. Results showed that during PL, the concentrations of toxic elements in the dust were higher than that of CL. Cd and Fe were lowest and highest in concentration with 1.56 to 41,970 µg/g and 0.82 to 39,330 µg/g in partial and complete lockdown period respectively. All toxic elements were detected at high levels above background values where Fe with the highest and Cd with lowest concentrations, respectively. By land use, the levels of toxic elements pollution followed IA > PFA > RA > CA. Correlation analysis (CA), principal component analysis (PCA), and hierarchal cluster analysis (HCA) revealed that the sources of these analyzed toxic elements were mainly from anthropogenic which are related to industrial and vehicular or traffic emissions. Enrichment factor (EF), geoaccumulation index (Igeo), contamination factor (CF), and pollution load index (PLI) also suggested that the dust was more polluted during PL. Exposure of toxic elements to human was mainly via skin contact followed by ingestion and inhalation. Hazard quotient (HQ) values were < 1 except for Mn through dermal contact at all sites during partial and complete lockdown, similar to hazard index (HI), while Cr further showed high non-carcinogenic risks to children. Generally, children HI values were about 5-6 times higher than those of adults, suggesting a greater vulnerability of children to the health concerns caused by toxic elements in street dust. Carcinogenic risk (CR) values via ingestion pathway indicated all elements (except Pb) had significant health effect, while CR value by inhalation results showed no significant health effect. Cumulative carcinogenic risk (CCR) value had significant health effect except Pb in all land use categories. CCR values decreased during CL and reached at acceptable limit for most of the cases. This research provides a message to the local governments and environmental authorities to have a complete assessment of toxic elements in the street dust of Dhaka megacity in order to assuring public health safety and ecological sustainability.

Introduction

Bangladesh was ranked the most polluted country in the world, while Dhaka was designated the second most polluted city, according to the 2019 world air quality reports (Ali and Devnath 2020). Dhaka has long struggled with environmental pollutants, notably causing air pollution. The Department of Environment (DoE) has issued a public warning about air pollution after Dhaka was rated lowest in the air quality index (AQI) since 2019. It claimed in a public notice that particulate matter from road and soil dust, automobiles, biomass burning, and traditional brick kilns surrounding and within the city are all contributing to Dhaka's air pollution (Islam and Chowdhury 2021). Air pollution is a severe issue in Bangladesh owing to its negative effects (Islam et al. 2021). It is a result of civilization’s evolution and, in reality, a cost of progress. Severe air pollution is a hazard to Bangladesh’s human health, ecology, and economic progress (Hasnat et al. 2018). The primary causes of air pollution include emissions from defective automobiles, particularly diesel-powered vehicles, brick kilns, street and construction site dust, and hazardous gases from industry (Haque et al. 2017).

As a vital factor in boosting social and economic growth, roads or streets have also contributed to significant environmental degradation (Wang et al. 2020). Road traffic is a significant pollutant of the environment, causing pollution, noise, and increased land usage (Ibe et al. 2018). The contribution of automobiles and road transportation to worldwide emissions of pollutants into the atmosphere is rising on a regular basis (Enyoh et al. 2021). In addition, it causes soil pollution in nearby areas by pollutant transfer through air fallouts. Street or road dust seems to be one of the main air pollution problems in atmospheric environment, and it has become a growing concern in recent years. It contains heavy metals, a variety of organic pollutants and other emerging contaminants which are generated from traffic, industrial, domestic, plant emissions, etc. The impact of traffic load on heavy metal levels in top soils or dust, as well as the variability of these contents with distance, has been shown by a large number of studies (Ahmed et al. 2016; Newaz et al. 2021). Airborne dust presents serious risks for human health and the size of particles is directly linked to their potential for causing health problems. Smaller particles pose the greatest problems, because they can penetrate the lower respiratory tract and enter the bloodstream, where they can affect all internal organs and be responsible for cardiovascular disorders. Smaller particle size also has larger specific area and higher adsorption rate compared to larger particles; that is why, high concentrations of toxic elements were usually associated with smaller particle size (Kabir et al. 2021b). However, particles < 246 μm usually adhere to children’s hands, and are therefore more likely to be ingested, while particles < 200 μm are retained by skin (Mercier et al. 2011), which may pose health threat through dermal uptake. Metals in street dust enter into the respiratory, and they reach the systemic circulation. In the blood metals are attached to proteins or ionized entering into the different organs and cells producing a variety of diseases. Some metals such as Cr, Pb, Co, Ni, As, and Cd interact with enzymes inhibiting its actions and also may interact directly with the components of the cell which is leading to cell death (Fortoul et al. 2015). It is a serious environmental health hazard affecting the populations of Bangladesh and caused due to increasing population, associated motorization, and industrial emissions.

COVID-19, or new corona virus disease, is a contagious illness caused by the acute respiratory syndrome coronavirus-2 (SARS-CoV-2) (World Health Organization 2020; Sohrabi et al. 2020) from 2019. As the corona virus pandemic spreads rapidly around the globe, several governments have implemented non-therapeutic preventative measures, including travel restrictions, remote office operations, national lockdown, and, most significantly, social isolation. Recently, Bangladesh was compelled to shut down industry, public transit, and other anthropogenic operations due to COVID-19. Bangladesh detected its first COVID-19 case on March 7, 2020, and conducted its first shutdown from March 26 to May 30, 2020. Recently, partial lockdown began on April 5th and ended on April 11th, 2021, while the second stage of total lockdown began on April 14th and ended on April 28th, 2021. As a consequence, it is believed that a total or partial shutdown would result in an improvement in air quality, which is directly proportional to the quantity of emissions. During partial lockdown, the following was ensured; public transports could not carry passengers more than 50% of its seating capacity, inter-district vehicular movement was restricted, all the educational institutions were close, all government and non-government offices/institutions were running by 50% manpower and unnecessarily roaming and gathering were stopped, while during complete lockdown, all transport services were completely closed; all government and private offices, factories, and industries were closed; and unnecessarily roaming and gathering were stopped too.

Environmental pollution is recognized to be caused mostly by human activities in a variety of ecosystems (Enyoh et al. 2021). The excessive rate of urbanization and industrialization occurring throughout the world has resulted in the depletion of natural resources with little time to prepare for their restoration (Isiuku and Enyoh 2019; Yunus et al. 2020). Natural restoration has been recognized as a key component of the COVID-19 lockdown, according to different research (Aravinthasamy et al. 2021; Karunanidhi et al. 2021). Since the COVID-19 lockdown, which has nearly completely halted industrial activity and vehicle movement in many nations, there has been a significant reduction in air and water pollution around the world, according to recent reports (Khan et al. 2021). The impact of COVID-19 lockdown has been demonstrated in numerous studies conducted around the world (Arora et al. 2020; Kumar et al. 2021a), but none of these studies has attempted to investigate the presence of toxic metals in street dust in Dhaka, Bangladesh, during partial and complete lockdown.

The determination of heavy metals along the roadside or on the street is becoming more popular in Bangladesh, due to metal biomagnification in the food chain and the possible health consequences of exposure (Ahmed et al. 2016; Newaz et al. 2021; Kabir et al. 2021b). While the nation was under partial and complete lockdown, the present research focuses on identifying toxic elements in the dust collected from the different land use categories of Dhaka during that time. Therefore, the main objectives of the this study were (i) measuring the concentrations of toxic elements (Cr, Mn, Zn, Fe, Pb, Cu, Co, Ni, As, and Cd) in dust during partial and complete lockdown; (ii) determining potential pollution indices using enrichment factor (EF), geoaccumulation index (Igeo), contamination factor (CF), and pollution load index (PLI); and (iii) defining their natural and anthropogenic contributions by multivariate statistical techniques including correlation analysis (CA), principal component analysis (PCA), and hierarchal cluster analysis (HCA). Monitoring anthropogenic release of heavy metals is often conducted to ascertain the spread of contaminants and the source attribution (Enyoh et al. 2020a). Among statistical approaches, both PCA and HCA are effective in identifying common patterns in data distribution, hence reducing the initial dimension of datasets and facilitating their interpretation (Ringnér 2008; Verla et al. 2020). These techniques aid in categorizing examined parameters into distinct factors/groups based on their likely sources of contribution and have been frequently utilized to uncover variable redundancy and combine environmental variables into single factors (Enyoh and Isiuku 2020). These are useful for identifying pollution sources and distinguishing between natural and human-caused pollution. On the basis of these findings, it is hoped that this research will give baseline data on the distribution, accumulation, and sources for heavy metals in Dhaka, Bangladesh, throughout periods of partial and complete lockdown. The results of this comparative analysis will aid in the quantification of the consequences of the closure of anthropogenic activities and other businesses.

Materials and methods

Study area and sampling sites

The dust samples were collected from the different streets in the metropolitan area of Dhaka city. Dhaka is the capital and centre of Bangladesh having about 20 million people in its 1500 km area where the increase rate of population is 7% per year (Saha et al. 2020). With the growth of people, the number of vehicles and industries are also increasing as a result significant smog is found in Dhaka city air (Department of Environment 2012). Vehicles like two stoke auto rickshaws, aged trucks, and mini buses are the important factors of air pollution (Bhuiyan 2018). Additionally, several heavy and light industries such as textile, glass, ceramic, battery, pharmaceutical, metallurgical, and leather processing have been built in the Dhaka metropolitan area of Bangladesh (Rahman et al. 2019). All these anthropogenic activities create huge amounts of waste, effluents, and atmospheric pollutants which causes serious harm to the ecosystem of Dhaka city (Kormoker et al. 2019). According to the Dhaka Urban Transport Network Development, the major categories of land use in Dhaka city are residential areas (44.35%), commercial areas (4.29%), industrial areas (2.01%), public facilities areas (7.97%), urban green areas (1.20%), roads/railways (10.46%), and restricted areas (8.42%) (available online: https://openjicareport.jica.go.jp/pdf/11996782_03.pdf (accessed on 15 January 2022)). The sampling sites in the area are presented in Fig. 1.

Fig. 1

a The location of the study site (the metropolitan area of Dhaka city; red marked area) in Bangladesh map and b four different land use categories sampling sites in Dhaka metropolitan area

Sample collection and processing

Sampling sites were selected based on the significance of the sites such as population density, traffic load, and surroundings. Street dust samples were collected by a pre-clean plastic dustpan and polyethylene brushes (Trojanowska and Świetlik 2019) during partial and complete lockdown condition. The polyethylene brush was carefully used to sweep the surface of the soil into the dustpan before being transferred into a zip lock bag as described in prior studies (Enyoh et al. 2020b) (Fig. 2). Samples for partial and complete lockdown were collected in partial and complete lockdown between April 5th to 11th, 2021, and April 14th to 28th, 2021, respectively. During this period, the average temperature was 33 °C, with no precipitation and no rainfall (https://weather-and-climate.com/Dhaka-April-averages). The sites covered in this study were selected based on land usage, including industrial area (IA), commercial area (CA), public facilities area (PFA), and residential area (RA). Approximately 500 g of street dust was collected from each test location by randomly sweeping 1 m2 area that included impermeable surfaces such as street, pavement, and gutter (Delibašić et al. 2020). Four sub-dust samples were collected and mixed comprehensively to make a composite representative sample (Jiang et al. 2014). During partial and complete lockdown, a total of 96 street dust samples were collected from twelve sampling locations around Dhaka’s metropolitan region. Prior to sampling, superfluous debris such as cigarette buds, stones, scrap plastic goods, and disassembled construction trash were gathered and removed from the sample area. All the samples were then stored in sealed polyethylene bags with appropriate labeling. Then collected samples were separated into different particle sizes by vibratory sieve shaker (AS 200 digit Retsch AS200). Finally, the samples were kept in Ziploc plastic-bags until analysis (Fig. 2).

Fig. 2

Collection and processing of street dust samples

Sample analysis procedure

For measuring the concentration of toxic elements, 50 mg of the sieved street dust (< 20 µm) was mixed with 20 mL of aqua regia solution (5 mL 63% HNO3 and 15 mL 36% HCL). To prepare aqua regia, an analytical grade reagent (HNO3 and HCl) was employed, and Milli-Q water (Type 1) was used to make all of the solutions. The diluted suspension was heated using hotplate (ZOJIRUSHI, EA-DD10-TA) at 150 °C for 1 h 30 min until the evolution of reddish-brown fumes ceased. Then, the digest was reduced to an approximate volume of 1 mL or close to dryness and allowed to cool down to room temperature before adding 20 mL of 2% HNO3. Afterwards, samples were filtered through Whatman filter paper of 5C 110 mm in diameter (pore size: 11 μm) and stored in a refrigerator until analysis (Kabir et al. 2021b). The concentrations of toxic elements in the final solution were measured by inductively coupled plasma mass spectrometry (ICP-MS) (Agilent Technologies, 7700 series, USA).

Quality assurance and quality control

For the estimate of the metals examined from road dust samples, quality assurance and control (QA/QC) techniques were used. All analytical glassware was acid cleaned and thoroughly rinsed with deionized water before to use. A similar approach was used to treat reagent blanks as samples and digest them concurrently. As part of the quality control procedure for % recovery by the technique, a triplicate of certified reference materials (CRM) (Gobi kosa Dust, NIES CRM No. 30) was made and digested concurrently with the samples. Each digested sample solution was evaluated three times, and their repeated analyses yielded a relative standard deviation (RSD) of less than 5%. We got relatively excellent elemental recoveries of the examined heavy metals from CRM (85, 93, 107, 100, 86, 95, 85, 95, 97, 100% for Cr, Mn, Cu, Zn, Pb, Co, Ni, Fe, Cd, and As, respectively). After every ten determinations, standards were recalibrated. Cr, Mn, Ni, Cu, Zn, As, Pb, Co, Ni, Fe, Cd, and As had limits of detection (LODs) of 0.018, 0.041, 0.088, 0.048, 0.067, 0.085, 0.009, 0.014, 0.003, and 0.001 ng/mL, respectively.

Methods for assessment of contamination

Contamination factor

The CF is stated as follows, and it indicates the magnitude of one element's increase in dust relative to the same element concentration in the geological background:where Csample is the measured concentration of element in dust and Cbackground is the background value for the element. In this study, the element concentrations in the upper continental crust reported by Wedepohl (1995) were used as background values. The CF values of < 1, 1–3, 3–6, and > 6 indicate low, moderate, considerable, and very high contamination, respectively (Gope et al. 2017).

Pollution load index

The PLI provides information on the cumulative pollution load on a place by aggregating hazardous elements. Each sample site’s cumulative pollutant load was determined using the pollution load index (PLI) established by Tomlinson et al. (1980) in the following manner:where n is the number of elements studied, and CF is the contamination factor for individual element calculated as described in Eq. 1. When PLI < 1 denotes no pollution load by toxic elements; when PLI = 1 indicate baseline levels of pollutants are present, and PLI > 1 indicates that it is polluted (Kumar et al. 2021b).

Enrichment factor

The EF was used to quantify element contamination and to distinguish between natural and human sources. The EF was determined using the equation shown below (Barbieri 2016):where (C/Cref)sample and (C/Cref)crust refer to the ratio of the concentration of a target and reference element in the analyzed samples and background material, respectively. By Wedepohl (1995), this research employed aluminum as a reference element due to its geochemistry (Kabir et al. 2021a) element concentrations in the upper continental crust (UCC) as background data. The EF values are categorized as follows: EF < 2 shows no to little enrichment, (ii) 2 ≤ EF < 5 suggests moderate enrichment, (iii) 5 ≤ EF < 20 indicates substantial enrichment, (iv) 20 ≤ EF < 40 indicates very high enrichment, and (v) EF > 40 indicates very high enrichment (Kowalska et al. 2018).

Geo-accumulation index

The Igeo, which was first developed to analyze the contamination of bottom sediment (Müller 1969), is now widely used to assess the contamination of dust by comparing the observed element concentration to a reference value (Rehman et al. 2020). The Igeo was calculated using the following Eq. (4):where C is the measured concentration of toxic elements in dust, and B is the geochemical background concentration of the same toxic elements adopted from by Wedepohl (1995). The constant 1.5 is introduced to minimize the effect of possible variations in the background values, which may be attributed to lithological variations in the samples. According to Ali et al. (2017) the Igeo values were divided into seven groups: Igeo ≤ 0 = ‘uncontaminated’; 0 < Igeo ≤ 1 = “uncontaminated to moderately contaminated”; 1 < Igeo ≤ 2 = “moderately contaminated”; 2 < Igeo ≤ 3 = “moderately to heavily contaminated”; 3 < Igeo ≤ 4 = “heavily contaminated”; 4 < Igeo ≤ 5 = “heavily to extremely contaminated”; and Igeo > 5 = “extremely contaminated.”

Ecological risk

To quantitatively express the potential ecological risk of a given contaminant in each land use area, ecological risk is calculated using the following formula:where Tr refers to the level of toxicity that the metals have on the environment, while CF refers to the contamination factor. From the accumulated data, the Tr values for the metals are chromium (Cr) = 2, manganese (Mn) = zinc (Zn) = iron (Fe) = 1, lead (Pb) = copper (Cu) = cobalt (Co) = nickel (Ni) = 1, arsenic (As) = 10, cadmium (Cd) = 30 (Hakanson 1980). From the accumulated risk factors, the levels are classified as follows: Er < 40 = “low potential ecological risk”; 40 < Er < 80 = “medium potential ecological risk”; 80 ≤ Er < 160 = “considerable potential risk”; 160 ≤ Er < 320 = “high ecological potential risk”; Er > 320 = “very high potential risk” (Kamani et al. 2017).

Risk index

The risk index (RI) of the integration between the risk potential values of the heavy metals and the contamination factor is calculated, using the following formula:where n is the number of studied elements, and the i is the ith element (Hakanson 1980). Based on Hakanson (1980), the RI values are grouped into five several ranks, i.e., RI < 150 = “low ecological risk”; 150 < RI < 300 = “moderate ecological risk”; 300 < RI < 600 = “considerable ecological risk”; RI > 600 = “very high ecological risk”.

Health risk assessment

The assessment of human health risk is a process that determines the potential health consequences of exposure to cancer-causing and non-cancerous manmade substances (US EPA 2001). The risk assessment method consists of four critical steps: hazard rearrangement, exposure assessment, toxicity assessment (dose reaction assessment), and risk characterization (US EPA 2001). Fundamentally, hazard identifiable proof entails investigating synthetic compounds that are accessible at any random location, their concentrations, and geographical distribution. Toxic elements (i.e., Cr, Mn, Co, Ni, Zn, Pb, Cu, Cd, and As) were targeted in the research region in order to detect potential dangers for the population.

Exposure dose

The purpose of exposure assessment is to quantify or evaluate the magnitude, frequency, and duration of human exposure to environmental pollutants. Exposure assessment was conducted in this inquiry by calculating the daily dose (D) of toxic elements prior to their ingestion, inhalation, and skin adsorption by adults and children from the investigation region using the US Environmental Protection Agency’s health risk models (US EPA 1989). Adults and children are socially and physiologically distinct (Zhou et al. 2019).

Ingestion of dust particles (Dingestion) via mouth

Inhalation of dust particles via mouth or nose (Dinhalation)

Dermal contact/adsorption (Ddermal) via skin

The descriptions for the different parameters are summarized in Table 1.

Table 1

The parameters used for calculating the average metal daily intake and health risk assenting of toxic elements in street dust

Factor	Definition	Unit	Value of children	Value of adult	Reference
C	Toxic element concentration	mg/kg	C	C	This study
ED	Exposure duration	y	6	30	Zheng et al. (2010)
ExF	Exposure frequency	d/y	180	180	Zheng et al. (2010)
CF	Conversion factor	kg·mg−1	1 × 10−6	1 × 10−6	US EPA (1989)
BW	Average body weight	kg	16.2	61.8	MHC (2008)
ATnon-cancer	Average time	d	ED × 365	ED × 365	Zheng et al. (2010)
ATcancer	Average time	d	LT × 365	LT × 365	Zheng et al. (2010)
LT	Average lifetime	y	76	76	MHC (2008)
IngR	Ingestion rate	mg/d	200	100	US EPA (2001)
InhR	Inhalation rate	m3/d	7.6	20	Van den Berg (1995)
PEF	Particle emission factor	m3·kg−1	1.36 × 109	1.36 × 109	US EPA (2001)
SL	Skin adherence factor	mg /(cm−2·d−1)	0.2	0.07	US EPA (2001)
SA	Exposed skin area	cm2	2800	5700	US EPA (2001)
ABS	Dermal absorption factor	Unitless	0.01 (0.03 for As)	0.01 (0.03 for As)	US EPA (2001)

where C denotes the concentration of hazardous components in street dust samples (exposure-point concentration), as well as the characteristics of the exposure parameters used to derive an estimate of the “sensible most severe exposure” (Van den Berg 1994). The inhalation rate is given by InhR, the exposure frequency is given by ExF, the exposure duration is given by ED, the contact or adsorption rate is given by CR, the body weight of the exposed single person is given by BW, and the particle discharge factor is given by PEF in m3/kg

Non-carcinogenic risk estimation

The hazard quotient (HQ) and hazard index (HI) were used to estimate the non-carcinogenic effects of toxic elements. The hazard index (HI) is a value that takes into account the cumulative effect of ingesting, inhalation, and dermal adsorption dosages (US EPA 1989). The following equation is a description of it:where D and RfD are the hazardous element’s dosage and reference dose, respectively. The ratio of D/RfD is referred to as the HQ (hazard quotient) or non-carcinogenic risk. HI is used to estimate the risk of exposure to elements by three different routes of exposure: (i) ingestion, (ii) inhalation, and (iii) skin contact (US EPA 1989). RfD is the maximum permitted risks determined by daily exposure to the human body, and SF is the slope factor for each element (Ferreira-Baptista and De Miguel 2005), which are summarized in the following Table 2.

Table 2

Values of reference dose (RfD) (Li et al. 2016; Men et al. 2020)

Reference dose (RfD)	Value (mg kg−1 d−1)
RfDingestion	Pb = 3.5 × 10−3, Cu = 4 × 10−2, Zn = 3 × 10−1, Cr = 3 × 10−3, Ni = 2 × 10−2, As = 3 × 10−4, Co = 2 × 10−2, Mn = 4.6 × 10−2, Cd = 1 × 10−3, Fe = 8 × 10−1
RfDinhalation	Pb = 5.25 × 10−3, Cu = 1.2 × 10−2, Zn = 6 × 10−2, Cr = 6 × 10−5, Ni = 5.4 × 10−3, As = 1.23 × 10−4, Co = 1.60 × 10−2, Mn = 1.84 × 10−3, Cd = 5.71 × 10−5
RfDdermal	Pb = 3.52 × 10−3, Cu = 4 × 10−2, Zn = 3 × 10−1, Cr = 2.86 × 10−5, Ni = 2.06 × 10−2, As = 3.01 × 10−4, Co = 5.71 × 10−6, Mn = 1.43 × 10−5, Cd = 2.5 × 10−5

Carcinogenic risk estimation

The LADD is the lifetime average daily dosage (mg/kg/day) as specified below (EPA 1996; US EPA 2002; Ferreira-Baptista and De Miguel 2005):

The cumulative carcinogenic risk (CCR) associated with exposure to hazardous components in street dust was determined by multiplying the carcinogenic risk (CR) associated with ingestion (CRingestion) by the carcinogenic risk associated with inhalation (CRinhalation). Carcinogenic risks associated with Cr, Ni, Cd, and As (as recognized carcinogens) and Pb (as suspected carcinogens) were examined in this research. Ingestion and inhalation absorption are thought to be the primary modes of exposure to these hazardous components based on known slope factors.where CSFingestion and CSFinhalation are the cancer slope factors (kg day/mg) associated with hazardous components ingested and inhaled, respectively. The CSF were Pb = 0.0085, Cr = 0.5, Ni = 0.91, As = 1.5, Cd = 1.5 for ingestion and Pb = 0.042, Cr = 0.41, Ni = 0.84, As = 15.5, Cd = 6.3 for inhalation (US EPA 1989; Wahab et al. 2020; Rahman et al. 2021).

Statistical analysis

Multivariate statistics such as Pearson correlation analysis (CA), principal component analysis (PCA) and hierarchical cluster analysis (HCA) by applying square Euclidean distance and Ward’s cluster methods were performed to elucidate the possible sources of toxic elements in street dust during lockdown (Verla et al. 2020). Two factors analysis of variance (ANOVA) without replication were performed to determine significant differences between land use category and period for toxic elements concentrations. All statistical analyses were performed using the IBM SPSS Version 23.

Results and discussion

Distribution of toxic elements in dust

High concentrations of toxic elements were usually associated with smaller grain size particles (Mercier et al. 2011). This happens due to their larger specific area and higher adsorption rate compared to larger particles. The concentration of toxic elements in the dusts (< 20 µm) during partial and complete lockdown and in comparison, with standard permissible limits is presented in Fig. 3. Overall, during partial lockdown, the concentrations of toxic elements in the dust were usually higher than the complete lockdown. As a result, temporal fluctuations in the abundances of many potentially harmful elements in Dhaka City road dust are found, revealing the fluctuating state of the atmospheric environment. This happens due to less restriction of vehicle and anthropogenic activities compared to complete lockdown. However, the distribution toxic element concentrations are varied across the land use category with a overall order of Fe > Zn > Mn > Cr > Cu > Ni > Co > As > Cd.

Fig. 3

Concentrations of toxic elements in street dust under partial lockdown and complete lockdown

The concentration of Cr in the street dust during the partial lockdown ranged from 133.58 µg/g in RA to 142.7 µg/g in IA, while during the complete lockdown, the concentration reduced by 27% ranging from 102.93 µg/g in RA to 124.99 µg/g in CA. The concentrations ranged were higher than the UCC level of 35 µg/g (Fig. 3). However, Cr concentrations showed significant differences (p = 0.04) between lockdown period, while between land usage, there was a significant difference (p > 0.05). The order for Cr distribution followed; IA > CA > PFA > RA during partial lockdown and CA > IA > PFA > RA during complete lockdown. The highest Cr concentration in street dust from industrial and commercial area found in this study is in agreement with report of (Ahmed and Ishiga 2006) for the same Dhaka city. The reduction in Cr levels during complete lockdown was attributed to the switch off of all probable sources like traffic, anthropogenic sources, coal-related and industrial activities, and leather tanning industries within the area. These activities are known sources of toxic elements in street dusts (Liu et al. 2018; Men et al. 2018). In comparison with other studies, Newaz et al. (2021) reported maximum Cr concentration 413 µg/g in road side soils across cities in Bangladesh, while Ahmed and Ishiga (2006) reported maximum concentrations of 203 µg/g in Dhaka city. These studies are comparable to what is obtained in the current study. High Cr above UCC values in the dust is not desirable as the size studied in this study can easily be ingested. Chromium compounds are irritants to the respiratory system and may induce pulmonary sensitization when breathed (Enyoh et al. 2020a). Inhalation of Cr(VI) compounds on a long-term basis increases the chance of developing lung, nasal, or sinus cancer. Contact with Cr(VI) compounds may cause severe dermatitis and mostly painless skin ulceration (Dayan and Paine 2001).

The concentrations of Mn ranged from 681.5 9 µg/g in RA to 700.78 µg/g in CA and from 592.29 µg/g in IA to 674.08 µg/g in RA. The Mn concentrations decreased for about 5 to 15% in all sites during the complete lockdown. The drop in concentration can also be attributed to the switching off activities during the period. The IA and CA had the highest concentrations of Mn in the dusts during partial and complete lockdown respectively. However, the concentrations showed no significant differences (p > 0.05) for period and land use category. However, Mn concentrations during partial and complete lockdown were higher than UCC value of 527 µg/g but lower than the minimum concentration of 1870 µg/g reported in dust from Dhaka Aricha highway, Bangladesh (Ahmed et al. 2016). High exposure to high levels of Mn may cause a persistent neurological illness called manganism, which has symptoms such as tremors, difficulties walking, and facial muscle spasms (ATSDR 2012). These symptoms are often followed by other, less severe symptoms such as anger, aggression, and hallucinations, among others (ATSDR 2012).

Maximum concentrations of Co and Ni in street dust were found in partial lockdown compared with complete lockdown in all study sites (Fig. 3). Previous research showed that Co and Ni are entered in street dust mainly from anthropogenic sources, human activities especially industrial activities (Chen et al. 2015; Zhang et al. 2016). Due to complete lockdown, maximum concentrations found at IA decreased by 19% and 29% for Co and Ni, respectively. However, for Ni, all samples (100%) during partial and complete lockdown were above UCC limits of 18.6 µg/g, while for Co, 100% during partial and 25% during complete lockdown had high values above UCC of 11.6 µg/g. Ni showed significant differences (p < 0.07) between land usage and period, while Co showed no significant differences (p > 0.05) for land usage.

Similarly, high concentrations of Cu and Zn were usually associated with partial lockdown (Fig. 3). In case of Cu, at IA, concentration had about 36% decreases during complete lockdown. The highest concentrations were recorded in PFA and RA during partial and complete lockdown respectively. In case of Zn, as a result of complete lockdown, the concentration level decreased 46% at industrial area (IA). The trend for Zn was IA > RA > PFA > CA. However, based on land usage and period, no significant differences (p > 0.05) on Cu and Zn concentrations were recorded. The concentrations of Cu and Zn recorded were still higher than the UCC values of 14.3 and 52 µg/g, respectively. Previous report has also reported high concentrations for these metals in Dhaka City (Safiur et al. 2019; Newaz et al. 2021). High levels of Cu and Zn in road side dust have been associated with emission from vehicle including tire and brake wear, wasted lubricating oil, and street surface erosion (Budai and Clement 2018).

High conc. of As, Cd, Pb, and Fe were also found in partial lockdown compared with complete lockdown at all places (Fig. 2). In case of As, during complete lockdown, maximum concentration decreased by 26% from partial lockdown at commercial area (CA). Because of all anthropogenic activities and vehicle movements were closed during complete lockdown. For Cd, there was a 59% decreased at public facilities area (PFA) during complete lockdown. This may be because all sources were closed during complete lockdown. Previous research showed that Cd can accumulate in the environment from anthropogenic activities, lubricating oil or petrochemical (Vu et al. 2017). However, both As and Cd concentrations were very high during the partial and complete lockdown when compared to their background values. This is in agreement with reported values in the study of Newaz et al. (2021) and Kormoker et al. (2021). Based on land usage and period, no significant differences (p > 0.05) on As concentrations was recorded while only by period that Cd concentrations showed significant differences (p = 0.02). In case of Pb and Fe, the maximum concentration recorded at IA during partial lockdown decreased by 17% and 51% in complete lockdown. Because of all vehicular emission was closed during complete lockdown and this place was also high traffic area and the presence of metal-based industrial units. Previous research also showed that vehicular emission is the major source of lead in high traffic density areas may originate from traffic sources, such as wear and tear of vulcanized vehicle tires and corrosion of galvanized automobile parts (Qiang et al. 2015), while the metal-based industrial units in the area have been fingered as the major source Fe in the street dust of the area (Singh 2011) which were closed during complete lockdown. Both Pb and Fe showed no significant differences (p > 0.05), while their concentrations were also very high above background values of 17 and 30,890 µg/g, respectively. These findings are in agreements with previous studies from the area (Safiur et al. 2019; Diganta et al. 2020; Kormoker et al. 2021).

Source appraisal

In order to perform the source appraisal for the toxic elements in street dust during partial and complete lockdown, Pearson’s CA, PCA, and HCA were computed.

Correlation analysis

Pearson’s correlation coefficient between the elements in the street dust was calculated in the form of matrices and used as a measure of similarity and inter-relationship among elements assessed during the partial and complete lockdown. The correlation matrix is presented in Table 3. Specific elements showed significant correlation in dust during partial and complete lockdown. In partial lockdown, Fe showed strong relationship with the following elements Cr (r = 0.717), Cu (r = 0.818), Zn (r = 0.794), and Pb (r = 0.999); Co showed strong relationship with Mn (r = 0.528), Ni (r = 0.563), and As (r = 0.923); Ni further showed strong relationship with Mn (r = 0.995) and As (r = 0.588); Cu with Cr (r = 0.692), Zn (r = 0.809), Cd (r = 0.590), and Pb (r = 0.803); As further showed strong relationship with Mn (r = 0.664) and Pb further with Zn (r = 0.988). Correlation coefficients that are positive and strong are indicative of these elements in road dust that are similar or common, while negative indicate dissimilar or uncommon source(s) (Enyoh et al. 2020a). Generally, in partial lockdown, the toxic elements like Cr, Fe, Cu, Zn, Cd, and Pb were positively correlated to each other signifying that they may share similar geochemical characteristics and origin, viz., traffic, industrial, construction activity, fuel combustion, brake fire wear, and motor oil. Similarly, positive correlation was also found on the toxic elements like Mn, Co, Ni, and As implying that their source of emission to the environment was same, i.e., industries located within the area. In complete lockdown, all the industries and market were closed due and some elements which showed dissimilar source(s) during partial lockdown, now share common source(s). Generally, the toxic elements like Cr, Co, Ni, and As were strongly correlated to each other and toxic elements like Mn, Fe, Co, Cu, Zn, As, Cd, and Pb were also strongly correlated implying that their source of emission may be atmospheric deposition and could be activities during the partial lockdown. Similar relationship between some of the toxic elements in the dust from Dhaka have been reported in recent studies (Kormoker et al. 2021; Newaz et al. 2021; Kabir et al. 2021b).

Table 3

Correlation matrix for toxic elements in street dust during partial lockdown and complete lockdown

Toxic elements	Cr	Mn	Fe	Co	Ni	Cu	Zn	As	Cd	Pb
Cr	1.0	− .013	.717*	− .652	.123	.692*	.794*	− .731	.289	.693
Mn		1.0	− .659	.528*	.955*	− .639	− .563	.664*	− .091	− .675
Fe			1.0	− .667	− .468	.818*	.992*	− .902	.025	.999*
Co				1.0	.563*	− .973	− .666	.923*	− .760	− .646
Ni					1.0	− .611	− .365	.588*	− .299	− .480
Cu						1.0	.809*	− .986	.590*	.803*
Zn							1.0	− .894	.037	.988*
As								1.0	− .451	− .890
Cd									1.0	− .004
Pb										1.0
Cr	1.0	.185	.253	.945*	.740*	− .597	.212	.567*	− .495	− .578
Mn		1.0	.988*	.431	− .517	.636*	.984*	.888*	.748*	.636*
Fe			1.0	.516*	− .437	.542*	.998*	.935*	.672*	.537*
Co				1.0	.545*	− .417	.486	.785*	− .275	− .410
Ni					1.0	− .973	− .466	− .091	− .950	− .961
Cu						1.0	.559*	.214	.985*	.999*
Zn							1.0	.923*	.689*	.550*
As								1.0	.368	.211
Cd									1.0	.981*
Pb										1.0

*Significant (p < 0.05)

Principal component analysis

The principal component analysis (PCA) was used to pinpoint the source(s) of metal contamination in the dust during the partial and total lockdown. PCA was done on the toxic elements data by maximizing the sum of the variances of the component coefficients using varimax rotation and Kaiser Normalization. This approach categorizes variables into components. The main components were extracted based on eigenvalues greater than 1, and the resulting total variations are shown in Table S1. During partial lockdown, three components were extracted which explained by the following variations 67.970%, 16.589%, and 15.441% for PC1, PC2, and PC3, respectively, while during complete lockdown, two components were extracted explained by the following variations 59.600% and 39.121% for PC1 and PC2, respectively.

The PCA plot in rotated space for toxic elements in the dust is represented in Fig. 4, while the loading scores is presented in Table S2. According to Liu et al. (2003) and Verla et al. (2020), component loading values of > 0.75, 0.75–0.50, and 0.50–0.30 were classified as “strong,” “moderate,” and “weak,” respectively. During partial lockdown, Cr, Fe, Zn, Pb, and Cu showed moderate to strong correlation to PC1 and thus were clustered together in the same group; this has also been reported earlier in investigations of street dust (Legalley and Krekeler 2013; Lee et al. 2018; Aguilera et al. 2021). Lee et al. (2018) determined that lead chromate in dust particles originated from yellow street paint and that lead chromate-containing paint is a significant source of lead contamination in street dust. However, the presence of other elements in the same cluster suggests that their sources are mainly from auto mechanic and traffic related sources like abrasion of the tire, uses of lubricants, corrosion of vehicular parts, fuel combustion, and motor oil. Second cluster (PC2) encompassed Mn, Ni, As, and Co have been influenced by industrial activities such as cement and lime-based mortar dust from the widespread buildings, roads, flyovers and transportation, and construction in Dhaka city. Third cluster consists Cd and Cu has been influenced by atmospheric deposition from diesel fuel combustion of vehicles as well as incineration of municipal waste containing plastics and batteries (Ahmed et al. 2016; Adebambo and Owen 2017). However, due to complete lockdown, sources of toxic elements decreased in two groups (PC1 and PC2). One group (PC1) consists of Cu, Cd, and Pb has been originated mainly from natural sources or could be from activities experienced during partial or without lockdown. Another cluster that was Cr, Mn, Fe, Co, Zn, and As has been influenced by mixed sources including atmospheric deposition and surface run-off. Numerous studies have shown that these sources contribute significantly to the introduction of toxic elements into the environment (Enyoh and Isiuku 2020).

Fig. 4

Principal components (PC) plots in rotated space for toxic elements in street dust during a partial lockdown and b complete lockdown

Hierarchical cluster analysis

Based on square Euclidean distance (SED), hierarchical cluster analysis (HCA) was used to determine the similarities and differences between the source and presence of harmful components in dust during partial and complete lockdown. As seen in Fig. 5, the findings of this research are displayed as dendrograms. A dendrogram is a tree-like branch diagram that depicts the degree of association or resemblance between parameters (Verla et al. 2020). The HCA differentiated the analyzed toxic elements among two groups, wherein Fe, Pb, Zn, Cu, Cr, and Cd were clustered in same group, suggesting their identical source of origin, possibly from traffic related sources like abrasion of the tire, uses of lubricants, corrosion of vehicular parts, fuel combustion, and motor oil. Second cluster encompassed Mn, Ni, Co, and As has been influenced by industrial activities such as cement and lime-based mortar dust from the widespread buildings, roads, flyovers, and transportation, construction in Dhaka city. During complete lockdown, one cluster consists all the elements except Fe; i.e., they came from same source like atmospheric deposition or could be activities during partial or without lockdown. Another cluster consist only Fe that have been originated from geogenic sources.

Fig. 5

Hierarchical cluster analysis showing the grouping for toxic elements in street dust during a partial lockdown and b complete lockdown

Contamination and pollution appraisal

Contamination factors and pollution load index

The contamination factor was computed to determine the level of contamination of toxic elements in dust samples above background values during partial and complete lockdown. The result for CF of toxic elements is presented in Figure S1. The classification for CF is given as CF =  < 1 is low, CF = 1–3 is moderate, CF =  > 3–6 is considerable, and > 6 is very high contamination (Gope et al. 2017). All toxic elements in dust in all sites during the partial and complete lockdown showed moderate to very high contamination, which is in agreements with previously reported studies in Dhaka city (Kormoker et al. 2021; Newaz et al. 2021; Kabir et al. 2021b). The toxic elements always had higher contamination factors during partial lockdown to complete lockdown (Figure S1). As showed considerable contamination in all site, while Cr, Mn, Ni, Co, and Fe showed moderate contamination. Meanwhile, very high contamination was shown Cu, Cd, Pb, and Zn. These elements are toxic to ecological systems when in high concentrations. Exposure can result to diarrhea, headaches, and in severe cases, kidney failure (Verla et al. 2020).

The pollution load index (PLI) gives an idea about the cumulative pollution load from the summation of toxic elements on site. In Fig. 6, the value of PLI during both partial and complete lockdown was more than 1 that indicates deterioration of site quality in all the sampling sites. But PLI value of all the land use was always lower during the complete lockdown, and maximum decreased level was found at PFA. The PLI followed the order PFA > IA > RA > CA during partial lockdown, while RA > IA > CA > PFA during complete lockdown. In comparison with other studies, Diganta et al. (2020) found that dust collected from road sides in Tangail Municipality of Bangladesh were not polluted by toxic elements (Pb, Cr, and Cd) studied. However, high toxic element pollution loads were reported in dust samples collected from Dhaka city (Ahmed et al. 2016; Kabir et al. 2021a; Kormoker et al. 2021).

Fig. 6

Pollution load index (PLI) for toxic elements in street dust under partial lockdown and complete lockdown

Calculating a normalized enrichment factor (EF) for hazardous element concentrations above uncontaminated background levels is a standard method for evaluating the anthropogenic influence on dust (Abrahim and Parker 2008; Kormoker et al. 2021). The EF calculation attempts to decrease the variability of elements due to differences in dust ratios and is a helpful technique for displaying geochemical trends over wide geographic regions with significant dust variation. The EF technique normalizes the detected harmful element level against a reference element in the sample, such as Fe or Al (Ravichandran et al. 1995).

The computed EF is presented in Fig. 7. In this study, the distribution for EF followed, Cd > Zn > Pb > Cu > Cr > As > Fe > Mn > Co > Ni. Again, the complete lockdown caused a general reduction in the toxic elements enrichment of the dust compared to the partial lockdown. The EF value for As, Pb, and Cu showed significant enrichment, and during complete lockdown, maximum decreased level was found in RA. Cr, Fe, Mn, and Co were moderately enriched in the dust, and the highest decreased level was found in dust from RA during the complete lockdown. In case of Ni, it showed minimal enrichment while Zn, and Cd was very highly enriched in the dust. In accordance with the findings, all examined sites in the study area were comparatively contaminated by the studied toxic elements, indicating that urban solid waste ash and industrial waste, along with traffic-related activities and atmospheric aerosol deposition, may have an impact on road dust quality in the Dhaka megacity area. This conclusion is consistent with prior findings (Kabir et al. 2021b).

Fig. 7

Enrichment factor (EF) of toxic elements in street dust under partial lockdown and complete lockdown

The geoaccumulation index (Igeo) is used to quantify harmful element contamination in terms of seven enrichment classes, using the index’s rising numerical values. The Igeo values are presented in Fig. 8. For all elements, Igeo value of partial lockdown is higher than complete lockdown in all the land use. According to Ali et al. (2017) classification, Mn, Co, and Fe were practically unpolluted (Igeo < 0), Ni was unpolluted to moderately polluted (Igeo = 0–1), Cr and As were moderately polluted (Igeo = 1–2), Cu and Pb were moderately to highly polluted (Igeo = 2–3), and Zn and Cd were highly polluted (Igeo = 3–4). Due to complete lockdown, Igeo value at IA is reached the lowest polluted range for all elements except Cr and As. For Cr and As, maximum decreased Igeo values were found at RA and CA, respectively. So, it proved that traffic and industries are the major reason for this contamination.

Fig. 8

Geo-accumulation index (Igeo) of toxic elements in street dust under partial lockdown and complete lockdown

Ecological risk and risk index

The ecological risk indices (Er) quantify the risks of toxic elements in dust to ecological systems. According to Kamani et al. (2017), Er < 40 = low potential ecological risk, 40 ≤ Er < 80 = medium potential ecological risk, 80 ≤ Er < 160 = considerable potential risk, 160 ≤ Er < 320 = high ecological potential risk, and Er > 320 = very high potential risk. In case of all these elements, Er value was higher in partial lockdown than complete lockdown (Table 4). It can also be seen that due to complete lockdown, the Er value decreased in all land use category and maximum decreased Er value was recorded at industrial area (IA). All the elements showed low potential ecological risk except Cd. At commercial area, As showed medium potential ecological risk, while in industrial area, Pb showed medium potential ecological risk. Cd was very high potential risk (Er > 320) at all land category. High ecological risks of Cd indicate high Cd toxicity to ecological systems. The RI is presented in Fig. 9. In the figure, according to Hakanson (1980) classification, we can see that during partial lockdown, very high ecological risk (RI > 600) was found at public facilities area (PFA). Other land use category also showed considerable ecological risk (300 < RI < 600). But due to complete lockdown, potential ecological risk index (RI) decreased at every land use category. The RI followed the ranking order of PFA > RA > IA > CA during partial lockdown, while RA > PFA > CA > IA during complete lockdown.

Table 4

Ecological risk (Er) of toxic elements in street dust under partial lockdown and complete lockdown

Toxic Elements	Lockdown	Land use category
		IA	CA	PFA	RA
Cr	Partial Complete	8.15 ± 0.2 5.98 ± 0.1	7.44 ± 0.6 7.14 ± 0.3	7.93 ± 1.8 6.30 ± 0.2	7.63 ± 0.8 5.88 ± 1.0
Mn	Partial Complete	1.31 ± 0.06 1.12 ± 0.02	1.32 ± 0.02 1.23 ± 0.05	1.31 ± 0.06 1.22 ± 0.03	1.29 ± 0.2 1.27 ± 0.05
Co	Partial Complete	5.38 ± 0.2 4.34 ± 0.08	5.83 ± 0.1 5.58 ± 0.1	5.13 ± 0.5 4.63 ± 0.2	5.32 ± 0.3 4.62 ± 0.8
Ni	Partial Complete	13.59 ± 1.01 9.60 ± 0.3	14.33 ± 0.4 10.40 ± 1.3	11.94 ± 3.5 8.59 ± 0.6	8.70 ± 2.2 7.30 ± 0.5
Cu	Partial Complete	35.19 ± 1.4 22.60 ± 1.5	22.35 ± 0.7 21.35 ± 1.06	37.40 ± 3.8 31.03 ± 1.2	36.24 ± 1.9 35.05 ± 6.1
Zn	Partial Complete	14.54 ± 0.9 7.91 ± 0.3	11.65 ± 2.6 10.78 ± 0.4	13.10 ± 1.2 9.89 ± 1.5	13.76 ± 0.7 11.72 ± 2.8
As	Partial Complete	36.69 ± 2.7 30.26 ± 0.4	50.57 ± 1.6 37.25 ± 0.6	37.31 ± 2 33.69 ± 1.4	36.73 ± 1.1 36.11 ± 6.5
Fe	Partial Complete	1.38 ± 0.07 1.15 ± 0.01	1.32 ± 0.04 1.31 ± 0.03	1.35 ± 0.05 1.26 ± 0.03	1.37 ± 0.04 1.35 ± 0.2
Cd	Partial Complete	391.3 ± 36.6 196.6 ± 16.6	373.5 ± 19.5 204.3 ± 10.9	629.0 ± 49.6 260.0 ± 22.1	442.3 ± 27.7 301.1 ± 66.5
Pb	Partial Complete	41.91 ± 1.1 20.48 ± 0.5	23.18 ± 0.7 19.15 ± 1.2	32.17 ± 7.6 31.93 ± 0.7	39.34 ± 1.04 35.94 ± 5.7

Fig. 9

Risk index (RI) of toxic elements in street dust under partial lockdown and complete lockdown

Non-carcinogenic health risks

Humans are often exposed to toxic elements found in dust by ingestion/oral, inhalation, and skin contact (dermal). Exposure may occur via a single mechanism or through a mix of pathways (Tables 5, 6, 7 and 8). As a result, it is critical to investigate these exposure routes in order to determine the degree of the threats that these toxic elements bring to human health. For non-cancer-causing risk appraisal, three different ways of exposure dosages (i.e., ingestion, inhalation, and dermal contact) of toxic elements were recognized. The hazard quotient (HQ) of a non-carcinogen was divided by the average daily dosage from the three exposure routes to provide a particular reference dose (RfD), in mg/kg/day) for comparing the risk to the maximum permitted risk to humans from daily exposure over a lifetime. When HQ ≤ 1 is seen as safe for health effects, however HQ > 1 is regarded as posing a danger to health. The results for HQs are presented in Table 5 to 7. The HQs typically indicate that children face a greater non-carcinogenic risk than adults from all exposure pathways (Tables 5, 6, 7). Numerous studies have shown that children are more likely to be exposed to hazardous substances (Liang et al. 2017; Diganta et al. 2020). Children display pica in their efforts to explore the world around them, exposing them to hazardous components in dust on a continuous basis. Pica children are therefore more likely to have increased body levels of toxic elements than non-pica counterparts, which is undesirable given their vulnerability to toxic elements as a result of their low body weight and developing body systems (Enyoh and Isiuku 2020).

Table 5

Hazard quotient (HQ) for children and adult expose via ingestion pathway in different land use of street dust during partial lockdown and complete lockdown

Sites	IA		CA		PFA		RA
Toxic elements	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown
Cr	2.90E − 01	2.12E − 01	2.65E − 01	2.54E − 01	2.82E − 01	2.24E − 01	2.71E − 01	2.09E − 01
Mn	9.19E − 02	7.84E − 02	9.28E − 02	8.63E − 02	9.20E − 02	8.56E − 02	9.02E − 02	8.92E − 02
Co	3.80E − 03	3.07E − 03	4.12E − 03	3.94E − 03	3.63E − 03	3.27E − 03	3.76E − 03	3.27E − 03
Ni	1.54E − 02	1.09E − 02	1.62E − 02	1.18E − 02	1.35E − 02	9.73E − 03	9.86E − 03	8.27E − 03
Cu	1.53E − 02	9.84E − 03	9.73E − 03	9.30E − 03	1.63E − 02	1.35E − 02	1.58E − 02	1.53E − 02
Zn	1.54E − 02	8.35E − 03	1.23E − 02	1.14E − 02	1.38E − 02	1.04E − 02	1.45E − 02	1.24E − 02
As	1.49E − 09	1.23E − 09	2.05E − 09	1.51E − 09	1.51E − 09	1.37E − 09	1.49E − 09	1.47E − 09
Cd	8.10E − 03	4.07E − 03	7.73E − 03	4.23E − 03	1.30E − 02	5.38E − 03	9.16E − 03	6.23E − 03
Pb	2.48E − 01	1.21E − 01	1.37E − 01	1.13E − 01	1.90E − 01	1.89E − 01	2.33E − 01	2.13E − 01
Cr	3.80E − 02	2.78E − 02	3.47E − 02	3.32E − 02	3.69E − 02	2.93E − 02	3.55E − 02	2.74E − 02
Mn	1.20E − 02	1.03E − 02	1.22E − 02	1.13E − 02	1.21E − 02	1.12E − 02	1.18E − 02	1.17E − 02
Co	4.98E − 04	4.02E − 04	5.40E − 04	5.17E − 04	4.75E − 04	4.29E − 04	4.93E − 04	4.28E − 04
Ni	2.02E − 03	1.43E − 03	2.13E − 03	1.54E − 03	1.77E − 03	1.28E − 03	1.29E − 03	1.08E − 03
Cu	2.01E − 03	1.29E − 03	1.28E − 03	1.22E − 03	2.13E − 03	1.77E − 03	2.07E − 03	2.00E − 03
Zn	2.01E − 03	1.09E − 03	1.61E − 03	1.49E − 03	1.81E − 03	1.37E − 03	1.90E − 03	1.62E − 03
As	1.95E − 02	1.61E − 02	2.69E − 02	1.98E − 02	1.98E − 02	1.79E − 02	1.95E − 02	1.92E − 02
Cd	1.06E − 03	5.33E − 04	1.01E − 03	5.54E − 04	1.71E − 03	7.06E − 04	1.20E − 03	8.17E − 04
Pb	3.25E − 02	1.59E − 02	1.80E − 02	1.48E − 02	2.49E − 02	2.48E − 02	3.05E − 02	2.79E − 02

Table 6

Hazard quotient (HQ) for children and adult expose via inhalation pathway in different land use of street dust during partial lockdown and complete lockdown

Sites	IA		CA		PFA		RA
Toxic elements	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown
Cr	4.05E − 04	2.97E − 04	3.70E − 04	3.54E − 04	3.94E − 04	3.13E − 04	3.79E − 04	2.92E − 04
Mn	6.42E − 05	5.48E − 05	6.48E − 05	6.03E − 05	6.42E − 05	5.98E − 05	6.30E − 05	6.23E − 05
Co	1.33E − 07	1.07E − 07	1.44E − 07	1.38E − 07	1.27E − 07	1.14E − 07	1.31E − 07	1.14E − 07
Ni	1.91E − 06	1.35E − 06	2.02E − 06	1.46E − 06	1.68E − 06	1.21E − 06	1.22E − 06	1.03E − 06
Cu	1.43E − 06	9.17E − 07	9.06E − 07	8.66E − 07	1.52E − 06	1.26E − 06	1.47E − 06	1.42E − 06
Zn	2.14E − 06	1.17E − 06	1.72E − 06	1.59E − 06	1.93E − 06	1.46E − 06	2.03E − 06	1.73E − 06
As	1.01E − 05	8.37E − 06	1.40E − 05	1.03E − 05	1.03E − 05	9.32E − 06	1.02E − 05	9.99E − 06
Cd	3.96E − 06	1.99E − 06	3.78E − 06	2.07E − 06	6.37E − 06	2.63E − 06	4.48E − 06	3.05E − 06
Pb	4.62E − 06	2.26E − 06	2.55E − 06	2.11E − 06	3.54E − 06	3.52E − 06	4.33E − 06	3.96E − 06
Cr	2.79E − 04	2.05E − 04	2.55E − 04	2.44E − 04	2.72E − 04	2.16E − 04	2.61E − 04	2.01E − 04
Mn	4.43E − 05	3.78E − 05	4.47E − 05	4.16E − 05	4.43E − 05	4.12E − 05	4.35E − 05	4.30E − 05
Co	9.15E − 08	7.39E − 08	9.93E − 08	9.50E − 08	8.74E − 08	7.89E − 08	9.05E − 08	7.87E − 08
Ni	1.10E − 06	7.77E − 07	1.16E − 06	8.41E − 07	9.65E − 07	6.95E − 07	7.04E − 07	5.90E − 07
Cu	9.84E − 07	6.32E − 07	6.25E − 07	5.97E − 07	1.05E − 06	8.68E − 07	1.01E − 06	9.80E − 07
Zn	1.48E − 06	8.05E − 07	1.19E − 06	1.10E − 06	1.33E − 06	1.01E − 06	1.40E − 06	1.19E − 06
As	7.00E − 06	5.78E − 06	9.65E − 06	7.11E − 06	7.12E − 06	6.43E − 06	7.01E − 06	6.89E − 06
Cd	2.73E − 06	1.37E − 06	2.61E − 06	1.43E − 06	4.40E − 06	1.82E − 06	3.09E − 06	2.10E − 06
Pb	3.19E − 06	1.56E − 06	1.76E − 06	1.46E − 06	2.45E − 06	2.43E − 06	2.99E − 06	2.73E − 06

Table 7

Hazard quotient (HQ) for children and adult expose via dermal pathway in different land use of street dust during partial lockdown and complete lockdown

Sites	IA		CA		PFA		RA
Toxic elements	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown
Cr	8.51E − 01	6.24E − 01	7.77E − 01	7.45E − 01	8.28E − 01	6.57E − 01	7.96E − 01	6.14E − 01
Mn	8.28E + 00	7.06E + 00	8.35E + 00	7.78E + 00	8.28E + 00	7.71E + 00	8.13E + 00	8.04E + 00
Co	3.73E − 01	3.01E − 01	4.04E − 01	3.87E − 01	3.56E − 01	3.21E − 01	3.69E − 01	3.20E − 01
Ni	4.18E − 04	2.96E − 04	4.41E − 04	3.20E − 04	3.68E − 04	2.65E − 04	2.68E − 04	2.25E − 04
Cu	4.29E − 04	2.76E − 04	2.72E − 04	2.60E − 04	4.56E − 04	3.78E − 04	4.42E − 04	4.27E − 04
Zn	4.30E − 04	2.34E − 04	3.44E − 04	3.19E − 04	3.87E − 04	2.92E − 04	4.07E − 04	3.46E − 04
As	1.25E − 02	1.03E − 02	1.72E − 02	1.27E − 02	1.27E − 02	1.15E − 02	1.25E − 02	1.23E − 02
Cd	9.07E − 03	4.56E − 03	8.66E − 03	4.74E − 03	1.46E − 02	6.03E − 03	1.03E − 02	6.98E − 03
Pb	6.90E − 03	3.37E − 03	3.82E − 03	3.15E − 03	5.30E − 03	5.26E − 03	6.48E − 03	5.92E − 03
Cr	1.59E − 01	1.17E − 01	1.45E − 01	1.39E − 01	1.55E − 01	1.23E − 01	1.49E − 01	1.15E − 01
Mn	1.55E + 00	1.32E + 00	1.56E + 00	1.45E + 00	1.55E + 00	1.44E + 00	1.52E + 00	1.50E + 00
Co	6.96E − 02	5.62E − 02	7.55E − 02	7.23E − 02	6.65E − 02	6.00E − 02	6.88E − 02	5.98E − 02
Ni	7.82E − 05	5.52E − 05	8.24E − 05	5.98E − 05	6.87E − 05	4.94E − 05	5.01E − 05	4.20E − 05
Cu	8.01E − 05	5.15E − 05	5.09E − 05	4.86E − 05	8.51E − 05	7.07E − 05	8.25E − 05	7.98E − 05
Zn	8.03E − 05	4.37E − 05	6.43E − 05	5.95E − 05	7.23E − 05	5.46E − 05	7.60E − 05	6.47E − 05
As	2.22E − 09	1.83E − 09	3.06E − 09	2.26E − 09	2.26E − 09	2.04E − 09	2.22E − 09	2.19E − 09
Cd	1.69E − 03	8.51E − 04	1.62E − 03	8.85E − 04	2.72E − 03	1.13E − 03	1.92E − 03	1.30E − 03
Pb	1.29E − 03	6.30E − 04	7.13E − 04	5.89E − 04	9.90E − 04	9.82E − 04	1.21E − 03	1.11E − 03

Table 8

Hazard index (HI) for children and adult through all three exposure pathways in different land use of street dust during partial lockdown and complete lockdown

Sites	IA		CA		PFA		RA
Toxic elements	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown
Cr	1.14E + 00	8.37E − 01	1.04E + 00	9.99E–01	1.11E + 00	8.81E–01	1.07E + 00	8.23E–01
Mn	8.37E + 00	7.14E + 00	8.45E + 00	7.86E + 00	8.38E + 00	7.79E + 00	8.22E + 00	8.13E + 00
Co	3.76E − 01	3.04E − 01	4.08E–01	3.91E–01	3.59E–01	3.24E–01	3.72E–01	3.24E–01
Ni	1.58E − 02	1.12E − 02	1.67E–02	1.21E–02	1.39E–02	1.00E–02	1.01E–02	8.49E–03
Cu	1.58E − 02	1.01E − 02	1.00E–02	9.56E–03	1.67E–02	1.39E–02	1.62E–02	1.57E–02
Zn	1.58E − 02	8.59E–03	1.26E–02	1.17E–02	1.42E–02	1.07E–02	1.49E–02	1.27E–02
As	1.25E − 02	1.03E–02	1.72E–02	1.27E–02	1.27E–02	1.15E–02	1.25E–02	1.23E–02
Cd	1.72E − 02	8.63E–03	1.64E–02	8.97E–03	2.76E–02	1.14E–02	1.94E–02	1.32E-–02
Pb	2.55E − 01	1.25E–01	1.41E-01	1.16E–01	1.96E–01	1.94E–01	2.39E–01	2.19E–01
Cr	1.97E − 01	1.45E–01	1.80E–01	1.73E–01	1.92E–01	1.52E–01	1.85E–01	1.42E–01
Mn	1.56E + 00	1.33E + 00	1.57E + 00	1.46E + 00	1.56E + 00	1.45E + 00	1.53E + 00	1.51E + 00
Co	7.01E − 02	5.66E–02	7.61E–02	7.28E–02	6.69E–02	6.04E–02	6.93E–02	6.03E–02
Ni	2.10E − 03	1.48E–03	2.21E–03	1.61E–03	1.84E–03	1.33E–03	1.34E–03	1.13E–03
Cu	2.09E − 03	1.34E–03	1.33E–03	1.27E–03	2.22E–03	1.84E–03	2.15E–03	2.08E–03
Zn	2.09E − 03	1.14E–03	1.68E–03	1.55E–03	1.89E–03	1.42E–03	1.98E–03	1.69E–03
As	1.95E − 02	1.61E–02	2.69E–02	1.98E–02	1.99E–02	1.79E–02	1.96E–02	1.92E–02
Cd	2.76E − 03	1.39E–03	2.63E–03	1.44E–03	4.43E–03	1.83E–03	3.12E–03	2.12E–03
Pb	3.38E − 02	1.65E–02	1.87E–02	1.54E–02	2.59E–02	2.57E–02	3.17E–02	2.90E–02

However, this research discovered that the most prevalent route for adults and children to be exposed to toxic elements is via skin contact with dust particles, followed by ingestion and inhalation (Fig. 10). This contradicts the results of Nkansah et al. (2017) and Kormoker et al. (2021) who stated that the majority of the toxic elements they tested reached their maximum HQ through ingestion, followed by skin contact and finally inhalation but our results agrees with Diganta et al. (2020) for toxic elements in dust collected from Tangail Municipality of Bangladesh. The HQ values computed for all hazardous elements investigated in adults and children for all routes did not surpass the standard guideline limits (≤ 1), except for Mn through dermal contact at all sites during partial and complete lockdown (Table 9). This indicates that administering Mn through the dermal route may represent a greater risk to public health.

Fig. 10

Average (mean) of exposure pathways to toxic elements in street dust during partial lockdown and complete lockdown. a Children. b Adult

Table 9

Carcinogenic risk (CR) and Cumulative Carcinogenic risk (CCR) of child and adult due to ingestion and inhalation of toxic elements in different land use of street dust during partial lockdown and complete lockdown

Sites	IA		CA		PFA		RA
Toxic elements	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown	Partial lockdown	Complete lockdown
Cr	5.68E − 05	4.17E − 05	5.19E − 05	4.97E − 05	5.52E − 05	4.39E − 05	5.31E − 05	4.09E − 05
Ni	3.66E − 05	2.59E − 05	3.86E − 05	2.80E − 05	3.22E − 05	2.31E − 05	2.35E − 05	1.97E − 05
Pb	9.64E − 07	4.71E − 07	5.33E − 07	4.40E − 07	7.40E − 07	7.34E − 07	9.05E − 07	8.27E − 07
Cd	1.59E − 06	7.98E − 07	1.52E − 06	8.29E − 07	2.55E − 06	1.06E − 06	1.79E − 06	1.22E − 06
As	8.76E − 06	7.22E − 06	1.21E − 05	8.89E − 06	8.91E − 06	8.04E − 06	8.77E − 06	8.62E − 06
Total	1.05E − 04	7.61E − 05	1.05E − 04	8.79E − 05	9.96E − 05	7.68E − 05	8.81E − 05	7.13E − 05
Cr	3.50E − 09	2.56E − 09	3.19E − 09	3.06E − 09	3.40E − 09	2.70E − 09	3.27E − 09	2.52E − 09
Ni	2.54E − 09	1.79E − 09	2.68E − 09	1.94E − 09	2.23E − 09	1.60E − 09	1.63E − 09	1.36E − 09
Pb	3.58E − 10	1.75E − 10	1.98E − 10	1.63E − 10	2.74E − 10	2.72E − 10	3.36E − 10	3.07E − 10
Cd	5.01E − 10	2.52E − 10	4.78E − 10	2.61E − 10	8.05E − 10	3.33E − 10	5.66E − 10	3.85E − 10
As	6.62E − 09	5.46E − 09	9.12E − 09	6.72E − 09	6.73E − 09	6.08E − 09	6.63E − 09	6.52E − 09
Total	1.35E − 08	1.02E − 08	1.57E − 08	1.21E − 08	1.34E − 08	1.10E − 08	1.24E − 08	1.11E − 08
Cr	5.68E − 05	4.17E − 05	5.19E − 05	4.97E − 05	5.52E − 05	4.39E − 05	5.31E − 05	4.10E − 05
Ni	3.66E − 05	2.59E − 05	3.86E − 05	2.80E − 05	3.22E − 05	2.31E − 05	2.35E − 05	1.97E − 05
Pb	9.64E − 07	4.71E − 07	5.33E − 07	4.41E − 07	7.40E − 07	7.35E − 07	9.05E − 07	8.27E − 07
Cd	1.59E − 06	7.98E − 07	1.52E − 06	8.29E − 07	2.55E − 06	1.06E − 06	1.80E − 06	1.22E − 06
As	8.77E − 06	7.23E − 06	1.21E − 05	8.90E − 06	8.91E − 06	8.05E − 06	8.78E − 06	8.63E − 06
Total	1.05E − 04	7.61E − 05	1.05E − 04	8.79E − 05	9.96E − 05	7.68E − 05	8.81E − 05	7.14E − 05

The hazard index (HI) is a value that takes into account the cumulative effect of ingesting, inhalation, and dermal adsorption dosages (US EPA 1989). An HI of 1 indicates that no chronic non-cancer health problems are expected, but an HI of > 1 indicates that non-cancer unfavorable health effects are possible. The computed HI is presented in Table 8. This study found that all HI were generally less than 1 except for Mn for both adult and children during partial and complete lockdown at all sites and Cr to children during partial lockdown. These suggest non-cancer health risks by Mn and Cr (to children only). Manganese has a strong influence on the respiratory tract and the brain. Manganese toxicity is characterized by hallucinations, forgetfulness, and nerve damage. Manganese may also result in Parkinson’s disease, pulmonary embolism, and pneumonia. When exposed to manganese over an extended length of time, males may develop impotence (ATSDR 2012), while Cr are irritants to the respiratory system and may induce pulmonary sensitization when breathed (Enyoh et al. 2020a). As a result, it has been proposed that exposure to Cr and Mn from street dust in Dhaka should not be neglected. Additionally, this research revealed that children had HI values that are 5–6 times those of adults, suggesting a greater vulnerability of children to the health concerns caused by toxic elements in street dust, which is consistent with HQ results and also corroborate those of Kabir et al. (2021a) and Wahab et al. (2020). However, the highest HI was recorded at CA, followed by IA and the least at RA.

Carcinogenic health risks

The term “carcinogenic risk (CR)” refers to the likelihood of a person developing any sort of cancer as a result of lifelong exposure to carcinogenic elements. In this study, carcinogenic risks attributed to Cr, Ni, Cd, and As (as known carcinogens) and Pb (as probable carcinogens) were assessed (Table 9). Based on available slope factors, ingestion and inhalation absorption are considered as exposure routes for these toxic elements. The CR values for the exposure paths were in the following order: ingestion > inhalation, which corresponds to the findings of non-carcinogenic exposure methods in all locations. The acceptable range for CR was 10−6 to 10−4 (Chen et al. 2015). During partial and complete lockdown, carcinogenic risk values of these toxic elements in size fractionated street dust in all land use categories via pathways were higher than 1 × 10−6 indicating potential carcinogenic risk to human except Pb. Therefore, it may demonstrate that serious long-term health hazards for adults and children from street dust samples would happen. This agrees with Kormoker et al. (2021) who reported high CR above standard limits but in contrast with earlier study of Rahman et al. (2019) in which acceptable CR values of toxic elements in dust of Dhaka City, Bangladesh, were reported. The study also found that CR values were decreased in all cases by complete lockdown, which is also due to the close of anthropogenic activities. The total cumulative carcinogenic risk (CCR) via ingestion and inhalation pathway ranged from 9.96E − 05 to 1.05E − 04, indicating that the additive carcinogenic risks of the toxic elements are within acceptable limits and will pose no risks, agreeing with Kormoker et al. (2021).

Conclusion

The present study analyzed the concentration of toxic elements in street dust samples collected from four different areas in the metropolitan Dhaka city in Bangladesh to identify the possible sources of pollution in the areas. The results of this study mainly focused on < 20 µm particle size fractions of street dust for different land-use categories in Dhaka city. According to the concentration of toxic elements of street dust, samples in all the sites showed higher concentration during partial lockdown compared with complete lockdown. The value of EF, CF, Igeo, PLI, Er, and RI were higher in partial lockdown compared with complete lockdown which is prove that industrial, vehicle emission, human activities, and other anthropogenic activities are responsible for increasing toxic elements in street dust. Multivariate statistical approaches (Pearson’s correlation coefficient analysis, principal component analysis, and hierarchical cluster analysis) identified several point and non-point sources for the studied potentially toxic elements. Succinctly, PCA showed that during partial lockdown, three discreet sources were responsible for the presence of the studied toxic elements in the dust which reduced to two during the complete lockdown. Transportation-affiliated activities and industrial processes were mostly governing the elemental enrichments rather than the natural processes. That is why, industrial activities, vehicular emission, construction, and human activities in Dhaka city should be reduced to decrease the concentration of toxic elements. This research results will be very helpful to take actions for the authority for reducing the existing dust pollution problems.

This study was investigated of possible health risks due to expose of human body of toxic elements of street dust through ingestion, inhalation, and dermal contact. In case of children, hazard quotient (HQ) value for different three ways of all toxic elements were safe (HQ < 1) except Mn through dermal pathway during both lockdown period. Hazard index (HI) values at different land use category for all toxic elements were also safe (HI < 1) except Mn and Cr. But Cr is decreased and reached the standard permissible limit by complete lockdown. In case of adult, hazard quotient (HQ) value for all land use category during lockdown were safe except Mn through dermal pathway. Hazard index (HI) value at all land use category for three different ways of all toxic elements were safe except Mn. Therefore, Mn indicating that non-cancer adverse health effects to children and adult could occur. Carcinogenic risk (CR) via ingestion pathway had significant health effect except Pb, but carcinogenic risk value by inhalation has no significant health effect. Cumulative carcinogenic risk (CCR) value had significant health effect except Pb in all land use category. Cumulative carcinogenic risk values decreased by complete lockdown and reached at acceptable limit for most of the cases. Local governments and environmental authorities should devote more resources to conducting a complete assessment of toxic elements in the street dust of Dhaka’s megacity in order to assure public health safety and ecological sustainability. However, the results of this research may be used to inform policymakers in other megacities throughout the world that face a similar situation.

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 139 KB)