Assessment of heavy metals pollution status of surface soil dusts at the Katima Mulilo urban motor park, Namibia

Abstract

The aim of the study was to examine the pollution status of environmentally concerned heavy metals: lead, cadmium, chromium, arsenic, cobalt, nickel, copper, zinc, vanadium, and manganese in surface soil dusts at the Katima Mulilo urban motor park (KMUMP), Namibia. Composite surface soil dusts samples were randomly collected from three points at 10 m apart within the motor park, and a control site on a weekly basis over 8 weeks. Pooled sampled were homogenized and 20 sub-samples (<75 μm soil fraction) were taken from the large sieved sample and digested according to EPA method 3050B. The digestates were analyzed for concentrations of the heavy metals using ICP-OES (Perkin Elmer Optima 7000 DV). The results showed a wide range of heavy metals concentrations from 0.33 mg/kg Cd to 13.7 mg/kg Zn, and differed statistically between study locations (p < 0.05). The results were generally lower than their WHO’s maximum permissible concentrations in soils for the protection of ecosystem’s health. The ecological risk indexes of the heavy metals suggest that the surface soil dusts at KMUMP were not contaminated by the heavy metals at this point. However, this does not preclude exposure risks to travelers, especially vulnerable children due to heavy metals’ toxicity and bioaccumulation.

SIGNIFICANT STATEMENT AND CONTRIBUTION TO LITERATURE

The capabilities of heavy metals to cause both acute and chronic toxicities have been widely reported in several pollution studies, making their presence at any levels in human environments such as the urban motor park with high human activities an important safety concern. This study provided baseline data of the pollution status of environmentally concerned heavy metals in the surface soil dusts at the Katima Mulilo urban motor park. The Katima Mulilo Urban motor park is a designated point of loading and dropping passengers by commercial vehicle transport operators in Katima Mulilo town and hence, constitute a significant source of heavy metals exposure risk for travelers and tourists, especially vulnerable children who frequently used the park. Despite the high human activities in and around the Katima Mulilo urban motor park due to its location bordering the Katima Mulilo Sport Centre and shopping areas, there is no documented study to establish any environmental pollutants such as heavy metals which have several routes of unintended population exposure in the environment. Thus, the present study provided important environmental pollution data of lead, cadmium, chromium, arsenic, cobalt, nickel, copper, zinc, vanadium, and manganese which can be used to monitor future phenomena associated with the presence of these heavy metals in the study area. Moreover, there is currently a dearth of heavy metal pollution data in motor parks in Namibia. Thus, apart from contributing the Namibia’s perspective to the global literature of heavy metals pollution of urban motor park soils, these data are critical to the Namibia government’s effort towards providing a clean and healthy environment across the country.

Keywords:

• Heavy metals
• pollution
• surface soil
• motor park
• Namibia

1. Introduction

The main purpose of this study is to assess the heavy metals pollution status of surface soil dusts at the Katima Mulilo urban motor park, Namibia. Environmental pollution by heavy metals has increasingly become a problem of great concern due to the adverse effects it is causing around the world (Briffa et al. 2020). Motor parks constitute a significant part of urban environment but ironically, they pose environmental health risks to living biota both within the soil and around the motor park environment. Recently, numerous studies on heavy metal contamination of urban and industrial soils have been carried out worldwide and varying degrees of environmental pollution have been reported (Men et al. 2018; Khademi et al. 2019; Roy et al. 2019; Xie et al. 2019; Yadav et al. 2019; Adimalla et al. 2020; Egbueri et al. 2020; Li et al. 2020; Chen et al. 2021; Montaño-López and Biswas 2021; Silva et al. 2021; Yuan et al. 2021; Tešíc et al. 2022; Wu et al. 2022; Yildiz and Ozkul 2022; Zhou et al. 2022). Interestingly, the numerous studies conducted in different parts of the world within the last two decades found a large share of contaminated urban soils near traffic routes (Czarnowska and Bednarz 2000; Sternbeck et al. 2002; Akbar et al. 2006; Wiseman et al. 2013, 2015; Zwolak et al. 2019; Rate 2021).

In a study on the sources of soil pollution by heavy metals, Zwolak et al. (2019), noted that the rapid global industrialization and poor urbanization has resulted in a significantly increased risk of environmental contamination with heavy metals. Globally, there are more than 10 million sites of soil pollution reported, with > 50% of the sites contaminated with heavy metals and/or metalloids (Montaño-López and Biswas 2021). Urban soil may be contaminated by the accumulation of heavy metals through diverse sources such as emissions from industrial activities (metallurgy, auto repair shop, coal combustion, etc.), road construction (asphalt, concrete and road paints), traffic (vehicular emissions, wear and tear of tyres and brakes linings, leakage of oil, etc.), spillage of petrochemicals, mining among others (Velea et al. 2009). According to Akbar et al. (2006), and Olukanni and Adebiyi (2012), vehicular emissions and other traffic-related phenomena constitute the major sources of urban soil heavy metal pollution.

Despite being unequivocally the most important component of the environment, soils serves as a major reservoir for contaminants as it can bind to various chemical agents. Reportedly, soil possesses high ability to adsorb heavy metals and accumulate them continuously (Pan et al. 2018; Zhang et al. 2018). In particular, the re-suspension of metal-enriched soil dusts caused by vehicle traffic may be the main source of heavy metals pollution, especially along roads and motor parks with intense traffic and high proportion of heavy vehicles (Czarnowska and Bednarz 2000; Sternbeck et al. 2002; Lough et al. 2005; Wiseman et al. 2013, 2015). According to Elnazer et al. (2015), vehicle exhaust is considered as a first-line source of heavy metal pollutants. Specific metals widely associated with traffic or vehicular emissions (and found around roadside and motor park soil) include copper (Cu), lead (Pb), chromium (Cr), cadmium (Cd), iron (Fe), and nickel (Ni) (Simon et al. 2013). This is due to the fact that they are present in the fuel as anti-knock agents, used as material in producing tyres, metal bodies of vehicles, and car batteries (Suzuki et al. 2009).

Due to their properties such as toxicity, persistence, and non-biodegradation, environmental contamination with heavy metals is a serious and widespread global threat, particularly in urban areas (Yang-Guang et al. 2016). The problem of heavy metals pollution is not only associated with their toxic properties but also with their ability to accumulate in the body (Zwolak et al. 2019). Heavy metals can exert their toxicity via dermal, inhalation, and ingestion pathways, and influence human health with severe consequences (Sieghardt et al. 2005). At low levels of exposure to heavy metals, clinical signs do not manifest immediately and their effects can be observed only at the physiological or biochemical level (Wojciechowska-Mazurek et al. 2008). The World Health Organization (WHO) estimated that about a quarter of the diseases facing mankind today occur due to prolonged exposure to environmental pollution (Abah et al. 2014). Additionally, the International Occupational Safety and Health Information Centre (IOSHIC) reported that long-term exposure to heavy metals may result in slowly progressing physical, muscular, and neurological degenerative processes that mimic Alzheimer’s disease, Parkinson’s disease, muscular dystrophy, and multiple sclerosis (Abah et al. 2017). It was also noted that most human load of toxic metals is acquired from the ambient concentrations of these metals through inhalation of dust and fumes, ingestion of food and drink and/or absorption through skin in extreme cases (OSHA, 1991; ATSDR 2007).

While previous studies have reported heavy metals pollution status of some environmental indices in Katima Mulilo Namibia, notably, levels of some heavy metals in roadside dusts along Katima Mulilo Urban road construction (Abah et al. 2014), in-situ concentrations of some heavy metals in surface soil dusts at the Katima Mulilo Urban waste dumpsite (Abah et al. 2015), heavy metals pollution status of the pasture grass around Katima Mulilo municipal solid wastes dumpsite (Abah et al. 2017), and more recently, heavy metals pollution status of the Katima Mulilo Urban open land wastewater disposal centre and the immediate vicinity (Abah et al. 2020), these were all pollution studies which are site-specific in nature and results obtained depend largely on the specific environmental characteristics of the study site. Moreover, pollution results obtained in one location can only provide reference information and not data that can be adopted verbatim to define the pollution status of another location with entirely different ecological characteristics. Thus, establishing the heavy metals pollution status of the surface soil dusts at the Katima Mulilo Urban motor park with essentially vehicular activities as the main anthropogenic activities, is critical for providing informed recommendations for the protection of this ecosystem and contributing to the current literature.

Potential exposure to heavy metal-laden surface soil dusts is a major public safety concern in the study area because of the high population of travelers, tourists, and petty traders traversing the Katima Mulilo urban motor park on daily basis. Unfortunately to date, there is no documented study to determine any environmentally concerned heavy metals in and within the vicinity of the Katima Mulilo urban motor park. The park serves as the major point of entry and exit by road to and from the Katima Mulilo town and hence, constitutes a significant source of heavy metals exposure risk for travelers and tourists who frequently used the park. According to Chen et al. (2005), assessing the concentration of potentially harmful heavy metals in the soil of urban motor parks is imperative in order to evaluate the potential risks to residents and tourists. Thus, the main objective of this study was to assess the status of the heavy metals pollution of surface soil dusts at the Katima Mulilo urban motor park, Namibia, and compare the levels with WHO’s permissible limits for the protection of ecosystem’ health. This is a baseline study and provides important environmental pollution data necessary for future monitoring and devising heavy metals pollution mitigation measures in the study area, and similar environment.

2. Methodology

2.1. Study site

The study site is the Katima Mulilo urban motor park located on latitude 17^°50′S and longitude 24^°27′E based on the Global Positioning System (GPS) geographical information recorded at the site on 04 September 2021 at 06:22. The Katima Mulilo Urban motor park is a designated point of loading and dropping passengers by commercial vehicle transport operators in Katima Mulilo town and it is the busiest point of arrival and departure for travelers by road into and out of the town. Based on the Namibia’s 2011 population and housing census data, the Katima Mulilo Urban area has an estimated population of 28,362 and a total land area of 32.12 Sq.Km (NPC 2011). However, the town has witnessed tremendous population growth and urbanization in recent times with a large influx of tourists from around the world all year-round, and road travel constitutes the major route of entry and out of the town. This means that a greater population of residents and visitors visited the Katima Mulilo urban motor park on frequent basis and are therefore, exposed to the contaminant-laden surface soil dust.

Figure 1 is the map of the study area showing the sampling locations in the study site.

Figure 1. Map of the study area showing the sampling points.

2.2. Sample collection and pretreatment

A total of 48 composite surface soil dusts samples were randomly collected from three points at 10 m apart within the Katima Mulilo urban motor park over 8 weeks (04 September to 23 October, 2021), pooled together and homogenized. On each sampling day (deliberately chosen as Saturday of each week), 6 separate surface soil dusts samples (2 per sampling point) were collect during the still morning weather, usually between 6:00 and 8:00 in the area, to allow dust emitted into the atmosphere during the day to settle overnight (Abah et al. 2015). The dust samples were swept with plastic brush into plastic waste packer and transferred into pre-labelled polyethene bags. Different plastic brush and plastic waste packer were used at each sampling point to minimize unintended sample mixing due to adhering dust particles. On each sampling day, control surface soil dusts sample was similarly collected from a remote location, about 4.7 km away from the Katima Mulilo urban motor park. The chosen control site is characteristically a very quiet, remote residential area with very low population, negligible vehicular activities and zero commercial activities unlike the very high anthropogenic activities at the Katima Mulilo urban motor park and its vicinity. This made the control site suitable to provide a pristine environmental quality necessary to assess the impact of the high anthropogenic activities on the levels of heavy metals recorded in the surface soil dusts at the motor park.

All unwanted materials like pieces of papers, broken bottles, cigarette ends, dry leaves, pebbles, textile materials, etc., were first carefully hand-picked after which samples collected at each point were mixed thoroughly to ensure homogeneity and filtered through 75 μm stainless steel sieve (Abah et al. 2015). This sieve fraction was selected because previous research reported that dust particles ranging from 75–125 μm contain high levels of heavy metals and are known to be very harmful to humans if inhaled (Ward and Dudding, 2004; Ewen et al. 2009, Abah et al. 2015). The filtered dust samples were packaged in air-tight plastic containers purchased specifically for this purpose, and labelled according to the sampling points.

All materials used for homogenization, sieving and storing the dust samples were pre-cleaned to minimize the potential of cross contamination (Abah et al. 2015). The materials were first washed thoroughly with tap water and Luminox® soap, and rinsed three times with deionized water. Then, they were placed in a drying oven and dried at 70 °C overnight before being used.

2.3. Sample digestion

A total of 20 sub-samples were digested at the Analytical Laboratory Services, Windhoek Namibia, according to the EPA method 3050B for Inductively Coupled Plasma-Optical Emission Spectrophotometer (ICP-OES) analysis as described by Abah et al. (2015). A measured amount (1.00 g) of each sieved surface soil dusts sample was transferred into a digestion vessel and 10 mL of 1:1 nitric acid (HNO₃) was added, mixed thoroughly and covered with a watch glass. Then, the samples were heated to 90 °C and refluxed at this temperature for 10 min after which they were allowed to cool for 5 min under room temperature. Thereafter, 5 mL of concentrated HNO₃ was added to each sample, covered and refluxed again at 90 °C for 30 min. Then, the solutions were allowed to evaporate without boiling to approximately 5 mL each and cooled again for 5 min. This was followed by the addition of 2 mL of deionised water plus 3 mL of 30% hydrogen peroxide (H₂O₂) to each sample vessel. The vessels were covered and heated just enough to warm the solutions for the peroxide reaction to start and the heating was continued until effervescence subsided and then, the solutions were cooled to room temperature (EPA 1996). The acid-peroxide digestates were covered with watch glasses and heated until the volume was reduced to approximately 5 mL again. Then, 10 mL of concentrated hydrochloric acid (HCl) was added to each sample vessel, covered and heated to boiling on a heating mantle, then refluxed at 90 °C for 15 min. After cooling to room temperature, each digestate was filtered through Whatman No. 41 filter paper into a 100 mL volumetric flask and the volume was made up to the mark with deionised water (EPA 1996).

2.4. Sample analysis

Ten (10) mL of each digestate was taken and mixed with equal volume of matrix modifier (EPA 1996), and then analyzed using ICP-OES (ICP: Perkin Elmer Optima 7000 DV) for the levels of lead, chromium, cadmium, arsenic, cobalt, nickel, copper, zinc, selenium, vanadium, manganese, uranium. The results of the heavy metals concentrations were obtained in the unit of mg/kg and recorded.

2.5. Data analysis

The laboratory data were captured on IBM SPSS v21 numerical software programme, and descriptive statistics was used to obtain the mean concentrations (mg/kg) of five replicate analyses of each element. Furthermore, inter-elemental correlation and cluster analysis employing the Bray–Curtis similarity index were calculated to determine the degree of association between the heavy metals.

2.6. Assessment of site contamination

First, the heavy metals concentrations recorded in the surface soil dusts samples were compared with their corresponding WHO’s Maximum Permissible Concentrations (MPC) which are widely used as regulatory guideline limits, and based on which informed decision about the site’s quality was made. The MPC is the concentration of a substance in air, water, soil or sediment that should protect all species in ecosystems from adverse effects of that substance (Janssen et al. 2004). Further assessment of the site’s contamination was done using a contamination factor (Cf) which is a single element pollution index calculated in order to determine the individual contribution of the heavy metals to the site’s pollution, degree of contamination (Eq. (1)(1) $$\mathrm{C}f=\left(\text{Cn}/\text{PMC}\right)$$(1) ); (C_d) which is aimed at providing a measure of the degree of overall contamination in surface layers at a particular sampling site (Rahman et al. 2012) (Eq. (2)(2) $$\mathrm{C}d=\sum \mathrm{C}f$$(2) ), ecological risk factor (Er) used here to provide an indicator of each element’s ecological risk index, and potential ecological risk factors (Eq. (3)(3) $$\text{Er}=\text{Tr}\text{ x C}f$$(3) ) (PEri), which gives insight into the heavy metals toxicity and environment response (Hakanson 1980). The potential ecological risk factors not only consider heavy metal level in the soil but also associate ecological and environmental effects with toxicology, and evaluate pollution using comparable and equivalent property index grading method (Qui 2010). Furthermore, enrichment factor (EF) and geoaccumulation index (Igeo) which have been extensively used to determine whether a certain element has additional or anthropogenic sources other than it’s predominate sources (Onjefu et al. 2016) were determined (see Eqs. (4)(4) $$\text{PErf}=\sum \text{Er}$$(4) and (5)(5) $$\text{EF}=\left({\text{Cn}/\text{Fe}}_{(\mathit{sample})}\right)/\left({\text{Cn}/\text{Fe}}_{(\mathit{Earth}\mathrm{ }\mathit{crust})}\right)$$(5) ). Each of these assessment criteria was calculated using the following equations: (1) $$\mathrm{C}f=\left(\text{Cn}/\text{PMC}\right)$$(1) (2) $$\mathrm{C}d=\sum \mathrm{C}f$$(2) (3) $$\text{Er}=\text{Tr}\text{ x C}f$$(3) (4) $$\text{PErf}=\sum \text{Er}$$(4) (5) $$\text{EF}=\left({\text{Cn}/\text{Fe}}_{(\mathit{sample})}\right)/\left({\text{Cn}/\text{Fe}}_{(\mathit{Earth}\mathrm{ }\mathit{crust})}\right)$$(5) (6) $$\text{Igeo}=\left(\text{lnCn}\right)/\left(1.5\mathrm{ }x\mathrm{ }\text{Bn}\right)$$(6) where Cn is the mean concentration of a particular element; in Eq. (6)(6) $$\text{Igeo}=\left(\text{lnCn}\right)/\left(1.5\mathrm{ }x\mathrm{ }\text{Bn}\right)$$(6) , Bn is the geochemical background value; and 1.5 is a constant which allows one to analyze the natural fluctuations in the content of each metal in the surface soil and to detect very small anthropogenic influence (Barbieri 2016).

3. Results and discussion

3.1. Mean concentrations of the heavy metals in surface soil dusts at Katima Mulilo urban motor park

The results (Figure 2) present the mean concentrations of lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), cobalt (Co), nickel (Ni), vanadium (V), copper (Cu), zinc (Zn), and manganese (Mn) determined in the surface soil dusts samples collected at the Katima Mulilo urban motor park and the control site. The results showed varying levels of the heavy metals in the motor park’s surface soil dusts with Zn recording the highest mean concentration ranging from 5.3 mg/kg to 13.7 mg/kg while Cd recorded the lowest mean concentration of 0.33 mg/kg to 0.55 mg/kg across the three designated sampling points (labeled points A to C). The other results revealed that Cr recorded 2.38 mg/kg to 2.40 mg/kg, As recorded 1.05 mg/kg to 2.88 mg/kg, Co recorded 1.30 kg/mg to 1.85 mg/kg, Ni recorded 1.45 mg/kg to 2.08 mg/kg, V recorded 4.45 mg/kg to 9.70 mg/kg while Pb, Cu, and Mn recorded 0.84 mg/kg to 1.20 mg/kg, 2.95 mg/kg to 7.40 mg/kg, and 1.5 mg/kg to 1.83 mg/kg respectively. At the control site located approximately 4.7 km from the motor park, Zn still recorded the highest concentration with surprisingly 62.25 mg/kg, Cd and As were not detected at the control site, while the results of the other metals were 0.48 mg/kg Co, 0.71 mg/kg Ni, 2.45 mg/kg V, 1.53 mg/kg Cu, and 2.99 mg/kg Mn. Apart from Zn and Mn, the other heavy metals concentrations were higher than the corresponding values recorded at the control site. The analysis of variance (ANOVA at p = 0.05) between the mean heavy metals levels in the surface soil dusts across the sampling locations was statistically significant (p < 0.05; Table 1). This might be due to varying degree of metal inputs from anthropogenically derived sources across the sampling points.

Figure 2. Levels of the heavy metals in the surface soil dusts at the Katima Mulilo Urban Motor Park. Key: Zn = x 10; different alphabets on bars indicate that ANOVA (p = 0.05) between the mean heavy metals levels in the surface soil dusts across the sampling locations was statistically significant.

Table 1. ANOVA single factor between the mean concentration of the heavy metals in the surface soil dusts at the different sampling locations.

Source of variation	SS	df	MS	F	P-value	F crit
Between groups	17672904	10	1767290	21.05098	3.94E-11	2.153156
Within groups	2602540	31	83952.9
Total	20275443	41

Statistically significant (p < 0.05).

In comparison with the results of similar studies from other countries (Table 2), the concentrations of heavy metals in the present study were lower than similar results obtained in those countries except Cd 0.06, Cr 0.84, As 0.70, Ni 0.58 and Cu 2.01 recorded in Kenya as well as Cd 0.1 in Turkiye were lower than the present concentrations of the heavy metals. These results were not surprising because apart from the natural geologic source, heavy metals concentrations in urban soils are influenced by several anthropogenic factors such as high industrialization, vehicular traffics, construction works, urban waste incinerations and disposal, surface run-off from polluted industrial sites, spillage of petrochemicals, and storm water. Thus, the more industrialized countries such as China, India, Mexico, South Africa and Nigeria compared with the present study area are more likely to be affected by these anthrophonic activities and hence, the higher concentrations of the heavy metals recorded in their urban soils.

Table 2. Comparison of mean concentrations (mg/kg) of the heavy metals in this study with results of similar studies in other countries.

	Present study	South Africa	China	Iraq	Kenya	Nigeria	Turkiye	India	Mexico
Pb	0.97	47.06	234.66	11.44	1.92	95.1	21.9	120.7	128.2
Cd	0.45	0.70	2.03	–	0.06	8.4	0.1	2.65	–
Cr	2.39	140.14	109.16	3.43	0.84	85.8	139.9	148.8	51.4
As	1.97	2.68	12.0	3.44	0.70	3.9	24.3	–	–
Co	1.54	–	–	–	–	–	–	–	7.4
Ni	1.73	138.86	56.75	6.45	0.58	20.2	217.1	36.4	36.3
V	6.62	–	–	–	–	–	–	–	26.8
Cu	5.00	215.21	149.62	3.95	2.01	46.8	20.2	191.7	99.7
Zn	8.93	556.76	655.94	5.6	9.3	228.6	50.6	284.5	280.7
Mn	1.68	2715.04	–	0.74	–	–	–	–	235.2
		a	b	c	d	e	f	g	h

a = Olowoyo et al. (2022); b. Wei and Yang (2010); c = Al-Rubaiee and Al-Owaidi (2022); d = Mungai and Wang (2019); e = Odewande and Abimbola (2008); f = Yildiz and Ozkul (2022); g = Suryawanshi et al. (2016); h = Aguilera et al. (2021).

Generally, the concentrations of the heavy metals recorded in this study were however, lower than their respective WHO’s maximum permissible concentrations in soils for the protection of ecosystem’s health (Table 3). Nevertheless, the presence of heavy metals in the surface soil dusts, especially at the motor parks with high human activities constitutes health risks due to frequent exposure to the contaminant-bearing dusts. This is mainly because, once heavy metals enter the human body either through dust inhalation, ingestion, dermal contact and absorption; they are not biodegradable but accumulate gradually in the human body to potentially toxic levels. According to Ferner (2001), heavy metals toxicity is a clinically significant condition when it does occur, and if unrecognized or inappropriately treated, the toxicity can result in significant illness and reduced the quality of life (Amirah et al. 2013). Research report indicated that heavy metals-induced toxicity and carcinogenicity involves many mechanistic aspects, some of which are not clearly elucidated or understood, and each metal is known to have unique features and physico-chemical properties that confer to its specific toxicological mechanisms of action (Tchounwou et al. 2012). In the biological systems, heavy metals have been reported to affect cellular organelles and components such as cell membrane, mitochondrial, lysosome, endoplasmic reticulum, nuclei, and some enzymes involved in metabolism, detoxification, and damage repair (Wang and Shi 2001). These effects could be more dangerous among the vulnerable population group such as children. Thus, the need to assess and constantly monitor any potential sources of heavy metals contaminations in the human environment within the context of establishing the contamination status and devising precautionary measures to minimize unintended human exposures to metal contaminants cannot be over-emphasized.

Table 3. Standard criteria used for the assessment of the heavy metals pollution.

Heavy metal	Soil MPC (mg/kg)^a	TRF^b	Average Shale values^c	Igeo criteria	Cf assessment criteria^b	Er assessment criteria^b	PEri assessment criteria^b
Pb	100	5	20	Igeo ≤ 0	Cf< 1, no contamination	Er< 40, low risk index	PEri< 150, low risk index
Cd	3	30	0.3	Practically uncontaminated
Cr	100	2	90	0 < Igeo < 1	1 ≤ Cf ≤ 3, moderate contamination	40 ≤ Er< 80 moderate risk index	150 ≤ PEri< 300, moderate risk index
As	10	10	13	Uncontaminated to moderately contaminated
Ni	75	5	68	1 < Igeo < 2 Moderately contaminated	3 ≤ CF ≤ 6, considerable contamination	80 ≤ Er< 160 considerable risk index	300 ≤ PEri< 600 considerable risk index
Cu	100	5	45	2 < Igeo < 3 Moderately to heavily contaminated
Co	30	5	19	3 < Igeo < 4 Heavily contaminated	CF > 6, high contamination	160 ≤ Er< 320, high risk index	PEri ≥ 600, high risk index
Mn	1500	1	850	4 < Igeo < 5 Heavily to extremely contaminated
V		2	13	Igeo ≥ 5 Extremely contaminated
Zn	200	1	95
Fe			46000

MPC = Maximum permissible concentration, TRF = Toxic response factor, Igeo = index of geo-accumulation, Cf = Contamination factor, Er = Ecological risk index, PEri = Potential ecological risk index

Source: Abah et al. (2020).

^a WHO.

^b Hakanson (1980).

^c Jonathan et al. (2016).

3.2. Contamination factors of the heavy metals

The results in Figure 3 show the contamination factors of the individual heavy metals in the surface soil dusts at the Katima Mulilo urban motor park and the control site. The contamination factors showed different trends across the sampling locations. At Point A (Southern axis) of the motor park, As > Cd > Cu > Zn > V > Co > Cr > Ni > Pb > Mn, At Point B (middle of the motor park), Cd > As > Co > V=Cu > Zn > Cr > Ni > Pb > Mn while at Point C (Northern axis), As > Cd > Co > Cu > Zn > V > Ni > Cr > Pb > Mn. At the control site, the trend of the heavy metal contamination indices of the surface soil dusts was Zn > Cr > Co = V > Cu > Ni > Mn > Pb. Cadmium and arsenic were not detected at the control site. Based on standard criteria for interpreting heavy metal contaminations of environmental components (Table 3), the present results (Cf < 1) did not suggest that the surface soil dusts at the Katima Mulilo urban motor park was contaminated by the heavy metals.

Figure 3. Contamination factors of the heavy metals in the surface soil dusts.

However, results of the degree of contamination (Figure 4), which provides the measure of the heavy metals’ overall contamination of the surface soil dusts at the study sites revealed that the motor park surface soil dusts were 1.5 times more contaminated than the control site, a remote residential area located 4.7 km south of the motor park. This may be due to the different degree of anthropogenic inputs of the heavy metals among the two study sites. The presence of high vehicular activities at the Katima Mulilo urban motor park in particular, may no doubt account for the elevated degree of heavy metals contamination of the surface soils dusts samples collected at this site compared to the control site. Post studies have shown that motor vehicles constitute the principal source of heavy metals pollutants (Voutsa et al. 1996; Kakulu 2003; Onianwa et al. 2003). As a major means of transportation in the study area, the explosively rising urban population relies heavily on automobiles which have become a dominant source of pollution in many cities (Dauda and Odoh 2012). According to Zwolak et al. (2019), heavy metals are emitted via motor vehicles’ exhausts and their releases are also associated with wears and tears of vehicle parts such as tires, brakes, and catalysts. These emissions, wears and tears could contribute greatly to the higher degree of surface soil dust contamination at the motor park. In several other related studies, the re-suspensions of metal-enriched road dusts caused by vehicle traffic have been implicated as the main source of road soil pollution, especially along roads with more intense traffic and higher proportion of heavy vehicles (Czarnowska and Bednarz 2000; Sternbeck et al. 2002; Lough et al. 2005; Wiseman et al. 2013, 2015; Zwolak et al. 2019). Thus, similar effect is expected at the Katima Mulilo urban motor park with high and frequent influx and exit of different sizes of vehicles, both old and new.

Figure 4. Degree of contamination and potential ecological risk index of heavy metals in the surface soil dusts. Key: KMUMP = Katima Mulilo Urban Motor Park, T-test of paired means (bars) with different alphabets are statistically significant (p < 0.05).

The potential ecological risk indices (PEri) of the heavy metals across the sampling sites (Figure 4) revealed similar pattern to the site’s degree of contamination with the Katima Mulilo urban motor park recording significantly higher index (7.33) than the control site (0.631). Based on the criteria for interpreting PEri of heavy metals in soils (Table 3), the recorded values at both the Katima Mulilo urban motor park and control site represent low level [PEri< 150] (Hakanson 1980). However, this finding does not preclude the concern for accumulation of these heavy metals in the surface dusts soil since by their nature, metals are non-degradable and hence, environmentally persistent (Abah et al. 2017). The biggest problem with heavy metals is the fact that they are persistent, and it is very difficult to eliminate them from the environment (Marjanovic et al. 2009; Briffa et al. 2020). Thus, there is need for continuous monitoring of heavy metals pollution status of urban motor park to provide environmental data needed to protect human health. The frequent presence of heavy metals in soil has been reported as an indicator of the quality of urban environment (Kamani et al. 2014).

In a study on the contamination and ecological risk assessment of heavy metals in surface soils of Esfarayen City Iran, Mohseni-Bandpei et al. (2016) held that contamination of urban surface soils with heavy metals is one of the worrying problems owing to their extensive causes, resistant to biodegradation, toxic and accumulative properties. Moreover, the presence of heavy metals in human environment has been associated with different adverse health effects in humans (Tchounwou et al. 2012). Even at low levels, some heavy metals such as cadmium and lead are dangerous to human health (Naghipour et al. 2014). For example, cadmium accumulation in human body causes kidney malfunction and cancer; lead in body causes neurological disorders, anaemia and renal damage. Thus, the accumulative tendency and chronic effect of the heavy metals constitute environmental safety concern in the study area (Abah et al. 2017).

3.3. Enrichment factors and geo-accumulation indices of the heavy metals

The soil enrichment factors of the heavy metals recorded in the surface soil dusts at the Katima Mulilo urban motor park (Figure 5) revealed that the results varied between 0.04 (Mn) to 4.833 (Cd). Based on the referenced criteria for classification of heavy metals’ enrichment factors of soil (Table 3), majority of the analyzed heavy metals namely, Pb, Cr, Co, Ni, V, Cu and Mn showed deficient to minimal indices of enrichment (EF < 2) while a few others – Cd, Co and Zn showed moderate indices of enrichment (2 < EF < 5). However, due to their persistent and accumulative tendencies in any environment, the presence of these heavy metals in the surface soil dusts of a busy environment such as the Katima Mulilo urban motor park with high intensity of human activities present potential health risk to travelers, especially vulnerable children. Some of these heavy metals (e.g. Pb, Cr) have been identified among the toxic elements that will continue to accumulate in urban environment due to their non-biodegradability and long residence time (Abah et al. 2014). In a related research report, it was noted that once present, heavy metals are persistent environmental contaminants (Singh et al. 2011). Apart from causing acute or chronic poisoning, heavy metals can be transferred from one generation to another with potential toxicity from the viewpoint of public health (Rajaganapathy et al. 2011). In their studies, Mohseni-Bandpei et al. (2016) also held that the severe accumulation of metals in the urban surface soils have harmful effects on soil ecosystem, citizens’ health and cause other environmental problems.

Figure 5. Enrichment factors (EF) and geo-accumulation indices (Igeo) of the heavy metals in the surface soil dusts.

Figure 5 also presents the geo-accumulation indices (Igeo) of the heavy metals at the Katima Mulilo urban motor park. The results obtained ranged from −9.97 (Mn) to −3.31 (As). The results were −4.97 (Pb), −5.8 (Cr), −4.21 (Co), −5.88 (Ni), −4.88 (V), −3.76 (Cu) and −7.38 (Zn). Based on the standard criteria for interpreting the Igeo of soil heavy metals (Table 3), the surface soil dusts at the Katima Mulilo urban motor park revealed uncontaminated to moderately contaminated classification (0 < Igeo < 1). However, this does not necessarily mean there was no pollution from anthropogenic sources or other enrichment over the background values. Additionally, the present results do not exclude the potential risk of heavy metal toxicities among the exposed population due to their frequent exposure and contact with the contaminant-laden soil dusts at the motor park. Moreover, the Igeo of metals is one of the indices which numerically identify, the pollution level of soils because it represents the real bio-available fraction which exerts a decisive impact on soil quality (Barbieri, 2016). Thus, the accumulation of these toxic metals in the surface soil posts environment risk to the people operating within the vicinity of the Katima Mulilo urban motor park due to possibilities of inhaling, ingesting and absorbing the contaminant-bearing dust emanating from the area.

3.4. Ecological risk indices of the heavy metals

The results of ecological risk indices of the heavy metals (Figure 6) showed similar trends across the sampling locations A, B and C which are within the Katima Mulilo urban motor park. At all the three locations, Cd recorded the highest ecological risk indices of 5.49, 3.30, and 4.80 respectively followed by As with 1.98, 1.05, and 2.88 respectively while Mn recorded the least value of 0.001 at each location. The order of ecological risk indices of the heavy metals revealed that at sampling location A, Cd > As > Cu > Co > V > Ni > Zn > Pb > Cr > Mn, at location B, the order was Cd > As > Co > Ni > Cu > V > Cr > Pb > Zn > Mn, at location C, it was Cd > As > Co > Cu > Ni > V > Cr > Pb > Zn > Mn while the order at the control site, was Zn > Co > Cu > Pb > Ni > Cr > V > Mn. Cd and As did not record any ecological risk indices at the control site because they were not detected in the surface dusts soil collected at this location. Based on the standard criteria for interpreting ecological risk indices (Table 3), the present results generally suggest low ecological risk [Er < 40] (Hakanson 1980) of the heavy metals across the sampling sites. However, the ecological risk index of each of the heavy metals recorded at the Katima Mulilo urban motor park was higher than the corresponding value recorded at the control site. This suggests that the enrichment of the surface soil dusts by the heavy metals was influenced by anthropogenically induced sources, which in this study, may be attributed to the high vehicular activities at the motor park.

Figure 6. Ecological riskx indices of the heavy metals at the sampling sites.

3.5. Inter-elemental correlation between the heavy metals

As shown in Table 4, the results of the inter-elemental correlation analysis between the heavy metals recorded across the sampling locations revealed varying degrees of correlation coefficients. Majority of the heavy metals showed extremely high positive correlation (1 > r > 0.9) and strong positive correlation (0.9 > r > 0.7), while others showed moderate positive correlation (0.7 > r > 0.5), weak positive correlation (0.5 > r > 0.3), and very weak positive correlation (0.3 > r > 0.1). According to Salah et al. (2012), positive inter-elemental correlations generally show that the heavy metals recorded at the sampling sites have common sources of anthropogenic inputs. This is very likely in this study since all the sampling locations at the Katima Mulilo urban motor park are exposed to emissions, wears and tears from motor vehicles. Besides, within close proximity, adjacent sampling locations could be proportionately affected by transboundary transfer and deposition of metal particulates. Other heavy metals such as As, Mn surprisingly recorded extremely high negative correlations (−1 > r > −0.9) with all the other heavy metals. For instance, As recorded extremely high negative correlations (−1 > r > −0.9) with Pb and Cr but strong negative correlation (−0.9 > r > −0.7) with Co, V, Cu, and Zn, while Ni recorded very weak negative correlation (−0.3 > r > −0.1) with Pb and Cr. These findings show that some of these metals originate from different sources of input such as geological source. In a study on the spatial distribution and correlation characteristics of heavy metals in seawater, Zhang et al. (2018) reported that different correlations between dissolved metals and related environmental parameters result from various behaviors, and different sources of metals.

Table 4. Correlation coefficients between the heavy metals recorded in the surface soil dusts.

	Pb	Cd	Cr	As	Co	Ni	V	Cu	Zn	Mn
Pb	1.0000
Cd	0.8086	1.0000
Cr	0.9948	0.7448	1.000
As	−0.9163	−0.5054	−0.9522	1.0000
Co	0.9747	0.9195	0.9470	−0.8038	1.0000
Ni	−0.1060	0.4993	−0.2062	0.4952	0.1187	1.0000
V	0.9917	0.8772	0.9736	−0.8575	0.9953	0.0221	1.0000
Cu	0.9591	0.9419	0.9255	−0.7657	0.9981	0.1794	0.9875	1.0000
Zn	0.9815	0.9062	0.9570	−0.8228	0.9994	0.0861	0.9979	0.9955	1.0000
Mn	−0.9648	−0.9347	−0.9332	0.7789	−0.9991	−0.1590	−0.9905	−0.9997	−0.9973	1.0000

Furthermore, results of the cluster analysis using the Bray–Curtis similarity index on the heavy metals recorded at the different sampling points (Figure 7) revealed two main clusters: D and ACB. According to the SIMPER test results, there was higher association between sampling points B, C and A, a cluster that was different from point D. This is not surprising because points A, B, C are within the Katima Mulilo urban motor park and hence, could be affected to approximately the same degree by a common anthropogenic input, unlike point D which is the remote control site that is 4.7 km away from the motor park. Within the motor park area, there are high vehicular activities with continuous emissions and depositions of vehicle exhaust and dusts including metal particulates on adjacent areas and these could be responsible for proportionate impact of anthropogenic input of heavy metals in clusters B and C as well as A which are within close proximity, about 10 m apart in the motor park. In environmental pollution, particulates transportation and deposition are critical threat to pristine environments. In fact, transboundary pollution is part of the reasons why pollution has remained a global challenge.

Figure 7. Dendrogram for hierarchical clustering analysis of the heavy metals recorded at the different sampling locations.

4. Conclusion

The main aim of this study was to assess the heavy metals pollution status of surface soil dusts at the Katima Mulilo urban motor park, Namibia The results of the study revealed wide range of the concentrations of the heavy metals determined in the Katima Mulilo urban motor park surface soil dusts. Notably, zinc levels were consistently higher than the other heavy metals across the different sampling locations while cadmium recorded the least levels. The present levels of all the heavy metals were generally lower than their respective WHO’s maximum permissible concentrations in soils for the protection of ecosystem’s health. Based on the standard criteria for interpreting heavy metal contaminations of soils and ecological risk, the present results did not suggest meaningful contamination of the surface soil dusts by the heavy metals. However, due to heavy metals’ persistent and accumulative tendencies in any environment, their presence as recorded in the surface soil dusts of the busy Katima Mulilo urban motor park with high intensity of human activities present potential risk of exposures to travelers, vehicle operators, and hawkers especially vulnerable children frequently traversing the area. Thus, it is very important to sustain periodic monitoring of the metal levels with a view to advising precautionary measures to minimize unintended human exposures via inhalation, ingestion, and absorption of the contaminant-laden soil dusts.

5. Limitation of the experiment

The study sample collection was carried out over 8 weeks (04 September to 23 October, 2021). Thus, the results obtained cannot be used to assess the monthly variation of the heavy metals pollution status of the surface soil dusts at the Katima Mulilo urban motor park. The sample was also collected during the peak of the dry season months (September to October) in the study area and hence, the present results will not give the true picture of the surface soil dusts heavy metals pollution at the motor park during the rainy season, and hence seasonal variation.

Acknowledgements

The authors greatly acknowledged the financial support provided by the University of Namibia, Katima Mulilo Campus to undertake this study under the campus Research Agenda project 5. The authors are also thankful to the Katima Mulilo Town Council for the approval granted to carry out the study on the Katima Mulilo urban motor park surface soil dusts. Finally, the authors thank the Analytical Services Laboratory Windhoek Namibia, for the laboratory preparations and analyses of the samples.

Disclosure statement

The authors hereby declared that there is no conflict of interest regarding the conduct and publication of this study. All the authors have read and approved the publication of the article.

Data availability statement

Upon reasonable request, the authors affirm to make the data that support the results or analyses presented in this paper freely available to the person concerned.