Characterizing pollution indices and children health risk assessment of potentially toxic metal(oid)s in school dust of Lahore, Pakistan

Ecotoxicology and Environmental Safety 190 (2020) 110059

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Characterizing pollution indices and children health risk assessment of potentially toxic metal(oid)s in school dust of Lahore, Pakistan

T

Abdul Rehmana,b, Guijian Liua,b,∗, Balal Yousafa, Muhammad Zia-ur-Rehmanc, Muhammad Ubaid Alia, Muhammad Saqib Rashida, Muhammad Raza Farooqd, Zeeshan Javede a

CAS-Key Laboratory of Crust-Mantle Materials and the Environments, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, PR China b State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, The Chinese Academy of Sciences, Xi'an, Shaanxi, 710075, PR China c Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad, 38000, Punjab, Pakistan d Advanced Laboratory for Functional Agriculture, Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, 215123, Jiangsu, PR China e School of Environmental Science and Engineering, Nanjing University of Science and Technology, Nanjing 210044, PR China

ARTICLE INFO

ABSTRACT

Keywords: Potentially toxic metal(oid)s Geo-accumulation index Pollution index Integrated pollution index Pollution load index Health risk assessment

Toxic metal pollution is a renowned environmental concern, especially to sensitive environments like school classrooms and their association with children's health. The study was planned to determine the pollution characteristics of 13 potentially toxic metal (oid)s (PTMs) and their associated children's health risk assessment from school dust samples of considerably three land-use types (residential, roadside, and industrial areas) of Lahore, Pakistan. Geo-accumulation (Igeo), pollution (PI), integrated pollution (IPI) and pollution load (PLI) indexes were used to determine the PTMs contamination and USEPA health risk assessment models were employed to assess the health risks in children. The mean concentrations of Cd, Cr, Cu, Ni, Pb, and Zn for three landuse types were found much higher than the permissible limits. Results of pollution indices revealed that school dust was strongly contaminated with Cd, Pb, and Zn whilst moderately contaminated with Cr and Cu. Moreover, the health risk assessment models revealed no significant non-cancerous risks in children with predominantly highest hazardous index (HI) of Cr in industrial (4.61E-01) and Pb in both roadside (4.30E-01) and residential (2.26E-01) area schools. According to cumulative HI of all PTMs and exposure routes, the land-use areas were in descending order as industrial > roadside > residential. The calculations of hazardous quotient (HQ) showed ingestion was the leading pathway of PTMs exposure through school dust. For carcinogenic health risk (CR), the most prominent PTM was Cr with values of 1.53E-06 in industrial area schools, found close to the tolerable range (1.0E-06). Hence, school dust of Lahore prominently contaminated with eminent PTMs triggering slight health risks predominantly by ingestion exposure to children.

1. Introduction The rapid growth in population, urbanization, motorization, and industrialization result in the enhancement of anthropogenic activities from all over the globe. In the recent era, uncontrolled anthropogenic activities especially in Pakistan comprising stone crushing, coal burning, vehicular and industrial fuel combustion, agriculture, poultry, and animal industries, extensive use of metal contaminated fertilizers and pesticides are continuously polluting the overall environment with

toxic metals (Mohmand et al., 2015). These activities ultimately lead to an increase in the level of particulate matter, and potentially toxic metals loaded dust in the atmosphere (Shah and Shaheen, 2007). Particulate matter with particle size ranges from 1 to 10,000 μm, referred to as dust (Habil et al., 2013), which mostly susceptible to travel long distances. These tiny particles were often lying on bare surfaces of ground or any object and can easily be blown by natural or mechanical force (Adekola and Dosumu, 2001). However, dust can be transported into the indoor environment which is composite particulate matter of

∗ Corresponding author. CAS-Key Laboratory of Crust-Mantle Materials and the Environments, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, PR China. E-mail addresses: [email protected] (A. Rehman), [email protected] (G. Liu), [email protected] (B. Yousaf), [email protected] (M. Zia-ur-Rehman), [email protected] (M.U. Ali), [email protected] (M.S. Rashid), [email protected] (M.R. Farooq), [email protected] (Z. Javed).

https://doi.org/10.1016/j.ecoenv.2019.110059 Received 24 September 2019; Received in revised form 21 November 2019; Accepted 5 December 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.

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both interior (such as stove burning, smoking, wall corrosion, and painting, etc.) and exterior (i.e. traffic emission, waste burning, automobile repairing, welding, soldering, playground dust etc.) pollution sources (Wong et al., 2006). Particle size and potentially toxic metal composition of dust are vital components to decide the environmental air quality and hence, human health (Yap et al., 2011). Potentially toxic metal (oild)s (PTMs), also known as heavy metals and poisonous elements, perhaps due to their densities and/or atomic masses and adverse effects on living organisms, lies from groups III to V in periodic table and classify into elemental metals, transition metals, metalloids, lanthanides and actinides (Kamunda et al., 2016). The PTMs have become ubiquitous due to the rapid pace of urbanization and industrialization (Johnson et al., 2011). Therefore toxic metal pollution is now a major environmental issue all over the world. The PTMs sourced from various natural and anthropogenic activities remain deposited in the earth's crust, as they are not biodegradable or readily phyto-available. Consequently, it can be transported via multiple agents, i.e., air, water, living organisms etc. While, continuous addition of PTMs into natural environments, i.e., soil, air, water via various sources refer as PTMs contamination, some of all metals like iron, zinc, copper and manganese are essential for normal growth and development of living organisms but only at specific permissible levels (Kosolapov et al., 2004). When PTMs exceeding their maximum permissible levels, they become harmful and toxic to the environment refer as PTMs polluted environment. There are a lot of published literature which suggest the extent of PTMs pollution levels with respect to their corresponding background values through different pollution characterizing indices, i.e., geo-accumulation index, pollution load index, etc. and consequently the composition and source of PTMs depend upon various activities of the specific study area (Ali et al., 2017; Duzgoren-Aydin et al., 2006). However, some of the other PTMs like cadmium, arsenic, nickel, and lead have more significant anthropogenic input into the natural environment having low permissible levels and potential health concerns (Ademuyiwa et al., 2009; Afolabi et al., 2015; Akinwunmi et al., 2017). The dust containing tiny particles with exceptional susceptibility to retain PTMs have significant ecological and human health concerns while exposed through any pathway. Numerous studies have been suggested three main routes of human dust exposure, i.e., direct or indirect ingestion, inhalation, and dermal contact (Ali et al., 2017; Zheng et al., 2010). Through these pathways, toxic metals can invade the human body and cause serious health risks, i.e., disorder and malfunctioning of the nervous and reproductive system and gastrointestinal problems (Wu et al., 2010; Yousaf et al., 2016; Zheng et al., 2009). Continuous exposure of PTMs like Cd and Cu to the human beings is most probable to cause lung cancer (Zukowska and Biziuk, 2008), Pb and Zn have adverse effects on central nervous system (Kaufmann et al., 2003), and Cr can be carcinogenic to the respiratory organs (Langård et al., 1980). Pb exposure is likely to cause abnormalities in behaviors and learning issues in children (Rehman et al., 2018). Most importantly, dust carrying PTMs can accumulate in human internal organs while young children are most vulnerable to dust as compared to adults, as they try to ingest soils, eat dirty foods with dirty hands, play on dusty floor, and put contaminated stuff like toys and grimy hands into their mouths, additionally, the immune system in early age is not much developed either to resist the adverse effects of metal toxicity (Luo et al., 2012; Tahir et al., 2007). Children spend about 6 h of their awakened time of the day into schools for all seasons instead of holidays (Habil and Taneja, 2011). So, it becomes more crucial to assess such sensitive environments like school classrooms for PTMs as they can be enriched by several outdoor and indoor activities (Rasmussen, 2004). Thus PTMs can adversely affect the children's health and, ultimately, their learning and intellectual outcomes in both academic and social life. Studies on the indoor school environment in regards to PTMs pollution and children's health have been conducted around the world (Table 2). In-country like Pakistan, the living and working environments are

sometimes unhygienic because of poor implementation of environmental and sanitation policies and public awareness. Consequently, young children and adults are often suffering from illness and sometimes death due to continuous exposure to environmental potentially toxic pollutants. The elevated amount of PTMs have been well documented for the environment of Lahore, which situated at northeastern side of Pakistan adjacent with northern area of India, has now become most industrialized site of sub-continent with serious environmental pollution issues (Biswas et al., 2008; Ghauri et al., 2007; von Schneidemesser et al., 2010). Besides, Lahore has recently declared as the most polluted city of the country, and schools were called off several times due to environmental pollution problems in metropolitan areas of the city. To date, a few studies have been conducted on health risks posed by PTMs from dust samples for Pakistan (Aiman et al., 2016; Eqani et al., 2016; Mohmand et al., 2015) however, studies on school indoor environments with potentially toxic metals concerns and their impact on children health have been scarce. Therefore, this study aimed to assess 1) the concentrations of 13 PTMs, i.e., As, Cd, Cr, Cu, Ge, Mo, Ni. Pb, Sb, Sn, Sr, V, and Zn, 2) pollution level of PTMs by calculating different pollution indices, i.e., pollution index, pollution load index, integrated pollution index and geo-accumulation index, and 3) in the last, both non-carcinogenic and carcinogenic health risks assessment of children posed by PTMs of school dust samples. 2. Material and methods 2.1. Area description Lahore (Latitude 31° 34′ 55″N, Longitude 74° 19′ 46″), the capital of province Punjab having a population of about 11 million people, ranked the second-most populous city of Pakistan after Karachi. The city covers an area of about 1772 km2. Normally, the environment is very dusty around the city because of dense traffic and industrial works especially with a semi-arid climate and low rainfall. Lahore ranked first in terms of education on the national level, having hundreds of schools at primary, secondary and higher secondary levels with millions of students. Cumulatively 40 primary and secondary schools based on three land-use types, i.e. residential, roadside and industrial areas of Lahore city, were randomly selected for this study. Though Lahore is a kind of city where the recognition of specific land-use type is a bit difficult, the schools were selected carefully. Because the city is bestrewed by small industries manufacturing metal-containing products, vehicular and electronics-based workshops, and spare parts markets. For residential area schools, no to the minimum influence of roadside activities and industries were considered. The schools in the vicinity of busiest roads with dense traffic and heavy industrial influence considered as roadside and industrial area schools, respectively. The locations of selected schools as per land-use consideration are given in Fig. 1. 2.2. Sampling strategy The number of selected schools for residential, roadside, and industrial areas was 16, 11, and 13, respectively. Dust samples from desks, benches, and tables were collected from the classrooms with the help of small plastic brush onto the filter paper and carefully shifted into plastic zip bags in august, 2018. A composite sample of 5–7 g representing one school was made by dust collection from 3 to 5 different classrooms of the selected school. Local characteristics of the area were carefully observed while selecting the school for a particular land-use type. 2.3. Acid digestion Collected dust samples were first oven-dried at 70 °C for two days. Though the dust samples were physically seemed to be very fine with 2

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Fig. 1. Locations of schools that were selected for dust sampling.

no pebbles, gravel, sand, and other organic stuff, but still passed through a 200-μm mesh sieve. Usually, finer particles of dust carry higher toxic elemental fractions and susceptible to cause hazards, especially to school children (Duggan and Inskip, 1985). To assess metal concentrations, 0.2 g of each sample was weighed, transferred into sterilized Erlenmeyer flask of 50 ml volume, and allowed to digest overnight with the addition of aqua regia (4 ml of HNO3 and 12 ml of HCL to each sample) in the fume hood. After overnight digestion, all the samples were heated at 210 °C on hotplate until evaporated near to dry state. Allow samples to heat at 100 °C with the addition of 5 ml deionized (DI) water until complete or near to dryness. Subsequently, 15 ml volume was made by adding DI water into all samples and then filtered for instrumental analysis.

to understand the cumulative explanation of PTMs pollution in school dust (Faiz et al., 2009; Jahan and Strezov, 2018). 2.5.1. Geo-accumulation index (Igeo) The geo-accumulation index is the most eminent method developed by (Muller, 1969) to assess the PTMs pollution levels with respect to their corresponding background values mainly from soil and sediment samples (Aiman et al., 2016; Irshad et al., 2019; Li et al., 2014; Rehman et al., 2018; Trujillo-González et al., 2016). Besides, many researchers have also used Igeo for dust samples (Eqani et al., 2016; Faiz et al., 2009; Gope et al., 2017; Hou et al., 2019; Li et al., 2017; Olujimi et al., 2015) For geo-accumulation index, the PTMs pollution levels are categorized into seven different classes given in Table S1 (Martínez and Poleto, 2014; Wei et al., 2015) while the formula for calculation of Igeo is;

2.4. Instrumental analysis

Igeo = log 2

Inductively coupled plasma mass spectrometer (ICP-MS, Agilent 7500cx, Santa Clara, CA, USA) was used to analyze the concentrations of 13 PTMs (As, Cd, Cr, Cu, Ge, Mo, Ni, Pb, Sb, Sn, Sr, V, and Zn). Multi elemental stock solutions of 5, 10, 25, and 50 mg kg−1 concentrations were prepared to calibrate the ICP-MS. Blank samples were prepared to know the metal traces of acids and the DI water used in the digestion process. After analyzing every ten samples, standard solutions were run to know the precision and accuracy of ICP-MS and to minimize the error.

Cn 1.5Bn

(1)

where Cn is the concentration of PTM, 1.5 is a constant factor to control the erroneous variations of environmental influence, and Bn is the background values of PTM. Since dust contains tiny particles of soil, can conceivably be transported to the school environment and deposited on bare surfaces, the background values of soil can be used for dust. As environmental baseline data is yet to establish, some studies based on Pakistan have used the elemental values from (Turekian et al., 1961) as background values (Eqani et al., 2016). 2.5.2. Pollution index (PI) The pollution index is also known as contamination factor refers to the ratio of elemental concentration of the sample to the background value of the element and the formula for calculation is;

2.5. Pollution characteristics Many quantification methods have been used to calculate the PTM pollution levels in natural environmental samples, e.g., dust, soil, and sediments. In this study, the indexes of geo-accumulation (Igeo), pollution (PI), integrated pollution (IPI), and pollution load (PLI) (Faiz et al., 2009; Jahan and Strezov, 2018) were employed to assess the degree of PTMs pollution in school dust samples of Lahore. Index of geo-accumulation distinct from other pollution indices because of log function and constant factor of 1.5 to avoid lithogenic effects that may be attributed to the variations in background values (Othman et al., 2019). However, IPI shows the mean value of the PIs of all PTMs, and PLI helps

PI =

Cn Bn

(2)

where Cn is the sample concentration and Bn is the background value of the toxic metal. While the classification of PI is also given in Table S1. 2.5.3. Integrated pollution index (IPI) The arithmetic mean of pollution index for every individual toxic 3

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metal is defined as integrated pollution index and the classification is given in Table S1. The given formula can calculate IPI.

IPI =

PIi n

CRI = MDI × SF (slope factor ) 2.7. Quality assurance

(3)

Acids used for sample digestion and certified reference material (GBW07406) (Janotková et al., 2013; Ubaid Ali et al., 2019) purchased from the National Center of Standard Materials of China (NCSMC). The certified reference material (CRM) and a blank sample with no dust material progressed through the same digestion procedure and analyzed for PTMs. The recovery rate of all PTMs for CRM was (95.3–103.8%) within the limits of certified standards. Duplicate samples, along with the DI water used in the experiment analyzed for PTMs to ensure the precision and quality of the data. The digested solutions of selected PTMs were within the recovery range of 91.4 and 103.6%. The precision of ICP-MS was verified by testing standard solutions after every ten samples. The calibration curves were linear within the range (R2 > 0.99) that indicates the accuracy and consistency of the instrument for the PTMs determination.

where PIi represents the pollution index of i element and n is the number of total values (samples). 2.5.4. Pollution load index (PLI) The pollution load index describes the overall contamination level and accumulative explanation of the pollution status of PTMs. It was proposed by (Tomlinson et al., 1980) and classified as either pollution or no pollution of toxic metals. It can be calculated by IPI values as; 1

PLI = (IPIE1 × IPIE 2 × IPIE 3 × IPIE 4 × ……×IPIEn)

n

(3)

where, IPIEn is the mean value of pollution index/contamination factor of PTMs and n is the number of toxic metals (Jahan and Strezov, 2018). 2.6. Health risk assessment

3. Results and discussion

In the present study, the health risk has been assessed for school children. Above-given methods can assess contamination of dust PTMs; however, health risk can be evaluated by two steps as provided by USEPA, i.e., exposure assessment and risk characterization (US-EPA, 1989; US-EPA, 2011) . USEPA's models of health risk assessment are extensively used to determine both carcinogenic and non-carcinogenic risks of PTMs through various exposure routes (Irshad et al., 2019; Rehman et al., 2018; Tan et al., 2016). However, the parameter used in this study for USEPA's models were explained in Table S2.

3.1. Toxic metal concentration The concentrations (mg kg−1) of selected PTMs of dust samples and permissible limits according to international guidelines were summarized in Table 1. The worldwide comparison of PTMs data of school dust samples was also compiled from literature and given in Table 2, which showed that PTMs concentrations in school dust of Lahore, Pakistan were higher than most of the other countries. The ICP-MS results showed that the mean concentrations of PTMs were in descending order asZn > Pb > Sr > Cr > Cu > Ni > V > As > Cd > Sn > Mo > Sb > Ge which was quite similar for both residential and roadside areas however the trend for industrial area was Zn > Cr > Sr > Pb > Cu > Ni > V > As > Cd > Sn > Mo > Sb > Ge. Taken as a whole, Table 1 showed that there is no significant difference has been found in the sequence rank of all toxic metals concerning land-use type. However, the land-use types have ranked as a descending order of industrial > roadside > residential area schools with respect to mean concentrations of all toxic metals. To date, there are no national guidelines obtained for PTMs of soil or dust in Pakistan; the data were compared with the guidelines of neighboring countries, i.e., India (Awashthi, 1999) and China (SEPAC, 1995; 2005). The concentrations of Cd, Cr, Cu, Pb, and Zn were significantly higher than the background values (Turekian et al., 1961) in all selected schools. More noticeably, the average values (mg kg−1) of Zn as 866, 1090, and 1253 for residential, roadside, and industrial area schools, respectively, have been found much higher than both Chinese and Indian guideline values. Though Zn is an essential nutrient, its higher concentrations can disrupt the functioning of the brain, respiratory and gastrointestinal tract and hence may cause cancer (Fosmire, 1990; Plum et al., 2010). Higher concentrations of Zn showed clear anthropogenic impact like airborne contamination by small industries working on iron, aluminum, and other metals related products. As it is an essential nutrient for plants, the intensive use of fertilizers, pesticides, and insecticides also be the source of Zn in school dust samples (Olama et al., 2014). The mean lead (Pb) concentrations (mg kg−1) were 339 ranges from 192 to 621 in roadside area schools, clearly, indicate the high impact of vehicular emissions of leaded fuel burnings. Since 2002, the leaded fuel has been prohibited in Pakistan, but its deposition in soil may be the source of dust exposure (Qadir et al., 2008). On the other hand, the usage of lead batteries, paints, glazes in pottery pesticides and insecticides containing lead arsenate may also be the source of high Pb exposure to children via dust (Abdullah et al., 2015). The highest mean concentration of Cd was 6.13 mg kg−1 in industrial area schools followed by 5.73 mg kg−1 in roadside area schools, which were higher than the permissible limits set

2.6.1. Exposure assessment Risk is always around if there is any contamination of toxic chemicals to any environment, and it can be lethal via exposure pathways as far as children's health concerns. The dust particles exposed to children via three routes, i.e. oral ingestion, inhalation, and dermal contact.

MDIIng =

C × RIng × EF × ED × CF BW × AT

(4)

MDIInh =

C × RInh × EF × ED PEF × BW × AT

(5)

MDIDer =

C × SA × CF × AF × ABF × EF × ED BW × AT

(6)

Equations (4)–(6) were used to calculate the average metal daily intake dose for oral ingestion (MDIIng), inhalation (MDIInh), and dermal contact (MDIDer). Since, local guidelines for human health risk assessment has not been developed yet, the parameter used for the calculations of USEPA's health risk models were taken from literature on dust exposure to the children based on either Pakistan (Mohmand et al., 2015) or/and school environment (Chen et al., 2014), and given in Table S2. 2.6.2. Risk characterization For children's health risk characterization of PTM exposure via school dust, the hazards quotient (HQ), hazards index (HI), and carcinogenic risk index (CRI) were employed. The HQ and HI explain noncarcinogenic risk, and CRI estimates the probability of cancer risk potential of PTMs to children. equations (7)–(9) were used to evaluate these three characteristics.

HQ = HI =

(MDI ) Metal daily intake dose (RfD ) Reference dose HQi

(9)

(7) (8) 4

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Table 1 Statistical summary of PTMs in school dust samples from the residential, roadside, and industrial areas of Lahore. As

Cd −1

Residential Area (n = 16)

Roadside Area (n = 11)

Industrial Area (n = 13)

Permissible limits

AM SD Min Max Median GM AM SD Min Max Median GM AM SD Min Max Median GM Chinaa WHOb Indiac BGd

Cr −1

Cu −1

Ge −1

mg kg

mg kg

mg kg

mg kg

mg kg

6.03 3.48 0.07 9.95 7.55 3.45 8.91 3.07 0.03 11.5 9.65 5.77 8.33 3.87 0.07 12.3 9.51 4.61 30 20 NA 13

4.12 1.68 0.42 6.82 4.13 3.52 5.73 3.68 2.45 14.8 4.43 5.21 6.13 2.11 4.16 10.7 5.73 5.82 0.6 3 3–6 0.3

139 72.8 38.4 305 129 121 156 61.5 77.3 258 124 145 293 175 94.2 662 236 252 200 100 NA 90

93.1 34.5 17.1 153 92.8 84.2 131 36.3 83.3 190 144 126 133 32.6 77.1 200 125 129 100 100 135 45

0.16 0.04 0.05 0.23 0.17 0.16 0.18 0.03 0.13 0.23 0.17 0.18 0.24 0.05 0.12 0.32 0.17 0.18 NA NA NA 1.6

Mo −1

Ni −1

Pb −1

Sb −1

Sn −1

Sr −1

V −1

Zn −1

mg kg

mg kg

mg kg

mg kg

mg kg

mg kg

mg kg

mg kg−1

0.84 0.65 0.01 1.95 0.64 0.52 1.83 1.14 0.48 3.94 1.93 1.42 1.92 1.29 0.02 4.52 1.49 0.95 NA 40 NA 2.6

44.7 11.5 19.6 62.2 46.7 43.1 56.2 6.37 48.5 65.3 53.9 55.7 63.1 19.7 44.7 120 56.8 60.4 50 50 75 68

177 70.5 25.1 364 175 159 339 142 192 621 288 315 202 40.6 141 278 187 198 300 100 250 20

0.18 0.17 0.03 0.57 0.11 0.11 0.41 0.21 0.03 0.71 0.35 0.32 0.25 0.14 0.03 0.44 0.22 0.21 NA NA NA 1.5

2.51 2.02 0.01 6.13 2.06 1.12 4.91 3.05 0.05 10.1 4.83 3.05 2.85 2.53 0.01 5.97 2.91 0.83 NA NA NA 6

177 48.9 40.9 260 183 167 203 28.2 154 253 200 201 209 25.2 158 248 212 208 NA NA NA 300

30.2 13.8 1.09 49.1 30.9 22.6 41.9 14.9 5.81 64.9 42.7 37.2 40.5 20.5 1.47 73.3 42.7 28.2 NA NA NA 130

866 287 138 1320 861 790 1090 233 798 1532 1055 1066 1253 231 912 1656 1224 1234 200 300 300 95

AM = Arithmetic mean, SD= Standard deviation, GM = Geometric mean, BG= Background. a (SEPAC, 1995; 2005). b (Khan et al., 2018). c (Awashthi, 1999). d (Turekian et al., 1961).

by China (0.6 mg kg−1) and European Union (1.5 mg kg−1). The source of Cd was probably the industrial activities like PVC, Cd containing batteries, platting, paint, and fertilizers (rock phosphate) production industries (Abdullah et al., 2015; Zafar et al., 2015). The highest mean concentrations of Cr were found in industrial area schools as 293 mg kg−1; however, mean values (mg kg−1) for Sr, Cu, and Ni in industrial area schools as 209, 133, and 63.1 respectively, were slightly higher than the roadside area schools. The source of these PTMs probably the use of different chemicals and salts in leather industries, smelters, glass industries, manufacturing of sound devices (Abdullah et al., 2015; Zheng et al., 2010).

3.2. Pollution characteristics The geo-accumulation index (Igeo), pollution index, integrated pollution index, and pollution load index were used to assess the contamination level of all selected PTMs. These methods have widely been used to determine the pollution level of toxic metals from dust, as reported by (Aiman et al., 2016; Faiz et al., 2009; Muller, 1969; TrujilloGonzález et al., 2016). 3.2.1. Geo-accumulation index (Igeo) The Igeo values of PTMs are given in Fig. 2. The contamination degree of toxic metals ranged from 0 to 6 class (Table S1), indicating the pollution of individual toxic metal in school dust samples. The Igeo

Table 2 Toxic metal concentrations mg kg−1 of the schools environment of various countries. Country a

Pakistan (N = 40) Indiab (N = 210) Chinac (N = 97) Malaysiad e (N = 90) Hong Kongf (N = 53) Nigeriag (N = 55) Mexicoh (N = 25) Armeniai (N = 12) South Africaj (N = 32) a b c d e f g h i j

As

Cd

Cr

Cu

Ge

Mo

Ni

Pb

Sb

Sn

Sr

V

Zn

7.51 13.2 2.04 1.59

5.17 3.75 – 0.23 8.48 855 2.83 1.18 0.64

194 3.28 150 11.9 – 41.8 10.7 39.1 49.6

116 10.5 70.8 30.2 247 40.9 27.9 149 32.7

0.18 – – – – – – – –

1.43 – – – – 0.59 – 29.4 –

53.6 4.02 34.6 9.04 – 12.7 4.75 64.5 21.2

230 19.3 181 254 200 27.6 28.2 156 47.1

0.26 – – – – – – – 1.34

3.28 – – – – 0.49 – – –

195 – – – – 41.1 – – –

36.7 – 67.6 – – 21.7 7.63 – –

1053 78.1 462 145 2294 121 297 170 186

Present study. (Habil et al., 2013). (Chen et al., 2014). (Latif et al., 2014). (Omar et al., 2012). (Tong and Lam, 1998). (Olujimi et al., 2015). (Meza-Figueroa et al., 2007). (Maghakyan et al., 2017). (Olowoyo et al., 2016). 5

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Fig. 2. Geo-accumulation index of PTMs in school dust samples for residential, roadside and industrial area schools.

values of As, Ge, Mo, Ni, Sb, Sn, Sr, and V were ≤0 showing no contamination of these metals in all samples. However, a few samples from the roadside and industrial area schools showed values greater than 0 for Mo, Sn, and Ni. Furthermore, maximum values for Cr and Cu lay in class 1, which indicates uncontaminated to moderately contaminated school dust. The mean Igeo values for Cr and Cu were −0.16 and 0.32 from residential, 0.10 and 0.90 from the roadside, and 0.90 and 0.93 from industrial area schools, respectively. The heavily contaminated PTMs with maximum of their values found in class 4 were Cd and Zn, while Pb is heavily contaminated (class 4) in roadside area schools and moderately to heavily contaminated (class 3) in residential and industrial area schools. Besides, the mean values of Cd, Pb, and Zn are 2.97, 2.41, and 2.47 for residential, 3.46, 3.39, and 2.90 for roadside, and 3.69, 2.72, and 3.11 for industrial area schools, respectively. The consequences of anthropogenic activities could be the reason for various PTMs accumulation. Besides, air transportation and atmospheric deposition may impart contaminated media to become ubiquitous (Jin et al., 2019). The PTMs like Cd, Cr, Cu, Pb, and Zn are known to be urban elements, and their raised concentrations are ultimately the results of the anthropogenic activities. Even high accumulation of Cd, Pb, and Zn observed in the residential area schools. Immense use of rechargeable batteries, plastic toys (for kindergarten and playgroup), paints and pigments (painting activities), fertilizers and insecticides (in the playground) in schools could be the source of Cd and Zn (Alam et al., 2015; Wuana and Okieimen, 2011). Additionally, teachers might have a habit of cigarette smoking, which can be the source of Cd deposition in school dust (Piadé et al., 2015). The Zn contributes to dust pollution due to the rusting of metallic materials like chairs, tables, desks, benches, windows, and doors. Emissions from fuel burnings are an obvious source of Pb in school dust sampled from the vicinity of dense traffic areas (Saeedi et al., 2012). However, the contribution of household and industrial burnings to Pb accumulation in school dust is also significant. Evidently, a major contributor to Pb pollution in the Lahore environment is industrial emission, as reported by (von Schneidemesser et al., 2010). Moreover, corrosion and eruption of wares, railings, and walls often contain Cd, Cr, Cu, and Zn, which can ooze to the environment and accumulate in school dust (Shabbaj et al., 2018). Results of the present study revealed Lahore school dust has high contamination of Cd, Cu, Ni, Pb, and Zn as compared with previous studies on dust and soil of Islamabad and Lahore, Pakistan (Aiman et al., 2016; Faiz et al., 2009).

pollution in roadside and industrial area schools. Furthermore, PI and IPI values of Cd, Pb, and Zn showed an extreme level of pollution for all land-use settings. On the other hand, pollution load index (PLI) which indicates the cumulative pollution load of all PTMs and the results of PLI were 0.90, 1.33, and 1.26 for residential, roadside and industrial area schools, respectively, which indicate that no to low pollution load found in residential area schools but high pollution load of all PTMs were in roadside and industrial area schools. 3.3. Children health risk assessment The air transported dust may laden with, and deposit toxic metals to the bare surface, food, drinks, and other appliances and hence posed health risks to residents especially children who are highly susceptible to toxic materials with relatively less developed immune system (Li et al., 2013; Zheng et al., 2010). The non-carcinogenic and carcinogenic health risks associated with toxic metals for children were calculated by using the USEPA health risk assessment method. It is quite useful to estimate the exposure of PTMs carrying dust to school children by different pathways, i.e., ingestion, inhalation, and dermal contact. The rate of emission and intake of particles can be compared with those ascertained for dust. The total risk for carcinogenic and non-carcinogenic risk can be calculated by summing up all the individual values of all exposure pathways as well as all PTMs for selected land-use area schools (USEPA, 2002; USEPA, 2011; Ali et al., 2017). The average metal daily exposure to children through different routes such as ingestion (MDIing), inhalation (MDIinh) and dermal contact (MDIder), rate of their reference doses (Ring and Rinh) and contact frequency were used as prescribed by USEPA standard guidelines and given in Table S2 (USEPA, 2002). The hazard quotient (HQ) and hazard index (HI) of non-carcinogenic and carcinogenic health risks were calculated subsequently with the help of MDIing, MDIinh, and MDIder values for the PTMs exposed to children via school dust. Where HI indicated the cumulative risk of all hazard quotients as well as all toxic metals for selected land use type (Zheng et al., 2010). In addition, only nine toxic metals (As, Cd, Cr, Cu, Ni, Pb, Sr, V, and Zn) for non-carcinogenic and five toxic metals (As, Cd, Cr, Ni, and Pb) for carcinogenic health risk assessment were selected for the present study. The reference dose (RfD) for different exposure pathways and slope factors for the calculations of noncarcinogenic and carcinogenic hazard indices were given in Table S3. Health risk consequences of non-carcinogenic and carcinogenic by HQ, HI, and CR (cancer risk) calculations have been given in Table 3. The prominent route of toxic metals exposure to children is ingestion, followed by dermal contact and inhalation of dust particles for noncarcinogenic risks. There were no significant non-carcinogenic health risks of PTMs found in all land-use settings as the values of HQs for all exposure routes were below 1, which indicates no adverse non-cancerous health effects due to exposure of school dust to children by all pathways. However, some of all PTMs, i.e. As, Cr, and Pb, have shown values very close to 1 for different exposure pathways, which indicate slight health risks as further anthropogenic activities may exceed their pollution levels and hence health risk.

3.2.2. PI, IPI, and PLI The values ranges of PI, IPI, and PLI for pollution level descriptions are given in Table S1. While Fig. 3 shows the IPI (mean of PI) and PLI of all school dust samples according to several land-use types of Lahore. The results revealed that there had been no to low pollution found for As, Ge, Mo, Ni, Sb, Sn, Sr, and V as their values were less than 1 for all land-use settings. Chromium was moderately polluted in residential and roadside area schools, and its IPI value exceeds 2 in industrial area schools, which indicates a high level of pollution. The Cu showed middle-level pollution in the case of residential area schools and high 6

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Fig. 3. Integrated pollution index (IPI) and pollution load index (PLI) of PTMs in school dust of Lahore.

For residential area schools, the highest values have been found for HQing of Pb (2.24E-01) followed by Cr (2.06E-01) and As (8.79E-02), for roadside area schools, Pb (4.29E-01) followed by Cr (2.30E-01) and As (1.31E-01), and for industrial area schools, Cr (4.33E-01) followed by Pb (2.56E-01) and As (1.22E-01). For all land-use settings, the Cr have higher values in the case of HQinh and HQder than other PTMs. In addition, the descending order of PTMs in residential area schools was for HQing as Pb > Cr > As > V > Zn > Cu > Ni > Cd > Sr, for HQinh as Cr > Pb > As > Cd > Zn > Cu > Ni and for HQder as

Cr > As > V > Pb > Cd > Zn > Ni > Cu > Sr. Consequently, the descending order of PTMs for HQinh was found, same for all landuse settings, while in case of HQing, the PTMs order of residential area schools was same as roadside area schools, furthermore, HQder of residential area schools showed same order as industrial area schools. In the present study, the hazard index (HI) has been calculated in order to assess the cumulative non-carcinogenic risk from every individual toxic metal and exposure route of school dust. Toxic metal rank for HI was observed same for residential and roadside area schools as descending

Table 3 Non-carcinogenic and carcinogenic risk indices of potentially toxic metal (oids) of school dust samples. As

Cd

Cr

Cu

Ni

Pb

Sr

V

Zn

HI

HQIng 8.79E-02 1.80E-03 HQInh 2.46E-06 5.04E-07 6.65E-03 7.44E-04 HQDer HI 9.46E-02 2.54E-03 CR 1.12E-08 3.18E-09 Roadside Area Schools (n = 11)

2.06E-01 6.05E-04 1.28E-02 2.19E-01 7.27E-07

1.03E-02 2.87E-07 3.55E-05 1.03E-02

9.92E-03 2.70E-07 3.80E-05 9.96E-03 4.67E-09

2.24E-01 6.26E-06 1.55E-03 2.26E-01 1.87E-10

1.31E-03

1.90E-02

6.76E-06 1.31E-03

1.96E-03 2.10E-02

1.28E-02 3.59E-07 6.62E-05 1.29E-02

6.37E-02 8.79E-05 2.65E-03 6.64E-02 1.49E-07

HQIng 1.31E-01 2.53E-03 HQInh 3.67E-06 7.11E-07 9.93E-03 1.63E-03 HQDer HI 1.41E-01 4.16E-03 CR 1.67E-08 4.48E-09 Industrial Area Schools (n = 13)

2.30E-01 6.77E-04 5.24E-04 2.31E-01 8.14E-07

1.45E-02 4.06E-07 5.95E-05 1.46E-02

1.24E-02 3.38E-07 1.53E-06 1.24E-02 5.85E-09

4.29E-01 1.20E-05 4.89E-04 4.30E-01 3.58E-10

1.50E-03

2.66E-02

1.86E-07 1.50E-03

1.33E-02 3.99E-02

1.61E-02 4.52E-07 3.21E-06 1.61E-02

9.61E-02 9.93E-05 2.88E-03 9.90E-02 1.68E-07

HQIng HQInh HQDer HI CR

4.33E-01 1.27E-03 2.68E-02 4.61E-01 1.53E-06

1.47E-02 4.10E-07 5.07E-05 1.48E-02

1.39E-02 3.77E-07 5.31E-05 1.39E-02 6.53E-09

2.56E-01 7.13E-06 1.76E-03 2.57E-01 2.13E-10

1.55E-03

2.57E-02

8.00E-06 1.56E-03

2.65E-03 2.83E-02

1.85E-02 5.20E-07 9.58E-05 1.86E-02

9.87E-02 1.84E-04 4.65E-03 1.03E-01 3.11E-07

Residential Area Schools (n = 16)

1.22E-01 3.42E-06 9.27E-03 1.32E-01 1.56E-08

2.71E-03 7.59E-07 1.12E-03 3.83E-03 4.78E-09

7

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order Pb > Cr > As > V > Zn > Cu > Ni > Cd > Sr but in case of industrial area schools, Cr ranked as first and Pb as second while rest of the PTMs ranked in same order as other land-use types. Hazard index values for all PTMs were below 1 in all land-use settings which showed that there are no adverse health problems due to these PTMs. But Cr in industrial area schools and Pb in roadside area schools showed values of 4.61E-01 and 4.30E-01 respectively, indicating the slight risk of non-carcinogenic health hazards. On the other hand, the cumulative hazard index of all PTMs showed that ingestion was the most prominent mode of PTMs exposure via school dust for this study. The cumulative hazard index (HI) values of all PTMs with respect to exposure routes were as, for ingestion, 9.87E-02 in industrial, 9.61E-02 in roadside and 6.37E-02 in residential area schools, for dermal contact, 4.65E-03 in industrial, 2.88E-03 in roadside and 2.65E-03 in residential area schools, and for inhalation, 1.84E-04 in industrial, 9.93E-05 in roadside and 8.79E-05 in residential area schools. Although, the observed values of HI were in the safer limit with no health risks, but the descending order for exposure route was HQing > HQder > HQinh for all land-use types. A similar kind of trend for the exposure routes of dust PTMs to children was found in other studies (Chen et al., 2014; Tan et al., 2018). The increased tendency of children to ingestion route of toxic metals via dust possibly due to habit of unintentional taking everything into their mouth, carelessness to cleanliness, and playing in the dusty environment (Habil et al., 2013; Latif et al., 2014). Even though, the HI values were fallen within the safe range but the higher concentrations of PTMs can impose severe developmental and neurological health effects specifically to children because of higher exposure rates of toxic metals with respect to their body weight (Ali et al., 2017; Cheng and Hu, 2010; He et al., 2009; Li et al., 2014). However, according to HI values of all toxic metals as well as exposure routes, the descending order of land-use types was observed as industrial > roadside > residential area schools. The carcinogenic health risks were assessed for school children, and values are given in Table 3. Because of the non-availability of reference slope factors, the cancer risks (CR) were evaluated for As, Cd, Cr, Ni, and Pb through inhalation mode of exposure. For carcinogenic health risks, only Cr was the prominent metal among other selected PTMs for all land use types as its calculated values were close to the acceptable/ tolerable range (1.0E-04 to 1.0E-06), which means that Cr can cause non-significant cancerous health risks to school children (Chen et al., 2016). The cancer risk (CR) values for Cr were 1.53E-06, 8.14E-07, and 7.27E-07 in industrial, roadside and residential area schools, respectively. However, the cancer risk for other PTMs was negligible as their values were less than the acceptable value (1.0E-06). The trend of Cr carcinogenic risk assessment for children in the present study found to be quite similar to a study on classroom dust in Ogun State, Nigeria (Olujimi et al., 2015). It is uncertain to understand the association between PTMs pollution characteristics and health risk assessment due to a lack of consistency in environmental processes and human characteristics. Pollution characteristics can be obtained using reference material, which considers being unpolluted; likewise, health risk also needs a reference dose, which counts being as unharmful or tolerable to humans. However, in this study, school dust was deliberately polluted with Cd, Pb, Zn, Cr, and Cu with no to less harmful aspects on children health. Chromium was the only PTM having HI and CR values close to the acceptable ranges to cause non-carcinogenic and carcinogenic risks to the children, while pollution indices suggest moderate level pollution of Cr. Contrastingly, Cd was found strongly polluted in school dust having negligible health risks on children. It is obvious to understand that these elements have potentially harmful health effects, and further contamination of these PTMs to school dust can be lethal to the children.

Pakistan, according to their land-use types, i.e. residential, roadside and industrial area schools. All samples were subjected to the standard analytical procedure, and concentrations of 13 PTMs were obtained using ICP-MS. The results indicate elevated levels of concentrations for Zn, Pb, Cr, Cu, and Cd as compared to International guidelines. The geoaccumulation index and other pollution indexes showed substantial contamination of Cd, Pb, and Zn and moderate contamination of Cr and Cu. Hazard index of the individual as well as cumulative of all PTMs showed no to very less non-carcinogenic health risks; however, ingestion was the most prominent mode of PTMs exposure to children. For carcinogenic risk, only Cr was found with slight cancer risk as its values laid very close to the tolerable range (1.0E-04 to 1.0E-06). The pollution characteristics suggest that school dust the polluted by PTMs especially immense influence of Cd, and the carcinogenic risks on children's health were close to the acceptable range especially for Cr. Consequently, some remediation strategies should be adopted to reduce the PTMs exposure risks like ultra-cleanliness of indoor and green infrastructure of outdoor school buildings to protect vulnerability to children. The findings of this study help to increase awareness about PTMs pollution among the public and government to take essential steps to improve environmental quality in schools. In spite of this, the studies on isotopic identification of potential sources, chemical speciation, along with morphological characteristics of terrestrial stuff, can enhance our knowledge to develop more remediation techniques of PTMs from school environments. Acknowledgments This work was supported by the National Natural Science Foundation of China (No. 41672144) and Key research and development projects of Anhui Province (1804b06020358). We are greatly acknowledge the efforts of Sheikh Sohail Ahmed, Muhammad Shoaib, and Muhammad Umair Riaz for their help and all school head teachers for their cooperation during sampling. We would also like to thank Qumber Abbas, Rafay Ahmad, Mudassir Hussain and Samina Irshad for their valuable suggestions to improve the quality of manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoenv.2019.110059. References Abdullah, M., Fasola, M., Muhammad, A., Malik, S.A., Bostan, N., Bokhari, H., Kamran, M.A., Shafqat, M.N., Alamdar, A., Khan, M., 2015. Avian feathers as a non-destructive bio-monitoring tool of trace metals signatures: a case study from severely contaminated areas. Chemosphere 119, 553–561. https://doi.org/10.1016/j. chemosphere.2014.06.068. Adekola, F.A., Dosumu, O.O., 2001. Heavy metal determination in household dust from Ilorin City, Nigeria. Niseb J 1, 217–221. https://doi.org/10.12691/jap-4-1-4. Ademuyiwa, O., Agarwal, R., Chandra, R., Behari, J.R., 2009. Lead-induced phospholipidosis and cholesterogenesis in rat tissues. Chem. Biol. Interact. 179, 314–320. https://doi.org/10.1016/j.cbi.2008.10.057. Afolabi, O.K., Wusu, A.D., Ogunrinola, O.O., Abam, E.O., Babayemi, D.O., Dosumu, O.A., Onunkwor, O.B., Balogun, E.A., Odukoya, O.O., Ademuyiwa, O., 2015. Arsenic-induced dyslipidemia in male albino rats: comparison between trivalent and pentavalent inorganic arsenic in drinking water. BMC Pharmacol. Toxicol. 16, 15. https:// doi.org/10.1186/s40360-015-0015-z. Aiman, U., Mahmood, A., Waheed, S., Malik, R.N., 2016. Enrichment, geo-accumulation and risk surveillance of toxic metals for different environmental compartments from Mehmood Booti dumping site, Lahore city, Pakistan. Chemosphere 144, 2229–2237. https://doi.org/10.1016/j.chemosphere.2015.10.077. Akinwunmi, F., Akinhanmi, T.F., Atobatele, Z.A., Adewole, O., Odekunle, K., Arogundade, L.A., Odukoya, O.O., Olayiwola, O.M., Ademuyiwa, O., 2017. Heavy metal burdens of public primary school children related to playground soils and classroom dusts in Ibadan North-West local government area, Nigeria. Environ. Toxicol. Pharmacol. 49, 21–26. https://doi.org/10.1016/j.etap.2016.11.006. Alam, N., Ahmad, S.R., Qadir, A., Ashraf, M.I., Lakhan, C., Lakhan, V.C., 2015. Use of statistical and GIS techniques to assess and predict concentrations of heavy metals in soils of Lahore City, Pakistan. Environ. Monit. Assess. 187, 636. https://doi.org/10. 1007/s10661-015-4855-1.

4. Conclusion Samples of classroom dust were collected from 40 schools of Lahore, 8

Ecotoxicology and Environmental Safety 190 (2020) 110059

A. Rehman, et al. Ali, M.U., Liu, G., Yousaf, B., Abbas, Q., Ullah, H., Munir, M.A.M., Fu, B., 2017. Pollution characteristics and human health risks of potentially (eco)toxic elements (PTEs) in road dust from metropolitan area of Hefei, China. Chemosphere 181, 111–121. https://doi.org/10.1016/j.chemosphere.2017.04.061. Awashthi, S.K., 1999. Prevention of Food Adulteration Act no 37 of 1954. Cent. State rules as Amend. 3. . Biswas, K.F., Ghauri, B.M., Husain, L., 2008. Gaseous and aerosol pollutants during fog and clear episodes in South Asian urban atmosphere. Atmos. Environ. 42, 7775–7785. https://doi.org/10.1016/j.atmosenv.2008.04.056. Chen, H., Lu, X., Li, L.Y., 2014. Spatial distribution and risk assessment of metals in dust based on samples from nursery and primary schools of Xi’an, China. Atmos. Environ. Times 88, 172–182. https://doi.org/10.1016/j.atmosenv.2014.01.054. Chen, H., Teng, Y., Lu, S., Wang, Y., Wu, J., Wang, J., 2016. Source apportionment and health risk assessment of trace metals in surface soils of Beijing metropolitan, China. Chemosphere 144, 1002–1011. https://doi.org/10.1016/j.chemosphere.2015.09. 081. Cheng, H., Hu, Y., 2010. Lead (Pb) isotopic fingerprinting and its applications in lead pollution studies in China: a review. Environ. Pollut. 158, 1134–1146. https://doi. org/10.1016/j.envpol.2009.12.028. Duggan, M.J., Inskip, M.J., 1985. Childhood exposure to lead in surface dust and soil: a community health problem. Public Health Rev. 13, 1–54. Duzgoren-Aydin, N.S., Wong, Csc, Aydin, A., Song, Z., You, M., Li, X.D., 2006. Heavy metal contamination and distribution in the urban environment of Guangzhou, SE China. Environ. Geochem. Health 28, 375–391. https://doi.org/10.1007/s10653005-9036-7. EPA, U.S., 1989. Risk assessment guidance for superfund. Hum. Heal. Eval. Man. Part A. Eqani, S.A.M.A.S., Kanwal, A., Bhowmik, A.K., Sohail, M., Ullah, R., Ali, S.M., Alamdar, A., Ali, N., Fasola, M., Shen, H., 2016. Spatial distribution of dust–bound trace elements in Pakistan and their implications for human exposure. Environ. Pollut. 213, 213–222. https://doi.org/10.1016/j.envpol.2016.02.017. Faiz, Y., Tufail, M., Javed, M.T., Chaudhry, M.M., Naila-Siddique, 2009. Road dust pollution of Cd, Cu, Ni, Pb and Zn along Islamabad expressway, Pakistan. Microchem. J. 92, 186–192. https://doi.org/10.1016/j.microc.2009.03.009. Fosmire, G.J., 1990. Zinc toxicity. Am. J. Clin. Nutr. 51, 225–227. https://doi.org/10. 1093/ajcn/51.2.225. Ghauri, B., Lodhi, A., Mansha, M., 2007. Development of baseline (air quality) data in Pakistan. Environ. Monit. Assess. 127, 237–252. https://doi.org/10.1007/s10661006-9276-8. Gope, M., Masto, R.E., George, J., Hoque, R.R., Balachandran, S., 2017. Bioavailability and health risk of some potentially toxic elements (Cd, Cu, Pb and Zn) in street dust of Asansol, India. Ecotoxicol. Environ. Saf. 138, 231–241. https://doi.org/10.1016/j. ecoenv.2017.01.008. Habil, M., Taneja, A., 2011. Children's exposure to indoor particulate matter in naturally ventilated schools in India. Indoor Built Environ. 20, 430–448. https://doi.org/10. 1177/1420326X11409455. Habil, M., Massey, D.D., Taneja, A., 2013. Exposure of children studying in schools of India to PM levels and metal contamination: sources and their identification. Air Qual. Atmos. Heal. 6, 575–587. https://doi.org/10.1007/s11869-013-0201-3. He, K., Wang, S., Zhang, J., 2009. Blood lead levels of children and its trend in China. Sci. Total Environ. 407, 3986–3993. https://doi.org/10.1016/j.scitotenv.2009.03.018. Hou, S., Zheng, N., Tang, L., Ji, X., Li, Y., Hua, X., 2019. Pollution characteristics, sources, and health risk assessment of human exposure to Cu, Zn, Cd and Pb pollution in urban street dust across China between 2009 and 2018. Environ. Int. 128, 430–437. https://doi.org/10.1016/j.envint.2019.04.046. Irshad, S., Liu, G., Yousaf, B., Ullah, H., Ali, M.U., Rinklebe, J., 2019. Estimating the pollution characteristics and health risks of potentially toxic metal(loid)s in urbanindustrial soils in the Indus basin, Pakistan. Environ. Monit. Assess. 191, 748. https:// doi.org/10.1007/s10661-019-7909-y. Jahan, S., Strezov, V., 2018. Comparison of pollution indices for the assessment of heavy metals in the sediments of seaports of NSW, Australia. Mar. Pollut. Bull. 128, 295–306. https://doi.org/10.1016/j.marpolbul.2018.01.036. Janotková, I., Prokeš, L., Vaculovič, T., Holá, M., Pinkas, J., Steffan, I., Kubáň, V., Kanický, V., 2013. Comparison of inductively coupled plasma optical emission spectrometry, energy dispersive X-ray fluorescence spectrometry and laser ablation inductively coupled plasma mass spectrometry in the elemental analysis of agricultural soils. J. Anal. At. Spectrom. 28, 1940–1948. https://doi.org/10.1039/ C3JA50169H. Jin, Y., O'Connor, D., Ok, Y.S., Tsang, D.C.W., Liu, A., Hou, D., 2019. Assessment of sources of heavy metals in soil and dust at children's playgrounds in Beijing using GIS and multivariate statistical analysis. Environ. Int. 124, 320–328. https://doi.org/10. 1016/j.envint.2019.01.024. Johnson, C.C., Demetriades, A., Locutura, J., Ottesen, R.T., 2011. Mapping the Chemical Environment of Urban Areas. John Wiley & Sonshttps://doi.org/10.1002/ 9780470670071. Kamunda, C., Mathuthu, M., Madhuku, M., 2016. Health risk assessment of heavy metals in soils from witwatersrand gold mining basin, South Africa. Int. J. Environ. Res. Public Health 13. https://doi.org/10.3390/ijerph13070663. Kaufmann, R.B., Staes, C.J., Matte, T.D., 2003. Deaths related to lead poisoning in the United States, 1979–1998. Environ. Res. 91, 78–84. https://doi.org/10.1016/S00139351(02)00017-8. Khan, Z.I., Ugulu, I., Umar, S., Ahmad, K., Mehmood, N., Ashfaq, A., Bashir, H., Sohail, M., 2018. Potential toxic metal accumulation in soil, forage and blood plasma of buffaloes sampled from Jhang, Pakistan. Bull. Environ. Contam. Toxicol. 101, 235–242. https://doi.org/10.1007/s00128-018-2353-1. Kosolapov, D.B., Kuschk, P., Vainshtein, M.B., Vatsourina, A.V., Wiessner, A., Kästner, M., Müller, R.A., 2004. Microbial processes of heavy metal removal from

carbon‐deficient effluents in constructed wetlands. Eng. Life Sci. 4, 403–411. https:// doi.org/10.1002/elsc.200420048. Langård, S., Andersen, A. a, Gylseth, B., 1980. Incidence of cancer among ferrochromium and ferrosilicon workers. Br. J. Ind. Med. 37, 114–120. https://doi.org/10.1136/ oem.37.2.114. Latif, M.T., Yong, S.M., Saad, A., Mohamad, N., Baharudin, N.H., Mokhtar, M. Bin, Tahir, N.M., 2014. Composition of heavy metals in indoor dust and their possible exposure: a case study of preschool children in Malaysia. Air Qual. Atmos. Heal. 7, 181–193. https://doi.org/10.1007/s11869-013-0224-9. Li, H., Qian, X., Hu, W., Wang, Y., Gao, H., 2013. Chemical speciation and human health risk of trace metals in urban street dusts from a metropolitan city, Nanjing, SE China. Sci. Total Environ. 456, 212–221. https://doi.org/10.1016/j.scitotenv.2013.03.094. Li, Z., Ma, Z., van der Kuijp, T.J., Yuan, Z., Huang, L., 2014. A review of soil heavy metal pollution from mines in China: pollution and health risk assessment. Sci. Total Environ. 468–469, 843–853. https://doi.org/10.1016/j.scitotenv.2013.08.090. Li, H.H., Chen, L.J., Yu, L., Guo, Z.B., Shan, C.Q., Lin, J.Q., Gu, Y.G., Yang, Z.B., Yang, Y.X., Shao, J.R., Zhu, X.M., Cheng, Z., 2017. Pollution characteristics and risk assessment of human exposure to oral bioaccessibility of heavy metals via urban street dusts from different functional areas in Chengdu, China. Sci. Total Environ. 586, 1076–1084. https://doi.org/10.1016/j.scitotenv.2017.02.092. Luo, X.-S., Ding, J., Xu, B., Wang, Y.J., Li, H.B., Yu, S., 2012. Incorporating bioaccessibility into human health risk assessments of heavy metals in urban park soils. Sci. Total Environ. 424, 88–96. https://doi.org/10.1016/j.scitotenv.2012.02.053. Maghakyan, N., Sahakyan, L., et al., Belyaeva, O., Kafyan, M., Tepanosyan, G., 2017. Assesment of heavy metal pollution level and children's health risk in a kindergarten area. Natl. Acad. Sci. RA Electron. J. Nat. Sci. 1, 10–15. https://doi.org/10.1016/j. ecoenv.2017.04.013. Martínez, L.L.G., Poleto, C., 2014. Assessment of diffuse pollution associated with metals in urban sediments using the geoaccumulation index (I geo). J. Soils Sediments 14, 1251–1257. https://doi.org/10.1007/s11368-014-0871-y. Meza-Figueroa, D., De la O-Villanueva, M., De la Parra, M.L., 2007. Heavy metal distribution in dust from elementary schools in Hermosillo, Sonora, México. Atmos. Environ. Times 41, 276–288. https://doi.org/10.1016/j.atmosenv.2006.08.034. Mohmand, J., Eqani, S.A.M.A.S., Fasola, M., Alamdar, A., Mustafa, I., Ali, N., Liu, L., Peng, S., Shen, H., 2015. Human exposure to toxic metals via contaminated dust: bio-accumulation trends and their potential risk estimation. Chemosphere 132, 142–151. https://doi.org/10.1016/j.chemosphere.2015.03.004. Muller, G., 1969. Index of geoaccumulation in sediments of the rhine river. GeoJournal 2, 108–118. Olama, V., Ronaghi, A., Karimian, N., Yasrebi, J., Hamidi, R., Tavajjoh, M., Kazemi, M.R., 2014. Seed quality and micronutrient contents and translocations in rapeseed (Brassica napus L.) as affected by nitrogen and zinc fertilizers. Arch. Agron Soil Sci. 60, 423–435. https://doi.org/10.1080/03650340.2013.796588. Olowoyo, J.O., Mugivhisa, L.L., Magoloi, Z.G., 2016. Composition of trace metals in dust samples collected from selected high schools in Pretoria, South Africa. Appl. Environ. Soil Sci. 2016, 1–9. https://doi.org/10.1155/2016/5829657. Olujimi, O., Steiner, O., Goessler, W., 2015. Pollution indexing and health risk assessments of trace elements in indoor dusts from classrooms, living rooms and offices in Ogun State, Nigeria. J. Afr. Earth Sci. 101, 396–404. https://doi.org/10.1016/j. jafrearsci.2014.10.007. Omar, N.A., Ismail, Z.S., Nasir, R.A., Sumari, S.M., Darus, F.M., 2012. Heavy metals composition of indoor dust in nursery schools building. Procedia - Soc. Behav. Sci. 38, 169–175. https://doi.org/10.1016/j.sbspro.2012.03.337. Othman, M., Latif, M.T., Matsumi, Y., 2019. The exposure of children to PM2.5 and dust in indoor and outdoor school classrooms in Kuala Lumpur City Centre. Ecotoxicol. Environ. Saf. 170, 739–749. https://doi.org/10.1016/j.ecoenv.2018.12.042. Piadé, J.-J., Jaccard, G., Dolka, C., Belushkin, M., Wajrock, S., 2015. Differences in cadmium transfer from tobacco to cigarette smoke, compared to arsenic or lead. Toxicol. Rep. 2, 12–26. https://doi.org/10.1016/j.toxrep.2014.11.005. Plum, L.M., Rink, L., Hajo, H., 2010. The essential toxin: impact of zinc on human health. Int. J. Environ. Res. Public Health 7, 1342–1365. https://doi.org/10.3390/ ijerph7041342. Qadir, A., Malik, R.N., Husain, S.Z., 2008. Spatio-temporal variations in water quality of Nullah Aik-tributary of the river Chenab, Pakistan. Environ. Monit. Assess. 140, 43–59. https://doi.org/10.1007/s10661-007-9846-4. Rasmussen, K., 2004. Places for children – children's Places. Childhood 11, 155–173. https://doi.org/10.1177/0907568204043053. Rehman, I. ur, Ishaq, M., Ali, L., Khan, S., Ahmad, I., Din, I.U., Ullah, H., 2018. Enrichment, spatial distribution of potential ecological and human health risk assessment via toxic metals in soil and surface water ingestion in the vicinity of Sewakht mines, district Chitral , Northern Pakistan. Ecotoxicol. Environ. Saf. 154, 127–136. https://doi.org/10.1016/j.ecoenv.2018.02.033. Saeedi, M., Li, L.Y., Salmanzadeh, M., 2012. Heavy metals and polycyclic aromatic hydrocarbons: pollution and ecological risk assessment in street dust of Tehran. J. Hazard Mater. 227–228, 9–17. https://doi.org/10.1016/j.jhazmat.2012.04.047. SEPAC, 1995. Environmental Quality Standards for Soils. State Environmental Protection Administration, China, GB 15618-1995. SEPAC, 2005. The Limits of Pollutants in Food. State Environmental Protection Administration, China GB 2762–2005. Shabbaj, I.I., Alghamdi, M.A., Shamy, M., Hassan, S.K., Alsharif, M.M., Khoder, M.I., 2018. Risk assessment and implication of human exposure to road dust heavy metals in Jeddah, Saudi Arabia. Int. J. Environ. Res. Public Health 15. https://doi.org/10. 3390/ijerph15010036. Shah, M.H., Shaheen, N., 2007. Statistical analysis of atmospheric trace metals and particulate fractions in Islamabad, Pakistan. J. Hazard Mater. 147, 759–767. https://doi. org/10.1016/j.jhazmat.2007.01.075.

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Ecotoxicology and Environmental Safety 190 (2020) 110059

A. Rehman, et al. Tahir, N.M., Chee, P.S., Jaafar, M., 2007. Determination of heavy metals content in soils and indoor dusts from nurseries in Dungun. Terengganu. Malays J Anal Sci 11, 280–286. Tan, S.Y., Praveena, S.M., Abidin, E.Z., Cheema, M.S., 2016. A review of heavy metals in indoor dust and its human health-risk implications. Rev. Environ. Health 31, 447–456. https://doi.org/10.1515/reveh-2016-0026. Tan, S.Y., Praveena, S.M., Abidin, E.Z., Cheema, M.S., 2018. Heavy metal quantification of classroom dust in school environment and its impacts on children health from Rawang (Malaysia). Environ. Sci. Pollut. Res. 25, 34623–34635. https://doi.org/10. 1007/s11356-018-3396-x. Tomlinson, D.L., Wilson, J.G., Harris, C.R., Jeffrey, D.W., 1980. Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution index. Helgol. Meeresunters. 33, 566–575. https://doi.org/10.1007/BF02414780. Tong, S.T.Y., Lam, K.C., 1998. Are nursery schools and kindergartens safe for our kids? The Hong Kong study. Sci. Total Environ. 216, 217–225. https://doi.org/10.1016/ S0048-9697(98)00161-2. Trujillo-González, J.M., Torres-Mora, M.A., Keesstra, S., Brevik, E.C., Jiménez-Ballesta, R., 2016. Heavy metal accumulation related to population density in road dust samples taken from urban sites under different land uses. Sci. Total Environ. 553, 636–642. https://doi.org/10.1016/j.scitotenv.2016.02.101. Turekian, K.K., Haven, N., Hans, K., Universitat, W.M. Der, 1961. Distribution of the Elements in Some Major Units of the Earth's Crust. America (NY). KARL K. TUREKIAN Dept. Geology, Yale University, New Haven, Conn. KARL HANS WEDEPOHL Mineralogische-Institut der Universitat, Gottingen, Germany. pp. 175–192. https://doi.org/10.1130/0016-7606(1961)72[175:DOTEIS]2.0.CO;2. Ubaid Ali, M., Liu, G., Yousaf, B., Ullah, H., Irshad, S., Ahmed, R., Hussain, M., Rashid, A., 2019. Evaluation of floor-wise pollution status and deposition behavior of potentially toxic elements and nanoparticles in air conditioner dust during urbanistic development. J. Hazard Mater. 365, 186–195. https://doi.org/10.1016/j.jhazmat.2018.11. 005. U.S. Environmental Protection Agency (U.S. EPA), 2011. Exposure Factors Handbook: 2011 Edition. EPA/600/R-090/052F. Natl. Cent. Environ. Assess. 1–1466. EPA/600/ R-090/052F. (USEPA), U.S.E.P.A., 2002. Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites, Appendix A—Generic SSLs for the Residential and Commercial/ industrial Scenarios.

von Schneidemesser, E., Stone, E.A., Quraishi, T.A., Shafer, M.M., Schauer, J.J., 2010. Toxic metals in the atmosphere in Lahore, Pakistan. Sci. Total Environ. 408, 1640–1648. https://doi.org/10.1016/j.scitotenv.2009.12.022. Wei, X., Gao, B., Wang, P., Zhou, H., Lu, J., 2015. Pollution characteristics and health risk assessment of heavy metals in street dusts from different functional areas in Beijing, China. Ecotoxicol. Environ. Saf. 112, 186–192. https://doi.org/10.1016/j.ecoenv. 2014.11.005. Wong, C.S.C., Li, X., Thornton, I., 2006. Urban environmental geochemistry of trace metals. Environ. Pollut. 142, 1–16. https://doi.org/10.1016/j.envpol.2005.09.004. Wu, G., Kang, H., Zhang, X., Shao, H., Chu, L., Ruan, C., 2010. A critical review on the bio-removal of hazardous heavy metals from contaminated soils: issues, progress, eco-environmental concerns and opportunities. J. Hazard Mater. 174, 1–8. https:// doi.org/10.1016/j.jhazmat.2009.09.113. Wuana, R.A., Okieimen, F.E., 2011. Heavy Metals in Contaminated Soils: A Review of Sources, Chemistry, Risks and Best Available Strategies for Remediation. https://doi. org/10.5402/2011/402647. ISRN Ecol [Internet]. 2011;2011:1–20. Available from: http://www.hindawi.co.ISRNEcol.2011,1_20. Yap, C.K., Krishnan, T., Chew, W., 2011. Heavy metal concentrations in ceiling fan dusts sampled at schools around Serdang area, Selangor. Sains Malays. 40, 569–575. Yousaf, B., Amina Liu, G., Wang, R., Imtiaz, M., Rizwan, M.S., Zia-ur-Rehman, M., Qadir, A., Si, Y., 2016. The importance of evaluating metal exposure and predicting human health risks in urban-periurban environments influenced by emerging industry. Chemosphere 150, 79–89. https://doi.org/10.1016/j.chemosphere.2016.02.007. Zafar, A., Eqani, S.A.M.A.S., Bostan, N., Cincinelli, A., Tahir, F., Shah, S.T.A., Hussain, A., Alamdar, A., Huang, Q., Peng, S., 2015. Toxic metals signature in the human seminal plasma of Pakistani population and their potential role in male infertility. Environ. Geochem. Health 37, 515–527. https://doi.org/10.1007/s10653-014-9666-8. Zheng, M.K., Xie, J., Wang, Y.L., Wu, J.S., Li, J.J., Peng, J., 2009. Heavy metal accumulation characters and risk assessment in the soil of agriculture and forest of shenzhen area. Asian J. Ecotoxicol. 4, 726–733. Zheng, N., Liu, J., Wang, Q., Liang, Z., 2010. Health risk assessment of heavy metal exposure to street dust in the zinc smelting district, Northeast of China. Sci. Total Environ. 408, 726–733. https://doi.org/10.1016/j.scitotenv.2009.10.075. Zukowska, J., Biziuk, M., 2008. Methodological evaluation of method for dietary heavy metal intake. J. Food Sci. 73. https://doi.org/10.1111/j.1750-3841.2007.00648.x.

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