Heavy metals contamination and human health risk assessment in soils of an industrial area, Bandar Abbas – South Central Iran

Abstract

The purpose of this study was to determine the contamination level, distribution, health risk and potential sources of Cr, Cd, Pb, Zn, Cu, Ni and As in 66 topsoil samples from industrial areas in Bandar Abbas County. The geoaccumulation index, pollution index and pollution load index were calculated to assess the pollution level in the industrial soils. The hazard index and carcinogenic risk were used to assess human health risk of heavy metals. Results showed that the contamination levels of heavy metals were in the descending order of Cu> Cd> Pb> Zn> As> Ni> Cr. Moreover, based on principal component analysis, Cd, Zn, Cu, and Pb originated mainly from anthropogenic sources, including power plants, oil and gas refinery, steel and zinc production factories and municipal waste landfills. For non-carcinogenic effects, hazard index of studied metals decreased in the order of Cr> As> Cd> Pb> Ni > Cu> Zn. Arsenic, chromium and cadmium were regarded as the priority pollutants. Carcinogenic risks due to Cd and As in suburban soils were within tolerable risk to human health; however, children faced more health risk in their daily life than adults via their unconscious ingestion and dermal contact pathway.

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Heavy metals contamination and human health
risk assessment in soils of an industrial area,
Bandar Abbas – South Central Iran
Tahereh Moghtaderi, Shahla Mahmoudi, Ata Shakeri & Mohammad Hassan
Masihabadi
To cite this article: Tahereh Moghtaderi, Shahla Mahmoudi, Ata Shakeri & Mohammad Hassan
Masihabadi (2018): Heavy metals contamination and human health risk assessment in soils of an
industrial area, Bandar Abbas – South Central Iran, Human and Ecological Risk Assessment: An
International Journal, DOI: 10.1080/10807039.2017.1405723
To link to this article: https://doi.org/10.1080/10807039.2017.1405723
Published online: 18 Jan 2018.
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Heavy metals contamination and human health risk assessment
in soils of an industrial area, Bandar Abbas –South Central Iran
Tahereh Moghtaderi
a
, Shahla Mahmoudi
b
, Ata Shakeri
c
,
and Mohammad Hassan Masihabadi
d
a
Department of Soil Science, Science and Research Branch, Islamic Azad University, Tehran, Iran;
b
Department of
Soil Science, Faculty of Soil and Water Engineering, University of Tehran, Tehran, Iran;
c
Department of Applied
Geology, Faculty of Earth Science, Kharazmi University, Tehran, Iran;
d
Department of Soil Science, Science and
Research Branch, Islamic Azad University, Tehran, Iran
ARTICLE HISTORY
Received 20 October 2017
Revised manuscript
accepted 13 November 2017
ABSTRACT
The purpose of this study was to determine the contamination level,
distribution, health risk and potential sources of Cr, Cd, Pb, Zn, Cu, Ni
and As in 66 topsoil samples from industrial areas in Bandar Abbas
County. The geoaccumulation index, pollution index and pollution
load index were calculated to assess the pollution level in the
industrial soils. The hazard index and carcinogenic risk were used to
assess human health risk of heavy metals. Results showed that the
contamination levels of heavy metals were in the descending order of
Cu>Cd>Pb>Zn>As>Ni>Cr. Moreover, based on principal
component analysis, Cd, Zn, Cu, and Pb originated mainly from
anthropogenic sources, including power plants, oil and gas refinery,
steel and zinc production factories and municipal waste landfills. For
non-carcinogenic effects, hazard index of studied metals decreased in
the order of Cr>As>Cd>Pb>Ni >Cu>Zn. Arsenic, chromium and
cadmium were regarded as the priority pollutants. Carcinogenic risks
due to Cd and As in suburban soils were within tolerable risk to human
health; however, children faced more health risk in their daily life than
adults via their unconscious ingestion and dermal contact pathway.
KEYWORDS
heavy metals; human health;
industrial area; environment
management; suburban soils
1. Introduction
Soil, as a dynamic natural resource for the survival of human life, is the prime receiver of the
relentless pollutants (Goulding and Blake 1998; Luo et al. 2007). Nowadays, soil is one of the
most important, and also endangered parts of the environment, because many pollutants
can accumulate in topsoil from the atmosphere, impaction and interception, and pose a
potential threat to human health (Sezgin et al. 2004; Chen et al. 2013). The soil could be con-
sidered as both geochemical reservoir for the contaminants and a natural buffer for trans-
portation of chemical materials in the atmosphere, hydrosphere, and biomass (Benhaddya
and Hadjel 2014). Soils may severely be disturbed by human activities, including industrial
CONTACT Ata Shakeri atashakeri@khu.ac.ir; shakeri1353@gmail.com Department of Geochemistry, Faculty of Earth
Science, Kharazmi University, No. 43, Shahid Mofatteh Ave., Tehran 1571914911, Iran.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/bher.
© 2018 Taylor & Francis Group, LLC
HUMAN AND ECOLOGICAL RISK ASSESSMENT
https://doi.org/10.1080/10807039.2017.1405723

and energy production, vehicular emission, municipal waste disposal, and coal and fuel com-
bustion, giving rise to increasingly serious land contamination and consequently threatening
human health (Ljung et al. 2006; Zhang et al. 2015). Heavy metals (HMs) such as Cr, Ni, Pb,
and Cd are particularly hazardous among various types of environmental pollutants (Luo
et al. 2015). Metalloids such as arsenic (As) often fall into the heavy metal category due to
similarities in chemical properties and environmental behavior (Chen et al. 1999). Heavy
metals are natural components of the Earth’s crust, and their natural concentrations in soils
tend to remain low. Soil heavy metal pollution has become a severe problem in many parts
of the world (Pan et al. 2016). Metal contamination of the environment raises concern for
the possible impact on human health, is well-recognized as a potentially important source of
human exposure (Vicente et al. 2014; Chen et al. 2005; Davis et al. 2009; Muller and Anke
1994).
Heavy metal pollution is covert, persistent, and irreversible (Wang et al. 2001). This kind
of pollution not only degrades the quality of the soil, atmosphere, water bodies, and food
crops, but also threatens the health and well-being of animals and human beings by way of
the food chain (Dong et al. 2011; Nabulo et al. 2010; Wang et al. 2001). In the inhabited and
industrial areas, excess accumulation of heavy metals in surface soils can directly threaten
the well-being of exposed inhabitants via ingestion, inhalation, and dermal contact routes
(Granero and Domingo 2002; Shi et al. 2011; Liu et al. 2015). A few studies were conducted
on risk assessment of heavy metals in soils of South Central Iran. Bandar Abbas County is
located in the south of Iran and is one of the major industrial complex zones, refinery, ship-
building company, Zinc plant and petrochemical factory with extensive oil fields. Soil in the
study area is susceptible to contamination by anthropogenic activities in the form of indus-
trial wastewater, solid waste, runoff, agricultural activities, and atmospheric deposition. The
presence of heavy metals in soil without proper consideration to the environmental protec-
tion measures, will certainly lead to a significant environmental hazard in Bandar Abbas
County. Therefore, the main purposes of this study are to evaluate the contamination levels
and distribution, health risk assessment, and source identification of some heavy metals (As,
Cd, Cr, Cu, Ni, Pb, and Zn) in the industrial soils of Bandar Abbas County.
2. Methods and materials
2.1. Study area
Bandar Abbas county southern district (BCSD) with a total population of more than 680,000
in 2016 is located in Hormozgan province, covering approximately 4063 km
2
and lies
between 27000–27300N and 55540–56290E(Figure 1). The study area, as a commer-
cial port city along Iran’s southern coastline facing the Persian Gulf, has semiarid and arid
climate with an average annual temperature and rainfall of 27.2C and less than 250 mm,
respectively (Bakhtiari et al. 2013). Bandar Abbas is known as one of the industrial hubs in
Iran, and it’s important economic activities include heavy industries such as commercial
port (27060N and 56030E), fishing port (27080N and 56120E), petrochemical complex
(27100N and 56040E), Zinc production company (27040N and 55590E), oil and gas
refinery (27200N and 56250E), steel and aluminum complexes (27080N and 56120E)
and other industries, which employ about 74% of the active population (Dadras et al. 2015).
Based on the geological maps (Iran Geological survey 2012), the study area comprises mostly
2T. MOGHTADERI ET AL.

limestone, marl, sandstone, conglomerate and evaporate deposits. Also, pedological data
shows that the soils in the study area are mostly composed of Entisols/Aridisols and bad-
lands (Figure 1).
2.2. Soil sampling and analytical methods
A total of 66 topsoil samples were collected (0–10 cm depth) from the industrial sites (56
samples) and some residential/sub-urban areas (10 samples) of the BCSD (Table 1 and
Figure 1). Industrial soil sampling sites were selected in a way to cover an impacted area
based on known contamination sources, i.e., oil and gas refineries, petrochemical complex,
zinc production company, industrial complex zones, and landfills. In order to achieve a rep-
resentative sample, composite samples were prepared by mixing the four subsamples taken
at each corners of 2 £2m
2
cell (Shakeri et al. 2016) because composite sampling yields
homogenized samples for analyses (Rastegari Mehr et al. 2017). The subsamples were mixed
and a final sample of 1 kg was taken by repeated coning and quartering. To determine back-
ground concentration of heavy metals, soil samples were collected from areas far from
known sources of contamination (30 cm depth).
The collected samples were immediately stored in polyethylene bags and air-dried in the
laboratory at room temperature. Then, gravel and plant root were removed, samples passed
through a 2 mm stainless steel sieve. Grain size plays a significant role in determining ele-
mental concentrations in soils (Szefer et al. 1996). Salomons and Forstner (1984) recom-
mended a particle size fraction of <63 mm for analysis because they thought it was most
nearly equivalent to materials carried in suspension, the most important system for transport
of fine soils, and these finer particles would be re-suspended by wind action (Rastegari Mehr
Figure 1. Study area and location of the sampling stations.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 3

et al. 2016). The <2 mm fraction was ground in an agate mortar and pestle and passed
through a 63 micron sieve. Physicochemical properties of the soil samples were measured
using standard analytical methods. Organic carbon content was determined using Gaudette
et al. (1974) titration method. Soil pH was determined through equilibration with a homoge-
nized suspension of 10 g of sample with 50 mL of distilled water after shaking for 5 min, and
1 h pause using a calibrated ELE pH meter. In order to determine the concentration of As,
Cd, Cr, Cu, Ni, Pb, and Zn, complete dissolution of soil samples (approximately 1 g of each)
was carried out using a mixture of HF, HNO
3
, HClO
4
, and H
2
O
2
in a Teflon beaker on sand
bath at atmospheric pressure. The concentrations of the selected elements were measured by
an accredited commercial laboratory (Zar Azma Laboratory, Iran) using ICP-MS methods
(Agilent, 7700x, USA). Data quality was ensured through the use of internal duplicates,
blanks, and HRM. The precision and accuracy of measurements are 95% and C/¡5%
respectively.
2.3. Evaluation of heavy metals pollution
Geoaccumulation index (I
geo
), pollution index (PI) and pollution load index (PLI) were cal-
culated to quantify pollution level of heavy metals in soil samples (Chen et al. 2015; Islam
Table 1. GIS information of soil sampling stations (Zone 40N).
Sample X Y Sample X Y
IN01 410448 3003737 IN34 414737 3003951
IN02 411290 3003597 IN35 412121 3009438
IN03 410020 3003991 IN36 412430 3007463
IN04 447544 3025835 IN37 413869 3003786
IN05 448941 3029540 IN38 409297 3000261
IN06 441510 3017008 IN39 411960 3003395
IN07 441457 3017739 IN40 411859 3003448
IN08 412739 3008349 IN41 410481 3002960
IN09 409070 3004409 IN42 409718 3002815
IN10 410888 3003580 IN43 410362 3002896
IN11 393193 2991233 IN44 407750 3003976
IN12 408448 3004894 IN45 408903 3002880
IN13 414830 3003677 IN46 408634 3005226
IN14 434322 3016907 IN47 408779 3002372
IN15 435301 3017551 IN48 409250 3002882
IN16 401131 2996622 IN49 408310 3004450
IN17 412983 3006005 IN50 404097 2998628
IN18 409846 3003387 IN51 406597 2999328
IN19 410853 3005066 IN52 396389 2999387
IN20 412129 3008366 IN53 407214 3003979
IN21 395435 2989766 IN54 398835 3007485
IN22 391288 2994360 IN55 398835 3007485
IN23 391819 2994153 IN56 395630 2994908
IN24 391764 2993978 IN57 400000 2996313
IN25 413914 3007029 IN58 395630 2994908
IN26 409348 3003603 IN59 390323 3004828
IN27 441101 3025152 IN60 390324 3004828
IN28 446820 3030018 IN61 390324 3004828
IN29 442032 3028622 IN62 397382 2999923
IN30 443899 3023835 IN63 397685 2999973
IN31 412457 3021924 IN64 396079 2992228
IN32 414883 3003660 IN65 431075 3040981
IN33 414825 3003979 IN66 434661 3035971
4T. MOGHTADERI ET AL.

et al. 2015;Liet al. 2014;Wuet al. 2015). The I
geo
was calculated according to M€
uller (1969),
using the following equation:
Igeo Dlog2Cn61:5Bn
ðÞ (1)
where C
n
represents the measured concentration of the element n and B
n
is the background
content of element n in the soil of BCSD. I
geo
could be classified as follow: <0, practically
unpolluted; 0–1, unpolluted to moderately polluted; 1–2, moderately polluted; 2–3, moder-
ately to strongly polluted; 3–4, strongly polluted; 4–5, strongly to extremely polluted; and
>5, extremely polluted (Chen et al. 2005; Wei et al. 2015; Wei and Yang 2010).
The PI was defined as the ratio of element concentration in the soil sample to the back-
ground concentration of the corresponding element in the soil of BCSD. The PI of each ele-
ment was calculated and classified as either low (PI <1), middle (1 <PI <3) or high (PI
>3) (Chen et al. 2005;Wuet al. 2015). In addition, to give an assessment of the overall pollu-
tion status for a sample, the PLI of heavy metals was calculated using the following equation:
PLI DPI1£PI2£ £PIn
ðÞ
1n
=(2)
Based on the contamination degree, six categories are recognized for PI: unpolluted
(PLI <1), unpolluted to moderately polluted (1 <PLI <2), moderately polluted(2 <PLI <
3), moderately to highly polluted (3 <PLI <4), highly polluted(4 <PLI <5), or very highly
polluted (PLI >5) (Chen et al. 2015; Islam et al. 2015).
2.4. Health risk assessment
The methodology used for the health risk assessment was based on the guidelines and Expo-
sure Factors Handbook of US Environmental Protection Agency (USEPA 1986,1989,1997,
2001). The average daily doses (ADDs) of heavy metals received through ingestion, inhalation,
and dermal contact for both adults and children were calculated as follows (Xu et al. 2013):
ADDing DC£IR £EF £ED
BW £AT £10¡6(3)
ADDdermal DC£SA £AF £ABS £EF £ED
BW £AT £10 ¡6(4)
ADDinh DC£IR £EF £ED
BW £AT £PEF (5)
where ADD
ing
,ADD
inh
,andADD
derm
are the daily amount of exposure to metals (mg
kg
¡1
d) via ingestion, inhalation, and dermal contact, respectively. Other exposure fac-
tors and values used to evaluate the intake value and risk are presented in Table 2.In
this study, hazard quotient (HQ), hazard index (HI), and carcinogenic risk (RI) meth-
ods were used to estimate non-carcinogenic and carcinogenic effects of heavy metals
(Wei et al. 2015; Chabukdhara and Nema 2013). The HQ was calculated by subdividing
ADD of a heavy metal to its reference dose (RfD) for the same exposure pathway(s)
(USEPA 1989). If the ADD exceeds the RfD, HQ >1, it is likely that there will be
HUMAN AND ECOLOGICAL RISK ASSESSMENT 5

adverse health effects, whereas if the ADD is less than the RfD, HQ <1, it is considered
that there will be no adverse health effects (USEPA 1989,2001). A hazard index (HI),
the sum of HQs, which means the total risk of non-carcinogenic element via three
exposure pathways for single element of <1 indicates no adverse health effects, while
HI values >1 show possible adverse health effects. Carcinogenic risk is regarded as the
probability of an individual developing any type of cancer in the whole life time due to
exposure to carcinogenic hazards and was calculated for As and Cd as follows (Li et al.
2014):
The carcinogenic risk is calculated by using Eq. (6)
Risk RIðÞDX
n
iD1
ADD £SF (6)
The value of SF represents the probability of developing cancer per unit exposure
level of mg kg
¡1
d. The values for RfD and SF are given in Tables 4 and 5, respectively.
The acceptable risk range for carcinogens is set to 10
¡6
to by the USEPA, so that RI
values below 10
¡6
do not require further action, while risks greater than 10
¡4
are con-
sidered to be of concern and require additional action to reduce the exposure and
resulting risk (Wu et al. 2015).
2.5. Geographical information system (GIS) and statistical analysis
Spatial interpolation technique was used to display the spatial distribution of heavy metals
contamination level in BCSD soils. For this purpose, calculated PI and PLI for Cd, Cu, Pb,
and Zn were spatially investigated using inverse distance weighting (IDW), because this
method is the simplest and most practical interpolation method among several techniques
(Keshavarzi et al.2015). Statistical analysis of the data was carried out using SPSS 19.0 for
windows. In this study, in addition to descriptive statistics, principal component analysis
(PCA) was performed for the data set to reveal the relationship between parameters and
source identification.
Table 2. Exposure factors for risk assessment models.
Factor Definition Unit Value (children) Value (adults) Reference
C
soil
Heavy metal concentration in soil mg kg
¡1
——This study
IngR Ingestion rate of soil mg d
¡1
200 100 USEPA (2001)
EF Exposure frequency d year
¡1
350 350 Environmental site assessment
guideline (2009)
ED Exposure duration Years 6 30 USEPA (2001)
BW Body weight of the exposed
individual
kg 15 70 Environmental site assessment
guideline (2009)
AT Average time d 365ED 365ED USEPA (1989)
InhR Inhalation rate of soil m
3
d
¡1
7.63 12.8 Van den Berg (1995)
PEF Particle emission factor m
3
kg
¡1
1.36 £10
9
1.36 £10
9
USEPA (2001)
SA Exposed skin surface area cm
2
2800 5700 Environmental site assessment
guideline (2009)
AF Skin adherence factor mg cm
¡1
d 0.2 0.07 USEPA (1993)
ABF Dermal absorption factor Unitless 0.001 0.001 Chabukdhara and Nema (2013)
6T. MOGHTADERI ET AL.

3. Results and discussion
3.1. Heavy metals concentration in BCSD soils
The summary statistics for studied heavy metals concentration and physicochemical charac-
teristics in soil samples along with local background values and world average in soil are pre-
sented in Table 3. The soil pH ranges from 6.86 to 7.87, with an average value of 7.44
suggesting neutral conditions. Based on Ryan et al. (2007), this is the deal range for most
crops. Organic carbon (OC) contents of soil samples ranged from 0.03% to 2.40% (average
0.38%). The maximum OC value was measured in the samples collected from Bandar Abbas
power plant and eight oil refinery stations, probably due to oil-contaminated soils in these
stations. In this study, based on the USDA textural triangle (Figure 2), BCSD soil texture
could be classified as sandy loam (in most of samples), sandy clayey loam, loam, silty loam,
and clayey loam which shows the dominance of coarse texture in the study area. This coarse
texture caused low CEC values for soils in the study area, so that it ranges from 2.50 to 18.42
meq/100 g with an average of 6.34 meq/100 g.
The BCSD topsoil showed distinct changes in their heavy metals concentrations. The con-
centrations of Cr, Cd, Pb, Zn, Cu, Ni, and As varied between 18 and 155.50, 0.15 and 15.26,
5.30 and 858.20, 22.30 and 2585.8, 10.5 and 3121.8,17 and 248, 3 and 77.40 mg kg
¡1
, with
an average of 63, 1.40, 77.88, 246.86, 205.04, 68.01, and 19.39 mg kg
¡1
, respectively. The
coefficient of variation (CV) indicates the degree of variability within the concentrations of a
metal in soil. If CV <20%, it shows low variability; 21% <CV <50% is regarded as moder-
ate variability; 50% <CV <100% is observed as high variability; while CV above 100% is
considered as exceptionally high variability (Karim Nezhad et al. 2015). The CV of heavy
metals in BCSD soils decreased in the order: Cu (240.15%) >Cd (197.54%) >Zn (186.43%)
>Pb (185.75%) >Ni (53.35%) >Cr (43.26%) >As (84.29%).The large CV for Zn, Cd, Pb,
and Cu indicated that concentration of these heavy metals differed greatly with respect to
different sites. The CV of As and Ni showed as high variability while CV of Cr indicated a
moderate degree of variability reflecting the non-homogeneous distribution of Cr concentra-
tions. Comparison of mean concentration of the heavy metals in industrial soils with the ref-
erence values reveals that all heavy metals have higher contents than the world average in
soil and local background, indicating that study areas are being polluted considerably.
Table 3. Summary statistics of heavy metals concentration (mg kg
¡1
) and physicochemical parameters in
industrial soil samples.
Min Max Mean SD
Coefficient of
variation (CV)
World average
in soil Background
pH 6.86 7.87 7.44 0.22 0.03 ——
CEC (meq/100 g) 2.50 18.42 6.34 3.27 0.52 ——
OM (%) 0.03 2.40 0.38 0.53 1.38 ——
Sand (%) 22.00 82.00 57.75 13.09 0.23 ——
Silt (%) 8.00 60.00 25.14 12.49 0.50 ——
Clay (%) 8.00 30.00 17.11 5.21 0.30 ——
Cd 0.15 15.26 1.4 2.76 197.55 1.1 0.23
Cr 18 154.5 63 27.26 43.26 42 52.3
Cu 10.5 3121.8 205.04 492.4 240.15 14 20.49
Ni 17 248 68.01 36.29 53.36 18 51.28
Zn 22.3 2585.8 246.86 460.22 186.43 62 46.52
As 3 77.4 19.39 16.35 84.29 4.7 7.56
Pb 5.3 858.2 77.88 144.67 185.75 25 13.73
HUMAN AND ECOLOGICAL RISK ASSESSMENT 7

3.2. Assessment of heavy metals contamination
In this study, the I
geo
, PI, and PLI were applied to assess the intensity of heavy metals con-
tamination in BCSD soils. The calculated I
geo
values of heavy metals in industrial soils are
presented in Figure 3. The I
geo
ranged from ¡1.08 to 6.27 for Cu, ¡0.98 to 5.28 for
Cd, ¡0.64 to 5.04 for Zn, ¡1.21 to 5.12 for Pb, ¡1.87 to 1.19 for Cr, ¡1.52 to 1.64 for Ni
and ¡1.07 to 2.7 for As in BCSD soils. The mean values of I
geo
decreased in the order of
Table 4. Human health risk of heavy metals in BCSD soil.
Cd Cr Cu Ni Zn As Pb
Oral RfD 1.00E¡03 3.00E¡03 4.00E¡02 2.00E¡02 3.00E¡01 3.00E¡04 3.50E¡03
Dermal RfD 1.00E¡03 6.00E¡04 1.20E¡02 5.40E¡03 6.00E¡02 1.23E¡04 5.25E¡04
Inhal. RfD 1.00E¡03 1.00E¡04 4.00E¡02 5.00E¡05 3.00E¡01 1.50E¡05 3.50E¡03
Children
HQ
ing
Min 7.2E¡03 4.3E¡01 1.8E¡02 6.2E¡02 5.8E¡03 6.3E¡01 7.7E¡02
Max 3.4E¡01 2.1EC00 1.6EC00 3.5E¡01 1.9E¡01 7.9EC00 6.0EC00
Mean 5.7E¡02 1.0EC00 2.0E¡01 1.6E¡01 3.4E¡02 2.9EC00 9.3E¡01
HQ
inh
Min 2.0E¡07 3.6E¡04 4.9E¡07 7.0E¡04 1.6E¡06 3.5E¡04 2.1E¡06
Max 9.5E¡06 1.7E¡03 4.5E¡05 3.9E¡03 5.4E¡05 4.4E¡03 1.7E¡04
Mean 1.6E¡06 8.6E¡04 5.7E¡06 1.8E¡03 9.6E¡06 1.6E¡03 2.6E¡05
HQ
der
Min 2.8E¡01 2.4EC00 1.6E¡02 2.3E¡01 1.6E¡03 1.3E¡01 8.6E¡03
Max 1.3EC01 1.2EC01 1.5EC00 1.3EC00 5.4E¡02 1.6EC00 6.7E¡01
Mean 2.2EC00 5.7EC00 1.9E¡01 5.9E¡01 9.6E¡03 5.8E¡01 1.0E¡01
HI Min 2.9E¡01 2.8EC00 3.4E¡02 2.9E¡01 7.4E¡03 7.6E¡01 8.5E¡02
Max 1.4EC01 1.4EC01 3.1EC00 1.6EC00 2.5E¡01 9.5EC00 6.7EC00
Mean 2.3EC00 6.8EC00 4.0E¡01 7.6E¡01 4.4E¡02 3.4EC00 1.0EC00
Adults
HQ
ing
Min 7.7E¡04 4.6E¡02 1.9E¡03 6.7E¡03 6.2E¡04 6.8E¡02 8.2E¡03
Max 3.7E¡02 2.2E¡01 1.7E¡01 2.2E¡01 2.1E¡02 8.4E¡01 6.4E¡01
Mean 6.1E¡03 1.1E¡01 2.2E¡02 2.6E¡02 3.7E¡03 3.1E¡01 9.9E¡02
HQ
inh
Min 1.1E¡07 2.0E¡04 2.8E¡07 3.9E¡04 9.1E¡07 2.0E¡04 1.2E¡06
Max 5.4E¡06 9.8E¡04 2.5E¡05 2.2E¡03 3.1E¡05 2.5E¡03 9.4E¡05
Mean 8.9E¡07 4.8E¡04 3.2E¡06 1.0E¡03 5.4E¡06 9.0E¡04 1.4E¡05
HQ
der
Min 4.3E¡02 3.7E¡01 2.5E¡03 3.5E¡02 2.5E¡04 2.0E¡02 1.3E¡03
Max 2.0EC00 1.8EC00 2.3E¡01 1.9E¡01 8.3E¡03 2.5E¡01 1.0E¡01
Mean 3.4E¡01 8.8E¡01 2.9E¡02 9.1E¡02 1.5E¡03 8.9E¡02 1.6E¡02
HI Min 4.4E¡02 4.1E¡01 4.4E¡03 4.2E¡02 8.7E¡04 8.8E¡02 9.5E¡03
Max 2.1EC00 2.0EC00 4.0E¡01 3.4E¡01 2.9E¡02 1.1EC00 7.4E¡01
Mean 3.4E¡01 9.9E¡01 5.1E¡02 1.2E¡01 5.2E¡03 4.0E¡01 1.1E¡01
Table 5. Cancer risk of Cd and As by three exposure routes in BCSD soil.
Adults Children
Cd Ingestion Inhalation Dermal Cancer risk Ingestion Inhalation Dermal Cancer risk
Min 1.27E¡06 1.87E¡10 7.11E¡07 1.98E¡06 1.19E¡05 3.32E¡10 4.66E¡06 1.65E¡05
Max 5.76E¡05 8.47E¡09 3.22E¡05 8.98E¡05 5.37E¡04 1.50E¡08 2.11E¡04 7.48E¡04
Mean 9.38E¡06 1.38E¡09 5.24E¡06 1.46E¡05 8.76E¡05 2.45E¡09 3.43E¡05 1.22E¡04
As Ingestion Inhalation Dermal Cancer risk Ingestion Inhalation Dermal Cancer risk
Min 9.99E¡06 1.47E¡09 2.87E¡06 1.29E¡05 9.32E¡05 2.60E¡09 1.88E¡05 1.12E¡04
Max 9.50E¡05 1.40E¡08 2.73E¡05 1.22E¡04 8.87E¡04 2.48E¡08 1.79E¡04 1.07E¡03
Mean 3.40E¡05 5.00E¡09 9.77E¡06 4.38E¡05 3.17E¡04 8.87E¡09 6.40E¡05 3.81E¡04
8T. MOGHTADERI ET AL.

Cu >Pb >Cd >Zn >As >Ni >Cr. The mean I
geo
of Cu reveals moderately polluted,
while the mean I
geo
obtained for Cd, Zn, As, and Pb show unpolluted to moderate pollution.
The mean I
geo
of Cr and Ni showed that industrial soils were practically unpolluted. The
highest I
geo
values were observed in soil samples collected from power plant, oil and gas
refineries, and steel and zinc production factories.
The PI calculated based on the background concentration of heavy metals in BCSD soils
(Figure 4). Overall, the PI for all metals were in the descending order of Cu >Cd >Pb >
Zn >As >Ni >Cr. the PI values of Cu, Cd, Pb, and Zn ranged from 0.71 to 115.62, 0.73 to
58.08, 0.65 to 52.33, and 0.76 to 49.25, with a mean value of 9.77, 5.75, 5.48, and 5.21, respec-
tively. These data indicated that Cd, Zn, Cu, and Pb in BCSD soils presented high pollution,
such that 36%, 33%, 33%, and 28% of the samples are highly contaminated (PI >3) to Pb,
Cd, Cu, and Zn, respectively. As, Cr, and Ni exhibited lower values, ranging from 0.71 to
Figure 3. Boxplot showing geoaccumulation index of heavy metals in BCSD soils.
Figure 2. Textural triangle of soil samples.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 9

9.74, 0.41 to 3.43 and from 0.52 to 4.68, respectively. The results of mean pollution index for
As, Cr and Ni indicate middle pollution in the industrial soils. The distribution maps of PI
values for enriched heavy metals (Cd, Cu, Pb, and Zn) in the industrial soils are presented in
Figure 5. It is obvious from the maps that the highest Cd, Cu, Pb, and Zn (particularly Cu)
contamination values are located in the southwestern part of the study area, mostly due to
the concentration of important polluting sources such as steel and zinc production factories,
power plant, oil and gas refineries, and Bandar Abbas municipal waste landfill in this area.
However, PI values greater than 3 are also observed in central parts of BCSD.
The PLI values in all BCSD soil samples varied from 0.85 to 12.77 with an average of 2.44,
showing that the industrial and suburban soils are moderately polluted by the heavy metals
investigated. The PLI indicated that 13.63%, 4.54%, and 10.6% of soil samples have moder-
ately to strongly, strongly to extremely, and extremely polluted, respectively. Figure 6 shows
the distribution map of PLI in BCSD.
3.3. Human health risk assessment
Exposure doses of seven heavy metals in BCSD soils for children and adults were calculated
(Table 4). The mean HQ values for children via ingestion for Cd, Cr, Cu, Ni, Zn, As, and Pb
were 5.66E¡02, 1.03EC00, 2.05E¡01, 1.64E¡01, 3.44E¡02, 2.85EC00, 9.25E¡01, while that
via dermal contact were 2.22EC00, 5.74EC00, 1.91E¡01, 5.94E¡01, 9.64E¡03, 5.84E¡01,
and 1.04E¡01, and via inhalation were 1.58E¡06, 5.60E¡04, 5.73E¡06, 1.83E¡03,
9.62E¡06, 1.59E¡03 and 2.59E¡05, respectively. This indicated that the three different expo-
sure pathways for children decreased in the following order: Dermal contact >ingestion >
inhalation. The total exposure HQs from ingestion, dermal contact, and inhalation for all stud-
ied metals in each sample were higher for children than for adults. For most of the heavy met-
als (Cd, Cr, Cu, Pb, As, and Ni), the contribution of HQ
dermal
and HQ
ingestion
to HI (total risk
of non-carcinogenic) were the highest, suggesting that ingestion and dermal contact are the
main exposure pathways to inhabitants while HQs of all studied metals through inhalation
were much lower than those due to other exposure pathways. This result is also in accordance
with other studies (Chabukdhara and Nema 2013;Weiet al. 2015;Xiaoet al. 2015).
Figure 4. Boxplot showing PI values of individual heavy metals in BCSD soils.
10 T. MOGHTADERI ET AL.

The HI values of heavy metals for children and adults decreased in the order of Cr >As
>Cd >Pb >Ni >Cu >Zn (Table 4). For adults, the mean HI values for all the metals
were lower than 1, indicating no non-carcinogenic risk, while for children the mean HI of
Cr, As, Cd, and Ni were higher than 1, indicating that children have much more chances of
non-carcinogenic risk from heavy metals in BCSD soils than adults. The high non-carcino-
genic risk in children is mostly due to their pica behavior and hand or finger sucking (Wei
et al. 2015; Xiao et al. 2015; Zheng et al.2010). Moreover, because in this study only the total
contents of chromium were determined, and the Cr toxicity is dependent on its valence state,
further detailed investigation is required.
In this research the carcinogenic risk for arsenic and cadmium were estimated (Table 5).
For adults, dermal absorption is the primary pathway of exposure, whereas for children,
ingestion and dermal absorption both act as common routes of exposure. The mean RI val-
ues of Cd and As in BCSD soils were 1.22E
¡04
and 3.81E
¡04
for children and1.46E
¡05
and
4.38E
¡05
for adults, respectively. The mean RI values of Cd and As for children and adults
varied from1 £10
¡6
to 1 £10
¡4
indicating tolerable risk to social stability and to human
health. Also, children faced more health risk in their daily life than adults via their uncon-
scious ingestion and dermal contact pathways. Thus, because of the carcinogenic hazards
posed by these elements, more attention should be paid to this health topic.
The model used in this investigation provided a powerful tool for risk assessment in
identifying the relative human health risks of the heavy metals in soil. However, the
Figure 5. Distribution maps of PI values of enriched heavy metals in BCSD soils.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 11

calculated risk of both non-carcinogenic and carcinogenic for metal exposure from soil
was influenced by several uncertainty factors. The exposure factors and parameters for
health risk assessment of heavy metals were derived from the USEPA exposure hand-
book, which may be not suitable for Iranian practical situation. Until the present, there
have been no assessment guidance and exposure factors for a health risk assessment in
Iran. Moreover, total contents of heavy metals were used for health risk assessment in
this study.
3.4. Multivariate statistical analysis
Principle component analysis (PCA) using factor extraction with an eigenvalue >1 after
Varimax rotation was applied to assess elements relationship and identify their sources.
Before analysis, Kolmogrov–Smirnov normality test (p>0.01) was used to investigate the
normality of studied heavy metals. Table 6 shows the component matrix and the component
loadings for each variable. Two principal components explaining more than 89% variance of
the data were extracted. The factor 1 was significantly loaded with five metals (As, Cd, Cu,
Pb, and Zn) explaining 60.11% of the total variance. As confirmed by geochemical coeffi-
cients (I
geo
and PI), the metals of this component have been affected by anthropogenic sour-
ces, mainly power plant, oil and gas refineries, steel factories, zinc production company,
Bandar Abbas municipal waste landfill, etc. The second component explained 28.91% of the
total variance and loadings heavily on Cr and Ni. These metals are believed to be contributed
Figure 6. Distribution map of PLI values in BCSD soils.
12 T. MOGHTADERI ET AL.

by the lithogenic source and poorly affected by anthropogenic sources. Figure 7 shows com-
ponents plot in rotated matrix.
4. Conclusions
The concentration, spatial distribution, pollution level, and potential sources and health risk
of heavy metals in suburban top soil of Bandar Abbas County South District (BCSD) were
investigated in this study. Compared with the background values of elements in BCSD soil,
suburban soils have elevated metal concentrations as a whole. According to high contamina-
tion level and health risk of some studied heavy metals, and also due to the proximity of con-
tamination sources to residential district of the study area, more attention should be paid to
manage and reduce contamination emission. With the limited budget consideration, a hier-
archical risk management policy was suggested and the areas with high or moderate residen-
tial population density in the studied area were suggested to be the first priority areas for
toxic metals where preferentially environmental management and control also cut off the
main receptors exposure pathways, namely ingestion and dermal contact of topsoil pathway
and targeted pollution source control were required.
Acknowledgment
This study is supported by the Environment Protection organization of Iran.
Table 6. Varimax- rotated factor model for heavy metals in sediment samples.
Component
12
Pb 0.979 0.092
Zn 0.976 0.129
Cd 0.934 0.125
Cu 0.883 0.094
As 0.791 ¡0.338
Ni ¡0.018 0.966
Cr 0.136 0.963
Figure 7. PCA loading plot of studied heavy metals in rotated space.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 13

ORCID
Ata Shakeri http://orcid.org/0000-0001-6913-0784
References
Bakhtiari B, Nekooamal Kermanib M, and Bordbar MH. 2013. Rain gauge station network design for
Hormozgan province in Iran. DESERT 18:45–52.
Benhaddya ML and Hadjel M. 2014. Spatial distribution and contamination assessment of heavy metals in
surface soils of Hassi Messaoud, Algeria. Environ Earth Sci 71:1473–86. doi:10.1007/s12665-013-2552-3
Chabukdhara M and Nema A. 2013. Heavy metals assessment in urban soil around industrial clusters
in Ghaziabad, India: Probabilistic health risk approach. Ecotoxicol Environ Saf 87:57–64.
doi:10.1016/j.ecoenv.2012.08.032
Chen HM, Zheng CR, Tu C, and Zhu YG. 1999. Heavy metal pollution in soils in China: Status and
counter measures. Ambio 28:130–4.
Chen HY, Teng YG, Lu SJ, Wang YY, and Wang JS. 2015. Contamination features and health risk of
soil heavy metals in China. Sci Total Environ 512–513:143–53. doi:10.1016/j.scitotenv.2015.01.025
Chen TB, Zheng YM, Lei M, Huang ZC, Wu HT, Chen H, Fan KK, Yu K, Wu X, and Tian QZ. 2005.
Assessment of heavy metal pollution in surface soils of urban parks in Beijing, China. Chemo-
sphere 60:542–51. doi:10.1016/j.chemosphere.2004.12.072
Chen X, Lu X, Li LY, and Yang G. 2013. Spatial distribution and contamination assessment of heavy
metals in urban topsoil from inside the Xi’an second ringroad, NW China. Environ Earth Sci
68:1979–88. doi:10.1007/s12665-012-1885-7
Dadras M, Shafri HZ, Ahmad N, Pradhan B, and Safarpour S. 2015. Spatio-temporal analysis of urban
growth from remote sensing data in Bandar Abbas city, Iran. Egypt J Remote Sensing Space Sci
18:35–52. doi:10.1016/j.ejrs.2015.03.005
Davis HT, Aelion CM, McDermott S, and Lawson AB. 2009. Identifying natural and anthropogenic
sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation.
Environ Pollut 157:2378–85. doi:10.1016/j.envpol.2009.03.021
Dong J, Yang QW, Sun LN, Zeng Q, Liu SJ, Pan J, and Liu XL. 2011. Assessing the concentration and
potential dietary risk of heavy metals in vegetables at a Pb/Zn mine site, China. Environ Earth Sci
64:1317–21. doi:10.1007/s12665-011-0992-1
Environmental site assessment guideline. 2009. DB11/T 656-2009. (In Chinese).
Gaudette HE, Flight WR, Toner L, and Folger DN. 1974. An inexpensive titration method for the
determination of organic carbon in recent sediments. J Sedimentary Petrol 44:249–53.
Geological Survey of Iran. 2012. Geological map of Bandar Abbas. 1: 100000, Tehran, Report H 5.
Goulding KW and Blake L. 1998. Land use, liming and the mobilization of potentially toxic metals.
Agric ecosyst Environ 67:135–44. doi:10.1016/S0167-8809(97)00111-4
Granero S and Domingo JL. 2002. Levels of metals in soils of Alcal
ade Henares, Spain: Human health
risks. Environ Int 28:159–64. doi:10.1016/S0160-4120(02)00024-7
Islam MS, Ahmed MK, Habibullah-Al-Mamun M, Masunaga S. 2015. Potential ecological risk of haz-
ardous elements in different land-use urban soils of Bangladesh. Science of the Total Environment
512–513:94–102. doi:10.1016/j.scitotenv.2014.12.100
Karim Nezhad MT, Tabatabaii SM, and Gholami A. 2015. Geochemical assessment of steel
smelter-impacted urban soils, Ahvaz, Iran. J Geochem Explor 152:91–109. doi:10.1016/j.
gexplo.2015.02.005
KeshavarziB,MooreF,AnsariM,MehrMR,KaabiH,andKermaniM.2015.Macronutrients
and trace metals in soil and food crops of Isfahan Province, Iran. Environ Monit Assess
187:4113. doi:10.1007/s10661-014-4113-y
Li ZY, Ma ZW, van der Kuijp TJ, Yuan ZW, and Huang L. 2014. A review of soil heavy metal pollution
from mines in China: Pollution and health risk assessment. Sci Total Environ 468–469:843–53.
doi:10.1016/j.scitotenv.2013.08.090
14 T. MOGHTADERI ET AL.

Liu L, Zhang X, and Zhong T. 2015. Pollution and health risk assessment of heavy metals in urban soil
in China. Human Ecolog Risk Assess: Int J 22:424–434. doi:10.1080/10807039.2015.1078226.
doi:10.1080/10807039.2014.992854
Ljung K, Otabbong E, and Selinus O. 2006. Natural and anthropogenic metal inputs to soils in urban
Uppsala, Sweden. Environ Geochem Health 28:353–64. doi:10.1007/s10653-005-9031-z
Luo W, Lu Y, Giesy JP, Wang T, Shi Y, Wang G, and Xing Y. 2007. Effects of land use on con-
centrations of metals in surface soils and ecological risk around Guanting Reservoir, China.
Environ Geochem Health 29:459–71. doi:10.1007/s10653-007-9115-z
LuoXS,XueY,WangYL,CangL,XuB,andDingJ.2015.Sourceidentification and apportion-
ment of heavy metals in urban soil profiles. Chemosphere 127:152–7. doi:10.1016/j.
chemosphere.2015.01.048
M€
uller G. 1969. Index of geoaccumulation in sediments of the Rhine River. Geol J 2:108–18.
M€
uller M and Anke M. 1994. Distribution of cadmium in the food chain (soil-plant-human) of a cad-
mium exposed area and the health risks of the general population. Sci Total Environ 156:151–8.
doi:10.1016/0048-9697(94)90352-2
Nabulo G, Young SD, and Black CR. 2010. Assessing risk to human health from tropical leafy vegeta-
bles grown on contaminated urban soils. Sci total Environ 408:5338–51. doi:10.1016/j.
scitotenv.2010.06.034
Pan LB, Ma J, Wang XL, and Hou H. 2016. Heavy metals in soils from a typical county in Shanxi Prov-
ince, China: Levels, sources and spatial distribution. Chemosphere 148:248–54. doi:10.1016/j.
chemosphere.2015.12.049
Rastegari Mehr M, Keshavarzi B, Moore F, Sacchi E, Lahijanzadeh AR, Eydivand S, Jaafarzadeh N,
Naserian S, Setti M, and Rostami S. 2016. Contamination level and human health hazard assess-
ment of heavy metals and polycyclic aromatic hydrocarbons (PAHs) in street dust deposited in
Mahshahr, southwest of Iran. Human Ecol Risk Assess: Int J 22:1726–48. doi:10.1080/
10807039.2016.1219221
Rastegari Mehr M, Keshavarzi B, Moore F, SharifiR, Lahijanzadeh A, and Kermani M. 2017. Distribu-
tion, source identification and health risk assessment of soil heavy metals in urban areas of Isfahan
province, Iran. J Afr Earth Sci 132:16–26. doi:10.1016/j.jafrearsci.2017.04.026
Ryan J, Estefan G, and Rashid A. 2007. Soil and plant analysis laboratory manual. (2nd ed). The Inter-
national Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria and the
National Agricultural Research Center (NARC), pp–172. Vikas Publishing House, Islamabad,
Pakistan.
Salomons W and Forstner U. 1984. Metals in the Hydrocycle. Springer-Verlag, Berlin, Heidelberg.
ISBN: 978-3-642-69325-0
Sezgin N, Ozcan HK, Demir G, Nemlioglu S, and Bayat C. 2004. Determination of heavy metal con-
centrations in street dusts in Istanbul E-5 highway. Environ Int 29:979–85. doi:10.1016/S0160-
4120(03)00075-8
Shakeri A, Madadi M, and Mehrabi B. 2016. Health risk assessment and source apportionment of
PAHs in industrial and bitumen contaminated soils of Kermanshah Province; NW Iran. Toxicol
Environ Health Sci 8:201–12. doi:10.1007/s13530-016-0277-x
Shi G, Chen Z, Bi C, Wang L, Teng J, Li Y, and Xu S. 2011. A comparative study of health risk of
potentially toxic metals in urban and suburban road dust in the most populated city of China.
Atmospheric Environ 45:764–71. doi:10.1016/j.atmosenv.2010.08.039
Szefer P, Szefer K, Glasby GP, Pempkowiak J, and Kaliszan R. 1996. Heavy metal pollution in surficial
sediments from the southern Baltic Sea off Poland. J Environ Sci Health, Part A 31:2723–54.
USEPA. 1986. Superfund Public Health Evaluation Manual. 540, pp. 1–86. Office of Emergency and
Remedial Response, 20460 EPA, Washington, DC.
USEPA. 1989. Risk Assessment Guidance for Superfund. Human Health Evaluation Manual (Part A).
Vol.I; EPA/540/1-89/002. Office of Superfund Remediation and Technology Innovation, U.S. Envi-
ronmental Protection Agency, Washington, DC.
USEPA. 1993. Reference Dose (RfD): Description and Use in Health Risk Assessments. Background
Document 1A. Integrated risk information system (IRIS) Environmental Protection Agency,
Washington, DC. https://www.epa.gov/iris/reference-dose-rfddescription-and-use-heal.
HUMAN AND ECOLOGICAL RISK ASSESSMENT 15

USEPA. 1997. Exposure Factors Handbook EPA/600/P-95/002F, Washington, DC.
USEPA. 2001. Baseline Human Health Risk Assessment. Vasquez Boulevard and I-70 superfund site
Denver, Denver, CO. US Environmental Protection Agency.
Van den Berg R. 1995. Human exposure to soil contamination: a qualitative and quantitative analysis
towards proposals for human toxicological intervention values. RIVM Report no. 725201011.
National Institute of Public Health and Environmental Protection (RIVM), Bilthoven, the
Netherlands.
Vicente AB, Pardo F, Sanfeliu T, Casalta S, and Bech J. 2014. Assessment of PM10 and heavy metal
concentration in a ceramic cluster (NE Spain) and the influence on nearby soils. J Geochem Explor
144:320–7. doi:10.1016/j.gexplo.2013.12.015
Wang QR, Dong Y, Cui Y, and Liu X. 2001. Instances of soil and crop heavy metal contamination in
China. Soil Sediment Contam 10:497–510. doi:10.1080/20015891109392
Wei BG and Yang LS. 2010. A review of heavy metal contaminations in urban soils, urban road dusts
and agricultural soils from China. Microchem J 94:99–107. doi:10.1016/j.microc.2009.09.014
Wei X, Gao B, Wang P, Zhou HD, and 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 J 112:186–92. doi:10.1016/j.ecoenv.2014.11.005
Wu S, Peng S, Zhang X, Wu D, Luo W, Zhang T, Zhou S, Yang G, Wan H, and Wu L. 2015. Levels and
health risk assessments of heavy metals in urban soils in Dongguan, China. J Geochem Explor
148:71–8. doi:10.1016/j.gexplo.2014.08.009
Xiao Q, Zong Y, and Lu S. 2015. Assessment of heavy metal pollution and human health risk in urban
soils of steel industrial city (Anshan), Liaoning, Northeast China. Ecotoxicol Environ Saf 120:377–
85. doi:10.1016/j.ecoenv.2015.06.019
Xu S, Zheng N, Liu J, Wang Y, and Chang S. 2013. Geochemistry and health risk assessment of arsenic
exposure to street dust in the zinc smelting district, Northeast China. Environ Geochem Health
35:89–99. doi:10.1007/s10653-012-9463-1
Zhang C, Yang Y, Li W, Zhang C, Zhang R, Mei Y, Liao X, and Liu Y. 2015. Spatial distribution and
ecological risk assessment of trace metals in urban soils in Wuhan, Central China. Environ Monit
Assess 187:556. doi:10.1007/s10661-015-4762-5
Zheng N, Liu J, Wang Q, and Liang Z. 2010. Health risk assessment of heavy metal exposure to street
dust in the zinc smelting district, Northeast of China. Sci Total Environ 408:726–33. doi:10.1016/j.
scitotenv.2009.10.075
16 T. MOGHTADERI ET AL.