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Assessment of heavy metal pollution in soils and health risk consequences of human exposure within the vicinity of hot mix asphalt plants in Rivers State, Nigeria

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This study evaluated the level of heavy metal pollution in soils within the vicinity of hot mix asphalt (HMA) plants and the health risk consequences of human exposure to the heavy metals. Soil samples collected from two asphalt plants during dry and rainy seasons were analyzed for Cr, Co, Cu, Ni, Mn, Cd, Pb, and Zn with atomic absorption spectrophotometer (AAS). Health risk indices were assessed as chronic daily intake (CDI), hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR) while the degree of pollution was assessed with geo-accumulation index (Igeo) and contamination factor (CF). The pollution assessment revealed that the soil samples were moderately to highly polluted with Cd. In both seasons, Zn and Mn, respectively, had the highest CDI values for ingestion, inhalation, and dermal route for both asphalt plants while Cd has the least CDI values for all the routes in both plants. The HQ and HI values for all the metals were less than 1.00E + 00 indicating no non-carcinogenic risk from exposure to any of the metals. Furthermore, the dermal route was found to be the least likely model for health risks associated with human exposure to soil heavy metals within the vicinity of the plants. The CR values for the metals were also within threshold value indicating non-significant cancer risk from exposure to the metals. Though no significant health risks were observed in the study, clean and efficient production of hot mix asphalt should be encouraged to minimize health risks and environmental pollution during production and usage.
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Environ Monit Assess (2021) 193:461
https://doi.org/10.1007/s10661-021-09208-6
Assessment ofheavy metal pollution insoils andhealth risk
consequences ofhuman exposure withinthevicinity ofhot
mix asphalt plants inRivers State, Nigeria
IfennaIlechukwu· LeoC.Osuji· ChukwunonsoPeterOkoli ·
MarkO.Onyema· GloriaI.Ndukwe
Received: 3 September 2020 / Accepted: 7 June 2021
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021
had the highest CDI values for ingestion, inhalation,
and dermal route for both asphalt plants while Cd has
the least CDI values for all the routes in both plants.
The HQ and HI values for all the metals were less
than 1.00E + 00 indicating no non-carcinogenic risk
from exposure to any of the metals. Furthermore, the
dermal route was found to be the least likely model
for health risks associated with human exposure to
soil heavy metals within the vicinity of the plants.
The CR values for the metals were also within thresh-
old value indicating non-significant cancer risk from
exposure to the metals. Though no significant health
risks were observed in the study, clean and efficient
production of hot mix asphalt should be encouraged
to minimize health risks and environmental pollution
during production and usage.
Keywords Heavy metal· Health risk assessment·
Asphalt plant· Soil pollution· Geo-accumulation
index· Human exposure
Introduction
Heavy metal pollution is a problem associated with
areas of intensive industrial activities. Globally, it
has become a serious threat to human health and
ecosystem integrity (Bai et al., 2016; NNP, 2011;
Wang et al., 2017). Soils may become contami-
nated by heavy metals through emissions and wastes
from industrial activities, fertilizer applications,
Abstract This study evaluated the level of heavy
metal pollution in soils within the vicinity of hot
mix asphalt (HMA) plants and the health risk con-
sequences of human exposure to the heavy metals.
Soil samples collected from two asphalt plants dur-
ing dry and rainy seasons were analyzed for Cr, Co,
Cu, Ni, Mn, Cd, Pb, and Zn with atomic absorption
spectrophotometer (AAS). Health risk indices were
assessed as chronic daily intake (CDI), hazard quo-
tient (HQ), hazard index (HI), and carcinogenic risk
(CR) while the degree of pollution was assessed with
geo-accumulation index (Igeo) and contamination
factor (CF). The pollution assessment revealed that
the soil samples were moderately to highly polluted
with Cd. In both seasons, Zn and Mn, respectively,
I.Ilechukwu
Department ofIndustrial Chemistry, Madonna University,
P.M.B 48, Elele,RiversState, Nigeria
L.C.Osuji· M.O.Onyema
Department ofPure andIndustrial Chemistry, University
ofPort Harcourt, P.M.B 5323, Choba,RiversState5323,
Nigeria
C.P.Okoli(*)
Department ofChemistry/Biochemistry & Molecular
Biology, Alex Ekwueme Federal University, ,
NdufuAlike,EbonyiState, Nigeria
e-mail: nonsokoli@yahoo.com
G.I.Ndukwe
Department ofChemistry, Rivers State University,
Nkpolu-Oroworukwo,PortHarcourt,RiversState, Nigeria
Environ Monit Assess (2021) 193:461
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461 Page 2 of 14
hydrocarbon combustion, and spillage of petro-
chemicals (Trujillo-González, 2016; Mgbemena
etal., 2017; Ercilla-Montserrat etal., 2018; Khalifa
& Gad, 2018). Human health risks associated with
heavy metals in soil may be due to ingestion, inha-
lation, or dermal contact with contaminated soil,
food, and water. Other likely consequences include
reduced soil fertility and poor agricultural products
(Ezemonye etal., 2019; Eziz etal., 2018; Hu et al.,
2017; Li et al., 2013; Rahman et al., 2019). Soil
heavy metal contamination may also be an indica-
tion of the presence of other concomitant pollutants
(Keshta etal., 2020).
Asphalt cement is produced by mixing aggre-
gates with bitumen under high temperature condi-
tions. Bitumen contains heavy metals and hydrocar-
bons including heterocyclic compounds (NIOSH,
2001; Ilechukwu & Osuji, 2013a; Asphalt Institute
& European Bitumen Association,2015; Xiu etal.,
2020; Herazo etal., 2021). Asphalt production pro-
tocols such as heating of aggregates and bitumen
during mixture, loading and transportation of aggre-
gates and produced asphalt, and vehicles and facil-
ity maintenance introduce diverse pollutants into the
surrounding environment (Osuji etal., 2012; Rilwani
& Agbanure, 2010). Aggregates used for asphalt pro-
duction are from different lithogenic and anthropo-
genic sources with varying concentrations of heavy
metals. Some of these metals may escape from the
aggregates and bitumen during asphalt production
and usage into surrounding soils and groundwater
(Liang et al., 2017). The toxicity, carcinogenicity,
and mutagenic capabilities of these heavy metals
have been documented (Jan etal., 2015; Kim etal.,
2015; Reutova, 2017). The ever-increasing need for
road construction and expansion in Nigeria has led
to a corresponding increase in the number of hot mix
asphalt plants in the country. For convenience and
proximity to construction sites, some of these plants
are built in residential areas. Emissions from these
plants may contaminate the environment and consti-
tute public health risk (Iwegbue, 2013; Khare etal.,
2020).
Health risk assessment evaluates the likely occur-
rence of adverse effects of environmental pollution
to human health. Characterized into four major steps:
hazard identification, hazard characterization, exposure
assessment, and risk characterization, it has been an
important tool for assessing the probable occurrence
of health hazards associated with heavy metal pol-
lution (Dorne et al., 2011; Ezemonye etal., 2019; Jia
etal., 2018; Liang et al., 2017; Rahman et al., 2019).
However, the health risk assessment of heavy met-
als in asphalt plant vicinities has not received specific
attention like other pollutants generated during asphalt
production and usage (Axten etal., 2012; Chong etal.,
2014, 2018; Cui etal., 2020; Rhomberg et al., 2018).
This represents a knowledge gap for understanding
the potential effects of exposure of workers in asphalt
plants to soil heavy metals. This study, therefore,
aimed at assessing the level and human health risks
of heavy metal pollution in soils within the vicinity of
hot mix asphalt plants. Heavy metals selected for this
study have been listed as priority pollutants by USEPA
(Masindi & Muedi, 2018; Tóth etal., 2016). Some of
them have been found within the environment of indus-
tries that employ combustion or incineration in their
processes while some are components of bitumen and
have been detected among leached metals from asphalt
pavement (Von Gunten etal., 2020; Ozaki etal., 2019;
Zhao & Zhu, 2019; Mazumder et al., 2016; Asphalt
Institute & European Bitumen Association, 2015). The
result of this study will be helpful for pollution control
in relation to human health risk during asphalt produc-
tion and usage.
Materials andmethods
Study area
The two asphalt plants used for this study are located
in Obigbo (plant A) and Igwuruta (plant B) areas
of Rivers State, Nigeria (Fig. 1). Plant A is located
between latitude (4° 51 0 and 4° 51 55) N and lon-
gitudes (7°0.04 55 and 7°0.05 26) E while plant B
is located between latitude (4° 55 04 and 4° 56 30)
N and longitudes (7°0.02 30 and 7°0.03 0) E. Both
plants are located in satellite suburbs of Port Harcourt
city and have been in operation for 16years.
Sampling
The sampling protocol employed in this study
has been reported elsewhere (Ilechukwu & Osuji,
2013b). Soil samples (0–15cm) were randomly col-
lected cross-sectionally from the asphalt plants. Sam-
ples were collected at increasing distance of 10 m:
Environ Monit Assess (2021) 193:461
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five stations for plant A (10m, 20m, 30m, 40m, and
50m) and four stations for Plant B (10m, 20m, 30m,
and 40m) (Fig. 1). The number of sampling sites was
based on the relative size of the asphalt plant vicini-
ties. Plant A is larger than plant B and was the reason
for the extension of plant A to 50m while plant B was
40m. Two composite samples were derived from ten
samples collected 2m apart from each distance. The
samples were transferred into aluminum foil bags,
labeled accordingly, and taken to the laboratory. Sam-
ple collection for both plants was done in dry season
(March) and rainy season (August).
Sample digestion
The soil samples were ground with a porcelain
mortar and pestle after air-drying and then passed
through a 2-mm sieve. Five grams (5 g) of the
sieved soil was weighed into a digestion flask and
digested with 30 ml aqua regia (HNO3/HCl; 1:3
v/v) on a thermostatic hot plate at 150°C (Iwegbue
etal., 2015; Ngole-Jeme & Fantke, 2017). Deionized
water was added to rinse the flask after cooling. The
sample was filtered, and the filtrate was made up to
50ml with deionized water. Sample preparation and
analysis were done in triplicates. Quality control
procedure included the analysis of reference materi-
als and procedural blanks to ensure the accuracy and
precision of the analysis. Recoveries of the elements
ranged from 93 to 98%. The analysis was carried out
with AGILENT SPECTRA 55B atomic absorption
spectrophotometer (AAS) at detection limit (mg/kg)
of 0.5 (Cr), 0.3 (Co), 0.5 (Cu), 0.15 (Ni), 0.5 (Mn),
0.15 (Cd), 0.15 (Pb), and 0.3 (Zn).
Statistical analysis
Pearson correlation was used to examine inter-element
association. Statistical differences between metal con-
centrations in both plants and in both seasons were
determined with ANOVA and were considered signifi-
cant at p < 0.05.
Pollution assessment
Geo-accumulation index (Igeo) and contamination
factor (CF) were deployed for pollution assessment.
Geo-accumulation index (Igeo) was used to assess the
degree of pollution by heavy metals using the equa-
tion (Muller, 1969):
Fig. 1 Location map of the study site
Environ Monit Assess (2021) 193:461
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Where Cn is the concentration of heavy met-
als in soil, and Bn is the geochemical background
value of each element derived from the crustal val-
ues (Turekian & Wedepohl, 1961). The factor 1.5
accounts for variations in the background data due to
lithogenic effects. The seven categories of the geo-
accumulation index scale are in Table1.
Contamination factor (CF) is the ratio of metal
concentration in the sample (Cn) to that of the back-
ground concentration (Cb).
Background concentration (crustal abundance)
values of the respective metals were used for both
Igeo and CF calculation (Iwegbue etal., 2015). Con-
tamination factor of < 1 indicates low contamination,
and between 3 and 6 signifies considerable contami-
nation while CF > 6 is evidence of high contamina-
tion (Hakanson, 1980).
Health risk assessment
Exposure assessment
This quantifies the nature and probability of adverse
health effects on humans exposed to these metals. For
soils, exposure may be through three major pathways:
ingestion, dermal absorption, and inhalation (USEPA,
2011a; USEPA, 2011b; Dorne etal., 2011). Chronic
Igeo
=Log
2(
C
n
1.5 ×B
n)
CF =CnCb
daily intake (CDI) (mg/kg/d) for exposure assessment
is calculated thus.
where CDIing, CDIder, and CDIinh (mg/kg/d) repre-
sent the chronic daily intake of heavy metals through
ingestion, dermal contact, and inhalation, respec-
tively. CS is the heavy metal concentration in soil
(mg/kg). IR is soil ingestion rate (mg/day), CF is con-
version factor (kg/mg), EF is the exposure frequency
(day/year), ED is the exposure duration (year), PM10
is content of inhalable particulates in ambient air (mg/
m3), DAIR is the daily air inhalation rate (m3/day),
PIAF is retention fraction of inhaled particulates in
body, FSPO is fraction of soil-borne particulates in
air, SA is the exposed surface area of the skin (cm2),
AF is the skin adherence factor (kg/m2/day), ABS is
the dermal absorption factor, BW is the body weight
CDI
ing =
CS ×IR ×CF ×EF ×ED
BW ×AT
CDI
der =
CS ×SA ×AF ×ABS ×CF ×EF ×ED
BW ×AT
CDI
inh =
CS ×PM
10
×DAIR ×PIAF ×FSPO ×CF ×EF ×ED
BW ×AT
Table 1 Geo-accumulation index (Igeo) scale
Igeo value Class Sediment quality
≤ 0 0 Unpolluted
0–1 1 Unpolluted to moderately polluted
1–2 2 Moderately polluted
2–3 3 Moderately to strongly polluted
3–4 4 Strongly polluted
4–5 5 Strongly to extremely polluted
> 6 6 Extremely polluted
Table 2 Exposure parameter values
Parameter Value of parameter Reference
CS Observed metal concentration
IR 100 (USEPA, 2011b)
CF 10−6 (USEPA, 2002)
EF 350 (USEPA, 2002)
ED 30 (USEPA, 2002)
BW 65 (Jiang etal.,
2017)
AT 365 × ED (USEPA, 2011b)
LT 365 × 70 (USEPA, 2011b)
PM10 0.15 (NEPAC, 2014)
DAIR 14.5 (NEPAC, 2014)
PIAF 0.75 (NEPAC, 2014)
FSPO 0.5 (NEPAC, 2014)
AF 0.2 (USEPA, 2011b)
SA 5408 (USEPA, 2011b)
ABS 0.001 (USEPA, 2011b)
Environ Monit Assess (2021) 193:461
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(kg), and AT is the average time (day). The values of
these parameters are as shownin Table2.
Non‑carcinogenic risk assessment
Hazard quotient (HQ) is used for evaluation of non-
carcinogenic risk and is calculated by dividing CDI
with the reference dose (RfD) for specific metal
(Table3).
Hazard index
This is the sum of hazard quotient (HQ), and it assesses
the potential non-carcinogenic risk posed by all the
heavy metals. HI is expressed as .
If HI is greater than one (1), non-carcinogenic
effects of heavy metals to exposed individual may
occur. If the HI is below one, the exposed individual
may not be predisposed to any adverse effect.
Carcinogenic risk assessment
Carcinogenic risk is calculated as individual lifetime
cancer risk by multiplying lifetime average daily
doses (LADD) with cancer slope factor (CSF) (mg/
kg/day).
HQ
=
CDI
RfD
HI HQ CDIRfD
Total cancer risk (lifetime carcinogenic risk) is
expressed as the summation of the individual CR
(USEPA,2011a; Jia etal., 2018). LADD is calculated
with the same equation as CDI. However, average time
(AT) is replaced with lifetime (LT) expressed in day.
Acceptable threshold value for CR is 1.0E 4. CR val-
ues exceeding 1.0E 4 indicates potential lifetime car-
cinogenic risk (USEPA, 2011a).
Results anddiscussion
Results
The concentration of heavy metals in soils from plants
A and B are shown in Table4. For ease of under-
standing of the statistical analysis, the results are pre-
sented separately for each heavy metal pollutant.
Chromium
The mean concentration of Cr in soils from asphalt
plant A was 13.31 ± 1.25 mg/kg (dry season) and
11.52 ± 1.23 mg/kg (rainy season) while the con-
centration was 9.89 ± 1.30 mg/kg (dry season) and
11.82 ± 1.64 mg/kg (rainy season) for soils from plant
B. While Cr concentration in plant A was higher dur-
ing the dry season, the concentration in rainy season
was higher than that of the dry season in plant B. How-
ever, there was no significant difference (p < 0.05)
CR =LADD ×CSF
Table 3 Reference dose and slope factors of heavy metals
Metals Inhalation Ingestion Dermal Slope factor Reference
Cd 1.50E − 05 1.00E − 03 1.00E − 05 6.3 (inhalation) (USEPA, 2010; USEPA, 2012; Ngole-Jerne &
Fantke, 2017; Jia etal., 2018)
Co 6.00E − 06 3.00E − 04 1.60E − 02 (USEPA, 2010; Ngole-Jerne & Fantke, 2017)
Cr 2.86E − 05 3.00E − 03 6.00E − 05 0.5 (inhalation) (USEPA, 2010; USEPA, 2012; Ngole-Jerne &
Fantke, 2017; Jia etal., 2018)
Cu 6.90E − 04 4.00E − 02 1.20E − 02 (USEPA, 2010; Ngole-Jerne & Fantke, 2017)
Mn 1.43E − 05 4.60E − 02 1.84E − 03 (USEPA, 2010; Ngole-Jerne & Fantke, 2017)
Ni 9.00E − 05 2.00E − 02 9.00E − 05 0.84 (inhalation and ingestion) (USEPA, 2010; USEPA, 2012; Ngole-Jerne &
Fantke, 2017; Jia etal., 2018)
Pb 3.52E − 03 3.50E − 05 5.20E − 04 8.50E − 03 (ingestion) (USEPA, 2010; USEPA, 2012; Ngole-Jerne &
Fantke, 2017; Jia etal., 2018)
Zn 3.00E − 01 3.00E − 01 6.00E − 02 (USEPA, 2010; Ngole-Jerne & Fantke 2017)
Environ Monit Assess (2021) 193:461
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between Cr concentrations in dry and rainy seasons of
each plant and the Cr concentration in both plants.
Cobalt
The concentration of Co was 3.94 ± 0.69 mg/kg
(dry season) and 4.01 ± 0.73 mg/kg (rainy season)
for plant A and 2.58 ± 0.30 mg/kg (dry season) and
2.45 ± 0.07 mg/kg (rainy season) for plant B. Cobalt
concentration was higher in the rainy season and dry
season for plant A and plant B, respectively. There
was no significant difference (p < 0.05) between Co
concentrations in dry and rainy seasons of each plant
and the Co concentration in both plants.
Copper
The mean concentration of Cu in soil samples from
both plants was 5.14 ± 0.84 mg/kg (dry season) and
5.18 ± 0.88 mg/kg (rainy season) for plant A and
9.65 ± 1.31 mg/kg (dry season) and 8.41 ± 1.22 mg/kg
(rainy season) for plant B. While the Cu concentration
was higher in the rainy season for plant A, it was lower
in the rainy season for plant B. There was no significant
difference (p < 0.05) between the concentrations of Cu
in the dry and rainy seasons for plant A. However, the
Cu in soils from plant B showed a significant difference
(p < 0.05) between the concentrations in the dry and
rainy season. The concentration of Cu in the dry season
of Plant B was also significantly different from the con-
centration of Cu in both seasons for plant A.
Nickel
The mean concentration of Ni in soil samples from
the asphalt plants was 1.42 ± 0.41mg/kg (dry season)
and 1.28 ± 0.42 mg/kg (rainy season) for plant A and
2.18 ± 0.33 mg/kg (dry season) and 3.49 ± 0.51 mg/kg
(rainy season) for plant B. While the Ni concentration
in soils from plant A was higher in the dry season, that
of plant B was higher in the rainy season. Unlike plant
A, there was a significant difference (p < 0.05) between
the concentrations of Ni in dry and rainy seasons of
plant B. The concentration of Ni in rainy season of
plant B was also significantly different (p < 0.05) from
the Ni concentration for both seasons in plant A.
Manganese
The mean concentration of Mn in soils from the
asphalt plants was 8.84 ± 1.62 mg/kg (dry season),
9.72 ± 1.84mg/kg (rainy season) and 31.77 ± 2.22mg/
kg (dry season), and 33.46 ± 1.88 mg/kg (rainy sea-
son) for plant A and plant B, respectively. In both
plants, Mn concentration was higher in the rainy
season than in the dry season, and there was no
Table 4 Heavy metal concentration in soils from the asphalt plants
Results are expressed as mean ± standard error of mean (SEM). Letters a,b,c,d show the significant difference among the different
plant/seasons for each specific metal (p < 0.05)
* Regulatory guideline for heavy metal in industrial soils
Plant A (dry season)
Metals (mg/kg) Cr Co Cu Ni Mn Cd Pb Zn
Mean ± SEM 13.31 ± 1.25 3.94 ± 0.69 5.14 ± 0.84d1.42 ± 0.41c8.84 ± 1.62cd 0.92 ± 0.12cd 4.38 ± 0.61 31.64 ± 3.65cd
Range n = 10 7.84–19.30 2.27–9.88 2.45–11.07 0.26–4.63 3.08–33.41 0.37–1.52 2.56–8.09 9.37–48.01
Plant A (rainy season)
Mean ± SEM 11.52 ± 1.23 4.01 ± 0.73 5.18 ± 0.88d1.28 ± 0.42c9.72 ± 1.84cd 0.87 ± 0.10cd 3.37 ± 0.48 29.54 ± 3.78cd
Range n = 10 5.01–16.92 2.27–10.15 1.85–10.63 0.19–5.54 1.64–18.76 0.19–1.41 1.45–6.23 10.08–47.52
Plant B (dry season)
MEAN ± SEM 9.89 ± 1.30 2.58 ± 0.30 9.65 ± 1.31ab 2.18 ± 0.33 31.77 ± 2.22ab 1.58 ± 0.17ab 2.30 ± 0.62 10.08 ± 0.58ab
Range n = 8 5.34–15.36 1.19–3.81 5.42–15.2 1.03–3.92 22.46–41.13 1.22–2.71 1.25–6.48 7.50–12.63
Plant B (rainy season)
MEAN ± SEM 11.82 ± 1.64 2.45 ± 0.07 8.41 ± 1.22 3.49 ± 0.51ab 33.46 ± 1.88ab 1.87 ± 0.17ab 2.13 ± 0.64 9.95 ± 0.45ab
Range n = 8 6.42–21.36 2.22–2.77 3.91–14.35 0.67–5.41 26.00–40.85 1.09–2.38 0.54–6.31 7.93–11.58
*DPR 100 20 36 35 850 0.8 85 140
Environ Monit Assess (2021) 193:461
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significant difference (p < 0.05) between Mn concen-
trations in the dry and rainy seasons of each plant.
However, there was a significant difference (p < 0.05)
between Mn concentrations in both plants.
Cadmium
Cd concentrations in soils from both plants were
0.92 ± 0.12 mg/kg (dr y season), 0.87 ± 0.10 mg/kg
(rainy season) and 1.58 ± 0.17 mg/kg (dry season),
and 1.87 ± 0.17mg/kg (rainy season) for plant A and
plant B, respectively. Cd concentration in plant A was
higher in the dry season while the rainy season con-
centration was higher in plant B. There was no signif-
icant difference (p < 0.05) between Cd concentrations
in dry and rainy season samples of both plants, but
there was a significant difference (p < 0.05) between
Cd concentrations in both plants.
Lead
Pb concentration in soil samples from plant A was
4.38 ± 0.61 mg/kg (dry season) and 3.37 ± 0.48 mg/
kg (rainy season) while it was 2.30 ± 0.62 mg/kg
(dry season) and 2.13 ± 0.64 mg/kg (rainy season)
for plant B. In both plants, the Pb concentration was
higher in the dry season and there was no significant
difference (p < 0.05) between the dry season and rainy
season concentrations of Pb in both plants.
Zinc
Zn concentrations in soils from the asphalt
plant A were 31.64 ± 3.65 mg/kg (dry season)
and 29.54 ± 3.78 mg/kg (rainy season) while that
of plant B were 10.08 ± 0.58 mg/kg (dry season)
and 9.95 ± 0.45 mg/kg (rainy season). Dry season
soil samples recorded higher Zn concentration than
rainy season samples in both plants. No significant
difference (p < 0.05) was observed between Zn con-
centrations in dry and rainy season samples of each
plant, but there was a significant difference (p < 0.05)
between the Zn concentrations of both plants.
Discussion ofresults
Seasonal variation of the metals in soils from each
asphalt plant was not significant for most of the studied
metals except for Cu and Ni in plant B. Oftentimes,
this observation is because the effect of precipitation
on long-term accumulated metal concentration in soil
is negligible (Algül & Beyhan, 2020). Considering
the non-significance of these variations, increase or
decrease of the metals in either season may be attrib-
uted to leaching and dilution of the soil metal concen-
tration during the rainy season or evaporation in the dry
season leading to increased soil metal concentration
(Gune etal., 2020; Nguyen etal., 2020; Oluyemi etal.,
2008; Yahaya etal., 2009). The concentration of the
heavy metals in plant A was in the following order: Zn
> Cr > Mn > Cu > Pb > Co > Ni > Cd for dry season and
Zn > Cr > Mn > Cu > Co > Pb > Ni > Cd for rainy sea-
son. The following order was observed in plant B: Mn
> Zn > Cr > Cu > Co > Pb > Ni > Cd for dry season and
Mn > Cr > Zn > Cu > Ni > Co > Pd > Cd for rainy sea-
son. None of the metals from both plants and in both
seasons except Cd exceeded the threshold limit when
compared with regulatory standards and guidelines in
Nigeria (DPR, 2002). Cu, Ni, Mn, Cd, and Zn showed
a significant difference (p < 0.05) in their concentration
between soils from plant A and plant B. This may be
attributed to the differences in nature of aggregates,
road runoffs, and variations in anthropogenic activities
within the vicinity of the asphalt plants. No particular
trend was observed in the concentration of heavy met-
als in dry and rainy seasons of both plants. This indi-
cates that reduction in hot mix asphalt production as a
result of low construction activities in the rainy season
has minimal effects on the heavy metal concentration
in soils within hot mix asphalt plant vicinity.
Overall, these metals did not correlate with each
other in a particular context implying diverse sources.
They have been attributed to sources such as road
runoffs, vehicular exhaust emissions, and discharges
as well as engine oil disposal. Other sources include
metal plating, moving engine parts, diesel fuel,
asphalt paving, tire wear, and atmospheric deposi-
tion (Barber etal., 2006; Chen etal., 2018; Ghosh &
Maiti, 2018; Khalifa & Gad, 2018; Ma etal., 2016;
Ukabiala etal., 2010; Yan etal., 2013). The road to
any asphalt production plant is always heavy with
traffic. This is because heavy-duty vehicles most of
which operate on diesel are used for the supply of raw
materials (aggregates) and transportation of produced
asphalt to the construction sites. The operations of
these vehicles may have contributed more than any
other source to the soil heavy metals within the plant
Environ Monit Assess (2021) 193:461
1 3
461 Page 8 of 14
vicinities. High concentrations of Cr and Mn may also
be related to the use of bitumen in asphalt produc-
tion as these two metals have been found to be part
of bitumen components (Adebiyi etal., 2006; Asphalt
Institute & European Bitumen Association,2015).
Cr is easily released to the environment in acidic
soils. Perhaps this explains why it seems to occur
in higher concentrations more than the other metals
except Mn and Zn which are abundant in the earth’s
crust (Iwegbue et al., 2013). The presence of Mn
and Zn especially in relatively high concentrations
in soils within the asphalt plant vicinities may not
be unrelated to runoffs from aggregates stacked for
asphalt production considering their abundance in
the earth’s crust. Atmospheric deposition may also
be a very likely source since metals are distributed
in soils by the atmosphere within a distance that
depends on the size of particles, and some of these
particles escape from the plants during asphalt pro-
duction, transportation, and usage (Ferreira-Baptista
& De Miguel, 2005; Velea et al., 2009; Ma et al.,
2016; Chen etal., 2018; Yang etal., 2018; Cui etal.,
2020; Khare etal., 2020).
Pollution assessment
The mean Igeo values of all the elements in both
plants were negative except for Cd that was > 2
in plant A and > 3 in plant B, indicating that the
soil within the plant vicinities was moderately to
strongly polluted by Cd (Fig.2). These Igeo values
agree with the results of a similar study in asphalt
plant vicinities in Port Harcourt where the Igeo val-
ues of all the elements were negative except for As
and Cd (Edori & Iyama, 2021). Igeo values of all
elements in soil within the vicinity of asphalt plant
in Delta state, Nigeria, were also negative (Iwegbue
etal., 2015).
CF results (Fig.3) were consistent with the Igeo.
The mean CF of all the elements in soils from both
plants was < 1 except for Cd with values > 7, indicat-
ing high contamination.
Health risk assessment
The chronic daily intake (CDI) and the hazard quo-
tient (HQ) of the metals for plants A and B are
presented in Tables5 and 6, respectively. Zinc and
cadmium had the highest and the least CDI values,
respectively, for plant A in both seasons for inges-
tion, inhalation, and dermal routes (Table5). In plant
B, manganese and cadmium had the highest and the
least CDI values, respectively, for all the routes in
both seasons. The hazard quotient (HQ) values for
plant A in the dry season shows that cobalt had the
highest value for ingestion (1.94E 02) and inhala-
tion (7.90E 03) routes while chromium had the
highest value for dermal (3.54E 03) route. Nickel
Fig. 2 Component bar chart representing the Igeo of heavy metal pollution
Environ Monit Assess (2021) 193:461
1 3
Page 9 of 14 461
had the least values for ingestion (1.04E 04) and
inhalation (8.29E 07) routes while cobalt had the
least value for the dermal (3.93E 06) route. Haz-
ard quotient (HQ) for plant A in the rainy season
shows that cobalt, chromium, and manganese had
the highest values for ingestion (1.97E 02), dermal
(3.06E 03), and inhalation (8.18E-03), respectively,
while nickel had the least values for all the three
routes.
The values for HQ in Plant B were similar for
both seasons (Table6). Cobalt, chromium, and man-
ganese had the highest values for ingestion and der-
mal and inhalation routes, respectively. Zinc had the
least values for ingestion and inhalation routes while
cobalt had the least value for dermal route. HQ for
all the metals were less than 1(< 1) which indicated
that there were no health risks due to exposure to
the heavy metals via ingestion, inhalation, or dermal
Fig. 3 Component bar chart representing the CF of heavy metal pollution
Table 5 CDI and HQ for metals in plant A
THQ = HQing + HQder + HQinh
Metals Cr Co Cu Ni Mn Cd Pb Zn
Dry season
CDIing 1.96E − 05 5.81E − 06 7.58E − 06 2.09E − 06 1.30E − 05 1.36E − 06 6.46E − 06 4.67E − 05
CDIder 2.12E − 07 6.27E − 08 8.20E − 08 2.27E − 08 1.41E − 07 1.47E − 08 6.99E − 08 5.05E07
CDIinh 1.67E − 07 4.74E − 08 6.18E − 08 1.71E − 08 1.06E − 07 1.11E − 08 5.27E − 08 3.81E − 07
HQing 6.54E − 03 1.94E − 02 1.90E − 04 1.04E − 04 2.83E − 04 1.36E − 03 1.85E − 03 1.56E − 04
HQder 3.54E − 03 3.93E − 06 6.84E − 06 4.20E − 06 7.67E − 05 1.47E − 03 1.33E − 04 2.52E − 05
HQinh 5.60E − 03 7.90E − 03 1.54E − 06 8.29E − 07 7.44E − 03 4.61E − 03 1.50E − 05 1.27E − 07
THQ 1.57E − 02 2.72E − 02 1.98E − 02 1.10E − 04 7.80E − 03 7.43E − 03 1.99E − 03 1.82E − 04
Rainy season
CDIing 1.70E − 05 5.92E − 06 7.64E − 0E 1.89E − 06 1.43E − 05 1.28E − 06 4.97E − 05 4.36E − 06
CDIder 1.87E − 07 6.40E − 08 8.27E − 08 2.04E − 08 1.55E − 0 1.39E − 08 5.38E − 08 4.71E − 07
CDIinh 1.39E − 07 4.82E − 08 6.23E − 08 1.50E − 08 1.17E − 07 1.05E − 08 4.05E − 0 3.55E − 07
HQing 5.67E − 03 1.97E − 02 1.91E − 04 9.44E − 05 3.11E − 04 1.28E − 03 1.42E − 03 1.45E − 04
HQder 3.06E − 03 4.0E − 06 6.89E − 06 3.78E − 06 8.43E − 05 1.39E − 03 1.02E − 04 2.36E − 05
HQinh 4.85E − 03 2.54E − 02 1.55E − 06 7.48E − 07 8.18E − 03 4.36E − 03 1.15E − 05 1.18E − 06
THQ 1.36E − 02 2.78E − 02 1.99E − 04 9.89E − 05 8.57E − 03 7.03E − 03 1.53E − 03 1.70E − 04
Environ Monit Assess (2021) 193:461
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461 Page 10 of 14
routes (Essien et al., 2019; Ezemonye et al., 2019).
The exposure order from HQ was ingestion > inhala-
tion > dermal for both seasons in plant A while plant
B was inhalation > ingestion > dermal. This shows
that health risks associated with exposure of work-
ers in asphalt plants to soil heavy metals are likely to
occur from ingestion or inhalation of the soil particles
rather than dermal contact with the soil.
The total hazard quotient (THQ) sums up the
hazard quotient from ingestion and dermal and
inhalation routes for each metal. Cobalt and man-
ganese had the highest THQ for plant A and plant
B, respectively. The orders of THQ for the metals
were similar for both seasons in each plant and
were as follows: Co > Cr > Mn > Cd > Pb > Cu > Z
n > Ni for plant A and Mn > Co > Cd > Cr > Pb >
Cu > Ni > Zn for plant B. However, THQ for each
metal was less than 1.00E + 00 indicating no sig-
nificant non-carcinogenic risk (Essien etal., 2019;
Ezemonye etal., 2019). This implies that the haz-
ard index (HI) of the samples from both plants in
both seasons was also less than 1.00E + 00 which
is a safe limit for exposure to the soils from asphalt
plants (Fig.4).
The carcinogenic risk (CR) calculated as individ-
ual lifetime cancer risk was done for selected metals
such as Cr, Cd, Pb, and Ni because there are no exist-
ing carcinogenic factors for other metals (Liang etal.,
2017). The values of CR for the selected metals were
less than the threshold value of 1.0E 04 (Table7).
CR values exceeding 1.0E 04 indicate potential
Table 6 CDI and HQ for plant B
Metals Cr Co Cu Ni Mn Cd Pb Zn
Dry season
CDIing 1.46 − 05 3.81E − 06 1.42E − 05 3.22E − 06 4.69E − 05 2.33E − 06 3.93E − 06 1.49E − 05
CDIder 1.58E − 07 4.12E − 08 1.54E − 07 3.45E − 08 5.07E − 07 2.52E − 08 3.67E − 08 1.61E − 07
CDIinh 1.19E − 07 3.10E − 08 1.16E − 07 2.62E − 08 3.82E − 07 1.90E − 08 2.77E − 08 1.21E − 07
HQing 4.86E − 03 1.27E − 02 3.56E − 03 1.61E − 04 1.02E − 03 2.33E − 03 9.69E04 4.96E − 05
HQder 2.63E − 03 2.57E − 06 1.28E − 05 6.44E − 06 2.76E − 04 2.52E − 03 6.99E − 05 8.04E − 06
HQinh 4.16E − 03 5.17E − 03 2.89E − 06 1.27E − 06 2.67E − 02 7.92E − 03 7.86E − 06 4.04E − 07
THQ 1.17E − 02 1.79E − 02 3.72E − 04 1.69E − 04 2.80E − 02 1.28E − 02 1.05E − 03 5.80E − 05
Rainy season
CDIing 1.75E − 05 3.61E − 06 1.24E − 05 5.15E − 06 4.94E − 05 2.76E − 06 3.14E − 06 1.47E − 05
CDIder 1.88E − 07 3.91E − 08 1.34E − 07 5.57E − 08 5.34E − 07 2.98E − 08 3.40E − 08 1.59E − 07
CDIinh 1.42E − 07 2.95E − 08 1.01E − 07 4.20E − 08 4.07E − 07 2.25E − 08 2.56E − 08 1.20 − E07
HQing 5.81E − 03 1.20E − 02 3.10E − 04 2.57E − 04 1.07E − 03 2.76E − 03 8.98E − 04 4.89E − 05
HQder 3.14E − 03 2.44E − 06 1.12E − 05 1.03E − 05 2.90E − 04 2.98E − 03 6.47E − 05 7.94E − 06
HQinh 4.97E − 03 4.91E − 03 2.52E − 06 2.04E − 06 2.82E − 02 9.38E − 03 7.28E − 06 3.99E − 07
THQ 1.39E − 02 1.70E − 02 3.23E − 04 2.70E − 04 2.95E − 02 1.51E − 02 9.70E − 04 5.73E − 05
Fig. 4 Hazard index (HI) of metals in asphalt plants A and B
Environ Monit Assess (2021) 193:461
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Page 11 of 14 461
lifetime carcinogenic risk (Jia etal., 2018). The CR
for Pb was calculated for the ingestion route while
that of Cr, Ni, and Cd were calculated for the inhala-
tion route (Table2). The total cancer risk which is the
sum of cancer risks from all the exposure routes was
within the acceptable limit of 10−6 to 10−4 (Table7).
Conclusion
Heavy metal concentration in soils from the asphalt
plants used for this study was within the thresh-
old limit by regulatory standards except cadmium.
The pollution assessment also confirms that the
soils were moderately to strongly polluted by Cd.
Hazard quotient and hazard index values from the
health risk assessment were within allowable lev-
els. Dermal route proved to be the exposure route
least likely to cause any health hazard to humans
on exposure to soil heavy metals within asphalt
plants. Carcinogenic risks of the metals were also
within allowable levels. Although no serious pol-
lution nor significant health risk was observed in
this study, clean and efficient production of hot
mix asphalt and adequate use of personal protec-
tive equipment should be encouraged to minimize
health and environmental risks during both produc-
tion and usage.
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... Soil contamination with PTEs is significantly increasing over the world and associated with massive urbanization and uncontrolled agricultural and intensive industrial activities [3][4][5][6][7][8]. Recently, assessment of PTE contamination in the soil of different land-use types has received growing attention since it has been related to several serious environmental problems [9][10][11][12]. Moreover, transfer and bioaccumulation of soil PTEs to cultivated crops can pose a frightening risk to human health through the food chain [13][14][15][16]. ...
... Moreover, transfer and bioaccumulation of soil PTEs to cultivated crops can pose a frightening risk to human health through the food chain [13][14][15][16]. Many health-related problems were linked to overexposure to PTEs [10,17,18]. ...
... The majority of EF values of the measured PTEs have shown moderate enrichment (EF = 2-5). Some samples recorded high EF values (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) for Cr, Cu, Hg, Pb, and Zn, showing significant enrichment, suggesting that these elements are probably enriched through anthropogenic activities. ...
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Enhanced soil’s magnetic susceptibility reflects particles of anthropogenic/natural origin; therefore, it can be utilized as an indication of soil contamination. A total of 51 different land-use soil samples collected from Greater Cairo, Egypt, were assessed integrally using potentially toxic elements content (PTEs), magnetic susceptibility, and statistical and spatial analysis. PTE concentrations were compared to the world average, threshold, and screening values set by literature. Various environmental indices were estimated to assess soil contamination with these elements. Spatial distribution maps of PTEs and environmental indices were constructed to provide decision makers with a certain identification of riskier areas. In general, the concentrations of the analyzed PTEs showed variation with land-use types and follows a pattern of: Industrial > Agricultural > Urban. The distribution of PTEs in Greater Cairo was influenced by several anthropogenic sources, including traffic emission, industrial activity, and agricultural practices. The measured magnetic susceptibility values indicate magnetically enhanced soil signals dominated by multi-domain or pseudo-singledomain superparamagnetic particles of anthropogenic origin. A significant association was observed between magnetic susceptibility values and Co, Cr, Cu, Ni, and V, and the calculated environmental indices. It can be concluded that magnetic susceptibility is of proven effectivity in the assessment of soil contamination.
... For example, lead (Pb) is known for its negative effects on neural development (16), while cadmium (Cd) is known for its risk of preterm delivery (17). Usually, this can be seen in people living in highly industrialized, highly polluted and poor areas (18)(19)(20)(21)(22). As such, the assessment of these ions in the amniotic fluid is essential to understanding the risks these people might be facing. ...
... More importantly, the comparison between the two cities showed that patients from Petrosani, a well-known industrial region, had higher concentrations of Zn, Cd, Pb and As. This is in agreement with other international studies showing that people living in industrialized regions are susceptible to accumulation of these elements, even if they mostly measured the concentrations either in the mother's serum, urine, toe-nails, hair, fetal placenta and cord blood (16)(17)(18)(19)(20)(21)(22)90,115,120,121). These elements are important as their concentration may be further increased by tobacco and are secreted in colostrum and breast milk (122). ...
... This disease was due to the consumption of rice irrigated with water containing a strong load of cadmium. Heavy metal contamination levels ten times as high as the toxicity threshold were found in the inhabitants' urine [23][24][25][26]. In the same vein, the studies by [25,27] carried out in Lubumbashi showed that contamination of pregnant women by uranium and manganese led to the birth of three babies presenting malformations known as holoprosencephaly. ...
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... If 95% confidence intervals were all less than 0, mining in Southwest China did not significantly increase the content of heavy metals in soil (p < 0:05). If the 95% confidence interval contained 0, it was believed that mining in Southwest China had no significant impact on the content of heavy metals in soil (p < 0:05) [13,14]. In order to more conveniently explained the influence of mining on the content of heavy metals in soil in Southwest China, the percentage change of the content was calculated by the following formula: ...
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In order to solve the intensifying problem of heavy metal pollution of soil in mining areas, a method for monitoring air quality and soil environment in mining areas based on the Internet of Things is proposed. Using meta-analysis method and health risk assessment method, the impact of mining on soil heavy metal content in Southwest China was quantitatively analyzed, and the relationship between soil heavy metal value and its potential influencing factors was discussed, as well as the heavy metal pollution, ecological risk, and health caused by soil mining activities. Risks were assessed. The results showed that artificial and oral intake were the main modes of soil heavy metal exposure, with the highest daily intakes for noncarcinogenic risk children and the highest daily intakes for carcinogenic risk adult females. The noncarcinogenic risk (HQ>1) of soil As and Pb exposure to children was 3.74 and 1.44, respectively. The carcinogenic risk values of As, Cd, Cr, and Ni in soil were all higher than 10-6, indicating that the carcinogenic risk was within the tolerance range of human body. Children were exposed to the combined noncarcinogenic risk ( HI = 3.83 ), and the risk values of the three types of recipients were 1.19 × 10 − 4 , 1.21 × 10 − 4 , and 1.06 × 10 − 4 , respectively. The correlation between heavy metal content and environmental factors was obtained. It is verified that the system in this paper can effectively monitor the meteorological environment and soil environment, and at the same time, it reveals the pollution law of heavy metals in the soil of the mining area, which provides supporting conditions for future mining and heavy metal pollution management.
... Therefore, the cable industry and Cu received an entry in Table 1, f. Also the distance to the asphalt factory (sites 27-30, Fig. 1C) and concentrations of Cd, Cr, Cu, Ni, Pb, and Zn that can be emitted, amongst others, by this production (Ilechukwu et al., 2021) were put into a linear regression but was not significant. The asphalt factory did not raise local heavy metal concentrations either, which is why it had no entry in Table 1, f. ...
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Cuba is a country with considerable potential for economic growth, and special efforts are made to increase the agricultural output. As food production depends on the quality of soils, heavy metal concentrations were measured in 39 soils in the province of Mayabeque, Cuba, and interpreted in light of anthropogenic activities and pedogenic conditions (soil type and properties). With median concentrations of 1.8 Cd, 60.3 Cr, 48.1 Cu, 36.2 Ni, 16.7 Pb, 55.0 Zn, and 0.1 mg/kg Hg, soils of Mayabeque were mostly below Cuban quality reference values (QRV) representing benchmarks of quality standards but no official threshold values. Only Cd concentrations were in many cases above the QRV of 0.6 mg/kg and some Cu concentrations above the one of 83 mg/kg. While Cd, Cr, and Ni concentrations were rather pedogenically driven, Cu, Pb, Zn, and Hg contents were rather anthropogenically influenced. When evaluated statistically, Cd and Cr showed most times a significant influence of both sources. In contrast, Ni and Zn could not be significantly related with the origins investigated in this study. Hence, the allocation of heavy metal concentrations to pedogenic or anthropogenic contamination or pollution sources is tentative and needs further investigations. Nevertheless, the present data adds information on soil heavy metal concentrations in the Caribbean region, serves as reference before further industrial development, and sets the ground for adaptation of the QRV for Cd and possibly future national environmental standards.
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The aim of this research was to highlight the impact of urbanization and agriculture on soil quality, mainly by focusing on heavy metal accumulation (Cd, Cu, Fe, Mn, Ni, Pb and Zn) in the fragile riparian ecosystems of the Medjerda river (Souk-Ahras, Algeria). This study was performed in three cultivated soils (0-10, 10-20, 20-60 cm depth) along an increasing gradient of anthropogenic pressure in non-urban (NU), peri-urban (PU) and urban areas (U). Geo-accumulation index (Igeo), Enrichment factor (EF), Pollution load index (PLI) and Potential ecological risk index (RI) were calculated, as well as the potential non-carcinogenic risk for humans (HI). Additionally, to corroborate the role of Bufo spinosus D. as biosentinel, a skin biopsy was performed to quantify the concentration of heavy metals in both terrestrial and aquatic ecosystems. The results showed that when compared to NU, U and PU areas were richer in heavy metals. In particular, Igeo-Cd displayed strongly contaminated soil in U (>3), EF showed high enrichment of heavy metals (>2) for all the soils except for Ni, PLI presented no contamination for all (<1) while RI was significantly higher in U (>300), denoting a strong impact of heavy metals on soil quality. However, HI was below 1 for all the studied areas, although the highest values were related to U and PU. The skin biopsy showed the highest values for Cu, Fe and Pb in PU (0.328, 0.713 and 0.524 mg kg-1, respectively) similarly to trends observed in the soil of that area. This study shed light on the rising pollution of heavy metals due to urbanization and agricultural input in these fragile ecosystems where Bufo spinosus D. plays the role of potential bio-indicator for environmental pollution.
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Copper (Cu) and cadmium (Cd) metal distribution in soil–plant ecosystems and their public health risk impact on ruminants (cows, buffalo, and sheep) are explored in the present investigation. Five different forage crops were selected, and the foraging responses of three types of ruminants (cows, buffalo, and sheep) at three ecological sites were evaluated. The soil of these three ecological sites was metal polluted (due to wastewater irrigation) and was studied to evaluate the metal contamination and pollution load index. For the assessment of Cd and Cu, soil, vegetation, blood, hair, and feces samples were collected and analysed using an atomic absorption spectrophotometer. High consumption of fodder crops (Sorghum bicolor Kuntze, Sesbania bispinosa (Jacq.) W. Wight, Cynodon dactylon (L.) Pers., Suaeda fruticosa (L.) Forssk., and Tribulus terrestris L.) by cows and buffalo at site-III resulted in an increase in daily Cu and Cd intake. The pollution load index was higher at site-II and site-III, indicating a severe health risk scenario for local inhabitants. Cd and Cu were at their maximum levels in fodder crops. A significant increase in the concentrations of Cd and Cu was found in the blood, hair, and feces of cows and buffalo at site-III. Ecological indicators such as the bioaccumulation factor, the pollution load index, and the enrichment factor were found to be higher in buffalo than cows. The Cd level in forages was highest at the site-III Cd level and in the order of S. bispinosa > S. fruticosa > T. terresteris > C. dactylon > S. bicolor. Although these levels were lower than the permissible maximum limit, they were generally higher in the forage crops. Exposure of local inhabitants to the consumption of milk and meat from these cattle showed the serious health risks consequences. This situation can be properly managed by general monitoring of soil and vegetation pollution, avoiding metal contamination in the soil and food chain components, and using treated waste water and other alternate water sources for forage irrigation.
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