QUALITATIVE ASSESSMENT OF SOIL AND SEDIMENT POLLUTION
WITH SOME HEAVY METALS: A CASE STUDY OF DUHOK VALLEY IN THE KURDISTAN REGION OF
IRAQ
Najlaa M.A. Qaseem a,* , Maher Khalid a, Abdulazeez Y.T. Al-Saffawi b
a Faculty of
Science, University of Zakho, Zakho, Kurdistan Region, Iraq - (najlaa.qaseem, maher.ali )@uoz.edu.krd
b Faculty of
Educat. For Pure Sci. University of Mosul, Mosul, Iraq – (alsaffawia2025@uomosul.edu.iq)
Received: 28 Oct.,
2022 / Accepted: 20 Nov., 2022 / Published: 30 Jan., 2023 https://doi.org/10.25271/sjuoz.2022.11.1.1048
ABSTRACT:
The
current study was conducted on the valley of Duhok and the agricultural lands
irrigated from it, where three sites were identified for collecting samples
quarterly from soil and sediment using clean plastic bags for the purpose of
measuring lead, nickel, cobalt and copper. Pollution load index (PLI), Nemerow
pollution index (PIN), Potential Ecological Risk (PER) and Geo-accumulation
Index (Igeo) were also calculated according to the internationally approved
methods. The results indicated that most of lead, nickel and copper
concentrations in soils and sediments exceeded the limits allowed by WHO, reaching
annual rates (96.758, 168.746 and 29.88) , (111.25, 219.65
and 48.162) mg.kg-1, respectively. This fluctuation in
concentrations was reflected in the values of the studied indicators for both
soil and sediment, where 50% and 58% of the studied specimen are of the
polluted grade and the remnant
are of the non-polluted grade according to the PLI values. So is the case with
PIN where 58% of the soil specimen and 41.6% of the sediment samples were of
the severe pollution grade, while 25% and 33.3% of the specimen were of the heavy pollution grade and the remnant were slightly
pollution grade. The same applies to the results of the PER index values, where
50% and 41.67% of the specimen were from the Medium ecological risk category, and
the rest were from the low ecological risk category, likewise for the (Igeo) values,
100% and 96% of the soil and sediment samples were from the Weakly polluted
category.
KEYWORDS: Duhok Valley., Soil and Sediment Pollution, Heavy Metal,
PLI, PIN, Igeo.
Heavy
metals include all metallic and semi-metallic elements that have a relatively
high density (five times the density of water), and are characterized by their
high toxicity and lack of decomposition or damage, as well as the possibility
of their entry into the human body through vegetables, meat, drinking water and
air such as As, Hg, Cd, Pb, Cr, Co, Ni, Mn and Zn. Etc. Its danger comes as a result of its tendency
to accumulate and biomagnify within the bodies of living organisms, which
represents the increase in the concentration of chemicals (including heavy
metals) in the bodies of living organisms over time compared to their
concentrations in the environment in which they live (Vetrimurugan et al, 2017;
El-Saadani et al, 2022; Qaseem et al, 2022a). Some of these minerals
(Microelements such as Zn, Cu, Co, Mn and Fe etc.) have a necessary role in the
vital processes of plants and animals when they are present in low
concentrations in the environment, but it becomes toxic at high concentrations
(Suresh et al. 2015; Xu et al. 2016; Billah et al. 2017). Heavy metals arise to pollute soils and
bottom sediments of rivers, streams, and valleys, either naturally as a result
of the processes of decomposition and erosion of rocks in the ground or through
human activities (Wuana et al, 2020), such as chemical and petrochemical
industries, fossil fuel combustion, agricultural activities, vehicle exhaust
products, waste disposal, etc. The differences in the concentrations of heavy
metals in soil and sediments depended on
the size of the particles and the amount of organic matter in them, because the
abundance of organic materials works to bind and deposit them. (Samy and
El-Bady, 2014; Pereira et al, 2022). As for the distribution and spread of
heavy metals within ecosystems, they are subject to many complex processes for
the exchange of such pollutants (El-Sorogy etal, 2017). Heavy metals may also
be released into the soil solution or the water that rises, bottom sediments as
a result of microbial activities in the oxidation and reduction processes that
lead to a decrease in the pH, except for cobalt, it is amphoteric complexes (Abdo,
2004), to be absorbed by plants and microorganisms to enter the food chain
(Al-Khashman, 2012; ElSorogy etal, 2012). Which negatively affects ecosystems
as a result of their ability to accumulate and bio-magnify within ecosystems
(Ragi et al, 2017; Billah et al, 2017; Rakib et al, 2021).As for Duhok valley,
the pollution of the bottom sediments of the valley may be caused because it is
a waterway that collects most of the wastewater (civil, agricultural and
industrial) through estuaries spread on its sides and municipal solid waste, as it is removed in an
unscientific method and placed in open places, which causes a serious danger to
the surrounding environment (Hassan and Al-barware, 2016; Hammash and Abed,
2022; Qaseem et al, 2022b). These minerals are also transferred to the
agricultural soils near it as a result of irrigation operations with the water
of the valley, in addition to the use of agricultural fertilizers and particles
falling on them due to the burning of fossil fuels and plastic materials, and
as a result of the importance of heavy metal pollution for their negative
effects on plants and humans, and the lack of such studies in Iraq the current
study investigates the heavy metal elements in the bottom sediments of the
valley and agricultural soils that uses the water of the valley for irrigation
with the application of some mathematical indicators to assess the quality of
the soils and sediments, to take appropriate actions when needed.
When the concentrations
of these mineral elements rise in the soil or from the bottom sediments that
will be released to the surrounding environment at a low pH, which confuses the
ecosystem and negatively affects the crustaceans and aquatic organisms that
will accumulate in them with the possibility of their transmission to humans
through the food chain, causing serious health damage at high concentrations.
Such as cancerous diseases, prostate, kidney dysfunction, nervous system and
heart diseases, etc. (Biswas et al, 2017; Rakib et al, 2021).
The current study was
conducted on Duhok valley (which is locally called Hishkaro valley) and the
adjacent lands in the Duhok Governorate in northern Iraq. This valley is one of
the natural valleys to drain rainwater during the winter season, as well as
sulfur springs located in the northern part of the city, also, part of the
water of Duhok Dam, located north of the study area, is drained into the
valley. As well as the discharge of all domestic, agricultural and industrial
wastewater through many estuaries scattered on both sides of the valley to be
transferred outside the city through its 25 km course to pour into the Mosul
Dam lake, causing negative effects on the quality of its water. which may
affect the productivity of plants and soils irrigated with valley water (Qaseem
et al, 2022c). The region is characterized by a hot, dry climate in summer and
cold, rainy winter with little rainfall in recent years and extreme
temperatures to rise more than 53˚C in summer while dropping below zero ˚C in
winter.
All used glass and tools
must be washed with 10% nitric acid solution and then rinsed with distilled
water several times, and all the reagents used in the study are of high purity
(Kouassi et al, 2015). After conducting a field survey, three sites were
selected to collect sediment samples from the valley and the soils of farms
irrigated from its water during the four seasons (at the rate of three
repetitions per season for each site) starting from February 2021 until January
2022. Table (1) and Figure (1) show some characteristics of the study area.
Table (1):
Characteristics of the studied sites for the collection of sediments and soil
samples of Duhok valley, northern Iraq.
|
Sites |
Altitude |
Longitudes
(E) |
Latitudes (N) |
|
|
N1 |
Duhok dam |
607 m |
40°00’09” |
36°87’74” |
|
N2 |
Khashman Spring1 |
523 m |
42°99’38” |
36.85’39” |
|
N3 |
Bakhotmy |
364 m |
42°85’38” |
36°80’86” |
|
1Near
Duhok Stadium |
||||
Where the samples are
placed in polyethene bags, and then kept in a cooler box until taken to the
laboratory for the purpose of air drying the samples at atmospheric
temperature, then air drying them in an oven at 75° C for an hour
(Chandrasekaran et al, 2014; APHA, 2017). Fine pebbles and foreign bodies are
removed and the dried sediment and soil samples are smoothed using a ceramic
mortar and passed through a 2 mm sieve with manual stirring for several
minutes. After that, the samples are transferred to a polyethylene bag until
the digestion operations are performed.
A gram
of samples was weighed and transferred quantitatively to a glass beaker, in
which small ceramic pieces were added to avoid cracking and losing part of the
sample, then (10) ml of the digestion solution was added (acid mixture of H2SO4,
HNO3 and H2ClO4) (Balakrishnan et al, 2015),
the baker was covered with a glass watch to heat the samples by placing them in
a sand bath on a hotplate(in the hood), until the white and
Figure (1): shows the study area and sample collection sites.
brown
fumes disappear and the solution becomes clear (an appropriate amount of
digestion solution is added if necessary), The samples are cooled to complete
the volume to 50 ml with solution 2 % HNO3. The concentration of
metallic elements (Pb, Cu, Co and Ni) in the digested were measured using the
Atomic Absorption Spectrophotometer (AAS Perkin Elmer analysis) with the use of
the Blank coefficient as the samples, then the concentrations of the elements
are found compared to the standard curves prepared previously and the results
are expressed in mg.km-1 dry weight. according to (APHA, 1998; 2017;
Zhang et al, 2021)
The
state of pollution in sediments and soil for the current study determined four
indices (Najamuddin et al, 2016; Hu et al, 2013):
2.3.1
The pollution load index (PLI): The pollution load index for soil
and sediment is calculated for each site according to (Manea et al, 2019), as
follows:
Where:
n = the number of mineral elements, CF = Contamination factor which represents
the proportion of the metallic element measured over the background
concentration (Cf = Ci/ Bn), if the PLI value is higher than 1 it means that
the samples are contaminated, and if less than 1 it means that there is no
contamination in the sample, according to (Manea et al, 2019; Kouakoui et
al,2021)
2.3.2
Nemerow pollution index (PIN): The general pollution of the soil
represents the sedimentation with heavy metals and is calculated through the
following equation (Hu et al, 2013):
Where:
(PI)R: is the average value of a single pollution index., (PI)Max: is the
maximum value of a single pollution index, which is calculated from the ratio
between the concentration of the metallic element (Ci) in the soil or sediment
sample and the reference value (Si), ( PIi = Ci/ Si).
Therefore, soil and sediment quality are classified into five categories (Kour
et al, 2022): PIN< 0.7: un
polluted, 0.7 < PIN ≤ 1.0: Slightly polluted., 1.0< PIN
≤ 2.0 moderately polluted., 2.0 < PIN ≤ 3.0: Severely polluted.,
PIN > 3.0: Heavily polluted.
2.3.3Geo-accumulation Index (Igeo): The
geographical accumulation index (Igeo) is calculated to assess the risks of
heavy metals according to the Müller equation referred to (Najamuddin et al, 2016;
Wong et al, 2017; El-Saadani et al, 2022):
Igeo
= Log 2 × [
where Cn: is
the measured concentration of mineral n in soils and benthic sediments, and Bn:
is the value of the geochemical background of mineral n. The factor 1.5
compensates for possible fluctuations in background values of a given substance
in the environment, as well as very small human influences. Müller identified
seven categories for theGeo-accumulation Index (Igeo) (Chen et al, 2022):
Igeo ≤ 0 is
class 1 (unpolluted)., 0 < Igeo ≤ 1 is class 2 (weakly polluted)., 1 < Igeo ≤ 2 is
class 3 (moderately polluted)., 2 <
Igeo ≤ 3 is class 4 (moderately to strongly polluted) ., 3 < Igeo ≤ 4 is
class 5 (strongly polluted)., 4 < Igeo ≤ 5 is class 6 (strongly to extremely
polluted)., Igeo > 5 is class 7 and extremely polluted.
2.3.4Potential Ecological Risk index
(PERI): This index is widely used to assess the environmental parameters
of heavy metals in soils and sediments (Kaue et al, 2022) and is calculated
from the equations he mentioned (Kormoker et al, 2019; Wana et al, 2020):
ERf = CFi × Tri
Where,
ERf: Ecological Risk factor, CFi: contamination factor of heavy metal, Ci:
concentration of metal, Bn: Background Value of soil, Tri: toxicity response
factor of heavy metal the toxic response factors for lead: 5, copper: 5.5,
cobalt: 23 and nickel: 5 (Izah et al., 2018). The
Potential Ecological Risk index (PERI) values are categorized into five classes
as follows: PERI < 30: Slight risk., 30 ≤ PERI < 60: Medium risk., 60 ≤
PERI < 120: Strong risk., 120 ≤ PERI < 240 Very strong risk., 240 ≥ PERI
≥ 240: Extremely strong risk (Wuana et al, 2020).
The
seasonal, annual averages and the standard deviation of the four heavy metal
ions concentrations in the soils of fields and farms irrigated from the waters
of Duhok valley indicate that the seasonal average of lead concentration for
the three sites (N1, N2, N3) were (35.76 to 122.12), ( 44.40 to 131.35 and
(61.03 to 155.15) mg. kg -1 respectively, while the annual rate of
lead fluctuated between (32.645 ± 87.048 to 32.472 ± 97,375) mg. kg-1, as for
copper, cobalt and nickel, the annual rates of the studied sites ranged between
(29.88 ±5.6392 to 27.09 ±9.3635), (29.115 ±5.3607 to 32.088 ±19.119) and (111.43 ±6.8508 to 168.74
±47.013 ) successively, as in table 2.
|
Table (2): The seasonal and annual average of heavy metal
concentrations ions in the soils in the study area (mg. kg-1 dry
weight). |
|||||||
|
Elements |
Sites |
Winter |
Spring |
Summer |
Autumn |
Mean |
± Sd |
|
Pb |
N1 |
83.520 |
122.12 |
106.79 |
35.760 |
87.048 |
32.645 |
|
N2 |
131.35 |
44.400 |
113.06 |
100.69 |
97.375 |
32.472 |
|
|
N3 |
155.15 |
65.390 |
105.46 |
61.030 |
96.758 |
37.901 |
|
|
Cu |
N1 |
35.600 |
35.230 |
25.860 |
22.830 |
29.880 |
5.6392 |
|
N2 |
28.800 |
34.200 |
25.960 |
24.900 |
28.465 |
3.6051 |
|
|
N3 |
38.930 |
13.770 |
23.830 |
31.830 |
27.090 |
9.3635 |
|
|
Co |
N1 |
30.360 |
27.830 |
33.560 |
27.200 |
29.738 |
2.5038 |
|
N2 |
33.930 |
20.100 |
32.130 |
30.300 |
29.115 |
5.3607 |
|
|
N3 |
64.690 |
16.370 |
25.830 |
21.460 |
32.088 |
19.119 |
|
|
Ni |
N1 |
156.82 |
97.020 |
205.25 |
215.88 |
168.74 |
47.013 |
|
N2 |
133.42 |
110.59 |
98.620 |
136.12 |
119.69 |
15.694 |
|
|
N3 |
111.32 |
105.92 |
105.82 |
122.65 |
111.43 |
6.8508 |
|
The presence of heavy metal elements
in the soil is due to natural causes or human activities (Salem and Alwaleed,
2019), where the descending order of the elements was: Ni > Pb > Co >
Cu. In general, most of the concentration rates of Ni, Pb, and Cu ions were
exceeding the standard permissible limits for soils according to the WHO and
US-EPA, which was referred to by Ahmed (2019).
The concentration of heavy elements in the bottom sediments, depended on
many factors including: the amount of organic matter, the size of the sediment
particles, pH, electrical conductivity and ionic strength, as well as the
discharge of various wastewater into the valley. It is noted from Table (3) that
the relative high concentrations of heavy metals in the bottom sediments of the
valley is a result of the high concentration of organic matter in the sediments
that chelate with mineral ions, which facilitates their sedimentation (Ghrefat
and Yusuf, 2006). In addition to this, the reduction processes under anaerobic
conditions for some
|
Elements
|
Sites |
Winter |
Spring |
Summer |
Autumn
|
Mean |
±
Sd |
|
pb |
N1 |
43.362 |
69.226 |
56.994 |
63.994 |
58.394 |
9.7032 |
|
N2 |
77.959 |
132.82 |
67.893 |
91.536 |
92.508 |
24.718 |
|
|
N3 |
113.36 |
101.86 |
94.991 |
134.79 |
111.25 |
15.092 |
|
|
Cu |
N1 |
20.898 |
29.697 |
24.598 |
31.364 |
26.639 |
4.1473 |
|
N2 |
17.498 |
71.526 |
43.296 |
60.327 |
48.162 |
20.358 |
|
|
N3 |
26.597 |
29.830 |
45.895 |
12.665 |
28.747 |
11.816 |
|
|
Co |
N1 |
22.998 |
27.797 |
17.232 |
40.329 |
27.089 |
8.5102 |
|
N2 |
18.831 |
26.064 |
29.664 |
33.997 |
27.139 |
5.5584 |
|
|
N3 |
34.497 |
24.764 |
35.196 |
37.096 |
32.889 |
4.7859 |
|
|
Ni |
N1 |
176.02 |
281.14 |
190.98 |
230.44 |
219.65 |
40.690 |
|
N2 |
60.794 |
84.192 |
65.427 |
77.159 |
71.893 |
9.2735 |
|
|
N3 |
142.85 |
104.79 |
203.33 |
116.66 |
141.91 |
38.050 |
ions
that precipitate mineral elements, so that the seasonal average concentration of Pb, Cu, Co and Ni
ions in the valley deposits reaches (134.79, 71.526, 37.096 and 281.14) mg. kg1,
and for the annual rate, it reached
(111.25 ± 15.092, 48.162 ±20.358, 32.889 ±4.7859 and 219.65 ±40.69) mg.
kg-1 respectively. It is noted that most of the concentration rates
of lead, nickel and copper exceed the threshold effect levels (TEL) according
to (Rahman et al, 2017), as for the descending order of the annual rates for
the elements in the sediments as follows: Ni > Pb > Co > Cu. The presence of nickel, lead, copper and
cobalt elements in the soils and sediments may be due to their presence
naturally as a result of the weathering processes of the rocks, as well as human
activities such as atmospheric deposits, civil, agricultural and industrial
technical wastewater from car repair shops, repair of brakes and car tires,
electric storage batteries, Welding and paint shops, emissions
from burning fossil fuels and burning civil waste, especially plastics and
gasoline containing high concentrations of tetraethyl or methyl lead, which are
still used in Iraq to raise the octane number of fuel and prevent cracking in
vehicle engines (Bakan and Ozkoc, 2007; Yahya et al, 2012; Salem and Alwalayed,
2019; Islam, 2021).
Pollution Load Index (PLI)
The importance of the
Pollution Load Index (PLI) comes to
know the extent of contamination with heavy metals in soils and sediments to
take the essential actions to reduce their pollution and preserve the
environment from deterioration (Abou Elnwar et al, 2018; Kormoker et al, 2019;
Perumal et al, 2021). The results of the heavy metal pollution load index (PLI)
values Table (4) indicate the fluctuation of values in agricultural soils
between (0.617 to 1.418), where 42% of the soil samples irrigated from the
valley water were contaminated with heavy metals, because the PLI values are
greater than 1.0 (Perumal et al, 2021) due to the relative high concentration
of the studied metal elements, especially lead and nickel, which exceeded the
baseline. As for the valley sediments, the studied samples were between
polluted to non-polluted sediments. The
values of the metal pollution load index (PLI) ranged between (1.305 to 0.617)
Table (4), where 50% of the sediments were polluted to exceed the safe limits,
while the rest were uncontaminated.
Table (4): Results of the values and status of the pollution loads
index (PLI) of heavy metal in soil and sediments in the Duhok valley region.
|
Sites |
Winter |
Spring |
Summer |
Autumn |
Annual rate |
||||||
|
Value |
Status |
Value |
Status |
Value |
Status |
Value |
Status |
Value |
Status |
||
|
Soil |
N 1 |
1.071 |
P. E. |
1.012 |
P. E. |
1.153 |
P. E. |
0.817 |
N. P. |
1.015 |
P. E. |
|
N 2 |
1.123 |
P. E. |
0.749 |
N. P. |
0.964 |
N. P. |
0.990 |
N. P. |
0.957 |
N. P. |
|
|
N 3 |
1.418 |
P. E. |
0.617 |
N. P. |
0.894 |
N. P. |
0.830 |
N. P. |
0.934 |
N. P. |
|
|
Sediment |
N 1 |
0.764 |
N. P. |
1.106 |
P. E. |
0.809 |
N. P. |
1.148 |
P. E. |
0.957 |
N. P. |
|
N 2 |
0.617 |
N. P. |
1.180 |
P. E. |
0.853 |
N. P. |
1.077 |
P. E. |
0.932 |
N. P. |
|
|
N 3 |
1.084 |
P. E. |
0.925 |
N. P. |
1.305 |
P. E. |
0.910 |
N. P. |
1.056 |
P. E. |
|
P. E.:
Pollution Exist, N. P.: No Pollution
Generally, 33% of the
annual rate of soil and sediment samples are considered polluted. This rise in
pollution loads index values in agricultural soils and sediments may be due to
the relative high concentrations of lead and nickel elements compared to the
rest of the studied heavy metals, as it was characterized by high values of
contamination factor (CF) in the soil and due to the impact of human activities
such as the discharge of civil, agricultural and industrial waste into the
valley (Mekky et al, 2019).
Nemerow pollution index (PIN)
The Nemerow Pollution Index (PIN) is used for the environmental
assessment of the quality of soil and bottom sediments on a global scale to
know the levels of total pollution resulting from the continuous presence of a
group of heavy metals instead of pollution resulting from a single mineral
element (Yang et al, 2014; Hu et al, 2013).Table (5) summarize the values and
condition of the soil and the studied sediments for the Nemerow index of heavy
metals pollution (Pb, Cu, Co and Ni), where
the quality of the studied agricultural soil was between slight pollution to
severe pollution, the PIN values
fluctuated between (1.47 to 3.42). This deterioration in soil quality is
caused by the high concentrations of lead and nickel ions, which was negatively
reflected in the high PI values of lead and nickel concentrations to reach
(1.84 and 3.67) respectively, where 58%
|
Season Sites |
Winter |
Spring |
Summer |
Autumn |
|
|||||
|
Value |
Status |
Value |
Status |
Value |
Status |
Value |
Status |
|
||
|
Soil |
N 1 |
2.85 |
Se.
P. |
2.29 |
Se.
P |
3.07 |
H.P. |
3.42 |
H.P. |
|
|
N 2 |
2.67 |
Se.
P. |
2.20 |
Se.
P |
1.47 |
Sl. P. |
1.84 |
Sl.P. |
|
|
|
N 3 |
2.77 |
Se
.P. |
2.16 |
Se.
P |
3.29 |
H.P. |
2.47 |
Se. P. |
|
|
|
Sediment |
N 1 |
2.93 |
Se.
P. |
3.72 |
H.P. |
3.07 |
H.P. |
3.42 |
H.P. |
|
|
N 2 |
1.48 |
Sl.P. |
2.42 |
Se.
P |
1.47 |
Sl.P. |
1.84 |
Sl.P. |
|
|
|
N 3 |
2.75 |
Se. P. |
2.24 |
Se.
P |
3.29 |
H.P. |
2.47 |
Se. P |
|
|
|
Se.
P.; Severely Polluted, Sl.P.:
Slightly Pollution., H.P.: Heavy Pollution |
||||||||||
of the samples were severely polluted and 25% were heavy polluted and the rest were
slightly polluted. As for bottom sediments, their quality was between slight pollution
to heavy pollution, with PIN values ranging between (3.72 to 1.47), where
33.33% of the sediment samples were Heavy Pollution, 41.67% Severely Pollution
and the rest were Slightly Pollution. This deterioration in quality is due to
the high concentrations of lead and cobalt in the sediments, which was
reflected in the high PI values and the negative impact on the quality of the
sediments.
Geo-accumulation Index (Igeo)
The
results of the assessment of the pollution of agricultural soil irrigated from
the waters of Duhok valley according to the calculation of the Igeo values, Table
(6) indicates that the values for lead, copper, cobalt and nickel for the three
sites studied
|
Table (6): Seasonal results of (Igeo) values and status
of soils for different sites in the studied area. |
|||||||||
|
Elem. |
Seas. Sites |
Winter |
Spring |
Summer |
Autumn |
||||
|
Value |
Status |
Value |
Status |
Value |
Status |
Value |
Status |
||
|
Pb |
N1 N2 N3 |
0.316 0.497 0.587 |
Weakly polluted Weakly polluted Weakly polluted |
0.462 0.168 0.248 |
Weakly polluted Weakly polluted Weakly polluted |
0.404 0.428 0.399 |
Weakly polluted Weakly polluted Weakly polluted |
0.135 0.381 0.231 |
Weakly polluted Weakly polluted Weakly polluted |
|
Cu |
N1 N2 N3 |
0.079 0.064 0.087 |
Weakly polluted Weakly polluted Weakly polluted |
0.079 0.076 0.031 |
Weakly polluted Weakly polluted Weakly polluted |
0.058 0.058 0.053 |
Weakly polluted Weakly polluted Weakly polluted |
0.051 0.056 0.071 |
Weakly polluted Weakly polluted Weakly polluted |
|
Co |
N1 N2 N3 |
0.124 0.139 0.265 |
Weakly polluted Weakly polluted Weakly polluted |
0.114 0.082 0.067 |
Weakly polluted Weakly polluted Weakly polluted |
0.137 0.132 0.106 |
Weakly polluted Weakly polluted Weakly polluted |
0.111 0.124 0.088 |
Weakly polluted Weakly polluted Weakly polluted |
|
Ni |
N1 N2 N3 |
0.684 0.582 0.486 |
Weakly polluted Weakly polluted Weakly polluted |
0.423 0.482 0.462 |
Weakly polluted Weakly polluted Weakly polluted |
0.895 0.430 0.462 |
Weakly polluted Weakly polluted Weakly polluted |
0.942 0.594 0.535 |
Weakly polluted Weakly polluted Weakly polluted |
|
|
|||||||||
throughout the study
period were weakly polluted, where the values fluctuated between (0.135 to
0.587), (0.031 to 0.087, (0.067 to 0.265) and (0.423 to 0.942) respectively.
The same applies to the
Igeo values Table (7) for the bottom sediments of the valley and for all the
studied sites during the seasons of the year were weakly contaminated with the
exception of nickel at site N1 due to the deterioration of the quality of the
sediments relatively to medium pollution during the spring and autumn seasons
to reach the value of the index to (1.226 and 1.005), respectively. It is also
noted from the table that the seasonal rates of values for nickel increased
compared to the rest of the heavy metals studied, bringing the annual average
values for (Igeo, Ni) five times the
annual average values of (Igeo, Co)
and eight times the values for (Igeo.
Cu). This relative rise in the values is
due to the high concentrations of heavy elements in the sediments, and in
general, the rates of values for soils and sediments are consistent with the
studied index’s, so that the ascending order of the rates is as follows: Igeo
(Ni) > Igeo (Pb) > Igeo (Co) > Igeo (Cu).
|
Table (7):
Seasonal results of (Igeo) values and status of sediments for
different sites in the studied area. |
||||||||||
|
Elem. |
Seas. Sites |
Winter |
Spring |
Summer |
Autumn |
|
||||
|
Value |
Status |
Value |
Status |
Value |
Status |
Value |
Status |
|
||
|
Pb |
N1 N2 N3 |
0.164 0.295 0.429 |
W. Poll. W. Poll. W. Poll. |
0.262 0.503 0.386 |
W. Poll. W. Poll. W. Poll. |
0.216 0.257 0.360 |
W. Poll. W. Poll. W. Poll. |
0.242 0.346 0.510 |
W. Poll. W. Poll. W. Poll. |
|
|
Cu |
N1 N2 N3 |
0.047 0.039 0.059 |
W. Poll. W. Poll. W. Poll. |
0.066 0.159 0.067 |
W. Poll. W. Poll. W. Poll. |
0.055 0.097 0.102 |
W. Poll. W. Poll. W. Poll. |
0.070 0.135 0.028 |
W. Poll. W. Poll. W. Poll. |
|
|
Co |
N1 N2 N3 |
0.094 0.077 0.141 |
W. Poll. W. Poll. W. Poll. |
0.114 0.107 0.101 |
W. Poll. W. Poll. W. Poll. |
0.071 0.121 0.144 |
W. Poll. W. Poll. W. Poll. |
0.165 0.139 0.152 |
W. Poll. W. Poll. W. Poll. |
|
|
Ni |
N1 N2 N3 |
0.768 0.265 0.623 |
W. Poll. W. Poll. W. Poll. |
1.226 0.367 0.457 |
M. Poll. W. Poll. W. Poll. |
0.833 0.285 0.887 |
W. Poll. W. Poll. W. Poll. |
1.005 0.337 0.509 |
M. Poll. W. Poll. W. Poll. |
|
|
W. Poll.:
Weakly polluted., M. Poll.:
Moderately polluted |
||||||||||
Potential Ecological Risk index
(PERI)
The Potential Ecological Risk Index
(PERI) is one of the necessary indicators to monitor the degree of the risk of
heavy metal contamination of soils and bottom sediments (Wuana et al, 2020).
Table (8) indicates an increase in the PERI values, where the quality of the
studied soils and sediments were between slight ecological risk to medium ecological
risk, and the values ranged between (26.207 to 59.481) and (23.871 to 51,952) respectively. This relative
deterioration in the quality of soils and sediments is due to the relative high
values of ecological risk factor (ERf) for lead, cobalt and nickel to reach
(14.637, 15.926, and 17.046) and (12.716, 17.413 and 30.559) respectively.
|
Results Site |
Season |
Ecological
Risk factors (ERf) |
PERI |
Status |
||||
|
Pb |
Cu |
CO |
Ni |
|||||
|
Soil |
N
1 |
Winter Spring Summer Autumn |
7.879 11.521 10.075 3.374 |
2.176 2.153 1.580 1.395 |
14.251 13.063 15.753 12.767 |
17.046 10.546 22.310 23.465 |
41.351 37.282 49.717 41.001 |
M. Eco. Risk M. Eco. Risk M. Eco. Risk M. Eco. Risk |
|
N
2 |
Winter Spring Summer Autumn |
12.392 4.189 10.666 9.499 |
1.760 2.090 1.586 1.522 |
15.926 9.435 15.081 14.222 |
14.502 12.021 10.720 14.796 |
44.580 27.734 38.053 40.039 |
M. Eco. Risk S. Eco. Risk M. Eco. Risk M. Eco. Risk |
|
|
N
3 |
Winter Spring Summer Autumn |
14.637 6.169 9.949 5.758 |
2.379 0.842 1.456 1.945 |
30.365 7.684 12.124 10.073 |
12.100 11.513 11.502 13.332 |
59.481 26.207 35.032 31.107 |
M. Eco. Risk S. Eco. Risk M. Eco. Risk M. Eco. Risk |
|
|
Sediment |
N
1 |
Winter Spring Summer Autumn |
4.091 6.531 5.377 6.037 |
1.277 1.815 1.503 1.917 |
10.795 13.048 8.088 18.930 |
19.132 30.559 20.759 25.048 |
35.295 51.952 35.727 51.932 |
M. Eco. Risk M. Eco. Risk M. Eco. Risk M. Eco. Risk |
|
N
2 |
Winter Spring Summer Autumn |
7.355 12.530 6.405 8.619 |
1.069 4.371 2.646 3.687 |
8.839 12.234 13.924 15.958 |
6.608 9.151 7.112 8.387 |
23.871 38.287 30.086 36.650 |
S. Eco. Risk |
|
|
M. Eco. Risk |
||||||||
|
M. Eco. Risk |
||||||||
|
M. Eco. Risk |
||||||||
|
N
3 |
Winter Spring Summer Autumn |
10.694 9.609 8.961 12.716 |
1.625 1.823 2.805 0.774 |
16.192 11.624 16.521 17.413 |
15.527 11.390 22.103 12.680 |
44.039 34.446 50.390 43.582 |
M. Eco. Risk M. Eco. Risk M. Eco. Risk M. Eco. Risk |
|
|
S. Eco. Risk: Slight Ecological Risk, class A., M. Eco. Risk: Medium Ecological Risk,
class B. |
||||||||
It is noted that the results of (ERI) values agree with the
results of (PLI) and (PLN) ones. In general, the descending order of Erf rates
for soils and sediments is as follows:
Erf(Ni)
> Erf(Co) > Erf(Pb) > Erf(Cu).
Finally, the movement of
heavy metals, whether in soil and sediment into the soil solution or aquatic
environment, is affected by pH values. The occurrence of decomposition
processes of organic matter leads to the production of organic acids and in
anaerobic conditions leads to the formation of hydrogen sulfide, which oxidizes
when exposed to dissolved oxygen to sulfuric acid. In these cases, heavy metals
is released into the aquatic environment, causing
damage to the aquatic ecosystem through their entry and accumulation in
microorganisms and then their transfer to crustaceans, fish, etc. The Biomagnification of these metals may
occur in aquatic organisms. Hence, the impact on the human being, the final
consumer of the food chain (Al-Saffawi, 2018).
The study recommended
periodic follow-up of the concentration of pollutants and heavy metals in
agricultural soils and bottom sediments to reduce pollution problems.
1.
The current study
indicated that most of the concentrations of Ni, Pb, and Cu ions were exceeding
the permissible standard limits for soil and sedimentation according to WHO.
2.
42% of the soil samples
and 50% of the sediment samples are considered polluted according to the PLI
values, while the percentage was 50% and 41.7%, respectively, of medium ecological
risk (Class B) according to potential ecological risk index.
The results of Nemerow
pollution index (PIN) values indicated that 58% of the soil samples were severely
polluted and 25% of them were heavy polluted, while 41.7% of the sediment
samples were severely polluted and 33.33% were heavy polluted. Finally, most of
the studied soil and sediment samples according to the concentrations of lead,
copper, cobalt and nickel were from the weakly polluted class according to the
Igeo index.
Therefore,
the study recommends periodic follow-up of the concentrations of heavy metals
in the region, while activating environmental laws to prevent violators by
dumping wastewater contaminated with toxic metal compounds and treating it before
dumping it into the valley.
Abdo, M. H. (2004). Distribution of some chemical elements in the
recent sediments of Damietta branch, River Nile, Egypt. Journal of the Egyptian
Academic Society of Environmental Development. (D. Environmental Studies),
5(2), 125-146.
Ahmed, N.B. (2019). Impact of using Aldanfeeli valley water on the
pollution of soil with in heavy metal. Tikrit J. for Agricultural Sci. 19(2):
8-18. http://tujas.tu.edu.iq
Al-Khashman,
O. A. (2012). Assessment of heavy metal accumulation in urban soil around
potash industrial site in the east of the dead sea and their environmental
risks. Soil and Sediment Contamination. 21(2),
276–290. DOI: 10.1080/15320383.2011.609358
Al-Saffawi, A.A.Y.T., Al-Barwarri, M.R.A. and Khidr, N.K. (2009).
Physical, chemical and biological characteristic of Duhok valley water Tikrit
Journal of Pure Sciences. 4(3): 1-7.
Al-Saffawi, A.Y.T. (2018). Application of CCME WQI to assessment
the environmental status of Tigris river water for aquatic life within Nineveh
governorate, north Iraq. Alutroha for Environmental Sci. (5): 13-26. www.alutroha.com
APHA, AWWA and WCPE (1998). "Stand Method for Examination of
water and wastewater American public Health Association, 20th ed., Washington
DC, USA.
APHA, AWWA and WCPE (2017). "Stand Method for Examination of
water and wastewater American public Health Association, 23RD ed., Washington
DC, USA. https://doi.org/10.2105/SMWW.2882.216
Bakan, G, Ozkoc, H.B. (2007). An ecological risk assessment of the
impact of heavy metals in surfaces sediments on biota from the mid- Black sea
coast of Turkey. Int. J. Environ. Stud. 64(1):45-57. https://doi.org/10.1080/00207230601125069
Balakrishnan, T., Sundaramanickam, A., Shekhar, S. and
Balasubramanian, T. (2015). Distribution and seasonal variation of heavy metals
in sediments of Muthupet lagoon, southeast of India. Journal of Ecological
Engineering.16(3): 49–60. DOI:
10.12911/22998993/2805
Bhuiyan,
K.A., Qureshi, S., Billah, M.M., Kammella, S.V., Alam, R., Ray, S., Monwar, M.
and Abu Hena M. K. (2018). Distribution of Trace Metals in Channel Sediment: a Case Study in South Atlantic Coast of Spain. Water Air
Soil Pollut. 229:14-30. https://doi.org/10.1007/s11270-017-3653-5
Billah, M.M., Kamal, A.M., Idris, M.H. and Ismail, J. (2017).
Mangrove Macroalgae as Biomonitors of Heavy Metal Contamination in a Tropical
Estuary, Malaysia. Water Air Soil Pollution.
228: 347-361. DOI
10.1007/s11270-017-3500-8
Biswas, P.K., Uddin, N., Alam, S., Us-Sakib, T., Sultana, S. and
Ahmed, T. (2017). Evaluation of Heavy Metal Pollution Indices in Irrigation and
Drinking Water Systems of Barapukuria Coal Mine Area, Bangladesh. American
Journal of Water Resources. 5(5): 146-151. DOI:10.12691/ajwr-5-5-2
Chandrasekaran, A., Mukesh, M.V., Chidambaram, S.,
Singarasubramanian, S.R., Rajendran, S., Muthukumarasamy, R. and Tamilselvi, M.
(2014). Assessment of heavy metal distribution pattern in the sediments of
Tamirabarani river and estuary, east coast of Tamil Nadu, India. Environ Earth
Sci.
DOI 10.1007/s12665-014-3593-y
Chen, H., An, J., Wei, S. and Gu, J. (2015). Spatial Patterns and
Risk Assessment of Heavy Metals in Soils in a Resource- Exhausted City,
Northeast China. PLOS ONE. 1-13. DOI:10.1371/journal.pone.0137694
El-Saadani, Z., Mingqi, W., He, Z., Hamukwaya, S, L., Abdel Wahed,
M.S.M. and Abu Khatita, A. (2022).
Environmental Geochemistry and Fractionation of Cadmium Metal in Surficial
Bottom Sediments and Water of the Nile River, Egypt. Toxics. 10: 221.-240. https://doi.org/10.3390/toxics10050221
El-Sorogy AS, Abdelwahab M, Nour H (2012) Heavy metals
contamination of the Quaternary coral reefs, Red Sea coast, Egypt. Environ
Earth Sci 67:777–785.
DOI 10.1007/s12665-012-1535-0
El-Sorogy, A.S., Tawfik, M., Almadani, S.A. and Attiah, A. (2016).
Assessment of toxic metals in coastal sediments of the Rosetta area,
Mediterranean Sea, Egypt. Environ Earth Sci.
75:398-409. DOI
10.1007/s12665-015-4985-3
Ghrefat H, Yusuf N (2006) Assessing Mn, Fe, Cu, Zn and Cd
pollution in bottom sediments of Wadi Al-Arab Dam, Jordan. Chemosphere
65:2114–2121
Hammash, S.M. and Abed, M.F. (2022). Environmental Evaluation of
the Surface Water, Ground Water and Wastewater using Pollution Indices at the
Landfill Site, Southern Baiji, Salah Al-Din, Northern Iraq. Iraqi Geological J.
55(1B): 105-112. DOI:
10.46717/igj.55.1B.10Ms-2022-02-26
Hassan, N.E. and Al-barware, M.R.A. (2016). Assessment of
Wastewater in Duhok Valley, Kurdistan Region/Iraq. Advances in Sci., Techn. and Engin. Systems
J. 1(3): 7-13. www.astesj.com
Hu,
Y., Liu, X., Bai, J., Shih, K., Zeng, E.Y. and Cheng, H. (2013). Assessing
heavy metal pollution in the surface soils of a region that had undergone three
decades of intense industrialization and urbanization. Environ Sci Pollut Res
(2013) 20:6150– 6159. DOI
10.1007/s11356-013-1668-z
Islam, M.S. (2021). Preliminary assessment of trace elements in
surface and deep waters of an urban river (Korotoa) in Bangladesh and
associated health risk. Environmental science and pollution research
international. doi:10.1007/s11356-021-12541-5
Izah, S.C., Bassey, S.E. and Ohimain, E.I. (2018). Ecological risk
assessment of heavy metals in Cassava mill effluents contaminated soil in rural
community in the Niger delta region of Nigeria. Molecular Soil Biology. 9:
1-11.
Jaishankar, M., Tseten, T., Anbalagan, N., Mathew, B.B. and
Beeregowda, K.N. (2014). Toxicity, Mechanism and Health Effects of Some Heavy
Metals. Interdisciplinary
Toxicology.
60-72. https://doi.org/10.2478/intox-2014-0009
Kaur, J., Bhat, S.A., Singh, N., Bhatti, S.S., Kaur, V. and Katnoria,
G.K. (2022). Assessment of the heavy
metal contamination of roadside soil alongside Buddha Nullal, Ladhiana, Pangab.
India. Int. J. Enveron. Public Health. 9: 1596-1620. https://doi.org/10.3390/ijerph19031596
Kormoker, T., Proshad, R. and Islam, M.S. (2019). Ecological risk
assessment of heavy metals in sediment of the Louhajang river, Bangladesh. SF
Journal of Environmental and Earth Science. https://scienceforecastoa.com/
Kouakoui, A.R., Kouassi, N.L.B., Koukouassi, E.K., Trokourey, A.,
Yao, B.K. and Adouby, K. (2021). Lead
concentrations in sediments and mollusc gastropod from
Vridi Canal, Côte d’Ivoire.
Int. J. Biol. Chem. Sci. (IJBCS).
15(1): 293-305. DOI: https://dx.doi.org/10.4314/ijbcs.v15i1.26
Kouassi, N.G.L., Yao, K.M., Trokourey, A. and Soro, M.B. (2015).
Distribution, sources, and possible adverse biological effects of trace metals
in surface sediments of a tropical estuary. Environmental Forensics, 16:96–108.
DOI: 10.1080/15275922.2014.991433
Manea, M.H., Al-Tawash1, B.S. Al-Saady, Y.I. (2019). Environmental
Geochemical Assessment of Heavy Metals in Soil and Sediment of (Shatt-Al-Hilla)
Babil Governorate, Central Iraq. Iraqi Journal of Science. 60(5): 1055-1068. DOI: 10.24996/ijs.2019.60.5.15.
Mekky, H.S., Abou El-Anwar, E.A., Salman, S.A., Elnazer, A.A.,
Abdel Wahab., W., Asmoay, A.S. (2019). Evaluation of heavy metals pollution by
using pollution indices in the soil of Assiut District, Egypt. Egyptian Journal
of Chemistry, DOI: https:// doi.org/10.21608/EJCHEM.2019.9720.1654.
Mohammed, N.I. and Bamarni, K.A. (2019). Water quality monitoring of Duhok Dam
(Kurdistan Region of Iraq), ZANCO J. of Pure and applied Sci. (. ZJPAS). 31(1):
07-16. http://dx.doi.org/10.21271/ZJPAS.31.1.2
Najamuddin, Prartono, T., Sanusi, H.S. and Nurjaya, I.W. (2016).
Seasonal distribution and geochemical fractionation of heavy metals from
surface sediment in a tropical estuary of Jeneberang River, Indonesia. Marine
Pollution Bulletin. 111: 456–462.http://dx.doi.org/10.1016/j.marpolbul.2016.06.106
Pereira, W.V.D., Ramos, S.J., Melo, L.C.A., Braz, A.M.D; Dias,
Y.N., de Almeida, G.V.; Fernandes, A.R. (2022). Levels and environmental risks
of rare earth elements in a gold mining area in the Amazon. Environ. Res. 211:
113090. DOI: 10.1016/j.envres.2022.113090
Perumal, K., Antony, J. and Muthuramalingam, S. (2021). Heavy
metal pollutants and their spatial distribution in surface sediments from
Thondi coast, Palk Bay, South India. Environ Sci Eur. 33:63-83. https://doi.org/10.1186/s12302-021-00501-2
Qaseem, N., Al-Saffawi, A.Y. and Khalid, M. (2022a). Qualitative
assessment of water resources for watering livestock and poultry: A case study
of the waters of Duhok valley, Kurdistan region of Iraq. Oriental J. of Chemistry.
38(4): 990-997. http://dx.doi.org/10.13005/ojc/380421
Qaseem, N., Al-Saffawi, A.Y. and Khalid, M. (2022b). Assessment
the Environmental Reality of Duhok Valley Water on the Water Quality of Mosul
Dam Lake by Using
Water Quality Index (WQI).Egyptian J. of
Chemistry. 3(4): 32-43. http://dx.doi.org/10.21608EJCHEM.2022.133799.5897
Qaseem,
N., Al-Saffawi, A.Y. and Khalid, M. (2022c). Water Quality Assessment Using the
Pollution Index Model (Pij) For Irrigation Purposes. A Case Study: Duhok Valley
Water in Northern IRAQ. International J. of Applied Science and Engineering
Review. 3(4): 32-43. http://dx.doi.org/10.52267/IJASER.2022.3404
Ragi,
A. S., Leena, P. P., Cheriyan, E., & Nair, S. M. (2017). Heavy metal
concentrations in some gastropods and bivalves collected from the fishing zone
of South India. Marine Pollution Bulletin, 118, 452-458. DOI:10.1016/j.marpolbul.2017.03.029
Rahman, M.M., Islam, M.A., Bodrud-Doza, M., Muhib, M.I., Zahid,
A., Shammi, M., Tareq, S.M. and Kurasaki, M, (2017). Spatio-Temporal Assessment
of groundwater quality and human health risk: A case study in Gopalganj,
Bangladesh. Expo Health. DOI
10.1007/s12403-017-0253-y
Rakib, M.R.J., Jolly, Y.N., Begum, B.A., Choudhury, T.R., Fatema,
K.J., Islam, M.S., Ali, M. and Idris, A.M. (2021). Assessment of trace element
toxicity in surface water of a fish breeding river in Bangladesh: a novel
approach for ecological and health risk evaluation. Toxin Reviews. https://doi.org/10.1080/15569543.2021.1891936
Salem, M.A. and Alwalayed, S.M. (2019). Assessment of
physiochemical properties and concentration of some heavy metals at different
seasons in agricultural soils fertilized with phosphate and urea for long-time
at BRCK agricultural project. Libya. A
special issue of the 3th annual conference on theories and
applications. September 7, 2019, Basic and Biological Sciences. Misurata
University. Libya. 259-274.
Samy, Y. M. and El-Bady, M. S. M. (2014). Comparative study of the
mineralogy and geochemistry of the Burullus and Bardawil lake sediments,
Mediterranean Sea Coast, Egypt. Life Science Journal. 11(9): 686-700.
Suresh,
G., Ramasamy, V., Sundarrajan, M., & Paramasivam, K. (2015). Spatial and
vertical distributions of heavy metals and their potential toxicity levels in
various beach sediments from high-background-radiation area, Kerala, India.
Marine Pollution Bulletin, 91(1), 389–400.
DOI:10.1016/j.marpolbul.2014.11.007
Vetrimurugan,
E., Shruti, V.C., Jonathan, M.P., Roy, P.D., Kunene, N.W. and Villegas, L. E.C.
(2017). Metal concentration in the tourist beaches of South Durban: an
industrial hub of South Africa. Marine Pollution Bulletin, 117(1), 538–546.DOI:10.1016/j.marpolbul.2017.02.036
Wuana, R., Ogbodo, C., Itodo, A.U. and Eneji, I.S. (2020).
Ecological and Human Health Risk Assessment of Toxic Metals in Water, Sediment
and Fish from Lower Usuma Dam, Abuja, Nigeria. J. of Geoscience and Environ.
Protection. 8: 82-106. https://doi.org/10.4236/gep.2020.85006
Xu,
F., Qiu, L., Cao, Y., Huang, J., Liu, Z., Tian, X., et al. (2016a). Trace
metals in the surface sediments of the intertidal Jiaozhou Bay, China: sources
and contamination assessment. Marine Pollution Bulletin, 104(1), 371–378. DOI:10.1016/j.marpolbul.2016.01.019
Yahaya, M.I., Jacob, A.G., Agbendeh, Z.M., Akpan, G.P. and Kwasara,
A.A. (2012). Seasonal potential toxic
metals contents of Yauri river bottom sediments: North western Nigeria. Journal
of Environmental Chemistry and Ecotoxicology (JECE). 4(12): 212-221. DOI: 10.5897/JECE11.080
Yang, L., Huang, B., Hu, W., Chen, Y., Mao, M. and Yao, L. (2014).
The impact of greenhouse vegetable farming duration and soil types on
phytoavailability of heavy metals and their health risk in eastern China.
Chemosphere. 103: 121–130. doi:
10.1016/j.chemosphere.2013.11.047
Zhang, Q., Ren, F., Xiong, X., Gao, H., Wang, Y., Sun, W., Leng,
P., Li, Z. and Bai, Y. (2021). Spatial distribution and contamination
assessment of heavy metal pollution of sediments in coastal reclamation areas:
a case study in Shenzhen Bay, China. Environ. Sci. Europe. 33:90 – 101. https://doi.org/10.1186/s12302-021-00532-9
This is an open access under a CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/)