https://research.e-greenation.org/GIJES,

Vol. 3, No. 2, June - August 2025

DOI: https://doi.org/10.38035/gijes.v3i2
https://creativecommons.org/licenses/by/4.0/

Optimum Value for Zinc Removal from Saponin-Based Soil
Washing Across soils at Onyeama Dumpsite, Enugu State
Alexander Chidiebere Okoro1, Louis Chukwuemeka Orakwe2, Chike Pius
Nwachukwu3, Ella Ifeanyi Ugwu4, Elijah Chibuzo Ugwu5, Kenneth Eze6, Chukwuemeka
Obumneme Umobi7
1

Nnamdi Azikiwe University, Awka, Anambra State, Nigeria, merciescds@yahoo.com
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria, lc.orakwe@unizik.edu.ng
3
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria, cp.nwachukwu@unizik.edu.ng
4
University of Nigeria, Nsukka, Enugu State, Nigeria, ella.ugwu@unn.edu.ng
5
Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria,
ugwu.elijah@mouau.edu.ng
6
Enugu State University of Science and Technology, Enugu State, Nigeria, kennetheze@gmail.com
7
Nnamdi Azikiwe University, Awka, Anambra State, Nigeria, co.umobi@unizik.edu.ng
2

Corresponding Author: merciescds@yahoo.com1

Abstract: High reduction in the size of available land for agriculture has been a major
problem facing most farmers today. The adoption of available plant based surfactants is yet to
gain attention in south eastern Nigeria. This study was conducted to ascertain the level of
Zinc removal from heavy metal contaminated dumpsites. Soil samples (C1, C2 and C3) were
collected from the dumpsite and taken to the laboratory for analytical procedure. Saponin was
also extracted from siam weed to aid the process of batch experiment for the removal of Zinc
from contaminated soil. The result of the study showed that the optimum value for Zinc
removal with saponin for soils C1, C2 and C3 were 96%, 99% and 100% respectively. It is
recommended that saponin from Siam weed be adopted for the removal of Zinc from
contaminated soil.
Keyword: Remediation, Surfactant, Heavy metal, Batch experiment and Saponin

INTRODUCTION
In recent decades, anthropogenic activities like mining, smelting, electroplating, and
wastewater irrigating have contributed to heavy-metal pollution of water and soils, which has
become a major environmental concern worldwide (Jez and Lestan, 2016; Wang et al., 2020;
Zhang et al., 2021a; Zhang et al., 2021b). Over five million locations, encompassing 20
million hectares of land, have soils tainted by different heavy metals worldwide (Liu et al.,
2018; He et al., 2015). Heavy metal pollution of soil presents significant environmental risks
since the metals are not biodegradable, can build up in living things, and can have long-term

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negative impacts on human health. Remediation of heavy metal-contaminated soils and
preservation of soil environmental integrity are therefore urgently needed.
Many urban and industrial cities of developing countries still using landfills system to
accommodate their waste and due to the various socio-economic activities, wastes are
generated in tons. Landfills system is most adopted due to its capacity to accommodate great
amount of waste over a long period of time using simple disposal method such as burning
and/or decomposition. Notwithstanding these benefits, landfills are regarded as major
reservoir for organic compounds and heavy metals in the environment (Vongdala et al.,
2019). Hence, inefficient management of landfills waste has cause serious environmental and
human impact, which has influence on the long term achievement of sustainable development
(Ferronato and Torretta, 2019).
Many remediation methods have been proposed to remove heavy metals from polluted
soils. These methods are based on physical, chemical, and even biological processes.
Although some nutrients may be lost and secondary contamination may result, soil washing is
regarded as an efficient method that may permanently remove heavy metals from soil with
high remediation efficiency (Wei et al., 2016; Feng et al., 2020a). The most contaminated soil
particles are separated by physical means in soil washing, and the heavy metals are then
extracted chemically using certain washing chemicals to move them from the soil to solution
(Saponaro et al., 2002; Dermont et al., 2008). The extraction reagents and the efficacy of soil
washing in remediation are strongly connected. Numerous studies conducted in US
Superfund programs have demonstrated that improper washing reagent selection can result in
unsuccessful washing remediation (USEPA, 2004; 2005). Therefore, one of the hot topics in
washing remediation is the study of washing reagents.
In an attempt to address soil contamination issues at waste dump sites, it is important to
assess a suitable surfactant that is a plant-based metal remover with low toxicity, high
removal efficiency and manageable destruction of soil characteristics. Besides, making a
choice of the right plant based surfactant that is adapted to south eastern Nigeria is of
paramount importance. This paper is therefore targeted at ascertaining the optimum value for
zinc removal from saponin-based soil washing across soils at Onyeama dumpsite, Enugu
State
METHOD
1. Study Area Description
This research location is located at the Onyeama dumpsite in Ngwo, Udi Local
Government Area of Enugu State (figure 2.1). It is situated in the heart of a Nigerian coalfield
and in the state of Enugu. The city is home to gas work stations, a cement industry, and a
steel rolling mill. The city lies between 6°21IN and 7°261E in southeast Nigeria. The city is
located in a tropical rain forest zone with derived savannah, and its population was 722,664
according to the most recent National Population Census (2006) (Sanni, 2007). The humid
climate
of
Enugu
State
peaks
between
March
and
November
(https://en.wikipedia.org/wiki/Enugu). According to Sani (2007), Enugu State experiences an
average daily temperature of 26.7°C (80.1°F).

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Figure I. A pictorial representation of Onyeama Waste Dumpsite

2. Soil Sample Collection Method
Sampling of soil was taken randomly using soil core samplers from Onyeama dumpsite
in Enugu State. The sampling areas at Onyeama dumpsite were divided into three major
collection points, each of the major collection points had Three (3) soil samples were taken
from it, which gave a total of nine (9) soil samples. The sampling was done at 30cm depth
and 10meters away from each other. Three soil samples -soil 1(C1), soil; 2 (C2) and soil 3
(C3) with the highest contamination level, each from the major collection points were chosen
for remediation (Figure 2.2) after physiochemical analysis. After the three samples were
brought to the laboratory, the analytical process commenced instantly. The coordinates of the
sampling points for the selected soil for remediation were also taken with a Global
Positioning System (GPS) (Table 2.1). Three (3) soil samples were gathered in total for
analysis as was experimentally designed. The soil samples collection targeted the top soil of
the dumpsite at thirty centimeter (30cm) depth using soil auger from where a composite
sample was collected.

Figure 2. Enugu State's map displaying the soil sample collection
points at Onyeama Waste Dumpsite

3. The total quantity of metals in the soil
EPA method 3050B was employed in order to calculate the soil's overall metal content
(USEPA, 1996). This approach provides ecologically accessible metals rather than complete
digestion. The samples were digested by heating using a fume hood and a hotplate containing

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10 milliliters of nitric acid and a representative sample of 1 gram dry weight, then refluxing
the mixture for 15 minutes at 950C ± 50C (heating a solution to its boiling point and
condensing the vapour back into the solution). After that, the samples were digested by
repeatedly adding 5 milliliters of strong nitric acid until there was no more reaction with the
nitric acid. The conclusion of nitric acid digestion is indicated by the absence of dark vapors
from the solution. After that, 30% hydrogen peroxide was used to digest the material. Until
the sample's appearance remained constant, hydrogen peroxide (1 ml each) was added
repeatedly. Lastly, the material was digested for 15 minutes using 10 milliliters of strong
hydrochloric acid. Following their digestion, the samples were filled with 100 milliliters of
distilled water after being collected in a 100 milliliter volumetric flask and filtered through
Whatman No. 40 filter paper. Atomic Absorption (AA) Spectrometry was used to produce
and analyze the filtered sample at the appropriate dilutions (USEPA, 1996). To ensure safety,
soil sample digestion was carried out in triplicate under a hood.
4. Surfactants Extraction
The plant based surfactant was extracted from Siam weed leaves (Figure 2.3) at the
Project Development Institute (PRODA) labouratory in Emene Enugu State. Different
species and even different portions of the same plant have varying saponin extract
concentrations and compositions. Maceration method was adopted in this process (Silva et
al., 2017). The powdered material of dried Siam weed leaves (Figure 2.4) of a known weight
was separately placed in an airtight container, to which a predetermined amount of alcohol
was added, mixed for two hours, and then left to stand for twenty-four hours, then it was
allowed to stand for 24 hours. The mixture of each sample was filtered using Whatman's
filter paper size No. 1 after being sieved using a mucilin cloth to get a clean filtrate of the
extract. To remove the water and obtain a crude plant concentrate known as "Extract," the
filtrate was heated to 90°C in a hot water bath. Equation 2.1 was used to determine the plant
extract % yield in the following manner:
.

Figure 3. A picture of Siam weeds from Emene Forest

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a) Phytochemical screening
Standard phytochemical techniques described by Siddiqui and Ali (1997), Trease and
Evans (1998), and Harborne (1998) were used to screen the plant extracts and fractions both
quantitatively and qualitatively.

Figure 4. A pictorial representation of Siam weed undergoing drying
at PRODA Enugu labouratory

b) Test for saponins (Qualitative test).
Saponin was tested using the olive oil test method (Gul et al., 2017). The screening test
was based on saponins' capacity to form an emulsion with oil. In a water bath, 20 mg of
extract was cooked for five minutes in 20 ml of distilled water before being filtered. Five
milliliters were mixed with ten milliliters of the filtrate and distilled water, and the mixture
was agitated vigorously to create froth. Three drops of olive oil were combined with the
foam, agitated briskly, and the formation of an emulsion was monitored.
c) Determination of Total Saponins (Quantitative test)
After being ground, 20g of each sample and 100ml of 20% ethanol in water were put to
a 250ml conical flask. Over a hot water bath, the samples were continuously stirred while
being cooked for 2 hours at 55°C. The residue was extracted a second time after the mixtures
were filtered. 200ml more of 20% ethanol should be added. The saponin extracts were
reduced to 40 milliliters using a water bath at about 90°C. The concentrate was placed in a
250 ml separating funnel, and the aqueous layer was recovered after 20 ml of diethyl ether
was added and thoroughly shaken. The purifying procedure was carried out once more. Ten
milliliters of 5% aqueous sodium chloride were used twice to wash the nbutanol extracts
following the addition of 60 milliliters of n-butanol. The samples were dried in an oven to a
consistent weight after evaporation, the saponin content was ascertained, and the remaining
solution was boiled in a water bath. (Obdoni and Ochuko, 2001).

W1 = weight of the empty beaker
W2 = weight after drying
W.T = weight of sample.

d) Fractionation for saponins isolation using column chromatography.
Fractionation of the saponin extracts was carried out by column chromatography after
the methods of Gupta et al., with a few changes. After packing the silica gel into the column,
it was left to stand for a while. In order to separate the extract's polar and non-polar
components, the concentrated extract was then placed onto the column and its contents were

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eluted using a range of solvents arranged by polarity (n-hexane, dichloromethane, ethyl
acetate, and ethanol) (WHO, 2014). Following the concentration of the resultant fractions, the
phytochemical components were analyzed, revealing that the ethanol fraction was primarily
composed of saponin with trace levels of other chemicals. To determine the ideal solvent
mixture for isolating saponin from other minute components, Thin Layer Chromatography
(TLC) was performed in the lab. The ratios of n-butanol, methanol, and water were 1.5:1:0.5.
After that, the concentrated ethanol fraction was put into a silica gel column, which was used
as the stationary phase and divided between the n-butanol, methanol, and water combination.
Following concentration in a water bath, the phytochemical content of the resultant effluent
was examined.
After that, it was discovered that the effluent had glycosides, terpenoids, and
saponins. A second TLC examination will demonstrate that saponins can be separated from
other components using a methanol-chloroform mixture. The components were eluted using
silica gel as the stationary phase after After being placed in the column, the concentrated nbutanol eluent was split 9:1 between methanol and chloroform. A "saponin-rich fraction of
ethanoic leaf extract" is the quantity of saponin that was discovered bound to lactone and
glycoside compounds following the concentration of the final efluent and an analysis of its
phytochemicals. Since the saponin content was found to be low, the column was washed with
70% analytical grade ethanol to liberate the trapped saponin (figure 5).

Figure 5. A pictorial representation of extracted Saponin

5. Batch Soil Washing Studies
Research on Batch Soil Cleaning tests were used to examine how the desorption of
heavy metals from contaminated soil samples is affected by pH, the ratio of surfactant soil
solution, and contact time in order to liberate the trapped saponin (Ugwu, 2019). Using a
rotary shaker set to approximately 200 rpm, A 125 ml conical flask was used for a number of
batch tests in the laboratory. All tests were carried out at room temperature with variable
contact times. Samples were then gathered and centrifuged for 15 minutes at 7000g (Luna et
al., 2016). The starting pH was change by the addition either sodium hydroxide or
hydrochloric acid to the soil solution after collecting the supernatants on filter paper. The
nitric acid droplets were used to preserve the filtrates, which were then kept for heavy metal
analysis. A similar equation was used to calculate the responses, which were expressed as
percentages of metals eliminated from the washing experiment (Equation. 2.3). To examine
the heavy metals, an Atomic Adsorption Spectrophotometer (AAS) was employed.

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Where
C1 = concentrations of metal in soil before batch experiment (mg/kg)
C2 = concentrations of metal in the soil after the batch experiment (mg/kg).

All experiments were conducted in three replicates to guarantee accuracy, and the average
findings were displayed.
6. Experimental Design
The impact of pH, Soil-Solution Ratio (SSR), and contact time on the remediation of
Zn from a polluted soil was assessed in this study using the Box Behnken Design (version
13). These factors' interplay and optimization were examined. Three components in three
levels—coded as +1 (high), 0 (medium), and -1 (low)—were examined (Ugwu et al., 2022).
Ugwu et al. (2021a) provided the values for the three pH and time levels. Table 2.1 lists the
process variables along with their levels. Eqn. 2.4 defines the number of experiments (N) in
BBD (Gharibzadeh et al., 2018).

Where k is the number of factors and Co is the number of central points.
Table 1: Experimental Factors and their Levels
Factors/Levels
Level 1
Level 2
3
4
pH of Surfactants
1g:5mg/l
1g:10mg/l
Ratio of Soil to surfactant Concentration
6hours
12hours
Contact Time

Std

Run

15
6
1
11
9
16
10
2
5
13
12
3
7
14
4
17
8

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

Table 2: Experimental Runs using Box Behnken Design
Factor 1 Factor 2.
Factor 3.
Response
Response
A:Ph
B:Surfactant C:Contact
%Zinc (Zn) %Zinc (Zn)
Concentratio time(Hour) Removal
Removal
n(mg/l)
(soil C1)
(soil C2)
4
5
3
4
4
4
4
5
3
4
4
3
3
4
5
4
5

10
10
5
5
5
10
15
5
10
10
15
15
10
10
15
10
10

Level 3
5
1g:15mg/l
18hours

Response
%Zinc (Zn)
Removal
(soil C3)

12
6
12
18
6
12
6
12
6
12
18
12
18
12
12
12
6

The Box Behnken Design approach was used in the experiment's design. Every
numerical factor has three levels. For each combination of the categoric factor level, the Box
Behnken Design was replicated if categoric factors were introduced. It was set up as shown in
table 2.2 to determine the impact of three distinct elements at three distinct levels each. In the

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laboratory, 17 runs, or 17 tests, were carried out for each of the three soil samples. Saponin
from Siam weed was used in 51 tests in the laboratory. Every experiment was carried out
three times, with a record of the average values collected. RSM based on the Box Behnken
design was used for the optimization experiments.
RESULT AND DISCUSSION
Impact of Saponin-Based Soil Washing on the Zinc Removal Efficiency for Individual
and Accross Soils.
The result of the percentage removal of Zinc from soil C1, C2 and C3 using saponin as
a washing agent which was carried out with Box-Behnken design of the response surface
methodology (RSM) is as presented in table 3.1. and the design matrix contained 17
experimental runs with three responses. Optimization analyses were carried out in Design
Expert (V.13).
The optimum value was recorded in this study for soil C1 as 96% at pH, SSR and time
of 5, 15 and 10.8hrs respectively. Table 3.1 shows that Zinc (Zn) removal efficiency ranges
from 48.98% to 99.84%. High efficiency is observed at moderate to high pH levels, with
optimal results at pH 4, SSR 10, and moderate time. The optimum value was recorded in this
study for soil C2 as 99% at pH, SSR and time of 4, 13.6 and 16hrs respectively. Table 3.1
shows that Zinc (Zn) removal efficiency had a moderate to high efficiency (48.51%–
98.98%). Maximum removal occurs at high SSR and longer times. The optimum value was
recorded in this study for soil C3 as 100% at pH, SSR and time of 3.3, 14.4 and 18hrs
respectively. Table 3.1 also shows that Zinc (Zn) removal efficiency is high (53.85%–100%),
with multiple runs achieving complete removal (e.g., Run 9, 12).
Table 3. Responses to the Box-Behnken Design Matrix for Saponin Removal of Zinc from Soils
Soil C2
Soil C3
STD Run
A: pH
B:SSR C:Time
Soil C1
1
1
3
5
12
48.98
48.51
53.85
17
2
4
10
12
99.12
92.75
97.24
13
3
4
10
12
88.55
94.24
95.45
2
4
5
5
12
98.18
82.45
96.22
12
5
4
15
18
99.05
96.89
100
8
6
5
10
6
98.13
83.88
96.12
7
7
3
10
18
48.98
98.98
98.99
9
8
4
5
18
50.54
98.24
93.57
3
9
3
15
12
98.7
94.01
100
16
10
4
10
12
99.84
88.62
95.45
14
11
4
10
12
98.39
96.25
98.76
4
12
5
15
12
98.61
95.49
97.42
11
13
4
5
18
49.14
79.47
98.48
10
14
4
15
6
99.53
95.97
95.39
15
15
4
10
12
99.26
90.07
97.26
6
16
5
10
6
98.46
90.72
95.37
5
17
3
10
6
98.65
82.44
98.76

Soil C3 generally exhibits the highest Zn removal efficiency, with several runs
achieving 100%. Soil C1 performs similarly but shows more variability. Studies by Liu et al.,
(2019) reported Zn removal efficiencies of 90% using saponin, comparable to the high
efficiencies observed for Soils C1 and C3 in this study. Soil C2 shows moderate to high
efficiency but is slightly less consistent.
The high removal efficiencies across varying soils demonstrate the versatility of
saponin for soil remediation. Soil C3 shows slightly better overall performance, likely due to

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favorable soil characteristics. Mukhopadhyay, (2018) observed that soapnut was more
efficient than SDS due to its lower pH. Soapnut solution removed more than 73% zinc while
SDS solution could only wash out up to 31% of the total zinc from the soil under similar
experimental conditions.
120
100
80
Zn Removal(soil C1)
60

Zn Removal(soil C2)

40

Zn Removal(soil C3)

20
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Figure 6: A graphical of runs against removal efficiency of Zinc
Across soils using saponin as a washing agent.

The graph above shows the removal efficiencies of Zn across soils when washed with
saponin. It could be observed that soil C1 recorded the highest removal efficiency in most
cases, such as in runs 2, 4, 6, 10, 12, 14, 15 and 16 when compared to that of soil C2 and C3.
Soil C3 also recorded highest removal efficiencies at runs 1, 3, 5, 9, 11 and 13 when
compared to C1 and C2. C2 soil recorded its highest removal efficiency for zinc in runs 8
alone. The graph generally shows high removal efficiency for zinc when washed with
saponin. According to Feng et al, (2020b) Zinc recorded a low removal efficiency of between
21.82–27.94% when washed with F. esculentum, at concentration of 50 g/L, pH 3 and contact
duration of 120 min. this result is very low when compared to that of this study.
CONCLUSION
The overall results indicate that batch washing with biosurfactants showed promising
results in the treatment of heavy metal contaminated soil. The study provides knowledge
about performance of plant based surfactant into remediating real contaminated soil. Further
studies on soil washing with biosurfactants should be extended to other metals. An
assessment of the quality (in terms of fertility) of the remediated soil and the stability of
retained biosurfactants is needed.
Acknowledgments
The authors thank TETFund for providing the fund to sponsor this research work. It is
important to appreciate the staff of ministry of Environment Enugu, who assisted in the
collection of samples at the dumpsite.

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Vol. 3, No. 2, June - August 2025

Zhang, Y., Dai, Y., Wang, Y., Huang, X., Xiao, Y., and Pei, Q. (2021a). Hydrochemistry,
Quality and Potential Health Risk Appraisal of Nitrate Enriched Groundwater in the
Nanchong Area, Southwestern China. Sci. Total Environ. 784, 147186.
doi:10.1016/j.scitotenv.2021.147186
Zhang, Y., He, Z., Tian, H., Huang, X., Zhang, Z., Liu, Y., et al. (2021b). Hydrochemistry
Appraisal, Quality Assessment and Health Risk Evaluation of Shallow Groundwater
in the Mianyang Area of Sichuan Basin, Southwestern China. Environ. Earth Sci. 80
(17), 576. doi:10.1007/ s12665-021-09894-y
Zhang, Y., He, Z., Tian, H., Huang, X., Zhang, Z., Liu, Y., et al. (2021b). Hydrochemistry
Appraisal, Quality Assessment and Health Risk Evaluation of Shallow Groundwater
in the Mianyang Area of Sichuan Basin, Southwestern China. Environ. Earth Sci. 80
(17), 576. doi:10.1007/ s12665-021-09894-y
Zhang, Y., Dai, Y., Wang, Y., Huang, X., Xiao, Y., and Pei, Q. (2021a). Hydrochemistry,
Quality and Potential Health Risk Appraisal of Nitrate Enriched Groundwater in the
Nanchong Area, Southwestern China. Sci. Total Environ. 784, 147186.
doi:10.1016/j.scitotenv.2021.147186.
Zhang, Y., He, Z., Tian, H., Huang, X., Zhang, Z., Liu, Y. (2021b). Hydrochemistry
Appraisal, Quality Assessment and Health Risk Evaluation of Shallow Groundwater
in
the Mianyang Area of Sichuan Basin, Southwestern China. Environ. Earth Sci.
80 (17), 576. doi:10.1007/ s12665-021-09894-y

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