



































East


East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, Issue. 1, 1-14 
 

 

 

 
*Corresponding author: 
  Email: joseph.saria@gmail.com , +255-719936151   https://dx.doi.org/10.4314/eajbcs.v6i1.1S 
 

 

 

Influence of Vat Leach Reprocessed Tailings on Heavy Metals Levels around Sekenke Gold Mine, 

Iramba District, Tanzania 

 

 

Romanus Priscus *1 and Josephat Saria2 

 
1Geological Survey of Tanzania, P. O. Box 903, Dodoma, Tanzania  
2Dept. of Physical and Environmental Sciences The Open University of Tanzania, P. O. Box 23409, Dar 

es Salaam, Tanzania,  

 

KEYWORDS:  

Heavy Metals; 

Geoaccumulation Index (Igeo); 

Contamination factor (Cf); 

Pollution Load Index (PLI); 

Iramba 

 

 

 

 

 

 

 

 

ABSTRACT 

Soil pollution is a worldwide phenomenon which results from both natural and 

anthropogenic activities. This has resulted in several health and physiological problems in 

both plants and human. This study investigated the concentration of heavy metal 

contaminants at Senkenke gold mining areas in nine tailings samples before processing and 

in nine tailing samples after processing using XRF Rigaku Nex CG and arsenic was 

determined using AAS equipped with a continuous flow of VGA. Arsenic mean 

concentration in unprocessed samples was 32.873 ± 26.284 mg/kg, while in processed 

tailings was 24.390 ± 19.394 mg/kg. The mean concentration of Pb in unprocessed tailing 

was 44.012 ± 37.091mg/kg, while in processed tailing was 38.402 ± 28.270 mg/kg. The 

mean concentration of Cd in unprocessed tailing was 4.513 ± 1.022 mg/kg, while in 

processed tailing was 3.089 ± 1.329 mg/kg. Chromium mean concentration in unprocessed 

tailing was 194.526± 22.670 mg/kg while in processed tailing was 141.352 ± 30.726 mg/kg. 

The Igeo values found in the following increasing order in unprocessed tailing Zn < Fe < 

Pb < Cr < As < Cd while in processed tailing was in the following increasing order Zn < Fe 

< Cr < As < Pb < Cd. The PLI values calculated for tailing samples are found to 4.423 for 

unprocessed tailing and 2.807 for processed tailing which shows that the soils are polluted 

and the environment is deteriorated in their quality. The findings revealed that the soils and 

mine tailings in the study area were polluted with heavy metals, particularly As, Pb and Cr 

and mostly Cd. The heavy metal concentrations decrease from unprocessed tailing to 

processed tailings. This pollution poses significant environmental and health risks. 

. 

 
 

INTRODUCTION 

Mining is a crucial driver of global economic 

growth, with the extraction of precious metals 

serving as a significant source of foreign 

exchange for many developing nations. 

Tanzania, rich in minerals and natural resources 

such as gold, diamonds, coal and natural gas, 

generated around 3.6 billion U.S. dollars from 

mineral exports. This was a rise from 2.3 billion 

U.S. dollars in 2023 (Cowling, 2024). Gold was 

the largest contributor to the country's mineral 

export earnings. 

The extraction and processing of precious metals 

often come with considerable environmental and 

public health risks. For example, mine tailings 

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East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

2 
 

from gold ore processing can pollute the 

environment (Roussel et al., 2000). These 

tailings commonly contain heavy metals and 

leftover reagents such as cyanide. Several 

researchers (Raji et al., 2021, Shapi et al., 2021) 

have documented high concentrations of heavy 

metals in water streams near gold mines, while 

Miller (2022) indicated heavy metals from 

mining activities can remain in surface soil layers 

for many years. 

Tailings are a mix of finely ground rock residues 

left after valuable minerals have been extracted, 

combined with the water used in processing. In 

countries with limited environmental regulation 

enforcement, large volumes of open-dumped 

tailings are common (Baker and Banfield, 2003). 

The chemical and physical makeup of tailings 

resembles that of typical river sand and silt, 

shaped by factors such as ore type, geochemistry, 

extraction methods, particle size, and specific 

chemical treatments used in processing (Davies 

and Rice, 2001; Franks et al., 2011). Gold mine 

tailings, in particular, have poor physical 

qualities, including low aggregation, high 

hydraulic conductivity, fine texture, and weak 

cohesion (Khan et al., 2023). These 

characteristics set tailings apart from natural soil 

(Vega et al., 2004; Blight and Fourie, 2005), with 

low cohesion contributing to fluctuations in 

moisture content and temperature within this 

hazardous waste. 

Gold extraction generates a substantial amount of 

tailings, which are waste materials discarded 

after ore processing. These tailings often contain 

various contaminants, including mercury, 

arsenic, antimony, cyanide, and residuals (Uddin 

et al., 2021). The process of mining gold can 

release numerous toxic pollutants, which pose 

health risks even at low concentrations. 

According to Olise et al. (2019), artisanal gold 

mining is a well-known source of toxic metals in 

soil, sediment, and water, releasing harmful 

substances such as cadmium, arsenic, copper, 

lead, iron, chromium, nickel, and zinc into the 

environment.  

Zinc and iron are among the most abundant 

element on earth (Quintero-Gutiérrez et al., 

2008) and is a biologically essential component 

of every living organism (Aisen et al., 2001). 

Arsenic (As), a naturally occurring and abundant 

element in the earth's crust both organic and 

inorganic forms can be found in soil, with the 

latter being a very toxic form (Shrivastava et al., 

2015). Arsenic can be due to smelting of gold, 

mining processes like smelting pharmaceutical 

waste, wastewater in mining site or combustion 

of fossil fuels (Bhardwaj et al., 2020; Biamont-

Rojas et al., 2023). Cadmium is frequently used 

in production of polyvinylchloride (PVC) 

products, alloys, pigments and batteries (Wilson, 

1988; Yuan et al., 2019). Chromium can be 

found in metal plating and paints, and pigments, 

rubber, photography, tanning and mining and 

metallurgy/metal purification (Sharma et al., 

2021). Lead Combustion of fossil fuels, paints 

and pigments; application of lead in gasoline, and 

solid waste, explosives, ceramics and dishware, 

solid waste combustion, paints and pigments, 

industrial dust and fumes, manufacturing of lead-

acid batteries, pesticides, mining and metallurgy, 

some types of PVC, urban runoff (Obeng-Gyasi, 

2019). Even though long-term exposure to heavy 

metals is linked to serious health problems like 

cancer, the public remains largely unaware of the 

associated risks. This contamination can harm 

human health through both direct and indirect 

exposure to these toxic metals (Muradoglu et al., 

2015; Jin et al., 2019; Liu et al., 2020). 

According to Clancy et al. 2012, several acute 

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East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

3 
 

and chronic toxic effects of heavy metals affect 

different body organs. Gastrointestinal and 

kidney dysfunction, nervous system disorders, 

skin lesions, vascular damage, immune system 

dysfunction, birth defects, and cancer are 

examples of the complications of heavy metals 

toxic effects. 

Vat leaching is a process that involves using 

chemicals, such as cyanide or sulfuric acid, to 

extract gold from ore. When the leftover 

material, known as tailings, is reprocessed, these 

chemicals as well as heavy metals like arsenic, 

mercury, lead, and cadmium, which are often 

present in the ore can seep into nearby soil and 

water systems. Consequently, evaluating the 

impact of these tailings on heavy metal levels is 

essential for assessing potential contamination of 

local ecosystems. To address this knowledge 

gap, this study aims to determine levels of heavy 

metals in tailings before processing and compare 

them with levels that remain after processing. 

Specifically, this study will utilize XRD to 

analyze samples from Senkenke mining areas, to 

determine the concentrations of heavy metals and 

assess pollution load through statistical analysis. 

Materials and Methods 

Study Area 

The study was conducted at the Sekenke small-

scale gold mine in Iramba District, Tanzania. 

Located on a low rise in the Wembere depression 

at 03°57′S and 34°15′E, gold was discovered 

here before 1914, leading to significant 

development, making it the largest reef-gold 

producer in the country. The mine spans 

approximately 252 hectares and includes 9 

unprocessed tailings heaps, each containing 

around 5,000 tons of soil material. Additionally, 

there are 9 reprocessed tailings heaps, totaling 

about 12,000 tons, situated around various 

processing plants. 

Soil Sample Collection 

One sample from each tail was taken by opening 

small trenches/holes with a spade and using 

chisels for sampling. The collected 18 tailing 

samples were stored in Teflon bags, tightened 

separately and taken to the Geological Survey of 

Tanzania (GST) Laboratory for analysis. In the 

laboratory samples were air-dried under a 

controlled environment to achieve constant 

weight.  

Sample Preparation 

The samples were dried at 50-105ºC for 24 hours 

to remove the moisture. The samples were 

grounded and then sieved to remove coarse 

debris and rubble with a size greater than 2.0mm. 

A non-metallic sieve was used to avoid 

contamination of metals. Each sample was 

divided into three different potions (triplicate). 

From sample 1g of fine soil sample undergoes 

aqua regia digestion (HCl/HNO3: 3/1) to attack 

a wide range of soil and geological materials, 

heated slowly near dryness. After the process of 

digestion, 20ml of distilled water was added to 

each sample, filtered and kept in a 100 ml 

volumetric flask, which was then diluted to the 

mark. The sample solutions were stored well in 

Teflon bottles and analyzed by XRD instrument.  

The XRD operates by measuring the 

characteristic secondary radiation emitted from a 

sample that has been excited with an X-ray 

source. It is rapid, reliable, non-destructive and 

often quicker than other analysis techniques 

(Karathanasis and Hajek, 1996). To maintain the 

accuracy of the machine, three blank samples of 

silica sand collected from the Coastal region 



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

4 
 

were prepared following all protocols of 

collected soil samples from the mine site and then 

analysed simultaneously with the soil samples. 

Evaluation of Heavy Metal Pollution 

The degree of contamination was analyzed by 

three indices for environmental assessment of 

soil in small scale mining of Sekenke Singida 

Municipality. The indices are Geo-accumulation 

index (Igeo) and Contamination Factor (Cf). 

Geoaccumulation Index (Igeo) 

The Igeo is a pollution degree evaluation index 

proposed by Müller (1979) and is widely used to 

evaluate the pollution degree of single metal in 

water, ocean, and soil environments (Banu et al., 

2013). The calculation formula can be expressed 

as follows: 

Igeo = log2 










i

i

B

C

5.1
    (1)

 

Where Ci represents the concentration of heavy 

metals measured in the soil (mg/kg), and Bi refers 

to the geochemical background values based on 

the Average Composition of Shales as proposed 

by Turekian and Wedepohl (1961). These shale 

values were chosen for calculating pollution 

indices as they allow for meaningful 

comparisons across different regions, aiding in 

the understanding of global trends in element 

enrichment and contamination (Turekian and 

Wedepohl, 1961; Ali et al., 2016). Shale values 

offer a consistent, standardized reference point 

and are relatively stable, minimizing significant 

variations in elemental composition over 

time.The background values adopted from Edori 

and Kpee (2017) where: As= 13; Fe = 47,200; Cr 

= 90; Pb = 20; Cd = 0.3 and Zn = 95 both in 

mg/kg. 

Förstner et al. (1993) listed geo-accumulation 

classes and the corresponding contamination 

intensity for different indices Table 1.  

Table 1: Geo-accumulation Index Classification 

Soil Igeo Contamination Igeo Accumulation Class Intensity Index Igeo 

>5 6 Very Strong 

>4 - 5 5 Strong to very strong 

>3 - 4 4 Strong 

>2 -3 3 Moderate to strong 

>1 - 2 2 Moderate 

>0 - 1 1 Uncontaminated to moderate 

<0 0 Practically uncontaminated 

 

Contamination Factor 

Contamination factor ( fC ) was determined 

using Single Pollution Index Model. This is a 

basic and useful tool for detecting toxic metal 

contamination. This Cf used to evaluate the 

individual toxic metal contamination in the soil. 

The standard employed for the interpretation of 

the contamination factor values was adopted 

from Edori and Kpee (2017) as given in Eq. (2): 

= 
b

m

C

C
      (2) 

Where: Cf = Contamination factor; = Cm = the 

concentration of the metal and Cb = the 

background value.  



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

5 
 

Hakanson, (1980) suggested four categories of 

Cf to assess the metal contamination levels as 

when Cf < 1: Indicates low contamination (or no 

contamination). The concentration of the 

contaminant is less than the background level. 

When 1 ≤ Cf < 3 indicates moderate 

contamination while 3 ≤ Cf < 6 indicates 

considerable contamination and Cf ≥ 6: Indicates 

very high contamination. 

Hakanson, (1980) proposed the contamination 

degree (Cdeg) of the soil and was computed 

based on the sum of all contamination factors 

using the formula (equation 3) 

degC



n

i

Cf
1

    (3) 

Where n is the number of analyzed metals. 

Thecontamination degree of soil is divided into 

four groups: low (Cdeg < 8), moderate (8 ≤ Cdeg < 

16), considerable (16 ≤ Cdeg<32) and very high 

contamination degree (Cdeg ≥ 32). 

A modified form of the contamination degree 

equation for the calculation of the overall degree 

of contamination was presented by Abrahim and 

Parker (2008). The modified degree of 

contamination Cdeg, m) was calculated by the 

sum of all contamination factor (Cf) for a given 

set of soil pollutants divided by the number of 

analyzed pollutants. This was calculated by the 

following formula (equation 4). 





n

i

f

m
n

C
C

1

deg,     (4) 

The classifications of the modified degree of 

contamination (Cdeg,m) in soil are as follows: 

Cdeg,m < 15, very low degree of contamination; 15 

< Cdeg,m < 2, low degree of contamination; 2 < 

Cdeg, m < 4, moderate degree of contamination; 4 

< Cdeg,m < 8, high degree of contamination; 8 < 

Cdeg,m < 16, very high degree of contamination; 

16 <Cdeg,m < 32, extremely high degree of 

contamination; Cdeg,m > 32, ultra high degree of 

contamination spatial. 

Table 2: Classification of Different Pollution Indices  

geoI valuea Description Cf  valueb Description PLI valuec Description 

Igeo
 
< 0 Practically 

Uncontaminated 

Cf  < 1 Low 

contamination 
PLI  = 0 Excellent 

0< Igeo
 
<1 Uncontaminated to 

moderate 

contaminated 

1≤  Cf < 2 Low to 

moderate 

contamination 

PLI  = 1 Baseline level 

of pollutants 

1< Igeo
 
<2 Moderate 

Contaminated 

2≤ Cf < 3 Moderate 

contamination 
PLI > 1  Polluted 

2< Igeo
 
<3 Moderate to heavily 

contaminated 

3≤  Cf
 
< 4 Moderate to 

high 

contamination 

  

3< Igeo
 
<4 Heavily 

contaminated 

4≤  Cf
 
< 5 High 

contamination 

  

4< Igeo
 
<5 Heavily to extremely 

contaminated 

5≤ Cf
 
< 6 High to very 

high 

contamination 

  

5< Igeo
 
 Extremely 

contaminated 

Cf
  
≥ 6 Extreme 

contamination 
  

aMuller (1969), b Ma et al. (2022), cMkude et al. (2021)  



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

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The Pollution Load Index (PLI) 

The Pollution Load Index (PLI) is obtained as 

Concentration Factors (Cf). This Cf is the 

quotient obtained by dividing the concentration 

of each metal. The PLI of the place are calculated 

by obtaining the n-root from the n-Cf that was 

obtained for all the metals. With the PLI obtained 

from sampling site. Generally pollution load 

index (PLI) as developed by Lacatusu (2000) 

which is as follows (equation5): 

PLI  = ( 1fC × 2fC × 3fC × … fnC )
n/1

   (5) 

Where: PLI is Pollution Load Index, Cf 

contamination factor of respective metal, n = 

number of metals. 

Table 2 shows different classifications into 

which the contamination factor (Cf), Geo 

accumulation Index (Igeo) and Pollution load 

index (PLI) are categorized. 

Statistical Analysis 

A comprehensive statistical analysis was 

conducted on heavy metal data collected samples 

of two tiling categories. This analysis included 

the calculation of mean values, standard 

deviation (SD), and range. All statistical 

evaluations were performed using IBM SPSS 

Statistics (v. 20). To evaluate the contamination 

of tailing, the concentration, contamination 

factor (Cf), geo-accumulation index (Igeo), and 

pollution load index (PLI) were applied. 

RESULTS AND DISCUSSION 

The Concentration of Heavy metals in 

Tailings Samples 

The concentration (amount) of heavy metals in 

unprocessed and processed tailings is presented 

in Table 3. Arsenic was detected in both 

unprocessed and processed samples, as well as in 

all heaps. In unprocessed samples, arsenic 

concentrations ranged from 12.993 to 80.531 

mg/kg, with a mean of 32.873 ± 26.284 mg/kg. 

Approximately 67% of the unprocessed tailings 

samples had arsenic levels exceeding the 

WHO/FAO (2011) maximum acceptable limit of 

20.0 mg/kg. In processed tailings, arsenic levels 

ranged from 7.243 to 61.116 mg/kg, with a mean 

of 24.390 ± 19.394 mg/kg. About 44% of the 

processed tailings samples exceeded the 

WHO/FAO acceptable limit. Overall, arsenic 

concentrations were lower in processed tailings 

compared to unprocessed tailings. Previous 

studies (Harmanescu et al., 2011; Tóth et al., 

2016) have indicated a strong correlation 

between arsenic (As), cadmium (Cd), mercury 

(Hg), lead (Pb), and gold mining activities. The 

Arsenic levels in this study were lower than those 

found in earlier research in Ghana, where a 

maximum concentration of 8305 mg/kg was 

reported (Ahmad and Carboo, 2000), and in 

another study with a maximum concentration of 

1752 mg/kg in gold mine tailings (Bempah et al., 

2013). High levels of Arsenic contamination are 

concerning due to its potential health impacts, 

with previous epidemiological studies 

(Tchounwou et al., 2003) highlighting a strong 

link between Arsenic exposure and an increased 

risk of both carcinogenic and systemic health 

effects. 

Lead has many different industrial, agricultural 

and domestic applications. It is currently used in 

the production of lead-acid based batteries, 

ammunitions, metal products (solder and pipes), 

and devices to shield x-rays (Gabby, 2006). Lead 

is the most systemic toxicant that affects several 

organs in the body including the kidneys, liver, 



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

7 
 

central nervous system, hematopoetic system, 

endocrine system, and reproductive system (Tsai 

et al., 2017; Pirkle et al., 1998). 

Lead concentration in unprocessed tailing varied 

largely from 20.181 to 119.427 mg/kg with mean 

of 44.012 ± 37.091mg/kg. The concentration in 

processed tailing ranges from 18.219 to 97.233 

mg/kg with mean of 38.402 ± 28.270 mg/kg. The 

detected levels in both unprocessed and 

processed are higher than the maximum 

acceptable limit (WHO/FAO, 2011). The 

concentration in processed tailing is lower than 

in unprocessed tailing by the factor of 1.15. The 

values obtained in this study  are lower than the 

one detected in similar study (Ogola et al., 2002) 

where the level of Pb in  gold mining soils have 

been reported to be 510 mg/kg of Pb 

concentrations  in Kenya. 

Zn plays a key role during physiological growth 

and fulfills an immune function. It is vital for the 

functionality of more than 300 enzymes, for the 

stabilization of DNA, and for gene expression 

(Costa et al., 2023). Although some iron 

enzymes are sensitive to iron deficiency 

(Dallman, 1990), their activity has not been used 

as a successful routine measure of iron status. 

The most significant and common cause of 

anemia is iron deficiency (WHO/CDC, 2008). If 

iron intake is limited or inadequate due to poor 

dietary intake, anemia may occur. 

Table 3: Concentrations of Heavy Metals (mg/kg) 
Sample No. Concentration in Unprocessed Tailings Concentration in Processed Tailings 

As Pb Cd Fe Zn Cr As Pb Cd Fe Zn Cr 

1 13.782 31.681 4.413 22960.03 43.617 182.332 9.267 27.287 5.978 22011.47 40.200 179.174 

2 23.161 119.427 6.261 24463.80 169.589 220.024 21.341 77.013 4.112 23414.64 171.118 118.321 

3 26.567 20.181 3.833 25307.94 76.251 179.467 15.413 18.219 1.468 24000.12 66.726 137.226 

4 75.978 23.138 3.528 30089.13 80.408 148.881 61.116 26.871 2.973 26242.00 78.842 142.474 

5 13.922 28.864 3.913 22864.25 50.064 204.119 11.519 24.172 2.242 20177.43 44.221 144.387 

6 23.199 97.233 6.230 24476.98 147.219 196.354 22.011 97.233 3.104 25221.25 74.544 124.933 

7 25.726 21.386 3.877 25323.16 78.341 188.739 18.252 21.386 2.711 22824.77 81.663 110.439 

8 80.531 24.188 4.148 30102.12 69.961 214.638 53.347 24.188 1.988 23446.43 52.194 178.642 

9 12.993 30.014 4.418 23003.28 44.784 216.183 7.243 29.248 3.229 23684.40 44.007 199.573 

Mean 1 32.873 44.012 4.513 25398.96 84.470 194.526 24.390 38.402 3.089 23446.95 72.613 141.352 

STD ( ±) 26.284 37.091 1.022 2827.729 44.641 22.670 19.394 28.270 1.329 1748.619 40.240 30.726 

WHO/FAO (2011) 20.0 50.0 3.0 - 300 50 20.0 50.0 3.0 - 300 50 

Zinc concentration in unprocessed tailing ranges 

from 43.617 to 169.589 mg/kg with mean of 

88.470 ± 44.641 mg/kg. The concentration of 

analyzed samples is lower than maximum 

acceptable limit by WHO/FAO (2011). The 

concentration in processed tailing ranges from 

40.200 to 171.118 mg/kg with mean of 72.613± 

40.240 mg/kg. Surprisingly, the concentration in 

unprocessed tailing is lower than of the tailings 

processed tailing. This is due to the existing in 

geochemical environment where mostly in 

mining sites acid is and they mobilize zinc from 

sulfide minerals, concentrating it in the processed 

tailings (Miler et al., 2022). This redistribution 

lead to increase zinc concentrations in the 

processed material (Gleisner and Herbert, 2002). 

The values obtained in this study are higher than 

the value detected earlier in Ghana (Koranteng et 



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

8 
 

al., 2011), where the mean Zn concentrations in 

the sand soil samples ranged between 4.17±1.23 

mg/kg and 43.17±4.75 mg/kg. 

Iron concentration in unprocessed tailing ranges 

from 22844.250 to 30102.120 mg/kg with mean 

of 25398.96 ± 2827.729 mg/kg. The 

concentration in processed tailing ranges from 

22011.470 to 26242.00 mg/kg with mean of 

23446.95 ± 1748.619 mg/kg. The concentration 

observed in this study in in line with similar study 

in Nigeria (Fagbenro et al., 2021) where the 

mean concentration was 20,560.4 ± 84.30. 

Cadmium compounds are classified as human 

carcinogens by several regulatory agencies 

(IARC, 1993).  Cadmium is a severe pulmonary 

and gastrointestinal irritant, which can be fatal if 

inhaled or ingested. After acute ingestion, 

symptoms such as abdominal pain, burning 

sensation, nausea, vomiting, salivation, muscle 

cramps, vertigo, shock, loss of consciousness and 

convulsions usually appear within 15 to 30 min 

(Baselt. and Cravey, 1995). Acute cadmium 

ingestion can also cause gastrointestinal tract 

erosion, pulmonary, hepatic or renal injury and 

coma, depending on the route of poisoning 

(Baselt, 2000).  

Cadmium concentration in unprocessed tailing 

ranges from 3.528 to 6.261 mg/kg with mean of 

4.513 ± 1.022 mg/kg. About 100% of the 

analyzed samples have higher level than 

maximum acceptable limit by WHO/FAO 

(2011). The concentration in processed tailing 

ranges from 1.988 to5.978 mg/kg with mean of 

3.089 ± 1.329 mg/kg. About 44% of the samples 

analyzed have higher level than maximum 

acceptable limit by WHO/FAO (2011). The 

values obtained in this study  are lower than one 

detected in similar study (Bitala et al., 2009) 

where the level of Cd in  gold mining soils have 

been reported  to range between 6.4 to 11.7 

mg/kg of Cd concentrations  in Tanzania. 

Chromium (Cr) is a naturally occurring element 

present in the earth’s crust, with oxidation states 

(or valence states) ranging from chromium (II) to 

chromium (VI) (Jacobs and Testa 2005). 

Industries with the largest contribution to 

chromium release include metal processing, 

tannery facilities, chromate production, stainless 

steel welding, and ferrochrome and chrome 

pigment production. The main health problems 

seen in animals following ingestion of chromium 

(VI) compounds are irritation and ulcers in the 

stomach and small intestine, anemia, sperm 

damage and male reproductive system damage. 

Also it connected with cardiovascular, 

gastrointestinal, hematological, hepatic, renal, 

and neurological effects as part of the sequelae 

leading to death or in patients who survived 

because of medical treatment (ATSDR, 2008). 

Chromium concentration in unprocessed tailing 

ranges from 148.881 to 220.024 mg/kg with 

mean of 194.526± 22.670 mg/kg. The 

concentration in processed tailing ranges from 

110.439 to 199.573 mg/kg with mean of 141.352 

± 30.726 mg/kg. All samples analyzed detected 

higher level than maximum acceptable limit by 

WHO/FAO (2011). The concentration in 

processed tailing is lower than in unprocessed 

tailing by the factor of 1.38. The values obtained 

in this study are lower than the one detected in 

similar study in Oman (Abdul-Wahab and 

Marikar, 2012) where the level of Cr in gold 

mining soils reported to be 486 mg/kg in gold 

mine tailings. 

 

 



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

9 
 

Heavy Metals Pollution Levels  

Geo-accumulation Indices 

The calculated index of geo-accumulation (Igeo) 

for the investigated trace metals in the tailings are 

illustrated in Figures 1.  

The Igeo values obtained range from -2.237 to 

3.326 in unprocessed tailing and -0.970 to 3.3116 

in processed tailings. The index of geo 

accumulation (Igeo) was assessed based on the 

values proposed by Müller (1969) and their Igeo 

values estimated is found in the following 

increasing order in unprocessed tailing Zn < Fe < 

Pb < Cr < As < Cd while in processed tailing was 

in the following increasing order Zn < Fe < Cr < 

As < Pb < Cd. According to the Müller scale, the 

calculated results of Igeo values indicate that Cd 

can be classified in class 4 (strong pollutes) for 

both unprocessed and processed tailings (Figure 

1). 

These findings differ from a previous study on 

the enrichment factor (Igeo) of arsenic in surface 

sediments in Malaysia (Abdullah et al., 2020), 

which reported that 13% of the sampling stations 

were classified as moderately polluted, 52.2% as 

unpolluted to moderately polluted, and the rest as 

unpolluted. 

 
Figure 1: Geo-accumulation Indices Values for Unprocessed and Processed Tailings 

Contamination Factor (Cf) 

Figure 2 shows the Contamination Factors (Cf) 

for unprocessed tailings and processed tailing. 

The Cf for unprocessed tailings and processed 

tailing for As, Pb, Cd, Fe, Zn and Cr were 

observed in the ranges of 2.529 to 1.876, 2.201 to 

1.920, 15.043 to 10.297, 0.538to 0.497, 0.889 to 

0.764, and 2.161 to 1.571 respectively.



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

10 
 

 

Figure 2 Contamination Factors for Unprocessed and Processed Tailings

Accordingly, tailing samples can be classified as 

exhibiting low or no contamination with respect 

to Zn and Fe for all sampling tailings. The results 

are lower than those detected earlier (Fagbenro et 

al., 2021), where the average contamination 

factor for Fe was 1.15 and Zn was 1.06. For As, 

Pb, and Cr the Cf is in the range1 ≤ Cf < 

3indicating moderate contamination Cd, the Cf is 

in the range Cf ≥ 6 indicating very high 

contamination.  

The degree of contamination for unprocessed and 

processed tailing sample is 23.361 and 16.925 

respectively. This indicates the tailings are 

considerable contaminate. For the modified 

degree of contamination the unprocessed tailing 

have the value of 4.671 which shows high degree 

of contamination and processed tailing has the 

value of 3.385 which shows moderate degree of 

contamination. These results concur with 

previous study (Hamad et al., 2019), indicating 

the highest enrichment factor for Cr, Zn, Pb and 

As were 25.05 (very high), 7.21 (moderate), 5.07 

(deficiency to minimum) and 5.67 (deficiency to 

minimum) respectively.  

The Pollution Load Index (PLI) 

The pollution load index (PLI) was estimated to 

better realize the pollution level. In addition, it 

also provides useful data to the decision makers 

on the pollution level of the area. The PLI values 

calculated for tailing samples are found to 4.423 

for unprocessed tailing and 2.807 for processed 

tailing which shows that the soils are polluted and 

the environment is deteriorated in their quality. 

This shows the site is strongly affected by mining 

activities and soils in this region is seriously 

contaminated by heavy metals. The values in this 

study are higher than those detected earlier 

(Hamad et al., 2019), where the PLI determined 

ranged from 2.58 to 3.63. 

CONCLUSION & RECOMMENDATIONS 

Heavy metals do not degrade easily and can 

accumulate over time in soil, water, and biota, 



East Afr. J. Biophys. Comput. Sci. (2025), Vol. 6, No. 1, 1-14 
 

11 
 

posing prolonged risks to plant and animal health 

and contaminating food and water supplies. The 

heavy metals like arsenic, cadmium and lead can 

accumulate in organisms and magnify through 

food chains, impacting human health and 

biodiversity. They can cause chronic health 

issues (e.g., cancer, neurological damage) from 

direct and indirect exposure is crucial, especially 

in populations near mining sites. 

Soil is a major pool for contaminants as it 

encompasses ability to bond with various 

chemical materials and media for transportation 

of forms of various pollutants in the atmosphere, 

hydrosphere, and biomass. The results obtained 

in the present research of As, Pb, Cd, Fe, Zn and 

Cr in soil sample collected around unprocessed 

tailing and processed tailing showed that soil 

quality in the mine and areas around the gold 

mining is degrading.  

The studied area is extremely contaminated due 

to many years of mining activities. Our data 

disclose that Cd, As, Zn, Pb and Cr 

concentrations in soil samples are higher than 

WHO/FAO maximum acceptable limits The 

pollution assessment methods showed that soils 

in the studied area are significantly contaminated 

by Cd, As, Zn, Pb and Cr, where the 

concentration in processed tailing is lower than 

in unprocessed tailing by the factor of about 1.38. 

Thus, in future, based on the environmental 

quality criteria for soils, the site would need 

remediation. It is hereby recommended using 

plants and microorganisms to extract or stabilize 

heavy metals in contaminated soils, which can be 

cost-effective and sustainable over the long term. 

Also there is a need to engage local communities 

in monitoring efforts and educating them about 

safe practices, reducing exposure risks and 

fostering awareness of potential health impacts. 

Acknowledgment 

Many thanks to staff at Geological Survey of 

Tanzania (GST) staff members who allowed us to 

use their laboratory in analyzing the samples.  

 

 

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