This document presents a numerical simulation of bioremediation of polyaromatic hydrocarbon (PAH) polluted soil using different mushroom species and MATLAB. Soil samples were divided into cells and treated with saprophytic, symbiotic, or parasitic mushroom substrate over 10 weeks. PAH concentration was measured every 2 weeks. A kinetic model was developed and rate constants were calculated using the integral method in MATLAB. Results showed the parasitic mushroom degraded PAHs fastest with a rate constant of 0.3751 day-1, followed by symbiotic and saprophytic mushrooms. This indicates mushroom-assisted bioremediation can effectively degrade PAH pollution in soil over time.

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IJARET
© I A E M E
NUMERICAL SIMULATION OF BIOREMEDIATION OF POLY
AROMATIC HYDROCARBON POLLUTED SOIL USING MATLAB
1Olatunji, O. M., 2Horsfall, I.T
1Department of Agricultural and Environmental Engineering
Rivers State University of Science and Technology, P.M.B.5080, Port Harcourt, Nigeria.
2Department of Civil and Environmental Engineering
University of Port Harcourt, East West Road Choba, P.M.B.5323, Port Harcourt, Nigeria.
ABSTRACT
The numerical simulation of bioremediation of Poly Aromatic Hydrocarbon PAH was
carried out using exponential curve fitting in Matrice Laboratory (MATLAB). Three species of
Mushroom substrate (saprophytic, symbiotic and parasitic) were applied for remediation on 6
different cells of polluted soil at 0.1m depth. The experiment was allowed to stay for a period of
10 weeks at which the residual concentration was measured at an interval of 2 weeks. A kinetic
model was developed to study the biodegradation rates of PAHs. The reaction rates were studied
by using the integral method with MATLAB as a validating tool. From the results, the rate
constants are: 0.3523, 0.3751, and 0.3603 day-1 for saprophytic, parasitic and symbiotic
mushrooms respectively the residual concentrations for the 10th week are: 3.548, 2.825, 3.275
which shows that the parasitic specie of mushroom degrades PAHs faster than saprophytic and
symbiotic species.
Key words: Simulation, Mushroom, PAHs, MATLAB, Soil.
INTRODUCTION
Polycyclic aromatic hydrocarbon (PAH) is a class of organic compound that consists of
two or more fused benzene rings and/or pent acyclic molecules that are arranged in various
structural configurations (Harvey, 1998). They are highly recalcitrant molecules that can persist
in the environment due to their hydrophobicity and low water solubility. PAHs are ubiquitous in

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the natural environment, and originate from two main sources: these are natural (biogenic and
geochemical) and anthropogenic sources (Harvey 1997).
11
The latter source of PAHs is the major cause of environmental pollution and hence the
focus of many bioremediation activities.
Biological remediation is the use of microorganisms or plants to detoxify or remove organic and
inorganic xenobiotic compounds from the environment. The remediation option offer green
technology solution to the problem of environmental degradation. The process rely on microbial
enzymatic activities to transform or degrade the contaminants in the environment (Philip et al,
2005). It is a cost effective remediation technique when compared with other methods as it is
natural and does not usually produce toxic by-products. It also provides a permanent solution as
a result of complete mineralization of the contaminants in the environment (Perelo, 2010).
Poly aromatic Hydrocarbon (PAH) contamination is caused by leakage of crude oil and
their refined products and the spills of coal tar and creosote from coal gasification and wood
treatment sites (Mueller et al., 1998). Contaminated soil has elevated concentrations of PAH’s
or other substances deriving from man’s use of the soil. This soil contamination negatively
influence human health, surface and groundwater quality, nature and viability of ecosystems,
condition of buildings, other materials and archaeological artifacts within the ground area
(Vegher et al., 2002).
Thus, regulatory agencies have set acceptable limits of concentrations of many soil
contaminants depending on the intended use of the soil.
Mushroom (pleurotus tuber regium) serves as an important source of food for a variety of
animals ranging from insect to large mammalian herbivore such as Deer (Alexopolus et al,
1996). It is often used in thickening popular agusi – melon soup and serves as a substitute for
egusi – melon (cigrullus vulgaris) in south eastern Nigeria (Nwokolo, 1987; Okhuoya and
Isikhwemhen, 1999). It is a good source of vitamins, minerals low in sugar, lowers blood
cholesterol (Kenada and Tokuda, 1996), and a selective medicinal for diabetes (Bano, 1976;
change and miles, 1982; Gupta, 1989) as well as contributes to longevity in human being
(Flynm, 1991).
Mushroom contains quality good protein, low fat content and contains vitamins B1, B2
and C. It also has effects on tumours, blood pressure and viruses. It has ability to degrade lignin
and cellulose. Emuh (2009) reported that mushroom inoculated in locally sourced substrates
showed promise in bioremediation of hydrocarbon polluted soil.
This paper seeks to examine the efficiency of different species of mushroom applied on the
surface of a soil for bioremediation of PAHs.
MATERIALS AND METHOD
Description of Study
The Poly-Aromatic Hydrocarbon (PAHs) used for this experiment was obtained from
Nigeria National Petroleum Company (NNPC) in Port Harcourt, Rivers State. The Mushrooms
used were bought from Santana Market in Benin, Nigeria. The experimental cells were located
at the University Research Green House in Niger Delta University, Bayelsa State. Electrical
weighing and electronic balance was used to determine the density of the PAHs and also the
volume of mushroom used. A mathematical model was developed to describe the remediation
process.

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Design of Experiment
The soil was divided into 6 treatment cells that were made into 6 different containers,
each with dimension 0.2m x 0.2m and tilled to a depth of 0.1m. The different beakers of samples
were coded as AS-1 to AS-6. The beakers were use in order to control the temperature,
concentration, moisture content simultaneously (Mattewson Grubbs, 1998).
Soil Treatment
Poly aromatic hydrocarbon that obtained from Department of Petroleum Resources
(DPR) in NNPC is added to each treatment cell. The cells were left undisturbed for three days,
at the end of which the treatment options were then applied. The three day period allows
degradation to commence and follows from the work Odokuwa Dickson (2003).
Soil Sampling
Different random spot were augured using a 9 – inch hand due soil anger capable of
obtaining uniform cores of equal volume at the desired depths (Smith and Atkinson 1975),
bulked together (composite soil samples) and put in well labeled polyethylene bags. The samples
for total Hydrocarbon Content (THC) measurement were placed in 1L glass bottles and sealed
with aluminium foil to ensure accurate results. This procedure was done 3 times to form
replicates. The bags and glass bottles were immediately transferred to the laboratory for analysis.
The procedure is similar to that reported by Odokuwa and Dickson (2003).
Mushroom Application
Different types of mushroom were applied, broadcast to the relevant cell and worked into
10cm depth in each cell. Various quantities of mushroom applied to the different cells are noted
earlier in this work. About 100g of the mushroom substrate was applied once in 6 weeks to cells.
These quantities of mushroom supplied nitrogen to the cells for the 10 week remediation period.
In a related study, Odokuma and Dickson (2003) applied a total of 400kg/ha of mushroom
substrate to the relevant cells for a 9 week remediation period.
Tilling
The entire cells were tilled twice in a month to provide necessary aeration and adequate
mixing of nutrients and microbes with contaminated soil. The tilling was tone in line with
Christofi et al. (1998) which reviewed that agro-technical method such as tilling and loosening
provides proper aeration that could decrease the contamination level due to the oxidation of
easily degradable petroleum components.
Laboratory Methods
Soil physiochemical parameters such as: Moisture content, PAH, Total Hydrocarbon
content (THC), Total Organic Content (TOC), soil pH, were determined using standard methods.
The parameters obtained were used as indices for evaluating the levels of pollution and
remediation. Soil samples collected from the remediation cells were air-dried, homogenized and
made to pass through a 2mm mesh sieve.

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Model Derivation
The degradation of non-conservative substance is usually modeled as a first-order
reaction. It is assumed that the rate of loss of substance is proportional to the amount of
substance that is present (Gilbert, 2006).
Considering a steady state system with non-conservative pollutant, many contaminants
undergo biochemical reactions at a rate sufficient to treat them as a non-conservative substance.
Using the mass balance principle,
[Soil + PAHs] + Mushroom Substrate k Gases + Heat + New biomass
k = Rate of reaction, PAHs is the Pollutant
The bioremediation of PAHs from soil is dependent upon temperature, moisture content,
pH and THC of the soil as well as mushroom substrate.
Applying the principle of mass balance
Input of Poly aromatic hydrocarbon to soil = output rate + Disappearance due to biochemical
reaction + Accumulation (1)
Let PC0 = Input of PAH to the soil
Input = PC0 (2)
Let PC= Output of Poly aromatic hydrocarbon from the soil
Output = PC (3)
Let a = Rate of disappearance due to biochemical reaction
a = MSV (4)
Where, MS = Mushroom Substrate, V = Volume
Let g = Rate of accumulation
g =
(5)
Where, = Volume of soil
Substituting Eq. 2 to 5 into Eq. 1 we have

5. (6)
Dividing all through Eq. 6 by V

6. (7)

7. (8)

8. (9)
If C = 0 for complete removal of contaminant from the soil.
As C0 tends to C, we have:

9. (10)

10. (11)
Where Km = rate of degradation
(12)
The above equation can be solved using separation of variable method.

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(13)
Integrating both sides of Eq.13
14
In
(14)
In ! (15)
In (16)
(17)
Taking exponential on both sides of equation
#$% (18)
Therefore, the Model Equation can be written as: #$% (19)
Where,
C0 = Initial concentration of PAH (mg/L)
C = Final concentration of PAH (mg/L)
km = Reaction coefficient (time-1)
t = Time in weeks
Linearizing Eq. 19 we have
ln PAH = -kt + ln PAH(0) (20)
Where ln PAH = Final Concentration of PAH
ln PAH(0) = Initial Concentration of PAH
Comparing Eq. 20 with the general linear equation y = mx + c
y = ln PAH, m = gradient = k or rate of degradation
x = Time
c = Intercept = ln PAH(0)
Therefore, a plot of final concentration of PAHs in mg/L vs Time gives the km values using 100g
of Mushroom.
RESULT AND DISCUSSION
Table 1: Initial Assessment of Soil
Percentage (%) pH
1 : 2.5
EC
(μ/cm)
Percentage (%) C/N Ratio
Sand Silt Clay Moisture
content
Organic C Total N
13.7±0.5 41±0.2 45±0.5 14±1 4.65±0.1 29±2 0.18±0.02 0.62±0.3 0.4±0.01
Results represent the means ± standard deviation of three replicates

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Table 2: Physiochemical Characteristics of soil after contamination, prior to remediation
Percentage (%) pH
1 :
2.5
EC
(μ/c
m)
Percentage (%) C/N
Rati
o
Potassiu
m
(cμ/kg)
PAHs (ppm)
Sand Silt Clay Moisture
content
Organic
C
Total N
79.0 10.0 11.0 20.48 5.8 4.71 0.49 0.13 4 1.29 120.23
±0.007
Results represent the means ± standard deviation of three replicates
Tables 1 and 2 shows the experimental results obtained from the initial assessment of the
soil and the soil characteristics after contamination. The soil pH level is 4.65 which indicate
acidic condition and it does not favor bioremediation.
Table 3: The PAHs Concentration in treated soil using 100g of Mushroom Substrate
Table 3 shows the effect of mushroom on bioremediation and indicates that mushroom
substrate is time dependent in bioremediation. This is in agreement with the findings of Olatunji
and Horsfall (2013).
Table 4: Rate of reaction Constants (km)
Mushroom Substrate km (day-1)
Saprophytic 0.3523
Parasitic 0.3751
Symbiotic 0.3603
Time (weeks)
PAHs Concentration (mg/L) in soil treated by Mushroom
Parasitic
Mushroom
Saprophytic
Mushroom
Symbiotic
Mushroom
0 131.42 131.42 131.42
2 89.21 78.26 77.48
4 40.94 42.52 46.53
6 19.71 27.37 28.50
8 10.74 13.92 12.55
10 2.84 2.92 2.77

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16
The rates of reaction constants were obtained from the graph of ln PAHs vs time, where
Km is the slope of the graph. Figs.1-3 are plotted from the linearized equation of the
mathematical model (Eq. 19). The km values (Table 4) show that saprophytic mushroom will
degrade PAHs faster than parasitic and symbiotic mushrooms of 100g.
Table 5: Calculated values of PAH for 100g of Mushroom Substrate using Eq. 19
Time
(Weeks)
Residual concentration of PAHs (mg/L)
Symbiotic
Parasitic
Saprophytic
0 120.230 120.230 120.230
1 83.8565 82.6245 84.8300
2 58.4871 56.7813 59.4300
3 40.7928 39.0213 41.7837
4 28.4517 26.8162 29.3768
5 19.8441 18.4281 20.6539
6 13.8406 12.6645 14.5212
7 9.65337 8.70334 10.2094
8 6.73290 5.98111 7.17790
9 4.69598 4.11043 5.04656
10 3.27529 2.82471 3.54808
Simulation in MATLAB using the initial PAHs concentration of 120.23mg/L and the
mathematical model developed.
The result (Table 5) shows that there is a strong but negative correlation between time
and concentration of PAHs. The correlation between time and concentration of PAH for
saprophytic, parasitic and symbiotic mushroom are 0.9704, 0.9868 and 0.9701 respectively.
Similarly, Chi-square goodness of fit shows values of 0.0102, 0.0202 and 0.0065 respectively.

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Analysis of fit fit 1 for dataset Cpa vs. t with Ex
0 1 2 3 4 5 6 7 8 9 10
17
140
120
100
80
60
40
20
0
F it
fit 1
Cpa vs. t with Ex
0
-10
-20
-30
-40
-50
1s t d eriv
Fig. 1: Analysis of fit1 for the Concentration of Parasitic Mushroom versus Time
The Chi-test result shows that the model is valid and it can be used to predict the rate of
bioremediation of PAHs using mushroom as a remediating agent. As X2 tends to zero the closer
the calculated value to the experimental data of PAHs concentration.

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Analysis of fit fit 1 for dataset Cpa vs. t with Ex
fit 1
Cpa vs. t with Ex
0 1 2 3 4 5 6 7 8 9 10
Analysis of fit fit Symbiotic Mushroom in Bioremediation for dataset Csm vs. t with E
fit Symbiotic Mushroom in Bioremediation
0 1 2 3 4 5 6 7 8 9 10
18
140
120
100
80
60
40
20
0
Fit
Fig. 2: Analysis of fit1 Showing Experimental Result of the Concentration Parasitic
Mushroom against Time
140
120
100
80
60
40
20
0
Fit
0
-10
-20
-30
-40
-50
1st deriv
Fig. 3: Analysis of fit2 for the Concentration of Symbiotic Mushroom versus Time

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Time [Weeks] Concentration [mg/L]
19
140
120
100
80
60
40
20
0
-10
-20
-30
-40
Fig. 4: Analysis of fit3 for dataset; calculated value vs experimental values for Parasitic
Mushroom
140
120
100
80
60
40
20
Fig. 5: The effect of Parasitic Mushroom in bioremediation PAH for experimental and
calculated values
0
Fit
Analysis of fit fit 1 for dataset Cpa vs. t with E3
fit 1
Cpa vs. t with E3
0 1 2 3 4 5 6 7 8 9 10
-50
1st deriv
0 2 4 6 8 10 12 14
0
Parasitic Mushroom in Bioremediation of PAHs
Calculated values
Experimental values

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0 2 4 6 8 10 12 14
20
140
120
100
80
60
40
20
Fig. 6: The effect of Symbiotic Mushroom in bioremediation PAH for experimental and
calculated values
140
120
100
80
60
40
20
Fig. 7: The effect of Saprophytic Mushroom in bioremediation PAH for experimental and
calculated values
0
Time [Weeks]
Concentration [mg/L]
Symbiotic Mushroom in Bioremediation of PAHs
Calculated values
Experimental values
0 2 4 6 8 10 12 14
0
Time [Weeks]
Concentration [mg/L]
Saprophytic Mushroom in Bioremediation of PAHs
Calculated values
Experimental values

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Moisture content (mg/g) in soil treated by Mushroom
Parasitic Saprophytic
Symbiotic
0 20.5 20.5 20.5
2 22.38 23.32 20.38
4 20.33 19.31 18.35
6 14.35 14.48 14.42
8 14.27 14.27 14.14
10 14.27 14.17 14.12
pH (1: 2.5) in soil treated by Mushroom
Parasitic
Saprophytic Symbiotic
0 5.80 5.80 5.80
2 6.42 6.58 6.41
4 6.40 6.51 6.40
6 6.39 6.52 6.40
8 7.03 6.91 7.15
10 7.07 7.06 7.19
21
Moisture Content
Table 6 and 7 shows the effect of mushroom on moisture content and pH of the soil in
bioremediation of PAHs respectively.
Table 6: Moisture content in treated soil using 100g of Mushroom Substrate
Time (weeks)
Table 7: pH (1 : 2.5) in treated soil using 100g of Mushroom Substrate
pH Effect
Time
(weeks)
The pH of contaminated sites can often be linked to the pollutant. The result shows that
there is no significant change in pH as time increases. In a duration of 3 months, the pH value
increased from 5.8 – 7.1 which indicates a favorable condition for bioremediation.
CONCLUSIONS
From the results obtained it could be deduced that from the numerical computation and
model validation, there is a strong correlation between the experiment and the mathematical
model for the bioremediation of Poly Aromatic Hydrocarbons polluted soil with mushroom
substrate. The mathematical model developed can be used to predict the rate of remediation of
PAHs polluted soil using mushroom as a remediating agent.

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