Download prediction of concentration profiles of contaminants in groundwater

IJRRAS 15 (3) ● June 2013
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PREDICTION OF CONCENTRATION PROFILES OF CONTAMINANTS
IN GROUNDWATER POLLUTED BY LEACHATES FROM A LANDFILL
SITE
Lukmon Salami 1, Olaosebikan A. Olafadehan2, Gutti Babagana3 & Alfred A. Susu4*
Department of Chemical and Polymer Engineering, Lagos State University, Epe, Lagos, Nigeria
2,4
Department of Chemical Engineering, University of Lagos, Akoka, Yaba, Lagos, Nigeria
3
Department of Chemical Engineering, University of Maiduguri, Maiduguri, Borno State, Nigeria
*
Corresponding author: Professor Alfred A. Susu, [email protected]
1
ABSTRACT
Point sources such as landfills can release high concentration of contaminants into the groundwater because of
migration of leachate from its bottom. The leachate is generated primarily as a result of precipitation on an active
landfill surface, leading to the transport of organic and inorganic contaminants from landfill waste which is
subsequently discharged into groundwater in underlying aquifer. Landfill leachate has the potential to contaminate
the surrounding environment and impair groundwater use. A one dimensional transport model was used to predict
the concentration profiles of contaminants groundwater polluted by leachates from a landfill site using the finite
difference approach implemented in Matlab 7.0. The concentration profiles for organic and inorganic pollutants
indicated similar profiles, rising to a maximum with time and distance from the landfill. Three dimensional images
were generated for the concentration profiles of all the contaminants. The data provided by Jhnamnani and Singh
(2009) were used for the comprehensive prediction in this work.
Keywords: Leachate; Landfill; Contaminants; Groundwater; Prediction of contaminant concentration profiles;
Finite difference method.
1. INTRODUCTION
A landfill site is a site for the disposal of waste materials by burial. It is also the oldest form of solid waste treatment.
Historically, landfills have been the most common methods of organized waste disposal and remain so in many
places around the world. Landfills may include internal waste disposal site (where a producer of waste carries out
their own waste disposal at the place of production) as well as sites used by many producers. Many lands are also
used for waste management purposes, such as the temporary storage consolidation and transfer or processing of
waste materials (sorting, treatment or recycling).
Areas near landfills have a greater possibility of groundwater contamination because of the potential pollution
source of leachate originating from the landfill site. Such contamination of groundwater resource poses a substantial
risk to public health and to the natural environment. The impact of landfill on the surface and groundwater has given
rise to a number of studies in recent years (Saarela, 2001; Abu and Kofahi, 2001; Booser et al., 1999; Christensen et
al., 1998; De Rosa et al., 1996 and Flyhammer, 1995). Many approaches have been used to assess the contamination
of underground water. It can be assessed either by the experimental determination of the impurities or their
estimation through mathematical modeling (Moo-Young et al., 2004, Hudak, 1998 and Stoline et al., 1993). Rain
falling on the top of the landfill is the main contributor to the generation of leachate and is by far the largest
contributor for modern sanitary landfills which do not accept liquid waste (Jhnamnani and Singh, 2009). In old
unlined and un-engineered landfills, some leachates are produced during waste decomposition; additionally, surface
water from surrounding water system, can sometimes run onto the waste (Renou et al., 2008). The decomposition of
carbonaceous materials produces some additional water and a wide range of other materials including methane,
carbon dioxide and a complex mixture of organic acids, aldehydes, alcohol and simple sugars, which dissolve in the
leachate cocktail. The precipitation percolates through the waste and takes in dissolved and suspended components
from the biodegrading waste, through physical and chemical reactions (Jhnamnani and Singh, 2009).
The environmental risks of leachate generation arise from it escaping onto the environment around landfills,
particularly to waste courses and groundwater. These risks can be mitigated by properly designed and engineered
landfill sites. Such sites are those that are constructed on geologically impermeable materials or sites that use
impermeable liners made of geotextile or engineered clay (Anne and Fred, 1993). The use of linings is now
mandatory within both the United States and the European Union, except where the waste is closely controlled and
genuinely inert (Anne and Fred, 1993). Most toxic and difficult materials are now specifically excluded from landfill
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IJRRAS 15 (3) ● June 2013
Salami & al. ● Prediction of Concentration Profiles of Contaminants
(EPA, 1997). However, despite much stricter statutory controls, the leachates from modern sites are currently
stronger than ever as they contain a huge range of contaminants. In fact, anything soluble in the waste disposed will
enter the leachate (EPA, 1995). Therefore, the aims and objectives of this work are: (i) the study of the natural
attenuation of inorganic contaminants and (ii) the prediction of the contaminants concentration in subsurface region
and groundwater. The predictive model uses the data generated by Jhamnani and Singh (2009) to produce three
dimensional profiles of contaminant concentration in groundwater.
If the concentration of contaminants in groundwater can be predicted, it helps to put in place remediation measures
and proper waste management. The prediction of groundwater contaminants concentration therefore serves as a tool
to sanitise our environment and improve the quality of human life.
2. THEORY AND NUMERICAL SIMULATION
The governing one dimensional mass transport model used in this work was based on the dispersion model
developed by Jhamnani and Singh (2009) and is presented in Equation (1). This equation was solved using finite
difference method implemented on Matlab 7.0. The data for the characteristics of leachate for Bhalaswa landfill site
and groundwater samples from nearby locations (Jhamnani and Singh, 2009) are shown in Table1. The model
parameters are also taken from the same source and depicted in Table 2 and they were used for the simulation of
contaminants migration from the landfill.
Table1. Characteristics of Leachate from Bhalaswa landfills site and groundwater samples from nearby location
Concentration
in Landfill
Leachate
Parameters
Concentration in groundwater samples at radial distance from landfill facility
≤75m
75-500m
500m1000m
1000m1500m
Iron
20
7.04
6.53
5.11
3.61
(mg/L)
Copper
<10
0.1
0.08
0.06
0.05
(mg/L)
Nickel
<3
0.43
0.32
0.22
0.13
(mg/L)
Zinc
<10
3.37
3.27
2.14
1.11
(mg/L)
Chloride
4000
1174.2
1032.24
845.45
543.12
(mg/L)
Source: International journal of civil and environmental engineering (2009), 1(3):122
S/N
1
2
3
4
5
6
7
8
Table 2
Model parameters for simulation
Model Parameter
Unit
Value
Time
S
50
Molecular diffusion coefficient
m2/yr
0.027
Mechanical dispersion coefficient
m2/yr
0-075
Effective molecular diffusion coefficient
m2/yr
0-02
Dispersivity
M
0.15
Advective velocity
m/yr
0.5
Hydrodynamic dispersion
m2/yr
0.095
Porosity
0.4
9
Retardation factor
10
Equivalent height of leachate
M
10
11
t
S
1
12
z
M
1.5
1
366
1500m2000m
2000m5000m
1.73
0.64
0.02
0.01
0.43
0.43
0.06
0.02
324.23
135.36
IJRRAS 15 (3) ● June 2013
Salami & al. ● Prediction of Concentration Profiles of Contaminants
Source: International journal of civil and environmental engineering,(2009),1(3):124
C Dh  2 C
v C


2
t
R f z
R f z
where Dh = hydrodynamic dispersion coefficient
(1)
 = dispersivity
v = advective velocity
Rf = retardation factor
Equation (1) in finite difference form can be written as:
c
m 1
i
c
m 1
i

D C
R 
m

t
Making
C
 ci
f
m 1
i

m
i 1
h
m
m
Cm  Cm 
 2 C i  C i 1 
v
i 1
 
 i

2
2

z



Rf 
z

 
(2)
the subject in equation (2); it yields:
C
D t Cm  2Cm  Cm   vt C
i 1
i
i 1
2 R f z
R z 
D t
R z 

m
i
h
2
m

 Ci 1
m
i 1
(3)
f
h
Let A =
(4)
2
f
vt
2 R f z
B=
(5)
Substitute Equations (4) and (5) into Equation (3) and applying upwind correction, by replacing the forward
difference in the 4th term with backward difference, we have:
C
m 1

i
C
m
i
 A
C
m

 2 Ci  Ci 1  2 B
m
i 1
m
C
m
i
 Ci 1
m

(6)
Expanding Equation (6); it becomes:
C
m 1
i

C
m
i
 A C i 1  2 AC i  A C i 1  2 B C i  2 B Ci 1
m
m
m
m
m
(7)
Grouping Equation (7); it gives:
C
m 1
i
 1  2 A  2 B 
C
m
i
 A C i 1   A  2 B  C i 1
m
m
(8)
Equation (8) is the explicit finite difference approximation for the system.
The value of t and z are chosen in such a way that the stability criteria of Equation (9) is satisfied.
Dzt
vzt 1


2
Rf z  2 Rfz 2
(9)
The boundary condition (BC) is:
CT t   C 0 
1
Hf
 f c,  d
t
(10)
t
0
Where CT = concentration of contaminant in source at any time t
C 0 = initial concentration of contaminant in source
Hf = equivalent height of leachate
The initial condition (IC) is:
(11)
C z, o   0
According to Jhamnani and Singh (2009), advective dispersion transport in one dimension can be express as:
fT c,   nvzc  nDh
c
z
(12)
The negative sign arises from the fact that the contaminant move from high to low concentrations. The total mass of
contaminant transported out of the landfill up to some specific time t is obtained by integrating Equation (12).
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IJRRAS 15 (3) ● June 2013
Salami & al. ● Prediction of Concentration Profiles of Contaminants
Putting Equation (12) into Equation (10) yields:
1
CT t   C 0 
Hf
t

(nvzc  nDh
0
c
)d
z
(13)
Applying numerical method to Equation (13), we have:
t
c
 t

(14)
v
C
(
0
,
t
)

t

D
(0, t )t 
h
 z T
t 0 z
 t 0

c
Assuming the concentration gradient,
 0 (Jhamnani and Singh, 2009); Equation (14) reduces to:
z
t
n
CT (0, t )  Co 
vz  CT (0, t )t
(15)
H f t 0
CT (0, t )  Co 
n
Hf
Equation (15) can be written as:
t 1
 n

n
CT (0, t )  Co  
vz  CT (0, t )t 
vzCT (0, t )t 
Hf
 H f t 0

(16)
Rearranging Equation (16), it gives:
CT (0, t ) 
t 1
n
n
vzCT (0, t )t  Co 
vz  CT (0, t )t
Hf
H f t 0
(17)
Factorising the LHS of Equation (17), we have:
t 1


n
n
1

v

t
C
(
0
,
t
)

C

v

 T
z
o
z  CT (0, t )t
H f t 0
 H f

t 1
n
Co 
v z  CT (0, t )t
H f t 0
CT (0, t ) 


n
v z t 
1 
 Hf

(18)
(19)
3. RESULTS
The predictions of the variation of chloride concentration with time (at various depths) and distance (at various
times) from the landfill are shown in Figures 1 and 2, respectively. The work of Jhamnani and Singh (2009) only
showed the chloride concentration with time at only one depth of 5m below the bottom of the landfill. Our approach
allowed us to indicate a 3-D chloride profile with distance and time (Figure 3). Figure 2 showed quite clearly that
chloride concentration was negligible beyond a distance of 25m from the landfill for up to 30 years of operation of
the landfill.
We report in Figure 3 the 3-D profiles for chloride concentration with depth and time as variables. The advantage of
depicting the profiles for various depths indicates that the shape of the profile was retained, except that the
maximum decreased with time. We also showed the profiles for the heavy metals because of its impact on public
health.
Figures 4, 5 and 6 show the predicted zinc profiles from an initial value of <10 mg/L in the leachate concentration.
Figures 7, 8 and 9 show corresponding profiles for nickel (initial leachate concentration of <3 mg/L), Figures 10, 11
and 12 for copper (initial leachate concentration of <10 mg/L) and Figures 13, 14 and 15 for iron (initial leachate
concentration of 29 mg/L). All of the profiles for the heavy metals replicated all the features predicted for the
chloride profiles.
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IJRRAS 15 (3) ● June 2013
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Variation of chloride concentration with time at varying depths
chloride concentration (mg/L)
1500
depth
depth
depth
depth
depth
depth
1000
= 5m
= 10m
= 15m
= 20m
= 25m
= 30m
500
0
0
10
20
30
time (years)
40
50
60
Figure 1. Variation of chloride concentration with time
Variation of chloride concentration with distance
1800
time
time
time
time
time
time
chloride concentration (mg/L)
1600
1400
1200
= 5 years
= 10 years
= 15 years
= 20 years
= 25 years
= 30 years
1000
800
600
400
200
0
0
5
10
15
distance (meters)
20
Figure 2. Variation of chloride concentration with distance
369
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concentration-distance-time graph for chloride
2000
chloride concentration (mg/L)
1800
2000
1600
1400
1500
1200
1000
1000
500
800
600
0
200
400
150
60
100
50
distance (in meters)
200
40
20
0
0
0
time (in years)
Figure 3. Concentration – distance – time graph with time for chloride
Variation of zinc concentration with time at varying depths
4
depth
depth
depth
depth
depth
depth
zinc concentration (mg/L)
3.5
3
= 5m
= 10m
= 15m
= 20m
= 25m
= 30m
2.5
2
1.5
1
0.5
0
0
10
20
30
time (years)
40
50
Figure 4. Variation of zinc concentration with time
370
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IJRRAS 15 (3) ● June 2013
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Variation of zinc concentration with distance
4.5
time
time
time
time
time
time
4
zinc concentration (mg/L)
3.5
3
= 5 years
= 10 years
= 15 years
= 20 years
= 25 years
= 30 years
2.5
2
1.5
1
0.5
0
0
5
10
15
distance (meters)
20
25
Figure 5. Variation of zinc concentration with distance
concentration-distance-time graph for zinc
5
zinc concentration (mg/L)
4.5
5
4
4
3.5
3
3
2
2.5
2
1
1.5
0
200
1
150
60
100
40
50
distance (in meters)
20
0
0
0.5
0
time (in years)
Figure 6. Concentration – distance – time graph with distance
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Variation of nickel concentration with time at varying depths
0.8
depth
depth
depth
depth
depth
depth
0.6
0.5
0.4
0.3
0.2
0.1
0
0
10
20
30
time (years)
40
50
60
Figure 7. Variation of nickel concentration with time
Variation of nickel concentration with distance
0.9
time
time
time
time
time
time
0.8
0.7
nickel concentration (mg/L)
nickel concentration (mg/L)
0.7
= 5m
= 10m
= 15m
= 20m
= 25m
= 30m
0.6
= 5 years
= 10 years
= 15 years
= 20 years
= 25 years
= 30 years
0.5
0.4
0.3
0.2
0.1
0
0
5
10
15
distance (meters)
20
Figure 8. Variation of nickel concentration with distance
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concentration-distance-time graph for nickel
1
nickel concentration (mg/L)
0.9
1
0.8
0.8
0.7
0.6
0.6
0.4
0.5
0.4
0.2
0.3
0
200
0.2
150
60
100
50
distance (in meters)
0.1
40
20
0
0
0
time (in years)
Figure 9. Concentration-distance-time graph for nickel
Variation of copper concentration with time at varying depths
0.8
depth
depth
depth
depth
depth
depth
copper concentration (mg/L)
0.7
0.6
= 5m
= 10m
= 15m
= 20m
= 25m
= 30m
0.5
0.4
0.3
0.2
0.1
0
0
10
20
30
time (years)
40
50
Figure 10. Variation of copper concentration with time
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Variation of copper concentration with distance
0.9
time
time
time
time
time
time
copper concentration (mg/L)
0.8
0.7
0.6
= 5 years
= 10 years
= 15 years
= 20 years
= 25 years
= 30 years
0.5
0.4
0.3
0.2
0.1
0
0
5
10
15
distance (meters)
20
25
Figure 11. Variation copper concentration with distance
concentration-distance-time graph for copper
1
copper concentration (mg/L)
0.9
1
0.8
0.8
0.7
0.6
0.6
0.4
0.5
0.4
0.2
0.3
0
200
0.2
150
60
100
40
50
distance (in meters)
20
0
0
0.1
0
time (in years)
Figure 12. Variation-distance-time graph for copper
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Variation of iron concentration with time at varying depths
8
depth
depth
depth
depth
depth
depth
iron concentration (mg/L)
7
6
= 5m
= 10m
= 15m
= 20m
= 25m
= 30m
5
4
3
2
1
0
0
10
20
30
time (years)
40
50
60
Figure 13. Variation of iron concentration with time
Variation of iron concentration with distance
9
time
time
time
time
time
time
8
iron concentration (mg/L)
7
6
= 5 years
= 10 years
= 15 years
= 20 years
= 25 years
= 30 years
5
4
3
2
1
0
0
5
10
15
distance (meters)
20
Figure 14. Variation of iron concentration with distance
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concentration-distance-time graph for iron
11
10
9
10
8
8
7
6
6
4
5
2
4
0
200
3
iron concentration (mg/L)
12
150
60
100
40
50
distance (in meters)
20
0
0
2
1
0
time (in years)
Figure 15. Concentration-distance-time graph for iron
4. DISCUSSION
The average concentrations of chlorides and heavy metals in leachate from Bhalaswa landfill site and in the
groundwater samples at varying radial distances from the landfill are shown in Table 1. The average concentration
of chlorides in the leachates from the Bhalaswa landfill site has been found to be 4000mg/L. For the purpose of
simulation, the maximum concentration has been taken as 2000mg/L as the landfill has been started about 15 years
back, with continuous addition of landfill mass at the top of it, resulting in progressive increase of its height to the
present day condition of about 22m height (Jhamnani and Singh, 2009). Use of maximum concentration of chlorides
as 2000mg/L thus seems quite reasonable (Thamnani and Singh, 2009). The maximum concentrations of copper,
nickel and zinc were less than 10mg/L respectively while that of iron was 20mg/L. The use of maximum
concentration of copper, nickel, zinc and iron as 0.1mg/L, 5.0mg/L, 5mg/L and 11mg/L respectively thus seems
quite reasonable considering the concentration in ground water samples at radial distance.
It can be seen that the variation of contaminants concentration show behaviour typical of a convectional landfill
system. Simulated contaminants concentration in groundwater below the landfill facility increases, reaches a peak
and then declines. Figures 1 and 2 show the variation of chlorides concentration with time and distance in landfill
leachates while Figure 3 shows the concentration – distance – time graph for chloride. The graphs show the typical
shape of a variation of contaminants with time and distance in landfill leachates. It was observed that as the depth
increases, the time taken for the appearance of contaminants increases, that is, the depth is directly proportional to
the time of appearance of contaminants. From Figure 1 it can be seen that at a depth of 6m, the concentration of
chloride is about 1,150mg/L at the end of 15 years. The observed concentration of 1,174.2mg/L for chloride appears
to be quite in agreement with the simulated concentration. At the age of 50years, the concentration of chloride at the
depth of 6m will be about 500mg/L. From Figure 2, the concentration of chloride at the age of 5 years is the highest
which is attributed to the fact that as time increases, the concentration of contaminants decreases with increase in
depth.
Figures 7 and 5 show the variation of zinc concentration with time and distance, respectively while Figure 8 shows
the concentration - distance - time graph for zinc. The graphs also show the typical shape of variation of
contaminants with time and distance, in landfill leachates. It was observed that as the depth increases, the time taken
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for the appearance of contaminants increases which is in line with the chloride variation. From Figure 4, it can be
seen that at a depth of 6m, the concentration of zinc is about 3.2mg/L at the age of 15years. The observed
concentration of 3.37mg/L appears to be quite in agreement with the simulated concentration. At the age of 50 years,
the concentration of zinc at the depth of 6m will be about 1.3mg/L. From Figure 5 the concentration of zinc at the
age of 5 years is the highest which is in line with the fact that as time increases, the concentration of contaminants
decreases with increase in depth.
Figures 7 and 8 show the variation of nickel concentration with time and distance respectively while Figure 9 shows
the concentration – distance – time graph for nickel. The graphs portray the typical shape expected for variation of
contaminants in landfill leachates. It was also observed that as the depth increases, the time taken for the appearance
of the contaminants increases. From Figure 9 the concentration of nickel at 6m depth is 0.6mg/L at the age of
15years while the observed concentration is 0.43mg/L. At the age of 50 years, the concentration of nickel at the
depth of 6m would have reduced to about 0.35. From Figure 8 the concentration of nickel at the age of 5 years is the
highest while the lowest concentration is at the age of 30 years.
Figures 10 and 11 show the variation of copper concentration with time and distance respectively while Figure 12
shows the concentration – distance – time graph for copper. The graphs are in line with the typical shape expected of
contaminants variation in landfill leachates. From Figure 10 the concentration of copper at the depth of 6m, at the
age of 15years is about 0.58mg/L. The observed concentration of 0.1mg/L appears to deviates from the simulated
concentration of approximately 0.58mg/L. At the age of 50years, the concentration of copper at the depth of 6m
would have reduced to 0.25mg/L. From Figure 11 the concentration of copper at the age of 5years is the highest
while the lowest concentration is at age of 30years which follows the same pattern with other contaminants.
Figures 13 and 14 show the variation of iron concentration with time and distance respectively while Figure15
shows the concentration-distance-time graph for iron. The shapes of the graphs are in line with the shape of the
graph of other contaminants in landfill leachates. From Figure 13, the concentration of iron at the depth of 6m at the
age of 15years is about 6.8mg/L. The observed concentration of 7.04mg/L appears to be in agreement with the
simulated concentration. At the age of 50years, at the depth of 6m, the concentration of iron would have reduced to
about 2.8mg/L. From Figure 14, the concentration of iron at the age of 5years appears to be the highest while the
lowest concentration is at 30years which is in line with the other contaminants from landfill leachates.
5. CONCLUSION
The simulated concentrations of contaminants due to leachate are in consonance with the observed concentrations of
contaminants due to leachate. The developed one dimensional transport model can be used as a tool to predict the
concentrations of contaminants due to leachates in soil and groundwater. The natural attention of inorganic
contaminants reduces the health and environmental risk posed by these contaminants by changing the amount of
exposure, the exposure pathway or the toxicity of the chemicals.
The leachate from Bhalaswa landfill is also of low quality because it exceeded the threshold limit set by the
regulatory body. As the depth increases, the concentrations of contaminant in leachate decrease with increase in
time. It is therefore necessary to dig a high depth to source for groundwater. However, the observed chloride
concentration in groundwater at a radial distance less than 75m was 1174.2mg/L while it was 135.36mg/L at
distance in the range of 2000-2500m. Moreover, the observed concentration in groundwater at a distance less than
75m was 0.1mg/L while it was 0.001mg/L at a radial distance in the range of 2,000 – 2,500m. As we move away
from landfill locations, the concentrations of contaminants decrease that is the concentrations of contaminants due to
leachate is directly proportional to radial distance from landfill facility. Therefore, human activities should take
place at a distance form landfill sites.
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IJRRAS 15 (3) ● June 2013
Salami & al. ● Prediction of Concentration Profiles of Contaminants
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