 
Ecological Chemistry. St. Petersburg, Russia
SIMULATION OF HEAVY METALS MIGRATION IN PEAT DEPOSITS
I.L. Kharkhordin and F.G. Atroshchenko
St. Petersburg department of the Geology Institute of Russian Academy of Sciences,
196199 St. Petersburg
Interdepartmental Scientific Centre of Hydrogeoecology, St. Petersburg State University,
199178 St. Petersburg
(Accepted for publication September 30, 1998)
The problems of computer simulation of heavy metals migration in swamp deposits is considered taking as
an example a site at slime storage of the Arkhangelsk Thermal Power Station. Some principal results of the
simulation were found. Heavy metals in swamp and bog deposits are mainly in the sorbed state. The ratio of
sorbed to dissolved forms is 10
3
–10
4
. In low3lying swamps with near3neutral medium, peat exhibits consid3
erable buffer capacity with respect to both acid and alkaline solutions. In the initial migration state, heavy
metals concentration in water is virtually independent of their content in waste and is determined by the
composition of the exchange complex in peat. At low heavy metals concentrations in waste, interaction with
peat can lead either to their sorption or to their accumulation in solution. If the initial metal concentration
exceeds the first milligrams per litre, processes of self3purification predominate.
Key words: swamp deposits, heavy metals, slime storage, ion exchange, computer simulation.
Introduction
The prediction of changes in the chemical
composition  of  water  in  its  interaction  with
swamp deposits is necessary for solving many
practical  problems.  On  the  one  hand,  swamp
can accumulate heavy metals [1,2], radioactive
substances  [3],  and  oil  products.  Therefore,
they  can  be  used  as  slime  storage  spaces  and
places of incompletely purified waste and drill3
ing  water  discharge.  On  the  other  hand,  the
change  in  physico3chemical  conditions  in
swamp deposits under the effect of anthropo3
genic factors (drainage or flooding of swamps,
acid rains, etc.) can lead to desorption of toxic
elements previously accumulated in peat. The
aim of the present paper is to develop approach3
es  to  computer  simulation  of  these  processes
taking as an example a site of slime storage of
the  Arkhangelsk  Thermal  Power  Station
(ATPS).
Characteristic of the research location
Slime storage of ATPS is located in the delta of the
Northern Dvina River in the region of extensive swamp
deposits. It was constructed in the 1970s and is of a typ3
ical  dike  character.  The  discharged  material  differs  in
chemical  composition,  volume,  and  degree  of  toxicity.
Therefore,  the  storage  is  divided  in  three  sections:  1)
chemically  purified  water  (CPW)  about  130 thousand
m
3
in volume, 2) neutralized water (NW) — 50 thousand
m
3
in volume, 3) acid boiler washing water (AW) —
15 thousand m
3
in volume. At present only section CPW
and AW are used for discharging slime, and section NW
is  temporarily  closed.  Taking  into  account  the  ratio  of
solid to liquid phases in the discharged pulp, it was cal3
culated that in section CPW only 20% of capacity is filled
with slime, in section AW — about 10%, and in section
NW — not more than 2%. However, waste volume dis3
charged  into  these  sections  is  such  that  if  water  leaks
from  them  is  excluded,  as  is  required  the  Norms  and
Rules of designing these constructions [4], it would be
necessary  to  build  a  new  slime  storage  every  year.  At
present  the  level  in  this  storage  is  approximately  con3
stant. This implies that leak volume corresponds to the
volume of discharged waste and atmospheric precipita3
tion.  In  order  to  evaluate  the  effect  of  leaks  filtered
through the dike, extensive investigations were carried
out  including  testing  of  waste  and  pore  solutions  of
swamp deposits.
Chemical analyses were performed in the laboratory
of joint3stock society “Mekhanobr” by standard methods.
The  averaged  initial  composition  of  swamp  water  and
discharge to sections CPW and AW taken for simulation
is given in Table 1. We can note the following changes in
chemical composition near sections CPW and AW found
from data on hydrogeochemical testing.
1. Section CWP. In underground water the concen3
trations of magnesium and sulphate ions increased twice.
Manganese concentration increased four times, and Ni,
Co, and Zn appeared in quantities exceeding LAC two and
 
66
I.L. Kharkhordin and F.G. Atroshchenko
three times, although their concentrations in the section
itself are not high.
2. Section AW. During filtering swamp deposits, wa3
ter from this section is transformed indo weakly acid and
neutral  water  and  hydrobionts  appear.  The  concentra3
tions of Mo, V, Zn, and Cu decrease to LAC and the con3
centrations of Ni and Co to background values charac3
teristic of water of swamp deposits. The content of Co,
Mn, and Al changes only slightly.
3. Section NW. The transformation of chemical com3
position of water of this section in the swamp deposits is
accompanied by increasing concentration of Mn and Zn,
whereas Ni, Co, Mo, and Cu content decreases to LAC or
to background values.
Process of interaction between metal
ions and swamp deposits. Evaluation of
model parameters
For quantitative description and prediction
of  directions  of  further  changes  in  chemical
composition of underground water, computer
simulation of migration of solutions contain3
ing heavy metals in swamp deposits was devel3
oped.
In spite a long history of studying the proc3
esses of solutions interaction with humus ma3
terial, an effective procedure for their mathe3
matical description is not yet available. This
mainly due to complex structure of humic com3
pounds,  which  contains  various  functional,
groups [5]. It is also important that the com3
position of these compounds is variable. There3
for, it is impossible in principle to isolate indi3
vidual  humic  compounds  and  one  must  work
with  these  complex  mixtures.  For  instance,
according data in ref. [6], fulvic acids in natu3
ral  waters  migrate  in  the  form  of  associates
with molecular weight from 300 to 60000 (de3
pending on their concentration and pH of so3
lution). These authors suggest that monomers
of fulvic acids contain two or three carboxylic
(K
1
= 2
⋅
10
–3
, K
2
= 5
⋅
10
–5
) and one or two phenol
groups. The study of fulvic acids fractionation
on ion3exchange materials has shown that the
fraction  relatively  enriched  with  nitrogen  is
retained  by  cation  exchangers  at  pH  =  2  [7].
This  fact  indicates  that  nitrogen  is  predomi3
nantly  contained  in  amino3groups.  Cationic
groups in natural organic compounds are prob3
ably sorbed by clay minerals [8]. It is possible
that in this process hydrogen bonds and bonds
with the participation of metal ions are formed
It  is  established  that  mercapto3groups  are
present in peat. Their concentration depend on
redox conditions [10].
The complexation model is usually applied
for the mathematical description of interaction
of dissolved fulvic and humic acids with metal
ions.  However,  in  this  case  equilibrium  con3
stants are tentative and depend on the solution
composition,  in  particular  on  pH  [6].  This
makes it difficult to calculate the composition
of multicomponent systems. On the whole the
stability  constants  of  hydroxyfulvic  metal
complexes range from 10
3
to 10
11
increasing in
the following series:
Sr(II) < Ca(II) < Fe(II) < Ce(III) < Y(III) <
Cu(II) < Ru(IV) < Fe(III) < Sb(III) < Au(III) <
Hg(II) [11].
The model of cation exchange is generally
used to describe metal sorption on humic com3
pounds  in  the  solid  state  of  swamp  deposits.
Either the ternary system Me
I
3Me
II
3H
+
is con3
sidered  or  the  cation3exchange  system  is  re3
garded as a function of pH and solution com3
position. The principal investigation methods
are potentiometric titration of humic materi3
al in salt solution and experiments on ion ex3
change. It is observed that the mechanism of
chemical  bonding  of  metal  with  humic  acids
and with peat are not very different [12]. More3
Table 1
Model compositions of solutions
Waste waters
Index
Measuremen
t units
CWP
AW
Swamp
waters
(background)
t,
°
C
6.0
6.0
6.0
pH
9.0
3.6
7.03
HCO
3
–
mg
⋅
l
–1
206
2
206
Cl
–
–“–
74
500
27
SO
4
2–
–“–
399
750
20
Ca
2+
–“–
112
180
43
Mg
2+
–“–
25
45
2.5
Na
2+
–“–
148
364
34
Mn
2+
–“–
0.05
1.87
0.26
Ni
2+
–“–
0.002 17.37
0.001
Zn
2+
–“–
0.001
7.17
0.5
Cu
2+
–“–
0.001
0.71
0.0003
Pd
2+
–“–
0.002 0.086
0.002
Cd
2+
–“–
0.015 0.028
0.005
 
67
Simulation of Heavy Metals Migration in Peat Deposits
over,  most  metal  ions  retain  their  hydrate
shells and the bond is of electrostatic charac3
ter, whereas copper ions form predominantly
more stable covalent bonds. The absolute rate
of metals adsorption on peat decreases in the
following series: Pb
2+
> Cu
2+
> Cd
2+
> Zn
2+
>
Ca
2+
and the time of half3reaction of sorption
(desorption) ranges from 5 to 15 s [13].
In this work for the description of metals
migration in swamp deposits, the model of cat3
ion exchange is also used. Note that the model
of surface complexation is probably better suit3
ed to the natural process but at present in the
published  literature  the  quantity  of  experi3
mental  data  is  not  sufficient  to  evaluate  the
required constants.
The PHREEQC program [14] freely distrib3
uted by the USA Geological Service is used for
the simulation. This program makes it possi3
ble to calculate physico3chemical equilibrium
in  multiphase  and  multicomponent  systems
taking into account complexation in solution,
precipitation (dissolution) of minerals and ion
exchange. The user can introduce several types
of ion exchangers with different values of ex3
change constants. Particular attention should
be paid to the form of expression of constants
for ion exchange equilibrium in this program:
interactions  are  written  in  the  form  of  half3
reactions:
nX
–
+ Me
n+
= X
n
Me
and the law of mass action is corresponding3
ly expressed as
+
−
⋅
=
]
Me
[
]
X
[
]
Me
X
[
K
n
n
n
where [X] is the fictious activity of positions
in the exchange complex (value analogous to
electron activity in recording redox reactions
in the form of half3reactions), [Me
n+
] is the cat3
ion activity in solution, and [X
n
Me] is the ac3
tivity of the cation bound in the exchange com3
plex.  This  form  of  evaluating  ion3exchange
processes is more convenient for mathemati3
cal simulation and makes it possible to avoid
restrictions  appearing  when  usual  constants
for exchange of one cation by another are ap3
plied.  For  example,  it  is  necessary  to  enter  a
certain non3zero concentration for the “basic”
cation  through  which  the  expressions  of  ex3
change constants are written for other ions.
Exchange constants were evaluated by us3
ing the experimental results published in lit3
erature. Andre and Pijarovski [15] have car3
ried  out  the  most  complete  investigation  of
exchange equilibrium in peat at different pH
values with the participation of K
+
, NH
4
+
, Ca
2+
,
and Mg
2+
[15]. Exchange constants calculated
on the basis of these data are given in Table 2.
It  was  possible  to  obtain  satisfactory  coinci3
dence of calculated and experimental data by
assuming  the  existence  of  three  types  of  ex3
change parts corresponding to groups with dif3
ferent  degree  of  acidity  (real  distribution  of
exchange positions with respect to density of
bonding to hydrogen atoms is more complicat3
ed).  Capacity  ratio  of  strongly  acidic,  acidic
and weakly acidic groups is 7 : 12 : 11.
These ratios were used in estimating the ex3
change constants for heavy metals on the basis
of published experimental data [12,16–18, etc.].
Ion exchange constants on peat accepted in fur3
ther calculations are listed in Table 3.
The model is a series of 20 cells. At the zero
step, solution composition in cells corresponds
to  that  of  water  of  swamp  deposits,  and  the
composition  of  cations  in  the  exchange  com3
plex is calculated on the basis of the condition
of equilibrium with it. It should be pointed out
that the ratio of sorbed to dissolved forms for
different  metals  is  10
3
–10
4
. In other words,
under  natural  conditions  heavy  metals  in
swamp deposits are mainly in the sorbed state.
These results are in good agreement with data
of  geochemical  peat  tests.  Further,  it  is  as3
Table 2
Ion exchange constants for swamp deposits
calculated from experimental data [15]
Groups with different degrees of
acidity
Cation
Strongly
acidic
Acidic
Weakly
acidic
H
+
1.75
4.48
7.41
K
+
0.00
0.00
0.00
Ca
2+
1.0
2.27
1.7
Mg
2+
0.65
1.93
1.3
 
68
I.L. Kharkhordin and F.G. Atroshchenko
7.0
6.5
6.0
5.5
5
4.5
0
4
8
12
16
20
pH
Cell number
Fig. 1. Change in pH during waste filtration from the AW section in swamp deposits at the 10, 50, 300, and 10003th
calculated steps
10
50
300
1000
sumed that the solution corresponding to wa3
ter composition in the slime storage begins to
be  discharged  into  the  first  cell.  During  one
calculated step, the solution passes to the next
cell. After each passage solution composition
was brought into equilibrium with that of the
exchange  complex.  In  the  simulating  brine
migration from section AW, the possibility of
carbon dioxide dissolution with the formation
of hydrocarbonate ions absent in the initial so3
lution was also taken into consideration. Sat3
isfactory  agreement  between  calculated  and
measured  concentrations  of  hydrocarbonate
ions in solution was obtained at lg [CO
2
] = – 1.5.
Simulation results and their discussion
Let us consider in greater detail the pecu3
liar features of transformation of the chemi3
cal composition of waste in swamp deposits.
Section AW.
In the initial stage of filtration
of waste water from slime storage, as a result
of interaction with swamp deposits their chem3
ical  composition  is  transformed  drastically:
the pH of solutions increases (Fig. 1) and the
concentrations  of  micro3  and  macrocompo3
nents  change.  High  buffer  capacity  of  peat
with respect to acid and alkaline solutions over
a wide pH range is due to the presence of dif3
ferent groups in the exchange complex. Even
after repeated washing with an acid solution,
the  pH  of  swamp  deposits  are  5.5–6.  The
changes  in  concentrations  of  macrocompo3
nents  are  of  a  smoother  character  than  for
rocks  with  an  exchange  complex  of  a  single
type.  In  the  initial  stage  calcium  content
(Fig. 2) increases with respect to that in the pri3
mary solution, whereas the content of sodium
Table 3
Ion exchange constants for heavy metals
in swamp deposits
Groups with different degrees of acidity
Cation
Strongly
acidic
Acidic
Weakly
acidic
Mn
2+
0.8
2.0
1.6
Cd
2+
0.8
2.0
1.6
Zn
2+
1.0
2.4
1.8
Ni
2+
1.2
2.9
2.2
Pd
2+
1.3
3.2
2.4
Cu
2+
1.4
3.5
2.8
 
10
50
300
1000
Cell number
Ca,
m
g
⋅
l
–1
600
500
400
300
200
100
0
4
8
12
16
20
and  magnesium  decreases,  later  gradual  sta3
bilization takes place. The transformation of
the macrocomponent composition is virtually
completed  at  the  thousandth  calculated  step
(fifty3fold  change  of  solution  over  the  whole
simulation  range).  Effective  purification  of
waste  water  from  heavy  metals  takes  place.
Fig. 3 shows changes in nickel concentration
the initial content of which in the AW section
is  about  17  mg
⋅
l
–1
. After interaction with
swamp deposits it decreases by more than four
order of magnitude. Similar changes in concen3
Cell number
Fig. 3. Change in nickel concentration during waste filtration from the AW section in swamp deposits at the 10, 50,
300, and 10003th calculated steps.
4
8
12
16
20
0
20
16
12
8
4
Ni,
m
g
⋅
l
–1
10
50
300
1000
Fig. 2. Changes in calcium concentration during waste filtration from the AW section in swamp deposits at the 10, 50,
300, and 10003th calculated steps.
 
70
I.L. Kharkhordin and F.G. Atroshchenko
Fig. 4. Change in zinc concentration during waste filtration from the CWP section in swamp deposits at the 10, 50,
300, and 10003th calculated steps.
Zn,
m
g
⋅
l
–1
4
8
12
16
20
Cell number
0
0.02
0.016
0.012
0.008
0.004
0.009
Cell number
Fig. 5. Change in plumbum concentration during waste filtration from the CWP section in swamp deposits at the 10,
50, 300, and 10003th calculated steps.
tration are characteristic of zinc, copper, and
lead: their contents decrease from 7.5, 0.7, and
0.11 mg
⋅
l
–1
, respectively, to a few hundredths
and thousandths of milligram per litre. Man3
ganese content slightly increases at first, then
decreases and is stabilized at the level of the
initial solution.
Section CWP
. Waste water in this section
is also drastically transformed interacting
with swamp deposits: pH decreases to neutral
value and heavy metals concentrations change.
It  should  be  pointed  out  that  the  solution  is
purified from some metals and is contaminat3
ed with others. For instance, in the initial stage
zone  concentration  increases  almost  203fold
with  respect  to  that  in  the  initial  solution
(Fig. 4). It decreases only after the filtered so3
lution has been changed many times as zinc is
10
50
300
1000
Zn,
m
g
⋅
l
–1
0.008
0.007
0.006
0.005
0.004
0.003
0.002
0.001
4
8
12
16
20
10
50
300
1000
 
71
Simulation of Heavy Metals Migration in Peat Deposits
discharged  from  the  peat  exchange  complex.
Manganese behaves in a similar way. Cadmi3
um  content  slightly  increases  in  the  initial
stage,  then  it  decreases  and  stabilizes  at  its
concentration in the slime storage. Lead behav3
iour deserves particular attention (Fig. 5). In
the initial stage near the slime storage, high
lead concentration zone is formed in solution.
Subsequently it moves slowly downstream and
its  maximum  concentration  increases.  This
increase  is  caused  by  changes  in  migration
forms: near the storage the pH values of water
are  higher  and  lead  is  bound  into  carbonate
complex  compounds  to  a  considerable  extent
but with increasing distance from the storage
pH decreases and lead fraction in the ionic form
increases. Hence, ion exchange processes take
place more actively and cause lead bonding in
the exchange complex. Consequently, a mobile
geochemical  barrier  is  formed  in  which  the
process of concentration of lead in solution in3
creases.
On the whole the simulation results are in
good agreement with data on testing peat and
water of swamp deposits in the ATPS region.
Conclusions
The results of computer simulation proved
that heavy metals in swamp deposits are main3
ly in the solved state: the ratio of sorbed to dis3
solved forms is 10
3
–10
4
.
It was established that in low3lying swamps
at  pH  @  7  peat  exhibits  considerable  buffer
capacity for both acidic and alkaline solutions.
In the initial migration stage, the concen3
tration of heavy metals in the bulk of peat lay3
er in solution virtually does not depend on their
initial content in waste water and is determined
by the composition of the peat exchange com3
plex. At low concentrations of compounds of
heavy metals in waste water, interaction with
peat can lead both to ion sorption and to their
accumulation in solution. If the initial metal
concentration exceed the first milligrams per
litre, the processes of self3purification occur
actively.
This work is supported by Russian Founda3
tion for Basic Researches, project codes 973053
64419 and 96305364338.
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