Scientific Bulletin of the Electrical Engineering Faculty – Year 10 No. 1 (12)
ISSN 1843-6188
APPLICATION OF A GLOBAL MODEL TO THE STUDY
OF ARCTIC BASIN POLLUTION
C. NITU1, Vladimir F. KRAPIVIN2, Anda S. DOBRESCU1
University Politehnica of Bucharest, Splaiul Independenţei, nr. 313, 060042
V.A. Kotelnikov Institute of Radioengineering and Electronics, Russian Academy
of Sciences, 1 Vvedensky sq., Fryazino, Moscow region, 141190
E-mail: cnitu_ubp2001@yahoo.com
1
2
northwestern Siberia, coal and gold extraction in Yakutia
and Chukot as well as the mining industry on the Kola
Peninsula have led to a strong anthropogenic intervention
into the natural environment. Plant cover has been
violated over great territories, the area and productivity of
reindeer pastures diminished and the hydrologic regime
of rivers disturbed. The greatest quantities of pollution
substances are brought to the northern coast of Russia by
the rivers, violating the ecosystems of the northern seas.
Further adverse influence on the Arctic ecosystems can
lead to rising regional or even global scale negative
consequences. Thus the problem of the development of
the northern territories of Russia, the United States of
America, Canada and the Scandinavian countries needs
to be solved by careful analysis of all types of
ecosystem dynamics, by real time data collection and
formation of national databases and by defining
effective ways to coordinate development of the natural
and anthropogenic processes.
Abstract: The arctic basin pollution has some specific
characteristic in comparison with other seas because of the lower
temperatures and slower biologic processes. An understanding of
the environmental processes in the Arctic regions, which is a
prerequisite for finding scientific solutions to the problems
arising there, can be found only by combining many disciplines,
including ecology, oceanography, mathematical modeling, and
system analysis. This paper synthesizes data from many sources
and knowledge from various scientific fields in the form of a
Spatial Simulation Model of the Arctic Ecosystem (SSMAE).
Keywords: spatial simulation model, model of the Arctic
ecosystem
1. INTRODUCTION
The purpose of this study is to develop and to investigate
a simulation model of the pollution dynamics in the
Arctic basin. It is known that the ecosystems of the Arctic
seas are vulnerable to a considerable extent in
comparison with the ecosystems of other seas. [6] The
processes that clean the Arctic Ocean are slower and
marine organisms of the Arctic ecosystem live in a polar
climate where the vegetation period is restricted. Some
feedback mechanisms have significant time delays and
the capacity of the ecosystem to neutralize the effects of
human activity is feeble. Apart from these reasons the
Arctic ecosystem has specific boundary conditions
connected with the sea-ice ergocline which reduce its
survivability level.
2. ARCTIC BASIN POLLUTION PROBLEMS
The Arctic region plays a unique role in the global
environmental processes, forming numerous adverse
correlations with the Earth’s climatic system. Low
temperatures, a high level of atmospheric circulation and
the availability of large ice-covered aquatories are notable
for the high latitudes, quite unlike the other areas of the
globe. In the figure 1, it is presented the geographical
localization of the Arctic region. [7]
The intensive industrial development of the northern
territories has led to significant environmental change in
these regions, especially in the Russian territories. Oil
and gas extraction on the Yamal and Taimir peninsulas in
Figure 1. The geographical localization
of the Arctic region
The purpose of this study is to develop and to investigate
a simulation model of the pollution dynamics in the
Arctic basin. There are many experimental and
theoretical results giving estimates of the growing
dependencies between the pollution dynamics in the
World Ocean and the state of the continental
environment. The problem of the Arctic basin pollution
causes the most anxiety to investigators [2]. It is known
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Scientific Bulletin of the Electrical Engineering Faculty – Year 10 No. 1 (12)
that the ecosystems of the Arctic seas are vulnerable to a
considerable extent in comparison with the ecosystems of
other seas. Processes that clean the Arctic Ocean are
slower and marine organisms of the Arctic ecosystem live
in the polar climate where the vegetation period is
restricted. Some feedback mechanisms operate with
significant time delays and the capacity to neutralize the
effects of human activity is feeble. Apart from these
reasons the Arctic ecosystem has specific boundary
conditions connected with the sea-ice ergocline which
reduce its survivability level.
In connection with this circumstance, the Arctic basin is
the object for investigations in the frameworks of many
national and international environmental programs. [4]
The research strategies of these programs include the
theoretical and experimental study of the tundra
ecosystems, Siberian rivers and near-shore and open
arctic waters. The main problems arising here consist of
determining a set of the principle matters that are
necessary to study in the first place. These include the
following:
 Transport modeling of pollutants in the arctic
ecosystems.
 Modelling of the exchange processes of carbon
dioxide and methane between the tundra ecosystems
and the atmosphere.
 Modelling of the hydrological regime and estimation
of the pollutant flows in the Arctic Basin.
 Modelling of the Arctic ecosystems under conditions
of anthropogenic impacts.
 Modelling of the biogeochemical carbon cycle in the
“Atmosphere/Arctic Ocean” system.
 Development of a complex model for the functioning
of the hydrologic and biogeochemical systems in
Arctic.
 Stability estimation of the Arctic systems under
variable global climate conditions.
ISSN 1843-6188
3. SSMAE STRUCTURE
A conceptual diagram and the block contents of the
SSMAE are shown in Figure 2 and Table 1.
The functioning of the SSMAE is supported by the global
model of the nature-society system (GMNSS) and by the
climate model (CM). The SSMAE inputs are the data
about the pollutant sources of the near-shore Arctic
Basin, the ice areas and the current maps.
The SSMAE contains three types of blocks: mathematical
models of the natural ecological and hydrophysical
processes, service software and the scenarios generator.
The marine biota block (MBB) describes the dynamics of
the energy flows in the trophical chains of the Arctic
Basin ecosystem. The hydrological block (HB) describes
the spatial discretization of  on the water circulation in
the Arctic. The pollution simulation model (PSM)
contains the anthropogenic scenarios and the service
control block (SCB) provides for the control of the
simulation experiment.
An understanding of the environmental processes in the
Arctic regions, a prerequisite for finding scientific
solutions to the problems arising there, can be found only
by combining many disciplines, including ecology,
oceanography, mathematical modeling, and system
analysis. [5] This paper synthesizes many data sources
and knowledge from various scientific fields in the form
of a Spatial Simulation Model of the Arctic Ecosystem
(SSMAE).
The basic blocks of the SSMAE are oriented on the
description of the dynamics of any given pollutant. For
consideration of a specific pollutant it is necessary to
include in the SSMAE an additional block with the
description of its physical and chemical characteristics.
This procedure is demonstrated by examples of blocks
that simulate the characteristics of radionuclides, heavy
metals and oil hydrocarbons. The consideration of these
pollutants is restricted to elements with averaged
properties.
The Arctic basin aquatory, , which is studied in this
chapter has boundaries which include the peripheral
Arctic seas as well as the coast line and southern
boundaries of the Norwegian and Bering Seas.
Figure 2. Block-diagram of the SSMAE . Descriptions of
the blocks are given in Table 1.The Page Setup Dialog Box
(Margins) for formatting a paper in MS Word xx.
Table 1. Description of the SSMAE blocks (Figure 2)
Block
MBB
HB
PSM
SCB
APM
MFB
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Description of block
Marine Biota Block containing the set of
models for energy flows in the tropical
chains of the Arctic basin ecosystem.
Hydrological Block describing the water
circulation in the Arctic seas and the
movement of ecological elements.
Pollution Simulation Model of the Arctic
basin including the set of anthropogenic
scenarios.
Service Control Block to manage the
simulation experiment
Air Pollution transport Model.
Model of the Functioning of the Biota
under the conditions of energy exchange
the tropical chain of the Arctic Basin
ecosystem.
Scientific Bulletin of the Electrical Engineering Faculty – Year 10 No. 1 (12)
ISSN 1843-6188
Block
SS
MWD
MMT
IM
NM
MPT
MOT
MPR
MRF
MWS
MEF
MWT
ICI
ICD
ICV
- τu - summer,
- τa - autumn.
The procedure of spatial discretisation is provided for via
the ICI block of the SSMAE database, including the set
Description of block
Simulator of Scenarios describing the ice
fields, the synoptic situations and changes
in the hydrological regimes.
Model for the Water Dynamics of the
Arctic Basin.
Model for heavy Metals Transport
through the food chains.
The Illumination Model.
The Nutrients Model.
Model for Pollution Transport through
water-exchange between the Arctic Basin
and the Atlantic and Pacific Oceans.
Model for the process of Oil hydrocarbon
Transport to the food chains.
Model for the Process of Radionuclide
transport to the food chains.
Model of River Flow to the Arctic Basin.
Model of Water Salinity dynamics.
Model for Energy Flow transport in the
Arctic Basin ecosystem.
Model for calculating the Water
Temperature.
Interface for Control of the Identifiers.
Interface for Control of the Database.
Interface for Control of the Visualization.
of identifiers Ak  aij , where
k
is a specific
symbol to identify a real element of ij in the computer
memory. Identifier A1 reflects the spatial structure of the
1
Arctic basin and adjoining territories ( aij
 0 for
ij; a  1 for ij  when ij belongs
1
ij
to the land (islands).
Identifier A2 shows the position of the cells R, P, N,
S,  and describes the spatial distribution of the
pollutant sources. Other identifiers Ak are used to describe
ice fields (k=3), the spatial distribution of solar radiation
(k=4) and the dislocation of upwelling zones (k=5).
The user of the SSMAE in free-running mode may
choose different ways to describe the many input
parameters. Blocks ICI and ICD realize the on-line entry
to Ak and to the database. For example, if the user has
data about the spatial distribution of ice fields in , he
can form identifier A3 with
surface,
aij3  0 for an ice-free water
aij3  1 for new ice and aij3  2 for old ice. In
this case block SS enables the input of data from the
climate model concerning the ice fields.
The block structure of the SSMAE is provided for with a
C++ program. Each of the blocks from Table 1 is a C++
function. The main function provides the interactions
between the SSMAE, SGM and CM. This functional
specification supports overlapping output and input
streams of the SSMAE blocks. With the conversational
mode the user can toggle the data streams between the
slave blocks.
The calculating procedure is based on the subdivision of
the Arctic basin into boxes {ijk}. This is realized by
means of a quasi-linearization method [3]. All differential
equations of the SSMAE are substituted for in each box
ijk by easily integrable ordinary differential equations
with constant coefficients. The water motion and
turbulent mixing are realized in conformity with current
velocity fields which are defined on the same coordinate
grid as the {ijk}.
Let us designate the Arctic basin aquatory as 
where  and  are latitude and longitude, respectively.
Spatial inhomogeneity of the Arctic basin model is
T
CO2
provided by the set of cells
with latitude and
longitude steps of  and , respectively. These cells
are the basic spatial structure of  for the realization of
the computer algorithms. The cells ij are heterogeneous
as to their parameters and functioning. There are a set of
cells which are adjacent to the river mouths (R) and to
the ports (P), bordering on the land (   ), in the Bering
Strait (S) and on the south boundary of the Norwegian
Sea (N). The aquatory  is divided in depth z by step
z. The distribution of depths is given as the matrix H =
h ij  where h ij = H(  i ,λj), (  i ,λj)  ij. As a result,
the full water volume of  is divided into volumetric
4. SIMULATION RESULTS
compartments
ijk =   z|ii+1; jj+1;
zk zzk+1}
aijk
The SSMAE allows for the estimation of the pollution
dynamics of the Arctic basin under various a priori
suppositions about the intensities of the flows of
pollutants and under other anthropogenic impacts on the
ecosystems of this region. The thermal regime of the
Arctic basin is given by a normal distribution with
average temperatures and with dispersions on the
aquatories which are given by the SEDAAR (Strategic
Environmental Distributed Active Archive Resource).
The scheme of transport of pollutants in the atmosphere is
adopted from Christensen [1]. The estimates of
parameters for the blocks of Table 1 are given by
literature sources or personal recommendations. The
vertical distribution of pollutants in the initial moment t0
is taken as homogeneous. The average diameters of the
(1)
with volumes ijk =ΔφiΔjΔzk.
Within ijk
the water body is considered as a
homogeneous structure. The water temperature, salinity,
density and biomass of the compartments ijk are
described by box models. The anthropogenic processes
on the aquatory  are described for the four seasons:
- τw - winter,
- τs - spring,
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Scientific Bulletin of the Electrical Engineering Faculty – Year 10 No. 1 (12)
solid particles are estimated to be in the range from 0.12
m to 1000 m and the vertical velocity of sedimentation
is 0.003 m/s. The concentration of nutrients in the ice and
snow equals 0. Also it is supposed that the deep water
temperature t, = 0C and the surface ice
temperature f1(t,,)=-3 C for (   It is supposed
that the phytoplankton productivity in the ice layer is 2.5
percent of the primary production in the water column.
Let the ratio between solid and dissolved phases of heavy
metals at the moment t = t0 equal 1:2. The flows of heavy
metals are described by linear models. The boundaries of
the Norwegian and Bering Seas are approximated by
lines with N = 62 oN and B = 51 oN, respectively.
Simulation results include:
 The dynamics of Arctic Basin radionuclear
pollution.
 The dynamics of Arctic Basin pollution by heavy
metals.
 The dynamics of Arctic Basin pollution by oil
hydrocarbons.
Figure 3 gives example of simulation results. The Ob and
Yenisey rivers are considered to be the main sources of
radionuclear pollution, heavy metals and oil
hydrocarbons for the Kara Sea. Figure 3 shows the
influence of the river flow on the volume of pollutants
transported by the Kara Sea aquageosystem to the Central
basin. As shown by curves 1 and 2, the transference of
heavy metals and radionuclides from the Ob and Yenisey
rivers through the Kara Sea aquageosystem to the Central
aquatories of the Arctic basin amounts to 2.1 percent
when the river flow varies from 500 to 1000 km3/yr and
after that it begins to grow linearly up to 7.6 percent for
2000 km3/yr. Hence, there is a critical level of pollution
for the Kara Sea ecosystem beyond which it does not
have time to dilute the flow of heavy metals and
radionuclear pollutants.
ISSN 1843-6188
In the figure 3, the interval [F1,F2] between the dashed
lines corresponds to the range of variations of F in the
real world. Curves 1 and 2 show concentrations of the
heavy metals and radionuclides, respectively, at the point
with ,  = 75oN, 65oE in the northwestern part of the
Kara Sea. Curves 3 and 4 show the concentrations of
heavy metals and radionuclides, respectively, at the point
with ,  = 72oN, 150oW above the Alaskan North Coast
5. CONCLUSIONS
An understanding of the environmental processes in the
Arctic regions, which is a prerequisite for finding
scientific solutions to the problems arising there, can be
found only by combining many disciplines, including
ecology, oceanography, mathematical modeling, and
system analysis. This paper synthesizes data from many
sources and knowledge from various scientific fields in
the form of a Spatial Simulation Model of the Arctic
Ecosystem (SSMAE). Simulation results include:
 The dynamics of the Arctic basin radionuclear
pollution.
 The dynamics of Arctic basin pollution by heavy
metals.
 The dynamics of Arctic basin pollution by oil
hydrocarbons.
 Influence of the Arctic Sea ecosystems upon the
dynamics of the pollutants in the seawater.
 Dependence of the pollutant concentration at
different geographical points as a function of the
flow of the Siberian Rivers to the Arctic Basin.
6. REFERENCES
[1] Christensen, J.H. The Danish Eulerian hemispheric model a three-dimensional air pollution model used for the
Arctic. Atmospheric Environment, 1997, 31(24), 4169 4191.
[2] Krapivin V.F. and Varotsos C.A. Biogeochemical Cycles in
Globalization
and
Sustainable
Development.
Springer/Praxis, Chichester UK, 2008, 562 pp.
[3] Nitu. C., Krapivin, V. and Bruno, A. Intelligent techniques
in ecology. Printech, Bucharest, 2000, 150 pp.
[4] Nitu C. and Dobrescu A.S., Process control with energy
reduction, Ed. .MATRIX, Bucharest, 2009, 164 pp.
[5] Bobylev P. L., Kondratyev Ya. K., Johannessen M. O.,
Arctic Environment Variability in the Context of Global
Change, Ed. Springer - Praxis Publishing, 2003, 470 pp
[6] Wadhams P., Dowdeswell J A, Schofield A. M., Arctic and
Environmental Change, Ed. The Royal Society, 1996, 197
pp
[7] Van Vleet C, Amazing Arctic and Antarctic, Ed. Nomad
Press, 2008, 130 pp
Figure 3. Dependence of the concentrations of heavy metals
( + e) and radionuclides ( = 137Cs + 60Co) at different
geographical points as a function of the flow (F) of the Ob
and Yenisey rivers to the Kara Sea.
114