ARTICLE IN PRESS
Deep-Sea Research II 53 (2006) 1817–1841
www.elsevier.com/locate/dsr2
Processes controlling the redox budget for the oxic/anoxic water
column of the Black Sea
S.K. Konovalova,, J.W. Murrayb, G.W. Lutherc, B.M. Tebod
a
Marine Hydrophysical Institute, NASU, Kapitanskaya 2, Sevastopol 99011, Ukraine
School of Oceanography, University of Washington, Seattle, WA 98195-5351, USA
c
College of Marine Studies, University of Delaware, Lewes, DE 19958, USA
d
Marine Biology Research Division, Scripps Institution of Oceanography, University of California, San Diego, CA 92093,USA
b
Received 1 November 2003; accepted 27 March 2006
Available online 1 September 2006
Abstract
A one-dimensional isopycnal model has been constructed to simulate 16 major components of the Black Sea
biogeochemical structure and to discuss processes controlling the redox budget for the oxic/anoxic water column of the
Black Sea. The model includes parameterizations of physical exchange in the water column that takes account of vertical
advection and diffusion and lateral exchange between the Black Sea and the Bosporus Plume. The model incorporates
parameterizations for 25 biogeochemical processes, which we have found to be important to simulate the redox
biogeochemical structure over a period of several decades. Parameterizations for biogeochemical processes follow the
principles of formal chemical kinetics. Limiting functions are not applied. Neither physical nor biogeochemical processes
are limited to depth or density layers of water, making the generated biogeochemical structure flexible. The redox budget
and importance of individual processes for the budget of oxygen, sulfide, nitrate, ammonium, organic matter, manganese
and iron are discussed in detail. In particular, we demonstrate that the biogeochemical structure of the oxic and suboxic
layer strongly depends on export production and climate-induced variations in ventilation. The redox budget and the
biogeochemical structure of the anoxic zone highly depend on the lateral exchange between the Black Sea and the
Bosporus Plume, which appears to be the major reason for the existence of the suboxic zone.
r 2006 Elsevier Ltd. All rights reserved.
1. Introduction
During the last decade considerable progress has
been made modeling carbon cycling in the euphotic
zone (Oguz et al., 1996, 1998) and biogeochemical
processes in the oxic/anoxic environment of the
Corresponding author.
E-mail addresses: [email protected]
(S.K. Konovalov), [email protected] (J.W. Murray),
[email protected] (G.W. Luther), [email protected] (B.M. Tebo).
0967-0645/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.dsr2.2006.03.013
Black Sea (Belyaev et al., 1997; Lyubartseva and
Lyubartsev, 1998; Yakushev, 1998; Yakushev and
Neretin, 1997; Oguz et al., 1999, 2001). A diagnostic
model of redox cycling in the Black Sea suboxic
zone was presented by Oguz et al. (2001). Here, we
present a numerical investigation of the redox
budget and evolution of the biogeochemical structure throughout the aphotic oxic/anoxic water
column of the Black Sea.
The Black Sea is a land-locked marine basin with
restricted seawater-exchange through the Bosporus
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
and with heavy anthropogenic input. This is a
classic 2-layer density stratified system where
salinity increases from about 18 to 22 between the
upper and the lower layers (Murray et al., 1991)
(Fig. 1A). As a result, vertical exchange is restricted
and a vertical sequence of oxic, suboxic and anoxic
conditions occurs (Fig. 1B). The vertical stratification and depth of the main pycnocline (Fig. 1A)
varies spatially, and the density scale is preferred to
plot and analyze the biogeochemical structure
(Murray et al., 1995).
This marine system has become a reference site
for studying anthropogenic impacts on oceanography. The reported changes in biological (Yunev
et al., 2002; Vinogradov and Simonov, 1989) and
biogeochemical structure (Vladimirov et al., 1997;
Konovalov et al., 1999a, b; Konovalov and Murray,
2001) reflect dramatic degradation of the Black Sea
ecosystem (Mee, 1992; Mee et al., 2005) and have
resulted in economic losses of over $500 million per
year (Black Sea INCOM Science Plan, 2000). This
trend, if not reversed, might result in severe
consequences for people living at the coast, as there
is only a 100-m thick oxic lid overlying the 2000 m
thick sulfidic zone (Fig. 1B).
This marine system serves as a natural laboratory
(i) to investigate the influence of climate change and
anthropogenic eutrophication on the oxic/anoxic
balance, (ii) to understand natural processes supporting the oxic/anoxic balance over several millennia, and (iii) to provide knowledge that can be
used in other regions, where anoxic conditions
are or tend to be developed due to eutrophication
and other human-related activities. Numerous national cruises and international expeditions (summarized by Konovalov and Murray (2001) and
Ivanov et al. (1998), including the 1988, 2001 and
2003 KNORR expeditions, have provided fundamental observational data. This has made possible
comprehensive analysis (Konovalov and Murray,
2001; Yunev et al., 2002) and modeling (Oguz et al.,
1996, 1998; Stanev et al., 2001; Gregoire and
Lacroix, 2001) of the Black Sea biogeochemical
properties.
Fig. 1. Thermohaline (A) and oxic/anoxic (B) structure of the Black Sea water column. (CIL is the Cold Intermediate Layer with 8 1C for
its upper and lower boundary. T–S data and data on oxygen and sulfide are from NATO TU-Black Sea basin-wide cruises in 1991–1994.
The depth scale at panel (B) is changed at 300 m.)
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
Papers by Oguz et al. (1996, 1998, 1999) and
Gregoire and Lacroix (2001) serve as good examples
of the Fasham et al. (1990) and Ducklow and
Fasham (1992) type food-web models to successfully simulate nitrogen-dependent seasonal variations in the structure, distribution and activity of
phytoplankton and zooplankton. In particular,
Oguz et al. (1999) obtained a better understanding
and explanation of the role of individual biological
species and climatic forcing for primary and
secondary biological processes through modeling.
Gregoire and Lacroix (2001) investigated physical
and biogeochemical mechanisms that lead to
ventilation (oxygenation) of intermediate and deep
anoxic waters. They addressed the impact of winter
turbulent mixing, frontal instabilities, cascading
along the continental slope of the shelf waters,
remineralization of detritus, and processes of
nitrification.
Ecosystem food-web models have successfully
allowed investigations of the influence of the general
circulation and associated synoptic and meso-scale
structures on the space–time distribution of primary
and secondary production. However, models of
nitrogen transformations below the euphotic zone
have been oversimplified. Oxygen consumption has
been parameterized as a nitrogen-dependent and
nitrogen-equivalent process. In order to specifically
avoid oxygen consumption in the absence of
oxygen, a set of limiting functions (Gregoire and
Lacroix, 2001; Yakushev, 1998) and restriction of
individual processes to certain layers of water (Oguz
et al., 1999) were applied to the numerical scheme.
Similar procedures were applied to other biogeochemical properties. As a result, budgets and
variations in individual biogeochemical properties
were independent or weakly cross-linked below the
euphotic zone, while the budget and structure of the
euphotic layer was simulated realistically (Gregoire
and Lacroix, 2001; Oguz et al., 1999). A different
approach is required for ‘‘small’’ marine basins or
oxic/anoxic basins, such as the Black Sea, where the
inventory and annual inputs and outputs of nitrate
are of the same order of magnitude (Konovalov et
al., 2000). Here nitrogen cycling is not limited to
detritus oxidation and physical upward flux, but
also includes processes that are characteristic of
sub-oxic and anoxic conditions.
The goal of this work is to investigate (i) the
redox budget of the Black Sea, (ii) the importance of
individual processes, and (iii) possible changes in the
biogeochemical structure due to variations in
1819
climate conditions and the level of eutrophication.
We will elaborate on a one-dimensional (1-D)
biogeochemical model for the Black Sea water
column with simulation of horizontal ventilation
(i) extending it to the entire aphotic water column of
the Black Sea (from 50 m to the bottom), (ii)
introducing in the model all important redox budget
processes without artificial limiting functions, and
(iii) incorporating the latest achievements in parameterization of physical vertical exchange in the
Black Sea water column (Ivanov and Samodurov,
2001) and redox transformations (Konovalov et al.,
2004; Kahler and Koeve, 2001).
2. Model
The present model is based on the previously
developed numerical model of physical exchange
(Samodurov and Ivanov, 1998; Ivanov and Samodurov, 2001), extended to simulate the basic
biogeochemical processes in the Black Sea water
column. The vertical distribution of all properties
was assumed to be isopycnal (Figs. 1 and 2). This
assumption makes it possible to simulate the Black
Sea in a 1-D isopycnal simulation. In addition, the
Black Sea thermohaline structure is assumed to be
at steady state on a long-time scale. Centuryaveraged vertical profiles of temperature and
salinity have been utilized to derive the vertical
profiles of vertical velocity and diffusivity (Konovalov et al., 2000; Ivanov and Samodurov, 2001),
which are applied to calculate cross-isopycnal fluxes
and exchange between water from the Bosporus of
Mediterranean origin and the Black Sea (Eqs. (1)
and (2)). These exchange processes are often
referred in recent publications to explain the
vertically distributed source of salt and heat (Ozsoy
et al., 1995; Ivanov and Samodurov, 2001), the
entrainment of water from the Cold Intermediate
Layer (Murray et al., 1991; Buesseler et al., 1991),
the Bosporus Plume (a mixture of the Mediterranean and Black Sea waters), and intrusions in the
layer of the main pycnocline and anoxic zone
(Konovalov et al., 2003; Glazer et al., 2006). This
input from the Bosporus, modified by entrainment,
is the mechanism generating the basin-average
vertical advection, which reaches a maximum value
of about 3 m yr1 (Murray et al., 1991; Lee et al.,
2002) to 7 m yr1 (Ivanov and Samodurov, 2001)
in the middle pycnocline at density values of
st15.7–15.8.
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The resulting balance equations include simulation of the result of ventilation by the Bosporus
plume and can be written as
qC
þ wC,
qz
q
qC
qC
qw
k
ðC b CÞ,
þw
¼Rþ
qz
qz
qz
qz
(1)
Flux ¼ k
(2)
where k is the vertical diffusion coefficient and
kðqC=qzÞ is the diffusive flux, w is the vertical
velocity and, hence, wC is the advective flux
occurring due to displacement of the Black Sea
deep waters with the waters from the Bosporus
plume, R is the rate of biogeochemical production–
consumption, qw=qzðC b CÞ is rate of changes in
the biogeochemical structure due to the Bosporus
plume, C b is concentration in the ‘‘Bosporus
plume’’, and C is concentration of the same
substance in the ambient water (Samodurov and
Ivanov, 1998).
The role of the Bosporus plume for the biogeochemical structure varies with depth. C b varies
between the layers of entrainment of the Black Sea
waters to the plume, and it remains constant in each
individual layer of intrusions. qw=qz progressively
decreases with depth in the layer of intrusions,
making the plume-related flux of biogeochemical
Ammonium (NH4+), µM
(A)
0
10
20
30
40
components and the rate of changes in the
biogeochemical structure undetectable below
800–1000 m.
The resulting vertical profiles of the rate of
advection and turbulent diffusivity must satisfy
two basic constraints: (i) they must simulate the
observed thermohaline structure, and (ii) they must
realistically simulate temporal variations in the
distribution of conservative properties, which are
not the subject of biogeochemical transformations.
2.1. Biogeochemical components and terms
The 16 components of the biogeochemical structure of the water column we have included in this
model are dissolved oxygen, one form of particulate
and two forms of dissolved organic matter, nitrate,
ammonium, di-nitrogen gas, elemental sulfur, sulfide, dissolved manganese (II), suspended manganese (IV) oxide, suspended manganese (II)
carbonate, suspended manganese (II) sulfide, dissolved iron (II), suspended iron (III) oxide and
suspended iron (II) sulfide. This list includes the
components that appear to be the major biogeochemical elements for the overall redox budget
(Fig. 2). Only redox end-members have been considered for parameterization, unless an intermediate
Iron (Fe2+), nM
(B)
0
50
100
200
300
0
2
4
6
10
15.0
NO3Suboxic
zone
So
Sigma-t
Sigma-t
8
O2
O2
16.0
500
Manganese (Mn2+), µM
Elemental Sulfur (S°), µM
0.0
0.1
0.2
15.0
400
N2
Suboxic
zone
16.0
NH4+
17.0
0
100
200
300
Oxygen (O2) & Sulfide (H2S), µM
0.0
2.0
4.0
Fe2+
17.0
H2S
6.0
8.0
Nitrate (NO3-), µM
10.0
0
0
Mn2+
100
200
Oxygen (O2), µM
10
20
300
30
Nitrogen Excess (N2), µM
Fig. 2. Redox biogeochemical structure of the Black Sea water column (oxygen, nitrate, sulfide data are from NATO TU-Black Sea basinwide cruises in 1991–1994). Ammonium data are from the 1988 KNORR expedition. Manganese data are from the 1988 and 2001 KNORR
expeditions. Iron data are from the 1988 KNORR expedition and MHI cruises in 1991–1994. Data on elemental sulfur are from the 2001
KNORR expedition. Data on di-nitrogen gas are from Murray et al. (2003a, b).
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
product appears to be important for the redox
budget and structure of a layer.
Interaction between these components has been
simulated using 25 biogeochemical processes listed
in Table 1. Essentially all of these are biologically
mediated/catalyzed and utilized as a source of
energy or elements. Sulfide or iron (II), for example,
can be abiotically oxidized by oxygen and these
processes are abiotically catalyzed or auto-catalyzed, but these processes are also widely utilized by
bacteria as a source of energy in aquatic systems.
Biogeochemical processes are usually the result of
a number of elementary reactions. Thus, a sequence
of at least seven elementary reactions describe the
process of iron (II) oxidation (Table 1, process 13)
(Stumm and Morgan, 1996) and sulfide is oxidized
to sulfate through an extended sequence of inter-
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mediate products, such as thiosulfate, sulfite, polysulfide, elemental sulfur, etc. Every elementary
reaction is most likely a binary first-order process
with respect to each individual reagent, but kinetic
data are usually not available or make the model
overly complicated for practical utilization. The
experimental rate law expresses only the rate of an
overall process and it is as simple as possible to
realistically simulate the rate of the overall process,
which are widely applied in numerical models. The
order for reagents does not have to follow the
stoichiometry (Hausecroft and Constable, 1997)
and it often becomes a fraction. Variations in the
order for reagents allow application of the principles of formal chemical kinetics to typical abiotic
process of dissolution (Table 1, process 23), and to
typical microbial process, such as of respiration of
Table 1
Biogeochemical processes and their specific rate constants
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Biogeochemical processes
Specific rate
constants (Ki)
POM oxidation by oxygen C106(NH4)16(PO4)+106O2 ¼ 106CO2+16(NH4)+(PO4)
DOM(l) (DOC:DON ¼ 23.5) oxidation by oxygen
C23.5a(NH4)a(PO4)b+23.5aO2 ¼ 23.5aCO2+a(NH4)+b(PO4)
POM oxidation by nitrate
+
¼ 530CO2+276N2+256H2O+5(PO4)
5C106(NH4)16(PO4)+472NO
3 +392H
2
POM respiration to sulfide C106(NH4)16(PO4)+53SO2
4 ¼ 106CO2+53S +16(NH4)+(PO4)
DOM(l) (DOC:DON ¼ 23.5) respiration to sulfide
2
2C23.5a(NH4)a(PO4)b+23.5aSO2
4 ¼ 47aCO2+23.5aS +2a(NH4)+2b(PO4)
POM transformation to DOM(r) (DOC:DON ¼ 5)
aC106(NH4)16(PO4)+26aO2 ¼ 26aCO2+16C5a(NH4)a(PO4)b+(a16b)(PO4)
DOM(l) (DOC:DON ¼ 23.5) oxidation to POM
16C23.5a(NH4)a(PO4)b+270aO2 ¼ 270aCO2+aC106(NH4)16(PO4)+(16ba)(PO4)
DOM(l) (DOC:DON ¼ 23.5) ammonification to POM
106C23.5a(NH4)a(PO4)b+270a(NH4) ¼ 23.5aC106(NH4)16(PO4)+(106b23.5a)(PO4)
+
Nitrification NH+
4 +2O2 ¼ NO3 +H2O+2H
+
Manganese oxidation by nitrate 5Mn2++2NO
3 +4H2O ¼ 5MnO2+N2+8H
Manganese oxidation by oxygen 2Mn2++O2+2H2O ¼ 2MnO2+4H+
+
Iron oxidation by nitrate 10Fe2++2NO
¼ 10Fe3++N2+6H2O
3 +12H
Iron oxidation by oxygen 4Fe2++O2+2H2O ¼ 4Fe3++4OH
Sulfide oxidation by oxygen S2+2O2 ¼ SO2
4
2
Sulfide oxidation by nitrate 5S2+8NO
3 +4H2O ¼ 5SO4 +4N2+8OH
Sulfide oxidation by suspended manganese (IV)
0
MnO(OH)2+S2+CO2
3 +H2O ¼ MnCO3+S +4OH
Sulfide oxidation by suspended iron (III) S2+2Fe3+ ¼ S0+2Fe2+
+
De-nitrification 5NH+
4 +3NO3 ¼ 4N2+2H +9H2O
Ammonium denitrification/oxidation by suspended manganese (IV)
+
2NH+
¼ N2+3Mn2++6H2O
4 +3MnO2+4H
3+
Ammonium denitrification/oxidation by suspended iron (III) 2NH+
¼ N2+6Fe2++8H+
4 +6Fe
2+
Cross-oxidation of iron (II) by manganese (IV) MnO(OH)2+2Fe +H2O ¼ Mn2++2FeOOH+2H+
+
Elemental sulfur oxidation 2S0+3O2+2H2O ¼ 2SO2
4 +4H
2+
Dissolution of sinking manganese carbonate MnCO3 ¼ Mn +CO2
3
Generation of manganese sulfide MnCO3+2HS ¼ MnS2+CO2
3 +H2
Generation of iron sulfide Fe2++2HS ¼ FeS2+H2
7.5 103
5.0 108
1.0 105
6.35 104
5.0 106
2 103
1.2 105
2.75 106
6.5 103
3.0
2.5
5.0
4.0
2.5 102
0.5
2.7
5.0 102
2.0
5.0 102
5.0 102
0.74
0.03
1.7
5.0
1.35 103
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organic matter (Table 1, processes 1, 3, 4, etc.),
which are usually parameterized by Michaelis–
Menten kinetics. Thus, the parameterizations we
use here (Table 2) do not prove that ‘‘chemical’’
parameterizations are better than ‘‘microbiological’’, but they do allow us to formally fit the
observed distributions and to simplify calculations.
It is extremely important to emphasize that the
rate laws are often oversimplified. Thus,
q½H2 S
¼ K ½H2 Sx ½O2 y ,
qt
where K is a specific rate constant that does not
depend on the concentration of sulfide ½H2 S or
oxygen ½O2 , is often reduced to
q½H2 S
¼ K 1 ½H2 S,
qt
where K1 is a pseudo-first-order rate constant, and
used in this form to simulate sulfide oxidation in
oxic/anoxic marine systems. This reduced equation
describes kinetics of sulfide oxidation correctly if
only the oxygen concentration is high and remains
constant. That means that K 1 ¼ K ½O2 const:
and the rate of sulfide oxidation does not formally
depend on the concentration and even the presence
of oxygen. This assumption does not fit the real
conditions in the suboxic/anoxic transition layer of
the Black Sea.
A similar situation occurs when remineralization
of sinking POM and production of ammonium and
nitrate are parameterized by a first-order equation.
This assumes that the processes of POM and
ammonium oxidation do not depend on the ambient
concentrations of oxygen and require a limiting
function that artificially changes the rate of processes when the concentration of oxygen drops to
suboxic levels (Yakushev, 1998; Gregoire and
Lacroix, 2001). In fact, limiting functions are rarely
needed, if a complete equation
q½NHþ
y
þ x
4
¼ K NHþ4 ½NH4 ½O2 qt
or
q½POM
x
y
¼ K POM ½POM ½O2 qt
is used. The rate of oxidation varies proportionally
to the concentration of oxygen, and so equals zero
when oxygen is absent. In fact, the sulfide concentration, for example, never equals zero, but remains
at a sub-nanomolar level even in the exclusively oxic
marine systems (Luther et al., 1991). Sulfide, as an
intermediate product of transformation of organic
matter, exists in all marine environments, and
oxygen controls its equilibrium concentration.
Similarly, almost all redox processes are parameterized in this work by rate-law equations that include
the concentration of both reductants and oxidants
(Table 2). However, we have simplified equations
for the rate of POM and DOM respiration to sulfide
(processes 4 and 5, Table 1) because the concentration of sulfate never limits the rate of sulfide
production in the Black Sea water column.
The specific rate constants of the specific processes are listed as Ki (Table 1). These coefficients
were initially derived from published values and/or
estimated from redox capabilities of individual
reagents. Thus, for example, the specific rate
constant (K) of particulate organic matter oxidation
in oxygenated waters of 0.05–0.15 d1 (after Yakushev, 1998), is actually equal to K ¼ K 1 ½O2 y .
The final set of specific rate constants (Table 1) has
been adjusted in several runs of the model to keep
the numerically simulated biogeochemical structure
as close as possible to the observed values (Figs. 5
and 6).
In total, 25 specific rate constants and several
sinking rates drive the model (Tables 1 and 2). The
procedure of optimization of these values did not
take much effort, as there is a limited range over
which to vary the parameters. All budgets of
individual components are bounded and crossbounded through the stoichiometry of the processes
(Tables 1 and 2) and the resulting rate laws. Every
attempt to adjust the profile for an individual
component results in equivalent changes in profiles
of other components. If an individual specific rate
constant is chosen without consideration of other
components, the total biogeochemical structure
becomes unrealistic in a short run of the model.
The result of these parameterizations suggests that
the overall scheme of processes is more important
than specific values of the rate constants. Thus, for
example, data published by Oguz et al. (2001) and
Stanev et al. (2001) demonstrate that consideration
solely of oxygen interactions with sulfide always
results in a layer of co-existence of these components, rather than the observed suboxic zone.
Attempts to adjust the specific rate constant of
this process would be unsuccessful in simulation of
the suboxic zone, because important processes are
omitted.
5
4
3
2
Particulate organic matter (POM)
1
q½NO3 472
¼ K 3 ½POM ½NO3 þ 1 K 9 ½NH4 ½O2 qt
80
1 K 10 ½MnðIIÞ ½NO3 0:4 ½MnðIVÞ 1 K 12 ½FeðIIÞ ½NO3 3
1 K 15 ½S2 ½NO3 K 18 ½NH4 ½NO3 ½MnðIVÞ
5
Nitrate (NO3)
1 K 20 ½FeðIIIÞ ½NH4 q½NH4 ¼ 1 K 1 ½POM ½O2 0:2 þ 1 K 2 ½DOMðlÞ ½O2 0:5 þ 1 K 4 ½POM
qt
270
K 8 ½DOMðlÞ ½NH4 1 K 9 ½NH4 ½O2 þ 1 K 5 ½DOMðlÞ 376
1 K 18 ½NH4 ½NO3 ½MnðIVÞ 1 K 19 ½MnðIVÞ ½NH4 Ammonium (NH4)
q½DOMðrÞ
¼ 1 K 6 ½POM ½O2 0:2
qt
Refractory dissolved organic matter (DOM(r))
q½DOMðlÞ
¼ 1 K 2 ½DOMðlÞ ½O2 0:5 1 K 5 ½DOMðlÞ
qt
106
K 8 ½DOMðlÞ ½NH4 1 K 7 ½DOMðlÞ0:5 ½O2 376
Labile dissolved organic matter (DOM(l))
q½POM
¼ 1 K 1 ½POM ½O2 0:2 1 K 3 ½POM ½NO3 1 K 4 ½POM
qt
1 K 6 ½POM ½O2 0:2 þ 1 K 7 ½DOMðlÞ0:5 ½O2 þ K 8 ½DOMðlÞ ½NH4 Biogeochemical terms
No.
Table 2
Biogeochemical terms and boundary conditions
0.2 mM
0.01 mM
1 mM of DON
15 mM of DON
2.5 mM of PON
Upper boundary
concentration
0.054
Lower boundary flux
(mM m2 d1)
S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
ARTICLE IN PRESS
1823
11
10
9
8
7
Nitrogen gas (N2)
6
Manganese oxide (Mn(IV)), Sinking rate is 14.7 m d1
q½MnðIIÞ
5
¼ K 10 ½MnðIIÞ ½NO3 0:4 1 K 11 ½MnðIIÞ ½O2 ½MnðIVÞ
qt
2
3
1
þ K 19 ½MnðIVÞ ½NH4 þ K 21 ½MnðIVÞ0:5 ½FeðIIÞ þ 1 K 23 ½MnCO3 1:7
2
2
Dissolved Manganese (II) (Mn(II))
q½S0 ¼ 1 K 16 ½MnðIVÞ ½S2 0:125 þ 1 K 17 ½FeðIIIÞ ½S2 0:125 1 K 22 ½S0 ½O2 qt
Elemental Sulfur (S0)
q½S 53
23:5
¼
K 4 ½POM þ
K 5 ½DOM
qt
16
2
1 K 14 ½S2 ½O2 1 K 15 ½S2 ½NO3 1 K 16 ½MnðIVÞ ½S2 0:125
1
K 17 ½FeðIIIÞ ½S2 0:125 2 K 24 ½MnCO3 ½S2 2 K 25 ½FeðIIÞ ½S2 5
2
Sulfide (S2)
q½O2 106
26
¼ K 1 ½POM ½O2 0:2 23:5 K 2 ½DOM ½O2 0:5 K 6 ½POM ½O2 0:2
qt
16
16
270
1
0:5
K 7 ½DOMðlÞ ½O2 2 K 9 ½NH4 ½O2 K 11 ½MnðIIÞ ½O2 ½MnðIVÞ
16
2
1
3
2
K 13 ½FeðIIÞ ½O2 2 K 14 ½S ½O2 K 22 ½S0 ½O2 4
2
Oxygen (O2)
q½N2 276
¼
K 3 ½POM ½NO3 qt
80
1
1
þ K 10 ½MnðIIÞ ½NO3 0:4 ½MnðIVÞ þ K 12 ½FeðIIÞ ½NO3 2
2
1
4
þ K 15 ½H2 S ½NO3 þ K 18 ½NH4 ½NO3 ½MnðIVÞ
2
5
1
1
þ K 19 ½MnðIVÞ ½NH4 þ K 20 ½FeðIIIÞ ½NH4 2
2
Biogeochemical terms
No.
Table 2 (continued )
3.0 105 mM
330 mM
Concentration
oversaturation 5 mM
Upper boundary
concentration
0.002
0.213
Lower boundary flux
(mM m2 d1)
1824
S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
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16
15
14
13
12
q½FeS2 ¼ 1 K 25 ½FeðIIÞ ½S2 0
qt
Iron sulfide (FeS2), Sinking rate is 0.82 m d1
þ 1 K 21 ½MnðIVÞ0:5 ½FeðIIÞ
q½FeðIIIÞ
¼ 5 K 12 ½FeðIIÞ ½NO3 þ 1 K 13 ½FeðIIÞ½O2 qt
1 K 17 ½FeðIIIÞ ½S2 0:125 3 K 20 ½FeðIIIÞ ½NH4 Iron oxide (Fe(III)), Sinking rate is 5.3 m d1
1 K 21 ½MnðIVÞ0:5 ½FeðIIÞ 1 K 25 ½FeðIIÞ ½S2 0
q½FeðIIÞ
¼ 5 K 12 ½FeðIIÞ ½NO3 1 K 13 ½FeðIIÞ½O2 qt
þ 1 K 17 ½FeðIIIÞ ½S2 0:125 þ 3 K 20 ½FeðIIIÞ ½NH4 Dissolved Iron (Fe(II))
q½MnS
¼ 1 K 24 ½MnCO3 1:7 ½S2 0
qt
Manganese sulfide (MnS2), Sinking rate is 0.82 m d1
q½MnCO3 ¼ 1 K 16 ½MnðIVÞ ½S2 0:125 1 K 23 ½MnCO3 1:7
qt
1 K 24 ½MnCO3 1:7 ½S2 0
Manganese carbonate (MnCO3), Sinking rate is 193 m d1
q½MnðIVÞ
5
¼ K 10 ½MnðIIÞ ½NO3 0:4 ½MnðIVÞ
qt
2
þ 1 K 11 ½MnðIIÞ ½O2 ½MnðIVÞ 1 K 16 ½MnðIVÞ ½S2 0:125
3
1
K 19 ½MnðIVÞ ½NH4 K 21 ½MnðIVÞ0:5 ½FeðIIÞ
2
2
6.0 103 mM
S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
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1826
2.1.1. Inorganic components
The presence of dissolved oxygen, nitrate, ammonium, sulfide, dissolved manganese (II), and suspended hydrous manganese (IV) oxide have been
discussed as important redox components of the
Black Sea water column in a number of publications
(Codispoti et al., 1991; Murray et al., 1995;
Konovalov and Murray, 2001; Oguz et al., 2001;
Konovalov et al., 2004; etc.). Data for di-nitrogen
gas, as the end-product of denitrification, which
occurs in the suboxic zone, was discussed Murray
et al. (2003b, 2005). Recent work by Jorgensen et al.
(1991), Luther et al. (1991), Luther (1991), and
Glazer et al. (2006) have provided data on the
vertical distribution of elemental sulfur.
Speciation and cycling of manganese and iron in
the Black Sea water column has been investigated
by Lewis and Landing (1991) and Tebo (1991) and
parameterized for the purpose of numerical modeling by Konovalov et al. (2004). The forms of
manganese and iron included here are sufficient to
simulate numerically the observed distribution of
the dissolved and suspended forms of these metals
(Tables 1 and 2).
2.1.2. Particulate and dissolved organic matter
Organic matter is produced in the euphotic layer,
and the export production serves as a source of
organic carbon, nutrient elements and energy to
drive biogeochemical processes. Oxidation of organic matter under oxic conditions results in
consumption of oxygen and production of nitrate.
(A)
4
8
POC, µM
12
PON, µM
0.4 0.8 1.2 1.6 2
(B)
16
Sulfide and ammonium, which support chemosynthesis (Brewer and Murray, 1973), are the result
of respiration of organic matter under anoxic
conditions. Thus, organic matter is the most
important substance that drives the biogeochemical
processes in the oxic/anoxic water column of the
Black Sea.
While the distribution of particulate organic
matter (POM), the level of primary production,
and new production and temporal (seasonal to
decadal) variations in primary production are
somewhat known for the Black Sea (Vedernikov
and Demidov, 1997; Burlakova et al., 1997, 2003;
Ylmaz et al., 1998; Coban-Yildiz et al., 2000, 2006),
the distribution and cycling of DOM have been
poorly investigated (Polat and Tugrul, 1995; Morgan and Ducklow, 2000; Cauwet et al., 2002). Very
little is known about the importance of DOM for
carbon and nitrogen cycling in the Black Sea water
column and its DOC:DON ratio.
Data from 52 stations of nine cruises by MHI for
different seasons of 1987 to 1994 have been used to
construct average profiles of POC and PON (Fig. 3).
The average POC:PON ratio of 7.2 varies little and
differs from the Redfield value of 6.7 by only
10%. High values tend to occur at certain
locations during warmer periods (Burlakova et al.,
2003).
POM sinking in the Black Sea water column
(mostly marine snow aggregates) has been estimated
to vary in size (0.5–5.5 mm diameter) and settling
speeds (1.3–280 m d1) (Diercks and Asper, 1997).
20
0
0
50
50
(C)
0
2.4 2.8
W (POM), m/day
2
4
6
14
100
150
150
200
200
Sigma-t
100
Depth, m
Depth, m
15
16
17
Fig. 3. Vertical distribution of POC (A), PON (B) and the rate of sinking of POM (C) below the euphotic zone. (POC and PON data are
from MHI and IBSS cruises in 1984–1993. The sinking rate of POM has been derived from the 1988 KNORR data on the flux and
concentration of POM (Karl and Knauer, 1991). Explanations are in the text.
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
sumption of oxygen in the layer above the nitrate
maximum at st15.6, suggesting that respiration of
carbon-enriched DOM is important for the Black
Sea. For these calculations we used data for the
vertical distribution of nitrate and oxygen and
Eq. (1) to calculate the profiles of the vertical flux
(Konovalov et al., 2000). The derivatives of the
vertical flux in respect to depth (Eq. (2)) were used
to calculate the rate of net production minus
consumption. The rate of oxygen consumption
was calculated based on the rate of nitrate production, assuming that oxygen is consumed oxidizing
POM with POC:PON ¼ 106:16. The resulting
deficit of nitrate (shaded area) cannot be attributed
to active processes of nitrate consumption like
denitrification. Nitrate consumption, inferred from
data for nitrite (Fig. 4), occurs primarily in the
euphotic layer above st14.6 and in the suboxic
layer from st15.6 to 16.0, but not in the layer of
active consumption of oxygen. Osterroht and
Thomas (2000) have reported a similar situation
for the Baltic Sea, where AOU suggests production
of excess DIC, while equivalent production of
inorganic nitrogen or phosphorus does not occur.
Following Ogawa et al. (1999) and Kahler and
Koeve (2001), we assume that DOM in the Black
Nitrate Production-Consumption, M.m-1.y-1
9
-4x10
-2x109
0x100
2x109
4x109
From O2 data
14.5
15.0
Sigma-t
The rate of sinking is a complex function of the
density of both seawater and POM, of morphological characteristics of POM and ballast content,
which significantly vary in the Black Sea water
column. Thus, while parameterization of the rate of
POM sinking with a constant value may work in
rather thin layers (Oguz et al., 1999; Gregoire and
Lacroix, 2001), it may be insufficient if one wants to
simulate the biogeochemical structure and redox
budget for the pycnocline and the entire aphotic
zone to about 2000 m. As a first step, we derived the
profile of the sinking rate of POM from data on its
distribution and flux in the water column (Karl and
Knauer, 1991). The ratio of the flux to the
concentration gives an average rate of sinking
(Fig. 3C) that is used in the model. Data are not
available to distinguish between suspended, slow
and fast sinking POM. We fit the calculated values
to get a high-resolution profile (dashed line, Fig. 3C)
and modified the most upper part of the calculated
profile to limit the rate of sinking to an arbitrary
value of 0.2 m d1 at the upper boundary (solid line,
Fig. 3C).
Investigation of DOM has been a fast-developing
area of oceanography over the last decade (Hansell
and Carlson, 2001; Lefevre et al., 1996; Ogawa
et al., 1999). However, few publications have
addressed the distribution of DOM in the Black
Sea (Polat and Tugrul, 1995; Morgan and Ducklow,
2000; Cauwet et al., 2002). The vertical distribution
and seasonal variations for the Black Sea are similar
to other regions of the World Ocean, but the
concentrations of DOC in the Black Sea are higher.
The importance of DOM cycling in the ocean has
been uncertain until recently, while the ability of
DOM to transform to POM has been known since
at least 1963 (Baylor and Sutcliffe, 1963). Lefevre
et al. (1996) claimed that POC could support only
20% of the overall organic matter remineralization
in the aphotic layer (200–1000 m). However, Kahler
and Koeve (2001) concluded that DOM was needed
only to explain seasonal over-consumption of
oxygen in the euphotic zone, while its impact on
long-term carbon and nitrogen balance of the sea
was small.
Simultaneous measurements of DOM, POM,
oxygen consumption and ammonium and/or nitrate
production for the Black Sea are not available, but
the distributions of oxygen and nitrate are well
known (Fig. 2). The net production of nitrate
calculated from vertical distributions of nitrate
and oxygen (Fig. 4) reveals persistent over-con-
1827
From NO3 data
15.5
NO2-
16.0
0.00
0.20
0.40
Nitrite, µM
0.60
0.80
Fig. 4. Profiles (i) of the rate of nitrate production-consumption
derived from data on the distribution of nitrate and oxygen (solid
lines) and (ii) concentrations of nitrite (individual dots). (The
shaded area shows the layer and intensity of over-consumption of
oxygen due to respiration of carbon-enriched DON.)
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
1828
Sea is a mixture of a labile freshly produced fraction
(DOM(l)) with DOC:DON ¼ 23.5 and a refractory
fraction (DOM(r)) with DOC:DON ¼ 5. We also
assume after Baylor and Sutcliffe (1963) that labile
DOM can undergo transformation to POM (process 7, Table 1). This implies bacterial consumption
of labile DOM by partially oxidizing it for energy
supply and partially to use it to construct bacterial
biomass. Simplifying the scheme, we assume the
presence of only one fraction of POM with
POC:PON ¼ 106:16. POM can be respired to
refractory DOM (process 6, Table 1). Consumption
of refractory DOM (with DOC:DON ¼ 5) is not
considered in this scheme, because data on the
possibility of this process below the euphotic zone in
the Black Sea are not available. Thus, a physical
upward flux is the only sink of DOM(r).
2.2. Initial and boundary conditions and numerical
procedure
Average vertical profiles from the observed data
were used to initiate and calibrate the model, which
is to numerically simulate the biogeochemical
structure at steady state on a time scale of decades.
These profiles (Fig. 5) result from averaging tens to
hundreds of observations for POM, oxygen, sulfide,
nitrate, ammonium versus sigma-t scale obtained
from the central part of the Black Sea in the late
0
10
50
Di-nitrogen gas, µM
10
15
20
5
(A)
Ammonium, µM
20
30
40
1980s to early 1990s (KNORR-88, NATO TU-Black
Sea, NATO Ocean Data Base Management System
(ODBMS), etc.). Data on dissolved and suspended
manganese (Fig. 6) were pooled from the 1988
KNORR cruise (Lewis and Landing, 1991; Tebo,
1991), from several NATO TU-Black Sea cruises in
the early 1990s, and from the 2001 KNORR cruise
(unpublished data of B. Tebo). Data for dissolved
iron originated from the 1988 KNORR cruise (Lewis
and Landing, 1991) and NATO TU-Black Sea
cruises (unpublished data of E. Ovsyaniy, MHI,
Ukraine). Data on suspended iron are rare and the
initial profile originates from Lewis and Landing
(1991). Data of the vertical distribution of dinitrogen gas were pooled from several NATO
ODBMS cruises and the 2001 KNORR cruise
(Murray et al., 2003a, b). The profile of elemental
sulfur was simulated in numerical experiments to
compare to results from the 2001 KNORR expedition (unpublished data of G. Luther; Glazer et al.,
this volume; Konovalov et al., 2003). The total
profile of DOM was drawn to follow Morgan and
Ducklow (2000) and Cauwet et al. (2002) (Fig. 5B).
The boundary conditions were set using a flux at
the bottom boundary (st ¼ 17:236, 2132 m) and a
concentration at the upper boundary (st ¼ 14:4,
50 m). All values are listed in Table 2. The flux of all
solutes, except for dissolved Mn(II), ammonium
and sulfide, were set equal to zero at the bottom
25
(B)
0
0.3
PON, µM
0.6
0.9
1.2
1.5
16
20
O2
15.0
PON
15.0
16.0
N2
DON
17.0
H2S
0
0.0
16.0
NH4+
S°
17.0
Suboxic
zone
Sigma-t
Sigma-t
NO3-
100
200
Oxygen & Sulfide, µM
2.0
4.0
6.0
Nitrate, µM
8.0
300
0
4
8
12
DON, µM
10.0
Fig. 5. Numerically simulated (solid lines and open symbols) vs. initial profiles (dashed lines with solid symbols) of oxygen, sulfide, nitrate,
di-nitrogen, ammonium (A) and PON and DON (B) in the simulated water column.
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
Iron dissolved, µM
(A)
0
0.1
0.2
(B)
0
0.3
0.05
15.0
Sigma-t
15.0
Sigma-t
Iron particulate, µM
0.025
1829
Suboxic
zone
16.0
16.0
Mnpart
Fediss
Mndiss
17.0
0
4
8
Manganese dissolved, µM
Fepart
17.0
12
0
0.01
0.02
0.03
Manganese particulate, µM
Fig. 6. Numerically simulated (solid lines with open symbols) vs. average profiles (dashed lines with solid symbols) of dissolved (A) or
arbitrary profiles (dashed lines) of particulate (B) manganese and iron in the simulated water column.
boundary. The flux for dissolved manganese (II),
sulfide and ammonium were adjusted to keep the
concentration of these solutes in the bottom layer of
water at steady state. These fluxes are discussed
below. The concentrations at the upper boundary
were set to correspond to the average values for the
late 1980s–1990s or the published values for input of
suspended Mn(IV) and Fe(III).
The water column from st ¼ 14:4 (50 m) to the
bottom (st ¼ 17:236 at 2132 m) was divided into
intervals of Dst ¼ 0:01 (the three deepest levels were
set at st ¼ 17:233, 17.235 and 17.236), which vary in
depth from 0.25 m in the middle pycnocline
(st15.5) to 300 m near the bottom. The time
step of numerical integration was set to 0.0025 d.
The present version of the model allows simulation
of about 5 years of the Black Sea evolution per hour
of numerical integration on a PC equipped with a
Pentium 2.2 GHz processor.
2.3. Numerical simulation of the biogeochemical
structure
The rates of the processes depend on the vertical
distribution of individual components and these
rates affect these distributions at every step of the
integration. Distributions of biogeochemical properties are generated as the model runs forward in
time. Vertical advection and diffusion influence all
properties. Biogeochemical processes are linked and
coupled through those substances that take part in
multiple processes. Thus, the profile of oxygen, for
example, is affected by physical processes of
advection, diffusion, entrainment (st o15:5) and
intrusions (st 415:5) of the Bosporus plume, and
by nine biogeochemical processes. The generated
distribution of oxygen affects both physical fluxes of
oxygen and the intensity of all nine biogeochemical
processes.
Initial experiments were conducted to calibrate
the model and to optimize the set of processes in
order to keep the numerically simulated biogeochemical structure as close to the average profiles as
possible (Figs. 5 and 6). An initial attempt to
simulate the biogeochemical structure without
including DOM cycling revealed that either consumption of POM and production of nitrate became
unrealistically high or modeled consumption of
oxygen in the upper pycnocline was too low. This
resulted in a downward movement of the oxycline
with time or in a distortion of the profile of nitrate
with a few-fold increase in the maximum concentrations and an unobserved shift of this maximum to
st15.1, where the maximum of oxygen consumption was observed (Fig. 4). When DOM cycling was
included, the distribution, flux and rate of production–consumption of oxygen, POM and nitrate
became reasonably close to the observed values
(Fig. 5). The difference between the simulated and
initial vertical distribution of nitrate may be related
to our poor understanding the distribution and
reactivity of DOM and its C:N ratio in the Black
Sea.
Similarly, we could not accurately simulate the
distribution of sulfide assuming that it was oxidized
by suspended manganese (IV) to sulfate. The deeper
part of the profile of nitrate, the upper part of the
profile of sulfide, and the suboxic/anoxic part of the
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
profile of dissolved manganese (II) were distorted
and shifted relative to observed data. Consideration
and parameterization of elemental sulfur cycling, as
an intermediate product of oxidation of sulfide,
resulted in a simulated peak of elemental sulfur
(Fig. 5A), whose magnitude and depth fit precisely
the results of the 2001 KNORR expedition (Glazer
et al., 2006; Konovalov et al., 2003). The anoxic
part of the simulated distribution of elemental
sulfur predicted higher concentrations than observed probably because biogeochemical processes
governing elemental sulfur consumption under
anoxic conditions were not considered. Thus,
elemental sulfur appears to be an essential redox
component that needs to be considered to correctly
simulate the oxic/anoxic structure and the redox
budget of the Black Sea water column.
The model predictions of the biogeochemical
structure of the oxic/anoxic water column (Figs. 5
and 6) successfully reproduce the observed system
and remains close to steady state on a time scale
of several decades. It did drift slowly, so that
the detectable changes were observed over time
scales of a century. We used T–S data averaged for
about 70 years to parameterize vertical exchange in
the water column, and biogeochemical data averaged for about one decade to parameterize and
calibrate redox processes, so any deviations from
steady state in excess of a century could reflect
natural trends or limitations in the applied parameterizations.
3. Discussion
3.1. Redox budget and importance of individual
processes
When physical and biogeochemical processes are
in balance, the budget and distributions of properties are at steady state. The model provides an
independent way to estimate the importance of
individual processes, as they cannot be modified and
fixed individually, but have to be adjusted simultaneously to keep all simulated profiles as close to
the initial average distributions, as possible (Figs. 5
and 6). Figs. 7, 9 and 10 present data on the
numerically simulated budgets of individual biogeochemical components. We believe that the budget
simulated in this way reveals the importance of
specific physical and individual biogeochemical
processes.
3.1.1. Oxygen
The simulated budget of oxygen for the early
1990s (Fig. 7A) strongly depends on the diffusive
flux of oxygen from the Cold Intermediate Layer
(CIL, Fig. 1), as this flux is the only source of
oxygen for the layer of the oxycline, where oxygen is
mostly consumed to oxidize organic matter. About
30% of this consumption is spent to oxidize POM,
while 40% is used to oxidize DOM. The important
role of DOM for O2 consumption explains the
excess-consumption of oxygen in the upper oxycline
(Fig. 4). Lefevre et al. (1996) reported that POM
could account for 20% of oxygen consumption
in the Mediterranean. However, the Mediterranean is less biologically productive and the ratio
of POM/DOM production is lower than in the
Black Sea.
About 10% of oxygen is consumed to oxidize
ammonium to nitrate, mostly in the layer of the
oxycline above the suboxic zone (the vertical
distributions of the rate of individual physical and
biogeochemical processes are not shown). Only 4%
is utilized in redox processes in the suboxic zone
itself. The other biogeochemical processes we
consider here play a minor role and do not affect
the budget of oxygen to any significant extent. Only
about 0.1% of the vertical flux of oxygen is spent to
oxidize sulfide and other reduced species coming up
from the anoxic zone. The specific rate constants of
oxidation of sulfide and ammonium or manganese
(II) and iron (II) are much higher than similar
values for oxidation of POM and DOM (Table 1),
but the vertical flux of oxygen does not reach the
lower part of the suboxic zone and therefore cannot
play any important role in suboxic biogeochemistry
(Murray et al., 1995).
The sum of all biogeochemical processes in the
oxic and suboxic zones appears to be responsible for
consumption of 88% of the vertical flux of oxygen.
The remaining 12% is entrained into the Bosporus
plume to generate the lateral flux of oxygen into the
suboxic and anoxic zones. Entrainment of Black Sea
water into the Bosporus plume and intrusion of the
plume waters in the anoxic zone has been discussed
by Murray et al. (1991) and Ozsoy et al. (1995) for
physical properties and by Buesseler et al. (1991) for
cesium-137, but intrusions of the plume waters also
should generate the lateral flux of oxygen. This flux
of oxygen has been previously deduced (Konovalov
and Murray, 2001) from deviations of the ratio of
sulfide to ammonium in the anoxic zone from the
expected value (Fig. 8B) and it has been recently
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
(A)
(B)
DOM(l) to POM
POM to NH4
NH4 to NO3
S(0) to SO4
POM to DOM(r)
DOM(l) to NH4
H2S to SO4
Mn(II) to Mn(IV)
Fe(II) to Fe(III)
1831
Sulfide by Mn(IV)
Sulfide by NO3
Sulfide by Fe(III)
Sulfide by O2
DOM(l) respiration
POM respiration
Intrusion
Entrainment
Advection
Intrusions
Entrainment
Advection
Diffusion
Diffusion
Biogeochemical processes
Biogeochemical processes
Physical processes
Physical processes
Balance
-12
Balance
-8
-4
0
4
8
12
Consumption or Production of Oxygen,
µM.m-2.day-1
(C)
-1.0
-0.5
0.0
0.5
Consumption or Production
of Sulfide, µM.m-2.day-1
(D)
H2S by NO3 to N2
Mn(II) by NO3 to Mn(IV)
NH4 & NO3 to N2
POM by NO3
Fe(II) by NO3 to Fe(III)
DOM(l) by O2 to NH4
DOM(l) respiration
POM respiration
POM by O2 to NH4
NH4 by O2 to NO3
Intrusion
Entrainment
Advection
Diffusion
1.0
NH4 by O2 to NO3
NH4 & NO3 to N2
DOM(l) & NH4 to POM
NH4 by Fe(III)
NH4 by Mn(IV)
Intrusions
Entrainment
Advection
Diffusion
Biogeochemical processes
Biogeochemical processes
Physical processes
Balance
-0.6
Physical processes
Balance
-0.3
0
0.3
0.6
Consumption or Production of Nitrate,
µM.m-2.day-1
-1.0
-0.5
0.0
0.5
1.0
Consumption or Production of Ammonium,
µM.m-2.day-1
Fig. 7. The oxygen (A), sulfide (B), nitrate (C), and ammonium (D) simulated budget in the water column. (Bars are in three groups at
every diagram to show the importance of individual biogeochemical processes (upper group), physical processes (middle group), and an
integrated result (lower group) of bars.)
7.6
7.8
Temperature, C
8
8.2
8.4
(A) 12
(B) 16.0
2001 KNORR data
Voltammetric Data
Volumetric Data
Temperature, C
16.2
Sigma-t
Sigma-t
13
14
16.4
16.6
15
1988 KNORR data
The ratio 16/53
equation 4, Table 1
16.8
16
17.0
0
100
200
300
Oxygen, µM
400
0.0
1.0
2.0
Ammonium/Sulfide Ratio
3.0
Fig. 8. Lateral intrusions of oxygenated Bosporus plume waters (A) and the result of these intrusions for the ammonium/sulfide ratio (B).
Data are reproduced from Konovalov et al. (2003) and Konovalov and Murray (2001).
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confirmed (Konovalov et al., 2003; Glazer et al.,
2006) by direct observations (Fig. 8A).
3.1.2. Sulfide
The simulated budget of sulfide (Fig. 7B) reveals
quantitative estimates of individual processes that
can be hardly resolved from direct measurements.
Only 8% of sulfide can be produced from respiration of DOM, while 74% of sulfide production is
generated due to respiration of POM. Any attempt
to increase the specific rate constant of anoxic
respiration of DOM alters the entire biogeochemical
structure for the worse. The minor role of DOM in
sulfide production fits well the conclusions from
other studies, that DOM is important for biogeochemical processes in the upper part of the water
column, while POM basically drives biogeochemistry of deep layers of water (e.g., Kahler and
Koeve, 2001). The fact that 82% of the sulfide is
produced due to respiration of organic matter in the
anoxic water column is not surprising, as the
microbiological origin of sulfide is presently widely
accepted. The other 18% of sulfide production is
estimated to flux from sea-bottom respiration of
organic matter sinking to the sediments. Our model
estimated value of 0.2 mmole m2 d1 fits well the
published rate of sulfide production in Black Sea
sediments of 0.6 mmole m2 d1 (Weber et al., 2001),
as only a fraction of sulfide produced reaches the
water column. Most of the sulfide produced is
buried in the sediments (see review by Rickard et al.,
1995).
Based on these model results oxidation of sulfide
by the vertical flux of oxygen accounts for less than
0.5% of the total upward flux of sulfide. This
process is not artificially limited in the model by, for
example, a low specific rate constant of this process
(Table 1). The applied specific rate constant of
oxidation of sulfide suggests its t1/2 of about 0.3 h
for oxygen saturated conditions, which agrees with
data published by Millero (1991). Rather, oxidation
of sulfide by the vertical flux of oxygen does not
happen because sulfide and oxygen are consumed by
other processes and concentrations of these components are too small at the onset of sulfide to support
oxidation of any importance. Sinking manganese
(IV) oxides, generated in the suboxic zone, oxidize
almost 25% of the vertical flux of sulfide. About 8%
of the flux of sulfide is oxidized by nitrate, but only
2% is oxidized by the vertical flux of nitrate, while
6% is oxidized inside the anoxic zone due to the flux
of nitrate injected with the Bosporus plume. In a
similar way the lateral flux of oxygen (Fig. 8)
oxidizes over 60% of sulfide inside the anoxic zone.
The mechanism of this process includes mediation
and catalysis by manganese (II)–manganese (IV)
redox transformations (Luther et al., 1991), but
catalytic cycles do not affect the overall redox
budget and they are not parameterized in this work,
although the catalytic effect is taken into account by
the value of specific rate constants.
The simulated budget of sulfide reveals that about
5% of the sulfide remains available to increase the
inventory of sulfide in the anoxic zone. This value
may demonstrate the presence of some uncertainty
in the rates of different processes, but this also is
consistent with observations that the inventory and
concentrations of sulfide are increasing with time
inside the anoxic zone (Konovalov et al., 1999a, b;
Konovalov and Murray, 2001).
3.1.3. Nitrate
The budget of nitrate (Fig. 7C) is linked to the
budgets of oxygen, sulfide and ammonium (Fig. 7),
organic matter (Fig. 9), manganese and iron (Fig. 10).
Nitrate is the ultimate product of oxidation of
ammonium. The rate of this process increases
towards the maximum of nitrate around st15.5
and then decreases abruptly in the suboxic zone
towards the onset of sulfide (data are not shown).
The very low concentrations of oxygen in the
suboxic zone result in low rates of organic matter
oxidation and ammonium production.
Neither oxidation of organic matter nor dissolved
iron by nitrate appears to play an important role in
the Black Sea but for different reasons. Ottley et al.
(1997) have demonstrated that direct chemical
reduction of nitrate by dissolved iron (II) is feasible,
but oxidation of iron cannot play an important role
for nitrate in the Black Sea because the upward flux
of iron (II) is too small to impact the nitrate budget
(this may not be true for other oxic/anoxic marine
systems). Oxidation of organic matter by nitrate
does occur in the Black Sea and the rate of this
process is proportional to the concentration of
organic matter and nitrate, but the concentrations
of organic matter and nitrate, as well as the
concentration of N2O (data of M. Westley from
the 2001 and 2003 KNORR cruises), and the
thickness of the suboxic layer in the Black Sea are
much smaller than in the regions of the Arabian Sea
where denitrification is important for the redox
budget.
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
(A)
(B)
POM by O2 to NH4
1833
DOM(l) by O2 to POM
POM respiration
DOM(l) & NH4 to POM
POM by O2 to DOM(r)
DOM(l) respiration
POM by NO3
DOM(l) by O2
DOM(l)&NH4 to POM
DOM(l) by O2 to POM
Intrusion
Intrusion
Entrainment
Entrainment
Advection
Advection
Sinking
Diffusion
Biogeochemical processes
Biogeochemical processes
Physical processes
Physical processes
Balance
-1
Balance
-0.5
0
0.5
Consumption or Production
of POM, µM.m-2.day-1
1
-1
-0.5
0
0.5
Consumption or Production
of DOM(l), µM.m-2.day-1
1
Fig. 9. The POM (A) and DOM(l) (B) simulated budget in the water column.
(A)
(B)
Mn(II) by NO3
Mn(II) by O2
Mn(IV) by NH4
Mn(IV) by Fe(II)
MnCO3 dissolution
Fe(II) to FeS2
Fe(II) by Mn(IV)
Fe(II) by NO3
Fe(II) by O2
Fe(III) by NH4
Fe(III) by Sulfide
Intrusion
Intrusion
Entrainment
Entrainment
Advection
Advection
Diffusion
Diffusion
Biogeochemical processes
Biogeochemical processes
Physical processes
Physical processes
Balance
Balance
-0.40
-0.20
0.00
0.20
Consumption or Production
of Mn(II), µM.m-2.day-1
(C)
0.40
-0.06 -0.04 -0.02
0
0.02 0.04
Consumption or Production
of Fe(II), µM.m-2.day-1
(D)
Mn(IV) by Sulfide
Mn(IV) by Fe(II)
Mn(IV) by NH4
0.06
Fe(III) by Sulfide
Fe(III) by NH4
Fe(II) by O2
Fe(II) by NO3
Fe(II) by Mn(IV)
Mn(II) by O2
Mn(II) by NO3
Entrainment
Entrainment
Sinking
Advection
Sinking
Advection
Diffusion
Diffusion
Biogeochemical processes
Physical processes
Biogeochemical processes
Physical processes
Balance
-0.30 -0.20 -0.10 0.00 0.10 0.20
Consumption or Production
of Mn(IV), µM.m-2.day-1
Balance
0.30
-0.06 -0.04 -0.02
0
0.02 0.04
Consumption or Production
of Fe(III), µM.m-2.day-1
0.06
Fig. 10. The dissolved manganese (A) and iron (B), and suspended manganese (C) and iron (D) simulated budget in the water column.
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The model predicts more than 12% of nitrate
consumption to oxidize the upward flux of ammonium from the anoxic zone. This process is known
as the anammox reaction between nitrite and
ammonium (Kuypers et al., 2003). Murray et al.
(1995, 2003b) discussed this process in regard to
denitrification and production of di-nitrogen gas in
the suboxic zone. In addition, over 19% of nitrate
consumption appears to be utilized to oxidize
dissolved manganese in the suboxic zone, while
other 24% occurs during oxidation of sulfide inside
the anoxic zone.
In total, 57% of nitrate produced in the Black Sea
is consumed in redox processes in the suboxic and
anoxic layers. The flux of nitrate to the Black Sea
with the Mediterranean waters (Ozsoy et al., 1995)
is equivalent to as much as 3% of nitrate production
and the upward flux of nitrate at the upper
boundary of the simulated water column accounts
for 46% of nitrate production. (57% of nitrate
consumption and 46% of the upward flux equal
100% of production and 3% of influx with the
Mediterranean waters.) The upward flux of nitrate
to the euphotic zone equals 39%, when calculated
for the initial profile of nitrate (Konovalov et al.,
2000), and we consider 7% difference to be a good
result, as very little is known about the POM:DOM
ratio and DOC:DON composition of DOM in the
Black Sea.
Among all components of the budget of nitrate,
the amount of nitrate that is consumed to oxidize
the upward flux of dissolved manganese is the most
intriguing. This process has never been confirmed
by direct microbiological measurements (Tebo,
1991), but it is often referred to (e.g., Murray
et al., 1995; Oguz et al., 2001; Luther et al., 1997).
A similar process of oxidation of iron (II) by nitrate
has been reported by Ottley et al. (1997). It has been
proposed (Konovalov et al., 2004) that oxidation of
dissolved manganese by nitrate is the process that
can balance the redox budget of the suboxic zone
and explain the observed vertical profile of dissolved
manganese. This process might involve Mn(II)–
Mn(III)–Mn(IV) redox transformations, a catalytic
cycle of trace metals (Luther et al., 1997) or
hydrogen peroxide (detected from the results of
voltammetric profiling; unpublished data of B. Tebo
and G. Luther from the 2001 and 2003 KNORR
expedition to the Black Sea). The results of
numerical experiments are not proof of oxidation
of dissolved manganese by nitrate, but they
demonstrate that the budget of oxygen in the
suboxic zone cannot support the redox budget of
manganese, while nitrate can. Experimental microbiological investigations of manganese redox cycling
are thus very important.
3.1.4. Ammonium
POM oxidation in the oxic layer and POM
respiration in the sulfidic zone appear to be the
major sources of ammonium in the Black Sea water
column (Fig. 7D) and account for 61% and 32% of
its production. These processes are most important
to sustain a steady-state distribution of ammonium
in the oxic, the suboxic and the upper to middle part
of the anoxic layer. An attempt to simulate aerobic
or anaerobic oxidation of DOM with an equivalent
release of ammonium has revealed that these
processes are not of major importance for the
budget of ammonium. This is consistent with data
showing that ammonium and amino acids are
consumed by microorganisms, rather than released,
in the presence of DOM (Amon and Benner, 1996).
As with sulfide, we predict there should be
substantial flux of ammonium from the sediments
to support the distribution of ammonium in, and to
balance the physical upward flux out of, the deepest
anoxic layers. This flux of ammonium should be
close to 6% of all sources of ammonium.
Sources of ammonium are balanced by the
processes of ammonium oxidation in the oxic layer
(72%) and de-nitrification (including anammox) in
the suboxic layer (15%). Choe et al. (2000)
discussed denitrification of nitrate by iron to dinitrogen gas, and Luther et al. (1997) demonstrated
that oxidation of ammonium by manganese (IV) is
thermodynamically possible. However, attempts to
numerically simulate oxidation of ammonium by
manganese (IV) or iron (III) oxides show that these
processes are probably not important for the budget
and distribution of ammonium.
Utilization of DOM and ammonium to produce
POM (mimicking bacterial DOM and ammonium
utilization) can be responsible for consumption of
about 12% of produced ammonium. The average
upward flux of ammonium to the euphotic zone is
extremely small because both the concentration and
the vertical gradient of concentration are very low,
as compared to nitrate (Fig. 5A).
3.1.5. DOM and POM
The simulated budget of POM (Fig. 9A) suggests
that sinking from the euphotic zone provides 55%
of POM that is oxidized and respired in the water
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column. The reminder of the POM supply seems to
be derived by bacterial conversion of labile DOM(l)
to POM. If production of POM from DOM(l) is not
included in the model, it becomes impossible to
generate (i) the observed over-consumption of
oxygen and a lack of nitrate in the upper oxycline
(Fig. 4), and (ii) the major sink of labile DOM(l)
(Fig. 9B). The simulated bacterial DOM(l) utilization, which is responsible for 98% of the overall
consumption of DOM (Fig. 9B), is parameterized
by two major processes. The most important one
(86%) represents oxidation of a large portion of
organic carbon in DOM(l) to produce energy. This
agrees with the published low efficiency of bacterial
consumption of DOM (Kahler et al., 1997; Ducklow et al., 2002). A minor part of carbon and all
nitrogen is converted by heterotrophic microorganisms into biomass. Incorporation of DOM(l) and
ammonium from ambient waters to produce POM
is also significant (12%). While the flux, production
and utilization of energy have not been calculated
and parameterized in the present version of the
model, the results for the importance of individual
processes obtained by fitting the observed distributions agrees with those for an optimized bioenergetic model of bacterial DOM utilization (Vallino
et al., 1996). For several possible processes, the
most energy-efficient process becomes the major
way for both bacterial growth and geochemical
transformations.
Production and sinking of POM is balanced by its
oxidation in the oxic layer (71%) and respiration in
the anoxic layer (29%). This partitioning of overall
consumption of POM between oxic and anoxic
layers fits well the published data by Lein and
Ivanov (1991) on the sulfur and carbon balances in
the Black Sea.
3.1.6. Manganese and iron
The budgets of reduced (dissolved) and oxidized
(suspended) forms of manganese and iron (Fig. 10)
reveal several features that make these elements
similar in one way and different in another. Thus,
physical processes redistribute dissolved iron (II)
between individual layers of the water column, but
do not affect the overall budget of dissolved iron
(II), as fluxes of this solute at the boundaries of the
water column are equal or close to zero. The flux of
dissolved manganese (II) from sediments has been
adjusted to be about 1% of the overall production
of this form of manganese, and model results
suggest this flux cannot be larger at steady state.
1835
Results of initial numerical experiments demonstrate that the flux of dissolved iron (II) from
sediments is equal to zero. This demonstrates that
pyritization in Black Sea sediments prevents the net
flux of dissolved iron (II) to the water column
(Rickard et al., 1995).
The flux of manganese at the upper boundary of
the modeled water column (st ¼ 14:4, 50 m) is 20%
of its flux from sediments and it is below 0.2% of
produced in the water column (Fig. 10A), making
the budget of manganese basically dependant on
recycling inside the water column. Temporal variations are very slow, and the residence time of
manganese in the Black Sea water column is on the
time scale of millennia (Lewis and Landing, 1991;
Konovalov et al., 2004). The flux of iron at the
upper boundary of the modeled water column
(st ¼ 14:4, 50 m) is about 70 times the flux for
manganese, while the inventory of iron in the water
column is about 0.005 times that for manganese. In
contrast to manganese, the external supply of iron
supports 54% of the sources of iron (III). Thus, we
predict a short residence time and fast temporal
variations in the distribution of iron in response to
changes in external fluxes of iron to the Black Sea.
Both dissolved manganese (II) and iron (II) are
oxidized in the lower part of the suboxic zone, but
the model predicts that 97% of the dissolved
manganese is oxidized by nitrate (Fig. 10C), while
39% of dissolved iron (II) is oxidized by nitrate and
the rest is oxidized by suspended manganese (IV)
(Fig. 10D). The latter process has been investigated
by Postma (1985) and Postma and Appelo (2000)
for sediments and in laboratory experiments and
parameterized for the Black Sea conditions by
Konovalov et al. (2004). The main evidence for
considering this process is that oxidation of
dissolved iron (II) occurs both in the lower part of
the suboxic zone and in the upper part of the anoxic
layer. This process appears to be important for the
budget of iron (Fig. 10D), but it consumes less than
3% of suspended manganese (IV) (Fig. 10C).
Suspended manganese (IV) and iron (III) are
primarily used to oxidize sulfide (Fig. 10C and D).
This accounts for 96% of the sink of manganese
(IV) and results in oxidation of up to 25% of the
upward flux of sulfide (Fig. 7B). A similar process
accounts for consumption of 84% of the particulate
iron (III) flux, but it has a minor effect for the
budget of sulfide because the absolute flux of iron
(III) is much smaller, compared to manganese (IV).
Bottcher and Thamdrup (2001) have reported on
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
oxidation of sulfide by manganese (IV) and iron
(III) to sulfate, but our results fit the data published
by Yao and Millero (1993, 1996) which suggest
elemental sulfur is the main product. The presence
of elemental sulfur in the lower suboxic and upper
anoxic zone was reported by Jorgensen et al. (1991)
and Luther et al. (1991) and more recently by
Luther (unpublished data from the 2001 KNORR
expedition), Konovalov et al. (2003), and Glazer et
al. (2006). The simulated profile of elemental sulfur
fits quite well the maximum values and the location
of the maximum in the very upper anoxic zone, but
the simulated peak of elemental sulfur is much
broader compared with observations (Fig. 5A),
because the model does not include consumption
of elemental sulfur in the anoxic zone of the sea.
Manganese is largely recycled within the water
column. The upward flux of dissolved manganese
(II) increases towards the suboxic/anoxic boundary,
as dissolved manganese (II) is oxidized in the
suboxic zone to ultimately produce suspended
hydrous manganese (IV) oxide. The latter sinks
back to the anoxic zone facilitating oxidation of
sulfide and production of suspended manganese (II)
carbonate. The MnCO3 sinks into deeper layers and
is dissolved, compensating the upward flux and
keeping the vertical distribution of Mn(II) at a
steady state. The flux of manganese both at the
upper (st ¼ 14:4, 50 m) and lower (st ¼ 17:236,
2132 m) boundaries of the water column is very
small, and it cannot result in annual-to-decade
variations in the distribution of manganese.
Unlike manganese, the budget and distribution of
iron crucially depend on the external flux to the
water column. This flux is required to balance the
loss (precipitation) of iron sulfide from the water
column (Cutter and Kluckhohn, 1999; Rickard and
Luther, 1997), which is equal to 54% of the iron
(II)—iron (III) redox transformations. This makes
the distribution of iron sensitive to temporal
variations in external supply of iron that can result
in at least 2-fold changes in the inventory of
dissolved iron (II) in the water column over a
period of 5–10 years (Konovalov et al., 2004). While
the distribution of manganese is sensitive to the
basic redox structure, recycling and redistribution
of manganese within the water column are the
primary processes in its budget, but iron reveals a
sequence of redox and dissolved-suspended transformations from the upper boundary of the water
column towards sediments, rather than cycling
within the water column.
3.2. Evolution of the biogeochemical structure
The calculated budget of oxygen (Fig. 7A)
suggests that the vertical distribution of the main
redox species and the structure of the oxic and
suboxic zone depend strongly on the concentration
of oxygen in the CIL (the main source) (Fig. 1A)
and export production of POM (the main sink). The
concentration of oxygen in the CIL is important
because this concentration determines the overall
gradient of oxygen through the oxycline, which in
turn drives the vertical diffusive flux. Export
production appears to be responsible for consumption of up to 85% of the vertical flux of oxygen.
This makes the vertical distribution of oxygen (and
thus the structure of the oxycline and location of the
upper boundary of the suboxic zone) very sensitive
to any climate- and human-driven changes in
eutrophication.
After a sequence of years with mild winters,
which result in weakening of ventilation of the CIL,
the oxygen concentration can vary by a factor of 2,
from 320 mM in 1993 (Konovalov and Murray,
2001; data from the TU-Black Sea database) to
180 mM, in 2001 (data from the cruise of R.V.
KNORR 2001). Some numerically generated results
for decreasing concentration of oxygen in the CIL
are presented in Fig. 11A. All parameterizations
of biogeochemical processes and the export production of organic matter are the same as described
above, while the concentration of oxygen in the CIL
has been set at 180 mM simulating the observed
warming and weakening of ventilation from 1993
to 2001. The model realistically reproduces the
observed changes, as it is demonstrated by comparison with the cruise data from the central and
northern deep part of the sea, which are directly not
affected by the lateral flux of oxygen (Murray et al.,
2003a).
The most prominent result of a reduction in
ventilation of the CIL is that the oxycline moves up
and the thickness of the suboxic zone increases. A
decrease in the maximum concentration of nitrate,
and a slight shoaling of the onset of dissolved
Mn(II) (Fig. 11A) and sulfide (Murray et al., 2003a)
also occur after this perturbation. The fact that
variations in the suboxic zone thickness primarily
result from changes in the depth of the upper
boundary of this layer, whereas changes in the
location of the onset of sulfide are minor, also is
consistent with published data on the temporal
changes in the structure of the suboxic zone
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S.K. Konovalov et al. / Deep-Sea Research II 53 (2006) 1817–1841
Mn(II) & NO3, µM
2
4
6
8
(A)
0
14.5
2
0
4
6
8
10
14.5
O2
O2
15.0
NO3
15.5
Sigma-t
Sigma-t
Mn(II) & NO3, µM
(B)
10
15.0
16.0
Mn(II)
NO3
15.5
16.0
16.5
16.5
H2S
17.0
1837
17.0
NH4
0
Mn(II)
H2S
100
200
300
O2, H2S and NH4, µM
400
NH4
0
100
200
300
O2, H2S and NH4, µM
400
Fig. 11. Numerically simulated (dashed lines) evolution vs. initial (solid lines) biogeochemical structure and vs. 2001 KNORR data
(individual points) due to variations in the concentration of oxygen in CIL (A) and export production (B).
(A)
Mn(II) & NO3, µM
2
4
6
0
14.5
8
0
10
2
4
14.5
O2
Sigma-t
NO3
15.5
16.0
8
10
O2
NO3
15.5
16.0
Mn(II)
16.5
17.0
6
15.0
15.0
Sigma-t
Mn(II) & NO3, µM
(B)
Mn(II)
16.5
H2S
17.0
NH4
0
H2S
100
200
300
O2, H2S and NH4, µM
400
NH4
0
100
200
300
O2, H2S and NH4, µM
400
Fig. 12. Numerically simulated evolution of the biogeochemical structure and transformation of the suboxic zone in absence of the lateral
flux of oxygen in 5 (A) and 12 (B) years. (Solid lines—simulated profiles, dashed lines—initial data.)
(Buesseler et al., 1994; Konovalov and Murray,
2001).
The influence of eutrophication on the biogeochemical structure of the Black Sea water column,
as compared to the effects of climate change on the
ventilation of the CIL, was investigated by increasing the export production 2-fold and keeping all
other applied parameterizations and boundary
conditions unchanged (Fig. 11B). While the upper
oxycline does not change much, the suboxic zone
broadens, nitrate concentrations increase, and the
onset of sulfide shoals slightly fitting observations
for the 1980s (Konovalov et al., 1999b; Konovalov
and Murray, 2001).
The most fascinating result of these numerical
experiments is related to the nature of the suboxic
zone. Konovalov and Murray (2001) suggested that
the suboxic zone could exist when the flux of
organic matter is enough to consume the vertical
flux of oxygen, if the upward flux of sulfide does not
exceed the oxidative capacity of the Bosporus
plume. If this is true, the suboxic zone would not
exist if the Bosporus plume waters were oxygen-free.
We tested this scenario in an experiment where the
parameterizations and boundary conditions were
kept unchanged, but the concentration of oxygen in
the Bosporus plume was set to zero (Fig. 12). The
simulated ‘‘shrinking’’ of the suboxic zone and
appearance of a layer with overlapping O2 and H2S
(the ‘‘C-layer’’) is another indication of the critical
role played by the lateral flux of oxygen from the
Bosporus Plume.
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This experiment also allows prediction of the
possible consequences of eutrophication, which
exceeds the oxidative capacity of the Bosporus
Plume. With an increase in the export flux of
organic matter, the oxic/anoxic boundary moves
upward towards the upper boundary of the suboxic
zone. Nitrate is consumed during remineralization
of organic matter and compensation of the upward
flux of reducers from the anoxic layer. Concentrations of nitrate decrease several-fold but nitrate
alone cannot sustain the suboxic zone, which
disappears in about 5–10 years (Fig. 12). The
oxycline moves up to the depth where the vertical
flux of oxygen balances the downward flux of
organic matter and upward flux of sulfide and other
reduced species. The suboxic zone disappears and a
layer of co-presence of oxygen and sulfide appears,
making this virtual situation in the Black Sea similar
to the presently observed structure in Mariager
Fjord (Zopfi et al., 2001), Framvaren Fjord
(Velinsky and Fogel, 1999) and frequently in the
Cariaco Trench (Scranton et al., 2001).
Acknowledgments
This work was funded by the NATO Collaborative
Linkage grant to SK and JM. SK acknowledges
partial support from CRDF Projects #UG1-2432-SE02 and #UG2-2080. JWM acknowledges NSF Grants
OCE 0081118 and MCB 0132101. GWL acknowledges NSF Grant OCE-0096365. BMT acknowledges
NSF Grants OCE-0221500 and EAR-9725845.
Data on POM have been generously provided by
Z.P. Burlakova and L.V. Eremeeva from Marine
Hydrophysical Institute, Ukraine.
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