1 supplements - bg.copernicus.org€¦ · 1 supplements 1.1 detailed model description the...
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1 Supplements
1.1 Detailed model description
The reactions in the reactive transport model describe organic matter degradation coupled to different electron acceptors.Reactions are divided in primary redox reactions and other biogeochemical reactions (Table S.6). The succession of oxidantsduring organic matter degradation (Froelich et al., 1979) is described by means of Monod kinetics (Table S.2; Boudreau (1997)).5This means that the oxidants with the highest metabolic free energy yield are preferentially used until they become limiting andthe oxidant with the next highest energy yield is used (Berg et al., 2003; Boudreau, 1996a; Wang and Van Cappellen, 1996).Respiratory reactions occur where O2, NO
–3 , Mn(OH)2, Fe(OH)3 and SO4
2− serve as electron acceptors and finally organicmatter is subject to methanogenesis (Reed et al. (2011a, b); Rooze et al. (2016); Table S.2). Organic matter includes carbon (C),nitrogen (N) and P in a C:N:P ratio of 106:16:0.35. In the model, oxidation of CH4 is possible with O2, Mn(OH)2, Fe(OH)3 and10SO4
2−. Dissolved inorganic carbon in the model is calculated as the sum of the carbon in CO2 and HCO2–
3 , which is producedor consumed by modeled reactions (Table S.6).
The generic mass conservation equations for solids and solutes are described by Eq. 1 and 2;
(1 −φ)∂Cs∂t
=−(1 −φ)v ∂Cs∂z
+∑
Rs (1)
φ∂Caq∂t
= φD ′∂2Caq∂z2
−φu ∂Caq∂z
+∑
Raq (2)15
D ′ =Dm
1 − lnφ2(3)
where Cs is the concentration of solid species (mol L−1), Caq is the concentration of dissolved species (mol L−1), t is time(yr), φ is the sediment porosity, v and u are the advective velocities of solid and dissolved species (cm yr−1), respectively.Variables v and u were described by a depth-dependent function to account for changes in porosity (Meysman et al., 2005).Distance from the sediment-water interface is z (cm), D′ the diffusion coefficient of dissolved species (cm2 yr−1), corrected20for tortuosity in the porous medium ((Boudreau, 1996b), Eq. 3).
∑Rs and
∑Raq are the net reaction rates from the chemical
reaction (Table S.2) for solid and dissolved species.Porosity (φ) is described by Eq. 4 to account for sediment compaction (Meysman et al., 2005; Reed et al., 2011b),
φ(x ) = φ∞+(φ0 −φ∞)e−xy (4)
where φ0 is the porosity at the sediment-water interface, φ∞ is the porosity at depth and y is the porosity attenuation25factor/e-folding distance (Fig. S.3A, Table S.3). The model code was written in R with the use of the marelac geochemicaldataset package (Soetaert et al., 2010). To calculate the transport in porous media, the R package Reactran was used (Soetaertand Meysman, 2012). The set of ordinary differential equations was solved numerically with the Lsode integrator algorithm(Petzold, 1983).
Zero gradient boundary conditions were applied to the base of the model domain for all chemical species. To avoid influence30of the boundary conditions at the base of the model domain results, the total depth of the model was set to 90 cm (divided into900 grid cells of 0.1 cm).
Reaction parameters were mostly taken from literature or obtained within existing parameter ranges (Table S.7). If thesewere not available, or no fit to the data could be obtained with existing ranges, parameters were constrained by fitting themodel to the measured data.35
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NB1
ww
m−2
1995 2000 2005 2010 20150102030405060
N6
ww
m−2
1995 2000 2005 2010 20150
50
100
150
N10
ww
m−2
1995 2000 2005 2010 20150
10
20
30
40
50M. BalthicaM. AffinisMarenzelleria spp.Saduria entomon
N7
ww
m−2
1995 2000 2005 2010 20150102030405060
Year
NB8
ww
m−2
1995 2000 2005 2010 20150
5
10
15
20
Mac
rofa
una
Mac
rofa
una
Mac
rofa
una
Mac
rofa
una
Mac
rofa
una
Figure S.1. Wet weight of macrofauna (ww m−2; in grams) at sites NB1, N6, N10, N7 and NB8 in the Öre Estuary from 1995-2015(www.SMHI.se).
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Dep
th (c
m)
NB1 210Pbdpm g−1
0.5 1.0 1.5
70
60
50
40
30
20
10
0
N6 210Pb
0.2 0.3 0.4 0.5 0.6
N10 210Pb
0.5 1.0 1.5
Dep
th (c
m)
N7 210Pb
0.5 1.0 1.5 2.0 2.5
70
60
50
40
30
20
10
0
NB8 210Pb
0.5 1.0 1.5 2.0 2.5 3.0
dpm g−1 dpm g−1
dpm g−1 dpm g−1
Figure S.2. Solid phase depth profiles of 210Pb at sites NB1, N6, N10, N7 and NB8 and model fits (black lines). Sites NB1, N6, N10 and N7were sampled in April 2015. Site NB8 was sampled in August 2015.
3
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Dep
th (c
m)
Porosity
0.80 0.95
80
60
40
20
0
Db cm2 yr−1
0 104
α
yr−1
0 20 40
Re−adsorptioncoefficient
0.0 0.4 0.8
vol vol-1A B C D
Figure S.3. Depth profiles used in the model A: Measured porosity (vol vol−1) for April 2015 (black circles) and fitted porosity (black line);B: bioturbation coefficient (Db; cm yr−1); C: bioirrigation coefficient (α; yr−1); D: Re-adsorption coefficient for HPO 2–4 .
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Year
αβγ
1965 1990 20150
2
4
6
8
10
12
1965 1990 20150.0
0.5
1.0
1.5
Year
αβγβ pulse
1965 1990 20150.00
0.01
0.02
0.03
0.04
Year
αβMncarb
(mol
m−2
yr−1 )
Org
anic
mat
ter f
lux
(mol
m−2
yr−1 )
Fe o
xide
flux
(mol
m−2
yr−1 )
Man
gane
se fl
ux
1965 1990 2015
0.00
0.05
0.10
0.15
0.20
0.25
Year
Rat
io P
:Fe
1965 1990 2015
0.00
0.05
0.10
0.15
0.20
0.25
Year
A B C
D E
(mol
m−2
yr−1 )
P-F
e ox
ide
flux
(mol
mol
-1)
Figure S.4. Transient scenarios used in the reactive transport model between 1965 and 2015; A: different phases of organic matter; B differentphases of Fe oxides; C: different phases of manganese; D: average P:Fe ratio of all Fe oxide fractions combined, E: total P input bound to Feoxides. The various types of organic matter, Fe oxides and Mn oxides are indicated as α (highly reactive), β (less reactive) and γ (refractory).
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Feoxµmol g−1
0 100
70
50
30
10
FeOx 1FeOx 2
Dep
th (c
m)
Fecarb
0 150
Femag
0 30 60
S0
0 100
CRS
0 40 100
NB8µmol g−1 µmol g−1 µmol g−1 µmol g−1
Figure S.5. Solid phase depth profiles of the sum of easily reducible Fe oxides and reducible (crystalline) Fe oxides (FeOx = FeOx1 +FeOx2), Fe carbonates (Fecarb), magnetite (Femag), elemental S (S
0) and S in pyrite (CRS) for site NB8 in April 2015.
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0.0 1.0 2.0
80
60
40
20
0
R1D
epth
(cm
)0.00 0.15
R2
0.00 0.06 0.12
R3
0.0 0.2 0.4 0.6
R4
0.0 0.4 0.8
R5
0.1 0.3 0.5
R6
0.000 0.003
R7
0.000 0.015 0.030
R8
0.00 0.04 0.08
80
60
40
20
0
R9
Dep
th (c
m)
0.00 0.10 0.20
R10
0.00000 0.00025
R11
0e+00 6e−05
R12
0.000 0.010
R13
0.0 0.4 0.8
R14 & R15
alphaTotal
0.00 0.10 0.20
R16
0.0e+00 2.0e−15
R17
0.00 0.10 0.20
80
60
40
20
0
R18
Dep
th (c
m)
0.00 0.06
R19
0.00 0.06
R20
0.000 0.008
alphaTotal
R21
0.0 0.3 0.6
R22
−1.0 0.0 1.0
R23
0.0e+00 1.0e−05
R24
0e+00 6e−04
R25
0 0.0008
80
60
40
20
0
R26
Dep
th (c
m)
0e+00 6e−04
R27
alphaTotal
0.000 0.010
R28 & R29
alphaTotal
0.00 0.03 0.06
R30
0.0000 0.0020
alphaTotal
R31
−0.05 0.10
R32
0e+00 6e−04
Rviv
Figure S.6. Depth profiles of reaction rates calculated for the baseline scenario in 2015. Rates are in mol m−3 yr−1. Reactions are describedin Table S.6.
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Phosphorus burial forms
A B C
−70% −40% 0% +25%
28 28 27 29 33 37 43
4 4 5 711 14
1949 30 22 16
1515
18
19 38 45 48 41 34 20
−25% −5% 0 +5% +25%
59 47 36 33 31 27 24
21
16
13 1110 9
8
18
17
1514 15
1414
2 20 36 41 45 50 54
0.25 0.75 1 1.25 2
Ca-POrg-PFeOx-PVivianite
0
20
40
60
80
100
Sedimentation rate (cm yr−1)
Perc
enta
ge (%
) 24 40 41 32 33 35 39 4435
26 19
13 11 10 99
4133
23
16 15 14 1616
0 1 16 40 41 41 37 32
OM inputFe-oxide input0.5 0.85 1.5 −50%−10% +10% +10%-25%
0
20
40
60
80
100
0
20
40
60
80
100
Figure S.7. Modeled burial forms of P as a function of changes in A: sedimentation rates between 0.25 and 2 cm yr−1; B: organic matterinputs ranging between -70% and +25% C: inputs of Fe oxides ranging between -25% and 25%. Corresponding P burial rates are shown infigure 9.
Year1900 1925 1950 1975 2000
0
50
100
150
200
250
(km
3 yr
−1)
Riv
er d
isch
arge
Figure S.8. Averaged summer river discharge for 86 Swedish rivers from 1900-2015 (www.SMHI.se).
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Table S.1. Chemical species included in the model.
Species NotationSolidOrganic mattera OMα,β,γ
Iron oxidea Fe(OH)3α,β
Elemental sulfur S0
Iron monosulfide FeSPyrite FeS2Iron-bound Phosphorus Fe(OH)3PVivianite Fe3(PO4)2Siderite FeCO3Organic phosphorus PorgAuthigenic (Ca) phosphorus CaPDetrital phosphorus DetrPManganese oxideb Mn(OH)2
α,β
Manganese carbonate MnCO3SoluteChloride Cl–
Oxygen O2Nitrate NO –3Sulfate SO 2–4Methane CH4Iron Fe2+
Ammoniumc∑
NH +4Hydrogen sulfidec
∑H2S
Phosphatec∑
HPO 2–4Dissolved Inorganic Carbon DICManganese Mn2+
a chemical species consist of 3 types: reactive (α), less reactive (β) and refractory (γ). Fe oxideβ(pulse) and Fe oxideβ(max)
are not specifically named because they have the same characteristics as Fe oxideβ .b chemical species consist of two types: reactive (α) and less reactive (β).
c∑
denotes that all species of an acid are included.
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Table S.2. Reaction pathways and stoichiometries implemented in the model.
Primary redox reactionsOMα,β + aO2 → aCO2 + bNH +4 + cH3PO4 + aH2O R1OMα,β + 0.8aNO –3 + 0.8aH
+ → aCO2 + bNH +4 + cH3PO4 + 0.4aN2 + 1.4a H2O R2OMα,β +2aMn(OH)2
α + 2aH+ → 2 Mn2+ +aCO2 + cH3PO4 + 2aH2O R3OMα,β + 4a Fe(OH)3
α + 4aχαFeoxP + 12aH+ → aCO2 + bNH +4 + (c+4aχα)H3PO4 + 13aH2O + 4aFe +2 R4OMα,β + 0.5a SO 2–4 + aH
+ → aCO2 + bNH +4 + cH3PO4 + 0.5aH2S + aH2O R5OMα,β → 0.5aCO2 + bNH +4 + cH3PO4 + 0.5aCH4 R6CO2 + 4H2 → CH4 + 2H2O R7Secondary and other reactions2O2 + NH
+4 + 2HCO
–3 → NO –3 + 2CO2 + 3H2O R8
O2 + 4Fe2+ + 8HCO –3 + 2H2O + 4χ
αH2PO–
4 → 4 Fe(OH)3α+ 4χα FeoxP + 8CO2 R92O2 + FeS→ SO 2–4 + Fe2+ R107O2 + 2FeS2 + 2H2O→ 4SO 2–4 + 2Fe2+ + 4H+ R112O2 + H2S + 2HCO
–3 → SO 2–4 + 2CO2 + 2H2O R12
2O2 + CH4 → CO2 + 2H2O R132Fe(OH)3
α + 2χαFeoxP + H2S + 4CO2 → 2Fe2+ + 2χαH2PO –4 + S0 + 4HCO –3 + 2H2O R142Fe(OH)3
β,β(max),β(pulse) + 2χαFeoxP + H2S + 4CO2 → 2Fe2+ + 2χαH2PO –4 + S0 + 4HCO –3 + 2H2O R15Fe2+ + H2S→ FeS + 2H+ R16FeS + H2S→ FeS2 + H2 R174S0 + 4H2O→ 3H2S + SO 2–4 + 2H+ R18FeS + S0 → FeS2 R19SO 2–4 + CH4 + CO2 → 2HCO –3 + H2S R20CH4 + 8Fe(OH)3
α,β,β(max),β(pulse) + 8χα,β FeoxP + 15H+ → HCO –3 + 8Fe2+ + 8χα,βH2PO –4 + 21H2O R21
Fe(OH)3α + (χα - χβ)FeoxP→ Fe(OH)3β + (χα - χβ)H2PO –4 R22
Fe2+ + CO 2–3 → FeCO3 R23Fe(PO4)2 + 3H2S→ 2FeS + 2HPO 2–4 + 4H+ R24Mn2+ + HCO –3 + OH
– →MnCO3 + H2O R252Mn2+ + 2O2 + 4H
+ → 2Mn(OH)2α R26Mn(OH)2
α,β + 2H3PO4 + 2Fe2+ →Mn2+ + 2χαFeoxP R27
Mn(OH)2α + H2S→Mn2+ + S0 + 2H2O R28
Mn(OH)2β + H2S→Mn2+ + S0 + 2H2O R29
Mn(OH)2α→Mn(OH)2β R30
4 Mn(OH)2α,β + CH4 + 7H
+ → 4Mn2+ + HCO –3 + 5H2O R31Fe(OH)3
β,β(pulse) + (χβ(max) - χβ,β(pulse))HPO 2–4 → Fe(OH)3β(max) R32Organic matter is of the form ((CH2O)a(NH
+4 )b(H3PO4)c, where a=1, b= 1/16 and c = 300/1. α, β, & γ describe different
fractions (i.e. highly reactive, less reactive and refractory). χα,β,γ describes the different P:Fe ratios ofFe(OH)α,β,γ3 ·Reactions for different Fe(OH)3β fractions (β, β(max) and β(pulse) are the same and are therefore combined
as Fe(OH)3β).
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Table S.3. Environmental parameters used in the model.
Description Symbol Value or expression unit sourcePorosity at the Surface φ0 0.935 vol vol−1 aPorosity at depth φ∞ 0.87 vol vol−1 aPorosity e-folding distance γ 35 cm bSediment density ρ 2.65 g cm−3 cTemperature T 2.77 ◦C aSalinity S 5.05 aAdvective velocity v∞ Fsedρ(1−φ∞) −of solids at depthBioturbation coefficient at Db 1.76 cm2 yr−1 bsediment-water interfaceBioirrigation coefficient at α 45*104 yr−1 bsediment-water interfaceMixed layer depth ς 11 cm bC:N ratio of organic matter C/N 6.625 mol mol−1 dC:P ratio of organic matter C/P 300 mol mol−1 bP:Fe(OH)3
α χα 0.28 mol mol−1 bP:Fe(OH)3
β χβ 0.23 mol mol−1 bP:Fe(OH)3
γ χγ 0.11 mol mol−1 bP:Fe(OH)3
β(max) χβ(max) 0.28 mol mol−1 bP:Fe(OH)3
β(pulse) χβ(pulse) 0 mol mol−1 bSources: (a) Measured; (b) Model constrained; (c) Reed et al. (2011b); (d) Redfield (1958).
Table S.4. Boundary conditions of solids and solutes at the sediment-water interface in the model. Time dependent fluxes of OMα,β,γ ,Fe(OH)3
α,β,γ , Mn(OH)2α,β , Mn carbonates and sedimentation rate at the sediment-water interface are shown in figure 3. For all chemical
species a zero-gradient boundary condition was specified at the bottom of the model domain.
Solids Flux at sediment Unitwater interface
F FeS 0 mol m−2 yr−1
F FeS2 0 mol m−2 yr−1
F S0 0 mol m−2 yr−1
F FeCO3 0.27 mol m−2 yr−1
F Vivianite 0 mol m−2 yr−1
F Detr. P 0.034 mol m−2 yr−1
F Auth. P 0.03 mol m−2 yr−1
Solutes BW concentration UnitC O2 0.091 mol m
−3
C NO –3 0 mol m−3
C SO42− 4.05 mol m−3
C Fe2+ 0 mol m−3
C Mn2+ 0 mol m−3
C H2S 0 mol m−3
C NH +4 0 mol m−3
C HPO 2–4 0.21 mol m−3
C DIC 1.5 mol m−3
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Table S.5. Analyses of vivianite crystals from below the SMTZ at site NB8 with electron microprobe-EDS. Vivianite crystals were collectedfrom 3 different depths. The average value and standard deviation for each element was caulculated from 7 EDS point analyses.
Element mol %O 37.8 ± 3.4Na 0.4 ± 0.2Mg 0.8 ± 0.6Al 6.3 ± 6.2Si 2.6 ± 1.5P 13.5 ± 5.4Ca 0.3 ± 0.2Mn 6.9 ± 2.3Fe 31.4 ± 6.3
mol mol−1Fe/P 3.3 ± 2.0Fe/Mn 4.7 ± 0.8(Fe+Mn)/P 4.1 ± 2.5Mn/P 0.8 ± 0.5(Fe+Mn+Mg)/P 4.3 ± 2.5
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Table S.6. Reaction equations implemented in the model.
Primary redox reaction equationsR1 = kα,βOM
α,β(
[O2]Km,O2+[O2]
)E1
R2 = kα,βOMα,β
([NO −3 ]
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E2
R3 = kα,βOMα,β(
[Mn(OH)2]Km,Mn(OH)2
+[Mn(OH)2]
)( Km,NO
−3
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E3
R4 = kα,βOMα,β(
[Fe(OH)3]Km,Fe(OH)3
+[Fe(OH)3]
)(Km,Mn(OH)2
Km,Mn(OH)2+[Mn(OH)2]
)( Km,NO
−3
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E4
R5 = kα,βOMα,β
([SO 2−4 ]
Km,SO
2−4
+[SO 2−4 ]
)(Km,Fe(OH)3
Km,Fe(OH)3+[Fe(OH)3]
)(Km,Mn(OH)2
Km,Mn(OH)2+[Mn(OH)2]
)( Km,NO
−3
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E5
R6 = kα,βOMα,β
(K
m,SO2−
4
Km,SO
2−4
+[SO 2−4 ]
)(Km,Fe(OH)3
Km,Fe(OH)3+[Fe(OH)3]
)(Km,Mn(OH)2
Km,Mn(OH)2+[Mn(OH)2]
)( Km,NO
−3
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E6
R7 = k1DIC
(K
m,SO2−
4
Km,SO
2−4
+[SO 2−4 ]
)(Km,Fe(OH)3
Km,Fe(OH)3+[Fe(OH)3]
)(Km,Mn(OH)2
Km,Mn(OH)2+[Mn(OH)2]
)( Km,NO
−3
Km,NO
−3
+[NO −3 ]
)(Km,O2
Km,O2+[O2]
)E7
Secondary redox and other reaction equationsR8 = k2[O2][NH
+4 ] E8
R9 = k3[O2][Fe2+] E9
R10 = k4[O2][FeS] E10R11 = k5[O2][FeS2] E11R12 = k6[O2][
∑H2S] E12
R13 = k7[O2][CH4] E13R14 = k8[Fe(OH)3
α][∑
H2S] E14R15 = k9[Fe(OH)3
β,β(max),β(pulse)][∑
H2S] E15R16 = k10[Fe
2+][∑
H2S] E16R17 = k11[FeS][
∑H2S] E17
R18 = k12[S0] E18
R19 = k13[Fe2+][S0] E19
R20 = k14[SO2−
4 ][CH4] E20R21 = k15[Fe(OH)3
α,β,β(max),β(pulse)][CH4] E21R22 = k16[Fe(OH)3
α] E22R23 = k17[Fe
2+][HCO −3 ] E23R24 = k18[Fe3(HPO
2−4 )2][
∑H2S] E24
R25 = k19[Mn2+][HCO −3 ] E25
R26 = k20[Mn2+][O2] E26
R27 = k21[Mn(OH)2α,β][HPO2−4 ][Fe
2+] E27R28 = k22[Mn(OH)
α2 ][∑
H2S] E28R29 = k23[Mn(OH)2
β][∑
H2S] E29R30 = k24[Mn(OH)2
α] E30R31 = k25[Mn(OH)2
α,β][CH4] E31R32 = k26[Fe(OH)3
β,β(max),β(pulse)][HPO2−4 ] E32
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Table S.7. Reaction parameters used in the model.
Parameter Value Unit Source Values in literaturekα 0.3 yr−1 a,b 0.05-1.62kβ 0.0086 yr−1 b,h 0.0025-0.0086KO2 20 µm L
−1 c 1-30KNO−3 4 µm L
−1 c 4-80KMn(OH)2 4 µm g
−1 c 4-32KFe(OH)3 65 µm g
−1 c 65-100KSO 2−4 1.6 µm L
−1 c 1.6k1 (E7) 0.044 yr−1 i 0.0011k2 (E8) 10000 mmol yr−1 c,d 5000-39000k3 (E9) 1.4*105 mmol yr−1 c 1.4*105
k4 (E10) 300 mmol yr−1 c 300k5 (E11) 1 mmol yr−1 c 1k6 (E12) 160 mmol yr−1 c 160k7 (E13) 107 mmol yr−1 c 107
k8 (E14) 55 mmol yr−1 c,g,i 8-100k9 (E15) 44 mmol yr−1 c,j 0.004-100k10 (E16) 9000 mmol yr−1 b,d 100-14800k11 (E17) 10−15 mmol yr−1 e,i 0.0003-3.15k12 (E18) 3 yr−1 f 3k13 (E19) 0.0025 mmol yr−1 f,g 0.001-7k14 (E20) 17 mmol yr−1 c,g 10(c)-120(g)k15 (E21) 0.0021 mmol yr−1 g,i 1.6*10−7 - 0.0074k17 (E23) 0 mmol yr−1 i 0.0027k18 (E24) 8*10−4 mmol yr−1 i 8*10−4
k19 (E25) 0.265 mmol yr−1 Model constrainedk20 (E26) 1200 mmol yr−1 c 800-20.000k21 (E27) 0.002 mmol yr−1 f 2k22 (E28) 0.5 mmol yr−1 c
-
References
Berg, P., Rysgaard, S., and Thamdrup, B.: Dynamic modeling of early diagenesis and nutrient cycling. A case study in an Arctic marinesediment, American Journal of Science, 303, 905–955, https://doi.org/10.2475/ajs.303.10.905, 2003.
Boudreau, B. P.: A method-of-lines code for carbon and nutrient diagenesis in aquatic sediments, Computers and Geosciences, 22, 479–496,https://doi.org/10.1016/0098-3004(95)00115-8, 1996a.5
Boudreau, B. P.: The diffusive tortuosity of fine-grained unlithified sediments, https://doi.org/10.1016/0016-7037(96)00158-5, 1996b.Boudreau, B. P.: Diagenetic models and their implementation. Modelling transport and reactions in aquatic sediments, vol. 171,
https://doi.org/0.I007/97S-3-642-60421-S, 1997.Egger, M., Kraal, P., Jilbert, T., Sulu-Gambari, F., Sapart, C. J., Röckmann, T., and Slomp, C. P.: Anaerobic oxidation of methane alters
sediment records of sulfur, iron and phosphorus in the Black Sea, Biogeosciences, 13, 5333–5355, https://doi.org/10.5194/bg-13-5333-102016, 2016a.
Egger, M., Lenstra, W., Jong, D., Meysman, F. J., Sapart, C. J., Van Der Veen, C., Röckmann, T., Gonzalez, S., and Slomp, C. P.: Rapid sedi-ment accumulation results in high methane effluxes from coastal sediments, PLoS ONE, 11, https://doi.org/10.1371/journal.pone.0161609,2016b.
Froelich, P. N., Klinkhammer, G. P., Bender, M. L., Luedtke, N. A., Heath, G. R., Cullen, D., Dauphin, P., Hammond, D., Hartman, B., and15Maynard, V.: Early oxidation of organic matter in pelagic sediments of the eastern equatorial Atlantic: suboxic diagenesis, Geochimica etCosmochimica Acta, 43, 1075–1090, https://doi.org/10.1016/0016-7037(79)90095-4, 1979.
Meysman, F. J. R., Boudreau, B. P., and Middelburg, J. J.: Modeling reactive transport in sediments subject to bioturbation and compaction,Geochimica et Cosmochimica Acta, 69, 3601–3617, https://doi.org/10.1016/j.gca.2005.01.004, 2005.
Moodley, L., Middelburg, J. J., Herman, P. M. J., Soetaert, K., and de Lange, G. J.: Oxygenation and organic-matter preser-20vation in marine sediments: Direct experimental evidence from ancient organic carbon-rich deposits, Geology, 33, 889–892,https://doi.org/10.1130/G21731.1, 2005.
Petzold, L.: Automatic selection of methods for solving stiff and nonstiff systems of ordinary differential equations, SIAM J Sci and StatComput, 4, 136–148, https://doi.org/10.1137/0904010, 1983.
Redfield, A. C.: The Biological Control of Chemical Factors in the Environment, American Scientist, 46, 205–221,25https://doi.org/10.2307/27828530, http://www.jstor.org/stable/27827150, 1958.
Reed, D. C., Slomp, C. P., and de Lange, G. J.: A quantitative reconstruction of organic matter and nutrient diagenesis in MediterraneanSea sediments over the Holocene, Geochimica et Cosmochimica Acta, 75, 5540–5558, https://doi.org/10.1016/j.gca.2011.07.002, http://dx.doi.org/10.1016/j.gca.2011.07.002, 2011a.
Reed, D. C., Slomp, C. P., and Gustafsson, B. G.: Sedimentary phosphorus dynamics and the evolution of bottom-water hypoxia: A coupled30benthic-pelagic model of a coastal system, Limnology and Oceanography, 56, 1075–1092, https://doi.org/10.4319/lo.2011.56.3.1075,2011b.
Reed, D. C., Gustafsson, B. G., and Slomp, C. P.: Shelf-to-basin iron shuttling enhances vivianite formation in deep Baltic Sea sediments,Earth and Planetary Science Letters, 434, 241–251, https://doi.org/10.1016/j.epsl.2015.11.033, http://dx.doi.org/10.1016/j.epsl.2015.11.033, 2016.35
Rickard, D. and Luther, G. W.: Kinetics of pyrite formation by the H2S oxidation of iron (II) monosulfide in aqueous solutions between 25and 125C: The mechanism, Geochimica et Cosmochimica Acta, 61, 135–147, https://doi.org/10.1016/S0016-7037(96)00322-5, 1997.
Rooze, J., Egger, M., Tsandev, I., and Slomp, C. P.: Iron-dependent anaerobic oxidation of methane in coastal surface sediments: Potentialcontrols and impact, Limnology and Oceanography, https://doi.org/10.1002/lno.10275, 2016.
Soetaert, K. and Meysman, F.: Reactive transport in aquatic ecosystems: Rapid model prototyping in the open source software R, Environmen-40tal Modelling and Software, 32, 49–60, https://doi.org/10.1016/j.envsoft.2011.08.011, http://dx.doi.org/10.1016/j.envsoft.2011.08.011,2012.
Soetaert, K., Petzoldt, T., and Meysman, F. J. R.: Marelac: Tools for Aquatic Sciences v2.1.3, R package, 2010.Wang, Y. F. and Van Cappellen, P.: A multicomponent reactive transport model of early diagenesis: Application to redox cycling in coastal
marine sediments, Geochimica Et Cosmochimica Acta, 60, 2993–3014, https://doi.org/10.1016/0016-7037(96)00140-8, 1996.45
15
https://doi.org/10.2475/ajs.303.10.905https://doi.org/10.1016/0098-3004(95)00115-8https://doi.org/10.1016/0016-7037(96)00158-5https://doi.org/0.I007/97S-3-642-60421-Shttps://doi.org/10.5194/bg-13-5333-2016https://doi.org/10.5194/bg-13-5333-2016https://doi.org/10.5194/bg-13-5333-2016https://doi.org/10.1371/journal.pone.0161609https://doi.org/10.1016/0016-7037(79)90095-4https://doi.org/10.1016/j.gca.2005.01.004https://doi.org/10.1130/G21731.1https://doi.org/10.1137/0904010https://doi.org/10.2307/27828530http://www.jstor.org/stable/27827150https://doi.org/10.1016/j.gca.2011.07.002http://dx.doi.org/10.1016/j.gca.2011.07.002http://dx.doi.org/10.1016/j.gca.2011.07.002http://dx.doi.org/10.1016/j.gca.2011.07.002https://doi.org/10.4319/lo.2011.56.3.1075https://doi.org/10.1016/j.epsl.2015.11.033http://dx.doi.org/10.1016/j.epsl.2015.11.033http://dx.doi.org/10.1016/j.epsl.2015.11.033http://dx.doi.org/10.1016/j.epsl.2015.11.033https://doi.org/10.1016/S0016-7037(96)00322-5https://doi.org/10.1002/lno.10275https://doi.org/10.1016/j.envsoft.2011.08.011http://dx.doi.org/10.1016/j.envsoft.2011.08.011https://doi.org/10.1016/0016-7037(96)00140-8