A New Global Simulation of Mercury Air-Sea Exchange for Concentrations

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SUPPORTING INFORMATION
A New Global Simulation of Mercury Air-Sea Exchange for
Evaluating Impacts on Marine Boundary Layer
Concentrations
Anne L.
Soerensen*,†
†
, Elsie M. Sunderland‡‡, Christopher D.
‡, Daniel J.
Holmes
Jacob
†§, Sarah A. Strode|| , and Robert P.
‡†, Henrik Skov
Mason
, Robert
Yantosca, J. Christensen
National Environmental Research Institute, University of Aarhus, Frederiksborgvej 399,
DK-4000 Roskilde, Denmark
‡Harvard University, School of Engineering and Applied Sciences and Department
of Earth and Planetary Sciences, Cambridge MA, 02138, USA
§Department of Atmospheric Sciences, University of Washington, Seattle, WA,
98195 USA
||University of Connecticut, Department of Marine Sciences, 1080 Shennecossett
Road, Groton, CT, 0634, USA Contents
Page(s)
0 Data sources for observations shown in Figures 2 and 4. 1 Section I Supplemental
Results 3-5 Section II Model Updates and Formulation 6-11 References 12-13
Figure S1 Modeled seasonal surface water Hg saturation values for 2008. 3 Figure
S2 Seasonal variability in modeled oceanic evasion for 2008. 4 Figure S3
Comparison of monthly modeled and observed seawater total inorganic Hg. 5
0Figure S4 Comparison of modeled and observed seawater Hg0. 5 Figure S5 Modeled
contribution of oceanic Hg0 emissions to marine boundary Hg concentrations. 6
Figure S6 Conceptual diagram of model resolution, subsurface ocean
7
compartments and specified intermediate seawater Hg concentrations.
Table S1 Model differential equations 8 Table S2 Particle associated mercury reservoirs
and fluxes. 8 Table S3 Redox reactions. 11 Table S4 Gas-exchange parameterization. 12
1
Data sources for observations shown in Figures 2 and 4 in the main text:
for Figure 2 “Modeling results for 2008 atmospheric deposition to the global
Data sources
oceans, surface ocean fluxes, and aqueous Hg concentrations” are as follows: Atlantic (1-4);
0Pacific
(5-8); Arctic (9, 10); Mediterranean (11). We omitted outliers in Hg observations
from two cruises in the Atlantic Ocean in the 1990s due to an apparent contamination
problem (2, 3).
0Data
sources for Figure 4 “Modeled seasonal mean marine boundary layer Hg
concentrations and relative contributions of oceanic emissions” are as follows for cruise
observations: (12-18).
2
Section I: Supplemental Results
0Figure
S1. Modeled seasonal surface water Hg0 saturation values for 2008. The degree of
saturation indicates the direction of the flux across the air-sea interface. Less than 100%
indicates net deposition and greater than 100% indicates net evasion of Hg.
3
0Figure
4
S2. Seasonal variability in modeled oceanic Hg evasion for 2008.
Figure S3. Comparison of monthly modeled (2008) and observed (various years) total
inorganic Hg concentrations. Data sources are as follows: Pacific (5-7, 19-21); Atlantic
Ocean (1-3, 21); Arctic Ocean (9).
Figure S4. Comparison of monthly modeled (2008) and observed (various years) seawater
Hgconcentrations. Pacific Ocean: (5, 8, 19, 22); Atlantic Ocean (2, 11); Arctic Ocean: (9).
5
0
0
emissions to marine boundary Hg
Figure S5. Modeled contribution of
oceanic Hg
concentrations.
6
0
Section II: Model Updates and Formulation
Figure S6. Conceptual diagram of model resolution, subsurface ocean compartments and
specified intermediate seawater Hg concentrations.
7
Mup Hg0± Ment Hg±0 Moa kox M Hg0 + kr
/dt Change in HgHg(II)II mass over
time (dt)
F
red
M
HgII
M Hg
II
0
-1
dep
ent
Mup
(kg) Mass of Hgoa0
M (kg) Flux of HgsinkII
(kg) Reservoir of HgHg(0)0
o
(kg) Reservoir of HgHg(II)II
x
(s-1) Hg0 oxidation rate kox1 + kox2
r (s-1)
IIReduction rate of reducible pool of Hg kred1 + kbio
fraction in the dissolved phase 1/(1 + KD
(unitless) Hg
(unitless) Reducible fraction of the filtered Hg
w
(kg)Hg(p)
HgII mass in the particulate phase
( OC Hg ( II )
II
-1 (L kg
) Concentration of suspended particles 10
A
(m2
a
-2)
Standing stock of organic carbon in mixed layer
t
o
t
dMMdep+ Mup HgII± Ment HgIIMsin k+ koxMHgkrF
) Model time step M(kg) Deposition of Hg to the ocean surface M (kg) Mass of
/
mercury species introduced or removed due to deep
convection or shoaling of the
dt Change in HgTable S1. Model
mixed-layer
differential equations dMHg(0)0 mass over
time (dt)
(kg) Wind-driven mass transfer of mercury species due to Ekman
pumping
dt
(s
ev
ad
ed
fr
o
m
th
e
oc
ea
n
to
th
e
at
m
os
ph
er
e
M
lo
st
fr
o
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m
ix
ed
la
ye
r
wi
th
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nk
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pa
rti
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in
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ix
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th
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ac
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ix
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la
ye
r
k
k
FII
S
P
M
)
red
II
po
ol
0.
40
(3
,
23
,
24
)
C:
C
hl
a
(u
ni
tle
ss
)
C
ar
bo
n
to
ch
lo
rp
hy
ll
a
ra
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o
80
:1
(2
6)
w
et
wt
(u
ni
tle
ss
)
C
on
ve
rsi
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fo
r
w
et
w
ei
gh
ts
of
pl
an
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as
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et
w
ei
gh
t:
m
g
ca
rb
on
N
P
P
(
m
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C
m2
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N
et
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i
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ar
y
pr
od
uc
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vi
ty
20
03
M
O
D
IS
sa
tel
lit
e
da
ta
(2
7)
n
(u
ni
tle
ss
)
E
xp
on
en
t
de
sc
ri
bi
ng
re
lat
io
ns
hi
p
-0
.7
4
(2
8)
P
8
to organic carbon ratio in the mixed layer (1 F
M
) Hg ( II ) • A )
M 6OCtot
tot
(1
D
• wetwt •
A
3
-1
Chl
w
(mg m
Table S2. Particle associated mercury reservoirs and fluxes. K) Seawater partition coefficient for Hg 5.5±0.5 (3, 5) SPM (k
M
layer depth WOCE data assimilation (25)
tot
) Water surface area OC
•C:
Chl
Chltot (mg m-2) Integrated water column pigment
See text for derivation
content
2
1
Jorg
C
1.7
7
(mg C
m
n
) Organic carbon flux out of the mixed
d layer
0.1NPP
MLD
Hg:C (unitless) HgHg ( P )/(10
between declines in organic carbon flux
due to mineralization in the water column
with depth
MHg(P) (kg) Mass of Hg(II) sorbed to particles
JorgC • Hg : C •
A
P
Msin (kg) Mass of Hg lost from the mixed layer due to
k
particle sinking
( dt )
w
Method used for estimating suspended particulate matter concentrations No global data
sets on SPM concentrations in the ocean mixed layer are available. We therefore estimate SPM
concentrations in the surface mixed layer based on the standing biomass in the water column
derived from MODIS satellite chlorophyll a (Chl a, mg m-3) concentrations
(http://oceancolor.gsfc.nasa.gov/ftp.html) for the year 2003. We calculate the water column
integrated pigment content within the euphotic layer (Chl, mg mtot-2 1.0 mg m) based on the
statistical fits for subsurface algal productivity in the ocean developed by Morel and Berthon
(29) and updated by Uitz et al. (30).
These equations are as follows: 1. STRATIFIED
WATERS For stratified waters in low and mid latitude stations, where Chlsat-3
= 36.1 Chltota 0.357
1.0 mg msat
(1) Chl
(2) Chl
(3) Chl
= 37.7 Chltota
0.615
= 42.1 Chltotsat 0.538
eu
and z are calculated iteratively in the model to determine whether waters are
stratified or well mixed and the appropriate equations for Chl is derived as a
function of Chl. zby Morel and Maritorena (31):
tot -0.839
tot -0.547
eu
Chl
<102 m and Chleu
> 13.65 mg m-2
-2 < 13.65 mg m
For stratified waters in low and mid latitude stations, where Chl
eu
-3
z/MLD >1 then the waters are consider
2. WELL-MIXED WATERS For
well-mixed waters at high latitudes:
Waters are defined as well-mixed if z/MLD <1 Conversely, if
is the euphotic depth and is defined as the depth where the PAR et al. (25) from the National Oceanograp
irradiance is 1% of its value at the surface.
Experiment (WOCE) database, and the A
MLD (m) is the mixed layer depth derived from de Boyer Montegut http://www.loceanipsl.upmc.fr/~cdblod/m
tot
eu
tot
tot
eu
(4) zeu = 912 Chl
when 10 m < z
(5) zeu = 426.3 Chl
whe
n
102
m<
z
9
tot
<180 m and
Chltot
-2
We calculate the standing stock of organic carbon (OCtot, mg m) from the integrated water column pigment c
C:Chl a ratio of 80:1 based on Wetzel et al. (26). Thi
processes in the ocean where the C:Chla ratios are kno
limitation, depth, and phytoplankton growth rates amo
= Chltot • C : Chla
(6) OCtot
w
(7) SPM = 103(OCtot
We approximate the concentration of suspended particles in each
model grid cell from wet weights of planktonic biomass that are
derived by assuming that organic carbon is 50% of the dry weight
and the dry weight is 20% of the weight for phytoplankton, resulting
in an overall conversion factor of 10 mg wet weight: mg carbon (33).
This results in an overall conversion factor of 10 mg wet weight: mg
carbon.
• wetwt • A)/ MLD
Although the majority of particles in open ocean environments are
living and dead planktonic biomass, we allow for up to an additional
10% increase in SPM to account for allochtonous abiotic particles
such as mineral dust (34).
10
•RADµ
Table S3. Redox reactions. ) Photo-oxidation rate constant 6.6 10
(24) When RAD>
k(sox1 -1
-6min: 5.6x10 s-1-4-1 s (35) max: 9.7x10 (24) kox2-1 (s-7) Dark oxidation rate
constant 1.0x10 (35, 36) k(sred1 -16) Photolytic reduction rate constant 1.7
10•RADµ (24) When RAD>0
-7min: <1.0x10 s-4-1 (24, 35) max: 8.7x10 s (s (24) kbio-16) Biotic reduction rate constant 4.5 10-7-1 s•
1
NPP (24) min: 3.5x10-5-1 max: 8.3x10 s (37)
MLD
RADµ (W -2 ) Average shortwave radiation
RAD
m
intensity in the mixed layer
0
RA (W -2 ) Total local shortwave radiation
• RAD[ex1 ex 2]
MLD
1
x
2x1
D m
penetration in the mixed layer
6
0
-2RAD
(W m) Total shortwave radiation intensity GEOS-5 meteorology x(m)1
Surface depth 0 m x2 -1) Extinction coefficient for radiation (m) Bottom depth
MLD (mwater+ ChlCChl+ DOCC water-1 (m) Extinction coefficient for water 450 nm
(vis) = 0.0145 Chla-1 (m) Extinction coefficient for pigments 450 nm (vis) = 31
CChla (mg L-1) Average concentration of Chl a in mixed layer (Chltot• Aw)/ MLD
DOC
(mg L-1) Extinction coefficient for dissolved organic
carbon (DOC)
CDOC (mg L-1) Concentration of DOC in water column
DOC
av
g
450 nm (vis) = 0.654
1.5 • (
NPPi
/
)
NPPglobalavg (38)
-1
d
PPi (gC m-2
) NPP
N in model grid cell 2003 MODIS satellite data (27) NPP Global average NPP global
NPP/ocean surface area
11
12
Table S4. Gas exchange parameterization. M (kg) Air-sea
F • Aw ) dt /
v
exchange of Hgoa0-1 for each model time step (dt, s) (1 0
3600
0
) Hg
air-sea exchange flux Fv
= ( Ca
Fv
0
Kw Cw
(ng
m
w-3
(ng
0
ma-2(ng m-3
hr-1
/ H ( T)) C) Concentration of Hg in seawater See differential equations C)
Concentration of Hg in air GEOS-Chem atmospheric simulation
H'(T) Temperature dependent dimensionless Henry’s
ln H = ( 2403.3T + 6.92)
law constant
(39)
0.5
1
Kw (m ) Water-side mass transfer coefficient for
A u10 2( Sc /
)
(40)
hr
steady winds
ScCO2
A (unitless) Constant based on the Weibull distribution of
0.25 (41)
wind speeds over oceans
u1 -1 (m s) Wind speed normalized to 10 m above sea
GEOS-5 data
0 surface
2
ScCO Schmidt number for CO
2 0.11 T 6.16 T + 644.7 (42) T (ºC)Water temperature GEOS-5
number for Hg(0) / D
- ) Kinematic viscosity N/ = 0.017e( 0.025 T )
2 (cm
1
s
(42) (cP) Viscosity of water See text
(w Mw 1 /
2)
(g molw-1
(cmB3 mol-1) Molal volume of mercury at its normal
boiling temperature
w Solvent association factor introduced to define the
effective molecular weight of the solvent with respect to
the diffusion process
(8) log() =
1301 (998.333 + 8.1855( T 20) + 0.00585( T 20)2)
3.30233
T VB 0.6 M12.74 ) Molecular weight of
GEOS-5 data V
-3 (mg cm2-1 s) Diffusivity (Wilke-Chang (43)
method) ) Seawater density D (cm7.4 108
Aqueous Viscosity Loux (45) prov
viscosity as a function of aqueous tem
For water temperatures 20-100° C:
Where 20
/ 20) = 1.3272(20 T ) 0.001053( T 20) T
+1052
9) log(T
(
=
aqueous
viscosity
at 20ºC.
12
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