Introduction
The Atlantic Ocean contains the largest store of anthropogenic carbon
(Cant) of all the world's oceans, accounting for approximately 38 %
of the total Cant inventory (Sabine et al., 2004). Within the Atlantic,
the North Atlantic has been found to be responsible for the majority of the
uptake of Cant, due to the formation of North Atlantic Deep Water
(NADW; Lee et al., 2003; Sabine et al., 2004). However, a recent Atlantic
Basin inventory analysis indicates that in the past decade the South
Atlantic has been more effective at sequestering Cant (Wanninkhof et
al., 2010) than the North Atlantic. These authors calculated a rate of
increase in the North Atlantic inventory of 1.9 Pg C decade-1, whereas
the South Atlantic inventory grew at a rate of 3.0 Pg C decade-1.
Calculations by Ríos et al. (2012) indicate that the southwestern
Atlantic Ocean dominates the South Atlantic sink of Cant, with a
storage rate of 0.25 ± 0.035 Pg C decade-1. Quantifying the exact
rate of increase in anthropogenic carbon in ocean waters is inherently
problematic due to the highly variable nature of dissolved inorganic carbon (DIC) within the ocean and
the relatively small fraction of total DIC that
the anthropogenic component represents (∼ 3 %; Ríos et
al., 2010). In the past decade, a number of methods for calculating the
increase in Cant (ΔCant) between reoccupation of ocean
transects have been developed (TrOCA, ϕCT0, eMLR). Despite
the differing approaches and assumptions, there is overall coherence in the
determinations of the anthropogenic component of inorganic carbon in the
Atlantic Ocean (Lee et al., 2003; Vázquez-Rodríguez et al., 2009a;
Peng and Wanninkhof, 2010; Wanninkhof et al., 2010).
The southwestern Atlantic has been occupied several times over the past 20
years, and several techniques to determine Cant have been applied to the
WOCE '94 A17 transect by Ríos et al. (2010). These methods included
ΔC* (Gruber et al., 1996), TrOCA (Tracer combining Oxygen, inorganic Carbon
and total Alkalinity; Touratier et al., 2007), ϕCT∘
(Vázquez-Rodríguez et al., 2009a), and TTD
(transit time distributions; Waugh et al., 2006) and showed general conformity in the distribution
of Cant. The presence of the western boundary current in the South
Atlantic Ocean means that the Cant signal penetrates deeper and is
larger in the western half of the basin compared to the eastern half
(Wanninkhof et al., 2010; Ríos et al., 2010; Vázquez-Rodríguez
et al., 2009a). Similarly, Murata et al. (2008) show that the Cant
signal in Subantarctic Mode Water (SAMW) can be ∼ 7 µmol kg-1 higher west of 15∘ W compared to the east. Mode and
intermediate water formation constitute a major pathway of Cant into
the South Atlantic Ocean interior (McNeil et al., 2001; Sabine et al.,
2004). The SAMW is formed in the Subantarctic Zone (SAZ), between the
Subtropical Front (STF) and Subantarctic Front (SAF), where a calculated
anthropogenic CO2 uptake of 0.07–0.08 PgC yr-1 occurs (Sabine
et al., 1999; McNeil et al., 2001). A total CO2 sink of 1.1 Pg C yr-1 was calculated by McNeil et al. (2007) for the SAZ, making it
the largest CO2 sink in the Southern Ocean and a significant sink for
anthropogenic atmospheric CO2.
The increase in DIC that results from the uptake of anthropogenic CO2
from the atmosphere leads to increasing proton, bicarbonate ion and carbon
dioxide concentrations ([H+], [HCO3-], [CO2]) and
decreasing carbonate concentrations ([CO32-]), a process referred
to as ocean acidification. Sabine et al. (2004) state that approximately 50 % of the total
amount of Cant in the world's oceans resides in the upper 400 m. The
associated decrease in pH has been calculated as 0.1 pH units in the surface
ocean relative to pre-industrial times (Orr et al., 2005) and is ongoing.
In the North Atlantic Ocean, observations have found acidification rates of 0.0016 ± 0.0001 and 0.0012 ± 0.002 yr-1
for Subarctic Intermediate Water (SAIW) and Subpolar Mode Water (SPMW),
respectively (Vázquez-Rodríguez et al., 2012). Data from the
European Time Series in the Canary Islands (ESTOC) station show
significantly higher rates of pH decrease in surface waters of 0.0017 ± 0.0004 yr-1
for the time period 1995 to 2004, with notable
influence from regional climatic forcing (Santana-Casiano et al., 2007).
Acidification rates that deviate from the rate that is expected from
Cant increases alone have been observed in upper Labrador Sea Water
(uLSW), SAIW, and eastern North Atlantic Central Water (eNACW; Vázquez-Rodríguez et al., 2012). These variations have been
attributed to a combination of climatic and biological effects. The greater
sensitivity of some water masses to acidification has been well documented
by González-Dávila et al. (2011) through the application of the
buffering factors described by Egleston et al. (2010).
González-Dávila et al. (2011) highlighted waters originating at high
latitudes as particularly sensitive to increases in the concentration of
dissolved CO2 ([CO2 (aq)]), in particular Antarctic Intermediate
Water (AAIW) and upper Circumpolar Deep Water (uCDW) due to low ratios of total
alkalinity (AT) to DIC.
A number of the biological consequences of ocean acidification are related
to the changes in carbonate, and thus calcium carbonate (CaCO3), ion
concentration. Carbonate ions are used by marine calcifying organisms to
form both varieties of calcium carbonate: aragonite (e.g. by pteropods) and
calcite (e.g. by coccolithophores and foraminifera). Aragonite is the less
metastable form of CaCO3 resulting in a saturation horizon (ΩAr=1)
approximately 2 km shallower than that of calcite in the South
Atlantic Ocean, below which depth the CaCO3 present will be in
dissolved form. A number of experiments have observed shell dissolution in
pteropods incubated at elevated partial pressure of CO2 (pCO2)
(Orr et al., 2005; Lischka et al., 2011) associated with a lowering of the
aragonite saturation state. Recently similar results have been observed in situ in
the Southern Ocean (Bednaršek et al., 2012), indicating that species are
already being affected by Cant accumulation. Organisms that use
aragonite are thus much more vulnerable to decreases in [CO32-]
driven from the surface increase in [CO2].
This study examines the increase in Cant in the southwestern Atlantic
Ocean between two occupations of the WOCE A17 line, which took place in 1994
and 2010/2011. We calculate the changes in Cant (ΔCant) in
the different water masses and subsequently examine the pH changes driven by
the invasion of anthropogenic carbon between WOCE `94 A17 and GEOTRACES-NL
(2010/2011). These results are furthermore put into context with regard to
the differing buffering capacities of individual water masses.
Stations where DIC and AT samples were taken from both
cruises (black represents the WOCE `94 A17 stations; red represents the
GEOTRACES-NL (2010/2011) expeditions).
Data
The two data sets used in this study are the results from the CO2 survey
data from the WOCE `94 A17 section (public data at
http://cdiac.ornl.gov/oceans/woce_a17c.html) and the Dutch
West Atlantic GEOTRACES programme, completed in 2011 (GEOTRACES-NL, 2010/2011; public data available at
http://www.bodc.ac.uk/geotraces/data/idp2014/). The respective stations from
the two campaigns are shown in Fig. 1. The GEOTRACES-NL (2010/2011) section
was carried out in two parts. The shown stations north of the Equator were
occupied in July 2010 by the Dutch RV Pelagia (expedition 64PE321: from
Hamilton, Bermuda, to Fortaleza, Brazil), and the Southern Hemisphere was
sampled during March 2011 by the British RRS James Cook (JC057: from Punta
Arenas, Chile, to Las Palmas, Gran Canaria).
WOCE '94 A17 measurements
The WOCE '94 A17 section was similarly carried out in austral autumn, and
these data have undergone rigorous quality control (Key et al., 2010). The
data report is available from
http://cdiac.ornl.gov/oceans/ndp_084/ (Ríos et al.,
2005), where an offset of -8 µmol kg-1 in the total alkalinity
(AT) data has been reported and corrected for in this study. From this
data set, only the stations where data for both AT and DIC are available
were used. This resulted in a total of 59 stations and 1683 data points. For
a detailed analysis of the WOCE occupation we refer the reader to Ríos
et al. (2010).
GEOTRACES-NL (2010/2011) measurements
Dissolved inorganic carbon and total alkalinity
During the GEOTRACES-NL (2010/2011) cruises, for measurements of DIC and
AT, water samples of 600 mL were collected from throughout the water
column from 24 Niskin samplers mounted on a CTD rosette, following
standard operating procedures (Dickson et al., 2007). At least two
duplicates samples from different parts of the profile were collected at each station. Samples were simultaneously analysed immediately after collection on a VINDTA
3C (Versatile INstrument for the Determination of Total Alkalinity;
Marianda, Kiel) system. This system determines DIC by
coulometric titration using a coulometer (Johnson et al., 1987) and
determines AT by potentiometric titration with 0.1 M hydrochloric acid
(Mintrop et al., 2000). Quality control was performed through regular
measurements of certified reference material (CRM, batch #100) supplied
by Andrew Dickson at Scripps Institute of Oceanography (San Diego,
California). Based on the measurements performed on the CRM throughout both
cruises, DIC was measured with a precision of ±1.0 µmol kg-1
and the precision of AT was ±1.1 µmol kg-1.
Ancillary parameters
Dissolved oxygen samples were collected from a minimum of three depths
throughout the water column for CTD sensor calibration. Inorganic nutrients
(PO4, Si(OH)4, NO3) were analysed following the methods of
Grasshoff et al. (1983). In every run, a control and a naturally sterilized reference nutrient sample (RMNS, Kanso, Japan) were measured for validation.
Precision was estimated to be ±0.01, 0.2 and 0.2 µmol L-1 for PO4,
Si(OH)4 and NO3, respectively. Values of
salinity are reported on the practical salinity scale.
pH calculations
From DIC, AT and supplementary data (salinity, temperature, pressure,
Si(OH)4, PO4), pH, and pCO2 were also calculated in situ
for both data sets using CO2_SYS (Lewis and Wallace, 1998)
adapted for MATLAB (van Heuven, 2011a), applying the acid dissociation
constants of Mehrbach et al. (1973), refitted by Dickson and Millero (1987), and
the KSO4 constant of Dickson (1990). Identical calculations were carried
out on AT and DIC data from both the WOCE '94 A17 and GEOTRACES-NL
(2010/2011) data sets, with the resulting pH reported on the total pH scale.
The residuals of the MLR fits of the (a) WOCE '94 A17 and
(b) GEOTRACES-NL (2010/2011) data sets.
Consistency between data sets
In a later section, we employ the extended multi-linear regression (eMLR)
method (Wallace, 1995; Friis et al., 2005) to infer ΔCant
between the two cruises. The eMLR method considers various biogeochemical
properties (in this case salinity, DIC, NO3, Si(OH)4 and apparent
oxygen utilization (AOU = [O2]sat–[O2]obs)) and is
particularly sensitive to large-scale (“secular”) changes in the
distributions of these properties, as well as to analytical biases in their
measurement. In order to assess the magnitude and distributions of these
changes, we gridded the values of salinity, DIC, NO3, Si(OH)4 and
AOU of each data set, and the gridded WOCE data set was subtracted from the
GEOTRACES grid. Grid spacing was every 2∘ of latitude, with 80 layers
in the vertical direction, with increased density towards the surface. In
the lower Circumpolar Deep Water (lCDW; conceivably the most stable water mass in
the section), the differences average -0.01 ± 0.015 (salinity),
-4.2 ± 12.1 (DIC),
-1.92 ± 0.78 (NO3), -5.05 ± 3.3 (Si(OH)4)
and -3.13 ± 3.9 µmol kg-1 (AOU).
By limiting the comparison to just lCDW, the number of data points available
is limited; as such, we further performed a more robust crossover analysis
of the GEOTRACES 2010/2011 data set with data from the CARINA database (CARINA
Group, 2009; Tanhua, 2010). This was done for all the tracers used at depths
deeper than 3000m. We find an offset of +1 ± 0.8 % for NO3,
-1 ± 0.5 % for dissolved oxygen, -0.004 ± 0.001 for salinity,
-1 ± 0.3 % for Si(OH)4, +1.17 ± 2.8 µmol kg-1
for DIC, and +5.3 ± 4.4 µmol kg-1 for AT. These
values are all within the threshold values of the CARINA synthesis (Key et
al., 2010); thus no corrections were applied to our data.
Hydrography of the South Atlantic Ocean
The distributions of potential temperature, salinity, AOU, silicate,
AT and DIC of the GEOTRACES-NL (2010/2011) section are shown in Fig. 3. The large water masses have been described elsewhere (Mémery et al.,
2000; Ríos et al., 2010; Wanninkhof et al., 2010); thus the
treatment is relatively concise here. Located deeper than 4500 dbar throughout
the section is Antarctic Bottom Water (AABW), characteristic in its high
DIC and AOU. Values for DIC in this water mass range from 2243
to 2267 µmol kg-1, and AOU values occupy a narrow band between
111 and 128 µmol kg-1. The DIC maximum (2267 µmol kg-1) and potential
temperature minimum (-0.16 ∘C) are both
found in this water mass, which also shows the deep-water
(> 1000 dbar) AT maximum (2369 µmol kg-1). These characteristics
are all representative of the old age of the water mass and are caused by
the large amount of organic matter remineralization which has taken place
within it. The AABW can most easily be distinguished from the overlying
lower Circumpolar Deep Water (lCDW) by the high silicate concentrations, which
reach values greater than 120 umol kg-1 in AABW. Silicate
concentrations in the deep waters (> 4000 dbar) demonstrate a
strong covariance with AT (R2= 0.95), which has been previously
noted and stems from the simultaneous dissolution of opaline and calcium
carbonate shells from the hard tissue of organisms (Pérez et al., 2002).
Section distributions of temperature (∘C),
salinity, AOU (µmol kg-1), silicate (µmol kg-1),
AT (µmol kg-1) and DIC (µmol kg-1)
from the GEOTRACES-NL (2010/2011) data set.
The lCDW has a core at approximately 3500 dbar at 50∘ S,
above which it merges into uCDW, with its
respective core identified by an oxygen minimum at approximately 1500 m
(Mémery et al., 2000). Both branches of CDW display properties similar
to that of AABW, as they represent a mixture of AABW and Weddell Sea Deep
Water (Wong et al., 1999; Orsi et al., 1999). The uCDW and lCDW share
isopycnals with upper North Atlantic Deep Water (uNADW) and lower North Atlantic Deep
Water (lNADW), respectively, in the northern half of the section (Fig. 3a).
The uCDW and uNADW occupy the density band between σθ > 27.4 and σ3 < 41.47, with the front
between the two water masses found at approximately 26∘ N
(Mémery et al., 2000). The NADW has been more recently ventilated than
CDW and is thus distinguished by lower AOU values of ∼ 60 µmol kg-1 and DIC
values lower than 2200 µmol kg-1. The deeper lNADW can be separated from uNADW through higher
silicate values, which rise to 40 µmol kg-1, whereas uNADW has
maximum silicate concentrations of 20 µmol kg-1 (Fig. 3d). The
AT values are also lower (∼ 20 µmol kg-1) in
uNADW compared to lNADW.
The AAIW enters the section at 200 dbar just
south of 48∘ S, identifiable as a tongue of water with very low
salinity and AT (34.05 and 2275 µmol kg-1,
respectively, Fig. 3b). The AAIW lies above uCDW and below SAMW (Peterson and Whitworth, 1989). This water mass is carried
northward at intermediate depths between σθ > 27.1 and σθ < 27.4 (Ríos et al., 2012) from
south of the SAF. In the southwestern Atlantic Ocean, AAIW extends further
north than in other oceans, due to the western boundary current along the
coast of South America (Talley, 1996). The AAIW is a relatively young water
mass and has AOU values comparable to NADW (∼ 50–100 µmol kg-1); however, it can be distinguished from uNADW, in its
northward reaches, by its elevated silicate concentrations. Situated above
the AAIW, the SAMW is often considered a component of the AAIW (McCartney,
1977). This water mass can be easily identified by the tracer
Si* = [Si(OH)4]–[NO3-],
which has values from -10 to -15 µmol kg-1 in regions of SAMW formation (Sarmiento et al., 2004). The SAMW
formation region is located just south of 47∘ S in SAZ, north of the SAF (McCartney, 1977), where deep
winter mixing forms this high-oxygen water mass.
Distribution of Cant (µmol kg-1) calculated
using the ϕCT0 method with the GEOTRACES-NL (2010/2011)
data set (top); distribution of ΔCant1994-2011
(µmol kg-1), calculated using the eMLR approach (middle); and the
distribution of the ΔpH1994-2011 associated with ΔCant1994-2011 (bottom). The aragonite saturation horizon (ΩAr) is marked for pre-industrial times (solid line), 1994 (dashed line)
and 2011 (dotted line).
We locate the STF at ∼ 41∘ S,
where there is a steep gradient in salinity in the surface 200 dbar. North
of the STF, in the surface, and extending northward to a density of σθ< 26.5 kg m-3, is South Atlantic Central Water
(SACW; Ríos et al., 2012), heavily depleted in silicate and with
elevated salinity and AT. Against this background, the two Amazon
plumes are very distinct at 5 and 15∘ N, with salinity values of 34.11 and 32.3 and AT values of 2265 and
2157 µmol kg-1, respectively. The maximum values of both
salinity and AT correspond to SACW in
the subtropics (17∘ S), reaching absolute maxima of 37.5 and 2456 µmol kg-1, respectively, at 50 dbar depth. The subtropical part of
the SACW that features high salinity and AT is often referred to as the
Salinity Maximum Water (SMW). In this study we make no distinction between
SMW and SACW.
Results and discussion
Anthropogenic carbon in the southwestern Atlantic Ocean
The distribution of Cant in 2011, calculated using the ϕCT∘ method (Vázquez-Rodríguez, 2009a), and the calculated increase in
Cant (ΔCant) from 1994 to 2011, obtained from an eMLR
analysis, are shown in Fig. 4a and b, respectively. Both distributions
show good consistency with previous studies (Ríos et al., 2010, 2012;
Wanninkhof et al., 2010) and are not dissimilar from
each other, with areas of high Cant also demonstrating the highest
ΔCant from 1994 to 2010/2011. The total Cant (Fig. 4a) values
show an increase in the surface waters compared to that of Ríos et al. (2010), calculated from the WOCE '94 A17 data set, which is consistent with
the calculated ΔCant presented here (Fig. 4b). The general
pattern is that, from 1994 to 2011, the most evident increase in Cant
occurred in the upper 1000 dbar, particularly in the southern half of the
section, with the ΔCant increasing towards the surface. The
atmosphere is the main source of Cant to the ocean; thus it follows
that the waters most recently in contact with the atmosphere will show the
greatest ΔCant. Within the surface waters (< 100 dbar)
of the section the ΔCant gradually decreases northwards in a
linear relationship with latitude (R2=-0.74) to a concentration
of 0 µmol kg-1 just north of the Equator (∼ 5∘ N). Despite containing large quantities of Cant (Fig. 4a),
low ΔCant values (< 5 µmol kg-1) have been
previously noted in the tropical Atlantic region, to a depth of 200 dbar,
similar to that observed here (Schneider et al., 2012). The same
authors(Schneider et al., 2012) have suggested that greater precipitation in the Intertropical Convergence
Zone can cause errors in the surface Cant determinations in the
tropical Atlantic, due to the related increase in Revelle factor. In the
section presented here the Amazon outflow can also be seen in salinity
values; thus a variation in freshwater input may also contribute to errors
in the method.
The calculated rates of increase in Cant and rates of
decrease in pH along the section, listed per water mass. The identification
criteria for each water mass are provided. Error represents 2σ/N0.5.
Water mass
Density range
Latitude
Pressure
dCant/dt
dCant/dt*
dpH/dt
(dbar)
(µmol kg-1yr-1)
(µmol kg-1yr-1)
(yr-1)
SACW
σθ20–σθ26.8
23–18∘ S
90–160
0.99 ± 0.14
0.90 ± 0.04
-0.0016
SAMW
σθ26.8–σθ27.1
50–48∘ S
90–160
0.53 ± 0.11
0.53 ± 0.02
-0.0014
AAIW
σθ27.1–σθ27.4
50–48∘ S
360–450
0.36 ± 0.06
0.36 ± 0.06
-0.0010
uCDW
σθ27.4–σ341.47
50–49∘ S
1400–1800
0.33 ± 0.07
0.16 ± 0.04
-0.0010
uNADW
σθ27.4–σ341.47
10–15∘ N
1600–1800
0.20 ± 0.03
0.16 ± 0.04
-0.0005
lCDW
σ341.47–σ445.9
50–48∘ S
3250–3750
0 ± 0.06
0.08 ± 0.04
0.0000
lNADW
σ341.47–σ445.9
10–15∘ N
3000–3500
0 ± 0.02
0.08 ± 0.04
0.0000
* Values from Ríos et al. (2012).
The largest increase (up to 37 µmol kg-1) in surface waters was
found in the SAZ, just south of 45∘ S, in agreement with the
findings of Wanninkhof et al. (2010). The steepest vertical gradient of
ΔCant is found in the same region, at ∼ 47∘ S just north of the SAF, where over a depth range of 0–600
dbar the ΔCant decreases from 37 to 0 µmol kg-1.
Further north, the deepest penetration of positive ΔCant values
in the southern half of the section is found at 1200 dbar in the SubTropical Zone (STZ),
between 25 and 40∘ S. The ΔCant zero-contour shoals southward of 35∘ S to
∼ 600 dbar at 50∘ S, coinciding with the lower
limits of AAIW, as has been noted in other ocean basins (Sabine et al.,
2004). In the northern half of the section, the deepest limit of ΔCant penetration in AAIW reaches a depth of ∼ 700 dbar
at 15∘ S, and north of the Equator the AAIW signal becomes
distorted as it mixes with NADW. The NADW shows near-zero concentrations of
ΔCant throughout its extent, with the exception of the uNADW in
the equatorial region, which shows ΔCant values up to 5 µmol kg-1. In lNADW and the other deep and bottom waters (AABW, lCDW),
ΔCant shows no change or a tendency towards negative values.
To estimate the rate of increase in Cant in each water mass, we
identified their respective cores (Fig. 3b) using the water mass
descriptions given in Mémery et al. (2000) and Ríos et al. (2012)
and averaged their values of ΔCant. Assuming a constant yearly
increase, we then divided this total increase by 17 to obtain the rate of
yearly increase in Cant over the period 1994 to 2011. The calculated
values are shown in Table 2 with those of Ríos et al. (2012) for
comparison. The highest rates of increase were found in SACW and SAMW with
Cant increase rates of 0.99 ± 0.14
and 0.53 ± 0.11 µmol kg-1 yr-1, respectively. The
latter value shows good consistency with that calculated by Ríos et al. (2012) (0.53 ± 0.02 µmol kg-1 yr-1). However, there is a
notable difference of 0.09 µmol kg-1 yr-1 between the
increase for SACW calculated here and that of
0.90 ± 0.04 µmol kg-1 yr-1 (Ríos et al., 2012). As this is a surface water
mass, and our study utilized data collected 6 years after those used for
comparison in Ríos et al. (2012), we corrected the ΔCant
accordingly. Assuming equilibration between the atmosphere and ocean, we
corrected our ΔCant value for the additional DIC increase
caused solely by atmospheric increases over the last 6 years. The resulting
calculated Cant1994-2005 increase rate was 0.92 ± 0.14 µmol kg-1 yr-1, making our result consistent with the
previous estimate. As such, we attribute the difference in calculated
ΔCant increase rates in SACW to the increase in DIC driven by
higher atmospheric pCO2 concentrations in 2010/2011.
Despite the similarities in formation history between SAMW and AAIW, the
latter shows a much lower Cant increase rate of
0.37 ± 0.06 µmol kg-1 yr-1. The discrepancy between the Cant increase rates in
these two water masses is in line with the differences in air–sea CO2
flux in the region (McNeil et al., 2007). In the SAZ a combination of
biological production and temperature variability leads to a large seasonal
signal of pCO2. The SAMW is formed in the SAZ, where there is high
biological production in spring and summer and wintertime cooling of surface
waters. The wintertime cooling effect on the solubility of CO2 is
sufficient to counteract the increase in DIC from mixing, resulting in a
strong year-round CO2 sink. South of the SAF, where AAIW is formed,
similar processes operate; however, the biological production is lower, and
convective wintertime mixing brings up high-DIC waters, thus reducing the
CO2 sink (McNeil et al., 2007). It has also been shown that the formation rate of AAIW in the
Indian Ocean is less than that of SAMW, which
facilitates more efficient sequestration of Cant by the latter (Hartin
et al., 2011).
Modest increase rates of 0.33 ± 0.07 and
0.20 ± 0.03 µmol kg-1 yr-1 were calculated for uCDW and
uNADW, respectively. Both these water masses have been fairly recently
ventilated, allowing modest increases in ΔCant. The increase
rate for uNADW is in line with values found by Perez et al. (2010). Due to
the very low ΔCant values found in lNADW and lCDW, their
respective increase rates are not significant and are not discussed further.
In contrast to our calculated ΔCant, a number of studies have
found increasing concentrations of Cant in AABW (Murata et al., 2008;
Vázquez-Rodríguez et al., 2009a; Brown et al., 2010). However, it
has been noted previously that it is absent in eMLR analyses (Wanninkhof et
al., 2010). The distributions of Cant in AABW presented in
Vázquez-Rodríguez et al. (2009a) also indicate that Cant
concentrations have not yet spread further north than 50∘ S,
potentially explaining its absence in our analysis.
Associated changes in pH
Assuming no changes in AT between the WOCE '94 A17 and GEOTRACES-NL
(2010/2011) occupations, we use the ΔCant calculated by eMLR
and the measured AT during GEOTRACES-NL (2010/2011) to calculate the
anthropogenically driven change in pH from 1994 to 2011 (ΔpH1994-2011). From the application of the ϕCT0 method
of anthropogenic carbon determination (Sect. 2.3.2) to the WOCE '94 A17
data set, we obtain the total Cant signal from pre-industrial times to
1994 (Fig. 4a). The Cant value allows the calculation of the decline in
pH, which has been caused by increasing Cant during this time period
(from pre-industrial times to 1994: ΔpH1994). The average
surface (< 250 dbar) ΔpH1994 across the section was
-0.08, which is just under the predicted general surface ocean decrease of
0.1 (Orr et al., 2005). The ocean interior experienced relatively small
ΔpH1994; however, the change was accompanied by a significant
shoaling of the aragonite saturation horizon, most notably in the southern
half of the section (Fig. 4c). From pre-industrial times to 1994, south of
the SAF, at ∼ 49∘ S, the aragonite saturation
horizon rose by ∼ 250 m, whereas further north, at
25∘ S, it rose just 200 m. The change was almost
imperceptible north of the Equator. From 1994 to 2011, ΔpH1994-2011, there is a further decline of 0.03 units, making the
total surface ΔpH2011 -0.11 units since pre-industrial times.
Thus, of the total decrease since pre-industrial times to the present day,
27 % occurred within the past 17 years. However, we can detect no notable
change to the aragonite saturation horizon over the past 17 years (Fig. 4c).
Historically, the uptake of Cant by the surface ocean was relatively
gradual, which allowed it to be well distributed throughout the water
column. In contrast, the effects of the more recent, steeply increasing
anthropogenic acidification have not yet significantly penetrated into the
deeper ocean.
The distribution of ΔpH1994-2011 across the section broadly
follows the Cant increases (compare Fig. 4b, c), as expected under the
assumption of constant AT. By assuming a constant decrease
over the 17 years, the yearly acidification rates are calculated from
ΔpH1994-2011 and identified for each water mass core, as done
for the yearly Cant increases (Table 2). The highest rates of
acidification were found in the surface waters, where we also observe the
greatest rates of Cant increase, with SACW showing a rate of pH
decrease of 0.0016 yr-1. The latter value is in line with that
calculated for the same water mass on the eastern side of the North Atlantic
Ocean at the ESTOC site (0.0017 yr-1) for the period 1995 to 2004
(Santana-Casiano et al., 2007; González-Dávila et al., 2011). The
SAMW demonstrates the next greatest rate of decline of 0.0014 yr-1,
followed by AAIW and uCDW both showing acidification rates of 0.001 yr-1, which are comparable with values from other recently ventilated
water masses in the North Atlantic: acidification rates of 0.0019
and 0.0012 yr-1 have been reported for SAIW and
SPMW, respectively (Vázquez-Rodríguez et al., 2012).
The lowest non-zero acidification rate of 0.0005 yr-1 is found in
uNADW.
Buffering capacity
The continuing uptake of atmospheric CO2 gradually depletes the
naturally available carbonate ion in the surface ocean, thereby decreasing
the capacity to “buffer” further CO2 uptake and leading to the gradual
acidification of the seawater. The extent to which the pH is affected by the
increase in DIC is dependent upon several properties, including temperature,
pressure and AT, which together determine the buffering capacity of the water. As DIC
increases, assuming no other changes take place, the buffering capacity of
the water is reduced as [CO32-] decreases and [CO2]
increases. The AT is not altered by the flux of atmospheric CO2
into the ocean. However, AT is affected by biological processes,
notably the dissolution and formation of calcium carbonate, with dissolution
dominating in deep waters and formation playing a more important role in the
surface. Table 2 quantifies the extent to which the calculated ΔCant has impacted pH in the water masses of the southwestern Atlantic
Ocean. Examination of this table clearly shows that the rate of
acidification per µmol kg-1 of DIC is not equal between water
masses. The SAMW, a relatively fresh, low-alkalinity water mass, has an
acidification rate of -0.0014 yr-1, which is 88 % of that of SACW, a
warmer, more saline water mass. However, the Cant increase rate of SAMW
is only 54 % that of SACW. The AAIW shows the same rate of acidification
as uCDW; however, the increase in Cant in uCDW is 10 % lower than that
of AAIW. These differences can be attributed to the varying buffering
capacities of the water masses.
The distributions of the Revelle factor and the sensitivities of
[H+](βDIC), [CO2](γDIC) and ΩCaCO3
(ωDIC) to changes in DIC for the southwestern Atlantic are shown in
Fig. 5 and given per water mass in Table 3. The highest buffer factors,
which indicate the greatest sensitivities to increasing DIC (denoted by low
values in Fig. 5b, c, and high values in d) were generally found in the
deep waters. That is to say that, for a given increase in DIC, these waters
will show large resultant changes in [H+], [CO2] and
[CO32-], or aragonite and calcite saturation (ΩAr,
ΩCa). Both uCDW and lCDW show very similar behaviour – as
expected from their similar history – however, interestingly, there is a
notable difference between the buffering capacities of the two limbs of
NADW. The difference is most noticeable in ωDIC, likely caused by
the slightly higher AT / DIC ratio in lNADW. A lower βDIC in
uNADW denotes a greater sensitivity to acidification in response to
increasing DIC concentrations. More rapid acidification in uNADW compared to
lNADW has been observed by Vázquez-Rodríguez et al. (2012) and
attributed to mixing with Labrador Sea Water (LSW), which exhibits a strong
decreasing pH trend with time. The lower pH of LSW and its contribution to
uNADW could account for the reduced buffering capacity calculated in this
water mass in the southwestern Atlantic Ocean.
The average water mass values of salinity and potential
temperature, with accompanying average buffering capacity values (γDIC, βDIC, ωDIC and Revelle factor) calculated using the
GEOTRACES-NL (2010/2011) data set. Water masses are determined using the same
criteria as given in Table 2.
Water mass
Salinity
Theta
γDIC
βDIC
ωDIC
Revelle factor
(∘C)
(mmol kg-1)
(mmol kg-1)
(mmol kg-1)
SACW
36.854
22.693
0.211
0.256
-0.327
10.02
SAMW
34.021
4.4218
0.144
0.161
-0.181
14.83
AAIW
34.222
2.8567
0.136
0.149
-0.165
16.02
uCDW
34.682
1.9528
0.132
0.143
-0.156
17.14
uNADW
34.987
3.8578
0.132
0.168
-0.191
14.40
Distribution of the Revelle factor across the section (top
left) and the three buffering factors relating to DIC: βDIC (top
right), γDIC (bottom left) and ωDIC (bottom right). The
latter three are all given in mmol kg-1.
The lowest Revelle factor and highest βDIC values are found in SACW,
closely followed by SAMW, which despite containing large concentrations of
Cant, both have relatively low concentrations of DIC compared to the
other water masses. The SACW and SAMW also have higher concentrations of
AT giving them greater buffering capacity. The three water masses with
the greatest response in pH relative to ΔCant were AAIW, uCDW
and lCDW, with βDIC values of 0.148, 0.141 and 0.143 mmol kg-1, respectively. These water masses show
the highest DIC / AT ratios along the section as they all originate in
the Southern Ocean (SO), where upwelling brings deep waters rich in
[CO2(aq)] and low in [CO32-] to the surface. In addition,
these waters have slightly lower salinities and thus lower borate
concentrations, which further diminish their buffering capacity, also
reflected in the high Revelle factors (Fig. 5a). For the same DIC value, the
buffering capacity of AAIW is substantially lower than that of uCDW stemming
from the low AT of AAIW, which is also reflected in the high ωDIC values. With the current calculated rate of increase in Cant,
aragonite will become undersaturated in AAIW around the year 2100, when DIC
concentrations reach 2208 µmol kg-1. This could happen even
sooner, as wintertime, storm-driven upwelling entrainment of deep waters
into the surface in the SO is predicted to cause seasonal aragonite
undersaturation in the region as soon as 2030, when atmospheric CO2
levels reach ∼ 450 ppm (McNeil and Matear, 2008).
Continued Cant increase
The buffering capacity of each water mass will be reduced by increasing the
DIC concentrations. To investigate how the buffering capacities of the
different water masses in this section have changed over time, and how they will
continue to change, the DIC buffer factors of each water mass were calculated
and plotted against DIC concentration (Fig. 6). Due to the large
relative error of the calculated ΔCant increases in the deeper
waters, these were not included. The high rate of uptake of Cant by
SACW means that this water mass has seen the largest decrease in buffering
capacity since pre-industrial times. The βDIC value has decreased
from 0.281 to 0.247 mmol kg-1 and ΩAr has decreased from
4.1 to 3.3. In contrast, uCDW has shown relatively little change due to the
low values of Cant. However, extrapolating our calculated Cant
rates of increase, we predict a 33 µmol kg-1 increase in this water
mass over the next century, which will result in a significant reduction in
buffering and a pH decrease of -0.102. The buffering capacities of SAMW and
AAIW follow a similar pattern to each other; however, SAMW contains a
greater proportion of subtropical water than AAIW, and thus it maintains a
slightly higher buffering capacity than AAIW. Both AAIW and uCDW will see a
similar increase in Cant over the next century (37 and 33 µmol kg-1,
respectively); however, the decline in ΩAr will be
1.6 times greater in AAIW, due to higher ωDIC values. The SAMW will
see approximately 54 % of the increase in Cant that SACW will
experience; however, it will undergo 84 % of the associated pH decline. These
extrapolated predictions highlight the vulnerability of SAMW and AAIW to
increasing Cant, as also noted by Gonzalez-Davila et al. (2011).
The buffer factors βDIC (top), γDIC (middle)
and ωDIC (bottom) of each water mass over a range of DIC
concentrations. The vertical lines denote the DIC concentration in
pre-industrial times, 1994 and 2011 and the projected concentration in 2110.
The observed pattern of ΔCant in the southwestern Atlantic clearly
identifies the SAZ as the most effective entry point of Cant into the
ocean. In addition, the buffering factors of Egleston et al. (2010)
explicitly show that by, the end of this century, the two dominant water
masses in this area (SAMW and AAIW) will be the most sensitive to further
Cant increases. Whilst it is clear that this will accelerate the rate
of acidification in these water masses, it is unclear how it will affect the
CO2 uptake in the SAZ. Assuming no changes to primary production, the
increased sensitivity of SAMW to DIC changes will lead to much greater
seasonal variability in the carbonate system of this water mass between the
productive and non-productive period. The biological uptake of DIC in the
SAZ in austral spring and summer would lead to a more dramatic decrease in
surface water pCO2, allowing a greater air–sea pCO2 flux.
Conversely, the acidification and decline in ΩAr may be
detrimental to calcifying organisms in the area, as observed in the Southern
Ocean (Bednarsek et al., 2012), thus limiting export via the biological
pump.
The water masses SAMW and AAIW both risk further reduction in their
buffering capacities by long-term variability to their physical properties.
On decadal timescales a freshening of AAIW has been observed in the Pacific
and Indian sectors of the Southern Ocean (Wong et al., 1999). Decadal
variability has also been noted in temperature, salinity and biogeochemical
parameters of SAMW (Bindoff et al., 2007; Alvarez et al., 2011), which could
further diminish or enhance the buffering capacity of this water mass and
thus the Cant-driven acidification. Variations on decadal timescales
have been related to the Southern Annular Mode, the dominant climate forcing
over the region (Lovenduski et al., 2007; Álvarez et al., 2011).
Similarly in the North Atlantic, the North Atlantic Oscillation exerts a
degree of control over the carbonate system variables and Cant uptake
(Santana-Casiano et al., 2007; Pérez et al., 2010). Such external
controls will cause irregular Cant uptake over time, as was
observed by Brown et al. (2010), making it difficult to accurately predict
future Cant uptake and associated changes in the buffering capacity.