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Relative to previously published methods, applying this RP-HPLC technique reduces the required sample volume significantly (as can be seen in Table3.3), by∼20-fold and∼60-fold in the case of FIA and ICP-MS respectively. This is due to the combination of the extremely sensitive fluorescence detection system and the advantages of HPLC such as low system dead volumes, excellent analyte focusing on highly efficient columns and little band broadening. However, as discussed earlier, comparison with ICP-MS in this case is not fair, as that is a multi-element technique.

3.5

Conclusions

A major limitation of this technique is the time required for sample pre-treatment. This is a function of the slow reaction kinetics of Al (Eigen,1963). Resing and Measures(1994) andBrown and Bruland (2008) have shown how the heating of the reagent-sample mixture would increase

Chapter 3: RP-HPLC determination of dAl in open ocean seawater 59 0.0 0.5 1.0 1.5 2.0 4000 3000 2000 1000 0 DAl (nM) Depth (m) | | | | | | | | | | | | | | | | | | | | | | | | || | | LOD

Figure 3.4: Example depth profile of dAl from the SR3 transect (Station N20, 144°E, 49.3°S, within the

Polar Frontal Zone of the SO, sampled in April 2008 as part of the International Polar Year - GEOTRACES program).

the kinetics of the Al–lumogallion complex formation. However, it also increases the rate of complex decomposition. Therefore, increasing the rate of kinetics requires in-line systems that can standardise the time between mixing with the reagent and detection (such as those used by

Resing and Measures (1994) and Brown and Bruland(2008)). The HPLC system available to the authors at the time of development was not capable of automating the addition of the reagent to the sample hence a more conservative approach to sample pretreatment was adopted, focusing on the long-term stability of the Al–lumogallion complex.

The use of an automated sample dosing and injection system would reduce the time required for complex formation, whilst maintaining the large gains in robustness and automation. The authors would also expect an increase in sensitivity, as the time of maximum complex yield could be targeted.

seawater. It employs similar chemistry to the FIA method and has good agreement with agreed values for the SAFe standard reference material. Therefore, open ocean dAl data produced with RP-HPLC are compatible for comparison with the existing global data set. The RP-HPLC method is recommended for future work for those determining Al in seawater due its robustness, sample volume requirements and automation capacity, while achieving comparable LOD, precision and accuracy to existing methods.

Chapter 4: Using dissolved aluminium concentrations to constrain trace element supply to the

subantarctic SO south of Australia 61

Chapter

4

Using dissolved aluminium concentrations to

constrain trace element supply to the subantarctic

SO south of Australia

4.1

Introduction

In the high-nutrient, low-chlorophyll (HNLC) regions of the ocean, primary production is significantly influenced by micronutrient supply (Martin and Fitzwater,1988;Martin et al., 1990). Therefore, constraining the relative contributions of the various sources and sinks of micronutrients is important for understanding the biogeochemical cycling in these regions.

The SAZ is a circumpolar HNLC region and is the interface of the major ocean basins to the SO. The SAZ has phytoplankton concentrations that are relatively high for the SO, exhibit low seasonality and regional variability and are controlled by a complex interplay between light, mixed layer depth (MLD), micronutrient and silicic acid supply and grazing pressure (Rintoul and Trull,2001;Bowie et al.,2011a,b;Ebersbach et al.,2011).

The SAZ-Sense (Sensitivity of the Subantarctic Zone to Environmental Change, GEOTRACES cruise GIPY2) project aim was to examine the links between circulation, macro- and micronutrient supply, microbial ecology, and carbon cycling (Bowie et al., 2011a). Three process stations were identified (see Figure 4.1: two in the SAZ just to the south-west (P1) and the south-east (P3) of Tasmania to compare the east-west gradient; and a third (P2) just poleward of the Polar Front (PF), due south of Tasmania, as it was representative of source waters into both P1 and P2 and to provide a reference water body. P1 was expected to be typical of the present-day SAZ, while P3 was expected to be more characteristic of the zone under the influence of future climate change (Bowie et al.,

2011a). P1 was expected to be of lower biomass, and P3 was expected to be of higher biomass. Key parameters (identified by the international GEOTRACES program) were analysed at each station in an attempt to elucidate the relative magnitude of micronutrient supplies and sinks. Aeolian deposition is thought to be an important source of micronutrients (such as Iron, Fe) to the open ocean (Martin,1990;Martin et al.,1990;Martin,1991;Duce and Tindale, 1991;Boyd et al.,1996,2000;

Figure 4.1:8-day composite MODIS image of chlorophyll-a concentrations from 18-Feb-2007, fromMongin

et al.(2011b). Chlorophyll-a (as a proxy for biomass) concentrations were P3>>P1>P2. Process station

locations were selected to discern the physical and biogeochemical drivers of regional differences in biomass and primary production.

Bowie et al.,2009). However, estimating the contribution of aeolian dust to the micronutrient budget of the SAZ and SO is difficult due to: the sporadic and variable nature of these events (Gabric et al.,

2010); the remote location of the target region; the high instance of cloud (reducing the usefulness of satellites); and the biogeochemistry of the target micronutrients (e.g. biologically active, poor solubility in seawater, short residence times (weeks) (Frank et al., 2003; SCOR Working Group,

2006,2007,2012)).

Al is a GEOTRACES key parameter, used to identify the relative magnitude of aeolian deposition events. Al is ∼8% of earths crust (Taylor, 1964; Wedepohl, 1995; Yaroshevsky, 2006) and is

readily transported in dust during deposition events to the open ocean (Duce and Tindale, 1991;

Chapter 4: Using dissolved aluminium concentrations to constrain trace element supply to the

subantarctic SO south of Australia 63

in seawater is assumed to be insignificant and it is an element that is readily scavenged (Paces,

1978;Stoffyn,1979;Mackin and Aller,1984c;Walker et al.,1988;Moran and Moore,1988,1992;

VanBeusekom et al., 1997). As it is readily scavenged it has a relatively short residence time in the surface ocean, generally assumed to be<3 years (Stoffyn,1979;Stoffyn and Mackenzie,1982;

Orians and Bruland, 1985,1986), but can range from days to weeks in region of high productivity to >3 years in regions of low productivity (Orians and Bruland, 1986; Moran and Moore, 1988;

Brown et al., 2010). This makes it useful as a biogeochemical tracer of watermasses over these timescales. Al can indicate the level of interaction the target watermass has had with terrestrial sources of micronutrients, such as aeolian deposition into the ocean (Measures and Edmond,1989), although this relationship is limited to surface waters due to sedimentary resuspension (Moran and Moore, 1991; Middag et al., 2009). dAl concentrations in the ocean can be used as inputs into the MADCOW model (Measures and Vink,2001) to estimate the aeolian dust deposition rate (g.m−2_.y−1_{), and therefore, the relative magnitude of dust as a source of micronutrients compared}

to upwelling and lateral advection (Measures and Edmond,1989).

Within this context, dAl concentrations were determined at each station (both transect and process stations) and in combination with other parameters used in an effort to constrain micronutrient supply mechanisms to each process station (P1, P2 and P3).