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Studies on trace metal dynamics in mesoscale anticyclonic eddies in the Gulf of Alaska Crispo, Sabrina Marie 2007

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STUDIES ON TRACE METAL DYNAMICS IN MESOSCALE ANTICYCLONIC EDDIES IN THE GULF OF ALASKA by SABRINA MARIE CRISPO B.Sc. Chemistry, Saint Francis Xavier University, 1999 Dip. Engineering, Saint Francis Xavier University, 1999 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA August 2007 © Sabrina Marie Crispo, 2007 ABSTRACT Haida eddies are large, anticyclonic eddies that form off the coast of the Queen Charlotte Islands, British Columbia during the winter. They can transport up to 6000km of coastal water offshore annually. The eddy can retain its coastal signature for up to 3 years before it dissipates. Due to the length of time these eddies exist and their rninimal interactions with surroundings, the Haida eddies are an ideal laboratory in which to study processes affecting trace metal distributions as coastal water ages. Haida eddies were found to transport high concentrations of dissolved aluminum and manganese into the Gulf of Alaska. Average dissolved aluminum and manganese concentrations decreased within the eddy as it aged. The quantity of dissolved aluminum these eddies supply to the Gulf of Alaska was similar to the predicted amount of dissolved aluminum supplied by dust deposition to this region. Average dissolved cadmium and copper concentrations increased within the eddy as it traveled offshore into waters with higher nutrient concentrations. For both cadmium and copper, the increase in the amount of the dissolved metal concentration within the core of the eddy over time was not significantly different from the amount predicted by physical mixing. The processes controlling dissolved iron distributions within the surface waters of the Haida eddy over time were also studied with the aid of tracers. It was found that both biological uptake and particle scavenging played a role in dissolved iron removal. Dissolved manganese supplied information on external dissolved iron inputs, although removals of dissolved manganese and dissolved iron were not correlated. Changes in cadmium to phosphate ratios support the theory of preferential cadmium uptake in iron-limited waters, and the similarities between iron and copper dynamics in the surface waters suggest that the biological uptake and regeneration of copper and iron are linked. iii TABLE OF CONTENTS ABSTRACT i i LIST OF TABLES viii LIST OF FIGURES x i i LIST OF ABBREVIATIONS .xvii ACKNOWLEDGEMENTS. -xix DEDICATION. xx GENERAL INTRODUCTION 1 1.1 Introduction 1 1.2 Metals in Seawater. 2 1.2.1 Fractions of Trace Metals 2 1.2.2 Dissolved Trace Metals. 4 1.2.2.1 Dissolved Trace Metal Distributions. 5 1.2.2.2 Trace Metal Analysis. .8 1.2.3 Trace Metals of Interest 10 1.2.3.1 Aluminum 10 1.2.3.1.1 Chemistry in Seawater 10 1.2.3.1.2 Dissolved Depth Profile. 10 1.2.3.1.3 Sources and Removals 12 1.2.3.2 Cadmium. 13 1.2.3.2.1 Chemistry in Seawater 13 1.2.3.2.2 Dissolved Depth Profile. 14 1.2.3.2.3 Sources and Removals 15 1.2.3.2.4 Cadmium and Phosphate Relationship 15 1.2.3.3 Copper 17 1.2.3.3.1 Chemistry in Seawater 17 1.2.3.3.2 Dissolved Depth Profile. 18 1.2.3.3.3 Sources and Removals 19 1.2.3.4 Manganese 20 iv 1.2.3.4.1 Chemistry in Seawater 20 1.2.3.4.2 Dissolved Depth Profile. 21 1.2.3.4.3 Sources and Removals 23 1.2.4 Trace Metals as Iron Tracers 24 1.2.4.1 Iron Biogeochemistry 24 1.2.4.2 Chemical Tracers and Their Ability to Trace Iron 26 1.3 Mesoscale Eddies. 28 1.3.1 Introduction 28 1.3.2 Eddy Background 30 1.3.2.1 Classification 30 1.3.2.2 Eddy Formation and Propagation 31 1.3.2.3 Eddies in the Gulf of Alaska 33 1.3.3 Haida Eddy Study 34 1.4 Thesis Objectives and Thesis Outline 35 1.5 References 37 CHAPTER 2: DISSOLVED ALUMINUM DYNAMICS WITHIN MESOSCALE ANTICYCLONIC EDDIES IN THE GULF OF ALASKA. 66 2.1 Introduction. 66 2.2 Methods 68 2.2.1 Trace Metal Sampling 68 2.2.2 Dissolved Aluminum Analysis 70 2.2.3 Data Analysis 71 2.3 Results and Discussion 72 2.3.1 Eddy Background 72 2.3.2 Haida Eddy Source Waters 73 2.3.3 Surface Dynamics 74 2.3.4 Deep Water Transport 78 2.3.5 Total Offshore Transport 82 2.3.6 Scavenging Rates and Residence Times 85 2.4 Conclusion 87 2.5 References .88 V CHAPTER 3: A STUDY OF THE FACTORS CONTROLLING THE DISSOLVED IRON IN SURFACE WATERS WITHIN AN ANTICYCLONIC EDDY. 94 3.1 Introduction 94 3.2 Methods 97 3.2.1 Sample Stations 97 3.2.2 Trace Metal Sampling... 98 3.2.3 Trace Metal Analysis. 99 3.2.4 Data Analysis 100 3.3 Results. 102 3.3.1 Haida Eddy Evolution 102 3.3.2 Newly Formed Haida Eddy. 104 3.3.3 Changes in Surface Mixed Layer. 108 3.3.3.1 Aluminum 108 3.3.3.2 Cadmium 108 3.3.3.3 Manganese I l l 3.3.3.4 Copper 112 3.3.3.5 Iron ...113 3.4 Discussion. 114 3.4.1 Major Controls on Tracer Distributions. 114 3.4.1.1 Aluminum 114 3.4.1.2 Cadmium 114 3.4.1.3 Manganese 116 3.4.1.4 Copper 117 3.4.2 Iron Surface Dynamics 118 3.4.2.1 Age: 0 months. 118 3.4.2.2 Age: 0 to 4 months 119 3.4.2.3 Age: 4 to 7 months 120 3.4.2.4 Age: 7 to 12 months 122 3.4.2.5 Age: 12 to 16 months 123 3.4.2.6 Age: 16 to 19 months 124 3.5 Conclusion 124 vi 3.6 References . 126 CHAPTER 4: PROCESSES CONTROLLING TRACE M E T A L DISTRIBUTIONS WITHIN THE SUB-SURFACE WATERS OF A HAIDA EDDY 132 4.1 Introduction. 132 4.2 Methods '. 133 4.2.1 Trace Metal Sampling 133 4.2.2 Trace Metal Analysis 135 4.2.3 Data Analysis 135 4.2.4 Physical Parameters. 137 4.3 Results and Discussion 138 4.3.1 Eddy Background 138 4.3.2 Salinity and Trace Metal Depth Profiles 138 4.3.3 Physical Mixing Model 139 4.3.3.1 Description of Physical ModeL 139 4.3.3.2 Physical Model Results 143 4.3.4 Physical Mixing Model Predictions 146 4.3.4.1 Aluminum 147 4.3.4.2 Manganese 149 4.3.4.3 Cadmium. 149 4.3.4.4 Copper 150 4.4 Conclusion 150 4.5 References 152 CHAPTER 5: GENERAL DISCUSSION. 155 5.1 Introduction. 155 5.2 General Discussion 155 5.2.1 Haida Eddy Transport 155 5.2.2 The Study of Iron Dynamics using Tracers 157 5.3 Importance to Field of Study 158 5.4 Future Direction. 159 5.5 References 162 APPENDIX A: METHODS AND ANALYSIS 164 V l l A P P E N D I X B : E R R O R A N A L Y S I S O F P R O C E D U R E . 175 A P P E N D I X C : C O M P A R I S O N O F C O M M E R C I A L L Y A V A I L A B L E C H E L E X ® 100 A N D I N - L A B S Y N T H E S I Z E D 8 - H Y D R O X Y Q U I N O L I N E B O U N D T O A M B E R L I T E ® XAD-2 R E S I N F O R T H E A N A L Y S I S O F S E A W A T E R 184 A P P E N D I X D : T R A C E M E T A L D A T A 196 V l l l L I S T O F T A B L E S Table 1.1. Classification of dissolved trace metal depth profiles. Mean oceanic residence time given in years. The equation for calculating residence time in given in text (Equation 1.1) 6 Table 2.1. Comparison of change in surface dissolved aluminum (in percent) between cruises with chlorophyll concentrations and mixed layer integrated biogenic silica. Chlorophyll concentrations from Crawford et al., 2005. Biogenic silica concentrations from Peterson, 2005 76 Table 2.2. Removal of dissolved Al during eddy lifetime. Removal is given as nM of dissolved Al/day. 80 Table 2.3. Comparison of dissolved Al content in Haida eddies over time with the predicted dissolved Al input from dust deposition in the area influenced by Haida eddies. Area influenced by Haida eddies is 133°W to 145°W and 46°N to 55°N. Units are moles of dissolved Al... : 83 Table 2.4. Depth of 26.8 isopycnal from CTD data. Isopycnal depression, given in meters, compared to surrounding (reference station) waters 85 Table 3.1. List of cruise dates, stations sampled and locations. 98 Table 3.2. Average percent error on replicate samples (at 95% confidence level), instrument limit of detection, and method detection limit for aluminum, cadmium, copper, and manganese. Detection limits are converted to units of nM in original seawater by dividing by concentration factor, "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample) 101 Table 3.3. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval. 102 Table 3.4. Rates of change in mixed layer dissolved metal concentrations over sampling periods. Rate of change given in pM day"1; positive means gain in dissolved metal concentration; negative sign indicates removal of dissolved metal. Percent change is calculated as change in dissolved metal between sampling times divided by the dissolved concentration determined at the earlier sampling time: % Change = ([M]^- [ML^O/TM]^ 111 Table 3.5. Cadmium to Phosphate ratios in surface mixed layers, in nmol Cd/umol P. Cd/P ratios in surface mixed layers at reference stations sampled in September 2002 given for comparison purposes 112 ix Table 4.1. Percent error (at 95% confidence level), instrument limit of detection and method detection limit for aluminum, cadmium, copper, and manganese. Detection limits are converted to units of nM in original seawater by dividing by concentration factor, "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample). 136 Table 4.2. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval 137 Table 4.3. Depth (in meters) of the 34.0 isohaline for Haida-00 eddy 141 Table B-l . Summary table of different detection limits for aluminum, cadmium, copper, and manganese (converted to units of nM in original seawater by dividing by concentration factor), "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample 175 Table B-2. Average percent recovery for aluminum, cadmium, copper and manganese. The average recovery is expressed as an average recovery ± 95% confidence interval, where the confidence interval is equal to ts I *Jn 179 Table B-3. Results of precision test for column procedure. The average concentration is expressed as an average concentration in seawater sample ± 95% confidence intervaL.180 Table B-4. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval. 180 Table B-5. Method blank results from analysis of reagents in high purity, deionized water, and processed through entire analytical method. Results are given in units of nM, and reported as concentrations in original sample, before processing 181 Table B-6. Linear regression results from procedural blank analysis. Matrix effect results in units of nM of original seawater concentration, to make comparison to limits of detection 182 Table C-l . Chelex® 100 cleaning method based on method from Price et al., 1988-1989. All rinsing steps performed using a Millipore Sterifil funnel setup and a polypropylene suction flask with 75um Spectra/Mesh fluorocarbon (TPE,FEP) filter supplied by Spectrum Medical Industries, Inc 188 Table C-2. Recovery test results for both the 8-HQ and Chelex® 100 resins using a flow rate of 0.8mL/min. Recovery values stated as percents plus/minus standard deviation. Standard deviation calculated with a sample size of 4 or 6. n.d. signifies that recovery was not determined for that pH 192 X Table C-3. 8-HQ resin recovery dependency on flow rate using a pH of 7. Data for the recovery of gallium at a flow rate of 0.8mL/min missing but would be expected to be in the range of 80-90% from pH dependence data. 192 Table D-l. June 2000 Cruise - Reference Station 197 Table D-2. June 2000 Cruise - Haida-00 Center Station 198 Table D-3. June 2000 Cruise - Haida-00 Edge Station 199 Table D-4. September 2000 Cruise - Reference Station. 200 Table D-5. September 2000 Cruise - Haida-00 Center Station 201 Table D-6. September 2000 Cruise - Haida-00 Edge Station 202 Table D-7. February 2001 Cruise - Haida-00 Center Station 203 Table D-8. February 2001 Cruise - Haida-01 Center Station 204 Table D-9. June 2001 Cruise - Reference Station 205 Table D-10. June 2001 Cruise - Haida-00 Center Station 206 Table D-l 1. June 2001 Cruise - Haida-00 Edge Station 207 Table D-l2. June 2001 Cruise - Haida-01 Center Station 208 Table D-13. June 2001 Cruise - Haida-01 Edge Station 209 Table D-14. September 2001 Cruise - Reference Station .210 Table D-l5. September 2001 Cruise - Haida-00 Center Station 211 Table D-l6. September 2001 Cruise - Haida-00 Edge Station 212 Table D-l7. September 2001 Cruise - Haida-01 Center Station 213 Table D-18. September 2001 Cruise - Haida-01 Edge Station 214 Table D-l9. September 2002 Cruise - Ocean Station Papa 215 Table D-20. September 2002 Cruise - Hecate Strait Coastal Station (MT08) 216 Table D-21. September 2002 Cruise - Hecate Strait Coastal Station (MT10) 216 xi Table D-22. September 2002 Cruise - Queen Charlotte Sound (PCI) 217 Table D-23. September 2002 Cruise - Queen Charlotte Sound (MT3) 218 Table D-24. September 2002 Cruise - Queen Charlotte Sound (J5), 219 Table D-25. September 2002 Cruise - Queen Charlotte Sound (Rl 1). 220 X l l LIST OF FIGURES Figure 1.1. Schematic of the 'Great Ocean Conveyor Belt' first proposed by Broecker in 1987 to describe ocean circulation. Figure adapted from Kerr, RA, SCIENCE 239: 259-260 (Jan 15 1988). Reprinted with permission from AAAS 7 Figure 1.2. Dissolved Al depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 78, Orians, K. J. and Bruland, K. W., The biogeochemistry of aluminum in the Pacific Ocean, 397-410, copyright © 1986, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Geochimica et Cosmochimica Acta, 47, Hydes, D. J . , Distribution of aluminum in waters of the North East Atlantic 25 N to 35 N, 967-973, copyright © 1983, with permission from Elsevier.) 11 Figure 1.3. Dissolved Cd depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 47, Bruland, K. W., Oceanographic distribution of cadmium, zinc, nickel, and copper in the North Pacific, 176-198, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Deep Sea Research Part II Topical Studies in Oceanography, 40(1-2), Martin, J. H. et al., Iron, Primary Production and Carbon Nitrogen Flux Studies During the JGOFS North-Atlantic Bloom Experiment, 115-134, copyright © 1993, with permission from Elsevier.) 14 Figure 1.4. Dissolved Cu depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 47, Bruland, K. W., Oceanographic distribution of cadmium, zinc, nickel, and copper in the North Pacific, 176-198, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (from Trace Metals in Seawater, 1983, pp 395-414, Mn, Ni, Cu, Zn and Cd in the western North Atlantic, Bruland, K. W. and Franks, R. P., Plenum Press, with kind permission of Springer Science and Business Media.) 18 Figure 1.5. Dissolved Mn depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 49(1), Landing, W. M. and Bruland, K. W., Manganese in the North Pacific, 45-56, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Marine Chemistry, 61(1-2), Statham, P. J., Yeats, P. A. and Landing, W. M., Manganese in the eastern Atlantic Ocean: processes influencing deep and surface water distributions, 55-68, copyright © 1998, with permission from Elsevier) 21 Figure 1.6. Dissolved Fe depth profiles. The full circles represent a North Pacific station (reprinted from Deep Sea Research Part A Oceanographic Research Papers 36(5), Martin, J. H. et al., VERTEX: phytoplankton/iron studies in the Gulf of Alaska, 649-680, copyright © 1989, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Deep Sea Research Part II Topical Studies in Oceanography, 40(1-2), Martin, J. H. et al., Iron, Primary Production and Carbon Nitrogen Flux Studies X l l l During the JGOFS North-Atlantic Bloom Experiment, 115-134, copyright © 1993, with permission from Elsevier 25 Figure 1.7. Schematic of eddy circulation in the Northern Hemisphere (plan view) with a) clockwise flow around anti-cyclonic eddies (solid arrow) which results in build-up of water in the center of the eddy due to Coriolis deflection (dashed arrows); b) counter-clockwise flow around cyclonic eddies (solid arrow) which results in deficit of water in center of eddy (dashed arrows) 30 Figure 1.8. Schematic showing the side view of an anti-cyclonic eddy, a) shows the depression of isopycnals caused by build-up of water in the center of eddy due to eddy circulation, b) shows the rebounding of isopycnals due to frictional decay as the eddy spins down 31 Figure 1.9. Radar satellite altimetry contours showing the presence of a Haida eddy (dark spot at approximately 53 °N, 136°W) to the west of the Queen Charlotte Islands on June 18,2000. Height anomalies of ± 5cm indicate eddy locations. Solid contour lines indicate SSH anomalies > 0, dashed contour lines indicate SSH anomalies < 0. Image provided by the Colorado Centre for Astrodynamics Research (CCAR) online at http://argo.colorado.edu/~realtime/welcome/. 34 Figure 2.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time of sampling denoted by numbers below (or to the side) of the location symbol: 1 - June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001 .69 Figure 2.2. a) Oceanographically consistent dissolved aluminum depth profile with data from the reference station sampled in September 2001. b) Profiles from center station in September 2000, with actual data represented by closed circles and solid line, and predicted oceanographically consistent lower limit represented by open circles and dashed line 72 Figure 2.3. Dissolved aluminum concentrations versus depth at a) two sites within Hectare Strait: MT08 (53° 9.7' N, 130° 26.2' W; closed squares) and MT10 (53° 37.0' N, 130° 44.9' W; open squares) sampled in September 2002 and b) center of newly formed Haida-01 eddy sampled in February 2001. Error bars for MT08 and MT10 contained within symbol 74 Figure 2.4. Changes in average dissolved aluminum concentrations (determined by integration) witliin the surface mixed layer depth during the eddies lifetime. Full circle indicates Haida-00; open circle is Haida-01; full triangle indicates cruise reference stations. Solid line near bottom indicates average surface waters at Station P (50° N, 145° W; sampled September 2002) and dashed line indicates average Hectare Strait waters : 75 xiv Figure 2.5. Dissolved aluminum concentrations versus depth at the center of the eddy at 4 months. Full circle indicates Haida-00 and open circle indicates Haida-01. Data points without error bars have an error that is smaller than the symbol size. 77 Figure 2.6. Dissolved aluminum concentrations versus depth at the reference stations sampled in June 2000 (55° 44.8' N, 135° 50.2' W; solid triangles) and June 2001 (52° 45.0' N, 137° 0' W; open triangles). Data points without error bars have an error that is smaller than the symbol size 78 Figure 2.7. (a) Dissolved aluminum concentrations at (or near) a sigma-9 of 26.8 for Haida-00 (full circles), Haida-01 (open circles) and reference stations (full triangles) over 2 year sampling period. Note: low concentration for Haida-00 at 7 months may be due missing the sigma- 0 of 26.8 isopycnal, as shown in Figure 2.8 (b) where full circles represent H-00 at 4 months and empty circles represent H-00 at 7 months. Data points without error bars have an error that is smaller than the symbol size.) 79 Figure 2.8. Sea surface height anomaly plots showing the merger of a smaller, younger eddy with Haida-00 in June 2001. Plots produced by the Colorado Centre of Astrodynamic Research (CCAR) using TOPEX/POSEIDON-ERS-2 radar altimetry data. 81 Figure 2.9. Changes in depth integrated aluminum concentrations within eddy core (200-600m) during the eddies lifetime. Full circle indicates Haida-00; open circle is Haida-01; and the full triangle indicates reference stations. The 7-month value for Haida-00 is likely an underestimate due to no sample of the expected high aluminum signal at sigma-9 of 26.8 82 Figure 3.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time of sampling denoted by numbers below (or to the right) of the location symbol: 1 - June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001 Figure 3.2. Sea surface height anomaly plots showing the merger of a smaller, younger eddy with Haida-00 in June 2001. Plots produced by the Colorado Centre of Astrodynamic Research (CCAR) using TOPEX/POSEIDON-ERS-2 radar altimetry data 103 Figure 3.3. Temperature, salinity, density (represented by sigma-9) and oxygen data for different cruises, a) Haida-01, February 2001; b) Haida-01, June 2001; c) Haida-01, September 2001; d) Haida-00, September 2000; e) Haida-00, February 2001; f) Haida-00, June 2001; g) Haida-00, September 2001 105-106 Figure 3.4. Depth profiles of dissolved a) aluminum, b) cadmium, c) copper, d) manganese, and e) iron in the newly formed Haida-01 eddy, sampled in February 2001 off the coast of the Queen Charlotte Islands, British Columbia. Dissolved iron data X V supplied by W.K. Johnson, Department of Fisheries and Oceans, Canada. Data points without error bars have an error that is smaller than the symbol size. '. 107 Figure 3.5. Average dissolved concentrations of a) aluminum, b) cadmium, c) manganese, d) copper, e) phosphate, f) silicate and g) iron in the surface mixed layer of the Haida-00 (full circle) and Haida-01 (empty circle) over the sampling period. 0 months refers to February of the formation year, and age is calculated from that time. Full triangles indicate concentration of dissolved metal in the surface mixed layer of the waters surrounding, but not in direct contact, with the eddy. The dashed line indicates surface values for open ocean water, measured at Ocean Station Papa (50° N, 145° W) in September 2002. Dissolved iron data supplied by W.K. Johnson, Department of Fisheries and Oceans, Canada. Dissolved nutrient (phosphate and silicate) data provided by T. D. Peterson, University of British Columbia, Canada.... „ 109-110 Figure 3.6. Linear relationship between dissolved iron and dissolved manganese in surface mixed layer of newly formed Haida-01 eddy 119 Figure 3.7. Dissolved metal depth profiles from Haida-01 in September 2001 for dissolved Cd (full triangle), dissolved Fe (empty circle) and dissolved Cu (full circle). Winter ventilation mixed layer depth shown as dashed line. Data points without error bars have an error that is smaller than the symbol size 122 Figure 4.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time of sampling denoted by numbers below (or to the side) of the location symbol: 1 — June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001 134 Figure 4.2. Depth profiles at the center (full circle), edge (empty circle) and reference station (full triangle) for a) salinity and dissolved b) aluminum, c) cadmium, d) copper and e) manganese for June 2000, September 2000 and June 2001 sampling times. Average concentration value determined by integration plotted as dashed line, with error bars shown at 40 and 400m depths 140-141 Figure 4.3. Average core salinity from edge station (0km) to center station (~55.7km) over sampling period. 142 Figure 4.4. Average eddy core salinity (circles) and average (40 to 400m) reference station salinity (triangles) over sampling period 142 Figure 4.5. Plot of equation 4.2, used to determine the time constant T and initial salinity in Haida-00 (S,) 143 Figure 4.6. Comparison of exponential (solid curve) and linear (dashed line) fit for average eddy core salinity versus age of eddy (in months) 145 xvi Figure 4.7. Plot of SSH anomaly (from CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer) versus the average eddy core salinity (SE) 145 Figure 4.8. Plot of the volume of water exchanged with the surroundings (Vs) versus the age of the Haida-00 eddy in months 146 Figure 4.9. Comparison of predicted average eddy core dissolved metal concentrations accounting for physical mixing only (CE represented by solid line) and measured average eddy core concentrations (represented by full circles and error bars) for a) aluminum, b) manganese, c) cadmium and d) copper. 148 Figure A - l . Column set-up. 165 Figure B-l. Results of procedural blank analysis plotted as Volume of Seawater (mL) versus the dissolved concentration of a) aluminum, b) cadmium, c) copper and d) manganese in parts per billion 182 Figure C-l . Synthesis reaction for a) the chloromethylated 8-HQ and b) the adding of the chloromethylated 8-HQ to the Amberlite XAD-2 by means of a Friedel-Crafts alkylation reaction 187 Figure C-2. Plot of volume of rinse (methanol for chloromethylated 8-HQ removal; 2N Q-HNO3 for aluminum removal) versus chloromethylated 8-HQ (open square) on the left axis and aluminum (full circle) on the right axis 189 Figure C-3. Breakthrough curve for 8-HQ resin using a flow rate of 0.81mL/min and a 50ppm copper solution at a pH of 5.3 191 xvii LIST OF ABBREVIATIONS A Angstrom (lA = 0.1 nm) AA atomic absorption spectrophtotometer Al Aluminum 8-HQ 8-hydroxyquinoline CASS Coastal Atlantic Surface Seawater CCAR Colorado Centre of Astrodynamics Research Cd Cadmium C.O.D. Criterion for Detection (C.O.D. = 1.645 times the standard deviation of blank sample) CTD Conductivity, Temperature, Depth Cu Copper Da Dalton (measure of molecular mass, IDa = 1 Hydrogen atom) DDI-H2O Doubly Deionized Water (ultra pure (18MQcm)) DOM Dissolved Organic Matter EDTA Emylenediaminetetraacetic acid ERS European Remote Sensing Satellite ESA European Space Agency Fe Iron fM femtomolar (lfM = 10"15 M) GF-AAS Graphite Furnace Atomic Absorption Spectrophotometer g grams HAc Acetic Acid HC1 Hydrochloric Acid HDPE High Density Polyethylene HEPA High Efficiency Pure Air HNLC High Nutrient, Low Chlorophyll HNO3 Nitric Acid ICP-MS Inductively Coupled Plasma - Mass Spectrometry km kilometers (1km = 103 m) IDA iminodiacetatic acid LDPE Low Density Polyethylene LMF sample Laboratory Fortified Matrix Sample L.O.D. Limit of Detection (L.O.D. = 3.29 times the standard deviation of the blank + average blank signal) L.O.Q. Limit of Quantification (L.O.Q. = 10 times the standard deviation of the blank) m meters M Molarity (IM = 1 mole/litre) MQ megaohm (1MQ = 106 ohms) mA milliamperes (1mA = 10"3 amperes) M.D.L. Method Detection Limit (M.D.L. = t times the standard deviation of sample + average blank signal) mL milliliters (lmL = 10"3 liters) mol mole MLD Mn N NASA NH3/NH3OH NH 4Ac nm nM OSP pE pH pM POM ppb ppm PVC SeaWIFS Sigma-9 SSH t TOPEX TPE/FEP ULPA w/v w/w uL um umol uM Mixed Layer Depth Manganese Normality (which equals molarity multiplied by the number of protons exchanged in a reaction) National Aeronautics and Space Administration ammonia/ammonium hydroxide ammonium acetate nanometer (lnm = 10"9 m) nanomolar (InM = 10"9 M) Ocean Station Papa (50° N, 145° W) a measure of the tendency of a chemical system to exchange electrons or undergo redox reactions measure of acidity (pH = -log (activity of protons)) picomolar (lpM = 10"12 M) Particulate Organic Matter parts per billion parts per million Polyvinylchloride Sea-viewing-Wide-Field-of-view Sensor Potential density Sea Surface Height t-value used to determine confidence limits, dependent on both the confidence level percentage and the number of replicates analyzed Ocean Topography Experiment Thermoplastic Elastomer/Fluorinated Ethylene Propylene Ultra-Low Penetration Air filter weight per volume weight per weight microliter (luL = 10"6 L) micrometer, also called a micron (1pm micromole (lumole = 10"6 moles) micromolar (luM = IO 6 M) Residence time lO^m) xix ACKNOWLEDGEMENTS There have been many people throughout my graduate career who have been responsible for shaping the way I look at my research and the world in general. I would like to thank all these people for their contributions to my research and my life. In particular, I would like to thank my supervisor, Dr. Kristin Orians, and my committee members for their support and patience throughout the writing of my dissertation. In addition, I would like to thank the scientists at the Institute of Ocean Sciences for allowing me to participate in the Haida Eddy Project. I would specifically like to thank Keith Johnson and Ness Sutherland for training me a trace metal chemist at sea. Back on land, I would like to thank Maureen Soon and Burt Mueller, both knowledgeable technicians in the Department of Earth and Ocean Sciences, for all their help and training. Outside of the science realm, I would like to extend my appreciation to all my friends and family: both new and old, here and back home in Nova Scotia, you will never understand how important your support and encouragement is to me. And finally, I would like to thank Trey for understanding; this really has been one crazy year. X X My dissertation is dedicated to my Mom, Thank you for everything... 1 GENERAL INTRODUCTION 1.1. Introduction Trace metal distributions provide information about the biological, chemical and physical processes that occur in the ocean. Major processes that control reactive trace metal concentrations within the ocean are phytoplankton growth, organic re-mineralization, particle exchange, oxidation-reduction reactions, and the physical mixing and circulation of the ocean. The changes in trace metal distributions caused by these processes have been studied in laboratories and at sea. Depending on the conditions used, laboratory and field experiments can sometimes reach different conclusions. Ideally, the effect of these processes could be studied in a controlled environment, where the effects could be quantified over time in an isolated water mass. It is difficult to track water masses over time however, due to physical mixing and advection. A couple of ways of studying changes over time have been by large-scale enclosure studies and by labeling water masses with tracers, such as sulfur hexafluoride (SF6). Large-scale enclosures overcome the problem of tracking a water mass by confining it, although problems due to interactions with enclosure walls occur (Confer, 1972; Eppley et al., 1978; Dudzik et al., 1979; Chen and Kemp, 2004). Injection of a tracer such as SF 6 allows for tracking water masses. Over time, signal dilution and subduction of water masses can occur, making it difficult to study surface processes (Law et al., 1998; Watson and Ledwell, 2000). Another way to study temporal changes is by sampling along transects, where one assumes that oceanographic consistency applies (Boyle et al., 1976b), and the age of water measured farther away from sources can be estimated. This can work in upwelling systems and also river/estuary systems where tracers, such as salinity in river/estuary systems, are used as an indicator of degree of mixing. The ages can be estimated from this relative manner, if assumptions can be made about the rate of water transport and mixing, resulting in ranges of removals or inputs. An oceanographic feature that remains relatively intact for some time are mesoscale eddies that form at ocean current boundaries. These eddies "trap" water within the center of the eddy, and can transport chemically and physically distinct waters for Chapter 1: General Introduction 2 months or years, depending on the type of eddy, the location of formation and direction of travel (Olson, 1991). Until the advent of satellite altimetry, the tracking of these eddies for long periods of time was difficult since it relied on either temperature determined by satellite, a signal which could be lost due to cloud cover or summer insolation warming surface waters (Stumpf and Legeckis, 1977; Vukovich and Crissman, 1980), or satellite buoys placed within the eddy, that eventually drift out of the eddy and need to be replaced every few months (Nilsson and Cresswell, 1981; Zhurbas et al., 2004; Yelland and Crawford, 2005). Sea surface height (SSH) anomalies calculated from satellite altimetry data allows for the tracking of the eddy and in addition, to perform studies comparing other satellite information, such as chlorophyll distributions, with eddy location (Crawford et al., 2005). In 2000 and 2001, a series of cruises were undertaken to study the physical, chemical and biological processes occurring within large eddies that form off the coast of British Columbia and travel westward into the Gulf of Alaska. This project allowed for the study of processes affecting trace metal distributions as coastal water ages. In Section 1.2, a primer on trace metal analysis and distribution in ocean environments is provided. Section 1.3 focuses on eddy processes and studies, with focus on the Gulf of Alaska eddies. Section 1.4 outlines thesis objectives and the division of thesis chapters. 1.2. Metals in Seawater 1.2.1. Fractions of Trace Metals Metals in seawater can be found in the dissolved phase, bound to organic or inorganic ligands, or in the particulate phase, through precipitation and scavenging reactions or inside a mineral lattice. These two fractions have been historically separated using 0.45 pm membranes, similar to natural water analysis (Goldberg, 1952). The definition of "dissolved" to mean "all metal in the fraction smaller than 0.45 pm" has been regarded as an unsatisfactory definition since it also treats colloidal material as "dissolved" (Moore et al., 1979; Morel and Gschwend, 1987; Koike et al., 1990; Wells and Goldberg, 1991; Karlsson et al., 1994; Howell et al., 2006). Colloids can result in differences in the measured "dissolved" fraction between filter types and filtration Chapter 1: General Introduction 3 methods (i.e. vacuum versus pressure, Hall et al., 1996; Horowitz, 1997). Cross-flow and ultra filtration techniques to study the effects of colloids on trace metal speciation have shown that trace metals interact with this colloid fraction (Whitehouse et al., 1990; Moran, 1991; Bertine and VernonClark, 1996; Singhal et al., 2006). Although the interaction between metals and the colloid phase is accepted, there has yet to be a consensus reached on a newly defined "dissolved" fraction, and at this time, many researchers use the 0.45 um definition to define "total dissolved" fraction to allow for comparison to previous studies, while others have changed their definition of "total dissolved" to the trace metal fraction less than 0.22um, which still contains part of the colloidal fraction. The dissolved metal fraction can be broken down into organic and inorganic species. In oxic seawater, the major inorganic anions with which trace metals can bind include hydroxide, chloride, sulfate and carbonate. In anoxic seawater, sulfides are also important in metal inorganic speciation. Metals can also react with organic molecules, some of which are part of a larger group of organic material referred to as dissolved organic matter (DOM). A large portion of DOM (up to 80%) is made up of large organic compounds that are classified as refractory decomposition products of biological matter. They are extremely variable in structure and elemental composition making them difficult to characterize (Williams and Druffel, 1988; Abbt-Braun et al., 2003). Though they are variable in structure, they usually contain negatively charged functional groups and much larger than 103-104Da in size (Wells and Goldberg, 1991; Moran and Buesseler, 1993; Bertine and VernonClark, 1996; Guo and Santschi, 1997). The negative functional groups consists of a range of binding sites, some of which are soft donors, such as nitrogen, sulphur and phosphorous containing groups, and others which are hard donors, such as oxygen-containing carboxyl and phenolic groups (Calace and Petronio, 2004). Another portion of dissolved organic matter is smaller, and is produced by phytoplankton. These ligands are usually highly selective and can be produced to either increase or decrease the bioavailability of the selected metals (Florence and Batley, 1976; Florence et al., 1992; Xue and Sigg, 1998; Hutchins et al., 1999; Maldonado and Price, 1999; Boye and van den Berg, 2000). Chapter 1: General Introduction 4 The metal particulate fraction can be separated into organic or inorganic species. Metals can bind to negative sites of surfaces on particulate organic matter (POM), which includes phytoplankton cells, waste products from higher trophic levels or large aggregations of dissolved organic matter (Whitfield and Turner, 1987; Schlekat et al., 1998; Fein et al., 2001). Inorganic particles from sediment, dust deposition, or precipitation of metal hydroxides (such as manganese and iron) can also strip particle reactive metals out of solution (Baes Jr. and Mesmer, 1981; Balikungeri and Haerdi, 1988; Gagnon et al., 1992). An additional group of inorganic particles are calcium carbonate or silica tests (shells) that are produced by certain species of phytoplankton. These tests can react with metals directly; either through surface reactions, the substitution for calcium in the lattice structure, or they can provide a surface onto which metal precipitates can form (Moran and Moore, 1992; Gehlen et al., 2002). Metals can be exchanged between the dissolved and particle phases. The rate at which exchange occurs depends on the metal involved, the environmental conditions (such as pH, pE, or light), and the particle parameters (such as exchange capacity, surface area, or chemical composition; Stumm and Morgan, 1981). These interactions can also be controlled by phytoplankton or mediated by bacteria (Emerson et al., 1982; Diem and Stumm, 1984; Grantham et al., 1997). 1.2.2. Dissolved Trace Metals In the late 1970's the first uncontaminated measurements of dissolved transition metal concentrations were made in open ocean seawater. The values found were in the nanomolar (nM) to femtomolar (fM) range and thus considered "trace". The first analyses focused on a single element at a time (Patterson, 1974; Boyle et al., 1976b; Bruland et al., 1978b) and the concentration versus depth profiles determined were scarce due to the amount of work required to obtain them. It was found that for a specific metal the shape of open ocean depth profiles was usually consistent between oceans, although the concentrations may be different. Dissolved trace metal depth distributions can be generalized into three main categories: conservative, recycled and scavenged. These divisions are based on the main factors that control the trace metal distribution, although some metals have distributions that are a combination of the three main categories. Chapter 1: General Introduction 5 1.2.2.1. Dissolved Trace Metal Distributions Metals with conservative distributions have approximately constant dissolved concentrations throughout the water column and different ocean basins. The concentrations vary proportionally to salinity and are dependent on mixing of water masses and changes (addition/removal) in fresh water content (Table 1.1). This is a result of the low reactivity of the metal such that the sources and sinks for these metals are quite small compared to the amount contained in the ocean. These metals have a residence time greater than 105 years. This residence time is larger than the overall circulation of the oceans, which is approximately a thousand years. Residence time (t) of an element refers to the average time an element resides in the ocean, and is calculated using its total input or removal rate (Equation 1.1). Average Concentration in Ocean x Volume of Ocean ^ . T = ==; Equation 1.1 2_, Rate of input or removal per year Recycled distributions follow dissolved nutrient (nitrate, phosphate and silicate) depth profiles (Table 1.1). These profiles have low concentrations in surface water due to biological uptake by microscopic floating plants (phytoplankton) growing in the euphotic zone (surface waters that have enough light to support photosynthesis). Most metals that have a recycled profile are biologically required to some extent by phytoplankton. The plant biomass eventually sinks below the euphotic zone due to aggregation and sinking, or by being consumed and excreted by zooplankton. Once below this zone the plant biomass is broken down by one of the following means: being ingested and respired by organisms, bacterial decomposition or chemical breakdown. During this breakdown of organic matter trace metals are released into the dissolved phase. This causes an increase in concentration at depths below the euphotic zone. The residence time of recycled metals is on the order of 103-105 years. This residence time is greater than the overall circulation of the ocean. The overall circulation of the ocean, sometimes referred to as the great ocean conveyor belt, describes the path of seawater as it cools and sinks to depth in the North Atlantic, then travels south to the South Atlantic and then into the Southern Ocean. It Chapter 1: General Introduction 6 Element Type Mean Oceanic Residence Time Profile Type Conservative >10 5 Concentration • • 1 Recycled 10 3to 10 5 Concentration • Q . 01 O • Scavenged <10 3 Concentration • * 1 8 1 ( Table 1.1. Classification of dissolved trace metal depth profiles. Mean oceanic residence time given in years. The equation for calculating residence time in given in text (Equation 1.1). Chapter 1: General Introduction 7 Figure 1.1. Schematic of the 'Great Ocean Conveyor Belt' first proposed by Broecker in 1987 to describe ocean circulation. Figure adapted from Kerr, RA, SCIENCE 239: 259-260 (Jan 15 1988). Reprinted with permission from AAAS. then travels north into the Indian Ocean and the South and North Pacific, where the deep water is up welled and continues its journey back to the North Atlantic in the shallow flow (Broecker, 1987; Figure 1.1). Once the seawater sinks in the North Atlantic and begins its cycle at depth, it continues to accumulate recycled metals (and nutrients) from the waters above, so that deep waters in the North Pacific have higher concentrations of recycled metals. Scavenged distributions describe depth profiles of elements that are rapidly adsorbed onto particles or precipitate once introduced to seawater (Table 1.1). These metals tend to have very short residence times in the ocean (T < 10 years) and therefore older waters, such as the deep waters of the North Pacific, which are removed from the sources of these metals have lower concentrations of dissolved scavenged metals. Due to scavenging, the dissolved concentrations of these metals are very low compared to their crustal abundances and the depth profiles exhibit concentration maximums that indicate Chapter 1: General Introduction 8 sources. These sources include dust deposition, river input, hydrothermal vents, sediment re-suspension and reduction-oxidation reactions that bring the metal back into solution. These three generalized categories are useful in classifying trace metals and the major processes that control their distribution but some metals have more than one controlling factor and therefore the resulting dissolved depth profile may be a combination of these idealized profiles. 1.2.2.2. Trace Metal Analysis At the International Decade of Ocean Exploration (TDOE) conference in 1972 the reliability of lead analysis in seawater was questioned (Patterson, 1974). It was determined through inter-laboratory comparisons that the analysis and collection methods used to determine lead in seawater prior to that year were not clean enough, and thus the results published were probably erroneous. It was suggested other seawater metal analysis could also have problems with contamination and that cleaner techniques would be required to gain accurate values of metal concentrations in seawater. Following those recommendations, cleaner sampling and analytical techniques were developed, which lead to the discovery that metal concentrations were at least one order of magnitude lower than previously determined (Bruland et al., 1978b). Trace metal clean sampling techniques, such as the use ofTeflon™-coatedGO-Flo™ bottles (General Oceanics) and Kevlar® hydroline, developed in the late 1970's (Bruland et al., 1979) are still in use today, although methods for trace metal analysis, including concentration methods and instrumentation, do still vary by the metal studied and by different research groups. Instrumentation since the beginning of trace metal analysis in seawater has increased in sensitivity and decreased limits of detection to the point where certain trace metals in coastal samples are being detected directly by inductively coupled plasma -high resolution mass spectrometers with only a dilution step (Rodushkin and Ruth, 1997; Field et al., 1999). Open ocean measurements, with lower trace metal concentrations, still require a concentration step before analysis (Wells and Bruland, 1998; Hirata et al., 2001). Other instruments used include graphite furnace-atomic absorption spectrophotometers, voltammeters (anodic/cathodic), and flow injection methods Chapter 1: General Introduction 9 equipped with UV-Visible spectrophotometers, fluorimeters or chemiluminescence detectors (some instrumentation review articles include: van den Berg and Achterberg, 1994; Cave et al., 2000; Achterberg et al., 2001; Hill et al., 2002; Rao et al., 2005). Concentration methods vary greatly, from organic ligand extraction (Bruland et al., 1979; Sturgeon et al., 1980; Bruland et al., 1985), co-precipitation methods (Wu and Boyle, 1997; 1998), and the use of chelating resins (Sturgeon et al., 1981; Willie et al., 1983; Landing et al., 1986; Dierssen et al., 2001). One purpose of these methods is to concentrate the metals of interest. Another important purpose is to isolate the metals from the major components of seawater, alkali and alkaline earth metal salts (referred to hereafter as major salts), thus reducing the matrix effects during analysis. Organic extraction involves addition of an organic ligand to the seawater and subsequent extraction of the organic ligand-trace metal complex into an organic phase, which reduces the concentration of major salts in the analyte considerably. This method requires a large amount of sample handling, sample transfers and the addition of organic liquids, all of which can increase the probability of contamination (Bruland et al., 1985). Co-precipitation methods involve the addition of a chemical (such as a base or an insoluble organic compound) that causes a solid precipitate to form in the sample, which the metals adsorb to or react with directly (Boyle and Edmond, 1977; Akagi and Haraguchi, 1990; Ouddane et al., 1997; Wu and Boyle, 1998). Centrifuging and/or filtration are used to isolate the precipitation, which is then dissolved in some mixture of acid for analysis. One disadvantage to this procedure is that the amount of precipitate and trace metal recovery is generally not reproducible, so usually an internal standard method (i.e. isotope dilution) is required. Some trace metals only have one stable atomic mass (e.g. aluminum, manganese), and thus cannot be analyzed by this method with confidence. The use of chelating resins requires a volume of seawater to be passed slowly over the resin to allow the transition metals to bind to the resin. After the sample is passed over the resin, the resin is eluted, usually with an acid, and the concentrated sample is analyzed. This method has the advantage that it can be miniaturized, and flow injection analysis can be performed. Flow injection into a inductively coupled plasma-mass spectrometer has been used for a range of metals (Bloxham et al., 1994; Willie et Chapter 1: General Introduction 10 al., 1998; Beck et al., 2002). Additionally, flow injection instruments using ultra violet-visible light absorption, chemiluminescence, or fluorescence detection methods have been developed, allowing for at-sea determinations of metal concentrations (Chapin et al., 1991; Elrod et al., 1991; Coale et al., 1992; Obata et al., 1993; Resing and Measures, 1994). 1.2.3. Trace Metals of Interest 1.2.3.1. A luminum 1.2.3.1.1. Chemistry in Seawater Aluminum (Al) has an interesting distribution in natural environments. It has the highest abundance in the Earth's crust of any metallic element (at 8.23% by weight) but is dissolved in seawater at only nanomolar concentrations. Al is a mono-isotopic, trivalent metal that preferentially binds to hard ligands. This results in the hydrolysis of Al in seawater to form particle reactive species, Al(OH)3 and [Al(OH)4]\ Both of these species are important in seawater, and by using equilibrium calculations to determine the species distribution, a speciation change between a mainly [Al(OH)4]" dominated surface layer (at approximately 75% anionic form) to a dominating neutral form, Al(OH)3, at depth is expected (Turner et al., 1981; Orians and Bruland, 1986). Al can also be associated with the colloidal phase. Colloidal analysis suggests that 0 to 11% of dissolved Al may be bound to colloids, with less than 1% Al bound at open ocean sites, but a preference between organic or inorganic colloids has not yet been detennined (Reitmeyer etal., 1996). 1.2.3.1.2. Dissolved Depth Profde Early analyses of dissolved Al in seawater were from sites in the Mediterranean Sea (Mackenzie et al., 1978; Caschetto and Wollast, 1979). These findings suggested that dissolved Al varied with the nutrient silicate, with lower dissolved Al in surface waters (20-3 OnM) and an increase below the euphotic zone, to values of 140nM at depth. From this information, they concluded that the Al ocean cycle was similar to the silicate cycle, and dissolved Al in seawater was biologically controlled. Open ocean measurements followed, in both the North Atlantic (Hydes, 1979; 1983; Measures et al., 1984) and the Chapter 1: General Introduction 11 5000 6000 Dissolved Aluminum (nM) 10 20 30 40 O -O- -+- T p r - C -50 Figure 1.2. Dissolved Al depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 78, Orians, K. J. and Bruland, K. W., The biogeochernistry of aluminum in the Pacific Ocean, 397-410, copyright © 1986, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Geochimica et Cosmochimica Acta, 47, Hydes, D. J., Distribution of aluminum in waters of the North East Atlantic 25 N to 35 N, 967-973, copyright © 1983, with permission from Elsevier.) North Pacific (Orians and Bruland, 1985; 1986). They found lower dissolved Al concentrations and a dissolved profile that suggested Al is a scavenged element, and not a recycled element like first proposed. The average value of dissolved Al in the open ocean is approximately 1.1 nM, with values ranging from less than 0.06nM in the mid-depth North Pacific waters to 20. InM in the surface waters of the Arabian Sea, a location of high dust input (Measures and Vink, 1999). Dissolved Al depth profiles consist of a surface maximum and a mid-depth minimum supporting the conclusion that Al in the oceans behaves as a scavenged element (Figure 1.2). Increased dissolved Al concentrations below 1000m were also measured at some locations, although this increase is not a constant feature in open ocean profiles. Dissolved Al concentrations are low unless a point source, such as dust Chapter 1: General Introduction 12 deposition, river input or a sediment source is in close proximity. Dissolved Al displays a scavenged profile in most open ocean environments, with older waters, such as the deep North Pacific, having lower concentrations of dissolved Al (Orians and Bruland, 1985). The continual removal of Al as water ages and fewer sources of Al to the Pacific Ocean results in Al having the largest inter-ocean fractionation, with concentrations in the deep Pacific being 8 to 40 times lower than those at similar depths in the Atlantic (Orians and Bruland, 1985; 1986). 1.2.3.13. Sources and Removals River input has been found to be a significant source of dissolved Al in some regions, such as the North Sea (Kremling and Hydes, 1988), coastal waters of the Arabian Sea (Narvekar and Singbal, 1993) and possibly within the Panama Basin (Measures et al., 1984) but river input isn't considered a major source of dissolved Al to the open oceans. Removal of dissolved Al occurs within estuaries, as the slightly acidic river waters (pH 6 - 6.5) mix with slightly basic seawater (pH 8.2-8.3) causing Al to form particle reactive species. In addition, ocean waters on the continental shelf and slope are highly productive zones which result in high particle concentrations and therefore rapid removal of dissolved aluminum (Hydes and Liss, 1977; Maring and Duce, 1987; Walsh, 1991; Merrin, 2002). The predominant source of Al to surface waters of the open ocean is aeolian dust deposition (Maring and Duce, 1987). Although the total Al concentration wthin dust reflects average crustal abundance, the solubility of aeolian dust has been measured to range from 1.5 to 10% (Maring and Duce, 1987; Prospero et al., 1987; Chester et al., 1993). This discrepancy has been attributed to the location of the dust source, chemical modifications of dust during transport, the method of deposition and possibly interactions with phytoplankton (Chester et al., 1993; Gehlen et al., 2003). Estimates of the residence time of dissolved Al in surface waters ranged from weeks to 3.5 years, and are dependent on particle concentrations (Orians and Bruland, 1986; Maring and Duce, 1987; Jickells et al., 1994). Other factors that affect calculated residence time are estimates of dust flux and dust solubility. The residence time of dissolved aluminum in the deep North Pacific ocean, determined using vertical advection diffusion scavenging model, was calculated to Chapter 1: General Introduction 13 vary between 30 to 200 years depending on the flux of particles from overlying waters (Orians and Bruland, 1986). Removal of dissolved Al from seawater occurs at all depths and is dependent on the concentration of particles in the water (Hydes, 1979; Orians and Bruland, 1986; Li, 1991). It has also been suggested that the particle composition may play a role in the removal of Al from surface waters. Specifically, silica particles, such as diatom shells, have a high affinity for Al (Moran and Moore, 1992) and some studies found Al bound within the silica lattice, which suggested either substitution or incorporation of Al during shell formation (VanBennekom and Vandergaast, 1976; Dymond et al., 1997; Gehlen et al., 2002). 1.2.3.2. Cadmium 1.2.3.2.1. Chemistry in Seawater In seawater, dissolved cadmium (Cd) is a divalent cation. The majority of Cd in the oceans is in the dissolved phase (from 65 to 99.9%), with the maximum concentration of particulate Cd in surface waters corresponding to the chlorophyll maximum (Bruland et al., 1994). Organic complexation of Cd is dominant only in surface waters. In the North Pacific surface waters, up to 70% of the dissolved Cd has been found to be complexed to organic ligands (Bruland, 1992). The remaining 30% is expected to be bound to chloride, in either CdCh or CdCl + forms, with approximately 0.9% remaining as free hydrated Cd 2 + (Byrne et al., 1988; Bruland, 1992). The concentration of the organic ligands decreases with depth, and in water deeper than 200m 97% of the dissolved Cd should be bound to chloride, and 3% is in a free hydrated form (Byrne et al., 1988; Bruland, 1992). Similar results were found in the North Atlantic, with up to 100% of Cd in surface waters bound to organic ligands and a switch to predominately inorganic species occurring at depth (Helmers, 1994). The large percentage of Cd organic complexation in surface waters suggests that the source of the organic ligands are produced by phytoplankton, possibly produced for Cd detoxification (Lee et al., 1996; Morel and Price, 2003). Chapter 1: General Introduction 14 Dissolved Cadmium (pM) 1000 2000 £ 3000 Q . <D Q 4000 H 200 f— 400 o o o o 600 —h-800 1000 — I — 1200 5000 -A 6000 - 1 - 1 Figure 1.3. Dissolved Cd depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 47, Bruland, K. W., Oceanographic distribution of cadmium, zinc, nickel, and copper in the North Pacific, 176-198, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Deep Sea Research Part II Topical Studies in Oceanography, 40(1-2), Martin, J. H. et.al., Iron, Primary Production and Carbon Nitrogen Flux Studies During the JGOFS North-Atlantic Bloom Experiment, 115-134, copyright © 1993, with permission from Elsevier.). 1.23.2.2. Dissolved Depth Profile Cd exhibits a recycled element profile in open ocean waters (Figure 1.3). Preliminary dissolved Cd vertical distributions, measured in the North Pacific, showed very low l-2pM concentrations in open ocean surface waters that increased with depth, up to a maximum of 1.1 nM in the nutrient-rich bottom waters (Boyle et al., 1976a; Martin et al., 1976; Bruland et al., 1978a; Bruland, 1980). The surface to depth enrichment of dissolved Cd was found to be almost 1,000 fold, and is the greatest of any trace metal. In the Atlantic Ocean, similar surface values were measured, ranging from 3 to 50pM in surface waters (Danielsson et al., 1985; Landing et al., 1995; Yeats et al., 1995; Saager et al., 1997) with increasing dissolved Cd concentrations in the deep waters Chapter 1: General Introduction 15 of up to 200pM. Similar to the major nutrients, dissolved Cd is more enriched in deep waters of the North Pacific, with up to five times more dissolved Cd in the deep North Pacific compared to the North Atlantic. 1.23.23. Sources and Removals Sources of Cd to the ocean include river input and dust deposition (Kremling and Hydes, 1988). Internal processes that redistribute dissolved Cd within the ocean include remineralization of biological material below the mixed layer, and upwelling processes that bring higher concentrations of dissolved Cd to the surface waters. Cd's nutrient-like profile, which suggests biological control, was surprising considering Cd is usually considered toxic (Satarug et al., 2003). Cd is not considered to be highly particle reactive (Whitfield and Turner, 1987), although it has been suggested that a portion of dissolved Cd removal from surface waters occurs by adsorption to bacterial surfaces (Yee and Fein, 2001). It is also known to substitute for calcium in calcium carbonate shells, and has been used as a indicator of paleooceanic phosphate concentrations in both surface and deep waters (Boyle, 1988). There is also evidence that Cd can substitute for zinc (Zn) in carbonic anhydrase under Zn limitation (Price and Morel, 1990) and laboratory studies show it may also be taken up by phytoplankton when manganese, iron or carbon dioxide concentrations are at low levels (Sunda and Huntsman, 1998; Cullen et al., 1999; Sunda and Huntsman, 2000). The average concentration of Cd ranges from 1 to 2pmol kg"1 in surface waters to 1.2nmol kg"1 in deep waters. Its oceanic distribution is controlled mainly by its shallow regeneration cycle similar to the major nutrients. Residence times for Cd have been calculated on the order of 50,000 years using a global average river input (Bruland, 1980). 1.2.3.2.4. Cadmium - Phosphate Relationship The global oceanic distribution of dissolved Cd has been found to resemble the distribution of the dissolved inorganic phosphate (PO4) in both horizontal and vertical profiles (Boyle et al., 1976a; Martin et al., 1976; Bruland, 1980; Knauer and Martin, 1981; Frew and Hunter, 1992). This correlation was first discovered in late 1970's in Chapter 1: General Introduction 16 many locations within the Pacific Ocean (Boyle et al., 1976a; Martin et al., 1976; Bruland et al., 1978a). From the North Pacific data, a linear relationship with a zero-intercept between dissolved Cd and PO4 was suggested (Hester and Boyle, 1982). This relationship implied that Cd was removed by phytoplankton in a relatively constant ratio to phosphate and other micronutrients. As the number of data sets and locations studied increased, two different Cd/P04 linear relationships were observed. The division of the two relationships occurred at PO4 concentrations of approximately 1.3pM. The PO4 concentrations above 1.3pM consist mainly of data collected from Pacific, Indian and Southern Oceans and have slope of approximately 0.4 x 10" Cd/P04. The PO4 concentrations less than 1.3pM are mainly from North Atlantic Oceans and surface waters, and the linear relationship has a smaller slope of approximately 0.2 x 10'3 Cd/P04 (for reviews of cadmium-phosphate relationship see de Baar et al., 1994; Loscher et al., 1997; Cullen, 2006). Several mechanisms have been suggested to describe this so-called 'kink' in the deep-water data. Frew and Hunter, 1992 suggest a low Cd/P04 relationship in the sub-Antarctic region of the Pacific basin plays a major role in the formation of these two relationships. They suggest that the 'kink' could be a result of (1) the ventilation of low Cd/P04 sub-Antarctic water to intermediate depth by formation of Antarctic Intermediate Water or (2) the remineralization of low CCI/PO4 detritus produced in waters formed at the subtropical convergence. Frew, 1995 suggested an alternate theory in which the formation of Antarctic Bottom Water played a role. Near-surface waters close to the coast of Antarctica contain a high Cd to PO4 ratio due to interactions with shelf sediments. These waters are used in the formation of Antarctic Bottom Water, resulting in deep waters with a higher C0VPO4, and the ventilation of these waters is the cause of the kink. The ratio of CQVPO4 is found to be constant in waters deeper than 1000m, with variations within ±7% of the average Cd/P04 ratio for that region. The Cd /PO4 ratio within surface waters has been found to be consistently lower than deep waters (de Baar et al., 1994; Rutgers van der Loeff et al., 1997) and exhibits high spatial variability (Elderfield and Rickaby, 2000). The highest variability is found within areas where phytoplankton growth is limited by iron (Martin et al., 1989; Martin et al., 1990). This had led to the suggestion that Cd is preferentially removed by phytoplankton in surface Chapter 1: General Introduction 17 waters relative to PO4 (Knauer and Martin, 1981; Saager and de Baar, 1993; Loscher et al., 1998), and increased Cd uptake by iron-limited phytoplankton may be the source of the visible 'kink' (Cullen, 2006). An alternative explanation is that PO4 rernineralization occurs at shallower depths (within in the mixed layer) than Cd (Boyle et al., 1981; Boyle, 1988; de Baar etal., 1994). 1.2.33. Copper 1.233.1. Chemistry in Seawater Copper (Cu) exists in seawater as carbonato- and hydroxy-complexes, as a free hydrated ion, and in organic complexes. In surface seawater, Cu is complexed by organic ligands that decrease the bioavailable free Cu ion concentration from toxic to nutritive levels (van den Berg, 1984; Coale and Bruland, 1988; Moffett, 1995). There is evidence from field studies that these ligands are of biological origin (Coale and Bruland, 1988), and in-lab culture studies have revealed that phytoplankton can produce ligands to specifically bind Cu in response to Cu toxicity (Moffett and Brand, 1996; Leal et al., 1999; Croot et al., 2000). Within surface waters of the North Pacific, greater than 99.7% of the dissolved Cu is complexed to these strong Cu binding ligands (Coale and Bruland, 1988). Below 200m, more labile, inorganic Cu exists. At depths of 1000m, only 50 to 70% of total dissolved Cu bound to strong organic ligands. Similar results were found in surface waters of.the North Atlantic, with concentrations of the free hydrated Cu ion depending on concentrations of ligand and the total dissolved Cu concentration present (Moffett, 1995). Within surface waters, dissolved Cufll) undergoes photoreduction reactions, resulting in Cu(I) formation (Moffett and Zika, 1988). Cu(I) displays a surface maximum, contributing from 5 to 10% the total Cu within the surface mixed layer. Concentrations of Cu(I) drop rapidly with depth, to concentrations below 0.015nM at the bottom of the mixed layer and the rest of the water column (Moffett and Zika, 1988). Cu(I) distribution appears to be controlled by many factors including Cu(U) speciation, photochemically or biologically produced Cu(H) reductants, and possibly Cu(I) chelators (Moffett and Zika, 1988; Buerge-Weirich and Sulzberger, 2004). Chapter 1: General Introduction 18 Dissolved Copper (nM) 2 3 4 1000 2000 £ 3000 CL Q 4000 O °o t o • o * o o o 5000 6000 J 1 Figure 1.4. Dissolved Cu depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 47, Bruland, K. W., Oceanographic distribution of cadmium, zinc, nickel, and copper in the North Pacific, 176-198, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (from Trace Metals in Seawater, 1983, pp 395-414, Mn, Ni, Cu, Zn and Cd in the western North Atlantic, Bruland, K. W. and Franks, R. P., Plenum Press, with kind permission of Springer Science and Business Media.) 1.233.2. Dissolved Depth Profile Dissolved Cu exhibits a modified nutrient profile in open ocean waters (Figure 1.4). The first depth profiles of dissolved Cu were measured in the Pacific Ocean (Boyle et al., 1976b; Boyle et al., 1977; Bruland, 1980). The vertical distribution of dissolved Cu in the Pacific is characterized by an approximately linear increase with depth, with bottom water values as high as 5.3nmol kg"1. This steady increase below the euphotic zone is unlike most other elements involved in biological uptake/regeneration cycles, which show a mid-depth maximum in the North Pacific due to shallow regeneration. This behavior of dissolved Cu indicates that there is both a deep water removal of Cu and a source of dissolved Cu from seafloor sediments (of up to 2nmol cm" year", Boyle, 1979). Surface dissolved Cu concentrations were found to decrease from coastal values Chapter 1: General Introduction 19 of 1.2nmol kg"' off the California coast to 0.4 to 0.5nmol kg"1 in open ocean regions (Bruland, 1980). In the Atlantic Ocean, the dissolved Cu depth profiles also increased linearly with depth, although compared to the North Pacific the difference between surface and depth was not as large (Bruland and Franks, 1983; Yeats and Campbell, 1983; Kremling, 1985; Kremling and Pohl, 1989; Landing et al., 1995; Yeats et al., 1995; Saager et al., 1997). Surface values in the eastern and south Atlantic stations were found to range from 0.7nmol kg"1 to 1.3nmol kg"1, and deep waters ranging from 1.2 to 3.1nmol kg"1. Similar to other nutrients, enrichment in bottom waters is observed between the North Atlantic and North Pacific Oceans. The vertical distribution of dissolved Cu reflects the influence of biological uptake and regeneration, along with in-situ scavenging and bottom water sources, resulting in a profile that is intermediate between a nutrient and a scavenged metal. 1.2333. Sources and Removals Dissolved Cu distributions are influenced by continental sources, such as rivers (Kremling, 1985) and continental shelves (Kremling, 1983; Westerlund et al., 1986; Pohl et al., 1993). These Cu inputs are transported offshore quite far, possibly due to strong complexation by humic matter (Boyle et al., 1981). The magnitude of the Cu flux from sediments depends on the concentration of Cu in pore waters, where the highest Cu fluxes are associated with hemipelagic clays and carbonate oozes and not siliceous oozes and pelagic clays (Callender and Bowser, 1980). An aeolian source of Cu, originally suggested as a way to explain the link between Cu and lead-210 in surface waters (Boyle et al., 1977), was ruled out as a significant source of Cu to the open ocean because there is no central gyre surface water maximum (Boyle et al., 1981). Cu is a biologically required element, and surface removal of dissolved Cu is dependent on biological uptake (Boyle, 1979; Bruland, 1980; Sunda and Huntsman, 1995). Scavenging of dissolved Cu by non-biogenic particles (e.g. Mn and Fe oxyhydroxides) becomes more important near continental margins, where a decoupling of Cu from major nutrients can occur (Bruland, 1980; Sunda and Huntsman, 1995). Mid and deep water removal also occurs as a result of Cu adsorbing to the surfaces of fine particles and being transported to sediment by interactions with larger, faster settling Chapter 1: General Introduction 20 particles (Whitfield and Turner, 1987). The rate of Cu scavenging is found to be correlated with the amount of primary production in the overlying water column (Collier and Edmond, 1984). The removal half-life of Cu with respect to the deep water scavenging process is approximately 1000 years. The overall residence time of Cu relative to river/atmospheric input is calculated to be approximately 5000 years, suggesting that most of the dissolved Cu that is scavenged at depth must be re-supplied from the sediment-water interface (Boyle, 1979). 1.2.3.4. Manganese 1.2.3.4.1. Chemistry in Seawater Manganese (Mn) exists in two dominant oxidation states in seawater (Stumm and Morgan, 1981). In oxygenated seawater at a pH of 8, the thermodynamically stable form is Mn(IV), which is extremely insoluble in seawater and forms particulate oxides. The unstable reduced form Mn(U) is water-soluble and exists within seawater mainly as free hydrated Mn but also as MnCl . Dissolved Mn(II) forms weak complexes, with minimal organic complexation within coastal regions (Roitz and Bruland, 1997), although some Mn-organic complexation is found in marine systems that are characterized by high organic decomposition and low O2 concentrations (Luther et al., 1994). Some metastable Mn(III) also occurs with Mn(IV) in mixed oxidation state solids (Emerson et al., 1982; Grill, 1982; Kalhorn and Emerson, 1984). Equilibrium dissolved concentrations of Mn(II) are predicted to be on the order of pmol Mn kg"1 or less using the redox couples of Mn(II)/Mn02 and Mn(IT)/MnOOH. Measured values of dissolved Mn within seawater are on the order of nmol kg"1, and this is attributed to the slow kinetics of the Mn(II) oxidation resulting in a non-equilibrium state (Diem and Stumm, 1984). It has been suggested that no significant chemical oxidation occurs at the seawater pH (Kessick and Morgan, 1975); and that any oxidation that does occur is microbially catalyzed (Nealson and Tebo, 1980; Emerson et al., 1982; Cowen and Silver, 1984; Sunda and Huntsman, 1987). The slow oxidation results in a calculated lifetime of dissolved Mn based on this removal to be on the order of 70 years in the open ocean (Yeats and Bewers, 1985). Additionally, within surface waters reduction of Mn-oxides occurs. The photo-dissolution of these oxides was found to result Chapter 1: General Introduction 21 Dissolved Manganese (nM) 0.0 0.2 0.4 0.6 0.8 1.0 -t %-o^—oa+-Kt 1000 H 2000 H £ 3000 H Q. (U Q 4000 Q O O O O o o o o o 1.2 5000 6000 -« 1 Figure 1.5. Dissolved Mn depth profiles. The full circles represent a North Pacific station (reprinted from Earth and Planetary Science Letters, 49(1), Landing, W. M. and Bruland, K. W., Manganese in the North Pacific, 45-56, copyright © 1980, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Marine Chemistry, 61(1-2), Statham, P. J., Yeats, P. A. and Landing, W. M., Manganese in the eastern Atlantic Ocean: processes influencing deep and surface water distributions, 55-68, copyright © 1998, with permission from Elsevier). primarily from Mn reduction by H2O2, produced in seawater from the photo-reduction of O2 by dissolved organic matter (Sunda et al., 1983; Sunda and Huntsman, 1994). 1.23.4.2. Dissolved Depth Profile Mn is an element required for many biological processes, including photosynthesis (Sauer, 1980), the detoxification of oxygen products produced by aerobic respiration (Ehrlich, 1984; Ghiorse, 1984) and in the production of ATP (Ehrlich, 1984). Unlike most biologically required elements, dissolved Mn does not have a nutrient profile. Instead, Mn exhibits a scavenged element profile in the ocean (Figure 1.5). Initial measurements of dissolved Mn in the ocean were made in the Pacific Ocean (Klinkhammer and Bender, 1980; Landing and Bruland, 1980; Martin and Knauer, Chapter 1: General Introduction 22 1984; Jones and Murray, 1985; Martin et al., 1985). The depth profiles were typically dominated by external inputs leading to surface maxima and intermediate depth maxima associated with the O2 minimum. In regions influenced by active hydrothermal vents a deeper, mid-depth water maxima was also observed. Concentrations of dissolved Mn in surface waters of the North Pacific showed a decrease from coastal regions to offshore stations, with concentrations nearshore of 2 to lOnmol kg"1 decreasing to 0.6 to lnmol kg1 offshore. Slightly higher concentrations were observed vvithin the central gyre, with a range of 1 to 2nmol kg"1. Horizontal gradients were measured within the O2 minimum zone as well, with concentrations of dissolved Mn decreasing from 1.4 to 7nmol kg*1 near the continental slope to 0.5 to 0.7nmol kg"1 in open waters. Three mechanisms were proposed to account for the existence of this secondary maximum: (1) the release of soluble Mn(II) from organic matter as it is consumed; (2) the reduction of Mn (IV) oxides within the oxygen minimum as minerals re-equilibrate with the water column under low oxygen and pH conditions and (3) the reduction of Mn(IV) oxides in continental margin sediments that intersect the oxygen minimum followed by lateral transport of soluble Mn (II) into the oceans interior. Mechanisms 1 and 2 were proposed and tested by KJinkhammer and Bender, 1980; Johnson et al., 1996; and mechanism 3 was proposed by Martin et al., 1985. Johnson et al., 1996 found they could describe the secondary maximum without requiring additional inputs or over-estimating the dissolved Mn concentrations using a model based on mechanism 1 (release of Mn(H) from organic matter). A model based on mechanism 2 tended to over-estimate dissolved Mn(H) (Klinkhammer and Bender, 1980) and mechanism 3 was discounted due to sediment flux measures performed by Johnson et al., 1992. In the Atlantic Ocean, dissolved Mn depth profiles exhibit a surface enrichment, and a decrease in dissolved concentration with depth (Figure 1.5; Yeats and Bewers, 1985; Yeats et al., 1992; Saager et al., 1997; Statham et al., 1998). Dissolved Mn concentrations in surface waters decrease away from shelf waters, with maximum concentrations close to 6nM, to oceanic waters with minimum concentrations of 0.5nM. Dissolved Mn concentrations also decrease with depth, to minimum values of 0.1 to 0.5nM. In several areas, high dissolved Mn concentrations are observed (up to 0.85nM) suggesting a source from reducing sediments on the shelf and slope. Chapter 1: General Introduction 23 The average concentration of dissolved Mn in the oceans is approximately 360pmol kg"1; with open ocean surface waters having concentrations up to 3.5nmol kg"1 in the Atlantic and up to 3nmol kg"1 in the Pacific. Dissolved Mn is continually being scavenging from seawater, resulting in older waters having lower concentrations of dissolved Mn (Landing and Bruland, 1980). 1.2.3.43. Sources and Removals The main sources of dissolved Mn to coastal waters are from river runoff (Bender et al., 1977; Jones and Murray, 1985) and a dissolved Mn flux from reducing shelf sediments (Trefry and Presley, 1982; Heggie et al., 1987; Johnson et al., 1992). In addition, aeolian dust deposition contributes dissolved Mn to surface waters of the open ocean (Statham and Burton, 1986; Guieu et al., 1994). Hydrothermal input of dissolved Mn is potentially the largest single source of Mn to the worlds oceans (Weiss, 1977; Aballea et al., 1998). Concentrations of dissolved Mn in the 350°C end-member hydrothermal fluid is estimated to be on the order of lmmol kg"1. The hydrothermal Mn signal may be observed for many kilometers away from the source, before scavenging and mixing of water masses erode the signal. Removals of dissolved Mn include uptake by phytoplankton, oxidation, and scavenging to particles. Intense oxidative scavenging can remove Mn from the water column leading to decreased concentrations with depth and age of water (Landing and Bruland, 1980). Several mechanisms have been proposed for the scavenging of dissolved Mn(U) onto particles, including microbial mediation (Trefry and Presley, 1982; Tebo and Emerson, 1986; Sunda and Huntsman, 1987); and/or passive scavenging onto the surface of biogenic or organically coated particles (Martin and Knauer, 1983). Oxidation reactions and scavenging of Mnfll) become more efficient within deeper waters, resulting in a larger proportion (up to 30%, Yeats and Bewers, 1985) of total Mn(II) at depth to be associated with the particulate phase and the residence time within the deep waters to be approximately 50 years (Weiss, 1977). The average residence time of Mn in the ocean, calculated using the ocean standing stock and measured vertical fluxes is approximately 60 years (Martin and Knauer, 1980), although residence time estimates can vary, especially in surface waters, Chapter 1: General Introduction 24 and depend on method of calculation. Calculated surface water residence times for dissolved Mn vary from 5 to 10 years depending on the estimated dust input, the assumed solubility and average surface concentrations (Martin and Knauer, 1984; Statham and Burton, 1986; Jickells et al., 1994). Landing and Bruland, 1980 calculated a scavenging residence time for dissolved Mn in the North Pacific to range from 3 to 74 years depending on particle concentration, but based on horizontal mixing in the surface mixed layer, they found that Mn residence times varied from 0.4 years (nearshore) to 19 years (1000 km offshore). 1.2.4. Trace Metals as Iron Tracers 1.2.4.1. Iron Biogeochemistry The biogeochemistry of iron (Fe) in seawater has been the subject of many studies (such as Bruland et al., 1991; Geider and Laroche, 1994; Hutchins, 1995; Wells et al., 1995). The oceanic distribution of Fe is similar to other major nutrients, with low dissolved concentrations in surface waters and a rapid increase at the nutricline, where biological material is remineralized. One major difference between dissolved Fe distributions and the major nutrient distributions is that Fe does not show inter-ocean fractionation, as is characteristic of major nutrients (Figure 1.6; Martin et al., 1993). This lack of inter-ocean fractionation occurs because in addition to biological uptake and release, other factors play a role in controlling the distribution of dissolved Fe in the world's oceans (Johnson et al., 1997). Fe, in addition to being an important micronutrient, is a scavenged metal. In oxic seawater, thermodynamics predict that the major inorganic speciation of Fe should be Fe(HT), which forms oxides, resulting in a decrease in dissolved Fe. This removal reduces the bioavailability of Fe, since studies indicate that only certain dissolved Fe species are available for biological uptake (Hudson and Morel, 1990; Hutchins et al., 1999; Maldonado and Price, 1999). Concentrations of dissolved Fe in surface waters are higher than expected by Fe-oxide solubility alone, and this is attributed to the large amount of organic ligands that bind Fe strongly (Rue and Bruland, 1995; van den Berg, 1995; Croot and Johansson, 2000) and photo-reduction reactions that occur in surface waters (Wells and Mayer, 1991; Miller et al., 1995). Chapter 1: General Introduction 25 0.0 1000 -4 2000 £ 3000 CL Q 4000 -I Dissolved Iron (nM) 0.2 0.4 0.6 0.8 (9 •• ^ O +-o9 o o 5000 H 6000 -J 1 Figure 1.6. Dissolved Fe depth profiles. The full circles represent a North Pacific station (reprinted from Deep Sea Research Part A Oceanographic Research Papers 36(5), Martin, J. H. et al., VERTEX: phytoplankton/iron studies in the Gulf of Alaska, 649-680, copyright © 1989, with permission from Elsevier) and the empty circles a North Atlantic station (reprinted from Deep Sea Research Part II Topical Studies in Oceanography, 40(1-2), Martin, J. H. et al., Iron, Primary Production and Carbon Nitrogen Flux Studies During the JGOFS North-Atlantic Bloom Experiment, 115-134, copyright © 1993, with permission from Elsevier). The combination of biological and chemical controls on dissolved Fe concentrations in the surface ocean make it difficult to determine the relative importance of these different removal mechanisms from surface waters. Models of dissolved Fe controls at depth suggest that organic complexation plays a role in the apparent Fe(lJT) solubility in deep waters, with high concentrations of weak organic ligands causing dissolved Fe to be greater than predicted by scavenging rates alone (Johnson et al., 1997). Models that include surface water detenriinations require a combination of factors, such as scavenging rates, biological uptake and organic complexation to model the system (Weber etal., 2005). Chapter 1: General Introduction 26 The quick removal of Fe from surface waters, coupled with low input of Fe, result in regions of the ocean being Fe-limited. Inputs of Fe to the surface ocean consist of river/coastal sources; upwelling of deeper waters from either below the ferricline or waters that come in contact with reducing shelf sediments (Chase et al., 2005); and dust deposition (Measures and Vink, 1999; Bonnet and Guieu, 2004). 1.2.4.2. Chemical Tracers and Their Ability to Trace Iron Seawater carries signatures of dissolved chemical tracers, and the concentration of these tracers can vary greatly for different water masses and at different times (see, e.g., Broecker and Peng, 1982; Libes, 1992; Poole and Tomczak, 1999). Chemical tracers can be any chemical compound, element or isotope that is dissolved in seawater (England and Maier-Reimer, 2001). With the use of tracers, detailed information on the movement of water masses and biogeochemical cycles can be obtained. Trace metals that have non-conservative behavior and short residence times are considered to have the greatest potential as tracers of physical processes, such as mixing and circulation in the ocean (Burton and Statham, 1988). An example of this type of trace metal is dissolved Al, which has been used as a tracer of water masses both near shore and offshore (Measures and Edmond, 1988; Measures, 1995; Hall and Measures, 1998). In addition to physical mixing processes, trace metals can give information on biogeochemical processes, including supply and dissolution of dust, fluxes from anoxic sediment, scavenging rates and oxidation-reduction reactions (Weiss, 1977; Burton and Statham, 1988; Coale et al., 1991; Measures and Vink, 2000; Measures et al., 2005). Tracing the Fe biogeochemical cycle requires knowledge of its sources and removals. External inputs of Fe to the ocean include river input, remobilization from shelf and slope sediments and aeolian dust deposition (Croot and Hunter, 1998; Johnson et al., 1999). Internal inputs of dissolved Fe include phytoplankton remineralization and reduction of iron oxides in surface waters (Martin and Gordon, 1988; Wells and Mayer, 1991; Voelker and Sedlak, 1995; Voelker et al., 1997). Removals of Fe include uptake by phytoplankton, oxidation reactions and scavenging onto particle surfaces (King et al., 1995; Wells et al., 1995; Johnson et al., 1997; Kuma et al., 2003). The complex Chapter 1: General Introduction 27 biogeochemistry of Fe can be studied by looking at a number of different tracer metals that have better defined major controls. Dissolved A l in the open ocean is rapidly scavenged (Orians and Bruland, 1986) and distributions of A l exhibiting high dissolved concentrations indicate A l sources. A l has a dust source similar to Fe but since A l is not used significantly in biological production, the input signal remains in surface waters for a longer time (Measures and Vink, 2000). For this reason, dissolved A l surface distributions have been used in many studies to predict the quantity of dust input, by using knowledge of dust solubility. In addition, dissolved A l has been used as a proxy for Fe deposition for dust sources in models (Measures and Vink, 2000; Vink and Measures, 2001; Measures et al., 2005). Similar to Fe, A l is a scavenged metal and its scavenging rates are proportional to particle concentration (Orians and Bruland, 1986). Dissolved Mn, although a biologically required element has a distribution that exhibits its sources and is controlled mainly by its oxidation-reduction chemistry. Mn and Fe undergo similar oxidation-reduction reactions, although the rates of Mn oxidation are found to be slower (Stumm and Morgan, 1996; Luther, 2005). Similar redox chemistries also results in Mn and Fe having a similar continental shelf and slope sediment source (Chase et al., 2005). Dissolved Cd and Cu have recycled distributions, with Cu's dissolved profile modified by rapid scavenging. Cd is taken up by phytoplankton in surface waters and is regenerated at depth, similar to Fe but without a significant amount of particle scavenging. Cd can be used to trace coastal upwelling and deep winter ventilation (Shen et al., 1987; van Geen and Husby, 1996). In addition, new studies suggest that the cadmium-phosphate ratio may supply information on iron limitation (Cullen, 2006). Cu can be used as a tracer that has similar controls to iron, such as biological uptake and scavenging. Similar to Cd, an increase in biological uptake of Cu may indicate a limitation of iron. Some lab experiments have shown that copper is used by some phytoplankton to chemically reduce Fe(III) under Fe stress (Peers et al., 2005; Maldonado et al., 2006) and that some phytoplankton rely more on Photosystem I when under Fe-stress, which has a higher Cu requirement (Peers and Price, 2006). Chapter 1: General Introduction 28 1.3. Mesoscale Eddies 1.3.1. Introduction The term "eddy" has been used by physical oceanographers to describe a class of variable turbulent flows that includes the meandering of currents, semi-attached rings, separated rings, deep advective vortices, shallow lens vortices, planetary and topographic waves (Robinson, 1983). These variable flows can exist on timescales from weeks to months, and have spatial scales from tens to hundreds of kilometers. Eddies exist almost everywhere they are looked for, but their distribution is heterogeneous, intermittent and eventful. Mesoscale eddies exist within the 10 to 100 km spatial scale and are responsible for the distribution of most of the turbulent kinetic energy within this scale, with only the strong eastern boundary currents having comparable kinetic energy (Wyrtki et al., 1976). These mesoscale eddies possess excess energy compared to background, and are characterized by rotational speeds greater than the long-term average flow (Robinson and Leslie, 1985). The first measurements of mesoscale eddies were found in long-term current measurements made by scientists in the former Union of the Soviet Socialist Republics (U.S.S.R.). The following references were reviewed in English in Kamenkovich et al., 1986, but are referenced by the original authors. Shtokman and Ivanovskii, 1937 first reported anomalous current measurements in the Caspian Sea. Following this study, other measurements in the Black Sea (Ozmidov, 1962), the North Atlantic (Ozmidov and Yampol'skii, 1965) and the Arabian Sea (Shtokman et al., 1969) confirmed the ubiquitous nature of these rotating mesoscale features. From these studies, more detailed investigations on mesoscale eddies in the open ocean were performed, such as Polygon-67, Polygon-70 and MODE, (Brekhovskikh et al., 1971a; Brekhovskikh et al., 1971b; Kamenkovich et al., 1986; Koshlyakov, 1986). These investigations increased the knowledge about eddy flow fields and the physical characteristics of mesoscale eddies. They also determined that these mesoscale variable flows have a large impact on turbulent mixing and energy transported within the ocean. In addition to the physical importance of these mesoscale eddies, it was apparent that these eddies can also transport, trap and disperse nutrients, trace metals, organic compounds, organic and inorganic particulate matter, and phytoplankton that could Chapter 1: General Introduction 29 influence the biological, chemical and geological processes vvithin the ocean areas affected by these eddies (Robinson, 1983). Tracking of mesoscale eddies has been difficult due to technological, logistical and theoretical challenges (Gargett, 1982; Matear and Wong, 1997). Some of these problems have been overcome recently with satellite technology and mooring arrays. Many studies have focused on the role eddies play in nutrient transport and biological production within the ocean on both spatial and temporal scales (for example: McGillicuddy and Robinson, 1997; Oschlies and Garcon, 1998; Siegel et al., 1999; Garcon et al., 2001; Martin and Richards, 2001; Woodward and Rees, 2001; Fernandez et al., 2005). Only a few studies have focused on trace metal distributions and transport within eddies. One study measured particulate Al distributions within a coastal eddy that formed off the coast of Taiwan during the summer months (Hsu et al., 1998). They found that river borne particulate Al was concentrated within the center of the eddy, and this focusing of terrigenous particles lead to the eddy acting as a barrier to offshore transport. Another study found that eddies formed by the Gulf Stream aided in the transport of particulate Mn offshore by means of'streamer' currents formed around the eddy (Joyce et al., 1992). Measurements of dissolved metals within eddies are rare, and are usually associated with transects that happen to traverse an eddy (Saito and Moffett, 2002). Gd distributions were measured within an eddy in the East China Sea (Hsu et al., 2003). They found that both dissolved and particulate Cd was concentrated near the eddy center, with high dissolved and particulate Cd concentrations found in near-bottom water of the eddy. They concluded that the eddy served as an important transport mechanism for nutrients and Cd from the coast to the sea. Mesoscale eddies are known to be a ubiquitous feature within the oceans so there is interest in how eddies affect the biogeochemical cycles and biological production, on both short and long time scales. The role of eddies in the global climate is still not understood (Berloff et al., 2002; Simmons and Nof, 2002; Gordon, 2003), although information on eddy activity derived from satellite images suggest that eddy evolution may be related to climatic events, such as El Nino, and may play a role in climatic control and oceanic climate feedbacks (Mysak, 1985; Melsom et al., 1999). Figure 1.7. Schematic o f eddy circulation in the Northern Hemisphere (plan view) with a) clockwise flow around anti-cyclonic eddies (solid arrow) which results in build-up o f water in the centre o f the eddy due to Coriolis deflection (dashed arrows); b) counter-clockwise flow around cyclonic eddies (solid arrow) which results in deficit o f water in centre o f eddy (dashed arrows). 1.3.2. Eddy Background 1.3.2.1. Classification Mesoscale eddies can be classified as either anti-cyclonic (clockwise in the Northern Hemisphere) or cyclonic (counterclockwise in the Northern Hemisphere), based on the direction of rotation (Figure 1.7). A deflection o f the rotating current to the right in the Northern Hemisphere, due to the Coriolis effect and pressure gradient, causes a build up o f water in the center o f anti-cyclonic eddies, and a deficit o f water in the center o f cyclonic eddies. This build-up o f water in the center of anti-cyclonic eddies result in a downwelling in the center of the eddy to balance the Coriolis force and pressure gradients that direct the water toward the center o f the anti-cyclonic eddy; the opposite is true for cyclonic eddies (Joyce et al., 1981; Joyce et al., 1984). Due to the downwelling in anti-cyclonic eddies, a depression in isopycnals is observed (Figure 1.8a). Chapter 1: General Introduction 31 ~~ Sea Surface Height Anomaly I Isopycnal Depression b Sea Surface Height Anomaly Rebound Figure 1.8. Schematic showing the side view of an anti-cyclonic eddy, a) shows the depression of isopycnals caused by build-up of water in the centre of eddy due to eddy circulation, b) shows the rebounding of isopycnals due to frictional decay as the eddy spins down. 1.3.2.2. Eddy Formation and Propagation Eddies can form at strong boundary currents (such as the Gulf Stream and Kuroshiro Currents; Kamenkovich, 1986a). They form when a strong current first meanders and then resumes its path, trapping water on the opposite side of the current (ocean water on the coastal side of the current or vice versa). This results in the formation of a 'ring', with the water in the center of the eddy being surrounded by an annulus of the current water. Weaker boundary currents can also form eddies, although they are usually not as intense as the western boundary current eddies (Thorpe, 1998), and are usually formed by baroclinic instabilities caused by topographical or geographical features (Owen, 1980). Other causes of eddy formation include direct wind forcing (Bernstein and White, 1974; Thomson and Gower, 1998), tidal rectification (Thomson and Wilson, Chapter 1: General Introduction 32 1987), or by changes in bottom topography (Huppert and Bryan, 1976; Kamenkovich, 1986b; Cenedese and Whitehead, 2000; Nof et al., 2002). Once formed, mesoscale eddies travel westward at speeds of 1 to 5 km day"1. This westward motion occurs for both anti-cyclonic and cyclonic eddies and is due to the influence of latitude (P-effect) on the Coriolis parameter (Nof, 1981; Cushman-Roisin et al., 1990). Latitudinal differences in the Coriolis parameter, which is a measure of planetary rotation as a function of latitude, result in a gradient of vorticity between the equator and the poles which leads to the westward propagation of eddies. The rate at which eddies travel westward is dependent on their size and potential energy (Shapiro, 1986; Cushman-Roisin et al., 1990). In special cases, theory predicts that eastward drift may occur, but that requires joint vortices where one eddy is 'stacked' on top of another eddy (Nof, 1985). Due to the westward propagation of mesoscale eddies, eddies which form at the eastern boundary of an ocean travel away from the coast. Eddies formed in the Bay of Biscay (Pingree and Lecann, 1992), off Mexico (Lukas and Santiago-Mandujano, 2001) and in the Gulf of Alaska (Whitney and Robert, 2002) all transport coastal water offshore. So although eastern boundary current eddies may not be as intense as western boundary current eddies, they exist longer (Joyce et al., 1984) and also transport coastal water, rich in nutrients and some trace metals, offshore against the prevailing currents. As the eddy ages, frictional forces result in the loss of energy within the eddy (Molinari, 1970; Franks et al., 1986; Okada and Sugimori, 1986; Fukumori, 1992). This loss in energy results in isopycnal rebound, thus decreasing the difference in density at depth between waters within and outside the eddy (Figure 1.8b). This decrease results in greater horizontal mixing, with leakage of coastal waters from the eddy and input of oceanic waters from surroundings along isopycnals (Flierl and Mied, 1985). Eventually, this mixing and frictional decay results in the eddy disappearance. This decay can take from months to years, depending on the location of eddy formation and the amount of energy within the newly formed eddy (Flierl and Mied, 1985). Chapter 1: General Introduction 33 1.3.23. Eddies in the Gulf of Alaska The Gulf of Alaska is part of the Northeastern Pacific Ocean, and is usually defined as the region between the Alaska Peninsula and the Alexander Archipelago. The Gulf of Alaska has long been noted as an area of mesoscale eddy activity, with eddies being detected by anomalous salinity and temperature measurements in hydrographic data (Tully et al., 1960; Tabata, 1982); anti-cyclonic drifter tracks (Kirwan Jr. et al., 1978) and within physical models of the region (Melsom et al., 1999). The first in-depth study by Tabata, 1982 focused on an eddy formed off the coast near Sitka, Alaska. These eddies, named Sitka after their place of origin, were found to occur in the same location annually, have a diameter of 200 to 300km, and were anti-cyclonic in nature. Tabata suggested they survive for at least 6 months, but due to a lack of adequate spatial and temporal coverage, conclusions on the generation, maintenance and dissipation of the eddy were not possible at that time. In September 1998, abnormal temperature depth profiles were detected at stations 600km west of Vancouver Island, along the frequently sampled Line-P (Crawford and Whitney, 1999). These shipboard observations combined with satellite SSH anomaly imagery led to the discovery of a spawning site for these mesoscale anti-cyclonic eddies at the southern tip of the Queen Charlotte Islands, British Columbia (Figure 1.9). These large, anti-cyclonic eddies were given the name Haida after the First Nations name for the islands, Haida Gwaii, and were defined as anti-cyclonic vortices that are generated south of 54.5°N along the coast of the Queen Charlotte Islands (Crawford, 2002). These eddies usually form at Cape Saint James in the winter months, and the eddy formation is associated with the buoyant plumes formed by the average advective flow of warmer, fresher coastal waters around the cape (Di Lorenzo et al., 2005). By February of their formation year, these eddies are visible in SSH anomaly data from satellites. Depending on the year, these eddies track either northwest, west or southwest and can persist for 1 to 3 years. Larger eddies with higher SSH anomalies form in El Nino years, suggesting the formation may be a result of a feedback mechanism to redistribute energy and heat, brought on by changes in climate conditions (Mysak, 1985; Melsom et al., 1999). The Haida eddies generally have a diameter of 150 - 300 km, a core depth of 500-600m at the center (core determined by isohaline of 33.9) and can transport between 3000 to 6000km3 Chapter 1: General Introduction 34 1SQT/W 145TW 140"W 135"W 13Q-W 125TIV 120"W -30 -25 -20 -15 - 1 0 - 5 0 5 10 15 20 25 30 Figure 1.9. Radar satellite altimetry contours showing the presence of a Haida eddy (dark spot at approximately 53°N, 136°W) to the west of the Queen Charlotte Islands on June 18, 2000. Height anomalies of ± 5cm indicate eddy locations. Solid contour lines indicate SSH anomalies > 0, dashed contour lines indicate SSH anomalies < 0. Image provided by the Colorado Center for Astrodynamics Research (CC AR) online at http://argo.colorado.edu/~realtime/welcome/ of coastal water offshore (Crawford, 2002; Whitney and Robert, 2002). They travel at speeds of up to 2cm/sec and therefore during their existence these eddies can travel as far west as Station Papa (145°W), as far north as 55°N or as far south as 46°N (Onishi et al., 2000; Whitney and Robert, 2002; Johnson et al., 2005). Due to the quantity of coastal water transport, the length of time they persist, the size of open ocean with which they can interact and their relationship with climatic changes, a 2-year study on these eddies was conducted. 1.3.3. Haida Eddy Study The Haida eddies were the focus of a large study, initiated by the Institute of Ocean Sciences (Department of Fisheries and Oceans, Canada), to determine the quantity Chapter 1: General Introduction 35 of coastal water transported and the effect these large eddies have on the Eastern North Pacific Ocean (Miller et al., 2005). This study was motivated by the reoccurring nature of Haida eddies in the Gulf of Alaska and the lack of information about their biological and chemical properties, and their impact on the physics, chemistry and biology of the region. Between February 2000 and September 2001, the major characteristics of these large anti-cyclonic eddies were studied on six separate cruises. This large study was a collaboration between scientists from the Institute of Ocean Sciences, the University of British Columbia, the University of Victoria, the Pacific Biological Station (Nanaimo, BC), and the University of Southampton (Southampton, U.K.). Transport of heat and freshwater into the Gulf of Alaska (W.R. Crawford), current structure (D.R. Yelland and W.R. Crawford), changes in the carbon system (M. Chierici and L.A. Miller), plankton distributions and primary productivity (D.L. Mackas, D.R. Yelland, M. Tsurumi, M. Galbraith, S.D. Batten, and T.D. Peterson), nutrient changes (T.D. Peterson, P.J. Harrison and F.A. Whitney), changes in iron (W.K. Johnson, L.A. Miller, N.E. Sutherland, and C.S. Wong), dissolved zinc speciation (M.C. Lohan and P.J. Statham) and other trace metal distributions (this thesis) were investigated simultaneously to give an overall picture of the changes that occur during the Haida eddy lifetime. Results from this study have shown that these eddies transport large amounts of heat and fresh water (Crawford, 2005), and that the core of the eddy remains chemically distinct from surrounding waters in terms of nutrients (Peterson et al., 2005) and iron content (Johnson et al., 2005) for at least 2 years. In 2005, a special edition of journal Deep Sea Research Part IT. Topical Studies in Oceanography was dedicated to this study: Haida Eddies: Mesoscale Transport in the Northeast Pacific Volume 52, Numbers 7-8, 2005. 1.4. Thesis Objectives and Thesis Outline The objectives of this thesis were to 1) use the semi-isolated body of water contained in the mesoscale, anti-cyclonic Haida eddy as a natural laboratory to study the changes in trace metal distributions as coastal waters age and to determine if these mesoscale eddies were a source of dissolved trace metals to the Gulf of Alaska; and 2) Chapter 1: General Introduction 36 use a selection of trace metals to study the processes controlling the changes in dissolved iron concentrations, with focus a on surface water distributions. This thesis is organized into 5 chapters, with chapters 2 to 4 written in manuscript form, using the format of the Journal of Marine Chemistry. Chapter 2 focuses on the changes in dissolved aluminum within the Haida eddy over time, with emphasis on deep-water transport and rates of removal. 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Water circulation and characteristics of currents of different scales in the upper layer of the Black Sea from drifter data. Oceanology, 44(1): 30-43. 66 CHAPTER 2: DISSOLVED ALUMINUM IN MESOSCALE ANTICVCLONIC EDDIES IN THE GULF OF ALASKA 2.1. Introduction Aluminum has a strong preference to be bound to hydroxides, and is readily scavenged by sinking particles in seawater (Turner et al., 1981; Orians and Bruland, 1985). This preference to be in the particulate phase results in aluminum having one of the shortest residence times in the ocean; 3-6.5 years in surface waters (Orians and Bruland, 1986; Jickells et al., 1994; Jickells and Spokes, 2001) and 150-200 years in North Pacific deep water (Orians and Bruland, 1986). This short residence time, compared to ocean circulation, results in aluminum having the largest inter-ocean fractionation, with concentrations in the deep water of the North Pacific being up to 40 times lower than similar depths in the North Atlantic Ocean (Orians and Bruland, 1985). Since duminum remains in the dissolved phase for a relatively short time, the distribution of dissolved aluminum in seawater reflects its sources. Sources of dissolved aluminum to the ocean include rivers, sediment and atmospheric dust. Fluvial input has been suggested to be an important source of dissolved aluminum in coastal regions (Hydes and Liss, 1977a; Measures et al., 1984; Morris et al., 1986; Kremling and Hydes, 1988; Narvekar and Singbal, 1993). In addition, release of aluminum from sediments on the continental shelf and slope can also contribute to higher dissolved aluminum in coastal regions (Hydes, 1977; Orians and Bruland, 1986; Moran and Moore, 1991; Hydes and Kremling, 1993; van Beusekom et al., 1997). Ocean waters on the continental shelf and slope are highly productive zones which results in the removal of dissolved aluminum before coastal waters are advected offshore (Hydes and Liss, 1977b; Maring and Duce, 1987; Walsh, 1991; Yeats et al., 1992). This had lead to the acceptance that the major source of aluminum to the open oceans is dust deposition (Hydes, 1979; 1983; Measures et al., 1984; Orians and Bruland, 1986; Measures and Vink, 2000). Concentrations of dissolved aluminum in surface waters have been used to predict the average amount of dust that has deposited in the Arabian Sea (Measures and Vink, 2000), the South Atlantic (Vink and Measures, 2001), and most recently the Western North Pacific Ocean (Measures et al., 2005). Surface measurements of dissolved Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 67 duminum have also been included in models to predict the amount of dust flux that has dissolved in the oceans (Measures and Vink, 2000), and from these calculations the amount of iron flux to the world's oceans. Iron is an important micronutrient and, like aluminum, it is particle reactive. Quantification of the amount of iron being delivered to the worlds oceans is important to global carbon models; especially in High Nutrient Low Chlorophyll (HNLC) regions where phytoplankton growth is known to be limited by iron (Martin and Fitzwater, 1988; Martin and Gordon, 1988; Coale et al., 1996; Boyd, 2002). One area known to be a HNLC region is the northeast subarctic Pacific Ocean (Martin and Fitzwater, 1988). In the North Pacific, concentrations of dissolved aluminum found in the surface waters are low, signifying the low flux of dust into the area (Measures et al., 2005), although dissolved aluminum measurements in the Gulf of Alaska are sparse (Orians and Bruland, 1988; Gehlen et al., 2003). Another possible source of dissolved aluminum to the eastern North Pacific and Gulf of Alaska is mesoscale anticyclonic eddies. These large eddies were first discovered as anomalous anticyclonic drogue drifter tracks by Kirwan Jr. et al., 1978 and were described by Tabata, 1982. With the advent of satellite altimetry, it has been discovered that these mesoscale anticyclonic eddies are a ubiquitous feature within the Gulf of Alaska, with large eddies forming every winter at different sites on the eastern coast of the Pacific. One site of formation is off the coast of the Queen Charlotte Islands (Haida Gwaii) in British Columbia, Canada. This group of eddies are referred to as Haida eddies, after their place of origin. They form by the merging of several smaller eddies at the southern tip of the Queen Charlotte Islands (Di Lorenzo et al., 2005). The fully formed eddy is usually discernable with sea surface height (SSH) anomaly measurements from satellite altimetry data by February of the year of formation. They have diameters of 150 to 300 km, SSH anomalies of up to 30cm and can transport between 3000 and 6000 km3 of coastal water offshore annually (Whitney and Robert, 2002). They track westward into the North Pacific with speeds of 2 cm/s (Crawford and Whitney, 1999). Depending on their size, they have lifetimes of up to 3 years and have been found as far west as 145° W (Okkonen et al., 2003). Due to the volume of coastal water they transport and the speed in which they travel, these eddies may transport dissolved aluminum into the Gulf of Alaska before it is removed from the dissolved phase by scavenging processes. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 68 The Haida eddies were the focus of a large study, initiated by the Institute of Ocean Sciences (Department of Fisheries and Oceans, Canada), to determine the quantity and quality of coastal water transported and the effect these large eddies have on the Eastern North Pacific Ocean (Miller et al., 2005). Results from this study have shown that these eddies transport large amounts of heat and fresh water (Crawford, 2005), and that the core of the eddy remains chemically distinct from surrounding waters in terms of nutrients (Peterson et al., 2005) and iron content (Johnson et al., 2005), for at least two years. The amount of iron transported within the eddy core (200-600m) was of a similar magnitude to the iron calculated to deposit in this region yearly from atmospheric sources (Johnson et al., 2005). In this chapter the distribution of dissolved aluminum within two Haida eddies is presented. The changes in dissolved aluminum concentrations as the eddy ages are described, and comparisons to the surrounding Gulf of Alaska waters are made. In addition, evidence is presented to suggest these eddies may be a significant source of dissolved aluminum to the Gulf of Alaska. 2.2. Methods 2.2.1. Trace Metal Sampling Sampling was performed over a 15-month period, from June 2000 to September 2001, in conjunction with the Institute of Ocean Sciences, Department of Fisheries and Oceans, Canada. The Haida eddies were first located by sea surface height anomaly images determined from TOPEX/Poseidon and ERS-2 altimetry data supplied by the Colorado Centre of Astrodynamics Research (CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer). Once in the region of the eddy, CTD profiles were performed along a transect of the eddy and the "center" and "edge" stations were determined. The center of the eddy was selected at the site of maximum downward isotherms (Whitney and Robert, 2002; Yelland and Crawford, 2005) and the edge station was selected as the site with the greatest slope of isopycnals between 200 and 500m and the swiftest currents (Yelland and Crawford, 2005). Another station, selected at a distance away from the eddy so as to not to be affected by eddy circulation, was also sampled during each cruise to supply information about waters surrounding the eddy. The Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 6 9 135 Longitude, W Figure 2.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time of sampling denoted by numbers below (or to the side) o f the location symbol: 1 - June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001. location of the station, referred to in this text as a reference station, was different from one cruise to another. A n open ocean station (designated as Station P, at 50° N , 145° W) and Hecate Strait (MT08 and MT10) data, collected i n September 2002, w i l l also be presented in this paper for comparison. A l l station locations are shown in Figure 2.1. Trace metal depth profiles, down to depths o f 1000m, were collected at the center and reference stations. A l l handling o f surface samples was performed within an on-deck P V C ultra-low penetration air filter ( U L P A ) clean hood. Surface samples (10, 25 and 40m) were collected using an air-driven double bellows Teflon® pump (Asti) and a Teflon® sampling tube. Surface samples were pumped through a 0.22um Opticap™ cartridge filter, and collected within the on-deck clean hood. Samples from 75m depth and deeper were collected using clean 10-, 12- or 30-L GO-FLO® bottles (Teflon®-lined, General Oceanics) attached to a Kevlar®-line and triggered using solid Teflon® messengers (for specifics, see Johnson et al., 2005). Samples collected using the G O -FLO® bottles were filtered using a 0.22um Opt icap™ cartridge filter that was connected Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 70 to the GO-FLO® bottle spigot. The filtered seawater was collected in acid-cleaned 500mL LDPE bottles and acidified within the on-deck clean hood to a pH < 2 using 6N Q-HC1 and stored until analysis. An exception to this sampling procedure was the June 2000 samples. They were collected in acid-washed 125mL high-density polyethylene (HDPE) bottles in triplicate and frozen. On shore, the samples were defrosted and filtered through an acid-washed 0.22um polycarbonate filter (45mm diameter, AMD Manufacturing Inc.) by suction filtration inside a Class 100 Laminar flow hood. Approximately 375mL of filtrate was combined in acid-cleaned 500mL low-density polyethylene (LDPE) bottles and acidified to pH < 2 using 6N quartz distilled hydrochloric acid (Q-HC1, Seastar Baseline®). Conductivity, temperature and depth measurements were collected at each station using a Seabird 91 lplus CTD mounted on a 24-bottle rosette frame. Sigma-0 values were calculated from CTD data. 2.2.2. Dissolved Aluminum Analysis Seawater samples were pH adjusted to 7.0 ±0.1 using concentrated high-purity ammonium hydroxide (Q-NH3, Seastar Baseline®) and acetic acid (Q-HAc, Seastar Baseline®). The pH-adjusted seawater was dripped through 2mL of Chelex® 100 using a flow rate of 0.80 ± 0.02mL/min. The column was then rinsed with 6mL of 0.3M Q-NH4AC buffer (pH of 7) and 4mL of pH-adjusted high-purity, deionized water (18MQ cm, Millipore Milli-Q, Bedford, MA, USA). The concentrated metals were then eluted using lOmL of 2N quartz distilled nitric acid (Q-HNO3, Seastar Baseline®). The eluent was concentrated again by evaporation, and brought up in 4mL of 1% Q-HNO3. The column recovery for aluminum using for the concentration method was 110 ± 13% (n = 16). The concentrated eluent was analyzed on a Varian SpectraAA 300/400 equipped with a graphite tube atomizer and Zeeman background correction. Quantification was performed using standard addition calibration, employing a 2% w/w EDTA and 0.2% Titron-X chemical modifier to reduce calcium interference (Matsusaki and Sata, 1994; Volynskii, 2003). Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 71 2.2.3. Data Analysis Error on sample concentrations was found to be < 5% for the samples run in triplicate or a higher number of replicates. The percent error dropped as concentrations increased, but 5% error was assumed on all data unless otherwise specified. The instrumental limit of detection was determined to be 0.098nM for the seawater samples, and was calculated as 3.129 times the standard deviation of the blank (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). A method detection limit was determined by running replicate samples of a bulk seawater sample through the entire procedure and determining the standard deviation of the sample concentrations (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). The method detection limit was found to be 0.191nM. All seawater samples analyzed were found to have dissolved aluminum concentrations above both the instrument limit of detection and the method detection limit. Integrated values were determined by trapezoidal integration. Errors on integrations were determined by comparing station depth profile to an oceanographic consistent depth profile for confirmation (Figure 2.2a). If there were anomalous points, an upper and/or lower limit was predicted by excluding anomalous data (Figure 2.2 b,c). One exception to this rule was the high values at the sigma-9 of 26.8. Although these values seem erroneous in terms of oceanographic consistency, these values were thought to represent a real signal, given that samples from different sites and on different cruises had consistently high concentrations at that sigma-9. Average dissolved metal concentrations were also calculated by integration. The error on the graphs was plotted as either the integration error or a 5% error whichever was greater. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 72 a) Dissolved Aluminum (nM) 2 4 6 b) Dissolved Aluminum (nM) 2 4 6 700 Figure 2.2. a) Oceanographically consistent dissolved aluminum depth profile with data from the reference station sampled in September 2001. b) Profiles from center station in September 2000, with actual data represented by closed circles and solid line, and predicted oceanographically consistent lower limit represented by open circles and dashed line. 2.3. Results and Discussion 2.3.1. Eddy Background The two eddies sampled were formed in the years 2000 and 2001, and will be referred to in the following discussion as Haida-00 and Haida-01 respectively. Haida-00 was sampled 5 times: at 4 months (June 2000), 7 months (September 2000), 12 months (February 2001), 16 months (June 2001) and 19 months (September 2001). After leaving the coast, Haida-00 traveled northwest and by May 2000 had stalled on the Bowie Seamount, approximately 180 km offshore. It remained at the seamount until September 2000, with the center station drifting about 20 km west between the 4-month and 7-month sampling times. Once it left the seamount, it traveled approximately 325 km northwest between September 2000 and September 2001, into an HNLC area. Haida-01, the smaller Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 73 of the two eddies, took a more southern route from the coast after formation and missed the seamount entirely. Haida-01 was sampled only 3 times: at 0 months (February 2001), 4 months (June 2001) and 7 months (September 2001). By the September 2001 sampling of Haida-01, it had traveled over 200km offshore. 2.3.2. Haida Eddy Source Waters Di Lorenzo et al., 2005 detennined, through models, that the source water for the Haida Eddies is a combination of Hecate Strait and Northern Vancouver Island shelf water. Hecate Strait is located between the Queen Charlotte Islands and mainland British Columbia, Canada and has a maximum depth of 300m. Two sites within Hecate Strait, just off Douglas Channel, were sampled in September 2002. The dissolved aluminum concentrations at these stations were higher in the surface waters (1.2-1.6nM) than at depth (0.4-0.8nM) (Figure 2.3a), which was probably be due to outflow from rivers near the stations. The deepest sample (at 175m) is 5 meters from the bottom, suggesting there wasn't a dissolved aluminum sediment source, or at least not one as large as the surface river source. The eddy sampled in February 2001 (newly formed Haida-01) had a similar depth profile structure to that of Hecate Strait with higher dissolved aluminum concentration in surface waters, although the dissolved aluminum concentrations were approximately 8 to 9 times higher (Figure 2.3b). An additional input of aluminum to the surface waters was required to achieve the concentrations found in the newly formed Haida-01 eddy. This source could be either from a sediment source near the site of eddy formation or from higher fresh water run-off that occurs during the winter in this region (Crawford et al., 2002). An upwelled sediment source is also possible since there is a steep bathymetric gradient in the region that the Haida eddies form (Crawford, 2002), and there is some evidence of a sediment aluminum source being transported offshore at a sigma- 0 of 26.8 (see Section 2.3.4). Neither source can be dismissed at this time given the limited data in the Hecate Strait region. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 74 Dissolved Aluminum (nM) Dissolved Aluminum (nM) 5 10 15 Figure 2.3. Dissolved aluminum concentrations versus depth at a) two sites within Hecate Strait: MT08 (53° 9.7' N, 130° 26.2' W; closed squares) and MT10 (53° 37.0' N, 130° 44.9' W; open squares) sampled in September 2002 and b) center of newly formed Haida-01 eddy sampled in February 2001. Error bars for MT08 and MT10 contained within symbol. 233. Surface Dynamics The dissolved aluminum concentration within the surface mixed layer decreased as the eddies aged. The high concentrations found on the coast quickly dropped to concentrations similar to or below the surrounding waters (reference stations) within the first 4 months of formation (Figure 2.4). This could be due to the higher primary production within the eddies during the first few months of formation (Crawford et al., 2005), or a mixing of eddy surface waters with surroundings (Mackas et al., 2005). Crawford et al., 2005 determined monthly chlorophyll concentrations within the Haida eddies from composite images obtained by Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite imagery. At the center of the eddies, a maximum chlorophyll was measured during the spring which corresponded to a spring bloom. The occurrence of a spring bloom within an anticyclonic eddy is not expected due to the anticyclonic eddy circulation resulting in downwelling at the eddy center. High levels of primary production have been recorded within other anticyclonic eddies (Tranter et al., 1980; Yentsch and Phinney, 1985; Franks et al., 1986; Zhang et al., 2001; Perez et al., 2003), Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 75 0 5 10 15 20 Age of Eddy (months) Figure 2.4. Changes in average dissolved aluminum concentrations (determined by integration) within the surface mixed layer depth during the eddies lifetime. Full circle indicates Haida-00; open circle is Haida-01; full triangle indicates cruise reference stations. Solid line near bottom indicates average surface waters at Station P (50° N, 145° W; sampled September 2002) and dashed line indicates average Hecate Strait waters. although different causes for the increased growth have been proposed (Tranter et al., 1980; Martin and Richards, 2001; Zhang et al., 2001; Crawford et al., 2005). The timing of the blooms in 2000 and 2001 varied slightly (April-May 2000 and May 2001) but both occur before the sampling of the eddy in June of each year, by which time the chlorophyll values dropped to below 0.4 mg/m3 (Crawford et al., 2005). Using the February values measured in the surface waters for Haida-01 as the 0 month concentration for both eddies, a larger percent decrease in dissolved aluminum was measured between the February and June sampling times (Table 2.1). In Haida-00, this decrease was approximately 51% of the total dissolved aluminum at the start of this time period. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 76 Feb-00 Jun-00 Sep-00 Feb-01 Jun-01 to Jun-00 to SeDt-00 to Feb -01 to Jun-01 to SeDt-01 % Removal of Haida-00 51%b 4% 40% 16% 31% dissolved A l a Haida-01 68% 36% Chlorophyll Haida-00 <3.6 <0.6 0.6 - 0.8 <0.6 <0.4 (mg m"3) Haida-01 > 1 <0.5 June - 00 Sept-00 June-01 Sent-01 Biogenic Silica Haida-00 10.8-13.8 6.16 40.1-40.5 12-19.3 (mmol m"2) Haida-01 19-45 Table 2.1. Comparison of change in surface dissolved aluminum (in percent) between cruises with chlorophyll concentrations and mixed layer integrated biogenic silica. Chlorophyll concentrations from Crawford et al., 2005. Biogenic silica concentrations from Peterson, 2005. Notes: a: % Removal calculated by taking difference between two cruises and dividing it by the average concentration of the earlier cruise. b: Percent removal for Feb-00 to June-00 calculated assuming February Haida-00 surface concentration equal to surface concentration found in newly formed Haida-01. The 2001 spring bloom within Haida-00 had a lower total chlorophyll measurement and the dissolved aluminum removal, although similar as a percent removal, corresponded to a lower absolute aluminum removal. In Haida-01, a larger percent decrease (68%) was measured within the first four months (February to June 2001), compared to the removal measured within Haida-00 during its first year. This large decrease did not correspond to an increased chlorophyll signal in Haida-01 the spring of2001 compared to Haida-00. This increased removal wilhin Haida-01, however, could be attributed to the increased concentration of biogenic silica particles measured in June 2001. The integrated biogenic silica within the surface layer of both Haida-00 and Haida-01 in June 2001 was up to five times higher than that measured in the surface layer of Haida-00 in June 2000. This higher biogenic silica signal did not produce a higher chlorophyll signal within the eddy compared to the previous year and was possibly transported into the eddy from the coast or due to a diatom bloom outside the eddy (Peterson and Harrison, in prep.). Although this suggests the diatoms were not grown in-Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 77 Dissolved Aluminum (nM) 5 10 15 20 25 900 Figure 2.5. Dissolved aluminum concentrations versus depth at the center of the eddy at 4 months. Full circle indicates Haida-00 and open circle indicates Haida-01. Data points without error bars have an error that is smaller than the symbol size. situ, the empty tests could still scavenge dissolved aluminum from surface waters. Since the tests were still measured in surface waters in June 2001, they may also account for the higher dissolved aluminum removal in June to September 2001 in both eddies (compared to Haida-00 in the previous summer). Between June and September of both sampling years, when insolation increased stratification, a decrease in chlorophyll occurred in both eddies (Crawford et al., 2005). This decrease in chlorophyll corresponded to a decrease in the percent aluminum removal (Table 2.1). Following the decrease in chlorophyll over the summer months, a late summer/early autumn chlorophyll maximum was visible by satellite within the eddies. In Haida-00, the second chlorophyll maximum occurred in September 2000. This second maximum in growth resulted in a larger drawdown of dissolved aluminum between the September 2000 and February 2001 than between June and September 2000. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 78 Dissolved Aluminum (nM) 0 5 10 15 20 <D Q 800 A 1000 A 1200 J Figure 2.6. Dissolved aluminum concentrations versus depth at the reference stations sampled in June 2000 (55° 44.8' N , 135° 50.2' W; solid triangles) and June 2001 (52° 45.0' N , 137° 0' W; open triangles). Data points without error bars have an error that is smaller than the symbol size. 23.4. Deep Water Transport As the eddy leaves the coast, there was a dissolved aluminum maximum in the eddy depth profiles at a depth that corresponded to the "bottom" of the eddy, at a salinity of 33.9 and a sigma-6 of approximately 26.8 (Figure 2.5). This water mass also contained higher concentrations of dissolved iron (Johnson et al., 2005; Chong et al., in prep.). The dissolved aluminum maximum at depth was also visible at the reference station sampled during the June 2000 cruise, and was thus attributed to a sediment source on the shelf that is advected offshore at that isopycnal and not only isolated in the eddy core. The other reference station, sampled in June 2001, is 80 km farther west of the June 2000 reference station and by that distance from the shelf the higher aluminum signal was no longer visible (Figure 2.6). The Haida-00 eddy retained the "deep" aluminum maximum, Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 79 0 + , , , , , _ , , 1 26.2 26.3 26.4 26.5 26.6 26.7 26.8 26.9 27.0 27.1 Sigma-G Figure 2.7. (a) Dissolved aluminum concentrations at (or near) a sigma-0 of 26.8 for Haida-00 (full circles), Haida-01 (open circles) and reference stations (full triangles) over 2 year sampling period. Note: low concentration for Haida-00 at 7 months may be due missing the sigma- 9 of 26.8 isopycnal, as shown in Figure 2.8 (b) where full circles represent H-00 at 4 months and empty circles represent H-00 at 7 months. Data points without error bars have an error that is smaller than the symbol size. compared to the surrounding waters, until an age of 16 months (Figure 2.7). The removal of dissolved aluminum at the sigma-0 of 26.8 in Haida-00 gave a rate of 0.004-0.06nM/day (Table 2.2). The lower limit occurred between the ages of 7 andl6 months, Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 80 Surface Removal Removal at Depth Change Between Haida-00 Haida-01 Haida-00 Haida-01 0 to 4 months 0.03a 0.10 4 to 7 months 0.002 0.008 0.02 0.13 7 to 12 months 12 to 16 months 0.01 0.004 0.004" 16 to 19 months 0.006 0.06 Table 2.2. Removal of dissolved Al during eddy lifetime. Removal is given as nM of dissolved Al/day. Notes: a: Rate of removal calculated assuming Haida-00 would have a similar dissolved aluminum concentration in surface waters as Haida-01 in the month of formation. b: Rate of removal calculated from data at 7 and 16 months, no data was collected at the sigma-T of 26.8 at 12 months. and was due to a combination of a longer time between sampling and the reduced growth of phytoplankton (and therefore lower particle flux through the eddies) during most of that time. The rate determined between the ages of 16 and 19 months could also be an underestimate since the 16-month sampling occurred before the influx of additional coastal water occurred, from a younger eddy that combined with Haida-00 in the latter part of June 2001 (Figure 2.8). The rate of decrease in dissolved aluminum measured in Haida-01 between 4 to 7 months of age was almost three times higher than Haida-00 experienced the previous year. This is again attributed to the fact that in June 2001 the amount of biogenic silica measured in the eddies was almost 5 times higher than the previous year (Peterson, 2005), and this higher particle flux scavenged more aluminum, since aluminum is preferentially scavenged by silica particles (Moran and Moore, 1992; Gehlen et al., 2003). The rate of Al removal at depth follows the surface water removal, although a delay was observed (Table 2.2). This suggests that the particles that removed aluminum from the surface waters were reaching 400m depths by 3 - 4 months time. Assuming a constant settling rate between sampling times, an average particle-settling rate of approximately 3m/day was calculated, which was similar to the rate found using particulate thorium-230 distributions (1.7m/day; Krishnaswami et al., 1976) and the Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 81 •42*W MOW 138YV 13TW 13<"W 132 "W 130*W '42"W 14Crw 138"W 13€*W 134*W 132W 130"W 142*W 140"W I38W 13S*W 134*W 132W W w S*a Surface Height Anortwlv (ml •30 27 44 21 .18 -15.12 -9 -6 -3 Q 3 6 9 12 tS 18 2 ! 24 27 30 Figure 2.8. Sea surface height anomaly plots showing the merger o f a smaller, younger eddy with Haida-00 in June 2001. Plots produced by the Colorado Centre o f Astrodynamic Research ( C C A R ) using T O P E X / P O S E I D O N - E R S - 2 radar altimetry data. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 82 6000 Age of Eddy (months) Figure 2.9. Changes in depth integrated aluminum concentrations within eddy core (200-600m) during the eddies lifetime. Full circle indicates Haida-00; open circle is Haida-01; and the full triangle indicates reference stations. The 7-month value for Haida-00 is likely an underestimate due to no sample of the expected high aluminum signal at sigma-0 of 26.8. settling rates determined using standing aluminum particle concentrations and deposition rates (2.6m/day; Krishnaswami and Sarin, 1976). If the particles within the eddy settled much faster, we would expect either a) no delay in removal rates, or b) no correlation of removal rates. This slow settling rate suggests that small particles (< 53um) are responsible for most aluminum scavenging within the eddy, consistent with the work of Krishnaswami and Sarin, 1976; Clegg and Whitfield, 1991. The similar removal rates in the surface and at depth also suggested that although there may be mixing of surface waters with surroundings, the particles in surface waters at the center of the eddy tended to sink through the eddy core, since the higher biogenic silica seen in the eddy surface waters was not measured in the surface of the surrounding waters (Peterson, 2005). 2.3.5. Total Offshore Transport The Haida eddy contained a significant amount of aluminum in its core (200-600m), an amount higher than the surrounding waters, up until at least 7 months of age Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 83 Dissolved Al Content of Haida Eddies (0-600m) Age (months) Haida-00 Haida-01 4 1.5 x 107 2.6 x 107 7 8.2 x 106 1.4 x 107 12 16 8.9 x 106 19 4.9 x 106 Predicted Dissolved Al Input from Dust Deposition GESAMP Model (Duce and Tindale. 199D Measures et.al., 2005 Dust solubility Range Low flux: 0.1 g m"2 vr"1 High flux: 1 g m"2 vr"1 0.02 g m"2 vr"1 1.5% 3.9 x 106 3.9 x 107 7.8 x 105 5.0% 1.3 x 107 1.3 x 108 2.6 x 106 Table 2.3. Comparison of dissolved Al content in Haida eddies over time with the predicted dissolved Al input from dust deposition in the area influenced by Haida eddies. Area influenced by Haida eddies is 133°W to 145°W and 46°N to 55°N. Units are moles of dissolved Al. (Figure 2.9). The Haida-00 eddy had a lower integrated aluminum that the reference station at 7 months but this was probably due to not having sampled at the sigma-0 (26.8) where the dissolved aluminum maximum was observed during other sampling times (Figure 2.7b). At 19 months, the Haida-00 had higher integrated duminum in its core compared to the surround waters (630umol m" versus 240umol m"). This was probably due to the eddy traveling slightly farther offshore, and the influx of coastal water from the merger with the smaller eddy in June 2001. As the eddy aged, the total dissolved aluminum in the eddy decreased. The amount of dissolved Al transported offshore by the Haida-00 eddy compared to surroundings would have been greater but Haida-00 got caught up on the Bowie Seamount, resulting in most duminum being removed from the eddy while it was still "nearshore". Hdda-01 traveled southwest and avoided the seamount, and therefore should transport more duminum into the open ocean; unfortunately Hdda-01 was not sampled after 7 months (Figure 2.9). To determine the quantity of dissolved aluminum transported offshore in eddies, we required both the average dissolved concentration of duminum within the eddy and Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 84 the volume of coastal water transported by the eddy. The volume transported by the Haida-00 has been determined to be approximately 3000km3 (Whitney and Robert, 2002; Johnson et al., 2005). Integrated aluminum concentrations from the surface to 600m at both the center and edge stations of Haida-00 give similar results to each other for all sampling times, with the edge station having dissolved aluminum values (mol/km2) between 84-130% of the center station. Using the integrated concentration from the center station and a volume of 3000 km resulted in a calculated 1.5 x 10 mol of dissolved aluminum being carried in the 4-month old Haida-00 (Table 2.3). As the eddy ages, the amount of aluminum transported decreased to approximately 4.9 x 106 mol dissolved aluminum contained in the core of the eddy at 19 months of age. Using integrated aluminum concentrations from OSP and a volume of 3000 km3, the same volume of open ocean water at the sample depth range would contain approximately 1.1 x 106 mol of dissolved aluminum, which is less than 50% of the amount of dissolved aluminum contained within a 19-month-old Haida-00. To determine how this related to the overall flux of aluminum to the open ocean, we first needed to determine the area that could be influenced by the Haida eddies. The region in which these eddies have been tracked spans from the Queen Charlotte Islands (133°W) to as far west as Station P (145°W), as far north as 55°N and as far south as 46°N (Whitney and Robert, 2002; Johnson et al., 2005). Using the crustal abundance of Al (8.3%) and a solubility of dust ranging from 1.5% to 5% (Measures et al., 2005), we determined the annual aluminum flux to this area by dust deposition (Table 2.3). Using a dust deposition of 0.1 - 1 g m"2 yr"1 predicted from the GESAMP model (Duce and Tindale, 1991), a minimum of 3.9 x 106 mol (using 1.5% solubility and minimum dust deposition) and a Q maximum of 1.3 x 10 mol (using 5% solubility and maximum dust deposition) of Al is calculated to have deposited and dissolved within this area. Using this range, the amount of aluminum a 4-month eddy transports was between 0.2 to 5 times the amounts of dissolved aluminum predicted to be deposited by aeolian dust deposition. A recent study in the western and central North Pacific suggests that the dust deposition in the subarctic Pacific is closer to the 0.1 g m"2 yr"1 prediction and could be as low as 0.02 g m"2 yr"1 (Measures et al., 2005). Compared to the lowest deposition, the Haida-00 eddy at 19 months would contain over 6 times more dissolved aluminum Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 85 Dentil of 26.8 Isopvcnal Isopvcnal Depression (m) Age (months) Haida-00 Haida-01 Haida-00 Haida-01 0 365 4 460 350 200 90 7 453 320 193 60 12 330 16 290 80 19 350 150 Table 2.4. Depth of 26.8 isopycnal from CTD data. Isopycnal depression, given in metres, compared to surrounding (reference station) waters. than what is to be supplied from dust according to deposition models. The aluminum in the core of the eddy, if it reached surface waters, could affect the predicted aluminum dust input and therefore iron fluxes calculated for this region. As the eddy aged, shoaling of the isopycnals brought the 'deep' aluminum maximum signal closer to the surface (Table 2.4). In Haida-00, the depression of the sigma-0 of 26.8 between June 2001 (16 months) and September 2001 (19 months) from 290 to 350m was due to the merger of the new eddy with the Haida-00 in June 2001. Haida-01 began with a smaller depression of the sigma-9 of 26.8 since it was a smaller eddy, and therefore less coastal water was transported in its core. Although the shoaling of the isopycnals did occur as the eddy aged, the 26.8 sigma-9 waters within the eddy would not rise above the surrounding waters of the same density (which was approximately 200-260m below the surface) and therefore the high dissolved aluminum in the core should not reach the surface waters before it is removed through particle scavenging. In addition, during the 19 months the Haida-00 was sampled, the maximum peak of dissolved aluminum at depth remained near the sigma-0 of 26.8 waters with only slight vertical diffusion, so an upward flux of aluminum across isopycnals was not large. 23.6. Scavenging Rates and Residence Times Scavenging rates have been shown to depend oh particle concentration and also particle flux (Voice et al., 1983; Santschi, 1984; Honeyman and Santschi, 1988). This fact was noticeable in the removal rates for dissolved aluminum listed in Table 2.2. When Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 86 there was higher production there was an increase in dissolved aluminum removal (0.03 versus 0.002nM/day). In addition, the type of the particles also affected the rate; for example, when biogenic silica in the surface waters was higher an increased scavenging rate was measured. During the June 2001 cruise, while the chlorophyll maximum recorded between February and June 2001 was smaller than the previous year's bloom, the biogenic silica in surface waters was up to five times higher, which resulted in a removal rate of O.lOnM/day versus the 0.03nM/day calculated for the same time span during 2000. This suggested that the quality of the particulate matter was also important in determining removal and scavenging rates. The residence time of dissolved aluminum in the surface waters of the eddies (T P) can be calculated the following equation: Tp = [Meaq]/rs Equation 2.1 Where [Meaq] is the total dissolved concentration of aluminum and rs is the net rate of transfer from the dissolved to the particulate phase, in mol L"1 day"1 (Honeyman and Santschi, 1988). Using the original surface concentration of 8.5nM (measured in February, right after the formation of the eddy) and an average removal rate of 0.017nM/day (calculated as an overall yearly average from the Haida-00 data) resulted in a surface residence time of approximately 510 days (1.4 years). This residence time could vary depending on whether the year had a higher particle flux (such as the one that occurred in 2001), but the increased flux only shortened the calculated residence time to just approximately half a year (160 days). The calculated residence time is slightly lower than the 3 - 5 year residence time calculated for the open ocean (Orians and Bruland, 1986). This is expected in the surface waters of a highly productive eddy, where particle concentrations are expected to exceed those of the open ocean. The effect of the Gulf of Alaska eddies on the open ocean aluminum residence time estimates requires certain assumptions to be made about the overall quantity of dissolved aluminum delivered to the oceans. The relative amount of dust input versus eddy transport allows us to compare the effects each would have on the residence time. If the eddies transported only 5% of the total dust input, then the effect the eddies would have on the overall residence time, determined using yearly dust deposition, would be to Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 87 decrease the residence time slightly. However, if the eddies transported 5 times more dissolved aluminum than the yearly dust deposition (using the minimum dust input) then the residence time of dissolved aluminum in the Gulf of Alaska could be much smaller than that calculated using dust fluxes alone. Since the suggestion of a lower dust deposition is recent (Measures et al., 2005), the overall residence time estimated in previous studies is probably still on the correct time scale, and just the source of dissolved aluminum to the region may be in question. 2.4. Conclusion Haida eddies are a source of dissolved aluminum to the Gulf of Alaska. Four months after formation, a Haida eddy contains approximately 2.1 x 107mols of dissolved aluminum. Although removal of dissolved aluminum occurs over time, at 19 months after formation Haida-00 still contained twice the amount of dissolved aluminum as the same volume of water in open ocean. Most of the dissolved aluminum is transported at depth within the eddy core, at a sigma-9 of 26.8. As the eddy ages, the isopycnals rebound due to frictional decay. This rebound causes a shallowing of the dissolved aluminum maximum, but the maximum does not reach the surface. 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W., 1988. The marine geochemistry of dissolved gallium: A comparison with dissolved aluminum. Geochimica et Cosmochimica Acta, 52: 2955-2962. Perez, F. F., Gilcoto, M. and Rios, A. F., 2003. Large and mesoscale variability of the water masses and the deep chlorophyll maximum in the Azores Front. Journal of Geophysical Research - Oceans, 108(C7). Peterson, T. D., 2005. Studies on the Biological Oceanography of Haida Eddies. Ph.D. Thesis, University of British Columbia, Vancouver, 440 pp. Peterson, T. D. and Harrison, P. J., in prep. Transport of Fresh Water Into the Gulf of Alaska Via Mesoscale Eddy Circulation as Inferred From Diatom Frustules. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 92 Peterson, T. D., Whitney, F. A. and Harrison, P. J., 2005. Macronutrient dynamics in an anticyclonic mesoscale eddy in the Gulf of Alaska. Deep Sea Research Part II -Topical Studies in Oceanography, 52(7-8): 909-932. Santschi, P. H., 1984. Particle-Flux and Trace-Metal Residence Time in Natural-Waters. Limnology and Oceanography, 29(5): 1100-1108. Tabata, S., 1982. The Anticyclonic, Baroclinic Eddy off Sitka, Alaska, in the Northeast Pacific Ocean. Journal of Physical Oceanography, 12(11): 1260-1282. Tranter, D. J., Parker, R. R. and Cresswell, G. R., 1980. Are Warm-Core Eddies Unproductive. Nature, 284(5756): 540-542. Turner, D. R., Whitfield, M. and Dickson, A. G., 1981. The Equilibrium Speciation of Dissolved Components in Fresh-Water and Seawater at 25-Degrees-C and 1 Arm Pressure. Geochimica et Cosmochimica Acta, 45(6): 855-881. van Beusekom, J. E. E., van Bennekom, A. J., Treguer, P. and Morvan, J., 1997. Aluminium and silicic acid in water and sediments of the Enderby and Crozet Basins. Deep Sea Research Part II - Topical Studies in Oceanography, 44(5): 987-1003. Vink, S. and Measures, C. I., 2001. The role of dust deposition in deterrnining surface water distributions of Al and Fe in the South West Atlantic. Deep Sea Research Part n - Topical Studies in Oceanography, 48(13): 2787-2809. Voice, T. C , Rice, C. P. and Weber, W. J., 1983. Effect of Solids Concentration on the Sorptive Partitioning of Hydrophobic Pollutants in Aquatic Systems. Environmental Science & Technology, 17(9): 513-518. Volynskii, A. B., 2003. Chemical modifiers in modern electrothermal atomic absorption spectrometry. Journal of Analytical Chemistry, 58(10): 905-921. Walsh, J. J., 1991. Importance of continental margins in the marine biogeochemical cycling of carbon and nitrogen. Nature, 350: 53- 55. Whitney, F. and Robert, M., 2002. Structure of Haida eddies and their transport of nutrient from coastal margins into the NE Pacific Ocean. Journal of Oceanography, 58(5): 715-723. Yeats, P. A., Dalziel, J. A. and Moran, S. B., 1992. A Comparison of Dissolved and Particulate Mn and Al Distributions in the Western North-Atlantic. Oceanologica Acta, 15(6): 609-619. Yelland, D. and Crawford, W. R., 2005. Currents in Haida Eddies. Deep Sea Research Part II - Topical Studies in Oceanography, 52(7-8): 875-892. Chapter 2: Aluminum Dynamics in mesoscale eddies in the NE Pacific 93 Yentsch, C. S. and Phinney, D. A., 1985. Rotary Motions and Convection as a Means of Regulating Primary Production in Warm Core Rings. Journal of Geophysical Research - Oceans, 90(NC2): 3237-3248. Zhang, J. Z., Wanninkhof, R. and Lee, K., 2001. Enhanced new production observed from the diurnal cycle of nitrate in an oligotrophic anticyclonic eddy. Geophysical Research Letters, 28(8): 1579-1582. 94 CHAPTER 3: A STUDY OF THE FACTORS CONTROLLING THE DISSOLVED IRON WITHIN THE SURFACE WATERS OF AN ANTICYCLONIC EDDY 3.1. Introduction Iron is an important micronutrient for phytoplankton (Raven, 1990; Geider and Laroche, 1994), and when in low concentrations, can limit phytoplankton growth (Sunda and Huntsman, 1995; 1997). Due to iron's particle reactivity and low solubility, phytoplankton growth is limited in large regions of the world's oceans. These regions are distinguished as high nutrient low chlorophyll (HNLC) regions, and are located in areas of low iron inputs, such as the subarctic Pacific, equatorial Pacific and the Southern Ocean (Martin and Fitzwater, 1988; Martin et al., 1989; Fitzwater et al., 1996; de Baar et al., 2005). Many studies have focused on what influences dissolved iron in the oceans because of the control iron exhibits on biological production (Johnson et al., 1997). The oceanic distribution of iron is similar to other major nutrients, with low dissolved concentrations in surface waters and a rapid increase in dissolved concentration at the nutricline, where biological material is remineralized (Bruland et al., 1991). One major difference between dissolved iron distributions and major nutrient distributions is that iron does not have the inter-ocean fractionation which is characteristic of major nutrient distributions (Martin et al., 1993). This lack of inter-ocean fractionation suggests that in addition to biological uptake and release, other factors play a role in controlling the distribution of dissolved iron in the world's oceans (Johnson et al., 1997). Iron, in addition to being an important micronutrient, is a scavenged metal. In oxic seawater, thermodynamics predict that the major inorganic speciation of iron should be Fe (DI), which forms oxides, resulting in iron being removed from the dissolved phase. Concentrations of dissolved iron in surface waters are higher than expected by iron oxide solubility alone, and this is attributed to the large amount of organic ligands that complex iron strongly (Rue and Bruland, 1995; van den Berg, 1995; Croot and Johansson, 2000) and photoreduction reactions that occur in surface waters (Wells and Mayer, 1991; Miller et al., 1995). The combination of biological and chemical controls on dissolved iron concentrations in the surface ocean make it difficult to determine the importance of the different surface removal pathways. Models predicting dissolved iron at depth have lead Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 95 to the conclusion that organic complexation plays a role in the apparent Fe (IH) solubility in waters at depth, with high concentrations of weak organic ligands keeping more iron in solution than predicted by scavenging rates (Johnson et al., 1997). Models that include surface water determinations require a combination of factors, such as scavenging rates, biological uptake and organic complexation to model the system (Weber et al., 2005). Processes in the surface waters that affect the dissolved iron concentration include inputs such as dust deposition, biological uptake by phytoplankton, scavenging to the surfaces of particulate matter, precipitation of iron oxides, and phytoplankton production of siderophores. Physical processes such as mixing with surrounding waters and upwelled water also affect dissolved iron concentrations, and by observing other dissolved trace metal distributions the importance of these separate controls on dissolved iron will be studied. The trace metals included in this study are aluminum, cadmium, copper and manganese. The cadmium and copper were selected since their distributions are most sensitive to biological processes in surface waters, while aluminum and manganese reflect continental input, scavenging processes and reduction-oxidation chemistry. Dissolved aluminum in the open ocean is rapidly scavenged (Orians and Bruland, 1986) and distributions of aluminum exhibiting high dissolved concentrations indicate aluminum sources. Aluminum has a dust source similar to iron but since aluminum is not used significantly in biological production, the input signal remains in surface waters for a longer time (Measures and Vink, 2000). For this reason, dissolved aluminum surface distributions have been used in many studies to predict the quantity of dust input into surface waters and dissolved aluminum has been used as a proxy for iron deposition for dust sources in models (Measures and Vink, 2000; Vink and Measures, 2001; Measures et al., 2005). Similar to iron, aluminum is a scavenged metal and its scavenging rates are proportional to particle concentration (Orians and Bruland, 1986). Dissolved manganese, although a biologically required element has a distribution that exhibits its sources and is controlled mainly by its oxidation-reduction chemistry. Manganese and iron undergo similar oxidation-reduction reactions, although the rates of manganese oxidation are found to be slower (Stumm and Morgan, 1996; Luther, 2005). In addition, both manganese and iron have a similar continental shelf sediment source (Chase et al., 2005). Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 96 Dissolved cadmium and copper have recycled distributions, with copper's dissolved profile modified by rapid scavenging. Cadmium is taken up by phytoplankton in surface waters and is regenerated at depth, similar to iron but without significant scavenging to particles. Cadmium can be used to trace upwelling or mixing below the nutricline (Shen et al., 1987; van Geen and Husby, 1996). In addition, new studies suggest that the cadmium-phosphate ratio may supply information on iron limitation (Cullen, 2006). Copper can be used as a tracer that has similar controls to iron, such as biological uptake and scavenging. Similar to cadmium, an increase in biological uptake of copper may indicate a limitation of iron. Lab experiments have shown that copper is used by some phytoplankton to reduce Fe(HI) under iron stress (Peers et al., 2005; Maldonado et al., 2006). In addition, iron limitation was found to increase the use of Photosystem I, which has greater copper requirements (Peers and Price, 2006). This group of trace metals will give information on the chemical and biological controls on iron. To study the changes in dissolved iron requires tracking of a water mass over time. Physical controls on iron distributions, such as upwelling and mixing of water masses, and the difficulties in tracking specific water masses could complicate the tracer signals. The problem of tracking seawater was addressed by studying the changes in dissolved iron within large, anticyclonic eddies. These eddies, termed the Haida eddies, are one of a group of mesoscale, anticyclonic eddies that form in the Gulf of Alaska (Kirwan et al., 1978; Tabata, 1982).. The eddies were followed by tracking the sea surface height anomalies determined from TOPEX/Poseidon and ERS-2 altimetry data and supplied by the Colorado Centre of Astrodynamics Research (CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer). The Haida eddies have lifetimes of up to 3 years, allowing them to be studied over time. The Haida eddies were the focus of a large study, initiated by the Institute of Ocean Sciences (Department of Fisheries and Oceans, Canada), to determine the quantity and quality of coastal water transported and the effect these large eddies have on the Eastern North Pacific Ocean (Miller et al., 2005). Results from this study have shown that these eddies transport large amounts of heat and fresh water (Crawford, 2005), and that the core of the eddy remained chemically distinct from surrounding waters in terms of nutrients (Peterson et al., 2005) and iron content (Johnson et al., 2005), for at least 2 Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 97 years. The amount of iron transported within the eddy core (200-600m) was of a similar magnitude to the iron calculated to deposit in this region yearly from atmospheric sources (Johnson et al., 2005). In this paper the changes in dissolved aluminum, manganese, cadmium and copper concentrations as the eddy ages are discussed. The combination of these changes is then used to understand the importance of processes controlling dissolved iron in the mixed layer. 3.2. Methods and Materials 3.2.1. Sampling Stations Sampling was performed over a 15-month period, from June 2000 to September 2001, in conjunction with the Institute of Ocean Sciences, Department of Fisheries and Oceans, Canada. The Haida eddies were first located by sea surface height anomaly images determined from TOPEX/Poseidon and ERS-2 altimetry data supplied by the Colorado Centre of Astrodynamics Research (CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer). Once in the region of the eddy, conductivity, temperature and depth (CTD) profiles were performed on a transect of the eddy and the "center" station was selected at the site of maximum downward isotherms (Whitney and Robert, 2002; Yelland and Crawford, 2005). A reference station, that was far enough away from the eddy as to not to be affected by eddy dynamics, was also sampled during each cruise. Ocean Station Papa (50.0° N, 145.0° W) and Hecate Strait (MT08; 53.2° N, 130.4° W and MT10; 53.6° N, 130.7° W) data, collected in September 2002, will also be presented for comparison. All station locations are given in Table 3.1, and shown on a map in Figure 3.1. Conductivity, temperature and depth measurements were collected at each station using a Seabird 91 lplus CTD mounted on a 24-bottle rosette frame. Sigma-8 values were calculated from CTD data. Nutrient samples were collected and analyzed by Peterson et al., 2005. Samples were run on a Technicon II AutoAnalyser® following procedures in Barwell-Clarke and Whitney, 1996. Duplicate phosphate analysis were performed on 10-15% of the samples and gave a standard deviation of ± 0.012uM (Peterson et al., 2005). Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 98 Date Station Latitude CTSD Longitude (°W) Jun-00 Reference 51.7 135.8 Sep-00 Reference 51.8 136.2 H-00 Center 52.8 136.2 Feb-01 H-00 Center 53.8 138.0 H-01 Center 52.9 132.8 Jun-01 Reference 52.8 137.0 H-00 Center 54.4 138.2 H-01 Center 51.3 134.0 Sep-01 Reference 52.5 138.8 H-00 Center 54.5 138.3 H-01 Center 51.0 133.3 Sep-02 Ocean Station Papa 50.0 145.0 Hecate Strait-MT08 53.2 130.4 Hecate Strait-MTI0 53.6 130.7 Table 3.1. List of cruise dates, stations sampled and locations. 3.2.2. Trace Metal Sampling Trace metal depth profiles, down to depths of 1000m, were collected at the center and reference stations. All handling of surface samples was performed within an on-deck PVC ultra-low penetration air filter (ULPA) clean hood. Surface samples (10,25 and 40m) were collected using an air-driven double bellows Teflon® pump (Asti) and a Teflon® sampling tube. Surface samples were pumped through a 0.22um Opticap™ cartridge filter, and collected within the on-deck clean hood. Samples from 75m depth and deeper were collected using clean 10-, 12- or 30-L GO-FLO® bottles (Teflon®-lined, General Oceanics) attached to a Kevlar®-line and triggered using solid Teflon® messengers (for specifics, see Johnson et al., 2005). Samples collected using the GO-FLO® bottles were filtered using a 0.22pm Opticap™ cartridge filter that was connected to the GO-FLO® bottle spigot. The filtered seawater was collected in acid-cleaned 500mL LDPE bottles and acidified within the on-deck clean hood to a pH < 2 using 6N Q-HC1 and stored until analysis. Iron sampling was also performed using the same sampling equipment but treatment of samples after collection varied. Samples were taken for total iron, Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 99 58 150 —| • 1 H - I ' I . j • • i . . . " 7 Tj 145 140 135 130 Longitude, W 125 120 Figure 3.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time of sampling denoted by numbers below (or to the right) of the location symbol: 1 - June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001. extractable iron, dissolved iron and total dissolved iron. Details on sampling and sample treatment can be found in Johnson et al., 2005. Data presented in the results and discussion sections compare dissolved trace metal (aluminum, cadmium, copper, and manganese) with total dissolved iron determined by Johnson et al., 2005. The total dissolved iron was chosen for comparison since it was the fraction that was acidified to pH<2 and stored for more than 7 months before analysis. This process was similar to the determination of dissolved aluminum, cadmium, copper and manganese in terms of filtration, acidification and storage. 3.2.3. Trace Metal Analysis Seawater samples were pH adjusted to 7.0 ±0.1 using concentrated ammonium hydroxide (Q-NH3, Seastar Baseline®) and acetic acid (Q-HAc, Seastar Baseline®). The (fe pH-adjusted seawater was dripped through 2mL of Chelex 100 using a flow rate of 0.80 Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 100 ± 0.02mL/min. The column was then rinsed with 6mL of 0.3M Q-NH4AC buffer (pH of 7) and 4mL of pH-adjusted high purity, deionized water (18MQ cm, Millipore Milli-Q, Bedford, MA, USA). The concentrated metals were then eluted using lOmL of 2N quartz distilled nitric acid (Q-HNO3, Seastar Baseline®). The eluent was concentrated again by evaporation, and brought up in 4mL of 1% Q-HNO3. This resulted in an overall concentration factor of approximately 125. Column recovery tests were performed using spiked seawater solutions made using certified lOOOppm Atomic Absorption standards (Delta Scientific Lab Products). The column recoveries were determined to be 110 ± 13% (n = 16) for aluminum, 104 ± 7% (n = 36) for cadmium, 96 ± 5% (n = 34) for copper, and 108 ± 6% (n = 23) for manganese. The concentrated eluent was analyzed on a Varian SpectraAA 300/400 atomic absorption spectrophotometer equipped with a graphite tube atomizer and Zeeman background correction. Quantification was performed using the auto-sampler and standard addition calibration. For the aluminum analysis a 2% w/w EDTA and 0.2% Titron-X chemical modifier was used to reduce calcium interference (Matsusaki and Sata, 1994; Volynskii, 2003). Cadmium, copper and manganese analysis were performed using a graphite furnace equipped with a platform to allow for higher ashing and atomization temperatures. The manganese analysis required the use of a 0.1% palladium (w/w) in 1% nitric acid modifier to reduce matrix interferences (Qiao and Jackson, 1991). 3.2.4. Data Analysis Error on sample concentrations was found to be < 5% for the samples run in triplicate or a higher number of replicates. The percent error decreased as concentration of the metal in the sample increased, but due to the limited number of replicate samples analyzed a 5% error was assumed on all data unless otherwise specified. The instrumental limit of detection (Table 3.2) was calculated as 3.129 times the standard deviation of the blank (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). A method detection limit was detennined by running replicate samples of a bulk seawater sample through the entire concentration procedure and determining the standard deviation of the sample concentrations (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). All seawater samples analyzed were found to have Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 101 Aluminum Cadmium Copper Manganese Average percent error Error = ts/Vn 4% 5% 3% 5% Lower Level of Detection L.O.D. = 3.29(s of blk) + avg blk 0.098 0.003 0.108 0.037 Method Detection Limit M.D.L. = t(s of sample) + avg blk 0.191 0.006 0.099 0.029 Table 3.2. Average percent error on replicate samples (at 95% confidence level), instrument limit of detection, and method detection limit for aluminum, cadmium, copper, and manganese. Detection limits are converted to units of nM in original seawater by dividing by concentration factor, "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample). dissolved metal concentrations larger than the instrument limit of detection and the method detection limit. A certified reference material, CASS-3 (Certified Atlantic Surface Seawater - 3; National Research Council of Canada), was analyzed to test the accuracy of the cadmium, copper and manganese analysis. The reference material was run in triplicate and the results, with a comparison to the certified values, are listed in Table 3.3. Aluminum data was also measured but no certified value for comparison was available. Dissolved cadmium, copper, and manganese were all determined to be within the error limits of the certified reference values. Average surface dissolved metal concentrations were calculated by determining the integrated metal amount within the mixed layer and dividing by the mixed layer depth. Integration values were determined by trapezoidal integration. The error on the following graphs was plotted as either the integration error or a 5% concentration error, whichever was determined to be larger. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 102 Measured Value Certified Reference (P-g/L) Value (pg/L) Aluminum 0.294 ± 0.004 II n Cadmium 0.032 ± 0.002 0.030 ± 0.005 Copper 0.514 ±0.065 0.517 ±0.062 Manganese 2.85 ± 0.25 2.51 ±0.36 Table 3.3. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval. 3.3. Results 3.3.1. Haida Eddy Evolution Two eddies sampled were formed in the years 2000 and 2001, and will be referred to in the following discussion as Haida-00 and Haida-01 respectively. Haida-00 was sampled four times: at 7 months (September 2000), 12 months (February 2001), 16 months (June 2001) and 19 months (September 2001). After leaving the coast, Haida-00 traveled northwest and by May 2000 had stalled on the Bowie Seamount, approximately 180 km offshore. It remained at the seamount until September 2000. Once it left the seamount, it traveled approximately 325 km northwest between September 2000 and September 2001, into an HNLC area. Between June and September 2001, a smaller newly formed eddy merged with Haida-00, bringing with it an influx of coastal water (Figure 3.2). Haida-01 took a southerly route from the coast and missed the seamount. By September 2001 Haida-01 had traveled over 200km offshore. Although Haida-01 had traveled a less complicated route, it was sampled only three times: at 0 months (February 2001), 4 months (June 2001) and 7 months (September 2001). Salinity, temperature, sigma-0 and oxygen profiles for the center stations as the eddy ages are shown in Figure 3.3. During the winter, the depth of the mixed layer (determined as the depth where the change in sigma-0 between the surface and depth is 0.125 units; Levitus, 1982) was approximately 80-90m. During the June and September Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 103 142*W 140"W 138*W 136W 134 "W 132"W 130V/ '•42W 140W 138"W "!36"W 134"W 132VV 130V,' I » ' I ! 1 1 8 I '•' ! 1 1 ' " f •30-274441.18.15-12 -9 -6 4 0 3 8 9 12 15 18 21 24 27 30 Figure 3.2. Sea surface height anomaly plots showing the merger of a smaller, younger eddy with Haida-00 in June 2001. Plots produced by the Colorado Centre o f Astrodynamic Research (CC A R ) using T O P E X / P O S E I D O N - E R S - 2 radar altimetry data. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 104 cruises, the mixed layer was approximately 30m. Between these two sampling times, an even greater shoaling of the mixed layer due to summer insolation was expected, but by September the mixed layer depth was back to approximately 30m. The oxygen profiles show a decrease with depth but an oxygen minimum does not occur within the eddy. The surface waters of the Haida eddy were not as isolated from interactions with surroundings as the core of the eddy. During periods of high winds, waters in the shallow mixed layer were determined to be transported laterally across the eddy (Mackas et al., 2005). Although some lateral advection occurred, surface mixed layer salinity and nutrient concentrations at the eddy center stations remained chemically different from surrounding waters during the first year of evolution (Peterson et al., 2005). This suggested that surface waters at the center of the eddy remain isolated for months at a time (Yelland and Crawford, 2005), which resulted in differences in nutrient drawdown between eddy and non-eddy waters (Peterson et al., 2005). This isolation allowed for the analysis of changes in dissolved iron concentrations in surface waters over time. 3.3.2. Newly Formed Haida Eddy In February 2001, a newly formed eddy was sampled at five depths and the depth profiles of the dissolved metals are shown in Figure 3.4. Although the mixed layer depth was approximately 90m in the newly formed eddy (Figure 3.3a), there was some structure in the dissolved metal distributions in that layer. Dissolved aluminum in the surface layer was elevated, with a range of 7.8 - 10.8nM, which decreased to 3.6 ± 0.2nM by 400m. The maximum was observed at a depth of 75m (Figure 3.4a). Dissolved cadmium concentrations in the surface layer were similar to the concentrations measured in Hecate Strait, ranging from 0.24 to 0.40nM (Figure 3.4b). The cadmium depth profile was nutrient-like, with a dissolved concentration of approximately 0.78 ± 0.04nM at 400m. The dissolved copper profile within in the surface mixed layer was most similar to the dissolved aluminum profile, with a sub-surface maximum of 2.8 ± 0.1 nM at 75m and lower values (from 1.56nM to 1.65nM) in the surface waters (Figure 3.4c). Dissolved copper decreased with depth from the sub-surface maximum, but unlike aluminum, the dissolved copper concentration at 400m (2.2 ± 0.1 nM) was still larger than the surface values. The dissolved manganese profile also showed a sub-surface maximum within the surface mixed layer, with a maximum concentration of 3.5 ± 0.2nM at a depth of 40m Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 105 Figure 3.3. Temperature, salinity, density (represented by sigma-0) and oxygen data for different cruises, a) Haida-01, February 2001; b) Haida-01, June 2001; c) Haida-01, September 2001; d) Haida-00, September 2000; e) Haida-00, February 2001; f) Haida-00, June 2001; g) Haida-00, September 2001. a) Temperature (°C) b) 0 2 4 6 8 10 12 14 16 i 1 1 1 1 1 i „J i Oxygen (nmol/kg) 0 50 100 150 200 250 300 350 Temperature (°C) 0 2 4 6 8 10 12 14 16 i 1 1 1 1 i i i i Oxygen (nmol/kg) 0 50 100 150 200 250 300 350 200 A 400 a. Q 600 800 H 1000 I I I c.. \ — • — ' ) / \ / / w / / =: ^ / x / 1 / x 1 / x 1 1 1 / 1 / 1 / 1 / I \ \ \ \ \ \ \ \ \ \ i 200 400 Q. Q 800 1000 / / V / / i \ / / ;\ 1 \< / / \ / / \ 1 \ 1 . \ 1 / 1 / \ : \ 1 / 1 / i / \ \ 32.0 32.5 33.0 33.5 34.0 34.5 35.0 32.0 32.5 33.0 33.5 34.0 34.5 35.0 Salinity Salinity c) 24 25 26 27 28 Sigma-0 Temperature (°C) 0 2 4 6 8 10 12 14 16 I 1 I I 1 I I I I Oxygen (nmol/kg) 0 20 40 60 80 100 120 140 160 180 24 25 26 27 Sigma-6 28 d) 200 H £ 400 Q. a 6oo 800 1000 • i. ' ' I I j ' _ \ - 'T'\ ' / !\ / / '\ / / \ / / \ \ I \ 1 / ' \ I ' l l \ \ \ \ \ \ _ M Temperature (°C) 0 2 4 6 8 10 12 14 16 I 1 1— 1 1 1 L 1 1 Oxygen (nmol/kg) 0 50 100 150 200 250 300 350 32.0 32.5 33.0 33.5 34.0 34.5 35.0 Salinity 32.0 32.5 33.0 33.5 34.0 34.5 35.0 Salinity 24 25 26 27 Sigma-6 28 24 25 26 27 Sigma-9 28 Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 106 e ) Temperature (°C) 0 2 4 6 8 10 12 14 16 Temperature (°C) _ i I i Oxygen (umol/kg) 0 50 100 150 200 250 300 350 0 2 4 6 8 10 12 14 16 i 1 1 1 i i i ' • Oxygen (umol/kg) 0 50 100 150 200 250 300 350 200 400 Q. <U Q 600 800 1000 1 ~—1 1 ,—1 / " ' " " - ^ / / A / / \ \ / / \ / / \ / / \ / / \ - / / \ / / \ \ j / \ \ 1 1 / \ \ \ - J — J — r — i ( \ \ — M 32.0 32.5 33.0 33.5 34.0 34.5 35.0 Salinity 32.0 32.5 33.0 33.5 34.0 34.5 35.0 Salinity 24 25 26 Sigma-0 27 28 24 25 26 27 Sigma-0 28 Temperature Salinity Density Oxygen (Figure 3.4d). There was an increase in dissolved manganese between 75m and 400m, which might reflect a sediment source but since only one depth below the mixed layer was sampled, it is difficult to be certain. The dissolved iron profile from Johnson et al., 2005 was similar to the dissolved manganese distribution in the mixed layer, with a sub-surface maximum of 4.8 ± 0.2nM at 40m (Figure 3.4e). Below the surface mixed layer, unlike manganese, dissolved iron concentration decreased from 1.8 ± 0.09nM at 75m to 1.1 ± 0.05nM at 400m below the surface. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 107 500 - 1 1 Figure 3.4. Depth profiles of dissolved a) aliiminum, b) cadmium, c) copper, d) manganese, and e) iron in the newly formed Haida-01 eddy, sampled in February 2001 off the coast of the Queen Charlotte Islands, British Columbia. Dissolved iron data supplied by W.K. Johnson, Department of Fisheries and Oceans, Canada. Data points without error bars have an error that is smaller than the symbol size. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 108 3.3.3. Changes in Surface Mixed Layer The surface mixed layer of the Haida eddy was treated as an isolated parcel of water during the rest of this paper. Although there may have been some exchange between the Haida eddy surface waters and the surrounding waters, this exchange was limited at least during the first year of evolution (Yelland and Crawford, 2005; Chierici et al., 2005). In the following sections, explanations of changes from 0 to 7 months will be in reference to the Haida-01, whereas changes after 7 months will refer to samples collected from Haida-00. 3.3.3.1. Aluminum In February of its natal year, Haida-01 had a surface mixed layer concentration of approximately 8.9 ± 0.4nM. As the eddy aged, the surface mixed layer concentration decreased until it reached a concentration of 1.4 ± 0. InM at an age of 19 months, which was lower than the surface concentrations in the surrounding waters (3.0 ± 0.2nM measured at the reference station, Figure 3.5a). The rate of removal of aluminum from the surface waters decreased as the eddy aged, with the highest removal rate during the 0 to 4 month range (February to June; Table 3.4). Although the rate of removal decreased over time, the percent decrease of dissolved aluminum within Haida-00 was still high during the spring bloom of its second year (2001), with a 34% removal during the 12 to 16 month period (February to June), versus a 2 to 26% removal over the other times sampled. 3.3.3.2. Cadmium As the eddy aged, the dissolved cadmium concentrations in the surface mixed layer changes were similar to the changes in dissolved phosphate concentrations (Figure 3.5b and 3.5e). At an age of 0 months (February) the concentration in the surface waters was 0.27 ± 0.0InM, which was almost half the average surface concentration measured in Hecate Strait source waters (0.48 ± 0.03nM, MT08 and MT10). By 7 months (September), the concentration of dissolved cadmium decreased in the surface layer to 0.04-0. lOnM, which was similar or below the dissolved concentrations measured in the surrounding waters. Over the winter (7 to 12 months), the mixed layer deepened to approximately 90m (Figure 3.3e), which resulted in the dissolved cadmium Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 109 Figure 3.5. Average dissolved concentrations of a) aluminum, b) cadmium, c) manganese, d) copper, e) phosphate, f) silicate and g) iron in the surface mixed layer of the Haida-00 (full circle) and Haida-01 (empty circle) over the sampling period. 0 months refers to February of the formation year, and age is calculated from that time. Full triangles indicate concentration of dissolved metal in the surface mixed layer of the waters surrounding, but not in direct contact, with the eddy. The dashed line indicates surface values for open ocean water, measured at Ocean Station Papa (50° N, 145° W) in September 2002. Dissolved iron data supplied by W.K. Johnson, Department of Fisheries and Oceans, Canada. Dissolved nutrient (phosphate and silicate) data provided by T. D. Peterson, University of British Columbia, Canada. a^  b> U . 5 < 5 T J < ( O O Z Q - 5 I L 2 < 2 T T < ( 0 o U - 2 < 5 4 T < ( O O Z Q " L . 5 < 5 T T < » ) Age of Eddy (months) Age of Eddy (months) c) lL2<5nn<(0O2Qnk5<5-i-)<ll)O u . S < 5 ^ ^ < W O Z Q ™ l T S < 5 ^ ^ < o o O 5 10 15 Age of Eddy (months) 5 10 15 Age of Eddy (months) Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 110 o.o-l , , , 1 0 5 10 15 20 Age of Eddy (months) concentrations at 12 months (February2001 for Haida-00) to be similar to the values measured in the newly formed eddy at 0 months. By September of the second year (eddy age of 19 months), the dissolved cadmium concentration was found to be lower than the concentration measured during the September of the first year (0.032 ± 0.002nM at 19 months versus 0.041 ± 0.002nM at 7 months). By an age of 19 months, the Haida-00 eddy had traveled into a HNLC region. Due to the high concentrations of dissolved cadmium (and other nutrients) within the surface waters of HNLC regions, the eddy had surface dissolved cadmium concentrations 0.28nM lower than the dissolved cadmium Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 111 Month Range Aluminum Cadmium Manganese Copper Iron 0to4 Rate -60 ± 7 -0.7 ±0.1 9 ± 1 -8 ± 2 -29 ± 1 % Change -72% -26% 30% -47% -96% 4 to 7 Rate -5 ± 7 -0.8 ±0.1 -17 ± 1 9 ± 1 1.3 ±0.1 % Change -23% -46% -47% 113% 134% 7 to 12 Rate -0.5 ± 1 1.8 ±0.1 2.4 ± 0.4 -14.5 ±0 .9 -0.93 ± 0.04 % Change -2% 626% 25% -59% -70% 12 to 16 Rate -9 ± 2 -0.5 ±0.1 0.2 ± 0.6 -0.8 ± 0.6 0.37 ± 0.03 % Change -34% -20% 2% -6% 74% 16 to 19 Rate -5 ± 2 -1.9 ±0.1 8.2 ± 0.8 -2.7 ±0 .6 -0.07 ± 0.04 % Change -26% -86% 55% -21% -8% Table 3.4. Rates of change in mixed layer dissolved metal concentrations over sampling periods. Rate of change given in pM day"1; positive means gain in dissolved metal concentration; negative sign indicates removal of dissolved metal. Percent change is calculated as change in dissolved metal between sampling times divided by the dissolved concentration determined at the earlier sampling time: % Change = ([M]^- rMWO/'M]^ measured at the September 2001 reference station. The decrease in cadmium was accompanied by a decrease in other nutrients, including phosphate (Figure 3.5e). During the year, the percent removal of dissolved cadmium from surface waters was greater than the percent phosphate removal and this was apparent in the change in the ratio of cadmium to phosphate in the surface waters from 0.22 - 0.23nmol Cd/umol P during the winter sampling in February to 0.09 -0.13nmol Cd/umol P at 7 months and 0.04nmol Cd/umol P at 19 months (Table 3.5). 3333. Manganese Changes in the mixed surface layer dissolved manganese concentrations were more complex that for aluminum or cadmium (Figure 3.5c). At 0 months of age (February), the concentration of manganese in the surface mixed layer was Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 1 Cd/P (nmol/umon Aae (months) Date Haida-00 Haida-01 0 February 0.23 4 June 0.24 7 September 0.09 0.13 12 February 0.22 16 June 0.23 19 September 0.04 Reference Stations Cd/P (nmol/umon Ocean Station Papa (50.0°N, 145.0°W) 0.22 MT08 (50.0°N, 130.4°W) 0.49 MT10(53.6°N, 130.7°W) 046 Table 3.5. Cadmium to Phosphate ratios in surface mixed layers, in nmol Cd/umol P. Cd/P ratios in surface mixed layers at reference stations sampled in September 2002 given for comparison purposes. approximately 3.21 ± 0.02nM. During the first spring bloom, the concentration of dissolved manganese increased to 4.2 ± 0.2nM (measured in June at 4 months), but then decreased over the summer to 2.2 ± 0. InM (measured in September at 7 months). From 4 to 7 months of age (June to September), the concentration of manganese in the dissolved layer decreased, at a rate of 17 ± l p M day"1 (Table 3.4). This decrease was then followed by an increase in dissolved manganese concentrations from 7 to 19 months of age, with an increase of 0.33 ± 0.06nM between 7 and 12 months (September 2000 and February 2001) and an even larger increase between 16 and 19 months (June and September 2001) of 0.87 ± 0.09nM. 3.3.3.4. Copper During the first year of the eddy's existence, the dissolved copper concentration decreased between February and June (0 to 4 months, Figure 3.5d). This removal corresponded to 8 ± 2pM day"1 removal rate, and reduced the dissolved copper Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 113 concentration by 47% (Table 3.4). By 4 months, the dissolved copper concentration measured in Haida-01 (1.0 ± 0.2nM) was similar to the waters surrounding the eddy at the time (1.26 ± 0.07nM). Over the first summer (June to September/4 to 7 months), the dissolved copper concentration more than doubled in the surface mixed layer. This resulted in the measured dissolved copper concentration within the eddy surface waters to be greater than the open ocean value (1.18 ± 0.06nM), but still smaller than what was measured at the reference station (5.1 ± l.OnM). From 7 to 12 months of age (September to February), the dissolved copper once again decreased in surface waters, at a rate of 14.5 ± 0.5pM day1. Between February and June (12 to 16 months) of the second year, there was a small decrease in average dissolved copper concentrations from 1.43 ± 0.07nM to 1.34 ± 0.07nM. By 19 months (September), the dissolved copper measured in surface waters had decreased to 1.05 ± 0.05nM, a value lower than the surrounding non-eddy waters (1.4 ± 0.8nM). 3.3.3.5. I ron Johnson et al., 2005 measured total dissolved iron in the surface mixed layer for Haida-00 and Haida-01 (Figure 3.5g). The concentration of dissolved iron in the mixed surface layer in February of the year of formation was 3.2 ± 0.2nM. Within the first four months, the surface mixed layer concentration decreased to 0.11 ± O.OlnM, which was equal to a removal rate of 29 ± lpM day"1. By the age of 7 months (in September) the dissolved iron concentration in Haida-01 had increased to 0.27 ± O.OlnM, which was approximately 0.1 OnM higher than the surrounding waters. By an age of 9 months (September 2000), Haida-00 surface waters had a concentration similar to the surrounding waters. Another decrease in dissolved iron concentration occurred from 7 to 12 months (September 2000 to February 2001). This decrease resulted in a surface dissolved iron concentration of 0.056 ± 0.003nM, which was slightly lower than the concentration usually found within HNLC waters, such as Ocean Station Papa (Maldonado and Price, 1999; Nishioka et al., 2001). Within the second spring (12 to 16 months) the iron concentration increased slightly to 0.098 ± 0.005nM, followed by a slight decrease over the summer to a dissolved concentration of 0.090 ± 0.006nM. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 114 Values measured in Haida-00 after 12 months were similar to the values measured at the reference stations. 3.4. Discussion 3.4.1. Major Controls on Tracer Distributions 3.4.1.1. Aluminum The major controlling factor on the dissolved aluminum concentration in the eddy surface mixed layer was scavenging to particles, as the concentration of dissolved aluminum continually decreased with time. This suggested that there was no input of dust during the sampling period. The removal of aluminum from the dissolved phase occurred between all sampling times, although a faster relative rate of removal occurred during phytoplankton blooms (Table 3.4). During these periods, chlorophyll concentrations measured from SeaWIFS data show increased production in the center of the eddy with respect to the surroundings (Crawford et al., 2005). Although the blooms result in higher particle concentration and therefore more scavenging (60 ± 9pmol day"1 first spring bloom and 9 ± 2pmol day"1 during second spring), there were still enough particles in the surface mixed layer during the summer (June to September) to remove aluminum at a rate of approximately 5pM day"1 (Table 3.4). 3.4.1.2. Cadmium Surface layer dissolved cadmium concentrations were dependent on both biological and physical conditions. The removal rate of cadmium was found to be higher between June and September for both years (Table 3.3). This was unexpected since major nutrients, such as phosphate, had higher removal rates during the spring blooms versus the summer months (Figure 3.5f). The lower aluminum removal during the summer months (Table 3.3) suggested a decrease in surface water particle concentration and flux. A decrease in particle flux, coupled with the reduced growth over the summer (Crawford et al., 2005), suggested that the summer growth had higher cadmium requirements than the spring bloom. In the second year, a similar increase in removal rate over the summer months (16 to 19 months) occurred, but the rate was larger (1.92 ± 0.06pM day"1). The increase in cadmium uptake could be a result of lower zinc bioavailability, but organic Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 115 speciation measurements determined that zinc was not limited, at least during the first year of eddy evolution (M. Lohan, pers. comm.). Another possible cause of increased cadmium uptake is iron limitation (Sunda and Huntsman, 2000; Cullen et al., 2003). Shipboard incubation experiments performed by Cullen et al., 2003 found that iron limited phytoplankton preferentially take up cadmium relative to phosphate, resulting in a lower C0VPO4 ratio in surface waters. By June of each year, the average concentration of dissolved iron ranged from 0.09-0.1 InM, which was slightly higher than the values measured within HNLC waters (0.06-0.07nM). This suggested that at least during June, iron might not have been limited, although without organic speciation measurements it cannot be confirmed. Over the year, the C0VPO4 ratio decreased in surface waters (Table 3.4). The ratio decreased from 0.23nmol Cd/umol P at 0 months to 0.13 by the 7 months. Over the winter months, the mixed layer depth deepened, which increased the dissolved cadmium and phosphate in surface waters, and returned the C d : P 0 4 ratio to 0.22nmol Cd/pmol P . During the second year, dissolved cadmium concentrations again decreased over the bloom period, at a rate slightly lower than the first year, which was to be expected due to less phytoplankton growth occurring during the second spring bloom. Over the second summer, the rate of decrease in dissolved cadmium in surface waters was larger than all other measured decreases (Table 3.3). This could be a result of the merger of the Haida-00 eddy with the younger, smaller one which either a) had lower cadmium in its surface waters, since the merger occurred after the spring bloom, or b) the influx of coastal water stimulated phytoplankton growth thereby drawing down cadmium. If the new eddy has similar growth dynamics to the Haida-00 and Haida-01 had in their natal year, the expected concentration of dissolved cadmium within the younger (approximately 0.20nM) would not have decreased the mixed layer surface concentration to the values measured in second September (19 months age). This means there was still drawdown of cadmium during this time. The coastal water influx could have increased the phytoplankton growth that resulted in cadmium drawdown. Since this drawdown resulted in the C d : P 0 4 ratio dropping to 0.04nmol Cd/umol P , this growth could possibly be iron or zinc limited. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 116 3.4.1.3. Manganese The changes in dissolved manganese concentrations, as the eddy ages, are more complex than the changes in dissolved aluminum or cadmium. Physical mixing, oxidation-reduction reactions and biological uptake all play a role in the distribution of manganese in the eddy over the two years of sampling. During the first year of the eddy lifetime, dissolved manganese concentrations increased between February and June in the surface waters of the Haida-01 eddy (Figure 3.5c). This increase could be attributed to either mixing with surrounding waters with higher manganese concentration, dust deposition or in-situ photo-reduction of manganese oxides (Sunda et al., 1983; Sunda and Huntsman, 1988). The reference station had lower manganese concentrations (3.5 ± 0.2nM) than what was found in the Haida-01 eddy center in June (4.2 ± 0.2nM) so mixing with ocean waters could be ruled out as the major source. Dust deposition would have also resulted in an increase in dissolved aluminum, which did not occur (Figure 3.5a). This increase may have been caused by the photo-reduction of the manganese oxides. A source of these manganese oxide particles could be small sediment particles that were re-suspended and transported to the surface during eddy formation. The slow reduction of manganese oxide particles could result in a delay in the dissolved manganese signal, as occurs off the coast of California during upwelling events (Chase et al., 2005). Manganese is a required nutrient (Brand et al., 1983; Coale, 1991; Sunda and Huntsman, 1998), but uptake in surface waters during the April bloom was not evident from dissolved manganese concentrations measured in February and June. Between 4 and 7 months (June and September) a decrease in dissolved manganese surface concentrations occurred. This removal resulted in a dissolved manganese decrease of approximately 47%, and gave a removal rate of 17 ± lpM day"1 (Table 3.3). The removal of manganese was higher than what was expected from non-oxidative particle scavenging alone, since the removal is 10 to 20 times higher than the measured removal rate of Cd(lT), a metal with a similar scavenging index (Whitfield and Turner, 1987). If this removal was due only to manganese oxidation, then the formation of manganese oxides would be at a rate of 0.01-0.02nM day"1, which is on same order of magnitude to the rate of O.OlnM/day found by Sunda and Huntsman, 1988 in the upper Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 117 40m of the Sargasso Sea. The decrease in dissolved manganese was probably due to a combination of scavenging, oxidation and biological uptake. In the second year of the eddy lifetime, a slight increase occurred between 12 and 16 months (February to June). This could be a result of less particulate manganese in surface waters to be photoreduced compared to the year of formation. In addition, prior to the merging of the Haida-00 eddy and the newly formed eddy in the summer of 2001, there was some evidence of coastal water being transported offshore due to the combined eddy circulation (Peterson and Harrison, in prep.), which could have supplied the extra dissolved manganese to the surface waters. The increase between 16 and 19 months (June to September 2001) could also be due to the merging of the eddies thereby increasing the dissolved manganese in the eddy. 3.4.1.4. Copper Changes in dissolved copper concentrations are more complex than cadmium, suggesting that processes other than just biological uptake were affecting its concentration. During the first four months after eddy formation, copper was removed from surface waters (Table 3.3). The dissolved copper removal resulted in a 47% decrease in dissolved concentrations. This removal corresponded to an 8 ± 2pM day"1 removal rate, but since copper, in addition to being particle reactive, is also a required nutrient, a faster removal probably occurred during the phytoplankton bloom and a slower removal the rest of the time. Between 4 and 7 months (June to September), there was 113% increase in dissolved copper concentrations in the surface mixed layer. An external source, such as dust, can be dismissed due to the lack of increase in dissolved aluminum and manganese during this time. In addition, this increase occurred during the first summer (from 4 to 7 months of age) for both eddies, suggesting it was an internal process and not one that relied on an outside source. One internal source could be deeper water replenishing the dissolved copper concentration through upwelling. If this was the case, dissolved cadmium concentrations (and other nutrients) in the surface waters should also increase, which was not observed. In addition, the summer insolation should actually cause stronger stratification. The most probable internal source would be the rernineralization of phytoplankton in the surface layer. An increase in dissolved silicate concentrations Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 118 supported this theory, but nitrate or phosphate changes do not. This suggested the possible remineralization of diatoms, combined with phytoplankton growth, which was supported by the drawdown of other nutrients (Peterson et al., 2005) and inorganic carbon (Chierici et al., 2005) measured over this time period. From 7 to 12 months (September to February), the dissolved copper concentration decreased in surface waters at a rate of 14.5 ± 0.9pM day"1. This decrease could be attributed mainly to the second smaller bloom in phytoplankton during October 2000 (Crawford et al., 2005). The rate of dissolved copper removal during this period was larger than the first spring bloom. This may be due to the lower dissolved iron within the eddy after the first bloom which resulted in a higher copper demand to aid in iron uptake (Peers et al., 2005; Maldonado et al., 2006), or the bloom composition was made up of species with higher copper requirements (Quigg et al., 2003). From 12 months to 16 months the removal of dissolved copper concentrations could be attributed to biological uptake. 3.4.2. Iron Surface Dynamics Using information from the temporal changes in dissolved aluminum, manganese, cadmium, and copper concentrations within the mixed layer, the probable causes of the changes in total dissolved iron concentrations are discussed in the following sections. The discussion is broken up into sections based on the age of the eddy. 3.4.2.1. Age: 0 months A comparison of the dissolved iron values found in the surface waters of Hecate Strait (0.23 to 0.48nM, Chong et al., in prep.) and the newly formed eddy (Figure 3.4e) showed that the dissolved iron in the surface waters of the new eddy could not have come only from Hecate Strait waters, so another source of dissolved iron to the eddy was required. The options for an iron source could be river, dust or sediment. The dissolved manganese and iron in the surface mixed layer of the newly formed eddy had a linear relationship, with higher iron values corresponding to higher manganese values (Figure 3.6). Although none of the sources for the high dissolved iron concentration could be ruled out the relationship between the dissolved iron concentration and dissolved manganese concentration suggested that either the source or the processes affecting the Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 119 0 1 2 3 4 Disso lved M a n g a n e s e (nM) Figure 3.6. Linear relationship between dissolved iron and dissolved manganese in surface mixed layer of newly formed Haida-01 eddy. dissolved iron and manganese in the surface waters of the newly formed eddy were probably related. 3.4.2.2. Age: 0 to 4 months In the first four months (February to June), the concentration of dissolved iron decreased in the surface waters (Figure 3.5g). During this time, the major nutrients also decreased (nitrate, phosphate and silicate) due to a phytoplankton bloom that occurred in April-May 2001 (Crawford et al., 2005). This bloom was most likely a bloom of diatoms due to measure nitrate to silicate uptake (Peterson et al., 2005). The dissolved phosphate concentrations in the surface mixed layer decreased from 1.20 ± O.OluM to 0.83 ± 0.01 uM over this time period. If the total phosphate decrease measured was associated with phytoplankton growth, the expected decrease in dissolved iron from nitrate removal was calculated to be 2.78 ± 0.09nM based on a ratio of P0 4 : Fe of 1,000 : 7.5 (from Ho et al., 2003). The expected decrease is 0.28nM less than the measured change of 3.06 ± 0.09nM. The ratio determined by Ho et al., 2003 is an average ratio of phosphate to iron Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 120 in a mixture of coastal and open ocean phytoplankton species under ideal growth conditions. Since Haida-01 traveled from the coast to an open ocean environment during the first spring bloom, the use of the average ratio may be suitable. The difference between the calculated average dissolved iron decrease and the measured decrease requires an additional removal. Three explanations for removal of the excess iron are 1) the phytoplankton community was composed of mainly coastal species that require more iron for growth, or 2) Fe was oxidized and precipitated out, or 3) Fe was scavenged by particles. The composition of the phytoplankton bloom cannot be assessed, but by using changes in other metals the removal of iron by other processes can be assessed. Between February and June, the removal rate of aluminum was high and suggested a large particle flux. This large particle flux could be responsible for non-oxidative removal due to colloidal iron binding to larger particles (greater than 2pm), and being removed from the dissolved phase. Another option of removal is the oxidative removal of iron from the dissolved phase due to Fe (II) being oxidized to Fe (HI), and the subsequent precipitation as iron oxides. The amount of oxidation cannot be assessed, since during this time there was no measurable oxidation of manganese within the surface layer. This has been attributed to manganese oxide reduction in surface waters over the February to June period. Since reduction occurred for manganese and iron and manganese have similar oxidation potentials, the amount of iron oxidized during this period was probably not a significant removal. This suggested that particle scavenging is the method of removal at a rate of 2.6 ± 0.8pM day"1, although it was possible a combination of oxidative and non-oxidative removal occurred. 3.4.2.3. Age: 4 to 7 months Between 4 and 7 months of age, the concentration of dissolved iron in the mixed layer of the surface waters of Haida-01 increased from 0.114 ± 0.006nM to 0.27 ± O.OlnM. During this time, the silicate concentration within the surface waters also increased slightly (0.44pM, Peterson et al., 2005). Since the other major inorganic nutrients (nitrate, phosphate) and dissolved cadmium continued to decrease over this time, some phytoplankton growth occurred. From the increase in dissolved silicate concentration, the growth of diatoms was not likely. Peterson et al., 2005 suggested that the source of the silicate increase could be a silicate flux from below the mixed layer, Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 121 although this did not correspond to an increased flux of cadmium, or other major nutrients. Another option could be that some organic matter produced during the spring bloom remained in the surface waters, and was remineralized over this time span. If the spring bloom consisted of mainly diatoms (Peterson et al., 2005), the rernineralization would result in the release of silicate, iron and copper to different degrees. There would also be a major nutrient (nitrogen and phosphorus) release, but this regenerated source of nitrogen and phosphorus could be reused during the summer phytoplankton growth. The decrease observed for nitrate and phosphate was smaller than what was measured over other time periods, which may have been a result of slower growth over the summer and/or an additional source of nutrients not measured in the dissolved phase at 4 months (June). The increase in dissolved iron in the surface waters followed the increase seen in copper (Figure 3.5d); but they did not increase at the same ratio (Cu.Fe of 7.0:1) as the 0 to 4 month removal (Cu:Fe of 0.23:1). This could be because 1) less iron was incorporated into the phytoplankton during the spring bloom (due to iron limitation) or that the iron released during rernineralization was 2) used in the new growth occurring over the summer, or 3) removed by scavenging or oxidation reactions. These options are difficult to distinguish between given the limited information. For option 1 or 2 the uptake ratios of nitrate to iron would have to vary between the spring and summer growing seasons. The required uptake ratio of phosphate to metal can vary depending on the type of phytoplankton. Quigg et al., 2003 found a correlation between the trace metal requirements and the two major plastid families. The major families, referred to as the red and green superfamilies, differ in their accessory photosynthetic pigment. The green superfamily used chlorophyll b and the red superfamily used chlorophyll c. Quigg et al., 2003 found the red superfamily required more cadmium, manganese and cobalt than the green superfamily, which required more iron, copper and zinc. During the summer, there was a decrease in dissolved manganese and cadmium; and an increase in dissolved iron, copper and zinc (Table 3.3; M.C. Lohan, pers. comm.) within the mixed layer. The change could possibly be a result of a switch in dominant phytoplankton species from the spring bloom to the late summer growth. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 122 Dissolved Iron (nM) 0.0 0.5 1.0 1.5 2.0 2.5 i 1 1 i i i Dissolved Cadmium (nM) 0.0 0.2 0.4 0.6 0.8 1.0 0 - • 50 -100 -E •£ 150 -Q . <D Q 200 -250 -300 - -0 1 2 3 4 Dissolved Copper (nM) Figure 3.7. Dissolved metal depth profiles from Haida-01 in September 2001 for dissolved Cd (full triangle), dissolved Fe (empty circle) and dissolved Cu (full circle). Winter ventilation mixed layer depth shown as dashed line. Data points without error bars have an error that is smaller than the symbol size. 3.4.2.4. Age: 7 to 12 months From September to February, the dissolved iron concentrations decreased in surface waters. During this time period, a second, smaller phytoplankton bloom occurred within Haida-00 (Crawford et al., 2005). This growth could be the reason for the iron decrease. Over this time, copper concentrations also decreased, with a ratio of 15.5 mol Cu/mol Fe. The Cu:Fe ratio was larger than the spring removal ratio, but dissolved iron concentrations were lower than the spring concentrations, and the resulting iron changes could be less obvious due to organic ligands keeping iron dissolved in solution (Rue and Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 123 Bruland, 1995; Wu and Luther, 1995). If the changes in dissolved iron was used for phytoplankton growth, a production of approximately 2 to 5umol C was possible, depending on the level of iron limitation (Maldonado and Price, 1999; Ho et al., 2003). This cannot be confirmed by nutrient drawdown since between the two sampling times, the mixed layer depth deepened to 90m, renewing both macronutrient and dissolved cadmium concentrations in the surface waters. The deepening of the mixed layer depth was not deep enough to renew iron and copper to surface waters, thus a decrease was measured for both these metals over this time period (Figure 3.10). Scavenging of iron was also a possibility since the amount of dissolved aluminum removal was larger over this time period. Oxidation of iron over this time was again not likely since the manganese concentration over this time increased, possibly due to photoreduction mediated by organic matter, although this increase wasn't as large as the spring bloom. 3.4.2.5. Age: 12 to 16 months During the first four months of the second year (February to June), there was a slight increase in the dissolved iron concentration. This increase corresponded to an increase in dissolved manganese concentrations, with a ratio of 0.65nmol Mn/nmol Fe. Sources for this increase could be upwelled water, rernineralization, dust input or coastal input. Upwelled water can be dismissed as a source since nutrients, although in higher concentrations than the previous year did not increase in surface waters. The spring bloom that occurred during this time occurred later than the first year, and since there was no evidence of rernineralization in year 1, it was probably not the cause of the year 2 increase. A dust input should result in an increase in aluminum, which did not occur. Prior to the merger of Haida-00 eddy with a newly formed eddy from the coast of the Queen Charlotte Islands, the two eddies were in contact for a few months. It was hypothesized that during this time, water of coastal origin is transported offshore through eddy edge currents and mixed into the surface waters of the Haida-00 eddy. This is supported by a decrease in salinity during this time (32.7 to 32.5), and evidence of empty neritic diatom tests found in the sub-surface layer of Haida-00 suggests that months of transport and settling had occurred (Peterson and Harrison, in prep.). The increase in dissolved iron, compared to dissolved manganese, was smaller than what would be expected from a Hecate Strait coastal source. The surface waters in Hecate Strait, in Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 124 February, have a ratio of 1.3 for Mn:Fe. This reduction of iron between the coast and what was found in the eddy at four months could be a combination of iron oxidation and uptake for phytoplankton growth. Since the waters combining with the eddy contain high concentrations of coastal diatom tests, which theoretically grew in these waters before transport, a lower iron concentration due to higher iron demand by neritic diatoms (Sunda et al., 1991; Sunda and Huntsman, 1995) might be the cause of this lower than expected iron input. 3.4.2.6. Age: 16 to 19 months Over the final summer of sampling, the dissolved iron concentration in surface waters underwent a slight decrease, from 0.098 ± 0.005nM to 0.090 ± 0.005nM. The stability in the dissolved iron concentrations over this time, near the open ocean values of 0.06-0.07nM, could be attributed to the production of strongly binding organic ligands in the surface waters. This theory could not be tested, since iron speciation was not measured. Although the decrease in dissolved iron was small, it once again mirrored the change in dissolved copper concentration, which decreased by 0.28 ± 0.06nM during this time. After the June sampling, a merger of the Haida-00 eddy with an eddy formed in 2001 occurred. This increase in coastal waters was visible in salinity decreases in the surface waters, along with an increase in manganese concentrations. The aluminum continued to decrease over this period, as did the concentrations of nutrients and cadmium. The decrease in the Cd:P ratio (Table 3.5) and large dissolved copper removal, relative to dissolved iron, suggested that by this time in the eddy lifetime phytoplankton growth within the eddy was iron limited. An increase in dissolved iron was not visible during this merger, but this merger occurred after the spring bloom, which probably reduced the dissolved iron concentrations to less than O.lnM, similar to the concentrations found in Haida-01 after the spring bloom. 3.5. Conclusion The dissolved iron concentration within the surface mixed layer of the Haida eddies was controlled not only by biological processes, but also chemical and physical processes. Sources of iron to the eddy surfaces during the first two years included a Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 125 source of high dissolved iron during eddy formation, and a second infusion of iron from coastal sources during interaction with a newly formed eddy during the second year. Removal of dissolved iron during the first four months was a combination of biological uptake and scavenging, although the importance of oxidative versus particle scavenging could not be determined. Once the dissolved iron concentrations reached the levels of less than 0.20nM, variability in dissolved iron over time decreases. It was suggested that this was due to organic ligand complexation but this could not be confirmed due to lack of information on iron speciation. Dissolved aluminum, manganese, cadmium and copper distributions aided with the determination of the controlling factors on dissolved iron. The directional change in dissolved iron in the surface mixed layer over the two years followed dissolved copper dynamics, except during the interaction of Haida-00 with the newly formed eddy. This was expected since both metals are required for biological growth and are prone to scavenging. The changes in dissolved iron were found to be inversely related to dissolved manganese changes, with the only one exception, an input of coastal water from the merging an older eddy with a younger eddy caused both dissolved metal concentrations to increase. Manganese was found to be a suitable tracer of external iron inputs but surface water controls on dissolved manganese distribution did not give information on processes controlling dissolved iron in the surface mixed layer. Dissolved aluminum and dissolved cadmium gave information about particle scavenging and biological uptake respectively. These tracers gave a picture of dissolved iron removal, where scavenging and biological uptake played a role wthin the first 4 months. Analysis within the isolated environment of the surface eddy waters aids in the tracking these changes over a long two-year sampling period. One problem faced was that the time scale on which the controlling processes operate was much smaller than the time between eddy sampling. Sampling more frequently, or at times when rapid changes are expected, such as immediately before and after the first spring bloom could overcome this problem. Chapter 3: Controls on Dissolved Iron in surface waters of Haida Eddies 126 3.6. References American Public Health Association, American Water Works Association and Water Environment Federation, 1998. Standard Methods for the Examination of Water and Wastewater, 20th edition. 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Deep Sea Research Part H - Topical Studies in Oceanography, 52(7-8): 875-892. 132 CHAPTER 4: PROCESSES CONTROLLING TRACE M E T A L DISTRIBUTIONS WITHIN T H E SUB-SURFACE WATERS OF A HAIDA EDDY 4.1. Introduction Trace metal distributions provide information about the biological, chemical and physical processes that occur in the ocean. Major processes that control reactive trace metal concentrations within the ocean are phytoplankton uptake, organic re-mineralization, particle exchange, oxidation-reduction reactions, and the physical mixing and circulation of the ocean. Ideally, the effect of these processes could be studied in a controlled environment, where the effects could be quantified over time in an isolated water mass. It is difficult to track water masses over time however, due to physical mixing and advection. Large-scale enclosure studies and labeling water masses with tracers, such as sulfur hexafluoride (SFe) are two ways water has been tracked in the past. Large-scale enclosures overcome the problem of tracking a water mass by confining it, although problems due to interactions with enclosure walls occur (Confer, 1972; Eppley et al., 1978; Dudzik et al., 1979; Chen and Kemp, 2004). Injection of a tracer such as SF6 allows for tracking water masses although over time signal dilution and subduction of water masses do occur (Law et al., 1998; Watson and Ledwell, 2000). An oceanographic feature that remains relatively intact for some time are mesoscale eddies that form at ocean current boundaries. These eddies trap water within the center of the eddy, and can transport chemically and physically distinct waters for months or years, depending on the type of eddy, the location of formation and direction of travel (Olson, 1991). With the advent of satellite altimetry tracking a large eddy over time is now possible. In 2000 and 2001, a series of cruises were undertaken to study the physical, chemical and biological processes occurring within large eddies that form off the coast of British Columbia and travel westward into the Gulf of Alaska (Miller et al., 2005). This project allowed for the study of processes affecting trace metal distributions as coastal water ages. Results from this study have shown that these eddies transport large amounts of heat and fresh water (Crawford, 2005), and that the core of the eddy remains Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 133 chemically distinct from surrounding waters in terms of nutrients (Peterson et al., 2005) and iron content (Johnson et al., 2005), for at least two years. In this chapter a physical mixing model for the sub-surface waters of the Haida 2000 eddy is presented, and trace metal concentrations are predicted from the physical mixing. Finally, the predicted trace metal concentrations are compared to the measured values and the processes controlling the dissolved metal distributions are discussed. 4.2. Methods 4.2.1. Trace Metal Sampling Sampling was performed over a 15-month period, from June 2000 to September 2001, in conjunction with the Institute of Ocean Sciences, Department of Fisheries and Oceans, Canada. The Haida eddies were first located by sea surface height (SSH) anomaly images determined from TOPEX/Poseidon and ERS-2 altimetry data supplied by the Colorado Centre of Astrodynamics Research (CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer). Once in the region of the eddy, CTD profiles were performed along a transect of the eddy and the "center" and "edge" stations were determined. The center of the eddy was selected at the site of maximum downward isotherms (Whitney and Robert, 2002; Yelland and Crawford, 2005) and the edge station was selected as the site with the greatest slope of isopycnals between 200 and 500m and the swiftest currents (Yelland and Crawford, 2005). Another station, selected at a distance away from the eddy so as to not to be affected by eddy circulation, was also sampled during each cruise to supply information about waters surrounding the eddy. The location of the station, referred to in this text as a reference station, was different from one cruise to another. All station locations are shown in Figure 4.1. Trace metal depth profiles, down to depths of 1000m, were collected at the center and reference stations. All handling of surface samples was performed within an on-deck PVC ultra-low penetration air filter (ULPA) clean hood. Surface samples (10,25 and 40m) were collected using an air-driven double bellows Teflon® pump (Asti) and a Teflon® sampling tube. Surface samples were pumped through a 0.22um Opticap™ cartridge filter, and collected within the on-deck clean hood. Samples from 75m depth and deeper were collected using clean 10-, 12- or 30-L GO-FLO® bottles (Teflon®-lined, Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 134 Longitude, W Figure 4.1. Sample locations. Empty circles denote Haida-00, empty diamonds denote Haida-01, and full triangles denote reference stations. Time o f sampling denoted by numbers below (or to the side) of the location symbol: 1 - June 2000; 2 - September 2000; 3 - February 2001; 4 - June 2001; and 5 - September 2001. General Oceanics) attached to a Kevlar®-line and triggered using solid Teflon® messengers (for specifics, see Johnson et al. , 2005). Samples collected using the G O -FLO® bottles were filtered using a 0.22um Opticap™ cartridge filter that was connected to the G O - F L O bottle spigot. The filtered seawater was collected in acid-cleaned 500mL L D P E bottles and acidified within the on-deck clean hood to a p H < 2 using 6 N Q-HC1 and stored until analysis. A n exception to this sampling procedure was the June 2000 samples. They were collected in acid-washed 125mL high-density polyethylene (HDPE) bottles in triplicate and frozen. On shore, the samples were defrosted and filtered through an acid-washed 0.22um polycarbonate filter (45mm diameter, A M D Manufacturing Inc.) by suction filtration inside a Class 100 Laminar flow hood. Approximately 375mL o f filtrate was combined in acid-cleaned 500mL low-density polyethylene ( L D P E ) bottles and acidified to p H < 2 using 6 N quartz distilled hydrochloric acid (Q-HC1, Seastar Baseline®). Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 135 4.2.2. Trace Metal Analysis Seawater samples were pH adjusted to 7.0 ±0 .1 using concentrated ammonium hydroxide (Q-NH3, Seastar Baseline®) and acetic acid (Q-HAc, Seastar Baseline®). The pH-adjusted seawater was dripped through 2mL of Chelex® 100 using a flow rate of 0.80±0.02 mL/min. The column was then rinsed with 6mL of 0.3M Q-NH4AC buffer (pH of 7) and 4mL of pH-adjusted high purity, deionized water (18MQ cm, Millipore Milli-Q, Bedford, MA, USA). The concentrated metals were then eluted using lOmL of 2N quartz distilled nitric acid (Q-HNO3, Seastar Baseline®). The eluent was concentrated again by evaporation, and brought up in 4 m L of 1% Q-HNO3. This resulted in an overall concentration factor of approximately 125; except for the June 2000 samples, which were brought up in 3.5mL with a concentration factor of approximately 95. Column recovery tests were performed using spiked seawater solutions made using certified lOOOppm Atomic Absorption standards (Delta Scientific Lab Products). The column recoveries were determined to be 110 ± 13% (n = 16) for duminum, 104 ± 7% (n = 36) for cadmium, 96 ± 5% (n = 34) for copper, and 108 ± 6% (n = 23) for manganese. The concentrated eluent was analyzed on a Varian SpectraAA 300/400 atomic absorption spectrophotometer equipped with a graphite tube atomizer and Zeeman background correction. Quantification was performed using the auto-sampler and standard addition calibration. For the aluminum analysis a 2% w/w EDTA and 0.2% Titron-X chemical modifier was used to reduce calcium interference (Matsusaki and Sata, 1994; Volynskii, 2003). Cadmium, copper and manganese analysis were performed using a graphite furnace equipped with a platform to allow for higher ashing and atomization temperatures. The manganese analysis required the use of a 0.1% palladium (w/w) in 1% nitric acid modifier to reduce matrix interferences (Qiao and Jackson, 1991). 4.2.3. Data Analysis Error on sample concentrations was found to be < 5% for the samples run in triplicate or a higher number of replicates. The percent error decreased as concentration of the metal in the sample increased, but due to the limited number of replicate samples analyzed a 5% error was assumed on all data unless otherwise specified. The instrumental limit of detection (Table 4.1) was calculated as 3.129 times the standard deviation of the blank Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 136 (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). A method detection limit was determined by running replicate samples of a bulk seawater sample through the entire procedure and determining the standard deviation of the sample concentrations (American Public Health Association, American Water Works Association and Water Environment Federation, 1998). All seawater samples analyzed were found to have dissolved metal concentrations above both the instrument limit of detection and the method detection limit. A certified reference material, CASS-3 (Certified Atlantic Surface Seawater - 3; National Research Council of Canada), was analyzed to test the accuracy of the cadmium, copper and manganese analysis. The reference material was run in triplicate and the results, with a comparison to the certified values, are listed in Table 4.2. Aluminum data was also measured but no certified value for comparison was available. Dissolved cadmium, copper, and manganese were all determined to be within the error limits of the certified reference values. Aluminum Cadmium Copper Manganese Average percent error Error = ts/Vn 4% 5% 3% 5% Lower Level of Detection L.O.D. = 3.29(s of blk) + avg blk 0.098 0.003 0.108 0.037 Method Detection Limit M.D.L. = t(s of sample) + avg blk 0.191 0.006 0.099 0.029 Table 4.1. Percent error (at 95% confidence level), instrument limit of detection and method detection limit for aluminum, cadmium, copper, and manganese. Detection limits are converted to units of nM in original seawater by dividing by concentration factor, "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample). Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 137 Measured Value Certified Reference (M-g/L) Value (ug/L) Aluminum 0.294 ± 0.004 II n Cadmium 0.032 ± 0.002 0.030 ± 0.005 Copper 0.514 ±0.065 0.517 ±0.062 Manganese 2.85 ± 0.25 2.51 ±0.36 Table 4.2. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval. Average core concentration values were calculated by first determining the integrated metal amount over the 40 to 400m depth range, and then dividing the calculated amount by the total depth. Integration values were determined by trapezoidal integration. Errors on the integration values were determined by comparing depth profile to an oceanographic consistent depth profile for confirmation. The average value was determined using all data and the low and high values were determined by excluding data that did not follow oceanographic consistent depth profiles. One exception to this rule was the high values at the sigma-9 of 26.8. Although these values seem erroneous in terms of oceanographic consistency, these values were thought to represent a real signal, given that samples from different sites and on different cruises had consistently high concentrations at that sigma-0. The error on the average values was determined in a similar manner as the integrated values. The error on the graphs was plotted as either the integration error or a 5% error whichever was greater. 4.2.4. Physical Parameters Conductivity, temperature and depth measurements were collected at each station using a Seabird 91 Iplus CTD mounted on a 24-bottle rosette frame. Sigma-0 values were calculated from CTD data. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 138 4.3. Results and Discussion 43.1. Eddy Background The two eddies sampled were formed in the years 2000 and 2001, and will be referred to in the following discussion as Haida-00 and Haida-01 respectively. Haida-00 was sampled 5 times: at 4 months (June 2000), 7 months (September 2000), 12 months (February 2001), 16 months (June 2001) and 19 months (September 2001). After leaving the coast, Haida-00 traveled northwest and by May 2000 had stalled on the Bowie Seamount, approximately 180 km offshore. It remained at the seamount until September 2000, with the center station drifting about 20 km west between the 4-month and 7-month sampling times. Once it left the seamount, it traveled approximately 325 km northwest between September 2000 and September 2001, into an HNLC area. Between June 2001 and September 2001 a younger, smaller eddy from the coast merged with the older, larger Haida-00 eddy. Haida-01, the smaller of the two eddies, took a more southern route from the coast after formation and missed the seamount entirely. Haida-01 was sampled only 3 times: at 0 months (February 2001), 4 months (June 2001) and 7 months (September 2001). By the September 2001 sampling of Haida-01, it had traveled over 200km offshore. 4.3.2. Salinity and Trace Metal Depth Profiles As the eddy traveled west, the salinity within the core of the eddy increased toward the reference station salinity (Figure 4.2a). The salinity measurements for the edge of the eddy were found to be between the values measured for the center and the reference stations. The dissolved trace metal depth profiles varied more with location and time of sampling than the salinity (Figure 4.2 b-e). This was due to additional processes controlling the trace metal distributions within the core of the eddy. The variability within the eddy was taken into account when determining the average trace metal concentrations, with errors on the average reflecting the variability within the depth profile, and between the edge and center stations. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 139 4.3.3. Physical Mixing Model 4.3.3.1. Description of Physical Model The physical mixing model was designed using the salinity data from the Haida-00 eddy. Only the average salinity data from 4 to 16 months was used in the model. A small eddy merged with Haida-00 over the summer of 2001, which was not sampled before the two eddies merged and therefore the effect on the 19-month core salinity could not be quantified. The eddy stations used to determine the average core salinity were the center station and the edge station defined in section 4.2.1. and a station approximately halfway between the edge and center stations (Figure 4.3). The average core salinity at each station was determined by first integrating over the depth range, using trapezoidal integration method, then dividing by the depth range. The average salinity for the eddy core was determined by integration of salinity depth profiles along the radius of the eddy, from the edge to the center stations. The difference in average salinity values between the center station and the edge station within the core was determined to be 0.35% or less for each cruise. The distance between the edge and center station was approximately 55km during each sampling period, with a range of 55.5km to 55.9km. An average radius of 55.7km was used to determine the eddy core volume. The depth of the eddy core was chosen to be from a depth of 40m to a depth of 400m. The depth of 40m was chosen as it was one of the depths that was sampled for trace metals and it was also below the surface mixed layer, except for the February sampling period. The bottom depth of 400m was chosen because in addition to being a sampling depth for trace metal sampling, it also remained shallower or close to the 33.9 isohaline (Table 4.3), which was the highest salinity measured within Hecate Strait, and thus is considered the "bottom" of the eddy. As the eddy aged the average core salinity increased towards the average salinity determined for the reference stations sampled on the cruises (Figure 4.4). Using the change in eddy core average salinity, the volume of seawater exchange required to account for the average core salinity increase could be determined. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 140 Figure 4.2. Depth profiles at the center (full circle), edge (empty circle) and reference station (full triangle) for a) salinity and dissolved b) aluminum, c) cadmium, d) copper and e) manganese for June 2000, September 2000 and June 2001 sampling times. Average concentration value determined by integration plotted as dashed line, with error bars shown at 40 and 400m depths. June 2000 (4 months) a) Salinity Sept 2000 (7 months) Salinity June 2001 f 16 months) Salinity k) Dissolved Aluminum (nM) 0 2 4 6 8 10 12 Dissolved Aluminum (nM) 6 8 10 12 Dissolved Aluminum (nM) 6 8 10 12 c) ' Dissolved Cadmium (nM) 1.5 2.0 0.0 0.5 1.0 DissolvedCadmium (nM) 0.0 0.5 1.0 1.5 2.0 Dissolved Cadmium (nM) 1.0 1.5 2.0 0.0 0.5 500 500 500 Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 141 d) June 2000 (4 months) Dissolved Copper (nM) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Sept 2000 (7 months) Dissolved Copper (nM) 2 4 6 8 June 2001 (16 months) Dissolved Copper (nM) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 500 500 500 e) Dissolved Manganese (nM) 0 1 2 3 4 Dissolved Manganese (nM) 0 1 2 3 4 Dissolved Manganese (nM) 0 1 2 3 4 Cruise Station Depth of 34.0 isohaline (m) Jun-00 Center 547 Edge 432 Sep-00 Center 540 Edge 392 Feb-01 Center 401 Edge 400 Jun-01 Center 408 Edge 395 Table 4.3. Depth (in meters) of the 34.0 isohaline for Haida-00 eddy. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 142 c "to CO 34.0 33.8 33.6 33.4 33.2 33.0 50 60 20 30 40 Distance (km) Figure 4.3. Average core salinity from edge station (0km) to center station (-55.7km) over sampling period. 33.75 33.70 33.45 10 Time (months) 15 20 Figure 4.4. Average eddy core salinity (circles) and average (40 to 400m) reference station salinity (triangles) over sampling period. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 143 Time of months (t) 0 2 4 6 8 10 12 14 16 18 0 -j 1 1 1 1 1 1 1 1 -0.5 --3-" 1 Figure 4.5. Plot of equation 4.2, used to detennine the time constant x and initial salinity in Haida-00 (Si). 4.33.2. Physical Model Results Data was modeled using a simple exponential mixing model: C(t) = C(p)xe~i,T Equation 4.1 where C(t) was equal the difference between the average reference station salinity between 40-400m (SR) and the average salinity of the eddy core (SE) at time = t; and C(o) was equal to (SR) and the initial average salinity of the eddy core at time t = 0 (Si). To determine the value of time constant x and of Si, the natural log of the exponential equation was plotted (Figure 4.5): ln(SR - S E ) = \a(SR -Sj)-- Equation 4.2 T where the slope was found to be -0.084 and a x value of 11.848. The intercept was found to be -1.095 and resulted in a Si of 33.394. This value is within 0.06% of the Haida-01 initial salinity of 33.375. The Haida-01 initial salinity was determined from the eddy Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 144 center station only, whereas the Si value would be representative of average core initial salinity and would therefore expected to be slightly higher. The resulting exponential function: (SR-SE) = (SR-SI)xe ' / ( 1 1 8 4 8 ) Equation4.3 was plotted against the average core salinity data (Figure 4.6) given an R 2 value of0.977. This fit was better than a linear fit, which gave a R 2 of 0.945. Since the equation used to model the change in average eddy core salinity (SE) was an exponential, the determination of the length of the eddy lifetime was not possible to calculate using that equation directly. A plot of SSH anomaly versus the average eddy core salinity was used to determine the average eddy core salinity when the SSH anomaly was equal to zero, and the eddy would no longer be detected (Figure 4.7). The average core salinity that corresponded to SSH anomaly of zero was 33.69 ± 0.14. When this salinity was substituted into the exponential mixing model as SE , a time of 27.97 ± 0.05 months (approximately 2.33 ± 0.04 years) was found. This lifetime value was comparable to the 2 to 3 years suggested by Crawford and Whitney, 1999. From the simple exponential mixing model, the volume exchanged between the eddy and surroundings can be calculated by the following equation: (SR ~ $E ) * VS = (SE ~ 51/ ) * VE Equation 4.4 whereVs is equal to volume exchanged with surroundings, SE is equal to the salinity in the eddy at time = t and SE is equal to the average eddy core salinity. The average core salinity can be calculated by: SE=— \^R-(SR-Sj)*e-t/T dt~ ( S E + S r i Equation4.5 N t=0 2 The average salinity calculated by integration was found to be approximately equal to that determined by using the average salinity calculated from Si and SE at time t. The largest difference between the two calculations occurred at 16 months, and the Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 145 Exponential Curve Fit: S E = S R - (S R -S, re^ / ( 1 1 8 4 8 ) R* = 0.977 Linear Fit: SE = 0.013t + 33.444 R* = 0.945 14 16 0 2 4 6 8 10 12 Time in months (t) Figure 4.6. Comparison of exponential (solid curve) and linear (dashed line) fit for average eddy core salinity versus age of eddy (in months). 18 33.66 33.46 -I , , , , 1 0 5 10 15 20 25 SSH anomaly (cm) Figure 4.7. Plot of SSH anomaly (from CCAR; Global Near Real-Time Sea Surface Anomaly Data Viewer) versus the average eddy core salinity (SE). Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 146 0.0E+00 6 8 10 12 Time in months (t) 14 16 18 Figure 4.8. Plot of the volume of water exchanged with the surroundings (Vs) versus the age of the Haida-00 eddy in months. variation was less than 0.12%. Use of the approximate average salinity equation simplified the Vs calculation: vs = (SE-Sj) (SR-0.5SE-0.5Sj) Equation 4.6 The results of the calculation are plotted in Figure 4.8. The volume exchanged gave a percent of original eddy water that remained at 12 months to be 28%, which was similar to the 28.9% found by Crawford, 2005 in their freshwater calculation. 4.3.4. Physical Mixing Model Predictions After calculating the amount of volume exchanged between the eddy core and the surroundings over time, the expected average trace metal concentrations within the core of the eddy due to the physical mixing was determined. By rearranging the mass balance Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 147 equation (Equation 4.6) and replacing the salinity variables (S) with the concentration of trace metals ( C ) , the expected average dissolved concentration of trace metals within the core of the eddy (CE) was determined by: C e - (VE+0.5VS) Equation4.7 where Q was the average initial dissolved trace metal concentration within the eddy core and C R was the average dissolved trace metal concentration between 40-400m at the reference stations. Since Haida-00 was not sampled in its first month of formation (February 2000) and the eddy core data from February 2001 for Haida-01 included only the 40m and 400m depths, the initial time for the following trace metal concentration predictions was set to the 4 month data. 4.3.4.1. Aluminum As the eddy aged, the average dissolved aluminum concentration within the core of the eddy decreased. A decrease in the dissolved aluminum concentration was expected due to the waters surrounding the eddy having lower dissolved concentrations of aluminum than the core of the eddy (4.7nM in the eddy at 4 months versus 2.2nM in the surroundings). The predicted dissolved aluminum concentration values determined by the physical mixing model were found to be higher than the average dissolved concentration values measured at both 7 and 16 months (Figure 4.9a). The extra removal of aluminum, conesrx>nding to 49% of the overall dissolved aluminum decrease, can be attributed to the removal of the dissolved aluminum by particle scavenging (Orians and Bruland, 1985; 1986). The difference between the decrease in dissolved aluminum concentration due to the volume exchanged and the concentrations measured was found to be (3.9 ± 0.7) x 106 moles between 4 and 7 months, and (5.0 ± 0.3) x 106 moles between 4 and 16 months. This removal corresponds to a removal rate of 11 ± 2pM/day from 4 to 7 months and 4.1 ± 0.2pM/day from 4 to 16 months. The difference in the two rates was due to the 4 to 7 month rate measuring the removal during a period of high particle flux, whereas the 4 to 16 months gives an average removal over an entire year. A residence time for dissolved aluminum using the yearly removal rate was found to be 3.2 ± 0.2years within the eddy Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 148 < 6 8 10 12 14 Time in months (t) 4 6 8 10 12 14 Time in months (t) 4 6 8 10 12 14 16 18 Time in months (t) 4 6 8 10 12 14 Time in months (t) 18 Figure 4.9. Comparison of predicted average eddy core dissolved metal concentrations accounting for physical mixing only (CE represented by solid line) and measured average eddy core concentrations (represented by full circles and error bars) for a) aluminum, b) manganese, c) cadmium and d) copper. core. This removal rate falls within the range of residence times found by other authors (Orians and Bruland, 1986; Jickells et al., 1994; Jickells and Spokes, 2001) although it was on the lower end of the range. The shorter residence time within the eddy can be attributed to the higher productivity, and therefore higher particle flux, within the eddy compared to the open ocean. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 149 4.3.4.2. Manganese The average dissolved manganese concentrations found within the core of the eddy decreased as the eddy aged, similar to dissolved aluminum. The decrease in average dissolved manganese was larger than predicted by the physical mixing model (Figure 4.9b). The extra removal of dissolved manganese was approximately 39% of the average dissolved manganese decrease. The extra removal can be attributed to the scavenging of manganese onto particles due to microbial manganese oxidation (Cowen and Silver, 1984; Tebo and Emerson, 1986; Sunda and Huntsman, 1987) or the passive scavenging onto the surface of organically coated particles (Martin and Knauer, 1980; Balistrieri et al., 1981; Martin and Knauer, 1983). The removal rates were found to be 3.5 ± 0.6pM/day between 4 and 7 months, with a yearly average removal rate of 0.68 ± 0.03pM/day. The removal rates calculated are lower than the dissolved aluminum removal rates, although this expected due to the greater particle scavenging of dissolved aluminum. The rate of removal is smaller than the oxidative removal found by Sunda and Huntsman, 1988 in the surface waters of the Sargasso Sea (lOpM/day). The lower rate within the eddy core waters could be due to less microbial oxidation occurring at depth. Using the yearly removal rate, a residence time of approximately 6.5 ± 0.3years was found. This residence time was shorter than the average residence time found for manganese in deep waters of the North Pacific (60 years, Martin and Knauer, 1980), but is within the range of 3 to 74 years found by Landing and Bruland, 1980 when measuring the variation in dissolved manganese residence times from the coast to open ocean. 4.3.4.3. Cadmium As the eddy aged, the average dissolved cadmium concentration within the core of the eddy increased. The waters surrounding the eddy had higher dissolved cadmium concentrations than the core of the eddy, which resulted in an increase due to physical mixing (Figure 4.9c). The average cadmium concentration measured within the eddy core at 7 months (0.60 ± 0.03nM) was slightly lower than the concentration predicted by the model (0.66nM), but was within error. By 16 months the measured core average cadmium concentration was higher (0.92 ± 0.05nM) than the predicted amount (0.89nM), Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 150 although the predicted value is within the error range of the measured value. From the model predictions it was found that the majority of the dissolved cadmium increase within the eddy core was a result of physical mixing, with any recycling occurring from surface waters to be minimal. 4.3.4.4. Copper The average dissolved copper concentration within the core of the eddy increased as the eddy traveled offshore. An increase in the dissolved copper concentration was expected due to the waters surrounding the eddy having higher dissolved concentrations of copper than the core of the eddy (0.78 ± 0.09nM in the eddy at 4 months versus 1.4 ± 0.07nM in the surroundings). The predicted dissolved copper concentrations determined by the physical mixing model were found to be slightly lower than the average dissolved concentration values measured at both 7 and 16 months, although were found to be not significantly different at 95% confidence level (Figure 4.9d). Similar to cadmium results, it was found that the majority of the dissolved copper increase within the eddy core was a result of physical mixing, with any recycling occurring from surface waters to be minimal. 4.4. Conclusion The physical mixing model for the core of the eddy was found to produce results, such as initial salinity, lifetime prediction, and volume exchanged, with values similar to observations and published estimates from other studies on the Haida 2000 eddy (Crawford and Whitney, 1999; Crawford, 2005). With the use of the physical mixing model, the major controls on trace metals in the eddy core were studied. Average dissolved aluminum and manganese concentrations decreased within the eddy core as it aged. For aluminum it was found that 51% of the average dissolved decrease within core waters was due to physical mixing with surrounding waters, whereas 49% was a result of particle scavenging. For manganese, 61% of the overall decrease in dissolved manganese concentration could be explained by the mixing of the eddy with the waters surrounding the eddy while 39% is presumably due to oxidative scavenging. From the model predictions removal rates for aluminum and manganese Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 151 were determined to be 4.0 ± 0.2 pM/day and 0.68 ± 0.03pM/day respectively. Residence times of 3.2 ± 0.2years for aluminum and 6.5 ± 0.3years for manganese were calculated. Average dissolved cadmium and copper concentrations increased within the eddy as it traveled offshore into waters with higher nutrient concentrations. The average dissolved cadmium and copper concentrations within the core of the eddy increased as the eddy traveled offshore into HNLC waters. For both cadmium and copper, the amount of the dissolved metal concentration increase within the core of the eddy at 16 months was not significantly different from the amount predicted from the physical mixing model. This suggested that within the 40 to 400m core of the eddy any recycling occurring from biological uptake in surface waters was minimal. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 152 4.5. References American Public Health Association, American Water Works Association and Water Environment Federation, 1998. Standard Methods for the Examination of Water and Wastewater, 20th edition. American Public Health Association, Washington, D.C, 1220 pp. Balistrieri, L., Brewer, P. G. and Murray, J. W., 1981. Scavenging Residence Times of Trace-Metals and Surface-Chemistry of Sinking Particles in the Deep Ocean. Deep Sea Research Part A - Oceanographic Research Papers, 28(2): 101-121. Chen, C. C. and Kemp, W. M., 2004. Periphyton communities in experimental marine ecosystems: scaling the effects of removal from container walls. Marine Ecology-Progress Series, 271: 27-41. Confer, J. L., 1972. Interrelations among Plankton, Attached Algae, and Phosphorus Cycle in Artificial Open Systems. Ecological Monographs, 42(1): 1-&. Cowen, J. P. and Silver, M. W., 1984. The Association of Iron and Manganese with Bacteria on Marine Macroparticulate Material. Science, 224(4655): 1340-1342. Crawford, W. R., 2005. Heat and fresh water transport by eddies into the Gulf of Alaska. Deep Sea Research Part II - Topical Studies in Oceanography, 52(7-8): 893-908. Crawford, W. R. and Whitney, F. A., 1999. Mesoscale eddy aswirl with data in the Gulf of Alaska. EOS, Transactions of the American Geophysical Union, 80(33): 365-370. Dudzik, M., Harte, J., Jassby, A., Lapan, E., Levy, D. and Rees, J., 1979. Some Considerations in the Design of Aquatic Microcosms for Plankton Studies. International Journal of Environmental Studies, 13(2): 125-130. Eppley, R. W., Koeller, P. and Wallace, G. T., 1978. Stirring Influences Phytoplankton Species Composition within Enclosed Columns of Coastal Sea-Water. Journal of Experimental Marine Biology and Ecology, 32(3): 219-239. Jickells, T., Church, T., Veron, A. and Arimoto, R., 1994. Atmospheric Inputs of Manganese and Aluminum to the Sargasso Sea and Their Relation to Surface-Water Concentrations. Marine Chemistry, 46(3): 283-292. Jickells, T. D. and Spokes, L. J., 2001. Atmospheric Iron Inputs to the Oceans. In: D.R. Turner and K.A. Hunter (Editors), Biogeochemistry of Iron in Seawater. IUPAC Series on Analytical and Physical Chemistry of Environmental Systems. SCOR-IUPAC, Baltimore, pp. 85-121. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 153 Johnson, W. K., Miller, L. A., Sutherland, N. E. and Wong, C. S., 2005. Iron transport by mesoscale Haida eddies in the Gulf of Alaska. Deep Sea Research Part II -Topical Studies in Oceanography, 52(7-8): 933-953. Landing, W. M. and Bruland, K. W., 1980. Manganese in the North Pacific. Earth and Planetary Science Letters, 49(1): 45-56. Law, C. S., Watson, A. J., Liddicoat, M. I. and Stanton, T., 1998. Sulphur hexafluoride as a tracer of biogeochemical and physical processes in an open-ocean iron fertilisation experiment. Deep Sea Research Part II - Topical Studies in Oceanography, 45(6): 977-994. Martin, J. H. and Knauer, G. A., 1980. Manganese Cycling in the Northeast Pacific Waters. Earth and Planetary Science Letters, 51(2): 266-274. Martin, J. H. and Knauer, G. A., 1983. Vertex - Manganese Transport with CaC03. Deep Sea Research Part A - Oceanographic Research Papers, 30(4): 411-425. Matsusaki, K. and Sata, T., 1994. Removal of Sulfate Interference in the Determination of Indium and Gallium by Graphite-Furnace Aas. Bunseki Kagaku, 43(8): 641-643. Miller, L. A., Robert, M. and Crawford, W. R., 2005. The large, westward-propagating Haida Eddies of the Pacific eastern boundary. Deep Sea Research Part II - Topical Studies in Oceanography, 52(7-8): 845-851. Olson, D. B., 1991. Rings in the Ocean. Annual Review of Earth and Planetary Sciences, 19: 283-311. Orians, K. J. and Bruland, K. W., 1985. Dissolved aluminum in the central North Pacific. Nature, 316(6027): 427-429. Orians, K. J. and Bruland, K. W., 1986. The biogeochemistry of aluminum in the Pacific Ocean. Earth and Planetary Science Letters, 78: 397-410. Peterson, T. D., Whitney, F. A. and Harrison, P. J., 2005. Macronutrient dynamics in an anticyclonic mesoscale eddy in the Gulf of Alaska. Deep Sea Research Part II -Topical Studies in Oceanography, 52(7-8): 909-932. Qiao, H. C. and Jackson, K. W., 1991. Mechanism of Modification by Palladium in Graphite-Furnace Atomic-Absorption Spectrometry. Spectrochimica Acta Part B -Atomic Spectroscopy, 46(14): 1841-1859. Sunda, W. G. and Huntsman, S. A., 1987. Microbial Oxidation of Manganese in a North-Carolina Estuary. Limnology and Oceanography, 32(3): 552-564. Chapter 4: Trace Metal Processes within Sub-surface Waters of the Haida Eddies 154 Sunda, W. G. and Huntsman, S. A., 1988. Effect of Sunlight on Redox Cycles of Manganese in the Southwestern Sargasso Sea. Deep Sea Research Part A -Oceanographic Research Papers, 35(8): 1297-1317. Tebo, B. M. and Emerson, S., 1986. Microbial Manganese(II) Oxidation in the Marine-Environment - a Quantitative Study. Biogeochemistry, 2(2): 149-161. Volynskii, A. B., 2003. Chemical modifiers in modern electrothermal atomic absorption spectrometry. Journal of Analytical Chemistry, 58(10): 905-921. Watson, A. J. and Ixdwell, J. R., 2000. Oceanographic tracer release experiments using sulphur hexafluoride. Journal of Geophysical Research - Oceans, 105(C6): 14325-14337. Whitney, F. and Robert, M., 2002. Structure of Haida eddies and their transport of nutrient from coastal margins into the NE Pacific Ocean. Journal of Oceanography, 58(5): 715-723. Yelland, D. and Crawford, W. R., 2005. Currents in Haida Eddies. Deep Sea Research Part II - Topical Studies in Oceanography, 52(7-8): 875-892. 155 CHAPTER 5: GENERAL DISCUSSION 5.1. Introduction The Haida eddies are a group of mesoscale, anticyclonic eddies that form off the coast of the Queen Charlotte Islands, British Columbia during the winter months. They generally have a diameter of 150 - 300 km, a core depth of 500-600m at the center (core determined by isohaline of 33.9) and can transport between 3000 to 6000km3 of coastal water offshore into the Gulf of Alaska (Crawford, 2002; Whitney and Robert, 2002). An important feature of these eddies is their longevity. The eddy decay process in the Gulf of Alaska is slow; an eddy can retain its coastal signature for up to 3 years before frictional decay causes the eddy to dissipate. Due to the length of time these eddies exist and the rninimal interactions with surroundings, they are an ideal laboratory in which to study the processes affecting trace metal distributions as coastal water ages. 5.2. General Discussion The objectives of this thesis were to 1) use the semi-isolated body of water contained in the mesoscale, anti-cyclonic Haida eddy as a natural laboratory to study the changes in trace metal distributions as coastal waters age and to determine if these mesoscale eddies were a source of dissolved trace metals to the Gulf of Alaska; and 3) use a selection of trace metals to study the processes controlling the changes in dissolved iron concentrations, with focus a on surface water distributions. 5.2.1. Haida Eddy Transport The Haida eddies were found to transport higher dissolved concentrations of the scavenged trace metals offshore. After formation of the Haida-01 eddy, higher concentrations of aluminum (up to 8.5 ± 0.9nM) were measured within the surface waters of the eddy compared to the Hecate Strait source waters. The elevated dissolved aluminum concentration could possibly be due to a sediment source since the elevated values were found within the core of the eddy, at a sigma-0 of approximately 26.8. Dissolved aluminum was found to be transported off the shelf along this isopycnal, with a dissolved aluminum maximum of 7.7 ± 0.4nM measured at a reference station approximately 250km offshore. By 330km offshore the dissolved aluminum maximum at Chapter 5: General Discussion 156 depth was no longer observed. A sub-surface dissolved aluminum maximum was transported within the Haida eddies as well, and was carried within the eddy core. This dissolved aluminum trapped within the eddy core was transported up to 200km farther offshore than the lateral transport along the isopycnal at sigma-0 of 26.8. The amount of dissolved aluminum transported within a Haida eddy was calculated to be between 0.2 to 5 times the amount of dissolved aluminum predicted to be deposited through dust deposition within the area of the Gulf of Alaska that can interact with the Haida eddies. The large range was due to the uncertainty in the amount of dust input and the predicted dust dissolution for the Gulf of Alaska. Recent dust predictions suggest very low dust input into the sub-arctic North Pacific (Measures et al., 2005), which would result in the dissolved aluminum supplied by the eddies to be comparable or higher in magnitude than aeolian dust input to the Gulf of Alaska. Dissolved manganese concentrations within the newly formed Haida eddy, while not larger than Hecate Strait waters, were more concentrated at depth than open ocean waters, and remained higher than Station P values until 7 months. The average dissolved manganese concentrations in surface waters fluctuated over time but never dropped below the average Station P surface concentration, which suggested that the Haida eddies are a source of dissolved manganese to the open ocean. Average dissolved aluminum and manganese concentrations decreased within the eddy core (40 to 400m depth) as the eddy aged. For aluminum, 51% of the average dissolved decrease within core waters was due to physical mixing with surrounding waters, whereas 49% was a result of particle scavenging. For manganese, 61% of the overall decrease in dissolved manganese concentration could be explained by the mixing of the eddy with the waters surrounding the eddy while 39% is presumably due to oxidative scavenging. From the model predictions removal rates for aluminum and manganese were determined to be 4.0 ± 0.2 pM/day and 0.68 ± 0.03pM/day respectively. Average dissolved cadmium and copper concentrations increased within the eddy as it traveled offshore into waters with higher nutrient concentrations. For both cadmium and copper, the amount of the dissolved metal concentration increase within the core of the eddy at 16 months was not significantly different from the amount predicted from the Chapter 5: General Discussion 157 physical mixing model. This suggested that within the 40 to 400m core of the eddy any recycling occurring from biological uptake in surface waters was minimal. Within the surface waters, dissolved cadmium behaved as a nutrient, with removal occurring over the spring and summer months and winter ventilation returning dissolved cadmium concentrations to values found in the surface waters in the first winter. The ratio of dissolved cadmium to dissolved phosphate decreased within the surface water of the Haida eddy over the year, and could be due to 1) dissolved cadmium being taken up faster than phosphate or 2) a faster recycling of dissolved phosphate in surface waters during the year (Boyle et al., 1981; Boyle, 1988; de Baar et al., 1994). Winter ventilation within the eddy resulted in the surface water dissolved Cd:PC«4 ratio to return to a value of 0.23-0.24, which was similar to the ratios found in the North Pacific (Martin et al., 1976; Bruland, 1980; de Baar et al., 1994). The cyclic nature of the Cd:PO*4 ratio, with a larger decrease in dissolved cadmium to dissolved phosphate over spring bloom, may be a result of preferential cadmium uptake due to iron limitation (Cullen, 2006). The fluctuations in the surface dissolved concentrations of copper and manganese were more complex, with oxidation-reduction reactions and biological uptake playing a role in their distributions. 5.2.2. The Study of Iron Dynamics using Tracers The use of aluminum, manganese, cadmium and copper as tracers of dissolved iron dynamics within the surface waters of the Haida eddy was also studied. When there was no evidence of external inputs of iron, the concentration of dissolved iron varied directly with dissolved copper. Although the direction of the changes (increase/decrease) was the same for dissolved iron and dissolved copper, the ratio of Cu:Fe during the changes did not remain constant. This correlation was of interest given recent laboratory studies linking the uptake of iron, specifically when iron is limiting, to copper biological uptake (Maldonado et al., 2006; Peers and Price, 2006). The changes in dissolved iron were found to be inversely correlated with dissolved manganese changes, with the only exception due to a similar input source, from the merging an older eddy with a younger eddy. This suggested that although manganese would be a good tracer of iron inputs, it is not a suitable tracer of oxidation/reduction controls of iron over the sampling period Chapter 5: General Discussion 158 studied. Dissolved alurninum and dissolved cadmium gave information about particle scavenging and biological uptake respectively. These tracers gave a picture of dissolved iron removal, where scavenging and biological uptake played a role within the first 4 months followed by lower dissolved iron controlled mainly by biological uptake/remineralization and possibly organic complexation. Due to the low frequency of sampling, quantification of the chemical, biological and physical controls on the dissolved iron distributions was difficult, although on shorter time scales this suite of metals may provide information of the importance of different dissolved iron controls, including supplies and removals. 5.3. Importance to Field of Study This work is important to the field of trace metal chemical oceanography because it describes a new input mechanism of coastal water and dissolved trace metals to the Gulf of Alaska. Also, these eddies transport certain trace metals farther offshore than lateral diffusion. This input, especially of higher dissolved iron, may be important in determining the productivity within the Northeast Pacific given its High Nutrient Low Chlorophyll status. In addition, the frequency and size of these mesoscale eddies have found to be correlated with changes in climate such as El Nino, with larger, deeper and more persistent eddies occurring during El Nino years (Melsom et al., 1999). With large parts of the worlds ocean being iron limited and iron fertilization experiments studying whether iron additions can decrease carbon dioxide within the atmosphere, more information on how dissolved iron chemistry affects its bioavailability and what controls dissolved iron distribution within surface waters is an important area of study. This thesis has shown the ability of other trace metals to help detennine the importance of different processes on dissolved iron distributions. This study, combined with the iron study performed by Johnson et al., 2005, was also the first study to follow a mesoscale anticyclonic eddy over time to study the changes in trace metal distributions as the eddy travels. Only two other studies combining dissolved trace metal distributions and mesoscale eddies have been performed. In one study, during the 1996 PRIME (Plankton Reactivity In the Marine Environment) cruise, a large anticyclonic eddy in the Northeast Atlantic Ocean was sampled (Savidge and Chapter 5: General Discussion 159 Williams, 2001). Dissolved iron was analysed on this cruise but was not published. Another eddy study within the China Sea measured cadmium distributions within a cyclonic eddy. They found that their eddy upwelled waters within the center of the eddy and possibly provided a transport mechanism for dissolved and particulate cadmium into the China Sea. In conclusion, this thesis study found that Haida eddies are a source of dissolved aluminum and manganese to the Gulf of Alaska. The quantity of dissolved aluminum these eddies supply to the Gulf of Alaska was comparable to the predicted amount of dissolved aluminum supply by dust deposition. This suggests that Haida eddies should be taken into account when determining aluminum residence times in the Gulf of Alaska. Dissolved manganese was not transported for as long a time as aluminum, although can be transported up to 360km offshore before removals result in manganese concentrations to be similar to open ocean values. The processes controlling iron distributions in the surface of these mesoscale eddies were also studied through the use of tracers. It was found that iron was controlled by both particle scavenging and biological production. The suite of metals chosen as tracers for this analysis aided in the description of processes controlling iron changes over time. Changes in cadmium to phosphate ratios support the theory of preferential cadmium uptake in iron limited waters, and the similarities between iron and copper dynamics in the surface waters suggest that the biological uptake and regeneration of copper and iron are linked. 5.4. Future Directions The Haida eddy study was the first oceanographic project to track an eddy to study its physical, chemical and biological characteristics over time. The sampling times and frequency was determined by the availability of ship time. The sampling locations and depths were chosen with limited knowledge of these eddies from chance sampling on Line P cruises. These eddies have now been characterized and it has been determined that they are important in the transport of coastal waters to the Gulf of Alaska, that the core of the eddy remains chemically intact for up to two years and surface waters remain semi-isolated from surroundings. With this knowledge, future studies should be designed to Chapter 5: General Discussion 160 focus on specific questions about trace metal dynamics and trace metal transport within Haida eddies. 1) What quantity of dissolved trace metals are transported within the Haida eddies? And how do the removal rates vary over time? These questions were addresses in this thesis, but due to spatial resolution another study might be warranted. Transport of dissolved aluminum witnin the Haida eddies is discussed in Chapter 2 and the other trace metal transport is mentioned in section 5.2.1 of this chapter. One suggestion for future studies would be a study using density not distance to determine sampling depths. This suggestion arises from the fact that the eddy transports metals, such as was observed for aluminum, within certain isopycnals. As the eddy ages and loses energy, deep isopycnals shoal, and leakage of coastal water out of the eddy along these isopycnals occurs. In addition, only slight vertical diffusion occurs between density layers within the eddy, resulting in sub-surface dissolved trace metal maximum to shoal with the isopycnals. Using distance to determine depth choices can result in missing sub-surface maxima and thus difficulties in determining transport and removal over time. 2) How does a phytoplankton bloom affect surface values of dissolved trace metals within the eddy? How quickly do the changes occur and how long does it last before other processes, such as remineralization or particle scavenging, affect trace metal distributions? One disadvantage of the sampling times and frequency used for the Haida eddy project was that the effect of the spring bloom was not studied directly. The effect the spring bloom had on trace metal distributions was inferred from changes that occurred between February and June sampling, but within that time frame other processes could cause the effects of the spring bloom to be skewed. More frequent sampling over the timing of the phytoplankton bloom could give more information on uptake and removal due to plankton biomass. It would be difficult to plan for a study such as this, since timing and magnitude of spring blooms change from year to year, but sampling during the springtime, such as March and end Chapter 5: General Discussion 161 of April may give more information on what changes were due to phytoplankton bloom. 3 ) Biogeochemical questions, such as how do particle concentrations and composition affect removal of reactive metals? Or how does species composition affect cadmium to phosphate ratios?, could be addressed on a larger scale within a semi-isolated water mass. Biogeochemical processes are studied in laboratories, large water enclosures and by tracking water masses using tracers and perfonrung transects. The use of a mesoscale eddy to perform these studies would reduce the need for tracers, the calculation of time on a relative scale, and interactions with container walls. Experiments could be performed on many different time scales, from days to years if required. Additionally, studies on biogeochemical changes within coastal water as it ages could be performed, similar to this study. Chapter 5: General Discussion 162 5.5. References Boyle, E. A., 1988. Cadmivjm: Chemical tracer of deepwater paleoceanography. Paleoceanography, 3(4): 471-489. Boyle, E. A., Huested, S. S. and Jones, S. P., 1981. On the Distribution of Copper, Nickel, and Cadmium in the Surface Waters of the North-Atlantic and North Pacific-Ocean. Journal of Geophysical Research - Oceans and Atmospheres, 86(NC9): 8048-8066. Bruland, K. W., 1980. Oceanographic distribution of cadmium, zinc, nickel, and copper in the North Pacific. Earth and Planetary Science Letters, 47: 176-198. Crawford, W. R., 2002. Physical characteristics of Haida Eddies. Journal of Oceanography, 58(5): 703-713. Cullen, J. T., 2006. On the nonlinear relationship between dissolved cadmium and phosphate in the modern global ocean: Could chronic iron limitation of phytoplankton growth cause the kink? Limnology and Oceanography, 51(3): 1369-1380. de Baar, H. J. W., Saager, P. M., Nolting, R. F. and Vandermeer, J., 1994. Cadmium Versus Phosphate in the World Ocean. Marine Chemistry, 46(3): 261-281. Johnson, W. K., Miller, L. A., Sutherland, N. E. and Wong, C. S., 2005. Iron transport by mesoscale Haida eddies in the Gulf of Alaska. Deep Sea Research Part II -Topical Studies in Oceanography, 52(7-8): 933-953. Maldonado, M. T., Allen, A. E., Chong, J. S., Lin, K., Leus, D., Karpenko, N. and Harris, S. L., 2006. Copper-dependent iron transport in coastal and oceanic diatoms. Limnology and Oceanography, 51(4): 1729-1743. Martin, J. H., Bruland, K. W. and Broenkow, W. W., 1976. Cadmium transport in the California Current. In: H.L. Windom and R.A. Duce (Editors), Marine Pollution Transfer. Lexington Books, Lexington, Mass., pp. 159-184. Measures, C. I., Brown, M. T. and Vink, S., 2005. Dust deposition to the surface waters of the western and central North Pacific inferred from surface water dissolved aluminum concentrations. Geochemistry Geophysics Geosystems, 6: Art No. Q09M03. Melsom, A., Meyers, S. D., Hurlburt, H. E., Metzger, E. J. and O'Brien, J. J., 1999. ENSO Effects on Gulf of Alaska Eddies. Earth Interactions, 3. Peers, G. and Price, N. M., 2006. Copper-containing plastocyanin used for electron transport by an oceanic diatom. Nature, 441(7091): 341-344. Chapter 5: General Discussion Savidge, G. and Williams, P. J. L., 2001. The PRIME 1996 cruise: an overview. Deep Sea Research Part II - Topical Studies in Oceanography, 48(4-5): 687-704. Whitney, F. and Robert, M., 2002. Structure of Haida eddies and their transport of nutrient from coastal margins into the NE Pacific Ocean. Journal of Oceanography, 58(5): 715-723. 164 APPENDIX A: METHODS AND ANALYSIS A - l . Cleaning Methods A - l . l . Plasticware Cleaning Procedure This procedure was used for all plastic bottles, pipet tips, resin columns, evaporation beakers and any other plasticware required for analysis. All solutions were prepared with and all rinses performed with high-purity, deionized water (< 18.0 MQ-cm resistance), from a water-purifying system (Millipore Milli-Q, Bedford, MA, USA) referred to hereafter as DDI-H2O. Steps for cleaning: 1. A one-week soak in diluted Extran-100 detergent followed by 8-10 rinses with DDI-H2O 2. Heat overnight (minimum of 8 hours) at 60°C in 4N reagent grade HC1 followed by5rinsesofDDI-H20 3. Heat overnight (minimum of 8 hours) at 60°C in IN Environmental grade HNO3 followed by 5 rinses of DDI-H2O 4. Fill with 0.1% Seastar™ HN03 (for at least a week) and double bag. If required sooner, can heat overnight (minimum of 8 hours) at 60°C and let cool 5. Before use, rinse 3 times with DDI-H2O and dry (if needed) in a laminar flow hood with HEPA filters in clean room A-l.2. Filter Cleaning Procedure The filters used were 0.22um polycarbonate filters (45mm diameter, AMD Manufachiring Inc.). First, the filters were soaked in a 10% Seastar™ HC1 bath for a week. After acid soak, the filters were stored in a DDI-H2O bath until use. The filters were handled with a set of plastic forceps. The forceps were acid cleaned in 50% Seastar™ HC1 and were rinsed with 10% Seastar™ HC1 and DDI-H20 before use. A-1.3. Cationic Exchange Resin Cleaning Method The cationic exchange resin cleaning method was based on Price et al., 1988-1989 with slight variations. The ion exchange resin used was Chelex® 100 Chelating Ion Appendix A: Method and Analysis 165 Exchange Resin (Bio-Rad). It consists of a styrene-divinylbenzene copolymer with paired iminodiacetic acid functional groups. Cleaning Steps: 1. Soak in methanol for 2 hours at room temperature (w/v 40g to 200mL); rinse with 750mL DDI-H20 A 2. Soak in 1M Q-HC1 for 2 hours at room temperature; rinse with 1L DDI-H2O 3. Soak in Q-NH4OH for two days at room temperature; rinse with 1L DDI-H2O 4. Soak in 0.1M Q-HC1 for 10 minutes; rinse with 2L DDI-H20 5. Rinse with 0.3M NH+Ac buffer (pH 8) until liquid exiting funnel is of pH 8 6. Store in 0.3M NFLAc buffer (pH 8) until use B A Rinsing steps performed using a Millipore Sterifu funnel setup and a polypropylene suction flask with 75 um Spectra/Mesh fluorocarbon (TPE, FEP) filter supplied by Spectrum Medical Industries, Inc. and cut to size. B The resin was stored in pH 8 buffer to keep it from losing its chelating capacity (Chelex® 100 and Chelex® 20 Chelating Ion Exchange Resin Instruction Manual, Bio-Rad) A-2. Metal Concentration Method The method and column set-up is shown in Figure A-l.1. The separatory funnel, stopcocks and tubing were made out of Teflon®. The columns were polypropylene poly-prep columns from Bio-Rad Laboratories Inc. Stopcock #1 Stopcock #2 Column with resin Figure A - l . Column set-up Appendix A: Method and Analysis 166 A-2.1. Method for setting flow rates 1. Using a pipet, transfer approximately 2mL of Chelex® 100 in 0.3M NH4AC buffer into the poly-prep columns. The volume can be measured using the markings on column. 2. Fill separatory funnels to the 250mL mark with DDI-H2O 3. Set flow rates between 0.77 and 0.83g/min by adjusting stopcock #2. Stopcock #1 should be used to start and stop flow. Make sure set-up is airtight 4. Once flow rate set, empty separatory funnel, then rinse and fill with hot 1 .OM Seastar™ HNO3 (approximately 20mL for rinse; 200mL fill) 5. Drip the hot acid through setup overnight, including the columns containing the resin A-2.2. Concentration Method 1. Remove caps from columns and collect liquid as column blank 2. Rinse separatory funnels with: a. 3 times DDI-H2O b. 1 time with 0.3M Seastar™ NH 4Ac buffer, pH adjusted to required pH 3. Put approximately 25mL buffer into separatory funnel and remove all liquid 4. While rinsing, pH adjust columns using 0.3M Seastar™ NFUAc buffer, pH adjusted to desired pH 5. Drip buffer through separatory funnel set-up until pH of liquid leaving system is the desired pH 6. Attach caps to pH adjusted columns and let rest of buffer remaining in separatory funnel to drip through columns 7. Weigh out seawater samples: a. If using samples, weigh bottle and seawater b. If doing recovery tests, weigh bottle, add seawater and re-weigh and then make standard and add to spike bottles and weigh once more 8. pH adjust seawater samples using concentrated Seastar™ Nth; concentrated Seastar™ HAc and concentrated Seastar™ NH4AC buffer, weigh after addition and after pH check Appendix A: Method and Analysis 167 9. Weigh collection bottles 10. Pour seawater into separatory funnels 11. Create a bubble in the tubing and then start flow, begin collection (and timing) when the seawater reaches the column 12. Refill separatory funnels after first 250mL has eluted 13. When samples are complete: a. Turn off stopcock #1 on separatory funnel and record the time b. Remove collection bottle and put lid on c. Place waste container under column d. Remove column cap and empty the liquid in column e. Weigh collection bottles f. Rinse columns with i. 6mL dilute buffer ii. 4mL pH adjusted DDI-H20 g. After columns stop dripping, place Teflon beaker under column and elute column with 2 times 5mL of 2N Seastar™ HNO3 h. When elution complete, place beakers on hot plate i. Evaporate samples down and re-dissolved in 0.1% Seastar™ HNO3 14. Rinse separatory funnels 3 times with DDI-H2O A-3. Graphite Furnace Atomic Absorption Spectrophotometer Analysis A-3.1. Instrument Parameters Most instrument parameters; such as lamp current, slit width, wavelength, time constant, measurement time, and maximum absorbance; are a function of the element of analysis and the suggested values for the element are used. For the analysis of samples, a standard addition method was used to compensate for any excess salts, such as calcium, that may have been concentrated along with the metals of interest. All concentrations were measured within the linear region of the standard addition curves. If an absorption reading was found to be out of this range, the sample was diluted with 1% HNO3 to place it within this linear range. Zeeman Appendix A: Method and Analysis 168 background correction was used to compensate for polyatomic molecule absorption or particle backscatter that may have occurred during analysis A-3.1.1. Graphite Tubes Two types of pyrolytically coated graphite tubes were used during trace metal analysis: the partition tube and the L'vov platform (or plateau) tube. The graphite tube is where the sample is injected. It is located within the furnace set-up and is held there between two electrodes. The temperature within the tube is controlled by applying a current between the electrodes, with the temperature of the graphite tube increasing due to the resistance of the graphite to the applied current. Partition tubes use off-the-wall atomization, which is where the sample is in contact with the tube wall and is heated directly. They are called partition due to the ridge within the tube that confines the liquid sample to the center section of the tube. This type of tube is most commonly used, and has the advantages of fast analysis time, the ability to use a normal slit width, thereby increasing the signal, and the ability to accommodate sample volumes larger than 40uL. L'vov platform tubes are graphite tubes that contain grooves that allow the placement of a single piece of solid graphite, called a platform, which remains suspended above the bottom of the tube. The platform has a depression on the surface to allow it to contain liquid samples, up to volumes of 40uL. The suspension of the platform above the bottom of the tube results in slight physical contact between the tube and the platform, resulting in samples contained within the platform groove to be heated by heat radiating from the tube, thus delaying the atomization until the tube has reached a high stable temperature. This helps reduced interferences and increases the sensitivity. Disadvantages to this technique include longer analysis time, increased temperatures required (approximately 200°C greater than partition tube), and reduction in slit widths due to platform obstructing light from the lamp source within the tube. A-3.1.2. Matrix Modifiers A couple of the metals analyzed required matrix modifiers to acquire reproducible and linear standard addition curves. A matrix modifier is used to remove interferences by Appendix A : Method and Analysis 169 either binding to the interfering chemical to free the analyte or by reacting directly with the element of interest to either increase or decrease its volatility, thus reducing the interfering factors. The two matrix modifiers employed during this analysis were a palladium modifier and an ethylenediaminetetraacetic acid (EDTA) modifier in a surfactant (Triton-X) matrix. The palladium modifier with nitric acid was used during the analysis of manganese to increase the temperature of pyrolysis, thereby allowing for the removal of more matrix interferents (Qiao and Jackson, 1991; Volynskii, 2003). The EDTA modifier was used during the aluminum analysis to aid in the removal of chloride and sulfate interferences, by the formation of organic complexes with metal cations during the drying step (Matsusaki and Sata, 1994; Volynskii, 2003). A-3.2. Graphite Furnace-Atomic Absorption Spectrophotometer Programs The instrument used for analysis was the Varian SpectraAA 300/400 atomic absorption spectrophotometer equipped with a graphite tube atomizer and Zeeman background correction. The programs in the following sections are examples of the programs used, since certain conditions such as the graphite tube age resulted in modifications to the program each day for optimal performance. Appendix A: Method and Analysis 170 A-3.2.1. Aluminum Analysis mstrument Parameters Instrument Mode: Calibration Mode: Measurement Mode: Lamp Current (mA): Slit Width (nm): Slit Height: Wavelength: Sample Introduction: Time Constant: Measurement Time (sec): Background Correction: Maximum Absorbance: Graphite Tube: Absorbance Standard Addition Peak Area 10 0.5 Normal 396.2 Sampler Automixing 0.05 1.0 ON 2.00 Partition Furnace Parameters Step Temperature Time Gas Flow Read Number CO (sec) (L/min) Command 1 95 5.0 3.0 NO 2 110 5.0 3.0 NO 3 120 25.0 3.0 NO 4 140 5.0 3.0 NO 5 140 10.0 3.0 NO 6 1400 3.0 3.0 NO 7 1400 10.0 3.0 NO 8 1400 1.0 0.0 NO 9 2700 0.9 0.0 YES 10 2700 2.0 0.0 YES 11 2700 2.0 3.0 NO 12 2800 1.0 3.0 NO Auto-sampler Parameters Total Injection Volume: 24uL Matrix Modifier: 2uL of 2% w/w EDTA and 0.2% Titron-X Appendix A: Method and Analysis 171 A-3.2.2. Cadmium Analysis Instrument Parameters mstrument Mode: Calibration Mode: Measurement Mode: Lamp Current (mA): Slit Width (nm): Slit Height: Wavelength: Sample Introduction: Time Constant: Measurement Time (sec): Background Correction: Maximum Absorbance: Graphite Tube: Absorbance Standard Addition Peak Area 4 0.5 Reduced 228.8 Sampler Automixing 0.05 1.0 O N 0.70 Platform Step Number 1 Temperature (°C) 285 Furnace Parameters Time (sec) 8.0 Gas Flow (L/min) 3.0 Read Command NO 2 300 20.0 3.0 N O 3 700 3.0 3.0 N O 4 700 30.0 3.0 N O 5 700 1.0 0.0 N O 6 2300 1.0 0.0 YES 7 2300 3.0 0.0 YES 8 2300 2.0 3.0 N O 9 40 13.3 3.0 NO Auto-sampler Parameters Total Injection Volume: 24uL Matrix Modifier: None Appendix A: Method and Analysis 172 A-3.23. Copper Analysis Instrument Parameters Instrument Mode: Absorbance Calibration Mode: Measurement Mode: Lamp Current (mA): Slit Width (nm): Slit Height: Wavelength: Sample Introduction: Time Constant: Measurement Time (sec): Background Correction: Maximum Absorbance: Graphite Tube: Standard Addition Peak Area 4 0.5 Reduced 327.4 Sampler Automixing 0.05 1.0 ON 1.60 Platform Step Number 1 Temperature CC) 320 Furnace Parameters Time (sec) 6.0 Gas Flow (L/min) 3.0 Read Command NO 2 320 35.0 3.0 NO 3 1000 3.0 3.0 NO 4 1000 10.0 3.0 NO 5 1000 1.0 0.0 NO 6 2600 0.9 0.0 YES 7 2600 3.5 0.0 YES 8 2600 1.0 3.0 NO 9 40 13.3 3.0 NO Auto-sampler Parameters Total Injection Volume: 24pL Matrix Modifier: None Appendix A: Method and Analysis 173 A-3.2.4. Manganese Analysis mstrument Parameters Instrument Mode: Calibration Mode: Measurement Mode: Lamp Current (mA): Slit Width (nm): Slit Height: Wavelength: Sample Introduction: Time Constant: Measurement Time (sec): Background Correction: Maximum Absorbance: Graphite Tube: Absorbance Standard Addition Peak Area 5 0.2 Reduced 279.5 Sampler Automixing 0.05 1.0 ON 1.20 Platform Step Number 1 Temperature (°C) 320 Furnace Parameters Time (sec) 10.0 Gas Flow (L/min) 3.0 Read Command NO 2 320 35.0 3.0 NO 3 1500 3.0 3.0 NO 4 1500 10.0 3.0 NO 5 1500 1.0 0.0 NO 6 2700 0.9 0.0 YES 7 2700 3.5 0.0 YES 8 2700 1.0 3.0 NO 9 40 13.3 3.0 NO Auto-sampler Parameters Total Injection Volume: 30pL Matrix Modifier: 3pLof0.1%PdinHNO3 Appendix A: Method and Analysis 174 A-4. References Matsusaki, K. and Sata, T., 1994. Removal of Sulfate Interference in the Determination of Indium and Gallium by Graphite-Furnace AAS. Bunseki Kagaku, 43(8): 641-643. Price, N. M., Harrison, G. I., Hering, J. G., Hudson, R. J., Nirel, P. M. V., Palenik, B. and Morel, F. M. M., 1988-1989. Preparation and chemistry of the artificial algal culture medium Aquil. Biological Oceanography(6): 443-461. Qiao, H. C. and Jackson, K. W., 1991. Mechanism of Modification by Palladium in Graphite-Furnace Atomic-Absorption Spectrometry. Spectrochimica Acta Part B -Atomic Spectroscopy, 46(14): 1841-1859. Volynskii, A. B., 2003. Chemical modifiers in modern electrothermal atomic absorption spectrometry. Journal of Analytical Chemistry, 58(10): 905-921. 175 APPENDIX B: ERROR ANALYSIS OF PROCEDURES B-l . Introduction The error and detection limits discussed in this appendix are for the analysis of trace metals using a graphite furnace - atomic absorption spectrophotometer (GF-AAS, model: Varian SpectraAA 300/400). The procedure for the concentration of metals from seawater and the GF-AAS programs used are explained in Appendix A. B-2. Limit of Detection The detection limits given in Table B-l were calculated following the guidelines set out in "Standard Methods for the Examination of Water and Wastewater, 20th edition", published by the American Public Health Association, the American Water Works Association and the Water Environment Federation. Descriptions of the different detection limits are in Sections B-2.1 to B-2.4. Aluminum Cadmium Copper Manganese Criterion for Detection C.O.D. = 1.645(s of blk) 0.049 0.001 0.068 0.018 Lower Level of Detection L.O.D. = 3.29(s of blk) + avg blk 0.098 0.003 0.108 0.037 Method Detection Limit M.D.L. = t(s of sample) + avg blk 0.191 0.006 0.099 0.029 Limit of Quantification L.O.Q. = 10(s of blk) 0.254 0.008 0.352 0.108 Table B-l . Summary table of different detection limits for aluminum, cadmium, copper, and manganese (converted to units of nM in original seawater by dividing by concentration factor), "avg blk" stands for average blank reading and "s" represents standard deviation of either the blank (blk) or bulk seawater sample (sample). Appendix B: Error Analysis of Procedures 176 B-2.1. Criterion of Detection (C.O.D.) The Criterion of Detection (C.O.D.) is defined as 1.645 times the standard deviation of the blank. The C.O.D. was determined by nmning samples of 0.1% nitric acid (Seastar Chemicals Inc.), which was diluted with ultra pure, deionized (18mficm) water from a water purification system (Millipore Milli-Q, Bedford, MA, USA). The number of replicates analyzed was greater than 30 for all metals (Al: n=31; Cd: n=42; Cu: n=32; Mn: n=55) and standard error was determined from acid blanks which were analyzed over four years. The C.O.D. deterrnined for aluminum, cadmium, copper and manganese are in Table B-l. B-2.2. Lower Level of Detection (L.O.D.) The Lower Level of Detection (L.O.D.) is defined as the concentration that produces a detectable signal in at least 99% of trials. The L.O.D. was calculated by determining the concentration that gives a signal 3.290 times the standard deviation of the blank. Increasing the multiplication factor from 1.645 times (C.O.D.) to 3.290 times (L.O.D.) decreases the chance of a false positive (or a false negative) to 5%. The 0.1% nitric acid samples used to calculate the L.O.D. were the same samples used to calculate the C.O.D., and the results are given in Table B-l. B-2.3. Method Detection Limit (M.D.L.) The Method of Detection Limit (M.D.L.) is similar to the L.O.D. in that it determines the minimum concentration required in a sample to produce a detectable signal that is different from the blank in 99% of the trials. The M.D.L. differs from the L.O.D. in that the samples analyzed to determine the M.D.L. have been processed through the entire analytical method (described in Appendix A) and also include any matrix effects. The seawater samples used for the M.D.L. calculation were collected from a depth of 10m using an air-driven double-bellows Teflon® pump (Asti) at Ocean Station Papa (50° N, 145° W) and filtered using a 0.22um cartridge filter (Opticap™ with Durapore® membrane by Millipore). The bulk seawater sample was collected in a 40L polycarbonate carboy (Nalgene) and was acidified to pH < 2 using concentrated hydrochloric acid (doubly quartz distilled, Seastar™ Chemicals Inc). Appendix B: Error Analysis of Procedures 177 B-2.4. Level of Quantification (L.O.Q. or M.Q.L.) The final detection level calculated was the level of quantification (L.O.Q.). The L.O.Q. is defined as the analyte concentration that produces a signal significantly greater than the blank, which can be detected during routine analysis. It is calculated as the concentration that produces a signal that is 10 times the standard deviation of the blank. The L.O.Q. was calculated using the same sample blanks as the C.O.D. and the L.O.D. and the values are given in Table B-l. B-2.5. Summary The limits of detection were compared to the trace metal seawater concentrations determined from the samples collected on the research cruises. The seawater concentrations are given in Appendix D. The C.O.D. for each metal was 4 to 28 times smaller than the lowest concentrations measured in the seawater samples. The L.O.D. for each metal had a value that was less than half of the lowest concentration measured in the seawater samples analyzed. The M.D.L. was lower than the measured values for all seawater samples as well, although in the case of dissolved aluminum the M.D.L. was only 0.3% smaller than the smallest dissolved aluminum concentration measured in the seawater samples. The L.O.Q., the largest valued limit, was smaller than the lowest seawater measurements for manganese and cadmium, but aluminum and copper each had one seawater sample value to be below the L.O.Q.. For aluminum, the seawater sample was the 25m-depth sample at Ocean Station Papa. The dissolved aluminum concentration for this station was 25% lower than the L.O.Q.. For copper, the 200m from reference station from the 2000-10 cruise was the sample with the dissolved copper concentration that was lower, although the measurement was only 7% lower than the L.O.Q.. The values found to be lower than the L.O.Q. are designated with an asterisk (*) in the data tables in Appendix D. In addition, during analysis on the GF-AAS, all samples were run in duplicate or triplicate. If the root square mean percent was greater than 5% for the replicates, either a tube clean program was performed (which consisted of ramping the temperature of the graphite furnace to greater than 2700 degrees) or the graphite furnace was replaced Appendix B: Error Analysis of Procedures 178 before the sample was re-run. Also, a new standard addition curve was produced before the samples were re-analyzed. B-3. Column Concentration Method The goal of the column concentration method was to concentrate the metals of interest while removing unwanted major salts. This was accomplished by running a volume of seawater over a cationic exchange resin, and then eluting the resin with a small volume of dilute acid. Specific instructions for the column concentration method are given in Appendix A. B-3.6. Recovery Tests The seawater matrix can affect the absorption of metals to the cationic exchange resin. For this reason, recovery tests were performed using a laboratory fortified matrix sample (LFM sample). A LFM sample is a seawater sample to which known amounts of the analyte standards were added before sample processing. This method allows for the effects of the matrix on the analyte recovery to be measured. Both the sample and the LFM sample are analyzed and the percent recovery of the analytes are determined using Equation 1. „, ^ (LFM sample result-sample result) „, % Recovery = \ 7 ^ 7 - 7 7 ^ " ^ x 1 0 0 / o Equation 1 known LFM added concentration The seawater matrix used for recovery test comparisons was collected from a depth of 10m using an air-driven double-bellows Teflon® pump (Asti) at Ocean Station Papa (50° N, 145° W) and filtered using a 0.22pm cartridge filter (Opticap™ with Durapore® membrane by Millipore). It was collected in a 25L polycarbonate carboy (Nalgene) and stored in the dark. Since it had been stored for more than 2 years, it was acidified to pH < 2 using concentrated hydrochloric acid (doubly quartz distilled, Seastar™ Chemicals Inc.) and re-filtered through an acid-washed 0.22pm polycarbonate filter (45mm diameter, AMD Manufachiring Inc.) by gravity filtration before use. The standards used to spike the seawater were certified lOOOppm atomic absorption standards (Delta Scientific Lab Products), and were diluted with ultra pure, deionized (18MQcm) Appendix B: Error Analysis of Procedures 179 water from a water purification system (Millipore Milli-Q, Bedford, MA, USA). Recovery tests were performed by spiking 500mL of the stock seawater with lOOuL of a metal solution containing varying amounts of metals, to produce a concentration approximately 3 to 10 times the amount expected in the non-spiked seawater. The seawater samples (un-spiked samples and LMF samples) were then processed using the column concentration method described in Appendix A. Overall results from recovery tests are given in Table B-2. The variation in the percent recovery did not correlate with column used or the date the recovery test was performed so the 95% confidence interval should represent the random scatter in the column recovery. Aluminum Cadmium Copper Manganese Average Recovery (%) 110 ± 13 104 ± 7 96 ± 5 108 ± 6 n 16 36 34 23 s 0.247 0.195 0.155 0.142 a 0.05 0.05 0.05 0.05 Degree of freedom 15 35 33 22 t(a/2) 2.131 2.030 2.036 2.074 Table B-2. Average percent recovery for aluminum, cadmium, copper and manganese. The average recovery is expressed as an average recovery ± 95% confidence interval, where the confidence interval is equal to ts I V« • B-3.7. Precision and Accuracy of the Analysis Method The precision of the analysis method was determined by performing replicate analysis of bulk seawater used for the recovery tests. Replicate samples of seawater were put through the identical concentration method and then analyzed. Results of the metal concentrations in the original seawater sample are given in Table B-3. The 95% confidence interval for all metals was 5% or less, with the higher percent error associated with metals with the smaller concentrations. Again, the variation in the percent recovery Appendix B: Error Analysis of Procedures 180 Aluminum (nM) Cadmium (nM) Copper (nM) Manganese (nM) Avg Cone. ± 95% CI. 0.99 ±0.04 0.120 ±0.006 1.40 ±0.04 0.46 ± 0.03 Std Dev. 0.05 0.010 0.05 0.03 N 8 12 8 8 T 2.365 2.201 2.365 2.365 % Error 4% 5% 3% 5% Table B-3. Results of precision test for column procedure. The average concentration (avg cone.) is expressed as an average concentration in seawater sample ± 95% confidence interval. did not correlate with column used or the analysis date so the 95% confidence interval should represent the random scatter. A certified reference material, CASS-3 (Certified Atlantic Surface Seawater - 3; National Research Council of Canada), was analyzed to test the accuracy of the cadmium, copper and manganese analysis. The reference material was run in triplicate and the results, with a comparison to the certified values, are listed in Table B-4. Aluminum data was also measured but no certified value for comparison was available. Dissolved cadmium, copper, and manganese were all determined to be within the error limits of the certified reference values. Measured Value Certified Reference (P-g/L) Value (ug/L) Aluminum 0.294 ± 0.004 it H Cadmium 0.032 ± 0.002 0.030 ± 0.005 Copper 0.514 ±0.065 0.517 ±0.062 Manganese 2.85 ± 0.25 2.51 ±0.36 Table B-4. Comparison of measured and certified values for CASS-3. Samples were run in triplicate, and the error represents the 95% confidence interval. Appendix B: Error Analysis of Procedures 181 B-3.8. Background Measurements Two methods were used to assess the background signal due to the reagents and column materials. Method blanks were determined using high purity, deionized water (18mQcm, Millipore Milli-Q, Bedford, MA, USA) in place of seawater, which were treated to the same acidification, pH adjustment and concentration steps as the seawater samples. The results are listed in Table B.5. The reagent blank concentrations for aluminum and for copper were under the C.O.D. listed in Table B.l . Although the cadmium and manganese reagent blank readings were above the C.O.D., the values were below the L.O.D. Therefore, the contribution of dissolved metals from the reagents were considered negligible. Aluminum (nM) Cadmium (nM) Copper (nM) Manganese (nM) Avg Reading ± 95% C.I. 0.011 ±0.036 0.002 ± 0.001 0.010 ±0.013 0.028 ± 0.007 Std Dev. 0.023 0.001 0.016 0.006 N 4 7 8 5 T 3.182 2.447 2.365 2.571 Table B-5. Method blank results from analysis of reagents in high purity, deionized water, and processed through entire analytical method. Results are given in units of nM, and reported as concentrations in original sample, before processing. To measure the effect of the seawater matrix on the background measurements, procedural blanks were determined by analyzing different volumes (approximately 100, 250 and 500mL) of a bulk seawater sample. The residual signal from the metals (listed in Table B-6) was determined by plotting the volume of seawater analyzed versus the concentration of dissolved metal in the eluent (normalized to 4mL). A regression line was then fit to the data and the y-intercept was determined (Figure B-l). The y-intercept would be equal to the concentration signal expected when OmL of seawater was analyzed, which would be due to the effect of the seawater matrix. Appendix B: Error Analysis of Procedures 182 Volume of Seawater (mL) Volume of Seawater (mL) Figure B-l . Results of procedural blank analysis plotted as Volume of Seawater (mL) versus the dissolved concentration of a) aluminum, b) cadmium, c) copper and d) manganese in parts per billion. Aluminum Cadmium Copper Manganese Slope 0.951 0.013 0.083 0.016 Intercept 0.004 0.108 -0.831 0.387 R 0.987 0.953 0.995 0.972 Matrix Effect (nM) 0.001 0.008 -0.107 0.058 Table B-6. Linear regression results from procedural blank analysis. Matrix effect results in units of nM of original seawater concentration, to make comparison to limits of detection. Appendix B: Error Analysis of Procedures 183 The absolute value of the matrix effect calculated was lower than the L.O.Q. for all metals. The result for the aluminum procedural blank was lower than the C.O.D. and the copper result lower than the L.O.D.. B-4. Conclusion The procedure used was found to be a suitable method for metal analysis, with the percent recovery of 95% or greater for all metals analyzed, with the lowest recovery being for copper and the highest for aluminum. Both the reagent and procedural background measurements were found to be below L.O.Q. for all metals, with the aluminum and copper results found to be lower than the calculated L.O.D. of the instrument. The reproducibility of metal analysis was found to be acceptable, with the standard error (at the 95% confidence level) being 5% or less. The accuracy of the method was also measured for cadmium, copper, and manganese and the concentration values were found to be within the determined confidence levels of the certified reference material. B-5. References American Public Health Association, American Water Works Association and Water Environment Federation, 1998. Standard Methods for the Examination of Water and Wastewater, 20th edition. American Public Health Association, Washington, D.C, 1220 pp. 184 APPENDIX C: COMPARISON OF COMMERCIALLY AVAILABLE CHELEX® 100 AND IN-LAB SYNTHESIZED 8-HYDROXYQUINOLINE BOUND TO AMBERLITE® XAD-2 RESIN FOR T H E ANALYSIS OF SEAWATER C- l . Background Chelex® 100 from Bio-Rad industries is one resin material that has been used since the inception of trace metal analysis (Kingston et al., 1978; Bruland et al., 1979) but has never been considered an ideal column material. Chelex® 100 consists of an iminodiacetate (IDA) functional group bound to a cross-linked polystyrene/divinyl benzene backbone. This resin has some advantages; such as its stability over a wide range of pH, its high capacity, and its commercial availability, which explains why it is still used. The major problems with this resin are that it is not very selective (especially in the seawater matrix), it has slow binding kinetics, and it changes size when converted from hydrogen to other cationic forms making it inappropriate for flow injection analysis. Due to its low selectivity, alkaline and alkali cations (such as sodium, calcium, magnesium), that make up the majority of the salt in seawater are retained on the column and can cause clogging of sample/skimmer cones in inductively coupled plasma mass spectrometers. Many other resins, containing a variety of functional groups, have since been developed and tested. One functional group used is 8-hydroxyquinoline (8-HQ), which has several advantages over IDA, such as greater selectivity towards transition metals. There have been many different synthesized resins containing 8-HQ using a variety of substrates and linkages (Hill, 1973; Sturgeon et al., 1981; Willie et al., 1983; Landing et al., 1986; Dierssen et al., 2001 and references therein). The choice of substrate and the manner in which the 8-HQ is attached can affect the resins' capacity, selectivity, stability and binding kinetics. A commonly used linkage is an azo-linkage (Landing et al., 1986). One disadvantage with this linkage is its low stability in acid and oxidizing media. In addition, the resin preparation is difficult, there have been problems with reproducibility and it can also introduce a second functional group with an azo-functionality (Seubert et al., 1995). The resin which was synthesized to be compared to Chelex® 100 contained a memyl-linkage between the 8-HQ and the Amberlite XAD-2 resin (polystyrene-divinylbenzene polymer) first introduced by Persaud and Cantwell, 1992. Using this Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 185 linkage increases stability in the presence of acid and should be more selective for transition metals than alkaline earth metals. C-2. Materials and Methods C-2.1. Instrumentation A Varian AA-875 flame atomic absorption spectrophotometer was used to determine the breakthrough capacity of the 8-HQ resin. A Varian SpectraAA 300/400 equipped with a graphite tube atomizer and Zeeman background correction was used for calcium quantification, 8-HQ resin copper capacity and cleaning tests, and Chelex 100 recovery test measurements. A Thermo Finnigan Element2 high resolution inductively coupled plasma mass spectrometer was used for analysis of the 8-HQ resin recovery tests. Standard addition analysis was used for quantification when possible. C-2.2. Chemicals Chemicals used for the synthesis of the 8-HQ resin were of analytical grade or better, except for the formaldehyde (reagent grade), which was used in the chloromethylating step. The resin used for the 8-HQ synthesis was a styrene-divinylbenzene copolymer, Amberlite XAD-2 resin (Rohm and Haas). The Chelex® 100 Chelating Ion Exchange Resin (sodium form, reagent grade, 100-200 mesh) was purchased from Bio-Rad Industries (Richmond, CA, USA) and cleaned as described in Section C-2.5. Doubly quartz distilled acids (hydrochloric (Q-HC1), nitric (Q-HNO3) and acetic (Q-HAc)) and high purity ammonium hydroxide (Q-NH3) used for acidifying, pH adjusting and column sample elution were purchased from Seastar™ Chemicals Inc. Certified lOOOppm atomic absorption standards (Delta Scientific Lab Products) were used to prepare spiked solutions for capacity tests, recovery tests and diluted standards for metal analysis. All solutions were prepared using ultra pure, deionized (18mQcm) water from a water purification system (DDI-H2O; Millipore Milli-Q, Bedford, MA, USA). All solution preparation and column work for recovery tests were performed in a Class 1000 clean room. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 186 C-2.3. Synthesis of 8-HQ Resin The 8-HQ was chloromethylated following the procedure described in Persaud and Cantwell, 1992. 20. lg of 8-HQ was dissolved in a mixture of 60mL of concentrated hydrochloric acid and 60mL of 36-38% formaldehyde and HC1 gas was bubbled through the mixture, while stirring, for 2 hours (Figure C.la). The yellow crystals, once dried, gave a percent yield of -99%. NMR analyses performed on both the precursor and final product confirm the chloromethylated product was produced. The addition of the chloromethylated product (1.84g) to the Amberlite XAD-2 resin (4.0g) was performed using a Friedel-Crafts reaction using 12mL of 1.8M aluminum chloride in anhydrous nitrobenzene (Figure C.lb). This reaction was similar to the Warshawsky et al., 1978 method, and was described in more detail in Persaud and Cantwell, 1992. This mixture was stirred for 72 hours at 70°C, and the product was then poured into lOOmL of methanol and filtered. The resin was then rinsed with methanol, 1:1 hot methanol-concentrated hydrochloric acid, methanol, chloroform, and lastly diethyl ether. Following the rinses, the resin was dried at 70°C. The 8-HQ resin was then loaded into columns, wetted and rinsed with methanol and then acid. The rinses were collected to check for complete removal of excess 5-cWoromethyl-8-hydroxyquinoline and aluminum chloride. C-2.4.8-HQ Capacity Tests Two capacity tests were performed, one in which the resin was allowed to equilibrate with a copper solution for 24 hours and the other was a breakthrough capacity test similar to Dierssen et al., 2001. The equilibrium test was performed using copper standard of 14.6ppm, pH-adjusted to 5.3 with a clean ammonium acetate buffer. Approximately 12mL of this standard solution was added to a column containing approximately 0.5g dry resin that was pre-wetted with methanol then water. The column was capped, shaken and left to sit overnight in the copper standard solution. After 24 hours, the copper standard was drained from the resin and collected. The resin was then rinsed with 30mL of DDI-H2O and then eluted with approximately 50mL of IN Q-HNO3. Rinses and acid elution were collected in lOmL aliquots and analyzed for copper content. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 187 Figure C-l . Synthesis reaction for a) the chloromethylated 8-HQ and b) the adding of the chloromethylated 8-HQ to the Amberlite XAD-2 by means of a Friedel-Crafts alkylation reaction The breakthrough capacity test was performed by attaching a column containing approximately 0.5g of resin (dried and weight after use) to the aspirator of a flame atomic absorption spectrophotometer. A 50ppm copper solution (in 0.0IM ammonium acetate buffer at pH 5.3) was pumped through the resin at 0.8mL/min by means of a peristaltic pump. The copper contained in the liquid exiting the column was measured until the copper signal increased to levels expected without the column being present. The extra liquid required for the aspirator was supplied through a Y - valve and consisted of a 0.0 I M ammonium acetate buffer, adjusted to a pH of 5.3. C-2.5. ChelexlOO® Cleaning Procedure The cleaning procedure used was based on the method of Price et al., 1988-1989 with slight variations (Table C-l). Once cleaned, the resin was stored in 0.3M ammonium acetate buffer at pH 8 until use, in order to avoid loss of chelating capacity which can Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 188 occur if the resin is stored in hydrogen form for more than a few hours (Bio-Rad Laboratories). Cleaning Step Volume DDI FLO rinse Table C-l . 1. Soak in methanol for 2 hours at room temperature (w/v 40g to 200mL) Table C-2. 2. Soak in IM Q-HC1 for 2 hours at room temperature 750mL lOOOmL 3. Soak in Q-NH4OH for 2 days at room temperature lOOOmL 4.Soak in 0.1 M Q-HC1 for 10 minutes 2000mL 5. Rinse with 0.3M NfLAc buffer (pH 8) until liquid exiting funnel is equal to a pH 8 6. Store in 0.3M NHjAc buffer (pH 8) until use Table C- l . Chelex 100 cleaning method based on method from Price et al., 1988-1989. All rinsing steps performed using a Millipore Sterifii funnel setup and a polypropylene suction flask with 75um Spectra/Mesh fluorocarbon (TPE,FEP) filter suDDlied bv Spectrum Medical industries. Inc. C-2.6. Trace Metal Recovery Tests The seawater used for recovery test comparisons was collected from a depth of 10m using an air-driven double-bellows Teflon® pump (Asti) at Ocean Station Papa (50° N, 145° W) and filtered using a 0.22um cartridge filter (Opticap™ with Durapore® membrane by Millipore). It was collected in a 25L polycarbonate carboy (Nalgene) and stored in the dark. Since it had been stored for more than 2 years, it was acidified to pH < 2 using concentrated Q-HC1 and re-filtered through an acid-washed 0.22um polycarbonate filter (45mm diameter, AMD Manufacturing Inc.) by gravity filtration before use. Recovery tests were performed by spiking 500mL of seawater with lOOuL of a metal solution containing varying amounts of metals, to produce a concentration approximately 3 to 10 times the amount expected in the non-spiked seawater. The seawater samples (spiked and non-spiked) were then pH-adjusted to the required pH using a combination of concentrated ammonium acetate buffer solution, Q-NH3 and Q-HAc (if required). The pH-adjusted seawater was allowed to drip through the column at a Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 189 flow rate of 0.8 mL/min, unless otherwise specified. The resin bed volume was set to lmL for the 8-HQ and 2mL for the Chelex® 100 columns. The choice of 2mL for Chelex® 100 was based on the previous methods performed in our lab (Merrin, 2002), and the reason for lmL 8-HQ was due to the limited amount of resin synthesized. Columns were then rinsed with 3 times the resin bed volume of 0.3M ammonium buffer at the pH of interest, 2 times the resin bed volume of pH adjusted DDI -H2O and then eluted with lOmL of acid. The eluted acid was 2N Q-HNO3 for the Chelex® 100 columns (Merrin, 2002) and a combination of 2N Q-HC1 and 0.5N Q-HNO3 for the 8-HQ resin (Dierssen et al., 2001). The eluent was evaporated down in Teflon® beakers and brought up in 4mL 0.1% Q-HNO3 and then analyzed. C-3. Results and Discussion C-3.1. Cleaning Results for 8-HQ Resin After the 8-HQ resin was dried and re-suspended in methanol, the resin was rinsed with methanol and then 2N Q-HNO3 to confirm the removal of excess chloromethylated 8-hydroxyquinoline and aluminum chloride catalyst respectively. 35 j CI i f 30 O 25 X •8P 20 0) 00 15 >» JC "5  E 10 0 0 JZ 5 -0 0 T 7 0 60 50 40 (qdd) 30 < 20 10 - 0 50 300 350 100 150 200 250 Volume of rinse (mL) Figure C-2. Plot of volume of rinse (methanol for chloromethylated 8-HQ removal; 2N Q-HNO3 for aluminum removal) versus chloromethylated 8-HQ (empty square) on the left axis and aluminum (full circle) on the right axis. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 190 Analysis of methanol rinses was performed using a Hewlett Packard 8452A diode array spectrophotometer. Evidence of chloromethylated reagent was visible in methanol aliquots until a rinse volume of approximately 80mL was reached (Figure C-2). Analysis of acid rinses on atomic absorption spectrometer revealed that aluminum concentrations decreased rapidly over the first lOOmL of acid rinse but leveled off at approximately 5ppb after 270mL of acid rinse (Figure C-2). This leveling off resulted in a high aluminum background and therefore the analysis of aluminum using this resin wasn't possible. If aluminum analysis was desired either more rinses should be performed or other Friedel-Crafts catalysts could be tested, such as gallium (7JJ) chloride, molybdenum (V) chloride or antimony (V) fluoride. C-3.2. Capacity Tests for 8-HQ Resin The capacity of the 8-HQ resin determined using the equilibrium method was 15.83umol Cu(II) per gram of dry resin. Using the break-through capacity method (Figure C-3) gave a capacity of 9.89umol Cu (U) per gram of resin. The capacity measured corresponded to 0.02 to 0.03 miUiequivalents of charge/gram of dry resin. The capacity found was over 10 times smaller than the Chelex® 100 resin (at 0.4meq/mL resin). The capacity of the resin was found to be within the range other 8-HQ resins synthesized, although it was at the low end of the range. Persaud and Cantwell, 1992 found a capacity of264 ± 2umol Cu (IT) per gram of dry resin with an 8-HQ resin synthesized using the same chloromethylation/alkylation method as this paper. It is possible the differences in capacity are due to differences in cleaning steps performed between formation of the resin and analysis of the capacity. The purpose of their resin was to measure magnesium in seawater, and thus they may not have cleaned the resin as harshly before measuring the capacity. Seubert et al., 1995 performed a similar reaction in which the macroporous co-polymer was first chloromethylated and then the 8-HQ ligand attached through a Friedel-Crafts alkylation. They found a capacity of 2.8umol O r / m L resin bed volume. The capacity found was slightly lower than the one reported in this paper, although this possibly due to Seubert et al., 1995 not grinding polymer used for backbone of resin or their use of shorter reaction times during Friedel-Crafts Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 191 1.00 0 10 20 30 40 50 umol Cu (II) Figure C-3. Breakthrough curve for 8-HQ resin using a flow rate of 0.81mL/min and a 50ppm copper solution at a pH of 5.3. alkylation step. For other synthesized resins containing 8-HQ (or derivatives) bound to silica gels (TSK-Gel), a range of capacities from 23 to 190umol Cu (IT) per gram dry resin were measured (Dierssen et al., 2001). C-3.3. Recovery Tests In Table C-2, recovery test results for Chelex® 100 and the 8-HQ resin are given for different pHs. The 8-HQ resin gave comparable or higher recoveries for the metals analyzed, except for cadmium. Cadmium had lower and more variable recoveries for 8-HQ. The copper recovery was approximately 100% for 8-HQ at all pHs tested, which was higher than the Chelex® 100 recoveries but more variable. Variations in copper recoveries on Chelex 100 have been linked to copper organic complexation and the slow binding kinetics of Chelex® 100 (Florence and Batley, 1976; Bruland et al., 1979; Paulson, 1986). This suggested that 8-HQ resin has faster binding kinetics and/or higher affinity for copper than Chelex® 100. The higher affinity/faster binding kinetics may be due to the square planar arrangement of the 8-HQ binding sites. In Table C-3, 8-HQ resin recovery dependency on flow rate is given. The use of a faster flow rate appeared to have decreased the recovery for cadmium, although the Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 192 pH6 pH7 pH8 8-HQ Chelex 8-HQ Chelex 8-HQ Chelex Cadmium 82 ± 4 109 ± 3 107 ± 6 99±5 87 ± 5 103 ± 3 Cobalt 55 ± 11 n.d. n.d. n.d. 57± 11 n.d. Copper 103 ± 2 1 57 ± 4 104 ± 12 70 ± 6 108 ± 12 46 ± 3 Gallium 89 ± 6 93 ± 3 n.d. 72 ± 1 86 ± 5 70 ± 4 Manganese n.d. 83 ± 3 100 ± 15 83 ± 2 120 ± 8 95 ± 5 Table C-2. Recovery test results for both the 8-HQ and Chelex 100 resins using a flow rate of 0.8mL/min. Recovery values stated as percents ± 95% confidence interval. Standard deviation calculated with a sample size of 4 or 6. n.d. signifies that recovery was not determined for that pH. higher cadmium recovery at pH 7 may be anomalous considering the recoveries of 80-90% for pH 6 and 8. Gallium recoveries probably decreased with increased flow rate as well, given that pH 6 and 8 gave recoveries in the range of 80-90%. The overall recovery for the other metals increased with increased flow rate. This increase was also accompanied by a larger error. The testing of faster flow rates to see if this increase was indeed a trend was not possible due to the flow resistance within the resin. Faster flow rates could be achieved by eliminating the synthesis step in which the Amberlite XAD-2 resin was ground up to a smaller mesh size, although this would probably affect the capacity of the resulting 8-HQ resin similar to results of Seubert et al., 1995. 0.8mL/min 1.2mL/min Cadmium 107 ± 9 92 ± 6 Cobalt 55 ± 10 64 ± 7 Copper 104 ± 10 120 ± 3 0 Gallium n.d. 32 ± 1 Manganese 100 ± 13 124 ± 4 0 Table C-3. 8-HQ resin recovery dependency on flow rate using a pH of 7, stated as percents ± 95% confidence interval. Data for the recovery of gallium at a flow rate of 0.8mUmin was not available but would be expected to be in the range of 80-90% from pH dependence data. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 193 C-3.4. Calcium Results To determine the recovery of major salts from the seawater, calcium was analyzed. Calcium was used because it has a relatively high concentration in seawater, and is more favorably bound to Chelex® 100 than magnesium (Bio-Rad Laboratories). Using similar methods of concentration and elution, it was found that the acid eluent for the 8-HQ resin contained approximately 0.2 ± 0.1 ppm of calcium whereas the Chelex® 100 resin eluent contained 300 ± 90ppm. Although the measured calcium in the Chelex® 100 eluent was lower than the suggested upper limit for total dissolved solids (0.1%) contained in solutions entering an ICP-MS, a large decrease in internal standard signal over time (down to 50% within first 10-15 samples) and a plugging of sample cone was evident when analyzing these samples by ICP-MS. This was not a problem with the samples concentrated using the 8-HQ resin due to the lower concentration of salts in the samples. The salt content in the Chelex eluent can be decreased with larger buffer rinse volumes but only slightly (calcium decreased to 250ppm using a 12mL rinse) and the additional buffer rinse also reduced manganese recoveries. C -4. Conclusion Preliminary studies using this 8-hydroxyquinoline resin for the concentration of trace metals in seawater looked promising. Advantages of this resin over the commercially available Chelex® 100 included a higher selectivity towards trace metals, lower capacity and therefore less salts retained on the column, and no size change during the concentration and elution steps. Additionally, the 8-hydroxyquinoline resin gave better copper recoveries, due to either faster kinetics or higher affinity for copper. These advantages allow for analysis of trace metals in seawater that have very low concentrations naturally (such as gallium) and the option to incorporate this resin into a flow-injection system. The main problem with this synthesis was the use of the aluminum chloride Friedel-Crafts catalyst resulted in not being able to analyze aluminum. This may be overcome with extra cleaning steps, or use of a different catalyst. Optimization of synthesis, including whether or not to grind the resin and reaction times, and reference material analysis needs to be performed before this resin can confidently be used for trace metal analysis in seawater. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 194 C-5. References Bio-Rad Laboratories. Chelex® 100 and Chelex 20 Chelating Ion Exchange Resin Instruction Manual, Hercules, CA, USA. LIT 200 REV B. Bruland, K. W., Franks, R. P., Knauer, G. A. and Martin, J. H., 1979. Sampling and Analytical Methods for the Determination of Copper, Cadmium, Zinc, and Nickel at the Nanogram Per Liter Level in Sea-Water. Analytica Chimica Acta, 105(1): 233-245. Dierssen, H., Belzer, W. and Landing, W. M., 2001. Simplified synthesis of an 8-hydroxyquinoline chelating resin and a study of trace metal profiles from Jellyfish Lake, Palau. Marine Chemistry, 73(3-4): 173-192. Florence, T. M. and Batley, G. E., 1976. Trace-Metals Species in Sea-Water .1. Removal of Trace-Metals from Sea-Water by a Chelating Resin. Talanta, 23(3): 179-186. Hill, J. M., 1973. Silica-Gel as an Insoluble Carrier for Preparation of Selective Chromatographic Adsorbents - Preparation of 8-Hydroxyquinoline Substituted Silica-Gel for Chelation Chromatography of Some Trace Metals. Journal of Chromatography, 76(2): 455-458. Kingston, H. M., Barnes, I. L., Brady, T. J., Rains, T. C. and Champ, M. A., 1978. Separation of 8 Transition-Elements from Alkali and Alkalme-Earth Elements in Estuarine and Seawater with Chelating Resin and Their Determination by Graphite Furnace Atomic-Absorption Spectrometry. Analytical Chemistry, 50(14): 2064-2070. Landing, W. M., Haraldsson, C. and Paxeus, N., 1986. Vinyl Polymer Agglomerate Based Transition-Metal Cation Chelating Ion-Exchange Resin Containing the 8-Hydroxyquinoline Functional-Group. Analytical Chemistry, 58(14): 3031-3035. Merrin, C , 2002. Sources of Mn, Al, Cd, and Cu to Coastal Waters of the California Current System. Ph.D. Thesis, University of British Columbia, Vancouver, 178 pp. Paulson, A. J., 1986. Effects of Flow-Rate and Pretreatment on the Extraction of Trace-Metals from Estuarine and Coastal Seawater by Chelex-100. Analytical Chemistry, 58(1): 183-187. Persaud, G. and Cantwell, F. F., 1992. Detennination of free magnesium ion concentration in an aqueous solution using 8-hydroxyquinoline Immobilized on a Non-polar Adsorbent. Analytical Chemistry, 64: 89-94. Price, N. M., Harrison, G. I., Hering, J. G., Hudson, R. J., Nirel, P. M. V., Palenik, B. and Morel, F. M. M., 1988-1989. Preparation and chemistry of the artificial algal culture medium Aquil. Biological Oceanography(6): 443-461. Appendix C: Comparison of cationic resins for analysis of trace metals in seawater 195 Seubert, A., Petzold, G. and McLaren, J. W., 1995. Sythesis and application of an inert type of 8-hydroxyquinoline-based chelating ion exchanger for seawater analysis using online inductively coupled plasma mass spectrometry detection. Journal of Analytical Atomic Spectrometry, 10(5): 371-379. Sturgeon, R. E., Berman, S. S., Willie, S. N. and Desaulniers, J. A. H., 1981. Pre-Concentration of Trace-Elements from Sea-Water with Silica-Immobilized 8-Hydroxyquinoline. Analytical Chemistry, 53(14): 2337-2340. Warshawsky, A., Kalir, R. and Patchornik, A., 1978. Functionalization of polystyrene. 1. Alkylation with substituted benzyl halide and benzyl alcohol compounds. Journal of Organic Chemistry, 43(16): 3151-3157. Willie, S. N., Sturgeon, R. E. and Berman, S. S., 1983. Comparison of 8-Quinolinol-Bonded Polymer Supports for the Pre-Concentration of Trace-Metals from Sea-Water. Analytica Chimica Acta, 149(MAY): 59-66. 196 APPENDIX D: TRACE M E T A L DATA D-l. Description of Cruises Trace metal data for six cruises is given in the following pages. The data is organized first by year, then month then by station. For the eddy cruises, the order of stations is as follows: reference station, Haida-00 center and edge stations, and Haida-01 center and edge stations. D-2. Description of Table Data Data is organized in the tables as follows: Salinity: Defined using the Practical Salinity Scale Depth: Corrected using salinity measured from Go-Flo bottles (metres below sea surface) Sigma-0: Determined from salinity measurements and CTD data (unitless) Trace Metal: Total dissolved metals (< 0.22um) given in nM concentrations. Values below the limit of quantification (for definition, see Appendix B) are designated with an asterisk (*). Values that were not possible to determine were designated by a dash (-). Nutrients: Collected from rosette bottles at depths from 0 to 1000-3000m and analysed on a Technicon II Autoanalyser®, given in pM. Oxygen: Dissolved oxygen is given in umol kg"1 Appendix D: Trace Metal Data 1 9 7 a o 03 s a* 4> to "3 v C S a* O s 1-5 Z CM ^ CM 2 «o Q r-ay o m in co es H 8 <n y .2 3 *5b o oo O a, en O Oh 03 C O § 00 On O u s 03 U <x> s to ft a> O C/3 3 CS vo CS 00 CS m co cs © TT in OS vd r-" r-" 00 OS* OS os VO o CS CS CS CS 1—1 00 Os in 00 o ,—< rr" <n co CS r-- TT oo o OS O T-l r-H <n TT 00 VO co r-~; © »—< cs" cs" cs" co ro oo vq cs" cs vd cs in in cs co T T CO © o VO ro cs OS ro Os cs cs co* co co cs o ro OS in -3-^ o CO OS T P in oo os Os os r—1 © " o o" © " * oo CO OS o TT vq cs VO VO oc TT" in in in vd vd vd vd CS CS cs CS cs cs cs cs «n cs 0 ~ cs o o in ° . v3 ^ £ 22 £ VO OS cs vd o o CO r- cs cs TT vo >n os cs oo VO TT •*" © ' Tf T-H cs oo" cs' r - 1 cs CO CO CO Tf OO —i -3- r-~ o ©' cs 00 vo vo m o o o cs o oo © cs VO OS cs o m os CO CO vo cs in oo CO CO © o © o" o" © © * ©" o o" in VO in 00 VO OO CO OO cs r-in cs cs CO* r-" cs cs © © m © oo m © CO TT OS cs cs VO OS TI- TI- m o CO oo OS OS © CS' CS' cs cs' CO CO CO co TT' TT" CO co CO CO CO CO CO CO CO CO Appendix D: Trace Metal Data c TS 05 • * * C O u s U e © s "3 i 0> SO '3 u o «n o Q W o o CS a 3 1> 3 H (73 U co oo o o in co a eib c o r-1 c 00 >% x O OH CO O PL. 00 TH <U OH OH O U § c I cd C O H-» OH (L> Q C O oo] o a 1 s 'co B is 1 i u Tf Os o VO o vq 00 in O oo in m oo ON CO Tf' CN r~* r-" Os OS OS in o CN CN CM cs CN VO 00 ro <n CO vo vo* in Tf oo TT © CN o CO p CO T—H © os CN CO CN OO Tf co Tf m oo vq 00 OS T-H CN CN CN CN OO OO VO VO CO r— Tf OO OS CN CN Tt"' CO os TT r-" in in VD <n oo o o o co © OO m Tf CN r-; CN Tf r~- o Tf CO in CN T-H Tf r-* T - H T-H T-H CN CO CO CO TI-GS VO o vo T-H oo CN CO p TT vq p CO cs" CO Tf m os Tf T-H r- vo oo CO Tt" Tf CO Os CN o VD r-o" © © * o CO T-H os r-~ CN OS Os m CN in CO CN o OS in o OS oo in T—1 OS Tf vo vo r~l "-H »-H cs CN Tf in VO oo T—H © ' o" o © " © " © " o o © ' " — l OS vo in O oo o o CO vq in T^H VO Tf in cs CO oo CO Tf' Tf CN cs" CO Tf CO OS CN oo oo cs Tf vq OS m o oo o Tf* Tf* in" in in in vd vd vd CN cs cs cs CN cs CN cs cs cs in CN o m uo ° ° oo ~ £ o o cs o o CO o o C S T~* Tf VO r- o CO os VO Tf VO Tf cs cs CO Tf in T-H Os os o cs" cs' cs C N C S CO CO CO CO Tf" co co CO CO CO CO CO co CO co Appendix D: Trace Metal Data a o -** C 0 u bf) T3 es "SS I g M o ffi CN Q * _ CO H O co ° o Q W • in S CN 3 in CN NO ON O »n O CO ID •T-H T3 3 C o h-4. u 00 >> X o <u tx CO O OH 0) CO DO <u P-, O U S u S 3 i CO CO Q CO 3 (U CO 1 00 NO co NO OS NO o oo in O co Vi CO o NO ON in NO -rf CN ON ON ON ON OO co C N CM CN CN CN 00 ^r ON NO' OO NO CN <n NO NO ON o O o CN O ON CN OO NO in co oo CN i CN CN CN NO © NO in in CN © co -Tf © >—1 '—i i CN CO 1^" co CN NO oo o o o O ,—< in co co oo ON o CN NO ON oo NO CN oo NO CO o NO' © 1 — 1 CN co ro o oo >n CN <—< CN CN* CN CN O <n NO <n ^ - v o oo oo NO ON © o © O ON o o m NO NO NO >n ON CN OO o o o o o o o O o .132 CN CN r-CN CN in CN NO CN CO oo m NO CO CO oo ON CO o o o o o O o o o o T—1 NO o NO o oo 00 <n NO o CN CO o oo CO in" CN CN CO CO CO o 1—t CN ON <n 00 ON in in in NO NO NO NO CN CN CN CN CN CN CN CN CN o m CN o m O NO o o o o ON o o CO in o NO CN CO NO m CO ON CN ^t- ON TJ" in t-- 00 ON ON CN CN CN CN CN CO CO CO CO CO CO CO CO CO CO CO CO CO CO Table D-4. September 2000 Cruise - Reference Station Cruise #: 2000-30 Station Name: ED01 Latitude: 51'45.04 °N Longitude: 136' 09.93 °W Salinity Depth Sigma-6 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.44 10 24.2 6.00 0.106 1.21 1.99 0.50 7.4 0.43 271.12 32.44 25 24.3 4.78 0.053 14.32 1.94 0.82 7.6 0.46 268.71 32.45 50 25.4 6.01 0.136 6.51 2.03 8.31 13.0 1.03 296.74 32.75 70 25.7 4.24 0.531 0.98 1.90 14.05 18.8 1.32 263.81 33.84 150 26.6 - 0.579 0.94 1.03 30.81 46.4 2.22 132.14 33.91 200 26.7 4.91 0.599 0.76 0.91 34.80 56.5 2.48 103.49 33.94 310 26.9 2.94 0.697 0.89 0.81 39.61 72.7 2.81 72.93 34.03 425 27.0 2.20 - 1.11 1.80 42.40 88.5 3.03 43.00 to o o Table D-5. September 2000 Cruise - Haida-00 Center Station Cruise #: 2000-30 Station Name: ED05 Latitude: 52' 45.15 °N Longitude: 136' 09.99 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) - 10 24.2 2.11 0.041 2.94 0.84 0.00 6.0 0.41 308.16 32.28 25 24.4 5.08 0.040 4.76 2.08 2.08 7.9 0.58 278.47 32.29 50 25.3 4.81 0.156 5.80 1.46 12.10 17.7 1.17 253.86 32.54 70 25.5 5.75 0.273 0.87 2.09 14.28 20.8 1.30 253.03 32.80 100 25.7 4.22 0.627 0.87 1.61 17.29 25.6 1.48 231.96 33.52 150 26.3 4.85 0.554 0.74 0.71 28.05 43.0 2.13 133.64 33.90 315 26.7 2.46 0.785 0.66 0.89 34.36 56.4 2.49 91.30 34.05 610 27.0 1.78 0.430 0.85 0.54 40.92 88.0 2.93 45.45 Appendix D: Trace Metal Data 202 © CZ! 6X1 "O i S3 -O et a i so '3 i . U O CN U V V o "S ^ G. • a> o " o GO N O Q =tfe ij co O E M o 05 E <D 1 0 0 _ ) b D C o O •a co O PH 0) CO b D u C L , O O S 3 <r> • s b D C O Q C O 0 0 3 o C O 3 •a £ ca w U N O o oo N O O CO N O oo o N O CN N O © O N O N r-i N O N O o CN CN CN CN CN CN i CO O N CN CN CN © oo <n CO i n O N r- co O N « — I O N CN CO CO N O 00 © in N O O N CN OO in* CN O N O N I - * CN N O co CN o N O O N CO oo N O CO CO CN O N i—i CO i™™* o C O N O CN O NO i n CN ^ i-i r-o CN CO CN CO CO Tf "4* "3* CN CN CN <n CN in CN N O in CN O N O CN 00 N O CN o i n y-i CN O m in N O o oo o CN 00 -1 00 i—i O i—i i—• i—i CN CN m CN i™^  CO CN m N O N O O N o O N CN CN in CO N O 00 N O CO 1 - ' O N O N «—4 CN o * oo i—< i—• N O © " CO I - 1 CN CO N O N O m N O 00 O N oo o 00 •3- CO CN o in ,—* oo CN o o CN 00 1—1 m N O © ' © " © o o o "- , o © O N CN CO ON I - I N O K CN CN © © <n © © 00 co -rj- in CN 00 O N in T—1 in © CO N O O N N O O N © CN CN CN CN CO co CO CO CO CO CO CO CO CO Appendix D: Trace Metal Data c o 03 ce u a U © o I 03 S '3 K i <u W) • w* 3 U £ 9 3 S u to o ^ p Q os o <u CO o O H CO cs 3 in Z "J 2 . 2 2 03 2 H U 03 "£ C O 3 H-» bO C o Oxygen (umol/kg) 305.55 305.12 3U0.4U 302.81 62.97 Phosphate (uM) 1.30 1.30 1.31 1.39 2.89 Silicate (uM) 16.6 16.3 16.4 17.6 71.0 Nitrate (uM) 13.90 14.00 14.12 15.32 39.75 Manganese (nM) o oo t~- r-~ os CO OS T f CO CO Copper (nM) 1.57 1.32 1.35 1.56 2.40 Cadmium (nM) 0.291 0.309 0.282 0.710 Aluminum (nM) 3.47 2.83 1.23 1.54 3.44 Sigma-9 25.7 25.7 95 7 AD. 1 25.7 26.9 Depth (m) o «n o v~> 2 - CN T f r - o Salinity 32.65 32.65 32 65 32.70 33.98 Table D-8. February 2001 Cruise - Haida-01 Center Station Cruise #: 2001-06 Station Name: ME01 Latitude: 52' 52.18 °N Longitude: 132' 48.00 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.37 10 25.3 8.99 0.239 1.64 2.99 11.60 17.5 1.18 295.74 32.37 25 25.3 8.54 0.252 1.65 3.48 11.80 17.8 1.18 295.91 32.38 40 25.3 7.75 0.246 1.57 3.32 12.02 18.1 1.20 295.81 32.40 75 25.3 10.79 0.395 2.81 2.86 12.51 18.6 1.23 298.19 33.97 400 26.9 3.63 0.776 2.20 3.61 38.90 68.9 2.81 68.98 Table D-9. June 2001 Cruise - Reference Station Cruise #: 2001-08 Station Name: ED 19 Latitude: 52' 45.0 °N Longitude: 137' 0.1 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.58 10 25.3 2.63 0.324 0.92 1.26 10.13 16.0 1.09 313.80 32.60 25 25.5 2.33 0.374 1.04 1.32 10.56 16.2 1.11 321.70 32.61 40 25.5 2.74 0.490 0.87 1.52 11.01 16.7 1.15 319.90 32.65 70 25.6 2.09 0.439 0.91 1.87 12.30 17.8 1.23 310.57 32.85 85 25.9 3.38 0.645 1.48 1.10 16.59 23.4 1.47 281.74 33.81 150 26.7 1.83 1.241 1.55 0.56 34.00 55;0 2.42 123.13 33.87 200 26.8 1.83 1.310 1.30 0.58 36.88 64.8 2.62 101.13 33.96 320 26.9 1.70 1.415 1.16 1.02 40.97 81.6 2.90 62.51 34.08 420 27.0 2.04 1.371 1.23 1.43 42.69 94.1 3.05 35.97 34.21 600 27.2 1.97 1.381 1.95 1.22 44.35 115.4 3.16 20.49 34.29 770 27.3 1.07 1.260 1.42 0.68 44.51 129.8 3.19 18.49 34.37 980 27.4 1.92 1.876 1.87 0.68 44.95 144.2 3.21 16.38 2 O Appendix D: Trace Metal Data 206 a #© « CO s. a « U « '3 i an '3 u CN m o o Q os —• w So 8 TT =3 o CO 00 o H-l c u 00 X O ts OH a> O 4 3 P H c3 O CO 00) o o T f C N O s 00 T f CO T f C N VO T f o o r-" T-H OS T f o o OS 00 c o C N C N CN C N C N T - H SO T f o T - H CO <n T f OO VO OS i n CO OS o* o i n C N C-" i n SO o CO CO CO r~-i n r -C N i n T f C N 00 o o p m C N C N CN* C N CO CO CO i n i n so so OS OS o o SO o o CO OS i n r-" C N C N C N T f m r - o o CO r-- _ Tf" i n o o C N T f T - H T - H rate s CO OS T f m T f o C N SO r -T f C N o s o o v q CO VO v q r--s o T f 00 o d O s o T - H Tf* oo" CO Tf* CO o o CO T f CO T f T f T f T f T f ese 00 CO i n s q 00 CO T f OS C N i n o o s T f CO CO o o o CO l > T - H '—1 T - H '- 1 '-" o © T - H 1—1 T " H T - H T - H pper pper /-—s o o CO CO C N S O T f S O T f o OS i n r -T f o s C N v o CO p o o Co W CN* CN CN* CO C N admium | r -C N C N S O i n C N i n OS CN i n CO O s OO T f CO o o o o C N O s C N o T - H s o <—i SO VO o OS r--CN admium o o O o o © o u um G T - H o o T - H C N S O O CO T f T f O s v q T f v q r— CO 00 OS . 00 O i n 1-H C N C N t-" T - ^ CO* < CD dj CO i n i n O s i n t ~ - o o OS T - H CO T f J) i n " C N i n C N i n " C N i n C N i n C N s d C N s d C N S O C N v d C N C N r-" C N i > C N CO Depth (m) o T—H m C N o T f OS r-~ o o O i n i n C N C N o C N CO O OS CO i n s o m o 00 o r~-o s • r H C CO i n s o m OS i n o r -o OS m OS m OS T - H o CN T - H m C N CO CO Sali C N CO C N CO C N CO C N CO CN* CO CO CO CO CO CO CO Tf* CO Tf* CO T f CO Tf* CO Table D- l l . June 2001 Cruise - Haida-00 Edge Station Cruise #: 2001-08 Station Name: ED28 Latitude: 54' 55.0 °N Longitude: 138' 9.8 °W Salinity Depth Sigma-0 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.51 10 25.1 1.14 0.154 1.23 1.55 8.33 13.9 1.00 301.10 32.53 25 25.3 1.67 0.173 1.01 1.40 8.33 14.5 1.01 304.50 32.55 40 25.4 1.14 0.304 1.11 1.49 9.13 15.0 1.07 305.30 32.61 79 25.6 2.34 0.397 1.20 1.-31 12.03 17.2 1.23 298.67 33.01 110 25.9 2.15 0.626 1.36 0.94 19.75 27.4 1.64 239.45 33.78 165 26.5 3.57 0.965 1.16 0.63 30.83 46.8 2.25 130.51 33.88 200 26.7 1.54 1.061 1.36 0.46 33.16 53.2 2.39 116.89 33.95 320 26.9 1.38 1.157 1.39 0.83 39.21 73.1 2.79 75.03 34.15 490 27.0 1.48 1.230 1.62 1.01 42.94 96.0 3.07 38.23 34.27 800 27.3 1.54 1.197 1.63 1.00 45.39 125.4 3.21 17.19 34.35 980 27.4 1.75 1.249 1.93 0.85 45.27 138.7 3.25 15.29 to o -o Table D-12. June 2001 Cruise - Haida-01 Center Station Cruise #: 2001-08 Station Name: ED 15 Latitude: 51' 15.0 °N Longitude: 133' 59.9 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.35 10 25.0 0.86 0.197 1.18 4.14 5.85 8.4 0.83 298.49 32.36 25 25.1 6.21 0.207 0.45 4.23 5.79 8.4 0.83 299.92 32.40 40 25.2 1.09 0.217 1.22 4.12 7.08 10.0 0.93 296.00 32.60 65 25.5 1.52 0.338 1.28 2.59 12.11 16.7 1.21 270.19 33.17 95 25.9 2.06 0.781 1.41 1.52 21.74 31.1 1.74 189.12 33.81 155 26.5 3.24 0.825 1.35 5.67 31.06 47.1 2.30 106.48 33.92 190 26.6 2.33 1.250 1.99 2.31 33.27 52.7 2.41 94.70 33.96 250 26.7 2.11 1.284 1.67 1.91 35.57 58.9 2.56 81.21 34.02 390 26.9 23.92 0.926 1.51 2.77 39.43 74.4 2.84 54.81 34.11 610 27.0 1.97 0.994 2.13 0.37 42.99 92.7 3.08 31.87 34.23 825 27.2 2.05 1.442 1.75 1.62 39.95 99.5 2.91 15.44 34.35 1035 27.3 3.57 1.436 2.02 1.47 0.00 0.0 0.00 12.43 Table D-13. June 2001 Cruise - Haida-01 Edge Station Cruise #: 2001-08 Station Name: ED8b Latitude: 51 ' 35.0 °N Longitude: 133' 50.2 °W Salinity Depth Sigma-0 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.41 10 25.2 0.82 0.201 1.08 2.23 7.25 11.0 0.58 307.10 32.47 25 25.3 4.58 0.251 0.57 1.56 8.26 12.8 0.63 308.10 32.50 40 25.3 0.92 0.280 1.06 3.52 8.62 13.5 0.66 310.32 32.58 75 25.5 1.61 0.257 1.19 1.41 10.01 14.2 0.80 300.86 32.82 95 25.7 1.91 0.465 1.43 1.25 12.82 18.2 1.14 248.32 33.79 160 26.5 1.20 1.210 1.20 1.15 30.86 43.7 1.93 128.90 33.97 295 26.8 1.80 1.309 2.12 1.04 37.85 63.6 2.41 83.30 34.00 375 26.9 6.02 1.012 1.63 1.20 40.20 74.8 2.65 61.95 34.16 630 27.1 3.20 1.039 1.42 1.47 43.86 102.8 3.04 24.60 34.29 825 27.3 0.98 1.522 1.67 1.21 45.07 121.7 3.13 13.98 34.37 1000 27.4 1.42 1.508 3.24 1.62 45.11 133.3 3.15 13.21 O N O Appendix D: Trace Metal Data 210 a '& 85 •*•» CO <u o S3 u Cm V S o CN -Q a r—I Oa c n 4* Z <n «n r r I Q 05 H i—i • • c n o J> „ O g CN ( N a m 4t "" o <D oo g 03 -*-» CO <D a 00 c n <D a 5b e o a (D 00 O <D 9-co O fin CO <D co a> oo (D a, a, o U S T 3 03 U 03 CO a. ID Q a co (D 1 I o o o ON NO rf r~- ON CN CN c n <n r-" c n ON c n O o r - oo ON o O ON CN CN CN c n c n CN ON CN ON CN CN O NO ON 00 ON" o ON >n "— 1 CN o NO o CN OO rf i n C N C N m rf ON ON 00 ON C N C N C N c n e n c n o c n C N c n NO , - . N O rf' rf' C N C N c n ON i n r-- 00 ;_; NO o ,—< OO © < C N rf 1 — 1 1—i i—i ON o o ON 00 ON ON rf i n NO 00 i n o o NO NO OO o o o o ON i n ON 00 ,—< c n rf rf * 1 C N c n rf rf rf rf o o c n m c n o o c n ON *-< i n c n 00 NO m NO o o c n o C N C N O i n O c n t—i CN i—i i n o i n c n rf T - H i n NO o o c n C N rf c n C N O o o o o c n 1—t rf O N rf m c n c n c n N O NO o c n c n o o" © o © ' o C N c n o ON o 00 ON © m NO i n c n © o © —« ON NO NO >n NO NO 00 m 00 ON C N rf rf i n i n i n NO NO NO C N C N C N C N C N C N C N C N C N i n C N o rf O 8 S o o i n i—i ON I—i C N C N NO r - i i n r - l O c n o o rf rf C N c n o © ~ c n i n © ON 00 00 o o © c n C N rf C N o o t~- i n t - ON C N C N ON C N 00 00 ON c n c n ON NO rf rf rf NO NO c n ON C N C N c n C N C N C N C N C N c n c n c n rf rf rf c n c n c n c n c n c n c n c n c n c n c n Table D-15. September 2001 Cruise - Haida-00 Center Station Cruise #: 2001-31 Station Name: HOOF Latitude: 54' 29.7 °N Longitude: 138' 20.2 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.28 10 24.5 1.56 0.035 1.10 2.57 3.46 11.8 0.74 274.20 32.28 25 24.5 1.13 0.027 0.94 2.16 3.49 11.6 0.76 274.53 32.39 40 24.9 1.54 0.072 0.90 2.37 7.48 14.2 0.96 277.23 32.81 85 25.7 2.04 0.620 0.91 1.45 18.30 25.3 1.57 241.22 33.41 135 26.2 2.19 0.738 0.89 0.92 27.66 40.6 2.11 152.82 33.74 170 26.5 1.67 0.917 1.38 0.79 32.39 48.6 2.36 105.61 33.94 320 26.8 1.50 1.061 1.43 1.29 36.81 63.2 2.65 65.46 34.09 570 27.0 1.58 1.201 1.94 1.28 42.63 92.7 3.05 36.84 34.22 775 27.2 2.19 1.188 1.06 0.97 44.20 114.1 3.17 19.47 34.30 930 27.3 6.40 1.205 1.54 1.16 45.30 126.1 3.21 16.82 to Table D-16. September 2001 Cruise - Haida-00 Edge Station Cruise #: 2001-31 Station Name: H00L Latitude: 54' 00.0 °N Longitude: 138' 44.95 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.29 10 24.6 1.19 0.054 1.08 1.85 4.01 11.7 0.76 282.10 32.33 25 24.7 0.71 0.065 1.24 1.82 5.27 12.6 0.83 281.75 32.47 40 25.2 0.77 0.416 1.12 1.75 9.82 15.5 1.09 284.12 32.73 75 25.7 1.53 0.601 1.21 1.38 18.05 25.9 1.55 249.71 32.98 100 25.9 1.19 0.707 1.52 1.06 21.16 30.1 1.72 223.34 33.81 170 26.6 1.43 1.067 1.60 0.63 31.89 49.9 2.31 120.14 33.89 215 26.7 0.90 1.091 1.69 0.52 33.39 54.7 2.38 116.90 33.94 300 26.8 1.06 1.224 1.38 0.63 38.51 69.2 2.69 79.41 33.99 375 26.9 1.91 1.251 1.51 1.07 40.30 80.0 2.85 60.06 34.16 625 27.1 0.96 1.296 1.92 1.19 43.94 105.6 3.13 23.35 34.27 790 27.3 1.36 1.303 1.52 1.08 44.94 119.2 3.20 16.87 34.33 940 27.4 0.96 1.208 2.10 1.04 44.87 130.5 3.22 15.28 O to to Appendix D: Trace Metal Data e _© 03 u a u 0 3 2 '3 '3 u o & v CH m U i ^§ I o S £ s -CM OS OS m co M M 03 £ fl -g 3 ,2 3 '5b Oxygen (umol/kg) 273.97 272.60 m 11 221.71 147.06 90.07 23.67 Phosphate (uM) 0.83 0.82 1.56 2.03 2.46 3.10 Silicate (uM) 8.9 9.0 9.4 24.4 37.0 53.2 96.1 Nitrate (uM) 5.02 5.01 C 1 C\ 5.19 18.77 26.82 34.52 43.70 Manganese (nM) 2.31 1.94 9 ft7 1.66 1.20 1.26 1.33 Copper (nM) 2.20 1.65 1 an 1.67 1.40 1.26 1.53 1.31 Cadmium (nM) 0.113 0.093 c\ no7 0.499 0.663 0.865 0.691 Aluminum (nM) 1.91 1.82 1.47 1.84 3.15 8.88 1.35 Sigma-0 24.6 24.6 94 7 25.7 26.2 26.6 27.1 Depth (m) o uo o «/o g g § - < N T J - r- 2 C N S O Salinity 32.30 32.30 32 33 32.89 33.46 33.93 34.14 H O &o i—l i—l Table D-18. September 2001 Cruise - Haida-01 Edge Station Cruise #: 2001-31 Station Name: HOI B Latitude: 50' 45.01 °N Longitude: 134' 45.0 °W Salinity Depth Sigma-6 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.30 10 24.6 1.35 0.081 1.73 1.74 4.81 10.1 0.81 290.30 32.42 40 25.0 1.82 0.084 1.22 1.73 8.35 14.3 1.00 277.64 32.71 70 25.6 0.54 0.327 0.85 1.26 15.74 24.1 1.41 251.04 33.07 100 25.9 2.98 0.495 1.14 1.02 21.91 30.3 1.75 214.22 33.93 200 26.7 2.82 0.861 1.21 0.93 34.01 52.5 2.40 105.63 34.01 400 26.9 0.62 0.968 1.22 1.33 41.39 80.7 2.90 56.56 Table D-19. September 2002 Cruise - Ocean Station Papa Cruise #: 2002-30 Station Name: Station P Latitude: 50' 0.14 °N Longitude: 145' 0.26 °W Salinity Depth Sigma-6 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.60 25 - 0.192* 0.225 1.18 1.23 9.59 14.2 1.00 286.11 32.75 40 - 0.27 0.417 1.25 1.53 13.71 21.8 1.35 306.81 32.74 50 - 1.06 0.485 5.43 1.52 15.49 24.6 1.40 313.99 32.81 75 - 0.34 0.634 1.37 1.53 18.64 28.0 1.65 309.07 32.87 100 - 0.30 0.666 1.51 1.73 20.85 32.3 1.77 304.38 33.74 200 - 0.45 1.001 1.95 1.14 36.68 68.2 2.67 108.65 33.88 300 - 0.42 1.012 3.18 1.26 41.46 85.2 2.99 61.33 34.03 400 - 0.48 1.099 1.36 1.37 43.56 99.8 3.13 43.68 34.19 600 - 0.26 1.030 1.65 1.04 45.54 118.4 3.19 25.71 34.30 800 - 0.52 1.145 1.66 0.77 43.96 132.2 3.25 22.83 Table D-20. September 2002 Cruise - Hecate Strait Coastal Station Cruise #: 2002-30 Station Name: MT08 Latitude: 53' 09.735 °N Longitude: 130' 26.213 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 31.35 10 - 1.21 0.456 3.84 11.15 6.97 26.3 0.88 -32.00 40 - 1.65 0.615 3.01 9.06 16.25 35.5 1.50 -33.61 160 - 0.60 0.973 1.65 9.37 34.54 64.2 2.64 -33.67 175 - 0.39 0.933 1.52 8.41 35.44 65.2 2.67 -Table D-21. September 2002 Cruise - Hecate Strait Coastal Station Cruise #: 2002-30 Station Name: MT10 Latitude: 53' 37.04 °N Longitude: 130' 44.86 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 31.41 10 - 1.20 0.474 3.29 15.82 6.51 14.8 1.01 -31.80 40 - 1.18 0.571 4.93 12.54 13.38 26.7 1.44 -33.36 165 - 0.65 0.966 1.69 34.56 34.75 71.4 2.82 -33.36 170 - 0.84 0.989 1.80 32.19 35.02 74.4 2.83 -Table D-22. September 2002 Cruise - Queen Charlotte Sound Cruise #: 2002-30 Station Name: P C I Latitude: 53' 35.8 °N Longitude: 130' 17.6 °W Salinity Depth Sigma-6 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 30.76 10 - - 0.439 - - 16.46 29.7 1.46 -32.38 100 - - 0.520 - - 25.36 45.3 2.10 -32.38 100 - - 0.512 - - 25.36 45.3 2.09 -32.79 300 - - 0.548 - - 27.84 50.3 2.26 -32.81 375 - - 0.561 - - 28.00 51.4 2.28 -Table D-23. September 2002 Cruise - Queen Charlotte Sound Cruise #: 2002-30 Station Name: M T 3 Latitude: 51 ' 56.9 °N Longitude: 130' 27.0 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.08 10 - - 0.230 - - 8.44 20.4 1.02 -32.28 100 - - 0.372 - - 11.06 23.1 1.21 -33.56 175 - - 0.625 - - 30.53 56.2 2.56 -33.90 200 - - 0.669 - - 33.78 57.1 2.74 -34.02 B-25 - - 0.719 - - 39.57 80.9 3.30 -34.03 B-10 - - 0.854 - - 39.89 82.1 3.31 -to 00 Table D-24. September 2002 Cruise - Queen Charlotte Sound Cruise #: 2002-30 Station Name: J5 Latitude: 51' 27.4 °N Longitude: 132' 23.6 °W Salinity Depth Sigma-9 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.19 10 - - 0.010 - - 0.00 4.5 0.40 -32.19 25 - - 0.016 - - 0.00 4.2 0.44 -32.45 40 - - 0.116 - - 8.34 8.8 1.13 -32.50 75 - - 0.291 - - 14.29 16.4 1.36 -32.56 100 - - 0.359 - - 15.69 18.7 1.45 -33.50 150 - - 0.577 - - 26.83 39.5 2.04 -33.79 200 - - 0.712 - - 31.51 50.4 2.28 -33.93 300 - - 0.740 - - 36.65 64.7 2.64 -33.97 400 - - 0.767 - - 39.89 77.1 2.85 -34.14 600 - - 0.799 - - 43.64 104.0 3.14 -34.28 800 - - 0.824 - - 44.74 119.3 3.27 -to NO Table D-25. September 2002 Cruise - Queen Charlotte Sound Cruise #: 2002-30 Station Name: R l l Latitude: 51' 15.1 °N Longitude: 136' 40.4 °W Salinity Depth Sigma-8 Aluminum Cadmium Copper Manganese Nitrate Silicate Phosphate Oxygen (m) (nM) (nM) (nM) (nM) (uM) (uM) (uM) (umol/kg) 32.26 10 - - 0.051 - - 1.81 2.0 0.53 -32.26 25 - - 0.079 - - 3.67 3.7 0.71 -32.50 40 - - 0.310 - - 12.68 11.7 1.29 -32.54 75 - 0.53 0.311 1.28 1.09 14.60 16.1 1.44 -32.61 100 - - 0.373 - - 16.52 19.5 1.54 -33.25 150 - - 0.569 - - 25.29 34.8 2.02 -33.84 200 - - 0.723 - - 33.56 51.2 2.48 -33.93 300 - 0.73 0.792 1.45 0.69 39.33 70.3 2.86 -33.99 400 - - 0.778 - - 42.02 82.8 3.03 -34.18 600 - - 0.815 - - • 44.10 106.5 3.22 -34.30 800 - - 0.806 - - 45.01 124.5 3.29 -NJ NJ O 

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