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Concentration and size partitioning of trace metals in surface waters of the global ocean and storm runoff
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Concentration and size partitioning of trace metals in surface waters of the global ocean and storm runoff
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Content
CONCENTRATION AND SIZE PARTITIONING OF TRACE METALS IN SURFACE
WATERS OF THE GLOBAL OCEAN AND STORM RUNOFF
by
Paulina Pinedo Gonzalez
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(GEOLOGICAL SCIENCES)
August 2016
Copyright 2016 Paulina Pinedo Gonzalez
ii
Acknowledgements
I would like to thank all the people who made this work possible.
First, I’d like to thank my two wonderful advisors Dr. A. Joshua West and Dr. Sergio
Sañudo-Wilhelmy. Your guidance, insight, knowledge, and support over the course of
my Ph.D. have been inspirational. I can’t be grateful enough for your kind words
during my I-can’t-do-this-anymore moments and for encouraging me to be a better
scientist everyday.
I would like to say a big thank you to my dissertation and qualifying exam committees,
Dr. David Hutchins, Dr. Doug Hammond, and Dr. Jan Amend, for your well-directed
comments, questions, guidance, and time.
A big thank to the Earth Sciences department. To the staff and professors that make
this department the BEST department at the university. I will always feel proud to be
part of this beautiful geo-family.
I thank my friends and lab family for sharing this experience with me. For all the beer
we drank, the songs we danced/sang, the tears we shared and for all the wonderful
memories I’ll cherish forever. Thank you for being my friends, I love you all.
A special thank to Kirstin, for being the best office mate and friend I could have ever
asked for. Thank you for being there for me through all the good and bad times and for
all the silliness we shared over the last 3 years.
Gracias a toda mi familia por su apoyo y amor incondicional, y por siempre recibirme
con una gran sonrisa a la hora que sea en el aeropuerto. Gracias mamá y papá por ser
los mejores papás del mundo, por quererme y apapacharme aunque estemos a muchos
kilometros de distancia. Cada uno de mis logros hubiera sido imposible sin ustedes.
Gracias hermanos y sobrinos porque cada uno de ustedes son parte esencial de mi. Los
amo a todos.
Finally, I’d like to thank Raúl for sharing this journey with me. Espero que podamos
sumar más historias de éxito y felicidad a nuestra vida juntos.
iii
Contents
Acknowledgements
List of Tables
List of Figures
Abstract
1 Introduction
1.1 The role of trace metal as micronutrients to phytoplankton
1.2 Size fractionation of metals between the colloidal and soluble pools
1.3 Trace metals as tracers for anthropogenic inputs
1.4 References
2 Diel changes in trace metal concentration and distribution in
coastal waters: Catalina Island as a study case
2.1 Opening statement
2.2 Introduction
2.3 Materials and methods
2.4 Results and discussion
2.4.1 Light intensity and water temperature variations in the
surface ocean off Catalina Island
2.4.2 Metals showing distributions and size-fractionation
independent of diurnal cycles
2.4.3 Metal distributions and size fractionation influenced by
diurnal variations
2.4.4 Potential processes controlling diurnal concentrations and
partitioning of trace metals in coastal waters off Southern
California
2.5 Conclusions
2.6 References
3 Surface distribution of dissolved trace metals in the oligotrophic
ocean and their influence on phytoplankton biomass and
productivity
3.1 Opening statement
3.2 Introduction
3.3 Methods
3.3.1 Malaspina Circumnavigation Expedition
ii
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viii
x
1
2
5
6
7
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15
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40
iv
3.3.2 Collection and analysis of samples for trace metals
3.3.3 Collection and analysis of nutrients and chlorophyll a
3.3.4 Phytoplankton productivity measurement
3.3.5 Data interpretation
3.4. Results and discussion
3.4.1 Trace metals, hydrography, and phytoplankton productivity
3.4.1.1 Indian Ocean
3.4.1.1.1 Hydrography
3.4.1.1.2 Surface trace metal distribution and
phytoplankton biomass and production
3.4.1.2 Atlantic Ocean
3.4.1.2.1 Hydrography
3.4.1.2.1.1 Colombia to Spain transect
3.4.1.2.1.2 Spain to Brazil transect
3.4.1.2.1.3 Brazil to South Africa transect
3.4.1.2.2 Surface trace metal distribution and
phytoplankton biomass and production
3.4.1.2.2.1 Colombia to Spain transect
3.4.1.2.2.2 Spain to Brazil transect
3.4.1.2.2.3 Brazil to South Africa transect
3.4.1.3 Pacific Ocean
3.4.1.3.1 Hydrography
3.4.1.3.1.1 New Zealand to Hawaii transect
3.4.1.3.1.2 Hawaii to Panama transect
3.4.1.3.2 Surface trace metal distribution and
phytoplankton biomass and production
3.4.1.3.2.1 New Zealand to Hawaii transect
3.4.1.3.2.2 Hawaii to Panama transect
3.4.2 Temporal changes in trace metal concentrations in the
surface Atlantic Ocean
3.4.3 Effect of trace metals, hydrography and macronutrients on
phytoplankton biomass and productivity
3.5 Conclusions
3.6 References
4 Changes in the size partitioning of metals in storm runoff following
wildfires: implications for the transport of bioactive trace metals
4.1 Opening statement
4.2 Introduction
4.3 Method
4.3.1 Study area
4.3.2 Storm-water sampling
4.3.3 Analytical procedure
41
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v
4.4 Results and Discussion
4.4.1 Total dissolved concentration
4.4.2 Partitioning
4.5 Conclusions
4.6 References
5 Assessment of dissolved Pb concentration and isotopic composition
in surface waters of the modern global ocean
5.1 Opening Statement
5.2 Introduction
5.3 Materials and methods
5.3.1 Malaspina Circumnavigation Expedition
5.3.2 Collection and analysis of samples for Pb and Pb isotopes
5.4 Results
5.4.1 Surface distributions of Pb
5.4.1.1 Surface distribution of Pb in the Global Ocean
5.4.1.2 Surface distribution of Pb in the Indian Ocean
5.4.1.3 Surface distribution of Pb in the Atlantic Ocean
5.4.1.4 Surface distribution of Pb in the Pacific Ocean
5.4.2 Surface distribution of Pb isotopes
5.4.2.1 Surface distribution of Pb isotopes in the Indian
Ocean
5.4.2.2 Surface distribution of Pb isotopes in the Atlantic
Ocean
5.4.2.3 Surface distribution of Pb isotopes in the Pacific
Ocean
5.5 Discussion
5.5.1 Temporal evolution of Pb and Pb isotopes in the North
Pacific Ocean
5.5.2 Possible Pb sources to Surface Waters
5.5.2.1 Possible Pb sources to the Indian Ocean
5.5.2.2 Possible Pb sources to the Atlantic Ocean
5.5.2.3 Possible Pb sources to the Pacific Ocean
5.6 Conclusions
5.7 References
6. Conclusions
Appendix A
Appendix B
Appendix C
Appendix D
89
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95
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vi
List of Tables
3.1 Best Fit Linear Models and Diagnostic Statistics for Primary
Productivity
3.2 Variables and Correlation Type (Positive or Negative)
4.1 Characteristics of the sampling sites
4.2 Concentrations of trace metals (µg L
-1
)
5.1 Historical Pb concentrations and isotopic composition of surface
waters of the North Pacific Ocean near Hawaii
A.1 Analytical results of the analysis of seawater reference material
A.2 Mann-Whitney U-test results
A.3 Total dissolved trace metal concentrations, June 2012
A.4 Soluble trace metal concentrations, June 2012
A.5 Colloidal trace metal, June 2012
A.6 Total dissolved trace metal concentrations, July 2012
A.7 Soluble trace metal concentrations, July 2012
A.8 Colloidal trace metal concentrations, July 2012
A.9 Temperature, light intensity, and Chlorophyll-a values measured in
the surface ocean off Catalina Island in July 2012
B.1 Complete list of Longhurst biogeographical provinces
B.2 Total dissolved trace metal concentrations, salinity, temperature,
PO
4
, NO
3
, SiO
4
, Chlorophyll a (Chl-a) and depth integrated
primary productivity (PPi), measured during the circumnavigation
expedition Malaspina 2010
B.3 Analytical results of the analysis of seawater reference material
B.4 Dissolved nutrients values from laboratory culture experiments
65
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163
163
vii
C.1 Total dissolved and soluble trace metal concentrations measured in
the San Gabriel Control and Burned catchments
C.2 Total dissolved and soluble trace metal concentrations measured in
the Los Angeles, San Gabriel and Santa Clara Rivers
D.1 Dissolved Pb, and
206
Pb/
207
Pb,
208
Pb/
206
Pb isotope ratios measured
in the surface ocean during the circumnavigation expedition
Malaspina 2010 from December 2010 to July 2011
164
165
166
viii
List of Figures
2.1 Map of the study site and diel light intensity and temperature
variations
2.2 Variations in total dissolved, soluble, and colloidal Ni (A), Ag (B),
V (C), and Mo (D) concentrations
2.3 Diel changes in total dissolved, soluble, and colloidal Pb (A), Fe
(B), Cu (C), Cd (D), Co (E), and chlorophyll a (F) concentrations
3.1 Map of the cruise track and Longhurst biogeochemical ocean
provinces
3.2 Hydrological, biological, trace-nutrient and macronutrient for the
Indian Ocean
3.3 Hydrological, biological, trace-nutrient and macronutrient for the
transect from Colombia to Spain in the Atlantic Ocean
3.4 Hydrological, biological, trace-nutrient and macronutrient for the
transect from Spain to Brazil in the Atlantic Ocean
3.5 Hydrological, biological, trace-nutrient and macronutrient for the
transect from Brazil to South Africa in the Atlantic Ocean
3.6 Hydrological, biological, trace-nutrient and macronutrient for the
transect from New Zealand to Hawaii in the Pacific Ocean
3.7 Hydrological, biological, trace-nutrient and macronutrient for the
transect from Hawaii to Panama in the Pacific Ocean
3.8 Map of oceanographic campaigns in the Atlantic Ocean
3.9 Hydrological, biological, trace-nutrient and macronutrient
distributions and box-and-whiskers plot
3.10 Observed versus modeled primary productivity
4.1 Map of the study site
4.2 Stage height records and detailed hydrographs
4.3 Hydrographs for a storm event on December 3, 2012
16
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ix
4.4 Total dissolved and soluble concentrations of metals in storm
runoff
4.5 Percentage of soluble metals in storm runoff
4.6 Mean colloidal and soluble fractions in storm runoff
5.1 Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb ratios in the global ocean
5.2 Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb ratios in the Indian Ocean
5.3 Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb ratios in the Atlantic Ocean
5.4 Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb ratios in the Pacific Ocean
5.5 Dissolved lead concentrations and isotopic composition of surface
waters of the North Pacific Ocean near Hawaii for the past 35 years
5.6 Comparison in triple isotope space between surface water samples
collected during the MCE along the Indian Ocean and literature
data
5.7 1/Pb versus
206
Pb/
207
Pb in surface waters of the Indian Ocean
5.8 Comparison in triple isotope space between surface water samples
collected during the MCE in the Atlantic Ocean and literature data
5.9 1/Pb versus
206
Pb/
207
Pb in surface waters collected in the transect
from Spain to Brazil in the Atlantic Ocean
5.10 Comparison in triple isotope space between surface water samples
collected during the MCE in the Pacific Ocean and literature data
5.11 1/Pb versus
206
Pb/
207
Pb and
208
Pb/
206
Pb in surface waters collected
in the Pacific Ocean
A.1 Diel primary productivity, soluble Fe, and bacterial-abundance
B.1 Vertical temperature field contour from the combined CTD and
XBT data
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x
Abstract
Trace metals play an important role in aquatic environments as participants in,
and tracers of, processes of fundamental interest. Some trace elements (e.g. Fe, Co,
Zn) exert a significant control in the biological activity of aquatic phytoplankton,
which are responsible for about half of the photosynthetic carbon fixation on Earth. In
trace quantities, many of these metals are essential macronutrients for enzymatic
activity, but in high concentrations they may be inhibitory or toxic to biological
systems. Therefore, the distribution of biologically active trace metals have the
potential to impact upon the global carbon cycle and hence climate.
Other trace metals (e.g. Pb) are influenced by global-scale anthropogenic
emissions. Through the study of their transport dynamics and fates in aquatic
environments, we have been able to deconvolute atmospheric metal sources, resolve
exchange processes between dissolved and particulate fractions within the water
column, and document the fate of other anthropogenic pollutants in the ocean.
In order to understand the biogeochemical cycling of trace elements in aquatic
environments, qualitative and quantitative studies are needed. In this Ph.D. thesis I
focused on generating new data on some biologically essential and anthropogenic
metals in a wide variety of aquatic environments (i.e. coastal ocean, global open ocean,
and the land-ocean interface), providing new insights into the physicochemical and
biological influences that interact to control their biogeochemistry.
Understanding biogeochemical cycling of trace metals in the ocean requires
information about variability in metal concentrations and distribution over short time
scales. Such short time scale variability and the factors that influence it have been very
xi
poorly characterized in past work. Chapter 2 of this thesis, on “Diel Changes in Trace
Metal Concentration and Distribution in Coastal Waters: Catalina Island As a Study
Case” [Pinedo-Gonzalez et al., 2014], describes the research that targeted this
shortcoming. This study, which involved sampling sea surface water off Catalina
Island every 3 hours for 3 consecutive days, is the first to demonstrate the existence of
diel cycles of dissolved and colloidal trace metals in coastal oceans. These findings
promise to impact a wide community of scientists, including those interested in
sampling and interpreting trace metal data from the surface ocean, and those studying
bioavailability and transport of contaminants, environmental quality monitoring, and
toxicology.
Chapter 3, “Surface distribution of dissolved trace metals in the oligotrophic
ocean and their influence on phytoplankton biomass and productivity” [Pinedo-
Gonzalez et al., 2015] presents an extensive dataset on the distribution of trace metals,
dissolved inorganic nutrients, primary production and phytoplankton biomass in
surface waters of the global ocean. This chapter is divided into three sections: (i) a
description of the distribution of the bio-essential trace metals – Co, Fe, Cd, Cu, Ni, V,
and Mo – in surface waters of the Atlantic, Indian and Pacific oceans, providing new
data from poorly explored and unexplored regions as well as for some understudied
metals, (ii) a comparison between our trace metal data and previously published
datasets, facilitating the identification of changes in the distribution of some trace
metals in surface waters of the Atlantic Ocean over the last 30 years, and (iii) results
from a multivariable linear regression model identifying the trace metals that might
have important biogeochemical roles constraining primary productivity in the photic
zone of the surface ocean. Although this research builds on decades of prior work on
spatial patterns of surface ocean metal concentrations, the global extent of our new
xii
data is particularly novel and allows analysis and interpretation about the
biogeochemical implications that has not been possible in the past. In particular, I have
been able to identify the links between metal distributions and phytoplankton biomass
and primary productivity over basin-wide spatial scales, which is crucial for
understanding the controls on the biological cycles of carbon and nitrogen, including
the biological transfer of carbon to the deep sea, which helps regulate atmospheric
CO
2
.
Chapter 4, “Changes in size fractionation of metals in storm runoff following
wildfires: implications for the transport of bioactive trace elements” (submitted to
Applied Geochemistry) evaluates the partitioning of metals between the colloidal and
soluble phases in storm-runoff from three different environments (an area affected by a
natural wildfires, a natural catchment, and highly urbanized rivers) in order to gain
information about potential sources of soluble (i.e., bioavailable) elements that are
delivered to receiving waters. Although the size partitioning of metals between
different size fractions has been investigated before in both urban and natural runoff,
little work has been done on burned areas. This study is the first to provide conclusive
evidence that storm runoff from burned landscapes has the potential to supply a greater
proportion of trace elements in bioactive soluble form, compared to runoff from urban
or unburned areas, potentially increasing the impact of wildfire-delivered metals on
receiving waters and thus affecting primary productivity and carbon export in these
aquatic environments.
The final component of my Ph.D. research, described in Chapter 5, is a study
that explores the temporal variations in lead (Pb) concentrations and isotopic
composition in the global ocean. Lead produced by human activities, mainly from
leaded gasoline combustion and high-temperature industries, dominates Pb in our
xiii
present-day oceans. Previous studies have shown that surface ocean Pb concentrations
and isotope ratios have varied in time and space, reflecting the changes in the amount
of inputs and sources of anthropogenic Pb. However, data on surface ocean Pb is quite
limited, especially for understudied basins like the Indian Ocean. This last chapter of
my thesis made use of our unique sample set of global surface waters to produce a new
data set that enable us to assess the impact of anthropogenic Pb inputs to the ocean and
the relative importance of various Pb sources, providing new insights into the transport
and fate of Pb in the oceans.
1
Chapter 1
Introduction
The chemical composition of natural waters (e.g. oceans, rivers, lakes) includes
most elements, a variety of naturally occurring and human-made radionuclides, and
numerous organic compounds all in different proportions. Of these constituents, metals
occur in a wide range of concentrations. For example, in seawater the concentration of
metals range over 15 orders of magnitude from sodium, the most abundant cation at a
concentration close to 0.5 mol/kg, to iridium at a concentration as low as 0.5 fmol/kg,
equivalent to 90 parts-per-quadrillion (10
-15
). Due to this wide range of concentrations
in natural waters, metals are classified as major, minor and trace, where major metals
are those present in concentrations over 1mg/L, minor metals between 1mg/L and 0.1
mg/L, and trace metals those present in concentrations under 0.1 mg/L [Namieśnik,
2002]. Due to the low concentration of trace metals in natural waters relative to the
ubiquitous presence of metals in other components of the environment (dust, rust,
paint, dirt, etc.), their determination is analytically challenging. Problems caused by
contamination when measuring trace metals were first brought to the attention of the
scientific community by Clair Patterson and co-workers in their investigations of
stable Pb isotopes in the 1970s and 1980s [e.g. Murozumi et al., 1969; Schaule and
Patterson, 1981]. Largely through his influence, clean methods became part of the
standard operating procedures used first by chemical oceanographers and slowly
adopted by a wide community interested in the accurate determination of trace metals
in natural waters [Ahlers et al., 1990]. Tied to these advances in sampling and handling
trace metals, advances in the analytical technology (e.g. ICP-MS) allowed scientist to
2
recognize the important role of many trace metals in aquatic environments. For
example, in the late 1980’s the potential for Fe to serve as a limiting micronutrient in
many areas of the ocean began to be fully appreciated [e.g. Martin and Fitzwater,
1988; Martin et al., 1991]. Similarly, it is now suspected that the distribution and
bioavailability of some other trace metals (e.g. Co, Zn, Cu) have the potential to
enhance or limit primary productivity and carbon export in some regions of the world
ocean [e.g. Boyle and Edmond, 1975]. In addition to their wide range of biological
functions, trace metals have the potential to serve as tracers of pollution and oceanic
processes (e.g. Pb, Hg, Ag). For example, abundances of the stable isotopes of Pb are
used to identify natural and industrial sources of Pb to the ocean [e.g. Boyle et al.,
1986; Flegal et al., 1984; Desenfant et al., 2006], rivers [e.g. Elbaz-Poulichet et al.,
1986; Monna et al., 1995; Millot et al., 2004], and lakes [Flegal et al., 1989].
Despite the huge technical advances that made possible accurate
determinations of trace metals in aquatic environments and the sustained efforts made
by trace–metal scientists around the world, our understanding of the global
biogeochemical cycles of many trace elements is still very limited. In this Ph.D.
dissertation, I report the results of four projects designed to generate new evidence of
the physical, biological, and chemical processes that influence the concentration and
fractionation of trace metals in a variety of aquatic environments. By linking these
observations, my PhD research provides an important piece of the puzzle in
understanding the biogeochemistry of a variety of trace metals in aquatic systems.
1.1 The role of trace metals as micronutrients to phytoplankton
It is well known that, on land, one of the most important factors limiting the
growth of plants is the bioavailability of nutrient elements, in particular nitrogen (N)
3
and phosphorus (P). In an analogous way, the growth of aquatic plants (phytoplankton)
is often limited by the bioavailability of the same nutrients. In addition, a number of
trace elements, particularly first and second row transition metals (Fe, Co, Ni, Cu, Cd,
V, Mo, and Zn) are also essential for the growth of phytoplankton by serving as
essential active centers or structural factors in enzymes [Morel and Price, 2003; Morel
et al., 2006]. For example, Fe plays a central role in the light reactions of
photosynthesis, during which Fe is an essential component in the reaction centres of
photosystems I and II [Moore et al., 2009; Saito et al., 2014]. It is also well established
that the supply of Fe limits total productivity in the HNLC regions of the surface ocean
[e.g. Coale et al., 1996]. Zinc, another essential micronutrient, is a component of
nearly 300 enzymes involved in virtually all aspects of metabolism [Vallee and Auld,
1990]. For example, it occurs in carbonic anhydrase, which catalyzes inorganic carbon
acquisition [Lindskog, 1997]. It is also present in RNA polymerase [Coleman, 1992],
and it is involved in DNA regulation and transcription [Sankaranarayanan et al., 2000].
Like Zn, the primary role of Co in most phytoplankton is to serve as a metal centre in
carbonic anhydrase. In some taxa, Co can substitute for Zn in this enzyeme [Lane and
Morel, 2000]. Co is also present as the central metal ion in vitamin B
12
[Bertrand et al.,
2007; Taylor and Sullivan, 2008; Panzeca et al 2008]. Therefore, low Co
concentrations in some regions of the world’s oceans (e.g. the Ross Sea) could limit
the production of de novo vitamin B
12,
excreting nutritional controls on phytoplankton
growth and production [Bertrand et al., 2007]. Nickel serves as the active metal center
in urease, a metalloenzyme involved in the assimilation of urea as a nitrogen source
[Syrett and Peplinska 1988; Ermler et al., 1998]. Nickel also serves as a cofactor in
other enzymes, including hydrogenase and Ni-superoxide dismutase (Ni-SOD), an
enzyme that protects organisms from oxidative stress caused by superoxide
4
[Mulrooney and Hausinger, 2003; Dupont et al., 2008]. Copper is also an essential
micronutrient. It occurs along with iron cytochrome oxidase, the terminal protein in
respiratory electron transport that reduces O
2
to H
2
O [Peers et al., 2005]. It also occurs
in plastocyanin, which substitutes for the iron-protein cytochrome C6 in
photosynthetic electron transport in ocean diatoms [Peers and Price, 2006; Sunda,
2012]. Because Cu is needed for Fe uptake and can metabolically substitute for Fe, co-
limitations can occur for Cu and Fe [Peers et al., 2005; Annett et al., 2008; Sunda,
2012]. Cd is biologically important for marine diatoms under conditions of low Zn, as
it substitutes for this metal as the metallocenter in carbonic anhydrase [Lane and
Morel, 2000]. Molybdenum and V, while typically abundant in the water column with
average concentrations around 100 nM [Collier, 1985] and 35 nM, respectively
[Dupont et al., 1991], play important biological roles, particularly as the metal
cofactors in nitrogenases and other enzymes involved in N-fixation [Kisker et al.,
1997, Rehder, 2000; Crans et al., 2004].
Despite the well-recognized importance of trace metals in the metabolism of
phytoplankton, our5 understanding of their oceanic distribution and influence on
productivity is still limited. Chapter 3 provides a comprehensive synoptic dataset of
the distribution of dissolved Co, Fe, Cd, Cu, Ni, V, and Mo in surface waters of the
major oligotrophic regions of the ocean, which enabled us to identify the links between
metal distributions and phytoplankton biomass and primary productivity over basin-
wide spatial scales.
5
1.2 Size fractionation of metals between the colloidal and soluble
pools
As discussed above (section 1.1), elements like Co, Fe, Zn, Cd, Cu, Ni, V, and
Mo are important elements in the biogeochemistry of aquatic ecosystems, as they are
required by phytoplankton for various metabolic functions. In addition, it is believed
that association of metals with carriers of different dimensions and composition
controls their transport (diffusion-advection-coagulation-sedimentation),
bioavailability and toxicity [e.g., Buffle, 1988; Guéguen, 2003]; therefore knowledge
of the physical and chemical forms of metals is essential to understand their reactivity
and interaction with living organisms [Bruland, 1980].
Metals in natural systems have traditionally been subdivided into two fractions:
“dissolved” (<0.2µm) and “particulate” (>0.2 µm). The “dissolved” fraction not only
represents the truly dissolved metal pool, but it also contains nanoparticles (or
colloids) with sizes operationally defined as ranging from 1nm to 1000nm diameter
[Tessier and Turner, 1995]. Due to their high surface area to volume ratio and
abundance in aquatic systems, nanoparticles are thought to play an important role in
metal cycling in aquatic environments such as oceans, lakes and rivers [Wells and
Goldberg, 1993; Honeyman and Santschi, 1989]. For example, the occurrence of Fe in
colloidal particles decreases Fe bioavailability [Wells et al., 1983; Wu et al., 2001] and
increases Fe removal via colloid aggregation into larger particles or through salt-
induced coagulation in estuaries [Honeyman and Santschi, 1989].
Although previous work has explored colloidal partitioning of metals in some
aquatic environments, i.e. ground water [Sañudo-Wilhelmy et al., 2002], ocean
[Sañudo-Wilhelmy et al., 1996; Donat et al., 1994], urban runoff [Grout et al., 1999;
Tucillo, 2006], and rivers [Guéguen and Dominik, 2003], the importance of colloidal
6
particles for the cycling of metals is still unclear. The studies reported in Chapters 2
and 4 provide new insights into the physical and chemical processes that affect size
partitioning of trace metals in both coastal oceans (Chapter 2) and storm runoff from
natural and urban catchments (Chapter 4).
1.3 Trace metals as tracers for anthropogenic inputs
The oceanic cycle of many trace metals has been significantly impacted by
human activity. In addition to being toxic to natural and human ecosystems, some of
these trace metals (e.g. Pb, Ag, Hg) can serve as tracers of biogeochemical processes
and are good indicators of the strength of external inputs.
For example, Pb is one of the elements most influenced by human activities. Pb
in the modern ocean is dominated by anthropogenic Pb, and the distribution of Pb and
Pb isotopes throughout the ocean provides valuable information on the transport and
removal of these anthropogenic inputs and the time scales of those processes in the
ocean. In addition, Pb is also useful in predicting the fate of other anthropogenic
elements (e.g., Cu, Cd, Zn and Hg) that are produced and introduced to the ocean via
similar pathways. Anthropogenic Pb can also serve as a transient tracer of oceanic
processes (e.g., ventilation) because Pb and Pb isotopes vary in time and space,
reflecting changes in the amount of inputs and sources of anthropogenic Pb. However,
despite this importance, modern data on Pb in the ocean are very limited, mostly
because most studies on Pb were conducted before the phase-out of leaded gasoline in
North America (1975), Europe (1985), and Asia (2000).
In chapter 5 of this Ph.D. dissertation, I report the distribution of Pb and Pb
isotopes in surface waters of the global ocean and explore the relative importance of
various Pb sources, improving our current understanding of Pb in the modern ocean.
7
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10
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11
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12
Chapter 2
Diel changes in trace metal
concentration and distribution in
coastal waters: Catalina Island as a
study case
2.1 Opening Statement
As discussed in Chapter 1, the growth of oceanic phytoplankton that play a
central role in the global carbon cycle is often limited by the bioavailability of trace
metals. Therefore, it is crucial to improve our understanding of the physical, chemical
and biological processes that could potentially alter trace metal concentrations and size
partitioning in the ocean. This chapter reports the results of a field study designed to
explore changes in metal concentration and size fractionation over short (i.e. diel) time
scales. This study is the first to demonstrate that both the concentration and the size
partitioning of some biologically essential (Fe, Cu, Co, and Cd) and anthropogenic
(Pb) metals are subjected to diel variations that may be related to both inorganic and
biological processes. These results suggest that changes occurring over time scales of
hours may be of importance in governing trace metal availability to marine
phytoplankton, thus impacting ocean processes including marine ecosystem dynamics
and carbon cycling.
Drs. Joshua West and Sergio Sañudo-Wilhelmy are acknowledged for their
13
insights and supervision. Dr. Ignacio Rivera-Duarte was responsible for analyzing the
first half of samples at SPAWAR Systems Center Pacific, while the other half was
analyzed by PP-G at USC. Brian Seegers, Christopher Suffridge, and David Needham
are all thanked for their assistance with sample collection. Financial support for this
research was provided by the National Science Foundation (Chemical Oceanography
Program grant OCE 0962209) and the Wrigley Institute's 2012 Rose Hills Summer
Science Fellowship at the USC Wrigley Marine Science Center on Catalina Island,
CA.
This paper was published in 2014 as:
Pinedo-Gonzalez, P., West, A. J., Rivera-Duarte, I., & Sañudo-Wilhelmy, S. A.
(2014). Diel changes in trace metal concentration and distribution in coastal waters:
Catalina Island as a study case. Environmental science & technology, 48 (14), 7730-
7737.
2.2 Introduction
Day and night cycles resulting from Earth’s rotation are a primary source of
biological and physicochemical variability in the surface ocean. This diurnal cycle
produces regular and dynamic changes in numerous physical and biogeochemical
parameters and processes (i.e. surface temperature, solar radiation and associated
photochemical reactions, photosynthesis and respiration), and thus it is expected to
influence the concentrations of photochemical and bioactive chemical constituents in
the surface ocean, including some trace metals. Trace metals are important elements in
14
the biogeochemistry of marine ecosystems, since some are required by aquatic
organisms for various metabolic functions [Bruland et al., 1991].
The role of trace metal concentrations in the productivity of the world’s ocean
has stimulated several research programs (e.g. GEOTRACES) to acquire accurate data
on metal concentration, chemical form, and distribution. However, these research
programs, due to the challenges of sampling around-the-clock at a single location, do
not evaluate the patterns that might occur in metal concentrations over diel time scales.
It is not just variability in total metal concentrations that are important to understand;
numerous studies have shown that the traditional subdivision of trace metals into two
fractions, “dissolved” (typically defined as <0.2-0.45 µm) and “particulate” (defined as
>0.2-0.45 µm), provides limited information about the actual behavior of several
elements in the ocean [Tessier and Turner, 1995; Sañudo-Wilhelmy et al., 1996; Boye
et al., 2010; Bergquist et al., 2007; Wu et al., 2001]. This is because the dissolved
fraction of many metals not only includes the soluble metal pool, but it also contains
colloids with sizes operationally defined as ranging from 1.0 or 10 kDa to 0.2-1.0 µm
[Buffle, 1992; Gustafsson et al., 1996; Lead and Wilkinson, 2006; Doucet et al., 2007].
These colloids can have a significant effect on metal transport, distribution,
bioavailability, and toxicity [Buffle, 1998; Benoit et al., 1994; Tessier and Turner,
1995]. Thus it is important to evaluate not only changes in total dissolved metal
concentration over diel timescales, but also changes in their distribution between
difference size fractions, referred to as their size fractionation. Comprehensive studies
in streams [Gammons et al., 2005; Nimick et al., 2003; Parker et al., 2008; Tercier-
Waeber, 2009]
and lakes [Shirokova et al., 2010; Pokrovsky and Shirokova, 2013]
have demonstrated that dissolved concentrations and size fractionation of many trace
elements change substantially during 24-h periods. These variations in metal
15
concentrations have been attributed to changes in temperature, biological activity,
photo-induced metal reduction/oxidation, and adsorption/desorption processes.
In the ocean, diurnal fluctuations in the concentration and size fractionation of
trace metals along with the main factors that control these variations remain poorly
investigated. To address the extent to which trace metal concentrations and partitioning
between the traditionally defined total dissolved (<0.2 µm), colloidal (defined here as
0.02 to 0.2 µm) and soluble (<0.02µm) fractions are affected by diurnal changes in the
surface ocean, we measured trace element concentrations in each metal pool every 3-4
hours in surface waters off Catalina Island, CA for three consecutive days and nights.
We conducted this experiment on two occasions; each experiment was spaced a month
apart (June and July 2012). Our results show that both the concentration and size
partitioning of some biologically essential (Fe, Cu, Co, and Cd) and anthropogenic
(Pb) metals are affected by diel changes. In contrast, the partitioning and
concentrations of other metals such as Mo, Ag, V, and Ni seem to be independent of
the day-night cycle. The occurrence of diel trace metal cycles in the surface ocean has
important implications for trace metal sampling protocols and data interpretation.
2.3 Materials and methods
Surface water samples were collected in June and July, 2012, at one station off
Catalina Island, California every 3-4 hours for 3 consecutive days (>72hr) during each
month. Catalina Island, in the Southern California Bight (SCB), is located about 35km
southwest of Los Angeles, California in the Gulf of Santa Catalina (Figure 2.1A). The
area around Catalina Island is considered a relatively pristine environment where trace
metal cycling is not directly affected by anthropogenic activities. The sampling
location (+33° 27' 24.66", -118° 29' 20.72") was situated ~2 km off the mainland side
16
of Catalina Island's Isthmus
Cove (Two Harbors), in an
area that receives waters from
the San Pedro Channel, a
33km waterway located
between Santa Catalina Island
and mainland Southern
California, USA.
All samples were
collected using trace metal
clean techniques at a depth of
approximately 1-2 meters
from the surface using a pole-
sampling protocol and acid-
washed 4-L polyethylene
bottles. After sample
collection, sealed bottles
were transported to the
laboratory facilities at the
USC Wrigley Institute for
Environmental Studies where
samples were filtered within 30 minutes of collection. Samples were filtered through
acid-washed 0.2µm filter cartridges for measurement of the total dissolved (<0.2µm)
trace metal concentrations. A portion of the 0.2µm filtrate was further syringe filtered
through acid cleaned 25-mm-diameter 0.02µm Anatop Al-oxide filters to isolate the
34.1°&
Catalina
Island!
Los Angeles!
&&
5 mi!
10 Km!
Long Beach!
Sampling
point!
34.0°&
33.9°&
33.8°&
33.7°&
33.6°&
33.5°&
33.4°&
33.3°&
118.5°& 118.7°& 118.3°& 118.1°& 117.9°& 117.7°&
A
Figure 2.1. (A) Catalina Island, CA sampling station map.
Surface (1−2 m depth) water samples were collected in June
22−25 and July 20−23, 2012. (B) Diel light intensity and
temperature variations in the surface ocean off Catalina Island
(July, 2012). In these and other figures, shadowed areas
represent nighttime based on sunrise and sunset hours recorded
during the sampling campaigns.
17
soluble fraction (<0.02µm). The difference between the total dissolved (<0.2µm) and
the soluble fraction (passing through 0.02µm filter) is considered to be the colloidal
fraction. This approach has successfully been used to establish the importance of
colloidal size particles on the cycling of Fe in open ocean and coastal environments
[Bergquist et al., 2007; Wu et al., 2001; Fujii et al., 2008; Ussher et al., 2010).
Biomass (as chlorophyll-a), temperature, and light intensity were measured at the time
of collection using a Biospherical Instruments Profiling Natural Fluorometer (model
PNF-300).
Filtrates (<0.2 and <0.02 µm) were doubled bagged in polyethylene bags and
transported to a class-100 clean room at the USC main campus, where they were
acidified (<3 days after collection) using Optima grade hydrochloric acid to a pH<2
and stored for at least one month prior to preconcentration by organic extraction using
the APDC/DDDC ligand technique described in Bruland et al. [1985]. Levels of Fe,
Cu, Pb, Cd, Mo, Ag, V, Co, and Ni in the total dissolved and soluble fractions were
quantified by ICP-MS on a Thermo Element 2 HR-ICP-MS at USC, using external
calibration curves and an internal indium standard [Zhang et al., 2001; Ndung’u et al.,
2001; Tovar-Sanchez and Sañudo-Wilhelmy, 2011; Smail et al., 2012]. To evaluate the
accuracy of our analytical procedures, a certified seawater reference material (SRM)
(CASS-5) was preconcentrated by organic extraction and metals quantified by ICP-
MS. The recoveries of the SRM ranged from 90% for Pb to 101% for Mo of the
certified concentration as shown in Table A1 in Appendix A.
18
2.4 Results and discussion
2.4.1 Light intensity and water temperature variations in the surface
ocean off Catalina Island
Light intensity and surface water temperature changes during the July cruise
are illustrated in Figure 2.1B. As expected, light intensity followed a clear diel cycle
with maximum intensity (7.3x10
4
Lux) between 11AM and 3PM (Figure 2.1B). Water
temperature variations were minor (19.3 ± 0.4°C) although some diel variations can be
observed. Temperature decreased from the afternoon to early morning by 0.6°C (from
18.8°C to 19.4°C), with the highest value measured around 7pm (Figure 2.1B).
2.4.2 Metals showing distributions and size-fractionation independent of
diurnal cycles
The trace metals measured in this study are classified in two groups based on their diel
behavior: metals subject to day-night variations (Fe, Cu, Cd, Co, and Pb) and metals
whose behavior was statistically independent of a diurnal cycle (Mo, Ag, V, and Ni).
According to a Mann-Whitney U test (Table A2 Appendix A), the concentration and
size fractionation of metals in the second group did not show any significant regular
variation with time of the day (Tables A3-A8 Appendix A), as illustrated in Figure
2.2. The range of dissolved Mo, Ag, V, and Ni concentrations measured off Catalina
(95-110 nM, 3.5-4.8 pM, 21-26 nM, 3.3-3.9 nM respectively) are consistent with those
measured in other coastal waters off southern California (Mo, 76-99 nM; Ag, 2-13 pM;
V, 14-46 nM; Ni, 1.8-4.3 nM) [Smail et al., 2012; Sañudo-Wilhelmy and Flegal,
1991].
Our study also shows that only a small percentage of these metals was
contained within the colloidal fraction [Mo: 10%, Ag: 12%, V: 4%, Ni: 5% of the total
19
Figure 2.2. Variations in total dissolved (>0.2 µm), soluble (<0.02 µm), and colloidal (0.02−0.2 µm) Ni
(A), Ag (B), V (C), and Mo (D) concentrations in the surface ocean off Catalina Island (June and July,
2012). The June and July sampling episodes are separated by a break. Total dissolved, soluble, and
colloidal fractions are represented in solid circles, open circles, and gray squares, respectively. The
metals shown in this figure do not show statistically significant diel variations (see statistical analysis in
Supporting Information).
dissolved], since the total dissolved metal pool was not significantly different from the
soluble pool using our size-fraction scheme. These results are consistent with previous
studies that have used cross-flow ultrafiltration to separate colloids and associated
trace elements, reporting that Mo, Cd, Co, Ni, and Ag reside primarily in the soluble
phase (i.e., in the <1kDa size range, compared to our soluble cutoff at 0.02µm,
equivalent to approximately 200 kDa) [Sañudo-Wilhelmy et al., 1996; Pokrovsky and
Shirokova, 2013; Hassellöv et al., 1999; Wen et al., 1999].
20
2.4.3 Metal distributions and size fractionation influenced by diurnal
variations
Diel variation of the total dissolved (<0.2µm) fraction. Total dissolved Fe, Co, Cu, and
Cd concentrations follow a clear diurnal pattern (Figure 2.3B-E). Total dissolved Fe
concentration decreased from sunrise to sunset by a factor of 4 (from 7.0 to 1.5 nM),
with the highest concentrations measured during nighttime (7.0 nM at 1AM) (Figure
2.3B). Temporal variation in the concentration of dissolved Cu, Co and Cd follows a
similar trend to dissolved Fe concentrations, but the proportional variations are
smaller. Concentrations reach maxima during nighttime, with Cu: 1.2 nM, Co: 50 pM,
Cd: 0.17 nM during the day (11AM) versus Cu: 2.3 nM, Co: 65 pM, Cd: 0. 20 nM
during night (11PM) (Figure 2.3C-E). In contrast to Fe, Cu, Co and Cd, total dissolved
Pb concentration (Figure 2.3A) remained relatively constant over our diel sampling
(20-33 pM), and was independent of the day-night cycle.
Total dissolved metal concentrations measured off Catalina were consistent
with metal levels previously measured in the Santa Monica and San Pedro Basins (Pb:
25-79 pM, Cu: 0.61-3.2 nM, and Co: 50-80 pM) [Smail et al., 2012; Johnson et al.,
1988]
and with other southern California coastal environments (Fe: 0.25-7.5 nM and
Cd: 180-210 pM) [Sañudo-Wilhelmy and Flegal, 1991].
Diel variation of the soluble (<0.02µm) fraction and relative proportion of colloidal
metals (0.02 to 0.2µm) to the total dissolved pool. In contrast to the constant diel
pattern observed for the total dissolved Pb pool, time series measurements of Pb in the
<0.02 µm pool revealed large diurnal fluctuations (by a factor of 5, ranging from 5.3 to
28.1 pM), reaching a maximum concentration around 12 noon (Figure 2.3A). These
large fluctuations in the soluble pool were undetectable in the total dissolved fraction
(Figure 2.3A) that is traditionally measured in most environmental studies [Patterson
21
et al., 1976; Schaule and Patterson, 1981; Capodaglio et al., 1990; Sañudo-Wilhelmy
and Flegal, 1994]. Iron and Cu also showed a significant diel variation in their
concentrations in the soluble pool; Fe varied during the day-night cycle by a factor of
40 (0.1 to 4.0 nM), and Cu by a factor of 2 (1.1 to 2.1 nM) (Figure 2.3B and C).
Cadmium and Co showed only small variations in their soluble pool; Cd varied by a
factor of 1.2 (0.16 to 0.19 nM) and Co by a factor of 1.6 (45 to 75 pM) (Figure 2.3D
and E). Iron, Cd, and Co reached maximum concentrations in the soluble pool during
nighttime (2AM; Figure 2.3B, D and E ). In contrast, soluble Pb and Cu reached
maximum concentrations during daytime (1PM; Figure 2.3A and C).
Some of the largest diel fluctuations were observed in the colloidal pool. For example,
the contribution of colloidal Pb to the total dissolved fraction increased from about 6 ±
3% during the day to as much as 70-80% during the night (Figure 2.3A). The highest
proportion of colloidal Cu was also measured at nighttime although the contribution of
this fraction to the dissolved pool was only about 30% (Figure 2.3C). A large portion
of the total dissolved Fe pool also consisted of colloidal particles (ranging from 50 ±
5% to 90-100% of the total dissolved). In contrast to Cu and Pb, the largest proportion
of colloidal Fe was measured during the day (1PM; Figure 2.3B). Cadmium and Co
also showed some fluctuations in their colloidal pool. However, the colloidal pool of
these elements only represents a small percentage of the total dissolved (10% and 16%
respectively). The proportion of colloidal metals in this study appears to be consistent
with previously reported results. For example, analyses that have used the same size
cutoff to separate the soluble fraction (<0.02µm) in the oligotrophic north Pacific and
north Atlantic [Wu et al., 2001], and in the sub-tropical and tropical Atlantic Ocean
[Bergquist et al., 2007], indicate that a significant portion (>90%) of the total dissolved
Fe (>0.2µm) consists of colloids. Laboratory and field measurements that have
22
separated colloids using ultrafiltration also indicate that a high percentage (up to 90%)
of the total dissolved Fe and Pb in natural waters consists of high molecular weight
colloids (10kDa-0.2µm) [Sañudo-Wilhelmy et al., 1996; Boye et al., 2010; Pokrovsky
and Shirokova, 2013; Wells et al., 1998] and that the majority of the total dissolved
species of Cu, Cd and Co are primarily in the low molecular weight (<10kDa) fraction
in coastal waters [Sañudo-Wilhelmy et al., 1996; Hassellöv et al., 1999; Wells et al.,
1998; Batlet and Florence, 1976; Hasle and Abdullah, 1981].
2.4.4 Potential processes controlling diurnal concentrations and
partitioning of trace metals in coastal waters off Southern California
Potential processes influencing the diel cycling of Pb. The observed decrease in the
concentration of colloidal Pb during the day (Figure 2.3A) might be due to a transfer
of Pb from the colloidal to the soluble pool mediated by the photolysis of colloidal
organic matter and the photoredox cycling of colloidal metal(hydrous)oxides.
Dissolved organic matter in the >200kDa (>0.02µm) pool is degraded by sunlight into
a variety of low molecular weight (<200kDa, equivalent to <0.02µm) organic
compounds [Moran and Zepp, 1997].
Similarly, colloidal metal oxides (i.e. Fe) are
photochemically reduced to dissolved metal (II) species, which are highly soluble and
not bound appreciably by organic ligands [Sunda and Huntsman, 2003]. This UV-
mediated photolysis and photo-reduction releases metal ions into the soluble pool
where they could be complexed by low molecular weight ligands that are UV
transparent and no longer photoreactive [Moran and Zepp, 1997; Vahatalo, 2010], thus
increasing the concentration of soluble metals during the day. In our study, therefore,
the observed transfer of Pb from the colloidal to the soluble pool during the day is
consistent with reported UV-mediated decomposition of dissolved organic matter and
23
photoredox cycling of colloidal metal oxides [Moran and Zepp, 1997; Moran et al.,
2000; Shiller et al., 2006].
Figure 2.3. Diel changes in total dissolved (>0.2 µm), soluble (<0.02 µm), and colloidal (0.02−0.2 µm)
Pb (A), Fe (B), Cu (C), Cd (D), Co (E), and chlorophyll a (F) concentrations in the surface ocean off
Catalina Island (June and July, 2012). The June and July sampling episodes are separated by a break.
Total dissolved, soluble, and colloidal fractions are represented in solid circles, open circles, and gray
squares, respectively.
24
There is evidence indicating that soluble metals generated by both the
photolysis of colloidal organic matter and photo-reduction of colloidal metal oxides
can be significantly more biologically active [Moran and Zepp, 1997; Sunda, 2012]
so
we might expect bioactive metals released to the soluble pool via this mechanism to be
rapidly taken up biologically. Our results show that soluble Pb concentrations
increased directly with chlorophyll-a concentrations (Figure 2.3A and F) suggesting no
biological uptake following release by photolysis and photoreduction. The observed
increase is expected for a non-biologically essential element, and is consistent with the
lack of correlation in the diel fluctuations of total dissolved Pb concentrations and
chlorophyll-a (2.3A and F).
During our study, colloidal Pb seems to be regenerated at night (Figure 2.3A).
This pattern seems to be consistent with reported biological processes that are capable
of recycling components of cellular metabolism and therefore generate organic matter
capable of complexing particle-reactive elements in the colloidal size [Hutchins and
Bruland, 1994; Lee and Fisher, 1994; Strom et al., 1997; Fuhrman, 1999; Wilhelm and
Suttle, 1999; Poorvin et al., 2004]. For example, in marine environments, planktonic
grazers can release as much as 80% of phytoplankton and bacterial production
[Carlson, 2002] as colloidal (<0.2µm) organic carbon [Fuhrman, 1999]. It is also
known that maximum grazing activity generally occurs at night [Boyd et al., 1980;
Welschmeyer et al., 1984; Stearns, 1986; Daro, 1988].
Thus the formation of new
colloidal organic matter produced by grazing activities at night along with the lack of
sunlight might explain the observed transfer of the soluble Pb generated during the day
to the colloidal pool at night (Figure 2.3A). In addition to these biological processes
capable of regenerating colloidal Pb, the regeneration of colloidal
metal(hydrous)oxides at night (with a reaction rate of approximately l0
7
s
-1
in
25
oxygenated seawater) [Rush and Bielski, 1985], may also explain the trends observed
for Pb.
Processes influencing iron diel concentrations and size-fractionation. As discussed
above, Fe concentrations decrease during the day in the total, colloidal and soluble
pools (Figure 2.3B). The decrease in the concentration of colloidal Fe during the day
(Figure 2.3B) might be due to a transfer of Fe from the colloidal to the soluble pool
mediated by the photolysis of colloidal organic matter, the formation of low molecular
weight (<1kDa) Fe(III) complexes [Ilina et al., 2013], and the photoreduction of
colloidal iron oxides. It is well documented that, under UV radiation, Fe (III) can be
photo-reduced to Fe (II) by direct photolysis of ferric chelates or by photochemically
produced superoxide radicals (O
2
-
) [Maldonado and Price, 2001]. Although resulting
Fe (II) is unstable in oxygenated seawater at pH 8.0, photoreduction of Fe (III)
increases the concentration of soluble and bioavailable Fe species in the surface ocean
[Sunda and Huntsman, 2003]. Thus sunlight could potentially enable the transfer of Fe
from the colloidal to the soluble pool, facilitating Fe consumption by growing
phytoplankton and Fe adsorption onto bacteria cells, causing a decrease of Fe
concentrations in all pools (Figure 2.3B). A mass balance using our measured mean
primary production data (510 nmol C/m
3
sec during 10 hours; Figure A1 Appendix A)
yields an Fe uptake ranging from 0.93 to 1.11 nM. This uptake could account for 26 –
32% of the observed decrease in soluble Fe. Using our measured bacteria count data
(average of 500x10
6
cells/mL during the day; Figure A1 Appendix A), and the number
of surface-active groups capable of adsorbing Me
2+
(1-2 µmol/g
dry
)
[Pokrovsky and
Shirokova, 2013] we estimated that Fe adsorption onto bacteria surfaces may account
for 34-68% of the observed soluble Fe (Figure 2.3B). At night, Fe concentration in all
pools (total, colloidal and soluble) is regenerated (Figure 2.3B). As discussed for Pb,
26
grazing activities and the lack of sunlight renew supplies of colloidal organic carbon
and metal(hydrous)oxides, both capable of complexing particle-reactive metals. This
facilitates the transfer of Fe from the soluble to the colloidal pool and thus might
account for the observed increase in the concentration of colloidal Fe at night (Figure
2.3B).
The increase in soluble Fe concentration at night (Figure 2.3B) can potentially
be explained as a transfer from the particulate pool (Fe absorbed by growing
phytoplankton and/or adsorbed onto bacteria cells) to the soluble pool mediated by
biological mechanisms such as viral lysis, zooplankton grazing and microbial
decomposition. Grazing and microbial decomposition are capable of rapidly
regenerating metals contained in the cytoplasm or bound to structural components of
ingested prey, facilitating recycling of both unassimilable and biologically required
trace metals [Hutchins and Bruland, 1994; Lee and Fisher, 1994]. In addition,
microbes and grazers release various low molecular weight organic byproducts (i.e.
sugars, proteins, porphyrins, polysaccharides) that are able to complex Fe and keep it
in the soluble fraction [Hunter and Boyd, 2007; Strzepek et al., 2005]. Viral lysis is
another important mechanism in the regeneration of trace metals in the surface ocean
[Fuhrman, 1999; Wilhelm and Suttle, 1999; Poorvin et al., 2004]; it is estimated that
approximately 3% of primary production is lost to viral lysis each day [Suttle, 1994].
During viral lysis, the host cells are broken down into material that ranges in size from
dissolved (<0.20µm) through particulate (>0.20µm) size fractions, resulting in the
release of significant quantities of complexed metals [Wilhelm and Suule, 2000].
We
hypothesize that this mechanism contributes to the observed restoration of both total
and soluble Fe concentrations at night (Figure 2.3B).
27
Processes influencing copper, cobalt, and cadmium diel concentrations and size-
fractionation. Cadmium and Co are not particle reactive metals (i.e. they do not form
strong surface-metal complexes) due to their low ionic potential. Instead, they have a
high affinity for low molecular weight (LMW) dissolved organic matter [Sañudo-
Wilhelmy and Flegal, 1991].
Although Cu also exhibits high affinity for LMW organic
matter (e.g. biota exudates), a fraction of this metal can also be adsorbed onto particles
(e.g. cell surfaces) [Pokrovsky et al., 2008], and colloids. As shown in figure 2.3C, a
portion (<30%) of the total dissolved Cu pool is colloidal. This fraction exhibits clear
diurnal changes in its concentration (Figure 2.3C) that might be explained by the
transference of Cu from the colloidal pool to the soluble pool mediated by mechanisms
like the photolysis of colloidal organic matter and photoreduction of Cu (II) [Ferraudi
and Muralidharan, 1981]. The decrease in the Cu, Cd, and Co soluble pools during the
day (Figure 2.3C – E) might suggest biological uptake. This is supported by the
inverse correlation between chlorophyll-a and Cu, Cd and Co concentrations (r = –
0.72, –0.88, –0.73 respectively) (Figure 2.3C – F). However, since these elements
have a strong affinity for low molecular weight dissolved organic matter and the
biological requirements of these metals are relatively low (Cu: 1.5-5x10
-4
mol/mol P;
Cd: 2.1x10
-4
mol/mol P; Co: 1.9x10
-4
mol/mol P) [Wallace et al., 1977; Collier and
Edmond, 1984; Moore et al., 1984; Quigg et al., 2003; Ho et al., 2003], compared to
Fe (1.0-5x10
-2
mol Fe per mol P) [Wallace et al., 1977; Collier and Edmond, 1984;
Moore et al., 1984; Quigg et al., 2003; Ho et al., 2003], the concentrations of Cu, Cd
and Co undergo only small fluctuations (factor of 2, 1.3 and 1.4, respectively,
compared to factor of 40 for Fe) (Figure 2.3B – E).
At night, total dissolved Cu, Cd, and Co pools are regenerated. Although the
systematic fluctuations in their concentrations agree with their strong affinity for low
28
molecular weight dissolved organic matter and the mechanisms described above
capable of transferring metals from the particulate pool back to the dissolved fraction
(i.e., viral lysis, zooplankton grazing and microbial decomposition) information about
variation in metal concentrations in the particulate pool is needed in order to confirm
this hypothesis.
2.5 Conclusions
In summary, this study demonstrates that short term processes, like diel cycles
of photosynthesis, respiration, and light intensity have an important bearing on
understanding the biogeochemistry of trace metals in the ocean. As demonstrated in
studies in streams and lakes, where the concentration and partitioning of many trace
elements change substantially during 24-h periods [Gammons et al., 2005; Nimick et
al., 2003; Parker et al., 2008; Tercier-Waeber, 2009; Shirokova et al., 2010; Pokrovsky
and Shirokova, 2013], results show that in the surface ocean, both the concentration
and size partitioning of some biologically essential (Fe, Cu, Co, and Cd) and
anthropogenic (Pb) metals are also affected by diel changes in temperature, biological
activity, photo-induced metal reduction/oxidation, and adsorption/desorption
processes. This has critical implications in terms of how cyclical variation in metal
concentrations may affect single measurements of trace metals. Our results show the
importance of considering changes that occur in the matter of hours when designing
sampling protocols for some bioactive trace metals in order to get representative
results. If a single one-time sample from the surface ocean is acquired, our results
suggest that an early morning or late afternoon sample should represent the multiday
average concentration. Further similar studies in other locations will be important to
assess whether this is generally the case.
29
Finally, our results could have important implications for biogeochemical studies in
the marine realm. For example, in high nutrient-low chlorophyll regions of the ocean,
phytoplankton growth is limited by Fe [Martin and Fitzwater, 1988; Nightingale et al.,
1996; DeBaar, 1990; Hutchins and Bruland, 1998]. If current data on Fe
concentrations is biased by sampling time then the extent to which phytoplankton in
these regions are Fe-limited may not be accurately understood. Further careful
assessment of diel variability in other oceanic settings is needed.
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36
Chapter 3
Surface distribution of dissolved trace
metals in the oligotrophic ocean and
their influence on phytoplankton
biomass and productivity
3.1 Opening Statement
In addition to characterizing the variability in metal concentrations and size
partitioning over short temporal scales, as in Chapter 2, examining the link between
metal distributions and phytoplankton biomass over basin-wide spatial scales is also
essential for understanding the controls on the biological cycles of carbon and
nitrogen. To study this connection, the concentrations of Cd, Co, Cu, Fe, Mo, Ni, and
V were determined for 110 surface water samples collected during the Malaspina 2010
Circumnavigation Expedition. These results are presented and discussed in this
chapter. Trace metal concentrations measured in surface waters of the Atlantic Ocean
during the Malaspina cruise were compared to previously published data for the same
region. The comparison revealed little temporal changes in the distribution of Cd, Co,
Cu, Fe, and Ni over the last 30 years. We utilized a multivariable linear regression
model to describe potential relationships between primary productivity and the
hydrological, biological, trace nutrient and macronutrient data collected during the
same expedition. Our statistical analysis suggests that some of the lesser-studied trace
37
elements (e.g., Ni, V, Mo, Cd) may play a more important role in regulating oceanic
primary productivity than previously thought and points to their importance for future
experiments to verify their potential biological functions.
Drs. Joshua West and Sergio Sañudo-Wilhelmy are acknowledged for their
insights and supervision. Dr. Carlos M. Duarte was the senior scientist for the
Malaspina 2010 Circumnavigation Expedition. Samples for trace metals,
macronutrients, chlorophyll a, and primary productivity were collected by the
Malaspina 2010 Circumnavigation Expedition team: Antonio Tovar-Sanchez (trace
metal collection), Emilio Marañon (primary productivity), Pedro Cermeño (primary
productivity), Natalia González (primary productivity), Cristina Sobrino (primary
productivity), María Huete-Ortega (primary productivity), Ana Fernández (primary
productivity), Daffne C. López-Sandoval (nutrients), Montserrat Vidal (nutrients),
Dolors Blasco (nutrients), and Marta Estrada (nutrients). We thank L. Pinho, E. Mesa,
H. Marota and A. Dorsett for help with metal sampling, E. Fraile and V. Benitez for
CTD data, M. Galindo for help with nutrient analyses, the UTM for help with the
maintenance of the sampling system, and the captain and crew of R/V Hesperides for
help during the circumnavigation. All trace metal samples were processed and
analyzed at USC by PP-G. This research was funded by the Spanish Ministry of
Economy and Competitiveness through the Malaspina 2010 expedition project
(Consolider-Ingenio 2010, CSD2008-00077).
This paper was published in 2015 as:
Pinedo‐González, P., West, A. J., Tovar‐Sánchez, A., Duarte, C. M., Marañón, E.,
Cermeño, P., González, N., Sobrino, C., Huete-Ortega, M., Fernández, A., López-
Sandoval, D. C., Vidal, M., Blasco, D., Estrada, M., Sañudo Wilhelmy, S. A. (2015).
38
Surface distribution of dissolved trace metals in the oligotrophic ocean and their
influence on phytoplankton biomass and productivity. Global Biogeochemical
Cycles, 29 (10), 1763-1781.
3.2 Introduction
Marine phytoplankton account for about half of the photosynthetic carbon
fixation on Earth [Field et al., 1998], thus playing a key role in the global carbon cycle
and in associated climate regulation. When studying phytoplankton productivity, much
of the focus is placed on the macronutrients nitrogen and phosphorus, which are
known to exert a significant control on phytoplankton metabolism and community
structure [e.g., Tyrrell, 1999; Wu et al., 2000; Ammerman et al., 2003; Falkowski and
Oliver, 2007; Moore et al., 2013]. However, a dozen trace elements, particularly first
and second row transition metals, are also essential for the growth of phytoplankton by
serving as essential active centers or structural factors in enzymes [e.g., Morel and
Price, 2003; Morel et al., 2006]. Several of these bioessential trace metals—iron (Fe),
cobalt (Co), nickel (Ni), copper (Cu), cadmium (Cd), vanadium(V), and
molybdenum(Mo)—are present at low concentrations in seawater, therefore possibly
limiting phytoplankton production [Da Silva and Williams, 1993; Moore et al., 2013].
In some oceanic regions, Fe availability limits both oceanic primary
productivity and marine nitrogen fixation capacity [Moore et al., 2009; Saito et al.,
2014]. Iron occurs in high amounts in the redox centers of nitrogenase responsible for
N2 reduction to NH3 and in various cytochromes and Fe-S redox centers involved in
anoxygenic and oxygenic photosynthesis [Saito et al., 2011; Sunda, 2012]. Cobalt has
been demonstrated to co-limit the growth of some phytoplankton in both field and
laboratory culture studies either as inorganic Co or as the central metal ion in vitamin
B12 [Bertrand et al., 2007; Taylor and Sullivan, 2008; Panzeca et al., 2008]. Cobalt
39
can also substitute for Zn in carbonic anhydrase [Lane and Morel, 2000a, 2000b].
Nickel serves as the active metal center in urease, a metalloenzyme involved in the
assimilation of urea as a nitrogen source [Syrett and Peplinska, 1988; Ermler et al.,
1998]. Nickel also serves as a cofactor in other enzymes, including hydrogenase and
Ni-superoxide dismutase (Ni-SOD), an enzyme that protects organisms from oxidative
stress caused by superoxide [Mulrooney and Hausinger, 2003; Dupont et al., 2008].
Copper is also an essential micronutrient. It occurs along with iron cytochrome
oxidase, the terminal protein in respiratory electron transport that reduces O2 to H2O
[Wikström, 2006]. It also occurs in plastocyanin, which substitutes for the iron-protein
cytochrome C6 in photosynthetic electron transport in ocean diatoms [Peers and Price,
2006; Sunda, 2012]. In addition, co-limitations can occur for Cu and Fe as observed in
diatom cultures and batch incubation experiments [Peers et al., 2005; Annett et al.,
2008; Sunda, 2012]. Cadmium is biologically important for marine diatoms under
conditions of low Zn, as it substitutes for this metal as the metallocenter in carbonic
anhydrase [Lane and Morel, 2000a, 2000b]. Molybdenum and V, while typically
abundant in the water column with average concentrations around 100 nM [Collier,
1985] and 35 nM [Dupont et al., 1991], respectively, play important biological roles,
particularly as the metal cofactors in nitrogenases and other enzymes involved in N
fixation [Kisker et al., 1997; Rehder, 2000; Crans et al., 2004].
Zinc is required in a variety of essential proteins needed for cell growth and
replication. It occurs in carbonic anhydrase [Lindskog, 1997], RNA polymerase
[Coleman, 1992], involved in DNA regulation and transcription, and in tRNA
synthetase [Sankaranarayanan et al., 2000], involved in tRNA translation into proteins.
The distributions and bioavailability of some of the bioactive trace metals
discussed above have the potential to enhance or limit primary productivity and carbon
40
export in some regions of the world ocean. Examining the link between metal
distributions and phytoplankton biomass and primary productivity over basin-wide
spatial scales is thus essential for understanding the controls on the biological cycles of
carbon and nitrogen, including the biological transfer of carbon to the deep sea, which
helps regulate atmospheric CO2. In the last three decades, significant advances have
been made in understanding the oceanic distribution of trace metals [e.g., SCOR
Working Group, 2007]. Surface water samples collected during the Malaspina 2010
Circumnavigation Expedition (MCE) provided an opportunity to further advance the
study of both the distribution of trace elements in surface waters of all major oceanic
oligotrophic regions and the potential role that these micronutrients may exert on
phytoplankton biomass and primary productivity.
Taking advantage of the opportunity provided by the MCE samples, this study
aims to (i) determine the distribution of Co, Fe, Cd, Cu, Ni, V, and Mo in surface
waters of the tropical and subtropical Atlantic, Indian, and Pacific Oceans measured
during the MCE, providing new data from poorly explored and unexplored regions as
well as for some understudied metals; (ii) test for changes in the distribution of some
trace metals in surface waters of the Atlantic Ocean over the last 30 years; and (iii)
develop empirical models describing relationships between primary productivity and
the hydrological, biological, trace nutrient and macronutrient data collected during the
MCE.
3.3 Methods
3.3.1 Malaspina Circumnavigation Expedition
Surface water samples were collected during the MCE aboard the R/V
Hespérides from December 2010 to July 2011 (Figure 3.1 and Table B2 in appendix
41
B). The MCE consisted of six oceanic transects: a meridional transect from Cadiz,
Spain, to Rio de Janeiro, Brazil (Stations 37–54) from December 2010 to January
2011, a transect from Brazil to Cape Town, South Africa (Stations 55–69) from
January to February 2011, a transect in the Indian Ocean from South Africa to Perth,
Australia (Stations 1–18) from February to March 2011, two transects in the Pacific
Ocean, from Auckland, New Zealand, to Honolulu, Hawaii (Stations 70–86) from
April to May 2011 and from Hawaii to Panama (Stations 87 to 110) from May to June
2011, and a final transect back to Spain across the subtropical Atlantic, from Cartagena
de Indias, Colombia to Cartagena, Spain (Stations 19 to 36) from June to July 2011
(Table B2). Temperature and salinity were monitored during the cruise using a CTD
(SeaBird 9 plus, Bellevue, WA, USA). The mixed layer depth (MLD) was determined
from density profiles as the depth at which the density difference from the surface was
0.1 kg m
-3
.
3.3.2 Collection and Analysis of Samples for Trace Metals
Samples for trace metals were collected using a teflon tow-fish sampling
system deployed at approximately 3m depth utilizing established trace metal-clean
techniques [e.g., Bruland et al., 2005; Berger et al., 2008]. After sample collection,
seawater was filtered on board through acid-washed 0.2 µm filter cartridges and
acidified using Optima grade HCl to a pH<2.
42
Figure 3.1. Map showing cruise track and Longhurst biogeochemical ocean provinces [Longhurst,
1998]. The provinces crossed during the MCE were the following: (2) Australia-Indonesia Coastal
province, (3) Benguela Current Coastal province, (10) East Africa Coastal province, (30) Caribbean
province, (33) Indian South Subtropical Gyre province, (34) North Atlantic Tropical Gyral province,
(35) North Pacific Equatorial Countercurrent province, (36) North Pacific Tropical Gyre province, (37)
Pacific Equatorial Divergence province, (38) South Atlantic Gyral province, (40) Western Tropical
Atlantic province, (45) North Atlantic Subtropical Gyral province (east), and (51) South Pacific
Subtropical Gyre province. For a complete list of provinces please refer to Table B1 in appendix B.
Colors represent the different sections used in the multivariable linear regression model. Sections were
determined on the basis of distinct hydrographic and biological regimes and tested by k-means cluster
analysis.
Dissolved samples (<0.2 µm) were double bagged in polyethylene bags and
shipped to the trace metal clean laboratories at the University of Southern California in
Los Angeles, where they were preconcentrated by an organic extraction procedure
using the ammonium pyrrolidine dithiocarbamate/diethylammonium
diethyldithiocarbamate (APDC/DDDC) ligand technique described in Bruland et al.
[1985]. Levels of Fe, Cu, Cd, Mo, V, Co, and Ni were quantified by high-resolution
inductively coupled plasma mass spectrometry (HR-ICP-MS) on a Thermo Element 2
HR-ICP-MS, using external calibration curves and an internal indium standard. To
evaluate the accuracy of our analytical procedures, a certified seawater reference
material (SRM) (CASS-5) was preconcentrated and analyzed with the samples. The
recoveries of the SRM ranged from 96% for Ni to 107% for Co of the certified
43
concentration as shown in Table B3 in appendix B.
3.3.3 Collection and Analysis of Samples for Nutrients and Chlorophyll a
Samples for dissolved inorganic nutrients (PO4, NO3+NO2, SiO4),
phytoplankton biomass (as chlorophyll a) and primary production were collected by
means of 12 L Niskin bottles mounted on a rosette frame. Samples used for dissolved
nutrient analyses were drawn from the Niskin bottles into polyethylene vials and
immediately frozen (-20°C) until analysis. Concentrations were measured
spectrophotometrically with a Skalar autoanalyzer following standard procedures
[Grasshoff et al., 2009; Moreno-Ostos, 2012]. A volume of 250–500 mL was drawn
from the Niskin bottles for the total chlorophyll a determination, filtered through
Whatman® glass microfiber filters (25mm diameter, grade GF/F, Sigma-Aldrich,
Buchs, Switzerland) and kept frozen for at least 6 h until extraction. Pigments were
extracted by placing them in 5–7mL of 90% acetone at 4°C for 24 h, and the
fluorescence of the extract was determined by means of a Turner Designs fluorometer
[Yentsch and Menzel, 1963] calibrated with a chlorophyll a standard (Sigma-Aldrich,
Buchs, Switzerland).
3.3.4 Phytoplankton Productivity Measurement
Phytoplankton primary production was measured with the 14C-uptake
technique, following the procedures detailed in Marañón et al. [2000]. Samples were
obtained from five depths in the euphotic layer, corresponding to 100% (3m depth),
50%, 20%, 7%, and 1% incident PAR (photosynthetically active radiation) levels. For
each depth, four 70mL polystyrene bottles (three light bottles and one dark bottle)
were filled with unfiltered seawater under dimlight conditions, inoculated with 10–20
µCi of NaH
14
CO
3
and incubated inside temperature-controlled deck incubators for 6–8
h. Appropriate irradiance levels inside each incubator were obtained by using neutral
44
density and Blue Lagoon (Lee Filters, UK) filters. The incubation was terminated by
gentle filtration (vacuum pressure < 100mmHg) through 0.2 µm polycarbonate filters,
which were then exposed to concentrated HCl fumes to remove the nonfixed,
inorganic
14
C. After adding 5mL of liquid scintillation cocktail to the filters, the
radioactivity on each sample (disintegrations per minute (DPM)) was determined using
a Wallac scintillation counter. To compute the rate of photosynthetic carbon fixation,
the dark-bottle DPM value was subtracted from the light-bottle DPM value. A constant
value of 25,700 µg L
-1
was assumed for the concentration of dissolved inorganic
carbon. Euphotic zone-integrated values were computed by trapezoidal integration of
the volumetric data down to the 1% PAR depth.
3.3.5 Data Interpretation
A multivariable linear regression model was used to explore correlations
between oceanic primary productivity and the biogeochemical parameters measured
during the MCE. Statistical work was performed in R: A language and environment
for statistical computing program [R Core Team, 2014]. Prior to statistical analysis, the
data set was subdivided into sections on the basis of distinct hydrographic and
biological regimes. This hypothesis was tested via application of k-means cluster
analysis [R Core Team, 2014] on the data set. Linear regression models for integrated
primary productivity were constructed by employing a stepwise linear regression
algorithm [Lumley, 2009] to exhaustively calculate polynomial regressions versus
three response variables for all possible combinations of up to three variables. On the
basis of R2 and p values, statistically significant models were retained, and leave-one-
out cross validation was performed to aid in selection of linear regression models that
most likely reflect real trends and not data noise [Canty and Ripley, 2014].
45
3.4 Results and Discussion
3.4.1 Trace Metals, Hydrography, and Phytoplankton Productivity
Trace metal concentrations (Co, Fe, Cd, Cu, Ni, V, and Mo) varied spatially in
surface waters of the world’s oceans (Figures 2.2–2.7 and Table B2). Because distinct
physical and biogeochemical processes influence each ocean basin, trace metal
concentrations and phytoplankton properties are described separately for each region
and/or transect. Integrated primary production rates were, in most stations, within the
range of 10–60 mg C m
-2
h
-1
, which considering the photoperiod length and dark
respiratory losses, is roughly equivalent to 100–600mg C m
-2
d
-1
. The lowest rates of
production were measured near the center of the subtropical gyres, whereas the highest
values tended to occur in equatorial waters and near coastal zones.
3.4.1.1 Indian Ocean
Trace metals in the Indian Ocean have been poorly studied, especially in the
south subtropical zone, a region with relatively complex circulation forced by the
seasonal reversal of the dominant wind systems [Longhurst, 1998].
The MCE transect covered from South Africa to Western Australia. Samples
were taken during the second half of the austral summer, in the premonsoon period
(February–March). The transect conducted along the Indian Ocean crossed three
distinct oceanographic regimes (Figure 3.1): (i) the Eastern Africa Coastal province
influenced by the Agulhas current and the Agulhas Retroflection current, (ii) the
Indian South Subtropical Gyre province influenced by the seasonal monsoon winds,
and (iii) the Australia-Indonesia Coastal province influenced by the warm low-salinity
water from the Leeuwin current [Longhurst, 1998; Peterson and Stramma, 1991;
Gordon et al., 1987].
46
Figure 3.2. For the transect from South Africa to west Australia in the Indian Ocean, surface water
distributions are shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-
integrated primary productivity (PPi), (d) NO3, SiO4, and PO4, (e) cobalt, iron, and cadmium, (f)
copper and nickel, and (g) vanadium and molybdenum.
3.4.1.1.1 Hydrography
During the MCE, the influence of warm low-salinity water from the Agulhas
current and its retroflection was observed between 20 and 50°E (Figure 3.2a). Between
90 and 120°E, on the eastern side of the sampling transect, we detected the influence
S. Africa to Australia
A
20 30 40 50 60 70 80 90 100 110 120
Salinity (PSU)
35.2
35.4
35.6
35.8
36.0
Temperature (`C)
21
22
23
24
25
26
27
Salinity
Temperature
20 30 40 50 60 70 80 90 100 110 120
Chl-a (
µ
g/L)
0.00
0.04
0.08
0.12
0.16
0.20
PPi (mgC/m
2
h)
0
10
20
30
40
50
60
Chl-a
PPi
Longitude
20 30 40 50 60 70 80 90 100 110 120
PO4 (
µ
M)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
NO3 (
µ
M)
0.0
0.2
0.4
0.6
0.8
1.0
SiO4 (
µ
M)
0.0
0.5
1.0
1.5
2.0
2.5
PO4
NO3
SiO4
20 30 40 50 60 70 80 90 100 110 120
Fe (nM)
0.0
0.4
0.8
1.2
1.6
2.0
Co (pM)
0
10
20
30
40
Cd (pM)
8
12
16
20
24
28
Fe
Co
Cd
20 30 40 50 60 70 80 90 100 110 120
Ni (nM)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Cu (nM)
0.4
0.8
1.2
1.6
2.0
Ni
Cu
Longitude
20 30 40 50 60 70 80 90 100 110 120
Mo (nM)
70
80
90
100
110
120
V (nM)
15
20
25
30
35
Mo
V
B
C
D
E
G
F
47
of the warm low-salinity water from the Leeuwin current. Between 50 and 90°E at the
center of the Indian Ocean gyre, we observed the mixing between west gyre waters
(influenced by the warm low-salinity water of the south equatorial current with salinity
of 35.3) and east subtropical gyre waters (influenced by the west Australian current,
with salinity of 36.2).
3.4.1.1.2 Surface Trace Metal Distribution and Phytoplankton Biomass and
Production
In the Indian Ocean, trace metal distributions showed spatial differences along
the surface transect. In general, the concentration of all measured trace metals showed
enrichments near coastal zones, coincident with enhanced chlorophyll a and primary
productivity values (Figure 3.2). Away from the coastal zones, in the subtropical gyre
(between 85 and 105°E), pronounced surface chlorophyll a and integrated primary
productivity maxima (of 0.13 µg L
-1
and 6.84mgC m
-2
h
-1
, respectively) coincide with
maxima in Cd (27 pM), Ni (2.5 nM), Mo (106 nM), and V (29 nM) concentrations as
well as minima in Fe (0.18 nM), Co (3 pM), and the inorganic nutrients PO4 (0.02
µM) and NO3 (0.05 µM) (Figure 3.2). The enhanced biological productivity observed
at this location is probably due to detached cyclonic eddies developed from the
Leeuwin current, containing higher levels of chlorophyll a biomass and coastal
phytoplankton communities (Figure B1) [Griffin et al., 2001; Moore et al., 2007; Feng
et al., 2007].
Across the Indian Ocean transect, dissolved Mo, V, and Cu ranged from 70 to
110 nM, 18 to 32 nM, and 0.6 to 1.6 nM, respectively, with none of these elements
displaying a clear longitudinal trend (Figures 3.2e and 3.2f). Dissolved Cd, Co, and Ni
ranged from 12 to 26 pM, 5 to 32 pM, and 1.2 to 2.5 pM, respectively. Between 60 and
80°E, in the oligotrophic gyre, these metals showed an excellent negative correlation
48
with salinity (R
2
= 0.74, 0.80, and 0.80, respectively, p<0.05) suggesting that the
geographical distributions observed for these trace elements were influenced by water
mass mixing: the west gyre waters influenced by the warm low-salinity water of the
south equatorial current with relatively high metal concentrations (probably due to wet
deposition at the intertropical convergence zone (ITCZ)) mixing with the cold, high-
salinity, metal-depleted waters of the east subtropical gyre (Figures 3.2d and 3.2e).
Indian Ocean dissolved Fe concentrations ranged from 0.18nM in the oligotrophic
gyre to 1.8nM at the coastal zone off South Africa. No longitudinal trend was observed
for this metal other than enhanced values at the extreme eastern and western
boundaries of the sampling transect (Figure 3.2d).
3.4.1.2 Atlantic Ocean
The Atlantic Ocean is perhaps the best-studied ocean basin in the world,
particularly in the case of the North Atlantic. However, much of the prior attention has
focused on the distribution of Fe due to its importance in regulating oceanic primary
productivity. In comparison, relatively little is known about the regional distribution of
metals like V, Mo, Co, Cd, Cu, and Ni in the Atlantic. Therefore, samples collected
during the MCE provide an excellent opportunity to build on the work of previous
oceanographic campaigns and improve our understanding of some understudied trace
elements. The Atlantic Ocean sampling campaign was divided into three transects:
Colombia to Spain (June–July 2011), Spain to Brazil (December 2010 to January
2011), and Brazil to South Africa (January–February 2011) (Figure 3.1). In particular,
trace metal samples collected along two understudied transects in the Atlantic Ocean
(Colombia to Spain and Brazil to South Africa, Figure 3.1) provide new information
about the distribution of trace elements in this ocean basin.
49
3.4.1.2.1 Hydrography
3.4.1.2.1.1 Colombia to Spain Transect
The longitudinal transect that started in Cartagena de Indias, Colombia, and
ended in Cartagena, Spain, crossed three distinct biogeochemical ocean provinces
(Figure 3.1): (i) the Caribbean province influenced by the North Brazil current and the
north equatorial current, (ii) the North Atlantic Tropical Gyre province where the
lowest surface chlorophyll a values of the North Atlantic are usually found, and (iii)
the North Subtropical Gyre province influenced by the Canary current [Longhurst,
1998].
Samples were collected in late May to early June, when the North Equatorial
Counter current surface flow is discontinuous and North Brazil current waters
(chemically modified by the Amazon and Orinoco River waters) enter the province
between Trinidad and Barbados [Farmer et al., 1993; Longhurst, 1998]. The influence
of this warm (28°C) low-salinity (35.7) water is observed in the western side of the
sampling transect between 60° and 80°W (Figure 3.3a). On the eastern side of the
sampling section between 15° and 25°W, the influence of relatively cold (21°C) high-
salinity (36.8) water from the Canary current is observed. The center of the North
Atlantic tropical gyre (25 to 80°W) seems to be a mixture of these two distinct water
masses (Figure 3.3a).
50
Figure 3.3. For the transect from Colombia to Spain in the Atlantic Ocean, surface water distributions
are shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-integrated
primary productivity (PPi), (d) NO
3
, SiO
4
, and PO
4
, (e) cobalt, iron, and cadmium, (f) copper and nickel,
and (g) vanadium and molybdenum.
3.4.1.2.1.2 Spain to Brazil
The transect that started in Cadiz, Spain, and ended in Rio de Janeiro, Brazil,
covered four different biogeochemical ocean provinces (Figure 3.1): (i) the North
Subtropical Gyre province, (ii) the North Atlantic Tropical Gyre province, (iii) the
Colombia to Spain
A
-80 -70 -60 -50 -40 -30 -20 -10
Salinity (PSU)
35.0
35.5
36.0
36.5
37.0
37.5
38.0
Temperature (`C)
20
22
24
26
28
30
32
Salinity
Temperature
-80 -70 -60 -50 -40 -30 -20 -10
Chl-a (
µ
g/L)
0.0
0.1
0.2
0.3
0.4
PPi (mgC/m
2
h)
0
10
20
30
40
Chl-a
PPi
Longitude
-80 -70 -60 -50 -40 -30 -20 -10
PO4 (
µ
M)
0.00
0.04
0.08
0.12
NO3 (
µ
M)
0.0
0.2
0.4
0.6
0.8
SiO4 (
µ
M)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
PO4
NO3
SiO4
-80 -70 -60 -50 -40 -30 -20 -10
Fe (nM)
0.0
0.4
0.8
1.2
1.6
Co (pM)
20
30
40
50
60
Cd (pM)
5
10
15
20
25
30
35
Fe
Co
Cd
-80 -70 -60 -50 -40 -30 -20 -10
Ni (nM)
0.8
1.2
1.6
2.0
2.4
2.8
Cu (nM)
0.0
0.4
0.8
1.2
1.6
2.0
Ni
Cu
Longitude
-80 -70 -60 -50 -40 -30 -20 -10
Mo (nM)
70
80
90
100
110
120
V (nM)
8
12
16
20
24
28
32
Mo
V
B
C
E
F
D
G
51
Western Tropical Atlantic province influenced by the seasonally varying strength and
position of the hemispheric trade winds and the ITCZ, and (iv) the South Atlantic
Gyral province (west), influenced by the Brazil and south equatorial currents [Peterson
and Stramma, 1991; Longhurst, 1998].
Figure 3.4. For the transect from Spain to Brazil in the Atlantic Ocean, surface water distributions are
shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-integrated primary
productivity (PPi), (d) NO3, SiO4, and PO4, (e) cobalt, iron, and cadmium, (f) copper and nickel, and
(g) vanadium and molybdenum.
Spain to Brazil
-30 -20 -10 0 10 20 30 40
Salinity (PSU)
35.0
35.5
36.0
36.5
37.0
37.5
Temperature (
O
C)
16
20
24
28
32
Salinity
Temperature
-30 -20 -10 0 10 20 30 40
Chl-a (
µ
g/L)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
PPi (mgC/m
2
h)
0
10
20
30
40
Chl-a
PPi
Latitude
-30 -20 -10 0 10 20 30 40
PO4 (
µ
M)
0.00
0.05
0.10
0.15
0.20
0.25
NO3 (
µ
M)
0.0
0.4
0.8
1.2
1.6
2.0
SiO4 (
µ
M)
0.0
0.4
0.8
1.2
1.6
2.0
PO4
NO3
SiO4
-30 -20 -10 0 10 20 30 40
Fe (nM)
0.0
0.5
1.0
1.5
2.0
Co (pM)
0
20
40
60
80
Cd (pM)
10
15
20
25
30
Fe
Co
Cd
-30 -20 -10 0 10 20 30 40
Ni (nM)
0.8
1.2
1.6
2.0
2.4
2.8
Cu (nM)
0.4
0.8
1.2
1.6
2.0
2.4
Ni
Cu
Latitude
-30 -20 -10 0 10 20 30 40
Mo (nM)
60
80
100
120
140
V (nM)
16
20
24
28
32
36
Mo
V
B
C
E
F
D
G
A
52
The influence of relatively cold (18–22°C) high-salinity (36.5–37) waters from
the Canary current is observed in the northern part of the sampling transect between 24
and 35°N (Figure 3.4a). The rest of the transect maintains a roughly constant
temperature of about 28°C (Figure 3.4a) suggesting the southward flow of this water
mass and subsequent mixing with warmer waters from the north and south equatorial
currents and ultimately with the warm subtropical waters of the Brazil current
[Peterson and Stramma, 1991; Longhurst, 1998]. In contrast, salinity values dropped
between 15°N and 5°S latitude (Figure 3.4a) consistent with high net precipitation
caused by the ITCZ at those latitudes [Peterson and Stramma, 1991; Bigg, 2003].
3.4.1.2.1.3 Brazil to South Africa
The sampling transect that began in Brazil and ended in Cape Town, South
Africa, encompasses only one biogeochemical ocean province (Figure 3.1), the South
Atlantic Gyral province, influenced by the coastal boundary currents of Brazil and
Benguela [Longhurst, 1998]. The hydrographic conditions observed during this
transect seem to reflect the interaction between the warm (27°C) high-salinity (36.6)
waters that dominate the western side of the South Subtropical Gyre and the relatively
cold (20°C) low-salinity (35.5) waters from the South Atlantic current (Figure 3.5a).
The observed salinity and temperature trends between Brazil and South Africa seem to
be the result of mixing between these water masses.
3.4.1.2.2 Surface Trace Metal Distribution and Phytoplankton Biomass and
Production
3.4.1.2.2.1. Colombia to Spain
In this region of the Atlantic Ocean we observed trace metal concentration
enrichments near coastal areas (Figures 3.3d–3.3f). In the Caribbean province, between
53
70 and 55°W, pronounced surface water chlorophyll a and integrated primary
productivity maxima of 0.3µg L
-1
and 38mg C m
-2
h
-1
, respectively, coincide with
maxima in V (26 nM) and Mo (115 nM) concentrations as well as minima in Co (23
pM) and PO4 (0.03µM) (Figures 3.3b–3.3f).
Figure 3.5. For the transect from Brazil to South Africa in the Atlantic Ocean, surface water
distributions are shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-
integrated primary productivity (PPi), (d) NO3, SiO4, and PO4, (e) cobalt, iron, and cadmium, (f)
copper and nickel, and (g) vanadium and molybdenum.
Brazil to S. Africa
-40 -30 -20 -10 0 10 20
Salinity (PSU)
35.4
35.6
35.8
36.0
36.2
36.4
36.6
Temperature (
O
C)
20
21
22
23
24
25
26
27
28
Salinity
Temperature
-40 -30 -20 -10 0 10 20
Chl-a (
µ
g/L)
0.00
0.02
0.04
0.06
0.08
0.10
0.12
PPi (mgC/m
2
h)
10
15
20
25
30
35
40
Chl-a
PPi
Longitude
-40 -30 -20 -10 0 10 20
PO4 (
µ
M)
0.00
0.04
0.08
0.12
0.16
0.20
NO3 (
µ
M)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
SiO4 (
µ
M)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
PO4
NO3
SiO4
-40 -30 -20 -10 0 10 20
Fe (nM)
0.5
0.6
0.7
0.8
0.9
1.0
Co (pM)
15
20
25
30
35
40
45
Cd (pM)
8
12
16
20
24
28
Fe
Co
Cd
-40 -30 -20 -10 0 10 20
Ni (nM)
0.0
0.5
1.0
1.5
2.0
2.5
Cu (nM)
1.0
1.2
1.4
1.6
1.8
2.0
Ni
Cu
Longitude
-40 -30 -20 -10 0 10 20
Mo(nM)
65
70
75
80
85
90
95
V (nM)
16
18
20
22
24
26
Mo
V
B
C
E
F
D
G
A
54
Dissolved Fe and Ni ranged from0.4 to 1.2nM and 1.1 to 2.4 nM, respectively,
with neither element displaying a clear longitudinal trend other than enhanced Fe
values at the eastern and western sections of the transect, in environments influenced
by land proximity (Figures 3.3d and 3.3e).
Dissolved Cd and Cu ranged from 6.3 to 29pM and 0.4 to 1.6 nM, respectively.
Both metals showed a similar trend, with the highest levels detected between 80 and
45°W in the Caribbean province and decreasing concentrations toward the eastern side
of the transect, with the lowest values measured between 40 and 20°W (Figures 3.3d
and 3.3e).
In the case of Cu, however, high concentrations of this metal were measured at
the easternmost station. Dissolved V and Mo ranged from 12 to 28 nM and 75 to 115
nM, respectively. Between 70 and 45°W within the Caribbean province, their
maximum values coincide with the highest levels of phytoplankton biomass (as
chlorophyll a) and primary productivity (Figure 3.3f). Dissolved Co concentration was
55 pM in the coastal zone off Colombia while in the rest of the Caribbean province, Co
concentrations were around 25 pM. The lowest Co levels were measured between
72°W and 50°W longitude, coinciding with maxima in both chlorophyll a and primary
productivity values.
3.4.1.2.2.2. Spain to Brazil
The distribution of trace metals in surface waters of this latitudinal transect
showed distinct regional features (Figure 3.4). Between 20°N and 3°S, pronounced
chlorophyll a and primary productivity maxima of 0.24 µg L
-1
and 31mgC m
-2
h
-1
,
which reflect the effect of the Mauritanian and equatorial upwelling regions [Marañón
et al., 2000], coincided with a maximum in SiO4 (1.55 µM) concentration and minima
in Co (10 pM), Fe (0.5 nM), V (20 nM), and PO4 (0.02 µM) (Figures 3.4b–3.4f).
55
Figure 3.6. For the transect from New Zealand to Hawaii in the Pacific Ocean, surface water
distributions are shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-
integrated primary productivity (PPi), (d) NO3, SiO4, and PO4, (e) cobalt, iron, and cadmium, (f)
copper and nickel, and (g) vanadium and molybdenum.
Dissolved Cd, Mo, and V ranged from 14 to 28 pM, 70 to 135 nM, and 20 to
33 nM, respectively, and none of these elements displayed a clear latitudinal trend
(Figures 3.4d–3.4f). Concentrations of Co and Fe ranged from 10 to 60 pM and 0.5 to
1.8 nM, respectively. The highest levels of both elements were measured in the
New Zealand to Hawaii
A
-40 -30 -20 -10 0 10 20 30
Salinity (PSU)
34.2
34.4
34.6
34.8
35.0
35.2
35.4
Temperature (`C)
20
22
24
26
28
30
32
Salinity
Temperature
-40 -30 -20 -10 0 10 20 30
Chl-a (
µ
g/L)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
PPi (mgC/m
2
h)
0
10
20
30
40
50
60
Chl-a
PPi
Latitude
-40 -30 -20 -10 0 10 20 30
NO3 (
µ
M)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
PO4 (
µ
M)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
SiO4 (
µ
M)
0
1
2
3
4
5
6
NO3
PO4
SiO4
-40 -30 -20 -10 0 10 20 30
Co (pM)
6
8
10
12
14
16
18
20
22
Fe (nM)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Cd (pM)
14
16
18
20
22
24
26
28
Co
Fe
Cd
-40 -30 -20 -10 0 10 20 30
Cu (nM)
0.2
0.4
0.6
0.8
1.0
1.2
Ni (nM)
1.0
1.5
2.0
2.5
3.0
3.5
Cu
Ni
Latitude
-40 -30 -20 -10 0 10 20 30
V (nM)
16
20
24
28
32
36
Mo (nM)
70
80
90
100
110
120
130
V
Mo
B
C
D
E
F
G
56
northern part of the transect, decreasing southward (Figure 3.4d). This geographical
trend is probably due to dust deposition, which is higher in the North Atlantic
downwind from the Sahara, decreasing rapidly south of the ITCZ [Bristow et al., 2010;
Ridley et al., 2012].
Dissolved Cu ranged from 1.6 to 2.2 nM. No latitudinal trend is displayed by
concentrations of this metal other than enhanced values at the extreme north and south
parts of the transect (Figure 3.4e). Dissolved Ni concentration ranged from 0.9 to 2.4
nM, and although no clear latitudinal trend is observed for this metal, the variation
follows closely that of chlorophyll a (Figures 3.4b and 3.4e).
3.4.1.2.2.3. Brazil to South Africa
The highest levels of dissolved Fe (0.7 nM), Co (40 pM), Ni (2.1 nM), Cu (1.8
nM), and NO3 (0.5 µM) along this transect were measured off the coast of South
Africa (Figures 3.5c–3.5e). These high values coincide with areas of enhanced primary
productivity (37mgC m
-2
h
-1
) probably due to the influence of the nutrient-rich waters
from the Benguela current (Figure 3.5b).
The distribution of dissolved Co, Cu, and Ni ranged from 23 to 40 pM, 1.1 to
1.8 nM, and 1.0 to 2.1 nM, respectively, and their spatial distribution was inversely
related to both surface salinity and temperature (Figure 3.5a).
Minimum values were found in the western side of the oligotrophic gyre and
maximum values in the eastern side of the transect (Figures 3.5d and 3.5e). Dissolved
Fe concentrations ranged from 0.5 to 0.9 nM, and no longitudinal trend was observed
for this metal other than higher values in the western side of the gyre and off the coast
of South Africa (Figure 3.5d). Similarly, dissolved Cd, V, and Mo concentrations,
which ranged from 18 to 42 pM, 18 to 25 nM, and 67 to 90 nM, respectively, did not
show a clear longitudinal trend (Figures 3.5d and 3.5f).
57
3.4.1.3 Pacific Ocean
The Pacific Ocean is the world’s largest ocean basin, with about 165.25 million
square kilometers in area, covering one third of Earth’s total surface area. Accurate
data on the distribution of trace metals in the surface waters of the Pacific Ocean have
been generated over many years [e.g., Boyle et al., 1977; Bruland, 1980; Nürnberg et
al., 1983; Bruland et al., 1994; Boyle et al., 2005; Blain et al., 2008; Slemons et al.,
2010]. However, it is not surprising that many areas of this vast ocean basin remain
understudied or have not been studied at all, especially regarding trace metal
concentrations. Dissolved Co, Fe, Cd, Cu, Ni, V, and Mo concentrations measured in
the MCE provide a new data set that improves our understanding of the distribution of
trace metals in this ocean basin. Samples were collected along two transects in the
Pacific Ocean: from Auckland, New Zealand, to Honolulu, Hawaii, (April–May 2011)
and from Hawaii to Panama (May–June 2011).
3.4.1.3.1. Hydrography
3.4.1.3.1.1. New Zealand to Hawaii
The latitudinal transect from New Zealand to Hawaii crossed three different
biogeochemical ocean provinces (Figure 3.1): (i) the South Subtropical Gyre province,
which may be the most uniform and seasonally stable region of the open ocean, (ii) the
Pacific Equatorial Divergence province that encompass the nitrate-replete waters of the
eastern tropical Pacific, and (iii) the North Pacific Tropical Gyre province, where curls
due to wind stress form eddies that induce upwelling and downwelling off the
Hawaiian Islands [Longhurst, 1998; Jia et al., 2011].
58
Figure 3.7. For the transect from Hawaii to Panama in the Pacific Ocean, surface water distributions are
shown for (a) depth, (b) salinity and temperature, (c) chlorophyll a (Chl a) and depth-integrated primary
productivity (PPi), (d) NO3, SiO4, and PO4, (e) cobalt, iron, and cadmium, (f) copper and nickel, and
(g) vanadium and molybdenum.
Most of the sampling sites along this transect were located within the tropics.
Consequently, the temperature measured at the stations between 19°S and 7°N was
fairly constant, oscillating between 27.7 and 29.6°C (Figure 3.6a). In contrast, samples
collected at the southernmost site (34°S) were located in colder water (21°C)
Hawaii to Panama
A
-160 -150 -140 -130 -120 -110 -100 -90 -80
Salinity (PSU)
32.8
33.2
33.6
34.0
34.4
34.8
35.2
Temperature (`C)
20
22
24
26
28
30
32
Salinity
Temperature
-160 -150 -140 -130 -120 -110 -100 -90 -80
Chl-a (
µ
g/l)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
PPi (mgC/m
2
h)
0
20
40
60
80
100
Chl-a
PPi
Longitude
-160 -150 -140 -130 -120 -110 -100 -90 -80
NO3 (
µ
M)
0
1
2
3
4
PO4 (
µ
M)
0.00
0.05
0.10
0.15
0.20
0.25
SiO4 (
µ
M)
0
1
2
3
4
NO3
PO4
SiO4
-160 -150 -140 -130 -120 -110 -100 -90 -80
Co (pM)
0
5
10
15
20
25
Fe (nM)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Cd (pM)
0
5
10
15
20
25
30
Co
Fe
Cd
-160 -150 -140 -130 -120 -110 -100 -90 -80
Cu (nM)
0.0
0.2
0.4
0.6
0.8
Ni (nM)
0.4
0.8
1.2
1.6
2.0
2.4
Cu
Ni
Longitude
-160 -150 -140 -130 -120 -110 -100 -90 -80
V (nM)
0
10
20
30
40
Mo (nM)
60
70
80
90
100
110
V
Mo
B
C
D
E
F
G
59
influenced by the Antarctic Circumpolar current. The influence of the South Pacific
convergence zone (SPCZ) is observed between 20° and 10°S, where salinity levels
drop from 35.2 to 34.4 (Figure 3.6a). Between 10°S and 1°N, east of the SPCZ, a
surface salinity maximum is formed due to a positive evaporation-precipitation
balance [Donguy, 1994]. The influence of the ITCZ is observed at the northernmost
part of the transect, south of the Hawaiian Islands between 2 and 15°N, where salinity
declines from the tropical salinity maximum value of 35.5 to 34.6 (Figure 3.6a).
3.4.1.3.1.2. Hawaii to Panama
The longitudinal transect that started in Hawaii and ended in Panama covered
two different biogeochemical ocean provinces (Figure 3.1): (i) the North Pacific
Tropical Gyre province influenced by the North Equatorial and California current
systems as well as by the effect of the Hawaiian Islands and (ii) the North Pacific
Equatorial Countercurrent province, influenced by the quasi-permanent cyclonic
feature, the Costa Rica dome [Umatani and Yamagata, 1991; Longhurst, 1998].
The distribution of salinity at the surface shows maximum values of 35 around the
coast of Hawaii at about 157°W (Figure 3.7a). These high-salinity values are likely
due to the influence of waters flowing from the subtropical salinity maximum [Talley
et al., 2011]. In the middle of the sampling transect (around 105°W), salinity values
start decreasing probably due to the influence of heavy precipitation in the vicinity of
the ITCZ [McClymont et al., 2012]. Values keep decreasing eastward, where a
minimum is observed between 85 and 88°W (Figure 3.7a). The occurrence of this low-
salinity water at the farthest east side of the transect is probably due to local coastal
precipitation, as it has been shown that during the rainy season, from May to
November, such low-salinity water is confined to coastal areas [Peterson, 1960].
60
3.4.1.3.2. Surface Trace Metal Distribution and Phytoplankton Biomass
and Production
3.4.1.3.2.1. New Zealand to Hawaii
Close to the equator, between 5°S and 5°N, we observed pronounced primary
productivity and chlorophyll a maxima of 50mgC m
-2
h
-1
and 0.35 µg L
-1
, respectively,
which coincided with maxima in concentrations of Co, Cd, Ni, V, and Mo
concentrations (19 pM, 25 pM, 3.2 nM, 34 nM, and 120 nM, respectively) and the
macronutrients
NO3, PO4, and SiO4 (2.7 µM NO3, 0.3 µM PO4, and 5.3 µM SiO4) (Figure 3.6). The
enhanced biological productivity and the high macronutrient and trace-nutrient levels
are probably due to the influence of equatorial upwelling that replaces the warm
nutrient-depleted surface waters with denser, cooler, nutrient-rich waters from below
[Talley et al., 2011]. Along this transect, dissolved Co, Cd, Ni, Cu, Mo, and V ranged
from 8 to 20 pM, 16 to 26 pM, 1.5 to 3.3 nM, 0.5 to 3.3 nM, 80 to 120 nM, and 20 to
34 nM, respectively, although none of these elements displayed a clear longitudinal
trend (Figures 3.6d–3.6f). Dissolved Fe concentration along this transect ranged from
0.2 to 1.1 nM. No latitudinal trend was observed for Fe other than higher values at the
northern and southern ends of the transect (Figure 3.6d). Although Fe levels are low
(<0.5 nM) around the equator at about 13°S to 10°N, the lowest concentrations are
found in the Southern Hemisphere at about 5°S (0.2nM), increasing steadily toward
the north. This trend agrees well with the process suggested by Duce and Tindale
[1991], in which African dust from the desertification of the Sahel is carried into the
Caribbean and across the Isthmus of Panama, depositing 1–10 mg Fe m
2
yr
-1
onto the
surface of the Pacific Equatorial Divergence province just north of the equator (Figure
3.1). There is also direct evidence that in this province the trade winds of the Northern
61
Hemisphere carry a significantly higher concentration of mineral dust than the trades
of the Southern Hemisphere [Maenhaut et al., 1983], potentially enhancing Fe,
chlorophyll a, and primary productivity values in the Pacific Ocean between 5° and
8°N (Figure 3.6c).
3.4.1.3.2.2. Hawaii to Panama
The divergent upwelling effect at the Costa Rica dome in the eastern part of
this transect causes the transport of the tropical thermocline (and its associated
nutricline) to the surface in the center of the dome with significant biological
consequences [Umatani and Yamagata, 1991]. This effect is observed between 100°
and 80°W as pronounced surface water primary productivity and chlorophyll a
maxima of 82mg C m
-2
h
-1
and 0.5 µg L
-1
, respectively, which coincide with maxima
in Fe (0.9 nM), Cd (20 pM), and Mo (102 nM) and nutrients NO3 (3.5 µM), PO4 (0.2
µM), and SiO4 (3.6 µM) (Figure 3.7). As observed in other regions of the world
oceans, dissolved Cu, Ni, V, and Mo ranged from 0.2 to 0.7 nM, 0.8 to 2.2 nM, 10 to
30 nM, and 70 to 105 nM, respectively, with none of these elements displaying a clear
longitudinal trend (Figures 3.7e and 3.7f). Dissolved Co, Fe, and Cd ranged from 1 to
20 pM, 0.1 to 1.1 nM, and 5 to 25 pM respectively. No longitudinal trend is displayed
by these metals other than enhanced values off the coast of Hawaii and between 100°
and 85°W, the area affected by the Costa Rica dome (Figure 3.7d).
3.4.2 Temporal Changes in Trace Metal Concentrations in the Surface
Atlantic Ocean.
Since the advent of trace metal clean techniques, trace metal distributions have
been established for vast areas of the ocean, in particular the Atlantic Ocean. The data
derived from samples collected along the Spain to Brazil transect (Figure 3.1) provide
the opportunity to explore temporal variability in the distribution of trace metals in
62
surface waters of the Atlantic Ocean by comparing our results with some of those
measured along the same section over the last 30 years. In this analysis, our goal is not
to provide a comprehensive survey of prior work but rather to put our results in
context—both demonstrating the quality of our data and providing an opportunity to
consider temporal trends for one restricted region by focusing attention on a set of
previously published studies that covered the most similar region to our own Atlantic
transect.
A comparison of the
salinity measured
between Spain and Brazil
in December 2010 and
January 2011 during the
MCE and that measured
in the same area in 1978
[Boyle et al., 1981], 1980
[Kremling, 1985], 1989
[Pohl et al., 2011], 1990
[Van Der Loeff et al.,
1997], and 2002 [Saito
and Moffett, 2002; Bowie
et al., 2002] (Figure 3.8)
show that the
hydrographic conditions
in surface waters of the
Atlantic Ocean are
Figure 3.8. Map showing the cruise tracks of eight different
oceanographic campaigns (including MCE, reported in this study)
in the Atlantic Ocean basin along the Spain to Brazil transect.
63
statistically similar (Figures 3.9a and 3.9b). The fact that surface salinity levels in this
area of the ocean have remained relatively unchanged over the last 30 years suggests
that the physical processes influencing this area of the Atlantic Ocean (e.g., water mass
composition/structure and general circulation) have also remained relatively steady.
Therefore, any changes in trace metal levels in our temporal comparison are most
likely due to fluctuation in the inputs and outputs of metals.
Figure 3.9. Surface water distributions and box-and-whiskers plot comparison ofmeasured (a and b)
salinity, (c and d) cobalt, (e and f) iron, (g and h) nickel, (i and j) copper, and (k and l) cadmium with
literature data for the transect from Spain to Brazil. Boxes encompass values between the 25th and 75th
percentiles, whiskers give the 95% range of values, and lines in the box represent the median values of
the distribution. Solid circles represent outliers, which are values above 1.5 times the length of the box.
Dissolved Co concentrations measured during the MCE, plotted in Figure 3.9c
as a function of latitude along with data from four other Atlantic cruises [Pohl et al.,
2011; Bowie et al., 2002; Berquist and Boyle, 2006], did not exhibit statistical
differences with respect to previously published data (Figure 3.9d). These similarities
-30 -20 -10 0 10 20 30 40
Co (pM)
0
20
40
60
80
100
Malaspina
Pohl, 1989
Saito, 2002
Bowie, 2002
Pohl Bowie Saito
D C
Malaspina
-30 -20 -10 0 10 20 30 40
Salinity (PSU)
33
34
35
36
37
38
Malaspina, 2011
Boyle, 1981
Der Loeff (VII/5), 1997
Pohl, 1989
Kremling, 1985
Der Loeff(IX/1), 1997
Saito, 2002
Bowie, 2002
Boyle DerLoeff Pohl Kremling Bowie Saito Malaspina
B A
Berquist -30 -20 -10 0 10 20 30 40
Fe (nM)
0.0
0.5
1.0
1.5
2.0
2.5
Malaspina
Pohl, 1989
Bowie, 2002
Berquist, 2006
Pohl Bowie Malaspina
E F
Malaspina Boyle Pohl Kremling
DerLoeff
Latitude
-30 -20 -10 0 10 20 30 40
Cd (pM)
0
20
40
60
130
140
Malaspina
Oceanus, 1978
Der Loeff VIII/7, 1990
Pohl, 1989
Kremling, 1985
Der Loeff IX/1, 1990
-30 -20 -10 0 10 20 30 40
Ni (nM)
0
1
2
3
4
5
Malaspina
Boyle, 1981
Pohl, 1989
Kremling, 1985
-30 -20 -10 0 10 20 30 40
Cu (nM)
0.0
0.5
1.0
1.5
2.0
2.5
Malaspina
Boyle, 1981
Der Loeff VIII/7, 1990
Pohl, 1989
Der Loeff IX/1, 1990
Kremling, 1985
Boyle Malaspina Pohl Kremling
DerLoeff Boyle Malaspina Pohl Kremling DerLoeff
J I
H G
K L
Latitude
64
suggest that in this part of the Atlantic Ocean (Figure 3.8), the balance of Co inputs
and outputs has remained relatively invariant over the last 30 years. The same
unchanged temporal trend can be observed for Cu, Ni, and Cd (Figures 3.9g–3.9l). In
the case of Fe, concentrations measured on the MCE samples are between the range
reported by Pohl et al. [2011] for samples collected in 1989 and Bowie et al. [2002] for
samples collected in 1996 (Figures 3.9e and 3.9f). However, Fe concentrations were
on average 0.3 nM higher in 2011 at the MCE sampling sites (median = 0.6 nM) than
the levels reported by Bergquist and Boyle [2006] (median = 0.3 nM) (Figures 3.9e
and 3.9f). The differences might be attributed to the season in which the samples were
collected, as pulses of northeast winds that draw South Atlantic Central water to the
surface occur more frequently during the austral spring-summer (when the MCE
samples were collected) than in autumn-winter (when the Bergquist and Boyle [2006]
samples were collected). Although both sets of samples were collected approximately
200 km away from the upwelling-downwelling zone of Cape Frio, the influence of
upwelling is observed more in the MCE samples as suggested by the higher
concentrations of Fe, Cd, NO3, and PO4 (Figures 3.3c and 3.3d).
In general, the distribution of metals measured in the latitudinal transect between Spain
and Brazil during the MCE agrees well with metal levels reported in the literature
(Figure 9). This leads to the conclusion that the balance of inputs and outputs foremost
trace metals has remained relatively unchanged in this part of the world ocean over the
last 30 years.
3.4.3 Effect of Trace Metals, Hydrography, and Macronutrients on
Phytoplankton Biomass and Productivity
We utilized a modeling approach to describe potential relationships between
primary productivity and the hydrological, biological, trace-nutrient and macronutrient
65
data collected during the MCE (Table B2). We used a multivariable linear regression
model (equation (1)) to identify the variables within the sample set that best correlate
with the observed primary productivity in each ocean basin, as follows:
Primary Productivity = C
0
+ C
1
X
1
+ C
2
X
2
+ C
3
X
3
(1)
where Cn are the regression weights, computed in a way that minimizes the sum of
squared deviations, and Xn are the independent variables (e.g. trace metal
concentrations).
Table 3.1. Best Fit Linear Models and Diagnostic Statistics for Primary Productivity for the Ocean
Basins and Transects Sampled During the MCE.
Linear regression models were constructed using a stepwise linear regression
algorithm [Lumley, 2009] and validated by a leave-one-out cross-validation method
[Canty and Ripley, 2010] to minimize over fitting. After the validation step, the best fit
model was determined by the highest R2, lowest p value, and lowest predictive error.
Best fit models and relevant statistical metrics for all six MCE transects are presented
in Table 3.1, summarized in Table 3.2, and plotted versus observed field data in Figure
3.10.
Ocean&Basin Transect Section Model&variables R
2
p PE
1 Chla&+&NO3&+&Ni 0.86 0.001 0.03
2 Temp&+&SiO4&+&Cd 1.00 0.001 0.09
1 NO
3
&+&V&+&Mo 0.97 0.045 0.00
2 Chl>a&+&PO
4
&+&Fe 0.76 0.007 0.24
1 NO
3
&+&Co&+&Cu 0.94 0.000 0.25
2 MLD&+&Co&+&Fe 0.97 0.007 0.03
1 MLD&+&Chl>a&+&Co 0.94 0.001 0.07
2 Co&+&Cd&+&NO
3 0.94 0.036 0.00
1 SiO
4
&+&NO
3
&+&Cd 0.78 0.001 0.14
2 Salinity&+&NO
3
&+&Cd 0.92 0.004 0.32
1 PO
4
&+&Fe&+&V 0.84 0.020 0.46
2 Temp&+&Fe&+&Cd 0.97 0.002 0.18
Atlantic&Ocean
Colombia&to&Spain
Spain&to&Brazil
Brazil&to&S.&Africa
Pacific&Ocean
Hawaii&to&Panama
NZ&to&Hawaii
Indian&Ocean S.&Africa&to&Australia
66
The best fit model for primary productivity for the transect from South Africa
to Australia involves chlorophyll a, NO3, and Ni for the western section and
temperature, SiO4 and Cd for the eastern side of the transect (Table 3.1 and Figure
3.10a). For the transect from Colombia to Spain, primary productivity is best predicted
by NO3, V, and Mo for the western part and chlorophyll a, PO4 and Fe for the eastern
side of the transect (Table 3.1 and Figure 3.10b). From Spain to Brazil, the best fit
model identifies Co as an important independent variable in the entire transect, while
NO3 and Cu were significant for the northern section, and Fe and mixed layer depth
(MLD) for the southern part of the transect (Table 3.1 and Figure 3.10c). From Brazil
to South Africa, the model shows the relevance of Co for the entire transect, and
chlorophyll a and MLD for the western section, while Cd and NO3 were important
variables for the eastern side of the transect (Table 3.1 and Figure 3.10d).
Table 3.2. Table Summarizing the Variables and Correlation Type (Positive or Negative) Identified in
the Best Fit Models Describing Productivity for All the Ocean Basins and Transects Sampled During the
MCE
The model for the transect from Hawaii to Panama includes NO
3
and Cd
concentrations for the entire transect, SiO
4
for the western section, and salinity for the
eastern part of the transect (Table 3.1 and Figure 3.10e). The best fit model for primary
productivity along the transect from New Zealand to Hawaii includes Fe
concentrations for the entire transect, PO
4
and V for the southern section, and
!
Ocean&Basin& Transect& Salinity& Temp& Chl4a& SiO
4&
NO
3&
PO
4&
Co& Fe& Cd& Cu& Ni& V& Mo& MLD&
Indian&Ocean&
S.#Africa#to#
Australia#
+ + - +
-
-
Atlantic&Ocean&
Colombia#to#
Spain#
+
+ +
+
+ +
Spain#to#
Brazil#
-
- +
+
+
Brazil#to#S.#
Africa#
+
+
+
+
+
Pacific&Ocean&
Hawaii#to#
Panama#
+
+ -
+
New#Zealand#
to#Hawaii#
-
+
- +
+
!
67
temperature and Cd for the northern section (Table 3.1 and Figure 3.10f).
The multivariable linear regression approach allows us to explore correlative
relationships among the independent variables that could influence surface biomass
along the MCE cruise. However, among other shortcomings, a major conceptual
limitation of linear regression models is that they do not identify the underlying causal
mechanisms responsible for the observed correlations. With this in mind, a functional
discussion of the multivariable linear model outcome is presented below, particularly
considering the extent to which our model results are consistent with field and
laboratory observations reported in the literature.
Although the variables statistically determining primary productivity during the
MCE were different for the different regions sampled, NO
3
comes out as an important
parameter describing primary productivity in most ocean basins (Table 3.2), which is
consistent with the low dissolved inorganic N:P ratios (Table B4) and the established
notion that most of the global ocean is nitrogen limited [Ryther and Dunstan, 1971;
Falkowski, 1997; Moore et al., 2013]. The exception to this trend was observed in the
transect from New Zealand to Hawaii, the only transect in which NO
3
is not required
as an independent variable in the best fit model for primary productivity. This result is
consistent with the fact that this transect crossed a zone of increased NO
3
concentrations —the Pacific Equatorial Divergence province [Longhurst, 1998]— and
with recent work showing that primary productivity in this area of the Pacific Ocean
has increased in recent decades due to a shift in phytoplankton community structure
from mostly eukaryotes to mostly nitrogen-fixing prokaryotes [Karl et al., 2001;
Sherwood et al., 2014]. For the same transect, Table 3.2 shows that PO4 and Fe are
elements influencing primary productivity in this area of the ocean. This result is
consistent with studies showing that both Fe [e.g., Rueter et al., 1992; Falkowski,
68
1997; Wu et al., 2000] and phosphorus [Sañudo-Wilhelmy et al., 2001] availability are
primary factors limiting nitrogen fixation in the oceans, so the presence of these metal
micronutrients in the best fit model agrees well with those studies.
Our model results also show that the lesser studied trace metal V is included as
an important variable in some of the primary productivity models. Although the
biological role for this element is not well characterized, high concentrations of V in
field-collected Trichodesmium colonies have been observed [Tovar-Sanchez and
Sañudo-Wilhelmy, 2011; Nuester et al., 2012], suggesting that V is enriched for N2-
fixing organisms.
Furthermore, employing linear regression modeling of the North East Atlantic spring
bloom, Klein et al. [2013] suggested that V might be linked to the removal of reactive
oxygen species via V-haloperoxidases and/or passive uptake as an analog of PO
4
3-
during P-limited conditions. It has also been shown that V enhances chlorophyll a
biosynthesis by stimulating the synthesis of the porphyrin precursor 6-aminolevulinic
acid (ALA), where V catalyzes the nonenzymatic transamination of 4.5-dioxovaleric
acid to ALA [Meisch and Bielig, 1975, 1980]. In addition, Meisch and Bielig [1975]
showed that V has the ability to overcome Fe deficiency in chlorophyll synthesis in
some algal cells.
69
Figure 3.10. Observed versus modeled primary productivity (PPi) for the transect from (a) South Africa
to Australia, (b) Colombia to Spain, (c) Spain to Brazil, (d) Brazil to South Africa, (e) Hawaii to
Panama, and (f) New Zealand to Hawaii. The graphed model for each transect is that with the highest
R2, lowest p value, and lowest predictive error (Table 3.1). Formulas are given for each regression.
Vertical dashed line separates different sections (see sections in Figure 3.1). Sections were determined
on the basis of distinct hydrographic and biological regimes and tested by k-means cluster analysis.
70
The results of the multivariable linear regression modeling presented here are
consistent with these previous studies, as the two transects that have V in the best fit
model (Table 3.2) also include Fe and PO4, nutrients that have the potential to limit
nitrogen fixation in the ocean [Rueter et al., 1992; Falkowski, 1997; Wu et al., 2000;
Sañudo-Wilhelmy et al., 2001]. Additionally, the inclusion of Fe in these models also
supports the findings of Meisch and Bielig [1975] that the effect of V in the
biosynthesis of chlorophyll a significantly increases in Fe-limited environments. This
result is of particular interest, as the relationship between Fe, V, and the production of
chlorophyll a in the open ocean is not well understood, meriting particular further
attention.
The presence of SiO4 in two of the best fit regression models (South Africa to
Australia, and Hawaii to Panama) (Table 3.2 and Figures 3.10a and 3.10e) suggests
that SiO4 is a nutrient that may be controlling oceanic primary productivity in these
areas of the ocean, where diatoms carry out the majority of the new production
[Dugdale and Wilkerson, 1998], thus rendering SiO4 a potential limiting nutrient. In
fact, the North Tropical Pacific has been classified as a low-silicate, high-nutrient,
low-chlorophyll a region because SiO4 concentrations are not sufficiently high to
support new production [Dugdale and Wilkerson, 1998]. Furthermore, the presence of
Cd in all the best fit models that have SiO4 as a variable (Table 3.2) agrees with
culture and field measurements suggesting that Cd becomes biologically important for
marine diatoms under conditions of low zinc [Price and Morel, 1990; Lee and Morel,
1995; Lane and Morel, 2000a, 2000b]. Although Zn levels were not determined for the
MCE samples, it has been demonstrated that low zinc conditions are typical of open
ocean environments [Bruland, 1989].
In general, the best fit models for all transects include metals other than Fe that
71
may be important bioactive elements that can potentially limit or co-limit oceanic
primary productivity. For example, it has been reported that low Co concentrations in
some regions of the world oceans limit the production of vitamin B12 by heterotrophic
and phototrophic bacteria, especially in the North Atlantic Ocean [Panzeca et al.,
2008]. The presence of Co in the best fit model for the northern section of the transect
from Spain to Brazil (Table 3.1 and Figure 3.10c) agrees well with this previous study.
Table 3.2 also shows that the metal micronutrients Ni and Mo were identified as
elements influencing primary productivity in some of the sampled regions. It is well
known that Mo plays an important role in the nitrogen cycle as a metal cofactor in
nitrogenase [Kisker et al., 1997], and at least nine Ni-containing enzymes have been
reported [Mulrooney and Hausinger, 2003]. However, gaps remain in our
understanding of the biological role of these metals in the marine environment. Our
linear regression modeling results could be used, with due caution in terms of
functional inferences, as a tool in the design of future studies exploring unknown and
potentially important roles for lesser-studied trace metals.
3.5 Conclusions
The results reported here include dissolved Co, Fe Cd, Cu, Ni, V, and Mo
distributions in surface waters of the global ocean, providing new data from
unexplored regions of the ocean as well as for some understudied metals. By
comparing our new data to previously published data sets on the distribution of trace
metals in surface waters of the Atlantic Ocean (specifically the Spain to Brazil
transect), we have explored changes in the distribution of trace metals that have
occurred in the last 30 years; for most metals, little change is observed over this time
period. Multivariable linear regression modeling was used as a tool to describe
72
relationships between primary productivity and the biogeochemical parameters
measured during the MCE.
Although caution must be taken in inferring causation from correlation models
such as those presented here, this study suggests that some trace metal nutrients may
have important biogeochemical roles by constraining, often in concert with
macronutrients, algal biomass, and primary productivity. The results presented here
point to the need of future experiments to verify a direct causal relationship between
some of the lesser studied trace elements (e.g., Ni, V, Mo, and Cd) and oceanic
primary productivity.
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80
Chapter 4
Changes in the size partitioning of
metals in storm runoff following
wildfires: implications for the
transport of bioactive trace metals
4.1 Opening Statement
As discussed in Chapters 1 and 3, the spatial distribution of trace metal
nutrients in the ocean has profound influence on phytoplankton communities.
Concentrations of many trace metals are usually higher, sometimes by orders of
magnitude, in the surface waters of coastal zones that receive terrestrial input than they
are in open-ocean waters. This reflects the inputs from two major primary external
sources, i.e. fluvial runoff and atmospheric deposition. River runoff from regions
affected by both natural wildfires and dense urbanization has been clearly identified as
a source of trace metals to receiving waters, influencing coastal ocean metal budgets.
However, most studies of fire and urban runoff have focused on identifying metal
sources, concentrations, and loadings, paying relatively little attention to metal
partitioning between the colloidal and soluble phases.
As discussed in Chapters 1 and 2, the partitioning of metals between different
size fractions affects the dynamics of metal transport, reactivity, and bioavailability.
Thus, understanding metal partitioning in runoff is a key factor in order to understand
81
the fate of elements delivered to receiving waters. To address the lack of such data,
particularly for regions burned by wildfires, the partitioning of metals between the
colloidal and soluble phases in storm-runoff was evaluated in three different settings
that are characteristic of coastal environments in Mediterranean climate: (i) a
catchment affected by the 2012 Williams Fire (September 2 – 13) in the San Gabriel
Mountains, (ii) a neighboring control catchment in the San Gabriels, and (iii) three
rivers draining the Los Angeles County area. Results from each region were compared
to each other in order to gain information about potential sources of soluble (i.e.,
bioavailable) elements that are delivered to receiving waters. Our results suggest that
storm runoff from burned landscapes has the previously unrecognized potential to
supply a greater proportion of trace elements in bioactive soluble form, compared to
runoff from urban or unburned areas, potentially increasing the impact of wildfire-
delivered metals on receiving waters and thus affecting primary productivity and
carbon export in these aquatic environments.
This chapter is the result of a collaborative effort. Bridget Hellige
collected all
the samples in the San Gabriel Mountains, monitored stream height, and analyzed the
samples from this area under my supervision. I collected and analyzed the samples
from the other sites. Again, Drs. Joshua West and Sergio Sañudo-Wilhelmy provided
valuable insights and supervision. We thank Roman DiBiase for assistance in the field.
B.H. was supported by the USC Earth Sciences Undergraduate Research
Apprenticeship Program (ESRAP). P.P.-G. was supported by the USC Earth Sciences
Graduate Student Research Fund.
This paper was submitted in February 2016 to Applied Geochemistry journal
82
4.2 Introduction
Contaminant loading associated with urban runoff contributes to the pollution
and impairment of watersheds around the world [e.g., Vaze and Chiew, 2004; Ahn et
al., 2005; Joshi and Balasubramanian, 2010]. Similar delivery of pollutants, including
suspended solids, nutrients, trace elements, and organic compounds, can occur
following wildfires [e.g., in southern California: Stein et al., 2012; Burke et al., 2013;
in Iran: Norouzi and Ramezanpour, 2013; in New Mexico: Bitner et al., 2001; in
Australia: Smith et al., 2011; in Portugal: Campos et al., 2015].
Trace metals are one of the most extensively studied categories of pollutants
due to their direct impact on the ecosystems of receiving waters, both through toxicity
and, in some cases, as required micronutrients that affect aquatic productivity [Tucillo,
2006]. Most prior studies on trace metal pollution of surface waters have focused on
identifying metal sources, concentrations, and loadings, whereas only a few have paid
attention to metal speciation and size fractionation [e.g., Grout et al., 1999; Guéguen
and Dominik, 2003; Tucillo, 2006; Brown et al., 2011, 2013]. In natural waters, the
partitioning of metals between different sizes – particulate, colloidal, and soluble –
affects the dynamics of metal transport, reactivity, and bioavailability [Gächter et al.,
1973; Kaplan et al., 1995; Laegdsmand et al., 1999; Paquin et al., 2002]. These size
fractions are generally operationally defined, with particulate metals defined as those
associated with material larger than a 0.45 or 0.2µm membrane filter, colloidal metals
in the size fraction between 0.2µm and 0.02µm, and the soluble pool comprising
metals in the <0.02µm fraction. The soluble and colloidal metals together make up the
“total dissolved” pool (i.e. all metals associated with the size fraction <0.2µm).
The distinction of colloidal- versus soluble-associated metals is important from
a water quality perspective since toxicity of trace elements depends not only on their
83
abundance but also on their bioavailability, and it is well documented that trace metals
in the colloidal phase do not posses immediate risk to many organisms [Guéguen and
Dominik, 2003; Guéguen et al., 2004; Tucillo, 2006]. It has even been suggested that
in many cases the physico-chemical forms in which metals exist are more important
for the ecosystems of receiving waters than the total metal concentrations [Tessier and
Turner, 1995].
The extent to which dissolved metals are associated with colloidal vs. soluble
fractions in natural waters depends on (i) the metal geochemistry and (ii) the nature of
the colloids, which varies in different settings. Some prior work has explored colloidal
partitioning of metals in urban runoff [Grout et al., 1999; Guéguen and Dominik,
2003; Tucillo, 2006; Brown et al., 2011, 2013]. However, there is little data on
colloidal partitioning of metals from burned landscapes, leaving a gap in
understanding how these environments act as metal pollution sources.
The primary goal of the current study was to evaluate whether dissolved metals
from urban vs. wildfire sources are associated with different partitioning between
colloidal and soluble forms. The focus is on storm runoff in Southern California,
where such partitioning data has not been reported previously. Storm runoff is a major
source of pollution to many waterways in this region, delivering contaminants from
both urban [e.g., Davis et al., 2001; Ackerman et al., 2003; Ahn et al., 2005; Rule et
al., 2006; Aryal et al., 2010; Tang et al., 2013] and burned lands [e.g., Stein et al.,
2012, Burke et al., 2013]. In this study, the partitioning of metals between the colloidal
and soluble phases in storm runoff was evaluated in three different environments: (i) a
catchment affected by the 2012 Williams Fire in the San Gabriel Mountains, (ii) a
neighboring control catchment in the San Gabriels, and (iii) three rivers draining an
urban-to-rural gradient in the Los Angeles County area. Results from each region were
84
compared to each other, focusing on how the partitioning of metals between different
size fractions differs for urban vs. wildfire settings.
Figure 4.1. Map showing approximate sample collection sites in the Los Angeles, San Gabriel, and
Santa Clara Rivers. Inset A shows a shaded elevation map (whites - high elevation; blacks- low; from an
SRTM-derived 90m digital elevation model; Reuter et al., 2007) with the approximate sample collection
sites in the San Gabriels burned catchment and the neighboring control catchment. Dashed line in Inset
A shows extent of the Williams Fire burn area (from U.S. Forest Service, unit identifier: CA-ANF, fire
number: G7L0) The sampling sites are located at: San Gabriel River – East Wardlow Rd (33˚49’08’’N,
118˚05’28’’W); Los Angeles River – West Willow St (33˚48’15’’N, 118˚12’19’’W); Santa Clara River
– South Mountain Rd (34˚20’53’’N 119˚03’05’’W); San Gabriels burned catchment (34˚14’24’’N
117˚48’27’’W); and San Gabriels unburned control catchment (34˚14’40’’N 117˚49’16’’W).
4.3 Methods
4.3.1 Study area
To study post-fire runoff chemistry, storm-water runoff was sampled from two
immediately adjacent, similar sized catchments in the San Gabriel Mountains, one
burned by the Williams Fire and the other not burned (Figure 4.1). We refer to the
Santa%Clara%River%
Los%Angeles%River%
San%Gabriel%River%
Inset%A%
Pacific%Ocean%
Inset&A&
Sampled%sites%
Sampled%site%
Sampled%sites%
5%mi%
10%Km%
SG%Burned%area%
SG%%control%watershed%
SG%%burned%watershed%
85
former as the San Gabrial Burned catchment and the latter as the San Gabriels Control
catchment. The Williams fire occurred on September 2 2012, originating at 34.239°N,
117.822°W between the Shooting Range and Camp Williams along East Fork Road in
San Gabriel Canyon [InciWeb, 2012]. The fire took 10 days to contain and burned
roughly 4,192 acres, fueled by mainly chaparral vegetation and 15-20 year old conifers
[InciWeb, 2012]. The fire stopped at the divide between the burned and control
catchments, so these two catchments share similar pre-fire land cover, geology, soils,
and climate. The bedrock in both catchments is Precambrian igneous and metamorphic
rock (Table 4.1). The primary native soil types in this area are sandy loam, silt loam,
and clay loam [Los Angeles County Department of Public Works, 2005].
For comparison to the burned-unburned catchment pair in the San Gabriels, we
also collected samples from two unburned, urban sites in the greater Los Angeles
region and a reference, non-urban site on the Santa Clara River (Figure 4.1). The two
urban storm runoff collection sites were located at the downstream end of the Los
Angeles and San Gabriel Rivers in Long Beach, California (Figure 4.1; Table 4.1). At
the sampling locations, which were chosen to avoid tidal influences, the total upstream
drainage area is 2136 and 1761 square kilometers respectively (Table 4.1; Los Angeles
County Department of Public Works). These sites drain heavily urbanized areas where
runoff from commercial, industrial, and residential land uses is conveyed through
engineered flood control channels [Stein et al., 2012; Los Angeles County Department
of Public Works]. The Santa Clara River was chosen as an additional control site to
assess the concentration and partitioning of metals associated with storm runoff from
natural areas. To ensure that the sampling site represented natural conditions without
influence from any land based anthropogenic input, the sampling location was selected
based on the criteria described in Yoon and Stein [2008] for natural catchments.
86
All of the sites in this study share similar Mediterranean climate conditions that
are characteristic of Southern California, with mostly dry summers (except for rare
summer thunderstorms) and cold, wet winters.
Figure 4.2. (a) Stage height record from 9 December 2012 to 31 January 2013 for the San Gabriels
control catchment, and (b) detailed hydrographs from individual storms that occurred on December 13,
2012 and January 24, 2013, when samples were collected (time of sample collections shown by black
dots).
4.3.2 Storm-water sampling
Storm-water runoff was collected from the San Gabriel catchment pair during
the first two storms following the Williams Fire (December, 2012 and January, 2013;
Table 4.1). Samples were collected in acid-washed 250 mL polyethylene bottles using
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
2500$ 4500$ 6500$ 8500$ 10500$ 12500$ 14500$ 16500$
Stage hight (m)
Date
0.35
0.4
0.45
0.5
0.55
0.6
3450$ 3550$ 3650$ 3750$
Stage height (m)
Time (hr)
0.3
0.35
0.4
0.45
0.5
0.55
15550$ 15650$ 15750$ 15850$
Stage height (m)
Time (hr)
12/09 12/16 12/23 12/30 1/06 1/13 1/20 1/27
$00:01$$$$$$$$$$08:00$$$$$$$$$$16:00$$$$$$$$$24:00$$
12/13/12
December 2012 – January 2013
$00:01$$$$$$$$$$$08:00$$$$$$$$$$$16:00$$$$$$$$$$24:00$$
1/24/13
87
trace-metal-clean techniques every three hours during a six- to nine-hour period in
order to capture different portions of the storm hydrograph (Figure 4.2).
Table 4.1. Characteristics of the sampling sites in this study. Stream height was
monitored in the San Gabriels catchments (e.g., Figure 4.4) but not converted to a
discharge value.
Storm runoff was collected from the urban Los Angeles and San Gabriel River
stations during five storm events (December, 2012; January, February, March, and
December 2013; Table 4.1) and from the Santa Clara River station during three storm
events (December, 2012; January, December 2013; Table 4.1) by dropping an acid-
washed 250 mL polyethylene bottle from a bridge above each selected site (Figure
4.1). Due to limiting sampling personnel and the fact that in urban watersheds
concentrations and loadings are typically higher during the early portion of storms
[Characklis and Wiesner, 1997; Tiefenthaler et al., 2008], urban runoff samples were
collected during the initial rise of the hydrograph to capture the “first flush” of metals
from land surfaces (Figure 4.3, data obtained from the Los Angeles County
Department of Public Works).
Stream'sampled
Sample'site'
latitude
Sample'site'
longitude
Sampling'
dates
Watershed'
size'(km
2
)
Plant'
community
Geology'type
Daily'mean'
discharge'(ft
3
/sec)
24Ahour'event'
rainfall'(mm)
San$Gabriels$burned$
catchment
34˚14'N 117˚48'W 12/13/2012$
01/24/2013
7.9 Burned Precambrian$igneous$and$
metamorphic$rock$
complex
N/A$$$$$$$$$$$$$$$$$$$$$$
N/A
38.35$$$$$$$$$$
26.6
San$Gabriels$control$
catchment
34˚14'N 117˚49'W 12/13/2012$
01/24/2013
5.9 Chaparral,$
brush,$mixed$
conifers
Precambrian$igneous$and$
metamorphic$rock$
complex
N/A$$$$$$$$$$$$$$$$$$$$$$
N/A
38.35$$$$$$$$$$
26.6
Santa$Clara$River 34˚20'N 119˚03'W 12/03/2012$
01/24/2013$
12/19/2013
1061 Mostly$shrub,$
some$conifer$
forest
Sedimentary,$Sandstone,$
siltstone,$shale,$and$
conglomerate
2.79$$$$$$$$$$$$$$$$$$$$$$
2.20$$$$$$$$$$$$$$$$$$$$
1.75
4.1$$$$$$$$$$$$$$$
18.8$$$$$$$$$$$$$$$
1.2
San$Gabriel$River 33˚49'N 118˚05'W 12/03/2012$
01/24/2013$
02/19/2013$
03/08/2013$
12/19/2013
1761 Minimal Concrete$and$asphalt 1533$$$$$$$$$$$$$$$$$$$$
1306$$$$$$$$$$$$$$$$$$$$$
133$$$$$$$$$$$$$$$$$$$$$$$
797$$$$$$$$$$$$$$$$$$$$$$$
324
10.6$$$$$$$$$$$$
19.0$$$$$$$$$$$$$$
3.8$$$$$$$$$$$$$$
21.1$$$$$$$$$$$$$$$$$$
6.1
Los$Angeles$River 33˚48'N 118˚12'W 12/03/2012$
01/24/2013$
02/19/2013$
03/08/2013$
12/19/2013
2136 Minimal Concrete$and$asphalt 3040$$$$$$$$$$$$$$$$$$$$$
4550$$$$$$$$$$$$$$$$$$$$$
254$$$$$$$$$$$$$$$$$$$$$$$
4570$$$$$$$$$$$$$$$$$$$$$$$
830
10.6$$$$$$$$$$$$
19.0$$$$$$$$$$$$$$$
3.8$$$$$$$$$$$$$$
21.1$$$$$$$$$$$$$$$$$
6.1
88
All samples were processed in
the field immediately after collection.
A portion of each sample was filtered
through an acid-cleaned 25mm
diameter 0.2 µm polyvinylidene
fluoride syringe filter for
measurement of the total dissolved
(<0.2 µm) trace metal concentrations.
A portion of the 0.2 µm filtrate was
further syringe-filtered through acid-
cleaned 25 mm diameter 0.02 µm
Anatop Al-oxide filters to isolate the
soluble fraction (<0.02 µm). The
difference between the total
dissolved and the soluble fraction
(that passing through a 0.02 µm
filter) is considered to be the
colloidal fraction. This approach has successfully been used to study the role of
colloidal size particles in the cycling of trace elements in open ocean and coastal
environments [Bergquist et al., 2007; Wu et al., 2001; Fujii et al., 2008; Ussher et al.,
2010; Pinedo-Gonzalez et al., 2014]. Field blanks and duplicate samples were included
in the above procedures for quality control.
Precipitation and flow data were measured on site using a pressure transducer
(WL16 Water Level Logger) deployed in the San Gabriels control catchment during
the duration of the sampling year, or were obtained from the Los Angeles County
Figure 4.3. Hydrographs for a storm event on December
3, 2012 showing times of sample collection at the San
Gabriel River (SGR) and the Los Angeles River (LAR)
sites. The examples here are representative of the
approximate sample collection time relative to
hydrograph for other samples collected from these sites
and from the Santa Clara River.
89
Department of Public Works [http://www.ladpw.org/; site F42B-R for the San Gabriel
River, F319-R for the Los Angeles River, and F92C-R for the Santa Clara River).
4.3.3 Analytical procedure
Filtrates (<0.2 and <0.02 µm) were transported to a class-100 clean room
where they were acidified using Optima grade nitric acid to pH <2. Levels of Fe, Cu,
Zn, Co, Pb, Cd, Ni, Mo and V in both the total dissolved and soluble fractions were
quantified by ICP-MS on a Thermo Element 2 HR-ICP-MS using external calibration
curves and an internal indium standard.
The procedural blank was in all cases insignificant and did not warrant
correction of the measured concentrations. Approximate limits of detection (3 standard
deviations of the blank) were (ng L
-1
): Fe 30, Cu 15, Zn 35, Co 70, Pb 10, Cd 50, Ni
60, Mo 10 and V 95. To evaluate the accuracy of our analytical procedures, a certified
seawater reference material (CASS-5) was analyzed with the samples.
The colloidal fraction was calculated as the difference between the total
dissolved (<0.2 µm) and the soluble fraction (passing through 0.02 µm filter).
4.4 Results and Discussion
4.4.1 Total dissolved concentration
Total dissolved and soluble trace metal concentrations measured in storm
runoff from the San Gabriel Mountains (control and burned catchments), urban areas
[Los Angeles and San Gabriel Rivers), and the Santa Clara River are listed in Table C1
and C2 in appendix C, and plotted in Figures 4.4 and 4.5.
The total dissolved concentrations of Cd, Co, Mo, and Ni measured in both the
Los Angeles and the San Gabriel Rivers were higher than the concentrations measured
90
in the natural areas (San Gabriel control and burned catchments, and the Santa Clara
River) (Figure 4.4). In the urban areas, the total dissolved concentrations of Cd, Co,
Mo, and Ni were approximately 6.7, 2.1, 2.5, and 4.1 times higher, respectively, than
the concentrations measured in the San Gabriels control catchment, 5.4, 2.4, 1.7, and 3
times higher, respectively, than the concentrations in the burned catchment, and 1.8,
1.8, 1.9, and 3.7 times higher, respectively, than the concentrations in the control Santa
Clara River (Figure 4.4). These results agree with previous studies showing that the
dissolved concentrations of various trace elements in runoff from urban areas are much
higher than those from natural areas [Davis et al., 2001; Yoon and Stein, 2008; Joshi et
al., 2010]. The trace metals that are found in high concentrations in urban storm runoff
originate from a variety of sources. The major sources include, among others,
automobiles, atmospheric deposition (both wet and dry), industrial activities, corroding
metal surfaces, and combustion processes [e.g., Davis et al., 2001; Rule et al., 2006;
Aryal et al., 2010; Tang et al., 2013].
For the other elements measured in this study (Fe, Cu, Zn, Pb, and V), the total
dissolved concentrations measured in the catchment affected by the Williams Fire are
comparable to those of urban landscapes. Total dissolved concentrations of Fe, Cu, Zn,
Pb, and V measured in runoff from the burned catchment, and from both the Los
Angeles and San Gabriel Rivers are significantly higher than the concentrations
measured in the San Gabriels control catchment and in the Santa Clara River (Figure
4.4). These results agree with previous studies showing that for some elements, storm
runoff from recently burned areas exhibits considerably higher concentrations
compared to natural background levels and similar contaminant-loading properties to
those of urban landscapes [Stein et al., 2012, Burke et al., 2013]. Enhanced stream
trace metal concentrations following wildfires may be attributed to the release of
91
Figure 4.4. Total dissolved (blue bars) and soluble (pink bars) concentrations of metals in storm runoff
from the San Gabriels control (SGC) and burned (SGB) catchments, the Los Angeles River (LAR), the
San Gabriel River (SGR), and the Santa Clara River (SCR). Error bars represent the mean concentration
+ standard deviation of all samples collected in this study from each site.
0"
100"
200"
300"
400"
500"
600"
700"
800"
900"
1000"
µg/L"
Fe#
Total"dissolved"
Soluble"
0"
0.2"
0.4"
0.6"
0.8"
1"
1.2"
µg/L"
Co#
0"
2"
4"
6"
8"
10"
12"
14"
16"
18"
µg/L"
Cu#
0"
2"
4"
6"
8"
10"
12"
14"
16"
µg/L"
Pb#
0"
5"
10"
15"
20"
25"
30"
35"
40"
45"
µg/L"
Zn#
0"
2"
4"
6"
8"
10"
12"
14"
µg/L"
Ni#
0"
0.1"
0.2"
0.3"
0.4"
0.5"
0.6"
0.7"
µg/L"
Cd#
0"
1"
2"
3"
4"
5"
6"
7"
8"
9"
µg/L"
V"
0"
2"
4"
6"
8"
10"
12"
14"
µg/L"
Mo#
!SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR! !SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR!
!SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR! !SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR!
!SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR! !SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR!
!SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR! !SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR!
!SGC!!!!!!!!SGB!!!!!!!!LAR!!!!!!!!SGR!!!!!!!SCR!
92
metals from vegetation and soil surfaces by the combustion of organic matter and its
subsequent mobilization and transport during post-fire storms [Ulery et al., 1993;
Pereira and Úbeda, 2010].
Table 4.2 presents a comparison of trace metal concentrations collected in this
study relative to those from other studies reported in the literature. This comparison
shows that the range of total dissolved Cd, Pb, Fe, Ni, Cu, and Zn concentrations
measured in this study for samples collected in unburned natural areas (the San
Gabriels control catchment and the Santa Clara River) is lower than those measured by
Stein et al. [2012] and Burke et al. [2013] and within the range reported by Yoon and
Stein [2008]. Although the four sets of samples were all collected in natural
catchments in Southern California, samples collected by Stein et al. [2012] and Burke
et al. [2013] were not filtered, explaining why they display higher trace metal
concentrations, especially for elements associated with particulate matter such as Fe
and Pb.
In the case of runoff from the burned site, the concentrations of Cd, Pb, Fe, Ni,
Cu, Zn and V were lower in the present study than those reported by Stein et al. [2012]
and Burke et al. [2013] for post-fire storm runoff from five wildfire areas in Southern
California, and within the range of those reported by Gallaher and Koch [2004] for
samples collected after the Cerro Grande fire in New Mexico. Again in this case, the
higher concentrations reported by Stein et al. [2012] and Burke et al. [2013] may be
attributed to the fact that water samples in these two studies were not filtered before
analyzing their trace metal contents, while the samples collected by Gallaher and Koch
[2004] were filtered similarly to those in this study.
93
µg/L
Joshi*et*
al.*(2010)
Davis*et*al.*
(2001)
Rule*et*al.*
(2006)
Barret*et*al.*
(1998)
Ackerman*et*al.*
(2003)
Yoon*and*Stein*
(2008)
Gallaher*and*
Koch,*(2004)
Metal Narural Burned Urban Urban Urban Urban urban natural urban burned natural natural burned burned
Cd 0.0753430.29 0.09 0.43430.5 0.113430.470.123431.30.093430.33 0.143(0.083430.24) 0.0053430.017 0.173430.56 0.263(0.0634322)
Pb 0.193431.1 11 4.83435.7 1.063436.63 1.534362 4.734316 3.034353 <10 0.513(0.243431.06) 0.13431.33 31.6343177 0.793(0.05534377)
Fe 7334104 750 461343577 113343521 2493432824 200343540 9623(4003432313) 563431000 560034317000 3983(293439240)
Ni 1.93432.1 2.7 7.73438.4 0.993434.71 <20 1.033(0.433432.4) 0.743432.37 3.1634317 2.553(0.4634321)
Cu 2.43433.2 11 10.534314.912.434319.27.5343200 11.834357 7.0437 10.034311.0 1.53(0.753433.17) 43.5 62.5 6.2 1.773435.62 1734350 5.393(0.5534370)
Zn 10.434313 32 2934336 52.23432391003431100 23343141 24343222 10.034340.0 5.323(2.5434311) 220 300 20 4.2134317 31.6343177 14.63(0.633432600)
V 1.73433.9 5 5.93436.5 2.073434.46 5.383(0.934317)
Stein*et*al.*(2012) Burke*et*al.,*(2013) This*study
Table 4.2. Concentrations of trace metals (µg L
-1
) from urban,
burned and natural runoff measured in this study relative to other
studies reported in the literature.
94
Figure 4.5. Percentage of soluble metals in storm runoff from the San Gabriels control and burned
catchments, the Los Angeles River (LAR), the San Gabriel River (SGR) and the Santa Clara River
(SCR). Both San Gabriel catchments (control and burned) were sampled 3 times during two storm
events. Samples from the Los Angeles and San Gabriel Rivers were collected during five different storm
events (one sample per storm). Samples from the Santa Clara River were collected during three different
storm events.
80#
85#
90#
95#
100#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Mo"
75#
80#
85#
90#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Cd"
0"
10"
20"
30"
40"
50"
60"
70"
1" 2" 3" 4" 5" 6" 7"
%"Soluble"
Pb"
85#
90#
95#
100#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
V"
0"
5"
10"
15"
20"
25"
30"
1" 2" 3" 4" 5" 6" 7"
%"Soluble"
Fe"
85#
90#
95#
100#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Co"
70#
75#
80#
85#
90#
95#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Ni"
65#
70#
75#
80#
85#
90#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Cu"
80#
85#
90#
95#
100#
1# 2# 3# 4# 5# 6# 7#
%"Soluble"
Zn"
Storm&1& Storm&2&
SG#Control#
SG#Burned#
LAR& SGR& SCR& Storm&1& Storm&2& Storm&1& Storm&2& LAR& SGR& SCR& Storm&1&Storm&2&
Storm&1& Storm&2& LAR& SGR& SCR& Storm&1& Storm&2& Storm&1& Storm&2& LAR& SGR& SCR& Storm&1&Storm&2&
Storm&1& Storm&2& LAR& SGR& SCR& Storm&1& Storm&2& Storm&1& Storm&2& LAR& SGR& SCR& Storm&1&Storm&2&
Storm&1& Storm&2& LAR& SGR& SCR& Storm&1& Storm&2& Storm&1& Storm&2& LAR& SGR& SCR& Storm&1&Storm&2&
Storm&1& Storm&2& LAR& SGR& SCR& Storm&1&Storm&2&
95
Urban runoff concentrations of Cd, Pb, Fe, Ni, Cu, Zn, and V measured in this
study are within the range of those reported by Joshi et al. [2010], Davis et al. [2001],
Rule et al [2006], Barrett et al. [1998], Ackerman et al. [2003], and Stein et al. [2012].
Although the concentrations of trace elements in urban storm runoff can vary
significantly depending on the nature and intensity of human activities, there is not a
significant difference in the concentrations of trace metals in runoff from the different
urban areas reported in Table 4.2. This similarity may be attributed to the fact that
relatively large quantities and numerous kinds of trace metals are inherent in
commercial, industrial and high-density residential areas.
4.4.2 Partitioning
While the total dissolved metal concentrations measured in runoff from the
burned and urban areas are similar for some elements (i.e. Fe, Co, Cu, Pb, Zn, and V),
their size partitioning is different, and these differences could lead to distinct
environmental impacts. The percentage of soluble metals in storm runoff from the
natural, burned and urban areas at each sampling time is plotted in Figure 4.5. The
partitioning of trace metals between the colloidal and soluble phases did not exhibit
systematic variations over time during the sampling period for samples from any
individual site (e.g., for samples collected at different times from the Los Angeles
River site). This suggests that the differences in the size partitioning of metals reported
in this study are not an artifact of the time when samples were collected, i.e.,
differences between sites as discussed below are larger than differences between
different sampling times.
The contribution of soluble and colloidal metals to the total dissolved metal
concentration for selected trace elements in natural, post-fire and urban runoff is
shown in Figure 4.6. The colloidal and soluble fractions have different weighting for
96
different trace elements and environments. The soluble fraction was dominant for Mo
(88-94%), Cd (82-86%), V (91-98%), Co (91-95%), Ni (79-91%), Cu (76-85%), and
Zn (89-95%) in runoff from natural, burned and urban environments (Figures 4.5 and
4.6). These results are consistent with previous studies that have used ultrafiltration to
separate colloids and associated trace elements, reporting that Mo, Cd, Co, and Ni
reside primarily in the soluble phases [Guéguen and Dominik, 2003, Sañudo-
Wilhelmy et al., 1996; Hassellöv et al., 1999; Wen et al., 1999]. For the more particle-
reactive metals Fe and Pb, the distribution between the colloidal and soluble fractions
showed notable differences between storm runoff from the burned catchment and from
both the natural and urban areas (Figure 4.6). While the colloidal fraction was
dominant in storm runoff from the natural (92-94% and 87-97%, respectively) and
urban (94-97% and 83-84%, respectively) areas, the contribution of colloidal Fe and
Pb to the total dissolved pool was lower in storm runoff from the burned catchment
(76% and 42%, respectively) (Figure 4.6). These results provide an initial indication
that fires may affect size partitioning, specifically enhancing the soluble association of
some metals at least under some circumstances. This observation merits further testing
in future studies, as well as more investigation to understand the causative
mechanisms.
A plausible mechanism may be the effect of fires on soil organic material.
When organic matter content is high, the mobility and availability of metals in soil are
generally low [Yoon et al., 2006]. In recently burned areas, however, combustion of
organic carbon and higher soil pH increase the mobility and concentrations of both
total and bioavailable fractions of some metals [Gallaher and Koch, 2004; De Marco et
al., 2005; Warrick et al., 2012; Norouzi and Ramezanpour, 2013]. Although data on
the size of residual organic matter following wildfires are lacking, numerous organic
97
compounds are produced during wildfires due to the incomplete oxidation of biomass
[Almendros et al., 1990; González-Pérez et al., 2004]. It has also been suggested that
the high temperatures generated by wildfires have the potential to chemically reduce
metal constituents [Gallaher and Koch, 2004]. We suggest that these processes may
conspire to produce small organic molecules (soluble ligands) capable of complexing
free, reduced metals (e.g., Fe and Pb). As a result, wildfires could modify trace metal
fractionation between the colloidal and soluble phases, explaining our observations of
relatively high fractions of soluble Fe and Pb in the San Gabriels burned catchment.
Fire-driven changes in metal size partitioning may affect trace metal transport,
bioavailability, and final fate in receiving waters, emphasizing the importance of
further testing and better understanding the observations from this study. Metals bound
to particles and colloids are quickly incorporated into the sediments through
gravitational settling, facilitated by processes such as colloidal coagulation caused by
salinity changes in coastal waters [Guéguen and Dominik, 2003; Lead and Wilkinson,
2006; Tercier Waeber et al., 2012]. Thus, despite the high metal concentrations in
these larger size fractions, their direct bioavailability may be limited. In contrast,
soluble metals (<0.02µm) have a longer residence time in water, may be transported
over long distances [Guéguen and Dominik, 2003; Tercier Waeber et al., 2012], and
are often readily bioavailable [Campbell et al., 2002; Wilkinson and Buffle, 2004].
Thus, although the total contribution of metals in the soluble phase is small, it may
have a disproportionate influence on the quality of receiving waters.
98
Figure 4.6. Pie charts displaying the mean colloidal (dark green) and soluble (light green) fractions that
make up the total dissolved metal concentration from the San Gabriels control (SGC) and burned (SGB)
catchments, the Los Angeles River (LAR), the San Gabriel River (SGR) and the Santa Clara River
(SCR).
Co#
Cu#
Pb#
Zn#
Ni#
Cd#
V#
Fe#
SGC# SGB# LAR# SGR# SCR#
92%$
8%$
76%$
24%$
94%$
6%$
93%$
7%$
3%$
97%$
94%$
6%$
95%$
5%$
94%$
6%$
91%$
9%$
92%$
8%$
76%$
24%$
85%$
15%$
21%$
79%$
81%$
19%$
23%$
77%$
90%$
10%$
58%$
42%$
84%$
16%$
83%$
17%$
87%$
13%$
91%$
9%$
95%$
5%$
91%$
9%$
90%$
10%$
89%$
11%$
90%$
10%$
21%$
79%$
81%$
19%$
80%$
20%$
84%$
16%$
84%$
16%$
85%$
15%$
83%$
17%$
83%$
17%$
86%$
14%$
94%$
6%$
93%$
7%$
91%$
9%$
95%$
5%$
2%$
98%$
94%$
6%$
93%$
7%$
91%$
9%$
90%$
10%$
88%$
12%$
Mo#
99
Previous studies have also demonstrated a connection between wildfires and
enhanced oceanic primary productivity [Spencer and Hauer, 1991; Planas et al., 2000;
Abram et al., 2003]. Fires influence the supply of macro- and micro-nutrients via two
routes: (i) aerosol inputs via the atmosphere, and (ii) increased delivery via rivers.
Atmospheric deposition is the most important source of nutrients for open ocean sites,
whereas riverine runoff dominates near-shore nutrient fluxes. Although most studies of
fire effects on marine biogeochemistry have focused on the delivery of nutrients to the
ocean via atmospheric deposition from fire-born aerosols [e.g., Abram et al., 2003;
Gao et al., 2003; Guieu et al., 2005; Ito, 2011], our results show that post-fire runoff
has the potential to supply a greater proportion of trace elements in bioactive soluble
form, compared to runoff from unburned (natural or urban) areas, potentially
increasing the impact of wildfire-delivered metals on receiving waters and thus
affecting ecosystems in these aquatic environments.
4.5 Conclusions
Dissolved concentrations and size fractionation of trace metals in storm runoff
from three different environments in southern California were investigated. It was
found that concentrations of Fe, Cu, Pb, V, and Zn in a recently burned catchment in
the San Gabriel Mountains were similar to those in the urban rivers and higher than in
unburned natural areas. Concentrations of Cd, Co, Ni, and Mo in urban rivers (Los
Angeles and the San Gabriel Rivers) were significantly higher than the concentrations
measured in natural areas (both burned and unburned). These results confirm the
importance of wildfires and subsequent rainfall in the mobilization of some but not all
trace elements in the environment.
100
In general, the contribution of soluble metals to the total dissolved metal
concentration in storm runoff from burned landscapes is higher than that from urban
and natural areas, especially for the particle reactive metals Fe and Pb. This largely
unexplored source of bioavailable metals may have important implications for the
biogeochemistry of receiving waters, through the supply of elements that can enhance
(e.g., Fe, Zn) or inhibit (e.g., Cu, Pb) biological activity.
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106
Chapter 5
Assessment of dissolved Pb
concentration and isotopic
composition in surface waters
of the modern global ocean
5.1 Opening Statement
Surface water samples collected during the Malaspina 2010 Circumnavigation
Expedition provided an opportunity to map the distribution of seven bioactive trace
metals in the world’s ocean (as reported in Chapter 2). Following the same logic and
taking further advantage of our unique sample set of global surface waters, the
distribution of Pb and Pb isotopes is discussed in this chapter. This dataset provides the
opportunity to assess the impact of anthropogenic Pb inputs to the ocean and the
relative importance of various Pb sources, providing new insights into the transport
and fate of Pb in the modern ocean.
This chapter, like all other chapters in this dissertation, would not have been
possible without the support and encouragement of my two advisors Drs. Joshua West
and Sergio Sañudo-Wilhelmy. I thank Dr. Carlos Rivera-Duarte and the rest of the
Malaspina 2010 Circumnavigation Expedition team for sample collection and for
sharing general cruise data, as detailed in the opening statement of Chapter 2.
107
This research was funded by the Spanish Ministry of Economy and Competitiveness
through the Malaspina 2010 Expedition project (Consolider-Ingenio 2010, CSD2008-
00077).
5.2 Introduction
Lead (Pb) is a natural constituent of the Earth’s crust that is commonly found
in soils, plants, and even in oligotrophic surface waters at trace metal levels. For the
past two centuries, however, anthropogenic Pb emissions to the atmosphere mainly
from leaded gasoline combustion and high-temperature industrial activities (e.g. coal
burning, cement production, smelting of Pb and other metals) have dominated over
natural Pb emissions (Nriagu, 1979). Global natural Pb emissions are estimated to be 2
x 10
6
kg/year (Adriano, 2001) while anthropogenic Pb emissions are about 200 times
greater (400 x 10
6
kg/year) (Adriano, 2001). Spatial and temporal variability of Pb
fluxes to the surface ocean has been studied directly from seawater measurements (e.g.
Schaule and Patterson, 1981; Boyle et al., 1986; Boyle et al., 2005) as well as
indirectly from Pb measurements in corals (Lee et al., 2014; Kelly et al., 2009;
Desenfant et al., 2006; Inoue et al., 2006), and sediments (Trefry et al., 1985; Véron et
al., 1987; Hamelin et al., 1990). In general, these previous studies have shown that in
surface waters of some oceanic basins such as the Atlantic Ocean, the concentration of
Pb increased rapidly with the onset of the industrial revolution and the combustion of
leaded gasoline (Shotyk et al., 1998; Shen and Boyle, 1988; Wu and Boyle, 1997),
decreasing quickly after the phase-out of leaded gasoline in North America and Europe
in the late 1970s and early 1980s. More recent studies have shown that, contrary to the
108
decreasing trend found in surface waters of the Atlantic Ocean, Pb concentrations have
increased in other ocean basins like the North Pacific (Gallon et al., 2011) and Indian
Ocean (Echegoyen et al., 2014) due to the intensification of industrial activities in
Asia.
In addition to increasing the concentration of Pb in the ocean, anthropogenic
inputs have also modified the stable Pb isotopic composition of seawater. Many
different types of ore deposits and anthropogenic sources of Pb have distinct isotopic
signatures that depend on when and where the ore was formed. Furthermore, the
composition of Pb is not affected by physical or chemical fractionation processes, so
since each source of Pb has its own isotopic signature, it is possible to identify the
source of Pb by matching the Pb isotopic composition of seawater with that of the
potential sources. In addition, source apportionment can be quantified in cases where
all potential sources of Pb are characterized. Therefore, the combination of Pb
concentrations and unique Pb isotopic signatures provides a powerful tool for
interpreting changes in anthropogenic Pb inputs and sources to oceanic surface waters,
as well as investigating ocean-mixing rates.
Although in the last three decades significant advances have been made in
documenting the Pb distribution and isotopic composition of oceanic waters
(e.g.Flegal et al., 1984; Shen and Boyle, 1988; Veron et al., 1994; Wu et al., 2010), our
understanding on the transport and sources of anthropogenic Pb to the ocean is still
very limited due to the lack of data from many different oceanic regions. So far, Pb
and its isotopes have been mostly studied in the North Atlantic Ocean and only
109
recently, modern data from the North Pacific and North Indian Ocean has become
available (e.g. Gallon et al., 2011; Lee et al., 2015). Therefore, surface water samples
collected during the Malaspina 2010 Circumnavigation Expedition (MCE) provide an
opportunity to further advance the study of the concentrations and isotopic
composition of Pb in surface waters of all major oceanic oligotrophic regions. The
main objective of the study is to determine the levels of Pb and their isotopic
composition in surface waters collected in different oceanic basins during the MCE.
These measurements allow us to estimate current levels of this trace element in the
surface ocean as well as to establish concentration declines associated to reductions in
Pb emissions. The geographical gradients in Pb isotopic composition allow us to
identify potential sources of Pb to the different oceanic basins sampled during the
MCE.
5.3 Materials and methods
5.3.1 Malaspina Circumnavigation Expedition
Surface water samples were collected during the MCE aboard the R/V
Hespérides from December 2010 to July 2011 (Figure 5.1 and Table D1 in the
supporting information). The MCE consisted of six oceanic transects: a meridional
transect from Cadiz, Spain, to Rio de Janeiro, Brazil, (Stations 37–54) from December
2010 to January 2011, a transect from Brazil to Cape Town, South Africa, (Station 55–
69) from January to February 2011, a transect in the Indian Ocean from South Africa
110
to Perth, Australia, (Station 1–18) from February to March 2011, two transects in the
Pacific Ocean, from Auckland, New Zealand, to Honolulu, Hawaii, (Stations 70–86)
from April to May 2011 and from Hawaii to Panama (Station 87 to 110) from May to
June 2011, and a final transect back to Spain across the subtropical Atlantic, from
Cartagena de Indias, Colombia to Cartagena, Spain (Stations 19 to 36) from June to
July 2011.
Figure 5.1. Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb
ratios in the global ocean.
Concentration
pM
206
Pb/
207
Pb
208
Pb/
206
Pb
111
5.3.2 Collection and analysis of samples for Pb and Pb isotopes
Samples were collected using a teflon tow-fish sampling system deployed at
approximately 3m depth utilizing established trace metal-clean techniques (e.g.,
Bruland et al., 2005; Berger et al., 2008). After sample collection, seawater was
filtered on board through acid-washed 0.2 µm filter cartridges and acidified using
Optima grade HCl to a pH<2. Dissolved samples (<0.2 µm) were double bagged in
polyethylene bags and shipped to the trace metal clean laboratories at the University of
Southern California in Los Angeles, where they were preconcentrated using the
technique described in Bruland et al. (1985).
Levels of Pb were quantified by high-resolution inductively coupled plasma
mass spectrometry (HR-ICP-MS) on a Thermo Element 2 HR-ICP-MS, using external
calibration curves and an internal indium standard. To evaluate the accuracy of our
analytical procedure, a certified seawater reference material (SRM) (CASS-5) was
preconcentrated and analyzed with the samples. The recovery of the SRM was 90% of
the certified concentration as shown in Table D2 in appendix D.
Lead isotopes (
206
Pb,
207
Pb, and
208
Pb) of the samples were measured using a
HR-ICP-MS (Thermo Element 2). Analyses were calibrated with concurrent
measurements of NIST SRM 981 Common Lead Isotopic Standard. Replicate analyses
of the samples (n = 3) produced data within <2 permil of the average value for
206
Pb/
207
Pb, and
208
Pb/
206
Pb.
112
5.4 Results
The MCE consisted of six oceanic transects, one in the Indian Ocean, two in
the Pacific Ocean and three in the Atlantic Ocean (Figure 5.1). The distribution of
dissolved Pb and Pb isotopes is presented in Figures 5.1 – 5.4 and Table D1. Because
distinct physicochemical processes influence each ocean basin, Pb concentrations and
Pb isotopic composition are described separately for each region and/or transect.
Hydrographic data were reported and discussed elsewhere (Pinedo-Gonzalez et al.,
2015).
5.4.1 Surface distributions of Pb
5.4.1.1 Surface distribution of Pb in the Global Ocean
Lead concentrations in surface waters of the global ocean ranged from 10pM to
49pM (Figure 5.1). The highest concentrations were found in the north Atlantic close
to Europe. However, the median Pb concentration for this basin (21pM) is similar to
that of the Pacific (24pM) and Indian (21pM) oceans. The lowest concentrations were
found in the southern hemisphere close to New Zealand and in the South Atlantic. This
geographical distribution is not surprising because historically, Pb concentrations in
the northern hemisphere have always being higher due to the larger number of
industrialized countries surrounding these ocean basins. It is noteworthy that Pb
concentrations measured in the samples collected during the MCE are in the order of
tens of picomol L
-1
, while in the past, when leaded gasoline was intensively used,
typical concentrations measured in surface waters of the central ocean gyres were
113
about an order of magnitude higher (e.g. 160pM in the North Atlantic Ocean, Schaule
and Patterson, 1983; 65pM North Pacific Ocean, Schaule and Patterson, 1981; Flegal
et al., 1984).
5.4.1.2 Surface distribution of Pb in the Indian Ocean
Lead data (concentrations and isotopic ratios) from the Indian Ocean are very
scarce, especially in the south subtropical zone, a region with relatively complex
circulation forced by the seasonal reversal of the dominant wind system (Longhurst,
1998). The MCE transect covered from South Africa to Western Australia. Samples
were taken during the second half of the austral summer, during the pre-monsoon
period (February-March; reference).
Dissolved Pb concentrations ranged from 17pM to 37pM with a median of
21pM in the Indian Ocean. The highest concentrations were found near coastal zones,
especially in the eastern side of the transect (Figure 5.2). Away from the coastal zones,
in the subtropical gyre (between 60 and 105˚E) the concentration of Pb ranged
between 17 and 22pM. Dissolved Pb concentrations measured in the Indian Ocean
during the MCE are similar to those measured in surface waters of the western Indian
Ocean at about 31˚S (21pM; Echegoyen et al., 2015).
114
Figure 5.2. Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb
ratios in the Indian Ocean.
Concentration (pM)
206
Pb/
207
Pb
208
Pb/
206
Pb
115
5.4.1.3 Surface distribution of Pb in the Atlantic Ocean
Figure 5.3. Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb
ratios in the Atlantic Ocean.
Concentration
pM
206
Pb/
207
Pb
208
Pb/
206
Pb
116
With respect to Pb, the Atlantic Ocean is perhaps the best-studied ocean basin
in the world, particularly in the case of the North Atlantic. This ocean basin was
historically the most heavily impacted by early industrializing economies, receiving a
large atmospheric flux of Pb during the last several decades from industrial activities
and leaded gasoline utilization in the US and Europe. Many studies have documented
the spatial and temporal variability of Pb in the North Atlantic Ocean (e.g. Schaule and
Patterson, 1983; Boyle et al., 1986; Shen and Boyle, 1988; Helmers et al., 1991; Veron
et al., 1994; Kelly et al., 2009; Desfenant et al., 2006). In comparison, relatively little
is known about the regional distribution of Pb in the South Atlantic (e.g. Muñoz et al,
2004; Alleman et al., 2001). Therefore, samples collected during the MCE provide an
excellent opportunity to build on the work of previous oceanographic campaigns and
improve our understanding of some understudied areas of the Atlantic Ocean.
The Atlantic Ocean sampling campaign was divided into three transects:
Colombia to Spain (June–July 2011), Spain to Brazil (December 2010–January 2011),
and Brazil to South Africa (January-February 2011) (Figure 5.3).
Dissolved Pb levels along the longitudinal transect that started in Cartagena the
Indias, Colombia and ended in Cartagena, Spain ranged from 19pM to 41pM with a
median of 25pM. The highest concentrations were found in the northern part of the
transect close to Spain, probably due to the input of Pb aerosols from the Trade winds
which carry European Aerosols (Hamelin et al., 1989, 1990). However, even the
highest concentrations found in this region of the Atlantic Ocean are significantly
117
lower than those observed in previous decades when surface concentrations in this
basin exceeded 150pM (Schaule and Patterson, 1981; Kelly el al., 2009).
Dissolved Pb concentrations along the transect from Spain to Brazil exhibit a
strong latitudinal gradient, with concentrations decreasing from 49pM close to the
coast of Spain to 17pM in the southern hemisphere close to Brazil (Figure 5.3). This
gradient corresponds to the different Pb inputs along the transect. In the northern part,
European aerosols carried by the Trade winds may explain the high concentrations
observed close to the Spanish coast. The high concentrations observed between 0˚and
25˚N may be explained by aeolian inputs of mineral dust from the Sahel. Chiapello et
al. (1997) showed that during the winter (MCE samples were collected in December
and January) the low altitude Trade winds deposit large quantities of dust in surface
waters of the Eastern Atlantic. Finally, below the equator, Pb concentrations drop
down to <20pM.
Lead levels along the longitudinal transect from Brazil to South Africa are the
lowest Pb concentrations measured in the Atlantic Ocean during the MCE (median:
14pM), with concentrations ranging from 20pM close to the eastern and western
margins to 10pm in the oligotrophic gyre. The low Pb concentrations measured in the
southern Atlantic Ocean are probably due to both the lower Pb emissions emitted by
the countries surrounding the basin and the low dust inputs relative to the north
Atlantic.
118
5.4.1.4 Surface distribution of Pb in the Pacific Ocean
In 1981, Schaule and Patterson (1981) obtained the first oceanic Pb data on
samples collected near Hawaii. Since then, accurate data on the distribution of Pb in
surface waters of the Pacific Ocean have been generated (e.g. Nürnberg et al., 1983;
Flegal et al., 1984; Flegal and Patterson, 1983; Boyle et al., 2005; Gallon et al., 2012;
Wu et al., 2010). However, due to the large extent of this ocean basin, it is not
surprising that many areas of the Pacific Ocean remain understudied or have not been
studied at all. For example, only three studies reporting Pb concentrations in waters of
the South Pacific have been published to date (Flegal and Patterson, 1983; Flegal et al.,
1984; Wu et al., 2010). Dissolved Pb concentrations measured during the MCE
provide a new data set that contributes to this limited pool of studies, improving our
understanding of the distribution of Pb in the Pacific Ocean. Samples were collected
along two transects in the Pacific Ocean: from Auckland, New Zealand to Honolulu,
Hawaii (April-may 2011) and from Hawaii to Panama (May-June 2011).
Dissolved Pb levels in surface waters of the Pacific Ocean ranged from 13 to
34pM with a median of 25pM. The highest values were found in the stations close to
the Hawaiian Islands and South America (Figure 5.4). The enriched concentrations in
the area close to Hawaii are probably due to the influence of aeolian inputs of
industrial lead from Mainland China. This hypothesis is supported by the isentropic air
mass trajectories in this area of the Pacific Ocean (Merrill, 1989).
Lead concentrations along the transect from NZ to Hawaii exhibit a strong
latitudinal gradient, with concentrations increasing from around 13pM to 31pM close
119
to Hawaii (Figure 5.4). This gradient corresponds to the dispersion of Asian
anthropogenic Pb emissions to the atmosphere that are highest within the mid-latitudes
of the northern hemisphere and the subsequent transport of these Pb emissions across
the North Pacific by prevailing Westerlies (Schaule and Patterson, 1981). Lead
concentrations of 14 – 17pM measured in the South Pacific at 14˚-19˚S (Figure 5.4)
correspond to pre-industrial surface water Pb concentrations of 16 – 19pM inferred
from measurements of corals from Fiji (Shen and Boyle, 1987), implying that Pb
concentrations in this area of the Pacific Ocean have returned to natural pre-industrial
levels.
Lead concentrations along the Hawaii to Panama transect ranged from 17pM to
34pM with a median of 25pM. The highest concentrations were found in both the east
(34pM) and west (30pM) sides of the transect, while the median Pb concentration in
the middle of the transect was 21pM (Figure 5.4). This trend suggests the influence of
Asian aeolian inputs to the west and American inputs to the east (Merrill, 1989).
5.4.2. Surface distribution of Pb isotopes
Similar to Pb concentrations, Pb isotopes varied spatially in surface waters of
the world’s ocean (Figures 5.1 – 5.4).
Global
206
Pb/
207
Pb ratios ranged from 1.134 to 1.184 and
208
Pb/
206
Pb ratios
ranged from 2.071 to 2.111 (Figure 5.1). The highest
206
Pb/
207
Pb ratios were found in
the northwestern Atlantic Ocean, while the lowest ratios were found in the Indian
Ocean (Figure 5.1). The highest
208
Pb/
206
Pb ratios were found in the Indian Ocean
120
close to the Australian coast and the lowest
208
Pb/
206
Pb ratios in the north Atlantic and
the northeastern Pacific Ocean (Figure 5.1).
5.4.2.1 Surface distribution of Pb isotopes in the Indian Ocean
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios in surface waters of the Indian Ocean ranged
from 1.134 to 1.150 and 2.110 to 2.127, respectively (Figure 5.2). These ratios are
similar to recent measurements of Pb isotopic composition in surface waters of the
Southwestern Indian Ocean (
206
Pb/
207
Pb ratios 1.1398 to1.1502;
208
Pb/
206
Pb ratios
2.1114 to 2.1221) (Lee et al., 2015). Lead isotope ratios of a coral collected in the
equatorial Indian Ocean in 1990 (5˚15.8’S, 71˚45.3’E) showed
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios of 1.153 and 2.094 respectively, (Lee et al., 2014). These isotopic
ratios are significantly different than those measured in the MCE samples, indicating
that the main source of Pb affecting both regions might be different.
The overall distribution of
206
Pb/
207
Pb ratios is inversely proportional to Pb
concentrations, with the lowest
206
Pb/
207
Pb ratios appearing in waters with elevated Pb
concentrations (Figure 5.2), indicating larger anthropogenic Pb inputs to the eastern
part of the Indian Ocean compared to the rest of this basin. This conclusion is
supported by measurements of urban aerosols collected in the countries that surround
the Indian Ocean showing that Pb emitted by these countries have lower Pb isotope
ratios than natural Pb (Bollhöfer and Rosman, 2000, 2001).
121
5.4.2.2 Surface distribution of Pb isotopes in the Atlantic Ocean
Lead isotopic ratios of surface waters of the Atlantic Ocean ranged from 1.161
to 1.184 for
206
Pb/
207
Pb with a median of 1.178 and from 2.071 to 2.102 for
208
Pb/
206
Pb
with a median of 2.081 (Figure 5.3). Along the transect from Colombia to Spain,
208
Pb/
206
Pb isotope ratios increase toward the east from 2.071 to 2.093 while the
206
Pb/
207
Pb ratios decrease from 1.184 to 1.173 (Figure 5.3). The observed trend in this
transect toward lower
206
Pb/
207
Pb ratios close to Europe may be caused by the increase
in the relative inputs of European-derived Pb relative to US-derived Pb. Aerosols from
Western Europe generally exhibit lower values (1.10 – 1.16) than US aerosols (1.16 –
1.22) (Bollhöfer and Rosman, 2000, 2001; Noble et al., 2015).
206
Pb/
207
Pb isotope ratios along the transect from Spain to Brazil ranged from
1.172 to 1.176 with the exception of samples collected close to the coast of Africa,
which showed higher values of about 1.181.
208
Pb/
206
Pb ratios showed the same
variability, with ratios ranging from approximately 2.077 in the southern part of the
transect to 2.085 close to the coast of Africa and then increasing again to 2.095 close
to Europe (Figure 5.3). The
206
Pb/
207
Pb and
208
Pb/
206
Pb range found in our northern
MCE samples along this transect is within the range of surface water samples reported
by Noble et al. (2015) for samples collected in 2010 along a more northward transect
(
206
Pb/
207
Pb = 1.172-1.192;
208
Pb/
206
Pb = 2.063-2.089).
122
Figure 5.4. Map of sampling stations and the distribution of dissolved Pb,
206
Pb/
207
Pb, and
208
Pb/
206
Pb
ratios in the Pacific Ocean.
Concentration
pM
206
Pb/
207
Pb
208
Pb/
206
Pb
123
206
Pb/
207
Pb ratios along the longitudinal transect from Brazil to South Africa
decreased from 1.179 in the west side of the transect to 1.161 in the east side close to
South Africa, while
208
Pb/
206
Pb increased from 2.076 to 2.102 (Figure 5.3). The overall
distribution of Pb isotope ratios observed in this transect agrees well with both the air
mass trajectories (Veron et al., 1992) and the isotopic composition of aerosols from
South America (
206
Pb/
207
Pb = 1.12 – 1.18) and anthropogenic aerosols emitted by
South Africa, with lower
206
Pb/
207
Pb ratios than natural Pb (
206
Pb/
207
Pb = 1.06 – 1.08)
(Bollhöfer and Rosman, 2000, 2001).
5.4.2.3 Surface distribution of Pb isotopes in the Pacific Ocean
Lead isotopic ratios of surface waters of the Pacific Ocean ranged from 1.156
to 1.174 for
206
Pb/
207
Pb and from 2.082 to 2.111 for
208
Pb/
206
Pb (Figure 5.4). Although
Pb isotopic composition data in surface waters of the central tropical and subtropical
Pacific are very scarce, the Pb isotopic ratios measured during the MCE are similar to
other recent measurements of Pb isotopic compositions in the central Pacific Ocean.
For example, isotopic ratios (
206
Pb/
207
Pb = 1.164-1.167;
208
Pb/
206
Pb = 2.095-2.097) of
surface water collected during the MCE near Hawaii are similar to those of surface
water samples collected in the North Pacific (30˚N, 140˚W) in 2004 (
206
Pb/
207
Pb =
1.159;
208
Pb/
206
Pb = 2.114) (Wu et al., 2010) and 2011 (
206
Pb/
207
Pb = 1.164-1.169;
208
Pb/
206
Pb = 2.093-2.103) (Gallon et al., 2011).
124
206
Pb/
207
Pb ratios increase eastwards along the Hawaii to Panama transect and
northwards along the New Zealand to Hawaii transect. The area that extends from the
equator to the vicinity of the Hawaiian Islands has a very uniform
206
Pb/
207
Pb and
208
Pb/
206
Pb isotopic composition of about 1.165 and 2.095 respectively (Figure 5.4).
The homogeneity of isotopic ratios in this area of the Pacific Ocean suggests a
common Pb source that influence a large region of the ocean basin. Based on the
elevated Pb concentrations measured in our samples collected in this transect (Figure
5.4), the isentropic air mass trajectories (Merrill, 1989), and the typical Pb isotopic
composition of Asian aerosols (Bollhöfer and Rosman, 2000, 2001), we can infer that
industrial aerosols from Asia are the most likely source of Pb to this area of the Pacific
Ocean.
In the southern hemisphere and the area close to South America, the isotopic
composition is very different (
206
Pb/
207
Pb = 1.160;
208
Pb/
206
Pb = 2.108, and
206
Pb/
207
Pb
= 1.173;
208
Pb/
206
Pb = 2.082, respectively) (Figure 5.4), reflecting the influence of
different Pb sources.
5.5 Discussion
5.1.1 Temporal evolution of Pb and Pb isotopes in the North Pacific Ocean
The data derived from samples collected in the North Pacific Ocean, in
particular close to the Hawaiian Islands, provide the opportunity to explore the
temporal variability of Pb and Pb isotopes in surface waters of the Pacific Ocean. This
125
temporal change is accomplished comparing our results with those measured around
the same area over the last 30 years.
Table 5.1. Historical Pb concentrations and isotopic composition of surface waters of the North Pacific
Ocean near Hawaii.
A comparison of Pb concentrations measured close to the Hawaiian Islands in
May 2011 during the MCE and those measured around the same area in 1978
(Nürnberg et al., 1983), 1979 (Schaule and Patterson, 1981, Flegal et al., 1984), 1980
(Flegal and Patterson, 1983), 1997 and 1999 (Boyle et al., 2005), 2002 (Gallon et al.,
2012), and 2005 (Wu et al., 2010) (Figure 5.5A; Table 5.1) show that Pb
concentrations in this area of the Pacific Ocean have been steadily decreasing from
about 65pM measured in 1977 to about 30pM measured in 2011 during the MCE
cruise. Surface water Pb levels started decreasing in 1980 (Figure 5.5A). This trend
has been attributed to the elimination of leaded gasoline in Japan, the United States
and Canada (Boyle et al., 2005). Although leaded gasoline was not phased out in
China until the year 2000, gasoline consumption by China was small (9%) by
comparison to Pb gasoline utilization by the U.S. (Thomas, 1995). Figure 5.5A also
shows that the rapid decrease observed in Pb levels in surface waters of the Pacific
Ocean near Hawaii slowed down in the mid-1990s.
Lead concentrations during the 21-yr period form 1976 to 1997 decreased by half
(65pM to 39pM), while in the following 15 years from 1997 to 2011, Pb
Concentration* Latitude* Longitude* Year*
206
Pb/
207
Pb*
208
Pb/
207
Pb* Reference*
65.6$ 24.3$ (154.5$ 1977$ $$ $$
Schaule$and$Patterson,$
1981$
62.0$ 11.9$ (150.1$ 1978$
$ $
Nürnberg$et$al.,$1983$
63.2$ 19.0$ (158.0$ 1979$ 1.196$ 2.044$ Flegal$et$al.,$1984$
54.5$ 20.0$ (160.0$ 1980$
$ $
Flegal$and$Patterson,$1983$
39.4$ 22.0$ (148.0$ 1997$
$ $
Boyle$et$al.,$2005$
34.2$ 22.0$ (148.0$ 1999$
$ $
Boyle$et$al.,$2005$
32.8$ 22.5$ (158.0$ 2002$ 1.166$ 2.093$ Gallon$et$al.,$2012$
34.3$ 22.0$ (158.0$ 2005$ 1.159$ 2.114$ Wu$et$al.,$2010$
30.1$ 21.3$ (157.9$ 2011$ 1.164$ 2.095$ This$study$
!
126
concentrations decrease
only by a quarter (39pM to
30). We hypothesize that
the difference in decreasing
rates is due to a switch in
the emission sources of Pb.
After the complete phased
out of leaded gasoline in
the surrounding
industrialized countries, the
dominant sources of Pb to
the North Pacific Ocean
became coal combustion
and other high-temperature
industrial activities in
China, Japan and Korea. This
conclusion appears to be
consistent with the Pb
emission patterns mapped by
Pacyna et al. (1995) and further evidenced by the temporal shift in the Pb isotope
signatures (Figure 5.5B). During earlier decades,
206
Pb/
207
Pb ratios were dominated by
US derived Pb, with values trending more toward a US end-member in excess of 1.2
(Flegal et al., 1984). Over time, that ratio has decreased from 1.196 in 1979 to 1.159-
1.166 in the 2000s, reflecting both an increasing relative influence of lower
206
Pb/
207
Pb
Asian-derived Pb (with typical
206
Pb/
207
Pb aerosol ratios of 1.141-1.166), and a
20.0
25.0
30.0
35.0
40.0
45.0
50.0
55.0
60.0
65.0
70.0
1975 1980 1985 1990 1995 2000 2005 2010 2015
Pb#(pM)#
Year
2.04
2.05
2.06
2.07
2.08
2.09
2.1
2.11
2.12
1.15 1.16 1.17 1.18 1.19 1.2
208
Pb/
206
Pb
206
Pb/
207
Pb
Flegal&et&al.,&1984&
Gallon&et&al.,&2012&
Wu&et&al.,&2010&
This&study&
A#
B#
Figure 5.5. (A) Dissolved lead concentrations and (B)
associated isotopic composition of surface waters of the North
Pacific Ocean near Hawaii for the past 35 years. 1977 –
Schaule and Pattreson, 1981; 1978 – Nürnberg et al., 1983;
1979 – Flegal et al., 1984; 1980 – Flegal and Patterson, 1983;
1997 and 1999 – Boyle et al., 2005; 2002 – Gallon et al., 2012;
2005 – Wu et al., 2010; 2011 – This study
127
decrease in fluxes from US sources (with typical
206
Pb/
207
Pb aerosol ratios of 1.173-
1.223) caused by the phase out of leaded gasoline.
5.5.2 Possible Pb sources to Surface Waters of the world ocean
Surface water distribution of Pb and Pb isotopes reflect recent fluxes to the
surface ocean and give an indication of the source region of those fluxes because the
isotopic ratios of Pb ores are unaltered by smelting and other manufacturing processes
(Flegal and Smith, 1995). As a result, Pb and its stable isotopes have been effectively
used as tracers of atmospheric emission sources and transport processes in marine
environments (Flegal and Patterson, 1983; Véron et al., 1987; Shen and Boyle, 1988;
Flegal et al., 1989; Lambert et al., 1991). Surface water samples collected during the
MCE provide an extraordinary opportunity to identify the potential sources of Pb to
the different regions of the world’s oceans.
5.5.2.1 Possible Pb sources to the Indian Ocean
Figure 5.6 shows the composition of Pb in surface water samples collected
along the South Africa to Australia transect in the Indian Ocean along with previously
published isotopic composition of Pb in surface waters (Lee et al., 2015), aerosols
(Witt et al., 2006; Bollhöfer and Rosman, 2000), and other atmosphere-derived Pb
sources from the countries surrounding the Indian Ocean. The triple isotope plot shows
the combined effect of different Pb sources in surface waters of the Indian Ocean. The
sources of natural Pb in the Southern Indian Ocean have been suggested to be
continental dust from the arid regions of South Africa (e.g. the Kalahari and Namib
128
Figure 5.6. Comparison in triple isotope space between surface water samples collected during the MCE
along the Indian Ocean, surface water samples collected in the southwestern Indian Ocean (Lee et al.,
2015), aerosols collected in the major cities of Australia, new Zealand and the mid-Indian Ocean (Witt
et al., 2006; Bollhöfer and Rosman, 2000), and the average of Pb in Fe-Mn deposits in the Indian Ocean
basin (Vlastélic et al., 2001).
deserts) and Australia (Hovan and Rea, 1992). The isotopic composition of this source
of natural Pb has
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios of 1.203 ± 0.005 and 2.069 ± 0.008,
respectively, as inferred from ferromanganese nodules deposited in the Indian Ocean
(Vlastélic et al., 2001; Figure 5.6). The anthropogenic Pb reaching the Southern Indian
Ocean below ~20˚S originates mainly from the southern part of Africa and Australia.
The influence of the Inter Tropical Convergence Zone (ITCZ), located between 0˚ and
10˚S, effectively removes aerosols by wet deposition and limits the southward
transport of the aerosols from the Northern Hemisphere. Significant transport of
Australian dust and aerosols into the eastern part of the Indian Ocean occurs during
2.04
2.06
2.08
2.1
2.12
2.14
2.16
2.18
2.2
2.22
2.24
1.02 1.04 1.06 1.08 1.1 1.12 1.14 1.16 1.18 1.2 1.22
208
Pb/
2076
Pb
206
Pb/
207
Pb
Surface(water(samples,(
Lee(et(al.,(2015(
S.(Africa(to(Autralia,(This(
study(
South(African(aerosols(
Mid?indian(ocean(aerosls(
Australian(aerosols(
New(Zealand(aerosols(
Fe?Mn(deposits(
129
December-February
(when MCE samples
were collected) due to the
prevailing high
southeasterly winds
(Rajeev et al., 2000).
Lead from Southern
Africa reaches the Indian
Ocean through the semi-
permanent subtropical continental anticyclones and westerly disturbances that
transport dust and aerosols from South Africa to the southeast over the Indian Ocean
(Garstang et al., 1996). Lead in aerosols from both South Africa and Australia have
lower
206
Pb/
207
Pb and higher
208
Pb/
206
Pb ratios than natural Pb values (Figure 5.6).
Hence, our data are consistent with the premise that anthropogenic Pb inputs from
South Africa and Australia dominate the Southern portion of the Indian Ocean. This
conclusion is substantiated by both the fact that the Pb isotopic composition of our
samples fall on a two end-members mixing line of these two sources (Figure 5.6) and
by the high linear correlation (R
2
= 0.90) observed in a plot of the inverse of Pb
concentration vs. the
206
Pb/
207
Pb isotopic signature (Figure 5.7). The isotopic
anomalies shown in Figure 5.7 correspond to the samples collected close to the coast
of South Africa and Australia, which have elevated Pb concentrations from some
unknown local source.
y"="0.4674x"+"1.123"
R²"="0.899"
1.132
1.134
1.136
1.138
1.140
1.142
1.144
1.146
1.148
1.150
1.152
0.025 0.030 0.035 0.040 0.045 0.050 0.055 0.060
206
Pb/
207
Pb
1/Pb
Figure 5.7. 1/Pb versus
206
Pb/
207
Pb in surface waters of the
Indian Ocean. The high correlation coefficient suggests a
mixing of two end members
130
5.5.2.2 Possible Pb sources to the Atlantic Ocean
Over the last two centuries, the distribution of Pb in surface waters of the
Atlantic Ocean has changed significantly in response to changes in industrial Pb
emissions from North America and Western Europe (e.g., Boyle et al., 1986; Kelly et
al., 2009). Dissolved Pb concentrations increased considerably in the North Atlantic
between 1930 and 1970 due to atmospheric dispersal of residues from alkyl leaded
gasoline and decreased rapidly after the countries surrounding this ocean basin began
to phase-out Pb from gasoline – USA, 1975; Europe, 1985; South Africa, 1996; and
South America, 1998 (Wu and Boyle, 1997). Because Pb residence time in
oligotrophic surface waters is about 2 years (Bacon et al., 1976), both Pb
concentrations and its isotopic ratios respond relatively quickly (few years) to changes
in the main sources (e.g., Kelly et al., 2009). Therefore, the modern isotopic
composition measured in surface waters of the Atlantic Ocean during the MCE reflect
the lesser contribution of vehicle emissions and the greater contribution from industrial
activities like high temperature industrial processes, coal burning and smelting.
Figure 5.8A shows the composition of Pb in surface water samples collected
along the 3 different transects in the Atlantic Ocean along with previously published
isotopic composition of Pb in surface waters (Noble et al., 2015), pre-
anthropogenic/Holocene sediments (Sun, 1980), aerosols (Noble et al., 2015; Bollhöfer
and Rosman, 2000, 2001), Pb ores (Diaz-Somano et al., 2009), and coals (Diaz-
Somano et al., 2009) from different countries surrounding the Atlantic Ocean.
131
Figure 5.8. Comparison in triple isotope space between surface water samples collected during the MCE
in the Atlantic Ocean and (A) US and South African ores, S. African, European, US, Central and South
American aerosols, North American, European and S. African coals, Saharan dust, Holocene sediments
and corals from the Caribbean. (B) European, African, N. American, Central and South American
aerosols, ore and coal lines. Darker symbols are samples closer to the Northern or Western side of the
transect. Lighter symbol are samples closer to the Southern or eastern side of the transect.
Because of the short residence time of dissolved Pb in oceanic surface waters we
focused on the most recent aerosol data available, from 1998 or later. The 3-isotope
1.95
2
2.05
2.1
2.15
2.2
1.040 1.060 1.080 1.100 1.120 1.140 1.160 1.180 1.200 1.220 1.240
208
Pb/
206
Pb
206
Pb/
207
Pb
Colombia(to(Spain(
Spain(to(Brazil(
Brazil(to(S.(Africa(
US(Ores(
median(South(Africa(ores(
Central(America((aerosols)(
South(America((aerosols)(
North(America((coal)(
Europe((coal)(
South(Africa((coal)(
S.(Africa(aerosols(
Europe(aerosols(
US(aerosols(
Holocene((
sediments(
Coral,(1914(
Coral,(1997(
A"
Saharan(dust(
2.06
2.065
2.07
2.075
2.08
2.085
2.09
2.095
2.1
2.105
1.160 1.165 1.170 1.175 1.180 1.185
208
Pb/
206
Pb
206
Pb/
207
Pb
B"
North/West(
South/East(
Colombia to Spain
Spain to Brazil
Brazil to S. Africa
European Pb sources
African Pb sources
N. American Pb sources
Central American Pb sources
South American Pb sources
132
plot shows that our samples fall along a trajectory that is influenced by more than two
end-members (Figure 5.8A). To try to tease apart the sources, Figure 5.8B shows
mixing lines between likely Pb sources for each transect (e.g. European aerosols and
European coal to generate the line for European Pb sources, etc.).
Samples from the
Brazil to South Africa
transect seem to be grouped
in two main clusters, the
samples close to Africa with
low
206
Pb/
207
Pb ratios and
the samples close to South
America with a more
radiogenic isotopic signature
(Figure 5.8B). A mixing line of South African aerosols and African coal and ores
(Figure 5.8B) produces the
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios observed in the eastern
part of this transect, but in order to explain the isotopic signature of the western side,
the influence of a source with lower
208
Pb/
206
Pb and higher
206
Pb/
207
Pb ratios is needed.
According to Figure 5.8B, the influence of North American, Central American and
South American sources could yield the observed increase in the overall radiogenicity
found in these samples (radiogenicity: South America > Central America > North
America). However, the influence of North American sources is limited by the
formation of an air-mass barrier at the ITCZ (Alleman et al., 2001). Consequently,
!
R²!=!0.844!
!
R²!=!0.654!
1.17
1.172
1.174
1.176
1.178
1.18
1.182
0.015 0.025 0.035 0.045 0.055 0.065
206
Pb/
207
Pb
1/Pb
North!
South!
Figure 5.9. 1/Pb versus
206
Pb/
207
Pb in surface waters collected
in the transect from Spain to Brazil in the Atlantic Ocean. The
high correlation coefficients suggest different Pb sources
between the Northern and Southern hemisphere.
133
aeolian Pb inputs from emissions in the northern hemisphere are not generally
considered to be substantial in the southern hemisphere (Flegal and Patterson, 1983;
Boutron and Patterson, 1987). Therefore, we conclude that the main Pb sources to the
South Atlantic are industrial emissions from South Africa and Central and South
America. This hypothesis is also consistent with i) estimates of dust inputs to the South
Atlantic region (Mahowald et al., 2005), and ii) studies illustrating the importance of
the Trade winds in the overall elemental composition of aerosols arriving to the South
Atlantic (Swap et al., 1996).
The transect from Colombia to Spain is influenced by the main North Atlantic
wind regimes: the Westerlies that transport Pb from North America to the southeast,
the Easterlies that transport European pollutant Pb to the central and north Atlantic,
and the Trade Easterlies that transport large amounts of dust from the great desserts in
North Africa (Sahel and Sahara) to the west (Church et al., 1990; Helmers et al.,
1990). The influence of the Westerlies is evident in the western part of this transect,
where a mixture of both Central American aerosols and North American Pb sources
produce the
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios observed in this region (Figure 5.8B).
During earlier decades the isotopic composition of surface waters in the North Atlantic
was dominated by US-derived Pb; however, our results suggest that this is not the case
anymore, especially in the eastern North Atlantic where the isotopic composition of
surface waters reflect an increasing relative influence of Pb sources with lower
206
Pb/
207
Pb and higher
208
Pb/
206
Pb ratios (Figure 5.8B). This conclusion is supported by
the main wind regime in this area of the Atlantic Ocean (Easterlies carrying aerosols
134
from western Europe with lower
206
Pb/
207
Pb ratios), the completion of leaded gasoline
phase-out by the US, and the rise of coal combustion as one of the most significant
contributors to atmospheric Pb. The consumption of coal in North America (12.6% of
world total in 2010) although higher than that of Central America (0.5%) and Africa
(2.5%), is similar to European consumption (12.3%) (BP Statistical Review of World
Energy, 2014). Thus North America Pb isotopic signature seems to be currently
restricted to the Western North Atlantic (Figure 5.8B).
The influence of different Pb sources in the western North Atlantic is also
illustrated by Pb isotope ratios from annually-banded corals that grew in Mona Island
in the Caribbean basin (Desenfant et al., 2006). Figure 5.8A shows that isotopic ratios
measured in surface waters of the western North Atlantic during the MCE (
206
Pb/
207
Pb
= 1.181-1.184;
208
Pb/
206
Pb = 2.071-2.079) are much closer to the 1914 ratios of the
Mona Island coral (
206
Pb/
207
Pb = 1.188;
208
Pb/
206
Pb = 2.069) than those of 1997
(
206
Pb/
207
Pb = 1.167;
208
Pb/
206
Pb = 2.076). Additionally, the 1914 isotopic ratios of this
coral are similar to those of Quaternary marine sediments from this basin (
206
Pb/
207
Pb
= 1.207 ± 0.005;
208
Pb/
206
Pb = 2.062 ± 0.007; Sun, 1980). These results demonstrate
that the dominant Pb sources to the western North Atlantic have evolved over time and
that the relative importance of natural Pb sources is increasing.
The transect that started in Cadiz, Spain, and ended in Rio de Janeiro, Brazil, is
influenced by the main North Atlantic wind regimes described above, the seasonally
varying strength and position of the hemispheric Trade winds and the ITCZ, the
southeast Trade winds that transport natural and anthropogenic Pb from South Africa
135
to the west, and the south Westerlies that transport Pb from South America to the
northeast. Hence, Pb sources to this transect are very diverse. The lowest
206
Pb/
207
Pb
ratios were encountered in the northernmost part of the transect (Figure 5.3). In Figure
5.8B we have identified the influence of European Pb sources, which is consistent with
the air mass trajectories in this part of the Atlantic Ocean (Easterlies carrying Pb
aerosols from western Europe with lower
206
Pb/
207
Pb ratios). South from this area,
between 22˚N and the equator, we observed highly radiogenic samples (Figure 5.3).
We attribute the relatively radiogenic Pb to aeolian inputs from the North African
Trade Easterlies that carry Saharan dust with high
206
Pb/
207
Pb ratio (1.204). This result
reflects both an increase in the relative influence of radiogenic natural-derived Pb
sources, and a decrease in anthropogenic fluxes from the US and Europe.
Below the equator
206
Pb/
207
Pb ratios decrease again; this rapid change is
probably due to the effective removal of Saharan dust in the ITCZ and the influence of
southern hemisphere Pb sources like those from Central and South America with lower
206
Pb/
207
Pb ratios. This hypothesis is supported by the fact that Pb isotopic
compositions of samples from the southern hemisphere lie closer to both Central and
South American Pb sources (Figure 5.8B). Furthermore, a plot of the inverse of Pb
concentration vs. the
206
Pb/
207
Pb isotopic ratios (Figure 5.9) shows that samples are
grouped in two main clusters, samples from the northern hemisphere with higher
concentrations and a narrow range of
206
Pb/
207
Pb ratios and samples from the Southern
hemisphere with lower concentrations but a much wider isotopic range. The high
linear correlation observed in both the northern (R
2
= 0.84) and southern hemisphere
136
(R
2
= 0.65) clusters suggest that our samples are mixtures of two main component end
members, though teasing apart the exact sources is difficult, and it may be possible
that more than two sources could lie along this line.
5.5.2.3 Possible Pb sources to the Pacific Ocean
Previous work has shown that atmospheric deposition of anthropogenic
particles is the major contributor of Pb to North Pacific surface waters (Nagaoka et al.,
2010; Flegal and Patterson, 1983). During the 20
th
century, most anthropogenic Pb was
released to the atmosphere through combustion of leaded gasoline, especially between
1950 and 2000, when China phased-out the use of gasoline with Pb alkyls. Today, coal
combustion has become the principal source of aeolian Pb to the Pacific Ocean.
Countries like Indonesia, the Philippines and South Korea have all more that doubled
the amount of coal consumed between 1990 and 2011 (BP statistical review of world
Energy, 1990 and 2011). In addition, China became the world’s largest coal consumer
(50.6% of total coal consumption) (BP statistical review of world Energy, 2014). Thus,
it is expected that this rapid change in atmospheric Pb sources, in conjunction with the
short residence time of dissolved Pb in oceanic surface waters (<2 years), has greatly
modified Pb isotopic composition in surface waters of the Pacific Ocean over the last
decade. There have been a few studies investigating the modern distribution of Pb and
Pb isotopes in surface waters of the Northwestern Pacific Ocean (e.g. Wu et al., 2010;
Gallon et al., 2011), so samples collected during the MCE provide the opportunity to
137
contribute new data from the Northeast and Southwest Pacific Ocean – largely
unexplored regions of this vast ocean basin.
Figure 5.10. Comparison in triple isotope space between surface water samples collected during the
MCE in the Pacific Ocean and surface waters collected in the western Pacific Ocean by Gallon et al.,
2011, South and Central American, US, Australian, New Zealand, Western Pacific, Japanese, Korean,
Chinese and Vietnamese aerosols, Australian, New Zealand, Indonesia and China coals, Australia, US,
and China ores. The lines represent a regression of Chinese, Australian, New Zealand and US sources
respectively.
Figure 5.4 shows that the isotopic composition of seawater in the Pacific Ocean
can be described as 3 isotopically distinct regions – (i) the Southern Pacific, with
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios of about 1.158 and 2.105 respectively, (ii) a more
radiogenic section in the northwestern Pacific with
206
Pb/
207
Pb and
208
Pb/
206
Pb ratios of
1.165 and 2.095 respectively, and finally (iii) the northeastern section (east of 130˚W)
2.0000
2.0500
2.1000
2.1500
2.2000
2.2500
1.0400 1.0600 1.0800 1.1000 1.1200 1.1400 1.1600 1.1800 1.2000 1.2200 1.2400
208
Pb/
206
Pb(
(
(
206
Pb/
207
Pb
New$Zeland$to$Hawaii$(sorted$by$
la3tude)$
Hawaii$to$Panama$(sorted$by$
longitude)$
Surface$waters$
South$America$aerosols$
Central$America$aerosols$
United$States$aerosols$
Australia$aerosols$
New$Zealand$aerosols$
Western$Pacific$aerosols$
Japan$
Korea$
China$
Vietnam$
Australia$(coal)$
New$Zealand$(coal)$
Indonesia$(coal)$
Australia$Ores$
China$(coal)$
US$Ores$
N.$China$ores$
S.$China$ores$
China$
Australia$
New$Zealand$
US$
138
showing the highest
206
Pb/
207
Pb (1.172) and lowest
208
Pb/
206
Pb (2.085) ratios measured
in this ocean basin. In the transect from New Zealand to Hawaii, we observe a rapid
latitudinal change in the isotopic composition of seawater between the northern and
southern hemisphere, suggesting different Pb sources to each hemisphere and low
north-south interaction. This is consistent with previously reported atmospheric
transport patterns over the Pacific Ocean (Merrill, 1989), and the limited inter-
hemispheric advection of industrial Pb aerosols due to the influence of the ITCZ,
which brings intense and frequent rainfall in April and May, enhancing particle
removal from the atmosphere by scavenging.
In the northern hemisphere, the isotopic composition of seawater collected in
the western Pacific is very distinct from that collected in the eastern Pacific,
suggesting different Pb sources (Figure 5.10). To explore the predominant origin of Pb
in the different regions of the Pacific Ocean, we plotted Pb isotopic composition
(
206
Pb/
207
Pb vs.
208
Pb/
206
Pb) measured in surface waters sampled during the MCE and
those of previously published northwest Pacific surface waters (Gallon et al., 2011),
aerosols (Bollhöfer and Rosman, 2000, 2001), Pb ores (Diaz-Somano et al., 2009), and
coals (Diaz-Somano et al., 2009) from circum-Pacific countries (Figure 5.10).
Although the comparison of isotopic ratios is far from definitive, this 3-isotope plot
suggests that the Pb isotope ratios in our samples reflect mixtures between multiple Pb
sources.
139
Figure 5.11. 1/Pb versus (A)
206
Pb/
207
Pb and (B)
208
Pb/
206
Pb in surface waters collected in the Pacific
Ocean. The intercepts of each regression line with the y axis provide end-member ratios at infinitely
high concentrations, hence approximating the signatures of the main source of Pb in the samples.
To try to separate the different Pb sources, we plotted Pb isotopic compositions of the
3 different sections identified in Figure 5.4 vs. the inverse of Pb concentrations (Figure
5.11). The intercept of each regression –
206
Pb/
207
Pb = 1.170;
208
Pb/
206
Pb = 2.088 for
the Southern hemisphere,
206
Pb/
207
Pb = 1.160;
208
Pb/
206
Pb = 2.125 for the northwestern
Pacific and
206
Pb/
207
Pb = 1.175;
208
Pb/
206
Pb = 2.080 for the northeast Pacific, provides
Northwestern
y = 0.1929x + 1.160
R² = 0.674
Northeastern
y = -0.1035x + 1.175
R² = 0.481
Southern Hemisphere
y = -0.1644x + 1.170
R² = 0.613
1.154
1.156
1.158
1.160
1.162
1.164
1.166
1.168
1.170
1.172
1.174
1.176
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
206
Pb/
207
Pb
1/Pb
Northwestern
y"="$0.3064x"+"2.125"
R²"="0.655"
Northeastern
y"="0.1471x"+"2.080"
R²"="0.436"
Southern Hemisphere
y"="0.304x"+"2.088"
R²"="0.781"
2.080
2.085
2.090
2.095
2.100
2.105
2.110
2.115
0 0.02 0.04 0.06 0.08 0.1
208
Pb/
206
Pb
1/Pb
A
B
140
an estimate of the isotopic ratios of the main source of lead in the samples. For the
southern hemisphere, the intercept falls on the line describing Pb aerosols, ore, and
coal in both Australia and New Zealand (Figure 5.10). These findings are consistent
with air mass trajectories in the southern hemisphere at the time of sampling, in which
air from the west could have transported Australian pollutant Pb to the eastern South
Pacific.
For the northwest Pacific, the intercept falls on the line describing Pb aerosols,
ore, and coal in China (Figure 5.10). Although China banned the production of leaded
gasoline in 2000, aerosol Pb emissions in China are nearing their pre-2000 levels due
to the high density of metal smelters and intensive coal consumption in the country (Li
et al., 2012). In addition to high Pb concentrations in Chinese aerosols, the prevailing
winds over China aid the transport of Pb to the North Pacific Ocean, and it has even
been suggested that modern Asian Pb emissions are impacting atmospheric Pb
concentrations in USA and Canada (Osterberg et al., 2008; Zdanowicz et al., 2006).
Our results are also consistent with previous studies that have suggested that Chinese
industrial Pb emissions are now the dominant source of Pb inputs to the western and
central North Pacific (e.g. Gallon et al., 2011).
The elevated
206
Pb/
207
Pb ratios near the coast of Central America can
also be explained by the growing relative importance of natural radiogenic inputs, for
example African dust carried into the Caribbean and across the Isthmus of Panama
(Duce and Tindale, 1991). This hypothesis is consistent with the high Fe
concentrations measured at the same stations (Pinedo-Gonzalez et al., 2015). Finally,
141
our results indicate that distinguishing between natural and industrial Pb fluxes in the
Northeast Pacific is more difficult now that (i) the use of gasoline with lead alkyls
have been eliminated completely and (ii) coal combustion in North America has
decreased in the last decade from 28% of the world’s total consumption in 1998 to
12% in 2014 (BP statistical review of world Energy, 1998 and 2014).
5.6 Conclusions
The results reported here include dissolved Pb and Pb isotope composition in
surface waters of the global ocean, providing new data from unexplored regions of the
ocean. By comparing our new data to previously published data sets on the distribution
of Pb and Pb isotopes in surface waters of the central Pacific Ocean (specifically close
to Hawaii), we have explored changes in the distribution of Pb concentrations and Pb
isotope signatures that have occurred in the last 30 years; a dramatic drop in Pb
concentrations was observed in the period from 1976 to 1997, followed by a more
gradual reduction in Pb concentrations over the next 15 year period.
206
Pb/
207
Pb ratios
also decreased over time, reflecting an increasing relative influence of lower
206
Pb/
207
Pb Asian-derived Pb and a decrease in fluxes from US sources caused by the
phase out of leaded gasoline.
Although more recent data is needed (i.e. isotopic composition of modern
aerosols) and our results are far from definitive, we were able to identify the potential
main Pb sources to the Southern Indian, Atlantic and Pacific Oceans by comparing the
142
Pb isotope ratios of our surface water samples with previously published ratios in
aerosols and other atmosphere-derived Pb sources from the countries surrounding the
different ocean basins.
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149
Chapter 6
Conclusions
The results of this dissertation work are novel, important, and of interest to a
wide community not only because it provides extensive datasets that are likely to be
useful to those interested in the distribution of trace metals in the surface ocean, but
also because it is generating new evidence of the physical, biological and chemical
processes that influence the concentration and fractionation of trace metals in a variety
of aquatic environments. This research provides new insights into the link between
trace metal distribution and primary productivity, which is crucial for understanding
the global carbon cycle, including the factors that regulate atmospheric CO
2
, as well as
for understanding the state of the world’s ocean ecosystems.
In chapter 2, a high-temporal-resolution sampling strategy was used in order to
gain information about variability in metal concentrations and distribution over short
time scales. Results from this study show that both the concentration and size
partitioning of some biologically essential (Fe, Cu, Co, and Cd) and anthropogenic
(Pb) metals are affected by diel changes in temperature, biological activity, photo-
induced metal reduction/oxidation, and adsorption/desorption processes. This has
critical implications in terms of how cyclical variation in metal concentrations may
affect single measurements of trace metals. Our results show the importance of
considering changes that occur in the matter of hours when designing sampling
protocols for some bioactive trace metals in order to get representative results.
In Chapter 3, I report and discuss an extensive dataset on the distribution of
dissolved Co, Fe Cd, Cu, Ni, V, and Mo in surface waters of the global ocean,
150
providing new data from unexplored regions of the ocean as well as for some
understudied metals. By comparing our new data to previously published data sets on
the distribution of trace metals in surface waters of the Atlantic Ocean (specifically the
Spain to Brazil transect), we have explored changes in the distribution of trace metals
that have occurred in the last 30 years; for most metals, little change is observed over
this time period. Finally, in the last section of this chapter, I discuss the results from a
multivariable linear regression model identifying the trace metals that might have
important biogeochemical roles constraining primary productivity in the photic zone of
the surface ocean. Although this research builds on decades of prior work on spatial
patterns of surface ocean metal concentrations, the global extent of our new data is
particularly novel and allows analysis and interpretation about the biogeochemical
implications that has not been possible in the past. In particular, I have been able to
identify the links between metal distributions and phytoplankton biomass and primary
productivity over basin-wide spatial scales, which is crucial for understanding the
controls on the biological cycles of carbon and nitrogen, including the biological
transfer of carbon to the deep sea, which helps regulate atmospheric CO
2
.
In Chapter 4, I investigate the partitioning of metals between the colloidal and
soluble phases in storm-runoff from three different environments (an area affected by a
natural wildfires, a natural catchment, and highly urbanized rivers) in order to gain
information about potential sources of soluble (i.e., bioavailable) elements that are
delivered to receiving waters. This study shows that the concentrations of Fe, Cu, Pb,
V and Zn in a recently burned catchment in the San Gabriel Mountains were similar to
those in the urban rivers and higher than in unburned natural areas, confirming the
importance of wildfires and subsequent rainfall in the mobilization of some but not all
trace elements in the environment. Furthermore, this study is the first to provide
151
conclusive evidence that storm runoff from burned landscapes has the potential to
supply a greater proportion of trace elements in bioactive soluble form, compared to
runoff from urban or unburned areas. This largely unexplored source of bioavailable
metals may have important implications for the biogeochemistry of receiving waters,
through the supply of elements that can enhance (e.g., Fe, Zn) or inhibit (e.g., Cu, Pb)
biological activity.
In chapter 5, dissolved Pb concentrations and stable isotopes (
206
Pb,
207
Pb, and
208
Pb) were analyzed in surface water samples (3m depth) collected during the
Malaspina Circumnavigation Expedition, 2010. The results were compared with data
from the literature to i) evaluate the changing status of metal contamination in surface
waters of the global ocean over the last 30 years, and ii) propose potential sources of
modern Pb to the oceans. Our results show that Pb concentrations in surface waters of
both the North Atlantic and Pacific Oceans have decreased ~ 40% since 1975,
attributable to the phase-out of leaded gasoline in North America. This result is
corroborated by stable Pb isotope measurements. In addition, results from an
understudied transect in the Southern Indian Ocean give an indication of the source
region of Pb delivered to this region. This study provides an opportunity to build on
the work of previous oceanographic campaigns, enabling us to assess the impact of
anthropogenic Pb inputs to the ocean and the relative importance of various Pb
sources, providing new insights into the transport and fate of Pb in the oceans.
152
Appendix A
Appendix A provides the supported information and all data for chapter 2.
Table A1. Analytical results of the analysis of nearshore seawater reference material
for trace metals CASS-5.
(µg/L)
Table A2. Results of the Mann-Whitney U-test performed on the trace metal data
collected in June and July, 2012.
Note:
*p
≤
0.05
Element Certified value Measurement result
Mo 9.59 ± 0.70 10.0 ± 0.06
Cd 0.0210 ± 0.0017 0.022 ± 0.0002
Pb 0.011 ± 0.002 0.0097 ± 0.0004
V 1.28 ± 0.14 1.30 ± 0.007
Fe 1.40 ± 0.11 1.47 ± 0.004
Co 0.093 0.10 ± 0.0002
Ni 0.322 ± 0.022 0.31 ± 0.003
Cu 0.371 ± 0.028 0.36 ± 0.001
!
June,&2012 July,&2012
Element u"value z"score
p------------
(two"tails) Element u"value z"score
p------------
(two"tails)
Variation(in(both(fractions Variation(in(both(fractions
Fe(T 0 -2.51 0.01* FeT 0 -2.51 0.01*
FeS 0 -2.51 0.01* FeS 0 -2.51 0.01*
CoT 4 -1.67 0.05* CoT 0 -2.51 0.01*
CoS 4 -1.67 0.05* CoS 1 -2.30 0.02*
CuT 0 -2.51 0.01* CdT 3 -1.88 0.05*
CuS 0 2.51 0.01* CdS 4 -1.67 0.05*
variation(in(one(fraction variation(in(one(fraction
PbT 5 1.46 0.14 PbT 5 1.57 0.12
PbS 0 2.51 0.01* PbS 0 2.51 0.01*
CdT 1 -2.51 0.01* CuT 0 -2.51 0.01*
CdS 10 0.42 0.67 CuS 9 0.63 (((((((0.53
No(variation No(variation
AgT 6 1.25 0.21 AgT 5 -1.46 (((((((0.14
AgS 3 1.98 0.05 AgS 3 -1.88 0.06
MoT 9 -0.63 0.52 MoT 12 0.00 1.00
MoS 10 -0.42 0.67 MoS 8 -0.94 0.35
VT 7 -1.04 0.29 VT 9 -0.73 0.46
VS 8 -0.84 0.40 VS 8 -0.94 0.35
NiT 11 0.21 0.83 NiT 3 1.88 0.06
NiS 11 -0.21 0.83 NiS 11 0.21 0.83
153
Table A3. Total dissolved trace metal concentrations measured in the surface ocean off
Catalina Island in June 2012.
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 19 27.95 3.18 1.53 94.10 4.72 0.18 24.62 64.37 3.60
1 22 27.05 5.28 1.96 92.49 4.38 0.19 20.78 67.37 3.61
2 1 26.30 5.94 2.00 102.47 4.03 0.20 23.77 73.41 3.49
2 4 27.97 5.87 2.33 94.22 4.35 0.20 23.38 77.06 3.61
2 7 28.07 4.60 2.17 105.77 4.56 0.20 23.13 69.55 3.54
2 10 29.12 3.27 2.15 98.54 4.41 0.19 24.01 57.63 3.47
2 13 28.79 1.31 1.91 94.43 4.27 0.19 21.94 75.43 3.63
2 16 30.57 2.31 1.66 108.00 4.38 0.18 24.90 68.35 3.81
2 22 31.66 4.94 1.81 97.88 4.35 0.19 24.18 70.88 3.73
3 1 27.68 6.38 1.91 101.42 4.31 0.20 25.99 79.08 3.60
3 4 26.10 6.21 2.30 96.71 4.48 0.20 24.74 81.74 3.57
3 7 30.17 5.10 2.34 102.93 4.77 0.19 20.92 62.24 3.34
3 10 31.76 2.98 2.00 103.02 4.57 0.19 22.17 70.67 3.64
3 13 30.46 1.82 1.98 93.87 4.39 0.19 22.97 60.79 3.61
3 16 31.06 2.10 1.82 93.75 4.82 0.18 21.90 50.67 3.85
3 19 30.63 3.71 1.22 91.97 4.76 0.18 22.61 66.03 3.81
4 1 28.90 6.76 2.14 106.17 4.42 0.20 22.59 76.53 3.65
4 13 31.17 2.05 1.72 96.43 4.57 0.18 20.72 52.83 3.75
154
Table A4. Soluble trace metal concentrations measured in the surface ocean off
Catalina Island in June 2012.
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 19 13.05 1.00 1.25 90.92 4.01 0.17 23.52 60.38 3.55
1 22 11.16 2.08 1.45 89.62 3.99 0.17 19.20 59.31 3.26
2 1 7.41 2.91 1.39 101.38 3.65 0.17 23.15 71.75 3.22
2 4 9.02 2.61 1.80 88.69 3.86 0.18 22.81 63.64 3.61
2 7 16.26 1.56 1.83 105.30 4.24 0.18 23.48 65.21 3.16
2 10 22.57 1.05 1.92 92.04 4.38 0.18 23.32 58.24 3.51
2 13 26.99 0.04 1.82 93.39 4.03 0.18 21.06 65.29 3.22
2 16 25.96 0.58 1.48 100.27 4.24 0.18 25.17 63.63 3.74
2 22 10.89 1.55 1.43 93.01 4.03 0.18 24.18 60.55 3.59
3 1 4.86 3.06 1.27 99.19 4.17 0.19 24.47 68.45 3.43
3 4 4.75 3.09 1.68 95.64 4.27 0.18 23.59 79.94 3.50
3 7 14.62 1.96 2.05 104.20 4.38 0.18 20.71 55.50 3.26
3 10 23.21 0.71 1.82 103.24 4.24 0.19 21.63 62.75 3.61
3 13 26.56 0.12 1.92 87.67 4.22 0.20 22.92 58.81 3.21
3 16 23.54 0.42 1.66 92.40 4.46 0.16 21.47 55.33 3.74
3 19 16.39 1.15 1.04 85.81 4.43 0.17 21.23 61.22 3.62
4 1 10.84 3.53 1.55 99.14 4.03 0.19 22.27 71.19 3.59
4 13 25.85 0.29 1.71 95.14 4.41 0.17 20.35 47.17 3.50
155
Table A5. Colloidal trace metal concentrations calculated by difference (Total
dissolved – Soluble) from the surface ocean off Catalina Island in June 2012.
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 19 14.90 2.18 0.28 3.19 0.71 0.01 1.11 3.99 0.05
1 22 15.89 3.20 0.51 2.87 0.39 0.02 1.58 8.06 0.35
2 1 18.89 3.04 0.62 1.09 0.38 0.02 0.61 1.66 0.27
2 4 18.95 3.26 0.53 5.53 0.49 0.02 0.57 13.42
2 7 11.81 3.04 0.35 0.47 0.31 0.01 4.34 0.38
2 10 6.55 2.22 0.24 6.50 0.04 0.01 0.69
2 13 1.80 1.26 0.09 1.04 0.24 0.01 0.88 10.14 0.41
2 16 4.61 1.73 0.18 7.73 0.15 0.00 4.72 0.06
2 22 20.77 3.38 0.38 4.88 0.32 0.01 0.00 10.33 0.14
3 1 22.83 3.32 0.64 2.23 0.15 0.01 1.52 10.63 0.17
3 4 21.35 3.12 0.62 1.07 0.21 0.03 1.15 1.80 0.07
3 7 15.56 3.14 0.29 0.38 0.01 0.20 6.74 0.08
3 10 8.55 2.26 0.18 0.34 0.00 0.54 7.92 0.04
3 13 3.90 1.70 0.06 6.20 0.17 0.06 1.98 0.40
3 16 7.52 1.68 0.16 1.35 0.35 0.02 0.43 0.12
3 19 14.24 2.55 0.19 6.16 0.33 0.01 1.39 4.81 0.18
4 1 18.06 3.24 0.59 7.03 0.38 0.01 0.31 5.34 0.06
4 13 5.32 1.76 0.02 1.29 0.16 0.01 0.37 5.66 0.25
156
Table A6. Total dissolved trace metal concentrations measured in the surface ocean off
Catalina Island in July 2012.
Table A7. Soluble trace metal concentrations measured in the surface ocean off
Catalina Island in July 2012.
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 7 24.83 4.06 1.87 99.81 4.31 0.20 23.95 55.61 3.47
1 11 28.55 3.09 1.70 111.41 4.10 0.18 24.20 48.50 3.45
1 15 24.26 3.01 1.81 91.82 3.80 0.19 23.69 55.44 3.37
1 19 27.81 4.19 1.97 108.47 4.48 0.20 23.57 53.31 3.59
1 23 23.53 6.08 2.02 98.40 3.90 0.20 25.57 63.72 3.37
2 3 24.22 5.00 2.22 100.15 4.21 0.19 25.28 62.81 3.37
2 7 24.69 3.40 2.11 110.18 3.82 0.20 25.19 53.00 3.47
2 11 25.86 2.81 1.91 106.12 3.49 0.17 24.02 53.67 3.60
2 15 26.27 2.39 1.82 93.70 4.30 0.19 25.14 55.17 3.52
2 19 26.70 4.32 1.91 110.75 3.93 0.20 25.47 57.72 3.21
2 23 22.98 6.79 2.07 100.27 4.44 0.21 25.90 58.63 3.26
3 3 21.67 4.63 2.31 109.05 4.77 0.18 24.87 59.47 3.38
3 7 24.41 3.70 2.02 98.07 3.70 0.19 24.15 59.17 3.44
3 11 24.41 1.89 1.67 108.18 3.50 0.18 25.20 50.11 3.47
3 23 25.07 7.34 2.09 103.86 4.69 0.20 25.10 60.94 3.33
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 7 20.50 1.22 1.74 95.78 3.61 0.19 23.10 54.58 3.43
1 11 26.42 0.47 1.57 89.47 3.32 0.16 23.22 43.01 3.42
1 15 19.97 0.50 1.55 91.05 3.21 0.19 23.49 55.12 3.10
1 19 13.25 1.47 1.62 99.32 3.86 0.18 23.11 50.04 3.33
1 23 4.77 3.08 1.39 96.35 3.73 0.20 24.69 59.90 3.38
2 3 9.77 3.92 1.68 100.15 3.71 0.19 24.10 60.32 3.30
2 7 19.92 0.85 1.90 106.78 3.33 0.19 24.20 53.96 3.40
2 11 24.74 0.36 1.85 90.34 3.12 0.17 24.00 48.01 3.52
2 15 22.36 0.48 1.47 92.76 3.50 0.18 24.70 51.61 3.15
2 19 8.04 1.38 1.47 104.58 3.54 0.20 24.59 59.50 3.21
2 23 4.88 3.27 1.46 99.58 4.28 0.18 25.26 58.11 3.28
3 3 10.31 3.33 1.80 106.81 4.50 0.17 24.87 59.00 3.29
3 7 20.74 1.30 1.76 100.24 3.19 0.19 23.98 58.73 3.38
3 11 22.01 0.17 1.58 98.24 3.17 0.16 23.75 45.59 3.37
3 23 3.80 3.45 1.53 99.90 4.57 0.19 25.11 55.10 3.31
157
Table A8. Colloidal trace metal concentrations calculated by difference (Total
dissolved – Soluble) from the surface ocean off Catalina Island in July 2012.
Table A9. Temperature, light intensity, and Chlorophyll-a values measured in the
surface ocean off Catalina Island in July 2012.
Day Time
Pb
[pM]
Fe
[nM]
Cu
[nM]
Mo
[nM]
Ag
[pM]
Cd
[nM]
V
[nM]
Co
[pM]
Ni
[nM]
1 7 4.33 2.84 0.13 4.04 0.70 0.01 0.86 1.02 0.04
1 11 2.12 2.61 0.13 21.94 0.78 0.02 0.98 5.49 0.03
1 15 4.28 2.52 0.26 0.77 0.59 0.00 0.20 0.32 0.27
1 19 14.56 2.72 0.36 9.15 0.62 0.02 0.46 3.27 0.27
1 23 18.76 3.00 0.62 2.05 0.17 0.00 0.88 3.82
2 3 14.46 1.08 0.54 0.01 0.50 0.01 1.18 2.49 0.08
2 7 4.77 2.55 0.21 3.40 0.50 0.02 0.99 0.06
2 11 1.11 2.44 0.06 15.78 0.37 0.00 0.02 5.66 0.08
2 15 3.91 1.91 0.35 0.94 0.80 0.02 0.44 3.56 0.37
2 19 18.66 2.94 0.43 6.17 0.39 0.00 0.88 0.01
2 23 18.10 3.52 0.60 0.69 0.16 0.03 0.64 0.52
3 3 11.36 1.30 0.51 2.24 0.27 0.01 0.47 0.09
3 7 3.67 2.40 0.26 0.51 0.17 0.44 0.06
3 11 2.40 1.72 0.08 9.94 0.33 0.01 1.46 4.52 0.11
3 23 21.27 3.89 0.57 3.96 0.12 0.01 5.84 0.02
Day Time Chl-‐a
Temerature
[°C]
Light
intensity
[Lux]
1 7 0.504 18.98 3400.0
1 11 0.628 19.26 72900.0
1 15 0.957 19.44 72900.0
1 19 0.819 19.16 11100.0
1 23 0.210 19.25 1.5
2 3 0.338 19.05 1.1
2 7 0.997 18.84 9450.0
2 11 1.328 19.12 64800.0
2 15 1.229 19.24 67500.0
2 19 1.174 19.44 14000.0
2 23 0.205 19.38 1.2
3 3 0.201 19.39 1.2
3 7 0.469 19.03 3190.0
3 11 1.329 19.45 70200.0
3 23 0.000 19.25 0.9
158
Figure A1. Diel primary productivity, soluble Fe, and bacterial-abundance variations
in the surface ocean off Catalina Island (July 2012).
Mass balance describing the diel changes in Fe distribution:
Active Uptake:
- Mean primary production: 510nmolC/m
3
sec (Figure A1)
- Fe decline (in soluble pool): 3.5nM (Figure 5.3B)
- nmol Fe required to keep primary production: 1.12nM, assuming 19671-
16533nmol C:1nmol Fe (Ho et al., 2003)
- Biological uptake accounts for 26-31% of Fe decline
Surface adsorption:
- Bacteria surface adsorption capacity: 1-2µmol/g
dry
(Pokrovsky and Shirokova,
2013)
- Fe adsorbed by bacteria: 1.2-2.4nmol/L
- Surface adsorption accounts for 34-68% of Fe decline
159
Appendix B
Appendix B provides the supported information and data for chapter 3.
Figure B1. Vertical temperature field contour from the combined CTD and XBT data
showing changes in the isotherms/isopycnals due to cyclonic and anticyclonic eddies
developed from the Leeuwin current.
Table B1. Complete list of Longhurst biogeographical provinces shown in Figure 3.1
1. Alaska
Downwelling
Coastal
Province
19.
Red
Sea,
Persian
Gulf
Province
37.
Pacific
Equatorial
Divergence
Province
2. Australia-‐Indonesia
Coastal
Province
20.
Sunda-‐Arafura
Shelves
Province
38.
S.
Atlantic
Gyral
Province
3. Benguela
Current
Coastal
Province
21.
SW
Atlantic
Shelves
Province
39.
W.
Pacific
Warm
Pool
Province
4. Brazil
Current
Coastal
Province
22.
W.
India
Coastal
Province
40.
Western
Tropical
Atlantic
Province
5. California
Upwelling
Coastal
Province
23.
Antarctic
Province
41.
Gulf
Stream
Province
6. Canary
Coastal
Province
24.
Atlantic
Arctic
Province
42.
Kuroshio
Current
Province
7. Central
America
Coastal
Province
25.
Atlantic
Subarctic
Province
43.
Mediterranean
Sea,
Black
Sea
Province
8. Chile-‐Peru
Current
Coastal
Province
26.
Austral
Polar
Province
44.
N.
Atlantic
Drift
Province
9. China
Sea
Coastal
Province
27.
Boreal
Polar
Province
45.
N.
Atlantic
Subtropical
Gyral
Province
(east)
10. E.
Africa
Coastal
Province
28.
N.
Pacific
Epicontinental
Province
46.
N.
Atlantic
Subtropical
Gyral
Province
(west)
11. E.
India
Coastal
Province
29.
Archipelagic
Deep
Basin
Province
47.
N.
Pacific
Polar
Front
Province
12. E.
Australia
Coastal
Province
30.
Caribbean
Province
48.
N.
Pacific
Subtropical
Gyre
Province
(west)
13. Guianas
Coastal
Province
31.
Eastern
Tropical
Atlantic
Province
49.
Pacific
Subarctic
Gyres
Province
(east)
14. Guinea
Current
Coastal
Province
32.
Indian
Monsoon
Gyres
Province
50.
Pacific
Subarctic
Gyres
Province
(west)
15. NE
Atlantic
Shelves
Province
33.
Indian
S.
Subtropical
Gyre
Province
51.
S.
Pacific
Subtropical
Gyre
Province
16. New
Zealand
Coastal
Province
34.
N.
Atlantic
Tropical
Gyral
Province
52.
S.
Subtropical
Convergence
Province
17. NW
Arabian
Upwelling
Province
35.
N.
Pacific
Equatorial
Countercurrent
Province
53.
Subantarctic
Province
18. NW
Atlantic
Shelves
Province
36.
N.
Pacific
Tropical
Gyre
Province
54.
Tasman
Sea
Province
160
Table B2. Total dissolved trace metal concentrations, salinity, temperature, PO
4
, NO
3
, SiO
4
, Chlorophyll a (Chl-a), depth integrated
primary productivity (PPi), and mixed layer depth (MLD) measured in the surface ocean during the circumnavigation expedition
Malaspina 2010 from December 2010 to July 2011.
Transect
Station,
number
Latitude Longitude Mo,(nM) Cd,(pM) V,(nM) Fe,(nM) Co,(pM) Ni,(nM) Cu,(nM) Salinity
Temperat.,
(˚C)
PO4,(µM) NO3,(µM) SiO4,(µM)
Chla,,
(µg/L)
PPi,
(mgC/m2h)
MLD,(m)
S.#Africa#to#Australia 1 034.8 27.5 107.19 26.33 26.50 1.81 32.25 2.66 1.05 35.29 26.39 0.070 0.440 1.740 0.170 49.08 26
S.#Africa#to#Australia 2 034.4 31.1 95.31 24.81 20.81 1.53 30.09 2.06 0.76 35.52 23.70 0.010 0.310 0.940 0.090 3.94 32
S.#Africa#to#Australia 3 034.2 33.7 94.19 12.37 22.80 0.57 19.53 1.27 0.88 35.60 23.93 0.027 0.331 1.448 0.090 19.78 30
S.#Africa#to#Australia 4 033.9 37.1 83.83 20.94 25.37 0.38 26.90 2.19 0.84 35.63 23.86 0.080 0.310 1.470 0.110 10.16 38
S.#Africa#to#Australia 5 033.5 39.9 86.14 21.30 26.73 0.47 24.58 2.06 0.82 35.55 24.46 0.071 0.281 1.198 0.110 18.73 36
S.#Africa#to#Australia 6 033.2 43.3 113.18 16.34 28.93 0.62 24.76 1.81 1.17 35.51 23.71 0.260 0.370 1.380 0.080 15.55 70
S.#Africa#to#Australia 7 027.9 63.6 86.90 23.28 23.39 0.53 30.84 2.04 0.79 35.32 26.32 0.030 0.510 0.620 0.080 20.37 44
S.#Africa#to#Australia 8 028.2 66.5 83.13 21.33 25.09 0.52 28.54 2.05 0.79 35.40 25.78 0.030 0.410 1.133 0.070 14.65 44
S.#Africa#to#Australia 9 029.3 69.9 73.20 20.63 28.68 0.51 27.26 1.89 0.58 35.54 25.70 0.020 0.370 1.030 0.050 8.11 32
S.#Africa#to#Australia 10 029.6 73.1 78.59 20.94 20.31 0.50 25.97 1.74 0.95 35.77 24.92 0.010 0.390 2.380 0.040 7.30 40
S.#Africa#to#Australia 11 029.9 76.2 79.77 19.29 24.55 0.53 24.68 1.83 1.61 35.98 22.90 0.060 0.566 1.570 0.030 9.34 40
S.#Africa#to#Australia 12 029.8 79.6 83.75 16.30 18.32 0.70 19.24 1.66 0.68 36.01 23.55 0.070 0.410 1.700 0.060 8.95 28
S.#Africa#to#Australia 13 029.6 97.2 96.90 27.24 27.63 0.19 3.56 2.42 1.06 35.76 22.20 0.020 0.040 0.690 0.130 6.85 90
S.#Africa#to#Australia 14 029.9 100.0 104.59 22.70 29.18 0.30 22.40 1.84 0.89 35.55 22.12 0.020 0.090 1.550 0.070 3.90 26
S.#Africa#to#Australia 15 030.4 103.9 74.16 17.57 20.67 0.31 25.74 1.65 1.13 35.73 22.11 0.030 0.100 1.850 0.060 12.80 36
S.#Africa#to#Australia 16 030.8 107.3 80.08 23.21 21.68 0.52 21.52 2.46 0.98 35.52 23.43 0.050 0.120 1.340 0.100 13.53 52
S.#Africa#to#Australia 17 031.2 110.9 94.62 22.02 24.82 0.65 15.58 2.17 0.93 35.47 23.41 0.040 0.240 1.030 0.160 21.67 60
S.#Africa#to#Australia 18 031.6 114.2 105.09 24.04 31.75 0.81 27.95 2.09 1.14 35.32 25.20 0.030 0.840 2.050 0.100 10.31 42
Colombia#to#Spain 19 11.9 074.7 79.73 25.79 17.87 1.19 54.03 1.99 1.38 35.70 28.90 0.061 0.506 2.443 0.130 18.97 60
Colombia#to#Spain 20 13.7 072.3 76.03 25.39 15.36 1.02 26.57 1.19 1.64 35.56 29.21 0.071 0.569 1.258 0.145 26.72 92
Colombia#to#Spain 21 14.8 069.9 92.51 17.94 19.62 0.67 23.54 1.68 0.94 35.45 29.31 0.068 0.340 1.513 0.091 13.05 98
Colombia#to#Spain 22 15.4 067.8 90.79 23.93 23.91 0.49 23.84 1.74 1.23 35.53 29.64 0.038 0.569 1.451 0.193 38.50 62
Colombia#to#Spain 23 17.4 059.8 115.40 23.69 25.99 0.93 25.54 2.05 1.25 35.52 29.43 0.025 0.342 1.160 0.267 34.36 96
Colombia#to#Spain 24 17.8 058.6 104.78 20.21 11.85 0.70 28.63 1.92 1.30 35.65 29.03 0.006 0.379 1.247 0.307 19.96 148
Colombia#to#Spain 25 18.7 055.9 86.53 17.65 15.07 0.55 23.75 1.26 1.27 36.66 28.52 0.088 0.446 1.086 0.054 18.35 120
Colombia#to#Spain 26 19.9 053.2 79.38 20.52 22.44 0.55 30.45 1.98 1.19 36.83 28.08 0.054 0.506 1.368 0.073 20.41 136
Colombia#to#Spain 27 20.7 050.3 93.46 26.51 19.76 0.82 29.83 1.96 1.05 37.07 27.63 0.049 0.598 0.840 0.056 19.34 136
Colombia#to#Spain 28 21.4 048.5 107.30 29.20 23.32 0.73 29.39 2.42 1.36 37.07 27.49 0.053 0.402 0.832 0.058 21.50 128
Colombia#to#Spain 29 24.9 038.7 83.24 14.14 28.94 0.61 35.28 1.90 1.12 37.56 25.67 0.085 0.288 0.819 0.077 19.66 162
Colombia#to#Spain 30 26.1 035.3 76.70 18.30 25.93 0.45 45.23 1.14 0.76 37.63 24.88 0.069 0.442 0.987 0.049 15.99 138
Colombia#to#Spain 31 26.9 032.9 79.54 19.43 26.73 0.54 43.47 1.12 0.45 37.47 24.39 0.088 0.342 0.567 0.045 13.00 150
Colombia#to#Spain 32 27.8 030.0 81.64 17.47 26.49 0.62 47.14 1.69 0.67 37.33 23.31 0.062 0.412 0.554 0.044 9.45 130
Colombia#to#Spain 33 28.9 027.0 75.74 15.52 19.00 0.41 41.92 1.67 0.61 37.37 23.00 0.057 0.472 1.099 0.099 17.11 118
Colombia#to#Spain 34 29.8 024.1 110.11 10.30 28.53 0.56 44.52 1.55 0.60 36.95 21.62 0.131 0.564 0.586 0.065 27.61 98
Colombia#to#Spain 35 31.0 020.6 80.18 8.34 20.65 0.90 38.75 1.12 0.74 36.88 21.52 0.100 0.453 0.583 0.075 29.33 84
Colombia#to#Spain 36 32.1 017.3 100.41 6.35 20.15 1.12 36.97 1.35 1.38 36.86 21.88 0.093 0.437 0.507 0.066 27.81 86
161
Table B2. Continues
Spain&to&Brazil 37 35.3 19.2 115.67 27.63 26.12 1.59 59.97 1.85 2.17 36.52 18.95 0.074 0.646 0.874 0.145 6.98 65
Spain&to&Brazil 38 29.8 117.2 92.39 21.37 23.04 1.00 24.26 1.58 0.78 36.93 21.19 0.084 0.646 0.874 0.114 8.01 102
Spain&to&Brazil 39 28.7 118.8 79.87 26.12 21.75 1.49 40.29 2.08 1.04 37.08 22.19 0.022 0.259 0.890 0.094 9.99 64
Spain&to&Brazil 40 25.4 120.8 72.07 18.87 25.38 1.46 34.03 2.60 1.04 36.95 23.20 0.009 0.731 0.626 0.151 9.50 71
Spain&to&Brazil 41 23.5 122.1 76.91 24.92 26.36 1.63 33.23 2.13 1.12 37.06 23.81 0.022 0.623 0.874 0.222 9.74 86
Spain&to&Brazil 42 21.5 123.4 88.30 22.60 24.01 1.54 18.00 1.51 0.97 36.69 26.88 0.078 0.263 1.001 0.179 20.58 84
Spain&to&Brazil 43 20.3 124.3 110.51 27.76 25.47 1.89 22.39 1.74 1.12 36.61 25.57 0.084 0.646 0.874 0.140 18.26 64
Spain&to&Brazil 44 16.6 126.0 95.78 22.78 26.12 1.75 10.00 1.72 1.12 36.40 27.00 0.084 0.208 0.849 0.201 38.26 68
Spain&to&Brazil 45 7.3 126.0 81.15 19.58 20.09 0.55 9.71 1.75 0.90 35.40 28.27 0.017 0.344 1.549 0.245 31.19 58
Spain&to&Brazil 46 13.0 127.3 85.67 24.75 24.66 0.81 28.24 1.49 0.96 36.15 28.00 0.112 0.102 0.956 0.146 21.48 80
Spain&to&Brazil 47 14.1 127.8 87.57 15.73 24.58 0.91 27.25 1.00 0.94 36.35 27.75 0.148 0.232 0.956 0.109 15.08 110
Spain&to&Brazil 48 17.2 129.3 87.25 16.68 26.25 0.66 25.67 1.10 0.73 35.81 30.90 0.135 0.082 1.148 0.099 19.68 122
Spain&to&Brazil 49 18.7 130.0 85.18 13.54 19.78 0.72 28.95 0.98 0.83 36.65 27.65 0.215 0.083 0.400 0.058 20.91 142
Spain&to&Brazil 50 110.9 131.0 93.28 25.94 20.15 0.66 20.08 1.74 0.95 36.87 27.67 0.138 0.102 1.456 0.040 21.01 152
Spain&to&Brazil 51 113.7 132.4 81.10 22.70 23.74 0.67 29.61 0.93 1.05 37.13 27.43 0.130 0.102 0.956 0.047 13.47 148
Spain&to&Brazil 52 115.2 133.1 95.64 27.82 27.37 0.76 20.77 1.88 1.15 37.24 27.84 0.112 0.102 0.956 0.090 27.92 158
Spain&to&Brazil 53 120.6 135.7 133.96 27.31 33.23 0.64 27.13 1.97 1.19 36.99 27.40 0.110 1.588 0.804 0.125 15.64 124
Spain&to&Brazil 54 124.2 136.7 89.86 21.39 24.23 0.71 22.86 1.49 1.47 36.57 26.95 0.030 0.140 0.820 0.077 16.00 112
Brazil&to&S.&Africa 55 124.2 136.7 89.86 21.39 24.23 0.71 22.86 1.49 1.47 36.57 26.95 0.030 0.140 0.820 0.077 16.00 112
Brazil&to&S.&Africa 56 124.8 133.5 84.45 12.07 19.84 0.90 20.55 0.92 1.05 36.65 27.12 0.010 0.270 1.060 0.082 15.79 120
Brazil&to&S.&Africa 57 125.4 130.2 80.24 23.31 18.40 0.82 23.60 1.57 1.31 36.58 26.04 0.000 0.350 0.930 0.097 27.02 122
Brazil&to&S.&Africa 58 125.7 128.4 84.93 15.02 21.17 0.77 21.53 1.09 1.18 36.49 25.68 0.096 0.243 1.041 0.078 22.48 138
Brazil&to&S.&Africa 59 126.4 124.5 71.11 17.31 22.17 0.72 27.30 1.96 1.45 36.41 24.62 0.060 0.340 1.330 0.047 17.81 144
Brazil&to&S.&Africa 60 126.8 122.2 80.73 12.61 19.28 0.63 21.54 1.12 1.14 36.21 23.94 0.100 0.200 1.490 0.094 19.39 128
Brazil&to&S.&Africa 61 127.5 118.5 81.19 26.11 19.04 0.53 26.50 1.94 1.45 36.21 23.82 0.100 0.100 1.390 0.036 11.45 116
Brazil&to&S.&Africa 62 128.0 115.6 86.67 22.37 24.96 0.53 23.99 1.77 1.42 36.51 23.80 0.096 0.243 1.041 0.035 14.70 152
Brazil&to&S.&Africa 63 129.0 19.9 66.99 14.43 24.89 0.65 29.61 1.80 1.29 36.04 23.32 0.093 0.274 1.075 0.063 23.09 26
Brazil&to&S.&Africa 64 129.7 15.6 75.92 17.95 19.20 0.59 35.94 1.81 1.92 36.10 22.74 0.150 0.330 0.770 0.040 12.40 108
Brazil&to&S.&Africa 65 130.1 13.1 79.77 19.29 24.55 0.63 26.68 1.83 1.61 35.98 22.90 0.170 0.243 1.041 0.034 25.18 104
Brazil&to&S.&Africa 66 130.8 0.8 80.44 15.81 20.19 0.54 29.98 2.03 1.63 36.10 22.80 0.180 0.360 0.670 0.060 22.01 74
Brazil&to&S.&Africa 67 131.3 3.7 84.79 16.33 17.97 0.60 37.35 2.05 1.73 35.79 21.67 0.110 0.340 1.310 0.041 12.65 78
Brazil&to&S.&Africa 68 131.8 6.8 76.80 13.36 22.04 0.65 38.39 2.15 1.80 35.77 21.37 0.130 0.435 1.040 0.058 14.09 82
Brazil&to&S.&Africa 69 132.8 12.7 82.51 18.13 21.37 0.77 39.93 2.19 1.84 35.47 20.91 0.140 0.520 0.930 0.064 37.06 56
162
Table B2 continues
NZ#to#Hawaii 70 ,34.0 ,176.0 85.50 22.85 20.73 1.08 8.74 1.67 0.63 35.38 21.37 0.101 0.040 0.190 0.192 19.01 72
NZ#to#Hawaii 71 ,22.8 ,178.1 90.15 24.68 25.53 0.98 10.55 1.55 0.73 35.29 27.07 0.070 0.040 0.150 0.194 18.16 106
NZ#to#Hawaii 72 ,19.2 ,176.1 109.82 26.42 29.72 1.03 14.66 1.70 0.81 34.56 28.96 0.040 0.030 0.100 0.183 43.04 94
NZ#to#Hawaii 73 ,16.4 ,174.8 82.39 18.77 23.98 0.94 11.97 1.70 0.49 34.44 29.55 0.040 0.160 0.190 0.101 17.48 108
NZ#to#Hawaii 74 ,14.2 ,173.7 102.68 17.79 29.71 0.26 8.18 1.87 0.60 34.93 29.66 0.090 0.030 0.180 0.086 20.96 122
NZ#to#Hawaii 75 ,12.9 ,173.1 97.24 17.54 27.52 0.26 8.08 1.79 0.48 35.19 29.63 0.128 0.926 0.751 0.063 19.84 96
NZ#to#Hawaii 76 ,9.0 ,171.9 95.71 18.61 25.56 0.27 13.62 1.41 1.00 35.25 29.53 0.128 0.926 0.751 0.101 5.78 86
NZ#to#Hawaii 77 ,7.6 ,171.6 109.21 15.80 30.08 0.21 8.23 1.92 0.78 35.48 28.92 0.050 0.070 4.754 0.067 7.05 116
NZ#to#Hawaii 78 ,6.2 ,171.0 108.29 23.69 29.40 0.29 11.92 2.30 0.76 35.37 28.75 0.103 0.593 5.326 0.180 20.83 76
NZ#to#Hawaii 79 ,3.6 ,169.6 73.52 17.58 28.77 0.37 12.77 2.71 0.38 35.37 28.56 0.310 2.380 1.360 0.193 18.92 78
NZ#to#Hawaii 80 ,2.2 ,168.8 115.25 18.69 25.86 0.36 13.02 3.24 0.82 35.36 27.93 0.250 2.760 1.350 0.219 37.16 50
NZ#to#Hawaii 81 1.0 ,167.2 92.93 19.75 34.26 0.51 15.45 2.07 0.60 35.08 27.65 0.110 0.593 1.610 0.313 27.04 8
NZ#to#Hawaii 82 3.0 ,166.1 122.66 24.89 30.40 0.54 18.84 1.82 0.64 34.99 28.00 0.230 1.620 1.270 0.353 50.62 8
NZ#to#Hawaii 83 6.8 ,164.5 93.64 20.03 33.34 0.46 15.23 2.12 0.75 34.81 27.75 0.030 0.370 0.860 0.281 37.42 22
NZ#to#Hawaii 84 8.6 ,163.7 99.48 16.95 24.81 0.49 9.27 1.69 0.60 34.84 27.39 0.030 0.060 0.700 0.293 12.10 74
NZ#to#Hawaii 85 13.8 ,161.4 101.48 15.91 23.57 0.56 8.35 2.02 0.56 34.54 25.99 0.140 1.036 5.478 0.078 9.69 140
NZ#to#Hawaii 86 21.3 ,157.9 81.41 25.65 20.20 1.11 19.92 2.09 0.65 34.73 25.05 0.020 0.070 0.640 0.160 21.01 166
Hawaii#to#Panama 87 21.3 ,157.9 81.41 25.65 20.20 1.11 19.92 2.09 0.65 34.73 25.05 0.020 0.070 0.640 0.160 21.02 166
Hawaii#to#Panama 88 21.7 ,154.2 85.70 26.26 19.54 0.60 4.18 1.19 0.49 34.94 24.93 0.160 0.080 2.240 0.186 33.98 134
Hawaii#to#Panama 89 21.4 ,152.5 85.46 22.00 18.77 0.47 11.92 2.25 0.72 34.53 24.41 0.080 0.030 0.750 0.093 19.68 110
Hawaii#to#Panama 90 20.9 ,149.1 86.31 4.56 23.13 0.45 2.96 1.28 0.59 34.58 24.28 0.099 0.040 0.420 0.167 9.99 124
Hawaii#to#Panama 91 20.6 ,146.5 82.97 11.48 29.17 0.22 0.91 1.72 0.23 34.84 23.72 0.121 0.094 0.742 0.104 18.63 138
Hawaii#to#Panama 92 19.9 ,142.0 82.45 17.93 28.51 0.28 8.55 1.86 0.58 34.62 23.79 0.180 0.020 1.080 0.234 16.43 130
Hawaii#to#Panama 93 19.4 ,139.5 81.59 12.99 28.69 0.13 3.78 0.86 0.24 34.79 22.76 0.130 0.250 0.700 0.096 19.39 122
Hawaii#to#Panama 94 18.9 ,137.1 72.76 16.41 16.60 0.20 8.41 2.19 0.49 34.69 23.20 0.150 0.110 0.790 0.148 14.13 116
Hawaii#to#Panama 95 17.6 ,131.5 83.20 10.32 22.69 0.26 5.38 1.30 0.47 34.84 22.06 0.110 0.070 0.610 0.175 10.55 112
Hawaii#to#Panama 96 16.8 ,128.3 83.38 15.67 14.77 0.16 3.92 0.99 0.27 34.69 23.18 0.150 0.100 0.810 0.215 13.01 102
Hawaii#to#Panama 97 15.9 ,124.6 91.47 14.33 22.89 0.20 8.09 1.86 0.52 34.67 23.84 0.130 0.160 0.800 0.435 21.33 56
Hawaii#to#Panama 98 15.5 ,122.9 83.96 6.38 25.44 0.32 1.95 1.47 0.50 34.52 24.60 0.050 0.170 0.100 0.254 10.92 124
Hawaii#to#Panama 99 14.7 ,119.5 81.85 6.08 24.77 0.13 2.41 1.55 0.18 34.37 25.28 0.060 0.504 0.812 0.206 24.51 90
Hawaii#to#Panama 100 13.8 ,115.8 92.53 15.19 22.84 0.32 8.55 1.87 0.51 34.20 26.67 0.050 0.070 0.280 0.183 17.99 90
Hawaii#to#Panama 101 13.4 ,113.9 72.39 14.10 12.10 0.25 3.65 1.26 0.32 34.05 28.48 0.126 0.485 0.720 0.346 21.02 76
Hawaii#to#Panama 102 12.2 ,108.9 86.72 7.81 26.65 0.16 6.90 0.93 0.32 34.12 28.61 0.170 0.410 0.540 0.319 43.61 66
Hawaii#to#Panama 103 11.4 ,105.4 73.79 10.20 19.98 0.27 8.51 1.60 0.57 33.62 28.71 0.156 0.485 1.204 0.453 28.36 32
Hawaii#to#Panama 104 11.0 ,103.2 82.77 12.24 19.50 0.11 10.30 0.78 0.44 33.44 29.69 0.170 0.130 0.470 0.185 21.70 38
Hawaii#to#Panama 105 10.2 ,99.7 69.56 16.83 21.17 0.70 18.75 2.04 0.71 33.85 29.46 0.160 0.220 0.860 0.367 53.78 38
Hawaii#to#Panama 106 9.6 ,97.0 89.83 14.90 10.26 0.62 7.84 0.96 0.35 33.94 28.97 0.150 0.140 1.080 0.525 47.68 20
Hawaii#to#Panama 107 8.9 ,94.0 102.36 20.38 26.33 0.94 10.80 1.73 0.59 34.33 28.14 0.230 2.940 3.630 0.215 44.16 28
Hawaii#to#Panama 108 8.4 ,91.3 92.01 20.13 22.48 0.57 11.85 1.59 0.49 34.24 28.57 0.230 0.380 3.000 0.210 82.68 28
Hawaii#to#Panama 109 7.5 ,88.7 88.47 14.85 21.89 0.50 7.66 1.29 0.49 34.16 28.18 0.200 3.530 2.330 0.358 31.38 8
Hawaii#to#Panama 110 6.2 ,85.3 84.19 20.56 18.75 1.05 8.32 0.75 0.49 33.14 28.01 0.100 0.210 1.060 0.312 33.01 46
163
Table B3. Analytical results of the analysis of nearshore seawater reference material
for trace metals CASS-5.
Table B4 – Comparison of the range and median values (in parentheses) of dissolved
nutrients with literature values from laboratory culture experiments, standardized to P.
Element Certified value Measurement result
Mo 9.59 ± 0.70 10.0 ± 0.06
Cd 0.0210 ± 0.0017 0.022 ± 0.0002
Pb 0.011 ± 0.002 0.0097 ± 0.0004
V 1.28 ± 0.14 1.30 ± 0.007
Fe 1.40 ± 0.11 1.47 ± 0.004
Co 0.093 0.10 ± 0.0002
Ni 0.322 ± 0.022 0.31 ± 0.003
Cu 0.371 ± 0.028 0.36 ± 0.001
!
164
Appendix C
Appendix C provides the supported information and data for chapter 4.
Table C1. Total dissolved and soluble trace metal concentrations measured in the San
Gabriel Control and Burned catchments. Samples from both San Gabriel catchments
(control and burned) were collected at 3 times during two storm events.
San$Gabriel$Control$and$Burned$catchments$(µg/L)
Metal Fraction T1 T2 T3 T1 T2 T3 T1 T2 T3 T1 T2 T3
Mo95(LR) Total 4.387 4.403 3.744 5.382 4.750 6.777 4.444 4.276 4.176 7.393 6.920 5.735
soluble 4.032 4.144 3.321 5.134 4.676 6.186 4.010 3.811 3.877 6.878 6.560 5.221
Cd111(LR) Total 0.070 0.068 0.064 0.106 0.089 0.092 0.088 0.074 0.088 0.081 0.099 0.098
soluble 0.059 0.055 0.051 0.092 0.074 0.082 0.075 0.063 0.072 0.069 0.082 0.087
Pb208(LR) Total 0.191 0.189 0.193 7.470 12.656 15.559 0.195 0.163 0.209 10.510 13.430 6.464
soluble 0.020 0.017 0.021 4.042 7.184 8.346 0.023 0.015 0.018 6.375 8.429 3.991
V51(MR) Total 1.428 1.413 1.401 4.785 5.263 5.032 2.092 2.292 2.148 5.390 5.052 5.023
soluble 1.348 1.264 1.298 4.702 5.144 4.973 1.956 2.200 2.103 5.192 5.002 4.872
Fe56(MR) Total 73.876 72.859 74.479 758.967 666.240 862.010 68.770 75.059 73.745 772.290 565.930 875.085
soluble 7.518 6.410 7.224 214.256 142.042 198.607 4.655 5.884 5.049 156.080 135.087 235.697
Co59(MR) Total 0.409 0.419 0.400 0.243 0.420 0.310 0.311 0.320 0.293 0.280 0.308 0.330
soluble 0.382 0.379 0.359 0.232 0.409 0.299 0.295 0.309 0.275 0.266 0.291 0.304
Ni60(MR) Total 1.345 1.147 1.962 4.373 3.217 1.461 2.257 1.966 3.080 2.107 3.105 1.992
soluble 1.134 0.891 1.572 3.862 2.892 1.318 1.884 1.559 2.400 1.849 2.860 1.861
Cu63(MR) Total 2.149 1.010 3.179 10.004 15.090 8.240 3.907 1.733 2.719 12.380 11.040 11.453
soluble 1.609 0.739 2.295 8.630 13.415 6.581 3.032 1.296 2.255 10.591 9.186 9.838
Zn64(MR) Total 8.892 7.292 11.096 30.293 36.374 37.629 13.290 10.724 11.488 27.043 31.301 32.936
soluble 7.576 6.548 10.142 27.797 34.559 36.737 12.519 10.199 10.349 25.163 29.708 31.864
Control$(first$rain$event) Burned$(first$rain$event) Control$(second$rain$event) Burned$(second$rain$event)
165
Table C2. Total dissolved and soluble trace metal concentrations measured in the Los
Angeles, San Gabriel and Santa Clara Rivers. Samples from the Los Angeles and San
Gabriel Rivers were collected during five different storm events (one sample per
storm). Samples from the Santa Clara River were collected during three different storm
events.
Urban&and&Control&Rivers&(µg/L)
Metal Fraction Storm&1 Storm&2 Storm&3 Storm&4 Storm&5 Storm&1 Storm&2 Storm&3 Storm&4 Storm&5 Storm&1 Storm&2 Storm&3
Mo95(LR) Total 13.100 10.200 9.900 12.500 11.900 11.300 10.200 8.600 9.300 10.500 6.540 5.760 4.300
soluble 11.672 8.843 8.682 11.300 10.258 10.309 9.519 8.173 8.576 9.961 5.864 5.185 3.893
Cd111(LR) Total 0.680 0.420 0.350 0.480 0.550 0.430 0.620 0.510 0.480 0.580 0.230 0.350 0.310
soluble 0.575 0.342 0.315 0.412 0.455 0.355 0.524 0.442 0.399 0.479 0.190 0.291 0.257
Pb208(LR) Total 4.800 5.100 2.800 8.800 7.100 4.638 5.900 2.200 3.809 7.920 1.034 0.900 1.600
soluble 0.706 0.890 0.331 1.495 1.066 0.825 0.852 0.432 0.432 1.735 0.081 0.113 0.256
V51(MR) Total 7.500 6.300 7.900 5.100 5.800 5.300 4.700 6.700 7.000 6.200 3.900 4.500 3.300
soluble 7.148 5.903 7.118 4.769 5.469 4.840 4.365 6.177 6.353 5.525 3.696 4.227 3.169
Fe56(MR) Total 461.000 552.200 659.500 470.000 744.900 472.967 578.240 383.010 388.290 482.930 105.967 93.870 113.540
soluble 27.265 44.839 31.062 42.408 30.690 16.053 31.432 4.909 15.675 13.534 5.082 5.097 8.781
Co59(MR) Total 1.100 0.870 0.950 0.730 0.810 0.670 0.580 0.860 0.710 0.630 0.450 0.320 0.490
soluble 1.033 0.793 0.857 0.698 0.768 0.605 0.539 0.807 0.636 0.556 0.410 0.299 0.454
Ni60(MR) Total 4.600 8.400 15.200 3.800 10.300 5.300 11.400 12.900 2.900 6.100 1.100 3.200 2.160
soluble 3.919 7.039 12.373 3.200 8.765 4.174 9.121 10.014 2.350 4.875 0.895 2.625 1.747
Cu63(MR) Total 14.350 15.670 15.250 16.080 13.350 9.004 15.090 7.240 11.380 10.040 1.856 4.730 3.270
soluble 11.395 12.560 12.450 12.212 10.551 7.033 12.489 5.911 8.837 8.611 1.479 3.532 2.487
Zn64(MR) Total 39.070 27.910 43.440 33.510 37.220 28.085 26.630 25.320 35.970 30.520 12.013 15.690 13.970
soluble 36.095 25.245 37.642 30.646 33.875 25.632 24.165 23.250 32.130 28.082 10.524 14.091 12.575
Los&Angeles&River San&Gabriel&River Santa&Clara&River
166
Appendix D
Appendix C provides the supported information and data for chapter 4.
Table D1. Dissolved Pb, and
206
Pb/
207
Pb,
208
Pb/
206
Pb isotope ratios measured in the
surface ocean during the circumnavigation expedition Malaspina 2010 from December
2010 to July 2011.
Transect Station Longitude Latitude 206Pb/207Pb 208Pb/206Pb concen.9(pM)
Colombia(to(Spain 2535 074.70 11.86 1.184 2.071 25.4
Colombia(to(Spain 2584 072.28 13.69 1.182 2.074 23.8
Colombia(to(Spain 2590 069.94 14.85 1.181 2.077 24.8
Colombia(to(Spain 2537 067.76 15.40 1.182 2.076 21.2
Colombia(to(Spain 2519 059.83 17.43 1.182 2.076 22.9
Colombia(to(Spain 2546 058.64 17.80 1.182 2.077 20.3
Colombia(to(Spain 2587 055.90 18.75 1.181 2.076 18.8
Colombia(to(Spain 2412 053.15 19.86 1.182 2.072 23.6
Colombia(to(Spain 2545 050.33 20.74 1.183 2.074 21.1
Colombia(to(Spain 2530 048.50 21.39 1.181 2.079 24.5
Colombia(to(Spain 2566 038.72 24.87 1.179 2.082 30.0
Colombia(to(Spain 2577 035.34 26.08 1.179 2.081 33.3
Colombia(to(Spain 2579 032.92 26.94 1.180 2.082 36.1
Colombia(to(Spain 2395 030.02 27.84 1.179 2.085 38.9
Colombia(to(Spain 2397 026.98 28.89 1.178 2.082 40.1
Colombia(to(Spain 2394 024.11 29.82 1.178 2.085 37.9
Colombia(to(Spain 2565 020.64 30.97 1.175 2.089 38.1
Colombia(to(Spain 2557 017.29 32.07 1.173 2.093 41.4
Spain(to(Brazil 2520 09.23 35.26 1.172 2.095 49.4
Spain(to(Brazil 2516 017.19 29.78 1.174 2.089 45.3
Spain(to(Brazil 2588 018.83 28.71 1.175 2.086 47.3
Spain(to(Brazil 2528 020.77 25.36 1.177 2.084 41.9
Spain(to(Brazil 2527 022.08 23.46 1.180 2.083 42.0
Spain(to(Brazil 2572 023.43 21.54 1.180 2.079 39.3
Spain(to(Brazil 2542 024.35 20.30 1.181 2.080 40.8
Spain(to(Brazil 2512 025.96 16.60 1.180 2.080 38.5
Spain(to(Brazil 2402 025.99 7.33 1.179 2.079 26.2
Spain(to(Brazil 2574 027.33 03.03 1.179 2.078 24.8
Spain(to(Brazil 2563 027.81 04.05 1.179 2.077 24.2
Spain(to(Brazil 2567 029.31 07.24 1.178 2.081 18.2
Spain(to(Brazil 2585 030.01 08.72 1.178 2.079 20.6
Spain(to(Brazil 2591 031.04 010.90 1.178 2.080 18.6
Spain(to(Brazil 2580 032.35 013.66 1.177 2.080 16.8
Spain(to(Brazil 2586 033.09 015.16 1.176 2.081 19.5
Spain(to(Brazil 2534 035.73 020.59 1.176 2.079 17.3
Spain(to(Brazil 2576 036.70 024.23 1.176 2.077 18.3
167
Table D1 continues
Brazil'to'S.'Afica 2576 336.70 324.23 1.176 2.077 18.3
Brazil'to'S.'Afica 2564 333.47 324.78 1.179 2.076 19.9
Brazil'to'S.'Afica 2559 330.16 325.41 1.176 2.082 17.4
Brazil'to'S.'Afica 2558 328.41 325.72 1.175 2.081 15.5
Brazil'to'S.'Afica 2393 324.53 326.41 1.171 2.087 13.5
Brazil'to'S.'Afica 2562 322.23 326.81 1.169 2.096 12.1
Brazil'to'S.'Afica 2592 318.51 327.47 1.174 2.085 14.4
Brazil'to'S.'Afica 2573 315.60 327.98 1.169 2.096 11.6
Brazil'to'S.'Afica 2398 39.92 328.97 1.168 2.086 10.4
Brazil'to'S.'Afica 2403 35.55 329.72 1.166 2.098 13.8
Brazil'to'S.'Afica 2589 33.05 330.14 1.168 2.094 12.7
Brazil'to'S.'Afica 2568 0.83 330.85 1.169 2.093 11.4
Brazil'to'S.'Afica 2515 3.72 331.29 1.164 2.101 14.0
Brazil'to'S.'Afica 2523 6.85 331.82 1.161 2.099 16.8
Brazil'to'S.'Afica 2575 12.65 332.78 1.162 2.102 18.8
Indian3ocean 2494 27.54 334.84 1.150 2.112 28.1
Indian3ocean 2424 31.11 334.44 1.150 2.110 26.5
Indian3ocean 2488 33.66 334.17 1.149 2.114 20.6
Indian3ocean 2428 37.06 333.85 1.150 2.113 19.0
Indian3ocean 2425 39.87 333.52 1.146 2.115 20.0
Indian3ocean 2415 43.30 333.19 1.148 2.115 18.7
Indian3ocean 2495 63.57 327.85 1.148 2.117 19.0
Indian3ocean 2426 66.48 328.17 1.149 2.117 18.0
Indian3ocean 2490 69.85 329.34 1.147 2.119 19.7
Indian3ocean 2532 73.07 329.64 1.148 2.112 17.4
Indian3ocean 2589 76.19 329.90 1.147 2.117 20.0
Indian3ocean 2416 79.61 329.80 1.146 2.119 21.4
Indian3ocean 2417 97.17 329.61 1.142 2.121 22.6
Indian3ocean 2497 100.00 329.89 1.141 2.122 26.1
Indian3ocean 2496 103.88 330.39 1.139 2.124 28.0
Indian3ocean 2427 107.25 330.81 1.139 2.122 31.2
Indian3ocean 2414 110.86 331.17 1.137 2.126 32.1
Indian3ocean 2533 114.22 331.65 1.134 2.127 37.1
168
Table D1 continues
New$Zeland$to$Hawaii 2413 2176.02 233.98 1.156 2.111 15.1
New$Zeland$to$Hawaii 2518 2178.06 222.85 1.158 2.108 13.0
New$Zeland$to$Hawaii 2521 2176.13 219.18 1.157 2.104 17.6
New$Zeland$to$Hawaii 2419 2174.78 216.45 1.159 2.106 16.7
New$Zeland$to$Hawaii 2522 2173.70 214.22 1.160 2.109 14.9
New$Zeland$to$Hawaii 2536 2173.09 212.89 1.161 2.107 18.8
New$Zeland$to$Hawaii 2547 2171.86 29.01 1.162 2.105 17.2
New$Zeland$to$Hawaii 2411 2171.58 27.59 1.161 2.104 19.6
New$Zeland$to$Hawaii 2406 2171.00 26.21 1.161 2.099 24.3
New$Zeland$to$Hawaii 2423 2169.57 23.60 1.163 2.098 27.9
New$Zeland$to$Hawaii 2531 2168.81 22.17 1.164 2.103 24.8
New$Zeland$to$Hawaii 2418 2167.18 0.98 1.165 2.097 24.4
New$Zeland$to$Hawaii 2507 2166.13 3.00 1.167 2.093 27.8
New$Zeland$to$Hawaii 2513 2164.45 6.79 1.166 2.096 28.3
New$Zeland$to$Hawaii 2529 2163.67 8.64 1.167 2.097 27.9
New$Zeland$to$Hawaii 2514 2161.37 13.77 1.165 2.095 31.5
New$Zeland$to$Hawaii 2407 2157.86 21.27 1.164 2.095 30.0
Hawaii$to$Panama 2407 2157.86 21.27 1.164 2.095 30.0
Hawaii$to$Panama 2501 2154.19 21.69 1.167 2.097 31.5
Hawaii$to$Panama 2404 2152.53 21.45 1.165 2.096 30.2
Hawaii$to$Panama 2550 2149.09 20.89 1.167 2.094 29.7
Hawaii$to$Panama 2551 2146.55 20.56 1.166 2.094 27.0
Hawaii$to$Panama 2405 2141.99 19.94 1.166 2.095 24.6
Hawaii$to$Panama 2561 2139.48 19.41 1.168 2.091 22.2
Hawaii$to$Panama 2505 2137.07 18.86 1.168 2.095 25.6
Hawaii$to$Panama 2552 2131.49 17.59 1.169 2.092 20.8
Hawaii$to$Panama 2502 2128.32 16.82 1.169 2.091 22.9
Hawaii$to$Panama 2503 2124.61 15.94 1.169 2.088 19.0
Hawaii$to$Panama 2549 2122.90 15.52 1.171 2.089 17.7
Hawaii$to$Panama 2548 2119.46 14.70 1.170 2.089 22.9
Hawaii$to$Panama 2506 2115.83 13.82 1.169 2.088 17.3
Hawaii$to$Panama 2499 2113.94 13.36 1.171 2.087 18.7
Hawaii$to$Panama 2578 2108.89 12.18 1.171 2.089 20.7
Hawaii$to$Panama 2498 2105.39 11.42 1.172 2.086 19.2
Hawaii$to$Panama 2560 2103.23 10.96 1.170 2.089 21.2
Hawaii$to$Panama 2396 299.67 10.18 1.170 2.088 25.6
Hawaii$to$Panama 2544 296.97 9.60 1.171 2.086 27.9
Hawaii$to$Panama 2508 293.97 8.94 1.171 2.086 26.9
Hawaii$to$Panama 2500 291.32 8.36 1.172 2.086 28.4
Hawaii$to$Panama 2543 288.73 7.55 1.172 2.085 31.9
Hawaii$to$Panama 2553 285.33 6.19 1.174 2.082 33.8
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Pinedo Gonzalez, Paulina
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Concentration and size partitioning of trace metals in surface waters of the global ocean and storm runoff
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Geological Sciences
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