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Hamburger Bodenkundliche ArbeitenHamburger Bodenkundliche Arbeiten
Verein zur Förderung der Bodenkunde Hamburgc/o Institut für Bodenkunde - Universität Hamburg
https://www.geo.uni-hamburg.de/de/bodenkunde.html
HBA
B
and
101 Band 101
2021
2021
ISSN: 0724-6382
Mathias Spieckermann
Controls of Oxygen Consumption of Sediments in the Upper Elbe Estuary
The Author Mathias J. Spieckermann was born in Eutin. He studied geoecology at the Technical University of Braunschweig with a focus on soil science and environmental modeling.In his master thesis, he reproduced a new system for the decentralized treatment of wastewater in the laboratory and developed a 2-D model for the simulation of solute fluxes in this system. During his PhD thesis he focused on the oxygen consumption potential (OCP) of sediments from the upper Elbe estuary. He investigated the spatial and seasonal variability of the OCP and developed a predictive model to calculate the oxygen consumption of resuspended sediments.
M. S
piec
kerm
ann
Controls of Oxygen Consumption
of Sediments in the
Upper Elbe Estuary
Dissertation
with the aim of achieving a doctoral degree
at the Faculty of Mathematics,
Informatics and Natural Sciences
Department of Earth Sciences
at Universität Hamburg
Submitted by
Mathias Johannes Spieckermann
From Eutin, Germany
Hamburg, 2021
Accepted as Dissertation at the Department of Earth Sciences.
Reviewers: Prof. Dr. Annette Eschenbach
Dr. Alexander Gröngröft
Date of Disputation: 15 April 2021
Chair of the subject doctoral committee: Prof. Dr. Dirk Gajewski
Dean of Faculty of MIN: Prof. Dr. Heinrich Graener
Published as
Hamburger Bodenkundliche Arbeiten, Volume 101
Editor: Verein zur Förderung der Bodenkunde Hamburg
Allende‐Platz 2, 20146 Hamburg
Editorship: Dr. Klaus Berger
https://www.geo.uni‐hamburg.de/en/bodenkunde/ueber‐das‐institut/hba.html
3
Preface
I would like to thank all those who stood by me during my doctoral thesis, supported me and
helped me to focus on the essentials. Without your help, I would not have made it this far.
Special thanks go to my supervisors Annette Eschenbach and Alexander Gröngröft, who
made my work possible. From the very beginning, they supported me with words and deeds.
I especially want to thank Monika Voß, Deborah Harms, Birgit Grabellus, Birgit Schwinge
and Sumita Rui for their great support in the laboratory and their friendly and helpful manner.
The many analyses and experiments performed in the laboratory would not have been
possible without your help.
Also, special thanks to Volker Kleinschmidt, who helped me with the design and setup of
my experiments and always had a solution to my technical problems.
I would also like to thank Kay‐Christian Emeis, who accompanied my work in the course
of the School of Integrated Climate System Sciences, for the interesting and stimulating
discussions.
Further, I would like to thank Stephan Schwank and Rolf Lüschow, who supported me
during the numerous samplings on the Elbe River.
I would like to thank Maja Karrasch and Julia Gebert for the nice collaboration and
stimulating discussions.
I also want to thank Liz, Miriam, Adrian, Alex, Jona and Lars for the many fruitful
discussions and their moral support and the whole Institute of Soil Science for the nice working
atmosphere. I felt comfortable with you guys from the first day and I will miss you.
To all my family, Marten and Timo I would like to thank you for always believing in me
and always finding encouraging words for me. I would also like to give a very special thank you
to my wife Christin, whom I met and fell in love with here, as she supported and cheered me
up throughout the entire time.
I would also like to thank my wife Christin, whom I met and fell in love with here at the
institute, as she supported and cheered me up throughout the entire time.
This study was funded by the Hamburg Port Authority.
4
Publications related to this Dissertation
Appendix Publication A
Oxygen consumption of resuspended sediments of the upper Elbe estuary: Process
identification and Prognosis.
M.J. Spieckermann, A. Gröngröft, M. Karrasch, A. Neumann, A. Eschenbach
Submitted to Aquatic Geochemistry on 17 January 2021.
Appendix Publication B
Oxygen consumption of resuspended sediments of the upper Elbe estuary: Spatial and
temporal dynamics.
M.J. Spieckermann, A. Gröngröft, M. Karrasch, A. Eschenbach
Submitted to the Journal of Soils and Sediments on 11 September 2020.
Appendix Publication C
Temperature dependent oxygen consumption of sediments of the upper Elbe estuary.
M.J. Spieckermann, A. Gröngröft, A. Eschenbach.
Submitted to Estuaries and Coasts on 14 April 2021.
5
Contents
Preface ........................................................................................................................................ 3
Publications related to this Dissertation .................................................................................... 4
List of Abbreviations ................................................................................................................... 8
Abstract ...................................................................................................................................... 9
Zusammenfassung .................................................................................................................... 11
1 Introduction ...................................................................................................................... 13
1.1 Sediments as Sinks of Oxygen .................................................................................... 13
1.2 Spatial and Seasonal Variability ................................................................................. 15
1.3 The Upper Elbe Estuary .............................................................................................. 16
1.4 Oxygen Concentration in the Elbe Estuary ................................................................ 17
2 Objectives of the Study ..................................................................................................... 19
3 Material and Methods ...................................................................................................... 21
3.1 Sampling Approaches ................................................................................................. 21
3.2 Development of an Oxygen Consumption Model ..................................................... 23
4 Summary of Key Results .................................................................................................... 25
4.1 Sediment Characteristics ........................................................................................... 25
4.2 OCP of the Sediments ................................................................................................ 25
4.3 Seasonal Dynamic ...................................................................................................... 27
4.4 Spatial Variability ....................................................................................................... 28
4.5 Prognosis Model ......................................................................................................... 28
4.6 Oxygen Consumption under Stable Conditions ......................................................... 29
5 Outlook and Implications .................................................................................................. 31
Appendix publication A ........................................................................................................... 35
Oxygen Consumption of Resuspended Sediments of the Upper Elbe Estuary: Process
Identification and Prognosis ..................................................................................................... 35
A.1 Introduction ............................................................................................................... 36
A.2 Material and Methods ............................................................................................... 38
A.2.1 Study Site and Sampling ................................................................................. 38
A.2.2 Sediment Characterisation ............................................................................. 39
6
A.2.3 Oxygen Consumption ..................................................................................... 39
A.2.4 Calculation of Oxidation Reactions ................................................................ 40
A.2.5 Development of an Oxygen Consumption Model .......................................... 41
A.3 Results ........................................................................................................................ 41
A.3.1 Characterisation of the Sediments ................................................................. 41
A.3.2 OCP ................................................................................................................. 43
A.3.3 Stoichiometric Analysis and Correlations....................................................... 45
A.3.4 Development of an Oxygen Consumption Model .......................................... 47
A.3.5 Validation of the Oxygen Consumption Model .............................................. 51
A.4 Discussion ................................................................................................................... 54
A.4.1 Sediment Composition ................................................................................... 55
A.4.2 OCP and Stoichiometric Analysis .................................................................... 55
A.5 Conclusion .................................................................................................................. 57
Appendix publication B ........................................................................................................... 59
Oxygen Consumption of Resuspended Sediments of the Upper Elbe Estuary: Spatial and
Temporal Dynamics .................................................................................................................. 59
B.1 Introduction ............................................................................................................... 60
B.2 Material and Methods ............................................................................................... 62
B.2.1 Study Site and Sampling ................................................................................. 62
B.2.2 Sediment Characterisation ............................................................................. 64
B.2.3 OCP ................................................................................................................. 64
B.3 Results ........................................................................................................................ 65
B.3.1 Oxygen Dynamics in the Water Phase ........................................................... 65
B.3.2 Temporal Dynamics of Sediment Characteristics .......................................... 66
B.3.3 Temporal Dynamics of OCP ............................................................................ 68
B.3.4 Spatial Variability of OCP ................................................................................ 70
B.4 Discussion ................................................................................................................... 72
B.4.1 Temporal Dynamic ......................................................................................... 72
B.4.2 Spatial Variability ............................................................................................ 74
B.5 Conclusion .................................................................................................................. 75
7
Appendix publication C ........................................................................................................... 77
Temperature‐Dependent Oxygen Consumption of Sediments of the Upper Elbe Estuary ..... 77
C.1 Introduction ............................................................................................................... 78
C.2 Material and Methods ............................................................................................... 80
C.2.1 Sampling and Basic Analyses .......................................................................... 80
C.2.2 High Resolutions Oxygen Concentration Profiles .......................................... 81
C.3 Results ........................................................................................................................ 82
C.3.1 Sediment Characteristics ................................................................................ 82
C.3.2 Oxygen Concentration Profiles ...................................................................... 82
C.3.3 Oxygen Consumption Rates ........................................................................... 84
C.4 Discussion ................................................................................................................... 85
C.5 Conclusion .................................................................................................................. 87
References ................................................................................................................................ 89
8
List of Abbreviations
Ctotal Total Carbon
MSL Mean Sea Level
NRMSE Normalized Root Mean Squared Error
Ntotal Total Nitrogen
OCP Oxygen Consumption Potential
OCP168 Oxygen Consumption Potential after 168 h of Incubation
RMSE Root Mean Squared Error
SOD Sediment Oxygen Demand
TOC Total Organic Carbon
9
Abstract
This thesis deals with sediments and their influence on the oxygen balance of the tidal Elbe
River. The study area is the upper Elbe estuary, including the Port of Hamburg. In this area,
minimal oxygen content zones are frequently formed during the summer months, where the
oxygen content falls below the critical value of 3 mg O2 l‐1 for fish. The biogeochemical
processes that lead to this oxygen depletion are well known in the water phase. However, the
influence of sediments with their spatially and temporally variable composition on the oxygen
balance is largely unknown. The way sediments consume oxygen varies. Under resuspension,
large amounts of oxygen‐consuming substances are quickly released into the water phase and
can negatively affect the oxygen balance. Under stable conditions, oxygen diffusely penetrates
the sediment surface and is slowly but continuously consumed in the oxic sediment layer.
The aim of this thesis is to clarify how strong the sediment‐induced influence on oxygen
consumption is, which processes play a major role in this and how much the sediments and
their oxygen consumption potential (OCP) differ on a spatial and seasonal level during
resuspension. In two approaches, the spatial and seasonal variability of sediment composition
and OCP during sediment resuspension was determined. In a third approach, the oxygen
consumption of sediments under stable conditions and its temperature dependence was
determined.
The OCP was quantified by seven‐day incubation experiments, in which the sediment
samples were kept in resuspension. To identify the oxygen‐consuming sub‐processes, the CO2
formed, and the pore water concentration of relevant anions and cations were determined
before and after the experiments. From this information, the most important oxygen‐
consuming sub‐processes could be distinguished, and their respective shares of the total
oxygen consumption were calculated stoichiometrically. Based on the analysed sediment
properties and the quantified sub‐processes, we developed a prognosis model that predicts
the OCP of sediments by using a single key parameter. In order to assess the oxygen
consumption of sediments under stable conditions, high‐resolution oxygen depth profiles
were recorded for the first time on sediment cores from three sites in the upper Elbe estuary.
Within the upper Elbe estuary, the sediments showed a high spatial and seasonal
variability in their composition and OCP. Towards the North Sea, the OCP of the sediments
decreased, which can be attributed to a reduced input of fresh biomass in combination with
a decrease in the degradability of the organic matter. The OCP of the sediments varied
spatially between 0.005 and 0.967 mmol O2 g d.wt.‐1 and was up to 5.5 times higher in
summer than in winter. This seasonality was also evident in the pore water composition with
an enrichment of ammonium and a decrease in sulphate concentration in summer, due to
more reduced conditions. Spatially, the highest OCP and chlorophyll concentrations were
recorded in the transition zone between the shallow and the deeper and navigable
downstream area of the harbour. Looking at the OCP of the sediments during a seven‐day
resuspension event, the spatial variability was greater than the seasonal variability. Oxygen
consumption under stable conditions showed a clear increase with temperature, with one of
10
the three samples characterised by a higher temperature effect due to a lower TOC/Ntotal ratio
of the sample, indicating a more easily degradable biomass. The input and degradability of
fresh biomass in conjunction with seasonal changes such as sediment and pore water
composition along with bacterial productivity/biomass control the oxygen consumption under
stable conditions.
The results from the spatial and seasonal analysis showed that the OCP of the sediments
during a seven‐day resuspension event is controlled by the concentration of fresh organic
matter. As a proxy for the fresh organic matter, we used the concentration of chlorophyll in
the sediment. The total chlorophyll concentration showed the highest correlation with the
OCP, followed by Ntotal and TOC. The most important biogeochemical processes involved in
oxygen consumption during a resuspension event were identified as the rapid biochemical
oxidation of reduced compounds (Fe2+, Mn2+, and sulphur compounds like H2S, FeS, FeS2), the
nitrification (mean velocity) and the slower mineralisation of organic matter. Based on these
findings, a model was developed that predicts the oxygen consumption of the sediments of
the upper Elbe estuary with only one sediment parameter (Ntotal). The developed prediction
model is well suited to calculate the oxygen consumption of resuspended sediments in the
Hamburg harbour area during the relevant warmer months (NRMSE <0.11 ± 0.13).
The results of this extensive spatial and seasonal observation of the OCP of sediments
improve the understanding of the role of sediments and their influences on the oxygen budget
in the Port of Hamburg. The knowledge gained should now be integrated into water quality
models. This will make it possible to better assess the effects of major resuspension events,
such as water injection dredging, and serve the development of measures to reduce the
environmental impact of maintenance measures in the Port of Hamburg. The next step should
be to transfer the point data to the area, combined with further sampling to capture the
distribution of sediment properties in a more detailed form. This can be accompanied by
additional oxygen consumption measurements under stable conditions aiming to enlarge the
data set and to correlate the oxygen consumption to sediment properties.
The results showed that the sediments have a high potential to affect the Elbe River's
oxygen budget negatively. For the future, questions arise with regard to the resuspension time
of different sediment types and how the combination of the spatial distribution of the
sediment properties together with the different maintenance measures influence the oxygen
balance of the tidal Elbe. Moreover, how strong the influence of oxygen consumption of
sediments is under stable conditions and how the influence of the above‐mentioned
processes could change because of global climate change.
11
Zusammenfassung
Diese Arbeit beschäftigt sich mit Sedimenten und deren Einfluss auf den Sauerstoffhaushalt
der Tideelbe. Im Untersuchungsgebiet, dem oberen Elbeästuar einschließlich des Hamburger
Hafens, bilden sich in den Sommermonaten häufig Sauerstoffminimumzonen aus, in denen
der Sauerstoffgehalt unter den für Fische kritischen Wert von 3 mg O2 l‐1 fällt. Die
biogeochemischen Prozesse in der Wasserphase, die zu diesem Sauerstoffdefizit führen, sind
bereits erforscht. Welchen Einfluss aber die Sedimente mit ihrer räumlich und zeitlich
variablen Zusammensetzung auf den Sauerstoffhaushalt haben, ist weitestgehend unbekannt.
Sedimente können bei Resuspension schnell große Mengen sauerstoffzehrender Stoffe in die
Wasserphase abgegeben und somit die Sauerstoffbilanz unmittelbar negativ beeinflussen.
Unter stabilen Bedingungen hingegen, dringt der Sauerstoff diffus in die Sedimentoberfläche
ein und wird in der oxischen Sedimentschicht langsam, aber kontinuierlich verbraucht.
Ziel dieser Arbeit ist es, exemplarisch für das obere Elbeästuar zu erfassen, wie groß der
sedimentbedingte Einfluss auf den Sauerstoffverbrauch ist, welche sauerstoffzehrenden
Prozesse eine wesentliche Rolle spielen und wie stark sich die Sedimente und ihr
Sauerstoffzehrungspotential (OCP) während einer Resuspension auf räumlicher und
saisonaler Ebene unterscheiden. In zwei Messkampagnen wurde die räumliche und saisonale
Variabilität der Sedimentzusammensetzung und des OCP während der Resuspension von
Sedimenten erfasst. In einem dritten Untersuchungsansatz wurde die Temperatur‐
abhängigkeit der Sauerstoffzehrung von Sedimenten unter stabilen Bedingungen bestimmt.
Zur Quantifizierung des OCP wurden siebentägige Inkubationsversuche, bei denen
Sedimentproben in Resuspension gehalten wurden, durchgeführt. Um die sauerstoff‐
zehrenden Teilprozesse zu identifizieren, wurden das gebildete CO2 und die Porenwasser‐
konzentration relevanter An‐ und Kationen vor und nach den Experimenten bestimmt.
Anhand dieser Informationen konnten die wichtigsten sauerstoffzehrenden Teilprozesse
unterschieden und ihre jeweiligen Anteile am gesamten Sauerstoffverbrauch stöchiometrisch
berechnet werden. Auf dieser Grundlage wurde ein Prognosemodell zur Berechnung des OCP
entwickelt. Zur Erfassung des Sauerstoffverbrauches von Sedimenten unter stabilen
Lagebedingungen, wurden erstmalig hochauflösende Sauerstofftiefenprofile an Sediment‐
kernen von drei Standorten aus dem oberen Elbästuar erfasst.
Die Sedimente wiesen innerhalb des oberen Elbeästuars eine hohe räumliche und
saisonale Variabilität in ihrer Zusammensetzung und im OCP auf. In Richtung Nordsee nahm
das OCP der Sedimente ab, was auf einen verringerten Eintrag von frischer Biomasse in
Kombination mit einer Abnahme der Abbaubarkeit der organischen Substanz zurückgeführt
werden kann. Das OCP der Sedimente variierte räumlich zwischen 0,005 und 0,967 mmol O2 g
TS‐1 und war im Sommer bis zu 5,5‐mal höher als im Winter. Diese Saisonalität zeigte sich auch
in der Porenwasserzusammensetzung mit einer Anreicherung von Ammonium und einer
Abnahme der Sulfatkonzentration im Sommer, aufgrund stärker reduzierter Bedingungen.
Räumlich wurden die höchsten OCP und Chlorophyllkonzentrationen in der Übergangszone
zwischen dem flachen und dem tieferen und schiffbaren stromabwärts gelegenen Bereich des
12
Hafens erfasst. Betrachtet man das OCP der Sedimente während eines siebentägigen
Resuspensionsereignisses, so war die räumliche Variabilität größer als die saisonale. Die
Sauerstoffzehrung unter stabilen Bedingungen zeigte einen deutlichen Anstieg mit der
Temperatur, wobei eine der drei Proben durch einen höheren Temperatureffekt aufgrund
eines niedrigeren TOC/Ntotal‐Verhältnisses der Probe gekennzeichnet war, was auf eine
leichter abbaubare Biomasse hinweist. Der Eintrag und die Abbaubarkeit von frischer
Biomasse in Verbindung mit den saisonalen Veränderungen, wie der Sediment‐ und
Porenwasserzusammensetzung und der bakteriellen Produktivität/Biomasse, steuern die
Sauerstoffzehrung unter stabilen Bedingungen.
Die Ergebnisse aus der räumlichen und saisonalen Analyse zeigten, dass das OCP der
Sedimente, während eines siebentägigen Resuspensionsereignisses, durch die Konzentration
frischer organischer Substanz gesteuert wird. Die Chlorophyllkonzentration im Sediment dient
dabei als Indikator für die frische organische Substanz und zeigte die höchste Korrelation mit
dem OCP der Sedimente, gefolgt vom Ntotal und TOC Gehalt. Als wichtigste biogeochemische
Prozesse, die an der Sauerstoffzehrung während eines Resuspensionsereignisses beteiligt
sind, wurden die schnelle biochemische Oxidation von reduzierten Verbindungen (Fe2+, Mn2+
und Schwefelverbindungen wie H2S, FeS, FeS2), die Nitrifikation (mittlere Geschwindigkeit)
und die langsamere Mineralisierung von organischem Material identifiziert. Basierend auf
diesen Befunden wurde ein Modell entwickelt, dass mit nur einem Sedimentparameter (Ntotal)
den Sauerstoffverbrauch der Sedimente des oberen Elbeästuars prognostiziert. Das
entwickelte Prognosemodell ist gut geeignet, den Sauerstoffverbrauch von resuspendierten
Sedimenten im Hamburger Hafengebiet während der relevanten wärmeren Monate zu
berechnen (NRMSE <0,11 ± 0,13).
Die gewonnenen Erkenntnisse sollten nun in Wassergütemodelle integriert werden.
Damit können Auswirkungen von größeren Resuspensionsereignissen, wie zum Beispiel beim
Wasserinjektionsverfahren, besser bewertet werden und der Entwicklung von Maßnahmen
zur Reduzierung der Umweltauswirkungen von Unterhaltungsmaßnahmen im Hamburger
Hafen dienen. Um im nächsten Schritt die Übertragung der Punktdaten auf die Fläche zu
ermöglichen, sollte die räumliche Verteilung der Sedimenteigenschaften im oberen Elbeästuar
in einer höher aufgelösten Form erfasst werden. Einhergehend kann der Datensatz zur
Sauerstoffzehrung unter stabilen Bedingungen durch zusätzliche Untersuchungen erweitert
werden, um so aussagekräftige Korrelationen zwischen dem Sauerstoffverbrauch und den
Sedimenteigenschaften unter diesen Bedingungen zu erhalten.
Die Ergebnisse zeigen, dass die Sedimente ein hohes Potential haben den
Sauerstoffhaushalt der Elbe negativ zu beeinflussen. Für die Zukunft stellen sich die Fragen,
wie die Kombination von räumlicher Verteilung der Sedimenteigenschaften und die
unterschiedlichen Unterhaltungsmaßnahmen den Sauerstoffhaushalt der Tideelbe, zum
Beispiel über die Dauer der Resuspension, beeinflussen, wie stark der Einfluss der
Sauerstoffzehrung von Sedimenten unter stabilen Bedingungen ist und wie sich infolge des
globalen Klimawandels der Einfluss der oben genannten Prozesse verändern wird.
13
“The saddest aspect of life right now is that
science gathers knowledge faster than society gathers wisdom”
–Isaac Asimov–
1 Introduction
The availability of dissolved oxygen is a prerequisite for an intact aquatic ecosystem. It directly
affects the biological health of river systems (Williams and Boorman 2012) and is used as an
indicator for the quality of surface water bodies (Cude 2001, Bayram et al. 2015). As the most
abundant electron acceptor, oxygen has a major influence on the sulphur, nitrogen,
phosphorus, and carbon cycles and influences the metabolic processes taking place in the
sediment (Glud 2008). The water body’s oxygen content is the result of oxygen‐consuming
and oxygen‐supplying processes. Atmospheric inputs and the oxygen‐supplying
photosynthesis of algae enrich the water with oxygen. Oxygen‐consuming processes, such as
the mineralisation of organic matter, respiration, or the oxidation of reduced compounds lead
to a reduction of oxygen. An imbalance between oxygen‐supplying and oxygen‐consuming
processes leads to oxygen depletion, which occurs in coastal waters and estuaries worldwide
(Morris et al. 1982; Sarma et al. 2013; Su et al. 2017). In the worst case, the oxygen
concentration falls below critical values and leads to aquatic life's mortality. The appearance
of this imbalance is a problem that seems to be growing globally (Díaz and Rosenberg 2008,
Gilbert et al. 2010) and in relation to climate change it is unclear how this will affect the
different types of estuaries (Bruce et al. 2014).
The oxygen consumption in estuaries takes place both in the water phase and in the
sediment. Depending on their composition, sediments can have a strong influence on the
oxygen balance of water bodies. They can act as an oxygen sink by removing oxygen from the
water phase through oxygen‐consuming processes within the sediment or as a source of
oxygen‐consuming substances that enter the water phase through diffuse fluxes or by
resuspension. The upper Elbe estuary, as a highly dynamic system, serves as the study area to
answer the open questions regarding the oxygen consumption properties of sediments.
1.1 Sediments as Sinks of Oxygen
Sediments can be regarded as a kind of archive that by their composition reflect the prevailing
environmental conditions under which they were formed. Their composition is influenced by
several factors, such as their location, sedimentation rates, flow velocities, temperature, and
the input of organic biomass. Due to the high number of different factors, sediments can differ
immensely from one another, leading to a strong spatial and temporal variability in oxygen
consumption from sediments. According to Veenstra and Nolen (1991), sediment oxygen
demand (SOD) is defined as the rate of oxygen consumption, biologically or chemically, on or
in the sediment at the bottom of a water body. The SOD combines two main oxygen sinks:
(i) the sediment oxygen uptake by aerobic mineralisation of organic matter as well as
oxidation of reduced substances and (ii) the flux of reduced substances out of the sediment
14
(Steinsberger et al. 2019). Barcelona (1983) and Rong and Shan (2016) divided the SOD into
chemical oxidation of dissolved iron, manganese, hydrogen sulphide/sulphur, and into
biochemical oxidation of ammonium and nitrite to nitrate, in addition to the mineralisation of
organic matter and respiration.
In the case of SOD, a distinction must be made between oxygen consumption at stable
conditions and consumption at resuspension caused by a disturbance of the sediment surface.
Under stable conditions, SOD is diffusion limited. Oxygen diffusely penetrates the sediment.
The thickness of the oxic zone can range from a few mm in organic rich sediments (Sweerts et
al. 1989) to several cm (Wenzhöfer et al. 2001) in sandy sediments. The penetration depth is
regulated by the organic carbon degradation, the oxygen concentration of the water, and the
transport of oxygen from the water phase into the sediment, whereby the sediment porosity
and the diffusion coefficient of oxygen plays a role (Cai and Sayles 1996). If oxygen is no longer
available for the energy metabolism, other electron acceptors take over its part (suboxic and
reduced zone). As a result of the diagenetic processes, the sediment and pore water
accumulates with reduced compounds from the anaerobic metabolism (Figure 1).
Figure 1: A schematic illustration of some significant diagenetic processes in sediments (Adapted
according to Glud 2008).
The SOD during resuspension is the sum of multiple processes driven by the oxygen supply,
the biochemical processes taking place, and the sediment properties. The oxygen
consumption potential (OCP) of sediments becomes apparent during their resuspension, as
there is a sudden release of all solid sediment components and the pore water. The release of
reduced compounds such as iron, manganese, or hydrogen sulphide leads to rapid
biochemical oxygen consumption. Ammonium, as the end product of the anaerobic
degradation of organic matter, accumulates in the pore water and is released during
resuspension. The nitrification that then occurs consumes 4.57 gram of oxygen per gram of
ammonium (Wezernak and Gannon 1967). Sedimented organic matter is released and is
available for aerobic mineralisation. In organic rich sediments, oxygen is the only limiting
factor and the OCP can be seen as a function of the electron acceptors (Bryant et al. 2010).
15
Almroth et al. (2009) and Sloth et al. (1996) showed in their experiments that a resuspension
of sediments causes a local and temporary increase of reduced inorganic compounds and
organic matter within the water, which enhances the oxygen consumption.
Resuspension of sediments takes place in both limnic and marine areas worldwide. It
occurs when the shear stress is high enough to transport sediment particles into the water
column (Almroth et al. 2009). This critical shear stress can be exceeded by natural forces such
as tidal currents, wind, and biological activities (Sanford et al. 1991; Graf and Rosenberg 1997),
or by human activities such as ship induced waves (Schoellhamer 1996) and dredging
operations (Cappuyns et al. 2006).
For an assessment of human activities on a water body's oxygen balance, models that
combine physical and biochemical processes can be used. However, a shortcoming of many
numerical models that include biochemical processes at the sediment‐water interface is that
they are unable to model the resuspension of sediments and its effect on oxygen and nutrient
dynamics (Moriarty et al. 2018). Therefore, it is of high interest to quantify the impact of
resuspended sediments to improve water quality modelling.
1.2 Spatial and Seasonal Variability
The influence of sediments on the oxygen balance of water bodies is mainly controlled by their
composition. As already mentioned, many different factors control the composition of the
sediments. If one wants to know more about the ability of sediments to consume oxygen, the
prevailing hydrographic conditions and the distances to potential sources of input play an
important role. Sedimentation rates, flow velocities, and accumulation of organic material
depend on these factors. The particle size distribution is influenced by the flow velocity and
thus the input of organic matter. A reduction in flow velocity leads to an increased
sedimentation of finer particles and thus to an accumulation of organic material that is
associated with the fine‐grained fraction (de Haas et al. 2002; Giles et al. 2007). This leads to
a change in the composition of the sediments and consequently to a variability in the ability
to consume oxygen. In addition to this rigid spatial structure, the sediments also differ on the
temporal scale. Due to seasonal variations in temperature, discharge rates, sedimentation
rates, and algal biomass development, the sediment is subject to a constant change. Besides,
precipitation and the resulting runoff lead to an input of terrestrial organic material. A change
in water temperature has a direct influence on the oxygen saturation and controls the activity
of the micro‐ and macrofauna. Many sediment properties have been found to correspond with
SOD, such as sediment organic matter, nitrogen, pigments (chlorophyll a, phaeopigment a,
total carotenoids), as well as the water depth and spatial location of the sediments (Vidal et
al. 1992; Duineveld et al. 1997; Grant et al. 2002; Giles et al. 2007; Mügler et al. 2012). In
addition, water temperature shows a positive correlation with SOD (Hopkinsion et al. 2001;
Fulweiler et al. 2010). Many authors have reported a seasonal variability in SOD, with an
increase in summer and a decrease in winter in rivers and coastal sediments (Rasmussen and
Jørgensen 1992; Rysgaard et al. 1995; Hopkinsion et al. 2001; Akomeah and Lindenschmidt
2017). This summer‐winter difference is explained by changes in the biological activity and a
16
variation in the input of labile organic matter such as dead settled algae. These facts make it
obvious that sediments are subject to spatial and seasonal dynamics. However, little is known
about the spatial and seasonal variability of the SOD and sediment parameters that control
the sediment oxygen consumption.
As this study deals with the variability of sediments, the lower Elbe estuary serves as the
selected study region. Due to the Port of Hamburg, the tidal influence, and its location in a
climate zone with distinct seasons, the upper Elbe estuary is a spatially and temporally variable
system. This results in a system of differently composed sediments, each with different oxygen
consumption properties, which is necessary to answer the existing questions.
1.3 The Upper Elbe Estuary
The upper Elbe estuary (Germany), characterized by fresh water from the Middle Elbe,
stretches from the weir Geesthacht (stream‐km 586) 46 km downstream to Wedel (stream‐
km 541) and includes the large area of the Port of Hamburg (Figure 2). Between stream‐km
609 and 626, the Elbe forms an inland delta with the Northern Elbe and the Southern Elbe as
its major branches. With the start of the trafficability for ocean vessels at about stream‐km
619 (Southern Elbe) and stream‐km 624 (Northern Elbe), the fairway's depth and the harbour
basins have been increased from 2.7 m to 15 m below MSL.
The hydrology of the upper Elbe estuary is spatially and temporally dynamic. Flow
velocities vary strongly between the fairway and the rear parts of harbour basins. Due to low‐
flow areas or differences in cross‐flow sections, hot spots of sedimentation occur. Particulate
organic matter originates from the Middle Elbe and the North Sea and is mixed in varying
proportions within the upper estuary depending on the headwater discharge (Gröngröft et al.
1998; Kleisinger et al. 2015; Reese et al. 2019). Additionally, seasonal changes in temperature
and phytoplankton concentration prevail. Therefore, it is assumed that this variability
influences the oxygen demand of the Hamburg port sediments.
Figure 2: Port of Hamburg with the Northern and Southern Elbe, which form the inland delta (source:
www.bing.com/maps/).
17
The Port of Hamburg is the largest seaport in Germany and the third‐largest in Europe. Seen
from the mouth of the Elbe, it lies 110 km east in the country's interior. With 136.6 million
tonnes of cargo handled in 2019 (Port of Hamburg 2020), the port's primary use is cargo
handling. An essential aspect of the management of the harbour is to ensure the navigable
depth of the Elbe. This falls under the task of the Hamburg Port Authority (HPA).
Due to high sedimentation rates in the fairways and adjacent harbour basins in the
Hamburg port area each year an amount of 1.7 to 6 million tons (as dry substance) must be
dredged to keep the fairway navigable (2010–2018; Hamburg Port Authority unpublished
data). For this purpose, different systems such as Hopper dredging, bed levelling, and water
injection are used in the Elbe estuary. During hopper dredging operations, sediments are
sucked up from the riverbed and dumped back into the water column at the respective
disposal site. Bed levellers use a plough to relocate the sediment without raising it into the
water column. Water injection application uses nozzles to pump water directly onto the
sediment. The remobilised sediments are then transported away from the site of operation
by the current. These procedures are subject to various regulations. At specific oxygen
concentrations in the river water, they are prohibited in order to prevent the oxygen content
from falling to critical levels. Due to the critical oxygen concentration in summer in the upper
estuary, the disposal of sediments is restricted to the winter months. In other not oxygen‐
depleted areas, such as the outer estuary and the North Sea, disposal of Elbe sediments is also
carried out in summer. In the tidal Elbe, it is restricted below 6 mg O2 l‐1 and prohibited below
5 mg O2 l‐1 in order to avoid oxygen depletion due to sediment disposal (BfG 2008). Water
injection applications are used with restrictions in summer and are prohibited at an oxygen
concentration of below 4 mg O2 l‐1 (Hamburg Port Authority 2018).
1.4 Oxygen Concentration in the Elbe Estuary
In the upper part of the Elbe estuary with the Port of Hamburg and all its harbour basins, a
strong decline in dissolved oxygen concentrations is frequently observed during the summer
months (Figure 3) (Bergemann et al. 1996; Schroeder 1997; Schöl et al. 2014) regularly
reaching critical values of less than 3 mg O2 l‐1.
Before the fall of the Iron Curtain, large quantities of oxygen‐consuming and toxic
substances were discharged into the Elbe. This resulted in the fact that the minimum oxygen
concentration of 3 mg O2 l‐1 required for fish in the tidal Elbe was frequently not reached
(Figure 3). Such oxygen minimum zones resulted in regularly occurring fish mortality. After
reunification, the closure of factories and the installation of wastewater treatment plants led
to an improvement in the tidal Elbe's oxygen content (Bergemann et al. 1996; Sanders et al.
2017). Despite an improvement, there is still the formation of oxygen minimum zones within
the tidal Elbe. Due to the high nutrient content of the relatively shallow Middle Elbe, strong
algae masses are formed in spring and summer. These algae are transported to the navigable
depth of the tidal Elbe. Due to turbulent transport, they reach the lightless, deeper zone, and
oxygen is first consumed by respiration and then by their decomposition. Therefore, these
oxygen minimum zones are mainly attributed to algal respiration and carbon degradation
18
(Schroeder 1997) as well as zooplankton grazing (Schöl et al. 2014). Kerner (2000) also came
to the conclusion that microbial oxygen consumption, coupled with the degradation of freshly
transported organic material from the upper stream, controls the oxygen concentration in the
warmer seasons. Schroeder (1997) postulated that nitrification and sediment processes are of
minor relevance, while Sanders et al. (2017) found a substantial increase in nitrification in the
Hamburg area in spring and summer. Therefore, mineralisation and respiration have a strong
influence on oxygen consumption in the water phase. Studies in other rivers have shown that
the oxygen consumption of sediments can be the major source of water column oxygen
depletion (Boynton and Kemp 1985; Rutherford et al. 1991; Matlock et al. 2003; MacPherson
et al. 2007). So far, sediment driven oxygen consumption is less investigated in the Hamburg
harbour area. It is not possible to make any quantitative statements about the influence of
the Hamburg harbour sediments on the oxygen budget of the Elbe. Especially with regard to
the regularly occurring oxygen minimum zones in the upper Elbe estuary, it is not yet clear
what role the sediments have in this.
Figure 3: Daily mean values of oxygen concentration at the Hamburg‐Seemannshöft measuring station
1982 – 2006 (Adapted according to ARGE ELBE / FGG ELBE 2007).
As a result of the global climate change, the influence of the processes mentioned above is
likely to change. In order to better understand the influence of different dredging activities
and the possible effects of climate change on sediment composition and thus on the SOD, it
is essential to identify the individual parameters and processes that influence the oxygen
consumption by sediments.
19
2 Objectives of the Study
As described in the previous sections, the effective and potential oxygen consumption of
sediments is composed of different sub‐processes and is controlled by the properties of the
water body and the sediment composition. With regard to the sediments of the upper Elbe
estuary, the following questions arise:
‐ Which biochemical processes control the OCP of sediments?
‐ What is the share of the main biochemical processes?
‐ Which sediment properties control the involved biochemical processes?
Due to the economic importance of the Port of Hamburg, its waterways must be maintained
regularly. This can lead to a resuspension of the sediments, resulting in a decrease in the water
phase's oxygen concentration. Being able to estimate the influence of resuspended sediments
on the basis of individual sediment parameters would help to optimize maintenance measures
and to reduce the risk to the aquatic environment. Therefore, next question is:
‐ Is it possible to predict the OCP of sediments from known sediment parameters?
As the Port of Hamburg is located in a climate zone with distinct seasons, there are strong
seasonal dynamics in terms of temperature, precipitation, solar radiation, and the runoff
between summer and winter. As a result, there is a seasonal change in sediment composition
and SOD. In order to determine the influence of this seasonality on the sediments and their
OCP, the following question has to be answered:
‐ What seasonal changes occur with regard to the composition and the OCP of
sediments?
Due to the structure of the Port of Hamburg, with its different harbour basins, water depths,
tidal influences, cross‐sections, distance to the Middle Elbe, and the resulting flow velocities
and sedimentation rates, was a further question:
‐ How does the OCP vary spatially?
Previous research questions have dealt with resuspended sediments and the processes and
sediment parameters that control the potential oxygen consumption. Besides the effect of
resuspension, where the shear resistance must be overcome so that the sediment
components pass into the water phase, sediments also consume oxygen when they are under
stable conditions. The oxygen consumption of sediments at stable conditions takes place
independently of external disturbances and can therefore be regarded as a continuous
process. For the upper Elbe estuary, no studies are available so far that use high‐resolution
oxygen depth profiles to investigate the oxygen consumption of sediments at stable
conditions. The temperature dependence and sediment composition and its influence on the
20
oxygen consumption of sediments at stable conditions was, therefore, the focus of the next
questions.
‐ How much oxygen is consumed from the sediments under stable conditions?
‐ How much does temperature control the SOD?
21
3 Material and Methods
In this thesis, the oxygen consumption of sediments in the upper Elbe estuary was determined
and investigated by three approaches (Figure 4). The first approach focused on the spatial
variability of sediment composition and oxygen consumption during resuspension (OCP). The
second approach aimed to determine the seasonal dynamics of sediment composition and
oxygen consumption during resuspension (OCP), and the third approach investigated the
oxygen consumption of sediments at stable conditions (SOD).
3.1 Sampling Approaches
During the first approach to study the spatial variability, sediments from 21 sites in the upper
Elbe estuary were investigated (Figure 5, P1‐P21). The sampled area extended from the
easternmost point Stover Strand (stream‐km 589) to the westernmost point at the sediment
trap Wedel (stream‐km 643). Samples in the area of the Hamburg harbour were taken both in
the fairway and at the entrances of the harbour basins and their ends. The sampling was
carried out from 2017‐06‐30 to 2017‐07‐04. To characterise the influence of sediment age,
these samples were divided into two age categories: <2 years and >2 years. For an estimation
of the age of the sediments, the data of the last maintenance dredging at the sites were taken
into account. In addition, the load of trace elements was taken into account, which has been
decreasing over time in the Elbe since the 1990s (HPA, unpublished document 2019).
In order to answer the research questions on seasonal dynamics, monthly samples were
taken at a single location for a period of two years from December 2016 to November 2018
(2nd approach). To ensure that the sediment composition represents the current
environmental conditions, we selected a location with a known high sedimentation rate. This
condition applies to the entrance area of the Hansahafen (Figure 5, P10). This area is
characterized by a widening of the cross section of the Northern Elbe, where increased
sedimentation rates occur with the formation of a mud lens. At the edge of the mud lens
sedimentation rates are reported to be up to 2 cm day‐1 and up to 9 cm day‐1 in the centre of
the lens. Consequently, dredging activities in this area are quite frequent.
Samples were taken from a ship with a core sampler (Frahm‐Lot, length 80 cm, inner
diameter 10 cm). In both approaches, the layers of 0‐20 cm and 40‐60 cm were analysed.
Seven‐day incubation experiments served to determine the OCP of the sediments. Typical
sediment parameters such as organic carbon content (TOC), total nitrogen content (Ntotal) or
grain size distribution were determined. A more detailed overview of the methodological
design is given in Figure 4.
22
Figure 4: Schematic overview of the study design including sampling, preparation of samples in the
laboratory, and the analysis performed.
23
Figure 5: Sampling locations within the upper Elbe estuary and the Port of Hamburg. Black dots
represent the sampling locations between river km 589 (P1) and 643 (P21) to analyse the spatial
variability. Point P10 refers to the access area of the Hansahafen for the analysis of the seasonal
dynamic. The circles represent the sampling locations for the analysis of oxygen consumption of
sediments under stable conditions. From the left: Köhlfleet, Hansahafen, and the Fairway Norderelbe
(source of map: unpublished and adapted data from Hamburg Port Authority).
To quantify the individual processes (biochemical oxidation of reduced compounds and
nitrification) involved in oxygen consumption, the concentrations of sulphate, nitrate, nitrite,
iron, and manganese were determined before and after the incubation experiments. By the
change of concentration, the respective proportions of the individual processes in the oxygen
consumption was calculated stoichiometrically. The proportion of mineralisation in the
oxygen consumption was deduced from the measured amount of CO2, that has been formed
during the incubation experiments.
In a 3rd approach, samples from three locations were taken (Figure 5 circles). These
samples were used to investigate the oxygen consumption of sediments under stable
conditions with high resolution oxygen depth profiles (Berg et al. 1998). The measurements
were carried out at 5 °C, 15 °C, and 25 °C to determine the temperature effect on SOD under
stable conditions. The sample at the location Hansahafen was taken on 2018‐04‐20, the
sample at the location Köhlfleet on 2018‐06‐23, and the sample at the location Fairway
Norderelbe on 2018‐08‐28.
3.2 Development of an Oxygen Consumption Model
To develop a model for OCP calculation, we used the following approach: (i) The cumulative
oxygen consumption curves of the samples from the 1st approach were divided into three
24
phases that characterize the biogeochemical chain of processes. The respective curves of the
individual phases were fitted. (ii) The resulting parameters of the fitting functions of all
samples were correlated with the sediment properties. This resulted in six linear or nonlinear
regression equations between sediment properties and fitting parameters. Using the
sediment properties, we were able to calculate the six parameters per sample, which allowed
us to calculate the oxygen consumption and their involved processes along the timeline. For
all samples, the normalized root mean squared error (NRMSE) between measured and
modelled oxygen consumption was calculated. (iii) To validate the model, the samples from
the 2nd approach were used. Using the sediment properties, the six parameters per sample
were determined, and the oxygen consumption was calculated and compared with the
measured oxygen consumption. Thus, the accuracy of the model could be quantified.
25
4 Summary of Key Results
4.1 Sediment Characteristics
The study of Elbe estuary sediments reveals that the properties of the analysed samples from
all three approaches varied strongly. For instance, the sand content of the samples from the
spatial analysis (1st approach) ranged between 1.1 and 99.2%‐d.wt. and the amount of fine
grained particles (<20 µm) ranged from 0.8 to 89.0%‐d.wt. The TOC, which is a relevant driver
for the oxygen demand, ranged between 0.2%‐d.wt. and 6.3%‐d.wt. and showed a high
positive correlation with the grain size fraction <20 µm (rsp = 0.780; p <0.01). Location 4
showed the highest TOC content with 6.3%‐d.wt, the highest chlorophyll concentration
(1100.9 µg g d.wt.‐1), and the lowest TOC/Ntotal ratio (7.3) and is located in the transition zone
where the fairway is deepened for oceangoing vessels.
The samples from the temporal analysis at the position Hansahafen (2nd approach)
showed less variation in their composition. The TOC content varied between 1.3 and
3.9%‐d.wt., the TOC/Ntotal ratio lies between 7.2 and 9.8, the chlorophyll concentration ranged
from 49.4 to 257.7 µg g d.wt.‐1, and the grain size fraction <20 µm ranged from 17.1 to 73.7%‐
d.wt. The maximum values for TOC, Ntotal, chlorophyll, and the grain size fraction <20 µm were
found during the summer months combined with the lowest TOC/Ntotal ratio.
The sediment characteristics of the 3rd approach differed strongly from each other but
are within the range mentioned above. Of the three location, the sediment at the location
Köhlfleet showed the highest TOC content (4.1%‐d.wt.) and the highest content of the grain
size fraction <20µm (78.8%‐d.wt.). The sediment at the location Fairway Norderelbe had the
lowest TOC/Ntotal ratio (8.1). TOC, Ntotal, and the grain size fraction <20 µm of this sample were
in the range between the other two sites.
4.2 OCP of the Sediments
The input of fresh organic matter controls the OCP of the sediments during a seven‐day
resuspension. The sediment parameters total chlorophyll, Ntotal, and TOC had the most
significant influence on the OCP of the sediments. This applies to the data set from spatial
analysis and to the data set from the seasonal analysis. In both data sets, the total chlorophyll
concentration showed the highest correlation with the OCP, followed by Ntotal.
From the measured cumulative oxygen consumption curves and the calculated oxygen
consumption rates it can be seen that several processes control the oxygen consumption of
the sediments during resuspension. This is indicated by the shape of the curves. The curves
can be divided into three phases, which are distinguished by a decrease in the consumption
rate (Figure 6). The processes that control these phases are subject to different kinetics and
sources of educts. A reduction in the consumption rate occurs when a corresponding source
is depleted.
The three sub‐processes were identified as: (i) The biochemical oxidation of reduced
compounds (Fe2+, Mn2+, and sulphur compounds like H2S, FeS, and FeS2), (ii) the nitrification
of ammonium to nitrate, and (iii) the mineralisation of organic matter (Figure 6). Within the
26
first hours (Phase 1), the consumption rate is highest and is dominated by the oxidation of
reduced compounds. After consuming the corresponding educts, the rate decreases, and the
nitrification (Phase 2) controls the oxygen consumption. If ammonium is no longer available,
the oxygen consumption rate decreases a second time substantially, and the consumption is
controlled by the mineralisation of organic matter (Phase 3). That the assumptions about the
processes are correct showed a Spearman correlation between the measured oxygen
consumption and the stoichiometrically calculated oxygen consumption, which gave a
Spearman correlation coefficient (rsp) of 0.960 (p<0.05) for the 1st approach and a rsp of 0.966
(p<0.05) for the 2nd approach.
Figure 6: Example of the oxygen consumption rate and the cumulative oxygen consumption curve for
seven‐day resuspension event. The oxygen consumption is divided into three phases. Phase 1 = The
biochemical oxidation of reduced compounds (blue), Phase 2 = nitrification of ammonium (orange),
Phase 3 = mineralisation of organic matter (red).
The proportions of the processes in the total oxygen consumption were spatially and
temporally different and were controlled by the sediment composition and age. In general,
the mineralisation showed the largest share of the total consumption if one considers an
incubation period of seven days (168 h). The proportions of biochemical oxidation of reduced
compounds and nitrification varied widely and may account for more than half of the seven
days oxygen consumption. However, it must be considered that these results refer to a long
incubation period. With decreasing incubation time, the proportion of mineralisation in the
total consumption also decreases. A statistical evaluation showed no significant differences
between the layers, the locations (fairway, entrance, and end areas of the harbour basins),
and the calculated process proportions involved in the OCP. There was only a significant
difference within the proportions of the processes in sediments older or younger than two
years. Sediments older than two years consumed more oxygen through the biochemical
oxidation of reduced compounds (Figure 7). Nitrification and mineralisation showed lower
27
proportions of the total consumption. This can be attributed to the age of the organic material.
During degradation, labile organic compounds are preferentially degraded, which leads to a
selective decrease in the reactivity of the organic material over time (Arndt et al. 2013).
Additionally, with ongoing anaerobic degradation of organic matter sulphate respiration leads
to an accumulation of reduced sulphur compounds (FeS or FeS2), resulting in a higher
proportion in the total oxygen consumption.
Figure 7: Schematic illustration of the sediment age‐related changes in sediment composition and the
resulting changes in the percentages of the sub‐processes involved in OCP during an incubation period
of 168 hours.
4.3 Seasonal Dynamic
In the laboratory, samples from the summer months showed an OCP up to 5.5 times higher
than samples from the winter (Figure B 6). Seasonal dynamics in water temperature, in the
water's oxygen content, or in the formation of algal blooms influence the sediment and pore
water composition and the OCP of the sediments. Increased water temperatures lead to a
reduction of the solubility of oxygen in the water and to increased microbiological activity. As
a result, this causes a change in the pore water composition due to more reduced conditions.
The porewater is therefore enriched with ammonium (decomposition of organic matter) and
reduced sulphur compounds such as H2S, FeS and FeS2 (sulphate reduction). A resuspension
leads to an increased oxygen consumption by releasing these substances. A reduction in
headwater discharge results in an increased sedimentation of finer particles and thus to an
accumulation of organic material associated with the fine‐grained fraction (de Haas et al.
2002; Giles et al. 2007). The increased algae masses also lead to an enrichment of the
sediment with fresh, easily degradable algae biomass. The chlorophyll concentrations varied
from 50 to 250 µg g d.wt.‐1 between winter and summer (Figure B 7). As a result, the
28
sediments are enriched with Ntotal, which leads to a tighter TOC/Ntotal ratio in summer. What
fits well into the overall picture is that the quotient between the measured oxygen
consumption and the TOC content of the sediments was subject to a seasonal dynamic (Figure
B 7). The results showed that more oxygen per gram TOC is consumed in summer, indicating
a change in the organic matter's degradability.
4.4 Spatial Variability
The upper Elbe estuary had a strong spatial variability regarding the OCP (Figure B 9) and
sediment parameters. The lowest OCP was determined at site 7 with 0.005 mmol O2 g d.wt.‐1
and an almost 200‐fold higher value was determined at site 4 with 0.967 mmol O2 g d.wt.‐1.
Both sites were strongly contrasting in terms of TOC, chlorophyll, and sand content. Clear
statements about the spatial behaviour of the OCP of sediments between the different sites
(fairway, entrances, and the end of different harbour basins) cannot be made since the
number of samples is too small. However, certain spatial statements can be made. The OCP
of the sediments showed a decrease with increasing stream‐km (Figure B 9). This results from
a reduced input of fresh biomass (distance to the Middle Elbe increases) combined with a
decrease in the degradability of the organic mass, as described by Zander et al. (2020). The
transition zone from the shallower (2.7 m below MSL) to the deeper area (15 m below MSL)
of the Port of Hamburg leads to an increased accumulation of dead algae. The increased water
depth creates a larger lightless area in the water, which causes the death of the algae
(Schöl et al. 2014). Accordingly, the sediments are enriched with fresh algal biomass, which
leads to an increase in OCP. The distance from possible sources of oxygen‐consuming
substances and labile organic matter input controls the OCP of sediments on a spatial scale.
4.5 Prognosis Model
To improve predictions and water quality models, we developed a model that calculates the
OCP of sediments based on the Ntotal content. Together with the chlorophyll content, the Ntotal
content showed the highest correlations with the OCP of the sediments for both
measurement approaches. For the model Ntotal was selected because it is one of the standard
parameters in sediment analysis and this parameter is also measurable in the lower sediment
layers. The prediction model describes the three processes involved in oxygen consumption.
The biochemical oxidation of reduced compounds and the mineralisation of organic matter
are described by first order degradation functions and the nitrification by a constant rate with
a certain duration. The respective function parameters are calculated by means of established
correlations and the Ntotal content of the sediments. The prognosis model was developed using
the data from the 1st approach and validated using the data from the 2nd approach. A linear
regression between the modelled and measured oxygen consumption showed a good fit with
an R2 of 0.840 (1st approach) and an R2 of 0.818 (2nd approach) for an incubation period of
168 h. Figure 8 shows an example of a comparison between the measured oxygen
consumption and the oxygen consumption derived from the prediction model with its
29
individual components. The total oxygen consumption results from the sum of the individual
processes and can be calculated for any time of resuspension.
Figure 8: Comparison between measured and predicted oxygen consumption calculated from the
prognosis model based on the Ntotal content of the sample. The model calculates the oxygen
consumption based on the biochemical oxidation of reduced compounds (SO42‐‐formation), the
nitrification of ammonium, and the mineralisation of organic matter. The sum results in the total
oxygen consumption of the sample.
For shorter resuspension times of 3 h and 24 h the model also provided good adjustments
(Figure A 5). For both approaches, the R2 was greater than 0.784. The slope of the regression
line ranged between 0.609 and 1.152, which can lead to an overestimation or underestimation
of the total oxygen consumption. The results from the 2nd approach showed a clear difference
in the adjustment between the winter and summer samples. The summer samples showed a
lower scatter and smaller NRMSE than the winter samples. This difference can be attributed
to seasonal processes that are not covered by our model. The activity and composition of the
microbial community, the quality of the organic matter or a changed TOC/Ntotal ratio can lead
to the differences. Nevertheless, the model provides a good basis to calculate the OCP of
sediments in the relevant warm season and thus to determine the influence of increased
quantities of resuspended sediment.
4.6 Oxygen Consumption under Stable Conditions
A clear temperature dependence can be seen in the oxygen consumption of sediments under
stable conditions (Figure C 3). With increasing temperature, the oxygen penetration depth
decreased, and the oxygen consumption rates increased, which is consistent with other
studies (Seiki et al. 1994; Hancke and Glud 2004; de Klein et al. 2017). The rising temperature
also increases the microbial activity (McDonnell 1969), which leads to higher metabolism
rates. However, the temperature effect was smaller than expected (10‐degree rule), since the
30
decrease of the penetration depth also reduces the sediment volume and thus the number of
organisms involved in oxygen consumption.
Seasonality in the sediment composition of the upper millimetres and the input of fresh
organic material seems to have a greater effect on oxygen consumption rates than the spatial
variability. The Köhlfleet site had a TOC and Ntotal content twice as high as the Hansahafen site,
with both sites showing similar oxygen consumption rates. The sample with the largest
temperature change was taken in August 2018 (Fairway Norderelbe). The TOC and Ntotal
contents of this sample were between those of the other two samples, but the August sample
had the lowest TOC/Ntotal ratio. A low TOC/Ntotal ratio indicates fresh and easily degradable
organic matter. In addition, higher temperatures in August can lead to more anoxic conditions,
which enriches the sediment pore water with more reduced compounds. Furthermore,
Therkildsen and Lomstein (1993) also found out that the sediment macrofauna biomass
correlates positively with temperature. Van Duyl and Kop (1994) found no seasonal changes
in the microbial biomass, but an increased productivity of the bacteria in August compared to
February. Therefore, the spatial distribution of TOC and Ntotal and its influence on oxygen
consumption rates may be of less importance and seasonal changes are of larger relevance.
Therefore, an increased productivity and or biomass may be the reason for a higher SOD under
stable conditions at the location Fairway Norderelbe, as sampling took place in August.
The measured SOD values are consistent with the results of other authors, where SOD
represents more than 50% of the total oxygen consumption in the water phase. This indicates
that the sediments could have a strong influence on the oxygen balance of the Elbe water.
However, in the studies mentioned, the SOD was determined by chamber incubation
experiments and not by oxygen microprofiles. A comparison of different methods (chamber
incubation with total oxygen uptake and oxygen microprofiles) for the determination of SOD
showed that oxygen microprofiles can lead to an underestimation of total SOD (Kim and Kim
2007). Glud et al. (1994) showed in their experiments that the total oxygen uptake was 1.2 to
4.2 times higher than the diffuse oxygen consumption. Rasmussen and Jørgensen (1992) also
found that the total oxygen uptake was on average 145 % higher than the consumption
calculated from the microprofiles. Both studies explained the difference with the presence of
benthic macrofauna and that the total oxygen uptake is strongly related to ventilation and
respiration by macrofauna. In contrast, in the absence of macrofauna, measurements of total
oxygen uptake and microprofiles lead to similar results (Rasmussen and Jørgensen 1992).
31
5 Outlook and Implications
For the first time, a detailed study of the sediment oxygen consumption in the estuarine
harbour of Hamburg was conducted. The aim was to record the spatial and seasonal variability
of the sediment oxygen consumption and their dependency on sediment properties precisely
and to estimate the influence of the sediments on the oxygen balance of the Elbe water. The
background of these investigations was the frequent occurrence of oxygen minimum zones in
the upper Elbe estuary, where the basic oxygen‐consuming processes in the water phase are
known, yet the influence of the sediments was still unclear. The obtained results help to
improve the understanding of the influence of sediments on the oxygen budget of the upper
Elbe estuary and to better estimate possible effects of human activities such as ship traffic and
maintenance measures in the harbour.
In the Elbe estuary, the variability of the OCP of sediments under resuspension is – in
addition to the hydrographic conditions – mainly controlled by the input of fresh organic
matter and the changed redox condition due to a change in water temperature and oxygen
concentration. At one monitoring site, the summer sediment samples showed a 5.5‐fold
higher OCP than the winter samples. Likewise, lower discharge rates and higher algae activities
in summer lead to an increase in sedimentation of finer and more reactive particles. It has to
be taken into account that the seasonal effect of resuspension of sediments is even larger as
quantified in the laboratory, as here the temperature is kept constant, whereas in the river in
winter the lower water temperature reduces the oxidation processes additionally. We found
a high spatial variability in the sediment composition within the Port of Hamburg. Thus, an
extrapolation of the local findings to the whole area of the upper estuary was not possible.
For this aim, a mapping of the sediment properties is a prerequisite. However, we found a
longitudinal gradient in the OCP of the sediments, whereby the OCP decreases with increasing
stream‐km. In addition, spatial changes can serve as a hot spot for the enrichment of the
sediments with fresh organic matter, which leads to a high OCP of the sediments.
Based on our laboratory findings, three processes with varying kinetics control the oxygen
consumption within seven days of sediment resuspension: The fast biochemical oxidation of
reduced compounds, the nitrification of ammonium to nitrate with a mean velocity, and the
slow mineralisation of organic matter. The total oxygen consumption strongly correlated with
the chlorophyll content, Ntotal and TOC content of the sediment. Based on these results, we
developed a prognosis model that allows us to calculate the OCP of the sediments during
resuspension based on a single sediment parameter (Ntotal). The model was created using data
from summerly sediment samples of different origin and was validated with the two‐years
data of the samples of one position. It calculates the respective proportions of the three
oxygen‐consuming processes and the total consumption for any desired resuspension time
within seven days. The model shows a good adjustment during the critical months (April to
August) for the oxygen budget, while the OCP of the winter samples is less well fitted. We
explained this by the fact that the data set used for the development of the model was
collected in summer. Accordingly, the sediment properties are characterized by summer
conditions. During winter times, the OCP is generally smaller and thus the difference between
32
measurements and model estimates is relatively larger. The model provides good results for
the crucial summer period (April to August), where oxygen minimum zones occur. However,
there is still a lack of data to improve the forecast for the winter months. For this, additional
data would have to be collected in winter and then used to refine the model. For the critical
month of the year, we have developed a tool that helps us to calculate the oxygen
consumption of resuspended sediments with only basic knowledge of sediment properties.
This allows improving water quality models, since many numerical models do not consider the
influence of resuspension (Moriarty et al. 2018). Especially in port areas, where large
quantities of sediment are dredged and resuspended, it can be of great interest to calculate
the possible impact of these measures on the environment and to include seasonal variation
to prevent negative effects.
Oxygen consumption also takes place under stable conditions. To our knowledge, this is
the first time that high‐resolution oxygen depth profiles have been measured in sediment
cores from the Hamburg harbour area to determine the oxygen consumption of sediments
under stable conditions. The results showed that under these conditions sediments have a
high potential to remove oxygen from the water phase. The temperature showed a clear
influence on the oxygen consumption. In addition, the seasonal influence on the SOD under
stable conditions seems to be of greater relevance than the spatial influence due to more
input of organic matter, higher microbial activity, and more reduced conditions in summer.
Oxygen consumption during resuspension is a time‐limited process (usually a few hours),
which can exceed the oxygen consumption at stable conditions multiple times. The increased
oxygen consumption potential results from the sudden release of oxygen‐consuming
compounds (e.g. from sulphur, nitrogen, and iron) when the sediment is disturbed. Under
stable conditions in contrast, the oxygen consumption rate is lower but takes place
continuously and can therefore have a strong influence on the oxygen balance.
Both experimental approaches to determine the oxygen consumption of sediments
during resuspension provide a small differently selected view on the role of sediments on the
oxygen consumption. The oxygen consumption during resuspension gives information about
the oxygen consumption potential when the sediment is disturbed. Oxygen consumption
determined by high resolution oxygen depth profiles tells us how strong the sediment's
biochemical oxygen consumption is but neglects the respiration of fauna living in the
sediment. This oxygen consumption can be determined by chamber experiments. For a
complete consideration and differentiation of the oxygen consumption of sediments, the
consumption by the oxic sediment layer (oxygen depth profiles), the consumption of the
sediment surface including the respiration of fauna (chamber incubation), the consumption
during resuspension of sediments, and the oxygen consumption in the water phase must be
taken into account. Only this clear distinction enables us to obtain a more detailed idea of the
effects of sediments on the oxygen balance of the Elbe River water.
We were able to answer our research questions regarding the OCP of sediments in the
upper Elbe estuary and their controlling factors. To integrate this knowledge into practise,
three steps seem to be relevant:
33
The first step is to transfer the knowledge gained from the point data to the whole
area of the upper estuary by mapping the sediment properties. This step is necessary
to improve the understanding of local maintenance measures on possible effects on
the oxygen budget. While mapping the sediment properties, the database on the
oxygen consumption at stable conditions should be expanded in order to clarify the
relationship between sediment properties and oxygen consumption and to better
describe the seasonal and spatial aspects.
In addition, there are still questions about the temporal significance of resuspension
effects to be solved. Currently, it is still largely unknown how long the various sediment
particles remain in resuspension and thus to which proportion the three oxygen‐
consuming processes really take place. Therefore, detailed in‐situ investigations
should be carried out during a resuspension event. The experiments should cover the
entire water column and the oxygen consumption and sedimentation rates. An
analysis of the water composition (important anions and cations) before, during, and
after resuspension can provide information about the prevailing oxygen‐consuming
sub‐processes.
The knowledge of this thesis should be integrated into water quality models for the
upper Elbe estuary. The seasonality (temperature, the input of fresh biomass, and
sedimentation of particles) and the effect of resuspension should be included in the
models. With the help of our model, the individual oxygen‐consuming sub‐processes
can be represented in order to better assess the influence of human activities.
Our results, including the three steps, improve the understanding of the sediment‐induced
influence on the oxygen budget of the upper Elbe estuary and can help to characterise possible
impacts of climate change on sediment composition and the OCP. This will help to better
assess the effects of dredging operations in combination with a change in sediment
composition due to climate change. A possible decrease in precipitation and an increase in
temperature during the summer months may result in an even larger difference between
summer and winter until the system is overturned, for example by exceeding the optimum for
algal growth or microbial activity.
35
Appendix publication A
Oxygen Consumption of Resuspended Sediments of the Upper Elbe
Estuary: Process Identification and Prognosis
M.J. Spieckermann1, A. Gröngröft1, M. Karrasch2, A. Neumann3, A. Eschenbach1
1 Institute of Soil Science, CEN, University of Hamburg, Hamburg, Germany
2 Hamburg Port Authority, Hamburg, Germany 3 Institute of Coastal Research, Helmholtz‐Zentrum Geesthacht, Geesthacht, Germany
AUTHOR CONTRIBUTION: The authors Mathias Spieckermann, Alexander Gröngröft,
Maja Karrasch and Annette Eschenbach conceived and designed the study. Material
preparation, data collection and analysis were carried out by Mathias Spieckermann and
Alexander Gröngröft. The analysis of chlorophyll was carried out by Andreas Neumann. The
first draft of the manuscript was written by Mathias Spieckermann and Alexander Gröngröft.
All authors contributed through discussion on the interpretations of the results.
36
Abstract
The resuspension of sediment leads to an increased release of nutrients and organic
substances into the overlying water column, which can have a negative effect on the oxygen
budget. Especially in the warmer months with a lower oxygen saturation and higher biological
activity, the oxygen content can reach critical thresholds in estuaries like the upper Elbe
estuary. Many studies have dealt with the nutrient fluxes that occur during a resuspension.
However, the sediment properties that influence the oxygen consumption potential (OCP) and
the different biochemical processes have not been examined in detail. To fill this gap, we
investigated the biochemical composition, texture, and OCP of sediments at 21 locations as
well as the temporal variability within one location for a period of 2 years (monthly sampling)
in the upper Elbe estuary. The OCP of sediments during a seven‐day resuspension event can
be described by the processes of sulphate formation, nitrification, and mineralisation.
Chlorophyll, Ntotal and TOC showed the highest correlations with the OCP. Based on these
correlations, we developed a prognosis model to calculate the oxygen consumption for the
upper Elbe estuary with a single sediment parameter (Ntotal). The model is well suited for
calculating the oxygen consumption of resuspended sediments in the Hamburg port area
during the relevant warmer months (NRMSE <0.11 ± 0.13). Thus, the effect of maintenance
measures such as water injection dredging and ship‐induced wave on the oxygen budget of
the water can be calculated.
A.1 Introduction
Resuspension of sediments causes diverse consequences to the aquatic environment. One of
these is the increased consumption of dissolved oxygen in the river water phase. Low oxygen
concentration in river and estuarine systems is critical for fish populations (Thiel et al. 1995;
Miller et al. 2002; Rong et al. 2016) as well as for the trophic interaction (Breitburg et al. 1997).
According to Veenstra and Nolen (1991), sediment oxygen demand (SOD) is defined as the
rate of oxygen consumption, biologically or chemically, on or in the sediment at the bottom
of a water body. The SOD combines two main oxygen sinks: (i) the sediment oxygen uptake
by aerobic mineralisation of organic matter (OM) as well as oxidation of reduced substances
and (ii) the flux of reduced substances out of the sediment (Steinsberger et al. 2019). In natural
rivers, SOD can account for more than 50% of the total oxygen consumption (Rutherford et al.
1991; Matlock et al. 2003) besides respiration and the degradation of organic carbon in the
water phase. Therefore, it is crucial to examine the total oxygen demand caused by sediments
and to understand the share of involved processes.
In the upper part of the Elbe estuary with the Port of Hamburg and all its harbour
basins, a strong decline in dissolved oxygen concentrations is frequently observed during the
summer months (Bergemann et al. 1996; Schroeder 1997; Schöl et al. 2014). This decline is
mainly attributed to algal respiration and carbon degradation (Schroeder 1997) as well as
zooplankton grazing (Schöl et al. 2014). Schroeder (1997) postulated that nitrification and
sediment processes are of minor relevance, while Sanders et al. (2017) found a substantial
37
amount of nitrification in the Hamburg area in spring and summer. Kerner (2000) also came
to the conclusion that microbial oxygen consumption coupled with the degradation of freshly
transported organic material from the upper stream controls the oxygen concentration in the
warmer seasons. However, the influence of the biochemical sediment composition on the
oxygen consumption within the Hamburg area is still unknown.
In the Hamburg port area, the sedimentation rate in the fairway and in the adjacent
port basins is high. Each year, an amount of 1.7 to 6 million tons of dry substance must be
dredged to keep the fairway navigable (2010–2018; Hamburg Port Authority, unpublished
data).
Physical processes lead to a resuspension of sediments, and this causes a local and
temporary increase of reduced inorganic compounds and organic matter within the water,
which enhances oxygen consumption (Sloth et al. 1996; Almroth et al. 2009). The SOD during
resuspension is the sum of multiple processes driven by the oxygen supply, the biochemical
processes taking place, and the sediment properties. Barcelona (1983) and Rong and Shan
(2016) divided the SOD into chemical oxidation of dissolved iron, manganese, and hydrogen
sulphide/sulphur, and into biochemical oxidation of ammonium and nitrite to nitrate, in
addition to the mineralisation of organic matter and respiration.
Resuspension of sediments takes place in both limnic and marine areas worldwide. It
occurs when the shear stress is high enough to transport sediment particles into the water
column (Almroth et al. 2009). This critical shear stress can be exceeded by natural forces such
as tidal currents, wind, and biological activities (Sanford et al. 1991; Graf and Rosenberg 1997),
or by human activities such as shipping and dredging (Cappuyns et al. 2006).
To our knowledge, the influence of such activities on the oxygen budget of water
bodies has not yet been quantified. Many numerical models that calculate biochemical
processes within the water phase exclude the resuspension of sediments and its effect on
oxygen and nutrient dynamics (Moriarty et al. 2018).
Therefore, the objective of this study is to (i) derive the OCP of sediments from typical
sediment parameters; (ii) quantify the sediment oxygen consumption; and (iii) analyse the
biochemical composition and texture of the sediments within the upper Elbe estuary. This was
performed by two sampling campaigns in which the spatial variability and temporal dynamics
of the sediments were investigated.
Our methodological approach includes the continuous measurement of oxygen
consumption during resuspension of the sediments for seven days at constant temperature.
By analysing the change in sulphate and nitrate concentrations as well as the production of
carbon dioxide, we were able to calculate the oxygen consumption stoichiometrically and to
distinguish among oxygen consumption due to sulphate formation, nitrification, and
mineralisation of organic matter. Finally, one set of the sediment properties was used to
calibrate a forecast model to estimate the OCP. This model was then validated with a second
set of data from a temporal analysis. The aim of the study is to understand the individual sub‐
processes that lead to oxygen consumption during resuspension and to derive a simple
prognosis model for future practical application. This study aims to answer the following
research questions:
38
(1) Which biochemical processes control the OCP of sediments during a seven‐day
resuspension?
(2) What is the share of the main biochemical processes compared to the total OCP of
sediments?
(3) Which sediment properties control the OCP?
(4) Can the OCP of sediments be predicted by using sediment parameters?
A.2 Material and Methods
A.2.1 Study Site and Sampling
The upper Elbe estuary (Germany), characterized by fresh water from the Middle Elbe,
stretches from the weir Geesthacht (stream‐km 586) 46 km downstream to Wedel (stream‐
km 541) and includes the large area of the Port of Hamburg. Between stream‐km 609 and 626,
the Elbe forms an inland delta with the Northern Elbe and the Southern Elbe as its major
branches. With the start of the trafficability for ocean vessels at about stream‐km 619
(Southern Elbe) and stream‐km 624 (Northern Elbe), the depth of the fairway and the harbour
basins has been increased to 15 m.
Two sampling campaigns were carried out. The first campaign aimed at obtaining a
large number of sediments with different properties. For this purpose, samples were taken at
21 locations in the Hamburg area between 2017‐06‐30 and 2017‐07‐04. The sites were located
in the fairway, in the entrance area and end area of the different harbour basins, and in the
upper stream. The second sampling campaign aimed to investigate the seasonal changes in
sediment properties and their influence on the OCP. Sampling took place monthly at one
location in the Port of Hamburg, from December 2016 to November 2018, except for August
2017 and July and October 2018, when no samples could be taken.
Samples were taken from a ship with a core sampler (Frahm‐Lot, length 80 cm, inner
diameter 10 cm). For further analyses, two layers per core (0–20 cm and 40–60 cm) were
sampled. To determine the sediment depth, we only used cores that contained at least 60 cm
of sediment and some supernatant water. Each single sampling consists of three parallel core
samples that were combined to mixed samples of respective sediment depth. However, the
actual sampling points were about 1 to 10 meters apart from each other. Aboard the ship,
sediment samples were filled into airtight jars (1,000 ml volume) up to the rim and then
transported to the laboratory. This procedure was carried out for the first sampling campaign
and the first eight sampling dates (until May 2017) of the second campaign. Later on, two
parallels were taken per sampling, and the corer was improved such that it could be divided
into three segments. These core segments were separated in the laboratory, and the sediment
was removed and homogenized under nitrogen atmosphere. Each homogenized sample was
divided into two subsamples and stored at 4 °C until measurement started. The first
subsample was used to determine the OCP, and the airtight jar was opened only for this
purpose. The second subsample was used to extract the pore water and to determine the
sediment solid parameters. At the locations 2, 6, 17, and 18 no samples could be taken for the
lower layer.
39
A.2.2 Sediment Characterisation
The pore water was extracted through centrifugation at 2,816 rcf (relative centrifugal force)
for 30 min. Afterwards it was vacuum filtered through a 0.45 µm cellulose acetate filter under
a nitrogen atmosphere. Ammonium was measured photometrically
(Photometer DR5000, Hach, USA) using the indophenol blue method (DIN 38406‐5) within
three days after sampling. Sulphate, nitrate, and nitrite were analysed with an ion
chromatograph (Metrohm, Germany) according to DIN EN ISO 10304‐1. Dissolved iron and
manganese were analysed with a flame atomic absorption system AA280FS (Agilent, USA) as
given by DIN 38406‐32 and DIN 38406‐33.
For the analysis of solid parameters, mixed samples were dried at 105 °C and ground
for analysis of carbon and nitrogen content. Total carbon and nitrogen (Ntotal) were
determined by dry combustion using a Vario MAX cube analyser (Elementar Analysensysteme
GmbH, Germany) (DIN ISO 10694). Inorganic carbon was determined after acidification with
42.5% phosphoric acid according to Luther‐Mosebach et al. (2018). Organic carbon (TOC) was
obtained by difference. The grain size fraction <20 µm was estimated by the sedimentation
method (DIN ISO 11277).
Chlorophyll concentrations were measured as an indicator for the biomass of algae.
Therefore, 50 ml of the homogenized samples from the upper sediment layer (0–20 cm depth)
were freeze‐dried. The samples were extracted with 90% acetone, and the concentrations of
chlorophyll‐a and pheophytin‐a were determined according to Lorenzen (1967). The
chlorophyll value given in this study represents the sum of the chlorophyll‐a concentration
and its degradation product pheophytin‐a.
A.2.3 Oxygen Consumption
The OCP of sediments during resuspension was measured with the respirometer BSB‐digi O2
(Selutec, Germany) at 20 °C ± 0.5 °C. The respirometer measures the power consumption for
electric oxygen production, which is necessary to compensate for the uptake of oxygen and
thus keep the internal pressure in the chamber constant. The CO2 produced by the
mineralisation was adsorbed in 1 M sodium hydroxide solution. For further information, see
Young et al. (1965), Montgomery (1967), and Young and Baumann (1976). Of the fresh
sediment, 30 g were bottled (500 ml) under a nitrogen atmosphere to avoid oxidation
processes and 200 ml demineralised water were added. The suspension was stirred at 300
revolutions per minute. OCP was measured continuously for 168 h, and data were recorded
in 0.5 h intervals. Using the cumulative oxygen consumption curves, the oxygen consumption
rate and the total OCP after 168 h were calculated. Three parallel measurements were
conducted per sample. However, some incubations failed during the experiments. Therefore,
the indicated errors are the minimum and maximum of the measured values as given in the
figures. All runs were made in the absence of light. Immediately after each experiment, the
supernatant water was filtered and analysed for nutrient concentration. To determine the
share of the mineralisation compared to the total consumption, the CO2 adsorbed in NaOH
was quantified by titration with 0.1 M HCl solution and phenolphthalein as an indicator. The
40
absorbed CO2 was calculated 1 to 1 into oxygen consumption. Parallel to the samples, blank
values were measured with demineralised water, which were subtracted from the samples.
For five samples (1 L1, 2 L1, 4 L1 and L2, and 8 L2) the CO2 formation could not be determined
because the CO2 production exceeded the sorption capacity of the NaOH. For these samples,
the proportion of the mineralisation was calculated using the cumulative oxygen consumption
curves. A linear fit was adjusted to the curves for the period from hour 100 to hour 168, in
which to our knowledge the consumption rate is characteristic of the mineralisation of organic
matter. The regression was forced through the origin, and the calculated value after 168 h is
given as the proportion of mineralisation in the total oxygen consumption.
In two additional sets of incubation experiments, the effect of ammonium on oxygen
consumption was analysed. Therefore, a sediment sample was incubated with and without an
addition of ammonium. The sample originated from location 10 and was taken on 2018‐06‐
22. The suspension was also prepared with 250 ml of demineralised water. At the beginning,
50 ml of the suspension were sampled to determine the initial ammonium concentration.
Experiment A had an additional ammonium concentration in the suspension of 978 µmol l‐1
and experiment B of 1,911 µmol l‐1. Per experiment, we measured six replicates with and six
replicates without the addition of ammonium. At the beginning of the experiments, the
ammonium concentration in each suspension was measured. Then after 24, 48, and 168 h,
two incubations were stopped and the remaining ammonium concentration in the suspension
was analysed. Experiment A was stopped after 138 h due to a failure of the respirometer.
Therefore, the ammonium concentration was determined after 138 h.
A.2.4 Calculation of Oxidation Reactions
The oxygen consumption was calculated stoichiometrically based on the change in
concentration of the involved compounds in the pore water after sampling and after the
incubation. The oxidation reactions are given in Equations 1–6 (mineralisation, nitrification in
two steps, and the oxidation of iron, manganese, and hydrogen sulphide, respectively).
Equation 6 stands for the oxygen consumption during the formation of sulphate. Because
sulphur can be present in different compounds (FeS and FeS2, Schippers and Jørgensen 2001)
and sulphate can be the product of different oxidation reactions, we assume that two moles
of oxygen were consumed per mole of formed sulphate. The oxygen consumption due to the
oxidation of the metals is neglected here, as we do not know the relation of the different
sulphur compounds.
C H O 6 O → 6 CO 6 H O (1)
NH 1,5 O → NO H O 2 H (2)
NO 0,5 O → NO (3)
2Fe 0.5 O 2 H O → Fe O 4 H (4)
41
Mn 0.5 O H O → MnO 2 H (5)
MeS 2 O → SO 2 H (6)
Spearman correlation analyses were performed using the software OriginLab (Pro) (Version
2019b).
A.2.5 Development of an Oxygen Consumption Model
In order to develop a model for the calculation of oxygen consumption we used the following
approach: (i) The cumulative oxygen consumption curves of the samples from the spatial
investigation were divided into three phases. We have fitted the respective curves of the
individual phases. (ii) The resulting function parameters of all samples were correlated with
the sediment properties. This resulted in six linear or nonlinear regression equations between
sediment properties and parameters. Using the sediment properties, we were able to
calculate the six parameters per sample, which allowed us to calculate the oxygen
consumption and their involved processes along the time‐line. For all samples the normalized
root mean squared error (NRSME) between measured and modelled oxygen consumption was
calculated. (iii) To validate our model the samples from the second campaign were used. Using
the sediment properties, the six parameters per sample were determined, and the oxygen
consumption was calculated.
A.3 Results
A.3.1 Characterisation of the Sediments
The samples from the spatial investigation showed a strong variability in their sediment
composition (Table A 1). Location 7 had the lowest TOC content with 0.2%‐d.wt. and location
4 the highest with 6.3%‐d.wt. TOC showed a high positive correlation with the grain size
fraction <20 µm (rsp = 0.780; p <0.01). A high variability can also be seen in the Ntotal content.
The TOC/Ntotal ratio of all samples varied between 7.3 and 10 for the top layer and between
8.2 and 10.9 for the bottom layer. In general, the lower layers had higher TOC/Ntotal ratios than
the upper ones. Chlorophyll was measured only for the upper layer and showed a strong
variability among the different sites.
The samples from the second measuring campaign showed less variation in their
composition. Here, the maximum values for TOC, Ntotal, chlorophyll, and the grain size fraction
<20 µm were found during the summer months combined with the lowest TOC/Ntotal ratio.
42
Table A 1: Sediment properties for both campaigns. The results from the temporal analysis campaign are given with the measured minimum and maximum values. The lower layer was not analysed for chlorophyll.
Position Layer TOC Ntotal TOC/Ntotal ratio Chlorophyll Particles <20 µm [%‐d.wt.] [%‐d.wt.] [‐] [µg g d.wt.‐1] [%‐d.wt.]
1 0‐20 6.1 0.68 8.9 369.7 67.3
1 40‐60 3.1 0.34 9.1 ‐‐ 38.9
2 0‐20 6.2 0.79 7.9 801.6 83.1
2 40‐60 5.7 0.65 8.7 ‐‐ 75.8
3 0‐20 2.9 0.31 9.3 150.4 40.3
3 40‐60 ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
4 0‐20 6.3 0.87 7.3 1100.9 83.6
4 40‐60 5.4 0.64 8.4 ‐‐ 79.1
5 0‐20 1.4 0.18 7.9 195.2 24.1
5 40‐60 2.3 0.25 9.3 ‐‐ 23.4
6 0‐20 4.8 0.50 9.6 260.1 63.6
6 40‐60 4.4 0.41 10.9 ‐‐ 44.7
7 0‐20 0.2 0.02 10.0 1.7 0.8
7 40‐60 ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
8 0‐20 4.1 0.51 8.1 228.6 89.0
8 40‐60 4.5 0.55 8.2 ‐‐ 76.9
9 0‐20 4.5 0.54 8.3 402.5 38.8
9 40‐60 4.0 0.49 8.3 ‐‐ 46.0
10 0‐20 3.4 0.40 8.5 208.9 49.3
10 40‐60 2.7 0.30 8.8 ‐‐ 45.5
11 0‐20 1.8 0.21 8.5 97.9 33.2
11 40‐60 2.0 0.22 9.2 ‐‐ 35.7
12 0‐20 3.6 0.43 8.4 171.3 70.6
12 40‐60 4.1 0.48 8.6 ‐‐ 54.7
13 0‐20 4.0 0.47 8.6 224.0 80.7
13 40‐60 3.9 0.44 8.9 ‐‐ 77.0
14 0‐20 3.9 0.46 8.6 178.4 71.2
14 40‐60 4.2 0.51 8.3 ‐‐ 73.6
15 0‐20 1.8 0.20 9.3 47.8 32.8
15 40‐60 1.2 0.11 10.2 ‐‐ 15.6
16 0‐20 3.4 0.39 8.7 105.7 36.5
16 40‐60 3.8 0.43 8.7 ‐‐ 44.5
17 0‐20 1.3 0.16 8.7 40.9 30.3
17 40‐60 ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
18 0‐20 0.9 0.09 9.5 18.4 14.8
18 40‐60 ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
19 0‐20 3.2 0.34 9.5 137.2 55.4
19 40‐60 4.5 0.43 10.4 ‐‐ 38.0
20 0‐20 3.5 0.42 8.3 120.6 80.6
20 40‐60 3.7 0.44 8.4 ‐‐ 59.7
21 0‐20 1.6 0.17 9.5 27.3 34.8
21 40‐60 2.2 0.25 8.8 ‐‐ 39.3
Temporal 0‐20 1.3‐3.9 0.14‐0.46 7.5‐9.8 49.4‐257.7 17.1‐73.7
Temporal 40‐60 1.6‐3.6 0.19‐0.45 7.2‐9.7 ‐‐ 24.2‐71.5
TOC total organic carbon, Ntotal total nitrogen, ‐‐ no sample could be obtained
43
A.3.2 OCP
During the incubation of resuspended sediment samples for 168 h the cumulative oxygen
consumption curves and more noticeably the oxygen consumption rates reflect different
phases of oxygen consumption. All samples showed the highest oxygen consumption during
the first hours and at least one sharp decrease in the oxygen consumption rate. Afterwards
the rate was often nearly constant for several hours before the rate droped a second time.
Figure A 1a gives a typical example of the measured oxygen consumption (sample 6 L1). Here,
after 16 h and 39% of the measured oxygen consumption the first bend point is reached. After
another 42 h with nearly constant oxygen consumption rate the second decrease begins. At
this moment 72% of the measured oxygen consumption has been measured. From 58 h to
168 h the oxygen consumption rate is low and slightly further decreasing, forming a curved
course of the cumulative consumption. This pattern applied to most of the measured oxygen
consumption curves. However, some samples showed three decreases in the rates or even an
increase in the rate after the first drop (Figure A 1b). After six hours the oxygen consumption
rate decreases, and 26% of the measured oxygen consumption is reached. The rate remains
constant for a few hours and then increases. After 35 h, the rate drops again, and 59% of the
measured oxygen consumption is reached. It then remains constant for about 25 h, with a
lower rate than in the previous phase. After 65 h the rate flattens for the third time, and 81%
of the measured oxygen consumption is reached.
Figure A 1: Cumulative oxygen consumption (grey) during a 168 h incubation period and the respective
oxygen consumption rates (black) for locations 6 L1 (a) and 13 L2 (b). The error bars indicate the
standard deviation (n=3).
44
In order to determine the influence of nitrification on the oxygen consumption rate, two
incubation experiments were carried out with an ammonium addition of 978 µmol l‐1 and
1911 µmol l‐1 (Figure A 2). As expected from equations (2) and (3), the samples with additional
ammonium displayed (i) a higher oxygen consumption than preparations without additional
ammonium and (ii) a later occurrence of the second decrease in the oxygen consumption
curve. After the second decrease, no remaining ammonium was detected in the samples
(Table A 2). These results indicate that nitrification has a strong influence on the oxygen
consumption and that the second phase in the consumption curve is controlled by
nitrification.
Figure A 2: Cumulative oxygen consumption during 168 h of incubation of samples with (dashed line)
and without (dotted line) additional ammonium. a) additional ammonium concentration in suspension
of 978 µmol l‐1 and b) additional ammonium concentration in suspension of 1,911 µmol l‐1.
45
Table A 2: Ammonium concentrations in sediment suspensions from an experiment to determine the
influence of ammonium on oxygen consumption. Measured initial and final concentrations of the
samples with and without additional ammonium after certain times. Experiment A with additional
ammonium concentration in suspension of 978 µmol l‐1 and experiment B with additional ammonium
concentration in suspension of 1,911 µmol l‐1. In experiment A, samples “with 3” and “with 6” could not
be determined.
Experiment A Experiment B
Start conc. Stop conc. Stop Start conc. Stop conc. Stop
[µmol l‐1] [µmol l‐1] time [h] [µmol l‐1] [µmol l‐1] time [h]
With 1 1279 476 24 2008 1146 24
With 2 1318 440 24 1962 1195 24
With 3 ‐‐ ‐‐ ‐‐ 1992 <LOD 48
With 4 1308 <LOD 48 1950 <LOD 48
With 5 1328 <LOD 48 1916 <LOD 168
With 6 ‐‐ ‐‐ ‐‐ 1908 <LOD 168
Without 1 330 <LOD 24 36 <LOD 24
Without 2 326 <LOD 24 39 <LOD 24
Without 3 328 <LOD 48 44 <LOD 48
Without 4 337 <LOD 48 49 <LOD 48
Without 5 323 <LOD 138 49 <LOD 168
Without 6 335 <LOD 138 52 <LOD 168
Conc. Concentration, <LOD below the limit of determination (55 µmol l‐1)
A.3.3 Stoichiometric Analysis and Correlations
Based on the measured change in concentration of nitrate, sulphate, iron, manganese, and
the formed CO2, the total oxygen consumption was calculated stoichiometrically according to
equations (1) to (6). The oxygen consumptions of the individual processes were summed up
to compare the total with the measured oxygen consumption (Figure A 3). Between calculated
and measured oxygen consumption a high correlation exists (rsp = 0.960). There was no
general trend in over‐ or underestimation of the calculated oxygen consumption.
There was a high variability in oxygen consumption with respect to the different
processes. In most cases, the mineralisation had the highest proportion of oxygen
consumption after 168 h. The oxygen consumption due to the formation of sulphate and
nitrate varied between 5.3% and 57.6% and between 1.2% and 40.5%, respectively. However,
this was very different according to the individual sites and layers. Iron and manganese
oxidation showed only a very small contribution (<0.5%) to the total oxygen consumption,
which is due to the neglected oxidation of metal ions by our calculation of the oxygen
consumption by sulphate formation. Therefore, the processes of sulphate formation,
nitrification, and mineralisation are sufficient to describe the oxygen consumption.
46
Location 4 L1 showed the highest measured oxygen consumption after 168 h
(0.967 mmol O2 g d.wt.‐1) with the largest influence of mineralisation, high rates of
nitrification, and minor rates of sulphur oxidation. This was the sample with the highest
content of TOC (6.3%‐d.wt.) and the lowest TOC/Ntotal ratio (7.2). In contrast, location 7 L1
showed the lowest oxygen consumption (0.005 mmol O2 g d.wt.‐1). Here, the TOC content was
very low as well (0.2%‐d.wt.). This relationship corresponds to the results of the Spearman
correlation analysis (Figure A 4). The total measured oxygen consumption correlated highly
with TOC (rsp = 0.939), Ntotal (rsp = 0.946), and chlorophyll (rsp = 0.960). Also, chlorophyll and
Ntotal were strongly correlated with each other (rsp = 0.923). The chlorophyll concentration
varied between 1.7 µg g d.wt.‐1 and 1100.9 µg g d.wt.‐1. The locations with the four highest
OCPs also showed the four highest sediment chlorophyll concentrations.
Figure A 3: Comparison of the stoichiometric calculation of the oxygen consumption (height of column)
and the measured oxygen consumption (circle) for the two layers (L1 and L2) of the spatial sampling
campaign. The samples were sorted according to their Ntotal content. The calculated consumption
consists of the proportion of carbon dioxide formed (mineralisation), the sulphate formation, the
nitrification, and iron and manganese oxidation. + the proportion of mineralisation in the total
consumption was calculated. Numbers in brackets indicate the sample, and numbers without brackets
indicate the Ntotal content (%‐d.wt.). The error bars display the min and max values for the replicates
(n = 2 to 3).
47
Figure A 4: Above the diagonal: Scatter plots for the measured and calculated oxygen consumption and
the sediment composition of the spatial analysis. Below the diagonal: Results of a Spearman correlation
analysis between the measured (O2 meas.) and calculated (O2 calc.) oxygen consumption, the sediment
composition, and the chlorophyll concentration (Chl.). All parameters tested are significantly correlated
with each other (p <0.05).
A.3.4 Development of an Oxygen Consumption Model
Within the studied time frame, 3 sub‐processes can describe the cumulative oxygen
consumption of sediments during resuspension. Sub‐process 1 comprises the rapid chemical
and microbial oxidation of dissolved iron, manganese, and hydrogen sulphide as well as solid
sulphur compounds such as iron monosulphides, elemental sulphur, or pyrite. The second sub‐
process reflects the nitrification of ammonium to nitrate via nitrite. The third sub‐process is
the mineralisation of organic matter. As supported by the analysed course of oxygen
consumption, we can describe sub‐processes 1 and 3 by a first‐order exponential degradation
function. And, as visualized in Figure A 1, nitrification can be described by a constant rate
(zero‐order kinetic) and a given time period.
Based on these considerations, the model development starts with an adaptation of
the corresponding functions to the measured curve shapes. This was done in three steps: a)
for every sample i the data of cumulative oxygen consumption after the second drop in rate
were fitted with an exponential degradation function (equation 7), resulting in the parameters
A and t . The resulting function was differentiated (equation 8) to result in A∗. The constants
48
A∗ and t were regarded to describe the kinetics of mineralisation of every sample for the
whole studied period (168 h). From the measured oxygen consumption rates, the calculated
fitted mineralisation was subtracted.
y ; y ; A ∗ e (7)
r ; A∗ ∗ e
(8)
A∗ A ∗
1t
(9)
where y ; = calculated cumulative mineralisation of sample i at time x (mmol O2 g d.wt.‐1)
y ; = offset of sample i (mmol O2 g d.wt.‐1)
r ; = calculated rate of mineralisation of sample i at time x (mmol O2 g d.wt.‐1 h‐1)
A = amplitude of sample i (mmol O2 g d.wt.‐1)
A∗ = amplitude of sample i (mmol O2 g d.wt.‐1 h‐1)
x = time (h)
t = degradation rate constant (h‐1)
b) For each sample, the remaining curves of the oxygen consumption rates were analysed for
the mean rate of nitrification. Based on equation 10 the oxygen consumption due to
nitrification was calculated. For the period from 0 to D the resulting nitrification rate R (mmol
O2 g d.wt‐1 h‐1) was again subtracted from the remaining measuring values.
r ; R ∗ D (10)
where r ; = calculated cumulative nitrification of sample i at time x (mmol O2 g d.wt.‐1)
R = calculated rate of nitrification of sample i at time x (mmol O2 g d.wt.‐1 h‐1)
D = calculated duration of nitrification of sample i (h)
c) Finally, the remaining cumulative oxygen consumption curve was handled as in step a. An
exponential degradation function (equation 11) was fitted to the data, resulting in the
parameters B , s , and B∗, which were regarded as a description of the fast chemical oxidation
processes.
y ; y ; B ∗ e (11)
r ; B∗ ∗ e (12)
where r ; = calculated rate of fast chemical oxidation of sample i at time x (mmol O2 g d.wt.‐1 h‐1)
49
y ; = offset of sample i (mmol O2 g d.wt.‐1)
B = amplitude of sample i (mmol O2 g d.wt.‐1)
B∗ = amplitude of sample i (mmol O2 g dw‐1 h‐1)
s = chemical oxidation rate constant (h‐1)
In total, with the curve‐fitting process for each sample six independent parameters were
derived, of which two were always necessary to quantify the kinetics of the three sub‐
processes and which in sum result in the total oxygen consumption. The parameters obtained
in this way were correlated to the sediment properties TOC, Ntotal, TOC/Ntotal ratio, particle
fraction <20 µm, and total chlorophyll. However, 5 samples were excluded from correlation
because they had either a high sand content (7 L1 and 18 L1), an outstanding chlorophyll
content (2 L1 and 4 L1), or an irregular oxidation dynamic resulting in a negative t (19 L2). The best correlations were observed for Ntotal and TOC (Table A 3). The parameters A∗
and B∗ show a rSp >0.698 (p <0.05) for TOC and Ntotal. The degradation rate constant t does not significantly correlate to the sediment properties but has a higher correlation with the
parameter A (rsp >0.606). The nitrification rate R and the pool of nitrification (R ∗ D )
significantly correlate to Ntotal and TOC. The duration D , however, does not significantly
correlate to the studied sediment properties.
Table A 3: Results of a Spearman correlation analysis between the sediment properties (TOC and Ntotal)
and the fitted functions parameters of the oxidation consumption model. Above the diagonal:
Spearman correlation coefficient. Below the diagonal: The two‐tailed significant values, significant
values p <0.05 bold.
TOC Ntotal A∗ t R D R ∗ D B∗ s
TOC ‐‐ 0.966 0.744 ‐0.057 0.608 0.098 0.761 0.778 0.381
Ntotal 0.000 ‐‐ 0.698 0.021 0.655 0.071 0.767 0.825 0.352
A∗ 0.000 0.000 ‐‐ ‐0.350 0.523 ‐0.120 0.526 0.595 0.295
t 0.753 0.906 0.046 ‐‐ 0.046 0.222 0.073 ‐0.022 0.150
R 0.000 0.000 0.002 0.797 ‐‐ ‐0.411 0.785 0.614 0.004
D 0.580 0.691 0.507 0.214 0.016 ‐‐ 0.159 ‐0.074 0.324
R ∗ D 0.000 0.000 0.002 0.686 0.000 0.369 ‐‐ 0.633 0.291
B∗ 0.000 0.000 0.000 0.904 0.000 0.679 0.000 ‐‐ 0.114
s 0.026 0.041 0.095 0.406 0.983 0.062 0.095 0.521 ‐‐
TOC total organic carbon, Ntotal total nitrogen, A∗ amplitude of sample i (mineralisation),
t degradation rate constant (mineralisation), R calculated rate of nitrification of
sample i at time x, D calculated duration of nitrification of sample i, R ∗ D pool
of nitrification, B∗ amplitude of sample i (chemical oxidation), s chemical
oxidation rate constant
Univariate regression functions among the six model variables and the significantly correlating
sediment properties were used to derive estimated variables (Table A 4). For A∗ ,
50
R, B∗, and R ∗ D, linear regression was used with Ntotal as proxy. For the rate constant t and s, linear regression was used with the estimated function parameters A and B as proxies,
respectively (Table A 4). The nitrification duration variable D was calculated from the pool
R ∗ D ) and the rate. Based on the derived regression functions and known sediment
properties, the corresponding function parameters can be calculated and thus also an
estimate of the oxygen consumption for each step in time.
Table A 4: Estimated function parameters and the linear and nonlinear functions fitted to the
correlation, their goodness of fit, and the variable used for correlation.
Estimated
paramete
r
Fitted
function
Resulting
variable
a
Resulting
variable
b
Resulting
variable
c
Adjust
ed
R2
RMSE Applied
variable
x
A A a b ∗ e ‐9.39*10‐2 ‐4.52*10‐2 ‐2,58*10‐1 0.214 0.241 Ntotal
A∗ A∗ a b ∗ x ‐5.95*10‐6 2.57*10‐3 ‐‐ 0.492 ‐‐ Ntotal
t t a b ∗ x 107.99 ‐852.44 ‐‐ 0.359 ‐‐ A
R R a b ∗ x ‐7.08*10‐6 4.14*10‐3 ‐‐ 0.358 ‐‐ Ntotal
D
D a b ∗ x/R
‐1.63*10‐2 1.81*10‐1 ‐‐
0.451 ‐‐ Ntotal
B B a b ∗ x 1.61*10‐2 ‐1.65*10‐1 ‐‐ 0.551 ‐‐ Ntotal
B∗ B∗ a b ∗ x 1.49*10‐3 2.99*10‐2 ‐‐ 0.706 ‐‐ Ntotal
s s a b ∗ x 1.74 ‐37.61 ‐‐ 0.702 ‐‐ B
A estimated amplitude (mineralisation), A∗ estimated amplitude (mineralisation), t
estimated degradation rate constant (mineralisation), R estimated rate of nitrification, D
estimated duration of nitrification, B estimated amplitude (nitrification), B∗ estimated
amplitude (nitrification), s estimated degradation rate constant (nitrification)
Figure A 5 compares the measured cumulative oxygen consumption values with the estimated
values according to the equations of Table A 4 after 3, 24, and 168 h for all samples. These
times were chosen because they reflect respective sub‐processes (chemical oxidation [3 h],
nitrification [24 h], and mineralisation [168 h]), as shown before. Linear regressions showed a
good fit with an Adj. R2 >0.840 and a low scattering for all three periods. The slope varied
between 1.152 (3 h) and 0.697 (168 h), resulting in a slight underestimation or overestimation
of oxygen consumption by the model. This was particularly evident in the samples with a high
chlorophyll content and an oxygen consumption >0.8 mmol O2 g d.wt.‐1, where the model
strongly underestimated the consumption after 168 h.
51
Figure A 5: Comparison between the measured oxygen consumption after 3 h (a), 24 h (b), and 168 h
(c) and the calculated oxygen consumption for all samples of the data set “spatial analysis”.
In 28 of the 38 samples, the NRMSE was below 0.2 after 168 h and in 13 samples below 0.1
(Figure A 6). Among the three selected times, the 3 h‐values showed the highest deviations
between the model and the measured consumption, with a mean NRMSE of 0.17 ± 0.11
(sample 7 L1 excluded). For the sandy sample 7 L1 the oxygen consumption was strongly
overestimated by the model and therefore showed the largest error (NRMSE >0.5). The mean
NRMSE after 24 h was 0.12 ± 0.11. In most cases the NRMSE was smaller than after 3 h. For
those samples where this was not the case, the consumption rate due to nitrification or the
duration was over‐ or underestimated by the model. After 168 h, the mean NRMSE was
0.14 ± 0.10.
Figure A 6: Normalized root mean squared error (NRMSE) between the calculated and measured
oxygen consumption curves from the spatial sampling campaign for the upper (L1) and lower (L2) layer.
* no sample exists for the lower layer.
A.3.5 Validation of the Oxygen Consumption Model
The oxygen consumption curves of 82 samples from the temporal analysis campaign were
used to validate the model. Oxygen consumption was calculated from Ntotal of the samples,
and Figure A 7 compares the measured oxygen consumption with the calculated one. The
results showed a good fit considering the samples from the summer (April to August). After
3 h and 24 h the summer samples showed a lower scatter and a steeper slope (Figure A 7)
compared to the winter samples from September to March, which showed a slope of 0.488
52
after 3 h (Adj. R2 = 0.321) and a slope of 0.771 after 24 h (Adj. R2 = 0.497). After 168 h the
winter samples showed a steeper slope (0.920) but also a larger dispersion (Adj. R2 = 0.610).
The adjustment improves with increasing resuspension time.
Figure A 7: Comparison between the measured oxygen consumption after 3 h (a), 24 h (b), and 168 h
(c) and the calculated oxygen consumption for all samples of the data set “temporal analysis.” The
samples are divided into summer samples (April to August) and winter samples (September to March).
The regression line refers to the summer samples.
Comparing the calculated NRMSE values for the year 2018 (Figure A 8), it is also evident that
the model provides a better adjustment in the summer months (April to August) than in the
winter months (September to March). The NRMSE was higher in the winter months and had
a mean value of 0.27 ± 0.20 (3 h), 0.36 ± 0.24 (24 h), and 0.22 ± 0.09 (168 h). In the summer
months the average calculated error was 0.15 ± 0.06 (3 h), 0.10 ± 0.09 (24 h), and 0.09 ± 0.09
(168 h). The NRMSE values between summer and winter differed significantly (p <0.01) for the
24 and 168 hourly values. The difference for the 3 h values was not significant at a significance
level of p = 0.069.
Figure A 8: Normalized root mean squared error (NRMSE) between the calculated and measured
oxygen consumption curves from the temporal sampling campaign for the upper (L1) and lower (L2)
layer. Letters A and B indicate the replicates.
53
The difference between summer and winter is also reflected in the measured oxygen
consumption, where the sediments showed the highest OCP between May and August (Figure
A 9). Figure A 9 shows that the assumptions made about the sub‐processes can also be applied
to the data set temporal dynamics. For the year 2018 a high correlation exists (rsp = 0.967)
between the calculated and measured oxygen consumption, and there is no general trend in
over‐ or underestimation of the calculated oxygen consumption.
Figure A 9: Comparison of the stoichiometric calculation of the oxygen consumption (height of column)
and the measured oxygen consumption (circle) for the temporal analysis. Shown are the respective
replicates (A and B) for the upper layer. The calculated consumption consists of the proportion of carbon
dioxide formed (mineralisation), the sulphate formation, the nitrification, and iron and manganese
oxidation. + the proportion of mineralisation in the total consumption was calculated. The error bars
display the min and max values for the replicates (n = 2 to 3).
Measured and calculated oxygen consumption and the sediment properties were correlated
significantly with each other (p <0.05) with one exception between TOC and TOC/Ntotal ratio
(p = 0.07) (Figure A 10). Chlorophyll showed the highest correlation with the measured oxygen
consumption. TOC (rsp = 0.752) and Ntotal (rsp = 0.839) correlated highly with the OCP even
though the data of the temporal analysis showed a larger scattering compared to the spatial
analysis. Additionally, at the temporal analysis, Ntotal showed a higher correlation to the OCP
than TOC.
54
Figure A 10: Above the diagonal: Scatter plots for the measured and calculated oxygen consumption
and the sediment composition. Below the diagonal: Results of a Spearman correlation analysis between
the measured (O2 meas.) and calculated (O2 calc.) oxygen consumption, the sediment composition, and
the chlorophyll concentration (Chl.). All parameters tested are significantly correlated (p <0.05) with
each other with one exception: The correlation between the TOC and the TOC/Ntotal ratio (p = 0.07)
shows no significance.
A.4 Discussion
Two sampling campaigns were carried out to investigate the factors influencing the OCP of
sediments and the biogeochemical processes taking place. The OCP of sediments in the
Hamburg area of the river Elbe is attributable to three main processes: sulphate formation,
nitrification, and the mineralisation of organic matter. These processes differ in their kinetics
and available substrate pools. Upon depletion of the respective substrates, sulphate
formation and nitrification eventually cease, and a distinct decrease in the oxygen
consumption rate is observed. By contrast, the aerobic degradation of organic matter is a still
ongoing process at the end of the measurement period of seven days.
The OCP of the sediments showed a high correlation to Ntotal, TOC, and the chlorophyll
content. A prognosis model was developed that can be used to calculate the oxygen
consumption of Hamburg port sediments.
55
A.4.1 Sediment Composition
The sediment composition is substantially more variable spatially than temporally. The
structure of the upper estuary with shallow waters and the deep fairway, harbour basins, and
channels results in different flow velocities and sedimentation rates. This corresponds to the
varying properties of the sediments at the respective locations with regard to grain size
composition, TOC, and origin of the particulate matter. Tidal influence is known to transport
marine particles into the upper estuary up to approximately stream‐km 620 (Weilbeer 2014;
Reese et al. 2019). The smaller scatter within the sediment composition from the data set
“temporal analysis” can be attributed to the fact that the samples were taken from one single
site. Here the sediment properties are controlled only by seasonal parameters such as
temperature, organic matter input, and flow velocities, which had a smaller impact on the
variation than the spatial parameters (Table A 1).
A.4.2 OCP and Stoichiometric Analysis
Sediment resuspension results in an increased release of nutrients into the water phase
(Kristensen et al. 1992; Wainright and Hopkinson 1997; Gibson et al. 2015). Even thin
sediment layers in the range from a few mm to cm are sufficient to affect the water column
substantially (Tengberg et al. 2003; Blackburn 1997). This frequently leads to an increased
oxygen consumption in the water column, due to the oxidation of reduced inorganic and
organic products from anaerobic processes in the sediment (Sloth et al. 1996; Almroth et al.
2009).
Due to the release of these products the oxygen consumption during resuspension is
subject to various processes (chemical and microbial oxidation, nitrification, and carbon
mineralisation of organic matter). These processes vary in their reaction rates and in their
influence on oxygen consumption, depending on the concentration of the educts. The
cumulative oxygen consumption curves and rates (Figure A 1) clearly show that the rates
decrease at distinct times. These decreases are explained by the oxidation of the respective
educts. Therefore, the OCP can be divided into three phases, whereby these phases are
dominated by different processes.
The first phase includes the chemical and microbial oxidation of dissolved iron and
manganese and reduced sulphur compounds. Due to the experimental design, we cannot
distinguish between spontaneous chemical oxidation and oxidation by microbes of the
respective educts. Barcelona (1983) showed in his 24 h experiments that more than half of
the SOD took place in the first half hour and attributed this to chemical oxidation processes.
The oxidation of reduced sulphur compounds such as pyrite (FeS2), iron sulphide (FeS), and
hydrogen sulphide (H2S) is subject to different reaction rates. Richards et al. (2018) estimated
oxidation rates for acid‐volatile sulphide (AVS) between 8 and 21 mmol S kg‐1 d‐1, which are
three orders of magnitudes higher than those for hydrogen sulphide (6 to 26 µmol S kg‐1 d‐1).
Morse (1991) concluded from his experiments that the oxidation of pyrite is characterized by
a daily to monthly time scale, whereby the rates depend on the particle size so that smaller
particles are oxidized faster. Sulphate formation is therefore a process that can have a high
56
influence on the measured oxygen consumption, both within the first hours and over a longer
term. Although the sulphate release may take place over a longer period of time, the results
show that the second flattening of the cumulative oxygen curve is initiated by the end of
nitrification and that sulphate formation and chemical oxidation no longer dominate.
Therefore, the first phase can be attributed to the chemical oxidation of dissolved iron and
manganese and the rapid oxidation of sulphur compounds.
As shown in Figure A 2, the second phase is characterized by nitrification. Morin and
Morse (1999) showed in their resuspension experiments that the ammonium release comes
in equal parts from the pore water, the loosely bound fraction, and the tightly bound fraction.
Some samples showed three decreases in the oxygen consumption rates. One explanation for
this could be the coupled process of nitrification. According to Ossenbruggen et al. (1996) and
Brouwer et al. (1998) this so‐called double tailing occurs when stage two of nitrification
(conversion of nitrite to nitrate) is slower than stage one of nitrification (conversion of
ammonium to nitrite). The increase in the rate after the first drop can be attributed to
bacterial growth and thus to a higher conversion rate (Wainright 1987; Sloth et al. 1996).
Oxygen consumption by nitrification therefore depends not only on ammonium concentration
but also on the activity and density of microorganisms.
The third phase is dominated by the mineralisation of organic substances. The
mineralisation rate is determined by the composition and degradability of the organic matter.
Fresh algal biomass shows a greater and faster degradability than older or terrestrial biomass
(Arndt et al. 2013). Therefore, this algal biomass is easily consumed and can enhance the
oxygen consumption, in contrast to sediments with only refractory organic matter. This
relationship is highlighted by the high correlations between the sediment chlorophyll
concentration and the oxygen consumption. The third phase shows the lowest consumption
rate but has the highest consumption potential in relation to a long‐term resuspension due to
the storage of TOC. Therefore, the relative effect of carbon mineralisation on the oxygen
consumption is lowest at the beginning and increases with time.
The OCP showed the highest correlation with the chlorophyll values. As a degradation
product of fresh algal biomass, it serves as an indicator of this. The high correlation between
Ntotal and chlorophyll can be explained by the accumulation of dead algal biomass. As a result,
the sediment is enriched with fresh biomass and nitrogen, because they have a close
TOC/Ntotal ratio (Meyers 1994).
The aim of the model development was to enable the prognosis of oxygen
consumption of resuspended sediments based on easily available sediment properties. The
chlorophyll content showed the strongest correlation to the OCP, but it is not a typical
parameter that is determined by standard methods. Therefore, this parameter was excluded
from the search for proxies. Within the available standard properties, Ntotal showed the
strongest relation to the 168 h oxygen consumption and to the chlorophyll content. The
correlation between TOC and Ntotal and oxygen consumption differed only slightly in the spatial
analysis. In the temporal analysis, however, Ntotal showed a higher correlation with the OCP
than TOC.
57
In the comparison of the calculated and measured oxygen consumption, the model
was able to predict the oxygen consumption. The deviations show in most cases a NRMSE less
than 0.2. However, in some samples the oxygen consumption was substantially over‐ or
underestimated. This can have various origins. The functional parameters for the calculation
of the mineralisation were adjusted based on the last phase of the cumulative oxygen
consumption curve. In some cases, the consumption rate did not decrease consistently due to
mineralisation. This can be explained by the composition of the organic matter. If the organic
matter consists of a well and a poorly degradable fraction, the rate may decrease during
mineralisation when the well degradable fraction has been consumed. Likewise, nitrogen
tailing and bacterial growth are not included as parameters in the model, although their
inclusion may lead to an improved estimation. The model was calibrated using the samples
from the spatial analysis, which were taken in summer. The calculation of the oxygen
consumption curves based on the nitrogen contents from the temporal analysis showed the
largest deviations in winter, when the overall OCP is lower. In summer, however, the
consumption could be predicted with small deviations (NRMSE = 0.09). Seasonal processes,
such as the type and composition of the microorganisms and their activity, the quality of the
organic matter, and its TOC/Ntotal ratio are not included in the model, which may be a reason
for the larger deviation in winter months. If necessary, a calibration of the model with oxygen
consumption curves from the winter months could improve the fitting. However, the model
is well suited to assess the OCP of sediments under resuspension in the critical summer
months with ecologically relevant high values. It must be taken into account that the tests
were carried out under laboratory conditions, and the sediment rarely remains in suspension
for this amount of time.
A.5 Conclusion
The sediments within the Port of Hamburg show a strong spatial variability in their
composition and OCP. This high variability makes it difficult to estimate the effects of
resuspension on the oxygen balance and nutrient release, for example due to maintenance
measures such as water injection dredging. We have shown that the oxygen consumption
after 168 h is strongly dependent on the chlorophyll, Ntotal, and TOC content, so future studies
should focus on these factors. The OCP after 168 h can be described by sulphate formation,
nitrification, and mineralisation, whereby these three processes show different reaction
kinetics. The developed prognosis model calculates the oxygen consumption by using a single
sediment parameter. The model shows the best adjustment in the months critical for the
oxygen budget from April to August. The OCP of sediments can thus be calculated for any
resuspension duration and can therefore lead to an improvement of maintenance measures
and their effects.
59
Appendix publication B
Oxygen Consumption of Resuspended Sediments of the Upper Elbe
Estuary: Spatial and Temporal Dynamics
M.J. Spieckermann1, A. Gröngröft1, M. Karrasch2, A. Eschenbach1
1 Institute of Soil Science, CEN, University of Hamburg, Hamburg, Germany
2 Hamburg Port Authority, Hamburg, Germany
AUTHOR CONTRIBUTION: The authors Mathias Spieckermann, Alexander Gröngröft,
Maja Karrasch and Annette Eschenbach conceived and designed the study. Material
preparation, data collection and analysis were carried out by Mathias Spieckermann. The
first draft of the manuscript was written by Mathias Spieckermann. All authors contributed
through discussion on the interpretations of the results.
60
Abstract
Resuspension of sediments can lead to a strong reduction of dissolved oxygen in a water body,
whereby the sediment composition determines the amount of consumed oxygen. The local
composition of the sediment is controlled by the flow regime and the load of organic matter
transported by the river, with both variables varying spatially and seasonally. Depending on
the temperature, sediment composition, and microbial activity, sediments may exhibit a high
oxygen consumption potential (OCP). In this study, the spatial and temporal variability of the
OCP of sediments from the upper Elbe estuary including the Hamburg port area was
investigated. Seven‐day incubation experiments were conducted to examine the OCP during
resuspension. Sediment properties and pore water concentrations were analyzed to identify
the influencing factors of the OCP. Irrespective of the variation in temperature, in summer the
OCP is up to 5.5 times higher than in winter. Chlorophyll, Ntotal, and TOC show a positive
significant correlation with the OCP. Within the study area the OCP of the sediments varied
between 0.005 and 0.967 mmol O2 g d.wt.‐1. The highest OCP and total chlorophyll
concentration was found in the transition zone between the shallow and deeper navigable
area of the harbour. OCP is therefore controlled not only by the texture and amount of organic
matter but also by the supply and sedimentation of fresh organic material from upstream.
Through the extensive spatial and seasonal observation of the OCP of sediments, the results
can help to better evaluate the consequences of resuspension events on the oxygen balance
of the Elbe water.
B.1 Introduction
Dissolved oxygen has a strong influence on the biological health of rivers (Williams and
Boorman 2012) and is used as an indicator for the quality of surface water bodies (Cude 2001;
Bayram et al. 2015). Oxygen, produced by photosynthesis or ingressed into surface waters by
exchange with the atmosphere, is consumed by respiration, the degradation of organic matter
and the oxidation of reduced compounds. In the upper part of the Elbe estuary a strong
decline in dissolved oxygen concentrations is observed in the summer months (Bergemann et
al. 1996; Schroeder 1997; Schöl et al. 2014; Sanders et al. 2017), regularly reaching critical
values of less than 4 mg O2 l‐1. Schroeder (1997) concluded that this decline is mainly
attributed to algal respiration and carbon degradation. The oxygen consumption takes place
directly in the water phase or in the upper layers of the sediments. The sediment oxygen
demand (SOD) is a widely used measure of total benthic mineralisation (Glud 2008) and as an
indicator of the influence of sediments on the oxygen budget of a water body. According to
Matlock et al. (2003) and Rutherford et al. (1991), SOD can account for more than 50% of the
total oxygen consumption in natural rivers. With regard to the upper Elbe estuary, the
contribution of SOD to the total oxygen budget has not been quantified.
Many sediment properties have been found to control SOD, such as sediment organic
matter, nitrogen, and pigments (chlorophyll‐a, phaeopigment‐a, total carotenoids), as well as
the water depth and spatial location of the sediments (Vidal et al. 1992; Duineveld et al. 1997;
61
Grant et al. 2002; Giles et al. 2007; Mügler et al. 2012). In addition, water temperature shows
a positive correlation with SOD (Hopkinsion et al. 2001; Fulweiler et al. 2010). Many authors
have reported a seasonal variability in SOD, with an increase in summer and a decrease in
winter in rivers and coastal sediments (Rasmussen and Jørgensen 1992; Rysgaard et al. 1995;
Hopkinsion et al. 2001; Akomeah and Lindenschmidt 2017). This variation is explained by
changes in microbial and macrofauna activity and a variation in the input of labile organic
matter such as dead settled algae.
However, most of these studies focused on the oxygen flux at the sediment water
boundary, whereby only a few mm plays a role in organic‐rich sediments (Glud 2008). The
spatial and temporal variability of the OCP of the bulk sediment, especially of deeper sediment
layers, is less understood. In port areas it is often necessary to remove sediments to ensure
the fairway depth. These measures contribute to the resuspension of surface and deeper
sediments in addition to tidal current and anthropogenic influences such as the propeller wash
from large ships (Stoscheck et al. 2014). In addition to hopper dredging, bed levelling and
water injection are used in the Elbe estuary to keep the fairway navigable if oxygen
concentrations are above 4 mg O2 l‐1 (Hamburg Port Authority 2018). A resuspension of
sediments can lead to increased oxygen consumption due to an increased release of reduced
inorganic compounds and greater concentration of organic matter within the water column
(Almroth et al. 2009; Sloth et al. 1996).
The upper estuary of the Elbe is a spatially and temporally dynamic area. Tidal flow
velocities vary strongly between the fairway and the rear parts of harbour basins. Due to low‐
flow areas or differences in cross‐flow sections, hot spots of sedimentation occur. Particulate
matter originates from the Middle Elbe and the North Sea and is mixed in varying proportions
within the upper estuary depending on the headwater discharge (Gröngröft et al. 1998;
Kleisinger et al. 2015; Reese et al. 2019). Additionally, seasonal changes in temperature and
phytoplankton concentration prevail. Therefore, it is assumed that this variability influences
the OCP of the Hamburg port sediments.
It is likely that these conditions have a cumulative effect on the observed periods of
oxygen deficiencies in summer. The quantification of OCP can therefore be used to provide a
better quantification of the oxygen problem within the upper Elbe estuary. However, detailed
studies on the spatial and temporal course of oxygen consumption during resuspension are
lacking so far. This study thus aims to characterize the spatial and temporal variability of the
OCP of sediments within the upper Elbe estuary. The biochemical processes involved during
the oxygen consumption of resuspended sediments and the influencing sediment parameters
were explored in the first publication (Spieckermann et al. 2021a). To study the spatial
variability, sediment samples were taken at 21 sites distributed in the upper area of the
estuary including the Port of Hamburg. The temporal variability was determined by monthly
sampling at a single site, representing the respective present conditions, for a period of two
years.
The aim is to quantify the seasonal and spatial impact on the sediment composition
and OCP; therefore our key questions are:
62
(1) What seasonal changes occur with regard to the composition and OCP of sediments?
(2) How does the OCP vary spatially?
B.2 Material and Methods
B.2.1 Study Site and Sampling
The sampling site is located in the Port of Hamburg, one of the most frequented seaports in
North Europe. The Port of Hamburg is situated in the tidal Elbe River, which covers a distance
of 142 km from the weir Geesthacht to the North Sea. At stream‐km 609 the Elbe splits into
the Northern Elbe and the Southern Elbe, which flow together at stream‐km 626. In the
Southern Elbe there is an increase in water depth between stream‐km 615 and km 619.5 from
2.7 m to 15.1 m, to ensure the trafficability for ocean vessels. In the Northern Elbe this
increase is located between stream‐km 614 and km 624 (Figure B 1).
Two sampling campaigns were carried out to determine the spatial and temporal
variability in the OCP of sediments. For both campaigns, samples were taken from a ship with
a core sampler (Frahm‐Lot, length 80 cm, inner diameter 10 cm). For further laboratory
analyses the sediment layers 0–20 cm and 40–60 cm were separated. In the laboratory the
layers were homogenized under a nitrogen atmosphere and stored in airtight glasses at 4 °C
until measurement. Each homogenized sample was divided into two subsamples. The first
subsample was used to determine the OCP, and the airtight jar was opened only for this
purpose. The second subsample was used to extract the pore water and to determine the
sediment solid parameters. Samples from the first campaign (spatial variability) are composed
of three individual cores, which were combined to a single sample. In the second campaign
(temporal variability), the sampling consisted of two parallel samples. A more detailed
description of the sampling can be found in Spieckermann et al. (2021a).
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Figure B 1: Sampling locations within the upper Elbe estuary and the Port of Hamburg. Black dots
represent the sampling locations between stream‐km 589 (P1) and 643 (P21) for the analysis of the
spatial variability. P10 refers to the access area of the Hansahafen for the analysis of the seasonal
dynamic. The circles represent water monitoring stations (WMS) of the Hamburg Service Portal (source:
unpublished and adapted data from Hamburg Port Authority).
During the sampling campaign “spatial variability” (2017‐06‐30 to 2017‐07‐04), samples were
taken at 21 locations in the Port of Hamburg (Figure B 1). In order to obtain a large variety of
different sediments, samples were taken in the fairway, at the entrances, and at the end of
different harbour basins. Sample locations 1, 3, 5, 7, 15, 17, 18, and 21 represent the fairway
of the tidal Elbe and the fairway of the Northern and Southern Elbe. Locations 2, 4, 10, 11, 12,
16, and 20 were chosen to represent the entrance areas of different harbour basins; samples
6, 8, 9, 13, and 19 represent the end; and sample 14 represents the middle part of these
harbour basins. The sampling design was based on different flow velocities, sedimentation
rates, and distance to the fairway. At locations 3, 7, 17, and 18 no samples could be taken for
the lower layer.
The sampling campaign “temporal analysis” took place monthly from December 2016
to November 2018, with the exceptions of August 2017 and July and October 2018, when no
samples could be taken. To ensure that the sediment composition represents the current
environmental conditions, we selected a location with a known high sedimentation rate. Due
to the access area of the Hansahafen, between stream‐km 621 and 622 the Northern Elbe
shows an enlargement in the cross‐flow section. This leads to a decrease of the flow velocity
and an increase in the sedimentation rate with the formation of a mud lens. From regular
soundings, the location is noted for the highest sedimentation rates in the months of April to
64
June. At the edge of the mud lens this can be up to 2 cm day‐1 and up to 9 cm day‐1 in the
middle of the lens. For this reason, the entrance of the Hansahafen was selected as the
representative sampling site for the temporal analysis.
B.2.2 Sediment Characterisation
The analysis of the filtered pore water included ammonium (DIN 38406‐5) sulphate, nitrate,
nitrite (DIN EN ISO 10304‐1), dissolved iron (DIN 38406‐32), and dissolved manganese (DIN
38406‐33). Measured solid parameters were particle size distribution (DIN ISO 11277), total
carbon and nitrogen (Ntotal) (DIN ISO 10694), and inorganic carbon determined after
acidification with 42.5% phosphoric acid according to Luther‐Mosebach et al. (2018). Organic
carbon (TOC) was obtained by difference. For a detailed description, see Spieckermann et al.
(2021a).
As an indicator of fresh biomass, chlorophyll‐a and its degradation product
pheophytin‐a were analysed according to Lorenzen (1967). It was measured in the upper layer
of the samples from the spatial analysis and for the samples taken from April 2017 to
November 2018. The values given in the results section represent the sum of both parameters.
The carbon‐to‐chlorophyll ratio was assumed to be 40.5 according to Lorenzen (1968), which
falls in the range of published ratios (Jakobsen and Markager 2016).
For rough age estimations of sediments, the dates of the last maintenance dredging
measures at the sites were taken into account. In addition, the load of trace elements was
considered, which has been decreasing over time in the river Elbe since the 1990s (HPA,
unpublished document 2019). For the interpretation of the results, the sediments were
divided into two age categories: <2 years and >2 years.
B.2.3 OCP
Using incubation experiments, the spatial and temporal variability of the OCP of sediments
during resuspension were analysed. The OCP was determined with the respirometer BSB‐digi
O2 (Selutec, Germany). The respirometer measures the change in pressure due to the uptake
of oxygen in a constant volume and simultaneously by adsorption of produced CO2 by
mineralisation in 1 M sodium hydroxide solution. Under nitrogen atmosphere, 30 g of fresh
sediment were added to the incubation vessels (500 ml). Then 200 ml demineralised water
was added to the samples in the laboratory to allow resuspension. The samples were
subsequently connected to the respirometer and stirred at 300 rpm. The measurement
interval was 0.5 h, and the cumulative OCP was determined for 168 hours (OCP168) at 20 °C +‐
0.5 °C. Three replicates were performed per sample. Unfortunately, some cells failed. As a
result, the given errors represent the minimum and maximum values of the replicates. All runs
were made in the absence of light.
The oxygen consumption of resuspended sediments can be described by the
mineralisation of organic matter, nitrification, sulphate formation, and the oxidation of
reduced iron and manganese (Spieckermann et al. 2021a). Because the variability of these
processes and their influence on the OCP is unknown, a stoichiometric calculation of these
65
individual oxidation processes was carried out. Therefore, after incubation experiments the
supernatant water was filtered and analysed for nutrient concentration (sulphate, nitrite,
nitrate, iron, and manganese). The share of the mineralisation on the total consumption was
quantified by titration of the NaOH solution with 0.1 M HCl solution and phenolphthalein as
an indicator. The absorbed CO2 was calculated 1 to 1 into oxygen consumption. The calculation
was performed using the determined amounts of redox partners as described in
Spieckermann et al. (2021a).
A 2‐way ANOVA was performed to check if there were significant differences between
sediment age, layers, and locations of the samples and the processes involved in the oxygen
consumption. As the requirements for an ANOVA were not always met, a Kruskal‐Wallis test
was also carried out.
B.3 Results
B.3.1 Oxygen Dynamics in the Water Phase
During the two years of investigation, the properties of the water of the upper Elbe estuary
shows strong temporal dynamics (Figure B 2): The water temperature varies between 0 °C
(January to March) and 27 °C (July to August) in the years 2017 to 2018, whereby between the
two stations (Bunthaus and Seemannshöft) only slight differences have been observed (about
0.8 °C as a rule). The runoff is lowest in summer/autumn (250 m3 s‐1) and highest in
winter/spring (1300 m3 s‐1). The maximum is reached in March 2017. In 2018 the peak
occurred in January, two months earlier than in the previous year. The oxygen concentration
shows the opposite course than the water temperature. Between May and August, the oxygen
content is lowest at both stations. In order to distinguish between the temperature‐related
decrease in oxygen concentration and the decrease by consumption, the thin black line in
Figure B 2c represents the oxygen content (0% salinity, 1013 hPa) at 100% saturation for the
respective temperatures and days. While the values in Bunthaus are partly above this line
(>100% saturation), Seemannhöft shows much lower values. This difference indicates an
oxygen consumption between the two stations Bunthaus and Seemannshöft. Over the two
years, the oxygen content at Seemannshöft drops below 4 mg O2 l‐1 regularly in the summer
season, whereby the lowest value for 2017 is 2.9 mg O2 l‐1 (33% saturation) and 1.6 mg O2 l‐1
(19% saturation) for 2018. The chlorophyll concentrations in the water differ strongly between
both stations, with much less chlorophyll at the downstream position. At Bunthaus, both
studied years vary in the maximum concentrations of chlorophyll, with 162 µg l‐1 at the
beginning of May 2017 and 197 µg l‐1 at the end of May 2018.
66
Figure B 2: Properties of the river water measured at the stations Bunthaus at stream‐km 609 (grey
line) and Seemannshöft at stream‐km 629 (black line). a: course of temperature; b: runoff, recorded at
the station Neu Darchau (stream‐km 536); c: dissolved oxygen (the thin line represents oxygen
concentration at 100% saturation); d: total chlorophyll. (Source: Hamburg service Portal 2020).
B.3.2 Temporal Dynamics of Sediment Characteristics
The composition of the upper sediment layer changes regularly with the season. This was
found for the grain size parameters of fine sand, amount of particles <20 µm, and clay as well
as for the organic matter parameters TOC, Ntotal, and TOC/Ntotal ratio and some pore water
characteristics. Fitting these variables with a wave function resulted in extreme values around
mid‐February to the beginning of March and from the middle to end of August. Figure B 3
depicts the grain size fraction <20 µm as an example. The fitting for the upper layer
(RMSE = 11.46) indicates that the summerly peak in fine‐grained particles is nearly double that
of the winterly minimum.
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Figure B 3: Seasonal variation of the particle size fraction <20 µm for the upper (0–20 cm) and lower
(40–60 cm) layer. A sine wave function was fitted to the variables with a RMSE of 11.43 (p <0.05) for
the upper layer and an RMSE of 10.85 (p <0.05) for the lower layer. The thin line represents an adjusted
sine function with the respective 95% confidence band.
TOC and the TOC/Ntotal ratio also showed strong seasonal dynamics in the upper sediment
layer. During the warm season, the highest TOC values and the lowest TOC/Ntotal ratio were
measured (Figure B 4). For the lower layer, clear seasonal dynamics were not evident for most
of the studied sediment characteristics.
Figure B 4: Seasonal variation of the TOC (left) and the TOC/Ntotal ratio (right) of the sediments for the
upper (0–20 cm) and lower (40–60 cm) layer. A sine wave function was fitted to the variables with a
RMSE of 0.61 (p <0.05) for the upper layer (TOC), a RMSE of 0.44 (p <0.05) for the lower layer (TOC),
and a RMSE of 0.38 (p <0.05) for the upper layer (TOC/Ntotal’). The thin line represents an adjusted sine
function with the respective 95% confidence band.
Ammonium in pore water displayed a high temporal dynamic in both layers (Figure B 5). In the
warmer seasons the concentration increased, and in the colder season it decreased. The
sulphate concentration in the upper layer showed an opposite behaviour (Figure B 5). In the
lower layer most of the samples were without sulphate (below detection limit), and all of the
six samples with detectable sulphate concentration originated from the months of January to
April.
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Figure B 5: Seasonal variation of the ammonium and sulphate concentration in pore water for the upper
(0–20 cm) and lower (40–60 cm) layer. A sine wave function was fitted to the variables with a RMSE of
1.09 (p <0.05) for the upper layer (ammonium), a RMSE of 1.19 (p <0.05) for the lower layer
(ammonium), and a RMSE of 0.43 (p <0.05) for the upper layer (sulphate). The thin line represents an
adjusted sine function with the respective 95% confidence band.
B.3.3 Temporal Dynamics of OCP
The OCP168 given in Figure B 6 showed a clear seasonal variability within the upper layer. The
highest OCP168 was measured between May and September and is up to 5.5 times higher than
the lowest consumption potential between December and April. The OCP168 of the lower layer
did not show such a clear dynamic, similar to TOC and the TOC/Ntotal ratio. Here the OCP168
was 3.5 times higher in summer than in winter (Figure B 6). Some parallels showed larger
variances, which can be explained by the small‐scale spatial variability at the sampling
position. The oxygen consumption after three and 24 hours also showed a clear seasonal
dynamic. After three hours, the oxygen consumption between May and September was 13
times higher than the consumption between December and April. The same applies to the
measured oxygen consumption after 24 hours, where it was 10 times higher (data not shown).
Figure B 6: OCP analysed during laboratory incubation for 168 hours of upper (0–20 cm) and lower
sediment layers (40–60 cm) over two years’ time period. A sine wave function was fitted to the variables
with a RMSE of 0.05 (p <0.05) for the upper layer. Two replicates were taken per sampling and per
69
layer. The error bars indicate the min and max values of two to three parallels. The thin line represents
an adjusted sine function with the respective 95% confidence band.
As expected, TOC and OCP168 were strongly correlated (Spearman rsp = 0.752). To check the
temporal dynamic of the relation, the quotient of both parameters was calculated (Figure B
7). The results showed that more oxygen per gram TOC was consumed in the warmer season.
Thereby the oxygen consumption in relation to TOC can be 3 times higher than in the winter
months. This clearly indicates that the composition of the organic matter changes over the
seasons. This is underpinned by the seasonal dynamics of total chlorophyll concentration.
Chlorophyll also showed a strong temporal dynamic, with maximum concentrations between
June and August (Figure B 7).
Figure B 7: Temporal dynamics of the quotient calculated from the measured oxygen consumption after
168 hours and the TOC (left) and the measured total chlorophyll concentration in the upper sediment
layer (right). A sine wave function was fitted to the variables with a RMSE of 0.99 (p <0.05) for the
calculated quotient and a RMSE of 42.31 (p <0.05) for the total chlorophyll concentration. The thin line
represents an adjusted sine function with the respective 95% confidence band.
The detected OCP can be described by the superimposition of the three relevant processes
sulphate formation, nitrification, and mineralisation and can be calculated on the basis of the
Ntotal content of the sediments by our prognosis model (Spieckermann et al. 2021a). The
results showed that the sub‐processes are subject to a temporal dynamic and changing redox
conditions, and the highest values occur in the warm season (Figure B 8). If one compares the
minimum and maximum values of the years 2017 and 2018, the proportion of mineralisation
in the warmer months was up to 3 times (2017) and 4 times (2018) higher than in the colder
season. The proportion of nitrification was up to 5 times (2017) and 7 times (2018) higher, and
the sulphate formation increased up to 5 times (2017) and 6 times (2018).
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Figure B 8: Temporal dynamics of the oxygen‐consuming processes (sulphate formation, nitrification,
and mineralisation) and the measured oxygen consumption for the upper layer. The processes were
calculated using a prognosis model based on the nitrogen content (Spieckermann et al. 2021a). A sine
wave function was fitted to the variables with a RMSE of 0.05 (p <0.05) (oxygen consumption), a RMSE
of 0.03 (p <0.05) (mineralisation), a RMSE of 0.01 (p <0.05) (sulphate formation), and a RMSE of 0.01
(p <0.05) (nitrification). The thin line represents an adjusted sine function with the respective 95%
confidence band.
B.3.4 Spatial Variability of OCP
The mixture of the main river sections, shallow bays, closed‐end harbour basins, and inner‐
harbour connecting channels is responsible for varying tidal flow velocities and water
exchange rates. Consequently, the sediment composition follows these hydro‐morphological
features
(Spieckermann et al. 2021a): (i) Within the central sections of the Elbe River, pure sands (>97%
sand) dominated by medium sand (0.2–0.63 mm) are found. These sediments are almost free
of organic matter. (ii) Within the river borders and adjacent parts of the harbour basins,
sediments with mixtures of fine and coarse particles occur, dominated by fine sand (0.063–
0.2 mm) and coarse silt (20–63 µm) and with a medium amount of organic matter. (iii) In the
inner‐harbour channels, the rear parts of the harbour basins, and the closed bays along the
river with low water exchange rates, sediments with low sand content (<10%) and high
proportions of fine‐grained particles (<63 µm) and organic matter dominate.
Within the upper Elbe estuary, the OCP168 showed a high spatial variability (Figure B
9). The highest OCP168 was measured in the upper layer of location 4 (0.967 mmol O2 g d.wt.‐1)
where the fairway is deepened to 9 m for oceangoing vessels. The lowest OCP168 was
measured at location 7 (0.005 mmol O2 g d.wt.‐1), which had the lowest TOC content
(0.2%‐d.wt.) and chlorophyll concentration (1.7 µg g d.wt.‐1) (Spieckermann et al. 2021a). This
site was located directly in the fairway, and its sediment had a sand content of 99 %‐d.wt. The
results showed that with increasing stream‐km the OCP168 slightly decreases, and there is no
obvious trend for the upper or lower sediment layer to consume more oxygen (Figure B 9). A
Spearman correlation analysis showed that the OCP168 is highly correlated with TOC
71
(rsp = 0.939), Ntotal (rsp = 0.946), and total chlorophyll (rsp = 0.960). As can be seen from Figure
B 10, the quotient between the measured OCP and the TOC as well as the proportion of
chlorophyll‐C relative to TOC decreases with increasing stream‐km as a rule. The highest
quotient and proportion were measured at the beginning of the deepened fairway in the
Southern Elbe at location 4 (stream‐km 615.5). Site 5 showed a high proportion of chlorophyll‐
C in the TOC but has a relatively low OCP168, which is explained by the low TOC content
(1.4%‐d.wt.) of the sample.
Figure B 9: Spatial variability of the measured OCP168 for the upper and lower sediment layers of sites
1 to 21 in the order of the stream‐km. The error bars indicate the min and max values of two to three
parallels. * no sample exists for the lower layer.
Figure B 10: Quotient calculated from the measured oxygen consumption after 168 hours and the TOC
(right) for the data set “spatial analysis.” Proportion of chlorophyll‐C to total TOC content (left) for the
upper layer and the data set “spatial analysis.” Chlorophyll‐C was calculated with the factor 40.5
according to Lorenzen (1967). Sites 1 to 21 in the order of the stream‐km. * no sample exists for the
lower layer.
In addition to the spatial variability in the OCP, the sediment age also showed an influence on
the proportions of oxygen‐consuming processes. The two groups of old and young sediments
72
differed from each other in terms of the percentage of the calculated oxygen consumption by
sulphate formation, nitrification, and mineralisation (Figure B 11). Sulphate formation
(p <0.05) and nitrification (p <0.05) differed significantly between the two age groups for both
layers. Mineralisation showed a significant difference between the two age groups for the
lower layer (p <0.05) and a p‐value of 0.06 for the upper layer. The old sediments had on
average 19% less oxygen consumption by mineralisation, 12% less by nitrification, and 31%
more by sulphate formation. An exception was the sample of position 7, which also showed a
high proportion of oxygen consumption due to sulphate formation. However, this sample is
outstanding due to its extremely low TOC content and OCP168 value. Except for the age
differentiation of the sediments, a statistical evaluation showed no significant differences
between the layers, the locations (fairway, entrance and end areas of the harbour basins), and
the calculated process proportions involved in the OCP.
Figure B 11: Percentage of the sub‐processes of OCP168 for the upper layer (L1) and lower layer (L2). The
samples are divided into sediments younger and older than two years. Sites 1 to 21 in the order of the
stream‐km. + proportion of mineralisation was calculated according to Spieckermann et al. (2021a).
B.4 Discussion
B.4.1 Temporal Dynamic
Water temperature, oxygen saturation, and algal biomass in the Elbe estuary show a distinct
seasonal dynamic and, as demonstrated by our measurements, they can affect the sediment
composition and thus the OCP of sediments during resuspension. In the results from long‐
term monitoring of the Elbe water quality, the studied years 2017 and 2018 show a particularly
73
low runoff compared to the 30‐year average. The average of the years 2014–2019 is 487 m3 s‐1,
whereas the long‐term average is almost 700 m3 s‐1 (WTI 2019).
The oxygen concentration in the water shows a strong decrease between the stations
Bunthaus and Seemannshöft in summer. Various authors have already described these oxygen
deficits in the water body (Bergemann et al. 1996; Schroeder 1997; Schöl et al. 2014). Algae
respiration and the degradation of freshly transported organic matter from the upper stream
control the oxygen concentration in the water phase during the warm season (Kerner and
Gramm 1995; Schroeder 1997; Kerner 2000, Schöl et al. 2014). According to Schöl et al. (2014),
zooplankton also contributes to the lack of oxygen. Algae growth, however, is determined by
various factors, such as input of nutrients from agriculture (Kerner 2000) or water
temperature and flow velocity (Quiel et al. 2011).
Additionally, the OCP of the sediments shows a strong temporal variability with
maximum values in May and June. The studied uppermost layer of the sediments (0–20 cm)
showed a clear temporal response to the changes in the water column. The results showed
that during the summer months, the material is substantially more fine‐grained, has more
TOC, and has a higher proportion of total chlorophyll and thus a lowered TOC/Ntotal ratio. This
temporal variability within the sediment composition can be attributed to the reduced
headwater discharge velocities in combination with algae mass development. The reduction
in headwater discharge leads to an increased sedimentation of finer particles and thus to an
accumulation of organic material that is associated with the fine‐grained fraction (de Haas et
al. 2002; Giles et al. 2007). On the other hand, the increased algal masses lead to an
enrichment of the sediment with nitrogen and carbon and due to the close TOC/Ntotal ratio of
algae (Meyers 1994) and to a lowered TOC/Ntotal ratio. When algae die, they sink to the bottom
of the river and enrich the sediment with fresh organic biomass, as can be seen from the
determined total chlorophyll concentration of the sediment. This variation within the
sediment composition leads to a high temporal variability of the OCP of sediments. TOC, Ntotal,
and chlorophyll are highly positively correlated with the OCP of sediments (Spieckermann et
al. 2021a). During the warm season, the OCP168 was up to 5.5 times higher than in the cold
season. Additionally, this difference further expands when the river water temperature is
taken into account. The calculated quotient between the measured oxygen consumption and
the TOC content shows that up to 3 times more oxygen can be consumed per gram of TOC,
which underpins the greater degradability of the organic matter during phases of algae
breakdown. Likewise, the measured oxygen consumption after three and 24 hours shows a
strong seasonal variability. Due to the changed pore water composition, the proportions of
the oxygen‐consuming processes increase in summer. The rapid biochemical oxidation of iron,
manganese, and sulphides influences the oxygen consumption within the first hours, whereas
nitrification has an influence on the oxygen consumption over a longer period of time
(Spieckermann et al. 2021a).
Besides the changed input of oxygen‐consuming compounds over the year, the change
in temperature also contributes to a change in the OCP of sediments. An increase in water
temperature leads to a decrease of the solubility of oxygen and to an increase in microbial
activity. Due to the reduced solubility and increased microbial activity, more reduced
74
conditions result in the sediment (Jørgensen 1977). The increased ammonium concentration
and the decreased sulphate concentration in the pore water indicate a change to suboxic and
anoxic conditions in the sediment (Froelich et al. 1979). In their investigations, Nedwell and
Floodgate (1972) also showed an increased sulphate reduction during the summer, as the
activity of the sulphate‐reducing microbial population in winter was limited by the
temperature. Ammonium accumulates in the pore water due to the anaerobic mineralisation
of organic matter (Mackin and Aller 1984), while sulphate is reduced under anoxic conditions
to hydrogen sulphide (Pallud and Van Cappellen 2006), which reacts with iron to form pyrite
and other iron sulphides (Berner 1984). Therefore, the sediment is enriched with reduced
compounds during the warmer months, which leads to higher oxygen consumption during a
resuspension event. This is shown by the increased oxygen consumption due to nitrification
and sulphate during the warmer months (Figure B 8).
Our results showed a lower seasonal dynamic in the lower sediment layer with respect
to TOC, TOC/Ntotal ratio, and the OCP168. Because the input of fresh organic algal biomass
shows a high influence on the OCP, the seasonal dynamics are weakened by its degradation.
In the course of the year, the upper sediment layer is overlaid and the organic material is
degraded under anaerobic conditions. Due to the sediment depth and the associated longer
degradation times, the reactivity of the organic matter decreases and the seasonal influence
is weakened. A further reduction of the seasonal dynamics of the lower sediment layers can
be achieved by sediment consolidation. With increasing sediment depth, the material
solidifies and compacts, which can lead to the lower sample containing more depositional
periods than the upper one. Another possibility might be that the deeper layers have been
disturbed by fairway maintenance measures such as bed levelling and water injection.
However, if so, such a perturbation seems to be negligibly small for the upper layer because
the OCP increases or decreases at the respective season even if maintenance measures were
carried out beforehand.
B.4.2 Spatial Variability
The spatial analysis of the sediments showed a distinct distribution with respect to the OCP168
and the oxygen‐consuming processes. The highest OCP168 occurred at location 4
(0.967 mmol O2 g d.wt.‐1), where the navigable depth for ocean vessels of the Elbe begins. This
location also shows the highest total chlorophyll concentration. Due to the increasing water
depth (from 2.7 m to about 15 m below MSL) and the resulting lightless deeper area, the
phytoplankton dies (Schöl et al. 2014), resulting in the enrichment of fresh biomass in the
sediment. Further, toward the direction of the sea, the decrease of the OCP results from a
lower input of fresh biomass combined with a decrease of the degradability of the organic
matter, as described by Zander et al. (2020).
The samples showed a high variability with respect to the different oxygen‐consuming
processes. The proportion of mineralisation of the young sediments had a higher share in the
total oxygen consumption than the old sediments. This can be attributed to the age of the
organic material. During degradation, labile organic compounds are preferentially degraded,
75
which leads to a selective decrease in the reactivity of the organic material over time (Arndt
et al. 2013). Additionally, with ongoing anaerobic degradation of organic matter, the
concentration of ammonium in the pore water and at the exchange complex increases (Kofod
1994) and, due to sulphate respiration, reduced sulphur compounds (FeS or FeS2) accumulate.
The resuspension of the old sediments led to a high sulphate formation and a lower oxygen
consumption due to mineralisation, which is shown by Figure B 11.
The input of fresh organic biomass controls the behavior of the OCP of sediments in
space and time. TOC and Ntotal and thus also the texture affect the OCP of the sediments.
Furthermore, the position (longitudinal gradient) has an influence on the OCP and the
composition of the sediments. Old sediments show a significant change in the percentage
composition of the oxygen‐consuming processes, with increased oxygen consumption due to
sulphate formation and reduced consumption due to mineralisation and nitrification.
B.5 Conclusion
For the first time a detailed investigation on the spatial and seasonal variability of the OCP of
sediments in the estuarine harbour of Hamburg was conducted. In the Elbe estuary, the
variability of OCP of sediments under resuspension is—in addition to the hydrographic
conditions—mainly controlled by the input of fresh organic biomass and the changed redox
conditions due to the change in temperature and oxygen concentration. In seasonal terms,
the upper sediment layer is most strongly influenced. In summer it shows a 5.5‐fold higher
OCP than in winter. Spatially, there was a longitudinal gradient in the OCP of the sediments,
whereby the OCP decreased with increasing stream‐km. Spatial changes, such as the increase
of the fairway depth of the Elbe (location 4), can serve as a hot spot for the enrichment of the
sediments with fresh organic biomass, which leads to a high OCP of the sediments. Our results
on the parameters that influence the oxygen consumption of sediments during resuspension
are consistent with other studies, which determined the oxygen fluxes into the sediment. A
larger amount of resuspended sediments can have a high impact on the oxygen budget of a
water body. The results obtained provide a more precise insight into the OCP of harbour
sediments and can thus be used to quantify the effects of resuspension events on the oxygen
balance of the Elbe water, whereby a resuspension of the upper sediment layer is caused by
the stream current, by propeller wash, and by maintenance measures. A release of larger
amounts of material from deeper sediment layers occurs during dumping and water injection
operations. However, dumping is not allowed in Hamburg in summer and water injection is
prohibited at oxygen concentrations below 4 mg O2 l‐1 not to worsen the oxygen deficit. This
study focused on the oxygen consumption of sediments during resuspension. But the oxygen
consumption of sediments in the case of non‐resuspension is also an important factor. The
influence of this consumption on the oxygen budget of the Elbe, especially in the summer
months with a strong decline of the oxygen concentration, could not be answered in this
study. Therefore, further investigations should focus on the SOD at stable conditions, if we
want to know more about the influence of sediments on the oxygen budget of the river Elbe.
77
Appendix publication C
Temperature‐Dependent Oxygen Consumption of Sediments of the
Upper Elbe Estuary
M.J. Spieckermann, A. Gröngröft, A. Eschenbach
Institute of Soil Science, CEN, University of Hamburg, Hamburg, Germany
AUTHOR CONTRIBUTION: The authors Mathias Spieckermann, Alexander Gröngröft, and
Annette Eschenbach conceived and designed the study. Material preparation, data collection
and analysis was carried out by Mathias Spieckermann. The first draft of the manuscript was
written by Mathias Spieckermann. All authors contributed through discussion on the
interpretations of the results.
78
Abstract
Sediment oxygen demand (SOD) can strongly influence the oxygen budget of a water body
and can thus affect the ecological health of an aquatic ecosystem. Thereby, SOD rates are
positively related to the amount and degradability of organic matter and to the temperature.
Minimum oxygen zones regularly occur in the area of the upper Elbe estuary. The influence of
SOD in this area is not yet fully understood. To our knowledge, we were the first to measure
high‐resolution oxygen depth profiles in the area of the Port of Hamburg and used them to
determine the SOD rates. Sediments from three locations were studied at different times and
oxygen depth profiles at 5 °C, 15 °C and 25 °C were measured in the laboratory. Our results
are consistent with the results of other studies, who measured a temperature effect of SOD.
A rise in temperature leads to a decrease in oxygen penetrations depth and an increase in
SOD. Two sites show similar changes with temperature, although they are composed
different, while one site showed a stronger increase in SOD rate with increasing temperature.
Seasonal changes in the sediment and pore water composition and bacterial
productivity/biomass could be the reason for the higher SOD rate, as this sample was taken in
August. Comparing our results with the findings of other authors leads to the conclusion the
SOD of Port of Hamburg sediments have a high potential in effecting the oxygen budget of the
Elbe River water.
C.1 Introduction
Sediment oxygen demand (SOD) is a highly dynamic process with respect to a spatial and
seasonal scale (Matlock et al. 2003; Akomeah and Lindenschmidt 2017). It correlates positively
with the proportion and degradability of organic matter, the nitrogen content and the silt and
clay content (Giles et al. 2007) as well as with the temperature (Hopkinsion et al. 2001;
Fulweiler et al. 2010; de Klein et al. 2017). It is necessary to understand how and to what
extent sediments consume oxygen in order to improve modelling approaches that are a
helpful tool in trying to reduce environmental impacts.
The availability of dissolved oxygen is a prerequisite for an intact aquatic ecosystem. It
is produced during photosynthesis and consumed directly or indirectly through the
decomposition of organic matter (Glud 2008). The concentration of dissolved oxygen has a
major influence on the sulphur, nitrogen, phosphorus and carbon cycles and influences the
metabolic processes taking place in the sediment. This indirectly controls the pore water
composition and the fate of metals and metal oxides (Cai and Sayles 1996). In aquatic
sediments, oxygen can be consumed by three processes: aerobic decomposition of organic
matter, respiration, and the oxidation of reduced compounds (NH4+, Fe2+, Mn2+, H2S, FeS and
FeS2) derived from anaerobic metabolism (Berg et al. 2003; Spieckermann et al. 2021a).
In the area of the tidal Elbe (Northern Germany), oxygen minimum zones are formed
in the summer months, which can extend as far as to the Port of Hamburg. Within this zone,
the oxygen content may drop to critical values for aquatic life (≤3 mg O2 l‐1). This decline is
mainly attributed to algal respiration and carbon degradation (Schroeder 1997) as well as to
79
zooplankton grazing (Schöl et al. 2014). Oxygen is thus consumed directly in the water phase.
To which extend the decline in oxygen concentration is additionally influenced by oxygen
consumption from the Elbe River sediments is unclear. Investigations of other rivers have
shown that the oxygen consumption of sediments can be the major source of water column
oxygen depletion (Boynton and Kemp 1985; Rutherford et al. 1991; Matlock et al. 2003;
MacPherson et al. 2007). The oxygen consumption by sediments can take place either by
resuspension of the sediments, whereby increased amounts of nutrients and reduced
substances are released into the water phase (Kristensen et al. 1992; Wainright and
Hopkinson 1997; Gibson et al. 2015), or under stable conditions.
Under stable conditions, oxygen diffusely penetrates the sediment. The penetration
depth is regulated by the organic carbon degradation, the oxygen concentration of the water
and the transport of oxygen from the water phase into the sediment, whereby the sediment
porosity and the diffusion coefficient of oxygen plays a role (Cai and Sayles 1996). The oxic
zone can range from a few mm in organic rich sediments (Sweerts et al. 1989) to several cm
in organic poor sediments (Wenzhöfer et al. 2001).
Giles et al. (2007) showed in their experiments on the northeastern New Zealand
continental shelf that the oxygen uptake is strongly dependent on water depth and the
distance to terrestrial and riverine input, with the highest oxygen uptake being measured at
the shallowest point (4.2 m; 1222 µmol m‐2 h‐1) and the lowest at the deepest point (360 m;
128 µmol m‐2 h‐1). A high spatial variability in sediment oxygen uptake was also found by
Matlock et al. (2003). Their investigations in the Arroyo Colorado River show differences of up
to two orders of magnitude between sites that were less than 2 km apart. They concluded
that the oxygen consumption under stable conditions is influenced by the sediment
composition, predominantly by sedimentation of organic‐rich material.
Despite the regular occurrence of oxygen minimum zones in the Port of Hamburg, less
attention was paid to oxygen consumption by sediments. Due to the high variability of the
sediment composition in the area of the Port of Hamburg, it is of interest to quantify the
oxygen consumption by characteristic sediment parameters and to integrate this knowledge
into water quality models in order to provide better forecasts. The oxygen consumption of
resuspended sediments has been quantified by Spieckermann et al. (2021b).
The aim of this study is to determine the SOD of Hamburg harbour sediments under
stable conditions for the first time using high‐resolution oxygen depth profiles; therefore, our
questions are:
(1) What is the oxygen consumption of Hamburg harbour sediments under stable
conditions?
(2) What influence does the temperature have on the oxygen consumption rates of
sediments under stable conditions?
80
C.2 Material and Methods
C.2.1 Sampling and Basic Analyses
The upper Elbe estuary (Northern Germany) which comprises the Port of Hamburg and
adjacent parts of the river is characterised by fresh water from the Middle Elbe River and a
tidal amplitude of about 3.66 m in the harbour area. Here at stream‐km 609, the river splits
into the Northern Elbe and Southern Elbe and reunites at stream‐km 626 (Figure C 1). From
stream‐km 624 (North Elbe) and stream‐km 619 (South Elbe) downstream, the Elbe estuary
has been deepened by dredging for ocean going vessels resulting in a depth of the fairway and
the harbour basin of about 15 m below MSL.
Sediment samples were taken from a ship with a core sampler (Frahm‐Lot, core
length 80 cm, inner diameter 10 cm) at three positions within the estuary (Figure C 1) at a
water depth of approximately 10 m: Hansahafen, Köhlfleet and Fairway Norderelbe. The
amount of supernatant water in the core was about 10 to 20 cm. On board, the core was
sealed airtight and transported upright and carefully to the laboratory. Without further
processing, the sediments in the core were used to measure the oxygen concentration
profiles. Afterwards sediment samples were extracted from the column down to 5 cm depth,
the samples prepared and the solid sediment parameters analysed.
Figure C 1: Map of the Port of Hamburg and locations of the investigated sediments. The numbers mark
the stream‐km (source: unpublished and adapted data from Hamburg Port Authority).
The analysis of the solid sediment parameters included the particle size distribution (DIN ISO
11277), total carbon (Ctotal) and nitrogen (Ntotal) content (DIN ISO 10694). Inorganic carbon was
determined after acidification with 42.5% phosphoric acid according to Luther‐Mosebach et
81
al. (2018). Organic carbon (TOC) was obtained by difference. The porosity was calculated
according to Avnimelech et al. (2001). The volume of the sediment sample was calculated
from the ratio between the dry weight of the sample and the average sediment particle
density, corrected for the proportion of organic matter and the weight of the wet sample.
C.2.2 High Resolutions Oxygen Concentration Profiles
In the laboratory, the cores were placed upright in a temperature controlled water bath. The
samples were allowed to adjust to the temperature for at least 12 h until the measurements
were started. The measurement of the oxygen concentration profiles was performed in two
runs to determine the influence of temperature and the storage time. In the first run the
oxygen concentration profiles were measured at approximately 5 °C, 15 °C, and 25 °C. Then a
second run was performed starting again at 5 °C. After each temperature change in the water
bath, the oxygen depth profiles were measured after at least 12 hours, to allow a stabilization
of the temperature in the column and of the microbial activity. The oxygen concentration of
the supernatant water was adjusted to 100% by pumping air through a tube into the water
without stirring up sediment. The air supply was kept constant in all experiments as well as
the position of the tube. The saturation of the water was started at least three hours before
the measurements. The experiments were performed under room light. The profiles were
checked to see if there was an increase in oxygen concentration at the sediment surface due
to photosynthesis of algae. However, an increase in oxygen concentration was never
observed, thus we could exclude the impact of photosynthesis on the depth profiles.
The depth profiles were determined with the oxygen microsensors OX‐100 (UNISENSE,
Denmark) with a tip diameter of 100 µm. These Clark‐type sensors measure the oxygen partial
pressure, whereby oxygen diffuses through a silicone membrane and reduces at the cathode.
To obtain sufficient depth profiles, two sensors with a lateral distance of 3 cm were used
simultaneously. The measurement started in the water phase and the sensors were lowered
in 100 µm steps until the oxygen concentration dropped to zero. For each core and
temperature level, the measurements ended after at least six depth profiles were measured
successfully. Some measurements had to be aborted because the sensors broke or an increase
of oxygen in the deeper layer was observed, which led to profiles for which the oxygen
consumption rates could not be calculated. This oxygen increase can be explained by
mesofauna living in the sediment. Their digging activities can lead to an oxygen input into the
oxygen‐poorer deeper layers.
Using the software SensorTrace Suite (UNISENSE; Denmark), the oxygen consumption
rates for the corresponding sediments and temperatures were calculated from the measured
profiles. The calculations are based on the method reported by Berg et al. (1998). The
programme allows different boundary conditions. To calculate the rates of oxygen
consumption, either the boundary conditions “Top Concentration + Bottom Concentration”
or “Bottom Concentration + Bottom Flux” were selected. For further information, see Berg et
al. (1998) and the SensorTrace Suite User Manual (2020). Whereby, in a stationary state, the
net consumption as a function of depth can be calculated by using the concentration depth
82
profile, Ficks 1st law and the mass transport coefficient of oxygen in the sediment. The mass
transport coefficient can be calculated from the porosity of the sediment and the molecular
diffusion coefficient of oxygen in water.
In order to calculate the oxygen consumption rate, the sediment surface had to be
determined for the profiles. This was done either optically during the measurement, if this
was possible, or based on the profiles. Since the diffusion of oxygen in the sediment is slower
than in the water phase, there is a change in slope of the oxygen profile at the sediment‐water
interface. This point was then considered as the sediment surface.
C.3 Results
C.3.1 Sediment Characteristics
The sediments of the three locations differed strongly with respect to their composition (Table
C 1). The sediment of the Hansahafen showed the highest TOC/Ntotal ratio (9.4) as well as the
lowest porosity and the lowest fraction of particle <20 µm. At the location Köhlfleet the
sediment had the highest proportion of the grain size fraction <20 µm, the highest porosity
and a TOC/Ntotal ratio of 8.6. The sediment at the location Fairway Norderelbe had the lowest
TOC/Ntotal ratio. The porosity, TOC, Ntotal, and the fraction <20 µm were in the range between
the other two sites.
C.3.2 Oxygen Concentration Profiles
In general, all analysed depth profiles had a smooth course with a continuous reduction of
dissolved oxygen with depth in the sediment, as e.g. given by Glud (2008). For all depth
profiles, the total penetration depth of oxygen into the sediment ranged between 1200 µm
and 3900 µm. Looking at the temperature‐dependent oxygen depth profiles of the sediments
(Figure C 2), an increase in the penetration depth of oxygen into the sediment can be seen
with decreasing temperature. For the sediments from the Hansahafen the point at which
dissolved oxygen was no longer detectable shifts downwards from 1500 µm to 2300 µm
between the experiments at 25.2 °C and 6.5 °C (Figure C 2a and b). The sediment from the
location Köhlfleet showed the highest penetration depths of 3900 µm at the lowest
temperature.
83
Table C 1: Characterisation of sediment samples: Total carbon (Ctotal), total nitrogen (Ntotal), fraction of
grain size <20 µm (<20 µm), total organic carbon (TOC), TOC/Ntotal ratio, porosity and sampling date of
the investigated samples.
Location Ctotal Ntotal <20 µm TOC TOC/Ntotal Porosity
Sampling
date
[%‐d.wt.]
[%‐
d.wt.]
[%‐
d.wt.]
[%‐
d.wt.] [‐] [%]
Hansahafen 2.8 0.19 27.0 1.7 9.4 84.9 2018‐04‐20
Köhlfleet 5.4 0.48 78.8 4.1 8.6 96.4 2018‐06‐23
Fairway
Norderelbe 4.1 0.35 38.5 2.9 8.1 90.1
2018‐08‐28
Figure C 2: Temperature‐dependent oxygen depth profiles at approximately 5 °C, 15 °C, and 25 °C for the two runs per investigated location. a and b are the measured profiles of the location Hansahafen, c and d are the profiles of the location Köhllfeet and e and f are the profiles of the location Fairway Norderelbe. Error bars indicate the standard deviation of measured profiles (n= 6 to 11).
84
A comparison of the depth profiles for each temperature range between the corresponding
runs showed that within the total measuring time no major shift in oxygen consumption rates
occurred within the samples. For each depth step in the sediment, the difference between the
mean oxygen concentration of the two runs was calculated. The results showed that the
difference is usually smaller than the respective standard deviations of the mean values. An
exception was the location Hansahafen for the 14.7 °C and 14.9 °C measurement, but the
difference was only slightly larger and lies between 10 and 20 µmol O2 l‐1. Also, the mean
oxygen penetration depths showed no or only slight differences of 100 µm between the runs.
An exception is the location Fairway Norderelbe. Here the average penetration depths at
7.6 °C and 6.6 °C differ by 400 µm. One reason could be the higher temperature difference of
1 °C compared to the other samples and runs. Likewise, the runs from the Hansahafen site at
14.7 °C and 14.9 °C show a difference of 300 µm.
C.3.3 Oxygen Consumption Rates
The calculated oxygen consumption rates (Figure C 3 and Table C 2) for the sediments of the
three sites showed similar rates between 19.1 and 26.9 mmol O2 m‐2 d‐1 for temperatures at
about 5 °C. With increasing temperature, the calculated oxygen consumption rate of all sites
increased. The sediments of the Fairway Norderelbe showed the highest increase with
temperature with a slope of 3.03 mmol O2 m‐2 d‐1 °C‐1 (Table C 3). The sediments of location
Köhlfleet showed a medium increase with temperature with a slope of
1.73 mmol O2 m‐2 d‐1 °C‐1. At about 25 °C the lowest measured oxygen consumption rate was
46.7 ± 5.5 mmol O2 m‐2 d‐1 (Hansahafen) and the highest was 84.8 ± 25.6 mmol O2 m‐2 d‐1
(Fairway Norderelbe). The sediments of the site Fairway Norderelbe differed significantly from
the other two sites since the 95% confidence intervals do not overlap.
Table C 2: Temperature step, oxygen consumption rates, and number of measured depth profiles for
the three locations and runs.
Hansahafen Köhlfleet Fahrrinne Norderelbe
Runs [°C] [mmol O2 m‐2 d‐1] n [°C] [mmol O2 m‐2 d‐1] n [°C] [mmol O2 m‐2 d‐1] n
a) 6.5 19.1 ± 2.5 7 6.4 20.1 ± 1.9 8 7.6 26.9 ± 5.7 9
b) 6 23.7 ± 2.9 7 4.5 20.3 ± 4.1 9 6.6 25.8 ± 6.5 11
a) 14.9 29.8 ± 6.3 6 15 32 ± 3.3 9 15.5 41.1 ± 6.8 9
b) 14.7 28 ± 8.6 7 14.6 36.6 ± 6.8 10 15.7 57.2 ± 17.6 9
a) 25.2 51.7 ± 18.2 7 24.7 50.4 ± 7 8 25.8 80.6 ± 16.9 10
b) 24.7 46.7 ± 5.5 7 25.2 57.7 ± 12.9 8 25.5 84.4 ± 25.6 10
85
Figure C 3: Calculated oxygen consumption rates of the sediments of the three sites and at differnent
temperatures with fitted regression line and corresponding 95% confidence band. Error bars indicate
the standard deviation of the calculated consumption rates (n= 6 to 11).
Table C 3: Results of a linear regression analysis between the calculated oxygen consumption rates and
the adjusted temperatures for the three locations.
Location
Intersection with the Y‐axis
[mmol O2 m‐2 d‐1]
Slope
[mmol O2 m‐2 d‐1 °C‐
1] Adj. R2
Hansahafen 10.16 1.50 0.911
Köhlfleet 10.07 1.73 0.951
Fairway Norderelbe 3.75 3.03 0.946
C.4 Discussion
In this study, we tested the temperature dependence of SOD on samples of three location
from the Port of Hamburg. The results showed a decrease in oxygen penetration depth with
increasing temperature, which is consistent with other studies (Seiki et al. 1994; Hancke and
Glud 2004; de Klein et al. 2017). Within the natural range microbial activity increases with
rising temperature (McDonnell 1969), which leads to increased respiration (Hancke and Glud
2004; Allen et al. 2005). As a result, oxygen is consumed more rapidly and consequently the
penetration depth decreases. As the temperature increases, the rate of oxygen consumption
also increases which was also fund by Fulweiler et al. (2010). The sediments of the three sites
showed a different influence on temperature, with the site Fairway Norderelbe showing the
greatest change with increasing temperature. As the sediments were excavated at different
times (April, June and August) and locations, we cannot say exactly whether this is a seasonal
or spatial effect. An increase in the oxygen consumption rate after the 10‐degree‐rule could
not be observed. However, the sediments differed in their composition in terms of TOC, Ntotal
and the TOC/Ntotal ratio. It is known that SOD correlates positively with the proportion and
86
degradability of organic matter, particulate organic nitrogen (Giles et al. 2007; Kim and Kim
2007), and also with the sediments pigments (Vidal et al. 1992; Clough et al. 2005). Likewise,
seasonal changes in SOD are reported (Kim and Kim 2007) due to changes in temperature and
nutrient loads.
Due to the comparatively high TOC and Ntotal content, one would expect that the
sediments of the Köhlfleet site (5.4%‐d.wt. and 0.48%‐d.wt.) would show the highest
consumption rate with the highest temperature. However, the sediments of the site Fairway
Norderelbe showed the highest consumption rates, whereas this site had the lowest TOC/Ntotal
ratio. Even though Giles et al. (2007) found no significant correlation between the SOD and
the TOC/Ntotal ratio. A decrease in the TOC/Ntotal ratio is an indicator of algae sedimentation
(Therkildsen and Lomstein 1993) and therefore an indicator for fresh labile biomass. This in
turn can explain the increased consumption rates, as easily degradable organic biomass is
available. Therkildsen and Lomstein (1993) also found out that the sediment macrofauna
biomass correlates positively with temperature. Van Duyl and Kop (1994) found no seasonal
changes in the microbial biomass, but an increased productivity of the bacteria in August
compared to February. An increased productivity and or biomass may therefore also be the
reason for the higher SOD at the location Fairway Norderelbe, as sampling took place in
August.
Investigations within the study area on sediment composition and the oxygen
consumption potential of resuspended sediments have shown a strong seasonal dynamic. In
summer the oxygen consumption potential (OCP) of sediments was up to 5.5 times higher
than in winter, which could be explained by a higher input of TOC and fresh labile biomass
from dead algae (total chlorophyll) due to lower flow velocities and algae blooms. As a result,
the TOC/Ntotal ratio showed a lowering in the summer months. Due to the higher temperature
and the resulting lower oxygen saturation, more anoxic conditions prevail in the sediments
and the pore water was enriched with reduced substances. The investigations showed that
the sediment parameter chlorophyll and Ntotal have the strongest influence on the OCP of the
sediments in spatial and temporal relation and that the spatial variability in the sediment
composition had a higher influence on the OCP than the seasonal variability (Spieckermann et
al. 2021b).
The Köhlfleet site had a TOC and Ntotal content twice as high as the Hansahafen site,
with both sites showing similar oxygen consumption rates. Therefore, the spatial distribution
of TOC and Ntotal and its influence on oxygen consumption rates may be of less importance. In
contrast, the input and degradability of fresh biomass combined with the seasonal changes
seems to be of larger relevance. Especially since under stable conditions only the uppermost
mm of freshly deposited sediments play a role in oxygen consumption and deeper and older
material is of less interest.
However, the measured SOD level is consistent with the results of other authors.
Matlock et al. (2003) reported SOD rates between 4.1 and 37.5 mmol O2 m‐2 d‐1, which
represents 52 % to 94 % of the total oxygen uptake in the water phase. MacPherson et al.
(2007) measured mean rates between 36.3 and 67.2 mmol O2 m‐2 d‐1, which were significantly
higher than the biological oxygen demand of water samples. Boynton and Kemp (1985)
87
measured a SOD of 46.9 mmol O2 m‐2 d‐1 to 96.9 mmol O2 m ‐2 d‐1, which accounted for 16%
to 50% of total respiration in the water phase. Our measured rates are within these values.
The results indicate that the sediments could have a strong influence on the oxygen balance
of the Elbe water. In the studies mentioned, the SOD was determined by chamber incubation
experiments and not by oxygen microprofiles. However, SOD can vary considerably depending
on the method used.
The oxygen consumption of sediments calculated by microprofiles gives information
about the oxygen uptake within the oxic layer of sediments. A comparison of different
methods (chamber incubation with total oxygen uptake and oxygen microprofiles) for the
determination of SOD showed that oxygen microprofiles can lead to an underestimation of
total SOD (Kim and Kim 2007). Glud et al. (1994) showed in their experiments that the total
oxygen uptake was 1.2 to 4.2 times higher than the diffuse oxygen consumption. Rasmussen
and Jørgensen (1992) also found that the total oxygen uptake was on average 145 % higher
than the consumption calculated from the microprofiles. Both studies explained the
difference with the presence of marcofauna and that the total oxygen uptake is strongly
related to ventilation and respiration by macrofauna. In contrast, in the absence of
macrofauna, measurements of total oxygen uptake and microprofiles lead to similar results
(Rasmussen and Jørgensen 1992). Samples taken on 17.09.2018 also showed twice as high a
rate of oxygen consumption in a comparison between microprofiles and incubation
experiments (data not shown). This samples had a high number of macrofauna, and clear
traces of wormholes were visible at the core border. This should be taken into account when
interpreting the SOD and it influence of the oxygen budget of a water body.
For a complete consideration and differentiation of the oxygen consumption of
sediments, the consumption by the oxic sediment layer (oxygen depth profiles), the
consumption of the sediment surface (chamber incubation) and the consumption during
resuspension of sediments must be taken into account. Oxygen consumption during
resuspension is a time‐limited process (usually a few hours), which can exceed the oxygen
consumption at stable conditions multiple times. The increased oxygen consumption results
from the sudden release of oxygen‐consuming compounds when the sediment is disturbed.
In water quality models, the oxygen consumption is calculated by diffuse fluxes of reduced
substances out of the sediment and by the flux of oxygen into the sediment. The effect of
resuspension on the oxygen balance has not been taken into account in numerical models to
date (Moriarty et al. 2018). Especially in port areas, where large quantities of sediment are
often dredged and resuspended, it can be of great interest to calculate the impact of these
measures on the environment and to include seasonal variation in the oxygen flux in order to
prevent negative effects.
C.5 Conclusion
In our experiments, we were the first to investigate the SOD by high‐resolution oxygen depth
profiles in sediment cores from the area of the upper Elbe estuary. The results show that
sediments at stable conditions have a high potential to remove oxygen from the water phase.
88
The ambient temperature had a clear influence on oxygen consumption. Higher temperatures
increase the microbial activity and the pore water is enriched with reduced compounds, which
results in an increase in oxygen consumption rates. However, due to the decrease of the
consuming sediment volume with increasing temperature, the temperature effect is smaller
than the respective change in microbial activity (“10‐degrees‐rule”) and can be fitted with a
linear regression. Due to the different sediment composition of the three sites, different
oxygen uptake rates were expected, but the two sites with the largest difference in sediment
composition showed similar uptake rates within the studied temperature range. The low
TOC/Ntotal ratio and the changed conditions (August sample) within the sediment can be used
as an explanation for the high consumption rate of the site Fairway Norderelbe, even though
this site has a lower TOC and Ntotal content than the site Köhlfleet. This indicates that the
seasonal influence on SOD under stable conditions is stronger than the influence of the spatial
variability, due to more input of labile organic material, higher microbial activity and reduced
conditions. In order to quantify the influence of the in‐situ sediments on the oxygen balance
of the Elbe and the resulting oxygen minimum zones, the investigations should be intensified.
89
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