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Distributions of n-alkanes as a Palaeoenvironmental indicator in an Ombrotrophic Peat Bog (White Sea, Russia)
As partial fulfilment for: MChem with a year in Industry
In collaboration with the British Geological Survey
Loach, Oliver G.
2013-14
1. Abstract:
Subarctic ombrotrophic bogs hold vast amounts of terrestrial organic matter, which is
sensitive to climate change. n-Alkane distributions are frequently used as palaeoclimate
proxies in peat deposits. The distributions differ greatly between plant species, but n-
alkanes are not species specific molecules. It is important to know different abundances of
n-alkanes in various plant species because these molecular markers are especially useful in
highly decomposed peat where plant remains are no longer recognisable. A species of major
interest is Sphagnum moss, as it has interesting inter-species variation that can be detected
by their biomarkers, specifically the n-C23 and n-C25 alkanes. The aim of this study is to use
new and published proxies in order to elucidate how the vegetation can vary due to the
climate change over time. n-Alkane analysis of a 5 m core (White Sea, Russia) reveal shifts in
the n-C23/n-C25 ratio, which track changes in the abundance of S. fuscum comparable to
previous literature. A subarctic Sphagnum molecular proxy, (PSAS), was quantitatively used
based on the abundant and consistent n-alkanes throughout the core samples in order to
separate the Sphagnum dominated peat’s organic geochemical signal from the higher
terrestrial vegetation. The data gathered supports the application of n-alkane biomarkers in
peat archives for tracing past shifts in individual Sphagnum species abundance.
Contents1. Abstract:........................................................................................................................................2
2. Scope of the Industrial Year...........................................................................................................5
3. Introduction...................................................................................................................................5
3.1. Biosynthesis...........................................................................................................................6
3.2. C3 Plants.................................................................................................................................6
3.3. Organic Geochemical Applications........................................................................................7
3.4. Biomarker Applications..........................................................................................................9
3.5. Biomarker Proxies..................................................................................................................9
3.6 The Study Area.....................................................................................................................11
4. The Aim and Rationale.................................................................................................................12
2
5. Method........................................................................................................................................13
5.1. Gas Chromatography Flame Ionisation Detector (GC-FID)...................................................13
5.2. The Internal Standard..........................................................................................................14
5.3. Pilot Run..............................................................................................................................16
5.4. Sample Preparation.............................................................................................................16
5.5. Column Chromatography.....................................................................................................18
5.6. The GC-FID method..............................................................................................................18
6. Results and Discussion.................................................................................................................19
7. Conclusion...................................................................................................................................34
8. Other Project involvement..........................................................................................................36
8.1. Denmark Paleo-Eocene Thermal Maximum (PETM)............................................................36
8.2. Greek Tsunami.....................................................................................................................39
8.3. Molecular sieves..................................................................................................................40
8.4. Stalagmites..........................................................................................................................43
8.5. Total Petroleum Hydrocarbon (TPH) analysis......................................................................44
8.6. Carbon-13 Isotope preparation...........................................................................................48
8.7. Pant y llyn............................................................................................................................49
8.8. Lead-210 gamma spectroscopy...........................................................................................51
9. Problems and solutions...............................................................................................................53
10. Training of succeeding students..............................................................................................57
11. Acknowledgements.................................................................................................................58
12. Bibliography.............................................................................................................................59
Supplementary Information................................................................................................................63
Acronyms and Definitions:
ACL - Average Chain Length
ASE - Accelerated Solvent Extractor
BGS - British Geological Survey
CPI - Carbon Preference Index
DCM - Dichloromethane
EE - Extraction Efficiency
3
EOP - Even-over-Odd Predominance
FID - Flame Ionisation Detector
GC - Gas Chromatograph
HCL - Hydrochloric Acid
n-C - Straight Chain Alkane
NERC - Natural Environment Research Council
OEP - Odd-over-Even Predominance
PAH - Poly-Aromatic Hydrocarbons
Paq - Aquatic Ratio Proxy
PETM - Palaeo-Eocene Thermal Maximum
PSAS - Sub-Arctic Sphagnum Proxy
TAR - Terrigenous Aquatic Ratio
TOC - Total Organic Carbon
TPH - Total Petroleum Hydrocarbons
UCM - Unresolved Complex Mixture
2. Scope of the Industrial YearThe overall aim of the year was to get an insight and hands on approach to the research that
goes on outside of the University. Throughout the year, equipment was used that students
in the first three years don’t usually get to operate; performing method development and
improvement of laboratory/report writing skills were enhanced as the year progressed.
The British Geological Survey (BGS) is part of the Natural Environment Research Council
(NERC), which is the UK's main agency for funding and managing research, training, and
knowledge exchange in the environmental sciences.
4
Throughout the year there were many projects starting from the sample preparation, to
instrumental analysis through to data interpretation. There were also the important jobs
around the laboratory in order to retain quality and control, for instance regular balance
checks and fridge temperature readings for quality assurance and cleaning glassware with
chromic acid which were just a few of the many essential day to day activities.
3. IntroductionEpicuticular wax, found on the leaves of terrestrial plants, consists of an abundance of lipids
which are sub-categorised to n-alkanes, n-alkanoic acids and n-alcohols.
The leaf wax serves as a barrier from the surrounding environment, protecting the leaf from
the loss of water through evaporation (Jetter and Kunst (2008) [1]) bacterial and fungal
attacks, and to prevent leaching of important minerals by the rain. The n-alkanes are the
cause of hydrophobic properties of the leaf wax due to their lack of polarity. The wax
covering can vary for example; plants that grow in arid conditions have a thicker waxy
cuticle, thus containing longer n-alkanes than those that grow in colder environments.
3.1.BiosynthesisThe saturated aliphatics in the plant waxes are derived from the decarboxylation of fatty
acids. Fatty acids are long chain carboxylic acids that can be saturated or unsaturated. There
are many different synthesis routes, but they are commonly synthesised in plants via a
multi-enzyme elongase system which catalyses a series of reactions. The fatty acids are
formed through the use of the CoA enzyme and the process causes them to have an even-
over-odd preference (EOP). This is caused because an acetyl-CoA (C2) unit, which is derived
from glucose, reacts with a malonyl-CoA (C3) unit which produces a butyryl group (C4 )with
the loss of CO2 (Killops and Killops (2009) [2]). The 4 carbon unit then reacts with more
5
malonyl-CoA, thus building longer chain fatty acids (Figure 3.1.1). Biosynthesis of the
alkanes from the acids occurs by enzymatic decarboxylation, and this causes a loss of a
carbon as CO2 therefore it will always cause the n-alkanes to have an odd-over-even
predominance (OEP) (Killops and Killops (2009) [2]).
Figure 3.1.1. The schematic of the formation of n-alkanes in plants.
3.2.C3 PlantsMosses are typically C3 plants, that require high levels of CO2 to balance the CO2 lost to
respiration. These plants have no mechanism for storing CO2 so all CO2 enters the
photosynthesis pathway. The initial step involves the CO2 being bound to ribulose
bisphosphate, a 5 carbon molecule, combines with CO2 to form two molecules of
phosphoglycerate, which is a 3 carbon molecule, hence known as a C3 plant. The
key enzyme that catalyzes carbon fixation is rubisco. The C3 plants such as bryophytes live in
a delicate balance where CO2 concentration is high, temperature and light intensity are
moderate, and surface water is abundant, hence a bog contains the perfect conditions. This
is because in hot climates, the stomata are closed to prevent water loss. When leaves get
wet, the CO2 struggles to diffuse, however, the thin cuticle of mosses allows CO2 to diffuse,
6
and it helps prevent waterlogging (Ehleringer and Cerling (2002) [3]). Sphagnum has water-
holding hyaline cells which help to solve this problem.
The other vegetation that may be involved in the bog/mire system might photosynthesise
using the C4 mechanism, which uses a more active enzyme that fixes CO2 into oxaloacetate,
an acid. Thus it can be stored until it diffuses to the sheath cell from the mesophyll cells,
where it is decarboxylated and refixed via the normal C3 pathway.
3.3. Organic Geochemical ApplicationsThe plant wax n-alkanes tend to be between 21 and 37 carbons in length, with a strong odd-
over-even (OEP) number carbon chain length predominance, (Eglinton and Hamilton ((1967)
[4]). The n-alkanes are widely used as plant biomarkers, which have been studied since 1934
(Chibnall, Piper ((1934) [5])]). Since the n-alkanes are straight chained and lack any functional
group, they are particularly stable and enduring molecules. Alkanes can occur in marine
sediment (Sachse, Radke (2004) [6]); in soils, fluvial sediments and palaeosols (Smith, Wing
(2007) [7]); and both fossil and modern leaves. Distributions of long chain n-alkanes, are
useful indicators of past terrestrial environments and ecosystems.
Lipid biomarkers are molecular fossils that can help to identify the origin of the organic
matter, to reconstruct past environmental conditions and to assess microbial degradation in
sediments (Meyers and Ishiwatari (1993) [8]). Lipid biomarkers have proved useful in studies
of peat sequences. These studies show that both the production and preservation of lipid
biomarkers are sensitive to hydrologic conditions in peatlands. Different peat forming plants
produce characteristic n-alkane distributions.
Variations of stable carbon isotope ratios, (δ13C) values of land plant n-alkanes are related to
the environmental or vegetation changes in the source land areas. The C3 and C4 metabolic
7
pathways are both different, therefore the isotope values are contrasting. The C3
photosynthesis pathway results in low δ13C values, and the C4 pathway results in higher δ13C
values. This difference in stable carbon isotope signature can be used as a tracer for in situ
labelling of soil organic matter when the dominant vegetation type has changed from C3 to
C4 species or vice-versa. Environmental changes, in particular, rainfall and partial pressure of
CO2 during glacial/interglacial transitional periods can affect vegetation, thus the C3 and C4
plant ratios, resulting in δ13C changes in the preserved land plant biomarkers (Ratnayake,
Suzuki (2006) [9]).
Lipid distributions have been used in identifying aquatic plants (Ficken, Li (2000) [10]). It has
been found that submerged/floating species contain an enhanced amount of mid-chain
length, n-C23 – n-C25 alkanes. However, the emergent and terrestrial vegetations had long
chain length homologues, greater than n-C29. This has led to the proxy ratio, Paq (section 3.5),
being formulated to compare non-emergent with emergent ratios.
3.4.Biomarker Applications Mosses play an important role in the plant communities of bogs and fens and different
species have adapted to specific peatland environments based on the relative position of
the water table to the peat surface. Sphagnum mosses are particularly important in the peat
forming environments. There are some sphagnum species that grow well in moisture rich
peatland surfaces and in wet hollows such as Sphagnum balticum, Sphagnum cuspidatum
and Sphagnum majus, which have higher abundances of the n-C23 alkane (Ficken, Barber
(1998) [11, Nott, Xie (2000) [12]). Other species of Sphagnum such as Sphagnum fuscum and
Sphagnum capillifolium, are abundant on relatively dry hummocks (Rydin and Jeglum (2013)
[13]). These species have n-alkane distributions that maximise at n-C25 and n-C31, respectively
(Corrigan, Kloos (1973) [14, Vonk and Gustafsson (2009) [15, Bingham, McClymont (2010) [16]).
8
The n-alkane distributions for non-sphagnum mosses common in peatlands contain a much
higher concentration of the longer chain homologues (n-C27 – n-C33) than the Sphagnum
species. There are also peat forming vascular plants which include dwarf shrubs of the
Ericaceae family such as heathers which typically have n-alkane distributions that maximise
at n-C31 (Salasoo (1987) [17]). Sedges and lichens are also found in peatlands, where the Cmax is
at n-C27, n-C29 and n-C31. The Sphagnum species can provide lucrative information on the
temporal changes in the past using distribution of n-alkanes down cores.
3.5.Biomarker Proxies The terrigenous-aquatic ratio (TAR) is used as an indicator of relative terrigenous versus
aquatic organic matter input. High terrigenous/aquatic ratios in recent sediments would
indicate more terrigenous input from the surrounding watershed relative to the aquatic
sources.
TAR=nC27+nC29+nC31nC15+nC17+nC19
When aquatic sources predominate, the terrigenous/aquatic ratio decreases to values
below 1, and a value above 1 indicates predominant terrestrial vegetation (Mille, Asia (2007)
[18]). It is valuable for determining changes in the relative contributions of a sediments
organic matter from land and aquatic sources. However, it is a crude indicator since it is
sensitive to biodegradation and thermal changes in time. Also, land organic matter generally
contains more n-alkanes than aquatic organics, thus it will always be weighted towards land
input.
The Carbon Preference Index (CPI) is used as a numerical means of representing the odd
over even predominance (OEP) in n-alkanes within a particular range (Meyers and Ishiwatari
(1993) [8]) and is calculated as below.
9
CPI=[∑odd (C 21−33)+∑
odd(C23−35)]
(2×∑even C22−34)It can be used as a maturity measurement for when there is a strong OEP in n-C25 – n-C33
alkanes resulting from higher plant waxes. For most plant derived sediments the CPI values
are usually greater than 1, but will tend towards 1 with increasing maturity. This is because
of the range becoming diluted by the production of large amounts of additional n-alkanes in
the same range without any odd or even preference.
The proxy ratio, Paq, is used in distinguishing submerged/floating aquatic input against
emergent and terrestrial input based on n-alkanes. It takes into account the mid-chain
length to long chain length homologues (Ficken, Li (2000) [10]).
Paq=nC23+nC25
nC23+nC25+nC29+nC31
When dealing with modern plants, the proxy has an average of 0.09 for terrestrial, 0.25 for
emergent species and 0.69 for submerged/floating species.
Average Chain Length (ACL) is the weight averaged number of carbon atoms of the higher
plant n-C25 - n-C33 alkanes. It describes the average number of carbon atoms per molecule
based on the abundance of the odd-carbon-numbered higher plant n-alkanes (Poynter and
Eglinton (1987) [19]).
ACL=25 (nC25 )+27¿¿¿
The abundance of individual n-alkanes from higher plant sources generally increases with
increasing carbon number in most environments for example coastal marine sediments,
however, this trend is reversed for petrogenic hydrocarbons. The ACL would potentially be
10
lowered if petrogenic hydrocarbons were added to sediments containing biogenic
hydrocarbons alone.
3.6 The Study AreaFigure 3.6.1. The cross section of an ombrotrophic bog.
Ombrotrophic mires accumulate peat in a raised mass above the groundwater table and so
receive no input of minerogenic water. The water balance of these mires is totally
dependent upon rainfall, thus making them particularly sensitive to climatic change. Peat
deposits occur extensively in the sub-arctic regions of the northern hemisphere. These mires
contain substantial amounts of organic matter as the leaf waxes can be transferred to
marine sediments through eolian and fluvial transport caused by rain and wind. Mosses are
the most important types of vegetation found in ombrotrophic bogs. Several proxies based
on the specific n-alkane distribution pattern of sphagnum moss have been developed to
serve as biomarkers to identify sphagnum derived organic matter. They have been applied
in palaeoclimatic reconstruction (Pancost, Baas (2002) [20]) and as indicators of terrestrial
organic matter in the coastal ocean (Vonk, van Dongen (2008) [21]).
4. The Aim and RationaleThe aim of this study is to use n-alkane distributions to track the change in the
palaeoenvironment. The samples for analysis were from a 5 metre core, taken from an
ombrotrophic peat bog in the Arkhangelsk Oblast region of the White Sea, Russia (Figure
11
4.1). The core was taken at coordinates 64° 36' 19.1874", 38° 10' 55.0554" which is about 6
km away from the village of Luda, on the Onega peninsula.
The objectives were:
To analyse the n-alkane distributions across all samples, both from the core and the
individual surface vegetation
Distinguish biomarkers for known species, in particular Sphagnum moss.
Use histograms and proxies to identify trends and variation
Ascertain information on how the climate may have altered through time
The choice of instrumentation was a Gas Chromatography Flame Ionisation Detector (GC-
FID):
n-alkanes are non-polar compounds, so a non-polar column can be used to provide a
separation where no co-elution takes place
The compounds are separated based on boiling points
FIDs can measure organic substance concentration at very low and very high levels,
having a large linear response.
FIDs are very rugged and can withstand a very concentrated sample where other
instruments may fail to cope
12
5. Method
5.1.Gas Chromatography Flame Ionisation Detector (GC-FID)Gas-Chromatography Flame Ionisation Detector (GC-FID) is composed of a heater, injector,
capillary column and detector. The auto-sampler injects 1 µL (20-30 mg/µL) of sample to the
inlet where it is volatilised. Helium carrier gas conveys all of the sample (splitless) or a part
of it (split mode) into the column. Split mode is used when a high concentration of analyte
may be introduced, and so part of the mixture (1:10 – 1:50) is let out through the split vent
before being swept through by the carrier gas. Splitless mode is used when trace analysis is
performed on low concentrations of analyte, and so the whole amount is introduced while
the split vent is closed. The carrier gas is the mobile phase and the column into which the
sample is carried acts as the stationary phase. The column is made from fused silica, with a
thermo-stable polymer on the outside. The film on the inside (the stationary phase) is
typically a siloxane polymer. The polarity of the sample must closely match the polarity of
the column stationary phase to increase resolution and separation while reducing run time.
13
Figure 4.1. Exact GPS location of the core site.
The separation and run time also depends on the film thickness. The sample will interact
with the stationary phase and so different compounds will elute at different retention times.
The FID works by passing the eluted compounds through a hydrogen-air flame. When an
organic compound passes through the flame, the number of ions greatly increases. A
polarizing voltage attracts the ions and the current produced is proportional to the amount
of sample being burned. This current is sent to an electrometer and transferred to a
chromatogram.
The output is a chromatogram of voltage against time. The different organic compounds will
give peaks of varying strength at different retention times. For quantitative analysis, the
peak areas are calculated and then using the internal standard response factor, the amounts
of each compound can be calculated.
Response Factor = [ISTD response x Sample amount] / [ISTD amount x Sample response]
5.2.The Internal StandardThe Internal Standard used contained three organic compounds that were similar, but not
identical or could be found naturally in the sample. The compounds used were fully
deuterated n-tetracosane (n-C24d50), fully deuterated n-hexatriacontane (n-C36d74) and
squalane (C30H62). Roughly 10 mg of each were dissolved and made up to 10 mL in toluene to
give a 1 mg/mL solution which was then transferred to a capillary vial. Using a 500 µL
syringe, 1 mL was removed and made to 10 mL in toluene to form a 0.1 mg/mL
concentration. This process was repeated once more to finally achieve 10 mL of the internal
standard at a concentration of 0.01 mg/mL.
Getting the amounts and concentration correct for the internal standard is crucial for
achieving a reliable calibration. The calibration was achieved using a set of spiked standards.
14
The standards made were different concentrations of the range nC8 – nC40 with pristane and
phytane. A 5 mL stock solution of 10 ng/µL was made up from dissolving 100 µL in hexane
from the 500 ng/µL commercial standard. This was then used to make up four different
response factor standards that were each spiked with a known amount of internal standard,
100 µL in each (Table 5.2.1.).
Range of Calibration standards 0.1 ng/µL 1 ng/µL 2.5 ng/µL 5 ng/µL
Volume of 10 ng/µL stock (µL) 10 100 250 500
ISTD concentration (mg/mL) 1 1 1 1
Volume of ISTD (µL) 100 100 100 100
Volume of Hexane (µL) 890 800 650 400
Table 5.2.1. The makeup of each calibration level standard.
The lowest concentration was 0.1 ng/µL, being at the bottom end of detection and the
largest, 5 ng/µL, being at the peak of linearity before the line that is forced through the
origin starts to tail off.
5.3.Pilot RunIn order to get an idea for the amount of sample to use and the amount of internal standard
to spike the samples with, three samples from the core were tested. 0.25 g of a sample was
taken from near the top (76.5 cm), the middle (289 cm) and at the bottom (464 cm). These
results showed very strong concentrations of long-chain odd carbon dominated saturates
(approximately 150 µg/g). As there were very small amounts of each sample, 0.35 g of each
was to be used. This would mean the volume of internal standard needed to be added
without causing the powdered sample turning into a slurry. Instead of using 10 µL of the 1
15
mg/mL standard to have 10 µg of ISTD in the sample, 50 µL was added of a new
concentration that was made to 0.2 mg/mL. By putting a larger volume on, it causes the
error to be reduced providing more reliable results.
5.4.Sample Preparation A high resolution set of 40 samples taken at roughly every 12 cm down a single 5 m core
were milled using the freezer mill because some of the samples were very fibrous and in a
standard metal ball mill they would just heat up, thus breaking down the saturates required
for analysis. Freezer milling would prevent this as the samples would simply freeze and
become brittle in the liquid nitrogen before being ground to a fine powder with a solenoid.
Once a fine powder, 0.35 g was weighed from each sample onto a watch glass since and
then spiked with 50 µL of the 0.2 mg/mL internal standard solution. This was left for at least
an hour to allow the solvent to evaporate off. In each batch on the ASE a quality control was
included to ensure a quality assurance, which was one of the samples for analysis that was
in abundance compared with the rest. The sample at 464 cm was chosen as the control as
there was sufficient volume of material and this could be compared throughout each
extraction to ensure that the distribution remained relatively equal (supplementary
information). There were three quality controls per ASE batch along with one blank and
twenty samples. After being spiked, the samples and quality controls were each mixed
separately with sand that had been cooked at 500°C overnight, sonicated with DCM, and
then another night at 500°C in order to eradicate any organics; and copper powder to
remove any sulphur. This mixture was added to a cell which was then placed in the ASE for
extraction (Table 5.4.1).
Instrument parameter Setting
Solvent DCM: methanol (9:1, v:v)
16
Pressure 725 psi
Temperature 75°C
Heating time 5 minutes
Static time 5 minutes
Flush 50%
Purge 60 seconds
Table 5.4.1. ASE parameters used
The organic extracts were collected and blown down under a stream of nitrogen on a
Caliper Turbo eVap LV until there was roughly 1 mL left in the large vials. This was then
transferred to pre-weighed and labelled GC vials via Pasteur pipette before then being
reduced under nitrogen again to dryness. The total organic extracts could then be weighed
for each. Each vial containing the dry solid organic extracts were then made up to 1 mL
volume using DCM:propan-2-ol (2:1) to dissolve it into solution.
5.5.Column ChromatographySilica gel 60 (0.2-0.5 mm) was activated by heating in oven at 650°C overnight, and then
cooled in a dessicator, before deactivating by adding 5% its weight in water. The deactivated
silica was shaken thoroughly and left for 24 hrs to equilibrate. Each sample was transferred
onto a small amount of the prepared silica and left for a few hours to allow solvent to
evaporate. The columns were then packed with silica gel made from mixing the activated
silica with hexane. They were packed up to roughly 20 cm on each column. The silica
extracts were added to each column. Then 46 mL of hexane was eluted through the column
(roughly three times the volume of the column). The eluate from each sample was then
reduced under a stream of nitrogen on the turbo evaporator down to roughly 1 mL. This
was transferred to individually pre-weighed GC vials, where it was blown down to dryness
17
under a stream of N2. Each was weighed to get a total saturate weight, before being made
up to 1 mL with hexane ready for analysis on the GC-FID.
5.6.The GC-FID methodIdentification of different peaks in the saturated fraction was carried out on a HP 6890 gas
chromatograph coupled with a flame ionisation detector (FID) fitted. The GC was fitted with
an Agilent J&W scientific non polar DB-1 column (60 m x 250 µm internal diameter; film
thickness 0.1 µm). BOC CP-grade helium carrier gas 1 mL/min constant flow was used as the
mobile phase. The temperature program was to hold at 60°C for 1 minute, then ramp to 320
°C at a rate of 10°C/min, and finally held at 320°C for 20 minutes. The samples were
dissolved in hexane and a splitless injection was applied for injection. The FID was kept at a
constant temperature of 320°C with a makeup of H2 and air with flows of 40 mL/min and
400 mL/min respectively.
18
6. Results and DiscussionThe top two metres of the core are dominant in the high odd n-alkane chain lengths. The
uppermost sample analysed, 1.5 cm (Figure 6.1), has a distribution which is dominated in
the higher odd carbon chain length homologues, n-C31 and n-C33. These peaks are often
associated with vascular plants because they produce a thick waxy cuticle on the leaves.
These two n-alkanes are high in concentration, 143 µg/g and 138 µg/g respectively. The
surface vegetation shows a strong n-C31 throughout all the species and so the top sample
consists mostly of fresh input of these leaf waxes to the soil and little build up of other
material will have taken place. These being so large influence the TAR ratio to shift to a very
high value as well as the CPI providing values of 260 and 5.5 respectively (supplementary
information). At the depth of 51.5 cm there is an unusual distribution where the n-C33
homologue is the maximum peak (52 µg/g) however, the heather sample (Figure 6.4.) that
was analysed showed a dominant n-C33 that is extremely strong in concentration and this
could be the most probable cause of the dominant peak in the core sample.
The Sphagnum sample that was analysed is actually from the UK and so it is not
representative of the typical Sphagnum species found on the surface of the subarctic
Russian peat bogs. This sample of Sphagnum is likely to be Sphagnum magellanicum
because it is one of the only types of Sphagnum where the distribution has a dominant n-C31
peak with a strong peak of n-C33 as well (Bingham, McClymont (2010) [16]). When the samples
were collected, there was very limited space for what could be brought back from the
remote area of Russia from where the cores were taken, so unfortunately there were no
samples of the subarctic Sphagnum for analysis. This study will refer to a select few papers
19
for n-alkane values of specific species of Sphagnum found in the subarctic areas (Vonk and
Gustafsson (2009) [15, Bingham, McClymont (2010) [16, Andersson, Kuhry (2011) [22]).
The sample at the depth of 164 cm showed an increased concentration of n-C25, which is
a biomarker for Sphagnum species, in particular, Sphagnum fuscum and Sphagnum
capillifolium. These are typically found in subarctic bogs and grow when conditions are dry
and so will reside on hummocks in a raised peat bog. In both samples however the second
dominant n-alkane is of 31 carbons in chain length. This combined with other higher plant
input forms the strong odd-over-even predominance that can be seen in the sample.
Sphagnum mosses produce n-alkanes in their tissues in greater quantities than most
gymnosperms (seed producing), but still less than those of angiosperm (flowering plant)
leaves (Pancost, Baas (2002) [20]). Even though the n-C25 peak is not the dominant, but the
third strongest with a concentration of 45 µg/g, it is still large enough to consider it for a
biomarker, indicating that sphagnum will have been present at this point.
The core sample at 214 cm deep then shows a considerable increase in concentration of
the n-C25 alkane (181 µg/g), but again it is not dominant as the n-C27 alkane is the major peak
at 274 µg/g. It does contain a large amount of sphagnum though as there is an obvious
orange/brown band that appears in the high resolution picture of the core made from a
picture of each individual sample that was analysed (supplementary information). In this
coloured band, the plant remains are mostly Sphagnum leaves and so it must have been
abundant at these sites before being replaced by grasses, sedges and ericaceous shrubs.
There is also another large band at the depth of 239 cm. This can be seen in the histogram
(Figure 6.2) because the two most dominant peaks are n-C25 and n-C23. Therefore it seems to
20
be that mainly Sphagnum existed at this point in time on the surface as both biomarkers are
indicative of it being so and little other higher plant input.
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
20
40
60
80
100
120
140
160
1.5 cm
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
10
20
30
40
50
60
51.5 cm
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
20
40
60
80
100
120
140
101.5 cm
Conc
entra
tion
(µg/
g)
nC13nC15
nC17nC19
nC21nC23
nC25nC27
nC29nC
31nC33
nC35nC37
nC390.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
164 cm
Conc
entra
tion
(µg/
g)
21
Figure 6.1. Histograms showing n-alkane distributions of some core samples with their
corresponding chromatograms. The peaks marked with dots are the internal standard
peaks.nC
13nC
14nC
15nC
16nC
17nC
18nC
19nC
20nC
21nC
22nC
23nC
24nC
25nC
26nC
27nC
28nC
29nC
30nC
31nC
32nC
33nC
34nC
35nC
36nC
37nC
38nC
39nC
40
0
50
100
150
200
250
300
214 cm
Conc
entr
ation
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
5
10
15
20
25
30
35
40
45
239 cm
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
20
40
60
80
100
120
140
276.5 cm
Conc
entr
ation
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
5
10
15
20
25
314 cm
Conc
entr
ation
(µg/
g)
22
Figure 6.2. Histograms showing n-alkane distributions of some core samples with their
corresponding chromatograms. The peaks marked with dots are the internal standard
peaks.nC
13nC
14nC
15nC
16nC
17nC
18nC
19nC
20nC
21nC
22nC
23nC
24nC
25nC
26nC
27nC
28nC
29nC
30nC
31nC
32nC
33nC
34nC
35nC
36nC
37nC
38nC
39nC
4005
101520253035404550
364 cm
Conc
entr
ation
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
10
20
30
40
50
60
414 cm
Conc
entr
ation
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
5
10
15
20
25
30
35
451.5 cm
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0.00
0.10
0.20
0.30
0.40
0.50
0.60
476.5 cm
Conc
entr
ation
(µg/
g)
23
Figure 6.3. Histograms showing n-alkane distributions of some core samples with their
corresponding chromatograms. The peaks marked with dots are the internal standard
peaks.
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
5
10
15
20
25
30
35
Grass
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
50
100
150
200
250
300
350
400
Heather
Conc
entra
tion
(µg/
g)
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
10
20
30
40
50
60
Lichen
Conc
entra
tion
(µg/
g)
24
nC13
nC14
nC15
nC16
nC17
nC18
nC19
nC20
nC21
nC22
nC23
nC24
nC25
nC26
nC27
nC28
nC29
nC30
nC31
nC32
nC33
nC34
nC35
nC36
nC37
nC38
nC39
nC40
0
10
20
30
40
50
60
SphagnumCo
ncen
tratio
n (µ
g/g)
Figure 6.4. Histograms showing n-alkane distribution of individual surface vegetation with
their corresponding chromatograms. The peaks marked with dots are the internal standard
peaks.
The majority of individual samples have n-alkane distributions that vary down the core
however; there are sections in which the pattern remains similar throughout, such as
between 364 cm and 451.5 cm deep. Here the distribution consists of a maximum carbon
chain length preference of 27 carbons. This was quite unexpected as none of the surface
vegetation that was analysed had a distribution like this; in particular, there were no
dominant n-C27 peaks.
There are two possible reasons for this distribution; the first being the fact that these
samples are likely to be at least 5000 years old, so in that time different surface vegetation
will have existed providing different distributions. Secondly, the peat at this depth may have
undergone diagenesis, thus n-C27 is more dominant because of the breakdown of longer n-
alkane homologues through increased pressure and temperature. When looking at the
ratios (Figure 6.7), they show that the environment was most probably colder and wetter in
this lower third of the core, therefore the first explanation would have more of an influence
on this distribution especially as different vegetation would have favoured these conditions.
Due to constant water-saturation resulting in anoxia, the rate of net primary production by
plants exceeds microbial decomposition in peat bogs and so Sphagnum, a rootless
25
bryophyte, thrives since its litter has antimicrobial properties allowing it to build up the peat
bog very quickly. Once enough peat has accumulated to form hummocks, stunted trees and
shrubs begin to grow on these less water-saturated raised areas and will have developed
shallower root systems to avoid anoxic soil layers.
The very last couple samples, one of which is 476.5 cm deep (Figure 6.3), show an extremely
weak concentration of saturates because this part of the core is made of diatomaceous clay.
This is made from a type of hard-shell algae which forms a siliceous sedimentary rock that is
typically grey in colour.
0.00 200.00 400.00 600.00 800.00 1000.00
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0Total concentration of n-alkanes down core
Concentration (µg/g)
Depth (cm)
0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0Conc. of nC31 down core
Concentration (µg/g)
Depth (cm)
26
Figure 6.5. Concentration of all n-alkanes combined for each sample (left), concentration of
only n-C31 alkane for each sample (right)
As can be seen from the above graphs (Figure 6.5.), the common terrestrial plant signal n-
C31 has an influence on the total concentration. It is so strong for much of the top three
metres, that where the n-C31 has peaks, the total concentration peaks in the same positions.
The cycles in the top half of the core are difficult to explain without other analysis, but they
could be caused by a number of reasons; there may have been a number of particularly cold
snaps that caused the terrestrial vegetation to recede or it could be due to a rise in sea
levels due to extreme tides since the White sea lies close to the sample point and the
salinity of the peat may have increased, again causing terrestrial plants to give way
temporarily to aquatic species. However, below this three metre mark, the n-C31
concentrations fall away to much lower values, whereas the total concentration drops but
retains larger concentrations, therefore it is influenced by other n-alkanes in the samples.
27
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0Conc. of nC23 down core
Concentration (µg/g)Depth
(cm)
0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0Conc. of nC25 down core
Concnetration (µg/g)
Depth (cm)
Figure 6.6. Variation of the individual concentrations of n-C23 (left) and n-C25 (right) alkanes
down core.
The graphs (Figure 6.6.) are of the two common biomarkers for Sphagnum moss species. In
contrast to figure 6.5 these show a low concentration initially and then start to increase
from halfway down the core. Thus these are the cause of the total concentration of n-
alkanes not reducing as much as the individual n-C31 peak did. This is therefore showing an
increase in Sphagnum in the last half of the core. The concentration of the n-C25 alkane is
higher than that of the n-C23 alkane throughout, but the graph of the n-C23/n-C25 ratio (Figure
6.7.) displays that the amount of n-C23 does gain in concentration against the n-C25 from half
way down the core. This implies that it is likely a different species of Sphagnum would have
28
been present at the lower depths due to the change in composition of the biomarkers.
Sphagnum with a dominant n-C23 is an indication of a species that thrives in a wetter and
colder environment than that of the dominant n-C25 species. The Sphagnum species that
prefer hollows in an ombrotrophic bog are Sphagnum cuspidatum and Sphagnum imbrictum
(Bingham, McClymont (2010) [16]). However, in this core, there is no dominant n-C23 as such,
just an increase, so the type of sphagnum is most probably S.rubellum because this has a n-
C23/n-C25 range of 0.66 – 0.75 which is based on the values from (Pancost, Baas (2002) [20]),
which looks at species in Finland and so this is more resemblant of the subarctic conditions.
When looking at the upper section of the core, the n-C25 becomes even more abundant than
the n-C23, thus using the values from the Finnish samples analysed by Bingham et al. 2010, it
is shown that S. Fuscum is the most likely species to have dominated as the ratio gives
values in the range 0.44-0.55.
Since an increased concentration of n-C23 is common in Sphagnum that has adapted to
growing in wet conditions, and n-C25 is predominant if the Sphagnum is one that has evolved
to grow in drier conditions, therefore the shifts in the ratio n-C23/n-C25 can be used to reflect
changes in the bog wetness from the past. From this ratio, it can be seen that in the past,
the peatlands were generally wetter and so the surface vegetation may have existed in
hollows in the bog.
The n-alkane proxy Paq (section 3.5) can be used to distinguish between different groups of
aquatic plants and land plants (Ficken, Li (2000) [10]). This proxy is based on the abundances
of n-C23 and n-C25 alkanes in submerged and floating macrophytes, whereas longer chain
lengths are relatively more abundant in emergent macrophytes and terrestrial plants. This
proxy can also be used to determine the relative abundance of Sphagnum derived organic
29
matter (Nichols, Booth (2006) [23]). This proxy gives typical values of 0.05-0.2 for terrestrial
species, 0.2-0.55 for emergent macrophytes and >0.55 for submerged/floating
macrophytes.
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0 PaqAquatic ratio
Depth (cm
)
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0C23/C25ratio
Depth (cm
)
Figure 6.7. Paq proxy against depth (left); n-C23/n-C25 ratio against depth (right)
The Paq proxy clearly shows that the core largely consists of terrestrial input in the
top half, down to 214 cm, where there is a sudden shift before becoming terrestrial again at
251 cm deep until 300 cm. From here the Paq then increases and stays steady at around 0.50
implying there is emergent vegetation dominant in the samples, most probably Sphagnum.
The Paq proxy is useful, but when dealing with a peat core from the subarctic, the more
abundant n-alkane throughout seems to be n-C25. The samples show the n-alkane proxy C25/
(C25+C29) to be the most suitable in defining Sphagnum for this system. n-C29 was used
30
because of the possible abundance of the n-C31 in Sphagnum. The n-alkane proxy C23/
(C23+C29) was considered, but most values were relatively low due to the fairly low
abundance of n-C23. This ratio however would be much higher in more temperate regions
because of the higher contribution of n-C23 relative to n-C25 compared with subarctic areas.
Taking the values gained from the heather vegetation sample, the higher plant C25/ (C25+C29)
ratio is 0.11. Using Sphagnum values from the data gathered by (Vonk and Gustafsson
(2009) [15]), the typical ratio is around 0.60. This proxy has been combined with the Paq in a
graph (Figure 6.8.) because they are complimentary of each other. It shows there is an
obvious change in the composition of the core, the top three metres being on the left with
the generally lower values and the bottom two metres on the right with the higher values of
Paq and the increased C25/ (C25+C29) ratio.
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.700.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70 Paq vs C25/(C25+C29)
301.5 - 489 cm1.5 - 289 cm
Paq
C25/
(C25
+C29
)
Figure 6.8. Bubble graph showing Paq against the ratio of C25/ (C25+C29), with the bubble
31
diameter indicating the depth in the core. The smallest diameter relates to the top of the
core and largest corresponds to the bottom of the core.
The two main sections show that a climatic change has taken place as there is a
change in composition of n-alkanes thus meaning a change in the vegetation that was on
the surface thousands of years ago to what there is now. It further backs up what the other
graphs have shown in that it must have been wetter and colder conditions many thousands
of years ago and so small bryophytes such as Sphagnum and other mosses would have
thrived in that kind of environment. Over the last couple thousand years to present, the
environment from which this core was taken has become drier and most likely warmer,
resulting in raised hummocks.
Mosses tend to grow more quickly than lichens, heathers, and other small shrubs; and they
can trap more organic material in their feathery growth. They also produce a larger amount
of decomposing matter, and this in turn helps with the formation and accumulation of more
soil. Over time, this provides enough nutrients for higher plants to become established,
plants which can colonise a hummock include bracken (Pteridium aquilinum),
heather (Calluna vulgaris) and lichen. If a hummock develops in a more open setting, most
vegetation gives way to heather, which thrives best in bright conditions. This seems to be
the case with the core that was sampled as it was taken from an open, heather dominated
area that was very dry. The lead up to this is shown by the few anomalies in the bubble
graph (Figure 6.8.). The few red bubbles scattered around the blue grouping are the
samples in the transition zone from 300 cm below the surface; through the 300 – 214 cm
depth, so they show the increase in most probably S. Fuscum, the hummock adhering
32
Sphagnum, while it builds up soil that gains in nutrition for the more terrestrial higher plants
to then take hold.
The few surface vegetation samples that were actually from the core site all consist of a very
strong n-C33 homologue. The grass, lichen and heather all demonstrate this (Figure 6.4.) but
n-C33 values for all species of Sphagnum are very low in concentration or even non-
detectable as shown by (Bingham, McClymont (2010) [16]) and (Vonk and Gustafsson (2009)
[15]). Therefore, a new proxy was produced that takes this into account and so it can further
detect that Sphagnum may be present in subarctic environments. The proxy that was
established based on the n-alkane distributions acquired is for Subarctic Sphagnum (SAS):
PSAS=nC25+nC27
(nC¿¿25+nC27+nC33)¿
The n-C25 is used because it is the most consistent Sphagnum biomarker throughout the core
and the n-C27 is very abundant through the later parts of the core as well as being a lot
higher in concentration for Sphagnum species than n-C33. From the literature, the n-C25 is the
most abundant biomarker for sphagnum in the subarctic (Vonk and Gustafsson (2009) [15]).
The graph (Figure 6.9) below shows how this proxy varies down the core, picking out the
distinct change in the middle. When plotted against average chain length, it can be seen
how the increased n-C25 and n-C27 reduce the ACL from a very terrestrial value in the upper
part of the core to a lower average value towards the bottom of the core. It correlates very
well with the ratio chosen as shown it has an R2 value of 0.9131.
33
0.00 0.20 0.40 0.60 0.80 1.00 1.200.00
2.00
4.00
6.00
8.00
10.00
12.00
f(x) = NaN x + NaNR² = 0 ACL vs PSAS
C25+C27/(C25+C27+C33)
ACL
Figure6.9. Graph showing average chain length against the proxy for sub-Arctic Sphagnum.
The ACL shows that the abundance of individual n-alkanes from higher plant sources
generally increases with increasing carbon number, but this trend is reversed for Sphagnum
rich peat as they are generally dominated by mid-chain length n-alkanes. The main outlier is
the sample at 251.5 cm deep, which is the central sample from the core. It shows that it
most probably contains Sphagnum, but still influenced by a terrestrial value for ACL. This is
the downfall of this ratio because terrestrial plants can have a relatively high abundance of
n-C27, thus causing the PSAS to be high, however, the sample in this case does contain a large
amount of n-C33 as well (supplementary information), causing the ACL to be high, so this
shows the mixture of vegetation input as the climate changed and new vegetation started to
grow.
34
251 cm
0-239 cm
264-489 cm cm
7. ConclusionGC-FID analysis of n-alkane distributions down the core provided a relatively good indication
of how the environment has changed through time. The proxies used; Paq, CPI, ACL, TAR and
other various ratios along with the proxy PSAS which was established, helped to draw
inferences from the data. These trends displayed two distinct parts to the core; the bottom
two metres and the top two metres with fluctuations in-between them. The bottom half by
sight was darker and was probably more degraded, however, using the various ratios, and
literature values, it showed to contain Sphagnum moss. It was mostly characterised by the
large concentrations of n-C25 and some n-C23. There was a considerable increase of
terrestrial input towards the top of the core; however, there was a distinct transition from
the lower sediments (250 cm-500 cm) to the upper sediments (0 cm-250 cm) from what
would have been a wetter and cooler climate into an environment that is now generally
drier and probably warmer. The peat had built up enough in order to provide enough
nutrients for lichens, grasses, heathers and Scots Pine to grow on. Although the abundance
of n-C31 is very large (250 µg/g) in the upper samples, there is still a considerable amount of
n-C25 indicating that Sphagnum is still thriving, but this species will be different to that of the
species found in older parts of the core. The type of Sphagnum from the lower part is likely
to be S. rubellum because this prefers wetter conditions in hollows and has a n-C23/n-C25
range of 0.66 – 0.75. The species that then builds up on hummocks and of which there is
most likely to still be present is S. Fuscum. This has a n-C23/n-C25 range of 0.44-0.55, so it is
more dominant in n-C25 as well as n-C31, which this ratio does not show, thus it is the most
likely substituent of the upper part of the core, along with the higher terrestrial plants and
sedges that have built up on the nutrient rich soil the sphagnum has formed. The n-alkane
analysis of a core does help in tracking changes in the palaeoenvironment and the type of
35
Sphagnum based on its biomarkers can show changes in hydrology, however, it should be
used in conjunction with other methods to be able to draw any real evidence from it. For
example, pollen analysis and isotope studies can be carried out to show the exact
contributing species and temperature changes in the environment, and could help to
explain the cycles exhibited by the higher n-alkanes in the top half of the core. It would have
also helped to have more surface vegetation from the site and around the area, for instance
Sphagnum from the hummock where the core was taken and some Sphagnum from a wet
hollow nearby; thus the study would have been able to draw more accurate conclusions on
the exact species of Sphagnum in the core.
8. Other Project involvement
8.1.Denmark Paleo-Eocene Thermal Maximum (PETM)A core that had been taken off of the Denmark coast from just over 2 kilometres below the
sea floor was sampled. There were seven samples in all to analyse for n-alkane distribution.
The Paleo-Eocene Thermal maximum occurred 55.8 million years ago. There was a global
rise in temperature of around 6°C for a short time before dropping back rapidly and tapering
off to where it was before the event. Two of the samples for analysis came from before the
dramatic rise in temperature, one at the peak of the thermal maximum, one at the base of
the rapid drop in temperature, one at the Eocene hyperthermal (PETM2) and then the last
two during the gradual reduction to where it was originally. The aim was to ensure that the
n-alkane analysis agreed with the known records of δ13C isotopes. Graphically, it can be seen
36
that there is an extremely large carbon input to the oceans and atmosphere as the δ13C
records have a prominent negative excursion.
Because the samples were 55 million years old, many of the long chain alkanes had
decomposed, producing shorter, branched alkanes, thus forming a large unresolved
complex mixture (UCM) in all the samples. To reduce this, molecular sieves were used to
single out only the n-alkanes (section 8.3).
The results correlated with the records of the δ13C, thus proving that there was a change in
environment due to temperatures rising. The terragenious/aquatic ratio (Figure 8.1.1.)
shows that before the PETM, the environment was predominant in terrestrial species, but as
the temperature rise occurs, the ratio shows a shift towards an increased marine
environment. This is most probably a cause of rising sea levels as ice sheets melted. Then as
the climate stabilises, the ratio shows a slow shift returning to a terrestrial environment.
The Paq proxy (Figure 8.1.2.) shows that there were emergent species before the PETM, and
then during the PETM the species became submerged/floating due to the higher Paq value (>
0.6), which also occurs for the early Eocene hyperthermal as well.
There is a prominent odd-over-even preference before and a while after the PETM. This
leads to the CPI values (Figure 8.1.3.) being greater than 1. During the PETM, the odd-over-
even preference disappears as the species tend towards a marine environment, thus moving
the CPI value towards 1.
The n-alkane results in other similar experiments along with records of the δ13C isotopes
have been used in recent studies to further the understanding of climate change in recent
years due to ‘global warming’.
37
38
0.4 0.45 0.5 0.55 0.6 0.65
-2028
-2027
-2026
-2025
-2024
-2023
-2022
-2021
-2020
-2019
-2018
PaqPaq ratio
Dep
th (m
bsf)
Figure 8.1.1. Graph showing TAR vs depth for the PETM samples.
0.9 0.95 1 1.05 1.1 1.15 1.2 1.25 1.3
-2028-2027-2026-2025-2024-2023-2022-2021-2020-2019-2018
CPICPI ratio
Dept
h (m
bsf)
Figure 8.1.2. Graph showing Paq vs depth for the PETM samples.
0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6
-300
-250
-200
-150
-100
-50
0
PaqAquatic ratio
Dept
h (cm
)
Figure 8.1.3. Graph showing CPI vs depth for the PETM samples.
8.2.Greek Tsunami A core from Greece taken from 300m inland was sampled. The aim was to identify that a
tsunami had occurred there from historical records by n-alkane analysis which can identify
the palaeohydrology of the area. Six samples were used, of which the deepest sample was
from the section of the core where the tsunami took place. This was backed up by the n-
alkane results as the TAR value decreased majorly down the core and the Paq proxy showed
a value for the tsunami sample at 0.54 which is in the range of the submerged/floating
species, thus proving the environment at that time would have been aquatic. The purpose
of this mini-project was to pilot for a PhD project.
The Paq
proxy
39
0 5 10 15 20 25
-300
-250
-200
-150
-100
-50
0
TARTAR ratio
Dept
h (c
m)
Figure 8.2.1. Graph showing aquatic ratio against depth
nC14nC15nC16nC17nC18nC19nC20nC21nC22nC23nC24nC25nC26nC27nC28nC29nC30nC31nC32nC33nC34nC35nC36nC37nC38nC39nC400.00%
5.00%
10.00%
15.00%
20.00%
25.00%Test Peat %areas
Before
After
% ar
ea o
f Pea
k
Figure 8.2.2. Graph showing terrigenous/aquatic ratio against depth
provides information about the sample once existing in a marine environment due to the Paq
> 0.5 at the depth of 250 cm (Figure 8.2.1.) which indicates a submerged/floating species
type. As sedimentation has occurred since the tsunami, the environment has progressed
through an emergent stage and is now displaying a more terrestrial phase. The lowest TAR
value is 2.9, although this still denotes it is of terrestrial input, it is at a sufficiently lower
value than at where the more recent samples are. This value of 2.9 occurs at the supposed
time of the tsunami and this further backs up the evidence for it occurring as the n-alkane
distribution is typical of an increased marine signature.
8.3.Molecular sieves
Figure 8.3.1. Chromatogram showing the effect of using molecular sieves. The black
chromatogram is the UCM and the red chromatogram is after the sample has been
molecular sieved. It shows a large reduction in UCM.
When dealing with the Demark PETM samples, a large humped baseline in the
chromatogram appeared, which is known as an unresolved complex mixture (UCM) (Figure
8.3.1). This was due to the samples being millions of years old and so there were many
shorter branched alkanes that would have formed from larger alkanes degrading over time
from diagenesis. In the past, BGS organic labs have used urea adduction in order to reduce
UCMs, however, this has proved to change the distribution of the n-alkanes recovered.
40
Molecular sieves were therefore considered for the first time, and a vast amount of
literature was involved in order to get a better understanding. Molecular sieves are porous
materials which have holes of a precise and uniform size. In this case, a microporous sieve is
needed to adsorb the straight n-alkanes and to block any branched alkanes from the
saturated fraction from going into the sample to be analysed.
The method that was decided on involved a 5 Å calcium aluminium silicate
Linde type A zeolite that was dried in a furnace at 250°C for 24 hrs, then left to cool in a
desiccator. 0.5 g of molecular sieve was added to a 100 mL round-bottom flask. Isooctane
(25 mL) was added followed by the sample. With occasional stirring, the flask was heated
and refluxed for 4 hrs. The flask was then left to cool to room temperature. The mixture was
transferred to a glass funnel with a plug of silica wool (pre-rinsed with hexane) to retain the
molecular sieve.
The sieve was left to dry overnight. It was recovered from the funnel and placed
back into the original flask. Diluted HCL (50 mL, 20% v) and hexane (5 mL) were added to the
flask and capped. The mixture was stirred for 10 min then sonicated (37 kHz) in an
ultrasound bath for 4 hrs. The temperature of the bath was monitored to ensure the
temperature did not exceed 50°C. The solution was left to cool to room temperature and
then the aqueous phase was separated and rinsed with hexane (2 x 5 mL). The extract was
dried using sodium sulphate (1˞ g). The n-alkane fraction was then reduced to 1 mL using
nitrogen (Caravaggio, Charland (2007) [24]).
41
nC14nC15nC16nC17nC18nC19nC20nC21nC22nC23nC24nC25nC26nC27nC28nC29nC30nC31nC32nC33nC34nC35nC36nC37nC38nC39nC400.00%
5.00%
10.00%
15.00%
20.00%
25.00%Test Peat %areas
Before
After
% ar
ea o
f Pea
k
Figure.8.3.2. n-alkane distributions of a test peat before and after the molecular sieving.
The graph (Figure 8.3.2) shows the percentage area of each n-alkane peak in the test
peat before and after it had been molecular sieved. There is a large odd-to-even
predominance in the higher alkanes and that it has retained that distribution after being
sieved with only a slight loss in amount, which would be expected.
42
8.4.Stalagmites
Figure 8.4.1. Contaminated stalagmite with the black bands (left); non-contaminated
stalagmite (right).
Two pieces of stalagmites from the Peak district were to be prepared for poly-aromatic
hydrocarbon (PAH) analysis (Figure 8.4.1.). One was a clean white/cream colour and the
other had various black/grey bands embedded within the layers. The aim was to see if any
PAH contaminants were contributing towards the black band formation or if it were just a
natural occurrence. The samples were ground in a Retsch PM 100 ball mill and each was
weighed. Soxhlet extraction with DCM:Acetone (50:50) was chosen because it is a much
more efficient process than the ASE as the soxhlet was kept on for 48 hrs to ensure the
samples had been thoroughly flushed through many times and extensively extracted. The
resulting extracts were as expected, with the clean stalagmite yielding a clear extract and
the contaminated one conveying a darker solution. These were blown down and analysed
on a Varian 1200 GC-MS, which showed copious amounts of PAH contaminants in the
banded stalagmite that will have been attributed to the burning of matter above ground and
PAHs have leached down through the soil.
43
8.5.Total Petroleum Hydrocarbon (TPH) analysis
Staten Island:
Two cores (A and B) from Staten Island, roughly 5 metres apart were analysed for their total
petroleum hydrocarbon content. The TPH is a mixture of hydrocarbons that are typically
found in crude oil. It consists of three major groups, saturates, aromatics and
resins/asphaltenes. The depth of both cores was 90 cm with samples being taken every 2
cm; this spacing allowed a high resolution analysis of the cores. Both cores showed a very
dark band around 50 cm, indicating a past oil spill. ~0.5 g of each sample were weighed out
and the organics extracted on an Accelerated Solvent Extractor (ASE) using DCM:Acetone
(50:50). The ASE method is shown below in Table 8.5.1.
Preheat; 0 mins Purge; 60s Solvents;
Heat; 5 mins Cycles; 1 Acetone 50%
Static; 5 mins Pressure; 2000 psi DCM 50%
Flush; 50% Temp.; 100°C
Table 8.5.1. ASE extraction method
The extract was blown down to dryness under nitrogen in a turbo evaporator. This extract
was then made up to 0.5 mL in vials using toluene to dissolve the organics into solution and
transfer them from the ASE collection tubes.
In each batch there were four extraction efficiencies (EE). These are made by firstly
weighing out pristane (24 mg) and triphenylene (5.8 mg) then making up to 10 mL in
toluene. Then a soil that had been extracted multiple times so as it contains no organics; is
weighed (15 g) and 3.5 mL of the EE solution is spiked onto the soil along with a pre-made
resin standard of which only 50 µL is added. These EE samples were used as a quality control
so that the amounts of saturates, aromatics and resins in µg/g could be calculated. This
44
could then be checked when the samples had been analysed in order to get a percentage of
precision for each group of the TPH. Therefore with four being run with each batch, this acts
as a useful tool to help decide whether the results were accurate or whether the extraction
process was hindered, allowing samples for repeats to be selected appropriately.
To analyse the TPH content, an Iatroscan MK-6s was used. A calibration is achieved
by making calibration standards of which contain increasing concentrations of the Extraction
Efficiency standard. The standards 1,2,3,5 and 6 (Table 8.5.2) are spotted onto a rack of ten
silica rods, with each spotted on two rods. Then the rack is placed in a solvent tank of
hexane to elute the aliphatics for 25 mins, then put in a solvent tank of toluene to elute the
aromatics for 8 mins; and lastly placed in a tank of DCM:methanol (9:1) for 3 mins to elute
the resins. Once each group of the TPH’s have been separated the rack is finally placed in
the Iatroscan that uses an FID to transmit signals of the TPH’s, which typically displays a
three peak chromatogram. The same process is then used for the samples, however, on
every rack spotted the calibration standard 6 is used as a control on rods 1 and 2 so as to
ensure the real samples are of a suitable quality and be able to adjust them to a drift
correction.
Std. 1 Std. 2 Std. 3 Std. 4 Std. 5 Std. 6
EE Std. Vol.
(µL)150 300 500 700 1000 250
Resin Vol.
(µL)3 6 9 12 18 50
Toluene Vol.
(µL)850 700 500 300 0 250
Table 8.5.2. Calibration standards for the TPH analysis.
45
The results (Figure 8.5.3.) clearly display the oil spill that was visible in the two cores at 50
cm. Core A and core B show an intense rise in saturates to around 5800 mg/kg with resins
and aromatics also greatly increasing. However, in core B, just after 60 cm deep there is an
extremely intense peak of resins at a concentration of roughly 13000 mg/kg, with aromatics
at about 5800 mg/kg and saturates at around 4200 mg/kg. This is substantially more
concentrated, however it was not visible in the core as a dark band like the other spill. This
is most likely a crude oil spill that occurred since the composition is particularly strong in
resins, but since there are no records on it, it may not have been reported. The overall TPH
shows that both of these areas are over the US guideline maximum of TPH concentration at
most depths since the maximum is only 1000 mg/kg. This causes the unreported oil spill to
be 10 times over the limit. The data correlated with the analysis of PAHs on the samples by
Dr Alex Kim.
46
Figure 8.5.3. The left graph shows the variation of the three constituents of TPH down core A,
the middle one is TPH down core B. The graph on the right shows the overall TPH down both
cores taking all data points into account.
A few samples for n-alkanes were also analysed to further the evidence for pollution.
A sample was taken from each of the very contaminated sections and a couple from the
background, less-polluted areas. This analysis did again agree with the TPH data, with the
samples at 50 cm in both and 60 cm in core B producing very large UCMs.
London Earth soils:
The samples used for this TPH analysis were a set of X and A soils taken from around 120
different positions across London. The X soil was the topsoil (0-5 cm) and the A soils were
the 5-25 cm underneath X. These were prepared by using the ball mill in order to get a fine
47
powder for each. The process and methods for this analysis were exactly the same as used
with the Staten Island project (Table 8.5.1/2), apart from 1 g was measured out for each
sample. The locations of the samples were chosen on a statistically distributed basis and so
trends couldn’t be formed since the locations were unknown, however the data gained will
be used in conjunction with many other analysis techniques to put together a full document
at a later date.
8.6.Carbon-13 Isotope preparation
A number of samples were prepared for δ13C isotope analysis. Inorganic carbon can interfere
with the organic 13C in soils. Therefore the carbonates were broken down to be expelled as
CO2 as seen below:
2HCl + CaCO3 CaCl2 + H2O + CO2
Each sample was placed in a separate beaker before then adding 50 mL HCl (5%). Once left
for 24 hrs, it was topped up to 500 mL with water. After a day it was then decanted as best
as possible without losing the sediment, then it was topped up again with water. The
decanting was performed two more times in order to bring the pH back to neutral. Then
they were left in an oven to dry followed by using a pestle and mortar to crush into a fine
powder. Judging on the colour of the samples a very rough estimate of carbon percentage
could be deduced and based on this a certain amount was weighed into a tin capsule before
being analysed. This was completed for many peat core samples from Russia and samples
from the Haiyan typhoon.
48
The δ13C varies in time as a function of productivity, organic carbon burial and vegetation
type. The isotope signature is a measure of the stable isotopes 13C : 12C. It is analysed as per
mil, ‰, and it is calculated using the equation below (O'Leary (1988) [25]):
The calculation can be used to distinguish between biomass produced by C3 and C4
metabolic pathways, which allows for palaeo-reconstruction of species and ecosystems
range shifts based on the isotopic characterization of soil organic matter. The
C3 and C4 plants have different signatures, allowing them to be detected through time in
the δ13C record. Whereas C4 plants have a δ13C of −16 to −10 ‰, C3 plants have a δ13C of −33
to −24‰.
8.7.Pant y llyn 21 samples were removed at various intervals down a 6 metre core. They were based on
data that had already been gathered from pollen analysis, so it could be seen if the n-alkane
data would match the vegetation detected by the pollen and to reconstruct the
palaeoenvironment. Also, at the site from where the core was taken, there used to be a lake
and so the results would be able to show where the peat build up started from sampling
down the core. The same method was used as for the other n-alkane projects for the
preparation, extraction and analysis of the samples. From the data analysis, the proxy that
achieved the best visualisation of the core was the aquatic ratio (Paq) (Figure 8.7.1). The n-
alkane distribution for the top samples showed a dominant n-C29 peak in most cases, typical
of higher terrestrial plants. It agreed with the pollen data which suggested it was mineral
ground and roots from Carex swamp.
49
Figure 8.7.1. Aquatic ratio down the core (left); three graphs on the right show how the n-
alkane distribution alters down the core.
It is this minerotrophic soil that provides the nutrients for the sedges and grasses to
thrive, hence the Paq ratio is at its lowest point at the top end of the core. The aquatic ratio
gradually increases down the core, but in the centre, there is a large jump from a value of
0.33 to 0.68. The reason for this is that at this sample the pollen analysis detected
Sphagnum spalustre as being the dominant species. This Sphagnum has a dominant n-C23
and a secondary dominant n-C25 alkane as seen in the n-alkane distribution graph taken
from a depth of 246 cm. This causes the dramatic shift in aquatic ratio since these alkanes
are what the ratio are based on. The Paq then falls away to 0.38 and then begins to increase
gradually again, thus showing emergent/ floating plant species were present. The pollen
suggested that Potamogeton Natans was abundant in the lower parts of the core, which is a
floating species. This particular species also has an abundant n-C27 alkane (Tuo, Wu (2011)
50
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
-600
-500
-400
-300
-200
-100
0
Aquatic ratioPaq
Depth (cm
)
nC13
nC14nC1
5nC16
nC17nC18
nC19nC
20nC21
nC22nC23
nC24
nC25nC2
6nC27
nC28
nC29nC30
nC31
nC32nC
33nC34
nC35
nC36nC37
nC38nC39
nC40
0.0
5.0
10.0
15.0
20.0
25.0
10 cm
nC13nC14
nC15nC16
nC17nC18
nC19nC20
nC21nC22
nC23nC24
nC25nC26
nC27nC28
nC29nC30
nC31nC32
nC33nC34
nC35nC36
nC37nC38
nC39nC40
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0 246 cm
nC13nC14
nC15
nC16nC
17nC18
nC19
nC20nC21
nC22nC2
3nC
24nC25
nC26nC27
nC28
nC29nC3
0nC31
nC32nC33
nC34nC
35nC36
nC37
nC38nC3
9nC40
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0550 cm
[26]), which is shown by the distributions in the bottom samples analysed from this core. The
Paq ratio is a particularly helpful representation of the this core because it can be clearly
seen how the area it was taken from was once dominated by emergent and floating
vegetation, which was then followed by an onset of Sphagnum, where the values
significantly increase. The Sphagnum spalustre is dominant in n-C23 (Baas, Pancost (2000)
[27]), thus it grows in wet conditions and the increase in this will cause organic material to
build up and eventually form a peat in which higher plant growth can take place.
8.8.Lead-210 gamma spectroscopy
Lead-210 has a half-life of 22.3 years, and so is a good chronometer for most ecosystem
studies where changes have occurred within the last century. It provides age information,
especially with regards to sedimentation rate, in recent depositional environments allowing
for recent natural and socio-geographic impacts in depositional systems to be assessed. The
detector used for Pb-210 gamma spectroscopy is a high purity geranium (HPGe) detector.
The drawback of this detector is that it has to be constantly cooled in liquid nitrogen to
produce spectroscopic data and so each week the dewars containing the detector had to be
topped up. If the detector were in higher temperatures, the electrons can easily cross
the band gap in the crystal and reach the conduction band, where they are free to respond
to the electric field, producing too much electrical noise to be useful as a spectrometer.
Cooling it to liquid nitrogen temperature (77 K) reduces thermal excitations of valence
electrons so that only a gamma ray interaction can give an electron the energy necessary to
cross the band gap and reach the conduction band.
In nature, the uranium-238 series is broken by the diffusion of radon-222 from
minerals exposed at the earth’s surface. Radon-222 escapes into the atmosphere, and with
51
a half-life of 3.8 days, radon-222 decays through a series of very short half-life isotopes to
lead-210. This lead-210 is adsorbed onto surface sediments, thus producing excess lead-210
over that lead-210 in equilibrium with ambient radium-226 already within the sediments.
For age assessments the excess lead-210 is calculated.
The method, involved making sure the level of sediment within the sediment pot
was even and that it was weighed. Then the depth was measured of the sediment so as the
density could be calculated. The pot was placed in a detector that was protected from large
background radiation by lead, then cadmium foil to block the lead gamma rays followed by a
layer of copper to reduce the effect of the cadmium and lead radiation. The detector was
started on the software in order to start counting. The samples were very weak and so were
typically left for two or three days to count.
The Constant Rate of Supply model was used which assumes a constant lead-210
input but allows the sediment supply to vary (Appleby and Oldfield (1978) [28]). This model
applies to most sedimentary systems where the sediment supply may vary in response to
climatic or anthropogenic changes. This model requires, in addition to the determination the
excess lead-210, density measurements that were calculated from the geometry and weight
of the sediment pots.
A=∫∞
x
Cdm=∫x
x
ρCdx A=A (0 ) e−kt
A is the accumulative residual excess lead-210 beneath sediments of depth (x) or cumulative
dry mass (m) and ρ = dm/dx is the dry weight/wet volume ratio; it is then shown that the
age of the sediment of depth (x) is given by the equation.
52
9. Problems and solutions
Figure 9.1. Chromatogram showing the contamination
The first few runs on the GC-FID were producing some very bumpy backgrounds
(Figure 9.1) when injecting only hexane. It gave a regular hump every 3 minutes and so it
was initially assumed that column pressure was building up then releasing. With this kind of
extreme interference no integration of peaks can be reliable. The FID jet was removed and
changed with another, but the new one was too large, thus the flame would go out. Carried
on using original jet, and put it down to air pressure or quality. The H2: Air ratio flow to the
detector was reduced to 30:300 mL/min from 40:400 mL/min and a secondary regulator
was attached on to the air supply. Along with this, a scrubber was attached to remove any
hydrocarbons in the air supply and this eventually solved the issue.
When performing the molecular sieve procedure for the first time a problem arose
involving parafilm. The method was followed for the sieving process (section 8.3), and once
the first stage was complete, the washings were tested after the reflux. This was performed
in order to see if there was still a UCM with no odd-over-even preference and the
predictions were shown to be correct. Once the sieve was sonicated and broken down
53
again, it was analysed, but there were some extremely concentrated peaks in no order
preference in the range nC21 – nC33 (Figure 9.2). This meant that there was contamination
within the process. After back tracking the method and found that parafilm had been used
to seal the lid while sonication took place, a piece of parafilm was then sonicated in hexane
and analysed on the GC. The results produced the strong concentrations at the range of
same carbon numbers, therefore parafilm is now never used at all with anything to do with
the GC-FID since it will contaminate any n-alkane analysis.
54
nC21-nC33
nC21-nC33
Figure 9.2. The top chromatogram is the contaminated sample. The bottom chromatogram
shows a pure sample of the parafilm in hexane.
Figure 9.3. The top chromatogram shows the large bleed causing the disappearance of the
peaks. The lower chromatogram is what it should look like.
The column bleed is the normal background signal generated by the stationary column
phase. This is characterised by a gradual rise which reaches a plateau at the final
temperature of the ramp. However, when producing a few chromatograms on a quality
control, it was found that the bleed was a lot higher than usual. The base of the bleed
through to the plateau had a range of about 5 mV, which greatly affected the
55
≈5mV
n-C23 – n-C33
≈2mV
n-C23 – n-C33
chromatograms being produced since the n-alkane peaks in the range n-C23 – n-C33 (the most
important alkanes) were almost unidentifiable on the chromatogram (Figure 9.3). It could
have been some residue of high molecular weight that may have been adhering to the inlet
liner; therefore the liner was removed and cleaned as well as being sonicated in methanol.
Once dry it was replaced and noticeably there was a decline in the bleed level, but it still
hadn’t reduced enough. Then the column was removed from the inlet and using a ceramic
edge, neatly scored and flicked off around one metre of the column. This solved the
problem and the bleed was reduced back to 2 mV in range. The GC had to be recalibrated
after, since the column was shorter, so the retention times were reduced by around 10
seconds each.
In another case, it was discovered that some of the samples were contaminated
which were backed up by results from blanks run with them. The blanks showed a large
amount of n-alkane concentration, in particular around the n-C26 area. This correlated with
what was coming through in the samples as well, with many showing a dominant n-C26
alkane. Something similar had contaminated a few of the samples, so it had to have come
from the same source. Looking back through the experimental procedure, it was noticed
that sometimes a small amount of hexane may escape over the side of the columns when
performing column chromatography. This then flowed over the rubber on the clamp before
continuing into the collection vial, thus bringing with it contaminants from the rubber.
Therefore a piece of rubber from each clamp was analysed and they all had a uniform
distribution of n-alkanes with n-C26 being particularly abundant. Since the problem had been
found, the rubber parts have been wrapped in aluminium foil in case of spillage, preventing
unknown substances getting into the samples.
56
10. Training of succeeding studentsAs we were the first and only current users of the GC-FID at BGS, we put together an
instruction manual for the Clarity software run on the instrument. We designed it to be used
by anybody who had never used such an instrument before with clear and concise
instructions on how to set up methods, sequences and calibrations, all accompanied with
screenshots to help see the stages as well.
The two succeeding students came for two days in July in order to get a briefing and head
start on learning about the GC-FID and software before starting their placement a couple
months later. I showed them first general maintenance, for example, removing and
replacing the inlet, septum, injector, FID jet and the column. Then I would watch them have
a go and supervise. Then we moved on to the software and worked through setting up a
method and sequence. Then using a standard, we ran it on the GC-FID so I could take them
through the data analysis stage in the chromatogram window. When I felt they were
confident, I allowed them to then perform the set up themselves with myself watching over.
11. AcknowledgementsI would like to thank the BGS organic geochemistry team for providing an insightful and
enjoyable year’s placement. Thank goes to Dr Charles Gowing for taking time to train me on
the gamma spectroscopy instrumentation and software. Special thanks goes to Dr
Christopher Vane for providing me with an interesting project and gave guidance
throughout as well as keeping us busy with other fascinating projects. Also to Dr Alex Kim,
who gave a lot of time up at the start of the year to train us on various instrumental
57
software and maintenance, health and safety, general lab keeping and provided great
support throughout the year. Thank you to BGS for the funding of my placement year.
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metabolic engineering of waxes and hydrocarbon biofuels. The Plant Journal, 2008. 54(4): p.
670-683.
2. Killops, S.D. and V.J. Killops, Introduction to organic geochemistry. 2009: Wiley. com.
3. Ehleringer, J.R. and T.E. Cerling, C3 and C4 photosynthesis. Encyclopedia of Global
Environmental Change. The earth system: biological and ecological dimensions of global
environmental change, 2002. 2: p. 186-190.
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4. Eglinton, G. and R.J. Hamilton, Leaf Epicuticular Waxes. Science, 1967. 156(3780): p. 1322-
1335.
5. Chibnall, A.C., S.H. Piper, et al., The constitution of the primary alcohols, fatty acids and
paraffins present in plant and insect waxes. Biochemical Journal, 1934. 28(6): p. 2189.
6. Sachse, D., J. Radke, and G. Gleixner, Hydrogen isotope ratios of recent lacustrine
sedimentary n-alkanes record modern climate variability. Geochimica et Cosmochimica Acta,
2004. 68(23): p. 4877-4889.
7. Smith, F.A., S.L. Wing, and K.H. Freeman, Magnitude of the carbon isotope excursion at the
Paleocene–Eocene thermal maximum: The role of plant community change. Earth and
Planetary Science Letters, 2007. 262(1): p. 50-65.
8. Meyers, P.A. and R. Ishiwatari, Lacustrine organic geochemistry—an overview of indicators
of organic matter sources and diagenesis in lake sediments. Organic Geochemistry, 1993.
20(7): p. 867-900.
9. Ratnayake, N.P., N. Suzuki, et al., The variations of stable carbon isotope ratio of land plant-
derived< i> n</i>-alkanes in deep-sea sediments from the Bering Sea and the North Pacific
Ocean during the last 250,000 years. Chemical geology, 2006. 228(4): p. 197-208.
10. Ficken, K.J., B. Li, et al., An n-alkane proxy for the sedimentary input of submerged/floating
freshwater aquatic macrophytes. Organic Geochemistry, 2000. 31(7–8): p. 745-749.
11. Ficken, K., K. Barber, and G. Eglinton, Lipid biomarker,< i> δ</i>< sup> 13</sup> C and plant
macrofossil stratigraphy of a Scottish montane peat bog over the last two millennia. Organic
Geochemistry, 1998. 28(3): p. 217-237.
12. Nott, C.J., S. Xie, et al., n-Alkane distributions in ombrotrophic mires as indicators of
vegetation change related to climatic variation. Organic Geochemistry, 2000. 31(2–3): p.
231-235.
13. Rydin, H. and J.K. Jeglum, The Biology of Peatlands, 2e. 2013: Oxford University Press.
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14. Corrigan, D., C. Kloos, et al., Alkanes from four species of< i> Sphagnum moss</i>.
Phytochemistry, 1973. 12(1): p. 213-214.
15. Vonk, J.E. and Ö. Gustafsson, Calibrating n-alkane Sphagnum proxies in sub-Arctic
Scandinavia. Organic Geochemistry, 2009. 40(10): p. 1085-1090.
16. Bingham, E.M., E.L. McClymont, et al., Conservative composition of n-alkane biomarkers in
Sphagnum species: Implications for palaeoclimate reconstruction in ombrotrophic peat bogs.
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Biochemical systematics and ecology, 1987. 15(6): p. 663-665.
18. Mille, G., L. Asia, et al., Hydrocarbons in coastal sediments from the Mediterranean sea (Gulf
of Fos area, France). Marine Pollution Bulletin, 2007. 54(5): p. 566-575.
19. Poynter, J. and G. Eglinton. 14. MOLECULAR COMPOSITION OF THREE SEDIMENTS FROM
HOLE 717C: THE BENGAL FAN1. in Proceedings of the Ocean Drilling Program: Scientific
results. 1987. The Program.
20. Pancost, R.D., M. Baas, et al., Biomarkers as proxies for plant inputs to peats: an example
from a sub-boreal ombrotrophic bog. Organic Geochemistry, 2002. 33(7): p. 675-690.
21. Vonk, J.E., B.E. van Dongen, and Ö. Gustafsson, Lipid biomarker investigation of the origin
and diagenetic state of sub-arctic terrestrial organic matter presently exported into the
northern Bothnian Bay. Marine Chemistry, 2008. 112(1–2): p. 1-10.
22. Andersson, R.A., P. Kuhry, et al., Impacts of paleohydrological changes on n-alkane
biomarker compositions of a Holocene peat sequence in the eastern European Russian Arctic.
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23. Nichols, J.E., R.K. Booth, et al., Paleohydrologic reconstruction based on n-alkane
distributions in ombrotrophic peat. Organic Geochemistry, 2006. 37(11): p. 1505-1513.
60
24. Caravaggio, G.A., J.-P. Charland, et al., n-Alkane profiles of engine lubricating oil and
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61
Supplementary Information
62
Supplementary Information
63
CompoundBlank
RUS_OL_2RUS_OL_3RUS_OL_4
RUS_OL_5RUS_OL_6RUS_OL_7RUS_OL_8RUS_OL_9RUS_OL_10RUS_OL_11RUS_OL_12RUS_OL_13RUS_OL_14RUS_OL_15RUS_OL_16RUS_OL_17RUS_OL_18RUS_OL_19
RUS_OL_20RUS_OL_21RUS_OL_22RUS_OL_23RUS_OL_24
nC130.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC14
0.0000.000
0.5490.342
0.7140.920
0.5511.230
0.4971.254
1.2520.611
0.0001.423
0.6761.219
1.1751.280
0.5450.977
1.5851.644
0.4890.734
nC150.000
0.0000.389
0.5240.640
0.4630.551
0.5060.543
0.5240.584
0.7030.000
0.5540.590
0.5700.573
0.6060.483
0.6862.761
0.4660.261
0.258nC16
0.0000.157
0.3710.416
0.5260.343
0.2330.374
0.4630.410
0.4760.406
0.1030.446
0.5330.524
0.3720.377
0.2840.629
1.3810.506
0.3810.258
nC170.000
0.0890.000
0.2960.337
0.3030.301
0.2930.337
0.3130.340
0.3430.043
0.3030.372
0.3760.292
0.3310.227
0.3430.966
0.4312.205
0.166nC18
0.0000.166
0.3710.330
0.3710.320
0.2100.397
0.4630.291
0.3850.354
0.1080.371
0.3840.325
0.2640.320
0.2220.337
0.8580.609
0.3980.266
nC190.000
0.1490.383
0.2960.497
0.3770.261
0.5920.754
0.3820.504
0.4060.097
0.3770.596
0.4730.453
0.5830.432
0.7031.716
1.6210.773
0.221nC20
0.0000.169
0.7940.519
0.6060.423
0.3640.580
0.7200.319
0.6010.646
0.1600.440
0.9050.957
1.5301.503
5.2954.491
30.3136.184
12.6590.390
nC210.197
0.5492.600
4.2622.686
1.1831.244
2.6264.594
1.2931.824
1.6290.556
1.8743.054
1.3681.232
2.1544.511
15.76610.097
3.5801.881
0.754nC22
0.3890.480
2.4111.499
1.9941.337
0.8641.592
2.0971.003
1.1610.857
0.4420.914
1.1400.900
1.2031.263
1.3642.457
3.6702.121
2.0060.880
nC230.586
1.3634.920
4.8156.120
3.3033.023
5.9547.223
3.6014.958
4.7831.330
4.1895.966
3.7215.679
12.22923.330
9.21743.182
23.61534.665
2.413nC24
0.6861.209
5.5312.695
4.8293.857
3.3753.287
3.6001.818
1.8361.520
1.2021.429
1.9201.333
1.4331.874
2.4433.006
6.6934.391
22.0341.301
nC250.646
2.7269.903
9.54414.674
10.0469.688
15.15512.371
11.05413.365
13.0462.746
12.83411.885
9.00945.335
21.97124.591
18.594181.659
36.89738.892
2.633nC26
0.6371.951
11.0574.097
6.9834.669
3.2333.029
4.1262.325
2.6911.823
1.9091.731
2.5731.778
1.6101.863
2.3695.354
10.7275.615
4.7560.885
nC270.654
4.75118.520
13.55620.417
12.04611.943
16.66120.126
14.15416.924
16.7604.783
15.61116.223
12.09717.473
19.20032.767
48.046274.528
151.57520.750
4.238nC28
0.5691.866
11.9205.174
7.6404.931
2.5683.420
6.1542.655
3.3773.217
1.8632.314
4.1723.026
1.5931.446
1.89811.223
11.3015.368
3.1990.880
nC290.906
4.20039.623
34.73531.846
12.85710.756
35.006117.114
33.07744.295
72.5034.208
40.72092.642
48.55846.470
27.52644.688
121.87498.159
37.97722.028
3.364nC30
0.4831.311
11.3605.214
8.8514.457
2.8134.247
11.4403.766
4.5675.514
1.2963.794
9.2095.316
3.2781.943
3.79510.143
8.3522.167
1.9030.682
nC310.580
4.380143.143
116.724160.434
43.86944.233
108.569340.377
74.997118.516
172.0863.923
127.480344.888
139.157127.593
74.869199.250
251.811226.102
30.20720.597
3.837nC32
0.0000.909
16.0867.254
18.75413.394
15.1487.046
20.2175.584
6.2386.874
0.8956.429
24.42416.239
5.4671.823
6.83011.657
16.1144.793
2.1930.619
nC330.000
1.723138.509
66.501210.503
46.46352.960
70.816192.114
44.04660.244
69.8171.678
70.206205.960
72.65562.819
29.88679.432
67.01764.472
27.3565.744
1.289nC34
0.0000.323
5.8061.972
6.1092.017
1.5001.397
4.9542.148
2.1190.766
0.0001.177
3.8113.783
0.8140.440
0.3410.531
1.1480.661
1.1820.246
nC350.000
0.0008.571
3.15712.137
3.0233.125
2.9207.783
2.4621.779
1.3430.000
1.6294.602
3.0660.877
0.4510.693
1.4692.108
1.5630.795
0.249nC36
0.0000.000
1.4740.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
nC370.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC38
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
nC390.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC40
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
Total Conc6.331
28.469434.291
283.920517.669
170.600168.943
285.695758.069
207.476288.034
376.00627.342
296.246736.527
326.450327.536
203.937435.790
586.331997.892
349.345199.790
26.562Cmax
2731
3133
3333
3131
3131
3131
3131
3131
3131
3127
2725
27Paq
0.45320720.32
0.080.09
0.100.19
0.190.13
0.040.12
0.100.07
0.330.09
0.040.06
0.230.25
0.160.07
0.410.47
0.630.41
TAR#DIV/0!
56.22260.93
147.76144.27
60.1860.10
115.21292.25
100.24125.88
180.0692.51
148.92291.10
140.83145.32
80.00242.29
243.57110.01
87.3019.57
17.74CPI
1.29162362.33
5.518.66
8.013.70
4.5010.15
12.899.08
11.1816.03
2.4314.42
13.948.46
17.5414.73
16.5010.73
9.989.70
2.922.99
ACL(25-33)28.73
31.1830.80
31.4330.67
30.8330.65
30.9930.43
30.5430.56
28.6530.70
31.1330.81
29.9729.82
30.4530.19
28.3328.01
27.7728.60
ACL(23-25)24.33
24.3424.33
24.4124.51
24.5224.44
24.2624.51
24.4624.46
24.3524.51
24.3324.42
24.7824.28
24.0324.34
24.6224.22
24.0624.04
Concentration (µg/g) - Top half of Tracy Potter Core
64
CompoundBlank
RUS_OL_2RUS_OL_3RUS_OL_4
RUS_OL_5RUS_OL_6RUS_OL_7RUS_OL_8RUS_OL_9RUS_OL_10RUS_OL_11RUS_OL_12RUS_OL_13RUS_OL_14RUS_OL_15RUS_OL_16RUS_OL_17RUS_OL_18RUS_OL_19
RUS_OL_20RUS_OL_21RUS_OL_22RUS_OL_23RUS_OL_24
nC130.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC14
0.0000.000
0.5490.342
0.7140.920
0.5511.230
0.4971.254
1.2520.611
0.0001.423
0.6761.219
1.1751.280
0.5450.977
1.5851.644
0.4890.734
nC150.000
0.0000.389
0.5240.640
0.4630.551
0.5060.543
0.5240.584
0.7030.000
0.5540.590
0.5700.573
0.6060.483
0.6862.761
0.4660.261
0.258nC16
0.0000.157
0.3710.416
0.5260.343
0.2330.374
0.4630.410
0.4760.406
0.1030.446
0.5330.524
0.3720.377
0.2840.629
1.3810.506
0.3810.258
nC170.000
0.0890.000
0.2960.337
0.3030.301
0.2930.337
0.3130.340
0.3430.043
0.3030.372
0.3760.292
0.3310.227
0.3430.966
0.4312.205
0.166nC18
0.0000.166
0.3710.330
0.3710.320
0.2100.397
0.4630.291
0.3850.354
0.1080.371
0.3840.325
0.2640.320
0.2220.337
0.8580.609
0.3980.266
nC190.000
0.1490.383
0.2960.497
0.3770.261
0.5920.754
0.3820.504
0.4060.097
0.3770.596
0.4730.453
0.5830.432
0.7031.716
1.6210.773
0.221nC20
0.0000.169
0.7940.519
0.6060.423
0.3640.580
0.7200.319
0.6010.646
0.1600.440
0.9050.957
1.5301.503
5.2954.491
30.3136.184
12.6590.390
nC210.197
0.5492.600
4.2622.686
1.1831.244
2.6264.594
1.2931.824
1.6290.556
1.8743.054
1.3681.232
2.1544.511
15.76610.097
3.5801.881
0.754nC22
0.3890.480
2.4111.499
1.9941.337
0.8641.592
2.0971.003
1.1610.857
0.4420.914
1.1400.900
1.2031.263
1.3642.457
3.6702.121
2.0060.880
nC230.586
1.3634.920
4.8156.120
3.3033.023
5.9547.223
3.6014.958
4.7831.330
4.1895.966
3.7215.679
12.22923.330
9.21743.182
23.61534.665
2.413nC24
0.6861.209
5.5312.695
4.8293.857
3.3753.287
3.6001.818
1.8361.520
1.2021.429
1.9201.333
1.4331.874
2.4433.006
6.6934.391
22.0341.301
nC250.646
2.7269.903
9.54414.674
10.0469.688
15.15512.371
11.05413.365
13.0462.746
12.83411.885
9.00945.335
21.97124.591
18.594181.659
36.89738.892
2.633nC26
0.6371.951
11.0574.097
6.9834.669
3.2333.029
4.1262.325
2.6911.823
1.9091.731
2.5731.778
1.6101.863
2.3695.354
10.7275.615
4.7560.885
nC270.654
4.75118.520
13.55620.417
12.04611.943
16.66120.126
14.15416.924
16.7604.783
15.61116.223
12.09717.473
19.20032.767
48.046274.528
151.57520.750
4.238nC28
0.5691.866
11.9205.174
7.6404.931
2.5683.420
6.1542.655
3.3773.217
1.8632.314
4.1723.026
1.5931.446
1.89811.223
11.3015.368
3.1990.880
nC290.906
4.20039.623
34.73531.846
12.85710.756
35.006117.114
33.07744.295
72.5034.208
40.72092.642
48.55846.470
27.52644.688
121.87498.159
37.97722.028
3.364nC30
0.4831.311
11.3605.214
8.8514.457
2.8134.247
11.4403.766
4.5675.514
1.2963.794
9.2095.316
3.2781.943
3.79510.143
8.3522.167
1.9030.682
nC310.580
4.380143.143
116.724160.434
43.86944.233
108.569340.377
74.997118.516
172.0863.923
127.480344.888
139.157127.593
74.869199.250
251.811226.102
30.20720.597
3.837nC32
0.0000.909
16.0867.254
18.75413.394
15.1487.046
20.2175.584
6.2386.874
0.8956.429
24.42416.239
5.4671.823
6.83011.657
16.1144.793
2.1930.619
nC330.000
1.723138.509
66.501210.503
46.46352.960
70.816192.114
44.04660.244
69.8171.678
70.206205.960
72.65562.819
29.88679.432
67.01764.472
27.3565.744
1.289nC34
0.0000.323
5.8061.972
6.1092.017
1.5001.397
4.9542.148
2.1190.766
0.0001.177
3.8113.783
0.8140.440
0.3410.531
1.1480.661
1.1820.246
nC350.000
0.0008.571
3.15712.137
3.0233.125
2.9207.783
2.4621.779
1.3430.000
1.6294.602
3.0660.877
0.4510.693
1.4692.108
1.5630.795
0.249nC36
0.0000.000
1.4740.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
nC370.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC38
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
nC390.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.000nC40
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
Total Conc6.331
28.469434.291
283.920517.669
170.600168.943
285.695758.069
207.476288.034
376.00627.342
296.246736.527
326.450327.536
203.937435.790
586.331997.892
349.345199.790
26.562Cmax
2731
3133
3333
3131
3131
3131
3131
3131
3131
3127
2725
27Paq
0.45320720.32
0.080.09
0.100.19
0.190.13
0.040.12
0.100.07
0.330.09
0.040.06
0.230.25
0.160.07
0.410.47
0.630.41
TAR#DIV/0!
56.22260.93
147.76144.27
60.1860.10
115.21292.25
100.24125.88
180.0692.51
148.92291.10
140.83145.32
80.00242.29
243.57110.01
87.3019.57
17.74CPI
1.29162362.33
5.518.66
8.013.70
4.5010.15
12.899.08
11.1816.03
2.4314.42
13.948.46
17.5414.73
16.5010.73
9.989.70
2.922.99
ACL(25-33)28.73
31.1830.80
31.4330.67
30.8330.65
30.9930.43
30.5430.56
28.6530.70
31.1330.81
29.9729.82
30.4530.19
28.3328.01
27.7728.60
ACL(23-25)24.33
24.3424.33
24.4124.51
24.5224.44
24.2624.51
24.4624.46
24.3524.51
24.3324.42
24.7824.28
24.0324.34
24.6224.22
24.0624.04
Concentration (µg/g) - Top half of Tracy Potter Core
65
BlankRUS_OL_26RUS_OL_27RUS_OL_28RUS_OL_29
RUS_OL_30RUS_OL_31RUS_OL_32RUS_OL_33RUS_OL_34
RUS_OL_35RUS_OL_36RUS_OL_37RUS_OL_38RUS_OL_39RUS_OL_40RUS_OL_41RUS_OL_42RUS_OL_43RUS_OL_44RUS_OL_45RUS_OL_46RUS_OL_47RUS_OL_48
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
1.6010.946
0.7390.657
0.4620.241
0.0000.398
0.8690.526
0.0000.000
0.0000.000
0.1700.337
0.3090.200
0.0000.000
0.0000.000
0.0000.000
2.2392.074
0.5971.669
0.2170.000
0.0000.097
0.6060.400
0.0000.000
0.0000.456
0.1870.177
0.2230.131
0.0000.000
0.0000.000
0.0000.077
0.5750.667
0.4320.909
0.4220.183
0.1420.352
0.6170.543
0.1540.282
0.3870.416
0.2320.383
0.4970.349
0.1030.066
0.2180.175
0.0000.085
0.3870.462
0.3070.474
1.2360.418
0.2450.364
0.4910.440
0.0890.356
0.4100.370
0.2270.343
0.2510.217
0.1200.077
0.0620.121
0.3230.179
0.4840.575
0.3010.680
0.5640.344
0.1880.602
0.7490.629
0.1890.552
0.5930.752
0.5720.646
0.5710.331
0.2800.142
0.2070.328
0.0000.160
1.0541.721
0.8241.057
0.6840.585
0.5470.756
0.7260.897
0.1201.195
1.1451.151
1.0990.994
0.9830.457
0.1600.077
0.1270.144
0.0000.217
148.855182.479
46.34740.806
7.8232.888
2.6273.403
1.8000.994
0.1601.253
2.0063.385
0.9070.977
1.0230.400
0.1710.094
0.1700.198
0.2230.632
4.6044.490
4.3759.931
1.4761.633
1.6184.136
2.3438.331
0.5208.540
10.1259.373
7.9045.777
4.3261.811
0.6000.245
0.2750.559
0.6060.513
1.6181.732
1.0512.389
1.5611.782
1.2422.932
1.1202.634
0.5003.092
3.8013.453
2.9522.800
1.9140.891
0.5370.325
0.4110.497
0.8941.521
18.37611.145
5.2567.131
11.0379.914
10.22833.057
9.52612.811
1.52619.184
21.60723.060
18.15921.851
16.6178.217
1.4340.413
0.5071.325
1.1171.248
3.7664.142
2.7784.726
11.1286.779
7.48720.699
2.3893.440
1.2663.678
4.3874.405
2.9864.343
2.2461.229
0.6060.325
0.5010.864
0.9112.786
29.51621.459
12.39817.869
22.38715.140
14.73571.688
33.20022.023
2.60030.402
30.83232.462
24.37436.560
27.34912.840
1.9310.442
0.5582.028
0.6912.011
5.3908.786
6.54511.760
10.6893.994
3.76130.449
4.9774.057
1.7145.264
4.7185.368
3.3544.977
2.6061.549
0.5600.219
0.3091.014
0.3544.801
64.29145.618
20.05746.703
25.07720.109
16.889168.114
129.10946.006
4.63785.770
57.53378.610
54.21586.097
61.52029.869
3.5370.490
0.5013.573
0.0001.972
5.5619.863
9.51716.343
8.8894.092
3.65222.091
4.9943.651
1.9916.328
4.6505.840
3.4794.583
2.5141.697
0.5260.171
0.2921.000
0.0003.744
84.34873.293
58.761133.789
27.02623.570
19.67542.000
20.89723.069
4.20952.511
41.51041.641
36.16444.971
27.36012.669
2.8860.350
0.4392.754
0.0001.405
7.24210.650
5.93814.034
5.6812.401
2.21711.364
2.4571.737
1.9203.494
2.4272.957
1.7621.714
1.1541.577
0.5430.111
0.2350.740
0.0003.880
274.382274.103
122.085276.709
24.47318.390
15.52128.625
13.54911.303
4.63736.598
27.97723.721
18.31713.154
9.2746.657
3.3260.362
0.3943.073
0.0000.832
4.79818.348
3.8131.634
1.2931.112
2.6042.097
1.6172.383
1.9341.931
1.5161.214
2.2661.217
1.1201.954
0.3430.080
0.2150.596
0.0001.296
106.382129.561
40.97264.103
6.4393.668
4.02310.114
5.2065.594
2.5238.851
8.4058.701
8.5675.720
4.9893.080
1.0690.165
0.2461.153
0.0000.293
0.6041.510
0.9891.211
1.1230.585
0.7642.068
1.1540.314
1.2940.810
0.4160.501
0.4250.320
0.0000.000
0.0000.000
0.0000.000
0.0000.197
1.2712.291
0.9661.371
1.0430.785
0.9122.648
2.2691.006
0.9512.092
1.1911.071
1.1951.223
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
0.0000.000
5.12027.849
767.345805.915
345.045655.954
170.729118.613
109.077458.051
240.663152.789
32.934272.184
225.635248.906
189.513239.166
166.84686.126
18.7314.154
5.66920.144
2731
3131
3129
2929
2727
2727/31
2727
2727
2727
2727
2725
271.00
0.360.12
0.090.09
0.060.39
0.370.41
0.600.55
0.500.32
0.360.43
0.460.44
0.500.55
0.520.35
0.550.56
0.37#DIV/0!
50.71114.92
92.33116.31
142.8835.84
61.8965.76
196.3589.72
46.2764.64
112.7081.66
72.8271.85
95.2467.36
61.0634.82
7.817.03
35.400.87
2.173.27
2.363.42
5.922.45
3.883.40
3.759.90
6.441.92
9.168.04
7.778.96
9.8411.20
7.614.11
1.711.22
2.7225.56
28.5330.30
30.6330.25
30.2028.38
28.3928.36
27.3627.30
27.7528.98
28.1428.10
27.8928.05
27.5627.51
27.6928.70
28.2528.32
28.6424.01
24.2924.23
24.3224.40
24.4324.34
24.2124.18
24.3724.55
24.2624.26
24.2324.18
24.1724.15
24.2524.24
24.2224.15
24.0324.05
24.21
Bottom Half of Tracy Potter Core
A high resolution picture of each sample analysed put together to form a resemblant core.
66
1.5 cm
101.5 cm
201.5 cm
239 cm
489 cm
301.5 cm
401.5 cm
67
Compound
QC 1
QC 2
QC 3
QC 4
QC 5
QC 6
STDEV
Average
STDEV
/AV
G
nC130.000
0.0000.000
0.0000.000
0.000V
arience coefficient
nC140.000
0.0000.734
0.0000.000
0.000nC15
0.0000.000
0.2580.000
0.0000.000
nC160.157
0.1030.258
0.0770.154
0.1750.063
0.15441%
nC170.089
0.0430.166
0.0850.089
0.1210.041
0.09942%
nC180.166
0.1080.266
0.1790.189
0.3280.078
0.20638%
nC190.149
0.0970.221
0.1600.120
0.1440.042
0.14828%
nC200.169
0.1600.390
0.2170.160
0.1980.088
0.21541%
nC210.549
0.5560.754
0.6320.520
0.5590.086
0.59514%
nC220.480
0.4420.880
0.5130.500
0.4970.162
0.55229%
nC231.363
1.3302.413
1.5211.526
1.3250.418
1.58026%
nC241.209
1.2021.301
1.2481.266
0.8640.160
1.18214%
nC252.726
2.7462.633
2.7862.600
2.0280.282
2.58711%
nC261.951
1.9090.885
2.0111.714
1.0140.501
1.58132%
nC274.751
4.7834.238
4.8014.637
3.5730.484
4.46411%
nC281.866
1.8630.880
1.9721.991
1.0000.512
1.59532%
nC294.200
4.2083.364
3.7444.209
2.7540.594
3.74616%
nC301.311
1.2960.682
1.4051.920
0.7400.460
1.22638%
nC314.380
3.9233.837
3.8804.637
3.0730.537
3.95514%
nC320.909
0.8950.619
0.8321.934
0.5960.494
0.96451%
nC331.723
1.6781.289
1.2962.523
1.1530.502
1.61031%
nC340.323
0.0000.246
0.2931.294
0.0000.504
0.53994%
nC350.000
0.0000.249
0.1970.951
0.0000.421
0.46690%
nC360.000
0.0000.000
0.0000.000
0.000nC37
0.0000.000
0.0000.000
0.0000.000
nC380.000
0.0000.000
0.0000.000
0.000nC39
0.0000.000
0.0000.000
0.0000.000
nC400.000
0.0000.000
0.0000.000
0.000Total Conc
28.46927.342
26.56227.849
32.93420.144
Cm
ax27
2727
2727
27Paq
0.3227330.333956
0.4120260.361032
0.3180620.365231
TAR
56.2168792.5102
17.7422250.7093
64.6438435.40426
CPI2.333556
2.42752.991726
2.1728011.918186
2.721816
Quality Control D
istribution
Concentration (µg/g)
68
69
Histograms showing distributions of n-alkanes for all samples in the core.
70
DepthTAR
PaqCPI
ACLC23
C25C27
C29C31
C27+C29+C31C23/C31
C25/C31C23/C29
C25/C29C23/C25
Total conc.C23/(C23+C29)C25/(C25+C29)C25/(C25+C31)Psas
-1.5260.93
0.085.51
31.184.92
9.9018.52
39.62143.14
201.290.03
0.070.12
0.250.50
434.290.11
0.200.06
0.17-14
147.760.09
8.6630.80
4.819.54
13.5634.74
116.72165.01
0.040.08
0.140.27
0.50283.92
0.120.22
0.080.26
-26.5144.27
0.108.01
31.436.12
14.6720.42
31.85160.43
212.700.04
0.090.19
0.460.42
517.670.16
0.320.08
0.14-39
60.180.19
3.7030.67
3.3010.05
12.0512.86
43.8768.77
0.080.23
0.260.78
0.33170.60
0.200.44
0.190.32
-51.560.10
0.194.50
30.833.02
9.6911.94
10.7644.23
66.930.07
0.220.28
0.900.31
168.940.22
0.470.18
0.29-64
115.210.13
10.1530.65
5.9515.16
16.6635.01
108.57160.24
0.050.14
0.170.43
0.39285.70
0.150.30
0.120.31
-76.5292.25
0.0412.89
30.997.22
12.3720.13
117.11340.38
477.620.02
0.040.06
0.110.58
758.070.06
0.100.04
0.14-89
100.240.12
9.0830.43
3.6011.05
14.1533.08
75.00122.23
0.050.15
0.110.33
0.33207.48
0.100.25
0.130.36
-101.5125.88
0.1011.18
30.544.96
13.3716.92
44.29118.52
179.730.04
0.110.11
0.300.37
288.030.10
0.230.10
0.33-114
180.060.07
16.0330.56
4.7813.05
16.7672.50
172.09261.35
0.030.08
0.070.18
0.37376.01
0.060.15
0.070.30
-126.5148.92
0.0914.42
30.704.19
12.8315.61
40.72127.48
183.810.03
0.100.10
0.320.33
296.250.09
0.240.09
0.29-139
291.100.04
13.9431.13
5.9711.89
16.2292.64
344.89453.75
0.020.03
0.060.13
0.50736.53
0.060.11
0.030.12
-151.5140.83
0.068.46
30.813.72
9.0112.10
48.56139.16
199.810.03
0.060.08
0.190.41
326.450.07
0.160.06
0.23-164
145.320.23
17.5429.97
5.6845.34
17.4746.47
127.59191.54
0.040.36
0.120.98
0.13327.54
0.110.49
0.260.50
-176.580.00
0.2514.73
29.8212.23
21.9719.20
27.5374.87
121.590.16
0.290.44
0.800.56
203.940.31
0.440.23
0.58-189
242.290.16
16.5030.45
23.3324.59
32.7744.69
199.25276.70
0.120.12
0.520.55
0.95435.79
0.340.35
0.110.42
-201.5243.57
0.0710.73
30.199.22
18.5948.05
121.87251.81
421.730.04
0.070.08
0.150.50
586.330.07
0.130.07
0.50-214
110.010.41
9.9828.33
43.18181.66
274.5398.16
226.10598.79
0.190.80
0.441.85
0.24997.89
0.310.65
0.450.88
-226.587.30
0.479.70
28.0123.61
36.90151.57
37.9830.21
219.760.78
1.220.62
0.970.64
349.340.38
0.490.55
0.87-239
19.570.63
2.9227.77
34.6638.89
20.7522.03
20.6063.38
1.681.89
1.571.77
0.89199.79
0.610.64
0.650.91
-251.5114.92
0.123.27
30.3018.38
29.5264.29
84.35274.38
423.020.07
0.110.22
0.350.62
767.340.18
0.260.10
0.84-264
92.330.09
2.3630.63
11.1521.46
45.6273.29
274.10393.01
0.040.08
0.150.29
0.52805.91
0.130.23
0.070.34
-276.5116.31
0.093.42
30.255.26
12.4020.06
58.76122.09
200.900.04
0.100.09
0.210.42
345.050.08
0.170.09
0.44-289
142.880.06
5.9230.20
7.1317.87
46.70133.79
276.71457.20
0.030.06
0.050.13
0.40655.95
0.050.12
0.060.50
-301.535.84
0.392.45
28.3811.04
22.3925.08
27.0324.47
76.580.45
0.910.41
0.830.49
170.730.29
0.450.48
0.88-314
61.890.37
3.8828.39
9.9115.14
20.1123.57
18.3962.07
0.540.82
0.420.64
0.65118.61
0.300.39
0.450.91
-326.565.76
0.413.40
28.3610.23
14.7416.89
19.6815.52
52.090.66
0.950.52
0.750.69
109.080.34
0.430.49
0.89-339
196.350.60
3.7527.36
33.0671.69
168.1142.00
28.63238.74
1.152.50
0.791.71
0.46458.05
0.440.63
0.710.96
-351.589.72
0.559.90
27.309.53
33.20129.11
20.9013.55
163.550.70
2.450.46
1.590.29
240.660.31
0.610.71
0.97-364
46.270.50
6.4427.75
12.8122.02
46.0123.07
11.3080.38
1.131.95
0.560.95
0.58152.79
0.360.49
0.660.92
-376.5112.70
0.369.16
28.1419.18
30.4085.77
52.5136.60
174.880.52
0.830.37
0.580.63
272.180.27
0.370.45
0.74-389
81.660.43
8.0428.10
21.6130.83
57.5341.51
27.98127.02
0.771.10
0.520.74
0.70225.64
0.340.43
0.520.91
-401.572.82
0.467.77
27.8923.06
32.4678.61
41.6423.72
143.970.97
1.370.55
0.780.71
248.910.36
0.440.58
0.93-414
71.850.44
8.9628.05
18.1624.37
54.2236.16
18.32108.70
0.991.33
0.500.67
0.75189.51
0.330.40
0.570.90
-426.595.24
0.509.84
27.5621.85
36.5686.10
44.9713.15
144.221.66
2.780.49
0.810.60
239.170.33
0.450.74
0.96-439
67.360.55
11.2027.51
16.6227.35
61.5227.36
9.2798.15
1.792.95
0.611.00
0.61166.85
0.380.50
0.750.95
-451.561.06
0.527.61
27.698.22
12.8429.87
12.676.66
49.191.23
1.930.65
1.010.64
86.130.39
0.500.66
0.93-464
34.820.35
4.1128.70
1.431.93
3.542.89
3.339.75
0.430.58
0.500.67
0.7418.73
0.330.40
0.370.84
-476.57.81
0.551.71
28.250.41
0.440.49
0.350.36
1.201.14
1.221.18
1.260.94
4.150.54
0.560.55
0.85-489
7.030.56
1.2228.32
0.510.56
0.500.44
0.391.33
1.291.42
1.151.27
0.915.67
0.540.56
0.590.81
71
72
73
74
