Diploma thesis in Physics submitted by Florian Freundt born in ...

Faculty of Physics and Astronomy
Heidelberg University
Diploma thesis
in Physics
submitted by
Florian Freundt
born in Lemgo
2011

Measuring annual variation of soil
atmosphere composition focusing on
the effect of oxygen depletion on
noble gas partial pressures
This diploma thesis was carried out by Florian Freundt at the
Institute of Environmental Physics
under the supervision of
Prof. Dr. Werner Aeschbach-Hertig

Measuring annual variation of soil atmosphere composition
focusing on the effect of oxygen depletion on noble gas partial
pressures
Abstract
It is known that the partial pressures of soil atmosphere components like oxygen, carbon dioxide and
nitrous oxides show fluctuations on both temporal and spatial scales. These are primarily caused by
microbiologic activities in the soil. However, the use of noble gases dissolved in ground water as a climate
proxy utilizes the basic assumption that the ground air equilibrating with water during recharge is of
atmospheric composition with regard to noble gases. This assumption has been questioned to account
for lower than expected noble gas temperatures, suggesting a rise of noble gas partial pressures in the
soil atmosphere caused by removal of CO2 (produced by O2 depleting soil respiration) due to its high
solubility in water [Hall et al., 2005]. To test this proposition three permanent sampling sites were built
in clay dominated soil, allowing for sampling of ground air in regular intervals and depths up to 6 meters.
O2 and CO2 concentrations were measured on site while the noble gases helium, neon, argon, krypton
and xenon were sampled and measured in the laboratory using mass spectrometry.
It was confirmed that O2 and CO2 concentrations within the soil atmosphere fluctuate strongly, the sum
of O2 and CO2 reached a minimum of 16.5 Vol%. Soil atmosphere noble gas composition deviated from
atmospheric composition, i.e. their concentrations increased when O2+CO2 concentrations decreased.
The highest observed increase in noble gas concentrations was 106 % of atmospheric air concentrations.
Based on an actual soil temperature of 12 ◦ C, this would cause an underestimation of temperature by
the currently employed CE model by 1.5 ◦ C.
Zusammenfassung
Die Partialdrücke von Gasen wie Sauerstoff, Kohlendioxid und Stickoxiden in der Bodenluft schwanken
sowohl zeitlich als auch räumlich, angetrieben durch mikrobiologische Aktivität im Boden. Dennoch wird
bei der Rekonstruktion von Paläotemperaturen aus in Grundwasser gelösten Edelgasen angenommen,
dass die Edelgasanteile der Bodenluft identisch mit denen atmosphärischer Luft sind. Diese Annahme
wurde von Hall et al. [2005] in Frage gestellt, um Edelgastemperaturen unterhalb der erwarteten Werte
zu erklären. Hall et al. [2005] schlagen vor, dass der Anstieg der Edelgaspartialdrücke durch ein Defizit
der Summe von O2 und CO2 in der Bodenluft verursacht wird. Dieses Defizit entsteht, wenn mikrobiologische
Prozesse O2 in CO2 umwandeln und das CO2 durch seine hohe Löslichkeit bei Niederschlag aus
der Bodenluft entfernt wird. Um dies zu überprüfen wurden drei permanente Messstellen in Lehmböden
eingerichtet, die eine regelmäßige Beprobung der Bodenluft bis in 6 m Tiefe erlaubten. O2 und CO2
wurden vor Ort gemessen, Proben mit Bodenluft wurden im Labor am Massenspektrometer auf ihre
Edelgaszusammensetzung hin untersucht.
Die Schwankung der O2- und CO2-Konzentrationen in der Bodenluft konnte bestätigt werden, der niedrigste
gemessene Wert der Summe von O2 und CO2 war 16.5 Vol%. Die Edelgaszusammensetzung zeigte
Abweichungen von der atmosphärischen Zusammensetzung: Steigende Edelgaskonzentrationen korrelierten
mit der Abnahme der Summe von O2 und CO2. Die höchste gemessene Edelgaskonzentration
betrug 106 % der atmosphärischen Konzentration. Bei einer Bodentemperatur von 12 ◦ C würde ein derartiger
Anstieg bei dem derzeit verwendeten CE-Modell zu einer Unterschätzung der Temperatur um
1.5 ◦ C führen.

Contents
Abstract 4
Contents 6
1 Introduction 11
2 Theory 15
2.1 Noble gas temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.1 Solubility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.1.2 Noble gas fractions in ground water . . . . . . . . . . . . . . . . . . . . . 17
2.1.3 Excess air modeling approaches . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 Physical processes and properties of soils . . . . . . . . . . . . . . . . . . . . . . . 24
2.2.1 Subsurface thermal regime . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2.2 Soil structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.3 Gas transport processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.3 Soil atmosphere composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3.1 Sources, sinks and profiles of O2 and CO2 . . . . . . . . . . . . . . . . . . 28
2.3.2 Variability of soil respiration . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3.3 Molecular nitrogen and nitrogenous gases . . . . . . . . . . . . . . . . . . 32
2.3.4 Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3 Sampling sites and methods 35
7

CONTENTS CONTENTS
3.1 Setup of the sampling sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.1.1 Drilling and instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.1.2 Locations and soil properties . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.1.3 Development of the sites during the sampling period . . . . . . . . . . . . 39
3.2 Sampling methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.2.1 Noble gas samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.2.2 O2, CO2 and CH4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2.3 Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.2.4 Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4 Measuring methods 43
4.1 Mass spectrometry of He, Ne, Ar, Kr and Xe . . . . . . . . . . . . . . . . . . . . 43
4.1.1 Sample preparation and measuring procedure . . . . . . . . . . . . . . . . 43
4.1.2 Determination of sample gas amount . . . . . . . . . . . . . . . . . . . . . 44
4.1.3 Estimation of relative humidity within the inlet section . . . . . . . . . . 45
4.1.4 Resulting data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.2 On site measurement of O2, CO2, CH4 and Radon . . . . . . . . . . . . . . . . . 46
4.2.1 Geotech BM2000 Biogas Monitor . . . . . . . . . . . . . . . . . . . . . . . 46
4.2.2 Durridge RAD7 Radon Detector . . . . . . . . . . . . . . . . . . . . . . . 47
5 Results 49
5.1 Radon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2 Temperature profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3 O2 and CO2 profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.4 Borehole sealing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.4.1 Site A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5.4.2 Site B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.5 Noble gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
8

CONTENTS CONTENTS
5.5.1 Effects of storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.5.2 Atmospheric air samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5.3 Soil atmosphere samples from Site A . . . . . . . . . . . . . . . . . . . . 60
5.5.4 Soil atmosphere samples from Site B . . . . . . . . . . . . . . . . . . . . 62
6 Discussion 63
7 Summary 71
8 Outlook 73
A Calculations 75
A.1 Gas sample size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
A.1.1 Vapor pressure of water . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
A.1.2 Calculation of sample size using the inlet pressure . . . . . . . . . . . . . 75
A.1.3 Calculation of sample size using the sample tube length . . . . . . . . . . 76
A.2 Mass spectrometer inlet volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
A.3 Fractionation-Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
B Data 79
C Additional plots and figures 89
D Datasheets 107
Bibliography 111
Acknowledegment 117
Deposition 119
9

Chapter 1
Introduction
Understanding the Earth’s climate and the processes affecting it has become very important in
the past decades to comprehend how anthropogenic factors influence the climate. Predictions of
climate change rely on modeling approaches, which in turn require a large data basis of past and
present climate records. Data on climate parameters from direct human records extend only a
few hundred years back into the past at best. It is possible to reconstruct older data by using so
called climate proxies which are essentially physical characteristics of past climate parameters,
stored in natural archives. Various kinds of archives exist, containing paleoclimate tracers of
different type and quality. A few examples are tree rings, ice cores and ocean sediments. The
general concept is that a tracer dependent on a climate parameter, like temperature, precipitation
or CO2 concentrations in atmospheric air to name a few, is embedded into the archive at a
certain time and is ideally conserved, unaffected by any processes afterwards. As such archives
display a chronological structure due to their formation processes, dating of the embedded information
results in a paleoclimate record extending way beyond human recordings. The type of
climate parameter, its accuracy and the chronological range and resolution of the record depend
on the type of tracer and archive.
One of these archives is ground water. The analyzed tracers used to reconstruct paleotemperatures
from ground water are dissolved noble gases. Ground water makes up 30.1 % of the
Earth’s fresh water [Hölting and Coldewey, 2009], found within the Earth’s crust below the vadose
(unsaturated) soil zone. A water permeable ground layer containing ground water is called
an aquifer, while a layer restricting water flow is called aquitard. In an unconfined aquifer, where
the ground layer above the water saturated zone is water-permeable, the water reaches the water
table where the water pressure equals the ambient atmospheric pressure. The shallowest aquifer
in a given soil structure is usually unconfined. A confined aquifer is characterized by an aquitard
layer above the aquifer, restricting upwards movement of the ground water and thereby causing
the water pressure to be higher than the atmospheric pressure at the upper aquifer boundary.
A confined aquifer isolates the stored ground water from interaction with the soil atmosphere of
the overlying vadose zone.
Ground water flow within aquifers is dominated by gravitative forcing, volume flow rates are described
by Darcy’s law (see Hölting and Coldewey [2009] for a detailed description) and depend
11

1 Introduction
on the pressure gradient and a parameter describing the hydraulic conductivity of the given
soil. Flow rates and residence time of water within aquifers therefore vary depending on the
soil’s hydraulic properties an recharge rates. Water in confined aquifers can reach an age of up
to several 10 5 years [Sturchio et al., 2004]. Radiocarbon dating of dissolved inorganic carbon
in ground water is used to provide the age information for up to 50,000 year old water while
different isotopic dating methods have to be used for older ground waters.
Reconstructing paleotemperatures from ground water utilizes the dissolved noble gases neon,
argon, krypton and xenon and requires confined aquifers that limit gas exchange. The idea behind
this paleorecord is the temperature dependency of gas solubility: the infiltrating meteoric
water leading to ground water recharge is in contact with the soil atmosphere before entering
the aquifer. During this contact the gaseous and aqueous phases equilibrate. This equilibration
is dependent on soil temperature and the composition of the soil atmosphere. Due to temperature
damping within the soil, its temperature is closely related to annual mean atmospheric
temperatures [Hillel, 1980]. The standard assumption on soil atmosphere noble gas composition
is that it is close or equal to the atmospheric composition, showing only insignificant
fluctuations [Stute and Schlosser, 1993]. This however neglects the fact that soil atmospheres
greatly vary in O2 and CO2 composition spatially as well as temporally [Yamaguchi et al., 1967;
Dowdell and Smith, 1974; Amundson and Davidson, 1990; Magnusson, 1992]. This likely affects
the partial pressures of its remaining components. These changes in soil air composition are
mainly caused by microbiological activities and are influenced by a multitude of soil properties
like temperature, precipitation, soil hydraulic properties and others in a complex relationship
[Suarez and ˇ Sim˚unek, 1993; Welsch and Hornberger, 2004; Riveros-Iregui et al., 2011]. While
paleotemperature studies have largely neglected this possibility so far and have nonetheless successfully
employed modeling approaches to account for other factors affecting the dissolved noble
gases [Aeschbach-Hertig et al., 1999b; Kipfer et al., 2002; Peeters et al., 2003], studies on young
ground water in recharge areas [Stute and Sonntag, 1992; Ma et al., 2004; Castro et al., 2007]
have led to noble gas temperatures a few degrees below measured soil temperatures. Hall et al.
[2005] proposed that this shift could be caused by a deviation of noble gas partial pressures in
the soil atmosphere from atmospheric values. As the cause for this change they suggest the
process of oxygen depletion, meaning that the O2 removed from the soil atmosphere by microorganisms
is not replaced by an equimolar amount of CO2 produced by these organisms, leading
to a pressure deficit affecting the partial pressures of the remaining gases. While their modeling
approach including the proposed oxygen depletion effect successfully leads to matching noble
gas and mean atmospheric temperatures for their study area, an actual measurement of soil air
composition was not executed to prove oxygen depletion has the suggested effect on noble gas
partial pressures and could indeed be the main factor in causing the noble gas temperature shift.
Extensive research has been done on the composition of soil atmospheres for various reasons,
mainly owing to its importance in agricultural contexts. Modern climate research has also been
interested in soil atmospheres because of their part in the global atmospheric gas balance. Soils
provide both sinks and sources for CO2, CH4, N2O and various other gases relevant to the
Earth’s radiation balance. These studies mainly focused on O2, CO2 and nitrogenous gases and
usually their flux from the soil rather than in situ concentrations. Data on noble gases in the
soil atmospheres relevant to noble gas temperatures is sparse at best, as little research on soil
atmosphere composition focusing on the noble gas components has been done so far. While
12

1 Introduction
Molins and Mayer [2007] have noted a relative enrichment of N2 and Ar partial pressures in
the presence of O2 depletion at an examination of the soil atmosphere at a crude oil spill site,
their study neither did focus on noble gases nor did it contain any soils likely to be relevant
to paleoclimate research. Previous one-time samplings of soil atmospheres focused on noble
gas measurements in the region around Heidelberg (various permanent and singular sampling
sites), executed by Schneider [2010], could in fact not provide any data capable of supporting
the oxygen depletion model.
The objective of this study is to create an annual record of soil atmosphere composition at
various depths and locations, focusing on the stable noble gases He, Ne, Ar, Kr and Xe as well
as O2 and CO2 to confirm or refute the existence of changes in noble gas composition in soil
atmospheres and to quantify the possible annual variation and effect on noble gas temperatures
should such changes occur. Three permanent soil atmosphere sampling sites were created,
allowing for depth profiles to be taken. Noble gas samples were taken over a span of ten months
and the concentrations were measured using mass spectroscopy. O2 and CO2 concentrations
were measured over a span of five months.
13

Chapter 2
Theory
2.1 Noble gas temperatures
The concept of using dissolved noble gases in ground water as tracers for paleotemperature is
based on the observed temperature dependency of gas solubility in water, the mainly atmospherical
source of noble gases in ground water and the chemically inert behavior of noble gases.
Within the relevant temperature interval found at ground water recharge areas the solubility
decreases with increasing temperature, this effect is more distinctive for heavier noble gases.
The main source of all stable noble gases found in meteoric and ground water is the Earth’s
atmosphere. Radiogenic and terrigenic noble gas sources are of little influence, only 3 He, 4 He
and sometimes 40 Ar are influenced by non-atmospheric sources [Kipfer et al., 2002]. Due to this
influence and the small temperature dependance of its solubility, helium is not used for modeling
paleotemperatures.
Finally, the chemical inertness of the stable noble gases ensures the absence of chemical sinks,
making dissolved noble gases a conservative tracer and leading to a preservation of the temperature
information. This requires a confined aquifer however, since depressurization would cause
degassing and thereby loss of the temperature information.
When water from a confined aquifer is sampled and analyzed for its noble gas concentrations,
the resulting noble gas temperatures therefore represent mean annual soil temperatures at the
ground water table of the recharge area. The temporal resolution of the noble gas temperatures
depends on mixing, dispersion and transport processes within the aquifer and the accuracy of
the water sample dating.
The following description of gas solubility and noble gas temperature calculation is largely based
on Kipfer et al. [2002], Aeschbach-Hertig et al. [2008] and Schneider [2010].
15

2.1. Noble gas temperatures 2 Theory
� � � � � � � � � � � �� � � �
Figure 2.1: Temperature dependency of the Ostwald solubility L(T, S = 0) for the noble
gases He, Ne, Ar, Kr and Xe, at atmospheric pressure. Plot data was calculated using the
fit equation and parameters provided by Benson and Krause [1976].
2.1.1 Solubility
The partitioning of gas at the phase boundary between water and air at a constant temperature
is described by Henry’s Law, formulated in 1803 by William Henry:
C g
i = Hi(T, S) · C w i (2.1)
where C g
i and Cw i are the concentrations of gas i in the gas and the water phase respectively.
Hi is the gas specific Henry constant, a dimensionless constant that is a function of temperature
T and salinity S. Influences on Hi by chemical interactions of solutes found in water can be
neglected for meteoric and ground waters [Kipfer et al., 2002]. Since the Henry constant is
dimensionless, its numerical value is defined by the units chosen for the gas concentrations C.
The reciprocal of the Henry constant, called Ostwald solubility L, is a measure of solubility.
Li(T, S) =
1
Hi(T, S) = Cw i
C g
i
The temperature dependency of the solubility is described by a numerical approximation by
fitting measured data to an equation like
ln � Li(T, S = 0) � 1 1
= a0 + a1 + a2
T
16
T 2
(2.2)
(2.3)

2 Theory 2.1. Noble gas temperatures
where T is the temperature in Kelvin, leading to parameters ai as given Table B.1 [Benson and Krause,
1976]. The resulting functions for individual noble gases are shown in Figure 2.1 where the Ostwald
solubility Li(T, S = 0) is plotted versus temperature.
In ground water research it is usually more convenient to work with partial pressures pi of gas
i. As described by Kipfer et al. [2002], using the equilibrium concentration Ci,eq, Henry’s Law
is formulated as
pi = Hi(T, S) · Ci,eq
(2.4)
The partial pressures of noble gases in atmospheric air, based on the assumption that the
atmospheric noble gas composition is constant and usable as a standard [Porcelli et al., 2002],
is calculated from ambient atmospheric pressure ptot:
pi = zi · � ptot − p 0 �
H2O
with the volume fraction zi of the gas i in air (see Table B.3) and the saturated water vapor
pressure p0 H2O as defined in Appendix A.1.1. Local conditions in the recharge area (e.g. elevation)
may require some corrections of the total pressure as well as the equilibrium concentration due
to the atmosphere’s barometric pressure profile:
�
ptot(h) = p0 · exp − h
�
(2.6)
h0
�
ptot(h) − p
Ci,eq(T, S, ptot(h)) = Ci,eq(T, S, p0) ·
0 H2O
p0 − p0 �
(2.7)
H2O
with h being the local height above sea level and h0 the local scale height, typically at around
8000 – 8300 m [Kipfer et al., 2002]. Henry’s Law is then expressed as
Ci,eq(T, S, ptot(h)) = zi · (ptot(h) − pH2O)
Hi(T, S)
describing the gas concentration in water due to atmospheric equilibrium at the local site’s
meteorologic parameters.
2.1.2 Noble gas fractions in ground water
As shown above, noble gases enter the water phase by equilibration with air. In the case
of ground water recharge this equilibration takes place within the vadose zone between the
percolating meteoric water and the local soil atmosphere. The composition and similarity of soil
air compared to atmospheric air is the main objective of this study. Isotopic fractionation occurs
when this equilibration takes place due to mass differences of the different noble gas isotopes.
Benson and Krause [1980] found that the solubility of 3 He and 4 He deviates by up to 1.8 %.
Other studies [Aeschbach-Hertig, 1994; Beyerle et al., 2000] showed similar effects for Ne and
Ar in an order of magnitude of per mil.
The noble gas concentrations found in actual ground waters display additional influences as
shown in Figure 2.2, originating from various other sources which shall be discussed below.
17
(2.5)
(2.8)

2.1. Noble gas temperatures 2 Theory
Figure 2.2: Approximate representation of components of noble gas concentrations usually
found in ground water, standardized to the atmospheric equilibration component. Adapted
from Wieser [2011].
Radiogenic sources
Radioactive decay processes directly and indirectly produce noble gas isotopes. The yields for
all noble gases except He are so low that possible effects on the noble gas concentrations in
ground water can be ignored 1 [Stute, 1989]. The 4 He yield is large enough to influence the 4 He
concentration in ground water as 4 He is produced in α decays of mainly primordial radionuclides
found in the bedrock. The magnitude of this production depends on the bedrock type, as the
specific activity of various rocks differ [Scheffer and Schachtschabel, 2010]. The particle emitted
in α decays ionizes surrounding atoms by capturing electrons and thereby transforms to 4 He
α + 2e − −→ 4 He (2.9)
The term terrigenic noble gas describes radiogenic noble gases produced within the Earth’s soil,
bedrock, mantle and crust. Radiogenic 4 He in ground water is of terrigenic origin, as well as a
fraction of 3 He produced in processes related to the 4 He production [Ballentine and Burnard,
2002]. The part of helium originating from Earth’s mantle is characterized by a 3 He/ 4 He ratio
significantly higher than the ratio associated to crustal 4 He production [Aeschbach-Hertig et al.,
1999a].
1 The argon isotope 40 Ar is produced by the decay of 40 K. With a half-life τ1/2 = 1.25 × 10 9 a, this is only
relevant for very old ground waters.
18

2 Theory 2.1. Noble gas temperatures
The other fraction of 3He in ground water is tritiogenic 3He produced by the β− decay of the
hydrogen isotope tritium:
3 3 −
H −→ He + e + ¯νe
(2.10)
Tritium is produced in the upper lithosphere through a reaction of lithium with cosmogenic
neutrons and in the upper atmosphere through nuclear spallation of nitrogen atoms, induced by
cosmogenic neutrons as well. An anthropogenic fraction was induced into the atmosphere during
the 1960s by atmospheric hydrogen bomb tests. Atmospheric tritium enters the aquifers bound
in water molecules, where its decay leads to a rise in 3 He concentrations. Due to these additional
sources, He is usually not used to calculate noble gas temperatures [Stute et al., 1995].
Excess air
Additionally to the aforementioned additional noble gas sources, ground water noble gas concentrations
usually display a surplus that is air derived. In some cases this surplus is fractionated
relative to atmospheric air with the heavy noble gases more enriched than the lighter
ones [Stute et al., 1995; Aeschbach-Hertig et al., 1999b, 2000]. The origin of this surplus, called
excess air by Heaton and Vogel [1981], lies in gas bubbles caught in the pore space that get
trapped by ground water table fluctuations and are transported into the saturated soil zone.
There, increased hydrostatic pressure causes partial or complete dissolution of the gas into the
ground water. The amount of excess air introduced is highly variable and dependent on the soil
structure of the base of the vadose zone and precipitation patterns [Heaton and Vogel, 1981].
This allows for excess air to be used as proxy for past environmental conditions like water table
fluctuation in arid and semi-arid areas [Aeschbach-Hertig et al., 2002; Beyerle et al., 2003;
Wieser, 2011].
2.1.3 Excess air modeling approaches
Results of measurements of dissolved noble gases in ground waters are total gas concentrations.
As outlined above, the measured total concentrations are the sum of several different mechanisms
that introduce noble gases into the water:
Ci,m = Ci,eq + Ci,ex + Ci,rad + Ci,ter + Ci,tri
(2.11)
where m stands for measured, eq for atmospheric equilibration, ex for excess air, rad for radiogenic,
ter for terrigenic and tri for tritiogenic. This relation can be simplified for certain noble
gas isotopes as several of them ( 20 Ne, 36 Ar and virtually all Kr and Xe isotopes [Kipfer et al.,
2002]) are only influenced by atmospheric equilibrium and excess air. Modeling the excess air
fraction is therefore usually sufficient to calculate noble gas temperatures from measured total
gas concentrations. To describe the effect of excess air on measured noble gas concentrations,
various models were created and applied to ground water records. Some of them will be outlined
below.
The actual separation of components and calculation of noble gas temperatures is done by inverse
modeling, optimizing various model specific free parameters to achieve the best agreement of
19

2.1. Noble gas temperatures 2 Theory
modeled and measured data. The quality of this matching is assessed by using the χ 2 method
that weights the deviation between the measured and the predicted concentrations with the
measurement accuracy σi:
UA, PR and MR model
χ 2 = �
i
�
Ci,m − Cmodel �2 i
σ2 i
(2.12)
The first model created to account for the presence of an excess air component was the unfractionated
air model, or UA model. It is based on the assumption that enclosed air bubbles are
completely dissolved in the water at or below the ground water table, leading to an atmospheric
composition of the excess air component of the noble gas concentration without any signs of
fractionation, as described by
C UA
i = Ci,eq + A · Ci,atm (2.13)
where Ci,atm is the unfractioned excess air component and A is the fraction of air entrapped in
the water volume, a scaling parameter of this model. Using Henry’s law (Equation 2.1), this
relation is expressed as
C UA
i = Ci,eq(1 + A · Hi) (2.14)
This basic assumption of complete dissolution did not prove to be realistic though, as Stute et al.
[1995] showed excess air components in ground water to be enriched in the heavier noble gases.
They introduced a modification of the UA model, called partial re-equilibration model, or PR
model, assuming diffusive gas loss affecting the completely dissolved excess air component. The
mass and temperature dependent diffusion coefficients of the individual noble gases [Jähne et al.,
1987] would then account for the occurring fractionation. Inter-isotopic fractionation effects are
not observed however [Peeters et al., 2003], on which the PR model’s applicability was criticized.
Whether this effect should actually be expected at all to occur in a manner similar to internoble-gas
fractionation has been questioned though [Bourg and Sposito, 2008]. The PR model
can be expressed as [Aeschbach-Hertig et al., 2008]:
�
�
� ��
β
C PR
i
= Ci,eq
1 + A · Hi · exp
−FPR
� Di
DNe
(2.15)
where FPR is a parameter characterizing the amount of excess air loss, Di are the noble gas
diffusion coefficients and 0.5 ≤ β ≤ 1 is a model parameter from gas transfer theory. Since
this single step excess air intrusion and degassing leads to initial Ne excess amounts requiring
unrealistic physical conditions in some studies [Kipfer et al., 2002] and failed to describe certain
noble gas records [Ballentine and Hall, 1999], a variation of the PR model was introduced as the
multi-step partial re-equilibration model, or MR model, by Kipfer et al. [2002]. The MR model
assumes a physically more realistic occurrence of multiple (n) excess air intrusions and degassing
steps, containing the PR model as the special case n = 1:
�
�
� ��
β
C MR
i
= Ci,eq
1 + A · Hi ·
n�
exp
k=1
20
−k · FPR
� Di
DNe
(2.16)

2 Theory 2.1. Noble gas temperatures
Unfractionated excess air (UA)
AEW & air air entrapment complete dissolution
Oxygen depletion (OD)
AEW & O2 depl. air air entrapment complete dissolution
Partial re-equilibration (PR)
AEW & air air entrapment complete dissolution di�usive gas loss
Closed-system equilibration (CE)
Multi-step partial re-equilibration (MR)
AEW & air air entrapment partial dissolution,
equilibration
water-gas separation
Figure 2.3: Schematic illustration of the mechanisms leading to excess air as proposed by
some of the different presented models. Adapted from Wieser [2011].
21

2.1. Noble gas temperatures 2 Theory
CE model
The closed-system equilibration model, or CE model, was formulated by Aeschbach-Hertig et al.
[2002] and tries to explain the noble gas fractionation of the excess air component without
relying on diffusive degassing effects as the PR and MR do. Assuming smaller hydrostatic
pressure increases during ground water table fluctuations, incapable of causing the complete
dissolution of entrapped air bubbles leads to remaining bubbles below the water table. These
bubbles, representing limited gas reservoirs, then equilibrate with the surrounding water leading
to an inter-nobel-gas fractionation caused by the differing solubilities, but not leading to interisotopic
fractionation possibly caused by diffusive processes. A mathematical description can be
formulated as
�
C CE
i
�
1 + A ′
Hi
= Ci,eq ·
1 + BHi
(2.17)
with A ′ being the initial ratio of entrapped air volume to ground water volume and B being
the final ratio of remaining air volume to water volume. This allows for the definition of a
fractionation factor FCE = B/A ′ describing the magnitude of excess air influence, FCE < 1
indicates excess air influence, for FCE = 1 the CE model transforms to the UA model and for
FCE > 1 it describes degassed ground water.
OD and GR model
Studies on recent ground waters by Ma et al. [2004] and Hall et al. [2005] showed that modern
noble gas temperatures showed a systematical underestimation of the mean annual air temperatures
(MAAT) by several degrees Celsius. This prompted Hall et al. [2005] to introduce the oxygen
depletion model, or OD model, providing a different explanation for the excess air component
as it moved away from the assumption of Stute and Schlosser [1993] that equilibration within
the soil takes place between water and atmospherically composed air. While Stute and Schlosser
[1993] were aware of fluctuations in soil atmospheres in O2 and CO2 composition, they estimated
the effect on noble gas partial pressures to be negligible based on Brook et al. [1983], giving an
upper limit of 2 Vol% CO2 in usual soil atmospheres during growing season. A compilation
of worldwide data on soil atmosphere CO2 concentrations by Amundson and Davidson [1990]
shows that CO2 concentrations, while fluctuating strongly, generally increase with depth and
were observed to range between 0.04 and 13.0 Vol%. Hall et al. [2005] argue that biological
processes depleting 2 O2 and producing CO2 (see Section 2.3), combined with CO2 removal from
the soil air due to its high solubility in water may lead to a pressure deficit that is compensated
by rising partial pressures of the remaining gases.
The magnitude of this proposed effect of O2 depletion with an accompanying CO2 deficit on
the noble gas partial pressures is expressed by the parameter POD [Schneider, 2010]: The
parameter 0 ≤ α ≤ 1 describes the degree of O2 depletion, while Z is the amount of O2
given in Vol%, Zatm = 20.9 % [Porcelli et al., 2002]. The amount of O2 in soil air is given by
2 In the context of the OD model, the term oxygen depletion is often used synonymously with a noble gas partial
pressure increase. In this study however, the term shall only denote a decrease in O2 levels without implying
further changes of the soil atmosphere.
22

2 Theory 2.1. Noble gas temperatures
Figure 2.4: Theoretical increase of partial pressures of soil gases other than O2 if O2 depletion
isn’t fully compensated by CO2 increase. The expected realistically relevant interval of
O2+CO2 at the sampled sites is 20.9 – 16.9 Vol%, leading to theoretically expected noble
gas partial pressure increases of up to 5 % relative to atmospheric noble gas partial pressures.
From Schneider [2010].
Zsoil,O2 = α · Zatm. Correspondingly, the partial pressures of the remaining gases Zsoil,i change
by a factor POD = Zsoil,i
, related to Zatm,O2 by
Zatm,i
α · Zatm,O2 + POD · �
Zatm,i = 1 (2.18)
i
For atmospheric air without O2 with �
i Zatm,i = 79.1 % follows
POD =
1 − 0.209 · α
0.791
=⇒ 1 ≤ POD ≤ 1.264 (2.19)
The theoretical maximum increase of the sum of all partial pressures of the remaining gases
i would therefore be 26.4 % as shown in Figure 2.4 though such a scenario, requiring full O2
consumption without any CO2 production (or complete CO2 removal), is hardly realistic. The
previously observed CO2 deficits at one of this study’s sampling sites, resulting from O2 depletion,
reached up to 4 % [Schneider, 2010], leading to a theoretically expected increase of noble
gas partial pressures of around 5 %.
23

2.2. Physical processes and properties of soils 2 Theory
The OD model resembles the UA model in formulation [Aeschbach-Hertig et al., 2008] and can
be incorporated into the existing models:
C OD
i = Ci,eq(POD + A · Hi) (2.20)
A modification of the OD model adding partial re-equilibration at the air-water boundary layer,
the gas diffusion relaxation model, or GR model, was introduced by Sun et al. [2008] to describe
a noble gas record from a Michigan aquifer:
C GR
i
= Ci,eq
�
POD + A · Hi · exp
�
−FGRD β
i
��
(2.21)
where FGR is a parameter that depends on the time taken for the gas transfer as well as on the
length scale of the boundary layer.
Comparing the different models
Sun et al. [2010] showed in a recent comparison of the UA, the CE, the OD and the GR model
that, while the absolute noble gas temperatures deviate between the different models, temperature
differences are reproduced quite consistently by all models. While the accuracy of the fits
achieved by the different models and the respective χ 2 values give an indication of which model
might describe the given dataset best, the decisive criteria which model to employ should be the
physical relevance of the model concepts and of the parameters resulting from the optimization
process. Therefore a more detailed analysis of the processes involved in noble gas dissolution
is called for, like the observation of excess air formation done by Holocher et al. [2002] and
Klump et al. [2007, 2008].
This study’s intention is to test the physical foundation of the OD model’s assumption of increased
noble gas partial pressures in soil atmospheres to better assess the significance of the
good χ 2 values found by Hall et al. [2005] and Castro et al. [2007] using the OD model approach.
2.2 Physical processes and properties of soils
Understanding the soil regime is essential, as it provides the environment in which the components
of meteoric water relevant to noble gas paleoclimatology interact (ideally) for the last
time with the atmosphere before the water enters the aquifer. Both soil temperature and soil
atmosphere composition are related to conditions above the surface, but are not necessarily
identical and therefore an understanding of these relations is required to be able to interpret the
measured noble gas concentrations. The following summary of the soil regime’s properties and
processes is largely based on Scheffer and Schachtschabel [2010].
2.2.1 Subsurface thermal regime
The main heat source dominating the upper soil’s temperature profile is the radiation of the sun.
Geothermal heat flux can generally be neglected for depths relevant to ground water recharge
24

2 Theory 2.2. Physical processes and properties of soils
Temperature [°C]
50
40
30
20
10
0 0
0 4 8 12 16 20 24 J F M A M J J A S O N D
Time [h]
(a) (b)
30
Temperature [°C]
35
25
20
15
10
5
Month
Figure 2.5: Temperature variations in soil regimes. (a) Diurnal variations at different depths
at a loam soil. (b) Annual variation. From Hillel [1980].
as it usually takes place too close to the soil surface to be affected by geothermal heat. Heat
loss from the soil is caused by emission of infrared radiation from the soil and evaporation.
The driving force of conductive and convective heat transfer within the soil are up- and downward
temperature and pressure gradients. Convective heat transfer is usually mediated by the
movement of liquid water and water vapor through the soil structure. The importance of water
in the soil thermal regime is also visible in the fact that dry soils heat up more quickly and
to a higher temperature than wet soils, as water acts damping on heat transfer due to its high
heat capacity compared to air [Scheffer and Schachtschabel, 2010; Wieser, 2011]. Infiltrating
meteoric water does, aside from convectively introducing heat, cause significant temperature
changes depending on initial water content of the soil due to release of thermal energy during
adsorption, called heat of wetting [Prunty and Bell, 2005].
However, as a rough approximation, the soil temperature at a certain depth can be described as
oscillating sinusoidally around an average value, driven by atmospheric temperature changes (see
Figure 2.5). Sinusoidal approximation of the soil temperature as a function of depth and time
T (z, t) with the boundary conditions T (0, t) = ¯ T + A0 sin ωt and T (z = ∞, t) = ¯ T , with z = 0
being the soil surface and ¯ T the diurnal average surface temperature, leads to the introduction
of a damping depth d and a phase shift −z/d [Hillel, 1980]:
T (z, t) = ¯ �
T + A0 · exp − z
� �
· sin ωt −
d
z
�
(2.22)
d
The damping depth d is related to the thermal properties of the soil and is therefore individual
for any given soil regime. While the inclusion of the annual temperature fluctuations complicates
the situation, the basic characterization of soil temperature at fixed depths following a harmonic
oscillation around an average value as a crude description of soil temperature regimes remains
viable. An detailed description of temperature modeling is given by Saito and ˇ Sim˚unek [2009].
25

2.2. Physical processes and properties of soils 2 Theory
The temperatures calculated from dissolved noble gases in ground water ideally represent the
mean annual air temperature of the infiltration region. Yet this is not necessarily the case, as
the previously described propagation of heat within the soil is modulated by various mechanisms
leading to a decoupling of MAAT and mean annual soil temperatures. Some of these mechanisms
are meteorological and biological influences like cloud cover, precipitation, evaporation and
changes in albedo due to snow cover and vegetation and thereby affect the soil temperature
regime on various spatial and time scales.
Soil temperatures are also indirectly affecting noble gas temperatures as they do influence the
magnitude of microbiological activity within the soil [Ratkowsky et al., 1982], thereby modulating
the soil atmosphere composition in regard to O2 and CO2 [Fang and Moncrieff, 1999;
Howard and Howard, 1993], and possibly the noble gas partial pressures.
2.2.2 Soil structure
Air space within the soil matrix is defined by the available pore space, which is dependent on the
type of soil, its deposition as well as grain size and type. The porosity of a soil gives the fraction
of pore space volume in the total soil volume. Scheffer and Schachtschabel [2010] estimate the
porosity of silts as 55 – 30 % and that of clays as 65 – 35 %.
Since soils always contain a certain amount of water, even in arid climates, the pore space
available to gases within the vadose (unsaturated) zone is limited by the water content. Water
within the soil can be divided into two fractions, one being connate water that is held against
gravity by adsorption and capillary forces, filling the smaller pores. The other fraction is seeping
water moving downwards by gravitative forcing [Hölting and Coldewey, 2009].
The resulting available air space at maximum field capacity 3 for clay soils is given as 10 – 25 %
by Scheffer and Schachtschabel [2010], it is usually higher though since the water content of
maximum field capacity is rarely realized.
2.2.3 Gas transport processes
Convective mass transport of gases within the soil requires pressure gradients as the driving force,
like changes in barometric pressure or temperature. As shown above, anaerobic production of
methane is able to produce such high amounts of additional gas that convective transport of
CH4 towards the soil surface occurs. During rapid infiltration, water can displace gas from small
pore spaces, leading to fast convective degassing of air [Liu et al., 2002], as well as transport
of dissolved gas. Fluctuations of the ground water table also induce convective gas transport.
However, the sum of these effects is of little relevance, Amundson and Davidson [1990] estimate
that less than 10 % of the total loss of CO2 from soils are caused by convective mass transport.
Diffusive gas transport requires only partial pressure (concentration) gradients instead of total
pressure gradients as a driving force and is therefore much more prevalent than convective mass
3 Measure of soil water content that is retained against gravitative drainage [Hölting and Coldewey, 2009].
26

2 Theory 2.2. Physical processes and properties of soils
Di�usion coe�. D S [cm2 s-1]
0.015
0.010
0.005
Sand
Clay
Silt
waterlogged soils
0 5 10 15 20 25
Air content n [%]
Figure 2.6: CO2 diffusion coefficient DS of various soils in relation to their air content nA.
From Richter and Großgebauer [1978].
transport. The limiting factor of diffusive transport in the soil is its water content since diffusion
within water is 10 −4 times smaller than in air. Water mass and distribution within the pore
space therefore has a large influence on the diffusion dynamics, as shown in Figure 2.6. Diffusive
transport in a stationary system is described by Fick’s first law:
dc
I = −DS
dx
A
(2.23)
where I is the flow of gas in units of mol s −1 cm −2 , dc/dx is the concentration gradient and
DS is the diffusion coefficient of the respective gas in the soil, in units of cm 2 s −1 . Changes in
concentration C due to this diffusive flow are accounted for by using Fick’s second law, describing
a non-stationary situation:
∂C
∂t
∂
= DS
2C ∂x2 (2.24)
Because of the interaction of the gas molecules with the medium in which they are moving,
the diffusion coefficient is not only dependent on the molecule size but on various other factors.
These factors are accounted for by defining the diffusion coefficient in soil DS by weighting the
diffusion coefficient of air DA with the available air filled pore space nA and the turtuosity τ,
which is an approximation of the influence of geometric structure of the pore space on diffusion:
DS = − 1
τ · nA · DA
(2.25)
Various properties of the soil can therefore inhibit diffusive flow, most importantly the amount
and spatial distribution of water within the soil matrix as well as its structure.
27

2.3. Soil atmosphere composition 2 Theory
2.3 Soil atmosphere composition
2.3.1 Sources, sinks and profiles of O2 and CO2
The most important subsurface source of CO2 and sink of O2 is soil respiration, which summarizes
the production of CO2 caused by root respiration and microbiological processes. How
important each process is in a given soil is hard to estimate and varies with many parameters.
Usually the fraction of CO2 production caused by root respiration is given as ranging from 0
– 50 % [Amundson and Davidson, 1990; Scheffer and Schachtschabel, 2010]. Tang et al. [2005]
give an annual mean of 44 % and a growing season average of 56 % in a forest soil.
In the presence of O2, CO2 is produced by aerobic bacteria gaining energy from the decomposition
of glucose:
C6H12O6 + 6 O2 −→ 6 CO2 + 6 H2O + 2800 kJ/mol (2.26)
This reaction produces equimolar amounts of gas and therefore does not influence the partial
pressure equilibrium of the soil atmosphere directly as the sum of O2 and CO2 should still be
20.9 Vol%. The produced CO2 has a much higher solubility in water than O2, leading to a
reduction of CO2 partial pressure. In acidic soils (pH < 5) this removal of CO2 from the gaseous
phase is generally described by the following equilibrium reaction [Yamaguchi et al., 1967]:
CO2(g) + H2O ⇋ H2CO3 ⇋ HCO − 3 + H+ ⇋ CO 2−
3
+ 2 H+
(2.27)
Oxygen depletion by microbial activity can therefore lead to a deficit in partial pressure, which
is the basis for the proposed OD model presented in Section 2.1.3.
When O2 is not available (close to the water table or under waterlogged conditions), anaerobic
instead of aerobic bacteria flourish, leading to different carbohydrate decomposition processes.
In the absence of O2 the oxidation of glucose
C6H12O6 −→ 2 CH3 CO COOH + 4 H + + 4 e −
(2.28)
requires a matching reduction reaction to be provided by the microorganism, leading to various
possible reactions [Rowell, 1997] such as denitrification or the production of methane:
2 NO − 3 + 12 H+ + 10 e − −→ N2 + 6 H2O (2.29)
CO2 + 8 H + + 8 e − −→ CH4 + 2 H2O (2.30)
Another anaerobic process is given by Scheffer and Schachtschabel [2010] as
C6H12O6 −→ 3 CO2 + 3 CH4 + 188 kJ/mol (2.31)
Anaerobic processes are mostly non-equimolar regarding the gas phase, leading to an increase of
gas concentration and therefore a partial pressure gradient. In the case of waterlogged marshes
this can cause significant flow and emissions of CH4 from the soil.
In general, microbial activity reduces the amount of O2 in the soil and increases the amount of
CO2, CH4 and of some nitrogenous gases. The main source for O2 is the atmosphere, resulting in
28

2 Theory 2.3. Soil atmosphere composition
Gas concentrations [%]
Depth [cm]
0
10
20
30
40
CO2 production [mg m-2 cm-1 h-1]
10 20
30 40 50 60
Autumn day
Summer day
Figure 2.7: Depth dependency of the production of CO2 in a loess luvisol soil. From
Richter and Großgebauer [1978].
20
15
10
5
0
30 cm depth
O2
CO2
Mar Jun
Sep Dec
20
15
10
5
0
90 cm depth
O2
CO2
Mar Jun Sep Dec
Figure 2.8: O2 and CO2 concentrations of soil atmospheres at 30 and 90 cm depth.
The dotted line indicates a sandy silt while the solid line represents a silty clay. From
Boynton and Compton [1944].
29

2.3. Soil atmosphere composition 2 Theory
Depth [m]
0.0
0
0.2 0.4 0.6 0.8
1
2
Jan.
Feb.
Mar.
Apr.
CO2 concentration [Vol%]
0.0 0.2 0.4 0.6 0.8
May
Jun.
Jul.
Aug.
0.0 0.2 0.4 0.6 0.8
Sep.
Oct.
Nov.
Dec.
Figure 2.9: Monthly averaged CO2 concentration in relation to depth and its seasonal development
at a mountain forest site in Japan. From Hamada and Tanaka [2001].
decreasing O2 concentrations within the soil with increasing depth, starting at the atmospheric
20.9 Vol%. The main source of CO2 lies within the soil, its spatial distribution and strength
dependent on microbial diversity, organic nutrient reservoirs and temperature. The highest
CO2 production takes place within the first 10 – 50 cm of soil during growing season, as shown
in Figure 2.7. This corresponds to the fact that microbial biomass is one to two orders of
magnitude higher close to the surface than at 2 m depth and is likely caused by the availability
of nutrients [Fierer et al., 2003]. The main sink of CO2 is the atmosphere. CO2 concentrations
in soil atmospheres were observed to reach up to 13.0 Vol% [Amundson and Davidson, 1990],
in laboratory experiments on soil columns even up to 17.0 Vol% [Yamaguchi et al., 1967]. Due
to the production zone located close to the surface, diffusive transport of CO2 exists directed
both into the atmosphere as well as into deeper soil during spring and early summer, leading to
increased CO2 concentrations there. The diffusive flow within the deeper soil regions changes
direction in late summer and winter when microbial activity ceases. The CO2 concentration
profile therefore fluctuates heavily on diurnal as well as annual scales and is closely related to
the O2 concentrations, as shown in Figures 2.8 and 2.9.
30

2 Theory 2.3. Soil atmosphere composition
Respiration rate K [g CO2 m-2 d-1]
8
6
4
2
0
0
Jan
Mar Apr
Feb
Dec
Nov
5 10
K0 = 1.2
May
Oct
Aug
Jun
K0 = 0.9
average soil temperature at 10 cm depth [°C]
Figure 2.10: Relation between average soil temperature and daily respiration rate K of CO2
from a fallow soil. From Rowell [1997].
2.3.2 Variability of soil respiration
The dynamics of subsurface CO2 concentration can be described for modeling purposes as by
Riveros-Iregui et al. [2011] based on production terms stemming from autotrophic (root respiration
by carbon fixating organisms) and heterotrophic (mircobiotic organisms relying on the
availability of organic carbon) activities and a diffusive transport term:
∂CCO2
nA
∂t
= − ∂
∂z
�
DS
∂CCO2
∂z
15
Sep
Jul
20
4
3
2
1
0
Respiration rate K [10-3 m3 CO2 m-2 d-1]
�
+ γA(B, P AR, Θ) + γH(M, TS, Θ) (2.32)
where γA describes the autotrophic and γH the heterotrophic component. B parameterizes root
biomass, P AR is photosynthetically active radiation, M is soil organic matter, Θ is soil water
content and TS is soil temperature.
The driving force of soil respiration is microbial activity, which is highly dependent on soil
temperatures. The temperature dependency of the rates K of most chemical and biological
reactions is calculated by using the Arrhenius equation
�
K = K0 · exp − E
�
(2.33)
RT
31

2.3. Soil atmosphere composition 2 Theory
where K0 is a reaction specific constant, E the reaction specific activation energy and R the
universal gas constant. However, due to denaturation of essential proteins at high temperatures,
this approximation is only valid over a limited temperature interval. Winkler et al. [1996] found
that respiration rates of CO2 from soils generally followed the exponential predictions of the
Arrhenius equation between soil temperatures of 4 – 38 ◦ C, see also Figure 2.10. The Q10 value
describes the increase of respiration rate per 10 ◦ C and was found to be between 1.7 – 1.9,
decreasing linearly with increasing temperature. This means that for every 10 ◦ C increase in soil
temperature within the 4 – 38 ◦ C range, the soil respiration would nearly double, if not limited
by other parameters.
This is the reason temperature dependency is the primary controlling factor on soil respiration,
introducing an annual variability. Temperature also influences the diurnal cycle of CO2
production, however under certain conditions (high soil water content, production larger than
transport) this influence can be quite complicated, resulting in a hysteresis between production
rate and temperature [Riveros-Iregui et al., 2007].
Soil water content becomes the controlling factor of CO2 production and concentrations when soil
temperatures are ideal during spring and summer [Buyanovsky and Wagner, 1983; Yuste et al.,
2003] as high water availability enhances the biological activity and inhibits diffusive transport.
The lack of water reduces microbial activity, the more prolonged a drought, the greater the
adverse effect on size and functionality of microbial life within the soil [Schimel et al., 1999].
Both field [Liu et al., 2002; Tang et al., 2005] as well as laboratory [Orchard and Cook, 1983]
experiments showed a rapid and strong response of CO2 production after the rewetting of dry
soils.
Smaller, but still notable modulations of soil respiration are caused by soil type, nutrient availability
and vegetation above ground [Buyanovsky and Wagner, 1983] to name a few.
2.3.3 Molecular nitrogen and nitrogenous gases
Molecular nitrogen (N2) is a major component of soil air, as it is also the most abundant gas in
atmospheric air. Within the soil regime, N2 is influenced by a complex system of processes both
consuming as well as producing N2 and nitrogenous gases. Under aerobic conditions nitrification
takes place, producing nitric oxide NO and nitrous oxide N2O. Under anaerobic conditions, N2
an N2O are produced by denitrification [Nieder and Benbi, 2008].
While rarely measured in studies of soil atmosphere composition, Magnusson [1994] found N2
concentrations to fluctuate between 78 – 95 % in water saturated soils, where CO2 is removed
from the soil atmosphere by dissolution in water. Based on its high abundance and the existence
of a subsurface source additional to the atmospheric reservoir it shares with the noble gases,
N2 was speculated to be able to restore equilibrium conditions when O2 depletion and CO2
dissolution lead to a partial pressure deficit in the soil atmosphere by Schneider [2010].
32

2 Theory 2.3. Soil atmosphere composition
2.3.4 Radon
Even though it is a nobel gas, radon is irrelevant to noble gas paleotemperature studies as all
of its isotopes are radioactive and therefore not conserved in ground water.
222 Rn is produced within the soil as a member of the radioactive decay chain of 238 U, 220 Rn
within the 232 Th decay chain. The source strength for radon isotopes is dependent on the
uranium and thorium concentrations of the given soil and will therefore fluctuate depending on
the soil constituent’s chemical composition and their spatial allocation.
Since atmospheric radon concentrations are negligible [Porcelli et al., 2002], 222 Rn and 220 Rn
are used as tracers to mark the soil atmosphere origin of sampled air, as is being done in this
study.
33

Chapter 3
Sampling sites and methods
3.1 Setup of the sampling sites
The sampling sites were chosen based on preliminary data by Schneider [2010] suggesting high
probabilities of oxygen depletion, thereby being well suited to study whether oxygen depletion
has any influence on noble gas partial pressures. Additionally, all sampling sites are in a reasonably
close proximity to the Institute of Environmental Physics’ weather station as well as a
weather station owned by the company meteomedia.
3.1.1 Drilling and instrumentation
Drilling the sample sites was done using a pneumatic pile hammer driven by a gas compressor.
The pneumatic hammer was used to drive a hollow rod of 6 cm diameter and 1 m length into
the ground, allowing for 1 m long, partly compressed core samples to be extracted, from which
the soil layer structures were deduced. Using 1 m long solid extension rods the maximum depth
reachable with the rented equipment was 9 m, however the maximum achieved depth was 5.9 m
at Site A, 4.9 m at Site B and 2.9 m at Site C due to increasing friction at larger depths.
Ground water tables were not reached at any of the sites. For simplification all soil air sampling
depths are hereafter referred to by values rounded to the full meter.
Sampling equipment, consisting of three bundled TYGON R○ R-3603 Vacuum Tubing tubes of
different lengths and two LogTag TREX-8 temperature sensors, was lowered into the boreholes.
The tubes have an inner diameter of 8 mm and were closed at their tips and perforated over a
length of 10 cm by holes of 1 mm diameter (see Figure C.1). At 15 cm depth the tubes and sensor
cables ran horizontally into an underground box which was placed at a distance of about 20 cm
to the hole, with a footprint of 0.03 m 2 , minimally disturbing the immediate site surroundings.
The boxes were covered by removable grass sods and contained one LogTag TRIX-8 and two
LogTag TREX-8 temperature data loggers as well as connectors and valves to access the different
depth tubes. The sampling tubes were bundled into a single access tube, but remained isolated
from each other by valves, preventing contamination by backflow of atmospheric air.
35

3.1. Setup of the sampling sites 3 Sampling sites and methods
Figure 3.1: Equipment box at Site B before burying, with sampling tubes and temperature
sensor cables running to the open borehole at the left.
The instrumented boreholes were refilled with the excavated material from the respective sites,
mixed with water for better fluidity. The sample sites were drilled and refilled between 19 th and
21 st of June, 2010. First samples were taken one month later to allow for the refilled material
to settle down and solidify. Interconnectivity between the different depths through the refilled
borehole was tested for by measuring Radon profiles preceding each noble gas sampling. See
Section 5.1 for a detailed discussion of the results.
3.1.2 Locations and soil properties
Site A
Sampling Site A (see Figure C.2) was located a few meters north of the Institute of Environmental
Physics, at the coordinates N49 ◦ 25.050 ′′ E8 ◦ 40.496 ′′ at 112 m above sea level, see Figure
3.2. The borehole sits within an area of about 50 m 2 of lawn. To the east and south the ground
is sealed by paved roads, each at a distance of about 5 m to the site. Southeast, at a distance of
1.5 m to the borehole, grows a single tree.
The soil at the site predominantly consists of clay. The upper layers are most likely of an artificial
origin, as they were created or at least partly disturbed in 1998 when the Institute was
built. The first 10 cm of turf are followed by 20 – 30 cm of clay, a 10 cm thin layer of a mixture
36

3 Sampling sites and methods 3.1. Setup of the sampling sites
SITE B
SITE A
SITE C
Figure 3.2: Location of the sites created and sampled for this study [Source: Google Maps,
map data provided by Tele Atlas].
of sand and gravel and another layer of about 450 cm of clay (see Figure 3.3). Below a depth of
5 m the ground primarily consists of sand and gravel.
The site was equipped with three soil air sampling tubes, the inlet screens located at depths 6 m,
4 m and 2 m. Temperature sensors were installed at 2.5 m, 1.0 m and 0.1 m, the latter located
inside the buried equipment box.
Site B
Sampling Site B (see Figures 3.4 and C.3) was located in an agricultural environment near
Handschuhsheim, at the coordinates N49 ◦ 25.775 ′′ E8 ◦ 39.760 ′′ at 109 m above sea level, see Figure
3.2. The borehole was placed very close to the end of a hedge, partly covered by its leaves. A
paved road of approximately 2 m width runs from north to south, at a distance of 1.5 m to the
borehole. The immediate surrounding consists of a small meadow with apple trees, enclosed by
agriculturally used land.
The soil at the site consists predominantly of clay as well: The first 5 cm of turf are followed by
320 cm of clay, increasingly humid with depth. The following layer consisted of 25 cm of humid,
sandy clay. Below 3.5 m the clay displays a reddish gravel fraction.
37

3.1. Setup of the sampling sites 3 Sampling sites and methods
Figure 3.3: Detailed view of a core sample from a depth of 2 m at Site A, showing the soil’s
dense clay composition.
The site is equipped with three soil air sampling tubes, at depths 5 m, 3 m and 2 m. Temperature
sensors are installed at 2.5 m, 1.0 m and 0.1 m, the latter located inside the buried equipment
box.
Site C
Sampling Site C is located within an orchard on a hill slope above Dossenheim, at the coordinates
N49 ◦ 26.698 ′′ E8 ◦ 40.806 ′′ at 136 m above sea level, see Figure 3.2. The borehole was placed
on ivy-covered but otherwise bare ground, sloped to the west.
The soil at the site consists solely of clay down to the maximum depth of 3 m, a turf layer was
not discernible at this site.
The site is equipped with three soil air sampling tubes, at depths 3 m, 2 m and 1 m. No temperature
sensors were installed.
38

3 Sampling sites and methods 3.1. Setup of the sampling sites
3.1.3 Development of the sites during the sampling period
Site A
The radon measurements at Site A suggest that atmospheric sealing of the borehole was maintained
during the entire sampling period from late August 2010 to May 2011. However, continuous
O2 and CO2 measurements in May 2011, exceeding 10 minutes, showed a change in
air composition after 200 seconds at 2 m depth. For a more detailed discussion of the borehole
sealing quality see Section 5.4.1.
The extensive and unusual dry period during spring 2011 (Table B.8 and Figure C.9) led to the
decision to artificially irrigate Site A in May 2011. Between May 9 th and May 13 th , the site was
irrigated four times. The amount of water was estimated to be similar to 30 mm of precipitation
per irrigation event. It was artificially created by irrigating an area with a radius of 3 m around
the borehole with tap water over one hour. A fifth irrigation of 30 minutes length was done on
May 18 th , leading to about 15 mm of artificial precipitation.
The water was sprayed to emulate a natural rain event as accurately as possible, the amount
of 30 mm/h is comparable with heavy rain [Baumgartner, 1996]. If evaporation during spraying
and horizontal spreading of the water within the soil into the surrounding dry soil is accounted
for, this value likely represents a generous upper limit estimate.
During the irrigation period O2 and CO2 measurements as well as noble gas samples were taken
at an increased rate (Sample IDs A17 to A23), documenting the effect of the increased abundance
of water within the soil. Site A represents the largest and most detailed set of samples taken
during this study.
Site B
Site B was sampled regularly throughout the sampling period with at least one sample per
month. However, the radon data suggests problems with the borehole sealing in November
2010 and from April 2011 onward, see Section 5.4.2 for a detailed discussion of sealing quality
of this particular site. While noble gas samples were taken during the entire sampling time,
measurement of most of the samples taken during the time of verified atmospheric contamination
had low priority due to limitations in measuring time on the mass spectrometer. Therefore most
of the noble gas samples taken in 2011 were not evaluated and remain in storage at the time
this thesis is finished.
Site C
The sampling Site C was abandoned after problems had arisen early on caused by heavy rainfalls
the day before the first sampling attempt (August 2010, sample ID C01). The precipitation
created a water saturated layer in the soil. While pumping from the depths 1 m and 3 m led to
normal airflow, pumping at a depth of 2 m caused highly liquid sludge to be transported up the
39

3.2. Sampling methods 3 Sampling sites and methods
sampling tube. Sampling was interrupted and could not be continued at this depth until the
end of September 2010 (Sample ID C04). Additionally, several extractions of Site C samples
within the mass spectrometer failed due to mechanical damage to the sample sealing and led
to an even more incomplete record. Sporadic sampling during winter and limited access to the
mass spectrometer led to the site finally being omitted from sampling. Furthermore, an O2 and
CO2 measurement in May 2011 proved this site to suffer from atmospheric air contamination in
all three depths as well.
3.2 Sampling methods
Gas samples were extracted from the sites by attaching a Durridge RAD7 Radon Detector as
a pump to the buried sampling tubes via the connector tube inside the equipment boxes. The
perforated tips of the sampling tubes allow for soil air to be sampled from a screen of 10 cm height,
however the actual ground layer being sampled was probably larger. The RAD7 -pump has a
nominal maximum pump rate of 1 l/min, measurements of the pump rate resulted in an actual
maximum pump rate of only 0.45 l/min though [T. Reichel, personal note]. Pressures during
sample pumping were seldom more than 10 mbar below local atmospheric pressure, indicating
low resistance allowing the pump to reach its actual maximum pump rate. Each sampling depth
was pumped for 30 minutes before the actual noble gas sample was taken. The samples A17
to A23 were taken using the Geotech BM2000 Biogas Monitor pump instead of the RAD7 ’s,
omitting accompanying Radon measurements but leading to reduced pump times per sample of
approximately 2 min instead of 30 min 1 . The air within the largest occurring dead space (the 6 m
sampling tube at Site A) is moved away within the first 1.5 minutes of pumping at a pump rate
of 0.5 l/min. As Figure C.6 shows, O2 and CO2 measurements reached stable reading within the
first 60 seconds of pumping with the BM2000. Scheffer and Schachtschabel [2010] gives a range
of 65 – 35 % for pore space fraction of clay soils, assuming a worst case of 35 % leads to an upper
estimate of evacuated soil volume (at 0.5 l/min pump rate and 30 min of pumping) of 0.043 m 3
per sampling depth. Assuming ideally homogenous soil structure leading to an isotropic, circular
air inflow, this would correspond to an sampling radius of 22 cm.
Therefore the depth accuracies for noble gas, O2 and CO2 measurements are given as ±0.2 m
assuming intact sealing, while the depth uncertainties for the temperature data should not
exceed ±0.1 m.
3.2.1 Noble gas samples
The soil air was pumped through a 6x1 mm tube made of deoxidized copper (Wieland cuprofrio R○
Cu-DHP), see Figure C.4. After 30 minutes of pumping, the pump-ward end of the copper tube
was squeezed shut airtight [Wieser, 2006] using a pneumatic plier. Pressure was measured
inline after closing the pump-ward end of the copper tube: once the connection to the pump
1 Pump rates for the BM2000 were specified by the manufacturer as approximately 0.5 l/min. Comparison of
the achieved pumping pressures of the RAD7 and the BM2000 during sampling led to the conclusion that the
BM2000 ’s pump rate is likely higher than specified and lies somewhere in the range of 0.5 to 1.0 l/min.
40

3 Sampling sites and methods 3.2. Sampling methods
Figure 3.4: Typical sampling setup using the RAD7 as a pump, picturing Site B. (a)
Location of the refilled borehole. (b) Equipment box with access valves to the different
sampling screens and containing the LogTag dataloggers. (c) Inline pressure measurement
installed between borehole and sample tube. (d) O2 and CO2 measuring device installed
between borehole and sample tube. (e) Copper sample tube and temperature sensor. (f)
Drierite desiccant tube and RAD7 radon monitor.
was separated the inline pressure rose from the slightly lower pumping pressure to a value
corresponding to the current atmospheric pressure. Therefore all sampling tubes contain gas at
atmospheric pressure. From there the copper tube was divided into three parts of roughly the
same length, resulting in three samples per depth and sampling event. Sampling was always
done from top to bottom, starting with the shallowest available depth. The copper tubes were
marked by carving in the IDs rather than marking them with tape or a pen, to ensure minimal
contamination when installed in the mass spectrometer. The sample ID consists of the site name
(A, B or C), the two digit successive number of the sampling event and the depth given in roman
numerals, ascending with depth (at Site A, I, II and III referred to 2 m, IV, V and VI to 4 m
and VII, VIII and IX to 6 m). The ID A04-V therefore refers to a sample taken at Site B on
the fourth sampling event of that site, at a depth of 4 m.
The sample tube length was increased from ∼6 cm to ∼12 cm (corresponding to a volume of
∼0.7 cc and ∼1.5 cc) after the first batch of samples was analyzed in the mass spectrometer
showing that the amount of 84 Kr in the small samples was technically impractical for the utilized
mass spectrometer preparation line. Samples A01 – A08, B01 – B07 and C01 – C05 are of small
size, all other samples are of the larger variant.
41

3.2. Sampling methods 3 Sampling sites and methods
Over 350 noble gas samples were taken during the sampling period, 118 of which were successfully
evaluated in the mass spectrometer. The remaining samples either proved leaky or were not
analyzed in the mass spectrometer due to time constraints.
3.2.2 O2, CO2 and CH4
O2, CO2 and CH4 were measured on site using a Geotech BM2000 Biogas Monitor with a
built-in pump. Unfortunately the device was available only as of February 2011, leaving noble
gas samples A01 – A10, B01 – B09 and C01 – C05 without corresponding O2, CO2 and CH4
measurements.
The BM2000 was connected to the sampling tube parallel to the RAD7, measurements were
taken during the first two minutes as well as during the last ten minutes of the 30 minute
pumping period at each depth. Since variations between the two measurements never exceeded
the nominal accuracy of the sensors, the data from the last 10 minutes of pumping was used for
its closer proximity to the noble gas sample.
3.2.3 Radon
A Durridge RAD7 Radon Detector was used as the primary sampling pump as well as for
measuring 222 Rn and 220 Rn concentrations, given in Bq/m 3 . The RAD7 was set up behind the
noble gas sampling tubes and shielded from humidity by a Drierite desiccant tube. The RAD7
was set for three 10 minute cycles, only 222 Rn values from the last cycle were used.
3.2.4 Temperatures
Atmospheric ambient temperatures at 2 m height above ground were provided by a weather
station run by meteomedia close to Site A. The sampling sites were equipped each with LogTag
TREX-8 and TRIX-8 data loggers (see Figure C.5), the latter featuring build-in resistive temperature
sensors, the former attached to external resistive temperature sensors. The loggers were
set to record the temperature at an hourly interval. Accuracy of the sensors between −10 ◦ C
and +40 ◦ C is according to the specifications (see Datasheet D.2) ±0.5 ◦ C. While the TRIX-8
was placed inside the instrumentation box shielded from moisture (but also from fast temperature
changes due to the insulating air), none of the external sensors attached to the TREX-8 s
were rated for deployment in moist to wet surroundings. They were therefore insulated using
shrink-sleeves with glue and tested in water beforehand. Testing showed that moisture intrusion
leads to temporary offsets in temperature readings rather than complete failure.
42

Chapter 4
Measuring methods
4.1 Mass spectrometry of He, Ne, Ar, Kr and Xe
Measurements of He, Ne, Ar, Kr and Xe were conducted using a GV Instruments MM5400
mass spectrometer and a preparation line built and set up by Friedrich [2007]. The samples
were measured in four distinct runs, the first three during September to November 2010 and the
last one in May 2011. The first three runs utilized the same setup and sample size, while some
changes were made for the fourth run, including a slightly different inlet setup, different sample
size and modified measuring processes for He, Ar, Kr and Xe.
4.1.1 Sample preparation and measuring procedure
The copper sample tubes were installed in an inlet volume of known size which was evacuated
to less than 5.0 × 10 −6 mbar. The process of installing the sample tubes inside the inlet was
responsible for most sample losses since mechanical stress had to be exerted on the fragile sealing
before the surrounding volume was evacuated. The sample was vented into the evacuated inlet
volume by applying pressure perpendicular to one of the pinch points using a modified valve,
thereby cracking the sealing and releasing the gas into the inlet volume almost instantaneously.
In rare cases the cracking was so minute that the venting happened slowly over a timespan of 3
to 10 minutes.
After taking a pressure reading of the gas inside the inlet volume, the gas was transferred to
the preparation line where gas separation was done: The different noble gases cannot be measured
side by side in a single step but have to be separated. This is due to the differences
in concentration magnitudes as well as to prevent interference effects: The mass spectrometer
discriminates mass-to-charge ratios, therefore a twice ionized 40 Ar atom will provide the same
result as a single-ionized 20 Ne atom. The gas separation was realized by an adsorption refrigeration
system, adsorbing the noble gases Ar, Kr and Xe, as well as all other permanent gases, at
25 K in a permanent gas trap while He and Ne were adsorbed at temperatures below 12 K in an
activated carbon reservoir. The gases were then released separately through incremental heating
43

4.1. Mass spectrometry of He, Ne, Ar, Kr and Xe 4 Measuring methods
to their respective desorption temperatures. Depending on the gas amounts present within a
sample, a splitting step is required and was initiated if a specified limit was exceeded. This was
determined after separation using a quadrupole mass spectrometer to estimate the abundances
of each noble gas.
The gases were detected using a Faraday cup ( 4 He, 20 Ne, 22 Ne, 36 Ar, 40 Ar) and an electron
multiplier ( 3 He, 84 Kr, 132 Xe). A specified volume of gas (atmospheric air of known noble gas
composition) was measured at least once a day as a calibration standard and to characterize the
long term stability of the measurement process, short term variations were characterized by fast
calibrations executed before every sample measurement, using pure He, Ne and Kr-Xe gases.
4.1.2 Determination of sample gas amount
The amount of gas inside a sample tube was calculated using two different methods, both based
on the ideal gas law but relying on independently measured parameters. The first method
utilizes the empirical formula A.6 created by Wieser [2006] that relates the sample tube length
(at its closed state with squeezed ends) to its volume. The inline pressure during sample shutoff
and ambient temperature were measured during sampling. This method isn’t very accurate
though since both volume calculation and temperature measurement are prone to large errors,
resulting in relative errors in gas amount of 2.5 – 4.5 %. Details of the calculation can be found
in equation A.5.
The second method uses the gas pressure inside the inlet volume pinlet of the mass spectrometer,
as well as the laboratory temperature TLab after expanding the gas sample into the evacuated
inlet volume. The inlet pressure was measured using a Keller Lex 1 pressure gauge with a
nominal accuracy of 0.5 mbar (Datasheet D.3). The inlet volume was calculated from volumetric
measurements, by expanding air at known pressure from a known volume of a different part of the
mass spectrometer preparation line into the inlet volume. Details of the inlet volume calculation
can be found in Appendix A.2.
Since the most important parameters of this method were measured with better precision and
accuracy than those of the the other method, the accuracy of the calculated gas amount was
superior. Average relative errors achieved by this gas amount measurement are at 1 %. Therefore
this method, utilizing the inlet pressure, was chosen over the other for all further calculations
and data evaluations.
The equation (detailed in Appendix A.1.2) derived from the ideal gas law includes a correction
for the sample tube volume derived from its mass mCu and density ρCu as well as a correction
for the water vapor pressure pH2O due to humidity within the sample gas:
�
(pinlet − pH2O) · VC −
n =
mCu
�
ρCu
TLab · R
The vapor pressure of water pH2O is part of the total pressure in the sample tube and therefore
must be included in the calculation of the gas sample size. Neither water vapor pressure nor
the relative humidity were measured directly during or after sampling. Instead it was assumed
44
(4.1)

4 Measuring methods 4.1. Mass spectrometry of He, Ne, Ar, Kr and Xe
that the relative humidity of soil air is always higher than 95 % in non-arid regions [Hillel, 1980].
The vapor pressure of water was thus calculated from this assumption of relative humidity, as
detailed in Appendix A.1.1.
4.1.3 Estimation of relative humidity within the inlet section
Expanding the gas sample into the inlet volume of the mass spectrometer results in a change of
its relative humidity φ due to the increase in volume, φinlet �= φsample. Therefore the calculation
of the water vapor pressure has to be based on this new relative humidity φinlet, which is
calculated from the actual mass of the water mW,sample contained in a sample tube using the
absolute humidity ρW:
ρW = mW,sample
Vsample
and ρW = φsample · ρW,max(T ) (4.2)
⇒ mW,sample = φsample · ρW,max(T ) · Vsample (4.3)
The maximum vapor pressure above water ρW,max(T ) at a given temperature T is calculated
using the Magnus Formula [WMO, 2008]
ρW,max(T ) = EW(t)
RW · T
EW(t) = 6.112 hPa · exp
�
17.62 · t
243.12 ◦C + t
�
with the water vapor content EW(t), the specific gas constant of water RW = 461.52 J
kg K and
the temperature T [K], t [ ◦ C]. Assuming φsample ≈ 100 % for soil air [Hillel, 1980] leads to
mW,sample = EW(t)
RW · T
· Vsample
(4.6)
The sample volume is calculated using formula A.6, the sampling temperature however is of very
low accuracy. Soil air temperatures were not measured in situ during sampling at the respective
sampling depths. In addition, the sample gas temperature was influenced during sampling by
the process of pumping the soil air from the ground and through a copper tube at ambient
atmospheric temperature as well as by changing conditions (wind, direct sunlight versus cloud
cover) during sampling. Therefore the relative error of sampling temperature measurements is
estimated to be 5 %. The relative humidity within the mass spectrometer inlet volume is given
by
φinlet =
mW,sample
Vinlet · ρW,max(TLab)
where TLab is the average temperature of 24 ◦ C within the laboratory, and Vinlet = (26.832 ±
0.252) ml for runs 1 – 3 and Vinlet = (27.212 ± 0.153) ml for run 4, see Tables B.4 and B.5 for
the resulting relative humidities.
45
(4.4)
(4.5)
(4.7)

4.2. On site measurement of O2, CO2, CH4 and Radon 4 Measuring methods
Mass Spectrometer
noble gas
[ peak heights ]
Mass Spectrometer
calibration gas
[ peak heights ]
Sample
total gas amount
[ mol ]
4.1.4 Resulting data
WuCEM
data evaluation
software
Sample
noble gas amount
[ ccSTP ]
Sample
noble gas mixing ratios
[ Vol% ]
Sample
deviation from atm. air
[ % atm. air ]
Figure 4.1: Schematic diagram showing how the raw data was processed.
Volume of 1 mol
of gas at STP
[ ccSTP/mol ]
Atmospheric air
noble gas mixing ratios
[ Vol% ]
The detected signals are converted to gas amounts in units ccSTP 1 by comparing peak heights
of the calibration gas measurements with those of the measured sample gas using a specialized
evaluation software called WuCEM. The resulting gas amounts are therefore limited in accuracy
by statistical fluctuations, variations of the spectrometer’s sensitivity and the accuracy of the
calibration gas composition. Data characterizing the accuracy of the individual isotope readings
resulting from these measurements can be found in Table B.7. Gas concentrations were calculated
by dividing the gas amounts by the molar volume at STP and by the measured total gas
amount of the sample to deliver standardized and comparable gas concentrations.
Since the interest of this study is to show whether the soil air composition deviates from atmospheric
air composition, the noble gas concentrations were divided by the mixing ratio literature
data of the respective noble gas isotopes [Porcelli et al., 2002], resulting in a relative indication
of deviation, expressed in percent relative to atmospheric air. A schematic representation of the
processing can be found in Figure 4.1.
4.2 On site measurement of O2, CO2, CH4 and Radon
4.2.1 Geotech BM2000 Biogas Monitor
The Geotech BM2000 Biogas Monitor is a portable device capable of measuring O2, CO2, CH4
and CO, see Datasheet D.1. The O2 concentration is measured electrochemically, providing a
measuring range of 0 to 25 Vol% O2 with an error of ±1 Vol%. CO2 and CH4 are measured by
1 cm 3 gas at standard conditions for temperature and pressure, i.e. T = 273.15 K, p0 = 101.325 kPa.
46

4 Measuring methods 4.2. On site measurement of O2, CO2, CH4 and Radon
infrared spectroscopy. The range of the CO2 and of the CH4 sensor is 0 – 100 Vol% with an
accuracy of ±0.5 Vol% at 0 – 5, ±1.0 Vol% at 5 – 15 and ±3.0 Vol% above 15 Vol%. Calibration
of the device was verified by using a certified test gas, confirming the provided accuracies but
showing a slight overestimation of O2, well within the given error range though (see Table B.2).
Atmospheric air was regularly sampled before and after soil air samplings (see Figure C.7), the
mean O2 value of (20.89±0.04) Vol% is in good agreement with the literature value of 20.9 Vol%
[Porcelli et al., 2002].
4.2.2 Durridge RAD7 Radon Detector
The Durridge RAD7 Radon Detector detects α-particles of characteristic energies created within
the decay chains of 222 Rn and 220 Rn, using a solid state detector. Solid state detectors consist of
semiconductor material, a PN junction diode in reverse bias. An α-particle hitting the depletion
layer creates electron-hole pairs that get separated by the electrical field spanning the junction,
leading to a measurable current. The energy resolution depends on the semiconductor’s bandgap,
allowing to differentiate between the different decaying Radon isotopes: The RAD7 detects
the 6.00 MeV α-decay of 218 Po, which itself is the product of 222 Rn decay, and the 6.78 MeV
α-decay of 216 Po, belonging to the 220 Rn decay chain. This allows for the parallel monitoring
of 222 Rn and 220 Rn, leading to a more detailed source of information: while the readings of the
long-lived 222 Rn (t 1/2 = 3.82 days) will usually increase in every one of the three 10 minute
cycles due to its long lifetime, readings of the short-lived 220 Rn (t 1/2 = 55.6 sec) should be
constant in all three cycles. A change in 220 Rn readings in one of the three cycles therefore
indicates an inflow of differently composed air causing dilution or enrichment depending on its
220 Rn content.
47

Chapter 5
Results
5.1 Radon
222 Rn profiles were generally similar for Site A and Site B, the shallowest depths showing
the least amount of Radon, the medium depths the highest and the deepest depths a medium
concentration. This decrease of 222 Rn concentration is likely connected to the soil profile. Both
sampling sites showed a less dense soil structure at their respective deepest sampling depths
with increasing gravel and sand fractions. This may result in a better aeration compared to the
dense clay soil at medium depths, likely leading to the lower 222 Rn concentrations. In addition,
the radon source strength also differs due to variations in soil composition.
The 222 Rn measurements taken on Site A (Figure 5.4) show little variation. A closer look
reveals a slight increase of the 222 Rn concentration at 2 m depth by 10 %, starting in January
2011. The elevated 222 Rn concentrations coincide with an increase in the concentration of the
short-lived 220 Rn from the first to the second measuring cycle at each sampling of 2 m depth.
However, these 220 Rn increases are within the margin of error of the measurements.
The 222 Rn data at Site B shown in Figure 5.5, clearly display a steep dip in December 2010.
The concentrations recovered during January and February 2011. As of March 2011 the 222 Rn
concentrations recessed back to a decreased level.
5.2 Temperature profiles
The data loggers on Site B delivered a nearly complete record covering the entire sampling
period, as shown in Figure 5.1. At Site A the record (see Figure C.8) is not as complete,
showing gaps caused by logger failures as well as offsets caused by moisture intrusions into the
sensors. While the logged temperatures at both sites in general deviate very little from each
other, the diurnal variations at 0.1 m depth at Site B are more pronounced in August to October
2010. This is likely caused by the differing vegetation cover at the two sites, leading to different
durations of direct sunlight exposure.
49

5.2. Temperature profiles 5 Results
� � � � � � � � � � � ��� � �
Figure 5.1: Temperature measurements taken at Site B at 0.1 m, 1.0 m and 2.5 m depth
and sinusoidal fits. Depth placement accuracy is ±0.1 m, temperature accuracy is ±0.5 ◦ C.
The atmospheric daily mean temperatures were provided by meteomedia, measured by a
weather station close to Site A.
The damping of the atmospheric temperature signal is clearly visible and increasing in magnitude
with depth. The insulating effect of snow cover is apparent during December and January,
leading to nearly constant temperatures above zero at 0.1 m depth while atmospheric temperature
above ground was well below 0 ◦ C. Neither sampling site experienced ground frost at 0.1 m
depth and lower during the Winter 2010/2011.
Comparison of the minima of the sinusoidal fits of the temperature curves (excluding known
erroneous readings) show the retardation of temperature penetration into the soil. At 0.1 m
the retardation is about ten days, at 1.0 m it is one month and two months at 2.5 m. The
atmospheric average temperature based on the fit (to account for gaps in the datasets) of the
meteomedia data from August 2010 to May 2011 was (12.5 ± 0.5) ◦ C. At Site A, the average
temperatures in the same time frame were: (10.8 ± 0.5) ◦ C at 0.1 m, (11.7 ± 0.5) ◦ C at 1.0 m and
(13.1 ± 0.5) ◦ C at 2.5 m. At Site B they were: (11.0 ± 0.5) ◦ C at 0.1 m, (12.2 ± 0.5) ◦ C at 1.0 m
and (12.4 ± 0.5) ◦ C at 2.5 m. Accuracy is based on the sensor’s accuracy.
During the irrigation of Site A the temperature measurements at 1.0 m and 2.5 m show spikes
coinciding with the water intrusion 1 (see Figure 6.1). Whether these spikes represent accurate
1 The lack of reaction to the first irrigation is due to the loggers recording at hourly intervals at that time,
50

5 Results 5.3. O2 and CO2 profiles
temperature changes is questionable, as the temperature record shows several spikes unrelated to
active irrigation and reminiscent of previously observed sensor failures due to moisture intrusion.
These spikes do indicate though that the water infiltrated the soil to a depth of 2.5 m within an
hour, and therefore likely reached the lower depths as well within a short time.
5.3 O2 and CO2 profiles
O2, CO2 and CH4 were measured at Site A and Site B starting in February 2011. Since
the sealing of Site B is questionable (see Section 5.4) only the measured gas concentrations at
Site A are discussed here in detail, the entire dataset is included in Table B.11. Furthermore,
CH4 was never measured in any significant amount: the rare and unsystematic occurrences of
maximum readings of 0.1 Vol% can be ignored with respect to the sensor’s accuracy of 0.5 Vol%.
During February to April 2011, O2 and CO2 were measured only when noble gas samples were
taken to minimize disturbance of the site’s soil. During that time, the depth profiles (see
Figure 5.2, A and B) of both O2 and CO2 showed uniform concentrations, indicating low CO2
production. CO2 concentrations at all depths fell during that time from an initial maximum of
(4.7 ± 0.5) Vol% to (3.4 ± 0.5) Vol% while O2 concentration remained constant at all depths
(within the measurement’s accuracy) at (18 ± 1) Vol% (see Figure C.13). While O2 levels
were depleted compared to atmospheric concentration at that time, the deficit was more than
compensated by the rise in CO2 concentrations.
Irrigation of Site A was started on May 9 th , 2011 as a reaction to the prolonged dry period,
accompanied by an increase of the frequency of O2 and CO2 measurements (see Figure 5.3).
Measurements were executed directly before each irrigation and hourly afterwards. The response
of the O2 and CO2 concentrations was immediate at all three depths. The most pronounced
reaction occurred at the shallowest depth of 2 m, while at 6 m only little change was observed
(see Figure 5.2, C, D and E).
The response of the CO2 concentrations is characterized by two phases: the initial reaction is
a steep drop in CO2 concentrations at all depths, the maximum at 2 m was a drop by 1.7 Vol%
while at 6 m the largest drop was 0.2 Vol%. During the following hours the CO2 levels recovered
to the preceding levels at 6 m, at 2 and 4 m depth they rose above them. The gain in CO2 was
most highest at 2 m, where the CO2 concentration peaked at (6.8 ± 1.0) Vol% about two weeks
after the first irrigation (see Figure 5.2, E). After the last irrigation was done on May 19 th ,
the CO2 concentration at 2 and 4 m started to decrease slowly, but steadily. At 6 m, the CO2
concentrations never peaked but rose slowly and steadily by about 1.0 Vol% during the first 50
days after the initial irrigation (see Figures 5.3 and 5.2, F).
O2 concentrations at 2 m rose slightly during the first few hours after each irrigation, the overlying
trend however was a depletion of O2 during the first two weeks, reaching a minimum
concentration of (10.9 ± 1.0) Vol% ten days after the first irrigation (see Figure 5.2, D). Once
irrigation stopped, the levels rose again. At 4 m the influence of irrigation was much less pronounced
but visible, leading to a minimum in O2 concentrations at (13.2 ± 1.0) Vol% 15 days
logging frequency was subsequently increased to 5 minutes to be able to resolve the water incursion.
51

5.3. O2 and CO2 profiles 5 Results
Figure 5.2: O2 and CO2 depth profiles taken at Site A at various stages. Values at 0 m
depth are based on literature data for atmospheric air [Porcelli et al., 2002]. A-B: before
irrigation. C: during irrigation, showing the minimal CO2 concentration measured. D: 10
days after irrigation, minimum of the sum of O2 and CO2. E-F: several weeks after irrigation.
52

5 Results 5.3. O2 and CO2 profiles
Figure 5.3: O2 and CO2 concentrations in all three depths of Site A, as well as the sum of
O2 and CO2 at 2 m depth, starting in May 2011. Artificially introduced precipitation and
rainfall, data is limited to the interval May 9 th – May 18 th .
after the first irrigation. No effect of the irrigation was visible at 6 m, however over the entire
time since initial irrigation the concentration slowly fell by about 1.5 Vol%.
The sum of O2 and CO2 concentrations was most affected by the reaction to the irrigation at
2 m depth, leading to a minimum of 16.5 Vol%, causing a deficit compared to atmospheric composition
of 4.4 Vol%. However, such a deficit was never observed during conditions uninfluenced
by the irrigation. In fact the O2+CO2 concentration at 2 and 4 m was usually a bit above
20.9 Vol%, though well within the sum’s accuracy of 1.4 Vol%.
Figure C.13 shows an overview of the entire O2 and CO2 data available at Site A while Figure
C.14 provides a detailed view of the first ten days of irrigation.
The measurements of O2 and CO2 at Site B show little variation over time (Figure C.15), the
CO2 and O2 concentrations at 1 and 3 m depth are nearly identical. They fluctuate slightly
around 2 Vol% during the entire measurement period and are approximately 2 Vol% lower than
Site A’s CO2 concentrations at 2 m depth during the same time. At 5 m depth, the CO2
concentrations are increased and the O2 concentrations decreased compared to 1 and 3 m.
53

5.4. Borehole sealing 5 Results
5.4 Borehole sealing
Sealing of the sampling screens from atmospheric contamination as well as from each other is an
important factor for the reliability of the depth information of the measured gas concentrations.
While the estimated depth accuracy lies within the range of ±0.2 m, assuming homogeneous
soil structure, the actual depth accuracy is highly dependent on vertical gas permeability. The
weakest link of the sampling site setup is the refilling of the boreholes, possibly leading to large
pore space and channels along the buried sampling tubes potentially allowing direct air exchange
between the different sampling screens or even exchange with atmospheric air.
Radon, O2 and CO2 concentrations were used as tracers for atmospheric air contamination as
well as interconnectivity between the different screening depths. Combination of all three tracers
allows for discrimination between the two kinds of sealing breaches.
5.4.1 Site A
The small variations in 222 Rn measurements taken on Site A (see Figure 5.4) imply a fully
contained sealing against atmospheric contamination spanning the entire sampling period. O2
and CO2 measurements, taken during the first 2 minutes as well as during the last 10 minutes of
each 30 minute radon sampling showed no significant variation during each sampling, supporting
the case of intact sealing as well. A first indication of sealing failure was observed only after
the last noble gas sample (A23) was taken: A longer than usual O2 and CO2 measurement on
May 21 st showed an increase of O2 and a decrease of CO2 after around 3 minutes of pumping,
displayed in Figure 5.6. A 222 Rn measurement taken the day before did not show any signs of
dilution with 222 Rn-free 2 atmospheric air. However, the analysis of the entire 222 Rn dataset of
Site A led to the discovery of the slight upwards shift in 222 Rn concentrations at the 2 m depth
starting in January 2011. This increase likely represents an interconnectivity of the 2 m and 4 m
screening depths. This would not have been visible in the O2 and CO2 data before May 2011,
since until then the concentrations of O2 and CO2 were of very similar magnitude in all three
depths, thereby masking mixing effects. The assumption of an interconnectivity is supported by
an increase in the concentration of the short-lived 220 Rn from the first to the second measuring
cycle at each sampling of the 2 m depth, indicating the inflow of soil air from a lower depth
rather than atmospheric air.
Based on these observations, the samples taken until January 2011 (A01 to A09) contain air
from the respective sampling depths, while samples taken afterwards until April 2011 (A10 to
A16) at depths 2 m and 4 m likely contain mixed soil air. The samples collected in May 2011
(A17 to A23) were taken using the BM2000 instead of the RAD7, with less than 2 minutes of
pumping time. Based on the measurement shown in Figure 5.6, these samples contain unmixed
air from the respective sampling depths.
2 The atmospheric volume fraction of radon is about 6 × 10 −20 [Porcelli et al., 2002].
54

5 Results 5.4. Borehole sealing
�� �� ������������ �� � � � �� ���� ��� �� �� � �� ��� � � �� � � � � ��� �� � � � � � �
�� �� ������������������������� � �� �� �� �� ��� � � � � �
�� �� ������������ �� � � � �� ���� ��� �� �� � �� ��� � � �� � � � � � � �� �� � �
� �
�� �� ��� �� ������������������� � �� �� �� �� ��� � � � �
Figure 5.4: Radon concentrations during sampling at Site A. The 2 m values show a slight
upwards shift of about 10 % starting as of January 2011.
Figure 5.5: Radon concentrations during sampling at Site B. Higher than usual 222 Rn
values for atmospheric air are due to immediate previous use of the RAD7 with ground air
on a different sampling site and are unlikely to be actual atmospheric fluctuations.
55

5.4. Borehole sealing 5 Results
Figure 5.6: Continuous O2 and CO2 measurements at Site A, showing an increase of O2 and
a decrease of CO2 starting at around 200 s of pumping, indicating an inflow of air more closely
resembling atmospheric composition. This air inflow is not necessarily atmospheric though.
Based on the associated 222 Rn and 220 Rn data it is more likely that an interconnection
between the screens at 2 and 4 m exists. Since the 4 m soil air contained more O2 and
less CO2 than the 2 m soil air at the time, the mixing only appears to be atmospherically
influenced. Accuracy for both O2 and CO2 is 1 %, error bars have been omitted for better
visibility.
Figure 5.7: Continuous O2 and CO2 measurements at Site B, showing an increase of O2
and a decrease of CO2 starting at around 30 s of pumping, indicating an inflow of air more
closely resembling atmospheric composition. Accuracies are 1 % for O2 and 0.5 % for CO2,
error bars have been omitted for better visibility.
56

5 Results 5.5. Noble gases
5.4.2 Site B
The 222 Rn data in Figure 5.5 clearly indicates an atmospheric leak leading to a dilution of the
ground air with mostly 222 Rn-free atmospheric air on several, if not all, samplings. O2 and CO2
measurements shown in Figure 5.7 support the atmospheric leak scenario, showing an intrusion
of differently composed air within 30 seconds of pumping at all depths except 5 m. A contrasting
plot for Site A showing no atmospheric air inflow can be found in Figure C.6. Additionally,
CO2 concentrations measured at 1 and 3 m at Site B are significantly lower than at 2 m at Site
A while O2 concentrations are higher.
While the resealing of the borehole at Site B initially seemed to have been successful 3 , the
relatively dry period of September to October 2010 probably caused the deterioration of the
sealing by inducing the formation of contraction cracks [Scheffer and Schachtschabel, 2010] in
the drying clay soil. The recovery of the 222 Rn values during winter was likely caused by a
partial and temporal resealing of the upper soil layer due to the increase in precipitation.
This leads to the conclusion that most, if not all, samples taken at Site B do not contain soil
air from the respective sampling depths, but rather a mixture of soil and atmospheric air and
therefore cannot be used as a record to answer this thesis’ main objective.
5.5 Noble gases
The accuracy achieved by the mass spectrometer was best for the isotopes measured with the
faraday cup and significantly worse for those measured with the multiplier. The best relative
accuracy was achieved for 20 Ne (see Table B.7). Based on these accuracy patterns, the five
isotopes 4 He, 20 Ne, 22 Ne, 36 Ar and 40 Ar were chosen to be presented in detail as their average
measurement error was below 1.5 %. The final accuracy of the presented data is influenced by
the introduction of measured gas amount of each sample. The remaining three isotopes 3 He,
84 Kr and 132 Xe mirrored the general trends found in this study, but suffered from low accuracies
and more pronounced scattering. Plots and data for all measured isotopes can be found in the
Appendices B and C.
5.5.1 Effects of storage
Immediate measurement of the sampled air in the mass spectrometer was usually not possible
as the spectrometer was only available during certain time frames. Because the copper tubes
contain air with high O2 concentrations and humidity, the possibility of chemical reactions
occurring during storage affecting the noble gases was tested. This was done three times by
measuring all three samples of a single depth, one only a few hours after collecting the samples.
The remaining two backups were measured after storing them for different periods, the one for
3 Assuming the difference between absolute 222 Rn concentrations of Site A and Site B were caused by differing
source strengths. Otherwise it might even be the case that only the 222 Rn concentrations measured in February
2011 at Site B represent a sealed borehole.
57

5.5. Noble gases 5 Results
8 days, the other for more than 6 months. All three samples of B06 at 1 m depth (I – III) and
of B06 at 3 m depth (IV – VI) were successfully measured, of sample A23 at 2 m depth one (II)
of the three samples proved to be leaky and was lost.
The results show no change, scattering within the accuracy of the measurements (see Figure
C.16). This indicates that noble gas measurements were unaffected by potential chemical reactions
within the sample tubes during prolonged storage.
5.5.2 Atmospheric air samples
The atmospheric air samples display a -2 % shift relative to literature isotope mixing ratios of
atmospheric air at STP [Porcelli et al., 2002], as shown in Figure 5.8. Only the heavy noble
gas isotope 84 Kr does not display this behavior, as shown in Figure C.11. An isotope mass
dependency of the effect is not visible however, as 132 Xe does display the shifting as well.
Possible mechanisms leading to such a shift are connected to the noble gas concentrations of
the calibration gas 4 and the gas amount of each individual sample, calculated from various
parameters: inlet pressure pinlet, inlet volume Vinlet, relative humidity φinlet, sample tube mass m
and laboratory temperature TLab. While the latter three parameters would require unreasonably
high changes (> 30 %) to account for a 2 % change in gas amount n or have no effect at all in an
order of magnitude of percent, the gas amount is quite sensitive on changes of Vinlet and pinlet
and will be discussed below.
Errors in the calculation of noble gas amounts in the calibration gas are fairly improbable, but
possible. Measurements of atmospheric air equilibrated water samples using the same calibration
gas were inconspicuous however [T. Kaudse, personal note] and led to the conclusion that the
calibration gas concentrations were accurate.
Inaccuracy of the calculation of the inlet volume is another parameter that could account for the
-2 % shift, however the volume would have to be 0.54 ml smaller than measured. The accuracy
of the volumetric measurement is 0.15 ml or 0.6 %, based on the accuracies of the known volumes
used. While it is unlikely that an inaccurately determined inlet volume is responsible for the
entire shift in the noble gas concentrations, part of the effect may be attributed to it.
To account for the entire -2 % shift, the inlet pressure would have to have been overestimated by
2 %. The Keller pressure gauge regularly displayed a peak reading right after opening a sample
that decreased slightly during the next few seconds by 0.1 to 0.3 mbar, from an average total of
about 60 mbar. Readings were taken consistently during the first 15 to 20 seconds after opening
the sample, except for samples that barely cracked and consequently required up to several
minutes to vent into the inlet volume. The slow venting of these samples (A20-IV, A21-VIII
and A23-III) caused the Keller gauge to approach the final reading slowly from below, rather
than overshooting it like the instantly venting samples did. A comparison of the slowly vented
samples with instantaneously vented samples allows for a qualitative estimation of the effect:
Sample A23-III is a backup sample of the previously measured A23-I (which vented instantaneously
on cracking) from the same date and depth. While A23-III is slightly larger in sample
4 The noble gas content of the calibration gas was calculated from measurements of temperature, pressure and
humidity at the time that the calibration gas was sampled from atmospheric air.
58

5 Results 5.5. Noble gases
3
He [% atm. air]
4
He [% atm. air]
40
Ar [% atm. air]
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
110
105
100
95
90
105
100
95
90
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Date
20
Ne [% atm. air]
22
Ne [% atm. air]
36
Ar [% atm. air]
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
110
105
100
95
90
105
100
95
90
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Figure 5.8: Noble gas concentrations of atmospheric air samples relative to literature values
from Porcelli et al. [2002] for 3 He, 4 He, 20 Ne, 22 Ne, 36 Ar and 40 Ar. All isotopes show an
underestimation of roughly 2 %.
tube volume than A23-I, the measured inlet pressure is actually 0.6 mbar lower, indicating a
pressure overestimation on sample A23-I. A comparison of the noble gas concentrations calculated
for these two samples shows that A23-I displays a shift relative to A23-III by roughly -2 %
on most noble gas isotopes. Samples A20-IV and A21-VIII show elevated noble gas concentrations
compared with samples from the same depth and roughly the same time as well, however
comparing samples from different sampling dates can only deliver a vague indication at best. To
quantify the observed behavior of slowly decreasing pressure readings the Keller gauge and the
inlet volume were reinstalled in the mass spectrometer preparation line and eight atmospheric
air samples were opened. This experiment was unable to replicate the previously observed effect:
the readings for those instantaneously vented samples did not decrease. However this led to the
observation that the Keller gauge is highly sensitive to its spatial orientation, showing a 1 mbar
difference when rotated by 180 ◦ , possibly adding to the observed shift in atmospheric noble gas
values.
It was deemed most likely that the reading of the inlet pressure was executed prematurely, but
consistently, leading to a systematical overestimation of sample gas amount and thereby causing
the offset displayed by the atmospheric air samples. Therefore all measured samples’ individual
noble gas isotope values discussed below (except those that vented slowly) were standardized to
the mean fitted values of the measured atmospheric air.
59
Date

5.5. Noble gases 5 Results
5.5.3 Soil atmosphere samples from Site A
A total of 23 noble gas depth profiles were sampled at Site A and measured, the entire dataset
can be found in Table B.9. A few readings (marked red in Table B.9) were omitted from
analysis as they scatter unreasonably strong. Except for the 36 Ar reading of sample A01-I, all
these outliers were connected to technical problems that occurred during the measurement in the
mass spectrometer. The 36 Ar reading of sample A01-I is the only isotope of that sample showing
such elevated readings and is therefore regarded as an artifact of an undiscovered problem during
that single measurement.
The sampling frequency was increased during the irrigation period. Samples were taken right
before irrigation (A21), within one hour after irrigation (A22) and days after irrigation events.
The noble gas sample that is accompanied by the lowest sum of O2 and CO2 (16.7 Vol%) is A19
2 m depth.
Figure 5.9 shows the measured concentrations of the four isotopes 20 Ne, 22 Ne, 36 Ar and 40 Ar
standardized to literature data on atmospheric composition, plotted over time. The plots for the
remaining isotopes can be found in Figure C.17. It is quite clear that most of the noble gas data
is located above or at 100 % relative to atmospheric air composition. A significant drop below
100 %, consistent in all isotopes, was never observed. Only the heavy noble gas isotopes 84 Kr
and 132 Xe showed such reduced noble gas concentrations, though suffering from low accuracy
and strong scattering their reliability is questionable.
The data can be separated into two different time frames based on the differing visible trends.
The first interval is August 2010 – April 2011, when all noble gases show a decline from initial
values well above 100 % at the beginning to values scattering closely around 100 % within the
data’s accuracy. This trend is visible at all three depths, however it is most pronounced at
6 m, where the initial values are between 104 – 106 %, depending on the isotope. The shallower
depths both start at 102 – 105 % and reach 100 % earlier than at 6 m. Between December 2010
and April 2011, the noble gas concentrations scattered around 100 % at all depths.
The second interval is May – June 2011, marking the artificial irrigation of Site A. The reaction
of the noble gases at a depth of 2 m is immediate and strong, concentrations jump from 100 %
to 104 – 107 % (depending on the noble gas isotope) at the last measured noble gas sample
(A23), taken eleven days after the first irrigation (see Figure 6.1). At depths 4 and 6 m noble
gas concentrations show no reaction at all, remaining at around 100 %.
The noble gas isotope ratios 3 He/ 4 He, 4 He/ 20 Ne, 20 Ne/ 22 Ne and 40 Ar/ 36 Ar were calculated,
however a specific evaluation of the mass spectrometer data focused on these ratios was not
done. The ratios displayed no irregularities or significant deviations from literature values (see
Table B.9). The change of O2 and CO2 concentrations had no effect on these ratios, as shown
exemplarily in Figures C.20 and C.21 for 4 He/ 20 Ne and 20 Ne/ 22 Ne.
60

5 Results 5.5. Noble gases
20
Ne (2m) [% atm. air]
20
Ne (4m) [% atm. air]
20
Ne (6m) [% atm. air]
36
Ar (2m) [% atm. air]
36
Ar (4m) [% atm. air]
36
Ar (6m) [% atm. air]
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Date
22
Ne (2m) [% atm. air]
22
Ne (4m) [% atm. air]
22
Ne (6m) [% atm. air]
40
Ar (2m) [% atm. air]
40
Ar (4m) [% atm. air]
40
Ar (6m) [% atm. air]
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Figure 5.9: Concentrations of 20 Ne, 22 Ne, 36 Ar and 40 Ar in soil atmosphere samples from
the different depths of Site A over time, relative to atmospheric literature values from
Porcelli et al. [2002].
61
Date

5.5. Noble gases 5 Results
5.5.4 Soil atmosphere samples from Site B
Noble gas measurements at Site B show a similar, but less distinct trend of a decline of concentrations
from elevated values to 100 % in winter. The decline is similar at all sampled depths
(1, 3 and 5 m), in contrast to observations at Site A. Since it is very likely that the sampled
soil atmosphere at Site B was contaminated to an unknown extent with atmospheric air, the
quality of the data is questionable and the dataset has been omitted from discussion. Plots can
be found in Figures C.18 and C.19, the complete dataset is listed in Table B.10.
62

Chapter 6
Discussion
The O2 and CO2 measurements executed at Site A show the influence of several different factors
on soil respiration, all conforming with theoretical predictions and the results of other studies
as presented in Chapter 2, Section 2.3.
During late winter and early spring 2011, the O2 and CO2 profiles were uniform from 2 to 6 m,
showing a moderate depletion of O2, the sum of O2 and CO2 never fell below 20 Vol% though.
The dominating factor on soil respiration during early spring was temperature, leading to very
low CO2 production rates (see Chapter 2, Figure 2.10). The slight decline in CO2 and increase
in O2 concentrations in the shallower depths, as visible towards May 2011, is probably caused
by decreasing water content due to the dry period in spring. This would increase the diffusivity
of the soil, leading to stronger diffusive exchange with the atmosphere.
While soil temperatures started to rise during March 2011, O2 and CO2 measurements showed
no increase of soil respiration. In light of the rising temperatures and the low amounts of precipitation
during March and April (see Figure C.10), soil moisture content likely became the
dominant limiting factor on biological activity and thereby on soil respiration. The introduction
of water into the system caused a dramatical change, as shown in Figure 5.3. The immediate
reaction to this event was a steep drop in CO2 concentrations, caused by parts of the CO2 dissolving.
The abundance of water then activated microbial activity leading to quickly increasing
CO2 concentrations, as previously observed in other studies [Liu et al., 2002; Tang et al., 2005].
The measured maximum of soil respiration was located at 2 m depth, actual activity was likely
even higher at shallower depths [Fierer et al., 2003]. The smaller initial drop in CO2 concentrations
in response to the water at depths 4 and 6 m was presumably caused by smaller amounts of
water reaching those depths. Furthermore, due to the spatial distribution of microbial biomass,
the subsequent changes in O2 and CO2 concentrations at 4 m are likely influenced in part by
diffusive transport from shallower depths. The slow but constant rise of CO2 concentration at
6 m from initial 3.4 Vol% to 4.0 Vol% was probably caused entirely by diffusive transfer rather
than by in-situ production
The drop in O2 concentration at 2 m was quite significant and was amplified by the high water
content of the upper soil layers slowing down diffusive O2 replenishment from the atmosphere.
63

6 Discussion
This rather extreme amount of water intruding within a short time period created a situation
where oxygen depletion led to a gas deficit of up to 4.4 Vol% at the shallow depth of 2 m.
Continued measurements during the following two months indicate that this is in fact unusual:
O2 and CO2 readings at both 2 and 4 m depth returned towards their initial values despite the
onset of regular natural precipitation (see Figure 5.3). Rainfall had only limited and short-lived
effect on the concentrations at 2 m. The sum of O2 and CO2 remained below 20.9 Vol% only
at 6 m depth during the two months after irrigation, trending slightly towards further decrease.
The difference at the time this thesis was written was below 1 Vol% however.
O2 and CO2 depth profiles as measured by Schneider [2010] in August 2009 show that the sum
of O2 and CO2 descends well below 20.9 Vol% under certain natural conditions. The maximum
of O2 depletion and consequent gas deficit was located at greater depths, a minimum of the sum
of O2 and CO2 was measured by Schneider [2010] at 3.5 and 4.5 m depth with 15 Vol%. While
such O2 and CO2 profiles were not encountered during February to June 2011, it is very likely
that, depending on variations of weather, a similar situation will be encountered in late summer
or autumn 2011.
Despite being a slightly unusual intrusion into the system, the irrigation did provide valuable
information on the behavior of the noble gas concentrations. As Figure 6.1 shows, noble gas concentrations
did indeed rise significantly after the sum of O2 and CO2 dropped below 20.9 Vol%.
To test if the intrusion of water itself played a factor in this, samples A21 and A22 were taken
within an hour before and after an irrigation event. As visible in Figure 6.1, the difference
between the two samples is well within their accuracy and within the normal scattering of the
mass spectrometer measurement when compared with the double measurement of sample A23.
Therefore a direct influence of the water intrusion is improbable.
The correlation between noble gas concentrations and O2+CO2 deficit is shown in Figure 6.2 (
the entire dataset is plotted in Figures C.22 and C.23), where the relative change of noble gas
concentrations compared to atmospheric air concentrations is plotted against the sum of O2 and
CO2. Also included is the theoretical prediction derived from equation 2.19. The accuracies
of the O2 and CO2 measurements are relatively low. It is apparent nonetheless that noble gas
concentrations roughly follow the predictions of equation 2.19 when an O2+CO2 deficit occurs.
This holds also true when O2+CO2 increases slightly above 20.9 Vol%, which was often the case
at depths 2 and 4 m outside the irrigation period.
Furthermore, linear error weighted fitting of the dataset of Site A’s 2 m depth samples (see
Figure 6.2) indicates that there might be a mass discrimination involved: the lighter noble gas
isotopes appear to be less affected by changes in O2+CO2 concentrations as expected, while the
heavier isotopes conform more closely to the theoretical expectation. Gravitational separation as
described by Stute and Schlosser [1993] can not be responsible for this observation at this study’s
shallow depths. A plausible explanation of this observation might be the high diffusion coefficient
of helium in air [Cussler, 2005]. The rise in noble gas partial pressures creates a concentration
gradient between enriched soil air and atmospheric air. Diffusive transport reduces this gradient,
the rate of change is dependent on the diffusion coefficient as described by Fick’s second law
(Equation 2.24). Therefore, the observed low 4 He enrichment could be caused by much more
rapid reduction of the concentration gradient of 4 He than of those of the other noble gases.
64

6 Discussion
� � � � ��� � ���� �� � � ��� �� �
� � � � � � ��� � ���� � �� �
� � � � �� �� � � �� � ��� � �
� � � � � � � � � � � ��� � �
Figure 6.1: 40 Ar data from a depth of 2 m (top), sum of O2 and CO2 concentrations at 2 m
(center), soil temperature at 1.0 and 2.5 m and precipitation per day before break, per hour
after break (bottom), all from Site A over the period of January to March 2011, and in
May 2011. Scales on the date axis differ before and after the break.
65

)!
)!
*+,-./-01234*-56-20301.7*38*9-82/1:-9*17*;./

6 Discussion
F 20 Ne
F 84 Kr
1.04
1.02
1.00
0.98
0.96
1.10
1.05
1.00
0.95
Data from 2 m depth, A01 - A10
Data from 6 m depth, A01 - A10
Linear Fit of 2 m data
Linear Fit of 6 m data
0.96 0.98 1.00 1.02 1.04
F 4 He
Data from 2 m depth, A01 -- A10
Data from 6 m depth, A01 -- A10
Linear Fit of 2 m data
Linear Fit of 6 m data
0.90
0.90 0.95 1.00 1.05 1.10
F 4 He
F 20 Ne
1.04
1.02
1.00
0.98
Data from 2 m depth, A11 - A23
Data from 6 m depth, A11 - A23
Linear Fit of 2 m data
Linear Fit of 6 m data
(a) 0.96
(b)
F 84 Kr
1.10
1.05
1.00
0.95
0.96 0.98 1.00 1.02 1.04
F 4 He
Data from 2 m depth, A11 - A23
Data from 6 m depth, A11 - A23
Linear Fit of 2 m data
Linear Fit of 6 m data
(c) (d)
0.90
0.90 0.95 1.00 1.05 1.10
Figure 6.3: F-Values (see Section A.3 for definition) of 20 Ne (a, b) and 84 Kr (c, d) versus
F-Values of 4 He. Data in the left row (a, c) is from August 2010 – January 2011 (lacking
O2 and CO2 readings). Data in the right row (b, c) is from February – May 2011.
Unfortunately the dataset of noble gas measurements with corresponding O2+CO2 measurements
is quite small. While noble gas concentration changes were in fact measured at 6 m
depth in late summer 2010, the lack of accompanying O2 and CO2 data renders these noble gas
records useless for this specific analysis. Therefore a different method was employed to test if
the relatively lower enrichment of 4 He can also be found in the samples A01 – A10 (that lack
the O2+CO2 data): The F-Values (see Section A.3 for definition) of the isotopes 3 He, 20 Ne,
22 Ne, 36 Ar, 84 Kr and 132 Xe were plotted versus the F-Value of 4 He (see Figure C.24). Figure
6.3 displays a selective analysis where the data was separated by depth and by measuring date.
Figure 6.3 (b) shows that 4 He in samples from 2 m was slightly depleted relative to the standard
( 40 Ar) while 20 Ne was not, as expected based on Figure 6.2. Since the highest noble gas
enrichment during August 2010 – January 2011 was found at 6 m instead of 2 ˙m, Figure 6.3 (a)
should show a reversed behavior. This is apparently not the case, suggesting that 4 He might
have been influenced differently at 6 m. However, the accuracy of the data appears to be too
low to draw conclusions, as Figures 6.3 (c) and (d) show. Further improvement of the accuracy
as well as more extensive data is called for to test whether these trends can be confirmed and
whether they appear at all depths.
67
F 4 He

6 Discussion
Table 6.1: Synthetic data of noble gas concentrations in water at a temperature of 12 ◦ C.
A is the fraction of air entrapped in the water volume, POD is the change in noble gas
partial pressures as defined in equation 2.19, Ci are the noble gas concentrations. Ti are
the temperatures calculated by the respective model used to fit the synthetic data.
Input
ID A POD CHe CNe CAr CKr CXe
EQ0 0.000 0.00 4.61×10 −8 1.98×10 −7 3.69×10 −4 8.60×10 −8 1.23×10 −8
UA0 0.002 1.00 5.65×10 −8 2.34×10 −7 3.88×10 −4 8.83×10 −8 1.25×10 −8
OD3 0.002 1.03 5.79×10 −8 2.40×10 −7 3.99×10 −4 9.09×10 −8 1.28×10 −8
OD6 0.002 1.06 5.93×10 −8 2.46×10 −7 4.10×10 −4 9.35×10 −8 1.32×10 −8
Output
ID TCE ∆TCE TOD ∆TOD
UA0 12.0 0.4 12.0 2.1
OD3 11.2 0.4 12.0 2.1
OD6 10.5 0.4 12.0 2.1
The O2+CO2 deficits observed by this study are of the same order of magnitude as those
recorded by Schneider [2010], yet the findings on noble gas enrichment significantly differ. A
reason for this discrepancy could not be identified as both study’s setups, sampling procedures
and measurement methods appear reasonably reliable.
The high noble gas concentrations at 6 m depth in summer 2010, reaching up to (106.0 ± 1.7) %
relative to atmospheric air (and slightly lower at 4 m depth, see Figure 5.9), prove that the
OD model’s basic assumption of noble gas enrichment within the soil atmosphere, proposed by
Hall et al. [2005], is indeed encountered within natural soil environments. Based on theoretical
descriptions of soil CO2 depth profiles and the one-time depth profile from August 2009 by
Schneider [2010], it is reasonable to conclude that this measured increase in noble gases is
caused by the O2+CO2 deficit occurring during summer and autumn. Since this study could
not complete a full annual dataset at the time this thesis was written, giving an annual average
of noble gas enrichment is not possible at this time. In light of the observed fluctuations of the
soil atmosphere composition and the seasonal patterns of precipitation leading to ground water
recharge, it is questionable whether such an average should be used at all.
Estimating the maximum influence of noble gas enrichment on noble gas temperatures is however
reasonable and possible by using the maximum measured noble gas concentrations of one of the
most accurately measured isotopes, 40 Ar. Its concentration reached, both in summer 2009 at
6 m as well as during irrigation at 2 m, 106 % relative to atmospheric air concentrations. A small
set of synthetic data of noble gas concentrations in water was created, based on equilibrium
concentrations Ci,eq in water at 12 ◦ C and atmospheric pressure (EQ0). Three different variations
of this set were calculated: the first assumes atmospheric noble gas concentrations (UA0), the
second assumes an increase by 3 % (OD3) and the third an increase by 6 % (OD6). The initial
datasets and the resulting temperatures are detailed in Table 6.1. These datasets were fitted
68

6 Discussion
using a software solution developed by von Oehsen [2008], both the CE model and the OD model
were employed.
The OD model does reconstruct the initial temperature of 12 ◦ C well for all datasets but suffers
from low accuracy. While the CE model successfully reproduces the temperature of dataset UA0
at a much better accuracy compared to the OD model, it underestimates the temperatures of
datasets OD3 and OD6 by 0.8 ◦ C and 1.5 ◦ C respectively.
The observed elevated noble gas concentrations at this study’s sampling site were therefore
able to influence the temperatures reproduced by the CE model significantly. However, they
were not large enough to account entirely for deviations of noble gas temperatures from mean
annual air temperatures as observed by Ma et al. [2004] and Hall et al. [2005] in studies of
recent ground waters that prompted the proposition of the OD model to better describe the
excess air component of dissolved noble gases. Yet it is not unlikely that stronger O2+CO2
depletion occurs naturally at increased depths closer to the capillary fringe. Additionally, the
magnitude of influence on noble gas temperatures is also dependent on local annual temperature
and precipitation patterns, determining whether ground water recharge occurs at the same time
as the maximum of oxygen depletion: If both temperature and precipitation variations were
in phase (or the temperature basically constant at a level ideal for microbial activity), soil
respiration would presumably be at a maximum (disregarding other parameters) parallel to
ground water recharge, leading to a strong increase in noble gas concentrations. The CE model
would then underestimate the noble gas temperatures. The other extreme would be a situation
where temperature and precipitation were out of phase, leading to minimal soil respiration during
the time of ground water recharge, limiting the influence of oxygen depletion on ground water
noble gas concentrations. In that case the CE model would likely deliver accurate results while
the OD model, if based on maximum or mean O2+CO2 deficits, would overestimate noble gas
temperatures. This consideration is a rather schematic estimation, as it ignores that parameters
like infiltration speed, depths of ground water tables, soil structure and diffusive transport
variations may introduce more complex relations between soil temperature, soil atmosphere
composition and ground water recharge.
Further complicating the situation is the fact that the OD model handles O2+CO2 deficits in a
single parameter POD to account for the additional fraction Ci,od introduced by oxygen depletion
into the total measured concentration Ci,m. This parameter is optimized for an entire dataset. It
is unlikely, though, that the local and global climate parameters that influenced soil respiration
would remain constant over time scales relevant to paleoclimatology, and therefore the use of the
same, single parameter for every sample collected from an aquifer appears unreasonable to properly
describe the influence of oxygen depletion. Noble gas paleotemperatures have been used to
measure the temperature differences between the last glacial maximum and today. These differences
were found to be within the range of 4 – 5 ◦ C [Stute et al., 1995; Aeschbach-Hertig et al.,
2000; Wieser, 2011]. Based on the Q10 factor provided by Winkler et al. [1996], assuming soil
respiration rates to be 25 % smaller during the glacial maximum just due to the temperature
change appears reasonable. Using the same parameter POD to characterize the effect of oxygen
depletion for the entire dataset unlikely reflects the physical conditions.
69

Chapter 7
Summary
The results of this study’s measurements confirm that O2 and CO2 concentrations within the
soil atmosphere fluctuate strongly. The measured changes in noble gas concentrations should
not be neglected when calculating paleotemperatures from dissolved noble gas concentrations in
ground water. These changes are clearly correlated to the deviation of O2+CO2 concentration
from the atmospheric value. The combination of noble gas, O2 and CO2 readings implies that
the change in noble gas concentrations might be dependent on isotope mass, for reasons hitherto
unknown. It should be noted that the measurements of both the lightest isotope 3 He as well as
the two heaviest isotopes 84 Kr and 132 Xe suffer from low accuracy and significant scatter.
However, the observed increases in noble gas concentrations at this study’s sampling site were
not large enough to entirely account for deviations of noble gas temperatures and mean annual
air temperatures as observed by Ma et al. [2004] and Hall et al. [2005] in studies of recent ground
waters that prompted the proposition of the oxygen depletion model to better describe the excess
air component of dissolved noble gases. It is questionable whether it is reasonable to transfer and
compare these results directly to any ground water recharge area, as the processes controlling O2
consumption and CO2 production as well as removal are manifold and complicated. Variations of
diverse parameters on local as well as temporal scales have strong influences on the magnitude
of soil respiration and thereby on the noble gas concentrations of soil atmospheres. Due to
these mostly meteorological influences, soil respiration probably does not influence the absolute
calculated noble gas temperatures by introducing a constant offset but rather by individually
influencing every single data point depending on the local conditions at the recharge area.
This study could therefore confirm that the basic assumption of the OD model as proposed by
Hall et al. [2005] is valid, as noble gas enrichment indeed occurs in natural soil atmospheres and
is able to influence ground water noble gas concentrations significantly. In light of the measured
fluctuations of soil atmosphere compositions and the influence of several different parameters on
microbial activity in the soil, it is however likely that the OD model in its current implementation,
despite delivering statistically good results, does not capture the physical reality of most ground
water recharge sites very well.
71

Chapter 8
Outlook
Though it was successfully shown that noble gas concentrations are indeed influenced by fluctuations
in soil atmosphere composition, some questions remain unanswered and new ones were
raised. One interesting aspect is why there appears to be a mass discrimination when it comes
to the reaction of noble gas concentrations on O2+CO2 changes. The presently available data is
unfortunately quite scarce and of low accuracy, especially at the light and heavy end of the spectrum
of measured noble gas isotopes. Improving accuracy as well as an increase of the dataset
size seems to be called for to confirm this observation. Additionally, the goal of a full annual
dataset could not be achieved due to time constrains, and while the irrigation did provide valuable
insight, it did disturb the natural annual cycle. Therefore a continuation and improvement
of this investigation should be attempted.
During the work on this study several flaws in the construction of the sampling sites became
apparent, leaving only one of three sites intact at the time this thesis was written. Based on the
accumulated experience, improvements to the sampling sites as well as the sampling protocol
are possible. Future sampling sites should consist of a group of boreholes of different depths
in close proximity, each equipped with only one sampling tube. While significantly increasing
initial setup time and effort, this would reduce and compartmentalize the risk of sealing failure.
Increasing sampling depth should be attempted as well, ideally until reaching the ground water
table. Many microbiological processes occur at much deeper depths than those explored in
this study. These might have different influences on the total soil atmosphere composition.
Especially the soil atmosphere just above the capillary fringe would be most interesting to
analyze as it is closest to the aquifer where the last air contact of the infiltrating water occurs.
An automatization of O2 and CO2 measurement would improve the capability to record the
fluctuations the soil atmosphere with increased resolution and might allow resolving diurnal
fluctuations.
Measurement of the noble gas samples should be further improved as well, especially for the
heavier isotopes 84 Kr and 132 Xe. The determination of the sample gas amount by measuring
the inlet pressure needs improvement as well, mainly by increasing the accuracy of both the
pressure the volume measurement.
73

8 Outlook
Considering the manifold of parameters influencing the microbial activity, an expansion of the
sampling sites to different soil environments and climates might help to understand how sensitive
the noble gas concentrations are to changes in these parameters. This might allow for a better
parameterization of the effect of oxygen depletion on noble gas concentrations in ground water.
74

Appendix A
Calculations
A.1 Gas sample size
A.1.1 Vapor pressure of water
Equation from Seinfeld and Pandis [2006].
pH2O[mbar] = φ[%]
100 · p0 H2O[mbar] (A.1)
p 0 H2O[mbar] = 1013.25 · exp [13.3185a − 1.97a 2 − 0.6445a 3 − 0.1299a 4 ] (A.2)
a = 1 − 373.15
TLab[K]
(A.3)
• φ : relative humidity of the sample gas
• p0 H2O : saturated vapor pressure of water
A.1.2 Calculation of sample size using the inlet pressure
�
(pinlet[mbar] − pH2O[mbar]) · VC[ml] −
n(p)[mol] =
mCu[g]
ρCu[ g
cc ]
�
(TLab[ ◦C] + 273.15) · R � �
J · 10000
• n(p) : amount of gas inside the sample tube
molK
• pinlet : pressure inside the inlet volume after cracking the sample tube
• pH2O : water vapor pressure at laboratory temperature
• VC : inlet volume
75
(A.4)

A.1. Gas sample size A Calculations
• mCu : mass of the sample tube
• ρCu : density of copper
• TLab : laboratory temperature
• R : universal gas constant
Gaussian error propagation
(∆pH2O) 2 =
(∆n(P )) 2 =
�
∆a =
373.15
(TLab + 273.15)
2 · ∆TLab
�
∆φ
100 · 1013.25 · exp [13.3185a − 1.97a2 − 0.6445a 3 − 0.1299a 4 ]
�
φ
+
100 · 1013.25 · � 13.3185 − 2 · 1.97a − 3 · 0.6445a 2 − 4 · 0.1299a 3�
· exp � 13.3185a − 1.97a 2 − 0.6445a 3 − 0.1299a 4� · ∆a � 2
VC − mCu
ρCu
· ∆pKeller
(TLab + 273.15) · R · 10000
�
�2 pinlet − pH2O
+
· ∆VC
(TLab + 273.15) · R · 10000
⎛
+ ⎝ (pinlet
�
− pH2O) · VC − mCu
�
ρCu
(TLab + 273.15) 2 · R · 10000
� 2
· ∆TLab
+
�
+
⎞
⎠
�
� 2
VC − mCu
�2 ρCu
· ∆pH2O
(TLab + 273.15) · R · 10000
pinlet − pH2O
· ∆mCu
(TLab + 273.15) · R · ρCu · 10000
A.1.3 Calculation of sample size using the sample tube length
n(L)[mol] = (psample[mbar] − pH2O[mbar]) · V (L)[ml]
(T [ ◦C] + 273.15) · R � �
J · 10000
• n(L) : amount of gas inside the sample tube
• psample : sample pressure inside the copper tube
• pH2O : water vapor pressure during sampling
2
molK
• V (L) : inner volume of the sample tube, see below for calculation
• T : temperature of the soil air during sampling
• R : universal gas constant
76
(A.5)
� 2

A Calculations A.2. Mass spectrometer inlet volume
Calculation of the sample tube volume
The inner volume of the copper sample tubes is calculated using an empirical formula by Wieser
[2006], who characterized the relation of length to volume of copper tubes of the same kind,
squeezed shut using the same method as applied here. The inner volume is calculated from the
length of the copper tube, measured after the sample was extracted:
• L : length of the sample tube
• A = (−0.12284 ± 0.00336) cm 3 : empirical parameter
• B = (0.13583 ± 6.35 × 10 −4 ) cm 2 : empirical parameter
Gaussian error propagation
(∆n(L)) 2 =
V (L)[cm 3 ] = B · L[cm] + A (A.6)
�
V (L)
· ∆psample
(T + 273.15) · R · 10000
�
psample − pH2O
+
· ∆V (L)
(T + 273.15) · R · 10000
A.2 Mass spectrometer inlet volume
� 2
� 2
�
V (L)
+
· ∆pH2O
(T + 273.15) · R · 10000
�
psample − pH2O
+
(T + 273.15) 2 · ∆T
· R · 10000
The volume of the mass spectrometer inlet was volumetrically measured, using the following set
of previously measured [T. Marx, personal note] volumes:
V1 = (38, 876 ± 0, 470) ml
Vkl = (77, 338 ± 0, 040) ml
Volumes V1 and Vkl were connected and flooded with atmospheric air at pressures between 1 and
11 mbar. The inlet volume Vinlet and the unknown volume V2 connecting Vinlet and (V1+Vkl) were
evacuated. All volumes were at the same temperature when the gas was expanded successively
into the evacuated volumes. The pressures p1, p2 and p3 correspond to the volumes (V1 + Vkl),
(V1 + Vkl + V2) and (V1 + Vkl + V2 + Vinlet) respectively. The inlet volume is then calculated using
the following equation:
p1(V1 + Vkl) = p2 [(V1 + Vkl) + V2]
� �
p1
⇒ V2 = (V1 + Vkl) − 1
p1(V1 + Vkl) = p3 [(V1 + Vkl) + V2 + VC]
77
p2
� 2
� 2

A.3. Fractionation-Values A Calculations
For the measured pressures see Table B.6.
Gaussian error propagation
(∆V2) 2 =
(∆Vinlet) 2 =
�� p1
p2
A.3 Fractionation-Values
⇒ Vinlet = p1
(V1 + Vkl) − (V1 + Vkl) − V2
p3
�
p1
= (V1 + Vkl) − 1 −
p3
p1
�
+ 1
p2
� �
p1
= (V1 + Vkl)
� �2 ��
p1
− 1 ∆V1 +
p2
p3
− p1
p2
� �2 − 1 ∆Vkl
�� � �2 ��
(V1 + Vkl) +
∆p1 + −
p2
(V1 + Vkl)p1
p2 2
� �2 ∆p2
��
p1
−
p3
p1
� �2 ��
p1
∆V1 + −
p2
p3
p1
� �2 ∆Vkl
p2
��
(V1 + Vkl) +
−
p3
(V1
� �2 ��
+ Vkl) ∆p1 + −
p2
(V1 + Vkl)p1
p2 2
� �2 ∆p2
��
+ − (V1 + Vkl)p1
p3 2
� �2 ∆p3
The Fractionation-Values are calculated based on Kendrick et al. [2006], but use 40 Ar instead
of 36 Ar as the reference isotope, since in this study’s environment, influences by radiogenic 40 Ar
are negligible.
F X =
�
X
�
�
40Ar sample
� X
�
40Ar air
(A.7)
where X stands for the noble gas isotopes. The F-Value define a mixing line between atmospheric
composition and measured composition, if a sample noble gas isotope has an F-Value of 1 its
volume mixing ratio equals that of atmospheric air.
78

Appendix B
Data
Table B.1: Parameters for fitting noble gas solubilities from Benson and Krause [1976].
Noble gas a0 a1 [ ◦ K] a2 [ ◦ K 2 ]
He -5.0746 -4127.8 627250
Ne -4.2988 -4871.1 793580
Ar -4.2123 -5239.6 995240
Kr -3.6326 -5664.0 1122400
Xe -2.0917 -6693.5 1341700
Table B.2: Results of measuring a test gas comprised of 15.0 % O2, 2.0 % CO2, 2.2 % CH4 and
100 ppm CO using the BM2000. The data indicates that the device slightly overestimates
the O2 levels, but remains well within the given accuracy of 1 %.
CO2 [Vol%] CH4 [Vol%] O2 [Vol%] CO [ppm]
1.8 2.1 15.3 107
1.8 2.1 15.4 107
1.9 2.1 15.5 108
1.9 2.0 15.6 107
1.8 2.1 15.4 106
1.8 2.1 15.3 106
1.8 2.1 15.3 106
1.9 2.1 15.2 106
1.9 2.1 15.2 105
1.9 2.1 15.3 105
1.9 2.1 15.1 104
1.9 2.1 15.1 104
79

Table B.3: Noble gas volume mixing ratios and isotope composition in dry atmospheric air,
compiled by Porcelli et al. [2002].
Noble gas Volume fraction Isotope Relative isotopic
in atmospheric air abundance
He (5.24 ± 0.05)×10 −6 3 He 0.000140
4 He 100
Ne (1.82 ± 0.04)×10 −5 20 Ne 90.5
21 Ne 0.268
22 Ne 9.23
Ar (9.34 ± 0.01)×10 −3 36 Ar 0.3364
38 Ar 0.0632
40 Ar 99.60
Kr (1.14 ± 0.01)×10 −6 78 Kr 0.3469
80 Kr 2.2571
82 Kr 11.523
83 Kr 11.477
84 Kr 57.00
86 Kr 17.398
Xe (8.7 ± 0.1)×10 −8 124 Xe 0.0951
126 Xe 0.0887
128 Xe 1.919
129 Xe 26.44
130 Xe 4.070
131 Xe 21.22
132 Xe 26.89
134 Xe 10.430
136 Xe 8.857
80
B Data

B Data
Table B.4: Calculated values of relative humidity within mass spectrometer inlet for small
sample tube size and sampling temperatures ranging from 0 to 25 ◦ CC, based on an average
sample volume of (0.745 ± 0.028) cm 3 , a temperature uncertainty of ∆T = 5 ◦ C and 100 %
relative humidity of soil air.
T [ ◦ C] φinlet [%] ∆φinlet [%]
0 0.6 0.3
1 0.7 0.3
2 0.7 0.3
3 0.8 0.4
4 0.8 0.4
5 0.9 0.4
6 0.9 0.4
7 1.0 0.5
8 1.0 0.5
9 1.1 0.5
10 1.2 0.5
11 1.3 0.6
12 1.4 0.6
13 1.5 0.6
14 1.5 0.7
15 1.6 0.7
16 1.7 0.8
17 1.9 0.8
18 2.0 0.9
19 2.1 0.9
20 2.2 1.0
21 2.3 1.0
22 2.5 1.1
23 2.6 1.1
24 2.8 1.2
25 2.9 1.2
81

Table B.5: Calculated values of relative humidity within mass spectrometer inlet for large
sample tubes and sampling temperatures ranging from 0 to 25 ◦ C, based on an average
sample volume of (1.579 ± 0.029) cm 3 , a temperature uncertainty of ∆T = 5 ◦ C and 100 %
relative humidity of soil air.
T [ ◦ C] φinlet [%] ∆φinlet [%]
0 1.3 0.4
1 1.4 0.4
2 1.5 0.4
3 1.6 0.4
4 1.7 0.5
5 1.8 0.5
6 2.0 0.5
7 2.1 0.6
8 2.2 0.6
9 2.4 0.6
10 2.5 0.7
11 2.7 0.7
12 2.9 0.8
13 3.1 0.8
14 3.3 0.9
15 3.5 0.9
16 3.7 1.0
17 3.9 1.0
18 4.2 1.1
19 4.4 1.1
20 4.7 1.2
21 5.0 1.3
22 5.2 1.4
23 5.6 1.4
24 5.9 1.5
25 6.2 1.6
82
B Data

B Data
Table B.6: Results of the volumetric measurements done to calculate the inlet volume Vinlet
for the setup during the measuring runs 1 – 3 (M22 – M33) and run 4 (M42 – M56), which
featured a slightly different setup. Measurements M1 to M21 and M34 to M41 were omitted
due to systematic errors.
ID p1 [mbar] p2 [mbar] p3 [mbar]
M22 2.206 1.738 1.472
M23 5.191 4.088 3.462
M24 9.094 7.161 6.062
M25 9.464 7.448 6.303
M26 9.864 7.760 6.565
M27 6.981 5.490 4.642
M28 4.935 3.880 3.284
M29 3.492 2.747 2.324
M30 3.470 2.728 2.308
M31 2.452 1.927 1.630
M32 4.759 3.740 3.161
M33 7.838 6.162 5.210
M42 8.912 7.025 5.936
M43 3.935 3.101 2.621
M44 10.770 8.487 7.166
M45 5.051 3.977 3.359
M46 8.848 6.966 5.883
M47 9.503 7.484 6.320
M48 6.716 5.288 4.462
M49 4.757 3.747 3.162
M50 3.366 2.651 2.239
M51 6.002 4.722 3.986
M52 10.680 8.409 7.098
M53 4.694 3.696 3.120
M54 7.407 5.829 4.921
M55 10.580 8.336 7.034
M56 8.557 6.733 5.682
Table B.7: Minimum, maximum and average relative errors ∆ of the noble gas isotope gas
amount measurements from the mass spectrometer before recalculation to concentrations.
The low accuracy of the 132 Xe measurements was heavily influenced by 132 Xe calibration
measurements splitting in two distinct branches for reasons unknown.
3 He [%] 4 He [%] 20 Ne [%] 22 Ne [%] 36 Ar [%] 40 Ar [%] 84 Kr [%] 132 Xe [%]
∆min 1.71 0.44 0.24 0.34 1.39 1.08 1.86 2.84
∆avg 1.89 0.46 0.29 0.42 1.48 1.09 2.13 3.26
∆max 2.77 0.60 0.43 0.78 1.82 1.36 2.62 4.68
83

Table B.8: Precipitation record of the months February, March and April in the past 20
years, recorded by a Deutscher Wetterdienst weather station (ID 10729) near Mannheim.
The total precipitation during these months in 2011, 53.0 mm is well below the 20 year
average of 133.2 mm.
Precipitation [mm]
Year February March April Total
1991 18.3 35.2 27.4 80.9
1992 36.3 43.7 38.5 118.5
1993 9.7 23.0 23.8 56.5
1994 30.9 56.9 63.2 151.0
1995 37.4 53.6 98.5 189.5
1996 52.0 31.2 13.8 97.0
1997 49.7 28.6 34.0 112.3
1998 24.4 33.8 106.8 165.0
1999 61.7 73.6 42.8 178.1
2000 59.3 66.3 41.9 167.5
2001 57.4 125.7 56.0 239.1
2002 105.8 41.6 50.6 198.0
2003 10.3 27.7 17.6 55.6
2004 28.9 22.8 20.0 71.7
2005 59.0 28.8 71.2 159.0
2006 22.2 64.6 43.7 130.5
2007 72.0 70.1 0.7 142.8
2008 44.4 59.1 72.0 175.5
2009 61.2 54.7 44.6 160.5
2010 35.8 35.7 23.3 94.8
2011 23.7 16.3 13.0 53.0
� 42.9 47.3 43.0 133.2
84
B Data

B Data
Table B.9: Complete dataset (Offset corrected) of noble gases measured at Site A. Values
marked red were excluded from analysis. Values (except ratios) are given in % atmospheric
air, meaning they are standardized to atmospheric air noble gas concentrations taken from
Porcelli et al. [2002].
!" #$%&'()*+"$,- .-/0.-1 2.-/0.-1 3-4503-44 23-4503-44 6715067/8 26715067/8 .-103-45 2.-103-45 .-/ 2.-/ .-1 2.-1 3-45 23-45 3-44 23-44 67/8 267/8 6715 26715 97:1 297:1 ;-

Table B.10: Complete dataset of noble gases measured at Site B and Site C. Values (except
ratios) are given in % atmospheric air, meaning they are standardized to atmospheric air
noble gas concentrations taken from Porcelli et al. [2002].
!" #$%&'()*+"$,- .-/0.-1 2.-/0.-1 3-4503-44 23-4503-44 6715067/8 26715067/8 .-103-45 2.-103-45 .-/ 2.-/ .-1 2.-1 3-45 23-45 3-44 23-44 67/8 267/8 6715 26715 97:1 297:1 ;-

B Data
Table B.11: Complete dataset of O2 and CO2 concentrations measured at Site A. All values
are given in Vol%. NG ID identifies the noble gas sample ID corresponding to those O2 and
CO2 readings.
Date NG ID
2m 4m 6m 2m 4m 6m
2m 4m 6m
O2 ΔO2 O2 ΔO2 O2 ΔO2 CO2 ΔCO2 CO2 ΔCO2 CO2 ΔCO2 O2+CO2 ΔO2+CO2 O2+CO2 ΔO2+CO2 O2+CO2 ΔO2+CO2
15.02.11 A11 17.9 1.0 17.8 1.0 17.3 1.0 4.6 0.5 4.7 0.5 4.7 0.5 22.5 1.1 22.5 1.1 22.0 1.1
26.02.11 A12 19.1 1.0 19.0 1.0 18.6 1.0 4.4 0.5 4.5 0.5 4.5 0.5 23.5 1.1 23.5 1.1 23.1 1.1
28.03.11 A13 18.1 1.0 18.3 1.0 18.6 1.0 3.7 0.5 3.7 0.5 3.6 0.5 21.8 1.1 22.0 1.1 22.2 1.1
30.03.11 17.0 1.0 17.3 1.0 17.3 1.0 3.3 0.5 3.7 0.5 3.6 0.5 20.3 1.1 21.0 1.1 20.9 1.1
07.04.11 A14 17.7 1.0 17.5 1.0 18.0 1.0 3.6 0.5 3.5 0.5 3.4 0.5 21.3 1.1 21.0 1.1 21.4 1.1
12.04.11 A15 18.7 1.0 18.2 1.0 18.7 1.0 4.0 0.5 4.0 0.5 3.8 0.5 22.7 1.1 22.2 1.1 22.5 1.1
22.04.11 A16 17.0 1.0 17.9 1.0 18.5 1.0 3.6 0.5 3.5 0.5 3.4 0.5 20.6 1.1 21.4 1.1 21.9 1.1
28.04.11 17.6 1.0 16.2 1.0 17.6 1.0 3.8 0.5 3.9 0.5 3.6 0.5 21.4 1.1 20.1 1.1 21.2 1.1
04.05.11 18.5 1.0 17.9 1.0 17.9 1.0 3.3 0.5 3.5 0.5 3.4 0.5 21.8 1.1 21.4 1.1 21.3 1.1
05.05.11 18.1 1.0 17.1 1.0 16.8 1.0 3.2 0.5 3.4 0.5 3.4 0.5 21.3 1.1 20.5 1.1 20.2 1.1
09.05.11 18.8 1.0 18.2 1.0 17.7 1.0 2.8 0.5 3.0 0.5 3.3 0.5 21.6 1.1 21.2 1.1 21.0 1.1
09.05.11 18.4 1.0 17.8 1.0 17.4 1.0 2.4 0.5 3.1 0.5 3.3 0.5 20.8 1.1 20.9 1.1 20.7 1.1
09.05.11 17.6 1.0 17.4 1.0 17.1 1.0 3.0 0.5 2.9 0.5 3.1 0.5 20.6 1.1 20.3 1.1 20.2 1.1
09.05.11 17.9 1.0 17.5 1.0 17.3 1.0 3.2 0.5 3.1 0.5 3.2 0.5 21.1 1.1 20.6 1.1 20.5 1.1
09.05.11 18.1 1.0 18.1 1.0 18.1 1.0 3.6 0.5 3.1 0.5 3.2 0.5 21.7 1.1 21.2 1.1 21.3 1.1
10.05.11 17.0 1.0 17.2 1.0 17.6 1.0 3.7 0.5 3.6 0.5 3.3 0.5 20.7 1.1 20.8 1.1 20.9 1.1
10.05.11 17.0 1.0 17.1 1.0 17.4 1.0 2.0 0.5 3.2 0.5 3.3 0.5 19.0 1.1 20.3 1.1 20.7 1.1
10.05.11 A17 17.1 1.0 17.2 1.0 17.5 1.0 2.4 0.5 3.3 0.5 3.2 0.5 19.5 1.1 20.5 1.1 20.7 1.1
10.05.11 16.9 1.0 17.2 1.0 17.5 1.0 2.6 0.5 3.2 0.5 3.1 0.5 19.5 1.1 20.4 1.1 20.6 1.1
11.05.11 15.3 1.0 16.6 1.0 17.4 1.0 3.9 0.5 3.7 0.5 3.3 0.5 19.2 1.1 20.3 1.1 20.7 1.1
11.05.11 A18 15.0 1.0 16.7 1.0 17.4 1.0 2.5 0.5 3.4 0.5 3.3 0.5 17.5 1.1 20.1 1.1 20.7 1.1
11.05.11 15.3 1.0 17.1 1.0 17.6 1.0 2.8 0.5 3.4 0.5 3.3 0.5 18.1 1.1 20.5 1.1 20.9 1.1
11.05.11 15.7 1.0 17.2 1.0 17.7 1.0 3.0 0.5 3.3 0.5 3.2 0.5 18.7 1.1 20.5 1.1 20.9 1.1
12.05.11 14.4 1.0 16.7 1.0 18.1 1.0 4.2 0.5 3.8 0.5 3.4 0.5 18.6 1.1 20.5 1.1 21.5 1.1
12.05.11 14.4 1.0 17.3 1.0 18.0 1.0 4.2 0.5 3.7 0.5 3.4 0.5 18.6 1.1 21.0 1.1 21.4 1.1
12.05.11 13.8 1.0 16.9 1.0 17.7 1.0 4.2 0.5 3.7 0.5 3.4 0.5 18.0 1.1 20.6 1.1 21.1 1.1
13.05.11 13.4 1.0 16.1 1.0 17.5 1.0 4.5 0.5 3.9 0.5 3.4 0.5 17.9 1.1 20.0 1.1 20.9 1.1
13.05.11 A19 13.4 1.0 16.9 1.0 18.3 1.0 3.3 0.5 3.8 0.5 3.4 0.5 16.7 1.1 20.7 1.1 21.7 1.1
13.05.11 13.5 1.0 17.0 1.0 17.8 1.0 3.5 0.5 3.7 0.5 3.4 0.5 17.0 1.1 20.7 1.1 21.2 1.1
13.05.11 13.5 1.0 16.8 1.0 17.4 1.0 3.6 0.5 3.7 0.5 3.4 0.5 17.1 1.1 20.5 1.1 20.8 1.1
13.05.11 13.9 1.0 17.1 1.0 17.7 1.0 3.8 0.5 3.7 0.5 3.3 0.5 17.7 1.1 20.8 1.1 21.0 1.1
13.05.11 14.0 1.0 17.3 1.0 18.0 1.0 4.0 0.5 3.7 0.5 3.4 0.5 18.0 1.1 21.0 1.1 21.4 1.1
14.05.11 13.1 1.0 16.9 1.0 18.1 1.0 4.6 0.5 3.8 0.5 3.4 0.5 17.7 1.1 20.7 1.1 21.5 1.1
14.05.11 A20 12.6 1.0 16.1 1.0 16.8 1.0 4.6 0.5 3.7 0.5 3.3 0.5 17.2 1.1 19.8 1.1 20.1 1.1
14.05.11 13.0 1.0 17.2 1.0 18.0 1.0 4.6 0.5 3.8 0.5 3.4 0.5 17.6 1.1 21.0 1.1 21.4 1.1
14.05.11 12.9 1.0 17.1 1.0 17.8 1.0 4.7 0.5 3.8 0.5 3.4 0.5 17.6 1.1 20.9 1.1 21.2 1.1
14.05.11 12.5 1.0 16.1 1.0 18.1 1.0 4.8 0.5 4.0 0.5 3.4 0.5 17.3 1.1 20.1 1.1 21.5 1.1
15.05.11 12.0 1.0 15.6 1.0 17.5 1.0 5.0 1.0 4.1 0.5 3.4 0.5 17.0 1.4 19.7 1.1 20.9 1.1
15.05.11 12.3 1.0 17.0 1.0 18.2 1.0 5.0 1.0 4.0 0.5 3.4 0.5 17.3 1.4 21.0 1.1 21.6 1.1
15.05.11 12.2 1.0 17.1 1.0 18.0 1.0 5.0 1.0 3.9 0.5 3.4 0.5 17.2 1.4 21.0 1.1 21.4 1.1
15.05.11 11.9 1.0 16.3 1.0 17.6 1.0 5.0 1.0 4.0 0.5 3.4 0.5 16.9 1.4 20.3 1.1 21.0 1.1
15.05.11 12.1 1.0 15.9 1.0 18.2 1.0 5.1 1.0 4.2 0.5 3.4 0.5 17.2 1.4 20.1 1.1 21.6 1.1
15.05.11 12.2 1.0 16.1 1.0 18.1 1.0 5.1 1.0 4.2 0.5 3.4 0.5 17.3 1.4 20.3 1.1 21.5 1.1
16.05.11 12.0 1.0 16.0 1.0 18.3 1.0 5.2 1.0 4.3 0.5 3.4 0.5 17.2 1.4 20.3 1.1 21.7 1.1
16.05.11 11.9 1.0 16.2 1.0 17.9 1.0 5.2 1.0 4.1 0.5 3.4 0.5 17.1 1.4 20.3 1.1 21.3 1.1
16.05.11 12.0 1.0 17.1 1.0 18.0 1.0 5.2 1.0 3.9 0.5 3.4 0.5 17.2 1.4 21.0 1.1 21.4 1.1
16.05.11 12.7 1.0 17.2 1.0 17.8 1.0 5.1 1.0 3.8 0.5 3.4 0.5 17.8 1.4 21.0 1.1 21.2 1.1
16.05.11 12.7 1.0 17.2 1.0 17.9 1.0 5.1 1.0 3.8 0.5 3.4 0.5 17.8 1.4 21.0 1.1 21.3 1.1
17.05.11 11.8 1.0 15.5 1.0 17.7 1.0 5.4 1.0 4.3 0.5 3.4 0.5 17.2 1.4 19.8 1.1 21.1 1.1
17.05.11 11.9 1.0 16.2 1.0 18.0 1.0 5.4 1.0 4.2 0.5 3.5 0.5 17.3 1.4 20.4 1.1 21.5 1.1
17.05.11 11.5 1.0 16.1 1.0 17.5 1.0 5.4 1.0 4.1 0.5 3.4 0.5 16.9 1.4 20.2 1.1 20.9 1.1
17.05.11 11.7 1.0 16.9 1.0 17.9 1.0 5.5 1.0 3.9 0.5 3.4 0.5 17.2 1.4 20.8 1.1 21.3 1.1
18.05.11 11.9 1.0 15.7 1.0 18.0 1.0 5.6 1.0 4.4 0.5 3.5 0.5 17.5 1.4 20.1 1.1 21.5 1.1
18.05.11 11.7 1.0 15.0 1.0 17.3 1.0 5.7 1.0 4.5 0.5 3.5 0.5 17.4 1.4 19.5 1.1 20.8 1.1
18.05.11 A21 11.8 1.0 15.3 1.0 17.0 1.0 5.6 1.0 4.4 0.5 3.4 0.5 17.4 1.4 19.7 1.1 20.4 1.1
18.05.11 A22 12.0 1.0 16.5 1.0 17.7 1.0 5.3 1.0 4.3 0.5 3.5 0.5 17.3 1.4 20.8 1.1 21.2 1.1
18.05.11 12.2 1.0 16.7 1.0 17.5 1.0 5.3 1.0 4.1 0.5 3.5 0.5 17.5 1.4 20.8 1.1 21.0 1.1
18.05.11 12.2 1.0 16.5 1.0 17.2 1.0 5.2 1.0 3.9 0.5 3.4 0.5 17.4 1.4 20.4 1.1 20.6 1.1
19.05.11 10.9 1.0 15.8 1.0 17.5 1.0 5.7 1.0 4.2 0.5 3.5 0.5 16.6 1.4 20.0 1.1 21.0 1.1
19.05.11 10.9 1.0 16.0 1.0 17.1 1.0 5.7 1.0 4.1 0.5 3.4 0.5 16.6 1.4 20.1 1.1 20.5 1.1
19.05.11 11.0 1.0 15.9 1.0 17.5 1.0 5.8 1.0 4.2 0.5 3.5 0.5 16.8 1.4 20.1 1.1 21.0 1.1
20.05.11 11.1 1.0 15.1 1.0 17.7 1.0 6.0 1.0 4.7 0.5 3.5 0.5 17.1 1.4 19.8 1.1 21.2 1.1
20.05.11 11.0 1.0 14.9 1.0 17.3 1.0 6.0 1.0 4.6 0.5 3.5 0.5 17.0 1.4 19.5 1.1 20.8 1.1
20.05.11 A23 11.1 1.0 16.0 1.0 17.8 1.0 5.9 1.0 4.3 0.5 3.5 0.5 17.0 1.4 20.3 1.1 21.3 1.1
21.05.11 15.9 1.0 17.0 1.0 17.8 1.0 4.3 0.5 3.8 0.5 3.4 0.5 20.2 1.1 20.8 1.1 21.2 1.1
22.05.11 11.3 1.0 16.2 1.0 17.2 1.0 5.5 1.0 3.8 0.5 3.3 0.5 16.8 1.4 20.0 1.1 20.5 1.1
23.05.11 11.1 1.0 15.5 1.0 17.1 1.0 6.0 1.0 4.3 0.5 3.4 0.5 17.1 1.4 19.8 1.1 20.5 1.1
24.05.11 11.0 1.0 14.3 1.0 17.4 1.0 6.6 1.0 5.1 1.0 3.5 0.5 17.6 1.4 19.4 1.4 20.9 1.1
25.05.11 11.1 1.0 14.0 1.0 17.1 1.0 6.7 1.0 5.3 1.0 3.5 0.5 17.8 1.4 19.3 1.4 20.6 1.1
26.05.11 11.4 1.0 13.2 1.0 16.4 1.0 6.8 1.0 5.6 1.0 3.4 0.5 18.2 1.4 18.8 1.4 19.8 1.1
26.05.11 11.9 1.0 14.4 1.0 17.5 1.0 6.8 1.0 5.3 1.0 3.5 0.5 18.7 1.4 19.7 1.4 21.0 1.1
27.05.11 12.2 1.0 14.0 1.0 16.5 1.0 6.7 1.0 5.3 1.0 3.5 0.5 18.9 1.4 19.3 1.4 20.0 1.1
28.05.11 12.8 1.0 14.5 1.0 17.0 1.0 6.7 1.0 5.3 1.0 3.5 0.5 19.5 1.4 19.8 1.4 20.5 1.1
29.05.11 13.1 1.0 15.3 1.0 17.4 1.0 6.6 1.0 5.0 1.0 3.5 0.5 19.7 1.4 20.3 1.4 20.9 1.1
30.05.11 13.4 1.0 15.2 1.0 17.4 1.0 6.6 1.0 5.2 1.0 3.6 0.5 20.0 1.4 20.4 1.4 21.0 1.1
31.05.11 14.0 1.0 15.5 1.0 17.3 1.0 6.4 1.0 4.9 0.5 3.6 0.5 20.4 1.4 20.4 1.1 20.9 1.1
01.06.11 14.3 1.0 15.4 1.0 17.1 1.0 6.3 1.0 5.0 1.0 3.6 0.5 20.6 1.4 20.4 1.4 20.7 1.1
02.06.11 14.8 1.0 15.0 1.0 16.9 1.0 6.2 1.0 5.5 1.0 3.6 0.5 21.0 1.4 20.5 1.4 20.5 1.1
31.05.11 14.5 1.0 14.5 1.0 15.9 1.0 6.1 1.0 5.3 1.0 3.6 0.5 20.6 1.4 19.8 1.4 19.5 1.1
31.05.11 15.1 1.0 15.3 1.0 17.0 1.0 6.2 1.0 5.3 1.0 3.6 0.5 21.3 1.4 20.6 1.4 20.6 1.1
01.06.11 15.6 1.0 15.7 1.0 17.3 1.0 5.7 1.0 5.2 1.0 3.7 0.5 21.3 1.4 20.9 1.4 21.0 1.1
02.06.11 15.3 1.0 15.4 1.0 16.8 1.0 5.6 1.0 5.1 1.0 3.7 0.5 20.9 1.4 20.5 1.4 20.5 1.1
03.06.11 15.5 1.0 15.0 1.0 16.1 1.0 5.7 1.0 5.4 1.0 3.6 0.5 21.2 1.4 20.4 1.4 19.7 1.1
04.06.11 15.6 1.0 15.5 1.0 16.6 1.0 6.0 1.0 5.3 1.0 3.6 0.5 21.6 1.4 20.8 1.4 20.2 1.1
06.06.11 16.5 1.0 16.0 1.0 16.9 1.0 5.3 1.0 5.5 1.0 3.7 0.5 21.8 1.4 21.5 1.4 20.6 1.1
07.06.11 16.2 1.0 16.1 1.0 16.8 1.0 5.6 1.0 5.2 1.0 3.7 0.5 21.8 1.4 21.3 1.4 20.5 1.1
08.06.11 17.1 1.0 16.7 1.0 17.1 1.0 5.0 1.0 5.1 1.0 3.7 0.5 22.1 1.4 21.8 1.4 20.8 1.1
09.06.11 16.4 1.0 16.0 1.0 16.6 1.0 5.2 1.0 4.9 0.5 3.7 0.5 21.6 1.4 20.9 1.1 20.3 1.1
10.06.11 16.7 1.0 16.2 1.0 16.7 1.0 5.1 1.0 4.9 0.5 3.7 0.5 21.8 1.4 21.1 1.1 20.4 1.1
11.06.11 17.0 1.0 16.7 1.0 16.9 1.0 4.9 0.5 4.7 0.5 3.8 0.5 21.9 1.1 21.4 1.1 20.7 1.1
13.06.11 17.2 1.0 16.8 1.0 16.8 1.0 4.6 0.5 4.5 0.5 3.7 0.5 21.8 1.1 21.3 1.1 20.5 1.1
14.06.11 17.9 1.0 17.5 1.0 16.8 1.0 4.0 0.5 4.2 0.5 3.7 0.5 21.9 1.1 21.7 1.1 20.5 1.1
14.06.11 17.1 1.0 16.5 1.0 16.6 1.0 4.4 0.5 4.2 0.5 3.7 0.5 21.5 1.1 20.7 1.1 20.3 1.1
14.06.11 17.3 1.0 16.9 1.0 16.7 1.0 4.5 0.5 4.4 0.5 3.7 0.5 21.8 1.1 21.3 1.1 20.4 1.1
15.06.11 17.6 1.0 17.0 1.0 16.5 1.0 4.0 0.5 4.1 0.5 3.7 0.5 21.6 1.1 21.1 1.1 20.2 1.1
15.06.11 17.0 1.0 16.5 1.0 16.6 1.0 4.8 0.5 4.5 0.5 3.7 0.5 21.8 1.1 21.0 1.1 20.3 1.1
16.06.11 17.5 1.0 16.6 1.0 16.6 1.0 4.2 0.5 4.3 0.5 3.8 0.5 21.7 1.1 20.9 1.1 20.4 1.1
16.06.11 17.8 1.0 17.4 1.0 16.8 1.0 3.9 0.5 4.1 0.5 3.7 0.5 21.7 1.1 21.5 1.1 20.5 1.1
17.06.11 17.4 1.0 16.8 1.0 16.6 1.0 4.1 0.5 4.2 0.5 3.8 0.5 21.5 1.1 21.0 1.1 20.4 1.1
18.06.11 17.5 1.0 17.1 1.0 16.7 1.0 4.1 0.5 4.2 0.5 3.9 0.5 21.6 1.1 21.3 1.1 20.6 1.1
20.06.11 17.3 1.0 17.2 1.0 16.6 1.0 4.4 0.5 4.2 0.5 3.9 0.5 21.7 1.1 21.4 1.1 20.5 1.1
21.06.11 17.6 1.0 17.2 1.0 16.3 1.0 3.9 0.5 4.0 0.5 3.9 0.5 21.5 1.1 21.2 1.1 20.2 1.1
22.06.11 17.4 1.0 17.3 1.0 16.2 1.0 3.7 0.5 3.7 0.5 4.0 0.5 21.1 1.1 21.0 1.1 20.2 1.1
23.06.11 16.7 1.0 16.4 1.0 16.0 1.0 4.6 0.5 4.2 0.5 4.0 0.5 21.3 1.1 20.6 1.1 20.0 1.1
24.06.11 A24 17.5 1.0 17.3 1.0 16.6 1.0 3.9 0.5 4.0 0.5 4.0 0.5 21.4 1.1 21.3 1.1 20.6 1.1
24.06.11 17.4 1.0 16.6 1.0 16.3 1.0 4.3 0.5 4.2 0.5 4.0 0.5 21.7 1.1 20.8 1.1 20.3 1.1
27.06.11 17.9 1.0 17.4 1.0 16.1 1.0 3.5 0.5 3.8 0.5 4.0 0.5 21.4 1.1 21.2 1.1 20.1 1.1
27.06.11 17.8 1.0 17.3 1.0 16.0 1.0 3.5 0.5 3.8 0.5 4.0 0.5 21.3 1.1 21.1 1.1 20.0 1.1
28.06.11 18.0 1.0 17.7 1.0 16.0 1.0 3.2 0.5 3.4 0.5 4.0 0.5 21.2 1.1 21.1 1.1 20.0 1.1
28.06.11 17.6 1.0 17.2 1.0 15.8 1.0 3.4 0.5 3.5 0.5 3.9 0.5 21.0 1.1 20.7 1.1 19.7 1.1
87

Appendix C
Additional plots and figures
Figure C.1: Detailed view of the perforated tip of a sampling tube through which the soil
atmosphere was sampled. Installing finer filters to shield the tube from infiltration of sludge
was deemed unnecessary based on laboratory experiments with fully saturated soil where
sufficient flow rates were achieved. This was confirmed at Site C’s 2 m depth tube, where
the pump rates through the tube remained viable even after part of the tube was filled with
soil after pumping sludge/water upwards and had dried up inside.
89

Figure C.2: Taking samples at Site A in December 2010.
Figure C.3: Taking samples at Site B in April 2011.
90
C Additional plots and figures

C Additional plots and figures
Figure C.4: Copper sample tubes, ∼0.7 cc variety (top) and ∼1.5 cc variety (bottom).
Figure C.5: Accessing the LogTag data loggers at Site A.
91

C Additional plots and figures
Figure C.6: Continuous O2 and CO2 measurements at Site A, showing O2 and CO2 each
reaching a constant value soon after initiation of pumping. Accuracies are 1 % for O2 and
0.5 % for CO2, error bars have been omitted for better visibility.
�� � �� � � � � � � � � � ��
�� � � � �� � �� � �� ���� � ����� � �� � �� �� �� � ��� � ��
Figure C.7: All atmospheric O2 measurements taken at Site A and Site B with the BM2000
over time, the error weighted mean fit gives (20.89 ± 0.04) Vol% O2.
92

C Additional plots and figures
� � � � � � � � � � � ��� � �
Figure C.8: Temperature measurements taken at Site A at 0.1 m, 1.0 m and 2.5 m depth
and sinusoidal fits. Depth placement accuracy is ±0.1 m, temperature accuracy is ±0.5 ◦ C.
The atmospheric daily mean temperatures were provided by meteomedia, measured by a
weather station close to Site A. The offset visible at 1.0 m depth in August 2010 is caused
by a moisture intrusion into the sensor in August 2010 after refilling the borehole with
sludge. Comparison with the data from Site B leads to the conclusion that the sensor was
affected by this until early October 2010. The smaller offset at 2.5 m depth in December 2010
and January 2011 coincide with heavy precipitation (Figure C.10). The low atmospheric
temperatures at the time indicate that this also is an offset caused by moisture intrusion
rather than an actual temperature change by infiltrating rain water of different temperature.
Such an event is visible in May 2011, when cold tap water was used for irrigation, leading to
spikes in the temperature curves of 1.0 m and 2.5 m. The sensor at 0.1 m depth was shielded
against these sudden and short-lived temperature changes by being insulated by air inside
the instrumentation box.
93

C Additional plots and figures
Figure C.9: Model data of daily top soil moisture of Europe for May 29 th , 2011, provided
by the European Commission Joint Research Centre Institute for Environment and Sustainability
(http://edo.jrc.ec.europa.eu/php/index.php?action=viewid=20). Based
on measured meteorological data from JRC-MARS (http://www.marsop.info/marsop3)
94

C Additional plots and figures
Figure C.10: Daily sum of precipitation and daily mean relative humidity, provided by
meteomedia’s weather station at Site A.
� � �� �� �� ��
� � �� �� �� ��
Figure C.11: Noble gas concentrations of atmospheric air samples relative to literature values
from Porcelli et al. [2002], for 84 Kr and 132 Xe.
95

C Additional plots and figures
Figure C.12: Depth profile of O2 and CO2 at a one-time borehole on August 11th, 2009
within a radius of 10 m of Site A, based on data by Schneider [2010].
96

C Additional plots and figures
O 2 [Vol%]
CO 2 [Vol%]
O 2 + CO 2 [Vol%]
20
19
18
17
16
15
14
13
12
11
10
7
6
5
4
3
2
24
23
22
21
20
19
18
17
16
15
2m
4m
6m
2m
4m
6m
Feb Mar Apr May Jun
2m
4m
6m
Month, 2011
Feb Mar Apr May Jun
Month, 2011
Feb Mar Apr May Jun
Month, 2011
Figure C.13: Concentrations of O2, CO2 and O2+CO2 at Site A during February to June
2011. Accuracies are 1 % for O2 and 0.5 % for CO2 below 5 % absolute and 1 % above 5 %,
error bars have been omitted for better visibility.
97

O 2 [Vol%]
CO 2 [Vol%]
O 2 + CO 2 [Vol%]
20
19
18
17
16
15
14
13
12
11
10
7
6
5
4
3
2
23
22
21
20
19
18
17
16
2m
4m
6m
2m
4m
6m
15
9 May 11 May 13 May 15 May 17 May 19 May
Date, 2011
C Additional plots and figures
Figure C.14: Concentrations of O2, CO2 and O2+CO2 at Site A during the irrigation
period. Accuracies are 1 % for O2 and 0.5 % for CO2 below 5 % absolute and 1 % above 5 %,
error bars have been omitted for better visibility.
98
2m
4m
6m

C Additional plots and figures
4
He [% atm. air]
4
He [% atm. air]
4
He [% atm. air]
Figure C.15: Concentrations of O2 and CO2 at Site B. Accuracies are 1 % for O2 and 0.5 %
for CO2 error bars have been omitted for better visibility.
Oct Nov Apr May
110
105
100
95
90
105
100
95
90
105
100
95
B06 at 1 m depth
B06 at 3 m depth
A23 at 2 m depth
90
Oct Nov Apr May
Date of measurement in mass spectrometer
20
Ne [% atm. air]
20
Ne [% atm. air]
20
Ne [% atm. air]
Oct Nov Apr May
110
105
100
95
90
105
100
95
90
105
100
95
B06 at 1 m depth
B06 at 3 m depth
A23 at 2 m depth
90
Oct Nov Apr May
Date of measurement in mass spectrometer
Figure C.16: Concentrations of 4 He and 20 Ne of samples that were measured multiple times,
relative to atmospheric literature values from Porcelli et al. [2002], in relation to their date
of measuring.
99

3
He (2m) [% atm. air]
3
He (4m) [% atm. air]
3
He (6m) [% atm. air]
84
Kr (2m) [% atm. air]
84
Kr (4m) [% atm. air]
84
Kr (6m) [% atm. air]
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Date
4
He (2m) [% atm. air]
4
He (4m) [% atm. air]
4
He (6m) [% atm. air]
132
Xe (2m) [% atm. air]
132
Xe (4m) [% atm. air]
132
Xe (6m) [% atm. air]
110
105
100
95
90
C Additional plots and figures
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
115
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Figure C.17: Concentrations of 3 He, 4 He, 84 Kr and 132 Xe in soil atmosphere samples from
Site A over time, relative to atmospheric literature values from Porcelli et al. [2002].
100
Date

C Additional plots and figures
20
Ne (1m) [% atm. air]
20
Ne (3m) [% atm. air]
20
Ne (5m) [% atm. air]
36
Ar (1m) [% atm. air]
36
Ar (3m) [% atm. air]
36
Ar (5m) [% atm. air]
Aug Sep Oct Nov Dec Jan
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan
Date
22
Ne (1m) [% atm. air]
22
Ne (3m) [% atm. air]
22
Ne (5m) [% atm. air]
40
Ar (1m) [% atm. air]
40
Ar (3m) [% atm. air]
40
Ar (5m) [% atm. air]
Aug Sep Oct Nov Dec Jan
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan
Figure C.18: Concentrations of 20 Ne, 22 Ne, 36 Ar and 40 Ar in soil atmosphere samples from
Site B over time, relative to atmospheric literature values from Porcelli et al. [2002].
101
Date

3
He (1m) [% atm. air]
3
He (3m) [% atm. air]
3
He (5m) [% atm. air]
84
Kr (1m) [% atm. air]
84
Kr (3m) [% atm. air]
84
Kr (5m) [% atm. air]
Aug Sep Oct Nov Dec Jan
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan
Date
4
He (1m) [% atm. air]
4
He (3m) [% atm. air]
4
He (5m) [% atm. air]
132
Xe (1m) [% atm. air]
132
Xe (3m) [% atm. air]
132
Xe (5m) [% atm. air]
110
105
100
95
90
C Additional plots and figures
Aug Sep Oct Nov Dec Jan
115
110
105
100
95
90
110
105
100
95
90
115
110
105
100
95
90
110
105
100
95
90
110
105
100
95
90
Aug Sep Oct Nov Dec Jan
Figure C.19: Concentrations of 3 He, 4 He, 84 Kr and 132 Xe in soil atmosphere samples from
Site B over time, relative to atmospheric literature values from Porcelli et al. [2002].
102
Date

C Additional plots and figures
Figure C.20: 20 Ne/ 22 Ne ratios of Site A 2 m samples from before (A11 – A16) and during
(A17 - A23) the irrigation period. The data is absolute measured gas amounts.
Figure C.21: 4 He/ 20 Ne ratios of Site A 2 m samples from before (A11 – A16) and during
(A17 - A23) the irrigation period. The data is absolute measured gas amounts.
103

10
10
Theoretical expectation as described in Formula 2.19
4
He from samples A11 - A23, all depths
Theoretical expectation as described in Formula 2.19
3
He from samples A11 - A23, all depths
8
8
6
6
4
4
2
He compared to atm. air [%]
2
He compared to atm. air [%]
0
0
-2
Relative change of 4
-2
Relative change of 3
-4
-4
-6
-6
16 18 20 22 24
16 18 20 22 24
10
10
Theoretical expectation as described in Formula 2.19
22
Ne from samples A11 - A23, all depths
Theoretical expectation as described in Formula 2.19
20
Ne from samples A11 - A23, all depths
8
8
6
6
4
4
C Additional plots and figures
2
Ne compared to atm. air [%]
2
Ne compared to atm. air [%]
0
0
-2
Relative change of 22
-2
Relative change of 20
Figure C.22: The measured relative deviation of 3 He, 4 He, 20 Ne and 22 Ne concentrations
from atmospheric values of samples with existing O2 and CO2 data (A11 – A23, all depths),
plotted against the sample’s sum of O2 and CO2 concentration. The red line represents the
theoretically expected behavior as described in Section 2.1.3.
104
-4
-4
-6
-6
16 18 20 22 24
16 18 20 22 24
O 2 + CO 2 [Vol%] O 2 + CO 2 [Vol%]

C Additional plots and figures
10
10
Theoretical expectation as described in Formula 2.19
40
Ar from samples A11 - A23, all depths
Theoretical expectation as described in Formula 2.19
39
Ar from samples A11 - A23, all depths
8
8
6
6
4
4
2
Ar compared to atm. air [%]
2
Ar compared to atm. air [%]
0
0
-2
Relative change of 40
-2
Relative change of 39
-4
-4
-6
-6
16 18 20 22 24
16 18 20 22 24
10
10
Theoretical expectation as described in Formula 2.19
132
Xe from samples A11 - A23, all depths
Theoretical expectation as described in Formula 2.19
84
Kr from samples A11 - A23, all depths
8
8
6
6
4
4
2
Xe compared to atm. air [%]
2
Kr compared to atm. air [%]
0
0
-2
Relative change of 132
-2
Relative change of 84
Figure C.23: The measured relative deviation of 36 Ar, 40 Ar, 84 Kr and 132 Xe concentrations
from atmospheric values of samples with existing O2 and CO2 data (A11 – A23, all depths),
plotted against the sample’s sum of O2 and CO2 concentration. The red line represents the
theoretically expected behavior as described in Section 2.1.3.
105
-4
-4
-6
-6
16 18 20 22 24
16 18 20 22 24
O 2 + CO 2 [Vol%]
O 2 + CO 2 [Vol%]

F 3 He
F 22 Ne
F 84 Kr
1.10
1.05
1.00
0.95
0.90
0.90 0.95 1.00 1.05 1.10
1.10
1.05
1.00
0.95
F 4 He
0.90
0.90 0.95 1.00 1.05 1.10
1.10
1.05
1.00
0.95
F 4 He
0.90
0.90 0.95 1.00 1.05 1.10
F 4 He
F 20 Ne
F 36 Ar
F 132 Xe
1.10
1.05
1.00
0.95
C Additional plots and figures
0.90
0.90 0.95 1.00 1.05 1.10
1.10
1.05
1.00
0.95
F 4 He
0.90
0.90 0.95 1.00 1.05 1.10
1.10
1.05
1.00
0.95
F 4 He
0.90
0.90 0.95 1.00 1.05 1.10
Figure C.24: F-Values (see Section A.3 for definition) of 3 He, 20 Ne, 22 Ne, 36 Ar, 84 Kr and
132 Xe versus F-Values of 4 He. The data is from all noble gas samples of Site A and all
depths. Correlations are only visible for 20 Ne and 22 Ne but not systematically as the magnitude
of noble gas enrichment has no discernible influence on the position of the datapoint.
106
F 4 He

Appendix D
Datasheets
107

Besondere Merkmale des Biogasmonitors BM2000
analytische Systeme und
Componenten GmbH
� tragbar, batteriebetrieben, langzeitstabil, zuverlässige Messwerte,
� misst 4 Gase: Methan, Kohlendioxid, Sauerstoff und Schwefelwasserstoff,
� Infrarot-Technik - keine gegenseitige Beeinflussung von CO 2 und CH4,
� Abwesenheit von O 2 beeinflusst Messwerte nicht,
� Datenspeicher für 250 Wertesätze mit Anzeigefunktion am Messgerät und
Datenübertragung auf PC mit speziellem Programm,
� Luftdruckmessung (900 bis 1100 mbar), Druckmessung in der Messgasleitung,
� starke Pumpe bis 400 mbar Unterdruck (rel).
Technische Daten des Biogasmonitors BM2000
Messprinzip: Infrarotabsorption für CH 4 und CO 2 bei selektiven Wellenlängen,
elektrochemische Zelle für O 2 (langlebig, ca. 5 Jahre Lebensdauer),
Messbereiche: 0 - 100 Vol.-% für CH 4 , 0 - 100 Vol.-% für CO 2 ,
0 - 25 Vol.-% für O 2 , 0-10 000 ppm für H 2 S (Nachweisgrenze ca. 100 ppm).
(elektrochemische Sensoren zeigen Querempfindlichkeiten,
beim Schwefelwasserstoff (H2S) Sensor z.B. durch Wasserstoff (H2))
Fördervolumen der internen Probenahmepumpe: ca. 0,5 l/min bei freiem Fluss,
Pumpe stoppt bei ca. 400 mbar Unterdruck (rel).
Genauigkeit: Messkomponente: CH 4 CO 2 O 2
Messbereich: 0-100 0-100 0-25 (Vol.-%)
0 - 5 �0,5 �0,5 �1,0 (Vol.-%)
5 - 15 �1,0 �1,0 �1,0 (Vol.-%)
>15 �3,0 �3,0 �1,0 (Vol.-%)
Genauigkeit: Messparameter: Druck
Messbereich: 900-1100 (mbar)
900-1100 � 5 (mbar)
Temperatur: 0°C bis 40°C,
Feuchte: 0 bis 95 % rH, nicht kondensierend,
Batteriebetrieb: bei normalem Betrieb ca. 8 Stunden (im Auslieferungszustand),
Ladezeit: ca. 2 Stunden bei vollständiger Entladung der Batterien,
Schutzart: Gehäuse IP 65,
Display: LCD Anzeige, beleuchtbar, 40x16 Zeichen,
Maße: ca. 19 cm x 25 cm x 6 cm,
Gewicht: ca. 2,0 kg.
Optionelles Zubehör für den tragbaren Biogasmonitor BM2000
� Temperatursonde: Messbereich 0°C - 100°C
(im Bereich 0°C - 40°C Ex-Zulassung gültig ),
� externe Messeinrichtungen z.B. für kleine Konzentrationen an H2S,
mit ATEX-Zulassung,
� Sensor zur Messung von Gesamtgasfluss, Anemometer,
(nicht für den Ex-Bereich),
� RS-Kabel und Software zur Datenübertragung (nicht EX-zugelassen).
Weitere Produkte
� zusätzliche Sonden zur Messung des Wasserstandes (Lichtlote), des
Sickerwasserstandes oder der Mächtigkeit von Ölphasen auf Wasser.
Technische Änderungen vorbehalten 08/10 D 1I
ansyco analytische Systeme und Componenten GmbH · Ostring 4 · 76131 Karlsruhe
Telefon 0721 / 626560 · Telefax 0721 / 621332 · E-Mail info@ansyco.de · http://www.ansyco.de
Figure D.1: Datasheet Geotech BM2000 Biogas Monitor.
108
D Datasheets

D Datasheets
LogTag TREX-8 Technical Specifications
Part Order Code TREX-8
Remote Temperature Sensor Measurement range -40 ~ +99°C (-40°F ~ +210°F)
Recorder operating temperature range -40 ~ +85°C (-40°F ~ +185°F)
Rated Temperature reading accuracy *
* Ex-factory values with standard 1.5m LogTag supplied probe
With recorder case sitting in environmental temperature
between 0°C ~ 50°C the rated accuracy is :-
±0.5°C for -10°C~ +40°C
better than ±0.7°C for -10°C~ -30°C & +40°C~+60°C
better than ±0.8°C for -30°C~ -40°C & +60°C~+80°C
better than ±1.0°C for +80°C~+99°C
For generalized environment conditions see Chart below
Rated absolute accuracy
±3.0ºC
±2.5ºC
±2.0ºC
±1.5ºC
±1.0ºC
±.5ºC
LogTag TREX Temperature Recorder
Rated remote sensor temperature reading accuracy
-40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90 100
Temperature (ºC)
recorder @ +25°C recorder @ - 20°C recorder @ -40°C
Actual performance is normally much better than the rated
values.
Accuracy figures can be improved by recalibration.
Rated Native Resolution
Rated Temperature reading resolution #
less than 0.1°C for -40°C ~ +40°C,
less than 0.2°C for +40°C ~+80°C
less than 0.6°C for +80°C ~+99°C (see below)
1.0ºC
0.9ºC
0.8ºC
0.7ºC
0.6ºC
0.5ºC
0.4ºC
0.3ºC
0.2ºC
0.1ºC
LogTag TREX Temperature Recorder
Rated native temperature reading resolution
-40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90 100
Temperature (ºC)
# LogTag Analyser currently displays to one decimal place of °C
or °F. The native resolution is what is stored in the LogTag.
Capacity 8000 temperature readings (16Kbytes memory)
Sampling frequency adjustable, 30 sec to several hours
Download Time
Typically with full memory in less than 5 seconds
depending on computer or readout device used.
Environmental IP61
Power source 3V Lithium - replaceable by qualified technician
Battery life
2~3 years typical use – longer (up to 5-10 years)
if recorder is hibernated between uses.
Standard Remote Sensor Cable Lengths
Standard: 1.5m (4’11”)
Extended: 3 m (9’10”) (recommended maximum)
Remote Sensor Cable Type PTFE (FDA food contact rated) coaxial
Size 86mm(H)x54.5mm(W)x8.6mm(T)
Weight 35grams without ST100
Case Material Polycarbonate
Figure D.2: Datasheet LogTag TREX-8 data logger and sensor. TRIX-8 is identical but
with the sensor build into the casing.
DOC REV G 28/11/07 – ©Copyright 2007, LogTag Recorders Ltd. release version Page 2 of 4
109

HIGHLY PRECISE DIGITAL MANOMETER
PRECISION: 0,01 %FS *
LEX 1 is a micro-processor controlled, accurate and versatile digital pressure measuring
instrument with integrated Max.-/Min.-function for calibration and testing purposes.
The pressure is measured twice per second and displayed. The top display indicates the
actual pressure, the bottom display shows the Max.- or Min.-pressure since the last RESET.
LEX 1 has two operating keys. The left key is to turn the instrument on, to select the functions
and the pressure units. The right key executes the selected function resp. unit or serves to
display the Max.- and Min.-value.
The instrument has the following functions:
RESET: With the RESET-function, the Max.- and Min.-value is set to the actual pressure
value.
ZERO: The ZERO-function allows to set any value as a new Zero reference. Barometric
pressure variations can thus be compensated.
The factory setting of the Zero for the ranges ≤ 30 bar is at 0 bar absolute. For sealed
gauge pressure measurements, activate “ZERO SEt” at ambient pressure. Instruments
with ranges > 30 bar are calibrated in a sealed gauge mode with ambiant
pressure as a Zero reference.
CONT: The instrument turns off 15 Min. after the last key function. Activating CONT (Continuous)
deactivates this automatic turn-off.
UNITS: All standard instruments are calibrated in bar. The pressure can be indicated in 13
different units.
Optional Accessories:
Carrying bag, protective rubber covering
SPECIFICATIONS
Pressure Ranges, Resolution, Overpressure: Range Resolution Overpressure
-1…2 bar 0,1 mbar 3 bar
-1…20 bar 1 mbar 30 bar
0…200 bar 10 mbar 300 bar
0…400 bar 50 mbar 600 bar
0…1000 bar 100 mbar 1100 bar
Number of Digits 5 Digit
Accuracy (10…30 °C) * 0,05 %FS (including linearity, repeatability and hysteresis)
Precision * 0,05 %FS
Precision optional (≥ 20 bar) * 0,025 %FS / 0,01 %FS
Storage- / Operating Temperature -10…60 °C / 0…50 °C
Compensated Temperature Range 0…50 °C
Supply 3 V battery, type CR 2430
Battery Life 2000 hours continuous operation
Pressure Connection G1/4”
Interface RS485; rear-sided mating plug “Fischer”
compatible with PC-converter cable
K103-A (RS232) and K104-A (USB)
Protection IP65
Diameter x Height x Depth 76 x 118 x 42 mm
Weight 210 g
KELLER AG für Druckmesstechnik St. Gallerstrasse 119 CH-8404 Winterthur Tel. 052 - 235 25 25 Fax 052 - 235 25 00
KELLER Gesellschaft für Druckmesstechnik mbH Schwarzwaldstrasse 17 D-79798 Jestetten Tel. 07745 - 9214 - 0 Fax 07745 - 9214 - 50
Companies approved to ISO 9001 / EN 29001
Subject to alterations
Figure D.3: Datasheet Keller Lex 1 pressure gauge.
110
Display 5 Digit LEX 1
D Datasheets
LEX 1
* Accuracy and Precision
“Accuracy” is an absolute term, “Precision” a relative
term. Dead weight testers are primary standards for
pressure, where the pressure is defined by the primary
values of mass, length and time. Highest class primary
standards in national laboratories indicate the uncertainty
of their pressure references with 70 to 90 ppM or close to
0,01%.
Commercial dead weight testers as used in our facilities to
calibrate the transmitters and manometers indicate an
uncertainty or accuracy of 0,025 %. Below these levels,
KELLER use the expression “Precision” as the ability of a
pressure transmitter or manometer to be at each pressure
point within 0.01 %FS relative to these commercial standards.
The manometer’s full-scale output can be set up to match
any standard of your choice by correcting the gain with a
calibration software.
www.keller-druck.com
12/04

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[Aeschbach-Hertig et al. 2008] Aeschbach-Hertig, W. ; El-Gamal, H. ; Wieser, M. ;
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[Friedrich 2007] Friedrich, R.: Grundwassercharakterisierung mit Umwelttracern: Erkundung
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Acknowledegment
At the end of this thesis a few words of thanks are due: to all the people who helped me get
to this point, both personally as well as professionally. First of all I would like to thank my
parents for supporting me through my entire time at the Heidelberg University, through all the
good and all the difficult times.
Of course I would also like to thank my supervisor, Professor Dr. Werner Aeschbach-Hertig, for
giving me the chance to work on this thesis and for letting me handle it quite independently
while still providing valuable input and guidance. For all the input and shared knowledge, as
well as the great help at constructing the sampling sites I would like to thank my friend and
colleague Tim Schneider. In fact, the entire team was extremely kind and helpful with the many
problems and questions that arose. Primarily, but not exclusively, I would like to thank Martin
Wieser, Tillmann Kaudse, Lisa Broeder and for all their help and the extensive proofreading
and generally for the great time.
This study would also not have been possible without the kind assistance of Kurt Elfner, who
provided a small piece of his flower nursery’s land where I was able to set up one of my sampling
sites. Also very helpful was the company meteomedia, which made their weather data archive
of their nearest weather station available to me.
And of course there were the inhabitants of office 442: probably holding both the institute’s
attendance record on sundays and holidays (which might be a bit ambivalent) and always entertaining
visitors (which was a lot of fun as well as insightful). Claudia, Johannes, Joelle and
Fiete, you are the best!
A special and huge thanks goes to my good friend Julia Schaper who helped me a lot with some
great, extensive and always encouragingly funny proofreading and to Tina Straße, who somehow
always managed to motivate me and to get my spirit up. Your visits meant a lot to me! I would
not have made it this far without the support of my girlfriend Katja Weiß, who was always there
for me (even when I did not have time for her). Thank you!
117

Erklärung:
Ich versichere, dass ich diese Arbeit selbstständig verfasst und keine anderen als die angegebenen
Quellen und Hilfsmittel benutzt habe.
Heidelberg, 30.06.2011
.......................................
(Unterschrift)