AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus PublicationsGöttingen, Germany10.5194/amt-9-939-2016The airborne mass spectrometer AIMS – Part 1: AIMS-H2O for UTLS water vapor
measurementsKaufmannStefanstefan.kaufmann@dlr.dehttps://orcid.org/0000-0002-0767-1996VoigtChristianehttps://orcid.org/0000-0001-8925-7731JurkatTinaThornberryTroyhttps://orcid.org/0000-0001-7478-1944FaheyDavid W.https://orcid.org/0000-0003-1720-0634GaoRu-ShanSchlageRomySchäubleDominikZögerMartinDeutsches Zentrum für Luft- und Raumfahrt, Institut
für Physik der Atmosphäre, Oberpfaffenhofen, GermanyJohannes Gutenberg-Universität, Institut für
Physik der Atmosphäre, Mainz, GermanyNOAA Earth System Research Laboratory, Chemical Sciences
Division, Boulder, Colorado, USAUniversity of Colorado, CIRES, Boulder, Colorado,
USAInstitute for Advanced Sustainability Studies, Potsdam,
GermanyDeutsches Zentrum für Luft- und Raumfahrt, Flight
Experiments, Oberpfaffenhofen, GermanyStefan Kaufmann (stefan.kaufmann@dlr.de)7March20169393995327November201521December201518February201622February2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/articles/9/939/2016/amt-9-939-2016.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/articles/9/939/2016/amt-9-939-2016.pdf
In the upper troposphere and lower stratosphere (UTLS), the accurate
quantification of low water vapor concentrations has presented a significant
measurement challenge. The instrumental uncertainties are passed on to
estimates of H2O transport, cloud formation and the role of H2O in
the UTLS energy budget and resulting effects on surface temperatures. To
address the uncertainty in UTLS H2O determination, the airborne mass
spectrometer AIMS-H2O, with in-flight calibration, has been developed for
fast and accurate airborne water vapor measurements.
We present a new setup to measure water vapor by direct ionization of ambient
air. Air is sampled via a backward facing inlet that includes a bypass flow
to assure short residence times (< 0.2 s) in the inlet line, which
allows the instrument to achieve a time resolution of ∼4 Hz, limited by
the sampling frequency of the mass spectrometer. From the main inlet flow, a
smaller flow is extracted into the novel pressure-controlled gas discharge
ion source of the mass spectrometer. The air is directed through the gas
discharge region where ion–molecule reactions lead to the production of
hydronium ion clusters, H3O+(H2O)n (n=0,1,2), in
a complex reaction scheme similar to the reactions in the D-region of the
ionosphere. These ions are counted to quantify the ambient water vapor mixing
ratio. The instrument is calibrated during flight using a new calibration
source based on the catalytic reaction of H2 and O2 on a Pt surface
to generate a calibration standard with well-defined and stable H2O
mixing ratios. In order to increase data quality over a range of mixing
ratios, two data evaluation methods are presented for lower and higher
H2O mixing ratios respectively, using either only the
H3O+(H2O) ions or the ratio of all water vapor dependent
ions to the total ion current. Altogether, a range of water vapor mixing
ratios from 1 to 500 parts per million by volume (ppmv) can be covered with
an accuracy between 7 and 15 %. AIMS-H2O was deployed on two DLR
research aircraft, the Falcon during CONCERT (CONtrail and Cirrus ExpeRimenT)
in 2011, and HALO during ML-CIRRUS (Mid-Latitude CIRRUS) in 2014. The
comparison of AIMS-H2O with the SHARC tunable diode laser hygrometer
during ML-CIRRUS shows a correlation near to 1 in the range between 10 and
500 ppmv for the entire campaign.
Introduction
Airborne mass spectrometry is a powerful tool for the fast and accurate
measurement of various trace gases relevant for atmospheric chemistry and
climate. Linear quadrupole mass spectrometers (LQMS) can be operated in a
variety of configurations – e.g., for direct measurements of ions in the
atmosphere (Viggiano, 1993; McCrumb and Arnold, 1981), chemical ionization
mass spectrometry (CIMS) (e.g., Huey and Lovejoy, 1996),
proton-transfer-reaction mass spectrometry (PTR-MS) (Hansel et al., 1995) or
artificial ionization and characterization of ambient air (Thornberry et al.,
2013). In contrast to the other two techniques, CIMS and PTR-MS utilize
transfer reactions between artificially produced reagent ions and ambient air
molecules. The Atmospheric Ionization Mass Spectrometer (AIMS) described in
this work makes use of the three latter techniques. Part 1 of this paper
focuses on the measurement of water vapor down to low mixing ratios typical
for the lower stratosphere by direct ionization of ambient air. In Part 2
(Jurkat et al., 2016), the setup and measurements using the CIMS technique
with SF5- chemistry for the set of trace gases HCl, HNO3,
HNO2, SO2 and ClONO2 are presented.
The water vapor configuration of AIMS, referred to as AIMS-H2O, was
developed in response to the large discrepancies between different airborne
H2O measurements that have been found in the past (Oltmans et al.,
2000). Accurate knowledge of water vapor concentrations in the atmosphere is
crucial for understanding Earth's climate since it is the most important
greenhouse gas and engages in a positive feedback in the climate system (e.g.,
Manabe and Wetherald, 1967; Kiehl and Trenberth, 1997). The radiative impact
of changes in water vapor concentrations is particularly strong in the
tropopause region and in the lower stratosphere (Solomon et al., 2010; Riese
et al., 2012) where water vapor mixing ratios are in the range of only a few
parts per million by volume (ppmv, 10-6 mol mol-1). Measurements
in these regions, in situ as well as satellite-based instruments, showed
significant discrepancies in the past with offsets of the order of several
10 % (e.g., Weinstock et al., 2009; Vömel et al., 2007). These
uncertainties in UTLS water vapor concentrations directly transfer into the
calculation of the atmosphere's energy budget (Forster and Shine, 2002). In
addition, these uncertainties currently limit our understanding of
microphysical processes related to ice nucleation, growth and persistence of
cirrus clouds in the upper troposphere (Krämer et al., 2009; Jensen et
al., 2005; Heymsfield and Miloshevich, 1995) and the tropical UTLS region
(Jensen et al., 1994). In turn, this affects the quantification of the
tropical H2O transport to the stratosphere (Dinh et al., 2014) and the
UTLS radiation budget, including the effect of clouds (Ramanathan et al.,
1989; Sassen and Comstock, 2001; Liou, 1986; Dinh and Fueglistaler, 2014).
To address the disagreements in UTLS water vapor measurements, a series of
laboratory and field campaigns has been launched, one of the first being the
AquaVIT-I experiment in 2007 (Fahey et al., 2014) at the AIDA cloud chamber
in Karlsruhe. In the lab, discrepancies between the instruments were found to
be smaller than in the field but still above ±10 % especially at
water vapor mixing ratios below 10 ppmv. The instrument performance and
improvements have been re-evaluated in two follow-up experiments, AquaVIT-II
and III in 2013 and 2015 (not published yet). In order to assess the
technical improvements not only in the laboratory but also in the atmosphere,
an extensive comparison of in situ hygrometers was performed during the
airborne field mission MACPEX (Mid-latitude Airborne Cirrus Properties
EXperiment) in 2011. Although the performance of in situ water vapor
instruments has improved over the last decade (Rollins et al., 2014; Meyer et
al., 2015), the accuracy of airborne water vapor measurements in the
tropopause region still remains an issue of concern.
With the mass spectrometer AIMS-H2O, which includes in-flight calibration,
we have developed a significant contribution to the field of airborne water
vapor measurements with a focus on the low H2O mixing ratios of the
UTLS. The instrument was deployed on an aircraft for the first time during
the CONCERT (CONtrail and Cirrus ExpeRimenT) experiment with the DLR Falcon
in 2011 (Kaufmann et al., 2014). After further development, AIMS-H2O was
deployed on HALO during ML-CIRRUS (Midlatitude CIRRUS) in 2014. Its twin
configuration, AIMS-TG for trace gas observations, has also been operated on
the DLR Falcon during CONCERT (Voigt et al., 2014) and on HALO during
TACTS/ESMVal (Transport And Composition in the UT/LMS/Earth System Model
Validation) in 2012 (Jurkat et al., 2014).
In this work, we first describe the mechanical and electrical setup of
AIMS-H2O with a special emphasis on the novel gas discharge ion source
designed for the direct ionization of ambient water vapor. Second, we
present the in-flight calibration setup and performance that is used to
assure accurate and reliable airborne measurements. After a discussion of
data reduction methods used to quantify ambient H2O mixing ratios, we
derive the instrumental uncertainties and present the first airborne
measurements on HALO during ML-CIRRUS including a comparison with the
Sophisticated Hygrometer for Atmospheric ResearCh (SHARC) in situ tunable
diode laser hygrometer.
Setup of the mass spectrometer
AIMS consists of a linear quadrupole mass spectrometer (Huey et al., 1995)
which was designed and built by THS instruments at the Georgia Institute of
Technology (Greg Huey, Atlanta, USA). It is integrated in one HALO standard
rack plus an external plate where the bypass pump is mounted (behind the rack
in Fig. 1). The instrument is connected to a heated HALO Trace Gas Inlet
(TGI, enviscope GmbH, Germany) and can be operated with either a backward- or
forward-facing inlet geometry in order to sample the gas phase only or the
sum of the gas phase and condensed phase (evaporated), respectively. In order
to ensure a low residence time in the inlet line and thereby reduce inlet
artifacts, a bypass flow of up to 30 standard liters per minute (standard
L min-1) is established using an IDP-3 scroll pump (Agilent
Technologies, USA) (Fig. 2). The general flight setup of the mass
spectrometer is described below following the gas flow from the inlet line
through the pressure-regulated ionization chamber to the vacuum chamber of
the mass spectrometer. Details of the ion source and in-flight calibration
techniques are presented separately in Sects. 3 and 4.
Front view of instrument rack in AIMS-H2O configuration
integrated in a HALO standard rack. The inlet line is connected to a trace
gas inlet (TGI) mounted at the top fuselage of the aircraft.
Schematic of the flight configuration of AIMS. Ambient air enters
via a backward faced inlet and passes through a pressure regulation valve
before entering the ion source. The detailed setup of the ion source for the
two measurement modes is depicted in Fig. 5. The ion beam is then focused by
two adjacent octopoles and finally separated by mass-to-charge ratio in the
quadrupole. Additionally, connections for an optional dilution of ambient air
and background measurements and for addition of trace gases for in-flight
calibration (detail in Fig. 3) are mounted right beneath the inlet.
Inlet line
For the inlet line of AIMS-H2O we use a Synflex composite tube (Data sheet
Synflex 1300, www.goodrichsales.com/products/pdfs/1300.pdf) with an
outer diameter of 1/2′′. The tube consists of an aluminum body with an
inner ethylene copolymer film and an outer polyethylene jacket. The material
combines several features which are of benefit for water vapor measurements
in the aircraft. Adsorption of water vapor to the walls and diffusion through
the walls of Synflex lines is comparable to stainless steel tubes.
Furthermore, it is much more flexible than stainless steel tubing. An
approximately 40 cm length of tube is fitted inside a HALO TGI and heated to
40 ∘C controlled by a bimetal switch. A 1.2 m length of tube is
used to connect the TGI with the pressure regulation valve of AIMS-H2O.
Tubing connections are made using Swagelok stainless steel compression
fittings. This part of the tubing is heated separately to 40 ∘C
using a two-point temperature controller. Two tee fittings are integrated
into the sample line as depicted in Fig. 2. The one directly at the TGI is
used to add calibration gas, and the second one is used for an optional
dilution flow with dry synthetic air (Air Liquide GmbH, residual H2O,
∼0.5 ppmv). The dilution flow is added via a mass flow controller
(Type 1179, MKS Instruments) allowing for dilution ratios up to 2 : 1. A
third tee fitting allows subsampling of air into the instrument while the
large inlet flow needed for measurements with high time resolution flows
directly to the pump. Since the two configurations of AIMS require specific
properties of the inlet line, two different tubing sets are installed in the
aircraft: Synflex and stainless steel for AIMS-H2O and fluoropolymers
(PFA) for AIMS-TG.
Pressure regulation
In order to guarantee constant flow and pressure conditions in the ion
source, flow reactor and mass spectrometer, we use an automatically
controlled pressure regulation valve mounted upstream of the ion source
(Fig. 2). For AIMS-H2O, the ball valve consists of stainless steel with a
modified PTFE (D1710 Type 1) sealing (Swagelok SS-42GS4). The pressure
regulation has to be fast since it needs to compensate for rapid ambient
pressure changes during aircraft ascent and descent between 1000 and
150 hPa, but it also has to be both precise and accurate since the reaction
time for the ion–molecule reactions in the flow reactor scales linearly with
the pressure. The lever of the manual valve was replaced by an adapter to
control the valve using a servomotor (DA 22-30-4128, Volz Servos GmbH,
Germany). The motor is controlled by a PID controller regulating the pressure
measured by a Baratron manometer (MKS Instruments, Type 727) in the flow
reactor. For AIMS-H2O, 99 % of the measured pressure values have a
deviation of less than 0.02 hPa (0.5 %) from the nominal value of
4.3 hPa. The pressure regulation can compensate for pressure changes during
regular flight maneuvers like ascent and descent and thus contributes only a
minor error source for the overall measurement.
Vacuum chamber
The instrument flow path downstream of the pressure-regulating valve consists
of the ion source, the flow tube and three differentially pumped chambers
which are connected by pinholes of different sizes. As indicated in Fig. 2
the pressure decreases from a few hPa in the ion source to less than
10-4 hPa in the last chamber containing the quadrupole and electron
multiplier. The two chambers directly downstream of the ion source are
equipped with two separate octopoles which act as lenses for the ion beam.
Their main purpose is to focus the ion beam towards the quadrupole chamber.
The first octopole is pumped by a MDP5011 molecular drag pump (Pfeiffer), the
second one by a V-81M turbo pump (Agilent Technologies, USA). As backing pump
for the MDP, we use a SC15D scroll pump (Oerlikon Leybold Vacuum GmbH).
Separate DC electrical potentials (-250 to +250 V) can be applied to
each aperture and the octopoles in order to accelerate or decelerate the ion
current. This is of special importance in the first octopole chamber with a
higher pressure where the acceleration of ions relative to the neutral gas
molecules determines the fragmentation of ion–molecule clusters. For that
reason, this chamber is also referred to as the Collision Dissociation
Chamber (CDC). The aperture plate between the first and second octopole
chamber is connected to ground, so all potentials applied to octopoles and
apertures are relative to this aperture plate.
The third chamber, also pumped by a V-81M, contains the linear quadrupole
(GP-203D, Extrel CMS, USA). Here, the ions are separated by their mass to
charge ratio. Therefore both a DC and a high voltage RF potential are applied
to the quadrupole rods so that only ions with the same mass-to-charge ratios
can pass through the quadrupole on a stable trajectory at a time. Stray
fields in entrance and exit areas of the quadrupole are minimized by pre- and
post-filters, which themselves are short quadrupole rods at different
potentials. The separated ion species are detected by an electron multiplier
(Channeltron, ITT Ceramax 7550M, ITT Power Solutions) which counts single ion
impacts (up to ∼4×106 s-1).
The quadrupole can be operated in two different measurement modes. The so-called “hop mode” is used to obtain time series of a few fixed
mass-to-charge ratios. In this mode, the quadrupole repeatedly steps through
up to 16 fixed mass-to-charge ratios with an integration time of the order of
100 ms each. For in-flight measurements, we are predominantly interested in
the time dependence of known species, so the hop mode is the default
measurement mode. The second mode is the “scan mode”, in which the quadrupole
potentials are increased continuously in order to obtain a mass spectrum as
shown in Fig. 6. Depending on the step width, the time needed to record one
spectrum is of the order of 30 s. Such spectra can be performed manually or
automatically at specific time intervals in order to check for unexpected
product ions during flight.
In-flight calibration
Since the environmental conditions during aircraft measurements are rather
extreme in terms of changing pressure and temperature compared to the
relatively stable conditions in the laboratory, it is always difficult to
judge how a ground calibration transfers to in-flight conditions. In order
to achieve highly accurate measurements, it is therefore important to
calibrate during flight for the measured substances. However, there remains
a tradeoff between higher accuracy achieved by a thorough in-flight
calibration and the loss of precious (airborne) sampling time. The methods
for in-flight calibration thus have to be fast, they need to be integrated
in the airborne instrument setup and they need to be able to produce trace
gas amounts typical for the investigated atmospheric conditions in a stable
manner.
The in-flight calibration for the water vapor measurement is realized by the
catalytic reaction of H2 and O2 on a Pt-surface in order to create
a calibration flow with well-defined H2O mixing ratios (Rollins et al.,
2011). This technique was applied in flight for the first time during the
MACPEX mission in 2011 (Thornberry et al., 2013). A mixture of (420±8.4) ppmv H2 in synthetic air (Airliquide GmbH) is stored in a 150 mL
stainless steel cylinder (Swagelok) with a maximum pressure of 150 bar
(Fig. 3). The cylinder can be refilled after each flight via a quick
connector, thus for each flight 22.5 standard L of calibration gas are
available. After the pressure regulator (2 bar), the H2/ zero air
mixture flows over a Pt mesh (Sigma-Aldrich, Prod.-Nr. 298107) which is
folded inside a 1/4′′ stainless steel tube (Swagelok) and heated to
250 ∘C. In laboratory studies similar to the approach of Rollins et
al. (2011), the plateau where the conversion efficiency (CE = ratio
between H2 mixing ratio before and H2O mixing ratio after the
catalyst) is stable above 95 % is reached at around 150 ∘C. The
operating temperature of the catalyst is chosen to be high enough so that the
CE is independent of the exact catalyst temperature. It is important to
operate the system at temperatures well above this threshold since it was
found that the temperature of the gas stream can be up to 35 ∘C
lower than the controlled temperature measured at the outer wall of the
catalyst tube. This temperature difference depends on the gas flow rate
through the catalyst, which in our system is up to
0.5 standard L min-1, the maximum range of the MFC (MKS Instruments,
Type 1179A) right behind the catalyst. Since the in-flight calibration period
should be kept as short as possible to maximize measurement time, the flow
through the catalyst can alternatively be drained to the exhaust line. This
allows the catalyst and tubing system to equilibrate before the calibration
sequence is started.
Setup of the in-flight calibration: (a) zero air can be
added to the sample flow for dilution and background measurements.
(b) A mixture of H2 in zero air is passed over a heated
Pt-catalyst and reacts to H2O for calibration of the water vapor
configuration. The water vapor mixing ratio in the calibration gas can be
further adjusted by dilution with synthetic air from (a). To allow
for equilibration of the catalytic source, the calibration gas flow is
switched on early and guided to the exhaust line before starting a
calibration sequence.
At high temperature, the CE of the catalyst only depends on the available
reaction sites on the Pt mesh and the flow through the catalyst tube. At
higher flow, the CE decreases linearly with increasing flow rate since the
mean residence time, and thus the potential available reaction time, is
reduced. In order to increase the available reaction time, the MFC is located
downstream of the catalyst tube as depicted in Fig. 3b so that the catalyst
itself is exposed to a pressure of 2 bar. At flow rates below 0.06 standard
L min-1, the CE is 100 % within the uncertainties of H2 mixing
ratio, MFCs and the reference measurement. When increasing the flow up to the
maximum of 0.5 standard L min-1, the CE usually decreases down to
around 60 % (Fig. 4). This behavior is found to be stable over the
typical timescale of airborne measurement campaigns of a few weeks. To assure
a reproducible performance of the calibration source, it is regularly
characterized by ground measurements using an MBW 373-LX dew point mirror
(MBW Calibration AG, Switzerland) as a reference instrument. Using the
reference measurement, the flow dependency of the CE can be approximated by a
exponential fit function (Fig. 4). This enables the use of the complete range
of gas flows through the catalyst and thus a range of the in-flight
calibration from (0.5±0.1) ppmv up to (150±9) ppmv H2O. If
the residence time of the H2 molecules in the catalyst were the only
parameter controlling the conversion efficiency, one would expect a linear
decrease of the CE with increasing flow. Hence there must be additional
mechanisms influencing the CE which could be, e.g., occupation of calibration
sites or an inhomogeneous mixing within the catalyst.
Performance of the calibration source with respect to the MBW 373LX
reference instrument. The upper panel shows the expected H2O mixing
ratio calculated from the H2 concentration in the gas cylinder and the
gas flow through the catalyst assuming a complete conversion of every H2
molecule into H2O (black line). The blue line is the H2O mixing
ratio which was simultaneously measured by the dew point mirror. From the
discrepancy between both lines we can calculate the conversion efficiency
(CE) of the catalyst. The CE decreases with increasing flow through the
catalyst and is fitted with an exponential function.
Over longer time spans of several months, the CE can decrease significantly,
strongly dependent on storage conditions, probably due to contamination of
reaction sites on the Pt catalyst. Therefore, several treatments of the Pt
mesh were tested in order to restore the reaction sites. We found that a
simple roughening of the Pt surface, thereby physically removing contaminated
spots on the surface, works best and can reliably restore optimal conversion
conditions. However, the largest uncertainty in the calibration still arises
from the stability of the H2→ H2O conversion on the catalyst.
The calibration source is therefore regularly calibrated on ground during a
campaign period, typically between every two flights. Including the
uncertainty of the reference measurements (0.1 K in frost point, which
translates to roughly 1 % relative accuracy in mixing ratio) and H2O
contamination in the H2/ zero air mixture (stable at less than
0.5 ppmv, including bottle to bottle differences), the total accuracy of the
in-flight calibration source is around 6 %.
A typical in-flight calibration sequence takes about 10–20 min, depending
on the number of calibration steps. Due to the non-linearity of the
calibration (see next section), at least three calibration steps are required
in order to obtain a reliable calibration function. If there is enough time
during a specific flight sequence, usually five to six calibration steps are
performed in order to assure quality and consistency of the calibration. For
all steps the flow of the calibration gas is higher than the sampling flow
into the instrument. The excess flow is drained through the inlet.
Custom gas-discharge ion source
The ion source is an essential part of the mass spectrometer since its
geometry and the ionization mechanism determine the type and amount of
product ions used for the detection of trace gases. For AIMS we use different
DC gas-discharge ion sources which were developed specifically for the
different AIMS configurations. The gas-discharge ion source and the resulting
ionization process is one of the major differences between AIMS and the
CIMS-H2O instrument developed by Thornberry et al. (2013). Here, we
describe the ion source setup for the AIMS-H2O configuration.
Mechanical and electrical setup
Both ion sources utilize an electrical discharge between a gold needle at
high potential and a wall or aperture held near ground. The physical design
of the ion source is inspired by the work of Kürten et al. (2011), who
described a discharge ion source using a gold needle at atmospheric
pressures. In contrast to Kürten et al. (2011), the geometry, flow
conditions and pressure are adapted for AIMS. Since the pressure in the ion
source is significantly lower (4–40 hPa), the ionization mechanism for AIMS
differs from Kürten et al. (2011). The setup for the ion source of
AIMS-H2O is shown in Fig. 5. The ionization is realized by applying a
positive high voltage (HV) potential to a gold needle (Moxom SP-X Gold, Moxom
Acupuncture GmbH, Germany). The potential is provided by a HV module
(DPp100504245M, iseg Spezialelektronik GmbH, Germany) and can be adjusted
between 0 and 10 kV with a maximum current of 0.5 mA. The HV supply and
needle are connected via a SHV (safe high voltage) vacuum feedthrough (SHV20,
VACOM GmbH, Germany). Additionally, a 500 MΩ resistance is placed
between the HV supply and needle in order to limit the current to 0.01 mA
and prevent an uncontrolled self-maintaining discharge. The counter-electrode
is the wall of the ion source. In order to control the initial electrical
potential of the ions, the wall of the ion source can be set to a potential
between -250 and +250 V.
Gas-discharge ion source of AIMS-H2O: ambient air is guided to
the discharge zone between a gold needle and the wall of the source (red
shaded region). The needle has a positive potential of +5 kV relative to
the shielding of the assembly which itself can be set at variable potential
vs. ground. A resistance of 500 MΩ is integrated in order to limit
the maximum ion current to 0.01 mA.
The body of the ion source is a KF16 tee directly mounted to the mass
spectrometer. Ambient air enters from the left-hand side and is guided to the
discharge region (indicated in red). The fixture holding the gold needle
(PEEK) is designed for a distance of 6 mm between needle and the wall of the
ion source. In this setup, ambient air is ionized directly and guided to the
first chamber of the MS. The HV supply is set to a positive potential of
+5 kV; depending on the current, the potential between needle and wall is
lower. The ion source pressure is controlled to 4.3 hPa corresponding to an
atmospheric sample flow through the ion source of
0.9 standard L min-1. The wall of the ion source is set to +4.0 V
in order to accelerate the positive ions to the first pinhole held at
+1.5 V. The ionization region itself can be divided into two parts. In the
region in the direct vicinity of the needle tip, the electric field is strong
enough to split neutral molecules into positive ions and electrons. There,
negative ions and electrons are attracted by the needle tip and thus quickly
removed from the gas phase. In the much larger region between needle and
wall, the so-called ion drift region (Chen, 2002), positive ions are
accelerated towards the wall. This is the region where water molecules react
to form the detected product ions and ion–molecule clusters. The low
pressure in the flow tube and the short distance to the mass spectrometer
prevent further reactions of H3O+ ions with molecules of higher
proton affinity as is typically used for ionization in Proton Transfer
Reaction Mass Spectrometry. Thus the H3O+(H2O)n
product ions are not significantly consumed by subsequent chemical
ionization.
Ion reaction scheme for AIMS-H2O
For the H2O mode of AIMS, the ion–molecule reactions in the ion source
are very similar to the reactions in the D region of the ionosphere
(Thornberry et al., 2013). These reactions are described by, e.g., Fite (1969),
Fehsenfeld et al. (1971) and Ferguson (1974). Due to the rapid transfer of
charge from N2+ to O2, the majority of positive ions entering
the drift region are O2+ ions. After the three-body-collision
reaction
O2++O2+M→O4++M
including either neutral nitrogen or oxygen molecules (k=2.6×10-30 (T/300)3.2 cm6 s-1, Payzant et al., 1973),
ambient water vapor reacts with O4+ to produce the primary product
H3O+(H2O) via the following reactions:
O4++H2O→O2+H2O+O2O2+H2O+H2O→H3O+(OH)+O2H3O+(OH)+H2O→H3O+H2O+OH.
Mass spectra for m/z ratios from 15 to 80 amu for four different
water vapor mixing ratios. The black curve represents a measurement of an
added zero air flow, the other three spectra are samples of ambient
atmospheric air during flight. As H2O mixing ratios increase, the
signals on H3O+, H3O+(H2O) and (@450 ppmv)
H3O+(H2O)2 increase whereas the O2+ signal
decreases. The signal on H3O+(H2O)3 does not increase up
to mixing ratios of 450 ppmv. NO+ and NO2+ stay almost constant
over the range of water vapor mixing ratios shown here.
Reactions (R2)–(R4) have similar high rate constants of the order of
k=1.5×10-9 cm3 s-1 and are thus very fast (Ferguson,
1974). For that reason a short distance between the ionization region and the
entrance pinhole of the mass spectrometer is sufficient for the H2O
configuration. For the quantitative measurement of atmospheric water vapor we
use H3O+(H2O) as the primary product ion at a
mass-to-charge ratio of 37 amu (atomic mass unit). Since the reaction from
H2O to H3O+(H2O) has multiple steps it cannot be
considered as a first-order reaction. Thus the calibration of
H3O+(H2O) vs. H2O is expected to be non-linear.
Moreover, we also observe higher clusters of H3O+ with increasing
H2O formed by the reaction suggested by Cunningham et al. (1972):
H3O+(H2O)n-1+H2O+M⇄H3O+H2On+M.
In the upper troposphere and lower stratosphere, clusters with
n> 1 do not contribute significantly to the observed
H3O+ ion distribution. In more humid regions in the middle and
lower troposphere, clusters with n= 1–3 show a significant signal. By
using measurements of multiple clusters, AIMS-H2O is able to measure water
vapor from the lower troposphere up to the stratosphere.
Apart from the H2O branch of reactions described above, there are also
multiple reaction pathways to form NO+ and NO2+ ions from the
initial N2+ and O2+. Since nitrogen and oxygen are abundant
in the atmosphere and no water vapor is included directly in these reactions,
H2O has only a small impact on NO2+ formation and an
insignificant influence on NO+. Thus, the signal of NO+ at
m/z= 30 amu is used as an independent measure of the stability of the
ionization and ion–molecule reaction process. The signal of NO2+ is
1 order of magnitude lower than NO+ and exhibits a slight
anticorrelation with H2O.
Mass spectrum for the detection of water vapor
The reactions described above can be directly linked to the mass spectra
measured with AIMS-H2O. Four typical spectra corresponding to different
water vapor mixing ratios are shown in Fig. 5. In the mass range shown, all
ions have a single positive charge, hence the mass-to-charge ratio is
identical to the ion mass. The H3O+ ion at 19 amu exhibits a small
positive correlation with H2O, mainly due to fragmentation of
H3O+(H2O) in the CDC. However, the overall signal is weak
and not used for the evaluation of H2O. NO+ exhibits a stable
moderate signal at 30 amu and, as noted above, is independent of ambient
water vapor. As expected from Reactions (R1)–(R4) the signal of O2+
is very high at the lowest H2O mixing ratios and anti-correlated with
ambient water vapor since O2+ represents the source ion for the
reaction with H2O. Independent of the water vapor mixing ratio, we do
not observe any significant signal on the intermediate ions from
Reactions (R1)–(R4), namely O4+ (m/z= 64),
O2+(H2O) (m/z= 50) and H3O+(OH)
(m/z= 36). This suggests that the intermediate states are rather
short-lived and the reaction path (Reactions R1–R4) is already completed
within the reaction chamber. As the reactions also suggest, the
H3O+(H2O) ion at 37 amu shows the strongest correlation
with water vapor, and its signal strength is comparable to that of the
O2+ ion. At mixing ratios below 500 ppmv, the signal strength of
higher clusters is more than one order of magnitude lower. Hence, the
H3O+(H2O) signal can be used as direct measure for ambient
water vapor mixing ratios. At H2O mixing ratios above 500 ppmv, the
higher clusters H3O+(H2O)2 at 55 amu and
H3O+(H2O)3 at 73 amu become significant in terms of
signal strength.
In-flight calibration curves for two different evaluation methods.
(a) Time series of the H3O+(H2O) (m/z=37 amu)
signal for a characteristic calibration sequence. The corresponding water
vapor mixing ratio, calculated from the AIMS-H2O count rate, is shown in
blue. (b) Count rate on m/z=37 amu vs. H2O in the
calibration gas. In panel (c) the ratio of ion masses
(19+37+55)/(19+32+37+46+55) is plotted against H2O. The gray curves
mark the 95 % confidence interval of the respective fit curves, fit
parameters are given for both calibration methods.
Two data evaluation methods
The data reduction procedure begins with the evaluation of a laboratory or
in-flight calibration and an appropriate application of the calibration to
the flight data. In a second step, corrections for dilution, cross-sensitivities or other influences on the measurement can be applied. For
AIMS-H2O we utilize two different methods to determine the atmospheric
H2O mixing ratio from the count rates measured by the mass spectrometer,
both with benefits and disadvantages. Considering Reactions (R1)–(R4), a
direct way to determine ambient H2O is to calibrate the signal of the
H3O+(H2O) on mass 37 amu at different water vapor mixing
ratios. In doing so, one obtains a calibration as shown in Fig. 7b, derived
from a typical calibration sequence (Fig. 7a). As expected from the multiple
reaction steps to produce H3O+(H2O), the calibration
function is non-linear. For water vapor mixing ratios below 30 ppmv, the
number of H2O molecules is the limiting factor. Since three water
molecules are involved in the reaction pathway from O2+ to
H3O+(H2O), the calibration curve has a cubic shape in that
region. For high H2O, the available number of O2+ ions becomes
the limiting factor, until at a certain H2O mixing ratio all O2+
ions are depleted by Reactions (R1)–(R4). Hence the cubic shape is expected
to change into an exponential saturation. For H2O mixing ratios
> 500 ppmv in AIMS-H2O, no new H3O+(H2O)
ions are formed since O2+ is completely depleted. However,
Reaction (R5) still alters the hydration of the existing ions towards higher
clusters. In that region the amount of H3O+(H2O)2 and
H3O+(H2O)3 increases at the expense of
H3O+(H2O). Although the shape of the calibration curve can
be well understood from the point of reaction kinetics, a fit with two
different functions is rather impractical due to the high number of
parameters and the uncertainty in the transition region. Therefore we apply a
more pragmatic approach and use a logistic fit function:
y=A1-A21+(x/x0)p+A2.
This function is an asymmetric S-shaped curve with an initial value A1
at x=0, a final value A2 for x→∞, a center at x0 and a
power parameter p. This function combines the characteristic shapes
observed in both regimes at mixing ratios < 30 ppmv and between 30
and 100 ppmv. Moreover, it has only four free parameters and can be inverted
analytically, which makes it comfortable to handle. This evaluation method
using only the H3O+(H2O) signal is referred to as
method 1.
Measurement range, accuracy and precision for AIMS-H2O. Remarks
concern the parameters used to determine the precision and detection limit.
For AIMS-H2O, the two values for precision correspond to the two
evaluation schemes using ion mass 37 amu (H3O+(H2O)) and ion
ratio, respectively.
SensitivityAccuracyPrecision (%) Remark(countsppmv-1)(%)37 amuirGlobal (1–500 ppmv)50–4007–154–151.5–15Precision for 4 Hz data@ 5 ppmv (stratospheric)180710 (7)15 (8)Precision for both evaluation methodsand 4 Hz (1 Hz) data@ 100 ppmv (tropospheric)400116.5 (4.5)2 (1.7)Same as above with 1:1 dilution ratio
The confidence bands for method 1 (Fig. 7b) widen significantly when
approaching mixing ratios of 50 ppmv and above, indicating an increasing
uncertainty in the fit function and consequently in the determination of the
ambient mixing ratio. Therefore, an alternative evaluation method is shown in
Fig. 7c and referred to as method 2, which uses additional information
provided by the signal of the other H3O+ clusters, NO2+ and
most importantly O2+. The signal ion ratio is then calculated as
ir=∑n=02[H3O+(H2O)n][O2+]+[NO2+]+∑n=02[H3O+(H2O)n],
where the brackets symbolize the count rate on the respective ion mass. This
method includes all ions with significant count rates that respond to changes
in H2O. The idea behind the approach is to normalize counts of all water-dependent ions to the overall ion counts offering some benefits compared to
the single ion evaluation: (1) the signal to noise ratio is improved, (2) the
method automatically accounts for any (e.g., temperature-induced) drifts in
the efficiency of the ion source, (3) the confidence bands of the logistic
fit for the in-flight calibration stay almost constant over the entire
calibration range. However, as well as working for higher H2O mixing
ratios, the smaller slope of the calibration at mixing ratios below 15 ppmv
increases the precision of the measurement in that region (Table 1). For
mixing ratios between 15 and 70 ppmv, both evaluation methods agree within
±5 %. In order to combine the benefits of both evaluation methods, we
use the single ion method (method 1) for mixing ratios below 15 ppmv and the
ion ratio method (method 2) for H2O mixing ratios above 15 ppmv as
explained in detail in the next section on instrumental uncertainties.
Data quality and sources of uncertainty
The data quality depends on various factors, with sensitivity of the
instrument to a specific trace gas and signal noise being the most important
ones. Additionally, any kind of drift effects modifying the count rates,
cross-sensitivities and uncertainties in the in-flight calibration change
the data quality. In this work, we performed an extensive analysis of
possible sources of uncertainty which is necessary to judge the reliability
of the H2O measurements in the atmosphere.
Sensitivity and detection limits
For the determination of signal noise, the in-flight calibration sequences
are the most useful data since they are free of atmospheric variability and
usually exhibit periods with stable signal long enough for sufficient
statistics. The signal noise is best described by the standard deviation of
the count rate, which increases with the absolute signal. Starting from an
idealized statistical approach, the ion count rates can be described by a
Poisson distribution. Hence, the standard deviation of the signal should
equal the square root of the count rate. In reality, instrumental factors
like variability of the discharge in the ion source, the transmission of the
quadrupole and electrical noise from the detector increase the signal noise
compared to the idealized value. For the complete AIMS setup, all these
factors increase the signal noise roughly by a factor of 2 compared to
pure statistical noise from Poisson theory.
However, data quality is not only determined by signal noise but equally by
the instrument's sensitivity. For a linear calibration, sensitivity and
signal noise are usually used to determine the detection limit (MacDougall
and Crummett, 1980). The detection limit is the value below which the signal
cannot be distinguished statistically from the background noise within a
certain statistical significance. Assuming a constant calibration factor CF
and a standard deviation σ0 of the zero air signal, the detection
limit DL is defined as
DL=CF×σ0.
The classical combination of sensitivity and detection limit cannot be
directly transferred to the water vapor measurements with AIMS-H2O for two
reasons. First, the calibration is non-linear, hence sensitivity depends on
the actual water vapor mixing ratio. Second, the detection limit is not a
useful parameter for water vapor since even the lowest mixing ratios
prevalent in the atmosphere exceed the detection limit by at least 1 order
of magnitude. Hence, for water vapor we apply a different approach evaluating
sensitivity (defined as the first derivative of the calibration curve) and
signal noise as a function of the water vapor mixing ratio
〈H2O〉. We define the effective sensitivity by the
ratio of the sensitivity and noise as a function of
〈H2O〉:
ES(〈H2O〉)=∂[H3O+(H2O)]∂〈H2O〉(〈H2O〉)σH3O+(H2O)(〈H2O〉).
Effective sensitivity, as defined in Eq. (4), for evaluation
method 1 (black) and method 2 (red). ES increases up to ∼10 ppmv due
to the increase in the slope of the calibration curve. At higher mixing
ratios, the decrease of ES is caused by increasing signal noise. Below
15 ppmv, method 1 is used for calculation of atmospheric mixing ratios;
above 15 ppmv, method 2 is used.
This definition is similar to the classical signal-to-noise ratio but
accounts for the change in sensitivity depending on the ambient water vapor
mixing ratio. For the evaluation method 1, the ES reaches its highest
values of 1.3 ppmv-1 for low water vapor mixing ratios of around
5 ppmv (Fig. 8), which are typical values for the lower stratosphere. At
lower H2O mixing ratios, the ES decreases due to the decrease in the
slope of the calibration curve. At higher mixing ratios, the ES is lowered by
increasing signal noise and additionally by decreasing sensitivity at the
upper end of the calibration range. Using 1 Hz data for the calculation of
the ES instead of the 4 Hz data, the ES is higher by a factor of 1.3–1.5.
The ES can equally be calculated for method 2 by replacing the count rate
[H3O+(H2O)] by the ion ratio ir (red lines in Fig. 8).
Comparing the ES values for both evaluation methods one obtains a measure of
which method provides better data quality in a certain mixing ratio range. As
can be expected from the shape of the calibration curve in Fig. 7c, the
smaller slope at very low mixing ratios results in a reduced ES for the ratio
approach in that region. At higher mixing ratios, the ES using method 2 is a
factor of 1.5 (at 35 ppmv) to 4 (at 120 ppmv) higher than that using the
single ion evaluation. Hence this method provides better data quality in this
region. Although the ES is higher for method 2 compared to method 1 already
at mixing ratios above 2 ppmv, in practice method 1 (Fig. 8), using the
H3O+(H2O) count rate only, is more reliable and stable for
mixing ratios below 15 ppmv. A possible reason for this might be that at low
mixing ratios there is a large abundance of O2+ product ions. Thus,
the reaction of H2O to H3O+(H2O) is almost
independent of the actual number of O2+ ions. When including the
O2+ count rate in the data evaluation process, fluctuations in the
O2+ count rate (e.g., temperature induced) are likely to be
incorrectly interpreted as a water vapor signal. That increases the
uncertainty of the measurement rather than providing an additional source of
information as it does for the higher mixing ratios.
Instrumental uncertainties
In addition to the uncertainty arising from the calibration procedure, the
fitting procedures and the approximations in data evaluation, a couple of
other effects can lead to an increased uncertainty of the measurement with
AIMS.
One factor increasing measurement uncertainty is an observed dependence of
the quadrupole transmission on the cabin temperature in the aircraft. The
control electronics for the oscillating circuit are found to decrease the ion
transmission through the quadrupole with increasing cabin temperature. Since
this effect applies to all measured ions, the evaluation methods using
absolute ion counts for AIMS-H2O is affected most. Methods using ion
ratios are only affected by a mass- or count rate-dependence in the change in
ion counts. During flight, the effect is of minor importance since the air
conditioning provides a fairly stable (±1∘C) temperature
environment. However, the temperature dependence is identified to be a major
cause for the observed discrepancy between airborne and ground measurements.
The temperature dependence is hard to quantify in laboratory measurements,
but is addressed by a thorough in-flight calibration of the instrument.
A second important point influencing the measurement is the possible
artifact created by water desorbing slowly from the walls of the vacuum
chamber. In contrast to laboratory measurements where the turbomolecular
pumps run continuously for several days, the chamber must be pumped down
before every flight. This takes around 3 h prior to takeoff in order
to achieve stable vacuum conditions. Between the flights, the vacuum chamber
is either sealed under vacuum or filled with dry nitrogen. Both procedures
result in a similar time needed for the subsequent evacuation of the
chamber.
Not only the vacuum chamber, but also the inlet line can be contaminated
with water vapor and other trace gases. In order to minimize the effect of
moisture in the inlet, the whole inlet line is routinely flushed with dry
nitrogen during taxi and takeoff. Since components of the flow system with
high surface areas, such as the pressure regulation valve, exhibit a
passivation and hysteresis which can change typical response times by up to
a factor of 3, the effect depends on the measurement history.
Overall, the accuracy of the instrument is determined to be between 7 and
15 %, where the uncertainty of the in-flight calibration and the dilution
correction are the major contributors. The best accuracy can be achieved in
the range between 10 and 40 ppmv H2O where the instrument is most
sensitive. For lower mixing ratios, the relative accuracy increases due to
error sources with constant contribution – e.g., offsets in the mixing ratio
of the calibration flow. At higher mixing ratios, the accuracy decreases
mainly due to an increased uncertainty in the conversion efficiency of the
catalytic water vapor source and due to the dilution
correction.
Cross-sensitivity
We investigated the cross-sensitivity of selected trace gases on H2O
detected with AIMS-H2O. We observed no significant cross-sensitivity of
ozone, which is consistent with previous investigations (Thornberry et al.,
2013). In the same study, they found a very small influence of CH4 of
about 1 % of the sensitivity on H2O on their H3O+ signal.
Given typical ambient CH4 concentrations of around 1.8 ppmv, we obtain
a possible bias of 0.018 ppmv which is much smaller than the dominant
sources of uncertainty of the in-flight measurements. For CO2,
Thornberry et al. (2013) reported a decrease in sensitivity of around
10 % when adding ambient CO2 mixing ratios of 380 ppmv to the
sample flow. In order to evaluate the possible influence of CO2 for the
different ionization source we use here, two separate calibrations with and
without CO2 were performed with AIMS-H2O. In these calibrations, we
did not observe any change in sensitivity of the H3O+(H2O)
ion with or without additional CO2.
Time series of H2O mixing ratio (bottom panel) from a flight on
7 April 2014 during the ML-CIRRUS campaign. The blue curve is the gas phase
measurement of AIMS-H2O. For comparison, measured mixing ratios from the
SHARC TDL (gray) are shown. For the high mixing ratios between 34 000 and
35 600 s, the sample flow of AIMS-H2O was diluted with synthetic air.
The top panel shows the flight altitude, the middle panel denotes the
relative difference between both instruments. Data from both instruments
agree reasonably well.
Flight performance of AIMS-H2O on HALO during ML-CIRRUS
AIMS-H2O flew on the DLR Falcon in 2011 (Kaufmann et al., 2014; Voigt et
al., 2014) and on HALO during the ML-CIRRUS experiment in March/April 2014.
In order to provide an example of the performance of AIMS-H2O, the water
vapor time series of flight 9 on 7 April 2014 is shown in Fig. 9. The scope
of this flight was to study contrail cirrus above Germany. The contrail
cirrus were embedded in a frontal cirrus system extending above western and
eastern Germany. In addition, we planned an intercomparison with ground-based
lidar measurements in Munich and Leipzig and with data from a radiosonde
launched in Lindenberg. To this end, HALO took off from Oberpfaffenhofen,
near Munich, at 07:00 UT and performed three transects in the heavily
traveled airspace between Frankfurt and Berlin before returning to
Oberpfaffenhofen. Two transects were selected for in situ measurements of
contrail cirrus and natural cirrus while the third stratospheric transect
focused on remote sensing of the cirrus/contrail cirrus clouds with the
onboard lidar system. Hence, in this flight we performed measurements inside
cirrus clouds and in cloud-free air at a range of water vapor mixing ratios
down to 4 ppmv.
Besides data from AIMS-H2O, H2O mixing ratios measured by the tunable
diode laser hygrometer SHARC are shown in Fig. 9. SHARC is regularly
calibrated on the ground using a MBW373-LX as reference, and has been shown
to agree well with the established hygrometer FISH (Meyer et al., 2015). Both
instruments measured gas phase water vapor via an actively pumped backward-facing inlet. The agreement between the two instruments is excellent at water
vapor mixing ratios below 150 ppmv during a large part of the flight after
36 000 s UTC. In particular, at H2O mixing ratios down to 10 ppmv,
the agreement is within ±5 %. Since the measurement range of the
SHARC instrument is limited to mixing ratios above 10 ppmv, no comparison
could be done for the flight legs in the lower stratosphere.
At the beginning of the flight between 33 300 s and 35 600 s UT, H2O
mixing ratios measured by AIMS-H2O were 12–15 % higher than the SHARC
data, while short-timescale H2O variations were very similar. We
speculate that AIMS-H2O might overestimate the water vapor mixing ratio
near 300 ppmv during that flight sequence due to a bias in the dilution
correction. This effect is not permanent, but rather a feature observed only
during that flight. However, the deviations are still within the combined
uncertainty of both instruments (10 % for SHARC). Regarding the relative
humidity with respect to ice (RHi) derived from H2O mixing ratios and
static air temperature measurements from HALO, AIMS measured a slight mean
supersaturation with respect to ice in that sequence while SHARC measured a
slight mean subsaturation (lower panel in Fig. 10). Both instruments detected
rapid fluctuations in RHi between 60 and 140 %. Here we use the ice water
content (IWC) calculated from the total water measurement by the Water vapouR
Analyzer (WARAN) tunable diode laser instrument (Groß et al., 2014) as an
indicator for the occurrence of cirrus clouds (top panel in Fig. 10). The
large variation in IWC suggests that we sampled a rather inhomogeneous cirrus
cloud during the sequence from 33 300 to 35 600 s, which is consistent
with the scatter of RHi around saturation. In later parts of the measurement
sequence in Fig. 10 (36 000–38 000 s), the IWC suggests a more dense and
homogeneous cloud while both AIMS and SHARC indicate a mean subsaturation at
around 91 % RHi. For the two following cirrus penetrations at 37 000 and
37 800 s, RHi again fluctuates around saturation in both water vapor
instruments. The uncertainty of RHi (∼15–20 %) is almost equally
distributed between uncertainty of the H2O gas phase measurement and the
uncertainty of the static temperature measurement made from the aircraft
(0.5 K).
Top: ice water content (IWC) as cloud marker derived from total
water measurements by the WARAN tunable diode laser instrument. Bottom:
relative humidity with respect to ice calculated from AIMS H2O mixing
ratios (blue curve) and SHARC mixing ratios (gray curve) using the HALO
static air temperature measurement. Except for the middle part from 36 000
to 38 000 s where the in-cloud RHi is below 100 %, RHi typically
scatters around saturation inside the clouds.
In order to obtain a quantitative impression of the instrument performance
over the entire campaign, Fig. 11 shows a scatter plot of H2O mixing
ratios measured by AIMS-H2O and SHARC with an extensive set of 112 529
data points gathered in March/April 2014. The linear fit (H2O(AIMS) =1.007×H2O(SHARC)+1.66 ppmv) shows the excellent
overall agreement between the instruments, with a very high correlation
coefficient of 0.993 giving high confidence in the data quality from both
AIMS-H2O and SHARC. The scatter of the data is comparable to the
intercomparison published by Rollins et al. (2014).
While this paper focuses on the instrument description of AIMS-H2O, a
further detailed intercomparison of the set of water vapor instruments
participating in ML-CIRRUS is beyond the scope of this paper and will be
published elsewhere.
H2O mixing ratio of AIMS-H2O plotted versus the mixing ratio
measured by SHARC with data from the entire ML-CIRRUS campaign (gray dots).
Offset, slope and correlation coefficient of the linear fit function (black
line) indicate an excellent overall agreement between both instruments.
Summary and outlook
With the airborne mass spectrometer AIMS, we developed a measurement
technique to quantify low water vapor mixing ratios typical for the upper
troposphere and lower stratosphere. To this end, we built a new gas discharge
ion source which directly ionizes ambient air sampled via a backward facing
inlet. In a multi-step reaction similar to the reactions in the D-region of
the ionosphere, water vapor molecules in ambient air react to
H3O+(H2O)n (n= 0…3) ions which are detected
by the mass spectrometer. We perform a comprehensive and in-depth error
analysis and achieve a high accuracy between 7 and 15 % in the
measurement range between 1 and 500 ppmv, depending on specific humidity and
time resolution of the measurement. The accuracy is established by regular
in-flight calibration of the instrument using a water vapor standard
generated by the catalytic reaction of hydrogen and oxygen on a heated Pt
surface.
In order to increase the signal quality, two different data evaluation
methods are used to determine ambient water vapor mixing ratios from the
respective ion count rates. For water vapor mixing ratios below 15 ppmv, we
use the count rate of H3O+(H2O) at m/z= 37 to
determine atmospheric water vapor. For higher mixing ratios, a normalized
signal including all water vapor dependent ions provides better data quality.
Major other contributors to uncertainty in the measurement are contamination
of the vacuum chamber and inlet line with water vapor, and especially the
temperature dependence of the quadrupole transmission.
AIMS-H2O has been successfully deployed on the two DLR research aircraft
Falcon and HALO during CONCERT in 2011 and ML-CIRRUS in 2014, where the
comparison with airborne TDL hygrometer SHARC showed reasonable agreement
within ±10 % for most of the data.
During the CONCERT 2011 mission, AIMS-H2O data proved to be well suited
for accurate measurements of relative humidity in contrails and contrail
cirrus environments (Kaufmann et al., 2014). In future, open questions
regarding contrail microphysics (Voigt et al., 2011; Jeßberger et al.,
2013; Schumann et al., 2013) and the persistence of contrails (Gayet et al.,
2012; Kübbeler et al., 2011) will be addressed using ML-CIRRUS data from
AIMS-H2O. In addition, we will perform a thorough intercomparison of the
set of water vapor instruments operated on HALO to assess the quality of
water vapor in situ measurements in the lower stratosphere in mid-latitudes.
These data will help to better quantify uncertainties in H2O mixing
ratios in mid-latitudes, similar to the assessment of Rollins et al. (2014).
With the 4 Hz time resolution, water vapor and supersaturation fluctuations
can be investigated at spatial scales of the order of 50 m (Kärcher et
al., 2014).
Including H2O measurements with a frost point hygrometer (Voigt et al.,
2010) from a series of campaigns, we envisage constructing a database of
high-quality in situ H2O measurements in the UTLS which can be used for
comparison with lidar observations (Groß et al., 2014), meteorological
and balloon sondes (Hurst et al., 2011), satellite data (Hegglin et al.,
2013) and for model validation (Hegglin et al., 2014; Solomon et al., 2010).
With the flexible airborne mass spectrometer AIMS, we have developed a
multitool to address key issues concerning atmospheric composition of the UTLS
and processes related to trace gas transport, cloud formation and climate.
Acknowledgements
We thank the German Science Foundation DFG for funding within HALO-SPP 1294
under contract VO 1504/2-1. Christiane Voigt, Stefan Kaufmann and Tina Jurkat
are grateful for financing by the Helmholtz Association under contract VH-NG-309 and
under contract W2/W3-60. We thank Andreas Minikin, Ulrich Schumann and DLR
Flight Experiments for the coordination and realization of the ML-CIRRUS
campaign and Greta Stratmann for helpful comments on the
paper.The article processing charges for
this open-access publication were covered by a Research
Centre of the Helmholtz Association. Edited by: D. Baumgardner
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