Introduction
Formic acid (HCOOH, hereafter referred to as HFo), acetic acid
(CH3COOH, hereafter referred to as HAc), and
hydroxyacetaldehyde (HOCH2CHO, commonly referred to as
glycolaldehyde, and hereafter abbreviated as GA) are oxygenated
volatile organic compounds (OVOCs) found in remote and urban
environments in both gas and particle forms. Primary emissions for
both acids include vegetation, agriculture, biomass burning, and motor
vehicle emissions (Khare et al., 1999; Paulot et al., 2011). Secondary
sources also play a substantial role in the formation and distribution
of HFo and HAc and include photochemical production from gaseous VOCs
and OVOCs of biogenic and anthropogenic origin, biomass burning, and
primary and secondary organic aerosols (Khare et al., 1999; Paulot
et al., 2011). Both organic acids are photochemically long lived (>10 days with respect to HO photooxidation) and their removal is
primarily by dry and wet deposition at Earth's surface (Paulot
et al., 2011). Away from Earth's surface, these acids represent
a relatively long-lived intermediate product in the oxidation of
organic matter. However, there is a scarcity of organic acid
measurements in the upper troposphere with which to compare and assess
photochemical and transport theory. Millet et al. (2015), Reiner
et al. (1999), and Talbot et al. (1996) reported vertical profiles for
HFo and HAc; however, only Reiner et al. and Talbot et al. sampled
above 7 km. In remote environments, HFo and HAc are the
primary acids establishing the pH of cloud water and precipitation
(Galloway et al., 1982). HFo and HAc partitioning between gas and
aqueous phases is pH dependent. In the aqueous phase, both HFo and HAc
remain in the protonated form below their pKas of 3.75 and 4.76
(T=298.15 K), respectively (Johnson et al., 1996). As
emission controls on anthropogenic NOx and SO2
continue to decrease the contributions of these gases to precipitation
acidity, the organic acids are expected to compose a larger fractional
contribution to acidity in cloud water and precipitation.
Hydroxyacetaldehyde (or GA) is formed by the HO
oxidation of biogenic VOCs such as isoprene and methyl vinyl ketone (MVK)
(Lee et al., 1998; Tuazon and Atkinson, 1989) and by the HO oxidation
of unsaturated anthropogenic VOCs like ethene (Niki et al., 1981). GA
has also been measured in smoldering biomass burning plumes and can be
up to 1 % of the gaseous carbon detected in fire emissions
(Johnson et al., 2013; Yokelson et al., 1997). Table S1 provides
a summary of literature surface and aircraft measurements for GA in
urban, biomass burning, biogenic, and mixed environments. GA's primary
loss is by HO oxidation and wet deposition (Bacher et al., 2001). The
effective Henry's Law constant for GA (70 MhPa-1) is
surprisingly large (Betterton and Hoffmann, 1988) and an order of
magnitude larger than that for HAc (7.8 MhPa-1) at
a temperature of 288 K (Johnson et al., 1996; results
below). GA is more likely than HAc to be removed by precipitation
during transport through deep convection based upon model work by
Barth et al. (2003) and Bela et al. (2016). Unpublished model results
from Bela et al. showed a removal of GA 10 times greater than
HAc in a simulated Deep Convective Clouds and Chemistry
(DC3) deep convective storm.
There is a need to distinctly measure HAc and GA throughout the depth
of the troposphere. They provide a test point for the processing of
VOCs by different photochemical mechanisms. There are multiple
precursors that, depending on the chemical mechanism, will lead to
different portions of HAc and GA as second-generation or later
products. For example, while isoprene is an important precursor for GA,
it is thought to be insignificant for HAc (Y.-N. Lee et al., 1995;
Paulot et al., 2011). However, isoprene is also a significant source
for peroxy acetyl radical, which reacts with HO2 to form HAc
(Khare et al., 1999; Paulot et al., 2011). In addition, GA is relevant
to the tropospheric ozone budget (Y.-N. Lee et al., 1995; Petitjean
et al., 2010) and HAc directly effects precipitation acidity (Khare
et al., 1999; Paulot et al., 2011). Finally, both GA and HAc are
participants in the formation and growth of organic aerosols and in
aerosol photochemical processing (Carlton et al., 2006; Fuzzi and
Andreae, 2006; Lee et al., 2006; Perri et al., 2010; Yu,
2000). Airborne platforms provide one vehicle for instrumentation to
measure these compounds throughout the depth of the troposphere (e.g.,
Le Breton et al., 2012; Lee et al., 1998; Millet et al., 2015; Talbot
et al., 1996) and this adds an additional need for “fast”
instruments, especially for situations in which spatial–temporal
scales are relatively small, such as in the boundary layer or near
convective clouds.
In recent years there has been an increase in the number of
atmospheric gas-phase species measured using chemical ionization mass
spectrometry (CIMS) (Huey, 2007). The major advantages of CIMS include
rapid response times with high sensitivity and selectivity (e.g.,
Bertram et al., 2011; Crounse et al., 2006). Previous studies have
successfully measured gas-phase HFo and HAc via negative-ion-mode CIMS
using trifluoromethoxy anion (CF3O-), iodide
(I-), or acetate (CH3COO-) as the reagent ion
(e.g., Amelynck et al., 2000; Le Breton et al., 2012; Brophy and
Farmer, 2015; Veres et al., 2008). Yuan et al. (2016) reported HFo and
HAc using a H3O+ time-of-flight CIMS. Brophy and Farmer (2015)
developed a dual reagent ion system with I- used for HAc and
CH3COO- used for HFo, in which the reagent gases are
added in an alternating sequence. However, to our knowledge, to date
only one group has reported results for both HFo and HAc using an
I-CIMS (Lee et al., 2014). Proton-transfer-reaction mass
spectrometry (PTR-MS) has been used to quantify HFo and HAc with
H3O+ as the reagent ion (e.g., Müller et al., 2014); Wisthaler reports the sum of HAc and GA (Armin Wisthaler,
personal communication, 2015) using this methodology.
O'Sullivan et al. (2018) and Heikes et al. (2017) described a CIMS
instrument for the airborne measurement of peroxides called PCIMS. In
the course of developing the PCIMS, the opportunity presented itself
to investigate the sensitivity of HFo and HAc to multiple reagent
ions, specifically I- and O2-. The PCIMS system
was originally developed for the DC3 experiment (O'Sullivan et al., 2018) and modified in
post-mission calibration work. This modified system was then used in
the Front Range Air Pollution and Photochemistry Éxperiment
(FRAPPÉ) (Treadaway, 2015) and modified again
post-mission. The reason behind the post-mission DC3 development
involves serendipity and foresight. Prior to the DC3 mission, the
PCIMS underwent optimization for the measurement of hydrogen peroxide
and methyl peroxide and, before settling on a CO2-in-air
reagent gas for the peroxides, a CH3I-in-N2 reagent
gas was tested (O'Sullivan et al., 2018). I-, derived from
CH3I, proved to provide sufficient sensitivity for hydrogen
peroxide (H2O2, hereafter referred to as HP) but not
for methyl
peroxide (CH3OOH, hereafter referred to as MHP), which was a critical species for the PCIMS, especially for the
identification of deep convective storms during DC3 (O'Sullivan
et al., 2018). CH3I is a “sticky” gas and, even though the
reagent storage cylinder, regulator, and transfer lines had been
flushed, there remained a finite amount of CH3I in the system,
which bled off the reagent line's interior surfaces. Evidence of this
was observed at m/z ratios of 127 (I-), 145
(I-(H2O)), and 147 (I-(H218O)). It was
further noted that in addition to a m/z signal at 161
(I-(H2O2)), there were m/z signals at 173 and 187,
which were ascribed to HFo (I-(HFo)) based on the work of Le
Breton et al. (2012) and to HAc (I-(HAc)), respectively. In
DC3, the m/z signals at 173 and 187 were recorded with the
expectation that post-mission laboratory calibration work would allow
HFo and HAc to be quantified in the upper troposphere. This
calibration work appeared to be successfully accomplished in the
laboratory and validated in-flight during the FRAPPÉ mission in
2014. However, post-FRAPPÉ, GA, a potential isobaric interference,
was confirmed for I- chemistry with a relative response of
approximately 1:1 for HAc : GA. We necessarily report the
m/z 187 signal as the “acetic acid equivalent sum” (AAES) of HAc
and GA in our prior DC3 and FRAPPÉ datasets (data reporting in
progress).
This study details the detection and quantification of HFo and AAES
using a multi-reagent ion CIMS. The multi-reagent ion PCIMS is unique
as it allows the detection of HFo and AAES, as well as HP and MHP. The
multi-reagent ion gas system blends a CO2 in air mixture and
a CH3I in N2 mixture with pure N2. This is
different from other multi-reagent ion systems such as Brophy and
Farmer (2015), as the two reagent gases are added simultaneously and
tuned such that I-, O2-, and
O2-(CO2) ion cluster chemistries are
operable. O'Sullivan et al. (2018) presented PCIMS measurements for HP
and MHP using O2-(CO2) and O2-,
respectively. Heikes et al. (2017) presented an ion-neutral chemical
kinetic model to simulate the ion chemistry presented here and in
O'Sullivan et al. (2018). Here, we report the
results of the PCIMS calibration work with CH3I for HP, MHP,
HFo, and HAc and interference work with ethanol, propanol, and GA to
determine (1) the nominal CH3I concentration inadvertently
used in DC3, (2) pressure- and humidity-dependent sensitivity factors
for these analytes using I- cluster chemistry,
(3) interference characterization of a few common trace atmospheric
gases, and (4) initial DC3 and FRAPPÉ HFo and AAES observations by
the PCIMS instrument. The I- molecule cluster kinetics were
described in greater depth in Heikes et al. (2017).
Methods
Field campaigns
The DC3 field campaign was
conducted in the central US in May and June 2012. The PCIMS
was on board the National Center for Atmospheric Research Gulfstream V
aircraft (HIAPER; UCAR, 2005), which flew 22 research flights ranging
west to east from the Colorado Front Range to North Carolina, north to
south from Nebraska to the Gulf of Mexico, and from the boundary layer
to 13 km. A description of the project, platforms,
instrumentation, and measurements can be found in Barth et al. (2015).
FRAPPÉ consisted of 15 research flights in July and
August 2014. The PCIMS was flown on the National Center for
Atmospheric Research C-130 (UCAR, 1994) and primarily over the
northern Colorado Front Range from the boundary layer to
8 km. FRAPPÉ was the first campaign to use the two-syringe
microfluidic calibration system (Sect. 2.4) and the three-mixture
blended reagent ion scheme (Sect. 2.3). The project was
a multi-agency, multi-investigator program and details of the
experiment are available online
(https://www.eol.ucar.edu/field_projects/frappe and
http://discover-aq.larc.nasa.gov/).
Instrumental configuration
Continuous gas analysis was performed using a CIMS (THS Instruments,
Inc., Atlanta, GA) in negative-ion mode. The sample and analytical
systems were based on the Slusher et al. (2004) design. Our modified
CIMS, referred to as PCIMS, is depicted schematically in
Fig. 1a, and instrumental settings are listed in Table 1.
PCIMS was specifically designed to meet engineering standards for use
on HIAPER (O'Sullivan et al., 2018). Critical system elements include
a gas sample delivery inlet with calibration system and the PCIMS,
which is composed of a reagent gas blending system, ion generation and
air sample reaction system, ion selection (declustering, ion guide,
and quadrupole), multi-ion counting detector, and vacuum system.
(a) The peroxide chemical ionization mass
spectrometer (PCIMS) instrument is diagramed in panel (a). The inlet samples either ambient air or laboratory-generated pure air (Aadco Instruments Inc., Cleves, OH). RXN
refers to the ion reaction cell, CDC refers to the octopole
collision dissociation chamber, and MFC indicates a mass flow
controller and corresponds to the numbers in Table 1. CIMS
represents the quadrupole mass spectrometer. (b) Laboratory
calibration instrumental set up. Aadco is a pure air generator. CIMS in panel (b)
represents the full PCIMS instrument illustrated in panel (a).
PCIMS instrument settings: voltages, pressures, temperatures, and
MFC set points.
Description
Set point/nominal value
Range
Mass flow controller (MFC)
N2a reagent for P control (MFC 3)
variable
∼2 to 4.6 slpmb
CO2 in Airc reagent (MFC 2)
0.08 slpmc
CH3I in N2d reagent (MFC 1)
0.0005 slpm
∼0 to 0.01 slpm
N2a calibration gas carrier (MFC 4)
0.4 slpm
Inlet excess sample flow (MFC 6)
4.8 slpm
3.6 to 5 slpm
Drawback flow calibration gas (MFC 5)
1.2 slpm
Pressure
RXN cell
22 hPa
CDC chamber
0.61 hPa
Octopole chamber
0.0065 hPa
QMS chamber
0.00011 hPa
Temperature
HIML inlet (FRAPPÉ/DC3)
35 ∘C/70 ∘C
Inlet transfer line (FRAPPÉ/DC3)
35 ∘C/70 ∘C
Liquid-to-gas tee (FRAPPÉ/DC3)
45 ∘C/55 ∘C
CIMS instrument voltages
CDC plate
7 V
CDC DC bias
20 V
CDC RF
2.0 V
Octopole DC bias
-0.04
Octopole RF
2.49
Rear ion detector HV1
3.43 kV
Front ion detector HV2
1.51 kV
a N2 for RXN pressure control and calibration carrier gas was
ultra-high-purity nitrogen (Scott-Marrin) in FRAPPÉ and DC3 and liquid
nitrogen boil-off gas in the laboratory (Air Gas).
b slpm is standard liters per minute (Tref=273.15 K; Pref=1013.25 hPa).
c CO2 (400 ppm) in ultrapure air
(Scott-Marrin).
d CH3I (5 ppm) in ultra-high-purity N2
(Scott-Marrin).
Ambient or laboratory sample air entered the PCIMS system through
a PFA Teflon® inlet and transfer line. In the
laboratory, synthetic air mixtures were delivered to the inlet using
PFA Teflon®. In airborne field work, a HIAPER
Modular Inlet (HIMIL) was hard mounted on the fuselage and extended
beyond the aircraft boundary layer. The HIMIL is aerodynamically
designed to minimize the collection, volatilization, and subsequent
analysis of large aerosol and cloud drop and ice material as an artifact
in gas measurements. The HIMIL and gas transfer lines were heated to
313 K in DC3 and 343 K in FRAPPÉ to minimize
artifacts caused by the adsorption and/or release of the target gases
onto or from inlet surfaces. The HIMIL inlet surfaces were lined with PFA
Teflon® tubing. Field calibrations (Sect. 2.4) were
performed by standard addition to the sample air stream. The PCIMS
responded linearly to the analyte gases measured at a fixed sample
pressure and water vapor mixing ratio and species sensitivity was
determined using a single calibration gas mixing ratio for each
analyte. Analytical blanks (Sect. 2.5) were determined by passing the
sample air stream, with or without calibration gas, through serial
Carulite 200® and NaOH traps. As discussed below,
PCIMS sensitivity varied with sample pressure and water vapor mixing
ratio.
In PCIMS, the sample air passed through a series of chambers to form,
select, and quantify the organic acid ion clusters. The first chamber
was the ion-sample reaction cell – RXN in Fig. 1a. In the reaction
cell, the sample air was mixed with a reagent ion stream (Sect. 2.3)
of which the bulk was pure nitrogen and controlled by mass flow
controllers (MFCs). The total flow through the reaction cell was fixed
at 4.68 slpm (standard liters per
minute; T=273.15 K and P=1013.25 hPa) and the mean
transit time through the reaction cell was 17.8 ms. The
reagent gas mixture was passed through a commercial electrostatic
eliminator (model P2031-1000, NRD, Inc., Grand Island, NY), which
initially contained 20 mCi of 210Po, an alpha emitter, and
thus developed the requisite reagent ion stream (e.g., Heikes et al.,
2017). The electrostatic eliminator was pre-treated with sodium
bicarbonate per THS recommendation (THS Instruments, Inc., Atlanta,
GA) to trap emitted residual nitric acid vapor present in the ion
source from its manufacture. The RXN cell sample inlet and outlet
critical orifices were of fixed diameter and optimized by THS to have
a reaction cell pressure of 22 hPa, given the vacuum pumps and
reagent gas system employed. This pressure was stated to provide the
maximum yield of cluster ions and peak sensitivity and was not further
evaluated, although the work of Iyer et al. (2016) suggested a higher
RXN cell pressure could lead to higher sensitivities for analyte
molecules with eight or fewer atoms. For laboratory work in Narragansett,
RI, and Annapolis, MD, the reagent nitrogen and the sample flow rates
were effectively constant at 2.0 and 2.68 slpm,
respectively. However, in airborne operations, the inlet pressure
decreased with altitude, the sample flow decreased proportionately
because of its fixed orifice area and the reagent N2 flow was
necessarily increased to maintain a constant RXN cell pressure. Note that
a variable critical orifice sample inlet was unavailable at the time
of DC3 and, while available for FRAPPÉ, was not flown then to best
evaluate the DC3 post-mission calibrations and their use in DC3 to
recover HFo and HAc in that program. Consequently, instrument response
in this work varied with sample inlet pressure or sample flow rate and
was quantified in the laboratory and during FRAPPÉ (Treadaway,
2015; Heikes et al., 2017).
Reagent gas
The reagent gas during DC3 was CO2 (400 ppm,
0.080 slpm) in ultrapure air blended with pure N2
(Scott-Marrin, Riverside, CA). The CO2 and air reagent gas
flow rate was optimized for HP and MHP signal response (O'Sullivan
et al., 2018). An iodide source gas (iodomethane, CH3I) was
used during pre-DC3 experiments as a potential reagent gas and was
found to effectively cluster with HP but not with MHP (O'Sullivan
et al., 2018). A residual amount of CH3I had adsorbed onto
the reagent gas handling interior surfaces and was found to bleed off
this plumbing in DC3. Post-DC3, a laboratory CH3I in ultrapure
N2 mixture was developed which reproduced the I-
available during DC3. The CH3I reagent gas was prepared
similarly to Le Breton et al. (2012) but
without the addition of water. Liquid CH3I (Sigma-Aldrich,
St. Louis, MO) was first evaporated into a gas cylinder and diluted
with N2 gas (Scott-Marrin). This CH3I mixture was
further diluted with N2 to a 5 ppmCH3I mixing ratio,
which was found to reproduce the field sensitivities of HP, MHP, and
H218O observed in DC3 (Treadaway, 2015). The final
reagent gas blend of CH3I, CO2, O2, and
N2 yielded responses for I-, O2-, and
O2-(CO2) cluster ions with organic acids,
peroxides, hydroxyacetaldehyde, and water vapor.
Calibration configuration
HFo and HAc standards (HCOOH, >95 %, and CH3COOH,
99.9 %, respectively) were obtained from Sigma-Aldrich. The HP
standard was obtained from Fisher-Scientific (H2O2, 30 %)
and the MHP standard was synthesized (M. Lee et al., 1995). Dilutions of
both were standardized by titration and/or UV absorbance (M. Lee et al.,
1995). In-flight calibrations were performed by microfluidic
injection. Two versions of the microfluidic system were used to inject
the liquid standard into the PCIMS via a nitrogen gas line. For the
first setup, used during DC3, the standard was contained in
a Hamilton glass syringe and injected using a single syringe pump (1×10-6 Lmin-1 aqueous flow rate; KD Scientific
Inc., Holliston, MA). The liquid standard was vaporized in a heating
block (328 K) into a gaseous N2 stream
(0.4 slpm). The disadvantage of this system is that it can
only calibrate for peroxides or organic acids and was used exclusively
for the peroxides, as they were the target analytes of interest. After
DC3, a second microfluidic system was developed which allowed for
calibration of peroxides and organic acids. Both peroxide and organic
acid aqueous standards (in Hamilton glass syringes) were injected (5×10-7 Lmin-1) and evaporated into a N2
gas stream (0.4 slpm) via mixing T junctions and a ballast
PFA Teflon® mixing vessel. Both microfluidic
standard addition systems were contained within the PCIMS instrument
rack. In-flight calibrations were done as part of the FRAPPÉ
program in the summer of 2014 with the second microfluidic
setup. During FRAPPÉ the organic acid aqueous standards were
verified by titration (Treadaway, 2015). The percent errors between
the theoretical and titrated concentrations were 1.00 and 1.51 %
for HFo and HAc, respectively. The FRAPPÉ peroxide aqueous
standards, which were also used in post-mission laboratory work, were
standardized by titration and/or UV absorbance with an estimated
accuracy of 5 and 10 %, respectively.
Sensitivities were determined in-flight by standard addition. The
ambient signal before and after the calibration gas addition was used
to estimate the ambient signal at the time of calibration gas
addition. The sensitivity was then determined by dividing the
calibration gas mixing ratio in the reaction cell by the difference
between the combined standard addition and ambient signal and the
interpolated ambient signal. The sensitivity of each compound is
reported as counts per second per ppb (cpsppb-1). The
average error in laboratory sensitivity for HFo and HAc was 26 and
31 %, respectively. This accounts for error in the PCIMS signal
response and error in instrumental sources (e.g., MFCs).
Henry's Law constants were determined for HFo and HAc using
a gas–aqueous coil equilibrium apparatus. HFo (0.3 mM) and HAc
(0.9 mM) were acidified (0.02 NH2SO4) to keep
each acid in its protonated form and thereby ensure partitioning into
the gas phase according to each acid's Henry's Law constant. Henry's
Law constants from Johnson et al. (1996) were used. Zero air (0.2 or
0.4 slpm) was passed through an equilibration coil in a water
bath kept at 288 or 298 K along with the organic acid
standard. The resulting calibration gas was added to the sample air
stream after humidification (Sect. 2.6). For the work at
298 K, the laboratory room temperature was increased to
303 K to prevent water vapor from condensing on the transfer
tubing walls. This same setup was used for the GA Henry's Law
experiment and the alcohol interference work described below.
PCIMS response and sensitivity to GA at m/z 92 (O2-(GA)) and m/z 187 (I-(GA)) was determined using two
different methods to generate known amounts of GA based upon the
literature: (1) Henry's Law constants of Betterton and
Hoffmann (1988) and (2) the GA vapor pressure determination over neat
GA melt as a function of melt temperature by Petitjean et al. (2010)
with a serial gas dilution system. GA dimer was used as purchased
(Sigma-Aldrich, St Louis, MO).
For the Henry's Law experiment, 3.689×10-4 kg of GA dimer
was dissolved into 1.00×10-4 m3 of pure water
(18 MΩ), yielding
a 0.0614 M solution of GA monomer. The same gas–aqueous
equilibration coil apparatus was used as described above for the
organic acid Henry's Law work. From the data of Betterton and Hoffmann
(1988), the GA Henry's Law constant was predicted to equal
70 MhPa-1 at 288 K. The direct application of
this value to our experiments was referred to as Case 1. Betterton and
Hoffmann noted their Henry's Law constants for GA were significantly
larger than expected. Implicit assumptions in their analysis were that the
GA solution was all monomer (GA and GA hydrate) and that aqueous
hydration–dehydration kinetics were “fast” compared to the
gas–aqueous equilibration timescale of their experimental
system. However, Kua et al. (2013) reported that a 1 MGA
monomer equivalent aqueous solution is a mixture of monomers and
several dimer and trimer compounds. GA monomers were found to comprise
approximately 55 % of their solution with the monomer making up
3 % and the monomer hydrate 52 %. Using the experimental
equilibrium constants determined from Kua et al. (2013) and our “as
monomer” aqueous concentration, our aqueous solution was expected to
be 91 % monomer hydrate, 6 % monomer with the remaining
3 % nearly all dimer. Kua et al. also indicated the kinetics of
the trimer and dimer equilibration was “slow,” up to a few
hours. Using these distributions and an assumption of “fast” monomer
kinetics but “slow” kinetic exchange of trimer and dimer to monomer,
the gas-phase mixing ratio would be 97 % of the reported Betterton
and Hoffmann expected gas-phase mixing ratio at our aqueous
equilibration concentration, referred to here as Case 2. Further, if
the monomer hydration–dehydration kinetics were also “slow”, such
that the monomer hydrate does not have sufficient time in the
equilibrator to convert to monomer (e.g., dehydration rates of
Sørenson, 1972, are on the order of 0.01 to 0.1 s-1
depending upon solution pH), then we would observe as little as
6 % of the GA gas as expected from the Betterton and
Hoffmann (1988) Henry's Law constant and this situation was referred
to as Case 3. The conditions of Case 2 and Case 3 would falsify the
equilibrium assumption and cause the Betterton and Hoffmann Henry's
Law constant to be too large as they noted. Table S2 in the Supplement
lists the expected reaction cell GA mixing ratio for these three cases
at the five equilibration air flow rates used in the Henry's Law
experiments. The GA sensitivity was determined at two reaction cell
water vapor mixing ratios, 1700 and 7500 ppm.
In the melt “vapor pressure” GA source experiments, 1×10-4 kg of GA dimer was placed in a 1×10-5 m3 glass vessel and slowly heated in a stirred water
bath until fully melted at 358 K. A 1×10-3 slpm flow of 532 ppmCO2 in pure air was
passed through the 10 mL vessel holding the melted dimer and
the outflow immediately mixed with an Aadco air stream flowing at
0.3 slpm to prevent deposition of the GA monomer gas onto the
walls of the vessel and gas transfer lines. The residence time of air
in the vessel was 10 min and sufficiently long to allow mixing of the
air over the melt and for the melt to be in equilibrium with gas-phase
GA. The melt remained limpid as the bath temperature decreased to room
temperature, nominally 295 K, and as the water bath was heated
the next day up to a temperature of 358 K. The glass vessel
and gas mixing-Ts were submerged in the water bath and the temperature
was increased from 298 to 358 K in 20 K
increments. The water bath temperature was monitored and this
temperature was used to evaluate the partial pressure of GA above the
melt. Table S3 shows the expected GA reaction cell mixing ratio at
different melt temperatures using the data from Petitjean
et al. (2010).
The potential exists for ethanol and 1-propanol or 2-propanol to be
isobaric interferences in the measurement of HFo and HAc or GA,
respectively, at the PCIMS m/z resolution of 1.0. The PCIMS
sensitivity to these compounds was determined using their respective
Henry's Law constants (Sander, 2015) and the gas–aqueous equilibration
calibration apparatus described above. The alcohols were used as
purchased (Sigma-Aldrich, St Louis, MO) and diluted with pure water to
final concentrations of 1×10-4 M for ethanol,
1-propanol, and 2-propanol.
Blank configuration
Carulite-200® (Carus Corporation, Peru, IL),
a magnesium dioxide–copper oxide catalyst, is an effective ozone and
peroxide destruction catalyst and was used during DC3 as an analytical
blank substrate for the peroxides (O'Sullivan et al., 2018). It
further proved to be effective in removing but not destroying the
organic acids as well. Unfortunately, at low organic acid
concentrations, there can be a positive trap response due to
outgassing from the Carulite-200®. Therefore,
three different traps were tested as organic acid blank substrates:
Cu/NaHCO3, Na2CO3, and NaOH. It was determined that
the NaOH (5 %) trap was effective at removing organic acids but
not peroxides. Running the air sample through the Carulite 200® and then the NaOH trap removed both peroxides
and organic acids with minor outgassing.
In flight, blanks were performed periodically. Field detection limits
were determined from signal variability (3 times the SD) during the
trap-on cycle. The in-flight detection limits were 16 ppt for
HFo and 50 ppt for AAES. In laboratory work, detection limits
were calculated as 3 times the SD of the Aadco background and are
reported in Table 2 as a function of inlet pressure.
Laboratory detection limits (ppt) determined as 3 times the
SD of the blank using a pure air system as a function of
sample inlet pressure (hPa).
Pressure, hPa
HFo, ppt
HAc, ppt
120
46
86
180
23
46
306
13
37
600
18
59
1013
59
120
In FRAPPÉ, the calibration and blank cycles were both
720 s in duration. The calibration gas was on for
75 s and off for 645 s. The calibration gas was turned
on coincident with the blank traps being turned off. The 16 selected
m/z signals were sampled in 3.5 s. The full-response rise
time and fall time for calibration gases on and off were 11 and
7 s, respectively, for peroxides at m/z 80 and 110 and
organic acids at m/z 173 and 187. The full-response fall time and
rise time for the traps on and off were 14 and 11 s,
respectively.
Laboratory instrument calibration conditions: sample inlet
pressure, reaction cell water vapor mixing ratios, and reagent gas reaction
cell mixing ratios.
Sample
Reaction cell
pressure,
water vapor
hPa
mixing ratioa,
ppm
Reaction cell reagent gas mixing ratio
Low
High
CH3I, ppb
CO2, ppm
O2, ppm
N2, ppm
120
40
540
0.575
7.36
3678
996 322
180
50
610
0.580
7.42
3712
996 288
306
90
1100
0.616
7.88
3941
996 059
600
230
4400b
0.814
10.42
5212
994 788
1013
370
7700b
1.174
15.02
7512
992 488
a This work was performed with a water bath at 288 K.b This includes work in a water bath at 298 K.
PCIMS laboratory standard addition mass spectrum for the
multi-reagent ion system showing the I- and
O2-(CO2) masses. The PCIMS was operated at ambient
pressure (1013 hPa) and a 370 ppm reaction cell
water vapor mixing ratio. The mass dwell time was 50 ms. The
O2-(CO2) masses of interest are marked by red
vertical lines and listed in increasing numerical order. These
masses, and the corresponding ion clusters, are m/z 66
(O2-(HP)), m/z 78 (O2-(HFo)),
m/z 80 (O2-(MHP)), m/z 92
(O2-(HAc)), and m/z 110
(O2-(CO2)(HP)). The I- masses of interest
are marked by blue vertical lines and listed in increasing numerical
order. These masses, and the corresponding ion clusters, are
m/z 127 (I-), m/z 147 (I-(H218O)),
m/z 161 (I-(HP)), m/z 173 (I-(HFo)),
m/z 175 (I-(MHP)), and m/z 187 (I-(HAc)).
Note the count scale is linear up to 1000 and logarithmic above
1000.
Laboratory setup
The laboratory setup was described in detail in Treadaway (2015) and
only briefly presented here. In the laboratory, different field
conditions were simulated by varying the water vapor and/or the inlet
pressure of the sample air stream as depicted in Fig. 1b. A zero-air
generator (Aadco Instruments Inc., Cleves, OH) supplied the sample air
stream to prevent the addition of organics and excess water into the
system. This air stream was split between “dry” and humidified
lines. The dry line came directly from the Aadco. The water
concentration in the humidified line was controlled with two gas
washing bottles and a gas–water equilibration coil immersed in a water
bath kept at 288 or 298 K. By changing the ratio of air flow
through the dry and humidified lines, it was possible to alter the
overall water vapor mixing ratio in the air stream entering the
PCIMS. The inlet pressure was manually controlled after humidification
with a needle valve (V, Fig. 1b) and a pressure transducer. The needle
valve was able to approximate the atmospheric altitude and pressure
conditions (sea level to 14 km, approximately 120 hPa)
experienced in the field and inlet pressure change impacts on signal
response or sensitivity were investigated (Treadaway, 2015). The
reaction cell water vapor range, reagent gas reaction cell mixing
ratios, and sample pressures used in the laboratory are given in
Table 3.
Results
A laboratory calibration mass spectrum (Fig. 2) highlights the
O2-, O2-(CO2), and I- cluster
signal responses for HP, MHP, HFo, and HAc in the multi-reagent ion
system. For this scan, the dwell time at each mass was 50 ms and the
ambient pressure was 1013 hPa, and the reaction cell water
vapor mixing ratio was 370 ppm. PCIMS signal responses for HP
include m/z 66 (O2-(HP)), m/z 110
(O2-(CO2)(HP)), and m/z 161 (I-(HP)). MHP
is measured at m/z 80 (O2-(MHP)) and m/z 175
(I-(MHP)). See O'Sullivan et al. (2018) and Heikes
et al. (2017) for a more complete discussion of the ion cluster
chemistry of HP and MHP. HFo responds at m/z 78
(O2-(HFo)) and at m/z 173 (I-(HFo)). HAc
responds at m/z 92 (O2-(HAc)) and m/z 187
(I-(HAc)) as does GA. The I- concentration in the
PCIMS is monitored with the I-(H218O) cluster
(m/z 147). The I- signal in the PCIMS (m/z 127) is
marked as well for reference and under the reagent conditions
saturates the detector; similarly the signal at 145 for
I-(H2O) was typically saturated as well.
Laboratory calibration sensitivities (cpsppb-1)
for five CH3I flow rates (0.5–2.0 sccm) and FRAPPÉ
in-flight calibration sensitivities as a function of reaction cell
water vapor mixing ratio (ppm) for (a) I-(HFo)
at m/z 173, (b) I-HAc at m/z 187,
(c) I-(HP) at m/z 161, and
(d) I-(MHP) at m/z 175. Note the scale
difference for (d). The horizontal bar represents the limits of the
reaction cell water vapor mixing ratio bin and the mean sensitivity
of that bin is plotted. The length of the vertical bar represents
1 SD and the variability represents random variations in pressure,
ambient concentrations during the standard addition, and systematic
variations due to water vapor in a bin, calibration gas precision,
and instrumental precision.
This blended reagent ion system hinges on a balance between the iodide
and oxygen chemistry. In general, as the proportion of CH3I
increased the sensitivity of the CO2 and O2 clusters
decreased with the impact on MHP being greater than that for HP. The
PCIMS is not as sensitive for HAc as for HFo (Fig. S1 in the Supplement, Figs. 3 and 4) and
a sufficient amount of CH3I is needed to promote HAc
clustering. Therefore, finding a balance between the two reagent gases
ultimately depends on a prioritization between MHP and HAc. For this
reason, five CH3I flow rates (0.0005, 0.001, 0.0015, 0.002,
and 0.0025 slpm) were evaluated. Figure S1 shows I-
cluster laboratory sensitivities for I-(HFo),
I-(HAc), I-(HP), and I-(MHP) as
a function of CH3I flow rate. Figure S2 shows the laboratory
MHP sensitivity at m/z 80 (O2-(MHP)) as a function of
CH3I flow rate. All of the pressure and water work is combined
together which accounts for the large variance shown (1 SD). The ion
clusters' water dependencies are discussed below. As the CH3I
flow rate increased, the O2-(MHP) sensitivity
decreased. As expected, the sensitivities of the I-(HFo),
I-(HAc), I-(HP), and I-(MHP) clusters
increased as the CH3I flow rate increased with an approximate
doubling in sensitivity for HFo and HP corresponding to a doubling
in CH3I flow rate. Overall an increase in CH3I, and
consequently I-, resulted in an increase in
I-(HAc) sensitivity but at the cost of decreasing the
O2-(MHP) sensitivity. It was fortuitous that there was
enough CH3I present during DC3 to promote organic acid
clustering without impairing the O2-(MHP)
sensitivity. The data of Fig. S3, I-(HP) in Fig. 3, and
those for O2-(HP), O2-(CO2)(HP) (not
shown) were used to identify the CH3I flow rate of
0.0005 slpm as providing the best sensitivity matches to the
DC3 calibration data for HP and MHP.
FRAPPÉ in-flight sensitivities (cpsppb-1) as
a function of reaction cell water vapor for all PCIMS clusters. The
left panel contains all the O2- cluster and the right
panel contains all the I- clusters. The horizontal and
vertical error bars represent the same information as in
Fig. 3. O2-(CD3OOH) refers to the deuterated MHP
standard.
Figure S3 shows the MHP calibrations at m/z 80
(O2-(MHP)) from DC3 as a function of reaction cell
water vapor mixing ratio. Laboratory-derived MHP sensitivity at
m/z 80 is also shown as a function of reaction cell water vapor
mixing ratio for five different CH3I flow rates. The data are
binned by the reaction cell water vapor mixing ratio. The mean
sensitivity for that bin is plotted and the horizontal bar represents
the limits of the reaction cell water vapor mixing ratio. The length
of the vertical bar from the mean represents 1 SD and includes
random errors associated with variations in pressure, ambient
concentrations during the standard addition, and systematic variations
due to water vapor in a bin, calibration gas precision, and
instrumental precision. Figure 3 shows I- cluster
sensitivities for I-(HP), I-(MHP),
I-(HFo), and I-(HAc) for the FRAPPÉ experiment
and from the same CH3I laboratory work as in Fig. S3. The
horizontal and vertical error bars represent the same information as
in Fig. S3.
The laboratory calibration technique was verified by comparison to
in-flight calibrations from FRAPPÉ. The in-flight FRAPPÉ
calibrations are included in Fig. 3. The first two FRAPPÉ flights
are omitted due to in-flight vibrations (Heikes et al., 2017). HAc
calibrations were not available for all flights due to contamination
issues in the hanger (Heikes et al., 2017) and vibration. The
vibration problem led to “chatter” in the MFCs and
their orientation and location within the instrument rack were modified
between flights several times. The HFo and HAc laboratory
sensitivities were similar to the FRAPPÉ in-flight
calibrations. HAc sensitivity decreased with water above
1000 ppm. The HP and MHP FRAPPÉ sensitivity averages were
higher than the 0.0005 slpm laboratory work but within the
error. I-(MHP) was independent of water but there appeared
to be a water sensitivity maximum for I-(HP) at about
1000 ppm reaction cell water vapor. There was a pressure
dependency in the sensitivity of I-(HFo) and
I-(HAc); however, it was found insignificant compared to the
dependence with water vapor and is not discussed
further. Treadaway (2015) contains a complete analysis of the pressure
dependency investigation.
FRAPPÉ in-flight sensitivities as a function of reaction cell
water vapor for PCIMS analyte clusters are shown in Fig. 4. The
horizontal and vertical error bars represent the same information as
in Figs. S3 and 3. Figure 4a contains the O2- cluster
calibration data for HP, MHP, HFo, and HAc. The
O2-(CO2)(HP) cluster is also included on
Fig. 4a. O2-(HAc) sensitivity was independent of water
vapor but the other four compound sensitivities decreased with
increasing water vapor over the range of reaction cell water vapor
mixing ratios observed in FRAPPÉ. Figure 4b shows the I-
cluster sensitivities for HP, MHP, HFo, and HAc. As described above,
the I-(HP) and I-(HAc) sensitivities decreased
with water vapor mixing ratio whereas I-(HFo) and
I-(MHP) increased with reaction cell water vapor mixing
ratio.
Henry's Law constants were determined for HFo and HAc at 288 and
298 K and are presented in Table 4 along with the reaction
enthalpies. A wide range of Henry's Law constants from 5.4 to
13 MhPa-1 and 5.4 to 9.2 MhPa-1 have been
reported for HFo and HAc at 298 K, respectively (Sander,
2015). Of the measured values reported in Sander (2015), only Johnson
et al. (1996) experimentally determined the Henry's Law constants at
multiple temperatures. Our Henry's Law constants compared best to
those given by Johnson et al. (1996), especially for HAc. The Henry's
Law constants for HFo were lower than the Johnson et al. (1996)
values. The difference in Henry's Law constants could be due to
a higher gas-phase partitioning through the coil system than measured
by Johnson et al. (1996). Our reaction enthalpies for HFo were higher
than the Johnson values, which also could be due to a higher gas-phase
partitioning in our system. The HAc smaller reaction enthalpy,
relative to Johnson's value, was likely due to the higher Henry's Law
constant for HAc at 298 K. It is the only value in our work
that is higher than Johnson. It is possible that at the higher
temperature, and therefore higher water vapor mixing ratio in the
reaction cell (Treadaway, 2015), we were actually seeing a decrease in
HAc sensitivity not captured in the laboratory syringe calibrations
that occurred at lower water vapor mixing ratios. This would have
caused us to overestimate our Henry's Law constant.
Henry Law constants and enthalpies for formic and acetic acid.
Species
Temperature,
KH
KH
ΔHr,
ΔHr,
K
this work,
Johnson et
this work,
Johnson et
MhPa-1
al. (1996),
kJmol-1
al. (1996),
MhPa-1
kJmol-1
Formic acid
288
13.9
17.9
-65
-51
298
5.6
8.8
Acetic acid
288
7.8
8.4
-33
-52
298
4.9
4.1
Glycolaldehyde and acetic acid PCIMS reaction cell
sensitivities (cpsppb-1) for the
1700–7500 ppm reaction cell water vapor mixing ratio
range. Glycolaldehyde sensitivities at m/z 92 (O2-(GA)) and m/z 187 (I-(GA)) are for the Henry's Law source experiment, T=288 K.
Acetic acid microfluidic sensitivity at m/z 92 (O2-(HAc)) and m/z 187 (I-(HAc)) are based on laboratory and field data presented in
Figs. 3 and 4. All sensitivities are reported from low to high water.
Sensitivity
Sensitivity
at m/z 92
at m/z 187
(cpsppb-1)
(cpsppb-1)
Glycolaldehyde
Case 1 and Case 2
8–20×103
8–10×102
Case 3
10–30×104
10–20×103
Acetic acid
Fig. 3
NA
1.4–1×103
Fig. 4
1.4–1.6×104
1.4–1×103
NA indicates not available.
Ethanol (hereafter referred to as EtOH), 1- and 2-propanol (hereafter
referred to as 1- and 2-PrOH), and GA are potential
isobaric interferences for I-(HFo) and
I-(HAc). The PCIMS sensitivity to I-(EtOH),
I-(1-PrOH), and I-(2-PrOH) was quantified
using the Henry's Law equilibration system. The PCIMS was
substantially more sensitive to HFo and HAc compared to these
alcohols. At the lowest tested reaction cell water vapor mixing ratio
(∼30 ppm), the PCIMS was 140 times more sensitive to HFo
compared to EtOH and the ratio increased with increased water vapor
mixing ratio. At the lowest reaction cell water vapor mixing ratio,
the PCIMS HAc sensitivity was 140 and 90 times those for 1- and
2-PrOH, respectively. As with the EtOH measurements, the sensitivity
to HAc relative to 1- and 2-PrOH increased with increasing reaction
cell water vapor mixing. Baasandorj et al. (2015) performed a similar
study for EtOH and 2-PrOH using a PTR-MS instrument and reaction cell
water vapor range equivalent to 2500–15 000 ppm. They found
the HFo sensitivity to be 6 to 15 times higher than that for EtOH and
their HAc sensitivity was 200–300 times higher than that for 2-PrOH
over their experimental humidity range. It should be acknowledged that
these two techniques are different and some of the masses detected by
the PTR-MS were fragments of the alcohols. While a time-of-flight CIMS
can distinguish the alcohols from the organic acids (Yuan et al.,
2016), there is a paucity of quadruple I- CIMS data
available with which to compare our I- CIMS alcohol
interference work.
Glycolaldehyde sensitivities for the melt vapor pressure source
experiment (cpsppb-1).
Temperature
O2-(GA)
I-(GA)
(K)
at m/z 92
at m/z 187
298
6×104
7×103
318
7×104
1×104
338
NA
1×104
Nominal
6.5×104
9×103
NA indicates not available.
The PCIMS sensitivity to GA was evaluated using a Henry's Law
equilibration system and a vapor pressure melt system to generate
gaseous GA and the results are presented in Tables 5 and 6,
respectively. The sensitivities for the two GA generation systems were
further compared to the HAc sensitivity (Table 5; comparison
sensitivity was developed from Figs. 3 and 4). Case 1 and Case 2
are reported together because the sensitivities were indistinguishable
for reportable significant digits; therefore, comparison to the melt
method and HAc only considered Case 1 or Case 3. The GA sensitivities at
m/z 92 (O2-(GA)) and m/z 187 (I-(GA))
for the melt vapor pressure source of GA were between those from the
Case 1 and Case 3 assumption sets for the Henry's Law generated GA
sensitivities. The GA sensitivities using the Case 1 assumptions were
comparable to the HAc sensitivity at m/z 92 and m/z 187. The GA
sensitivities determined using the melt vapor pressure source were
a factor of 4 and a factor of 10 greater than the sensitivity of HAc
at m/z 92 and m/z 187, respectively. Unlike Petitjean
et al. (2010), we did not purify the GA dimer using a freeze–pump–thaw
cycle. This could have led to potential impurities in the solid, one
of which could be HAc, and possibly an overestimation of the vapor
pressure. Magneron et al. (2005) also reported partial pressure
ranges for GA at 298 and 333 K and the value at 298 K
was 20 times higher than Petitjean et al. (2010). Petitjean et al. (2010) suggested that this
difference could be from volatile impurities. When we use the Magneron
et al. (2010) vapor pressures instead of Petitjean et al. our sensitivities
at 298 K are 1×104 and 1×103 cpsppb-1 for m/z 92 and m/z 187,
respectively. These sensitivities are substantially closer to the
gas–aqueous work from Case 1. The GA reaction cell mixing ratio of GA
using Magneron's vapor pressure values were 22 ppb at
298 K and 64 ppb at 333 K (we measured at
338 K). In comparison, using Petitjean's vapor pressures the
GA reaction cell mixing ratios were 2 and 39 ppb at 298 and
338 K, respectively. Our high sensitivities determined with
the Petitjean et al. vapor pressures could be due to impurities in the
sample. Regardless, these results imply GA or HAc were a significant
interference in the measurement of the other using both
O2- and I- cluster formation. As GA atmospheric
mixing ratios are non-negligible (Table S1), PCIMS data collected at
m/z 187 are reported as the AAES
of HAc plus GA.
Discussion
Ion chemistry and water sensitivity dependence
Jones et al. (2014), Le Breton et al. (2012), and Lee et al. (2014)
observed an I-(HFo) sensitivity dependence on water
vapor. Lee et al. (2014) has shown I-(HAc) sensitivity to
vary with water vapor. O'Sullivan et al. (2018) and Heikes
et al. (2017) discussed the water sensitivity of
O2-(CO2)(HP) and O2-(MHP) clusters. HFo
and HAc sensitivities were the primary focus of this work and were
examined over a range of water vapor mixing ratios from ∼30 ppm to 20 000 ppm with a combination of
laboratory and field measurements. I-(HP) sensitivity was
also examined as it was used together with I-(H2O),
O2-(CO2)(HP), and O2-(MHP)
sensitivities to diagnose the PCIMS residual CH3I mixing ratio
present in DC3. In addition, a weak MHP calibration signal at
m/z 175 was observed in FRAPPÉ. Heikes et al. (2017) used these
data and developed a more detailed analysis of the I-
chemistry of HFo, HAc, HP, and MHP, which is briefly presented below.
The following ion chemistry was invoked to account for an iodide
cluster's observed sensitivity dependence on water vapor (Lee et al.,
2014; Heikes et al., 2017):
I-+H2O+M→I-(H2O)+M,I-+X+M→I-(X)+M,I-(H2O)n+X↔I-(X)-(H2O)n-1+H2O,I-(X)+H2O↔I-(H2O)+X,
where X represents HFo, HAc, HP, and MHP and M represents a third-body
reactant (typically N2, O2, H2O, and
CO2). Heikes et al. found that the pressure and humidity
trends seen in our PCIMS laboratory and field work for HP, HFo, and
HAc could not be replicated without the addition of
I-(H2O)2 (3), especially at the higher humidity
values. However, I-(H2O)2 was not present in mass scans
in FRAPPÉ or the laboratory and we inferred I-(H2O)2
binding was not strong enough to survive declustering in the collision
dissociation chamber.
Lee et al. (2014) found the I-(HFo) sensitivity plateaus
and declines when the reaction cell water was above
2200 ppm. The occurrence of a maximum sensitivity as
a function of water vapor is two-fold. First, Iyer et al. (2016) and
Heikes et al. (2017) have pointed out the rates of cluster forming
Reactions (R2) are promoted by a third-body reactant which acts as an
energy carrier and stabilizes the cluster. H2O is expected to
be more efficient in this regard than the other molecules listed
above. Second, H2O competes with X for I- (1) and
can shift the switching Reaction (R4) equilibrium in favor of
I-(H2O), thereby decreasing the yield of
I-(X) when H2O is large. Unlike Lee et al. (2014),
our HFo sensitivity did not decrease at the highest water mixing
ratios tested, though it appeared to plateau – most notably in the
ambient pressure (1013 hPa) laboratory work
(Fig. 3). Possibly, our highest reaction cell water mixing ratios were
insufficient to achieve a decline in sensitivity as observed by Lee
et al. (2014). The maximum water mixing ratio in the reaction cell during
laboratory experiments was 7800 ppm (Treadaway,
2015). However, the FRAPPÉ in-flight calibrations covered a larger
water mixing ratio yet there was still no decline in sensitivity
(Fig. 4). It is likely that instrumental differences between the two
CIMS configurations led to a shift in the location of the water
response peak in sensitivity. Lee et al. (2014) used a much higher
CH3I reagent gas mixing ratio and reaction cell pressure
(90 hPa) or [M], which, as mentioned above, can impact the
reaction velocity (1, 2). Jones et al. (2014) and Le Breton
et al. (2012) intentionally added water to promote clustering. Jones
et al. (2014) found a decrease in sensitivity at their lowest water
mixing ratios as a result of an insufficient water source to promote
clustering under the dry sampling conditions of the Arctic and upper
troposphere. Under the Le Breton et al. sampling conditions near the
surface they operated in a water-vapor-independent regime. Our
in-flight observations and unpublished Heikes et al. (2017) model
results with Le Breton's CH3I mixing ratio suggest that there
is a water-dependent regime between the altitudes sampled by Jones
et al. (2014) and Le Breton et al. (2012).
Figures 3 and 4 show I-(HAc) sensitivity was constant up to
approximately 1000 ppm reaction cell water vapor mixing ratio,
above which the sensitivity decreased. This suggested that Reaction (R2) for
HAc was likely able to dissipate the excess energy of reaction into
the cluster ion without requiring an explicit third-body
molecule. Above 1000 ppm, I-(HAc) sensitivity
decreased with increasing reaction cell water vapor mixing ratio,
indicating the switching reaction equilibrium for HAc (Reaction R4) behaved as was expected for HFo, but not observed, and was shifting towards
I-(H2O). By comparison, Lee et al. (2014) found a decrease
in I-(HAc) sensitivity with the addition of any water to
their system.
Iyer et al. (2016) reported a binding enthalpy of
-70.5 kJmol-1 for I-(HAc) and
-106.8 kJmol-1 for I-(HFo). The binding
enthalpies are reported here as negative values, indicating an
exothermic process and opposite to the NIST nomenclature for
ion–molecule reactions (Bartmess, 2017). They correlated the
sensitivities of Lee et al. (2014) to binding energy and theorized the
binding enthalpy for an analyte in an I- cluster could be
used to predict its sensitivity. Figures 3 and 4 suggested ambient
water vapor also had a significant role to play in determining an
analyte's sensitivity with our I- CIMS configuration.
Interferences
HFo, HAc, and GA were found to form cluster ions with both
O2- and I- ions. Figure 4, developed from
FRAPPÉ data, demonstrated that the O2- cluster sensitivity
for each of the analytes was greater than its I-
counterpart. By itself this argued for the use of O2-
over I-. However, m/z 78 (O2-(HFo)) in our
system may experience interference from cluster ions such as
CO3-(H2O) and 18O of O2-(CO2)
also at m/z 78 (Heikes et al., 2017; O'Sullivan et al.,
2018). Interference at m/z 92 (O2-(HAc)) included HAc
interference by GA and vice versa and speculative cluster ions like
CO3- (O2) or NO2-(HFo). A second
drawback to the use of O2- as a cluster ion stems not
from potential interferences but from the complex interplay between
O2-, CO2, and H2O and the analytes HP,
MHP, HFo, HAc, and GA (Heikes et al., 2017). Calibration under variable
water vapor conditions and variable trace species such as ozone or
nitrogen oxides was challenging.
From the results, it was clear that HAc and GA provided comparable response
as O2- clusters or I- clusters, even though the
GA gas-phase Henry's Law and melt vapor pressure systems used here
were not ideal, as outlined above. The HAc : GA relative sensitivity
was between 1:1 and 1:10. We are most confident in our Case 1 and
Case 2 Henry's Law work, which presumed “fast” monomer
hydration–dehydration (both Case 1 and 2) and “fast” monomer, dimer,
and trimer equilibrations (Case 1). To rule out “slow”
dehydration–hydration equilibration kinetics (Case 3) in the GA
aqueous solution, multiple gas flow rates through the coil were
used. A “slow” dehydration of monomer was expected to result in
a reduction in sensitivity as the flow rate was increased and monomer
was depleted before replacement could occur from the monomer-hydrate
pool. This was not observed and the hydration–dehydration kinetics
were taken to be “fast”. A Case 1 (or Case 2) result interpretation
yielded a 1:1 sensitivity ratio and implies that reported AAES mixing
ratios were close to the true sum of HAc and GA. If the melt vapor
pressure source sensitivity was correct, then we observed
approximately a factor of 10 higher sensitivity for GA than for
HAc. This implies reported AAES mixing ratios represent an upper limit
to the sum of HAc and GA; if in fact the AAES included only GA,
the AAES indicates 10 times the amount of GA than actually present.
Baasandorj et al. (2015) also tested GA interference in their PTR-MS
HAc measurements. They found a HAc : GA sensitivity ratio of
0.65–1.4 over their experimental humidity range. Our Case 1 Henry's
Law results, using drastically different ion chemistry, are consistent
with their work. St. Clair et al. (2014) measured HAc and GA with both
a single quadrupole and tandem CIMS with a CF3O-
reagent ion. Their single quadrupole HAc : GA ratio was 2:3 to
3:2 for four flights during the California portion of the Arctic
Research of the Composition of the Troposphere from Aircraft and
Satellites (CARB-ARCTAS). These flights sampled biomass burning and
high biogenic emissions with urban influence from Sacramento
(St. Clair et al., 2014). St. Clair's single quadrupole CIMS is
similar to ours, though with a different reagent ion, and they also
found a HAc : GA ratio consistent with our Case 1 Henry's Law
results. As a caveat, the Petitjean et al. (2010) critique of prior
work regarding GA absolute vapor pressure could apply to Baasandorj
et al. (2015), St. Clair et al. (2014), and our work, and GA
gas calibration is an unresolved issue.
Mixing ratios, as parts per billion (ppb), for
(a) formic acid (HFo) and (b) AAES (the sum of acetic
acid and glycolaldehyde) for FRAPPÉ Research Flight 12 on
12 August 2014.
FRAPPÉ example flight
Figure 5 shows PCIMS HFo and AAES data from FRAPPÉ Research
Flight 12 (RF 12) on 12 August 2014. The C130 flew a mountain-valley
flight pattern to sample “upslope” flow over the Rocky
Mountains. Part 1 of the flight was flown between Boulder and Greeley
in a series of stacked legs. Part 2 (after refueling at 16:00 MDT)
flew over Denver and then two legs over the Continental Divide with
a low-altitude “missed approach” at Granby airport on the western
side of the divide. Both HFo and AAES mixing ratios were at least
1 ppb for the majority of the flight. The highest HFo was
found west of Fort Collins near biogenic sources characterized by
isoprene greater than 75 ppt, MVK
greater than 100 ppt, and methacrolein (MACR) greater than
70 ppt (NCAR Trace Organic Gas Analyzer; Apel et al., 2015).
Elevated HFo (>1.5 ppb) in Granby corresponded to
elevated O3 (∼80 ppb, NCAR one-channel
chemiluminescence; Ridley et al., 1992) and a biogenic signature
(∼100 ppt MVK and ∼80 ppt isoprene). This
could be secondary production from an upslope flow event and
subsequent spillover event (Pfister et al., 2017). There was high
AAES (up to 14 ppb) below 0.5 km (a.g.l., above ground
level) corresponding to high NH3 (Aerodyne Research, Inc.,
Herndon et al., 2005) with a maximum mixing ratio of 180 ppb
near Greeley, which is an area associated with a concentration of
confined animal feedlot operations (Eilerman et al., 2016; Yuan
et al., 2017). If the signal at m/z 187 were primarily HAc, the
HAc : NH3 ratio was 0.078 ppbppb-1, which is
within the range reported by Paulot et al. (2011) though larger than
the enhancement ratio range of 0.02–0.04 ppbppb-1
reported by Yuan et al. (2017). A maximum AAES of ∼10 ppb was measured over the Denver Metropolitan area, when
HFo was approximately 1 ppb.
DC3 vertical profiles and test case
The DC3 observations were divided into three study regions as
indicated by the colored boxes in Fig. 6a and labeled
Colorado–Nebraska, Oklahoma–Texas, and Eastern region (states from
Arkansas to the Carolinas). HFo and AAES data for the three
subdomains were composited as a function of altitude and the
composite profiles are shown in Fig. 6b–d. The measurements are
binned in 1 km intervals, where the symbols denote the bin's
median value, the thicker lines indicate the bin's inner-quartile range,
and the thin lines show the 10th to 90th percentile
range. Stratospherically influenced air was removed before bin
statistics were computed by eliminating air samples with high ozone
(>150 ppb) and low carbon monoxide (<70 ppb).
(a) Map of three DC3 flight domains:
Colorado–Nebraska (red), Oklahoma–Texas (magenta), and Eastern
region (green) along with the HIAPER flight tracks.
(b) Profiles for the HFo and AAES mixing ratios as
a function of altitude for the three DC3 study regions
(Colorado–Nebraska (CO/NE), Oklahoma–Texas
(OK/TX), and Eastern Region). The symbols represent
the median value for each altitude bin, the thick lines the
interquartiles, and the thin line is the 10th–90th percentile.
Each study region had lower HFo mixing ratios compared to
AAES. Previous field measurements reported varied results about the
proportion of HFo to HAc. Reiner et al. (1999) and Talbot
et al. (1996) reported less HFo relative to HAc (by as much as
a factor of 2 from 7 to 12 km). Millet et al. (2015) sampled
HFo and HAc during the summer over the Southeastern US and found the mean
HFo to HAc ratio to be 1:1 at their maximum reported altitude
(approximately 5 km) and 1.0:1.4 at the lowest near-surface
altitudes. The HFo mixing ratios of Millet et al.'s (2015) were an order of
magnitude higher than reported here though our AAES mixing ratios were
within their reported HAc mean plus and minus SD ranges. The high
solubility of HFo and the large extent of vertical mixing
characteristic of the stormy conditions sampled during DC3 likely led
to a preferential sampling of conditions that diluted, and possibly
wet-deposited, HFo. These same conditions would also lead to diluted
and scavenged AAES measurements if AAES were mostly composed of GA.
In general, all three profiles had a decrease in HFo up to
6 km, followed by an increase back to boundary layer mixing
ratio values or higher. This profile was most pronounced in the
Eastern DC3 region. The Eastern region also had the highest-altitude
measurements and the HFo sensitivity started to decrease again above
12 km. The highest mixing ratios of both HFo and AAES in the
Oklahoma–Texas region were measured at 2 km. The Colorado HFo
profile has more HFo at the top of the profile than in the boundary
layer. The AAES altitude trend was not as strong in any of the study
regions though the mixing ratio decreased up to 6 km. The
Eastern region had the biggest difference between both HFo and AAES at
high altitude. The largest range of mixing ratios (represented by the
10th–90th percentile) was in the Oklahoma–Texas region and was
reflected in both the peroxide (not shown) and HFo–AAES profiles.
Figure 7 shows HP, MHP, HFo, and AAES mixing ratios during DC3 Research
Flight 5. The HIAPER altitude is plotted as well for reference. The
mission was to sample convective outflow from a Texas–Oklahoma storm
the night before. During a low-altitude leg, HFo was approximately
400 ppt and AAES was ∼1400 ppt in a biogenically
active area rich in isoprene, ∼6 ppb (NCAR Trace Organic
Gas Analyzer; Apel et al., 2015). AAES was greater than HFo during
most of the flight. The HIAPER also sampled biomass burning during
this flight (indicated on Fig. 7). AAES was >1 ppb during biomass burning sampling. Biomass burning was
identified by a CO enhancement of 80 ppb and HCN enhancement
of >200 ppt above background. There is no MHP reported
during this period due to potential interferences at mass 80 from
CO3-(H2O) with an 18O and/or
NO3-(H2O) (Heikes et al., 2017). The storm outflow portion
(identified by MHP > HP) had periods of elevated HFo (∼400 ppt) similar to the low-altitude measurements earlier in
the flight. A comparable increase back to lower-altitude mixing ratios
was not seen in AAES. Based on effective Henry's Law constants and
retention factors (e.g., Barth et al., 2007), HAc is expected to be
more efficiently transported through such storms relative to HFo and
therefore expected to have a greater mixing ratio in the storm
outflow. If AAES was dominated by GA, the expected outflow AAES would
be lower than HFo given the higher Henry's Law constant of GA. The
AAES mixing ratio in the storm outflow was about 2–3 times lower than
in the biomass burning plume; however, it was greater than the HFo,
which suggested AAES was likely a more balanced sum of HAc and GA and
not dominated by GA.
PCIMS DC3 Research Flight 5 (26 May 2012) sampling aged
outflow from a Texas–Oklahoma storm. (a) Mixing ratios of
HP (blue) and MHP (red) are shown in ppb as a function of flight
time. (b) Mixing ratios of HFo (blue) and AAES (red) are
shown in ppb as a function of flight time. The HIAPER altitude
(green line) is in kilometers (kilometers/10 for b). The periods of
biomass burning and outflow are indicated. MHP is not reported
during the low-altitude leg due to potential interferences at mass
80 from CO3-(H2O) with an 18O and
NO3-(H2O).
We have attempted to examine our AAES data in light of prior
measurements of GA and HAc in biogenic or isoprene rich air masses,
biomass burning plumes, and urban areas. Y.-N. Lee et al. (1995,
1998) reported GA surface and aircraft measurements from the Southern
Oxidation Study at a rural Georgia surface site in July and
August 1991 and in June 1992 and from aircraft measurements from the
Nashville/Middle Tennessee Ozone Study conducted in June and
July 1995. They did not measure or report HAc. HAc aircraft data were
compiled by Khare et al. (1999) and tower observations were made by Talbot
et al. (1995) (Shenandoah National Park, September 1990). Combining
these datasets, a surface HAc : GA ratio ranged from 0.9 to 10 and
the aircraft ratio, using HAc from remote regions, ranged from 1 to
14. Convolving our Case 1 HAc and GA relative sensitivities (1:1)
and the synthetic ratios from these four data sources, an AAES value
of 2 ppb would represent anywhere from 1 ppb of both
HAc and GA to 1.9 ppb HAc and 0.13 ppb GA. Doing the
same with our vapor-pressure-determined response ratio of 1:10,
the same AAES value of 2 ppb would represent HAc and GA mixing
ratios from 0.17 and 0.18 ppb to 1.2 and 0.083 ppb,
respectively. As seen above, in biogenically dominated areas it is
possible to have 1:1 proportions of HAc to GA in the AAES
measurements but HAc would dominate at the higher reported HAc mixing
ratios.
GA, HAc, and HFo should be co-emitted in fires. Biomass burning is
a primary emitter for GA and HAc and secondary for HFo (Khare et al.,
1999; Yokelson et al., 1997, 2009). Using summary data from Akagi
et al. (2011) and Stockwell et al. (2015) on emission ratios and
emission factors, it is reasonable to expect enhancements of
20–30 ppt in HFo, 170–180 ppt in HAc, and
potentially 30–40 ppt GA, for every 10 ppb
enhancement in CO near the source for a North American biomass burning
plume. St. Clair et al. (2014) found a higher average GA enhancement
of 57 ppt for every 10 ppb enhancement in CO for both
fresh and aged plumes. Performing the same analysis as above, we can
estimate the proportion of HAc and GA from an AAES value of
2 ppb and a 10 ppb enhancement in CO. Based on the
Case 1 Henry's Law HAc-to-GA relative sensitivities (1:1) and the
enhancements reported above, there would be 1.67 ppb HAc and
0.33 ppb GA or, for the work of St. Clair et al.,
1.5 ppb HAc and 0.5 ppb GA. Using the vapor pressure
response ratio of 1:10, the same AAES value of 2 ppb per
10 ppb of CO would result in HAc and GA mixing ratios of 0.67
and 0.133 ppb, or 0.46 and 0.15 ppb for GA enhancement
found by St. Clair et al., respectively. We would expect that most of
the AAES emitted from biomass burning would be HAc even at the 1:10
response rate because 3–5 times more HAc relative to GA is released.
There are limited measurements for GA in urban environments.
Spaulding et al. (2003) and St. Clair et al. (2014) measured GA at
a tower near the Blodgett Research Station on the western slope of the
Sierra Nevada. Spaulding et al. measurements were made in
August and September 2000 and GA ranged from
0.092 to 1.7 ppb. St. Clair et al. measurements were made in
June and July 2009 and they observed an average of 0.986 ppb
and a maximum of about 4 ppb. This site is influenced by
urban emissions from Sacramento and Spaulding et al. estimated
40 % of the GA was attributable to anthropogenic origins.
Therefore, we used 40 % of the average GA reported by Spaulding
et al. and St. Clair et al. for an urban estimate. Okuzawa
et al. (2007) observed a maximum GA mixing ratio of 1.77 ppb
in Tokyo. This is compared to our urban estimate from the Blodgett
Research Station. Grosjean (1990) measured HAc in Southern California
where it ranged from 0.9 to 13.4 ppb. From these studies we
inferred an urban HAc-to-GA ratio between 3:2 and 49:1. Again
taking a representative AAES value of 2 ppb, for the Case 1
scenario (1:1) there could be HAc and GA values anywhere from
1.39 ppb HAc and 0.61 ppb GA to 1.96 ppb HAc
and 0.04 ppb GA for the minimum and maximum reported HAc
values, respectively. Using the maximum HAc and GA reported mixing
ratios to determine their ratio, there would be 1.77 ppb HAc
and 0.23 ppb GA for an AAES value of 2 ppb. However, if
we use our vapor-pressure-determined HAc-to-GA response ratio of
1:10 and an AAES signal of 2 ppb, the HAc and GA ranged from
1.66 and 0.034 ppb to 0.374 and 0.16 ppb,
respectively, for the Sacramento conditions. For the urban maxima, HAc
and GA would be 0.9 and 0.11 ppb, respectively. Based on this
analysis there would be at least twice as much HAc as GA measured as
AAES in an urban air mass.
There is a continued need for simultaneous measurements of HAc and GA
in urban to biomass burning to rural environments from the surface to
upper troposphere. Baasandorj et al. (2015) developed a trap that
removed HAc, allowing GA to be measured by PTR-MS. We have not yet
tested how effectively our current trap system removes GA and this
also will need to be considered when reporting AAES results. We plan
to develop a trap that will remove GA but leave HAc. With a dual trap
system, it is conceivable HAc and GA can be determined sequentially
and independently of each other using I- CIMS or PTR-MS.