Volatile organic compounds were quantified during two aircraft-based field
campaigns using highly automated, whole air samplers with expedited
post-flight analysis via a new custom-built, field-deployable gas
chromatography–mass spectrometry instrument. During flight, air samples
were pressurized with a stainless steel bellows compressor into
electropolished stainless steel canisters. The air samples were analyzed
using a novel gas chromatograph system designed specifically for field use
which eliminates the need for liquid nitrogen. Instead, a Stirling cooler is
used for cryogenic sample pre-concentration at temperatures as low as
Volatile organic compounds (VOCs), chemical species consisting primarily of carbon, hydrogen and oxygen, are ubiquitous and important components of the atmosphere (Glasius and Goldstein, 2016; Schultz et al., 2015). VOCs are fundamental to the photochemical formation of ozone and secondary organic aerosol (de Gouw et al., 2005; Edwards et al., 2014; Kanakidou et al., 2005; Trainer et al., 2000) and can have direct and indirect effects upon both air quality and global climate (Hoyle et al., 2009; Monks et al., 2015). Measurements of VOCs can be used to identify and quantify emission sources and photochemical aging processes (Fortin et al., 2005; Mckeen and Liu, 1993; Warneke et al., 2012). Important primary sources for VOCs can vary by location and season – emissions from biogenic, biomass burning, urban/industrial and oil/natural gas extraction have all been characterized by this laboratory and others using in situ gas chromatography–mass spectrometry (GC-MS) (Gentner et al., 2014; Gilman et al., 2013, 2015; Goldan et al., 1995, 2000; Hornbrook et al., 2011).
The use of gas chromatography followed by mass spectrometry for the analysis of VOCs is a well-established technique due to its superior selectivity and sensitivity compared to other chromatograph detection methods (McClenny et al., 1996). For GC-MS, sensitivities can be enhanced by pre-concentration of the analytes, commonly by means of adsorbent(s) or cryogenic trapping (Brown and Purnell, 1979; Greenberg et al., 1994; McClenny et al., 1984; Woolfenden, 2010). Cryogenic sample pre-concentration allows high vapor pressure VOCs and halocarbons to be trapped without the use of strong adsorbents that can produce significant artifactual responses (Apel et al., 2003b; Sive et al., 2005); however, sufficient volumes of liquid cryogen (e.g., liquid nitrogen) can be difficult to obtain at remote field locations (Tanner et al., 2006; Wang et al., 2012). Cryogen-free systems that allow for low-temperature sample trapping by means of Peltier or refrigeration units suffer from slow temperature response times, lack of portability due to size and weight and/or insufficiently low trap temperatures to allow trapping of the most volatile gases (e.g., ethane) without adsorbents (Hopkins et al., 2011; Liu et al., 2016; Miller et al., 2008; Sive et al., 2005; Tanner et al., 2006; Wang et al., 2014).
Stirling coolers offer an alternative cooling technology for cryogenic
sample pre-concentration. Conceptually, the Stirling cooler consists of a
sealed cylinder filled with a gas (e.g., helium), with a piston that
compresses and expands the gas and a displacer that moves the gas from one
end of the cylinder to the other out of phase with the piston (de
Waele, 2011). Cooler performance is measured in watts of lift capacity, a
measure of the amount of heat transfer from one end of the cylinder to the
other while maintaining a constant temperature at the cold end. In this
application, the warm end of the cooler is subsequently cooled with forced
air. The Stirling cooler features low weight and size, modest power
consumption and maintenance-free operation but at the cost of low lift
capacity (ter Brake and Wiegerinck, 2002). Stirling
coolers have been used by at least two other gas chromatography groups for
air sample pre-concentration, but previous examples either required an
extended (20 min) cooling cycle to achieve cryogenic trapping temperature
(Oliver et al., 1996) or were operated at warmer (
Summary of measurement parameters for SENEX 2013 and SONGNEX 2015 campaigns.
Sample collection of whole air samples by canisters extends the utility of GC-MS analysis to locations and platforms unsuitable for a ground-based detection system or where fast time resolution sampling on the order of seconds is required without loss of method sensitivities (McClenny et al., 1991; Wang and Austin, 2006). Electropolished stainless steel canisters have been used for many years for quantifying trace gases, including from aircraft platforms (Colman et al., 2001; Heidt et al., 1989; McClenny et al., 1996; Simpson et al., 2010, 2014). Due to the space and weight constraints of operating a whole air sampling system aboard research aircraft, this laboratory, in conjunction with the National Center for Atmospheric Research (NCAR), constructed a new semi- to fully automated system, the improved whole air sampler (iWAS), for field work (Warneke et al., 2016). This system packages 12 electropolished stainless steel canisters in rack-mountable modules that can be rapidly installed in or uninstalled from a wing pod of the aircraft in sets of six and filled remotely. The sampler design and post-fabrication conditioning protocols have been adopted from the NCAR Advanced Whole Air Sampler (AWAS) and earlier whole air sampler designs (Heidt et al., 1989; Schauffler et al., 1999) and the UC Irvine whole air sampling program (Blake et al., 1994; Simpson et al., 2010). The NCAR AWAS system had previously been deployed for the NOAA field campaigns TexAQS II and CalNEX in 2006 and 2010, respectively (Parrish et al., 2009; Warneke et al., 2012). The stability of various classes of compounds in electropolished stainless steel canister systems as a function of canister preparation and sampling and analysis protocols has been well documented in the literature (Kelly and Holdren, 1995; Ochiai et al., 2002).
The combined iWAS/ACCBAR system was deployed during two aircraft-based field campaigns (summarized in Table 1). In summer 2013, the Southeast Nexus (SENEX) field campaign was conducted to investigate the roles of anthropogenic and biogenic emissions upon the formation of tropospheric ozone and secondary aerosol in the southeastern United States (Warneke et al., 2016). Twenty research flights were conducted aboard the NOAA WP-3D aircraft, based in Smyrna, TN, from May to July 2013. During SENEX, over 1100 canister samples were collected and subsequently analyzed in the field, with mixing ratios for 24 species reported. In spring 2015, the Shale Oil and Natural Gas Nexus (SONGNEX) field campaign was conducted to quantify the emissions of trace gases and fine particles from oil and natural gas basins throughout the western United States. The NOAA WP-3D aircraft was based in Broomfield, CO, and Austin, TX, from March to May and conducted 19 research flights. Over 1300 canister samples were collected and analyzed, with 24 VOC species reported.
This paper presents the instrumental details for the iWAS sampling and ACCBAR GC-MS analysis systems, as well as the methods used to fill and sample the canisters and the post-analysis cleaning process. The data analysis workflow, including peak area integration, normalization and calibration, is detailed, as well as a description of a series of instrument tests to identify possible artifacts in either the sample collection or analysis systems. Finally, a comparison of a subset of final reported mixing ratios from two field campaigns with measurements made by other instruments is provided.
Air samples were collected aboard the NOAA WP-3D aircraft, with the sampling
system installed in a wing pod mounted underneath the starboard wing of the
aircraft. The sample train consists of an unheated forward-facing stainless
steel inlet (10.2 mm ID) extending 15 cm from the outboard surface of the
wing pod with a reduced diameter outlet (2.2 mm ID) to increase ram air
pressure and an orthogonal stainless steel sampling arm (10.2 mm ID). The
sampling arm is connected via flexible stainless steel hose (9.5 mm ID) to a
two-stage stainless steel bellows compressor (Senior Aerospace p/n 28823-11)
used in series, capable of > 50 slpm of air flow at 60 psia (4140 hPa) with the inlet at 25
Schematic of instrument with flow path and valve position. Figure shown with open valve for a canister of middle-left sample module, Ch 1 flushing sample trap effluent to separation column, and Ch 2 loading sample trap.
Sample collection is controlled via a custom-built PC-104 data system
(Diamond Systems, Mountain View, CA) running LabView-based software
(National Instruments, Austin, TX) in a Microsoft Windows environment. The
flight scientist communicates with the data system over the aircraft local
area network using Windows remote desktop protocol. After takeoff, the
compressor is started with the bypass port open to reduce back pressure.
When the aircraft has reached the sampling area, the bypass port is closed
to allow adequate manifold pressure for filling canisters. Air samples are
sequentially collected by actuating the stainless steel bellows valve on an
individual canister and allowing the canister to be pressurized to 50 psia
(3450 hPa). Fill time for a canister with the system at standard sea level
pressure is 3 s and the time increases with increasing aircraft
altitude (decreasing ambient pressure). At an altitude of 5000 m a.s.l. (meters
above sea level), fill time is typically 11 s, and the maximum fill
time allowed by the flight computer is 15 s regardless of fill
pressure. During SONGNEX 2015,
Each canister is sequentially analyzed post-flight in the field with ACCBAR
(Fig. 1). The canister modules are connected to a welded electropolished
stainless steel sampling manifold via 2.2 mm ID passivated stainless steel
tubing (Restek Sulfinert-treated). The sampling manifold has eight
electropolished stainless steel bellows valves, which isolate individual
canister modules as well as a two-stage diaphragm vacuum pump and a supply of
zero air (General Air, ultra-zero grade) humidified by bubbler containing
water (Sigma Aldrich, HPLC grade). The sample manifold is connected to the
GC-MS with a VCR fitting using a nickel-plated stainless steel gasket with a
100
Conceptually, ACCBAR is a series of traps used to reduce unwanted
component(s) from the air sample matrix (i.e., water and carbon dioxide)
while concentrating the target analytes, which are subsequently injected on
separation columns and detected via mass spectrometry on a 20 min cycle.
The custom-built GC-MS ACCBAR consists of two channels, with channel 1
optimized for C2–C6 hydrocarbons and halocarbons using a PLOT column and
channel 2 optimized for C6–C10 hydrocarbons and oxygen- and nitrogen-containing
species using a low- to mid-polarity phase column. A single quadrupole mass
spectrometer detector (MSD) runs in selective ion mode for increased
signal-to-noise response and sequentially analyzes the effluent from the two
columns. This instrument is based on a two-channel GC-MS developed by NOAA
Chemical Sciences Division and deployed on many field campaigns over the
past 15 years (Gilman et al., 2013; Goldan et al., 1995). The new
instrument is designed for field deployment, capable of measuring in situ or analyzing canister samples, and is built into a
104 cm
Figure 1 presents a schematic of the flow path of ACCBAR, along with
alternative settings of the five two-position chromatography valves (Valco,
Vici Instruments, Houston, TX) used to direct gas flow. Channel 1 is shown
with the 10-port valve (1–10) in “flush” mode and the 6-port valve (1–6)
in “import” mode, where the sample trap is connected to the separation
column with carrier gas (UHP He) flowing through the sample trap and to the
column. Channel 2 is shown with the 10-port valve (2–10) in “load” mode
and the 6-port valve (2–6) in “backflush” mode, where sample flow is
directed through a water trap followed by the sample trap, while the
separation column is isolated and backflushed with UHP He. The four-port valve
is shown directing channel flow from the separation column on channel 1 to
the mass spectrometer, while channel 2 flow (UHP He) is vented. All
chromatography valves have stainless steel bodies with polyaryletherketone/PTFE rotors with 0.40 mm diameter channel, without external purging. The
valves and transfer lines (Restek,
When performing analysis, two 240 cm
After passing through the water traps, analytes from the air samples are
pre-concentrated via cryogenic trapping at nominal temperatures of
Chromatograms displayed as total ion current (TIC) with
select peaks identified. Top panel
The sample traps consist of a 330 mm section of treated fused silica tubing
(0.53 mm ID) mounted inside a thin-wall hypodermic stainless steel tube
(0.97 mm ID, 1.08 mm OD) that is resistively heated. The treated fused
silica tubing used for channel 1 is Al
Fig. 3a shows a typical temperature trace for each sample trap during an
analytical cycle. At cycle time (
Sample flow is directed to both traps starting at
After trapping, the concentrated samples are injected in turn onto the
respective chromatography columns. UHP He is used as the carrier gas, at a
constant flow of 2 sccm, with the total chromatogram requiring 780 s
of run time. After separation, the column effluent is directed sequentially
to the MSD via a four-port valve (Fig. 1), with channel 1 measured first,
followed by channel 2. Channel 1 uses an Al
The mass spectrometer (Agilent model 5975C) is usually operated in selected ion monitoring mode, scanning up to 11 masses per window, 28 windows per chromatogram with dwell times between 10 and 20 ms per mass, to optimize instrument sensitivity while providing enough sample points per mass to accurately determine peak area. Beginning with the 2015 SONGNEX campaign, a new peak-integration software package called TERN (Aerodyne Research, Inc.) has been used for automated peak-area retrieval (Isaacman-VanWertz et al., 2017). TERN is a custom-designed chromatographic data handler and peak integration package built upon Igor Pro's (Wavemetrics, Inc.) multi-peak fitting functionality. Chromatographic peaks are fit by minimizing the residual of a set of Gaussian and exponentially modified Gaussian peaks for a subset of the chromatogram (typically 20 s) on a single mass. The peak within this optimized fit considered most likely to be the analyte of interest is returned, and the peak area is calculated from the coefficients of the solution. Use of TERN to integrate chromatograms has reduced analysis time to approximately 1.25 min per chromatogram, at least an order of magnitude faster than the previous method using Agilent ChemStation and hand integration, while increasing peak area precision and accuracy (Isaacman-VanWertz et al., 2017). Additional information about TERN's peak fitting method and an intercomparison between peak areas determined by manual integration and automatic peak fitting is provided in the Supplement.
After the canisters have been analyzed, they must be prepared and
conditioned for reuse. An automated cleaning oven has been constructed that
allows for the unattended processing of three canister modules at one time.
All tubing and fittings in the oven are stainless steel. Each canister
manifold, and then each individual canister, is evacuated and leak-tested.
The canisters are then heated to 65
A full research flight of 72 canisters (6 modules) requires at least 12 h of cleaning and conditioning before they are ready to be reused. For the SENEX field campaign, humidified UHP nitrogen was used rather than water vapor, as most canisters were collected in the summertime southeastern US planetary boundary layer where ambient water vapor is adequate to condense liquid water in the sample canisters at sample pressures. This was switched to using water vapor for the SONGNEX campaign to ensure consistency of total water content in the canisters between the field campaigns. The presence of condensed water in the sample canisters is expected to have a deleterious impact upon soluble oxygenated VOCs (e.g., alcohols; Ochiai et al., 2002). Further discussion of water effects is presented in Sect. 3.4.4 below, and the ambient water mixing ratios of the collected samples from each field campaign is described in the Supplement. During a field campaign, the efficacy of the cleaning system is evaluated by filling cleaned and humidified canisters with the same zero air gas used to test for artifacts (Sect. 3.4.2).
For both chromatograph channels, normalization is required to account for
changes in instrument sensitivity primarily attributable to changes in
detector response. Long-lived halocarbon species in the atmosphere are used
for normalization, effectively serving as internal standards for canister
samples (Karbiwnyk et al., 2003). Four halocarbons have been
selected (only two were used for SENEX), which are abundant and relatively
constant in tropospheric air as a function of latitude over the typical
one-month time period of a field campaign: Freon-12 (CF
A normalization factor is calculated for every sample, based on the raw peak
area for CF
Sensitivities for all reported species are individually calculated by
measuring the instrument response to a set of dynamic dilutions of
gravimetric standards, using humidified UHP nitrogen as the diluent.
Dilutions are made using a dynamic dilution system, consisting of two high
flow mass flow controllers to provide UHP N
VOC species measured by iWAS/ACCBAR during SONGNEX. For
each compound, the instrument channel, nonlinearity (Nonlin.; as described
in the text, the ratio A : Sens
Example nonlinear sensitivity calibration for
m, p-xylenes. Panels
Typically, at least seven dilution levels are sampled over at least 3 orders of magnitude; for SONGNEX, this range was 0.03–70 ppbv. Hydrocarbon calibrations are performed with a nominal 1 ppm PAMS 57-component commercial standard (Scott Specialty), with a stated 5 % uncertainty of individual component concentrations. Other species – oxygenated compounds, alkyl nitrates, monoterpenes – are calibrated with in-house-made gravimetric standards consisting of 1–10 ppm mixtures of up to 10 species, with 5 % uncertainties. In-house standards include at least two hydrocarbons also found in the PAMS standard, typically benzene or toluene, in order to confirm that instrument response is consistent across a series of calibration tests. Secondary gas standards are exchanged and analyzed with the NOAA Global Monitoring Division (GMD) Halocarbons and other Atmospheric Trace Species (HATS) group on an informal basis every 1 to 2 years to establish the veracity of the stated gas standard concentrations. This process led to the discovery of the misstated ethane mixing ratio in our current primary PAMS standard (14 % higher than stated). Accounting for additional measurement errors of flows of the dynamic dilution system, 1 % for analyte and 2 % for dilution, we define the calibration accuracy as the uncertainties of concentration and flow added in quadrature. These values are listed in Table 2. We have left the larger uncertainty in ethane accuracy in our current description of the GC-MS performance, as we are continuing to evaluate ethane standards.
Instrument responses for most compounds are nonlinear over the dynamic
range of the calibrations. This behavior is consistent with what has been
observed on this laboratory's previous GC-MS system, although the nonlinear
response on the previous generation of this instrument was only significant
for later eluting compounds (those after benzene). When plotted with
linear-log scaling, the behavior is sigmoidal, in that sensitivity is
constant at low mixing ratios, then transitions to a higher sensitivity at
high mixing ratios. The sensitivity can be described well with an
exponential function:
This behavior is the opposite of what is typically observed when analyte breakthrough occurs at the sample trap, and we have tested the instrument up to 180 ppbv with a mixture of light hydrocarbons most susceptible to breakthrough (ethane, ethene, propane, propene, ethyne, n-butane) with no observed decrease in sensitivity; this mixing ratio is larger than any we have observed in ambient air with the WAS system. The nonlinearity is currently attributed to the water trap. At high mixing ratios the gas-phase analyte reaches equilibrium with adsorbed analyte on the wetted surfaces of the water trap, while at low mixing ratios this equilibrium is never reached and losses are kinetically determined. Precise control of the water trap temperature and sample flow rate are required to ensure that the nonlinearity is reproducible. Alternative water trap geometries and materials are currently under investigation to reduce this nonlinearity.
Intercomparison of n-hexane measurements made by the two different channels of iWAS/ACCBAR system during SENEX 2013. Data are shown with error bars based upon total analytical uncertainty presented in Table 2.
Retrieval efficiency as a function of added water vapor
to sample canisters after cleaning. Data points are the ratio of observed
mixing ratios in canister samples versus ambient mixing ratios measured by
ACCBAR during the time period the canisters were filled. Error bars indicate
standard deviation of multiple canisters filled simultaneously. Data are
offset on
Instrumental precision for most species is determined from the measurement
of the secondary standard described in Sect. 3.1 during field measurements.
The secondary standard is typically measured at the beginning and end of
each flight analysis and at least three times during analysis. For example,
during SONGNEX 1327 sample measurements and 138 standard measurements were
made. Precision is defined here as relative deviation from the mean of the
normalized response for each species measured in the secondary standard,
reported as a percentage. For species that are not in the standard,
precision is estimated from the standard deviation of a dynamic dilution
calibration normalized data point near the middle of the calibration dynamic
range. Precision uncertainty is less than 7 % for most species reported in
Table 2. Detection limits for the various species (DL; Table 2) may be
calculated in units of pptv analyte using the sum of a precision estimate
and the instrument sensitivity:
To assess the overall analytical uncertainty further, the measurements of
n-hexane, which is quantified on both channels of the GC-MS, are compared.
Figure 6 shows a scatter plot of n-hexane measurements for the entire SENEX
field campaign. The two-sided linear fit of the data indicates an agreement
within 4 % with an insignificant intercept and little scatter (a
least-squares fit gives a correlation coefficient,
Previous work (Kelly and Holdren, 1995; Ochiai et al., 2002; Palluau et al., 2005) has indicated that samples collected in dry electropolished stainless steel canisters may be subject to significant artifacts due to loss of certain VOCs to the canister walls, while samples humidified either via addition of water prior to sampling or by adequate ambient water vapor will be less prone to these effects. The iWAS/ACCBAR system was evaluated for potential artifacts due to canister preparation, sample collection and sample aging. This was accomplished via four sets of tests.
A series of humidification experiments were performed using ambient air
samples collected outside the laboratory in Boulder, CO, in canisters filled
with varying amounts of water vapor after the cleaning process (Fig. 7).
The goal of these tests was to determine the minimum level of water vapor
that should be added to the sample canisters in order to sufficiently reduce
analyte losses to the canister surfaces. ACCBAR collected and measured the
ambient air in situ while canister were simultaneously filled,
using a common PFA inlet for both systems. Ambient dew points during these
tests varied between
VOC species measured by iWAS/ACCBAR during SONGNEX.
Canister backgrounds (Blank), replicates and retrieval efficiencies (Rtv
Eff) and total uncertainties are reported. Replicate compares two analyses
of the same sample canister performed within 100 h of each other.
Retrieval efficiency (Rtv Eff) is the ratio of the observed mixing ratio
between canister and in situ samples collected simultaneously, with
the canisters then analyzed within 100 h of collection. Total
uncertainty is reported as %
During SONGNEX, the sampling system was evaluated for background signal by filling canisters with zero air immediately after cleaning and humidifying, then allowing the cans to sit 1–3 days before analysis. These tests are in contrast to the analysis system blanks (see Sect. 2.2.1) as they identify signal enhancements attributable to canister preparation. These results are presented in Table 3 as blanks in units of pptv. Hydrocarbons and alkyl nitrates have very small signals in the blanks, with ethane being the only species with a mixing ratio greater than 2 pptv. However, a few oxygenated species had blank values at atmospherically relevant levels. The blanks were significantly larger than the analysis system blanks (the same zero air passed through the sample train) so the artifacts are attributed to the canisters rather than the analysis system. Since nearly all species but oxygenates were below detection limit, the canister cleaning appears to be adequate. Instead, the source of contamination is likely the canister humidification system, confirming the observations noted in Sect. 3.4.1. Because of this contamination, oxygenates are not reported for SONGNEX. For SENEX, sample canisters were pre-treated not with water vapor but with humidified nitrogen (see Sect. 2.2.3), so mixing ratios of oxygenates collected in the planetary boundary layer are expected to be less perturbed for this dataset. Also note that during SONGNEX, ACCBAR showed a significant ethanol contamination that decayed exponentially throughout the campaign, so that the reported ethanol blank value here is likely a combination of instrument and canister artifact.
Canister samples versus in situ ambient samples collected in Boulder, CO, using sample canisters humidified to 12 torr water vapor during the cleaning process. Error bars indicate standard deviation of replicate canister samples.
Comparison of replicate analyses from the same sample canister sets from three flights during SONGNEX 2015 (flight dates: 9, 13, 23 April).
Additional canister tests were conducted to characterize the retrieval
efficiencies and short-term storage (< 100 h) effects of the
iWAS/ACCBAR system using canisters prepared with approximately 12 torr of
water vapor. For each sample period, four to nine canisters were filled with
air collected from outside the Boulder, CO, laboratory while ACCBAR
simultaneously measured the air in situ, similar to that in
described in Sect. 3.4.1. The ambient dew point during these tests was near
8
Intercomparison with PTRMS of select VOCs from
SENEX 2013. Slopes and intercepts from two-sided linear fits of the data are
presented, along with correlation coefficients (
During SONGNEX replicate analysis was performed on full sets of canister samples from three research flights to evaluate the analytical precision of the entire system (rather than just the GC-MS). The research flights were made on 9 April through the eastern Permian Basin of Texas, on 13 April in the Denver–Julesburg Basin and Colorado Front Range and on 23 April through the western Permian Basin of Texas and New Mexico. These canister sets were aged on average 37, 256 and 92 h, respectively, between the first and second analysis. Example scatter plots comparing the first and second analysis are shown in Fig. 9. For most species, the replicates were not significantly different than unity for the 37 and 92 h replicates, with the notable exception of alcohols which were enhanced for the second analysis due to temporary partitioning into the aqueous phase (Kelly and Holdren, 1995). Replicate results for aldehyde and ketone species typically agreed within 10 %, indicating that the analysis system does not contribute measurement artifacts for these species. For cans aged 256 h on average, several additional classes of compounds (ketones, alkyl nitrates, aromatics) showed enhancements in the second analysis. For SONGNEX, most canisters (92 %) were analyzed within 100 h of sampling, so only the 37 and 92 h replicate results are considered to be applicable here. The results of these tests are summarized in Table 3 as the slope of the two-sided linear regression of the combined 37 and 92 h replicates, ignoring the 256 h replicate samples.
Using the information from the canister tests and the total analytical
uncertainty reported in Sect. 3.3, we can describe the total uncertainty
for measurements reported from the iWAS/ACCBAR system for SONGNEX, reported
as relative plus absolute uncertainty (%
The iWAS/ACCBAR system was first field-deployed for the SENEX field campaign
in the southeastern USA in late-spring 2013, where canister samples were
collected aboard the NOAA WP-3D aircraft. As described in Sect. 2.2.3, the
canisters were not filled with water vapor but rather with humidified UHP
N
Intercomparison of alkane measurements made in oil and natural gas fields using a ground-based in situ GC-MS (Uinta Basin, UT (UBWOS 2012), Boulder Atmospheric Observatory (BAO; NACHTT 2011), Ft. Collins, CO (BIOCORN 2011)) and airborne WAS during SONGNEX 2015.
Due to the large ambient variability of some species, additional scatter in
the data is expected from the difficulty of time-aligning these two
measurements. Canister sample fill times were less than 8 s for more
than 95 % of all samples during SENEX, so the comparison requires a 15 s averaging window of PTRMS data centered about the midpoint of the
canister fill time. For SENEX, six individual or summed species measured by
both instruments are compared, as shown in Fig. 10a–f. Light aromatic
species (benzene and toluene) showed a significant difference in slope
between the instruments, with the iWAS mixing ratios lower than the PTRMS.
The trend is consistent with observed retrieval efficiency of toluene noted
during the canister tests discussed above, but significant benzene losses in
canisters have not been observed. Biogenic species were abundant in ambient
air during SENEX, and the comparison between instruments compares favorably
to previous published work (de Gouw and Warneke, 2007) for both
isoprene and summed monoterpenes (i.e.,
For SONGNEX, a more limited set of intercomparisons with other instruments
is available due to the apparent contamination of the canister during
preparation by oxygenated species (see Sect. 3.4) and due to the ambient
mixing ratios of observed species (isoprene and monoterpenes were at low
mixing ratios during early spring). The PTRMS instrument that had been used
for previous field missions was replaced with a new hydronium-ion chemical
ionization time-of-flight mass spectrometer (H
The intercomparisons with in situ instruments presented here show significant scatter, especially when compared to recent WAS validation work (Apel et al., 2003a; Hoerger et al., 2015). It should be recognized that the scatter in the data shown here is not unique, but it is typical in other presentations of comparisons between in situ and WAS measurements aboard aircraft (de Gouw et al., 2006; Hornbrook et al., 2011), as well as ground-based comparisons with fast time response and GC-MS systems (de Gouw et al., 2003; Plass-Dülmer et al., 2006; Pollmann et al., 2008).
An alternative evaluation for the quality of measurements made with the canister system is possible by comparing measurements made in the same airshed by different instruments at different times. Absolute mixing ratios are expected to vary with time, but ratios of species with high emission rates and relatively slow atmospheric reaction rates are expected to be stable if emission sources are consistent over the time period of the intercomparison. Research flights made during SONGNEX overflew two shale basins that had been recently characterized by NOAA CSD using an older GC-MS system: Uinta Basin in Utah (Warneke et al., 2014) and Denver–Julesburg in Colorado (Gilman et al., 2013). Figure 12a–b show intercomparisons of two different pairs of alkanes from the Uinta Basin and Denver–Julesburg fields, respectively. The ratio of propane to ethane, determined by the slope of a two-sided linear fit, was statistically equivalent for the Uinta Basin between 2012 and 2015, although the absolute mixing ratios observed during the ground-based campaign are considerably higher than the aircraft measurements. For Denver–Julesburg, two sets of ground-based measurements have previously been reported: wintertime measurements made at the southwest edge of the oil and gas exploration area (BAO, CO) and summertime measurements made at the northwest edge of the area near Ft. Collins, CO. The ratio of isopentane to n-pentane determined by a two-sided linear fit for the SONGNEX flight data is statistically equivalent to the Fort Collins, CO, data, but the BAO, CO, data have a slightly higher ratio. The difference for the BAO, CO, data may be due to the difference in season affecting the relative oxidation rates of isopentane and n-pentane or the influence of the nearby Denver metropolitan area where the isopentane to n-pentane ratio is higher because of gasoline emissions from mobile sources.
A new automated whole air sampler and GC-MS analysis system that relies upon
cryogenic sample pre-concentration without the need for liquid nitrogen has
been designed, built and field-deployed. The whole air sampler typically
fills 72 sample canisters during a single research flight; post-flight
analysis requires 30 h with minimal interaction with the operator. A new
peak integration software package allows for the automated retrieval of peak
areas, thereby reducing post-analysis data processing time by an order of
magnitude. Over 2400 air samples were analyzed during the SENEX 2013 and
SONGNEX 2015 field campaigns, with mixing ratios reported for a wide range
of hydrocarbons (alkanes, alkenes, aromatics), alkyl nitrates, monoterpenes
and select oxygenated species. The GC-MS analytical system limit of
detection is typically below one part per trillion with total uncertainty
(at 1
The field data presented here are available from the NOAA ESRL CSD data server, listed by field campaign:
2011 NACHTT
(
The authors declare that they have no conflict of interest.
The authors would like to thank the staffs of NOAA's Aircraft Operations Center and the Design and Fabrication Services shop of NCAR's Earth Observing Laboratory for their assistance with the work described in this paper. We thank Courtney Hatch, Alyssa Jaksish and Degan Hughes of Hendrix College and Megan Dumas of Stonehill College (now at UC Irvine) for their assistance with collecting and reducing data for SENEX. We thank William Dubé of the NOAA ESRL CSD laboratory for fruitful discussions of various engineering strategies employed in the analysis system. We thank Allen Goldstein and Doug Wornsop for their support in the development of TERN. Edited by: E. C. Apel Reviewed by: A.-C. Lewis and one anonymous referee