We deployed an extractive electrospray ionization
time-of-flight mass spectrometer (EESI-MS) for airborne measurements of
biomass burning aerosol during the Fire Influence on Regional to Global
Environments and Air Quality (FIREX-AQ) study onboard the NASA DC-8 research
aircraft. Through optimization of the electrospray working solution, active
control of the electrospray region pressure, and precise control of
electrospray capillary position, we achieved 1 Hz quantitative measurements
of aerosol nitrocatechol and levoglucosan concentrations up to pressure
altitudes of 7 km. The EESI-MS response to levoglucosan and nitrocatechol was
calibrated for each flight, with flight-to-flight calibration variability of
60 % (1
Extractive electrospray ionization time-of-flight mass spectrometry (EESI-TOF-MS, hereafter EESI-MS) allows for rapid measurements of the chemical composition of organic aerosol (OA) (Lopez-Hilfiker et al., 2019; Chen et al., 2006; Doezema et al., 2012). EESI-MS has been used to characterize sources of primary and secondary OA in cities (Stefenelli et al., 2019; Qi et al., 2019; Brown et al., 2021) and to track OA chemistry in laboratory studies (Doezema et al., 2012; Gallimore and Kalberer, 2013; Gallimore et al., 2017; Liu et al., 2019a, b), and proof of concept has been demonstrated for airborne applications (Lopez-Hilfiker et al., 2019).
During EESI-MS measurements, aerosol inlet flow is intercepted by an
electrospray, where collisions of the aerosol particles with electrospray
droplets lead to dissolution of particulate matter in the charged droplet,
followed by droplet evaporation, ionization of the dissolved components
(Kumbhani et al., 2018; Law et al., 2010), and detection by a high-resolution
time-of-flight mass spectrometer (Junninen et al., 2010). The advantage of
EESI-MS is the lack of sample preparation – analytes are not collected onto
a vaporizing element or filter, allowing many compounds to be sensitively
detected without thermal decomposition (Lopez-Hilfiker et al., 2019; Stark et al., 2017). Droplets are transferred into a vacuum through a steel capillary
(residence time 1.8 ms) that is heated to 250
Two key parameters that determine the range of compounds detectable with
EESI-MS are the composition of the electrospray solution and the ion
polarity. EESI-MS sensitivity has been shown to vary by orders of magnitude
based on the solubility of analytes in the electrospray solution (Law et al., 2010). Previous EESI-MS measurements of ambient OA have utilized positive
mode (EESI(
Airborne measurements of OA concentration and composition have been carried
out by filters for offline analysis (Maria et al., 2002; Huebert et al., 2004; Heald et al., 2005; Forrister et al., 2015), a particle-into-liquid
sampler (PILS) coupled to a total organic carbon analyzer (Sullivan et al., 2006; Duong et al., 2011), an Aerodyne aerosol mass spectrometer (AMS) (DeCarlo
et al., 2008), particle analysis by laser mass spectrometry (PALMS) (Froyd et al., 2019; Murphy et al., 1998), and chemical analysis of aerosol online with a
proton-transfer-reaction mass spectrometer (CHARON PTR-MS) (Piel et al., 2019). PILS coupled to offline ion chromatography (PILS-IC) (Sullivan et al., 2014, 2019) and CHARON PTR-MS (Piel et al., 2019) have both quantified
levoglucosan in biomass burning OA from airborne platforms, with PILS-IC
demonstrating a detection limit of 0.1 ng m
We deployed EESI-MS in a configuration that allowed for quantitative detection of components of biomass burning OA at pressure altitudes up to 7 km during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study onboard the National Aeronautics and Space Administration (NASA) DC-8 aircraft. This was achieved by optimizing the electrospray solution for performance at pressures suitable for airborne sampling, development of an automated electrospray capillary stage, and extensive flight-day and in-flight calibrations with a colocated AMS. Here we describe the instrument adaptations and its performance as deployed during FIREX-AQ and present comparisons to AMS and CHARON PTR-MS measurements during that campaign.
The sample flow path of the EESI-MS deployed for this study (Aerodyne Research, Inc. Billerica, MA, USA) is shown in Fig. 1. The National Center for Atmospheric Research (NCAR) High-Performance Instrumented Airborne Platform for Environmental Research Modular Inlet (HIMIL) (NCAR EOL, 2019; Stith et al., 2009) is shared with the University of Colorado high-resolution AMS (DeCarlo et al., 2006; Canagaratna et al., 2007; Nault et al., 2018; Guo et al., 2020). The AMS and EESI-MS shared several inlet components: a high-efficiency particulate air (HEPA) filter (Pall Corp., Port Washington, NY, USA) for removal of ambient aerosol when measuring instrument backgrounds and quantifying detection limits; a calibration system for monodisperse aerosol consisting of an atomizer (TSI 3076, Shoreview, MN, USA), differential mobility analyzer (DMA; TSI 3081), and condensation particle counter (CPC; TSI 3010); and a polydisperse aerosol generation system consisting of a medical nebulizer (deVilbiss, Somerset, PA, USA) operated with ultrahigh-purity (UHP) zero air (Praxair, Danbury, CT, USA) at 1.4 bar.
The EESI-MS pressure-controlled inlet (PCI) contains the multichannel
activated carbon denuder and the electrospray capillary (Fig. 1). Air enters
the PCI through a 350
The instrument background – the signal attributable to the electrospray itself or to contaminants in the ionization chamber – was measured for 15 s every 3 min by switching the PCI from ambient air to UHP zero air. The time response of EESI-MS to these background measurements was about 5 s, as shown in Fig. S1. Background signals were linearly interpolated between measurements. The instrument detection limits were then determined against this background by sampling ambient air through the main inlet HEPA filter, which was done for 15 s every 18 min. Detection limits were calculated for each filter period and interpolated across ambient sampling.
Organic gases in the atmosphere are detectable by secondary electrospray
ionization (SESI) (Zhao et al., 2017), so they must be removed from the sample
flow when measuring organic aerosol by EESI-MS. The denuder used to strip
away organic gases from the sample air in this study is an extruded
activated carbon cylinder 3.2 cm long and 1.6 cm in diameter, with
approximately 300 square channels. The denuder was regenerated by baking at
90
Demonstration of EESI-MS denuder efficiency for removing gas-phase
VOCs.
Inlet residence times and transmission efficiency were calculated across
DC-8 sampling altitudes using the geometry of the inlet tubing and the flow
rates used. Calculation of transmission efficiency accounts for particle
losses from gravitational settling, impaction, diffusion, and aspiration.
Total EESI-MS inlet residence times range from 1.4–1.6 s and are shown as
a function of sampling altitude, PCI pressure, and inlet subassembly in Fig. S3. Over half of the residence time is due to the volume of the PCI, which
was designed to ensure laminar flow at the entrance and exit of the denuder.
The calculated transmission efficiency of the inlet is shown as a function
of sampling altitude in Fig. S4 and is separated by loss process in Fig. S5.
The efficiency is calculated to be above 90 % for particle geometric
diameters between 50 and 350 nm, with 50 % transmission at roughly 15 nm
and 1
Organic gases are removed by the denuder during sampling to prevent
gas-phase ionization by SESI. The removal of semivolatile gases disturbs
gas–particle equilibrium, potentially leading to aerosol evaporation inside
the inlet. Heating of ambient air as it flows through inlet tubing also
drives aerosol evaporation. We calculate upper limits for the extent of
evaporative losses as a function of saturation vapor concentration at 298 K
(
The electrospray capillary position was controlled using a linear stepper
motor (Thorlabs ZFS13, Newton, NJ, USA) opposed by a 9 N spring. A
photograph of the custom stage is included in the Supplement (Fig. S7). The
stage gives the operator sub-millimeter precision in capillary position, allowing
optimization of the electrospray even in turbulent flight conditions. We
find that the electrospray capillary position at which the primary ESI signal
is greatest is also the position at which the EESI-MS signal is greatest (Fig. S8),
allowing the user to optimize the electrospray capillary position without
use of online aerosol standards. We interpret this as an indication that the
volume of the aerosol flow is larger than that of the electrospray and that
adjustments in electrospray capillary position are optimizing the extent to
which the electrospray (and thereby the extracted and ionized aerosol
components) is sampled by the aspiration of the mass spectrometer, rather
than lost to ionization chamber walls. This suggests that improvements in
EESI-MS sensitivity may be possible by narrowing the diameter of the
electrospray region or focusing the aerosol upstream of the electrospray.
The heated capillary is
Ions produced by EESI are detected using an atmospheric pressure interface
time-of-flight mass spectrometer (Junninen et al., 2010). Aerosol components
that were not ionized by EESI are not focused by the ion optics of the
TOF-MS and are pumped away or deposited on an internal surface of the
ionization volume or mass spectrometer. The TOF-MS was operated at an
extraction frequency of 21 kHz, recording up to
The EESI(
The previous study demonstrating that EESI(
The nonlinear effect of decreasing electrospray region pressure on the efficiency of EESI is shown in Fig. 3a, where the EESI-MS sensitivity is reduced by 83 % when PCI pressure is reduced by 30 % from 667 to 467 mbar. An additional 23 % reduction in pressure to 360 mbar results in a 30 % reduction in sensitivity. There are at least two separate processes contributing to the decrease in sensitivity: lower PCI pressure, reducing the flow rate (and therefore mass flux) of aerosol into the mass spectrometer (given that the volumetric flow rate is constant), and the reduction of ESI ionization efficiency at low pressures discussed above. We include the contribution of the reduced flow rate in Fig. 3a, showing that it is the reduction in ionization efficiency that drives the nonlinear relationship between electrospray region pressure and EESI-MS sensitivity.
These data indicate that small deviations in the electrospray region
pressure can have substantial impacts on EESI-MS sensitivity. From the
relationship shown in Fig. 3a, we calculate that a 25 mbar reduction in
electrospray region pressure (e.g. 667 to 642 mbar) can cause a 10 %
reduction in EESI-MS sensitivity. Pressure fluctuations of that magnitude
are not unique to aircraft sampling: common sources of inlet pressure
variability, such as pressure drops from sampling through particle filters
or switching a valve, can approach 25 mbar. These fluctuations must be
avoided during all EESI-MS measurements in order to avoid measurement bias
from the pressure dependence of EESI-MS sensitivity. The electrospray region
pressure during filter blanks and zero air backgrounds during FIREX-AQ was
kept constant by the pressure controller. Pressure transients caused by
valve switching were small (
The relationship between PCI pressure and EESI-MS sensitivity presented here
is for a
There is significant potential for further investigation and optimization of
electrospray dopants for EESI-MS. While use of NaI as an EESI(
The use of an acid dopant in negative-polarity electrospray has the
potential to suppress the ionization of compounds less acidic than the
dopant. As part of this study both formic acid and acetic acid were tested
as dopants for EESI(
EESI-MS was calibrated against the AMS before and after each flight during
FIREX-AQ using levoglucosan (EESI(
We estimate the uncertainty in the EESI-MS polydisperse calibration
(2
The effect of the aerosol matrix on EESI-MS sensitivity was tested by
nebulizing binary mixtures of analytes, size-selecting 300 nm particles with
a DMA, and calibrating the EESI-MS against particle mass calculated from CPC
counts, particle diameter, and the densities and mass fractions of the pure
calibrants. EESI(
EESI-MS detection limits during FIREX-AQ were calculated from periodic
measurements of ambient air that had all aerosol removed by a HEPA filter.
At a PCI pressure of 667 mbar, average EESI(
Raw and background-subtracted
Airborne EESI-MS measurements of biomass burning organic aerosol (BBOA) were
carried out onboard the NASA DC-8 aircraft from 22 July–3 September 2019
as part of the FIREX-AQ study (campaign map shown in Fig. S12). Flights
based out of Boise, Idaho, typically sampled wildland fire BBOA above
mountainous terrain, and the EESI-MS was operated at a PCI pressure of 467 mbar for most of these flights. Flights based out of Salina, Kansas,
primarily sampled BBOA from small agricultural fires at lower altitudes,
so EESI-MS was operated at a PCI pressure of 667 mbar for these flights. We
consistently switched ion polarities throughout the study, totalling 17
EESI(
EESI-MS data at FIREX-AQ cover 414 out of 538 plume transects (77 %). Of those transects with no EESI-MS data, the majority (76 out of 124) are from the three research flights during which EESI-MS was flown without a denuder. Excluding those flights, EESI-MS data cover 90 % of plume transects; 4 % of FIREX-AQ plume transects occurred above the operational ceiling of the EESI-MS.
Raw and background-corrected EESI(
Example 1 Hz
The EESI(
Calibrated 1 s time series of levoglucosan and nitrocatechol are shown
in Fig. 5, demonstrating the fast time response of airborne EESI-MS. Carbon
monoxide measurements are included to illustrate the spatiotemporal
boundaries and internal variability of each smoke plume. In addition to
levoglucosan and nitrocatechol, we also quantified the total aerosol EESI-MS
signal, which correlated with AMS OA, as shown in Fig. 6 for both EESI(
The coefficient of determination is
Bulk sensitivity of
During one FIREX-AQ research flight, EESI-MS and AMS were flown alongside a CHARON PTR-MS, allowing for an airborne intercomparison of the three instruments. CHARON PTR-MS operates by removing gas-phase organic compounds using a charcoal denuder, concentrating aerosol using an aerodynamic lens, evaporating components of OA using a heated vaporizer at 8 mbar, and detecting those OA components by PTR-MS. More detailed descriptions of the CHARON PTR-MS technique and its airborne operation have been published elsewhere (Piel et al., 2019; Eichler et al., 2015). CHARON PTR-MS and AMS ground measurement intercomparisons have been previously carried out (Müller et al., 2017). Intercomparisons of airborne CHARON PTR-MS and airborne EESI-MS with any other aerosol measurements have not been reported before.
EESI(
Comparison of EESI-MS quantification of levoglucosan
(C
The AMS C
Comparison of 1 min EESI-MS and CHARON PTR-MS excess levoglucosan and AMS excess levoglucosan-equivalent vs. excess CO for a single FIREX-AQ flight. Excess levoglucosan or CO is determined by subtracting the background concentration from the in-plume average concentration.
We deployed an EESI-MS onboard the NASA DC-8 aircraft during FIREX-AQ and quantified levoglucosan and nitrocatechol concentrations in biomass burning organic aerosol with 1 s time resolution. These measurements required optimization of the EESI-MS working solution to allow for operation at pressures as low as 360 mbar, precise control of electrospray capillary position, and flight-day calibrations. Characterization of EESI-MS sensitivity using monodisperse aerosol showed no size dependence for particles smaller than 400 nm in diameter, and no matrix effects were detected for added organic compounds or inorganic salts. Comparison with previously published EESI-MS bulk OA sensitivities adds support to the idea put forth in those studies that EESI-MS bulk sensitivity varies with OA chemical composition, although it is far less than for individual species. EESI-MS levoglucosan concentrations were consistent with those measured using AMS and CHARON PTR-MS, differing by 6 % (CHARON PTR-MS) and 30 % (AMS). Taken together these results demonstrate the ability to use EESI-MS for fast and accurate quantification of organic aerosol composition onboard aircraft platforms.
FIREX-AQ data for EESI-MS and all supporting measurements are publicly
available in the NASA Data Archive at
The supplement related to this article is available online at:
DP, PCJ, DAD, and JLJ designed the experiment and wrote the paper; HG, MKS, WLB, BAN, KS, AL, FP, LT, AW, MMC, GIG, HSH, RHM, DST, CW, and EBW collected and analyzed data; HS and DST developed software; and JEK contributed to EESI optimization. All authors reviewed and provided comments for the paper.
Jordan Krechmer, Harald Stark, and Benjamin Nault work for Aerodyne Research Inc., which has commercialized the EESI-TOF-MS instrument for geoscience research. Felix Piel works for Ionicon Analytik, which has commercialized the CHARON PTR-MS instrument. David Thomson is the founding partner of Original Code Consulting, which has commercialized the MICAS-X software. Armin Wisthaler profits from a license agreement (CHARON inlet) between the University of Innsbruck and Ionicon Analytik.
This work was supported by NASA grants 80NSSC18K0630 and 80NSSC19K0124, as well as a Cooperative Institute for Research in Environmental Sciences (CIRES) Innovative Research Program (IRP) grant. We thank Felipe Lopez-Hilfiker and the EESI-MS user community for useful discussions and support during the field phase of this research. We thank the CIRES Integrated Instrument Development Facility for their work making the EESI-MS flight-ready. We thank Anne Handschy, the crew of the DC-8, the Ames Earth Science Project Office, and FIREX-AQ leadership for support during FIREX-AQ. We thank Glenn Diskin, Joshua DiGangi, John Nowak, and the DACOM instrument team for the CO measurements used here. The CHARON PTR-MS instrument was partly funded by the Austrian Federal Ministry for Transport, Innovation and Technology (bmvit) through the Austrian Space Applications Programme (ASAP) of the Austrian Research Promotion Agency (FFG). CHARON PTR-MS instrumental support came from Ionicon Analytik; Tomas Mikoviny and Markus Müller provided technical assistance. Felix Piel received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 674911 (IMPACT EU ITN).
This research has been supported by the National Aeronautics and Space Administration (grant nos. 80NSSC18K0630 and 80NSSC19K0124) and Horizon 2020 (IMPACT (grant no. 674911)).
This paper was edited by Johannes Schneider and reviewed by Alexander Vogel and two anonymous referees.