We present a comprehensive characterization of cluster control and transmission through the Tofwerk atmospheric pressure interface installed on various chemical ionization time-of-flight mass spectrometers using authentic standards. This characterization of the atmospheric pressure interface allows for a detailed investigation of the acetate chemical ionization mechanisms and the impact of controlling these mechanisms on sensitivity, selectivity, and mass spectral ambiguity with the aim of non-targeted analysis. Chemical ionization with acetate reagent ions is controlled by a distribution of reagent ion-neutral clusters that vary with relative humidity and the concentration of the acetic anhydride precursor. Deprotonated carboxylic acids are primarily detected only if sufficient declustering is employed inside the atmospheric pressure interface. The configuration of a high-resolution time-of-flight chemical ionization mass spectrometer (HR-TOF-CIMS) using an acetate chemical ionization source for non-targeted analysis is discussed. Recent approaches and studies characterizing acetate chemical ionization as it applies to the HR-TOF-CIMS are evaluated in light of the work presented herein.
Recent commercialization and packaging of time-of-flight chemical ionization mass spectrometers (TOF-CIMS) into field-deployable packages by Aerodyne Research Inc. and Tofwerk AG has led to the widespread use of these instruments (Aljawhary et al., 2013; Bertram et al., 2011; Brophy and Farmer, 2015; Chhabra et al., 2015; Ehn et al., 2010, 2011, 2014; Faust et al., 2016; Friedman et al., 2016; Jokinen et al., 2012; Junninen et al., 2010; Krechmer et al., 2015; Lee et al., 2014; Lopez-Hilfiker et al., 2016, 2015, 2014; Mohr et al., 2013; Sipilä et al., 2015; Yatavelli et al., 2012, 2014; Zhao et al., 2014). Any chemical ionization (CI) source, or more generally any near-atmospheric pressure ion source, can be installed on the front end of the mass spectrometer providing a flexible TOF instrument platform. The design and operation of the ion source affects the sensitivity of the instrument, but the fundamental ion chemistry is the key consideration to designing a CI source that is both sensitive and selective. Thus, the selection of an appropriate reagent ion for detecting the compound, or class of compounds, of interest is important (Huey, 2007). The ions observed in the TOF mass spectrum do not necessarily represent the distribution of ions generated in the ion source due to collisional dissociation (Bertram et al., 2011) and mass-dependent transmission effects (Heinritzi et al., 2016). Collisional dissociation simplifies the observed mass spectrum and has a long history of use dating back to the original developments of tropospheric CIMS measurements (Eisele, 1986). Controlling the extent of collisional dissociation can be used to investigate the ion-neutral chemistry occurring in the ion source. The TOF-CIMS uses a tunable multistate atmospheric pressure interface (API) that can eliminate or transmit clusters, but the operational details of this interface have not been investigated with systematic rigor.
TOF-CIMS represents a distinct departure from traditional quadrupole CIMS
methodologies in which specific species are targeted for quantification.
TOF-CIMS collects a continuous mass spectrum at high (
Both TOF and quadrupole detectors remain subject to misinterpretation of the
mass spectrum in the absence of complex interferences. Quadrupole systems
with unit mass resolution can suffer from attributing the signal from a
single mass to charge ratio (
Acetate CIMS, originally termed negative-ion proton-transfer chemical
ionization, is conventionally thought to selectively ionize carboxylic acids
and some inorganic acids by proton abstraction (Reaction R1) (Veres
et al., 2008). Other compounds, such as nitrated phenols, are detectable
with acetate CIMS due to their gas-phase acidity relative to the acetate ion
(Mohr et al., 2013). However, acetate can also form adducts with
levoglucosan, which are detected as [levoglucosan
We note, however, that two other types of reactions may be occurring:
While rare, fragmentation reactions are also known to occur within CIMS
instrumentation:
In light of recent studies detecting nitrated phenols as deprotonated
products (Mohr et al., 2013) and detecting levoglucosan
(Zhao et al., 2014) and IEPOX/ISOPOOH (Budisulistiorini et
al., 2015) as acetate clusters, we suggest that these reaction should be
more generalized to include other molecules with various functional groups
and non-acidic protons. Reactions R1 and R2 have been reported in the
literature for acetate CIMS assuming that carboxylic acids are detected
(Bertram et al., 2011). Ligand exchange reactions (Reaction R3) have not
directly been identified to occur with acetate CIMS, but the chemistry
appears to be very similar to iodide adduct CIMS, where [I
Acetate CIMS can be contrasted to iodide adduct CIMS, another rapidly developing chemical ionization method being applied to TOF-CIMS platforms (Aljawhary et al., 2013; Friedman et al., 2016; Lee et al., 2014; Lopez-Hilfiker et al., 2014, 2016; Zhao et al., 2014). Iodide adduct CIMS predominantly form iodide adducts with neutral species due to its high electronegativity; iodide is not expected to substantially abstract protons or transfer electrons (Iyer et al., 2016). Once ion-neutral clusters are formed, the ion optics of the mass spectrometer must efficiently transmit these clusters to the mass analyzer. The lack of proton abstraction or charge transfer allows this CIMS method to be operated in a cluster mode because the iodide ion holds the vast majority of the negative charge. Thus, the dominant clustering mechanism involves iodide. The dominant clustering mechanism with acetate CIMS involves the acetate ion, but the prevalence of proton abstraction produces stable anions that will also undergo clustering reactions.
The Tofwerk API enables users to control and vary the extent of collisional dissociation, allowing for more representative descriptions of ion source chemistry. The Tofwerk API consists of two segmented radio-frequency-only (RF) quadrupoles: the Short Segmented Quadruple (SSQ) and the Big Segmented Quadrupole (BSQ). These components are housed in two differentially pumped vacuum chambers and contain various skimmers and entrance plates (Fig. 1). Between the entrance of the API and the last skimmer after the BSQ, there are nine individually controllable voltage components and the two RF-only segmented quadrupoles, making the task of optimally tuning the API a serious undertaking. This task is made more complex by the realization that instrument resolution, ion transmission efficiency, and extent of collisional dissociation are all interrelated.
Schematic of the Tofwerk atmospheric pressure interface (API) showing where the IMR mounts on the API, the short segmented quadrupole (SSQ), the big segmented quadrupole (BSQ), and the primary beam (PB) region.
Previous studies have examined these components with regard to controlling and/or understanding the transmission of ions and clusters to the TOF (Bertram et al., 2011; Heinritzi et al., 2016). The original description of the Tofwerk API uses no ion source and describes ambient ions and ion-neutral clusters in the atmosphere (Junninen et al., 2010). The authors characterize the ion transmission efficiency of the API-TOF tuned to transmit clusters using an electrospray source emitting tetraheptylammonium bromide. Ion transmission efficiency is defined as the fraction of ions at the inlet or in the ion source that make it to the detector. No attempt to systematically characterize or optimize the API components is presented, although the authors note that ion transmission efficiency is strongly dependent on the voltage settings in the API. A comparison of methods for experimentally determining mass-dependent ion transmission efficiency has also been reported, but no evaluation of the voltage settings, their relationships, and their effect on clustering or transmission efficiency is reported (Heinritzi et al., 2016).
The application of the Tofwerk API to a C-TOF configured as an acetate CI instrument provides some more insight to understanding the relationships between various API components as they relate to cluster transmission and collisional dissociation (Bertram et al., 2011). Here, the authors suggest that collisional dissociation of ion-neutral clusters occurs between the exit of the SSQ and the entrance of the BSQ vacuum stage. This claim appears to be in slight contrast to the recent results describing the use of voltage scanning to determine instrument sensitives with the iodide reagent ion (Lopez-Hilfiker et al., 2016). The authors scan the API voltages to increase the difference between the BSQ front and the last skimmer after the SSQ and lens skimmer (Fig. 1 and Table 1). Ion transmission efficiency is maintained by floating all components upstream of the last skimmer more negative as the voltage difference between these two components is increased. Systematic floating of API components to change the voltage difference between two components maintains the electric field strengths between all other components. This approach also prevents changing the axial-electric field across the RF-only segmented quadrupoles; changing the axial-electric field will result in changes in ion transmission efficacy which must be avoided so that a mass spectrum collected under one voltage setting is comparable to results collected using a different voltage configuration.
Component relationships defined by adjacent components in the API (see Fig. 1 for API schematic).
Previous work comparing the iodide adduct, acetate, and water cluster CIMS
methodologies using a HR-TOF-CIMS highlights the need for significant
characterization of collisional dissociation in the API (Aljawhary
et al., 2013). The authors tune a HR-TOF-CIMS to a “weak-field mode” for
iodide adduct and water cluster CIMS operation. A “strong-field mode” is
used while operating in acetate mode. Comparing the negative ion mode
voltage configurations under strong-field and weak-field operation presented
in the supplementary information shows numerous voltage relationships that
may lead to subtle differences in relative ion transmission efficiency. This
problem is not unique, and authors rarely publish exact voltage
configurations as the exact voltages needed to tune the API will vary across
instruments. The lack of careful study when configuring the API is obvious
in the available HR-TOF-CIMS literature using acetate CI where reported
[acetate
We present a comprehensive characterization of the Tofwerk API. This characterization of the API allows for a detailed investigation of the acetate ionization mechanisms and the impact of controlling for these mechanisms with collisional dissociation in the ion transfer optics on sensitivity, detection limits, selectivity, and mass spectral ambiguity with the general aim of non-targeted analysis. We show that the majority, if not all, ion-neutral chemistry occurs in the ion molecule reactor (IMR) where incoming sample air mixes with the output of the ion source. Lastly, we provide insight on configuring these HR-TOF-CIMS systems for non-targeted analysis and the detection of clusters.
The HR-TOF-CIMS (Tofwerk AG and Aerodyne Research, Inc.) is described
extensively in the literature (Bertram et al., 2011; Brophy and Farmer, 2015;
DeCarlo et al., 2006; Jokinen et al., 2012; Junninen et al., 2010; Lee et
al., 2014). The instrument described herein is operated in the negative ion
mode with acetate reagent ions. The configuration is described in detail by
Brophy and Farmer (2015). Notable differences include the use of a larger
SH-112 single scroll pump (Agilent Technologies, Inc.) backing the IMR, a
custom-built quartz glass reservoir with metal to quartz fittings for holding
the reagent precursor, and the use of the standard IMR critical orifice for
sampling from atmospheric pressure at 1900 sccm. Mass spectra are acquired
at an extraction frequency of 25.0 kHz and pre-averaged to 1 s mass spectra
over a mass range from 2 to 494
The quartz glass reagent reservoir is filled with acetic anhydride
(Sigma-Aldrich,
Gas-phase standards of formic (CH
All components of this system are automated to allow for comprehensive calibrations of the six authentic acid standards under different instrument settings and different RH conditions. LabVIEW scripts (LabVIEW 2014 Version 14.0f1, National Instruments, Inc.) control the gas flows using predetermined sets of flow rates, humidity settings, and instrument voltage configurations. Multiple data acquisition devices (Labjack Inc, U12) are implemented to record all flows, RH sensor output, and valve states. The HR-TOF-CIMS is controlled using the Tofwerk Application Programming Interface (Tofwerk AG, Version 1.97) from within the LabVIEW environment. All data streams read by the data acquisition devices are logged to the Tofwerk HDF files along with the HR-TOF-CIMS data.
Two general modes of operation exist for this experimental setup: full calibration mode and voltage scanning mode. Briefly, operating in full calibration mode produces one background-subtracted multipoint calibration curve at each specified RH setting. Next, LabVIEW changes the instrument voltage settings and repeats the experiment. One file is created for each instrument zero and calibration step in order to simplify data processing by averaging entire files of a fixed length. Voltage scanning mode utilizes the same flow system but maintains all the flows while switching instrument voltages. Again, a separate data file is created for each voltage configuration.
Post-processing is performed in Igor Pro (WaveMetrics Inc, Version 6.3.7.2)
running Tofware (Tofwerk AG, Aerodyne Research, Inc. Version 2.5.3). Tofware
is used to process, fit, and then extract HR-TOF data and auxiliary data
generated from the experimental setup. Once the integrated high-resolution
time series are extracted, scripts developed in Igor Pro process all of the
experimental data to produce calibration curve summaries and statistics. TOF
duty cycle corrections are made within Tofware at
Calibration experiments are normalized by the ratio of the total ion signal
at each calibration step relative to the total ion signal in zero air.
Traditionally, normalization is conducted using the acetate reagent ion.
Under declustered settings, acetate accounts for most of the total ion signal
(
Top panel: an ion of interest is normalized to the total ion signal
and plotted against the voltage difference for some component relation
(component relation 3 is shown here). The black circles show the portion of
the curve used to average the signal of the ion during operation under weak
(clustered) electric field strength, with an inset box-and-whisker plot
representing the clustered-average. Blue circles show the portion of the
curve used to average the signal of the ion during operation under strong
(declustered) electric field strength, with an inset box-and-whisker plot
representing the declustered-average. The dV
Exploration of the API component relations provides additional insight to the
operation of these complex instruments. Very large sets of voltages
(
Maintaining instrument and sample stability is essential during these
experiments, particularly when comprehensive (
We use nonlinear least-squares sigmoidal regression following the work by
Lopez-Hilfiker et al. to describe declustering voltage scans and determine
the characteristic voltage (dV
A representative background mass spectrum obtained by overflowing the IMR with zero air is shown at three voltage differences (component relation 5). Both the log-scale mass spectrum (left column) and linear-scale (right column) mass spectrum are displayed. Dominant peaks related to the reagent ion chemistry are labeled.
Lopez-Hilfiker et al. (2016) filter their fits based on the criterion that if
the mean square residual is
The overall effect of voltage scanning on the observed mass spectrum using
acetate CIMS is partially described in previous work characterizing the
application of the Tofwerk API with a C-TOF-CIMS (Bertram et al., 2011). Our
use of a HR-TOF-CIMS enables further identification of dominant peaks in the
mass spectrum and a more comprehensive analysis of tuning effects and
ionization chemistry. Figure 3 shows both the log-scale mass spectrum and
linear-scale mass spectrum collected while flowing ultra zero air into the
inlet and changing the voltage difference between the skimmer and BSQ front
(component relation 5). The mass spectrum collected under high electric field
strength (dV
Voltage scan results conducted between the seven component relations in the API.
Acetate (red dots) and the [acetic acid
The appearance of C
Voltage scans and cluster control have been discussed in terms of the voltage
difference between the skimmer and the BSQ front (component relation 5), but
numerous other component relations exist that may be suitable for controlling
collisional dissociation. To address other component relations, dry ultra
zero air is flowed into the instrument inlet, and acetate and the first
cluster, [acetic acid
If the voltage difference between adjacent components is set with a voltage difference of 0 V, ion flow through these components is controlled by fluid mechanics alone, and a decrease in ion transmission efficiency is observed. Thus, there is a lower limit to how gently one can transmit ions through these components while maintaining an electric field and high ion transmission efficiency. Deviations from the sigmoidal fit are observed at higher voltage differences for the axial voltage component on the BSQ (component relation 6). This field is applied between the BSQ back and BSQ front, but this deviation is attributable to ion transmission effects through the BSQ. This feature does not appear with the SSQ (component relation 2) because sufficiently high voltages needed to complete the curve could not be achieved due to voltage limits applied to the API to prevent electrical discharge. Another interesting feature is observed when scanning the second skimmer, located after the BSQ, and the BSQ back (component relation 7). Here, the cluster never reaches zero and the acetate signal remains correspondingly low in comparison to other components.
The effect of water vapor on various reagent ions is shown under two voltage
settings, dV
The exit of the SSQ to the lens skimmer (component relation 3) provides a
promising region for cluster control compared to the choice of components
used in previous studies (component relation 5) (Lopez-Hilfiker et al.,
2016). The dV
Operating the HR-TOF-CIMS with acetate reagent ions in a clustering mode provides a more representative view of the ion-neutral chemistry occurring in the IMR than the declustered mode. One interesting observation is that despite the relatively high pressure in the SSQ region (2 mbar) ion-neutral clusters do not appear to form in this region. One can attribute all the ion-neutral clustering chemistry to either reactions in the IMR or cluster condensation during the jet expansion from the IMR into the SSQ. This is inferred because clustering can be controlled between the SSQ entrance plate and the SSQ front (component relation 1). After passing through this region, the ions must make it through the entire length of the SSQ and subsequent skimmers, making up most of the residence time through this region.
RH effects on the reagent ions are investigated while operating the
HR-TOF-CIMS in both cluster mode (component relation 5, dV
Although Veres et al. (2008) note that a collisional dissociation chamber is
important to “dissociate weakly bound cluster ions such as
CH
The sensitivity to propionic acid and related clusters is plotted against
the voltage difference applied between the skimmer and BSQ front (component
relation 5) in units of normalized counts per second per ppb (ncps ppb
The propionic acid data used in Fig. 6 at a dV
Calibrations of six acid standards exhibit similar RH and voltage dependences
for both the deprotonated-declustered ions and ion-neutral clusters (Fig. 6,
Sect. S5). All voltage scans are conducted between the skimmer and the BSQ
front (component relation 5). Propionic acid is exemplary of the behavior of
the carboxylic acids. In cluster mode, the dominant ions are the
deprotonated-declustered conjugate base of the acid (
Voltage scanning experiments for a variety of potential fragment ions. Top: component relation 5. Bottom: component relation 3.
The RH dependence of these clusters proceeds in the same manner as the
reagent clusters. Increasing water vapor concentration in the IMR (or RH in
the sample line) decreases the [acetate
These effects can be clearly observed by examining a single voltage set
corresponding to a vertical slice of Fig. 6. Figure 7 shows this picture at
dV
Acetate CIMS measurements are characterized by high background count rates
which affect the limit of detection (LOD). The LOD is calculated for all
calibration curves (Sect. S5.3). The LODs of propionic acid ions detected in
cluster mode are plotted in Fig. 7. The high sensitivity to the
[acetate
These low LODs for the [acetate
Molecular fragmentation can occur at high electric field strengths. Specific
ions observed in the mass spectrum enable investigation of the voltages at
which fragmentation onsets. We investigate fragmentation between the SSQ back
and the lens skimmer (component relation 3) and between the skimmer and BSQ
front (component relation 5). We identify at least six ions (O
Mass defect plots from scanning component relation 3 during the
Bulk properties calculated in Tofware during the
We use a potential aerosol mass (PAM) chamber to create a complex mixture of
oxidized organic species in high concentrations from the oxidation of
Alkanoic acid species scanning results during authentic standard API
scanning (left column) and PAM chamber scanning (right column). dV
Individual alkanoic acid scans obtained during the scanning PAM chamber
experiment (left) and [alkanoic acid
Bulk descriptive values are calculated by Tofware using the ion signal
intensity to weight the contribution of each individual ion to the total
signal (Fig. 10). This approach is frequently conducted with the HR-TOF-CIMS,
either without correcting for differences in sensitivity (Friedman et al.,
2016), or by applying the sensitivity of one species (typically formic acid) to
every species (Chhabra et al., 2015). The main finding is that the average
oxygen to carbon ratio (O : C), hydrogen to carbon ratio (H : C),
oxidation state, and carbon number (number of carbons) all change significantly as
a function of applied voltage difference. The average number of carbons per ion
decreases by
dV
The shape of the declustered-deprotonated ions during the PAM declustering scan is different from the behavior of these species during single-component declustering scans in zero air. When individual authentic standards are added to zero air and declustering depletes the acetate-carboxylic acid cluster, the corresponding deprotonated-declustered ion ceases to change. In contrast, PAM declustering scans show a continually increasing signal for the C3–C5 alkanoic acids with declustering. The signal intensity of the C3–C5 alkanoic acids during the PAM experiment is quite low in comparison to formic acid. Thus, the amount of fragmentation or declustering from strongly bound clusters must be substantial to actually observe this effect for formic acid.
Acetate CIMS ionizes analytes by both proton abstraction (Reaction R1) and ion-neutral clustering reactions (Reacions R2–R3). Detected ions are observed as deprotonated-declustered ions because of the collisional dissociation that occurs during the transfer of the ions from the ion source to the mass analyzer (Reaction R4). The original development of this method by Veres et al. (2008) does not investigate the importance of clustering in the ion source due to the use of a quadrupole mass spectrometer, limited mass scan range, and a collisional dissociation chamber (CDC). The idea that acetate CIMS is selective towards carboxylic acids is true, but the two ionization pathways (clustering vs. direct proton abstraction) complicate mass spectral interpretation and efficient declustering with a CDC is necessary. Thus, the selectivity of acetate towards acids is really a function of both ion-neutral chemistry and instrument operation.
We find that the acetate CIMS reagent ions and reagent ion clusters behave similarly to the detected species in both clustering behavior and effects of API declustering. The observed clustering behavior of the reagent ions with water (Fig. 5) explains the sensitivity dependence on RH (Figs. 6–7, Sect. S4). During calibration, the analyte-containing clusters are shifting in abundance as a function of water vapor concentration, leading to differences in collisional dissociation efficiency and proton-abstraction efficiency. This is inconsistent with previous quadrupole acetate CIMS experiments that indicate no humidity dependence for formic acid (Veres et al., 2008). However, the ions most susceptible to humidity effects are the ion-neutral clusters; these species are rarely detected because of the operation of the API on the HR-TOF-CIMS in a declustered mode and the use of a CDC on quadrupole instruments. As such, the cluster distribution in the Veres et al. (2008) study may be completely different than the cluster distribution observed here, making comparison between these instruments and relative humidity effects nebulous. Collisional dissociation both simplifies the observed mass spectrum and eliminates the observation of acetate-containing ion-neutral clusters. Effective collisional dissociation is the key to predominantly detecting proton-abstraction reaction products and maintaining the level of selectivity desired with chemical ionization. Ambient detection of IEPOX and ISOPOOH using acetate clusters (Budisulistiorini et al., 2015) will likely suffer from severe humidity effects leading to large changes in sensitivity.
Similar humidity dependences are observed with iodide adduct CIMS (Lee et al., 2014). Acetate CIMS may be simpler because the sensitivities for the deprotonated-declustered ions follow approximately the same trend at a given voltage configuration in the API. In contrast, species clustered with iodide exhibit different RH dependences in both magnitude and shape for iodide adduct CIMS. We observe similarly complex RH dependencies in acetate and iodide reagent ions when run in a clustering mode (Fig. 7). The observation of carboxylic acids clustering with water and other ions has been observed using quadrupole instruments with atmospheric pressure ion sources (Viidanoja et al., 1998).
The role of water on acetate CIMS chemistry remains difficult to reconcile. Propionic acid sensitivities are the lowest under dry and very wet conditions (Fig. 6), but other trends exist for other deprotonated-declustered acids (Sect. S5.1). The formation of the water clusters, acetate clusters, and self-clusters shows identical RH dependence for all the calibration compounds: the addition of water shifts the cluster distribution as water is incorporated into acetate clusters. Additionally, normalization methods described herein do not eliminate the relative humidity dependence. Normalization of acetate CIMS data remains a challenge because the information about the cluster distribution is lost when collisional dissociation is sufficiently high that we observe only declustered, deprotonated ions. Relative-humidity-dependent calibrations may be the most direct method for rigorously addressing the water interference.
Controlling for clustering reactions by operating the API on the HR-TOF-CIMS
under declustered settings is obvious, but the API voltage configurations do
not exist as a binary system of clustered and declustered operation,
making the choice of voltages a balancing act. The data presented herein
indicate that operating with an acetate cluster ratio of
Acetate CIMS requires significant declustering for ambient atmospheric
measurement. The sensitivity to propionic acid detected as propanoate is
maximized for component relation 5 at a dV of 10–12 V (Fig. 6), although
the LOD and relative contribution of each cluster vs. the
deprotonated-declustered species remains surprisingly high at these voltages
(see Sect. S5 for additional compounds, LODs, and sensitivity ratios).
Increasing the dV at component relation 5 causes the relative contribution of
each cluster to drop and decreases the sensitivity of the
deprotonated-declustered ions (Sect. S5.2). However, these high-voltage
differences lead to the formation of potential fragment ions at low
Chhabra et al. (2015) present a method to account for clustering, or adduct
formation, in a study of
We note two challenges in quantifying the impact of clustering on observed bulk properties or mass. (1) The presence of self-clusters and clusters formed with other ions present in the background spectrum during single-component calibrations suggests that complex mixtures will be impacted by clustering from other species; for example, ambient formic acid may form formate ions that cluster with other carboxylic acids. In situ standard additions are one approach for identifying this problem of secondary chemical ionization. (2) RH changes the ratio of clustered analyte to deprotonated-declustered analyte (Fig. 7, Sect. S5.2), further complicating quantification in ambient field measurements. However, controlling cluster interference in observed mass spectra by collisional dissociation is a straightforward approach to the complexity of the acetate CIMS. Other formulations proposed in the literature may oversimplify this problem.
Quantification of complex mixtures with the acetate CIMS is a complex problem. Clustering is a key mechanism for abstracting protons from carboxylic acids. Proton-abstracted declustered ions are predominantly observed if clusters are collisionally dissociated during transmission from the IMR to the detector. This suggests that some combination of both cluster binding energy and gas-phase acidity control the extent to which the analyte species retains a charge upon declustering. The prevalence of cross-clustering reactions also demonstrates that secondary ion chemistry is occurring to an appreciable extent. The challenge of quantification when sensitivity varies by both analyte and RH may be further complicated by IMR design and ion transmission through the ion optics. With all these considerations, it is remarkable that such good agreement has been found between acetate CIMS measurements and aerosol mass spectrometer data, suggesting that despite the complexities and unknowns, the acetate CIMS captures an important fraction of the gas-phase chemistry relevant to secondary organic aerosol production and evolution (Aljawhary et al., 2013; Chhabra et al., 2015; Lopez-Hilfiker et al., 2016).
Non-targeted analysis using HR-TOF-CIMS with no pre-separation is
challenging, but remains a promising technique to understand atmospherically
relevant species at low (
Iodide adduct and nitrate adduct CIMS may also benefit from routinely operating in a voltage scanning mode for non-targeted analysis. The iodide CIMS mass spectrum contains a poorly understood region that is separated in mass defect space from the iodide-cluster region by the “iodide valley” (Lee et al., 2014). This region is thought to contain peroxy acids (R-C(O)OOH) which appear as carboxylic acids upon increasing the applied voltage difference in the API. Thus, under normal iodide adduct CIMS operation, species in this region will exist as a complex mixture of ion-neutral clusters without iodide. Upon declustering, the iodide adducts will fall apart along with any of the non-iodide-containing ion-neutral clusters observed in the more positive mass defect region. This would provide an additional set of information that can be compared to the results obtained in a clustered mode where only the iodide-containing clusters are evaluated. Lastly, if the lessons learned here about acetate CIMS apply to deprotonated-declustered anions in general, one may decrease the RH dependence observed with the iodide adducts by operating in a declustered mode and examining declustered species.
The API characterization presented herein may impact the analysis of atmospheric ions and new-particle formation under both ambient and laboratory conditions, such as the Cosmics Leaving OUtdoor Droplets (CLOUD) facility. Recent publications detailing CLOUD chamber measurements show stable clusters containing up to 17 sulfuric acid molecules clustered with other species (Schobesberger et al., 2015). The authors note that water is absent from most observed clusters due to evaporation inside the API-TOF, and that other species may also fragment (Olenius et al., 2013). The literature surrounding the API-TOF further acknowledges that declustering inside the instrument is poorly understood, and that fragmentation is highly related to instrument settings (Ehn et al., 2011; Junninen et al., 2010; Olenius et al., 2013). The scanning procedures presented herein may be of particular use to API-TOF instruments, in determining both the strength of these clusters and the API control/bias on observed cluster size and composition.
The observed mass spectrum acquired using the acetate CIMS is the combined result
of CI occurring in the IMR and declustering occurring throughout the
instrument. Ignoring clustering will result in either an over- or
underestimation of the average H : C ratio, O : C ratio, average
oxidation state, and average number of carbons depending on the extent of
clustering. Clustering is efficiently controlled using API component
relations, and clusters can be identified using nonlinear least-squares
sigmoidal regression and dV
Data used to prepare this paper are available upon request from the corresponding author.
We acknowledge the National Science Foundation (AGS 1240611) and the Arnold and Mabel Beckman Foundation (Young Investigator Award) for funding this work. We would also like to acknowledge Joel Kimmel and Manuel Hutterli (Tofwerk AG) for relevant discussions and technical support. Edited by: G. Phillips Reviewed by: two anonymous referees