Mass Spectra Of Individual Particles Research Articles

Improvement of peaks identification and dynamic range for bi-polar Single Particle Mass Spectrometer

Delay Extraction (DE) in Single Particle Mass Spectrometry (SPMS) provides substantial resolution enhancement. However, DE has two main drawbacks which are discussed in our article. First, ion peak position in this case becomes very sensitive to initial ion coordinate. Therefore, substantial peak jitter is observed when switching between mass spectra of individual particles. This peak jitter obstructs correct mass spectra accumulation resulting in wide peaks with irregular shapes in the accumulated mass spectrum, which leads to the fact that isotopic pattern identification becomes difficult. In the present article two ways of the peak jitter compensation, Dynamic Calibration and Mass Spectra correction based on Spectra Correlation, are proposed. It was shown that both proposed techniques provide substantial resolution improvement in the summed mass spectrum especially for small peaks with complex isotopic patterns. Second, time delay distorts regular quadratic dependence between time-of-flight and m/z. In our paper we also propose calibration equation with variable exponent for SPMS modified with DE. It is shown that usage of an exponent as a fitting parameter allows to achieve mass accuracy comparable with 4th degree equation proposed earlier.

Single-particle measurements of bouncing particles and in situ collection efficiency from an airborne aerosol mass spectrometer (AMS) with light-scattering detection

Abstract. A light-scattering module was coupled to an airborne, compact time-of-flight aerosol mass spectrometer (LS-AMS) to investigate collection efficiency (CE) while obtaining nonrefractory aerosol chemical composition measurements during the Southeast Nexus (SENEX) campaign. In this instrument, particles scatter light from an internal laser beam and trigger saving individual particle mass spectra. Nearly all of the single-particle data with mass spectra that were triggered by scattered light signals were from particles larger than ∼ 280 nm in vacuum aerodynamic diameter. Over 33 000 particles are characterized as either prompt (27 %), delayed (15 %), or null (58 %), according to the time and intensity of their total mass spectral signals. The particle mass from single-particle spectra is proportional to that derived from the light-scattering diameter (dva-LS) but not to that from the particle time-of-flight (PToF) diameter (dva-MS) from the time of the maximum mass spectral signal. The total mass spectral signal from delayed particles was about 80 % of that from prompt ones for the same dva-LS. Both field and laboratory data indicate that the relative intensities of various ions in the prompt spectra show more fragmentation compared to the delayed spectra. The particles with a delayed mass spectral signal likely bounced off the vaporizer and vaporized later on another surface within the confines of the ionization source. Because delayed particles are detected by the mass spectrometer later than expected from their dva-LS size, they can affect the interpretation of particle size (PToF) mass distributions, especially at larger sizes. The CE, measured by the average number or mass fractions of particles optically detected that had measurable mass spectra, varied significantly (0.2–0.9) in different air masses. The measured CE agreed well with a previous parameterization when CE > 0.5 for acidic particles but was sometimes lower than the minimum parameterized CE of 0.5.

Uptake of Semivolatile Secondary Organic Aerosol Formed from α-Pinene into Nonvolatile Polyethylene Glycol Probe Particles.

Semivolatile organic compounds (SVOCs) play an essential role in secondary organic aerosol (SOA) formation, chemical aging, and mixing of organic aerosol (OA) from different sources. Polyethylene glycol (PEG400) particles are liquid, polar, and nearly nonvolatile; they provide a new vehicle to study the interaction between SVOCs with OA. With a unique fragment ion C4H9O2(+) (m/z 89), PEG400 can be easily separated from α-pinene SOA in aerosol mass spectra. By injecting separately prepared PEG probe particles into a chamber containing SOA coated on ammonium sulfate seeds, we show that a substantial pool of SVOCs exists in equilibrium with the original SOA particles. Quantitative findings are based on bulk mass spectra, size-dependent composition, and the evolution of individual particle mass spectra, which we use to separate the two particle populations. We observed a larger fraction of SVOC vapors with increased amounts of reacted α-pinene. For the same amount of reacted α-pinene, the SOA formed from α-pinene oxidized by OH radicals had a higher fraction of SOA vapors than SOA formed by α-pinene ozonolysis. Compared to the PEG400 probe particles, we observed a lower mass fraction of SVOCs in poly(ethylene glycol) dimethyl ether (MePEG500) probe particles under otherwise identical conditions; this may be due to the lower polarity of the MePEG500 or caused by esterification reactions between the PEG400 and organic acids in the SOA.

Transition Metal Associations with Primary Biological Particles in Sea Spray Aerosol Generated in a Wave Channel

In the ocean, breaking waves generate air bubbles which burst at the surface and eject sea spray aerosol (SSA), consisting of sea salt, biogenic organic species, and primary biological aerosol particles (PBAP). Our overall understanding of atmospheric biological particles of marine origin remains poor. Here, we perform a control experiment, using an aerosol time-of-flight mass spectrometer to measure the mass spectral signatures of individual particles generated by bubbling a salt solution before and after addition of heterotrophic marine bacteria. Upon addition of bacteria, an immediate increase occurs in the fraction of individual particle mass spectra containing magnesium, organic nitrogen, and phosphate marker ions. These biological signatures are consistent with 21% of the supermicrometer SSA particles generated in a previous study using breaking waves in an ocean-atmosphere wave channel. Interestingly, the wave flume mass spectral signatures also contain metal ions including silver, iron, and chromium. The nascent SSA bioparticles produced in the wave channel are hypothesized to be as follows: (1) whole or fragmented bacterial cells which bioaccumulated metals and/or (2) bacteria-derived colloids or biofilms which adhered to the metals. This study highlights the potential for transition metals, in combination with specific biomarkers, to serve as unique indicators for the presence of marine PBAP, especially in metal-impacted coastal regions.

Sources of metals and bromine-containing particles in Milwaukee

An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was deployed in summer 2010 in central Milwaukee as part of a study to understand the sources of primary and secondary aerosol in the non-attainment area of Southeast Wisconsin. Measurements were made continually from mid-July to mid-August, collecting time, size, and chemical composition data on aerosol particles. Trace metals including Se, Cd, Mo, and Sb were detected in the particles. These metals were found to be related and provided information on source types in Milwaukee, generally located southwest of the sampling site, from plumes that appear to originate from point sources. Additionally, Br was detected in individual particle mass spectra during this study, the first such observation at an inland site. Particles that contained Br were found in two different size modes, each of which had a different representative chemical composition. In combination with an analysis of wind direction, the data suggest that the two different size modes of Br-containing particles originate from chemically distinct sources.

Persistence of organic carbon in heated aerosol residuals measured during Tropical Composition Cloud and Climate Coupling (TC4)

The Particle Analysis by Laser Mass Spectrometry (PALMS) single particle mass spectrometer was used to analyze the composition of the nonvolatile fraction of atmospheric aerosol in a number of different environments. The mass spectra of individual particles sampled through an inlet section heated to 300°C were compared to unheated particles during flights of the NASA DC‐8 aircraft during the Tropical Composition Cloud and Climate Coupling (TC4) mission. Comparisons are presented of measurements made in the marine boundary layer, the free troposphere, and the continental boundary layer over the Colombian jungle. The heated section completely removed sulfate from the aerosols except for sodium sulfate and related compounds in sea salt particles. Organic material in sea salt particles was observed to be less volatile than chlorine. Biomass burning particles were more likely to survive heating than other mixed sulfate‐organic particles. For all particle types, there was a significant contribution to the residues from carbonaceous material other than elemental carbon. These results demonstrate the remaining compositional complexity of aerosol residuals that survive heating in a thermal denuder.

Comparison between mass spectra of individual organic particles generated by UV laser ablation and in the IR/UV two-step mode

In ablation-based single particle mass spectrometry it is common to find that the mass spectra of particles with identical compositions exhibit significant particle-to-particle fluctuations and high degree of fragmentation. This is particularly true when it comes to particles containing organic compounds. At laser fluence that is sufficient to ionize sulfates, mass spectra of the identical organic particles are classified into multitude of classes, some of which are indistinguishable from elemental carbon. In contrast, the individual particle mass spectra generated in two-step mode, in which an IR laser pulse is used to evaporate the semivolatile particle components and a time delayed UV laser pulse is used to ionize the evaporating plume, exhibit greatly diminished particle-to-particle fluctuations and significantly improved mass spectral quality. Since individual particle mass spectra must first be classified and only then can be averaged and analyzed, the IR/UV mode greatly improves the capability to properly quantify particle compositions. We present an experimental investigation of the properties and behavior of individual particle mass spectra of organic particles that are generated by ablation and in the two-step mode as function of UV laser fluence and the delay between the two lasers. The study shows that the two-step mode yields highly reproducible mass spectra that contain sufficient detail to allow molecular identification. In addition it produces significantly higher mass spectral intensities that are linearly related to the mass of organics in the particles. In contrast, ablation generated mass spectra were found to exhibit high degree of fragmentation and large particle-to-particle fluctuations.

Chemical composition and size distribution of secondary organic aerosol formed from the photooxidation of isoprene

Photooxidation of isoprene leads to the formation of secondary organic aerosol (SOA). In this study, the chemical composition of SOA formed from OH-initiated photooxidation of isoprene has been investigated with gas chromatography/mass spectrometry (GC/MS) and a home-made aerosol time-of-flight mass spectrometer. Sampling particles generated in a home-made smog chamber. The size distribution of SOA particles was detected by a TSI 3321 aerodynamic particle size spectrometer in real time. Results showed that SOA created by isoprene photooxidation was predominantly in the form of fine particles, which have diameters less than 2.5 microm. The obtained mass spectra of individual particles show that products of the OH-initiated oxidation of isoprene contain methyl vinyl ketone, methacrolein, formaldehyde, and some other hydroxycarbonyls. The possible reaction mechanisms leading to these products were also discussed.

ClusterSculptor: Software for expert-steered classification of single particle mass spectra

To take full advantage of the vast amount of highly detailed data acquired by single particle mass spectrometers requires that the data be organized according to some rules that have the potential to be insightful. Most commonly cluster analysis methods are used to classify the individual particle mass spectra on the basis of their similarity. Cluster analysis is a powerful strategy for the exploration of high-dimensional data in the absence of a-priori hypotheses or data classification models. However, more often than not, the examination of the data clustering results reveals that many clusters contain particles of different types and that many particles of one type end up in a number of separate clusters. Our experience with cluster analysis shows that we have a vast amount of non-compiled knowledge and intuition that if brought to bear in this effort has the potential to greatly improve it. ClusterSculptor is software package designed to provide a comprehensive and intuitive visual framework to aid scientists introduce their vast knowledge into the data classification process. ClusterSculptor offers a wide variety of tools that are necessary for a high-dimensional, expert-driven activity we call cluster sculpting. ClusterSculptor is designed to be coupled to SpectraMiner, our data mining and visualization software package. The data are first visualized with SpectraMiner and identified problems are exported to ClusterSculptor, where the user steers the reclassification and recombination of clusters of tens of thousands of particle mass spectra in real-time. The resulting sculpted clusters can be then imported back into SpectraMiner. Here we present the results of a study, in which ClusterSculptor is used to classify a complex dataset that includes single particle mass spectra of a variety of particle types. The compositions of these laboratory generated particles were carefully chosen to test some of the more difficult aspects of single particle mass spectroscopy. We demonstrate the use of ClusterSculptor to greatly improve chemical speciation of single particles by introducing expert input into data classification process.

A High Resolution Study of the Effect of Morphology On the Mass Spectra of Single PSL Particles with Na-containing Layers and Nodules

The interpretation and quantification of measurements of particle composition by laser ablation based single particle mass spectrometry is complex. Among the most difficult systems to quantify are internally mixed particles containing alkali metals and organics. The alkali atoms in such particles tend to suppress the formation of other ions sometimes to below the detection limit. Here we present a study of the behavior of single particle mass spectral peak intensities as a function of the amount of the sodium containing compounds deposited on the surface of 240 nm polystyrene latex (PSL) spheres. We generate three morphologically distinct and well defined coating types: uniform layers, cubic nodules and rounded nodules, and measure the individual particle mass spectra as a function of the vacuum aerodynamic diameter with nanometer resolution. The data show that the probability of detecting the PSL spheres depends on the amount of the alkali metal on the PSL sphere surface, its morphological distribution and the ablation laser power. The data suggest that PSL spheres with localized Na-containing nodules are easier to detect than those which are completely encapsulated. We show, for example, that at low laser power, PSL particles that are completely encapsulated with Na-containing compounds, whose weight fraction is close to 50%, cannot be detected, while 35% of PSL spheres with same amount of coating can be detected if coating is localized in nodules on a fraction of the particle surface.

SpectraMiner, an interactive data mining and visualization software for single particle mass spectroscopy: A laboratory test case

Single particle mass spectrometers are sophisticated instruments designed to measure the sizes and compositions of a wide range of individual particles in situ, in real-time. They characterize hundreds of thousands or millions of particles, generating vast amounts of rich and complex data, the proper mining of which requires dedicated state of the art tools. The analysis of individual particle mass spectra is particularly difficult because of their high dimensionality—each data point, representing a single particle, includes the 450 mass spectral peak intensities, particle size, and time of detection. The first step is to organize the data; a process typically accomplished by grouping particles of similar attributes. Since the common assumption is that the data should be reduced to become manageable, they are typically classified into a small number of clusters (∼10), each of which is represented by an average/representative spectrum. Our approach is quite different. We have developed a data mining and visualization software package we call SpectraMiner that makes it possible to handle hundreds of clusters, limiting loss of information and thus overcoming the boundaries set by traditional statistical data analysis approaches. Data, which often include over 1 million particle spectra, are organized using K-mean clustering algorithm. The clusters are merged into nodes by sequentially combining similar clusters. The final structure is displayed in a hierarchical dynamical tree or circular dendogram. This interactive dendogram is the visual interface that allows for real-time data exploration and mining. Clicking on any of the clusters/nodes in the dendogram reveals the detailed information about the particles that reside at that position. At each step the scientist is in control of the level of detail and the visualization format, rapidly switching between them while running the program on a PC. Here we present a study that puts the classification aspect of SpectraMiner to the test. Twelve types of laboratory generated particles are carefully chosen to test some of the difficult aspects of single particle mass spectroscopy. We quantify the degree of particle identification and separation at a number of levels and demonstrate how the visualization tools that SpectraMiner provides can be used to refine, steer and control the data mining process.

Baltimore Supersite: Highly time- and size-resolved concentrations of urban PM 2.5 and its constituents for resolution of sources and immune responses

Protection of public health from the effects of air particulate matter (PM) requires measurements and methods that assess the PM chemical constituents, physical properties, and their sources. Sampling was conducted at three sites in the Baltimore area: a source-oriented (industrial) area in south Baltimore (FMC site), and two receptor area sites (Clifton Park and Ponca Street). FMC measurements were made for the initial 1-month of the project; Clifton measurements lasted for about 2 months, while measurements at Ponca Street lasted for about 9.5 months. Pollutant samples were collected at intervals ranging from 5 min to 1 h using semi-continuous monitors for PM 2.5 mass, sulfate, nitrate, elemental and organic carbon, particle number size distributions (10–20,000 nm), CO, NO x , O 3, 11 metals, and mass spectra of individual particles, throughout the project. In addition to standard meteorological measurements, a 3D-sonic anemometer and a LIDAR system were operated during selected periods as were a rotating drum impactor with 3- to 6-h resolution and a filter/PUF sampler for 3-h measurements of organic compounds. Standard speciation and FRM mass measurements were also made. This report describes the types of measurements that were made at the various sites of the Baltimore Supersite program as well as presents the summary statistics for some of the PM measurements that have been made. The measurements of aerosol mass, major components, and size distribution data for the three sites are compared. Results show comparable PM concentrations at Ponca Street and Clifton Park. Increased variability was observed at Ponca Street.

Determination of Single Particle Mass Spectral Signatures from Light-Duty Vehicle Emissions

In this study, 28 light-duty gasoline vehicles (LDV) were operated on a chassis dynamometer at the California Air Resources Board Haagen-Smit Facility in El Monte, CA. The mass spectra of individual particles emitted from these vehicles were measured using aerosol time-of-flight mass spectrometry (ATOFMS). A primary goal of this study involves determining representative size-resolved single particle mass spectral signatures that can be used in future ambient particulate matter source apportionment studies. Different cycles were used to simulate urban driving conditions including the federal testing procedure (FTP), unified cycle (UC), and the correction cycle (CC). The vehicles were selected to span a range of catalytic converter (three-way, oxidation, and no catalysts) and engine technologies (vehicles models from 1953 to 2003). Exhaust particles were sampled directly from a dilution and residence chamber system using particle sizing instruments and an ATOFMS equipped with an aerodynamic lens (UF-ATOFMS) analyzing particles between 50 and 300 nm. On the basis of chemical composition, 10 unique chemical types describe the majority of the particles with distinct size and temporal characteristics. In the ultrafine size range (between 50 and 100 nm), three elemental carbon (EC) particle types dominated, all showing distinct EC signatures combined with Ca, phosphate, sulfate, and a lower abundance of organic carbon (OC). The relative fraction of EC particle types decreased as particle size increased with OC particles becoming more prevalent above 100 nm. Depending on the vehicle and cycle, several distinct OC particle types produced distinct ion patterns, including substituted aromatic compounds and polycyclic aromatic hydrocarbons (PAH), coupled with other chemical species including ammonium, EC, nitrate, sulfate, phosphate, V, and Ca. The most likely source of the Ca and phosphate in the particles is attributed to the lubricating oil. Significant variability was observed in the chemical composition of particles emitted within the different car categories as well as for the same car operating under different driving conditions. Two-minute temporal resolution measurements provide information on the chemical classes as they evolved during the FTP cycle. The first two minutes of the cold start produced more than 5 times the number of particles than any other portion of the cycle, with one class of ultrafine particles (EC coupled with Ca, OC, and phosphate) preferentially produced. By number, the three EC with Ca classes (which also contained OC, phosphate, and sulfate) were the most abundant classes produced by the nonsmoking vehicles. The smoker category produced the highest number of particles, with the dominant classes being OC comprised of substituted monoaromatic compounds and PAHs, coupled with Ca and phosphate, thus suggesting used lubricating oil was associated with many of these particles. These studies show, by number, EC particles dominate gasoline emissions in the ultrafine size range particularlyforthe lowest emitting newer vehicles, suggesting the EC signature alone cannot be used as a unique tracer for diesels. This represents the first report of high time- and size-resolved chemical composition data showing the mixing state of nonrefractory elements in particles such as EC for vehicle emissions during dynamometer source testing.

Long-range sources of Toronto particulate matter (PM2.5) identified by Aerosol Laser Ablation Mass Spectrometry (LAMS)

Abstract An aerosol laser ablation mass spectrometer (LAMS) was operated continuously in downtown Toronto for a period of 11 months. The mass spectra of individual particles were classified according to their chemical composition using neural net-based adaptive resonance theory (ART-2a). The types of particles thereby identified were used as the basis for classifying particles from a 10-day sampling period within the 11-month sampling study. The particles within a class were further segregated by size, and the number of particles analyzed per hour was calculated for each of the resulting composition and sized based classes. ART-2a was used to combine these classes into groups based on similarity in their temporal trends. Two unusual sources were thereby identified: forest fire particles and intercontinental dust. The forest fire particles primarily exhibited potassium and potassium sulphate, while the intercontinental dust exhibited crustal metals, like titanium, aluminum, and iron. Back trajectory analysis of the air masses that transported these particles to Toronto revealed their origins as Northern Canada and Africa. From the chemical composition and size of the particles, a forest fire episode in Western Canada was identified during the 11-month sampling study on 1 June 2002. Other episodes of particles originating from Africa were not observed. These findings demonstrated the use of temporal variations in single particle chemistry to identify sources.

Hydroxymethanesulfonate as a tracer for fog processing of individual aerosol particles

Hydroxymethanesulfonate (HMS), an important component in fog and cloud systems, is identified in the negative ion mass spectra of individual particles sampled with an aerosol time-of-flight mass spectrometer (ATOFMS). The peak assignment at mass/charge ( m/ z)–111 is confirmed by analyzing HMS particles produced in the laboratory. Individual particle mass spectra from a field campaign in Bakersfield, California reveal the presence of HMS in the ambient aerosol during isolated time periods near the dissipation phase of fog suggesting fog processing of the aerosol. The lifetime of HMS in the aerosol is limited to less than 12 h. Using the presence of HMS as a tracer for aqueous-phase fog processing, the size distribution indicates that particles with aerodynamic diameters greater than 0.7 μm are most affected by the fog and associated high relative humidity. HMS is predominantly associated with particles containing carbon, ammonium, sulfate, and nitrate. Examination of elemental carbon particles containing HMS shows the presence of organic carbon which most likely enhances the hygroscopicity of these particles. This study demonstrates the ability for real-time measurements of fog processing at the single particle level using a chemical tracer for aqueous-phase reactions and highlights the possibilities for using high temporal resolution measurements to gain unique insights into atmospheric processes.

Formation of aerosol particles from reactions of secondary and tertiary alkylamines: characterization by aerosol time-of-flight mass spectrometry.

In ambient field studies conducted with aerosol time-of-flight mass spectrometry (ATOFMS), individual particle mass spectra commonly contain ion peaks at mass/charge (m/z) 86, 101, 102, and 118. Particles with mass spectra containing these peaks show a strong correlation with high relative humidity and low temperatures. In an effort to identify these peaks, a series of smog chamber studies were conducted probing the chemistry of secondary and tertiary alkylamines. Specifically, in separate studies, trimethylamine, di- and triethylamine, and di- and tripropylamine were reacted in a 1 m3 Teflon outdoor smog chamber with naturally occurring levels of gas phase oxidants in ambient air. The aerodynamic sizes and individual mass spectra of the resulting aerosol particles were acquired continuously using aerosol time-of-flight mass spectrometry (ATOFMS). Both oxidation and acid-base reactions between amines and acids commonly present in the atmosphere (i.e., nitric and sulfuric acid) appear to play roles in the formation and chemistry of organic nitrogen-containing particle phase species. Ion peaks in the individual particle mass spectra indicate the presence of alkyl ammonium salts, as well as other tentatively identified organic N-containing compounds formed by oxidation processes. Also, for the first time, tertiary alkylamine-N-oxides have been identified as alkylamine oxidation products in the aerosol particle phase. Smog chamber reactions involving triethylamine produce ATOFMS mass spectra with similar ion peak combinations as those observed in the spectra of particles commonly detected in ambient and vehicular source characterization studies. The results of this study suggest that amine chemistry involving gas-to-particle conversion and photooxidation processes may play a significant role in particle formation in regions with high amine concentrations.

Single particle analysis of suspended soil dust from Southern California

Single particle analysis of soil dust has been performed using aerosol time-of-flight mass spectrometry. The presence of crustal elements is observed in the mass spectra of individual particles. Aluminum and iron constitute the two most commonly detected cations. Other common cations observed in the mass spectra of soil particles include sodium, magnesium, potassium, calcium, titanium, and barium, and also lithium and lanthanide oxides which are not detectable by conventional techniques such as X-ray fluorescence. Silicates make up the bulk of detected anions, although the presence of phosphate is also observed. Characteristic peaks in both the positive and negative ion mass spectra enable us to identify individual dust particles in atmospheric samples and track chemically distinct dust particles in the atmosphere with a temporal resolution of 15 min using aerosol time-of-flight mass spectrometry.