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3 results for “chemical ionization mass spectrometry”
Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)
<p>These datasets are the raw data presented in the presented work of "Online Aerosol Chemical Characterization by Extractive Electrospray Ionization − Ultrahigh-Resolution Mass Spectrometry (EESI-Orbitrap)" in <em>Environmental Science & Technology Journal</em>, doi:10.1021/acs.est.9b07090.</p> <p>Abstract: Current mass spectrometry techniques for the online measurement of organic aerosol (OA) composition are subjected to either thermal/ionization-induced artifacts or limited mass resolving power, hindering accurate molecular characterization. Here, we combined the soft ionization capability of extractive electrospray ionization (EESI) and the ultrahigh mass resolution of Orbitrap for real-time, near-molecular characterization of OAs. Detection limits as low as tens of ng m<sup>−3</sup> with linearity up to hundreds of μg m<sup>−3</sup> at 0.2 Hz time resolution were observed for single- and mixed-component calibrations. The performance of the EESI-Orbitrap system was further evaluated with laboratory-generated secondary OAs (SOAs) and filter extracts of ambient particulate matter. The high mass accuracy and resolution (140 000 at <em>m/z</em> 200) of the EESI-Orbitrap system enable unambiguous identification of the aerosol components’ molecular composition and allow a clear separation between adjacent peaks, which would be significantly overlapping if a medium-resolution (20 000) mass analyzer was used. Furthermore, the tandem mass spectrometry (MS<sup>2</sup>) capability provides valuable insights into the compound structure. For instance, the MS<sup>2</sup> analysis of ambient OA samples and lab-generated biogenic SOAs points to specific SOA precursors in ambient air among a range of possible isomers based on fingerprint fragment ions. Overall, this newly developed and characterized EESI-Orbitrap system will advance our understanding of the formation and evolution of atmospheric aerosols.</p> <p>Structure of the datasets: The raw data are separated into individual file of excel format for the figures. Simulation data from Figure 4 can be generated using the matlab code named <em>Figure4PeakSimulation.m.</em> </p>
Highly time-resolved chemical speciation and source apportionment of organic aerosol components in Delhi, India, using extractive electrospray ionization mass spectrometry
<p>In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution,<br> especially during winters. Comprehensive knowledge of the composition and sources of the organic aerosol<br> (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating<br> effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary<br> OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA<br> sources. We address the latter through the first field deployment of an extractive electrospray ionization timeof-<br> flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer<br> (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF)<br> was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded<br> three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning<br> OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LOOOA).<br> On average, 40%of the total OA mass was apportioned to the secondary factors. The SOA contribution to<br> total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %,<br> 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA<br> sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary<br> biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin:<br> aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in<br> the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the<br> total AMS SOA (i.e. MO-OOA C LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major<br> SOA component during the daytime, with a 55.2% contribution to total SOA mass (42.4% contribution to total<br> OA). Its contribution to total SOA, however, decreased to 25.4% (7.9% of total OA) during the nighttime. This<br> factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA<br> accounted for 18.4% of total SOA mass (14.2% of total OA) during the daytime and 36.1% of total SOA mass<br> (11.2% of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2%<br> and 11.0% of total SOA mass (11.7% and 8.5% of total OA mass), respectively, during the daytime and 15.4%<br> and 22.9% of total SOA mass (4.8% and 7.1% of total OA mass), respectively, during the nighttime. A simple<br> dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime<br> concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged<br> biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production,<br> likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was<br> related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study<br> show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass<br> burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction.<br> Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the<br> daytime suggests an increased OA toxicity and health-related consequences for the general public.</p> <p>This repository has excel file corresponding to each figures presented in main text published version.</p>
Organic pesticide database with 716 molecules analyzed with chemical ionization mass spectrometry. Reagent ions: bromide, protonated acetone, hydronium ion, dioxide.
<p>The dataset joins the measurements output of two standard mixtures from GALAB Laboratories, containing 404 and 312 pesticides. The measurements were conducted at Karsa Oy with a thermal desorption multi-scheme chemical ionization inlet operating at atmospheric pressure, coupled to a linear trap quadrupole orbitrap mass spectrometer.</p> <p>The dataset contains:</p> <ul> <li>name of the compound</li> <li>CAS identifier</li> <li>SMILES</li> <li>signal of the compound with a sample analyzed at a specific concentration and with a specific ionization method.</li> </ul> <p>Reagent ions:</p> <ul> <li>bromide</li> <li>protonated acetone</li> <li>hydronium ion</li> <li>dioxide</li> </ul> <p>Sample concentrations:</p> <ul> <li>10 pg/µl</li> <li>20 pg/µl</li> <li>100 pg/µl</li> <li>1 ng/µl</li> <li>2,5 ng/µl</li> </ul> <p> </p> <p>The dataset has been analysed in the publications:</p> <ul> <li>Bortolussi, F., Sandström, H., Partovi, F., Mikkilä, J., Rinke, P., and Rissanen, M.: Technical note: Towards atmospheric compound identification in chemical ionization mass spectrometry with pesticide standards and machine learning, Atmos. Chem. Phys., 25, 685–704, https://doi.org/10.5194/acp-25-685-2025, 2025.</li> </ul>
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