Preprints
https://doi.org/10.5194/egusphere-2022-1318
https://doi.org/10.5194/egusphere-2022-1318
 
06 Dec 2022
06 Dec 2022

Chemical identification of new particle formation and growth precursors through positive matrix factorization of ambient ion measurements

Daniel John Katz1, Aroob Abdelhamid1, Harald Stark1,2, Manjula R. Canagaratna2, Douglas R. Worsnop2,3, and Eleanor C. Browne1 Daniel John Katz et al.
  • 1Department of Chemistry and Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, 80309, United States
  • 2Aeordyne Research, Inc., Billerica, Massachusetts, 01821, United States
  • 3Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland

Abstract. In the lower troposphere, rapid collisions between ions and trace gases result in the transfer of positive charge to the highest proton affinity species and negative charge to the lowest proton affinity species. Measurements of the chemical composition of ambient ions thus provide direct insight into the most acidic and basic trace gases and their ion-molecule clusters — compounds thought to be important for new particle formation and growth. We deployed an atmospheric pressure interface time-of-flight mass spectrometer (APi-ToF) to measure ambient ion chemical composition during the 2016 Holistic Interaction of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) campaign at the United States Department of Energy Atmospheric Radiation Measurement facility in the Southern Great Plains, an agricultural region. Cations and anions were measured for alternating periods of ~24 hours over one month. We use binned positive matrix factorization (binPMF) and scaled Kendrick mass defect (SKMD) analysis to obtain information about the chemical formulas and temporal variation in ionic composition without the need for averaging over a long timescale or a priori high-resolution peak fitting. Negative ions consist of strong acids including sulfuric and nitric acid, organosulfates, and clusters of NO3- with highly oxidized molecules (HOMs) derived from monoterpene and sesquiterpene oxidation. Organic nitrates derived from sesquiterpenes account for most of the HOM signal. Combined with the diel profiles and back trajectory analysis, these results suggest that nitrate radical chemistry is active at this site. Sesquiterpene oxidation products likely contribute to particle growth at the SGP site. The positive ions consist of bases including alkylpyridiniums and amines and a series of high mass species. Nearly all the positive ions contained only one nitrogen atom and in general support ammonia and amines as being the dominant bases that could participate in new particle formation. Overall, this work demonstrates how APi-ToF measurements combined with binPMF analysis can provide insight into the temporal evolution of compounds important for new particle formation and growth.

Daniel John Katz et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1318', Anonymous Referee #1, 28 Dec 2022
  • RC2: 'Comment on egusphere-2022-1318', Anonymous Referee #2, 10 Jan 2023
  • RC3: 'Comment on egusphere-2022-1318', Anonymous Referee #3, 14 Jan 2023

Daniel John Katz et al.

Data sets

Binned Positive Matrix Factorization Results Daniel Katz and Eleanor Browne https://scholar.colorado.edu/concern/datasets/g158bj60n

Daniel John Katz et al.

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Short summary
Ambient ion chemical composition measurements provide insight into trace gases that are precursors for the formation and growth of new aerosol particles. We use a new data analysis approach to increase the chemical information from these measurements. We analyze results from an agricultural region – an understudied land use type that is ~41 % of global land use – and find that the composition of gases important for aerosol formation and growth differ significantly from those in other ecosystems.