27 Mar 2023
 | 27 Mar 2023

J-GAIN v1.0: A flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models

Daniel Yazgi and Tinja Olenius

Abstract. New-particle formation from condensable vapors is a common atmospheric process that has significant but uncertain effects on aerosol particle number concentrations and impacts. Assessing the formation rates of nanometer-sized particles from different vapors is an active field of research within atmospheric sciences, with new data being constantly produced by molecular models and experimental studies. Such data can be implemented in large-scale climate and air quality models as parameterizations or look-up tables. Models benchmarked against measurement data provide a straight-forward means to assess formation rates over a wide range of atmospheric conditions for given chemical compounds. Ideally, the implementation of such formation rate data should be easy, efficient and flexible in the sense that same tools can be conveniently applied for different data sets in which the formation rate depends on different parameters. In this work, we present a tool to generate and interpolate look-up tables of formation rates for user-defined input parameters. The table generator routine applies a molecular cluster dynamics model with quantum chemistry input, but other types of particle formation models may be used as well. The interpolation routine uses a multivariate interpolation algorithm, which is applicable to different numbers of independent parameters, and gives fast and accurate results with typical interpolation errors of up to a few percent. These routines facilitate the implementation and testing of different aerosol formation rate predictions in large-scale models, allowing straight-forward inclusion of new or updated data without the need to apply separate parameterizations or routines for different data sets that involve different chemical compounds or other parameters.

Daniel Yazgi and Tinja Olenius

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-2022-1464', Anonymous Referee #1, 03 May 2023
  • RC2: 'Comment on egusphere-2022-1464', Anonymous Referee #2, 06 May 2023

Daniel Yazgi and Tinja Olenius

Model code and software

J-GAIN, Software repository Daniel Yazgi and Tinja Olenius

J-GAIN v1.0 Daniel Yazgi and Tinja Olenius

Daniel Yazgi and Tinja Olenius


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Short summary
We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers, and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate look-up tables for user-defined data, thus enabling easy inclusion and testing of formation schemes.