Preprints
https://doi.org/10.5194/gmd-2021-397
https://doi.org/10.5194/gmd-2021-397

Submitted as: model description paper 10 Dec 2021

Submitted as: model description paper | 10 Dec 2021

Review status: this preprint is currently under review for the journal GMD.

Description and evaluation of the community aerosol dynamics model MAFOR v2.0

Matthias Karl1, Liisa Pirjola2,11, Tiia Grönholm3, Mona Kurppa3, Srinivasan Anand4, Xiaole Zhang5, Andreas Held6, Rolf Sander7, Miikka Dal Maso8, David Topping9, Shuai Jiang10, Leena Kangas3, and Jaakko Kukkonen3,12 Matthias Karl et al.
  • 1Chemistry Transport Modelling, Helmholtz-Zentrum Hereon, Geesthacht, Germany
  • 2Department of Physics, University of Helsinki, Helsinki, Finland
  • 3Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
  • 4Health Physics Division, Bhabha Atomic Research Centre, Mumbai, India
  • 5Institute of Environmental Engineering (IfU), ETH Zürich, Zürich, Switzerland
  • 6Environmental Chemistry and Air Research, Technische Universität Berlin, Berlin, Germany
  • 7Air Chemistry Department, Max-Planck Institute of Chemistry, Mainz, Germany
  • 8Aerosol Physics, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland
  • 9Department of Earth and Environmental Science, University of Manchester, Manchester, UK
  • 10School of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui, China
  • 11Department of Automotive and Mechanical Engineering, Metropolia University of Applied Sciences, Vantaa, Finland
  • 12Centre for Atmospheric and Climate Physics Research, and Centre for Climate Change Research, University of Hertfordshire, Hatfield, UK

Abstract. Numerical models are needed for evaluating aerosol processes in the atmosphere in state-of-the-art chemical transport models, urban-scale dispersion models and climatic models. This article describes a publicly available aerosol dynamics model MAFOR (Multicomponent Aerosol FORmation model; version 2.0); we address the main structure of the model, including the types of operation and the treatments of the aerosol processes. The main advantage of MAFOR v2.0 is the consistent treatment of both the mass- and number-based concentrations of particulate matter. An evaluation of the model is also presented, against a high-resolution observational dataset in a street canyon located in the centre of Helsinki (Finland) during an afternoon traffic rush hour on 13 December 2010. The experimental data included measurements at different locations in the street canyon of ultrafine particles, black carbon, and fine particulate mass PM1. This evaluation has also included an intercomparison with the corresponding predictions of two other prominent aerosol dynamics models, AEROFOR and SALSA. All three models fairly well simulated the decrease of the measured total particle number concentrations with increasing distance from the vehicular emission source. The MAFOR model reproduced the evolution of the observed particle number size distributions more accurately than the other two models. The MAFOR model also predicted the variation of the concentration of PM1 better than the SALSA model. We also analysed the relative importance of various aerosol processes based on the predictions of the three models. As expected, atmospheric dilution dominated over other processes; dry deposition was the second most significant process. Numerical sensitivity tests with the MAFOR model revealed that the uncertainties associated with the properties of the condensing organic vapours affected only the size range of particles smaller than 10 nm in diameter. These uncertainties do not therefore affect significantly the predictions of the whole of the number size distribution and the total number concentration. The MAFOR model version 2 is well documented and versatile to use, providing a range of alternative parametrizations for various aerosol processes. The model includes an efficient numerical integration of particle number and mass concentrations, an operator-splitting of processes, and the use of a fixed sectional method. The model could be used as a module in various atmospheric and climatic models.

Matthias Karl et al.

Status: open (until 04 Feb 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-397', Anonymous Referee #1, 22 Jan 2022 reply

Matthias Karl et al.

Data sets

Release of the community aerosol dynamics model MAFOR v2 and the urban case dataset published in Karl et al., GMD, 2021 (v1.9.9) Karl, Matthias; Pirjola, Liisa; Grönholm, Tiia; Kurppa, Mona; Anand, Srinivasan; Zhang, Xiaole; Held, Andreas; Sander, Rolf; Dal Maso, Miikka; Topping, David; Jiang, Shuai; Kangas, Leena, & Kukkonen, Jaakko https://zenodo.org/record/5718580

Model code and software

MAFOR v2 - community model for aerosol dynamics Karl, Matthias https://github.com/mafor2/mafor

Matthias Karl et al.

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Short summary
Numerical process models are needed in air quality models and climate models to better understand atmospheric aerosols. The community aerosol dynamics model MAFOR consistently treats particulate matter both in terms of number and mass. An evaluation of the model against a high-resolution observational dataset in a street canyon shows that MAFOR accurately reproduces the evolution of the particle number size distribution and the variation of fine particulate matter on the street scale.