TY - JOUR
T1 - Description and evaluation of the community aerosol dynamics model MAFOR v2.0
AU - Karl, Matthias
AU - Pirjola, Liisa
AU - Grönholm, Tiia
AU - Kurppa, Mona
AU - Anand, Srinivasan
AU - Zhang, Xiaole
AU - Held, Andreas
AU - Sander, Rolf
AU - Dal Maso, Miikka
AU - Topping, David
AU - Jiang, Shuai
AU - Kangas, Leena
AU - Kukkonen, Jaakko
N1 - Funding Information:
This research has been supported by the European Commission Horizon 2020 Framework Programme projects SCIPPER (grant no. 814893) and EMERGE (grant no. 874990).
Funding Information:
Disclaimer. This work reflects only the authors’ view, and the Innovation and European Climate, Infrastructure and Environment Executive Agency (CINEA) is not responsible for any use that may be made of the information it contains. This research has also received funding from the Academy of Finland for the project “Global health risks related to atmospheric composition and
Publisher Copyright:
© 2022 Matthias Karl et al.
PY - 2022/5/16
Y1 - 2022/5/16
N2 - 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 model simultaneously solves the time evolution of both the particle number and the mass concentrations of aerosol components in each size section. In this way, the model can also allow for changes in the average density of particles. 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 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 simulated the decrease in the measured total particle number concentrations fairly well 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 therefore do not significantly affect 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 parameterizations 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.
AB - 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 model simultaneously solves the time evolution of both the particle number and the mass concentrations of aerosol components in each size section. In this way, the model can also allow for changes in the average density of particles. 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 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 simulated the decrease in the measured total particle number concentrations fairly well 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 therefore do not significantly affect 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 parameterizations 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.
U2 - 10.5194/gmd-15-3969-2022
DO - 10.5194/gmd-15-3969-2022
M3 - Article
AN - SCOPUS:85130482174
SN - 1991-959X
VL - 15
SP - 3969
EP - 4026
JO - GEOSCIENTIFIC MODEL DEVELOPMENT
JF - GEOSCIENTIFIC MODEL DEVELOPMENT
IS - 9
ER -