Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber
We present the combined power law and log-normal distribution (PL+LN) model, a computationally efficient model to be used in simulations where the particle size distribution cannot be accurately represented by log-normal distributions, such as in simulations involving the initial steps of aeroso...
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2016-06-01
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doaj-3db0481b6c8545968099500c27449e8b2020-11-24T22:49:18ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242016-06-01167067709010.5194/acp-16-7067-2016Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamberM. Olin0T. Anttila1T. Anttila2M. Dal Maso3Aerosol Physics Laboratory, Department of Physics, Tampere University of Technology, P.O. Box 692, 33101 Tampere, FinlandAerosol Physics Laboratory, Department of Physics, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finlandnow at: Finnish Meteorological Institute, Erik Palménin aukio 1, P.O. Box 503, 00101 Helsinki, FinlandAerosol Physics Laboratory, Department of Physics, Tampere University of Technology, P.O. Box 692, 33101 Tampere, FinlandWe present the combined power law and log-normal distribution (PL+LN) model, a computationally efficient model to be used in simulations where the particle size distribution cannot be accurately represented by log-normal distributions, such as in simulations involving the initial steps of aerosol formation, where new particle formation and growth occur simultaneously, or in the case of inverse modeling. The model was evaluated against highly accurate sectional models using input parameter values that reflect conditions typical to particle formation occurring in the atmosphere and in vehicle exhaust. The model was tested in the simulation of a particle formation event performed in a mobile aerosol chamber at Mäkelänkatu street canyon measurement site in Helsinki, Finland. The number, surface area, and mass concentrations in the chamber simulation were conserved with the relative errors lower than 2 % using the PL+LN model, whereas a moment-based log-normal model and sectional models with the same computing time as with the PL+LN model caused relative errors up to 17 and 79 %, respectively.https://www.atmos-chem-phys.net/16/7067/2016/acp-16-7067-2016.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Olin T. Anttila T. Anttila M. Dal Maso |
spellingShingle |
M. Olin T. Anttila T. Anttila M. Dal Maso Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber Atmospheric Chemistry and Physics |
author_facet |
M. Olin T. Anttila T. Anttila M. Dal Maso |
author_sort |
M. Olin |
title |
Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
title_short |
Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
title_full |
Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
title_fullStr |
Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
title_full_unstemmed |
Using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
title_sort |
using a combined power law and log-normal distribution model to simulate particle formation and growth in a mobile aerosol chamber |
publisher |
Copernicus Publications |
series |
Atmospheric Chemistry and Physics |
issn |
1680-7316 1680-7324 |
publishDate |
2016-06-01 |
description |
We present the combined power law and log-normal distribution
(PL+LN) model, a computationally efficient model to be used in simulations
where the particle size distribution cannot be accurately represented by
log-normal distributions, such as in simulations involving the initial steps
of aerosol formation, where new particle formation and growth occur
simultaneously, or in the case of inverse modeling. The model was evaluated
against highly accurate sectional models using input parameter values that
reflect conditions typical to particle formation occurring in the atmosphere
and in vehicle exhaust. The model was tested in the simulation of a particle formation
event performed in a mobile aerosol chamber at Mäkelänkatu street canyon
measurement site in Helsinki, Finland. The number, surface area, and mass
concentrations in the chamber simulation were conserved with the relative
errors lower than 2 % using the PL+LN model, whereas a
moment-based log-normal model and sectional models with the same computing
time as with the PL+LN model caused relative errors up to 17 and
79 %, respectively. |
url |
https://www.atmos-chem-phys.net/16/7067/2016/acp-16-7067-2016.pdf |
work_keys_str_mv |
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