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Sensitivity of spatial aerosol particle distributions to the boundary conditions in the PALM model system 6.0

Kurppa, Mona ; Roldin, Pontus LU ; Strömberg, Jani ; Balling, Anna ; Karttunen, Sasu ; Kuuluvainen, Heino ; Niemi, Jarkko V. ; Pirjola, Liisa ; Rönkkö, Topi and Timonen, Hilkka , et al. (2020) In Geoscientific Model Development 13(11). p.5663-5685
Abstract

High-resolution modelling is needed to understand urban air quality and pollutant dispersion in detail. Recently, the PALM model system 6.0, which is based on large-eddy simulation (LES), was extended with the detailed Sectional Aerosol module for Large Scale Applications (SALSA) v2.0 to enable studying the complex interactions between the turbulent flow field and aerosol dynamic processes. This study represents an extensive evaluation of the modelling system against the horizontal and vertical distributions of aerosol particles measured using a mobile laboratory and a drone in an urban neighbourhood in Helsinki, Finland. Specific emphasis is on the model sensitivity of aerosol particle concentrations, size distributions and chemical... (More)

High-resolution modelling is needed to understand urban air quality and pollutant dispersion in detail. Recently, the PALM model system 6.0, which is based on large-eddy simulation (LES), was extended with the detailed Sectional Aerosol module for Large Scale Applications (SALSA) v2.0 to enable studying the complex interactions between the turbulent flow field and aerosol dynamic processes. This study represents an extensive evaluation of the modelling system against the horizontal and vertical distributions of aerosol particles measured using a mobile laboratory and a drone in an urban neighbourhood in Helsinki, Finland. Specific emphasis is on the model sensitivity of aerosol particle concentrations, size distributions and chemical compositions to boundary conditions of meteorological variables and aerosol background concentrations. The meteorological boundary conditions are taken from both a numerical weather prediction model and observations, which occasionally differ strongly. Yet, the model shows good agreement with measurements (fractional bias < 0.67, normalised mean squared error < 6, fraction of the data within a factor of 2 > 0.3, normalised mean bias factor < 0.25 and normalised mean absolute error factor < 0.35) with respect to both horizontal and vertical distribution of aerosol particles, their size distribution and chemical composition. The horizontal distribution is most sensitive to the wind speed and atmospheric stratification, and vertical distribution to the wind direction. The aerosol number size distribution is mainly governed by the flow field along the main street with high traffic rates and in its surroundings by the background concentrations. The results emphasise the importance of correct meteorological and aerosol background boundary conditions, in addition to accurate emission estimates and detailed model physics, in quantitative high-resolution air pollution modelling and future urban LES studies.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Geoscientific Model Development
volume
13
issue
11
pages
23 pages
publisher
Copernicus GmbH
external identifiers
  • scopus:85096475916
ISSN
1991-959X
DOI
10.5194/gmd-13-5663-2020
language
English
LU publication?
yes
id
2cf4d61d-e3cf-4fa6-a734-4f84202f2712
date added to LUP
2020-11-30 13:39:21
date last changed
2025-04-04 14:30:17
@article{2cf4d61d-e3cf-4fa6-a734-4f84202f2712,
  abstract     = {{<p>High-resolution modelling is needed to understand urban air quality and pollutant dispersion in detail. Recently, the PALM model system 6.0, which is based on large-eddy simulation (LES), was extended with the detailed Sectional Aerosol module for Large Scale Applications (SALSA) v2.0 to enable studying the complex interactions between the turbulent flow field and aerosol dynamic processes. This study represents an extensive evaluation of the modelling system against the horizontal and vertical distributions of aerosol particles measured using a mobile laboratory and a drone in an urban neighbourhood in Helsinki, Finland. Specific emphasis is on the model sensitivity of aerosol particle concentrations, size distributions and chemical compositions to boundary conditions of meteorological variables and aerosol background concentrations. The meteorological boundary conditions are taken from both a numerical weather prediction model and observations, which occasionally differ strongly. Yet, the model shows good agreement with measurements (fractional bias &lt; 0.67, normalised mean squared error &lt; 6, fraction of the data within a factor of 2 &gt; 0.3, normalised mean bias factor &lt; 0.25 and normalised mean absolute error factor &lt; 0.35) with respect to both horizontal and vertical distribution of aerosol particles, their size distribution and chemical composition. The horizontal distribution is most sensitive to the wind speed and atmospheric stratification, and vertical distribution to the wind direction. The aerosol number size distribution is mainly governed by the flow field along the main street with high traffic rates and in its surroundings by the background concentrations. The results emphasise the importance of correct meteorological and aerosol background boundary conditions, in addition to accurate emission estimates and detailed model physics, in quantitative high-resolution air pollution modelling and future urban LES studies.</p>}},
  author       = {{Kurppa, Mona and Roldin, Pontus and Strömberg, Jani and Balling, Anna and Karttunen, Sasu and Kuuluvainen, Heino and Niemi, Jarkko V. and Pirjola, Liisa and Rönkkö, Topi and Timonen, Hilkka and Hellsten, Antti and Järvi, Leena}},
  issn         = {{1991-959X}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{5663--5685}},
  publisher    = {{Copernicus GmbH}},
  series       = {{Geoscientific Model Development}},
  title        = {{Sensitivity of spatial aerosol particle distributions to the boundary conditions in the PALM model system 6.0}},
  url          = {{http://dx.doi.org/10.5194/gmd-13-5663-2020}},
  doi          = {{10.5194/gmd-13-5663-2020}},
  volume       = {{13}},
  year         = {{2020}},
}