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Zhang, Hengheng https://orcid.org/0000-0001-5872-5985 [Institut für Meteorologie und Klimaforschung Atmosphärische Aerosolforschung (IMKAAF), Karlsruher Institut für Technologie (KIT)]

Huang, Wei [Huang, Wei]

Shen, Xiaoli [Shen, Xiaoli]

Ramisetty, Ramakrishna [Ramisetty, Ramakrishna]

Song, Junwei https://orcid.org/0000-0001-5573-3154 [Institut für Meteorologie und Klimaforschung Atmosphärische Aerosolforschung (IMKAAF), Karlsruher Institut für Technologie (KIT)]

Kiseleva, Olga [Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)]

Holst, Christopher Claus https://orcid.org/0000-0002-1911-6519 [Holst, Christopher Claus]

Khan, Basit [Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)]

Leisner, Thomas https://orcid.org/0000-0001-9693-7671 [Institut für Meteorologie und Klimaforschung Atmosphärische Aerosolforschung (IMKAAF), Karlsruher Institut für Technologie (KIT)]

Saathoff, Harald https://orcid.org/0000-0002-1301-8010 [Institut für Meteorologie und Klimaforschung Atmosphärische Aerosolforschung (IMKAAF), Karlsruher Institut für Technologie (KIT)]
Contributors:
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Title:
Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter
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Description:
(Abstract) Aerosol distributions are of great relevance for air quality especially for cities like Stuttgart with limited air exchange due to its location in a basin. We collected a comprehensive set of data from remote sensing, in-situ methods including radiosondes for the urban background of downtown Stuttga...

(Technical Remarks) This is data for Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter
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Geological Science
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Dataset
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Huang, Wei

Shen, Xiaoli

Ramisetty, Ramakrishna

Kiseleva, Olga

Holst, Christopher Claus https://orcid.org/0000-0002-1911-6519

Khan, Basit
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kitopen
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Archiving date:
2024-08-09
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30.1 MB
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kitopen
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e4fb23e8c7515023757db8f1c563b0ac (MD5)
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