Articles | Volume 19, issue 6
https://doi.org/10.5194/acp-19-3645-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-3645-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Mar 2019
Research article |
| 21 Mar 2019
| 21 Mar 2019
Constructing a data-driven receptor model for organic and inorganic aerosol – a synthesis analysis of eight mass spectrometric data sets from a boreal forest site
Mikko Äijälä
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
Kaspar R. Daellenbach
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
Francesco Canonaco
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
Liine Heikkinen
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
Heikki Junninen
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
Laboratory of Environmental Physics, University of Tartu, Tartu, Estonia
Tuukka Petäjä
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
Markku Kulmala
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
André S. H. Prévôt
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland
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Cited
14 citations as recorded by crossref.
- Detecting and Characterizing Particulate Organic Nitrates with an Aerodyne Long-ToF Aerosol Mass Spectrometer F. Graeffe et al. 10.1021/acsearthspacechem.2c00314
- Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens O. Zografou et al. 10.5194/amt-15-4675-2022
- Long-term sub-micrometer aerosol chemical composition in the boreal forest: inter- and intra-annual variability L. Heikkinen et al. 10.5194/acp-20-3151-2020
- Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach L. Heikkinen et al. 10.5194/acp-21-10081-2021
- Key drivers of cloud response to surface-active organics S. Lowe et al. 10.1038/s41467-019-12982-0
- Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique J. Camman et al. 10.5194/acp-24-3257-2024
- Determination of PM1 Sources at a Prague Background Site during the 2012–2013 Period Using PMF Analysis of Combined Aerosol Mass Spectra O. Makeš et al. 10.3390/atmos13010020
- Tropical and Boreal Forest – Atmosphere Interactions: A Review P. Artaxo et al. 10.16993/tellusb.34
- Influence of biogenic emissions from boreal forests on aerosol–cloud interactions T. Petäjä et al. 10.1038/s41561-021-00876-0
- Data‐Driven Compound Identification in Atmospheric Mass Spectrometry H. Sandström et al. 10.1002/advs.202306235
- Enhanced Aerosol Source Identification by Utilizing High Molecular Weight Signals in Aerosol Mass Spectra Y. Zhang et al. 10.1021/acsestair.3c00102
- Aerosol optical properties and brown carbon in Mexico City A. Retama et al. 10.1039/D2EA00006G
- Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments G. Sengupta & N. Prisle 10.1080/02786826.2024.2323641
- Impact of acidity and surface-modulated acid dissociation on cloud response to organic aerosol G. Sengupta et al. 10.5194/acp-24-1467-2024
14 citations as recorded by crossref.
- Detecting and Characterizing Particulate Organic Nitrates with an Aerodyne Long-ToF Aerosol Mass Spectrometer F. Graeffe et al. 10.1021/acsearthspacechem.2c00314
- Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens O. Zografou et al. 10.5194/amt-15-4675-2022
- Long-term sub-micrometer aerosol chemical composition in the boreal forest: inter- and intra-annual variability L. Heikkinen et al. 10.5194/acp-20-3151-2020
- Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach L. Heikkinen et al. 10.5194/acp-21-10081-2021
- Key drivers of cloud response to surface-active organics S. Lowe et al. 10.1038/s41467-019-12982-0
- Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique J. Camman et al. 10.5194/acp-24-3257-2024
- Determination of PM1 Sources at a Prague Background Site during the 2012–2013 Period Using PMF Analysis of Combined Aerosol Mass Spectra O. Makeš et al. 10.3390/atmos13010020
- Tropical and Boreal Forest – Atmosphere Interactions: A Review P. Artaxo et al. 10.16993/tellusb.34
- Influence of biogenic emissions from boreal forests on aerosol–cloud interactions T. Petäjä et al. 10.1038/s41561-021-00876-0
- Data‐Driven Compound Identification in Atmospheric Mass Spectrometry H. Sandström et al. 10.1002/advs.202306235
- Enhanced Aerosol Source Identification by Utilizing High Molecular Weight Signals in Aerosol Mass Spectra Y. Zhang et al. 10.1021/acsestair.3c00102
- Aerosol optical properties and brown carbon in Mexico City A. Retama et al. 10.1039/D2EA00006G
- Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments G. Sengupta & N. Prisle 10.1080/02786826.2024.2323641
- Impact of acidity and surface-modulated acid dissociation on cloud response to organic aerosol G. Sengupta et al. 10.5194/acp-24-1467-2024
Latest update: 23 Nov 2024
Short summary
Aerosol mass spectrometry produces large amounts of complex data, the analysis of which necessitates chemometrics – the application of advanced statistical and mathematical tools to chemical data. Here, we perform a data-driven analysis of multiple aerosol mass spectrometric data sets, to show that the traditional separation of organics and inorganics is not necessary. The resulting 7-component aerosol speciation explains 83 % to 96 % of observed variability at our boreal forest experiment site.
Aerosol mass spectrometry produces large amounts of complex data, the analysis of which...
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