Articles | Volume 17, issue 4
https://doi.org/10.5194/acp-17-3165-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/acp-17-3165-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Mar 2017
Research article |
| 01 Mar 2017
Resolving anthropogenic aerosol pollution types – deconvolution and exploratory classification of pollution events
Mikko Äijälä
Department of Physics, University of Helsinki, Helsinki, Finland
Liine Heikkinen
Department of Physics, University of Helsinki, Helsinki, Finland
Roman Fröhlich
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen,
Switzerland
Francesco Canonaco
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen,
Switzerland
André S. H. Prévôt
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen,
Switzerland
Heikki Junninen
Department of Physics, University of Helsinki, Helsinki, Finland
Tuukka Petäjä
Department of Physics, University of Helsinki, Helsinki, Finland
Markku Kulmala
Department of Physics, University of Helsinki, Helsinki, Finland
Douglas Worsnop
Department of Physics, University of Helsinki, Helsinki, Finland
Aerodyne Research Inc., Billerica, MA, USA
Department of Physics, University of Helsinki, Helsinki, Finland
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24 citations as recorded by crossref.
- Tropical and Boreal Forest – Atmosphere Interactions: A Review P. Artaxo et al. 10.16993/tellusb.34
- Comparison of dimension reduction techniques in the analysis of mass spectrometry data S. Isokääntä et al. 10.5194/amt-13-2995-2020
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- 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 M. Äijälä et al. 10.5194/acp-19-3645-2019
- Measurement report: Molecular composition and volatility of gaseous organic compounds in a boreal forest – from volatile organic compounds to highly oxygenated organic molecules W. Huang et al. 10.5194/acp-21-8961-2021
- Primary and secondary organic aerosol from heated cooking oil emissions T. Liu et al. 10.5194/acp-18-11363-2018
- Evaluation of the Sources, Precursors, and Processing of Aerosols at a High-Altitude Tropical Site P. Dominutti et al. 10.1021/acsearthspacechem.2c00149
- Real-world observations of reduced nitrogen and ultrafine particles in commercial cooking organic aerosol emissions S. Kim et al. 10.5194/acp-24-1281-2024
- Atmospheric Aerosols: Clouds, Chemistry, and Climate V. McNeill 10.1146/annurev-chembioeng-060816-101538
- Primary emissions and secondary production of organic aerosols from heated animal fats L. Zhou et al. 10.1016/j.scitotenv.2021.148638
- Augmenting Heritage Ocean-Color Aerosol Models for Enhanced Remote Sensing of Inland and Nearshore Coastal Waters M. Montes et al. 10.3389/frsen.2022.860816
- Seasonal analysis of submicron aerosol in Old Delhi using high-resolution aerosol mass spectrometry: chemical characterisation, source apportionment and new marker identification J. Cash et al. 10.5194/acp-21-10133-2021
- Application of fuzzy c-means clustering for analysis of chemical ionization mass spectra: insights into the gas phase chemistry of NO3-initiated oxidation of isoprene R. Wu et al. 10.5194/amt-17-1811-2024
- Characterization of atmospheric aerosol (PM10 and PM2.5) from a medium sized city in São Paulo state, Brazil B. Franzin et al. 10.1016/j.jes.2019.09.014
- Quantification of solid fuel combustion and aqueous chemistry contributions to secondary organic aerosol during wintertime haze events in Beijing Y. Tong et al. 10.5194/acp-21-9859-2021
- Detecting and Characterizing Particulate Organic Nitrates with an Aerodyne Long-ToF Aerosol Mass Spectrometer F. Graeffe et al. 10.1021/acsearthspacechem.2c00314
- Assessing volatile organic compound sources in a boreal forest using positive matrix factorization (PMF) M. Vestenius et al. 10.1016/j.atmosenv.2021.118503
- 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
- Investigating the Sources of Urban Air Pollution Using Low-Cost Air Quality Sensors at an Urban Atlanta Site L. Yang et al. 10.1021/acs.est.1c07005
- Sources and processes that control the submicron organic aerosol composition in an urban Mediterranean environment (Athens): a high temporal-resolution chemical composition measurement study I. Stavroulas et al. 10.5194/acp-19-901-2019
- Real-Time Source Apportionment of Organic Aerosols in Three European Cities G. Chen et al. 10.1021/acs.est.2c02509
- 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
- Cruise observation of the marine atmosphere and ship emissions in South China Sea: Aerosol composition, sources, and the aging process Q. Sun et al. 10.1016/j.envpol.2022.120539
- Cloud response to co-condensation of water and organic vapors over the boreal forest L. Heikkinen et al. 10.5194/acp-24-5117-2024
1 citations as recorded by crossref.
Latest update: 14 Dec 2024
Short summary
Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesising this “raw” data into chemical information necessitates the use of advanced, statistics-based data analysis techniques. Here we present an example of combining data dimensionality reduction (factorisation) with exploratory classification (clustering) and show that the results complement and broaden our current perspectives on aerosol chemical classification.
Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of...
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