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Influence of the sampling site, the season of the year, the particle size and the number of nucleation events on the chemical composition of atmospheric ultrafine and total suspended particles
Abstract Twenty one organic compounds including three monocarboxylic and ten dicarboxylic acids, four aldehydes, three polyols and one amine were determined in 61 atmospheric aerosol particle samples with different sizes (30 ± 4-nm, 40 ± 5-nm, 50 ± 5-nm and total suspended particles) collected at two sampling sites, the SMEAR II and SMEAR III stations during different seasons of the year. Non supervised pattern recognition techniques, such as hierarchical cluster analysis and principal component analysis were used to study the influence of the collection place, the season of the year and the particle size on the concentration and behavior of the target compounds. The reliability of these results was proved using a supervised pattern recognition technique such as soft independent modeling of class analogy. The results achieved demonstrate that the chemical composition of the atmospheric aerosol particles is affected by the potential emission sources and the reactivity of the studied compounds under certain atmospheric conditions. In addition, from quantitative analysis methodologies partial least squares regression and principal component regression models were successfully used to clarify the influence of the number of nucleation events on the chemical composition of the particles.
Highlights ► 61 aerosol particle samples (30 nm, 40 nm, 50 nm, TSP) were studied. ► Twenty one compounds studied are important in atmospheric aerosol chemistry. ► Chemical composition in ultrafine and TSP samples differ in place and in time. ► Correlations were found between analyte profiles and nucleation event number. ► Statistical models used as data analysis tools successfully completed the study.
Influence of the sampling site, the season of the year, the particle size and the number of nucleation events on the chemical composition of atmospheric ultrafine and total suspended particles
Abstract Twenty one organic compounds including three monocarboxylic and ten dicarboxylic acids, four aldehydes, three polyols and one amine were determined in 61 atmospheric aerosol particle samples with different sizes (30 ± 4-nm, 40 ± 5-nm, 50 ± 5-nm and total suspended particles) collected at two sampling sites, the SMEAR II and SMEAR III stations during different seasons of the year. Non supervised pattern recognition techniques, such as hierarchical cluster analysis and principal component analysis were used to study the influence of the collection place, the season of the year and the particle size on the concentration and behavior of the target compounds. The reliability of these results was proved using a supervised pattern recognition technique such as soft independent modeling of class analogy. The results achieved demonstrate that the chemical composition of the atmospheric aerosol particles is affected by the potential emission sources and the reactivity of the studied compounds under certain atmospheric conditions. In addition, from quantitative analysis methodologies partial least squares regression and principal component regression models were successfully used to clarify the influence of the number of nucleation events on the chemical composition of the particles.
Highlights ► 61 aerosol particle samples (30 nm, 40 nm, 50 nm, TSP) were studied. ► Twenty one compounds studied are important in atmospheric aerosol chemistry. ► Chemical composition in ultrafine and TSP samples differ in place and in time. ► Correlations were found between analyte profiles and nucleation event number. ► Statistical models used as data analysis tools successfully completed the study.
Influence of the sampling site, the season of the year, the particle size and the number of nucleation events on the chemical composition of atmospheric ultrafine and total suspended particles
Ruiz-Jimenez, Jose (author) / Parshintsev, Jevgeni (author) / Laitinen, Totti (author) / Hartonen, Kari (author) / Petäjä, Tuukka (author) / Kulmala, Markku (author) / Riekkola, Marja-Liisa (author)
Atmospheric Environment ; 49 ; 60-68
2011-12-12
9 pages
Article (Journal)
Electronic Resource
English
Aerosol ultrafine particles , Biogenic organic compounds , Anthropogenic organic compounds , SMEAR II station , SMEAR III station , Statistical analysis , Nucleation event , BSTFA , N,O-bis-(trimethylsilyl)-trifluoroacetamide , DEA , Diethylamine , DMA , Differential mobility analyzer , HCA , Hierarchical cluster analysis , PAH , Polycyclic aromatic hydrocarbons , PCA , Principal component analysis , PCR , Principal component regression , PEEK , Polyether ether ketone , PLSR , Partial least squares regression , PM , Particulate matter , TMCS , Trimethylchlorosilane , TSP , Total suspended particles , SIM , Selected ion monitoring , SIMCA , Soft independent modeling of class analogy , SMEAR , Station for measuring forest ecosystem atmosphere relations
| British Library Conference Proceedings | 1992