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Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions
To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol p...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4830933/ https://www.ncbi.nlm.nih.gov/pubmed/27075947 http://dx.doi.org/10.1038/srep24497 |
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author | Che, H. C. Zhang, X. Y. Wang, Y. Q. Zhang, L. Shen, X. J. Zhang, Y. M. Ma, Q. L. Sun, J. Y. Zhang, Y. W. Wang, T. T. |
author_facet | Che, H. C. Zhang, X. Y. Wang, Y. Q. Zhang, L. Shen, X. J. Zhang, Y. M. Ma, Q. L. Sun, J. Y. Zhang, Y. W. Wang, T. T. |
author_sort | Che, H. C. |
collection | PubMed |
description | To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol particles was the highest in clean weather, with the highest active fraction of all the weather types. For pollution with the same visibility, the residual aerosol particles in higher relative humidity weather conditions were more externally mixed and heterogeneous, with a lower hygroscopic capacity. The hygroscopic capacity (κ) of organic aerosols can be classified into 0.1 and 0.2 in different weather types. The particles at ~150 nm were easily activated in haze weather conditions. For CCN predictions, the bulk chemical composition method was closer to observations at low supersaturations (≤0.1%), whereas when the supersaturation was ≥0.2%, the size-resolved chemical composition method was more accurate. As for the mixing state of the aerosol particles, in haze, heavy haze, and severe haze weather conditions CCN predictions based on the internal mixing assumption were robust, whereas for other weather conditions, predictions based on the external mixing assumption were more accurate. |
format | Online Article Text |
id | pubmed-4830933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48309332016-04-19 Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions Che, H. C. Zhang, X. Y. Wang, Y. Q. Zhang, L. Shen, X. J. Zhang, Y. M. Ma, Q. L. Sun, J. Y. Zhang, Y. W. Wang, T. T. Sci Rep Article To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol particles was the highest in clean weather, with the highest active fraction of all the weather types. For pollution with the same visibility, the residual aerosol particles in higher relative humidity weather conditions were more externally mixed and heterogeneous, with a lower hygroscopic capacity. The hygroscopic capacity (κ) of organic aerosols can be classified into 0.1 and 0.2 in different weather types. The particles at ~150 nm were easily activated in haze weather conditions. For CCN predictions, the bulk chemical composition method was closer to observations at low supersaturations (≤0.1%), whereas when the supersaturation was ≥0.2%, the size-resolved chemical composition method was more accurate. As for the mixing state of the aerosol particles, in haze, heavy haze, and severe haze weather conditions CCN predictions based on the internal mixing assumption were robust, whereas for other weather conditions, predictions based on the external mixing assumption were more accurate. Nature Publishing Group 2016-04-14 /pmc/articles/PMC4830933/ /pubmed/27075947 http://dx.doi.org/10.1038/srep24497 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Che, H. C. Zhang, X. Y. Wang, Y. Q. Zhang, L. Shen, X. J. Zhang, Y. M. Ma, Q. L. Sun, J. Y. Zhang, Y. W. Wang, T. T. Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title | Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title_full | Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title_fullStr | Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title_full_unstemmed | Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title_short | Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
title_sort | characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4830933/ https://www.ncbi.nlm.nih.gov/pubmed/27075947 http://dx.doi.org/10.1038/srep24497 |
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