Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
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
_version_ 1782426975388827648
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
work_keys_str_mv AT chehc characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT zhangxy characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT wangyq characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT zhangl characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT shenxj characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT zhangym characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT maql characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT sunjy characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT zhangyw characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions
AT wangtt characterizationandparameterizationofaerosolcloudcondensationnucleiactivationunderdifferentpollutionconditions