Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing
Understanding the impacts of aerosol chemical composition and mixing state on cloud condensation nuclei (CCN) activity in polluted areas is crucial for accurately predicting CCN number concentrations (<i>N</i><sub>CCN</sub>). In this study, we predict <i>N</i>&...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-05-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/18/6907/2018/acp-18-6907-2018.pdf |
| _version_ | 1818113115046281216 |
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| author | J. Ren F. Zhang F. Zhang Y. Wang D. Collins X. Fan X. Jin W. Xu W. Xu Y. Sun Y. Sun M. Cribb Z. Li Z. Li |
| author_facet | J. Ren F. Zhang F. Zhang Y. Wang D. Collins X. Fan X. Jin W. Xu W. Xu Y. Sun Y. Sun M. Cribb Z. Li Z. Li |
| author_sort | J. Ren |
| collection | DOAJ |
| description | Understanding the impacts of aerosol chemical composition and mixing state on
cloud condensation nuclei (CCN) activity in polluted areas is crucial for
accurately predicting CCN number concentrations (<i>N</i><sub>CCN</sub>). In
this study, we predict <i>N</i><sub>CCN</sub> under five assumed schemes of aerosol
chemical composition and mixing state based on field measurements in Beijing
during the winter of 2016. Our results show that the best closure is achieved
with the assumption of size dependent chemical composition for which
sulfate, nitrate, secondary organic aerosols, and aged black carbon are
internally mixed with each other but externally mixed with primary organic
aerosol and fresh black carbon (external–internal size-resolved, abbreviated
as EI–SR scheme). The resulting ratios of predicted-to-measured
<i>N</i><sub>CCN</sub> (<i>R</i><sub>CCN_p∕m</sub>) were 0.90 – 0.98 under both clean and
polluted conditions. Assumption of an internal mixture and bulk chemical
composition (INT–BK scheme) shows good closure with <i>R</i><sub>CCN_p∕m</sub>
of 1.0 –1.16 under clean conditions, implying that it is adequate for CCN
prediction in continental clean regions. On polluted days, assuming the
aerosol is internally mixed and has a chemical composition that is size
dependent (INT–SR scheme) achieves better closure than the INT–BK scheme due
to the heterogeneity and variation in particle composition at different
sizes. The improved closure achieved using the EI–SR and INT–SR assumptions
highlight the importance of measuring size-resolved chemical composition for
CCN predictions in polluted regions. <i>N</i><sub>CCN</sub> is significantly
underestimated (with <i>R</i><sub>CCN_p∕m</sub> of 0.66 – 0.75) when using the
schemes of external mixtures with bulk (EXT–BK scheme) or size-resolved
composition (EXT–SR scheme), implying that primary particles experience rapid
aging and physical mixing processes in urban Beijing. However, our results
show that the aerosol mixing state plays a minor role in CCN prediction when
the <i>κ</i><sub>org</sub> exceeds 0.1. |
| first_indexed | 2024-12-11T03:29:42Z |
| format | Article |
| id | doaj.art-d37035fe07f54fcca79236681129bdb3 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-11T03:29:42Z |
| publishDate | 2018-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-d37035fe07f54fcca79236681129bdb32022-12-22T01:22:26ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-05-01186907692110.5194/acp-18-6907-2018Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban BeijingJ. Ren0F. Zhang1F. Zhang2Y. Wang3D. Collins4X. Fan5X. Jin6W. Xu7W. Xu8Y. Sun9Y. Sun10M. Cribb11Z. Li12Z. Li13College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaJoint Center for Global Change Studies (JCGCS), Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaDepartment of Atmospheric Sciences, Texas A & M University, College Station, TX, USACollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaState Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaEarth System Science Interdisciplinary Center and Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USACollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, ChinaEarth System Science Interdisciplinary Center and Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USAUnderstanding the impacts of aerosol chemical composition and mixing state on cloud condensation nuclei (CCN) activity in polluted areas is crucial for accurately predicting CCN number concentrations (<i>N</i><sub>CCN</sub>). In this study, we predict <i>N</i><sub>CCN</sub> under five assumed schemes of aerosol chemical composition and mixing state based on field measurements in Beijing during the winter of 2016. Our results show that the best closure is achieved with the assumption of size dependent chemical composition for which sulfate, nitrate, secondary organic aerosols, and aged black carbon are internally mixed with each other but externally mixed with primary organic aerosol and fresh black carbon (external–internal size-resolved, abbreviated as EI–SR scheme). The resulting ratios of predicted-to-measured <i>N</i><sub>CCN</sub> (<i>R</i><sub>CCN_p∕m</sub>) were 0.90 – 0.98 under both clean and polluted conditions. Assumption of an internal mixture and bulk chemical composition (INT–BK scheme) shows good closure with <i>R</i><sub>CCN_p∕m</sub> of 1.0 –1.16 under clean conditions, implying that it is adequate for CCN prediction in continental clean regions. On polluted days, assuming the aerosol is internally mixed and has a chemical composition that is size dependent (INT–SR scheme) achieves better closure than the INT–BK scheme due to the heterogeneity and variation in particle composition at different sizes. The improved closure achieved using the EI–SR and INT–SR assumptions highlight the importance of measuring size-resolved chemical composition for CCN predictions in polluted regions. <i>N</i><sub>CCN</sub> is significantly underestimated (with <i>R</i><sub>CCN_p∕m</sub> of 0.66 – 0.75) when using the schemes of external mixtures with bulk (EXT–BK scheme) or size-resolved composition (EXT–SR scheme), implying that primary particles experience rapid aging and physical mixing processes in urban Beijing. However, our results show that the aerosol mixing state plays a minor role in CCN prediction when the <i>κ</i><sub>org</sub> exceeds 0.1.https://www.atmos-chem-phys.net/18/6907/2018/acp-18-6907-2018.pdf |
| spellingShingle | J. Ren F. Zhang F. Zhang Y. Wang D. Collins X. Fan X. Jin W. Xu W. Xu Y. Sun Y. Sun M. Cribb Z. Li Z. Li Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing Atmospheric Chemistry and Physics |
| title | Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing |
| title_full | Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing |
| title_fullStr | Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing |
| title_full_unstemmed | Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing |
| title_short | Using different assumptions of aerosol mixing state and chemical composition to predict CCN concentrations based on field measurements in urban Beijing |
| title_sort | using different assumptions of aerosol mixing state and chemical composition to predict ccn concentrations based on field measurements in urban beijing |
| url | https://www.atmos-chem-phys.net/18/6907/2018/acp-18-6907-2018.pdf |
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