using different assumptions of aerosol mixing state and chemical composition to predict ccn concentrations based on field measurements in urban beijing
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2018
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Abstract
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 (NCCN). In
this study, we predict NCCN 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
NCCN (RCCN_p∕m) 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 RCCN_p∕m
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. NCCN is significantly
underestimated (with RCCN_p∕m 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 κorg exceeds 0.1.
| Reference Key |
ren2018atmosphericusing
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|---|---|
| Authors | ;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 |
| Journal | Journal of agricultural and food chemistry |
| Year | 2018 |
| DOI |
10.5194/acp-18-6907-2018
|
| URL | |
| Keywords |
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