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Consistency and applicability of parameterization schemes for the size-resolved aerosol activation ratio based on field measurements in the North China Plain.
- Source :
-
Atmospheric Environment . Jan2018, Vol. 173, p316-324. 9p. - Publication Year :
- 2018
-
Abstract
- Parameterization of the size-resolved particle activation ratio (AR) is useful for the prediction and analysis of the cloud condensation nuclei (CCN) number concentration ( N CCN ). Critical issues for the application of AR parameterizations in models are (1) the consistency of the different parameterization schemes in terms of fitting AR curves and (2) the applicability of the estimate of N CCN under different aerosol conditions. These issues are discussed in this study based on summertime measurements of the size-resolved AR in the North China Plain. By comparing parameterized AR curves, variations in the fitting parameters and application to N CCN calculations, the consistency of the three existing parameterization schemes is confirmed. Based on an analysis using representative AR fitting parameters, the method commonly used to calculate N CCN with a fixed AR was found to be accurate, except during periods affected by strong black carbon (BC) emissions or new particle formation (NPF) events. The N CCN value was overestimated by approximately 10% when BC aerosol emissions were abundant and deviated from the 1:1 line by 15% during NPF events. The bias of the calculated N CCN due to these significant emission or aerosol production events cannot be eliminated by using the appropriate representative fitting parameters. Under these circumstances, accurate prediction of N CCN requires real-time aerosol hygroscopicity data based on CCN measurements. This research furthers our understanding of the relationship between aerosol cloud activation and aerosol spectra. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13522310
- Volume :
- 173
- Database :
- Academic Search Index
- Journal :
- Atmospheric Environment
- Publication Type :
- Academic Journal
- Accession number :
- 126669306
- Full Text :
- https://doi.org/10.1016/j.atmosenv.2017.11.021