4.7 Article

Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China - Part 1: Size-resolved measurements and implications for the modeling of aerosol particle hygroscopicity and CCN activity

期刊

ATMOSPHERIC CHEMISTRY AND PHYSICS
卷 10, 期 7, 页码 3365-3383

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/acp-10-3365-2010

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资金

  1. China National Basic Research and Development Program [2002CB410801, 2002CB211605]
  2. Max Planck Society (MPG)
  3. Leibniz Institute for Tropospheric Research (IfT)
  4. Peking University (PKU)

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Atmospheric aerosol particles serving as Cloud Condensation Nuclei (CCN) are key elements of the hydrological cycle and climate. We measured and characterized CCN in polluted air and biomass burning smoke during the PRIDE-PRD2006 campaign from 1-30 July 2006 at a rural site similar to 60 km northwest of the mega-city Guangzhou in southeastern China. CCN efficiency spectra (activated fraction vs. dry particle diameter; 20-290 nm) were recorded at water vapor super-saturations (S) in the range of 0.068% to 1.27%. The corresponding effective hygroscopicity parameters describing the influence of particle composition on CCN activity were in the range of kappa approximate to 0.1-0.5. The campaign average value of kappa=0.3 equals the average value of kappa for other continental locations. During a strong local biomass burning event, the average value of kappa dropped to 0.2, which can be considered as characteristic for freshly emitted smoke from the burning of agricultural waste. At low S (<= 0.27%), the maximum activated fraction remained generally well below one, indicating substantial portions of externally mixed CCN-inactive particles with much lower hygroscopicity-most likely soot particles (up to similar to 60% at similar to 250 nm). The mean CCN number concentrations (N-CCN,N- S) ranged from 1000 cm(-3) at S=0.068% to 16 000 cm(-3) at S=1.27%, which is about two orders of magnitude higher than in pristine air. Nevertheless, the ratios between CCN concentration and total aerosol particle concentration (integral CCN efficiencies) were similar to the ratios observed in pristine continental air (similar to 6% to similar to 85% at S=0.068% to 1.27%). Based on the measurement data, we have tested different model approaches for the approximation/prediction of NCCN, S. Depending on S and on the model approach, the relative deviations between observed and predicted NCCN, S ranged from a few percent to several hundred percent. The largest deviations occurred at low S with a simple power law. With a Kohler model using variable kappa values obtained from individual CCN efficiency spectra, the relative deviations were on average less than similar to 10% and hardly exceeded 20%, confirming the applicability of the kappa-Kohler model approach for efficient description of the CCN activity of atmospheric aerosols. Note, however, that different types of kappa-parameters must be distinguished for external mixtures of CCN-active and-inactive aerosol particles (kappa(a), kappa(t), kappa(cut)). Using a constant average hygroscopicity parameter (kappa=0.3) and variable size distributions as measured, the deviations between observed and predicted CCN concentrations were on average less than 20%. In contrast, model calculations using variable hygroscopicity parameters as measured and constant size distributions led to much higher deviations: similar to 70% for the campaign average size distribution, similar to 80% for a generic rural size distribution, and similar to 140% for a generic urban size distribution. These findings confirm earlier studies suggesting that aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the information and parameterizations presented in this study should enable efficient description of the CCN activity of atmospheric aerosols in detailed process models as well as in large-scale atmospheric and cimate models.

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