Brookhaven Natl Lab, Biol Environm & Climate Sci Dept, Upton, NY 11973 - USA
 Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92037 - USA
Número total de Afiliações: 21
Tipo de documento:
Atmospheric Chemistry and Physics;
JUL 19 2018.
Citações Web of Science:
Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014-February 2015). In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1; Pohlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions: Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with D-Ait approximate to 70 nm and N-Ait approximate to 160 cm(-3), weak accumulation mode with D-acc approximate to 160 nm and N-acc approximate to 90 cm(-3)), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (kappa(Ait) approximate to 0.12, kappa(acc) approximate to 0.18). Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode (D-Ait approximate to 80 nm, N-Ait approximate to 120 cm(-3) vs. D-acc approximate to 180 nm, N-acc approximate to 310 cm(-3)), an increased abundance of dust and salt, and relatively high hygroscopicity (kappa(Ait) approximate to 0.18, kappa(acc) approximate to 0.35). The coarse mode is also significantly enhanced during these events. Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (D-Ait approximate to 70 nm, N-Ait approximate to 140 cm(-3) vs. D-acc approximate to 170 nm, N-acc approximate to 3400 cm(-3)), very high organic mass fractions (similar to 90 %), and correspondingly low hygroscopicity (kappa(Ait) approximate to 0.14, kappa(acc) approximate to 0.17). Mixed-pollution (MPOL) conditions with a super-position of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D approximate to 130 nm, N-CN,(10) approximate to 1300 cm(-3)), with high sulfate mass fractions (similar to 20 %) from volcanic sources and correspondingly high hygroscopicity (kappa (<) (100 nm) approximate to 0.14, kappa (>) (100 nm) approximate to 0.22), which were periodically mixed with fresh smoke from nearby fires (D approximate to 110 nm, NCN; 10 approximate to 2800 cm(-3)) with an organic-dominated composition and sharply decreased hygroscopicity (kappa (<) (150 nm) approximate to 0.10, kappa (>) (150 nm) approximate to 0.20). Insights into the aerosol mixing state are provided by particle hygroscopicity (kappa) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow kappa distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad kappa distributions). The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activation and droplet formation in convective clouds are mostly aerosol-limited under PR and LRT conditions and updraft-limited under BB and MPOL conditions. Normalized CCN efficiency spectra (CCN divided by aerosol number concentration plotted against water vapor supersaturation) and corresponding parameterizations (Gaussian error function fits) provide a basis for further analysis and model studies of aerosol-cloud interactions in the Amazon. (AU)