Data/hora: 08/06/2024 00:59:23

Biblioteca(s): 	Embrapa Amazônia Oriental.	
Data corrente: 	06/03/2017	
Data da última atualização: 	19/05/2022	
Autoria: 	PÖHLKER, M. L.; PÖHLKER, C.; DITAS, F.; KLIMACH, T.; ANGELIS, I. H. de; ARAUJO, A. C. de; BRITO, J.; CARBONE, S.; CHENG, Y.; CHI, X.; DITZ, R.; GUNTHE, S. S.; KESSELMEIER, J.; KÖNEMANN, T.; LAVRIC, J. V.; MARTIN, S. T.; MIKHAILOV, E.; MORAN-ZULOAGA, D.; ROSE, D.; SATURNO, J.; SU, H.; THALMAN, R.; WALTER, D.; WANG, J.; WOLFF, S.; BARBOSA, H. M. J.; ARTAXO, P.; ANDREAE, M. O.; PÖSCHL, U.	
Afiliação: 	Mira L. Pöhlker, Max Planck Institute for Chemistry; Christopher Pöhlker, Max Planck Institute for Chemistry; Florian Ditas, Max Planck Institute for Chemistry; Thomas Klimach, Max Planck Institute for Chemistry; Isabella Hrabe de Angelis, Max Planck Institute for Chemistry; ALESSANDRO CARIOCA DE ARAUJO, CPATU; Joel Brito, USP / University Blaise Pascal; Samara Carbone, USP / Federal University of Uberlândia; Yafang Cheng, Max Planck Institute for Chemistry; Xuguang Chi, Max Planck Institute for Chemistry / Nanjing University; Reiner Ditz, Max Planck Institute for Chemistry; Sachin S. Gunthe, Indian Institute of Technology Madras; Jürgen Kesselmeier, Max Planck Institute for Chemistry; Tobias Könemann, Max Planck Institute for Chemistry; Jost V. Lavric, Max Planck Institute for Biogeochemistry; Scot T. Martin, Harvard University; Eugene Mikhailov, St. Petersburg State University; Daniel Moran-Zuloaga, Max Planck Institute for Chemistry; Diana Rose, Goethe University Frankfurt am Main; Jorge Saturno, Max Planck Institute for Chemistry; Hang Su, Max Planck Institute for Chemistry; Ryan Thalman, Brookhaven National Laboratory / Snow College; David Walter, Max Planck Institute for Chemistry; Jian Wang, Brookhaven National Laboratory; Stefan Wolff, Max Planck Institute for Chemistry / INPA; Henrique M. J. Barbosa, USP; Paulo Artaxo, USP; Meinrat O. Andreae, Max Planck Institute for Chemistry / University of California; Ulrich Pöschl, Max Planck Institute for Chemistry.	
Título: 	Long-term observations of cloud condensation nuclei in the Amazon rain forest - Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction.	
Ano de publicação: 	2016	
Fonte/Imprenta: 	Atmospheric Chemistry and Physics, v. 16, n. 24, p. 15709-15740, Dec. 2016.	
Idioma: 	Inglês	
Notas: 	Na publicação: Araújo, A.	
Conteúdo: 	Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014?February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site. The CCN measurements were continuously cycled through 10 levels of supersaturation (S&#8239;&#8201;=&#8201;&#8239;0.11 to 1.10&#8239;%) and span the aerosol particle size range from 20 to . The mean critical diameters of CCN activation range from at The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode , higher values for the accumulation mode , and an overall mean value of, consistent with high fractions of organic aerosol. The hygroscopicity parameter, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes. For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.	
Palavras-Chave: 	Condensação de nuvem.	
Thesagro: 	Floresta Tropical.	
Thesaurus Nal: 	Amazonia.	
Categoria do assunto: 	P Recursos Naturais, Ciências Ambientais e da Terra	
Registro original: 	Embrapa Amazônia Oriental (CPATU)	
Exemplares: 	CPATU - (53483-1) - UPC - AP - DD -  -  -  - DIS