scholarly journals Observations of the aerosol particle number concentration in the marine boundary layer over the south-eastern Baltic Sea**The research leading to these results has received funding from Lithuanian-Swiss cooperation programme to reduce economic social disparities within the enlarged European Union under project AEROLIT agreement No. CH-3-ŠMM-01/08.

Oceanologia ◽  
2013 ◽  
Vol 55 (3) ◽  
pp. 573-597 ◽  
Author(s):  
Steigvile Byčenkienė ◽  
Vidmantas Ulevicius ◽  
Nina Prokopčiuk ◽  
Dalia Jasinevičienė
Keyword(s):  
Boundary Layer ◽  
European Union ◽  
Baltic Sea ◽  
Aerosol Particle ◽  
Particle Number ◽  
Marine Boundary Layer ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Social Disparities ◽  
Eastern Baltic

scholarly journals New Particle Formation and impact on CCN concentrations in the boundary layer and free troposphere at the high altitude station of Chacaltaya (5240 m a.s.l.), Bolivia

2016 ◽  
Author(s):  
C. Rose ◽  
K. Sellegri ◽  
I. Moreno ◽  
F. Velarde ◽  
M. Ramonet ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Particle Number ◽  
Particle Growth ◽  
Particle Formation ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Free Troposphere ◽  
New Particle Formation ◽  
Radiative Processes ◽  
The Impact

Abstract. Global models predict that new particle formation (NPF) is, in some environments, responsible for a substantial fraction of the total atmospheric particle number concentration and subsequently contribute significantly to cloud condensation nuclei (CCN) concentrations. NPF events were frequently observed at the highest atmospheric observatory in the world, Chacaltaya (5240 m a.s.l.), Bolivia. The present study focuses on the impact of NPF on CCN population. Neutral cluster and Air Ion Spectrometer and mobility particle size spectrometer measurements were simultaneously used to follow the growth of particles from cluster sizes down to ~ 2 nm up to CCN threshold sizes set to 50, 80 and 100 nm. Using measurements performed between January 1 and December 31 2012, we found that 61% of the 94 analysed events showed a clear particle growth and significant enhancement of the CCN-relevant particle number concentration. We evaluated the contribution of NPF events relative to the transport of pre-existing particles to the site. The averaged production of 50 nm particles during those events was 5072 cm−3, and 1481 cm−3 for 100 nm particles, with a larger contribution of NPF compared to transport, especially during the wet season. The data set was further segregated into boundary layer (BL) and free troposphere (FT) conditions at the site. The NPF frequency of occurrence was higher in the BL (48 %) compared to the FT (39 %). Particle condensational growth was more frequently observed for events initiated in the FT, but on average faster for those initiated in the BL, when the amount of condensable species was most probably larger. As a result, the potential to form new CCN was higher for events initiated in the BL (67 % against 56 % in the FT). In contrast, higher CCN number concentration increases were found when the NPF process initially occurred in the FT, under less polluted conditions. This work highlights the competition between particle growth and the removal of freshly nucleated particles by coagulation processes. The results support model predictions which suggest that NPF is an effective source of CCN in some environments, and thus may influence regional climate through cloud related radiative processes.

scholarly journals 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

2008 ◽  
Vol 8 (5) ◽  
pp. 17343-17392 ◽  
Author(s):  
D. Rose ◽  
A. Nowak ◽  
P. Achtert ◽  
A. Wiedensohler ◽  
M. Hu ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Biomass Burning ◽  
Particle Number ◽  
Size Range ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Average Value ◽  
Ccn Activity

Abstract. Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate, but their abundance, properties and sources are highly variable and not well known. We have measured and characterized CCN in polluted air and biomass burning smoke during the PRIDE-PRD2006 campaign on 1–30 July 2006 at a rural site ~60 km northwest of the mega-city Guangzhou in southeastern China. CCN efficiency spectra (activated fraction vs. dry particle diameter; 20–300 nm) were recorded at water vapor supersaturations (S) in the range of 0.07% to 1.27%. Depending on S, the dry CCN activation diameters were in the range of 30–200 nm, corresponding to effective hygroscopicity parameters κ in the range of 0.1–0.5. The hygroscopicity of particles in the accumulation size range was generally higher than that of particles in the nucleation and Aitken size range. The campaign average value of κ for all aerosol particles across the investigated size range was 0.3, which equals the average value of κ for other continental locations. During a strong local biomass burning event, the activation diameters increased by ~10% and the average value of κ 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, which indicates substantial proportions of externally mixed CCN-inactive particles with much lower hygroscopicity – most likely soot particles (up to ~60% at ~250 nm). The mean CCN number concentrations (NCCN,S) ranged from 1100 cm−3 at S=0.07% to 16 000 cm−3 at S=1.27%, representing ~7% to ~85% of the total aerosol particle number concentration. Based on the measurement data, we have tested different model approaches (power laws and κ-Köhler model) for the approximation/prediction of NCCN,S as a function of water vapor supersaturation, aerosol particle number concentration, size distribution and hygroscopicity. Depending on S and on the model approach, the relative deviations between measured and predicted NCCN,S ranged from a few percent to several hundred percent. The largest deviations occurred at low S and with power laws based on particle number concentration. With the κ-Köhler model and a constant hygroscopicity parameter of 0.3, the deviations were on average less than ~20%, which confirms that κ=0.3 may be suitable for approximating the hygroscopicity and CCN activity of continental aerosols in large scale models of the atmosphere and climate. On the other hand, the temporal variations of NCCN,S observed during the biomass burning event and in diurnal cycles could not be captured with constant κ (deviations up to ~80%). With variable κ values obtained from individual CCN efficiency spectra, the relative deviations were on average less than ~10% and hardly exceeded 20%, confirming the applicability of the κ-Köhler model approach for efficient description of the CCN activity of atmospheric aerosols. Note, however, that different types of κ-parameters have to be distinguished for external mixtures of CCN-active and -inactive aerosol particles.

scholarly journals Evaluation of global simulations of aerosol particle number and cloud condensation nuclei, and implications for cloud droplet formation

2019 ◽  
Author(s):  
George S. Fanourgakis ◽  
Maria Kanakidou ◽  
Athanasios Nenes ◽  
Susanne E. Bauer ◽  
Tommi Bergman ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Aerosol Formation ◽  
Condensation Nuclei ◽  
Short Term ◽  
Near Surface

Abstract. A total of sixteen global chemistry transport models and general circulation models have participated in this study. Fourteen models have been evaluated with regard to their ability to reproduce near-surface observed number concentration of aerosol particle and cloud condensation nuclei (CCN), and derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations, located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments, and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters > 50 nm and > 120 nm and −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. Fifteen models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −17 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally-derived value at lower than at higher updraft velocities (index-of-agreement of 0.47 vs 0.50). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration and to updraft velocity. Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high.

scholarly journals Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

2019 ◽  
Vol 19 (13) ◽  
pp. 8591-8617 ◽  
Author(s):  
George S. Fanourgakis ◽  
Maria Kanakidou ◽  
Athanasios Nenes ◽  
Susanne E. Bauer ◽  
Tommi Bergman ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Aerosol Formation ◽  
Condensation Nuclei ◽  
Short Term ◽  
Near Surface

Abstract. A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

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