Aerosol particle number concentration. Calibration of condensation particle counters

2015 ◽  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Number Concentration ◽  
Particle Number Concentration

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.

Multi-seasonal ultrafine aerosol particle number concentration measurements at the Gruvebadet observatory, Ny-Ålesund, Svalbard Islands

2016 ◽  
Vol 27 (S1) ◽  
pp. 59-71 ◽  
Author(s):  
Angelo Lupi ◽  
Maurizio Busetto ◽  
Silvia Becagli ◽  
Fabio Giardi ◽  
Christian Lanconelli ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Concentration Measurements ◽  
Ultrafine Aerosol

scholarly journals Aerosol particle properties in the tropical free troposphere observed at Pico Espejo (4765 m a.s.l.), Venezuela

2010 ◽  
Vol 10 (11) ◽  
pp. 29153-29189
Author(s):  
T. Schmeißner ◽  
R. Krejci ◽  
J. Ström ◽  
W. Birmili ◽  
A. Wiedensohler ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Dry Season ◽  
Number Concentration ◽  
Aerosol Size Distribution ◽  
Particle Number Concentration ◽  
Free Troposphere ◽  
Wet Season ◽  
Concentration Data ◽  
Diurnal Variability

Abstract. The first long-term measurements of aerosol number and size distributions in South-American tropical free troposphere were performed from March 2007 until Mai 2009. The measurements took place at the high altitude Atmospheric Research Station Alexander von Humboldt. The station is located on top of the Sierra Nevada mountain ridge at 4765 m a.s.l. nearby the city of Mérida, Venezuela. Aerosol size distribution and number concentration data was obtained with a custom-built Differential Mobility Particle Sizer (DMPS system) and a Condensational Particle Counter (CPC). The analysis of the annual and diurnal variability of the tropical free troposphere (FT) aerosol focused mainly on possible links to the atmospheric general circulation in the tropics. Considerable annual and diurnal cycles of the particle number concentration were observed. Highest total particle number concentrations were measured during the dry season (519±613 cm−3), lowest during the wet season (318±194 cm−3). The more humid FT contained generally higher aerosol particle number concentrations (573±768 cm−3 during dry season, 320±195 cm−3 during wet season) than the dry FT (454±332 cm−3 during dry season, 275±172 cm−3 during wet season), indicating the importance of convection for aerosol distributions in the tropical FT. The diurnal cycle in the variability of the particle number concentration was mainly driven by local orography.

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