Cloud Condensation Nuclei Closure Research Articles

The density of ambient black carbon retrieved by a new method: implications for cloud condensation nuclei prediction

Abstract. The effective density of black carbon (BC) is a crucial factor that is relevant to its aging degree and adds uncertainty in evaluating its climate effect. Here, we have developed a new method to retrieve the effective density of internally mixed BC in the atmosphere, combining field observations conducted from 15 November to 14 December 2016 in urban Beijing with the Köhler theory. The uncertainty in the retrieval method was evaluated to be within ±30 %, which was primarily caused by assumptions on both the hygroscopic parameter of organics and the proportional distribution of primary organic aerosols in different hygroscopic modes. Using the method, we find that the ambient internally mixed BC, accounting for 80 % ± 20 % of total BC aerosol particles, was retrieved with a campaign mean density of 1.1 ± 0.6 g cm−3 during the observed periods. The retrieved result was comparable with that reported in the literature. By applying a lower (0.14 g cm−3) and upper (2.1 g cm−3) limit of the retrieved BC density in the cloud condensation nuclei (CCN) number concentration (NCCN) estimation, we derived that the neglect of such variations in the BC density would lead to an uncertainty of −28 %–11 % in predicting NCCN at supersaturations of 0.23 % and 0.40 %. We also find that the NCCN was more sensitive to the variations in BC density when it was <1.0 g cm−3. This illustrates the necessity of accounting for the effect of BC density on CCN activity closer to source regions where the BC particles are mostly freshly emitted. The CCN closure was achieved when introducing the retrieved real-time BC density and mixing state. This study provides a unique way of utilizing field measurements to infer ambient BC density and highlights the importance of applying variable BC density values in models when predicting CCN and assessing its relevant climate effect.

Cloud Condensation Nuclei Closure Study Using Airborne Measurements Over the Southern Great Plains

AbstractAirborne measurements of non‐refractory bulk aerosol chemical composition, aerosol size distributions, and cloud condensation nuclei (CCN) were conducted onboard a research aircraft during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems field campaign in the spring and summer of 2016. A CCN closure study for the entire campaign period was performed where measured CCN concentrations at 0.24% and 0.46% supersaturation were compared with the predicted CCN concentrations calculated using κ‐Köhler theory, three different assumptions of aerosol mixing state, and various assumptions about hygroscopicity, density, and the insoluble fraction of organic particles. We found that the Closure Ratio (CR), calculated as the ratio of predicted to measured CCN concentrations, was equal to one under two different aerosol mixing state assumptions: (a) all particles are composed of 100% organic particles, and (b) particles are externally mixed and composed of pure sulfates, nitrates, and organic particles assuming hygroscopicity values for organic particles () between 0.04 and 0.17. The use of internal mixing state assumption often led to overprediction of CCN concentrations but the agreement within ±20% with the measured CCN concentrations was observed under certain closure permutations. A similar agreement, that is, within ±20%, was also observed using permuted parameters concerning density (1 and 1.5 g cm−3) and an insoluble fraction (0% and 20%) of organic particles. These findings may provide constraints on to predict CCN concentrations at a remote continental Southern Great Plains site.

Cloud condensation nuclei characteristics at the Southern Great Plains site: role of particle size distribution and aerosol hygroscopicity

The activation ability of aerosols as cloud condensation nuclei (CCN) is crucial in climate and hydrological cycle studies, but their properties are not well known. We investigated the long-term measurements of atmospheric aerosol properties, CCN concentrations (NCCN) at supersaturation (SS = 0.1%–1.0%), and hygroscopicity at the Department of Energy’s Southern Great Plains (SGP) site to illustrate the dependence of NCCN on aerosol properties and transport pathways. Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aged biomass burning aerosols from Central America were characterized by higher accumulation mode particles (Naccu; median value 805 cm−3) and relatively high aerosol hygroscopicity (κ; median value ∼0.25) values that result in the higher CCN activation and relatively high NCCN (median value 258–1578 cm−3 at a SS of 0.1%–1.0%). Aerosols from the Gulf of Mexico were characterized by higher Naccu (∼35%), and NCCN (230–1721 cm−3 at a SS of 0.1%–1.0%) with the lowest κ (∼0.17). In contrast, relatively high nucleation mode particles (Nnucl; ∼20%) and low NCCN (128–1553 cm−3 at a SS of 0.1%–1.0%) with higher κ (∼0.30) values were observed on the aerosols associated with a westerly wind. The results indicate particle size as the most critical factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary. Our CCN closure analysis suggests that chemical composition and mixing state information are more crucial at lower SS, whereas at higher SS, most particles become activated regardless of their chemical composition and size. This study affirms that soluble organic fraction information is required at higher SS for better NCCN prediction, but both the soluble organics fraction and mixing state are vital to reduce the NCCN prediction uncertainty at lower SS.

Characterization of submicron aerosols over the Yellow Sea measured onboard the Gisang 1 research vessel in the spring of 2018 and 2019

The physico-chemical properties of submicron aerosols were measured in the spring of 2018 and 2019 over the Yellow Sea onboard the Gisang 1 research vessel. Aerosol number concentrations in 2019 were slightly higher than those in 2018, and the mean number concentrations of particles larger than 10 nm and cloud condensation nuclei (CCN) at 0.6% supersaturation (S) in spring 2019 were 7312 ± 3807 cm−3 and 4816 ± 1692 cm−3, respectively. Aerosol concentrations in June were lower than those in April and May, which was considered to be due to the East Asian summer monsoon. Aerosol number concentrations and size distributions were significantly influenced by meteorological conditions, such as wind and relative humidity. Aitken and accumulation mode particles dominated the aerosol number size distributions over the Yellow Sea. A distinct new particle formation (NPF) and growth event was observed, the spatial extent of which was estimated to cover at least 200 km × 400 km of the Yellow Sea. The general characteristics of NPF and growth over the Yellow Sea were similar to those in rural areas. Aerosol number concentrations below 1000 cm−3 were recorded on extremely clean days. A CCN closure experiment conducted using previous measurement data showed good results, indicating that CCN concentrations can be estimated with good accuracy, and the hygroscopicity over the Yellow Sea was similar to that of aged continental aerosols.

Characteristics of CCN activation and cloud microphysics over the east coast of India during the Northeast Monsoon onset

Airborne observations conducted during the Northeast Monsoon onset as part of the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX 2011) are used to link the activation properties of aerosols with the observed cloud microphysics. This study illustrates the significant spatial variability in the aerosol spectrum, cloud condensation nuclei (CCN) activation characteristics, and the cloud droplet spectral properties over a coastal and an inland location. High concentrations of Aitken mode and black carbon aerosols were observed in the free troposphere and are attributed to the convectively transported smoke and aerosols from the coastal boundary layer. The assumption of an internally mixed organic and inorganic aerosol composition provided a better CCN closure over assumptions of either purely organic or purely inorganic aerosols. The coastal clouds were equally polluted as the inland clouds with high cloud droplet number concentrations near the cloud base. The vertical distribution of cloud droplet spectral characteristics was similar in both coastal and inland clouds. An increase in droplet number concentration up to 2 km above the cloud base indicated a prominent influence of submicron particles on the cloud microphysical parameters. Evidence for an enhanced concentration of supercooled drops above the freezing level up to temperatures below −12 °C is documented. The secondary ice production was evident through observations of graupel and snow particles. Heavy loading of aerosols near the cloud base leads to enhanced mixed-phase processes in these clouds.

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

During the Marine Aerosol Cloud and Wildfire Study (MACAWS) in June and July of 2018, aerosol composition and cloud condensation nuclei (CCN) properties were measured over the N.E. Pacific to characterize the influence of aerosol hygroscopicity on predictions of ambient CCN and stratocumulus cloud droplet number concentrations (CDNC). Three vertical regions were characterized, corresponding to the marine boundary layer (MBL), an above-cloud organic aerosol layer (AC-OAL), and the free troposphere (FT) above the AC-OAL. The aerosol hygroscopicity parameter (κ) was calculated from CCN measurements (κCCN) and bulk aerosol mass spectrometer (AMS) measurements (κAMS). Within the MBL, measured hygroscopicities varied between values typical of both continental environments (~0.2) and remote marine locations (~0.7). For most flights, CCN closure was achieved within 20% in the MBL. For five of the seven flights, assuming a constant aerosol size distribution produced similar or better CCN closure than assuming a constant “marine” hygroscopicity (κ = 0.72). An aerosol-cloud parcel model was used to characterize the sensitivity of predicted stratocumulus CDNC to aerosol hygroscopicity, size distribution properties, and updraft velocity. Average CDNC sensitivity to accumulation mode aerosol hygroscopicity is 39% as large as the sensitivity to the geometric median diameter in this environment. Simulations suggest CDNC sensitivity to hygroscopicity is largest in marine stratocumulus with low updraft velocities (<0.2 m s−1), where accumulation mode particles are most relevant to CDNC, and in marine stratocumulus or cumulus with large updraft velocities (>0.6 m s−1), where hygroscopic properties of the Aitken mode dominate hygroscopicity sensitivity.

Characterization of submicron aerosols and CCN over the Yellow Sea measured onboard the Gisang 1 research vessel using the positive matrix factorization analysis method

Aerosol size distributions and cloud condensation nuclei (CCN) number concentrations were measured in spring 2017 over the Yellow Sea on board the research vessel Gisang 1. The average number concentration of particles larger than 10 nm and CCN at 0.65% supersaturation (S) were 7622 ± 4038 cm−3 and 4821 ± 1763 cm−3, respectively. Characteristics of aerosol size distribution data were analyzed using a positive matrix factorization (PMF) method. It was found that only 6 Factors could explain the aerosol size distribution reasonably well. Factors 1 and 2 indicated nucleation mode particles, Factor 3 indicated Aitken mode particles, and Factors 4, 5, and 6 indicated accumulation mode particles. The concentrations of nucleation and Aitken mode particles showed a clear wind direction dependence; high under westerly winds due to the high concentrations of particles and precursor gases in eastern China. Meanwhile, the concentration of larger particles and CCN showed no significant wind direction dependence. Aerosol size distribution was also significantly influenced by meteorology. Small particles were predominant during clear days. In contrast during mist or fog days, the aerosol size distribution shifted to larger sizes. A CCN closure experiment was conducted using results of the PMF analysis. The assumption of internally mixed particles led to overestimation of predicted CCN concentrations but agreement was significantly better when externally mixed particles were considered. The logarithmic curve fit of NCCN(S) = 4825 ∗ log S + 4933 was found to very well explain measured CCN concentrations at a few S over the Yellow Sea, and therefore is recommended as input CCN spectral data for numerical models that explicitly treat CCN activation.

Cloud condensation nuclei over the Bay of Bengal during the Indian summer monsoon

The first measurements of cloud condensation nuclei (CCN) at five supersaturations were carried out onboard the research vessel “Sagar Kanya” (cruise SK-296) from the south to the head-bay of the Bay of Bengal as part of the Continental Tropical Convergence Zone (CTCZ) Project during the Indian summer monsoon of 2012. In this paper, we assess the diurnal variation in CCN distributions at supersaturations from 0.2% to 1% (in steps of 0.2%) and the power-law fit at supersaturation of 1%. The diurnal pattern shows peaks in CCN concentration (NCCN) at supersaturations from 0.2% to 1% between 0600 and 0700 LST (local standard time, UTC+0530), with relatively low concentrations between 1200 and 1400 LST, followed by a peak at around 1800 LST. The power-law fit for the CCN distribution at different supersaturation levels relates the empirical exponent (k) of supersaturation (%) and the NCCN at a supersaturation of 1%. The NCCN at a supersaturation of 0.4% is observed to vary from 702 cm−3 to 1289 cm−3, with a mean of 961±161 cm−3 (95% confidence interval), representing the CCN activity of marine air masses. Whereas, the mean NCCN of 1628±193 cm−3 at a supersaturation of 1% is higher than anticipated for the marine background. When the number of CCN spectra is 1293, the value of k is 0.57±0.03 (99% confidence interval) and its probability distribution shows cumulative counts significant at k ≈ 0.55±0.25. The results are found to be better at representing the features of the marine environment (103 cm−3 and k ≈ 0.5) and useful for validating CCN closure studies for Indian sea regions.

Role of organic aerosols in CCN activation and closure over a rural background site in Western Ghats, India

The cloud condensation nuclei (CCN) closure study was performed to exemplify the effect of aerosol chemical composition on the CCN activity of aerosols at Mahabaleshwar, a high altitude background site in the Western Ghats, India. For this, collocated aerosol, CCN, Elemental Carbon (EC), Organic Carbon (OC), sub-micron aerosol chemical speciation for the period from 3rd June to 19th June 2015 was used. The chemical composition of non-refractory particulate matter (<1 μm) as measured by Time of Flight – Aerosol Chemical Speciation Monitor (ToF-ACSM) was dominated by organics with average concentration of 3.81 ± 1.6, 0.32 ± 0.06, 0.15 ± 0.02, 0.13 ± 0.03 and 0.95 ± 0.12 μg m−3 for organics, ammonium, chloride, nitrate and sulphate, respectively. The PM1 number concentration as obtained by Wide Range Aerosol Spectrometer (WRAS) varied from 750 to 6480 cm−3. The average mass concentration of elemental carbon (EC) as measured by OC-EC analyzer was 1.16 ± 0.4 μg m−3. The average CCN concentrations obtained from CCN counter (CCNC) at five super-saturations (SS's) was 118 ± 58 cm−3 (0.1% SS), 873 ± 448 cm−3 (0.31% SS), 1308 ± 603 cm−3 (0.52% SS), 1610 ± 838 cm−3 (0.73% SS) and 1826 ± 985 cm−3 (0.94% SS). The CCN concentrations were predicted using Köhler theory on the basis of measured aerosol particle number size distribution, size independent NR-PM1 chemical composition and calculated hygroscopicity. The CCN closure study was evaluated for 3 scenarios, B-I (all soluble inorganics), B-IO (all soluble organics and inorganics) and B-IOOA (all soluble inorganic and soluble oxygenated organic aerosol, OOA). OOA component was derived from the positive matrix factorization (PMF) analysis of organic aerosol mass spectra. Considering the bulk composition as internal mixture, CCN closure study was underestimated by 16–39% for B-I and overestimated by 47–62% for B-IO. The CCN closure result was appreciably improved for B-IOOA where the knowledge of OOA fraction was introduced and uncertainty reduced to within 8–10%.

Hygroscopic properties of urban aerosols and their cloud condensation nuclei activities measured in Seoul during the MAPS-Seoul campaign

Aerosol physical properties, chemical compositions, hygroscopicity and cloud condensation nuclei (CCN) activities were measured in Seoul, the highly populated capital city of Korea, during the Megacity Air Pollution Studies (MAPS-Seoul) campaign, in May–June 2015. The average aerosol concentration for particle diameters >10 nm was 11787 ± 7421 cm−3 with dominant peaks at morning rush hours and in the afternoon due to frequent new particle formation (NPF) events. The average CCN concentration was 4075 ± 1812 cm−3 at 0.6% supersaturation, with little diurnal variation. The average hygroscopicity parameter (κ) value determined using a humidified tandem differential mobility analyzer (HTDMA) ranged 0.17–0.27 for a range of particle diameters (30–150 nm). The κ values derived using the aerosol mass spectrometer (AMS) data with three different methods were 0.32–0.34, significantly higher than those from HTDMA due to the uncertainties in the hygroscopicity values of different chemical compositions, especially organics and black carbon. Factors affecting the aerosol hygroscopicity seemed to be traffic and chemical processes during the NPF events. The CCN concentration predicted based on HTDMA κ data showed very good agreement with the measured one. Because of the overestimation of κ, CCN closure with the predicted CCN concentration based on AMS κ data over-predicted CCN concentration although the linear correlation between measured and predicted CCN concentration was still very good.

Inverse modelling of Köhler theory – Part 1: A response surface analysis of CCN spectra with respect to surface-active organic species

Abstract. In this study a novel framework for inverse modelling of cloud condensation nuclei (CCN) spectra is developed using Köhler theory. The framework is established by using model-generated synthetic measurements as calibration data for a parametric sensitivity analysis. Assessment of the relative importance of aerosol physicochemical parameters, while accounting for bulk–surface partitioning of surface-active organic species, is carried out over a range of atmospherically relevant supersaturations. By introducing an objective function that provides a scalar metric for diagnosing the deviation of modelled CCN concentrations from synthetic observations, objective function response surfaces are presented as a function of model input parameters. Crucially, for the chosen calibration data, aerosol–CCN spectrum closure is confirmed as a well-posed inverse modelling exercise for a subset of the parameters explored herein. The response surface analysis indicates that the appointment of appropriate calibration data is particularly important. To perform an inverse aerosol–CCN closure analysis and constrain parametric uncertainties, it is shown that a high-resolution CCN spectrum definition of the calibration data is required where single-valued definitions may be expected to fail. Using Köhler theory to model CCN concentrations requires knowledge of many physicochemical parameters, some of which are difficult to measure in situ on the scale of interest and introduce a considerable amount of parametric uncertainty to model predictions. For all partitioning schemes and environments modelled, model output showed significant sensitivity to perturbations in aerosol log-normal parameters describing the accumulation mode, surface tension, organic : inorganic mass ratio, insoluble fraction, and solution ideality. Many response surfaces pertaining to these parameters contain well-defined minima and are therefore good candidates for calibration using a Monte Carlo Markov Chain (MCMC) approach to constraining parametric uncertainties.A complete treatment of bulk–surface partitioning is shown to predict CCN spectra similar to those calculated using classical Köhler theory with the surface tension of a pure water drop, as found in previous studies. In addition, model sensitivity to perturbations in the partitioning parameters was found to be negligible. As a result, this study supports previously held recommendations that complex surfactant effects might be neglected, and the continued use of classical Köhler theory in global climate models (GCMs) is recommended to avoid an additional computational burden. The framework developed is suitable for application to many additional composition-dependent processes that might impact CCN activation potential. However, the focus of this study is to demonstrate the efficacy of the applied sensitivity analysis to identify important parameters in those processes and will be extended to facilitate a global sensitivity analysis and inverse aerosol–CCN closure analysis.

Measurement of cloud condensation nuclei (CCN) and CCN closure at Mt. Huang based on hygroscopic growth factors and aerosol number-size distribution

The number of cloud condensation nuclei (CCN) may indirectly influence the radiative balance of the atmosphere by changing the number of cloud droplets, which in turn changes the albedo, longevity and precipitation intensity of clouds. The spatial and temporal distribution of the CCN concentrations and the influence of particles on CCN activation spectra have received much attention. Measurements of CCN concentrations, aerosol number-size distribution and hygroscopic growth factors were conducted during the periods June 30 to July 17 and July 24 to 28, 2014, at the peak of Mt. Huang (1840 m above sea level). The results show that the CCN concentration were 419 ± 414 cm−3, 806 ± 720 cm−3, 1292 ± 905 cm−3, 1380 ± 873 cm−3, and 1506 ± 867 cm−3 at supersaturation levels of 0.1%, 0.2%, 0.5%, 0.7%, and 1%, respectively. The equation Nccn = N0(1-exp(-BSk)) fits the average CCN spectrum over the observation period. The CCN concentrations were calculated from the hygroscopic growth factors and the aerosol number-size distribution. The calculated CCN concentrations and measured CCN concentrations show close correlation and high accuracy. An analysis of the variation in the particle number-size distribution and hygroscopic growth factors indicates that the change in particle number-size distribution is the primary factor affecting the CCN concentrations.

CCN closure study: Effects of aerosol chemical composition and mixing state

AbstractThis study presents a detailed cloud condensation nuclei (CCN) closure study that investigates the effects of chemical composition (bulk and size resolved) and mixing state (internal and external) on CCN activity of aerosols. Measurements of the chemical composition, aerosol size distribution, total number concentration, and CCN concentration at supersaturation (SS = 0.2–1.0%) were performed during the winter season in Kanpur, India. Among the two cases considered here, better closure results are obtained for case 1 (low total aerosol loading, 49.54 ± 26.42 μg m−3, and high O:C ratio, 0.61 ±0.07) compared to case 2 (high total aerosol loading, 101.05 ± 18.73 μg m−3, and low O:C ratio, 0.42 ±0.06), with a maximum reduction of 3–81% in CCN overprediction for all depleted SS values (0.18–0.60%). Including the assumption that less volatile oxidized organic aerosols represent the soluble organic fraction reduced the overprediction to at most 40% and 129% in the internal and external mixing scenarios, respectively. At higher depleted SS values (0.34–0.60%), size‐resolved chemical composition with an internal mixing state performed well in CCN closure among all organic solubility scenarios. However, at a lower depleted SS value (0.18%), closure is found to be more sensitive to both the chemical composition and mixing state of aerosols. At higher SS values, information on the solubility of organics and size‐resolved chemical composition is required for accurate CCN predictions, whereas at lower SS values, information on the mixing state in addition to the solubility of organics and size‐resolved chemical composition is required. Overall, κtotal values are observed to be independent of the O:C ratio [κtotal= (0.36 ±0.01) × O:C − (0.03 ± 0.01)] in the range of 0.2&lt;O:C&lt;0.81, which indicates that the variation in the chemical composition of aerosols is not well represented by the changes in the O:C ratio alone.

Aerosol hygroscopicity and cloud condensation nuclei activity during the AC&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt;Exp campaign: implications for cloud condensation nuclei parameterization

Abstract. Aerosol hygroscopicity and cloud condensation nuclei (CCN) activity under background conditions and during pollution events are investigated during the Aerosol-CCN-Cloud Closure Experiment (AC3Exp) campaign conducted at Xianghe, China in summer 2013. A gradual increase in size-resolved activation ratio (AR) with particle diameter (Dp) suggests that aerosol particles have different hygroscopicities. During pollution events, the activation diameter (Da) measured at low supersaturation (SS) was significantly increased compared to background conditions. An increase was not observed when SS was &gt; 0.4%. The hygroscopicity parameter (κ) was ~ 0.31–0.38 for particles in accumulation mode under background conditions. This range in magnitude of κ was ~ 20%, higher than κ derived under polluted conditions. For particles in nucleation or Aitken mode, κ ranged from 0.20–0.34 for background and polluted cases. Larger particles were on average more hygroscopic than smaller particles. The situation was more complex for heavy pollution particles because of the diversity in particle composition and mixing state. A non-parallel observation CCN closure test showed that uncertainties in CCN number concentration estimates ranged from 30–40%, which are associated with changes in particle composition as well as measurement uncertainties associated with bulk and size-resolved CCN methods. A case study showed that bulk CCN activation ratios increased as total condensation nuclei (CN) number concentrations (NCN) increased on background days. The background case also showed that bulk AR correlated well with the hygroscopicity parameter calculated from chemical volume fractions. On the contrary, bulk AR decreased with increasing total NCN during pollution events, but was closely related to the fraction of the total organic mass signal at m/z 44 (f44), which is usually associated with the particle's organic oxidation level. Our study highlights the importance of chemical composition in determining particle activation properties and underlines the significance of long-term observations of CCN under different atmospheric environments, especially regions with heavy pollution.

Measured and modelled cloud condensation nuclei (CCN) concentration in São Paulo, Brazil: the importance of aerosol size-resolved chemical composition on CCN concentration prediction

Abstract. Measurements of cloud condensation nuclei (CCN), aerosol size distribution and non-refractory chemical composition were performed from 16 to 31 October 2012 in the São Paulo Metropolitan Area (SPMA), Brazil. CCN measurements were performed at 0.23, 0.45, 0.68, 0.90 and 1.13% water supersaturation and were subsequently compared with the Köhler theory, considering the chemical composition. Real-time chemical composition has been obtained by deploying, for the first time in the SPMA, an aerosol chemical ionization monitor (ACSM). CCN closure analyses were performed considering internal mixtures. Average aerosol composition during the studied period yielded (arithmetic mean~± standard deviation) 4.81 ± 3.05, 3.26 ± 2.10, 0.30 ± 0.27, 0.52 ± 0.32, 0.37 ± 0.21 and 0.04 ± 0.04 μg m−3 for organics, BC, NH4, SO4, NO3 and Cl, respectively. Particle number concentration was 12 813 ± 5350 cm−3, with a dominant nucleation mode. CCN concentrations were on average 1090 ± 328 and 3570 ± 1695 cm−3 at SS = 0.23% and SS = 1.13%, respectively. Results show an increase in aerosol hygroscopicity in the afternoon as a result of aerosol photochemical processing, leading to an enhancement of both organic and inorganic secondary aerosols in the atmosphere, as well as an increase in aerosol average diameter. Considering the bulk composition alone, observed CCN concentrations were substantially overpredicted when compared with the Köhler theory (44.1 ± 47.9% at 0.23% supersaturation and 91.4 ± 40.3% at 1.13% supersaturation). Overall, the impact of composition on the calculated CCN concentration (NCCN) decreases with decreasing supersaturation, partially because using bulk composition introduces less bias for large diameters and lower critical supersaturations, defined as the supersaturation at which the cloud droplet activation will take place. Results suggest that the consideration of only inorganic fraction improves the calculated NCCN. Introducing a size-dependent chemical composition based on filter measurements from previous campaigns has considerably improved simulated values for NCCN (average overprediction error 14.8 ± 38.6% at 0.23% supersaturation and 3.6 ± 21.6% at 1.13% supersaturation). This study provides the first insight on aerosol real-time composition and hygroscopicity at a site strongly impacted by emissions of a unique vehicular fleet due to the extensive biofuel usage.

CCN closure results from Indian Continental Tropical Convergence Zone (CTCZ) aircraft experiment

In-situ aircraft measurements of cloud condensation nuclei (CCN) and aerosol size distribution were carried out over the region spanning from 24.78 °N to 29.5 °N and 78.1 °E to 85.0 °E from June 29 to July 3, 2009 during the Indian Continental Tropical Convergence Zone (CTCZ) campaign, consisting of total 9 flight sorties. CCN measurements were conducted at a constant supersaturation (SS) of 0.84%. It was found that at higher altitudes (4.7–6.7km), 30nm sized particles were dominating while at lower altitudes (0.6–3.7km), 50nm particles. Overall, CCN closure ratio (CCNpredicted/CCNmeasured) at different altitudes using Köhler theory and assuming pure ammonium sulfate was 1.375 (R2=0.80). For each sortie, the closure ratio varied with height and depended greatly on measured CN concentrations. A case study of Khajuraho sortie showed that the closure ratio increased from 1.07 to 1.40 as the CCN concentration increased from 1000cm−3 to 4000cm−3. Results of CCN closure improved significantly (overprediction improved by 37.5% and 34.6% for Pantnagar and Gaya, respectively) with the assumption of internally mixed aerosols composed of ammonium sulfate and insoluble organics. Hygroscopicity parameter calculated for these two sorties (κ=0.51 and 0.5) indicates the presence of moderately hygroscopic organic species along with some inorganic content.

Analysis of CCN activity of Arctic aerosol and Canadian biomass burning during summer 2008

Abstract. The NASA DC-8 aircraft characterized the aerosol properties, chemical composition, and cloud condensation nuclei (CCN) concentrations of the summertime Arctic during the 2008 NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. Air masses characteristic of fresh and aged biomass burning, boreal forest, Arctic background, and anthropogenic industrial pollution were sampled. Observations were spatially extensive (50–85° N and 40–130° W) and exhibit significant variability in aerosol and CCN concentrations. The chemical composition was dominated by highly oxidized organics (66–94% by volume), with a water-soluble mass fraction of more than 50%. The aerosol hygroscopicity parameter, κ, ranged between κ = 0.08–0.32 for all air mass types. Industrial pollution had the lowest κ of 0.08 ± 0.01, while the Arctic background had the highest and most variable κ of 0.32 ± 0.21, resulting from a lower and more variable organic fraction. Both fresh and aged (long-range transported) biomass burning air masses exhibited remarkably similar κ (0.18 ± 0.13), consistent with observed rapid chemical and physical aging of smoke emissions in the atmosphere, even in the vicinity of fresh fires. The organic hygroscopicity (κorg) was parameterized by the volume fraction of water-soluble organic matter (εWSOM), with a κ = 0.12, such that κorg = 0.12εWSOM. Assuming bulk (size-independent) composition and including the κorg parameterization enabled CCN predictions to within 30% accuracy for nearly all environments sampled. The only exception was for industrial pollution from Canadian oil sands exploration, where an external mixture and size-dependent composition was required. Aerosol mixing state assumptions (internal vs. external) in all other environments did not significantly affect CCN predictions; however, the external mixing assumption provided the best results, even though the available observations could not determine the true degree of external mixing and therefore may not always be representative of the environments sampled. No correlation was observed between κorg and O : C. A novel correction of the CCN instrument supersaturation for water vapor depletion, resulting from high concentrations of CCN, was also employed. This correction was especially important for fresh biomass burning plumes where concentrations exceeded 1.5×104 cm−3 and introduced supersaturation depletions of &amp;amp;geq;25%. Not accounting for supersaturation depletion in these high concentration environments would therefore bias CCN closure up to 25% and inferred κ by up to 50%.

Aerosol cloud activation in summer and winter at puy-de-Dôme high altitude site in France

Abstract. Cloud condensation nuclei (CCN) size distributions and numbers were measured for the first time at Puy-de-Dôme high altitude (1465 m a.s.l) site in Central France. Majority of the measurements were done at constant supersaturation (SS) of 0.24%, which was also deduced to be representative of the typical in-cloud SS at the site. CCN numbers during summer ranged from about 200 up to 2000 cm−3 and during winter from 50 up to 3000 cm−3. Variability of CCN number was explained by both particle chemistry and size distribution variability. The higher CCN concentrations were measured in continental, in contrast to marine, air masses. Aerosol CCN activity was described with a single hygroscopicity parameter κ. Range of this parameter was 0.29 ± 0.13 in summer and 0.43 ± 0.19 in winter. When calculated using SS of 0.51% during summer, κ of 0.22 ± 0.07 was obtained. The decrease with increasing SS is likely explained by the particle size dependent chemistry with smaller particles containing higher amounts of freshly emitted organic species. Higher κ values during winter were for the most part explained by the observed aged organics (analysed from organic m/z 44 ratio) rather than from aerosol organic to inorganic volume fraction. The obtained κ values also fit well within the range of previously proposed global continental κ of 0.27 ± 0.21. During winter, the smallest κ values and the highest organic fractions were measured in marine air masses. CCN closure using bulk AMS chemistry led to positive bias of 5% and 2% in winter and summer, respectively. This is suspected to stem from size dependent aerosol organic fraction, which is underestimated by using AMS bulk mass composition. Finally, the results were combined with size distributions measured from interstitial and whole air inlets to obtain activated droplet size distributions. Cloud droplet number concentrations were shown to increase with accumulation mode particle number, while the real in-cloud SS correspondingly decreased. These results provide evidence on the effects of aerosol particles on maximum cloud supersaturations. Further work with detailed characterisation of cloud properties is proposed in order to provide more quantitative estimates on aerosol effects on clouds.

Impact of aerosol composition on cloud condensation nuclei activity

Abstract. The impact of aerosol composition on cloud condensation nuclei (CCN) activity were analyzed in this study based on field experiments carried out at downtown Tianjin, China in September 2010. In the experiments, the CCN measurements were performed at supersaturation (SS) of 0.1%, 0.2% and 0.4% using a thermal-gradient diffusion chamber (DMT CCNC), whereas the aerosol size distribution and composition were simultaneously measured with a TSI SMPS and an Aerodyne Aerosol Mass Spectrometer (AMS), respectively. The results show that the influence of aerosol composition on CCN activity is notable under low SS (0.1%), and their influence decreased with increasing SS. For example, under SS of 0.1%, the CCN activity increases from 4.5±2.6% to 12.8±6.1% when organics fraction decrease from 30–40% to 10–20%. The rate of increase reached up to 184%. While under SS of 0.4%, the CCN activity increases only from 35.7±19.0% to 46.5±12.3% correspondingly. The calculated NCCN based on the size-resolved activation ratio and aerosol number size distribution correlated well with observed NCCN at high SS (0.4%), but this consistence decreased with the falling of SS. The slopes of linear fitted lines between calculated and observed NCCN are 0.708, 0.947, and 0.995 at SS of 0.1%, 0.2% and 0.4% respectively. Moreover, the stand deviation (SD) of calculated NCCN increased with the decreasing of SS. A case study of CCN closure analyses indicated that the calculated error of NCCN could reach up to 34% at SS of 0.1% if aerosol composition were not included, and the calculated error decreased with the raising of SS. It is decreased to 9% at SS of 0.2%, and further decreased to 4% at SS of 0.4%.

Hygroscopicity and composition of California CCN during summer 2010

We present an overview and analysis of cloud condensation nuclei (CCN) sampled in California by a NOAA WP‐3D aircraft during the 2010 CalNex project. Four distinct geographical regions are characterized, including the Los Angeles basin, the San Joaquin and Sacramento Valleys, and the eastern Pacific Ocean west of southern California. Median size distributions in the Central Valley were unimodal (Dg ∼ 25 nm) with a larger fraction of organic species and smaller fraction of nitrate species in the Sacramento Valley aerosol than in the San Joaquin Valley aerosol. Size distributions in the Los Angeles basin and marine outflow were bimodal (geometric mean diameter, Dg ∼ 30, 90–100 nm) with similar organic fractions and some replacement of nitrate with sulfate in the marine outflow. Both fine particle and CCN concentrations were found to decrease rapidly above the planetary boundary layer (∼2 km altitude), with CCN concentrations in the boundary layer ranging from ∼102–104 cm−3 STP, while fine particle concentrations (0.004–1 μm diameters) ranged from ∼103–105 cm−3STP. The CCN‐active number fraction varied between 0–100% in the Los Angeles Basin and Marine Outflow, but was substantially lower (0–40%) in the San Joaquin and Sacramento Valleys. Values of the hygroscopicity parameter,κ, inferred from the CCN measurements varied from 0.1–0.25, with the highest values in the marine outflow and the lowest values in the Sacramento Valley. The κvalues agreed well with the predictions based on size‐resolved aerosol composition, but were overpredicted by almost twofold when size‐averaged composition was used. CCN closure was assessed for simplified compositional and mixing state assumptions, and it was found that assuming the aerosol to be internally mixed overpredicted CCN concentrations by 30–75% for all air mass types except within the Sacramento Valley, where good closure (overprediction &lt; 10%) was achieved by assuming insoluble organics. Assuming an externally‐mixed aerosol fraction or incorporating size‐resolved composition data improved closure in the other three regions, consistent with the bimodal nature of the aerosol size distribution.