Cloud Condensation Nuclei Measurements Research Articles

Multiple-charging effects on the CCN activity and hygroscopicity of surrogate black carbon particles

Accurate measurements of cloud condensation nuclei (CCN) activity and hygroscopicity of black carbon (BC)-containing particles are particularly important because of the positive climate forcing from these particles. Such measurements are typically conducted on particles selected by a Differential Mobility Analyzer (DMA), which in addition to singly charged particles transmits multiply charged larger particles that have the same electrical mobility. These larger particles activate at lower supersaturations than the singly charged particles, biasing measurements and resulting in overestimation of CCN activity and hygroscopicity parameter (κ). Here, we measure the CCN activity and determine κ for different BC surrogates with electrical mobility diameters from 100 to 200 nm selected 1) only by electrical mobility with a DMA, and 2) by both electrical mobility and mass using a DMA and a Centrifugal Particle Mass Analyzer (CPMA), thus allowing selection of only singly charged particles. We demonstrate the use of the DMA-CPMA system in resolving biases caused by multiply charged particles, and we show that the effect of multiple charging on the CCN activity of the BC particles is strongly influenced by morphology dispersion, i.e., the variability due to the range of morphologies of particles that have the same electrical mobility and mass. Our findings show that electrical mobility-based methods alone are unlikely to lead to accurate results in measurements of CCN activation and hygroscopicity of BC particles, even for those with a more compact morphology.

A New Method for Size‐Resolved Aerosol CCN Activity Measurement at Low Supersaturation in Pristine Atmosphere

AbstractUnderstanding aerosol‐cloud interactions under pristine atmospheric conditions is crucial for meaningful global climate change predictions. However, ability of aerosol particles to act as cloud condensation nuclei (CCN) activity of aerosols in pristine atmosphere remains limited, mainly because of the difficulty of measuring it in pristine environments. Given the extremely low CCN number concentration under low supersaturations (SSs) and the complex impact of the kinetic limitation in CCN measurements, size‐resolved CCN activity measurements at low SSs cannot be achieved with traditional methods using differential mobility analyzers and a CCN counter (CCNC) because of the low sample efficiency and the impact of particles with multiple charges. To overcome this difficulty, we propose a new method for measuring size‐resolved CCN activity at low aerosol number concentrations. The new method is based on a combined system comprising an aerodynamic aerosol classifier (AAC) and a CCNC (AAC‐CCNC system). A control program was developed to achieve high‐resolution scans of the SS and particle size within a reasonable time frame. A data inversion scheme, including corrections for the transfer function and kinetic limitation, was developed to obtain accurate size‐resolved CCN activity. In July‐August 2022, the new method was used to measure the size‐resolved CCN activity on the Tibetan Plateau. This new method can advance the size‐resolved CCN measurements, thereby enhancing our understanding of aerosol‐cloud interactions in pristine atmosphere.

Supersaturation and Critical Size of Cloud Condensation Nuclei in Marine Stratus Clouds

AbstractObservations of marine stratus clouds in clean air off the Californian coast reveal a functional relationship between the number of cloud condensation nuclei (CCN) and supersaturation. Satellite‐derived liquid droplet density estimates the number density of CCN. Combining the estimated supersaturation using Köhler theory, global maps of supersaturation and the critical activation size of CCN are estimated. Here, we show that high supersaturation >0.5% persists over the oceans with a critical CCN size of 25–30 nm, which is smaller than the conventional wisdom of 60 nm. Independent support for such high supersaturation in the marine cloud is obtained from CCN measurements provided by the “Atmospheric Tomography Mission.” Higher supersaturation implies smaller activation size for CCN making cloud formation more sensitive to changes in aerosol nucleation.

Effects of South Asian outflow on aerosol hygroscopicity and cloud droplet activation over the northern Indian Ocean

As a part of the Integrated Campaign for Aerosols, gases and Radiation Budget (ICARB-2018), shipborne measurements of aerosol properties were carried out to study the influence of South Asian outflow on cloud condensation nuclei (CCN) characteristics over the South East Arabian Sea (SEAS) and equatorial Indian Ocean (EIO) during winter, 2018. The poor association between CCN concentration and mass concentrations of the major aerosol species (organic matter, sulfate, and elemental carbon) is observed over SEAS, where airmass is mostly continental. In comparison, the CCN is well-correlated with aerosol mass concentrations over remote EIO. The dependence of CCN activation (at lower supersaturations) on the ultrafine particle fraction differs between SEAS and EIO depending on the mass concentration of organic aerosols. The coexistence of small and hydrophobic aerosols (organics) decreased the CCN activation ratio during ultrafine particle events. The hygroscopicity estimated using the chemical composition of aerosols is comparable to that estimated from CCN measurements over the Indian Ocean, except for the SEAS, where organic aerosols dominate. The effect of outflow aerosols on cloud droplet number concentration (CDNC) is simulated using a parcel model, which showed a good association (R ∼0.96) with CCN measurements over the EIO; however, the estimated CDNC did not follow the CCN variation over the SEAS region. This study highlights the importance of aerosol chemical composition, especially organics, in CCN activation and cloud droplet formation in the South Asian outflow over the Indian Ocean.

Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing

The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ, can be derived accurately from the fine aerosol mass fractions of organic particulate matter (ϵorg) and inorganic ions (ϵinorg) through a linear combination, κ = ϵorg ⋅ κorg + ϵinorg ⋅ κinorg. In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κorg = 0.12 ± 0.02 with κinorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κorg and κinorg is small, we constrain a critically important aspect of global climate modelling.

Cloud condensation nuclei activity of internally mixed particle populations at a remote marine free troposphere site in the North Atlantic Ocean

This study reports results from research conducted at the Observatory of Mount Pico (OMP), 2225 m above mean sea level on Pico Island in the Azores archipelago in June and July 2017. We investigated the chemical composition, mixing state, and cloud condensation nuclei (CCN) activities of long-range transported free tropospheric (FT) particles. FLEXible PARTicle Lagrangian particle dispersion model (FLEXPART) simulations reveal that most air masses that arrived at the OMP during the sampling period originated in North America and were highly aged (average plume age > 10 days). We probed size-resolved chemical composition, mixing state, and hygroscopicity parameter (κ) of individual particles using computer-controlled scanning electron microscopy with an energy-dispersive X-ray spectrometer (CCSEM-EDX). Based on the estimated individual particle mass from elemental composition, we calculated the mixing state index, χ. During our study, FT particle populations were internally mixed (χ of samples are between 53 % and 87 %), owing to the long atmospheric aging time. We used data from a miniature Cloud Condensation Nucleus Counter (miniCCNC) to derive the hygroscopicity parameter, κCCNC. Combining κCCNC and FLEXPART, we found that air masses recirculated above the North Atlantic Ocean with lower mean altitude had higher κCCNC due to the higher contribution of sea salt particles. We used CCSEM-EDX and phase state measurements to predict single-particle κ (κCCSEM-EDX) values, which overlap with the lower range of κCCNC measured below 0.15 % SS. Therefore, CCSEM-EDX measurements can be useful in predicting the lower bound of κ, which can be used in climate models to predict CCN activities, especially in remote locations where online CCN measurements are unavailable.

Rapid growth and high cloud-forming potential of anthropogenic sulfate aerosol in a thermal power plant plume during COVID lockdown in India

The COVID lockdown presented an interesting opportunity to study the anthropogenic emissions from different sectors under relatively cleaner conditions in India. The complex interplays of power production, industry, and transport could be dissected due to the significantly reduced influence of the latter two emission sources. Here, based on measurements of cloud condensation nuclei (CCN) activity and chemical composition of atmospheric aerosols during the lockdown, we report an episodic event resulting from distinct meteorological conditions. This event was marked by rapid growth and high hygroscopicity of new aerosol particles formed in the SO2 plume from a large coal-fired power plant in Southern India. These sulfate-rich particles had high CCN activity and number concentration, indicating high cloud-forming potential. Examining the sensitivity of CCN properties under relatively clean conditions provides important new clues to delineate the contributions of different anthropogenic emission sectors and further to understand their perturbations of past and future climate forcing.

Investigating the Applicability of a Global Average Calibration Line for Ambient Size-Resolved Cloud Condensation Nuclei (CCN) Measurements: A Technical Note

Abstract Aerosol–cloud–precipitation interaction represents the largest uncertainty in climate change’s current and future understanding. Therefore, aerosol properties affecting the cloud and precipitation formation and their accurate estimation is a first step in developing improved parameterizations for the prognostic climate models. Over the last couple of decades, a commercially available Cloud Condensation Nuclei Counter (CCNC) has been deployed in the field and laboratory for characterizing CCN properties of ambient or atmospherically relevant laboratory-generated aerosols. However, most of the CCN measurements performed in the field are often compounded with the erroneous estimation of CCN concentration and other parameters due to a lack of robust and accurate CCNC calibration. CCNC is not a plug-and-play instrument and requires prudent calibration and operation, to avoid erroneous data and added parameterization uncertainties. In this work, we propose and demonstrate the usability of a global calibration equation derived from CCNC calibration experiments from 8 contrasting global environments. Significant correlation was observed between the global calibration and each of the 16 individual experiments. A significant improvement in the correlation was observed when the calibration experiments were separated for high-altitude measurements. Using these equations, we further derived the effective hygroscopicity parameter and found lower relative uncertainty in the hygroscopicity parameter at higher effective supersaturation. Our results signify that altitude-based pressure change could be of importance for accurate calibration at high-altitude locations. Our results are consistent with previous studies emphasizing the criticality of the accurate CCN calibration for the lower supersaturations.

Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region

The estimation of cloud condensation nuclei (CCN) concentration at the cloud base is an essential constraint to aerosol-cloud interaction (ACI) studies. The long-term CCN measurements are sparse and difficult to obtain, which often led to the use of aerosol optical properties as proxies of CCN in ACI studies and remains the most significant uncertainty in numerical models and observational studies. In the present study, we estimate the height-resolved CCN from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) using Optical Modelling of CALIPSO Aerosol Microphysics (OMCAM) algorithm and validated the results with airborne in-situ CCN measurements collected during the Cloud Aerosol Interaction and Precipitation Enhanced Experiment (CAIPEEX) at six locations over the Indian Summer Monsoon (ISM) region. Out of 40 CAIPEEX flight measurements collected in the year of 2009, 15 profiles were selected for the validation of CALIPSO-derived CCN number concentrations (NCCN). We found a reasonable agreement between CALIPSO and the in-situ measurements with a correlation coefficient of 0.72. However, the overall comparison suggests that the CALIPSO overestimates the NCCN by 54 ± 33%. We further analyzed CALIPSO-derived NCCN for the in-situ stations. A strong seasonal variation of NCCN at SS 0.4% is observed in all six stations. The mean NCCN is maximum (minimum) during the post-monsoon (pre-monsoon) for Pathankot 2592 ± 1026 cm−3 (1636 ± 809 cm−3), Bareilly 3618 ± 1326 cm−3 (2078 ± 792 cm−3) stations whereas maximum (minimum) during winter (monsoon) for Guwahati 3696 ± 1400 cm−3 (2661 ± 1096 cm−3), Pune 3422 ± 1628 cm−3 (2241 ± 1086 cm−3), Hyderabad 3765 ± 1366 cm−3 (2498 ± 1084 cm−3) and Bangalore 2956 ± 1274 cm−3 (2401 ± 1071 cm−3).

Evaluation of aerosol–cloud interactions in E3SM using a Lagrangian framework

Abstract. A Lagrangian framework is used to evaluate aerosol–cloud interactions in the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 1 (E3SMv1) for measurements taken at Graciosa Island in the Azores where a U.S. Department of Energy Atmosphere Radiation Measurement (ARM) site is located. This framework uses direct measurements of cloud condensation nuclei (CCN) concentration (instead of relying on satellite retrievals of aerosol optical depth) and incorporates a suite of ground-based ARM measurements, satellite retrievals, and meteorological reanalysis products that when applied to over a 1500 trajectories provides key insights into the evolution of low-level clouds and aerosol radiative forcing that is not feasible from a traditional Eulerian analysis framework. Significantly lower concentrations (40 %) of surface CCN concentration are measured when precipitation rates in 48 h back trajectories average above 1.2 mm d−1 in the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product. The depletion of CCN concentration when precipitation rates are elevated is nearly twice as large in the ARM observations compared to E3SMv1 simulations. The model CCN concentration bias remains significant despite modifying the autoconversion and accretion rates in warm clouds. As the clouds in trajectories associated with larger surface-based CCN concentration advect away from Graciosa Island, they maintain higher values of droplet number concentrations (Nd) over multiple days in observations and E3SM simulations compared to trajectories that start with lower CCN concentrations. The response remains robust even after controlling for meteorological factors such as lower troposphere stability, the degree of cloud coupling with the surface, and island wake effects. E3SMv1 simulates a multi-day aerosol effect on clouds and a Twomey radiative effect that is within 30 % of the ARM and satellite observations. However, the mean cloud droplet concentration is more than 2–3 times larger than in the observations. While Twomey radiative effects are similar amongst autoconversion and accretion sensitivity experiments, the liquid water path and cloud fraction adjustments are positive when using a regression model as opposed to negative when using the present-day minus pre-industrial aerosol emissions approach. This result suggests that tuning the autoconversion and accretion alone is unlikely to produce the desired aerosol susceptibilities in E3SMv1.

Kinetic Limitations Affect Cloud Condensation Nuclei Activity Measurements Under Low Supersaturation

AbstractThe commercial continuous‐flow streamwise thermal‐gradient cloud condensation nuclei (CCN) counter is widely used in aerosol CCN activity measurements which are critical for investigating aerosol‐cloud interactions. In CCN measurements, a critical threshold is needed for distinguishing interstitial aerosols and activated droplets, and a default threshold of 0.75 μm was set in CCN counter. Theoretically, interstitial aerosols could also grow larger than 0.75 μm in CCN counter at low supersaturations, thus theoretical thresholds derived from the Köhler theory were suggested. Here, we report that droplet growth in the CCN counter is kinetically limited and CCN‐active droplets does not reach their theoretical diameters under low supersaturations. Neglecting the kinetic growth limitation in CCN identification would count less CCN and underestimate the aerosol hygroscopicity parameter by up to 50% for supersaturations lower than 0.1%. We recommend that thresholds considering kinetic limitations should be used as new criteria for CCN identification under low supersaturations.

Explicitly Modeling the Effects of Cloud Condensation Nuclei on Warm Rain Initiation

Abstract A bin (or spectral) model is developed to investigate the sensitivity of warm rain initiation to cloud condensation nuclei (CCN). It explicitly represents CCN with a formula whose parameters come from the Twomey relationship (or CCN measurements). By seamlessly integrating CCN activation and drop collection with thousands of bins, the model can replicate the effect of CCN on rain initiation, providing a benchmark to test the process parameterizations in rain initiation. The model is used to simulate two extreme cases with CCN parameters of maritime and continental clouds, respectively, where other actual cases usually lie between these two extreme cases. Its simulations show that rain can initiate within half an hour or less as observed in cumulus clouds. The fast rain initiation modeled is attributed mainly to a new process: the condensational conversion of cloud drops to raindrops via collision–coalescence initiators (or drops with radius between 28 and 100 μm). Since the new process is more important in rain initiation than the autoconversion of cloud drops to raindrops when large CCN exist, it is suggested that the process be parameterized into the weather and climate models to better represent CCN and subsequently remove the common bias of “too dense clouds.” Significance Statement The current weather and climate models represent aerosols via implicit parameterizations and have a bias of “too dense clouds.” Their implicit parameterizations of aerosols usually overlook (or misrepresent) some cloud processes. In this paper and its preceding part (Zeng and Li 2020) we proposed a new framework to explicitly parameterize one subset of aerosols: cloud condensation nuclei (CCN). To embody an explicit parameterization of CCN, we still need quantitative information to connect CCN activation and rain initiation, which motivates this study. In the study we developed an accurate microphysical model to simulate the growth of small CCN to large raindrops, providing information on the sensitivity of rain initiation to CCN. We performed many sensitivity simulations and found the condensational conversion of cloud drops to raindrops via collision–coalescence initiators is a vital process in warm rain initiation. Since the process has been overlooked by all the weather and climate models, the study suggests that the process be introduced in the weather and climate models to properly represent the fast warm rain initiation observed and subsequently remove the bias of “too dense clouds.”

Impact of urban aerosols on the cloud condensation activity using a clustering model

The indirect effect of aerosols on climate through aerosol-cloud-interactions is still highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is in the number of cloud condensation nuclei (CCN), which itself mainly stems from uncertainty in aerosol sources and how particles evolve to become effective CCN. We analyze particle number size distribution (PNSD) and CCN measurements from an urban site in a two-step method: (1) we use an unsupervised clustering model to classify the main aerosol categories and processes occurring in the urban atmosphere and (2) we explore the influence of the identified aerosol populations on the CCN properties. According to the physical properties of each cluster, its diurnal timing, and additional air quality parameters, the clusters are grouped into five main aerosol categories: nucleation, growth, traffic, aged traffic, and urban background. The results show that, despite aged traffic and urban background categories are those with lower total particle number concentrations (Ntot) these categories are the most efficient sources in terms of contribution to the overall CCN budget with activation fractions (AF) around 0.5 at 0.75 % supersaturation (SS). By contrast, road traffic is an important aerosol source with the highest frequency of occurrence (32 %) and relatively high Ntot, however, its impact in the CCN activity is very limited likely due to lower particle mean diameter and hydrophobic chemical composition. Similarly, nucleation and growth categories, associated to new particle formation (NPF) events, present large Ntot with large frequency of occurrence (22 % and 28 %, respectively) but the CCN concentration for these categories is about half of the CCN concentration observed for the aged traffic category, which is associated with their small size. Overall, our results show that direct influence of traffic emissions on the CCN budget is limited, however, when these particles undergo ageing processes, they have a significant influence on the CCN concentrations and may be an important CCN source. Thus, aged traffic particles could be transported to other environments where clouds form, triggering a plausible indirect effect of traffic emissions on aerosol-cloud interactions and consequently contributing to climate change.

Sensitivity analysis of an aerosol-aware microphysics scheme in Weather Research and Forecasting (WRF) during case studies of fog in Namibia

Abstract. Aerosol-aware microphysics parameterisation schemes are increasingly being introduced into numerical weather prediction models, allowing for regional and case-specific parameterisation of cloud condensation nuclei (CCN) and cloud droplet interactions. In this paper, the Thompson aerosol-aware microphysics scheme, within the Weather Research and Forecasting (WRF) model, is used for two fog cases during September 2017 over Namibia. Measurements of CCN and fog microphysics were undertaken during the AErosols, RadiatiOn and CLOuds in southern Africa (AEROCLO-sA) field campaign at Henties Bay on the coast of Namibia during September 2017. A key concept of the microphysics scheme is the conversion of water-friendly aerosols to cloud droplets (hereafter referred to as CCN activation), which could be estimated from the observations. A fog monitor 100 (FM-100) provided cloud droplet size distribution, number concentration (Nt), liquid water content (LWC), and mean volumetric diameter (MVD). These measurements are used to evaluate and parameterise WRF model simulations of Nt, LWC, and MVD. A sensitivity analysis was conducted through variations to the initial CCN concentration, CCN radius, and the minimum updraft speed, which are important factors that influence droplet activation in the microphysics scheme of the model. The first model scenario made use of the default settings with a constant initial CCN number concentration of 300 cm−3 and underestimated the cloud droplet number concentration, while the LWC was in good agreement with the observations. This resulted in droplet size being larger than the observations. Another scenario used modelled data as CCN initial conditions, which were an order of magnitude higher than other scenarios. However, these provided the most realistic values of Nt, LWC, MVD, and droplet size distribution. From this, it was concluded that CCN activation of around 10 % in the simulations is too low, while the observed appears to be higher reaching between 20 % and 80 %, with a mean (median) of 0.55 (0.56) during fog events. To achieve this level of activation in the model, the minimum updraft speed for CCN activation was increased from 0.01 to 0.1 m s−1. This scenario provided Nt, LWC, MVD, and droplet size distribution in the range of the observations, with the added benefit of a realistic initial CCN concentration. These results demonstrate the benefits of a dynamic aerosol-aware scheme when parameterised with observations.

Cloud condensation nuclei (CCN) activity analysis of low-hygroscopicity aerosols using the aerodynamic aerosol classifier (AAC)

Abstract. The aerodynamic aerosol classifier (AAC) is a novel instrument that size-selects aerosol particles based on their mechanical mobility. So far, the application of an AAC for cloud condensation nuclei (CCN) activity analysis of aerosols has yet to be explored. Traditionally, a differential mobility analyzer (DMA) is used for aerosol classification in a CCN experimental setup. A DMA classifies particles based on their electrical mobility. Substituting the DMA with an AAC can eliminate multiple-charging artifacts as classification using an AAC does not require particle charging. In this work, we describe an AAC-based CCN experimental setup and CCN analysis method. We also discuss and develop equations to quantify the uncertainties associated with aerosol particle sizing. To do so, we extend the AAC transfer function analysis and calculate the measurement uncertainties of the aerodynamic diameter from the resolution of the AAC. The analysis framework has been packaged into a Python-based CCN Analysis Tool (PyCAT 1.0) open-source code, which is available on GitHub for public use. Results show that the AAC size-selects robustly (AAC resolution is 10.1, diffusion losses are minimal, and particle transmission is high) at larger aerodynamic diameters (≥∼ 85 nm). The size-resolved activation ratio is ideally sigmoidal since no charge corrections are required. Moreover, the uncertainties in the critical particle aerodynamic diameter at a given supersaturation can propagate through droplet activation, and the subsequent uncertainties with respect to the single-hygroscopicity parameter (κ) are reported. For a known aerosol such as sucrose, the κ derived from the critical dry aerodynamic diameter can be up to ∼ 50 % different from the theoretical κ. In this work, we do additional measurements to obtain dynamic shape factor information and convert the sucrose aerodynamic to volume equivalent diameter. The volume equivalent diameter applied to κ-Köhler theory improves the agreement between measured and theoretical κ. Given the limitations of the coupled AAC–CCN experimental setup, this setup is best used for low-hygroscopicity aerosol (κ≤0.2) CCN measurements.

Hygroscopic growth and CCN activity of secondary organic aerosol produced from dark ozonolysis of γ-terpinene

The hygroscopic growth factor (GF) and cloud condensation nuclei (CCN) activity of secondary organic aerosol (SOA) particles produced during dark ozonolysis of γ-terpinene under different reaction conditions were investigated. The SOA particles were produced in the presence or absence of cyclohexane, an OH scavenger; 1,3,5-trimethylbenzene, an anthropogenic volatile organic compound; and (NH4)2SO4 seed particles. A hygroscopicity tandem differential mobility analyzer was used to determine the GFs of the SOA particles at RHs ≤ 93%. For some experiments, a CCN counter was used for size-resolved measurement of CCN activation at supersaturation (S) in the range of 0.1 to 1%. The single hygroscopicity parameter κ was derived from both the GF and CCN measurements. Under subsaturated conditions, all the SOA (except those in the presence of the (NH4)2SO4 seeds) showed small GF values. These GFs demonstrated that SOA mass loading affected the GF. A decrease in the SOA mass loading led to increased GF and corresponding κGFvalues. However, in a supersaturation regime, the SOA mass loading and the size of the particles did not significantly alter the CCN activity of the SOA. Our CCN measurements showed higher κCCN values (κCCN = 0.20–0.24) than those observed in most monoterpene ozonolysis studies (κCCN = 0.1–0.14). This difference may have been due to the presence of the two endocyclic double bonds in the γ-terpinene structure, which may have affected the SOA chemical composition, in contrast to monoterpenes that contain an exocyclic double bond. Our comparisons of sub- and supersaturated conditions showed a larger range of κ values than other experiments. Average κCCN/κGF ratios of ~7 and 14 were obtained in the unseeded SOA experiments at low and high SOA mass loadings, respectively. The average κCCN of 0.23 indicated that the SOA produced during ozonolysis of γ-terpinene exhibited fairly high CCN activity.

Airborne measurements of cloud condensation nuclei (CCN) vertical structures over Southern China

In this study, the vertical structures of cloud condensation nuclei (CCN) over southern China are investigated with two flight datasets during the period of 16–17 July 2019. The results show that the CCN number concentration (NCCN) increases first with the increasing height, peaking near 1.3 km above the ground, and then decreases sharply to a low value above 2.5 km. Good agreement is obtained by employing a segmentation fitting approach to describe the vertical CCN structure. More specifically a simple linear function is used to fit the NCCN below 1.3 km; a polynomial function is utilized to describe the measurements between 1.3 km and 2.5 km, and, a constant value of 7 cm−3 is assigned above 2.5 km. The CCN particle size distribution (CPSD) presents a unimodal mode with the peak that changes to the direction of larger diameter with growing water vapor supersaturation (SS). As for the effects of SS, NCCN, as well as the diameter of CCN increases with the increasing SS. The CCN spectrum is well represented by the classical Twomey power-law function of NCCN(SS) = C·SSk. Although the values of parameter C are 72 cm−3 and 150 cm−3 in the two measurements, respectively, the paramer k changes a little with its values being 1.5 or so. The results gained herein might be helpful for cloud microphysical parameterization in numerical models and provide a guide for weather modification.

Wetting properties of fresh urban soot particles: Evaluation based on critical supersaturation and observation of surface trace materials

Soot particles strongly absorb solar radiation and contribute to global warming. Also, wetting properties of soot at emission can affect its lifetime. We investigated surface conditions related to wetting and hydrophobic properties of fresh soot using data from measurements taken in Tokyo. A cloud condensation nuclei (CCN) counter was used to clarify surface conditions of particles composed mainly of water-insoluble (WI) materials: total and active particles as CCN around critical supersaturation (Sc) of 203-nm-diameter WI particles. Averaged number fractions of inactivated particles as CCN at 1.05% supersaturation (SS), which is Sc of hydrophilic WI particles, were estimated as 1.4%. Number fractions of inactive particles changed less at 1.78%SS during rush hour and increased at 0.89%SS, implying that most of the WI particles included small amounts of water-soluble (WS) materials rather than being completely hydrophobic. Based on transmission electron microscope (TEM) analysis of samples collected during rush hour, 69% of the mostly bare soot particles had Na or K small domains that are regarded as originating in fossil fuels. Based on water dialysis analysis results, some Na and K on soot were WS. Combination results with CCN measurements suggest that these WS materials decrease the Sc of soot. Moreover, the morphological structure of sulfate covering Na and K domains on the soot surface implicates pre-existing sodium and potassium compounds on soot as a trigger of soot aging. However, inactive particles at Sc at poor-hydrophilic particles and soot particles composed solely of WI materials on TEM samples were also found, although they were minor. Such particles, which are unfavorable for obtaining a wettable surface, might retain non-hygroscopicity for a longer period in the atmosphere. Evaluation of long-range soot transport can benefit from consideration of slight and inhomogeneous differences of chemical compounds on soot that occur along with their emission.

Calibration and evaluation of a broad supersaturation scanning (BS2) cloud condensation nuclei counter for rapid measurement of particle hygroscopicity and cloud condensation nuclei (CCN) activity

Abstract. For understanding and assessing aerosol–cloud interactions and their impact on climate, reliable measurement data on aerosol particle hygroscopicity and cloud condensation nuclei (CCN) activity are required. The CCN activity of aerosol particles can be determined by scanning particle size and supersaturation (S) in CCN measurements. Compared to an existing differential mobility analyzer (DMA) with CCN activity measurement, a broad supersaturation scanning CCN (BS2-CCN) system, in which particles are exposed to a range of S simultaneously, can measure the CCN activity with a high time resolution. Based on a monotonic relation between the activation supersaturation of aerosol particles (Saerosol) and the activated fraction (Fact) of the BS2-CCN measurement, we can derive κ, a single hygroscopicity parameter, directly. Here, we describe how the BS2-CCN system can be effectively calibrated and which factors can affect the calibration curve (Fact−Saerosol). For calibration, size-resolved CCN measurements with ammonium sulfate and sodium chloride particles are performed under three different thermal gradient (dT) conditions (dT=6, 8, and 10 K). We point out key processes that can affect the calibration curve and thereby need to be considered as follows: first, the shape of the calibration curve is primarily influenced by Smax, the maximum S in the activation tube. We need to determine appropriate Smax depending on the particle size and κ to be investigated. To minimize the effect of multiply charged particles, a small geometric mean diameter (Dg) and geometric standard deviation (σg) in number size distribution are recommended when generating the calibration aerosols. Last, Fact is affected by particle number concentration and has a decreasing rate of 0.02 per 100 cm−3 due to the water consumption in the activation tube. For evaluating the BS2-CCN system, intercomparison experiments between typical DMA-CCN and BS2-CCN measurements were performed with a laboratory-generated aerosol mixture and ambient aerosols. Good agreement of κ values between DMA-CCN and BS2-CCN measurements for both experiments shows that the BS2-CCN system can measure CCN activity well compared to the existing measurement method and can measure a broad range of hygroscopicity distributions with a high time resolution (∼1 s vs. a few minutes for a standard CCN activity measurement). As the hygroscopicity can be used as a proxy for the chemical composition, our method can also serve as a complementary approach for fast and size-resolved detection and estimation of aerosol chemical composition.

Relationship between cloud condensation nuclei (CCN) concentration and aerosol optical depth in the Arctic region

To determine the direct and indirect effects of aerosols on climate, it is important to know the spatial and temporal variations in cloud condensation nuclei (CCN) concentrations. Although many types of CCN measurements are available, extensive CCN measurements are challenging because of the complexity and high operating cost, especially in remote areas. As aerosol optical depth (AOD) can be readily observed by remote sensing, many attempts have been made to estimate CCN concentrations from AOD. In this study, the CCN–AOD relationship is parameterized based on CCN ground measurements from the Zeppelin Observatory (78.91° N, 11.89° E, 474 m asl) in the Arctic region. The AOD measurements were obtained from the Ny-Ålesund site (78.923° N, 11.928° E) and Modern-Era Retrospective Analysis for Research and Applications, Version 2 reanalysis. Our results show a CCN–AOD correlation with a coefficient of determination R2 of 0.59. Three additional estimation models for CCN were presented based on the following data: (i) in situ aerosol chemical composition, (ii) in situ aerosol optical properties, and (iii) chemical composition of AOD obtained from reanalysis data. The results from the model using in situ aerosol optical properties reproduced the observed CCN concentration most efficiently, suggesting that the contribution of BC to CCN concentration should be considered along with that of sulfate.