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Ice nucleating particles (INPs) influence the timing and amount of precipitation in mixed-phase clouds by acting as seeds for supercooled liquid droplets to form ice upon. High-resolution, long-term measurements of ice nucleating particles (INPs) have been impeded by complex instrumentation that requires a trained on-site technician to operate or analyze offline. We have significantly updated the well-characterized continuous flow diffusion chamber (CFDC) instrument to run autonomously with minimal in-person handling and easy remote access. This new CFDC, the CFDC-Ice Activation Spectrometer (CFDC-IAS) was deployed for four months (October 2020–January 2021) at the mountain-top Storm Peak Laboratory site in Colorado and provided 5-minute resolution measurements daily at target temperatures of -20, -25, and -30 °C. Concentrations of INPs across all temperatures had a median value of 6 per standard liter (sL-1), and a mean of 10 sL-1 with a range of ~0–470 sL-1. The CFDC-IAS was served once a week by a technician who changed out diffusion dryer desiccant and replaced the nitrogen tank as needed, and otherwise was operated remotely for desired changes in the sampling routine.

When aerosol particles seed the formation of liquid water droplets in the atmosphere, they are called cloud condensation nuclei (CCN). Different aerosols will act as CCN under different degrees of water supersaturation (relative humidity above 100 %), depending on their size and composition. In this work, we build and analyze a best-estimate CCN spectrum product, tabulated at ∼ 45 min resolution, generated using high quality data from seven independent instruments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The data product spans a large supersaturation range, from 0.0001 % to ∼ 30 %, and time period of 5 years, from 2009–2013, and is available on the ARM data archive. We leverage this added statistical power to examine relationships that are unclear in smaller datasets. Our analysis is performed in three main areas. First, probability distributions of many aerosol and CCN metrics are found to exhibit skewed log-normal distribution shapes. Second, clustering analyses of CCN spectra reveal that the primary drivers of CCN differences are aerosol number size distributions, rather than hygroscopicity or composition, especially at supersaturations above 0.2 %, while also allowing for a simplified understanding of seasonal and diurnal variations in CCN behavior. The predictive ability of using limited hygroscopicity data with accurate number size distributions to estimate CCN spectra is investigated, and the uncertainties of this approach are estimated. Third, the dynamics of CCN spectral clusters and concentrations are examined with cross-correlation and autocorrelation analyses. We find that CCN concentrations change rapidly on the timescale of 1–3 h, with some conservation beyond that which is greatest for the lower supersaturation region of the spectrum.

High-resolution, long-term measurements of ice nucleating particles (INPs) have been impeded by complex instrumentation that requires a trained on-site technician to operate or analyze offline. We have significantly updated the well-characterized continuous flow diffusion chamber (CFDC) instrument to run autonomously with minimal in-person handling and easy remote access. This new CFDC, the CFDC-Ice Activation Spectrometer (CFDC-IAS) was deployed for four months (October 2020–January 2021) at the mountain-top Storm Peak Laboratory site in Colorado and provided 5-minute resolution measurements daily at target temperatures of −20, −25, and −30 °C. Concentrations of INPs across all temperatures had a median value of 6 per standard liter (sL−1), and a mean of 10 sL−1 with a range of ~0–470 sL−1.

When aerosol particles seed formation of liquid water droplets in the atmosphere, they are called cloud condensation nuclei (CCN). Different aerosols will act as CCN under different degrees of water supersaturation (relative humidity above 100 %) depending on their size and composition. In this work we build and analyze a best-estimate CCN spectrum product, tabulated at ~45 min resolution, generated using high quality data from eight independent instruments at the US Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The data product spans a large supersaturation range, from 0.0001 to ~30 %, and time period, 5 years from 2009–2013 and is available on the ARM data archive. We leverage this added statistical power to examine relationships that are unclear in smaller datasets. Probability distributions of many aerosol and CCN metrics are found to exhibit skewed log-normal distribution shapes. Clustering analyses of CCN spectra reveal that the primary drivers of CCN differences are aerosol number size distributions, rather than hygroscopicity or composition, especially at supersaturations above 0.2 %, while also allowing for simplified understanding of seasonal and diurnal variations in CCN behaviour. The predictive ability of using limited hygroscopicity data with accurate number size distributions to estimate CCN spectra is investigated and uncertainties of this approach are estimated. Finally, the dynamics of CCN spectral clusters and concentrations are examined with cross-correlation and autocorrelation analyses, which assist in determining the time scales of changing CCN concentrations at different supersaturations and are important for cloud modelling studies.

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

A major component of California’s yearly precipitation comes from wintertime atmospheric river (AR) events which bring large amounts of moisture from the tropics up to the midlatitudes. Understanding these systems, specifically the effects of aerosol particles on precipitation associated with these storms, was a major focus of the 2015 Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), which was part of the wintertime CalWater 2015 campaign. The measurement campaign provided sampling platforms on four aircraft, including the ARM Aerial Facility G-1, as well as the NOAA Ronald H.Brown research vessel and at a ground station in Bodega Bay, CA. Measurements of ice nucleating particles (INPs) were made with the Colorado State University (CSU) Continuous Flow Diffusion Chamber (CFDC) aboard the G-1, and Aerosol filters were collected on the G-1, at the Bodega Bay site and on the Ronald H.Brown for post-processing via immersion freezing in the CSU Ice Spectrometer. Aerosol composition was measured aboard the G-1with the Aerosol Time-of-Flight Mass Spectrometer (ATOFMS). Here we present INP concentrati ons and aerosol chemical compositions during the course of the aircraft campaign. During the AR event, we found that marine aerosol was the main aerosol type and that marine INPs were dominant at cloud activation temperatures, which is in stark contrast to the dominance of dust INPs during the AR events in the CalWater 2011 campaign.

Ice nucleation is a fundamental atmospheric process that impacts precipitation, cloud lifetimes, and climate. Challenges remain to identify and quantify the compositions and sources of ice-nucleating particles (INPs). Assessment of the role of black carbon (BC) as an INP is particularly important due to its anthropogenic sources and abundance at upper-tropospheric cloud levels. The role of BC as an INP, however, is unclear. This is, in part, driven by a lack of techniques that directly determine the contribution of refractory BC (rBC) to INP concentrations. One previously developed technique to measure this contribution uses the Single Particle Soot Photometer (SP2) as a pre-filter to an online ice-nucleating particle counter. In this technique, rBC particles are selectively heated to their vaporization temperature in the SP2 cavity by a 1064 nm laser. From previous work, however, it is unclear under what SP2 conditions, if any, the original rBC particles were fully vaporized. Furthermore, previous work also left questions about the effect of the SP2 laser on the ice-nucleating properties of several INP proxies and their mixtures with rBC. To answer these questions, we sampled the exhaust of an SP2 with a Scanning Mobility Particle Sizer and a Continuous Flow Diffusion Chamber. Using Aquadag® as an rBC proxy, the effect of several SP2 instrument parameters on the size distribution and physical properties of particles in rBC SP2 exhaust were explored. We found that a high SP2 laser power (930 nW∕(220 nm PSL)) is required to fully vaporize a ∼ 0.76 fg rBC particle. We also found that the exhaust particle size distribution is minimally affected by the SP2 sheath-to-sample ratio; the size of the original rBC particle, however, greatly influences the size distribution of the SP2 exhaust. The effect of the SP2 laser on the ice nucleation efficiency of Snomax®, NX-illite, and Suwannee River Fulvic Acid was studied; these particles acted as proxies for biological, illite-rich mineral dust, and brown carbon INPs, respectively. The original size distribution and ice nucleation efficiency of all non-rBC proxies were unaffected by the SP2 laser. Furthermore, the ice nucleation efficiencies of all proxies were not affected when externally mixed with rBC. These proxies, however, always show a reduction in ice-nucleating ability when internally mixed with rBC. We end this work with recommendations for users who wish to use the SP2 as a pre-filter to remove large rBC particles from an aerosol stream.

Agricultural activities can modify natural ecosystems and change the nature of the aerosols emitted from those landscapes. The harvesting of crops can loft plant fragments and soil dust into the atmosphere that can travel long distances and interact with clouds far from their sources. In this way harvesting may contribute substantially to ice nucleating particle (INP) concentrations, especially in regions where agriculture makes up a large percentage of land use. However, a full characterization of particles emitted during harvesting has not been reported. This study characterizes immersion mode INPs emitted during harvesting of several crops in the High Plains region of the United States. The Colorado State University Continuous Flow Diffusion Chamber (CFDC) and the Ice Spectrometer (IS) were utilized to measure INP concentrations during active harvesting of four crops in Kansas and Wyoming. Large spikes of INPs were observed during harvesting, with concentrations over 200 L−1 at −30 °C measured during a wheat harvest. To differentiate between mineral and organic components, a novel heating tube method was employed in real-time upstream of the CFDC to deactivate organic INPs in-situ. The results indicate that harvesting produces a complex mixture of organic, soil dust, and mineral components that varies for different crops. Electron microscopy analysis showed that while mineral components made up a large proportion of INPs, organic components comprised over 40 % of measured INPs for certain crops at warm temperatures. Heating and enzyme post-treatment of aerosol samples collected for IS processing indicated that bacteria, heat-labile, and heat-stable organics contributed to wheat harvest-produced INPs. These results indicate that plant material and organic particles are a significant component of harvest INPs and their impacts on ice formation in clouds and precipitation on a regional scale should be explored.

We have developed a new method to determine ice nucleating particle (INP) concentrations observed by the Texas A&M University continuous flow diffusion chamber (CFDC) under a wide range of operating conditions. In this study, we evaluate differences in particle optical properties detected by the Cloud and Aerosol Spectrometer with POLarization (CASPOL) to differentiate between ice crystals, droplets, and aerosols. The depolarization signal from the CASPOL instrument is used to determine the occurrence of water droplet breakthrough (WDBT) conditions in the CFDC. The standard procedure for determining INP concentration is to count all particles that have grown beyond a nominal size cutoff as ice crystals. During WDBT this procedure overestimates INP concentration, because large droplets are miscounted as ice crystals. Here we design a new analysis method based on depolarization ratio that can extend the range of operating conditions of the CFDC. The method agrees reasonably well with the traditional method under non-WDBT conditions with a mean percent error of ±32.1 %. Additionally, a comparison with the Colorado State University CFDC shows that the new analysis method can be used reliably during WDBT conditions.

Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques. Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, ns, to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C < T < −11 °C) and covers 9 orders of magnitude in ns. In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 °C in terms of temperature, by 3 orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency expressed in ns of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns(T) spectra and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. While the agreement between different instruments was reasonable below ~ −27 °C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance, the ice nucleation activity expressed in ns was smaller for the average of the wet suspended samples and higher for the average of the dry-dispersed aerosol samples between about −27 and −18 °C. Only instruments making measurements with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −27 and −18 °C is discussed. Multiple exponential distribution fits in both linear and log space for both specific surface area-based ns(T) and geometric surface area-based ns(T) are provided. These new fits, constrained by using identical reference samples, will help to compare IN measurement methods that are not included in the present study and IN data from future IN instruments.

During the 2006 FLAME study (Fire Laboratory at Missoula Experiment), laboratory burns of biomass fuels were performed to investigate the physico-chemical, optical, and hygroscopic properties of fresh biomass smoke. As part of the experiment, two nephelometers simultaneously measured dry and humidified light scattering coefficients (bsp(dry) and bsp(RH), respectively) in order to explore the role of relative humidity (RH) on the optical properties of biomass smoke aerosols. Results from burns of several biomass fuels from the west and southeast United States showed large variability in the humidification factor (f(RH)=bsp(RH)/bsp(dry)). Values of f(RH) at RH=80–85% ranged from 0.99 to 1.81 depending on fuel type. We incorporated measured chemical composition and size distribution data to model the smoke hygroscopic growth to investigate the role of inorganic compounds on water uptake for these aerosols. By assuming only inorganic constituents were hygroscopic, we were able to model the water uptake within experimental uncertainty, suggesting that inorganic species were responsible for most of the hygroscopic growth. In addition, humidification factors at 80–85% RH increased for smoke with increasing inorganic salt to carbon ratios. Particle morphology as observed from scanning electron microscopy revealed that samples of hygroscopic particles contained soot chains either internally or externally mixed with inorganic potassium salts, while samples of weak to non-hygroscopic particles were dominated by soot and organic constituents. This study provides further understanding of the compounds responsible for water uptake by young biomass smoke, and is important for accurately assessing the role of smoke in climate change studies and visibility regulatory efforts.

As part of the Fire Lab at Missoula Experiments (FLAME) in 2006–2007, we examined hygroscopic properties of particles emitted from open combustion of 33 select biomass fuels. Measurements of humidification growth factors for subsaturated water relative humidity (RH) conditions were made with a hygroscopic tandem differential mobility analyzer (HTDMA) for dry particle sizes of 50, 100 and 250 nm. Results were then fit to a single-parameter model to obtain the hygroscopicity parameter, κ. Particles in freshly emitted biomass smoke exhibited a wide range of hygroscopicity (individual modes with 02.5 filter samples. Despite aerosol heterogeneity, reconstructions of κ using PM2.5 bulk chemical composition data fell along a 1:1 line with measured ensemble κ values.

第6回極域科学シンポジウム[OM] 極域気水圏11月16日（月） 統計数理研究所 セミナー室2（D304）

Article, New particle formation (NPF) is an important atmospheric phenomenon. During an NPF event, particles first form by nucleation and then grow further in size. The growth step is crucial because it controls the number of particles that can become cloud condensation nuclei. Among various physical and chemical processes contributing to particle growth, condensation by organic vapors has been suggested as important. In order to better understand the influence of biogenic emissions on particle growth, we carried out modeling studies of NPF events during the BEACHON-ROCS (Bio–hydro–atmosphere interactions of Energy, Aerosol, Carbon, H2O, Organics & Nitrogen – Rocky Mountain Organic Carbon Study) campaign at Manitou Experimental Forest Observatory in Colorado, USA. The site is representative of the semi-arid western USA. With the latest Criegee intermediate reaction rates implemented in the chemistry scheme, the model underestimates sulfuric acid concentration by 50 %, suggesting either missing sources of atmospheric sulfuric acid or an overestimated sink term. The results emphasize the contribution from biogenic volatile organic compound emissions to particle growth by demonstrating the effects of the oxidation products of monoterpenes and 2-Methyl-3-buten-2-ol (MBO). Monoterpene oxidation products are shown to influence the nighttime particle loadings significantly, while their concentrations are insufficient to grow the particles during the day. The growth of ultrafine particles in the daytime appears to be closely related to the OH oxidation products of MBO., published version, http://purl.org/eprint/status/PeerReviewed

The Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) project seeks to understand the feedbacks and inter-relationships between hydrology, biogenic emissions, carbon assimilation, aerosol properties, clouds and associated feedbacks within water-limited ecosystems. The Manitou Experimental Forest Observatory (MEFO) was established in 2008 by the National Center for Atmospheric Research to address many of the BEACHON research objectives, and it now provides a fixed field site with significant infrastructure. MEFO is a mountainous, semi-arid ponderosa pine-dominated forest site that is normally dominated by clean continental air but is periodically influenced by anthropogenic sources from Colorado Front Range cities. This article summarizes the past and ongoing research activities at the site, and highlights some of the significant findings that have resulted from these measurements. These activities include - soil property measurements; - hydrological studies; - measurements of high-frequency turbulence parameters; - eddy covariance flux measurements of water, energy, aerosols and carbon dioxide through the canopy; - determination of biogenic and anthropogenic volatile organic compound emissions and their influence on regional atmospheric chemistry; - aerosol number and mass distributions; - chemical speciation of aerosol particles; - characterization of ice and cloud condensation nuclei; - trace gas measurements; and - model simulations using coupled chemistry and meteorology. In addition to various long-term continuous measurements, three focused measurement campaigns with state-of-the-art instrumentation have taken place since the site was established, and two of these studies are the subjects of this special issue: BEACHON-ROCS (Rocky Mountain Organic Carbon Study, 2010) and BEACHON-RoMBAS (Rocky Mountain Biogenic Aerosol Study, 2011).

Recent research has shown that secondary organic aerosols (SOA) are major contributors to ultrafine particle growth to climatically relevant sizes, increasing global cloud condensation nuclei (CCN) concentrations within the continental boundary layer (BL). However, there are three recent developments regarding the condensation of SOA that lead to uncertainties in the contribution of SOA to particle growth and CCN concentrations: (1) while many global models contain only biogenic sources of SOA (with annual production rates generally 10–30 Tg yr−1), recent studies have shown that an additional source of SOA around 100 Tg yr−1 correlated with anthropogenic carbon monoxide (CO) emissions may be required to match measurements. (2) Many models treat SOA solely as semi-volatile, which leads to condensation of SOA proportional to the aerosol mass distribution; however, recent closure studies with field measurements show nucleation mode growth can be captured only if it is assumed that a significant fraction of SOA condenses proportional to the Fuchs-corrected aerosol surface area. This suggests a very low volatility of the condensing vapors. (3) Other recent studies of particle growth show that SOA condensation deviates from Fuchs-corrected surface-area condensation at sizes smaller than 10 nm and that size-dependent growth rate parameterizations (GRP) are needed to match measurements. We explore the significance of these three findings using GEOS-Chem-TOMAS global aerosol microphysics model and observations of aerosol size distributions around the globe. The change in the concentration of particles of size Dp > 40 nm (N40) within the BL assuming surface-area condensation compared to mass-distribution net condensation yielded a global increase of 11% but exceeded 100% in biogenically active regions. The percent change in N40 within the BL with the inclusion of the additional 100 Tg SOA yr−1 compared to the base simulation solely with biogenic SOA emissions (19 Tg yr−1) both using surface area condensation yielded a global increase of 13.7%, but exceeded 50% in regions with large CO emissions. The inclusion of two different GRPs in the additional-SOA case both yielded a global increase in N40 of < 1%, however exceeded 5% in some locations in the most extreme case. All of the model simulations were compared to measured data obtained from diverse locations around the globe and the results confirmed a decrease in the model-measurement bias and improved slope for comparing modeled to measured CCN number concentration when non-volatile SOA was assumed and the extra SOA was included.