2010, Duplissy, J., Enghoff, M.B., Aplin, K.L., Arnold, F., Aufmhoff, H., Avngaard, M., Baltensperger, U., Bondo, T., Bingham, R., Carslaw, K., Curtius, J., David, A., Fastrup, B., Gagné, S., Hahn, F., Harrison, R.G., Kellett, B., Kirkby, J., Kulmala, M., Laakso, L., Laaksonen, A., Lillestol, E., Lockwood, M., Mäkelä, J., Makhmutov, V., Marsh, N.D., Nieminen, T., Onnela, A., Pedersen, E., Pedersen, J.O.P., Polny, J., Reichl, U., Seinfeld, J.H., Sipilä, M., Stozhkov, Y., Stratmann, F., Svensmark, H., Svensmark, J., Veenhof, R., Verheggen, B., Viisanen, Y., Wagner, P.E., Wehrle, G., Weingartner, E., Wex, H., Wilhelmsson, M., Winkler, P.M.

During a 4-week run in October–November 2006, a pilot experiment was performed at the CERN Proton Synchrotron in preparation for the Cosmics Leaving OUtdoor Droplets (CLOUD) experiment, whose aim is to study the possible influence of cosmic rays on clouds. The purpose of the pilot experiment was firstly to carry out exploratory measurements of the effect of ionising particle radiation on aerosol formation from trace H2SO4 vapour and secondly to provide technical input for the CLOUD design. A total of 44 nucleation bursts were produced and recorded, with formation rates of particles above the 3 nm detection threshold of between 0.1 and 100 cm−3s−1, and growth rates between 2 and 37 nm h−1. The corresponding H2O concentrations were typically around 106 cm−3 or less. The experimentally-measured formation rates and \htwosofour concentrations are comparable to those found in the atmosphere, supporting the idea that sulphuric acid is involved in the nucleation of atmospheric aerosols. However, sulphuric acid alone is not able to explain the observed rapid growth rates, which suggests the presence of additional trace vapours in the aerosol chamber, whose identity is unknown. By analysing the charged fraction, a few of the aerosol bursts appear to have a contribution from ion-induced nucleation and ion-ion recombination to form neutral clusters. Some indications were also found for the accelerator beam timing and intensity to influence the aerosol particle formation rate at the highest experimental SO2 concentrations of 6 ppb, although none was found at lower concentrations. Overall, the exploratory measurements provide suggestive evidence for ion-induced nucleation or ion-ion recombination as sources of aerosol particles. However in order to quantify the conditions under which ion processes become significant, improvements are needed in controlling the experimental variables and in the reproducibility of the experiments. Finally, concerning technical aspects, the most important lessons for the CLOUD design include the stringent requirement of internal cleanliness of the aerosol chamber, as well as maintenance of extremely stable temperatures (variations below 0.1 °C

2015, Worringen, A., Kandler, K., Benker, N., Dirsch, T., Mertes, S., Schenk, L., Kästner, U., Frank, F., Nillius, B., Bundke, U., Rose, D., Curtius, J., Kupiszewski, P., Weingartner, E., Vochezer, P., Schneider, J., Schmidt, S., Weinbruch, S., Ebert, M.

In the present work, three different techniques to separate ice-nucleating particles (INPs) as well as ice particle residuals (IPRs) from non-ice-active particles are compared. The Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI) sample ice particles from mixed-phase clouds and allow after evaporation in the instrument for the analysis of the residuals. The Fast Ice Nucleus Chamber (FINCH) coupled with the Ice Nuclei Pumped Counterflow Virtual Impactor (IN-PCVI) provides ice-activating conditions to aerosol particles and extracts the activated particles for analysis. The instruments were run during a joint field campaign which took place in January and February 2013 at the High Alpine Research Station Jungfraujoch (Switzerland). INPs and IPRs were analyzed offline by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine their size, chemical composition and mixing state. Online analysis of the size and chemical composition of INP activated in FINCH was performed by laser ablation mass spectrometry. With all three INP/IPR separation techniques high abundances (median 20–70%) of instrumental contamination artifacts were observed (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH + IN-PCVI: steel particles). After removal of the instrumental contamination particles, silicates, Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types obtained by all three techniques. In addition, considerable amounts (median abundance mostly a few percent) of soluble material (e.g., sea salt, sulfates) were observed. As these soluble particles are often not expected to act as INP/IPR, we consider them as potential measurement artifacts. Minor types of INP/IPR include soot and Pb-bearing particles. The Pb-bearing particles are mainly present as an internal mixture with other particle types. Most samples showed a maximum of the INP/IPR size distribution at 200–400 nm in geometric diameter. In a few cases, a second supermicron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the sub-micrometer range. Silicates and Ca-rich particles were mainly found with diameters above 1 μm (using ISI and FINCH), in contrast to the Ice-CVI which also sampled many submicron particles of both groups. Due to changing meteorological conditions, the INP/IPR composition was highly variable if different samples were compared. Thus, the observed discrepancies between the different separation techniques may partly result from the non-parallel sampling. The differences of the particle group relative number abundance as well as the mixing state of INP/IPR clearly demonstrate the need of further studies to better understand the influence of the separation techniques on the INP/IPR chemical composition. Also, it must be concluded that the abundance of contamination artifacts in the separated INP and IPR is generally large and should be corrected for, emphasizing the need for the accompanying chemical measurements. Thus, further work is needed to allow for routine operation of the three separation techniques investigated.

2015, Hiranuma, N., Augustin-Bauditz, S., Bingemer, H., Budke, C., Curtius, J., Danielczok, A., Diehl, K., Dreischmeier, K., Ebert, M., Frank, F., Hoffmann, N., Kandler, K., Kiselev, A., Koop, T., Leisner, T., Möhler, O., Nillius, B., Peckhaus, A., Rose, D., Weinbruch, S., Wex, H., Boose, Y., DeMott, P.J., Hader, J.D., Hill, T.C.J., Kanji, Z.A., Kulkarn, G., Levin, E.J.T., McCluskey, C.S., Murakami, M., Murray, B.J., Niedermeier, D., Petters, M.D., O'Sullivan, D., Saito, A., Schill, G.P., Tajiri, T., Tolbert, M.A., Welti, A., Whale, T.F., Wright, T.P., Yamashita, K.

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.