Sea spray aerosol (SSA) generated by bubble bursting at the ocean surface is an important component of aerosol‐cloud interactions over remote oceans, providing the atmosphere with ice‐nucleating particles (INPs) or particles required for heterogeneous ice nucleation. Studies have shown that organic INPs are emitted during phytoplankton blooms, but changes in INP number concentrations (nINPs) due to ocean biological activity have not been directly demonstrated in natural SSA. In this study, a clean sector sampler was used to differentiate ice nucleation and composition of pristine SSA from terrestrial aerosol at the Mace Head Research Station in August 2015. Average nINPs active at −15 °C (nINPs,−15 °C) were 0.0011 L−1, and large variability (up to a factor of 200) was observed for INPs active warmer than −22 °C. Highest nINPs in the clean sector occurred during a period of elevated marine organic aerosol from offshore biological activity (M1, nINPs,−15 °C = 0.0077 L−1). A peak in nINPs was also observed in terrestrial organic aerosol (T1, nINPs,−15 °C = 0.0076 L−1). The impacts of heating and hydrogen peroxide digestion on nINPs indicate that INPs at Mace Head Research Station were largely organic and that INPs observed during M1 and T1 were biological (i.e., protein containing). Complexities of predicting increases in nINPs due to offshore biological activity are explored. A parameterization for pristine SSA INPs over the North Atlantic Ocean was developed, illustrating that SSA is associated with a factor of 1,000 fewer ice‐nucleating sites per surface area of aerosol compared to mineral dust.

Abstract. The second phase of the Fifth International Ice Nucleation Workshop (FIN-02) involved the gathering of a large number of researchers at the Karlsruhe Institute of Technology's Aerosol Interactions and Dynamics of the Atmosphere (AIDA) facility to promote characterization and understanding of ice nucleation measurements made by a variety of methods used worldwide. Compared to the previous workshop in 2007, participation was doubled, reflecting a vibrant research area. Experimental methods involved sampling of aerosol particles by direct processing ice nucleation measuring systems from the same volume of air in separate experiments using different ice nucleating particle (INP) types, and collections of aerosol particle samples onto filters or into liquid for sharing amongst measurement techniques that post-process these samples. In this manner, any errors introduced by differences in generation methods when samples are shared across laboratories were mitigated. Furthermore, as much as possible, aerosol particle size distribution was controlled so that the size limitations of different methods were minimized. The results presented here use data from the workshop to assess the comparability of immersion freezing measurement methods activating INPs in bulk suspensions, methods that activate INPs in condensation and/or immersion freezing modes as single particles on a substrate, continuous flow diffusion chambers (CFDCs) directly sampling and processing particles well above water saturation to maximize immersion and subsequent freezing of aerosol particles, and expansion cloud chamber simulations in which liquid cloud droplets were first activated on aerosol particles prior to freezing. The AIDA expansion chamber measurements are expected to be the closest representation to INP activation in atmospheric cloud parcels in these comparisons, due to exposing particles freely to adiabatic cooling. The different particle types used as INPs included the minerals illite NX and potassium feldspar (K-feldspar), two natural soil dusts representative of arable sandy loam (Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively, and a bacterial INP (Snomax®). Considered together, the agreement among post-processed immersion freezing measurements of the numbers and fractions of particles active at different temperatures following bulk collection of particles into liquid was excellent, with possible temperature uncertainties inferred to be a key factor in determining INP uncertainties. Collection onto filters for rinsing versus directly into liquid in impingers made little difference. For methods that activated collected single particles on a substrate at a controlled humidity at or above water saturation, agreement with immersion freezing methods was good in most cases, but was biased low in a few others for reasons that have not been resolved, but could relate to water vapor competition effects. Amongst CFDC-style instruments, various factors requiring (variable) higher supersaturations to achieve equivalent immersion freezing activation dominate the uncertainty between these measurements, and for comparison with bulk immersion freezing methods. When operated above water saturation to include assessment of immersion freezing, CFDC measurements often measured at or above the upper bound of immersion freezing device measurements, but often underestimated INP concentration in comparison to an immersion freezing method that first activates all particles into liquid droplets prior to cooling (the PIMCA-PINC device, or Portable Immersion Mode Cooling chAmber–Portable Ice Nucleation Chamber), and typically slightly underestimated INP number concentrations in comparison to cloud parcel expansions in the AIDA chamber; this can be largely mitigated when it is possible to raise the relative humidity to sufficiently high values in the CFDCs, although this is not always possible operationally. Correspondence of measurements of INPs among direct sampling and post-processing systems varied depending on the INP type. Agreement was best for Snomax® particles in the temperature regime colder than −10 ∘C, where their ice nucleation activity is nearly maximized and changes very little with temperature. At temperatures warmer than −10 ∘C, Snomax® INP measurements (all via freezing of suspensions) demonstrated discrepancies consistent with previous reports of the instability of its protein aggregates that appear to make it less suitable as a calibration INP at these temperatures. For Argentinian soil dust particles, there was excellent agreement across all measurement methods; measures ranged within 1 order of magnitude for INP number concentrations, active fractions and calculated active site densities over a 25 to 30 ∘C range and 5 to 8 orders of corresponding magnitude change in number concentrations. This was also the case for all temperatures warmer than −25 ∘C in Tunisian dust experiments. In contrast, discrepancies in measurements of INP concentrations or active site densities that exceeded 2 orders of magnitude across a broad range of temperature measurements found at temperatures warmer than −25 ∘C in a previous study were replicated for illite NX. Discrepancies also exceeded 2 orders of magnitude at temperatures of −20 to −25 ∘C for potassium feldspar (K-feldspar), but these coincided with the range of temperatures at which INP concentrations increase rapidly at approximately an order of magnitude per 2 ∘C cooling for K-feldspar. These few discrepancies did not outweigh the overall positive outcomes of the workshop activity, nor the future utility of this data set or future similar efforts for resolving remaining measurement issues. Measurements of the same materials were repeatable over the time of the workshop and demonstrated strong consistency with prior studies, as reflected by agreement of data broadly with parameterizations of different specific or general (e.g., soil dust) aerosol types. The divergent measurements of the INP activity of illite NX by direct versus post-processing methods were not repeated for other particle types, and the Snomax® data demonstrated that, at least for a biological INP type, there is no expected measurement bias between bulk collection and direct immediately processed freezing methods to as warm as −10 ∘C. Since particle size ranges were limited for this workshop, it can be expected that for atmospheric populations of INPs, measurement discrepancies will appear due to the different capabilities of methods for sampling the full aerosol size distribution, or due to limitations on achieving sufficient water supersaturations to fully capture immersion freezing in direct processing instruments. Overall, this workshop presents an improved picture of present capabilities for measuring INPs than in past workshops, and provides direction toward addressing remaining measurement issues.

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Abstract. We present the laboratory results of immersion freezing efficiencies of cellulose particles at supercooled temperature (T) conditions. Three types of chemically homogeneous cellulose samples are used as surrogates that represent supermicron and submicron ice-nucleating plant structural polymers. These samples include microcrystalline cellulose (MCC), fibrous cellulose (FC) and nanocrystalline cellulose (NCC). Our immersion freezing dataset includes data from various ice nucleation measurement techniques available at 17 different institutions, including nine dry dispersion and 11 aqueous suspension techniques. With a total of 20 methods, we performed systematic accuracy and precision analysis of measurements from all 20 measurement techniques by evaluating T-binned (1 ∘C) data over a wide T range (−36 ∘C <T<-4 ∘C). Specifically, we intercompared the geometric surface area-based ice nucleation active surface site (INAS) density data derived from our measurements as a function of T, ns,geo(T). Additionally, we also compared the ns,geo(T) values and the freezing spectral slope parameter (Δlog(ns,geo)/ΔT) from our measurements to previous literature results. Results show all three cellulose materials are reasonably ice active. The freezing efficiencies of NCC samples agree reasonably well, whereas the diversity for the other two samples spans ≈ 10 ∘C. Despite given uncertainties within each instrument technique, the overall trend of the ns,geo(T) spectrum traced by the T-binned average of measurements suggests that predominantly supermicron-sized cellulose particles (MCC and FC) generally act as more efficient ice-nucleating particles (INPs) than NCC with about 1 order of magnitude higher ns,geo(T).