Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations as well as hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a one-year period and full seasonal cycle (March 2014–February 2015). The presented measurements provide a climatology of CCN properties for a characteristic central Amazonian rain forest site. The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The observed mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), elevated values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol. The hygroscopicity parameter κ exhibits remarkably little temporal variability: no pronounced diurnal cycles, weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes. For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data

The role of aerosolized SARS-CoV-2 viruses in airborne transmission of COVID-19 has been debated. The aerosols are transmitted through breathing and vocalization by infectious subjects. Some authors state that this represents the dominant route of spreading, while others dismiss the option. Here we present an adjustable algorithm to estimate the infection risk for different indoor environments, constrained by published data of human aerosol emissions, SARS-CoV-2 viral loads, infective dose and other parameters. We evaluate typical indoor settings such as an office, a classroom, choir practice, and a reception/party. Our results suggest that aerosols from highly infective subjects can effectively transmit COVID-19 in indoor environments. This “highly infective” category represents approximately 20% of the patients who tested positive for SARS-CoV-2. We find that “super infective” subjects, representing the top 5–10% of subjects with a positive test, plus an unknown fraction of less—but still highly infective, high aerosol-emitting subjects—may cause COVID-19 clusters (>10 infections). In general, active room ventilation and the ubiquitous wearing of face masks (i.e., by all subjects) may reduce the individual infection risk by a factor of five to ten, similar to high-volume, high-efficiency particulate air (HEPA) filtering. A particularly effective mitigation measure is the use of high-quality masks, which can drastically reduce the indoor infection risk through aerosols.

Abstract. Airborne observations over the Amazon Basin showed high aerosol particle concentrations in the upper troposphere (UT) between 8 and 15 km altitude, with number densities (normalized to standard temperature and pressure) often exceeding those in the planetary boundary layer (PBL) by 1 or 2 orders of magnitude. The measurements were made during the German-Brazilian cooperative aircraft campaign ACRIDICON-CHUVA, where ACRIDICON stands for "Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems" and

Abstract. Two different single particle mass spectrometers were operated in parallel at the Swiss High Alpine Research Station Jungfraujoch (JFJ, 3580 m a.s.l.) during the Cloud and Aerosol Characterization Experiment (CLACE 6) in February and March 2007. During mixed phase cloud events ice crystals from 5-20 µm were separated from larger ice aggregates, non-activated, interstitial aerosol particles and supercooled droplets using an Ice-Counterflow Virtual Impactor (Ice-CVI). During one cloud period supercooled droplets were additionally sampled and analyzed by changing the Ice-CVI setup. The small ice particles and droplets were evaporated by injection into dry air inside the Ice-CVI. The resulting ice and droplet residues (IR and DR) were analyzed for size and composition by the two single particle mass spectrometers: a custom-built Single Particle Laser-Ablation Time-of-Flight Mass Spectrometer (SPLAT) and a commercial Aerosol Time-of-Flight Mass Spectrometer (ATOFMS, TSI Model 3800). During CLACE 6 the SPLAT instrument characterized 355 individual IR that produced a mass spectrum for at least one polarity and the ATOFMS measured 152 IR. The mass spectra were binned Correspondence to: J. Curtius (curtius@iau.uni-frankfurt.de) in classes, based on the combination of dominating substances, such as mineral dust, sulfate, potassium and elemental carbon or organic material. The derived chemical information from the ice residues is compared to the JFJ ambient aerosol that was sampled while the measurement station was out of clouds (several thousand particles analyzed by SPLAT and ATOFMS) and to the composition of the residues of supercooled cloud droplets (SPLAT: 162 cloud droplet residues analyzed, ATOFMS: 1094). The measurements showed that mineral dust was strongly enhanced in the ice particle residues. Close to all of the SPLAT spectra from ice residues did contain signatures from mineral compounds, albeit connected with varying amounts of soluble compounds. Similarly, close to all of the ATOFMS IR spectra show a mineral or metallic component. Pure sulfate and nitrate containing particles were depleted in the ice residues. Sulfate and nitrate was found to dominate the droplet residues (∼90% of the particles). The results from the two different single particle mass spectrometers were generally in agreement. Differences in the results originate from several causes, such as the different wavelength of the desorption and ionisation lasers and different size-dependent particle detection efficiencies.

The Midlatitude Cirrus experiment (ML-CIRRUS) deployed the High Altitude and Long Range Research Aircraft (HALO) to obtain new insights into nucleation, life cycle, and climate impact of natural cirrus and aircraft-induced contrail cirrus. Direct observations of cirrus properties and their variability are still incomplete, currently limiting our understanding of the clouds’ impact on climate. Also, dynamical effects on clouds and feedbacks are not adequately represented in today’s weather prediction models. Here, we present the rationale, objectives, and selected scientific highlights of ML-CIRRUS using the G-550 aircraft of the German atmospheric science community. The first combined in situ–remote sensing cloud mission with HALO united state-of-the-art cloud probes, a lidar and novel ice residual, aerosol, trace gas, and radiation instrumentation. The aircraft observations were accompanied by remote sensing from satellite and ground and by numerical simulations. In spring 2014, HALO performed 16 flights above Europe with a focus on anthropogenic contrail cirrus and midlatitude cirrus induced by frontal systems including warm conveyor belts and other dynamical regimes (jet streams, mountain waves, and convection). Highlights from ML-CIRRUS include 1) new observations of microphysical and radiative cirrus properties and their variability in meteorological regimes typical for midlatitudes, 2) insights into occurrence of in situ–formed and lifted liquid-origin cirrus, 3) validation of cloud forecasts and satellite products, 4) assessment of contrail predictability, and 5) direct observations of contrail cirrus and their distinction from natural cirrus. Hence, ML-CIRRUS provides a comprehensive dataset on cirrus in the densely populated European midlatitudes with the scope to enhance our understanding of cirrus clouds and their role for climate and weather

Between 1 September and 4 October 2014, a combined airborne and ground-based measurement campaign was conducted to study tropical deep convective clouds over the Brazilian Amazon rain forest. The new German research aircraft, High Altitude and Long Range Research Aircraft (HALO), a modified Gulfstream G550, and extensive ground-based instrumentation were deployed in and near Manaus (State of Amazonas). The campaign was part of the German–Brazilian Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems–Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON– CHUVA) venture to quantify aerosol–cloud–precipitation interactions and their thermodynamic, dynamic, and radiative effects by in situ and remote sensing measurements over Amazonia. The ACRIDICON–CHUVA field observations were carried out in cooperation with the second intensive operating period of Green Ocean Amazon 2014/15 (GoAmazon2014/5). In this paper we focus on the airborne data measured on HALO, which was equipped with about 30 in situ and remote sensing instruments for meteorological, trace gas, aerosol, cloud, precipitation, and spectral solar radiation measurements. Fourteen research flights with a total duration of 96 flight hours were performed. Five scientific topics were pursued: 1) cloud vertical evolution and life cycle (cloud profiling), 2) cloud processing of aerosol particles and trace gases (inflow and outflow), 3) satellite and radar validation (cloud products), 4) vertical transport and mixing (tracer experiment), and 5) cloud formation over forested/deforested areas. Data were collected in near-pristine atmospheric conditions and in environments polluted by biomass burning and urban emissions. The paper presents a general introduction of the ACRIDICON– CHUVA campaign (motivation and addressed research topics) and of HALO with its extensive instrument package, as well as a presentation of a few selected measurement results acquired during the flights for some selected scientific topics.

Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014-February 2015. In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1;Pöhlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions:-Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with D Ait ≈ 70 nm and N Ait ≈ 160 cm −3 , weak accumulation mode with D acc ≈ 160 nm and N acc ≈ 90 cm −3 ), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (κ Ait ≈ 0.12, κ acc ≈ 0.18).-Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode (D Ait ≈ 80 nm, N Ait ≈ 120 cm −3 vs. D acc ≈ 180 nm, N acc ≈ 310 cm −3 ), an increased abundance of dust and salt, and relatively high hygroscopicity (κ Ait ≈ 0.18, κ acc ≈ 0.35).The coarse mode is also significantly enhanced during these events.-Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (D Ait ≈ 70 nm, N Ait ≈ 140 cm −3 vs. D acc ≈ 170 nm, N acc ≈ 3400 cm −3 ), very high organic mass fractions (∼ 90 %), and correspondingly low hygroscopicity (κ Ait ≈ 0.14, κ acc ≈ 0.17).-Mixed-pollution (MPOL) conditions with a superposition of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D ≈ 130 nm, N CN,10 ≈ 1300 cm −3 ), with high sulfate mass fractions (∼ 20 %) from volcanic sources and correspondingly high hygroscopicity (κ < 100 nm ≈ 0.14, κ > 100 nm ≈ 0.22), which were periodically mixed with fresh smoke from nearby fires (D ≈ 110 nm, N CN,10 ≈ 2800 cm −3 ) with an organicdominated composition and sharply decreased hygroscopicity (κ < 150 nm ≈ 0.10, κ > 150 nm ≈ 0.20).Insights into the aerosol mixing state are provided by particle hygroscopicity (κ) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow κ distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad κ distributions).The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activa...

Abstract. Cloud residues and out-of-cloud aerosol particles with diameters between 150 and 900 nm were analysed by online single particle aerosol mass spectrometry during the 6-week study Hill Cap Cloud Thuringia (HCCT)-2010 in September–October 2010. The measurement location was the mountain Schmücke (937 m a.s.l.) in central Germany. More than 160 000 bipolar mass spectra from out-of-cloud aerosol particles and more than 13 000 bipolar mass spectra from cloud residual particles were obtained and were classified using a fuzzy c-means clustering algorithm. Analysis of the uncertainty of the sorting algorithm was conducted on a subset of the data by comparing the clustering output with particle-by-particle inspection and classification by the operator. This analysis yielded a false classification probability between 13 and 48 %. Additionally, particle types were identified by specific marker ions. The results from the ambient aerosol analysis show that 63 % of the analysed particles belong to clusters having a diurnal variation, suggesting that local or regional sources dominate the aerosol, especially for particles containing soot and biomass burning particles. In the cloud residues, the relative percentage of large soot-containing particles and particles containing amines was found to be increased compared to the out-of-cloud aerosol, while, in general, organic particles were less abundant in the cloud residues. In the case of amines, this can be explained by the high solubility of the amines, while the large soot-containing particles were found to be internally mixed with inorganics, which explains their activation as cloud condensation nuclei. Furthermore, the results show that during cloud processing, both sulfate and nitrate are added to the residual particles, thereby changing the mixing state and increasing the fraction of particles with nitrate and/or sulfate. This is expected to lead to higher hygroscopicity after cloud evaporation, and therefore to an increase of the particles' ability to act as cloud condensation nuclei after their cloud passage.