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Measurements of the ambient aerosol, various trace gases and meteorological quantities using a mobile laboratory (MoLa) were performed on the banks of the Lower Elbe in an emission control area (ECA) which is passed by numerous private and commercial marine vessels reaching and leaving the port of Hamburg, Germany. From 25–29 April 2011 a total of 178 vessels were probed at a distance of about 0.8–1.2 km with high temporal resolution. 139 ship emission plumes were of sufficient quality to be analyzed further and to determine emission factors (EFs). Concentrations of aerosol number and mass as well as polycyclic aromatic hydrocarbons (PAH) and black carbon were measured in PM1 and size distribution instruments covered the diameter range from 6 nm up to 32 μm. The chemical composition of the non-refractory submicron aerosol was measured by means of an Aerosol Mass Spectrometer (Aerodyne HR-ToF-AMS). Gas phase species analyzers monitored various trace gases (O3, SO2, NO, NO2, CO2) in the air and a weather station provided wind, precipitation, solar radiation data and other quantities. Together with ship information for each vessel obtained from Automatic Identification System (AIS) broadcasts a detailed characterization of the individual ship types and of features affecting gas and particulate emissions is provided. Particle number EFs (average 2.6e+16 # kg−1) and PM1 mass EFs (average 2.4 g kg−1) tend to increase with the fuel sulfur content. Observed PM1 composition of the vessel emissions was dominated by organic matter (72%), sulfate (22%) and black carbon (6%) while PAHs only account for 0.2% of the submicron aerosol mass. Measurements of gaseous components showed an increase of SO2 (average EF: 7.7 g kg−1) and NOx (average EF: 53 g kg−1) while O3 decreased when a ship plume reached the sampling site. The particle number size distributions of the vessels are generally characterized by a bimodal size distribution, with the nucleation mode in the 10–20 nm diameter range and a combustion aerosol mode centered at about 35 nm while particles \\ 1 μm were not found. \"High particle number emitters\" are characterized by a dominant nucleation mode. By contrast, increased particle concentrations around 150 nm primarily occurred for \"high black carbon emitters\". Classifying the vessels according to their gross tonnage shows a decrease of the number, black carbon and PAH EFs while EFs of SO2, NO, NO2, NOx, AMS species (particulate organics, sulfate) and PM1 mass concentration increase with increasing gross tonnages.

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.

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 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.

A compact mobile aerosol research laboratory (MoLa) for stationary and mobile measurements of aerosol and trace gas characteristics was developed at the Max Planck Institute for Chemistry (MPIC) in Mainz, Germany. Major efforts were made to design an aerosol inlet system which is optimized and characterised for both, stationary and mobile measurements using a particle loss modelling approach. The instrumentation on board allows the determination of a multitude of physical and chemical aerosol parameters, for example particle number and mass concentration (PM1/2.5/10), particle size distributions in the diameter range 6 nm up to 32 μm, and chemical composition of the sub-micron aerosol. Furthermore, trace gas concentrations of O3, SO2, CO, CO2, NO, NO2 and water vapour as well as meteorological parameters like temperature, relative humidity, pressure, wind, solar radiation and precipitation are measured together with various housekeeping parameters. All instruments collect data with high time resolution in the second to minute-range. The measurement platform, as well as data acquisition and handling tools, are optimized for efficient application to various measurement settings. The mobile laboratory is designed to be used for mobile investigation of anthropogenically influenced environments. Possible applications include pollutant mapping, chasing of mobile sources or Lagrangian-type measurements in emission plumes, but also stationary measurements with possible frequent position changes and a well-characterised instrument setup. In addition to the design and features of the mobile laboratory, its inlet system and instrumentation as well as examples of applications of this platform are presented. Challenges associated with such measurements and approaches to extract the desired information from the mobile datasets are discussed.

In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-Alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels. During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. A major advantage of the derivation of Slow and Savg from size-resolved CCN efficiency spectra is that it does not require the specific knowledge or assumptions about aerosol hygroscopicity that are needed to derive estimates of Slow, Shigh, and Savg from aerosol size distribution data. For the investigated cloud event, we derived Slow 0.07–0.25%, Shigh 0.86–1.31% and Savg 0.42–0.68%.

Single-particle mass spectrometry has proven a valuable tool for gaining information on the mixing state of aerosol particles. With the Aerodyne aerosol mass spectrometer (AMS) equipped with a light-scattering probe, non-refractory components of submicron particles with diameters larger than about 300 nm can even be quantified on a single-particle basis. Here, we present a new method for the analysis of AMS single-particle mass spectra. The developed algorithm classifies the particles according to their components (e.g. sulphate, nitrate, different types of organics) and simultaneously provides quantitative information about the composition of the single particles. This classification algorithm was validated by applying it to data acquired in laboratory experiments with particles of known composition, and applied to field data acquired during the MEGAPOLI summer campaign (July 2009) in Paris. As shown, it is not only possible to directly measure the mixing state of atmospheric particles, but also to directly observe repartitioning of semi-volatile species between gas and particle phase during the course of the day.

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 CHUVA is the acronym for Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (global precipitation measurement), on the German High Altitude and Long Range Research Aircraft (HALO). The campaign took place in September–October 2014, with the objective of studying tropical deep convective clouds over the Amazon rainforest and their interactions with atmospheric trace gases, aerosol particles, and atmospheric radiation. Aerosol enhancements were observed consistently on all flights during which the UT was probed, using several aerosol metrics, including condensation nuclei (CN) and cloud condensation nuclei (CCN) number concentrations and chemical species mass concentrations. The UT particles differed sharply in their chemical composition and size distribution from those in the PBL, ruling out convective transport of combustion-derived particles from the boundary layer (BL) as a source. The air in the immediate outflow of deep convective clouds was depleted of aerosol particles, whereas strongly enhanced number concentrations of small particles (< 90 nm diameter) were found in UT regions that had experienced outflow from deep convection in the preceding 5–72 h. We also found elevated concentrations of larger (> 90 nm) particles in the UT, which consisted mostly of organic matter and nitrate and were very effective CCN. Our findings suggest a conceptual model, where production of new aerosol particles takes place in the continental UT from biogenic volatile organic material brought up by deep convection and converted to condensable species in the UT. Subsequently, downward mixing and transport of upper tropospheric aerosol can be a source of particles to the PBL, where they increase in size by the condensation of biogenic volatile organic compound (BVOC) oxidation products. This may be an important source of aerosol particles for the Amazonian PBL, where aerosol nucleation and new particle formation have not been observed. We propose that this may have been the dominant process supplying secondary aerosol particles in the pristine atmosphere, making clouds the dominant control of both removal and production of atmospheric particles.

Black carbon (BC) aerosols influence the Earth's atmosphere and climate, but their microphysical properties, spatiotemporal distribution, and long-range transport are not well constrained. This study presents airborne observations of the transatlantic transport of BC-rich African biomass burning (BB) smoke into the Amazon Basin using a Single Particle Soot Photometer (SP2) as well as several complementary techniques. We base our results on observations of aerosols and trace gases off the Brazilian coast onboard the HALO (High Altitude and LOng range) research aircraft during the ACRIDICON-CHUVA campaign in September 2014. During flight AC19 over land and ocean at the northeastern coastline of the Amazon Basin, we observed a BC-rich layer at ∼3.5 km altitude with a vertical extension of ∼0.3 km. Backward trajectories suggest that fires in African grasslands, savannas, and shrublands were the main source of this pollution layer and that the observed BB smoke had undergone more than 10 d of atmospheric transport and aging over the South Atlantic before reaching the Amazon Basin. The aged smoke is characterized by a dominant accumulation mode, centered at about 130 nm, with a particle concentration of Nacc=850±330 cm−3. The rBC particles account for ∼15 % of the submicrometer aerosol mass and ∼40 % of the total aerosol number concentration. This corresponds to a mass concentration range from 0.5 to 2 µg m−3 (1st to 99th percentiles) and a number concentration range from 90 to 530 cm−3. Along with rBC, high cCO (150±30 ppb) and cO3 (56±9 ppb) mixing ratios support the biomass burning origin and pronounced photochemical aging of this layer. Upon reaching the Amazon Basin, it started to broaden and to subside, due to convective mixing and entrainment of the BB aerosol into the boundary layer. Satellite observations show that the transatlantic transport of pollution layers is a frequently occurring process, seasonally peaking in August/September. By analyzing the aircraft observations together with the long-term data from the Amazon Tall Tower Observatory (ATTO), we found that the transatlantic transport of African BB smoke layers has a strong impact on the northern and central Amazonian aerosol population during the BB-influenced season (July to December). In fact, the early BB season (July to September) in this part of the Amazon appears to be dominated by African smoke, whereas the later BB season (October to December) appears to be dominated by South American fires. This dichotomy is reflected in pronounced changes in aerosol optical properties such as the single scattering albedo (increasing from 0.85 in August to 0.90 in November) and the BC-to-CO enhancement ratio (decreasing from 11 to 6 ng m−3 ppb−1). Our results suggest that, despite the high fraction of BC particles, the African BB aerosol acts as efficient cloud condensation nuclei (CCN), with potentially important implications for aerosol–cloud interactions and the hydrological cycle in the Amazon.

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote 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 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), higher 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, only 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 modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.

Direct measurement of the acidity (pH) of ambient aerosol particles/droplets has long been a challenge for atmospheric scientists. A novel and facile method was introduced recently by Craig et al. (2018), where the pH of size-resolved aerosol droplets was directly measured by two types of pH-indicator papers (pH ranges: 0–2.5 and 2.5–4.5) combined with RGB-based colorimetric analyses using a model of G−B (G minus B) vs. pH2. Given the wide pH range of ambient aerosols, we optimize the RGB-based colorimetric analysis on pH papers with a wider detection range (pH ∼ 0 to 6). Here, we propose a new model to establish the linear relationship between RGB values and pH: pHpredict = a⋅Rnormal+b⋅Gnormal+c⋅Bnormal. This model shows a wider applicability and higher accuracy than those in previous studies and is thus recommended in future RGB-based colorimetric analyses on pH papers. Moreover, we identify one type of pH paper (Hydrion® Brilliant pH dip stiks, lot no. 3110, Sigma-Aldrich) that is more applicable for ambient aerosols in terms of its wide pH detection range (0 to 6) and strong anti-interference capacity. Custom-made impactors are used to collect lab-generated aerosols on this type of pH paper. Preliminary tests show that, with a collected particle size range of ∼ 0.4–2.2 µm, the pH paper method can be used to predict aerosol pH with an overall uncertainty ≤ 0.5 units. Based on laboratory tests, a relatively short sampling time (∼ 1 to 4 h) is speculated for pH prediction of ambient aerosols. More importantly, our design of the impactors minimizes potential influences of changed environmental conditions during pH paper photographing processes on the predicted aerosol pH. We further show that the routinely adopted way of using pH color charts to predict aerosol pH may be biased by the mismatch between the standard colors on the color charts and the real colors of investigated samples. Thus, instead of using the producer-provided color charts, we suggest an in situ calibration of pH papers with standard pH buffers.