Aerosol black carbon is a unique primary tracer for combustion emissions. It affects the optical properties of the atmosphere and is recognized as the second most important anthropogenic forcing agent for climate change. It is the primary tracer for adverse health effects caused by air pollution. For the accurate determination of mass equivalent black carbon concentrations in the air and for source apportionment of the concentrations, optical measurements by filter-based absorption photometers must take into account the "filter loading effect". We present a new real-time loading effect compensation algorithm based on a two parallel spot measurement of optical absorption. This algorithm has been incorporated into the new Aethalometer model AE33. Intercomparison studies show excellent reproducibility of the AE33 measurements and very good agreement with post-processed data obtained using earlier Aethalometer models and other filter-based absorption photometers. The real-time loading effect compensation algorithm provides the high-quality data necessary for real-time source apportionment and for determination of the temporal variation of the compensation parameter k.

Although black carbon (BC) is one of the key atmospheric particulate components driving climate change and air quality, there is no agreement on the terminology that considers all aspects of specific properties, definitions, measurement methods, and related uncertainties. As a result, there is much ambiguity in the scientific literature of measurements and numerical models that refer to BC with different names and based on different properties of the particles, with no clear definition of the terms. The authors present here a recommended terminology to clarify the terms used for BC in atmospheric research, with the goal of establishing unambiguous links between terms, targeted material properties and associated measurement techniques.

Mobility particle size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide range of applications in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards and guidelines with respect to the instrumental set-up, measurement mode, data evaluation as well as quality control. Technical standards were developed for a minimum requirement of mobility size spectrometry to perform long-term atmospheric aerosol measurements. Technical recommendations include continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyzer. We compared commercial and custom-made inversion routines to calculate the particle number size distributions from the measured electrical mobility distribution. All inversion routines are comparable within few per cent uncertainty for a given set of raw data. Furthermore, this work summarizes the results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research) and ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) to determine present uncertainties especially of custom-built mobility particle size spectrometers. Under controlled laboratory conditions, the particle number size distributions from 20 to 200 nm determined by mobility particle size spectrometers of different design are within an uncertainty range of around ±10% after correcting internal particle losses, while below and above this size range the discrepancies increased. For particles larger than 200 nm, the uncertainty range increased to 30%, which could not be explained. The network reference mobility spectrometers with identical design agreed within ±4% in the peak particle number concentration when all settings were done carefully. The consistency of these reference instruments to the total particle number concentration was demonstrated to be less than 5%. Additionally, a new data structure for particle number size distributions was introduced to store and disseminate the data at EMEP (European Monitoring and Evaluation Program). This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data.

Aerosol–cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set – ready to be used for model validation – of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles > 20 nm) across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ , calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3). We performed closure studies based on κ –Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of κ . The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating “migrating-CCNCs” to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

Atmospheric new particle formation (NPF) is an important phenomenon in terms of global particle number concentrations. Here we investigated the frequency of NPF, formation rates of 10 nm particles, and growth rates in the size range of 10–25 nm using at least 1 year of aerosol number size-distribution observations at 36 different locations around the world. The majority of these measurement sites are in the Northern Hemisphere. We found that the NPF frequency has a strong seasonal variability. At the measurement sites analyzed in this study, NPF occurs most frequently in March–May (on about 30 % of the days) and least frequently in December–February (about 10 % of the days). The median formation rate of 10 nm particles varies by about 3 orders of magnitude (0.01–10 cm⁻³ s⁻¹) and the growth rate by about an order of magnitude (1–10 nm h⁻¹). The smallest values of both formation and growth rates were observed at polar sites and the largest ones in urban environments or anthropogenically influenced rural sites. The correlation between the NPF event frequency and the particle formation and growth rate was at best moderate among the different measurement sites, as well as among the sites belonging to a certain environmental regime. For a better understanding of atmospheric NPF and its regional importance, we would need more observational data from different urban areas in practically all parts of the world, from additional remote and rural locations in North America, Asia, and most of the Southern Hemisphere (especially Australia), from polar areas, and from at least a few locations over the oceans.

This study was part of the international field measurement Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing‐2006). We investigated a new particle formation event in a highly polluted air mass at a regional site south of the megacity Beijing and its impact on the abundance and properties of cloud condensation nuclei (CCN). During the 1‐month observation, particle nucleation followed by significant particle growth on a regional scale was observed frequently (∼30%), and we chose 23 August 2006 as a representative case study. Secondary aerosol mass was produced continuously, with sulfate, ammonium, and organics as major components. The aerosol mass growth rate was on average 19 μg m⁻³ h⁻¹ during the late hours of the day. This growth rate was observed several times during the 1‐month intensive measurements. The nucleation mode grew very quickly into the size range of CCN, and the CCN size distribution was dominated by the growing nucleation mode (up to 80% of the total CCN number concentration) and not as usual by the accumulation mode. At water vapor supersaturations of 0.07–0.86%, the CCN number concentrations reached maximum values of 4000–19,000 cm⁻³ only 6–14 h after the nucleation event. During particle formation and growth, the effective hygroscopicity parameter κ increased from about 0.1–0.3 to 0.35–0.5 for particles with diameters of 40–90 nm, but it remained nearly constant at ∼0.45 for particles with diameters of ∼190 nm. This result is consistent with aerosol chemical composition data, showing a pronounced increase of sulfate.