Atmospheric new particle formation (NPF) is an important phenomenon in terms of the 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 one 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, taking place on about 30% of the days in March-May and on about 10% of the days in December-February. The median formation rate of 10 nm particles varies by about three 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 between the different measurement sites, as well as between 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 Northern America, Asia and most of the Southern Hemisphere (especially Australia), from polar areas, and from at least a few locations over the oceans.

<p><strong>Abstract.</strong> APHH-Beijing (Atmospheric Pollution and Human Health in a Chinese Megacity) is an international collaborative project to examine the emissions, processes and health effects of air pollution in Beijing. The four research themes of APHH-China are: (1) sources and emissions of urban atmospheric pollution; (2) processes affecting urban atmospheric pollution; (3) exposure science and impacts on health; and (4) interventions and solutions to reduce health impacts. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1–3 provide scientific data for Theme 4 on the development of cost-effective solutions. A key activity within APHH-Beijing was the two month-long intensive field campaigns at two sites: (i) central Beijing, and (ii) rural Pinggu. The coordinated campaigns provided observations of the atmospheric chemistry and physics in and around Beijing during November–December 2016 and May–June 2017. The campaigns were complemented by numerical air quality modelling and air quality and meteorology data at the 12 national monitoring stations in Beijing. This introduction paper provides an overview of (i) APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it in Beijing, and (iii) the air quality and meteorological conditions during the two field campaigns. The winter campaign was characterized by high PM<sub>2.5</sub> pollution events whereas the summer experienced high ozone pollution events. Air quality was poor during the winter campaign, but less severe than in the same period in 2015 when there were a number of major pollution episodes. PM<sub>2.5</sub> levels were relatively low during the summer period, matching the cleanest periods over the previous five years. Synoptic scale meteorological analysis suggests that the greater stagnation and weak southerly circulation in November/December 2016 may have contributed to the poor air quality.</p>

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Abstract. The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019–2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January–March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.