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Nucleation is a fundamental step in atmospheric new-particle formation. However, laboratory experiments on nucleation have systematically failed to demonstrate sulfuric acid particle formation rates as high as those necessary to account for ambient atmospheric concentrations, and the role of sulfuric acid in atmospheric nucleation has remained a mystery. Here, we report measurements of new particles (with diameters of approximately 1.5 nanometers) observed immediately after their formation at atmospherically relevant sulfuric acid concentrations. Furthermore, we show that correlations between measured nucleation rates and sulfuric acid concentrations suggest that freshly formed particles contain one to two sulfuric acid molecules, a number consistent with assumptions that are based on atmospheric observations. Incorporation of these findings into global models should improve the understanding of the impact of secondary particle formation on climate.

The stringency of vehicle exhaust emissions regulations resulted in a significant decrease in exhaust particulate matter (PM) emissions over the years. Non-exhaust particles (i.e., from brakes and tyres) account for almost half or more of road transport-induced ambient PM. Even with the internal combustion engine ban in 2035, electrified vehicles will still emit PM from brake and tyre wear. Consequently, non-exhaust PM emissions cannot decrease significantly without any regulatory measures. Because independent research carried out under different methods is not readily comparable, a Global Technical Regulation (GTR), which sets the procedures and boundaries of testing brake wear particle emissions, is currently under development. This overview describes the particle number (PN) measurement setup based on the well-known exhaust emissions PN methodology. We provide the technical requirements and the expected maximum losses. In addition, we estimate the effect of particle losses on the differences between different setups for typical size distributions observed during brake testing. Finally, we compare brake testing PN specifications to those of exhaust PN.

Many countries worldwide have introduced a limit for solid particles larger than 23 nm for the type approval of vehicles before their circulation in the market. However, for some vehicles, in particular for port fuel injection engines (gasoline and gas engines) a high fraction of particles resides below 23 nm. For this reason, a methodology for counting solid particles larger than 10 nm was developed in the Particle Measurement Programme (PMP) group of the United Nations Economic Commission for Europe (UNECE). There are no studies assessing the reproducibility of the new methodology across different laboratories. In this study we compared the reproducibility of the new 10 nm methodology to the current 23 nm methodology. A light-duty gasoline direct injection vehicle and two reference solid particle number measurement systems were circulated in seven European and two Asian laboratories which were also measuring with their own systems fulfilling the current 23 nm methodology. The hot and cold start emission of the vehicle covered a range of 1 to 15 × 1012 #/km with the ratio of sub-23 nm particles to the >23 nm emissions being 10–50%. In most cases the differences between the three measurement systems were ±10%. In general, the reproducibility of the new methodology was at the same levels (around 14%) as with the current methodology (on average 17%).

Atmospheric nucleation is the dominant source of aerosol particles in the global atmosphere and an important player in aerosol climatic effects. The key steps of this process occur in the sub—2-nanometer (nm) size range, in which direct size-segregated observations have not been possible until very recently. Here, we present detailed observations of atmospheric nanoparticles and clusters down to 1-nm mobility diameter. We identified three separate size regimes below 2-nm diameter that build up a physically, chemically, and dynamically consistent framework on atmospheric nucleation—more specifically, aerosol formation via neutral pathways. Our findings emphasize the important role of organic compounds in atmospheric aerosol formation, subsequent aerosol growth, radiative forcing and associated feedbacks between biogenic emissions, clouds, and climate.

Cloud cover at CERN A substantial source of cloud condensation nuclei in the atmospheric boundary layer is thought to originate from the nucleation of trace sulphuric acid vapour. Despite extensive research, we still lack a quantitative understanding of the nucleation mechanism and the possible role of cosmic rays, creating one of the largest uncertainties in atmospheric models and climate predictions. Jasper Kirkby and colleagues present the first results from the CLOUD experiment at CERN, which studies nucleation and other ion-aerosol cloud interactions under precisely controlled conditions. They find that atmospherically relevant ammonia mixing ratios of 100 parts per trillion by volume increase the nucleation rate of sulphuric acid particles by more than a factor of 100 to 1,000. They also find that ion-induced binary nucleation of H 2 SO 4 –H 2 O can occur in the mid-troposphere, but is negligible in the boundary layer and so additional species are necessary. Even with the large enhancements in rate caused by ammonia and ions, they conclude that atmospheric concentrations of ammonia and sulphuric acid are insufficient to account for observed boundary layer nucleation. Atmospheric aerosols exert an important influence on climate 1 through their effects on stratiform cloud albedo and lifetime 2 and the invigoration of convective storms 3 . Model calculations suggest that almost half of the global cloud condensation nuclei in the atmospheric boundary layer may originate from the nucleation of aerosols from trace condensable vapours 4 , although the sensitivity of the number of cloud condensation nuclei to changes of nucleation rate may be small 5 , 6 . Despite extensive research, fundamental questions remain about the nucleation rate of sulphuric acid particles and the mechanisms responsible, including the roles of galactic cosmic rays and other chemical species such as ammonia 7 . Here we present the first results from the CLOUD experiment at CERN. We find that atmospherically relevant ammonia mixing ratios of 100 parts per trillion by volume, or less, increase the nucleation rate of sulphuric acid particles more than 100–1,000-fold. Time-resolved molecular measurements reveal that nucleation proceeds by a base-stabilization mechanism involving the stepwise accretion of ammonia molecules. Ions increase the nucleation rate by an additional factor of between two and more than ten at ground-level galactic-cosmic-ray intensities, provided that the nucleation rate lies below the limiting ion-pair production rate. We find that ion-induced binary nucleation of H 2 SO 4 –H 2 O can occur in the mid-troposphere but is negligible in the boundary layer. However, even with the large enhancements in rate due to ammonia and ions, atmospheric concentrations of ammonia and sulphuric acid are insufficient to account for observed boundary-layer nucleation.

Differential mobility particle size spectrometers (DMPSs) are widely used to measure the aerosol number size distribution. Especially during new particle formation (NPF), the dynamics of the ultrafine size distribution determine the significance of the newly formed particles within the atmospheric system. A precision quantification of the size distribution and derived quantities such as new particle formation and growth rates is therefore essential. However, size-distribution measurements in the sub-10 nm range suffer from high particle losses and are often derived from only a few counts in the DMPS system, making them subject to very high counting uncertainties. Here we show that a CPC (modified Airmodus A20) with a significantly higher aerosol optics flow rate compared to conventional ultrafine CPCs can greatly enhance the counting statistics in that size range. Using Monte Carlo uncertainty estimates, we show that the uncertainties of the derived formation and growth rates can be reduced from 10 %–20 % down to 1 % by deployment of the high statistics CPC on a strong NPF event day. For weaker events and hence lower number concentrations, the counting statistics can result in a complete breakdown of the growth rate estimate with relative uncertainties as high as 40 %, while the improved DMPS still provides reasonable results at 10 % relative accuracy. In addition, we show that other sources of uncertainty are present in CPC measurements, which might become more important when the uncertainty from the counting statistics is less dominant. Altogether, our study shows that the analysis of NPF events could be greatly improved by the availability of higher counting statistics in the used aerosol detector of DMPS systems.

The Particle Size Magnifier is widely used for measuring nano-sized particles. Here we calibrated the newly developed Particle Size Magnifier version 2.0 (PSM 2.0). We used 1–10 nm particles with different compositions, including metal particles, organic particles generated in the laboratory, and atmospheric particles collected in Helsinki and Hyytiälä. A noticeable difference among the calibration curves was observed. Atmospheric particles from Hyytiälä required higher diethylene glycol (DEG) supersaturation to be activated compared to metal particles (standard calibration particles) and other types of particles. This suggests that chemical composition differences introduce measurement uncertainties and highlights the importance of in situ calibration. The size resolution of PSM 2.0 was characterized using metal particles. The maximum size resolution was observed at 2–3 nm. PSM 2.0 was then operated in Hyytiälä for ambient particle measurements in parallel with a Half Mini differential mobility particle sizer (DMPS). During new particle formation (NPF) events, comparable total particle concentrations were observed between the Half Mini DMPS and PSM 2.0 based on Hyytiälä atmospheric particle calibration. Meanwhile, applying the calibration with metal particles to atmospheric measurements caused an overestimation of 3–10 nm particles. In terms of the particle size distributions, similar patterns were observed between the DMPS and PSM when using the calibration of Hyytiälä atmospheric particles. In summary, PSM 2.0 is a powerful instrument for measuring sub-10 nm particles and can achieve more precise particle size distribution measurements with proper calibration.

Physical and chemical properties of particulate matter and concentrations of trace gases were measured at an urban site in Helsinki, Finland, for 5 weeks to investigate the effect of wintertime conditions on pollutants. The measurement took place in a street canyon (traffic supersite) in January–February 2022. In addition, measurements were conducted in an urban background station (UB supersite, SMEAR III, located approx. 0.9 km from the traffic supersite). Measurements were also made using the mobile laboratory. The measurements were made driving the adjacent side streets and the street along the traffic supersite. Source apportionment was performed for the soot particle aerosol mass spectrometer measurements to identify organic factors connected to different particulate sources. Particle number concentration time series and the pollution detection algorithm were used to compare local pollution level differences between the sites. During the campaign three different pollution events were observed with increased pollution concentrations. The increased concentrations during these episodes were due to both trapping of local pollutants near the boundary layer and the long-range and regional transport of pollutants to the Helsinki metropolitan area. Local road vehicle emissions increased the particle number concentrations, especially sub-10 nm particles, and long-range-transported and regionally transported aged particles increased the PM mass and particle size.

The most important parameters describing the atmospheric new particle formation process are the particle formation and growth rates. These together determine the amount of cloud condensation nuclei attributed to secondary particle formation. Due to difficulties in detecting small neutral particles, it has previously not been possible to derive these directly from measurements in the size range below about 3 nm. The Airmodus Particle Size Magnifier has been used at the SMEAR II station in Hyytiala, southern Finland, and during nucleation experiments in the CLOUD chamber at CERN for measuring particles as small as about 1 nm in mobility diameter. We developed several methods to determine the particle size distribution and growth rates in the size range of 1-3 nm from these data sets. Here we introduce the appearance-time method for calculating initial growth rates. The validity of the method was tested by simulations with the Ion-UHMA aerosol dynamic model.

Accurate measurements of the size distribution of atmospheric aerosol nanoparticles are essential to build an understanding of new particle formation and growth. This is particularly crucial at the sub-3 nm range due to the growth of newly formed nanoparticles. The challenge in recovering the size distribution is due its complexity and the fact that not many instruments currently measure at this size range. In this study, we used the particle size magnifier (PSM) to measure atmospheric aerosols. Each day was classified into one of the following three event types: a new particle formation (NPF) event, a non-event or a haze event. We then compared four inversion methods (stepwise, kernel, Hagen–Alofs and expectation–maximization) to determine their feasibility to recover the particle size distribution. In addition, we proposed a method to pretreat the measured data, and we introduced a simple test to estimate the efficacy of the inversion itself. Results showed that all four methods inverted NPF events well; however, the stepwise and kernel methods fared poorly when inverting non-events or haze events. This was due to their algorithm and the fact that, when encountering noisy data (e.g. air mass fluctuations or low sub-3 nm particle concentrations) and under the influence of larger particles, these methods overestimated the size distribution and reported artificial particles during inversion. Therefore, using a statistical hypothesis test to discard noisy scans prior to inversion is an important first step toward achieving a good size distribution. After inversion, it is ideal to compare the integrated concentration to the raw estimate (i.e. the concentration difference at the lowest supersaturation and the highest supersaturation) to ascertain whether the inversion itself is sound. Finally, based on the analysis of the inversion methods, we provide procedures and codes related to the PSM data inversion.