Explore the vast range of titles available.

The formation of new atmospheric aerosol particles and their subsequent growth have been observed frequently at various locations all over the world. The atmospheric nucleation rate (or formation rate) and growth rate (GR) are key parameters to characterize the phenomenon. Recent progress in measurement techniques enables us to measure atmospheric nucleation at the size (mobility diameter) of 1.5 (±0.4) nm. The detection limit has decreased from 3 to 1 nm within the past 10 years. In this protocol, we describe the procedures for identifying new-particle-formation (NPF) events, and for determining the nucleation, formation and growth rates during such events under atmospheric conditions. We describe the present instrumentation, best practices and other tools used to investigate atmospheric nucleation and NPF at a certain mobility diameter (1.5, 2.0 or 3.0 nm). The key instruments comprise devices capable of measuring the number concentration of the formed nanoparticles and their size, such as a suite of modern condensation particle counters (CPCs) and air ion spectrometers, and devices for characterizing the pre-existing particle number concentration distribution, such as a differential mobility particle sizer (DMPS). We also discuss the reliability of the methods used and requirements for proper measurements and data analysis. The time scale for realizing this procedure is 1 year.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between NCCN and AOPs was parameterized as NCCN≈((286±46)SAE ln(SS/(0.093±0.006))(BSF − BSFmin) + (5.2±3.3))σsp, where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS ≈0.1 %), the average bias, defined as the ratio of the AOP-derived and measured NCCN, varied from ∼0.7 to ∼1.9 at most sites except at a Himalayan site where the bias was >4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (N.sub.CCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating N.sub.CCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between N.sub.CCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ãngström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (Ï.sub.sp) of PM.sub.10 particles. The analysis first showed that the dependence of N.sub.CCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between N.sub.CCN and AOPs was parameterized as NCCNâ((286±46)SAE ln(SS/(0.093±0.006))(BSF - BSF.sub.min) + (5.2±3.3))Ï.sub.sp, where BSF.sub.min is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS â0.1 %), the average bias, defined as the ratio of the AOP-derived and measured N.sub.CCN, varied from â¼0.7 to â¼1.9 at most sites except at a Himalayan site where the bias was 4. At SS 0.4 % the average bias ranged from â¼0.7 to â¼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, â¼1.4-1.9. In other words, at SS 0.4 % N.sub.CCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ãngström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured N.sub.CCN varied from â¼0.5 to â¼0.8. To study the physical explanation of the relationships between N.sub.CCN and AOPs, lognormal unimodal particle size distributions were generated and N.sub.CCN and AOPs were calculated. The simulation showed that the relationships of N.sub.CCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of N.sub.CCN and AOPs were similar to those of the observed ones.

Aerosol optical properties (AOPs) and supporting parameters – particle number size distributions, PM2.5 mass concentrations, and the concentrations of trace gases (NOx and NOy) – were measured at SORPES, a regional background station in Nanjing, China from June 2013 to May 2015. The aerosol was highly scattering: the average scattering coefficient was σsp=403 ± 314 Mm−1, the absorption coefficient σap=26 ± 19 Mm−1, and the single-scattering albedo SSA = 0.93 ± 0.03 for green light. The SSA in Nanjing appears to be slightly higher than published values from several other sites in China and elsewhere. The average Ångström exponent of absorption (AAE) for the wavelength range 370–950 nm was 1.04 and the AAE range was 0.7–1.4. These AAE values can be explained with different amounts of non-absorbing coating on pure black carbon (BC) cores and different core sizes rather than contribution by brown carbon. The AOPs had typical seasonal cycles with high σsp and σap in winter and low ones in summer: the averages were σsp=544 ± 422 and σap=36 ± 24 Mm−1 in winter and σsp=342 ± 281 and σap=20 ± 13 Mm−1 in summer. The intensive AOPs had no clear seasonal cycles, the variations in them were rather related to the evolution of pollution episodes. The diurnal cycles of the intensive AOPs were clear and in agreement with the cycle of the particle number size distribution. The diurnal cycle of SSA was similar to that of the air photochemical age, suggesting that the darkest aerosol originated from fresh traffic emissions. A Lagrangian retroplume analysis showed that the potential source areas of high σsp and σap are mainly in eastern China. Synoptic weather phenomena dominated the cycle of AOPs on a temporal scale of 3–7 days. During pollution episodes, modeled boundary layer height decreased, whereas PM2.5 concentrations and σsp and σap typically increased gradually and remained high during several days but decreased faster, sometimes by even more than an order of magnitude within some hours. During the growth phase of the pollution episodes the intensive AOPs evolved clearly. The mass scattering efficiency MSE of PM2.5 grew during the extended pollution episodes from ∼ 4 to ∼ 6 m2 g−1 and the mass fraction of BCe decreased from ∼ 10 to ∼ 3 % during the growth phase of the episodes. Particle growth resulted in the backscatter fraction decreasing from more than 0.16 to less than 0.10, SSA growing from less than 0.9 to more than 0.95, and radiative forcing efficiency (RFE) changing from less than −26 W m−2 to more than −24 W m−2, which means that the magnitude of RFE decreased. The RFE probability distribution at SORPES was clearly narrower than at a clean background site which is in agreement with a published RFE climatology.

The metallurgical industry in the Kola Peninsula, north-west Russia, form, after Norilsk, Siberia, the second largest source of air pollution in the Arctic and subarctic domain. Sulfur dioxide (SO2) emissions from the ore smelters are transported to wide areas, including Finnish Lapland. We performed investigations on concentrations of SO2, aerosol precursor vapours, aerosol and ion cluster size distributions together with chemical composition measurements of freshly formed clusters at the SMEAR I station in Finnish Lapland relatively close (∼ 300 km) to the Kola Peninsula industrial sites during the winter 2019–2020. We show that highly concentrated SO2 from smelter emissions is converted to sulfuric acid (H2SO4) in sufficient concentrations to drive new particle formation hundreds of kilometres downwind from the emission sources, even at very low solar radiation intensities. Observed new particle formation is primarily initiated by H2SO4–ammonia (negative-)ion-induced nucleation. Particle growth to cloud condensation nuclei (CCN) sizes was concluded to result from sulfuric acid condensation. However, air mass advection had a large role in modifying aerosol size distributions, and other growth mechanisms and condensation of other compounds cannot be fully excluded. Our results demonstrate the dominance of SO2 emissions in controlling wintertime aerosol and CCN concentrations in the subarctic region with a heavily polluting industry.

This work presents airborne observations of sub-3 nm particles in the lower troposphere and investigates new particle formation (NPF) within an evolving boundary layer (BL). We studied particle concentrations together with supporting gas and meteorological data inside the planetary BL over a boreal forest site in Hyytiälä, southern Finland. The analysed data were collected during three flight measurement campaigns: May-June 2015, August 2015 and April-May 2017, including 27 morning and 26 afternoon vertical profiles. As a platform for the instrumentation, we used a Cessna 172 aircraft. The analysed flight data were collected horizontally within a 30 km distance from SMEAR II in Hyytiälä and vertically from 100 m above ground level up to 2700 m. The number concentration of 1.5-3 nm particles was observed to be, on average, the highest near the forest canopy top and to decrease with increasing altitude during the mornings of NPF event days. This indicates that the precursor vapours emitted by the forest play a key role in NPF in Hyytiälä. During daytime, newly formed particles were observed to grow in size and the particle population became more homogenous within the well-mixed BL in the afternoon. During undefined days with respect to NPF, we also detected an increase in concentration of 1.5-3 nm particles in the morning but not their growth in size, which indicates an interrupted NPF process during these undefined days. Vertical mixing was typically stronger during the NPF event days than during the undefined or non-event days. The results shed light on the connection between boundary layer dynamics and NPF.

We present the SMEARcore data infrastructure framework: a collection of modular programs and processing workflows intended for measurement stations and campaigns as a real-time data analysis and management platform. SMEARcore enables new SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) stations to be integrated in a way that is consistent with existing stations and transfers the existing data curation experience to the new station. It establishes robust data pipelines that allow easier diagnosis of problems. We show practical examples of how SMEARcore is utilized at operational measurement stations. This work differs from earlier similar concepts, such as those used at stations within ACTRIS (Aerosols, Clouds and Trace Gases Research Infrastructure) and ICOS (Integrated Carbon Observation System) networks, in three important aspects: firstly, by keeping all the processing under the control of the data owners; secondly, by providing tools for making data interoperable in general instead of harmonizing a particular set of instruments; and thirdly, by being extensible to new instruments. As such it is not meant as a replacement for these infrastructures but to be used in addition to them and to bring structured data curation to more measurement stations not yet using these practices.

New-particle formation (NPF) is globally an important source of climatically-relevant atmospheric aerosols. Here we explore the inter-annual variability and trends in sources and sinks of atmospheric nanoparticles in a boreal forest environment. We look into the precursor vapors leading to the aerosol formation, NPF frequency, as well as the formation and growth rates of the freshly-formed particles. The analysis is based on 16 years of data acquired from the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR II) in Hyytiala, Finland. The results indicate that the probability of NPF is connected to both air mass origin, explaining a large part of the year-to-year variability in the number of NPF events, and concentrations of low-volatile vapours. The probability of NPF increases with increasing gaseous sulphuric acid concentrations, but even better association is found between the NPF probability and product of sulphuric acid and low-volatile organic vapour (proxy) concentrations. While the concentrations of both sulphuric acid (evaluated by proxy) and sulphuric-acid precursor sulphur dioxide decreased over the 16-year measurement period, the new-particle formation and growth rates slightly increased. On the other hand, the proxy concentrations of oxidized organics increased in all seasons except in winter. The contribution of sulphuric acid to the particle growth was minor, and the growth rate had a clear connection with the ambient temperature due to higher emissions of biogenic volatile organic compounds at higher temperatures. For a given sulphuric acid concentration evaluated by proxy, particle formation rates tended to be higher at higher temperatures.

We analyzed size distributions measured continuously at a boreal forest measurement site at Hyytiälä, Finland between 1996 and 2003. From the eight-year data we identified days when new aerosol particle formation was taking place as well as days when no formation was detected, removing days with ambiguous status. The event days were then classified based on whether it was possible to determine formation and growth rates of new particles. These characteristics were then calculated. We found that new particle formation happens frequently in the boreal forest boundary layer, with at least 24% of days containing an event. Events are more probable during spring and autumn than during other times of the year. The average formation rate of particles larger than 3 nm was 0.8 cm–3 s–1, with enhanced rates during spring and autumn. The mean growth rate was 3.0 nm h–1, peaking in summer. The created event database is valuable for future studies of reasons leading to new particle formation in the atmosphere.

We studied variation in concentrations of airborne pollen and other particles of biological origin in a boreal forest in Finland during 2003-2004. The highest concentrations of pollen were observed in late spring and early summer, whereas the peak concentrations of other particles of biological origin (including e.g. fungal spores) occurred in August-September. Although the patterns in concentrations in 2003 and 2004 were similar, the concentration levels were significantly different between the years. The contribution of pollen and other particles of biological origin led to an increase in the measured particulate matter (PM) mass during the pollen season (mass of pollen and other particles of biological origin 5.9 and 0.4 µg [m.sup.-3], respectively, in respect to [PM.sub.total] mass of 9.9 µg [m.sup.-3]) but the effect on total particle number was negligible. The other particles of biological origin constituted the largest fraction of measured primary biological aerosol particle (PBAP) numbers (~99%), whereas pollen showed a higher relative mass fraction (~97%) of PBAP. These results underline the important contribution of PBAP to coarse atmospheric particle mass providing up to 65% of the total mass during the peak pollen season.