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Filter Inlet for Gases and Aerosols (FIGAERO) inlet coupled with Time-of-Flight Chemical Ionization Mass Spectrometers (ToF-CIMS) have been successfully employed in numerous studies during past years (Thornton et. al., 2020). The instrument can be used to study both gas-phase and particle-phase chemical compounds over a broad range of chemical functionalities. The inbuilt controlled thermal desorption mechanism also allows for the investigation of volatility of the compounds present in the particle phase. Such a particle volatility measurement using FIGAERO-ToF-CIMS relies on accurate identification of the Tmax for individual compounds, i.e. the temperatures at which highest respective signals are observed. These Tmax values can be converted to saturation vapor pressure Psat and saturation mass concentration C* values with a reliable calibration (Ylisirniö et. al., 2021). However, due to a lack of calibration compounds with known Psat at the low end of the volatility range (Psat

Early growth of atmospheric particles is essential for their survival and ability to participate in cloud formation. Many different atmospheric vapors contribute to the growth, but even the main contributors still remain poorly identified in many environments, such as high-altitude sites. Based on measured organic vapor and sulfuric acid concentrations under ambient conditions, particle growth during new particle formation events was simulated and compared with the measured particle size distribution at Chacaltaya Global Atmosphere Watch station in Bolivia (5240 m a.s.l.) during April and May 2018, as a part of the SALTENA (Southern Hemisphere high-ALTitude Experiment on particle Nucleation and growth) campaign . The simulations showed that the detected vapors were sufficient to explain the observed particle growth, although some discrepancies were found between modelled and measured particle growth rates. This study gives an insight on the key factors affecting the particle growth on the site. Low volatile organic compounds were found to be the main contributor to the particle growth, covering on average 65 % of simulated particle mass in particle with diameter of 40 nm In addition, sulfuric acid had a major contribution to the particle growth, covering at maximum 39 % of simulated particle mass in 40 nm particle during periods when volcanic activity was detected on the area, suggesting that volcanic emissions can greatly enhance the particle growth.

The multi-scheme chemical ionisation inlet 1 (MION1) allows fast switching between measuring atmospheric ions without chemical ionisation and neutral molecules by multiple chemical ionisation methods. In this study, the upgraded multi-scheme chemical ionisation inlet 2 (MION2) is presented. The new design features improved ion optics that increase the reagent ion concentration, a generally more robust operation and the possibility to run multiple chemical ionisation methods with the same ionisation time. To simplify the regular calibration of MION2, we developed an open-source flow reactor chemistry model (MARFORCE) to quantify the chemical production of sulfuric acid (H2SO4), hypoiodous acid (HOI) and hydroperoxyl radical (HO2). MARFORCE simulates convection-diffusion-reaction processes inside typical cylindrical flow reactors with uniform inner diameters. The model also provides options to simulate the chemical processes 1) when two flow reactors with different inner diameters are connected together and 2) when two flows are merged into one (connected by a Y-shape tee), but with reduced accuracy. Additionally, the chemical mechanism files in the model are compatible with the widely-used Master Chemical Mechanism, thus allowing future adaptation to simulate other chemical processes in flow reactors. We further carried out detailed characterisation of the bromide (Br−) and nitrate (NO3−) chemical ionisation methods with different ionisation times. We calibrated H2SO4, HOI and HO2 by combining gas kinetic experiments with the MARFORCE model. Sulfur dioxide (SO2), water (H2O) and molecular iodine (I2) were evaluated using dilution experiments from a gas cylinder (SO2), dew point mirror measurements (H2O), and a derivatization approach in combination with high-performance liquid chromatography quantification (I2), respectively. We find that the detection limit is negatively correlated with the fragmentation enthalpy of the analyte-reagent ion (Br−) cluster, i.e., a stronger binding (larger fragmentation enthalpy) leads to a lower detection limit. Additionally, a moderately longer reaction time enhances the detection sensitivity thus decreasing the detection limit. For example, the detection limit for H2SO4 is estimated to be 2.9 × 104 molec. cm−3 with a 300 ms ionisation time. A direct comparison suggests that this is even better than the widely-used Eisele-type chemical ionisation inlet. While the NO3− chemical ionisation method is generally more robust, we find that the Br− chemical ionisation method (Br−-MION2) is significantly affected by air water content. Higher air water content results in lower sensitivity for HO2 and SO2 within the examined conditions. On the other hand, a steep sensitivity drop of H2SO4, HOI and I2 is only observed when the dew point is greater than 0.5–10.5 ℃ (equivalent to 20–40 % RH; calculated at 25 ℃ hereafter). Future studies utilising atmospheric pressure Br− chemical ionisation method, including Br−-MION2, should carefully address the humidity effect on a molecular basis. By combining methods such as water-insensitive NO3−-MION2 with Br−-MION2, MION2 should be able to provide greater details of air composition than either of these methods alone. Combining instrument voltage-scanning, chemical kinetic experiments and quantum chemical calculations, we find that the HIO3 detection is not interfered with by iodine oxides under atmospherically relevant conditions. The IO3−, HIO3NO3− and HIO3Br− ions measured using the Br− and NO3− chemical ionisation methods are primarily, if not exclusively, produced from gaseous HIO3 molecules.

Despite a large number of studies, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in different sizes in total of for 21 measurement sites in Europe and Arctic. For 13 of those, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in-situ observations from Europe and five earth system models (ESM). We found that the trends of particle number concentrations were mostly consistent and decreasing in both, measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, were typically stronger in northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories. For EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, for others, the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showing clear differences in concentrations between remote and urban sites. To conclude, although anthropogenic mass emissions are harmonized in models, trends in different sized particles vary among the model due to assumptions in emission sizes and differences in how models treat size dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions.

Accurate information on gas-to-particle partitioning is needed to model secondary organic aerosol formation. However, determining reliable saturation vapor pressures of atmospherically relevant multifunctional organic compounds is extremely difficult. We estimated saturation vapor pressures of α-pinene ozonolysis derived secondary organic aerosol constituents using FIGAERO-CIMS experiments and COSMO-RS theory. We found a good agreement between experimental and computational saturation vapor pressures for molecules with molar masses around 190 g mol−1 and higher, most within a factor of 3 comparing the average of the experimental vapor pressures and the COSMO-RS estimate of the isomer closest to the experiments. Smaller molecules likely have saturation vapor pressures that are too high to be measured using our experimental setup. The molecules with molar masses below 190 g mol−1 that have several orders of magnitude difference between the computational and experimental saturation vapor pressures observed in our experiments are likely products of thermal decomposition occurring during thermal desorption. For example, dehydration and decarboxylation reactions are able to explain some of the discrepancies between measured and calculated saturation vapor pressures. Based on our estimates, FIGAERO-CIMS can best be used to determine saturation vapor pressures of compounds with low and extremely low volatilities.

Efforts have been spent on investigating the isothermal evaporation of α-pinene SOA particles at ranges of conditions and decoupling the impacts of viscosity and volatility on evaporation. However, little is known about the evaporation behavior of SOA particles from biogenic organic compounds other than α-pinene. In this study, we investigated the isothermal evaporation behaviors of α-pinene (αpin) and sesquiterpene mixture (SQTmix) SOA particles under a series of relative humidity (RH) conditions. With a set of in-situ instruments, we monitored the evolution of particle size, volatility, and composition during evaporation. Our finding demonstrates that the SQTmix SOA particles evaporated slower than the αpin ones at any set of RH (expressed with the volume fraction remaining (VFR)), which is primarily due to their lower volatility and possibly aided by higher viscosity under dry conditions. We further applied positive matrix factorization (PMF) to thermal desorption data containing volatility and composition information. Analyzing the net change ratios (NCRs) of each PMF-resolved factor, we can quantitatively compare how each sample factor evolves with increasing evaporation time/RH. When sufficient particulate water content was present in either SOA system, the most volatile sample factor was primarily lost via evaporation and changes in other sample factors were mainly governed by aqueous-phase processes. The evolution of each sample factor of SQTmix SOA particles was controlled by a single type of process, whereas for αpin SOA particles it was regulated by multiple processes. As indicated by the coevolution of VFR and NCR, the effect of aqueous-phase processes could vary from one to another according to particle type, sample factors and evaporation timescale.

Biogenic secondary organic aerosol (BSOA) constitutes a major fraction of aerosol over boreal forests. As the emissions of BSOA precursors are temperature dependent, changes in temperature have potentially important implications on regional aerosol radiative forcing. Here, we have used long-term aerosol composition and temperature data measurements from a boreal forest site together with remote sensing observations of aerosol and cloud properties to investigate the effect of increasing temperature on organic aerosol mass loadings, and further on aerosol direct and indirect radiative effects. The analysis was based on 7 years of measurements done at Hyytiälä, Southern Finland, and they cover the summer months (July-August) between 2012-2018. We limited the analyses to these summer months to isolate the temperature dependence of the organic mass loadings from the seasonal effects arising from the vegetation growth cycle. Our analysis showed that organic aerosol loadings and cloud condensation nuclei concentrations increased in concert with surface temperature. Furthermore, we found that cloud reflectivity increased when the organic aerosol loadings increased. This research presents the first direct observational evidence on the effect of BSOA on cloud properties and their climatic significance.

Multiple atmospheric properties were measured semi-continuously in the Budapest platform for Aerosol Research and Training laboratory, which represents the urban background for the time interval of 2008–2018. Data of 6 full measurement years during a decennial time interval were subjected to statistical time trend analyses by an advanced dynamic linear model and a generalized linear mixed model. The main interest in the analysed data set was on particle number concentrations in the diameter ranges from 6 to 1000 nm (N6−1000), from 6 to 100 nm (N6−100, ultrafine particles), from 25 to 100 nm (N25−100) and from 100 to 1000 nm (N100−1000). These data were supported by concentrations of SO2, CO, NO, NOx, O3, PM10 mass, as well as air temperature, relative humidity, wind speed, atmospheric pressure, global solar radiation, condensation sink, gas-phase H2SO4 proxy, classes of new aerosol particle formation (NPF), and growth events and meteorological macro-circulation patterns. The trend of the particle number concentrations derived as a change in the statistical properties of background state of the data set decreased in all size fractions over the years. Most particle number concentrations showed decreasing decennial statistical trends. The estimated annual mean decline of N6−1000 was (4–5) % during the 10-year measurement interval, which corresponds to a mean absolute change of −590 cm−3 in a year. This was interpreted as a consequence of the decreased anthropogenic emissions at least partly from road traffic alongside household heating and industry. Similar trends were not observed for the air pollutant gases. Diurnal statistical patterns of particle number concentrations showed tendentious variations, which were associated with a typical diurnal activity–time pattern of inhabitants in cities, particularly of vehicular road traffic. The trend patterns for NPF event days contained a huge peak from late morning to late afternoon, which is unambiguously caused by NPF and growth processes. These peaks were rather similar to each other in the position, shape and area on workdays and holidays, which implies that the dynamic and timing properties of NPF events are not substantially influenced by anthropogenic activities in central Budapest. The diurnal pattern for N25−100 exhibited the largest relative changes, which were related to particle emissions from high-temperature sources. The diurnal pattern for N100−1000 – which represents chemically and physically aged particles of larger spatial scale – were different from the diurnal patterns for the other size fractions.