ALBERT

Description: Highly oxygenated organic molecules (HOMs) from atmospheric oxidation of alpha-pinene can irreversibly condense to particles and contribute to secondary organic aerosol (SOA) formation. Recently, the formation of nitryl chloride (ClNO2) from heterogeneous reactions, followed by its subsequent photolysis, is suggested to be an important source of chlorine atoms in many parts of the atmosphere. However, the oxidation of monoterpenes such as alpha-pinene by chlorine atoms has received very little attention, and the ability of this reaction to form HOMs is completely unstudied. Here, chamber experiments were conducted with alpha-pinene and chlorine under low- and high-nitrogen-oxide (NOx, NOx=NO+NO2) conditions. A nitrate-based CI-APi-ToF (chemical ionization–atmospheric pressure interface–time of flight) mass spectrometer was used to measure HOM products. Clear distributions of monomers with 9–10 carbon atoms and dimers with 18–20 carbon atoms were observed under low-NOx conditions. With increased concentration of NOx within the chamber, the formation of dimers was suppressed due to the reactions of peroxy radicals with NO. We estimated the HOM yields from chlorine-initiated oxidation of alpha-pinene under low-NOx conditions to be around 1.8 %, though with a substantial uncertainty range (0.8 %–4 %) due to lack of suitable calibration methods. Corresponding yields at high NOx could not be determined because of concurrent ozonolysis reactions. Our study demonstrates that also the oxidation of alpha-pinene by chlorine atoms and yield low-volatility organic compounds.

Description: Our understanding of atmospheric oxidation chemistry has improved significantly in recent years, greatly facilitated by developments in mass spectrometry. The generated mass spectra typically contain vast amounts of information on atmospheric sources and processes, but the identification and quantification of these is hampered by the wealth of data to analyze. The implementation of factor analysis techniques have greatly facilitated this analysis, yet many atmospheric processes still remain poorly understood. Here, we present new insights into highly oxygenated products from monoterpene oxidation, measured by chemical ionization mass spectrometry, at a boreal forest site in Finland in autumn 2016. Our primary focus was on the formation of accretion products, i.e., dimers. We identified the formation of daytime dimers, with a diurnal peak at noontime, despite high nitric oxide (NO) concentrations typically expected to inhibit dimer formation. These dimers may play an important role in new particle formation events that are often observed in the forest. In addition, dimers identified as combined products of NO3 and O3 oxidation of monoterpenes were also found to be a large source of low-volatility vapors at night. This highlights the complexity of atmospheric oxidation chemistry and the need for future laboratory studies on multi-oxidant systems. These two processes could not have been separated without the new analysis approach deployed in our study, where we applied binned positive matrix factorization (binPMF) on subranges of the mass spectra rather than the traditional approach where the entire mass spectrum is included for PMF analysis. In addition to the main findings listed above, several other benefits compared to traditional methods were found.

Description: Ice-nucleating particle (INP) measurements were performed in the boreal environment of southern Finland at the Station for Measuring Ecosystem–Atmosphere Relations (SMEAR II) in the winter–spring of 2018. Measurements with the Portable Ice Nucleation Chamber (PINC) were conducted at 242 K and 105 % relative humidity with respect to water. The median INP number concentration [INP] during a 6-week measurement period was 13 L−1. The [INP] spanned 3 orders of magnitude and showed a general increase from mid-February until early April. No single dominant local or regional sources of INPs in the boreal environment of southern Finland could be identified. Rather, it is hypothesised that the INPs detected at SMEAR II are a result of long-range transport and dilution of INPs sourced far from the measurement site. Despite high variability, the measured [INP] values fall within the range expected for the [INP] measured elsewhere under similar thermodynamic conditions. The [INP] did not correlate with any of the examined parameters during the entire field campaign, indicating that no one single parameter can be used to predict the [INP] at the measurement location during the examined time period. The absence of a correlation across the entire field campaign also suggests that a variety of particles act as INPs at different times, although it was indirectly determined that ambient INPs are most likely within the size range of 0.1–0.5 µm in diameter on average. On shorter timescales, several particle species correlated well with the [INP]. Depending on the meteorological conditions, black carbon (BC), supermicron biological particles and sub-0.1 µm particles, most likely nanoscale biological fragments such as ice-nucleating macromolecules (INMs), correlated with the INP signal. However, an increase in the concentration of any of these particle species may not necessarily lead to the increase in the [INP]; the reasons for this remain unknown. Limitations of the instrumental set-up and the necessity for future field INP studies are addressed.

Description: Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

Description: Secondary organic aerosol (SOA) forms a major part of the tropospheric submicron aerosol. Still, the exact formation mechanisms of SOA have remained elusive. Recently, a newly discovered group of oxidation products of volatile organic compounds (VOCs), highly oxygenated organic molecules (HOMs), have been proposed to be responsible for a large fraction of SOA formation. To assess the potential of HOMs to form SOA and to even take part in new particle formation, knowledge of their exact volatilities is essential. However, due to their exotic, and partially unknown, structures, estimating their volatility is challenging. In this study, we performed a set of continuous flow chamber experiments, supported by box modelling, to study the volatilities of HOMs, along with some less oxygenated compounds, formed in the ozonolysis of α-pinene, an abundant VOC emitted by boreal forests. Along with gaseous precursors, we periodically injected inorganic seed aerosol into the chamber to vary the condensation sink (CS) of low-volatility vapours. We monitored the decrease of oxidation products in the gas phase in response to increasing CS, and were able to relate the responses to the volatilities of the compounds. We found that HOM monomers are mainly of low volatility, with a small fraction being semi-volatile. HOM dimers were all at least low volatility, but probably extremely low volatility; however, our method is not directly able to distinguish between the two. We were able to model the volatility of the oxidation products in terms of their carbon, hydrogen, oxygen and nitrogen numbers. We found that increasing levels of oxygenation correspond to lower volatilities, as expected, but that the decrease is less steep than would be expected based on many existing models for volatility, such as SIMPOL. The hydrogen number of a compound also predicted its volatility, independently of the carbon number, with higher hydrogen numbers corresponding to lower volatilities. This can be explained in terms of the functional groups making up a molecule: high hydrogen numbers are associated with, e.g. hydroxy groups, which lower volatility more than, e.g. carbonyls, which are associated with a lower hydrogen number. The method presented should be applicable to systems other than α-pinene ozonolysis, and with different organic loadings, in order to study different volatility ranges.

Description: The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83±8 % of variation in data, which increased to 96±3 % when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35±7 % of mass), low and semi-volatile oxidised organic aerosols (27±8 % and 12±7 %), biomass burning organic aerosol (11±7 %), a nitrate-containing organic aerosol type (7±2 %), ammonium nitrate (5±2 %), and hydrocarbon-like organic aerosol (3±1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ion-balance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statistics-based approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.

Description: Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statistics-based data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k-means+ + , for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral similarity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification and classification. Robust, statistics-based results and data visualizations also provide important clues to a human analyst on the existence and chemical interpretation of data structures. Applying these methods to a test set of data, aerosol mass spectrometric data of organic aerosol from a boreal forest site, yielded five to seven different recurring pollution types from various sources, including traffic, cooking, biomass burning and nearby sawmills. Additionally, three distinct, minor pollution types were discovered and identified as amine-dominated aerosols.

Description: The impact of aerosols on climate and air quality remains poorly understood due to multiple factors. One of the current limitations is the incomplete understanding of the contribution of oxygenated products, generated from the gas-phase oxidation of volatile organic compounds (VOCs), to aerosol formation. Indeed, atmospheric gaseous chemical processes yield thousands of (highly) oxygenated species, spanning a wide range of chemical formulas, functional groups and, consequently, volatilities. While recent mass spectrometric developments have allowed extensive on-line detection of a myriad of oxygenated organic species, playing a central role in atmospheric chemistry, the detailed quantification and characterization of this diverse group of compounds remains extremely challenging. To address this challenge, we evaluated the capability of current state-of-the-art mass spectrometers equipped with different chemical ionization sources to detect the oxidation products formed from α-Pinene ozonolysis under various conditions. Five different mass spectrometers were deployed simultaneously for a chamber study. Two chemical ionization atmospheric pressure interface time-of-flight mass spectrometers (CI-APi-TOF) with nitrate and amine reagent ion chemistries and an iodide chemical ionization time-of-flight mass spectrometer (TOF-CIMS) were used. Additionally, a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF 8000) and a new “vocus” PTR-TOF were also deployed. In the current study, we compared around 1000 different compounds between each of the five instruments, with the aim of determining which oxygenated VOCs (OVOCs) the different methods were sensitive to and identifying regions where two or more instruments were able to detect species with similar molecular formulae. We utilized a large variability in conditions (including different VOCs, ozone, NOx and OH scavenger concentrations) in our newly constructed atmospheric simulation chamber for a comprehensive correlation analysis between all instruments. This analysis, combined with estimated concentrations for identified molecules in each instrument, yielded both expected and surprising results. As anticipated based on earlier studies, the PTR instruments were the only ones able to measure the precursor VOC, the iodide TOF-CIMS efficiently detected many semi-volatile organic compounds (SVOCs) with three to five oxygen atoms, and the nitrate CI-APi-TOF was mainly sensitive to highly oxygenated organic (O 〉 5) molecules (HOMs). In addition, the vocus showed good agreement with the iodide TOF-CIMS for the SVOC, including a range of organonitrates. The amine CI-APi-TOF agreed well with the nitrate CI-APi-TOF for HOM dimers. However, the loadings in our experiments caused the amine reagent ion to be considerably depleted, causing nonlinear responses for monomers. This study explores and highlights both benefits and limitations of currently available chemical ionization mass spectrometry instrumentation for characterizing the wide variety of OVOCs in the atmosphere. While specifically shown for the case of α-Pinene ozonolysis, we expect our general findings to also be valid for a wide range of other VOC–oxidant systems. As discussed in this study, no single instrument configuration can be deemed better or worse than the others, as the optimal instrument for a particular study ultimately depends on the specific target of the study.

Description: While the role of highly oxygenated molecules (HOMs) in new particle formation (NPF) and secondary organic aerosol (SOA) formation is not in dispute, the interplay between HOM chemistry and atmospheric conditions continues to draw significant research attention. During the Influence of Biosphere-Atmosphere Interactions on the Reactive Nitrogen budget (IBAIRN) campaign in September 2016, profile measurements of neutral HOMs below and above the forest canopy were performed for the first time at the boreal forest SMEAR II station. The HOM concentrations and composition distributions below and above the canopy were similar during daytime, supporting a well-mixed boundary layer approximation. However, much lower nighttime HOM concentrations were frequently observed at ground level, which was likely due to the formation of a shallow decoupled layer below the canopy. Near the ground HOMs were influenced by the changes in the precursors and oxidants and enhancement of the loss on surfaces in this layer, while the HOMs above the canopy top were not significantly affected. Our findings clearly illustrate that near-ground HOM measurements conducted under stably stratified conditions at this site might only be representative of a small fraction of the entire nocturnal boundary layer. This could, in turn, influence the growth of newly formed particles and SOA formation below the canopy where the large majority of measurements are typically conducted.