Aerosol Material Research Articles

Optical Properties of Biomass Burning Aerosols from Simulated Wildfires and Prescribed Fires with Representative Fuel Beds from the Southeast United States.

We report measurements of the absorption Ångström exponent (AAE) and single scattering albedo (SSA) of biomass burning aerosol from the combustion of fuel beds representing three eco-regions of the Southeast U.S. (Piedmont, Coastal Plain, and Blue Ridge Mountains) with moisture content representative of wildfires and prescribed fires. We find a strong correlation between the AAE and SSA for both simulated wildfires (low fuel moisture) and prescribed fires (higher fuel moisture). For wildfires, the AAE and SSA are strongly dependent on the eco-region of the fuel bed and span a much wider range (AAE = 1.3-4.2, SSA = 0.75-0.97) than they do for prescribed fires (AAE = 2.4-3.1, SSA = 0.88-0.96). The AAE and SSA are also found to be correlated with the fraction of total carbon that is elemental carbon (f EC) for both wildfires and prescribed fires, but the range of f EC observed (0.02-0.14) from the fuel beds is much smaller than that reported previously from laboratory studies using individual fuels. The observations from the present study suggest that fuel-bed composition and moisture content are significant factors in determining the relative amount of organic material in biomass burning aerosols and, consequentially, their optical properties.

Preparation of antibacterial composite aerogel for biomedical purposes based on alginate-chitosan complex and calcium carbonate

Aerogel composites were synthesized on the basis of the sodium alginate-chitosan interpolymer complex with the inclusion of calcium carbonate microparticles and supercritical drying. It is shown that the textural characteristics of materials do not depend on the morphology of calcium carbonate particles: the specific surface area of aerogels is almost the same for all materials and amounts to 380–400 m2/g. The developed porous structure of composites along with the polyelectrolyte nature determines their high water absorption— up to 110 g/g. To impart antimicrobial properties, the materials were impregnated with atranorin isolated from the lichen Hypogymnia physodes, which has a pronounced inhibitory effect on the bacterium Proteus mirabilis, which is the main causative agent of wound infections. The minimum suppressive concentration of atranorine is 1 mg/ml. The release of the main amount of atranorine aerosol material included in the matrix occurs within 4 hours and amounts to 50%.

Acoustic levitation combined with laboratory-based small-angle X-ray scattering (SAXS) to probe changes in crystallinity and molecular organisation.

Single particle levitation techniques allow us to probe samples in a contactless way, negating the effect that surfaces could have on processes such as crystallisation and phase transitions. Small-angle X-ray scattering (SAXS) is a common method characterising the nanoscale order in aggregates such as colloidal, crystalline and liquid crystalline systems. Here, we present a laboratory-based small-angle X-ray scattering (SAXS) setup combined with acoustic levitation. The capability of this technique is highlighted and compared with synchrotron-based levitation-SAXS and X-ray diffraction. We were able to follow the deliquescence and crystallisation of sucrose, a commonly used compound for the study of viscous atmospheric aerosols. The observed increased rate of the deliquescence-crystallisation transitions on repeated cycling could suggest the formation of a glassy sucrose phase. We also followed a reversible phase transition in an oleic acid-based lyotropic liquid crystal system under controlled humidity changes. Our results demonstrate that the coupling of acoustic levitation with an offline SAXS instrument is feasible, and that the time resolution and data quality are sufficient to draw physically meaningful conclusions. There is a wide range of potential applications including topics such as atmospheric aerosol chemistry, materials science, crystallisation and aerosol spray drying.

Formation of In‐Cloud Aqueous‐Phase Secondary Organic Matter and Related Characteristic Molecules

AbstractThe formation process of in‐cloud aqueous‐phase secondary organic matter (aqSOM) and its characteristics are unclear. Herein, water‐soluble inorganic ions, oxalate, and water‐soluble organic carbon (WSOC) were determined in cloud water and aerosol (PM2.5) samples simultaneously collected at a remote mountain site in southern China during spring 2018 and winter 2020. The molecular compositions of water‐soluble organic matter (WSOM) in cloud water and aerosols were analyzed by a Fourier transform ion cyclotron resonance mass spectrometer in negative electrospray ionization (ESI‐) mode. The results showed that the mean concentration of WSOC was 6.27–8.54 mg C L−1 in cloud water and 0.60–1.37 μg C m−3 in aerosols. The strong correlation observed between WSOM and aqueous secondary matter (e.g., NO3− and oxalate), the positive matrix factorization results, and the elevated WSOM/K+ ratios observed in cloud water suggested enhanced aqSOM formation in cloud water. According to random forest analysis, the factors related to in‐cloud WSOM variation mainly included secondary ions, K+, cloud water pH, and atmospheric NOx. Additionally, 37 characteristic in‐cloud aqSOM molecules, classified as ‐Ox, ‐NOx, ‐N2Ox, and ‐N1‐2OxS, mainly consisting of dicarboxylic acids, nitrophenols, and dinitrophenols, were identified using linear discriminant analysis effect size (LefSe). The characteristic N‐ and S‐containing molecules in in‐cloud aqSOM with carbon numbers >10 had low or extremely low volatility; therefore, they might contribute to secondary organic aerosol formation after droplet evaporation. The results revealed the modifying effects of in‐cloud processes on aerosol organic composition at the molecular level and could improve our understanding of aerosol–cloud interactions.

Exploring band-free Raman microspectrometry combined with PCA and MCR-ALS for size-resolved forensic analysis of uranium in aerosols in a model nuclear atmosphere

Achieving non-destructive micrometer-scale molecular and structural analysis of uranic materials in atmospheric aerosols with traditional methodologies is a challenge. Spatially resolved analysis of uranium in actinide-bearing aerosols is critical for nuclear forensics. Although laser Raman microspectrometry enables this, for the normally low uranium concentrations in the aerosols the spectra are indiscernible (band-free) against pronounced background: trace analysis requires a push in analytical strategy. We combined laser Raman microspectrometry (utilizing two lasers (λ = 532 nm, λ = 785 nm)) with principal component analysis (PCA) and multivariate curve resolution–alternate least squares (MCR-ALS) to perform size-resolved analysis of uranium in aerosols. Uranium-specific Raman scatter bands corresponding to uranyl nitrate (860 cm−1), uranium sulphate (868 cm−1), uranyl chloride (816 cm−1) and uranium trioxide (839 cm−1) were detected. The 816 cm−1, 854 cm−1, 868 cm−1 bands were resolved by MCR-ALS and used to identify and map uranium in PM4.5 size aerosols. Based on spectral feature selection of the signature bands, PCA identified two sources of aerosol particles in model nuclear atmosphere - Sea spray for PM4.5 and re-suspension of ‘nuclear’ dust from a rare earth element (REE) mine for PM2.5. The MCR-ALS-resolved uranium bands showed the potential for attributive nuclear forensic analysis.

Predicting Real Refractive Index of Organic Aerosols From Elemental Composition

AbstractAccurate estimates of aerosol refractive index (RI) are critical for modeling aerosol‐radiation interaction, yet this information is limited for ambient organic aerosols, leading to large uncertainties in estimating aerosol radiative effects. We present a semi‐empirical model that predicts the real RI n of organic aerosol material from its widely measured oxygen‐to‐carbon (O:C) and hydrogen‐to‐carbon (H:C) elemental ratios. The model was based on the theoretical framework of Lorenz‐Lorentz equation and trained with n‐values at 589 nm () of 160 pure compounds. The predictions can be expanded to predict n‐values in a wide spectrum between 300 and 1,200 nm. The model was validated with newly measured and literature datasets of n‐values for laboratory secondary organic aerosol (SOA) materials. Uncertainties of predictions for all SOA samples are within 5%. The model suggests that ‐values of organic aerosols may vary within a relatively small range for typical O:C and H:C values observed in the atmosphere.

Development and evaluation of an improved offline aerosol mass spectrometry technique

Abstract. The offline aerosol mass spectrometry technique is a useful tool for the source apportionment of organic aerosol (OA) in areas and periods during which an aerosol mass spectrometer (AMS) is not available. However, the technique is based on the extraction of aerosol samples in water, while several atmospheric OA components are partially or fully insoluble in water. In this work an improved offline technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing significantly the uncertainty of the corresponding source apportionment. A major advantage of the proposed approach is that no corrections are needed for the offline analysis to account for the limited water solubility of some OA components. The improved offline AMS analysis was tested in three campaigns: two during winter and one during summer. Collocated online AMS measurements were performed for the evaluation of the offline method. Source apportionment analysis was performed separately for the online and the offline measurements using positive matrix factorization (PMF). The PMF results showed that the fractional contribution of each factor to the total OA differed between the online and the offline PMF results by less than 15 %. The differences in the AMS spectra of the factors of the two approaches could be significant, suggesting that the use of factor profiles from the literature in the offline analysis may lead to complications. Part of the good agreement between the online and the offline PMF results is due to the ability of the improved offline AMS technique to capture a bigger part of the OA, including insoluble organic material. This was evident by the significant fraction of submicrometer suspended insoluble particles present in the water extract and by the reduced insoluble material on the filters after the extraction process. More than half of the elemental carbon (EC) was on average missing from the filters after the water extraction. Significant EC concentrations were measured in the produced aerosol that was used as input to the AMS during the offline analysis.

Compound-specific radiocarbon analysis of benzene polycarboxylic acids for source apportionment of polyaromatic organic matter in ambient aerosols

Polyaromatic organic matter (POM) is an important group of pollutants and light absorbers in ambient aerosols, which consists of a wide range of chemicals with fused benzene rings. POM in ambient aerosols is mainly derived from the incomplete combustion of fossil fuel and biomass. Source apportionment of POM is crucial for advising efficient mitigation of anthropogenic emissions, but that is a challenge due to the complicated composition of POM and ambient aerosols. Benzene polycarboxylic acids (BPCAs) have recently been introduced as molecular markers of atmospheric POM. Compound-specific radiocarbon analysis of BPCAs is expected to be a powerful tool for apportioning fossil sources and contemporary (i.e., biomass burning) sources of POM in ambient aerosols, yet this application is still lacking. We developed a method for radiocarbon analysis of BPCAs substituted with 3–6 carboxylic groups (B6CA, B5CA, B4CAs and B3CAs). BPCAs were isolated with preparative liquid chromatography with high recoveries (≥85%). The method is validated with reference materials with fossil and contemporary radiocarbon signatures. Successful radiocarbon analysis of BPCAs was achieved for these reference materials after correcting for the presence of average blanks (B6CA: 1.2 ± 0.2 μg, B5CA: 2.3 ± 0.6 μg, individual B4CAs: 2.7 ± 0.2 μg and individual B3CAs: 6.9 ± 0.7 μg). Source apportionment of POM based on radiocarbon analysis of BPCAs was performed for an urban dust reference material, as well as bulk aerosols and water-soluble, methanol-soluble fractions of ambient aerosols from a megacity of southern China. The results show varied contributions of fossil and contemporary sources among different POM fractions.

Machine-Learning-Based Prediction of the Glass Transition Temperature of Organic Compounds Using Experimental Data.

Knowledge of the glass transition temperature of molecular compounds that occur in atmospheric aerosol particles is important for estimating their viscosity, as it directly influences the kinetics of chemical reactions and particle phase state. While there is a great diversity of organic compounds present in aerosol particles, for only a minor fraction of them experimental glass transition temperatures are known. Therefore, we have developed a machine learning model designed to predict the glass transition temperature of organic molecular compounds based on molecule-derived input variables. The extremely randomized trees (extra trees) procedure was chosen for this purpose. Two approaches using different sets of input variables were followed. The first one uses the number of selected functional groups present in the compound, while the second one generates descriptors from a SMILES (Simplified Molecular Input Line Entry System) string. Organic compounds containing carbon, hydrogen, oxygen, nitrogen, and halogen atoms are included. For improved results, both approaches can be combined with the melting temperature of the compound as an additional input variable. The results show that the predictions of both approaches show a similar mean absolute error of about 12-13 K, with the SMILES-based predictions performing slightly better. In general, the model shows good predictive power considering the diversity of the experimental input data. Furthermore, we also show that its performance exceeds that of previous parameterizations developed for this purpose and also performs better than existing machine learning models. In order to provide user-friendly versions of the model for applications, we have developed a web site where the model can be run by interested scientists via a web-based interface without prior technical knowledge. We also provide Python code of the model. Additionally, all experimental input data are provided in form of the Bielefeld Molecular Organic Glasses (BIMOG) database. We believe that this model is a powerful tool for many applications in atmospheric aerosol science and material science.

Application of DIAL/HSRL and CATCH algorithm-based methodologies for surface PM2.5 concentrations during the KORUS-AQ campaign

Particulate matter with an aerodynamic diameter of equal to or less than 2.5 μm (PM2.5) has been found to have a serious adverse effect on human health and the environment. While the importance of measuring PM2.5 has been demonstrated, doing so remotely remains challenging. In this study, methodologies for the assessment of aerosol PM2.5 and chemical composition based on a combination of regional and global models and active remote sensing were evaluated against surface observations from the KORUS-AQ campaign. The model outputs from the Community Multiscale Air Quality (CMAQ) and GEOS-Chem were used and were available at the KORUS-AQ campaign data archive. For remote sensing, aerosol extinction and derived aerosol types available from NASA Langley Airborne Differential Absorption Lidar (DIAL)/High Spectral Resolution Lidar (HSRL) flying onboard DC-8 aircraft were used. A revised version of the algorithm, which incorporates size-specific aerosol dry mass extinction efficiencies for sulfate, nitrate, and ammonia as well as organic matter, is also presented. The PM2.5 concentration estimates were compared with measurements taken at the ground stations. The estimated mean absolute error between the ground station measurements and the remote-sensing-based methodologies was significantly lower compared to the models. The data analysis has shown that uncertainties in relative humidity values, the presence of particles larger than 2.5 μm in diameter, and the abundance of black carbon and organic matter in Asian aerosol were unlikely to explain the differences between measured and predicted surface PM2.5. Local meteorology was found to play a key role influencing the spatiotemporal variability of aerosols and the most important factor determining the agreement between the estimated and ground site-measured PM2.5. The lowest mean absolute error was found for the May 1–16 period, when aerosols were well mixed within the mixing layer and homogeneous across the temporal (1 h) and spatial (8 km) scales used in this study. Under these conditions, the methodologies presented here could give reasonable estimates of PM2.5 concentration and derived chemical composition over South Korea when HSRL data are available.

Insoluble lipid film mediates transfer of soluble saccharides from the sea to the atmosphere: the role of hydrogen bonding

Abstract. Saccharides are a large portion of organic matter in sea spray aerosol (SSA). Although they can affect climate-related properties of SSA, the mechanism through which saccharides are transferred from bulk seawater to the ocean surface and ultimately into SSA is still debated. Here, the transfer of small soluble saccharides was validated using a controlled plunging jet sea spray aerosol generator to better understand the wide range of particle properties produced by natural seawater mixed with model organic species, glucose and trehalose. We showed that both soluble saccharides can promote the production of SSA particles, and the presence of trehalose could increase the SSA number concentration by 49.4 %. Conversely, the role of the insoluble fatty acid film on the seawater surface greatly reduced the production of SSA. The resulting inorganic–organic mixed particles identified by the transmission electron microscope (TEM) showed typical core–shell morphology. A Langmuir model was used to parameterize the adsorption and distribution of saccharide into SSA across the bubble surface, while infrared reflection–absorption spectroscopy (IRRAS) combined with Langmuir isotherms was undertaken to examine the effects of aqueous subphase soluble saccharides with various concentrations on the phase behavior, structure, and ordering of insoluble lipid monolayers adsorbed at the air/water interface. We found that the adsorption of glucose and trehalose on the fatty acid monolayer led to the expansion of the mean molecular area. Saccharide–lipid interactions increased with increasing complexity of the saccharide in the order of glucose < trehalose. In a seawater solution, the effects of dissolved saccharides on the ordering and organization of fatty acid chains were muted. The enhancement of the carbonyl band to the low wavenumber region implied that soluble saccharides can form new hydrogen bonds with fatty acid molecules by displacing large amounts of water near the polar headgroups of fatty acids. Our results indicate that the interaction between soluble saccharides and insoluble fatty acid molecules through hydrogen bonds is an important component of the sea–air transfer mechanism of saccharides.

Relationships of the Hygroscopicity of HULIS With Their Degrees of Oxygenation and Sources in the Urban Atmosphere

AbstractHumic‐like substances (HULIS) are unresolved compounds isolated from organic matter in atmospheric aerosols. Understanding the chemical structures and sources that control the hygroscopicity of HULIS is important for predicting its environmental impacts and possibly useful for parameterization of the hygroscopicity of organic aerosol (OA). Here, the hygroscopic growth of HULIS from total suspended particles samples in Beijing was analyzed using a hygroscopicity tandem differential mobility analyzer. The hygroscopicity parameter of HULIS (κHULIS) was determined to be 0.06 ± 0.03, and was found to correlate positively with O:C and f44 from offline aerosol mass spectrometry. Additionally, κHULIS was correlated positively with oxygenated organic aerosol (OOA) and correlated negatively with cooking OA and biomass burning OA, for which the source‐related OA types were from mass‐spectral‐based positive matrix factorization analyses. Further analysis resolved substantial κ values of 0.09 and 0.22, respectively, for less‐oxidized and more‐oxidized OOA, in contrast to the low κ values for cooking OA and biomass burning OA. Extensions of O:C‐ and source‐based parameterizations reasonably estimated the hygroscopicity of total OA with a moderate contribution from HULIS. This result and the fact that the obtained OOA contributions to κ of OA were similar to those from different environments suggest the applicability of parameterizing the hygroscopicity for a wide range of OA in particular based on source‐related structural characteristics.

Геохимическая активность снега и послойная изменчивость изотопного состава кислорода (δ18О) в снежной толще в условиях разной запыленности приземной атмосферы

The layered distribution of the isotopic composition (18O) in the snow mass under conditions of different dust pollution of the near-surface atmosphere was studied on the territory of two scientific test sites of the IAO SB RAS: the Fonovaya observatory and the suburban BEK test site (Tomsk). Interlayer differences in isotopic characteristics and the activity of snow chemical reactions were evaluated in conjunction with the analysis of the dispersed composition of the precipitated aerosol substance, the radiation transparency of snow in the UV range, and taking into account reverse trajectories of air mass transfer. Interlayer fluctuations in 18O values were established, the variability of which increased in layers confined to the thermal diffusion geochemical barrier. We suggested that due to the geochemical activity of snow and its ultraviolet transparency, as well as the presence of iron-containing dust-aerosol particles in the snow mass, conditions arose that initiated photoactivated snow-chemical reactions. Their occurrence may be accompanied by free radical oxidation of the precipitated aerosol matter and the formation of stable photoreaction products, which may be evidenced by the established post-sedimentary interlayer differences in the isotope stratification of the snow mass.

ВПЛИВ НА ВАРТІСТЬ ЗЕМЕЛЬНИХ ДІЛЯНОК ПОХИБОК ПОЛОЖЕННЯ МЕЖ ОТРИМАНИХ ІЗ ВИКОРИСТАННЯМ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ

Purpose. The study of the effect of errors in the position of landmarks obtained using unmanned aerial vehicles, on the value of real estate. Aerospace for several decades is an effective tool for conducting geodetic works, geophysical studies and conducting various types of monitoring, but such methods are not used to assess the real estate. Modern technologies for the creation of topographical and cadastral plans are based precisely on the use of digital aerosol materials. However, the cost of using airplanes and helicopters for local large-scale take-off is on an order of magnitude higher and therefore an alternative solution is the use of UAVs. Methodology. Unmanned aerial vehicles (UAVs) are most often used as a cheap alternative to conventional airplanes from airplanes, helicopters, telescopes and satellite (satellite) takeoffs. In addition to significant cost-effectiveness (cheaper by ten times), UAVs have additional privileges, namely: low altitude, point-and-shoot, mobility, environmental cleanliness of flights. Land management works are mostly carried out unsystematically and without reliable control, and therefore the application of usual geodetic methods and measurement results does not allow obtaining the required precision of the coordinates of the points, boundaries and the film basis. All this leads to the problems of combining the boundaries of adjoining areas due to the use of poor-quality cadastral information in databases that were formed over a significant period of time by the regional centers of the SLC. Results. The use of UAVs proves the importance of them to perform valuation works, which will increase the accuracy of the determination of the coordinates of the boundaries of real estate and significantly accelerate the evaluation procedure. It is established that for large settlements, the accuracy of the determination of the coordinates should be significantly increased, since the cost of real estate in these settlements is quite large and, accordingly, the errors in determining the coordinates of real estate objects lead to errors in the cost of real estate objects of the settlement, which is legally unacceptable and therefore For very large cities it is expedient to create shots at low altitudes and gradually increase the accuracy of photographing the terrain. Scientific novelty and practical significance. The importance of using UAVs for assessing the value of real estate objects has been proved, as the resulting calculations result in average square errors in the value of 1 sq. M of real estate, amounting to less than 0.3% of its total value. The practical significance of the use of UAVs lies in the existence of additional advantages over traditional shooting methods, namely the possibility of obtaining a super-distinction (one and ten centimeters) in the terrain; the detailed removal of small objects and small areas where it is completely unprofitable or technically impossible to do in other ways, for example, in urban development.

Particles of synthetic polymers in fresh snow in the northwest of the Kola peninsula in 2020–2021

Pollution of the hydrosphere, the atmosphere and the upper lithosphere by synthetic polymers has now become a global human problem. In this connection, a study of newly fallen solid precipitation was carried out from December 2020 to April 2021 in the north-west of the Kola Peninsula to identify polymeric particles that could be absorbed from the atmosphere by snow crystals. Snow sampling was carried out along highways at a distance from roads in calm weather. In the laboratory, melt snow water was filtered through nuclear filters, which were scanned under a binocular MBS-10 microscope to take account of insoluble polymer fibers. Simultaneously, filters stained with a Nile Red solution were analyzed under a Carl Zeiss AxioImager D1epifluorescent microscope for microplastic investigations. Synthetic polymer particles were identified among the aerosol material. The polymeric particle composition was strongly dominated by irregularly shaped polymer micro-fragments. Polymer macrofibres and polymer microfibers were also constantly present. By the research carried out the first assessment of polymeric particles flows to the earth surface with solid precipitation in the north-west of the Kola Peninsula was done.

Proteinaceous Matter and Liquid Water in Fine Aerosols in Nanchang, Eastern China: Seasonal Variations, Sources, and Potential Connections

AbstractThe transformation of aerosol proteinaceous matter (PrM) has potentially adverse environmental and health effects. The origins and atmospheric processes of PrM have obtained an increasing interest, but there are still large uncertainties. Although aerosol liquid water (ALW) has been found to be vital in numerous atmospheric processes, its impact on atmospheric degradation of PrM remains poorly understood. ALW, proteins, and low molecular weight PrM (LMW PrM, <10 kDa) were investigated in fine aerosols (PM2.5) collected in urban and suburban Nanchang (Eastern China) over a 1‐year period. The average concentrations of proteins and LMW PrM in the urban center were higher than those in the suburban area. Urban PrM tended to increase from cool season to warm season, which was opposite to the case of suburban PrM. These differences could be attributed to varied sources and atmospheric processes of PrM. Increase in ALW was prominent from the suburban site to the urban site, which was attributable to increased anthropogenic nitrate and sulfate. LMW PrM can be degraded from higher molecular weight PrM by ozone. Furthermore, correlation analysis between LMW PrM and ozone and ALW suggested that the enhanced ALW in the urban center facilitated the ozone‐induced LMW PrM release. The ALW‐related protein degradation was further supported by ozone exposure experiments with bovine serum albumin and PM2.5 samples under dry condition. Our findings suggest that ALW is a crucial promoter during PrM degradation by ozone, providing new insights into atmospheric transformation of proteins.

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

Particle Formation from Photooxidation of αpinene, Limonene, and Myrcene.

We present measurements of the effect of first-generation secondary organic aerosol (SOA) material on the growth of ∼10 nanometer diameter seed particles composed of sulfuric acid and water. Experiments were performed in an atmospheric pressure, vertically aligned flow reactor where OH was produced from HONO photolysis in the presence of either SO2 or a monoterpene. For typical conditions, organic compounds at ∼300 ppbv are exposed to photooxidation for a time of ∼80 s at a [OH] of about 6 × 106 cm-3: thus, oxidation products have minimal OH exposure. The measured size changes of the sulfuric acid seed particles can then be attributed to the uptake of first-generation products. Along with descriptions of the apparatus and the procedure, the analysis to obtain SOA yields by comparing them to growth with H2SO4(g) is detailed. Results from photooxidation experiments of αpinene, limonene, and myrcene give SOA yields of 0.040, 0.084, and 0.16, respectively. These SOA yields roughly double with each addition of a double bond to the compound. The αpinene and limonene results are in accord with the results of many previous SOA experiments, while the myrcene SOA yield stands alone. Photooxidation of myrcene also led to significant nucleation, and the species responsible is comparable to H2SO4 at a 35% relative humidity in its nucleation capability.

Wildfire atmospheric chemistry: climate and air quality impacts

Wildfire atmospheric chemistry: climate and air quality impacts

Ocean Aerobiology.

Ocean aerobiology is defined here as the study of biological particles of marine origin, including living organisms, present in the atmosphere and their role in ecological, biogeochemical, and climate processes. Hundreds of trillions of microorganisms are exchanged between ocean and atmosphere daily. Within a few days, tropospheric transport potentially disperses microorganisms over continents and between oceans. There is a need to better identify and quantify marine aerobiota, characterize the time spans and distances of marine microorganisms’ atmospheric transport, and determine whether microorganisms acclimate to atmospheric conditions and remain viable, or even grow. Exploring the atmosphere as a microbial habitat is fundamental for understanding the consequences of dispersal and will expand our knowledge of biodiversity, biogeography, and ecosystem connectivity across different marine environments. Marine organic matter is chemically transformed in the atmosphere, including remineralization back to CO2. The magnitude of these transformations is insignificant in the context of the annual marine carbon cycle, but may be a significant sink for marine recalcitrant organic matter over long (∼104 years) timescales. In addition, organic matter in sea spray aerosol plays a significant role in the Earth’s radiative budget by scattering solar radiation, and indirectly by affecting cloud properties. Marine organic matter is generally a poor source of cloud condensation nuclei (CCN), but a significant source of ice nucleating particles (INPs), affecting the formation of mixed-phase and ice clouds. This review will show that marine biogenic aerosol plays an impactful, but poorly constrained, role in marine ecosystems, biogeochemical processes, and the Earth’s climate system. Further work is needed to characterize the connectivity and feedbacks between the atmosphere and ocean ecosystems in order to integrate this complexity into Earth System models, facilitating future climate and biogeochemical predictions.