Articles | Volume 15, issue 22
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A universally applicable method of calculating confidence bands for ice nucleation spectra derived from droplet freezing experiments
Cosma Rohilla Shalizi
Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Santa Fe Institute, Santa Fe, NM 87501, USA
Ryan Christopher Sullivan
Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA 15213, USA
No articles found.
Zamin A. Kanji, Ryan C. Sullivan, Monika Niemand, Paul J. DeMott, Anthony J. Prenni, Cédric Chou, Harald Saathoff, and Ottmar Möhler
Atmos. Chem. Phys., 19, 5091–5110,Short summary
The ice nucleation ability of two natural desert dusts coated with a proxy of secondary organic aerosol is presented for temperatures and relative humidity conditions relevant for mixed-phase clouds. We find that at the tested conditions, there is no effect on the ice nucleation ability of the particles due to the organic coating. Furthermore, the two dust samples do not show variability within measurement uncertainty. Particle size and surface area may play a role in any difference observed.
Naruki Hiranuma, Kouji Adachi, David M. Bell, Franco Belosi, Hassan Beydoun, Bhaskar Bhaduri, Heinz Bingemer, Carsten Budke, Hans-Christian Clemen, Franz Conen, Kimberly M. Cory, Joachim Curtius, Paul J. DeMott, Oliver Eppers, Sarah Grawe, Susan Hartmann, Nadine Hoffmann, Kristina Höhler, Evelyn Jantsch, Alexei Kiselev, Thomas Koop, Gourihar Kulkarni, Amelie Mayer, Masataka Murakami, Benjamin J. Murray, Alessia Nicosia, Markus D. Petters, Matteo Piazza, Michael Polen, Naama Reicher, Yinon Rudich, Atsushi Saito, Gianni Santachiara, Thea Schiebel, Gregg P. Schill, Johannes Schneider, Lior Segev, Emiliano Stopelli, Ryan C. Sullivan, Kaitlyn Suski, Miklós Szakáll, Takuya Tajiri, Hans Taylor, Yutaka Tobo, Romy Ullrich, Daniel Weber, Heike Wex, Thomas F. Whale, Craig L. Whiteside, Katsuya Yamashita, Alla Zelenyuk, and Ottmar Möhler
Atmos. Chem. Phys., 19, 4823–4849,Short summary
A total of 20 ice nucleation measurement techniques contributed to investigate the immersion freezing behavior of cellulose particles – natural polymers. Our data showed several types of cellulose are able to nucleate ice as efficiently as some mineral dust samples and cellulose has the potential to be an important atmospheric ice-nucleating particle. Continued investigation/collaboration is necessary to obtain further insight into consistency or diversity of ice nucleation measurements.
Paul J. DeMott, Ottmar Möhler, Daniel J. Cziczo, Naruki Hiranuma, Markus D. Petters, Sarah S. Petters, Franco Belosi, Heinz G. Bingemer, Sarah D. Brooks, Carsten Budke, Monika Burkert-Kohn, Kristen N. Collier, Anja Danielczok, Oliver Eppers, Laura Felgitsch, Sarvesh Garimella, Hinrich Grothe, Paul Herenz, Thomas C. J. Hill, Kristina Höhler, Zamin A. Kanji, Alexei Kiselev, Thomas Koop, Thomas B. Kristensen, Konstantin Krüger, Gourihar Kulkarni, Ezra J. T. Levin, Benjamin J. Murray, Alessia Nicosia, Daniel O'Sullivan, Andreas Peckhaus, Michael J. Polen, Hannah C. Price, Naama Reicher, Daniel A. Rothenberg, Yinon Rudich, Gianni Santachiara, Thea Schiebel, Jann Schrod, Teresa M. Seifried, Frank Stratmann, Ryan C. Sullivan, Kaitlyn J. Suski, Miklós Szakáll, Hans P. Taylor, Romy Ullrich, Jesus Vergara-Temprado, Robert Wagner, Thomas F. Whale, Daniel Weber, André Welti, Theodore W. Wilson, Martin J. Wolf, and Jake Zenker
Atmos. Meas. Tech., 11, 6231–6257,Short summary
The ability to measure ice nucleating particles is vital to quantifying their role in affecting clouds and precipitation. Methods for measuring droplet freezing were compared while co-sampling relevant particle types. Measurement correspondence was very good for ice nucleating particles of bacterial and natural soil origin, and somewhat more disparate for those of mineral origin. Results reflect recently improved capabilities and provide direction toward addressing remaining measurement issues.
Michael Polen, Thomas Brubaker, Joshua Somers, and Ryan C. Sullivan
Atmos. Meas. Tech., 11, 5315–5334,Short summary
Ice nucleation commonly studied using droplet freezing measurements suffers from artifacts caused by water impurities or substrate effects. We evaluate a series of substrates and water sources to find methods that reduce the background freezing temperature limit. The best performance was obtained from our new microfluidic device and hydrophobic glass surfaces, using filtered HPLC bottled water. We conclude with recommendations for best practices in droplet freezing experiments and data analysis.
Sara C. Pryor, Ryan C. Sullivan, and Justin T. Schoof
Atmos. Chem. Phys., 17, 14457–14471,Short summary
The air temperature and water vapor content are increasing globally due to the increased concentration of "heat-trapping" (greenhouse) gases. But not all regions are warming at the same rate. This analysis is designed to improve understanding of the causes of recent trends and year-to-year variability in summertime heat indices over the eastern US and to present a new model that can be used to make projections of future events that may cause loss of life and/or decreased human well-being.
Hassan Beydoun, Michael Polen, and Ryan C. Sullivan
Atmos. Chem. Phys., 17, 13545–13557,Short summary
A new multicomponent heterogeneous ice nucleation model is tested using Snomax bacterial particles and a mixture of Snomax and illite. The complex freezing behavior of the particle mixture as concentrations are varied can be predicted using the properties of the pure components. When bacterial particles are present their strong freezing properties determine the freezing temperature of the droplet, completely overwhelming any influence from the weaker mineral dust ice nucleants.
Paola Crippa, Ryan C. Sullivan, Abhinav Thota, and Sara C. Pryor
Atmos. Chem. Phys., 17, 1511–1528,Short summary
Here we quantify WRF-CHEM sensitivity in simulating meteorological, chemical and aerosol properties as a function of spatial resolution. We demonstrate that WRF-Chem at high resolution improves model performance of meteorological and gas-phase parameters and of mean and extreme aerosol properties over North America. A dry bias in specific humidity and precipitation in the coarse simulations is identified as cause of the better performance of the high-resolution simulations.
Adam T. Ahern, Ramachandran Subramanian, Georges Saliba, Eric M. Lipsky, Neil M. Donahue, and Ryan C. Sullivan
Atmos. Meas. Tech., 9, 6117–6137,Short summary
The SP-AMS exhibited a different sensitivity to black carbon vs. potassium as more SOA mass was condensed onto biomass burning particles. The SP-AMS's sensitivity to BC mass did not plateau following successive SOA coatings, despite achieving high OA : BC mass ratios > 9. A laser ablation single-particle mass spectrometer exhibited a positive correlation to the condensed SOA mass on individual soot particles, demonstrating its ability to obtain mass quantitative measurements from complex matrices.
Hassan Beydoun, Michael Polen, and Ryan C. Sullivan
Atmos. Chem. Phys., 16, 13359–13378,Short summary
A particle's surface is treated as a continuum of ice nucleation sites with a Gaussian distribution of freezing ability to predict particle-induced freezing of cloud droplets. This does not require prescribing the size or number of active sites. Analysis of droplet freezing spectra revealed a critical total surface area threshold, above which the variability of active site ability saturates. Below this threshold an apparently higher ice active site density (ns) is retrieved for the same system.
P. Crippa, R. C. Sullivan, A. Thota, and S. C. Pryor
Atmos. Chem. Phys., 16, 397–416,Short summary
We evaluate the performance of high-resolution simulations of the Weather Research and Forecasting model coupled with Chemistry in capturing spatiotemporal variability of aerosol optical properties by comparison with ground- and space- based remote-sensing observations and investigate causes of model biases. This work contributes to assessing the model's ability to describe drivers of aerosol direct radiative forcing in the contemporary climate and to improving confidence in future projections.
P. J. DeMott, A. J. Prenni, G. R. McMeeking, R. C. Sullivan, M. D. Petters, Y. Tobo, M. Niemand, O. Möhler, J. R. Snider, Z. Wang, and S. M. Kreidenweis
Atmos. Chem. Phys., 15, 393–409,Short summary
Laboratory and field data are used together to develop an empirical relation between the concentrations of mineral dust particles at sizes above 0.5 microns, approximated as a single compositional type, and ice nucleating particle concentrations measured versus temperature. This should be useful in global modeling of ice cloud formation. The utility of laboratory data for parameterization development is reinforced, and the need for careful interpretation of ice nucleation data is emphasized.
C. E. Stockwell, R. J. Yokelson, S. M. Kreidenweis, A. L. Robinson, P. J. DeMott, R. C. Sullivan, J. Reardon, K. C. Ryan, D. W. T. Griffith, and L. Stevens
Atmos. Chem. Phys., 14, 9727–9754,
Related subject area
Subject: Aerosols | Technique: Laboratory Measurement | Topic: Data Processing and Information RetrievalEstimation of secondary organic aerosol formation parameters for the volatility basis set combining thermodenuder, isothermal dilution, and yield measurementsAn extraction method for nitrogen isotope measurement of ammonium in low concentrated environmentCharacterization of offline analysis of particulate matter with FIGAERO-CIMSMass spectrometry-based Aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosolThermal–optical analysis of quartz fiber filters loaded with snow samples – determination of iron based on interferences caused by mineral dustModelling ultrafine particle growth in a flow tube reactorSubstantial organic impurities at the surface of synthetic ammonium sulfate particlesContrasting mineral dust abundances from X-ray diffraction and reflectance spectroscopyFragment ion–functional group relationships in organic aerosols using aerosol mass spectrometry and mid-infrared spectroscopyEvolution under dark conditions of particles from old and modern diesel vehicles in a new environmental chamber characterized with fresh exhaust emissionsQuantification of isomer-resolved iodide chemical ionization mass spectrometry sensitivity and uncertainty using a voltage-scanning approachAssessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative studyHigh-resolution optical constants of crystalline ammonium nitrate for infrared remote sensing of the Asian Tropopause Aerosol LayerAssessing the accuracy of low-cost optical particle sensors using a physics-based approachComparison of dimension reduction techniques in the analysis of mass spectrometry dataDevelopment of a new correction algorithm applicable to any filter-based absorption photometerChemical discrimination of the particulate and gas phases of miniCAST exhausts using a two-filter collection methodExternal and internal cloud condensation nuclei (CCN) mixtures: controlled laboratory studies of varying mixing statesClassification of iron oxide aerosols by a single particle soot photometer using supervised machine learningMethod to measure the size-resolved real part of aerosol refractive index using differential mobility analyzer in tandem with single-particle soot photometerQuantitative capabilities of STXM to measure spatially resolved organic volume fractions of mixed organic ∕ inorganic particlesRevisiting the differential freezing nucleus spectra derived from drop-freezing experiments: methods of calculation, applications, and confidence limitsParticle wall-loss correction methods in smog chamber experimentsImproved real-time bio-aerosol classification using artificial neural networksMachine learning for improved data analysis of biological aerosol using the WIBSA machine learning approach to aerosol classification for single-particle mass spectrometryEvaluation of a hierarchical agglomerative clustering method applied to WIBS laboratory data for improved discrimination of biological particles by comparing data preparation techniquesUsing depolarization to quantify ice nucleating particle concentrations: a new methodReal-time analysis of insoluble particles in glacial ice using single-particle mass spectrometryEvaluation of machine learning algorithms for classification of primary biological aerosol using a new UV-LIF spectrometerSize distribution of particle-associated polybrominated diphenyl ethers (PBDEs) and their implications for healthPredicting ambient aerosol thermal–optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sitesElectrodynamic balance measurements of thermodynamic, kinetic, and optical aerosol properties inaccessible to bulk methodsMass-specific optical absorption coefficients and imaginary part of the complex refractive indices of mineral dust components measured by a multi-wavelength photoacoustic spectrometerAn experiment to measure raindrop collection efficiencies: influence of rear captureQuantitative single-particle analysis with the Aerodyne aerosol mass spectrometer: development of a new classification algorithm and its application to field dataA modeling approach to evaluate the uncertainty in estimating the evaporation behaviour and volatility of organic aerosolsA model of aerosol evaporation kinetics in a thermodenuder
Petro Uruci, Dontavious Sippial, Anthoula Drosatou, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 3155–3172,Short summary
In this work we develop an algorithm for the synthesis of the measurements performed in atmospheric simulation chambers regarding the formation of secondary organic aerosol (SOA). Novel features of the algorithm are its ability to use measurements of SOA yields, thermodenuders, and isothermal dilution; its estimation of parameters that can be used directly in atmospheric chemical transport models; and finally its estimates of the uncertainty in SOA formation yields.
Alexis Lamothe, Joel Savarino, Patrick Ginot, Lison Soussaintjean, Elsa Gautier, Pete D. Akers, Nicolas Caillon, and Joseph Erbland
Ammonia is a reactive gas in our atmosphere that is key in air quality issues. Assessing its emissions and how it reacts is a hot topic that can be answered from the past. Stable isotopes (the mass of the molecule) measured in ice cores (glacial archives) can teach us a lot for that. However, the concentrations in ice cores are very small. We propose a protocol to limit the contaminations and apply it to one ice core drilled in the Mont-Blanc describing the opportunities our method brings.
Jing Cai, Kaspar R. Daellenbach, Cheng Wu, Yan Zheng, Feixue Zheng, Wei Du, Sophie L. Haslett, Qi Chen, Markku Kulmala, and Claudia Mohr
Atmos. Meas. Tech., 16, 1147–1165,Short summary
We introduce the offline application of FIGAERO-CIMS by analyzing Teflon and quartz filter samples that were collected at a typical urban site in Beijing with the deposition time varying from 30 min to 24 h. This method provides a feasible, simple, and quantitative way to investigate the molecular composition and volatility of OA compounds by using FIGAERO-CIMS to analyze offline samples.
Markus Thoma, Franziska Bachmeier, Felix Leonard Gottwald, Mario Simon, and Alexander Lucas Vogel
Atmos. Meas. Tech., 15, 7137–7154,Short summary
We introduce the aerosolomics database and apply it to particulate matter samples. Nine VOCs were oxidized under various conditions in an oxidation flow reactor, and the formed SOA was measured using liquid chromatography mass spectrometry. With the database, an unambiguous top-down attribution of atmospheric oxidation products to their parent VOCs is now possible. Combining the database with hierarchical clustering enables a better understanding of sources, formation, and partitioning of SOA.
Daniela Kau, Marion Greilinger, Bernadette Kirchsteiger, Aron Göndör, Christopher Herzig, Andreas Limbeck, Elisabeth Eitenberger, and Anne Kasper-Giebl
Atmos. Meas. Tech., 15, 5207–5217,Short summary
The use of thermal–optical analysis for the determination of elemental carbon (EC) and organic carbon (OC) can be biased by mineral dust (MD). We present a method that utilizes this interference to quantify iron contained in MD in snow samples. Possibilities and limitations of applying this method to particulate matter samples are presented. The influence of light-absorbing iron compounds in MD on the transmittance signal can be used to identify samples experiencing a bias of the OC / EC split.
Michael S. Taylor Jr., Devon N. Higgins, and Murray V. Johnston
Atmos. Meas. Tech., 15, 4663–4674,Short summary
This modelling study investigates the complex growth kinetics of ultrafine particles in a flow tube reactor. When both surface- and volume-limited growth processes occur, the particle diameter growth rate changes as a function of time in the flow tube. We show that this growth can be represented by a parameter (growth factor, GF) which can be obtained experimentally from the outlet-minus-inlet particle diameter change without foreknowledge of the chemical growth processes involved.
Junteng Wu, Nicolas Brun, Juan Miguel González-Sánchez, Badr R'Mili, Brice Temime Roussel, Sylvain Ravier, Jean-Louis Clément, and Anne Monod
Atmos. Meas. Tech., 15, 3859–3874,Short summary
This work quantified and tentatively identified the organic impurities on ammonium sulfate aerosols generated in the laboratory. They are likely low volatile and high mass molecules containing oxygen, nitrogen, and/or sulfur. Our results show that these organic impurities likely originate from the commercial AS crystals. It is recommended to use AS seeds with caution, especially when small particles are used, in terms of AS purity and water purity when aqueous solutions are used for atomization.
Mohammad R. Sadrian, Wendy M. Calvin, and John McCormack
Atmos. Meas. Tech., 15, 3053–3074,Short summary
Mineral dust particles originate from surface soils, primarily in arid regions. They can stay suspended in the atmosphere, impacting Earth's radiation budget. Dust particles will have different perturbation effects depending on their composition. We obtained compositional information on dust collected in an urban setting using two different techniques. We recommended using the combination of measurements to determine the variability in dust mineral abundances.
Amir Yazdani, Nikunj Dudani, Satoshi Takahama, Amelie Bertrand, André S. H. Prévôt, Imad El Haddad, and Ann M. Dillner
Atmos. Meas. Tech., 15, 2857–2874,Short summary
While the aerosol mass spectrometer provides high-time-resolution characterization of the overall extent of oxidation, the extensive fragmentation of molecules and specificity of the technique have posed challenges toward deeper understanding of molecular structures in aerosols. This work demonstrates how functional group information can be extracted from a suite of commonly measured mass fragments using collocated infrared spectroscopy measurements.
Boris Vansevenant, Cédric Louis, Corinne Ferronato, Ludovic Fine, Patrick Tassel, Pascal Perret, Evangelia Kostenidou, Brice Temime-Roussel, Barbara D'Anna, Karine Sartelet, Véronique Cerezo, and Yao Liu
Atmos. Meas. Tech., 14, 7627–7655,Short summary
A new method was developed to correct wall losses of particles on Teflon walls using a new environmental chamber. It was applied to experiments with six diesel vehicles (Euro 3 to 6), tested on a chassis dynamometer. Emissions of particles and precursors were obtained under urban and motorway conditions. The chamber experiments help understand the role of physical processes in diesel particle evolutions in the dark. These results can be applied to situations such as tunnels or winter rush hours.
Chenyang Bi, Jordan E. Krechmer, Graham O. Frazier, Wen Xu, Andrew T. Lambe, Megan S. Claflin, Brian M. Lerner, John T. Jayne, Douglas R. Worsnop, Manjula R. Canagaratna, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 14, 6835–6850,Short summary
Iodide-adduct chemical ionization mass spectrometry (I-CIMS) has been widely used to analyze airborne organics. In this study, I-CIMS sensitivities of isomers within a formula are found to generally vary by 1 and up to 2 orders of magnitude. Comparisons between measured and predicted moles, obtained using a voltage-scanning calibration approach, show that predictions for individual compounds or formulas might carry high uncertainty, yet the summed moles of analytes agree reasonably well.
Dimitrios Bousiotis, Ajit Singh, Molly Haugen, David C. S. Beddows, Sebastián Diez, Killian L. Murphy, Pete M. Edwards, Adam Boies, Roy M. Harrison, and Francis D. Pope
Atmos. Meas. Tech., 14, 4139–4155,Short summary
Measurement and source apportionment of atmospheric pollutants are crucial for the assessment of air quality and the implementation of policies for their improvement. This study highlights the current capability of low-cost sensors in source identification and differentiation using clustering approaches. Future directions towards particulate matter source apportionment using low-cost OPCs are highlighted.
Robert Wagner, Baptiste Testa, Michael Höpfner, Alexei Kiselev, Ottmar Möhler, Harald Saathoff, Jörn Ungermann, and Thomas Leisner
Atmos. Meas. Tech., 14, 1977–1991,Short summary
During the Asian summer monsoon period, air pollutants are transported from layers near the ground to high altitudes of 13 to 18 km in the atmosphere. Infrared measurements have shown that particles composed of solid ammonium nitrate are a major part of these pollutants. To enable the quantitative analysis of the infrared spectra, we have determined for the first time accurate optical constants of ammonium nitrate for the low-temperature conditions of the upper atmosphere.
David H. Hagan and Jesse H. Kroll
Atmos. Meas. Tech., 13, 6343–6355,Short summary
Assessing the error of low-cost particulate matter (PM) sensors has been difficult as each empirical study presents unique limitations. Here, we present a new, open-sourced, physics-based model (opcsim) and use it to understand how the properties of different particle sensors alter their accuracy. We offer a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer recommendations for the choice of optimal calibrant.
Sini Isokääntä, Eetu Kari, Angela Buchholz, Liqing Hao, Siegfried Schobesberger, Annele Virtanen, and Santtu Mikkonen
Atmos. Meas. Tech., 13, 2995–3022,Short summary
Online mass spectrometry produces large amounts of data. These data can be interpreted with statistical methods, enabling scientists to more easily understand the underlying processes. We compared these techniques on car exhaust measurements. We show differences and similarities between the methods and give recommendations on applicability of the methods on certain types of data. We show that applying multiple methods leads to more robust results, thus increasing reliability of the findings.
Hanyang Li, Gavin R. McMeeking, and Andrew A. May
Atmos. Meas. Tech., 13, 2865–2886,Short summary
We present a new correction algorithm that addresses biases in measurements of aerosol light absorption by filter-based photometers, incorporating the transmission of light through the filter and some aerosol optical properties. It was developed using biomass burning aerosols and tested using rural ambient aerosols. This new algorithm is applicable to any filter-based photometer, resulting in good agreement between different colocated instruments in both the laboratory and the field.
Linh Dan Ngo, Dumitru Duca, Yvain Carpentier, Jennifer A. Noble, Raouf Ikhenazene, Marin Vojkovic, Cornelia Irimiea, Ismael K. Ortega, Guillaume Lefevre, Jérôme Yon, Alessandro Faccinetto, Eric Therssen, Michael Ziskind, Bertrand Chazallon, Claire Pirim, and Cristian Focsa
Atmos. Meas. Tech., 13, 951–967,Short summary
The partitioning of noxious chemical compounds between the particulate and gas phases in combustion emissions is key to delineate their exact impacts on atmospheric chemistry and human health. We developed a two-filter sampling system, a multi-technique analytical approach, and advanced statistical methods to fully characterize the composition of both phases in combustion emissions. We could successfully discriminate samples from a standard soot generator by their volatile–non-volatile species.
Diep Vu, Shaokai Gao, Tyler Berte, Mary Kacarab, Qi Yao, Kambiz Vafai, and Akua Asa-Awuku
Atmos. Meas. Tech., 12, 4277–4289,Short summary
Aerosol–cloud interactions contribute the greatest uncertainty to cloud formation. Aerosol composition is complex and can change quickly in the atmosphere. In this work, we recreate a transition in aerosol mixing state in the laboratory, which (to date) has only been observed in the ambient state. We then report the subsequent changes on cloud condensation nuclei (CCN) activation.
Kara D. Lamb
Atmos. Meas. Tech., 12, 3885–3906,Short summary
Recent atmospheric observations have indicated emissions of iron-oxide-containing aerosols from anthropogenic sources could be 8x higher than previous estimates, leading models to underestimate their climate impact. Previous studies have shown the single particle soot photometer (SP2) can quantify the atmospheric abundance of these aerosols. Here, I explore a machine learning approach to improve SP2 detection, significantly reducing misclassifications of other aerosols as iron oxide aerosols.
Gang Zhao, Weilun Zhao, and Chunsheng Zhao
Atmos. Meas. Tech., 12, 3541–3550,Short summary
A new method is proposed to retrieve the size-resolved real part of the refractive index (RRI). The main principle of deriving the RRI is measuring the scattering intensity by a single-particle soot photometer of a size-selected aerosol. This method is validated by a series of calibration experiments using the components of the known RI. The retrieved size-resolved RRI covers a wide range, from 200 nm to 450 nm, with uncertainty of less than 0.02.
Matthew Fraund, Tim Park, Lin Yao, Daniel Bonanno, Don Q. Pham, and Ryan C. Moffet
Atmos. Meas. Tech., 12, 1619–1633,Short summary
Scanning transmission X-ray microscopy (STXM) is a powerful tool which is able to determine the elemental and functional composition of aerosols on a subparticle level. The current work validates the use of STXM for quantitatively calculating the organic volume fraction of individual aerosols by applying the calculation to lab-prepared samples. The caveats and limitations for this calculation are shown as well.
Atmos. Meas. Tech., 12, 1219–1231,Short summary
The abundance of freezing nuclei in water samples is routinely determined by experiments involving the cooling of sample drops and observing the temperatures at which the drops freeze. This is used for characterizing the nucleating abilities of materials in laboratory preparations or to determine the numbers of nucleating particles in rain, snow, river water or other natural waters. The evaluation of drop-freezing experiments in terms of differential nucleus spectra is advocated in the paper.
Ningxin Wang, Spiro D. Jorga, Jeffery R. Pierce, Neil M. Donahue, and Spyros N. Pandis
Atmos. Meas. Tech., 11, 6577–6588,Short summary
The interaction of particles with the chamber walls has been a significant source of uncertainty when analyzing results of secondary organic aerosol formation experiments performed in Teflon chambers. We evaluated the performance of several particle wall-loss correction methods for aging experiments of α-pinene ozonolysis products. Experimental procedures are proposed for the characterization of particle losses during different stages of these experiments.
Maciej Leśkiewicz, Miron Kaliszewski, Maksymilian Włodarski, Jarosław Młyńczak, Zygmunt Mierczyk, and Krzysztof Kopczyński
Atmos. Meas. Tech., 11, 6259–6270,Short summary
In this study we demonstrate the application of artificial neural networks to the real-time analysis of single-particle fluorescence fingerprints acquired using BARDet (a BioAeRosol Detector). 48 different aerosols including pollens, bacteria, fungi, spores and nonbiological substances were characterized. An entirely new approach to data analysis using a decision tree comprising 22 independent neural networks was discussed. A very high accuracy of aerosol classification in real time resulted.
Simon Ruske, David O. Topping, Virginia E. Foot, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 11, 6203–6230,Short summary
Pollen, bacteria and fungal spores are common in the environment, can have very important implications for public health and may influence the weather. Biological sensors potentially could be used to monitor quantities of these types of particles. However, it is important to transform the measurements from these instruments into counts of these biological particles. The paper tests a variety of approaches for achieving this aim on data collected in a laboratory.
Costa D. Christopoulos, Sarvesh Garimella, Maria A. Zawadowicz, Ottmar Möhler, and Daniel J. Cziczo
Atmos. Meas. Tech., 11, 5687–5699,Short summary
Compositional analysis of atmospheric and laboratory aerosols is often conducted with mass spectrometry. In this study, machine learning is used to automatically differentiate particles on the basis of chemistry and size. The ability of the machine learning algorithm was then tested on a data set for which the particles were not initially known to judge its ability.
Nicole J. Savage and J. Alex Huffman
Atmos. Meas. Tech., 11, 4929–4942,Short summary
We show the systematic application of hierarchical agglomerative clustering (HAC) to comprehensive bioaerosol and non-bioaerosol laboratory data collected with the wideband integrated bioaerosol sensor (WIBS-4A). This study investigated various input conditions and used individual matchups and computational mixtures of particles; it will help improve clustering results applied to data from the ultraviolet laser and light-induced fluorescence instruments commonly used for bioaerosol research.
Jake Zenker, Kristen N. Collier, Guanglang Xu, Ping Yang, Ezra J. T. Levin, Kaitlyn J. Suski, Paul J. DeMott, and Sarah D. Brooks
Atmos. Meas. Tech., 10, 4639–4657,Short summary
We have developed a new method which employs single particle depolarization to determine ice nucleating particle (INP) concentrations and to differentiate between ice crystals, water droplets, and aerosols. The method is used to interpret measurements collected using the Texas A&M Continuous Flow Diffusion Chamber (TAMU CFDC) coupled to a Cloud and Aerosol Spectrometer with Polarization (CASPOL). This new method extends the range of operating conditions for the CFDC to higher supersaturations.
Matthew Osman, Maria A. Zawadowicz, Sarah B. Das, and Daniel J. Cziczo
Atmos. Meas. Tech., 10, 4459–4477,Short summary
This study presents the first-time attempt at using time-of-flight single particle mass spectrometry (SPMS) as an emerging online technique for measuring insoluble particles in glacial snow and ice. Using samples from two Greenlandic ice cores, we show that SPMS can constrain the aerodynamic size, composition, and relative abundance of most particulate types on a per-particle basis, reducing the preparation time and resources required of conventional, filter-based particle retrieval methods.
Simon Ruske, David O. Topping, Virginia E. Foot, Paul H. Kaye, Warren R. Stanley, Ian Crawford, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 10, 695–708,Short summary
Particles such as bacteria, pollen and fungal spores have important implications within the environment and public health sectors. Here we evaluate the performance of various different methods for distinguishing between these different types of particles using a new instrument. We demonstrate that there may be better alternatives to the currently used methods which can be further investigated in future research.
Yan Lyu, Tingting Xu, Xiang Li, Tiantao Cheng, Xin Yang, Xiaomin Sun, and Jianmin Chen
Atmos. Meas. Tech., 9, 1025–1037,Short summary
This study presents the particle size distribution of PBDEs in the atmosphere of a megacity and evaluates the contribution of size-fractionated PBDEs' deposition in the human respiratory tract.
Matteo Reggente, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 9, 441–454,Short summary
Organic carbon and elemental carbon are major components of atmospheric PM. Typically they are measured using destructive and relatively expensive methods (e.g., TOR). We aim to reduce the operating costs of large air quality monitoring networks using FT-IR spectra of ambient PTFE filters and PLS regression. We achieve accurate predictions for models (calibrated in 2011) that use samples collected at the same or different sites of the calibration data set and in a different year (2013).
S. S. Steimer, U. K. Krieger, Y.-F. Te, D. M. Lienhard, A. J. Huisman, B. P. Luo, M. Ammann, and T. Peter
Atmos. Meas. Tech., 8, 2397–2408,Short summary
Atmospheric aerosol is often subject to supersaturated or supercooled conditions where bulk measurements are not possible. Here we demonstrate how measurements using single particle electrodynamic levitation combined with light scattering spectroscopy allow the retrieval of thermodynamic data, optical properties and water diffusivity of such metastable particles even when auxiliary bulk data are not available due to lack of sufficient amounts of sample.
N. Utry, T. Ajtai, M. Pintér, E. Tombácz, E. Illés, Z. Bozóki, and G. Szabó
Atmos. Meas. Tech., 8, 401–410,
A. Quérel, P. Lemaitre, M. Monier, E. Porcheron, A. I. Flossmann, and M. Hervo
Atmos. Meas. Tech., 7, 1321–1330,
F. Freutel, F. Drewnick, J. Schneider, T. Klimach, and S. Borrmann
Atmos. Meas. Tech., 6, 3131–3145,
E. Fuentes and G. McFiggans
Atmos. Meas. Tech., 5, 735–757,
C. D. Cappa
Atmos. Meas. Tech., 3, 579–592,
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Heterogeneous ice nucleation (IN) alters cloud microphysics and climate, and droplet freezing assays are widely used to determine a material's IN ability. Existing statistical procedures require restrictive assumptions that may bias reported results, and there is no rigorous way to compare IN spectra. To improve the accuracy of reported IN data, we present a method for calculating statistics and confidence bands and testing statistical differences between IN activities in different materials.
Heterogeneous ice nucleation (IN) alters cloud microphysics and climate, and droplet freezing...