Articles | Volume 7, issue 5
Research article 19 May 2014
Research article | 19 May 2014
An experiment to measure raindrop collection efficiencies: influence of rear capture
A. Quérel et al.
No articles found.
Alexis Dépée, Pascal Lemaitre, Thomas Gelain, Marie Monier, and Andrea Flossmann
Atmos. Chem. Phys., 21, 6945–6962,Short summary
Present article describe a new In-Cloud Aerosol Scavenging Experiment (In-CASE) that has been conceived to measure the collection efficiency of submicron aerosol particles by cloud droplets. The present article focuses on the influence of phoretic effects on the collection efficiency.
Alexis Dépée, Pascal Lemaitre, Thomas Gelain, Marie Monier, and Andrea Flossmann
Atmos. Chem. Phys., 21, 6963–6984,Short summary
The present article describes a new In-Cloud Aerosol Scavenging Experiment (In-CASE) that has been conceived to measure the collection efficiency of submicron aerosol particles by cloud droplets. The present article focuses on the influence of electrostatic effects on the collection efficiency.
Jean-Luc Baray, Laurent Deguillaume, Aurélie Colomb, Karine Sellegri, Evelyn Freney, Clémence Rose, Joël Van Baelen, Jean-Marc Pichon, David Picard, Patrick Fréville, Laëtitia Bouvier, Mickaël Ribeiro, Pierre Amato, Sandra Banson, Angelica Bianco, Agnès Borbon, Lauréline Bourcier, Yannick Bras, Marcello Brigante, Philippe Cacault, Aurélien Chauvigné, Tiffany Charbouillot, Nadine Chaumerliac, Anne-Marie Delort, Marc Delmotte, Régis Dupuy, Antoine Farah, Guy Febvre, Andrea Flossmann, Christophe Gourbeyre, Claude Hervier, Maxime Hervo, Nathalie Huret, Muriel Joly, Victor Kazan, Morgan Lopez, Gilles Mailhot, Angela Marinoni, Olivier Masson, Nadège Montoux, Marius Parazols, Frédéric Peyrin, Yves Pointin, Michel Ramonet, Manon Rocco, Martine Sancelme, Stéphane Sauvage, Martina Schmidt, Emmanuel Tison, Mickaël Vaïtilingom, Paolo Villani, Miao Wang, Camille Yver-Kwok, and Paolo Laj
Atmos. Meas. Tech., 13, 3413–3445,Short summary
CO-PDD (Cézeaux-Aulnat-Opme-puy de Dôme) is a fully instrumented platform for atmospheric research. The four sites located at different altitudes from 330 to 1465 m around Clermont-Ferrand (France) host in situ and remote sensing instruments to measure atmospheric composition, including long-term trends and variability, to study interconnected processes (microphysical, chemical, biological, chemical, and dynamical) and to provide a reference point for climate models.
Christina Kagkara, Wolfram Wobrock, Céline Planche, and Andrea I. Flossmann
Nat. Hazards Earth Syst. Sci., 20, 1469–1483,Short summary
Over the Cévennes–Vivarais region in southern France, 5 h intensive rainfall covering an area of 1000 km2 with more than 50 mm rain accumulation was observed during IOP7a of HyMeX. This study evaluates the performance of a bin-resolved cloud model for simulating this heavy-precipitation event. The simulation results were compared with observations of rain accumulation, radar reflectivity, temporal and spatial evolution of precipitation, 5 min rain rates, and raindrop size distributions.
Pascal Lemaitre, Arnaud Querel, Marie Monier, Thibault Menard, Emmanuel Porcheron, and Andrea I. Flossmann
Atmos. Chem. Phys., 17, 4159–4176,Short summary
We present new measurements of the efficiency with which aerosol particles are collected by raindrops. These measurements provide the link to reconcile the scavenging coefficients obtained from theoretical approaches with those from experimental studies. We provide proof of the rear capture that is a fundamental effect on submicroscopic particles. Finally, we propose an expression to take into account this mechanism to calculate the collection efficiency for drops within the rain size range.
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053,
L. Deguillaume, T. Charbouillot, M. Joly, M. Vaïtilingom, M. Parazols, A. Marinoni, P. Amato, A.-M. Delort, V. Vinatier, A. Flossmann, N. Chaumerliac, J. M. Pichon, S. Houdier, P. Laj, K. Sellegri, A. Colomb, M. Brigante, and G. Mailhot
Atmos. Chem. Phys., 14, 1485–1506,
Related subject area
Subject: Aerosols | Technique: Laboratory Measurement | Topic: Data Processing and Information RetrievalHigh-resolution optical constants of crystalline ammonium nitrate for infrared remote sensing of the Asian Tropopause Aerosol LayerAssessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – A comparative studyAssessing 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 spectrometerQuantitative 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
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.
Dimitrios Bousiotis, Ajit Singh, Molly Haugen, David C. S. Beddows, Sebastián Diez, Pete M. Edwards, Adam Boies, Roy M. Harrison, and Francis D. Pope
Atmos. Meas. Tech. Discuss.,
Preprint under review for AMTShort summary
Measurement and source apportionment of atmospheric pollutants is crucial for the assessment of air quality and the implementation of policies for its 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.
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,
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,
Adrian, R. J.: Multi-point optical measurements of simultaneous vectors in unsteady flow–-a review, Int. J. Heat Fluid Fl., 7, 127–145, 1986.
Baklanov, A. and Sørensen, J. H.: Parameterisation of radionuclide deposition in atmospheric long-range transport modelling, Phys. Chem. Earth B, 26, 787–799, 2001.
Baron, P. A. and Willeke, K.: Aerosol Measurement, Principles, Techniques, and Applicaions (New York/Chichester/Weinheim/Brisbane/Singapore/Toronto), 2001.
Beard, K. V.: Experimental and numerical collision efficiencies for submicron particles scavenged by raindrops, J. Atmos. Sci., 31, 1595–1603, 1974.
Beard, K. V.: Terminal velocity and shape of cloud and precipitation drops aloft, J. Atmos. Sci., 33, 851–864, 1976.
Beard, K. V. and Chuang, C.: A new model for the equilibrium shape of raindrops, J. Atmos. Sci., 44, 1509–1524, 1987.
Bemer, D. and Tierce, P.: Ultrasonic generation of droplets for the production of fluorescein aerosol of mass median aerodynamic diameter between 1 and 10 μm and geometric standard deviation < 1.5, J. Aerosol Sci., 27, 393–394, 1996.
Bringi, V. N., Chandrasekar, V., Hubbert, J., Gorgucci, E., Randeu, W. L., and Schoenhuber, M.: Raindrop size distribution in different climatic regimes from disdrometer and dual-polarized radar analysis, J. Atmos. Sci., 60, 354–365, 2003.
Davenport, H. M. and Peters, L. K.: Field studies of atmospheric particulate concentration changes during precipitation, Atmos. Environ., 12, 997–1008, 1978.
Flossmann, A. I.: A theoretical investigation of the removal of atmospheric trace constituents by means of a dynamic model, PhD thesis, university Johannes Gutenberg, Mainz, 1986.
Flossmann, A. I.: The scavenging of two different types of marine aerosol particles calculated using a two-dimensional detailed cloud model, Tellus B, 43, 301–321, 1991.
Flossmann, A. I.: Interaction of aerosol particles and clouds, J. Atmos. Sci., 55, 879–887, 1998.
Flossmann, A. I. and Wobrock, W.: A review of our understanding of the aerosol–cloud interaction from the perspective of a bin resolved cloud scale modelling, Atmos. Res., 97, 478–497, 2010.
Greenfield, S. M.: Rain scavenging of radioactive particulate matter from the atmosphere, J. Meteorol., 14, 115–125, 1957.
Grover, S. N., Pruppacher, H. R., and Hamielec, A. E.: A numerical determination of the efficiency with which spherical aerosol particles collide with spherical water drops due to inertial impaction and phoretic and electrical forces, J. Atmos. Sci., 34, 1655–1663, 1977.
Hinds, W. C.: Aerosol technology, Wiley-Interscience, New York, 1982.
Hobbs, P. V.: Aerosol-Cloud-Climate Interactions (San Diego/New York/Boston/London/Sydney/Tokyo/Toronto), 1993.
Jaenicke, R.: Aerosol physics and chemistry, in: Landolt-Boernstein: Zahlenwerte und Funktionen aus Naturwissenschaften und Tecknik, edited by: Fischer, G., 4b, 391–457, 1988.
Kerker, M. and Hampl, V.: Scavenging of aerosol particles by a falling water drops and calculation of washout coefficients, J. Atmos. Sci., 31, 1368–1376, 1974.
Laakso, L., Grönholm, T., Rannik, Ü., Kosmale, M., Fiedler, V., Vehkamäki, H., and Kulmala, M.: Ultrafine particle scavenging coefficients calculated from 6 years field measurements, Atmos. Environ., 37, 3605–3613, 2003.
Lai, K.-Y., Dayan, N., and Kerker, M.: Scavenging of aerosol particles by a falling water drop, J. Atmos. Sci., 35, 674–682, 1978.
Marjamaki, M., Keskinen, J., Chen, D. R., and Pui, D. Y. H.: Performance evaluation of the electrical low-pressure impactor (ELPI), J. Aerosol Sci., 31, 249–261, 2000.
Marshall, J. S. and Palmer, W. M.: The distribution of raindrops with size, J. Meteorol., 5, 165–166, 1948.
Mocho, V.: Pollution microbienne, particulaire et gazeuse d'un espace protégé par une ou plusieurs barrières de confinement dynamique, PhD thesis, University of Paris-Val-de-Marne, Paris XII, 1996.
Motzkus, C.: Etude de la mise en suspension de particules lors de l'impact de gouttes, PhD thesis, Paris XII, 2007.
Pranesha, T. S. and Kamra, A. K.: Scavenging of aerosol particles by large water drops 1. Neutral case, J. Geophys. Res., 101, 23373–23380, 1996.
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation (Dordrecht/Boston/London), 1997.
Quérel, A.: Lessivage de l'atmosphère par la pluie?: approche microphysique, PhD thesis, University Blaise Pascal, Clermont-Ferrand, 2012.
Quérel, A., Monier, M., Flossmann, A. I., Lemaitre, P., and Porcheron, E.: The importance of new collection efficiency values including the effect of rear capture for the below-cloud scavenging of aerosol particles, Atmos. Res., 142, 57–66, https://doi.org/10.1016/j.atmosres.2013.06.008, 2014.
Skibin, D., Kaimal, J. C., and Gaynor, J. E.: Could the vertical velocity explain the discrepancy between theory and measurements of air polution?, in: 7th Symp. on Turbulence and Diffusion, (Boston, U.S.A.), 1986.
Slinn, W. G. N.: Some approximations for the wet and dry removal of particles and gases from the atmosphere, Water Air Soil Poll., 7, 513–543, 1977.
Szakáll, M., Diehl, K., Mitra, S. K., and Borrmann, S.: A Wind Tunnel Study on the Shape, Oscillation, and Internal Circulation of Large Raindrops with Sizes between 2.5 and 7.5 mm, J. Atmos. Sci., 66, 755–765, 2009.
Szakáll, M., Mitra, S. K., Diehl, K., and Borrmann, S.: Shapes and oscillations of falling raindrops – A review, Atmos. Res., 97, 416–425, 2010.
Thurai, M., Bringi, V. N., Szakáll, M., Mitra, S. K., Beard, K. V., and Borrmann, S.: Drop Shapes and Axis Ratio Distributions: Comparison between 2D Video Disdrometer and Wind-Tunnel Measurements, J. Atmos. Ocean. Tech., 26, 1427–1432, 2009.
Villani, P., Picard, D., Michaud, V., Laj, P., and Wiedensohler, A.: Design and Validation of a Volatility Hygroscopic Tandem Differential Mobility Analyzer (VH-TDMA) to Characterize the Relationships Between the Thermal and Hygroscopic Properties of Atmospheric Aerosol Particles, Aerosol Sci. Tech., 42, 729–741, 2008.
Vohl, O., Wurzler, S., Diehl, K., Huber, G., Mitra, S. K., and Pruppacher, H. R.: Experimental and theoritical studies of the effects of turbulence on impaction scavenging of aerosols, gas uptake by water drops, and collisional drop growth, J. Aerosol Sci., 30, S575–S576, 1999.
Volken, M. and Schumann, T.: A critical review of below-cloud aerosol scavenging results on Mt Rigi, Water Air Soil Poll., 68, 15–28, 1993.
Wang, P. K. and Pruppacher, H. R.: An experimental determination of the efficiency with which aerosol particles are collected by water drops in subsaturated air, J. Atmos. Sci., 34, 1664–1669, 1977.
Wang, P. K., Grover, S. N., and Pruppacher, H. R.: On the effect of electrical charges on the scavenging of aerosol particles by clouds and small raindrops, J. Atmos. Sci., 35, 1735–1743, 1978.
Whitby, K. T.: On the multimodal nature of atmospheric size distribution, 3rd int. Conf. on Nucleation, Leningrad, USSR, 1973.