Articles | Volume 14, issue 12
https://doi.org/10.5194/amt-14-7909-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7909-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Dec 2021
Research article |
| 21 Dec 2021
Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data
Department of Marine, Earth, and Atmospheric Sciences, NC State University, Raleigh, NC 27695-8208, USA
Related authors
Sabin Kasparoglu, Mohammad Maksimul Islam, Nicholas Meskhidze, and Markus D. Petters
Atmos. Meas. Tech., 15, 5007–5018, https://doi.org/10.5194/amt-15-5007-2022, https://doi.org/10.5194/amt-15-5007-2022, 2022
Short summary
Short summary
A modified version of a Handix Scientific printed optical particle spectrometer is introduced. The paper presents characterization experiments, including concentration, size, and time responses. Integration of an external multichannel analyzer card removes counting limitations of the original instrument. It is shown that the high-resolution light-scattering amplitude data can be used to sense particle-phase transitions.
Sabin Kasparoglu, Ying Li, Manabu Shiraiwa, and Markus D. Petters
Atmos. Chem. Phys., 21, 1127–1141, https://doi.org/10.5194/acp-21-1127-2021, https://doi.org/10.5194/acp-21-1127-2021, 2021
Short summary
Short summary
Viscosity is important because it determines the lifetime, impact, and fate of particulate matter. We collected new data to rigorously test a framework that is used to constrain the phase state in global simulations. We find that the framework is accurate as long as appropriate compound specific inputs are available.
Samuel A. Atwood, Sonia M. Kreidenweis, Paul J. DeMott, Markus D. Petters, Gavin C. Cornwell, Andrew C. Martin, and Kathryn A. Moore
Atmos. Chem. Phys., 19, 6931–6947, https://doi.org/10.5194/acp-19-6931-2019, https://doi.org/10.5194/acp-19-6931-2019, 2019
Short summary
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This paper presents measurements of aerosol particles at a coastal location. The particles were classified into distinct aerosol types using both microphysical measurements and meteorological information, allowing rapid changes between the aerosol types to be reliably identified. These particles can alter cloud and precipitation processes, and inclusion of the differences between types can improve atmospheric models and remote sensing retrievals in littoral zones.
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, https://doi.org/10.5194/acp-19-4823-2019, https://doi.org/10.5194/acp-19-4823-2019, 2019
Short summary
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.
Ankit Tandon, Nicholas E. Rothfuss, and Markus D. Petters
Atmos. Chem. Phys., 19, 3325–3339, https://doi.org/10.5194/acp-19-3325-2019, https://doi.org/10.5194/acp-19-3325-2019, 2019
Short summary
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Organic compounds may form a barrier to condensation. Such barriers have been hypothesized to prevent water and other substances from mixing with salt cores. This will hinder the particles' ability to aid cloud formation of < 100 nm particles. Here we perform experiments encasing particles in plastic shells akin to water bottles. Against expectations, the plastic shell did not alter the droplet activation behavior of the encased particles. Water appears to readily permeate the plastic shell.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys., 19, 1413–1437, https://doi.org/10.5194/acp-19-1413-2019, https://doi.org/10.5194/acp-19-1413-2019, 2019
Short summary
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A new cloud parcel model that simulates entrainment, condensational growth, and collision–coalescence processes is presented and evaluated against airborne observations in complex terrain during IPHEx. Analysis of model simulations reveals that nonlinear interactions among turbulent dispersion, activation, and droplet growth processes modulate spectral width and explain the emergence of bimodal cloud drop spectra in aircraft measurements from different cloud regions and at different heights.
Jian Wang, John E. Shilling, Jiumeng Liu, Alla Zelenyuk, David M. Bell, Markus D. Petters, Ryan Thalman, Fan Mei, Rahul A. Zaveri, and Guangjie Zheng
Atmos. Chem. Phys., 19, 941–954, https://doi.org/10.5194/acp-19-941-2019, https://doi.org/10.5194/acp-19-941-2019, 2019
Short summary
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Earlier studies showed organic hygroscopicity increases with oxidation level. Such increases have been attributed to higher water solubility for more oxidized organics. By systematically varying the water content of activating droplets, we show that for secondary organic aerosols, essentially all organics are dissolved at the point of droplet activation. Therefore, the organic hygroscopicity is not limited by solubility but is dictated mainly by the molecular weight of organic species.
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, https://doi.org/10.5194/amt-11-6231-2018, https://doi.org/10.5194/amt-11-6231-2018, 2018
Short summary
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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.
Paul J. DeMott, Thomas C. J. Hill, Markus D. Petters, Allan K. Bertram, Yutaka Tobo, Ryan H. Mason, Kaitlyn J. Suski, Christina S. McCluskey, Ezra J. T. Levin, Gregory P. Schill, Yvonne Boose, Anne Marie Rauker, Anna J. Miller, Jake Zaragoza, Katherine Rocci, Nicholas E. Rothfuss, Hans P. Taylor, John D. Hader, Cedric Chou, J. Alex Huffman, Ulrich Pöschl, Anthony J. Prenni, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 17, 11227–11245, https://doi.org/10.5194/acp-17-11227-2017, https://doi.org/10.5194/acp-17-11227-2017, 2017
Short summary
Short summary
The consistency and complementarity of different methods for measuring the numbers of particles capable of forming ice in clouds are examined in the atmosphere. Four methods for collecting particles for later (offline) freezing studies are compared to a common instantaneous method. Results support very good agreement in many cases but also biases that require further research. Present capabilities and uncertainties for obtaining global data on these climate-relevant aerosols are thus defined.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-396, https://doi.org/10.5194/acp-2017-396, 2017
Revised manuscript not accepted
Short summary
Short summary
To investigate aerosol-cloud interactions in cumulus development, a new cloud parcel model is developed to predict the vertical structure of cloud formation at early stages and evaluated against airborne observations during the Integrated Precipitation and Hydrology Experiment over the Southern Appalachian Mountains. The findings provide new insights into determinant factors of mid-day cumulus congestus formation that can explain a large fraction of warm season rainfall in mountainous regions.
Andrew C. Martin, Gavin C. Cornwell, Samuel A. Atwood, Kathryn A. Moore, Nicholas E. Rothfuss, Hans Taylor, Paul J. DeMott, Sonia M. Kreidenweis, Markus D. Petters, and Kimberly A. Prather
Atmos. Chem. Phys., 17, 1491–1509, https://doi.org/10.5194/acp-17-1491-2017, https://doi.org/10.5194/acp-17-1491-2017, 2017
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Anthropogenic influence on air quality, aerosol properties, and cloud activity was observed at Bodega Bay, CA, during periods when air from California's interior was transported to the coast. The sudden change in aerosol properties can impact atmospheric radiative balance and cloud formation in ways that must be accounted for in regional climate simulations.
M. D. Petters, S. M. Kreidenweis, and P. J. Ziemann
Geosci. Model Dev., 9, 111–124, https://doi.org/10.5194/gmd-9-111-2016, https://doi.org/10.5194/gmd-9-111-2016, 2016
Short summary
Short summary
Organic particles suspended in air serve as nucleation seeds for droplets in atmospheric clouds. Over time their chemical composition changes towards more functionalized compounds. This work presents a model that can predict an organic compounds' ability promote the nucleation of cloud drops from its functional group composition. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote droplet nucleation. Methylene and nitrate moieties inhibit droplet nucleation.
N. Hiranuma, S. Augustin-Bauditz, H. Bingemer, C. Budke, J. Curtius, A. Danielczok, K. Diehl, K. Dreischmeier, M. Ebert, F. Frank, N. Hoffmann, K. Kandler, A. Kiselev, T. Koop, T. Leisner, O. Möhler, B. Nillius, A. Peckhaus, D. Rose, S. Weinbruch, H. Wex, Y. Boose, P. J. DeMott, J. D. Hader, T. C. J. Hill, Z. A. Kanji, G. Kulkarni, E. J. T. Levin, C. S. McCluskey, M. Murakami, B. J. Murray, D. Niedermeier, M. D. Petters, D. O'Sullivan, A. Saito, G. P. Schill, T. Tajiri, M. A. Tolbert, A. Welti, T. F. Whale, T. P. Wright, and K. Yamashita
Atmos. Chem. Phys., 15, 2489–2518, https://doi.org/10.5194/acp-15-2489-2015, https://doi.org/10.5194/acp-15-2489-2015, 2015
Short summary
Short summary
Seventeen ice nucleation measurement techniques contributed to investigate the immersion freezing behavior of illite NX. All data showed a similar temperature trend, but the measured ice nucleation activity was on average smaller for the wet suspended samples and higher for the dry-dispersed aerosol samples at high temperatures. A continued investigation and collaboration is necessary to obtain further insights into consistency or diversity of ice nucleation measurements.
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, https://doi.org/10.5194/acp-15-393-2015, https://doi.org/10.5194/acp-15-393-2015, 2015
Short summary
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.
T. K. V. Nguyen, M. D. Petters, S. R. Suda, H. Guo, R. J. Weber, and A. G. Carlton
Atmos. Chem. Phys., 14, 10911–10930, https://doi.org/10.5194/acp-14-10911-2014, https://doi.org/10.5194/acp-14-10911-2014, 2014
S. Nakao, S. R. Suda, M. Camp, M. D. Petters, and S. M. Kreidenweis
Atmos. Meas. Tech., 7, 2227–2241, https://doi.org/10.5194/amt-7-2227-2014, https://doi.org/10.5194/amt-7-2227-2014, 2014
J. D. Hader, T. P. Wright, and M. D. Petters
Atmos. Chem. Phys., 14, 5433–5449, https://doi.org/10.5194/acp-14-5433-2014, https://doi.org/10.5194/acp-14-5433-2014, 2014
M. D. Petters and S. M. Kreidenweis
Atmos. Chem. Phys., 13, 1081–1091, https://doi.org/10.5194/acp-13-1081-2013, https://doi.org/10.5194/acp-13-1081-2013, 2013
Sabin Kasparoglu, Mohammad Maksimul Islam, Nicholas Meskhidze, and Markus D. Petters
Atmos. Meas. Tech., 15, 5007–5018, https://doi.org/10.5194/amt-15-5007-2022, https://doi.org/10.5194/amt-15-5007-2022, 2022
Short summary
Short summary
A modified version of a Handix Scientific printed optical particle spectrometer is introduced. The paper presents characterization experiments, including concentration, size, and time responses. Integration of an external multichannel analyzer card removes counting limitations of the original instrument. It is shown that the high-resolution light-scattering amplitude data can be used to sense particle-phase transitions.
Sabin Kasparoglu, Ying Li, Manabu Shiraiwa, and Markus D. Petters
Atmos. Chem. Phys., 21, 1127–1141, https://doi.org/10.5194/acp-21-1127-2021, https://doi.org/10.5194/acp-21-1127-2021, 2021
Short summary
Short summary
Viscosity is important because it determines the lifetime, impact, and fate of particulate matter. We collected new data to rigorously test a framework that is used to constrain the phase state in global simulations. We find that the framework is accurate as long as appropriate compound specific inputs are available.
Samuel A. Atwood, Sonia M. Kreidenweis, Paul J. DeMott, Markus D. Petters, Gavin C. Cornwell, Andrew C. Martin, and Kathryn A. Moore
Atmos. Chem. Phys., 19, 6931–6947, https://doi.org/10.5194/acp-19-6931-2019, https://doi.org/10.5194/acp-19-6931-2019, 2019
Short summary
Short summary
This paper presents measurements of aerosol particles at a coastal location. The particles were classified into distinct aerosol types using both microphysical measurements and meteorological information, allowing rapid changes between the aerosol types to be reliably identified. These particles can alter cloud and precipitation processes, and inclusion of the differences between types can improve atmospheric models and remote sensing retrievals in littoral zones.
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, https://doi.org/10.5194/acp-19-4823-2019, https://doi.org/10.5194/acp-19-4823-2019, 2019
Short summary
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.
Ankit Tandon, Nicholas E. Rothfuss, and Markus D. Petters
Atmos. Chem. Phys., 19, 3325–3339, https://doi.org/10.5194/acp-19-3325-2019, https://doi.org/10.5194/acp-19-3325-2019, 2019
Short summary
Short summary
Organic compounds may form a barrier to condensation. Such barriers have been hypothesized to prevent water and other substances from mixing with salt cores. This will hinder the particles' ability to aid cloud formation of < 100 nm particles. Here we perform experiments encasing particles in plastic shells akin to water bottles. Against expectations, the plastic shell did not alter the droplet activation behavior of the encased particles. Water appears to readily permeate the plastic shell.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys., 19, 1413–1437, https://doi.org/10.5194/acp-19-1413-2019, https://doi.org/10.5194/acp-19-1413-2019, 2019
Short summary
Short summary
A new cloud parcel model that simulates entrainment, condensational growth, and collision–coalescence processes is presented and evaluated against airborne observations in complex terrain during IPHEx. Analysis of model simulations reveals that nonlinear interactions among turbulent dispersion, activation, and droplet growth processes modulate spectral width and explain the emergence of bimodal cloud drop spectra in aircraft measurements from different cloud regions and at different heights.
Jian Wang, John E. Shilling, Jiumeng Liu, Alla Zelenyuk, David M. Bell, Markus D. Petters, Ryan Thalman, Fan Mei, Rahul A. Zaveri, and Guangjie Zheng
Atmos. Chem. Phys., 19, 941–954, https://doi.org/10.5194/acp-19-941-2019, https://doi.org/10.5194/acp-19-941-2019, 2019
Short summary
Short summary
Earlier studies showed organic hygroscopicity increases with oxidation level. Such increases have been attributed to higher water solubility for more oxidized organics. By systematically varying the water content of activating droplets, we show that for secondary organic aerosols, essentially all organics are dissolved at the point of droplet activation. Therefore, the organic hygroscopicity is not limited by solubility but is dictated mainly by the molecular weight of organic species.
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, https://doi.org/10.5194/amt-11-6231-2018, https://doi.org/10.5194/amt-11-6231-2018, 2018
Short summary
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.
Paul J. DeMott, Thomas C. J. Hill, Markus D. Petters, Allan K. Bertram, Yutaka Tobo, Ryan H. Mason, Kaitlyn J. Suski, Christina S. McCluskey, Ezra J. T. Levin, Gregory P. Schill, Yvonne Boose, Anne Marie Rauker, Anna J. Miller, Jake Zaragoza, Katherine Rocci, Nicholas E. Rothfuss, Hans P. Taylor, John D. Hader, Cedric Chou, J. Alex Huffman, Ulrich Pöschl, Anthony J. Prenni, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 17, 11227–11245, https://doi.org/10.5194/acp-17-11227-2017, https://doi.org/10.5194/acp-17-11227-2017, 2017
Short summary
Short summary
The consistency and complementarity of different methods for measuring the numbers of particles capable of forming ice in clouds are examined in the atmosphere. Four methods for collecting particles for later (offline) freezing studies are compared to a common instantaneous method. Results support very good agreement in many cases but also biases that require further research. Present capabilities and uncertainties for obtaining global data on these climate-relevant aerosols are thus defined.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-396, https://doi.org/10.5194/acp-2017-396, 2017
Revised manuscript not accepted
Short summary
Short summary
To investigate aerosol-cloud interactions in cumulus development, a new cloud parcel model is developed to predict the vertical structure of cloud formation at early stages and evaluated against airborne observations during the Integrated Precipitation and Hydrology Experiment over the Southern Appalachian Mountains. The findings provide new insights into determinant factors of mid-day cumulus congestus formation that can explain a large fraction of warm season rainfall in mountainous regions.
Andrew C. Martin, Gavin C. Cornwell, Samuel A. Atwood, Kathryn A. Moore, Nicholas E. Rothfuss, Hans Taylor, Paul J. DeMott, Sonia M. Kreidenweis, Markus D. Petters, and Kimberly A. Prather
Atmos. Chem. Phys., 17, 1491–1509, https://doi.org/10.5194/acp-17-1491-2017, https://doi.org/10.5194/acp-17-1491-2017, 2017
Short summary
Short summary
Anthropogenic influence on air quality, aerosol properties, and cloud activity was observed at Bodega Bay, CA, during periods when air from California's interior was transported to the coast. The sudden change in aerosol properties can impact atmospheric radiative balance and cloud formation in ways that must be accounted for in regional climate simulations.
M. D. Petters, S. M. Kreidenweis, and P. J. Ziemann
Geosci. Model Dev., 9, 111–124, https://doi.org/10.5194/gmd-9-111-2016, https://doi.org/10.5194/gmd-9-111-2016, 2016
Short summary
Short summary
Organic particles suspended in air serve as nucleation seeds for droplets in atmospheric clouds. Over time their chemical composition changes towards more functionalized compounds. This work presents a model that can predict an organic compounds' ability promote the nucleation of cloud drops from its functional group composition. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote droplet nucleation. Methylene and nitrate moieties inhibit droplet nucleation.
N. Hiranuma, S. Augustin-Bauditz, H. Bingemer, C. Budke, J. Curtius, A. Danielczok, K. Diehl, K. Dreischmeier, M. Ebert, F. Frank, N. Hoffmann, K. Kandler, A. Kiselev, T. Koop, T. Leisner, O. Möhler, B. Nillius, A. Peckhaus, D. Rose, S. Weinbruch, H. Wex, Y. Boose, P. J. DeMott, J. D. Hader, T. C. J. Hill, Z. A. Kanji, G. Kulkarni, E. J. T. Levin, C. S. McCluskey, M. Murakami, B. J. Murray, D. Niedermeier, M. D. Petters, D. O'Sullivan, A. Saito, G. P. Schill, T. Tajiri, M. A. Tolbert, A. Welti, T. F. Whale, T. P. Wright, and K. Yamashita
Atmos. Chem. Phys., 15, 2489–2518, https://doi.org/10.5194/acp-15-2489-2015, https://doi.org/10.5194/acp-15-2489-2015, 2015
Short summary
Short summary
Seventeen ice nucleation measurement techniques contributed to investigate the immersion freezing behavior of illite NX. All data showed a similar temperature trend, but the measured ice nucleation activity was on average smaller for the wet suspended samples and higher for the dry-dispersed aerosol samples at high temperatures. A continued investigation and collaboration is necessary to obtain further insights into consistency or diversity of ice nucleation measurements.
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, https://doi.org/10.5194/acp-15-393-2015, https://doi.org/10.5194/acp-15-393-2015, 2015
Short summary
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.
T. K. V. Nguyen, M. D. Petters, S. R. Suda, H. Guo, R. J. Weber, and A. G. Carlton
Atmos. Chem. Phys., 14, 10911–10930, https://doi.org/10.5194/acp-14-10911-2014, https://doi.org/10.5194/acp-14-10911-2014, 2014
S. Nakao, S. R. Suda, M. Camp, M. D. Petters, and S. M. Kreidenweis
Atmos. Meas. Tech., 7, 2227–2241, https://doi.org/10.5194/amt-7-2227-2014, https://doi.org/10.5194/amt-7-2227-2014, 2014
J. D. Hader, T. P. Wright, and M. D. Petters
Atmos. Chem. Phys., 14, 5433–5449, https://doi.org/10.5194/acp-14-5433-2014, https://doi.org/10.5194/acp-14-5433-2014, 2014
M. D. Petters and S. M. Kreidenweis
Atmos. Chem. Phys., 13, 1081–1091, https://doi.org/10.5194/acp-13-1081-2013, https://doi.org/10.5194/acp-13-1081-2013, 2013
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
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Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Comprehensive detection of analytes in large chromatographic datasets by coupling factor analysis with a decision tree
Combined organic and inorganic source apportionment on yearlong ToF-ACSM dataset at a suburban station in Athens
Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC
Automated identification of local contamination in remote atmospheric composition time series
A multiple charging correction algorithm for broad supersaturation scanning cloud condensation nuclei (BS2-CCN) system
Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques
SMEARcore – Modular data infrastructure for atmospheric measurement stations
Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements
A systematic re-evaluation of methods for quantification of bulk particle-phase organic nitrates using real-time aerosol mass spectrometry
Data imputation in in situ-measured particle size distributions by means of neural networks
Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg
New correction method for the scattering coefficient measurements of a three-wavelength nephelometer
Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network
Modeled source apportionment of black carbon particles coated with a light-scattering shell
Estimation of particulate organic nitrates from thermodenuder–aerosol mass spectrometer measurements in the North China Plain
Aerosol pH indicator and organosulfate detectability from aerosol mass spectrometry measurements
Determination of equivalent black carbon mass concentration from aerosol light absorption using variable mass absorption cross section
Effects of multi-charge on aerosol hygroscopicity measurement by a HTDMA
A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data
Estimation of pollen counts from light scattering intensity when sampling multiple pollen taxa – establishment of an automated multi-taxa pollen counting estimation system (AME system)
A novel lidar gradient cluster analysis method of nocturnal boundary layer detection during air pollution episodes
Assessment of particle size magnifier inversion methods to obtain the particle size distribution from atmospheric measurements
A global analysis of climate-relevant aerosol properties retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories
Development of an automatic linear calibration method for high-resolution single-particle mass spectrometry: improved chemical species identification for atmospheric aerosols
A hybrid method for reconstructing the historical evolution of aerosol optical depth from sunshine duration measurements
The influence of the baseline drift on the resulting extinction values of a cavity attenuated phase shift-based extinction monitor (CAPS PMex)
Evaluation of equivalent black carbon source apportionment using observations from Switzerland between 2008 and 2018
Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
Filling the gaps of in situ hourly PM2.5 concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles
Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi
Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes
Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps
An open platform for Aerosol InfraRed Spectroscopy analysis – AIRSpec
Understanding atmospheric aerosol particles with improved particle identification and quantification by single-particle mass spectrometry
Multi-scale measurements of mesospheric aerosols and electrons during the MAXIDUSTY campaign
A new method of inferring the size, number density, and charge of mesospheric dust from its in situ collection by the DUSTY probe
Atmospheric particulate matter characterization by Fourier transform infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks
Data inversion methods to determine sub-3 nm aerosol size distributions using the particle size magnifier
A novel method for calculating ambient aerosol liquid water content based on measurements of a humidified nephelometer system
Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting
Daniel A. Jaffe, Colleen Miller, Katie Thompson, Brandon Finley, Manna Nelson, James Ouimette, and Elisabeth Andrews
Atmos. Meas. Tech., 16, 1311–1322, https://doi.org/10.5194/amt-16-1311-2023, https://doi.org/10.5194/amt-16-1311-2023, 2023
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PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations. However, the raw PAS data have significant biases, so the sensors must be corrected. We analyzed data from numerous sites and found that the standard correction to the PAS Purple Air data is accurate in urban pollution events and smoke events but leads to a 6-fold underestimate in the PM2.5 concentrations in dust events. We propose a new correction algorithm to address this problem.
Yilin Chen, Yuanjian Yang, and Meng Gao
Atmos. Meas. Tech., 16, 1279–1294, https://doi.org/10.5194/amt-16-1279-2023, https://doi.org/10.5194/amt-16-1279-2023, 2023
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The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events related to typhoons. The present study leverages machine learning to predict typhoon-associated air quality over the area. The model evaluation shows that the model performs excellently. Moreover, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
Yandong Tong, Lu Qi, Giulia Stefenelli, Dongyu Simon Wang, Francesco Canonaco, Urs Baltensperger, André Stephan Henry Prévôt, and Jay Gates Slowik
Atmos. Meas. Tech., 15, 7265–7291, https://doi.org/10.5194/amt-15-7265-2022, https://doi.org/10.5194/amt-15-7265-2022, 2022
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We present a method for positive matrix factorisation (PMF) analysis on a single dataset that includes measurements from both EESI-TOF and AMS in Zurich, Switzerland. For the first time, we resolved and quantified secondary organic aerosol (SOA) sources. Meanwhile, we also determined the retrieved EESI-TOF factor-dependent sensitivities. This method provides a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.
Zefeng Zhang, Hengnan Guo, Hanqing Kang, Jing Wang, Junlin An, Xingna Yu, Jingjing Lv, and Bin Zhu
Atmos. Meas. Tech., 15, 7259–7264, https://doi.org/10.5194/amt-15-7259-2022, https://doi.org/10.5194/amt-15-7259-2022, 2022
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In this study, we first analyze the relationship between the visibility, the extinction coefficient, and atmospheric compositions. Then we propose to use the harmonic average of visibility data as the average visibility, which can better reflect changes in atmospheric extinction coefficients and aerosol concentrations. It is recommended to use the harmonic average visibility in the studies of climate change, atmospheric radiation, air pollution, environmental health, etc.
Hyungwon John Park, Jeffrey S. Reid, Livia S. Freire, Christopher Jackson, and David H. Richter
Atmos. Meas. Tech., 15, 7171–7194, https://doi.org/10.5194/amt-15-7171-2022, https://doi.org/10.5194/amt-15-7171-2022, 2022
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We use numerical models to study field measurements of sea spray aerosol particles and conclude that both the atmospheric state and the methods of instrument sampling are causes for the variation in the production rate of aerosol particles: a critical metric to learn the aerosol's effect on processes like cloud physics and radiation. This work helps field observers improve their experimental design and interpretation of measurements because of turbulence in the atmosphere.
Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 15, 6419–6431, https://doi.org/10.5194/amt-15-6419-2022, https://doi.org/10.5194/amt-15-6419-2022, 2022
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Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.
Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney
Atmos. Meas. Tech., 15, 6309–6328, https://doi.org/10.5194/amt-15-6309-2022, https://doi.org/10.5194/amt-15-6309-2022, 2022
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How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, https://doi.org/10.5194/amt-15-6051-2022, 2022
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We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer
Atmos. Meas. Tech., 15, 5619–5642, https://doi.org/10.5194/amt-15-5619-2022, https://doi.org/10.5194/amt-15-5619-2022, 2022
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Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.
Marta Via, Gang Chen, Francesco Canonaco, Kaspar R. Daellenbach, Benjamin Chazeau, Hasna Chebaicheb, Jianhui Jiang, Hannes Keernik, Chunshui Lin, Nicolas Marchand, Cristina Marin, Colin O'Dowd, Jurgita Ovadnevaite, Jean-Eudes Petit, Michael Pikridas, Véronique Riffault, Jean Sciare, Jay G. Slowik, Leïla Simon, Jeni Vasilescu, Yunjiang Zhang, Olivier Favez, André S. H. Prévôt, Andrés Alastuey, and María Cruz Minguillón
Atmos. Meas. Tech., 15, 5479–5495, https://doi.org/10.5194/amt-15-5479-2022, https://doi.org/10.5194/amt-15-5479-2022, 2022
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This work presents the differences resulting from two techniques (rolling and seasonal) of the positive matrix factorisation model that can be run for organic aerosol source apportionment. The current state of the art suggests that the rolling technique is more accurate, but no proof of its effectiveness has been provided yet. This paper tackles this issue in the context of a synthetic dataset and a multi-site real-world comparison.
Sungwoo Kim, Brian M. Lerner, Donna T. Sueper, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 15, 5061–5075, https://doi.org/10.5194/amt-15-5061-2022, https://doi.org/10.5194/amt-15-5061-2022, 2022
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Atmospheric samples can be complex, and current analysis methods often require substantial human interaction and discard potentially important information. To improve analysis accuracy and computational cost of these large datasets, we developed an automated analysis algorithm that utilizes a factor analysis approach coupled with a decision tree. We demonstrate that this algorithm cataloged approximately 10 times more analytes compared to a manual analysis and in a quarter of the analysis time.
Olga Zografou, Maria Gini, Manousos I. Manousakas, Gang Chen, Athina C. Kalogridis, Evangelia Diapouli, Athina Pappa, and Konstantinos Eleftheriadis
Atmos. Meas. Tech., 15, 4675–4692, https://doi.org/10.5194/amt-15-4675-2022, https://doi.org/10.5194/amt-15-4675-2022, 2022
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A yearlong ToF-ACSM dataset was used to characterize ambient aerosols over a suburban Athenian site, and innovative software for source apportionment was implemented in order to distinguish the sources of the total non-refractory species of PM1. A comparison between the methodology of combined organic and inorganic PMF analysis and the conventional organic PMF took place.
Jeramy L. Dedrick, Georges Saliba, Abigail S. Williams, Lynn M. Russell, and Dan Lubin
Atmos. Meas. Tech., 15, 4171–4194, https://doi.org/10.5194/amt-15-4171-2022, https://doi.org/10.5194/amt-15-4171-2022, 2022
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A new method is presented to retrieve the sea spray aerosol size distribution by combining submicron size and nephelometer scattering based on Mie theory. Using available sea spray tracers, we find that this approach serves as a comparable substitute to supermicron size distribution measurements, which are limited in availability at marine sites. Application of this technique can expand sea spray observations and improve the characterization of marine aerosol impacts on clouds and climate.
Ivo Beck, Hélène Angot, Andrea Baccarini, Lubna Dada, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Markus Lampimäki, Nicolas Bukowiecki, Matthew Boyer, Xianda Gong, Martin Gysel-Beer, Tuukka Petäjä, Jian Wang, and Julia Schmale
Atmos. Meas. Tech., 15, 4195–4224, https://doi.org/10.5194/amt-15-4195-2022, https://doi.org/10.5194/amt-15-4195-2022, 2022
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We present the pollution detection algorithm (PDA), a new method to identify local primary pollution in remote atmospheric aerosol and trace gas time series. The PDA identifies periods of contaminated data and relies only on the target dataset itself; i.e., it is independent of ancillary data such as meteorological variables. The parameters of all pollution identification steps are adjustable so that the PDA can be tuned to different locations and situations. It is available as open-access code.
Najin Kim, Hang Su, Nan Ma, Ulrich Pöschl, and Yafang Cheng
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-188, https://doi.org/10.5194/amt-2022-188, 2022
Revised manuscript accepted for AMT
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We propose a multiple charging correction algorithm for BS2-CCN system which can obtain the aerosol hygroscopicity and CCN activity with a high time resolution. Unlike existing algorithms, the correction algorithm aims at deriving the true value of activation fraction at each particle size. The meaningful differences between corrected and original κ values (single hygroscopicity parameter) emphasize the importance of correction algorithm for ambient aerosol measurement.
Emily B. Franklin, Lindsay D. Yee, Bernard Aumont, Robert J. Weber, Paul Grigas, and Allen H. Goldstein
Atmos. Meas. Tech., 15, 3779–3803, https://doi.org/10.5194/amt-15-3779-2022, https://doi.org/10.5194/amt-15-3779-2022, 2022
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The composition of atmospheric aerosols are extremely complex, containing hundreds of thousands of estimated individual compounds. The majority of these compounds have never been catalogued in widely used databases, making them extremely difficult for atmospheric chemists to identify and analyze. In this work, we present Ch3MS-RF, a machine-learning-based model to enable characterization of complex mixtures and prediction of structure-specific properties of unidentifiable organic compounds.
Anton Rusanen, Kristo Hõrrak, Lauri R. Ahonen, Tuomo Nieminen, Pasi P. Aalto, Pasi Kolari, Markku Kulmala, Tuukka Petäjä, and Heikki Junninen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-67, https://doi.org/10.5194/amt-2022-67, 2022
Revised manuscript accepted for AMT
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We present a framework for setting up SMEAR (Station for Measuring Earth Surface-Atmosphere Relations) type measurement station data flows. This framework, called SMEARcore, consists of modular open-source software components that can be chosen to suit various station configurations. The benefits of using this framework are automation of routine operations, real-time monitoring of measurement results and station status.
Jiaoshi Zhang, Yang Wang, Steven Spielman, Susanne Hering, and Jian Wang
Atmos. Meas. Tech., 15, 2579–2590, https://doi.org/10.5194/amt-15-2579-2022, https://doi.org/10.5194/amt-15-2579-2022, 2022
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New nonparametric, regularized methods are developed to invert the growth factor probability density function (GF-PDF) from humidity-controlled fast integrated mobility spectrometer measurements. These algorithms are computationally efficient, require no prior assumptions of the GF-PDF distribution, and reduce the error in inverted GF-PDF. They can be applied to humidified tandem differential mobility analyzer data. Among all algorithms, Twomey’s method retrieves GF-PDF with the smallest error.
Douglas A. Day, Pedro Campuzano-Jost, Benjamin A. Nault, Brett B. Palm, Weiwei Hu, Hongyu Guo, Paul J. Wooldridge, Ronald C. Cohen, Kenneth S. Docherty, J. Alex Huffman, Suzane S. de Sá, Scot T. Martin, and Jose L. Jimenez
Atmos. Meas. Tech., 15, 459–483, https://doi.org/10.5194/amt-15-459-2022, https://doi.org/10.5194/amt-15-459-2022, 2022
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Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.
Pak Lun Fung, Martha Arbayani Zaidan, Ola Surakhi, Sasu Tarkoma, Tuukka Petäjä, and Tareq Hussein
Atmos. Meas. Tech., 14, 5535–5554, https://doi.org/10.5194/amt-14-5535-2021, https://doi.org/10.5194/amt-14-5535-2021, 2021
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Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. However, due to the instrumental insufficiency and inversion limitations, the raw dataset contains missing gaps or negative values, which hinder further analysis. With a merged particle size distribution in Jordan, this paper suggests a neural network method to estimate number concentrations at a particular size bin by the number concentration at other size bins.
Xiansheng Liu, Hadiatullah Hadiatullah, Xun Zhang, L. Drew Hill, Andrew H. A. White, Jürgen Schnelle-Kreis, Jan Bendl, Gert Jakobi, Brigitte Schloter-Hai, and Ralf Zimmermann
Atmos. Meas. Tech., 14, 5139–5151, https://doi.org/10.5194/amt-14-5139-2021, https://doi.org/10.5194/amt-14-5139-2021, 2021
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A monitoring campaign was conducted in Augsburg to determine a suitable noise reduction algorithm for the MA200 Aethalometer. Results showed that centred moving average (CMA) post-processing effectively removed spurious negative concentrations without major bias and reliably highlighted effects from local sources, effectively increasing spatio-temporal resolution in mobile measurements. Evaluation of each method on peak sample reduction and background correction further supports the reliability.
Jie Qiu, Wangshu Tan, Gang Zhao, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 4879–4891, https://doi.org/10.5194/amt-14-4879-2021, https://doi.org/10.5194/amt-14-4879-2021, 2021
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Considering nephelometers' major problems of a nonideal Lambertian light source and angle truncation, a new correction method based on a machine learning model is proposed. Our method has the advantage of obtaining data with high accuracy while achieving self-correction, which means that researchers can get more accurate scattering coefficients without the need for additional observation data. This method provides a more precise estimation of the aerosol’s direct radiative forcing.
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827, https://doi.org/10.5194/amt-14-4805-2021, https://doi.org/10.5194/amt-14-4805-2021, 2021
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We propose a spectroscopic method for estimating several mixture-averaged molecular properties (carbon number and molecular weight) in particulate matter relevant for understanding its chemical origins. This estimation is enabled by calibration models built and tested using laboratory standards containing molecules with known structure, and can be applied to filter samples of PM2.5 currently collected in existing air pollution monitoring networks and field campaigns.
Aki Virkkula
Atmos. Meas. Tech., 14, 3707–3719, https://doi.org/10.5194/amt-14-3707-2021, https://doi.org/10.5194/amt-14-3707-2021, 2021
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The Aethalometer model is used widely for estimating the contributions of fossil fuel emissions and biomass burning to black carbon. The calculation is based on measured absorption Ångström exponents, which is ambiguous since it not only depends on the dominant absorber but also on the size and internal structure of the particles, core size, and shell thickness. The uncertainties of the fractions of absorption by eBC from fossil fuel and biomass burning are evaluated with a core–shell Mie model.
Weiqi Xu, Masayuki Takeuchi, Chun Chen, Yanmei Qiu, Conghui Xie, Wanyun Xu, Nan Ma, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Meas. Tech., 14, 3693–3705, https://doi.org/10.5194/amt-14-3693-2021, https://doi.org/10.5194/amt-14-3693-2021, 2021
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Here we developed a method for estimation of particulate organic nitrates (pON) from the measurements of a high-resolution aerosol mass spectrometer coupled with a thermodenuder based on the volatility differences between inorganic nitrate and pON. The results generally had improvements in reducing negative values due to the influences of a high concentration of inorganic nitrate and a constant ratio of NO+ to NO2+ of organic nitrates (RON).
Melinda K. Schueneman, Benjamin A. Nault, Pedro Campuzano-Jost, Duseong S. Jo, Douglas A. Day, Jason C. Schroder, Brett B. Palm, Alma Hodzic, Jack E. Dibb, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 2237–2260, https://doi.org/10.5194/amt-14-2237-2021, https://doi.org/10.5194/amt-14-2237-2021, 2021
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This work focuses on two important properties of the aerosol, acidity, and sulfate composition, which is important for our understanding of aerosol health and environmental impacts. We explore different methods to understand the composition of the aerosol with measurements from a specific instrument and apply those methods to a large dataset. These measurements are confounded by other factors, making it challenging to predict aerosol sulfate composition; pH estimations, however, show promise.
Weilun Zhao, Wangshu Tan, Gang Zhao, Chuanyang Shen, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1319–1331, https://doi.org/10.5194/amt-14-1319-2021, https://doi.org/10.5194/amt-14-1319-2021, 2021
Chuanyang Shen, Gang Zhao, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 1293–1301, https://doi.org/10.5194/amt-14-1293-2021, https://doi.org/10.5194/amt-14-1293-2021, 2021
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Aerosol hygroscopicity measured by the humidified tandem differential mobility analyzer (HTDMA) is affected by multiply charged particles from two aspects: (1) number contribution and (2) the weakening effect. An algorithm is proposed to do the multi-charge correction and applied to a field measurement. Results show that the difference between corrected and measured size-resolved κ can reach 0.05, highlighting that special attention needs to be paid to the multi-charge effect when using HTDMA.
Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt
Atmos. Meas. Tech., 14, 923–943, https://doi.org/10.5194/amt-14-923-2021, https://doi.org/10.5194/amt-14-923-2021, 2021
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Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Kenji Miki and Shigeto Kawashima
Atmos. Meas. Tech., 14, 685–693, https://doi.org/10.5194/amt-14-685-2021, https://doi.org/10.5194/amt-14-685-2021, 2021
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Laser optics have long been used in pollen counting systems. To clarify the limitations and potential new applications of laser optics for automatic pollen counting and discrimination, we determined the light scattering patterns of various pollen types, tracked temporal changes in these distributions, and introduced a new theory for automatic pollen discrimination.
Yinchao Zhang, Su Chen, Siying Chen, He Chen, and Pan Guo
Atmos. Meas. Tech., 13, 6675–6689, https://doi.org/10.5194/amt-13-6675-2020, https://doi.org/10.5194/amt-13-6675-2020, 2020
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Air pollution has an important impact on human health, climatic patterns, and the ecological environment. The complexity of the nocturnal boundary layer (NBL), combined with its strong physio-chemical effect, induces worse polluted episodes. Therefore, we present a new approach named cluster analysis of gradient method (CA-GM) to overcome the multilayer structure and remove the fluctuation of NBL height using raw data resolution.
Tommy Chan, Runlong Cai, Lauri R. Ahonen, Yiliang Liu, Ying Zhou, Joonas Vanhanen, Lubna Dada, Yan Chao, Yongchun Liu, Lin Wang, Markku Kulmala, and Juha Kangasluoma
Atmos. Meas. Tech., 13, 4885–4898, https://doi.org/10.5194/amt-13-4885-2020, https://doi.org/10.5194/amt-13-4885-2020, 2020
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Using a particle size magnifier (PSM; Airmodus, Finland), we determined the particle size distribution using four inversion methods and compared each method to the others to establish their strengths and weaknesses. Furthermore, we provided a step-by-step procedure on how to invert measured data using the PSM. Finally, we provided recommendations, code and data related to the data inversion. This is an important paper, as no operating procedure exists regarding how to process measured PSM data.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Shengqiang Zhu, Lei Li, Shurong Wang, Mei Li, Yaxi Liu, Xiaohui Lu, Hong Chen, Lin Wang, Jianmin Chen, Zhen Zhou, Xin Yang, and Xiaofei Wang
Atmos. Meas. Tech., 13, 4111–4121, https://doi.org/10.5194/amt-13-4111-2020, https://doi.org/10.5194/amt-13-4111-2020, 2020
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Single-particle aerosol mass spectrometry (SPAMS) is widely used to detect chemical compositions and sizes of individual aerosol particles. However, it has a major issue: the mass accuracy of high-resolution SPAMS is relatively low. Here we developed an automatic linear calibration method to greatly improve the mass accuracy of SPAMS spectra so that the elemental compositions of organic peaks, such as Cx, CxHy, CxHyOz and CxHyNO peaks, can be directly identified just based on their m / z values.
William Wandji Nyamsi, Antti Lipponen, Arturo Sanchez-Lorenzo, Martin Wild, and Antti Arola
Atmos. Meas. Tech., 13, 3061–3079, https://doi.org/10.5194/amt-13-3061-2020, https://doi.org/10.5194/amt-13-3061-2020, 2020
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This paper proposes a novel and accurate method for estimating and reconstructing aerosol optical depth from sunshine duration measurements under cloud-free conditions at any place and time since the late 19th century. The method performs very well when compared to AErosol RObotic NETwork measurements and operates an efficient detection of signals from massive volcanic eruptions. Reconstructed long-term aerosol optical depths are in agreement with the dimming/brightening phenomenon.
Sascha Pfeifer, Thomas Müller, Andrew Freedman, and Alfred Wiedensohler
Atmos. Meas. Tech., 13, 2161–2167, https://doi.org/10.5194/amt-13-2161-2020, https://doi.org/10.5194/amt-13-2161-2020, 2020
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The effect of the baseline drift on the resulting extinction values of three CAPS PMex monitors with different wavelengths was analysed for an urban background station. A significant baseline drift was observed, which leads to characteristic measurement artefacts for particle extinction. Two alternative methods for recalculating the baseline are shown. With these methods the extinction artefacts are diminished and the effective scattering of the resulting extinction values is reduced.
Stuart K. Grange, Hanspeter Lötscher, Andrea Fischer, Lukas Emmenegger, and Christoph Hueglin
Atmos. Meas. Tech., 13, 1867–1885, https://doi.org/10.5194/amt-13-1867-2020, https://doi.org/10.5194/amt-13-1867-2020, 2020
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Black carbon (BC) is an important atmospheric pollutant and can be monitored by instruments called aethalometers. A pragmatic data processing technique called the
aethalometer modelcan be used to apportion aethalometer observations into traffic and woodburning components. We present an exploratory data analysis evaluating the aethalometer model and use the outputs for BC trend analysis across Switzerland. The aethalometer model's robustness and utility for such analyses is discussed.
Charlotte Bürki, Matteo Reggente, Ann M. Dillner, Jenny L. Hand, Stephanie L. Shaw, and Satoshi Takahama
Atmos. Meas. Tech., 13, 1517–1538, https://doi.org/10.5194/amt-13-1517-2020, https://doi.org/10.5194/amt-13-1517-2020, 2020
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Infrared spectroscopy is a chemically informative method for particulate matter characterization. However, recent work has demonstrated that predictions depend heavily on the choice of calibration model parameters. We propose a means for managing parameter uncertainties by combining available data from laboratory standards, molecular databases, and collocated ambient measurements to provide useful characterization of atmospheric organic matter on a large scale.
Kaixu Bai, Ke Li, Jianping Guo, Yuanjian Yang, and Ni-Bin Chang
Atmos. Meas. Tech., 13, 1213–1226, https://doi.org/10.5194/amt-13-1213-2020, https://doi.org/10.5194/amt-13-1213-2020, 2020
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A novel gap-filling method called the diurnal-cycle-constrained empirical orthogonal function (DCCEOF) is proposed. Cross validation indicates that this method gives high accuracy in predicting missing values in daily PM2.5 time series by accounting for the local diurnal phases, especially by reconstructing daily extrema that cannot be accurately restored by other approaches. The DCCEOF method can be easily applied to other data sets because of its self-consistent capability.
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181, https://doi.org/10.5194/amt-12-5161-2019, https://doi.org/10.5194/amt-12-5161-2019, 2019
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Here we present a simultaneous Gaussian process regression (GPR) and linear regression pipeline to calibrate and monitor dense wireless low-cost particulate matter sensor networks (WLPMSNs) on the fly by using all available reference monitors across an area. Our approach can achieve an overall 30 % prediction error at a 24 h scale, can differentiate malfunctioning nodes, and track drift. Our solution can substantially reduce manual labor for managing WLPMSNs and prolong their lifetimes.
Stina Ausmeel, Axel Eriksson, Erik Ahlberg, and Adam Kristensson
Atmos. Meas. Tech., 12, 4479–4493, https://doi.org/10.5194/amt-12-4479-2019, https://doi.org/10.5194/amt-12-4479-2019, 2019
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We present a method for identifying individual exhaust plumes of air pollution emitted from shipping, by linking these to specific ships using identification information which all ships transmit. We also quantify the contribution of these plumes to local particle levels, which has relevance for health effects. Ships emit a lot of nanometre-sized particles, which proved to be a good indicator of plumes at a distance of about 10 km downwind of a shipping lane in the Baltic Sea.
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452, https://doi.org/10.5194/amt-12-3435-2019, https://doi.org/10.5194/amt-12-3435-2019, 2019
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The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.
Matteo Reggente, Rudolf Höhn, and Satoshi Takahama
Atmos. Meas. Tech., 12, 2313–2329, https://doi.org/10.5194/amt-12-2313-2019, https://doi.org/10.5194/amt-12-2313-2019, 2019
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The infrared spectra of atmospheric particles are rich in chemical information but require sophisticated statistical methods to extract information on account of their complex absorption profiles. We present an open software suite which makes current algorithms used for analysis of such spectra available to the community, with a browser-based interface for general users and modular architecture that facilitates addition of new methods by developers.
Xiaoli Shen, Harald Saathoff, Wei Huang, Claudia Mohr, Ramakrishna Ramisetty, and Thomas Leisner
Atmos. Meas. Tech., 12, 2219–2240, https://doi.org/10.5194/amt-12-2219-2019, https://doi.org/10.5194/amt-12-2219-2019, 2019
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Based on single-particle mass spectra from field measurements in the upper Rhine valley, we identified characteristic particle classes and estimated their mass contributions without the need of a reference instrument in the field. Our study provides a good example for quantitative interpretation of single-particle data. Together with the complimentary results from bulk measurements, we have shown how a better understanding of the mixing state of ambient aerosol particles can be achieved.
Tarjei Antonsen, Ove Havnes, and Andres Spicher
Atmos. Meas. Tech., 12, 2139–2153, https://doi.org/10.5194/amt-12-2139-2019, https://doi.org/10.5194/amt-12-2139-2019, 2019
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This paper presents measurements of changes in mesospheric aerosol populations on different length scales, as detected by the DUSTY and MUDD probes on the MAXIDUSTY-1B rocket on 8 July 2016. Identical probes recorded very different currents, which we attribute to adverse flow effects. We find a general anti-correlation for charged aerosols and electrons, but not consistently on all length scales. We conclude that there is no simple relationship between aerosols and PMSE (radar echoes).
Ove Havnes, Tarjei Antonsen, Gerd Baumgarten, Thomas W. Hartquist, Alexander Biebricher, Åshild Fredriksen, Martin Friedrich, and Jonas Hedin
Atmos. Meas. Tech., 12, 1673–1683, https://doi.org/10.5194/amt-12-1673-2019, https://doi.org/10.5194/amt-12-1673-2019, 2019
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We present a new method of analyzing data from rocket-borne aerosol detectors of the Faraday cup type (DUSTY). By using models for how aerosols are charged in the mesosphere and how they interact in a collision with the probes, fundamental parameters like aerosol radius, charge, and number density can be derived. The resolution can be down to ~ 10 cm, which is much lower than other available methods. The theory is furthermore used to analyze DUSTY data from the 2016 rocket campaign MAXIDUSTY.
Satoshi Takahama, Ann M. Dillner, Andrew T. Weakley, Matteo Reggente, Charlotte Bürki, Mária Lbadaoui-Darvas, Bruno Debus, Adele Kuzmiakova, and Anthony S. Wexler
Atmos. Meas. Tech., 12, 525–567, https://doi.org/10.5194/amt-12-525-2019, https://doi.org/10.5194/amt-12-525-2019, 2019
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Mid-infrared spectra of particulate matter (PM) samples are complex but chemically informative and present an opportunity for cost-effective measurement of PM provided that quantitative calibration models can be built. We review an emerging strategy for building statistical calibration models using collocated measurements, interpreting the physical bases for such models and evaluating the suitability of existing calibration models to new samples.
Runlong Cai, Dongsen Yang, Lauri R. Ahonen, Linlin Shi, Frans Korhonen, Yan Ma, Jiming Hao, Tuukka Petäjä, Jun Zheng, Juha Kangasluoma, and Jingkun Jiang
Atmos. Meas. Tech., 11, 4477–4491, https://doi.org/10.5194/amt-11-4477-2018, https://doi.org/10.5194/amt-11-4477-2018, 2018
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We tested the performance of four inversion methods to recover sub-3 nm aerosol size distributions using the particle size magnifier (PSM). The PSM is widely used in new particle formation study; however, the inversion methods used in previous studies may report false particle concentrations. Due to the results, we suggest using the expectation–maximization algorithm to address the PSM inversion problem. We also gave practical suggestions on PSM operation based on the inversion analysis.
Ye Kuang, Chun Sheng Zhao, Gang Zhao, Jiang Chuan Tao, Wanyun Xu, Nan Ma, and Yu Xuan Bian
Atmos. Meas. Tech., 11, 2967–2982, https://doi.org/10.5194/amt-11-2967-2018, https://doi.org/10.5194/amt-11-2967-2018, 2018
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Aerosol water has become an important topic recently because of its implications for multiphase secondary aerosol formation during severe haze events in Asia. This is a timely paper on this topic; a novel method is proposed to calculate ambient aerosol liquid water contents based only on measurements of a three-wavelength humidified nephelometer system. The advantage of this method is that this technique can provide continuous measurements of the changing ambient conditions.
Cheng Wu and Jian Zhen Yu
Atmos. Meas. Tech., 11, 1233–1250, https://doi.org/10.5194/amt-11-1233-2018, https://doi.org/10.5194/amt-11-1233-2018, 2018
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A new data generation scheme that employs the Mersenne twister (MT) pseudorandom number generator is proposed to conduct benchmark tests on a variety of linear regression techniques. With an appropriate weighting, Deming regression (DR), weighted ODR (WODR), and York regression (YR) are recommended for atmospheric studies when both x and y data have measurement errors. An Igor-based program (Scatter Plot) is developed to facilitate the regression implementation.
Cited articles
Agarwal, S., Mierle, K., and Others: Ceres Solver,
available at: http://ceres-solver.org, 2020. a
Atwood, S. A., Kreidenweis, S. M., DeMott, P. J., Petters, M. D., Cornwell, G. C., Martin, A. C., and Moore, K. A.: Classification of aerosol population type and cloud condensation nuclei properties in a coastal California littoral environment using an unsupervised cluster model, Atmos. Chem. Phys., 19, 6931–6947, https://doi.org/10.5194/acp-19-6931-2019, 2019. a, b, c
Baart, M. L.: The Use of Auto-Correlation for Pseudo-Rank
Determination in Noisy III-Conditioned Linear Least-Squares
Problems, IMA Journal of Numerical Analysis, 2, 241–247,
https://doi.org/10.1093/imanum/2.2.241, 1982. a
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.: Julia: A Fresh
Approach to Numerical Computing, SIAM Review, 59, 65–98,
https://doi.org/10.1137/141000671, 2017. a
Bodega Bay Preprocessed Data: Size-resolved cloud condensation nuclei data collected during the CalWater 2015 field campaign (Version v1.0), edited by: Petters, M. D., Rothfuss, N. E., Taylor, H., Kreidenweis, S. M., DeMott, P. J., and Atwood, S. A.: Zenodo [Data set], https://doi.org/10.5281/zenodo.2605668, 2019.
Borsdorff, T., Hasekamp, O. P., Wassmann, A., and Landgraf, J.: Insights into Tikhonov regularization: application to trace gas column retrieval and the efficient calculation of total column averaging kernels, Atmos. Meas. Tech., 7, 523–535, https://doi.org/10.5194/amt-7-523-2014, 2014. a
Chen, H., Hodshire, A. L., Ortega, J., Greenberg, J., McMurry, P. H., Carlton, A. G., Pierce, J. R., Hanson, D. R., and Smith, J. N.: Vertically resolved concentration and liquid water content of atmospheric nanoparticles at the US DOE Southern Great Plains site, Atmos. Chem. Phys., 18, 311–326, https://doi.org/10.5194/acp-18-311-2018, 2018. a
Cubison, M., Coe, H., and Gysel, M.: A Modified Hygroscopic Tandem DMA and
a Data Retrieval Method Based on Optimal Estimation, J. Aerosol
Sci., 36, 846–865, https://doi.org/10.1016/j.jaerosci.2004.11.009, 2005. a, b, c
Dawson, K. W., Petters, M. D., Meskhidze, N., Petters, S. S., and Kreidenweis,
S. M.: Hygroscopic Growth and Cloud Droplet Activation of Xanthan Gum as a
Proxy for Marine Hydrogels, J. Geophys. Res.-Atmos.,
121, 11803–11818, https://doi.org/10.1002/2016JD025143, 2016. a
Dubovik, O. and King, M. D.: A Flexible Inversion Algorithm for Retrieval of
Aerosol Optical Properties from Sun and Sky Radiance Measurements,
J. Geophys. Res.-Atmos., 105, 20673–20696,
https://doi.org/10.1029/2000JD900282, 2000. a
Eldén, L.: A Weighted Pseudoinverse, Generalized Singular Values, and
Constrained Least Squares Problems, BIT Numerical Mathematics, 22, 487–502,
https://doi.org/10.1007/BF01934412, 1982. a, b
Farmer, D. K., Cappa, C. D., and Kreidenweis, S. M.: Atmospheric Processes
and Their Controlling Influence on Cloud Condensation Nuclei
Activity, Chem. Rev., 115, 4199–4217, https://doi.org/10.1021/cr5006292, 2015. a
Golub, G. H., Heath, M., and Wahba, G.: Generalized Cross-Validation as
a Method for Choosing a Good Ridge Parameter, Technometrics, 21,
215–223, https://doi.org/10.2307/1268518, 1979. a, b
Hansen, P. C.: 2. Decompositions and Other Tools, in:
Rank-Deficient and Discrete Ill-Posed Problems, Mathematical
Modeling and Computation, Society for Industrial and
Applied Mathematics, 19–44, https://doi.org/10.1137/1.9780898719697.ch2, 1998. a, b
Hansen, P. C.: Regularization Tools Version 4.0 for Matlab 7.3,
Numerical Algorithms, 46, 189–194, https://doi.org/10.1007/s11075-007-9136-9, 2007. a
Hodshire, A. L., Lawler, M. J., Zhao, J., Ortega, J., Jen, C., Yli-Juuti, T., Brewer, J. F., Kodros, J. K., Barsanti, K. C., Hanson, D. R., McMurry, P. H., Smith, J. N., and Pierce, J. R.: Multiple new-particle growth pathways observed at the US DOE Southern Great Plains field site, Atmos. Chem. Phys., 16, 9321–9348, https://doi.org/10.5194/acp-16-9321-2016, 2016. a
Huckle, T. and Sedlacek, M.: Data Based Regularization Matrices for the
Tikhonov-Phillips Regularization, PAMM, 12, 643–644,
https://doi.org/10.1002/pamm.201210310, 2012. a, b, c
Jefferson, A., Hageman, D., Morrow, H., Mei, F., and Watson, T.: Seven Years of
Aerosol Scattering Hygroscopic Growth Measurements from SGP: Factors
Influencing Water Uptake, J. Geophys. Res.-Atmos., 122,
9451–9466, https://doi.org/10.1002/2017JD026804, 2017. a, b
Jiang, J., Kim, C., Wang, X., Stolzenburg, M. R., Kaufman, S. L., Qi, C., Sem,
G. J., Sakurai, H., Hama, N., and McMurry, P. H.: Aerosol Charge Fractions
Downstream of Six Bipolar Chargers: Effects of Ion Source,
Source Activity, and Flowrate, Aerosol Sci. Tech., 48,
1207–1216, https://doi.org/10.1080/02786826.2014.976333, 2014. a
Jimenez, J. L., Canagaratna, M. R., Drewnick, F., Allan, J. D., Alfarra, M. R.,
Middlebrook, A. M., Slowik, J. G., Zhang, Q., Coe, H., Jayne, J. T., and
Worsnop, D. R.: Comment on “The Effects of Molecular Weight and Thermal
Decomposition on the Sensitivity of a Thermal Desorption Aerosol Mass
Spectrometer”, Aerosol Sci. Tech., 50,
https://doi.org/10.1080/02786826.2016.1205728, 2016. a
Joutsensaari, J., Ozon, M., Nieminen, T., Mikkonen, S., Lähivaara, T., Decesari, S., Facchini, M. C., Laaksonen, A., and Lehtinen, K. E. J.: Identification of new particle formation events with deep learning, Atmos. Chem. Phys., 18, 9597–9615, https://doi.org/10.5194/acp-18-9597-2018, 2018. a
Jung, J. and Kawamura, K.: Hygroscopic properties of newly formed ultrafine particles at an urban site surrounded by deciduous forest (Sapporo, northern Japan) during the summer of 2011, Atmos. Chem. Phys., 14, 7519–7531, https://doi.org/10.5194/acp-14-7519-2014, 2014. a
Knutson, E. O. and Whitby, K. T.: Aerosol Classification by Electric Mobility:
Apparatus, Theory, and Applications, J. Aerosol Sci., 6, 443–451,
https://doi.org/10.1016/0021-8502(75)90060-9, 1975. a, b
Krakauer, N. Y., Schneider, T., Randerson, J. T., and Olsen, S. C.: Using
Generalized Cross-Validation to Select Parameters in Inversions for Regional
Carbon Fluxes, Geophys. Res. Lett., 31, L19108, https://doi.org/10.1029/2004GL020323,
2004. a
Kreidenweis, S. M., Petters, M., and Lohmann, U.: 100 Years of Progress
in Cloud Physics, Aerosols, and Aerosol Chemistry Research,
Meteorological Monographs, 59, 11.1–11.72,
https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0024.1, 2019. a
Kuang, C.: Scanning Mobility Particle Spectrometer Instrument Handbook,
Tech. Rep. DOE/SC-ARM-TR-147, U.S. Department of Energy, Office of Science,
ARM Climate Research Facility, 2016. a
Lampe, J., Reichel, L., and Voss, H.: Large-Scale Tikhonov Regularization
via Reduction by Orthogonal Projection, Special Issue dedicated to Danny
Sorensen's 65th birthday, 436, 2845–2865, https://doi.org/10.1016/j.laa.2011.07.019,
2012. a
Lira, M., Iyer, R., Trindade, A. A., and Howle, V.: QR Versus Cholesky: A
Probabilistic Analysis, International Journal of Numerical Analysis and
Modeling, 1, 114–121, 2016. a
Lopez-Yglesias, X. F., Yeung, M. C., Dey, S. E., Brechtel, F. J., and Chan,
C. K.: Performance Evaluation of the Brechtel Mfg. Humidified
Tandem Differential Mobility Analyzer (BMI HTDMA) for Studying
Hygroscopic Properties of Aerosol Particles, Aerosol Sci. Tech., 48, 969–980, https://doi.org/10.1080/02786826.2014.952366, 2014. a
Mahish, M., Jefferson, A., and Collins, R. D.: Influence of Common
Assumptions Regarding Aerosol Composition and Mixing State on
Predicted CCN Concentration, Atmosphere, 9, https://doi.org/10.3390/atmos9020054,
2018. a, b
Marinescu, P. J., Levin, E. J. T., Collins, D., Kreidenweis, S. M., and van den Heever, S. C.: Quantifying aerosol size distributions and their temporal variability in the Southern Great Plains, USA, Atmos. Chem. Phys., 19, 11985–12006, https://doi.org/10.5194/acp-19-11985-2019, 2019. a
Martin, A. C., Cornwell, G. C., Atwood, S. A., Moore, K. A., Rothfuss, N. E., Taylor, H., DeMott, P. J., Kreidenweis, S. M., Petters, M. D., and Prather, K. A.: Transport of pollution to a remote coastal site during gap flow from California's interior: impacts on aerosol composition, clouds, and radiative balance, Atmos. Chem. Phys., 17, 1491–1509, https://doi.org/10.5194/acp-17-1491-2017, 2017. a
Mikhailov, E., Vlasenko, S., Niessner, R., and Pöschl, U.: Interaction of aerosol particles composed of protein and saltswith water vapor: hygroscopic growth and microstructural rearrangement, Atmos. Chem. Phys., 4, 323–350, https://doi.org/10.5194/acp-4-323-2004, 2004. a
Mogensen, P. K. and Riseth, A. N.: Optim: A Mathematical Optimization
Package for Julia, Journal of Open Source Software, 3, 615,
https://doi.org/10.21105/joss.00615, 2018. a, b
Müller, D., Chemyakin, E., Kolgotin, A., Ferrare, R. A., Hostetler, C. A.,
and Romanov, A.: Automated, Unsupervised Inversion of Multiwavelength Lidar
Data with TiARA: Assessment of Retrieval Performance of Microphysical
Parameters Using Simulated Data, Appl. Opt., 58, 4981–5008,
https://doi.org/10.1364/AO.58.004981, 2019. a, b, c
Oxford, C. R., Dang, A. J., Rapp, C. M., and Williams, B. J.: Interpretation of
Volatility Tandem Differential Mobility Analyzer (V-TDMA) Data
for Accurate Vapor Pressure and Enthalpy Measurement: Operational
Considerations, Multiple Charging, and Introduction to a New Analysis Program
(TAO), Aerosol Sci. Tech., 54, 410–425,
https://doi.org/10.1080/02786826.2019.1709617, 2020. a
Ozon, M., Seppänen, A., Kaipio, J. P., and Lehtinen, K. E. J.: Retrieval of process rate parameters in the general dynamic equation for aerosols using Bayesian state estimation: BAYROSOL1.0, Geosci. Model Dev., 14, 3715–3739, https://doi.org/10.5194/gmd-14-3715-2021, 2021a. a
Ozon, M., Stolzenburg, D., Dada, L., Seppänen, A., and Lehtinen, K. E. J.: Aerosol formation and growth rates from chamber experiments using Kalman smoothing, Atmos. Chem. Phys., 21, 12595–12611, https://doi.org/10.5194/acp-21-12595-2021, 2021b. a
Park, K., Dutcher, D., Emery, M., Pagels, J., Sakurai, H., Scheckman, J., Qian,
S., Stolzenburg, M. R., Wang, X., Yang, J., and McMurry, P. H.: Tandem
Measurements of Aerosol Properties – A Review of
Mobility Techniques with Extensions, Aerosol Sci. Tech.,
42, 801–816, https://doi.org/10.1080/02786820802339561, 2008. a, b
Petters, M. D.: Software and data for “Revisiting Matrix-Based Inversion of SMPS and HTDMA Data”, Zenodo [data set], https://doi.org/10.5281/zenodo.5550382, 2021. a
Phillips, D. L.: A Technique for the Numerical Solution of Certain Integral
Equations of the First Kind, Journal of the ACM, 9, 84–97,
https://doi.org/10.1145/321105.321114, 1962. a
Rader, D. and McMurry, P.: Application of the Tandem Differential Mobility
Analyzer to Studies of Droplet Growth or Evaporation, J. Aerosol
Sci., 17, 771–787, https://doi.org/10.1016/0021-8502(86)90031-5, 1986. a, b
Rawat, V. K., Buckley, D. T., Kimoto, S., Lee, M.-H., Fukushima, N., and Hogan,
C. J.: Two Dimensional Size – Mass Distribution Function Inversion
from Differential Mobility Analyzer – Aerosol Particle Mass Analyzer
(DMA – APM) Measurements, J. Aerosol Sci., 92,
70–82, https://doi.org/10.1016/j.jaerosci.2015.11.001, 2016. a, b, c
Reineking, A. and Porstendörfer, J.: Measurements of Particle Loss
Functions in a Differential Mobility Analyzer (TSI, Model 3071)
for Different Flow Rates, Aerosol Sci. Tech., 5, 483–486,
https://doi.org/10.1080/02786828608959112, 1986. a, b, c
Riemer, N., Ault, A. P., West, M., Craig, R. L., and Curtis, J. H.: Aerosol
Mixing State: Measurements, Modeling, and Impacts, Rev. Geophys., 57, 187–249, https://doi.org/10.1029/2018RG000615, 2019. a, b
Royalty, T. M., Phillips, B. N., Dawson, K. W., Reed, R., Meskhidze, N., and
Petters, M. D.: Aerosol Properties Observed in the Subtropical North
Pacific Boundary Layer, J. Geophys. Res.-Atmos., 122,
9990–10,012, https://doi.org/10.1002/2017JD026897, 2017. a
Russell, L. M., Zhang, S.-H., Flagan, R. C., Seinfeld, J. H., Stolzenburg,
M. R., and Caldow, R.: Radially Classified Aerosol Detector for
Aircraft-Based Submicron Aerosol Measurements, J. Atmos. Ocean. Technol., 13, 598–609,
https://doi.org/10.1175/1520-0426(1996)013<0598:RCADFA>2.0.CO;2, 1996. a
SGP SMPS Data: Atmospheric Radiation Measurement (ARM) user facility. 2016, updated hourly, Scanning mobility particle sizer (AOSSMPS), 2020-01-01 to 2020-09-27, Southern Great Plains (SGP) Lamont, OK (Extended and Co-located with C1) (E13), edited by: Kuang, C., Salwen, C., Boyer, M., and Singh, A., ARM Data Center, https://doi.org/10.5439/1095583, last access: 29 September 2020a.
SGP HTDMA Data: Atmospheric Radiation Measurement (ARM) user facility. 2017, updated hourly. Humidified Tandem Differential Mobility Analyzer (AOSHTDMA), 2020-01-01 to 2020-02-22, Southern Great Plains (SGP) Lamont, OK (Extended and Co-located with C1) (E13), edited by: Uin, J., Salwen, C., and Senum, G., ARM Data Center, https://doi.org/10.5439/1095581, last access: 29 September 2020b.
Shen, C., Zhao, G., and Zhao, C.: Effects of multi-charge on aerosol hygroscopicity measurement by a HTDMA, Atmos. Meas. Tech., 14, 1293–1301, https://doi.org/10.5194/amt-14-1293-2021, 2021. a, b, c, d
Shingler, T., Sorooshian, A., Ortega, A., Crosbie, E., Wonaschütz, A.,
Perring, A. E., Beyersdorf, A., Ziemba, L., Jimenez, J. L., Campuzano-Jost,
P., Mikoviny, T., Wisthaler, A., and Russell, L. M.: Ambient Observations of
Hygroscopic Growth Factor and f(RH) below 1: Case Studies from
Surface and Airborne Measurements, J. Geophys. Res.-Atmos., 121, 13661–13677, https://doi.org/10.1002/2016JD025471, 2016. a
Sipkens, T., Olfert, J., and Rogak, S.: Inversion Methods to Determine
Two-Dimensional Aerosol Mass-Mobility Distributions: A Critical
Comparison of Established Methods, J. Aerosol Sci., 140, 105484,
https://doi.org/10.1016/j.jaerosci.2019.105484, 2020. a, b, c
Suda, S. R. and Petters, M. D.: Accurate Determination of Aerosol
Activity Coefficients at Relative Humidities up to 99% Using the
Hygroscopicity Tandem Differential Mobility Analyzer Technique, Aerosol
Sci. Technol., 47, 991–1000, https://doi.org/10.1080/02786826.2013.807906,
2013. a
Swietlicki, E., Hansson, H. C., Hämeri, K., Svenningsson, B., Massling, A.,
Mcfiggans, G., Mcmurry, P. H., Petäjä, T., Tunved, P., Gysel, M.,
Topping, D., Weingartner, E., Baltensperger, U., Rissler, J., Wiedensohler,
A., and Kulmala, M.: Hygroscopic Properties of Submicrometer Atmospheric
Aerosol Particles Measured with H-TDMA Instruments in Various
Environments – a Review, Tellus B, 60, 432–469, https://doi.org/10.1111/j.1600-0889.2008.00350.x, 2008. a
Talukdar, S. S. and Swihart, M. T.: An Improved Data Inversion Program for
Obtaining Aerosol Size Distributions from Scanning Differential
Mobility Analyzer Data, Aerosol Sci. Tech., 37, 145–161,
https://doi.org/10.1080/02786820300952, 2003. a, b, c, d
Tikhonov, A. N.: Solution of Incorrectly Formulated Problems and the
Regularization Method, Soviet Mathematics Doklady, 4, 1035–1038, 1963. a
Twomey, S.: On the Numerical Solution of Fredholm Integral Equations of the
First Kind by the Inversion of the Linear System Produced by Quadrature, J.
ACM, 10, 97–101, 1963. a
Uin, J. and Smith, S.: Southern Great Plains (SGP) Aerosol Observing
System (AOS) Instrument Handbook, Tech. Rep. DOE/SC-ARM-TR-267,
U.S. Department of Energy, Office of Science, ARM Climate Research
Facility, 2020. a
Voutilainen, A., Kolehmainen, V., and Kaipio, J. P.: Statistical Inversion of
Aerosol Size Measurement Data, Inverse Problems in Engineering, 9, 67–94,
https://doi.org/10.1080/174159701088027753, 2001. a, b, c
Wang, S. C. and Flagan, R. C.: Scanning Electrical Mobility Spectrometer,
Aerosol Sci. Tech., 13, 230–240,
https://doi.org/10.1080/02786829008959441, 1990. a, b, c
Wiedensohler, A.: An Approximation of the Bipolar Charge Distribution for
Particles in the Submicron Size Range, J. Aerosol Sci., 19,
387–389, https://doi.org/10.1016/0021-8502(88)90278-9, 1988. a
Wolfenbarger, K. J. and Seinfeld, J. H.: Inversion of Aerosol Size Distribution
Data, J. Aerosol Sci., 21, 227–247,
https://doi.org/10.1016/0021-8502(90)90007-K, 1990. a, b
Wu, Z., Birmili, W., Poulain, L., Wang, Z., Merkel, M., Fahlbusch, B., van Pinxteren, D., Herrmann, H., and Wiedensohler, A.: Particle hygroscopicity during atmospheric new particle formation events: implications for the chemical species contributing to particle growth, Atmos. Chem. Phys., 13, 6637–6646, https://doi.org/10.5194/acp-13-6637-2013, 2013. a
Zhang, S.-H., Akutsu, Y., Russell, L. M., Flagan, R. C., and Seinfeld, J. H.:
Radial Differential Mobility Analyzer, Aerosol Sci. Tech.,
23, 357–372, https://doi.org/10.1080/02786829508965320, 1995. a
Short summary
Inverse methods infer physical properties from a measured instrument response. Measurement noise often interferes with the inversion. This work presents a general, domain-independent, accessible, and computationally efficient software implementation of a common class of statistical inversion methods. In addition, a new method to invert data from humidified tandem differential mobility analyzers is introduced. Results show that the approach is suitable for inversion of large-scale datasets.
Inverse methods infer physical properties from a measured instrument response. Measurement noise...
