Articles | Volume 14, issue 11
https://doi.org/10.5194/acp-14-5327-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-5327-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
03 Jun 2014
Research article |
| 03 Jun 2014
Modeling the evolution of aerosol particles in a ship plume using PartMC-MOSAIC
J. Tian
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
N. Riemer
Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
M. West
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
L. Pfaffenberger
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen, Switzerland
H. Schlager
Dt. Zentrum für Luft- und Raumfahrt, Inst. für Physik der Atmosphäre, Oberpfaffenhofen, 82234 Wessling, Germany
A. Petzold
Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research, IEK-8-Troposphere, Jülich, Germany
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Cited
31 citations as recorded by crossref.
- Convergence of a generalized Weighted Flow Algorithm for stochastic particle coagulation L. DeVille et al. https://doi.org/10.3934/jcd.2019003
- Detection of ship plumes from residual fuel operation in emission control areas using single-particle mass spectrometry J. Passig et al. https://doi.org/10.5194/amt-14-4171-2021
- Simulating aerosol chamber experiments with the particle-resolved aerosol model PartMC J. Tian et al. https://doi.org/10.1080/02786826.2017.1311988
- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics M. Hughes et al. https://doi.org/10.3390/atmos9010015
- Description and evaluation of the community aerosol dynamics model MAFOR v2.0 M. Karl et al. https://doi.org/10.5194/gmd-15-3969-2022
- Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion F. Mena et al. https://doi.org/10.5194/acp-17-9399-2017
- Exploring the aerosol activation properties in coastal shallow convection using cloud- and particle-resolving models G. Yu et al. https://doi.org/10.5194/acp-25-7527-2025
- Aerosol mixing state matters for particles deposition in human respiratory system J. Ching & M. Kajino https://doi.org/10.1038/s41598-018-27156-z
- The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations W. Tang et al. https://doi.org/10.5194/acp-26-9221-2026
- Using particle-resolved aerosol model simulations to guide the interpretations of cloud condensation nuclei experimental data P. Razafindrambinina et al. https://doi.org/10.1080/02786826.2023.2202741
- Detailed Microphysical Modeling of the Formation of Organic and Sulfuric Acid Coatings on Aircraft Emitted Soot Particles in the Near Field H. Wong et al. https://doi.org/10.1080/02786826.2014.953243
- Reduced light absorption of black carbon (BC) and its influence on BC-boundary-layer interactions during “APEC Blue” M. Gao et al. https://doi.org/10.5194/acp-21-11405-2021
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. https://doi.org/10.5194/acp-14-8255-2014
- Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling Z. Zheng et al. https://doi.org/10.1029/2020EA001500
- Emission factors of SO2, NOx and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling J. Beecken et al. https://doi.org/10.5194/acp-15-5229-2015
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. https://doi.org/10.5194/gmd-7-1137-2014
- Mixing State, Morphology, and Chemical Composition of Ship-Emitted Soot Revealed by UAV-Based Plume Observations S. Bie et al. https://doi.org/10.1021/acs.est.6c00632
- Metrics to quantify the importance of mixing state for CCN activity J. Ching et al. https://doi.org/10.5194/acp-17-7445-2017
- A single-column particle-resolved model for simulating the vertical distribution of aerosol mixing state: WRF-PartMC-MOSAIC-SCM v1.0 J. Curtis et al. https://doi.org/10.5194/gmd-10-4057-2017
- Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model Z. Zheng et al. https://doi.org/10.5194/acp-21-17727-2021
- Characterizing the Particle Composition and Cloud Condensation Nuclei from Shipping Emission in Western Europe C. Yu et al. https://doi.org/10.1021/acs.est.0c04039
- Retrieving the polarization information for satellite-to-ground light communication Q. Tao et al. https://doi.org/10.1088/2040-8978/17/8/085701
- Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes S. Ausmeel et al. https://doi.org/10.5194/amt-12-4479-2019
- The impacts of aerosol mixing state on heterogeneous N 2 O 5 hydrolysis Y. Liu et al. https://doi.org/10.1080/02786826.2024.2443587
- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. https://doi.org/10.1016/j.atmosenv.2022.119384
- Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008 M. Alvarado et al. https://doi.org/10.5194/acp-16-9435-2016
- Ship plumes in the Baltic Sea Sulfur Emission Control Area: chemical characterization and contribution to coastal aerosol concentrations S. Ausmeel et al. https://doi.org/10.5194/acp-20-9135-2020
- Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors M. Karl et al. https://doi.org/10.3390/ijerph17030777
- On the Ship Particle Number Emission Index: Size‐Resolved Microphysics and Key Controlling Parameters J. Mao et al. https://doi.org/10.1029/2020JD034427
- Effects of marine fuel sulfur restrictions on particle number concentrations and size distributions in ship plumes in the Baltic Sea S. Seppälä et al. https://doi.org/10.5194/acp-21-3215-2021
- Airborne survey of trace gases and aerosols over the Southern Baltic Sea: from clean marine boundary layer to shipping corridor effect M. Zanatta et al. https://doi.org/10.1080/16000889.2019.1695349
31 citations as recorded by crossref.
- Convergence of a generalized Weighted Flow Algorithm for stochastic particle coagulation L. DeVille et al. https://doi.org/10.3934/jcd.2019003
- Detection of ship plumes from residual fuel operation in emission control areas using single-particle mass spectrometry J. Passig et al. https://doi.org/10.5194/amt-14-4171-2021
- Simulating aerosol chamber experiments with the particle-resolved aerosol model PartMC J. Tian et al. https://doi.org/10.1080/02786826.2017.1311988
- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics M. Hughes et al. https://doi.org/10.3390/atmos9010015
- Description and evaluation of the community aerosol dynamics model MAFOR v2.0 M. Karl et al. https://doi.org/10.5194/gmd-15-3969-2022
- Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion F. Mena et al. https://doi.org/10.5194/acp-17-9399-2017
- Exploring the aerosol activation properties in coastal shallow convection using cloud- and particle-resolving models G. Yu et al. https://doi.org/10.5194/acp-25-7527-2025
- Aerosol mixing state matters for particles deposition in human respiratory system J. Ching & M. Kajino https://doi.org/10.1038/s41598-018-27156-z
- The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations W. Tang et al. https://doi.org/10.5194/acp-26-9221-2026
- Using particle-resolved aerosol model simulations to guide the interpretations of cloud condensation nuclei experimental data P. Razafindrambinina et al. https://doi.org/10.1080/02786826.2023.2202741
- Detailed Microphysical Modeling of the Formation of Organic and Sulfuric Acid Coatings on Aircraft Emitted Soot Particles in the Near Field H. Wong et al. https://doi.org/10.1080/02786826.2014.953243
- Reduced light absorption of black carbon (BC) and its influence on BC-boundary-layer interactions during “APEC Blue” M. Gao et al. https://doi.org/10.5194/acp-21-11405-2021
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. https://doi.org/10.5194/acp-14-8255-2014
- Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling Z. Zheng et al. https://doi.org/10.1029/2020EA001500
- Emission factors of SO2, NOx and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling J. Beecken et al. https://doi.org/10.5194/acp-15-5229-2015
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. https://doi.org/10.5194/gmd-7-1137-2014
- Mixing State, Morphology, and Chemical Composition of Ship-Emitted Soot Revealed by UAV-Based Plume Observations S. Bie et al. https://doi.org/10.1021/acs.est.6c00632
- Metrics to quantify the importance of mixing state for CCN activity J. Ching et al. https://doi.org/10.5194/acp-17-7445-2017
- A single-column particle-resolved model for simulating the vertical distribution of aerosol mixing state: WRF-PartMC-MOSAIC-SCM v1.0 J. Curtis et al. https://doi.org/10.5194/gmd-10-4057-2017
- Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model Z. Zheng et al. https://doi.org/10.5194/acp-21-17727-2021
- Characterizing the Particle Composition and Cloud Condensation Nuclei from Shipping Emission in Western Europe C. Yu et al. https://doi.org/10.1021/acs.est.0c04039
- Retrieving the polarization information for satellite-to-ground light communication Q. Tao et al. https://doi.org/10.1088/2040-8978/17/8/085701
- Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes S. Ausmeel et al. https://doi.org/10.5194/amt-12-4479-2019
- The impacts of aerosol mixing state on heterogeneous N 2 O 5 hydrolysis Y. Liu et al. https://doi.org/10.1080/02786826.2024.2443587
- Measurements and modelling of the three-dimensional near-field dispersion of particulate matter emitted from passenger ships in a port environment M. Haugen et al. https://doi.org/10.1016/j.atmosenv.2022.119384
- Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008 M. Alvarado et al. https://doi.org/10.5194/acp-16-9435-2016
- Ship plumes in the Baltic Sea Sulfur Emission Control Area: chemical characterization and contribution to coastal aerosol concentrations S. Ausmeel et al. https://doi.org/10.5194/acp-20-9135-2020
- Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors M. Karl et al. https://doi.org/10.3390/ijerph17030777
- On the Ship Particle Number Emission Index: Size‐Resolved Microphysics and Key Controlling Parameters J. Mao et al. https://doi.org/10.1029/2020JD034427
- Effects of marine fuel sulfur restrictions on particle number concentrations and size distributions in ship plumes in the Baltic Sea S. Seppälä et al. https://doi.org/10.5194/acp-21-3215-2021
- Airborne survey of trace gases and aerosols over the Southern Baltic Sea: from clean marine boundary layer to shipping corridor effect M. Zanatta et al. https://doi.org/10.1080/16000889.2019.1695349
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