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Atmospheric Chemistry and Physics
An interactive open-access journal of the European Geosciences Union
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- About
- Editorial board
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- Highlight articles
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IF 5.414
5.958CiteScore
9.7SNIP 1.517
SJR 2.601
index 191h5-index 89
Abstracted/indexed
Abstracted/indexed
Volume 14, issue 11
Atmos. Chem. Phys., 14, 5327–5347, 2014
https://doi.org/10.5194/acp-14-5327-2014
© Author(s) 2014. This work is distributed under
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.
Atmos. Chem. Phys., 14, 5327–5347, 2014
https://doi.org/10.5194/acp-14-5327-2014
© Author(s) 2014. This work is distributed under
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.
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 et al.
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Total article views: 1,828 (including HTML, PDF, and XML)
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Total article views: 1,443 (including HTML, PDF, and XML)
Cumulative views and downloads
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- EndNote: 2
Cited
20 citations as recorded by crossref.
- Metrics to quantify the importance of mixing state for CCN activity J. Ching et al. 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. 10.5194/gmd-10-4057-2017
- Simulating aerosol chamber experiments with the particle-resolved aerosol model PartMC J. Tian et al. 10.1080/02786826.2017.1311988
- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics M. Hughes et al. 10.3390/atmos9010015
- Retrieving the polarization information for satellite-to-ground light communication Q. Tao et al. 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. 10.5194/amt-12-4479-2019
- Quantification of black carbon mixing state from traffic: implications for aerosol optical properties M. Willis et al. 10.5194/acpd-15-33555-2015
- Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion F. Mena et al. 10.5194/acp-17-9399-2017
- Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008 M. Alvarado et al. 10.5194/acp-16-9435-2016
- Aerosol mixing state matters for particles deposition in human respiratory system J. Ching & M. Kajino 10.1038/s41598-018-27156-z
- 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. 10.1080/02786826.2014.953243
- Ship plumes in the Baltic Sea Sulfur Emission Control Area: chemical characterization and contribution to coastal aerosol concentrations S. Ausmeel et al. 10.5194/acp-20-9135-2020
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. 10.5194/acp-14-8255-2014
- Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors M. Karl et al. 10.3390/ijerph17030777
- Emission factors of SO<sub>2</sub>, NO<sub><i>x</i></sub> and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling J. Beecken et al. 10.5194/acp-15-5229-2015
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. 10.5194/gmd-7-1137-2014
- 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. 10.1080/16000889.2019.1695349
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. 10.5194/gmdd-7-691-2014
- Quantifying aerosol mixing state with entropy and diversity measures N. Riemer & M. West 10.5194/acp-13-11423-2013
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. 10.5194/acpd-14-8419-2014
17 citations as recorded by crossref.
- Metrics to quantify the importance of mixing state for CCN activity J. Ching et al. 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. 10.5194/gmd-10-4057-2017
- Simulating aerosol chamber experiments with the particle-resolved aerosol model PartMC J. Tian et al. 10.1080/02786826.2017.1311988
- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics M. Hughes et al. 10.3390/atmos9010015
- Retrieving the polarization information for satellite-to-ground light communication Q. Tao et al. 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. 10.5194/amt-12-4479-2019
- Quantification of black carbon mixing state from traffic: implications for aerosol optical properties M. Willis et al. 10.5194/acpd-15-33555-2015
- Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion F. Mena et al. 10.5194/acp-17-9399-2017
- Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008 M. Alvarado et al. 10.5194/acp-16-9435-2016
- Aerosol mixing state matters for particles deposition in human respiratory system J. Ching & M. Kajino 10.1038/s41598-018-27156-z
- 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. 10.1080/02786826.2014.953243
- Ship plumes in the Baltic Sea Sulfur Emission Control Area: chemical characterization and contribution to coastal aerosol concentrations S. Ausmeel et al. 10.5194/acp-20-9135-2020
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. 10.5194/acp-14-8255-2014
- Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors M. Karl et al. 10.3390/ijerph17030777
- Emission factors of SO<sub>2</sub>, NO<sub><i>x</i></sub> and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling J. Beecken et al. 10.5194/acp-15-5229-2015
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. 10.5194/gmd-7-1137-2014
- 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. 10.1080/16000889.2019.1695349
3 citations as recorded by crossref.
- The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test J. Kaiser et al. 10.5194/gmdd-7-691-2014
- Quantifying aerosol mixing state with entropy and diversity measures N. Riemer & M. West 10.5194/acp-13-11423-2013
- Contribution of ship traffic to aerosol particle concentrations downwind of a major shipping lane N. Kivekäs et al. 10.5194/acpd-14-8419-2014
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Latest update: 09 Aug 2020
Atmospheric Chemistry and Physics
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