Articles | Volume 17, issue 8
https://doi.org/10.5194/acp-17-4997-2017
© Author(s) 2017. 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-17-4997-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
18 Apr 2017
Research article |
| 18 Apr 2017
Impact of temperature dependence on the possible contribution of organics to new particle formation in the atmosphere
Atmospheric Sciences Research Center, State University of New York at Albany,
251 Fuller Road, Albany, New York 12203, USA
Atmospheric Sciences Research Center, State University of New York at Albany,
251 Fuller Road, Albany, New York 12203, USA
Alexey B. Nadykto
Atmospheric Sciences Research Center, State University of New York at Albany,
251 Fuller Road, Albany, New York 12203, USA
Department of Applied Mathematics, Moscow State University of
Technology “Stankin”, Vadkovsky 1, Moscow 127055, Russia
Jason Herb
Atmospheric Sciences Research Center, State University of New York at Albany,
251 Fuller Road, Albany, New York 12203, USA
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- Contributions of traffic emissions and new particle formation to the ultrafine particle size distribution in the megacity of Beijing H. Wu et al. 10.1016/j.atmosenv.2021.118652
- Inter-annual trends of ultrafine particles in urban Europe M. Garcia-Marlès et al. 10.1016/j.envint.2024.108510
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- Improving new particle formation simulation by coupling a volatility-basis set (VBS) organic aerosol module in NAQPMS+APM X. Chen et al. 10.1016/j.atmosenv.2019.01.053
- Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations S. Lin et al. 10.1016/j.envpol.2022.119795
- High concentration of ultrafine particles in the Amazon free troposphere produced by organic new particle formation B. Zhao et al. 10.1073/pnas.2006716117
- Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models F. Yu et al. 10.1029/2022GL098551
- High occurrence of new particle formation events at the Maïdo high-altitude observatory (2150 m), Réunion (Indian Ocean) B. Foucart et al. 10.5194/acp-18-9243-2018
- Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements A. Nair & F. Yu 10.5194/acp-20-12853-2020
- Environmental exposure disparities in ultrafine particles and PM2.5 by urbanicity and socio-demographics in New York state, 2013–2020 A. Nair et al. 10.1016/j.envres.2023.117246
- The potential mechanism of atmospheric new particle formation involving amino acids with multiple functional groups J. Liu et al. 10.1039/D0CP06472F
- Look Up: Probing the Vertical Profile of New Particle Formation and Growth in the Planetary Boundary Layer With Models and Observations S. O’Donnell et al. 10.1029/2022JD037525
- Comprehensive simulations of new particle formation events in Beijing with a cluster dynamics–multicomponent sectional model C. Li et al. 10.5194/acp-23-6879-2023
- Causes and importance of new particle formation in the present‐day and preindustrial atmospheres H. Gordon et al. 10.1002/2017JD026844
22 citations as recorded by crossref.
- Aerosol characteristics and particle production in the upper troposphere over the Amazon Basin M. Andreae et al. 10.5194/acp-18-921-2018
- The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States A. Nair et al. 10.1016/j.scitotenv.2022.160756
- The role of highly oxygenated organic molecules in the Boreal aerosol-cloud-climate system P. Roldin et al. 10.1038/s41467-019-12338-8
- Strong particle production and condensational growth in the upper troposphere sustained by biogenic VOCs from the canopy of the Amazon Basin Y. Liu et al. 10.5194/acp-23-251-2023
- Contribution of regional aerosol nucleation to low-level CCN in an Amazonian deep convective environment: results from a regionally nested global model X. Wang et al. 10.5194/acp-23-4431-2023
- New Particle Formation in the Atmosphere: From Molecular Clusters to Global Climate S. Lee et al. 10.1029/2018JD029356
- Influence of atmospheric conditions on sulfuric acid-dimethylamine-ammonia-based new particle formation H. Li et al. 10.1016/j.chemosphere.2019.125554
- Constraining nucleation, condensation, and chemistry in oxidation flow reactors using size-distribution measurements and aerosol microphysical modeling A. Hodshire et al. 10.5194/acp-18-12433-2018
- Wintertime new particle formation and its contribution to cloud condensation nuclei in the Northeastern United States F. Yu et al. 10.5194/acp-20-2591-2020
- Contributions of traffic emissions and new particle formation to the ultrafine particle size distribution in the megacity of Beijing H. Wu et al. 10.1016/j.atmosenv.2021.118652
- Inter-annual trends of ultrafine particles in urban Europe M. Garcia-Marlès et al. 10.1016/j.envint.2024.108510
- The potential role of organics in new particle formation and initial growth in the remote tropical upper troposphere A. Kupc et al. 10.5194/acp-20-15037-2020
- Improving new particle formation simulation by coupling a volatility-basis set (VBS) organic aerosol module in NAQPMS+APM X. Chen et al. 10.1016/j.atmosenv.2019.01.053
- Particle surface area, ultrafine particle number concentration, and cardiovascular hospitalizations S. Lin et al. 10.1016/j.envpol.2022.119795
- High concentration of ultrafine particles in the Amazon free troposphere produced by organic new particle formation B. Zhao et al. 10.1073/pnas.2006716117
- Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models F. Yu et al. 10.1029/2022GL098551
- High occurrence of new particle formation events at the Maïdo high-altitude observatory (2150 m), Réunion (Indian Ocean) B. Foucart et al. 10.5194/acp-18-9243-2018
- Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements A. Nair & F. Yu 10.5194/acp-20-12853-2020
- Environmental exposure disparities in ultrafine particles and PM2.5 by urbanicity and socio-demographics in New York state, 2013–2020 A. Nair et al. 10.1016/j.envres.2023.117246
- The potential mechanism of atmospheric new particle formation involving amino acids with multiple functional groups J. Liu et al. 10.1039/D0CP06472F
- Look Up: Probing the Vertical Profile of New Particle Formation and Growth in the Planetary Boundary Layer With Models and Observations S. O’Donnell et al. 10.1029/2022JD037525
- Comprehensive simulations of new particle formation events in Beijing with a cluster dynamics–multicomponent sectional model C. Li et al. 10.5194/acp-23-6879-2023
1 citations as recorded by crossref.
Latest update: 18 Apr 2024
Short summary
H2SO4–organics clustering thermodynamics from quantum studies has been employed to develop a scheme to include temperature dependence in an H2SO4–organics nucleation parameterization. We show that temperature has a strong impact on nucleation rates, particle number concentrations, and aerosol first indirect radiative forcing in summer. To our knowledge, the study represents the first attempt to study the temperature effect on organics-mediated nucleation in the global atmosphere.
H2SO4–organics clustering thermodynamics from quantum studies has been employed to develop a...
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