Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2663-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2663-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
17 Jun 2020
Development and technical paper |
| 17 Jun 2020
| 17 Jun 2020
H2SO4–H2O binary and H2SO4–H2O–NH3 ternary homogeneous and ion-mediated nucleation: lookup tables version 1.0 for 3-D modeling application
Atmospheric Sciences Research Center, University at Albany, Albany,
New York, USA
Alexey B. Nadykto
Atmospheric Sciences Research Center, University at Albany, Albany,
New York, USA
Department of Applied Mathematics, Moscow State University of
Technology (STANKIN), Moscow, Russia
National Research Nuclear University MEPhI (Moscow Engineering
Physics Institute), Department of General Physics, Moscow, Russia
Atmospheric Sciences Research Center, University at Albany, Albany,
New York, USA
Jason Herb
Atmospheric Sciences Research Center, University at Albany, Albany,
New York, USA
Related authors
Naveed Ahmad, Changqing Lin, Alexis K. H. Lau, Jhoon Kim, Tianshu Zhang, Fangqun Yu, Chengcai Li, Ying Li, Jimmy C. H. Fung, and Xiang Qian Lao
Atmos. Chem. Phys., 24, 9645–9665, https://doi.org/10.5194/acp-24-9645-2024, https://doi.org/10.5194/acp-24-9645-2024, 2024
Short summary
Short summary
This study developed a nested machine learning model to convert the GEMS NO2 column measurements into ground-level concentrations across China. The model directly incorporates the NO2 mixing height (NMH) into the methodological framework. The study underscores the importance of considering NMH when estimating ground-level NO2 from satellite column measurements and highlights the significant advantages of new-generation geostationary satellites in air quality monitoring.
Huiyun Du, Jie Li, Xueshun Chen, Gabriele Curci, Fangqun Yu, Yele Sun, Xu Dao, Song Guo, Zhe Wang, Wenyi Yang, Lianfang Wei, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1432, https://doi.org/10.5194/egusphere-2024-1432, 2024
Short summary
Short summary
Inadequate consideration of mixing state and coatings on BC hinders aerosol radiation forcing quantification. While core-shell mixing results match observations closely, partial internal mixing and coating are more realistic. The fraction of embedded BC and coating aerosols resolved by a microphysics module were used to constrain the mixing state. This led to a 30~43 % absorption enhancement decrease over Northern China, offering valuable insights for the assessment of BC's radiative effects.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Jason L. Tackett, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1127, https://doi.org/10.5194/egusphere-2024-1127, 2024
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosols over the western North Atlantic Ocean (WNAO) during the winter and summer campaigns of ACTIVATE 2020. Model results are evaluated against in situ and remote sensing measurements from two aircraft as well as ground-based and satellite observations. The improved understanding of the aerosol life cycle, composition, transport pathways, and distribution has important implications for characterizing aerosol-cloud-meteorology interactions over the WNAO.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
Short summary
Short summary
Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Kun Wang, Xiaoyan Ma, Rong Tian, and Fangqun Yu
Atmos. Chem. Phys., 23, 4091–4104, https://doi.org/10.5194/acp-23-4091-2023, https://doi.org/10.5194/acp-23-4091-2023, 2023
Short summary
Short summary
From 12 March to 6 April 2016 in Beijing, there were 11 typical new particle formation days, 13 non-event days, and 2 undefined days. We first analyzed the favorable background of new particle formation in Beijing and then conducted the simulations using four nucleation schemes based on a global chemistry transport model (GEOS-Chem) to understand the nucleation mechanism.
Fangqun Yu, Gan Luo, Arshad Arjunan Nair, Sebastian Eastham, Christina J. Williamson, Agnieszka Kupc, and Charles A. Brock
Atmos. Chem. Phys., 23, 1863–1877, https://doi.org/10.5194/acp-23-1863-2023, https://doi.org/10.5194/acp-23-1863-2023, 2023
Short summary
Short summary
Particle number concentrations and size distributions in the stratosphere are studied through model simulations and comparisons with measurements. The nucleation scheme used in most of the solar geoengineering modeling studies overpredicts the nucleation rates and particle number concentrations in the stratosphere. The model based on updated nucleation schemes captures reasonably well some aspects of particle size distributions but misses some features. The possible reasons are discussed.
Noah S. Hirshorn, Lauren M. Zuromski, Christopher Rapp, Ian McCubbin, Gerardo Carrillo-Cardenas, Fangqun Yu, and A. Gannet Hallar
Atmos. Chem. Phys., 22, 15909–15924, https://doi.org/10.5194/acp-22-15909-2022, https://doi.org/10.5194/acp-22-15909-2022, 2022
Short summary
Short summary
New particle formation (NPF) is a source of atmospheric aerosol number concentration that can impact climate by growing to larger sizes and under proper conditions form cloud condensation nuclei (CCN). Using novel methods, we find that at Storm Peak Laboratory, a remote, mountaintop site in Colorado, NPF is observed to enhance CCN concentrations in the spring by a factor of 1.54 and in the winter by a factor of 1.36 which can occur on a regional scale having important climate implications.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Yanda Zhang, Fangqun Yu, Gan Luo, Jiwen Fan, and Shuai Liu
Atmos. Chem. Phys., 21, 17433–17451, https://doi.org/10.5194/acp-21-17433-2021, https://doi.org/10.5194/acp-21-17433-2021, 2021
Short summary
Short summary
This paper explores the impacts of dust on summertime convective cloud and precipitation through a numerical experiment. The result indicates that the long-range-transported dust can notably affect the properties of convective cloud and precipitation by enhancing immersion freezing and invigorating convection. We also analyze the different dust effects predicted by the Morrison and SBM schemes, which are partially attributed to the saturation adjustment approach utilized in the bulk schemes.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Gongda Lu, Eloise A. Marais, Tuan V. Vu, Jingsha Xu, Zongbo Shi, James D. Lee, Qiang Zhang, Lu Shen, Gan Luo, and Fangqun Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-428, https://doi.org/10.5194/acp-2021-428, 2021
Revised manuscript not accepted
Short summary
Short summary
Emission controls were imposed in Beijing-Tianjin-Hebei in northern China in autumn-winter 2017. We find that regional PM2.5 targets (15 % decrease relative to previous year) were exceeded. Our analysis shows that decline in precursor emissions only leads to less than half (43 %) the improved air quality. Most of the change (57 %) is due to interannual variability in meteorology. Stricter emission controls may be necessary in years with unfavourable meteorology.
Xueshun Chen, Fangqun Yu, Wenyi Yang, Yele Sun, Huansheng Chen, Wei Du, Jian Zhao, Ying Wei, Lianfang Wei, Huiyun Du, Zhe Wang, Qizhong Wu, Jie Li, Junling An, and Zifa Wang
Atmos. Chem. Phys., 21, 9343–9366, https://doi.org/10.5194/acp-21-9343-2021, https://doi.org/10.5194/acp-21-9343-2021, 2021
Short summary
Short summary
Atmospheric aerosol particles have significant climate and health effects that depend on aerosol size, composition, and mixing state. A new global-regional nested aerosol model with an advanced particle microphysics module and a volatility basis set organic aerosol module was developed to simulate aerosol microphysical processes. Simulations strongly suggest the important role of anthropogenic organic species in particle formation over the areas influenced by anthropogenic sources.
Xiaojing Shen, Junying Sun, Fangqun Yu, Ying Wang, Junting Zhong, Yangmei Zhang, Xinyao Hu, Can Xia, Sinan Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 7039–7052, https://doi.org/10.5194/acp-21-7039-2021, https://doi.org/10.5194/acp-21-7039-2021, 2021
Short summary
Short summary
In this work, we revealed the changes of PNSD and NPF events during the COVID-19 lockdown period in Beijing, China, to illustrate the impact of reduced primary emission and elavated atmospheric oxidized capicity on the nucleation and growth processes. The subsequent growth of nucleated particles and their contribution to the aerosol pollution formation were also explored, to highlight the necessity of controlling the nanoparticles in the future air quality management.
Ling Liu, Fangqun Yu, Kaipeng Tu, Zhi Yang, and Xiuhui Zhang
Atmos. Chem. Phys., 21, 6221–6230, https://doi.org/10.5194/acp-21-6221-2021, https://doi.org/10.5194/acp-21-6221-2021, 2021
Short summary
Short summary
Trifluoroacetic acid (TFA) was previously proved to participate in sulfuric acid (SA)–dimethylamine (DMA) nucleation in Shanghai, China. However, complex atmospheric environments can influence the nucleation of aerosol significantly. We show the influence of different atmospheric conditions on the SA-DMA-TFA nucleation and find the enhancement by TFA can be significant in cold and polluted areas, which provides the perspective of the realistic role of TFA in different atmospheric environments.
Arshad Arjunan Nair and Fangqun Yu
Atmos. Chem. Phys., 20, 12853–12869, https://doi.org/10.5194/acp-20-12853-2020, https://doi.org/10.5194/acp-20-12853-2020, 2020
Short summary
Short summary
Small particles in the atmosphere can affect cloud formation and properties and thus Earth's energy budget. These cloud condensation nuclei (CCN) contribute the largest uncertainties in climate change modeling. To reduce these uncertainties, it is important to quantify CCN numbers accurately, measurements of which are sparse. We propose and evaluate a machine learning method to estimate CCN, in the absence of their direct measurements, using more common measurements of weather and air quality.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
Short summary
Short summary
Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Gan Luo, Fangqun Yu, and Jonathan M. Moch
Geosci. Model Dev., 13, 2879–2903, https://doi.org/10.5194/gmd-13-2879-2020, https://doi.org/10.5194/gmd-13-2879-2020, 2020
Short summary
Short summary
This work improved pH calculation for cloud, rain, and wet surfaces, fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of cloud, empirical washout by rain and snow, and wet surface uptake in GEOS-Chem v12.6.0. We compared simulated mass concentrations of aerosol precursors and aerosols with surface monitoring networks, Arctic sites, and ATom observations, and showed that the model results with the updated wet processes agree better for most species.
Fangqun Yu, Gan Luo, Arshad Arjunan Nair, James J. Schwab, James P. Sherman, and Yanda Zhang
Atmos. Chem. Phys., 20, 2591–2601, https://doi.org/10.5194/acp-20-2591-2020, https://doi.org/10.5194/acp-20-2591-2020, 2020
Short summary
Short summary
Particle number concentration (PNC) is a key parameter important for the health and climate impacts of atmospheric aerosols. We show that, even during wintertime, regional nucleation occurs and contributes significantly to number concentrations of ultrafine particles and cloud condensation nuclei. Due to low biogenic emissions, wintertime regional nucleation is solely controlled by inorganic species, and ternary ion-mediated nucleation is able to capture the observed variations in PNC.
Xiaoyan Ma, Hailing Jia, Rong Tian, Fangqun Yu, and Jiagnan Li
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-54, https://doi.org/10.5194/acp-2020-54, 2020
Preprint withdrawn
Short summary
Short summary
BC Mixing state, is one of critical microphysical properties to modulate optical properties, radiative forcing (RF), and climatic effect. However, it has been simply assumed previously as either external or internal mixing. In this study, by employing a nested GEOS-Chem-APM with predicted BC mixing state, we examined the effect of mixing state on aerosol optical properties, RF, and heating rate over East Asia. This will improve the predictions of aerosol climatic effect in the future.
Gan Luo, Fangqun Yu, and James Schwab
Geosci. Model Dev., 12, 3439–3447, https://doi.org/10.5194/gmd-12-3439-2019, https://doi.org/10.5194/gmd-12-3439-2019, 2019
Short summary
Short summary
GEOS-Chem 12.0.0 has been recognized to significantly overestimate the concentrations of gaseous nitric acid, aerosol nitrate, and aerosol ammonium over the United States. In this study, we show that most or all of the overestimation issue appears to be associated with wet scavenging processes. With the updated wet scavenging scheme in this work, we successfully improve the skill of the model in predicting the three species concentrations, which are important for air quality and climate studies.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
Short summary
Short summary
Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Fangqun Yu, Alexey B. Nadykto, Jason Herb, Gan Luo, Kirill M. Nazarenko, and Lyudmila A. Uvarova
Atmos. Chem. Phys., 18, 17451–17474, https://doi.org/10.5194/acp-18-17451-2018, https://doi.org/10.5194/acp-18-17451-2018, 2018
Short summary
Short summary
Aerosol nucleation exerts important influences on the climate, hydrological cycle, and air quality. We have developed an advanced physical–chemical model that describes ion-induced and neutral nucleation involving ammonia, sulfuric acid, and water vapors. The model is shown to reproduce laboratory measurements taken under a wide range of conditions, offers physiochemical insights into the ternary nucleation process, and provides an accurate approach to calculate ternary rate in the atmosphere.
Jingbo Mao, Fangqun Yu, Yan Zhang, Jingyu An, Lin Wang, Jun Zheng, Lei Yao, Gan Luo, Weichun Ma, Qi Yu, Cheng Huang, Li Li, and Limin Chen
Atmos. Chem. Phys., 18, 7933–7950, https://doi.org/10.5194/acp-18-7933-2018, https://doi.org/10.5194/acp-18-7933-2018, 2018
Short summary
Short summary
A few pptv of gaseous amines have been observed to affect particle nucleation and growth, and it is necessary to understand the sources and concentrations of atmospheric amines. This study presents the source-dependent amines to ammonia emission ratios and simulates methylamines concentrations in a polluted region in China with WRF-Chem. The performance of simulations based on source-dependent ratios is much better than those based on fixed ratios that have been assumed in all previous studies.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
Short summary
Short summary
The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Fangqun Yu, Gan Luo, Alexey B. Nadykto, and Jason Herb
Atmos. Chem. Phys., 17, 4997–5005, https://doi.org/10.5194/acp-17-4997-2017, https://doi.org/10.5194/acp-17-4997-2017, 2017
Short summary
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.
F. Yu, G. Luo, S. C. Pryor, P. R. Pillai, S. H. Lee, J. Ortega, J. J. Schwab, A. G. Hallar, W. R. Leaitch, V. P. Aneja, J. N. Smith, J. T. Walker, O. Hogrefe, and K. L. Demerjian
Atmos. Chem. Phys., 15, 13993–14003, https://doi.org/10.5194/acp-15-13993-2015, https://doi.org/10.5194/acp-15-13993-2015, 2015
Short summary
Short summary
The role of low-volatility organics in new particle formation (NPF) in the atmosphere is assessed. An empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics significantly overpredicts NPF in the summer.
Two different schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America.
F. Yu and G. Luo
Atmos. Chem. Phys., 14, 12455–12464, https://doi.org/10.5194/acp-14-12455-2014, https://doi.org/10.5194/acp-14-12455-2014, 2014
Short summary
Short summary
Global lifetimes and concentrations of gaseous methylamines (MMA, DMA, and TMA) have been simulated.
Oxidation and aerosol uptakes are dominant sinks for these methylamines. The oxidation alone leads to their lifetimes of 5-10h in most parts of low and middle latitude regions. The uptake by secondary species can shorten their lifetime to as low as 1-2h over central Europe, eastern Asia, and the eastern US.
The modeled concentrations are substantially lower than observed values available.
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
X. Ma, K. Bartlett, K. Harmon, and F. Yu
Atmos. Meas. Tech., 6, 2391–2401, https://doi.org/10.5194/amt-6-2391-2013, https://doi.org/10.5194/amt-6-2391-2013, 2013
Naveed Ahmad, Changqing Lin, Alexis K. H. Lau, Jhoon Kim, Tianshu Zhang, Fangqun Yu, Chengcai Li, Ying Li, Jimmy C. H. Fung, and Xiang Qian Lao
Atmos. Chem. Phys., 24, 9645–9665, https://doi.org/10.5194/acp-24-9645-2024, https://doi.org/10.5194/acp-24-9645-2024, 2024
Short summary
Short summary
This study developed a nested machine learning model to convert the GEMS NO2 column measurements into ground-level concentrations across China. The model directly incorporates the NO2 mixing height (NMH) into the methodological framework. The study underscores the importance of considering NMH when estimating ground-level NO2 from satellite column measurements and highlights the significant advantages of new-generation geostationary satellites in air quality monitoring.
Huiyun Du, Jie Li, Xueshun Chen, Gabriele Curci, Fangqun Yu, Yele Sun, Xu Dao, Song Guo, Zhe Wang, Wenyi Yang, Lianfang Wei, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1432, https://doi.org/10.5194/egusphere-2024-1432, 2024
Short summary
Short summary
Inadequate consideration of mixing state and coatings on BC hinders aerosol radiation forcing quantification. While core-shell mixing results match observations closely, partial internal mixing and coating are more realistic. The fraction of embedded BC and coating aerosols resolved by a microphysics module were used to constrain the mixing state. This led to a 30~43 % absorption enhancement decrease over Northern China, offering valuable insights for the assessment of BC's radiative effects.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Jason L. Tackett, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1127, https://doi.org/10.5194/egusphere-2024-1127, 2024
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosols over the western North Atlantic Ocean (WNAO) during the winter and summer campaigns of ACTIVATE 2020. Model results are evaluated against in situ and remote sensing measurements from two aircraft as well as ground-based and satellite observations. The improved understanding of the aerosol life cycle, composition, transport pathways, and distribution has important implications for characterizing aerosol-cloud-meteorology interactions over the WNAO.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
Short summary
Short summary
Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Jun-Wei Xu, Jintai Lin, Gan Luo, Jamiu Adeniran, and Hao Kong
Atmos. Chem. Phys., 23, 4149–4163, https://doi.org/10.5194/acp-23-4149-2023, https://doi.org/10.5194/acp-23-4149-2023, 2023
Short summary
Short summary
Research on the sources of Chinese PM2.5 pollution has focused on the contributions of China’s domestic emissions. However, the impact of foreign anthropogenic emissions has typically been simplified or neglected. Here we find that foreign anthropogenic emissions play an important role in Chinese PM2.5 pollution through chemical interactions between foreign-transported pollutants and China’s local emissions. Thus, foreign emission reductions are essential for improving Chinese air quality.
Kun Wang, Xiaoyan Ma, Rong Tian, and Fangqun Yu
Atmos. Chem. Phys., 23, 4091–4104, https://doi.org/10.5194/acp-23-4091-2023, https://doi.org/10.5194/acp-23-4091-2023, 2023
Short summary
Short summary
From 12 March to 6 April 2016 in Beijing, there were 11 typical new particle formation days, 13 non-event days, and 2 undefined days. We first analyzed the favorable background of new particle formation in Beijing and then conducted the simulations using four nucleation schemes based on a global chemistry transport model (GEOS-Chem) to understand the nucleation mechanism.
Fangqun Yu, Gan Luo, Arshad Arjunan Nair, Sebastian Eastham, Christina J. Williamson, Agnieszka Kupc, and Charles A. Brock
Atmos. Chem. Phys., 23, 1863–1877, https://doi.org/10.5194/acp-23-1863-2023, https://doi.org/10.5194/acp-23-1863-2023, 2023
Short summary
Short summary
Particle number concentrations and size distributions in the stratosphere are studied through model simulations and comparisons with measurements. The nucleation scheme used in most of the solar geoengineering modeling studies overpredicts the nucleation rates and particle number concentrations in the stratosphere. The model based on updated nucleation schemes captures reasonably well some aspects of particle size distributions but misses some features. The possible reasons are discussed.
Noah S. Hirshorn, Lauren M. Zuromski, Christopher Rapp, Ian McCubbin, Gerardo Carrillo-Cardenas, Fangqun Yu, and A. Gannet Hallar
Atmos. Chem. Phys., 22, 15909–15924, https://doi.org/10.5194/acp-22-15909-2022, https://doi.org/10.5194/acp-22-15909-2022, 2022
Short summary
Short summary
New particle formation (NPF) is a source of atmospheric aerosol number concentration that can impact climate by growing to larger sizes and under proper conditions form cloud condensation nuclei (CCN). Using novel methods, we find that at Storm Peak Laboratory, a remote, mountaintop site in Colorado, NPF is observed to enhance CCN concentrations in the spring by a factor of 1.54 and in the winter by a factor of 1.36 which can occur on a regional scale having important climate implications.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Yanda Zhang, Fangqun Yu, Gan Luo, Jiwen Fan, and Shuai Liu
Atmos. Chem. Phys., 21, 17433–17451, https://doi.org/10.5194/acp-21-17433-2021, https://doi.org/10.5194/acp-21-17433-2021, 2021
Short summary
Short summary
This paper explores the impacts of dust on summertime convective cloud and precipitation through a numerical experiment. The result indicates that the long-range-transported dust can notably affect the properties of convective cloud and precipitation by enhancing immersion freezing and invigorating convection. We also analyze the different dust effects predicted by the Morrison and SBM schemes, which are partially attributed to the saturation adjustment approach utilized in the bulk schemes.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Gongda Lu, Eloise A. Marais, Tuan V. Vu, Jingsha Xu, Zongbo Shi, James D. Lee, Qiang Zhang, Lu Shen, Gan Luo, and Fangqun Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-428, https://doi.org/10.5194/acp-2021-428, 2021
Revised manuscript not accepted
Short summary
Short summary
Emission controls were imposed in Beijing-Tianjin-Hebei in northern China in autumn-winter 2017. We find that regional PM2.5 targets (15 % decrease relative to previous year) were exceeded. Our analysis shows that decline in precursor emissions only leads to less than half (43 %) the improved air quality. Most of the change (57 %) is due to interannual variability in meteorology. Stricter emission controls may be necessary in years with unfavourable meteorology.
Xueshun Chen, Fangqun Yu, Wenyi Yang, Yele Sun, Huansheng Chen, Wei Du, Jian Zhao, Ying Wei, Lianfang Wei, Huiyun Du, Zhe Wang, Qizhong Wu, Jie Li, Junling An, and Zifa Wang
Atmos. Chem. Phys., 21, 9343–9366, https://doi.org/10.5194/acp-21-9343-2021, https://doi.org/10.5194/acp-21-9343-2021, 2021
Short summary
Short summary
Atmospheric aerosol particles have significant climate and health effects that depend on aerosol size, composition, and mixing state. A new global-regional nested aerosol model with an advanced particle microphysics module and a volatility basis set organic aerosol module was developed to simulate aerosol microphysical processes. Simulations strongly suggest the important role of anthropogenic organic species in particle formation over the areas influenced by anthropogenic sources.
Xiaojing Shen, Junying Sun, Fangqun Yu, Ying Wang, Junting Zhong, Yangmei Zhang, Xinyao Hu, Can Xia, Sinan Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 21, 7039–7052, https://doi.org/10.5194/acp-21-7039-2021, https://doi.org/10.5194/acp-21-7039-2021, 2021
Short summary
Short summary
In this work, we revealed the changes of PNSD and NPF events during the COVID-19 lockdown period in Beijing, China, to illustrate the impact of reduced primary emission and elavated atmospheric oxidized capicity on the nucleation and growth processes. The subsequent growth of nucleated particles and their contribution to the aerosol pollution formation were also explored, to highlight the necessity of controlling the nanoparticles in the future air quality management.
Ling Liu, Fangqun Yu, Kaipeng Tu, Zhi Yang, and Xiuhui Zhang
Atmos. Chem. Phys., 21, 6221–6230, https://doi.org/10.5194/acp-21-6221-2021, https://doi.org/10.5194/acp-21-6221-2021, 2021
Short summary
Short summary
Trifluoroacetic acid (TFA) was previously proved to participate in sulfuric acid (SA)–dimethylamine (DMA) nucleation in Shanghai, China. However, complex atmospheric environments can influence the nucleation of aerosol significantly. We show the influence of different atmospheric conditions on the SA-DMA-TFA nucleation and find the enhancement by TFA can be significant in cold and polluted areas, which provides the perspective of the realistic role of TFA in different atmospheric environments.
Arshad Arjunan Nair and Fangqun Yu
Atmos. Chem. Phys., 20, 12853–12869, https://doi.org/10.5194/acp-20-12853-2020, https://doi.org/10.5194/acp-20-12853-2020, 2020
Short summary
Short summary
Small particles in the atmosphere can affect cloud formation and properties and thus Earth's energy budget. These cloud condensation nuclei (CCN) contribute the largest uncertainties in climate change modeling. To reduce these uncertainties, it is important to quantify CCN numbers accurately, measurements of which are sparse. We propose and evaluate a machine learning method to estimate CCN, in the absence of their direct measurements, using more common measurements of weather and air quality.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
Short summary
Short summary
Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Gan Luo, Fangqun Yu, and Jonathan M. Moch
Geosci. Model Dev., 13, 2879–2903, https://doi.org/10.5194/gmd-13-2879-2020, https://doi.org/10.5194/gmd-13-2879-2020, 2020
Short summary
Short summary
This work improved pH calculation for cloud, rain, and wet surfaces, fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of cloud, empirical washout by rain and snow, and wet surface uptake in GEOS-Chem v12.6.0. We compared simulated mass concentrations of aerosol precursors and aerosols with surface monitoring networks, Arctic sites, and ATom observations, and showed that the model results with the updated wet processes agree better for most species.
Fangqun Yu, Gan Luo, Arshad Arjunan Nair, James J. Schwab, James P. Sherman, and Yanda Zhang
Atmos. Chem. Phys., 20, 2591–2601, https://doi.org/10.5194/acp-20-2591-2020, https://doi.org/10.5194/acp-20-2591-2020, 2020
Short summary
Short summary
Particle number concentration (PNC) is a key parameter important for the health and climate impacts of atmospheric aerosols. We show that, even during wintertime, regional nucleation occurs and contributes significantly to number concentrations of ultrafine particles and cloud condensation nuclei. Due to low biogenic emissions, wintertime regional nucleation is solely controlled by inorganic species, and ternary ion-mediated nucleation is able to capture the observed variations in PNC.
Xiaoyan Ma, Hailing Jia, Rong Tian, Fangqun Yu, and Jiagnan Li
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-54, https://doi.org/10.5194/acp-2020-54, 2020
Preprint withdrawn
Short summary
Short summary
BC Mixing state, is one of critical microphysical properties to modulate optical properties, radiative forcing (RF), and climatic effect. However, it has been simply assumed previously as either external or internal mixing. In this study, by employing a nested GEOS-Chem-APM with predicted BC mixing state, we examined the effect of mixing state on aerosol optical properties, RF, and heating rate over East Asia. This will improve the predictions of aerosol climatic effect in the future.
Gan Luo, Fangqun Yu, and James Schwab
Geosci. Model Dev., 12, 3439–3447, https://doi.org/10.5194/gmd-12-3439-2019, https://doi.org/10.5194/gmd-12-3439-2019, 2019
Short summary
Short summary
GEOS-Chem 12.0.0 has been recognized to significantly overestimate the concentrations of gaseous nitric acid, aerosol nitrate, and aerosol ammonium over the United States. In this study, we show that most or all of the overestimation issue appears to be associated with wet scavenging processes. With the updated wet scavenging scheme in this work, we successfully improve the skill of the model in predicting the three species concentrations, which are important for air quality and climate studies.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
Short summary
Short summary
Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Fangqun Yu, Alexey B. Nadykto, Jason Herb, Gan Luo, Kirill M. Nazarenko, and Lyudmila A. Uvarova
Atmos. Chem. Phys., 18, 17451–17474, https://doi.org/10.5194/acp-18-17451-2018, https://doi.org/10.5194/acp-18-17451-2018, 2018
Short summary
Short summary
Aerosol nucleation exerts important influences on the climate, hydrological cycle, and air quality. We have developed an advanced physical–chemical model that describes ion-induced and neutral nucleation involving ammonia, sulfuric acid, and water vapors. The model is shown to reproduce laboratory measurements taken under a wide range of conditions, offers physiochemical insights into the ternary nucleation process, and provides an accurate approach to calculate ternary rate in the atmosphere.
Jingbo Mao, Fangqun Yu, Yan Zhang, Jingyu An, Lin Wang, Jun Zheng, Lei Yao, Gan Luo, Weichun Ma, Qi Yu, Cheng Huang, Li Li, and Limin Chen
Atmos. Chem. Phys., 18, 7933–7950, https://doi.org/10.5194/acp-18-7933-2018, https://doi.org/10.5194/acp-18-7933-2018, 2018
Short summary
Short summary
A few pptv of gaseous amines have been observed to affect particle nucleation and growth, and it is necessary to understand the sources and concentrations of atmospheric amines. This study presents the source-dependent amines to ammonia emission ratios and simulates methylamines concentrations in a polluted region in China with WRF-Chem. The performance of simulations based on source-dependent ratios is much better than those based on fixed ratios that have been assumed in all previous studies.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
Short summary
Short summary
The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Fangqun Yu, Gan Luo, Alexey B. Nadykto, and Jason Herb
Atmos. Chem. Phys., 17, 4997–5005, https://doi.org/10.5194/acp-17-4997-2017, https://doi.org/10.5194/acp-17-4997-2017, 2017
Short summary
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.
F. Yu, G. Luo, S. C. Pryor, P. R. Pillai, S. H. Lee, J. Ortega, J. J. Schwab, A. G. Hallar, W. R. Leaitch, V. P. Aneja, J. N. Smith, J. T. Walker, O. Hogrefe, and K. L. Demerjian
Atmos. Chem. Phys., 15, 13993–14003, https://doi.org/10.5194/acp-15-13993-2015, https://doi.org/10.5194/acp-15-13993-2015, 2015
Short summary
Short summary
The role of low-volatility organics in new particle formation (NPF) in the atmosphere is assessed. An empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics significantly overpredicts NPF in the summer.
Two different schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America.
F. Yu and G. Luo
Atmos. Chem. Phys., 14, 12455–12464, https://doi.org/10.5194/acp-14-12455-2014, https://doi.org/10.5194/acp-14-12455-2014, 2014
Short summary
Short summary
Global lifetimes and concentrations of gaseous methylamines (MMA, DMA, and TMA) have been simulated.
Oxidation and aerosol uptakes are dominant sinks for these methylamines. The oxidation alone leads to their lifetimes of 5-10h in most parts of low and middle latitude regions. The uptake by secondary species can shorten their lifetime to as low as 1-2h over central Europe, eastern Asia, and the eastern US.
The modeled concentrations are substantially lower than observed values available.
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
X. Ma, K. Bartlett, K. Harmon, and F. Yu
Atmos. Meas. Tech., 6, 2391–2401, https://doi.org/10.5194/amt-6-2391-2013, https://doi.org/10.5194/amt-6-2391-2013, 2013
Related subject area
Atmospheric sciences
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
Short summary
Short summary
Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
Short summary
Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
Short summary
Short summary
Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
Short summary
Short summary
Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
Short summary
Short summary
Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
Short summary
Short summary
Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Cited articles
Coffman, D. J. and Hegg, D. A.: A preliminary study of the effect of
ammonia on particle nucleation in the marine boundary layer, J. Geophys.
Res., 100, 7147–7160, 1995.
Doyle, G. J.: Self-nucleation in the sulfuric acid-water system, J. Chem.
Phys., 35, 795–799, 1961.
Dunne, E. M., Gordon, H., Kürten, A., Almeida, J., Duplissy,
J., Williamson, C., Ortega, I. K., Pringle, K. J., Adamov, A.,
Baltensperger, U., Barmet, P., Benduhn, F., Bianchi, F., Breitenlechner,
M., Clarke, A., Curtius, J., Dommen, J., Donahue,
N. M., Ehrhart, S., Flagan, R. C., Franchin, A., Guida, R.,
Hakala, J., Hansel, A., Heinritzi, M., Jokinen, T., Kangasluoma,
J., Kirkby, J., Kulmala, M., Kupc, A., Lawler, M. J., Lehtipalo,
K., Makhmutov, V., Mann, G., Mathot, S., Merikanto,
J., Miettinen, P., Nenes, A., Onnela, A., Rap, A., Reddington,
C. L. S., Riccobono, F., Richards, N. A. D., Rissanen,
M. P., Rondo, L., Sarnela, N., Schobesberger, S., Sengupta,
K., Simon, M., Sipilä, M., Smith, J. N., Stozkhov, Y., Tomé,
A., Tröstl, J., Wagner, P. E., Wimmer, D., Winkler, P. M.,
Worsnop, D. R., and Carslaw, K. S.: Global particle formation from CERN CLOUD
measurements, Science, 354, 1119–1124, https://doi.org/10.1126/science.aaf2649, 2016.
Kazil, J. and Lovejoy, E. R.: A semi-analytical method for calculating rates of new sulfate aerosol formation from the gas phase, Atmos. Chem. Phys., 7, 3447–3459, https://doi.org/10.5194/acp-7-3447-2007, 2007.
Kazil, J., Stier, P., Zhang, K., Quaas, J., Kinne, S., O'Donnell, D., Rast, S., Esch, M., Ferrachat, S., Lohmann, U., and Feichter, J.: Aerosol nucleation and its role for clouds and Earth's radiative forcing in the aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 10, 10733–10752, https://doi.org/10.5194/acp-10-10733-2010, 2010.
Kirkby, J., Curtius, J., Almeida, J., Dunne, E., Duplissy, J., Ehrhart,
S., Franchin, A., Gagné, S., Ickes, L., Kürten, A., Kupc, A., Metzger,
A., Riccobono, F., Rondo, L., Schobesberger, S., Tsagkogeorgas,
G., Wimmer, D., Amorim, A., Bianchi, F., Breitenlechner,
M., David, A., Dommen, J., Downard, A., Ehn, M., Flagan, R. C.,
Haider, S., Hansel, A., Hauser, D., Jud,W., Junninen, H., Kreissl,
F., Kvashin, A., Laaksonen, A., Lehtipalo, K., Lima, J., Lovejoy,
E. R., Makhmutov, V., Mathot, S., Mikkilä, J., Minginette,
P., Mogo, S., Nieminen, T., Onnela, A., Pereira, P., Petäjä, T.,
Schnitzhofer, R., Seinfeld, J. H., Sipilä, M., Stozhkov, Y., Stratmann,
F., Tomé, A., Vanhanen, J., Viisanen, Y., Vrtala, A., Wagner,
P. E., Walther, H., Weingartner, E., Wex, H., Winkler, P. M.,
Carslaw, K. S., Worsnop, D. R., Baltensperger, U., and Kulmala,
M.: The
role of sulfuric acid, ammonia and galactic cosmic rays in atmospheric
aerosol nucleation, Nature, 476, 429–433, 2011.
Kuang, C., McMurry, P. H., McCormick, A. V., and Eisele, F. L.: Dependence
of nucleation rates on sulfuric acid vapor concentration in diverse
atmospheric locations, J. Geophys. Res., 113, D10209,
https://doi.org/10.1029/2007JD009253, 2008.
Kulmala, M., Laaksonen, A., and Pirjola, L.: Parameterizations for sulfuric
acid/water nucleation rates, J. Geophys. Res., 103, 8301–8308, 1998.
Kürten, A., Bianchi, F., Almeida, J., Kupiainen-Määttä, O., Dunne,
E. M., Duplissy, J., Williamson, C., Barmet, P., Breitenlechner,
M., Dommen, J., Donahue, N. M., Flagan, R. C., Franchin, A.,
Gordon, H., Hakala, J., Hansel, A., Heinritzi, M., Ickes, L., Jokinen,
T., Kangasluoma, J., Kim, J., Kirkby, J., Kupc, A., Lehtipalo,
K., Leiminger, M., Makhmutov, V., Onnela, A., Ortega,
I. K., Petäjä, T., Praplan, A. P., Riccobono, F., Rissanen, M.
P., Rondo, L., Schnitzhofer, R., Schobesberger, S., Smith, J. N.,
Steiner, G., Stozhkov, Y., Tomé, A., Tröstl, J., Tsagkogeorgas, G.,
Wagner, P. E., Wimmer, D., Ye, P., Baltensperger, U., Carslaw,
K., Kulmala, M., and Curtius, J.: Experimental particle formation rates spanning
tropospheric sulfuric acid and ammonia abundances, ion production rates, and
temperatures, J. Geophys. Res.-Atmos., 121, 12377–12400,
https://doi.org/10.1002/2015JD023908, 2016.
Lee, S.-H., Gordon, H., Yu, H., Lehtipalo, K., Haley, R., Li, Y., and Zhang,
R.: New particle formation in the atmosphere: From molecular clusters to
global climate, J. Geophys. Res., 124, 7098–7146, https://doi.org/10.1029/2018JD029356,
2019.
Liu, X., Easter, R. C., Ghan, S. J., Zaveri, R., Rasch, P., Shi, X., Lamarque, J.-F., Gettelman, A., Morrison, H., Vitt, F., Conley, A., Park, S., Neale, R., Hannay, C., Ekman, A. M. L., Hess, P., Mahowald, N., Collins, W., Iacono, M. J., Bretherton, C. S., Flanner, M. G., and Mitchell, D.: Toward a minimal representation of aerosols in climate models: description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5, 709–739, https://doi.org/10.5194/gmd-5-709-2012, 2012.
Lovejoy, E. R., Curtius, J., and Froyd, K. D.: Atmospheric ion-induced
nucleation of sulfuric acid and water, J. Geophys. Res., 109, D08204,
https://doi.org/10.1029/2003JD004460, 2004.
Määttänen, A., Merikanto, J., Henschel, H., Duplissy, J.,
Makkonen, R., Ortega, I. K., and Vehkamäki, H.: New Parameterizations for Neutral
and Ion-Induced Sulfuric Acid-Water Particle Formation in Nucleation and
Kinetic Regimes, J. Geophys. Res.-Atmos., 123, 1269–1296.
https://doi.org/10.1002/2017JD027429, 2018.
Modgil, M. S., Kumar, S., Tripathi, S. N., and Lovejoy, E. R.: A
parameterization of ion-induced nucleation of sulphuric acid and water for
atmospheric conditions, J. Geophys. Res., 110, D19205,
https://doi.org/10.1029/2004JD005475, 2005.
Pierce, J. R. and Adams, P. J.: Uncertainty in global CCN concentrations from uncertain aerosol nucleation and primary emission rates, Atmos. Chem. Phys., 9, 1339–1356, https://doi.org/10.5194/acp-9-1339-2009, 2009.
Riipinen, I., Sihto, S.-L., Kulmala, M., Arnold, F., Dal Maso, M., Birmili, W., Saarnio, K., Teinilä, K., Kerminen, V.-M., Laaksonen, A., and Lehtinen, K. E. J.: Connections between atmospheric sulphuric acid and new particle formation during QUEST III–IV campaigns in Heidelberg and Hyytiälä, Atmos. Chem. Phys., 7, 1899–1914, https://doi.org/10.5194/acp-7-1899-2007, 2007.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics From
Air Pollution to Climate Change. John Wiley & Sons, Hoboken, 2016.
Spracklen, D. V., Carslaw, K. S., Kulmala, M., Kerminen, V.-M., Sihto,
Riipinen, I., Merikanto, J., Mann, G. W., Chipperfield, M. P., Wiedensohler,
A., Birmili, W., and Lihavainen, H.: Contribution of particle formation to
global cloud condensation nuclei concentrations, Geophys. Res.
Lett., 35, L06808, https://doi.org/10.1029/2007GL033038, 2008.
Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125–1156, https://doi.org/10.5194/acp-5-1125-2005, 2005.
Vehkamäki, H., Kulmala, M., Napari, I., Lehtinen, K. E. J., Timmreck,
C., Noppel, M., and Laaksonen, A.: An improved parameterization for sulfuric
acid–water nucleation rates for tropospheric and stratospheric conditions,
J. Geophys. Res., 107, 4622, https://doi.org/10.1029/2002JD002184, 2002.
Wang, M. and Penner, J. E.: Aerosol indirect forcing in a global model with particle nucleation, Atmos. Chem. Phys., 9, 239–260, https://doi.org/10.5194/acp-9-239-2009, 2009.
Weber, R. J., Marti, J. J., McMurry, P. H., Eisele, F. L., Tanner, D. J.,
and Jefferson, A.: Measured atmo-spheric new particle formation rates:
implications for nu-cleation mechanisms, Chem. Eng. Commun., 151, 53–64,
https://doi.org/10.1080/00986449608936541, 1996.
Williamson, C. J., Kupc, A., Axisa, D., Bilsback, K. R., Bui, T.,
Campuzano-Jost, P., Dollner, M., Froyd, K. D., Hodshire, A. L., Jimenez, J. L., Kodros, J.
K., Luo, G., Murphy, D. M., Nault, B. A., Ray, E. A., Weinzierl, B.,
Wilson, J. C., Yu, F., Yu, P., Pierce, J. R., and Brock, C. A.: A Large Source of Cloud
Condensation Nuclei from New Particle Formation in the Tropics, Nature, 574,
399–403, 2019.
Yu, F.: From molecular clusters to nanoparticles: second-generation ion-mediated nucleation model, Atmos. Chem. Phys., 6, 5193–5211, https://doi.org/10.5194/acp-6-5193-2006, 2006.
Yu, F.: Ion-mediated nucleation in the atmosphere: Key controlling
parameters, implications, and look-up table, J. Geophy. Res., 115, D03206,
https://doi.org/10.1029/2009JD012630, 2010.
Yu, F.: Lookup tables for H2SO4-H2O binary and H2SO4-H2O-NH3 ternary homogeneous and ion-mediated nucleation (Version 1.0.0) [Data set], Zenodo, https://doi.org/10.5281/zenodo.3483797, 2019.
Yu, F. and Luo, G.: Simulation of particle size distribution with a global aerosol model: contribution of nucleation to aerosol and CCN number concentrations, Atmos. Chem. Phys., 9, 7691–7710, https://doi.org/10.5194/acp-9-7691-2009, 2009.
Yu, F. and Turco, R. P.: From molecular clusters to nanoparticles: The role
of ambient ionization in tropospheric aerosol formation, J. Geophys. Res.,
106, 4797–4814, 2001.
Yu, F., Luo, G., Bates, T., Anderson, B., Clarke, A., Kapustin, V.,
Yantosca, R., Wang, Y., and Wu, S.: Spatial distributions of particle number
concentrations in the global troposphere: Simulations, observations, and
implications for nucleation mechanisms, J. Geophys. Res., 115, D17205,
https://doi.org/10.1029/2009JD013473, 2010.
Yu, F., Luo, G., Liu, X., Easter, R. C., Ma, X., and Ghan, S. J.: Indirect radiative forcing by ion-mediated nucleation of aerosol, Atmos. Chem. Phys., 12, 11451–11463, https://doi.org/10.5194/acp-12-11451-2012, 2012.
Yu, F., Nadykto, A. B., Herb, J., Luo, G., Nazarenko, K. M., and Uvarova, L. A.:
Zhang, K., O'Donnell, D., Kazil, J., Stier, P., Kinne, S., Lohmann, U., Ferrachat, S., Croft, B., Quaas, J., Wan, H., Rast, S., and Feichter, J.: The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations, Atmos. Chem. Phys., 12, 8911–8949, https://doi.org/10.5194/acp-12-8911-2012, 2012.
Zhang, R., Suh, I., Zhao, J., Zhang, D., Fortner, E. C., Tie, X., Molina, L. T., and Molina,
M. J.: Atmospheric new particle formation enhanced by organic acids,
Science, 304, 1487–1490, 2004.
Zhang, R., Khalizov, A. F., Wang, L., Hu, M., and Wen, X.: Nucleation and growth
of nanoparticles in the atmosphere, Chem. Rev., 112, 1957–2011, https://doi.org/10.1021/cr2001756, 2012.
Zhang, Y., McMurry, P. H., Yu, F., and Jacobson, M. Z.: A Comparative Study of
Homogeneous Nucleation Parameterizations, Part I. Examination and Evaluation
of the Formulations, J. Geophys. Res., 115, D20212,
https://doi.org/10.1029/2010JD014150, 2010.
Short summary
Secondary particles formed via nucleation have important implications for air quality and climate. Here we describe nucleation rate lookup tables for four different nucleation mechanisms that can be readily used in chemistry transport and climate models. The nucleation rates predicted have been assessed against state-of-the-art laboratory measurements. The lookup tables cover a wide range of key parameters controlling binary, ternary, and ion-mediated nucleation in the Earth's atmosphere.
Secondary particles formed via nucleation have important implications for air quality and...
