Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7731-2022
© Author(s) 2022. 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-15-7731-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
21 Oct 2022
Development and technical paper |
| 21 Oct 2022
| 21 Oct 2022
A lumped species approach for the simulation of secondary organic aerosol production from intermediate-volatility organic compounds (IVOCs): application to road transport in PMCAMx-iv (v1.0)
Stella E. I. Manavi
Department of Chemical Engineering, University of Patras, Patras,
26540, Greece
Institute of Chemical Engineering Sciences, Foundation for Research
and Technology – Hellas, Patras, 26540, Greece
Spyros N. Pandis
CORRESPONDING AUTHOR
Department of Chemical Engineering, University of Patras, Patras,
26540, Greece
Institute of Chemical Engineering Sciences, Foundation for Research
and Technology – Hellas, Patras, 26540, Greece
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Organic vapors of intermediate volatility have often been neglected as sources of atmospheric organic aerosol. In this work we use a new approach for their simulation and quantify the contribution of these compounds emitted by transportation sources (gasoline and diesel vehicles) to particulate matter over Europe. The estimated secondary organic aerosol levels are on average 60 % higher than predicted by previous approaches. However, these estimates are probably lower limits.
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Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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Stella E. I. Manavi and Spyros N. Pandis
Atmos. Chem. Phys., 24, 891–909, https://doi.org/10.5194/acp-24-891-2024, https://doi.org/10.5194/acp-24-891-2024, 2024
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Andreas Aktypis, Christos Kaltsonoudis, David Patoulias, Panayiotis Kalkavouras, Angeliki Matrali, Christina N. Vasilakopoulou, Evangelia Kostenidou, Kalliopi Florou, Nikos Kalivitis, Aikaterini Bougiatioti, Konstantinos Eleftheriadis, Stergios Vratolis, Maria I. Gini, Athanasios Kouras, Constantini Samara, Mihalis Lazaridis, Sofia-Eirini Chatoutsidou, Nikolaos Mihalopoulos, and Spyros N. Pandis
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Atmos. Chem. Phys., 23, 7461–7477, https://doi.org/10.5194/acp-23-7461-2023, https://doi.org/10.5194/acp-23-7461-2023, 2023
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Organic aerosols directly emitted from wood and pellet stove combustion are found to chemically transform (approximately 15 %–35 % by mass) under daytime aging conditions simulated in an environmental chamber. A new marker for lignin-like compounds is found to degrade at a different rate than previously identified biomass burning markers and can potentially provide indication of aging time in ambient samples.
Petro Uruci, Dontavious Sippial, Anthoula Drosatou, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 3155–3172, https://doi.org/10.5194/amt-16-3155-2023, https://doi.org/10.5194/amt-16-3155-2023, 2023
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In this work we develop an algorithm for the synthesis of the measurements performed in atmospheric simulation chambers regarding the formation of secondary organic aerosol (SOA). Novel features of the algorithm are its ability to use measurements of SOA yields, thermodenuders, and isothermal dilution; its estimation of parameters that can be used directly in atmospheric chemical transport models; and finally its estimates of the uncertainty in SOA formation yields.
Christina N. Vasilakopoulou, Kalliopi Florou, Christos Kaltsonoudis, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 16, 2837–2850, https://doi.org/10.5194/amt-16-2837-2023, https://doi.org/10.5194/amt-16-2837-2023, 2023
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Spiro D. Jorga, Kalliopi Florou, David Patoulias, and Spyros N. Pandis
Atmos. Chem. Phys., 23, 85–97, https://doi.org/10.5194/acp-23-85-2023, https://doi.org/10.5194/acp-23-85-2023, 2023
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We take advantage of this unexpected low, new particle formation frequency in Greece and use a dual atmospheric simulation chamber system with starting point ambient air in an effort to gain insight about the chemical species that is limiting nucleation in this area. A potential nucleation precursor, ammonia, was added in one of the chambers while the other one was used as a reference. The addition of ammonia assisted new particle formation in almost 50 % of the experiments conducted.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Geosci. Model Dev., 15, 8899–8912, https://doi.org/10.5194/gmd-15-8899-2022, https://doi.org/10.5194/gmd-15-8899-2022, 2022
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The performance of a chemical transport model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Total PM2.5 mass is reproduced well by the model during the winter when compared to regulatory measurements, but in the summer PM2.5 is underpredicted, mainly due to difficulties in reproducing regional secondary organic aerosol levels.
Christina Vasilakopoulou, Iasonas Stavroulas, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Meas. Tech., 15, 6419–6431, https://doi.org/10.5194/amt-15-6419-2022, https://doi.org/10.5194/amt-15-6419-2022, 2022
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Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols when online AMS measurements are not available. In this study, we examine whether and how the low time resolution (usually 24 h) of the offline technique affects source apportionment results. We concluded that use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis.
Aristeidis Voliotis, Mao Du, Yu Wang, Yunqi Shao, Thomas J. Bannan, Michael Flynn, Spyros N. Pandis, Carl J. Percival, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 22, 13677–13693, https://doi.org/10.5194/acp-22-13677-2022, https://doi.org/10.5194/acp-22-13677-2022, 2022
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The addition of a low-yield precursor to the reactive mixture of aVOC and bVOC can increase or decrease the SOA volatility that is system-dependent. Therefore, the SOA volatility of the mixtures cannot always be predicted based on the additivity. In complex mixtures the formation of lower-volatility products likely outweighs the formation of products with higher volatility. The unique products of each mixture contribute significantly to the signal, suggesting interactions can be important.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ksakousti Skyllakou, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-648, https://doi.org/10.5194/acp-2022-648, 2022
Revised manuscript not accepted
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A number of factors have influenced the biogenic secondary organic aerosol (SOA) levels in the southeastern US from 2001 to 2010. The increases in temperature have led to an increase of the emissions of biogenic volatile organic compounds by trees and a corresponding increase of the SOA. However, this increase has been balanced by the reductions in the anthropogenic emissions of organic gases and particulate matter as well as of the oxides of nitrogen keeping the biogenic SOA roughly constant.
Pablo Garcia Rivera, Brian T. Dinkelacker, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys., 22, 2011–2027, https://doi.org/10.5194/acp-22-2011-2022, https://doi.org/10.5194/acp-22-2011-2022, 2022
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The contribution of various pollution sources to the variability of fine PM in an urban area was examined using as an example the city of Pittsburgh. Biomass burning aerosol shows the largest variability during the winter with local maxima within the city and in the suburbs. During both periods the largest contributing source to the average PM2.5 is particles from outside the modeling domain. The average population-weighted PM2.5 concentration does not change significantly with resolution.
David Patoulias and Spyros N. Pandis
Atmos. Chem. Phys., 22, 1689–1706, https://doi.org/10.5194/acp-22-1689-2022, https://doi.org/10.5194/acp-22-1689-2022, 2022
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Our simulations indicate that the recently identified production and subsequent condensation effect of extremely low-volatility organic compounds have a smaller-than-expected effect on the total concentration of atmospheric particles. On the other hand, the oxidation of intermediate-volatility organic compounds leads to decreases in the ultrafine-particle concentrations. These results improve our understanding of the links between secondary organic aerosol formation and ultrafine particles.
Miska Olin, David Patoulias, Heino Kuuluvainen, Jarkko V. Niemi, Topi Rönkkö, Spyros N. Pandis, Ilona Riipinen, and Miikka Dal Maso
Atmos. Chem. Phys., 22, 1131–1148, https://doi.org/10.5194/acp-22-1131-2022, https://doi.org/10.5194/acp-22-1131-2022, 2022
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An emission factor particle size distribution was determined from the measurements at an urban traffic site. It was used in updating a pre-existing emission inventory, and regional modeling was performed after the update. Emission inventories typically underestimate nanoparticle emissions due to challenges in determining them with high certainty. This update reveals that the simulated aerosol levels have previously been underestimated especially for urban areas and for sub-50 nm particles.
Ksakousti Skyllakou, Pablo Garcia Rivera, Brian Dinkelacker, Eleni Karnezi, Ioannis Kioutsioukis, Carlos Hernandez, Peter J. Adams, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 17115–17132, https://doi.org/10.5194/acp-21-17115-2021, https://doi.org/10.5194/acp-21-17115-2021, 2021
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Significant reductions in pollutant emissions took place in the US from 1990 to 2010. The reductions in sulfur dioxide emissions from electric-generating units have dominated the reductions in fine particle mass. The reductions in transportation emissions have led to a 30 % reduction of elemental concentrations and of organic particulate matter by a factor of 3. On the other hand, changes in biomass burning and biogenic secondary organic aerosol have been modest.
Spiro D. Jorga, Kalliopi Florou, Christos Kaltsonoudis, John K. Kodros, Christina Vasilakopoulou, Manuela Cirtog, Axel Fouqueau, Bénédicte Picquet-Varrault, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 15337–15349, https://doi.org/10.5194/acp-21-15337-2021, https://doi.org/10.5194/acp-21-15337-2021, 2021
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We test the hypothesis that significant secondary organic aerosol production can take place even during winter nights through the oxidation of the emitted organic vapors by the nitrate radicals produced during the reaction of ozone and nitrogen oxides. Our experiments, using as a starting point the ambient air of an urban area with high biomass burning activity, demonstrate that, even with sunlight, there is 20 %–70 % additional organic aerosol formed in a few hours.
Aristeidis Voliotis, Yu Wang, Yunqi Shao, Mao Du, Thomas J. Bannan, Carl J. Percival, Spyros N. Pandis, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 21, 14251–14273, https://doi.org/10.5194/acp-21-14251-2021, https://doi.org/10.5194/acp-21-14251-2021, 2021
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Secondary organic aerosol (SOA) formation from mixtures of volatile precursors can be affected by the molecular interactions of the products. Composition and volatility measurements of SOA formed from mixtures of anthropogenic and biogenic precursors reveal processes that can increase or decrease the SOA volatility. The unique products of the mixture were more oxygenated and less volatile than those from either precursor. Analytical context is provided to explore the SOA volatility in mixtures.
Athanasios Nenes, Spyros N. Pandis, Maria Kanakidou, Armistead G. Russell, Shaojie Song, Petros Vasilakos, and Rodney J. Weber
Atmos. Chem. Phys., 21, 6023–6033, https://doi.org/10.5194/acp-21-6023-2021, https://doi.org/10.5194/acp-21-6023-2021, 2021
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Ecosystems and air quality are affected by the dry deposition of inorganic reactive nitrogen (Nr, the sum of ammonium and nitrate). Its large variability is driven by the large difference in deposition velocity of N when in the gas or particle phase. Here we show that aerosol liquid water and acidity, by affecting gas–particle partitioning, modulate the dry deposition velocity of NH3, HNO3, and Nr worldwide. These effects explain the rapid accumulation of nitrate aerosol during haze events.
Georgia N. Theodoritsi, Giancarlo Ciarelli, and Spyros N. Pandis
Geosci. Model Dev., 14, 2041–2055, https://doi.org/10.5194/gmd-14-2041-2021, https://doi.org/10.5194/gmd-14-2041-2021, 2021
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Two schemes based on the volatility basis set were used for the simulation of biomass burning organic aerosol (bbOA) in the continental US. The first is the default scheme of the PMCAMx-SR model, and the second is a recently developed scheme based on laboratory experiments. The alternative bbOA scheme predicts much higher concentrations. The default scheme performed better during summer and fall, while the alternative scheme was a little better during spring.
Weiqi Xu, Chun Chen, Yanmei Qiu, Ying Li, Zhiqiang Zhang, Eleni Karnezi, Spyros N. Pandis, Conghui Xie, Zhijie Li, Jiaxing Sun, Nan Ma, Wanyun Xu, Pingqing Fu, Zifa Wang, Jiang Zhu, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Chem. Phys., 21, 5463–5476, https://doi.org/10.5194/acp-21-5463-2021, https://doi.org/10.5194/acp-21-5463-2021, 2021
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Here aerosol volatility and viscosity at a rural site (Gucheng) and an urban site (Beijing) in the North China Plain (NCP) were investigated in summer and winter. Our results showed that organic aerosol (OA) in winter in the NCP is more volatile than that in summer due to enhanced primary emissions from coal combustion and biomass burning. We also found that OA existed mainly as a solid in winter in Beijing but as semisolids in Beijing in summer and Gucheng in winter.
Stylianos Kakavas, David Patoulias, Maria Zakoura, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 21, 799–811, https://doi.org/10.5194/acp-21-799-2021, https://doi.org/10.5194/acp-21-799-2021, 2021
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The dependence of aerosol acidity on particle size, location, and altitude over Europe during a summertime period is investigated. Differences of up to 1–4 pH units are predicted between sub- and supermicron particles in northern and southern Europe. Particles of all sizes become increasingly acidic with altitude (0.5–2.5 pH units decrease over 2.5 km). The size-dependent pH differences carry important implications for pH-sensitive processes in the aerosol.
Antonios Tasoglou, Evangelos Louvaris, Kalliopi Florou, Aikaterini Liangou, Eleni Karnezi, Christos Kaltsonoudis, Ningxin Wang, and Spyros N. Pandis
Atmos. Chem. Phys., 20, 11625–11637, https://doi.org/10.5194/acp-20-11625-2020, https://doi.org/10.5194/acp-20-11625-2020, 2020
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A month-long set of summertime measurements in a remote area in the Mediterranean is used to quantify aerosol absorption. The measured light absorption was two or more times higher than that of fresh black carbon. The absorption enhancement due to the coating of black carbon cores by other aerosol components could explain only part of this absorption enhancement. The rest was due to brown carbon, mostly in the form of extremely low volatility organic compounds.
Athanasios Nenes, Spyros N. Pandis, Rodney J. Weber, and Armistead Russell
Atmos. Chem. Phys., 20, 3249–3258, https://doi.org/10.5194/acp-20-3249-2020, https://doi.org/10.5194/acp-20-3249-2020, 2020
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We show that aerosol acidity (pH) and liquid water content naturally emerge as previously ignored parameters that drive particulate matter formation in the atmosphere, and its sensitivity to emissions of ammonia and nitric acid. The simple framework presented is easily applied to ambient measurements or model output, and it provides the
chemical regimeof PM sensitivity to ammonia and nitric acid availability.
Weiqi Xu, Conghui Xie, Eleni Karnezi, Qi Zhang, Junfeng Wang, Spyros N. Pandis, Xinlei Ge, Jingwei Zhang, Junling An, Qingqing Wang, Jian Zhao, Wei Du, Yanmei Qiu, Wei Zhou, Yao He, Ying Li, Jie Li, Pingqing Fu, Zifa Wang, Douglas R. Worsnop, and Yele Sun
Atmos. Chem. Phys., 19, 10205–10216, https://doi.org/10.5194/acp-19-10205-2019, https://doi.org/10.5194/acp-19-10205-2019, 2019
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We present the first aerosol volatility measurements in Beijing in summer using a thermodenuder coupled with aerosol mass spectrometers. Our results showed that organic aerosol (OA) comprised mainly semi-volatile organic compounds in summer, and the freshly oxidized secondary OA was the most volatile component. We also found quite different volatility distributions in black-carbon-containing primary and secondary OA, ambient OA, ambient secondary OA and the WRF-Chem model.
Christos Kaltsonoudis, Spiro D. Jorga, Evangelos Louvaris, Kalliopi Florou, and Spyros N. Pandis
Atmos. Meas. Tech., 12, 2733–2743, https://doi.org/10.5194/amt-12-2733-2019, https://doi.org/10.5194/amt-12-2733-2019, 2019
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A portable dual-smog-chamber system was developed using two identical pillow-shaped smog chambers surrounded by UV lamps. The system has been designed to use ambient air as the starting point of the experiments. It can be easily disassembled and transported, enabling the study of various atmospheric environments and it can be used with natural sunlight. The results of test experiments using ambient air are discussed as examples of applications of this system.
Katerina S. Karadima, Vlasis G. Mavrantzas, and Spyros N. Pandis
Atmos. Chem. Phys., 19, 5571–5587, https://doi.org/10.5194/acp-19-5571-2019, https://doi.org/10.5194/acp-19-5571-2019, 2019
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We explore the morphologies of multicomponent nanoparticles through atomistic molecular dynamics simulations under atmospherically relevant conditions. Phase separation is predicted for almost all simulated nanoparticles either between organics and inorganics or between hydrophobic and hydrophilic constituents. Three main particle types were identified: organic islands at the surface, inorganic core-organic shell morphologies and complex structures with hydrophobic and hydrophilic domains.
Georgia N. Theodoritsi and Spyros N. Pandis
Atmos. Chem. Phys., 19, 5403–5415, https://doi.org/10.5194/acp-19-5403-2019, https://doi.org/10.5194/acp-19-5403-2019, 2019
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The chemical transport model PMCAMx was extended to investigate the effects of partitioning and photochemical aging of biomass burning emissions on organic aerosol (OA) concentrations and was applied in Europe. During the summer, the contribution of biomass burning to total OA levels over continental Europe was 16 % and during winter 47 %. Intermediate volatility organic compounds are predicted to be important precursors of secondary OA from biomass burning.
Anthoula D. Drosatou, Ksakousti Skyllakou, Georgia N. Theodoritsi, and Spyros N. Pandis
Atmos. Chem. Phys., 19, 973–986, https://doi.org/10.5194/acp-19-973-2019, https://doi.org/10.5194/acp-19-973-2019, 2019
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The ability of positive matrix factorization (PMF) factor analysis to identify and quantify the organic aerosol (OA) sources accurately is tested in this modeling study. The estimated uncertainty of the contribution of fresh biomass burning is less than 30 % and of the other primary sources is less than 40 %, when these sources contribute more than 20 % to the OA. Τhe first oxygenated OA factor includes mainly highly aged OA, while the second oxygenated OA factor contains fresher secondary OA.
Ningxin Wang, Spiro D. Jorga, Jeffery R. Pierce, Neil M. Donahue, and Spyros N. Pandis
Atmos. Meas. Tech., 11, 6577–6588, https://doi.org/10.5194/amt-11-6577-2018, https://doi.org/10.5194/amt-11-6577-2018, 2018
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The interaction of particles with the chamber walls has been a significant source of uncertainty when analyzing results of secondary organic aerosol formation experiments performed in Teflon chambers. We evaluated the performance of several particle wall-loss correction methods for aging experiments of α-pinene ozonolysis products. Experimental procedures are proposed for the characterization of particle losses during different stages of these experiments.
David Patoulias, Christos Fountoukis, Ilona Riipinen, Ari Asmi, Markku Kulmala, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 13639–13654, https://doi.org/10.5194/acp-18-13639-2018, https://doi.org/10.5194/acp-18-13639-2018, 2018
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PMCAMx-UF, a 3-D chemical transport model focusing on the simulation of ultrafine particles, has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol. The model was applied in Europe and its predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The condensation of organics led to an increase (50–120 %) in the larger particles but the total number concentration decreased by 10–30 %.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Andrea Pozzer, Spyros N. Pandis, and Jos Lelieveld
Geosci. Model Dev., 11, 3369–3389, https://doi.org/10.5194/gmd-11-3369-2018, https://doi.org/10.5194/gmd-11-3369-2018, 2018
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A new module, ORACLE 2-D, that calculates the concentrations of surrogate organic species in two-dimensional space defined by volatility and oxygen-to-carbon ratio has been developed and evaluated. ORACLE 2-D uses a simple photochemical aging scheme that efficiently simulates the net effects of fragmentation and functionalization. ORACLE 2-D can be used to compute the ability of organic particles to act as cloud condensation nuclei and serves as a tool to quantify their climatic impact.
Eleni Karnezi, Benjamin N. Murphy, Laurent Poulain, Hartmut Herrmann, Alfred Wiedensohler, Florian Rubach, Astrid Kiendler-Scharr, Thomas F. Mentel, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 10759–10772, https://doi.org/10.5194/acp-18-10759-2018, https://doi.org/10.5194/acp-18-10759-2018, 2018
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Different parameterizations of the organic aerosol (OA) formation and evolution are evaluated using ground and airborne measurements collected in the 2012 PEGASOS field campaign in the Po Valley (Italy). Total OA concentration and O : C ratios were reproduced within experimental error by a number of schemes. Anthropogenic secondary OA (SOA) contributed 15–25 % of the total OA, 20–35 % of SOA from intermediate volatility compounds oxidation, and 15–45 % of biogenic SOA depending on the scheme.
Evangelia Kostenidou, Eleni Karnezi, James R. Hite Jr., Aikaterini Bougiatioti, Kate Cerully, Lu Xu, Nga L. Ng, Athanasios Nenes, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 5799–5819, https://doi.org/10.5194/acp-18-5799-2018, https://doi.org/10.5194/acp-18-5799-2018, 2018
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The volatility distribution of organic aerosol (OA) and its sources during the Southern Oxidant and Aerosol Study (SOAS) was estimated. The volatility distribution of all components covered a wide range including both semi-volatile and low-volatility components. The oxygen content of the factors can be combined with their estimated volatility and hygroscopicity to provide a better view of their physical properties.
Ningxin Wang, Evangelia Kostenidou, Neil M. Donahue, and Spyros N. Pandis
Atmos. Chem. Phys., 18, 3589–3601, https://doi.org/10.5194/acp-18-3589-2018, https://doi.org/10.5194/acp-18-3589-2018, 2018
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This study investigates aging in the α-pinene ozonolysis system with hydroxyl radicals (OH) through smog chamber experiments. After an equivalent of 2–4 days of typical atmospheric oxidation conditions, homogeneous OH oxidation of the α-pinene ozonolysis products resulted in a 20–40 % net increase in the organic aerosol concentration and an increase in aerosol O : C by up to 0.04. The relative humidity in the 5–50 % range had a minimum effect on aging.
Kerrigan P. Cain and Spyros N. Pandis
Atmos. Meas. Tech., 10, 4865–4876, https://doi.org/10.5194/amt-10-4865-2017, https://doi.org/10.5194/amt-10-4865-2017, 2017
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Hygroscopicity, oxidation level, and volatility of organic pollutants are three crucial properties that determine their fate in the atmosphere. This study assesses the feasibility of a novel measurement and analysis technique to determine these properties of organic aerosol
components at the same time and to establish their relationship.
Evangelos E. Louvaris, Eleni Karnezi, Evangelia Kostenidou, Christos Kaltsonoudis, and Spyros N. Pandis
Atmos. Meas. Tech., 10, 3909–3918, https://doi.org/10.5194/amt-10-3909-2017, https://doi.org/10.5194/amt-10-3909-2017, 2017
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A method for the determination of the organic aerosol volatility distribution combining thermodenuder and isothermal dilution measurements is developed. The approach was tested in experiments that were conducted in a smog chamber using organic aerosol produced during meat charbroiling. Addition of the dilution measurements to the thermodenuder data results in a lower uncertainty of the estimated vaporization enthalpy as well as the semivolatile content of the aerosol.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Spyros N. Pandis, and Jos Lelieveld
Atmos. Chem. Phys., 17, 7345–7364, https://doi.org/10.5194/acp-17-7345-2017, https://doi.org/10.5194/acp-17-7345-2017, 2017
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We analyzed the sensitivity of model-predicted global-scale OA to parameters and assumptions that control primary emissions, photochemical aging, and the scavenging efficiency of LVOCs, SVOCs, and IVOCs. The simulated OA concentrations were evaluated against a global dataset of AMS measurements. According to our analysis, a combination of increased IVOCs and decreased hygroscopicity of the freshly emitted IVOCs can help reduce discrepancies between simulated SOA and observed OOA concentrations.
Christos Kaltsonoudis, Evangelia Kostenidou, Evangelos Louvaris, Magda Psichoudaki, Epameinondas Tsiligiannis, Kalliopi Florou, Aikaterini Liangou, and Spyros N. Pandis
Atmos. Chem. Phys., 17, 7143–7155, https://doi.org/10.5194/acp-17-7143-2017, https://doi.org/10.5194/acp-17-7143-2017, 2017
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Cooking emissions can be a significant source of particulate matter in urban areas. In this study the aerosol- and gas-phase emissions from meat charbroiling were characterized. More than 99% of the aerosol emitted was composed of organic compounds. The fresh particles were similar to the cooking organic aerosol over Greek cities during the winter, while the reacted particles were similar to those found in the atmosphere during the summer.
Kalliopi Florou, Dimitrios K. Papanastasiou, Michael Pikridas, Christos Kaltsonoudis, Evangelos Louvaris, Georgios I. Gkatzelis, David Patoulias, Nikolaos Mihalopoulos, and Spyros N. Pandis
Atmos. Chem. Phys., 17, 3145–3163, https://doi.org/10.5194/acp-17-3145-2017, https://doi.org/10.5194/acp-17-3145-2017, 2017
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The composition of fine particulate matter (PM) in two major Greek cities (Athens and Patras) was measured during two wintertime campaigns in 2012 and 2013. Residential wood burning has dramatically increased due to the Greek financial crisis, contributing around 50 % of the fine PM on average and more than 80 % during nighttime. Cooking is also an important source during both midday and evening, while transportation dominates only during the morning rush hour.
Christos Kaltsonoudis, Evangelia Kostenidou, Kalliopi Florou, Magda Psichoudaki, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 14825–14842, https://doi.org/10.5194/acp-16-14825-2016, https://doi.org/10.5194/acp-16-14825-2016, 2016
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Volatile organic compounds (VOCs) were monitored in urban backgrounds sites, in Athens and Patras in Greece. In summer most of the measured VOCs were due to biogenic and traffic emissions. Winter measurements in Athens revealed that biomass burning used for residential heating was the dominant VOC source. The biomass burning VOC emission ratios and emission factors were estimated.
Antigoni Panagiotopoulou, Panagiotis Charalampidis, Christos Fountoukis, Christodoulos Pilinis, and Spyros N. Pandis
Geosci. Model Dev., 9, 4257–4272, https://doi.org/10.5194/gmd-9-4257-2016, https://doi.org/10.5194/gmd-9-4257-2016, 2016
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The ability of chemical transport model PMCAMx to reproduce ground and satellite aerosol optical depth (AOD) measurements over Europe is evaluated. PMCAMx reproduces AOD values over Spain, the UK, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. The model overestimates the AOD over northern Europe probably due to an overestimation of organic aerosol and sulfates, and underestimates over the Balkans due to an underestimation of sulfates.
Elham Baranizadeh, Benjamin N. Murphy, Jan Julin, Saeed Falahat, Carly L. Reddington, Antti Arola, Lars Ahlm, Santtu Mikkonen, Christos Fountoukis, David Patoulias, Andreas Minikin, Thomas Hamburger, Ari Laaksonen, Spyros N. Pandis, Hanna Vehkamäki, Kari E. J. Lehtinen, and Ilona Riipinen
Geosci. Model Dev., 9, 2741–2754, https://doi.org/10.5194/gmd-9-2741-2016, https://doi.org/10.5194/gmd-9-2741-2016, 2016
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The molecular mechanisms through which new ultrafine (< 100 nm) aerosol particles are formed in the atmosphere have puzzled the scientific community for decades. In the past few years, however, significant progress has been made in unraveling these processes through laboratory studies and computational efforts. In this work we have implemented these new developments to an air quality model and study the implications of anthropogenically driven particle formation for European air quality.
Alexandra P. Tsimpidi, Vlassis A. Karydis, Spyros N. Pandis, and Jos Lelieveld
Atmos. Chem. Phys., 16, 8939–8962, https://doi.org/10.5194/acp-16-8939-2016, https://doi.org/10.5194/acp-16-8939-2016, 2016
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In this work we use a global chemistry climate model together with a comprehensive global AMS data set in order to provide valuable insights into the temporal and geographical variability of the contribution of the emitted particles and the chemically processed organic material from combustion sources to total OA. This study reveals the high importance of SOA from anthropogenic sources on global OA concentrations and identifies plausible sources of discrepancy between models and measurements.
Christos Fountoukis, Athanasios G. Megaritis, Ksakousti Skyllakou, Panagiotis E. Charalampidis, Hugo A. C. Denier van der Gon, Monica Crippa, André S. H. Prévôt, Friederike Fachinger, Alfred Wiedensohler, Christodoulos Pilinis, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 3727–3741, https://doi.org/10.5194/acp-16-3727-2016, https://doi.org/10.5194/acp-16-3727-2016, 2016
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We use PMCAMx with high grid resolution over Paris to simulate carbonaceous aerosol during the summer and winter MEGAPOLI campaigns. PMCAMx reproduces BC observations well. Addition of cooking organic aerosol emissions of 80 mg per day per capita is needed to reproduce the corresponding observations. While the oxygenated organic aerosol predictions during the summer are encouraging a major wintertime source appears to be missing.
Andrea Paciga, Eleni Karnezi, Evangelia Kostenidou, Lea Hildebrandt, Magda Psichoudaki, Gabriella J. Engelhart, Byong-Hyoek Lee, Monica Crippa, André S. H. Prévôt, Urs Baltensperger, and Spyros N. Pandis
Atmos. Chem. Phys., 16, 2013–2023, https://doi.org/10.5194/acp-16-2013-2016, https://doi.org/10.5194/acp-16-2013-2016, 2016
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We estimate the volatility distribution for the organic aerosol (OA) components during summer and winter field campaigns in Paris, France as part of the collaborative project MEGAPOLI. The OA factors (hydrocarbon like OA, cooking OA, marine OA, oxygenated OA) had a broad spectrum of volatilities with no direct link between the average volatility and average oxygen to carbon of the OA components.
G. I. Gkatzelis, D. K. Papanastasiou, K. Florou, C. Kaltsonoudis, E. Louvaris, and S. N. Pandis
Atmos. Meas. Tech., 9, 103–114, https://doi.org/10.5194/amt-9-103-2016, https://doi.org/10.5194/amt-9-103-2016, 2016
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A method for the measurement of the nonvolatile atmospheric particle size distribution is developed and tested. The tests include laboratory experiments with biogenic and anthropogenic secondary organic aerosol as well as nucleation experiments with ambient air. The method is then further tested during an ambient campaign.
E. Kostenidou, K. Florou, C. Kaltsonoudis, M. Tsiflikiotou, S. Vratolis, K. Eleftheriadis, and S. N. Pandis
Atmos. Chem. Phys., 15, 11355–11371, https://doi.org/10.5194/acp-15-11355-2015, https://doi.org/10.5194/acp-15-11355-2015, 2015
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The concentration and chemical composition of fine particulate matter were measured during the summer of 2012 in two Greek cities, Patras and Athens. The composition of PM1 was surprisingly similar in both areas, demonstrating the importance of regional sources. Analysis of the Aerosol Mass Spectrometer data suggested that the contribution of the primary sources to organic aerosol was important (22% in Patras and 35% in Athens) but not dominant.
M. Pikridas, J. Sciare, F. Freutel, S. Crumeyrolle, S.-L. von der Weiden-Reinmüller, A. Borbon, A. Schwarzenboeck, M. Merkel, M. Crippa, E. Kostenidou, M. Psichoudaki, L. Hildebrandt, G. J. Engelhart, T. Petäjä, A. S. H. Prévôt, F. Drewnick, U. Baltensperger, A. Wiedensohler, M. Kulmala, M. Beekmann, and S. N. Pandis
Atmos. Chem. Phys., 15, 10219–10237, https://doi.org/10.5194/acp-15-10219-2015, https://doi.org/10.5194/acp-15-10219-2015, 2015
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Aerosol size distribution measurements from three ground sites, two mobile laboratories, and one airplane are combined to investigate the spatial and temporal variability of ultrafine particles in and around Paris during the summer and winter MEGAPOLI campaigns. The role of nucleation as a particle source and the influence of Paris emissions on their surroundings are examined.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
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A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
L. Hildebrandt Ruiz, A. L. Paciga, K. M. Cerully, A. Nenes, N. M. Donahue, and S. N. Pandis
Atmos. Chem. Phys., 15, 8301–8313, https://doi.org/10.5194/acp-15-8301-2015, https://doi.org/10.5194/acp-15-8301-2015, 2015
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Secondary organic aerosol (SOA) is transformed after its initial formation. We explored the effects of this chemical aging on the composition, mass yield, volatility, and hygroscopicity of SOA formed from the photo-oxidation of small aromatic volatile organic compounds. Higher exposure to the hydroxyl radical resulted in different SOA composition, average carbon oxidation state, and mass yield. The vapor pressure of SOA formed under different conditions varied by as much as a factor of 30.
D. Patoulias, C. Fountoukis, I. Riipinen, and S. N. Pandis
Atmos. Chem. Phys., 15, 6337–6350, https://doi.org/10.5194/acp-15-6337-2015, https://doi.org/10.5194/acp-15-6337-2015, 2015
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A new aerosol dynamics model (DMANx) describing the organic vapor condensation on nanoparticles based on the volatility basis set framework is used to simulate typical nucleation events in two contrasting environments in Hyytiälä (Finland) and Finokalia (Greece). The role of semivolatile, low, and extremely low volatility organics and the corresponding surface energies is investigated.
I. Riipinen, N. Rastak, and S. N. Pandis
Atmos. Chem. Phys., 15, 6305–6322, https://doi.org/10.5194/acp-15-6305-2015, https://doi.org/10.5194/acp-15-6305-2015, 2015
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Atmospheric organic aerosol is complex and thus a challenge to model. We introduce a theoretical framework (solubility distributions) to represent the solubility of multicomponent mixtures. Using the framework, we evaluate the commonly made assumptions about the cloud condensation nucleus (CCN) activity of organic mixtures. We find that material with water solubilities larger than 0.1-100 g/L can usually be treated as completely soluble, which simplifies the treatment of organic CCN.
A. Tasoglou and S. N. Pandis
Atmos. Chem. Phys., 15, 6035–6046, https://doi.org/10.5194/acp-15-6035-2015, https://doi.org/10.5194/acp-15-6035-2015, 2015
A. P. Tsimpidi, V. A. Karydis, A. Pozzer, S. N. Pandis, and J. Lelieveld
Geosci. Model Dev., 7, 3153–3172, https://doi.org/10.5194/gmd-7-3153-2014, https://doi.org/10.5194/gmd-7-3153-2014, 2014
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A computationally efficient module for the description of OA composition and evolution in the atmosphere has been developed. This module subdivides OA into several compounds based on their source of origin and volatility, allowing the quantification of POA vs. SOA as well as biogenic vs. anthropogenic contributions to OA concentrations. Such fundamental information can shed light on long-term changes in OA abundance, and hence project the effects of OA on future air quality and climate.
A. G. Megaritis, C. Fountoukis, P. E. Charalampidis, H. A. C. Denier van der Gon, C. Pilinis, and S. N. Pandis
Atmos. Chem. Phys., 14, 10283–10298, https://doi.org/10.5194/acp-14-10283-2014, https://doi.org/10.5194/acp-14-10283-2014, 2014
E. Karnezi, I. Riipinen, and S. N. Pandis
Atmos. Meas. Tech., 7, 2953–2965, https://doi.org/10.5194/amt-7-2953-2014, https://doi.org/10.5194/amt-7-2953-2014, 2014
C. Fountoukis, A. G. Megaritis, K. Skyllakou, P. E. Charalampidis, C. Pilinis, H. A. C. Denier van der Gon, M. Crippa, F. Canonaco, C. Mohr, A. S. H. Prévôt, J. D. Allan, L. Poulain, T. Petäjä, P. Tiitta, S. Carbone, A. Kiendler-Scharr, E. Nemitz, C. O'Dowd, E. Swietlicki, and S. N. Pandis
Atmos. Chem. Phys., 14, 9061–9076, https://doi.org/10.5194/acp-14-9061-2014, https://doi.org/10.5194/acp-14-9061-2014, 2014
M. Crippa, F. Canonaco, V. A. Lanz, M. Äijälä, J. D. Allan, S. Carbone, G. Capes, D. Ceburnis, M. Dall'Osto, D. A. Day, P. F. DeCarlo, M. Ehn, A. Eriksson, E. Freney, L. Hildebrandt Ruiz, R. Hillamo, J. L. Jimenez, H. Junninen, A. Kiendler-Scharr, A.-M. Kortelainen, M. Kulmala, A. Laaksonen, A. A. Mensah, C. Mohr, E. Nemitz, C. O'Dowd, J. Ovadnevaite, S. N. Pandis, T. Petäjä, L. Poulain, S. Saarikoski, K. Sellegri, E. Swietlicki, P. Tiitta, D. R. Worsnop, U. Baltensperger, and A. S. H. Prévôt
Atmos. Chem. Phys., 14, 6159–6176, https://doi.org/10.5194/acp-14-6159-2014, https://doi.org/10.5194/acp-14-6159-2014, 2014
B. N. Murphy, N. M. Donahue, A. L. Robinson, and S. N. Pandis
Atmos. Chem. Phys., 14, 5825–5839, https://doi.org/10.5194/acp-14-5825-2014, https://doi.org/10.5194/acp-14-5825-2014, 2014
A. Bougiatioti, I. Stavroulas, E. Kostenidou, P. Zarmpas, C. Theodosi, G. Kouvarakis, F. Canonaco, A. S. H. Prévôt, A. Nenes, S. N. Pandis, and N. Mihalopoulos
Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, https://doi.org/10.5194/acp-14-4793-2014, 2014
K. Skyllakou, B. N. Murphy, A. G. Megaritis, C. Fountoukis, and S. N. Pandis
Atmos. Chem. Phys., 14, 2343–2352, https://doi.org/10.5194/acp-14-2343-2014, https://doi.org/10.5194/acp-14-2343-2014, 2014
L. Ahlm, J. Julin, C. Fountoukis, S. N. Pandis, and I. Riipinen
Atmos. Chem. Phys., 13, 10271–10283, https://doi.org/10.5194/acp-13-10271-2013, https://doi.org/10.5194/acp-13-10271-2013, 2013
E. Kostenidou, C. Kaltsonoudis, M. Tsiflikiotou, E. Louvaris, L. M. Russell, and S. N. Pandis
Atmos. Chem. Phys., 13, 8797–8811, https://doi.org/10.5194/acp-13-8797-2013, https://doi.org/10.5194/acp-13-8797-2013, 2013
Q. J. Zhang, M. Beekmann, F. Drewnick, F. Freutel, J. Schneider, M. Crippa, A. S. H. Prevot, U. Baltensperger, L. Poulain, A. Wiedensohler, J. Sciare, V. Gros, A. Borbon, A. Colomb, V. Michoud, J.-F. Doussin, H. A. C. Denier van der Gon, M. Haeffelin, J.-C. Dupont, G. Siour, H. Petetin, B. Bessagnet, S. N. Pandis, A. Hodzic, O. Sanchez, C. Honoré, and O. Perrussel
Atmos. Chem. Phys., 13, 5767–5790, https://doi.org/10.5194/acp-13-5767-2013, https://doi.org/10.5194/acp-13-5767-2013, 2013
E. Athanasopoulou, H. Vogel, B. Vogel, A. P. Tsimpidi, S. N. Pandis, C. Knote, and C. Fountoukis
Atmos. Chem. Phys., 13, 625–645, https://doi.org/10.5194/acp-13-625-2013, https://doi.org/10.5194/acp-13-625-2013, 2013
V.-M. Kerminen, M. Paramonov, T. Anttila, I. Riipinen, C. Fountoukis, H. Korhonen, E. Asmi, L. Laakso, H. Lihavainen, E. Swietlicki, B. Svenningsson, A. Asmi, S. N. Pandis, M. Kulmala, and T. Petäjä
Atmos. Chem. Phys., 12, 12037–12059, https://doi.org/10.5194/acp-12-12037-2012, https://doi.org/10.5194/acp-12-12037-2012, 2012
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Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
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
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of 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 models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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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 rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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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 new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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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 at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
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
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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
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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
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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
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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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
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
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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.
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Pye, H. O. T. and Seinfeld, J. H.: A global perspective on aerosol from low-volatility organic compounds, Atmos. Chem. Phys., 10, 4377–4401, https://doi.org/10.5194/acp-10-4377-2010, 2010.
Qi, L., Liu, H., Shen, X. E., Fu, M., Huang, F., Man, H., Deng, F., Shaikh,
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Short summary
The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
The paper describes the first step towards the development of a simulation framework for the...
