Articles | Volume 25, issue 17
https://doi.org/10.5194/acp-25-10183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-10183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Sep 2025
Research article |
| 10 Sep 2025
| 10 Sep 2025
Aerosol composition trends during 2000–2020: in-depth insights from model predictions and multiple worldwide near-surface observation datasets
Alexandra P. Tsimpidi
CORRESPONDING AUTHOR
Institute of Climate and Energy Systems: Troposphere (ICE-3), Forschungszentrum Jülich GmbH, Jülich, Germany
Susanne M. C. Scholz
Institute of Climate and Energy Systems: Troposphere (ICE-3), Forschungszentrum Jülich GmbH, Jülich, Germany
Alexandros Milousis
Institute of Climate and Energy Systems: Troposphere (ICE-3), Forschungszentrum Jülich GmbH, Jülich, Germany
Nikolaos Mihalopoulos
Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Athens, 15236, Greece
Vlassis A. Karydis
Institute of Climate and Energy Systems: Troposphere (ICE-3), Forschungszentrum Jülich GmbH, Jülich, Germany
Related authors
Alexandra P. Tsimpidi and Vlassis A. Karydis
EGUsphere, https://doi.org/10.5194/egusphere-2026-1709, https://doi.org/10.5194/egusphere-2026-1709, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed a simplified representation of organic aerosol formation and evolution for long-term climate simulations. Organic aerosol affects air quality, human health, and climate but is difficult to model due to its complexity. Our approach preserves the key physical and chemical processes while reducing computational cost by about 14%. The model reproduces observed global patterns reasonably well, enabling more efficient and reliable studies of long-term changes in air pollution and climate.
Stylianos Kakavas, Stelios Myriokefalitakis, Alexandra P. Tsimpidi, Vlassis A. Karydis, and Spyros N. Pandis
EGUsphere, https://doi.org/10.5194/egusphere-2026-37, https://doi.org/10.5194/egusphere-2026-37, 2026
Short summary
Short summary
The computationally efficient configuration of the ORACLE v1.0 module (ORACLE-lite) is implemented into the TM5-MP global chemical transport model, which represents the chemistry-transport component of the EC-Earth3-AerChem ESM. The models bias is reduced by approximately half in the standalone TM5-MP simulation and by a factor of three in EC-Earth3-AerChem when ORACLE-lite is implemented.
Alexandros Milousis, Susanne M. C. Scholz, Hendrik Fuchs, Alexandra P. Tsimpidi, and Vlassis A. Karydis
Atmos. Chem. Phys., 26, 571–605, https://doi.org/10.5194/acp-26-571-2026, https://doi.org/10.5194/acp-26-571-2026, 2026
Short summary
Short summary
Nitrate aerosol has become a dominant atmospheric component, surpassing sulfate in aerosol composition. However, its simulation remains challenging due to complex formation processes and regional variability. We use the EMAC model to assess key factors in nitrate predictions. Increasing grid resolution, reducing dinitrogen pentoxide hydrolysis uptake, and refining emissions improve model performance, although seasonal and diurnal discrepancies persist, requiring further refinement.
Susanne M. C. Scholz, Vlassis A. Karydis, Georgios I. Gkatzelis, Hendrik Fuchs, Spyros N. Pandis, and Alexandra P. Tsimpidi
Geosci. Model Dev., 18, 10119–10142, https://doi.org/10.5194/gmd-18-10119-2025, https://doi.org/10.5194/gmd-18-10119-2025, 2025
Short summary
Short summary
We studied how pollution from cars and trucks contributes to tiny airborne particles that affect air quality and climate. These particles, called secondary organic aerosols, were often underestimated in global models. By improving how certain overlooked emissions from fuel use are represented in our model, we found that their impact is much larger than previously thought. Our results suggest that road traffic plays a far greater role in global air pollution than earlier estimates showed.
Xurong Wang, Alexandra P. Tsimpidi, Zhenqi Luo, Benedikt Steil, Andrea Pozzer, Jos Lelieveld, and Vlassis A. Karydis
Atmos. Chem. Phys., 25, 10559–10586, https://doi.org/10.5194/acp-25-10559-2025, https://doi.org/10.5194/acp-25-10559-2025, 2025
Short summary
Short summary
Ammonia (NH3) is an abundant alkaline gas and key precursor in particulate matter formation. While SO2 and NOx emissions have decreased, global NH3 emissions are stable or rising. This study investigates NH3 emission impacts on size-resolved aerosol composition and acidity using the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model, analyzing three emission schemes. Sulfate–nitrate–ammonium aerosols in fine-mode sizes are most sensitive to NH3 changes. Regional responses vary. NH3 buffers aerosol acidity, mitigating pH shifts.
Mingxuan Wu, Hailong Wang, Zheng Lu, Xiaohong Liu, Huisheng Bian, David D. Cohen, Yan Feng, Mian Chin, Didier A. Hauglustaine, Vlassis A. Karydis, Marianne T. Lund, Gunnar Myhre, Andrea Pozzer, Michael Schulz, Ragnhild B. Skeie, Alexandra P. Tsimpidi, Svetlana G. Tsyro, and Shaocheng Xie
Atmos. Chem. Phys., 25, 10049–10074, https://doi.org/10.5194/acp-25-10049-2025, https://doi.org/10.5194/acp-25-10049-2025, 2025
Short summary
Short summary
A key challenge in simulating the life cycle of nitrate aerosol in global models is accurately representing the mass size distribution of nitrate aerosol, which lacks sufficient observational constraints. We found that most global models underestimate the mass fraction of fine-mode nitrate at the surface in all regions. Our study highlights the importance of gas–aerosol partitioning parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.
Alexandros Milousis, Klaus Klingmüller, Alexandra P. Tsimpidi, Jasper F. Kok, Maria Kanakidou, Athanasios Nenes, and Vlassis A. Karydis
Atmos. Chem. Phys., 25, 1333–1351, https://doi.org/10.5194/acp-25-1333-2025, https://doi.org/10.5194/acp-25-1333-2025, 2025
Short summary
Short summary
This study investigates the impact of dust on the global radiative effect of nitrate aerosols. The results indicate both positive and negative regional shortwave and longwave radiative effects due to aerosol–radiation interactions and cloud adjustments. The global average net REari and REaci of nitrate aerosols are −0.11 and +0.17 W m−2, respectively, mainly affecting the shortwave spectrum. Sensitivity simulations evaluated the influence of mineral dust composition and emissions on the results.
Ryan Vella, Matthew Forrest, Andrea Pozzer, Alexandra P. Tsimpidi, Thomas Hickler, Jos Lelieveld, and Holger Tost
Atmos. Chem. Phys., 25, 243–262, https://doi.org/10.5194/acp-25-243-2025, https://doi.org/10.5194/acp-25-243-2025, 2025
Short summary
Short summary
This study examines how land cover changes influence biogenic volatile organic compound (BVOC) emissions and atmospheric states. Using a coupled chemistry–climate–vegetation model, we compare present-day land cover (deforested for crops and grazing) with natural vegetation and an extreme reforestation scenario. We find that vegetation changes significantly impact global BVOC emissions and organic aerosols but have a relatively small effect on total aerosols, clouds, and radiative effects.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
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
Short summary
Short summary
This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
Short summary
Short summary
A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Vlassis A. Karydis, Alexandra P. Tsimpidi, Andrea Pozzer, and Jos Lelieveld
Atmos. Chem. Phys., 21, 14983–15001, https://doi.org/10.5194/acp-21-14983-2021, https://doi.org/10.5194/acp-21-14983-2021, 2021
Short summary
Short summary
Aerosol particle pH is well-buffered by alkaline compounds, notably NH3 and crustal elements. NH3 is found to supply remarkable buffering capacity on a global scale, from the polluted continents to the remote oceans. Potential future changes in agricultural NH3 must be accompanied by strong reductions of SO2 and NOx to avoid particles becoming highly acidic, with implications for human health (aerosol toxicity), ecosystems (acid deposition), clouds, and climate (aerosol hygroscopicity).
Alexandra P. Tsimpidi and Vlassis A. Karydis
EGUsphere, https://doi.org/10.5194/egusphere-2026-1709, https://doi.org/10.5194/egusphere-2026-1709, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed a simplified representation of organic aerosol formation and evolution for long-term climate simulations. Organic aerosol affects air quality, human health, and climate but is difficult to model due to its complexity. Our approach preserves the key physical and chemical processes while reducing computational cost by about 14%. The model reproduces observed global patterns reasonably well, enabling more efficient and reliable studies of long-term changes in air pollution and climate.
Anchal Garg, Maximilien Desservettaz, Aliki Christodoulou, Theodoros Christoudias, Vijay Punjaji Kanawade, Chrysanthos Savvides, Mihalis Vrekoussis, Shahid Naqui, Tuija Jokinen, Joseph Byron, Jonathan Williams, Nikos Mihalopoulos, Eleni Liakakou, Jean Sciare, and Efstratios Bourtsoukidis
Atmos. Chem. Phys., 26, 2597–2622, https://doi.org/10.5194/acp-26-2597-2026, https://doi.org/10.5194/acp-26-2597-2026, 2026
Short summary
Short summary
This study reports multi-year (2022–2024) measurements of 76 volatile organic compounds (VOCs) at a rural site in Cyprus. Oxygenated VOCs were the most abundant and showed strong daytime increases due to sunlight-driven chemistry. Air-mass analysis showed that transport from Middle East strongly influenced aromatic VOC levels. Climate–chemistry modeling underestimated most VOCs, highlighting gaps in current emission and chemical processes.
Elie Bimenyimana, Jean Sciare, Michael Pikridas, Konstantina Oikonomou, Minas Iakovides, Emily Vasiliadou, Chrysanthos Savvides, and Nikos Mihalopoulos
Atmos. Chem. Phys., 26, 1605–1622, https://doi.org/10.5194/acp-26-1605-2026, https://doi.org/10.5194/acp-26-1605-2026, 2026
Short summary
Short summary
Long-term (2015–2023) source apportionment analysis reveals that reduction in PM10 concentration levels from traffic in Cypriot cities is completely offset by the concomitant increase of uncontrolled PM from local sources (road dust resuspension, and domestic wood burning), along with rising Middle East PM from fossil fuel emissions. This poses a major challenge for Cyprus to comply with the stricter PM10 limits set by the new EU air quality directive.
Stylianos Kakavas, Stelios Myriokefalitakis, Alexandra P. Tsimpidi, Vlassis A. Karydis, and Spyros N. Pandis
EGUsphere, https://doi.org/10.5194/egusphere-2026-37, https://doi.org/10.5194/egusphere-2026-37, 2026
Short summary
Short summary
The computationally efficient configuration of the ORACLE v1.0 module (ORACLE-lite) is implemented into the TM5-MP global chemical transport model, which represents the chemistry-transport component of the EC-Earth3-AerChem ESM. The models bias is reduced by approximately half in the standalone TM5-MP simulation and by a factor of three in EC-Earth3-AerChem when ORACLE-lite is implemented.
Alexandros Milousis, Susanne M. C. Scholz, Hendrik Fuchs, Alexandra P. Tsimpidi, and Vlassis A. Karydis
Atmos. Chem. Phys., 26, 571–605, https://doi.org/10.5194/acp-26-571-2026, https://doi.org/10.5194/acp-26-571-2026, 2026
Short summary
Short summary
Nitrate aerosol has become a dominant atmospheric component, surpassing sulfate in aerosol composition. However, its simulation remains challenging due to complex formation processes and regional variability. We use the EMAC model to assess key factors in nitrate predictions. Increasing grid resolution, reducing dinitrogen pentoxide hydrolysis uptake, and refining emissions improve model performance, although seasonal and diurnal discrepancies persist, requiring further refinement.
Susanne M. C. Scholz, Vlassis A. Karydis, Georgios I. Gkatzelis, Hendrik Fuchs, Spyros N. Pandis, and Alexandra P. Tsimpidi
Geosci. Model Dev., 18, 10119–10142, https://doi.org/10.5194/gmd-18-10119-2025, https://doi.org/10.5194/gmd-18-10119-2025, 2025
Short summary
Short summary
We studied how pollution from cars and trucks contributes to tiny airborne particles that affect air quality and climate. These particles, called secondary organic aerosols, were often underestimated in global models. By improving how certain overlooked emissions from fuel use are represented in our model, we found that their impact is much larger than previously thought. Our results suggest that road traffic plays a far greater role in global air pollution than earlier estimates showed.
Anna Maria Neroladaki, Maria Tsagkaraki, Kyriaki Papoutsidaki, Kalliopi Tavernaraki, Filothei Boufidou, Pavlos Zarmpas, Irini Tsiodra, Eleni Liakakou, Aikaterini Bougiatioti, Giorgos Kouvarakis, Nikos Kalivitis, Christos Kaltsonoudis, Athanasios Karagioras, Dimitrios Balis, Konstantinos Michailidis, Konstantinos Kourtidis, Stelios Myriokefalitakis, Nikos Hatzianastassiou, Spyros N. Pandis, Athanasios Nenes, Nikolaos Mihalopoulos, and Maria Kanakidou
Atmos. Chem. Phys., 25, 17953–17971, https://doi.org/10.5194/acp-25-17953-2025, https://doi.org/10.5194/acp-25-17953-2025, 2025
Short summary
Short summary
Aerosol acidity affects aerosol composition and properties, and therefore climate, human health and ecosystems. We use summer and winter fine aerosol observations at 6 sites across Greece, and a thermodynamic model to calculate the spatial and seasonal variability of aerosol acidity. Aerosols were acidic to moderately acidic and more acidic during summer than winter. The importance of organics for aerosol acidity was small. Depending on location different factors controlled aerosol acidity.
Aino Ovaska, Elio Rauth, Daniel Holmberg, Paulo Artaxo, John Backman, Benjamin Bergmans, Don Collins, Marco Aurélio Franco, Shahzad Gani, Roy M. Harrison, Rakesh K. Hooda, Tareq Hussein, Antti-Pekka Hyvärinen, Kerneels Jaars, Adam Kristensson, Markku Kulmala, Lauri Laakso, Ari Laaksonen, Nikolaos Mihalopoulos, Colin O'Dowd, Jakub Ondracek, Tuukka Petäjä, Kristina Plauškaitė, Mira Pöhlker, Ximeng Qi, Peter Tunved, Ville Vakkari, Alfred Wiedensohler, Kai Puolamäki, Tuomo Nieminen, Veli-Matti Kerminen, Victoria A. Sinclair, and Pauli Paasonen
Aerosol Research, 3, 589–618, https://doi.org/10.5194/ar-3-589-2025, https://doi.org/10.5194/ar-3-589-2025, 2025
Short summary
Short summary
We trained machine learning models to estimate the number of aerosol particles large enough to form clouds and generated daily estimates for the entire globe. The models performed well in many continental regions but struggled in remote and marine areas. Still, this approach offers a way to quantify these particles in areas that lack direct measurements, helping us understand their influence on clouds and climate on a global scale.
Lu Liu, Thorsten Hohaus, Andreas Hofzumahaus, Frank Holland, Hendrik Fuchs, Ralf Tillmann, Birger Bohn, Stefanie Andres, Zhaofeng Tan, Franz Rohrer, Vlassis A. Karydis, Vaishali Vardhan, Philipp Franke, Anne C. Lange, Anna Novelli, Benjamin Winter, Changmin Cho, Iulia Gensch, Sergej Wedel, Andreas Wahner, and Astrid Kiendler-Scharr
Atmos. Chem. Phys., 25, 16189–16213, https://doi.org/10.5194/acp-25-16189-2025, https://doi.org/10.5194/acp-25-16189-2025, 2025
Short summary
Short summary
We measured air particles at a rural site in Germany over a year to understand how their sources and properties change with the seasons. Particles from natural sources peaked in summer, especially during heatwaves, while those from burning activities like residential heating and wildfires dominated in colder months. Winds carrying air from other regions also influenced particle levels. These findings link air quality to climate change and energy transitions.
Xurong Wang, Alexandra P. Tsimpidi, Zhenqi Luo, Benedikt Steil, Andrea Pozzer, Jos Lelieveld, and Vlassis A. Karydis
Atmos. Chem. Phys., 25, 10559–10586, https://doi.org/10.5194/acp-25-10559-2025, https://doi.org/10.5194/acp-25-10559-2025, 2025
Short summary
Short summary
Ammonia (NH3) is an abundant alkaline gas and key precursor in particulate matter formation. While SO2 and NOx emissions have decreased, global NH3 emissions are stable or rising. This study investigates NH3 emission impacts on size-resolved aerosol composition and acidity using the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model, analyzing three emission schemes. Sulfate–nitrate–ammonium aerosols in fine-mode sizes are most sensitive to NH3 changes. Regional responses vary. NH3 buffers aerosol acidity, mitigating pH shifts.
Mingxuan Wu, Hailong Wang, Zheng Lu, Xiaohong Liu, Huisheng Bian, David D. Cohen, Yan Feng, Mian Chin, Didier A. Hauglustaine, Vlassis A. Karydis, Marianne T. Lund, Gunnar Myhre, Andrea Pozzer, Michael Schulz, Ragnhild B. Skeie, Alexandra P. Tsimpidi, Svetlana G. Tsyro, and Shaocheng Xie
Atmos. Chem. Phys., 25, 10049–10074, https://doi.org/10.5194/acp-25-10049-2025, https://doi.org/10.5194/acp-25-10049-2025, 2025
Short summary
Short summary
A key challenge in simulating the life cycle of nitrate aerosol in global models is accurately representing the mass size distribution of nitrate aerosol, which lacks sufficient observational constraints. We found that most global models underestimate the mass fraction of fine-mode nitrate at the surface in all regions. Our study highlights the importance of gas–aerosol partitioning parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, P. Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gómez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal L. Weagle, and Xi Zhao
Atmos. Chem. Phys., 25, 4665–4702, https://doi.org/10.5194/acp-25-4665-2025, https://doi.org/10.5194/acp-25-4665-2025, 2025
Short summary
Short summary
Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Here, we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the data sets to model output.
Alexandros Milousis, Klaus Klingmüller, Alexandra P. Tsimpidi, Jasper F. Kok, Maria Kanakidou, Athanasios Nenes, and Vlassis A. Karydis
Atmos. Chem. Phys., 25, 1333–1351, https://doi.org/10.5194/acp-25-1333-2025, https://doi.org/10.5194/acp-25-1333-2025, 2025
Short summary
Short summary
This study investigates the impact of dust on the global radiative effect of nitrate aerosols. The results indicate both positive and negative regional shortwave and longwave radiative effects due to aerosol–radiation interactions and cloud adjustments. The global average net REari and REaci of nitrate aerosols are −0.11 and +0.17 W m−2, respectively, mainly affecting the shortwave spectrum. Sensitivity simulations evaluated the influence of mineral dust composition and emissions on the results.
Xiansheng Liu, Xun Zhang, Marvin Dufresne, Tao Wang, Lijie Wu, Rosa Lara, Roger Seco, Marta Monge, Ana Maria Yáñez-Serrano, Marie Gohy, Paul Petit, Audrey Chevalier, Marie-Pierre Vagnot, Yann Fortier, Alexia Baudic, Véronique Ghersi, Grégory Gille, Ludovic Lanzi, Valérie Gros, Leïla Simon, Heidi Héllen, Stefan Reimann, Zoé Le Bras, Michelle Jessy Müller, David Beddows, Siqi Hou, Zongbo Shi, Roy M. Harrison, William Bloss, James Dernie, Stéphane Sauvage, Philip K. Hopke, Xiaoli Duan, Taicheng An, Alastair C. Lewis, James R. Hopkins, Eleni Liakakou, Nikolaos Mihalopoulos, Xiaohu Zhang, Andrés Alastuey, Xavier Querol, and Thérèse Salameh
Atmos. Chem. Phys., 25, 625–638, https://doi.org/10.5194/acp-25-625-2025, https://doi.org/10.5194/acp-25-625-2025, 2025
Short summary
Short summary
This study examines BTEX (benzene, toluene, ethylbenzene, xylenes) pollution in urban areas across seven European countries. Analyzing data from 22 monitoring sites, we found traffic and industrial activities significantly impact BTEX levels, with peaks during rush hours. The risk from BTEX exposure remains moderate, especially in high-traffic and industrial zones, highlighting the need for targeted air quality management to protect public health and improve urban air quality.
Pamela A. Dominutti, Jean-Luc Jaffrezo, Anouk Marsal, Takoua Mhadhbi, Rhabira Elazzouzi, Camille Rak, Fabrizia Cavalli, Jean-Philippe Putaud, Aikaterini Bougiatioti, Nikolaos Mihalopoulos, Despina Paraskevopoulou, Ian Mudway, Athanasios Nenes, Kaspar R. Daellenbach, Catherine Banach, Steven J. Campbell, Hana Cigánková, Daniele Contini, Greg Evans, Maria Georgopoulou, Manuella Ghanem, Drew A. Glencross, Maria Rachele Guascito, Hartmut Herrmann, Saima Iram, Maja Jovanović, Milena Jovašević-Stojanović, Markus Kalberer, Ingeborg M. Kooter, Suzanne E. Paulson, Anil Patel, Esperanza Perdrix, Maria Chiara Pietrogrande, Pavel Mikuška, Jean-Jacques Sauvain, Katerina Seitanidi, Pourya Shahpoury, Eduardo J. d. S. Souza, Sarah Steimer, Svetlana Stevanovic, Guillaume Suarez, P. S. Ganesh Subramanian, Battist Utinger, Marloes F. van Os, Vishal Verma, Xing Wang, Rodney J. Weber, Yuhan Yang, Xavier Querol, Gerard Hoek, Roy M. Harrison, and Gaëlle Uzu
Atmos. Meas. Tech., 18, 177–195, https://doi.org/10.5194/amt-18-177-2025, https://doi.org/10.5194/amt-18-177-2025, 2025
Short summary
Short summary
In this work, 20 labs worldwide collaborated to evaluate the measurement of air pollution's oxidative potential (OP), a key indicator of its harmful effects. The study aimed to identify disparities in the widely used OP dithiothreitol assay and assess the consistency of OP among labs using the same protocol. The results showed that half of the labs achieved acceptable results. However, variability was also found, highlighting the need for standardisation in OP procedures.
Ryan Vella, Matthew Forrest, Andrea Pozzer, Alexandra P. Tsimpidi, Thomas Hickler, Jos Lelieveld, and Holger Tost
Atmos. Chem. Phys., 25, 243–262, https://doi.org/10.5194/acp-25-243-2025, https://doi.org/10.5194/acp-25-243-2025, 2025
Short summary
Short summary
This study examines how land cover changes influence biogenic volatile organic compound (BVOC) emissions and atmospheric states. Using a coupled chemistry–climate–vegetation model, we compare present-day land cover (deforested for crops and grazing) with natural vegetation and an extreme reforestation scenario. We find that vegetation changes significantly impact global BVOC emissions and organic aerosols but have a relatively small effect on total aerosols, clouds, and radiative effects.
Stelios Myriokefalitakis, Matthias Karl, Kim A. Weiss, Dimitris Karagiannis, Eleni Athanasopoulou, Anastasia Kakouri, Aikaterini Bougiatioti, Eleni Liakakou, Iasonas Stavroulas, Georgios Papangelis, Georgios Grivas, Despina Paraskevopoulou, Orestis Speyer, Nikolaos Mihalopoulos, and Evangelos Gerasopoulos
Atmos. Chem. Phys., 24, 7815–7835, https://doi.org/10.5194/acp-24-7815-2024, https://doi.org/10.5194/acp-24-7815-2024, 2024
Short summary
Short summary
A state-of-the-art thermodynamic model has been coupled with the city-scale chemistry transport model EPISODE–CityChem to investigate the equilibrium between the inorganic gas and aerosol phases over the greater Athens area, Greece. The simulations indicate that the formation of nitrates in an urban environment is significantly affected by local nitrogen oxide emissions, as well as ambient temperature, relative humidity, photochemical activity, and the presence of non-volatile cations.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
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
Short summary
Short summary
This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
Short summary
Short summary
Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
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
Atmos. Chem. Phys., 24, 65–84, https://doi.org/10.5194/acp-24-65-2024, https://doi.org/10.5194/acp-24-65-2024, 2024
Short summary
Short summary
Extensive continuous particle number size distribution measurements took place during two summers (2020 and 2021) at 11 sites in Greece for the investigation of the frequency and the spatial extent of new particle formation. The frequency during summer varied from close to zero in southwestern Greece to more than 60 % in the northern, central, and eastern regions. The spatial variability can be explained by the proximity of the sites to coal-fired power plants and agricultural areas.
Akriti Masoom, Ilias Fountoulakis, Stelios Kazadzis, Ioannis-Panagiotis Raptis, Anna Kampouri, Basil E. Psiloglou, Dimitra Kouklaki, Kyriakoula Papachristopoulou, Eleni Marinou, Stavros Solomos, Anna Gialitaki, Dimitra Founda, Vasileios Salamalikis, Dimitris Kaskaoutis, Natalia Kouremeti, Nikolaos Mihalopoulos, Vassilis Amiridis, Andreas Kazantzidis, Alexandros Papayannis, Christos S. Zerefos, and Kostas Eleftheratos
Atmos. Chem. Phys., 23, 8487–8514, https://doi.org/10.5194/acp-23-8487-2023, https://doi.org/10.5194/acp-23-8487-2023, 2023
Short summary
Short summary
We analyse the spatial and temporal aerosol spectral optical properties during the extreme wildfires of August 2021 in Greece and assess their effects on air quality and solar radiation quantities related to health, agriculture, and energy. Different aerosol conditions are identified (pure smoke, pure dust, dust–smoke together); the largest impact on solar radiation quantities is found for cases with mixed dust–smoke aerosols. Such situations are expected to occur more frequently in the future.
Aliki Christodoulou, Iasonas Stavroulas, Mihalis Vrekoussis, Maximillien Desservettaz, Michael Pikridas, Elie Bimenyimana, Jonilda Kushta, Matic Ivančič, Martin Rigler, Philippe Goloub, Konstantina Oikonomou, Roland Sarda-Estève, Chrysanthos Savvides, Charbel Afif, Nikos Mihalopoulos, Stéphane Sauvage, and Jean Sciare
Atmos. Chem. Phys., 23, 6431–6456, https://doi.org/10.5194/acp-23-6431-2023, https://doi.org/10.5194/acp-23-6431-2023, 2023
Short summary
Short summary
Our study presents, for the first time, a detailed source identification of aerosols at an urban background site in Cyprus (eastern Mediterranean), a region strongly impacted by climate change and air pollution. Here, we identify an unexpected high contribution of long-range transported pollution from fossil fuel sources in the Middle East, highlighting an urgent need to further characterize these fast-growing emissions and their impacts on regional atmospheric composition, climate, and health.
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
Short summary
Short summary
The offline aerosol mass spectrometry technique is a useful tool for the source apportionment of organic aerosol in areas and periods during which an aerosol mass spectrometer is not available. In this work, an improved offline technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing the uncertainty of the corresponding source apportionment significantly.
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
Short summary
Short summary
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.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
Short summary
Short summary
We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
Short summary
Short summary
A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Irini Tsiodra, Georgios Grivas, Kalliopi Tavernaraki, Aikaterini Bougiatioti, Maria Apostolaki, Despina Paraskevopoulou, Alexandra Gogou, Constantine Parinos, Konstantina Oikonomou, Maria Tsagkaraki, Pavlos Zarmpas, Athanasios Nenes, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 21, 17865–17883, https://doi.org/10.5194/acp-21-17865-2021, https://doi.org/10.5194/acp-21-17865-2021, 2021
Short summary
Short summary
We analyze observations from year-long measurements at Athens, Greece. Nighttime wintertime PAH levels are 4 times higher than daytime, and wintertime values are 15 times higher than summertime. Biomass burning aerosol during wintertime pollution events is responsible for these significant wintertime enhancements and accounts for 43 % of the population exposure to PAH carcinogenic risk. Biomass burning poses additional health risks beyond those associated with the high PM levels that develop.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
Short summary
Short summary
Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Vlassis A. Karydis, Alexandra P. Tsimpidi, Andrea Pozzer, and Jos Lelieveld
Atmos. Chem. Phys., 21, 14983–15001, https://doi.org/10.5194/acp-21-14983-2021, https://doi.org/10.5194/acp-21-14983-2021, 2021
Short summary
Short summary
Aerosol particle pH is well-buffered by alkaline compounds, notably NH3 and crustal elements. NH3 is found to supply remarkable buffering capacity on a global scale, from the polluted continents to the remote oceans. Potential future changes in agricultural NH3 must be accompanied by strong reductions of SO2 and NOx to avoid particles becoming highly acidic, with implications for human health (aerosol toxicity), ecosystems (acid deposition), clouds, and climate (aerosol hygroscopicity).
Dimitrios Bousiotis, Francis D. Pope, David C. S. Beddows, Manuel Dall'Osto, Andreas Massling, Jakob Klenø Nøjgaard, Claus Nordstrøm, Jarkko V. Niemi, Harri Portin, Tuukka Petäjä, Noemi Perez, Andrés Alastuey, Xavier Querol, Giorgos Kouvarakis, Nikos Mihalopoulos, Stergios Vratolis, Konstantinos Eleftheriadis, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Thomas Tuch, and Roy M. Harrison
Atmos. Chem. Phys., 21, 11905–11925, https://doi.org/10.5194/acp-21-11905-2021, https://doi.org/10.5194/acp-21-11905-2021, 2021
Short summary
Short summary
Formation of new particles is a key process in the atmosphere. New particle formation events arising from nucleation of gaseous precursors have been analysed in extensive datasets from 13 sites in five European countries in terms of frequency, nucleation rate, and particle growth rate, with several common features and many differences identified. Although nucleation frequencies are lower at roadside sites, nucleation rates and particle growth rates are typically higher.
Cited articles
Aggarwal, S. G. and Kawamura, K.: Carbonaceous and inorganic composition in long-range transported aerosols over northern Japan: Implication for aging of water-soluble organic fraction, Atmos. Environ., 43, 2532–2540, https://doi.org/10.1016/j.atmosenv.2009.02.032, 2009.
Aiken, A. C., DeCarlo, P. F., Kroll, J. H., Worsnop, D. R., Huffman, J. A., Docherty, K. S., Ulbrich, I. M., Mohr, C., Kimmel, J. R., Sueper, D., Sun, Y., Zhang, Q., Trimborn, A., Northway, M., Ziemann, P. J., Canagaratna, M. R., Onasch, T. B., Alfarra, M. R., Prevot, A. S. H., Dommen, J., Duplissy, J., Metzger, A., Baltensperger, U., and Jimenez, J. L.:
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
Alvarez, D.: JUWELS Cluster and Booster: Exascale Pathfinder with Modular Supercomputing Architecture at Juelich Supercomputing Centre, Journal of large-scale research facilities JLSRF, 7, https://doi.org/10.17815/jlsrf-7-183, 2021.
Ames, R. B. and Malm, W. C.: Comparison of sulfate and nitrate particle mass concentrations measured by IMPROVE and the CDN, Atmos. Environ., 35, 905-916, https://doi.org/10.1016/s1352-2310(00)00369-1, 2001.
Andreae, M. O. and Rosenfeld, D.: Aerosol-cloud-precipitation interactions. Part 1. The nature and sources of cloud-active aerosols, Earth-Sci. Rev., 89, 13–41, https://doi.org/10.1016/j.earscirev.2008.03.001, 2008.
Anttila, P. and Tuovinen, J. P.: Trends of primary and secondary pollutant concentrations in Finland in 1994–2007, Atmos. Environ., 44, 30–41, https://doi.org/10.1016/j.atmosenv.2009.09.041, 2010.
Astitha, M., Lelieveld, J., Abdel Kader, M., Pozzer, A., and de Meij, A.: Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties, Atmos. Chem. Phys., 12, 11057–11083, https://doi.org/10.5194/acp-12-11057-2012, 2012.
Bacer, S., Sullivan, S. C., Karydis, V. A., Barahona, D., Krämer, M., Nenes, A., Tost, H., Tsimpidi, A. P., Lelieveld, J., and Pozzer, A.: Implementation of a comprehensive ice crystal formation parameterization for cirrus and mixed-phase clouds in the EMAC model (based on MESSy 2.53), Geosci. Model Dev., 11, 4021–4041, https://doi.org/10.5194/gmd-11-4021-2018, 2018.
Batmunkh, T., Kim, Y. J., Lee, K. Y., Cayetano, M. G., Jung, J. S., Kim, S. Y., Kim, K. C., Lee, S. J., Kim, J. S., Chang, L. S., and An, J. Y.: Time-Resolved Measurements of PM2.5 Carbonaceous Aerosols at Gosan, Korea, J. Air Waste Manage. Assoc., 61, 1174–1182, https://doi.org/10.1080/10473289.2011.609761, 2011.
Bian, H., Chin, M., Hauglustaine, D. A., Schulz, M., Myhre, G., Bauer, S. E., Lund, M. T., Karydis, V. A., Kucsera, T. L., Pan, X., Pozzer, A., Skeie, R. B., Steenrod, S. D., Sudo, K., Tsigaridis, K., Tsimpidi, A. P., and Tsyro, S. G.: Investigation of global particulate nitrate from the AeroCom phase III experiment, Atmos. Chem. Phys., 17, 12911–12940, https://doi.org/10.5194/acp-17-12911-2017, 2017.
Bougiatioti, A., Stavroulas, I., Kostenidou, E., Zarmpas, P., Theodosi, C., Kouvarakis, G., Canonaco, F., Prévôt, A. S. H., Nenes, A., Pandis, S. N., and Mihalopoulos, N.: Processing of biomass-burning aerosol in the eastern Mediterranean during summertime, Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, 2014.
Bourotte, C., Curl-Amarante, A. P., Forti, M. C., Pereira, L. A. A., Braga, A. L., and Lotufo, P. A.: Association between ionic composition of fine and coarse aerosol soluble fraction and peak expiratory flow of asthmatic patients in Sao Paulo city (Brazil), Atmos. Environ., 41, 2036–2048, https://doi.org/10.1016/j.atmosenv.2006.11.004, 2007.
Bouwman, A. F., Lee, D. S., Asman, W. A. H., Dentener, F. J., VanderHoek, K. W., and Olivier, J. G. J.: A global high-resolution emission inventory for ammonia, Global Biogeochem. Cy., 11, 561–587, https://doi.org/10.1029/97gb02266, 1997.
Bozzetti, C., El Haddad, I., Salameh, D., Daellenbach, K. R., Fermo, P., Gonzalez, R., Minguillón, M. C., Iinuma, Y., Poulain, L., Elser, M., Müller, E., Slowik, J. G., Jaffrezo, J.-L., Baltensperger, U., Marchand, N., and Prévôt, A. S. H.: Organic aerosol source apportionment by offline-AMS over a full year in Marseille, Atmos. Chem. Phys., 17, 8247–8268, https://doi.org/10.5194/acp-17-8247-2017, 2017.
Brook, R. D., Rajagopalan, S., Pope, C. A., 3rd, Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A., Peters, A., Siscovick, D., Smith, S. C., Jr., Whitsel, L., and Kaufman, J. D.: Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association, Circulation, 121, 2331–2378, https://doi.org/10.1161/CIR.0b013e3181dbece1, 2010.
Budisulistiorini, S. H., Canagaratna, M. R., Croteau, P. L., Marth, W. J., Baumann, K., Edgerton, E. S., Shaw, S. L., Knipping, E. M., Worsnop, D. R., Jayne, J. T., Gold, A., and Surratt, J. D.: Real-Time Continuous Characterization of Secondary Organic Aerosol Derived from Isoprene Epoxydiols in Downtown Atlanta, Georgia, Using the Aerodyne Aerosol Chemical Speciation Monitor, Environ. Sci. Technol., 47, 5686–5694, https://doi.org/10.1021/es400023n, 2013.
Budisulistiorini, S. H., Baumann, K., Edgerton, E. S., Bairai, S. T., Mueller, S., Shaw, S. L., Knipping, E. M., Gold, A., and Surratt, J. D.: Seasonal characterization of submicron aerosol chemical composition and organic aerosol sources in the southeastern United States: Atlanta, Georgia,and Look Rock, Tennessee, Atmos. Chem. Phys., 16, 5171–5189, https://doi.org/10.5194/acp-16-5171-2016, 2016.
Budisulistiorini, S. H., Riva, M., Williams, M., Miyakawa, T., Chen, J., Itoh, M., Surratt, J. D., and Kuwata, M.: Dominant contribution of oxygenated organic aerosol to haze particles from real-time observation in Singapore during an Indonesian wildfire event in 2015, Atmos. Chem. Phys., 18, 16481–16498, https://doi.org/10.5194/acp-18-16481-2018, 2018.
Canagaratna, M. R., Jayne, J. T., Jimenez, J. L., Allan, J. D., Alfarra, M. R., Zhang, Q., Onasch, T. B., Drewnick, F., Coe, H., Middlebrook, A., Delia, A., Williams, L. R., Trimborn, A. M., Northway, M. J., DeCarlo, P. F., Kolb, C. E., Davidovits, P., and Worsnop, D. R.: Chemical and microphysical characterization of ambient aerosols with the aerodyne aerosol mass spectrometer, Mass Spectrom. Rev., 26, 185–222, https://doi.org/10.1002/mas.20115, 2007.
Cash, J. M., Langford, B., Di Marco, C., Mullinger, N. J., Allan, J., Reyes-Villegas, E., Joshi, R., Heal, M. R., Acton, W. J. F., Hewitt, C. N., Misztal, P. K., Drysdale, W., Mandal, T. K., Shivani, Gadi, R., Gurjar, B. R., and Nemitz, E.: Seasonal analysis of submicron aerosol in Old Delhi using high-resolution aerosol mass spectrometry: chemical characterisation, source apportionment and new marker identification, Atmos. Chem. Phys., 21, 10133–10158, https://doi.org/10.5194/acp-21-10133-2021, 2021.
Celis, J. E., Morales, J. R., Zaror, C. A., and Inzunza, J. C.: A study of the particulate matter PM10 composition in the atmosphere of Chillan, Chile, Chemosphere, 54, 541–550, https://doi.org/10.1016/s0045-6535(03)00711-2, 2004.
Chakraborty, A., Bhattu, D., Gupta, T., Tripathi, S. N., and Canagaratna, M. R.: Real-time measurements of ambient aerosols in a polluted Indian city: Sources, characteristics, and processing of organic aerosols during foggy and nonfoggy periods, J. Geophys. Res.-Atmos., 120, 9006–9019, https://doi.org/10.1002/2015JD023419, 2015.
Cheng, I., Zhang, L., He, Z., Cathcart, H., Houle, D., Cole, A., Feng, J., O'Brien, J., Macdonald, A. M., Aherne, J., and Brook, J.: Long-term declines in atmospheric nitrogen and sulfur deposition reduce critical loads exceedances at multiple Canadian rural sites, 2000–-2018, Atmos. Chem. Phys., 22, 14631–14656, https://doi.org/10.5194/acp-22-14631-2022, 2022
Cho, S. Y. and Park, S. S.: Resolving sources of water-soluble organic carbon in fine particulate matter measured at an urban site during winter, Environ. Sci.-Proc. Imp., 15, 524–534, https://doi.org/10.1039/c2em30730h, 2013.
Chow, W. S., Liao, K., Huang, X. H. H., Leung, K. F., Lau, A. K. H., and Yu, J. Z.: Measurement report: The 10-year trend of PM2.5 major components and source tracers from 2008 to 2017 in an urban site of Hong Kong, China, Atmos. Chem. Phys., 22, 11557–11577, https://doi.org/10.5194/acp-22-11557-2022, 2022.
Cottrell, L. D., Griffin, R. J., Jimenez, J. L., Zhang, Q., Ulbrich, I., Ziemba, L. D., Beckman, P. J., Sive, B. C., and Talbot, R. W.: Submicron particles at Thompson Farm during ICARTT measured using aerosol mass spectrometry, J. Geophys. Res.-Atmos., 113, D08212, https://doi.org/10.1029/2007jd009192, 2008.
Crippa, M., Canonaco, F., Lanz, V. A., Äijälä, M., Allan, J. D., Carbone, S., Capes, G., Ceburnis, D., Dall'Osto, M., Day, D. A., DeCarlo, P. F., Ehn, M., Eriksson, A., Freney, E., Hildebrandt Ruiz, L., Hillamo, R., Jimenez, J. L., Junninen, H., Kiendler-Scharr, A., Kortelainen, A.-M., Kulmala, M., Laaksonen, A., Mensah, A. A., Mohr, C., Nemitz, E., O'Dowd, C., Ovadnevaite, J., Pandis, S. N., Petäjä, T., Poulain, L., Saarikoski, S., Sellegri, K., Swietlicki, E., Tiitta, P., Worsnop, D. R., Baltensperger, U., and Prévôt, A. S. H.: Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach, Atmos. Chem. Phys., 14, 6159–6176, https://doi.org/10.5194/acp-14-6159-2014, 2014.
Dalsøren, S. B., Myhre, C. L., Myhre, G., Gomez-Pelaez, A. J., Søvde, O. A., Isaksen, I. S. A., Weiss, R. F., and Harth, C. M.: Atmospheric methane evolution the last 40 years, Atmos. Chem. Phys., 16, 3099–3126, https://doi.org/10.5194/acp-16-3099-2016, 2016.
DeCarlo, P. F., Kimmel, J. R., Trimborn, A., Northway, M. J., Jayne, J. T., Aiken, A. C., Gonin, M., Fuhrer, K., Horvath, T., Docherty, K. S., Worsnop, D. R., and Jimenez, J. L.: Field-deployable, high-resolution, time-of-flight aerosol mass spectrometer, Anal. Chem., 78, 8281–8289, https://doi.org/10.1021/ac061249n, 2006.
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J.-P., Textor, C., Schulz, M., van der Werf, G. R., and Wilson, J.: Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom, Atmos. Chem. Phys., 6, 4321–4344, https://doi.org/10.5194/acp-6-4321-2006, 2006.
de Sá, S. S., Rizzo, L. V., Palm, B. B., Campuzano-Jost, P., Day, D. A., Yee, L. D., Wernis, R., Isaacman-VanWertz, G., Brito, J., Carbone, S., Liu, Y. J., Sedlacek, A., Springston, S., Goldstein, A. H., Barbosa, H. M. J., Alexander, M. L., Artaxo, P., Jimenez, J. L., and Martin, S. T.: Contributions of biomass-burning, urban, and biogenic emissions to the concentrations and light-absorbing properties of particulate matter in central Amazonia during the dry season, Atmos. Chem. Phys., 19, 7973–8001, https://doi.org/10.5194/acp-19-7973-2019, 2019.
Docherty, K. S., Aiken, A. C., Huffman, J. A., Ulbrich, I. M., DeCarlo, P. F., Sueper, D., Worsnop, D. R., Snyder, D. C., Peltier, R. E., Weber, R. J., Grover, B. D., Eatough, D. J., Williams, B. J., Goldstein, A. H., Ziemann, P. J., and Jimenez, J. L.: The 2005 Study of Organic Aerosols at Riverside (SOAR-1): instrumental intercomparisons and fine particle composition, Atmos. Chem. Phys., 11, 12387–12420, https://doi.org/10.5194/acp-11-12387-2011, 2011.
Dominici, F., Peng, R. D., Bell, M. L., Pham, L., McDermott, A., Zeger, S. L., and Samet, J. M.: Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases, JAMA, 295, 1127–1134, https://doi.org/10.1001/jama.295.10.1127, 2006.
Du, W., Sun, Y. L., Xu, Y. S., Jiang, Q., Wang, Q. Q., Yang, W., Wang, F., Bai, Z. P., Zhao, X. D., and Yang, Y. C.: Chemical characterization of submicron aerosol and particle growth events at a national background site (3295 m a.s.l.) on the Tibetan Plateau, Atmos. Chem. Phys., 15, 10811–10824, https://doi.org/10.5194/acp-15-10811-2015, 2015.
EMEP: EMEP Status Report: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components, Norwegian Meterological Institute, https://emep.int/publ/reports/2021/EMEP_Status_Report_1_2021.pdf (last access: 25 August 2025), 2021.
EPA: U.S. Environmental Protection Agency (EPA), Air Pollutant Emissions Trends Data, https://www.epa.gov/air-emissions-inventories/air-pollutant-emissions-trends-data (last access: 25 August 2025), 2025.
Fagerli, H., Tsyro, S., Denby, B., Olivie, D., Nyiri, A., Gauss, M., Simpson, D., Wind, P., Benedictow, A., Mortier, A., Jonson, J., Schulz, M., Kirkevåg, A., Valdebenito, A., Iversen, T., Seland, Ø., Aas, W., Hjellbrekke, A.-G., Solberg, S., and Varma, V.: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components, EMEP Status Report 2016, https://doi.org/10.13140/RG.2.2.27632.46088, 2016.
Fang, T., Guo, H. Y., Zeng, L. H., Verma, V., Nenes, A., and Weber, R. J.: Highly Acidic Ambient Particles, Soluble Metals, and Oxidative Potential: A Link between Sulfate and Aerosol Toxicity, Environ. Sci. Technol., 51, 2611–2620, https://doi.org/10.1021/acs.est.6b06151, 2017.
Favez, O., Cachler, H., Sciare, J., Alfaro, S. C., El-Araby, T. M., Harhash, M. A., and Abdelwahab, M. M.: Seasonality of major aerosol species and their transformations in Cairo megacity, Atmos. Environ., 42, 1503–1516, https://doi.org/10.1016/j.atmosenv.2007.10.081, 2008.
Feng, J., Hu, M., Chan, C. K., Lau, P. S., Fang, M., He, L., and Tang, X.: A comparative study of the organic matter in PM2.5 from three Chinese megacities in three different climatic zones, Atmos. Environ., 40, 3983–3994, https://doi.org/10.1016/j.atmosenv.2006.02.017, 2006.
Fuzzi, S., Decesari, S., Facchini, M. C., Cavalli, F., Emblico, L., Mircea, M., Andreae, M. O., Trebs, I., Hoffer, A., Guyon, P., Artaxo, P., Rizzo, L. V., Lara, L. L., Pauliquevis, T., Maenhaut, W., Raes, N., Chi, X. G., Mayol-Bracero, O. L., Soto-Garcia, L. L., Claeys, M., Kourtchev, I., Rissler, J., Swietlicki, E., Tagliavini, E., Schkolnik, G., Falkovich, A. H., Rudich, Y., Fisch, G., and Gatti, L. V.: Overview of the inorganic and organic composition of size-segregated aerosol in Rondonia, Brazil, from the biomass-burning period to the onset of the wet season, J. Geophys. Res.-Atmos., 112, D01201, https://doi.org/10.1029/2005jd006741, 2007.
George, D. T., Howard, K., Isabella, A.-M., John, B., Robert, D. B., Kevin, C., Sara De, M., Francesco, F., Bertil, F., Mark, W. F., Jonathan, G., Dick, H., Frank, J. K., Nino, K., Robert, L., Annette, P., Sanjay, T. R., David, R., Beate, R., Jonathan, M. S., Thomas, S., Torben, S., Jordi, S., and Bert, B.: A joint ERS/ATS policy statement: what constitutes an adverse health effect of air pollution? An analytical framework, Eur. Respir. J., 49, 1600419, https://doi.org/10.1183/13993003.00419-2016, 2017.
Gioda, A., Amaral, B. S., Monteiro, I. L. G., and Saint'Pierre, T. D.: Chemical composition, sources, solubility, and transport of aerosol trace elements in a tropical region, J. Environ. Monitor., 13, 2134–2142, https://doi.org/10.1039/c1em10240k, 2011.
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi, N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version), Copernicus Atmosphere Monitoring Service (CAMS), Laboratoire d'Aérologie/Claire Granier, https://doi.org/10.24380/d0bn-kx16, 2019.
Guelle, W., Schulz, M., Balkanski, Y., and Dentener, F.: Influence of the source formulation on modeling the atmospheric global distribution of sea salt aerosol, J. Geophys. Res.-Atmos., 106, 27509–27524, https://doi.org/10.1029/2001JD900249, 2001.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Guerreiro, C. B. B., Foltescu, V., and de Leeuw, F.: Air quality status and trends in Europe, Atmos. Environ., 98, 376–384, https://doi.org/10.1016/j.atmosenv.2014.09.017, 2014.
Hand, J., Copeland, S. A., McDade, C., Day, D., Moore, Jr., Dillner, A., Pitchford, M., Indresand, H., Schichtel, B., Malm, W., and Watson, J.: Spatial and seasonal patterns and temporal variability of haze and its constituents in the United States, IMPROVE Report V, https://vista.cira.colostate.edu/improve/wp-content/uploads/2016/08/IMPROVE_V_FullReport.pdf (last access: 25 August 2025), 2011.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543, https://doi.org/10.1029/1999rg000078, 2000.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Huang, X.-F., He, L.-Y., Hu, M., Canagaratna, M. R., Sun, Y., Zhang, Q., Zhu, T., Xue, L., Zeng, L.-W., Liu, X.-G., Zhang, Y.-H., Jayne, J. T., Ng, N. L., and Worsnop, D. R.: Highly time-resolved chemical characterization of atmospheric submicron particles during 2008 Beijing Olympic Games using an Aerodyne High-Resolution Aerosol Mass Spectrometer, Atmos. Chem. Phys., 10, 8933–8945, https://doi.org/10.5194/acp-10-8933-2010, 2010.
IPCC: Climate Change 2013 – The physical science basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781107415324, 2014.
IPCC: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157926, 2023.
Janssen, R. H. H., Tsimpidi, A. P., Karydis, V. A., Pozzer, A., Lelieveld, J., Crippa, M., Prévôt, A. S. H., Ait-Helal, W., Borbon, A., Sauvage, S., and Locoge, N.: Influence of local production and vertical transport on the organic aerosol budget over Paris, J. Geophys. Res.-Atmos., 122, 8276–8296, https://doi.org/10.1002/2016JD026402, 2017.
Jayne, J. T., Leard, D. C., Zhang, X., Davidovits, P., Smith, K. A., Kolb, C. E., and Worsnop, D. R.: Development of an Aerosol Mass Spectrometer for Size and Composition Analysis of Submicron Particles, Aerosol Sci. Tech., 33, 49–70, https://doi.org/10.1080/027868200410840, 2000.
Jöckel, P., Tost, H., Pozzer, A., Brühl, C., Buchholz, J., Ganzeveld, L., Hoor, P., Kerkweg, A., Lawrence, M. G., Sander, R., Steil, B., Stiller, G., Tanarhte, M., Taraborrelli, D., van Aardenne, J., and Lelieveld, J.: The atmospheric chemistry general circulation model ECHAM5/MESSy1: consistent simulation of ozone from the surface to the mesosphere, Atmos. Chem. Phys., 6, 5067–5104, https://doi.org/10.5194/acp-6-5067-2006, 2006.
Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H., Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717–752, https://doi.org/10.5194/gmd-3-717-2010, 2010.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Kakavas, S., Pandis, S. N., and Nenes, A.: ISORROPIA-Lite: A Comprehensive Atmospheric Aerosol Thermodynamics Module for Earth System Models, Tellus B, 74, 1–23, https://doi.org/10.16993/tellusb.33, 2022.
Kanakidou, M., Seinfeld, J. H., Pandis, S. N., Barnes, I., Dentener, F. J., Facchini, M. C., Van Dingenen, R., Ervens, B., Nenes, A., Nielsen, C. J., Swietlicki, E., Putaud, J. P., Balkanski, Y., Fuzzi, S., Horth, J., Moortgat, G. K., Winterhalter, R., Myhre, C. E. L., Tsigaridis, K., Vignati, E., Stephanou, E. G., and Wilson, J.: Organic aerosol and global climate modelling: a review, Atmos. Chem. Phys., 5, 1053–1123, https://doi.org/10.5194/acp-5-1053-2005, 2005.
Karydis, V. A., Tsimpidi, A. P., Pozzer, A., Astitha, M., and Lelieveld, J.: Effects of mineral dust on global atmospheric nitrate concentrations, Atmos. Chem. Phys., 16, 1491–1509, https://doi.org/10.5194/acp-16-1491-2016, 2016.
Karydis, V. A., Tsimpidi, A. P., Bacer, S., Pozzer, A., Nenes, A., and Lelieveld, J.: Global impact of mineral dust on cloud droplet number concentration, Atmos. Chem. Phys., 17, 5601–5621, https://doi.org/10.5194/acp-17-5601-2017, 2017.
Karydis, V. A., Tsimpidi, A. P., Pozzer, A., and Lelieveld, J.: How alkaline compounds control atmospheric aerosol particle acidity, Atmos. Chem. Phys., 21, 14983–15001, https://doi.org/10.5194/acp-21-14983-2021, 2021.
Klingmüller, K., Metzger, S., Abdelkader, M., Karydis, V. A., Stenchikov, G. L., Pozzer, A., and Lelieveld, J.: Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch), Geosci. Model Dev., 11, 989–1008, https://doi.org/10.5194/gmd-11-989-2018, 2018.
Klingmüller, K., Lelieveld, J., Karydis, V. A., and Stenchikov, G. L.: Direct radiative effect of dust–pollution interactions, Atmos. Chem. Phys., 19, 7397–7408, https://doi.org/10.5194/acp-19-7397-2019, 2019.
Klingmüller, K., Karydis, V. A., Bacer, S., Stenchikov, G. L., and Lelieveld, J.: Weaker cooling by aerosols due to dust–pollution interactions, Atmos. Chem. Phys., 20, 15285–15295, https://doi.org/10.5194/acp-20-15285-2020, 2020.
Kok, J. F., Storelvmo, T., Karydis, V. A., Adebiyi, A. A., Mahowald, N. M., Evan, A. T., He, C. L., and Leung, D. M.: Mineral dust aerosol impacts on global climate and climate change, Nature Reviews Earth & Environment, 4, 71–86, https://doi.org/10.1038/s43017-022-00379-5, 2023.
Kostenidou, E., Florou, K., Kaltsonoudis, C., Tsiflikiotou, M., Vratolis, S., Eleftheriadis, K., and Pandis, S. N.: Sources and chemical characterization of organic aerosol during the summer in the eastern Mediterranean, Atmos. Chem. Phys., 15, 11355–11371, https://doi.org/10.5194/acp-15-11355-2015, 2015.
Kuzu, S. L., Yavuz, E., Akyüz, E., Saral, A., Akkoyunlu, B. O., Özdemir, H., Demir, G., and Ünal, A.: Black carbon and size-segregated elemental carbon, organic carbon compositions in a megacity: a case study for Istanbul, Air Quality, Atmosphere & Health, 13, 827–837, https://doi.org/10.1007/s11869-020-00839-1, 2020.
Kyllönen, K., Vestenius, M., Anttila, P., Makkonen, U., Aurela, M., Wängberg, I., Mastromonaco, M. N., and Hakola, H.: Trends and source apportionment of atmospheric heavy metals at a subarctic site during 1996–2018, Atmos. Environ., 236, 117644, https://doi.org/10.1016/j.atmosenv.2020.117644, 2020.
Lang, P. E., Carslaw, D. C., and Moller, S. J.: A trend analysis approach for air quality network data, Atmos. Environ.-X, 2, 100030, https://doi.org/10.1016/j.aeaoa.2019.100030, 2019.
Lanz, V. A., Alfarra, M. R., Baltensperger, U., Buchmann, B., Hueglin, C., and Prévôt, A. S. H.: Source apportionment of submicron organic aerosols at an urban site by factor analytical modelling of aerosol mass spectra, Atmos. Chem. Phys., 7, 1503–1522, https://doi.org/10.5194/acp-7-1503-2007, 2007.
Lanz, V. A., Alfarra, M. R., Baltensperger, U., Buchmann, B., Hueglin, C., Szidat, S., Wehrli, M. N., Wacker, L., Weimer, S., Caseiro, A., Puxbaum, H., and Prevot, A. S. H.: Source attribution of submicron organic aerosols during wintertime inversions by advanced factor analysis of aerosol mass spectra, Environ. Sci. Technol., 42, 214–220, https://doi.org/10.1021/es0707207, 2008.
Lanz, V. A., Prévôt, A. S. H., Alfarra, M. R., Weimer, S., Mohr, C., DeCarlo, P. F., Gianini, M. F. D., Hueglin, C., Schneider, J., Favez, O., D'Anna, B., George, C., and Baltensperger, U.: Characterization of aerosol chemical composition with aerosol mass spectrometry in Central Europe: an overview, Atmos. Chem. Phys., 10, 10453–10471, https://doi.org/10.5194/acp-10-10453-2010, 2010.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The contribution of outdoor air pollution sources to premature mortality on a global scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015.
Li, L., Wang, W., Feng, J., Zhang, D., Li, H., Gu, Z., Wang, B., Sheng, G., and Fu, J.: Composition, source, mass closure of PM2.5 aerosols for four forests in eastern China, J. Environ. Sci., 22, 405–412, https://doi.org/10.1016/s1001-0742(09)60122-4, 2010.
Liu, X., Lara, R., Dufresne, M., Wu, L., Zhang, X., Wang, T., Monge, M., Reche, C., Di Leo, A., Lanzani, G., Colombi, C., Font, A., Sheehan, A., Green, D. C., Makkonen, U., Sauvage, S., Salameh, T., Petit, J.-E., Chatain, M., Coe, H., Hou, S., Harrison, R., Hopke, P. K., Petäjä, T., Alastuey, A., and Querol, X.: Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK), Environ. Int., 185, 108519, https://doi.org/10.1016/j.envint.2024.108519, 2024.
Lohmann, U. and Ferrachat, S.: Impact of parametric uncertainties on the present-day climate and on the anthropogenic aerosol effect, Atmos. Chem. Phys., 10, 11373–11383, https://doi.org/10.5194/acp-10-11373-2010, 2010.
Mallet, M. D., D'Anna, B., Même, A., Bove, M. C., Cassola, F., Pace, G., Desboeufs, K., Di Biagio, C., Doussin, J.-F., Maille, M., Massabò, D., Sciare, J., Zapf, P., di Sarra, A. G., and Formenti, P.: Summertime surface PM1 aerosol composition and size by source region at the Lampedusa island in the central Mediterranean Sea, Atmos. Chem. Phys., 19, 11123–11142, https://doi.org/10.5194/acp-19-11123-2019, 2019.
Mariani, R. L. and de Mello, W. Z.: PM2.5-10, PM2.5 and associated water-soluble inorganic species at a coastal urban site in the metropolitan region of Rio de Janeiro, Atmos. Environ., 41, 2887–2892, https://doi.org/10.1016/j.atmosenv.2006.12.009, 2007.
Martin, S. T., Andreae, M. O., Artaxo, P., Baumgardner, D., Chen, Q., Goldstein, A. H., Guenther, A., Heald, C. L., Mayol-Bracero, O. L., McMurry, P. H., Pauliquevis, T., Poschl, U., Prather, K. A., Roberts, G. C., Saleska, S. R., Dias, M. A. S., Spracklen, D. V., Swietlicki, E., and Trebs, I.: Sources and Properties of Amazonian Aerosol Particles, Rev. Geophys., 48, RG2002, https://doi.org/10.1029/2008rg000280, 2010.
Milousis, A., Tsimpidi, A. P., Tost, H., Pandis, S. N., Nenes, A., Kiendler-Scharr, A., and Karydis, V. A.: Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity, Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, 2024.
Mkoma, S. L., Maenhaut, W., Chi, X. G., Wang, W., and Raes, N.: Characterisation of PM10 atmospheric aerosols for the wet season 2005 at two sites in East Africa, Atmos. Environ., 43, 631–639, https://doi.org/10.1016/j.atmosenv.2008.10.008, 2009.
Mohr, C., DeCarlo, P. F., Heringa, M. F., Chirico, R., Slowik, J. G., Richter, R., Reche, C., Alastuey, A., Querol, X., Seco, R., Peñuelas, J., Jiménez, J. L., Crippa, M., Zimmermann, R., Baltensperger, U., and Prévôt, A. S. H.: Identification and quantification of organic aerosol from cooking and other sources in Barcelona using aerosol mass spectrometer data, Atmos. Chem. Phys., 12, 1649–1665, https://doi.org/10.5194/acp-12-1649-2012, 2012.
Molina, L. T., Kolb, C. E., de Foy, B., Lamb, B. K., Brune, W. H., Jimenez, J. L., Ramos-Villegas, R., Sarmiento, J., Paramo-Figueroa, V. H., Cardenas, B., Gutierrez-Avedoy, V., and Molina, M. J.: Air quality in North America's most populous city – overview of the MCMA-2003 campaign, Atmos. Chem. Phys., 7, 2447–2473, https://doi.org/10.5194/acp-7-2447-2007, 2007.
Molina, L. T., Madronich, S., Gaffney, J. S., Apel, E., de Foy, B., Fast, J., Ferrare, R., Herndon, S., Jimenez, J. L., Lamb, B., Osornio-Vargas, A. R., Russell, P., Schauer, J. J., Stevens, P. S., Volkamer, R., and Zavala, M.: An overview of the MILAGRO 2006 Campaign: Mexico City emissions and their transport and transformation, Atmos. Chem. Phys., 10, 8697–8760, https://doi.org/10.5194/acp-10-8697-2010, 2010.
Ng, N. L., Canagaratna, M. R., Zhang, Q., Jimenez, J. L., Tian, J., Ulbrich, I. M., Kroll, J. H., Docherty, K. S., Chhabra, P. S., Bahreini, R., Murphy, S. M., Seinfeld, J. H., Hildebrandt, L., Donahue, N. M., DeCarlo, P. F., Lanz, V. A., Prévôt, A. S. H., Dinar, E., Rudich, Y., and Worsnop, D. R.: Organic aerosol components observed in Northern Hemispheric datasets from Aerosol Mass Spectrometry, Atmos. Chem. Phys., 10, 4625–4641, https://doi.org/10.5194/acp-10-4625-2010, 2010.
Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Zhang, Q., Ulbrich, I. M., and Worsnop, D. R.: Real-Time Methods for Estimating Organic Component Mass Concentrations from Aerosol Mass Spectrometer Data, Environ. Sci. Technol., 45, 910–916, https://doi.org/10.1021/es102951k, 2011.
Paatero, P.: Least squares formulation of robust non-negative factor analysis, Chemometr. Intell. Lab., 37, 23–35, https://doi.org/10.1016/s0169-7439(96)00044-5, 1997.
Paatero, P.: The Multilinear Engine – A Table-Driven, Least Squares Program for Solving Multilinear Problems, Including the n-Way Parallel Factor Analysis Model, J. Comput. Graph. Stat., 8, 854–888, https://doi.org/10.1080/10618600.1999.10474853, 1999.
Paatero, P. and Tapper, U.: Positive matrix factorization-A nonnegative factor model with optimal utilization of error-estimates of data values, Environmetrics, 5, 111–126, https://doi.org/10.1002/env.3170050203, 1994.
Parworth, C., Fast, J., Mei, F., Shippert, T., Sivaraman, C., Tilp, A., Watson, T., and Zhang, Q.: Long-term measurements of submicrometer aerosol chemistry at the Southern Great Plains (SGP) using an Aerosol Chemical Speciation Monitor (ACSM), Atmos. Environ., 106, 43–55, https://doi.org/10.1016/j.atmosenv.2015.01.060, 2015.
Pathak, R. K., Wang, T., Ho, K. F., and Lee, S. C.: Characteristics of summertime PM2.5 organic and elemental carbon in four major Chinese cities: Implications of high acidity for water-soluble organic carbon (WSOC), Atmos. Environ., 45, 318–325, https://doi.org/10.1016/j.atmosenv.2010.10.021, 2011.
Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze, D. K.: Ammonia emissions in the United States, European Union, and China derived by high-resolution inversion of ammonium wet deposition data: Interpretation with a new agricultural emissions inventory (MASAGE_NH3), J. Geophys. Res.-Atmos., 119, 4343–4364, https://doi.org/10.1002/2013JD021130, 2014.
Petit, J.-E., Favez, O., Sciare, J., Crenn, V., Sarda-Estève, R., Bonnaire, N., Močnik, G., Dupont, J.-C., Haeffelin, M., and Leoz-Garziandia, E.: Two years of near real-time chemical composition of submicron aerosols in the region of Paris using an Aerosol Chemical Speciation Monitor (ACSM) and a multi-wavelength Aethalometer, Atmos. Chem. Phys., 15, 2985–3005, https://doi.org/10.5194/acp-15-2985-2015, 2015.
Pope, C. A., Ezzati, M., and Dockery, D. W.: Fine-Particulate Air Pollution and Life Expectancy in the United States, New Engl. J. Med., 360, 376–386, https://doi.org/10.1056/NEJMsa0805646, 2009.
Pozzer, A., Jöckel, P., Sander, R., Williams, J., Ganzeveld, L., and Lelieveld, J.: Technical Note: The MESSy-submodel AIRSEA calculating the air-sea exchange of chemical species, Atmos. Chem. Phys., 6, 5435–5444, https://doi.org/10.5194/acp-6-5435-2006, 2006.
Pozzer, A., Reifenberg, S. F., Kumar, V., Franco, B., Kohl, M., Taraborrelli, D., Gromov, S., Ehrhart, S., Jöckel, P., Sander, R., Fall, V., Rosanka, S., Karydis, V., Akritidis, D., Emmerichs, T., Crippa, M., Guizzardi, D., Kaiser, J. W., Clarisse, L., Kiendler-Scharr, A., Tost, H., and Tsimpidi, A.: Simulation of organics in the atmosphere: evaluation of EMACv2.54 with the Mainz Organic Mechanism (MOM) coupled to the ORACLE (v1.0) submodel, Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, 2022.
Price, C. and Rind, D.: A Simple Lightning Parameterization for Calculating Global Lightning Distributions, J. Geophys. Res.-Atmos., 97, 9919–9933, 1992.
Pringle, K. J., Tost, H., Message, S., Steil, B., Giannadaki, D., Nenes, A., Fountoukis, C., Stier, P., Vignati, E., and Lelieveld, J.: Description and evaluation of GMXe: a new aerosol submodel for global simulations (v1), Geosci. Model Dev., 3, 391–412, https://doi.org/10.5194/gmd-3-391-2010, 2010.
Radhi, M., Box, M. A., Box, G. P., Mitchell, R. M., Cohen, D. D., Stelcer, E., and Keywood, M. D.: Optical, physical and chemical characteristics of Australian continental aerosols: results from a field experiment, Atmos. Chem. Phys., 10, 5925–5942, https://doi.org/10.5194/acp-10-5925-2010, 2010.
Rattanavaraha, W., Canagaratna, M. R., Budisulistiorini, S. H., Croteau, P. L., Baumann, K., Canonaco, F., Prevot, A. S. H., Edgerton, E. S., Zhang, Z., Jayne, J. T., Worsnop, D. R., Gold, A., Shaw, S. L., and Surratt, J. D.: Source apportionment of submicron organic aerosol collected from Atlanta, Georgia, during 2014–2015 using the aerosol chemical speciation monitor (ACSM), Atmos. Environ., 167, 389–402, https://doi.org/10.1016/j.atmosenv.2017.07.055, 2017.
Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh, L., Manzini, E., Schlese, U., and Schulzweida, U.: Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model, J. Climate, 19, 3771–3791, https://doi.org/10.1175/jcli3824.1, 2006.
Sander, R., Baumgaertner, A., Cabrera-Perez, D., Frank, F., Gromov, S., Grooß, J.-U., Harder, H., Huijnen, V., Jöckel, P., Karydis, V. A., Niemeyer, K. E., Pozzer, A., Riede, H., Schultz, M. G., Taraborrelli, D., and Tauer, S.: The community atmospheric chemistry box model CAABA/MECCA-4.0, Geosci. Model Dev., 12, 1365–1385, https://doi.org/10.5194/gmd-12-1365-2019, 2019.
Schlag, P., Kiendler-Scharr, A., Blom, M. J., Canonaco, F., Henzing, J. S., Moerman, M., Prévôt, A. S. H., and Holzinger, R.: Aerosol source apportionment from 1-year measurements at the CESAR tower in Cabauw, the Netherlands, Atmos. Chem. Phys., 16, 8831–8847, https://doi.org/10.5194/acp-16-8831-2016, 2016.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Second, John Wiley & Sons, Inc., Hoboken, New Jersey, ISBN 0471720186, 2006.
Snider, G., Weagle, C. L., Martin, R. V., van Donkelaar, A., Conrad, K., Cunningham, D., Gordon, C., Zwicker, M., Akoshile, C., Artaxo, P., Anh, N. X., Brook, J., Dong, J., Garland, R. M., Greenwald, R., Griffith, D., He, K., Holben, B. N., Kahn, R., Koren, I., Lagrosas, N., Lestari, P., Ma, Z., Vanderlei Martins, J., Quel, E. J., Rudich, Y., Salam, A., Tripathi, S. N., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., and Liu, Y.: SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications, Atmos. Meas. Tech., 8, 505–521, https://doi.org/10.5194/amt-8-505-2015, 2015.
Snider, G., Weagle, C. L., Murdymootoo, K. K., Ring, A., Ritchie, Y., Stone, E., Walsh, A., Akoshile, C., Anh, N. X., Balasubramanian, R., Brook, J., Qonitan, F. D., Dong, J., Griffith, D., He, K., Holben, B. N., Kahn, R., Lagrosas, N., Lestari, P., Ma, Z., Misra, A., Norford, L. K., Quel, E. J., Salam, A., Schichtel, B., Segev, L., Tripathi, S., Wang, C., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., Liu, Y., Martins, J. V., Rudich, Y., and Martin, R. V.: Variation in global chemical composition of PM2.5: emerging results from SPARTAN, Atmos. Chem. Phys., 16, 9629–9653, https://doi.org/10.5194/acp-16-9629-2016, 2016.
Solomon, P. A., Crumpler, D., Flanagan, J. B., Jayanty, R. K. M., Rickman, E. E., and McDade, C. E.: US National PM2.5 Chemical Speciation Monitoring Networks-CSN and IMPROVE: Description of networks, J. Air Waste Manage. Assoc., 64, 1410–1438, https://doi.org/10.1080/10962247.2014.956904, 2014.
Souza, P. A. d., Mello, W. Z. d., Mariani, R. L., and Sella, S. M.: Caracterização do material particulado fino e grosso e composição da fração inorgânica solúvel em água em São José dos Campos (SP), Quím. Nova, 33, 1247–1253, 2010.
Stavroulas, I., Bougiatioti, A., Grivas, G., Paraskevopoulou, D., Tsagkaraki, M., Zarmpas, P., Liakakou, E., Gerasopoulos, E., and Mihalopoulos, N.: Sources and processes that control the submicron organic aerosol composition in an urban Mediterranean environment (Athens): a high temporal-resolution chemical composition measurement study, Atmos. Chem. Phys., 19, 901–919, https://doi.org/10.5194/acp-19-901-2019, 2019.
Sun, Y., Xu, W., Zhang, Q., Jiang, Q., Canonaco, F., Prévôt, A. S. H., Fu, P., Li, J., Jayne, J., Worsnop, D. R., and Wang, Z.: Source apportionment of organic aerosol from 2-year highly time-resolved measurements by an aerosol chemical speciation monitor in Beijing, China, Atmos. Chem. Phys., 18, 8469–8489, https://doi.org/10.5194/acp-18-8469-2018, 2018.
Sun, Y., He, Y., Kuang, Y., Xu, W., Song, S., Ma, N., Tao, J., Cheng, P., Wu, C., Su, H., Cheng, Y., Xie, C., Chen, C., Lei, L., Qiu, Y., Fu, P., Croteau, P., and Worsnop, D. R.: Chemical Differences Between PM1 and PM2.5 in Highly Polluted Environment and Implications in Air Pollution Studies, Geophys. Res. Lett., 47, e2019GL086288, https://doi.org/10.1029/2019GL086288, 2020.
Sun, Y. L., Wang, Z. F., Fu, P. Q., Yang, T., Jiang, Q., Dong, H. B., Li, J., and Jia, J. J.: Aerosol composition, sources and processes during wintertime in Beijing, China, Atmos. Chem. Phys., 13, 4577–4592, https://doi.org/10.5194/acp-13-4577-2013, 2013.
Tiitta, P., Vakkari, V., Croteau, P., Beukes, J. P., van Zyl, P. G., Josipovic, M., Venter, A. D., Jaars, K., Pienaar, J. J., Ng, N. L., Canagaratna, M. R., Jayne, J. T., Kerminen, V.-M., Kokkola, H., Kulmala, M., Laaksonen, A., Worsnop, D. R., and Laakso, L.: Chemical composition, main sources and temporal variability of PM1 aerosols in southern African grassland, Atmos. Chem. Phys., 14, 1909–1927, https://doi.org/10.5194/acp-14-1909-2014, 2014.
Timonen, H., Carbone, S., Aurela, M., Saarnio, K., Saarikoski, S., Ng, N. L., Canagaratna, M. R., Kulmala, M., Kerminen, V.-M., Worsnop, D. R., and Hillamo, R.: Characteristics, sources and water-solubility of ambient submicron organic aerosol in springtime in Helsinki, Finland, J. Aerosol Sci., 56, 61–77, https://doi.org/10.1016/j.jaerosci.2012.06.005, 2013.
Tørseth, K., Aas, W., Breivik, K., Fjæraa, A. M., Fiebig, M., Hjellbrekke, A. G., Lund Myhre, C., Solberg, S., and Yttri, K. E.: Introduction to the European Monitoring and Evaluation Programme (EMEP) and observed atmospheric composition change during 1972–2009, Atmos. Chem. Phys., 12, 5447–5481, https://doi.org/10.5194/acp-12-5447-2012, 2012.
Tsigaridis, K., Daskalakis, N., Kanakidou, M., Adams, P. J., Artaxo, P., Bahadur, R., Balkanski, Y., Bauer, S. E., Bellouin, N., Benedetti, A., Bergman, T., Berntsen, T. K., Beukes, J. P., Bian, H., Carslaw, K. S., Chin, M., Curci, G., Diehl, T., Easter, R. C., Ghan, S. J., Gong, S. L., Hodzic, A., Hoyle, C. R., Iversen, T., Jathar, S., Jimenez, J. L., Kaiser, J. W., Kirkevåg, A., Koch, D., Kokkola, H., Lee, Y. H., Lin, G., Liu, X., Luo, G., Ma, X., Mann, G. W., Mihalopoulos, N., Morcrette, J.-J., Müller, J.-F., Myhre, G., Myriokefalitakis, S., Ng, N. L., O'Donnell, D., Penner, J. E., Pozzoli, L., Pringle, K. J., Russell, L. M., Schulz, M., Sciare, J., Seland, Ø., Shindell, D. T., Sillman, S., Skeie, R. B., Spracklen, D., Stavrakou, T., Steenrod, S. D., Takemura, T., Tiitta, P., Tilmes, S., Tost, H., van Noije, T., van Zyl, P. G., von Salzen, K., Yu, F., Wang, Z., Wang, Z., Zaveri, R. A., Zhang, H., Zhang, K., Zhang, Q., and Zhang, X.: The AeroCom evaluation and intercomparison of organic aerosol in global models, Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, 2014.
Tsimpidi, A. P., Karydis, V. A., Pozzer, A., Pandis, S. N., and Lelieveld, J.: ORACLE (v1.0): module to simulate the organic aerosol composition and evolution in the atmosphere, Geosci. Model Dev., 7, 3153–3172, https://doi.org/10.5194/gmd-7-3153-2014, 2014.
Tsimpidi, A. P., Karydis, V. A., Pandis, S. N., and Lelieveld, J.: Global combustion sources of organic aerosols: model comparison with 84 AMS factor-analysis data sets, Atmos. Chem. Phys., 16, 8939–8962, https://doi.org/10.5194/acp-16-8939-2016, 2016.
Tsimpidi, A. P., Karydis, V. A., Pozzer, A., Pandis, S. N., and Lelieveld, J.: ORACLE 2-D (v2.0): an efficient module to compute the volatility and oxygen content of organic aerosol with a global chemistry–climate model, Geosci. Model Dev., 11, 3369–3389, https://doi.org/10.5194/gmd-11-3369-2018, 2018.
Vasilakopoulou, C. N., Matrali, A., Skyllakou, K., Georgopoulou, M., Aktypis, A., Florou, K., Kaltsonoudis, C., Siouti, E., Kostenidou, E., Błaziak, A., Nenes, A., Papagiannis, S., Eleftheriadis, K., Patoulias, D., Kioutsioukis, I., and Pandis, S. N.: Rapid transformation of wildfire emissions to harmful background aerosol, npj Climate and Atmospheric Science, 6, 218, https://doi.org/10.1038/s41612-023-00544-7, 2023.
Wang, Y., Li, W., Gao, W., Liu, Z., Tian, S., Shen, R., Ji, D., Wang, S., Wang, L., Tang, G., Song, T., Cheng, M., Wang, G., Gong, Z., Hao, J., and Zhang, Y.: Trends in particulate matter and its chemical compositions in China from 2013–2017, Science China Earth Sciences, 62, 1857–1871, https://doi.org/10.1007/s11430-018-9373-1, 2019.
Wang, X., Tsimpidi, A. P., Luo, Z., Steil, B., Pozzer, A., Lelieveld, J., and Karydis, V. A.: The influence of ammonia emissions on the size-resolved global atmospheric aerosol composition and acidity, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-527, 2025.
Weinstein, J. P., Hedges, S. R., and Kimbrough, S.: Characterization and aerosol mass balance of PM2.5 and PM10 collected in Conakry, Guinea during the 2004 Harmattan period, Chemosphere, 78, 980–988, https://doi.org/10.1016/j.chemosphere.2009.12.022, 2010.
WHO: Health aspects of air pollution with particulate matter, ozone and nitrogen dioxide: report on a WHO working group, Bonn, Germany, 13–15 January 2003, https://iris.who.int/handle/10665/107478 (last access: 25 August 2025), 2003.
WHO: WHO global air quality guidelines: Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide, https://iris.who.int/bitstream/handle/10665/345329/9789240034228-eng.pdf (last access: 25 August 2025), 2021.
WHO: Ambient (outdoor) air pollution, https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health, last access: 15 September 2024.
Xu, L., Suresh, S., Guo, H., Weber, R. J., and Ng, N. L.: Aerosol characterization over the southeastern United States using high-resolution aerosol mass spectrometry: spatial and seasonal variation of aerosol composition and sources with a focus on organic nitrates, Atmos. Chem. Phys., 15, 7307–7336, https://doi.org/10.5194/acp-15-7307-2015, 2015.
Xu, W., Sun, Y., Wang, Q., Zhao, J., Wang, J., Ge, X., Xie, C., Zhou, W., Du, W., Li, J., Fu, P., Wang, Z., Worsnop, D. R., and Coe, H.: Changes in Aerosol Chemistry From 2014 to 2016 in Winter in Beijing: Insights From High-Resolution Aerosol Mass Spectrometry, J. Geophys. Res.-Atmos., 124, 1132–1147, https://doi.org/10.1029/2018JD029245, 2019.
Yang, Y., Smith, S. J., Wang, H., Lou, S., and Rasch, P. J.: Impact of Anthropogenic Emission Injection Height Uncertainty on Global Sulfur Dioxide and Aerosol Distribution, J. Geophys. Res.-Atmos., 124, 4812–4826, https://doi.org/10.1029/2018JD030001, 2019.
Yao, X. and Zhang, L.: Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches, Atmos. Chem. Phys., 24, 7773–7791, https://doi.org/10.5194/acp-24-7773-2024, 2024.
Yienger, J. J. and Levy, H.: Empirical-model of global soil-biogenic NOx emissions, J. Geophys. Res.-Atmos., 100, 11447–11464, https://doi.org/10.1029/95jd00370, 1995.
Zhai, S., Jacob, D. J., Wang, X., Shen, L., Li, K., Zhang, Y., Gui, K., Zhao, T., and Liao, H.: Fine particulate matter (PM2.5) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology, Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, 2019.
Zhang, F., Xu, L., Chen, J., Yu, Y., Niu, Z., and Yin, L.: Chemical compositions and extinction coefficients of PM2.5 in peri-urban of Xiamen, China, during June 2009–May 2010, Atmos. Res., 106, 150–158, https://doi.org/10.1016/j.atmosres.2011.12.005, 2012.
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H., Ulbrich, I., Alfarra, M. R., Takami, A., Middlebrook, A. M., Sun, Y. L., Dzepina, K., Dunlea, E., Docherty, K., DeCarlo, P. F., Salcedo, D., Onasch, T., Jayne, J. T., Miyoshi, T., Shimono, A., Hatakeyama, S., Takegawa, N., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian, K., Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R. J., Rautiainen, J., Sun, J. Y., Zhang, Y. M., and Worsnop, D. R.: Ubiquity and dominance of oxygenated species in organic aerosols in anthropogenically-influenced Northern Hemisphere midlatitudes, Geophys. Res. Lett., 34, L13801, https://doi.org/10.1029/2007gl029979, 2007.
Zhang, Y., Sun, J., Zhang, X., Shen, X., Wang, T., and Qin, M.: Seasonal characterization of components and size distributions for submicron aerosols in Beijing, Science China Earth Sciences, 56, 890–900, https://doi.org/10.1007/s11430-012-4515-z, 2013.
Zhang, Y., Tang, L., Yu, H., Wang, Z., Sun, Y., Qin, W., Chen, W., Chen, C., Ding, A., Wu, J., Ge, S., Chen, C., and Zhou, H.-C.: Chemical composition, sources and evolution processes of aerosol at an urban site in Yangtze River Delta, China during wintertime, Atmos. Environ., 123, 339–349, https://doi.org/10.1016/j.atmosenv.2015.08.017, 2015a.
Zhang, Y. J., Tang, L. L., Wang, Z., Yu, H. X., Sun, Y. L., Liu, D., Qin, W., Canonaco, F., Prévôt, A. S. H., Zhang, H. L., and Zhou, H. C.: Insights into characteristics, sources, and evolution of submicron aerosols during harvest seasons in the Yangtze River delta region, China, Atmos. Chem. Phys., 15, 1331–1349, https://doi.org/10.5194/acp-15-1331-2015, 2015b.
Zhang, Y. M., Zhang, X. Y., Sun, J. Y., Hu, G. Y., Shen, X. J., Wang, Y. Q., Wang, T. T., Wang, D. Z., and Zhao, Y.: Chemical composition and mass size distribution of PM1 at an elevated site in central east China, Atmos. Chem. Phys., 14, 12237–12249, https://doi.org/10.5194/acp-14-12237-2014, 2014.
Zhao, P. S., Dong, F., He, D., Zhao, X. J., Zhang, X. L., Zhang, W. Z., Yao, Q., and Liu, H. Y.: Characteristics of concentrations and chemical compositions for PM2.5 in the region of Beijing, Tianjin, and Hebei, China, Atmos. Chem. Phys., 13, 4631–4644, https://doi.org/10.5194/acp-13-4631-2013, 2013.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zhou, W., Xu, W., Kim, H., Zhang, Q., Fu, P., Worsnop, D. R., and Sun, Y.: A review of aerosol chemistry in Asia: insights from aerosol mass spectrometer measurements, Environ. Sci.-Proc. Imp., 22, 1616–1653, https://doi.org/10.1039/D0EM00212G, 2020a.
Zhou, W., Xu, W., Kim, H., Zhang, Q., Fu, P., Worsnop, D. R., and Sun, Y.: A review of aerosol chemistry in Asia: insights from aerosol mass spectrometer measurements, Environ. Sci.-Proc. Imp., 22, 1616–1653, https://doi.org/10.1039/d0em00212g, 2020b.
Short summary
This study examines global changes in air pollution from 2000 to 2020, focusing on fine aerosols that impact climate and health. Using models and global data, it finds that organic aerosols dominate in many regions, especially with wildfires or natural emissions. Pollution from sulfate and nitrate has decreased in Europe and North America due to regulations, while trends in Asia are more complex. The findings improve understanding and support policies for cleaner air and healthier environments.
This study examines global changes in air pollution from 2000 to 2020, focusing on fine aerosols...
Altmetrics
Final-revised paper
Preprint