Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7791-2022
© 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-15-7791-2022
© 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
| 
24 Oct 2022
Development and technical paper |
| 24 Oct 2022
| 24 Oct 2022
Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
Li Fang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Arjo Segers
TNO, Department of Climate, Air and Sustainability, Utrecht, the Netherlands
Hai Xiang Lin
Institute of Environmental Sciences, Leiden University, Leiden, the Netherlands
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
Mijie Pang
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Cong Xiao
Key Laboratory of Petroleum Engineering, Ministry of Education, China University of Petroleum, Beijing, China
Tuo Deng
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
Hong Liao
CORRESPONDING AUTHOR
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
Related authors
Ji Xia, Yi Zhou, Li Fang, Yingfei Qi, Dehao Li, Hong Liao, and Jianbing Jin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3938, https://doi.org/10.5194/egusphere-2024-3938, 2025
Short summary
Short summary
This study established an ammonia emission inventory in South Asia via assimilation-based inversion system. The posterior emissions, calculated by integrating the CEDS inventory and IASI satellite observations, showed significant improvement over the prior. Validation against various measurements all support our posterior emission. It offers valuable insights of ammonia emissions for policymakers and researchers aiming to develop air quality management and mitigation strategies there.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
Short summary
Short summary
Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
Short summary
Short summary
Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Dehao Li, Jianbing Jin, Guoqiang Wang, Mijie Pang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-2186, https://doi.org/10.5194/egusphere-2025-2186, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Efficient air quality modeling in future emission scenarios is vital for air pollution policies. Restricted by model structure, previous methods are computationally expensive or focus on single target. Thus, based on advanced machine learning framework "Transformer", this study introduces a rapid GEOS-Chem proxy model "TGEOS v1.0". Its predictions are similar to the GEOS-Chem v14.2.2 output. It can also predict the probability distributions of PM2.5 and O3 under various emission scenarios.
Xueqing Wang, Jia Zhu, Guanjie Jiao, Xi Chen, Zhenjiang Yang, Lei Chen, Xipeng Jin, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-1880, https://doi.org/10.5194/egusphere-2025-1880, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Impacts of meteorology on ozone vary with diverse meteorological datasets and analytical methods. Uncertainties of meteorology-driven ozone trends in China were examined. Multi-dataset analysis shows the largest meteorology-driven ozone trend with the best consistency occurs in spring. Multi-method analysis shows the best (worst) consistency occurs in winter (summer). Overall, meteorology boosts ozone growth in all seasons, with uncertainty from multi-method larger than that from multi-dataset.
Keqin Tang, Haoran Zhang, Ge Xu, Fengyi Chang, Yang Xu, Ji Miao, Xian Cui, Jianbin Jin, Baojie Li, Ke Li, Hong Liao, and Nan Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-1407, https://doi.org/10.5194/egusphere-2025-1407, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Our research combined satellite observations with air quality modeling to establish a high-resolution ammonia emission inventory for Eastern China. Reducing ammonia emissions could lower particulate pollution levels by 1.5~8.8 micrograms per cubic meter and reduce related health risks. Meanwhile, sensitivity simulations highlight the critical need to non-agricultural emission controls for effective particulate mitigation.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Canjie Xu, Jianbing Jin, Ke Li, Yinfei Qi, Ji Xia, Hai Xiang Lin, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-140, https://doi.org/10.5194/egusphere-2025-140, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study optimizes non-methane volatile organic compound (NMVOC) emissions in China using satellite formaldehyde retrievals. A semi-variogram spatial analysis demonstrated the advantages of TROPOMI and OMPS products over the conventional OMI. Emission inversion was applied, resulting in better emission inventories. The optimized results significantly enhance model simulations of NMVOCs and ozone, with notable accuracy improvements nationwide, especially in polluted regions like NCP.
Nadia K. Colombi, Daniel J. Jacob, Xingpei Ye, Robert M. Yantosca, Kelvin H. Bates, Drew C. Pendergrass, Laura Hyesung Yang, Ke Li, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-1799, https://doi.org/10.5194/egusphere-2025-1799, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Surface ozone pollution in East Asia is among the highest in the world and has risen steadily over the past two decades. Using aircraft observations and a global 3-D chemical transport model, we show that ozone in the lower atmosphere in East Asia has risen in part due to intensified transport from the upper atmosphere. This rising natural background limits the effectiveness of local pollution controls, with major implications for air quality policy.
Yufen Wang, Ke Li, Xi Chen, Zhenjiang Yang, Minglong Tang, Pascoal M. D. Campos, Yang Yang, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 25, 4455–4475, https://doi.org/10.5194/acp-25-4455-2025, https://doi.org/10.5194/acp-25-4455-2025, 2025
Short summary
Short summary
The impacts of biomass burning and anthropogenic emissions on high tropospheric ozone levels are not well studied in southern Africa. We combined model simulations with recent observations at the surface and from space to quantify tropospheric ozone and its drivers in southern Africa. Our work focuses on the impact of emissions from different sources at different spatial scales, contributing to a comprehensive understanding of air pollution drivers and their uncertainties in southern Africa.
Marc Guevara, Augustin Colette, Antoine Guion, Valentin Petiot, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Andrea Bolignano, Paula Camps, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Hugo Denier van der Gon, Gaël Descombes, John Douros, Hilde Fagerli, Yalda Fatahi, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Risto Hänninen, Kaj Hansen, Oriol Jorba, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Victor Lannuque, Frédérik Meleux, Agnes Nyíri, Yuliia Palamarchuk, Carlos Pérez García-Pando, Lennard Robertson, Felicita Russo, Arjo Segers, Mikhail Sofiev, Joanna Struzewska, Renske Timmermans, Andreas Uppstu, Alvaro Valdebenito, and Zhuyun Ye
EGUsphere, https://doi.org/10.5194/egusphere-2025-1287, https://doi.org/10.5194/egusphere-2025-1287, 2025
Short summary
Short summary
Air quality models require hourly emissions to accurately represent dispersion and physico-chemical processes in the atmosphere. Since emission inventories are typically provided at the annual level, emissions are downscaled to a refined temporal resolution using temporal profiles. This study quantifies the impact of using new anthropogenic temporal profiles on the performance of an European air quality multi-model ensemble. Overall, the findings indicate an improvement of the modelling results.
Ling Kang, Hong Liao, Ke Li, Xu Yue, Yang Yang, and Ye Wang
Atmos. Chem. Phys., 25, 3603–3621, https://doi.org/10.5194/acp-25-3603-2025, https://doi.org/10.5194/acp-25-3603-2025, 2025
Short summary
Short summary
Using the model of Global Change and Air Pollution version 2.0, climate change over 2010–2045 under a carbon neutrality scenario is simulated to increase summertime maximum daily 8 h average ozone (O3) levels in eastern China, the North China Plain, and the Yangtze River Delta by 2.3, 4.7, and 3.0 ppbv, respectively. Temperature, radiation, and relative humidity are the key meteorological parameters and net chemical production is the key process in climate-driven O3 increases in eastern China.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Yang Yang, Li You, Hailong Wang, Huimin Li, Pinya Wang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-840, https://doi.org/10.5194/egusphere-2025-840, 2025
Short summary
Short summary
This study used machine learning to predict global and regional temperature changes under carbon neutrality and high emissions from 2015 to 2100.The results show that while carbon neutrality slows long-term warming, it causes short-term warming due to the rapid decline in aerosols. In contrast, greenhouse gases dominate warming in the high-emission scenario. These findings emphasize the important role of aerosols in shaping near-term climate change under carbon-neutral pathways.
Xi Chen, Ke Li, Ting Yang, Xipeng Jin, Lei Chen, Yang Yang, Shuman Zhao, Bo Hu, Bin Zhu, Zifa Wang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2025-430, https://doi.org/10.5194/egusphere-2025-430, 2025
Short summary
Short summary
Aerosol vertical distribution that plays a crucial role in aerosol-photolysis interaction (API) remains underrepresented in chemical models. We integrated lidar and radiosonde observations to constrain the simulated aerosol profiles over North China and quantified the photochemical responses. The increased photolysis rates in the lower layers led to increased ozone and accounted for a 36 %–56 % reduction in API effects, resulting in enhanced atmospheric oxidizing capacity and aerosol formation.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
Short summary
Short summary
The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Ke Li, Rong Tan, Wenhao Qiao, Taegyung Lee, Yufen Wang, Danyuting Zhang, Minglong Tang, Wenqing Zhao, Yixuan Gu, Shaojia Fan, Jinqiang Zhang, Xiaopu Lyu, Likun Xue, Jianming Xu, Zhiqiang Ma, Mohd Talib Latif, Teerachai Amnuaylojaroen, Junsu Gil, Mee-Hye Lee, Juseon Bak, Joowan Kim, Hong Liao, Yugo Kanaya, Xiao Lu, Tatsuya Nagashima, and Ja-Ho Koo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3756, https://doi.org/10.5194/egusphere-2024-3756, 2025
Short summary
Short summary
East Asia and Southeast Asia has been identified as a global hot spot with the fastest ozone increase. This paper presents the most comprehensive observational view of ozone distributions and evolution over East Asia and Southeast Asia across different spatiotemporal scales in the past two decades, which will have important implications for assessing ozone impacts on public health and crop yields, and for developing future ozone control strategies.
Ji Xia, Yi Zhou, Li Fang, Yingfei Qi, Dehao Li, Hong Liao, and Jianbing Jin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3938, https://doi.org/10.5194/egusphere-2024-3938, 2025
Short summary
Short summary
This study established an ammonia emission inventory in South Asia via assimilation-based inversion system. The posterior emissions, calculated by integrating the CEDS inventory and IASI satellite observations, showed significant improvement over the prior. Validation against various measurements all support our posterior emission. It offers valuable insights of ammonia emissions for policymakers and researchers aiming to develop air quality management and mitigation strategies there.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Jiyuan Gao, Yang Yang, Hailong Wang, Pinya Wang, and Hong Liao
EGUsphere, https://doi.org/10.5194/egusphere-2024-3399, https://doi.org/10.5194/egusphere-2024-3399, 2024
Short summary
Short summary
The decline in aerosols in China altered temperature and pressure gradients between the two hemispheres, which intensified the Southern Trade Winds and caused a moisture divergence in Australia, resulting in less rainfall. Reduced surface moisture led to more energy being converted into sensible heat instead of evaporating as latent heat, which raised near-surface temperatures. Our findings offer insights for managing drought and wildfire risks in Australia.
Yueming Cheng, Tie Dai, Junji Cao, Daisuke Goto, Jianbing Jin, Teruyuki Nakajima, and Guangyu Shi
Atmos. Chem. Phys., 24, 12643–12659, https://doi.org/10.5194/acp-24-12643-2024, https://doi.org/10.5194/acp-24-12643-2024, 2024
Short summary
Short summary
In March 2021, east Asia experienced an outbreak of severe dust storms after an absence of 1.5 decades. Here, we innovatively used the time-lagged ground-based aerosol size information with the fixed-lag ensemble Kalman smoother to optimize dust emission and reproduce the dust storm. This work is valuable for not only the quantification of health damage, aviation risks, and profound impacts on the Earth's system but also revealing the climatic driving force and the process of desertification.
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. Discuss., https://doi.org/10.5194/gmd-2024-157, https://doi.org/10.5194/gmd-2024-157, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
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.
Cuini Qi, Pinya Wang, Yang Yang, Huimin Li, Hui Zhang, Lili Ren, Xipeng Jin, Chenchao Zhan, Jianping Tang, and Hong Liao
Atmos. Chem. Phys., 24, 11775–11789, https://doi.org/10.5194/acp-24-11775-2024, https://doi.org/10.5194/acp-24-11775-2024, 2024
Short summary
Short summary
We investigate extremely hot weather impacts on surface ozone over the southeastern coast of China with and without tropical cyclones. Compared to hot days alone, ozone concentration decreased notably in the Yangtze River Delta (YRD) but increased in the Pearl River Delta (PRD) during tropical cyclones and hot days. The YRD benefited from strong and clean sea winds aiding ozone elimination. In contrast, the PRD experienced strong northeasterly winds that potentially transport ozone pollution.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-113, https://doi.org/10.5194/gmd-2024-113, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of model and observation. However, few have addressed the challenges in the prior vertical structure. A variety of 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.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
Short summary
Short summary
The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
Short summary
Short summary
We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Yang Yang, Shaoxuan Mou, Hailong Wang, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 24, 6509–6523, https://doi.org/10.5194/acp-24-6509-2024, https://doi.org/10.5194/acp-24-6509-2024, 2024
Short summary
Short summary
The variations in anthropogenic aerosol concentrations and source contributions and their subsequent radiative impact in major emission regions during historical periods are quantified based on an aerosol-tagging system in E3SMv1. Due to the industrial development and implementation of economic policies, sources of anthropogenic aerosols show different variations, which has important implications for pollution prevention and control measures and decision-making for global collaboration.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
Preprint withdrawn
Short summary
Short summary
Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Hao Yang, Lei Chen, Hong Liao, Jia Zhu, Wenjie Wang, and Xin Li
Atmos. Chem. Phys., 24, 4001–4015, https://doi.org/10.5194/acp-24-4001-2024, https://doi.org/10.5194/acp-24-4001-2024, 2024
Short summary
Short summary
The present study quantifies the response of aerosol–radiation interaction (ARI) to anthropogenic emission reduction from 2013 to 2017, with the main focus on the contribution to changed O3 concentrations over eastern China both in summer and winter using the WRF-Chem model. The weakened ARI due to decreased anthropogenic emission aggravates the summer (winter) O3 pollution by +0.81 ppb (+0.63 ppb), averaged over eastern China.
Feifan Yan, Hang Su, Yafang Cheng, Rujin Huang, Hong Liao, Ting Yang, Yuanyuan Zhu, Shaoqing Zhang, Lifang Sheng, Wenbin Kou, Xinran Zeng, Shengnan Xiang, Xiaohong Yao, Huiwang Gao, and Yang Gao
Atmos. Chem. Phys., 24, 2365–2376, https://doi.org/10.5194/acp-24-2365-2024, https://doi.org/10.5194/acp-24-2365-2024, 2024
Short summary
Short summary
PM2.5 pollution is a major air quality issue deteriorating human health, and previous studies mostly focus on regions like the North China Plain and Yangtze River Delta. However, the characteristics of PM2.5 concentrations between these two regions are studied less often. Focusing on the transport corridor region, we identify an interesting seesaw transport phenomenon with stagnant weather conditions, conducive to PM2.5 accumulation over this region, resulting in large health effects.
Yang Yang, Yang Zhou, Hailong Wang, Mengyun Li, Huimin Li, Pinya Wang, Xu Yue, Ke Li, Jia Zhu, and Hong Liao
Atmos. Chem. Phys., 24, 1177–1191, https://doi.org/10.5194/acp-24-1177-2024, https://doi.org/10.5194/acp-24-1177-2024, 2024
Short summary
Short summary
This study reveals that extreme ozone pollution over the North China Plain and Yangtze River Delta is due to the chemical production related to hot and dry conditions, and the regional transport explains the ozone pollution over the Sichuan Basin and Pearl River Delta. The frequency of meteorological conditions of the extreme ozone pollution increases from the past to the future. The sustainable scenario is the optimal path to retaining clean air in China in the future.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary
Short summary
This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Xiaodong Xie, Jianlin Hu, Momei Qin, Song Guo, Min Hu, Dongsheng Ji, Hongli Wang, Shengrong Lou, Cheng Huang, Chong Liu, Hongliang Zhang, Qi Ying, Hong Liao, and Yuanhang Zhang
Atmos. Chem. Phys., 23, 10563–10578, https://doi.org/10.5194/acp-23-10563-2023, https://doi.org/10.5194/acp-23-10563-2023, 2023
Short summary
Short summary
The atmospheric age of particles reflects how long particles have been formed and suspended in the atmosphere, which is closely associated with the evolution processes of particles. An analysis of the atmospheric age of PM2.5 provides a unique perspective on the evolution processes of different PM2.5 components. The results also shed lights on how to design effective emission control actions under unfavorable meteorological conditions.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
Short summary
Short summary
Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
Short summary
Short summary
We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Zhenxin Liu, Yuanhao Chen, Yuhang Wang, Cheng Liu, Shuhua Liu, and Hong Liao
Geosci. Model Dev., 16, 4385–4403, https://doi.org/10.5194/gmd-16-4385-2023, https://doi.org/10.5194/gmd-16-4385-2023, 2023
Short summary
Short summary
The heterogeneous layout of urban buildings leads to the complex wind field in and over the urban canopy. Large discrepancies between the observations and the current simulations result from misunderstanding the character of the wind field. The Inhomogeneous Wind Scheme in Urban Street (IWSUS) was developed to simulate the heterogeneity of the wind speed in a typical street and then improve the simulated energy budget in the lower atmospheric layer over the urban canopy.
Pengwei Li, Yang Yang, Hailong Wang, Su Li, Ke Li, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 23, 5403–5417, https://doi.org/10.5194/acp-23-5403-2023, https://doi.org/10.5194/acp-23-5403-2023, 2023
Short summary
Short summary
We use a novel technique that can attribute O3 to precursors to investigate O3 changes in the United States during 1995–2019. We found that the US domestic energy and surface transportation emission reductions are primarily responsible for the O3 decrease in summer. In winter, factors such as nitrogen oxide emission reduction in the context of its inhibition of ozone production, increased aviation and shipping activities, and large-scale circulation changes contribute to the O3 increases.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
Short summary
Short summary
Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Nadia K. Colombi, Daniel J. Jacob, Laura Hyesung Yang, Shixian Zhai, Viral Shah, Stuart K. Grange, Robert M. Yantosca, Soontae Kim, and Hong Liao
Atmos. Chem. Phys., 23, 4031–4044, https://doi.org/10.5194/acp-23-4031-2023, https://doi.org/10.5194/acp-23-4031-2023, 2023
Short summary
Short summary
Surface ozone, detrimental to human and ecosystem health, is very high and increasing in South Korea. Using a global model of the atmosphere, we found that emissions from South Korea and China contribute equally to the high ozone observed. We found that in the absence of all anthropogenic emissions over East Asia, ozone is still very high, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Jianbing Jin, Bas Henzing, and Arjo Segers
Atmos. Chem. Phys., 23, 1641–1660, https://doi.org/10.5194/acp-23-1641-2023, https://doi.org/10.5194/acp-23-1641-2023, 2023
Short summary
Short summary
Aerosol models and satellite retrieval algorithms rely on different aerosol size assumptions. In practice, differences between simulations and observations do not always reflect the difference in aerosol amount. To avoid inconsistencies, we designed a hybrid assimilation approach. Different from a standard aerosol optical depth (AOD) assimilation that directly assimilates AODs, the hybrid one estimates aerosol size parameters by assimilating Ängström observations before assimilating the AODs.
Mengyun Li, Yang Yang, Hailong Wang, Huimin Li, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 23, 1533–1544, https://doi.org/10.5194/acp-23-1533-2023, https://doi.org/10.5194/acp-23-1533-2023, 2023
Short summary
Short summary
Using the GEOS-Chem model, the impact of the quasi-biennial oscillation (QBO) on summertime tropospheric O3 in China is investigated. In the warm phases of sea surface temperature anomalies over the eastern tropical Pacific, the QBO has a significant positive correlation with near-surface O3 concentrations over central China. The QBO impacts on O3 pollution in China are mainly a result of changing vertical transport of O3.
Huimin Li, Yang Yang, Jianbing Jin, Hailong Wang, Ke Li, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 23, 1131–1145, https://doi.org/10.5194/acp-23-1131-2023, https://doi.org/10.5194/acp-23-1131-2023, 2023
Short summary
Short summary
Future climate change will aggravate ozone pollution in Asia, especially in high-forcing scenarios. Ozone pollution in China will expand from North China to South China and extend into the cold season in a warmer future. The emphasis of this work is to quantify the impacts of future climate change on O3 pollution in Asia, which is of great significance for future O3 pollution mitigation strategies.
Huibin Dai, Hong Liao, Ke Li, Xu Yue, Yang Yang, Jia Zhu, Jianbing Jin, Baojie Li, and Xingwen Jiang
Atmos. Chem. Phys., 23, 23–39, https://doi.org/10.5194/acp-23-23-2023, https://doi.org/10.5194/acp-23-23-2023, 2023
Short summary
Short summary
We apply the 3-D global chemical transport model (GEOS-Chem) to simulate co-polluted days by O3 and PM2.5 (O3–PM2.5PDs) in Beijing–Tianjin–Hebei in 2013–2020 and investigate the chemical and physical characteristics of O3–PM2.5PDs by composited analyses of such days that are captured by both the observations and the model. We report for the first time the unique features in vertical distributions of aerosols during O3–PM2.5PDs and the physical and chemical characteristics of O3–PM2.5PDs.
Yang Yang, Liangying Zeng, Hailong Wang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 22, 14489–14502, https://doi.org/10.5194/acp-22-14489-2022, https://doi.org/10.5194/acp-22-14489-2022, 2022
Short summary
Short summary
Using an aerosol–climate model, dust pollution in China affected by different spatial and temporal types of El Niño are examined. Both eastern and central Pacific El Niño and short-duration El Niño increase winter dust concentrations over northern China, while long-duration El Niño decreases concentrations. Only long-duration El Niño events can significantly affect dust over China in the following spring. This study has profound implications for air pollution control and dust storm prediction.
Zhenqi Xu, Wei Feng, Yicheng Wang, Haoran Ye, Yuhang Wang, Hong Liao, and Mingjie Xie
Atmos. Chem. Phys., 22, 13739–13752, https://doi.org/10.5194/acp-22-13739-2022, https://doi.org/10.5194/acp-22-13739-2022, 2022
Short summary
Short summary
This work uses a solvent (DMF) that can efficiently dissolve low-volatility OC to examine BrC absorption and sources, which will benefit future investigations on the physicochemical properties of large organic molecules. The study results also shed light on potential sources for methanol-insoluble OC. These results highlight the importance of testing different solvents to investigate the structures and light absorption of low-volatility BrC.
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
Short summary
Short summary
We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Chenguang Tian, Xu Yue, Jun Zhu, Hong Liao, Yang Yang, Yadong Lei, Xinyi Zhou, Hao Zhou, Yimian Ma, and Yang Cao
Atmos. Chem. Phys., 22, 12353–12366, https://doi.org/10.5194/acp-22-12353-2022, https://doi.org/10.5194/acp-22-12353-2022, 2022
Short summary
Short summary
We quantify the impacts of fire aerosols on climate through direct, indirect, and albedo effects. In atmosphere-only simulations, we find global fire aerosols cause surface cooling and rainfall inhibition over many land regions. These fast atmospheric perturbations further lead to a reduction in regional leaf area index and lightning activities. By considering the feedback of fire aerosols on humidity, lightning, and leaf area index, we predict a slight reduction in fire emissions.
Shijie Cui, Dan Dan Huang, Yangzhou Wu, Junfeng Wang, Fuzhen Shen, Jiukun Xian, Yunjiang Zhang, Hongli Wang, Cheng Huang, Hong Liao, and Xinlei Ge
Atmos. Chem. Phys., 22, 8073–8096, https://doi.org/10.5194/acp-22-8073-2022, https://doi.org/10.5194/acp-22-8073-2022, 2022
Short summary
Short summary
Refractory black carbon (rBC) aerosols are important to air quality and climate change. rBC can mix with many other species, which can significantly change its properties and impacts. We used a specific set of techniques to exclusively characterize rBC-containing (rBCc) particles in Shanghai. We elucidated their composition, sources and size distributions and factors that affect their properties. Our findings are very valuable for advancing the understanding of BC and controlling BC pollution.
Sudhanshu Pandey, Sander Houweling, and Arjo Segers
Geosci. Model Dev., 15, 4555–4567, https://doi.org/10.5194/gmd-15-4555-2022, https://doi.org/10.5194/gmd-15-4555-2022, 2022
Short summary
Short summary
Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements. Multidecadal inversions are needed to extract information from the long measurement records of methane. However, multidecadal inversion computations can take months to finish. Here, we demonstrate an order of magnitude improvement in wall clock time for an iterative multidecadal inversion by physical parallelization of chemical transport model.
Xiaohui Wang, Martin Verlaan, Jelmer Veenstra, and Hai Xiang Lin
Ocean Sci., 18, 881–904, https://doi.org/10.5194/os-18-881-2022, https://doi.org/10.5194/os-18-881-2022, 2022
Short summary
Short summary
The accuracy of the Global Tide and Surge Model is significantly affected by some parameters. We correct the bathymetry and bottom friction coefficient with mathematical methods to improve model accuracy. The lack of tide gauge data in many coastal areas affects the correction process. We propose using observations from altimetry tidal products like FES2014 that have higher accuracy than our model to offset the data lack. Model accuracy is greatly improved, especially in the European shelf.
Jiyuan Gao, Yang Yang, Hailong Wang, Pinya Wang, Huimin Li, Mengyun Li, Lili Ren, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 22, 7131–7142, https://doi.org/10.5194/acp-22-7131-2022, https://doi.org/10.5194/acp-22-7131-2022, 2022
Short summary
Short summary
China has been implementing a sequence of policies for clean air since the year 2013. The aerosol decline produced a 0.09 ± 0.10°C warming during 2013–2017 estimated in this study, and the increase in ozone in the lower troposphere during this time period accelerated the warming, leading to a total 0.16 ± 0.15°C temperature increase in eastern China. Residential emission reductions led to a cooling effect because of a substantial decrease in light-absorbing aerosols.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
Short summary
Short summary
Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Haoran Zhang, Nan Li, Keqin Tang, Hong Liao, Chong Shi, Cheng Huang, Hongli Wang, Song Guo, Min Hu, Xinlei Ge, Mindong Chen, Zhenxin Liu, Huan Yu, and Jianlin Hu
Atmos. Chem. Phys., 22, 5495–5514, https://doi.org/10.5194/acp-22-5495-2022, https://doi.org/10.5194/acp-22-5495-2022, 2022
Short summary
Short summary
We developed a new algorithm with low economic/technique costs to identify primary and secondary components of PM2.5. Our model was shown to be reliable by comparison with different observation datasets. We systematically explored the patterns and changes in the secondary PM2.5 pollution in China at large spatial and time scales. We believe that this method is a promising tool for efficiently estimating primary and secondary PM2.5, and has huge potential for future PM mitigation.
Pinya Wang, Yang Yang, Huimin Li, Lei Chen, Ruijun Dang, Daokai Xue, Baojie Li, Jianping Tang, L. Ruby Leung, and Hong Liao
Atmos. Chem. Phys., 22, 4705–4719, https://doi.org/10.5194/acp-22-4705-2022, https://doi.org/10.5194/acp-22-4705-2022, 2022
Short summary
Short summary
China is now suffering from both severe ozone (O3) pollution and heat events. We highlight that North China Plain is the hot spot of the co-occurrences of extremes in O3 and high temperatures in China. Such coupled extremes exhibit an increasing trend during 2014–2019 and will continue to increase until the middle of this century. And the coupled extremes impose more severe health impacts to human than O3 pollution occurring alone because of elevated O3 levels and temperatures.
Hao Yang, Lei Chen, Hong Liao, Jia Zhu, Wenjie Wang, and Xin Li
Atmos. Chem. Phys., 22, 4101–4116, https://doi.org/10.5194/acp-22-4101-2022, https://doi.org/10.5194/acp-22-4101-2022, 2022
Short summary
Short summary
Aerosols can influence O3 through aerosol–radiation interactions, including aerosol–photolysis interaction (API) and aerosol–radiation feedback (ARF). The weakened photolysis rates and changed meteorological conditions reduce surface-layer O3 concentrations by up to 9.3–11.4 ppb, with API and ARF contributing 74.6 %–90.0 % and 10.0 %–25.4 % of the O3 decrease in three episodes, respectively, which indicates that API is the dominant way for O3 reduction related to aerosol–radiation interactions.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
Short summary
Short summary
This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Donglin Chen, Hong Liao, Yang Yang, Lei Chen, Delong Zhao, and Deping Ding
Atmos. Chem. Phys., 22, 1825–1844, https://doi.org/10.5194/acp-22-1825-2022, https://doi.org/10.5194/acp-22-1825-2022, 2022
Short summary
Short summary
The black carbon (BC) vertical profile plays a critical role in BC–meteorology interaction, which also influences PM2.5 concentrations. More BC mass was assigned into high altitudes (above 1000 m) in the model, which resulted in a stronger cooling effect near the surface, a larger temperature inversion below 421 m, more reductions in PBLH, and a larger increase in near-surface PM2.5 in the daytime caused by the direct radiative effect of BC.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972, https://doi.org/10.5194/acp-22-951-2022, https://doi.org/10.5194/acp-22-951-2022, 2022
Short summary
Short summary
CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Yulu Qiu, Zhiqiang Ma, Ke Li, Mengyu Huang, Jiujiang Sheng, Ping Tian, Jia Zhu, Weiwei Pu, Yingxiao Tang, Tingting Han, Huaigang Zhou, and Hong Liao
Atmos. Chem. Phys., 21, 17995–18010, https://doi.org/10.5194/acp-21-17995-2021, https://doi.org/10.5194/acp-21-17995-2021, 2021
Short summary
Short summary
Photochemical pollution over the North China Plain (NCP) is attracting much concern. Our observations at a rural site in the NCP identified high peroxyacetyl nitrate (PAN) concentrations, even on cold days. Increased acetaldehyde concentration and hydroxyl radical production rates drive fast PAN formation. Moreover, our study emphasizes the importance of formaldehyde photolysis in PAN formation and calls for implementing strict volatile organic compound controls after summer over the NCP.
Jianping Guo, Jian Zhang, Kun Yang, Hong Liao, Shaodong Zhang, Kaiming Huang, Yanmin Lv, Jia Shao, Tao Yu, Bing Tong, Jian Li, Tianning Su, Steve H. L. Yim, Ad Stoffelen, Panmao Zhai, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 17079–17097, https://doi.org/10.5194/acp-21-17079-2021, https://doi.org/10.5194/acp-21-17079-2021, 2021
Short summary
Short summary
The planetary boundary layer (PBL) is the lowest part of the troposphere, and boundary layer height (BLH) is the depth of the PBL and is of critical importance to the dispersion of air pollution. The study presents the first near-global BLH climatology by using high-resolution (5-10 m) radiosonde measurements. The variations in BLH exhibit large spatial and temporal dependence, with a peak at 17:00 local solar time. The most promising reanalysis product is ERA-5 in terms of modeling BLH.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
Short summary
Short summary
Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Baojie Li, Lei Chen, Weishou Shen, Jianbing Jin, Teng Wang, Pinya Wang, Yang Yang, and Hong Liao
Atmos. Chem. Phys., 21, 15883–15900, https://doi.org/10.5194/acp-21-15883-2021, https://doi.org/10.5194/acp-21-15883-2021, 2021
Short summary
Short summary
This study focused on improving fertilizer-application-related NH3 emission inventories. We comprehensively evaluated the dates and times of fertilizer application to the major crops in China, improved the spatial allocation methods for NH3 emissions from croplands with different rice types, and established a NH3 emission inventory for mainland China in 2016. The inventory showed a higher level of accuracy than other inventories based on evaluation using the WRF-Chem and observation data.
Lili Ren, Yang Yang, Hailong Wang, Pinya Wang, Lei Chen, Jia Zhu, and Hong Liao
Atmos. Chem. Phys., 21, 15431–15445, https://doi.org/10.5194/acp-21-15431-2021, https://doi.org/10.5194/acp-21-15431-2021, 2021
Short summary
Short summary
Due to the COVID-19 pandemic, human activities were strictly restricted in China. Even though anthropogenic aerosol emissions largely decreased, haze events still occurred. Our results shows that PM2.5 over the North China Plain is largely contributed by local sources. For other regions in China, PM2.5 is largely contributed from nonlocal sources. As emission reduction is a future goal, aerosol long-range transport and unfavorable meteorology are increasingly important to air quality.
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021, https://doi.org/10.5194/gmd-14-5607-2021, 2021
Short summary
Short summary
When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
Chao Qin, Yafeng Gou, Yuhang Wang, Yuhao Mao, Hong Liao, Qin'geng Wang, and Mingjie Xie
Atmos. Chem. Phys., 21, 12141–12153, https://doi.org/10.5194/acp-21-12141-2021, https://doi.org/10.5194/acp-21-12141-2021, 2021
Short summary
Short summary
In this study, we found that the aqueous solution in aerosols is an important absorbing phase for gaseous polyols in the atmosphere, indicating that the dissolution in aerosol liquid water should not be ignored when investigating gas–particle partitioning of water-soluble organics. The exponential increase in effective partitioning coefficients of polyol tracers with sulfate ion concentrations could be attributed to organic–inorganic interactions in the particle phase.
Yadong Lei, Xu Yue, Hong Liao, Lin Zhang, Yang Yang, Hao Zhou, Chenguang Tian, Cheng Gong, Yimian Ma, Lan Gao, and Yang Cao
Atmos. Chem. Phys., 21, 11531–11543, https://doi.org/10.5194/acp-21-11531-2021, https://doi.org/10.5194/acp-21-11531-2021, 2021
Short summary
Short summary
We present the first estimate of ozone enhancement by fire emissions through ozone–vegetation interactions using a fully coupled chemistry–vegetation model (GC-YIBs). In fire-prone areas, fire-induced ozone causes a positive feedback to surface ozone mainly because of the inhibition effects on stomatal conductance.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421, https://doi.org/10.5194/acp-21-11405-2021, https://doi.org/10.5194/acp-21-11405-2021, 2021
Short summary
Short summary
Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
Liangying Zeng, Yang Yang, Hailong Wang, Jing Wang, Jing Li, Lili Ren, Huimin Li, Yang Zhou, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 21, 10745–10761, https://doi.org/10.5194/acp-21-10745-2021, https://doi.org/10.5194/acp-21-10745-2021, 2021
Short summary
Short summary
Using an aerosol–climate model, the impacts of El Niño with different durations on aerosols in China are examined. The modulation on aerosol concentrations and haze days by short-duration El Niño events is 2–3 times more than that by long-duration El Niño events in China. The frequency of short-duration El Niño has been increasing significantly in recent decades, suggesting that El Niño events have exerted increasingly intense modulation on aerosol pollution in China over the past few decades.
Ioanna Skoulidou, Maria-Elissavet Koukouli, Astrid Manders, Arjo Segers, Dimitris Karagkiozidis, Myrto Gratsea, Dimitris Balis, Alkiviadis Bais, Evangelos Gerasopoulos, Trisevgeni Stavrakou, Jos van Geffen, Henk Eskes, and Andreas Richter
Atmos. Chem. Phys., 21, 5269–5288, https://doi.org/10.5194/acp-21-5269-2021, https://doi.org/10.5194/acp-21-5269-2021, 2021
Short summary
Short summary
The performance of LOTOS-EUROS v2.2.001 regional chemical transport model NO2 simulations is investigated over Greece from June to December 2018. Comparison with in situ NO2 measurements shows a spatial correlation coefficient of 0.86, while the model underestimates the concentrations mostly during daytime (12 to 15:00 local time). Further, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and S5P/TROPOMI observations for July and December 2018.
Zhongjing Jiang, Jing Li, Xiao Lu, Cheng Gong, Lin Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 2601–2613, https://doi.org/10.5194/acp-21-2601-2021, https://doi.org/10.5194/acp-21-2601-2021, 2021
Short summary
Short summary
This study demonstrates that the intensity of the western Pacific subtropical high (WPSH), a major synoptic pattern in the northern Pacific during summer, can induce a dipole change in surface ozone pollution over eastern China. Ozone concentration increases in the north and decreases in the south during the strong WPSH phase, and vice versa. The change in chemical processes associated with the WPSH change plays a decisive role, whereas the natural emission of ozone precursors accounts for ~ 30 %.
Maria-Elissavet Koukouli, Ioanna Skoulidou, Andreas Karavias, Isaak Parcharidis, Dimitris Balis, Astrid Manders, Arjo Segers, Henk Eskes, and Jos van Geffen
Atmos. Chem. Phys., 21, 1759–1774, https://doi.org/10.5194/acp-21-1759-2021, https://doi.org/10.5194/acp-21-1759-2021, 2021
Short summary
Short summary
In recent years, satellite observations have contributed to monitoring air quality. During the first COVID-19 lockdown, lower levels of nitrogen dioxide were observed over Greece by S5P/TROPOMI for March and April 2020 (than the preceding year) due to decreased transport emissions. Taking meteorology into account, using LOTOS-EUROS CTM simulations, the resulting decline due to the lockdown was estimated to range between 0 % and −37 % for the five largest Greek cities, with an average of ~ −10 %.
Xinrui Ge, Martijn Schaap, Richard Kranenburg, Arjo Segers, Gert Jan Reinds, Hans Kros, and Wim de Vries
Atmos. Chem. Phys., 20, 16055–16087, https://doi.org/10.5194/acp-20-16055-2020, https://doi.org/10.5194/acp-20-16055-2020, 2020
Short summary
Short summary
This article is about improving the modeling of agricultural ammonia emissions. By considering land use, meteorology and agricultural practices, ammonia emission totals officially reported by countries are distributed in space and time. We illustrated the first step for a better understanding of the variability of ammonia emission, with the possibility of being applied at a European scale, which is of great significance for ammonia budget research and future policy-making.
Jianbing Jin, Arjo Segers, Hong Liao, Arnold Heemink, Richard Kranenburg, and Hai Xiang Lin
Atmos. Chem. Phys., 20, 15207–15225, https://doi.org/10.5194/acp-20-15207-2020, https://doi.org/10.5194/acp-20-15207-2020, 2020
Short summary
Short summary
Data assimilation provides a powerful tool to estimate emission inventories by feeding observations. This emission inversion relies on the correct assumption about the emission uncertainty, which describes the potential spatiotemporal spreads of sources. However, an unrepresentative uncertainty is unavoidable. Especially in the complex dust emission, the uncertainties can hardly all be taken into account. This study reports how adjoint can be used to detect errors in the emission uncertainty.
Yixuan Gu, Fengxia Yan, Jianming Xu, Yuanhao Qu, Wei Gao, Fangfang He, and Hong Liao
Atmos. Chem. Phys., 20, 14361–14375, https://doi.org/10.5194/acp-20-14361-2020, https://doi.org/10.5194/acp-20-14361-2020, 2020
Short summary
Short summary
High levels and statistically insignificant changes of ozone are detected at a remote monitoring site on Sheshan Island in Shanghai, China, from 2012 to 2017; 6-year observations suggest regional transport exerted minimum influence on the offshore oceanic air in September and October. Both city plumes and oceanic air inflows could contribute to ozone enhancements in Shanghai, and the latter are found to lead to 20–30 % increases in urban ozone concentrations based on WRF-Chem simulations.
Ke Li, Daniel J. Jacob, Lu Shen, Xiao Lu, Isabelle De Smedt, and Hong Liao
Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, https://doi.org/10.5194/acp-20-11423-2020, 2020
Short summary
Short summary
Surface summer ozone increased in China from 2013 to 2019 despite new governmental efforts targeting ozone pollution. We find that the ozone increase is mostly due to anthropogenic drivers, although meteorology also plays a role. Further analysis for the North China Plain shows that PM2.5 continued to decrease through 2019, while emissions of volatile organic compounds (VOCs) stayed flat. This could explain the anthropogenic increase in ozone, as PM2.5 scavenges the radical precursors of ozone.
Baozhu Ge, Syuichi Itahashi, Keiichi Sato, Danhui Xu, Junhua Wang, Fan Fan, Qixin Tan, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Jung-Hun Woo, Junichi Kurokawa, Yuepeng Pan, Qizhong Wu, Xuejun Liu, and Zifa Wang
Atmos. Chem. Phys., 20, 10587–10610, https://doi.org/10.5194/acp-20-10587-2020, https://doi.org/10.5194/acp-20-10587-2020, 2020
Short summary
Short summary
Performances of the simulated deposition for different reduced N (Nr) species in China were conducted with the Model Inter-Comparison Study for Asia. Results showed that simulated wet deposition of oxidized N was overestimated in northeastern China and underestimated in south China, but Nr was underpredicted in all regions by all models. Oxidized N has larger uncertainties than Nr, indicating that the chemical reaction process is one of the most importance factors affecting model performance.
Juan Feng, Jianlei Zhu, Jianping Li, and Hong Liao
Atmos. Chem. Phys., 20, 9883–9893, https://doi.org/10.5194/acp-20-9883-2020, https://doi.org/10.5194/acp-20-9883-2020, 2020
Short summary
Short summary
This paper explores the month-to-month variability of aerosol concentrations (ACs) over China. The AC variability is dominated by the monopole mode and the meridional dipole mode. The associated dynamic and thermal impacts of the climate systems are examined to explain their contributions to the formation of the two modes. The result suggests the variations are originating from the tropical Pacific, and extratropical atmospheric systems contribute to the dominant variabilities of ACs over China.
Lili Ren, Yang Yang, Hailong Wang, Rudong Zhang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 20, 9067–9085, https://doi.org/10.5194/acp-20-9067-2020, https://doi.org/10.5194/acp-20-9067-2020, 2020
Short summary
Short summary
Observations show that the concentrations of Arctic aerosols have declined since the early 1980s, which potentially contributed to the recent, rapid Arctic warming. We found that changes in sulfate and black carbon aerosols over the midlatitudes of the Northern Hemisphere had a larger impact on Arctic temperature than other regions and that the aerosol-induced temperature change explained approximately 20 % of the observed Arctic warming during 1980–2018.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
Short summary
Short summary
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Jiani Tan, Joshua S. Fu, Gregory R. Carmichael, Syuichi Itahashi, Zhining Tao, Kan Huang, Xinyi Dong, Kazuyo Yamaji, Tatsuya Nagashima, Xuemei Wang, Yiming Liu, Hyo-Jung Lee, Chuan-Yao Lin, Baozhu Ge, Mizuo Kajino, Jia Zhu, Meigen Zhang, Hong Liao, and Zifa Wang
Atmos. Chem. Phys., 20, 7393–7410, https://doi.org/10.5194/acp-20-7393-2020, https://doi.org/10.5194/acp-20-7393-2020, 2020
Short summary
Short summary
This study evaluated the performance of 12 chemical transport models from MICS-Asia III for predicting the particulate matter (PM) over East Asia. Four model processes were investigated as the possible reasons for model bias with measurements and the factors causing inconsistent predictions of PM from different models: (1) model inputs, (2) gas–particle conversion, (3) dust emission modules and (4) removal mechanisms (wet and dry depositions). The influence of each process was discussed.
Shelley C. van der Graaf, Richard Kranenburg, Arjo J. Segers, Martijn Schaap, and Jan Willem Erisman
Geosci. Model Dev., 13, 2451–2474, https://doi.org/10.5194/gmd-13-2451-2020, https://doi.org/10.5194/gmd-13-2451-2020, 2020
Short summary
Short summary
Chemical transport models (CTMs) are important tools to determine the fate of reactive nitrogen (Nr) emissions. The parameterization of the surface–atmosphere exchange in CTMs is often only linked to fixed, land-use-dependent values. In this paper, we present an approach to derive more realistic, dynamic leaf area index (LAI) and roughness length (z0) input maps using multiple satellite products. We evaluate the effect on Nr concentration and deposition fields modelled in the LOTOS-EUROS CTM.
Cheng Gong, Yadong Lei, Yimian Ma, Xu Yue, and Hong Liao
Atmos. Chem. Phys., 20, 3841–3857, https://doi.org/10.5194/acp-20-3841-2020, https://doi.org/10.5194/acp-20-3841-2020, 2020
Short summary
Short summary
We evaluate ozone–vegetation feedback using a fully coupled chemistry–carbon–climate global model (ModelE2-YIBs). Ozone damage to photosynthesis, stomatal conductance, and isoprene emissions parameterized by different schemes and sensitivities is jointly considered. In general, surface ozone concentrations are increased due to ozone–vegetation interactions, especially over the regions with a high ambient ozone level such as the eastern US, eastern China, and western Europe.
Yadong Lei, Xu Yue, Hong Liao, Cheng Gong, and Lin Zhang
Geosci. Model Dev., 13, 1137–1153, https://doi.org/10.5194/gmd-13-1137-2020, https://doi.org/10.5194/gmd-13-1137-2020, 2020
Short summary
Short summary
We coupled a dynamic vegetation model YIBs with the chemical transport model GEOS-Chem to develop a new tool for studying interactions between atmospheric chemistry and biosphere. Within this framework, leaf area index and stomatal conductance are predicted for chemical simulations. In turn, surface ozone causes negative impacts to plant growth and the consequent dry deposition. Such interactions are important for air pollution prediction but ignored in most of current chemical models.
Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Arjo Segers, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Atmos. Chem. Phys., 20, 2795–2823, https://doi.org/10.5194/acp-20-2795-2020, https://doi.org/10.5194/acp-20-2795-2020, 2020
Short summary
Short summary
MAX-DOAS tropospheric NO2 vertical column retrievals from a set of European measurement stations are compared to regional air quality models which contribute to the operational Copernicus Atmosphere Monitoring Service (CAMS). Correlations are on the order of 35 %–75 %; large differences occur for individual pollution plumes. The results demonstrate that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Syuichi Itahashi, Baozhu Ge, Keiichi Sato, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Junichi Kurokawa, Gregory R. Carmichael, and Zifa Wang
Atmos. Chem. Phys., 20, 2667–2693, https://doi.org/10.5194/acp-20-2667-2020, https://doi.org/10.5194/acp-20-2667-2020, 2020
Short summary
Short summary
This study gives an overview of acid deposition from the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. Wet deposition simulated by a total of nine models is evaluated with observation data from the Acid Deposition Monitoring Network in East Asia (EANET). The total deposition maps comparing to emissions over Asia are presented. To seek a way to improve the model performance, ensemble approaches and the precipitation-adjusted method are discussed.
Yang Yang, Sijia Lou, Hailong Wang, Pinya Wang, and Hong Liao
Atmos. Chem. Phys., 20, 2579–2590, https://doi.org/10.5194/acp-20-2579-2020, https://doi.org/10.5194/acp-20-2579-2020, 2020
Short summary
Short summary
Aerosol concentration decreased in Europe during 1980–2018, of which 7 % was induced by the changes in non-European emissions. Aerosols transported from other source regions are increasingly important to air quality in Europe. Contributions to the sulfate radiative forcing over Europe from both European and non-European emissions should decrease at a comparable rate in the next three decades. Future changes in non-European emissions are important in causing regional climate change in Europe.
Xu Yue, Hong Liao, Huijun Wang, Tianyi Zhang, Nadine Unger, Stephen Sitch, Zhaozhong Feng, and Jia Yang
Atmos. Chem. Phys., 20, 2353–2366, https://doi.org/10.5194/acp-20-2353-2020, https://doi.org/10.5194/acp-20-2353-2020, 2020
Short summary
Short summary
We explore ecosystem responses in China to 1.5 °C global warming under stabilized versus transient pathways. Remarkably, GPP shows 30 % higher enhancement in the stabilized than the transient pathway because of the lower ozone (smaller damages to photosynthesis) and fewer aerosols (higher light availability) in the former pathway. Our analyses suggest that an associated reduction of CO2 and pollution emissions brings more benefits to ecosystems in China via 1.5 °C global warming.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Joshua S. Fu, Xuemei Wang, Syuichi Itahashi, Kazuyo Yamaji, Tatsuya Nagashima, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Lei Chen, Meigen Zhang, Zhining Tao, Jie Li, Mizuo Kajino, Hong Liao, Zhe Wang, Kengo Sudo, Yuesi Wang, Yuepeng Pan, Guiqian Tang, Meng Li, Qizhong Wu, Baozhu Ge, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 181–202, https://doi.org/10.5194/acp-20-181-2020, https://doi.org/10.5194/acp-20-181-2020, 2020
Short summary
Short summary
Evaluation and uncertainty investigation of NO2, CO and NH3 modeling over China were conducted in this study using 14 chemical transport model results from MICS-Asia III. All models largely underestimated CO concentrations and showed very poor performance in reproducing the observed monthly variations of NH3 concentrations. Potential factors related to such deficiencies are investigated and discussed in this paper.
Miguel Escudero, Arjo Segers, Richard Kranenburg, Xavier Querol, Andrés Alastuey, Rafael Borge, David de la Paz, Gotzon Gangoiti, and Martijn Schaap
Atmos. Chem. Phys., 19, 14211–14232, https://doi.org/10.5194/acp-19-14211-2019, https://doi.org/10.5194/acp-19-14211-2019, 2019
Short summary
Short summary
In this work we optimise LOTOS-EUROS CTM for simulating tropospheric O3 during summer in the Madrid metropolitan area, one of the largest conurbations in the Mediterranean. Comparing the outputs from five set-ups with different combinations of spatial resolution, meteorological data and vertical structure, we conclude that the model benefits from fine horizontal resolution and highly resolved vertical structure. Running optimized configuration run, we interpret O3 variability during July 2016.
Cheng Gong and Hong Liao
Atmos. Chem. Phys., 19, 13725–13740, https://doi.org/10.5194/acp-19-13725-2019, https://doi.org/10.5194/acp-19-13725-2019, 2019
Short summary
Short summary
Severe O3 pollution events (OPEs) were observed frequently in summer in North China. We found a typical weather pattern that was responsible for the 21 OPEs observed in North China in May to July of 2014–2017. This weather pattern is characterized by high daily maximum temperature, low relative humidity and an anomalous high-pressure system at 500 hPa. Under such a weather pattern, chemical production of O3 is high between 800 and 900 hPa, which is then transported downward to enhance O3 levels.
Jie Li, Tatsuya Nagashima, Lei Kong, Baozhu Ge, Kazuyo Yamaji, Joshua S. Fu, Xuemei Wang, Qi Fan, Syuichi Itahashi, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Meigen Zhang, Zhining Tao, Mizuo Kajino, Hong Liao, Meng Li, Jung-Hun Woo, Jun-ichi Kurokawa, Zhe Wang, Qizhong Wu, Hajime Akimoto, Gregory R. Carmichael, and Zifa Wang
Atmos. Chem. Phys., 19, 12993–13015, https://doi.org/10.5194/acp-19-12993-2019, https://doi.org/10.5194/acp-19-12993-2019, 2019
Short summary
Short summary
This study evaluated and intercompared 14 CTMs with ozone observations in East Asia, within the framework of the Model Inter-Comparison Study for ASIA Phase III (MICS-Asia III). Potential causes of the discrepancies between model results and observation were investigated by assessing the planetary boundary layer heights, emission fluxes, dry deposition, chemistry and vertical transport among models. Finally, a multi-model estimate of pollution distributions was provided.
Renske Timmermans, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, Johan de Haan, Jukka Kujanpää, William Lahoz, Albert Oude Nijhuis, Samuel Quesada-Ruiz, Philippe Ricaud, Pepijn Veefkind, and Martijn Schaap
Atmos. Chem. Phys., 19, 12811–12833, https://doi.org/10.5194/acp-19-12811-2019, https://doi.org/10.5194/acp-19-12811-2019, 2019
Short summary
Short summary
We present an evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for air quality analyses of NO2. For this, synthetic observations for both missions are generated and combined with a chemistry transport model. While hourly Sentinel-4 NO2 observations over Europe benefit modelled NO2 analyses throughout the entire day, daily Sentinel-5P NO2 observations with global coverage show an impact up to 3–6 h after overpass. This supports the need for a combination of missions.
Lei Chen, Yi Gao, Meigen Zhang, Joshua S. Fu, Jia Zhu, Hong Liao, Jialin Li, Kan Huang, Baozhu Ge, Xuemei Wang, Yun Fat Lam, Chuan-Yao Lin, Syuichi Itahashi, Tatsuya Nagashima, Mizuo Kajino, Kazuyo Yamaji, Zifa Wang, and Jun-ichi Kurokawa
Atmos. Chem. Phys., 19, 11911–11937, https://doi.org/10.5194/acp-19-11911-2019, https://doi.org/10.5194/acp-19-11911-2019, 2019
Short summary
Short summary
Simulated aerosol concentrations from 14 CTMs within the framework of MICS-Asia III are detailedly evaluated with an extensive set of measurements in East Asia. Similarities and differences among model performances are also analyzed. Although more considerable capacities for reproducing the aerosol concentrations and their variations are shown in current CTMs than those in MICS-Asia II, more efforts are needed to reduce diversities of simulated aerosol concentrations among air quality models.
Shixian Zhai, Daniel J. Jacob, Xuan Wang, Lu Shen, Ke Li, Yuzhong Zhang, Ke Gui, Tianliang Zhao, and Hong Liao
Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, https://doi.org/10.5194/acp-19-11031-2019, 2019
Short summary
Short summary
Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Lei Chen, Jia Zhu, Hong Liao, Yi Gao, Yulu Qiu, Meigen Zhang, Zirui Liu, Nan Li, and Yuesi Wang
Atmos. Chem. Phys., 19, 10845–10864, https://doi.org/10.5194/acp-19-10845-2019, https://doi.org/10.5194/acp-19-10845-2019, 2019
Short summary
Short summary
The formation mechanism of a severe haze episode that occurred over North China in December 2015, the aerosol radiative impacts on the haze event and the influence mechanism were examined. The PM2.5 increase during the aerosol accumulation stage was mainly attributed to strong production by the aerosol chemistry process and weak removal by advection and vertical mixing. Restrained vertical mixing was the main reason for near-surface PM2.5 increase when aerosol radiative feedback was considered.
Juan Feng, Jianping Li, Hong Liao, and Jianlei Zhu
Atmos. Chem. Phys., 19, 10787–10800, https://doi.org/10.5194/acp-19-10787-2019, https://doi.org/10.5194/acp-19-10787-2019, 2019
Short summary
Short summary
Background climate can affect the aerosol concentration (AC). It is found that when negative NAO overlaps El Niño, the anomalous circulations are not favorable for the transportation of aerosol, resulting in enhanced AC over eastern China. By contrast, a sole negative NAO event is linked with increased AC over central China. The results suggest that both the extratropical and tropical climate systems play an important role in impacting the AC over China.
Ruijun Dang and Hong Liao
Atmos. Chem. Phys., 19, 10801–10816, https://doi.org/10.5194/acp-19-10801-2019, https://doi.org/10.5194/acp-19-10801-2019, 2019
Short summary
Short summary
We used a global chemical transport model to examine the historical changes in severe winter haze days (SWHDs) in Beijing–Tianjin–Hebei (BTH) in China. Simulated frequency of SWHDs in BTH showed an increasing trend over 1985–2017 with obvious fluctuations. We found that meteorology has dominated the frequency decrease in 1992–2001, and both anthropogenic emissions and meteorology contributed to the increase in 2003–2012. These results have important implications for the control of SWHDs in BTH.
Jianbing Jin, Hai Xiang Lin, Arjo Segers, Yu Xie, and Arnold Heemink
Atmos. Chem. Phys., 19, 10009–10026, https://doi.org/10.5194/acp-19-10009-2019, https://doi.org/10.5194/acp-19-10009-2019, 2019
Run Liu, Lu Mao, Shaw Chen Liu, Yuanhang Zhang, Hong Liao, Huopo Chen, and Yuhang Wang
Atmos. Chem. Phys., 19, 8563–8568, https://doi.org/10.5194/acp-19-8563-2019, https://doi.org/10.5194/acp-19-8563-2019, 2019
Short summary
Short summary
The recent paper by Shen et al. (2018; referred to hereafter as SHEN) made a sweeping statement on the winter haze pollution in Beijing by claiming an
Insignificant effect of climate change on winter haze in Beijing. We argue that the paper contains three serious flaws. Any one of the three flaws can nullify the claim of SHEN.
Lu Shen, Daniel J. Jacob, Xiong Liu, Guanyu Huang, Ke Li, Hong Liao, and Tao Wang
Atmos. Chem. Phys., 19, 6551–6560, https://doi.org/10.5194/acp-19-6551-2019, https://doi.org/10.5194/acp-19-6551-2019, 2019
Anna Katinka Petersen, Guy P. Brasseur, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Ying Xie, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 1241–1266, https://doi.org/10.5194/gmd-12-1241-2019, https://doi.org/10.5194/gmd-12-1241-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality is providing daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas of China. The paper presents the evaluation of the different forecasts performed during the first year of operation.
Xuan Wang, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Lei Zhu, Qianjie Chen, Becky Alexander, Tomás Sherwen, Mathew J. Evans, Ben H. Lee, Jessica D. Haskins, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Gregory L. Huey, and Hong Liao
Atmos. Chem. Phys., 19, 3981–4003, https://doi.org/10.5194/acp-19-3981-2019, https://doi.org/10.5194/acp-19-3981-2019, 2019
Short summary
Short summary
Chlorine radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a comprehensive simulation of tropospheric chlorine in a global 3-D model, which includes explicit accounting of chloride mobilization from sea salt aerosol. We find the chlorine chemistry contributes 1.0 % of the global oxidation of methane and decreases global burdens of tropospheric ozone by 7 % and OH by 3 % through the associated bromine radical chemistry.
Guy P. Brasseur, Ying Xie, Anna Katinka Petersen, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 33–67, https://doi.org/10.5194/gmd-12-33-2019, https://doi.org/10.5194/gmd-12-33-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality provides daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas in China. The paper presents an intercomparison of the different forecasts performed during a specific period of time and highlights recurrent differences between the model output. Pathways to improve the forecasts by the multi-model system are suggested.
Christine D. Groot Zwaaftink, Stephan Henne, Rona L. Thompson, Edward J. Dlugokencky, Toshinobu Machida, Jean-Daniel Paris, Motoki Sasakawa, Arjo Segers, Colm Sweeney, and Andreas Stohl
Geosci. Model Dev., 11, 4469–4487, https://doi.org/10.5194/gmd-11-4469-2018, https://doi.org/10.5194/gmd-11-4469-2018, 2018
Short summary
Short summary
A Lagrangian particle dispersion model is used to simulate global fields of methane, constrained by observations through nudging. We show that this rather simple and computationally inexpensive method can give results similar to or as good as a computationally expensive Eulerian chemistry transport model with a data assimilation scheme. The three-dimensional methane fields are of interest to applications such as inverse modelling and satellite retrievals.
Simon Chabrillat, Corinne Vigouroux, Yves Christophe, Andreas Engel, Quentin Errera, Daniele Minganti, Beatriz M. Monge-Sanz, Arjo Segers, and Emmanuel Mahieu
Atmos. Chem. Phys., 18, 14715–14735, https://doi.org/10.5194/acp-18-14715-2018, https://doi.org/10.5194/acp-18-14715-2018, 2018
Short summary
Short summary
Mean age of stratospheric air is computed for the period 1989–2015 with a kinematic transport model which uses surface pressure and wind fields from five reanalyses: ERA-I, MERRA-2, MERRA, CFSR, JRA-55. The spread between the resulting datasets is as large as in climate model intercomparisons; the age trends have large disagreement and depend strongly on the considered period. We highlight the need for similar studies using diabatic transport models which also use temperature and heating rates.
Nan Li, Qingyang He, Jim Greenberg, Alex Guenther, Jingyi Li, Junji Cao, Jun Wang, Hong Liao, Qiyuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 7489–7507, https://doi.org/10.5194/acp-18-7489-2018, https://doi.org/10.5194/acp-18-7489-2018, 2018
Short summary
Short summary
O3 pollution has been increasing in most Chinese cities in recent years. Our study reveals that the synergistic impact of individual source contributions to O3 formation should be considered in the formation of air pollution control strategies, especially for big cities in the vicinity of forests.
Martijn Schaap, Sabine Banzhaf, Thomas Scheuschner, Markus Geupel, Carlijn Hendriks, Richard Kranenburg, Hans-Dieter Nagel, Arjo J. Segers, Angela von Schlutow, Roy Wichink Kruit, and Peter J. H. Builtjes
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-491, https://doi.org/10.5194/bg-2017-491, 2017
Revised manuscript has not been submitted
Short summary
Short summary
Deposition of nitrogen and sulfur from the atmosphere on ecosystems causes a loss of biodiversity. We used a combination of atmospheric modelling and deposition observations to estimate the deposition to ecosystems across Germany. We estimate that 70 % of the ecosystems in Germany receive too much nitrogen from deposition. The results are used to determine whether economic activities causing nitrogen emissions are allowed in sensitive areas.
Astrid M. M. Manders, Peter J. H. Builtjes, Lyana Curier, Hugo A. C. Denier van der Gon, Carlijn Hendriks, Sander Jonkers, Richard Kranenburg, Jeroen J. P. Kuenen, Arjo J. Segers, Renske M. A. Timmermans, Antoon J. H. Visschedijk, Roy J. Wichink Kruit, W. Addo J. van Pul, Ferd J. Sauter, Eric van der Swaluw, Daan P. J. Swart, John Douros, Henk Eskes, Erik van Meijgaard, Bert van Ulft, Peter van Velthoven, Sabine Banzhaf, Andrea C. Mues, Rainer Stern, Guangliang Fu, Sha Lu, Arnold Heemink, Nils van Velzen, and Martijn Schaap
Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, https://doi.org/10.5194/gmd-10-4145-2017, 2017
Short summary
Short summary
The regional-scale air quality model LOTOS–EUROS has been developed by a consortium of Dutch institutes. Recently, version 2.0 of the model was released as an open-source version. Next to a technical description and model evaluation for 2012, this paper presents the model developments in context of the history of air quality modelling and provides an outlook for future directions. Key and innovative applications of LOTOS–EUROS are also highlighted.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
Short summary
Short summary
This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
Xu Yue, Nadine Unger, Kandice Harper, Xiangao Xia, Hong Liao, Tong Zhu, Jingfeng Xiao, Zhaozhong Feng, and Jing Li
Atmos. Chem. Phys., 17, 6073–6089, https://doi.org/10.5194/acp-17-6073-2017, https://doi.org/10.5194/acp-17-6073-2017, 2017
Short summary
Short summary
While it is widely recognized that air pollutants adversely affect human health and climate change, their impacts on the regional carbon balance are less well understood. We apply an Earth system model to quantify the combined effects of ozone and aerosol particles on net primary production in China. Ozone vegetation damage dominates over the aerosol effects, leading to a substantial net suppression of land carbon uptake in the present and future worlds.
Guangliang Fu, Hai Xiang Lin, Arnold Heemink, Sha Lu, Arjo Segers, Nils van Velzen, Tongchao Lu, and Shiming Xu
Geosci. Model Dev., 10, 1751–1766, https://doi.org/10.5194/gmd-10-1751-2017, https://doi.org/10.5194/gmd-10-1751-2017, 2017
Short summary
Short summary
We propose a mask-state algorithm (MS) which records the sparsity information of the full ensemble state matrix and transforms the full matrix into a relatively small one. It will reduce the computational cost in the analysis step for plume assimilation applications. Ensemble-based DA with the mask-state algorithm is generic and flexible, because it implements exactly the standard DA without any approximation and it realizes the satisfying performance without any change of the full model.
Yu-Hao Mao, Hong Liao, and Hai-Shan Chen
Atmos. Chem. Phys., 17, 4799–4816, https://doi.org/10.5194/acp-17-4799-2017, https://doi.org/10.5194/acp-17-4799-2017, 2017
Short summary
Short summary
We applied a global 3-D CTM to examine the impacts of the East Asian summer and winter monsoons on the interannual variations of surface concentrations, vertical distributions, and direct radiative forcing of black carbon (BC) over eastern China and the mechanisms through which the monsoon influences the variations of BC. Model results from our study have important implications for guiding measures to reduce BC emissions to mitigate near-term climate warming and to improve air quality in China.
Jia Zhu, Hong Liao, Yuhao Mao, Yang Yang, and Hui Jiang
Atmos. Chem. Phys., 17, 3729–3747, https://doi.org/10.5194/acp-17-3729-2017, https://doi.org/10.5194/acp-17-3729-2017, 2017
Short summary
Short summary
Asian O3 outflow exhibited a small and statistically insignificant decadal trend with large interannual variations from 1986–2006. The latter were mainly caused by variations in the meteorological conditions. Future climate change will aggravate the effects of the increases in anthropogenic emissions on future changes in the Asian O3 outflow. These findings help us to understand the variations in tropospheric O3 in the regions downwind of East Asia on different timescales.
Guangliang Fu, Fred Prata, Hai Xiang Lin, Arnold Heemink, Arjo Segers, and Sha Lu
Atmos. Chem. Phys., 17, 1187–1205, https://doi.org/10.5194/acp-17-1187-2017, https://doi.org/10.5194/acp-17-1187-2017, 2017
Short summary
Short summary
A Satellite Observational Operator (SOO) is proposed to translates satellite-retrieved 2-D volcanic ash mass loadings to 3-D concentrations. The SOO makes the analysis step of assimilation comparable in the 3-D model space, and thus it avoids the artificial vertical correlations by not involving the integral operator in directly assimilating 2-D data. The results show that satellite data assimilation with SOO can efficiently improve the estimate of volcanic ash state and the forecast.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
Short summary
Short summary
A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
E. N. Koffi, P. Bergamaschi, U. Karstens, M. Krol, A. Segers, M. Schmidt, I. Levin, A. T. Vermeulen, R. E. Fisher, V. Kazan, H. Klein Baltink, D. Lowry, G. Manca, H. A. J. Meijer, J. Moncrieff, S. Pal, M. Ramonet, H. A. Scheeren, and A. G. Williams
Geosci. Model Dev., 9, 3137–3160, https://doi.org/10.5194/gmd-9-3137-2016, https://doi.org/10.5194/gmd-9-3137-2016, 2016
Short summary
Short summary
We evaluate the capability of the TM5 model to reproduce observations of the boundary layer dynamics and the associated variability of trace gases close to the surface, using 222Rn. Focusing on the European scale, we compare the TM5 boundary layer heights with observations from radiosondes, lidar, and ceilometer. Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe, with 222Rn harmonized measurements from 10 stations.
Yu Fu, Amos P. K. Tai, and Hong Liao
Atmos. Chem. Phys., 16, 10369–10383, https://doi.org/10.5194/acp-16-10369-2016, https://doi.org/10.5194/acp-16-10369-2016, 2016
Short summary
Short summary
The effects of climate change would partly counteract the emission-driven increase in PM2.5 in winter in most of eastern China, but exacerbate PM2.5 pollution in summer in North China Plain. Land cover and land use change might partially offset the increase in summertime PM2.5 but further enhance wintertime PM2.5 in the model by modifying the dry deposition of various PM2.5 precursors and biogenic volatile organic compound emissions, which also act as important factors in modulating air quality.
Guangliang Fu, Arnold Heemink, Sha Lu, Arjo Segers, Konradin Weber, and Hai-Xiang Lin
Atmos. Chem. Phys., 16, 9189–9200, https://doi.org/10.5194/acp-16-9189-2016, https://doi.org/10.5194/acp-16-9189-2016, 2016
Short summary
Short summary
Assimilating aircraft in situ measurements can significantly improve aviation advice on distal part of volcanic ash plume.
Yixuan Gu, Hong Liao, and Jianchun Bian
Atmos. Chem. Phys., 16, 6641–6663, https://doi.org/10.5194/acp-16-6641-2016, https://doi.org/10.5194/acp-16-6641-2016, 2016
Short summary
Short summary
This is the first study to examine nitrate aerosol in the upper troposphere and lower stratosphere (UTLS) over the Tibetan Plateau (TP) and the South Asian summer monsoon (SASM) region in summer. Nitrate aerosol is simulated to be the most dominant aerosol species in the UTLS over the studied region. The mechanisms for the accumulation of nitrate in the UTLS over the TP/SASM region include vertical transport and the gas-to-aerosol conversion of nitric acid to form nitrate.
Jin Feng, Hong Liao, and Jianping Li
Atmos. Chem. Phys., 16, 4927–4943, https://doi.org/10.5194/acp-16-4927-2016, https://doi.org/10.5194/acp-16-4927-2016, 2016
Short summary
Short summary
We examine the impacts of monthly variations in Pacific-North America (PNA) teleconnection on aerosol concentrations in the United States during wintertime by observations from the EPA-AQS and the model results from the GEOS-Chem. The surface-layer PM2.5 concentrations in the PNA positive phases were higher by 8.7 % (12.2 %) relative to the PNA negative phases based on observed (simulated) concentrations, which have important implications for understanding and prediction of air quality in the US.
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
Short summary
Short summary
This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
Short summary
Short summary
The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
S. Banzhaf, M. Schaap, R. Kranenburg, A. M. M. Manders, A. J. Segers, A. J. H. Visschedijk, H. A. C. Denier van der Gon, J. J. P. Kuenen, E. van Meijgaard, L. H. van Ulft, J. Cofala, and P. J. H. Builtjes
Geosci. Model Dev., 8, 1047–1070, https://doi.org/10.5194/gmd-8-1047-2015, https://doi.org/10.5194/gmd-8-1047-2015, 2015
P. Bergamaschi, M. Corazza, U. Karstens, M. Athanassiadou, R. L. Thompson, I. Pison, A. J. Manning, P. Bousquet, A. Segers, A. T. Vermeulen, G. Janssens-Maenhout, M. Schmidt, M. Ramonet, F. Meinhardt, T. Aalto, L. Haszpra, J. Moncrieff, M. E. Popa, D. Lowry, M. Steinbacher, A. Jordan, S. O'Doherty, S. Piacentino, and E. Dlugokencky
Atmos. Chem. Phys., 15, 715–736, https://doi.org/10.5194/acp-15-715-2015, https://doi.org/10.5194/acp-15-715-2015, 2015
M. Alexe, P. Bergamaschi, A. Segers, R. Detmers, A. Butz, O. Hasekamp, S. Guerlet, R. Parker, H. Boesch, C. Frankenberg, R. A. Scheepmaker, E. Dlugokencky, C. Sweeney, S. C. Wofsy, and E. A. Kort
Atmos. Chem. Phys., 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, https://doi.org/10.5194/acp-15-113-2015, 2015
T. P. C. van Noije, P. Le Sager, A. J. Segers, P. F. J. van Velthoven, M. C. Krol, W. Hazeleger, A. G. Williams, and S. D. Chambers
Geosci. Model Dev., 7, 2435–2475, https://doi.org/10.5194/gmd-7-2435-2014, https://doi.org/10.5194/gmd-7-2435-2014, 2014
Q. Mu and H. Liao
Atmos. Chem. Phys., 14, 9597–9612, https://doi.org/10.5194/acp-14-9597-2014, https://doi.org/10.5194/acp-14-9597-2014, 2014
Y. Yang, H. Liao, and J. Li
Atmos. Chem. Phys., 14, 6867–6879, https://doi.org/10.5194/acp-14-6867-2014, https://doi.org/10.5194/acp-14-6867-2014, 2014
A. Mues, J. Kuenen, C. Hendriks, A. Manders, A. Segers, Y. Scholz, C. Hueglin, P. Builtjes, and M. Schaap
Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, https://doi.org/10.5194/acp-14-939-2014, 2014
H. Jiang, H. Liao, H. O. T. Pye, S. Wu, L. J. Mickley, J. H. Seinfeld, and X. Y. Zhang
Atmos. Chem. Phys., 13, 7937–7960, https://doi.org/10.5194/acp-13-7937-2013, https://doi.org/10.5194/acp-13-7937-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
R. Kranenburg, A. J. Segers, C. Hendriks, and M. Schaap
Geosci. Model Dev., 6, 721–733, https://doi.org/10.5194/gmd-6-721-2013, https://doi.org/10.5194/gmd-6-721-2013, 2013
Related subject area
Atmospheric sciences
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
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
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)
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
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
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy 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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a 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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements 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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-148, https://doi.org/10.5194/gmd-2024-148, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled chemistry meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the CMA-GFS operational global numerical weather model. The results show that assimilating BC observations can generate analysis increments not only for BC but also for atmospheric variables.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Cited articles
Abu Awad, Y., Koutrakis, P., Coull, B. A., and Schwartz, J.: A spatio-temporal prediction model based on support vector machine regression: Ambient Black Carbon in three New England States, Environ. Res., 159, 427–434, https://doi.org/10.1016/j.envres.2017.08.039, 2017. a
Altmann, A., Toloşi, L., Sander, O., and Lengauer, T.: Permutation importance: a corrected feature importance measure, Bioinformatics, 26, 1340–1347, https://doi.org/10.1093/bioinformatics/btq134, 2010. a
Bai, Y., Li, Y., Zeng, B., Li, C., and Zhang, J.: Hourly PM2.5 concentration forecast using stacked autoencoder model with emphasis on seasonality, J. Clean. Prod., 224, 739–750, 2019. a
Bartier, P. M. and Keller, C.: Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW), Comput. Geosci., 22, 795–799, https://doi.org/10.1016/0098-3004(96)00021-0, 1996. a
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res.-Atmos., 106, 23073–23095, https://doi.org/10.1029/2001JD000807, 2001. a
Brokamp, C., Jandarov, R., Rao, M., LeMasters, G., and Ryan, P.: Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches, Atmos. Environ., 151, 1–11, https://doi.org/10.1016/j.atmosenv.2016.11.066, 2017. a
Burnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope, C. A., Apte, J. S., Brauer, M., Cohen, A.,
Weichenthal, S., Coggins, J., Di, Q,. Brunekreef, B., Frostad, J., Lim, S. S., Kan, H., Walker, K. D., Thurston, G. D., Hayes,
R. B., Lim, C. C., Turner, M. C., Jerrett, M., Krewski, D., Gapstur, S. M., Diver, W. R., Ostro, B., Goldberg, D., Crouse, D.
L., Martin, R. V., Peters, P., Pinault, L., Tjepkema, M., van, Donkelaar. A., Villeneuve, P. J., Miller, A. B., Yin, P., Zhou,
M., Wang, L., Janssen, NAH., Marra, M., Atkinson, R. W., Tsang, H., Quoc, Thach. T., Cannon, J. B., Allen, R. T., Hart, J.
E., Laden, F., Cesaroni, G., Forastiere, F., Weinmayr, G., Jaensch, A., Nagel, G., Concin, H., and Spadaro, J. V.: Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter, P. Natl. Acad. Sci. USA, 115, 9592–9597, 2018. a
Cao, D., Chen, Y., Chen, J., Zhang, H., and Yuan, Z.: An improved algorithm for the maximal information coefficient and its application, Roy. Soc. Open Sci., 8, 201424, https://doi.org/10.1098/rsos.201424, 2021. a
Casalicchio, G., Molnar, C., and Bischl, B.: Visualizing the Feature Importance for Black Box Models, in: Machine Learning and Knowledge Discovery in Databases, edited by: Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N., and Ifrim, G., Springer International Publishing, Cham, 655–670, https://doi.org/10.1007/978-3-030-10925-7_40, 2019. a
Chandrashekar, G. and Sahin, F.: A survey on feature selection methods, Comput. Electr. Eng., 40, 16–28, https://doi.org/10.1016/j.compeleceng.2013.11.024, 2014. a
Chen, D., Liu, X., Lang, J., Zhou, Y., Wei, L., Wang, X., and Guo, X.: Estimating the contribution of regional transport to PM2.5 air pollution in a rural area on the North China Plain, Sci. Total Environ., 583, 280–291, https://doi.org/10.1016/j.scitotenv.2017.01.066, 2017. a
Chen, Y., Zeng, Y., Luo, F., and Yuan, Z.: A new algorithm to optimize maximal information coefficient, PloS one, 11, e0157567, https://doi.org/10.1371/journal.pone.0157567, 2016. a
Cobourn, W. G.: An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations, Atmos. Environ., 44, 3015–3023, https://doi.org/10.1016/j.atmosenv.2010.05.009, 2010. a
Copernicus Climate Change Service (C3S): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS), https://cds.climate.copernicus.eu/cdsapp#!/home (last access: June 2022), 2017. a
Covert, I., Lundberg, S. M., and Lee, S.-I.: Understanding Global Feature Contributions With Additive Importance Measures, in: Advances in Neural Information Processing Systems, vol. 33, edited by: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F., and Lin, H., Curran Associates, Inc., 17212–17223, https://proceedings.neurips.cc/paper/2020/file/c7bf0b7c1a86d5eb3be2c722cf2cf746-Paper.pdf (last access: June 2022), 2020. a, b, c, d
Di, Q., Amini, H., Shi, L., Kloog, I., Silvern, R., Kelly, J., Sabath, M. B., Choirat, C., Koutrakis, P., Lyapustin, A., Wang, Y., Mickley, L. J., and Schwartz, J.: An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution, Environ. Int., 130, 104909, https://doi.org/10.1016/j.envint.2019.104909, 2019. a
Fan, T., Liu, X., Ma, P.-L., Zhang, Q., Li, Z., Jiang, Y., Zhang, F., Zhao, C., Yang, X., Wu, F., and Wang, Y.: Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models, Atmos. Chem. Phys., 18, 1395–1417, https://doi.org/10.5194/acp-18-1395-2018, 2018. a
Fang, L.: The ground observations for RFSML, Zenodo [data set and code], https://doi.org/10.5281/zenodo.6551820, 2022. a, b
Fernando, H., Mammarella, M., Grandoni, G., Fedele, P., Di Marco, R., Dimitrova, R., and Hyde, P.: Forecasting PM10 in metropolitan areas: Efficacy of neural networks, Environ. Pollut., 163, 62–67, https://doi.org/10.1016/j.envpol.2011.12.018, 2012. a
Fritsch, F. N. and Carlson, R. E.: Monotone piecewise cubic interpolation, SIAM J. Numer. Anal., 17, 238–246, 1980. a
Fryer, D. V., Strümke, I., and Nguyen, H.: Shapley values for feature selection: The good, the bad, and the axioms, arXiv [preprint], https://doi.org/10.48550/arXiv.2102.10936, 22 February 2021. a
Golizadeh Akhlaghi, Y., Aslansefat, K., Zhao, X., Sadati, S., Badiei, A., Xiao, X., Shittu, S., Fan, Y., and Ma, X.: Hourly performance forecast of a dew point cooler using explainable Artificial Intelligence and evolutionary optimisations by 2050, Appl. Energ., 281, 116062, https://doi.org/10.1016/j.apenergy.2020.116062, 2021. a
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 6957–6975, https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005. a
Guo, J., He, J., Liu, H., Miao, Y., Liu, H., and Zhai, P.: Impact of various emission control schemes on air quality using WRF-Chem during APEC China 2014, Atmos. Environ., 140, 311–319, https://doi.org/10.1016/j.atmosenv.2016.05.046, 2016. a
Guyon, I. and Elisseeff, A.: An introduction to variable and feature selection, J. Mach. Learn. Res., 3, 1157–1182, 2003. a
Hao, X., Li, J., Wang, H., Liao, H., Yin, Z., Hu, J., Wei, Y., and Dang, R.: Long-term health impact of PM2.5 under whole-year COVID-19 lockdown in China, Environ. Pollut., 290, 118118, https://doi.org/10.1016/j.envpol.2021.118118, 2021. a
Hu, J., Wang, Y., Ying, Q., and Zhang, H.: Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta, China, Atmos. Environ., 95, 598–609, https://doi.org/10.1016/j.atmosenv.2014.07.019, 2014. a
Hu, J., Li, X., Huang, L., Ying, Q., Zhang, Q., Zhao, B., Wang, S., and Zhang, H.: Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China, Atmos. Chem. Phys., 17, 13103–13118, https://doi.org/10.5194/acp-17-13103-2017, 2017. a
Huang, L., Liu, S., Yang, Z., Xing, J., Zhang, J., Bian, J., Li, S., Sahu, S. K., Wang, S., and Liu, T.-Y.: Exploring deep learning for air pollutant emission estimation, Geosci. Model Dev., 14, 4641–4654, https://doi.org/10.5194/gmd-14-4641-2021, 2021. a
Huang, X.-F., Zou, B.-B., He, L.-Y., Hu, M., Prévôt, A. S. H., and Zhang, Y.-H.: Exploration of PM2.5 sources on the regional scale in the Pearl River Delta based on ME-2 modeling, Atmos. Chem. Phys., 18, 11563–11580, https://doi.org/10.5194/acp-18-11563-2018, 2018. a
Hutzell, W. T. and Luecken, D. J.: Fate and transport of emissions for several trace metals over the United States, Sci. Total Environ., 396, 164–179, https://doi.org/10.1016/j.scitotenv.2008.02.020, 2008. a
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019. a, b
Jeong, J. I. and Park, R. J.: Efficacy of dust aerosol forecasts for East Asia using the adjoint of GEOS-Chem with ground-based observations, Environ. Pollut., 234, 885–893, https://doi.org/10.1016/j.envpol.2017.12.025, 2018. a
Jin, J., Lin, H. X., Segers, A., Xie, Y., and Heemink, A.: Machine learning for observation bias correction with application to dust storm data assimilation, Atmos. Chem. Phys., 19, 10009–10026, https://doi.org/10.5194/acp-19-10009-2019, 2019. a
Jothi, N., Husain, W., and Rashid, N. A.: Predicting generalized anxiety disorder among women using Shapley value, J. Infect. Public Heal., 14, 103–108, https://doi.org/10.1016/j.jiph.2020.02.042, 2021. a
Ke, H., Gong, S., He, J., Zhang, L., Cui, B., Wang, Y., Mo, J., Zhou, Y., and Zhang, H.: Development and application of an automated air quality forecasting system based on machine learning, Sci. Total Environ., 806, 151204, https://doi.org/10.1016/j.scitotenv.2021.151204, 2021. a
Kincaid, D., Kincaid, D. R., and Cheney, E. W.: Numerical analysis: mathematics of scientific computing, vol. 2, American Mathematical Soc., ISBN 978-0-8218-4788-6, 2009. a
Kinney, J. B. and Atwal, G. S.: Equitability, mutual information, and the maximal information coefficient, P. Natl. Acad. Sci. USA, 111, 3354–3359, 2014. a
Leufen, L. H., Kleinert, F., and Schultz, M. G.: MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series, Geosci. Model Dev., 14, 1553–1574, https://doi.org/10.5194/gmd-14-1553-2021, 2021. a
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories in China: a review, Natl. Sci. Rev., 4, 834–866, https://doi.org/10.1093/nsr/nwx150, 2017. a, b
Li, X., Peng, L., Yao, X., Cui, S., Hu, Y., You, C., and Chi, T.: Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation, Environ. Pollut., 231, 997–1004, https://doi.org/10.1016/j.envpol.2017.08.114, 2017. a
Li, Z., Ma, Z., van der Kuijp, T. J., Yuan, Z., and Huang, L.: A review of soil heavy metal pollution from mines in China: Pollution and health risk assessment, Sci. Total Environ., 468–469, 843–853, https://doi.org/10.1016/j.scitotenv.2013.08.090, 2014. a
Liao, T., Wang, S., Ai, J., Gui, K., Duan, B., Zhao, Q., Zhang, X., Jiang, W., and Sun, Y.: Heavy pollution episodes, transport pathways and potential sources of PM2.5 during the winter of 2013 in Chengdu (China), Sci. Total Environ., 584–585, 1056–1065, https://doi.org/10.1016/j.scitotenv.2017.01.160, 2017. a
Liaw, A. and Wiener, M.: Classification and regression by randomForest, R news, 2, 18–22, 2002. a
Liu, H., He, J., Guo, J., Miao, Y., Yin, J., Wang, Y., Xu, H., Liu, H., Yan, Y., Li, Y., and Zhai, P.: The blue skies in Beijing during APEC 2014: A quantitative assessment of emission control efficiency and meteorological influence, Atmos. Environ., 167, 235–244, https://doi.org/10.1016/j.atmosenv.2017.08.032, 2017. a
Liu, J. and Diamond, J.: China's environment in a globalizing world, Nature, 435, 1179–1186, https://doi.org/10.1038/4351179a, 2005. a
Liu, T., Lau, A. K. H., Sandbrink, K., and Fung, J. C. H.: Time Series Forecasting of Air Quality Based On Regional Numerical Modeling in Hong Kong, J. Geophys. Res.-Atmos., 123, 4175–4196, https://doi.org/10.1002/2017JD028052, 2018. a
Ma, J., Ding, Y., Gan, V. J. L., Lin, C., and Wan, Z.: Spatiotemporal Prediction of PM2.5 Concentrations at Different Time Granularities Using IDW-BLSTM, IEEE Access, 7, 107897–107907, https://doi.org/10.1109/ACCESS.2019.2932445, 2019. a
Ma, T., Duan, F., He, K., Qin, Y., Tong, D., Geng, G., Liu, X., Li, H., Yang, S., Ye, S., Xu, B., Zhang, Q., and Ma, Y.: Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016, J. Environ. Sci.-China, 83, 8–20, https://doi.org/10.1016/j.jes.2019.02.031, 2019. a
Masih, A.: Machine learning algorithms in air quality modeling, Global Journal of Environmental Science and Management, 5, 515–534, 2019. a
Molnar, C.: Interpretable Machine Learning, Lulu.com, 2020. a
Muñoz Sabater, J.: ERA5-Land hourly data from 1950 to 1980, Copernicus Climate Change Service (C3S)
Climate Data Store (CDS)[data set], https://doi.org/10.24381/cds.e2161bac, 2021. a
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021. a
Murray, C. J., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., and GBD 2019 Risk Factors Collaborators: Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019, Lancet, 396, 1223–1249, 2020. a
Osowski, S., Siwek, K., and Markiewicz, T.: MLP and SVM networks-a comparative study, in: Proceedings of the 6th Nordic Signal Processing Symposium, 2004, NORSIG 2004, Espoo, Finland, 11–11 June 2004, 37–40, ISBN 951-22-7065-X IEEE,2004. a
Park, H. and Park, D. Y.: Comparative analysis on predictability of natural ventilation rate based on machine learning algorithms, Build. Environ., 195, 107744, https://doi.org/10.1016/j.buildenv.2021.107744, 2021. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011. a
Pérez, P., Trier, A., and Reyes, J.: Prediction of PM2.5 concentrations several hours in advance using neural networks in Santiago, Chile, Atmos. Environ., 34, 1189–1196, https://doi.org/10.1016/S1352-2310(99)00316-7, 2000. a
Pui, D. Y., Chen, S.-C., and Zuo, Z.: PM2.5 in China: Measurements, sources, visibility and health effects, and mitigation, Particuology, 13, 1–26, https://doi.org/10.1016/j.partic.2013.11.001, 2014. a
Qin, Z., Cen, C., and Guo, X.: Prediction of Air Quality Based on KNN-LSTM, J. Phys. Conf. Ser., 1237, 042030, https://doi.org/10.1088/1742-6596/1237/4/042030, 2019. a
Rodriguez-Galiano, V., Chica-Olmo, M., Abarca-Hernandez, F., Atkinson, P., and Jeganathan, C.: Random Forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture, Remote Sens. Environ., 121, 93–107, https://doi.org/10.1016/j.rse.2011.12.003, 2012. a
Sawaragi, Y., Soeda, T., Tamura, H., Yoshimura, T., Ohe, S., Chujo, Y., and Ishihara, H.: Statistical prediction of air pollution levels using non-physical models, Automatica, 15, 441–451, https://doi.org/10.1016/0005-1098(79)90018-9, 1979. a
Shapley, L. S.: A Value for N-Person Games, RAND Corporation, Santa Monica, CA, https://doi.org/10.7249/P0295, 1952. a, b
Shishegaran, A., Saeedi, M., Kumar, A., and Ghiasinejad, H.: Prediction of air quality in Tehran by developing the nonlinear ensemble model, J. Clean. Prod., 259, 120825, https://doi.org/10.1016/j.jclepro.2020.120825, 2020. a
Shtein, A., Kloog, I., Schwartz, J., Silibello, C., Michelozzi, P., Gariazzo, C., Viegi, G., Forastiere, F., Karnieli, A., and Just, A.: Estimating Daily PM2.5 and PM10 over Italy Using an Ensemble Model, Environ. Sci. Technol., 54, 120–128, https://doi.org/10.1021/acs.est.9b04279, 2020. a
Shu, Z., Liu, Y., Zhao, T., Xia, J., Wang, C., Cao, L., Wang, H., Zhang, L., Zheng, Y., Shen, L., Luo, L., and Li, Y.: Elevated 3D structures of PM2.5 and impact of complex terrain-forcing circulations on heavy haze pollution over Sichuan Basin, China, Atmos. Chem. Phys., 21, 9253–9268, https://doi.org/10.5194/acp-21-9253-2021, 2021. a
Song, C., He, J., Wu, L., Jin, T., Chen, X., Li, R., Ren, P., Zhang, L., and Mao, H.: Health burden attributable to ambient PM2.5 in China, Environ. Pollut., 223, 575–586, https://doi.org/10.1016/j.envpol.2017.01.060, 2017a. a
Song, C., Wu, L., Xie, Y., He, J., Chen, X., Wang, T., Lin, Y., Jin, T., Wang, A., Liu, Y., Dai, Q., Liu, B., Wang, Y., and Mao, H.: Air pollution in China: Status and spatiotemporal variations, Environ. Pollut., 227, 334–347, https://doi.org/10.1016/j.envpol.2017.04.075, 2017b. a, b
Sun, G., Li, J., Dai, J., Song, Z., and Lang, F.: Feature selection for IoT based on maximal information coefficient, Future Gener. Comp. Sy., 89, 606–616, https://doi.org/10.1016/j.future.2018.05.060, 2018. a
Sun, W. and Li, Z.: Hourly PM2.5 concentration forecasting based on feature extraction and stacking-driven ensemble model for the winter of the Beijing-Tianjin-Hebei area, Atmos. Pollut. Res., 11, 110–121, https://doi.org/10.1016/j.apr.2020.02.022, 2020a. a
Sun, W. and Li, Z.: Hourly PM2.5 concentration forecasting based on mode decomposition-recombination technique and ensemble learning approach in severe haze episodes of China, J. Clean. Prod., 263, 121442, https://doi.org/10.1016/j.jclepro.2020.121442, 2020b. a
Sun, W., Zhang, H., Palazoglu, A., Singh, A., Zhang, W., and Liu, S.: Prediction of 24-hour-average PM2.5 concentrations using a hidden Markov model with different emission distributions in Northern California, Sci. Total Environ., 443, 93–103, https://doi.org/10.1016/j.scitotenv.2012.10.070, 2013. a
Taylor, K. E.: Taylor diagram primer, Work. Pap., 1–4, https://www.atmos.albany.edu/daes/atmclasses/atm401/spring_2016/ppts_pdfs/Taylor_diagram_primer.pdf (last
access: October 2022), 2005. a
Wu, X., Wang, Y., He, S., and Wu, Z.: PM2.5 / PM10 ratio prediction based on a long short-term memory neural network in Wuhan, China, Geosci. Model Dev., 13, 1499–1511, https://doi.org/10.5194/gmd-13-1499-2020, 2020. a
Xi, X., Wei, Z., Xiaoguang, R., Yijie, W., Xinxin, B., Wenjun, Y., and Jin, D.: A comprehensive evaluation of air pollution prediction improvement by a machine learning method, in: 2015 IEEE International Conference on Service Operations And Logistics, And Informatics (SOLI), Yasmine Hammamet, Tunisia, 15–17 November 2015, 176–181, https://doi.org/10.1109/SOLI.2015.7367615, 2015. a
Xu, M., Jin, J., Wang, G., Segers, A., Deng, T., and Lin, H. X.: Machine learning based bias correction for numerical chemical transport models, Atmos. Environ., 248, 118022, https://doi.org/10.1016/j.atmosenv.2020.118022, 2021. a, b
Xue, T., Zhu, T., Zheng, Y., Liu, J., Li, X., and Zhang, Q.: Change in the number of PM2.5-attributed deaths in China from 2000 to 2010: Comparison between estimations from census-based epidemiology and pre-established exposure-response functions, Environ. Int., 129, 430–437, https://doi.org/10.1016/j.envint.2019.05.067, 2019. a
Yu, S. and Ma, J.: Deep Learning for Geophysics: Current and Future Trends, Rev. Geophys., 59, e2021RG000742, https://doi.org/10.1029/2021RG000742, 2021.
a
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. a, b, c, d
Zhan, C., Xie, M., Fang, D., Wang, T., Wu, Z., Lu, H., Li, M., Chen, P., Zhuang, B., Li, S., Zhang, Z., Gao, D., Ren, J., and Zhao, M.: Synoptic weather patterns and their impacts on regional particle pollution in the city cluster of the Sichuan Basin, China, Atmos. Environ., 208, 34–47, https://doi.org/10.1016/j.atmosenv.2019.03.033, 2019. a
Zhang, Q., Ma, Q., Zhao, B., Liu, X., Wang, Y., Jia, B., and Zhang, X.: Winter haze over North China Plain from 2009 to 2016: Influence of emission and meteorology, Environ. Pollut., 242, 1308–1318, https://doi.org/10.1016/j.envpol.2018.08.019, 2018. a
Zhang, Q., Wu, S., Wang, X., Sun, B., and Liu, H.: A PM2.5 concentration prediction model based on multi-task deep learning for intensive air quality monitoring stations, J. Clean. Prod., 275, 122722, https://doi.org/10.1016/j.jclepro.2020.122722, 2020. a
Zhang, S.: Nearest neighbor selection for iteratively kNN imputation, J. Syst. Software, 85, 2541–2552, https://doi.org/10.1016/j.jss.2012.05.073, 2012. a
Zhou, G., Xu, J., Xie, Y., Chang, L., Gao, W., Gu, Y., and Zhou, J.: Numerical air quality forecasting over eastern China: An operational application of WRF-Chem, Atmos. Environ., 153, 94–108, https://doi.org/10.1016/j.atmosenv.2017.01.020, 2017. a
Zimmermann, J. and Poppe, D.: A supplement for the RADM2 chemical mechanism: The photooxidation of isoprene, Atmos. Environ., 30, 1255–1269, https://doi.org/10.1016/1352-2310(95)00417-3, 1996. a
Ziomas, I. C., Melas, D., Zerefos, C. S., Bais, A. F., and Paliatsos, A. G.: Forecasting peak pollutant levels from meteorological variables, Atmos. Environ., 29, 3703–3711, https://doi.org/10.1016/1352-2310(95)00131-H, 1995. a
Short summary
This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
This study proposes a regional feature selection-based machine learning system to predict...
