Articles | Volume 22, issue 15
https://doi.org/10.5194/acp-22-10389-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-22-10389-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Aug 2022
Research article |
| 15 Aug 2022
| 15 Aug 2022
Long-range transport of Asian dust to the Arctic: identification of transport pathways, evolution of aerosol optical properties, and impact assessment on surface albedo changes
Xiaoxi Zhao
Center for Atmospheric Chemistry Study, Shanghai Key Laboratory of
Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
Kan Huang
CORRESPONDING AUTHOR
Center for Atmospheric Chemistry Study, Shanghai Key Laboratory of
Atmospheric Particle Pollution and Prevention (LAP), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200433, China
Institute of Eco-Chongming (IEC), Shanghai, 202162, China
Joshua S. Fu
Department of Civil and Environmental Engineering, University of
Tennessee, Knoxville, TN, USA
Sabur F. Abdullaev
Physical Technical Institute of the Academy of Sciences of Tajikistan, Dushanbe, Tajikistan
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Julian Hofer, Holger Baars, Zhenping Yin, Andi Klamt, Martin Radenz, Leonard König, Athena A. Floutsi, Cristofer Jimenez, Moritz Haarig, Dietrich Althausen, Benedikt Gast, Håvard S. Buholdt, Nathan Skupin, Jonas Neumann, Sabur F. Abdullozoda, Abduvosit N. Makhmudov, Johannes Bühl, Ronny Engelmann, Ulla Wandinger, and Albert Ansmann
EGUsphere, https://doi.org/10.5194/egusphere-2026-3928, https://doi.org/10.5194/egusphere-2026-3928, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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A comparison of manually and automatically analyzed lidar profiles of aerosol optical properties is presented. The manual analysis was performed using a custom software in multiple analyses steps based on visual inspection of the lidar signals. The automatic analysis was performed using an automatic processing chain. The comparison shows good agreement and demonstrates the suitability of the automatic retrievals for various applications of aerosol optical property profiles.
Georg Holger Müller, Athena Augusta Floutsi, Julian Hofer, Ronny Engelmann, Dietrich Althausen, Ulla Wandinger, Martin Radenz, Moritz Haarig, Sabur Fuzailovich Abdullaev, Shohina Kh. Khalifaeva, Albert Ansmann, and Holger Baars
EGUsphere, https://doi.org/10.5194/egusphere-2026-3390, https://doi.org/10.5194/egusphere-2026-3390, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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A five-year dataset of lidar measurements from Dushanbe, Tajikistan, was analyzed to investigate the annual dust cycle and intraanual variability in the region. The dataset consists of automatically processed data, including the separation of the dust and non-dust particle backscatter coefficient and enabling the calculation of monthly and seasonal dust mass concentration within the atmosphere. The study highlights the importance of continuous lidar measurements in the Central Asian region.
Shichang Kang, Jie Huang, Qianggong Zhang, Junming Guo, Xiufeng Yin, Shiwei Sun, Xuejun Sun, Lekhendra Tripathee, Sabur Abdullaev, Wenjun Tang, Yi Zhang, Xiwen Miao, Liujian Liao, and Lusheng Che
Earth Syst. Sci. Data, 18, 4943–4963, https://doi.org/10.5194/essd-18-4943-2026, https://doi.org/10.5194/essd-18-4943-2026, 2026
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The Third Pole is a critical region for studying global mercury (Hg) cycling due to its extensive cryosphere. This comprehensive dataset-spanning air, aerosols, precipitation, glaciers, soils, surface waters, ice cores, and sediments-was collected through the Atmospheric Pollution and Cryospheric Change program. It reveals spatial and temporal Hg patterns influenced by emissions, transport, and deposition processes. The data support interdisciplinary research on multi-sphere interactions.
Holger Baars, Moritz Haarig, Leonard König, Athena A. Floutsi, Elizaveta Basharova, Julian Hofer, Henriette Gebauer, Ronny Engelmann, Dietrich Althausen, Annett Skupin, Benedikt Gast, Felix Fritzsch, Kevin Ohneiser, Cristofer Jimenez, Tom Gaudek, Martin Radenz, Håvard Buholdt, Birgit Heese, Andi Klamt, Patric Seifert, David P. Donovan, Gerd-Jan van Zadelhoff, Sabur F. Abdullaev, Shohina K. Khalifaeva, Dilovar F. Nozirov, and Ulla Wandinger
Atmos. Meas. Tech., 19, 3831–3864, https://doi.org/10.5194/amt-19-3831-2026, https://doi.org/10.5194/amt-19-3831-2026, 2026
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The satellite mission EarthCARE (Earth Cloud, Aerosol, and Radiation Explorer) was launched in May 2024 and has 4 unique instruments on board. We used ground-based PollyNET/ACTRIS (Aerosol, Clouds and Trace gases Research Infrastructure) profiling data to discuss the quality of EarthCARE’s lidar products based on case studies from different geographic locations. Our investigations revealed that the space-borne lidar instrument has remarkable profiling capabilities but currently also still some limitations, however, not preventing first scientific studies when quality checking the data intensively.
Rong-You Chien and Joshua S. Fu
EGUsphere, https://doi.org/10.5194/egusphere-2026-1451, https://doi.org/10.5194/egusphere-2026-1451, 2026
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We built a faster way to calculate atmospheric chemistry in a major climate model. It cut computing time by about one third while producing nearly the same ozone results and remaining stable in year-long runs. We did this to help climate models handle growing chemical detail and finer time steps more efficiently. We compared the new approach with the model’s standard method in short and long simulations and found that it can save time without reducing reliability.
Yan Zhang, Jiani Tan, Qing Mu, Joshua S. Fu, and Li Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-6160, https://doi.org/10.5194/egusphere-2025-6160, 2026
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Despite growing use of machine learning in environmental research, few have studied how input data affects findings. We examined the impact of input data characteristics on nitrogen deposition estimates in East and Southeast Asia. Insufficient sample size cuts accuracy by up to 12 %, while data-scarce and remote areas show up to 50 % bias due to poor training data representation. We created a transferable framework for uncertainty quantification, applicable to other data-scarce geospatial tasks.
Xiaofei Qin, Hao Li, Jia Chen, Junjie Wei, Hao Ding, Xiaohao Wang, Guochen Wang, Chengfeng Liu, Da Lu, Shengqian Zhou, Haowen Li, Yucheng Zhu, Ziwei Liu, Qingyan Fu, Juntao Huo, Yanfen Lin, Congrui Deng, Yisheng Zhang, and Kan Huang
Atmos. Chem. Phys., 25, 13815–13830, https://doi.org/10.5194/acp-25-13815-2025, https://doi.org/10.5194/acp-25-13815-2025, 2025
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Mercury is a persistent toxic pollutant that has equally important anthropogenic and natural sources. This study developed a quantitative method for separating the anthropogenic and natural contributions of total gaseous mercury. The underlying impacts on the sea–air exchange fluxes of mercury are evaluated. The new method developed in this study can be reproduced in other regions, and the findings are innovative in the field of mercury sources and biogeochemical cycles.
Xin Xi, Jun Wang, Zhendong Lu, Andrew M. Sayer, Jaehwa Lee, Robert C. Levy, Yujie Wang, Alexei Lyapustin, Hongqing Liu, Istvan Laszlo, Changwoo Ahn, Omar Torres, Sabur Abdullaev, James Limbacher, and Ralph A. Kahn
Atmos. Chem. Phys., 25, 7403–7429, https://doi.org/10.5194/acp-25-7403-2025, https://doi.org/10.5194/acp-25-7403-2025, 2025
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The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and dynamic surfaces and the lack of in situ constraints on aerosol properties. The performance and consistency of satellite algorithms in observing Aralkum-generated saline dust remain unknown. This study compares multisensor UVAI (ultraviolet aerosol index), AOD (aerosol optical depth), and ALH (aerosol layer height) products and reveals inconsistencies and potential biases over the Aral Sea basin.
Steven Soon-Kai Kong, Joshua S. Fu, Neng-Huei Lin, Guey-Rong Sheu, and Wei-Syun Huang
Atmos. Chem. Phys., 25, 7245–7268, https://doi.org/10.5194/acp-25-7245-2025, https://doi.org/10.5194/acp-25-7245-2025, 2025
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The accuracy of the chemical transport model, a key focus of our research, is strongly dependent on the dry deposition parameterization. Our findings show that the refined CMAQ dust model correlated well with ground-based and high-altitude in situ measurements by implementing the suggested dry deposition schemes. Furthermore, we reveal the mixing state of two types of aerosols at the upper level, a finding supported by both the optimized model and measurements.
Hanzheng Zhu, Yaman Liu, Man Yue, Shihui Feng, Pingqing Fu, Kan Huang, Xinyi Dong, and Minghuai Wang
Atmos. Chem. Phys., 25, 5175–5197, https://doi.org/10.5194/acp-25-5175-2025, https://doi.org/10.5194/acp-25-5175-2025, 2025
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Dust-soluble iron deposition from East Asia plays an important role in the marine ecology of the Northwest Pacific. Using the developed model, our findings highlight a dual trend: a decrease in the overall deposition of soluble iron from dust but an increase in the solubility of the iron itself due to the enhanced atmospheric processing. The study underscores the critical roles of both dust emission and atmospheric processing in soluble iron deposition and marine ecology.
Ling Huang, Xinxin Zhang, Chris Emery, Qing Mu, Greg Yarwood, Hehe Zhai, Zhixu Sun, Shuhui Xue, Yangjun Wang, Joshua S. Fu, and Li Li
Atmos. Chem. Phys., 25, 4233–4249, https://doi.org/10.5194/acp-25-4233-2025, https://doi.org/10.5194/acp-25-4233-2025, 2025
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Ground-level ozone pollution has emerged as a significant air pollutant in China. Chemical transport models (CTMs) serve as crucial tools in addressing ozone pollution. This study reviews CTM applications for simulating ozone in China and proposes goal and criteria benchmark values for evaluating ozone. Along with prior work on PM₂₅ and other pollutants, this effort establishes a comprehensive framework for evaluating CTM performance in China.
Wenxin Zhang, Yaman Liu, Man Yue, Xinyi Dong, Kan Huang, and Minghuai Wang
Atmos. Chem. Phys., 25, 3857–3872, https://doi.org/10.5194/acp-25-3857-2025, https://doi.org/10.5194/acp-25-3857-2025, 2025
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Understanding long-term organic aerosol (OA) trends and their driving factors is important for air quality management. Our modeling revealed that OA in China increased by 5.6 % from 1990 to 2019, primarily due to a 32.3 % increase in secondary organic aerosols (SOAs) and an 8.1 % decrease in primary organic aerosols (POAs), both largely driven by changes in anthropogenic emissions. Biogenic SOA increased due to warming but showed little response to changes in anthropogenic nitrogen oxide emissions.
Siwei Li, Yu Ding, Jia Xing, and Joshua S. Fu
Earth Syst. Sci. Data, 16, 3781–3793, https://doi.org/10.5194/essd-16-3781-2024, https://doi.org/10.5194/essd-16-3781-2024, 2024
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Surface PM2.5 data have gained widespread application in health assessments and related fields, while the inherent uncertainties in PM2.5 data persist due to the lack of ground-truth data across the space. This study provides a novel testbed, enabling comprehensive evaluation across the entire spatial domain. The optimized deep-learning model with spatiotemporal features successfully retrieved surface PM2.5 concentrations in China (2013–2021), with reduced biases induced by sample imbalance.
Victoria A. Flood, Kimberly Strong, Cynthia H. Whaley, Kaley A. Walker, Thomas Blumenstock, James W. Hannigan, Johan Mellqvist, Justus Notholt, Mathias Palm, Amelie N. Röhling, Stephen Arnold, Stephen Beagley, Rong-You Chien, Jesper Christensen, Makoto Deushi, Srdjan Dobricic, Xinyi Dong, Joshua S. Fu, Michael Gauss, Wanmin Gong, Joakim Langner, Kathy S. Law, Louis Marelle, Tatsuo Onishi, Naga Oshima, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Manu A. Thomas, Svetlana Tsyro, and Steven Turnock
Atmos. Chem. Phys., 24, 1079–1118, https://doi.org/10.5194/acp-24-1079-2024, https://doi.org/10.5194/acp-24-1079-2024, 2024
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It is important to understand the composition of the Arctic atmosphere and how it is changing. Atmospheric models provide simulations that can inform policy. This study examines simulations of CH4, CO, and O3 by 11 models. Model performance is assessed by comparing results matched in space and time to measurements from five high-latitude ground-based infrared spectrometers. This work finds that models generally underpredict the concentrations of these gases in the Arctic troposphere.
Da Lu, Hao Li, Mengke Tian, Guochen Wang, Xiaofei Qin, Na Zhao, Juntao Huo, Fan Yang, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Xinyi Dong, Congrui Deng, Sabur F. Abdullaev, and Kan Huang
Atmos. Chem. Phys., 23, 13853–13868, https://doi.org/10.5194/acp-23-13853-2023, https://doi.org/10.5194/acp-23-13853-2023, 2023
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Environmental conditions during dust are usually not favorable for secondary aerosol formation. However in this study, an unusual dust event was captured in a Chinese mega-city and showed “anomalous” meteorology and a special dust backflow transport pathway. The underlying formation mechanisms of secondary aerosols are probed in the context of this special dust event. This study shows significant implications for the varying dust aerosol chemistry in the future changing climate.
Hannah J. Rubin, Joshua S. Fu, Frank Dentener, Rui Li, Kan Huang, and Hongbo Fu
Atmos. Chem. Phys., 23, 7091–7102, https://doi.org/10.5194/acp-23-7091-2023, https://doi.org/10.5194/acp-23-7091-2023, 2023
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We update the 2010 global deposition budget for nitrogen (N) and sulfur (S) with new regional wet deposition measurements, improving the ensemble results of 11 global chemistry transport models from HTAP II. Our study demonstrates that a global measurement–model fusion approach can substantially improve N and S deposition model estimates at a regional scale and represents a step forward toward the WMO goal of global fusion products for accurately mapping harmful air pollution.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
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DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
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This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
Xiaofei Qin, Shengqian Zhou, Hao Li, Guochen Wang, Cheng Chen, Chengfeng Liu, Xiaohao Wang, Juntao Huo, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Kan Huang, and Congrui Deng
Atmos. Chem. Phys., 22, 15851–15865, https://doi.org/10.5194/acp-22-15851-2022, https://doi.org/10.5194/acp-22-15851-2022, 2022
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Using artificial neural network modeling and an explainable analysis approach, natural surface emissions (NSEs) were identified as a main driver of gaseous elemental mercury (GEM) variations during the COVID-19 lockdown. A sharp drop in GEM concentrations due to a significant reduction in anthropogenic emissions may disrupt the surface–air exchange balance of Hg, leading to increases in NSEs. This implies that NSEs may pose challenges to the future control of Hg pollution.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Yun Fat Lam, Chi Chiu Cheung, Xuguo Zhang, Joshua S. Fu, and Jimmy Chi Hung Fung
Atmos. Chem. Phys., 21, 12895–12908, https://doi.org/10.5194/acp-21-12895-2021, https://doi.org/10.5194/acp-21-12895-2021, 2021
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In recent years, air pollution forecasting has become an important municipal service of the government. In this study, a new spatial allocation method based on satellite remote sensing and GIS techniques was developed to address the spatial deficiency of industrial source emissions in China, providing a substantial improvement on NO2 and PM2.5 forecast for the Pearl River Delta/Greater Bay Area.
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Short summary
Long-range transport of Asian dust to the Arctic was considered an important source of Arctic air pollution. Different transport routes to the Arctic had divergent effects on the evolution of aerosol properties. Depositions of long-range-transported dust particles can reduce the Arctic surface albedo considerably. This study implied that the ubiquitous long-transport dust from China exerted considerable aerosol indirect effects on the Arctic and may have potential biogeochemical significance.
Long-range transport of Asian dust to the Arctic was considered an important source of Arctic...
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