Articles | Volume 25, issue 1
https://doi.org/10.5194/acp-25-347-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-347-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jan 2025
Research article |
| 09 Jan 2025
| 09 Jan 2025
Opposing trends in the peak and low ozone concentrations in eastern China: anthropogenic and meteorological influences
Zhuang Wang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Chune Shi
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Hao Zhang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Xianguang Ji
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
Yizhi Zhu
School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Congzi Xia
Institute of Big Data for Vocational Education, Guangdong Polytechnic of Science and Technology, Zhuhai 519000, China
Xiaoyun Sun
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Xinfeng Lin
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Shaowei Yan
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Suyao Wang
Huaibei Meteorological Bureau, Huaibei 235000, Anhui, China
Yuan Zhou
Jiangxi Ecological Meteorology Center, Nanchang 330096, China
Nanchang National Climate Observatory, Nanchang 330043, China
Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA, Shouxian 232200, China
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China
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Improved knowledge of the chemistry and drivers of surface ozone over the Qinghai-Tibet Plateau (QTP) is significant for regulatory and control purposes in this high-altitude region in the Himalayas. Our study investigates the processes and drivers of surface ozone anomalies by using machine-learning model-based meteorological normalization methods between 2015 and 2020 in urban areas over the QTP. This study can provide valuable implication for ozone mitigation over the QTP.
Youwen Sun, Hao Yin, Wei Wang, Changgong Shan, Justus Notholt, Mathias Palm, Ke Liu, Zhenyi Chen, and Cheng Liu
Atmos. Meas. Tech., 15, 4819–4834, https://doi.org/10.5194/amt-15-4819-2022, https://doi.org/10.5194/amt-15-4819-2022, 2022
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This study summarizes an overview of the status and perspective of GHG monitoring in China. This study not only improves our understanding with respect to the status, advances, and challenges of GHG monitoring in China but also presents an outlook for further improving GHG monitoring capacity in China.
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EGUsphere, https://doi.org/10.5194/egusphere-2022-578, https://doi.org/10.5194/egusphere-2022-578, 2022
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Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
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Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-187, https://doi.org/10.5194/essd-2022-187, 2022
Manuscript not accepted for further review
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We develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O3 over 2005–2021 in China. It can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).
Hao Yin, Youwen Sun, Justus Notholt, Mathias Palm, and Cheng Liu
Atmos. Chem. Phys., 22, 4167–4185, https://doi.org/10.5194/acp-22-4167-2022, https://doi.org/10.5194/acp-22-4167-2022, 2022
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In this study, we quantity the long-term variabilities and the underlying drivers of NO2 from 2005 to 2020 over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China. We reveal the significant effect of the Action Plan on the Prevention and Control of Air Pollution since 2013 adopted by the Chinese government to reduce NOx pollution. Our study can improve the understanding of pollution control measures on a regional scale.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
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Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
Xiaoyun Sun, Tianliang Zhao, Yongqing Bai, Shaofei Kong, Huang Zheng, Weiyang Hu, Xiaodan Ma, and Jie Xiong
Atmos. Chem. Phys., 22, 3579–3593, https://doi.org/10.5194/acp-22-3579-2022, https://doi.org/10.5194/acp-22-3579-2022, 2022
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This study revealed the impact of anthropogenic emissions and meteorological conditions on PM2.5 decline in the regional transport of air pollutants over a receptor region in central China. The meteorological drivers led to upwind accelerating and downward offsetting of the effects of emission reductions over the receptor region in regional PM2.5 transport, and the contribution of gaseous precursor emissions to PM2.5 pollution was enhanced with reduced anthropogenic emissions in recent years.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Xiangde Xu, Chan Sun, Deliang Chen, Tianliang Zhao, Jianjun Xu, Shengjun Zhang, Juan Li, Bin Chen, Yang Zhao, Hongxiong Xu, Lili Dong, Xiaoyun Sun, and Yan Zhu
Atmos. Chem. Phys., 22, 1149–1157, https://doi.org/10.5194/acp-22-1149-2022, https://doi.org/10.5194/acp-22-1149-2022, 2022
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A vertical transport window of tropospheric vapor exists on the Tibetan Plateau (TP). The TP's thermal forcing drives the vertical transport
windowof vapor in the troposphere. The effects of the TP's vertical transport window of vapor are of importance in global climate change.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608, https://doi.org/10.5194/acp-21-18589-2021, https://doi.org/10.5194/acp-21-18589-2021, 2021
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This study uses high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. These unexpected O3 enhancements were induced by meteorological anomalies and caused dramatically high health risks.
Chengzhi Xing, Cheng Liu, Hongyu Wu, Jinan Lin, Fan Wang, Shuntian Wang, and Meng Gao
Earth Syst. Sci. Data, 13, 4897–4912, https://doi.org/10.5194/essd-13-4897-2021, https://doi.org/10.5194/essd-13-4897-2021, 2021
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Observations of atmospheric composition, especially vertical profile observations, remain sparse and rare on the Tibetan Plateau (TP), due to extremely high altitude, topographical heterogeneity and the grinding environment. This paper introduces a high-time-resolution (~ 15 min) vertical profile observational dataset of atmospheric composition (aerosols, NO2, HCHO and HONO) on the TP for more than 1 year (2017–2019) using a passive remote sensing technique.
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Short summary
This study attempts to explain the surface ozone background and typical and peak trends in eastern China by combining a large number of ground-based and satellite observations. We found diametrically opposed trends in peak (decreasing) and low (increasing) ozone concentrations. Anthropogenic emissions primarily drive trends in low and peak ozone concentrations in eastern China, though meteorological effects also play a role.
This study attempts to explain the surface ozone background and typical and peak trends in...
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