Articles | Volume 18, issue 5
https://doi.org/10.5194/essd-18-3559-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-3559-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A dataset of vertical profiles of O3 and HONO from the hyperspectral vertical remote sensing network in China (2021–2024)
Tiliang Zou
School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China
Xiangguang Ji
State Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology, Anhui University, Hefei, 230601, China
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, Anhui, 230601, China
Shaocong Wei
Institute of Environment Hefei Comprehensive National Science Center, Hefei, 230031, China
Wei Tan
Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China
Haoran Liu
Institute of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China
Institute of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026, 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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Zhongfeng Pan, Hao Yin, Zhenda Sun, Chongyang Li, Youwen Sun, and Cheng Liu
Atmos. Chem. Phys., 26, 2545–2559, https://doi.org/10.5194/acp-26-2545-2026, https://doi.org/10.5194/acp-26-2545-2026, 2026
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This study examines air pollution in Beijing-Tianjin-Hebei and the Yangtze River Delta from 2015 to 2022. PM2.5 (particulate matter) decreased by 9.1-31.4 μg/m³ and PM10 by 9.8–42.9 μg/m³. Weather factors like humidity, air pressure, and rainfall influenced pollution, with tailored solutions needed for different regions.
Zhenda Sun, Hao Yin, Zhongfeng Pan, Chongyang Li, Ke Liu, Yu Yang, Youwen Sun, and Cheng Liu
EGUsphere, https://doi.org/10.5194/egusphere-2025-6052, https://doi.org/10.5194/egusphere-2025-6052, 2025
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We studied how nitrogen dioxide moves into and out of the Tibetan Plateau over the past two decades using satellite and ground observations. We found that pollution near the ground has decreased in cities, but levels higher in the air have risen. The plateau acts as a two-way passage, receiving pollution from the southwest and sending it northeast. These changes mean that the region is becoming more important for air quality and environmental conditions across a wider area.
Qijin Zhang, Chengzhi Xing, Yikai Li, Haochen Peng, Haoran Liu, Chao Liu, Zhiguo Zhang, Wanchao Ma, Tianyu Tang, and Cheng Liu
EGUsphere, https://doi.org/10.5194/egusphere-2025-5807, https://doi.org/10.5194/egusphere-2025-5807, 2025
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Our study uses ship-based MAX-DOAS to validate multi-satellite products (TROPOMI, GEMS, GOME-2) and identify source mechanisms of BrO (sea ice-coupled photochemistry) and IO (biogenic-driven).
Zhenda Sun, Hao Yin, Zhongfeng Pan, Chongyang Li, Xiao Lu, Ke Liu, Youwen Sun, and Cheng Liu
Atmos. Chem. Phys., 25, 6823–6842, https://doi.org/10.5194/acp-25-6823-2025, https://doi.org/10.5194/acp-25-6823-2025, 2025
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This study investigates the variability and driving forces of transboundary CO transport flux over the Tibetan Plateau from May 2018 to April 2024. During this period, external CO influx increased by 2.86 Tg yr-1, while internal efflux slightly declined by 1.70 Tg yr-1. The rising influx in recent years is likely linked to the rapid increase in CO concentrations from South Asia.
Peiyuan Jiao, Chengzhi Xing, Yikai Li, Xiangguang Ji, Wei Tan, Qihua Li, Haoran Liu, and Cheng Liu
Earth Syst. Sci. Data, 17, 3167–3187, https://doi.org/10.5194/essd-17-3167-2025, https://doi.org/10.5194/essd-17-3167-2025, 2025
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Vertical profile observations are key to understanding regional air pollution but remain scarce due to existing limits. This study presents a high-time-resolution (ca. 15 min) dataset of aerosol, nitrogen dioxide, and formaldehyde vertical profiles from 32 sites in China (2019–2023) using passive remote sensing. It documents vertical distribution, seasonal variations, and diurnal patterns, revealing long-term trends. Data are available at Zenodo under https://doi.org/10.5281/zenodo.15211604.
Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu
Atmos. Chem. Phys., 25, 759–770, https://doi.org/10.5194/acp-25-759-2025, https://doi.org/10.5194/acp-25-759-2025, 2025
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This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
Zhuang Wang, Chune Shi, Hao Zhang, Xianguang Ji, Yizhi Zhu, Congzi Xia, Xiaoyun Sun, Xinfeng Lin, Shaowei Yan, Suyao Wang, Yuan Zhou, Chengzhi Xing, Yujia Chen, and Cheng Liu
Atmos. Chem. Phys., 25, 347–366, https://doi.org/10.5194/acp-25-347-2025, https://doi.org/10.5194/acp-25-347-2025, 2025
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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.
Chengzhi Xing, Cheng Liu, Chunxiang Ye, Jingkai Xue, Hongyu Wu, Xiangguang Ji, Jinping Ou, and Qihou Hu
Atmos. Chem. Phys., 24, 10093–10112, https://doi.org/10.5194/acp-24-10093-2024, https://doi.org/10.5194/acp-24-10093-2024, 2024
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We identified the contributions of ozone (O3) and nitrous acid (HONO) to the production rates of hydroxide (OH) in vertical space on the Tibetan Plateau (TP). A new insight was offered: the contributions of HONO and O3 to the production rates of OH on the TP are even greater than in lower-altitudes areas. This study enriches the understanding of vertical distribution of atmospheric components and explains the strong atmospheric oxidation capacity (AOC) on the TP.
Zhuang Wang, Chune Shi, Hao Zhang, Yujia Chen, Xiyuan Chi, Congzi Xia, Suyao Wang, Yizhi Zhu, Kaidi Zhang, Xintong Chen, Chengzhi Xing, and Cheng Liu
Atmos. Chem. Phys., 23, 14271–14292, https://doi.org/10.5194/acp-23-14271-2023, https://doi.org/10.5194/acp-23-14271-2023, 2023
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The annual cycle of dust and anthropogenic aerosols' vertical distributions was revealed by polarization Raman lidar in Beijing. Anthropogenic aerosols typically accumulate at the top of the mixing layer (ML) due to the hygroscopic growth of atmospheric particles, and this is most significant in summer. There is no significant relationship between bottom dust mass concentration and ML height, while the dust in the upper air tends to be distributed near the mixing layer.
Chengzhi Xing, Shiqi Xu, Yuhang Song, Cheng Liu, Yuhan Liu, Keding Lu, Wei Tan, Chengxin Zhang, Qihou Hu, Shanshan Wang, Hongyu Wu, and Hua Lin
Atmos. Chem. Phys., 23, 5815–5834, https://doi.org/10.5194/acp-23-5815-2023, https://doi.org/10.5194/acp-23-5815-2023, 2023
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High RH could contribute to the secondary formation of HONO in the sea atmosphere. High temperature could promote the formation of HONO from NO2 heterogeneous reactions in the sea and coastal atmosphere. The aerosol surface plays a more important role during the above process in coastal and sea cases. The generation rate of HONO from the NO2 heterogeneous reaction in the sea cases is larger than that in inland cases in higher atmospheric layers above 600 m.
Yuhang Song, Chengzhi Xing, Cheng Liu, Jinan Lin, Hongyu Wu, Ting Liu, Hua Lin, Chengxin Zhang, Wei Tan, Xiangguang Ji, Haoran Liu, and Qihua Li
Atmos. Chem. Phys., 23, 1803–1824, https://doi.org/10.5194/acp-23-1803-2023, https://doi.org/10.5194/acp-23-1803-2023, 2023
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Using the MAX-DOAS network, we successfully analyzed three typical transport types (regional, dust, and transboundary long-range transport), emphasizing the unique advantages provided by the network in monitoring pollutant transport. We think that our findings provide the public with a thorough understanding of pollutant transport phenomena and a reference for designing collaborative air pollution control strategies.
Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov
Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022, https://doi.org/10.5194/amt-15-6739-2022, 2022
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CFC-11 and CFC-12, which are classified as ozone-depleting substances, also have high global warming potentials. This paper describes obtaining the CFC-11 and CFC-12 total columns from the solar spectra based on ground-based Fourier transform infrared spectroscopy at Hefei, China. The seasonal variation and annual trend of the two gases are analyzed, and then the data are compared with other independent datasets.
Hao Yin, Youwen Sun, Justus Notholt, Mathias Palm, Chunxiang Ye, and Cheng Liu
Atmos. Chem. Phys., 22, 14401–14419, https://doi.org/10.5194/acp-22-14401-2022, https://doi.org/10.5194/acp-22-14401-2022, 2022
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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.
Bo Li, Cheng Liu, Qihou Hu, Mingzhai Sun, Chengxin Zhang, Shulin Zhang, Yizhi Zhu, Ting Liu, Yike Guo, Gregory R. Carmichael, and Meng Gao
EGUsphere, https://doi.org/10.5194/egusphere-2022-578, https://doi.org/10.5194/egusphere-2022-578, 2022
Preprint archived
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Ambient particles have an important impact on human health, meteorology and climate change. By building a deep spatiotemporal neural network model we have overcome the long-standing limitations and get the full time and space coverage ground PM2.5 concentrations. We open the neural network black box data model by using sensitivity analysis and visualization techniques. This research will help improve health effects studies, climate effects of aerosols, and air quality prediction.
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
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
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.
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.
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.
Mingshuai Zhang, Chun Zhao, Yuhan Yang, Qiuyan Du, Yonglin Shen, Shengfu Lin, Dasa Gu, Wenjing Su, and Cheng Liu
Geosci. Model Dev., 14, 6155–6175, https://doi.org/10.5194/gmd-14-6155-2021, https://doi.org/10.5194/gmd-14-6155-2021, 2021
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Biogenic volatile organic compounds (BVOCs) can influence atmospheric chemistry and secondary pollutant formation. This study examines the performance of different versions of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in modeling BVOCs and ozone and their sensitivities to vegetation distributions over eastern China. The results suggest more accurate vegetation distribution and measurements of BVOC emission fluxes are needed to reduce the uncertainties.
Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
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This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Youwen Sun, Hao Yin, Cheng Liu, Emmanuel Mahieu, Justus Notholt, Yao Té, Xiao Lu, Mathias Palm, Wei Wang, Changgong Shan, Qihou Hu, Min Qin, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 11759–11779, https://doi.org/10.5194/acp-21-11759-2021, https://doi.org/10.5194/acp-21-11759-2021, 2021
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The variability, sources, and transport of ethane (C2H6) over eastern China from 2015 to 2020 were studied using ground-based Fourier transform infrared (FTIR) spectroscopy and GEOS-Chem simulations. C2H6 variability is driven by both meteorological and emission factors. The reduction in C2H6 in recent years over eastern China points to air quality improvement in China.
Youwen Sun, Hao Yin, Yuan Cheng, Qianggong Zhang, Bo Zheng, Justus Notholt, Xiao Lu, Cheng Liu, Yuan Tian, and Jianguo Liu
Atmos. Chem. Phys., 21, 9201–9222, https://doi.org/10.5194/acp-21-9201-2021, https://doi.org/10.5194/acp-21-9201-2021, 2021
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We quantified the variability, source, and transport of urban CO over the Himalayas and Tibetan Plateau (HTP) by using measurement, model simulation, and the analysis of meteorological fields. Urban CO over the HTP is dominated by anthropogenic and biomass burning emissions from local, South Asia and East Asia, and oxidation sources. The decreasing trends in surface CO since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.
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Short summary
Here we present vertical profile measurements of HONO (Nitrous acid) and O3 acquired by the Chinese Hyperspectral Vertical Remote Sensing Network during 2021–2024. The dataset comprises 22 representative sites spanning urban, suburban, plateau, and basin environments, covering diverse surface and climatic regimes.
Here we present vertical profile measurements of HONO (Nitrous acid) and O3 acquired by the...
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