Articles | Volume 23, issue 22
https://doi.org/10.5194/acp-23-14271-2023
© Author(s) 2023. 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-23-14271-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report
| 
16 Nov 2023
Measurement report |
| 16 Nov 2023
| 16 Nov 2023
Measurement report: Dust and anthropogenic aerosols' vertical distributions over northern China dense aerosols gathered at the top of the mixing layer
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, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base 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, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base 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, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base of CMA, Shouxian 232200, China
Yujia Chen
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base of CMA, Shouxian 232200, China
Xiyuan Chi
National Meteorological Center, Beijing 100081, China
Congzi Xia
GBA Branch of Aerospace Information Research Institute, Chinese Academy of Sciences, Guangzhou 510530, China
Suyao Wang
Huaibei Meteorological Bureau, Huaibei 235000, Anhui, China
Yizhi Zhu
School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Kaidi Zhang
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base of CMA, Shouxian 232200, China
Xintong Chen
Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
Shouxian National Climatology Observatory, Shouxian 232200, China
Huaihe River Basin Typical Farmland Ecological Meteorological Field Science Experiment Base of CMA, Shouxian 232200, 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
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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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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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
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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.
Youwen Sun, Hao Yin, Cheng Liu, Lin Zhang, Yuan Cheng, Mathias Palm, Justus Notholt, Xiao Lu, Corinne Vigouroux, Bo Zheng, Wei Wang, Nicholas Jones, Changong Shan, Min Qin, Yuan Tian, Qihou Hu, Fanhao Meng, and Jianguo Liu
Atmos. Chem. Phys., 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021, https://doi.org/10.5194/acp-21-6365-2021, 2021
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This study mapped the drivers of HCHO variability from 2015 to 2019 over eastern China. Hydroxyl (OH) radical production rates from HCHO photolysis were evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO abundance were analyzed. Contributions of various emission sources and geographical regions to the observed HCHO summertime enhancements were determined.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Jan-Lukas Tirpitz, Udo Frieß, François Hendrick, Carlos Alberti, Marc Allaart, Arnoud Apituley, Alkis Bais, Steffen Beirle, Stijn Berkhout, Kristof Bognar, Tim Bösch, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Mirjam den Hoed, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Martina M. Friedrich, Arnoud Frumau, Lou Gast, Clio Gielen, Laura Gomez-Martín, Nan Hao, Arjan Hensen, Bas Henzing, Christian Hermans, Junli Jin, Karin Kreher, Jonas Kuhn, Johannes Lampel, Ang Li, Cheng Liu, Haoran Liu, Jianzhong Ma, Alexis Merlaud, Enno Peters, Gaia Pinardi, Ankie Piters, Ulrich Platt, Olga Puentedura, Andreas Richter, Stefan Schmitt, Elena Spinei, Deborah Stein Zweers, Kimberly Strong, Daan Swart, Frederik Tack, Martin Tiefengraber, René van der Hoff, Michel van Roozendael, Tim Vlemmix, Jan Vonk, Thomas Wagner, Yang Wang, Zhuoru Wang, Mark Wenig, Matthias Wiegner, Folkard Wittrock, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 14, 1–35, https://doi.org/10.5194/amt-14-1-2021, https://doi.org/10.5194/amt-14-1-2021, 2021
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Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a ground-based remote sensing measurement technique that derives atmospheric aerosol and trace gas vertical profiles from skylight spectra. In this study, consistency and reliability of MAX-DOAS profiles are assessed by applying nine different evaluation algorithms to spectral data recorded during an intercomparison campaign in the Netherlands and by comparing the results to colocated supporting observations.
Zhuang Wang, Cheng Liu, Zhouqing Xie, Qihou Hu, Meinrat O. Andreae, Yunsheng Dong, Chun Zhao, Ting Liu, Yizhi Zhu, Haoran Liu, Chengzhi Xing, Wei Tan, Xiangguang Ji, Jinan Lin, and Jianguo Liu
Atmos. Chem. Phys., 20, 14917–14932, https://doi.org/10.5194/acp-20-14917-2020, https://doi.org/10.5194/acp-20-14917-2020, 2020
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Significant stratification of aerosols was observed in North China. Polluted dust dominated above the PBL, and anthropogenic aerosols prevailed within the PBL, which is mainly driven by meteorological conditions. The key role of the elevated dust is to alter atmospheric thermodynamics and stability, causing the suppression of turbulence exchange and a decrease in PBL height, especially during the dissipation stage, thereby inhibiting dissipation of persistent heavy surface haze pollution.
Wenjing Su, Cheng Liu, Ka Lok Chan, Qihou Hu, Haoran Liu, Xiangguang Ji, Yizhi Zhu, Ting Liu, Chengxin Zhang, Yujia Chen, and Jianguo Liu
Atmos. Meas. Tech., 13, 6271–6292, https://doi.org/10.5194/amt-13-6271-2020, https://doi.org/10.5194/amt-13-6271-2020, 2020
Short summary
Short summary
The paper presents an improved retrieval of the TROPOMI tropospheric HCHO column over China. The new retrieval optimized both slant column retrieval and air mass factor calculation for TROPOMI observations of HCHO over China. The improved TROPOMI HCHO is subsequently validated by MAX-DOAS observations. Compared to the operational product, the improved HCHO agrees better with the MAX-DOAS data and thus is better suited for the analysis of regional- and city-scale pollution in China.
Yang Wang, Arnoud Apituley, Alkiviadis Bais, Steffen Beirle, Nuria Benavent, Alexander Borovski, Ilya Bruchkouski, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Henning Finkenzeller, Martina M. Friedrich, Udo Frieß, David Garcia-Nieto, Laura Gómez-Martín, François Hendrick, Andreas Hilboll, Junli Jin, Paul Johnston, Theodore K. Koenig, Karin Kreher, Vinod Kumar, Aleksandra Kyuberis, Johannes Lampel, Cheng Liu, Haoran Liu, Jianzhong Ma, Oleg L. Polyansky, Oleg Postylyakov, Richard Querel, Alfonso Saiz-Lopez, Stefan Schmitt, Xin Tian, Jan-Lukas Tirpitz, Michel Van Roozendael, Rainer Volkamer, Zhuoru Wang, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Thomas Wagner
Atmos. Meas. Tech., 13, 5087–5116, https://doi.org/10.5194/amt-13-5087-2020, https://doi.org/10.5194/amt-13-5087-2020, 2020
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Short summary
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.
The annual cycle of dust and anthropogenic aerosols' vertical distributions was revealed by...
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