Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6155-2021
© Author(s) 2021. 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-14-6155-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
13 Oct 2021
Model description paper |
| 13 Oct 2021
| 13 Oct 2021
Modeling sensitivities of BVOCs to different versions of MEGAN emission schemes in WRF-Chem (v3.6) and its impacts over eastern China
Mingshuai Zhang
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
Chun Zhao
CORRESPONDING AUTHOR
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
CAS Center for Excellence in Comparative Planetology, University of Science and Technology of China, Hefei, China
Frontiers Science Center for Planetary Exploration and Emerging Technologies, University of Science and Technology of China, Hefei, China
Yuhan Yang
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
Qiuyan Du
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
Yonglin Shen
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Shengfu Lin
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, China
Division of Environment and Sustainability, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China
Wenjing Su
Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
Cheng Liu
Department of Precision Machinery and Precision Instrument, University of Science and Technology of China, Hefei, China
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Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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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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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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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.
Eliane Gomes Alves, Raoni Aquino Santana, Cléo Quaresma Dias-Júnior, Santiago Botía, Tyeen Taylor, Ana Maria Yáñez-Serrano, Jürgen Kesselmeier, Efstratios Bourtsoukidis, Jonathan Williams, Pedro Ivo Lembo Silveira de Assis, Giordane Martins, Rodrigo de Souza, Sérgio Duvoisin Júnior, Alex Guenther, Dasa Gu, Anywhere Tsokankunku, Matthias Sörgel, Bruce Nelson, Davieliton Pinto, Shujiro Komiya, Diogo Martins Rosa, Bettina Weber, Cybelli Barbosa, Michelle Robin, Kenneth J. Feeley, Alvaro Duque, Viviana Londoño Lemos, Maria Paula Contreras, Alvaro Idarraga, Norberto López, Chad Husby, Brett Jestrow, and Iván Mauricio Cely Toro
Atmos. Chem. Phys., 23, 8149–8168, https://doi.org/10.5194/acp-23-8149-2023, https://doi.org/10.5194/acp-23-8149-2023, 2023
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Isoprene is emitted mainly by plants and can influence atmospheric chemistry and air quality. But, there are uncertainties in model emission estimates and follow-up atmospheric processes. In our study, with long-term observational datasets of isoprene and biological and environmental factors from central Amazonia, we show that isoprene emission estimates could be improved when biological processes were mechanistically incorporated into the model.
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
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.
Hongxia Zhu, Rui Li, Shuping Yang, Chun Zhao, Zhe Jiang, and Chen Huang
Atmos. Chem. Phys., 23, 2421–2437, https://doi.org/10.5194/acp-23-2421-2023, https://doi.org/10.5194/acp-23-2421-2023, 2023
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The impacts of atmospheric dust aerosols and cloud dynamic conditions on precipitation vertical development in southeastern China were studied using multiple satellite observations. It was found that the precipitating drops under dusty conditions grow faster in the middle layer but slower in the upper and lower layers compared with their pristine counterparts. Quantitative estimation of the sensitivity of the precipitation top temperature to the dust aerosol optical depth is also provided.
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
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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.
Qiongqiong Wang, Shan Wang, Yuk Ying Cheng, Hanzhe Chen, Zijing Zhang, Jinjian Li, Dasa Gu, Zhe Wang, and Jian Zhen Yu
Atmos. Chem. Phys., 22, 11239–11253, https://doi.org/10.5194/acp-22-11239-2022, https://doi.org/10.5194/acp-22-11239-2022, 2022
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Secondary organic aerosol (SOA) is often enhanced during fine-particulate-matter (PM2.5) episodes. We examined bi-hourly measurements of SOA molecular tracers in suburban Hong Kong during 11 city-wide PM2.5 episodes. The tracers showed regional characteristics for both anthropogenic and biogenic SOA as well as biomass-burning-derived SOA. Multiple tracers of the same precursor revealed the dominance of low-NOx formation pathways for isoprene SOA and less-aged monoterpene SOA during winter.
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.
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022, https://doi.org/10.5194/gmd-15-6143-2022, 2022
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Accurate prediction of aerosol pH in chemical transport models is essential to aerosol modeling. This study examines the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) on aerosol pH predictions and the sensitivities to emissions of nonvolatile cations and NH3, aerosol-phase state assumption, and heterogeneous sulfate production. Temporal evolution of aerosol pH during haze cycles in Beijing and the driving factors are also presented and discussed.
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
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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.
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218, https://doi.org/10.5194/gmd-15-199-2022, https://doi.org/10.5194/gmd-15-199-2022, 2022
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Regional models are widely used to investigate aerosol climatic impacts. However, there are few studies examining the sensitivities of modeling results to regional domain size. In this study, the regional model is used to study the aerosol impacts on the East Asian summer monsoon system and focus on the modeling sensitivities to domain size. This study highlights the important impacts of domain size on regional modeling results of aerosol climatic impacts, which may not be limited to East Asia.
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
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.
Biogenic volatile organic compounds (BVOCs) can influence atmospheric chemistry and secondary...
