Articles | Volume 17, issue 10
https://doi.org/10.5194/essd-17-5355-2025
© 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/essd-17-5355-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Oct 2025
Data description paper |
| 15 Oct 2025
| 15 Oct 2025
A full-coverage satellite-based global atmospheric CO2 dataset at 0.05° resolution from 2015 to 2021 for exploring global carbon dynamics
Zhige Wang
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, 310058, China
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
UK Centre for Ecology & Hydrology, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK
Kejian Shi
School of Geographical Sciences, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China
Yulin Shangguan
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, 310058, China
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Bifeng Hu
Department of Land Resource Management, School of Public Administration, Jiangxi University of Finance and Economics, Nanchang, 330013, China
Key Laboratory of Data Science in Finance and Economics of Jiangxi Province, Jiangxi University of Finance and Economics, Nanchang, 330013, China
Xueyao Chen
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, 310058, China
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Department of Earth and Environmental Sciences, Faculty of Science, The Chinese University of Hong Kong, Sha Tin, Hong Kong, China
Danqing Wei
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, 310058, China
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Zhejiang Economic Information Center, Hangzhou, 310006, China
State Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, 310058, China
College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 311215, China
Peter M. Atkinson
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
Geography and Environment, University of Southampton, Highfield, Southampton SO17 1BJ, UK
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
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Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
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Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
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Secondary organic aerosol (SOA) is an important aspect of poor air quality for urban regions around the world, where a large fraction of the population lives. However, there is still large uncertainty in predicting SOA in urban regions. Here, we used data from 11 urban campaigns and show that the variability in SOA production in these regions is predictable and is explained by key emissions. These results are used to estimate the premature mortality associated with SOA in urban regions.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
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Bo Zheng, Qiang Zhang, Guannan Geng, Cuihong Chen, Qinren Shi, Mengshi Cui, Yu Lei, and Kebin He
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Here we report the monthly anthropogenic pollutant emissions in China during the COVID-19 pandemic by using a bottom-up approach based on near-real-time data. The COVID lockdowns were estimated to have reduced China's emissions substantially between January and March in 2020, with the largest reduction in February. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to levels comparable to those of 2019 through December 2020.
Jun Liu, Dan Tong, Yixuan Zheng, Jing Cheng, Xinying Qin, Qinren Shi, Liu Yan, Yu Lei, and Qiang Zhang
Atmos. Chem. Phys., 21, 1627–1647, https://doi.org/10.5194/acp-21-1627-2021, https://doi.org/10.5194/acp-21-1627-2021, 2021
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In this study, we investigated the decadal changes in carbon dioxide and air pollutant emissions in China's cement industry for the period 1990–2015 based on intensive unit-based information. We found that from 1990 to 2015, accompanied by a 10.3-fold increase in cement production, CO2, SO2, and NOx emissions from China's cement industry increased by 627 %, 56 %, and 659 %, whereas CO, PM2.5, and PM10 emissions decreased by 9 %, 63 %, and 59 %, respectively.
Yarong Peng, Hongli Wang, Qian Wang, Shengao Jing, Jingyu An, Yaqin Gao, Cheng Huang, Rusha Yan, Haixia Dai, Tiantao Cheng, Qiang Zhang, Meng Li, Li Li, Shengrong Lou, Shikang Tao, Qinyao Hu, Jun Lu, and Changhong Chen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1108, https://doi.org/10.5194/acp-2020-1108, 2020
Revised manuscript not accepted
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The evolution of NMHCs emissions and the effectiveness of control measures were investigated based on long term measurements in a megacity of China. Discrepancies between measurements and emission inventories emphasized the need for emission validation both in speciation and sources. Varied trends of NMHCs speciation and sources suggested the differential effect of the past control measures, which provided new insights into future clean air policies in polluted region including China.
W. Joe F. Acton, Zhonghui Huang, Brian Davison, Will S. Drysdale, Pingqing Fu, Michael Hollaway, Ben Langford, James Lee, Yanhui Liu, Stefan Metzger, Neil Mullinger, Eiko Nemitz, Claire E. Reeves, Freya A. Squires, Adam R. Vaughan, Xinming Wang, Zhaoyi Wang, Oliver Wild, Qiang Zhang, Yanli Zhang, and C. Nicholas Hewitt
Atmos. Chem. Phys., 20, 15101–15125, https://doi.org/10.5194/acp-20-15101-2020, https://doi.org/10.5194/acp-20-15101-2020, 2020
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Air quality in Beijing is of concern to both policy makers and the general public. In order to address concerns about air quality it is vital that the sources of atmospheric pollutants are understood. This work presents the first top-down measurement of volatile organic compound (VOC) emissions in Beijing. These measurements are used to evaluate the emissions inventory and assess the impact of VOC emission from the city centre on atmospheric chemistry.
Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang
Atmos. Chem. Phys., 20, 12265–12284, https://doi.org/10.5194/acp-20-12265-2020, https://doi.org/10.5194/acp-20-12265-2020, 2020
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In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM2.5, which is important for studies on the effectiveness of emission control strategies.
Wei Tao, Hang Su, Guangjie Zheng, Jiandong Wang, Chao Wei, Lixia Liu, Nan Ma, Meng Li, Qiang Zhang, Ulrich Pöschl, and Yafang Cheng
Atmos. Chem. Phys., 20, 11729–11746, https://doi.org/10.5194/acp-20-11729-2020, https://doi.org/10.5194/acp-20-11729-2020, 2020
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We simulated the thermodynamic and multiphase reactions in aerosol water during a wintertime haze event over the North China Plain. It was found that aerosol pH exhibited a strong spatiotemporal variability, and multiple oxidation pathways were predominant for particulate sulfate formation in different locations. Sensitivity tests further showed that ammonia, crustal particles, and dissolved transition metal ions were important factors for multiphase chemistry during haze episodes.
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Short summary
The irreversible trend in global warming underscores the necessity for accurate monitoring of atmospheric carbon dynamics on a global scale. This study generated a global dataset of column-averaged dry-air mole fraction of CO2 (XCO2) at 0.05° resolution with full coverage using carbon satellite data and a deep learning model. The dataset accurately depicts global and regional XCO2 patterns, advancing the monitoring of carbon emissions and understanding of global carbon dynamics.
The irreversible trend in global warming underscores the necessity for accurate monitoring of...
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