Articles | Volume 19, issue 19
https://doi.org/10.5194/acp-19-12413-2019
https://doi.org/10.5194/acp-19-12413-2019
Research article
 | 
08 Oct 2019
Research article |  | 08 Oct 2019

Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau

Dongren Liu, Baofeng Di, Yuzhou Luo, Xunfei Deng, Hanyue Zhang, Fumo Yang, Michael L. Grieneisen, and Yu Zhan

Related authors

Spatial disparities of ozone pollution in the Sichuan Basin spurred by extreme, hot weather
Nan Wang, Yunsong Du, Dongyang Chen, Haiyan Meng, Xi Chen, Li Zhou, Guangming Shi, Yu Zhan, Miao Feng, Wei Li, Mulan Chen, Zhenliang Li, and Fumo Yang
Atmos. Chem. Phys., 24, 3029–3042, https://doi.org/10.5194/acp-24-3029-2024,https://doi.org/10.5194/acp-24-3029-2024, 2024
Short summary
Evolution of nucleophilic high molecular-weight organic compounds in ambient aerosols: a case study
Chen He, Hanxiong Che, Zier Bao, Yiliang Liu, Qing Li, Miao Hu, Jiawei Zhou, Shumin Zhang, Xiaojiang Yao, Quan Shi, Chunmao Chen, Yan Han, Lingshuo Meng, Xin Long, Fumo Yang, and Yang Chen
Atmos. Chem. Phys., 24, 1627–1639, https://doi.org/10.5194/acp-24-1627-2024,https://doi.org/10.5194/acp-24-1627-2024, 2024
Short summary
Extreme weather exacerbates ozone pollution in the Pearl River Delta, China: role of natural processes
Nan Wang, Hongyue Wang, Xin Huang, Xi Chen, Yu Zou, Tao Deng, Tingyuan Li, Xiaopu Lyu, and Fumo Yang
Atmos. Chem. Phys., 24, 1559–1570, https://doi.org/10.5194/acp-24-1559-2024,https://doi.org/10.5194/acp-24-1559-2024, 2024
Short summary
Sequential spatiotemporal distribution of PM2.5, SO2 and Ozone in China from 2015 to 2020
Yufeng Chi, Yu Zhan, Kai Wang, and Hong Ye
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-76,https://doi.org/10.5194/essd-2023-76, 2023
Manuscript not accepted for further review
Short summary
Measurement report: Intensive biomass burning emissions and rapid nitrate formation drive severe haze formation in the Sichuan Basin, China – insights from aerosol mass spectrometry
Zhier Bao, Xinyi Zhang, Qing Li, Jiawei Zhou, Guangming Shi, Li Zhou, Fumo Yang, Shaodong Xie, Dan Zhang, Chongzhi Zhai, Zhenliang Li, Chao Peng, and Yang Chen
Atmos. Chem. Phys., 23, 1147–1167, https://doi.org/10.5194/acp-23-1147-2023,https://doi.org/10.5194/acp-23-1147-2023, 2023
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
Atmos. Chem. Phys., 24, 2759–2782, https://doi.org/10.5194/acp-24-2759-2024,https://doi.org/10.5194/acp-24-2759-2024, 2024
Short summary
Extreme weather exacerbates ozone pollution in the Pearl River Delta, China: role of natural processes
Nan Wang, Hongyue Wang, Xin Huang, Xi Chen, Yu Zou, Tao Deng, Tingyuan Li, Xiaopu Lyu, and Fumo Yang
Atmos. Chem. Phys., 24, 1559–1570, https://doi.org/10.5194/acp-24-1559-2024,https://doi.org/10.5194/acp-24-1559-2024, 2024
Short summary
Multidecadal ozone trends in China and implications for human health and crop yields: a hybrid approach combining a chemical transport model and machine learning
Jia Mao, Amos P. K. Tai, David H. Y. Yung, Tiangang Yuan, Kong T. Chau, and Zhaozhong Feng
Atmos. Chem. Phys., 24, 345–366, https://doi.org/10.5194/acp-24-345-2024,https://doi.org/10.5194/acp-24-345-2024, 2024
Short summary
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations
Leon Kuhn, Steffen Beirle, Vinod Kumar, Sergey Osipov, Andrea Pozzer, Tim Bösch, Rajesh Kumar, and Thomas Wagner
Atmos. Chem. Phys., 24, 185–217, https://doi.org/10.5194/acp-24-185-2024,https://doi.org/10.5194/acp-24-185-2024, 2024
Short summary
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023,https://doi.org/10.5194/acp-23-15235-2023, 2023
Short summary

Cited articles

Arellano, A. F. and Hess, P. G.: Sensitivity of top-down estimates of CO sources to GCTM transport, Geophys. Res. Lett., 33, 493–495, https://doi.org/10.1029/2006gl027371, 2006. 
Barret, B., Sauvage, B., Bennouna, Y., and Le Flochmoen, E.: Upper-tropospheric CO and O3 budget during the Asian summer monsoon, Atmos. Chem. Phys., 16, 9129–9147, https://doi.org/10.5194/acp-16-9129-2016, 2016. 
Boria, R. A., Olson, L. E., Goodman, S. M., and Anderson, R. P.: Spatial filtering to reduce sampling bias can improve the performance of ecological niche models, Ecol. Model., 275, 73–77, https://doi.org/10.1016/j.ecolmodel.2013.12.012, 2014. 
Borsdorff, T., Aan de Brugh, J., Hu, H., Aben, I., Hasekamp, O., and Landgraf, J.: Measuring Carbon Monoxide with TROPOMI: First Results and a Comparison With ECMWF-IFS Analysis Data, Geophys. Res. Lett., 45, 2826–2832, https://doi.org/10.1002/2018gl077045, 2018. 
Buchholz, R. R., Deeter, M. N., Worden, H. M., Gille, J., Edwards, D. P., Hannigan, J. W., Jones, N. B., Paton-Walsh, C., Griffith, D. W. T., Smale, D., Robinson, J., Strong, K., Conway, S., Sussmann, R., Hase, F., Blumenstock, T., Mahieu, E., and Langerock, B.: Validation of MOPITT carbon monoxide using ground-based Fourier transform infrared spectrometer data from NDACC, Atmos. Meas. Tech., 10, 1927–1956, https://doi.org/10.5194/amt-10-1927-2017, 2017. 
Download
Short summary
The spatiotemporal distributions of daily ground-level CO concentrations across China during 2013–2016 are derived by fusing the data from remote sensing and ground monitoring. The population–weighted CO was predicted to be 0.99 ± 0.30 mg m−3 and showed a decreasing trend of −0.021 ± 0.004 mg m−3 per year. The CO pollution was the most severe in the North China Plain. The hotspots in the Tibetan Plateau overlooked by the remote sensing were depicted by the data-fusion approach.
Altmetrics
Final-revised paper
Preprint