Articles | Volume 23, issue 15
https://doi.org/10.5194/acp-23-8531-2023
https://doi.org/10.5194/acp-23-8531-2023
Research article
 | 
02 Aug 2023
Research article |  | 02 Aug 2023

Estimating nitrogen and sulfur deposition across China during 2005 to 2020 based on multiple statistical models

Kaiyue Zhou, Wen Xu, Lin Zhang, Mingrui Ma, Xuejun Liu, and Yu Zhao

Related authors

Development of a High-Resolution Integrated Emission Inventory of Air Pollutants for China
Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-3,https://doi.org/10.5194/essd-2024-3, 2024
Preprint under review for ESSD
Short summary
Long-term Variability in Black Carbon Emissions Constrained by Gap-filled Absorption Aerosol Optical Depth and Associated Premature Mortality in China
Wenxin Zhao, Yu Zhao, Yu Zheng, Dong Chen, Jinyuan Xin, Kaitao Li, Huizheng Che, Zhengqiang Li, Mingrui Ma, and Yun Hang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2758,https://doi.org/10.5194/egusphere-2023-2758, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Simulation of ozone-vegetation coupling and feedback in China using multiple ozone damage schemes
Jiachen Cao, Xu Yue, and Mingrui Ma
EGUsphere, https://doi.org/10.5194/egusphere-2023-2149,https://doi.org/10.5194/egusphere-2023-2149, 2023
Short summary
High-resolution regional emission inventory contributes to the evaluation of policy effectiveness: a case study in Jiangsu Province, China
Chen Gu, Lei Zhang, Zidie Xu, Sijia Xia, Yutong Wang, Li Li, Zeren Wang, Qiuyue Zhao, Hanying Wang, and Yu Zhao
Atmos. Chem. Phys., 23, 4247–4269, https://doi.org/10.5194/acp-23-4247-2023,https://doi.org/10.5194/acp-23-4247-2023, 2023
Short summary
A dynamic ammonia emission model and the online coupling with WRF–Chem (WRF–SoilN–Chem v1.0): development and regional evaluation in China
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023,https://doi.org/10.5194/gmd-16-1641-2023, 2023
Short summary

Related subject area

Subject: Gases | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Diagnosing Ozone-NOx-VOCs-Aerosols Sensitivity to Uncover Urban-nonurban Discrepancies in Shandong, China using Transformer-based High-resolution Air Pollution Estimations
Chenliang Tao, Yanbo Peng, Qingzhu Zhang, Yuqiang Zhang, Bing Gong, Qiao Wang, and Wenxing Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2640,https://doi.org/10.5194/egusphere-2023-2640, 2023
Short summary
Automated detection and monitoring of methane super-emitters using satellite data
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023,https://doi.org/10.5194/acp-23-9071-2023, 2023
Short summary
Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning
Vigneshkumar Balamurugan, Jia Chen, Adrian Wenzel, and Frank N. Keutsch
Atmos. Chem. Phys., 23, 10267–10285, https://doi.org/10.5194/acp-23-10267-2023,https://doi.org/10.5194/acp-23-10267-2023, 2023
Short summary
A machine learning approach to downscale EMEP4UK: analysis of UK ozone variability and trends
Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
EGUsphere, https://doi.org/10.5194/egusphere-2023-632,https://doi.org/10.5194/egusphere-2023-632, 2023
Short summary
Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques
Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Atmos. Chem. Phys., 23, 5317–5333, https://doi.org/10.5194/acp-23-5317-2023,https://doi.org/10.5194/acp-23-5317-2023, 2023
Short summary

Cited articles

Ahmad, I., Tang, D., Wang, T., Wang, M., and Wagan, B.: Precipitation trends over time using Mann-Kendall and Spearman's rho tests in Swat River Basin, Pak. Adv. Meteorol., 2015, 431860, https://doi.org/10.1155/2015/431860, 2015. 
An, Z., Huang, R. J., Zhang, R., Tie, X., Li, G., Cao, J., Zhou, W., Shi, Z., Han, Y., Gu, Z., and Ji, Y.: Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes, P. Natl. Acad. Sci. USA, 116, 8657–8666, https://doi.org/10.1073/pnas.1900125116, 2019. 
Baker, L. A., Herlihy, A. T., Kaufmann, P. R., and Eilers, J. M.: Acidic Lakes and Streams in the United States: The Role of Acidic Deposition, Science, 252, 1151–1154, https://doi.org/10.1126/science.252.5009.1151, 1991. 
Beachley, G., Puchalski, M., Rogers, C., and Lear, G.: A summary of long-term trends in sulfur and nitrogen deposition in the United States: 1990–2013, JSM Environ. Sci. Ecol., 4, 1030–1034, 2016. 
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q. B., Liu, H. G. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res.-Atmos., 106, 23073–23095, https://doi.org/10.1029/2001jd000807, 2001. 
Download
Short summary
We developed a dataset of the long-term (2005–2020) variabilities of China’s nitrogen and sulfur deposition, with multiple statistical models that combine available observations and chemistry transport modeling. We demonstrated the strong impact of human activities and national pollution control actions on the spatiotemporal changes in deposition and indicated a relatively small benefit of emission abatement on deposition (and thereby ecological risk) for China compared to Europe and the USA.
Altmetrics
Final-revised paper
Preprint