Articles | Volume 25, issue 21
https://doi.org/10.5194/acp-25-14643-2025
© 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/acp-25-14643-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report
| 
04 Nov 2025
Measurement report |
| 04 Nov 2025
| 04 Nov 2025
Measurement report: Unraveling PM10 sources and oxidative potential across Chinese regions based on CNN-LSTM data preprocessing and receptor model
Qinghe Cai
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Dongqing Fang
CORRESPONDING AUTHOR
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
Field Scientific Experiment Base of Akdala Atmospheric Background, China Meteorological Administration, Urumqi, 830002, China
Junli Jin
Meteorological Observation Center, China Meteorological Administration, Beijing, 100081, China
Xiaoyu Hu
City University of Hong Kong, Hongkong, 999077, China
Yuxuan Cao
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Tianyi Zhao
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
Yang Bai
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Beijing Yanshan Earth Critical Zone National Research Station, Beijing, 101408, China
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Chenghao Xu, Jintai Lin, Hao Kong, Junli Jin, Lulu Chen, and Xiaobin Xu
Atmos. Chem. Phys., 25, 9545–9560, https://doi.org/10.5194/acp-25-9545-2025, https://doi.org/10.5194/acp-25-9545-2025, 2025
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We observed a strong increase in deseasonalized ozone at urban stations in the Tibetan Plateau from 2015 to 2019, far exceeding the trend at the baseline station Waliguan and the Tibetan Plateau average trend of four tropospheric ozone products. By combining multiple datasets and modeling approaches, we identified the main contributing factors as more frequent transport passing through the lower layers of high-emission regions and the increase in local and non-local anthropogenic emissions.
Yuanyuan Qin, Xinghua Zhang, Wei Huang, Juanjuan Qin, Xiaoyu Hu, Yuxuan Cao, Tianyi Zhao, Yang Zhang, Jihua Tan, Ziyin Zhang, Xinming Wang, and Zhenzhen Wang
Atmos. Chem. Phys., 24, 8737–8750, https://doi.org/10.5194/acp-24-8737-2024, https://doi.org/10.5194/acp-24-8737-2024, 2024
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Environmental persistent free radicals (EPFRs) and reactive oxygen species (ROSs) play an active role in the atmosphere. Despite control measures having effectively reduced their emissions, reductions were less than in PM2.5. Emission control measures performed well in achieving Parade Blue, but reducing the impact of the atmosphere on human health remains challenging. Thus, there is a need to reassess emission control measures to better address the challenges posed by EPFRs and ROSs.
Weijun Quan, Zhenfa Wang, Lin Qiao, Xiangdong Zheng, Junli Jin, Yinruo Li, Xiaomei Yin, Zhiqiang Ma, and Martin Wild
Earth Syst. Sci. Data, 16, 961–983, https://doi.org/10.5194/essd-16-961-2024, https://doi.org/10.5194/essd-16-961-2024, 2024
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Radiation components play important roles in various fields such as the Earth’s surface radiation budget, ecosystem productivity, and human health. In this study, a dataset consisting of quality-assured daily data of nine radiation components is presented based on the in situ measurements at the Shangdianzi regional GAW station in China during 2013–2022. The dataset can be applied in the validation of satellite products and numerical models and investigation of atmospheric radiation.
Yuanyuan Qin, Juanjuan Qin, Xiaobo Wang, Kang Xiao, Ting Qi, Yuwei Gao, Xueming Zhou, Shaoxuan Shi, Jingnan Li, Jingsi Gao, Ziyin Zhang, Jihua Tan, Yang Zhang, and Rongzhi Chen
Atmos. Chem. Phys., 22, 13845–13859, https://doi.org/10.5194/acp-22-13845-2022, https://doi.org/10.5194/acp-22-13845-2022, 2022
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Deep interrogation of water-soluble organic carbon (WSOC) in aerosols is critical and challenging considering its involvement in many key aerosol-associated chemical reactions. This work examined how the chemical structures (functional groups) and optical properties (UV/fluorescence properties) of WSOC were affected by pH and particle size. We found that the pH- and particle-size-dependent behaviors could be used to reveal the structures, sources, and aging of aerosol WSOC.
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.
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Short summary
This study analyzed PM10 and oxidative potential (OP) in 12 Chinese regions (Jun 2022-May 2023) via Convolutional Neural Networks and Long Short-Term Memory networks (CNN-LSTM) and Positive Matrix Factorization (PMF) at 4 representative sites. PM10 was higher in the northwest, lower in the northeast; urban areas had higher OP. Most sites showed peak PM10 and OP in winter, lowest in summer. Traffic, biomass burning, and coal combustion were major OP contributors.
This study analyzed PM10 and oxidative potential (OP) in 12 Chinese regions (Jun 2022-May 2023)...
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