Articles | Volume 25, issue 3
https://doi.org/10.5194/acp-25-1569-2025
© 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-25-1569-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Feb 2025
Research article |
| 04 Feb 2025
| 04 Feb 2025
Impacts of meteorology and emission reductions on haze pollution during the lockdown in the North China Plain
Lang Liu
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, 410073, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, 410073, China
Xin Long
CORRESPONDING AUTHOR
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Yi Li
CORRESPONDING AUTHOR
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, 410073, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, 410073, China
Zengliang Zang
College of Meteorology and Oceanography, National University of Defense Technology, Changsha, 410073, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha, 410073, China
Fengwen Wang
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, College of Environment and Ecology, Chongqing University, Chongqing, 400030, China
Yan Han
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Zhier Bao
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Yang Chen
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Tian Feng
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo, 315211, China
Jinxin Yang
School of Geography and Remote Sensing, Guangzhou University, Guangzhou, 510006, China
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Cited
10 citations as recorded by crossref.
- Effects of Meteorology, Emissions, and Regional Transport on Atmospheric Nr Deposition in Lake Taihu, China M. Ma et al. https://doi.org/10.1021/acs.est.6c08714
- Contrasting impacts of policy interventions and population mobility on organic aerosols and oxygenated volatile organic compounds in Beijing Y. Zhang et al. https://doi.org/10.1016/j.envpol.2026.128408
- Compositional transition and coupled formation pathways of PM2.5 pollution in a typical industrial city: An empirical study based on Handan, China R. Shi et al. https://doi.org/10.1016/j.envpol.2026.129296
- Evaluation and prediction of atmospheric environmental carrying capacity in an Inland urban agglomeration in northern China Z. Zhen et al. https://doi.org/10.1016/j.atmosres.2025.108584
- Interannual Meteorological Forcing and Spatial Heterogeneity of Winter PM2.5 Regimes in Central China Y. He et al. https://doi.org/10.3390/atmos17050502
- Predicting Short-Term Air Quality Index in the Beijing–Tianjin–Hebei Urban Agglomeration: A Comparative Assessment of Linear, Ensemble, and Recurrent Forecasting Models X. Ling et al. https://doi.org/10.3390/atmos17070651
- Intercomparison of multiple chemical mechanisms in simulating severe haze event over the North China plain Z. Li et al. https://doi.org/10.1016/j.atmosenv.2025.121439
- Remote sensing of rural clean heating impacts on air quality: An STL-Q3 framework in Henan Province, China Y. Yang et al. https://doi.org/10.1016/j.rsase.2026.102126
- Predicting the Concentration Levels of PM2.5 and O3 for Highly Urbanized Areas Based on Machine Learning Models C. Wei et al. https://doi.org/10.3390/su17209211
- Understanding the spatial heterogeneity of black carbon variation drivers in China: Views from explainable machine learning H. Zheng et al. https://doi.org/10.1016/j.atmosres.2026.108749
10 citations as recorded by crossref.
- Effects of Meteorology, Emissions, and Regional Transport on Atmospheric Nr Deposition in Lake Taihu, China M. Ma et al. https://doi.org/10.1021/acs.est.6c08714
- Contrasting impacts of policy interventions and population mobility on organic aerosols and oxygenated volatile organic compounds in Beijing Y. Zhang et al. https://doi.org/10.1016/j.envpol.2026.128408
- Compositional transition and coupled formation pathways of PM2.5 pollution in a typical industrial city: An empirical study based on Handan, China R. Shi et al. https://doi.org/10.1016/j.envpol.2026.129296
- Evaluation and prediction of atmospheric environmental carrying capacity in an Inland urban agglomeration in northern China Z. Zhen et al. https://doi.org/10.1016/j.atmosres.2025.108584
- Interannual Meteorological Forcing and Spatial Heterogeneity of Winter PM2.5 Regimes in Central China Y. He et al. https://doi.org/10.3390/atmos17050502
- Predicting Short-Term Air Quality Index in the Beijing–Tianjin–Hebei Urban Agglomeration: A Comparative Assessment of Linear, Ensemble, and Recurrent Forecasting Models X. Ling et al. https://doi.org/10.3390/atmos17070651
- Intercomparison of multiple chemical mechanisms in simulating severe haze event over the North China plain Z. Li et al. https://doi.org/10.1016/j.atmosenv.2025.121439
- Remote sensing of rural clean heating impacts on air quality: An STL-Q3 framework in Henan Province, China Y. Yang et al. https://doi.org/10.1016/j.rsase.2026.102126
- Predicting the Concentration Levels of PM2.5 and O3 for Highly Urbanized Areas Based on Machine Learning Models C. Wei et al. https://doi.org/10.3390/su17209211
- Understanding the spatial heterogeneity of black carbon variation drivers in China: Views from explainable machine learning H. Zheng et al. https://doi.org/10.1016/j.atmosres.2026.108749
Saved (final revised paper)
Latest update: 25 Oct 2026
Short summary
This study uses WRF-Chem to assess how meteorological conditions and emission reductions affected fine particulate matter (PM2.5) in the North China Plain (NCP). It highlights regional disparities: in the northern NCP, adverse weather negated emission reduction effects. In contrast, the southern NCP featured a PM2.5 decrease due to favorable weather and emission reductions. The research highlighted the interaction between emissions, meteorology, and PM2.5.
This study uses WRF-Chem to assess how meteorological conditions and emission reductions...
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