Articles | Volume 18, issue 17
https://doi.org/10.5194/acp-18-12933-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-18-12933-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2018
Research article |
| 07 Sep 2018
| 07 Sep 2018
Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method
Mengyao Liu
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Yuchen Wang
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Earthquake Research Institute, The University of Tokyo, Tokyo
113-0032, Japan
Yang Sun
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Center for Earth System Science, Tsinghua University, Beijing 100084,
China
Jingyuan Shao
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Lulu Chen
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Yixuan Zheng
Ministry of Education Key Laboratory for Earth System Modeling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
China
Jinxuan Chen
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str.10, 07745
Jena, Germany
Tzung-May Fu
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Yingying Yan
Laboratory for Climate and Ocean-Atmosphere Studies, Department of
Atmospheric and Oceanic Sciences, School of Physics, Peking University,
Beijing 100871, China
Qiang Zhang
Center for Earth System Science, Tsinghua University, Beijing 100084,
China
Zhaohua Wu
Center for Ocean–Atmospheric Prediction Studies, Florida State
University, Tallahassee, Florida 32306-2741, USA
Department of Earth, Ocean and Atmospheric Science, Florida State
University, Tallahassee, Florida 32306-4520, USA
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Cited
41 citations as recorded by crossref.
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- Application of Turbulent Diffusion Term of Aerosols in Mesoscale Model W. Jia et al. 10.1029/2021GL093199
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
- NOx emissions in China: Temporal variations, spatial patterns and reduction potentials L. Jiang et al. 10.1016/j.apr.2020.06.003
- Air pollution exposure associates with increased risk of neonatal jaundice L. Zhang et al. 10.1038/s41467-019-11387-3
- Review on Recent Progress in Near-Field Tsunami Forecasting Using Offshore Tsunami Measurements: Source Inversion and Data Assimilation Y. Wang et al. 10.1007/s00024-021-02910-z
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- Tropospheric NO2 vertical column densities retrieved from ground-based MAX-DOAS measurements at Shangdianzi regional atmospheric background station in China S. Cheng et al. 10.1016/j.jes.2018.12.012
- Impact of weather and emission changes on NO2 concentrations in China during 2014–2019 Y. Shen et al. 10.1016/j.envpol.2020.116163
- High-resolution (0.05° × 0.05°) NO<sub><i>x</i></sub> emissions in the Yangtze River Delta inferred from OMI H. Kong et al. 10.5194/acp-19-12835-2019
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- Satellite-based estimation of surface NO2 concentrations over east-central China: A comparison of POMINO and OMNO2d data K. Qin et al. 10.1016/j.atmosenv.2020.117322
- Air pollution-induced missed abortion risk for pregnancies L. Zhang et al. 10.1038/s41893-019-0387-y
- Estimation and Spatiotemporal Analysis of NO2 Pollution in East Asia During 2001–2016 M. Hu et al. 10.1029/2021JD035129
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- Effect modification of greenness on PM2.5associated all-cause mortality in a multidrug-resistant tuberculosis cohort E. Ge et al. 10.1136/thoraxjnl-2020-216819
- Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence J. Wei et al. 10.1021/acs.est.2c03834
- Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk Q. Yu et al. 10.3390/ijerph18105353
- Untangling the contributions of meteorological conditions and human mobility to tropospheric NO2 in Chinese mainland during the COVID-19 pandemic in early 2020 Y. Zhang et al. 10.1093/nsr/nwab061
- Fugitive Road Dust PM2.5 Emissions and Their Potential Health Impacts S. Chen et al. 10.1021/acs.est.9b00666
- Atmospheric Nitrogen Deposition to a Southeast Tibetan Forest Ecosystem W. Wang et al. 10.3390/atmos11121331
- Recommendations on benchmarks for photochemical air quality model applications in China — NO2, SO2, CO and PM10 H. Zhai et al. 10.1016/j.atmosenv.2023.120290
- Short-term effect of NO2 on outpatient visits for dermatologic diseases in Xinxiang, China: a time-series study L. Chao et al. 10.1007/s10653-021-00831-3
40 citations as recorded by crossref.
- Hourly Profiles of Air Pollution Variation in Selected Cities, Towns and Villages in Poland R. Cichowicz et al. 10.1051/e3sconf/201910103003
- Application of Turbulent Diffusion Term of Aerosols in Mesoscale Model W. Jia et al. 10.1029/2021GL093199
- Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite H. Kong et al. 10.1021/acs.est.1c07723
- NOx emissions in China: Temporal variations, spatial patterns and reduction potentials L. Jiang et al. 10.1016/j.apr.2020.06.003
- Air pollution exposure associates with increased risk of neonatal jaundice L. Zhang et al. 10.1038/s41467-019-11387-3
- Review on Recent Progress in Near-Field Tsunami Forecasting Using Offshore Tsunami Measurements: Source Inversion and Data Assimilation Y. Wang et al. 10.1007/s00024-021-02910-z
- Long-term (2006–2015) variations and relations of multiple atmospheric pollutants based on multi-remote sensing data over the North China Plain Y. Si et al. 10.1016/j.envpol.2019.113323
- Modeling diurnal variation of surface PM<sub>2.5</sub> concentrations over East China with WRF-Chem: impacts from boundary-layer mixing and anthropogenic emission Q. Du et al. 10.5194/acp-20-2839-2020
- Tropospheric NO2 vertical column densities retrieved from ground-based MAX-DOAS measurements at Shangdianzi regional atmospheric background station in China S. Cheng et al. 10.1016/j.jes.2018.12.012
- Impact of weather and emission changes on NO2 concentrations in China during 2014–2019 Y. Shen et al. 10.1016/j.envpol.2020.116163
- High-resolution (0.05° × 0.05°) NO<sub><i>x</i></sub> emissions in the Yangtze River Delta inferred from OMI H. Kong et al. 10.5194/acp-19-12835-2019
- Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical Modeling J. Jia et al. 10.3390/atmos13050697
- Top-down estimate of black carbon emissions for city clusters using ground observations: a case study in southern Jiangsu, China X. Zhao et al. 10.5194/acp-19-2095-2019
- A Tsunami Warning System Based on Offshore Bottom Pressure Gauges and Data Assimilation for Crete Island in the Eastern Mediterranean Basin Y. Wang et al. 10.1029/2020JB020293
- Long-term variations of ground-level NO2 concentrations along coastal areas in China N. Zhan et al. 10.1016/j.atmosenv.2022.119158
- Satellite-based estimation of surface NO2 concentrations over east-central China: A comparison of POMINO and OMNO2d data K. Qin et al. 10.1016/j.atmosenv.2020.117322
- Air pollution-induced missed abortion risk for pregnancies L. Zhang et al. 10.1038/s41893-019-0387-y
- Estimation and Spatiotemporal Analysis of NO2 Pollution in East Asia During 2001–2016 M. Hu et al. 10.1029/2021JD035129
- Absorption of NO from simulated flue gas using citric acid complexed ferrous ion/heat coactivated persulfate system D. Chen et al. 10.1016/j.cherd.2023.10.046
- Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China H. Mak et al. 10.3390/rs10111789
- Real-Time Tsunami Data Assimilation of S-Net Pressure Gauge Records during the 2016 Fukushima Earthquake Y. Wang & K. Satake 10.1785/0220200447
- Multi-timescale variation characteristics of PM2.5 in different regions of China during 2014–2022 R. Liu et al. 10.1016/j.scitotenv.2024.171008
- Evaluating the methods and influencing factors of satellite-derived estimates of NOX emissions at regional scale: A case study for Yangtze River Delta, China Y. Yang et al. 10.1016/j.atmosenv.2019.117051
- Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation L. Li 10.3390/rs12030492
- Spatiotemporal and probability variations of surface PM2.5 over China between 2013 and 2019 and the associated changes in health risks: An integrative observation and model analysis Z. Jiang et al. 10.1016/j.scitotenv.2020.137896
- Atmospheric dry and bulk nitrogen deposition to forest environment in the North China Plain Y. Fu et al. 10.1016/j.apr.2019.06.004
- Relative effects of open biomass burning and open crop straw burning on haze formation over central and eastern China: modeling study driven by constrained emissions K. Mehmood et al. 10.5194/acp-20-2419-2020
- A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm Y. Zhang et al. 10.5194/amt-16-4643-2023
- A Method of Real-Time Tsunami Detection Using Ensemble Empirical Mode Decomposition Y. Wang et al. 10.1785/0220200115
- Identifying convergence in nitrogen oxides emissions from motor vehicles in China: A spatial panel data approach S. He & L. Jiang 10.1016/j.jclepro.2021.128177
- Retrieval of surface PM2.5 mass concentrations over North China using visibility measurements and GEOS-Chem simulations S. Li et al. 10.1016/j.atmosenv.2019.117121
- Evaluation of WRF-Chem simulations on vertical profiles of PM2.5 with UAV observations during a haze pollution event C. Liu et al. 10.1016/j.atmosenv.2021.118332
- High spatial resolution WRF-Chem model over Asia: Physics and chemistry evaluation P. Sicard et al. 10.1016/j.atmosenv.2020.118004
- Effect modification of greenness on PM2.5associated all-cause mortality in a multidrug-resistant tuberculosis cohort E. Ge et al. 10.1136/thoraxjnl-2020-216819
- Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence J. Wei et al. 10.1021/acs.est.2c03834
- Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk Q. Yu et al. 10.3390/ijerph18105353
- Untangling the contributions of meteorological conditions and human mobility to tropospheric NO2 in Chinese mainland during the COVID-19 pandemic in early 2020 Y. Zhang et al. 10.1093/nsr/nwab061
- Fugitive Road Dust PM2.5 Emissions and Their Potential Health Impacts S. Chen et al. 10.1021/acs.est.9b00666
- Atmospheric Nitrogen Deposition to a Southeast Tibetan Forest Ecosystem W. Wang et al. 10.3390/atmos11121331
- Recommendations on benchmarks for photochemical air quality model applications in China — NO2, SO2, CO and PM10 H. Zhai et al. 10.1016/j.atmosenv.2023.120290
Discussed (final revised paper)
Latest update: 18 Apr 2024
Short summary
Eastern China is heavily polluted by NO2, PM2.5, and other air pollutants. Our study uses EOF–EEMD to analyze the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes. Their regular diurnal cycles are mainly affected by human activities, while irregular day-to-day variations are dominated by weather processes representing synchronous variation or north–south opposing changes over Eastern China.
Eastern China is heavily polluted by NO2, PM2.5, and other air pollutants. Our study uses...
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