Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/acp-2017-1180
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
07 Mar 2018
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Chemistry and Physics (ACP).
Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method
Mengyao Liu1, Jintai Lin1, Yuchen Wang1,2, Yang Sun3, Bo Zheng4, Jingyuan Shao1, Lulu Chen1, Yixuan Zheng5, Jinxuan Chen1,6, May Fu1, Yingying Yan1, Qiang Zhang4, and Zhaohua Wu7,8 1Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
2Earthquake Research Institute, The University of Tokyo, Tokyo 113-0032, Japan
3Institute of Atmospheric Physics, Chinese Academy of Sciences
4Center for Earth System Science, Tsinghua University, Beijing 100084, China
5Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
6Max Planck Institute for Biogeochemistry, Hans-Knöll-Str.10, 07745 Jena, Germany
7Center for Ocean–Atmospheric Prediction Studies, Florida State University, Tallahassee, Florida 32306-2741, USA
8Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, Florida 32306-4520, USA
Abstract. Eastern China (27° N–41° N, 110° E–123° E) is heavily polluted by nitrogen dioxide (NO2), particulate matter with aerodynamic diameter below 2.5 μm (PM2.5) and other air pollutants. These pollutants vary in a variety of temporal and spatial scales, with many temporal scales non-periodic and non-stationary, challenging proper quantitative characterization and visualization. This study uses a newly compiled EOF-EEMD analysis-visualization package to evaluate the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes over Eastern China in Fall–Winter 2013. Applying the package to observed hourly pollutant data reveals a primary spatial pattern representing Eastern China-wide synchronous variation in time, which is dominated by diurnal variability with a much weaker day-to-day signal. A secondary spatial mode, representing north-south opposing changes in time with no constant period, is characterized by wind-related dilution or buildup of pollutants from one day to another.

We further evaluate simulations of GEOS-Chem and WRF/CMAQ in capturing the spatiotemporal variability of pollutants. GEOS-Chem underestimates NO2 by about 17 μg/m3 and PM2.5 by 35 μg/m3 on average. It reproduces the diurnal variability for both pollutants. For the day-to-day variation, GEOS-Chem reproduces the observed north-south contrasting mode for both pollutants but not the Eastern China-synchronous mode (especially for NO2). The model errors are due to a first model layer too thick (about 130 m) to capture the near-surface vertical gradient, deficiencies in the nighttime nitrogen chemistry in the first layer, and missing secondary organic aerosols and anthropogenic dusts. CMAQ overestimates the diurnal cycle of pollutants due to too weak boundary layer mixing – especially in the nighttime, CMAQ overestimates NO2 by about 30 μg/m3 and PM2.5 by 60 μg/m3. For the day-to-day variability, CMAQ reproduces the observed Eastern-China synchronous mode but not the north-south opposing mode of NO2. Both models capture the day-to-day variability of PM2.5 better than that of NO2. These results shed light on model improvement. The EOF-EEMD package is freely accessible.

Citation: Liu, M., Lin, J., Wang, Y., Sun, Y., Zheng, B., Shao, J., Chen, L., Zheng, Y., Chen, J., Fu, M., Yan, Y., Zhang, Q., and Wu, Z.: Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1180, in review, 2018.
Mengyao Liu et al.
Mengyao Liu et al.
Mengyao Liu et al.

Viewed

Total article views: 452 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
323 114 15 452 11 11

Views and downloads (calculated since 07 Mar 2018)

Cumulative views and downloads (calculated since 07 Mar 2018)

Viewed (geographical distribution)

Total article views: 452 (including HTML, PDF, and XML)

Thereof 449 with geography defined and 3 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 23 Jun 2018
Publications Copernicus
Download
Short summary
Eastern China is heavily polluted by NO2, PM2.5 and other air pollutants. Our study use EOF-EEMD to analysis the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes. The regular diurnal cycle of them are mainly affected by human activities while irregular day to day variations are dominated by weather process, 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 use...
Share