Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.414
IF5.414
IF 5-year value: 5.958
IF 5-year
5.958
CiteScore value: 9.7
CiteScore
9.7
SNIP value: 1.517
SNIP1.517
IPP value: 5.61
IPP5.61
SJR value: 2.601
SJR2.601
Scimago H <br class='widget-line-break'>index value: 191
Scimago H
index
191
h5-index value: 89
h5-index89
Volume 18, issue 8
Atmos. Chem. Phys., 18, 5343–5358, 2018
https://doi.org/10.5194/acp-18-5343-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 18, 5343–5358, 2018
https://doi.org/10.5194/acp-18-5343-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Apr 2018

Research article | 19 Apr 2018

Understanding meteorological influences on PM2.5 concentrations across China: a temporal and spatial perspective

Ziyue Chen1,2, Xiaoming Xie1, Jun Cai3, Danlu Chen1, Bingbo Gao4, Bin He1,2, Nianliang Cheng5, and Bing Xu3 Ziyue Chen et al.
  • 1State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China
  • 2Joint Center for Global Change Studies, Beijing 100875, China
  • 3Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
  • 4National Engineering Research Center for Information Technology in Agriculture, 11 Shuguang Huayuan Middle Road, Beijing 100097, China
  • 5Beijing Municipal Environmental Monitoring Center, Beijing 100048, China

Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Publications Copernicus
Download
Short summary
With an advanced causality analysis method CCM, we quantified the influence of individual meteorological factors on PM2.5 concentrations and revealed notable spatial and temporal variations of meteorological influences on PM2.5 concentrations across China. Temperature, humidity and wind exert the strongest influences on PM2.5 concentrations in most cities across China. Given the notable spatial variations, meteorological means for reducing PM2.5 concentrations should be designed accordingly.
With an advanced causality analysis method CCM, we quantified the influence of individual...
Citation
Altmetrics
Final-revised paper
Preprint