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

Journal metrics

Journal metrics

  • IF value: 5.509 IF 5.509
  • IF 5-year value: 5.689 IF 5-year 5.689
  • CiteScore value: 5.44 CiteScore 5.44
  • SNIP value: 1.519 SNIP 1.519
  • SJR value: 3.032 SJR 3.032
  • IPP value: 5.37 IPP 5.37
  • h5-index value: 86 h5-index 86
  • Scimago H index value: 161 Scimago H index 161
Volume 17, issue 19 | Copyright

Special issue: Regional transport and transformation of air pollution in...

Atmos. Chem. Phys., 17, 12031-12050, 2017
https://doi.org/10.5194/acp-17-12031-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 10 Oct 2017

Research article | 10 Oct 2017

A modeling study of the nonlinear response of fine particles to air pollutant emissions in the Beijing–Tianjin–Hebei region

Bin Zhao1,2,3, Wenjing Wu1,2, Shuxiao Wang1,2, Jia Xing1,2, Xing Chang1,2, Kuo-Nan Liou3, Jonathan H. Jiang4, Yu Gu3, Carey Jang5, Joshua S. Fu6, Yun Zhu7, Jiandong Wang1,2, Yan Lin8, and Jiming Hao1,2 Bin Zhao et al.
  • 1School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
  • 2State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
  • 3Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA
  • 4Jet propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
  • 5U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
  • 6Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, USA
  • 7School of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China
  • 8Norwegian Institute for Water Research, Oslo, 0349, Norway

Abstract. The Beijing–Tianjin–Hebei (BTH) region has been suffering from the most severe fine-particle (PM2. 5) pollution in China, which causes serious health damage and economic loss. Quantifying the source contributions to PM2. 5 concentrations has been a challenging task because of the complicated nonlinear relationships between PM2. 5 concentrations and emissions of multiple pollutants from multiple spatial regions and economic sectors. In this study, we use the extended response surface modeling (ERSM) technique to investigate the nonlinear response of PM2. 5 concentrations to emissions of multiple pollutants from different regions and sectors over the BTH region, based on over 1000 simulations by a chemical transport model (CTM). The ERSM-predicted PM2. 5 concentrations agree well with independent CTM simulations, with correlation coefficients larger than 0.99 and mean normalized errors less than 1%. Using the ERSM technique, we find that, among all air pollutants, primary inorganic PM2. 5 makes the largest contribution (24–36%) to PM2. 5 concentrations. The contribution of primary inorganic PM2. 5 emissions is especially high in heavily polluted winter and is dominated by the industry as well as residential and commercial sectors, which should be prioritized in PM2. 5 control strategies. The total contributions of all precursors (nitrogen oxides, NOx; sulfur dioxides, SO2; ammonia, NH3; non-methane volatile organic compounds, NMVOCs; intermediate-volatility organic compounds, IVOCs; primary organic aerosol, POA) to PM2. 5 concentrations range between 31 and 48%. Among these precursors, PM2. 5 concentrations are primarily sensitive to the emissions of NH3, NMVOC+IVOC, and POA. The sensitivities increase substantially for NH3 and NOx and decrease slightly for POA and NMVOC+IVOC with the increase in the emission reduction ratio, which illustrates the nonlinear relationships between precursor emissions and PM2. 5 concentrations. The contributions of primary inorganic PM2. 5 emissions to PM2. 5 concentrations are dominated by local emission sources, which account for over 75% of the total primary inorganic PM2. 5 contributions. For precursors, however, emissions from other regions could play similar roles to local emission sources in the summer and over the northern part of BTH. The source contribution features for various types of heavy-pollution episodes are distinctly different from each other and from the monthly mean results, illustrating that control strategies should be differentiated based on the major contributing sources during different types of episodes.

Download & links
Publications Copernicus
Special issue
Download
Short summary
Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we find that the emissions of primary inorganic PM2.5 make the largest contribution to PM2.5 concentrations and thus should be prioritized in PM2.5 control strategies. Among the precursors, PM2.5 concentrations are primarily sensitive to the emissions of NH3, NMVOC+IVOC, and POA, and the sensitivities increase substantially for NH3 and NHx with the increase in emission reduction ratio.
Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we...
Citation
Share