WRF-Chem modeling of particulate matter in the Yangtze River Delta region: Source apportionment and its sensitivity to emission changes

PLoS One. 2018 Dec 7;13(12):e0208944. doi: 10.1371/journal.pone.0208944. eCollection 2018.

Abstract

China has been troubled by high concentrations of fine particulate matter (PM2.5) for many years. Up to now, the pollutant sources are not yet fully understood and the control approach still remains highly uncertain. In this study, four month-long (January, April, July and October in 2015) WRF-Chem simulations with different sensitivity experiments were conducted in the Yangtze River Delta (YRD) region of eastern China. The simulated results were compared with abundant meteorological and air quality observations at 138 stations in 26 YRD cities. Our model well captured magnitudes and variations of the observed PM2.5, with the normal mean biases (NMB) less than ±20% for 19 out of the 26 YRD cities. A series of sensitivity simulations were conducted to quantify the contributions from individual source sectors and from different regions to the PM2.5 in the YRD region. The calculated results show that YRD local source contributed 64% of the regional PM2.5 concentration, while outside transport contributed the rest 36%. Among the local sources, industry activity was the most significant sector in spring (25%), summer (36%) and fall (33%), while residential source was more important in winter (38%). We further conducted scenario simulations to explore the potential impacts of varying degrees of emission controls on PM2.5 reduction. The result demonstrated that regional cooperative control could effectively reduce the PM2.5 level. The proportionate emission controls of 10%, 20%, 30%, 40% and 50% could reduce the regional mean PM2.5 concentrations by 10%, 19%, 28%, 37% and 46%, respectively, and for places with higher ambient concentrations, the mitigation efficiency was more significant. Our study on source apportionment and emission controls can provide useful information on further mitigation actions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollutants
  • Air Pollution
  • China / epidemiology
  • Cities
  • Environmental Monitoring*
  • Environmental Pollutants / chemistry
  • Environmental Pollutants / toxicity*
  • Housing
  • Humans
  • Particulate Matter / chemistry
  • Particulate Matter / toxicity*
  • Rivers / chemistry*
  • Seasons
  • Water Pollution

Substances

  • Air Pollutants
  • Environmental Pollutants
  • Particulate Matter

Grants and funding

This work was supported by the National Natural Science Foundation of China (41705128), Nanjing University of Information Science and Technology (2016r063), and Opening Project of Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3) (FDLAP17003). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. QYH was supported by Nanjing Star-jelly Environmental Consultants Co., Ltd. The funder provided support in the form of salaries for author [QYH], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.