Application of WRF-Chem to simulate air quality over Northern Vietnam

Environ Sci Pollut Res Int. 2021 Mar;28(10):12067-12081. doi: 10.1007/s11356-020-08913-y. Epub 2020 May 23.

Abstract

The WRF-Chem (Weather Research and Forecasting with Chemistry) model is implemented and validated against ground-based observations for meteorological and atmospheric variables for the first time in Northern Vietnam. The WRF-Chem model was based on HTAPv2 emission inventory with MOZCART chemical-aerosol mechanism to simulate atmospheric variables for winter (January) and summer (July) of 2014. The model satisfactorily reproduces meteorological fields, such as temperature 2 m above the ground and relative humidity 2 m above the ground at 45 NCHMF meteorological stations in January, but lower agreement was found in those simulations of July. PM10 and PM2.5 concentrations in January showed good temporal and spatial agreements to observations recorded at three CEM air monitoring stations in Phutho, Quangninh, and Hanoi, with correlation coefficients of 0.36 and 0.59. However, WRF-Chem model was underestimated with MFBs from - 27.9 to - 118.7% for PM10 levels and from - 34.2 to - 115.1% for PM2.5 levels. It has difficulty in capturing day-by-day variation of PM10 and PM2.5 concentrations at each station in July, but MFBs were in the range from - 27.1 to - 40.2% which is slightly lower than those in January. It suggested that further improvements of the model and local emission data are needed to reduce uncertainties in modeling the distribution of atmospheric pollutants. Assessment of biomass burning emission on air quality in summer was analyzed to highlight the application aspect of the WRF-Chem model. The study may serve as a reference for future air quality modeling using WRF-Chem in Vietnam.

Keywords: Air quality modeling; Northern Vietnam; WRF-Chem.

MeSH terms

  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Environmental Monitoring
  • Particulate Matter / analysis
  • Vietnam

Substances

  • Air Pollutants
  • Particulate Matter