Awkash Kumar 1, Rashmi S. Patil1, Anil Kumar Dikshit1, Rakesh Kumar2

  • 1 Centre for Environmental Science and Engineering, Indian Institute of Technology, Bombay, Mumbai - 400 076, India
  • 2 Council of Scientific and Industrial Research-National Environmental Engineering Research Institute Mumbai Zone, Mumbai - 400 076, India

Received: August 1, 2016
Revised: January 12, 2017
Accepted: April 3, 2017
Download Citation: ||https://doi.org/10.4209/aaqr.2016.06.0265  

  • Download: PDF


Cite this article:
Kumar, A., Patil, R.S., Dikshit, A.K. and Kumar, R. (2017). Application of WRF Model for Air Quality Modelling and AERMOD – A Survey. Aerosol Air Qual. Res. 17: 1925-1937. https://doi.org/10.4209/aaqr.2016.06.0265


HIGHLIGHTS

  • WRF model has been reviewed for application of air quality model.
  • WRF model can generate required input data for air quality model.
  • Various air quality model and AERMOD also have been reviewed.

 

ABSTRACT


Meteorology plays a crucial role in air quality. The presence of uncertainties of a significant nature in the meteorological profile used during air quality model simulation has the potential to affect negatively the results of the simulations. This paper describes a most recent version of the meteorological model called Weather Research and Forecasting (WRF) model and its importance in air quality. The performance of WRF depends upon the intended application and parameterization scheme of physics options. WRF model is also applied to investigate the simulation results with various land surface models (LSMs) and Planetary Boundary Layer (PBL) parameterizations and various set of microphysics options. It predicts various meteorological spatial parameters like mixing layer height, temperature, humidity, rain fall, cloud cover and wind. The WRF results are integrated with air quality model (AQM) and the AQM depends upon the performance of WRF. It has been applied for evaluation of national pollution control policy, behaviour of plume rise, property of aerosols, prediction of Ozone, SO2, NOx, PM10, PM2.5 etc. using AQM for various sources. The effect of topography and different seasons on the concentration of pollutants in the atmosphere has also been studied using AQM. AQM AERMOD has also been reviewed with various other AQM models such as ADMS-Urban and CALPUFF. AERMOD has been used for different time scales, health risk assessment, evaluation of various control strategies, Environmental Impact Assessment (EIA) studies and emission factor estimation. This paper presents the importance of meteorological model to AQM as well as many applications of AQM to demonstrate various scientific questions and policies.


Keywords: Air quality modeling; Atmospheric dispersion; Meteorological model; WRF model; AERMOD; Urban region


Don't forget to share this article 

 

Subscribe to our Newsletter 

Aerosol and Air Quality Research has published over 2,000 peer-reviewed articles. Enter your email address to receive latest updates and research articles to your inbox every second week.

Latest coronavirus research from Aerosol and Air Quality Research

2018 Impact Factor: 2.735

5-Year Impact Factor: 2.827


SCImago Journal & Country Rank