About AAQR

Aims and Scope

Articles online
For contributors
Call for Papers
Guideline for the
Special Issue Proposal
Subscription
Information

Advertising

Contact Us
 
Search for  in   Search  Advanced search  

 

Volume 17, No. 2, February 2017, Pages 381-393 PDF(5.99 MB)  
doi: 10.4209/aaqr.2016.07.0294   

Atmospheric Dispersion of PM2.5 Precursor Gases from Two Major Thermal Power Plants in Andhra Pradesh, India

Venkata Bhaskar Rao Dodla, China Satyanarayana Gubbala, Srinivas Desamsetti

Department of Atmospheric Science, K L University, Andhra Pradesh 522502, India

 

Highlights
  • Prediction of meteorological variables using ARW model.
  • Assessment of seasonal variation of wind flow.
  • Simulation of dispersion of SO2 and NO using HYSPLIT model.
  • Pollutant dispersion over two urban complexes.

Abstract

 

Fine particulate matter (PM2.5) predominantly comprises sulphates and nitrates, which results from sulphur dioxide (SO2) and nitrogen oxide (NOx) gases that are emanated from excessive industrial activities and transport systems. PM2.5 is known to affect respiratory health in humans. Coal-fired thermal power plants are a major source of SO2 and NOx gases. Evaluation of the dispersion characteristics of these precursor gases from the power plants would help understand the vulnerability. Meteorological conditions that prevail over the region would influence the dispersion characteristics. In this study, dispersion of SO2 and NO from two major coal-fired thermal power plants in Andhra Pradesh, India have been studied using an integrated modeling approach of the Advanced Research Weather Research & Forecasting (ARW) model and Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Meteorological conditions are obtained at 3-km resolution using the ARW model and dispersions of SO2 and NO is computed using the HYSPLIT model for the four seasons of winter, summer, monsoon and post-monsoon. Forward trajectories produced by the HYSPLIT model show diurnal variations and dispersion patterns show seasonal variations indicating the influence of meteorological conditions. Dispersion characteristics show high dispersion in winter due to calm and stable atmospheric conditions to insignificant in summer season due to stronger winds and higher atmospheric instability. The study establishes the usefulness of integrated meteorological and dispersion models for the evaluation of pollutant dispersion.

 

 

Keywords: Particulate matter; Dispersion; Power plants; ARW model; HYSPLIT.

 

 

Copyright © 2009-2014 AAQR All right reserved.