Prediction of SPM Concentration Using Air Dispersion Model: A Case Study of Thermal Power Plant Volume 6 - Issue 1

Akshey Bhargava¹*, Megha TS² and SheetalKamble³

• ¹Ex. Rajasthan Pollution Control Board, CEPT University, India
• ²Department of Civil Engineering (Translational Engineering), Government Engineering College Barton Hill, India
• ³Assistant Professor, Environmental Science, P P Savani University, India

Received: February 04, 2021   Published: February 24, 2021

Corresponding author: Akshey Bhargava, Ex. Rajasthan Pollution Control Board, CEPT University, India

DOI: 10.32474/OAJESS.2021.06.000229

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Abstract

Air pollution has been termed as a democratizing force, but it is far from that, as it propagates existing environmental injustices. Industrial development and rapid urbanization have adversely affected urban air quality due to industrial and vehicular emissions. Air pollution exposure has shown to affect cognitive development in children, slow lung development and has resulted in high levels of mortality from respiratory infections. The elderly is more likely to develop cardiac illnesses and chronic respiratory as a result of long-term exposure and are more susceptible to strokes and heart attacks during episodic high pollution events. Thermal Power Plant has been a major source of air pollution for so long. Increasing health problems has made particulate matter to give special attention by control technology and framing regulations. Suspended particulate matter (SPM) is considered to be the main pollutant emitted by the power station. Atmospheric dispersion pollution modelling is of great and actual concern in the scientific international community. Many dispersion models have been developed and used to estimate the downwind ambient concentration of air pollutants from sources such as industrial plants, vehicular traffic, or accidental chemical release. Among them, Gaussian model is perhaps the most commonly used model type. It is often used to predict the dispersion of air pollution plumes originated from ground-level or elevated sources. An attempt has been made in the present paper by the authors to discuss such models with a view to select a particular model that can be used for a particular area or application. An effort has also been made to predict SPM concentrations from a coal based thermal power plant at various receptor points using model of Gaussian dispersion.

Keywords: Suspended particulate matter (SPM); Thermal power plant; Air dispersion model; Gaussian approach; Dispersion coefficients; Predictions; Urbanization; Gaussian model; Atmospheric dispersion modelling; Meteorology; Mitigation; Air pollution; Turbulent fluxes; Atmosphere; Estimated wind velocities

Abstract| Introduction| Air Pollution Modelling| Case Study| Findings| Conclusion| References|