Thesis Abstract

Abstract
Gas flaring is a common practice in the oil and gas industry for the controlled burning of flammable gases released during various operations. However, the combustion of these gases produces emissions that can have environmental and health impacts. Understanding the dispersion patterns of gas flare emissions is crucial for assessing the potential risks associated with exposure to these pollutants. In this study, we developed a simulation model to analyze the dispersion of gas flare emissions in different environmental conditions. The simulation model utilized computational fluid dynamics (CFD) techniques to predict the dispersion patterns of gas flare emissions. The model considered factors such as wind speed, atmospheric stability, and the characteristics of the flare stack to simulate the behavior of the emitted gases. By incorporating these parameters into the simulation, we were able to assess how the emissions would disperse and interact with the surrounding environment. Through the simulations, we observed that the dispersion patterns of gas flare emissions were highly influenced by wind speed and direction. Under stable atmospheric conditions, the emissions tended to stay closer to the ground and disperse over shorter distances. In contrast, unstable atmospheric conditions resulted in greater vertical dispersion and longer travel distances for the pollutants. These findings highlight the importance of considering meteorological factors when assessing the potential impacts of gas flare emissions on nearby communities and ecosystems. Furthermore, the simulation model allowed us to evaluate different scenarios and assess the effectiveness of mitigation measures. By adjusting parameters such as flare stack height or introducing wind barriers, we could observe how these changes affected the dispersion patterns of gas flare emissions. This capability provides valuable insights for designing strategies to minimize the environmental and health risks associated with gas flaring activities. Overall, this study demonstrates the utility of simulation models in predicting the dispersion patterns of gas flare emissions and assessing their potential impacts on the environment. By incorporating meteorological factors and varying scenarios, the model provides a versatile tool for decision-makers in the oil and gas industry to optimize flare management practices and minimize the adverse effects of gas flare emissions.

Thesis Overview

INTRODUCTION

Industrialization is highly desirable for the sustenance of a nation’s economy and the enhancement of the citizenry’s well-being. In the face of its numerous benefits, industrialization is characterized by environmental problems, chief among which is the release of the noxious substances into the atmosphere. Such releases come as a result of the combustion of associated gases following oil-field development, and combustion of hydrocarbon gases in oil refineries and vehicular as well as fugitive emissions, amongst others.

There is concern about the presence of persistent semi-volatile organic and inorganic compounds in the atmosphere. This is especially for those that are subject to long-range atmospheric transport and as a result, display toxic effect at low concentrations. A key regulatory response to the increasing levels of contaminants and green house gases is to monitor their concentrations in the atmosphere as well as other media, in an effort to establish source and distance trends. The presence of one or more of these contaminants in the outdoor or indoor atmosphere in quantities and duration such as to be injurious to human, animal or plant life is known as Air pollution. Since the issue of pollution is global, any study that is aimed at establishing trends in concentration levels of green house gases, particulates and other unfriendly substances in the atmosphere using analytical or numerical techniques is highly desirable.

1.2     Statement of the problem

Activities associated with Gas field development and other exploration and production activities usually deposit unwanted by-products into the ecological system. The effects may be catastrophic if their levels are uncontrolled or unchecked at least. In Nigeria, there is paucity of data on the major cities in Nigeria which involves a high level of sampling and analysis. On the other hand, simple sampling techniques can be adopted to evaluate urban and rural air quality for a few cities in order to generate a data base which can serve as base-line information for numerical studies in air quality in those cities. A combined monitoring-modeling approach, in which the concentration of inorganic species, total hydrocarbons and particulate matter in the atmosphere is obtained at various distances from a datum by analytical techniques followed by modeling and simulation of atmospheric dispersion, is a good starting point for generating a large of body information in atmospheric discharges.

 

 

 

 

 

1.3     Study objectives

The objective of this work is to evaluate the adaptability of a modified Gaussian dispersion model and has necessitated the following aims and objectives of this study:

• To develop a dispersion model suitable for predicting air quality for various atmospheric stability conditions.
• To design a simple quality simulator based on developed model.
• To simulate the concentration profiles of pollutants using computer program (Engineering Equation Solver)

1.4       Methodology

A modified Gaussian dispersion model was developed by applying Fick`s law of diffusion and conservation of species on a differential portion of a plume. This application led to a steady-state equation, whose general solution is given by Robert (1996).The expression for calculating the steady-state concentration field from point source was derived by substituting the turbulent diffusivities that are related to dispersion coefficients as shown by Robert (1996) into the general solution equation.

An algorithm for implementing the solution of the governing equation was developed using computer program as illustrated in a flow chart. The concentration profiles of pollutants were simulated using computer program (EES) and the results obtained were compared to those of SCREEN 4.