Chapter 10. Dispersion of air pollutants

Table of Contents

10.1. Introduction
10.2. Overview of air dispersion modelling
10.2.1. The transport equation
10.2.2. Turbulence parameterization
10.2.3. Chemical reactions and radioactive decay
10.3. Gaussian dispersion models
10.3.1. Theory and limitations of Gaussian models
10.3.2. History of development
10.3.3. Advanced Gaussian models
10.4. Lagrangian models
10.4.1. Calculation of trajectories
10.4.2. Puff models
10.4.3. Trajectory models
10.5. Eulerian models
10.5.1. Solving atmospheric transport equations
10.5.2. Operator splitting
10.6. Computational Fluid Dynamics models

10.1. Introduction

There are many accidents and natural events, where harmful and toxic chemical species can be emitted into the atmosphere (e.g., accidental release at nuclear power plant (NPP), volcano’s eruptions, forest fires). These air pollutants can travel hundreds and thousands kilometres from their release points across the globe depending on their chemical (chemical composition) and physical (e.g., solubility in water, size distribution for aerosol particles) properties, and they affect the human health and result in a long-term effect on our environment. Moreover, such incidents could have huge economical impact. For example the eruption of Eyjafjallajökull in Iceland over a period of six days in April, 2010 caused enormous disruption to air travel in most part of Europe because of the closure of airspace. Estimated lost of airlines was about US$1.7 billion.

It is important to note that model simulations must have a high degree of accuracy and must be achieved faster than real time to be of use them in an effective decision support. Therefore, accurate and fast simulation of dispersion of toxic chemical substances or radionuclides in the atmosphere is one of the most important and challenging tasks in atmospheric sciences. Chernobyl disaster and an increased demand from the society have stimulated the development of accidental release programs and complex decision making softwares (e.g., RODOS). Underestimating the maximum concentrations of air pollutants may have serious health consequences, and conversely, applying remediation measures in regions where significant dosage will not be received would waste valuable resources and may have significant social implications if evacuation or other interventions is required. This demand and extreme pressure from the society and business bodies can be illustrated by the following statement by Giovanni Bisignani, chief executive of IATA, during the Eyjafjallajökull incidents: “Airspace was being closed based on theoretical models, not on facts. Test flights by our members showed that the models were wrong.”

Dispersion of air pollutants in the troposphere is mainly governed by advection (wind) field, however, other processes like turbulent diffusion (turbulence) or radioactive decay, chemical reaction and deposition of air pollutants play important role in the spatiotemporal evolution of dispersion pattern. Development of models requires complex thinking and interaction of researchers from different fields. For simulating the dispersion of air pollutants, various modelling approaches have been developed. The main aim of this chapter is to provide a comprehensive review of air pollution modelling. The chapter is structured as follows. Section 2 provides an overview of air pollution modelling. Following 3 sections describe Gaussian, Lagrangian and Eulerian dispersion models with their advantages and drawbacks. Finally, section 6 discusses computational fluid dynamics models for environmental modelling.