Modeling

Modeling - Basic Overview

Air quality/pollution modeling is an indispensable tool for managing air quality. Modeling helps estimate the relationship between sources of pollution and their effects on ambient air quality. Air quality managers use models to identify source contributions to air quality problems and assist in the design of effective strategies to reduce harmful air pollutants.

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Modeling - Intermediate Overview

Topics include uses of models (regulatory compliance and resolution of litigation), categorization of model by general type (Gaussian and grid-based), general governing equations, categories of model inputs, types of solutions of equations, alternative model formulations, spatial and temporal scales addressed and resolutions adopted, types of uncertainty of concern, experience and current and proposed approaches to evaluation of model performance, and data needs.

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Modeling - Advanced Overview

The first comprehensive book on Air Pollution Modeling was published in 1990. Later, this book was expanded into a series of four multi-author volumes (Air Quality Modeling). The original 1990 book can still be used to provide a panoramic view of topics, equations, and numerical methods for air pollution modeling, together with a historical perspective.

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Data Needs

Sources of meteorological observations, weather maps, and satellite imagery. Compiled by Ron Baskett.

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Emission Modeling and Inventory

The US EPA "AP-42: Compilation of Air Emission Factors" is one of the most complete and useful references to calculate emission data for a large set of activities and scenarios. It contains emissions factors and process information for more than 200 air pollution source categories.

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Use of Models - Legal Cases

Many legal cases around the world involve environmental issues and, in particular, air pollution problems. This is especially noticeable in the United States. Often, simulation models play an important role in these cases, for example when a chemical accidental release occurred and an expert is asked to assess the incident.

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Use of Models - Preparedness and Response

A report authored by Michael Pirhalla, M.S., U.S. Environmental Protection Agency (US EPA) discusses Dispersion Modeling Systems Relevant to Homeland Security Preparedness and Response. The report includes a literature review and lists 96 dispersion models that could be used for emergency response to a wide-area release.

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Atmospheric Transformations

Atmospheric transformations encompass both physical and chemical changes of chemicals in the atmosphere. Modeling atmospheric transformations include gas phase chemical reactions, phase transitions, aqueous phase reactions, and processes involved in the formation of ozone, particulate matter, hazardous air pollutants, and halogen chemistry.

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Atmospheric Transformations - Gas Phase

A set of introductory slides on gaseous pollutants has been provided, courtesy of Dr. Christian Seigneur. These slides are the basis of his 2019 book: Air Pollution - Concepts, Theory, and Applications.

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Atmospheric Transformations - Aerosols

A set of introductory slides on atmospheric particles has been provided, courtesy of Dr. Christian Seigneur. These slides are the basis of his 2019 book: Air Pollution - Concepts, Theory, and Applications.

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Deposition Phenomena

A set of introductory slides on transfer of pollutants between the atmosphere and surfaces has been provided, courtesy of Dr. Christian Seigneur. These slides are the basis of his 2019 book: Air Pollution - Concepts, Theory, and Applications.

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Deposition Phenomena

Deposition phenomena are the way the atmosphere cleans itself by depositing chemicals on earth surfaces. This exchange process can be parameterized and modeled by simulating the turbulence characteristics of the atmospheric flow. These turbulence characteristics require specific parameterization procedures to take very different and complex environments into account.

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Gaussian Models

Prof. Romualdo Salcedo has developed IMDIS - A Teaching Tool for Air Pollution Dispersion Modeling. This book intends to serve as a reference to follow-up on a better comprehension of air pollution modeling with the aid of hands-on user-friendly software, highlighting the main advantages (but also disadvantages) of using Gaussian dispersion as the main drive to teach this subject.

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Gaussian Models

Both AERMOD and CALPUFF are air quality dispersion models widely used worldwide. Currently, AERMOD is the main dispersion model in the list of the preferred and recommended models by the US-EPA. CALPUFF was part of that list from 2003 to 2017, but now is listed as an “alternative model”.

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Gaussian Models - Plume

Gaussian plume models are based on a simple mathematical formulation. The plume is assumed to travel horizontally and expand in the vertical and lateral (crosswind) directions. At each downwind distance the expansion of the plume is assumed to have a Gaussian distribution, and therefore to be described by the horizontal and vertical standard deviations of the distributions.

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Gaussian Models - Plume

The Gaussian Plume Model is the most common air pollution formulation used throughout the world. Today, the preferred model in the US is the AERMOD Modeling System, as recommended by the US EPA. A simplified, easy-to-use Gaussian plume model is AERSCREEN. EPA models can be freely downloaded from the EPA site.

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Gaussian Models - Puff

Since the 1980s, Gaussian puff models have provided an interesting and cost-effective approach, which maintains the basic Gaussian plume formulation, but allows dynamic, instead of steady state, simulations and permits the incorporation of three-dimensional meteorological inputs.

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Gaussian Models - Special Applications

Gaussian models are routinely used to simulate air quality throughout the world. They exist in several forms, from a relatively simple equation, such as the straight-line stationary Gaussian plume, to other more complex formulations, such as Gaussian segmented plume and Gaussian puffs.

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Eulerian Dispersion Models

Eulerian Models are typically described as models in which there is a fixed reference grid system and pollution concentrations are calculated at each time step and each point in the grid. They are different from Lagrangian models in which pollution elements (e.g., puffs or particles) are followed in time and space along their trajectories.

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Lagrangian Particle Models

In a Lagrangian stochastic model (LSM), also called Lagrangian Particle or Random Walk model, the motion of air masses or particles passively following the flow is studied. To simulate the presence of turbulent eddies, particle velocities are subject to a random forcing.

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Indoor Air Pollution Modeling

Emission of pollutants and their accumulation due to poor ventilation and air exchange are serious problems that are currently under investigation by many researchers. Recent concerns include indoor spreading of viruses and the use of indoor modeling to properly design ventilation in hospitals and public indoor areas.

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Meteorological Modeling - Coupling Meteorological and Air Quality Models

The coupling of meteorological and air quality models is important to assure that air quality dispersion models take full advantage of the three-dimensional data simulated by meteorological models (e.g., wind vectors).

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Model Evaluation and Uncertainty

Model evaluation is a collection of activities one should perform in order to understand how a model behaves and how a model compares with observations. One of the elements of model evaluation is statistical model evaluation.

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Modeling of Adverse Effects

When one publishes risk assessment results, it is necessary to clarify that these estimates are very uncertain and conservative, and to underline that these estimates should be used for relative instead of absolute evaluations.

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Modeling of Adverse Effects - Odor Modeling

Odor modeling presents some challenges. In fact, models used for air quality compliance purposes calculate fixed time-averaged concentrations that can be directly compared with ambient air quality standards and criteria (generally with 1-hour to 1-year averaging times). Odors, on the other hand, can be recognized on the order of seconds or minutes.

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Modeling of Adverse Effects - Stratospheric Ozone

A set of introductory slides on the stratospheric ozone layer has been provided, courtesy of Dr. Christian Seigneur. These slides are the basis of his 2019 book: Air Pollution - Concepts, Theory, and Applications.

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Modeling of Adverse Effects - Visibility Impairment

A set of introductory slides on atmospheric radiation and visibility has been provided, courtesy of Dr. Christian Seigneur. These slides are the basis of his 2019 book: Air Pollution - Concepts, Theory, and Applications.

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Modeling of Pesticide Application, Deposition, and Drift

Applied modeling techniques are available to simulate ground spraying and aerial spraying of pesticides. One of the most important applications of these models is related to concerns about off-target drift of aerially applied pesticide sprays. Droplets depositing off-target are a waste of material and, more importantly, can damage nearby agricultural fields.

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Plume Rise

The initial phase of a chemical emission, characterized by temperature higher than the surrounding air and/or by an initial vertical velocity, is creating conditions for an initial rise of the plume. The rise stops when the plume becomes in equilibrium with the surrounding air. Almost all air quality models include special calculations for the simulation of the plume rise.

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Regulatory Modeling

Regulatory modeling is the science related to the development and use of agency-approved computer models for specific regulatory purposes. The main approach in regulatory modeling is the identification of proper simulation tools and default assumptions to assure a uniform and fair application of air quality laws and regulations.

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Statistical Modeling - Forecast and Alarm Systems

Statistical and stochastic models can be used to predict critical pollutant concentrations both in industrial and urban areas. Statistical models are generally useful when the information available from measured concentration trends is more relevant than the one obtained from the deterministic analyses.

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Statistical Modeling - Receptor Models

Receptor models are mathematical or statistical procedures for identifying and quantifying the sources of air pollutants at a receptor location. Unlike photochemical and dispersion air quality models, receptor models do not use pollutant emissions, meteorological data and chemical transformation mechanisms to estimate the contribution of sources to receptor concentrations.

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