Posted: December 22nd, 2014Author: All4 Staff
As discussed in my recent blog, there has recently been some buzz surrounding the ozone primary and secondary National Ambient Air Quality Standards (NAAQS). Due to the proposed decrease in the ozone NAAQS and the possibility of them causing more ozone nonattainment areas, it is important to understand how the ozone NAAQS and nonattainment areas may be established using modeling techniques that are not the same as one generally uses for traditional air permitting requirements.
Ozone is a secondary pollutant; it is not generally directly emitted into the atmosphere. Ozone in the lowest levels of the atmosphere is formed through the reaction of sunlight and emissions of nitrogen oxides (NOX) and volatile organic compounds (VOC) directly in a given regional area or many miles downwind. The chemical reaction requires ultraviolet energy from sunlight, and is referred to as a “photochemical reaction.” Photochemical reactions are molecular reactions triggered by exposure to sunlight, and some of these reactions create extremely reactive molecular fragments called “radicals.” These radicals can react with VOC and NOX to form ozone. Due to the complexity of the chemistry involved in the ozone reactions, ozone cannot be evaluated using simple diffusion and dispersion (steady-state plume) algorithms (e.g., U.S. EPA’s AERMOD model). Instead, the ozone pre-cursors, the meteorological conditions, and atmospheric chemistry need to be modeled through a series of intricate equations over much larger spatial scales. As a result of the chemical complexity and the requirement to evaluate the effectiveness of future controls, U.S. EPA’s guidance strongly recommends using photochemical computer models to analyze ozone issues. Computer simulations are the most effective tools to address both the chemical complexity and the future case evaluation.
Photochemical air quality models have become widely recognized and routinely utilized tools by state regulatory agencies for regulatory analysis and attainment demonstrations by assessing the effectiveness of control strategies. The models have not typically entered into the air quality permitting process for individual facilities evaluating specific projects. These photochemical models are large-scale air quality models that simulate the changes of pollutant concentrations in the atmosphere using a set of mathematical equations characterizing the physical and chemical processes in the atmosphere. Photochemical grid models are intended to accurately depict the ways in which air pollution forms, accumulates, and dissipates by simulating the processes that are most essential in generating ozone pollution. These models have emission data from industrial sources, cars, trucks, locomotives, and many other sources that emit chemicals that lead to the formation of ozone and simulate the atmospheric reactions that result in ozone formation. The models are driven by meteorological models that are similar to those relied upon by weather forecasters because they can analyze the winds that carry pollutants to other areas around where the source is.
Ozone modeling involves two (2) major phases, the base case and the future case (with substeps in each phase). The base case evaluates procedures and ensures that the model is performing correctly. The future case evaluates the effectiveness of controls and demonstrates attainment based on how much ozone will be created in the future. A photochemical grid model simulates the atmosphere above a city by dividing it into thousands of boxes, essentially splitting it into individual grid cells that are typically a few kilometers wide. The thickness of the cells varies as the grid cells that are higher in the atmosphere tend to be thicker than the grid cells closer to the ground. The photochemical model calculates concentrations of pollutants, such as ozone, in each cell by simulating the following four (4) parameters: (1) the movement of air into and out of the grid cells, (2) the mixture of pollutants vertically among the layers, (3) the injection of new emissions from sources such as point, area, mobile, biogenic into each grid cell, and (4) the chemical reactions based on chemical equations, pollution precursors, and incoming solar radiation in each grid cell.
The two (2) most popular photochemical models most used by the air quality modeling community are the Comprehensive Air Quality Model with Extensions (CAMx) and the Community Multiscale Air Quality (CMAQ) Modeling System. These models might experience a rise in popularity in the coming years if the proposal to reduce the ozone primary and secondary standards is finalized. If U.S. EPA opts to introduce them into the Prevention of Significant Deterioration (PSD) permitting process for specific projects that trigger PSD permitting requirements for NOX or VOCs, it will add another layer of planning for those projects. ALL4 will continue to track U.S. EPA’s plans relative to photochemical modeling. The final ozone standards are set to be issued by October 1, 2015 and state nonattainment designation will be due in October of 2017.
TCEQ’s Introduction to Air Quality Modeling: Photochemical Modeling