Modeling: Providing a useful guide to air quality
Published on October 24, 2024
A lot has been written about air quality. But how is it possible to discover facts and make future predictions about the air people breathe? That information is found through air quality modeling.
Modeling is a process that uses computers and math to estimate air pollution and associated human health exposures. Utilizing various factors that affect air quality, such as emissions from vehicles, industries and natural sources, models can be made that help us better understand air quality. This work can be done using two different types of modeling: Photochemical and Dispersion.
Photochemical modeling combines weather, chemistry, and emissions at the surface to simulate the changes of pollutant concentrations in the atmosphere. The information produced by photochemical models helps tell us which emissions sources contribute to ozone concentrations and how different control strategies will impact the production of ozone.
Dispersion modeling tells us how a pollutant will spread from its emission source based on factors like emission rates, weather, and facility-specific details The information from dispersion modeling can then be used to assess potential impacts to human health and the environment. Modeling is important because the information garnered can be used to help reduce emissions and protect vulnerable populations.
However, a model is only as good as the observations you start with. This is why Weld County invested in collecting regulatory-grade air monitoring data to fill in gaps in data across the county. Weld County air quality and weather data will be available for dispersion modeling by the Permit Modeling Unit at the Air Pollution Control Division for Colorado to inform air permit decisions. In addition, Weld County staff are working with the Regional Air Quality Council to ensure our air quality data is used to evaluate the photochemical modeling used to determine effective ozone reduction strategies.
Learn more about air quality modeling.