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Armistead G Russell¹

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The U.S. Environmental Protection Agency

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Area of Science:

Environmental Science
Atmospheric Chemistry
Air Quality Modeling

Background:

The U.S. Environmental Protection Agency's (EPA) Supersite Program aimed to enhance air quality models.
High-resolution data from Supersites are crucial for evaluating and improving these models.

Purpose of the Study:

To review modeling studies that utilized Supersites data.
To assess the performance of air quality models and their application in air quality management.

Main Methods:

Utilized fine temporal resolution data from Supersites.
Evaluated air quality modeling systems like Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with extensions (CAMx).
Examined model responses to various emissions control scenarios.

Main Results:

Inorganic thermodynamic approaches and sulfate production descriptions in models are accurate.
Significant uncertainties exist in nitric acid production, emissions (biogenic, ammonia), secondary organic aerosol formation, and ultrafine particle evolution.
Emissions controls may lead to nitrate partially replacing sulfate in particulate matter (PM), with minor seasonal effects.

Conclusions:

Supersites data have advanced PM models and benefited policy-related modeling by EPA and other agencies.
While some model components are accurate, further research is needed to address identified uncertainties in air quality modeling.