Photochemical model assessment of single source NO₂ and O₃ plumes using field study data.

Area of Science:

• Atmospheric chemistry and air quality modeling.
• Environmental science and policy.
• Geospatial analysis of air pollution.

Background:

• Photochemical grid models are crucial for air quality policy but lack sufficient field data for evaluating single source impacts.
• Evaluating the spatial extent and chemical composition of industrial plumes is essential for accurate air quality assessments.
• New measurement techniques provide opportunities to validate and improve air quality models.

Purpose of the Study:

• To evaluate photochemical model performance in simulating single source plumes using new field measurements.
• To compare source sensitivity and source apportionment methods for attributing air pollution impacts.
• To assess the influence of grid resolution on the accuracy of single source impact modeling.

Main Methods:

• Application of photochemical models with source sensitivity (brute-force, DDM) and source apportionment approaches.
• Utilizing new tropospheric column NO2 and in-plume chemical measurements for model evaluation.
• Simulating single source impacts at various grid resolutions (1-12 km).

Main Results:

• Source sensitivity methods effectively captured NO2 plume extent and ozone dynamics (titration to production).
• Source apportionment methods showed variability in attributing plume extent and ozone production.
• Finer grid resolutions (1-12 km) improved the representation of plume extent and magnitude for both NO2 and PM2.5.

Conclusions:

• Photochemical models can capture single source plumes, with finer grid resolutions yielding better results.
• Source sensitivity approaches, particularly DDM, offer improved accuracy in attributing ozone impacts compared to source apportionment.
• Model evaluation with field data is critical for refining air quality assessments and supporting regulatory decisions.