Process analysis requires a substantial amount of expertise to be interpreted to full

advantage. However, useful insights are also possible with less detailed analyses. An analysis

can focus on selected grid cells in a small area. Process analysis then takes advantage of the fact

that a numerical grid model addresses physical and chemical factors affecting secondary

pollutants in a sequential manner. For example, a typical sequence followed in a model for each

time step (e.g., 1 hour) might be (1) advection of PM2.5 components and precursors present at the

beginning of the time step, (2) PM2.5 and precursor emissions added during the time step, (3)

vertical diffusion of the advected material and fresh emissions, (4) estimated cloud cover and its

effects on photolysis rates, (5) atmospheric chemistry involving advected and diffused material

with fresh emissions, and (6) deposition of certain compounds. Process analysis examines

incremental effects on changes in component and/or PM2.5 predictions from hour to hour

attributable to each of the processes described above. In this way, one gets a sense of how

important each process is as a contributor to predicted air quality at a specified time and location.

If a focused diagnostic analysis, such as one obtained with process analysis, suggests a

particular model prediction may be an artifact of a model assumption rather than a result of real

chemical/physical atmospheric processes, States may wish to go back to the meteorological or

emissions model to verify that the inputs and assumptions that have been used are correct. If a

prediction is the result of an apparent artifact which cannot be resolved, States may wish to

discount that prediction in the attainment demonstration or uniform rate of progress assessment.

 

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