Process analysis: Process analysis techniques allows one to quantitatively track (mass

balancing) the contributions of individual physical and chemical atmospheric processes to the

overall change in pollutant concentrations at a particular time and location. Thus, process

analysis will assess the relative importance of each physical and chemical process for a particular

model simulation as well as explain how model predictions are obtained, which is valuable when

modeling nonlinear systems such as atmospheric photochemistry. Since models used to simulate

ozone and secondary particulate matter are similar, process analysis should also be useful for

addressing both ozone and PM2.5 (and visibility related) applications.

Three of the most common process analysis tools implemented in grid models are the

integrated process rate (IPR) analysis, the integrated reaction rate (IRR) analysis, and the

chemical process analysis (CPA). The IPR analysis is used to determine the relative contributions

of individual physical (e.g., advection, diffusion, emissions) and chemical (e.g., chemical

reaction, aqueous chemistry, aerosol production) processes, potentially revealing unexpected low

or high process contributions. The IRR analysis is used to identify and explain the details of the

chemical transformations (chemical pathways and key chemical characteristics) in a particular

model simulation. Typically, IRR analyses have been used to determine and understand model

prediction differences between chemical mechanisms (e.g., CB-IV, SAPRC). Likewise, the CPA

is an improvement on the IRR analysis technique where part of the processing of IRR information

is internalized within the air quality grid model to yield key chemical parameters directly (e.g.,

budget terms for ozone and NOx).

 

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