Reduced
complexity tools that provide a representation of both
primarily emitted particulate matter with an aerodynamic diameter
less than 2.5 μm (PM2.5), secondarily formed PM2.5, and ozone (O3) allow for a quick assessment
of many iterations of pollution control scenarios. Here, a new reduced
complexity tool, Pattern Constructed Air Pollution Surfaces (PCAPS),
that estimates annual average PM2.5 and seasonal average
maximum daily average 8 h (MDA8) O3 for any source location
in the United States is described and evaluated. Typically, reduced
complexity tools are not evaluated for skill in predicting change
in air pollution by comparison with more sophisticated modeling systems.
Here, PCAPS was compared against multiple types of emission control
scenarios predicted with state-of-the-science photochemical grid models
to provide confidence that the model is realistically capturing the
change in air pollution due to changing emissions. PCAPS was also
applied with all anthropogenic emissions sources for multiple retrospective
years to predict PM2.5 chemical components for comparison
against routine surface measurements. PCAPS predicted similar magnitudes
and regional variations in spatial gradients of measured chemical
components of PM2.5. Model performance for capturing ambient
measurements was consistent with other reduced complexity tools. PCAPS
also did well at capturing the magnitude and spatial features of changes
predicted by photochemical transport models for multiple emissions
scenarios for both O3 and PM2.5. PCAPS is a
flexible tool that provides source-receptor relationships using patterns
of air quality gradients from a training data set of generic modeled
sources to create interpolated air pollution gradients for new locations
not part of the training database. The flexibility provided for both
sources and receptors makes this tool ideal for integration into larger
frameworks that provide emissions changes and need estimates of air
quality to inform downstream analytics, which often includes an estimate
of monetized health effects.