Support Center for Regulatory Atmospheric Modeling (SCRAM)
Photochemical Modeling Applications
Provides access to modeling applications involving photochemical models, including modeling of ozone, particulate matter (PM), and mercury for national and regional EPA regulations such as the Clean Air Interstate Rule (CAIR) and the Clean Air Mercury Rule (CAMR).
CAIR 2010/2015 Ozone Source Apportionment Source Apportionment modeling was completed with the Comprehensive Air Quality Model with Extensions (CAMx) to look at the relative contributions of emissions from various source sectors (by State) to projected residual 8-hour ozone nonattainment in 2010 and 2015. This modeling has accounted for the NOx reductions resulting from the Clean Air Interstate Rule (CAIR) within the future-year base emissions. The analysis can be useful in considering potential control strategies within certain projected nonattainment areas. However, it cannot be used as a substitute for finer-scale State attainment demonstration modeling, as the modeling is regional in nature. Further this modeling does not assess which emissions control strategies are cost effective and practical to control.
CMAQ-based Response Surface Modeling of PM2.5 We developed a Response Surface Model (RSM) based on the Community Multi-scale Air Quality (CMAQ) model to support the Regulatory Impact Assessment for the proposed PM2.5 National Ambient Air Quality Standards (NAAQS). RSM is based on a new approach known as air quality metamodeling that aggregates numerous pre-specified air quality modeling simulations into a multi-dimensional air quality “response surface”. Simply, this metamodeling technique is a “model of the model” and can be shown to reproduce the results from an individual modeling simulation with little bias or error. The RSM is based on statistical relationships between model inputs and outputs to provide real-time estimate of these air quality changes. The RSM provides a wide breadth of model outputs, which can be used to develop emissions control scenarios. The RSM approach informs the selection and evaluation of various control scenarios. This approach allows for the rapid assessment of air quality impacts of different combinations of emissions reductions and was used to estimate air quality changes for various control scenarios for the proposed PM2.5 NAAQS. The documentation provides information on (1) the emissions inventories and development of projections, (2) the air quality modeling and development of model inputs, (3) development and experimental design of the RSM, and (4) the performance and validation of the RSM as compared to the air quality modeling.