Development and application of a parallelized version of the advanced modeling system for transport, emissions, reactions and deposition of atmospheric matter (AMSTERDAM): 1. Model performance evaluation and impacts of plume–in–grid treatment

The Community Multiscale Air Quality Model (CMAQ) is a comprehensive three–dimensional “one–atmosphere” air quality model that is now routinely used to address urban, regional–scale and continental–scale multi– pollutant issues such as ozone, particulate matter, and air toxics. Several updates have been made to CMAQ by the scientific community to enhance its capabilities and to provide alternative science treatments of some of the relevant governing processes. The Advanced Modeling System for Transport, Emissions, Reactions and Deposition of Atmospheric Matter (AMSTERDAM) is one such adaptation of CMAQ that adds an Advanced Plume–in–grid Treatment (APT) for resolving sub–grid scale processes associated with emissions from elevated point sources. It also incorporates a state–of–the–science alternative treatment for aerosol processes based on the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID). AMSTERDAM is configured to provide flexibility to the model user in selecting options for the new science modules. This paper describes the parallelization of AMSTERDAM to make it a practical tool for plume–in–grid (PinG) treatment of a large number of point sources, and presents results from its application to the central and eastern United States for summer and winter periods in 2002. Over 150 coal–fired power plants in the domain with high emissions of sulfur dioxide (SO2) and nitrogen oxides (NOX) were selected for PinG treatment in the CMAQ–MADRID–APT configuration of AMSTERDAM used for this application. Although both model configurations (grid–only and PinG) give similar model performance results (an aggregate measure of model skill), the results show significant differences between the two versions in the specific nature of the predicted spatial distribution of ozone and PM2.5 concentrations. These differences can be important in determining source contributions to ambient concentrations. A companion paper examines the differences in the predicted contributions of hypothetical source regions from the two configurations of the model.