High-resolution three-dimensional plume modeling with Eulerian atmospheric chemistry and transport models

Abstract

Eulerian chemical transport models are extensively used to steer environmental policy, forecast air quality and study atmospheric processes. However, the ability of these models to simulate concentrated atmospheric plumes, including fire-related smoke, may be limited. Wildland fires are important sources of air pollutants and can significantly affect air quality. Emissions released in wildfires and prescribed burns have been known to substantially increase the air pollution burden at urban locations across large regions. Air quality forecasts generated with numerical models can provide valuable information to environmental regulators and land managers about the potential impacts of fires. Eulerian models present an attractive framework to simulate the transport and transformation of fire emissions. Still, the limitations inherent to chemical transport models when applied to replicate smoke plumes must be identified and well understood to adequately interpret results and further improve the models' predictive skills. Here, a modeling framework centered on the Community Multiscale Air Quality modeling system (CMAQ) is used to simulate several fire episodes that occurred in the Southeastern U.S. and investigate the sensitivity of fine particulate matter concentration predictions to various model inputs and parameters. Significant sources of uncertainty in the model are identified and discussed, including the spatiotemporal allocation of fire emissions and meteorological drivers. In addition, special attention is given to model grid resolution. Adaptive grid modeling is explored as a strategy to simulate fire-related plumes. An adaptive version of CMAQ, capable of dynamically restructuring the grid on which solution fields are estimated and providing refinement at the regions where accuracy is most dependent on resolution, is presented. The fully adaptive three-dimensional modeling technique can be applied to reach unprecedented levels of grid resolution and provide insight into plume dynamics unattainable with static grid models. Through this work the capability of current chemical transport models to replicate fire-related air quality impacts is evaluated, key research needs to achieve effective simulations are identified, and numerical tools designed to improve model performance are developed.