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WILDFIRE EMISSION MODELING: INTEGRATING BLUESKY AND SMOKE
Citation:
POULIOT, G., T. E. PIERCE, W. G. BENJEY, S. M. ONEILL, AND S. A. FERGUSON. WILDFIRE EMISSION MODELING: INTEGRATING BLUESKY AND SMOKE. Presented at 14th International Emission Inventory Conference, Las Vegas, NV, April 11 - 14, 2005.
Impact/Purpose:
The objectives of this task are to develop, improve, and evaluate EPA's Community Multiscale Air Quality (CMAQ) model, as an air quality management and NAAQS implementation tool. CMAQ is a multiscale and multi-pollutant chemistry-transport model (CTM) that includes the necessary critical science process modules for atmospheric transport, deposition, cloud mixing, emissions, gas- and aqueous-phase chemical transformation processes, and aerosol dynamics and chemistry. To achieve the advances in CMAQ, research will be conducted to develop and test appropriate chemical and physical mechanisms, improve the accuracy of emissions and dry deposition algorithms, and to develop and improve state-of-the-science meteorology models and contributing process parameterizations.
The model will be tested and evaluated to thoroughly characterize the performance of the emissions, meteorological and chemical/transport modeling components of the CMAQ system, with an emphasis on the chemical/transport model, CMAQ. Emissions-based models are composed of highly complex scientific hypotheses concerning natural processes that can be evaluated through comparison with observations, but not truly validated. Both operational and diagnostic evaluations, together with sensitivity analyses are needed to both establish credibility and build confidence within the client and scientific community in the simulation results for policy and scientific applications. The characterization of the performance of Models-3/CMAQ is also a tool for the model developers to identify aspects of the modeling system that require further improvement.
Description:
Atmospheric chemical transport models are used to simulate historic meteorological episodes for developing air quality management strategies. Wildland fire emissions need to be characterized accurately to achieve these air quality management goals. The temporal and spatial estimates of emissions from fires, both wild and prescribed, have been problematic primarily because of uncertainty in the size and location of sources, and their temporal and spatial variability. Therefore, methods to estimate wildfire emissions that characterize their temporal and spatial variability are needed. The US Forest Service (USFS) and the US Environmental Protection Agency (EPA) have signed an interagency agreement to improve the episodic modeling of fires with improved fuel loading data, fire location information, and fire behavior modeling (including plume behavior), using meteorological inputs. The USFS has developed a tool known as BlueSky to predict cumulative impacts of smoke from forest, agricultural, and range fires. The BlueSky modeling framework combines state of the art emissions, meteorology, and dispersion models to generate predictions of smoke impacts across the landscape. The Sparse Matrix Operator Kernel Emission (SMOKE) processing system is a tool that creates gridded, speciated, and temporally allocated emission estimates for use in atmospheric chemical models. Portions of these tools have been combined to allow for an accurate characterization of fuel loading, temporal and spatial distribution of fire emissions, and a more accurate representation of fire plumes. By combining these two tools, the ability to simulate the impact of wildfires on air quality and develop air quality management strategies will be enhanced. This paper shows results from combining these two tools and an example from an air quality modeling simulation.