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Modeling Fire and Ecosystems: Improving the Vertical Allocation of Smoke in a Chemical Transport Model
The area burned by wildland fires (prescribed and wild) across the contiguous United States has expanded by nearly 50% over the past 20 years, now averaging 5 million ha per year.
Chemical transport models are used by environmental decision makers to both examine the impact of air pollution on human health and to devise strategies for reducing or mitigating exposure of humans to harmful levels of air pollution. Since wildfires are increasing in size and burning more intensely, the exposure of humans to fine particulate matter (PM2.5) and ozone (O3) is projected to grow.
Currently, there is little consensus on fire pollution vertical transport methods. The height to which a biomass burning plume is injected into the atmosphere, or plume rise, is not only difficult to qualitatively determine but also comes with quantitative difficulties due to poor understanding of physical constraints within models.
Many air quality models rely on plume rise algorithms to determine vertical allocation of emissions using various input models or in-line plume height calculations to determine plume height vertical structures and invoke transport of emissions. In this work, we test basic plume rise methods currently being used in chemical transport modeling in order to determine where the Community Multiscale Air Quality (CMAQ) modeling system’s current capabilities can be improved.
We investigate proposed improvements for allocating the vertical distribution of smoke by separately characterizing the impacts of model grid resolution, emissions temporal profile, and plume rise algorithm.
