A new study by University of Wisconsin-Madison and Argonne National Laboratory is utilizing machine learning and high-resolution data to estimate boundary layer height in real time, with a focus on the impact of wildfire smoke from Canada on air quality in Wisconsin. Changes in boundary layer height play a crucial role in the dispersion of pollutants, with lower heights trapping pollutants near the surface. This model will assist public health officials in anticipating changes in air quality conditions, including smoke impacts, and providing earlier warnings to the public. By understanding the dynamics of the boundary layer, experts can better address the challenges of air pollution and climate change.
https://www.enn.com/articles/78187-predicting-where-wildfire-smoke-will-go-next