– Rodriguez, L.M., P.E. Bieringer, T.Warner 2013 | J. Atmospheric Environment, Volume 64, January 2013, Pages 25-39, ISSN 1352-2310, 10.1016/j.atmosenv.2012.08.037
The transport and dispersion (T&D) models used for air-quality and defense applications require information describing the source parameters and meteorological conditions to forecast concentration and
dosage fields. In many cases the source parameters are known and the meteorological conditions are based on observational data or mesoscale-model-generated forecast conditions. This research examines
how errors in the input wind fields translate into uncertainty in the contaminant concentration predictions. In particular, this study focuses on street-level errors in the dispersion patterns that occur in “building aware” T&D models that are sensitive to urban designs (e.g. road and building patterns) and release locations relative to the buildings. This problem was evaluated by first creating a “truth” plume for a given release location and wind direction. Then the T&D model uncertainty associated with input wind errors were determined by comparing plumes calculated using wind directions varied at 2
increments to the truth plume. The uncertainty is quantified as fraction of overlap (FOO). The results are evaluated in a control simulation with no buildings, and in two commonly observed city designs (e.g. a regular grid, and hub and spoke configuration).
The analysis examines both idealized building configurations along with the urban topography from cities that represent the regular grid and hub and spoke city designs. Results show that the relative impact of the uncertainty in the meteorological conditions and the corresponding sensitivity of the model to variations in the wind direction vary significantly with the release location and city designs. This suggests that some source locations are less (more) sensitive to uncertainty in meteorological conditions and that this information can be factored into the confidence that is placed in emergency response decisions based on this information. Published by Elsevier Ltd.