From Mark Monmonier’s Air Apparent: How Meteorologists Learned to Map, Predict, and Dramatize Weather (1999):
“Different chemicals and weather conditions generate surface plumes, or footprints, varying in shape and length” (104).
“A map focused on one location can either present the model plume for a particular hypothetical accident under specific meteorological conditions or describe composite, average vulnerability for representative variations in local weather” (102).
Emergency response officials in state and local government, “rely on user-friendly, menu-driven software to link SARA Title III information and meteorological data with toxicity databases electronic maps, and mathematical models. Two types of models are required: a source model that describes the substance, its storage vessel, and the circumstances of its release, and a dispersion model that estimates concentration at points downwind for specific times since the release began. The source model reckons the state (liquid or gas), concentration, and release rate of the escaping fluid from the size and elevation of the tank, the amount in storage, the size and position of the opening, and temperatures inside and outside the tank—whether a gas escapes slowly or rapidly is important, as is the likely rate at which a refrigerated liquid is likely to boil to a vapor. […] The dispersion model then simulates dilution and transport by the atmosphere under specific assumptions about wind speed, air temperature, and other meteorological factors” (104-105).
“Can residents and local officials trust the maps and the planners’ conclusions? Federal and state regulations suggest they can. After all, the air-quality analysis was conducting according to EPA guidelines under state supervision by air-quality scientists at the New York State Department of Environmental Conservation, and the estimated risk proved minimal, not borderline.
Weather, of course acts as its own mapping engine, generating a continual stream of informative graphics. Regulatory decisions, by contrast, must rely on the eagerness of engineers, public officials, and concerned citizens to consider numerous designs and locations and thereby use air-dispersion modeling as an exploratory tool, not just as a means of conjuring up a few maps to appease clean-air statues. However imperfect, air-dispersion modeling can be a highly effective tool (and this is always a big if) the user understands how to use it and how well it performs. Atmospheric scientists need not only to develop more sophisticated models but also to improve their methods for both assessing and communitcating a model’s expected performance. After all, a flawed forecast based on a poorly understood environmental-impact or emergency-response model can have consequences far more tragic than an inaccurate five-day weather outlook.” (115-116).