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3 cards from this section. Quick, good the night before a test.
What does the steady-state assumption imply for pollutant concentration?
Think about time and measurement in the environment.
Identify the key characteristic of Gaussian dispersion.
Consider shapes and how pollutants spread.
What is the essence of the steady-state assumption?
Think about measurements taken over time.
True or False: Idealized curves in dispersion modeling are always reliable.
Consider the variability of actual environmental data.
Given a scenario where a new factory is introduced into a community, analyze the potential impact of pollutant dispersion using Gaussian modeling, considering wind patterns and height of emissions.
Use vector analysis for wind direction with the emission height.
Explore a case where pollution levels in a real-world setting do not conform to the ideal Gaussian distribution. What causes this deviation?
Think of sudden weather changes or geographic barriers.
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