Modeling variable emissions using a Monte-Carlo approach

What is it about?

Emissions of pollutants such as SO2 from external combustion sources can vary widely depending on fuel sulfur content and load. To respond to a need to account for emission distributions to address probabilistic 1-hour ambient air quality standards for SO2 and NO2, the authors have developed an advanced technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling of emission rates in modeling associated with user-specified emission distributions and their probabilities. EMVAP is typically used to simulate hundreds or even thousands of years of concentration predictions, from which a median estimate of the critical concentrations can be obtained.

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Why is it important?

Air quality models lack the means to account for randomly-occurring emission spikes, but operating permits often do not allow for these important and unavoidable events. The EMVAP approach allows a user to define the frequency and magnitude of these events and to test them rigorously to show that ambient standards are still met if the emission spikes are sufficiently infrequent.

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