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For research on the sustainability (carbon emissions) of shared autonomous vehicles, I'm building a very simple model that takes the occupancy and modal shift as uncertainties. CO2 equivalent and the modal mix (in a summation series) lead to total emissions.
However, I have the case of a shifting reference scenario: transport is already electrifying and the electricity production is moving to carbon neutral.
What's the best practice on handling that? Internalizing these uncertainties in the model? Full SD? Just wrapping some scenarios in an outer loop? Or are there some smarter tricks? (considering I want to keep it simple)
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Hi @quaquel,
For research on the sustainability (carbon emissions) of shared autonomous vehicles, I'm building a very simple model that takes the occupancy and modal shift as uncertainties. CO2 equivalent and the modal mix (in a summation series) lead to total emissions.
However, I have the case of a shifting reference scenario: transport is already electrifying and the electricity production is moving to carbon neutral.
What's the best practice on handling that? Internalizing these uncertainties in the model? Full SD? Just wrapping some scenarios in an outer loop? Or are there some smarter tricks? (considering I want to keep it simple)
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