Light Rail and GHG Emissions Modeling Assignment

Many cities in the U.S. that have historically been highly dependent on automobiles for transportation are currently planning, constructing, or expanding their light rail public transit systems. To use Austin as an example, voters approved Project Connect in 2020, and it envisions building two light rail lines in addition to commuter rail lines, more rapid bus routes, and various other projects. One motivation for investing in light rail, although certainly not the only one, is that enabling residents to travel via light rail instead of automobiles should reduce greenhouse gas (GHG) emissions and thus constitute a climate change mitigation strategy.

When a city invests in light rail, what effect does it have on GHG emissions?

Fundamentally, this is the question that you must answer. What type of model you build and what type of analysis you perform are totally up to you. A strong model will have sensible mechanisms that link light rail investment to changes in residents choices and activities that determine their GHG emissions. To the extent that your model represents residents whose choices and activities endogenously respond to the addition of light rail, this will lead to a richer model than one that makes exogenous assumptions about how they respond.

Create a Mathematical model taking into consideration the transportation network model, a behavioral model of residents, a GHG emissions model, and a land use model. Choose the necessary variables, constraints, and assumptions/limitations to make this model work.