Example Application Modeling Trains in Regional MARKAL Evelyn

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Example Application: Modeling Trains in Regional MARKAL Evelyn Wright & Dan Loughlin APB/APPCD/NRMRL/ORD/USEPA Presentation

Example Application: Modeling Trains in Regional MARKAL Evelyn Wright & Dan Loughlin APB/APPCD/NRMRL/ORD/USEPA Presentation to NESCAUM December 18 th, 2003

Regional Transportation: Trains Types of Demand

Regional Transportation: Trains Types of Demand

Regional Transportation: Trains Types of Demand Inter-city Trains

Regional Transportation: Trains Types of Demand Inter-city Trains

Regional Transportation: Trains Types of Demand Commuter Trains

Regional Transportation: Trains Types of Demand Commuter Trains

Regional Transportation: Trains Types of Demand Intra-City Transit

Regional Transportation: Trains Types of Demand Intra-City Transit

Regional Transportation: Trains Build Database Type Fuel Efficiency (bil-passmi/PJ) Cost ($bil/bilpass-mi) Lifespan (years) Demand(t)

Regional Transportation: Trains Build Database Type Fuel Efficiency (bil-passmi/PJ) Cost ($bil/bilpass-mi) Lifespan (years) Demand(t) (bil-passmi/yr) Light Duty Rail Electricity 0. 82 … … TA(t) Heavy Duty Rail Electricity 1. 09 … … TA(t) Commuter Rail Electricity 0. 98 … … TB(t) Diesel 0. 44 … … TB(t) Electricity 0. 66 … … TC(t) Diesel 0. 39 … … TC(t) Inter-city Rail

Regional Transportation Define RES Energy Technology Demand Inter-City Rail Diesel Inter-City Rail Electricity Electric

Regional Transportation Define RES Energy Technology Demand Inter-City Rail Diesel Inter-City Rail Electricity Electric TA Intercity Demand Commuter Rail Diesel Commuter Rail Electric Heavy Rail Light Rail TB Commuter Demand TC Intracity Demand

Regional Transportation What does the model do? Energy Technology Demand Inter-City Rail Diesel Inter-City

Regional Transportation What does the model do? Energy Technology Demand Inter-City Rail Diesel Inter-City Rail Electricity Electric TA Intercity Demand Commuter Rail Diesel Commuter Rail Electric Heavy Rail Light Rail TB Commuter Demand TC Intracity Demand

Regional Transportation: Trains Scenarios Base case: * technology choices (types of trains, investment cost,

Regional Transportation: Trains Scenarios Base case: * technology choices (types of trains, investment cost, etc. ) * fuel usage by type * fuel prices * emissions * ? local emissions ? – depends on detail * ? economic impacts ? – depends on linkage to econ model Construct scenarios to evaluate effects of: * technology changes and emergence of new technologies * changes in energy prices * subsidized ticket prices and/or infrastructure * additional capacity * changes in prices for other transportation modes * mode changes – depends on elasticities, travel demand

Regional Transportation: Trains Issues Competition Inter-city Rail: Competes with planes, buses, and autos Commuter

Regional Transportation: Trains Issues Competition Inter-city Rail: Competes with planes, buses, and autos Commuter Rail: Competes with buses, taxis, and autos Intra-city Rail: Competes with buses, taxis, and autos Could feed same demand pools. Use price elasticities to determine demand for each mode. Need info on purpose of auto, bus travel.

Regional Transportation: Trains Issues Time of day: (peak vs. off-peak) Rush hour Time Specify

Regional Transportation: Trains Issues Time of day: (peak vs. off-peak) Rush hour Time Specify peak and off-peak demand Provide peak capacities

Regional Transportation: Trains Issues Geographical Constraints * Limited capacity in existing lines * Limited

Regional Transportation: Trains Issues Geographical Constraints * Limited capacity in existing lines * Limited availability of land for new systems Place constraints in model representing capacity constraints

Regional Transportation: Trains Conclusions * Try simple representation first * Characterize -> what is

Regional Transportation: Trains Conclusions * Try simple representation first * Characterize -> what is missing -> does it matter? * If “yes”, Prioritize and refine * Level of detail required is a function of objectives -> be flexible, but -> define as early in the process as possible * Remember, /good/ modeling is inherently iterative