Energy Implications of High-Speed Passenger Transportation: Examining Aviation, High-Speed Rail, and their Climate Impacts

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1 Energy Implications of High-Speed Passenger Transportation: Examining Aviation, High-Speed Rail, and their Climate Impacts Regina Clewlow, PhD Candidate Engineering Systems Division Massachusetts Institute of Technology Committee: J. Sussman (Chair), H. Balakrishnan, M. Webster Behavior, Energy, and Climate Change Conference Washington, DC November 30, 2011

2 The Increasing Impact of High-Speed Transportation Trend towards faster modes of transportation with GDP growth (Schafer, 2000). In the U.S., aviation is the dominant highspeed mode. U.S. Aviation Emissions Under Climate Policies Under business-as-usual, global aviation emissions anticipated to grow by 300% by 2050 (IEA, 2008). Climate policy analysis suggests that reductions in the aviation sector will be difficult to achieve (Winchester et al, 2011). CO 2 (billion kg) Business as Usual Most Stringent Policy Case 200 Economic and Environmental Effects of Cap-and-Trade Policies in Aviation, Joint University Program (JUP) Winter Progress Meeting, Federal Aviation Administration (FAA) Technical Center, Atlantic City, NJ, January

3 Broad Research Overview Europe Empirical analysis of systemwide air traffic. Impacts of airrail connectivity. U.S. Scenario analysis of potential impacts of climate policy on high-speed transport. China Experimental survey design and analysis of passenger preferences for intercity travel. 3

4 The European Case: Key Questions How has HSR impacted air traffic demand? How has HSR impacted total aviation system demand? How does air-rail connectivity impact demand? Air Traffic Decline (%) Air Traffic Decline vs. Rail Journey Time 150% 100% 50% 0% % -100% -150% -200% Rail Journey Time 4

5 The European Case: An Econometric Analysis Data: air traffic for 86 origindestination pairs, Model structure: Aviation Demand = α + β X + δ Rail Travel Time + ε Key Variables Dimension Aviation demand Price/ fares Income Population Distance Rail competition Variable Air traffic Jet fuel Household income Density Distance Rail travel time Key Findings: Average reduction of 3% per year on short-haul routes. Rail travel time improvements significantly impact shorthaul air traffic (coefficient estimate of 4.588). Density. Cities with higher densities experience greater reductions. Jet fuel price has a significant negative affect (elasticity range: to -1.13). 5

6 Hundred thousand tons CO2 equiv The European Case: Analysis of Systemwide Air Traffic Aviation CO 2 Emission Equivalents of Flights Departing Major European Airports Key Findings: Medium-haul markets have grown significantly, fueled by expansion of lowcost carrier service. Airlines maintain certain levels of frequency in the short-haul markets to feed long-haul traffic. Emissions savings from short-haul traffic reductions are negated by significant growth in medium- and long-haul traffic Year International traffic EU traffic National traffic 6

7 Future Work: A Climate Policy Analysis of the U.S. Case Climate Policies Fuel Prices Air Fares HSR Investment Travel Times Electricity Prices Rail Fares Mode Choice Electricity Mix GDP Aggregate Demand Baseline Aggregate Demand Aviation Demand HSR Demand Emissions 7

8 Thank You! Regina Clewlow PhD Candidate, ESD, MIT

9 Back-Up Slides Back-up slides

10 Europe: Paris CDG and ORY Air Passenger Capacity and Traffic Annual Passengers 1,200,000 1,000, , , , ,000 (a) Annual Passengers: Orly Annual Passengers (c) Annual Passengers: Charles de Gaulle 600, , , , , , Annual Flights Paris Orly - Bordeaux Paris Orly - Lyon Saint Exupery Paris Orly - Montpellier Paris Orly - Strasbourg (b) O-D Flights: Orly 10,000 8,000 6,000 4,000 2, Paris Orly - Bordeaux Paris Orly - Lyon Saint Exupery Paris Orly - Montpellier Paris Orly - Strasbourg Annual Flights Paris CDG - Bordeaux Paris CDG - Lyon Saint Exupery Paris CDG - Montpellier Paris CDG - Strasbourg Paris CDG - Nantes (d) O-D Flights: Charles de Gaulle 6,000 5,000 4,000 3,000 2,000 1, Paris CDG - Bordeaux Paris CDG - Lyon Saint Exupery Paris CDG - Montpellier Paris CDG - Strasbourg Paris CDG - Nantes B1

11 The Chinese Case: An Overview Air passenger travel increased at a rate of 16% per year between 1978 and 2009, and is projected to continue to increase at a rate of 12% (Civil Aviation Administration of China). China now has the world's longest high-speed rail network with about 6,012 mi of track in service as of June New Beijing-Shanghai highspeed rail corridor was opened on June 30, Conducted an intercept survey at Beijing and Shanghai airports and train stations in July/August B2

12 The Chinese Case: Survey Design and Data Collection Household Characteristics Household income Home city, neighborhood (or zip code?) Age Household Characteristics (in the context of a trip) Trip purpose Number of travelers Frequency of travel on this corridor (how many trips per year) Travel Characteristics Line haul time (station to station, airport to airport, terminal to terminal) Access/ egress time (home to station/airport/terminal) Frequency Fare (by class) Intercept survey design: Demographic data (age, income, etc.) Current choice attributes (# of bags, trip purpose, etc.) Hypothetical choice data: 12 choice sets in block of 4 questions. Data collection: Intercept surveys collected at: Beijing Airport Beijing South Rail Station Beijing Rail Station Shanghai Hongqiao Airport Shanghai Hongqiao Station July 22 August 4, rail surveys airport surveys 565 total surveys B3

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