environmental payback and tradeoffs in california high speed rail

Page S1 of S14

SUPPLEMENTARY INFORMATION for

High-speed Rail with Emerging Automobiles and Aircraft Can Reduce Environmental Impacts in California's Future

Authors:

Mikhail Chester † Assistant Professor, Civil, Environmental, and Sustainability Engineering Affiliate Faculty, School of Sustainability Arizona State University [email protected]

Arpad Horvath Professor, Civil and Environmental Engineering University of California, Berkeley [email protected]

† Author to whom correspondence should be addressed

Table of Contents:

S1 System Boundary ..................................................................................................................................................... S2 S2 High-speed Rail Electricity Propulsion Electricity Consumption ................................................................... S3 S3 Aircraft Operational Energy Consumption and Emissions ............................................................................. S4 S4 End-use Energy Consumption Results ................................................................................................................ S9 S5 Marginal Effects ..................................................................................................................................................... S10 S6 California Without and With HSR Transportation System Contrasts .......................................................... S11 S7 Existing Infrastructure Expansion Schedules ................................................................................................... S12 S8 Supplementary Information References ............................................................................................................ S13

Additional project background is available at: www.sustainable-transportation.com

mailto:[email protected]

Supplementary Information for: M Chester and A Horvath Page S2 of S14 High-speed Rail with Emerging Automobiles and Aircraft Can Reduce Environmental Impacts in California's Future

S1 System Boundary

An attributional LCI that compares transportation modes or consequential LCI that compares policy or

decision outcomes requires the establishment of a commensurate system boundary. A commensurate system

boundary ensures that equivalent life-cycle stages are compared so that results are meaningful. Each bullet in

Table S1 has been evaluated for energy inputs and air emission outputs.

Table S1 – Life-cycle Assessment System Boundary

Component Automobiles Rail Aircraft

Veh

icle

Co

mp

on

ents

Gro

up

ing

Active Operation Running

Cold start

Running (propulsion) Take off

Climb out

Cruise

Approach

Landing

Inactive Operation Idling Idling

Auxiliaries (heating, ventilation, air conditioning, and lighting)

Auxiliary Power Unit operation

Startup

Taxi out

Taxi in

Manufacturing (facility construction excluded)

Vehicle manufacturing

Engine manufacturing

Train manufacturing Aircraft manufacturing

Engine manufacturing

Maintenance Automobile maintenance

Tire replacement

Battery replacement

Train maintenance

Train cleaning

Flooring replacement

Aircraft maintenance

Engine maintenance

Insurance Vehicle liability Crew health and benefits

Train liability

Crew health and benefits

Aircraft liability

Infr

ast

ructu

re C

om

po

nen

ts G

roup

ing

Construction Roadway construction Station construction

Track construction

Airport construction

Runway/taxiway/tarmac construction

Operation Roadway lighting

Herbicide spraying

Roadway salting

Station lighting

Escalators

Train control

Station parking lighting

Station miscellaneous (e.g., other electrical equipment)

Runway lighting

Deicing fluid production

Ground Support Equipment operation

Maintenance Roadway maintenance is the result of heavy duty vehicles and thus not charged to automobiles [Huang 2004].

Station maintenance

Station reconstruction

Station cleaning

Track maintenance

Airport maintenance

Airport reconstruction

Runway/taxiway/tarmac maintenance

Parking Construction and Maintenance

Roadside, surface lot, and parking garage parking

Station parking Airport parking

Insurance Infrastructure benefits and liability (e.g., auto mechanics and construction workers)

Non-crew health insurance and benefits

Infrastructure liability insurance

Non-crew health and benefits

Infrastructure liability

Fu

el

Cycle

Co

mp

on

ents

Gro

up

ing

Gasoline, Jet A, and Electricity Production

Gasoline and diesel fuel refining and distribution (includes through fuel truck delivery stopping at fuel station. Service station construction and operation are excluded)

Raw fuel extraction and processing, electricity generation, transmission and distribution

Extraction, refining and distribution


S2 High-speed Rail Electricity Propulsion Electricity Consumption

Life-cycle inventory (LCI) results for a new HSR system will be highly sensitive to train propulsion electricity,

a factor that is uncertain and should be contextualized against systems in Europe and Japan. A large body of

literature exist characterizing HSR electricity consumption, often with the goal of evaluating operating costs

or greenhouse gas (GHG) emissions. A sample of this literature is shown in Table S2 with reported electricity

consumption normalized to kilowatt-hours per seat-kilometer (kWh/seat-km).

Table S2 – HSR Electricity Consumption Literature Survey

Source Figure S1 Code

Notes Electricity

kWh/seat-km

IFEU (2011) Α Deutsche Bahn, ICE, <200 km/hr 0.029

ATOC (2009) Β Shinkansen 700 Series, 300 km/hr 0.029

ATOC (2009) Γ AGV 300 km/hr, 14-car, max of 300 km/hr 0.033

ATOC (2009) Δ Virgin Class 390 Pendolino, 200 km/hr, 9 cars 0.033

IFEU (2011) Ε Deutsche Bahn ICE >200 km/hr 0.034

Kosinksi et al (2010) Ζ Shinkansen Nozomi 700N At 220 km/hr 0.037

ATOC (2009) Η TGV Duplex, 300 km/hr, 1090 seats 0.037

ATOC (2009) Θ TGV Reseau, 300 km/hr 0.039

Network Rail (2009) Ι AVE S103 Velaro, 300 km/hr 0.039

ATOC (2009) Κ Eurostar Class 373, 300 km/hr 0.041

Janic (2003) Λ French TGV, 250 km/hr 0.044

Andersson and Lukaszewicz (2006) Μ Type 73 Signatur, <210 km/hr, 4-car unit, 201 seats 0.045

van Wee et al (2003) Ν Hanze line (HZL), <260 km/hr 0.055

van Wee et al (2003) Ξ Zuider Zee line (ZZL), <260 km/hr 0.056

Janic (2003) Ο Deutsche Bahn ICE, 250 km/hr 0.058

Kumagi (2008) Π Shinkansen Nozomi 700N, 260-300 km/hr 0.062

van Wee et al (2003) Ρ Zuider Zee line (ZZL) Maglev Intercity, <400 km/hr 0.065

Kosinksi et al (2010) Σ Shinkansen Zero Series, 220 km/hr 0.072

van Wee et al (2003) Τ Zuider Zee line (ZZL) Maglev Metro, <400 km/hr 0.074

( indicates that the electricity consumption factor was used for future CAHSR results in the main manuscript)

The data reported in Table S2 captures a broad range of physical, environmental, and operating characteristics

that lead to a wide range (0.029 to 0.074 kWh/seat-km) of electricity propulsion values. The range in values is

the result of differing vehicle ages (e.g., Kosinski et al 2010 report two generations of Shinkansen 700 trains),

sizes, operating characteristics (e.g., speed), technology (e.g., magnetic levitation or overhead power supply),

and environment (e.g., elevation changes), to name a few. Figure S1 shows the electricity consumption factors

ordered from lowest to highest.


Figure S1 – HSR Electricity Consumption Literature Survey Comparison (kWh/seat-km)

The 0.029 kWh/seat-km factor for sub-200 km/hr and 0.034 km/hr factor for above 200 km/hr from IFEU

(2011) are used for future CAHSR trains producing the results reported in the main manuscript. This

electricity consumption is on the low end and represents a modern HSR train today. While future HSR trains

may offer greater propulsion efficiency, speculation on this factor is imprudent. However, the reporting of

life-cycle effects when trains are powered by a wind and solar mix provides a lower bound of what can be

expected as train efficiency improves.

S3 Aircraft Operational Energy Consumption and Emissions

Using the U.S. Federal Aviation Administration’s (FAA) Emission and Dispersion Modeling System (EDMS)

software [FAA 2010] and with assistance from Pratt and Whitney, near airport (startup, taxi out, takeoff,

climb out, approach, and taxi in) and cruise fuel use and emissions are determined for Boeing 737 legacy

models, the current Boeing 737-800, and a future Bombardier CS300ER. Cruise phase effects are not

rigorously reported to allow for detailed estimates for flights at different lengths, aircraft models, and engine

models. In general, aircraft emissions near airports are monitored to avoid human health impacts and help

improve local non-attainment standards. Previous air travel LCIs used cruise phase emissions estimates from

EEA (2006). A new approach was developed to allow for a more flexible parametric analysis including new

engine models and a California-corridor specific flight profile, and the effects on cruise phase fuel use and

emissions.

Engine emission indexes are combined with flight profiles and engine thrust factors to determine near airport

operations effects. The legacy Boeing 737 is modeled with two CFM56-3B-2 engines and the Boeing 737-800

with two CFM56-7B26/2 engines with the EDMS software [FAA 2010]. Table S3 and Table S4 detail the

time-in-phase and fuel and emission indexes for these two aircraft.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Α Β Γ Δ Ε Ζ Η Θ Ι Κ Λ Μ Ν Ξ Ο Π Ρ Σ Τ


The startup, taxi out, and taxi in phases can produce significant CO and VOC emissions [Wood et al 2008].

During startup, the fuel flow to the engines is initiated and the spark ignition system activated to establish a

flame. The engine reaches a stable temperature in 30 to 90 seconds at which point hydrocarbons and CO

emission indexes stabilize. Prior to ignition, fuel pushed through the combustor is unburned producing the

same VOC speciation as evaporative emissions. This speciation has a very different profile than VOCs

produced during combustion; they consist mostly of alkanes and are much less toxic. The taxi out and in CO

emission index of 30.1 g kg-1 is consistent with Figure 6 in Wood et al (2008) which shows CO at this level at

around 10% of rated engine thrust.

Table S3 – CFM56-3B-2 Engine Emission Indexes from EDMS for a Legacy Boeing 737

Step Mode Time (s) Fuel (kg/s) CO EI (g/kg) VOC EI (g/kg) NOx EI (g/kg) PM EI (g/kg)

Departure 1 Startup 60.000 0.005 - 994.786 - -

2 Taxi Out 1,140.000 0.131 30.100 2.013 4.100 0.154

3 Takeoff 4.912 1.243 0.900 0.477 19.399 0.150

4 Takeoff 4.912 1.237 0.900 0.477 19.399 0.150

5 Takeoff 4.912 1.229 0.900 0.477 19.399 0.150

6 Takeoff 4.912 1.221 0.900 0.477 19.399 0.150

7 Takeoff 4.912 1.211 0.900 0.477 19.399 0.150

8 Takeoff 4.912 1.200 0.900 0.477 19.399 0.150

9 Takeoff 4.912 1.188 0.900 0.477 19.399 0.150

10 Takeoff 4.912 1.175 0.900 0.477 19.399 0.150

11 Takeoff 4.912 1.161 0.900 0.477 19.399 0.150

12 Takeoff 1.135 1.152 0.900 0.048 19.401 0.150

13 Takeoff 1.353 1.151 0.901 0.048 19.406 0.150

14 Takeoff 1.607 1.149 0.902 0.048 19.411 0.150

15 Takeoff 2.025 1.147 0.903 0.048 19.418 0.150

16 Takeoff 2.713 1.145 0.905 0.048 19.427 0.150

17 Takeoff 4.013 1.141 0.907 0.048 19.439 0.150

18 Takeoff 7.106 1.135 0.911 0.048 19.457 0.150

19 Climb Out 3.358 1.097 0.913 0.048 19.471 0.138

20 Climb Out 6.885 1.058 0.915 0.049 19.478 0.139

21 Climb Out 6.885 1.050 0.917 0.049 19.487 0.139

22 Climb Out 4.569 1.043 0.919 0.049 19.495 0.139

23 Climb Out 9.523 1.036 0.923 0.049 19.511 0.139

24 Climb Out 19.194 1.019 0.933 0.049 19.544 0.139

Arrival 1 Approach 68.655 0.139 24.375 1.456 4.497 0.131

2 Approach 35.900 0.190 11.560 0.494 5.786 0.131

3 Approach 38.466 0.237 6.831 0.230 6.911 0.131

4 Approach 81.964 0.266 5.201 0.155 7.546 0.131

5 Approach 0.083 0.266 5.244 0.158 7.491 0.131

6 Taxi In 1.602 0.433 4.600 0.071 10.599 0.154

7 Taxi In 4.218 0.555 0.900 0.062 12.405 0.154

8 Taxi In 4.218 0.468 1.331 0.068 11.121 0.154

9 Taxi In 4.218 0.384 2.163 0.076 9.794 0.154

10 Taxi In 420.000 0.131 30.100 2.013 4.100 0.154

SOx emissions are introduced as a uniform 1.292 g kg-1 across all steps [FAA 2010].


Table S4 – CFM56-7B26/2 Engine Emission Indexes from EDMS for a Boeing 737-800

Step Mode Time (s) Fuel (kg/s) CO EI (g/kg) VOC EI (g/kg) NOx EI (g/kg) PM EI (g/kg)

Departure 1 Startup 60.000 0.005 0.000 994.786 0.000 0.000

2 Taxi Out 1,140.000 0.124 39.930 6.763 4.270 0.224

3 Takeoff 5.009 1.352 1.640 0.052 19.199 0.125

4 Takeoff 5.009 1.345 1.640 0.052 19.199 0.125

5 Takeoff 5.009 1.337 1.640 0.052 19.199 0.125

6 Takeoff 5.009 1.328 1.640 0.052 19.199 0.125

7 Takeoff 5.009 1.318 1.640 0.052 19.199 0.125

8 Takeoff 5.009 1.307 1.640 0.052 19.199 0.125

9 Takeoff 5.009 1.295 1.640 0.052 19.199 0.125

10 Takeoff 5.009 1.281 1.640 0.052 19.199 0.125

11 Takeoff 5.009 1.267 1.640 0.052 19.199 0.126

12 Takeoff 1.131 1.258 1.641 0.052 19.201 0.126

13 Takeoff 1.348 1.256 1.642 0.052 19.206 0.126

14 Takeoff 1.602 1.254 1.644 0.052 19.211 0.126

15 Takeoff 2.017 1.250 1.646 0.052 19.218 0.126

16 Takeoff 2.703 1.246 1.649 0.052 19.226 0.126

17 Takeoff 3.999 1.241 1.653 0.052 19.238 0.126

18 Takeoff 7.081 1.231 1.659 0.052 19.257 0.126

19 Takeoff 9.123 1.216 1.666 0.053 19.275 0.126

20 Takeoff 8.537 1.199 1.671 0.053 19.288 0.126

21 Takeoff 8.584 1.181 1.677 0.053 19.300 0.126

22 Takeoff 2.095 1.170 1.681 0.053 19.310 0.126

23 Climb Out 2.728 1.078 1.684 0.053 17.357 0.134

24 Climb Out 1.383 0.988 1.687 0.053 15.446 0.135

25 Climb Out 21.555 1.981 1.700 0.054 15.430 0.135

Arrival 1 Approach 12.688 0.045 41.623 7.050 4.305 0.964

2 Approach 1.321 0.046 41.557 7.039 4.304 0.964

3 Approach 0.409 0.199 33.544 6.309 5.619 0.964

4 Approach 26.615 0.350 22.961 4.283 7.630 0.964

5 Approach 9.442 0.350 23.057 4.324 7.612 0.964

6 Approach 18.886 0.350 23.126 4.354 7.597 0.964

7 Approach 2.692 0.350 23.179 4.377 7.586 0.964

8 Approach 16.188 0.350 23.232 4.399 7.576 0.964

9 Approach 28.324 0.350 23.347 4.449 7.552 0.964

10 Approach 28.310 0.350 23.490 4.512 7.522 0.964

11 Approach 18.864 0.349 23.614 4.568 7.496 0.964

12 Approach 18.856 0.349 23.710 4.608 7.475 0.964

13 Approach 18.855 0.349 23.803 4.650 7.454 0.964

14 Approach 9.425 0.349 23.880 4.683 7.438 0.964

15 Approach 8.624 0.349 23.928 4.705 7.427 0.964

16 Approach 3.996 0.349 23.929 4.709 7.422 0.964

17 Approach 0.082 0.349 23.910 4.703 7.423 0.964

18 Taxi In 1.731 0.494 9.860 1.059 9.318 0.224

19 Taxi In 4.003 0.595 6.135 0.477 10.525 0.224

20 Taxi In 4.003 0.512 9.065 0.920 9.531 0.224

21 Taxi In 4.003 0.431 14.166 7.949 8.490 0.224

22 Taxi In 420.000 0.124 39.930 6.763 4.270 0.224

Cruise phase fuel consumption and emissions are determined from rated power use relative to the climb out

stage. The rated power at cruise (16%) and climb out (85%) are a percentage of fuel flow and are based on

Pratt and Whitney (2011).


Total emissions for a legacy Boeing 737 and a Boeing 737-800 are determined by Equation 1:

where N = Number of Engines TIM = Time in Mode (sec) F = Fuel Index (kg sec-1) EI = Emission Index (g kg-1)

Equation 1

For an average U.S. Boeing 737 flight in 2009, the total trip distance was 1,400 km (840 mi) and air time 120

min, and for an average CA flight 570 km and 58 min [BTS 2011], producing the fuel and emissions profiles

in Table S5 and Table S6.

Table S5 – Legacy Boeing 737 U.S. Flight Fuel Consumption and Emissions

Phase Time (s) Fuel (kg) CO (g) VOC (g) NOx (g) PM (g) SOx (g)

Departure Startup 60.00 0.60

594.25 0.77

Taxi Out 1140.00 298.45 8983.41 600.74 1223.56 45.99 385.60

Takeoff 64.16 152.29 137.36 53.13 2955.93 22.86 196.76

Climb Out 50.41 104.77 96.76 5.13 2044.24 14.53 135.36

Cruise Cruise (U.S.) 6812.42 2664.97 2369.02 125.65 50041.89 355.63 3313.56

Cruise Cruise (CA) 3144.57 1230.13 1093.53 58.00 23099.02 164.16 1529.52

Approach Approach 225.07 94.70 976.27 45.61 620.61 12.44 122.35

Taxi In 434.26 123.21 3332.54 222.23 599.21 18.99 159.19

Validation Calculated LTO

774.03 13526.33 1521.09 7443.55 114.81 1000.05

Validation ICAO (2007) LTO

780.00 13030.00 840.00 7190.00

780.00

Following a similar methodology, the International Civil Aviation Organization (ICAO) reports landing-take

off (LTO) emissions for various aircraft types [ICAO 2007]. The validation rows show that the approach

used in Equation 1 produces accurate flight fuel consumption estimates and emissions.

Table S6 – Boeing 737-800 U.S. Flight Fuel Consumption and Emissions



637.22 0.83

Taxi Out 1140.00 283.40 11316.32 1916.72 1210.05 63.62 366.16

Takeoff 93.30 235.75 389.38 12.29 4533.98 29.59 304.59

Climb Out 25.67 94.01 159.65 5.04 1461.92 12.65 121.46

Cruise Cruise (U.S.) 6809.52 4694.79 4351.29 137.29 40084.03 344.94 3312.15

Cruise (CA) 3141.67 2166.01 2007.53 63.34 18493.33 159.14 1528.11


Taxi In 433.74 118.43 4301.19 741.41 580.18 26.58 153.01

Validation Calculated LTO

879.93 19651.64 3978.85 8894.46 274.88 1136.87

Validation ICAO (2007) LTO

880.00 7070.00 720.00 12300.00

880.00


For future aircraft emissions, results in Table S6 are joined with reported improvements by Pratt and Whitney

for their developing PW1524G engines. These engines are expected to reduce fuel consumption and CO2

emissions by 20%, and NOx emissions by 50% [Bombardier 2011]. Based on preliminary testing, they are

expected to generate CO emissions profiles that are 36% of Committee on Aviation Environmental

Protection series 6 (CAEP6) standards, VOC at 4%, NOx at 42%, and PM at 50% [Hoke 2011]. These

profiles are compared against the Boeing 737-800’s CFM56-7B26/2 engines emissions with CO at 75% of

CAEP6 standards, VOCs at 73%, NOx at 69%, and PM at 3% [ICAO 2010]. Applying the PW1524G

emissions profile percentages against the CFM56-7B26/2’s flight results in Table S6 produces the results for a

future Bombardier CS300ER (Table S7).

Table S7 – Bombardier CS300ER U.S. Flight Fuel Consumption and Emissions



35.06 0.66

Taxi Out 1140.00 226.72 5460.96 105.46 739.77 1026.09 292.93

Takeoff 93.30 188.60 187.91 0.68 2771.87 477.33 243.67

Climb Out 25.67 75.21 77.04 0.28 893.75 204.05 97.16

Cruise Cruise (U.S.) 6809.52 3755.83 2099.82 7.55 24505.52 5563.56 2649.72

Cruise (CA) 3141.67 1732.81 968.78 3.49 11305.97 2566.83 1222.49


Taxi In 433.74 94.74 2075.64 40.79 354.69 428.77 122.40

CO2 emissions are based on 3.1 kg CO2 per kg fuel and a heating value of 46.9 MJ per kg fuel.


S4 End-use Energy Consumption Results

Results for end-use energy consumption are shown in Figure S2 and reveal similar dominating life-cycle

components to GHG emissions. Energy consumption is dominated by vehicle propulsion (fuel cycle for

CAHSR and vehicle operation for automobiles and aircraft) but show significant increases when life cycle

components are included. Steel and plastic use dominates automobile vehicle manufacturing and maintenance

is largely the result of supply chain electricity. Heavy use of concrete dominates CAHSR infrastructure

construction effects. Refineries, oil and gas extraction activities, and electricity use in supply chain activities

are primary contributors to non-propulsion fuel-cycle effects.

Figure S2 – End-use Energy Consumption Results in MJ per PKT


S5 Marginal Effects

Marginal life-cycle results are important for understanding consequential effects. Past passenger

transportation LCIs [Chester and Horvath 2010, Chester and Horvath 2009, Chester 2008] have reported

results at long-term averages. Here we examine the marginal effects of the decision to travel by a particular

mode, normalized per vehicle-kilometer-traveled (VKT). We distinguish between short-run marginal, mid-run

marginal, and long-run average to capture relevant timescales for life-cycle effects. Results for a 670 seat

CAHSR train using WECC-RPS electricity, Boeing 737-800, and 35 mpg Sedan (representative future

vehicles) are shown in Figure S3.

Figure S3 – Average and Marginal GHG Emissions in g CO2e/VKT

Life-cycle Grouping Vehicle Operation

Short, Mid, Long Vehicle Manufacturing

Mid, Long Vehicle Maintenance

Mid, Long Vehicle Insurance

Mid, Long Infrastructure Construction

Long Infrastructure Operation

Long Infrastructure Maintenance

Mid, Long Infrastructure Parking

Long Infrastructure Insurance

Long Fuel Cycle

Mid, Long Life-cycle Grouping Legend

Short, Mid, and Long Mid and Long Long

The short-run is defined as the instance the trip occurs. In the short-run, the decision to travel on a mode

produces no effects on HSR or the Boeing 737-800 because the vehicle trip happens anyways. For the

automobile, assuming a single occupancy automobile, only vehicle operation effects occur in the short-run.

Mid-run marginal effects capture life-cycle components directly affected by vehicle operation both in the

immediate and sub-decadal timeframe. For mid-run marginal, the decision to travel on a mode produces

vehicle manufacturing, vehicle maintenance, vehicle insurance, infrastructure maintenance, and fuel cycle

effects, in addition to vehicle operation. These effects occur independently of decisions en masse that choose

that mode. Lastly, long-run average results (those reported and discussed in the main manuscript) add


infrastructure construction, operation, parking, and insurance effects to represent the total life-cycle effects.

To reduce infrastructure long-run effects for any mode, a large-scale critical mass of travelers must choose

other modes. For example, to avoid highway construction effects for the automobile, large shifts would have

to occur to HSR or aircraft so that future roadway construction or expansion is avoided.

S6 California Without and With HSR Transportation System Contrasts

The consequential assessment compares 2040 without and with CAHSR. The critical comparison parameters

are shown in Table S8. Note that only the differences (or displacement of effects) are considered in the

presentation as net changes of transportation impacts.

Table S8 – Consequential Assessment Operation/Propulsion and Life-cycle Scenario Differences for Phase 1 in 2040

Without HSR With HSR Auto Operation 481 billion VKT [PB 2012 BCA] 475 billion VKT [PB 2012 BCA] Auto Life-cycle

Construction and maintenance of 1,000 freeway lane kilometers [PB 2011 EC]. Section S7 details the rehabilitation schedules.

Vehicle (manufacturing and maintenance), infrastructure (operation and parking), and crude oil extraction, refining to gasoline, and distribution.

Roadway expansion is prorated with the HSR ridership uncertainty assessment. For example, in the manuscript Figure 4, the HSR 50% ridership uncertainty stratum corresponds to 50% of lane kilometers constructed (i.e., 1,250).

Vehicle (manufacturing and maintenance), infrastructure (operation and parking), and crude oil extraction, refining to gasoline, and distribution.

Air Operation 33 million trips [PB 2011 BCA] 5.1 to 5.9 million trips displaced [PB 2012 BCA].

Using average flight occupancy and distance, it is estimated that this displacement results in a reduction of 27 million aircraft VKT.

Air Life-cycle Construction and maintenance of 3,600 meters of runways [PB 2011 EC]. Taxiways, tarmac, and gate expansion are also included based Chester and Horvath (2009). Section S7 details the rehabilitation schedules.

Vehicle (manufacturing and maintenance), infrastructure (operation and parking), and crude oil extraction, refining to jet fuel, and distribution.

Runways (10,000 meters), taxiways, and tarmacs are prorated with the HSR ridership uncertainty assessment following the approach described for automobiles.

Vehicle (manufacturing and maintenance), infrastructure (operation and parking), and crude oil extraction, refining to jet fuel, and distribution.

HSR Propulsion Several forecasts are considered [PB 2012 O&M]: ▫ High: 41 million VKT ▫ Medium: 34 million VKT ▫ Low: 27 million VKT

Uncertainty analysis is performed on the High forecast by consecutively removing 10% of HSR VKT and corresponding riders and shifting them to autos and aircraft (manuscript Figure 4).

HSR Life-cycle Vehicle (manufacturing and maintenance), infrastructure (operation and parking), and electricity production primary fuel extraction and processing.


S7 Existing Infrastructure Expansion Schedules

In the decision to not build California High-speed Rail (CAHSR), highways and airports must be expanded to

meet forecasted travel demand growth, and this expansion will not occur instantaneously. The CAHSR

Authority estimates that an additional 3,700 freeway lane kilometers and 13,000 m of runways will be needed

(with associated taxiways and tarmacs) [CAHSRA 2012]. Given the 20 year and 50 year wearing course and

subbase lifetimes for these paved surfaces, and the assumptions that 1) the expansion starts 10 years after it is

decided not to construct high-speed rail (HSR), and 2) that expansion occurs over 30 years, a construction

schedules is produced (Table S9).

Table S9 – Construction and Reconstruction Schedule for Asphalt and Concrete Road and Air Infrastructure Expansion

Axis Text First 3rd

Wearing Course Second 3rd

Wearing Course Third 3rd

Wearing Course First 3rd Subbase

Second 3rd Subbase

Third 3rd Subbase

D1

D2

D3

D4

D5

D6

D7

D8

D9

D10

( = Initial Construction, = Reconstruction)

The construction and reconstruction scheduled activities in Table S9 are used to determine the consequential

avoided effects of the decision to implement HSR.


S8 Supplementary Information References

[Andersson and Lukaszewicz 2006, Andersson and Lukaszewicz (2006)]

Andersson E and Lukaszewicz P 2006 Energy Consumption and Related Air Pollution for Scandinavian Electric Passenger Trains KTH Royal Institute of Technology Report KTH/AVE 2006:46 (Stockholm, Sweden). [ATOC 2009, ATOC (2009)]

Association of Train Operating Companies (ATOC) 2009 Energy Consumption and CO2 Impacts of High Speed Rail: ATOC Analysis for Greengauge 21 (London, United Kingdom). [Bombardier 2011, Bombardier (2011)]

Bombardier 2011 Change is in the Air (available online at http://www.cseries.com/). [BTS 2011, BTS (2011)]

Bureau of Transportation Statistics (BTS) 2011 Air Carrier Statistics (Form 41 Traffic) Tables T100 and P52 U.S. Department of Transportation (Washington, DC, available online at http://www.transtats.bts.gov/). [CAHSRA 2012, CAHSRA (2012)]

California High-speed Rail Authority (CAHSRA) April 2, 2012 California High-speed Rail Program Draft Revised Business Plan (Sacramento, CA). [CAHSRA 2011, CAHSRA (2011)]

California High-speed Rail Authority (CAHSRA) October 2011 California High-speed Rail Benefit-Cost Analysis (BCA) (Sacramento, CA). [Chester and Horvath 2011, Chester and Horvath (2011)]

Chester M V and Horvath A 2011 Vehicle Manufacturing Futures in Transportation Life-cycle Assessment University of California, Berkeley Institute of Transportation Studies Research Report #UCB-ITS-RR-2011-3 (available online at escholarship.org/uc/item/1qp3f0vc). [Chester and Horvath 2010, Chester and Horvath (2010)]

Chester M V and Horvath A 2010 Life-cycle Assessment of High-speed Rail: the Case of California Environmental Research Letters 5(1) (doi:10.1088/1748-9326/5/1/014003). [Chester and Horvath 2009, Chester and Horvath (2009)]

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environmental payback and tradeoffs in california high speed rail

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