Franklin Gbologah, Yanzhi Ann Xu, Michael O. Rodgers, Randall Guensler

Demonstrating Bottom-Up Framework for Evaluating Energy and

Emission Performance of Various Electric Rail Transit Options

Overview

Existing frameworks for analyzing emission performance of

public transit systems utilize top-down approaches that can

provide useful information at the network level but are

often uninformative at the project level where the influence

of route and vehicle characteristics can significantly impact

emission profiles of candidate transit options.

This paper describes an alternative bottom-up

framework using second-by-second travel activity data to

estimate total power consumption and related emissions

for propulsion purposes with application to electric rail

transit systems.

The performance goals of the framework include

sensitivity to systems characteristics such as:

Passenger loading profiles

Speed profiles & track profiles

Ambient weather conditions

Fuel & vehicle technologies

The model was calibrated with data from Portland, OR and

is here used with activity data from Chicago, IL.

Developed Framework

Data

Travel Activity Data from Portland, OR

Travel activity data was obtained from the MAX Blue Line

Total of 47 stations

Covering about 32.5 miles

Travel Activity Data from Chicago, IL GPS speed and position data were collected on the “L”

Brown Line

Valid data obtained for a 8.2 mile/ 18 station segment of

the overall 11.4 mile/28 station route from Kimball to

Downtown Chicago

GPS speed and position data were collected on the “L”

Orange Line

Valid data obtained for a 9.1 mile/ 9 station segment of the

overall 12.5 mile/ 17 station line from Midway Airport to

Downtown Chicago

Other Data

The study relied on published data provided by the FTA in the

2011 National Transit Database with supplemental

information from third-parties as necessary.

Brown Line Data Collection Orange Line Data Collection

Instantaneous Rolling

Tractive Effort Module

Power

Recovery

Module

Starting Tractive Effort

Module

Data Reporting Module

Energy and Emission Analysis Module

Data Reporting Module

Receives required information about a specific trip or transit

service such as:

Station names, mileposts, and elevations

Weight of empty railcar, number of axles per car, number of

cars per train, passenger/seating capacity per car, HVAC

operation, power recovery range.

Ambient temperature, indication of dry, wet, snow/icy

Track infrastructure information such as track type and

condition

Second-by-second train speed

Instantaneous Rolling Tractive Effort Module

Computes the instantaneous energy requirements for the

moving train based on the unit moving resistance on level grade,

unit acceleration/deceleration resistance, hotel load, and grade

resistance.

𝑅 = 0.6 +20

𝑤𝑝+ 0.01𝑉2 +

𝐾𝑉22

𝑤𝑝𝑛𝑝+ 20 ∗ 𝜃 + 70

𝑉22 − 𝑉1

2

𝐿∗ γ

wp = weight per passenger rail car axle (tons)

V2, V1 = current & previous instantaneous speed of train (mph)

K = train drag coefficient

np = number of axles per passenger rail car

θ = positive track gradient at instantaneous location (%)

L = distance moved in a second (ft)

γ = empirical adjustment factor for post 1950 rail car design

R = unit resistance to moving train (lb/ton)

The components of the equation were developed by W. J. Davis.

The first four terms are often called the modified Davis Equation. This research is part of a larger research effort which developed a Public Transit

Greenhouse Gas Emissions Management Calculator for rail and bus transit systems.

wwww.alwaysodgen.com www.sacrt.com www.visualizenashua.com

School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA.

Corresponding author email: franklin.gbologah@gatech.edu

* Model’s estimate. ** Calculated from NTD 2011

Summary

This research was done in collaboration with Oak Ridge National Laboratory, under the

sponsorship of the Federal Transit Administration. Opinions expressed here are those of the

authors and not necessarily those of the Federal Transit Authority.

This paper provides a bottom-up framework using second-by-second

travel activity data to estimate energy and emissions performance of

rail transit systems.

Results show that:

the model’s power consumption estimates and derived estimates

from NTD are within 1 – 8 percent difference.

the power consumption per seat mile estimates are sensitive to

speed profiles of service lines. Observed maximums are 55 and 47

mph on Orange and Brown lines respectively, and in both peak and

off-peak the Orange line consumes about 7 percent more power per

seat mile.

the model’s power consumption estimates are sensitive to

differences in train configuration, e.g., peak period Orange and

Brown line configurations.

the framework accounts for the impacts of varying power generation

mixes in different regions, e.g., Chicago “L” system consumes about

27 – 35 percent more power per seat mile but it produces about 300

– 355 percent more emissions than Portland TriMet system.

kWh/Vehicle Mile kWh/Seat Mile

MAX Blue Line* All day 13.57 0.11

MAX Blue Line** All day 13.57 0.11

Brown Line*

Peak Period 41.32 0.14

Off-peak Period 25.67 0.13

Orange Line*

Peak Period 50.28 0.15

Off-peak Period 26.75 0.14

Avg. (Brown & Orange Lines)* 36.01 0.14

Avg. (All lines in “L” system)** 36.44 0.13

Starting Tractive Effort Module

Computes additional effort required to move from zero speed,

e.g. after alighting passengers. Considers five factors:

Grade resistance, Bearing resistance, Track resistance,

Weather resistance, Track condition

Power Recovery Module

For trains with regenerative braking capability, the analyst must

enter average recovery potential in data reporting module

Energy & Emission Analysis Module

Calculates the total electrical power consumed for propulsion

(including hotel load) and related emissions

CO2, CH4, N2O, CO, VOC, NOX, PM2.5, PM10 and SO2.

Emission rates obtained for all U.S. states from the most

recent version of GREET

Model Setup and Calibration

MAX Blue line is assumed to be representative of the entire

system because it is the longest of all the six routes and all

TriMet lines have similar operating characteristics

Calibrated adjustment factor (γ ) = 0.782.

Max Blue Line Chicago Orange

Line

Chicago Brown

Line

Empty car weight (tons) 54.5 27.15 27.15

# of axles per car 6 4 4

Train drag coefficient 0.07 0.07 0.07

Seats per car 64 49 49

Peak load % N/A

87.5 87.5

Off-peak load % 25.0 25.0

Avg. daily load % 43.0 45.0 45.0

# of cars in Peak 2 7 6

# of cars in Off-peak 2 4 4

Max. hotel load / car (kW) 25 25 25

Car HVAC level Normal Normal Normal

Weight / passenger (lbs) 150 150 150

Power recovery rate (%) - - -

Ambient temp. (F) 74 74 74

Weather condition Dry Dry Dry

Track type 115 lbs 115 lbs 115 lbs

Track condition

Good rail and

crossties

Good rail and

crossties

Good rail and

crossties

0

10

20

30

40

50

60

CO2 (kg) CO (g) VOC (g) NOX (g) PM2.5 (g) PM10 (g) SO2 (g)

Em

issio

ns p

er

veh

icle

mil

e

Estimated Emissions per Vehicle Mile

"L" Brown line "L" Orange line MAX Blue line

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

CO2 (kg) CO (g) VOC (g) NOX (g) PM2.5 (g) PM10 (g) SO2 (g)

Em

issio

ns p

er

seat

mil

e

Esitmated Emissions per Seat Mile

"L" Brown line "L"Orange line MAX Blue line

Model Setup Parameters

Results

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500

Sp

eed

(m

ph

)

Seconds of Operation

Speed Profile For Brown & Orange Lines

Brown Line Orange Line