This document summarizes a study that estimates future greenhouse gas emissions from urban travel in three Indian cities - Ahmedabad, Mumbai, and Surat - under various policy scenarios. The researchers developed bottom-up models to forecast travel activity and mode share out to 2040 based on population and income growth as well as different policy approaches. Their analysis found that emissions could be 6-10 times higher than current levels by 2040 under an "automobility" scenario but only 2-4 times higher under a "sustainable transport" scenario that prioritizes public transit, walking and cycling. The scenarios demonstrate the large influence that transport and land use policies can have on future emissions levels at the city scale.

1. Urban Mobility Forecasts:
Emissions Scenarios for Three Indian Cities
January 11, 2010 TRB Annual Meeting
Lisa Rayle Madhav Pai
Graduate Student Technical Director - India
Dept. Urban Studies & Planning EMBARQ, WRI Center for
MIT Sustainable Transport
lrayle@mit.edu mpai@wri.org 1

2. 2

3. 3

4. Overview
• Magnitude of future emissions is very
uncertain
• Purpose is to illustrate how transport and
land use planning policies could influence
GHG emissions at the city level
• Estimates future emissions from urban travel
under various policy scenarios for
Ahmedabad, Mumbai, and Surat
• Uses newly available household travel data
4

5. Existing research on future transport
emissions in India
• Studies of national level (Schipper et al.
2009, Singh 2006)
• City-level studies based on correlations
with population and income growth (Bose
& Nesamani 2000), vehicle numbers (Das
& Parikh 2004), travel characteristics
(Fabian & Gota 2009).
• Very few city-level studies based on travel
behavior.
5

6. City Characteristics
Mumbai Ahmedabad Surat
Population 17.7 million 5.4 million 2.4 million
(2001)
Decadal growth 32% 30% 62%
rate
Urban growth • Established • Fifth largest city in • Huge recent
major metropolitan India; typical of growth; high in-
area. large cities. migration rate.
• Growth • Growth lower than • Typical of “now
continues despite previous decades, exploding” cities.
space limitations. but still significant.
6

7. Travel Behavior Characteristics
Mumbai Ahmedabade Suratf
Average trip length - motorized
(km) 12.4c 14.4 8.5
Average trip length - non-
motorized (km) 2b 2.3 3.6
Mode split (% of total trips)
Walk 27d 37.6 42
Bicycle 6 17.6 13.4
Auto-rickshaw 6 8.3 10.8
Bus 26 8.4 2.3
Train 20 0.3 0.1
Motorcycle 10 25.3 28.4
Private car 5 2.48 2.6
Sources: a(9); b(11); c(10); dMode split data for Mumbai based on (9) and (11); 7 (6); f(
e

8. Approach
“Bottom-up” model to estimate emissions
Focus on amount of travel and mode share – factors that can be
influenced by transport and land use policy
Travel activity f (trip frequency, trip length,
vehicle occupancy, population)
GHG
Emissions Mode share f (relative travel cost)
Emissions factor f (energy consumption, vehicle
type, fuel mix)
8

9. Sources of travel data
Surat 1988, household surveys - Central Road Research
2004 Institute (CRRI), reported in Surat
Comprehensive Mobility Plan
2005 Household survey - Consulting Engineering
Services Pvt. Ltd.
Ahmedabad 2000 household travel survey, referenced in
Ahmedabad BRT Plan Report
Mumbai 2005 Mumbai Comprehensive Development Plan
1993 Mumbai Metropolitan Regional Development
Authority
2003- World Bank-funded household survey
2004 conducted in 2003 and 2004
9

10. Scenario 1
Automobility
Ubiquity
• increased household wealth, widespread
automobile ownership
• more road space devoted to cars
• investment in public transport is low priority
• greater car travel at expense of other modes
• extreme congestion, but alternatives to driving
unattractive
10

11. Scenario 2
Two-Wheeler
World
• increased household wealth
• policies to encourage small vehicles (e.g.
designation of road space, economic incentives)
• investment in public transport is low priority
• two-wheel vehicles dominate
11

12. Scenario 3
Sustainable Urban
Transport
• increased household wealth
• policies prioritize public transport, walking, and
cycling
– investment in public transit
– street design promotes non-motorized modes
• coordinated land use planning
• increase in transit ridership, stabilization of
motorized share
12

13. Assumed mode share for each scenario,
2040 – Surat
Mode Share (% of total trips)
Two- Sustainable
Automobility
Mode Current Wheeler Urban
Ubiquity
World Transport
Walk 42.0 22 18 20
Bicycle 13.4 6 2 15
Auto-rickshaw 10.8 8 5 5
Motorcycle 28.4 12 50 8
Bus 2.3 10 10 45
Train 0.1 0 0 0
Private car 2.6 42 15 7
13

14. Methodology: travel activity
Trip rate for
workers
Trip rate for Daily trip
nonworkers rate Daily passenger
trips
Workforce Population
participation Daily travel
rate (pass-km/day)
Trip Daily travel
Avg. trip
length-city (veh-km/day)
length
area ratio
Population Vehicle
City size
Population occupancy
density
Mode split
14

15. Methodology: travel activity
Historical and projected population growth - Surat
Decadal
Growth
Year Rate
1951 -
1961 29%
1971 64%
1981 65%
1991 93%
2001 62%
2011 63%
2021 50%
2031 40%
2041 30%
15

16. Methodology: travel activity
Trip frequency for selected cities and countries
Average Per
Capita Daily
Location Year Trips
Delhia 1969 0.49
Delhia 1981 0.72
Mumbaib 1991 0.95
Mumbaic 2000 1.67
Suratd 1988 1.02
Suratd 2004 1.31
International
U.S.e 1995 3.8
U.K.e 1997 2.9
Singaporeg 1991 2
Norwayg 1992 3
Sources: a(13); b Netherlandsg
c d e f
(10); (11); (8); (14); (15); g(16). 1995 3.5 16

17. Methodology: travel activity
Trip length
• Have trip length data by mode, but no historical data
• Base future trip length estimates on city size
• Suppose that density is given by scenarios. (constant
under Two-Wheeler and Sustainability; somewhat lower
under Automobility)
• Assume current relationship between city radius and
average trip length remains
• Limitations to this estimate (cities will become more
polycentric), but it gives a decent approximation.
17

18. Emission Factors for Current Indian Vehicles
as Estimated from Three Studies
Vehicle Type Emission Factor
(g CO2/km)
Motorcycle (2-stroke) 45.2
Motorcycle (4-stroke) 34.6
Auto-rickshaw (2-stroke) 87.2
Auto-rickshaw (4-stroke) 85.6
Petrol car 259.9
Diesel car 286.2
Diesel bus 704.8
Train (metro) 1541
Train (suburban rail) 1063
Sources: a Bose & Nesamani (2009); bMittal & Sharma (2006); cIyer (2006)
18

19. Projected Emission Factors for Vehicles in
India
*actual analysis distinguishes between 2-
and 4-stroke
19

20. Results: Estimated Travel Activity and
CO2 Emissions
Sustainable
Current Automobility Two-Wheeler Transport
2005 2021 2041 2021 2041 2021 2041
Total Daily Trips (millions)
Mumbai 29.6 65.4 146.9 65.4 146.9 65.4 146.9
Ahmedabad 5.6 14.9 39.8 14.9 39.8 14.9 39.8
3.2 10.9 32.6 10.9 32.6 10.9 32.6
Total Emissions (million tons CO2/year)
Mumbai 2.33 14.89 49.12 6.08 15.20 5.36 10.26
Ahmedabad 0.33 3.49 12.32 1.56 4.19 0.93 1.97
0.15 1.56 9.52 0.93 3.62 0.60 1.92
Total Per Capita Emissions (kg CO2/person/year)
Mumbai 132 490 1011 200 313 176 211
Ahmedabad 61 397 933 178 317 106 149
63 262 879 156 334 101 177
Ratio to 2005 emissions
Mumbai 6.4 21.1 2.6 6.5 2.3 4.4
Ahmedabad 10.6 37.4 4.8 12.7 2.8 6.0
10.2 62.3 6.1 23.6 3.9 12.6
20

21. Growth in population and total daily
trips for Surat, 2005-2040
Population
21

22. Annual CO2 emissions for Surat
22

23. Per capita emissions: current and under
scenarios for 2040
23

24. Estimated 2040 emissions as a ratio to
2005 levels
24

25. Percent of total emissions for each
mode - Surat
25

26. Limitations and sources of uncertainty
• Lack of historical data on trip length and trip
frequency
– forecasts estimated based on demographic
trends and assumptions about city form
– Forecasts validated against data from other
countries, but questions about applicability
– Time, congestion constraints could slow growth in
travel distances
• Uncertainty in vehicle technology
• Unclear when and whether urban populations
will stabilize – how big is too big?
26

27. Conclusions
• Differences between scenarios reflect great
deal of uncertainty, but also opportunity.
• Scenarios show importance of providing good
public transport and promoting more
sustainable modes, while discouraging
automobile travel.
– Cities taking some steps: e.g. BRT in Ahmedabad
and Surat, metro in Mumbai
• Land use and street design policies also
important to prevent “worst case” scenario
• Need for better data on travel behavior
27

28. Thank you!
Questions?
Contact:
Lisa Rayle
lrayle@mit.edu
Madhav Pai
mpai@wri.org
28

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