Sustainable Transport Saves Lives: Opportunities and Challenges for Urban India (Part 1)

Sustainable Transport Saves Lives

Challenges and Opportunities for

Urban India

Darío Hidalgo, PhD

Director of Research and Practice

EMBARQ, The WRI Center for Sustainable Transport

Urban Mobility India

Delhi, December 3-5 2010

Principles

• Most premature

deaths are

preventable and

predictable

• Transport creates

health risk factors at

three levels:

– Emission of Air

Pollutants

– Road Safety

– Physical Activity

Transport is related to 5 of the 12 leading

causes of premature death and disability

6.6

5.9

5.8

4.5

4.1

3.9

3.3

3.0

2.6

2.4

1.9

1.8

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

1. Perinatal conditions

2. Lower respiratory infections

3. HIV/AIDS

4. Unipolar depressive disorders

5. Diarrhoeal diseases

6. Ischaemic heart disease

7. Cardiovascular disease

8. Malaria

9. Road traffic injuries

10. Tuberculosis

11. Chronic obstructive pulmonary disease

12. Congenital anomalies

Proportion of Total (%)

12 Leading Causes of DALYs by WHO, 2002All Member States

So

urc

e: W

HO

Glo

ba

l B

urd

en

of

Dis

ea

se

pro

ject,

20

02

DALY: Disability-adjusted life year. A health-gap measure that combines information on the number of

years lost from premature death with the loss of health from disability

Transport sector traditional approaches do not

help health, nor other aspects of sustainability

Predict (auto traffic) and

provide (road capacity)

approach has resulted in

auto dependency

Developing countries have the opportunity to follow a

sustainable path through alternative transport solutions

Sao Paulo

Guayaquil

ManilaSantiago

http://www.embarq.org/en/india-transport-indicators












Sustainable Transport ASI Framework

ST Measures

Avoid unnecessary

motor vehicle travel

(number and length

of the trips)

•Planning for denser, mix use

(TOD)

• Information technology

(telecommute)


ST Measures

Shift trips to

efficient and safer

(slower) modes

•Active (NMT) and Public

Transport

•Traffic Demand Management


ST Measures

Improve vehicles,

facilities, operations

•Fuel efficiency and alternative

energy

•Managed operations (rules and

enforcement)

•Safer vehicles (in and out)

•Forgiving infrastructure and

operations design

Sustainable Transport Reduces Risk Factors

ST Measures Health Impacts

Avoid unnecessary

motor vehicle travel

(number and length

of the trips)

•Planning for denser, mix use

(TOD)

• Information technology

(telecommute)

•Less pollutant

emissions (better air

quality)

•Reduced number

and severity of

crashes (less road

injuries and deaths)

• Increased physical

activity (ped & bike

trips: reduced

obesity)

Shift trips to

efficient and safer

(slower) modes

•Active (NMT) and Public

Transport

•Traffic Demand Management

Improve vehicles,

facilities, operations

•Fuel efficiency and alternative

energy

•Managed operations (rules and

enforcement)

•Safer vehicles (in and out)

•Forgiving infrastructure and

operations design

Challenges for ASI

Sustainable Transport

• Population Growth

• Motorization

• Inertia of ―business-as-

usual‖ solutions

• Lack of Resources

– Financial

– Human Capital

Urbanization is happening quickly

Source: United Nations Population Division, World Urbanization

Prospects, The 2007 Revision

India urban population will surpass Latin America and

the Caribbean by 2030

21

5,7

47

28

9,4

38

36

6,8

58

47

2,5

61

61

1,4

07

30

1,6

46

39

4,1

68

47

1,2

48

54

2,8

75

60

3,4

57

26%

28%

30%

34%

41%

71%

75%

79%

82%

85%

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

1990 2000 2010 2020 2030

Urb

an P

op

ula

tio

n (T

ho

usa

nd

s)

India Urban 2.6% per year LAC Urban 1.7% per year

Source: United Nations Population Division, World

Urbanization Prospects, The 2007 Revision

Motorization grows with economic growth

Source: Lee Schipper, University of California, Berkeley, 2009

Not to the same

level in every

country

Auto use is not correlated with economic growth

Source: INDICATORS OF TRANSPORT EFFICIENCY IN 37 GLOBAL CITIES, Jeff Kenworthy, Felix Laube, Peter Newman

and Paul Barte, Worrld Bank, 1997

Automobile Use (km per year per person)

Automobile Use and Regional Economy

Re

gio

na

l G

ros

s P

rod

uc

t p

er

Ca

pit

a

(US

$ 1

99

0)

USA

Europe

Trend

Inertia of “BAU”

Transport Solutions?

Building highways end result

Congestion

Urban Sprawl

More vehicle use more air pollutant emissions

y = 0.0761x + 0.0867R² = 0.3894

-

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0

PM

gm

s p

er

ca

pit

a/d

ay

Vehicle-km/capita/day

Particulate Matter 15 Latin American Cities

Source: Observatorio Movilidad Urbana CAF http://omu.caf.com/

http://omu.caf.com/

More vehicle use more accidents

Cities of United States have 66% more deaths in traffic accidents per person than peer cities in Europe and Asia, and 123% more than Toronto (1990)

Accidentalidad

R2 = 0.5748

0.0

5.0

10.0

15.0

20.0

25.0

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000

Uso de Automóvil (Km por año por Persona)

Mu

ert

es e

n A

ccid

en

te d

e

Trá

nsit

o p

or

100, 000

Hab

itan

tes

Australia

EEUU

Toronto

Europa

Asia

Tendencia

Fuente: INDICATORS OF TRANSPORT EFFICIENCY IN 37 GLOBAL CITIES, Jeff Kenworthy, Felix Laube, Peter Newman and

Paul Barte, Worrld Bank, 1997

Automobile Use (km per year per person)

Road Safety

Ro

ad

Tra

ffic

De

ath

s p

er

10

0,0

00

po

pu

lati

on

USA

Europe

Trend

Coef. t Stat. P value

Daily VKT per person 0.52 10.68 0.000

Constant -10.05 4.45 0.000

US States (urban roads only) 2008

Source: Federal Highway Administration, Highway Statistics 2008

Analysis: Nicolae Duduta, EMBARQ

R² = 0.69

0

10

20

30

40

0 20 40 60 80 100

An

nu

al tr

aff

ic f

ata

liti

es

/

10

0 0

00

po

pu

lati

on

Daily VKT/ capita (urban roads)


Daily PKT per person (private car) 0.65 2.85 0.008

Constant -1.89 -0.65 0.522

German cities (2003 – 2006)

Source: Eurostat, the European Commission’s Directorate General for Statistics, 2006


R² = 0.21

0

3

6

9

12

15

6 8 10 12 14 16 18

An

nu

al t

raff

ic fa

taliti

es

/

10

0 0

00

po

pu

lati

on

Daily PKT in private car per person


Daily VKT per person 0.94 2.36 0.064

Constant -20.17 1.78 0.133

Australian States and Territories (2009)

Source: Australian Government, Department of Infrastructure and Transport, 2009


R² = 0.53

0

2

4

6

8

10

25.5 26 26.5 27 27.5 28 28.5 29 29.5 30 30.5

An

nu

al t

raff

ic fa

taliti

es

/

10

0 0

00

po

pu

lati

on

Daily VKT/capita

Adjusted R2= 0.57


Daily VKT per person (private car) 1.55 3.51 0.013

Population density -0.27 2.32 0.059

Constant 14.98 3.22 0.018

South African Provinces (2003)

Source: Arrive Alive, a road safety database endorsed by the South African

Government, 2003; Analysis: Nicolae Duduta, EMBARQ

R² = 0.39

10

20

30

40

50

0 5 10 15 20

An

nu

al t

raff

ic fa

taliti

es

/

10

0 0

00

po

pu

lati

on

Daily VKT / capita

Coefficients t Stat P-value

Intercept 0 N/A N/A

Private car VKT / capita 2.33 4.23 0.000

Public transit VKT / capita -1.19 0.28 0.779

Latin American Cities (2008)

Source: Andean Development Corporation (CAF) 2010


0

3

6

9

12

15

18

- 1 2 3 4 5 6 7 8

Ro

ad

Fa

taliti

es

pe

r 1

00

,00

0 h

ab

Vehicle-km/day per person private

VKT and fatalities over time (United States, 1990 – 2008)

adjusted R2 = 0.79

Coef. t stat. P value

VKT/person 0.29 2.29 0.036

Year -0.28 5.38 0.000

Constant 5.73 1.17 0.259

Source: US National Highway Traffic Safety Administration, 2009


10

12

14

16

18

20

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

An

nu

al t

raff

ic fa

taliti

es

/

10

0 0

00

po

pu

lati

on

actual fatality rates

estimated fatality rates

at constant 1990 VKT

Traffic Fatalities 1990-2008: 792 860

VKT 1990: 37 km/person/day

VKT 2008: 42 km/person/day

Traffic Fatalities at VKT (1990) :721 753 (est.).

Lives that could have been saved 1990-2008 ~71 000 (9%)

Example of a neighborhood design that discourages physical activity:

• low density

• single use

• poor connectivity

• auto oriented

Urban design and rendering: Nicolae Duduta, EMBARQ

Increasing physical activity:

1. Improving connectivity

Source: Cervero, Robert , Sarmiento, Olga L. , Jacoby, Enrique , Gomez, Luis Fernando and

Neiman, Andrea. 2009. Influences of Built Environments on Walking and Cycling: Lessons

from Bogotá, International Journal of Sustainable Transportation, 3: 4, 203 — 226



2. Increasing density

Source: Cervero, R., K. Kockelman. 1997. Travel Demand and the 3Ds: Density, Diversity

and Design. Transportation Research Part D, vol.2 issue 3, pp. 199-219.



2. Increasing density

Source: Cervero, R., K. Kockelman. 1997. Travel Demand and the 3Ds: Density, Diversity

and Design. Transportation Research Part D, vol.2 issue 3, pp. 199-219.



3. Mixed use, transit oriented development

Sources: Rundle A, Roux A, Free L, Miller D, Neckerman K, Weiss C. 2007. The urban built environment

and obesity in New York City: A multilevel analysis. American Journal of Health Promotion 24(4S):326–

334.

Cervero and Kockelman, op. cit.



4. Provision of parksSources: Gomez, L.F., D.C. Parra, D. Buchner, R.C. Brownson, O. Sarmiento, J.D. Pinzon, M. Ardilla, J.

Moreno, M. Serrato, F. Lobelo. 2010. Built Environment Attributes and Walking Patterns Among the

Elderly Population in Bogota. American Journal of Preventive Medicine; 38(6) pp. 592-599.

Zlot, A.I., T. Schmid. 2005. Relationships Among Community Characteristics and Walking and Bicycling

for Transportation or Recreation. American Journal of Health Promotion, March-April 2005, vol.19, no.4.



5. Safe, multi-modal streets, with priority for non motorized modes

(increased capacity for people)Sources: Lopez, R. 2004. Urban Sprawl and Risk for Being Overweight and Obese. American Journal of

Public Health, September 2004, vol. 94, no.9

Viola, R., M. Roe, H, Shin. 2010. The New York City Pedestrian Safety Study and Action Plan. New York

City Department of Transportation: August 2010, p. A12.

Cervero, R., K. Kockelman. 1997. Travel Demand and the 3Ds: Density, Diversity and Design.

Transportation Research Part D, vol.2 issue 3, pp. 199-219.


Key Messages• Challenge is large: urban and motor vehicle growth, strong

barriers: financial, physical, institutional, cultural

• Predict-and-provide approach is not sustainable

• Avoind-shift-improve through active and public transport,

demand management, integrated urban development

– High impact, fast implementation, low cost, structural

change

– Excellent examples in developing and developed countries

– Requires political leadership to change of paradigms:

people first not the motor vehicles

¡Muchas Gracias!

Documents

Sustainable Transport Saves Lives: Opportunities and Challenges for Urban India (Part 1)