environmentally sustainable transport performance index for

ESTP INDEX FOR RESIDENTIAL NEIGHBOURHOOD

Environmentally Sustainable Transport Performance Index for Residential Neighbourhoods

Urban Mobility India 2012 3rd Research symposium on Urban Transport

Megha Kumar

Prof. Sanjay Gupta Department of Transport Planning

School of Planning & Architecture, Delhi

1


Research Context

• 60% of GHG emissions accounted by vehicular emissions

• Neighbourhoods travel patterns are increasingly becoming

unsustainable due to increase usage on motorised modes which

are not environment friendly

• Research Need

• Conventional four stage demand modeling approach does not

address mobility needs of people at micro-level

• Neighbourhood planning approach is normative - ignores local mobility

needs

• Environmentally sensitive transport planning approach missing

“Objective is to develop ESTP Index approach”

Context Literature Case Study ESTP Index Model Scenarios

2


Literature

• Kersentuin, Utrecht, The Netherlands

• Vauban, Freiburg, Germany

• Valbona, Barcelona Area

• Fort St. John, Canada

• International best practices: Major findings • Compact & mixed development

• Higher % of circulation for EST networks

• Restricted movement of motorised vehicles

• Discouraging parking at doorstep

• Defining EST • Zero carbon emitting modes;

considering only tailpipe emissions

• walk, cycle, cycle-rickshaw, electric vehicles

As per ,OECD, Paris

• Provides for viable, & socially acceptable

access

• Meets generally accepted objectives for health & environmental quality

• Protects ecosystems

• Does not aggravate adverse global phenomena


3


• Phenomenal growth of population@ 4.1% annually (1991-2011)

Delhi

• Pressure on land & infrastructure

• Vision for Delhi (MPD 2021)

• Transit improvement: expansion of metro, BRTS

• Clean fuel; CNG

• Current focus of city

Macro level

Micro level mobility issues??

• global metropolis & a world-class city

• a sustainable environment


4


Case studies Socio-economic & travel behaviour

Selection criteria Housing typology

• Group housing

Income category

• MIG & HIG

Determinants of neighbourhood level mobility

Attributes Dwarka, sec-

22

Mayur Vihar-II,

Pocket B,C

Housing typology G+8 G+4

Income category MIG,HIG MIG

Area (Ha) 34.76 38.70

Estimated Population 10,000 people

Net Residential Density 830pph 483pph

Gross Residential Density 288pph 258pph

DWARKA, SEC-22

MAYUR VIHAR-II

Delhi


Case study description (Delhi residential Neighborhoods)

Purpose

5


Surveys

• Household survey

Case study Dwarka,

sector-22

Mayur

Vihar-II

HH

surveyed

85 87

Trip

information

323 292

• Other surveys

• Road Inventory Survey

• Spot Speed Survey

• EST Mode Supply Survey

Information collected • HH size

• HH income

• Vehicle ownership

• User preference

• Only intra

neighbourhood travel

information collected

• 1% sample size

collected


6


Case neighbourhood: Dwarka, Sector-22

Landuse break-up


DE

LH

I M

ETR

O

DE

PO

T

SEC.20

SE

C.2

3

SEC.8

ISBT

Plan

View •High density, compact

7


Case neighbourhood: Mayur Vihar – II, Pocket B,C

Landuse break-up


Plan

View •Low rise, medium density

8


Household Socio economic characteristics

• Income & Vehicle ownership levels

Household income and vehicle ownership levels are higher in

Dwarka, sector-22 neighbourhood


9


Travel Characteristics Dwarka, sector-22

neighbourhood Mayur Vihar-II neighbourhood

Total Trips 253 365

VKT/capita 0.064 0.077

Travel characteristics

Higher use of motorised vehicles in Dwarka,

sector-22 neighbourhood


Mode use Trip Rates Trip purpose

Motorised PCTR

MV-II Dwarka-22

0.32 0.71

10


Acceptable walking distance

Plotting cumulative frequency curves of average trip lengths (ATL)

For shopping • 245m for Dwarka, sector-22

• 280m for MayurVihar-II

For all trip purposes • 240m for Dwarka, sector-22

• 365m for MayurVihar-II


11


Network characteristics

• ROW & CW width

• Dwarka, sector-22 has higher width

ROW, CW width Dwarka-22 Mayur Vihar-II

Highest Hierarchy 60m, 35m 24m, 18m

Lowest Hierarchy 12m,7m 3m,0

• Speed on network

• Dwarka, sector-22 has higher speed

Speed Dwarka-22 Mayur Vihar-II

Highest Hierarchy High** High

Lowest Hierarchy High Low

** High: S>35kmph

• Footpath availability • Dwarka, sector-22: 100%

• Mayur Vihar-II: 60%

Footpath width Dwarka-22 Mayur Vihar-II

Highest Hierarchy 2.5m 3m

Lowest Hierarchy 3m 3m(exclusive)

Higher % of EST trips Mayur Vihar-II: Safe walking environment


12


Mayur Vihar –II Dwarka, sector-22


13


Determinants of Environmental Sustainable Transport (EST) mode usage

As distance increases

• Use of EST modes decrease &

• Use of motorised modes is increasing

EST supply Household income

Dwarka, sector-22

Mayur Vihar-II

Distance to shopping facility

Partial influence Insignificant influence

Dwarka, sector-22 Mayur Vihar-II

Mayur Vihar-II


14


Approach to evolve Environmentally Sustainable Transport Performance (ESTP) Index

Concept -“ Measure of transport performance of a residential

neighbourhood in terms of its environmental sustainability ”

S t e p 1

Deriving weight of each parameter

Scores for each parameter

In user preference survey :

Each parameter rated between 0 – 5

5: best score & 0: least score

Relative weight of each parameter is

worked out: kruskal wallice function

ESTP Index

S t e p 2

S t e p 3

S t e p 4

Neighbourhood attributes

Percentage of ∑(weighted score) of all

parameters

Study of local (development level) travel

pattern Setting up parameters


Analytical Approach (4 step)

15


Parameters Weight Factor

Distance From Shopping 3

Availability of Footpath(%) 2

Availability Of Exclusive EST

Network

2

Speed Of Traffic 2.5

Continuity 1

Crossing Facility 1

EST Mode Supply 2

S t e p 1

Setting up parameters Deriving weight of each parameter

S t e p 2


16


SCORING SYSTEM

DISTANCE FROM

SHOPPING WITHIN150M 150-250M 250-350M 350M-500M 500M & BEYOND

SCORE 5 4 3 2 1

AVAILABILITY OF

FOOTPATH(%) 100-80 80-60 60-40 40-20 20-0

SCORE 5 4 3 2 1

CONTINUITY HIGHEST HIGH MEDIUM LOW LOWEST

SCORE 5 4 3 2 1

SPEED OF TRAFFIC LOW (<25KMPH) MEDIUM (25-

35KMPH) HIGH (>35KMPH)

SCORE 5 3 1

CROSSING FACILITY DISABLED

FRIENDLY

ZEBRA

CROSSING +

LEVEL KERBS

+ TACTILE

PAVEMENTS

ZEBRA

CROSSING +

LEVEL KERBS

ZEBRA-

CROSSING+

MEDIAN

TREATMENT

ZEBRA-

CROSSING

SCORE 5 4 3 2 1

EST MODE SUPPLY

(NO. OF CYCLE

RICKSHAWS)

10-8 8-6 6-4 4-2 2-1

SCORE 5 4 3 2 1

TOTAL SCORE 35

S t e p 3


17


WEIGHTED SCORE FOR EACH PARAMETER (SCORE X WEIGHT)

PARAMETERS WEIGHT FACTOR HIGHEST SCORE WEIGHTED SCORE

DISTANCE FROM SHOPPING 3 5 15

AVAILABILITY OF FOOTPATH(%) 2 5 10

AVAILABILITY OF EXCLUSIVE EST

NETWORK 2 5 10

SPEED OF TRAFFIC 2.5 5 12.5

CONTINUITY 1 5 5

CROSSING FACILITY 1 5 5

EST MODE SUPPLY 2 5 10

TOTAL WEIGHTED SCORE 67.5

ESTP Index = Total weighted score of a cluster

67.5

X 100

ESTP Index

S t e p 4


18


Dwarka, sector-22 neighbourhood


ESTP Index assessment in BAU Scenario

19


Mayur Vihar-II neighbourhood


20

ESTP Index assessment in BAU Scenario


Cluster in Mayur Vihar-II ESTP Index(%)

Cluster in Dwarka, sector-

22 ESTP Index(%)

B1 67 A 56

B2 67 B1 54

C1 59 B3 54

B3 57 B2 48

C3 57 C1 44

B4 56 B4 41

C2 45 C2 39

C4 39 C3 39

Average 56 Average 47

ESTP Index of case neighbourhoods

ESTP Index of Mayur vihar-II is higher than Dwarka, sector-22


Comparative cluster level ESTP Indices in case studies

21


Case neighbourhood Total CO2 emissions (Kg/Day)

Dwarka, sector-22 175.8

Mayur Vihar-II 118.98

Transport dependent CO2 emissions

• Intra-neighbourhood vehicular emissions

USEPA Formula : Vehicle Distance Travelled (VKT)

Average Fuel Economy (KM/L) X Carbon Content of Fuel

(KG/L)

CO2

emissions =

• Dwarka, sector-22 has higher emissions


22


Relation between ESTP Index &transport dependent CO2 emissions

• Regression based model to predict CO2 emissions from ESTP

Index

y = -0.7177x + 49.306 R² = 0.7375

y = [CO2 EMISSIONS(KG)/CAPITA/DAY] X 1000

x = ESTP INDEX

As ESTP Index improves, transport dependent emissions decreases


23


Evaluation of Alternate Scenarios Scenario I: Optimistic scenario

• Highest possible ESTP Index, irrespective of feasibility of improvement

Highest score to network parameters :

Speed of traffic on residential streets

Continuity of footpath

Footpath & excl EST network availability

Crossing facility

Case neighbourhood ESTP Index

Dwarka, sector-22 70

Mayur Vihar-II 73

Mayur vihar-II has higher ESTP Index


24


Parameters Dwarka, sector-22 Mayur vihar-II

Distance to

shopping Availability of

footpath 100% availability

Partial

improvement

Exclusive EST

network

√Restrictions on

motorised traffic

No alternate

parking space

Continuity of

footpath √ Design improvements Crossing facility

Speed of traffic √ Traffic calming

EST mode supply

Scenario II: Feasible scenario

• Only feasible improvements considered

Case

neighbourhood

ESTP Index

Dwarka, sector-22 67

Mayur Vihar-II 70


• Feasible interventions

25

Evaluation of Alternate Scenarios


CO2 Emissions for différent scenarios

Neighbourhood

Est. Co2 Emissions(Kg)/Day Reduction in Co2

Emissions:

Scenario-I & BAU

Reduction in Co2

emissions

Scenario-II & BAU BAU Scenario-I Scenario-II

Dwarka, sector-22 175.80 15.27 20.42 11.5 Times Less

Than BAU

8.5 Times Less Than

BAU

Mayur Vihar-II 118.98 10.29 18.10 11.5 Times Less

Than BAU

6.5 Times Less Than

BAU

• Implication of ESTP Index approach

• Measurable impacts of transport infrastructure

• Emissions are significantly lower even in feasible scenario


26


• ESTP Index offers a new paradigm in neighbourhood planning with reference to transport provisions

• It is a potential scientific tool to measure impacts of improvements in

transport infrastructure on environmental quality in residential neighborhoods

• It emphasises on environmentally sustainable transport at neighborhood

level

• Has potential utility in evaluating existing as well as proposed residential

layouts in terms of environmental sustainability by planners

“ ESTP Index has the potential to be an effective decision

making tool to develop sustainable communities ”

Summing Up

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environmentally sustainable transport performance index for

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