1. Mobility energy use for different residential urban patterns in India Anil Kashyap, Jim Berry, Stanley McGreal, School of the Built Environment

2. Aim of the research 2  To consider relationships between, transport, spatial design of the built environment, energy use in mobility, and sustainability outcomes.  To use a case study approach to a middle tier city in India  To assess planned (i.e. structured) versus unplanned (i.e. organic, unstructured) residential neighbourhoods in terms of energy use and mobility patterns  To show whether better planning and design can contribute to a more energy efficient and environmentally sustainable urban form.

3. Literature review 3 Mobility is essential part of society Relationships exist between residential density, household vehicle use, and household vehicle fuel use 1 Rapid increase in motorised mobility due to the increase in 2 household income, commercial and industrial activity, availability of motorised transport and improvement in road infrastructure Increase in mobility has energy use implications 1 Brownstone (2009), 2 Singh (2006),

4. Literature review 4 Residents living in suburban neighborhoods drive more and walk less than their counterparts in traditional neighborhoods 3. Individuals choose the number of trips by each mode to maximize their utility 4 Residential neighborhood characteristics may be a good predictor for non-motorized travel 3 Built environment influences individuals’ travel behavior 3. Increasing residential density impacts on household vehicle holdings and vehicle fuel usage 5 3 Cao et al. (2009), 4 Crane et al. (1996, 2001), 5 Fang (2009),

5. Methodology Case study selection – Growing city in National Capital Region of Delhi – Spatially distinct, socio-economic homogeneous neighbourhoods Questionnaire survey to identify – Major activity nodes, Trip distances, no of trips, mode of travel – 225 households (22.5%) Calculation of energy use – Based on Specific energy consumption values for different modes (Stead, 2001) – 1.96 MJ/passenger-km travelled by motorised modes – lower and upper range of frequency calculated using the 95% confidence interval around the mean value 5

6. Case study location 6 Located in fastest growing National Capital Region Delhi Administrative Centre at district level Population of 250,000 (Census 2001) Growing at rapid pace with new residential and industrial development in the periphery Situated on major regional road and rail network Government focus on developing as self contained city to ease population pressure on Delhi

7. Urban form – unplanned element Prior to planning intervention, town grew organically around the central core or business spine or artery 7 Organic/Traditional urban structure of NHs Central Core Road Networks New Development

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9. Urban form – planned element The developments are mainly in the form of green field development, in the outskirts of existing towns 9 Central Core Road Networks Planned NH - Grid- Iron pattern Facilities Building blocks New Development

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11. Mobility pattern and energy use 11 Activity nodesTrip distance (Km)Mode share (%)Trip frequency (n) Car/ JeepMotor bike/ Scooter Car/ Jeep Motor bike/ Scooter Car/ JeepMotor bike/ Scooter Local shopping3.102.8137.9047.0010.8111.09 Other shopping6.556.4441.4046.705.195.76 Primary education4.255.156.5013.1024.00 Higher education0.008.094.3047.800.0024.55 Medical facilities3.944.1548.2042.201.802.15 Work10.969.6945.6043.5023.6624.22 Professional services3.933.5834.6050.903.763.44 Religious/comm. facilities4.046.1623.0029.1011.7613.19 Social & leisure12.259.2625.0016.903.329.04 Entertainment122.400.0080.603.201.240.00 Comparative analysis Activity nodesTrip distance (Km)Mode share (%)Trip frequency (n) Car/ Jeep Motorbike/ Scooter Car/ Jeep Motorbike/ Scooter Car/ Jeep Motorbike/ Scooter Local shopping1.502.543.6548.865.06.0 Other shopping0.002.580.0044.440.04.3 Primary education0.006.000.005.100.024.1 Higher education0.007.800.0027.780.023.7 Medical facilities4.553.905.0046.581.72.2 Work7.006.448.2146.2724.423.6 Professional services2.672.544.0245.542.03.0 Religious/comm. facilities2.253.102.0216.1610.510.8 Social & leisure13.283.6312.8520.002.82.7 Entertainment110.834.5725.5314.901.81.7 Planned Neighbourhood Unplanned Neighbourhood

12. Mobility pattern – Trip distance 12 Planned neighbourhood

13. Mobility pattern – Trip distance 13 Outside Neighbourhood trips Unplanned neighbourhood

14. Mobility pattern – Mode 14 Planned neighbourhood

15. Mobility pattern – Mode 15 Unplanned neighbourhood

16. Comparative analysis 16

17. Comparative analysis 17 ActivitiesUnplanned Neighbourhood Planned Neighbourhood % difference Local shopping281.02994.5071.7 Other shopping93.091073.6891.3 School education1719.633867.4155.5 Higher education2186.872359.317.3 Medical facilities250.08251.970.7 Work5163.458462.6039.0 Professional services190.10441.0056.9 Religious & Comm. facilities 828.171860.1555.5 Social & Leisure817.021639.8750.2 Entertainment2626.862641.630.6 Total14156.3023592.1240.0 Travel to activities namely work, shopping, school education, religious and social trips consumes significantly lower energy

18. Key findings 18 Mixed land use neighbourhoods use more non- motorised modes Car trips for local shopping is lower than walking, motorbike and other locally available means of transport such as auto-rickshaw, cycle rickshaw Public transport rather than cars, used for higher order shopping trips, school trips and higher education trips Non-motorised modes of travel increases with the location of facilities within the same neighbourhood or in adjoining neighbourhoods Unplanned neighbourhood

19. Key findings Share of motorised travel to medical facilities, work and professional services is high Walking trips is higher for travel to religions/community and social facilities. Non-motorised modes more extensively used for local facilities Higher trip distance for higher order shopping for more specialised items 19 Planned neighbourhood

20. Conclusions : Process  Influence of urban form characteristics on energy use for household mobility can inform policy decision making  Need for a more responsive planning system to manage the growth dynamic within cities in India  Well defined neighbourhoods and non-motorised use of transport reduces per capita carbon emissions  Infrastructure to support activity nodes and service provision in a sustainable way

21. Conclusions: Actions  Integrated planning and transportation policy response  Financial institutions need to support investment in sustainable transport.  Innovative design solutions to reflect the principles of sustainability agenda  Up skilling key actors in future implication of climate change on urban environment 21

22. Thank you for your attention 22