Urban Mobility Forecasts: Emissions Scenarios for Three Indian Cities
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Urban Mobility Forecasts: Emissions Scenarios for Three Indian Cities

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By Lisa Rayle, Graduate Student, Dept. Urban Studies & Planning, MIT, lrayle@mit.edu and Madhav Pai, Technical Director - India, EMBARQ, WRI Center for Sustainable Transport, mpai@wri.org.

By Lisa Rayle, Graduate Student, Dept. Urban Studies & Planning, MIT, lrayle@mit.edu and Madhav Pai, Technical Director - India, EMBARQ, WRI Center for Sustainable Transport, mpai@wri.org.

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  • After looking the amount of C02 emissions in India, i would like to request automobile companies to buy solar rickshaw http://www.dezeen.com/2008/05/28/solar-rickshaw-by-solarlab/ as it can reduce emissions by up to 2 tons per rickshaw - Raakaa Alton (SEO Executive at http://www.secretsauce.in/)
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    Urban Mobility Forecasts: Emissions Scenarios for Three Indian Cities Urban Mobility Forecasts: Emissions Scenarios for Three Indian Cities Presentation Transcript

    • 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
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    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • Projected Emission Factors for Vehicles in India *actual analysis distinguishes between 2- and 4-stroke 19
    • 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
    • Growth in population and total daily trips for Surat, 2005-2040 Population 21
    • Annual CO2 emissions for Surat 22
    • Per capita emissions: current and under scenarios for 2040 23
    • Estimated 2040 emissions as a ratio to 2005 levels 24
    • Percent of total emissions for each mode - Surat 25
    • 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
    • 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
    • Thank you! Questions? Contact: Lisa Rayle lrayle@mit.edu Madhav Pai mpai@wri.org 28
    • References 1. Bose, R., and K.S. Nesamani. Urban Transport, Energy and Environment: A Case of Delhi. Institute of Transportation Studies, University of California, Davis, 2000. 2. Das, A. and J. Parikh. Transport scenarios in two metropolitan cities in India: Delhi and Mumbai. Energy Conversion and Management, Vol. 45, No. 15-16, 2004, pp. 2603-2625. 3. Fabian, B. and S. Gota. Emissions from India's Intercity and Intracity Road Transport. Clean Air Initiative for Asian Cities Center (CAI-Asia), 2009. 4. Schipper, L., I. Banerjee, and W. Ng. CO2 Emissions from Land Transport in India: Scenarios of the Uncertain. Submitted to Transportation Research Record, 2009. 5. Singh SK. Future mobility in India: Implications for energy demand and CO2 emission. Transport Policy. 2006 Sep ;13(5):398-412. 6. CEPT. Bus Rapid Transit System, Ahmedabad - Final Report. Centre for Environmental Planning and Technology, 2006. 7. Schipper, L., C. Marie-Lilliu, and R. Gorham. Flexing the Link between Transport and Greenhouse Gas Emissions: A Path for the World Bank. Paris: IEA, 2000. 8. CEPT. Surat Comprehensive Mobility Plan and Bus Rapid Transit System Plan: Detailed Project Report. Centre for Environmental Planning and Technology, 2008. 9. Lea Associates. Mumbai Comprehensive Development Plan. Lea Associates South Asia Ltd., 2005. 10. MMRDA. Regional Plan for Mumbai Metropolitan Region, 1996 - 2011. Mumbai Metropolitan Regional Development Authority, 1999. http://www.regionalplan-mmrda.org/. Accessed July 1, 2009. 11. Baker, J., R. Basu, M. Cropper, S. Lall, and A. Takeuchi. Urban Poverty and Transport: The Case of Mumbai. World Bank, 2005. 12. Hanson, S. and P. Hanson. Gender and Urban Activity Patterns in Uppsala, Sweden. Geographical Review, Vol. 70, No. 3, 1980, pp. 291-299. 13. Padam, S. and S.K. Singh. Urbanization and urban transport in India: the search for a policy. Europe Transport, Vol. 27, 2004, pp. 26-44. 29
    • References 14. Giuliano, G. and D. Narayan. Another look at travel patterns and urban form: The US and Great Britain. Urban Studies, Vol. 40, No. 11, 2003, pp. 2295-2312. 15. Miller, E.J. and A. Shalaby. Evolution of Personal Travel in Toronto Area and Policy Implications. Journal of Urban Planning and Development, Vol. 129, No. 1, 2003, pp. 1-26. 16. Schafer, A. Regularities in travel demand: An international perspective. Journal of Transportation and Statistics, Vol. 3, No. 3, 2000. 17. Mittal, M.L. and C. Sharma. Anthropogenic emissions from energy activities in India: generation and source characterization. Part II: Emissions from vehicular transport in India. USAID, 2006. 18. Iyer, N. Vehicle technology: 2 and 3 wheelers in Asia: Current and future greenhouse gas emissions. Manila: Asian Development Bank, 2006. 19. IEA. Energy Statistics - Electricity for India. International Energy Agency, 2006. http://www.iea.org/Textbase/stats/electricitydata.asp?COUNTRY_CODE=IN. Accessed July 10, 2009. 20. Kenworthy, J.R. Transport Energy Use and Greenhouse Gases in Urban Passenger Transport Systems: A Study of 84 Global Cities. Notre Dame University, Fremantle, 2003. 21. An, F. and A. Sauer. Comparison of passenger vehicle fuel economy and GHG emission standards around the world. Pew Center on Global Climate Change, 2004. 22. Jalihal, S.A. and T. Reddy. CNG: An alternative fuel for public transport. Journal of Scientific & Industrial Research, Vol. 65, 2006, pp. 426-431. 23. Takeuchi, A., M. Cropper, and A. Bento. The Impact of Policies to Control Motor Vehicle Emissions in Mumbai, India. Journal of Regional Science, Vol. 47, No. 1, 2007, pp. 27-46. 24. Kenworthy, J.R. and F.B. Laube. Patterns of automobile dependence in cities: an international overview of key physical and economic dimensions with some implications for urban policy. Transportation Research Part A: Policy and Practice, Vol. 33, 1999, 691-723. 25. Cameron I., T.J. Lyons, and J.R. Kenworthy. Trends in vehicle kilometres of travel in world cities, 1960–1990: underlying drivers and policy responses. Transport Policy, Vol. 11, No. 3, 2004, pp. 287-298. 30