Scoping Post 2012 Climate Instruments: Nationally Appropriate Mitigation Actions –NAMAsCase Study on Opportunities in Braz...
Proposed Framework forthe NAMA<br />Publicpolicyobjective<br /> NAMA Components<br /> GHG Mitigation<br /> Co-Benefits<br ...
Belo Horizonte, Brazil<br />http://i170.photobucket.com/albums/u252/rmcastanheira/BelaFoto.jpg<br />http://upload.wikimedi...
Goals<br />
NAMA Components<br />
Roadway<br />and Transit<br />Networks<br />(Supply 2008)<br />Socio-Economic<br />Characteristics <br />Origin-Destinatio...
For 2030 expected reductions of 1millionCO2eq tons compared with baseline, for a cumulative value of 9 million CO2eqtons<b...
In 2030 182 million hours saved in public transport and 170 million hours saved in private transport. Economic equivalent:...
Air Pollutants<br />
ClimateChangeFundingPotential<br />
http://www.bogotacomovamos.org/datos/AE_14_Bogota_Como_Vamos_2009.pdf<br />1600 surveys, error 2.6% with a 95% confidence ...
Conclusions<br />For 2030 the plan is expected to save 36% in GHG, 25% in travel time, 19% in transport costs and 39% in p...
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Scoping Post 2012 Climate Instruments: Nationally Appropriate Mitigation Actions (NAMAs)

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Case Study on Opportunities in Brazilian Cities – Belo Horizonte. By Dario Hidalgo. EMBARQ. Supported by Inter-American Development Bank. Presented at Latin American Carbon Forum, October 13-15, 2010. Santo Domingo, Dominican Republic.

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  • Study Objective: To understand methodological and practical issues for the application of NAMAs in the transport sectorMain questions: ¿Which aspects does an avoid-shift-improve NAMA include?¿How to organize it?¿How to fund it?¿How to do MRV?¿Which are the GHG and co-benefits potential in an intermediate brazilian city?¿How to expand it to a national program?
  • Minas Gerais State Capital 2.4 millioninhabitants, 5.4 million in themetropolitanarea (3rd in Brazil)Has alreadydeveloped a comprehensivemobility plan “planmobBH”Largescale data collectionAdequatetransportplanningmodelingtechniquesEvaluationIndicatorsonlycovertransportissues (congestion, modal splits, speeds)
  • Increase the share of active and public transport in the total trips, reduce GHG emissions and improve transport and local environment conditions For 2030 the NAMA is expected to generate 36% reductions in GHG, 25% reduction in travel time, 19% reduction in transport costs, and 39% reduction in particulate matter.
  • Estimated climate change funding: USD 36 Million (1.4% of the program cost) Small amount, but very attractive: grant or concessional loan Funding “up front” to help plan preparation and implementationTotal funds from diverse sources: local, state, national, commercial credit, multilateral funds, etc.
  • Monitoring activity (trip frequency, transport mode, modo, trip length)Categorized random sampling , error 5%, 95% confidence levelRecommended categories: trip purpose, gender, income level5,400 surveys, ~USD 21,600 to 27,000, a fraction of a large scale transport study
  • Scoping Post 2012 Climate Instruments: Nationally Appropriate Mitigation Actions (NAMAs)

    1. 1. Scoping Post 2012 Climate Instruments: Nationally Appropriate Mitigation Actions –NAMAsCase Study on Opportunities in Brazilian Cities – Belo Horizonte<br />EMBARQ, The WRI Center on Sustainable Transport<br />Supported by: Inter-American Development Bank<br />
    2. 2. Proposed Framework forthe NAMA<br />Publicpolicyobjective<br /> NAMA Components<br /> GHG Mitigation<br /> Co-Benefits<br />Financing<br />InstitutionalSettings<br />Monitoring, Reporting and Verification MRV<br />RiskAnalysis<br />
    3. 3. Belo Horizonte, Brazil<br />http://i170.photobucket.com/albums/u252/rmcastanheira/BelaFoto.jpg<br />http://upload.wikimedia.org/wikipedia/commons/b/b8/South_america_%281%29.jpg<br />
    4. 4. Goals<br />
    5. 5. NAMA Components<br />
    6. 6. Roadway<br />and Transit<br />Networks<br />(Supply 2008)<br />Socio-Economic<br />Characteristics <br />Origin-Destination<br />Matrix<br />(Demand 2008)<br />Roadway<br />and Transit<br />Networks<br />(Supply 2020)<br />Socio-Economic<br />Characteristics<br />(Demand 2020)<br />Structure and Parameters<br />Transport<br />Model <br />Calibration<br />Base Year 2008<br />Transport<br />Model <br />Application<br />Base Year 2008<br />Travel Time<br />Vehicle Kilometers<br />Travel Time<br />Vehicle Kilometers<br />Emissions Factors<br />2008<br />GHG Emissions<br />2008<br />GHG Emissions<br />2020<br />Emissions Factors<br />2020<br />
    7. 7. For 2030 expected reductions of 1millionCO2eq tons compared with baseline, for a cumulative value of 9 million CO2eqtons<br />
    8. 8. In 2030 182 million hours saved in public transport and 170 million hours saved in private transport. Economic equivalent: USD 1,300 million <br />
    9. 9. Air Pollutants<br />
    10. 10.
    11. 11. ClimateChangeFundingPotential<br />
    12. 12. http://www.bogotacomovamos.org/datos/AE_14_Bogota_Como_Vamos_2009.pdf<br />1600 surveys, error 2.6% with a 95% confidence level<br />
    13. 13. Conclusions<br />For 2030 the plan is expected to save 36% in GHG, 25% in travel time, 19% in transport costs and 39% in particulate matter as compared with a projected linebase (BAU)<br />The potential funding from climate change sources is small as compared with the funding needs, but a supported NAMA will help in removing implementation barriers. <br />Base GHG and co-benefits estimation in good transport planning: <br />Detailed modeling with good information on demand and supply <br />Integration of multiple elements under the plan: active and public transport, land use and transport demand management<br />Base climate change funding on the reduction potential, not the size of the investments<br />Base MRV on activity surveys (mobility objectives)<br />

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