Jakapong Pongthanaisawan 1, Chumnong Sorapipatana 1 and Bundit Limmeechokchai 2
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1 The 2nd Joint International Conference on Sustainable Energy and Environment (SEE 2006) November 2006, Bangkok, Thailand Land Transport Demand Analysis and Energy Saving Potentials in Thailand Jakapong Pongthanaisawan 1, Chumnong Sorapipatana 1 and Bundit Limmeechokchai 2 1 The Joint Graduate School of Energy and Environment, King Mongkut s University of Technology Thonburi, Bangkok, Thailand 2 Sirindhorn International Institute of Technology, Thammasat University, Klong Luang, Pathumthani, Thailand
2 Presentation Outline Background Objective Methodology Result Conclusion
3 60,000 Energy Consumption by Economic Sector ktoe Background 50,000 Agriculture 6% 40,000 Resident & Commercial 21% 30,000 20,000 Industry 36% 79% 10,000 Transport 38% 0 Source: DEDE (2004) 2002 Energy demand is 1.4 times higher than GDP growth ( ) log ( Energy) Energy Elasticity = t Energy Consumption/ t GDP Ave. Energy Elasticity 1.4 : 1.0 New Target 1 : 1 or lower log (GDP) Source : EIA,DOE, BP Statistic Review of World Energy, EGAT
4 Objective To estimate energy demands and emissions of vehicles in road transport sector from 2005 to 2020 To analyze potential of scenarios of energy saving, energy substitution and emissions reduction in road transport sector from 2005 to 2020
5 End-use Analysis by Methodology Sector Sub-sector End-use Device Energy Intensity Transport (vehicles) Bangkok (%share of vehicles) Conventional Cars (vehicle-km) Fuel Economy (liter/veh-km) Provincial (%share of vehicles) Hybrid Cars (vehicle-km) Fuel Economy (liter/veh-km) Energy Demand = Level of Activity x Energy Intensity Socio-economic factor GDP number of population Transportation factor number of vehicles vehicle kilometers travel Energy efficiency of vehicles fuel economy Emission = Energy Demand x Emission Factor
6 Methodology Energy Demand = Level of Activity x Energy Intensity Energy Demand (ED) in the LEAP Model ED i = NV x VKT x PV i x FE i where ED i is the energy demand of fuel type i (ktoe) NV is the number of vehicles (vehicle) VKT is an average vehicle kilometer travel (kilometer/year) PV i is the proportion of vehicle by fuel type i FE i is the fuel economy of fuel type i (liter/vehicle-kilometer)
7 Methodology Energy Demand = Level of Activity x Energy Intensity Number of Vehicle (NV) Used in the LEAP Model NV = f (GDP, POP) where NV is number of vehicles (vehicle) GDP is the gross domestic product of Thailand at the constant prices (million baht) POP is the number of population (person) Vehicle Kilometer Travel (VKT) an average distances that vehicle travel in one year (kilometer per year) secondary data from the study of Chanchaona et al (1997) and Tanatvanit, et al.(2003)
8 Methodology Energy Demand = Level of Activity x Energy Intensity Fuel Economy (FE) Used in the LEAP Model an average fuel consumption of vehicle per vehicle-distance travel (liter/vehicle-kilometers) secondary data from the study of Chanchaona et al (1997), Tanatvanit, et al.(2003) and EPA (2005) Proportion of Vehicle by Fuel Types The types of fuel used in the road transport are classified into four main groups: gasoline diesel liquefied petroleum gas (LPG) compressed natural gas (CNG).
9 Emission = Energy Demand x Emission Factor Emission of Vehicles from the LEAP Model EM ij = ED x i EF ij x GWP j where EM ij is an amount of emission of substance j from fuel type i (kg CO2 equivalent) ED i is energy demand of fuel type i (ktoe) EF ij is emission factors of substance j from fuel type i (kg/ktoe) GWP i is emission conversion factors of substance j (kg CO2 equivalent/kg of substance) Methodology
10 Scenarios in the LEAP Model Based case scenario Business-as-usual scenario Methodology Alternative scenarios Alternative scenarios Natural gas vehicle scenario Hybrid cars scenario Fuel economy improvement scenario Business-as as-usual (BAU) Scenario Assumptions Growth rate of GDP is 5.5% per year. The efficiency of vehicle and the pattern of energy utilization of vehicle are unchanged from 2005 to The ongoing projects are not implemented. The environmental emissions are evaluated by using the technology and environment data based (TED) module in LEAP software.
11 Alternative Scenarios Natural Gas Vehicle (NGV) Scenario Applied from PTT s NGV Plan (2005): 740 filling stations and 500,000 NGVs in Growth rate of GDP is 5.5% per year. (Stations) (1,000 vehicles) No. of NGV No. of Filling Station '05 '06 '07 '08 '09 ' Source: PTT (Public) Co.,Ltd.
12 Alternative Scenarios Hybrid Car (HYB) Scenario The hybrid cars will be substituted for the new conventional sedan with a market penetration that shown in figure. Fuel economy of hybrid cars is liter per 100 km (EPA, 2005). Growth rate of GDP is 5.5% per year. 20.0% Market Penetration Rate of Hybrid Cars from 2006 to % 16.0% 15% of new sedan from % 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0% Year
13 Fuel Economy Improvement (FEI) Scenario From 2010, fuel economy of sedan and pickup should be exceed the minimum fuel economy standard, as shown in table. Growth rate of GDP is 5.5% per year. Alternative Scenarios Vehicle Type Gasoline Average Fuel Economy (liter/100 kilometer) Diesel Sedan Van & Pick Up Source: EPA, 2005 economy
14 Energy Demands of Vehicles in BAU Scenario Result ktoe Energy Demands in Road Transport Sector from 1999 to ,000 35,000 History Projections 34,386 30,000 29,150 25,000 20,000 20,776 24,627 15,000 10,000 5,000 14,244 GR: 4.2% GR: 3.4% Year LPG Gasoline Diesel CNG History Energy demands of vehicles would be increased 3.4% per year.
15 Result Emissions of Vehicles in BAU Scenario Million tons of CO2 eq Emission of vehicle in road transport sector by fuel types CNG Diesel Gasoline 60 LPG 40 GR: 4.1% Year Emissions of vehicles would be increased 4.1% per year.
16 Energy Demands (ktoe) Scenarios BAU Scenario LPG Gasoline 6,644 7,946 9,595 11,498 Diesel 13,772 16,194 18,899 22,007 CNG Total 20,776 24,627 29,150 34,386 NGV Scenario LPG Gasoline 6,644 7,767 9,289 11,186 Diesel 13,772 15,713 17, CNG 16 1,055 1,926 1,943 Total 20,776 24,640 29,152 34,365 NGV Scenario 34,000 32,000 30,000 28,000 Thousand Tonne of Oil Equivalents 34,000 32,000 30,000 28,000 26,000 24,000 22,000 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Energy demand of vehicles in road transport sector Scenario: Business-as-usual Years Energy demand of vehicles in road transport sector NGV Scenario BAU Scenario Scenario: CNG Substitution Result LPG Gasoline Diesel CNG LPG Gasoline Diesel CNG CNG could be substituted for conventional fuel by 1,032 ktoe in 2010, 1,894 ktoe in 2015 and 1,900 ktoe in Thousand Tonne of Oil Equivalents 26,000 24,000 22,000 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 CNG Substitution 4.2% 6.4% 4.8% 2, Years
17 Energy Demand of Vehicles in Road Transport Sector Result 35,000 ktoe Energy Demands of Road Transport Sector by Scenarios 30,000 25,000 20,000 15,000 HYB : 0.4% Saving FEI : 0.6% Saving HYB : 0.8% Saving FEI : 3.5% Saving HYB : 1.0% Saving FEI : 5.7% Saving 10,000 BAU Scenario 5,000 Hybrid cars Scenario Fule Economy Improvement Scenario Year Hybrid cars scenario could reduce energy demands by 0.4%, 0.8% and 1.0% in 2010, 2015 and 2020, respectively. Fuel economy improvement scenario could reduce energy demands by 0.6%, 3.5% and 5.7 % in 2010, 2015 and 2020, respectively.
18 Emission of Vehicles in Road Transport Result Thousand Tons of CO2 eq 160, , ,000 Emissions of Vehicles by Scenarios BAU Scenario NGV Scenario Hybrid Cars Scenario Fuel Economy Improvement Scenario 100,000 80,000 60,000 40,000 NGV : 19.7% Reduction HYB : 0.4% Reduction FEI : 0.4% Reduction NGV : 20.4% Reduction HYB : 0.8% Reduction FEI : 2.5% Reduction NGV : 14.5% Reduction HYB : 0.9% Reduction FEI : 4.0% Reduction 20, Year NGV scenario could be reducing the emissions by 19.7% in 2010, 20.4% in 2015 and 14.5% in Hybrid cars scenario could reduce the emissions by 0.4%, 0.8% and 0.9% in 2010, 2015 and 2020, respectively. Fuel economy improvement scenario could reduce the emissions by 0.4%, 2.5% and 4.0% in 2010, 2015 and 2020, respectively.
19 Conclusion Fuel economy improvement scenario is the highest potential strategies to reduce the energy demands comparing to hybrid car scenario. NGV scenario should be implemented to reduce the emissions and to substitute the conventional fuel with domestic energy sources. Even though, energy consumption with this scenario is higher than BAU scenario.
20 Acknowledgements The authors would like to thank you Thailand research fund (TRF), the Joint Graduate School of Energy and Environment (JGSEE) and King Mongkut s University of Technology Thonburi (KMUTT) for the financial support of this study. Moreover, the authors also would like to thank you Stockholm Environment Institute (SEI)-Boston Center for the LEAP model.
21 Thank you very much for your attention
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