1 cop8, 01 november 2002, new delhi, india mitigating environmental emissions from the urban...

1COP8, 01 November 2002, New Delhi, India

Mitigating Environmental Emissions Mitigating Environmental Emissions from the Urban Transport Systemfrom the Urban Transport System

Asian Regional Research Programme in Energy, Environment and Climate (ARRPEEC)

AsianAsian InstituteInstitute ofof Technology, ThailandTechnology, Thailand

Ram M. ShresthaS.C. BhattacharyaNazrul IslamN. T. Kim Oanh

COP8, 01 November 2002, New Delhi, India 2AIT

Cities CoveredCities Covered

Cities Country

Beijing and Hangzhou

China

Delhi and Mumbai

India

Jakarta and Bandung

Indonesia

Ho Chi Minh City

Vietnam

Manila Philippines


City ProfileCity Profile

City Category Area (km2)

Population (million)

Average Annual

Population Growth Rate

(%) Delhi (2001) Capital 1,483 14.2 4.3 Beijing (1998) Capital 16,807 10.9 1.4 Manila (2000) Capital 636 10.4 2.3 Mumbai (1991) Commercial 4,355 9.9 3.0 Jakarta (1997) Capital 660 9.5 4.2 Hangzhou (1998) Commercial 16,596 6.1 1.1 HCMC (1996) Commercial 2,000 4.7 2.4 Bandung (1997) Commercial 164 2.3 1.7


Project NetworkProject Network

AIT—Asian Institute of Technology, Thailand

DOSTE– Department of Science, Technology and Environment, Vietnam Prof. Nguyen Thien Nhan

ERI—Energy Research Institute, China Dr. Zhou Dadi

IGIDR—Indira Gandhi Institute of Development Research Prof. Jyoti Parikh

ITB—Institut Technologi Bandung, Indonesia Dr. Tatang H. Soerawidjaja

SATMP—Society for the Advancement of Technology in the Philippines, Philippines Dr. Joy V. Abrenica


Study ObjectivesStudy Objectives

To analyze the demand for urban transport services and associated energy demand and environmental emissions;

To analyze and select the technical options for energy efficiency improvement and mitigation of GHGs and other harmful emissions from the urban transport system; and

To identify and rank the barriers to the introduction of selected technical options to mitigate environmental emissions from the urban transport system.


Travel Demand, Energy Travel Demand, Energy Demand and Associated Demand and Associated

Environmental EmissionsEnvironmental Emissions


Projection of Travel DemandProjection of Travel Demand

GDP Growth Rate for BAU Projection (%)

City Bandung Beijing Delhi Hangzhou HCMC Jakarta Manila Mumbai

GDP growth rate

6.7 8.5-11.6 5.6 9.2-10.5 8.5-13 8.3 4.9 6.6

Alternative Scenario 1 is 1.5 times BAU GDP growth rate




GDP Growth Rate for Alternative Scenarios


Demand for Transport Services (p-km): Demand for Transport Services (p-km): BAU ProjectionBAU Projection

•Annual average growth rate of demand for transport services would be in the range of 3.3% (Beijing) to 7.3% (HCMC) during 1998-2020.

0

50

100

150

200

250

1995 2000 2005 2010 2015 2020

bill

ion

p-k

m

Bandung

Beijing

Delhi

Hangzhou

HCMC

Jakarta

Manila

Mumbai


Vehicle share (of the total vehicles) Vehicle share (of the total vehicles) in Bandung and Beijingin Bandung and Beijing

2005

Bus7%

Car26%

Trucks3%

2-Wheeler64%

2020

Bus10%

Car29%

Trucks2%

2-Wheeler59%

Bandung

Beijing

2005Bus1%

Car74%

2-Wheeler13%

Trucks12%

2020

Bus0%

Trucks9%2-Wheeler

7%

Car84%


Vehicle share (of the total vehicles) Vehicle share (of the total vehicles) in Delhi and Hangzhouin Delhi and Hangzhou

2005

Car32%

Bus1%

Others2%

Trucks4%

2-Wheeler61%

2020

Car28%

2-Wheeler66%

Bus0%Trucks

4%

Others2%

2005

Bus6%

Car50%

Trucks25%

2-Wheeler19%

2020

Bus2%

Car87%

2-Wheeler7%

Trucks4%

Delhi

Hangzhou


Vehicle share (of the total vehicles) Vehicle share (of the total vehicles) in HCMC and Jakartain HCMC and Jakarta

2005

2-Wheeler98%

Bus0%

Car1%

Trucks1%

2020

2-Wheeler96%

Bus0%

Car3%Trucks

1%

2005

Car18%

Bus12%

Others1%Trucks

12%

2-Wheeler57%

2020Trucks

13%

Others0%

Bus10% Car

16%

2-Wheeler61%

HCMC

Jakarta


Vehicle share (of the total vehicles) Vehicle share (of the total vehicles) in Manila and Mumbaiin Manila and Mumbai

2005Others51%

Bus1% Car

34%

2-Wheeler9%

Trucks5%

2020

Trucks3%

2-Wheeler8%

Car12%Bus

0%

Others77%

2005

Car34%

Bus1%

Others10%Trucks

3%

2-Wheeler52%

2020

Car26%

Bus1%

Others8%

Trucks3%

2-Wheeler62%

Manila

Mumbai


Change in Model Mix (2005-2020)Change in Model Mix (2005-2020)

Vehicle Type

Increased Share Decreased Share

Bus Bandung Beijing, Delhi, Hangzhou Jakarta, Manila, Mumbai

Car Bandung, Beijing, Hangzhou, HCMC

Delhi, Jakarta, Manila Mumbai

2-Wheeler Delhi, Jakarta, Mumbai Bandung, Beijing, Hangzhou, HCMC

Truck Jakarta, Mumbai Bandung, Beijing, Delhi Hangzhou, HCMC, Manila

Others Delhi, Jakarta, Manila Mumbai


Car Ownership in 1998 and 2020 Car Ownership in 1998 and 2020 (Units/1000 population)(Units/1000 population)

0

50

100

150

200

250

300

Bandung

Beijin

g

Delh

i

Hangzhou

HC

MC

Jakart

a

Manila*

Mum

bai

Un

its/1

000 p

op

ula

ton

1998

2020

•Beijing would have the highest car ownership among the cities (248 in 2020). However, the number would be still less than that in OECD countries.


Bus Ownership in 1998 and 2020 Bus Ownership in 1998 and 2020 (Units/1000 population)(Units/1000 population)

• Beijing would have the lowest bus ownership during the planning horizon.

0

5

10

15

20

25

Bandu

ng

Beijing Delh

i

Hangz

hou

HCMC

Jaka

rta

Man

ila

Mum

bai

Un

its/

1000

po

pu

lato

n1998

2020


Two-wheeler Ownership in 1998 and Two-wheeler Ownership in 1998 and 2020 (Units/1000 population)2020 (Units/1000 population)

0

100

200

300

400

500

600

700

800U

nit

s/1

000 p

op

ula

ton

1998

2020

• 2-wheeler ownership would be relatively low in Beijing, Hangzhou and Manila


Annual Average Growth Rate of Total Transport Annual Average Growth Rate of Total Transport Energy Demand (1998-2020): BAU Projection Energy Demand (1998-2020): BAU Projection

0

2

4

6

8

10

12

14A

AG

R (

%)

•AAGR is above 5% in all Cities


Share of CNG in Total Energy Demand in Share of CNG in Total Energy Demand in 2005 and 2020 (%)2005 and 2020 (%)

0

10

20

30

40

50

60

70

Beijing Delhi Hangzhou Jakarta Mumbai

CN

G (

%)

2005

2020

• The share of cleaner fuels, i.e. CNG, would increase in the future especially in the Indian cities of Mumbai and Delhi followed by Hangzhou Beijing and Jakarta.


Average Annual Growth Rate of COAverage Annual Growth Rate of CO22

Emission During 1998-2020 (%)Emission During 1998-2020 (%)

0%2%4%6%8%

10%12%14%

•Average annual growth rate: in the range of 3.1% (in Jakarta) to 12% (in Manila).

•Total transport CO2 emissions from the eight cities: 53.8 million

tonnes in 2020.


Ratio of CORatio of CO22 in 2020 to the Base Year in 2020 to the Base Year

(1998) Emission: BAU Projection (1998) Emission: BAU Projection I

0

1

2

3

4

5

6

7

Ra

tio


Modal Share in COModal Share in CO22 Emissions in Emissions in

Bandung and BeijingBandung and Beijing

Bandung

Beijing

1998

2-Wheelers32%

Trucks15%

Bus5%

Car48%

2020

2-Wheelers34%

Bus22%

Trucks11%

Car33%

1998

Bus11%

Car43%

Trucks43%

2-Wheelers3%

2020

Bus2%

Trucks16%

2-Wheelers16%

Car66%



Delhi and HangzhouDelhi and Hangzhou

Delhi

Hangzhou

1998

Car36%

Others10%

Bus26%

2-Wheelers12%

Trucks16%

2020

2-Wheelers6%

Car45%

Bus23%

Others6%Trucks

20%

1998

Car37%

2-Wheelers3%

Trucks35%

Bus25%

2020

Car57%

2-Wheelers8%

Trucks10% Bus

25%



HCMC and JakartaHCMC and Jakarta1998

2-Wheelers61%

Trucks32%

Car5%

Bus1%Others

1%

2020

2-Wheelers56%

Car7%Trucks

29%

Others2%

Bus6%

1998

Car41%

2-Wheelers14%

Trucks26%

Others2%

Bus17%

2020

2-Wheelers18%

Trucks33%

Others2%

Bus13%

Car34%

HCMC

Jakarta



Manila and MumbaiManila and Mumbai

1998

Car50%

Bus4%Others

34%

2-Wheelers4%

Trucks8%

2020

Trucks5%

2-Wheelers3%

Car46%

Bus3%

Others43%

1998

Car35%

2-Wheelers5%

Trucks6%

Others19%

Bus35%

2020

Car30%

2-Wheelers7%

Trucks8%

Others10% Bus

45%

Manila

Mumbai


Changes in Modal Share in COChanges in Modal Share in CO22

EmissionEmissionVehicle Type

Increase Decrease

Bus Bandung, HCMC, Mumbai

Beijing, Delhi, Hangzhou Jakarta, Manila

Car Beijing, Delhi, Hangzhou, HCMC

Bandung, Jakarta, Manila, Mumbai

2-Wheeler Bandung, Beijing, Hangzhou Jakarta, Mumbai

Delhi, HCMC

Truck Delhi, Jakarta, Mumbai

Bandung, Beijing, Hangzhou, HCMC, Manila

Others HCMC, Jakarta, Manila

Delhi, Mumbai


Ratio of Local Pollutants in 2020 to the Ratio of Local Pollutants in 2020 to the Base Year (1998) Emission: BAU ProjectionBase Year (1998) Emission: BAU Projection

Among the cities, Mumbai would have the lower ratio due to the higher share of buses, use of CNG and penetration of 4-stroke 2-wheelers.

HCMC would have the higher ratio due to the higher share of 2-wheelers.

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0R

ati

o

CO

NOx

SOx


Technical Options for Technical Options for COCO22 Emission Mitigation Emission Mitigation


Technology Options Considered for Technology Options Considered for Emission MitigationEmission Mitigation

Options Bandung Beijing Delhi Hangzhou HCMC Jakarta Manila Mumbai CNG1 - - LPG2 - - - BOV - -

MRTS - - - Catalytic Converter - - I & M5 - - - - CVID6 - - - - Hybrid Car - - - - - - 4-Stroke 2-Wheeler - - - - - - Efficient diesel car - - - - - - Ethanol3 - - - - - - Bio-Diesel4 - - - - - - Alco-Diesel (bus and truck)

- - - - - - -

Coco-Methyl ester (bus and truck)

- - - - - - -

Truck E100 - - - - - - - 1 Bus and car in Delhi, Bus, car and 3-wheeler in Mumbai, bus in Beijing and Hangzhou, bus, car, jeep, truck and pick up in Jakarta and bus in Manila. 2 Bus and car in Beijing and Hangzhou, bus, car, pick up, jeep, minibus and truck in Jakarta and Bundung and taxi in HCMC. 3 Pick up and minibus in Jakarta and minibus in Bandung 4 bus, car, jeep, pick up and truck in Bandung and Jakarta 5 I & M- Inspection and Maintenance, 6 CVID-Computer Variable Ignition Device Option selected


Least Cost COLeast Cost CO22 Mitigation Options Mitigation Options

Cities 0% Reduction 10% Reduction Bandung ADO buses (32.8%)

LPG buses (18.3%) Bio-diesel buses (18.3%) ADO minibuses (13.6%) Others (17%)

ADO buses (32.8%) LPG buses (18.3%) Bio-diesel buses (11.5%) Bio-diesel minibuses (6.6%) Others (30.8)

Beij ing Gasoline cars (42.7%) Diesel buses (33.5%) MRTS (14.2%) Diesel cars (3.7%) Others (5.9%)

Diesel buses (33.5%) Diesel Cars (28.3%) Gasoline cars (18.3%) MRTS (14.2%) Others (5.7%)

Delhi CNG buses (39.8%) Gasoline cars (22.4%) 4-S. 2-wheelers (17.2%) Diesel buses (11.6%) Others (9%)

CNG buses (39.8%) Gasoline cars (24.3%) 4-S. 2-wheelers (17.2%) Diesel buses (11.6%) Others (7.1%)

Hangzhou Diesel buses (71.9%) Gasoline cars (14.8%) MRTS (9.7%) LPG cars (3.6%) Others (0%)

Diesel buses (71.9%) MRTS (9.7%) Diesel cars (6.0%) Hybrid cars (4.6%) Others (7.9%)

ADO—Additive diesel oil


Least Cost COLeast Cost CO22 Mitigation Options Mitigation Options

Contd..Contd..

Cities 0% Reduction 10% Reduction Jakarta Gasoline minibus (26.8%)

ADO pick up (11.6%) CNG buses (11.3%) Bio-diesel buses (11.6%) Others (38.7%)

Gasoline minibus (22.8%) ADO buses (11.6%) CNG buses (11.6%) Bio-diesel buses (11.6%) Others (42.4%)

Manila Gasoline UV (25.8%) Diesel UV (17.6%) Gasoline cars (17.6%) Diesel buses (17.4%) Others (21.6%)

Car with cat. convert. (37.1%) Gasoline cars (17.5%) Diesel UV (15.4%) CNG buses (10.6%) Others (19.4%)

Mumbai Diesel buses (74.1%) Gasoline buses (10.5%) Diesel 3-wheelers (8.5%) CNG 3-wheelers (2.5%) Others (4.4%)

Diesel buses (70.4%) Gasoline cars (12.6%) Diesel 3-wheelers (6.0%) CNG buses (3.7%) Others (7.3%)

MRTS is cost effective at 20%, 40%, 25% and 40% CO2 reduction

target in Bandung, Beijing, Hangzhou and HCMC respectively.


Impact of COImpact of CO22 Mitigation Target on Mitigation Target on

Emissions of Local PollutantsEmissions of Local Pollutants

Local emission reduction objectives could still be served by focusing on CO2 emission reductions.

In the case of Beijing and Hangzhou, the introduction of efficient diesel car would reduce the emission level of CO, NOx and NMVOC. However, it would increase the emission of TSP.

TSP emission in Delhi would be reduced by 13% under 10% CO2

reduction target.

In Mumbai. TSP emission would be reduced 14% to 10%.

In the case of Manila, CO emissions would fall by 32% at 10% CO2 reduction.


Selected Technical Options to Selected Technical Options to Mitigate COMitigate CO22 Emission Emission

Bandung: LPG buses, bio-diesel buses and bio-ethanol buses

Beijing: CNG buses, diesel cars and MRTS

Delhi: CNG buses, CNG cars and 4-stroke 2-wheelers

Jakarta: CNG buses, LPG buses, bio-diesel buses and bio-ethanol buses

Hangzhou: CNG buses, diesel cars and MRTS

HCMC: MRT, Diesel bus

Manila: CNG buses, alco-diesel buses and (coconut methyl ester) CME buses

Mumbai: CNG cars, CNG 3-wheelers and BOV 3-wheelers


Barriers to the Barriers to the Adoption of Efficient Adoption of Efficient

OptionsOptions


Barriers to the Adoption of Barriers to the Adoption of Efficient OptionsEfficient Options

• Barriers varies from:

Country to country

City to City

Technology to Technology

• Technology specific barriers for each city were identified and the analysis of barriers are carried out using Analytic Hierarchy Process (AHP).


Barriers to the Adoption of CNG BusBarriers to the Adoption of CNG Bus

Beijing Hangzhou Manila

Lack of proper financing mechanism

Institutional and administrative barrier

High cost of engine conversion

Lack of public preference


Not able to use duel fuel

High initial cost


High investment for distribution infrastructure


Barriers to the Adoption of Bio-fuel Barriers to the Adoption of Bio-fuel Buses in ManilaBuses in Manila

Alco-Diesel Buses

CME Buses

High cost of local Alcohol

Amending the Clean Air Act

Uncertainty of impact on performance



Resistance from interest groups*


Barriers to the Adoption of CNG CarsBarriers to the Adoption of CNG Cars

Delhi

Mumbai

Inadequate resources and infrastructure


Additional cost Lack of enforcing mechanism

Availability of technology

Additional cost


Barriers to the Adoption of MRTSBarriers to the Adoption of MRTS

Beijing Hangzhou HCMC


Institutional and administrative barriers

High capital cost



Private vehicle usage psychology



Public vehicle fee


Barriers to the Adoption of 4-Stroke Barriers to the Adoption of 4-Stroke 2-wheelers in Delhi2-wheelers in Delhi

Additional cost Lack of enforcing mechanism Inadequate resources and infrastructure


Thank you


Additional Additional InformationInformation


Project ApproachProject Approach

Project Development(AIT, NRIs, Regional Experts/Policy Makers)

Development of Methodology(AIT)

Review of Methodology(NRIs)

Country Case Studies(NRIs)

Review of Case Studies(AIT)

Cross-Country Synthesis (AIT)

Publications(AIT, NRIs)

Dissemination(NRIs, AIT)


MethodologyMethodology

LEAP ModelLEAP Model

Econometric ModelEconometric Model

GDP

Vehicle Stocks

Emission

Energy Demand

Emission Factor

Energy Intensity

Utilization,

Occupancy Rate

Spread SheetModel

Spread SheetModel

Transport Demand (p-km)

Population


Modal Mix in 2005 and 2020 under Modal Mix in 2005 and 2020 under the BAU Case, %the BAU Case, %

City Year Bus Car 2-Wheeler Trucks Othersa Total Vehicles (103 units)

Bandung 2005 7.1 24.8 60.3 2.7 NA 429 2020 9.8 27.8 57.6 2.0 NA 1,117 Beijing 2005 0.5 74.5 13.3 11.7 NA 2,261 2020 0.2 84.0 7.1 8.6 NA 4,630 Delhi 2005 0.6 31.7 61.3 4.5 2.0 3,508 2020 0.4 28.0 65.3 3.9 2.4 8,854 Hangzhou 2005 5.8 50.2 19.1 24.9 NA 108 2020 2.3 83.1 6.5 3.8 NA 409 HCMC 2005 0.2 0.6 97.8 1.3 NA 2,717 2020 0.2 3.0 95.8 1.1 NA 6,740 Jakarta 2005 12.1 18.5 57.1 11.8 0.4 3,606 2020 10.4 15.8 60.9 12.6 0.2 8,853 Manila 2005 0.5 33.3 9.1 4.6 51.5 2,458 2020 0.2 13.0 7.9 2.9 81.3u 18,134 Mumbai 2005 1.5 33.5 51.5 3.1 10.5 876 2020 1.1 26.5 60.9 3.2 8.4 2,519 a Others include Jeepny in Manila, 3-Wheelers in Delhi, Jakarta, Mumbai and Lambro in HCMC NA=not applicable


Structure of the Projected Energy Structure of the Projected Energy Demand in 2005 and 2020Demand in 2005 and 2020

Fuel Share (%)

Gasoline Diesel LPG CNG Electricity

Total Energy Demand (106 GJ)

City

2005 2020 2005 2020 2005 2020 2005 2020 2005 2020 2005 2020

Bandung 74.4 75.4 25.6 24.6 NA NA NA NA NA NA 21.3 57.3 Beijing 69.3 75.4 21.8 15.9 7.6 6.9 0.8 1.1 0.6 0.7 82.9 140.5 Delhi 52.7 46.2 20.8 17.7 NA NA 26.2 34.9 0.2 1.2 67.5 136.9 Hangzhou 68.5 62.5 23.9 17.9 7.1 17.5 0.3 1.9 0.3 0.2 5.8 22.7 HCMC 68.0 71.5 32.4 28.5 NA NA NA NA NA NA 17.3 49.3 Jakarta 50.1 48.0 49.0 51.1 NA NA 0.9 0.9 NA NA 242.5 571.7 Manila 55.2 48.4 44.3 51.4 NA NA 0.0 0.1 0.5 0.1 93.3 598.0 Mumbai 35.7 25.1 28.8 7.4 NA NA 34.8 65.5 0.7 2.2 29.6 60.0 NA - not available

•The share of cleaner fuels, i.e. CNG, would increase in the future especially in the Indian cities of Mumbai and Delhi followed by the Chinese cities of Beijing and Hangzhou.


Ratio of Environmental Emission in Ratio of Environmental Emission in 2020 to the Base Year Emission2020 to the Base Year Emission

City CO2 CO SOx NOx TSPBandung 3.9 4.0 3.5 3.8 2.7Beijing 4 1.2 1.5 3.5 6.2Delhi 3.4 0.7 1.1 0.7 1.4Hangzhou 5.6 5.3 6.0 2.0 NA

HCMC 6.5 5.9 6.9 4.7 NA

Jakarta) 2.9 2.9 3.0 3.2 2.1Manila 3.3 3.3 3.3 1.8 3Mumbai 3.3 0.6 0.7 0.4 0.7


Flow Chart of MethodologyFlow Chart of Methodology

Vehicle-Mix Model

CostsCosts Candidate Options

Candidate Options

Vehicle-km by mode

Vehicle-km by modeTotal CostTotal CostVehicular

Mix

Vehicular Mix

Emission Factor

Emission Factor

Total Emissions

Total Emissions

Transport Demand Data

Transport Demand Data

Vehicle Penetration Rate

Fuel Availability

Emission target

Vehicle Penetration Rate

Fuel Availability

Emission target


Least-Cost Vehicle Options Least-Cost Vehicle Options Bandung and JakartaBandung and Jakarta

•In the base case, the shares of gasoline vehicles in total passenger transport service supplied in both cities would be decreasing while that of additive diesel oil (ADO) and LPG would be increasing

•At 20% reduction target, LPG and bio-diesel vehicles (car, minibus, truck, and bus), and MRT would be cost effective options to meet the CO2 reduction target

in Bandung. The share of bio-diesel vehicles at 20% target would be 24.6% in 2020.

•In the case of Jakarta, LPG car would be selected at 10% reduction target and bio-diesel vehicles (car, bus, jeep, minibus, bus, pick up and truck) and MRT would be selected at 40% reduction target. The share of bio-diesel vehicles and MRT at 40% reduction target would be 42.6% and 4.8% respectively in 2020 in Jakarta.


Least-Cost Vehicle Options Least-Cost Vehicle Options Contd..Contd.. Beijing and HangzhouBeijing and Hangzhou

Under Base Case, the shares of gasoline car and diesel buses on total passenger kilometer supplied would increase in both cities.

To achieve a reduction of 10% CO2 emission, gasoline cars needs to be replaced by diesel cars.

At higher emission reduction target of 40% for Beijing and 25% for Hangzhou, the share of MRTS would increase substantially.

The shares of diesel-buses in total passenger transport service supplied in different years would reduce significantly when the emission reduction target is increased from 30% to 40% for Beijing and 20% to 25% for Hangzhou.


Least-Cost Vehicle Options Least-Cost Vehicle Options Contd..Contd.. Delhi and MumbaiDelhi and Mumbai

Among the technologies considered, CNG buses would supply highest share of the transport services in passenger-km in Delhi while diesel buses would supply highest share of the transport services in Mumbai.

In Delhi, at higher emission reduction target level of 25%, diesel buses would replace the gasoline and diesel cars.

In the case of Mumbai, CNG buses would replace diesel buses at the emission reduction target of 5% while at higher emission reduction target of 30% battery operated 3-wheelers (2.5% in 2020) would replace the diesel 3-wheelers.


Least-Cost Vehicle Options Least-Cost Vehicle Options Contd..Contd.. ManilaAlco-diesel bus, alco-diesel trucks and cars with catalytic converters would be

cost effective technologies at the lower CO2 emission mitigation target of 5% in

Manila.As the emission mitigation target is increased, the share of these three

technologies would be increased, while the share of diesel buses and diesel trucks would decrease. At 15% reduction target, 99 % of the trucks would be using alco-diesel in 2020.

HCMCVans would be a cost effective technology at lower CO2 emission reduction

target of 3% in HCMC. At the emission reduction target of 3%, van would replace diesel buses.

At higher emission reduction targets of 12%, electric 2-wheelers would also be cost effective technology. Its share would be 27% at 12 % CO2 reduction target


Marginal Cost of CO2 Abatement (MAC), US$/tonne of CO2

•MAC would be relatively high for Manila (178 $/tonne of CO2 at

5% reduction target) and relatively low for HCMC (0.5 $/tonne of CO2 at 6% reduction target).

•The MAC values are relatively low in Beijing, Delhi and Mumbai.

Marginal Abatement Cost

City

Total Cumulative CO2

Emission (106 tonnes)

5% 10% 15% 20% 25% 30% 40%

Bandung 19 121 204 412 132,503 NA NA NA Beijing 105 29 33 NA 37 NA 39 253 Delhi 30 35 44 49 66 115 NA NA Hangzhou 6 76 89 NA 100 962 NA NA Jakarta 200 NA 112 NA 156 NA 269 246215 Manila 182 178 327 528 NA NA NA NA Mumbai 12 17 NA 19 21 24 47 NA

the figure for HCMC are 0.1, 0.5, 1.3 and 2.1 $/tonne of CO2 at 3%, 6%, % and 12% reduction targets respectively. NA – not available


Three important Barriers in Beijing and Three important Barriers in Beijing and Hangzhou for the Selected OptionsHangzhou for the Selected Options

Beijing CNG Buses Diesel Cars MRTS







High initial cost Lack of infrastructure Institutional and administrative barriers

Hangzhou

CNG Buses Diesel Car MRTS Institutional and administrative barrier




Institutional and administrative






Three important Barriers in Delhi and Three important Barriers in Delhi and Mumbai for the Selected OptionsMumbai for the Selected Options

Delhi CNG Buses CNG Cars 4-Stroke 2-Wheelers



Additional cost

Additional cost Additional cost Lack of enforcing mechanism

Lack of enforcing mechanism



Mumbai

CNG Cars CNG 3-Wheelers BOV 3-Wheelers Inadequate resources and infrastructure


Additional cost

Lack of enforcing mechanism



Additional cost Additional cost Lack of awareness


Three important Barriers in Three important Barriers in HCMC for the Selected OptionsHCMC for the Selected Options

MRTS MRTS + Bus Diesel Buses High capital cost High capital cost Private vehicle

usage psychology Private vehicle usage psychology

Private vehicle usage psychology

Bad road network

Public vehicle fee Subsidization on public vehicle

Poor services


Three important Barriers in Three important Barriers in Manila for the Selected OptionsManila for the Selected Options

Alco-Diesel Buses CME Buses CNG Buses High cost of local Alcohol

Amending the Clean Air Act

High cost of engine conversion





Resistance from interest groups*

High investment for distribution infrastructure

* Resistance of interest groups to divert coconut oil from exports to domestic use

1 cop8, 01 november 2002, new delhi, india mitigating environmental emissions from the urban...

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