co-benefits action plan for bandung
TRANSCRIPT
Co‐benefits Action Plan for Bandung
Sudarmanto Budi Nugroho Policy Researcher
Outline
• Background on Co‐benefits
• Co‐benefits Study in Bandung
• Concluding Thoughts
Yet a different view on co‐benefits
Source: Mayrhofer and Gupta, 2016
Primary data Secondary data
IVE Model
Base case EI Scenario EI
Scenario storyline
AIT‐ITB
IGES ‐ ITB
‐ VKT‐ Start‐up No.
Data processing
Emission reduction& co‐benefits
AIT‐ITB
Research framework
About IVE model
• IVE: developed by University of California at Riverside, Center for Environmental Research and Technology (CE‐CERT), Global Sustainable System Research (GSSR) and the International Sustainable System Research Center (ISSRC)
• Suitable for developing countries: many technology indexes• Main features:
Vehicle‐Specific Power Incorporate local situation and fuel characteristics
Challenge: Data collection and Matching of technology index
Required data for IVE
6
Data Method Collecting Data Types Input for IVE
Primary Data
Questionnaire survey
Vehicle models, model year, ages, engine volume
and odometer
Fleet input file: technology distribution
Vehicle countingManual video camera recording and volume counting + existing
Location input file: vehicle type fraction
Driving patternsGPS data loggers and driver interview
Location input file: ‐ VSP bin distribution‐ Average hourly velocity
& km travelledStart/Stop patterns
Soak time distribution and number of start‐up
Secondary Data
Literature and interview,
contact with meteorological department
The population of registered vehicle, fuel
type quality, meteorological data etc.
Total estimated VKT & fuel characteristics for location
input file
1. Parking lots survey: 6 sites
1
6
Type BojonegaraPC 51MC 30Taxi 72Bus 96Paratransits 30Total 279
Type TegalegaPC 50MC 30Taxi 70Bus 97Paratransits 30Total 277
Type KareesPC 50MC 30Taxi 75Bus 91Paratransits 23Total 269
Type CibeunyingPC 40MC 22Taxi 58Bus 104Paratransits 26Total 200
Type Ujung BerungPC 25MC 15Taxi 45Bus 45Paratransits 15Total 145
Type Gede BagePC 25MC 15Taxi 45Bus 45Paratransits 15Total 145
Total delivered: 1,350Total received: 1,315
A. Data Collection for Developing Baseline Emission
2. GPS Survey: Vehicle speed (km/hr)
0
10
20
30
40
7 8 9 10 11 12 13 14 15 16 17 18 19
Spe
ed, k
m/h
Weekday
0
5
10
15
20
25
7 8 9 10 11 12 13 14 15 16 17 18 19
Spe
ed, k
m/h
Weekend
Bus MC Paratransit PC Taxi
3. Traffic Counting: Traffic Volume: veh/hr
0
2000
4000
6000
8000
10000
0
50
100
150
200
250
5h 7h 9h 11h 13h 15h 17h 19h
MC and PC
Oth
ers
Highway
0
2000
4000
6000
8000
10000
0
200
400
600
800
5h 7h 9h 11h 13h 15h 17h 19h
MC and PC
Oth
ers
Arterial roads
Taxi Paratransit Bus MC PC
0
500
1000
1500
2000
2500
0
20
40
60
80
100
120
5h 7h 9h 11h 13h 15h 17h 19h
MC and PC
Oth
ers
Residential roads
Emission Inventory: Base case emission and shares
Gg/yr
0%
20%
40%
60%
80%
100%
CO VOC NOx PM BC OC Airtoxics
CO2 N2O CH4 SO2
Emission share (Base case)
Bus MC Paratransit PC Taxi
173 34 20.6 2.7 0.9 1.4 5.1 3315 0.1 5 0.3
Air toxics: 1,3‐Butadiene, acetaldehyde, formaldehyde and benzene
Ei,j = VKTi * EFrun i,j + No.Starti*EFst i,j
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• Many public policies and private decisions require weighing multiple objectives and contemplating trade‐offs (Saaty, 2008)
• Decision makers frequently consider several criteria beyond quantified benefits when formulating policies.
• Analytical Hierarchy Process (AHP) is used to screen policies and identify priorities before quantifying benefits.
• AHP involves pairwise comparisons and expert judgements to evaluate intangibles in relative terms and determine priorities.
B. Policy Study and Developing Scenario for IVE
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Framework of Analysis with AHP
Criteria for Policy Option (C):C1 Quantity Transport ServiceC2 Quality Transport ServiceC3 AffordableC4 ImplementableC5 Environmentally Sustainable
Alternative Policies (A):A1 School ZoningA2 Pedestarian FacilitiesA3 Work SchedulingA4 BRT (Bus Rapid Transit) SystemA5 Revitalization of AngkotA6 Car Free Day in Certain RoadA7 School BusA8 Promoting LRT/MRTA9 Eco DrivingA10 I/M ProgramA11 ATCS System
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Questionnaire Survey Four types of respondents/stakeholders in Bandung city: (a) Government Staffs; (b) Academia; (c) Private Sectors and (d) Citizen & NGO.
In total: 40 Samples were collected from respondents (@10 samples)
Distribution of Questionnaire for Government Staffs: (a) Transportation Agency; (b) Environmental Agency; (c) Industry/manufacture agency; (d) ublic health division, etc
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Questionnaire Survey – Results 1 (Criteria)
Criteria Weighting vector Percentage (%)
Quantity of Transport Service (C1)0.0939 9.397
Quality of Transport Service (C2)0.2178 21.780
Affordable (C3)0.2017 20.170
Implementable (C4)0.1977 19.778
Environmentally Sustainable (C5)0.2887 28.875
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Questionnaire Survey – Final Score of Alternative Policies
Scenario 1: Eco‐driving
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Running
Stop
Apply Stepwise Speed Function (SSF): average speed of each running period (Kanari et al., 2012) Re‐calculate Vehicle Specific Power (VSP) bin distribution Eco‐driving ratio of 100% for Bandung city
Eco‐driving: a new driving culture (smarter) that makes best use of advanced vehicle technologies for and more fuel‐efficient driving
S2: Pedestrian and non‐motorized program• Non‐motorized program for government officer Focus on Government Officers living in Urban Areas Shifting from private vehicle to bicycle or walking Assumption: 4,600 unit of PC and 12,800 unit of MC Recalculated on Total VKT
• Car free night (CFN) and car free day (CFD) Visitors use non‐motorized transport means (walking and cycling) 8 events in a month for CFN & CFD (96 events in a year) Average number of visitors reported in media (15,000 people for
both). It was assumed approximately : PC=1,300 unit, MC=5,500 unit
Recalculate total reduction of VKT (km/year) for PC and MC due to these events
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S3: Paratransit revitalization program• Local policy: Paratransit’s Vehicle age should be < 7 years & 3 years transition (10 years)
• Paratransit with age for more than 10 years will be scrappaged Technology distribution change (fleet file) Conduct IVE re‐simulation new composite emission factors
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0
0.05
0.1
0.15
0.2
0.25
0.3
«1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Fractio
n
Age, year
Paratransit age distribution Bandung
Scrappaged
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Summary of Emission Reductions
Species
Base case Scenario 1 Scenario 2 Scenario 3
Emission (Gg/yr)
Emission (Gg/yr)
Reduction (%)
Emission (Gg/yr)
Reduction (%)
Emission (Gg/yr)
Reduction (%)
CO 173.14 145.33 16.06% 171.02 1.22% 168.68 2.58%
VOC 34.00 32.87 3.31% 33.57 1.25% 33.49 1.48%
NOx 20.59 16.30 20.85% 20.42 0.81% 20.10 2.35%
SO2 0.33 0.30 10.71% 0.33 1.62% 0.33 1.57%
PM 2.73 2.40 12.13% 2.73 0.24% 2.73 0.23%
BC 0.88 0.76 12.91% 0.88 0.16% 0.88 0.17%
OC 1.36 1.21 11.06% 1.36 0.34% 1.36 0.32%
CO2 3315 2966 10.54% 3281 1.04% 3271 1.34%
N2O 0.07 0.06 11.00% 0.07 0.83% 0.07 0.74%
CH4 5.02 4.79 4.70% 4.97 1.19% 4.92 1.99%
Air toxics 5.13 5.02 2.06% 5.08 1.00% 5.08 1.04%
CO2 vs PM emission reductions
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Eco‐driving
Pedestrianization and non‐motorized
Paratransit
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
18.00%
20.00%
0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% 16.00% 18.00% 20.00%
CO2
PM
Concluding Thoughts• Contribution on Baseline of CO2 emission in Bandung city: Private cars: 51.72% Motorcycle: 29.02 % Public Transport Modes (Bus, Paratransit and Taxi): 19.26%.
• The reduction of CO2 emission through three selected priority policies: (a) Eco driving: 10.54 %; (b) revitalization of paratransit: 1.34% (c) Pedestrian and non‐motorized transport program: 1.04%
• On the Paratransit:(i) Eco Driving and Revitalization: reduce 52.89% of total emission. (ii) However, it is only about 1.67% of total emission of transport sector.
• Therefore, in the future, priority program should be more focus on Private Vehicle (Eco‐Driving & Pedestrianization). It will give more significant impact on CO2 emission reduction in Bandung City.
Other Important Studies on Transition in Asian Cities
• Household Energy Survey on Local Energy Conservation Policy in Bogor City
• Greening Paratransit in Asia
Research framework
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IVE Simulation
Base case EI for 14 pollutants: CO, VOC, VOC ev, SOx, NOx, PM, 1,3 Butadiene, Acetaldehydes,
Formaldehydes, NH3, Benzene, CO2, N2O, and CH4
Interviews with Bandung Officials to
identify two or possibly more than two
scenarios
Emissions under different scenarios
Dissemination/Policy Dialogue
Co‐benefit analysis
Appendix:
Fleet technologies matched IVE indexes
Type No. of Index.
Engine standardFuelPre‐
EuroEuro1&2 Euro3&4 Euro5
Bus 16 18.1% 50.7% 29.0% 2.2% Diesel: 100%
MC 9 29% 0% 71% 0% Gasoline: 100%
Para‐transit 17 52.9% 47.1% 0% 0% Gasoline: 85%
Diesel: 15%
PC 20 21.5% 75.3% 3.2% 0% Gasoline: 93%Diesel: 7%
Taxi 8 65.7% 34.3% 0% 0% Gasoline: 100%
Appendix:
GPS Survey RoutesBUS: 2x2 daysLeuwipanjang‐LeengCicaheum‐Cibeureum
PC
MC: 3x2 days
PARATRANSIT: 2x2 days Antapani‐CiroyomGedebage‐Dago
TAXI: 2x2 days
PC: 3x2 days
Camera Recording for Traffic Flow
Secondary data for night time counting was gathered from Transportation Office and ITB
Period of counting was from 6:00-18:00 (2 weekend, 2 weekdays) Arcamanik
(residential)
Ahmad Yani(Artery)
Pasteur (Highway)
Buahbatu(Highway)
Soekarno‐hatta (Artery) Margahayu
(Residential)
Calculation of emission
Type Fleet pop. Daily vehicle activityVKT, km Start‐up, No.
Bus 5,805 116.8 10MC 1,113,316 22.9 8Paratransit 5,521 91 10PC 339,959 27.1 4Taxi 1,826 69.8 11
Ei,j = VKTi * EFrun i,j + No.Starti*EFst i,j
Fleet population: registration as of August 2015
2. Emission inventory results