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Sudarmanto Budi Nugroho IGES – IPSS Cities Team 26 November 2013 MRV Methodology for transport projects: lessons from CDM towards JCM/BOCM
Sudarmanto Budi NugrohoIGES – IPSS Cities Team
26 November 2013
MRV Methodology for transport projects: lessons from CDM towards JCM/BOCM
2
OutlineCDM at a glance
Performance of transport CDM projects
CDM way of MRVing transport projects
Lessons learned – how simplified CDM methodologies as basis of MRV for JCM/BOCM
3
What is CDM?
• Clean Development Mechanism – one of the ‘flexibility mechanisms’ under the Kyoto Protocol
• stimulates sustainable development andemission reductions in developing countrieswhile giving industrialized countries someflexibility in how they meet their emissionreduction limitation targets
4
Status of CDM projects
only 27 in transport out of 3,820 registered CDM projects
67% of projects are in China and India
Approved CDM methodologies applicable to transport sector
Source: CDM Booklet (November 2012)
Bus Systems AM0031MRT Systems ACM0016 AMS-
III.U.High-Speed Rail Systems AM0101Energy efficiency AMS-III.C. AMS-
III.A.AMS-III.AP.
AMS-III.BC.
Fuel Switch AMS-III.S AMS-III.AQ
AMS-III.AY.
Transport of Cargo AM0090Technology for ImprovedDriving
AMS-III.AT.
AMS-III.BC
How CDM works – project cycle
Making the project design document
Approval of voluntary participation from designated national authority and host country
Independent evaluation of project activity vis-a-vis CDM requirements on the basis of PDD
Formal acceptance of validated project
PP collect data to calculate emission reduction based on monitoring plan
Ex-post review of monitored emission reduction
Issue CERs equal to the verified amount
ProjectsMethodology
usedNumber of days
prior to registration
Metro Delhi, India ACM0016 1,998BRT Zhengzhou, China AM0031 819BRT Lines 1-5 EDOMEX, Mexico ACM0016 946Modal shift from road to train AMS-III.C 721Biodiesel for transport AMS-III.T 567BRT Chongqing Lines 1-4, China AM0031 1,101Cable cars AMS-III.U 2,471Regenerative braking system AMS-III.C 2,374BRT Bogota: TransMilenio Phase II to IV AM0031 1,402
Duration of CDM projects in the pipeline prior to registration
Source: IGES CDM Database.
0
500
1000
1500
2000
2500
3000
2001 2002 2003 2004 2005 2007 2008 2009 2010 2011 2012No
of d
ays r
equi
red
for
regi
ster
ed a
s Tra
nspo
rt
CD
M p
roje
ct
Year of submission POA
No of Days to Registered as Transport CDM based on year of submission of POA
N.Days
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CDM way of doing MRV
STEP 1Baseline and
project emissions are measured and
monitored by project participant.
STEP 2Collected and
recorded data are reported to designated
operational entity (DOE).
STEP 3Data including procedures are
verified as well as certified by the
designated operational entity
(DOE).
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65 54 36 59 15140 186
168 185 147176
367
485
15920 23 77135
25
124
41
0
100
200
300
400
500
600
700
800
BRTBogota - 1
BRTBogota - 2
BRTBogota -3
BRTBogota - 4
MetroDelhi - 1
MetroDelhi - 2
MetroDelhi - 3
Monitoring report preparation DOE verification period
CDM EB consideration period
Source: IGES CDM Monitoring and Issuance Database, August 2011. Data on yearly basis per issuance of CERs.
Number of days from the end of monitoring to issuance of CERs
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Challenges
• Numerous parameters to be monitored which take along time taken for the DOE/UNFCCC secretariatto verify and check their accuracy
• Monitoring method specified by the CDMmethodology is not practical in some cases
• Lack of clear guidelines for MRV approaches suchas in sampling
• Lack of DOEs capable to do verification
Indicator AM0031The transport modes used in the absence of BRT project
Passenger survey
Fuel types of different modes Local statistics
Average speeds Project data of local statisticsSpecific fuel consumption by mode and fuel type
Local statistics, national or international literature, or IPCC values multiplied by an annual technology improvement factor of 0.99 for buses, taxis and passenger cars, 0.997 for motorcycles
Fuel emission factor IPCC valuesAverage occupancy rate of the vehicles by mode
Project statistics or official statistics
Average trip distance for each mode
Project statistics or official statistics
Total number of passengers on the new system
Recorded per entry station
Example: data needs for AM0031
Differences between CDM and NAMA
CDM NAMA
Emission reductions used for Annex-1 country Kyoto compliance
Emission reduction account for NAMA country targetsException for market based NAMA to be decided
Coordination via private or public sector
Coordination most likely by government body
Baseline and monitoring via CDM methodology
Baseline and MRV system not yet defined
Financed through market mechanisms Market mechanism only an option
Defined by PDD and CDM methodology
Broad, sectoral approaches beyond CDM possible
Source: Adopted from Sekinger, 2011.
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Identified issues –lesson from CDM
1. How to simplify existing CDM methodologies?
2.Cost-effectiveness data and its impact on Estimationreliability?
3. How to transfer accumulated capacity based fromCDM experiences of private project proponents togovernment agencies implementing transport NAMAs?
Simplify MRV Methodology under the Joint Credit Mechanism
Framework for the UNFCCC Framework
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Bilateral, domestic and voluntary
Mechanisms under Kyoto Protocol
Framework for Various Approaches
CDM
JI
IET
JCMDomestic
offset scheme
VCS, Gold standard
Other scheme
Regional, national, sub-national
trading scheme
Non-market mechanismsNet Avoided Emissions
Other approach
17Source: Government of Japan. (2013) Recent Development of JCM/BOCM, updated by the speaker.
http://www.mmechanisms.org/document/20130523_JCMBOCM_goj.pdf
The Bilateral Documents for the JCM have been signedwith Mongolia, Bangladesh, Ethiopia, Kenya, Vietnam andIndonesia by September, 2013.
Bilateral Relations
How to simplify transport MRV methodologies?
• Use of default values• Benchmarking• With/Without monitoring (Top Down/Bottom Up)• Adjustment of initial values after verification
STEP 1use of initial default
values(ex-ante estimation)
STEP 2With / Without
Monitoring (Top-down / Bottom-up)
STEP 3adjusted values
(ex-postverification)
No AMS-III.C. (UNFCCC) MRV –JCM (by GEC)
A Reference References: AMS-III.S and AMS-III.C (UNFCCC)
B Eligibility a. Vehicles for Passenger and Freight Transportation a. Public Buses
b. New electric and/or hybrid vehicle, for Passenger and Freight
b. New buses and/or retrofit bus
c. Biofuel is excludedd. Repleceable/Chargeable battery are allows, with special documented measures
Case Study 1- Bus Improvement Program at Vientiane-Lao PDR
No AMS-III.C. (UNFCCC) MRV –JCM (GEC)C Methodology
1. Basis: Calculation based on Annual Activity (VKT) 1.Basis: Fuel Consumption
Baseline Emission: E=VKT(km/year)*SFC(liter/km)*NCV(J/liter)*EF(gCO2/J)
a. With Monitoring Fuel Consumption Baseline Emission : E=TFC(Liter/year)*NCV(J/liter)
*EF(gCO2/J) b. Without Monitoring Baseline Emission:E=VKT(km/year)*SFC(liter/km)
*NCV(J/liter)*EF(gCO2/J)Notes: (1) Bus operation is Fixed Route and Schedule and total number of services per day also easily to get and therefore, daily activity is easily monitored; (2) Fuel monitoring is more accurate because come from actual condition. In case of estimation by using VKT, we need to input fuel efficiency which may differ depend on several factors which may out-of-control by authority, such as traffic jam, etc
AMS-III.C. (UNFCCC) MRV –JCM (GEC)Monitoring Items
1. Annual VKT 1. Fuel Consumption a. Monitoring All Vehicle a. Monitored ---> Fuel consumption basedb. Monitoring respresentative sample survey for each category
b. Without-monitoring Fuel Efficiency Based (Follow the CDM flow, using VKT)
2. Specific fuel/electricity consumption per kma. Monitoring All Vehicleb. Monitoring respresentative sample survey for each category3. Net calorific value of fuel 2. Net Calorific Value4. CO2 emission factor of fuel used by vehicle 3. CO2 emission factor of fuel used by
vehicle
5. CO2 emission factor of electricity used by vehicle
6. Losses on Transmission/Distribution for Providing Electricity
a. Not related with transport sector but Energy Supply)
b. May related to deterioration rate for vehicle
Case Study 2- MRT at Bangkok
No ACM0016 Version 3 MRV- JCM (GEC)1Eligibility Eligibility:
a. A new urban MRT and/or its extension a. New urban MRT, including its extension
b. Rail based-passenger b. Rail based-Passengerc. There exist public transport mode in the same route
c. There exist public transport mode in the same routed. Technology Transfer from Japan
2ref: NM0258 and NM0266 Reference: ACM00163Boundary Boundary
a. Access and Egress as indirect effect (encompasses all transport modes used by MRT User from O to D
a. Exclude Access and Egress (MRT Section only)
b. Didn't considered vehicle speed change b. Vehicle speed change-parallel road
B Methodology - Calculation of baseline emissionACM0016 Version 3 MRV- JCM (GEC)
1 Option for calculation due to Modal ShiftModal Shift based on Interview survey and stipulated calculation option is followed
a. Modal Shift without Interview survey (method 1-1)b. Modal Shift with Interview survey (ACM0016)(method 1-2)
2 Calculation of Change the vehicle speed Not Considered ! a. Certain distance of affected road (within
1 km paralel)b. Traffic Volume Survey --> from Monitoring c. Using VC approach
3 ACM0016 Version 3 MRV- JCM (GEC)Data for calculation of Modal Shifta. Survey/Questionnaire of O-D for all modes
(i) without surveya. Total passenger of MRT (aggregate/bulk data)
b. Expansion factor for improve survey accuracy
b. Mode shares of MRT (default value is allowed and fixed all the time)
c. VKT by MRT (Start-End point MRT)d. Default values for Occupancy rate of vehicles(ii) with surveya. Total passenger of MRT (aggregate/bulk data)b. Mode shares of MRT (default value is allowed and fixed all the time)
4Data for Calculating change in vehicle speedNot considered a. Volume and Road Capacity (Speed)
(V/C ratio)b. BPR Function (alpha and beta parameter), formula:V bs=
TV bs = TV PJ + P (mrt)*MSmrt
5LeakageEmissions due to changes in the load factor of taxis, buses and emissions due to reduced congestion on affected roads, leading to higher average vehicle speed are included. Leakage emissions are only counted when they exceed zero
No *The effects of traffic congestion mitigation is included in the reference scenario emissions and project emissions
1.0
Data Selection and Its Impact on Estimation Reliability
The project activity is to use electric instead of fossil fuel powered scooters in various cities and regions of India. EKO Vehicles
Private Limited Electric 2-Wheelers (EV 60, Cosmic) (Registered by September 2012-UNFCCC)
Baseline Emission = VKT(km/year)*SFC(liter/km)*NCV(J/liter)*EF(gCO2/J)Data Requirement= (i) Activity per year (VKT) (km/year)(ii) Fuel Consumption (SFC) (liter/km)(iii) Net Calorie of Fuel (NCV) (J/liter)(iv) Emission Factor of Fuel (EF) (gCO2/J)
1. Total Emission for Baseline & Prediction of Emission reduction based on market share of vehicles
2. Data for sample of Fuel Consumption: 20 vehicles 3. Monitoring: market penetration
Basis Calculation: Annual Vehicle Kilometer travelled (VKT)
A case study of AMS.III.C :Emission Reduction by Electric and Hybrid Vehicles
1. Inventory population of motorcycle taxi and Its distribution in Bandung city
2. Survey/ Data Collection & Calculation of GHG Emissions
Case Study 3: Estimation of Baseline GHG Emission from Motorcycle Taxi in Bandung city
*Number of station: 169 stations (as of June 2012)
*Total Population (Ojek Drivers) = 6371 Drivers
Map of Distribution of Ojek` station in Bandung city
Questionnaire Survey/Data Collection Population: 6371
One day survey: 400 (6.3%)
One week trips: 100 (1.6%)
No Type of Survey No of Samples Type of Data
1 One day averagedata
400 (6.3% of population)
a. Average daily travelled (km)b. Average fuel consumption (l)
2 One week data (paper based)
100 (1.6% of population )
a. Daily travelled (km)b. Daily fuel consumption (liter)c. Day-off services
3 One week GPS survey
100 (1.6% of population)
a. Real time trips b. Actual travelled kilometresc. Actual vehicle speed
Characteristics Mean St Dev Min MaxVehicle Age 2006.75 4.36 1982 2012Engine Size (cc) 115.34 14.20 90 200N-Trips/day 14.21 5.97 3 35Distance per trip (km) 2.18 0.59 1 8Total travel distance per day (km) 30.89 13.83 8 75Fuel Consumption per day (liter) 2.16 0.83 0.90 11.1Fuel consumption per kilometer (liter)
15.29 7.19 2.7 54.0
Fuel efficiency (liter per km) 0.039 0.024 0.000 0.185
1. Data from one day survey
Characteristics Bandung
N-Trips/week 43.54 (16.42)Total travel distance per week (km) 80.06 (56.36)No of working day per week 6.40 (0.7)Average fuel consumption per day (liter)
2.12 (0.636)
Fuel Efficiency (km/liter) 13.463 (10.544)
Note: About mean and standard deviation (inside bracket);
2. Data from one week interview survey
Characteristics Bandung
Total travel distance per week (km) 191.11 (67.561)Average speed (km/hour) 18.469 (3.572)Acceleration/Deceleration (%) 65.58Fuel efficiency (km/liter) 16.026 (8.628)Note: About mean and standard deviation (inside bracket)
No of Driver: 100 DriversDistribution: All 6 Clusters in BandungDuration: One weekInterval of observation: 1,3,5 second.Equipped with vehicle (under the seat)- to avoid missing data
3. Data from one week GPS survey
Fuel consumption of Motorcycle taxi- by using 3 different data sources
No Parameter Data Sources
One Day One Week GPS Survey
1 Fuel Consumption (l/day) 2.16 2.12 2.12
2 Fuel Efficiency (km/litre) 15.29 13.46 16.03
Baseline Emission (tCO2/year) One Day One Week GPS Survey
1 Based on Fuel Consumption 11410.28 11198.98 11198.98
2 Based on Fuel Efficiency (VKT) 6363.93 4475.35 8974.52
Comparison Analysis of 3 different data sources and Its impact on Estimation of GHG Emission.
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Way forward for development of MRV for JCM - Transport
A. Considerable experiences already available to MRV transportprojects under JCM and pro-active in efforts to simplifymethodologies.B. Improvement of methodologies:1. Apply JCM methodologies for other transport projects andactivities and Apply Bottom-up and Top-Down Approach Reliability of Information and Its Impact on GHG EmissionEstimation2. Optimizing Survey (Monitoring) Cost Effectiveness andAccuracy!
