Vi tn m Tr nsport Knowl d ri s - The World Bank · Vi ! tn " m Tr " nsport Knowl ! d #! S ! ri! s Support ! d b " AUSTRALIAÐWORLD BANK GROUP STRATEGIC PARTNERSHIP IN VIETNAM, GOVERNMENT

Vietnam Transport Knowledge Series Supported by AUSTRALIA–WORLD BANK GROUP STRATEGIC PARTNERSHIP IN VIETNAM, GOVERNMENT OF GERMANY and NDC PARTNERSHIP SUPPORT FACILITY

Addressing Climate Change in Transport

Volume 1: Pathway to Low-Carbon Transport

Jung Eun Oh, Maria Cordeiro, John Allen Rogers, Khanh Nguyen,

Daniel Bongardt, Ly Tuyet Dang, and Vu Anh Tuan

FINAL REPORTSeptember 2019

AddressingClimateChangeinTransport

Volume1:PathwaytoLow-CarbonTransport

VietnamTransportKnowledgeSeriesSupportedbyAUSTRALIA–WORLDBANKGROUPSTRATEGICPARTNERSHIPINVIETNAM,GOVERNMENTOFGERMANYandNDCPARTNERSHIPSUPPORTFACILITY

AddressingClimateChangeinTransport

Volume1:PathwaytoLow-CarbonTransport

JungEunOh,MariaCordeiro,JohnAllenRogers,KhanhNguyenDanielBongardt,LyTuyetDang,VuAnhTuan

FINALREPORT

September2019

©2019TheWorldBankandDeutscheGesellschaftfürInternationaleZusammenarbeitGmbH

1818HStreetNW,WashingtonDC20433

Telephone:202-473-1000;Internet:www.worldbank.org

This work is a product of the staff of The World Bank and the Deutsche Gesellschaft fürInternationaleZusammenarbeit (GIZ)withexternalcontributions.The findings, interpretations,and

conclusions expressed in thiswork donot necessarily reflect the viewsof TheWorldBank and itsBoard of Executive Directors. The World Bank or GIZ does not guarantee the accuracy orcompleteness of information in this document, and cannot be held responsible for any errors,

omissionsorlosses,whichemergefromitsuse.

Theboundaries,colors,denominationsandotherinformationasshownonanymapinthisworkdonot imply any judgment on the part of TheWorld Bank or GIZ concerning the legal status of any

territoryortheendorsementoracceptanceofsuchboundaries.

Nothinghereinshallconstituteorbeconsideredtobea limitationuponorwaiveroftheprivilegesandimmunitiesofTheWorldBank,allofwhicharespecificallyreserved.

AllqueriesonrightsandlicensesshouldbeaddressedtothePublishingandKnowledgeDivision,TheWorld Bank, 1818 H Street NW, Washington DC 20433, USA; fax: 202-522-2625; email:[email protected].

Coverphoto:WomanwaitingonhermotorbikeinHanoi,Vietnam.Credit:Beboy–stock.adobe.com.

Page|v

Contents

FiguresandTables ............................................................................................................vii

Forewords .........................................................................................................................xiWorldBankGroup.................................................................................................................................. xiEmbassyoftheFederalRepublicofGermanytotheSocialistRepublicofVietnam........................... xiii

Acknowledgments ............................................................................................................xv

AbouttheAuthors .......................................................................................................... xvii

AbbreviationsandAcronyms ...........................................................................................xix

ExecutiveSummary ......................................................................................................... 23

Chapter1:Introduction.................................................................................................... 31BackgroundandObjectives.................................................................................................................. 31TransportSectorDevelopmentinVietnam.......................................................................................... 33

Chapter2:Business-As-UsualReferenceScenario ............................................................ 41GrowthProjectionintheTransportSectorunderBAU........................................................................ 41GHGEmissionsResultsunderBAU....................................................................................................... 44

Chapter3:Scenario1—WithDomesticResourcesOnly.................................................... 49EmissionsMitigationMeasuresunderScenario1 ............................................................................... 49GHGEmissionsResultsunderScenario1 ............................................................................................. 52MarginalAbatementCostunderScenario1 ........................................................................................ 55Conclusions .......................................................................................................................................... 57

Chapter4:Scenario2—IncreasingAmbitionwithInternationalSupportandActiveEngagementofthePrivateSector ................................................................................... 59EmissionsMitigationMeasuresunderScenario2 ............................................................................... 59GHGEmissionsResultsunderScenario2 ............................................................................................. 61MarginalAbatementCostunderScenario2 ........................................................................................ 65Conclusions .......................................................................................................................................... 67

Chapter5:Scenario3—PushingTransformationoftheSectorwithLargerSupportfromInternationalResourcesandStrongPrivateSectorEngagement ...................................... 69EmissionsMitigationMeasuresunderScenario3 ............................................................................... 69GHGEmissionsResultsunderScenario3 ............................................................................................. 72MarginalAbatementCostunderScenario3 ........................................................................................ 75Conclusions .......................................................................................................................................... 77

Chapter6:CostofImplementation .................................................................................. 79MarginalAbatementCostMethodology.............................................................................................. 79MarginalAbatementCostResultsforEachMeasure........................................................................... 80

Promotionofbiofuel......................................................................................................................... 80Promotionofelectricmotorbikes ..................................................................................................... 81

Page|vi

Newvehiclefueleconomystandards ............................................................................................... 83Expansionofbussystems ................................................................................................................. 85Promotionofelectricbuses .............................................................................................................. 87ExpansionoftheBRTsystem............................................................................................................ 88Deploymentofmetrosystems.......................................................................................................... 90Promotionofelectriccars................................................................................................................. 91Freightmodalshiftfromroadtoinlandwaterwayandtocoastalshipping .................................... 94Modalshiftfromroadtorailway ..................................................................................................... 97IntroductionofCNGbuses................................................................................................................ 99Improvementoftruckloadfactor .................................................................................................. 100

MarginalAbatementCostCurve ........................................................................................................ 101

Chapter7:ConclusionsandPolicyRecommendations.....................................................107

Appendices .....................................................................................................................111A.GHGEmissionsInventory ............................................................................................................... 111B.ScenarioFormulation ..................................................................................................................... 112C.ModelingMethodology.................................................................................................................. 113D.KeyDataandAssumptions ............................................................................................................ 120E.MACCMethodology ....................................................................................................................... 124F.CoordinationofTechnicalAssistance ............................................................................................. 129

Page|vii

FiguresandTables

FIGURES

FigureE.1.GHGEmissionsfromTransportperCapitaandperGDP(2014–2030) .............................. 23

FigureE.2.CO2EmissionsProjectionbyTransportSubsectorsunderBAUScenario........................... 25

FigureE.3.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1......................... 26



FigureE.6.ComparisonofCO2EmissionsbetweenBAUandMitigationScenarios1,2and3 ............ 28

Figure1.1.FuelConsumptionintheTransportSectorbyFuelType ................................................... 34

Figure2.1.ModelingFramework ......................................................................................................... 41

Figure2.2.ProjectionofPassenger-KilometersTraveledunderBAU .................................................. 42

Figure2.3.ProjectionofFreightTon-KilometersTransportedunderBAU .......................................... 42

Figure2.4.ProjectionsofRoadDistancesTraveledbyVehicleType ................................................... 43

Figure2.5.ProjectionsofRoadVehicleFleetNumbersbyVehicleType ............................................. 43

Figure2.6.ProjectedCO2EmissionsbyTransportSubsectorsunderBAU........................................... 45

Figure2.7.ProjectedGHGEmissionsperGDPandperCapitaunderBAU .......................................... 46

Figure3.1.TheMitigationActionsAnalyzedunderScenario1............................................................ 49

Figure3.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario1 ............. 51

Figure3.3.CO2EmissionsbySubsectorsunderScenario1 ................................................................. 52

Figure3.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1......................... 53

Figure3.5.ComparisonofCO2EmissionsbetweenBAUandScenario1 ............................................. 54

Figure3.6.MACCResultsunderScenario1forAnalysisPeriod2014–2030and2014–2050.............. 56



Figure4.3.TotalCO2EmissionsbyTransportSubsectorsunderScenario2 ....................................... 62

Figure4.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario2 ......................... 64

Figure4.5.ComparisonofCO2EmissionsbetweenBAUandScenarios1and2.................................. 64

Figure4.6.MACCResultsunderScenario2,forAnalysisPeriod2014–2030and2014–2050............. 66



Figure5.3.TransportCO2EmissionsbySubsectorsunderScenario3 ................................................. 72

Page|viii

Figure5.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario3......................... 74

Figure5.5.ComparisonofCO2EmissionsbetweenBAUandScenarios1,2,and3............................. 75

Figure5.6.MACCresultsunderScenario3,forAnalysisPeriod2014–2030and2014–2050 ............. 76

Figure6.1.AFastChargerattheMinistryofIndustryandTradeBuildinginHanoi ............................ 93

FigureA-A.1.Bottom-UpApproachCalculatingtheGHGEmissionsinTransportSector .................. 111

FigureA-C.1.IntegrationofModelsforScenariosCalculation .......................................................... 115

FigureA-C.2.CalculationFlowSchematicforPassengerCarsandTwo-Wheelers ............................ 116

FigureA-C.3.CalculationFlowSchematicforPassengerMassTransport.......................................... 117

FigureA-C.4.CalculationFlowSchematicforOn-RoadFreightTransport......................................... 117

FigureA-C.5.CalculationFlowSchematicfortheFuelEfficiencyandEmissionsCalculationsforAllOn-RoadVehicles ................................................................................................................................ 118

FigureA-C.6.CalculationFlowSchematicforPassengerandFreightRailTransport ......................... 118

FigureA-C.7.CalculationFlowSchematicforWaterbornePassengerandFreightTransport ........... 119

FigureA-C.8.CalculationFlowSchematicforCivilAviation ............................................................... 119

FigureA-D.1.PopulationProjectionfrom2015to2030 .................................................................... 120

FigureA-D.2.TotalRoadVehicleFleetinVietnamfrom2014to2030.............................................. 121

FigureA-D.3.PassengerKilometerTraveled(PKT)from2014to2030.............................................. 122

FigureA-D.4.FreightTon-KilometerTransported(FTKT)from2014to2030.................................... 123

FigureA-E.1.MarginalAbatementCostCurveComponents ............................................................. 124

Figure A-F.1. Institutional Arrangements and GIZ/WBG Technical Assistance: Flowchart for Project

Implementation ............................................................................................................................ 129

TABLES

TableE.1.NPVofAdditionalInvestmentNeedsbyMitigationScenarioandAnalysisPeriod ............. 29

Table1.1.DistancesTraveledbyPassengersandFreightinVietnamin2014..................................... 33

Table1.2.FuelConsumptionbyFuelTypeinTransportSectorinVietnam......................................... 34

Table1.3.GHGMitigationStrategiesintheTransportSector ............................................................. 35

Table1.4.ListofGHGMitigationOptionsConsideredinScenarioAnalysis ........................................ 36

Table 2.1. Projected Energy Consumption by Source in Transport Sector under Business-As-Usual

Scenario........................................................................................................................................... 45

Table2.2.TransportCO2EmissionsinVietnamunderBusiness-As-UsualScenario ............................ 45

Table2.3.ProjectedShareofCO2EmissionsbyTransportSubsectors ................................................ 46

Table3.1.LevelofAmbitionforMitigationMeasuresAnalyzedunderScenario1 ............................. 50

Page|ix

Table3.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario1............... 51

Table3.3.TransportCO2EmissionsbySubsectorunderBAUandScenario1 .................................... 52

Table3.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1 .......................... 53

Table3.5.ComparisonofCO2EmissionsbetweenBAUandScenario1 .............................................. 54

Table3.6.MACCResultsunderScenario1,forAnalysisPeriod2014–2030and2014–2050.............. 55


Table4.2.ProjectEnergyConsumptionbySourceinTransportSectorunderScenario2................... 61

Table4.3.TransportCO2EmissionsbySubsectorunderScenario2 .................................................... 62

Table4.4.ReductionofCO2EmissionsbyEachMitigationOptionAnalyzedinScenario2 ................. 63

Table4.5.ComparisonofCO2EmissionsfromTransportbetweenBAUandScenario2 ..................... 64

Table4.6.MACCResultsunderScenario2,forAnalysisPeriod2014–2030and2014–2050.............. 65


Table5.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario3............... 71

Table5.3.TransportCO2EmissionsbySubsectorunderScenario3 ................................................... 72

Table5.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario3 .......................... 73

Table5.5.ComparisonofTransportCO2EmissionsinBAUandScenario3 ......................................... 74

Table5.6.MACCresultsunderScenario3,forAnalysisPeriod2014-2030and2014-2050 ................ 75

Table6.1.MACCalculationSummaryforPromotionofBiofuel .......................................................... 81

Table6.2CostAssumptionsforElectricScooters(LightMotorcycles) ................................................ 82

Table6.3.MACCalculationSummaryforPromotionofElectricMotorcycles ..................................... 83

Table6.4.ImplementationCostsforNewVehicleFuelEconomyStandards....................................... 84

Table6.5.MACCalculationSummaryforNewFuelEconomyStandards ............................................ 85

Table6.6.CostEstimateforaBusRoute ............................................................................................. 86

Table6.7.MACCalculationSummaryforExpansionofBusSystems .................................................. 87

Table6.8.CostEstimateforElectricBuses .......................................................................................... 87

Table6.9.MACCalculationSummaryfortheDeploymentofElectricBuses....................................... 88

Table6.10.CostAssumptionsforBRTSystemUsingDieselBuses ...................................................... 89

Table6.11.CostAssumptionsforBRTSystemUsingElectricBuses .................................................... 89

Table6.12.MACCalculationSummaryforExpansionofBRTSystems ................................................ 90

Table6.13.CostAssumptionsforMetroSystemsinVietnam ............................................................. 90

Table6.14.MACCalculationSummaryforDeploymentofMRTSystem............................................. 91

Table6.15.SummaryCostAssumptionsforElectricCars .................................................................... 92

Page|x

Table6.16.MACCalculationSummaryforPromotionofElectricCars................................................ 93

Table6.17.CostAssumptionsforInducingModalShiftofFreightfromRoadtoInlandWaterwaysand

CoastalTransport ............................................................................................................................ 95

Table6.18.MACCalculationSummaryforModalShiftfromRoadtoIWTandCoastalWaterwaysforScenario1........................................................................................................................................ 96

Table6.19.MACCalculationSummaryforModalShiftfromRoadtoIWTandCoastalWaterwaysforScenario2........................................................................................................................................ 96

Table6.20.MACCalculationSummaryforModalShiftfromRoadtoIWTandCoastalWaterwaysfor

Scenario3........................................................................................................................................ 97

Table6.21.CostAssumptionsforDeploymentofRailPassengerandFreightSystems...................... 98

Table6.22.MACCalculationSummaryforModalShiftfromRoadtoRailforScenario2 ................... 99

Table6.23.MACCalculationSummaryforModalShiftfromRoadtoRailforScenario3 ................... 99

Table6.24.CostAssumptionforDeploymentCNGBuses ................................................................. 100

Table6.25.MACCalculationSummaryforDeploymentofCNGBuses ............................................. 100

Table6.26.MACCalculationSummaryforImprovementofTruckLoadFactor ................................ 101

Table6.27.MitigationPotentialandCostsofMitigationbyScenarios.............................................. 102

Table7.1.NPVofAdditionalInvestmentNeedsbyMitigationScenarioandAnalysisPeriod ........... 107

Table7.2.CumulativeCO2EmissionsReductionbyMitigationScenarioandAnalysisPeriod........... 108

TableA-C.1.VietnamTransportStudiesUsingEFFECT ...................................................................... 114

TableA-C.2.CalculationFlowSchematicsbySector .......................................................................... 116

TableA-D.1.PassengerKm-TraveledandFreightTon-KmTransportedin2014 .............................. 122

TableA-E.1.FuelPrices ...................................................................................................................... 126

TableA-E.2.RailwayCostsAssumptions ............................................................................................ 127

TableA-E.3.VehicleEmissionsStandards .......................................................................................... 127

TableA-E.4.FuelEconomyforCars.................................................................................................... 127

TableA-E.5.RoadMapforFuelEconomyforCars............................................................................. 128

TableA-E.6.FuelEconomyforMotorcycles....................................................................................... 128

Page|xi

Forewords

WorldBankGroup

ClimatechangeissettohaveprofoundeffectsonVietnam’sdevelopment.Withnearly60percentof

its land area and 70 percent of population at risk ofmultiple natural hazards, Vietnam globally isamongthemostvulnerablecountriestobothchronicandextremeevents.Overthepast25years,extremeweather events have resulted in 0.4 to 1.7 percent of GDP loss,which climate change is

predicted to steeply rise by 2050. At the same time, as Vietnam’s economy grows, the country isbecomingasignificantemitterofgreenhousegases.WhileVietnam’sabsolutevolumeofemissionsisstill small compared to that of larger and richer countries, emissions are growing rapidly and

disproportionate to its economy size. Vietnam is the 13thmost carbon intensive economy in theworld, measured in terms of emissions per GDP, and 4th among the low- and middle-income

countriesinEastAsia.

Thetransportsectorplaysacriticalroleintheserecenttrends.Asteepriseinincomeandeconomicgrowthhasledtorapidmotorization:Thecountryofaround96millionpeopleisalsohometonearly

40 million vehicles, including 35 million motorbikes. While car ownership is still relatively low inVietnam,asincomerisescarsarequicklyreplacingmotorbikes,especiallyinthelargestcities.Publictransportmodalshareremainspersistentlylow,partlyduetothelowlevelofnetworkdevelopment

and partly to the convenience and affordability of two-wheeler-based mobility. Thanks to itseconomicsuccessandrapidintegrationwiththeinternationaltrade,cargotransportationinVietnamhas seen remarkablegrowth in the recent years.Vietnam’s long coastal linesandextensive inland

waterwaynetworkhavebeenextensively used for themovementof goods; however, theirmodalsharevis-à-visroadtransportisdeclining.

Vietnam’stransportnetwork,whichhasseenanimpressiveexpansionoverthepasttwodecades,is

increasinglyvulnerabletothe intensifyingclimatehazards.Today,Vietnam’sroadnetworkextendstoover400,000km,muchofwhichwasnotbuilttowithstandextremehazardscenarios,whichareexpectedtobecomemorefrequentduetoclimatechange.Withouteffortstoimprovetheresilience

ofthebuiltnetwork,Vietnam’sachievementsinprovidinguniversalaccesstoitsruralcommunitiesmay be undermined. Moreover, resilience of connectivity is critical to the continued success ofVietnam’s economy, which heavily relies on external trade and would increasingly depend on

seamlessrural-urbanlinkages.

Inthisanalyticalwork,AddressingClimateChangeinTransportforVietnam,carriedoutbytheWorldBank and several other partners with support from theMinistry of Transport of

Vietnam, the study aims to set out a vision and strategy for climate-smarttransport, in order to minimize the carbon footprint of the

sector while ensuring its resilience against future risks. The

analytical findingsandrecommendationsarepresentedin two volumes of the report: Volume 1—Pathway to

Page|xii

LowCarbonTransportandVolume2—PathwaytoResilientTransport.ThefirstvolumeprovideshowVietnam can reduce its carbon emissions by employing amix of diverse policies and investments,

under varying levels of ambition and resources. The second volume provides a methodologicalframeworktoanalyzenetworkcriticalityandvulnerability,andtoprioritizeinvestmentstoenhanceresilience.

Thesetworeportvolumeshavebeenpreparedatacriticaltime,wheretheGovernmentofVietnamisworkingtoupdateitsNationallyDeterminedContributionandsetoutitsnextmedium-termpublicinvestment plan for the period of 2021 to 2025.We hope that these findings can provide useful

insightsandspecificrecommendationstowardsthesecriticaldocuments,contributingtoVietnam’sachievementindevelopingalow-carbonandresilienttransportsector.

GuangzheChen OusmaneDione

GlobalDirector CountryDirector

TransportGlobalPractice Vietnam

Page|xiii

EmbassyoftheFederalRepublicofGermanytotheSocialistRepublicofVietnam

This report is the product of a collaborative effort by the Vietnamese Ministry of Transport’sDepartmentfortheEnvironment,theWorldBankandtheDeutscheGesellschaft für InternationaleZusammenarbeit GmbH (GIZ) on behalf of the German Federal Ministry of Environment, Nature

Conservation and Nuclear Safety (BMU). It also marks three years of cooperation between theMinistryofTransportandtheGermanGovernment-funded“AdvancingTransportClimateStrategies”project, which has focused on providing support for the systematic assessment and reduction of

greenhousegas(GHG)emissionsinthetransportsector.

Vietnam’s social and economic achievements are well known and mobility is key for furtherdevelopment. But progress has come at a cost: a growing demand for energy has led to a sharp

increase inGHGemissions,amajorcontributingfactortorisingglobaltemperatures.ThetransportsectorisamajorconsumerofenergyinVietnam.

Risingnumbersof roadvehiclesarecausingseriouscongestionandairpollution incities,affecting

the wellbeing of millions of people. If policy measures are not taken, GHG emissions from thetransportsectorareexpectedtotripleby2030tonearly90milliontonscarbondioxideequivalent(CO2e).

The findings in the report are alarming. Even in the most ambitious scenario, the emission fromtransport will still rise to nearly 70 million tons CO2e. Clearly, a new way of living, including arethinkingofmobility,isneeded.Thisisachallenge,notonlyinVietnam,butworldwide.

Therefore, I believe, this report contributes to Vietnam’s ongoing Nationally DeterminedContribution (NDC) Review and Update process lead by the Ministry of Natural Resources andEnvironment, and shows the importance of evidence-basedmitigation policies for theMinistry of

Transport’s2021–2030TransportClimateActionPlan.

IwouldliketotakethisopportunitytothanktheMinistryofTransport,especiallytheDepartmentforthe Environment, for its continuous commitment towards achieving sustainable transport in

Vietnam.Suchcommitmentisvitalforsuccessfullycombatingclimatechange.

Dr.GuidoHildner

AmbassadorExtraordinaryandPlenipotentiaryoftheFederalRepublicofGermanytotheSocialistRepublicofVietnam

Page|xv

Acknowledgments

This reportwaspreparedby theTransportGlobalPracticeand theEastAsiaandPacificRegionof theWorld Bank, and theDeutscheGesellschaft für Internationale Zusammenarbeit (GIZ) under its project“Advancing Transport Climate Strategies (TraCS) in Viet Nam” as part of the International Climate

Initiative (IKI). TheBundesministerium fürUmwelt,NaturschutzundnukleareSicherheit (BMU),or theFederalMinistryfortheEnvironment,NatureConservation,andNuclearSafetyofGermany,supportsthisinitiativeonthebasisofadecisionadoptedbytheGermanBundestag.Furtherinformationontheproject

contextunderTraCScanbefoundathttps://www.changing-transport.org/project/tracs.

ThepreparationofthereportwasledbyDr.JungEunOh,seniortransportspecialistatTheWorldBank,andDanielBongardt,senioradvisoratGIZ.Theteamincludes,attheWorldBank:MariaCordeiro,John

RogersandNguyenQuocKhanh;atGIZ:AnnaSchreyoegg,LyTuyetDang,andElenaScherer.ConsultantsVuAnhTuan,AnMinhNgoc,DiepAnhTuan,andPhamDuyHoangatUniversityofCommunicationsandTransport; and LeAnhTuanandTranQuangVinhatHanoiUniversityof ScienceandTechnologyalso

contributedinputstothisreport.

The team extends its appreciation for the guidance of theWorld Bankmanagement, Guangzhe Chen(GlobalDirector,TransportGlobalPractice),FranzR.Drees-Gross, (Director,TransportGlobalPractice),

OusmaneDione (VietnamCountryDirector),andAlmudWeitz (TransportPracticeManager,SoutheastAsiaandthePacific).TheteamalsoextendsitsappreciationfortheguidanceofGIZ´smanagement.

The team conducted the study in collaborationwith theGovernmentofVietnamand appreciates the

strongsupportandadvicegenerouslyprovidedbyMr.LeDinhTho,viceministeroftransport.TranAnhDuong(DirectorGeneral),Mrs.NguyenThiThuHang(DeputyDirector),Mr.VuHaiLuu(Official),andMrs.DoanThiHongTham(Official),andMr.MaiVanHien(Official)attheDepartmentofEnvironment,with

knowledge sharing provided by Ministry of Transport. Several government entities and organizationsprovided vital inputs, including the Directorate for Roads of Vietnam, Vietnam Inland WaterwaysAdministration,VietnamMaritimeAdministration,CivilAviationAuthorityofVietnam,VietnamRailway

Authority,andVietnamRegister.

The work benefitted from the advice provided by the following peer reviewers: Stephen Ling (LeadEnvironmentalSpecialist),CeciliaM.Briceno-Garmendia(LeadEconomist),NehaMukhi (SeniorClimate

ChangeSpecialist),andIanHalvdanRossHawkesworth(SeniorGovernanceSpecialist)attheWorldBank,andRobinBednall(FirstSecretary)andDuc-CongVu(SeniorInfrastructureManager)attheGovernmentof Australia. Kara Watkins (WBG Communications Consultant) thoroughly copyedited the report for

consistencyandreadability,andChiKienNguyen(TransportSpecialist)reviewedtheVietnamesetranslationforaccuracy,forwhichtheteamisgrateful.

The team would like to thank the Government of Germany, the

Government of Australia, and the NDC Partnership SupportFacilityfortheirgeneroussupportandfundingtowardthis

analyticalworkandpublication.

Page|xvii

AbouttheAuthors

JungEun“Jen”OhisaseniortransporteconomistattheWorldBank.Withabackgroundintransport

engineeringandeconomics,Jenhasledanumberofinvestmentprojectsandtechnicalassistanceforvariousclientcountries inSoutheastAsia,CentralAsia,Sub-SaharanAfrica,andEurope,coveringabroad range of transport sector issues. Jen served as a transport cluster leader for Vietnam from

2016 to 2019, overseeing and coordinating a large portfolio of World Bank-financed projects inVietnam’s transport sector, and led several knowledge pieces on climate change in transport,transportconnectivity,urbanmobility,and infrastructurefinancing.JenholdsanMSc ineconomics

and a PhD in transportation systems, andhas authored several articles, including a chapter in thebook,TheUrbanTransportCrisisinEmergingEconomies(2017),publishedbySpringerInternational.

MariaCordeiro isaformerseniortransportspecialistattheWorldBankandcurrentlyaconsultant

for the World Bank. Maria works with project teams globally to integrate climate changeconsiderationsinthepreparationanddesignoflendingoperations,usingtoolslikeGHGaccounting,shadow price of carbon, and climate and disaster risk screening. Maria also contributes to the

provisionoftechnicalassistancetoclientcountriestosupportplanningandthedeploymentoflow-carbonresilienttransportsystems.BeforejoiningtheWorldBank,Mariaworkedwithgovernmentsin LatinAmerica,Middle East, Europe in the analysis, design anddeployment of policies, planning

and projects in the fields of climate change, air quality, water and waste management, andbiodiversity conservation.Maria alsoworkedwith othermultilateral development banks, bilateralagencies,andresearchcentersinpolicyandplanningaswellasinthemanagementofprogramsand

projectsintheenvironment,transport,andinternationaldevelopmentfields.

JohnAllenRogers isanengineerspecializedinemissionsandlowcarbondevelopment,particularlyintransportandenergy.Throughmultilateraldevelopmentbanksandbilateralorganizations,hehas

providedtechnical support tomany low-andmiddle-incomecountries toenhancegreengrowth—lowemissions, and low-carbondevelopmentplanning—for the transport andenergy sectors.WiththeWorld Bank, he has designed and applied emissions and energymodels formany low-carbon

developmentstudiescoveringthepowersectorandtransport inLatinAmerica,Europe,Africa,andAsia,analyzinguseractivityandresultantemissionswithassociatedcostsandbenefits,intransportas well as in the power, industry, and building sectors (nonresidential and household energy

demand).

Khanh Nguyen, an energy expert, hasworked on a number of projectswith various internationaldonor organizations in the last few years. He has more than 15 years’ experience in sustainable

development and related issues, such as energy systemmodeling, renewable energyproject development, rural electrification, energy efficiency, and GHG emissions

inventoryandmonitoring.Currently,Khanh is leadinga studyon

future power sources to advocate sustainable policiesfor Vietnam. Prior to that, he provided support to the

Page|xviii

UNDP-led effort on the formulation of an action plan to implement the renewable energydevelopment strategy in Vietnam. Khanh earned a bachelor’s degree in energy economics and

energyplanningfromtheUniversityofScienceandTechnologyinHanoiin1997.In2001,heearneda master’s degree in renewable energies from the University of Oldenburg in Germany, and adoctorateinenergysystemmodeling,alsofromtheUniversityofOldenburg,in2005.

Daniel Bongardt, basedatGIZheadquarters inBonn,Germany, is senior advisoron transport andclimatechangeandheadoftheTraCSproject.From2011to2015,hewasprogramdirectoroftheSustainableTransportProgramme,aGIZinitiative,inBeijing.Hisresponsibilitiesincludedprojectson

urbantransportdemandmanagement,transport,andclimatechangeaswellaselectricmobility.Heworked on policy development, scenario building, andmonitoring of greenhouse gas emissions inurbanmobility and freight transport inChina.Before coming toBeijing,he servedas seniorpolicy

advisor at GIZ headquarters,where he developedGIZ’s transport and climate change agenda andheaded a project on Nationally Appropriate Mitigation Actions (NAMAs) in the transport sector.Daniel startedhis career in2001asa senior researcherat the transportdivisionof theWuppertal

Institute for Climate, Environment and Energy, a major German think tank on sustainabledevelopment.Danielholdsamaster’sdegreeinpoliticalsciences.

LyTuyetDang,basedinHanoi,Vietnam,isprojectofficerontransportandclimatechangeoftheGIZ

TraCS project. Previously, she worked as a consultant for a green freight project under TA 7779,whichADBimplementedinVietnamandLaoPDR.Sheworkedontheinitiativepilotinggreenfreightfor truckingcompaniesandassociations inbothVietnamandLaoPDR,monitoring thegreenhouse

gases of green freight measures, training eco-drive skills for drivers, and providing policyrecommendation for the governments. Shealsoworked inCDMprojects relating to transport and

clean energy, and prepared documents for companies following the requirement of the WorldCommissiononDams.Sheearnedamaster’sdegreeinscienceofclimatechangein2011.

Vu Anh Tuan has worked for 12 years as a lecturer and independent consultant in the field of

transportation. He is familiar with transport modeling software such as PTV VISUM, JICA-Strada,Omni-Trans,VISSIM,VisWalk,EFFECTandengineeringsoftware likeAutoCADandMapInfo.Hehasmanaged infrastructure performances, designed travel surveys, performed transport demand

modeling,preparedbusinessplansandengineeringdesigns,andtookonthepositionofteamleaderinseveral transportmasterplanstudies.Heoversawmanymajorpublic-fundedcapital investmentprogramsofupto$70millionfromdiversefundingsources.Hemanagedthetransportmasterplan

forthecityofHanoiin2007and2012aswellasforHaNamin2006.Furthermore,hepreparedthetrafficdemandforecastforthetechnicalprefeasibilityofHoChiMinhCity’sBus-Rapid-Transitsystemand developed Da Nang’s transport model. He conducted accessibility surveys and facilities

assessmentsurroundingtheUMRTstations.In2018and2019heworkedasaconsultantforTraCS.Mr.VuAnhTuanearnedamaster’s in transportplanningandtrafficengineering,withan

emphasis in trafficmodeling, from theNationalUniversityofRoad&Bridgeand the

UniversityofParis.

Page|xix

AbbreviationsandAcronyms

ASI Avoid-Shift-Improve

ADB AsianDevelopmentBank

BAU Businessasusual

BRT Busrapidtransit

BY Baseyear

CIEM CentralInstituteofEconomicManagement

CNG Compressednaturalgas

CO2 Carbondioxide

DoE DepartmentofEnvironment,MinistryofTransport

EEA EuropeanEconomicArea

EFFECT EnergyForecastingFrameworkandEmissionsConsensusTool

EMEP EuropeanMonitoringandEvaluationProgram

FTKT Freightton-kmtransported

GDP Grossdomesticproduct

GIZ DeutscheGesellschaftfürInternationaleZusammenarbeit

GSO GeneralStatisticOffice

HBEFA HandbookEmissionFactorsforRoadTransport

HCV Heavycommercialvehicles

ICAO InternationalCivilAviationOrganization

ICD Inlandcontainerdepot

IPCC IntergovernmentalPanelonClimateChange

IWT Inlandwaterwaytransport

IWW Inlandwaterway

JICA JapanInternationalCooperationAgency

LCV Lightcommercialvehicles

LEAP TheLong-RangeEnergyAlternativesPlanningmodel

MAC Marginalabatementcost

MACC Marginalabatementcostcurve

MMHE Meanmonthlyhouseholdexpenditure

MoNRE MinistryofNaturalResourcesandEnvironment

Page|xx

MoIT MinistryofIndustryandTrade

MoT MinistryofTransport

MRT Metrorailtransit

MtCO2e Million[metric]tonscarbondioxideequivalent

NAMA NationallyAppropriateMitigationActions

NDC NationallyDeterminedContribution

NEH NationalExpressHighway

NPV Netpresentvalue

OECD OrganizationforEconomicCo-operationandDevelopment

O&M Operationsandmaintenance

PC Passengercar

PKT Passenger-kmtransported

tCO2 Tonscarbondioxide

TRaCS AdvancingTransportClimateStrategies

UNFPA UnitedNationsPopulationFund

VAMA VietnamAutomobileManufacturersAssociation

VHLSS Vietnamhouseholdlivingstandardsurvey

VISUM VISUMsoftware

VNRA VietnamRailwayAuthority

VR VietnamRegister

WBG WorldBankGroup

Page|xxi

CURRENCYMEASURE

CurrencyUnits—US$andVND

WEIGHTANDMEASURES

Metricsystem

BASELINEDATAYEAR

Commodityfreights—2014

Macroeconomicdata—2014and2016

Censusdata—2014

EXCHANGERATES

US$1,2014=21,890VND

Page|23

ExecutiveSummary

Vietnam’sremarkablesuccessinmitigatingpovertyandpromotingeconomicdevelopmentoverthepast decades has been enabled by the rapid development of supporting economic infrastructure,including transport. This accelerated increase in the mobility of people, goods, and services has

benefitedboth theurbanandruralpopulations.Since1992, the lengthofVietnam’s roadnetworkhasincreasedsignificantlyandreachedover400,000kmasof2016;asaresultofthisendeavor,thenumberofcommuneswithoutaccesstoall-weatherroadsdroppedfrom606 in1997toonly65 in

2016.

Partly thanks to this success, the transport sector is becoming a large and growing contributor tototalgreenhousegas(GHG)emissionsinVietnam,accountingfor18percentoftotalCO2emissionsin

2014.1 Even though the carbon intensity of the economy is coming down (figure E.1, panel a),increasing per capita income—coupled with population growth and rural/urban migration—aredriving thedemand formobility,whichwould lead to continued growth in carbon intensity in the

transport sector over the comingdecades (figure E.1, panel b).Under thebusiness-as-usual (BAU)scenario, it isestimatedthatcarbonemissions fromtransportpercapitawouldrisesharply,by2.5fold,between2014and2030.

FigureE.1.GHGEmissionsfromTransportperCapitaandperGDP(2014–2030)

Source:WorldBankandGIZdata.DataproducedusingtheEFFECTmodel(seeappendixCformoreinformationonEFFECT).

As one of the developing countries most affected by climate change, Vietnam is committed toaddressing both mitigation and adaptation. In 1994 the country ratified the United Nations

FrameworkConventiononClimateChange (UNFCCC), in2002 theKyotoProtocol (KP), in2015 theDoha Amendment, and in 2016 approved the Paris Agreement. Vietnam established the National

ClimateChangeCommittee(NCCC)in2012tocoordinatenationalactiononclimatechangeandfulfillreportingcommitmentstotheUNFCCC.

In its IntendedNationally Determined Contribution (INDC orNDC) submitted in 2015, the country

committed to an 8 percent reduction in GHG emissions against baseline by 2030, and to raiseambitionto25percentreduction,contingentonreceivinginternationalsupport.VietnamsubmitteditsthirdnationalcommunicationinFebruary2019andiscurrentlypreparingarevisionofitsNDCfor

submission in September 2019. The transport sector would be responsible for a pro-rataunconditionalreductioninGHGemissionsof8percentin2030againstthesector’sBAUtrajectory.

Page|24

In the present technical assistance, the World Bank and GIZ collaborated with the Ministry ofTransport(MoT)ofVietnamtohelpinformtheirfutureNDCmodificationthroughtheselectionand

prioritization of policies and measures that mitigate GHG emissions. The activities and outputsincludedthedevelopmentofadetailedGHGemissionsinventoryforthetransportsector;scenario-based,bottom-upanalysisoftransportactivitiesandresultantemissionsfromabaseyearof2014to

2030 and beyond to 2050; and an analysis of marginal abatement cost (MAC) for mitigationmeasurestohelpprioritizebasedontheircost-effectiveness.

Boththeemissioninventoryandthescenario-basedemissionsbottom-upmodelingweredeveloped

with tools specifically modified for Vietnam, with consideration of the data availability andinstitutional arrangement. The scenarios were developed through extensive stakeholderconsultation,throughwhichaconsensuswasbuiltaroundwhatisachievablewithincertainlevelsof

resourcesandexistingregulatoryframework.Inadditiontothescenariodevelopmentandanalysis,localexpertsandofficialsweresupportedsothatthecountrycouldcontinuetomakeuseofthesecalibratedtoolsforfutureevaluationsandmeasurement,reporting,andverification(MRV)purposes.

Within the overarching framework of the country’s NDC, four scenarios were developed andanalyzed—BAU and Mitigation Scenarios 1, 2 and 3—each corresponding to varying levels ofambitionintermsofemissionsreductiontargetsandresourcesrequiredtoachievethem.TheBAU

forecastshowshowtransportactivityandemissionscanbeexpectedtochangeunderanagreedsetofmacro assumptions,which are uniformly used across the threemitigation scenarios. The threemitigation scenarios include increasingly ambitious sets of mitigation “levers”—policies or

investments that would provide sustainable transport solutions and lead to a reduction in GHGemissions:Scenario1includessomepoliciesandmeasuresintheexistingmasterplanandwouldbe

implemented only with domestic resources; Scenario 2 is also confined within the scope of theexistingmasterplanbutwouldrequireadditional resources from internationalsourcesandprivatesector participation for implementation; and Scenario 3 includes ambitious measures outside the

existingmasterplan.

BAU includesallpoliciesand interventions thatwereenacteduptoand includingthebaseyearof2014,withnoadditionaldeploymentofpoliciesandmeasuresafterthatdatetargetedatmitigating

GHG emissions. Results show that in 2014 under BAU conditions, transport sector CO2 emissionsincrease from33.2million tonsCO2 in 2014 to89.1million tons in 2030.2 Throughout this period,road isthe largestemitterwith26.4milliontonsCO2 in2014and increasingto71.7milliontons in

2030. This is partly due to the relatively high share of road traffic, which carries 94 percent ofpassengers and76percentof freight tons,3 but also its highenergy intensityperpassenger-kmorfreightton-kmcomparedtowaterborneorrailtransport.

Page|25

FigureE.2.CO2EmissionsProjectionbyTransportSubsectorsunderBAUScenario

Mitigation Scenario 1 considers mitigation policies and measures that are foreseen in Vietnam’sNational Transport Master Plan and can be implemented using domestic resources. They includemodal shifts towards public transport only in the large cities to achieve the targets set out in the

masterplan;improvementsinvehiclefuelefficiencyandemissionstechnology;shiftstowardslowercarbonfuels(compressednaturalgas,orCNG,usedin623urbanbuses,ethanolE5in40percentofgasoline sales up to the supply cap for ethanol of 145,000 m3); and promotion of electric two-

wheelers.Freightmodalshiftisconsideredfromroadtoinlandwaterwaysandnearcoastalshipping.

The combinationof thesemeasures reduces the sector’s CO2 emissions in 2030 from89.1 to 81.1million tons CO2; a reduction by 9 percent compared to BAU. Policies andmeasures that improve

vehiclefueleconomyhavethehighestpotentialforGHGemissionsreductions,at5.1milliontonsofCO2.Otheractionssuchasmodalshiftfromroadtowaterwaysandfromprivatetopublictransport,andtheshifttotheelectricvehiclesalsogreatlycontribute,asshowninfigureE.3.

Mostofthemeasureswouldbringabouteconomicbenefitsgreaterthaneconomiccostsduetotheimprovementinenergyefficiencyoftransportresultinginnegativemarginalabatementcosts.Modalshift from road to waterborne transport would entail most economic benefits, followed by

introduction of lower emissions vehicle technologies such as through electric vehicles, CNG busesand stricter fuel economy standards.Over theperiod from2014 to 2050, all themeasures exceptmetro and bus rapid transit (BRT) development have negative marginal costs, providing strong

economicjustificationforimplementation.

0

10

20

30

40

50

60

70

80

90

2014 2016 2018 2020 2022 2024 2026 2028 2030

MilliontonsCO

2

Road Rail Water NationalAir Othertransport

Page|26

FigureE.3.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1

Mitigation Scenario 2 builds on the policies and measures in Scenario 1 and includes additional

measures,suchas improvementsof freighttruck loadfactors, theshift fromroadtorail transport,and a higher level of sales of electric motorcycles and cars. Such a set of measures would beimplemented with support from international resources and active participation of the private

sector. In this scenario, the totalGHGemissions in the transport sector is75.6million tonsCO2 in2030, corresponding to a decrease of 15.2 percent compared to BAU. The road sector is still thehighestcontributorofCO2emissionswith79.3percentoftotaltransportemissions.Improvementsin

vehiclefueleconomyareassessedtobringthehighestimpacts,followedbythedevelopmentoftheelectricvehiclemarket,whichcontributestoa3.5million-tonreductioninCO2emissions(seefigureE.4).SimilartoScenario1,mostofthemeasureswouldpresentnegativeMACandstrongeconomic

justificationas theywould reduce transport costsandbringefficiency inaddition to theemissionsreduction.Overtheperiodfrom2014to2050,allthemeasuresexceptmetroandBRTdevelopmenthavenegativemarginalcosts.

-

2,000

4,000

6,000

8,000

10,000

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Emission

Red

uction

(tho

usan

dtonsCO2)

1.1Newfueleconomy&emissionstandard2.1Expansionofbussystems2.2ExpansionofBRTsystems2.3DeploymentofMetrosystems3.1/3.2ModalshiftfromroadtoIWT/Coastal4.1Promotionofbiofuels(E5)4.2Promotionofelectricmotorbikes4.3IntroductionofCNGbuses

Page|27


MitigationScenario3pushesthelevelofambitionandincludesmeasuresnotcurrentlyconsideredinVietnam’sTransportSectorMasterPlan,assumingsignificantsupportfrominternationalresourcesand active participation of the private sector. Such measures include a gradual increase in E10

contentupto100percentofgasolinesalesby2030;achieving30percentofelectrictwo-wheelersinmotorbike fleet by 2030; achieving 10 percent of electric vehicles in bus sales in the period from2020 to2030;and improving the load factorof freight transport from56percent to65percent in

2024.ThesemeasureswouldresultinareductionofCO2emissionsbythetransportsectorin2030to71.2milliontonsCO2—or20percentcomparedtoBAU.RoadtransportisstillthelargestcontributortoCO2emissions,with77.8percentoftotaltransportemissionsin2030.Waterwaysfollowthiswith

10percent,andaviationwith6percent.Rail transportemits the lowestshare,with0.7percentofCO2emissions in2030(seefigureE.5).As inScenarios1and2,mostmeasureshavenegativeMAC,especially inthelongerterm,providingstrongeconomic justificationfor implementation.MACsfor

severalmeasuresunderScenario3are lowerthantheircomparatorsunderthepreviousscenarios,suggestinggreaterambitionmightresult ingreatercost-effectivenessofmeasures; inotherwords,additionalmeasurestoachievemoreambitioustargetsarelikelytobeeconomicallyjustified.

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Thou

sand

tonsCO

2

1.1Newfueleconomy&emissionstandards1.2Improvementoftruckloadfactor2.1Expansionofbussystems2.2ExpansionofBRTsystems2.3Deploymentofmetrosystems3.1/3.2ModalshiftfromroadtoIWT/Coastal3.3Modalshiftfromroadtorail4.1Promotionofbiofuels(E5)4.2Promotionofelectricmotorbikes4.3IntroductionofCNGbuses

Page|28


Insum,underthemitigationscenariosdevelopedandanalyzed in thepresentstudy, thetransport

sector of Vietnamwould be able to achievemeaningful reductions in CO2 emissions. As shown infigure E.6, against the CO2 emissions trajectories of BAU, Scenario 1 would enable a 9 percentreductioninCO2emissionsby2030;Scenario2,15percent;andScenario3,20percent.Cumulatively

until2050,VietnamcouldachieveCO2emissionsreductionof512milliontonsunderScenario1,853milliontonsunderScenario2,andover1billiontonsunderScenario3,comparedtotheBAU.

FigureE.6.ComparisonofCO2EmissionsbetweenBAUandMitigationScenarios1,2and3

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Thou

sand

tonsCO

2

1.1Newfueleconomy&emissionstandards1.2Improvementoftruckloadfactor2.1Expansionofbussystems2.2ExpansionofBRTsystems2.3Deploymentofmetrosystems3.1/3.2ModalshiftfromroadtoIWT/Coastal3.3Modalshiftfromroadtorail4.1Promotionofbiofuels(E5/E10)4.2Promosionofelectricmotorbikes4.4Promotionofelectriccars4.4Promotionofelectricbuses

0

10

20

30

40

50

60

70

80

90

2014 2016 2018 2020 2022 2024 2026 2028 2030

MilliontonsCO

2

BAU Scenario1 Scenario2 Scenario3

Page|29

Comparing the three scenarios against the BAU, we conclude that Vietnam can adopt andimplement several highly cost-effective mitigation measures that are economically feasible to

achievesignificantemissionsreductioninthisrapidlygrowingsector.Theemissionsreductionunderthe above scenarios would help Vietnam achieving its NDC targets, when complemented by thepoliciesandinvestmentsinothersectors,especiallyinpowergeneration.AsshownintableE.1,the

netpresentvalues(NPVs)to2018oftheadditionalinvestment(notcountingchangesinoperation,maintenance, or fuel costs) are negative under all three mitigation scenarios and largest underScenario2,suggestingthestrongesteconomicjustification.Mostoflow-carbontransportmeasures

presentedandanalyzedinthisreportareconsideredgoodtransportsolutions,notonlybecauseofthe carbonprice, but also because they are sustainable solutions. The economic benefits of thesemeasureswould, in fact,begreater if theirco-benefits, suchas localemissions,qualityof life,and

health,arealsoconsidered.

TableE.1.NPVofAdditionalInvestmentNeedsbyMitigationScenarioandAnalysisPeriod

NPVofadditionalinvestmentcostbyperiod(in2018constantvalue)Scenario

2014–2030 2031–2050

Scenario1:

9%reduction(VND18.7trillion)(US$0.85billion)

(VND18.5trillion)(US$0.84billion)

Scenario2:



Scenario3:



Next Steps.While thesemeasures are economically feasible, bringing in great long-term benefitsthroughareductionintransportcosts,theywouldrequiresignificantinvestmentforwhichfinancingneedstobemobilizedeventhoughtheNPVoftheseinvestmentsislowerthanintheBAUscenario.

As a follow-up activity, a thorough financial analysiswould therefore be required to estimate thefinancing needs of variousmeasures. It would also be necessary to devise financing plans for the

additionalresourcesrequiredfrominternationalsupportaswellasprivatesectorparticipation.

Additionally, even themost ambitious scenarios presented in this report still yield increasing CO2trajectory,andthus,evenmoreambitiousmitigationmeasuresareneededtoreversethetrendsand

decreaseemissionsinabsoluteterms,posingsignificantchallengetothetransportsectorinVietnam.The solutions to this problemmay liewith “Avoid”measures, such as better integration betweenland-use and transport, which can help avoid unnecessary trips and complement the “Shift” and

“Improve”measures identified and analyzed in this report. Long-term land use and infrastructureplanningiscrucialgiventheirlong-termlock-ineffects.

Page|30

Notes

1.ThirdNationalCommunicationtotheUNFCCC:roadtransportemits27,404.64ktCO2ewhichcorrespondsto18.42percentoftotalCO2emissionswithlanduse,land-usechange,andforestry

(LULUCF);and9.65percentoftotalGHGemissionswithLULUCF,in2014.

2.Vietnam’sThirdNationalCommunicationtotheUNFCCCreportsthatin2014emissionsfromthetransportsectoraccountedfor30.4milliontonsCO2.Thedifferenceinvaluesreportedisjustifiedby

theNationalCommunicationusingatop-downapproachwhilethisreportusingabottom-upapproachtothecalculationofemissions.

3.DatatakenfromtheStatisticalYearbookofVietnam2016,publishedbytheVietnamGeneral

StatisticsOffice,in2016.Whentraveldistanceisincluded,thegreatestshareoffreighttrafficisoncoastal(55%)whileroadandwaterwaysaccountedfor22.3percentand20.6percentrespectively.

Reference

GSO(GeneralStatisticsOfficeofVietnam).2016.StatisticalYearbookofVietnam2016.Hanoi:GovernmentofVietnam.https://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=18533.

Page|31

Chapter1:Introduction

BackgroundandObjectives

Vietnam is committed to addressing climate change, including through signing of the Paris

Agreement in2015undertheUnitedNationsFrameworkConventiononClimateChange(UNFCCC)andsubmissionofitsIntendedNationallyDeterminedContribution(INDC,orsimplyNDC).InitsNDC,Vietnamsetthegoalofreducing itsGHGemissionsby8percent in2030,comparedtobusinessas

usual (BAU) using domestic resources, and raised its ambition to 25 percent emissions reductionagainstBAU,contingentonreceivinginternationalsupport.TheUNFCCCrequiresmemberstatestoregularlyupdateandadjust theirNDC,andVietnamiscurrentlypreparingarevisionof itsNDCfor

submission in September 2019. In recent years, Vietnam adopted legislation, policies, programs,planstorespondtoclimatechangeandsustainabledevelopment,includingthefollowing:

• TheCentralCommitteeoftheParty,SessionXI,adoptedtheResolutionNo.24-NQ/TWdatedJune 3, 2013, on active response to climate change, strengthening natural resourcesmanagement,andenvironmentalprotection.

• The National Assembly of the Socialist Republic of Vietnam adopted the Law onEnvironmentalProtectionNo.55/2014/QH1, in SessionXIII on June23,2014, inwhich theparticularcontentrespondingtoclimatechangeisatChapterIVoftheLaw.

• TheNationalAssemblyofSocialistRepublicofVietnamonNovember23,2015,adoptedtheLaw on Meteorology and Hydrology No. 90/2015/QH13, including contents related tomonitoring,impactassessment,andresponsetoclimatechange.

• TheGovernmentofVietnamapprovedResolutionNo.120/NQ-CPdatedNovember17,2017,on Sustainable Development of the Mekong River delta adapting to climate change and

issuedacomprehensiveactionplantoimplementthisresolutionwithspecifictasks,actions,andtimelinetobecarriedoutbyministries,sectors,andlocalities.

• ThePrimeMinisterissuedDecisionNo.2053/QD-TTg,datedOctober28,2016,approvingtheimplementationplanforParisAgreementonclimatechange

Thefast-growingtransportsectorcontributessignificantlytothetotalnationalGHGemissions,and

thus plays an increasingly important role in delivering Vietnam’s commitments under the NDC.Transportaccountedfor30.55MtCO2eor10.8percentoftotalCO2eemissionsin2014.1Vietnam’s

increasingdemandforgreatermobilityandthehighmotorizationrateposesignificantchallengesforVietnam’spotentialforreducinggreenhousegasemissionsinthissector.

Vietnam’s National Committee on Climate Change, led by the Ministry of Natural Resources and

Environment (MoNRE), engages ministries from relevant sectors in the definition andimplementationofpoliciesandmeasuresthatreduceGHGemissions. Inpastyears,severalstudieshave been conducted, such as Intended Nationally Determined Contribution of Viet Nam (MoNRE

2016),andVietNam’sSecondNationalCommunicationofVietNamtotheUNFCCC (MoNRE2010).Based on these reports and on interagency dialogue, the National Committee on Climate Changestatedthetransportsector,usingdomesticresources,wouldberesponsibleforcontributingtothe

commitmentofreducing8percentitsGHGemissionsagainstBAU,in2030.

Page|32

Recognizing the importanceof the transport sector todeliveronVietnam’sNDCcommitment, theDeutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) and the World Bank Group

cooperatedwithVietnam’sMinistryofTransport(MoT)anditsDepartmentofEnvironment(DoE)to(i) compile and analyze information on transport sector activities pertinent to GHG emissions, (ii)createknowledgeandbuildcapacitytofacilitatetheidentificationandprioritizationofpoliciesand

measures forGHGemissions reductions from the transport sector inVietnam,and (iii) informandparticipateinVietnam’sNDCrevisionprocess.Thespecificobjectivesofthisjointtechnicalassistanceincludethefollowing:

• ToimproveunderstandingofthesourcesofGHGemissionswithinthetransportsectorandtheir relative significance to facilitate the identification of policies and measures foremissionsmitigation.

• To develop GHG emissions scenarios based on increasing levels of ambition, internationalresources,andprivatesectorparticipation:

BAU: Businessasusualincludesallpoliciesandinterventionsuptoandincludingthe

base year of 2014, but no additional deployment of targeted policies andmeasuresafterthatdateaimedatmitigationofGHGemissionsinthetransportsector.

Scenario1: Implementation of some of the policies and measures included in Vietnam’s

Transport SectorMaster Plan that canbe implementedwithout support frominternationalresources.

Scenario2: ImplementationofmoreambitiouspoliciesandmeasuresincludedinVietnam’sTransportSectorMasterPlan,usingdomesticandinternationalresources.

Scenario3: Implementation ofmore ambitious policies andmeasures including some notcurrently included in Vietnam’s Transport Sector Master Plan—that use

domestic and international resources and have active participation of theprivatesector.

• Toassessthepotentialforemissionsreductionandcostefficiencyforeachmeasure,throughthedevelopmentofamarginalabatementcost(MAC)curve.

The project team, in close coordination with the Department of Environment ofMoT, developed

scenarios in extensive consultation with various stakeholders, including national governmentagencies,sectorandthematicexpertsfromlocalandinternationalacademia,theprivatesector,and

civil society. To ensure active participation and eventual consenus on the scenarios and individualmeasures,multipleworkshops and bilateralmeetingswere held at each stage of the analysis andreport preparation. Agencies that provided input to the data compilation and analysis include the

MoT, the Ministry of Finance (MoF), the Ministry of Natural Resources and the Environment(MoNRE),VietnamNationalDirectorateofRoads(DRVN),VietnamRailwayAuthority,VietnamInlandWaterways Administration (VIWA), VietnamMaritimeAdministration (VINAMARINE), Civil Aviation

AuthorityofVietnam (CAAV), theVietnamRegistry (VR),TransportDevelopmentStrategy Institute(TDSI),variousresearchandacademicinstitutes,andotherentities.

Page|33

TransportSectorDevelopmentinVietnam

Vietnam’sremarkablesuccessinmitigatingpovertyandpromotingeconomicdevelopmentoverthepastdecadeswasgreatlyenabledbytherapiddevelopmentofsupportingeconomicinfrastructure,

includingthoseoftransport.Thetransportinfrastructureenabledtherapidincreaseinthemobilityofpeopleandgoods,andimprovedtheaccessoftheruralpopulationtoessentialservices(suchashealthandeducation facilities)andeconomicopportunities.According to theMoT, since1992 the

lengthofVietnam’sroadnetworkincreasedsignificantlyandreachedover400,000kmin2016;asaresultofthisendeavor,thenumberofcommuneswithoutaccesstoall-weatherroadsdroppedfrom606in1997to235in2005andthento65in2016.

Thisrapiddevelopmentininfrastructurewasmetwitharapidincreaseinmobility,whichrosefasterthantheGDPgrowthsincethelate1990s.Overthepast25years,annualgrowthratesinfreightandpassengerdemandmeasuredintonperpassenger-kmwere11percentand10percentrespectively,

comparedtoGDPgrowthof6.4percent.Thetotalnationalpassenger-kmincreasedfrom32billionin2000 to 169 billion in 2016, or by about 520 percent; during the same period, the total nationalfreight ton-km increased from32billion to111billionorbyabout340percent.2 Suchexponential

growth in mobility, which on one hand was the contributor to and outcome of the impressiveeconomic growth and poverty reduction in Vietnam, resulted in negative environmentalconsequences. The transport sector has become and will continue to be a significant emitter of

greenhousegases(GHG),contributing30.6milliontonsCO2e,whichcorrespondsto10.76percentoftotal CO2e emissions3 in 2014. Road transport accounted for 89.7 percent of transport emissions.Roadtransport,whichcarried94percentofpassengersand76percentof freighttons,4represents

oneofthereasonsforthislargeshareofemissions.However,whentraveldistanceisincluded(seetable1.1),thegreatestshareoffreightflowsoccursalongcoastalareas(55percent),whileroadandwaterwaysaccountedfor22.3percentand20.6percentrespectively.

Table1.1.DistancesTraveledbyPassengersandFreightinVietnamin2014

Passenger/Freight Total Railway RoadInland

waterwayCoastalshipping

Aviation

Passenger-km(billion) 139.1 4.5 96.9 3.0 34.7

Freightton-km(billion) 223.2 4.3 48.2 40.1 130.0 0.5

Source:GeneralStatisticsOfficeofVietnam

Thetransportsectorconsumesfivetypesoffuel:Gasoline5isconsumedbyalmostallroadtransportmodes,suchastwo-wheelers,passengercars,lightcommercialvehicles;dieselisconsumedbyroad,

railway,andinlandwaterwaytransport;fueloil (FO) isonlyusedformaritimevehicles;keroseneisonlyusedinaviation;andelectricityismainlyconsumedbyelectrictwo-wheelers,andinthefuture,

bymetro.Dieselandgasolineareprojectedtocontinueincreasingsignificantly,morethandoublingitsconsumptionfrom2014to2030.Theconsumptionoffueloilandjetkeroseneisalmostconstantover the years, aligned with amodest increase in demand for inland waterways, coastal, and air

transport(table1.2andfigure1.1).

Page|34

Table1.2.FuelConsumptionbyFuelTypeinTransportSectorinVietnam

Inmilliontonsoilequivalent

Fueltype 2014 2020 2025 2030

Gasoline 4.86 7.05 9.33 12.33Diesel 5.44 7.46 10.62 15.10Fueloil 0.23 0.23 0.29 0.38Jetkerosene 0.37 0.93 1.16 1.44Electricity 0.00 0.01 0.02 0.02

Source:WorldBankandGIZdata.

Figure1.1.FuelConsumptionintheTransportSectorbyFuelType

TheAvoid-Shift-Improve(ASI)Frameworkprovidesasystematicapproachtoassessemissions

sourcesinthetransportsectorandtoidentifyopportunitiesforemissionsreduction:

• Avoid stands for actions that reduce the need for motorized transport or the distancetraveledbymotorized transport.Thiscan include, forexample,measuressuchas fosteringthedevelopmentofdense,polycentric,mixed-usecities,whichenablespeopletolivecloser

to locationsofwork, services, andgoods.Anotherexample is theapplicationof intelligentservicesandapplicationsthatenablepassengersandfreighttogofromorigintodestination

throughshorterroutes.Afurtherexampleisthedeploymentofincentivesforpassengerstosharetransportservicessuchashighoccupancylanesontollroadswheretollsareexemptedforhighoccupancyvehicles.

• Shiftstandsforactionsthatenableand incentivizetheshift fromhigher-emittingtransportmodes to cleaner transportmodes. One example is the deployment of infrastructure and

0

5

10

15

20

25

30

2014 2016 2018 2020 2022 2024 2026 2028 2030

Milliontonsoileq

uivalent(M

toe)

Gasoline Diesel FuelOil JetKerosene Electricity

Page|35

systemstofacilitatetheintegrationoftransportmodessuchaspublictransportwithbicyclelanes, or road with railway and inland waterways. Another example would be the

establishmentoflow-emissionsorlow-congestionzonesandtheprovisionofpublicandnon-motorizedtransportoptionstoaddressthecontinuingdemandfortransportmobility.

• Improvestandsforactionsthatreduceemissionsoftransportperunitofdistancetraveledandcanincludemeasuressuchasimprovementinvehiclefueleconomyandtheintroductionandswitchingtowardslowercarbonfuels.

WhilethestudyusedtheASIFrameworkasanapproachtoidentifymitigationactions,theanalysis

focused on the Shift and Improve components, which fall under the mandate of the Ministry of

Transport.Table1.3listsexamplesofGHGmitigationstrategieswithintheMoTmandates.

Table1.3.GHGMitigationStrategiesintheTransportSector

Useofbiofuels,includingethanolblend(E5/E10)

UseofnaturalgasFuelshift

Useofelectricity

Shiftfromprivatevehiclestopublictransportmodes(buses,busrapidtransitorBRT,andmetro)

ShiftfreighttransportfromroadtoothermodesModalshift

Encouragenon-motorizedtransport(NMT)

Vehiclemaintenance

Shifttoenergyefficiencyvehicles

Applytheenergysavingtechnology

Energyintransport

Energyefficiency

Fueleconomystandards

The scenario analysis assessed the mitigation impact of the listed policy measures, with each

scenarioconsideringdifferentlevelsofambition.Allscenariosassumethedemandfortransportwillcontinuetoincrease—drivenbyeconomicgrowth,populationgrowth,ruraltourbanmigration,andimprovedlivingstandards.Thebusiness-as-usualscenarioassumestherewillnotbedeploymentof

new policies and measures targeted at reducing emissions in the transport sector after 2014.Scenario 1 considers modest levels of ambition, corresponding to the implementation ofmeasures defined in Vietnam’s Transport Development Plan that can be implementedwithout

support from international resources. Scenario 2 considers a higher level of ambition thanScenario 1 for measures defined in Vietnam’s Transport Development Plan and is contingent onhavinginternationalfinancialsupport.Finally,Scenario3isagainahigherlevelofambitioninterms

ofGHGemissions reductionandgoesbeyondmeasures and levels defined inVietnam’s TransportDevelopmentPlan(seetable1.4).

Page|36

Table1.4.ListofGHGMitigationOptionsConsideredinScenarioAnalysis

No.

Mea

sure

nam

eSc

enar

io 1

Scen

ario

2Sc

enar

io 3

1. E

nerg

y effi

cien

cy

1.1

New

veh

icle

fuel

eco

nom

y an

d em

issi

ons

stan

dard

sFu

el e

cono

my

impr

ovem

ents

dep

loye

d in

two

stag

es:

Stag

e 1

(202

2–20

26)

• Sm

all c

ar (

<140

0cc)

: 6.1

L/1

00km

• M

ediu

m c

ar (

1400

-200

0cc)

: 7.5

2 L/

100k

m

•

Larg

e ca

r (>

2000

cc):

10.

4 L/

100k

m

In w

hich

•

2022

: 50%

of

car

sale

s ap

ply

fu

el e

con

om

y

•

2023

: 75%

of

car

sale

s ap

ply

fu

el e

con

om

y

•

2024

-202

6: 1

00%

of

car

sale

s ap

ply

fu

el e

con

om

y

•

2025

: Mo

torc

ycle

s: 2

.3 L

/100

km

St

age

2 (2

027–

) •

Smal

l car

(<1

400c

c): 4

.7 L

/100

km

;

•

Med

ium

car

(14

00-2

000c

c): 5

.3 l/

100

km;

• La

rge

car

(>20

00cc

): 6

.4 L

/100

km.

In

whi

ch

• 20

27: 5

0% o

f ca

r sa

les

app

ly f

uel

eco

no

my

• 20

28: 7

5% o

f ca

r sa

les

app

ly f

uel

eco

no

my

• 20

29: 1

00%

of

car

sale

s ap

ply

fu

el e

con

om

y

1.2

Impr

ovem

ent

of t

ruck

lo

adin

g fa

ctor

s

No

Frei

ght

load

fact

or

imp

rove

s fr

om

56

% t

o 6

0%.

Frei

ght

load

fact

or

imp

rove

s fr

om

56

% t

o 6

5%.

2. P

asse

nger

mod

al s

hift

from

pri

vate

veh

icle

s

2.1

Expa

nsio

n of

bus

sys

tem

sBu

s de

velo

pmen

t in

5 ci

ties

of c

entr

al

man

agem

ent

(Han

oi,

Ho

Ch

i Min

h C

ity,

H

ai P

ho

ng,

Da

Nan

g, C

an T

ho

)

Bus

deve

lopm

ent i

n 13

citi

es in

clud

ing

5 ci

ties

of c

entr

al m

anag

emen

t and

9

Clas

s 1

citie

s: H

anoi

, Ho

Chi M

inh

City

, Can

Tho

, Da

Nan

g, H

ai P

hong

, Vie

t Tri

, N

am D

inh,

Vin

h, H

ue, Q

uy N

hon,

Da

Lat,

Nha

Tra

ng, a

nd B

uon

Me

Thuo

t

2.2

Expa

nsio

n of

BRT

sy

stem

sH

anoi

: Li

ne 1

in o

pera

tion

in 2

017

Da

Nan

g:

Line

1 in

ope

ratio

n in

202

1H

CMC:

Li

ne 1

in o

pera

tion

in 2

021

Li

ne 2

in o

pera

tion

in 2

025

Han

oi:

Li

ne 1

in o

pera

tion

in 2

017;

1 n

ew li

ne in

ope

ratio

n in

202

5;

2

new

line

s in

ope

ratio

n in

203

0D

a N

ang:

Li

ne 1

in o

pera

tion

in 2

021;

1 n

ew li

ne in

ope

ratio

n in

203

0H

CMC:

Li

ne 1

in o

pera

tion

in 2

021;

2 n

ew li

nes

in o

pera

tion

in 2

025

Can

Tho:

Li

ne 1

in o

pera

tion

in 2

025;

Lin

e 2

in o

pera

tion

in 2

030

Hai

Pho

ng:

Line

1 in

ope

ratio

n in

202

5; L

ine

2 in

ope

ratio

n in

203

0

New

BRT

line

s us

ing

elec

tric

bus

es in

Han

oi a

nd H

CM c

ity fr

om 2

025

2.3

Dep

loym

ent

of m

etro

sy

stem

sH

anoi

: Li

ne 2

A in

ope

ratio

n in

201

9; L

ine

3 in

ope

ratio

n in

202

2H

CMC:

Li

ne 1

in o

pera

tion

in 2

022

Page|37

Table1.4continued

3. F

reig

ht m

odal

shi

ft fr

om ro

ad

3.1

Mod

al s

hift

from

road

to

inla

nd w

ater

way

tr

ansp

ort

Mod

al s

hift

for f

reig

ht tr

ansp

ort:

By 2

020:

•

FTKT

by

IWT

to in

crea

se fr

om

65.0

(BAU

) to

71.2

bill

ion

ton-

km

(20.

7% to

22.

6% o

f tot

al F

TKT)

; sh

are

of ro

ad to

dec

reas

e fr

om

23.0

% to

19.

1%.

By 2

030:

•

FTKT

by

IWT

to in

crea

se fr

om

127.

8 to

128

.8 b

illio

n to

n-km

(2

0.6%

to 2

0.8%

of t

otal

); m

odal

sh

are

of ro

ad to

dec

reas

e fr

om

23.4

% to

23.

0% in

203

0.

Mod

al s

hift

bot

h fo

r fre

ight

and

pas

seng

er tr

ansp

ort:

By 2

020:

•

FTKT

by

IWT

to in

crea

se fr

om 6

5.0

(BAU

) to

71.2

bill

ion

ton-

km (2

0.7%

to

22.6

% o

f tot

al F

TKT)

; sha

re o

f roa

d to

dec

reas

e fr

om 2

3.0%

to 1

9.1%

.

By 2

030:

•

FTKT

by

IWT

to in

crea

se fr

om 1

27.8

to 1

28.8

bill

ion

ton-

km (2

0.6%

to 2

0.8%

of

tota

l); m

odal

sha

re o

f roa

d to

dec

reas

e fr

om 2

3.4%

to 2

3.0%

in 2

030.

3.2

Mod

al s

hift

from

road

to

coa

stal

shi

ppin

gM

odal

shi

ft fo

r fre

ight

tran

spor

t:

• Th

e FT

KT fr

om ro

ad to

the

coas

tal t

rans

port

is a

ssum

ed to

be

equ

ival

ent t

o th

e FT

KT s

hift

ed

from

road

to IW

T in

the

sam

e tim

e.

Mod

al s

hift

for f

reig

ht tr

ansp

ort:

•

The

FTKT

from

road

to th

e co

asta

l tra

nspo

rt is

ass

umed

to b

e do

uble

the

FTKT

sh

ifted

from

road

to IW

T in

the

sam

e tim

e.

3.3

Mod

al s

hift

from

road

to

railw

ayN

oIn

acc

orda

nce

to th

e D

ecis

ion

318/

QĐ

-TTg

on

tran

spor

t ser

vice

dev

elop

men

t, th

e gr

owth

rate

of f

reig

ht tr

ansp

ort i

s ex

pect

ed to

be

12.5

%. T

he c

alcu

latio

n as

sum

es th

at

the

FTKT

on

the

railw

ay w

ill in

crea

se a

t thi

s sa

me

annu

al ra

te.

No.

Mea

sure

nam

eSc

enar

io 1

Scen

ario

2Sc

enar

io 3

Page|38

Table1.4continued

4.

Fue

l cha

nge

4.1

Prom

otion

of b

iofu

els

(E

5/E1

0)In

201

8: E

5 40

% o

f tot

al g

asol

ine

sale

s (fi

rst h

alf o

f 201

8)20

19–3

0: T

here

is a

sup

ply

cons

trai

nt

for

etha

nol o

f 145

,000

cub

ic m

eter

s pe

r ye

ar a

nd tr

ansp

ort d

eman

d do

es n

ot

exce

ed th

is fi

gure

.

In 2

018:

E5

40%

of t

otal

gas

olin

e sa

les

(firs

t hal

f of 2

018)

2019

–30:

E5

acco

unts

for

40%

of t

otal

ga

solin

e sa

les;

ass

ume

no s

uppl

y co

nstr

aint

.

2018

–24:

E5

incr

ease

s gr

adua

lly fr

om

40%

of t

otal

gas

olin

e sa

les

in 2

018

up to

10

0% in

202

4.20

25–3

0: E

5 is

gra

dual

ly re

plac

ed w

ith

E10,

at 5

0% in

202

5 in

crea

sing

to 1

00%

by

203

0.

4.2

Prom

otion

of e

lect

ric

mot

orbi

kes

Elec

tric

mot

orbi

kes

acco

unt f

or

7% o

f ann

ual m

otor

bike

sal

es.

Elec

tric

mot

orbi

kes

acco

unt f

or

14%

of a

nnua

l mot

orbi

ke s

ales

.El

ectr

ic m

otor

bike

s ac

coun

t for

30

% o

f tot

al tw

o-w

heel

er fl

eet.

4.3

Intr

oduc

tion

of C

NG

bu

ses

623

CNG

bus

es: 4

23 in

HCM

C;

200

in H

anoi

HCM

C: 4

23 C

NG

bus

es in

201

7H

anoi

: 50

CNG

bus

es in

201

8 an

d 20

0 un

its b

y 20

20

4.4

Prom

otion

of e

lect

ric

cars

and

bus

esN

o•

Elec

tric

car

s re

pres

ent 5

% o

f ann

ual

new

car

sal

es in

202

5•

Elec

tric

car

s re

pres

ent 3

0% o

f ann

ual

new

car

sal

es in

203

0•

All

BRT

lines

aft

er 2

020

use

elec

tric

bu

ses

• 5%

of a

nnua

l new

car

sal

es in

202

5•

30%

of a

nnua

l new

car

sal

es in

203

0•

All

BRT

lines

aft

er 2

020

use

elec

tric

bu

ses

• 10

% o

f bus

sal

es a

re e

lect

ric

vehi

cles

in

202

0–20

30

No.

Mea

sure

nam

eSc

enar

io 1

Scen

ario

2Sc

enar

io 3

Page|39

Notes1.AccordingtoVietnam’sThirdNationalCommunicationtotheUNFCCC:Transportemits30,552.31

ktCO2e,whichcorrespondsto10.76percentoftotalCO2eemissionswithoutlanduse,land-usechange,andforestry(LULUCF);and9.51percentoftotalCO2eemissionswithLULUCF,in2014.2.Takenfrom2018GeneralStatisticsOffice(GSO)transportstatistics,availableat:

https://www.gso.gov.vn/default_en.aspx?tabid=781.3.WithoutLULUCFin2014.ThetransportemissionsofCO2(withoutCH4andN2O)inthatyearwere30.35milliontonsCO2.

4.TakenfromtheStatisticalYearbookofVietnam2016,publishedbytheGeneralStatisticsOffice.Availableat:https://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=18533.5.Gasolinemaycontainafractionofethanol.

ReferencesMoNRE(MinistryofNaturalResourcesandEnvironment).2010.VietNam’sSecondNational

CommunicationtotheUnitedNationsFrameworkConventionofClimateChange.Hanoi:MinistryofNaturalResourcesandEnvironment,Vietnam.https://unfccc.int/sites/default/files/resource/Vietnam%20second%20national%20communicati

on.pdf.———.2016.IntendedNationallyDeterminedContributionofVietNam.TechnicalReport.Hanoi:

MinistryofNaturalResourcesandEnvironment,Vietnam.

https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/Viet%20Nam%20First/VIETNAM%27S%20INDC.pdf.

———.2019.ThirdNationalCommunicationofVietNamtotheUnitedNationsFrameworkConventionofClimateChange.RevisedApril20,2019.Hanoi:MinistryofNaturalResourcesandEnvironment,Vietnam.https://unfccc.int/sites/default/files/resource/Viet%20Nam%20-

%20NC3%20resubmission%2020%2004%202019_0.pdf.

Page|41

Chapter2:Business-As-UsualReferenceScenario

Thischapterpresents the transportactivitiesandemissionsprojectionunder thebusiness-as-usual(BAU) scenario estimate, based on the comprehensive inventory of transport activities andmacroeconomic assumptions. The study objectives required a suite ofmodels that would allow a

detailed bottom-up analysis of transport activity in all sectors, which determined the impact ofpoliciesandinvestmentsonthenationalgreenhousegas(GHG)emissions.Inturn,thestudyusedtheemissions analysis to calculate the transportation sector’s emissions scenarios for the Nationally

Determined Contribution (NDC) update. Figure 2.1 illustrates the modeling framework, whichemploysvarioustoolswithuniquecapabilities.

Figure2.1.ModelingFramework

GrowthProjectionintheTransportSectorunderBAUTransport sector emissions under the business-as-usual scenario are projected to increase withgrowingmobilitydemandandmotorization.Basedonpopulationandeconomicgrowthassumptions,detailedinAppendixD,passenger-kmtraveled(PKT)areprojectedtoincreaseatanannualaverage

growthrateof5.9percentfrom2014to2030(figure2.2).Themodalshareremainsrelativelystablethroughout the forecastperiod:Road transportaccounts for94percentofPKTconsistentlyduringtheperiod,althoughtheshareofcommercialPKTincreasessomewhatcomparedtoprivatePKT;air

transport PKT is maintained at around 4 percent of the total. Freight ton-km traveled (FTKT) isforecasttogrowatanaverageannualrateof6.9percent(figure2.3).Coastalshippingaccountsfor55percentofFTKT,whileroadandwaterwaysaccountfor23percentand21percentrespectively.

Page|42

Figure2.2.ProjectionofPassenger-KilometersTraveledunderBAU

Figure2.3.ProjectionofFreightTon-KilometersTransportedunderBAU

RoadTransport.RoadtransportisnotonlyoneofthemostdominantmodesinVietnam,butalsothefastest growingmode. Road infrastructure received the vastmajority of public funding allocation,

and its lengthquadrupledover thepast twodecades; themotorizationrate inVietnam,whileatamodest level compared to higher-income countries, is increasing rapidly. Based on the populationand economic growth assumptions, the total kilometer traveled by road vehicles is forecast to

increasefrom212.7billionkmperyearin2014to476.4billionkmperyearin2030(figure2.4),atanaverageannualgrowthrateof5.2percent.Of the totalkilometer traveled,motorcyclesaccountedfor60percent,passengercarsfor23percent,andtrucksandcoachesfor10percent.

0

100

200

300

400

500

600

700

800

900

2014 2016 2018 2020 2022 2024 2026 2028 2030

Passen

ger-kilometers(billion)

Onroad-Carandmotorbike Onroad-Commercial

Rail-MainlineandMetro InlandWaterwayandCoastal

NationalAir

0

100

200

300

400

500

600

700

2014 2016 2018 2020 2022 2024 2026 2028 2030

Freightton

-kilo

meters(billion)

Onroad-Commercial Rail-Mainline

InlandWaterway CoastalFreight

NationalAir

Page|43

Thetotalroadvehiclefleetisprojectedtoincreaseatanannualaveragerateof6.5percentduringthesameperiod,withgreatvariationacrossvehicletypes,rangingfrom3.0percentperannumfor

motorcycles (gasoline-fueled) and 6.5 percent for heavy commercial vehicles, to 13.3 percent forpassengercars(figure2.5).

Figure2.4.ProjectionsofRoadDistancesTraveledbyVehicleType

Figure2.5.ProjectionsofRoadVehicleFleetNumbersbyVehicleType

0

100

200

300

400

500

600

2014 2016 2018 2020 2022 2024 2026 2028 2030

Vehicle-km

peryear(in

billionorE+09) 2W 3W Car LCV-Passenger

LCV-Goods HCV-UrbanBus HCV-Coach HCV-Truck

0

10

20

30

40

50

60

70

2014 2016 2018 2020 2022 2024 2026 2028 2030

Million

Motorcycle ElectricMCCar LightCommercialVehicleHeavyCommercialVehicvle

Page|44

In2014,motorcyclesaccountedfor94percentofthetotalroadvehiclefleet inVietnam;however,this share is projected to reduce to 81 percent by 2030. Passenger cars have the second largest

share,with1millionin2014,withaprojectedincreaseto7.1millionvehiclesby2030.Theshareofelectricvehiclesinthevehiclefleetwillremainlow,reachingonlya2.5percentshareofprivatecars,by 2030. Light commercial vehicles (LCV)—typically small trucks—are projected to increase by 47

percentby2030.Heavycommercialvehicles(HCV)forfreightandpassengertransportwill increase2.5timesinnumberby2030.In2014,medium-sizedtrucks(7to16tons)accountedfor28percentofHCVfleetandareprojectedtoincreaseto40percentby2030.

InlandWaterwayandCoastalTransport.Vietnam’sinlandwaterwaytransport(IWT)hasgrownandimprovedsignificantlyinrecentyears,becomingavibrantsectorofactivitystrategicallyimportanttoVietnam’stransportsystem.Itcarriesnearlyoneinsixtonsofthedomesticgoodstransported1and

nearly80percentofthefreighttraffic(ton-km)carriedbyroadtransport.2

Passengerflowsby inlandwaterways isexpectedtogrowfrom2.9billionpassenger-kmin2014to6.2billionpassenger-kmin2030,atanaverageannualgrowthrateof1.7percent.Thegreatmajority

of vessels and barges (92 percent) are small, with a power capacity of below 100 HP. Inlandwaterwaysmoved 40.1 billion ton-km in 2014. Freight flows are projected to grow at an averageannualrateof9.0percent,reaching127.8billionton-kmin2030.Bulkvesselswithacapacitybelow

1,500tonsaccountedfor94percentofvesselsoperatingininlandwaterways.Freightflowsmovedbycoastaltransportisprojectedtoincreasefrom130billionton-kmin2014to338.4billionton-kmin2030;vesselsusedincoastaltransportareprojectedtobemostlybulk(64percent)withcapacity

over1,000tons.

DomesticAviation.Aviationisarapidlygrowingsectorofactivity.Passengerkilometerstraveledby

domesticcivilaviationrapidlyincreasedfrom4.4billionPKTin2000toreach11.0billionPKTin2014and is projected to increase to 36.5 billion PKT in 2030. While no dedicated freight services areoperatingdomestically,freightflowsonpassengerairplanes,so-called“bellycargos”isprojectedto

increasefrom0.1billionton-kmin2014to0.7billionton-kmin2030.

Railways. Rail transport in Vietnam accounts for a small and decreasing share of PKT and FTKT,largelydue to thedeterioratingconditionof the legacy infrastructure thatprovides low-speedand

low-capacityservices.Passengerkilometerstraveledbyrailwaywas4.4billionpassenger-kmin2014andareprojectedtoincreaseto7.1billionpassenger-kmin2030.Freighttonskilometerstraveledbyrailway,whichwas4.3billionton-kmin2014,graduallyreducedin2015and2016to3.1billionton-

km.However,forecastsindicaterailwayFTKTcouldreach8.5billionton-kmin2030.

GHGEmissionsResultsunderBAU

Without any targetedpolicies andmeasures to reduceGHGemissions in the transport sector, thecurrent composition of the energy sources is estimated to remain largely unchanged, with heavyrelianceongasolineanddieselfuelsandlowgrowthofelectricity,asdepictedintable2.1.

Page|45

Table2.1.ProjectedEnergyConsumptionbySourceinTransportSectorunderBusiness-As-UsualScenario

2014 2020 2025 2030 2014 2020 2025 2030Fueltype

(Inmilliontonsoilequivalent) (Fuelsinmilliontons,electricityinGWh)

Gasoline 4.86 7.05 9.33 12.33 4.60Mton 6.66 8.81 11.66

Diesel 5.44 7.46 10.62 15.10 5.29Mton 7.26 10.34 14.70

Fueloil 0.23 0.23 0.29 0.38 0.23Mton 0.24 0.30 0.40

Jetkerosene 0.37 0.93 1.16 1.44 0.36Mton 0.88 1.10 1.36

Electricity 0.00 0.01 0.02 0.02 19.4GWh 110.3 192.7 275.0

Consequently,emissionsareprojectedtoincreaseatanaverageof6to7percentperyear,reachingnearly90milliontonsofCO2emissionsin2030(table2.2andfigure2.6).

Table2.2.TransportCO2EmissionsinVietnamunderBusiness-As-UsualScenario

Inmilliontons

Subsector 2014 2020 2025 2030

Road 26.4 37.9 52.1 71.7

Railway 0.1 0.2 0.2 0.3

IWTandcoastaltransport 3.5 4.6 6.1 8.2

Aviation 1.1 2.8 3.5 4.3

Other 2.1 2.3 3.2 4.6

Total 33.2 47.7 65.1 89.1

Figure2.6.ProjectedCO2EmissionsbyTransportSubsectorsunderBAU

0

10

20

30

40

50

60

70

80

90

2014 2016 2018 2020 2022 2024 2026 2028 2030

MilliontonsCO

2

Road Railway IWTandCoastal Air Other

Page|46

UndertheBAUscenario,changesintheactivitylevelsofeachmodeaffectthecompositionoftotalsectoralCO2emissions.Thetotalemissionssharesfromrail (25percent)andwaterbornetransport

(11percent)decrease,while thesharesof roadandaviation increase (table2.3).Roadtransport isthehighestsourceofCO2emissions,accountingfor80percentoftotaltransportemissions;followedbyinlandwaterwaysandcoastaltransport,whichaccountforabout10percentoftotaltransportCO2

emissions.Emissionsfromrailwaysarenegligible.

Table2.3.ProjectedShareofCO2EmissionsbyTransportSubsectors

Subsector 2014 2020 2025 2030

Road 79.4% 79.4% 80.0% 80.4%

Railway 0.4% 0.4% 0.3% 0.3%

IWTandcoastaltransport

10.5% 9.7% 9.3% 9.3%

Aviation 3.4% 5.8% 5.3% 4.8%

Other 6.3% 4.8% 5.0% 5.2%

Total 100.0% 100.0% 100.0% 100.0%

Incomegrowth is themaindriver of such rapid growth inmobility, and resultant increases in fuelconsumptionandemissions.As international experience suggests, income rise is closely related to

increasingvehicleownershipanduse,andVietnamiscurrentlygoingthroughrapidmotorization.Asshown in figure 2.5, Vietnam’s motorization would see lower-emissions vehicles (motorbikes andlight goods vehicles) replaced with higher-emissions vehicles (passenger cars and heavy goods

vehicles),drivinganincreaseinemissionspercapita.

At the same time, Vietnam’s economy is open and trade-dependent with its trade-to-GDP rationearing200percent in2018.EconomicgrowthinVietnamisthus interdependentwith increases in

goods movement and trade volumes. It is, however, projected that emissions per GDP woulddecreaseundertheBAUscenario,suggestingfutureefficiencyimprovementinthetransportsector.Thesetrendsaredepictedinfigure2.7.

Figure2.7.ProjectedGHGEmissionsperGDPandperCapitaunderBAU

Page|47

Notes

1.Accordingto2018GSOstatistics,in2016inlandwaterways=216milliontonsoutofatotalof1,255milliontons.SeeStatisticalYearbookofVietnam2018.TransportandPostalService

Telecommunications.Table295:VolumeofFreightCarriedbyTypesofTransport.Availableat:https://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=19299.

2.Accordingto2018GSOstatistics,in2016road=57.4;inlandwaterways=44.9billionton-km.See

StatisticalYearbookofVietnam2018.TransportandPostalServiceTelecommunications.Table295:VolumeofFreightCarriedbyTypesofTransport.Availableat:https://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=19299.

Page|49

Chapter3:Scenario1—WithDomesticResourcesOnly

EmissionsMitigationMeasuresunderScenario1

MitigationScenario1includespoliciesandmeasuresundertheShiftandImprovecomponentsofthe

Avoid-Shift-Improve(ASI) framework firmlyunderthemandateof theMinistryofTransport (MoT),accordingtothetransportsectorstrategy.Inaddition,theincludedmitigationmeasureshavebeenassessedtobeimplementablewithdomesticresources.Figure3.1illustratesthemitigationoptions

chosenforScenario1.

Figure3.1.TheMitigationActionsAnalyzedunderScenario1

Note:IWW=Inlandwaterway;BRT=busrapidtransit;CNG=compressednaturalgas.

Table3.1 (asubsetof table1.4) laysout thedetailed levelofambition foreachdefinedmitigationmeasure,basedonthereviewofexistingtransportplansandinextensiveconsultationwithrelevant

stakeholders.

EnergyEfficiency

Newvehiclefueleconomyandemissionstandards

Passengermodalshiftfromroadtopublic

transport

Busimprovementsin

4cities

BRT:4routesin5cities

Metro:3linesand2cities

ModalshiftfromroadtoIWWandcoastal

transport

Toinlandwaterway

Tocoastalshipping

Fuelchange

Ethanol:E5uptosupplycap

Electricmotorcycles:7%ofsales

CNGfor623urbanbuses

Page|50

Table3.1.LevelofAmbitionforMitigationMeasuresAnalyzedunderScenario1

Measures Mitigationoptions Assumptions1.Energyefficiency

1.1Newvehiclefueleconomyandemissionsstandards

Vehiclefueleconomystandardfornewvehiclesdeployedintwostages:Stage1:(2022–2026)

Smallcar(<1400cc): 6.1L/100kmMediumcar(1400-2000cc): 7.52L/100kmLargecar(>2000cc): 10.4L/100km

Inwhich:2022:50%ofcarsalescomplywithstandard2023:75%ofcarsalescomplywithstandard2024–2026:100%ofcarsalescomplywithstandard2025:Motorcycles:2.3L/100km

Stage2:from2027onwardsSmallcar(<1400cc): 4.7L/100km;Mediumcar(1400-2000cc): 5.3L/100km;Largecar(>2000cc): 6.4L/100km.

Inwhich:2027:50%ofcarsalescomplywiththestandard2028:75%ofcarsalescomplywiththestandard2029:100%ofcarsalescomplywiththestandard

2.1Expansionofbussystems

Busdevelopmentin5citiesofcentralmanagement(Hanoi,HoChiMinhCity,HaiPhong,DaNang,CanTho)

2.2ExpansionofBRTsystems

Hanoi: Line1inoperationin2017DaNang: Line1inoperationin2021HCMC: Line1inoperationin2021 Line2inoperationin2025

2.Passengermodalshiftfromprivatevehicles

2.3Deploymentofmetrosystems

Hanoi: Line2Ainoperationin2019 Line3inoperationin2022HCMC: Line1inoperationin2022

3.1ModalshiftfromroadtoIWWtransport

ModalshiftforfreighttransportBy2020: • FTKTbyIWTtoincreasefrom65.0(BAU)to71.2billionton-km(20.7%to22.6%oftotalFTKT);shareofroadtodecreasefrom23.0%to19.1%

By2030: • FTKTbyIWTtoincreasefrom127.8to128.8billionton-km(20.6%to20.8%oftotal);modalshareofroadtodecreasefrom23.4%to23.0%in2030

3.Modalshiftfromroad

3.2Modalshiftfromroadtocoastalshipping

Modalshiftforfreighttransport• TheFTKTfromroadtothecoastaltransportisassumedtobeequivalenttotheFTKTshiftedfromroadtoIWTinthesametime

4.1Promotionofbiofuels(E5/E10)

In2018:• E540%oftotalgasolinesales(firsthalfof2018)

2019–30:• Thereisasupplyconstraintforethanolof145,000cubicmetersperyearandtransportdemanddoesnotexceedthisfigure.

4.2Promotionofelectricmotorbikes

Electricmotorbikesaccountfor7%ofannualmotorbikesales

4.Fuelchange

4.3IntroductionofCNGbuses

623CNGbuses:423inHCMC;200inHanoi

Note:BRT=busrapid transit; IWW= inlandwaterway;FTKT= freight ton-kmtransported;BAU=businessasusual;CNG=compressednaturalgas;HCMC=HoChiMinhCity.

Page|51

The abovemeasureswould result in a reduction in projected fuel consumption under Scenario 1,comparedtounderbusinessasusual(BAU),assummarizedintable3.2andfigure3.2.Comparedto

BAU, the gasoline consumption under Scenario 1 would drop by 13 percent in 2025 and by 22percentin2030.Theprojectedshiftfromprivatepassengertransporttopublictransportsuchasbus,busrapidtransit(BRT),andmetroaccountsforthisreduction. Theshiftfromfossil-fuelvehiclesto

electric vehicles (electric motorbikes, electric bus) also contributes to the reduction in gasolineconsumption, leading toa reduction inCO2emissionscompared toBAU.However,emissions fromelectricity generation is not included in the transport sector analysis, but in that of the energy

sector—both of which will be incorporated in the Government of Vietnam’s overall NationallyDetermined Contribution (NDC) commitment.While gasoline consumptionwould decrease, dieselconsumptionwouldincreasebyabout1percentcomparedtoBAU.

Table3.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario1

2014 2020 2025 2030 2014 2020 2025 2030Fueltype


Gasoline 4.86 6.46 8.08 9.67 4.60Mton 6.10 7.64 9.14

Diesel 5.44 7.30 10.68 15.23 5.29Mton 7.11 10.39 14.83

Fueloil 0.23 0.23 0.29 0.39 0.23Mton 0.24 0.30 0.40


Electricity 0.00 0.01 0.03 0.05 19.4GWh 171.4 363.4 556.2

Figure3.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario1

0

5

10

15

20

25

30

2014 2016 2018 2020 2022 2024 2026 2028 2030

Milliontonsoileq

uivalent(M

toe)


Page|52

GHGEmissionsResultsunderScenario1

Table3.3andfigure3.3presentthetotalCO2emissionsfromthetransportsectorandbreakdownbysubsectorunderScenario1.ComparedtoBAU,mostoftheemissionsreductionwouldoccurinthe

road sector with some in the inland waterway transport (IWT) and coastal transport. The modalshareoftotalgreenhousegas(GHG)emissionswouldremainrelativelyunchangedovertheperiod.

Table3.3.TransportCO2EmissionsbySubsectorunderBAUandScenario1

InmilliontonsCO2

2014 2020 2025 2030Transportmode

BAUScenario

1BAU

Scenario1

BAUScenario

1BAU

Scenario1

Road 26.4 26.4 37.9 35.3 52.1 49.0 71.7 65.2

Railway 0.1 0.1 0.2 0.2 0.2 0.2 0.3 0.3IWTandcoastaltransport

3.5 3.5 4.6 4.7 6.1 5.5 8.2 7.1

Air 1.1 1.1 2.8 2.8 3.5 3.5 4.3 4.3

Other 2.1 2.1 2.3 2.0 3.2 3.0 4.6 4.2

Total 33.2 33.2 47.7 45.1 65.1 61.2 89.1 81.1

Figure3.3.CO2EmissionsbySubsectorsunderScenario1

Scenario 1 includes eightmitigationmeasures to reduceCO2 emissions in the transport sector. As

shownintable3.4, investmentsorpoliciestowardsmodalshiftsfromroadtoinlandwaterwayandcoastal transportwould result in the largest emissions reduction during the 2014 to 2030 period.Strengthening of fuel economy and vehicle emissions standards would result in much greater

emissionsreductionoveralongerperiod,asstrongerstandardswouldaffectthelargeandgrowingfleetoffuturevehicles.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

20142015201620172018201920202021202220232024202520262027202820292030

Thou

sand

tonsCO

2


Page|53

Table3.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1

InthousandtonsCO2

CumulativereductionMitigationmeasures 2014 2020 2025 2030 2040 2050

2014–30 2014–501.1Newfueleconomyandemissionsstandard

0 0 695 5,130 17,749 24,904 15,810 360,462


53 370 436 326 594 1,619 5,815 20,836


0 2 7 3 1 2 65 119


0 23 125 115 100 94 1,167 3,190

3.1/3.2ModalshiftfromroadtoIWT/coastaltransport

0 1,905 2,059 1,560 3,134 6,396 22,844 93,544

4.1Promotionofbiofuels(E5)

0 256 269 267 243 209 3,487 8,278


0 122 345 580 1,046 1,517 3,945 25,343


0 5 5 3 6 3 64 146

Note:BRT=busrapidtransit;IWT=inlandwaterwaytransport;CNG=compressednaturalgas.

Figure3.4depictsthesemeasuresandtheircontributionstotheoverallemissionsreductionagainstthebusiness-as-usual(BAU)scenario.

Figure3.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario1

-

2,000

4,000

6,000

8,000

10,000

2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Emission

redu

ction(tho

usan

dtonsCO2)

1.1Newfueleconomy&emissionstandard2.1Expansionofbussystems2.2ExpansionofBRTsystems2.3DeploymentofMetrosystems3.1/3.2ModalshiftfromroadtoIWT/Coastal4.1Promotionofbiofuels(E5)4.2Promotionofelectricmotorbikes4.3IntroductionofCNGbuses

Page|54

Aggregating the impactsof allmeasures,CO2emissions started todecline from2015 to2017asaresult of efforts to improve public transport and increase the use of biofuel. Looking ahead, CO2

emissionsareprojectedtoreduceby5.4percent(2020),6.1percent(2025),and9.0percent(2030)inthecomparisonofBAU(seetable3.5andfigure3.5).

Table3.5.ComparisonofCO2EmissionsbetweenBAUandScenario1

InmilliontonsCO2

Scenario 2014 2020 2025 2030

CO2emissionsunderBAU 33.2 47.7 65.1 89.1

CO2emissionsunderScenario1 33.2 45.1 61.2 81.1

CO2emissionsreduction(1)–(2) 0.0 2.6 3.9 8.0

CO2emissionsreductionpercent 0.0% 5.4% 6.1% 9.0%

Figure3.5.ComparisonofCO2EmissionsbetweenBAUandScenario1

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032

Thou

sand

tonsCO

2

BAU Scenario1

Page|55

MarginalAbatementCostunderScenario1

To understand the costs of implementing the abovemitigationmeasures, the study conducted amarginal abatement cost (MAC) analysis. TheMAC analysis calculates for eachmeasure the GHG

mitigation potential (tCO2e), economic costs of implementation—including for capital investmentsand operating expenses—and economic benefits from reduced transport costs, along with otherbenefits. Then, the net costs—economic costs less economic benefits—are calculated per GHG

emissionsmitigation ($/tCO2e). Such informationoncost-effectiveness isuseful to informdialogueamong stakeholders and should be complemented with information on feasibility and analysis ofothercostandbenefitsnotincludedintheanalysis.

Mitigationmeasuresarethenplacedfromlowesttohighestcost-effectivenesstoformaMACcurveplot.They-axisshowsthemarginalabatementcostofGHGemissions($/tCO2e),wheretheheightofeachmeasurerepresentsitsnetpresentcostpertonofCO2ereductionovertheanalysisperiod.The

x-axisshowstheabatementpotentialofGHGemissions (tCO2e),wherethewidthofeachmeasurerepresentstheGHGabatementpotentialduringtheanalysisperiod.ThedetailsofthemethodologyanddatausedfortheanalysisareprovidedinappendicesDandE.

ThestudydevelopedMACcurves(MACC)fortwoanalysisperiods:2014to2030and2014to2050.As depicted in table 3.6 and figure 3.6, severalmeasures would incur negativeMACs, generatingbenefitsgreaterthantherequiredinvestments.Inthelongerterm,coveringtheperiodfrom2014to

2050,mostmeasureswouldgeneratenetbenefitsexcept formeasureswithheavyupfront capitalinvestments,suchasmetroandBRTsystems.Inthemediumterm(until2030),mitigationmeasures3.1(modalshiftfromroadtoIWTandcoastaltransport),4.2(promotionofelectricmotorbikes),and

1.1 (new and stricter vehicle fuel economy and emissions standards) would bring in the largestemissions reduction. In the longer term (until 2050), measure 1.1 (vehicle fuel economy andemissions standards) would account for the predominant share of emissions reduction, as this

measurewouldaffecttheentire,andcontinuouslygrowing,futurevehiclefleet.

Table3.6.MACCResultsunderScenario1,forAnalysisPeriod2014–2030and2014–2050

2014–2030 2014–2050Measure Mitigation

potentialMitigation

costMitigationpotential

Mitigationcost

3.1/3.2ModalshiftfromroadtoIWT/coastal 22.8 (8.9) 93.5 (3.1)

4.3IntroductionofCNGbuses 0.1 (3.7) 0.2 (2.3)

4.2Promotionofelectricmotorbikes 3.9 (4.7) 25.3 (1.7)

1.1Newfueleconomystandards 15.8 (3.4) 360.5 (1.2)

4.1Promotionofbiofuels 3.5 (0.3) 8.3 (0.2)

2.1Expansionofbussystems 5.8 4.0 20.8 (0.1)

2.3Deploymentofmetrosystems 1.2 40.0 3.2 18.6

2.2ExpansionofBRTsystems 0.1 78.8 0.2 61.7

Note:MitigationexpressedinMtCo2e.MitigationcostsexpressedinmillionVNDpertonCO2e.

Page|56

Figure3.6.MACCResultsunderScenario1forAnalysisPeriod2014–2030and2014–2050

53.2

512.0

During 2014–2030 period


Figure 3.6

Page|57

Conclusions

Upto2030,theimplementationofvehiclefueleconomystandardsfornewcarsandmotorcyclesareconsidered the most effective GHG emissions mitigation action, cumulatively accounting for 15.8

million tonsCO2emissions reductionagainstbusiness asusualduring2014 to2030.Other actionsanalyzed,suchasfreightmodalshiftfromroadtowaterway,passengermodalshiftfromprivatetopublictransport,andanincreasedshareofelectricvehicles,alsocontributegreatlytothereduction

ofGHGemissionsinthetransportsector.Withtheabovemeasures,thetransportsectoroverallcanreduceCO2emissionsby9.0percentcomparedtoBAUin2030.

The objectives set out in Vietnam’s transport development plans, such as in the inlandwaterway

infrastructuredevelopmentplanandthepublictransportdevelopmentplan,needalargeinvestmentto generate significant GHG emissions reduction. However, creating the market conditions topromotethechangeofhabitsinvolvedinmodalshiftimpliestheneedformanymeasures—notonly

tomakethecleanermodemoreattractive,butalsotodisincentivizetheuseofon-roadtransport.

Measures that promote the uptake of electric motorcycles beyond the 7 percent of salescontemplated in this report could result in an attractive additional emissions reduction.

Electrification ofmobility solutions represents an area with an expectation of notable technologyinnovationandmarketmaturation,whichare furtherexplored in Scenarios2and3 in subsequentchapters.

Page|59

Chapter4:Scenario2—IncreasingAmbitionwithInternationalSupportandActiveEngagementofthePrivateSector


Mitigation Scenario 2 includes policies andmeasures that can be strengthenedwith international

assistanceunder theShift and Improve componentsof theASI framework, componentsunder theMinistryofTransport(MoT)mandate(figure4.1).


Note:BRT=busrapidtransit;CNG=compressednaturalgas.

Thisextraeffort includesgreatermodalshift fromprivateroadtransport (carsandmotorcycles)tobuses, bus rapid transit (BRT) and metro, promoting more efficient passenger mass transit with

higherloadfactorsandincreasingthesaleofnewelectriccarsandmotorcycles.Table4.1describesthemitigationmeasuresandthelevelofambitionconsideredunderScenario2.

Page|60


Measures Mitigationoptions Assumptions1.1Newvehiclefueleconomyandemissionsstandards

SameasScenario11.Energyefficiency

1.2Improvementoftruckloadfactor

Freightloadfactorimprovesfrom56%to60%


Busdevelopmentin13citiesincluding5citiesofcentralmanagementand9citiesofclass1(Hanoi,HoChiMinhCity,CanTho,DaNang,HaiPhong,VietTri,NamDinh,Vinh,Hue,QuyNhon,DaLat,NhaTrang,andBuonMeThuot)


Hanoi: Line1inoperationin2017; 1newlineinoperationin2025; 2newlinesinoperationin2030DaNang: Line1inoperationin2021; 1newlineinoperationin2030HCMC: Line1inoperationin2021; 2newlinesinoperationin2025CanTho: Line1inoperationin2025; 2lineinoperationin2030HaiPhong: Line1inoperationin2025; Line2inoperationin2030NewBRTlinesusingelectricbusesinHanoiandHCMcityfrom2025

2.Passengermodalshiftfromprivatevehicles


SameasScenario1

3.1ModalshiftfromroadtoIWT

ModalshiftbothforfreightandpassengertransportBy2020:• FTKTbyIWTtoincreasefrom65.0(BAU)to71.2billionton-km(20.7%to22.6%oftotalFTKT);shareofroadtodecreasefrom23.0%to19.1%.

By2030:• FTKTbyIWTtoincreasefrom127.8to128.8billionton-km(20.6%to20.8%oftotal);modalshareofroadtodecreasefrom23.4%to23.0%in2030.


ModalshiftforfreighttransportTheFTKTfromroadtothecoastaltransportisassumedtobedoubletheFTKTshiftedfromroadtoIWTinthesametime

3.Modalshiftfromroad

3.3Modalshiftfromroadtorail

InaccordancetotheDecision318/QĐ-TTgontransportservicedevelopment,thegrowthrateoffreighttransportisexpectedtobe12.5%.ThecalculationassumesthattheFTKTontherailwaywillincreaseatthissameannualrate.


In2018:E540%oftotalgasolinesales(firsthalfof2018)2019–30:E5accountsfor40%oftotalgasolinesales;assumenosupplyconstraint


Electricmotorbikesaccountfor14%ofannualmotorbikesales

4.Fuelchange


HCMC:423CNGbusesin2017Hanoi:50CNGbusesin2018and200unitsby2020

4.4Promotionofelectriccarsandbuses

5%ofannualnewcarsalesin2025;30%ofannualnewcarsalesin2030;allBRTlinesafter2020useelectricbuses

Note:BRT=busrapidtransit;IWT=inlandwaterwaytransport;FTKT=freightton-kmtransported;BAU=businessasusual;CNG=compressednaturalgas;HCMC=HoChiMinhCity.

Page|61

These measures would result in a reduction of projected fuel consumption under Scenario 2, assummarizedintable4.2andfigure4.2.WithScenario2,gasolineconsumptionwouldbelowerthan

businessasusual(BAU)by16percentin2025andby27percentin2030.Dieselconsumptionduringthis period decreases by an average of 7 percent compared to BAU. Such a reduction in fuelconsumptionispossiblebasedonamarkedmodalshiftfrompassengerroadtransporttobuses,BRT

andmetrosystems,andsignificantadoptionofelectricmotorbikesandprivatecars.

Table4.2.ProjectEnergyConsumptionbySourceinTransportSectorunderScenario2

2014 2020 2025 2030 2014 2020 2025 2030Fueltype


Gasoline 4.86 6.36 7.86 8.98 4.60 Mton 6.01 7.43 8.49

Diesel 5.44 7.08 10.03 14.17 5.29 Mton 6.89 9.76 13.80

Fueloil 0.23 0.24 0.30 0.39 0.23 Mton 0.25 0.31 0.40

Jetkerosene 0.37 0.93 1.16 1.44 0.36 Mton 0.88 1.10 1.36

Electricity 0.00 0.02 0.06 0.15 19.4 GWh 278.0 691.0 1,777.9



Table4.3andfigure4.3presentthetotalCO2emissionsfromthetransportsectorandbreakdownbysubsectorunder Scenario2.Compared toBAUandScenario1, steeperemissions reductionwouldoccurintheroadsectorandwaterbornetransport.Theroadsector’sshareofroadsectorofthetotal

emissionswouldmarginallydecrease.

0

5

10

15

20

25

30

2014 2016 2018 2020 2022 2024 2026 2028 2030

Milliontonsoileq

uivalent(M

toe)


Page|62

Table4.3.TransportCO2EmissionsbySubsectorunderScenario2

InmilliontonsCO2


BAUScenario

2BAU

Scenario2

BAUScenario

2BAU

Scenario2

Road 26.4 26.4 37.9 34.5 52.1 46.4 71.7 60.0Railway 0.1 0.1 0.2 0.2 0.2 0.3 0.3 0.5IWTandcoastaltransport

3.5 3.5 4.6 4.7 6.1 5.6 8.2 7.1

Air 1.1 1.1 2.8 2.8 3.5 3.5 4.3 4.3Other 2.1 2.1 2.3 2.0 3.2 2.8 4.6 3.9

Total 33.2 33.2 47.7 44.1 65.1 58.5 89.1 75.6

Figure4.3.TotalCO2EmissionsbyTransportSubsectorsunderScenario2

Scenario2applies11mitigationoptions to reduceCO2emissions in the transport sector. Foreachoption,thespecificemissionsreductionissummarizedintable4.4.

Much like in Scenario 1, Scenario 2 measures to promote modal shifts from road to waterborne

transport would bring in the largest emissions reduction during the 2014 to 2030 period;strengthening of fuel economy and vehicle emissions standards would result in much greateremissions reduction over the 2014 to 2050 period. Figure 4.4 shows these measures and their

contributionstotheoverallemissionsreductionagainsttheBAUscenario.

Contingent to international support, under Scenario 2, emissions from the transport sector areexpected to reduce by 7.5 percent (2020), 10.3 percent (2025), and 15.2 percent (2030), against

businessasusual(table4.5andfigure4.5).

0

10

20

30

40

50

60

70

80

90

2014 2016 2018 2020 2022 2024 2026 2028 2030

MilliontonsCO

2


Page|63

Table4.4.ReductionofCO2EmissionsbyEachMitigationOptionAnalyzedinScenario2

InthousandtonsCO2


2014–30 2014–50

1.1Newfueleconomyandemissionsstandards

0 0 686 4,986 17,250 24,065 15,388 349,787


0 0 840 1,318 2,497 4,854 8,941 64,560


360 389 455 347 608 1,745 6,116 21,711


0 3 35 53 15 52 264 857


0 23 124 115 99 78 1,167 3,119


1 2,661 2,759 1,712 3,404 6,927 30,084 106,853


0 0 401 1,029 1,971 3,845 5,015 48,928

4.1Promotionofbiofuels(E5)

0 280 370 490 738 872 4,708 19,241


0 334 946 1,586 2,851 4,129 10,803 69,120


0 5 5 3 6 3 63 145

4.4Promotionofelectriccars

0 0 64 1,886 8,329 12,576 4,855 168,386

Note:BRT=busrapidtransit;IWT=inlandwaterwaytransport;CNG=compressednaturalgas.

Contingent to international support, under Scenario 2, emissions from the transport sector are

expected to reduce by 7.2 percent (2020), 11.5 percent (2025), and 15.9 percent (2030), againstbusinessasusual(table4.5andfigure4.5).

Page|64


Table4.5.ComparisonofCO2EmissionsfromTransportbetweenBAUandScenario2

InmilliontonsCO2

Scenario 2014 2020 2025 2030





Figure4.5.ComparisonofCO2EmissionsbetweenBAUandScenarios1and2

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Thou

sand

tonsCO

2

1.1Newfueleconomy&emissionstandards1.2Improvementoftruckloadfactor2.1Expansionofbussystems2.2ExpansionofBRTsystems2.3Deploymentofmetrosystems3.1/3.2ModalshiftfromroadtoIWT/Coastal3.3Modalshiftfromroadtorail4.1Promotionofbiofuels(E5)4.2Promotionofelectricmotorbikes4.3IntroductionofCNGbuses

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032

Thou

sand

tonsCO

2

BAU Scenario2 Scenario1

Page|65


Thestudydevelopedtwomarginalabatementcostcurves (MACCs) forScenario2 (shown in figure4.6),coveringtheanalysisperiodsfrom2014to2030and2014to2050.Aslistedintable4.6,from

2014 to 2030 themeasureswith negativemarginal abatement cost (MAC) include 3.1/3.2 (modalshift from road to IWW(inlandwaterway)andcoastal transport), 1.2 (improvements in truck loadfactor),4.2(promotionofelectricmotorbikes),and1.1(newfueleconomystandards).

From2014to2050,asalsoseen inScenario1,mostmeasureswouldgeneratenetbenefitsexceptthemeasureswithheavyupfrontcapital investments suchasmetroandBRTsystems.Particularly,MACs formeasures3.3 (modal shift to railway)and2.1 (expansionofbussystems)wouldbecome

negativeinthelongerterm,astheygenerateneteconomicbenefitsintheperiodbeyond2030.

Table4.6.MACCResultsunderScenario2,forAnalysisPeriod2014–2030and2014–2050


potentialMitigation


Mitigationcost

3.1/3.2ModalshiftfromroadtoIWT/coastal 30.1 (9.6) 106.9 (3.6)

1.2Improvementoftruckloadfactor 8.9 (9.4) 64.6 (3.5)

4.3IntroductionofCNGbuses 0.1 (3.7) 0.2 (2.3)

4.2Promotionofelectricmotorbikes 10.8 (4.7) 69.1 (1.7)

1.1Newfueleconomystandards 15.4 (3.4) 349.8 (1.2)

4.4Promotionofelectriccars 4.9 4.4 168.4 (0.6)

3.3Modalshiftfromroadtorail 5.0 (0.3) 48.9 (0.6)

4.1Promotionofbiofuels 4.7 (0.2) 19.2 (0.1)

2.1Expansionofbussystems 6.1 4.4 21.7 0.1

2.2ExpansionofBRTsystems 0.3 28.5 0.9 14.0

2.3Deploymentofmetrosystems 1.2 40.1 3.1 18.8

Note:MitigationexpressedinMtCo2e;mitigationcostsexpressedinmillionVNDpertonCO2e.

Page|66

Figure4.6.MACCResultsunderScenario2,forAnalysisPeriod2014–2030and2014–2050


1.2

87.5

Figure 4.6

852.8


1.2

Page|67

Conclusions

With international support and active participation of the private sector, under Scenario 2 thetransport sector is expected to reduce 15 percent of its CO2 emissions in 2030, against BAU.

Improvements invehiclefueleconomyareassessedtobethemost impactfulmitigationmeasures,resultinginanemissionsreductionof5.0milliontonsCO2in2030comparedtoBAU.Mainstreamingtheelectric vehiclemarketwouldbe the secondhighest contributor to emissions reductions,with

potentialtoreduce3.5milliontonsCO2 in2030againstBAU.Modalshiftsfromroadtowaterwaysandrailwaysalsohaveasignificantpotentialforemissionsreduction.However,thisisdependentoninfrastructure investments and their timelines. Improvements in freight load factors due to an

improvement in logistics service capability and reduction in empty backhaul is also a remarkableoptiontoreduceCO2emissionsfromthetransportsector.

Page|69

Chapter5:Scenario3—PushingTransformationoftheSectorwithLargerSupportfromInternationalResourcesandStrongPrivateSectorEngagement


MitigationScenario3setsoutavisioninwhichadditionalpoliciesandmeasurescurrentlynotpartofthemandateoftheMinistryofTransport(MoT),topushthelevelofambitionandattainagreater

levelofmitigationimpacts.Thesemeasures,presentedinfigure5.1andtable5.1,wouldpotentiallyrequireagreaterlevelofinvestments.


Note:BRT=busrapidtransit;CNG=compressednaturalgas.

Scenario3 includesall themitigationoptions fromScenario2,butwithanadditionalhigh levelofambitionintable5.1.

Page|70


Measures Mitigationoptions Assumptions

1.1Newvehiclefueleconomyandemissionsstandards

SameasScenarios1and2

1.Energyefficiency

1.2Improvementoftruckloadingfactors

Freightloadfactorimprovesfrom56%to65%.

2.1Bussystems SameasScenario2

2.2BRTsystems SameasScenario22.Passengermodalshiftfromprivatevehicles

2.3Metrosystems SameasScenarios1and2

3.1ModalshiftfromroadtoIWT

SameasScenario2


SameasScenario23.Modalshiftfromroad

3.3Modalshiftfromroadtorailway

SameasScenario2


2018–24:E5increasesgraduallyfrom40%oftotalgasolinesalesin2018upto100%in20242025–30:E5isgraduallyreplacedwithE10,at50%in2025and100%by2030


Electricmotorbikesaccountfor30%oftotaltwo-wheelerfleet


SameasScenario2

4.Fuelchange

4.4Promotionofelectriccarsandbuses

• 5%ofannualnewcarsalesin2025• 30%ofannualnewcarsalesin2030• AllBRTlinesafter2020useelectricbuses• 10%ofbussalesareelectricvehiclesin2020–2030

Note:BRT=busrapidtransport;IWT=inlandwaterwaytransport;CNG=compressednaturalgas.

Page|71

Table5.2andfigure5.2presenttransportsectorfuelconsumptionunderScenario3.WithScenario3,gasolineconsumptionreducesby22percentin2025andby36percentin2030againstbusinessas

usual(BAU).Dieselconsumptionduringthisperioddecreasesbyanaverageof6percentcomparedtotheBAU,similartoScenario2.Suchareductioninfuelconsumptionisattributedtomodalshiftsfromroadfreighttowaterbornetransportandfromprivatevehiclestopublictransport,andrapidly

increasingmarketsharesofelectricmotorbikesandprivatecars.

Table5.2.ProjectedEnergyConsumptionbySourceinTransportSectorunderScenario3

2014 2020 2025 2030 2014 2020 2025 2030EnergySource


Gasoline 4.86 6.14 7.35 8.29 4.60Mton 5.80 6.95 7.83

Diesel 5.44 7.05 9.46 13.25 5.29Mton 6.86 9.21 12.90

Fueloil 0.23 0.24 0.30 0.39 0.23Mton 0.25 0.31 0.40


Electricity 0.00 0.07 0.23 0.44 19.4GWh 767.2 2,634.7 5,081.5


0

5

10

15

20

25

2014 2016 2018 2020 2022 2024 2026 2028 2030

Milliontone

soilequ

ivalen

t(Mtoe)


Page|72


Table5.3andfigure5.3presentthetotalCO2emissionsfromthetransportsectorandbreakdownbysubsector under Scenario 3. A significant emissions reduction would occur in the road sector (23

percent)andwaterbornetransport(13percent).Theroadsectorshareofthetotalemissionswouldfurtherdecrease.

Table5.3.TransportCO2EmissionsbySubsectorunderScenario3

Inmilliontons


BAUScenario

3BAU

Scenario3

BAUScenario

3BAU

Scenario3

Road 26.4 26.4 37.9 33.6 52.1 44.0 71.7 55.5

Railway 0.1 0.1 0.2 0.2 0.2 0.3 0.3 0.5IWTandcoastaltransport

3.5 3.5 4.6 4.7 6.1 5.6 8.2 7.1

Air 1.1 1.1 2.8 2.8 3.5 3.5 4.3 4.3

Other 2.1 2.1 2.3 2.0 3.2 2.8 4.6 3.9

Total 33.2 33.2 47.7 43.3 65.1 56.1 89.1 71.3

Figure5.3.TransportCO2EmissionsbySubsectorsunderScenario3

0

10

20

30

40

50

60

70

80

90

2014 2016 2018 2020 2022 2024 2026 2028 2030

MilliontonsCO

2


Page|73

Each of the 11 measures under Scenario 3 contributes to the overall emissions reduction assummarized in table 5.4. Under this scenario, themeasure to promote electricmotorbikeswould

bring inthegreatestemissionsreductionduringthe2014to2030period,atabout4.4milliontonsCO2 in 2030. This is closely followed by the measures to promote modal shifts from road towaterbornetransport,tostrengthenfueleconomyandvehicleemissionsstandards,andtopromote

theuseofbiofuels.Electricmobility,muchmoreprominentlyfeaturedunderthisscenariocomparedtopreviousones,isprojectedtobringingreatlonger-termreductiontotaling24.2milliontonsCO2in2050. Thesemeasures and their contributions to the overall emissions reduction against the BAU

scenarioaredepictedinfigure5.4.

Table5.4.ReductionofCO2EmissionsbyEachMitigationOptionunderScenario3

Inthousandtons


2014–30 2014–50

1.1Newfueleconomyandemissionsstandards

0 0 656 4,484 15,402 20,902 13,952 310,186


0 0 840 1,318 2,497 4,854 8,941 64,560


360 372 338 211 540 1,713 5,145 19,493


0 2 31 49 17 45 235 804


0 24 119 104 84 75 1,119 2,828


0 2,660 2,758 1,711 3,403 6,927 30,074 106,838


0 0 402 1,030 1,971 3,845 5,022 48,941


0 421 1,416 2,520 3,797 4,484 15,483 90,248


0 1,031 2,723 4,435 8,599 12,810 31,120 207,446


0 0 62 1,794 7,897 11,918 4,640 159,691

4.4Promotionofelectricbuses

0 19 112 188 847 1,388 1,179 18,233

Note:BRT=busrapidtransit;IWT=inlandwaterwaytransport.

Page|74


Insum,Scenario3enables20percentreductioninCO2emissionsby2030,comparedtoBAU,whileScenario 2 results in 15 percent and Scenario 1 results in a 9 percent emissions reduction. These

resultsarepresentedintable5.5andfigure5.5.

Table5.5.ComparisonofTransportCO2EmissionsinBAUandScenario3

InmilliontonsCO2

Scenario 2015 2020 2025 2030





-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Thou

sand

tonsCO

2

1.1Newfueleconomy&emissionstandards





3.1/3.2ModalshiftfromroadtoIWT/Coastal



4.2Promosionofelectricmotorbikes


4.4Promotionofelectricbuses

Page|75

Figure5.5.ComparisonofCO2EmissionsbetweenBAUandScenarios1,2,and3


Figures5.6and5.7presentthetwomarginalabatementcostcurves(MACCs)developedforScenario3,coveringtheanalysisperiodsfrom2014to2030and2014to2050.Duringtheperiodfrom2014to2030, several measures have negative marginal abatement costs (MACs), indicating their cost-

effectiveness. These include 3.1/3.2 (modal shift from road to IWW and coastal transport), 1.2(improvementsintruckloadfactors);4.2(promotionofelectricmotorbikes);and1.1(introductionofnewfueleconomystandards).Asinpreviousscenarios,duringtheperiodfrom2014to2050,most

measuresgeneratenetbenefits,exceptmeasureswithhighupfrontcapitalcosts,suchasmetroandBRTsystems.MACsformeasures4.4(promotionofelectriccarsandbuses)and2.1(expansionofbussystems)wouldbecomenegativeinthelongerterm,astheygenerateneteconomicbenefitsduring

theperiodbeyond2030.

Table5.6.MACCresultsunderScenario3,forAnalysisPeriod2014-2030and2014-2050


potentialMitigation


Mitigationcost

4.3IntroductionofCNGbuses 0.1 (3.8) 1.1 (3.7)3.1/3.2ModalshiftfromroadtoIWT/coastal 30.1 (9.6) 106.8 (3.6)1.2Improvementoftruckloadfactor 8.9 (8.7) 64.6 (3.3)4.2Promotionofelectricmotorbikes 31.1 (4.9) 207.5 (1.7)1.1Newfueleconomystandards 14.0 (3.6) 310.2 (1.3)4.4Promotionofelectriccars 4.6 4.7 159.7 (0.6)3.3Modalshiftfromroadtorail 5.0 (0.3) 48.9 (0.6)4.4Promotionofelectricbuses 1.2 1.4 18.2 (0.1)4.1Promotionofbiofuels 15.5 (0.2) 90.3 (0.1)2.1Expansionofbussystems 5.2 4.8 20.5 0.12.2ExpansionofBRTsystems 0.2 33.3 1.0 19.22.3Deploymentofmetrosystems 1.1 41.6 2.8 19.7

Note:MitigationexpressedinMtCo2e.MitigationcostsexpressedinmillionVNDpertonCO2e.

20

30

40

50

60

70

80

90

20142015201620172018201920202021202220232024202520262027202820292030

MilliontonsCO

2

BAU Scenario3 Scenario2 Scenario1

Page|76

Figure5.6.MACCresultsunderScenario3,forAnalysisPeriod2014–2030and2014–2050


1.2

117.0

1,03

1.6


1.2

MtCO2e

Figure 5.6

MtCO2e

Page|77

Conclusions

Scenario3focusesonmarketdevelopmenttrendssuchasincreasingtheuseofelectricmotorcycles(accountingfor30percentofthetotalnumberofelectricmotorcycles inuse)andelectriccarsand

electricbuses(accountingfor10percentofthenationwidein-usefleet).Also,thefreightloadfactorisexpectedtoimproveupto65percentduetoimprovedfreightconsolidationandefficientlogisticssystem.Scenario3clearlyshowsthatpromotionofanexpandedmarketforelectricvehicleswould

result in significant emissions reductions,with expected implications for the national electric grid.Therefore, these promotional measures—and their expected benefits—would need to be furtheranalyzedandaddressedaccordingly.

Page|79

Chapter6:CostofImplementation

This chapter presents the marginal abatement cost of each GHG emissions mitigation measureconsideredunderthethreescenarios.Themarginalabatementcostprovidesaquantitativebasisfor

discussionabout therelativecost-effectivenessofeachmeasure indeliveringemissions reductionsandtheoverallabatementpotentialofthemeasuresconsidered.Thisanalysiscanserveasinputtodiscussionsonwhichmeasureswouldbe implementedusingnational resources, alongwithwhich

measurescouldbeimplementedconditionaltoreceivinginternationalsupport.

MarginalAbatementCostMethodology

Themarginal abatement cost (MAC) is calculated using data on the incremental cost of emissionssavingsbyeachmeasure,andthepotentialamountofemissionssavingsbyeachmeasureduringthe

periodofanalysis.SeeEquation1,below:

MACM=NPVINC,MM/EMM (1)

Where:

MACM = Marginal abatement cost of the mitigation measure over the analysis period,

comparing the cash flow of implementing the measure to a counterfactual alternativescenario in which this measure is not implemented in thousand VND per ton of CO2e

reduction(thousandVND/tCO2e);

NPVINCMM = Net present value of the difference in cash flow (costs and benefits) ofimplementing the mitigation measure over the analysis period when compared to an

alternative counterfactual scenario in which this measure is not implemented (thousandVND);and

EMM = Reduction in GHG emissions over the analysis period when compared to the

counterfactualscenarioinwhichthismeasureisnotimplemented(tCO2)

The costs and benefits of mitigation measures are analyzed relative to a business-as-usual (BAU)scenario, which reflects what could be expected to have happened had that particularmitigation

policyorinterventionnotbeenimplemented.Thedifferenceincosts(betweenthebusiness-as-usualandmitigationscenarios)includesdifferencesincapitalcosts,operatingcosts,andfuelcostsrelevantto energy use (and should not include transaction costs and taxes). Benefits are limited to cost

savingsassociatedwithreductionsinenergyconsumptionandGHGemissionsanddonotincludeco-benefits such as avoided environmental damages, health costs, avoided congestion, and otherbenefitstosociety.

Thebaseyearforthisstudyis2014,andtheanalysisperiodisfrom2014to2030,toalignwiththeNDCupdateassumptionsdefinedby theMinistryofNaturalResourcesandEnvironment (MoNRE).However,manymeasuresareexpected tobe implemented toward theendof thisperiod, suchas

thedeploymentofmetrorailtransit(MRT),electricbuses,andelectriccars.Inthesecases,modeling

Page|80

to 2030 captures most of the associated, expenses, but few of the benefits since a vehicle’s, orsystem’s useful life extends considerably beyond this date. To address this situation, this study

extended the analytical timeframe to 2050. It should be noted that the extension of the analysisperiod enables capturing fully the benefits associatedwithGHG emissions reductions and did notentailaddinganyadditionalmeasuresafter2030.

AllcashflowvaluespresentedinthisreportareatconstantVND2018values.Fuelpricesin2014aretaken from retail price by Petrolimex, after removal of applicable taxes and fees. Fuel prices until2025areprovidedbytherevisedVietnamPowerDevelopmentPlan(PDP7)forecast.Fuelpricesafter

2025 adjust the 2025 values to accommodate changes in crude oil and gas wholesale prices, asprojectedbyU.S.EnergyInformationAdministration(EIA).

MarginalAbatementCostResultsforEachMeasure

Promotionofbiofuel

The promotion of biofuel considers the share of ethanol in gasoline sales in Vietnam. Ethanol ismixedwith gasoline in two fractions, knownas E5andE10. E5 contains5percentethanol and95

percentgasoline,whileE10contains10percentethanoland90percentgasoline.

According to theMinistryof IndustryandTrade (MoIT), in20181 sevenethanolplantsoperated inVietnam, with a combined production capacity of 600,000 tons, including three plants owned by

PetroVietnam(PVN),namelyPhuTho,QuangNgai,andBinhPhuoc,eachwithanannualproductioncapacityof100,000 tons.2Ethanol canalsobe imported,andatpresent is subject toa20percentimporttax.Ongoingdiscussionprioritizesreducingtheimporttaxto17percentandloweringethanol

pricestoprovidemorechoiceforpetroldistributors.

Ethanolsalesin2018totransporttotaled145thousandtons,andduringthefirstsixmonthsofthatyear,E5accountedfor40.18percentofgasolinesales.

The level of penetration of E5 and E10 in gasoline sales varieswith the level of ambition of eachanalysisscenario,asfollows:

• Scenario1:In2018,E5represents40.18percentofgasolinesales.Overtheperiodfrom2019

to 2030, this percentage reduces tomaintain a constant production (for transport) of 145thousandtonsofethanolperyear.

• Scenario2:EthanolproductionincreasestomaintainE5ataconstant40percentofgasolinesalesovertheperiodto2030.

• Scenario 3: E5 reaches 100 percent of gasoline sales in 2024; 50 percent of the fuel isswitchedtoE10in2025,reaching100percentE10in2030.

Ethanolhaslessenergycontentandahigherspecificdensitythangasoline.Ithasanenergycontent

of0.027gigajoule(GJ)perkgandaspecificdensitygravityof0.79kgperliter,whilegasolinehasanenergycontentof0.0443GJperkgandaspecificdensitygravityof0.74kgperliter.Thus, theenergycontentofE5perliteris98.4percentthatofgasolineandE10is96.8percentofgasoline.

This analysis assumes that, on an energy basis, the prices of E5, E10, and gasolinewill stay equal

(which is the case today). Thus, onamassbasisover theanalysis period, theE5pricewill remain

Page|81

consistentlyat98percentthatofgasoline,withtheE10pricestayingat96percentofthegasolineprice. However, vehicles will consume proportionally more fuel to receive the same amount of

energy.

Table6.1providesthemarginalabatementcost(MAC)resultsforthepromotionofbiofuels,showingthatthismeasureiscost-effectiveforGHGemissionsabatement.

Table6.1.MACCalculationSummaryforPromotionofBiofuel

Valuebyscenarioandanalysisperiod

Scenario1 Scenario2 Scenario3Item Unit

2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcost VNDtrillion — — — — — —

NPVoffuelcost VNDtrillion (0.88) (1.21) (1.13) (2.01) (3.3) (7.97)

NPVofO&Mcost VNDtrillion — — — — — —

Totalcost VNDtrillion (0.88) (1.21) (1.13) (2.01) (3.3) (7.97)

CO2avoided ThousandtCO2 3,497 8,293 4,718 19,256 15,483 90,248

MACVND

million/tCO2(0.252) (0.146) (0.239) (0.105) (0.213) (0.088)

US$/tCO2 (11.5) (6.7) (10.9) (4.8) (9.7) (4.0)

Note:—=notavailable.

MACvaluesarenegativeinallscenariosandbothanalysisperiods.

TheMAC calculated over themore extended period (to 2050) is higher because of how theMACformulaiscalculated:Thenetpresentvalue(NPV)ofthefuturecostsavingsappearssmallerbecausefurtheroutfromthebaseyear,futurevalueshavelessimpactintheNPVwhiletheemissionssavings

arenotdiscounted.

These estimations do not include emissions from the production of ethanol since these areaccountedforinothersectorsoftheeconomyandtheIntergovernmentalPanelonClimateChange

(IPCC)guidelineslooktoavoidduplication.

Promotionofelectricmotorbikes

Thethreescenariosanalyzedthepromotionofelectricmotorbikesatdifferentlevelsofambition,asfollows:

• Scenario1:Electricmotorbikesaccountfor7percentofannualnewmotorbikesales.

• Scenario2:Electricmotorbikesaccountfor14percentofannualnewmotorbikesales.

• Scenario3:Electricmotorbikesaccountfor30percentofthemotorbikein-usepopulationby2030.

Currently,theelectricmotorbikessoldinthemarkethavealowinitialpurchaseprice(whichranges

betweenVND7millionandVND15milliondependingonthemodel),buttheyhaveshortlifetimes(usually less than ten years) and highmaintenance costs because the lead-acid batteriesmust be

replaced,onaverage,everytwoyears.Thus,intermsoflife-cyclecosts,currentelectricmotorbikescanbemoreexpensivethanconventionalgasolinemotorcycles.

Page|82

Newerdesigns featuring lithium-ionbatterieshavea longer lifetime,but are alsomoreexpensive.Forexample, thesalesprice foranelectricmotorcyclewitha lithium-ionbatterymanufacturedby

Vinfast, aVINGROUPcompany, is currentlyaroundVND57million,while comparablemodelswithleadbatteriescostaroundVND34million.However,thecostoflithium-ionbatteries(themajorcostcomponent of electric vehicles), is expected to reduce significantly in the coming years. In 2010,

lithium-ion automotive batteries cost US$1,000 per kilowatt hour (kWh). By 2016, the price hadfallen toUS$273perkWhand isexpectedto reduce further toapricepointofUS$90perkWhby20303or sooner. As production volume increases, other vehicle components are also expected to

experiencecostreductions.

Therefore,theanalysisassumesthatwhenleadingmotorcyclemanufacturerscomeintothemarketwithmainstreamvehicles,thepriceoftheelectricmotorcyclewillbecomparablewiththegasoline-

powereddesignitlookstoreplace,andthelifetimeofthesevehicleswillalsoincreasesubstantiallytothatcurrentlyenjoyedbygasoline-poweredunits.

Additionally, the analysis assumes that by 2025 the currently cheaper, short life lead-acid battery

units will be phased out and substituted by lithium-ion powered motorcycles that can genuinelycompetewithconventionalgasolinemotorcycles.

Concerningthecharginginfrastructure,theanalysisconsideredthatmostelectricmotorcycleswillbe

chargedathome.However,forthesetwo-wheelerstomainstream,theanalysisexpectsLevel2fastchargingstationswillneedtobedeployed,withinternationalexperiencesuggestinganeedforonefastchargingstationper1,000electricmotorcycles.

Table6.2providescostassumptionsforelectricmotorcycles.

Table6.2CostAssumptionsforElectricScooters(LightMotorcycles)

Costitems Unit 2018 2025 2030

Vehiclecost

• Purchasepricea,b VNDmillionpervehicle

13.5 20.8 20.8

• O&McostVNDpervehicle-km

193 130 120

Infrastructurec VNDmillion 328.35 328.35 328.35

Note:a.Pricefor2018isbasedonPEGAelectricscooter,whichisamongstthemostdemandedlightelectricmotorcyclesinthemarket.From2025onwards,thepurchasepriceissettobeequivalenttoHondaWave,whichisthereferencemotorcycle.b.Averagelifetimeofthecurrentlightelectricmotorcyclesisassumedattenyears.From2025onwards,anaveragelifetimeof17.5years,equivalenttothatofaconventionalmotorcycle,isassumed.c.OnefastchargingstationcostsUS$15,000andcanserve1,000electricscooters.

Asshownintable6.3,theMACforthismeasureisnegativeforbothanalysisperiods,indicatingmeasure4.2,promotingelectricmotorbikes,iseconomicallybeneficial.Thereductioninfuelcost

representsthemaincontributortothebeneficialresult.

Page|83

Table6.3.MACCalculationSummaryforPromotionofElectricMotorcycles



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcosta VNDtrillion (5.23) (6.01) (14.40) (16.45) (43.28) (49.57)


NPVofO&Mcost VNDtrillion 0.78 1.00 2.18 2.77 6.64 8.76

NPVofresidualcost

VNDtrillion 1.36 0.23 3.75 0.64 11.32 2.13



MAC VNDmillion/tCO2 (4.66) (1.68) (4.67) (1.69) (4.85) (1.73)

US$/tCO2 (212.85) (76.79) (213.16) (77.32) (221.58) (79.15)

Note:a.Includesinvestmentcostforinfrastructure.

TheGHGemissionspresentedintable6.3excludeGHGemissionsfromelectricitygeneration,asthis

isaccountedforbythepowersector,asperIPCCguidelines.

Newvehiclefueleconomystandards

Newvehiclefueleconomystandardsareconsideredinallthreeanalysisscenariosandareassumedtobedeployedintwostages:

Stage1(2022–2026): •Smallcar(<1400cc):6.1L/100km •Mediumcar(1400-2000cc):7.52L/100km

•Largecar(>2000cc):10.4L/100km Inwhich •2022:50percentofcarsalesmeetthestandard •2023:75percentofcarsalesmeetthestandard

•2024–2026:100percentofcarsalesmeetthestandard •2025:Motorcycles:2.3L/100km

Stage2(from2027): •Smallcar(<1400cc):4.7L/100km

•Mediumcar(1400-2000cc):5.3L/100km •Largecar(>2000cc):6.4L/100km

Inwhich •2027:50percentofcarsalesmeetthestandard •2028:75percentofcarsalesmeetthestandard

• 2029:100percentofcarsalesmeetthestandard

TheimplementationofthesestandardsisaccompaniedbyatransitiontoEuro5emissionsstandardsby 2022,with a resultant and significant improvement in the level of local pollutant emissions ofparticulate matter (PM less than 2.5 microns), Nitrogen oxides (NOx), carbonmonoxide (CO) and

volatileorganiccarbon(VOC).

Vietnam is following the Chinese standard with a five-year lag, which will minimize development

costsforvehiclemanufacturerswhoalreadyhavesupplychainsidentifiedandinplace.However,anynew vehicle emissions or fuel economy standard will require that the manufacturer first

Page|84

demonstrates prototype new vehicles meet the standard and then demonstrates productioncompliance.Forprototypecompliance,themanufacturersubmitsproofincountry-of-origin,butfor

production compliance, MoIT should select vehicles at random for testing in an independentlaboratory.Themanufacturernormallybearsthecostofthetests.

ExperienceinGermany,wherevehiclespecificationshavedevelopedfromEuro2toEuro6emissions

and at the same timemeet strict economy standards, shows despite original estimates of a largecorresponding increase in manufacturing costs, vehicles have not increased in price. This pricestabilityhasbeenduetocompetitivemarketpressureandcreativeproductdesignandsupplychain

management.

Therefore,theonlyexpectedcostassociatedwiththedeploymentofvehiclefueleconomystandardsis administrative cost, e.g., the cost for the formulation of regulations and cost for setting up an

administrativeunittocheckandensureregulationsarebeingmet.

For the purpose of the analysis and based on empirical examples, the following estimates wereappliedforvariouscostitems,asshownintable6.4.Theseinputdatacanbeconfirmedwhenthey

areimplementedinthefuture:

• Cost of two study tours (with 10 delegates each) to learn how fuel economy standards

regulation has been formulated and enacted in other countries = estimated cost per trip:US$50,000

• Costfortechnicalresearchtoapplythisregulation=estimatedUS$50,000

• Cost(governmentfee)toformulatetheregulations=estimatedUS$10,000

• Cost for setting up an office to ensure compliance of these regulations. Office would bestaffed by five employees and located inside theMinistry of Transport (MoT) building to

allowrooms,electricity,waterconsumption,andinternetaccesstobeprovidedbyMoT.Set-upcosts,forofficefurnitureandofficeequipment=estimatedUS$4,000.

• Cost of operating expenses, including wages and social obligations and operations cost(estimated:US$27,000peryear).

Table6.4.ImplementationCostsforNewVehicleFuelEconomyStandards

Costitems(US$) 2019 2020 2021 2022 2030 2050

Studytours 50,000 50,000

Costfortechnicalresearch 50,000

Draftingthelegaltext 10,000

Officeset-up 4,000

Officerunningcost 27,000 27,000 27,000 27,000

Total 100,000 50,000 41,000 27,000 27,000 27,000

Page|85

Policydevelopmentcosts,however,arenotconsideredintheMACCcalculation.Thus,therewillbenoinvestmentcostforthismeasure.

Table6.5providestheMACresultforthemeasureonnewfueleconomystandards.Thisregulation

leadstoreducedgasolineconsumptionbymotorcyclesandcars,which inturnresults indecreasedfuel cost and lower GHG emissions. Thus, its MAC is negative for the three scenarios and both

periods.

Table6.5.MACCalculationSummaryforNewFuelEconomyStandards



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcosta VNDtrillion — — — — — —




CO2avoided ThousandtCO2 14.958 358.571 14.542 347.929 13.343 309.285


US$/tCO2 (154.79) (54.09) (155.71) (54.59) (164.69) (58.20)

Note:—=notavailable.a.Includesinvestmentcostforinfrastructure.

Thoughthismeasureappliesinallthethreescenarios,theimpactofthemeasurewillvaryduetothe

cumulativeeffectofothermeasures.Forexample,Scenario3 introducesmoreelectricmotorcyclesand thus has fewer gasoline motorcycles. Hence, the impact of applying tighter fuel economy

standardstothesegasoline-poweredunitswillconsequentlybelower.

Expansionofbussystems

Bus systemdevelopmentwould result inGHGemissions reductions as a result of amodal shift ofpassengers from motorcycles and private cars toward buses, which can have a lower energyconsumptionperpassenger-km.Theanalysisassumesthatthebusoccupancyratewillimprovefrom

the current 25 percent in 2019 to 50 percent in 2024. Assumptions for theMAC analysis for theexpansionofbussystemsareasfollows:

• Scenario1:Morebusrouteswillbebuiltinfivecentrallymanagedcities—Hanoi,HoChiMinhCity(HCMC),HaiPhong,DaNang,andCanTho.

• Scenarios2and3:Bussystemsareexpandedin13cities,includingtheabovefivecitiesplus

nineClass 1 cities—Hanoi,HCMC,DaNang, CanTho,Hai Phong,Viet Tri,NamDinh,Vinh,Hue,QuyNhon,DaLat,NhaTrang,andBuonMeThuat.

Costitemsofanewbusroutegenerallyincludebuses,aglobalpositioningsystem(GPS),LEDboard,

andcommunicationsystem;infrastructure;fuelcosts,andO&Mcosts.Intermsofinfrastructure,thecostsmightinvolverouteinfrastructureimprovements.

Page|86

Theanalysisassumedthatuserswillmoveonlysomeoftheirtraveltothenewbuses(forexample,commuting towork) and that this will not affect their decisions to purchase privatemotorization

(motorcyclesandcars).

Table6.6providesacostestimateforabusrouteintwocases:(i)withtherequirementforon-routeinfrastructure improvement, and (ii) without investment in on-route infrastructure improvement.

Theyarepresentedperbusunittobeusefulforallscenarios.

Table6.6.CostEstimateforaBusRoute

Costitems UnitBusroutewiththerequirementfor

on-routeimprovementa

Busroutewithoutrequirementfor

on-routeimprovementb

Buscostc US$pervehicle 130,000 130,000

Infrastructureandothers US$pervehicle 156,500 6,600

O&Mcost US$pervehicle-km 0.23 0.23

Note:a.BasedonaprojectfundedbytheWorldBankinHaiPhongb.BasedonanFSforabusroutedevelopmentinDaNangc.Medium-sizedbus,includingGPSandLEDboardandcommunicationsystem

ToderivethecostestimatefortheexpandedbussystemsmeasureandsubsequentlycalculatetheMAC, the analysis assumes that 10 percent of new buses will require on-route infrastructure

improvements investments, while the remaining 90 percent will operate on existing routes andthereforeno infrastructure investmentcostasassigned.This isbasedontheteam’s judgmentthatwhilethebusnetworkexpansionwouldbeprioritizedinareaswherethereisalreadysuitableroad

infrastructureinplace,somenewroutesmayneedimprovementsininfrastructuretoaccommodatealargefleetofbuses.

Table6.7providestheMACresultsforthismeasure.TheMACvalueispositiveoverthe2014to2030

period, indicatingthismeasureismoreexpensivethanthecounterfactualBAUduetothelowloadfactor;until2018,busesoperatedata25percentloadfactor.Inthescenarios,morebuseswouldberequired, incurring more purchase costs and operation costs, which in this case outweighs fuel

savings.However,forthe2014to2050period,theMACissmaller,reflectingmorebenefitsgained(moresaving inpurchasecost, loweroperatingcostsandfuelcosts) thatresult fromthe increasedaveragenumberofpassengersperbus.

Page|87

Table6.7.MACCalculationSummaryforExpansionofBusSystems



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcosta VNDtrillion 118.42 118.42 125.95 125.95 125.95 125.95



NPVofresidualcost VNDtrillion 0.09 5.18 (0.56) 5.24 (0.56) 5.24

Totalcost VNDtrillion 62.93 (5.13) 70.51 3.30 72.01 5.04


MAC VNDmillion/tCO2 4.00 (0.09) 4.43 0.06 4.77 0.09

US$/tCO2 182.9 (3.9) 202.4 2.5 218.0 4.0


These results indicate thatalongwithbusdevelopment, initiatingsupportingmeasures to increase

busloadisequally important,asthiswillmakebussystemsmorecost-effective. Iffamiliesweretoforegobuyingamotorcycleorcarbecauseoftheimprovedbusservice,allMACscouldbenegative,thoughthisisunlikely.

Promotionofelectricbuses

The analysis considered the promotion of electric buses in Scenario 3 and assumed 10 percent of

annualbussalesintheperiodfrom2020to2030wouldbeofelectricbuses.

Table6.8presentsthecostsassociatedwiththismeasure.

Table6.8.CostEstimateforElectricBuses

ValueinCostitems Unit

2020 2025 2030

Electricbuscosta US$pervehicle 189,000 170,400 153,700

Infrastructureandotheritemsb US$pervehicle 86,700 55,011 46,257

O&Mcost US$pervehicle-km 0.14 0.14 0.14

Note:a.Lowerbatterycostsaccountforthereductioninelectricbuscostsovertime.b.Includescivilworksinbusdepots,runways,andstation;depotequipment;signagesystem,andcharginginfrastructure,amongothers.

Theanalysis considered the2014purchasepriceof amedium-sizedelectricbuswasUS$192,000,4approximately1.6timeshigherthananequivalentdieselbus.Theanalysisalsoconsideredthattheprice of batteries, a costly component of electric buses,would decrease over time. Electric buses

havelargebatteriesofabout400kWh,withaverageelectricityenergyconsumptionof1.5to2kWhperkm,givingthebusarangeof150km.Therefore,toincreasetheavailabilityofelectricbuses,is

the analysis assumedadditional batterieswouldbepurchasedand then chargeddailywhilebusesareonduty—and thuswouldbe ready for swapping. In addition, theanalysis considered thatbuschargingsystemswouldbedeployedatbusdepots,allowingforonechargerperthreebusesinthe

Page|88

fleet,5 at a price of around $20,0006 per charger. Electric buses have 30 percent fewer parts thandiesel buses, which dramatically reduces maintenance and operation costs—by approximately 39

percent.7

Themarginalabatementcostofthepromotionofelectricbusesispositiveduringthe2014to2030period,becausethecapitalcostofelectricvehiclesisnotoffsetbythesavingsinfuelconsumption,

O&M,andGHGemissions(seetable6.9).Thefullbenefitsofthismeasureareonlycapturedwhenconsideringtheextendedperiodfrom2014to2050,whichthenseesanegativeMAC.

Table6.9.MACCalculationSummaryfortheDeploymentofElectricBuses


Scenario1 Scenario2 Scenario3Item Unit2014–30

2014–50

2014–30

2014–50

2014–30

2014–50

NPVofcapitalcosta VNDtrillion 4.01 10.71

NPVoffuelcost VNDtrillion (2.44) (12.64)

NPVofO&Mcost VNDtrillion 0.36 1.47

NPVofresidualcost VNDtrillion (0.99) (0.78)

Totalcost VNDtrillion 0.94 (1.24)

CO2avoided ThousandtCO2 686 10,544

MAC VNDmillion/tCO2 1.37 (0.12)

US$/tCO2

Noconsideration Noconsideration

62.6 (5.4)


ExpansionoftheBRTsystem

Theanalysisconsideredtheexpansionofbusrapidtransit(BRT)systemsunderthethreescenarios.Assumptionsforthismeasureareasfollows:

• Scenario1:

• Hanoi:Line1inoperationin2017

• DaNang:Line1inoperationin2021

• HCMC:Line1inoperationin2021;Line2inoperationin2025

• Scenario2:

• Hanoi:Line1inoperationin2017;2newlinesinoperationin2025

• DaNang:Line1inoperationin2021;2newlinesinoperationin2025

• HCMC:Line1inoperationin2021;2newlinesinoperationin2025

• CanTho:Line1inoperationin2025

• HaiPhong:Line1inoperationin2025;Line2inoperationin2030

• NewBRTlinesusingelectricbusesinHanoiandHCMcityfrom2025

• Scenario3:

• SameBRTlinesasinScenario2butnewBRTlinesinHanoiandHCMcityfrom2025willuseelectricbuses

Page|89

ToestimatethecostsassociatedwithBRTdevelopment inVietnamusingdieselbuses,theanalysisused the reportedoperating costs for theBRT line inHanoi alongwith cost estimates for theBRT

linesinDaNangandHCMC.Thesecostitemsarepresentedonaper-vehiclebasisintable6.10.

Table6.10.CostAssumptionsforBRTSystemUsingDieselBuses

Costitems Unit Value

Vehiclecosta US$ 230,000

Infrastructureandothersb US$pervehicle 706,571

O&Mcost US$pervehicle-km 0.36

Note:a.Mediumsized,conventionalbusesb.Civilworksfordepot,runwaysandstation;equipmentfordepot,signagesystemandothers

The investment required for BRT developing using electric buses is more expensive. The analysisassumedthecostratiobetweendieselandelectricbusesusedforBRTwouldbethesameasthatfor

normalbusservices.Similarly,thecostforcharginginfrastructureisassumedtobethesameasthecostfornormalelectricbuses(table6.11).

Table6.11.CostAssumptionsforBRTSystemUsingElectricBuses

ValueinCostitems Unit

2025 2030

Electricbuscosta US$ 300,000 270,000

Infrastructureandothersb US$pervehicle 740,000 731,000

O&Mcost US$pervehicle-km 0.22 0.22

Note:a:Thelowercostin2030isduetoreducedbatterycostb:Civilworksfordepot,runwaysandstation;equipmentfordepot,signagesystem,charginginfrastructureandothers.

Table 6.12 shows theMAC calculation summary for the expansion of BRT systems. Similar to busdevelopment, BRT development would lead to reduced use of motorcycles and private cars andsubsequently less energy consumption due to BRT’s higher energy efficiency on a per-passenger

basis.However,theMACsforthismeasureforbothanalyticalperiodsarepositive,meaningthatthismeasure is not cost-effective for GHG emissions reduction. The high cost of the requiredinfrastructure—whichcannotbecompensatedbysavingsinfuelcosts—stemsfromalowerexpected

passengerflow(andnumberofbuses)thantherequiredBRTinfrastructurewouldneedtobecost-effective.

SinceBRTlineshavealowerpassenger-handlingcapacitythanametrorailsystem,butalsoamuch

lower investment requirement, itwould beworth re-studying the BRT option, perhaps on distinctroutes, considering the transport-related benefits BRT can offer—such as improve travel time,reducedcongestion,andreducedlocalairpollution.

Page|90

ThecalculatedGHGemissionsdonotincludeemissionsfromelectricitygeneration,which,accordingtoIPCCguidelines,arecountedinthepowersectorcategory.

Table6.12.MACCalculationSummaryforExpansionofBRTSystems



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50




NPVofresidualcost VNDtrillion (0.13) (0.02) (2.42) (0.34) (2.41) (0.33)

Totalcost VNDtrillion 2.06 2.51 4.42 7.20 4.46 7.31

CO2avoided ThousandtCO2 26 41 155 515 134 381

MAC VNDmillion/tCO2 78.76 61.70 28.46 13.99 33.32 19.17

US$/tCO2 3,597.78 2,818.81 1,300.05 638.95 1,522.15 875.86


Deploymentofmetrosystems

The analysis assumed ametro rail transit (MRT) systemwould be deployed in all three scenarios,withthesamelevel,asfollows:

• Hanoi:Line2Ainoperationin2019;Line3inoperationin2022

• HCMC:Line1inoperationin2022

Currently, threeMRT lines areunder construction. InHanoi, Line 2A, running fromCat Linh toHa

Dong,willbeoperationalin2019.Line3,connectingNhonandHanoirailwaystation,isexpectedto

startoperationsin2022.Line1inHCMC,the19.7kmBenThanh-SuoiTienline,alsoplanstolaunchoperationsin2022.

Table6.13providesanoverviewofthecostassumptionsformetrosystemsinVietnam.

Table6.13.CostAssumptionsforMetroSystemsinVietnam

Costitems Unit Value Datasource

Investmentcosta• Line2Ain

HanoiVNDbillion 11,529

TEDI(TransportEngineeringDesignInc.2016.HaNoiTransportDevelopmentPlanto2030withVisionto2050.

Line3inHanoi

VNDbillion 20,750TEDI(TransportEngineeringDesignInc.2016.HaNoi

TransportDevelopmentPlanto2030withVisionto2050.

Line1inHCMC

VNDbillion 47,325Revisedinvestmentcost.

(https://english.vietnamnet.vn/fms/business/176266/hcm-city-metro-projects-short-on-capital.html)

O&Mcost

Percentofinitial

investmentcost

1.4%

HCMPC(HoChiMinhCityPeople’sCommittee).2014.EstablishmentProposal:HoChiMinhCityUrbanRailwayNo.1.

(http://open_jicareport.jica.go.jp/pdf/12261772_02.pdf)

Note:a.Investmentcostdoesnotincludelandcompensationcost.

Page|91

Asshownintable6.14,theMACforthedeploymentofanMRTinVietnamispositiveforallscenariosandanalysisperiod.Infrastructurecapitalcostscomposethemaincostelementformetros,withno

savings in fuelorO&Mcostsdueto (i) theoperatingexpectationsof thesemetro lines inVietnamshowingenergyefficienciesandcostsaboveinternationalbenchmarks;and(ii)mostoftheexpectedmodalshiftisfrommotorcycles,whichareahighlyefficientformofpassengertransport,particularly

withtheacceleratedincorporationofelectricmotorcycles.

SimilartoBRT,theMRTmeasureisdrivenmorebytransport-relatedbenefitssuchasreducedtraveltimeandtravelcomfortratherthanthecost-effectivenessforGHGemissionsreduction.Itshouldbe

notedthat,asperIPCCguidelines,8GHGemissionsfromelectricitygenerationarenotincludedintheanalysisasthisisaccountedbythepowersector.

Table6.14.MACCalculationSummaryforDeploymentofMRTSystem



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50


NPVoffuelcost VNDtrillion 0.77 1.53 0.77 1.53 0.77 1.54


NPVofresidualcost VNDtrillion (8.40) 0 (8.4) 0 (8.4) 0

Totalcost VNDtrillion 44.56 55.80 44.58 55.82 44.63 55.90


MAC VNDmillion/tCO2 39.96 18.64 40.14 18.78 41.58 19.72

US$/tCO2 1825.7 851.5 1833.7 858.0 1899.7 901.0


Promotionofelectriccars

ThepromotionofelectriccarsincarsalesisconsideredinScenarios2and3withthesamelevelof

ambition,asfollows:

• 2025:Electriccarsaccountfor5percentannualcarsales

• 2030:Electriccarsaccountfor33percentannualcarsales

Stillanewtechnology,electricvehiclesexperiencemodestsales,evenindevelopedmarkets.Inthe

UnitedStates,battery-poweredelectricvehiclesandplug-inhybridelectricvehicles9nowaccountforjustover1percentofallnewvehiclesales.Between2014and2016,approximatesalesforthetopfour models reached 70,000 for the Tesla Model S, 60,000 for the Nissan LEAF, 60,000 for the

ChevroletVolt,and40,000fortheFordFusionEnergi.10

ForelectriccarsinVietnam,theanalysistakesthepopularNissanLEAFasthereference.TheNissanLEAFhas48lithium-ionmodulesthatstoreupto24kWh.Accordingtothemanufacturer’sdata,the

LEAF has a range of 200 km per charge; however, a range of between 120 and 150 km is morerealistic.In2016,theNissanLEAFretailedintheUnitedStatesforapproximatelyUS$31,500,withthebatteryaccountingfor40percentofthevehicle’scost,down73percentfromUS$1,000perkWhin

2010toUS$273perkWhin2016.AccordingtoConsultancy.uk,thepriceofanautomotivelithium-

Page|92

ionbatterycoulddroptoUS$90perkWhby2030.Ifthissavingsispassedontotheconsumer,onlywithbatterycostimprovement,thepriceofaNissanLEAFcoulddropinrealtermstoUS$25,000in

2025andtoUS$23,000in2030.

Asmajor carmanufacturers enter the electric vehiclemarket, costs should continue to decrease.Volkswagenplans toprice itsupcomingnewgenerationof fully electric vehicles lower than it had

previouslyhinted—aslowas€18,000inEurope,orapproximatelyUS$21,000foranentry-levelfullyelectric model set for a late-2019 launch in the United States.11 In view of this, a Deloitte studypredictsthatby2021,electricvehiclescouldcostthesameasgasolineanddieselcars.12Theanalysis

assumed that by around 2025, electric cars would compete directly with conventional cars inVietnam.

As for the operations and maintenance costs—excluding battery replacement—with fewer parts

versusgasolineanddieselcars,electriccarswouldseeadramaticreductioninO&Mcosts.

Thepromotionofelectriccarsdoesrequireaninvestmentincharginginfrastructure.AnormalLevel2charger(withapowercapacitybetween2and4kilowattsandachargingtimefrom3to6hours)

costs between US$500 and US$1,500. However, not all car owners have garages where normalchargerscanbeinstalled,indicatingtheneedtoinstallsemi-fastchargersforpublicuse.Currentlyinthe Netherlands, nearly 50,000 fully electric cars drive on Dutch roads. In Amsterdam alone, 838

publicchargingstationsofferatotalof2,000chargingpoints.InVietnam,approximately50percentofelectriccarswouldrelyonpublicchargers.Internationalexperiencesuggestsdevelopingonefast-charging station per 100 electric cars,with each charging station costing betweenUS$10,000 and

US$20,000.Figure6.1providesanexampleoffast-chargingstation,locatedattheMoIT.Inaddition,theanalysisexpects thedevelopmentanddeploymentofat-homechargersandsemi-fastchargers

forpublicuse.Asemi-fastchargercostsbetweenUS$1,500andUS$5,000.

Table6.15liststhesummarycostassumptionsforelectriccars,includingpurchaseprice,O&M,andinfrastructure.

Table6.15.SummaryCostAssumptionsforElectricCars

Costitems Unit 2025 2030

Vehiclecost• Purchasepricea VNDmillionpervehicle 612 612

• O&Mcost VNDpervehicle-km 329 329

Infrastructure VNDmillionpervehicle 59.10 59.10

Note:a.From2025onwards,purchasepriceissettobeequivalenttoToyotaVios,whichisthereferencecar<2L.

Page|93

Figure6.1.AFastChargerattheMinistryofIndustryandTradeBuildinginHanoi

Though this measure requires investment cost for electric vehicles and infrastructure, it leads toreducedfuelandO&Mcosts.Thetotalcostfortheelectriccarsmeasureduringtheperiodfrom2014

to2030 ispositivebecausebenefitsarenot fullycaptured (electriccarswouldbe firstdeployed in2025), rendering a positiveMAC value. After the benefits are fully captured in the 2014 to 2050period,thetotalcostandMACresultsbecomenegative.

Table6.16.MACCalculationSummaryforPromotionofElectricCars



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcosta VNDtrillion 32.68 105.18 32.68 105.18

NPVoffuelcost VNDtrillion (15.54) (182.44) (15.27) (178.42)

NPVofO&Mcost VNDtrillion (2.20) (26.56) (2.20) (26.56)

NPVofresidualcost VNDtrillion 6.06 3.52 6.06 3.52

Totalcost VNDtrillion 21.00 (100.29) 21.27 (96.27)

CO2avoided ThousandtCO2 4,804 162,767 4,570 153,982

MAC VNDmillion/tCO2 4.37 (0.62) 4.65 (0.63)

US$/tCO2

Noconsideration

199.7 (28.1) 212.6 (28.6)

Note:a.Includesinvestmentcostforinfrastructure(chargestations).

Page|94

Freightmodalshiftfromroadtoinlandwaterwayandtocoastalshipping

Anothermeasure considered in the analysis is the promotion of freightmodal shift from road toinland waterway transport (IWT) and coastal transport. The assumptions for this measure are as

follows:

Scenario1:

• IWTby2020:Freightton-kmtransported(FTKT)to increasefrom65.0(BAU)to71.2billionton-km

• Coastalby2020:FTKTtoincreasefrom172.0(BAU)to178.2billionton-km

• IWTby2030:FTKTtoincreasefrom127.8to128.8billionton-km


Scenario2andScenario3:

• IWTby2020:FTKTsameasScenario1


• IWTby2030:FTKTsameasScenario1


Enabling this level of modal shift requires investments in inland waterway and coastal transport

infrastructure.

ThefollowinginvestmentsininlandwaterwayinfrastructureareconsideredinScenario1:

• UpgradethewaterwaycorridoroftheRedRiverDelta

• UpgradethewaterwaycorridoroftheMekongDelta

• ImprovetheChoGaoCanal

• Upgradetheportfacilities(e.g.,crane)tohandlecargofromtruckstoships

• Constructnewriverports

ThefollowinginvestmentsincoastaltransportinfrastructureareconsideredinScenario1:

• Upgradecoastalcorridoranddevelopmentandupgradeoflogisticinfrastructure

• Constructnewseaports

ForScenario2,theanalysisassumedanincreasedcapacityofinlandcontainerdepots(ICDs)nearHai

Phong and HCMC to enable shipment of containerized cargo for long hauls and upgrade of roadinfrastructurenearports.

Costsfortheseinterventionsarepresentedintable6.17.

Page|95

Table6.17.CostAssumptionsforInducingModalShiftofFreightfromRoadtoInlandWaterwaysandCoastalTransport

Scenario Subsector ActionCost

US$million

Scenario1 IWT RedRiverDelta:UpgradewaterwayCorridor1a 200.0

Scenario1 IWT MekongRiverDelta:Upgradewaterwaycorridora 216.6

Scenario1 IWT ImproveChoGaoCanalb 39.5

Scenario1 IWT Upgradeportfacilitiesupgrade(e.g.,crane)c 35.4

Scenario1 Coastal Upgradecoastalcorridorandlogisticinfrastructurea 340.0

Scenario2and3 Coastal SetupICDsandcapacityimprovementc 300.0

Scenario2and3 Coastal Upgraderoadinfrastructurenearportsc 398.0

Source:a.BlancasMendiviletal2013.b.WorldBank2017.c.WorldBank2018.

MACcalculationsforthismeasurearepresentedintable6.18,table6.19andtable6.20,whichshownegativeMACvaluesinallthreescenariosandforbothanalyticalperiods,indicatingthismodalshift

from road to inland and coastal waterway transport would be cost-effective measure for GHGemissions reduction. Looking into thecost structureof thismeasure, it seems that thismeasure isalso cost-effective for transport efficiency improvement, since all cost items see a reduction,with

reducedcostsassociatedwith thepurchaseofnew trucksaswell asoperationalandmaintenancecosts. In inlandwaterways, the incremental investment foradditionalvessels tohandle the freightpreviouslytransportedbyroadwouldbeoffsetsomewhatbyashiftfromthecurrentfleetofmainly

small vessels to more medium and large vessels. The measure would also provide fuel savings,associatedwithimprovedmodeefficiencyandtheshifttolargervessels.

Intermsofmobility,thismeasureisalsocost-effective.Thereducednumberofrequiredtrucksand

improvements in transport and fuel efficiency—resulting from the shift to larger vessel sizes—producelowertotalsoncostitems.

Page|96

Table6.18.MACCalculationSummaryforModalShiftfromRoadtoIWTandCoastalWaterwaysforScenario1

Valuebyrelatedsectorandanalysisperiod

RoadIWTand

coastaltransportTotalItem Unit

2014–2030

2014–2050

2014–2030

2014–2050

2014–2030

2014–2050

NPVofcapitalcosta VNDtrillion (109.35) (127.64) 35.08 39.77 (74.27) (87.87)


NPVofO&Mcost VNDtrillion (24.21) (27.40) 0.56 0.82 (23.66) (26.57)

NPVofresidualcost VNDtrillion (9.59) 1.93 5.47 (1.80) (4.11) 0.13

Totalcost VNDtrillion (206.18) (228.33) 21.20 (34.73) (185.01) (263.07)


MAC VNDmillion/tCO2 (8.90) (3.09)

US$/tCO2 (407) (141)

Note:—=notavailable.a.Includesinvestmentcostforinfrastructure.



RoadIWTand

coastaltransportTotalItem Unit

2014–2030

2014–2050

2014–2030

2014–2050

2014–2030

2014–2050







MAC VNDmillion/tCO2 (9.64) (3,63)

US$/tCO2 (440) (166)


Page|97



RoadIWTand

coastalwaterwayTotalItem Unit

2014–2030

2014–2050

2014–2030

2014–2050

2014–2030

2014–2050








US$/tCO2 (440) (166)

Note:a.Includesinvestmentcostforinfrastructure(includinglogisticsparks).

Modalshiftfromroadtorailway

Scenario2andScenario3considerthemodalshiftof freight transport fromroadtorailways,withdeploymentlevelsasfollows:

• Freighttraffic(FTKT)toincreasefrom4.4(BAU)to5.1billionton-kmby2020

• Freighttraffic(FTKT)toincreasefrom8.6(BAU)to16.5billionton-kmby2030

The shift to railwaywill require investment in train carriages and railway infrastructure, including

development, improvement of railway freight terminals and ICDs, railway expansion, access ports,andcargohandlingfacilities.Table6.21presentsthecostassumptionsforthismeasure.

Tables6.22and6.23provideMACcalculationsummaryforthismeasureforScenario2andScenario3.Ascoveredabove,thismeasurerequiresinvestmentinrollingstockandinfrastructure,butthesecostsarecompensatedbythereducedneedtopurchasetrucksandinparticularareductioninon-

roadfuelcost.Intotal,thecostsassociatedwiththismeasurearenegative.Therefore,thismeasureiscost-effectiveforGHGemissionsreduction.

Page|98

Table6.21.CostAssumptionsforDeploymentofRailPassengerandFreightSystems

Costitems Unit Value Datasource

Investmentcost

Diesellocomotive VNDbillion 15.76

VietnamExpressnewsarticle(2004):“VietnamBought20NewChinese

Locomotives.”

https://vnexpress.net/tin-tuc/thoi-su/vn-mua-20-dau-may-xe-lua-moi-cua-trung-

quoc-2000471.html(accessedOctober2018)

Passengercar VNDbillion 10.60

TuoiTrenewsarticle(2018):“Bringing6NewTrainstoExploit

ThongNhatRailway.”

https://tuoitre.vn/dua-6-doan-tau-moi-vao-khai-thac-tuyen-duong-sat-thong-

nhat-20180110224437811.htm(accessedOctober2018)

Freightcar VNDbillion 6.91 Assumedat65%ofpassengercar

Infrastructure VNDbillion/locomotive 631.00

Basedonthemasterplanforrailwaydevelopment,inparticularbasedon

plannednumberofnewlocomotivesandtherequiredinfrastructure

O&Mcost

Operatingcost(E+03)VND/locomotive-

km44.60

Operatingcost (E+03)VND/car-km 5.10

Infrastructurecost (E+03)VND/train-km 16.20

Personnelcost,traincontrol,management

(E+03)VND/train-km 43.0

WorldBank.2018(unpublished).StrengtheningSectorPerformanceforRailTransportServicesinVietnam–Phase2.

Page|99

Table6.22.MACCalculationSummaryforModalShiftfromRoadtoRailforScenario2


Road Railway TotalItem Unit2014–2030

2014–2050

2014–2030

2014–2050

2014–2030

2014–2050

NPVofcapitalcosta VNDtrillion (46.56) (92.76) 42.10 103.81 (4.45) 11.06

NPVoffuelcost VNDtrillion (18.57) (68.63) 3.99 14.54 (14.59) (54.10)

NPVofO&Mcost VNDtrillion (5.80) (18.42) 10.54 33.31 4.74 14.89

NPVofresidualcost VNDtrillion 19.58 8.64 (6.84) (8.00) 12.74 0.64

Totalcost VNDtrillion (51.35) (171.16) 49.79 143.65 (1.56) (27.50)

CO2avoided ThousandtCO2 5,384 52,747 (846) (8,276) 4,538 44,471


US$/tCO2 (15.67) (28.25)

Note:a.Includesinvestmentcostforinfrastructure(chargestations).

Table6.23.MACCalculationSummaryforModalShiftfromRoadtoRailforScenario3


Road Railway TotalItem Unit2014–2030

2014–2050

2014–2030

2014–2050

2014–2030

2014–2050

NPVofcapitalcosta VNDtrillion (46.56) (92.76) 42.10 103.81 (4.45) 11.06

NPVoffuelcost VNDtrillion (18.57) (68.63) 3.99 14.54 (14.59) (54.10)

NPVofO&Mcost VNDtrillion (5.80) (18.42) 10.54 33.31 4.74 14.89

NPVofresidualcost VNDtrillion 19.58 8.64 (6.84) (8.00) 12.74 0.64

Totalcost VNDtrillion (51.35) (171.16) 49.79 143.65 (1.56) (27.50)

CO2avoided ThousandtCO2 5,384 52,747 (846) (8,276) 4,538 44,471


US$/tCO2 (15.67) (28.25)


IntroductionofCNGbuses

This measure pertains to the introduction of CNG buses—which run on compressed natural gas(CNG)—incityfleets,underthethreeanalysisscenarios,asfollows:

• HCMC:423unitsin2017

• HaNoi:50unitsin2018and200unitsin2020

Generally, CNG buses are more expensive than diesel buses and the deployment of CNG buses

require the installation of CNG filling stations. A CNG filling station for 100 buses can costapproximatelyUS$1million.Table6.24presentsthecostassumptionsforthismeasure.

Page|100

Table6.24.CostAssumptionforDeploymentCNGBuses

Costitems Unit Value

Buscosta US$pervehicle 140,000

Infrastructureandothersb US$pervehicle 21,590

O&Mcost US$pervehicle-km 0.23

CNGfillingstationc US$perstation 1,000,000

Note:a.Mediumsizedbus,includingGPSsystem,LEDboard,andcommunicationsystem.b.Includescostsforbusstopsanddepots.Thiscostcomponentissimilartothatofdieselbuses.c.Fillingstationfor100CNGbuses.

Despitehigherbuscostandadditionalinfrastructurerequirement(e.g.,CNGfillingstations)

comparedtodieselbuses,theCNGbusmeasuresavesmoneyduetothelowerCNGfuelcosts,shownintable6.25.MACvaluesforbothanalyticalperiodsarenegative.

Table6.25.MACCalculationSummaryforDeploymentofCNGBuses



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50




NPVofresidualcost VNDtrillion — — — — — —


CO2avoided ThousandtCO2 152.7 333.7 152.7 333.7 120.1 127.5


US$/tCO2 (168) (103) (168) (103) (174) (170)

Note:—=notavailable.a.Includesinvestmentcostforinfrastructure(includingCNGfillingstations).

Improvementoftruckloadfactor

Scenario2andScenario3considertheimprovementoftruckloadfactors,asfollows:

• Scenario2:increasestheaveragetruckloadingfactorfrom47percentin2014,to56percentin2018,and60percentin2027

• Scenario3:increasesfrom47percentin2014,to56percentin2018,and65percentin2027

The deployment of logistics parks near industrial parks and seaports is anticipated to enable

multimodalityand freightaggregation,atacostofaroundVND9,500billion (Lametal2019).TheanalysisassumestheScenario2investmentwoulddoubleforScenario3.

TheMAC for thismeasure isnegative forbothscenarios, indicatingcost-effectiveness for reducingGHG emissions. As presented in table 6.26, this measure results in a reduction of fuel costs andnumberoftrucksrequired,therebyreducingcapitalaswellasO&Mcosts.Thesesavingsmorethan

offsettheexpectedinvestmentcostsrequiredtoimprovethelogisticsinfrastructure.

Page|101

Table6.26.MACCalculationSummaryforImprovementofTruckLoadFactor



2014–30 2014–50 2014–30 2014–50 2014–30 2014–50

NPVofcapitalcosta VNDtrillion (56.24) (106.49) (100.19) (203.26)

NPVoffuelcost VNDtrillion (9.55) (23.09) (15.79) (43.89)

NPVofO&Mcost VNDtrillion 18.60 9.14 41.15 19.04

NPVofresidualcost VNDtrillion (76.64) (203.49) (125.15) (389.75)

Totalcost VNDtrillion 8,132 58,719 14,374 119,456

CO2avoided ThousandtCO2 (9.42) (3.47) (8.71) (3.26)

MAC VNDmillion/tCO2 (431) (158) (398) (149)

US$/tCO2

Noconsideration

(56.24) (106.49) (100.19) (203.26)

Note:a.Includesinvestmentcostforinfrastructure(includinglogisticsparks).

MarginalAbatementCostCurve

Themarginalabatementcostcurve(MACC)providesaneffectivevisualizationtoolthatenablesthe

comparison of GHG emissions mitigation measures based on their cost-effectiveness and theirpotentialforemissionsreduction.

Themarginalabatementcost,orMAC,resultswheneachmeasureispresentedinagraph,ordered

fromthelowesttothehighestMACvalue,whichthenshowsthecumulativemitigation.Thegraph’sx-axisofthegraphrepresentsthecumulativeCO2eabatementpotentialofthemitigationmeasuresduringtheanalysistimespan,whilethey-axisrepresentsthecostassociatedwithareductionofone

tonCO2eemissionsprovidedbyeachoftheanalyzedmeasures.

Measuresthatappearabovezerointhey-axisreflectapositivecost,meaningthenetpresentvalue(NPV)—across the analytical time span—of the cash flow (investment, operating costs, and fuel

costs)associatedwithimplementingthemeasureishigherthanthecounterfactualalternativeintheBAUscenario.

Measures that fall below zero on the y-axis reflect a negative cost,meaning that thosemeasures

offer net cost savings compared to the BAU. For these economically attractive measures, it isimportant toanalyzewhy theyhavenotbeen implementedpreviously, todiscoveranybarriers toimplementationthatcouldberemovedviaincentivesorotherpolicymeasures.

Table 6.27 provides an overview of the mitigation potential and cost of mitigation measuresconsideredundereachofthethreescenarios,inbothanalysisperiods.

Page|102

Table6.27.MitigationPotentialandCostsofMitigationbyScenarios

2014–2030 2014–2050Scenarioandmeasure Mitigation

potentialMitigation


Mitigationcost

Scenario13.1/3.2ModalshiftfromroadtoIWT/coastal 22.8 (8.9) 93.5 (3.1)4.3IntroductionofCNGbuses 0.1 (3.7) 0.2 (2.3)4.2Promotionofelectricmotorbikes 3.9 (4.7) 25.3 (1.7)1.1Newfueleconomystandards 15.8 (3.4) 360.5 (1.2)4.1Promotionofbiofuels 3.5 (0.3) 8.3 (0.2)2.1Expansionofbussystems 5.8 4.0 20.8 (0.1)2.3Deploymentofmetrosystems 1.2 40.0 3.2 18.62.2ExpansionofBRTsystems 0.1 78.8 0.2 61.7Scenario23.1/3.2ModalshiftfromroadtoIWT/coastal 30.1 (9.6) 106.9 (3.6)1.2Improvementoftruckloadfactor 8.9 (9.4) 64.6 (3.5)4.3IntroductionofCNGbuses 0.1 (3.7) 0.2 (2.3)4.2Promotionofelectricmotorbikes 10.8 (4.7) 69.1 (1.7)1.1Newfueleconomystandards 15.4 (3.4) 349.8 (1.2)4.4Promotionofelectriccars 4.9 4.4 168.4 (0.6)3.3Modalshiftfromroadtorail 5.0 (0.3) 48.9 (0.6)4.1Promotionofbiofuels 4.7 (0.2) 19.2 (0.1)2.1Expansionofbussystems 6.1 4.4 21.7 0.12.2ExpansionofBRTsystems 0.3 28.5 0.9 14.02.3Deploymentofmetrosystems 1.2 40.1 3.1 18.8Scenario3 4.3IntroductionofCNGbuses 0.1 (3.8) 1.1 (3.7)3.1/3.2ModalshiftfromroadtoIWT/coastal 30.1 (9.6) 106.8 (3.6)1.2Improvementoftruckloadfactor 8.9 (8.7) 64.6 (3.3)4.2Promotionofelectricmotorbikes 31.1 (4.9) 207.5 (1.7)1.1Newfueleconomystandards 14.0 (3.6) 310.2 (1.3)4.4Promotionofelectriccars 4.6 4.7 159.7 (0.6)3.3Modalshiftfromroadtorail 5.0 (0.3) 48.9 (0.6)4.4Promotionofelectricbuses 1.2 1.4 18.2 (0.1)4.1Promotionofbiofuels 15.5 (0.2) 90.3 (0.1)2.1Expansionofbussystems 5.2 4.8 20.5 0.12.2ExpansionofBRTsystems 0.2 33.3 1.0 19.22.3Deploymentofmetrosystems 1.1 41.6 2.8 19.7

Note:Mitigationexpressedinmillion(metric)tonscarbondioxideequivalent(MtCO2e).CostexpressedinmillionVNDpertonCO2e.

UnderScenario1, fiveoutofeightmitigationmeasureshavenegativeMACvalues,meaning thesemeasureswouldsavemoneyifimplemented.Fortheperiodfrom2014to2030,thetotalmitigation

potential for thesemeasures is 46million tCO2e, or 86percentof totalmitigationpotential underScenario1.Themeasuresinthisperiodwiththelargestmitigationpotential include3.1/3.2(modalshift from road to IWT and coastal transport), 2.1 (expansion of bus systems), and 1.1 (new fuel

economystandards).Thesethreemeasuresaccountfor83percentoftotalmitigationpotential fortheperiodfrom2014to2030.

UnderScenario1,measure2.2(expansionofBRTsystems)and2.3(deploymentofmetrosystems)

have positiveMAC, indicating thesemeasures are not cost-effective forGHGemissions reduction.

Page|103

Part of the reason, particularly for BRT, are the analysis assumptions of (i) very conservative low-volume corridors (but high-volume infrastructure) and (ii) low level of emissions reduction since

many new bus ormetro userswould shift from riding fuel-efficientmotorcycles that can carry atleastonepassenger.Theexpansionofbussystemsisnotacost-effectivemeasureforGHGemissionsreductions,butthecost-efficiencyofthismeasurecanbeimprovedbyincreasingthebusloadfactor.

For Scenario 1, the total investment cost (capital costs associated with vehicles and requiredinfrastructure) is estimated at VND 252 trillion for 2014 to 2030; the cost for measures with anegativeMACtotalsVND169.6trillion(67.2percentoftotalinvestmentcost).Measuresshowingthe

highest investment cost include 2.2 (expansion of bus systems) and 2.3 (deployment of metrosystems),whichare,unfortunately,notcost-effectiveasGHGemissionsreductionmeasures.

UnderScenario2,sevenoutofelevenmeasuresfortheperiodfrom2014to2030andsevenoutof

elevenmeasures for theperiod from2014to2050havenegativeMACs,meaning thesemitigationmeasures are cost-effective. These measures include 3.1/3.2 (modal shift from road to inlandwaterwayandcoastaltransport),1.1(establishmentofnewfueleconomystandards),4.1(promotion

ofbiofuels),and4.2(promotionofelectricmotorcycles).

For Scenario 2, from 2014 to 2030 the total investment required (capital costs associated withvehicles and required infrastructure) is estimated at VND 1,082 trillion; costs formeasureswith a

negativeMACtotalsVND232.67trillion(21.5percentoftotal investmentcost).Despitehavingthehighest investment cost, measure 4.4 (promotion of electric cars) has the potential to be a cost-effectivemeasure.

Under Scenario 3, seven out of twelvemeasures for the period of 2014 to 2030 and nine out ofeleven measures for the period of 2014 to 2050 have negative MACs, indicating their cost-

effectiveness.Thetotalmitigationpotentialforthesemeasures,from2014to2030,is106.32milliontCO2e,or83percentofthescenario’stotalmitigationpotential.

Measure4.4(promotionofelectricbuses),whichisanaddedmeasure,canbecost-effectiveforGHG

emissions reduction. It shouldbenoted thatemissionsdue toelectricconsumptionwereexcludedfromtheanalysis.Emissionsreductionscanbescaledupwiththedeploymentofothercost-effectivemeasures,suchasthepromotionofbiofuelsandelectricmotorcycles,andtheimprovementoftruck

loadfactors.

ThetotalinvestmentrequiredforScenario3(capitalcostsassociatedwithacquisitionofvehiclesanddeploymentofrequiredinfrastructure)isestimatedatVND1,273trillionfortheperiodfrom2014to

2030,withVND416trillion(32.6percenttotal investment)ofthatamounthavinganegativeMAC.Measure4.4(promotionofelectriccars)representsthemeasurewiththehighest investmentcost,accountingfor49.2percentofthetotalinvestmentcostrequiredinScenario3.

Page|104

Notes

1.CafeF2018.

2.Seepage15inPetroVietnam2019.

3.SeetheEnvironmentalandEnergyStudyInstitute(EESI)“FactSheet:Plug-inElectricVehicles(2017).”Accessedonline:https://www.eesi.org/papers/view/fact-sheet-plug-in-electric-vehicles-2017.

4.JICA2016.

5.Luetal2018.

6.Seepage49inKarlsson2016.

7.SeePROTERRA’soverviewdiscussiononelectricvehicles:http://proterra.com.

8.SeeChapter2(“StationaryCombustion”)inVolume2ofthe2006IPCCGuidelinesforNationalGreenhouseGasInventories:

https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/2_Volume2/V2_2_Ch2_Stationary_Combustion.pdf.

9.Plug-inhybridelectricvehicles(PHEVs)arepoweredbyacombinationofgridelectricityandliquidfuel.

10.SeetheEnvironmentalandEnergyStudyInstitute(EESI)“FactSheet:Plug-inElectricVehicles(2017).”Accessedonline:https://www.eesi.org/papers/view/fact-sheet-plug-in-electric-vehicles-2017#5.

11.Halverson2018.

12.Edelstein2019.

References

BlancasMendivil,LuisC.;El-Hifnawi,M.Baher.2013.Facilitatingtradethroughcompetitive,low-

carbontransport:thecaseforVietnam'sinlandandcoastalwaterways(English).Directionsindevelopment;countriesandregions.Washington,DC:WorldBankGroup.http://documents.worldbank.org/curated/en/800501468320727668/Facilitating-trade-through-

competitive-low-carbon-transport-the-case-for-Vietnams-inland-and-coastal-waterways

CafeF.2018.“Vìsaocó7nhàmáysảnxuấtnhưngchỉmộtcôngtyquyếtđịnhsốlượngxăngE5ởViệtNam?”[inVietnamese].CafeF,May8.http://cafef.vn/vi-sao-co-7-nha-may-san-xuat-nhung-chi-

mot-cong-ty-quyet-dinh-so-luong-xang-e5-o-viet-nam-20180427100053261.chn.

Edelstein,Stephen.2019.“ElectricVehiclesCouldCosttheSameasGasolineandDieselCarsby2021:Report.”TheDrive,January21.https://www.thedrive.com/news/26087/electric-vehicles-could-

cost-the-same-as-gasoline-and-diesel-cars-by-2021-report.

Halverson,Bengt.2018.“BasePriceofVW'sElectricCarsCouldBeAsLowAs$21,000.”GreenCarReports,November9.https://www2.greencarreports.com/news/1119827_base-price-of-vws-

electric-cars-could-be-as-low-as-21000

Page|105

JICA(JapanInternationalCooperationAgency).2016.“SocialistRepublicofVietnamDataCollectionSurveyonBRTinHanoi:FinalReport.”Tokyo:JICA.

http://open_jicareport.jica.go.jp/pdf/12266391_01.pdf

Karlsson,Elin.2016.“ChargingInfrastructureforElectricCityBuses:AnAnalysisofGridImpactandCosts.”Studentthesis.Stockholm:DepartmentofElectricPowerandEnergySystems,Royal

InstituteofTechnology,KTH.

Lam,YinYin,KaushikSriram,andNavdhaKhera.2019.StrengtheningVietnam’sTruckingSector:TowardsLowerLogisticsCostsandGreenhouseGasEmissions.VietnamTransportKnowledge

Series.Washington,DC:WorldBankGroup.http://documents.worldbank.org/curated/en/165301554201962827/Strengthening-Vietnam-s-Trucking-Sector-Towards-Lower-Logistics-Costs-and-Greenhouse-Gas-Emissions.

Lu,Lu,LuluXue,andWeiminZhou.2018.“HowDidShenzhen,ChinaBuildWorld’sLargestElectricBus Fleet?”World Resources Institute (blog), April 4. https://www.wri.org/blog/2018/04/how-did-shenzhen-china-build-world-s-largest-electric-bus-fleet.

PetroVietnam.2019.AnnualReport2018.Hanoi:PetroVietnam.https://www.pvoil.com.vn/Data/Sites/1/media/tai-lieu/%C4%91hc%C4%912019/cbtt_baocaothuongnien-pvoil-2018-eng.pdf.

WorldBank.2017(unpublished).FeasibilityStudyforVietnamSouthernRegionWaterwaysandTransportLogisticsCorridorProject.

WorldBank.2018(unpublished).StrengtheningSectorPerformanceforRailTransportServicesin

Vietnam–Phase2

Page|107

Chapter7:ConclusionsandPolicyRecommendations

Vietnam is committed to climate change mitigation, and the transport sector can provide asignificantcontributiontogreenhousegas(GHG)emissionsreductions.In2014,thetransportsectoremitted33.2milliontonsofCO2.Withgrowingtransportdemandandmotorization,theseemissions

areprojectedtoincreaseinabusiness-as-usual(BAU)scenario,atanannualaveragerateof6to7percent,reaching89.1milliontonsin2030.

Road transport is the highest source of CO2 emissions, with nearly 80 percent of total transport

emissions in 2014. Inlandwaterways and coastal transport emissions account for an additional 11percent of the total transport CO2 emissions. Rail produces the smallest source of transport CO2

emissionsduetoitslowlevelsofactivityandemissionsintensity.

The study’s analysis defined three GHG emissions mitigation scenarios based on a review of theGovernment of Vietnam’s policies and regulatory framework and through consultation ofgovernmentauthoritiesandlocalstakeholders.ThesescenariosindicateitispossibletoreduceGHG

emissionssignificantly,withtheanalysisshowingVietnamcouldachievea9percentreductioninCO2emissions by deploying the measures considered in transport development plans and by usingdomestic resources (Scenario 1).With international support, Vietnam could reduce CO2 emissions

evenfurther,from15to20percentby2030(Scenarios2and3).

The analysis expects most emissions mitigation measures to be highly cost-effective, generatingsignificanteconomicbenefitsthroughreducedtransportcosts.Otherco-benefitssuchasareduction

inlocalpollutantshavenotbeenquantifiedintheanalysis;nevertheless,theywouldbesignificant.

The study’s economic analysis of emissions scenarios indicates that ambition would pay off. Thepresent value (NPV) of additional investment needs (both public and private) compared to BAU

decreasessignificantlywith the levelofambition ineachscenarioandarenegativeunderall threescenarios(table7.1).

Table7.1.NPVofAdditionalInvestmentNeedsbyMitigationScenarioandAnalysisPeriod

AnalysisperiodScenario

2014–2030 2014–2050

Scenario1(9%reduction)









In addition to requiring a lower NPV for additional investments, each scenario reduces GHGemissions.Table7.2showsthecumulativereductioninGHGemissionsachievedundereachscenario

andtimeframe.

Page|108

Table7.2.CumulativeCO2EmissionsReductionbyMitigationScenarioandAnalysisPeriod

InmilliontonsCO2

CumulativeCO2emissionsreduction(milliontonsCO2)Scenario

2014–2030 2031–2050

Scenario19%reduction

53.2 512.0


87.5 852.8


117.0 1,031.6

The MAC analyses for the policies and measures show that, across all scenarios, the most cost-effectivemeasures—thosewithnegativecosts—include the following: (1) investmentsandpolicies

aimedatshiftingtraffictoothertransportmodessuchasinlandwaterwaysandcoastaltransport;(2)deployment of stricter vehicle fuel economy standards; and (3) promotion of electric mobility. Inaddition,theimprovementsinfreighttruckloadfactorsconsideredinScenario3alsooffersignificant

potentialforemissionsreductionatnegativecosts.

Measures with positive costs, but with higher potential for emissions reduction include theexpansionofbussystems.Investmentsinrail,metro,andbusrapidtransit(BRT)havepositivecosts,

and thusmore limited potential for emissions reductions. The relatively low level of two-wheeleremissionspercapitaaccounts for the limitedpotential for reductions in thesemeasures;ashigheremissions standards and electrification are introduced, a modal shift from motorbikes to public

transportwould further lower two-wheeleremissions levels.Withadditionalmeasures to increaseoccupancy and distances traveled by these alternative transportmodes, the analysis indicates thecostefficiencyof investmentswould increase, togetherwiththepotential foremissionsreductions

fromthesemeasures.

In conclusion, Vietnam can adopt and implement several highly cost-effective and economicallyfeasible mitigation measures to achieve significant emissions reduction in the rapidly growing

transportsector.TheemissionsreductionunderthethreemitigationscenarioswouldhelpVietnammeetitsNationallyDeterminedContribution(NDC)targets,alongwiththepoliciesandinvestmentsinother sectors, especially inpower generation.However,while thesemeasures areeconomically

feasibleandwouldbringsignificant long-termbenefitsthroughareduction intransportcosts, theywouldrequireaconsiderableinvestment,eventhoughtheNPVoftheseinvestmentsislowerthanintheBAUscenario.Asareferencepoint,theMinistryofTransportinvestedUS$25billionfrom2001to

2015—anaverageofUS$1.7billionperyear.

Based on these conclusions, for emissions mitigation, the study recommends the Ministry ofTransport(MoT)prioritizestheimplementationofinvestmentsandpoliciesaimedatshiftingfreight

andpassengertransportfromroadstoinlandwaterwaysandcoastaltransport.Considerationshouldalsobegiven to thepromotionofelectricmobility through two-wheeledvehiclesandcars.Finally,thestudyrecommendsMoTdeploystrictervehiclefueleconomystandards,asthesemeasureshave

significantpotentialforemissionsreductionsbasedontheirestimatednegativeNPVs(comparedtoBAU),indicatingthebenefitsoutweighthecostsofimplementation.

Page|109

Also worth noting: Some of the analyzed policies and measures—such as modal shift to inlandwaterways and rail—offer improvements in transport efficiency, which would reduce the cost of

transport. Inlandwaterwaytransportrequiresone-quarter thecostsof roadtransport,andrailwayrequires one-half the costs of road transport, per ton-km, indicating the improved transportefficiency that results from a modal shift from trucking to cleaner transport modes offers added

economic benefits. Furthermore, and importantly, the policies andmeasures considered for GHGmitigationalsogenerateotherassociatedbenefits,suchasareductionoflocalpollutantemissions—which,inturn,providehealthbenefitsforthelocalpopulation.

Inadditiontothefindingsfromthestudyresults,thefollowingarealsocriticaltokeepinmind:

• Theneedtoconsider“Avoid”measuresnotcapturedinthisstudy,suchasbetterintegrationbetweenland-useandtransporttohelpreduceunnecessarytrips;

• The importance of considering long-term land-use and infrastructure planning, given theirlock-ineffects;

• Thequestionofhowtomakeeconomicallycost-effectivemeasures financiallyattractive toprivateinvestment;

• TheneedforevenmoreambitiousmitigationmeasurestoreversetheoveralltrendsseeninthethreescenariosofanincreasingCO2trajectory(despiteareductioninemissionsagainstBAU)anddecreaseemissionsinabsoluteterms

• Theneedformorecross-sectoralanalysistohelpavoidunrealisticproportionaltargets(e.g.,8 percent for all sectors), especially in developing countrieswhere the transport sector is

typically difficult for mitigation and energy (power generation) often offers easier andcheapermitigation;and

• Transport solutions should never be enacted because of carbon prices alone, but becausethey are good sustainable transport solutions. A comprehensive framework should also

assess mitigation measures according to their co-benefits, such as reduction in localemissions,qualityoflife,andhealth.

Therelativeemissionscontributionoftransportsubsectors, thepotential foremissionsabatement,

andthecost-effectivenessofmeasures thatenact thisabatementprovidevaluable information fordialogue among stakeholders and decision-makers on where to focus mitigation efforts. Throughconsideration of alternative scenarios discussed in this report, an actionable package ofmeasures

canbedeveloped. Inaddition,anunderstandingof theeachscenario’s cumulativeabatementandcost can also inform the dialogue on the desirable ambition level of actions and support targetsettingforthetransportsector.

Page|111

Appendices

A.GHGEmissionsInventory

ShowninfigureA-A.1,thegreenhousegas(GHG)emissionsinventoryusedabottom-upapproachtoanalyze, in a disaggregated manner, the relative sizes of emissions sources within the transportsectorandfacilitatetheidentificationofleversforemissionsreductions.

FigureA-A.1.Bottom-UpApproachCalculatingtheGHGEmissionsinTransportSector

Page|112

B.ScenarioFormulation

The study defined the GHG emissions scenarios based on different levels of ambition andinternationalsupport:

• The business-as-usual (BAU) scenario that considers that after 2014 (base year), targetedpoliciesandmeasuresaimedatmitigatingGHGemissionsinthetransportsectorwillnotbedeployed. This scenario also considered expected technological and socio-economic

development forecasts for the country, such as evolution in demographics and grossdomestic product (GDP), as defined in the country’s Nationally Determined Contribution(NDC).

• Thenon-conditionalscenarioconsidersimplementationofpoliciesandmeasures—includedinVietnam’sTransportSectorMasterPlan—thatenablethereductionoftransportemissionsof10percent,by2030,withoutinternationalsupport.

• The conditional scenario considers implementation of more ambitious policies andmeasures—included in Vietnam’s Transport SectorMaster Plan—to enable a reduction oftransportemissionsof16percentagainstBAU,by2030,withinternationalsupport.

• Theambitiousscenarioconsidersimplementationofmoreambitiouspoliciesandmeasures

that go beyond those included in Vietnam’s Transport Sector Master Plan, to enable areduction of transport emissions of 22 percent against BAU, by 2030, with internationalsupport.

The base year for scenario analysis was selected as 2014 in reference and to be aligned with

Vietnam’s SecondBiennialUpdatedReport (BUR2)1and theThirdNationalCommunication (2019)2submitted to theUNFCCC. The timelineof scenario analysis is 2020 to 2030/2040/2050, reflecting

that 2020 to 2030 is of interest to the current NDC dialogue, while the 2030 to 2040 and 2050timeframesenableconsiderationofpoliciesandmeasuresthatmaybeimplementedtowardtheendofthe2020to2030periodwithlong-termimpacts.

Thestudyselectedpoliciesandmeasuresassignedtoeachscenariothroughthescreeningofexistinglawsand regulations,Vietnam’sNational TransportPlan, andotherplanningdocuments.After theidentification of an initial list of policies and measures, government agencies and sector experts

reviewedthemtoensureclarityofassumptionsandbuildingconsensus.

Notes

1.Availableonlineat:http://unfccc.int/files/national_reports/non-annex_i_parties/biennial_update_reports/application/pdf/97620135_viet_nam-bur2-1-viet_nam_-_bur2.pdf.

2.Availableonlineat:https://unfccc.int/sites/default/files/resource/Viet%20Nam%20-%20NC3%20resubmission%2020%2004%202019_0.pdf.

Page|113

C.ModelingMethodology

SelectionofModels

The study objectives required a suite of models that facilitated a detailed bottom-up analysis of

transportactivityinallsectorstodeterminetheimpactofpoliciesandinvestmentsonthenationalgreenhouse gas (GHG) emissions, and then to calculate the transportation sector’s emissionsscenariosfortheNationallyDeterminedContribution(NDC)update.

The desired features of this suite, as identified by national and international experts who arespecialistsinthisfield,included:

• Shouldanalyzeactivityandemissionsatthenationallevelto2030andbeyond(2050).

• Should calculate for all transport subsectors (road, rail, air, inland waterway/coastal, andmaritimesector)

• Shouldanalyzechangesintraveldemandandvehicletechnologiesinbusinessasusual(BAU)anddifferentmitigationscenarios

• Shouldcalculatetheeconomiccostsofeachpolicychangeorotherintervention

• Shouldprovide results thatcanbe integrated toanalyzeandcomparemarginalabatementcosts(MACs)foremissionsreductionfromdifferentpolicyinterventions.

• ShouldeasilyintegratewiththeMinistryofTransport’sGHGExcel-basedinventorytool.

• ShouldbefreelyandfullyaccessibletoDepartmentofEnvironment(DoE)intheMinistryof

Transport(MoT)toenablethedepartmenttomaintainandupdatethemodelwithnewdata,assumptions,andpolicychoices.

Afterdetailedanalysisofdifferentoptions,thestudychosethefollowingsuiteofmodels:

EFFECT (Energy Forecasting Framework and Emissions Consensus Tool) isa free,Excel-based toolthatcananalyzevarioustransportactivityscenarios,includingdetailedtechnologicalandbehavioralchanges for the transportation and other sectors at the national level. As an Excel-based,

engineering-style, bottom-up tool with some built-in optimization developed by the World Bank,EFFECT can be usedbymultiple stakeholders to build consensus aroundpolicy implementation toreduceGHGemissions,andisdesignedtofacilitateatransparentsharingofdataandassumptions.

FreelyavailablefromtheWorldBank,thetool iseasilycustomizabletolocalrequirements,suchasanalyzingspecificactivitiesandpolicies,andcanbereadilysetuptoruninanylocallanguage.Ithasan extensive self-paced training course provided through World Bank's Open Learning Portal

(available at: https://olc.worldbank.org/content/low-carbon-development-planning-modelling-self-paced) and theWorld Bank has trained over 2,000 practitioners in facilitated courses. Themodelcurrently analyzes separately up to 250 vehicle types and technologies, including 28 low-carbon

technologies,alongwithtraveldemandmanagement(TDM)andotherbehavioralmeasures.

TheEFFECTmodelmetmostoftheabovementionedrequirements.ThemodelwasfirstbuiltbytheWorldBankforworkonnationalenergyplanninganalysisinIndia.Sincethen,EFFECThasbeenused

in several other countries, including Brazil, Poland, Georgia, Macedonia, Malaysia, Indonesia,Thailand,Philippines,Nigeria,andVietnam.

Page|114

UseofEFFECTinTransportstudiesinVietNam

EFFECT has been used in Vietnam for transport studies over several cycles, providing continuitybetweenstudiesandallowingeachtobuildondataandanalysesprovidedfrompreviousstudies,as

listedinTableA-C.1.

TableA-C.1.VietnamTransportStudiesUsingEFFECT

Year Supportedby Study

2010 WorldBank

WindsofChange:EastAsia'sSustainableEnergyFuture

Availableonline:http://documents.worldbank.org/curated/en/942471468244547200/Winds-of-

change-East-Asias-sustainable-energy-future)

2011Asian

DevelopmentBank

StrengtheningPlanningCapacityforLowCarbonGrowthinDevelopingAsiaOverviewPPT:

https://openei.org/w/images/2/25/Strengthening_Planning_Capacity_for_Low_Carbon_Growth_in_Developing_Asia.pdf

2013 WorldBank

ExploringaLowCarbonDevelopmentPathforVietNamAvailableonline:

http://documents.worldbank.org/curated/en/773061467995893930/Exploring-a-low-carbon-development-path-for-Vietnam

2014Asian

DevelopmentBank

VietNam2050:Evaluatinglonger-termoptionsforlowcarbondevelopmentinVietNam

Emissionscalculationtoolforthetransportsector(Trigger)wasdevelopedforDoEandGIZinearly2017tocalculatetransportemissionsfornationalGHGinventories.Thistoolincludessomestatisticaldataontrafficactivitydata,suchasnumberofvehicles,trafficperformance,andthetotalamountof

fuelsoldin2015accordingtoalltypesoftransportmodesinVietnam.

VISUM, a geographic information system (GIS)-based data management tool that simulates alltransportmodes, isused in trafficplanningtoanalyzeand forecast trafficvolumes.Traveldemand

and performance of transport activities can bemodeled based on socio-economic data, operatingcosts,transportinfrastructure,etc.VISUMalsoprovidesinputdataofmajorcities(suchasHanoiand

DaNang),nationalroads,andexpresshighwaysfrompreviousanalyses.DatafortheentirenationaltransportnetworkinVietnamcanalsobeintegratedfromothersources.

LEAP is a free tool for all sectors. LEAP was used for Vietnam’s Intended Nationally Determined

Contribution(INDC,orNDC)in2015andwasplannedforuseinthenextNDC.WhileLEAPincludesthetransportsector,itisappliedonlyatamoremacrolevelthanothertools,whichseverelylimitsitsability to analyze the emissions impact and cash flow implications of individual transport policy

interventions. Previous data available in LEAP can be a source of input data (such as GDP andpopulationprojections)forothermodels.

Basedondiscussions, thestudyagreedthatEFFECTwouldbeusedasthemaintool forcalculating

scenarios.Othermodels(eitherlistedornotlistedhere)maybeusedtocomplementthecalculation.Inordertocombinecurrentdata,thestudysuggestedthefollowingsteps:

Page|115

• Include basic data (2014) from the inventory tool into EFFECT (to be consistently used inothercomplementarymodels)

• Includesocio-economicdataforBAUassociatedwithNDC

• Build consensus among stakeholders on the future inclusion of technology and behavioralmitigation scenarios, based on agreed plausible policy interventions and calculations fromotherscenarios.

• ForecastfuturetraveldemandforBAUscenario,usingcalculationsinEFFECTandanalyzinginVISUMifnecessary.

• Provideresultsofcalculatedtransportparameters,suchasvehiclekilometerstraveled(VKT),passenger-kilometers(PKM),andton-kilometers(TKM),emissions,andfueluseproducedinEFFECTtotheNDCteam,toensureconsistencywithLEAP-basedforecasts.

The use of EFFECT, togetherwithVISUM, to estimate travel demandwould be further elaborated

based on group discussions, workshops, and analysis of probability of results (within certainlimitationsontimeandbudget).

FigureA-C.1illustrateshowthestudyintegratedthesuiteofmodelsforscenarioscalculation.

FigureA-C.1.IntegrationofModelsforScenariosCalculation

Page|116

EFFECTMethodology

TheEFFECTmethodologyanduseisdocumentedinastand-aloneusermanual.

In the following figures,also listed in tableA-C.2, thecalculation flowschematic is shownforeach

subsector.Withabaseyearof2014,themodelcalculatesoveramodelingwindowofupto2055.

TableA-C.2.CalculationFlowSchematicsbySector

Figure Contents

A-C.2 CalculationFlowSchematicforPassengerCarsandMotorcycles

A-C.3CalculationFlowSchematicforPassengerMassTransport(LightCommercialVehicles,Buses,andCoaches)

A-C.4CalculationFlowSchematicforOn-RoadFreightTransport(Light,MediumandHeavy-DutyVehicles,Trucks,andTractor-Trailers)

A-C.5CalculationFlowSchematicfortheFuelEfficiencyandEmissionsCalculationsforAllOn-RoadVehicles

A-C.6CalculationFlowSchematicforPassengerandFreightRailTransport(Metro,LightRail,High-SpeedRail,SuburbanandMainlinePassengerandFreightService)

A-C.7CalculationFlowSchematicforWaterbornePassengerandFreightTransport(InlandWaterwaysandCoastalShipping)

A-C.8CalculationFlowSchematicforCivilAviation(NationalPassengerandFreight,PlusInternationalPassengerandFreightforBunkerCalculations)

FigureA-C.2.CalculationFlowSchematicforPassengerCarsandTwo-Wheelers

Note:Passengercarsandtwo-wheelersincludeprivate,commercial,andgovernmentvehicleownershipanduse.

Page|117

FigureA-C.3.CalculationFlowSchematicforPassengerMassTransport

Note:Passengermasstransportincludeslightcommercialvehicles,busesandcoaches.

FigureA-C.4.CalculationFlowSchematicforOn-RoadFreightTransport

Note:On-roadfreighttransportincludeslight,mediumandheavy-dutyvehicles,trucks,andtractor-trailers.

Page|118

FigureA-C.5.CalculationFlowSchematicfortheFuelEfficiencyandEmissionsCalculationsforAllOn-RoadVehicles

FigureA-C.6.CalculationFlowSchematicforPassengerandFreightRailTransport

Note:Passengerandfreightrailtransportincludesmetro,lightrail,high-speedrail,suburban,andmainlinepassengerandfreightservice.

Page|119

FigureA-C.7.CalculationFlowSchematicforWaterbornePassengerandFreightTransport

Note:Waterbornepassengerandfreighttransportincludesinlandwaterwaysandcoastalshipping.

FigureA-C.8.CalculationFlowSchematicforCivilAviation

Note:Civilaviationincludesnationalpassengerandfreight,plusinternationalpassengerandfreightforbunkercalculations.

Page|120

D.KeyDataandAssumptions

Thekeydataandassumptionsthatsupportthisanalysisarearrangedbelowaccordingtoinformationgroup,including:

GeneralInformation

Gross domestic product (GDP). According to statistics provided by the General Statistics Office(GSO),1Vietnam’sGDPgrewat6.0percent in2014and6.7percent in2015.ExpectedGDPgrowth

rateis7percentfrom2015to2030,asdefinedbytheDecision428/QD-TTgontheNationalPowerDevelopmentPlanAdjustmentfortheperiod2011to2020,withvisionupto2030.2

Population.GSOstatisticsindicatetheVietnampopulationreached90.7millionpeoplein2014.3As

showninfigureA-D.1,Populationprojectionfortheperiodfrom2015to2030isbasedonVietnam’sPopulationForecast2016,conductedbyGSOandtheUnitedNationPopulationFund(UNFPA).

FigureA-D.1.PopulationProjectionfrom2015to2030

DataonRoadTransport

Numberofvehiclefleets.Thestudycollected2014dataforthenumberofvehiclefleetsfromofficialreports prepared by the Vietnam Register (http://vr.org.vn) aswell as inlandwaterway transport,maritime,aviation,andrailwayauthorities.TheGSO’syearlystatisticsbooksprovidedanothercrucial

sourceofdata.FigureA-D.2illustratestheincreaseofroadvehicles.

88

90

92

94

96

98

100

102

104

106

108

110

2014 2016 2018 2020 2022 2024 2026 2028 2030

Num

berofpeo

ple(m

illion)

Year

Page|121

FigureA-D.2.TotalRoadVehicleFleetinVietnamfrom2014to2030

In2014,motorcyclesoccupied94percentofthetotalvehiclefleet;by2030,thisnumberisprojectedto reduce to 82 percent, with ownership rate projected to reach 513 motorcycles per 1,000population.

Conversely,privatepassengercarshaveexperiencedafastgrowthrate,reaching1million in2014,andshouldcontinuetoincreasetoaprojected7.1millionby2030.Theeconomyincreasetakesanincreaseofmeanmonthlyhouseholdexpenditure(MMHE)asasurrogateforincome,whichleadsto

theownershiprateofcarsincreasing.Theownershiprateforcars isprojectedtoreach56carsper1,000population.

In the business as usual scenario (BAU), the growth of electric vehicles remains low,with electric

vehiclesaccountingonlyfor2.5percentofthevehiclefleetin2030.

In2030,lightcommercialvehicles(LCVs)areexpectedtoseegrowthratesthreetimescomparedto2014.LCVsincludegoodscarriers(mostlysmalltruckslessthan3.5GVWandagrowingshareoflight

pick-uptrucks),andpassengervans.Goodscarriersaresuitableforshort-distancetransportinbothurbanandruralareas.Forecastscallforthenumberoflighterpick-uptrucksusedtocarrygoodstoaccountfor47percentofthetotalLCVsin2030.

In 2030, heavy commercial vehicles (HCVs) for goods andpassenger coaches, operatingmainly onlong-andmedium-distanceroutes,areexpected to increase2.5 timescomparedto2014. In2014,themedium-sized trucks (7 to 16 tonsGVW) accounted for 28 percent of the total fleet, and are

expectedtoclaima40percentshareby2030.

Transport volume. TableA-D.1and figureA-D.3 showGSOstatistics forpassenger-km transported(PKT)andfreightton-kmtransported(FTKT)inbaseyear2014.

0

10

20

30

40

50

60

70

2014 2016 2018 2020 2022 2024 2026 2028 2030

Million

Motorcycle ElectricMC Car LightCommercialVehicle HeavyCommercialVehicvle

Page|122

TableA-D.1.PassengerKm-TraveledandFreightTon-KmTransportedin2014

Passenger/Freight Total Railway Road IWTCoastalshipping

Aviation

Passengerkm-traveled(E+09)

139.1 4.5 96.9 3.0 34.7

Freightton-kmtransported(E+09)

223.2 4.3 48.2 40.1 130.0 0.5

PKTisprojectedbasedontherelationbetweenpassenger-kmpercapitaandGDPpercapita.FTKTisprojected based on the elasticity between the growth rate of FTKT and GDP growth rate. Asillustrated in figureA-D.3, on-road PKT (private and commercial) accounts for 94 percent in 2030,

withthePKTforprivatevehiclescomprising74percentofthetotalPKT.

FigureA-D.3.PassengerKilometerTraveled(PKT)from2014to2030

FigureA-D. 4 details theprojected FTKT, showing the coastal transport contributing 55percent ofFTKT. Road and waterway accounts for 22.3 percent and 20.6 percent respectively, with othertransportmodescombinedmakinguponly1.5percent.

0

100

200

300

400

500

600

700

800

900

2014 2016 2018 2020 2022 2024 2026 2028 2030

PKT(passenger-kmE+09)

Onroad-Carandmotorbike Onroad-Commercial Rail-MainlineandMetro

InlandWaterwayandCoastal NationalAir

Page|123

FigureA-D.4.FreightTon-KilometerTransported(FTKT)from2014to2030

Notes

1.GSOstatisticfor2014GDPgrowthrateaccessedonlineat:

https://www.gso.gov.vn/default_en.aspx?tabid=784.

2.GSOpopulationstatisticsforVietnamaccessedonlineat:https://www.gso.gov.vn/default_en.aspx?tabid=774.

3.MoreinformationonDecision428/QD-TTgavailableviatheMOIT/GIZEnergySupportProgramme.See:http://www.gizenergy.org.vn/media/app/media/PDF-Docs/Legal-Documents/PDP%207%20revised%20Decision%20428-QD-TTg%20dated%2018%20March%202016-

ENG.pdf.

0

100

200

300

400

500

600

700

2014 2016 2018 2020 2022 2024 2026 2028 2030

FTKT

(freightto

n-km

E+09)

Onroad-Commercial Rail-Mainline InlandWaterway

CoastalFreight NationalAir

Page|124

E.MACCMethodology

WhatisaMACC?

The marginal abatement cost (MAC) analysis provides information on the greenhouse gas (GHG)

mitigationpotential(tCO2e)ofapolicyormeasuresandthecostforunitofGHGemissionsmitigation($/tCO2e).SeefigureA-E.1.Thisinformationoncost-effectivenessisusefultoinformdialogueamongstakeholdersandshouldbecomplementedwithinformationonfeasibilityandanalysisofothercosts

andbenefitsnotincludedintheanalysis.

Mitigationmeasuresarethenplacedfromlowesttohighestcost-effectiveness,whereeachmeasureisrepresentedasastepalongtheMACcurve,orMACC,plot.They-axis isthemarginalabatement

cost of GHG emissions ($/tCO2e), where the height of each step represents the net present cost(incremental costs less benefits) of the mitigation measure per ton of CO2e reduction over theanalysisperiod.Thex-axisistheabatementpotentialofGHGemissions(tCO2e),wherethewidthof

each step represents the GHG abatement potential of a mitigation measure during the analysisperiod.They-axisisthemarginalcostimplicitinachievingthisabatement.TheheightofthestepisthetotalmarginalcostfortheCO2eabatementpotentialachievedbythemitigationmeasure.

Thecumulativeemissionsreductionachievedbytheprioritizedmitigationmeasures isobtainedbyaddingtheabatementpotentialofeachofthemitigationmeasuresplotted.Measuresthatfallbelowzeroonthey-axisreflectanegativecost-effectiveness,whichmeansthemeasuresoffernetsavings

(benefitsexceedcosts).Measuresthatappearabovezero,reflectapositivecost-effectiveness,whichmeansthemeasureshavecoststhatexceedtheirbenefits.Therefore,MACCprovidesaquantitativebasis for discussions about which measures would be most effective in delivering emissions

reductions,andwhattheymightcost.Accordingly,theMACCinformsdecisionsonwhichmeasuresshouldbe implementedvoluntarily throughdomestic resourcesandwhichshouldbe implementedwithinternationalsupport(conditionalmeasures).

FigureA-E.1.MarginalAbatementCostCurveComponents

Page|125

Oncethemeasureshavebeenselectedandconfirmed,MACCisalsohelpful indevelopingenablingpolicies for implementation. Formeasureswithnegativeabatement costs—very cost-effective and

usually implemented by domestic resources—enabling policies aim at reducing barriers, risks, andhidden costs. For measures with costs above zero—but lower than a certain level1 and thusimplementedwithconditions—policiesshouldaimatreducingcosts,risks,andofferingconcessional

finance.Formeasureswhosecostsareabovecappedlevel,thepoliciesshouldaimatresearchanddevelopmenttomakethosemeasuresimplementableassoonaspossible.

HowisaMACCdeveloped?TheMarginalAbatementCost,MACMM($/tCO2e),iscalculatedusingdata

for incrementalcostsandincrementalemissionssavingsachievedbythemitigationmeasure,alongwithandtheemissionssavingsovertheanalysisperiod(Equation1).Inthecaseoflargeinvestmentprojects, it is preferable to calculate the marginal abatement cost over the lifetime of the

investment.

MACM=NPVINC,MM/EMM (1)

Where:

MACM = marginal abatement cost of the mitigation measure over the analysis period inthousandVNDpertonofCO2ereduction(thousandVND/tCO2e);

NPVINCMM=Netpresentvalue(NPV)ofthedifferenceincashflow(costsandbenefits)ofthemitigationmeasureovertheanalysisperiod(thousandVND);and

EMM=reductioninGHGemissionsovertheanalysisperiod(tCO2)

Aneconomicanalysisevaluatesthecostsandbenefitsofeachmeasuretothecountry.Theanalysisexamines the costs and benefits of mitigation measures relative to a business-as-usual (BAU)scenario, which should reflect what could have happened if that particular mitigation policy or

intervention not been implemented. The difference in costs (between the BAU and mitigationscenarios) should include differences in capital costs, operating costs, and fuel costs relevant toenergyuse—andshouldnotincludetransactioncostsandtaxes.Benefitsarelimitedtocostsavings

associated with reductions in energy consumption and GHG emissions, and do not include co-benefitssuchasavoidedenvironmentaldamages,healthcosts,andothersocialproblems.

Keydataandassumptions

Thebaseyearforthemarginalabatementcost(MAC)analysisis2014,withtheanalysisperiodfrom2014to2030aligningwith theNationallyDeterminedContribution (NDC)updateassumptionsand

priorcommunicationbytheMinistryofNaturalResourcesandEnvironment(MoNRE).However,toshow a more comprehensive picture of impact, particularly for key measures, which areimplemented after 2020—metro rail transport (MRT), for example—an extended analysis period,

from2014to2050,allowsamorecomprehensiveaccountoftheresultantimpactonGHGemissions.

All cost components in themodel are valued in constant 2014 prices, but are presented in 2018pricesinthisreporttoprovideabettersenseofcosts.Traditionally,theWorldBankusesadiscount

rate between 10 percent and 12 percent for all World Bank-financed projects. In this analysis, a

Page|126

discountrateof10percentisappliedtoalignwiththeNDCupdateassumption.Theanalysisusesthe2014exchangerateof1US$=VND21,890.

Fuelprices.ThestudyusedthedatapresentedintableE.1forfuelprices.

TableA-E.1.FuelPrices

InthousandVNDperton

Fuels 2014 2015 2020 2025 2030

Fueloil(FO) 14,589 12,705 15,995 21,966 23,898

Dieseloil(DO)

20,693 17,516 22,391 31,007 33,734

Jetfuel 18,943 14,326 26,511 30,808 32,864

Petro 25,631 19,218 25,476 28,684 29,555

CNG 14,677 12,423 18,527 27,490 29,907

Note:Pricesfor2014and2015arebasedonPetrolimexandareactualpricesafterremovingapplicabletaxesandfees.Pricesafter2015arebasedPDP7revisedforDOandFOandAnnualEnergyOutlook2018bytheEIA(https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf)forothers.

Vehicle prices. Vehicles purchase prices and operating costs are calculated based on a referencetechnologyforeachvehicletype.Thereferencetechnologyisassumedtobethatofthevehiclewith

highestmarketpenetration.Forexample,theKiaMorningdefinedthereferencetechnologyforlessthana1.4-litercar,whiletheHondaWavedefinedthereferencetechnologyformotorcycles.

ThepurchasepriceforbusesincludeGPSsystem,LEDboards,andcommunications.Futurecostsare

forecastbasedonpasttrendsandconsiderationoftechnologyevolution,suchastheintroductionofelectriccarsinfleets.Costsarealsodefinedbasedonaliteraturereview.Forexample,theoperation

andmaintainence (O&M)cost for trucks isbasedonaWorldBank study,StrengtheningVietnam’sTruckingSectorforLowerLogisticsCostsandGHGEmissions(Lametal2019).

Traditionally, theWorld Bank has used a discount rate of 10 percent to 12 percent for all Bank-

financed projects. In this analysis, a discount rate of 10 percent is applied to align with theassumptionsusedintherevisionofVietnam’sNDC.Theexchangerateusedisfor2014(1US$=VND21,890).

Page|127

Railway.ThestudyusedthedatashownintableA-E.2todefinerailwaycosts.

TableA-E.2.RailwayCostsAssumptions

Costtype Costitems Unit Value Datasource

Diesellocomotive ThousandVND 15,760,800

VietnamExpressnewsarticle(2004):https://vnexpress.net/tin-tuc/thoi-su/vn-mua-20-dau-may-

xe-lua-moi-cua-trung-quoc-2000471.html

Passengercar ThousandVND 10,600,000

TuoiTrenewsarticle(2018):https://tuoitre.vn/dua-6-doan-tau-moi-vao-khai-thac-tuyen-duong-

sat-thong-nhat-20180110224437811.htm

Investmentcosts

Freightcar ThousandVND 6,911,000

OperatingcostThousandVND

perlocomotive-km44.6

OperatingcostThousandVNDpercar-km

5.1

InfrastructurecostThousandVNDpertrain-km

16.2

PersonnelcostThousandVNDpertrain-km

1.3

O&Mcosts

Passengerhandling,Traincontrol,management

ThousandVNDpertrain-km

41.8

Lametal2019

Fueleconomystandards.ThestudyusedthedataintablesE.3throughE.6forvehicleemissionsandfueleconomystandards.

TableA-E.3.VehicleEmissionsStandards

Vehicletype 2014 2017 2022

Motorcycle Euro2 Euro3 —

Car Euro2 Euro4 Euro5

Note:—=notavailable.

TableA-E.4.FuelEconomyforCars

Vehiclesize2022

(l/100km)2027

(l/100km)Gasoline

density(kg/l)2022(g/km) 2027(g/km)

Smallcar(<1.4L) 6.1 4.7 0.74 45.14 34.78Mediumcar(<2.0L) 7.52 5.3 0.74 55.65 39.22Largecar(>2.0L) 10.4 6.4 0.74 76.96 47.36

Page|128

TableA-E.5.RoadMapforFuelEconomyforCars

Vehiclesize 2022 2023 2024 2027 2028 2029

Smallcar(<1.4L) 50% 75% 100% 50% 75% 100%

Mediumcar(<2.0L) 50% 75% 100% 50% 75% 100%

Largecar(>2.0L) 50% 75% 100% 50% 75% 100%

TableA-E.6.FuelEconomyforMotorcycles

2025 2026 2027Roadmap 50% 75% 100%Fueleconomy(L/100km)

2.3 2.3 2.3

Notes

1.Theshadowpriceforcarbonismostoftenused.WhensettingCO2emissionsreductiontargetsfortheGreenGrowthDevelopmentStrategy,thelevelofUS$10/tCO2e)wasadopted.

References

Lam,YinYin,KaushikSriram,andNavdhaKhera.2019.StrengtheningVietnam’sTruckingSector:TowardsLowerLogisticsCostsandGreenhouseGasEmissions.VietnamTransportKnowledge

Series.Washington,DC:WorldBankGroup.http://documents.worldbank.org/curated/en/165301554201962827/Strengthening-Vietnam-s-Trucking-Sector-Towards-Lower-Logistics-Costs-and-Greenhouse-Gas-Emissions.

Page|129

F.CoordinationofTechnicalAssistance

FigureA-F.1.InstitutionalArrangementsandGIZ/WBGTechnicalAssistance:FlowchartforProjectImplementation

8 Dao Tan Street, Ba Dinh District, Hanoi, VietnamTelephone: +84 24 37740100 Facsimile: +84 24 37740111Website: www.dfat.gov.au

8th Floor, 63 Ly Thai To Street, Hoan Kiem District, Hanoi, VietnamTelephone: +84 24 39346600Facsimile: +84 24 39346597Website: www.worldbank.org/en/country/vietnam

With support from: