【推荐】亚开行-评估全球净零转型对亚洲发展中国家的影响：综合评估模型的启示（英）-2023.12-58页VIP专享VIP免费

下载本文档

阅读 293
格式 pdf
大小 4.09 MB
约58页
2023-12-25
收藏
点赞(0)
海报
举报

ASIAN DEVELOPMENT BANK

6 ADB Avenue, Mandaluyong City

1550 Metro Manila, Philippines

www.adb.org

ADB ECONOMICS

WORKING PAPER SERIES

NO. 

December 2023

Assessing the Implications of a Global Net-Zero Transition for Developing Asia

Insights from Integrated Assessment Modeling

Global climate goals will not be attainable unless Asia’s growth becomes much less carbon-intensive.

This paper uses a global integrated assessment model to assess how developing Asia would develop

in a world that meets Paris Agreement temperature goals. It ﬁnds that a profound transition is needed,

with a rapidly decarbonized power sector and a dramatic drop in land-use emissions. Beneﬁts are found

to be far in excess of costs for Asia if an ecient set of decarbonization policies is deployed.

About the Asian Development Bank

ADB is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Paciﬁc,

while sustaining its eorts to eradicate extreme poverty. Established in 1966, it is owned by 68 members

—49 from the region. Its main instruments for helping its developing member countries are policy dialogue,

loans, equity investments, guarantees, grants, and technical assistance.

ASSESSING THE IMPLICATIONS

OF A GLOBAL NETZERO TRANSITION

FOR DEVELOPING ASIA

INSIGHTS FROM INTEGRATED ASSESSMENT MODELING

Johannes Emmerling, Lara Aleluia Reis, Laurent Drouet,

David A. Raitzer, and Manisha Pradhananga

ASIAN DEVELOPMENT BANK

The ADB Economics Working Paper Series

presents research in progress to elicit comments

and encourage debate on development issues

in Asia and the Paciﬁc. The views expressed

are those of the authors and do not necessarily

reﬂect the views and policies of ADB or

its Board of Governors or the governments

they represent.

ADB Economics Working Paper Series

Johannes Emmerling, Lara Aleluia Reis,

Laurent Drouet, David A. Raitzer,

and Manisha Pradhananga

No. 709 | December 2023

Johannes Emmerling (johannes.emmerling@eiee.org)

is a senior scientist at the European Institute on

Economics and the Environment (EIEE) and co-lead

of the Low Carbon Pathways Unit. Lara Aleluia Reis

(lara.aleluia@eiee.org) is a scientist at EIEE. Laurent

Drouet (laurent.drouet@cmcc.it) is a senior scientist

at EIEE. David A. Raitzer (draitzer@adb.org) and

Manisha Pradhananga (mpradhananga@adb.org)

are economists at the Economic Research

and Development Impact Department, Asian

Development Bank.

Assessing the Implications of a Global Net-Zero Transition

for Developing Asia: Insights from Integrated Assessment

Modeling

Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO)

6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines

Tel +63 2 8632 4444; Fax +63 2 8636 2444

www.adb.org

Some rights reserved. Published in 2023.

ISSN 2313-6537 (print), 2313-6545 (electronic)

Publication Stock No. WPS230587-2

DOI: http://dx.doi.org/10.22617/WPS230587-2

The views expressed in this publication are those of the authors and do not necessarily reﬂect the views and policies

ofthe Asian Development Bank (ADB) or its Board of Governors or the governments they represent.

ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any

consequence of their use. The mention of speciﬁc companies or products of manufacturers does not imply that they

are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned.

By making any designation of or reference to a particular territory or geographic area, or by using the term “country”

inthis publication, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

This publication is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO)

https://creativecommons.org/licenses/by/3.0/igo/. By using the content of this publication, you agree to be bound

bytheterms of this license. For attribution, translations, adaptations, and permissions, please read the provisions

andterms of use at https://www.adb.org/terms-use#openaccess.

This CC license does not apply to non-ADB copyright materials in this publication. If the material is attributed

toanother source, please contact the copyright owner or publisher of that source for permission to reproduce it.

ADB cannot be held liable for any claims that arise as a result of your use of the material.

Please contact pubsmarketing@adb.org if you have questions or comments with respect to content, or if you wish

toobtain copyright permission for your intended use that does not fall within these terms, or for permission to use

theADB logo.

Corrigenda to ADB publications may be found at http://www.adb.org/publications/corrigenda.

Notes:

In this publication, “$” refers to United States dollars.

ADB recognizes “USA” as the United States.

/58

下载本文档

文本预览下载提示常见问题

ASSESSINGTHEIMPLICATIONSOFAGLOBALNET-ZEROTRANSITIONFORDEVELOPINGASIAINSIGHTSFROMINTEGRATEDASSESSMENTMODELINGJohannesEmmerling,LaraAleluiaReis,LaurentDrouet,DavidA.Raitzer,andManishaPradhanangaNO.709ADBECONOMICSWORKINGPAPERSERIESDecember2023ASIANDEVELOPMENTBANKADBEconomicsWorkingPaperSeriesAssessingtheImplicationsofaGlobalNet-ZeroTransitionforDevelopingAsia:InsightsfromIntegratedAssessmentModelingJohannesEmmerling,LaraAleluiaReis,JohannesEmmerling(johannes.emmerling@eiee.org)LaurentDrouet,DavidA.Raitzer,isaseniorscientistattheEuropeanInstituteonandManishaPradhanangaEconomicsandtheEnvironment(EIEE)andco-leadoftheLowCarbonPathwaysUnit.LaraAleluiaReisNo.709December2023(lara.aleluia@eiee.org)isascientistatEIEE.LaurentDrouet(laurent.drouet@cmcc.it)isaseniorscientistTheADBEconomicsWorkingPaperSeriesatEIEE.DavidA.Raitzer(draitzer@adb.org)andpresentsresearchinprogresstoelicitcommentsManishaPradhananga(mpradhananga@adb.org)andencouragedebateondevelopmentissuesareeconomistsattheEconomicResearchinAsiaandthePacific.TheviewsexpressedandDevelopmentImpactDepartment,AsianarethoseoftheauthorsanddonotnecessarilyDevelopmentBank.reflecttheviewsandpoliciesofADBoritsBoardofGovernorsorthegovernmentstheyrepresent.ASIANDEVELOPMENTBANKCreativeCommonsAttribution3.0IGOlicense(CCBY3.0IGO)©2023AsianDevelopmentBank6ADBAvenue,MandaluyongCity,1550MetroManila,PhilippinesTel+63286324444;Fax+63286362444www.adb.orgSomerightsreserved.Publishedin2023.ISSN2313-6537(print),2313-6545(electronic)PublicationStockNo.WPS230587-2DOI:http://dx.doi.org/10.22617/WPS230587-2TheviewsexpressedinthispublicationarethoseoftheauthorsanddonotnecessarilyreflecttheviewsandpoliciesoftheAsianDevelopmentBank(ADB)oritsBoardofGovernorsorthegovernmentstheyrepresent.ADBdoesnotguaranteetheaccuracyofthedataincludedinthispublicationandacceptsnoresponsibilityforanyconsequenceoftheiruse.ThementionofspecificcompaniesorproductsofmanufacturersdoesnotimplythattheyareendorsedorrecommendedbyADBinpreferencetoothersofasimilarnaturethatarenotmentioned.Bymakinganydesignationoforreferencetoaparticularterritoryorgeographicarea,orbyusingtheterm“country”inthispublication,ADBdoesnotintendtomakeanyjudgmentsastothelegalorotherstatusofanyterritoryorarea.ThispublicationisavailableundertheCreativeCommonsAttribution3.0IGOlicense(CCBY3.0IGO)https://creativecommons.org/licenses/by/3.0/igo/.Byusingthecontentofthispublication,youagreetobeboundbythetermsofthislicense.Forattribution,translations,adaptations,andpermissions,pleasereadtheprovisionsandtermsofuseathttps://www.adb.org/terms-use#openaccess.ThisCClicensedoesnotapplytonon-ADBcopyrightmaterialsinthispublication.Ifthematerialisattributedtoanothersource,pleasecontactthecopyrightownerorpublisherofthatsourceforpermissiontoreproduceit.ADBcannotbeheldliableforanyclaimsthatariseasaresultofyouruseofthematerial.Pleasecontactpubsmarketing@adb.orgifyouhavequestionsorcommentswithrespecttocontent,orifyouwishtoobtaincopyrightpermissionforyourintendedusethatdoesnotfallwithintheseterms,orforpermissiontousetheADBlogo.CorrigendatoADBpublicationsmaybefoundathttp://www.adb.org/publications/corrigenda.Notes:Inthispublication,“$”referstoUnitedStatesdollars.ADBrecognizes“USA”astheUnitedStates.ABSTRACTThispaperusesaglobalintegratedassessmentmodeltoassesshowdevelopingAsia,theworld’sfastest-growingsourceofcarbonemissions,couldtransitiontolow-carbongrowth.Itfindsthatnationalnet-zeropledgesdonothaveahighchanceofkeepingpeakwarmingbelow2°C.UnderanefficientapproachtoachievetheParisAgreementgoals,thepowersectorwouldalmostfullydecarbonizebymid-century,andemissionsfromlandusewouldstronglyfall.Althoughtheclimatehasalaggedresponsetoemissionsreductions,climatebenefitsoutweighcostsbyafactorof3,withgainsconcentratedinthelowest-incomesubregionsofAsia.Airqualitywouldalsoimprove,savingabout0.35millionlivesintheregionby2050.Includingtheseco-benefitsraisesthebenefit–costratioforAsiaunderambitiousdecarbonizationto5.Energy-relatedemploymentalsorisesduringthetransition.However,appropriatepoliciesareneededtoaddresspotentialeffectsondisadvantagedgroups.Keywords:climatechange,greenhousegas,mitigation,energy,landuse,net-zero,NDCsJELcodes:C61,D58,Q52,Q53,Q54_______________________ThispaperpresentsmuchofthemodellingthatunderpinsAsiaintheGlobalTransitiontoNetZero:AsianDevelopmentOutlook2023ThematicReportandwasinitiallypreparedasadraftbackgroundpaperpriortothatreport.1.IntroductionDevelopingAsiaisvulnerabletoclimatechange.Thegeographyoftheregionexposesmuchofthepopulationtoclimate-relatedrisks,whilecopingabilityisimpededbylimitedsocioeconomicdevelopmentinmanyeconomies.Accordingtothe2021ClimateRiskIndex,6outofthe10economiesmostaffectedbyweather-relatedlosseventssuchasfloods,storms,landslides,andheatwavesduring2000–2019wereindevelopingAsia.Atthesametime,theregionisincreasinglyacontributortoclimatechange,withitsshareofglobalgreenhousegas(GHG)emissionsincreasingfrom26%in2000to44%in2019.ThePeople’sRepublicofChina(PRC),SoutheastAsia(particularlyIndonesia),andIndiaallexperiencedsubstantialgrowthinemissions,whileSouthandCentralAsiaexperiencedonlymodestincreases(Figure1).Yet,percapitaemissionsfromtheregionremainlowerthantheglobalaveragetodate.Figure1:GreenhouseGasEmissions,1990–2020GtCO2eq=billiontonsofcarbondioxideequivalent;PRC=People’sRepublicofChina,RoW=restoftheworld.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’calculationsfromWorldResourcesInstitute.ClimateWatch(accessedFebruary2023).2Energyaccountsforcloseto75%ofGHGemissionsfromtheregion,withelectricitygenerationamajorcontributor.Agriculture,landuse,andforestryarealsoimportantsourcesofemissionsintheregion,especiallyinSoutheastAsiaandthePacific.CarbonintensityindevelopingAsiais41%higherthantheglobalaverage,sothateachunitofeconomicactivityisassociatedwithhigheremissions.Intensityfellrapidlyinthe1990sandearly2000sinthePRCandCaucasusandCentralAsiabuthasremainedstablesince2010(Figure2).Asia’sfuturegrowthhasimportantimplicationsforclimatechange.In2017,aboutonebillionpeopleintheregionwerestilllivingonlessthan$3.20adayinpurchasingpowerparity(PPP)terms,implyingmuchpotentialforfutureincomeincreases.Meanwhile,anestimated940millionpeopleintheregionexperiencefrequentpowerinterruptions,andabout350milliondonothaveadequatepowersupply(IEA2020),sothatenergyneedswillcontinuetoincrease.Figure2:CarbonIntensityinDevelopingAsiaandtheWorld,1990–2019GDP=grossdomesticproduct,kgCO2e=kilogrampercarbondioxideequivalent,PPP=purchasingpowerparity.Note:Emissionsfromlandusechangeandforestry,whichcanbepositiveornegative,areincluded.Source:Authors’calculationsfromWorldResourcesInstitute.ClimateWatch(accessedFebruary2023).3Policymakersineconomiesaroundtheworld,includingindevelopingAsia,haverecognizedtheneedtolimitglobalwarming.TheParisAgreement,agreeduponby196parties,seekstolimitglobalwarmingtowellbelow2degreesCelsius(°C)andpursueeffortsto1.5°Ccomparedtopre-industriallevels.Undertheagreement,partiessubmitnationallydeterminedcontributions(NDCs)toreducefutureGHGsandincreaseadaptationtoclimatechange.NDCswereinitiallysubmittedin2015,coveringuntil2030,buttheyareinsufficienttoachieveParisAgreementgoals(UNFCCC2022).Atthesametime,anexpandingnumberofeconomieshavepledgedtoachievecarbonneutrality,ornet-zeroemissions,byspecifictargetyears.Asoflate2022,140economiesgloballyhadannouncedorwereconsideringtargetsfornet-zeroemissions.Ofthisnumber,19developingAsianeconomies,accountingforapproximately80%oftheregion’s2019totalGHGemissions,haveputforwardnet-zeropledges.Yet,onlyafewarewrittenintolaw,andonlyafewgovernmentsintheregionhavedevelopedlong-termstrategiesundertheParisAgreement.1Article6oftheParisAgreementcontainsaprovisionforlinkingnationalcommitmentsthroughinternationallytransferredmitigationoutcomes(ITMOs).However,thereislackofclarityonthepotentialofITMOstoimprovetheeconomicefficiencyoftheAgreement.WhiletheParisAgreementalsocreatesprovisionsfora“sustainabledevelopmentmechanism”asaglobalemissionsoffsetmarket,detailsareyettoberesolved.Againstthisbackground,thispaperanalyzeswhatpursuingdifferentclimatepolicieswouldmeanfordevelopingAsia.Section2detailsthemethodology,includingthemodeledscenarios,whiletherestofthepaperexaminesthetransformationsrequiredinenergyandlanduseandtheirsocioeconomicimplications.1GlobalnetzeroemissionsareachievedwhenanthropogenicemissionsofGHGsintheatmospherearebalancedbyanthropogenicremovalsoveraspecificperiod(IPCC2018).Nationalnetzeropledgesseektoachieveabalanceofemissionsandremovalsatthenationallevel.42.Methodology2.1ScenarioDesignThispaperexaminestheimplicationsofclimatepoliciesondevelopingAsiabasedonfivecorescenarios(Table1).Thesescenariosrepresentsomeofthekeypolicychoicesconfrontingpolicymakers.Allfivescenariosfollowthe“middleoftheroad”sharedsocioeconomicpathway(SSP2)agreedonbytheinternationalmodelingcommunityforpopulationandeconomicgrowth(Riahietal.2017).•Currentpoliciesincludetheenactedenergyandclimatepoliciesinalleconomiesuntil2020.AcompletelistofpoliciesisdetailedintheAppendix.Nofurtherstrengtheningofpoliciesisassumedinthisscenario.Thisscenarioservesasthereferenceagainstwhichallscenariosarecompared.WhereNDCsandmorespecificsectorpoliciesdiverge,thisscenarioreflectssectorpoliciesratherthanNDCs.Thisissimilartohowthe6thAssessmentReport(AR6)oftheIntergovernmentalPanelonClimateChange(IPCC)definescurrentpolicies(IPCC2022a).•NDCeffortassumestheimplementationofunconditionalNDCsuntil2030.2ThereisgradualstrengtheningofNDCeffortsafterwards,withtheimplicitcarbonpriceineachregionassumedtogrowatthesocialdiscountrate,whichisapproximately3%(Aldyetal.,2017).Thescenarioincludesenergyconstraints,suchasthePRC’ssolarandwindcapacitytargetsandEurope’s55%emissions-reductiontargetfor2030.Whenenergyconstraintsarenotspecifiedorarenotimplementable,targetsforemissionsaremetusingacost-optimalstrategyimposedbythescenario’sregionalcarbontax2Pledgesthatcountrieswouldundertakeifinternationalsupportwereprovidedorotherconditionsaremet.ThispaperconsiderspledgessubmittedtotheUnitedNationsFrameworkConventiononClimateChange(UNFCCC)portaluntil22June2022.5extrapolation.TheAppendixprovidesmoredetailsontheinterpretationandimplementationofNDCs.•Uncoordinatednet-zeroimplementsunconditionalNDCsuntil2030followedbynationalnet-zeropledgesforeconomieswithsuchpledges.Itrepresentsanuncoordinatedeffortofpartiesusingthe“pledgeandreview”frameworkoftheParisAgreement.Economiespledgeemissionreductionsvoluntarily,withoutconsideringifsuchpledgesaresufficienttoachieveParisAgreementgoals.Foreconomieswithoutnet-zeropledges,thisfollowstheNDCeffortscenario.3TheAppendixprovidesmoredetailsonnet-zeropledgesincludedinthepaper.Thefinaltwomodeledscenarioscanbeconsideredasmoreoptimalalternativestothecurrentbottom-upapproachoftheParisAgreement.Underthesescenarios,globalclimatepolicyismorecoordinatedthanhasbeenthecasesofar.Bothscenariosareimplementedunderacarbonbudgetof1,150billiontonsofcarbondioxide(GtCO2).4Afterexhaustingthebudget,emissionsneedtostayclosetozerotokeeppeakwarmingwellbelow2°C,oranaveragepeakwarmingof1.7°C.ThisisunlikeolderstudiesthatreliedonoptimisticassumptionsaboutnegativeemissionstechnologybeingabletodrawdownexcessGHGconcentrationsinthelate21stcenturytocompensateforanovershootofthecarbonbudget(Drouetetal.2021,Riahietal.2021).Aglobalcarbonmarketallocatesemissionallowancesamongeconomiesviaa“contractionandconvergence”frameworkthattransitionsfromgrandfatheredemissionsharesto3Inthispaper,netzerorefersonlytonetzeroofCO2emissions,andthisisastandardapproachintheliterature(e.g.,Meinshausenetal.,2009;andMillaretal.2017).Onlynationalnetzeropledgesthatweretagged“achieved,”“documented,”and“declared”intheUNFCCC’slong-termstrategieswebsiteandtheWorldResourcesInstituteNet-ZeroTrackerandconfirmedbydocumentsandonlinenationalandinternationalmediawereconsidered.Informationonthepledgeswereanalyzedandconfirmedbydocumentsandonlinenationalandinternationalnews.WheneverinformationfromENOVATE(2022)couldnotbeconfirmedthroughotherdocumentsorinformationsources,thepledgewastaggedas“proposed”andwasnotconsidered.ThiswasthecaseforseveralcountriesthatappearedinENOVATE(2022)as“proposed/indiscussion”andwereonlymentionedatthe2019UnitedNationsClimateChangeConference(COP25).4Thetotalcarbonbudgetisexpressedrelativeto2020.6equalper-capitaallowancesby2050(Meyer2000).Emissionsrespondtoaglobalcarbonpricethattriggersoptimalabatementfortheglobetostaywithintheglobalcarbonbudget.Economiesthatemitmorethantheirallowancescompensateeconomiesthatemitlessthantheirallowancesbasedonthecarbonprice.Table1:ClimatePolicyScenariosScenarioNDCsuntil20302030toNet-ZeroInternationalCarbonEmissionsCurrentpoliciesNotreflectedYearCarbonTrade2020–2100CurrentpoliciesNo3,270GtCO2(endogenous)NDCeffortUnconditionalNDCsNo2,650GtCO2(endogenous)extrapolated1,420GtCO2(endogenous)Uncoordinatednet-zeroUnconditionalNet-zeropledgesNo1,150GtCO2Globalnet-zeroUnconditionalFasttransitionYes1,150GtCO2Acceleratedglobalnet-BeyondNDCsFasttransitionYeszeroGtCO2=billiontonsofcarbondioxide,NDC=nationallydeterminedcontribution.Source:Authors.Theseadditionalscenariosincludethefollowing:•Globalnet-zeroassumesunconditionalNDCsuntil2030andacoordinatedglobaleffortthereafter,tostaywithinacarbonbudget.•Acceleratedglobalnet-zerofollowstheprevious(globalnet-zero)scenario,exceptthatglobaleffortsareacceleratedfrom2023,ratherthanafter2030.2.2ModelImplementationThepaperusestheWorldInducedTechnicalChangeHybrid(WITCH)modeltoexploremitigationpathwaysunderthefivescenarios.CurrentlybeingdevelopedattheRFF-CMCCEuropeanInstituteonEconomicsandtheEnvironment(EIEE),WITCHisadynamicoptimizationmodeloftheworldeconomyspecificallydesignedtoassessclimatepolicies(Bosettietal.2006,Emmerlingetal.2016).Themodelcoversenergysystemtransition,land-usechange,andclimateandeconomicvariablesinacomprehensiveintegratedassessmentmodel(IAM).7IAMshavebeenwidelyusedtodevelopandevaluatesocioeconomicandenvironmentalpathways,andmorerecently,Paris-compatibleemissionspathways(Rogeljetal.2018,Weyant2017).InIPCC’sAR6report,over1,200scenariosdevelopedandimplementedinIAMs(over100intheWITCHmodel)havebeenusedprominentlytoassesscosts;benefits;economic,environmental,andenergy-relatedimplicationsofdifferentclimatetargets;andothervariationsinkeyassumptions.5WITCHincludeselectricitygenerationfromfossilfuels(naturalgascombinedcycle,fueloil,pulverizedcoal,andintegratedgasificationcombinedcyclecoalpowerplants)andnon-fossilsources(onshoreandoffshorewindturbines,solarphotovoltaicpanels,concentratedsolarphotovoltaics,hydroelectric,biomass,nuclear,andtwocarbon-freebackstoptechnologiesrepresentingtechnologicaloptionsthatarestillquitefarfromcommercialization,forlong-termscenarios).Carboncaptureandstorage(CCS)canbeaddedtocoal,gas,andbiomass.Gridintegrationismodeledconsideringflexibilityconstraintsthattracetogenerationtype,capacityconstraints,andgridstorageandcapital.Beyondelectricity,theuseofcoal,oil,andtraditionalbiomassareincorporatedbothgenerallyandspecificallyfortransport(includingbyinternationalaviation,shipping,androad).WITCHislinkedtotheGlobalBiosphereManagementModeltoincludeemissionsfromforestry,land-usechange,andagriculture,andtotheModelfortheAssessmentofGreenhouseGasInducedClimateChange(MAGICC)totranslateemissionsintoglobaltemperaturechanges.Themodelfeaturesendogenousrepresentationofresearchanddevelopment(R&D)anddiffusionandinnovationprocesses,allowingittoreflecthowR&Dinvestmentsinenergyefficiencyandcarbon-freetechnologiesintegratewithcurrentlyavailablemitigationoptions.Whilethemodel5SeePindyck(2017),Keppoetal.,(2021),andSternetal.(2022)foradiscussionoftheseassumptions,criticisms,aswellasrecentmodeldevelopmentsinWITCHsuchaspublishedinBosettietal.(2013),Drouetetal.(2021),Emmerlingetal.(2020),andKreyetal.(2018).8typicallycovers17worldregions,theversionforthispaperseparatesCaucasusandCentralAsiafromthetransitioneconomiestomodelresultsfor18regions(Table2).6Table2:RegionalAggregationUsedforModelingRegionsandEconomies1People’sRepublicofChina2India3Indonesia4CaucasusandCentralAsia:Armenia,Azerbaijan,Georgia,Kazakhstan,KyrgyzRepublic,Mongolia,Tajikistan,Turkmenistan,andUzbekistan5RestofSoutheastAsia:BruneiDarussalam,Cambodia,LaoPeople’sDemocraticRepublic,Malaysia,Myanmar,Philippines,Singapore,Thailand,Timor-Leste,andVietNam6RestofSouthAsia:Afghanistan,Bangladesh,Bhutan,Maldives,Nepal,Pakistan,andSriLanka7Oceania:Pacificislandeconomies,Australia,NewZealand,andPapuaNewGuinea8Canada9HongKong,China;Japan;Macau,China;RepublicofKorea;andTaipei,China10SouthAfrica11Brazil12Mexico13RestofLatinAmericaandCaribbean(excludingBrazilandMexico)14MiddleEastandNorthAfrica15Europe16RestofSub-SaharanAfrica(excludingSouthAfrica)17TransitionEconomies:Belarus,Moldova,RussianFederation,Türkiye,andUkraine18UnitedStatesNote:Effective1February2021,ADBplacedatemporaryholdonsovereignprojectdisbursementsandnewcontractsinMyanmar.ADBplacedonholditsregularassistanceinAfghanistaneffective15August2021.Source:Authors.3.EmissionsPathwaysGlobalemissionstrajectoriesandtheresultantmeanwarmingbytheendofthecenturyaresummarizedinFigure3.Underthecurrentpoliciesscenario,cumulativeglobalGHGemissionswillreach3,270GtCO2by2100,leadingtomeanwarmingof3.0°C(Figure3[a]).DevelopingAsiawillcontributetoabout44%ofannualGHGemissionsuntilmid-century.UndertheNDCeffortscenario,globalemissionswilltaperto2,650GtCO2by2100,whichisstillnotenoughmitigationtoachieveParisAgreementgoals,withmeanwarmingof2.4°C.Includingnationalnet-zero6WITCH.https://www.witchmodel.org/.9pledgesgeneratesamoredramaticreductionofemissionsundertheuncoordinatednet-zeroscenario,withonly209GtCO2eremainingby2100.Thisbudgetisinlinewithpreviousfindings,includingthoseofMeinshausenetal.(2022)andBirol(2021).However,theuncoordinatednet-zeroscenariodoesnotfullyachieveParisAgreementgoals,asthereisonly50%probabilityofstayingwithinthe2°Ctarget.7ThisimpliesthatthecurrentNDCsandnet-zeropledgesdonotyetfullyachieveParisAgreementgoals,highlightingtheneedtoraiseglobalambitionsandcooperation.Nevertheless,thenationalvoluntarynet-zeropledges,ifimplemented,representamajorsteptowardsanoptimalemissionpathway.TheParisAgreement’slong-termgoaloflimitingglobalwarmingtowellbelow2°Cisonlyachievedundertheglobalnet-zeroandacceleratedglobalnet-zeroscenariosimplementedunderstringentcarbonbudgets.Thesetwoscenariosaredesignedtoavoidovershootingoftemperatures,whichnotonlyreducestheriskoftriggeringclimatetippingpointsbutalsosignificantlylowerstheriskofclimatechangedamage(Drouetetal.2021).Overall,tomeettheParisAgreementtarget,theworldwouldachievenet-zeroCO2emissionsby2075intheglobalnet-zeroscenarioandby2085undertheacceleratedglobalnet-zeroscenario(Figure3[b]).Thedelayinclimateactionundertheglobalnet-zeroscenariomeansthatemissionsneedtofalltonet-zerofastertostaywithinthecarbonbudget,whileearlyactionunderacceleratedglobalnet-zeroscenarioallowsforasmoothertransition.7Wellbelow2°Cisinterpretedasahigher-than-67%probabilityofstayingbelowa2°Cpeaktemperatureincrease.ThisisbasedonclimatecategoryC3oftheIPCCAR6WorkingGroupIIIreport(IPCC2022b).Thepeaktemperatureisreachedin2080inthenetzeroscenarios.10Figure3:GHGandCO2EmissionPathwaysundertheModeledScenarios,2005–2100(a)GlobalGHGEmissionPathways(b)GlobalCO2EmissionPathways(c)DevelopingAsiaGHGEmission(d)DevelopingAsiaCO2EmissionPathwaysPathways(e)GlobalCumulativeCO2EmissionsandAverageTemperateIncreaseby2100CO2=carbondioxide,GHG=greenhousegas,GtCO2=billiontonsofcarbondioxide,GtCO2e/year=billiontonsofcarbondioxideequivalentperyear,NDC=nationallydeterminedcontribution,T=temperaturein2100.Notes:InternationalshippingandaviationemissionsarenotincludedintheglobalCO2emissionpathways.AlltemperaturescalculatedwithMAGICCv6model.Source:Authors’estimates.GHGandcarbondioxide(CO2)emissionpathwaysofdevelopingAsiaareshowninFigure3(c)and3(d),respectively.Notably,bothCO2andallGHGemissionscontinuetobepositivefortheregionbytheendofthecentury.Thisimpliesthat,globally,negativeemissiontechnologies11maybedeployedinregionswithhighpotentialforstorageorafforestation.Theuncoordinatednet-zeroscenario(redline),whereeconomiesindependentlyfollowthroughontheirpledges,showsalessstringentmitigationpatternuntilmid-century,afterwhichthenet-zeropledgesoflargeeconomiesintheregionwouldleadtoafastphaseoutofCO2emissions.Intheshortrun,however,themodeledpathwayremainssignificantlybelowthetrajectoriesfortheacceleratedandevenglobalnet-zeroscenarios(greenandyellowlines,respectively).Figure4:GHGEmissionPathwaysforSubregionsofDevelopingAsiaundertheModeledScenarios(MtCO2e/year)CaucasusandCentralAsiaPRCIndiaRestofSouthAsiaIndonesiaRestofSoutheastAsiaMtCO2e/year=milliontonsofcarbondioxideequivalentperyear,NDC=nationallydeterminedcontribution,PRC=People’sRepublicofChina.Source:Authors’estimates.12Figure4summarizestheGHGemissionpathwaysofkeyeconomiesandsubregionsofdevelopingAsia.Thechartsrevealalikelystrongincreaseinemissionsinmostoftheregionunderthecurrentpoliciesscenario,particularlyinSouthAsia.Overthelongerterm,thePRCwouldundergodecarbonization,evenunderthecurrentpoliciesscenario.Undertheuncoordinatednet-zeroscenario,economieswithnet-zeropledgessuchasthePRC,India,andIndonesiawillrequiredrasticreductionsinemissionscomparedtothemoreoptimalglobalnet-zeroscenarios,whereglobalcarbonmarketsleadtoamoreefficientallocationofmitigation.4.TransformationofKeyMitigationSectorsThisanalysisdecomposesmitigationeffortsindevelopingAsiaintocontributionsfromenergyefficiency,changeinenergymix,non-CO2abatementrelatedtolanduseandagriculture,andcarboncaptureandstorage(CCS)usingthekayaidentityandLogarithmic-MeanDivisiaIndex(LMDI)decomposition(AngandLiu2001,2007).8Figure5showsthisdecompositionfortheacceleratedglobalnet-zeroscenarioforkeyeconomiesandsubregionsinselectedyears.Energyefficiencyimprovementsdominatemitigationintheyearspriorto2040,exceptinIndonesiaandtherestofSoutheastAsiawherenon-CO2abatementfromagricultureandlanduseservesasanimportantsourceofmitigation.Inthelongerrun,transitionofenergytocleanersourceswillbethekeysourceofmitigationinmostoftheregion,accountingfor45%ofmitigationin2050.CCSisimportantafter2050.Forexample,in2060,CCSwillaccountforaboutathirdofmitigationinthePRCundertheacceleratedglobalnet-zeroscenario.8TheKayaidentitywasproposedin1989asamethodtodecomposeemissionchangesintofourdrivers:population,grossdomesticproduct(GDP)percapita,energyintensityofGDP,andcarbonintensityorenergy.Meanwhile,theadditiveLMDIprovidedawaytoidentifythesedriverssothatthetotaleffectequalsthesumoftheindividualcontributions.13Figure5:DecompositionofMitigationSourcesundertheAcceleratedGlobalNet-ZeroScenarioCCS=carboncaptureandstorage,CO2LU:carbondioxidefromlanduse,GDP=grossdomesticproduct,EN_EFF=energyefficiency,EN_MIX:energymix,MtCO2e=milliontonsofcarbondioxideequivalent,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.Landuse.ThereisgreatpotentialtoreduceemissionsfromlanduseinmuchofdevelopingAsia.However,thecurrentpoliciesandNDCeffortscenarioswilladdlittleadditionalforestcoverintheregion(blackandbluelines,respectively,inFigure6).ThisispartlybecauseitisdifficulttotranslatepledgedNDCsonlandusetoeconomy-levelvalues.Forestcovertendstoincreaseinthemoststringentscenarios(acceleratedandglobalnet-zerocasesrepresentedbygreenandyellowlines).Undertheacceleratedglobalnet-zeroscenario,forestcoverintheregionwillincreaseby95millionhectares,reaching30%oflandcoverversus26%underthecurrentpoliciesscenario.Undertheacceleratedglobalnet-zeroscenario,about36millionhectaresoflandcurrentlyusedtogrowfoodcropswillbeprimarilydivertedtogrowbioenergycropsby2050.By2070,about5%oflandareaintheregionwillbeusedtogrowbioenergycrops.14Figure6:TotalForestCoverasShareofTotalLandAreaunderModeledScenariosNDC=nationallydeterminedcontribution,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.EnergyTransition.Asmentionedearlier,theenergysectoristhelargestsourceofemissionsintheregionandwillbethemainsourceofmitigationinthemediumtolongrun.Figure7depictstheprimaryenergymixinkeyeconomiesandsubregionsofdevelopingAsiaacrossthemodeledscenarios.Energydemandintheregionwillincreaseby50%by2070underthecurrentpoliciesscenario,whileitwillgrowmoreslowlyundertheacceleratedglobalnet-zeroscenario.Thisispartlyduetohigherenergyefficiencyandpartlyduetolowerthermallossesinthelatterscenario,asmoreenergyisgeneratedfromnon-fossilfuelsources.Underthecurrentpoliciesscenario,theshareofcoalinprimaryenergyintheregionwilldecreasefromabout50%in2020tolessthan25%by2050.Undertheacceleratedglobalnet-zeroscenario,thiswillfurtherdecreaseto13%,whilerenewablesourcesofenergysuchassolar,wind,hydro,andbiomasswillprovideabout25%ofprimaryenergyintheregionby2050.15Figure7:PrimaryEnergyMixinDevelopingAsiaCaucasusandCentralAsiaIndiaIndonesiaPRCSouthAsiaSoutheastAsiaEJ=exajoules,NDC=nationallydeterminedcontribution,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.Thetransitiontocleanenergyismoredramaticwithintheelectricitysector.Theshareofcoalinelectricitygenerationwilldecreaseevenunderthecurrentpoliciesscenariotoonly17%by2050,whileunderthenet-zeroscenarios,coalwillbepracticallyphasedoutfromtheregion’spowersector.Figure8showsthatlarge-scalerenewableenergydeploymentwilldominateinmostregions,withsolarandwindpowercontributingtoabout75%oftheregion’selectricitysupplyby2040.CCScanprovideaneconomicaloptionforeconomiesandregionsthatrelyheavilyonfossilfuels(suchascoalandnaturalgas).BioenergywithCCS(BECCS)andbiomasswillpotentiallyaccountforalargeshareoftheenergygeneratedinIndonesiaandotherSoutheastAsianeconomies,whilehydropowerwillplayanimportantroleinSouthAsiaandthePRC.16Figure8:ElectricityMixinDevelopingAsiaCaucasusandCentralAsiaIndiaIndonesiaPRCSouthAsiaSoutheastAsiaCCS=carboncaptureandstorage,NDC=nationallydeterminedcontribution,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.ElectrificationofendservicesisanotherkeytransformationthatwillcontributetoadeclineinGHGemissions.Figure9showsthefinalenergycarriersharesindifferentsectorsunderthecurrentpoliciesandacceleratedglobalnet-zeroscenarios.Undertheacceleratedglobalnet-zeroscenario,thetransportsectorwillseethehighestelectrificationlevelbytheendofthecentury,withalmostafullshifttoelectricvehicles.Intheresidentialsector,traditionalbiomasswillbephasedout,whiletheshareofelectricitywillslowlyincrease.Inindustry,theshareofelectricitywillincreasefromaroundone-thirdoffinalenergytodaytotwo-thirdsbytheendofthecenturyintheacceleratedglobalnet-zeroscenario.17Figure9:FinalEnergyCarrierSharesinDevelopingAsia(Exajoules)Source:Authors’estimates.Thetransformationoftheenergysectorwillrequirerapidscalingupandreallocationofinvestmenttocleanersourcesofenergy.Figure10showsthatinvestmentsinpowersupplyindevelopingAsiawillneedtoincreasefromaround$529billionannuallyunderthecurrentpoliciesscenarioto$707billionundertheacceleratedglobalnet-zeroscenario.Thesearemostlyneededtoscaleuprenewableenergysupplyandfacilitatetheintegrationofintermittentpowerfromrenewables,thelatterthroughthedevelopmentofgridnetworksandstorage.Overall,theinvestmentsaccountforabout2.2%ofgrossdomesticproduct(GDP)intheregion,withslightlyhighersharesof2.6to2.7%intheCaucasusandCentralAsia.18$billionannually,2020–2050Figure10:AverageAnnualInvestmentinPowerSupplyinDevelopingAsiaCCS=carboncaptureandstorage,NDC=nationallydeterminedcontribution,NZ=net-zero.Note:Renewablesincludesolar,wind,hydro,andbiomass.InternationalEnergyAgency(IEA)datahasbeendownscaledusingweightsandaggregatedtothereportedregiondefinitions.Sources:InternationalEnergyAgency.2020.WorldEnergyOutlook2020:AccesstoElectricityDatabase;Authors’estimates.5.EconomicCostsofLow-CarbonPoliciesTheimpositionofcarbonpricesisthepolicythattriggersdecarbonizationwithintheWITCHmodel.Thesepricesaremodeledtoincreaseovertime.TheNDCeffortscenariorequireslittlecarbonpricingmodificationsincetheemissionspathwaysdonotdifferstronglyfromcurrentpolicies,whiletheuncoordinatednet-zeroscenariofeaturescarbonpricesthatvarystronglyamongregions.Undertheacceleratednet-zeroscenario,globalcarbonpricesriseto$70pertonofCO2equivalent(tCO2e)in2030and$153pertCO2ein2050(Figure11).Carbonpricesareinitiallyhigherintheacceleratedglobalnet-zeroscenariothanintheglobalnet-zeroscenario,buttheacceleratedscenariofaceslowerpricesby2040asearlymitigationprovestobemorecosteffectivethandelayedaction.19Figure11:GlobalCarbonPricesundertheModeledGlobalNet-ZeroScenarios($pertCO2e)tCO2e=tonofcarbondioxideequivalent.Source:Authors’estimates.Policycostsfollowsimilarpatternstocarbonprices.ThesecostsareverylowundertheNDCscenarioduetothemodestchangesfromcurrentpolicies.Net-zeropledgesimplementedinanuncoordinatedmannerhavehighercostsforeconomieswithmoreambitiousnet-zeropledges.Globalnet-zeroscenarioshavemuchlowercostsoverallincomparison.AmongsubregionsofdevelopingAsia,policycostsarelargerinmorecarbon-intensiveeconomiessuchasintheCaucasusandCentralAsia,Indonesia,andthePRC,whiletheyaregenerallylowerinpoorerandlesscarbon-intensiveeconomies.CentralAsiastandsoutashavingthehighestpolicycostsintheregion,primarilyduetoitsheavyeconomicdependenceonfossilfuels(Figure12).Aroundone-thirdofthepolicycostsinthissubregiontracestoareductioninexportrevenuesfromfossilfuels(suchascoal,naturalgas,andoil),whichinturntracestoreducedpricesandexportedquantities.Forothersubregions,however,thelowerimportcostsoffossilfuelshelptomitigatetheoutputlossesduetotheeconomicandenergytransition.Thedeclineinfossilfuelpricesundernet-zeroscenariosstem20fromlargechangesinthenetexportoftheseresources(Figure13),whicharemainlyduetoareductionindemandunderdecarbonizationpolicies.Figure12:PolicyCostsfortheModeledScenariosinDevelopingAsia,ExcludingBenefitsandRelativetoCurrentPolicies,2030,2050,and2070GDP=grossdomesticproduct,NDC=nationallydeterminedcontribution.Source:Authors’estimates.21Figure13:FossilFuelTradeinDevelopingAsiaundertheModeledScenariosCurrentpoliciesNDCeffortUncoordinatedGlobalnet-zeroAcceleratedglobalnet-zeronet-zeroCaucasusandCentralAsiaFossilFuelNetExports($billion)IndiaIndonesiaPRCSouthAsiaSoutheastAsiaNDC=nationallydeterminedcontributions,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.Figure14showstheexpectedflowsfromthetradeofcarbonpermitsindevelopingAsiaintheacceleratedglobalnet-zeroscenario.SouthAsia,especiallyIndia,standsoutasthelargestexporterofcarbonpermitsoverall.ThePRC,meanwhile,isexpectedtobecomeasubstantialimporterofthesepermits,withimportvalueestimatedtoreach$400billionby2050,whenemissionsrightswouldbeallocatedonanequalper-capitabasisacrosseconomies.22NetExportsinCarbonPermits($billion)Figure14:TradeBalanceofGHGOffsetsundertheAcceleratedGlobalNet-ZeroScenarioJapanandRepublicofKoreaGHG=greenhousegas,LACA=LatinAmericaandCaribbean,MENA=MiddleEastandNorthAfrica,OECD=OrganisationforEconomicCo-operationandDevelopment,PRC=People’sRepublicofChina.Notes:Positivevaluemeansexports,andnegativevaluemeansimports.SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.Net-zeropledgesleadtoadiscontinuousprogressionofeffortandcosts.NDCsimposelimitedemissionsreductionandcostsuntil2030,buteffortswillhavetorapidlyaccelerateafterthisperiodtomeetnet-zerotargets.Thiscreatesalargespikeinpolicycosts.Theacceleratedglobalnet-zerocase,ontheotherhand,exhibitsmuchhigherimmediatecosts,thoughthisisbalancedbylowerGDPlossesafter2050(Figure15).23Figure15:PolicyCostsOverTimefortheModeledScenariosGDP=grossdomesticproduct,NDC=nationallydeterminedcontributions,PRC=People’sRepublicofChina.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.Differentassumptionsabouttheavailabilityofadvancedtechnologiesleadtodifferentcostsoftheacceleratedglobalnet-zeropathways,althoughcostsremainatfeasiblelevelsevenwithoutthesetechnologies(Figure16).BECCSturnsouttobeanimportantdeterminantofmitigationcosts,asitallowsnegativeemissionsfromenergygeneration.Notably,theunavailabilityofBECCSincreasespolicycostsbyabout1to2percentagepoints,whiledirectaircapture(DAC)appearstoplayalessimportantrole,giventheenergyandheatrequirements,relativelylowstoragepotentialintheregion,andhighinvestmentcosts.Withouttheoptionofmitigationthroughreducedemissionsfromdeforestationandforestdegradation(REDD),thecostsincreaseinmostregions.Inareaswithrelativelycost-efficientREDDpotentialsuchasIndonesia,wherepeatlandprotectionandrestorationprovideanimportantpotentialcarbon-emissionsink(Humpenöderetal.2020),thismitigationstrategyallowslowercontributionoftheeconomytotheglobalemissionstarget,thusbringingdownpolicycosts.24Figure16:PolicyCostoftheAcceleratedGlobalNet-ZeroScenariowithoutCarbonDioxideRemovalTechnologiesBECSS=biomasswithcarboncaptureandstorage,BGE=balancedgrowthequivalent,ameasureofwelfare,CCA=CaucasusandCentralAsia,CCS=carboncaptureandstorage,DAC=directaircapture,GDP=grossdomesticproduct,PRC=People’sRepublicofChina,REDD=reducedemissionsfromdeforestationandforestdegradation,SA=restofSouthAsia,SEA=restofSoutheastAsia.Source:Authors’estimates.6.ClimateBenefitsofLow-CarbonPoliciesTheclimatescenarioshavedistinctimplicationsforglobalwarming,andconsequently,fortemperaturechangesandlossesfromclimatechangeinAsia.Figure17illustratesthepeaktemperaturesprojectedforindividualeconomieswithinthe21stcenturyunderthedifferentscenarios.Itisimportanttonotethattheacceleratedglobalnet-zeroscenarioconsistentlyyieldsthelowestmaximumtemperatures,emphasizingtheneedforswiftandcollaborativeclimateactiontomitigatethemostsevereconsequencesofclimatechangeacrosstheregion.25Figure17:MaximumTemperatureChangeOverthe21stCenturyComparedtoAverageHistoricalTemperatureNDC=nationallydeterminedcontribution.Note:ThemapshowsAsianDevelopmentBankdevelopingmembereconomies.Source:Authors’estimates.Thedifferencebetweentemperaturechangesinthescenariosallowscalculationofthenetbenefitsofclimateaction,measuredasthedifferencebetweenthedamagesavoidedcomparedtothecurrentpoliciesreferencescenarioandthemitigationcostsassociatedwiththepolicyscenario.Althoughthereissubstantialdisagreementintheliteratureregardingthemagnitudeofeconomicimpactsresultingfromclimatechange,thereisaconsensusthattheseimpactsescalatewithincreasingtemperatures.Theimplicationsofarangeofestimatesarefirstconsidered.Theanalysisincorporatesvariouseconometricestimatesfromtheliterature(O’Neilletal.2022,IPCC2022aandDrouetetal.[2022]),whichvaryintermsofdatasetusageandspecifications(e.g.,differentiationbetweenpoorandricheconomiesandinclusionofyear-lags).Itisimportanttomention,however,thattheseestimatesdonotaccountfornon-marketdamagesandcatastrophicorextremeevents,andprimarilyincludepersistentdamageswithlimitedadaptationmeasures.26Fivefunctionsareeconometric:(i)growthfunctionsoflineartemperaturewithpersistentdamage(Dell,Jones,andOlken2012);(ii)growthdamagefunctionsofquadratictemperaturewithpersistentdamage(Burke,Hsiang,andMiguel2015);(iii)specificationrefinementstoBurke,Hsiang,andMiguel(2015)inHenselerandSchumacher(2019);(iv)inclusionofwithin-yeartemperaturevariationintheBurke,Hsiang,andMiguel(2015)modelgenre(Pretisetal.2018);and(v)agrowth-basedfunctionofregionaltemperatureandannualtemperaturevariation(KalkuhlandWenz2020).Recentliteraturehaspointedoutlimitationsandissuesintheseeconometricestimates.Forexample,useofeconomicgrowthrateasdependentvariableleadstohigherdamageestimatesthanuseofeconomicactivitylevel,buttheformerindicatormaytendtobeunstableandsensitivetospecification(Newell,Prest,andSexton2021).Econometricmethodsallproxyweathervariationsforclimatechangeinamannerthatextrapolatesfromshocksthatcannotbeeasilypredictedtolonger-termtrends.Inviewoftheselimitations,damagefunctionsfromanexercisethatembedsectoralimpactsincomputablegeneralequilibriummodelsarealsoapplied(vanderWijstetal.2023).Thenetpresentvalue(NPV)ofnetcosts/benefitsin2020arecalculatedusinga3%discountrateacrossvariousscenarios,aspresentedinFigure18.MostAsianregionsexperiencebenefitsfromclimateaction,withsomeestimatesshowingsubstantialgains.InIndiaandSouthAsia,netbenefitsmayexceed20%oftheNPVofGDPunderthecurrentpoliciesscenariowithwarming.Astheseregionsfacesignificantimpactsfromclimatechange,therelativebenefitsarenotablyhigh.IndonesiaandSoutheastAsiaobservenetbenefitsofupto15%.27Figure18:SumofPolicyCostsandClimateBenefitsinDevelopingAsiaundertheModeledScenariosBHM2015=Burke,Hsiang,andMiguel2015;COACCH=Co-designingtheAssessmentofClimateChangecostssummarizedinvanderWijstetal.2023;DJO2012=Dell,Jones,andOlken2012;HS2019=HenselerandSchumacher2019;KW2020=KalkuhlandWenz2020;PRC=People’sRepublicofChina;PRETIS2018=Pretisetal.2018.Notes:ResultsforCaucasusandCentralAsiaarebasedonclimatedamagefunctionsthatoftenconsidertheregionaspartof“transitioneconomies”thataredominatedbylargereasternEuropeaneconomiesandmaynotrepresenteffectsfortheregionappropriately.Theyshouldbeinterpretedwithcautionandareomittedfromfurtheranalysis.SouthAsiaandSoutheastAsiaexcludeIndiaandIndonesia,respectively.Source:Authors’estimates.Acrossthevariousscenarios,certaintrendsemergeirrespectiveoftheestimatesused.TheNDCeffortscenarioyieldslownetbenefitscomparedtothecurrentpoliciesscenarioforallregions,whilethenet-zeroscenariosshowamorediverserangeofresponsesacrossregions.Intheglobalnet-zeroscenarios,netbenefitsfromclimateactionareobserved,butintheuncoordinatednet-zeroscenario,threeregions(India,Indonesia,andthePRC)experiencenetcosts,whileSouthAsiaandSoutheastAsiareportnetbenefits.Thishighlightstheimportanceofcoordinatedclimateaction.Earlyaction,asillustratedintheacceleratednet-zeroscenario,increasesnetbenefitscomparedtosloweractionundertheglobalnet-zeroscenario.28ClimateimpactsarecalculatedusingparametersproducedfromtherecentCo-designingtheAssessmentofClimateChangeChangecosts(COACCH)project,asillustratedinFigure19.Thisisconsideredapreferredsourceofdamagefunctions,astheprojectbasedlossesonsimultaneousconsiderationofmodeledsectorallossesinaneconomywideframework,ratherthanrootdamagesinunstableeconometricspecificationsthattypicallyproxyweatherforclimate.Resultsarealsolargelyconsistentwiththemeta-studyonclimatedamagefunctionsbyHowardandSterner(2017).Figure19:TotalGrossDamagesduetoClimateChangeundertheCOACCHSpecificationCOACCH=Co-designingtheAssessmentofClimateChangecostssummarizedinvanderWijstetal.2023;GDP=grossdomesticproduct;NDC=nationallydeterminedcontribution;PRC=People’sRepublicofChina.Notes:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.MoreinformationonCOACCHprojectcanbefoundinvanderWijstetal.2023.“NewDamageCurvesandMultimodelAnalysisSuggestLowerOptimalTemperature.”NatureClimateChange.13.434–441.ThepercentagechangeinGDPisrelativetothereferencescenariowithoutclimatechange.Source:Authors’estimates.UndertheCOACCHdamagefunction,thereisanincreaseinnetbenefitsfromthepresentuntiltheendofthecenturyformostregionsacrossallscenarios(Figure20).Notably,substantialnetbenefitsarenotexpectedbefore2050,asmitigationcoststendtooutweighavoideddamagesduringthisperiod.Infact,underthenet-zeroscenario,netcostsareexpectedtopersistuntilmid-29century.Inthelatterhalfofthecentury,oncethezero-emissiontargethasbeenachieved,avoideddamagesdominatemitigationcosts.Thisalignswiththeexistingliteraturethatexaminesthecostsandimpactsassociatedwithnet-zeroemissionspathways(Riahietal.,2021).Figure20:AnnualNetPolicyCostsandClimateBenefitsagainsttheCurrentPoliciesScenarioNDC=nationallydeterminedcontribution,PRC=People’sRepublicofChina.Note:ClimatebenefitsarebasedonvanderWijst,K.etal.2023.“NewDamageCurvesandMultimodelAnalysisSuggestLowerOptimalTemperature.”NatureClimateChange13.434–441.Netcostsarehighlightedinred,whilenetbenefitsareinblue.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.7.Co-benefitsofLow-CarbonPoliciesDecarbonizationisknowntoyieldco-benefitsintermsofairpollutionreduction(Raoetal.2017).Itisimportantthereforetoconsidernotonlythedirectclimatebenefitsofreducingfossilfuelconsumptionbutalsothepotentialimprovementsinairqualityandpublichealth.Exposuretoairpollutionisamajorhealthconcernworldwide.AccordingtotheGlobalBurdenofDisease(GBD)30studyin2019,oneinninedeathsgloballycanbeattributedtofineparticulatematter(PM2.5)andozone(O3)airpollution.Amongthesedeaths,5.7%areduetoO3,withtherestlinkedtoPM2.5.Toassesstheimpactofairpollutiononhumanmortality,theFASST(R)modelisemployed(Reisetal.2018).TheFASST(R)model(VanDingenenetal.2018)isaglobalsource-receptormodelthatestimatesconcentrationsofthemostharmfulpollutants(ozoneandPM2.5)basedonprecursoremissions.UsingO3andPM2.5concentrations,themodelappliesmortalityandcropimpactfunctionsasdescribedinVanDingenenetal.(2018).Althoughtheseestimatesmaybeconsideredconservative,asnewerGBDestimatesreporthighermortalityeffects,FASST(R)modelresultsfallwithinthelowerboundoftherangeintheliterature,whenconsideringotherstudies(Reisetal.,2022).Themodelconsidersemissionsofprimarypollutants(i.e.,nitrogenoxides[NOx],sulfurdioxide[SO2],volatileorganiccompounds[VOCs],organiccarbon[OC],ammonia[NH3],andblackcarbon[BC])andcalculatesPM2.5andO3concentrations.BCandOCconstitutetheprimarycomponentofPM2.5,whileNOx,SO2,VOCs,andNH3reactintheatmospheretoformsecondaryPM2.5.Additionally,NOx,VOC,and,toalesserextent,carbonmonoxide(CO)andmethane(CH4),reactintheatmospheretoproduceO3.TheanalysisinputsairpollutantemissionsdatafromtheWITCHmodelintotheFASST(R)model.TheseincludeNOx,SO2,VOCs,NH3,CH4,CO,OC,andBC.FASST(R)subsequentlycalculatespollutantconcentrationsandtheirimpactsonprematuremortalityandcropyields.Figure21showsthatinallscenarios,theregionsofdevelopingAsia—primarily,IndiaandthePRC—experiencethelargestairqualitybenefitsofdecarbonization.Clearly,globalnet-zeroscenariosnotonlyreduceclimaterisksbutalsodecreasemortalityassociatedwithairpollutionthroughoutdevelopingAsia.Acrucialinsightfromthisanalysisisthatdelayedclimatepoliciesleadtohighernear-termprematuredeaths,asshownbythedifferencebetweentheacceleratedglobalnet-zeroscenariosandNDC-basedonesin2030.Thisfindingunderscorestheneedtoincreaseambitionsinclimate31policiesnotonlypost-2030butalsoleadingupto2030(IPCC2018).Byprioritizingtimelyandeffectiveclimateaction,policymakerscanaddressbothclimatechangeandhealthobjectives.Figure21:AvoidedAnnualPrematureDeathsduetoOutdoorParticulateMatter2.5andOzoneundertheModeledScenariosNDC=nationallydeterminedcontribution,O3=ozone,PRC=People’sRepublicofChina.Notes:Avoidedmortalityiscalculatedagainstthecurrentpolicyscenario.SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.32Theanalysisfurtherrevealsthatallscenariosresultinavoidanceofcroplosses.Figure22indicatesthat,intermsofvolume,wheatandricearethecropsmostlikelytobenefitfromreducedairpollution.Meanwhile,cost-optimalpoliciesimplementedgloballyandearly,asintheacceleratedglobalnet-zerocase,arelikelytodeliverthehighestco-benefits.InthePRC,acceleratedglobalnet-zeropoliciesmaypreventproductionlossesofmorethan1millionmetrictons(MT)ofriceandover2.4millionMTofwheatby2030.Meanwhile,inIndia,riceproductioncouldyieldover1.2millionMTmoreinthesameyearundertheseambitiouspolicies.Airqualityco-benefitscanbeaddedtoclimatebenefitstogiveabroaderpictureofhowgainsofclimateactioncomparewithitslosses.Combiningthetotaleconomiccostsandbenefitsgivestheoveralllossesandgainsassociatedwiththestringentnet-zeroscenarios.Theprimarycomponentsconsideredincludetotalmitigationcosts,thevalueofair-pollution-relatedprematuredeathsbasedonthevalueofastatisticallife(VSL),andtheestimatedeconomiclossesfromglobalwarming.AVSLof160timesthegrossnationalincomeforeacheconomy,assuggestedbyRobinsonetal.(2019),isusedtotranslatemortalityintoeconomicvalues.Figure22:AvoidedAnnualCropLossfromOzoneundertheModeledScenarios(RelativetotheCurrentPoliciesScenario)NDC=nationallydeterminedcontribution.Source:Authors’estimates.33Figure23presentsthetotalflowofbenefitsandcostsfordevelopingAsiaandtheworld,includingairpollutionimpacts.Airpollutiondamagesareextrapolatedbeyond2050bytakingthedifferenceinprimaryPM2.5emissions(BCandOC)betweenastringentpolicyscenarioandthecurrentpoliciesscenario.By2050,mitigationcostsinallregionswillbeoutweighedbyairpollutionco-benefits—reachingupto1,200billioninthePRCand400billioninIndia—andclimateimpacts.Collectively,thenetpresentvalueofbenefits(discountedat3%)isfivetimescostsfordevelopingAsia,andallregionsfacebenefitsthatareatleast3timescosts.Thehighestratiosofbenefitstocostsareinthelowestincomeeconomies/subregionsofIndia,therestofSouthAsia,andtherestofSoutheastAsia.Figure23:AnnualNetPolicyCosts,ClimateBenefits,andAirQualityCo-benefitsinDevelopingAsiaundertheAcceleratedGlobalNet-ZeroScenario,RelativetotheCurrentPoliciesScenario(millionsof$)12,000DevelopingAsia1,500PRC6,000India1,0004,0008,000204020602,000204020604,000500000-2,000-4,000-500-1,00020202020204020602080-1,500210020202080210020802100IndonesiaRestofSouthAsiaRestofSoutheastAsia1,5001,5002,0001,0001,0001,5001,000500500005000-500-50020202020204020602080-5002040206020802100210020202040206020802100PRC=People’sRepublicofChinaSource:Authors’estimates.348.EquityImplicationsofLow-CarbonPoliciesTounderstandthedistributionalimplicationsofthenet-zeroscenariosvialabormarkets,anenergyemploymentmodulebasedoneconomy-leveldatafromPaietal.(2021)isapplied.ThemodelestimatestotaldirectemploymentintheenergysectorofdevelopingAsiaatabout12.7millionfull-timeequivalentjobsin2020(Figure24).Thisnumberisexpectedtoincreaseto15.5millionby2050undertheNDCeffortscenario,andevenfurtherto17.3millionintheacceleratedglobalnet-zeroscenario,anincreaseofover36%.ThePRCaccountsforalargeshareoftotalemployment,largelyduetomanufacturingofsolarphotovoltaic(PV)capacity,whichisestimatedtocoverabout77%oftheworldmarket.However,theincreasealsoimpliesalargeshiftintheenergysector’sworkforceacrossjobtypes,technologies,andregions.Comparedtotheoutlookundercurrentpolicies,about1.4millionjobsinthecoalsectormaybelostinAsiaundertheacceleratedglobalnet-zeroscenario,while2.9millionjobsmayeventuallybecreatedbymid-century,particularlyinthemanufacturingandinstallationofsolarPVsandwindmills(Figure25).35Figure24:TotalDirectEnergySectorJobsinDevelopingAsiaundertheModeledScenarios,2020and2050PRC=People’sRepublicofChina,O&M=operationsandmaintenance.Note:SouthAsiaandSoutheastAsiaexcludesIndiaandIndonesia,respectively.Source:Authors’estimates.36Figure25:ChangeinFull-timeDirectEnergySectorEmploymentbyTypeofEnergybetweentheCurrentPoliciesandAcceleratedGlobalNet-ZeroScenario(millionfull-time-equivalentjobs)Source:Authors’estimates.Theanalysishasfocusedsofaronexaminingtheregionalandeconomy-levelimpactsofthedifferentmitigationscenarios,inwhichtheneteffectsofanefficientandambitiousapproachtodecarbonizationarefoundasoverwhelminglypositive.However,itisalsocrucialtoconsiderwithin-economyimpactsofcarbonpricingandresultingenergyandfoodpricechanges,asthesemayleadtowinnersandlosers.Thefoodpriceindexservesasanindicatorofcompetitionforlandandresourcesaseconomicactorschoosebetweenforest,croplandforfoodproduction,andbioenergyproduction.Itisdecreasinginthecurrentpoliciesscenariobutrisesby5%to10%bytheendofthecenturyundertheNDCeffortscenario(Figure26).9Intheuncoordinatednet-zeroscenario,foodprices9Notethattheimpactsofclimatechangeonagriculturearenotreflectedinthepricesmodeled.37initiallyrisetoamaximumof10%aroundmid-century,andthenfallbacktotheirpreviousleveloncenet-zerotargetsareachieved.Intheglobalnet-zeroscenarios,foodpricesmayseearapidincreaseofupto20%to25%bytheendofthecentury.Ambitiousclimatechangemitigationpolicyalsoaffectshouseholdsviaenergypricesignals(Figure27).Householdenergysubstitutionfromtraditionalbiomasstoothersourcesandshiftsinelectricitypricesmeanthatenergyuseforcookingandheatingbecomesmorecostly.Transportationcostsalsoinitiallyincreasetocoverthecostsofchangestoinfrastructureandvehicleelectrification,eventhoughthosechangessaveexpendituresinthelongerterm.Arangeofstudiessuggeststhatcarbonpricingmayberegressivewithineconomies,asitplacesadisproportionatelyhigherburdenonpoorerhouseholds(e.g.,Budolfsonetal.2021,Feindtetal.2021,HallegatteandRozenberg2017).Revenuerecyclingandredistributionschemesorclimatedividendshavethusbeenproposedasasolutiontoalleviatetheregressiveeffectwhileatthesametimeensuringpolicysupportandacceptance.Figure26:FoodPriceIndexinDevelopingAsiaundertheModeledScenariosNDC=nationallydeterminedcontributions.Source:Authors’estimates.38Figure27:ChangeinHouseholdFood,Energy,andTransportationExpendituresfromtheCurrentPoliciestoAcceleratedGlobalNet-ZeroScenarioresidentialenergyfoodtransportation30%20%10%0%-10%-20%-30%20202025203020352040204520502055206020652070207520802085209020952100Source:Authors’estimates.BasedonhouseholdsurveysfromIndiaandthePRCmicroeconomicmodelsarecalibratedandcoupledtotheWITCHmodelforthedifferentscenarios.10ThisallowscomputationoftheenergyandfoodconsumptionofhouseholdsatthedecileleveloftheincomedistributionwhileincorporatingenergypricesandquantitiesprovidedbytheWITCHmodel.Thisallowsquantificationofthedistributionalimpactscomparedtothecurrentpoliciesscenario,whichservesasabaseline(MalerbaandEmmerling2022).Basedonthisapproach,theexpendituresforresidentialenergyconsumptiontendtoberegressiveinIndia,althoughenergyexpendituresareneutralinthePRC.Transportationenergyexpenditures,includinggasoline,aretypicallyprogressive,however,asricherhouseholdsspendmoreontransportation(Figure28).10GovernmentofIndia,MinistryofStatistics&ProgrammeImplementation.2012.NationalSampleSurvey2011–2012(68thround).ConsumerExpenditure.http://microdata.gov.in/nada43/index.php/catalog/1;GovernmentofthePRC.2013.ChineseHouseholdIncomeProject,2013wave(CHIP).CHIPDatasetHomepage.http://www.ciidbnu.org/chip/index.asp39Figure28:HouseholdExpenditureSharesforEnergyforHousingandTransportationperDecileinIndiaandthePeople’sRepublicofChina,2012–2013PRC=People’sRepublicofChina.Source:Authors’estimates.CombiningtheseresultswiththeenergyandfoodpricepatternsinthescenariosfindsstrongregressivityofambitiousclimatepolicyinIndia.Incontrast,theimpacttendstobemoreevenlydistributedacrossincomedecilesinthePRC(bluelineinFigure29).Redistributionofcarbonrevenuescanpartlyoffsetpotentiallyinequitableoutcomes.Forexample,asimpleclimatedividendintheformofanequalper-capita(EPC)transfertohouseholdsasinBudolfsonetal.(2021)canbecomparedwiththedefaultscenarioofusingcarbonrevenuestoreducegeneraltaxationpressure.Asthefigureshows,thispolicyprovidesgreatpotentialtoleadtoahighlyprogressiveclimate-policyimpactinbothIndiaandthePRC(redlineinFigure29).Thelowest2to4deciles,inparticular,maybecomebetteroffthantheywouldbeinthecurrentpolicybaselinescenario,implyinga“poverty”dividendfromclimatepolicyandredistribution.40Figure29:TotalImpactofAlternativeRedistributionofCarbonPricingRevenuesonHouseholdConsumptionundertheAcceleratedGlobalNet-ZeroScenarioComparedtotheCurrentPoliciesScenarioepc=equalpercapitatransfers,PRC=People’sRepublicofChina.Source:Authors’estimates.9.ConclusionDecarbonizationpresentsimportantchallenges,butitalsoholdspotentiallylargebenefitsfordevelopingAsia.Atthesametime,thechangesrequiredarelikelytobesubstantial,asthecurrentandpledgedpoliciesofeconomiesintheregionstillfallshortofambitionstomeetthetemperature-stabilizationgoalsoftheParisAgreement.Thefindingsindicatethatacontinuationofcurrentpolicieswouldleadtoglobalwarmingofaround3°Conaveragebytheendofthecentury,whileNDCeffortwillbringthisdowntoaround2.4°C.Theuncoordinatednet-zeroscenario,inwhicheacheconomysimplyfollowsitspledge,alsoleadstotemperatureincreasesthatdonotmeetthewellbelow2°Ctarget.Onlytheglobalnet-zeroscenariosare,bydesign,compatiblewiththeParisAgreement.41Coal,amajorsourceofemissions,alreadyseesnonewcapacityadditionsindevelopingAsiaunderexistingpolicies.Moreover,itisphasedoutcompletelyacrosstheregionby2040inthenet-zeroscenario,exceptinthenon-electricsector(suchastheheavyindustry,cement,andsteelindustries).Thepowersectormeanwhilewillneedtoachievefulldecarbonizationasearlyas2040intheacceleratedglobalnet-zeroscenario.Thisrapidpacewillrequirealargechangeinenergysysteminvestmentsoverthenexttwodecades.Land-useemissionswilllikewisehavetoberadicallycurtailed,includingthroughexpandedareaofforest,whichmaycompetewithfoodproduction.Ineconomicterms,anacceleratedglobalnet-zerotransitionmayincuraveragecostsofaround1%ofGDP.CentralAsia,theonlymajornetexporteroffossilfuelsindevelopingAsia,maysufferhigherlossesthanelsewhereintheregion.Losseshoweverarefoundtobesmallestinthesubregionswiththelowestincomes.Anacceleratedtransitiontonet-zeropotentiallyoffersnumerousbenefitsandgainstocompensateforthecosts.First,thefindingsindicatethataprojectedlossofapproximately2millionjobsintheenergysector,specificallyincoalmining,canbemorethanoffsetbythecreationof3to4millionjobsinmanufacturing(primarilyinthePRC)andinstallationofrenewables(acrossdevelopingAsia).Second,thereductioninairpollutionresultingfromthetransitioncanhelpreduceprematuredeathsandcroplosses,leadingtoabout0.4millionavoideddeathsannuallyby2050.Finally,adverseclimateimpactsavertedbecauseofclimatemitigationmeasureswillbesubstantial,withIndiaandtherestofSouthAsiamostlikelytoescapethebiggestdamagesrelativetothebaseline(currentpolicies)scenario.Overall,thesebenefitsmorethanoutweighthemitigationcostsinalmostallregionsby2030—andinCentralAsiafrom2040onwards—eventuallyexceedingcostsroughlybyafactoroffivetooneinthewholeofAsiaby2050.Atthesametime,noteveryoneisnecessarilyawinnerfromclimatepolicy.Attheeconomylevel,carbonpricingmayprovetoberegressive,andcertaingroupsmayexperienceadverse42employmentoutcomes.Redistributionandreskillingschemestohelptheaffectedarethuscriticallyimportant,especiallytomitigateadverseimpactsonthepoor,garnerpublicsupportforclimatepolicies,andultimatelyensureajusttransition.43APPENDIXInterpretationandImplementationofCurrentPolicies,NDCs,andNet-ZeroPledgesTableA1listsnationalpoliciesimplementedintheWorldInducedTechnicalChangeHybrid(WITCH)modelunderthecurrentpoliciesscenario.Policiesareimplementedasexplicitconstraintsonaspecificyear,forexample,thePeople’sRepublicofChina(PRC)hasatargetofachieving35%shareofelectricityfromrenewableenergyandnuclearenergyby2030,whichisimplementedasanexplicitconstraintinthemodelstartingin2030.Whenpoliciescannotberepresentedexplicitlyasconstraints,carbontaxesareimposed.Forexample,policiestoachievecertainindustryperformancetargetsortargetsonnumbersoftreesplantedareimposedascarbontaxes.TableA1:NationalClimate-EnergyPoliciesImplementedPoliciesSectorStartingEconomyTVaarlgueetUnitTransportDateARG0.12SharebiofuelsinfueloilElectricityproduction2030ARG0.18ElectricityproductionARG0.20Renewablesshare2023ElectricityproductionARG5.00$/tCO2RenewablesshareElectricityproduction2025ImplicitcarbontaxintheenergyTransportsectorin2025HFC2025ARG1.00$/tCO2Implicitcarbontaxintheland-use2030sectorin2025Wind2030AUS0.35RenewablesshareBiomass2030AUS0.50HydroAUS0.29RenewablesshareElectricityproductionAUS0.02GtCe/yearElectricityproductionIntensitychangePrimaryenergysupplyAUS3.00$/tCO2Emissions2029AUS0.01$/tCO2Implicitcarbontaxintheenergy2029sectorin20252029BRA0.04TWImplicitcarbontaxintheland-use2024BRA0.02TWsectorin20252029BRA0.11TWCapacitytargetpertechnology2029BRA0.16BRA0.81CapacitytargetpertechnologyBRA0.48CapacitytargetpertechnologyRenewablesshareRenewablesshareRenewablesshareContinuedonthenextpage44ImplementedPoliciesSectorStartingEconomyTVaarlgueetUnitTransportDateBRA0.15RenewablesshareBRAImplicitcarbontaxintheenergyTransport20231.00$/tCO2sectorin2025HFCImplicitcarbontaxintheland-useGHG(BAU)2015BRA0.00$/tCO2sectorin2025Ch4_20152036Sharebiofuelsinfueloil2030CAN0.05Electricityproduction2025CAN0.00EmissionsPrimaryenergysupplyCAN0.01GtCe/yearNuclearCAN0.40EmissionsEnergyconsumptionCAN5.00$/tCO2EmissionsTransportImplicitcarbontaxintheenergy2030CAN0.01$/tCO2sectorin2025GHG2035Implicitcarbontaxintheland-usePrimaryenergysupply2025PRC0.35sectorin2025Energyconsumption2025PRC0.20Renewables+NuclearshareTransport2025PRC0.07F-gases2020PRC0.18Renewables+NuclearshareEnergyconsumptionPRC0.142030PRC0.01CapacitytargetpertechnologyTransport2030Primaryenergysupply2030PRC0.01$/tCO2CO2IntensitychangeHydro2020Wind2030EUR8.29IntensitychangeSolar2030EUR0.27SolarEUR14800.00TWhRenewablesshareTransportEUR0.17Implicitcarbontaxintheland-useEUR0.66GtCe/yearsectorin2025EUR0.32EmissionsEUR25.00$/tCO2Renewables+Nuclearshare2025EUR3.00$/tCO2primaryenergyconsumption20252028EUR0.25Sharebiofuelsinfueloil2028INO0.232028INO0.01TWEmissionschange2035INO0.00TW2025INO0.00TWRenewablesshareINO0.00TWImplicitcarbontaxintheenergyINO0.23sectorin2025Implicitcarbontaxintheland-useINO0.01$/tCO2sectorin2025SharebiofuelsinfueloilINO0.01$/tCO2Renewables+NuclearshareCapacitytargetpertechnologyCapacitytargetpertechnologyCapacitytargetpertechnologyCapacitytargetpertechnologySharebiofuelsinfueloilImplicitcarbontaxintheenergysectorin2025Implicitcarbontaxintheland-usesectorin2025Continuedonthenextpage45ImplementedPoliciesSectorStartingEconomyTargetUnitSolarDateValueCapacitytargetpertechnologySolar2022IND0.10TWSolar2022IND0.06TWCapacitytargetpertechnologyHydro2022IND0.01TWElectricityproduction2022IND0.01TWCapacitytargetpertechnologyElectricityproduction2022IND0.202027IND0.24CapacitytargetpertechnologyWindEnergyconsumptionIND3.00$/tCO2RenewablessharereductionEnergyconsumptionIND0.50$/tCO2RenewablessharereductionImplicitcarbontaxintheenergyElectricityproduction2030JPN0.01TWsectorin20252020Implicitcarbontaxintheland-useElectricityproductionJPN0.06sectorin2025ElectricityproductionCapacitytargetpertechnologyElectricityproduction2030JPN0.16Windoffshore2030IntensitychangeWindonshoreJPN0.36HydroIntensitychangeBiomassJPN3.00$/tCO2RenewablesshareElectricityproduction2040JPN0.01$/tCO2ImplicitcarbontaxintheenergyElectricityproduction2034sectorin2025Electricityproduction2030ROK0.33Implicitcarbontaxintheland-use2030ROK0.40sectorin2025Primaryenergysupply2030ROK0.20Renewables+Nuclearshare2030ROK0.01TW2030ROK0.01TWRenewablesshareROK0.00TWROK0.00TWRenewables+NuclearshareROK3.33$/tCO2Capacitytargetpertechnology2030ROK0.01$/tCO2Capacitytargetpertechnology20182021MEX0.09GtCe/yearCapacitytargetpertechnology2024MEX0.25MEX0.30CapacitytargetpertechnologyMEX0.35Implicitcarbontaxintheenergysectorin2025MEX3.00$/tCO2Implicitcarbontaxintheland-usesectorin20252030MEX3.00$/tCO2CH4EmissionsRUS0.13RenewablesshareRUS3.00$/tCO2RenewablesshareRenewablesshareImplicitcarbontaxintheenergysectorin2025Implicitcarbontaxintheland-usesectorin2025Renewables+NuclearshareImplicitcarbontaxintheenergysectorin2025Continuedonthenextpage46ImplementedPoliciesSectorStartingEconomyTVaarlgueetUnitDate0.01$/tCO2Implicitcarbontaxintheland-useSolarRUS0.04TWsectorin2025Wind2040SAU0.01TWCapacitytargetpertechnology2040SAU0.10$/tCO2CapacitytargetpertechnologyFinalenergySAUImplicitcarbontaxintheenergyconsumptionsectorin2025EnergyintensitySAU0.01$/tCO2Implicitcarbontaxintheland-usereduction2010sectorin2025Electricityproduction2037THA0.34RenewablesshareBiomassHydro2036THA0.30IntensitychangeSolarWind2037THA0.21RenewablesshareTransport2037THA0.01TW2037THA0.00TWCapacitytargetpertechnologyHydro2037THA0.02TWCapacitytargetpertechnologyWind2037THA0.00TWCapacitytargetpertechnologySolar2020THA0.10CapacitytargetpertechnologyElectricityproductionSharebiofuelsinfueloilEnergyintensityTHA1.00$/tCO2Implicitcarbontaxintheenergyreduction2010sectorin2025Primaryenergysupply2023THA1.00$/tCO2Implicitcarbontaxintheland-use20152023sectorin20252023TUR0.03TWCapacitytargetpertechnologyTransport2023TUR0.01TWCapacitytargetpertechnologyTUR0.01TWCapacitytargetpertechnologyHydro2023TUR0.30RenewablesshareWindIntensitychangeCSPTUR0.20PVprimaryenergyconsumptionchange2023TUR0.14PJImplicitcarbontaxintheenergyTUR0.01$/tCO2sectorin2025Implicitcarbontaxintheland-use2022TUR0.01$/tCO2sectorin20252030USA0.21SharebiofuelsinfueloilUSA0.01GtCe/yearHFCEmissionsUSA8.00$/tCO2Implicitcarbontaxintheenergysectorin20252030USA1.00$/tCO2Implicitcarbontaxintheland-use2035sectorin20252030ZAF0.00TWCapacitytargetpertechnology2030ZAF0.02TWCapacitytargetpertechnologyZAF0.00TWCapacitytargetpertechnologyZAF0.01TWCapacitytargetpertechnologyContinuedonthenextpage47ImplementedPoliciesSectorStDaarttiengEconomyTVaarlgueetUnitCapacitytargetpertechnologyNuclear2030ZAF0.00TWSharebiofuelsinfueloilTransport2020ZAF0.05ImplicitcarbontaxintheenergyZAF5.00$/tCO2sectorin2025ZAF0.01$/tCO2Implicitcarbontaxintheland-usesectorin2025$/tCO2=UnitedStatesdollarpertonofcarbondioxide,GtCe/year=gigatonsofcarbonequivalent,ARG=Argentina,AUS=Australia,BAU=business-as-usual,BRA=Brazil,CAN=Canada,CH4=methane,CO2=carbondioxide,EUR=Europe,GHG=greenhousegas,HFC=hydrofluorocarbons,IND=India,INO=Indonesia,JPN=Japan,MEX=Mexico,PRC=People’sRepublicofChina,ROK=RepublicofKorea,RUS=RussianFederation,SAU=SaudiArabia,THA=Thailand,TUR=Türkiye,TW=terawatt,TWh=terawatt-hour,USA=UnitedStates,ZAF=SouthAfrica.Source:Authors.TableA2liststheinterpretationofnationallydeterminedcontributions(NDCs)ofdevelopingAsianeconomiesimplementedintheWITCHmodel.Itlistsbothunconditionalandconditionaltargetsintermsoffractionofemissionreductionalongwithreductioninabsoluteemissions.OnlyNDCsthatareimplementableinthemodelareincluded.Absoluteemissionsarenotgivenwheneconomiesarepartofamacroregionanddidnotprovideausablebaselinescenario(BAU),andabsoluteemissionsarecalculatedendogenouslyusingWITCHdownscaledBAUemissions.ForIndiaandthePRC,thetargetsaredefinedasintensitytargets,thereforethenumbersdisplayedinthetablerefertotheresultsoftheNDCeffortscenario.TableA2:NationallyDeterminedContributionsofDevelopingAsianEconomiesUnconditionalConditionalTargetUnconditionalConditionalReductionReductionYearAbsoluteAbsolute(fraction)(fraction)EmissionsEmissions(GtCO2e)(GtCO2e)Afghanistan0.400.1420300.0490.0420.350.4020300.0160.016Armenia0.06730.3520300.0450.0450.200.151220300.1580.143Azerbaijan1.000.201.00203012.312.3Bangladesh0.350.0290.019Brunei0.31890.5720301.951.63Darussalam0.432Bhutan2030China,People’sRepublicof2030Georgia2030IndonesiaContinuedonthenextpage48UnconditionalConditionalTargetUnconditionalConditionalReductionReductionYearAbsoluteAbsolute(fraction)(fraction)EmissionsEmissions(GtCO2e)(GtCO2e)India20304.164.160.2490.220Kazakhstan0.150.2520300.0130.0080.0900.090KyrgyzRepublic0.160.4420300.0420.034Cambodia0.420.4220300.0020.000LaoPDR0.600.6720250.0570.0540.7590.759SriLanka0.070.2320301.3630.8020.3250.093Maldives0.261.0020300.0650.0650.4440.416Myanmar20300.1360.1360.3920.392Mongolia0.230.2720300.8440.677Malaysia0.450.452030Pakistan0.150.502030Philippines0.030.722030Singapore2030Thailand0.200.252030Turkmenistan2030Uzbekistan2030VietNam0.090.272030GtCO2e=Billionoftonsofcarbondioxideequivalent,LaoPDR=LaoPeople’sDemocraticRepublic.Notes:Effective1February2021,ADBplacedatemporaryholdonsovereignprojectdisbursementsandnewcontractsinMyanmar.ADBplacedonholditsregularassistanceinAfghanistaneffective15August2021.Source:Authors.49TableA3listsnationalnet-zeropledgesofdevelopingAsianeconomies.ReisandTavoni(2023)hasacompletelistofglobalnet-zeropledgesimplementedinthemodel.TableA3:Net-ZeroPledgesofDevelopingAsianEconomiesISO3TargetYearStatusGHGCoveredAfghanistan2050ProposedCO2Bhutan2030AchievedCO2China,People’sRepublicof2060DocumentCO2IndonesiaIndia2060DeclaredGHGKazakhstan2070DeclaredCO2KyrgyzRepublic2060DeclaredCO2Cambodia2050ProposedCO2LaoPDR2050DocumentGHGSriLanka2050DocumentGHGMaldives2050DocumentCO2Myanmar2050ProposedCO2Malaysia2050ProposedCO2Nepal2050DeclaredCO2PapuaNewGuinea2050DocumentGHG2050DeclaredGHGSingapore2050DocumentCO2Thailand2065DocumentCO22050ProposedCO2Uzbekistan2050DeclaredCO2VietNamCO2=carbondioxide,GHG=greenhousegases,LaoPDR=LaoPeople’sDemocraticRepublic.Note:Effective1February2021,ADBplacedatemporaryholdonsovereignprojectdisbursementsandnewcontractsinMyanmar.ADBplacedonholditsregularassistanceinAfghanistaneffective15August2021.Source:Authors.50REFERENCESAldy,JosephE.,WilliamA.Pizer,andKeigoAkimoto.2017.“ComparingEmissionsMitigationEffortsAcrossCountries.”ClimatePolicy17(4),501–15.Ang,BengWah,andF.L.Liu.2001.“ANewEnergyDecompositionMethod:PerfectinDecompositionandConsistentinAggregation.”Energy26,537–48._____.2007.“Negative-ValueProblemsoftheLogarithmicMeanDivisiaIndexDecompositionApproach.”EnergyPolicy35(1),739–42.Birol,Faith2021.“COP26ClimatePledgesCouldHelpLimitGlobalWarmingto1.8°C,butImplementingThemWillBetheKey.”InternationalEnergyAgency(IEA).4November.Bosetti,Valentina,CarloCarraro,EnricaDeCian,EmanueleMassetti,andMassimoTavoni.2013.“IncentivesandStabilityofInternationalClimateCoalitions:AnIntegratedAssessment.”EnergyPolicy55,44–56.Bosetti,Valentina,CarloCarraro,MarzioGaleotti,EmanueleMassetti,andMassimoTavoni.2006.“WITCH—AWorldInducedTechnicalChangeHybridModel.”TheEnergyJournal27,13–37.Budolfson,Mark,FrancisDennig,FrankErrickson,SimonFeindt,MaddalenaFerranna,etal.2021.“ClimateActionWithRevenueRecyclingHasBenefitsforPoverty,InequalityandWell-Being.”NatureClimateChange11,1111–6.Burke,M.,Hsiang,S.M.,Miguel,E.,2015.“GlobalNon-linearEffectofTemperatureonEconomicProduction.”Nature527,235–39.Dell,M.,F.Jones,andB.A.Olken.2012."TemperatureShocksandEconomicGrowth:EvidencefromtheLastHalfCentury."AmericanEconomicJournal:Macroeconomics4(3),66–95.Drouet,Laurent,ValentinaBosetti,SimoneA.Padoan,LaraAleluiaReis,CristophBertram,etal.2021.“NetZero-EmissionPathwaysReducethePhysicalandEconomicRisksofClimateChange.”NatureClimateChange11,1070–6.Drouet,Laurent,ValentinaBosetti,andMassimoTavoni.2022.“NetEconomicBenefitsofWell-Below2°CScenariosandAssociatedUncertainties.”OxfordOpenClimateChange2(1),kgac003.Emmerling,Johannes,LaurentDrouet,LaraReis,MichelaBevione,LoicBerger,etal.2016.“TheWITCH2016Model-DocumentationandImplementationoftheSharedSocioeconomicPathways.”FEEMWorkingPaperNo.2016.42.FondazioneEniEnricoMattei(FEEM).Emmerling,Johannes,UlrikeKornek,ValentinaBosetti,andKaiLessmann.2020.“ClimateThresholdsandHeterogeneousRegions:ImplicationsforCoalitionFormation.”TheReviewofInternationalOrganizations16,293–316.51ENOVATE.2022.NetZeroTrackerEnovateNetZeroTrackerHttpszerotrackernetAug2022.https://zerotracker.net/(accessed30September2022).Feindt,Simon,UlrikeKornek,JoséM.Labeaga,ThomasSterner,andHaukeWard.2021.“UnderstandingRegressivity:ChallengesandOpportunitiesofEuropeanCarbonPricing.”EnergyEconomics103,105550.Hallegatte,Stephane,JulieRozenberg.2017.“ClimateChangeThroughaPovertyLens.”NatureClimateChange7,250–6.Harmsen,J.H.M.,DetlefP.vanVuuren,DaliR.Nayak,AndriesF.Hof,LenaHöglund-Isaksson,PaulL.Lucas,JensB.Nielsen,PeteSmith,andElkeStehfest.2019.“Long-TermMarginalAbatementCostCurvesofNon-CO2GreenhouseGases.”EnvironmentalScience&Policy99,136–49.Henseler,M.,andI.Schumacher.2019."TheImpactofWeatheronEconomicGrowthandItsProductionFactors."ClimaticChange154(3),417–33.Howard,PeterH.,andThomasSterner.2017.“FewandNotSoFarBetween:AMeta-analysisofClimateDamageEstimates.”EnvironmentalandResourceEconomics68,197–225.Humpenöder,Florian,KristineKarstens,HermannLotze-Campen,JensLeifeld,LorenzoMenichetti,etal.2020.“PeatlandProtectionandRestorationAreKeyforClimateChangeMitigation.”EnvironmentalResearchLetters15(10),104093.IEA.2020.TrackingCleanEnergyInnovation.Paris:InternationalEnergyAgency.IPCC.2018.SpecialReportonGlobalWarmingof1.5oC.Geneva:IntergovernmentalPanelonClimateChange._____.2022a.AnnexIII:ScenariosandModellingMethods.InIPCC2022:ClimateChange2022:MitigationofClimateChange.ContributionofWorkingGroupIIItotheSixthAssessmentReportoftheIntergovernmentalPanelonClimateChange[P.R.Shukla,J.Skea,R.Slade,A.AlKhourdajie,R.vanDiemen,D.McCollum,M.Pathak,S.Some,P.Vyas,R.Fradera,M.Belkacemi,A.Hasija,G.Lisboa,S.Luz,J.Malley,(eds.)].CambridgeUniversityPress,Cambridge,UKandNewYork,NY,USA._____.2022b.ClimateChange2022:MitigationofClimateChange.ContributionofWorkingGroupIIItotheSixthAssessmentReportoftheIntergovernmentalPanelonClimateChange.Kalkuhl,Matthias,andLeonieWenz.2020.“TheImpactofClimateConditionsonEconomicProduction.EvidencefromaGlobalPanelofRegions.”JournalofEnvironmentalEconomicsManagement103,102360.Keppo,I.,Butnar,I.,Bauer,N.,Caspani,M.,Edelenbosch,etal.2021.“ExploringthePossibilitySpace:TakingStockoftheDiverseCapabilitiesandGapsinIntegratedAssessmentModels.”EnvironmentalResearchLetters16(5),053006.52Krey,Volker,FeiGuo,PeterKolp,WenjiZhou,RobertoSchaeffer,etal.2018.“LookingUndertheHood:AComparisonofTechno-EconomicAssumptionsAcrossNationalandGlobalIntegratedAssessmentModels.”Energy172,1254–67.Malerba,Daniele,andJohannesEmmerling.2022.“ModellingtheInteractionBetweenClimateMitigationandIncomeInequality:TheUseofIntegratedAssessmentModelsandtheCaseofIndia.”InAnitaBreuer,DanieleMalerba,SrinivasaSrigiri,andPoojaBalasubramanian,eds.GoverningtheInterlinkagesbetweentheSDGs:Approaches,OpportunitiesandChallenges.Routledge,London.Meinshausen,Malte,JaredLewis,ChristopheMcGlade,JohannesGütschow,ZebedeeNicholls,etal.2022.“RealizationofParisAgreementPledgesMayLimitWarmingJustBelow2°C.”Nature604,304–9.Meinshausen,Malte,NicolaiMeinshausen,WilliamHare,SarahC.B.Raper,KatjaFrieler,etal.2009.“Greenhouse-GasEmissionTargetsforLimitingGlobalWarmingto2°C.”Nature458,1158–62.Meyer,Aubrey.2000.Contraction&Convergence:TheGlobalSolutiontoClimateChange.SchumacherBriefings.UITCambridgeLtd.,Totnes,Devon.Millar,RichardJ.,JanS.Fuglestvedt,PierreFriedlingstein,JoeriRogelj,MichaelJ.Grubb,etal.2017.“EmissionBudgetsandPathwaysConsistentWithLimitingWarmingto1.5°C.”NatureGeoscience10,741–7.Newell,R.,B.Prest,andS.Sexton.2021."TheGDP-TemperatureRelationship:ImplicationsforClimateChangeDamages."JournalofEnvironmentalEconomicsandManagement108.O'Neill,Brian,MaartenvanAalst,ZalinaZaitonIbrahim,LeaBerrangFord,SurruchiBhadwal,etal.2022.KeyRisksAcrossSectorsandRegions.In:ClimateChange2022:Impacts,AdaptationandVulnerability.ContributionofWorkingGroupIItotheSixthAssessmentReportoftheIntergovernmentalPanelonClimateChange[H.-O.Pörtner,D.C.Roberts,M.Tignor,E.S.Poloczanska,K.Mintenbeck,A.Alegría,M.Craig,S.Langsdorf,S.Löschke,V.Möller,A.Okem,B.Rama(eds.)].CambridgeUniversityPress,Cambridge,UKandNewYork,NY,USA,pp.2411–2538,doi:10.1017/9781009325844.025.Pai,Sandeep,JohannesEmmerling,LaurentDrouet,HishamZerriffi,andJessicaJewell.2021.“MeetingWell-Below2°CTargetWouldIncreaseEnergySectorJobsGlobally.”OneEarth4(7),1026–36.Pindyck,RobertS.2017.“TheUseandMisuseofModelsforClimatePolicy.”ReviewofEnvironmentalEconomicsandPolicy11(1),100–14.Pretis,F.,MoritzSchwarz,KevinTang,KarstenHaustein,andMylesR.Allen.2018."UncertainImpactsonEconomicGrowthWhenStabilizingGlobalTemperaturesat1.5°Cor2°CWarming."PhilosophicalTransactionsoftheRoyalSocietyA.Rao,Shilpa,ZbigniewKlimont,StevenJ.Smith,RitaVanDingenen,FrankDentener,etal.2017.“FutureAirPollutionintheSharedSocio-EconomicPathways.”GlobalEnvironmentalChange42,346–58.53Reis,LaraAleluia,LaurentDrouet,RitavanDingenen,andJohannesEmmerling.2018.“FutureGlobalAirQualityIndicesunderDifferentSocioeconomicandClimateAssumptions.”Sustainability10(10),3645.Reis,LaraAleluia,LaurentDrouet,andMassimoTavoni.2022.“InternalisingHealth-EconomicImpactsofAirPollutionintoClimatePolicy:AGlobalModellingStudy.”TheLancetPlanetaryHealth6(1),e40–8.Riahi,Keywan,DetlefP.vanVuuren,ElmarKriegler,JaeEdmonds,BrianC.O’Neill,etal.2017."TheSharedSocioeconomicPathwaysandTheirEnergy,LandUse,andGreenhouseGasEmissionsImplications:AnOverview."GlobalEnvironmentalChange42.Riahi,Keywan,ChristophBertram,DanielHuppmann,JoeriRogelj,ValentinaBosetti,etal.2021."CostandAttainabilityofMeetingStringentClimateTargetswithoutOvershoot."NatureClimateChange11Robinson,LisaA.,JamesK.Hammitt,andLucyO’Keeffe.2019.“ValuingMortalityRiskReductionsinGlobalBenefit-CostAnalysis.”JournalofBenefit-CostAnalysis10(S1),15–50.Rogelj,Joeri,AlexanderPopp,KatherineV.Calvin,GunnarLuderer,JohannesEmmerling,etal.2018.“ScenariosTowardsLimitingGlobalMeanTemperatureIncreaseBelow1.5°C.”NatureClimateChange8,325–32.Stern,Nicholas,JosephStiglitz,andCharlotteTaylor.2022.“TheEconomicsofImmenseRisk,UrgentActionandRadicalChange:TowardsNewApproachestotheEconomicsofClimateChange.”JournalofEconomicMethodology29(3),181–216.UNFCCC.2021.TechnologyframeworkunderArticle10,paragraph4,oftheParisAgreementhttps://unfccc.int/documents/187440(accessed28September2022).UnitedNationsFrameworkConventiononClimateChange.vanderWijst,Kaj-Ivar,FrancescoBosello,ShouroDasgupta,LaurentDrouet,JohannesEmmerling,etal.2023.“NewDamageCurvesandMultimodelAnalysisSuggestLowerOptimalTemperature.”NatureClimateChange13,434–41.VanDingenen,Rita,FrankDentener,MonicaCrippa,JoanaLeitao,ElinaMarmer,ShilpaRao,EfisioSolazzo,andLuanaValentini.2018.“TM5-FASST:AGlobalAtmosphericSource–ReceptorModelforRapidImpactAnalysisofEmissionChangesonAirQualityandShort-LivedClimatePollutants.”AtmosphericChemistryandPhysics18(21),16173–211.Weyant,John.2017.“SomeContributionsofIntegratedAssessmentModelsofGlobalClimateChange.”ReviewofEnvironmentalEconomicsandPolicy11(1),115–37.AssessingtheImplicationsofaGlobalNet-ZeroTransitionforDevelopingAsiaInsightsfromIntegratedAssessmentModelingGlobalclimategoalswillnotbeattainableunlessAsia’sgrowthbecomesmuchlesscarbon-intensive.ThispaperusesaglobalintegratedassessmentmodeltoassesshowdevelopingAsiawoulddevelopinaworldthatmeetsParisAgreementtemperaturegoals.Itfindsthataprofoundtransitionisneeded,witharapidlydecarbonizedpowersectorandadramaticdropinland-useemissions.BenefitsarefoundtobefarinexcessofcostsforAsiaifanefficientsetofdecarbonizationpoliciesisdeployed.AbouttheAsianDevelopmentBankADBiscommittedtoachievingaprosperous,inclusive,resilient,andsustainableAsiaandthePacific,whilesustainingitseffortstoeradicateextremepoverty.Establishedin1966,itisownedby68members—49fromtheregion.Itsmaininstrumentsforhelpingitsdevelopingmembercountriesarepolicydialogue,loans,equityinvestments,guarantees,grants,andtechnicalassistance.ASIANDEVELOPMENTBANK6ADBAvenue,MandaluyongCity1550MetroManila,Philippineswww.adb.org

1、当您付费下载文档后，您只拥有了使用权限，并不意味着购买了版权，文档只能用于自身使用，不得用于其他商业用途（如 [转卖]进行直接盈利或[编辑后售卖]进行间接盈利）。
2、本站所有内容均由合作方或网友上传，本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺！文档内容仅供研究参考，付费前请自行鉴别。
3、如文档内容存在违规，或者侵犯商业秘密、侵犯著作权等，请点击“违规举报”。

碎片内容

碳中和的最新文档