bcg -量子技术能否破解能源转型中最棘手的难题 What If Quantum Could Crack the Energy Transitions Toughest Problems

BCG

Institute

WhatIfQuantumCould

CracktheEnergyTransition’sToughestProblems?

September2026

ByMauriceBerns,MattLangione,JensBurchardt,Jean-FrancoisBobier,EndureMcTier,HanlPark,andEdenCottee-Jones

BCGInstituteisBostonConsultingGroup’sreal-worldthink

tank.Weresearchthefutureofthinkingaboutthefuture.BuiltonBCG’sdecades-longintellectuallegacyandaglobalnetworkofacademics,scientists,andinstitutionalpartners,webring

togetherexpertiseacrossdisciplinestoadvanceideasbefore

theybecomeconventionalwisdom.Trackingtheforces

reshapingbusiness,technology,economics,andgeopolitics,weturnemergingpatternsintoclarity,helpingleadersaroundtheworldturnearlyinsightintomeasurableoutcomes.

Thisarticleispartofaseriesofpublicationsexploringhownext-generationtechnologiescouldacceleratetheenergytransitioniftheyreachtheirfullpotential.

Introduction

Throughoutthepastdecade,massivetechnologicalbreakthroughs,alongwithdramaticdeclinesinthecostofrenewablesand

batteries,haveacceleratedtheenergytransitionglobally.But

despiteallthisprogress,cost-competitivegreenmoleculesandsolutionsformanyareasofindustrialdecarbonizationremainoutofreach.Quantumcomputingcouldchangethat.

Weestimatethatquantumcomputingcouldeventuallyunlock3to7gigatons(Gt)ofannualemissionssavings.Atthe

midpointofthatrange—roughly5Gt—thesavingswouldbeequivalenttonearlyatenthofglobalemissions.Mostofthatpotentiaisconcentratedinhard-to-abatesectors,suchassteel,cement,chemicals,trucking,aviation,andshipping,wherefeweconomicsolutionsexisttoday.

Butcomputationalbreakthroughsdonottranslateimmediatelyintoemissionsreductions.Companiesmuststillcommercializeanddeployquantum-enabledsolutionsacrossindustrial

assets,someofwhichcanoperatefor20to40years.Assumingnormalasset-replacementcycles,weestimatethatonlyabout

10%to15%ofquantumcomputing'sfullemissions-savings

potentialcouldberealizedby2040.Forbusinessleadersand

investors,however,longdeploymentcyclesmakequantumrelevantlongbeforethetechnologyreachesmaturity.Capitalplansandinvestmentdecisionsmadetodaycoulddeterminehowswiftlycompaniescanadoptquantum-enabled

technologiesastheybecomecommerciallyviable.

TherapidgrowthofAlhasdemonstratedhowquicklya

computingbreakthroughcancreatenewdemandsonthe

energysystem.Ouranalysissuggeststhatquantumcould

followaverydifferenttrajectory,generatingarelativelysmallcarbonfootprintevenasitsapplicatonsscale.

Ifquantum-enabledadvancesinmaterials,chemistry,and

industrialprocessesreachcommercialscale,theimplications

couldextendfarbeyondtheemissionssavings.Theycould

fundamentallychangepartsoftheenergysystemandbroadereconomy—electricitygenerationandstorage,foodproduction,andcarbonremoval.Wehaveidentifiedthreewaysthat

quantumcouldacceleratetheenergytransitionoverthelong

term,andwehavenotedseveralkeydecisionsthatbusinessesandinvestorscanmaketodaytoprepareforthoseopportunities.

WHATIFQUANTUMCOULDCRACKTHEENERGYTRANSITION'STOUGHESTPROBLEMS?(

QuantumComputingCouldScaleWithoutanAI-Sized

CarbonFootprint

TheenergydemandsofAIareacentralconcernforbusinessesandpolicymakers,andit’simportanttoknowwhether

quantumcomputingcouldcreateasimilarchallengeasitscales.Ouranalysissuggeststhatitisunlikelytodoso.

(Seetheappendix,“OurMethodology.”)

Quantumcomputingitselfconsumessignificantamountsof

energy,butitsoverallemissionsfootprintislikelytoremain

relativelysmall.Ourmodelingindicatesthatquantum

computingwillgenerateapproximately0.09Gtofcarbon

dioxideequivalent(CO2e)in2040,equivalenttolessthan0.2%oftheexpected50Gtofglobalemissionsthatyear.Thiswouldequatetoapproximately7%ofpotential2040datacenter

emissionsatthemidpoint.Theseemissionscomeprimarilyfromone-timemanufacturingprocessesassociatedwith

buildingeachmachine,inadditiontotheongoingenergyrequiredtooperatethefleet.(SeeExhibit1.)

Comparedwithroughly5Gtofpotentialannualemissions

savings,thatlevelofemissionsimpliesaclimatebenefitof

approximately60to1.Thepotentialsavingswouldbe

equivalenttoeliminatingnearly10%ofglobalemissionstodayandroughly90%ofcurrentUSemissions.

Therelativelysmallfootprintisnotanindicationthatquantum

computersthemselvesareenergyefficient.Afull-scalequantumcomputercoulddrawroughly1MWofpower,comparabletotheenergydemandsofasmalldatacenter.ButquantumisunlikelytorequiretheextensiveinfrastructurebuilttosupportAI.More

than11,000datacenters,ranginginoperatingrequirementsfromroughly1MWto100MW,alreadypowerAIandothertypesof

high-performancecomputing,withsomehyperscalefacilities

approaching1GW.Weestimatethatapproximately230to1,400machinescouldserveglobalquantumcomputingdemandby

2040,evenafteraccountingforsparecapacityandmachines

operatedbygovernments,laboratories,anduniversities.That

relativelysmallfleetreflectshowquantumcomputingislikelytobeused:notasawholesalereplacementforclassicalcomputing,butforaspecializedsetofproblemswhereitcanprovidea

computationaladvantage.

Additionalapplicationscouldemergeasthetechnologymatures,increasingdemandbeyondwhatwemodeltoday.Butcurrentlyidentifiableusecasessuggestthattherelativelysmallnumberofmachinesrequiredwilllimitquantum’sdirectemissions,despitethehighpowerconsumptionofeachmachine.

Quantum’sindirectemissionsfromenablingadvancesinoilandgas,AI,orreencryptionarelikelytobelimited,too.Inoilandgas,companiesareexploringearlyapplicationsinareassuchas

discoveryandoptimization,buttheemissionsimpactislikelyto

remainlimited.NordoweexpectquantumtomateriallyincreasegenerativeAIemissions,becauseitsadvantageliesinsolving

differenttypesofproblemsratherthaninmakinggeneral-purposecomputingcheaper.Andwhiletheshifttoquantum-safe

cryptographycouldrequireupgradestoinfrastructuresuchassatellitesandfibernetworks,theassociatedemissionswouldlargelybeone-timeratherthanrecurring.

EXHIBIT1

ComparedwithDataCenters,QuantumIsExpectedtoHaveSignificantlyLowerEmissions

Quantumemissions(GtCO₂e)

0.09

0.07

<0.01

2030

2035Operating

2040Manufacturing

Globalemissions(GtCO₂e)

1.31

0.73

0.45

0.07

0.09

<0.01

2035

2040

2030

QuantumDatacenters1

Source:BCGInstituteanalysis.

1Calculatedasdatacenterelectricityconsumption(TWh)×carbonintensity(gCO₂/kWh).ElectricityconsumptiondatafromBCGanalysis;carbonintensityfromIEA(2024–2026)extrapolatedto2040.Numbersrepresentthemidpointofeachestimatedrange.

4BOSTONCONSULTINGGROUP

WHATIFQUANTUMCOULDCRACKTHEENERGYTRANSITION’STOUGHESTPROBLEMS?5

WhereQuantumCouldUnlockNewPathsto

Decarbonization

Oftheroughly50knownquantumcomputingapplicationsthatweassessed,16couldplausiblyreduceemissions.Insevenof

thosecases—suchassolarphotovoltaiccellsandelectriccars—thesamesavingscouldbeachievedthroughexistingtechnologies,orthesavingswerecausedbyfactorsthatgreatercomputationalpowerwoulddolittletoaddress.Thatleavesnineusecaseswherequantumcouldenableemissionsreductionsthatclassical

computingandAIcannotachievetoday.(SeeExhibit2.)

Thesenineusecasesshareanimportantcharacteristic:theydependonsimulatinghowmoleculesandmaterialsbehaveandinteract.Designingabettercatalyst,batteryelectrode,

orcarbon-capturematerialrequiresaccuratelymodeling

interactionsamongelectrons.Theprocessofaccurately

modelingasmallmoleculewouldtakethousandsofyearsforeventhelargestsupercomputers.

Quantumcomputersaremuchbetteratmodelingcomplexinteractionsattheatomicandmolecularscale.Thiscould

enableresearcherstodiscoveramuchwidersetofcatalysts,sorbents,andcompounds,acceleratingthesearchfor

solutionsthatpossessthepropertiesneededtodecarbonizesomeofthehardest-to-abateindustrialsectors.

Wehavehighlightedthreeapplicationstoillustratetherangeofclimateproblemsthatquantumcouldhelpaddress:

carboncapture,greenhydrogenandammonia,andbatteries.(SeeExhibit3.)

EXHIBIT2

NineHigh-PriorityUseCasesforQuantumComputing

Carboncapture

SorbentsthatcaptureCO₂tightlyyetlooselyenoughforreleasewithouthighheat

Screenscandidatesthat

resembleexistingsorbents

Simulatesgenuinelynewsorbents

1.4

Methanevaccines

Vaccinesthatsuppressmethanogenproductioninlivestock

Modelswell-characterizedenzymes

Simulatesenzymebehaviorsthatdeterminewhethera

vaccinewillwork

0.9

Green

hydrogen

andammonia

Modelssimple,well-understoodcatalysts;hasrecently

managedFeMoco

Simulatesnewcatalysts

beyondFeMoco;enablesarangeofdownstreamuses1

Catalystsformoreefficienthydrogenreactionsandnitrogenfixation

0.9

Modelsincremental

improvementstoexistingmetalalloys/composites

Aviationmaterials

Simulatesnovelhigh-strength,low-weightmaterials

0.04

Lightermaterialsthatreduceairframeweight

Whatclassical

computingdoes

WhatquantumaddsSavings(Gt)

Keyneeds

Usecase

Cement

Binderstoreplaceclinker;productionofthelatterreleasesCO₂

Evaluatesknownclinkersubstitutes

Simulatesnewlow-carbon

bindersthatavoidcalcination

0.8

EVtrucks

Batteriesdenseenoughforlong-hauljourneyswithoutprohibitiveweight

Simulatesestablishedlithium-ionchemistries

Simulateshigher-density,longer-durationstoragechemistries

0.5

Steel

Methodforremovingironfromorewithoutcoal-firedblastfurnaces

Modelsconventionalfurnacechemistry

Simulatesthematerialsbehindmolten-oxideelectrolysis

0.4

Curtailmentreduction

Batteriesthatcanholdsurplusrenewablepowerforlongdurations

Simulatestoday’s

short-durationchemistries

Simulateshigher-density,longer-durationstoragechemistries

0.1

Aluminum

AnodesthatdonotemitCO₂duringsmelting

Modelsthebehaviorof

conventionalcarbonanodes

Simulatesinert,carbon-freeanodechemistries

0.04

Total5.0

Source:BCGInstituteanalysis.

Note:FeMoco=iron-molybdenumcofactor.Becauseofrounding,thesavingsnumberslisteddonotadduptothesumgiven.1Savingsopportunityaccountsforshippingandsteel.

Quantumcomputingpromisestoprovidenewsolutionsfor

mitigatingemissionsin

WHATIFQUANTUMCOULDCRACKTHEENERGYTRANSITION’STOUGHESTPROBLEMS?7

EXHIBIT3

AmongtheUseCasesforQuantum,CarbonCaptureOfferstheGreatestSavingsPotential

Totalquantumemissionssavingspotentialperusecase(GtCO₂e)

Sectoremissions

Emissionssaved

LOW–HIGH

0.6–2.1

0.2–1.6

0.7–1.1

0.5–1.1

0.3–0.6

0.2–0.5

<0.1–0.2

0.03–0.05

0.03–0.05

PERCENTAGE

ADDRESSED(%)1

~13

~18

~23

~34

~21

~15

~1

~16

~3

Usecase

CarboncaptureMethanevaccines

Greenhydrogenandammonia CementElectrictrucks

Steel

Curtailmentreduction

Aluminum

Aviationmaterials

Totalsavingspotential

2040TOTAL

10.5

3.0

3.92

2.4

2.2

2.6

10.5

0.3

1.4

AVERAGE

1.4

0.9

0.9

0.8

0.5

0.4

0.1

0.04

0.04

5.0

2.8–7.238.6~13

Source:BCGInstituteanalysis.

1“Percentageaddressed”istheaverageemissionssaveddividedbytotalsector-levelemissionsin2040.2Includesemissionsfromammoniaproductionanddownstreamapplicationsinshippingandsteel.

CarbonCapture

Carboncapturecanalleviateemissionsthatremaindifficultorexpensivetoeliminateattheirsource,butcostremainsa

majorbarrier.Directaircapture(DAC),forexample,costs

approximately$600to$1,000pertontoday,wellabovethe

roughly$100-per-tonlevelthatexpertsoftenciteasnecessaryforadoptionatscale.

PartofthatcostinvolvesthematerialsusedtocaptureCO₂.

Aneffectivesorbentmustbindstronglyenoughtocapture

carbonbutweaklyenoughtoreleaseitwithoutrequiringlargeamountsofenergy.Classicalcomputerscanscreenknown

candidatematerials,butaccuratelyevaluatingmillionsofnovelandcomplexstructuresbecomesincreasinglydifficult.

Quantumcomputingcouldexpandthesetofmaterialsthat

researcherscanrealisticallyevaluate,enablingmoreaccuratesimulationofhownovelsorbentsinteractwithCO₂without

relyingasheavilyonapproximationsderivedfrompast

examples.Findingmaterialsthatcaptureandreleasecarbonmoreefficientlycouldreducetheenergy—andthereforethecost—requiredforcarboncapture,helpingmakeitviableatmuchgreaterscale.

GreenHydrogenandAmmonia

Ammoniaformsthebasisofsyntheticfertilizersthatfeed

roughlyhalfoftheworld’spopulation,butproducingit

accountsforapproximately1%to2%ofglobalemissions.

Today’sprocessforcreatingammoniareliesonhydrogen

derivedlargelyfromnaturalgas,anditrequiresextreme

temperaturesandpressuretomakethechemicalconversion.

Abettercatalystcouldreducetheenergynecessaryforthatreactionandhelpmakelow-emissionammoniamore

economical.Thechallengeisfindingone.Predictinghowanovelcatalystwillperformrequiresmodelingcomplex

interactionsbetweenitselectronsandnitrogen(N2)

molecules,preciselythetypeofproblemthatbecomesdifficultforclassicalcomputerstosolveasmolecularcomplexityincreases.

8BOSTONCONSULTINGGROUP

Sufficientlycapablequantumcomputerscouldsimulatea

broaderrangeofnovelcatalystsmoreaccurately,helping

researchersidentifypromisingcandidatesbeforesynthesisandtesting.Theresultcouldbeafasterpathtowardlower-cost,

lower-emissionammoniaproduction,supportingfertilizerthatdependslessonfossilfuelsandstrengtheningthecasefor

lower-carbonshippingfuel.Thesesameadvanceswouldalso

makethecatalystsusedtoproducegreenhydrogenmore

efficient,loweringitscost,improvingthebusinesscasefor

hydrogen-basedsteelmaking,andtherebyopeninganother

routetocuttinghard-to-abateemissionsinsteelproduction.

Thelargestgainsfromunlockinggreenhydrogenandammoniacomenotfromlowercarbonproductionitself,butfromthe

downstreamindustriesthattheyhelpdecarbonize.

Batteries

Betterbatteriesarecriticaltoseveralpartsoftheenergy

transition,fromelectrifyinglong-haultruckstostoring

renewableelectricityfortimeswhensupplyexceedsdemand.

Buttoday’sbatteriesfacesignificantchallengesinenergy

storage,lifespan,andcost,whichrestrictstheiruseinsome

applicationswheretheycouldhavethegreatestclimateimpact.

Thecorechallengeistofindtherightcombinationofmaterialsfortheelectrodeandelectrolytes—thecomponentsthat

determinehowmuchenergyabatteryholds,howfastit

charges,andhowlongitlasts.Classicalcomputerscansimulatesimple,well-understoodchemistries,butasmaterialsbecome

morecomplex,themillionsofpotentialconfigurationsbecomeimpracticaltosimulateortestphysically,whichseverelylimitsthenumberofoptionsthatresearcherscanexplore.

Quantumcomputerscanaccuratelysimulatehownovel

electrodesandelectrolytesbehavewithouthavingtophysicallybuildthem.Bydirectingexperimentationtowardthemost

promisingchemistries,quantumcouldacceleratethe

developmentofbatteriesthatstoremoreenergy,costless,

orperformbetter,expandingelectrificationintoapplications

thattoday’sbatteriescannotservepracticallyoreconomically.

WillQuantum’sBenefitsActuallyArriveinTime?

Acrossthenineapplicationsthatweidentified,quantum

computingcouldeventuallyenableapproximately3Gtto7Gt

ofannualemissionssavingsiftheresultingsolutionswerefullydeployed.Butevenifquantumtechnologiesunlockthefull

emissions-reductionopportunity,realizingthatvaluewilldependlargelyonfactorsoutsidequantumitself.Ifcommerciallyviablequantumsolutionsemergearound2035,companieswillstill

needtotranslatethosebreakthroughsintoindustrial-scale

processes,buildorretrofittheinfrastructureneededtoproducethem,anddeploythemacrossexistingassets.

Thatprocesscouldtakedecades,particularlyinhard-to-abatesectorswheremuchofquantum’spotentialisconcentrated.

Steel,cement,chemicals,aluminum,oilandgas,aviation,

shipping,andtruckingarelikelytoaccountforroughly30%ofglobalemissionsin2040,andouranalysissuggeststhat

quantumcouldeventuallyabate20%to40%oftheiremissions.(SeeExhibit4.)

Butmanyofthesesectorsrelyonlong-lived,capital-intensiveassetssuchassteelmills,cementkilns,chemicalplants,andcarbon-capturefacilities,whichmayberefurbishedorreplacedonlyevery20to40years.Asaresult,evenwhenquantum

enablesabettermaterialorprocess,adoptionmayhaveto

waituntilacompanyreplacesorsubstantiallyupgradesthe

underlyingasset.Abreakthroughincementchemistry,for

example,mayhavelittlenear-termimpactonakilnthatwas

rebuiltthepreviousyearandisexpectedtooperateforanother30years.Shorter-livedassetssuchastruckscanadoptnew

technologiesmuchfaster,butthesameprincipleapplies:thepaceofemissionsreductiondependsheavilyonhowquickly

theindustryleveragesthenewtechnologyandhowswiftlytheunderlyingassetbaseturnsover.

Weestimatethatindustriesmayrealizeonlyapproximately10%to15%ofthefullemissions-savingspotentialby2040

undernormalasset-replacementcycles.(SeeExhibit5.)

Quantum’sclimateimpactisthereforelikelytobeheavily

back-weighted,withphysicaldeploymentratherthan

technologicalpotentialdetermininghowrapidlycompaniescancapturetheopportunity.Butour10%to15%estimateisnotaceiling.Acombinationofsufficientlycompelling

economics,governmentmandates,andcoordinatedglobal

industrystandardscouldpushthatfigurehigherby2040.

Subsidiesforindustrialretrofitsandassetreplacementcouldacceleratedeploymentbeyondnormalturnovercycles,andgreaterprioritizationofsolutionssuchasDACcouldcreate

additionalupsidebeyondourmodeledscenario.

Theinvestmentopportunityissimilarlyprimedforchange.

Someofquantum’slargestpotentialbeneficiariescouldbe

steelmakers,cementproducers,chemicalcompanies,and

otherindustrialincumbentsthatcandeploythesesolutionsatscale.Thesecompaniesalreadyownthephysicalassets,

engineeringcapabilities,andoperatinginfrastructurerequiredtoturncomputationalbreakthroughsintoreal-worldemissionsreductions.Investorscouldthereforebackstartupsengagedindevelopingnewtechnologieswhilealsodirectingcapital

towardtheestablishedindustrialcompaniesthatwill

ultimatelydeploythem.Fundingbothinnovatorsanddeployerscouldhelpaccelerateretrofittingandassetreplacement,andadvanceemissionssavingsthatmightotherwisetakedecadestomaterialize.

EXHIBIT4

WHATIFQUANTUMCOULDCRACKTHEENERGYTRANSITION’STOUGHESTPROBLEMS?9

QuantumCouldReduceApproximately1%ofEmissionsby2040,asMostoftheImpactWillComeAfterThatYear

Netemissionsimpact(GtCO2e)

60

40

20

0

~5Gt

–1.3%

2040

13%

~0.1

–12%

~56.4

~6.5

~49.9

~49.3

2040+

87%

~0.7

Quantum’stotal

savingsopportunity,byrealizationtiming

Emissionssaved

Emissionsgenerated

2040,

netofin-year

2040

(STEPS)

2025Baselineemissionsreduction(STEPS)

quantumimpact

Sources:ClimateActionTracker;IEA;BCGInstituteanalysis.

Note:STEPS=StatedPoliciesScenariofromtheIEA.

EXHIBIT5

QuantumComputingHasthePotentialtoMeaningfullyReduceHard-to-AbateSectorEmissions

Selecthard-to-abatesectoremissions(GtCO2e)

4.0

3.0

2.0

1.0

0.0

1.5

1.0

0.8

4.0

0.1

2.8

2.3

2.3

0.2

0.80.7

1.6

1.5

1.41.4

0.5

2.0

1.7

OilandgasIronandsteelHeavy-dutytruckingCementChemicalsShipping

20242040projectionPotentialimpactofquantumcomputingsavings1

Sources:IEA;BCGInstituteanalysis.

Note:Thereispotentialforquantum’soilandgassavingstotargetcoalemissionsaswell.Totalsdependonthetypeoffuelthatpowerplantsuse.1“Potentialimpactofquantumcomputingsavings”isnottime-bound,butratherreflectsfullrun-ratesavings.

Weestimatethatindustriesmayrealizeonlyapproximately10%to15%ofthefullemissions-savingspotentialby2040undernormal

asset-replacementcycles.

WHATIFQUANTUMCOULDCRACKTHEENERGYTRANSITION’STOUGHESTPROBLEMS?11

Businessleaders,investors,andpolicymakersshouldpreparebeforequantumreachescommercialmaturity.Devisingcapitalplans,developingassetreplacementstrategies,making

infrastructureinvestments,andformingtechnology

partnershipstodaycoulddeterminehowquicklycompanies

canputquantum-enabledbreakthroughstoworkoncethey

becomecommerciallyviable.Well-conceivedmandates,

standards,incentives,andtargetedinvestmentcould

determinewhetherquantum-enabledsolutionshelpaccelerateexistingasset-replacementcycles.

ThreeWaysQuantumCouldTransformtheEnergyTransition

Theemissionssavingsthatouranalysisquantifiescaptureonlythedirectimpactofquantum-enabledtechnologies.Ifthese

breakthroughsbecomecommerciallyviableatscale,their

effectscouldextendmuchfurther,changingtheeconomicsoftheenergytransitionandcreatingrippleeffectsacross

industries,economies,andsocieties.

Theseoutcomesarenotinevitable,andsomearefartherfromtoday’srealitythanothers.Butthreeexamplesillustratehow

breakthroughsthatbeginwithaquantumcomputationcouldultimatelytransformenergysystems—andwhydecisions

aboutcapital,infrastructure,andtechnologymadetodaycouldshapewhocapturesthatvalue.

BetterStorageCouldAccelerateGlobalElectrification

IEASTEPSprojectsthatrenewableenergywillgrowfrom

roughly30%ofglobalelectricitygenerationin2024to

approximately60%by2040.Butwindandsolardonotalwaysgenerateelectricitywhenneeded.Whengenerationexceeds

demand,poweriscurtailed;andwhenitfallsshort,gridsoftenrelyonfossilfuelsasbackup.In2024,renewableenergy

curtailmentincreasedbyapproximately55%,reaching4%ofwindand3%ofsolarPVgeneration.

Quantum-enabledadvancesinbatterychemistrycould

alleviatethisproblem.Batteriescapableofstoringenergyforlongerperiodscouldcaptureelectricitythatwouldotherwisebecurtailedandmakeitavailablewhenthegridneedsit,

reducingrelianceonfossil-fuelbackupandstrengtheningthecaseforrenewablestosupplyagreatershareoftheglobal

energymix.Improvementsinbatterycost,energydensity,andtransportabilitycouldexpandaccesstoelectricityinregions

hamperedbythedifficultyoftransportingtoday’sbatteries,bysuboptimalweatherconditionsforrenewables,orby

underdevelopedrenewableinfrastructure.

Businessesandinvestorshaveanopportunitytoinvestin

regionsbestpositionedforrenewablegenerationwhilealsobackingstoragetechnologies,infrastructure,andother

keyenablers.

GreenMoleculesCouldMake

FoodandEnergyMoreAbundant

Foodsecurityandaccesstoelectricityarefundamentalto

humandevelopment,yetbothcanbescarceindeveloping

economies.Syntheticfertilizersupportsfoodproductionfor

roughlyhalfoftheworld’spopulationandhashelpedincreasecropyieldsby30%to50%.Butitsproductiondependsheavilyonnaturalgas,whichexposesfertilizer-importingcountriestofluctuatinggaspricesandsupplyshocks.Studiesshowthat

cropyieldscouldbeprofitablydoublediffertilizersweren’tsoexpensive.Inaddition,hundredsofmillionsofpeoplestilllackaccesstoelectricity.

Quantumcomputingcouldhelpaddressbothchallenges.

Bettercatalystscouldmakegreenammoniamoreeconomical,reducingfertilizerproduction’sdependenceonnaturalgasandsupportinggreateragriculturalproductivityandfoodsecurity.Betterbatteriescouldmakeelectricitycheaperandmore

accessibleinregionswherereliablepoweriscurrentlytoocostlyorimpracticaltoprovide.

Thepotentialresultisadevelopmentbenefitthatextendswellbeyondemissions:greateragriculturalproductivityandfood

security,alongsidewideraccesstoreliablepower.Businesses,investors,andgovernmentscanidentifydevelopingregions

wherecheaperenergyandagriculturalinputswouldhavethegreatestimpactandinvestintheenergyandagricultural

infrastructureneededtodeploythematscale.

AffordableCarbonRemovalCouldCreateaCarbonThermostat

Quantumcomputingisstillyearsawayfromrealizing

itsfullpotential,andthereisnoguaranteethatthescenariosmodeledinourresearchwillmaterialize.Butouranalysis

suggeststhatitssignificancefortheenergytransitioncouldbesubstantial,thankstothenewsolutionsthatitcouldmake

possibleinsectorswhereemissionshavebeenparticularlydifficulttoreduce.

Realizingquantumcomputing’sfullpotentialintheenergy

transitionwillrequireprogressontwofronts.Quantum

technologymustmatureenoughtosolvethecomplex

chemistryandmaterialsproblemsattheheartofthese

applications.Meanwhile,businessesandgovernmentsmustbepreparedtocommercializethosediscoveriesanddeploythemacrosstheindustrialassets,infrastructure,andsupplychains

whereemissionsreductionsactuallyoccur.

Quantummayprovidecomputationalbreakthroughs,butthepaceofclimateimpactwilldependonhowquicklycompaniescanputthoseadvancestowork.Investmentsmadetoday—inquantumcapabilities,infrastructure,andthecompanies

positionedtodeploynewsolutions—coulddeterminehowmuchofquantum’spotentialcomestofruitionandwho

capturesthevaluethatitcreates.

DACremainsexpensive,atroughly$600to$1,000perton,andIEASTEPSprojectsthatDACwillcaptureonlyabout0.2GtofCO2by2040.Bycomparison,theUSEnvironmentalProtectionAgency’sestimateofthesocialcostofcarbon—theestimatedsocietaldamageresultingfromeachadditionaltonof

emissions—wasroughly$200pertonin2023,andtheEPA

expectedittorisetoapproximately$300pertonby2050.

BringingDACcostsclosertothe$100-per-tonleveloftencitedforadoptionatscalecouldmakeremovingatonofcarbon

cheaperthanbearingthe