2025年人工智能的环境影响研究报告（英文版）-绿色和平

ENVIRONMENTALIMPACTSOF

ARTIFICIALINTELLIGENCE

greenpeace.de

EnvironmentalImpactsofArtificialIntelligence

Authors

JensGröger

FelixBehrens

PeterGailhoferIngaHilbert

⃞oko-Institut

Öko-InstitutConsultGmbH

Borkumstraße2

13189Berlin

KeinGeldvonIndustrieundStaat

GreenpeacearbeitetinternationalundkämpftmitgewaltfreienAktionenfürdenSchutzderLebensgrundlagen.UnserZielistes,Umweltzerstörungzuverhindern,VerhaltensweisenzuändernundLösungendurchzusetzen.GreenpeaceistüberparteilichundvölligunabhängigvonPolitikund

Wirtschaft.Rund620.000FördermitgliederinDeutschlandspendenan

GreenpeaceundgewährleistendamitunseretäglicheArbeitzumSchutzderUmwelt,derVölkerverständigungunddesFriedens.

Impressum

Greenpeacee.V.Hongkongstraße10,20457Hamburg,T04030618-0PressestelleT04030618-340,F04030618-340,presse@greenpeace.de,greenpeace.dePolitischeVertretungBerlinMarienstraße19一20,10117Berlin,T030308899-0V.i.S.d.P.JonathanNieselTitelfoto©SamuelGolay/pictureallianceStand05/2025

Foreword

ArtificialIntelligence(AI)isomnipresentandtransformingtheworld.TheincreasinguseofAInotonlybringsprogress—italsointroducesnewenvironmentalchallenges.

Severalexamplesillustratethecurrentdynamic:

▶AImodelsarebecominglarger,morecomplex,andmoreenergy-hungry.

▷Thenumberofparametershasrisenfrom1.5billion(

GPT-2,2019

)to2trillion(

LLama4,2025

).

▷Thecomputationaleffortrequiredfortrainingdoublesapproximatelyeveryfivemonths.[EpochAI]

▶TheglobalelectricitydemandforAIcomputingisexpectedtobeabout11timeshigherin2030thanin

2023.[EnvironmentalImpactsofAI,Öko-Institut2025]

▶IntheU.S.,datacenterscouldconsumemoreelectricityby2030thantheentireenergy-intensivegoodsproductionsector(cement,chemicals,steel)combined.[InternationalEnergyAgency(IEA)]

Greenpeacehasbeenadvocatingforamoreenvironmentallyfriendlyinternetanddatacenterinfrastructureforyears(e.g.,benchmarkingtheenergyperformanceoftheITsectorin2009;

ClickingClean:Whoiswinningthe

racetobuildagreeninternetin2017

).

Butthosesuccessesarebeingundone:insteadofdecreasingemissionsfromGoogle,Microsoft,andAWS,the

companiesarereportingincreasingemissionsoronlyincompletedataonenvironmentalimpact.Atthesame

time,theyareheavilyinvestinginAIinfrastructuretosecuremarketshareandfutureprofits.Itremainsunclearwhetherandhowthisalignswiththeirself-imposedclimategoals.

AIcanbeausefultechnology,butitsnegativeenvironmentalimpactsmustbelimited.Greenpeacedoesnotfun-damentallyrejectAIbutemphasizestheurgencyoftakingactionnowtoensureAIdoesnotfurtherexacerbatetheclimatecrisis.

Thisreportpresents,forthefirsttime,acomprehensiveoverviewofAI’senvironmentalimpacts.Itisintendedasafact-based,scientificfoundationfordiscussion—oneonwhichwecancollectivelysearchforsolutionsandscaleenvironmentallysustainableapproaches.WhileAIclearlyhasmanysocialandsocietalopportunitiesandrisks,thisreportfocusesspecificallyonitsecologicalimpact.

ThereportbyGreenpeaceEastAsia

showsthatacceleratingthedeploymentofrenewableenergyispossiblewithinthechipproductionsupplychain.

Thereisalsogreatpotentialforimprovedenergyefficiencythrough"GreenAI"policiesincompanies—forexam-ple,bychoosingsmallermodels,usingpre-trainedmodels,andprovidingtrainingingreencoding.

Evenwithenergy-efficientalgorithms,electricityconsumptionfromAIapplicationswillcontinuetoriseas

morepeopleuseAIinboththeirprofessionalandprivatelives.AsofApril2025,ChatGPTusagesetanewglobalrecord,doublingto5.1billionvisitswithinayear.[Statista]

Technologicaladvancesalonewillnoteliminatetheenvironmentalimpactscausedbytechnology:efficiencygainsreducecosts,whichthenincreasesusageandoffsetsthesavings.Thisisknownasthereboundeffect,orJevonsparadox.

Therefore,avoidingenvironmentallyharmfulAIusecasesmustalsobepartofthesolution.Forinstance,itisnotdesirableforAIapplicationstolowerthecostofoilextraction,therebyincreasingfossilfuelconsumption.

GRNPAceENVIRONMENTALIMPACTSOFARTIFICIALINTELLIGENCE

GRNPAceENVIRONMENTALIMPACTSOFARTIFICIALINTELLIGENCE4

GreenpeacecallsforthefollowingmeasurestominimizetheenvironmentalimpactsofArtificialIntelligence:

1.Anenergy-efficientAIinfrastructurepowered100%byrenewableenergy.Thisgreenpowermustbeadditionallygenerated.

2.AIcompaniesmustdisclose:

a.HowmuchelectricityisusedinoperatingtheirAI.

b.HowmuchpowerisconsumedbyusersduringtheiruseofAI.

c.Thegoalsunderwhichtheirmodelsweretrained,andwhichenvironmentalparameterswereconsidered.

3.AIdevelopersmusttakeresponsibilityfortheirsupplychains.Theymustcontributetotheexpansionofrenewableenergyinlinewiththeirgrowthandensurethatlocalcommunitiesdonotsuffernegativeconsequences(e.g.,lackofdrinkingwater,higherelectricityprices).

Thislastpointisespeciallycriticalrightnow,asUNSecretary-GeneralAntónioGuterresemphasizedatthe2025AISummitinParis:

"ThepowerofAIcarriesimmenseresponsibilities.Today,thatpowersitsinthehandsofafew."

GreenpeaceviewsitcriticallythatAIiscurrentlydominatedbythesamelargetechcorporationsthatalso

controlmostsocialmediaplatforms—leadingtomediamonopoliesandknownissuessuchassocialpolarization,hatespeech,andfakenews.Thismarketpowermustbelimited,andEUdigitallegislationmustbeenforced.

TherearesolutionsthatcanmaketheenvironmentalimpactsofAIapplicationsmeasurable(e.g.,

AIEnergy

Score

,

GreenAlgorithms

).Germany’sEnergyEfficiencyActalreadyincludesbasicmeasuresthatmustbe

implementedswiftlyandcomprehensively(e.g.,mandatoryuseofwasteheat).

Itisimportanttofindinterdisciplinarysolutions,implementthemwithinorganizations,andstrengthenapproa-chesfocusedonthecommongood.Ifwesucceed,AIhasthepotentialtoacceleratesustainabledevelopment.

KarenPaul,GreenpeaceExpertforDigitalTransformation

JonathanNiesel,GreenpeaceExpertforArtificialIntelligence

GRNPAceENVIRONMENTALIMPACTSOFARTIFICIALINTELLIGENCE5

ExecutiveSummary

ArtificialIntelligenceisalreadyanintegralpartofmanyareasoflife–whetherit’spopularapplicationslikeChatGPTortheoptimizationofindustrialprocesses.Butthisprogresscomesatacost:Theinfrastructure

behindAIconsumesvastresources–especiallyenergy,butalsowaterandrawmaterialssuchasrareearths.

Thisreport,preparedbytheÖko-InstitutonbehalfofGreenpeaceGermany,providesthefirstcomprehensiveoverviewoftheenvironmentalimpactsofartificialintelligence–andprovidesguidelinesforsustainableAI.

Theauthorsevaluatedmorethan95studiesonthetopic,condensingalotoftheavailableliteratureinasinglereport.AIisheretostay–andwemustfindawaytouseitinaclimate-andenvironmentallyresponsible

manner.

ThefirstpartofthereportoutlinestheeconomictrajectoryofAIandexaminesthekeyplayersinthisrapidly

growingsector.TechgiantslikeGoogle,Microsoft,Amazon,AppleandMetaareinvestingbillionsinto

expandingtheirAI-poweredproductportfolios.Thisdevelopmentprimarilyaffectsthedatacentremarket:TheyarebuildingnewAI-specificdatacentresandcustomisedAIhardwareonalargescale.Accordingly,theshare

ofspecialisedAIhardwareintheenergyconsumptionofdatacentres(excludingcryptocurrencies)willgrow

fromanestimated14%in2023to47%by2030.Thenewlybuilt,so-calledhyperscaledatacentreshaveelectricalconnectioncapacitiesofseveralhundredmegawattsandoccupyfloorspaceofupto4squarekilometres.

ThesecondandmostcomprehensivesectionofthereportfocusesonAI’senvironmentalimpacts–particularlyregardingenergyconsumption,greenhousegasemissionsandwateruse.Electricityconsumptionisprojectedtotriplewithinjustsevenyears.By2030,thepowerdemandofAIdatacentersisexpectedtobeeleventimeshigherthanitwasin2023.Atthatpoint,AIdatacenterswillrequireasmuchelectricityasconventionaldatacenters

dotoday.Inshort,AIisnotonlyenergy-intensiveinitself–itisakeydriverofenergydemandintheentiredatainfrastructuresector.Despitetheassumptionofacarbon-neutralelectricitysupplyby2040,CO₂emissionsareprojectedtorise.Withinjustfiveyears,AIisexpectedtodominateoverallcomputingdemand.Theadditionalelectricityrequiredwillprolongtheoperationoffossilfuelpowerplants,puttingclimatetargetsatrisk.

InIreland,datacentresalreadyaccountformorethan20%oftotalnationalelectricityconsumption,andinthecapitalDublin,almost80%.Figuresbetween30%and40%canbefoundincitieslikeAmsterdam,LondonorFrankfurt/Main.Thesedevelopmentsarepushinglocalgridstotheirlimits,promptinggovernments–asinIreland–tointroduceregulationsontheexpansionofnewdatacentres.

AI’senvironmentalfootprintgoesbeyondenergy.Coolingdatacentresrequireslargequantitiesofwater–

accordingtotheprojectionsmadehere,datacentresworldwideconsumed175billionlitresofwaterin2023.

Waterconsumptionisforecasttomorethantripleby2030(664billionlitresintotal).Thisisparticularly

problematicinwater-scarceregions.Inaddition,indirectwateruseassociatedwithpowergenerationandchipmanufacturingfurthercompoundstheissue.TheproductionofAI-specificchipsisespeciallywater-intensiveandisoftenlocatedinecologicallyvulnerableareas.E-Wasteisanotherproblemthereportaddresses:Largequantitiesofupto5milliontonnesofadditionalelectronicwastewillbegeneratedbytheexpansionofdata

centresandAIcapacitiesuntil2030.

Thereportalsoaddressestheincreasingrelianceonnuclearenergybymajortechfirms.Google,Amazon/

AWS,MicrosoftandMetaareamongthesignatoriesoftheEUClimateNeutralDataCentrePact(CNDCP),whichcommitsthemtobecomingclimateneutralby2030.Inanattempttomeettheirmassiveelectricityneedswhileclaimingtobe"climateneutral,"thesecompaniesareinvestinginnuclearpowerplantsandSmallModular

Reactors(SMRs).However,thereportwarnsofthesignificantandwell-establishedenvironmentalandsafetyrisksofsuchtechnologies–includingradioactivewaste,highwateruse,andunresolvedstorageproblems.

GRNPAceENVIRONMENTALIMPACTSOFARTIFICIALINTELLIGENCE6

Beyondthesedirectimpacts,thereportexploresthesystemicandindirecteffectsofAI–suchasrebound

effects,whereefficiencygainsleadtohigheroverallresourceconsumption,andincreasedconsumerism

throughalgorithmicrecommendationsystems.Theseeffectsoftenamplifyratherthanmitigateenvironmentalpressures.Theauthorsarguethatthesebroaderdynamicsdeservegreaterscrutinyinsustainabilitydebates.

ToalignAIwithsustainabilitygoals,thereportproposesafive-pointframework:AIshouldonlybeusedwhenitsenvironmentalbenefitsoutweighitsimpacts;simpleralternativesshouldbepreferred;leanmodelsmustmeetrealperformanceneeds;efficiencyinsoftware,dataandhardwareuseshouldbecontinuouslyimproved;and

transparencyaroundenvironmentaleffectsmustbeensured.TheseprinciplesaimtominimiseAI’sresourcefootprintandmaximiseitscontributiontosustainability.

Finally,thereportoffersconcretepolicyrecommendations.ToreduceAI’senvironmentalfootprint,thereportcallsforclearpolicyaction:mandatoryreportingonenergy,waterandefficiencymetrics;efficiencylabels

fordatacentresandAIservices;betterintegrationwithrenewableenergyandlocalheatingnetworks;and

legalframeworksthatgobeyondhumansafetytoalsoaddressenvironmentalrisks.Onlywithclearregulatoryframeworks,internationalcoordinationandasustainability-driventechnologicalagendacanAIcontributetosolvingenvironmentalchallenges–ratherthanintensifyingthem.

EnvironmentalImpactsofArtificialIntelligence

EvaluationofcurrenttrendsandcompilationofanoverviewstudyforGreenpeacee.V.,Hamburg

Berlin,12.05.2025

Authors:JensGröger,FelixBehrens,PeterGailhofer,IngaHilbert

⃞oko-lnstitut

Oeko-InstitutConsultGmbH

info@oeko-consult.deoeko-consult.de

OfficeFreiburg

MerzhauserStraße17379100Freiburg

Phone+4976145295-0

OfficeBerlin

Borkumstraße213189Berlin

Phone+4930405085-0

OfficeDarmstadt

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64295Darmstadt

Phone+4961518191-0

Acknowledgementsandeditorialnotes

WewouldliketothanktheexternalexpertsinparticularSashaLuccioni,ShaoleiRen,AlexdeVriesand

ChristophPistnerwhocriticallyreviewedthisstudyandprovideduswithvaluablesuggestionsforimprovingthetext.

WewouldalsoliketothanktheGreenpeaceteamKarenPaul,JonathanNiesel,ManfredSantenandJoergFeddern,whocommissionedthisstudy,thoroughlyreviewedtheindividualpassages,andcontributedtheirfeedbacktomakethestudymorecomprehensiveandvaluableforreaders.

Finally,wewouldliketothanktheartificialintelligenceforsupportingusinourwork:Thepreparationofthisreportinvolvedtheuseoflargelanguagemodel(LLM)basedassistants(Claude,ChatGPT,DeepL)for

informationretrieval,summarization,translations,andlinguisticenhancementpurposes.Theenvironmentalimpactofthesespecificapplicationscannotbequantifiedunfortunately,astheprovidersdonotofferany

transparencyinthisregard.

EnvironmentalImpactsofArtificialIntelligence⃞ckolnstitut

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TableofContents

ListofFigures4

ListofTables4

ListofAbbreviations5

Summary6

1Currenttrendsindigitalinfrastructures8

1.1Generaltrendsindigitalinfrastructures8

1.2AIbusinessmodelsandthecompaniesbehind8

1.3Trendsinthedatacentremarket12

2Environmentalimpacts14

2.1Energy14

2.2Water22

2.3Resources27

2.4Indirectenvironmentalimpacts30

3Self-declarationsoftechcompanies34

3.1Sustainabilitypledges34

3.2Analysisofsustainabilityreports34

4Sustainableartificialintelligence37

5Policyoptions38

5.1TransparencyaboutenvironmentalimpactsofdatacentresandAIservices39

5.2Betterintegrationofdatacentresintoenergygrids39

5.3IncreasingtheenergyandresourceefficiencyofAIapplications40

5.4Adaptingthelegalframeworkconditions41

ListofReferences43

⃞okolnstitutEnvironmentalImpactsofArtificialIntelligence

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ListofFigures

Figure1-1:Digitalsupplychain,withandwithoutAI9

Figure1-2:ShareofAIspecifictototalglobaldatacentreelectricityconsumption12

Figure2-1:FutureScenarioofglobaldatacentre(DC)electricityconsumption15

Figure2-2:Estimatedshareofelectricityconsumptionofdatacentrestothetotalelectricity

consumptionintherespectiveregionin202316

Figure2-3:Estimatedgreenhousegasemissionsfromdatacentres(2023-2030)bygeographical

region19

Figure2-4:Estimatedgreenhousegasemissionsfromdatacentres(2023-2030)bytype20

Figure2-5:AverageWaterUsageEffectivenessintheUSfordifferentdatacentresizes24

Figure2-6:Estimatedglobalwaterconsumptionbydatacentres24

Figure2-7:Waterconsumptionofvariouspowergenerationtechnologies(includingmanufacturing

effortsandlossesduringoperation)26

ListofTables

Table1.Selectionofthelargesttechcompaniesintheyear2023sortedbyForbeslistNo.10

Table2:Ratiobetweenwaterlossesinpowergenerationtodirectlossesindatacentres27

Table3:Groupedbillofmaterialofastandardserver27

Table4:Estimatedrawmaterialsboundinglobalserveranddatastorageinventoryin202329

EnvironmentalImpactsofArtificialIntelligence⃞ckolnstitut

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ListofAbbreviations

AI

ArtificialIntelligence

AV

Autonomousvehicle

CAGR

CompoundAnnualGrowthRate.Definedastheratioofthevalueofthenextyeartothevalueofthecurrentyearminusone.

CNDCP

ClimateNeutralDataCentrePact

CRM

CriticalRawMaterial

CSR

CorporateSustainabilityReport

DC

DataCentre

ERF

EnergyReuseFactor,definedinEN50600-4-6astheratioofthereusedthermalenergytothetotaldischargedenergy.Theratiodescribesthereuseofwasteheat.

GPU

GraphicProcessingUnit

IoT

InternetofThings

IT

InformationTechnology

kgCO2e

Kilogramcarbondioxideequivalents

kWh

Kilowatthours=103watthours

LLM

LargeLanguageModel

PUE

PowerUsageEffectiveness,definedinEN50600-4-2astheratiooftheenergyconsumptionoftheentiredatacentreandtheenergyconsumptionoftheIT

RE

RenewableEnergy

REE

RareEarthElements

REF

RenewableEnergyFactor,definedinEN50600-4-3astheshareofrenewableen-ergyinthetotalenergyconsumptionofadatacentre

SMR

SmallModularReactor

SRM

StrategicRawMaterial

TPU

TensorProcessingUnit

TWh

Terawatthours,1TWh=1billionkilowatthours=1012watthours

WUEWaterUsageEffectiveness,definedinEN60500-4-9asaratioofthewatercon-

sumptionofadatacentreandtheenergyconsumptionoftheIT

⃞okolnstitutEnvironmentalImpactsofArtificialIntelligence

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Summary

Thisreportdescribestheenvironmentalimpactsofartificialintelligence,inparticularthroughthedigitalinfrastructuresrequiredforitstrainingandoperationandtheassociatedenergyconsumption,greenhousegasemissions,waterconsumption,resourcerequirementsandelectronicwastegener-ation.Inaddition,theso-calledindirectandsystemiceffectsofAIusearedescribedanecdotally.

Around100literaturesourcesandpublicationswereevaluatedandsummarisedforthispurpose.Eventhoughnoprimarydatawascollected,andnocomplexcalculationmodelsweredeveloped,thereportstillprovidesacomprehensiveoverviewoftheproblemsassociatedwiththeincreasinguseofdatacentresingeneralandAI-specificdatacentresinparticular.Althoughsomeofthecom-pileddataareonlyroughestimates,importantguidelinesforactionandpolicyrecommendationscanalreadybederivedfromthem.

Currenttrendsindigitalinfrastructures

Theincreasinguseofartificialintelligenceisdrivingtheexpansionofdigitalinfrastructures.Largetechnologycompaniesareinvestingheavilyinthistrend.Amazon,Microsoft,Google,AppleandMetahaveannouncedmulti-yearAIinvestmentcommitmentsintherangeofseveralhundredbillionUSdollars.ThesecompaniesarebuildingnewAI-specificdatacentresandcustomisedAIhardwareonalargescale.Accordingly,theshareofspecialisedAIhardwareintheenergyconsumptionofdatacentres(excludingcryptocurrencies)willgrowfromanestimated14%in2023to47%by2030.Thenewlybuilt,so-calledhyperscaledatacentreshaveelectricalconnectioncapacitiesofseveralhundredmegawattsandoccupyfloorspaceofupto4squarekilometres.

Environmentalimpacts

AIandthegrowthofdatacentresareleadingtoaverysharpincreaseinenergyconsumption.Theglobalelectricitydemandofdatacentres(includingcryptocurrencies)wasaround487TWhin2023andisforecastedtogrowatacompoundannualgrowthrate(CAGR)of16%onaverage.By2030,electricityconsumptionisestimatedtoreach1,389TWhaboutthreetimesthe2023figure.EvenaconservativeCAGRof12%resultsinapproximately1,093TWhby2030,andahigh-growthsce-narioof20%reacheselectricityconsumptionof1,766TWh.ThemaindriverisAI-specificdatapro-cessing:datacentreconsumptionforAItaskswillrisefrom50TWh(2023)to554TWhin2030,representingan11-foldincreasein7years.

Thesetrendswillleadtoarapidincreaseingreenhousegasemissions.GlobalCO:equivalentemissionsfromdatacentreswillrisefromaround212milliontonnes(Mt)in2023to355Mtin2030.Here,too,theincreaseisparticularlypronouncedinAI-specificdatacentres,withemissionsincreas-ingsixfoldfrom29Mtin2023to166Mtin2030.AI-specificinfrastructurewillhaveovertakentheemissionsoftraditionaldatacentresby2030.

Datacentresalsorequireenormousamountsofwaterforcooling.Accordingtotheprojectionsmadehere,datacentresworldwideconsumed175billionlitresofwaterin2023.Waterconsumptionisestimatedtomorethantripleby2030(664billionlitresintotal).AI-specialiseddatacentrescontributethemosttothis:theirwaterconsumptionwillrisefromaround30to338billionlitres.Theaveragewaterusagerate(litresperkWh)willincreasefrom0.36l/kWh(2023)to0.48l/kWh(2030)duetothehigherpowerdensitiesofAIdatacentres.

Intermsofthematerialfootprintofdatacentres,thestudyusesroughcalculationstodeterminethatthisissignificant(including920kilotonsofiron/steeland200ktofothermetals,aswellascritical,strategicorconflict-relatedrawmaterialsamountingtoaround100kt)butoverallonlyplaysaminorrolecomparedtoglobalproductionvolumes.Moreproblematic,however,arethelarge

EnvironmentalImpactsofArtificialIntelligence⃞ckolnstitut

7

quantitiesofupto5milliontonnesofadditionalelectronicwastethatwillbegeneratedbytheexpan-sionofdatacentresandAIcapacitiesuntil2030.

Self-declarationsoftechcompanies

LeadingtechnologycompaniespresenttheirdatacentrebusinessandAIservicesas‘green’,buttheirlatestreportsshowanabsoluteincreaseinemissions.Google,Amazon/AWS,MicrosoftandMetaareamongthesignatoriesoftheEUClimateNeutralDataCentrePact(CNDCP),whichcom-mitsthemtobecomingclimateneutralby2030.Thecompanieshaveleftthemselvesaloopholebydefiningnuclearenergyas‘cleanenergy’,whichtheyintendtousetocovertheiradditionalelectricityrequirementswithoutfailingtomeettheirclimatecommitments.Thestudyexplainswhynuclearen-ergyisneither‘clean’norclimate-friendly.

CorporateCSRreportsoftenlacktransparencyanddisclosureofabsolutefigures.Forexample,totalenergyandwaterconsumptiongenerallyincreasesevenwhentheefficiencyofdigitalinfra-structuresimproves.Whenitcomestotheuseofrenewableenergies,companieshavesofarfailedtopurchaseorgeneratetheappropriateamountsofenergytomatchtheirhourlyconsumption.

Sustainableartificialintelligence

SustainableAIinvolvesthedevelopmentanduseofAIwithexplicitenvironmentalandsocialgoals.Basedonexistingframeworks,afive-pointplanisoutlinedthatcanbeusedtoassessthesustaina-bilityofAIprojects.First,AIprojectsshouldhavedefinedsustainabilitygoalsandonlybecarriedoutiftheecologicalbenefitsjustifytheirenvironmentalimpact.Second,developersmustquestionthenecessityof