step initiative - mit-ncer used electronics flows report (final)
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StEP Initiative - MIT-NCER Used Electronics Flows Report (Final)TRANSCRIPT
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QuantitativeCharacterizationofDomesticandTransboundaryFlowsofUsedElectronicsAnalysisofGeneration,Collection,andExportintheUnitedStates
November2013
HuaboDuan,T.ReedMiller,JeremyGregory,RandolphKirchain
JasonLinnell
Undertheumbrellaof:Withfinancialsupportfrom:
Materials Systems Laboratory
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The vision of the StEP Initiative
“To be agents and stewards of change, uniquely leading global
thinking, knowledge, awareness and innovation in the
management and development of environmentally, economically
and ethically sound e-waste resource recovery, re-use and
prevention.”
Formoredetails:www.step‐initiative.org
Disclaimer
ThedesignationsemployedandthepresentationofthematerialinthispublicationdonotimplytheexpressionofanyopinionwhatsoeveronthepartoftheUnitedNationsUniversityandtheUnitedStatesEnvironmentalProtectionAgencyconcerningthelegalstatusofanycountry,territory,cityorareaorofitsauthorities,orconcerningdelimitationofitsfrontiersorboundaries.
Moreover,theviewsexpresseddonotnecessarilyrepresentthedecisionorthestatedpolicyoftheUnitedNationsUniversity,UnitedStatesEnvironmentalProtectionAgencyandSolvingtheE‐wasteProblem(StEP)Initiativeanditsmembersnordoescitingoftradenamesorcommercialprocessesconstituteendorsement.
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TableofContents
Definitions.....................................................................................................................................................8 ExecutiveSummary...............................................................................................................................10 1 Introduction......................................................................................................................................14 1.1 Background.................................................................................................................................14 1.2 ScopeoftheStudy....................................................................................................................15 1.3 OverviewofMethodology.....................................................................................................15 1.3.1 Generationandcollection............................................................................................16 1.3.2 Export....................................................................................................................................17
2 Results.................................................................................................................................................20 2.1 GenerationandCollectionResults....................................................................................20 2.1.1 TVs..........................................................................................................................................20 2.1.2 MobilePhones...................................................................................................................24 2.1.3 Computers...........................................................................................................................26 2.1.4 Monitors...............................................................................................................................29
2.2 ExportResults............................................................................................................................32 2.2.1 TVs..........................................................................................................................................32 2.2.2 MobilePhones...................................................................................................................34 2.2.3 Computers...........................................................................................................................36 2.2.4 Monitors...............................................................................................................................39
3 ComparisonandSummaryoftheFlowsforAllExaminedProducts.......................42 3.1 Generation,CollectionandExportComparison..........................................................42 3.2 ExportSummary.......................................................................................................................44 3.2.1 PotentialofRe‐exportofExportedUsedLaptops.............................................47 3.2.2 ComparisonwithOtherStudy....................................................................................48
4 ConclusionsandRecommendations......................................................................................49 4.1 Conclusions.................................................................................................................................49 4.2 Recommendations....................................................................................................................50
5 References.........................................................................................................................................51 6 Appendices........................................................................................................................................55 6.1 GenerationandCollection....................................................................................................56 6.1.1 MethodologyOverview.................................................................................................56 6.1.1.2.1 Literature‐based.......................................................................................................59 6.1.2 DataandIntermediateResults...................................................................................75
6.2 Export............................................................................................................................................96 6.2.1 MethodologyOverview.................................................................................................96 6.2.2 DataandIntermediateResults.................................................................................119
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ListofTables
Table1:ScopeofProductsinStudy,ExportApproach,andDistinctionofGenerationandCollectionbyOwnerTypes.................................................................................................................................15
Table2:GenerationandCollectionofUsedTVsin2010(Thousandunits)..................................22
Table3:GenerationandCollectionofUsedMobilePhonesin2010(Thousandunits)...........25
Table4:GenerationandCollectionofUsedComputersin2010(Thousandunits)...................28
Table5:GenerationandCollectionofUsedMonitorsin2010(Thousandunit).........................31
Table6:Potentialofre‐exportfrom2010toptendestinationcountriesQuantitiesoflaptopsinthousands.UsedexportsfromUSbasedonUSExportNVEM......................................47
Table7:ComparisonbetweenLiterature‐basedMethodandSurvey‐basedMethodforGenerationandCollection...................................................................................................................................59
Table8:Equationsusedtocalculatemeanpathlengthandmeanpathprobability.................62
Table9:DesignationofFailure,Generation,andCollectionbyDiscardType..............................66
Table10:Business/Public2010ComputerandMonitorScaleFactors..........................................74
Table11:SalesDataSourcesforTVs..............................................................................................................75
Table12:LifespanDataSources.......................................................................................................................77
Table13:ModeledLifespanStageLengths(Years).................................................................................78
Table14:ProbabilityofPathsLeadingtoGeneration(CRTTVs)......................................................79
Table15:MeanProbabilitiesandMeanTotalLifespansof6PathstoGeneration...................80
Table16:StatewideUsedElectronicsCollection(lbs)forThoseStateswithStatisticsin2010.........................................................................................................................................................................................81
Table17:StatewideUsedElectronicsDisposalRate,PercentageofMSWDisposalWeight..82
Table18:2010TVsCollectionApproachesEvaluation..........................................................................83
Table19:2010TVsCollectionRates..............................................................................................................84
Table20:SalesDataSourcesforMobilephone.........................................................................................88
Table21:LifespanDataSources.......................................................................................................................89
Table22:ModeledLifespanStageLengths(Years)................................................................................90
Table23:ProbabilityofPathsLeadingtoGeneration.............................................................................91
Table24:MeanProbabilitiesandMeanTotalLifespansof6PathstoGeneration....................91
Table25:2010MobilePhoneCollectionRates..........................................................................................92
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Table26:SalesDataSourcesforComputersandMonitors..................................................................93
Table27:MeanWeibullDistributionParametersforLengthofPeriodofOwnershipλ.........94
Table28:UnitWeight(kg)DataforComputersandMonitorsfromModelParameters.........96
Table29:Matrixofquantitativeapproachesbyeffortrequiredandinformationqualityyielded.Approachimplementedinthisstudyisinbold........................................................................97
Table30:ComparisonbetweenHSOTDMThresholdsandUSITCLowestX%UnitValues($/unit)......................................................................................................................................................................100
Table31:AttributesofUSExportTradeDatasets..................................................................................102
Table32:DatasetsUtilizedforUSExportsCalculations.Somedatasetsdonotreportquantityorweight.................................................................................................................................................102
Table33:ExportTradeDataSymbolsandTerms..................................................................................103
Table34:TVExportTradeCodesUsedinthisStudy............................................................................104
Table35:MobilePhoneExportTradeCodeusedinthisstudy........................................................104
Table36:ComputerExportTradeCodesUsedinthisStudy.............................................................105
Table37:ExampleApproximatePort‐LevelCalculationsforLaptopexport(FromtheUStoArgentina)(ResultsShaded)............................................................................................................................107
Table38:StatisticsonWorldwideCRTTVsSuppliersBasedonAlibabaB2BPlatform........117
Table39:SummaryandComparisonoftheThresholdsforAllElectronics(unitvalue:$/unit)........................................................................................................................................................................120
Table40:AuctionSalePricesforUsedElectronicsfromVariousSources(unitvalue:$/unit).......................................................................................................................................................................................122
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ListofFigures
Figure1:LifeCycleFlowChartofElectronicProducts...........................................................................16Figure2:Illustrationofexportquantityandunitvalueofdisaggregatedtradedataforagivenworldregion..................................................................................................................................................17Figure3:IllustrationofexportquantityandunitvalueofdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion..............................................................................................................................................................18Figure4:ExampleofChinaExportNVEMhistogramwith$5exportunitvaluefor2010exportoflaptopsfromChinatoLatinAmericaandtheCaribbean(LAC)byvessel..................18Figure5:IllustrationofsumofUsedandNewexportquantitiesfromdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion..................................................................................................................................................19Figure6:SalesofNewTVsandComparisonofGenerationEstimatesofUsedTVs..................20Figure7:GenerationandCollectionofUsedTVsin2010andComparisonwithOtherEstimates.....................................................................................................................................................................21Figure8:QuantityandWeightestimatesofGenerationandCollectionofUsedTVsin2010aComparisonwithEPAEstimates:.................................................................................................................23Figure9:SalesofNewMobilePhoneandComparisonofGenerationEstimatesofUsedMobilePhone.............................................................................................................................................................24Figure10:GenerationandCollectionofUsedMobilePhoneandComparisonwithEPAEstimatesin2010....................................................................................................................................................25Figure11:ResidentialSales,Generation,andCollectionEstimatesofUsedComputers.....26Figure12:GenerationandCollectionofUsedComputersandComparisonwithEPAEstimatesin2010....................................................................................................................................................27Figure13:ResidentialSales,Generation,andCollectionofEstimatesoftheUsedMonitors29Figure14:GenerationandCollectionofUsedMonitorsandComparisonwithEPAEstimatesin2010.........................................................................................................................................................................30Figure15:ExportFlowsofUsedTVsin2010:byTransportMode,DestinationRegion,andIncomeGroupClassificationoftheDestinationRegion.........................................................................32Figure16:FlowsofUsedTVsintheUSin2010........................................................................................33Figure17:ExportofUsedMobilePhonesfromtheUSin2010UsingtheThreeThresholdMethods.......................................................................................................................................................................34Figure18:ExportofUsedMobilePhonein2010:byRegionsandIncomeGroupandModeofTransport....................................................................................................................................................................35Figure19:FlowsofUsedMobilePhonesintheUSin2010..................................................................36Figure20:ExportofUsedComputersfromtheUSin2010UsingtheThreeThresholdMethods.......................................................................................................................................................................36Figure21:ExportofUsedComputersin2010:byRegions,IncomeGroupsandModeofTransport....................................................................................................................................................................37
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Figure22:FlowsofUsedComputersintheUSin2010.........................................................................38Figure23:ExportofUsedFlatPanelMonitorsfromtheUSin2010UsingtheThreeThresholdMethods.................................................................................................................................................39Figure24:ExportFlowofUsedMonitorsin2010:byRegions,IncomeGroupsandModeofTransport....................................................................................................................................................................40Figure25:FlowsofUsedMonitorsintheUSin2010.............................................................................41Figure26:FlowsofUsedElectronicsintheUSin2010.........................................................................42Figure27:WeightofusedproductscollectedintheUSin2010andthefractionofthosecollectedproductsthatweresubsequentlyexported.............................................................................43Figure28:WeightfractionsofUsedElectronicsintheUSin2010...................................................43Figure29:TheFractionofAllUSExportsofElectronicsProductsfromtheUSin2010ThatAreUsedandNew...................................................................................................................................................44Figure30:QuantityFractionsofUSExportFlowsin2010fortheFourUsedElectronicsTypesBrokenDownbyTransportMode,DestinationRegions,andIncomeGroupsClassificationoftheDestinationRegions......................................................................................................45Figure31:Top15ExportDestinationsforEachProductTypein2010.........................................46Figure32:Laptoptradebetweenthetoptendestinationcountriesin2010...............................47Figure33:ComparisonbetweenthisstudyandUSITCreport............................................................48Figure34:Illustrationthatexportedwholeunitsofusedelectronicsareasubsetofcollectedwholeunits,whichareasubsetofgeneratedwholeunits.[Letters]andcolorsrefertoFigure1(repeatedbelowforconvenience)...............................................................................................................56Figure35:Probabilitytreediagramofinformalpathsleadingtogeneration.LettersandcolorsrefertolifespanstagesinFigure1.TheprobabilitiesofapathtoalifespanstagearerepresentedbyP(lifespanstage),oritscomplementP(lifespanstage’).Someprobabilitiesareconditionalonpreviouspathways,P(lifespanstage|previouslifespanstage)...................60Figure36:ProbabilityTreeDiagramofInformalandFormalPathsLeadingtoGeneration.61Figure37:Probabilitytreediagramofpathsdirectlyaftergeneration.LettersandcolorsrefertolifespanstagesinFigure1.TheprobabilitiesofapathtoalifespanstagearerepresentedbyP(lifespanstage),oritscomplementP(lifespanstage’).........................................63Figure38:Respondents’internalprecisionofestimatingproductageandtimeathome.Zerorepresentshighprecision.........................................................................................................................67Figure39:Kaplan‐MeierSurvivalCurveforlaptops...............................................................................68Figure40:Stata®Weibullregressionanalysisforlaptops..................................................................69Figure41:GraphofWeibullregressionmodelforlaptops...................................................................69Figure42:ComparisonbetweenK‐McurvesandOLSfitlaptopWeibullregressioncurvesformean,andlowandhighboundsof95%confidenceinterval.......................................................70Figure43:Distributionoflaptoplengthofperiodofownership ....................................................70Figure44:Distributionsoflaptoplengthofperiodofownershipλallowingvariation(randomsample).....................................................................................................................................................71
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Figure45:Histogramandfittedlognormaldistributionsoflengthoftimealaptopiswithanowneruntilinformalreuseδ..............................................................................................................................72Figure46:EstimatedUSresidentialusedlaptopcollectionratesacrossseveralsurveys......73Figure47:CRTTVsSalesEstimatesforVariousDataSources,ModelParameters...................76Figure48:FlatPanelTVsSalesEstimatesforVariousDataSources,ModelParameters.......76Figure49:TVsinUSHomes................................................................................................................................85Figure50:ComparisonoftheGeneratedUsedTVswithVariousModels.....................................85Figure51:ContributiontoVarianceofGenerationandCollectionEstimatesofUsedCRTTVsin2010.........................................................................................................................................................................87Figure52:MobilePhoneSalesEstimatesforVariousDataSources.................................................88Figure53:MobilephoneSalesEstimatesforModelParameters.......................................................89Figure54:ContributiontoVarianceofGenerationandCollectionEstimatesofUsedMobilePhonesin2010.........................................................................................................................................................93Figure55:DistributionofLengthsofPeriodofOwnershipforeachproduct.Meanparameterspresented.Duringsimulation,distributionparametersvary....................................94Figure56:EstimatedUSresidentialusedelectronicscollectionratesacrossseveralsurveys.........................................................................................................................................................................................95Figure57:UnitWeightforComputersforModelParameters............................................................96Figure58:UnitWeightforMonitorsforModelParameters................................................................96Figure59:Differentiationofused(secondhand)andnewexportsusingexportunitvalue(unitprice).ExampleofTVsetsexportedfromJapantoChinain2001........................................98Figure60:ExampleofChinaExportNVEMhistogramwith$5exportunitvaluefor2010exportoflaptopsfromChinatoLatinAmericaandtheCaribbean(LAC)byvessel................109Figure61:InitialResidualCRTandCRTGlassShippingDestinations(fractionsofweight).......................................................................................................................................................................................117Figure62:PriceGapbetweentheUsedandNewLaptopsFoundfromAmazon(Aug.2012).......................................................................................................................................................................................121Figure63:Buy‐backPriceswithExcellentCosmeticConditionandnoHardwareFailure(surveyin2011,responses367).Theerrorbarsrepresentonestandarddeviationfromthemean............................................................................................................................................................................122
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DefinitionsTerm Definition
UsedElectronics Referstoelectronicsattheendofusebytheirowner.Maybereusedbyafriend,familymember,ordirectresaletoanotherpersonbeforegeneration(collectionordisposal).
GeneratedUsedElectronics
Referstousedelectronicscomingdirectlyoutofuse(retired)orpost‐usestoragedestinedforcollectionordisposal(landfillorincineration).
CollectedUsedElectronics
Referstousedelectronicscollectedbyafirmororganization.Maybedestinedforrefurbishmentorrepairormaybeobsolete,broken,orirreparableelectronicdevicesdestinedforrecyclingviadismantlingorshredding.
ExportedUsedElectronics
Collectedusedelectronicsthathavebeenexportedaswholeunits.
WholeUnitsofUsedElectronics
Referstointactusedelectronicsthatmayormaynotbeworking.Thisexcludesdisassembledproductsthatmaybeexportedasseveraldifferentcommoditymaterialorproductstreams.InthecaseofCRTs,theterm“wholeunits”isextendedtoincludeintactCRTtubes,butnotCRTglasscullet.ThisisdonebecausetheCRTtubecanfunctionasawholeunitwiththesimpleadditionofanewplasticcase.
TVs Televisions,includingCRTandFlatPanelTVs,includingRear‐projectiontelevision(RPTV).
MobilePhones Includingfeaturephonesandsmartphones,forthepurposesofbusiness,publicandprivateuse.Oldermobilephonesformotorvehiclesareexcluded.
DesktopComputers
Desktopcomputer,serverandotherprocessunit.Associatedmonitorsareconsideredseparately.
LaptopComputers Portablepersonalcomputer,excludingtablets.CRTMonitors CathodeRayTubeMonitors,worksinconjunctionwithcomputers.FlatPanelMonitors
Non‐CRTmonitorsincludingLiquid‐CrystalDisplay(LCD)andLight‐EmittingDiode(LED)display.Thesemonitorsaremainlyforcomputers,videomonitorsforsurveillanceareverysimilarandthusincluded.
HSOTDM HybridSalesObsolescence‐TradeDataMethod,whichiscreatedinthisstudyResidential ResidentialinoppositetotheBusinessandpublic,intheformofprivateand
familyBusiness/Public Commercial,institutionandeducationsectorsNVEM Neighborhoodvalley‐emphasismethod(NVEM),analgorithmemployedto
determinetheused‐newthresholdvalue(Seesection5.2.1inappendix).NA NorthAmerica(UnitedNationregions‐basedclassification)LAC LatinAmericaandCaribbean(UnitedNationregions‐basedclassification)LI Lowincome(WordBankIncomegroup‐basedclassification)LMI Lowmiddleincome(WordBankIncomegroup‐basedclassification)
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Term Definition
UMI Uppermiddle(WordBankIncomegroup‐basedclassification)HI Highincome(WordBankIncomegroup‐basedclassification)HI‐OECD HighincomeofOrganisationforEconomicCo‐operationandDevelopment
(OECD)countries(WordBankIncomegroup‐basedclassification)
Note:Incomegroup:Economiesaredividedaccordingto2012grossnationalincome(GNI)percapita,calculatedusingtheWorldBankAtlasmethod.Thegroupsare:lowincome,$1,035orless;lowermiddleincome,$1,036‐$4,085;uppermiddleincome,$4,086‐$12,615;andhighincome,$12,616ormore.
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ExecutiveSummary
Despitegrowinginterestandconcernsurroundingtransboundarymovementsofusedelectronicsaroundtheworld,thereisadearthofdataontheirmovements.Althoughamultitudeofdifferentdatasourcesexist,coherentsetsofinformationonusedelectronicsandtheirmovementarelackingbecauseofinherentchallengesinobtainingsuchinformation.Thesechallengesincludelimitedmechanismsfordatacollection,undifferentiatedtradecodes,lackofconsistentdefinitionsforcategorizingandlabelingusedelectronicsaswellastheircomponents,minimalregulatoryoversight,andlimitedagreementonthedefinitionsofenduses(i.e.,reusevs.recycling).Inspiteofthesechallenges,acharacterizationofthesources,destinations,andquantitiesofusedelectronicsflowswouldinformstrategicdecision‐makingofnumerousstakeholders.
Thefirststepofthisresearcheffortinvolvedexaminingavailablemethodologiestocalculatequantitiesofusedelectronicsgenerated(comingdirectlyoutofuseorpost‐usestoragedestinedforcollectionordisposal),collected(forrecyclingversusdisposal),andexported(aswholeunitstodevelopedordevelopingcountries),andassessingtheeffortrequiredandthequalityofinformationforeachapproach.Afewofthemostpromisingapproacheswereevaluatedinmoredetailanddemonstratedusinglaptopsasacasestudy.Thisstudybuildsoffoftheoutcomesofthepreviousworkanddetailstheresultsfromamorecomprehensiveefforttocalculategenerationandcollectionquantitiesforwholeunits(i.e.,notdisassembledproductormaterialstreams)ofusedelectronicsintheUnitedStates,alongwithtransboundaryflowsfromtheUnitedStatesforarangeofproductsincluding:TVs,mobilephones,computersandmonitors.Theyearofanalysisis2010.
Ahybridapproachofseveralmethodsisusedforcalculatingthequantitiesofgenerated,collected,andexportedwholeunits.Thesalesobsolescencemethodisusedtostochastically(i.e.,includinguncertainty)estimatethegenerationofusedelectronics.Collectionratesaremodeledandappliedtothegenerationresults;thecollectionresultsserveasupperboundsonexportestimates.Exportquantitiesarecalculatedusingatradedataapproach.Theadvantageofthismethodisthattradedataforalltypesofelectronicproductsiswidelyavailable(includingextensivehistoricaldata),updatedrelativelyfrequently,andprovidesinsightintothedestinationsofproducts.Thedisadvantageisthattherearenotradecodesforusedproductsandexportersmaynotbereportingshipmentsofusedproductsproperly.Ananalyticalapproachisusedheretodifferentiateusedproductsfromnewonesinthetradedata,buttheextentofmisclassificationbyexportersisunknown.Thus,itisnotcurrentlypossibletosayhowmucherrorexistsintheexportestimatesasaresultofmisclassification.Still,itissafetoassumethattheestimatesofexportquantitiesarelowerboundsofactualexportquantitiesduetothislikelymisclassificationerror.
FigureES1showsthatapproximately258.2millionunitsofusedelectronics(computers,monitors,TVsandmobilephones)weregeneratedin2010andofwhich171.4millionwerecollected,whichis66.4%ofthegeneratedestimateonaverage.FigureES1alsoshowsthat14.4millionusedelectronicproductswereexported,or8.5%ofthecollectedestimateonaverage.Uncertaintyparametersweremodeled;theerrorbarsfor
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generationandcollectionrepresent90%confidenceinterval,andtheerrorbarsforexportrepresenttheminimumandmaximum..Whenaccountingforproductweight,approximately1.6milliontonsofusedelectronicsweregeneratedandofwhich0.9millionwerecollected,and0.027milliontonswereexportedtotheworld(includingthedevelopedanddevelopingcountries),oronly3.1%ofthecollectedestimate.
FigureES1:FlowsofUsedElectronicsintheUSin2010byQuantity(a)andNormalizedDestinationsofUsedElectronicsExportsin2010byDestinationRegion(b)andIncomeGroups
Theresultsallshowthatmobilephonesaccountforthelargestquantityofusedelectronicsflows,butTVsaretheheaviestflowofgeneratedandcollectedusedelectronics,whilemonitorsarethemostmassiveexports.
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Anadvantageofthetradedataapproachisthatittracksthedestinationsofshippedproducts.However,thedestinationinthetradedatamaybeaninitialstoppingpoint,andtheproductsmaythenbereexportedtoafinaldestination;reexportsandfinaldestinationsarenotalwaysreportedintradedata.Thus,thelistingofadestinationregioninthisreportisanindicationofatleastthisinitialstop,butisnotdefinitivelythefinaldestination.However,ifitisastoppingpointbeforereexport,thefinaldestinationislikelyinthesameregion.
Thisstudydepictsthedestinationregionsandtheeconomicclassificationsoftheregionsforallproducts.Basically,bulkyelectronics,especiallyTVsandmonitors,weremorelikelytobeexportedoverlandorbyseatodestinationssuchasMexico,Venezuela,ParaguayandChina.ThemajordestinationsformobilephoneswereAsia(HongKong,HKSAR)andLatinAmericaandtheCaribbean(ParaguayandGuatemala,Panama,PeruandColombia).Bycontrast,AsiancountriesandregionswhichserveaskeytransitportsforinternationaldistributioninAsiaandAfrica,includingHongKong(HKSAR,China),UnitedArabEmirates(UAE)andLebanon,weremorelikelytoreceiveusedcomputers(especiallylaptops)andthereforemaybere‐exportingtosurroundingcountries.ItisinterestingtonotethatAfricamakesupaverysmallfractionofthetotalusedelectronicsexporteddirectlyfromtheUS.Around80%ofusedelectronics,includingTVs,monitorsandmobilephoneshavebeenexportedtocountrieswithuppermiddle,lowmiddle,andlowincomeeconomies.However,themajorityoftheuppermiddleeconomies,likeHonkKongandUAE,arelikelyre‐exporthubsforfurtherdistributiontoneighboringlowincomeeconomies.
ThisanalysisprovidesinsightsonthequantitiesofusedelectronicsgeneratedandcollectedintheUnitedStates,andexportedfromtheUnitedStates.Tosummarize,thekeyfindingsfromthisreportinclude:
Themethodologyusedtomakethecalculationsiscomprehensivefromgenerationofusedelectronicsatend‐of‐lifeallthewaytoexporttoaforeigndestination.Inaddition,themethodaccountsforuncertaintyingenerationandcollection.
Thescopeofproductsincludesinformationtechnology(computersandmonitors),telecommunication(mobilephones),andconsumerelectronicsproducts(TVs).
Approximately258.2millionunitsor1.6milliontonsofusedelectronicsweregeneratedintheUSin2010.
Oftheamountgenerated,66%wascollectedforreuseorrecyclingonaunitbasis,or56%onaweightbasis.
Oftheamountcollected,8.5%wereexportedonaunitbasis,or3.1%onaweightbasis.
Mobilephonesdominategeneration,collection,andexportonaunitbasis,butTVsandmonitorsdominateonaweightbasis.
LatinAmericaandtheCaribbeanisacommondestinationforproducts,alongwithNorthAmerica.Asiarepresentsthenextlargestdestination.Africaistheleastcommondestination.
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Whilethereissignificantrigorbehindthecalculations,gapsinavailabledatameanthattheexportquantitiesrepresentalowerbound.Thisisduetoalackofexplicitdataonusedwholeunittradeflows,whichnecessitatesseveralkeyassumptionsinthemethodology.Therefore,itisimportantthatotherapproachesbeusedtoestimateexportflowsandcomparedwiththequantitiescalculatedinthisreport.Thiswouldprovideinsightintothemagnitudeoftheerrorderivedfromthedatagaps.
Thereareseveralrecommendationsthatarisefromthiswork.
Thecreationoftradecodesforusedproductswouldenableexplicittrackingofthoseproducts.
Investigationsshouldbeconductedintothespecifictradecodesusedbyexportersforusedelectronicsthatarewholeunits.
Allowingmoreopenaccesstoshipmentleveltradedatawouldenablemoreaccurateanalysesofexportflows.
Increasedreportingofre‐exportdestinationswouldimprovetheaccuracyoffinaldestinationsfortradeflows.
Flowsshouldbeanalyzedacrossmultipleyearsinordertodiscerntrends. Otherapproachesshouldbeusedtoestimateexportflowsofusedelectronics
inordertounderstandtheimpactofthelimitationsinallapproachesontheestimationofquantities.
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1 Introduction
1.1 Background
Therehasbeensignificantinterestbyavarietyofstakeholdersinthequantitiesofusedelectronicproductsgenerated,collectedandexported.ThefederalgovernmentintheUShastakenaparticularinterestinunderstandingtheseissues.In2011anInteragencyTaskForceonElectronicsStewardshipco‐chairedbytheCouncilonEnvironmentalQuality(CEQ),theEnvironmentalProtectionAgency(EPA),andtheGeneralServicesAdministration(GSA)releasedTheNationalStrategyforElectronicsStewardshiptospecifyfederalactionsforensuringelectronicstewardshipintheUnitedStates(US)1.Recommendationsfocusonincentivizingdesignofgreenerelectronics,ensuringthefederalgovernmentleadsbyexampleinacquiring,managing,reusingandrecyclingitselectronics,increasingdomesticrecyclingefforts,andreducingharmfromUSexportsofusedelectronicsandimprovingsafehandlingofusedelectronicstodevelopingcountries.Furthermore,inJanuaryof2012theUnitedStatesTradeRepresentative(USTR)requestedthattheUnitedStatesInternationalTradeCommission(USITC)conductaninvestigationandprepareareportthatdescribesUSexportsofusedelectronicproducts2.Otherstudieshaveestimatedthequantityofusedelectronicsgeneratedandcollectedofattheworldwide,regional,orcountrylevel3‐7,includingtheUS8,9.RecentworkhassoughttoquantifyflowsofusedcomputersandmonitorsexportedfromNorthAmerica10‐12.Theseeffortsarehamperedbyalackofcomprehensivedataonkeytopicssuchasproductsalesandlifetimes,collectionamounts,andnodefinitionofusedproductsintraderecords.
Despitetheworkthathasbeendoneinthisfield,numerousquestionsremainregardingthequantitiesoftransboundaryflowswithintheUSandtoothercountriesandtheuncertaintyinthoseestimates.Anearlierstudy13bytheauthorsexaminedavailablemethodologiestocalculatequantitiesofusedelectronicsgeneratedandcollectedandcharacterizetransboundaryflows,andassessedtheeffortrequiredandthequalityofinformationforeachapproach.ThisreportdetailstheresultsfromasecondphaseofthiseffortinwhichtransboundaryflowsfortheUnitedStatesarequantifiedusingthemostpromisingapproachesfromthepreviousstudyforarangeofproductsincluding:
TVs(CRTandFlatPanel) MobilePhones Computers(LaptopsandDesktops) Monitors(CRTandFlatPanel)
TheanalysesofdesktopsandmonitorsweresupportedbyaseparateprojectinitiatedandfundedbytheCommissiononEnvironmentalCooperation(CEC)ofNorthAmerica,buttheapproachisidenticaltotheoneusedforotherproductsinthisstudy.TheauthorsgratefullyacknowledgeCEC’swillingnesstoincluderesultsfromitsstudyhere.
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1.2 ScopeoftheStudy
Thescopeofthisstudyisdefinedinthetablebelow,includingthedetailedclassificationofthefocalelectronicsandthedistinctionofgenerationandcollectionbyownertypesforthegenerationandcollectionanalysisI;exportswereanalyzedforallproductswithownertypescombined.Theexportmethodsusedomesticexporttradedata,whichtheoreticallycapturestheexportsofgoodsproducedintheUSorwereusedintheUS.SinceCRTTVsandCRTMonitorsarenolongerproducedintheUS,allexportswereassumedtobeused.Forallotherproducts,used‐newthresholdsbasedonexportunitvalueswereusedtodistinguishusedexports.
Table1:ScopeofProductsinStudy,ExportApproach,andDistinctionofGenerationandCollectionbyOwnerTypes
ProductCategory
SpecificProduct DistinctionofGenerationandCollectionbyOwnerTypes
ExportApproach
CRTTV(andParts)
CRTTV,ColorCRTTV,Monochrome
OwnerTypesCombinedExportsassumedtobeusedduetonon‐existentnewdomesticproduction
CRTTube,ColorCRTTube,MonochromeCRTTube,OtherCRTGlassEnvelopes
FlatPanelTV FlatPanelTVs OwnerTypesCombined ThresholdApproachMobilePhone MobilePhone Residential,Business/Public ThresholdApproach
Computer
Laptop
Residential,Business/PublicThresholdApproach(exceptDesktopswithCRTs)
DesktopDesktop:ServerDesktop:Other
CRTMonitor
WithDesktop
Residential,Business/PublicExportsassumedtobeusedduetonon‐existentnewdomesticproduction
WithOtherPCMonitorVideoMonitor
FlatPanelMonitor
PCMonitor Residential,Business/PublicThresholdApproach
VideoMonitor Business/PublicOnly
1.3 OverviewofMethodology
DetailsofthemethodologyareintheAppendix.AflowchartofthelifecycleofelectronicsisshowninFigure1asaguideforkeydefinitionsinthisreport.Theterm“generation”referstoelectronicscomingdirectlyoutofuse(retired)orpost‐usestoragedestinedforcollectionordisposal.Thus,“generation”isconsistentwiththeterm“ready
IThegenerationandcollectionquantitiesofserversandotherkindsofprocessingunitswerenotestimatedseparatefromdesktopsduetheunavailabilityofsalesdata.
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forend‐of‐life[EOL]management”9,14.Onegenerationpathwayforitemsisdisposal(F),includinglandfillsandincinerators.Anothergenerationpathwayalreadymentionediscollectionforprocessinginaworking(H)oranobsolete(G)state.Anassumptionismadethataftertwotermsofuse,itemsareobsolete.Theusedelectronicsprocessor,havingcollectedtheusedelectronicwholeunit,optseithertoprepareitforreusebyanewuserintheUS(C),recoverpartsandmaterialsfromtheitem(I)andtransfersthemtodownstreamvendors(someofwhichmaybeinforeigncountries),orexporttheusedelectronicproductasawholeunit(J).Thefocusofthisstudyisonusedelectronicproductsthatarewholeunits.“WholeUnits”referstointactmonitors,computers,mobilephones,etc.thatmayormaynothavebeenrefurbished.Thus,thisexcludesdisassembledproductsthatmaybeexportedasseveraldifferentcommoditymaterialorproductstreams.
Figure1:LifeCycleFlowChartofElectronicProducts
1.3.1 Generationandcollection
Asalesobsolescenceapproachisusedtocalculategenerationandcollectionquantitiesofusedelectronics.Unlikepreviousstudies,thisstudyincludesuncertaintyininputquantitiesandthenpropagatesthatuncertaintyintooutputsusingMonteCarlosimulations.Generationandcollectionquantitiesaremodeledseparatelyandthencombinedforthefollowingownertypes:residentialandbusiness/public.Thisisdonebecausetheseownertypeshavedifferentconsumption,use,andendofusedispositionhabits.
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Thebasicapproachforquantifyinggenerationandcollectionincludesthefollowingsteps:
1. Determinethesalesofaproductinaregionoveratimeperiod.2. Determinethetypicaldistributionoflifespansfortheproductoveratime
periodusingtwomethods:literature‐basedandsurvey‐based.3. Calculatehowmanyproductsarepredictedtobegeneratedinagivenyear
usingthesalesandlifespaninformation.4. Calculatehowmanyofthegeneratedproductsarepredictedtobecollected
inagivenyearbyapplyingcollectionrates.5. Calculatetheweightofgeneratedandcollectedproductsbymultiplyingunit
weightsbythequantities.Distributionofunitweightsofproductsarefoundfromempiricalcollectiondataforagivenyear.Theapplicationoftheunitweightdistributiontoyearsotherthanwhentheempiricaldatawascollectedintroducessomeuncertaintyduetochangesinproductsizeandweightovertime.
1.3.2 Export
Theoverallapproachistoutilizedetailed,disaggregatedtradedatatodistinguishthequantityofusedelectronicsexports.Thestepsareillustratedbelowand,thealgorithmandnumericalexampleareshowninsection5.21inAppendix.
1. Collectandpreparedisaggregated,detailedexporttradedata.
Figure2:Illustrationofexportquantityandunitvalueofdisaggregatedtradedataforagivenworldregion
2. Estimateused‐newthresholdunitvaluethresholdsfordifferentworldregions
byusingNeighborhoodValley‐Emphasismethod(NVEM,seesection5.2.1inappendix),seeFigure3.NVEMfindstheoptimalthresholdwhichsimultaneouslymaximizesthevariancebetweenthemodes(here,usedandnew)andminimizestheprobabilityoftheunitvaluebinatandaroundtheoptimalthreshold.AnexampleofthethresholdrangefoundbyNVEMinChinaExportNVEMisshown
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inFigure4,withapproximatedistributionssuperimposedonthehistogram.ExportPub.Methodtakesadvantageofpublishedreferencevaluesforusedgoods,andappliesthesamethresholdtoallworldregions.
Figure3:IllustrationofexportquantityandunitvalueofdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion
Figure4:ExampleofUSExportNVEMhistogramwiththresholdrange.2010exportoflaptopsfromUStoUpperMiddleIncomecountriesinLatinAmericaandtheCaribbean.UsedandNewestimatedmodelsuperimposed.
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3. SumthequantityofgoodsdomesticallyexportedfromtheUStopartnercountrieswithaunitvaluebelowtheused‐newthreshold.
Figure5:IllustrationofsumofUsedandNewexportquantitiesfromdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion
4. Optional:Estimatethere‐exportpotentialofdomesticexportsbyinvestigatingthetoptradepartner’sre‐exportactivity.
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2 Results
2.1 GenerationandCollectionResults
2.1.1 TVs
2.1.1.1 GenerationFigure6showssalesofnewproductsputonthemarketincomparisonwiththis
study’sestimationofhistoricalgeneration,foundwitha10,000trialMonteCarlosimulationinMicrosoftExcelusingOracleCrystalBall.Theuncertaintyinthegeneratedquantityestimatesiscausedbythevariationinsalesquantities(+/‐10%)anduncertaintyinthelifespanandgenerationpaths.Theerrorbarsforthegenerationestimatesinthisstudyrepresenta90%confidenceinterval.WhilethesalesofCRTTVshavedeclinedrapidlysince2002,thegenerationisstillatahighvolumeduringthepastfewyears.Thatisbecausethegenerationisalwaysalagofthesalesdataduetothelonguselifetimeandstorage.Forexample,thegenerationofusedTVsintheyear2010ismostlyfromsalesintheyeararound2000.However,generationstartedtodecreaseafter2008.WiththewidespreadsubstitutionofCRTTVswithFlatPanelTVsintheUS,thegenerationofFlatPanelTVswillcontinuetogrowinthenearterm.
Figure6:SalesofNewTVsandComparisonofGenerationEstimatesofUsedTVs
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2.1.1.2 CollectionandComparisonFigure7showsthisstudy’sestimateofgenerationandcollectionincomparison
withEPAestimates(EPAa,2008report8).TwomethodshavebeenusedtoestimatethecollectionofTVsinthisstudy,Literature‐basedA,Literature‐basedB,andSurvey‐based(seeAppendix6.1.1fordetails).Whiletheresidentialandbusiness/publicsectorswereseparatelysurveyedintheirsurvey,thegenerationandcollectionamountsfromthebusiness/publicsectorwereonly5%and7%oftheresidential,respectively.Thecollectionratescalculatedinthisstudyusingthreemethodsareallaround55%inyear2010,whichismuchhigherthantheEPAestimate,whichwasaround17%II.Asareminder,thecollectionrateusedinthisstudyismodeledbasedonsurveysfromtheyear2010.However,thecollectionratefromEPAestimateisprojectedbasedondatafromstateandlocalelectronicscollectionprogramsthatwascollectedin2004.
Note:EPAa,20088wascitedbecauseEPAb2011reportdidnotdifferentiatethetypeofTVs.Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure7:GenerationandCollectionofUsedTVsin2010andComparisonwithOtherEstimates
IIUSEPA,ElectronicswastemanagementintheUnitedStates(approach1).US.EnvironmentalProtectionAgency(USEPA).Washington,DC,US,2008:“CollectionrateinEPAreportisprojectedbasedonexistingstateandlocalelectronicscollectionprogramwhichhavebeendonein2004.”
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Table2presentstheestimatesofthequantityofTVsgeneratedandcollectedintheyear2010.Thecollectionrateusedtoestimatethecollectionisbasedonusingsurveydata.
Table2:GenerationandCollectionofUsedTVsin2010(Thousandunits)
Generation/Collection TypeofTV
MeanLow High
Qty %
GenerationCRTTVs 25,141 18,488 29,069
FlatPanelTVs 7,999 1,146 20,827Total 33,141 23,493 46,614
CollectionCRTTVs 12,317 49% 8,772 14,745
FlatPanelTVs 4,414 55% 528 9,843Total 16,879 51% 10,813 22,281
Note:Literature–basedmethod,andthelowandhighinthisstudyrepresent90%confidenceinterval.
Figure8presentscomparisonsoftheseresultsbothinquantityandweightwithEPAestimations(both2008and2011reports,thelatterisanupdatedversionof2008).WhiletheestimateofgenerationofCRTTVsiscomparabletoEPAresults,theestimateofgenerationofFlatPanelTVsislargerthantheEPAresults.ThedifferenceisbecauseashorterproductlifespanisassumedinthisstudythanintheEPAreport.EPAestimatesdifferentiatebetweenCRTandFlatPanelTVs,butusestaticaccountingforshiftingtrendsinlifespans.Furthermore,their“Totallife”figuresrefertolifespanstagesuntilgeneration.Inthisstudy,lifespanstageassumptionshavebeendisaggregatedbyTVtype,ownertype,anddistinguishbetweenfirstuse,reuse,andstoragebasedtheextensiveliteraturedataandsurveydatabyKahhatandWilliamsin2008(seesection5.1.2inAppendix).Wehavedonesimilarassumptionsandparametersmodelingforotherelectronicsinthisstudy.
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Note:EPAa,20088;EPAb,20119.Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure8:QuantityandWeightestimatesofGenerationandCollectionofUsedTVsin2010aComparisonwithEPAEstimates:
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2.1.2 MobilePhones
2.1.2.1 GenerationFigure9showssalesofnewmobilephone(includingfeaturephonesand
smartphones)putonthemarketincomparisonwiththisstudy’sestimateofthehistoricgeneration.Theresultshowsthatthegenerationiscontinuallyincreasingandtherewere177million(coefficientofvariation=14%)usedmobilephonesgeneratedin2010.Becausethelifespan(3‐5years)ofmobilephonesisshorterthanotherelectronics,thegenerationfollowsthetrendofthehistoricalsalesdatawithashortertimelag.Onlytheliterature‐basedmethodisappliedtothemobilephonebecausethereisnosurveydataavailable.
Note:Theerrorbarsforthegenerationestimatesinthisstudyrepresent90%confidenceinterval;Uncertaintywasassumedforthesalesdatawhenmodeling(COV=10%).
Figure9:SalesofNewMobilePhoneandComparisonofGenerationEstimatesofUsedMobilePhone
2.1.2.2 CollectionandComparisonFigure10presentsthisstudy’sestimateofgenerationandcollectionincomparison
withEPAestimates(both20088and20119);onlythisstudydifferentiatestheownertypeofmobilephones.Theresidentialsectordominatesthegeneratedandcollectedmobilephones,whichaccountsforaround70%ofthetotal.Duetothefactthatthecollectionrateusedinthisstudyis60%(average)inyear2010,thecollectionvolumeofusedmobilephoneisgreaterthanthatintheEPAreport8.
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Note:Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure10:GenerationandCollectionofUsedMobilePhoneandComparisonwithEPAEstimatesin2010
Table3presentsestimatesofthequantityofmobilephonesgeneratedandcollectedintheyear2010.Thelowandhighinthisstudyrepresent90%confidenceinterval.
Table3:GenerationandCollectionofUsedMobilePhonesin2010(Thousandunits)
Sectors
Generation Collection
Mean Low HighMean
Low HighQty %
Business/Public 54,883 48,069 63,765 48,016 87% 37,797 59,537
Residential 121,174 69,470 147,793 71,468 59% 40,742 87,610
Total 176,057 121,782 204,853 119,484 68% 87,451 140,180
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2.1.3 Computers
2.1.3.1 GenerationFigure11showssalesofnewproductsputonthemarketincomparisonwiththis
study’sestimateofhistoricalgenerationandcollection.Collectionestimateswerebasedonsurveydata.Althoughthesalesofdesktopshavedeclinedsince2000,generationhasbeenkeptatahighvolumeduringthepastfewyearsbecauseofthelagcausedbylonguselifetime(orreuse)andstorage.However,thereissomeevidencethatgenerationhasstartedtodeclineafter2011.Bycontrast,generationoflaptophasbeenincreasingrapidlyduetotheirpopularity.Onlytheliterature‐basedmethodisappliedtothecomputersandmonitorbecausethesurveydataisinsufficient.
Note:Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure11:ResidentialSales,Generation,andCollectionEstimatesofUsedComputers.
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2.1.3.2 CollectionandComparisonFigure12showsthisstudy’sestimateofgenerationandcollectionincomparison
withEPAestimates(EPAa,20088).Notethatuncertaintyinthecollectedquantityestimatesmayactuallybealowerboundduetouncertaintyinthecollectionrates.
Note:Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure12:GenerationandCollectionofUsedComputersandComparisonwithEPAEstimatesin2010
Whilethegenerationestimateofdesktopsintheyear2010iscomparable,thegenerationoflaptopsinthisstudyisalmosthalftheEPAestimate.Thesalesdatashouldbesimilarduetotheuseofasimilarsource.However,thedifferenceiscausedbythelifespanassumptions(seetheexplanationinsection2.1.1.2).Sincethecollectionrateusedinthisstudyisabove70%inyear2010,thecollectionvolumeofusedcomputersisgreaterthanthatintheEPAreport8,whichassumeda23%collectionrate.
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Table4presentsthequantitiesofcomputersgeneratedandcollectedinyear2010bothbytypeandsector.
Table4:GenerationandCollectionofUsedComputersin2010(Thousandunits)
SectorsandTypesGeneration Collection
Mean Low HighMean
Low HighQty %
Desktop
Business/Public 8,219 7,501 8,938 6,473 79% 4,698 8,404
Residential 14,385 12,823 16,049 10,181 71% 8,322 12,249
Total 22,604 20,773 24,481 16,654 74% 13,821 19,584
Laptop
Business/Public 3,570 3,258 3,883 2,790 78% 2,005 3,645
Residential 3,728 2,203 5,627 2,727 73% 1,575 4,243
Total 7,298 5,731 9,233 5,517 76% 4,013 7,252
TotalComputers
Business/Public 11,789 10,759 12,821 9,263 79% 6,703 12,049
Residential 18,113 15,673 20,843 12,908 71% 10,346 15,817
Total 29,902 27,145 32,878 22,171 74% 18,237 26,301
Note:Thelowandhighinthisstudyrepresent90%confidenceinterval.
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2.1.4 Monitors
2.1.4.1 GenerationFigure13showssalesofnewproductsputonthemarketincomparisonwiththis
study’sestimateofhistoricalgenerationandcollection.
Note:Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure13:ResidentialSales,Generation,andCollectionofEstimatesoftheUsedMonitors
TheinflectionpointofthesalescurveforCRTmonitorsstartedaround2000.Accordingly,generationkeptincreasingbefore2010andthendecreasingafterthat,likethesametrendassalesdata.Before2007,therewasfastsalesgrowthofFlatPanelmonitorsbecauseoftheirincreasingpopularity.Giventheaveragelifespanisaround10years,thegenerationofFlatPanelmonitorshasbeenrapidlyincreasinginrecentyears.
2.1.4.2 CollectionandComparisonFigure14showsthisstudy’sestimateofgenerationandcollectionquantitiesin
comparisonwithEPAestimates(EPAa,20088)intheyear2010.Notethatuncertaintyinthecollectedquantityestimatesmayactuallybealowerboundduetouncertaintyinthecollectionrates.
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Note:Theerrorbarsinthisstudyrepresent90%confidenceinterval.
Figure14:GenerationandCollectionofUsedMonitorsandComparisonwithEPAEstimatesin2010
WhilethequantityestimateofgenerationofCRTmonitorsinthisstudyiscomparabletotheEPAestimate,theweightissmallerthantheEPAestimate.Thisisbecausetheassumptionofunitweightdataisdifferent.Theunitweightdataforcomputersandmonitorsinthisstudyarebasedonsurveys(samplingdatain2010)ofusedelectronicsbyOregonandWashingtonI,withthesurveysamplesof3286and4191forcrossingbrandsofmonitorsbyOregonandWashington,1774and2655fordesktop,352and270forlaptop,respectively.Bycontrast,theEPAuseddatafromtheFlorida
INCERBrandDataManagementSystem,samplingsharefromcomputerandmonitors(weight)‐OregonandWashingtonSamplingData:http://www.electronicsrecycling.org/BDMS/AlphaList.aspx?sort=All
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DepartmentofEnvironmentalProtection(DEP)todevelopweightestimatesfordesktopCPUs,hard‐copydevices,PCFlatPanels,andCRTTVspriorto2008.
However,thegenerationestimateofFlatPanelmonitorsinthisstudyisalmosthalfoftheEPAestimate.Again,thesalesdatashouldbesimilarduetotheuseofasimilarsource.Thedifferenceiscausedbythelifespanassumptions.
Duetothefactthatthecollectionrateusedinthisstudyisabove70%(average)intheyear2010,thecollectionvolumeofusedcomputersisgreaterthanthatintheEPAreport8,whichassumeda23%collectionrate.Table5presentsthequantityofmonitorsgeneratedandcollectedinyear2010bothbytypeandbysector.MoreCRTmonitorsaregeneratedandcollectedthanFlatPanelmonitors.
Table5:GenerationandCollectionofUsedMonitorsin2010(Thousandunit)
SectorsandTypesGeneration Collection
Mean Low HighMean
Low HighQty %
CRT
Business/Public
3,264 2,979 3,550 2,896 89% 2,454 3,369
Residential 7,485 4,631 11,188 5,122 68% 3,081 7,864
Total 10,750 7,872 14,446 8,018 75% 5,897 10,782
FlatPanel
Business/Public
3,968 3,622 4,316 2,730 69% 1,554 4,009
Residential 2,953 1,690 4,596 2,020 68% 1,115 3,224
Total 6,921 5,571 8,602 4,750 69% 3,101 6,536
Total
Business/Public
7,232 6,601 7,865 5,626 78% 4,035 7,359
Residential 10,439 7,007 14,615 7,142 68% 4,629 10,397
Total 17,671 14,171 21,910 12,768 72% 9,523 16,421
Note:Thelowandhighinthisstudyrepresent90%confidenceinterval.
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2.2 ExportResults
2.2.1 TVs
Figure 15 shows the export flow of CRT TVs and Flat Panel TVs in terms oftransportation mode, destination region, and income groups classification of thedestinationregion.TheexportquantityoftheCRTTVsvialandisgreaterthanviaairandvessel,whichwereshippedtoneighboringregions,suchasNorthAmerica(NA)andLatinAmericaandCaribbean(LAC).ExportsofCRTTVsaremuchgreater thanFlatPanelTVs.ForCRTTVs, the fractionof exports toNA is thehighest (44%), followedbyLACwithafractionof39%andAsiaby10%.Ifgroupedbytheincome,themajordestinationsaretouppermiddleincomecountries(72%).
Figure15:ExportFlowsofUsedTVsin2010:byTransportMode,DestinationRegion,andIncomeGroupClassificationoftheDestinationRegion.
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Figure 16 compares the estimates and associated uncertainty for generated,collected, and exported used TVs. Considering the uncertainty in these estimates, thefractionsofusedCRTTVsandFlatPanelTVscollectedforprocessingthataresubsequentlyexportedare2.4%and0.2%onaveragerespectively.Asareminder,theexportquantitiespresentedhereonlyrepresentthetradeofwholeunits.Ofcourse,disassembledpartsandmaterialsmayalsobeexportedusingdifferenttradecodes(e.g.,circuitboardsorplastics),orusedwholeunitsmaybemisclassifiedandshippedusingothertradecodes.Thesewouldnotbeincludedinthefiguresreportedhere.
Note:Asareminder,inlightoftheassumptionthatthereisnoCRTTVsmanufacturingindustryintheUS,domesticexportofCRTTVs,TubesandTubesglasswereallassumedastheused.ExportresultforFlatPanelTVsisbasedonThresholdChinaExportNVEMbecausetheUSExportNVEMisnotapplicableduetotheinsufficientdata.Theerrorbarsforgenerationandcollectionrepresent90%confidenceinterval,andrepresenttheminimumandmaximumforexport.
Figure16:FlowsofUsedTVsintheUSin2010
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2.2.2 MobilePhones
Threeused‐newthresholdshavebeenappliedtomobilephonestodistinguishusedmobilephonesfromnewbasedonUSdomestictradedata.ThethreethresholdsaredescribedintheAppendix6.2.1.Asareminder,thethresholdsarecalculatedusingUSdomesticexportdatainUSExportNVEM,ChineseexportdatainChinaExportNVEMasacomparisonII,andsalesvalueestimatesinExportPub.Method.Figure17presentsthemobilephoneexportscalculatedusingthethreethresholdmethods.Thereisahighexportrateofusedmobilephones,whichaccountforaround90%ofthetotalexports(usedandnew)basedonthresholdUSExportNVEM.ThequantityofusedmobilephonesidentifiedbyExportPub.Methodisshownwithsignificantuncertainty,whichisduetothebroadrangeofthethresholdvalues.
Note:Theerrorbarsrepresenttheminimumandmaximum.
Figure17:ExportofUsedMobilePhonesfromtheUSin2010UsingtheThreeThresholdMethods
Figure 18 depicts the quantities of exported mobile phones broken down bytransport mode, destination region, and income group classification of the destinationregion. With regards to the destination regions, the fraction of exports to LAC are thehighest,71%onaverage,followedbyAsiawithaaverageof21%.Thereisasmallexportfraction toAfrica, less than1%.This finding is comparable to those in the reportby theElectronicsTakeBackCoalitionIII:“AlthoughthereissomemarketforusedcellphonesintheUS(suchasdomesticabuseprograms),theprincipalmarketsforusedandrefurbishedcell phones are in Latin America and South America”. In addition, while the mobile
IIThekeyassumptionsforthismethodare:themajorityofexportedelectronicgoodsarenew,sinceChinamanufacturesthemajorityoftheworld’selectronics,includingcomputersandmobilephones;goodsexporteddirectlytodestinationnationshavethesameunitvaluedistributionasthoseexportedthroughtransithubssuchasHongKongSAR;thresholdvaluesforcountriesinthesameworldregionwiththesameeconomicclassificationarethesame;andthethresholdvalueofelectronicsoriginating/manufacturedinChinaissimilartothatofgoodsoriginatingfromothercountries(i.e.U.S.).
IIIElectronicsTakeBackCoalition.ElectronicWaste(E‐waste)RecyclingFacts(2008).http://www.electronicstakeback.com/resources/facts‐and‐figures/
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communication standardusedby a country is a significant remarketing constraint, TimeDivisionMultipleAccess(TDMA)andCodeDivisionMultipleAccess(CDMA)prevailintheAmericas. Nevertheless, all interviewed industry experts say that demand for secondaryhandsets outstrips supply for all major standards IV. As for the income groupsclassifications,themajordestinationsareuppermiddleincome(40%),lowmiddleincome(27%)andhighincome(22%).Finally,inthemodeoftransport,thefractionsofairexportsare 73%, 19% for vessel exports and 8% for land exports. The large fraction of airtransportreaffirmsthedecisionnottousetheBillofLadingdataapproachtorepresentallexportsbecauseitexcludesairexportdata,andthereforeasignificantportionofexports.
Note:AverageresultsarebasedonthresholdUSExportNVEM.NA=NorthAmerica;LAC=LatinAmerica&Carribean;HI=HighIncome.UMI=UpperMiddleIncome;LMI=LowMiddleIncome;LI=LowIncome.
Figure18:ExportofUsedMobilePhonein2010:byRegionsandIncomeGroupandModeofTransport
Figure 19 compares the estimates and associated uncertainty for generated,collected and exported used mobile phones. Considering the uncertainty in theseestimates, the fraction of used mobile phones collected for processing that aresubsequentlyexportedisaround10%onaverage.
IVRolandGeyer&VeredDoctoriBlass(2010).Theeconomicsofcellphonereuseandrecycling.Int.J.Adv.Manuf.Technol.47:515–525
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Note:ExportresultsarebasedonthresholdUSExportNVEM.Theerrorbarsforgenerationandcollectionestimatesrepresent90%confidenceinterval,andrepresenttheminimumandmaximumforexport.
Figure19:FlowsofUsedMobilePhonesintheUSin2010.
2.2.3 Computers
Thethreeused‐newthresholdsmethodshavealsobeenappliedtocomputers(whicharedividedintotwotypes:laptopsanddesktops(includingserversandotherprocessunit))todeterminequantitiesofusedcomputersexported,andtheresultsforthisanalysisarepresentedinFigure20.Laptopshavesignificantlyhigherexportquantitiesthanthedesktops,whichispartlybecauselaptopshavehighervalueforfurtherreuseorrecyclingandcanbeeasilyshippedduetotheweightandvolumeadvantageascomparedtodesktops.TheuncertaintyinthequantityestimatesusingExportPub.Methodishigherthantheothertwomethodsduetothebroadrangeofpricesfoundforusedproducts.
Note:Theerrorbarsrepresenttheminimumandmaximum.
Figure20:ExportofUsedComputersfromtheUSin2010UsingtheThreeThresholdMethods
Figure21showstheexport flowsofcomputerproductsdividedby transportationmode,destinationregions,and incomegroupclassificationof thedestinationregions.Airtransportwas themost commonmode,and themost commondestinationswereEurope
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(32%ofallusedcomputerexports),Asia(31%),andNorthAmerica(21%).Whendividingbyincomegroupsclassifications,boththeuppermiddleincomesandhighOECDwerethemajordestinations,accountingfor75%ofthetotal.
Note:AverageresultsarebasedonthresholdUSExportNVEM.NA=NorthAmerica;LAC=LatinAmerica&Carribean;HI=HighIncome.UMI=UpperMiddleIncome;LMI=LowMiddleIncome;LI=LowIncome.
Figure21:ExportofUsedComputersin2010:byRegions,IncomeGroupsandModeofTransport
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Note:TheexportnumberisbasedonthresholdUSExportNVEM,andthedesktopchartincludesthedesktop,server,andotherdesktopcategories.Theerrorbarsforgenerationandcollectionrepresent90%confidenceinterval,andrepresenttheminimumandmaximumforexport.
Figure22:FlowsofUsedComputersintheUSin2010
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2.2.4 Monitors
ForCRTmonitors,allexportslistedinthetradedataareasassumedtobeusedbecausetheseproductsarenolongermanufacturedintheUSandthevalueoftheproductsinthetradedataaretoolowtobenewproducts.Thus,thethreeused‐newthresholdshaveonlybeenappliedtoFlatPanelmonitors.Figure23presentstheresultsoftheanalysisofexportsusingthethreethresholdmethods.ThequantityofusedFlatPanelmonitorsidentifiedbyExportPub.MethodhassignificantuncertaintybecauseofthebroadrangeoftheusedFlatPanelprices.
Note:Theerrorbarsrepresenttheminimumandmaximum.
Figure23:ExportofUsedFlatPanelMonitorsfromtheUSin2010UsingtheThreeThresholdMethods
Figure24showstheexportflowofCRTmonitorsandFlatPanelmonitorsintermsof transportation mode, destination regions, and income groups classification of thedestinationregion.ThereweremoreexportsofFlatPanelmonitors thanCRTmonitor interms of quantity, and the exports of PC monitors were greater than those of videomonitors.WhilemoreexportsofFlatPanelmonitorswereshippedviavesselthanlandorair,exportsofCRTmonitorsweresurprisinglyhighestbyair.Neighboringcountrieswerethemajor destinations for the two types of monitors. For CRTmonitors, NA ranks first(34%), followed by LAC (28%), and Asia (23%). When divided by income groupsclassifications, the upper middle incomes dominate the major destinations for CRTs,accounting for 48%of shipments, followedbyHI‐OECDwith a fractionof 31%. For LCDmonitors,LACranks firstasadestinationregion(51%), followedbyNA(38%),andAsia(8%). When divided by income groups classifications, the upper middle incomes alsodominatethemajordestinations forLCDs,accounting for79%ofshipments, followedbylowmiddleincomeswithafractionof10%.
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Note:AverageresultsforFlatPanelmonitorsarebasedonthresholdUSExportNVEM.NA=NorthAmerica;LAC=LatinAmerica&Carribean;HI=HighIncome.UMI=UpperMiddleIncome;LMI=LowMiddleIncome;LI=LowIncome.
Figure24:ExportFlowofUsedMonitorsin2010:byRegions,IncomeGroupsandModeofTransport
Figure 25 compares the estimates and associated uncertainty for generated,collected,andexportedusedmonitors.Consideringtheuncertaintyintheseestimates,thefractions of used CRT and Flat Panel monitors collected for processing that aresubsequentlyexportedare3.4%and12.2%(onaverage),respectively.
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Note:TheexportofCRTsincludesCRTmonitors,videomonitors,andmonitorswithdesktops;allexportswereassumedused.TheexportsofFlatPanelsarebasedonthresholdUSExportNVEM.TheFlatPanelcategoryincludesdesktopmonitorsandvideomonitors.Theerrorbarsforgenerationandcollectionrepresent90%confidenceinterval,andrepresenttheminimumandmaximumforexport.
Figure25:FlowsofUsedMonitorsintheUSin2010
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3 ComparisonandSummaryoftheFlowsforAllExaminedProducts
3.1 Generation,CollectionandExportComparison
Figure26depictsgeneration,collection,andexportquantitiesandweightforallusedelectronicproducts.Thetotalcollectionamountofallelectronicsaccountsformorethan60%ofthegeneration,andtheexportofwholeunitsaccountsfor8%ofthecollectionquantityandonly3%weight,respectively.Figure27showsthecollectionweightandthefractionoftheweightofthecollectedproductsthatwereexported.Figure28showstheweightbreakdownbyproductofgeneration,collection,andexportamounts.Theseresultsshowthatmobilephonesdominatethegenerated,collectedandexportedusedelectronicsbyquantity,andTVsdominatethegeneratedandcollectedusedelectronicsifmeasuredbyweight.However,monitorsdominatethetypesofusedelectronicsforexport.
Note:ExportresultsarebasedonthresholdUSExportNVEM,ifapplied.Theerrorbarsforgenerationandcollectionrepresent90%confidenceinterval,andrepresenttheminimumandmaximumfromthemeanforexport.
Figure26:FlowsofUsedElectronicsintheUSin2010
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Note:Exportresults(average)arebasedonthresholdUSExportNVEMifathresholdisapplied.
Figure27:WeightofusedproductscollectedintheUSin2010andthefractionofthosecollectedproductsthatweresubsequentlyexported.
Figure28:WeightfractionsofUsedElectronicsintheUSin2010
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3.2 ExportSummary
Figure29showsthefractionsofallUSexportsforeachproducttypethatareusedversusnew.Thereissignificantvariationacrosstheproducttypes,withexportsofCRTdisplaysbeingexclusivelyusedandexportsofFlatPaneldisplaysandcomputingequipmentbeingprimarilynew.Mobilephonesaresomewhereinbetween.
Note:NormalizedresultsarebasedonthresholdUSExportNVEMifathresholdisapplied.
Figure29:TheFractionofAllUSExportsofElectronicsProductsfromtheUSin2010ThatAreUsedandNew.
Figure30comparestheexportofusedelectronicsbytransportationmode,destinationregions,andincomegroupsclassificationofthedestinationregions.Theheavyelectronics,e.g.,TVsandmonitors,aremorelikelytobeshippedbylandandvesseltoneighboringregions(NAandLAC).ThemajordestinationsformobilephonewereLACandAsiancountries.EuropeancountriesandAsiancountriesweremorelikelytoreceiveusedcomputers.Africaistheleastcommondestination,whichissimilartowhatisfoundintheEUcountrystudies,mainlytheDutchFutureFlowsreport15.
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Note:NormalizedresultsarebasedonthresholdUSExportNVEM.
Figure30:QuantityFractionsofUSExportFlowsin2010fortheFourUsedElectronicsTypesBrokenDownbyTransportMode,DestinationRegions,andIncomeGroupsClassificationoftheDestinationRegions.
Figure31comparesthetop15exportdestinationsforthefourtypesofusedelectronics.UsedTVsandmonitorshavemainlybeenexportedtoMexico,becausetheworldhasfewCRTprocessingfacilities;mostareinMexicoandIndia.Forexample,thesurveysconductedbyUSITC10revealedthattheCRTglassattheCaliResources/TDMfacilityinMexico,whereglassisseparatedandcleaned,hasbeenshippedtoSamtel/VideoconinIndiafortheproductionofnewCRTglass.Themajordestinationsfor
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computerswereAsiancountries,includingHongKong,UnitedArabEmirates(UAE)andLebanon.BothHongKongandmanyLACcountriesweremostlikelytoreceiveusedmobilephones.Asareminder,thesecountriesshouldnotbeviewedasthefinaldestinationcountriesbecausetheymayactuallyrepresentastoppingpointforproductsbeforetheyarere‐exportedtoanothercountryintheregion.
Inthenextsection,HongKong,UAEandLebanonhavebeenshowntore‐exportasignificantfractionoflaptops,thoughthedatacannotdistinguishbetweenre‐exportsofusedandnewlaptops.Thetradedatadoesnotidentifywhetherproductswillbere‐exported,soitcanonlybeguessedbasedonthedestination(e.g.,somecountriesaremorelikelytobere‐exportlocationsthanothers).
Note:NormalizedresultsarebasedonthethresholdUSExportNVEM ifthresholdsareapplied
Figure31:Top15ExportDestinationsforEachProductTypein2010.
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3.2.1 PotentialofRe‐exportofExportedUsedLaptops
Publicallyavailabletradedataisreportedastransactionsbetweenanexporterandanimporter.Howeverduetore‐exports,sometimestheimportcountryisnotthefinaldestination.Togetasenseofthefinaldestinationofusedlaptops,theprobabilityofre‐exportuponimportofusedandnewlaptopsinthetoptendestinationcountrieswasestimated,asshowninTable6.Theratioofre‐exportstoimportsservesasthatestimatewherethedatawasavailable,andisotherwiseconsideredtobelessthanorequaltotheratioofgeneralexportstoimports.ConsideringthatdomesticexportsfromtheUSarenotlikelytobere‐exportedbacktotheUS,allexportfigurespresentedexcludetheUS.Overall,atmost80%ofexportsfromtheUStothesecountrieswouldnotbere‐exported.
Table6:Potentialofre‐exportfrom2010toptendestinationcountriesQuantitiesoflaptopsinthousands.UsedexportsfromUSbasedonUSExportNVEM.
Country UsedExportsfromUS
ImportsfromWorld
ExportstoWorld,exceptUS
Exports/Imports
Re‐ExportstoWorld,exceptUS
MaximumRe‐Exports/Imports
Lebanon 114.1 75.7 31.8 42.0% ≤42.0%Argentina 71.2 1,537.3 2.3 0.1% ≤0.1%HongKong 67.3 5,257.7 2,508.9 47.7% 2,508.7 47.7%Canada 60.7 5,436.9 148.2 2.7% 78.7 1.4%UnitedArabEmirates(2008) 59.5 674.6 229.1 34.0% 229.1 34.0%
Chile 57.4 1,280.0 23.6 1.8% ≤1.8%Bolivia 56.1 1,802.7 2.0 0.1% ≤0.1%Mexico 37.1 6,418.0 58.1 0.9% ≤0.9%UnitedKingdom 33.1 12,313.5 2,457.3 20.0% ≤20.0%China 31.9 1,226.1 134,209.6 10946.0% 376.2 30.7%
ConsiderabletradewithinthetoptendestinationcountrieswasobservedbyasdemonstratedinFigure31.Argentina,HongKong,UnitedArabEmirates,Chile,UnitedKingdomandChinaareexportdestinationsfromothertoptenUSdestinationcountries.Canada’stopthreere‐exportdestinationsaretoptendestinationcountries.Also,notethatLebanonreportsfewerimportsfromtheworldthantheUSexportestimate.
ExportingCountry TradeDirection ImportingCountryLebanon LebanonArgentina ArgentinaHongKong HongKongCanada CanadaUnitedArabEmirates UnitedArabEmiratesChile ChileBolivia BoliviaMexico MexicoUnitedKingdom UnitedKingdomChina ChinaFigure32:Laptoptradebetweenthetoptendestinationcountriesin2010
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3.2.2 ComparisonwithOtherStudy
InFigure33below,comparisonsaremadebetweenthisstudy’sexportestimates,averagedacrossallmethods,andresultsfromtheUSITC(2013)study10.AsdescribedindetailintheAppendix5.2.1.1,themainresultsoftheUSITCwereinferredfromabroadsurveyofplayersthroughouttheusedelectronicschain.Additionally,analysisofshipment‐leveltradedatafrom2011wascompleted.ThoughUsed‐Newthresholdswerenotidentified,statisticswereprovidedatthelowest10%,25%,50%and100%oftradebyaverageunitvalue.Comparisonsweremadebetweenappropriatestatisticsthatwerecomparablewiththisstudy’sUsed‐Newthresholds.Thecomparableresultsbetweenthisstudy’sapproachandtheUSITCshipment‐levelresults,withtheexceptionoflaptops,suggestthatthisstudy’stradedataapproachcanreasonablyapproximateshipment‐leveltotalquantities.
Figure33:ComparisonbetweenthisstudyandUSITCreport
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4 ConclusionsandRecommendations
4.1 Conclusions
Thisreportpresentstheresultsofanefforttocalculatequantitiesofusedelectronics(aswholeunits)generatedandcollectedintheUnitedStates,andexportedfromtheUnitedStates.TheproductsincludedTVs,mobilephones,computersandmonitors.Generationandcollectionquantitieswerecalculatedusingasalesobsolescencemethodthatincludeduncertainty,andexportquantitieswerecalculatedusingatradedataapproach.Theadvantageofthetradedataapproachisthattradedataforalltypesofelectronicproductsiswidelyavailable(includingextensivehistoricaldata),updatedrelativelyfrequently,andprovidesinsightintothedestinationsofproducts.Thedisadvantageisthattherearenotradecodesforusedproducts,exportersmaynotbereportingshipmentsofusedproductsproperly,andthedestinationlistedinthetradedatamayactuallybeaninitialstoppingpointandnotafinaldestination.Giventheselimitations,theexportflowsshouldbeviewedasalowerboundbecausetheymaynotbecapturingalloftheflowsofusedelectronicsshippedaswholeunits.
Theresultsshowthatapproximately258.2millionunitsofusedelectronicweregeneratedand171.4millionunitswerecollectedintheUSin2010.Exportflowswereestimatedtobe14.4millionunits,whichis8.5%ofthecollectedestimateonaverage.Onaweightbasis,1.6milliontonsofusedelectronicsweregeneratedintheUSin2010and0.9milliontonswerecollected.Oftheamountcollected,26.5thousandtonswereexported,whichis3.1%oftheweightcollected.Mobilephonesdominategeneration,collection,andexportonaunitbasis,butTVsandmonitorsdominateonaweightbasis.Asareminder,thismethodologycanonlybeusedtotrackwholeunitsandnotscrapcommoditystreamsfromunitsdisassembledintheUS.Whilethetotalquantityofusedelectronicsexportsreportedhereismostlikelyanunderestimateduetothelikelihoodthatsomeshipmentsofwholeunitsarenotreportedusingthepropertradecodes,theproportionsofexportstoworldregionsislikelyaccurate.
Analysisofthedestinationregionsindicatesthatbulkyelectronics,especiallyTVsandmonitors,weremorelikelytobeexportedoverlandorbyseatodestinationssuchasMexico,Venezuela,ParaguayandChina.ThemajordestinationsformobilephonewereAsia(HongKong)andLatinAmericaandtheCaribbean(ParaguayandGuatemala,Panama,PeruandColombia).Bycontrast,Asiancountries(HongKong,UnitedArabEmiratesandLebanon)weremorelikelytoreceivetheusedcomputers(especiallylaptops).Around80%ofusedelectronics,includingTVs,monitors,andmobilephones,areexportedtocountrieswithuppermiddleandlowermiddleincomegroups.ItisinterestingtonotethatAfricareceivesaverysmallfractionoftheusedelectronics(selectedtypesofelectronicsinthisstudy)exportedfromtheUS.
Generally,thekeydriversofgenerationofusedelectronicsestimateswerethelengthoftheuselifespanstageandthetotalsalesestimates.Thissuggeststhatforgenerationestimateswithloweruncertainty,uselifetimeestimateswithloweruncertaintyshouldbeatoppriority,followedbymoreaccuratesalesdataestimates.Unsurprisingly,
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collectionrateisthemostimportantparameterforcollectionestimatesandproductunitweightisthemostimportantparameterforweight‐basedestimates.Therangeofused‐newthresholdsdrivetheuncertaintyfortheexportestimate.Amongthethreeused‐newthresholdmethods,thesalesvalue‐basedthreshold(ExportPub.Method)hasalargeruncertaintythanthethresholdsbasedonthedistributionsofthetradedata(ExportNVEM).
4.2 Recommendations
Thereareseveralrecommendationsthatarisefromthiswork.
Thecreationoftradecodesforusedproductswouldenableexplicittrackingofthoseproducts.
Investigationsshouldbedoneintothespecifictradecodesusedbyexportersforusedelectronicsthatarewholeunits.
Allowingmoreopenaccesstoshipmentleveltradedatawouldenablemoreaccurateanalysesofexportflows.
Morecooperationandexchangeofdatabetweeninspectionauthoritiesinexportandimportcountriesshouldbeencouraged.
Increasedreportingofre‐exportdestinationswouldimprovetheaccuracyoffinaldestinationsfortradeflows.
Flowsshouldbeanalyzedacrossmultipleyearsinordertodiscerntrends.
Otherapproachesshouldbeusedtoestimateexportflowsofusedelectronicsinordertounderstandtheimpactofthelimitationsinallapproachesontheestimationofquantities.
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(55) DSM-ESI. 2010 Connecticut state-wide solid waste composition and characterization study, final report. DSM Environmental Services, Inc. (DSM-ESI) and Connecticut Department of Environmental Protection (CDEP). Hartford, Connecticut, US, 2010.
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(57) KCI. Florida Pinellas county 2007 waste composition study final report. Kessler Consulting, Inc. (KCI), Pinellas County Utilities. Tampa, FL, US, 2007.
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(59) CDM. 2009 Illinois commodity/waste generation and characterization study. CDM and Illinois Department of Commerce & Economic Opportunity. Illinois, US, 2009.
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(61) MID-ASWC. 2011 Iowa statewide waste: Characterization study. MID Atlantic Solid Waste Consultants (MID-ASWC) and Iowa Department Of Natural Resources. Iowa, US, 2011.
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(66) PDEP. 2003 Pennsylvania statewide waste composition study. Pennsylvania Department of Environmental Protection (PDEP). Pennsylvania, US, 2003.
(67) RWBI. Sioux Falls regional sanitary landfill waste characterization study. R. W. Beck, Inc. (RWBI) and City of Sioux Falls, South Dakota. South Dakota, US, 2007.
(68) Painter, R.; Watson, V. 2008 Tennessee waste characterization study. Tennessee Department of Environment and Conservation. Tennessee, US, 2008.
(69) RCC.; MSWC. 2009 Wisconsin statewide waste characterization study. MSW Consultants (MSWC), Recycling Connections Corporation (RCC), Wisconsin Department of Natural Resources (WDNR). Wisconsin, US, 2009.
(70) CCGI. 2001 Wisconsin statewide waste characterization study. Cascadia Consulting Group, Inc. (CCGI), Wisconsin Department of Natural Resources (WDNR). Wisconsin, US, 2003.
(71) Llamas, R. T.; Stofega, W. U.S. Mobile phone 2011-2015 forecast. IDC. 2011. (72) EI Mobile phones in the U.S. Euromonitor International (EI). 2012. (73) USITC. Wire less handsets: Industry & trade summary. United States International Trade Commission.
Washington, DC, USA, 2010. (74) Jang, Y.-C.; Kim, M. Management of used & end-of-life mobile phones in Korea: A review. Resources,
Conservation and Recycling 2010, 55(1), 11-19. (75) Yu, J.; Williams, E.; Ju, M. Analysis of material and energy consumption of mobile phones in China. Energy
Policy 2010, 38(8), 4135-4141. (76) Polák, M.; Drápalová, L. Estimation of end of life mobile phones generation: The case study of the Czech
Republic. Waste Management 2012. (77) Wilhelm, W.; Yankov, A.; Magee, P. Mobile phone consumption behavior and the need for sustainability
innovations. Journal of Strategic Innovation and Sustainabilit 2011, 7(2), 20-40. (78) ISG. 2010 residential recycling survey. ISG, Ramsey County Minnesota. Minnesota, US, 2010. (79) Hanks, K.; Odom, W.; Roedl, D.; Blevis, E. Sustainable millennials: Attitudes towards sustainability and the
material effects of interactive technologies. Proceedings of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, ACM, 2008; pp 333-342.
(80) Deb, P. Fmm: Stata module to estimate finite mixture models. Statistical Software Components 2012. (81) Miller, T. R.; Gregory, J.; Kirchain, R.; Duan, H. Characterizing transboundary flows of used electronics:
Summary report. In MIT and NCER: 2012.
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(82) Kahhat, R.; Williams, E. Product or waste? Importation and end-of-life processing of computers in Peru. Environmental Science & Technology 2009, 43(15), 6010-6016.
(83) Yoshida, A.; Tasaki, T.; Zollo, A. Material flow analysis of used personal computers in Japan. Waste Management 2009, 29(5), 1602-1614.
(84) Terazono, A., Generation and material flow of e-waste in East Asia. In Regional Workshop on E-Waste Identification toward the Prevention of Illegal Transboundary Movement for Hazardours Waste and Other Wastes in Asia, Beijing, China, 2008.
(85) NERC. Used electronics market study survey analysis. In Northeast Recycling Council, Inc.: 2003. (86) IAER. Iaer electronics recycling industry study. International Association of Electronics Recyclers. 2003. (87) IAER. Iaer electronics recycling industry report. International Association of Electronics Recyclers. 2006. (88) Daoud, D. Survey: Inside the u.S. Electronics recycling industry. In IDC: 2011. (89) World Bank Country and lending groups. http://data.worldbank.org/about/country-classifications/country-and-
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United States. MIT: 2012. (94) Fan, J.; Lei, B. A modified valley-emphasis method for automatic thresholding. Pattern Recognition Letters
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Commission (USITC). 1995. (98) Mizuki, C.; Pitts, G.; Aanstoos, T.; Nichols, S. CRT disposition: An assessment of limitations and
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(99) Weitzman, D. H. Is CRT glass-to-lead recycling safe and environmentally friendly? Electronics and the Environment, 2003. IEEE International Symposium on, IEEE, 2003; pp 329-334.
(100) Kwak, M.; Kim, H.; Thurston, D. Formulating second-hand market value as a function of product specifications, age, and conditions. Journal of Mechanical Design 2012, 134, 032001-11.
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6 Appendices
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6.1 GenerationandCollection
6.1.1 MethodologyOverview
Figure34demonstratesthatthequantityofgeneratedwholeunitsisgreaterthanthatofcollected,whichisgreaterthanthequantityexported.Differentmethodologicalapproacheswereneededtoestimateeachquantity,overallthisapproachisnamedtheHybridSalesObsolescence‐TradeDataMethod(HSOTDM)V.ThecollectedquantitywasestimatedbasedonthegeneratedquantityestimatedwithaSalesObsolescencemodel,whereastheexportedquantitywasdeterminedindependentlywithTradeData.Onetestforreasonablenessoftheexportestimateiswhetheritislessthanthecollectionestimate,sinceusedelectronicequipmentisassumedtobecollectedbeforeitisexported.Inthissection,themethodsusedtoestimatethegeneration,collectionandexportquantitiesforthelaptopcasestudyaredescribed,andresultsarepresented.
Figure34:Illustrationthatexportedwholeunitsofusedelectronicsareasubsetofcollectedwholeunits,whichareasubsetofgeneratedwholeunits.[Letters]andcolorsrefertoFigure1(repeatedbelowforconvenience).
VNotethatthismethodwassimilarlydescribedinMilleretal.2013.QuantitativeCharacterizationof
DomesticandTransboundaryFlowsofUsedElectronics:CaseStudy:UsedComputersandMonitorsinNorthAmerica.CommissionforEnvironmentalCooperationofNorthAmerica(CEC).
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Figure1:LifeCycleFlowChartofElectronicProducts
Thebasicapproachtodeterminegenerationandcollectionquantitiesconsistentacrossmoststudiesreviewedinvolvesstepsto:
1. Determinethesalesofaproductinaregionoveratimeperiod2. Determinethetypicaldistributionoflifespansfortheproductoveratime
period3. Calculatehowmanyproductsarepredictedtobegeneratedinagivenyear
usingthesalesandlifespaninformation4. Calculatehowmanyofthegeneratedproductsarepredictedtobecollected
inagivenyearbyapplyingcollectionrates5. Optional:Calculatetheweightofgeneratedandcollectedproductsby
multiplyingunitweightsbythequantities
Thesegenerationandcollectioncalculationstepsroughlycompriseasalesobsolescencemodel(alternativelyknownasmarketsupplymethod16).Studiescoverdifferentproducts,timeperiods,geographicalregions,andvaryincomplexity17‐21.
6.1.1.1 PreviousWorkOtherstudiestakeadvantageofpublishedstatisticsaboutthestockofelectronics,
orextrapolatefromin‐depthcasestudiesandsurveystoestimategeneration.Forexample,UNEP’sInternationalEnvironmentalTechnologyCenter(UNEP/DTIE‐IETC)describedin2007severalvariationsofsimplestockmodels16.Mulleretal.(2009)intentionallyutilized“freeorcheaplyavailableindicatorsprovidedbytheInternationalTelecommunicationUnion(ITU)andtheWorldBank”formuchoftheirstockandflowmodeldata22.Yangand
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Willams(2009)andYuetal.(2010)havecreatedstockandflowmodelsfortheUS7,23.Babbittetal.(2009)usedemployeepersonalcomputerpropertycontroldatafromArizonaStateUniversitytoestimatethehighereducationgenerationquantity24.KahhatandWilliams(2012)surveyedUScomputerownersandcapturedtheirownershipanddispositionbehavior25;generationandcollectionestimatesinthisstudyinpartderivesfromthosesamesurveys.Wangetal.(2013)developedan“advanced,flexibleandmultivariateInput–OutputAnalysis(IOA)method”which“linksallthreepillarsinIOA(productsales,stockandlifespanprofiles)toconstructmathematicalrelationshipsbetweenvariousdatapoints”and“demonstratessignificantdisparitybetweenvariousestimationmodels,arisingfromtheuseofdataunderdifferentconditions.”26
Surveys,collectionratesfromotherregions,andgovernmentdatahavebeenusedtoestimateUSusedelectronicscollectionrates.Severalsurveys,forexampleKahhatandWilliams(2012),RIS International (2003), Consumer Reports (2006), and Saphores et al. (2009),havebeenconductedtoascertaintheend‐of‐life(EoL)managementoptionsutilizedbyconsumersandbusinesselectronicsowners;thisdatacanbeusedtoinfercollectionrates25,27‐29.Gregoryetal.(2009)adjusteddocumentedEuropeantrendsincollectionforotherworldregions’CRTcollection20.USEPA(2011)useddatafromstateswithusedelectronicsrecyclingprogramstoestimatetheshareofresidentialgeneratedelectronicsthatarecollectedforprocessingversusdisposal.Lowcollectionrates(onepoundcollectedpercapita)wereassumedforstateswithoutprograms19.
InordertoestimatethegenerationandcollectionofTVs,mobilephones,computersandmonitorsintheUnitedStatesin2010,thereremainafewgapsintheexistingliterature.Allbutoneoftheexistinggenerationandcollectionestimatesfor2010combinesdesktopsandlaptopsintoasinglecomputercategory.Lifespandistributionsusedvaryconsiderablybetweenstudies.Theexistingestimatesdonotagreewithoneanother;thisstudywillmodelthegenerationoflaptopsfactoringintheuncertaintyassociatedwithrelevantparameters.
6.1.1.2 MethodologiesDevelopedandUtilizedTwoseparatemethodologiesweredevelopedtoestimategenerationandcollection
withintheoverallHSOTDM,andbothfollowthesamebasicfivestepsoutlinedatthebeginningofthechapter.Table7belowoutlinesthedifferencesinthemethodologicalstepsandproductscovered.Thefirstmethoddescribed(Literature‐basedMethod)reliesonpublishedlifespanestimatesandcollectionestimates,whilethesecondmethoddescribed(Survey–basedMethod)reliesondirectlyonlifespandistributions,generationandcollectionestimatesderivedfromrecentconsumerandbusinesssurveysaboutelectronicspurchase,use,anddiscardhabits.Thesesurveysfocusedoncomputersandmonitors,buttouchedonotherelectronicssuchasTVsaswell.
ThereisadditionalinformationavailableforTVs,andthereforeanothersetofvalidatingmethodologiesweredevelopedtotakeadvantageofthisdata.TheprevalenceofTVsinhomeshasbeenstudiedindepth,andsoasimplestockandflowmodelwasusedcombiningTVpenetrationdatawithsalesdatatoarriveatgenerationresults.ThisapproachcannotbeclassifiedasaLiterature‐basedorSurvey‐basedapproachasdefinedinthisstudy,andsoistreatedseparately.Also,manyUSstateshavehadcollectionprograms
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since2010,andsocollectionrateswereestimatedbasedonreportedcollectionquantities;TVsweretheonlyproductcategorywherethereweresufficientstatestoperformthisanalysisinarobustfashion(Literature‐basedMethodB).
Sincedifferentownertypeshavedifferentconsumption,useandendofusedispositionhabitsduetodifferentbudgetsandpriorities,generationandcollectionweremodeledseparatelyforresidentialandbusiness/publicowners.Resultsarepresentedwithtotalgenerationandcollectionquantitiessummed.
Table7:ComparisonbetweenLiterature‐basedMethodandSurvey‐basedMethodforGenerationandCollection
Step1‐5andProducts Literature‐basedMethod Survey–basedMethod
1.SalesDataOwnerTypes:Residential,Business/Public
OwnerTypes:Residential,Business/Public
2.LifespanEstimation Publishedestimates Modeledsurveydata
3.GenerationPredictionProbabilisticpathwayswithlognormaldistributions
ComputerandMonitors:Residential:ReusemodelwithWeibulldistributionsBusiness/Public:SurveyestimatesscaledupTVs:Surveyestimatesscaledup
4.CollectionPrediction A.PublishedestimatesB.Statecollectionprograms Surveyestimatedcollectionrates
5.WeightEstimation Publishedestimates ModelofstatecollectiondataProducts TVs,MobilePhones ComputersandMonitors,TVs
Bothmethodsrequiresalesofaproductinaregionoveratimeperiodforbothresidentialandbusiness/publicestimates.Anticipatingthatsomeusedelectronicsaregenerateddecadesaftertheirpurchase,timeseriessalesdataissoughtfromtwodecadesbeforetheyearofprediction.Salesdataestimatesthemselvesareusedinthebaselineanalysis,andareallowedtovary+/‐10%tocapturepotentialerrorintheMonteCarlosimulation.SalesdataforeachproductaredescribedinthefollowingDataandIntermediateResultssection.
6.1.1.2.1 Literature‐basedMethod
6.1.1.2.1.1 Determinethetypicaldistributionoflifespansfortheproductoveratimeperiod
ThismethodfordeterminingtypicaldistributionsoflifespansfortheproductisarefinementofthemodeldevelopedbyMatthewsetal.whichaccountsfortwousestages(initialandreused),andaccountsfordifferentfatesaftereachstage17.Theprimarydifferenceistheincorporationofadistributionoflifespanlengthsandpathprobabilitiessothatbothdataqualityuncertaintyandvariationareconsidered.Thestepsareasfollows:
i. Combineliteratureandindustryestimatesforthedistributionoflengthsofeachlifespanstage(s)(eg.B.InitialUse,E.ReuseStorage)inFigure1(repeatedaboveforconvenience)toarriveatameanestimatewithuncertaintyforeachlifespanstage.
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ii. Definepathwaystogeneration(Figure35)involvingcombinationsoflifespanstagesrelatedtoFigure1.
Thismethodissomewhatofanunderestimate,becausewedonotestimatethesecondroundofgenerationofproductsthatunderwentformaldomesticreuse.AfullmodelinclusiveofthesecondroundofgenerationispresentedinFigure35;initialsensitivityanalysessuggestthattheresultisnotverysensitivetotheexclusionofthesecondroundofgeneration.
Figure35:Probabilitytreediagramofinformalpathsleadingtogeneration.LettersandcolorsrefertolifespanstagesinFigure1.TheprobabilitiesofapathtoalifespanstagearerepresentedbyP(lifespanstage),oritscomplementP(lifespanstage’).Someprobabilitiesareconditionalonpreviouspathways,P(lifespanstage|previouslifespanstage).
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Figure36:ProbabilityTreeDiagramofInformalandFormalPathsLeadingtoGeneration.
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iii. Combinethelengthsofthelifespanstagestocalculatethelengthsofeachpathwaytogenerationandestimatetheprobabilityofeachpathwaytogeneration.
InTable8below,theequationsfordeterminingthemeanpathlengthandmeanpathprobabilityarefoundforeachofthesixpathwaystogeneration.
Table8:Equationsusedtocalculatemeanpathlengthandmeanpathprobability
SixPaths( ) MeanPathLength MeanPathProbability
PathB,D,C,E 1*P(D)*P(C|D)*P(E)
PathB,D,C,E’ 1*P(D)*P(C|D)*P(E’)
PathB,D,C’ 1*P(D)*P(C’|D)
PathB,D’,C,E 1*P(D’)*P(C|D’)*P(E)
PathB,D’,C,E’ 1*P(D’)*P(C|D’)*P(E’)
PathB,D’,C’ 1*P(D’)*P(C’|D’)
iv. Determinetheoverallmeanlifespanbyaggregatingthepathstogeneration
probabilistically.Estimatethevarianceofthelifespandistributionfromliterature.
Thegenerationmodelonlyincorporatesasinglemeanpathlength,andsoinEquation1,theoverallweightedmeanoflifespansforallsixpaths ispresented.
Equation1:Overallweightedmeanoflifespansforallsixpaths
6.1.1.2.1.2 Calculatehowmanyproductsarepredictedtobegeneratedinagivenyearusingthesalesandlifespaninformation
Thequantityofusedproductsgeneratedinyearyisbasedonthesalesinyearsandtheprobability thataproductsoldinyearsisgeneratedinyeary.Theprobabilitydistribution iscreatedusingparametersfromthelifespanestimates.Here,alognormaldistributionwasassumed,whichiscomparabletoauniversitycomputerlifespanstudy30.Equation2showsthehowthequantityiscalculated.
Equation2:Quantitygeneratedinyeary
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6.1.1.2.1.3 Literature‐basedMethoda:Calculatehowmanyofthegeneratedproductsarepredictedtobecollectedinagivenyearbyapplyingpublishedcollectionrates
Theusedelectronicscollectedforprocessinginyearyissimplytheproductofthegeneratedquantityinyearyandtheprobabilitythatgeneratedusedelectronicsarecollectedinthatyear, ,asshowninEquation3.
Equation3:Quantitycollectedforprocessinginyeary
,showninFigure37,canbethoughtofasthecollectionrate.Thecollected
quantitywascalculatedforeachownertypebecauseofdifferingcollectionrates.
Figure37:Probabilitytreediagramofpathsdirectlyaftergeneration.LettersandcolorsrefertolifespanstagesinFigure1.TheprobabilitiesofapathtoalifespanstagearerepresentedbyP(lifespanstage),oritscomplementP(lifespanstage’).
TheoverallestimatesandassociateduncertaintyofgeneratedandcollectedquantitiesweredeterminedusingMonteCarlosimulations.Allkeycalculationparameterswereallowedtovarywithinreasonabledistributions.Forexample,saleswereallowedtovaryuniformlytwostandarddeviationsfromthemean.A10,000trialMonteCarlosimulationwasconductedusingOracleCrystalBall®inMicrosoftExcel®.
6.1.1.2.1.4 Literature‐basedMethodB:Calculatehowmanyofthegeneratedproductsarepredictedtobecollectedinagivenyearbyapplyingcollectionratesderivedfromstatecollectionprograms
AsthissectionpertainsonlytoTVs,adescriptioncanbefoundinSection6.1.2.1.3.
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6.1.1.2.2 Survey‐basedMethod
DatausedformanystepsintheSurvey‐basedMethodarefromUSresidentialandbusiness/publicsurveysconductedbyKahhatandWilliamsin2011,withafocusontheyear201025.Forcomputersandmonitors,theresidentialsurveyaskedabouteachitem,whilethebusiness/publicsurveyaskedaboutgroupsofitems.Therefore,theresidentialgenerationandcollectionmethodologyfollowsthebasicapproachtodeterminegenerationandcollectionquantitiesconsistentacrossmoststudiesoutlinedatthebeginningofthechapter,whilethebusiness/publicisamoresimplisticextrapolation,describedinthischapteraftertheresidentialmethod.Afinalquestioninthesurveysaskbasicquestionsaboutthedispositionofabroadsetofusedelectronics.ForTVs,generationandcollectionresultsareextrapolatedfromtheseresponses.
ThefollowingexcerptdescribesthesurveymethodologyemployedbyKahhatandWilliams25:
“Inthisstudytwoonlinesurveyswerelaunchedtocollectprimarydataonadoptionandend‐of‐lifemanagementofpersonalcomputersintheresidentialandbusiness/publicsectoroftheUnitedStates.Theresidentialsectorstudyincluded1000completedsurveysdrawnfromalargerpanelof350,000prospectiverespondentsconstructedbytheconsultingfirmResearchNow.Thesamplechosenwasrepresentativeof2010Censusdatafortheadultpopulationforthefollowingparameters:Gender,State,Age,HouseholdIncome,andEducationalAttainment.Thesurveyconsistedof15questionscoveringthreetopicareas:demographics,computerownershipanduseathome,andcomputerdisposal.Fourhundredcompletesurveyswhereobtainedfromthebusiness/publicsector.ThesamplewasrepresentativeoftheUnitedStatesbusiness/publicsectoraccordingtogeographiclocationandnumberofemployeeswithinacompany.Althoughitwouldbedesirabletohaveasamplematchingthenationaldistributionoforganizations/employeesbyindustrysector(e.g.NorthAmericanIndustryClassificationSystem(NAICS)),thecostofsolicitingsuchasamplewasbeyondavailableeconomicresources.Therespondentpoolwasabout25,000eligibleparticipantsofapanelofITexpertscollectedbytheconsultingfirmOpinionology.ThepanelincludedITdecisionmakersandassetmanagers.Thesurveyquestionnaireincluded15questions.BothsurveyswerelaunchedinApril2011andthequestionsaddressedthe2010calendaryear.Allcompletedsurveyswereexaminedbythesurveycompanyandresearchteambeforeincludedintheanalysis.Theresidentialandbusiness/publicsectorsurveyshadamarginoferrorof3%and5%,respectively,consideringaconfidencelevelof95%.Confidencelevelandmarginoferrorarebasedonsamplesizeandsampledistribution.Surveyquestionnaireandresultsareincludedinsupportinginformation.”
6.1.1.2.2.1 ResidentialComputersandMonitors:Determinethetypicaldistributionoflifespansfortheresidentialproductoveratimeperiod
RawsurveydataprovidedbyKahhatandWilliams25wasutilizedtoestimatethelifespandistributionofresidentialcomputersandmonitorsin2010;thesewerethefocal
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productsofthesurveywhileotherelectronicswereaddressedbriefly.Thebusiness/publicmethoddidnotmodellifespans.
Tocomputethelifespandistributionsforeachresidentialproduct,survivalanalysisVItechniqueswereemployed.Survivalanalysisistypicallyemployedinstudiesofpatientsurvivalofdisease,orofmachinefailure,andtypicallyinvolvefittingtheWeibulldistribution.TheWeibulldistributionisusedinsimilarstudiesaswell15,31,32.Adaptingthatterminologytothisstudywiththeintentofunderstandingthelengthoftimeoneownerusesandstoresanelectronicitem,a“failure”isdefinedastheendofoneperiodofownership,delimitedeitherbygeneration(collectionortrash)orinformalreuse.Incomparisontotheliteraturemethod’sprobabilitytreediagraminFigure36,“failure”occursafter“D.InitialStorage”or“NoInitialStorage”.Thedistributionoflengthofoneperiodofownershipisaninputintothegenerationpredictionmodel,whichiswhyitissoughtversustimeuntilgenerationdirectlyasonemightexpect.Thestepstoestimatethedistributionoflengthofoneperiodownershipλareasfollows,andelaboratedonafterwords:
Overviewofsteps
i. Preparetheresidentialsurveydata.ii. Determinetheageofproductseitheratthepointof“failure”,oratthetimeof
“censor”(aproductiscensoredifitisstillwiththeownerwhensurveyed).Wherepossible,screentheresponsesbytherespondent’sprecisionofestimatingtheyearpurchasedincomparisonestimatingtimeinuseandstorage(cutoffof1yearwasdeemedreasonable).
iii. Determinetheyearthattheproductwaspurchased.iv. UseStata®12.1toproduceKaplan‐Meier(K‐M)survivorcurvesand
subsequentlyWeibullregressionsforalloftheproductstogether,andusethesameK‐McurveandassociatedWeibullregressionforallyearsofpurchaseVII.
v. FitadditionalparametersfortheWeibullregressiontotheK‐Mcurves.vi. TransformtheresultsoftheWeibullregressionintoaprobabilitydensity
function,whichwillbeusedasthedistributionoflengthofoneperiodownership.
vii. DuringtheMonteCarlosimulation,allowtheparametersoftheregressiontovarybetweena95%confidenceintervalandallowtheentiredistributiontoshiftleftandrighttoaccountforallowableerrorintherespondents’precision.Figure41displayssomeofthe10,000laptopdistributionsmodeledduringtheMonteCarlosimulationdescribedinthenextsection,andFigure43displaysthemeandistributionsforeachproduct.
Detailedexplanationofstepsusinglaptopsasacasestudy
VISinghR,MukhopadhyayK.Survivalanalysisinclinicaltrials:Basicsandmustknowareas.PerspectClinRes[serialonline]20112:145‐8.Availablefrom:http://www.picronline.org/text.asp?2011/2/4/145/86872VIIIdeally,estimateswouldbemadeasatrendforeachyear,butthatwasnotdoneduetodatalimitations.Also,ideallyitemswouldbeseparatedintothosethatwerepurchasednewandthosepurchasedusedsincenewproductslikelylastlonger,butthatwasnotpossiblewiththissurveydataset.
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i. Preparetheresidentialsurveydata.
Thesurveydatareceivedfromthesurveyfirmneededtobeconsolidated,becausethedataoriginallywasarrangedbyrespondentinsteadofbyelectronic.Thereweretwosetsofrelevantquestions,requiringseparatepreparation:questionspertainingtothosehadbeen“discarded”,andelectronicsthatwerestillinthehome.Someofthe“discarded”itemswereconsideredtobe“failures”andothers“censored”inTable9.
Table9:DesignationofFailure,Generation,andCollectionbyDiscardType
DiscardType Fail? Category Generated?Disposalviacurbsidegarbagecollection Fail Trash GeneratedRecycledviacurbsiderecyclingprogram Fail Collected GeneratedReturnedtocollectiondepotforrecycling Fail Collected GeneratedReturnedtoretailer Fail Collected GeneratedReturnedtomunicipalityduringaspecialcollectionevent
Fail Collected Generated
Returnedtomanufacturer Fail Collected GeneratedStorageoff‐site Censor NotIncluded NotGeneratedDonatedtofriend/familywithinhousehold Fail InformalReuse NotGeneratedDonatedtofriend/familyoutsideofhousehold Fail InformalReuse NotGeneratedDonatedtoacharitableorganization Fail InformalReuse NotGeneratedOtherdonation Fail InformalReuse NotGeneratedReturnedtosellerafterleaseexpired Fail Collected GeneratedSoldonline(e.g.eBay) Fail InformalReuse NotGeneratedSoldlocally Fail InformalReuse NotGeneratedSoldtoanacquaintance/friend/family Fail InformalReuse NotGeneratedOther Censor NotIncluded NotGeneratedNADidnotdiscard Censor NotIncluded NotGenerated
ii. Determinetheageofproductseitheratthepointof“failure”,oratthetimeof“censor”(aproductiscensoredifitisstillwiththeownerwhensurveyed).Wherepossible,screentheresponsesbytherespondent’sprecisionofestimatingtheyearpurchasedincomparisonestimatingtimeinuseandstorage(cutoffof1yearwasdeemedreasonable).
InTable9,itcanbeseenthatthevastmajorityofrespondentswereinternallyconsistentwhenreportingboththeyearpurchasedandthecorrespondingtimeinuseandtimeinstorageforcomputersandmonitorsathome.Figure38belowillustrateshowtheprecisionmetricwascalculated.
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Figure38:Respondents’internalprecisionofestimatingproductageandtimeathome.Zerorepresentshighprecision.
Notethatthismetriccannotbecalculatedforthoseelectronicsthatwere“discarded”,becausethesurveyaskedsolelyaboutlifespaninthehome,andnotaboutyearofpurchaseof“discarded”products.Theonlyqualitycontrolmetricavailablefor“discarded”electronicswastoensurethatwhenrespondentsreportedaboutthelifespanof“discarded”electronicsandseparatelyaboutthe“discardmethod”,thetypeofelectronicmatchedacrossthetwoquestions(eg.laptopandlaptop,notlaptopanddesktop).Mismatcheswereexcluded.
Equation4:DeterminationofInternalPrecisionofRespondent’s“Censored”Electronics
iii. Determinetheyearthattheproductwaspurchased.
For“censored”electronicsstillinthehome,theyearpurchasedwasgivendirectlybytherespondents.For“discarded”electronics,Equation5belowwasused.
Equation5:DeterminationofYearofPurchaseof“Discarded”Electronics
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iv. UseStata®12.1toproduceKaplan‐Meier(K‐M)survivorcurvesand
subsequentlyWeibullregressionsforalloftheproductstogether,andusethesameK‐McurveandassociatedWeibullregressionforallyearsofpurchase.
ThefollowingcodewasinputintoStata®12.1,andrelevantoutputandcommentsareincluded.
Setdataforsurvivalanalysis:stsetage,failure(failure)
Describedatatoensureitwasprocessedcorrectly:stdescribe
K‐MSurvivalAnalysis:stslist
Thisdata,whichliststheK‐Mcurvedataforthemodeledsurvivalcurveandthe95%confidenceintervaliscopiedintoMicrosoftExcel®forthenextstep.
stsgraph
Figure39:Kaplan‐MeierSurvivalCurveforlaptops
WeibullRegression:
stregyear,dist(weibull)ThisreturnstheinformationabouttheWeibullregressionforthelaptop
dataset.NotethatpisthescalefactorusedtomodelWeibulldistributions.
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Figure40:Stata®Weibullregressionanalysisforlaptops.
stcurve,surviv
ThisgraphsthesurvivalcurvebasedontheWeibullregression;Figure40modelstheK‐MsurvivalcurveinFigure38withtheparametersinFigure39.
Figure41:GraphofWeibullregressionmodelforlaptops
v. FitadditionalparametersfortheWeibullregressiontotheK‐Mcurves.
InordertodefineaWeibulldistribution,boththescaleandshapeparameterareneeded.ItisperhapspossiblebutdifficulttoextracttheshapeparametersfromtheWeibullregressiondata,andthereforethedatafromstslistiscopiedintoMicrosoftExcel®andtheSolveradd‐inisusedtofindtheshapeparametersminimizingthesquarederrorbetweenaninversecumulativeWeibullmodelandtheK‐Msurvivorcurves.
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Figure42:ComparisonbetweenK‐McurvesandOLSfitlaptopWeibullregressioncurvesformean,andlowandhighboundsof95%confidenceinterval.
vi. TransformtheresultsoftheWeibullregressionintoaprobabilitydensityfunction,whichwillbeusedasthedistributionoflengthofoneperiodownership.
UsingtheparametersfoundthroughtheWeibullregression(scaleparameters)andfitwithminimumsquarederror(shapeparameters),thelifespandistributionssoughtforlengthofoneperiodownershiparemodeledwiththeMicrosoft®ExcelWeibull.Distfunction.
Figure43:Distributionoflaptoplengthofperiodofownership
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Figure44:Distributionsoflaptoplengthofperiodofownershipλallowingvariation(randomsample)
Anotherlifespaninputtotheresidentialgenerationpredictionmodelisthedistributionoflengthoftimeuntilanelectronicisreused.Sincenotallelectronicsarereusedandthosethataretendtobeinbettercondition,themoregeneralperiodofownershipislikelylongerthanthetimeuntilanelectronicisreused.Giventhestructureofthesurveyquestions,thebestapproximationisfoundbymodelingthedistributionoflifespansofelectronicspreviously“discarded”intheInformalReusecategory(seeFigure44).Thisdoesnotcaptureelectronicsthatweresenttorecyclersandsubsequentlyreused,norelectronicsstillinthehomewhichwerepurchasedused.Still,itisareasonableapproximation.
BelowinFigure45isahistogramofthedistributionoflengthoftimeuntilanelectronicisreusedδ.Themeanwasallowedtovary+/‐2yearsforamarginoferror,andthestandarddeviationwasallowedtovary+/‐10%intheMonteCarlosimulation.Thesurveydataarethe100laptopswhichwere“discarded”forInformalReuse(seeFigure45).Thisisinputinthegenerationpredictionmodel.
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Figure45:Histogramandfittedlognormaldistributionsoflengthoftimealaptopiswithanowneruntilinformalreuseδ
6.1.1.2.2.2 ResidentialComputersandMonitors:Calculatehowmanyresidentialproductsarepredictedtobegeneratedinagivenyearusingthesalesandlifespaninformation
Thegoalofthisstepistoestimatehowmanyresidentialproductsaregeneratedinagivenyearandsowhich“discard”activitiesleadtogenerationisdefinedfirst;aswiththeliteraturemethod,informalreuseisnotconsideredgeneration(seeFigure36).Next,theapproachistomodelthequantityofelectronicsthatareonlyusedoncebeforegeneration(O),thosethatareinformallyreusedbeforegeneration(I),andthatareformallyreusedafterafirstroundofgenerationandcollection(C).UsingFigure45fromtheliterature‐basedmethod,thequantitygeneratedineachyearywasmodeled,withthestartingyearfortheperiodofownershipofreusepurchases(IandC)shiftedbythedistributionoflengthoftimeuntilanelectronicisreused.Thesamelengthofperiodofownershipλwasappliedtousedandnewproductsgivendataconstraintsrelatedtothesurveyquestions;ideallytherewouldbeseparatedistributionssinceusedproductslikelyhaveashorterfunctionaluseperiod.
Inordertodetermineinwhichyearyeachgroup(O,I,andC)islikelytobegenerated,itisassumedthatreusepurchases(IandC)inagivenyearsarestronglycorrelatedwithnewsalesinthesameyears.Itmakessensethatpopularityofusedproductstrendswiththepopularityofnewproducts.Theratiosβofusedtonewpurchasesinthesurveydatafrom2000to2010weremodeledinordertocapturethisphenomenon.Thenextstepwastoapproximatethefractionαofusedpurchasesthatoccurredthroughinformalreuse(I)ascomparedtoformalreuseaftergenerationandsubsequentcollection(C).Lastly,allofthenewpurchasesinagivenyearwereassumedtoundergooneusebeforegeneration(O)lessthosewhicharepredictedtobeinformallyreusedinfutureyears(I).ThetotalofthesethreegroupsisshownsimplyinEquation6.
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Equation6:TotalResidentialGenerationofUsedElectronicsinYeary
6.1.1.2.2.3 ResidentialComputersandMonitors:Calculatehowmanyoftheresidential
generatedproductsarepredictedtobecollectedinagivenyearbyapplyingresidentialcollectionrates
ThisstepismethodologicallysimilartothatusedintheLiterature‐basedmethod;thecalculationfollowsEquation3(repeatedbelowforconvenience).Thedifferenceisthatthesourceoftheresidentialcollectionratescalculatedsolelyfromsurveyresults,includingtheKahhatandWilliams25study.ThereweresixdifferentrepresentativegroupsofUSResidentialcomputerownersfrom2005to2012;somesurveyscoveredtwoyears28,33‐35.Toaccountforuncertaintyinthesurveydataandregression,theestimatedcollectionrateforagivenyearwereallowedtovary+/‐10%intheMonteCarlosimulation.Figure46belowprovidestheresultsforlaptops28,33‐35.
Equation3:Quantitycollectedforprocessinginyeary
Figure46:EstimatedUSresidentialusedlaptopcollectionratesacrossseveralsurveys.
6.1.1.2.2.4 Business/PublicComputersandMonitorsandTVsGenerationandCollectionSurvey‐basedSteps
Asareminder,theresidentialsurveyaskedabouteachitem,whilethebusiness/publicsurveyaskedaboutgroupsofitems.Therefore,thebusiness/publicgenerationandcollectionstepsareamoresimplisticextrapolationbasedonsurveyandsalesdata.Afinalquestioninthesurveysaskbasicquestionsaboutthedispositionofabroadsetofusedelectronics.ForTVs,generationandcollectionresultsareextrapolatedfromtheseresponses.Inthisapproach,theresponsestosurveyquestionsaboutmostrecentpurchasesinyear2010weretabulated;notethatbecausethisquestionaskedabout
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mostrecentpurchases,thereisnotafulltimeseriesofpurchases.AScaleFactorforyear2010wasfoundforeachproduct(laptops,desktops,CRTandFlatPanelmonitors)usingEquation7.
Equation7:ScaleFactorforBusiness/PublicGenerationandCollectionsteps
BothinputstotheequationwereallowedtovaryinaMonteCarlosimulation;the
Salestovaried+/‐10%andtheSurveydatatovarywithintheboundsofthesurveyconfidenceinterval(+/‐5%).SincetheScaleFactorsdifferedsomewhatforeachproduct,duetoinaccuraciesineitherthesurveyorthesalesdata,anaveragemean,minimumandmaximumScaleFactoracrosslaptops,desktops,andFlatPanelmonitorswasfoundandappliedtoallproducts.SalesdatereportednosalesofCRTmonitorsin2010,andthereforetheScaleFactorswas0,whichbroughttheoverallaveragedown.Table10belowpresentsthescalefactorsbyproduct,andincomparisontoascalefactorbasedonsurveyedemployeesatfacilitiesandtotalemployees;theproductscalefactorismuchlowerthantheemployeescalefactor,whichmaybebecausesurveyedbusinesseshavecomputerswhereasmanycompaniesdonot.
Table10:Business/Public2010ComputerandMonitorScaleFactors
ScaleFactor Mean Min Max
Desktop 922 837 1,006
Laptop 1,385 1,258 1,511
FlatPanelMonitor 891 809 973
CRTMonitor 0 0 0
ProductAverage 799 726 873
Employee 1,878 1,706 2,050
Toarriveat2010generationandcollectionestimates,thereported2010generatedandcollectedproductstabulatedfromsurveyweremultipliedbytheScaleFactors,asshowninEquation8andEquation9.TheScaleFactorswereallowedtovarybetweentheminimumandmaximumvaluesinaMonteCarlosimulation.
Equation8:Business/Public2010Generation
Equation9:Business/Public2010Collection
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6.1.2 DataandIntermediateResults
6.1.2.1 TVsToquantifygenerationandcollectionofusedTVs,Literature‐basedMethodB,
Survey‐basedMethod,andStockandFlowmodelsareused.
6.1.2.1.1 Sales
SeveralsourcesoffershipmentorsalesdataasshowninTable11.Shipmentshererefertomanufacturershipmentsintothechannel,whilesalesrefertoactualtransactionswithendusers.Salesarethereforeexpectedtobesomewhatlowerthanshipments.Salesdataismorerepresentativeoftheproductsavailableforuseandsubsequentgeneration.
Table11:SalesDataSourcesforTVs
Source TVstype DataType OwnerTypePurchaseYearsAvailable
Urban,etal.,2011(CEAdata)36
ColorCRTMonochromeCRTFlatPanelProjections
Sales Combined 2000‐2010
EPAa,20088EPAb,20119(CEA&IDCdata)
ColorCRTMonochromeCRTFlatPanelProjections
Sales Combined
1980‐2006(CEA)2007‐2011(IDC)
Euromonitor,201237
AnalogDigitals(LCD/LED/PDP/Other)
Sales Combined 2004‐2016
USCensusBureau(2012)I Combined
DomesticManufacturerShipments
Combined 2009
Therearethreedatasourcestogetthesalesdata,anditisnecessarytoevaluatetheuncertaintyandmakenecessaryadjustments.Thesalesdatainyears2000‐2010wasallowedtovaryonestandarddeviationfromthemeanofthethreedatasourcesintheMonteCarlosimulation.Thesalesdatainsurroundingyears(before2000andafter2010)withasingleCEAdatasourcewereallowedtovaryuniformlyonestandarddeviationfromthemean,bygivenanapproximate10%ofCorrelationofVariances(COV).
Figure47andFigure48displaytheTVssalesestimatesconsidered,aswellasthemodeledmean.Basedonthedataavailability,theTVshaveseparatedintoCRTTVs(AnalogTVs,ColorandMonochromeTVs)andFlatPanelTVs(LCD,LED,PDP,ProjectionsandotherDigitalTVs).
IUSCensusdata,ShipmentsofConsumerElectronics:2009and2008,Availableat:http://www.census.gov/compendia/statab/cats/manufactures.html
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Figure47:CRTTVsSalesEstimatesforVariousDataSources,ModelParameters
Figure48:FlatPanelTVsSalesEstimatesforVariousDataSources,ModelParameters
Ifitisrequiredtomodeleachownertype’sgenerationseparately,salesneedtobemodeledbyownertypeaswell.Differenttocomputers,theresidentialconsumersdominatethemarketfortheTVs.Oftheavailablesalesdatasourcesconsulted,thereisnodatasourcedistinguishedbyownertype.
6.1.2.1.2 Lifespan
Ideally,lifespanstageassumptionswouldbedisaggregatedbyTVstype,ownertype,andpurchaseyearanddistinguishingfirstuse,reuse,andstorage.Table12presentsthesourcesused.ManyestimatesdonotdifferentiatebetweenCRTandFlatPanelTVs.SomemodelgeneratedTVsusingstaticlifespans,whileothersaccountforshiftingtrendsinlifespans.“Totallife”referstolifespanstagesuntilgeneration.
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Table12:LifespanDataSources
Source TVType OwnerType Years Lifespanstages
Aoe,200338 CRTandFlatPanel
Combined 2002 Totallifetime
Feng&Ma,200939 Combined Combined 2009 Totallifetime
Liuetal.,200640 Combined Combined 2005 Totallifetime
MilovantsevaandSaphores,201241 Combined Combined 2010 Totallifetime
ConsumerReports,200642
Combined Combined 2005 Totallifetime
USEPA,2008&20118,9
CRTandFlatPanel
Combined1980‐2010,Static
Totallifetime
KahhatandWilliams,201211**
CRTFlatPanel
Residential 2008 Initiallifespanandinitialstoragelifespan
**USNationalsurveyin2008.Moredetaileddataisavailablejustbasedoninternaldatasharing.
LifespansweremodeledseparatelyforthefollowingTVstypes:CRTandFlatPanel.Therefore,therelevantestimatesforeachTVtypefromTable13wereincludedinthedevelopmentoflifespanstagelengthestimates.
Withagoalofmodelinggenerationinyear2010,theanalysisincludedlifespanstageestimatesfromtwentyoneyearspriorin1989,whichallowsforageneroustotallifespanofTVspurchasedin1989.BecausemostofthedatasourcesonlyreportedthetotallifespananddonotdifferentiatetheTVstype,lifespanstageestimatesforeachTVtypewereonlyincludedthesurveydataprovidedbyKahhatandWilliams.ThemeanµandstandarddeviationσforeachlifespanstageforeachTVtypeareshownin
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Table14.
KahhatandWilliamsconductedanationalsurvey(with1000questionnaires)toinvestigateuseofelectronics(TVs,MobilephoneandComputers)in2008,includingtheevaluationoftheinitialuselifespan(Howoftenisthedevicereplaced?)andinitialstoragelifespan(Howlonghaveyoukeptunuseddevicesbeforediscardingthem).Theinitialuselifespanisseparatedintothelifetimesof:lessthan1year,2years,3‐4years,5‐10yearsandabove10years;and,theinitialstoragelifespanwasseparatedintothelifetimesof:lessthan3months,1year,2‐3years,4‐5yearsandabove5years.Basedonthefrequenciesfellintovariousscopesofthelifetime,thegoodnessofdistributionfithasbeenevaluatedfortheinitialuselifespanandinitialstoragelifespan,respectively.Boththeµandσarederivedfromthelognormaldistributionfit,whichisrankedbyoneofthebestfit.Thelognormaldistributionhasalsobeenwidelyacceptedtorepresentrealsituationoftheusebehaviors.However,therearenotsurveysdatarelatedtothedomesticreuseandreusestoragelifetime,whichareassumedtobehalfoftheinitialusetimeandinitialstoragetimerespectively.
Table13:ModeledLifespanStageLengths(Years)
TVsB.InitialUse
D.InitialStorage*
C.DomesticReuse
E.ReuseStorage
CRT µ 8.01 1.69 4.01 0.85
σ 3.09 2.29 1.55 1.15
FlatPanel µ 6.12 1.69 3.06 0.85
σ 2.90 2.29 1.45 1.15
*TherewereonlysurveysdataforinitialuselifespanfortheFlatPanelTVs,theinitialstorageforFlatPanelisthereforeassumedtobethesametoCRTTVs.
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Table14:ProbabilityofPathsLeadingtoGeneration(CRTTVs)
Source ScopeStoragerate Reuserate ReuseStorage
rate*
Collectedforprocessing
rate
Reuserateafter
processing
P(D) P(D’) P(C) P(C’) P(E) P(E’) P(F) P(F’) P(H) P(H’)
MTI.,200343
WAKingCounty
surveys(2003)17% 83% 9% 92%
Florida,200344
Floridasurvey(2002,2003) 16% 84% 8% 92%
ConsumerReports,200642***
NationalSurveys(2005)
46% 54% 40% 60%
KahhatandWilliams,201211
NationalSurveys(2008)
57% 43% 42% 58%
KahhatandWilliams,2012
NationalSurveys
(2010)(CRT)6% 94% 51% 49% 3% 97% 64% 36%
KahhatandWilliams,2012
NationalSurveys
(2010)(FP)3% 97% 46% 54% 1.5% 98.5% 63% 37%
EPAb,20119
NationalInd.Surveys(2007)
30% 70%
EPAb,20119
NationalInd.Surveys(2010)
33% 67%
Daoud,2011(ISRI)45
NationalInd.Surveys(2011)
19% 81%
WisconsinDNR,201246
StatewideHousehold
surveys(2006) 51% 49% 30% 70%
WisconsinDNR,201246
StatewideHousehold
surveys(2010) 64% 36% 68% 32%
CCGI.,2008(WA)43
Countysurveys(2005) 41% 59% 38% 62%
CCGI.,2008(WA)43
Countysurveys(2007) 36% 64% 53% 47%
St.Louis,2007I
Citysurveys(2007) 51% 49% 51% 49%
Min 16% 36% 3% 40% 19%Max 17% 64% 9% 64% 30%Mean 13.0% 49.6% 6.5% 48.3% 27.3%
StandardDeviation 6.1% 8.8% 3.0% 13.2% 7.4%
*ReuseStoragerateisassumedhalfofInitialStoragerate;**Detailedsurveysdata(2008and2010)areprovidedbytheKahhatandWilliamsintermsofinformalsharing,andtheTVsincludetheCRTandFlatPanel(FP),,alloftheothersourcesdonotdifferentiatetheTVstype;***WhileitisunclearwhethertheTVscompriseboththeCRTandFP,weassumedCRTTVsdominatedthegenerationin2006.
ISt.Louis,2011,CitywideResidentialRecyclingTelephoneSurveyin2007Availableat:http://stlouis‐mo.gov/government/departments/street/refuse/recycle/recycling‐survey.cfm
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ThevaluesofP(D),P(C),P(E),P(F)andP(H)applicabletotheTVstypeswereallowedtouniformdistributionintheMonteCarlosimulationof .ComplementsP(D’),P(C’),P(E’),P(F’)andP(H’)arefoundbytakingthedifferencewith100%.
TheprobabilitiesofeachpathwayP(ϖ)andmeantotallifespanlengths byTVstypeareinTable15.SimilarityacrossTVstypesforP(ϖ)reflectstheabsenceofspecificprobabilityestimatesforeachTVstype.
Table15:MeanProbabilitiesandMeanTotalLifespansof6PathstoGeneration
ScopeCRT TVs FlatPanelTVs
P(ϖ) P(ϖ)
Path1(ϖ=1) 6% 9.7 5% 7.8
Path2(ϖ=2) 6% 13.7 5% 10.9
Path3(ϖ=3) 1% 15.3 0.5% 12.5
Path4(ϖ=4) 44% 8.0 45% 6.1
Path5(ϖ=5) 46% 12.0 47% 9.2
Path6(ϖ=6) 4% 13.7 4% 10.9
6.1.2.1.3 Literature‐basedMethodB:StatesCollectionProgram
Therearesomeworksgoingonaroundthecountrytopromotetheusedelectronicswasterecycling,including25statespassinglawsone‐wasterecycling,ofwhichmosthavepassedthedisposalbanII.
MostofthestateswiththeelectronicswasteregulationhaveasystemmodeledaftertheEUapproachcalledExtendedProducerResponsibility(EPR),whichrequiresthemanufacturestopayforelectronicsrecyclingcosts.CaliforniainsteadutilizesanAdvancedRecoveryFee(ARF),whichconcentratesonconsumersofelectronics.
Therefore,thestatesoftheUShavebeenclassifiedintotwogroupsforestimationonthecollectionratefortheyearof2010:
o Stateswithprogram:Thestateswithmandaterecyclingregulation,disposalbanorbothin2010;
o Stateswithoutprogram:Thestateswithout(orineffective)regulationsanddisposalbanin2010.
Thecollectionrateisbasedonthestatewideelectronicswasteormunicipalsolidwastestatisticreportsorsurveys.Whilemostofstateswithprogramshavereportedthedataoftotalelectronicwastecollectionforoneorseveralofthepastyears,onlyafew
IISustainableElectronicInitiative(2012),SummaryofUS.StateLawsonElectronicWasteandDisposal,Banshttps://ideals.illinois.edu/bitstream/handle/2142/16301/State%20Legislation_May09.pdf?sequence=2
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statesreportbreakdownsbyproducttype,showninTable1647.Manystatesdonotyethave2010data.Nostatesreportedmobilephoneorlaptopcollectiondata.
Table16:StatewideUsedElectronicsCollection(lbs)forThoseStateswithStatisticsin2010
StatePopulationFraction
UsedElectronics TVs Desktop Monitor
California 12.1% 193,720,571 Hawaii 0.4% 3,237,516 Illinois 4.2% 30,151,985 Maine 0.4% 5,366,578 3,960,387 1,208,586
Maryland 1.9% 17,031,978 Minnesota 1.7% 34,316,395 Missouri 1.9% 2,215,903 NorthCarolina
3.1% 9,154,064
Oklahoma 1.2% 5,514,486 Oregon 1.2% 24,174,077 14,972,860 2,897,973 6,520,439
RhodeIsland 0.3% 2,820,880 Texas 8.2% 24,391,194 Virginia 2.6% 4,480,573
Washington 2.2% 39,809,277 24,969,639 3,759,919 10,738,240WestVirginia 0.6% 1,646,155 Wisconsin 1.8% 20,643,759
Tomakefaircomparisons,itisimportanttoknowthattheseprogramsarenotallacceptingthesameproducts,andsomecollectfrommorethanjusthouseholds.Thus,thecollectionrate showninEquation10forseveralstatesreportwhichbreakdownsbyproducttype(TVsandcomputerproducts)havebeenselectedtorepresentthecollectionrateforgroup(withprogram)ThegenerationofthespecificelectronicstypeintheUSreferstheestimationfortheEPAreport(USEPA,2011).
Equation10
Sofar,thereisalmostnostatewithoutprogramwhichhasreportedthecollection
number.However,someofthestatesfromtwogroupshavereportedthedisposalquantityoftheelectronicswithintheirstatewidemunicipalsolidwastecompositioncharacterizationreportsduringthepastseveralyears,showninTable17.
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Table17:StatewideUsedElectronicsDisposalRate,PercentageofMSWDisposalWeight
States ReportYear
PrograminReportYear?
TVsandMonitor
Mobilephone
ComputerRelated
UsedElectronicsTotal*
California48 2008
Withprogram
0.20% 0.10% 0.50%California49 2003 0.60% 0.30% 1.20%Maine50 2011 0.92%
Maryland51 2009 1.80%Massachusetts52 2010 1.10% 0.90% 4.10%NewYorkStateI 2010 1.40%
Oregon53 2009 0.38% 0.08% 1.53%Washington54 2009 0.70% 0.10% 1.50%Connecticut55 2009
Withoutprogram
1.00% 0.40% 2.10%Delaware56 2006 1.50%Florida57 2007 2.70%Georgia58 2005 0.10% 0.10% 2.00%Illinois59 2008 0.20% 0.40% 1.30%Indiana60 2009 0.11% 0.02% 0.14% 1.23%Iowa61 2011 0.30% <0.01% 0.40% 2.30%Iowa62 2005 0.04% <0.01% 0.15% 1.70%
NewYorkCity63 2004 0.15% <0.01% 0.19% 0.85%Oregon64 2005 0.54% 0.30% 1.98%Oregon65 2002 0.67% 0.32% 1.91%
Pennsylvania66 2001 1.50%SouthDakota67 2007 0.15% 0.01% 0.24% 2.91%Tennessee68 2008 1.66%Wisconsin69 2009 0.60% 0.30% 2.60%Wisconsin70 2001 0.70% 0.10% 2.50%
*Someofthestate’sreportalsoincludesthecharacterizationofotherelectronics,e.g.,largehomeapplianceandmiscellaneoussmallelectronicandelectricproducts.
BasedonTable17,thereissomeevidencetosuggestthatthetwogroupshaveasimilardisposalrateoftheTVspercapita.Thet‐testonthedisposalratealsoshowsthatthereisnosignificantdifferencebetweenthemeansofthetwogroups.Ifweassumethegenerationoftheelectronicsforthetwogroupsareconsistent,thecollectionrateoftheelectronicwasteshouldbesimilar.Wethereforeassumedthecollectionratesfortwogroupsarethesame,althoughwerecognizethatthisdoesnotaccountforthepossibilitythatinstateswithoutprogramstherecouldbemorestorage,andownersdelaytakingactionontheirusedelectronicsuntilaprogramarises.
AsidefromthegovernmentalExtendedProducersResponsibility(EPR)andAdvancedRecyclingFee(ARF)recyclingprogram,somemanufacturers,retailers,serviceprovidersandsomesmallrecyclersaremakingtheefforttotakebackusedelectronicsbeyondwhatthelawsrequire.Thatmeansmanyfirms,non‐governmentagenciesandnon‐
IMSWMaterialsCompositioninNewYorkState,http://www.dec.ny.gov/chemical/65541.html
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profitsareactivelypromotingrecycling,andcommunitycollectioneventsarecommoninmanyareasII.Table18summarizesthepotentialapproachesfortheTVrecycling.Duetotheunavailabilityofdataformostofthepaths,thecollectionratebasedonstaterecyclingwhichisusedisexpectedtobeanunderestimateofthetotalcollectionrate.Table19summarizesthecollectionratesbytwoapproaches.
Table18:2010TVsCollectionApproachesEvaluation
CollectionPath ExamplesDatacharacterization
Dataavailability
Breakdownproducts Historicaldata
Governmentmandated
StateswithEPRorARFprograms
MostStates
Onlyafewstates
Onlyafewstates
Manufacturer Dell,Apple,Samsung,Lenovo,etc.
Few No Veryfew
Retailers BestBuy,Staples,Lowes,OfficeDepot,etc.
Few No Veryfew
Serviceproviders Verizon,AT&T,etc. Few No NoHandlers Recycler,
Repairer/Refurbisher,etc.Few No
Donation&Reuseoptions
CharityAmerica,GoodwillIndustries,SeriousGood,etc.
No No
Drop‐off&Mail‐In Communitycollectionevent No No
6.1.2.1.4 Survey‐basedMethod
BasedonthenationalsurveysconductedbyConsumerReport(2006)42,surveysin2008and2010byKahhatandWilliamsshownin
IIElectronicsTakeBackCoalition,2011.E‐wasteexportlegislationisthemostimportantactionthefederalgovernmentcantakeone‐wasteproblem.Availableat:http://www.electronicstakeback.com/2011/06/23/e‐waste‐export‐legislation/
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Table14,itwasfoundthat40%and60%oftheusedTVshavebeencollectedforprocessingin2006and2010respectively.Whilethesurveyshadbeenconductedbydifferentresearches,theresultsarestillcomparable.ThevaluesofP(F)applicabletotheTVswereallowedtovarywithinreasonableboundsofauniformdistributionintheMonteCarlosimulationof .Table19summarizesthecollectionratesfoundbythetwoapproaches.
Table19:2010TVsCollectionRates
Statesgroup Product Mean Min Max
Literature‐basedMethodB
Stateswithprogram AllTVs 47% 40% 54%Stateswithoutprogram AllTVs 47% 40% 54%
Survey‐basedMethod
National CRTTVs 49% 40% 64%National FlatPanel
TVs62% 57% 65%
6.1.2.1.5 StockandFlowModelforModelingTVsGeneration
6.1.2.1.5.1 Methodology
Besidesusingsalesobsolescencemodeltoquantifythegenerationofusedelectronics,thereisanotherpotentialmethodtoestimatethegeneratedquantityinagivenyearn,whichisexpressedinEquation11.Mulleretal.(2009)presentedasimilarequation.Thismethodisusefulwhenboththesalesdataandstockdataareavailable.
Equation11
6.1.2.1.5.2 Stockdata
TwosourcesofresidentialTVstockdatawerefoundtoprovidethestockdata,thoughbotharebasedonTVBasics(2012)IIIcitingNielsen2010.Theinstalledbaseestimateisfromthereportdirectly,whilethepossessioninthehomeestimatecombinedUScensusdatain200936,FloridaElectronicResidentialSurveyin2003,andthepenetrationisfromNielsensurvey(TVBasics2012).ThestockdatadoesnotdifferentiatethetypeofTVsbetweenCRTandFlatPanel.Figure49presentsthetrendsovertimechange.BecausethereisminordifferencebetweentheInstalledbaseandpossession,thusweusedtheaveragevaluetorepresentthestockofTVsintheUShome.Accordingly,thehistoricgenerationfortheTVscanbeestimated.
IIITelevisionBureauofAdvertising,Inc.(2010,TVBasics),http://www.tvb.org/media/file/TV_Basics.pdf
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Figure49:TVsinUSHomes
6.1.2.1.5.3 ResultsandComparison
Figure50presentsacomparisonofthisstudy’sTVgenerationfoundwiththeSales‐ObsolescencemodelinLiterature‐basedMethodandStockandFlowmodelandEPAestimates.Theresultsareallcomparable.Thissuggeststhatthoughthereisnotreadilyavailablestockdataforotherproducts,thisstudy’sLiterature‐basedMethodisvalidforgenerationestimates.
Figure50:ComparisonoftheGeneratedUsedTVswithVariousModels
6.1.2.1.6 UnitWeight
Inordertoquantifythegenerated,collectedandexportedusedelectronicsinweight,theunitweightdataismultipliedbythequantity.WhilerecentcollectiondatafromWashingtonandOregonwasusedforcomputersandmonitors,theTVdatadidnotdifferentiatebetweenCRTTVsandFlatScreenTVs.Therefore,theunitweightdataforTVsaretakenfromtheUSEPAreport(EPAb,2011):ElectronicsWasteManagementintheUnitedStatesThrough2009.Belowisanexcerptofthemethod.
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“Toconvertthenumberofelectronicproductssoldintotonnagessoldforeachmodelyear,wecollecteddataonthetypicalweightofindividualelectronicproductsbymodelyear.DatafromtheFloridaDepartmentofEnvironmentalProtection(DEP)wereusedtodevelopweightestimatesfordesktopCPUs,hard‐copydevices,PCFlatPanels,andCRTTVspriorto2008.Fortheremainingcategories,estimatesweretakenfromConsumerReportsAnnualandMonthlyBuyingGuides(from1984to1999)andonlineinformation.WeupdatedunitweightdatafordesktopCPUs,portables,multi‐functiondevices,mobiledevices,andflat‐panelTVsinthe2008,2009,and2010model‐yearsusing2008and2009ConsumerReportsBuyingGuidesandonlinemanufacturerspecificationsheets.1Foreachtypeofproduct,wesampledweightsacrossarangeofmodelsizestocalculateatypicalweight.Wewereunabletocalculateasalesshare‐weightedaverageweightforeachproduct,however,becausethedataonthesalesshareofindividualmodelswithineachtypeofproductwerenotavailable.”
6.1.2.1.7 SensitivityAnalysis
Theassumptionsthatcontributedmosttothevariance,representedbyerrorbarsinFigure7,areshowninFigure51.forgenerationestimatesandcollectionestimates.
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Figure51:ContributiontoVarianceofGenerationandCollectionEstimatesofUsedCRTTVsin2010
Themajorcontributorswerethelengthoftheinitialuselifespanstageandthesalesestimate.Thissuggeststhatfortightergenerationestimates,tighteruselifetimeestimatesshouldbeatoppriority,followedbymoreaccuratesalesdataestimates.Asonewouldexpect,thecollectionrateswerethetopdriverofvarianceinthecollectionestimates,followedbythesamedriversforthegenerationestimates.
6.1.2.2 MobilePhonesToquantifygenerationandcollectionofusedmobilephones,Literature‐based
MethodAisused.
6.1.2.2.1 Sales
SeveralsourcesoffershipmentorsalesdataasshowninTable20.Shipmentshererefertomanufacturershipmentsintothechannel,whilesalesrefertoactualtransactionswithendusers.Salesarethereforeexpectedtobesomewhatlowerthanshipments.Salesdataismorerepresentativeoftheproductsavailableforgeneration.
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Table20:SalesDataSourcesforMobilephone
Source DataType OwnerTypePurchaseYearsAvailable
EPAb,20119(InformInc.data)
Sales Combined 1995‐2014
EPAb,20119(IDCdata) Sales Combined 2004‐2009
IDC,201171 Sales Combined 2010‐2015Urban,etal.,2011(CEAdata)36 Sales Residential 1985‐2004Euromonitor,201272 Sales Residential 2004‐2016USITC,2010(TIAdata)73 Sales Residential 2004‐2008
USCensusBureau(2012)IDomesticManufacturerShipments
Combined 2007‐2011
Themobilephonesaleshavebeenseparated intoResidentialandBusiness/Publicowner types in order to model generation by owner type. Business/Public sales wereassumedtobetheremainderofCombinedsaleslessResidentialsales.Inyearswherethereweremultiple data sources, themean and standard deviation of the sale quantitywerefound. Inyearswithasingledatasource,themeanwasallowedtovary10%inaMonteCarlo simulation. Figure 52 and Figure 53 display the mobile phones sales estimatesconsidered,aswellasthemodeledmean.
Figure52:MobilePhoneSalesEstimatesforVariousDataSources
IUS.CensusBureau,Telecommunications–Summary.2010http://academicarchive.snhu.edu/bitstream/handle/10474/2007/mq334p105.pdf?sequence=1
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Figure53:MobilephoneSalesEstimatesforModelParameters
6.1.2.2.2 Lifespan
Ideally,lifespanstageassumptionswouldbedisaggregatedbyownertype,purchaseyear,andlifespanstage(firstuse,reuse,andstorage).Table21presentsthesourcesused.Manyestimatesdonotdifferentiatebetweenresidentialandbusiness/publicownertypes.Somemodelgeneratedmobilephoneusingstaticlifespans,whileothersaccountforshiftingtrendsinlifespans.
Table21:LifespanDataSources
Source OwnerType Years Lifespan stagesJangandKim,201074
Combined 2002 Timeuntilgeneration
Yuetal.,201075 Combined 2009 Timeuntilgeneration
PolakandDrapalova,201276
Combined 2005 Timeuntilgeneration
Wilhelmetal.,201177
Combined 2010 Initial use
2011,USEPA9 Combined 1980‐2010
Timeuntilgeneration(staticestimateacrossallyears)
ISG,201078 Combined 2007 Initialuse,initialstoragelifespan
KahhatandWilliams,201211
Residential 2008 Initialuse,initialstoragelifespan
Lifespansweremodeledasthesameforresidentialandbusiness/publicownertypes.Therefore,therelevantestimatesfromFigure44wereincludedinthedevelopmentoflifespanstagelengthestimates.
Becausemostofthedatasourcesonlyreportedthetotallifespananddonotdifferentiatetheownertype,lifespanstageestimatewasonlyincludedthesurveydata
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conductedbyKahhatandWilliamsin2008.ThemeanµandstandarddeviationσareshowninTable22.
KahhatandWilliamsconductedanationalsurveywith1,000questionnairestoinvestigateuseofelectronics(TVs,MobilephoneandComputers)in2008,includingtheevaluationoftheinitialuselifespan(Howoftenisthedevicereplaced?)andinitialstoragelifespan(Howlonghaveyoukeptunuseddevicesbeforediscardingthem).Theinitialuselifespanisseparatedintothelifetimesof:lessthan1year,2years,3‐4years,5‐10yearsandabove10years;and,theinitialstoragelifespanwasseparatedintothelifetimesof:lessthan3months,1year,2‐3years,4‐5yearsandabove5years.
Boththeµandσarederivedfromthelognormaldistribution,whichisrankedtobeoneofthebestfit.BesidestheWeibulldistribution,thelognormaldistributionhasalsobeenwidelyacceptedtorepresentrealsituationoftheusebehaviors.However,therearenotsurveysdatarelatedtothedomesticreuseandreusestoragelifetime,whichareassumedtobehalfoftheinitialusetimeandinitialstoragetimerespectively.
Table22:ModeledLifespanStageLengths(Years)
Mobilephone
B.InitialUse
D.InitialStorage*
C.DomesticReuse
E.ReuseStorage
µ 2.54 1.7 1.3 1.7σ 1.5 2.3 0.7 2.3
6.1.2.2.3 PathstoGeneration
FollowingFigure35andTable8,Table23presentsthesourcesoftheseprobabilityestimatesandtheirapplicability.Noneofthestudiesdifferentiatetheownertypes.Thus,thesamepathstogenerationandsamecollectionrateshavebeenassumedforresidentialandbusiness/publicownertypes.
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Table23:ProbabilityofPathsLeadingtoGeneration
Source ScopeStoragerate Reuserate
ReuseStoragerate*
CollectionRate
Reuserateafter
processingP(D) P(D’) P(C) P(C’) P(E) P(E’) P(F) P(F’) P(H) P(H’)
ConsumerReports,200642
NationalSurveys(2005)
57% 43%
58% 42%
KahhatandWilliams,2012
NationalSurveys(2008)
63% 37% 60% 40%
KahhatandWilliams,2012
NationalSurveys(2010)
16% 84% 64% 36% 8% 92% 59% 41%
EPAa,20119
NationalInd.Surveys(2007)
38% 62%
EPAb,20119
NationalInd.Surveys(2010)
42% 58%
Daoud,201145(IDC)
NationalInd.Surveys(2011)
WisconsinDNR,201246
Statewidesurveys(2006)
52% 48% 30% 70%
Hanksetal.,200879
Univ.Surveys2006(IN)
53% 47% 27% 74%
Wilhelm,201177
Univ.Surveys2010(IL)
67% 33% 34% 67%
OverallMean 45% 59% 23% 52% 40% OverallStandard
Deviation 26% 6% 13% 15% 3%
TheprobabilitiesofeachpathwayP(ϖ)andmeantotallifespanlengths areinTable24.
Table24:MeanProbabilitiesandMeanTotalLifespansof6PathstoGeneration
ScopeMobilephone
P(ϖ)Path1(ϖ=1) 17% 4.2Path2(ϖ=2) 22% 5.5Path3(ϖ=3) 6% 7.2Path4(ϖ=4) 25% 2.5Path5(ϖ=5) 31% 3.8
Path6(ϖ=6) 8% 5.5
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6.1.2.2.4 Collection
Sincemostofthestatesdonotincludethemobilephoneintotherecyclingprogramordisposal.Thereisrelativelylittledatafromstatereports.Thus,onlythesecondmethodissuitableforthecollectionrate.BasedonthenationalsurveysconductedbyConsumerReport(2006)42,KahhatandWilliams’surveys(2008and2010)showninTable25,itwasfoundthat57%and61%oftheusedmobilephonehavebeencollectedforprocessingin2006and2010respectively.Whilethesurveyssamplesarenotconsistent,theresultsarestillcomparable.
Table25:2010MobilePhoneCollectionRates
Statesgroup Mean Min Max
Overall(Literature-based Method B) 59% 57% 61%
*Thestatesreportswithoutbreakdownownertypes.
6.1.2.2.5 UnitWeight
Inordertoquantifythegenerated,collectedandexportedusedelectronicsinweight,theunitweightdataismultipliedbythequantity.WhilerecentcollectiondatafromWashingtonandOregonwasusedforcomputersandmonitors,mobilephonedatawasnotincludedsincemostcollectionprogramsdonotincludemobilephones.Therefore,theunitweightdataforCRTTVsandmobilephonesaretakenfromtheUSEPAreport(EPAb,2011):ElectronicsWasteManagementintheUnitedStatesThrough2009.Belowisanexcerptofthemethod.
“Toconvertthenumberofelectronicproductssoldintotonnagessoldforeachmodelyear,wecollecteddataonthetypicalweightofindividualelectronicproductsbymodelyear.DatafromtheFloridaDepartmentofEnvironmentalProtection(DEP)wereusedtodevelopweightestimatesfordesktopCPUs,hard‐copydevices,PCFlatPanels,andCRTTVspriorto2008.Fortheremainingcategories,estimatesweretakenfromConsumerReportsAnnualandMonthlyBuyingGuides(from1984to1999)andonlineinformation.WeupdatedunitweightdatafordesktopCPUs,portables,multi‐functiondevices,mobiledevices,andflat‐panelTVsinthe2008,2009,and2010model‐yearsusing2008and2009ConsumerReportsBuyingGuidesandonlinemanufacturerspecificationsheets.1Foreachtypeofproduct,wesampledweightsacrossarangeofmodelsizestocalculateatypicalweight.Wewereunabletocalculateasalesshare‐weightedaverageweightforeachproduct,however,becausethedataonthesalesshareofindividualmodelswithineachtypeofproductwerenotavailable.”
6.1.2.2.6 SensitivityAnalysis
TheassumptionsthosecontributedmosttothevarianceareshowninFigure54.SimilartotheTVs,themajorcontributorswerethemeanlengthoftheinitialuselifespanstage,initialstoragelifetimeandsalesestimate.Theresidentialownersaccountedforthemajorityofsalesinrecentyears,explainingtheimportanceofthoselifespansascompared
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tootherownertypes.Thissuggeststhatfortightergenerationestimates,tighterlifetimeandsalesdataestimatesshouldbeatoppriority,followedbymoreaccuratestoragelifetimeestimates.
Figure54:ContributiontoVarianceofGenerationandCollectionEstimatesofUsedMobilePhonesin2010
6.1.2.3 ComputersandMonitorsTheSurvey‐basedMethodwasusedtoquantifygenerationandcollectionestimates
ofusedcomputersandmonitors.
6.1.2.3.1 Sales
SeveralsourcesoffersalesdataasshowninTable26.
Table26:SalesDataSourcesforComputersandMonitors
Source DataType OwnerType YearIDC(EPAa,2008)IDCReport* Desktop Residential
Business/Public1990‐1994(IDCdatafromEPAreport)1995‐2011(IDC,data)
IDC(EPAa,2008)IDCReport* Laptop
ResidentialBusiness/Public
1990‐1994(IDCdatafromEPAreport)1995‐2011(IDC,data)
IDC(EPAa,2008)GIAInc.**IDCReport&
CRTandFlatPanelmonitor
ResidentialBusiness/Public
1990‐1999(IDCdatafromEPAreport)2000‐2007(GIA)2008‐2011(IDC)
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6.1.2.3.2 Lifespan
BelowinFigure55,themeanLengthsofPeriodofOwnershipλforeachproductarepresented.ItispossiblethatsincelaptopsandFlatPanelmonitorshavebeenintroducedintothemarketmorerecentlythandesktopsandCRTmonitorsthedatasetsareimpactedinsuchawaythattheirλvaluesareartificiallyslightlylonger.Moreadvanceddatamodelingmaybeabletocorrectforthiseffectifitispresent.
Figure55:DistributionofLengthsofPeriodofOwnershipforeachproduct.Meanparameterspresented.Duringsimulation,distributionparametersvary.
BelowinTable27,theWeibulldistributionparametersforthemeanLengthsofPeriodofOwnershipλforeachproductarepresented.
Table27:MeanWeibullDistributionParametersforLengthofPeriodofOwnershipλ
Product WeibullDistributionScaleParameter
WeibullDistributionShapeParameter
Desktop 2.09 7.61
Laptop 1.71 13.28
CRTMonitor 2.10 7.46
FlatScreenMonitor 1.77 15.05
6.1.2.3.3 Collection
BelowinFigure56,theresidentialcollectionratetrendsfoundfromseveralsurveysforusedcomputersandmonitorsarepresented28,33‐35.
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Figure56:EstimatedUSresidentialusedelectronicscollectionratesacrossseveralsurveys
6.1.2.3.4 UnitWeight
DifferenttotheTVsandmobileunitweightdatathosecitedfromEPAreport,theunitweightdataforcomputers(laptopanddesktop)andmonitorsareestimatedbasedonthesamplingdatain2010ofusedelectronicsbytheOregonandWashingtonStatesII,withthesamplesizesrangingfrom1,000to10,000forbrandsofeachtypeofelectronic.
Figure56illustratesthehistogramoftheunitweightdistributionfordesktopandlaptopcomputers,respectively.AccordingtothedistributiongoodnessfitbyusingCrystalBall,lognormaldistributionwasconfirmedtofitwellforboth.
DuetothecombinationoftheunitweightdataforCRTmonitorandFlatPanelmonitordata,theFiniteMixtureModels80(FMM)packageembodiedinStatadatamanagementsoftwarewasemployedtodifferentiatethedistribution(assumedlognormaldistributionforthetwocomponents:CRTandFlatPanel)(showninFigure58).
IINCERBrandDataManagementSystem,samplingsharefromcomputerandmonitors(weight)‐OregonandWashingtonSamplingData:http://www.electronicsrecycling.org/BDMS/AlphaList.aspx?sort=All.
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Figure57:UnitWeightforComputersforModelParameters
Figure58:UnitWeightforMonitorsforModelParameters
TheunitweightdataforcomputersandmonitorsfrommodelparametersareshowninTable28.
Table28:UnitWeight(kg)DataforComputersandMonitorsfromModelParameters
UsedElectronics Distribution Mean StandardDeviationDesktop Lognormal 10.6 3.3Laptop Lognormal 3.1 1.5
CRTmonitor Lognormal 15.4 1.2FlatPanelmonitor Lognormal 10.4 2.0
6.2 Export
6.2.1 MethodologyOverview
Avarietyofapproachesforquantitativecharacterizationoftransboundaryflowsofusedelectronicswereconsideredforthisstudy.Theseapproachesweregatheredthroughareviewoftherelevantliterature,discussionwithstakeholdersataworkshopinJune2011,andsubsequentdiscussionamongstthereport’sauthors.Amoredetailedfeasibility
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assessmentoftheapproacheslistedaboveisprovidedinCharacterizingTransboundaryFlowsofUsedElectronics:SummaryReport81.
Toestimatethelevelofeffortrequiredforresearcherstoexecuteanapproach(lowtosignificant),andthequalityofinformationobtainedfromtheresults(lowtohigh),fourcriteriawerebrieflyevaluated:uncertainty,representativeness,availabilityandcost.Uncertaintyreferstothereliabilityinthedatabeingcollected,andtakesintoaccountanysourcesoferrororestimation.Representativenessreferstotheabilityofsampledatagatheredtorepresenttherangeofusedelectronicsexports.Availabilityreferstotheexistenceofdataandaccessibilityofthedata,andcostreferstothefinancialcosttoaccomplishtheresearchorpoliticalcostfordiplomaticcollaboration.Table29providesasummaryofresultsfromthisbriefevaluation.Notethattheterm“handler”referstocollectorsandprocessorsofusedelectronics.Thetradedataapproachwasselectedforthisresearchamongallofthealternativesasbeingareasonablecombinationofeffortandinformationquality.
Table29:Matrixofquantitativeapproachesbyeffortrequiredandinformationqualityyielded.Approachimplementedinthisstudyisinbold.
LowEffort ModerateEffort SignificantEffort
LowInformationQuality
ProxyTradeData Demographicand
EconomicCorrelation
MediumInformationQuality
MonitorInternetTrading
State‐LevelData EnforcementData:
MandatoryReporting
TradeData StandardHandler
Surveys BillofLadingData EnforcementData:
Seizures MassBalance
Medium‐HighInformationQuality
BayesianTruthSerumHandlerSurvey
VoluntaryExportsStandardsData
CollaborationwithOEMs
HighInformationQuality
MaterialFlowMonitoring
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TheobjectivefortheexporttradedataapproachistodeterminethequantityofusedgoodsexportedfromtheUStovariouscountriesandworldregionswiththeassociateduncertainty.Thereareotherformsofuncertaintywhichcannotbequantifiedbythesemethods,however.Toavoidtariffs,lawsandregulations,orotherformsofnegativeattention,sometimesexportsareintentionallymisclassifiedortradedintheblackmarket82.Variousformsofhumanerrorcouldleadtounintentionalmisclassificationordatareporting.Theseunreportedexportswouldbedifficulttoquantifywithoutenforcementaction.Importpartnerdatararelyperfectlyalignswiththeexportdata,suggestingerrorsoneitherorbothends.Thisapproachproceedswithrecognitionthattheresultsareanunderestimateoftheactualusedlaptopexportquantity.
AversionofthetradedataapproachadoptedherehasbeendemonstratedpreviouslyforJapaneseexports.Yoshidaetal.(2009)demonstratedthismethodusing2004exportpricehistogramstodistinguishusedandnewdesktopandlaptopcomputerexports83.Terazono(2008)similarlydistinguishesSecondhandandBrand‐newTVsets,refrigerators,airconditionersandwashingmachinesexports.Forexample,Figure59presentsexportsofTVsetsfromJapantoChinain200184.
Figure59:Differentiationofused(secondhand)andnewexportsusingexportunitvalue(unitprice).ExampleofTVsetsexportedfromJapantoChinain2001.
Theoverallapproachistoutilizedetailed,disaggregatedtradedatatodistinguishthequantityofusedelectronicsexports.Thestepsareasfollows:
1. Collectandpreparedisaggregated,detailedexporttradedata.
2. Estimateused‐newthresholdunitvaluethresholdsfordifferentworldregions.
3. SumthequantityofgoodsdomesticallyexportedfromtheUStopartnercountrieswithaunitvaluebelowtheused‐newthreshold.
4. Estimatethere‐exportpotentialofdomesticexportsbyinvestigatingthetoptradepartner’sre‐exportactivity.
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6.2.1.1 PreviousworkFewcomprehensiveexportcomparisonsexistforthecountriesstudied.Most
pertinentsurveysandinterviewsofindustryexpertsinrecentyearshaveproducedestimatesofthefractionofcollectedelectronicsthatareexported.Theformoftheusedelectronicsinthefollowingestimatesiseitherunspecifiedormayencompassbothwholeunitsanddisassembledscrapstreams.Thisvariationinscopemakesitdifficulttocomparenumbers.AsurveyofusedelectronicsprocessorsintheNortheasternUSreportedthat45%oftherespondentsareengagedinexport.Allowingforlistingofmultipledestinations,oftheexportingorganizations,overtwo‐thirdsexportedtoAsia,aquarterexportedtoSouthAmerica,andaquarterexportedtoAfrica85.Anationwideindustrysurveyin2003reportedthat“verylittleoftheoutputfromelectronicsrecyclingoperationsisexportedoutsidetheUS(typicallynoneorlessthan10%)”86.Onecaninferfroma2005industrysurveythatalmost31%ofusedelectronicscollectedforprocessingareexportedaswholeunits87.A2010surveyconductedbyIDCsaid“theUSgeographyremainsthebiggestmarketforsurveyrespondents'directoutputinbothweightandvalue”;79%ofrespondents“reportedthattheiroutputwastraded,soldand/ortransferredwithintheUnitedStates”88.Totranslatetheexportfractionsintoquantitiesandcaptureuncertainty,stochasticmethodstoestimatecollectionquantitiesarealsoneeded.
Arecent2013reportfromtheUSInternationalTradeCommission(USITC)investigatedexportsofusedelectronics10.AccordingtotheNewsRelease:
“TheUSITCrecentlyconcludedtheinvestigationfortheU.S.TradeRepresentative.Thereportisbasedondatacollectedthroughanationwidesurveyof5,200refurbishers,recyclers,brokers,informationtechnologyassetmanagers,andotherhandlersofusedelectronicproducts.Itcoverstheyear2011andfocusesonaudioandvisualequipment,computersandperipheralequipment,digitalimagingdevices,telecommunicationequipment,andcomponentpartsoftheseproducts.
ThereportprovidesanoverviewoftheU.S.UEPindustry,includinginformationondomesticUEPcollection,theshareofgoodsthatarerefurbishedcomparedtotheshareofgoodsthatarerecycled,andthecharacteristicsofexportedproducts.ThereportalsoprovidesinformationonthetypesofenterprisesthatexportUEPsandthosethatimporttheseproductsfromtheUnitedStates,anditexaminesthefactorsthataffecttradeintheseproducts.”III
Forthepurposesofcomparisonwiththisstudy’sinvestigationintoexportsofusedwholeunits,surveyresultsregardingrefurbished,remanufactured,andrepairedproductsweremade.Thiscategoryincludes:“usedelectronicproductsthatarecollectedfromtheiroriginalusersandthencleaned,fixed,orotherwisebroughtbacktoworkingconditionandresold.Thiscategoryincludesproductsthataredisassembledandresoldasreclaimedelectronicpartsforuseinrepairingofotherelectronicproducts.”Whiletherearewhole
IIIUSITC, U.S. Exports of used electronic products valued at $1.5 billion in 2011, says USITC. In New Release, 2013. http://www.usitc.gov/press_room/news_release/2013/er0308ll1.htm
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unitexportsforrecyclinganddisposal,thesurveyresultsdidnotdistinguishwholeunitsfrompartsandmaterialsdestinedforrecyclinganddisposal.
TheUSITCstudyalsoreported2011shipmentleveltradestatisticsaboutexportsofseveralproducts.Whilethisstudyfocusedonyear2010,thecomparisonismadesincemanysurveyrespondentsreportedthatexportsin2011andpreviousyearswereaboutthesame.Notethatfordesktops,exportcode847150wasnotincluded,differingfromourapproach(seeTable7).Also,theUSITCreportincludesexportcodes851720050,851720080butnot851720020(confirmedtypoinreportafterconversationwithstaff)whereasthisstudyincludesallthree.Forflatpanelmonitors,USITCexcludedflatpanelvideomonitors,whereastheywereincludedinthisstudy.Lastly,thetradecodemethodwasnotusedforflatpanelTVssonocomparisonwasmade.
WhiletheUSITCstudydoesnotassignaused‐newthreshold,theyprovidestatisticsbythelowest10%,25%,50%and100%oftradebyunitvalue.Quantitiesreportedsumthequantitybelowtheparticularunitvalue.Inordertohaveanapples‐to‐applescomparison,thecomparisonismadebetweenquantitiesassociatedwiththerangeofunitvaluesthatcorrespondtothethresholdsestimatedinthisreport.Therefore,ifthisstudy’sthresholdrangeliesaboveoneunitvalueandbelowanother,thedifferenceofthosequantitiesisfound.ForCRTTVsmonitors,100%oftradewasusedsincenonewCRTsareassumedtobeexported.ComparisonisshownbelowinTable30,withselectedUSITCcomparableunitvaluesinbold.
Table30:ComparisonbetweenHSOTDMThresholdsandUSITCLowestX%UnitValues($/unit)
ProductHSOTDMThresholdRange USITCLowestX%byUnitValue,u
USExportNVEM
ChinaExportNVEM
ExportPub.Method
Max.u Avg.uX=10% X=25% X=50% x=100%
FlatPanelTV 120‐200 NA 100‐200 NA NA NA NACRTTV CRTTV NA,100%Export 263 341 604 431CRTTubes NA,100%Export 95 149 970 154
Mobilephone 60‐195 65‐195 75‐150 50 104 184 123Laptop 100‐305 100‐300 200‐250 270 440 400 485Desktop
Desktop 305‐395 305‐400 200‐400 750 1,250 3,654 2,294Server 290‐400 195‐400 300‐400 750 1,250 3,654 2,294Otherdesktop 440‐600 500‐600 400‐600 NA NA NA NA
Flatpanelmonitor
Flatpanelmonitor
140‐200 115‐200 100‐200 100 118 161 175
Videomonitor 115‐200 110‐200 100‐200 NA NA NA NACRTmonitors
Alone NA,100%Export 227 353 780 359WithDesktop NA,100%Export 324 570 1,712 740
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6.2.1.2 MethodologiesDevelopedandUtilized6.2.1.2.1 Collectandpreparedisaggregated,detailedexporttradedata
Figure2:Illustrationofexportquantityandunitvalueofdisaggregatedtradedataforagivenworldregion
AboveinFigure2(repeatedforconvenience),theexportquantityandexportunitvalueofdisaggregatedtradedataisillustrated.Forthisapproach,theunitvalueofeachproductshippedismodeled;evenwheneachrecordofshipmentisknown,onlytheoverallvaluefortheshipmentandquantityisreportedandnottheunitvalueofeachindividualpieceofequipment.
6.2.1.2.1.1 ExportTradeDatasets
Inordertomostaccuratelymodelthevalueoftheexportedequipment,disaggregated,detailedexporttradedataissought.Whenshipment‐leveldataisnotavailable,port‐levelordistrict‐leveldataareusedassubstitutesasdescribedattheendofthissection.Ideally,substitutetradedatasetswould:
Reporttrademonthly ContainvaluevinFOB,quantityofgoodsq,andweightw. Disaggregatedomesticexports(originatinginexportcountry)fromre‐
exports(originatinginpartnercountry) Disaggregatemodesoftransport Providetradecodesatthe10digitlevel
AftercomparingallofthepublicallyavailableUSexporttradedatasetsthatwewereabletolocateinTable31,threewereselected,seeTable32.Table33belowpresentsthesymbolsandtermsusedtodescribethedatasetsaswellasintheequationsinthefollowingsection.
SincetheidealUSexporttradedatasetofdetailedshipmentlevelreportingisnotavailableinfullIV,noristheidealsetofport‐leveldata,amethodwasdevelopedto
IVAftercompletingthecalculationspresentedinthisreportwediscoveredthatthesetypeofdataareavailablefromtheCensusResearchDataCentersasRestricted–UseTransactionsMicrodata:
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approximateport‐leveldomesticexportunitvaluesandquantities.Alldatasetscomparedreportedtrademonthlyandcontainvalue,v.Somedatasetsconsideredcontainquantityofgoodsq,and/orweightw.Someaggregatedshipmentsattheport,districtorcountrylevel,andsomeaggregateddomesticexports(originatinginUS)withre‐exports(originatinginpartnercountry);someaggregatedmodesoftransportaswell.
Table31:AttributesofUSExportTradeDatasets
Attribute UNComtradeI
USITCDataWeb
USATradeOnline
SICEX(USExports)
SICEX(MXImports)
StatisticsCanada(CANImports)
Value,v,Measure
FOB,CIF
FOB
FOB
FOB
FOB,CIF
CIF
Quantity,q,Measure
Quantity,Weight
Quantity Weight
Quantity,Weight
Quantity
Quantity
TradeFlows,f
AllAvailable
DomesticExports
GeneralExports
DomesticExports
ImportsbyOrigin
ImportsbyOrigin
Period AnnualII Monthly Monthly Monthly Monthly Monthly
Transportmodes,t
Combined Combined Air,Vessel
Air,Vessel,Multi,Other
Air,Vessel,Land,Other
Air,Vessel,Land
Region,r Country District Port District District Port
Table32:DatasetsUtilizedforUSExportsCalculations.Somedatasetsdonotreportquantityorweight.
Database 1.USATradeOnline 2.SICEX(USExports)
StatisticsCanada(CANImports)
Value,v
Quantity,q ‐‐
Weight,w
‐‐
http://www.census.gov/ces/rdcresearch/.However,onemustgothroughanextensiveapplicationprocessinordertoaccessthedata.I BACI data was considered as well, but not utilized for any purpose due to its inability to reconcile re-exports, and its use of 1996 export codes which are not as detailed as 2007 export codes used in other datasets. Gaulier, G. and S. Zignago BACI: International Trade Database at the Product-level: The 1994-2007 Version. CEPII. II UN Comtrade launched a free beta version of “UN Monthly Comtrade” in mid-2012 but it only reports value. http://comtrade.un.org/monthly/Public/Metadata.aspx.
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Table33:ExportTradeDataSymbolsandTerms
Symbol Term Symbol Term
u Exportunitvalue FOB Free‐on‐boardvalues
v Exportvalue CIF Cost,InsuranceandFreightvalues
q Exportquantity m Month(ofspecificyear)
w Exportweight n Tradepartnernation
x Exportunitweight t Transportmode(airandvessel)
fg Generalexporttradeflows rs Shipment‐levelregionalaggregation
fe Domesticexporttradeflows rp Port‐levelregionalaggregation
fg‐e Re‐exporttradeflows rd District‐levelregionalaggregation
fi Totalimporttradeflows rc Country‐levelregionalaggregation
Port‐levelweight(orquantity)dataareneededtocalculatetheapproximateport‐levelunitvalue,whichisgenerallyavailablethroughUSATradeOnline.Unfortunately,thedatasetsutilizeddonotcontainthisinformationforlandshipments,sodistrict‐leveldatawasusedformostexportstoCanadaandMexicofromtheUS.I
I“CanadaandtheUnitedStatesparticipateina'dataexchange',inwhichtheexportstatisticsofeachcountryarederivedfromthecounterpartimportdata;therefore,therearenounexplaineddifferencesintheirtradestatistics.However,differencesbetweentheofficialtradestatisticsoftheUnitedStatesandMexico,andCanadaandMexicoaresizeable”(EconomicsandStatisticsAdministrationofUSCensusBureau2000).Therefore,port‐levelCanadianimportdatafromSTATCANisusedforUSdomesticexportdatatoCanadaforthecaseoflaptopsonly.District‐level
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6.2.1.2.1.2 ExportTradeCodes
Thefollowingtablespresentthetradecodesforthefocusproductsofthisstudy.Table34presentsthecodesforTVs.
Table34:TVExportTradeCodesUsedinthisStudy
ProductTypeScheduleBExportCode OfficialDescription
CRTColorTVs
8528723000 TVreceptionapparatus,color,incorporatingvideorecordingorreproducingapparatus
8528726005TVreceptionapparatus,color,withpicturetube,combinedwithradiobroadcastreceiversorsoundrecordingapparatus
8528726010 TVreceptionapparatus,color,havingapicturetube,notexceeding52cm(<20inches)
8528726040TVreceptionapparatus,color,havingapicturetube,exceeding52cm(>20inches)
MonochromeTVs
8528730000 Other,blackandwhiteorothermonochrome
FlatPanelTVs 8528726057 TVreceptionapparatus,color,nothavingapicturetube
CRTTubes854011 Tubes,partsthereofCathode‐raytelevisionpicturetubes,
color
854012Tubes,partsthereofCathode‐raytelevisionpicturetubes,monochrome
CRTGlassEnvelopes
701120 Glassenvelopes(bulbsandtubes)forcathode‐raytubes,andglasspartsthereofcathode‐raytubesorthelike
Notethatformobilephones,asubsetoftheHScodeunder851712,8517120020(RadiotelephonesdesignedforinstallationinmotorvehiclesforthePublicCellular),hasbeenexcludedduetoitsdissimilaritywithtypicalmobilephones.
Table35:MobilePhoneExportTradeCodeusedinthisstudy
ProductTypeScheduleBExportCode OfficialDescription
Mobilephone 851712 Telephonesforcellularnetworksorforotherwirelessnetworks*
BelowinTable36aretheexportcodespertainingtocomputersandmonitors.USexportdataatthe10digitlevelwasusedtoidentifythequantitiesofDesktopswithCRTs(ScheduleBExportCodes8471410110and8471500110).GiventhatallCRTsexportedareassumedtobeused,desktopsexportedwithCRTsarealsoassumedtobeused.
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Table36:ComputerExportTradeCodesUsedinthisStudy
ProductTypeScheduleBExportCode
SpecificProduct
Desktop
8471410110 DesktopwithCRTMonitor8471410150 DesktopwithoutCRTMonitor847149 Server8471500110 OtherDesktopwithCRTMonitor8471500150 OtherDesktopwithoutCRTMonitor
Laptop 847130 Laptop
CRTMonitor
8471410110 WithDesktop8471500110 WithOtherDesktop852841 PCMonitor852849 VideoMonitor
FlatPanelMonitor
852851 PCMonitor852859 VideoMonitor
6.2.1.2.1.3 PreparationofExportTradeData
First,alldatautilizedwasaggregatedtotheannual,alltransportmode,partnercountryleveltocheckforconsistencyacrossv,q,andwandincomparisonwithUNComtradedata.Minorissueswereencounteredwithregardstoinconsistenciesincountryclassification(e.g.Sudan,Curacao)acrossdatasets;tradewiththesecountrieswasverysmall.
ThedisaggregatedUSdomesticexportunitvaluewascalculatedattwolevelsofaggregation:district‐level,andapproximateport‐level.Theterm“approximateport‐level”isusedtorepresentthatunitvaluescannotbecalculatedfromport‐leveldatadirectlyduetolackofquantitydata,andthereforeapproximationsaremadetoarriveatport‐levelunitvaluesandquantities.District‐levelunitvaluescanbecalculateddirectlyfromdistrict‐levelquantities,sodistrict‐levelresultsarefoundinordertocheckthattheapproximateport‐levelresultsarewithinreason.Attheapproximateport‐level,CanadianimportdatawassubstitutedforUSdomesticexportdata,anddistrict‐levelexportdatawasusedforexportstoMexico.
Thedistrict‐levelUSdomesticexportunitvalue wascalculatedwithSICEXdataasshowninEquation12.SinceSICEXdoesnotprovidequantitydisaggregatedbytransportmode,theexportunitvalueisdisaggregatedjusttoforeachmonth,partnernation,anddistrict.
Equation12
Toarriveattheapproximateport‐leveldatafornon‐NorthAmericancountries,thegeneralexportport‐levelvalueperweightismultipliedbythecorrespondingdomestic
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exportdistrict‐levelunitweight foreachmonth,partnernation,anddistrictasshowninEquation13andEquation14.
Equation13
Equation14
Toapproximatetheport‐levelquantity, ,theweightfractionof
district‐leveldomesticexportsoutofgeneralexportsismultipliedbyport‐levelgeneralexportweightinordertodeterminetheapproximateport‐leveldomesticexportweight,andthenweightisconvertedtoquantitybydividingbythecorrespondingdistrictaverageunitweight,asshowninEquation15.Substituting fromEquation13,Equation15isequivalenttothefractionofport‐levelgeneralexportweightoutofdistrict‐levelgeneralexportweightmultipliedbythedistrict‐leveldomesticexportquantityasshowninEquation16.Therefore,theapproximateport‐levelquantityessentiallyallocatesadistrict’sdomesticexportquantitytoaportbasedontheport’sshareofthedistrict’sgeneralexportweightforagivenmonthandtradepartnernation.
Equation15
Equation16
TocalculatebothoftheNorthAmericanimportunitvaluesfortradewithUSas
countryoforiginn,thevalueissimplydividedbyquantityforeachmonth,portordistrict,andtransportmode.CanadianimportunitvalueisshowninEquation17.
Equation17
AnexampletoarrivetheApproximatePort‐LevelCalculationsforLaptopexportis
showninTable37.
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Table37:ExampleApproximatePort‐LevelCalculationsforLaptopexport(FromtheUStoArgentina)(ResultsShaded)
Tradepartnernationn&Month
m
n=Argentina,m=September2010(Note:somerecordsexcludedforthisdemonstration)
District,d Houston‐Galveston,TX Miami,FLNewYorkCity,NY
Port,p
HoustonIntercont‐inentalAirport,TX
Houston,TX
MiamiInternatio
nalAirport,FL
Miami,FL
PortEverglades,
FL
JFKInternatio‐nalAirport,NY
$634,444 $634,444 $3,389,603 $3,389,603 $3,389,603 $‐ 912 912 5,742 5,742 5,742 ‐
$5,877 $5,877 $27,842 $27,842 $27,842 $‐ ‐ ‐ 350 350 350 ‐
$113,541 $113,541 $4,099,759 $4,099,759 $4,099,759 $56,440300 300 10,941 10,941 10,941 208
$378 $378 $375 $375 $375 $271‐ ‐ 26,625 26,625 26,625 212
815 815 589 589 589 ‐ 815 815 27,214 27,214 27,214 2123 3 2 2 2 1
$634,444 $‐ $7,412,903 $‐ $‐ $56,4405,877 ‐ 54,467 ‐ ‐ 212$293 $‐ $339 $‐ $‐ $271
$‐ $113,541 $‐ $48,674 $27,785 $‐ ‐ 815 ‐ 589 350 ‐
$‐ $378 $‐ $206 $197 $‐ 0% 0% 49% 49% 49% 100%
100% 100% 63% 63% 63% 0%
912 ‐ 5,671 ‐ ‐ ‐
‐ ‐ ‐ 45 27 ‐
‐ ‐ 10,704 ‐ ‐ 208
‐ 300 ‐ 149 88 ‐
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6.2.1.2.2 Estimateused‐newunitvaluethresholdvaluesfordifferentworldregions
FollowingTerazono(2008),theapproachinthisstudyassumesthatexportsbelowaunitvaluethresholdareusedandthoseaboveitarenew.Thethresholdapproachassumesthattheused‐newthresholdisconsistentacrossaregionforatypeofgood.WorldregionsweredefinedbyWorldBankcountryincomegroups89andUNmacrogeographicalregionI90forvessel,air,andlandtransport.Duetopriceadaptationtodifferentmarkets,methodsdevelopedinthisstudydonotassumethesameexportunitvaluetoallcountries.Co(2007)foundthat“USexportersdopricediscriminateacrossmarkets”,basedonincomelevel,Englishlanguage,andtosomeextentchangesincurrencyexchangerate91.BaldwinandHarrigan(2007)analyzeall2005USexportdataandfindthat“distancehasaverylargepositiveeffectonunitvalues”;exportstodestinationsfartherthan4000kmawayhadunitvaluesafactoroftwolargerthanexportstoothercountriesinNorthAmerica.Theyalsofoundanegativerelationshipwithexportunitvalueanddestinationmarketsize92.
Thethresholdvaluezisthevalleybetweentheusedandnewdistributionsembeddedinabimodaldistribution,asdemonstratedinFigure3,repeatedbelowforconvenience.
Figure3:IllustrationofexportquantityandunitvalueofdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion
Inthisstudy,itisassumedthatthemagnitudeoftheerrorduetoincludingnewgoodsinthesumbelowthethresholdisroughlyequivalenttothemagnitudeoftheerrorduetoincludingusedgoodsinthesumabovethethreshold.Thiserrorwillactuallyvarydependingonthemagnitudeandformofthedistributions.
Thethresholdvaluesweredeterminedusingthreeseparatemethodsforcomparisonpurposes.USExportNVEMandChinaExportNVEMutilizetheneighborhood
IThesearefollowedwiththeexceptionofMexicobeingassignedtoNorthAmericainthisstudy;itisambiguousinUNclassifications,andelsewhereMexicoisassignedtoNorthAmerica.
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valley‐emphasismethod(NVEM)foreachdestinationworldregionwithUSexportandChineseexportdata,respectivelyII94.Chinesedataisconsideredanticipatingthatthemajorityofexportedgoodsarenew,sinceChinaisamajormanufacturer95.NVEMfindstheoptimalthresholdwhichsimultaneouslymaximizesthevariancebetweenthemodes(here,usedandnew)andminimizestheprobabilityoftheunitvaluebin atandaroundtheoptimalthreshold.AnexampleofthethresholdrangefoundbyNVEMinChinaExportNVEMisshowninFigure60,withapproximatedistributionssuperimposedonthehistogram.ExportPub.Methodtakesadvantageofpublishedreferencevaluesforusedgoods,andappliesthesamethresholdtoallworldregions.
Figure60:ExampleofChinaExportNVEMhistogramwith$5exportunitvaluefor2010exportoflaptopsfromChinatoLatinAmericaandtheCaribbean(LAC)byvessel.
6.2.1.2.2.1 NeighborhoodValley‐EmphasisMethod(NVEM)forUsed‐NewThresholds
Thresholdswerecalculatedattheapproximateport‐level(ordistrictleveltoCanadaandMexico),foreachworldregionandforbothvesselandairtransport(andlandtransportforNorthAmerica).Sincethedatasetsutilizedlargelyreportexportvaluesthatdonotincludefreightcosts,itmayseemsuperfluoustofinddifferentthresholdsfortransportmodes.Still,considerabledifferencesinunitvaluesdistributionshavebeenobservedforthisdatasetbasedonmodeoftransport,soitmaybeuseful.
IINote:adifferentmethodfornumberingwasusedinreference[93]Miller,T.R.Quantitativecharacterizationoftransboundaryflowsofusedelectronics:Acasestudyoftheunitedstates.MIT:2012.
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Theneighborhoodvalley‐emphasismethod(NVEM)wasemployedtodeterminetheused‐newthresholdvaluezfortheUSExportNVEMandChinaExportNVEM.FanandLei(2012)describetheirapproachfordeterminingthethresholdfordifferentiationbetweenmodesinadistribution,developedforapplicationinfindingthethresholdofabimodalhistogramofagrayscaleimage.TheydemonstratethewiderapplicabilityoftheirNVEMversustheOtsuandvalley‐emphasismethods,whichtheymodify.ThismethodwaschosenbecausethethresholdzIIIvaluesarenoteasilydistinguishedbytheeye,andFanandLei(2012)convincinglydemonstratedthesuperiorityofthismethod.Sincethisrequiresahistogramwithadevelopeddistribution,themethodwasonlyappliedtosuitabledatasetswithconsiderabletradequantity(hereabove10,000units);thesecalculatedthresholdssubstitutedformissingthresholdsinworldregionswithlowtradequantities.Forworldregionswithasmallertradequantity,theExportPub.Methodwassubstituted.
Themethodfindstheoptimalthreshold, ,whichsimultaneouslymaximizesthevariancebetweenthemodes(orclasses)andminimizestheprobabilityoftheunitvaluebin atandaroundtheoptimalthreshold.Byconsideringnotonlytheprobabilityatthethresholdvaluebinconsidered(theterm“valuebin”isusedbecauseahistogramisanalyzed)butitsneighborunitvaluebinsaswell,sporadicdipsnotcorrespondingtotruevalleysarenotselected.Themethodproceedsasfollows.
Eachunitvaluebin isevaluatedasapossiblethreshold ,andthusitsneighborhoodprobability iscalculated.Equation18isthesumofneighborhoodunitvalueprobabilityininterval forunitvalue ,where istheneighborhoodlength,normallyanoddnumber,and isthecountofbinsevaluatedoneithersideof(FanandLei2012).Theanalysisproceedsforseveralvaluesof tofindareasonablelength,basedonthesizeofthevaluebinandreasonablenessoftheresultsintermsofavoidanceofextraneousvalues.Theresultsarepresentedfor =7,9,and11representingexportunitvalueneighborhoodlengthsof$35,$45,and$55,respectively.
Equation18
Modes(orclasses)aredefinedas and whereisthemaximumunitvaluebin.Thetotalprobabilitiesofeachclassarefoundwith
simplesummations,showninEquation19andEquation20.ThemeansofeachclassareshowninEquation21andEquation22.
Equation19
III Notation used here differs from that presented in Fan and Lei (2012)
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Equation20
Equation21
Equation22
Theoptimalthreshold, ,correspondstothemaximumacrossallvaluebinsofthe
objectivefunctionoftheneighborhoodvalley‐emphasismethod, ,inEquation23.
Equation23
6.2.1.2.2.2 ExportPub.MethodforUsed‐NewThresholds
InordertogetthesalesvaluesfortheusedelectronicsintheUSmarket,anumberofsalestradeplatformshavebeeninvestigated,includingbusinesstobusiness(e.g.,Alibaba),businesstoindividualconsumer(e.g.,AmazonandPriceGrabber)andindividualtoindividual(e.g.,ebay).Theadvantageisthatthesepotentialtransactionsshowusadirectsalevaluesfortheusedelectronics,aswellasthenormalpriceforthenewproductsasacomparison.However,thereareseveralconstraintsasfollows:
(a)Thepricescannotrepresentthesalesvalueofthewholeyear,onlythemostrecentspecificdate;
(b)Thereischangebetweentheauctionpricesandthefinalizedtradeprices;
(c)Itonlyrepresentsthemajorinternal‐basedtrades.
6.2.1.2.3 SumthequantityofgoodsdomesticallyexportedfromtheUStopartnercountrieswithaunitvaluebelow
Forthisstep,thequantityofexportsthatfallbelowtheused‐newthresholdforeachworldregionaresummed.Resultsarereportedforeachthresholdmethodandeachworldregion.Thetopusedexportrecipientsaredetermined.SignificantdifferencesintheresultsfromUSExportNVEM,ChinaExportNVEMandExportPub.Methodareinvestigated.Figure5below(repeatedforconvenience)illustratesthesummedquantities.
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Figure5:IllustrationofsumofUsedandNewexportquantitiesfromdisaggregatedtradedatawithUsed‐NewthresholddifferentiatingunderlyingUsedandNewdistributionsforagivenworldregion
6.2.1.2.4 Estimatethere‐exportpotentialofdomesticexportsbyinvestigatingthetoptradepartner’sre‐exportactivity
TheUSdomesticexportdatautilizeddetailstheexporttradepartner,butnotnecessarilythefinaldestinationassometradepartnerswillthenre‐exporttheimports.Therefore,toapproximatethepotentialofre‐exportafterimportfromtheUS,ratiosbasedonaggregateUNComtradedata96werefoundasademonstrationforthelaptopcase.Notethatthismethodassumesequallikelihoodofre‐exportacrossallunitvaluesinsteadofdistinguishingusedfromnew.Fewcountriesdistinguishre‐exports,thereforeratiosaredevelopedcomparingexportstoimportsformostcountries.SomecountriesdonotreporttradedatatotheUN;formajorUSexportdestinations,tradeflowsareinferredfromreportingcountries’importandexportflowswiththesecountries.Chinawastreateddifferentlysinceitisaknownmajormanufacturerandexporter.UtilizingshipmentlevelChineseexportdata(HSInternationalInc.2012),re‐exportdestinationsofusedlaptops(underUS$250)werefound.
6.2.1.2.5 InDepthExplorationofTVProduction,Collection,andExport
BasedonourpreviousworkIV,20,itwasfoundthattherearealmostnonewCRTTVsbeingmanufacturedinNorthAmerica,whichimpliesthereisprobablynonewCRTTVswhichcanbeexportedoutofthisregion(exceptthere‐export).ThereisahypothesisthattheexportsofCRTTVsfromtheUSareallused.Inanotherword,itisunnecessarytodistinguishtheusedfromthetradeundertheHScodeofCRTrelatedproducts.ThissectionaimstoreviewtheCRTindustryintheUSandhelpconfirmthehypothesis.
6.2.1.2.5.1 GlobalTVProduction
IVJenniferAtlee,JeremyGregory,andRandolphKirchain,2005,Anoverviewofcathoderaytuberecyclinginternalreport.previousworkdonebyMaterialsSystemsLaboratoryatMIT.
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USfirmsledtheworldinTVtechnologyandproductionuntiltheearly1970s.Then,foreign‐ownedfirmsgraduallytookcontroloftheUSmarketV.AreportfromIHSiSuppliVIindicatedthatglobalTVshipmentsreachedanall‐timehighof255millionunitsin2011butwilldeclineto241millionin2013.ThemajorreasonsforthedeclineinunitshipmentsarethecontinuedfallofCRTTVsandtheriseofinternettelevision.Thisisnotasurprisegiventhelong‐termdeclineofthemarket,butitishavinganimpactontheoverallshipmentoftelevisionsandcausingaperiodofadjustment.Currently,therearenoCRTTVsbeingshippedinWesternEurope,NorthAmericaandJapan.EasternEuropenowrepresentsonlyasliverofwhatoncewasamajorshipmentdestinationforthetechnology.EventheformerstrongholdofLatinAmericaisexperiencingadecreaseinthenumberofshipmentsofCRTTVsintheregion,withdigitizationandeconomicgrowthspurringtheuptakeofflat‐panels.By2016,CRTTVtechnologywillbecomenonexistentasallregionsswitchtoLCDandorganiclight‐emittingdiode(OLED)technology,IHSiSupplibelieves.ThemajorityofCRTTVsthatareshippednowgointotheAsia‐Pacificregion,ofwhich60%areshippedintoIndiaandIndonesia,withthenextmostsignificantregionbeingtheMiddleEastandAfrica,primarilysub‐SaharanAfrica,at15percent.However,eventheseregionswillbephasingoutoftheCRT‐TVbusinessduringthenextthreeyears.
6.2.1.2.5.2 USCRTGlassManufacturers
In1993(USITC,Industry&TradeSummary)97:
TelevisionPictureTubesandOther:therewere7producersofcolortelevisionpicturetubesintheUnitedStates,about30otherproducersofothertypesofCRTs,and21producersofelectrontubepartsexceptglassblanks;therewasnomonochrome(blackandwhite)tubeproductionintheUnitedStates.
RegardingtheCRTtubeglass,TechneglaswasthemajorsupplierofglassforpicturetubesintheUnitedStates,supplyinganestimated60to70percentofUSdemand.
In1997(USEPA,ComputerDisplayIndustry&MarketProfileVII):
ThemajorityofCRTdisplayfabricationtookplaceoutsideoftheUnitedStates.In1997,Asia(excludingJapan)produced54percentofallcolorTVsand79percentofallCRTmonitors.
CRTglass:FiveCRTglassmanufacturingplants,Techneglaswasthemajorsupplier
Picturetubes:7intotal,SonyforColormonitor;Hitachi,Matsushita,Philips,Thomson,Toshiba,andZenithforTVstubes.
CRTdisplayassembly,8intheUS.
VUSCongress,OfficeofTechnologyAssessment,theDeclineoftheUS.TVIndustry:Manufacturing.AppendixAfrom“TheBigPicture:HDTV&High‐resolutionSystems”,1990.Availableat:http://www.princeton.edu/~ota/disk2/1990/9007/900709.PDFVITomMorrod,GlobalTelevisionShipmentstoshrinkin2012,IHS‐iSuppli,2012,Availableat:http://www.isuppli.com/Display‐Materials‐and‐Systems/MarketWatch/Pages/Global‐Television‐Shipments‐to‐Shrink‐in‐2012.aspxVIIUSEPA,1998,ComputerDisplayIndustry&MarketProfile:Chapter2.Availableat:http://www.epa.gov/dfe/pubs/comp‐dic/tech_reports/SEC2‐0.pdf
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Mizukietal.(1997)98state,“Theonlycolor‐displayproductionintheUSisoflargeentertainmentsystems(19"orlarger)becauseofthehighcostofimportingtheseheavieritems.Only5%ofthemonochromemonitorandTVCRTsconsumedintheUSaremanufacturedintheUS,andnocolormonitorsorsmallcolorentertainmentsystems(lessthan19")areproduceddomestically.”
Since2000VIII,therewerethreeCRTmanufacturers(ThomsonConsumerElectronicsInc.,TechneglasInc.,andCorningAsahiVideoProductsCompanyInc.)thatpurchasedfurnacereadyCRTcullet(Toto2003bIX).However,thesituationhaschangedinthepastfewyears.
AmericanVideoGlassCompany(aCorningAsahi&SonyPartnership)isstillinvolvedinglassbusiness,butnotCRTmanufacturingX
ThomsonConsumerElectronicshasapparentlymovedoffshore(toEurope?–unverified)
TechneglasrecentlywentoutofbusinessXI(BaselActionNetwork2004XII)
6.2.1.2.5.3 USGlass‐to‐GlassandGlass‐to‐LeadCulletProviders
Aroundadecadebefore,therewereonlytworecyclersprovidingfurnace‐readyculletintheUS(De‐manufacturingofElectronicEquipmentforReuseandRecycling2002XIII).Descriptionsoftheserecyclersareprovidedin(MaterialsfortheFutureFoundation2001XIV):
Envirocycle,Inc.(PA)XV:“AllmaterialsreceivedbyEnvirocycleareinspectedforthepossibilityofresale.Unitswithnovaluearesenttobedismantledandsortedintothepropermaterialstreamsforrecycling.TheaveragetimeforprocessingCRTglassis2weeks.WithinonemonththeculletisbackintothecommercestreamasanewCRT.Envirocycleemploysapproximately50peopleintheirtear‐downprocessandiscurrentlyinvestinginresearchanddevelopmenttoimprovethedismantlingtechnology.”
VIIIThissectionispartlyfromtothepreviousworkdonebyMaterialsSystemsLaboratoryatMIT:Anoverviewofcathoderaytuberecycling(JenniferAtlee,JeremyGregory,andRandolphKirchain,2005,internalreport).IXToto,D.(2003),Monitoringthefuture,RecyclingToday41(12):24‐8.XEPAannouncementaboutpartnership:http://www.epa.gov/epaoswer/hazwaste/minimize/avglass.htmXIAuctionannouncementfromthebankruptcycourt:http://www.zonetrader.com/Auctions/AuctionDetail.asp?auctionID=9926NewsitemonTechneglasfilingforbankruptcy:http://www.dailyitem.com/archive/2004/0903/biz/stories/05biz.htmXIIBaselActionNetwork(2004),CRTGlassRecyclingSurveyResults,Availableat:http://ban.org/library/crt_survey_2004.pdfXIIIDe‐manufacturingofElectronicEquipmentforReuseandRecycling(TaskN.302),Availableat:http://www.ndcee.ctc.com/task_descriptions/N_302.pdfXIVMaterialsfortheFutureFoundation(2001),CRTGlasstoCRTGlassRecycling,Availableat:http://www.calrecycle.ca.gov/electronics/resources/Publications/GlassMFF.pdfXVEnvirocycle,Inc.(PA):http://www.enviroinc.com
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DlubakGlassCompany,Inc.(OH&PA)XVI:“DlubakGlassisthelargestglassrecyclerinthecountry;Dlubakhandlesautomotiveglass,lightingindustryglass,andCRTglass.Thecompanycurrentlyhandles300tonsofglassperyearandemployeesapproximately50workersintheUSFiveemployeeshandleCRTrecyclingattheDlubaksiteinSandusky,Ohio.Thesitehandles20to30truckloadsperday.CRTsarede‐manufacturedbyUSFederalPrisonIndustries,alsoknownasUNICOR.Dlubak’spartnershipwithUNICORprovidesdismantlingforfunnelandpanelglass,ferrousandnon‐ferrousmetalremovalforallnon‐glassmaterialsandpanelglasssortingbymaterials.”
Evenadecadeago,thereweremanyCRTrecyclersthatsentglasstoleadsmelters.Afewofthelargerprocessorsarementionedhere(Novelli,2003XVII).XVIII
UnitedRecyclersIndustries(IL):http://www.unitedrecycling.com GoldCircuit(AZ):http://www.goldcircuit.com.Tippingfeesof$0.18‐$0.25/lb,
areprincipalrevenueforplant.
6.2.1.2.5.4 LeadSmeltersUsingCRTCullet
Mizukietal.(199798)statedthatthirteensmeltersexistedintheUS(in1997)whohadprimaryandsecondarySICcodesforleadsmeltingorrefining,withNoranda,AsarcoIncorporated,andDoeRunCompanyappearingtobethemostwidelyusedprimarysmelters.
DoeRunandNorandaareconsistentlylistedastheprimaryleadsmeltersinNorthAmericaacceptingCRTcullet.However,Weitzman(2003)99alsolistsGopherResourceCorporationinMinnesota,Metalico/GolfCoastLeadinFlorida,andTeckComincoMetalsLTDinwesternCanadaasalternatives.ThelattertwodonotcurrentlyuseCRTcullet,butareexperimentingwiththepracticeandhaveplanstobringthepracticeon‐line.
6.2.1.2.5.5 CurrentCRTTubeandGlassReuseMarket
Likereuseofanyelectronics,CRTmarketsareprimarilyforeign,andsmallremainingmarketsforreuseofwholemonitors&TVs:Mexico,CentralandSouthAmerica,AfricaandAsia.ArecentreportreleasedbyCalRecycleCEWRecyclingProgram(2013XIX)indicatedthatthesolemanufacturerofnewCRTsacceptingprocessedglassislocatedinIndiaandischargingbetween$100and$200pertontodoso.
XVIDlubakGlassCompany,Inc.(OH&PA):http://www.dlubak.comXVIINovelli,L.R.(2003),MakingCRTrecyclingwork.Scrap60(2):107‐115.XVIIIUnitedRecyclersIndustries(IL):http://www.unitedrecycling.comGoldCircuit(AZ):http://www.goldcircuit.com.XIXCalRecycleCEWRecyclingProgram(2013),ResidualCRTGlassManagementandtheCEWRecyclingPaymentSystem,ElectronicWasteRecyclingStakeholderWorkshop,March13,2013.Availableat:http://www.calrecycle.ca.gov/Actions/Documents/77/20132013/835/Overview%20of%20CRT%20Issues%20and%20the%20CEW%20Program.pdf
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ReportedlyonlythreelargemetalsmeltersinNorthAmerica,whereonlyonefacilityintheUS(DoeRun,Missouri)andtwoinCanada(TeckComincoandXstrata)knowntoacceptCRTglassinquantityandataprice,thoughnewleadextractiontechnologiesforhigh‐leadcontentfunnelglassareallegedlybeingdevelopedonsmallerscales.Theexamplebelowshowsthereuseandrecycling(flows)ofCRTtubeandglassinCaliforniabasedontheCalRecycleCEWRecyclingProgram(2013I):
“Bymid‐2009,approximately75%ofresidualCRTsand/orCRTglasswerebeingshippedtoMexicanprocessors.However,inthe4thquarterof2009,accesstoMexicanCRTglassprocessorswasinterruptedfornearlyayear.BecauseCEWrecyclerswererequiredtoshipCRTglasstoadestination“authorizedtoreceiveandfurthertreat”theglasspriortofilingCEWrecyclingclaims,thisinterruptioncausedthevolumeofclaimedCEWtodecreasedramaticallywhilerecyclerssearchedforalternativeoutletsforCRTglass.Acoupleofrecyclerspursuedestablishingtheirownin‐stateCRTprocessingcapabilities,whileotherenterprisesstartedorofferedcapacitiesout‐of‐state”.
“AsofJanuary2013,over300millionpoundsofresidualCRTsandCRTglasshadbeenshippedbyCEWrecyclerssinceJanuary2010.Atthesametime,though,substantialreductionindestinationoptionsoccurredovertheselastthreeyears,particularlytoout‐ofstateandforeignlocations.WiththeexceptionofDoeRun(smelter)andSamtelGlass/VideoconIndustries(theCRTmanufacturerinIndia),allout‐of‐statedestinationsthatreceivedshipmentsin2012arenotultimateendpoints;instead,theyareintermediatefacilitiesthatpossiblyperformsomedegreeofCRTprocessingbeforepresumablyshippingtheglassontoasubsequentdestinationorultimatedisposition”.
ThefollowingFigure61isasummaryofinitialresidualCRT/CRTglassshipmentdestinations,derivedfromdocumentationcontainedinCEWrecyclingpaymentclaimsI.ThefigurepresentsshipmentsinallthreeyearssinceJanuary2010aswellasjustthoseshipmentssinceJanuary2012.ItimpliestheexportsofresidualCRTandCRTglassaccountfor25%ofthetotalcollection,whichexcludestheexportswithorwithoutprocessingbythefirst‐handreceivers.Alllistedin‐statedestinationsareostensiblyauthorizedtotreatCRTsunder22CCR66273.73andmayaccumulateCRTsand/orCRTglassforuptooneyearunderuniversalwasterulesbeforepresumablybeingshippedontoanotherappropriatedestination.Out‐of‐statedestinationsthatreceivedshipmentsin2012arenotultimateendpoints.ForeigndestinationsincludeprimarilyMexico,India,MalaysiaandKorea.Inaddition,notethatdatafor2012maybeincompleteduetoatime‐laginreceivingCEWrecyclingpaymentclaims.Alsonotethatasmallnumberofincidentalshipmentsamountingtolessthan0.1%oftotalvolumesshippedarenotaccountedforhere.
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Figure61:InitialResidualCRTandCRTGlassShippingDestinations(fractionsofweight)
The review on leaded class conducted by Thomas who went through the notifications to the US.US EPA for the shipment of broken CRTs in the year of 2010 and 2011 (enforcement data) found that 56% and 24% of exported CRTs scrap were been shipped to Canada and MexicoXX.
6.2.1.2.5.6 GlobalandUSCRTSupplyBasedonInternationalTradePlatform
InordertoconfirmthatthereisalmostnomanufacturingindustryoftheCRT‐relatedproductsintheUS,thisstudyalsoinvestigatesthesuppliers’worldwideandtheUSbaseddistributionontheinternationalbusinesstobusiness(B2B)andexports‐orientedtradeplatform‐Alibaba.
Basedonthesearchingonthesuppliers’informationofCRTTVsproducts(bothnewandused)inOctober2012XXI,itwasfoundthatmostofthesupplierswerefromChina,seetheTablebelow.
Table38:StatisticsonWorldwideCRTTVsSuppliersBasedonAlibabaB2BPlatform
RegionNumberofsuppliers
Fractionsofsuppliers
EastAsia 22,223 98.3%SouthAsia 66 0.3%SoutheastAsia 154 0.7%MiddleEast 27 0.1%Europe 77 0.3%SouthAmerica 2 0.0%NorthAmerica 38 0.2%Africa 31 0.1%
XXJakeThomas.Alookthroughtheleadedglass.E‐scrapNews,June,2013.http://resource‐recycling.com/node/3958XXIhttp://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchText=CRT+TVs
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Whilethereare38suppliersforCRTTVinNorthAmerica(mainlyfromtheUS),theproductsclassifiedintoCRTTVsonlyincludethesecondhanditemswithextremelylowsaleprices(lessthan$50/unit),suchastheBrokenScreenTVs,CRT/TVsscrap,usedCRTmonitor,usedTVsorCRTTVs,untestedColorTVs(used),testedTVforreusedandcleanfunnelandpanelCRTglass,CRTglassandTVsplasticscrap.Inaddition,thereisafewsuppliersthattradetheproductsclassifiedintoCRTtubesorprocessedglassfromtheUS.ThisinformationhelpsprovideindirectevidencethatthereisalmostnomanufacturingindustryoftheCRT‐relatedproductsintheUS.
6.2.1.2.5.7 CRTGlassRecyclingSummary
Noglass‐to‐glassrecyclingmarketforUSgeneratedCRTglass,marketsforreuseofCRTsinmanufacturingnewTVsisinAsia.
Onlyend‐useatthemomentforleadedCRTfunnelglassisaleadsmelter.NotenoughsmeltingcapacitytomanagethesupplyofleadedCRTfunnelglass.
Thereareend‐marketoptionsforCRTpanelglasswithoptionsinthebuildingproductsandinsulationmarketsXXII.
6.2.1.2.6 SubstitutedMethodologyforCRTExports
WhiletheUSmarketstillhashighdemandforFlatPanelTVsandrelatedproductsXXIII,itwasfoundthattherewerealmostnomanufacturersforCRTTVsintheUSatleastaftertheyearof2010.Inaddition,onlyasmallquantityofFlatPanelTVshavebeendomesticallyXXIVmanufactured.ThereportreleasedbyUSITC10‐intermsoftheirsurvey–alsostatedthatthe“UShaslimitedcapacitytoprocessusedelectronicsintwosegmentsoftheindustry—CRTglassandfinalsmelting—creatingincentivestoexportCRTmonitors,CRTglass,andcircuitboardsdestinedforsmeltingtoretrievepreciousmetals.Some CRTs are exported to large plants in Mexico, where they are reportedly washed and readied for further processing, and Canada, where the lead is removed. According to one industry source, it is likely that future U.S. exports of CRTs for recycling will end up in India, as the only other glass-to-glass furnaces in the world (in China and Malaysia) are scheduled to close by 2013.” An latest report of “U.S. CRT Glass Management: A Bellwether for Sustainability of Electronics Recycling in the United States” published by TransparentPlanet LLC XXV discussed about the current status of CRT recycling from the perspectives of:“Factors contributing to stockpiling,
XXIIWasteManagementWorld,2011,MarketforRecycledCRTGlassDryingUpasVolumesRise,Availableat:http://www.waste‐management‐world.com/articles/2011/09/market‐for‐recycled‐crt‐glass‐drying‐up‐as‐volumes‐rise.htmlXXIIIStatista,thestatistic(fromUSCensusBureau)illustratesthetelevision,VCRandothervideoequipmentimportsfrom2002to2011.TheUS.importsamountedto33,486millionUS.dollarsin2011.Availableat:http://www.statista.com/statistics/221693/us‐imports‐of‐tvs‐vcrs‐and‐video‐equipment‐from‐world/.
XXIVUnitedStatesCensusBureau,CurrentIndustrialReports:MA334M–ConsumerElectronics(2010Annual).Availableat:http://www.census.gov/manufacturing/cir/historical_data/ma334m/index.html
XXVTransparentPlanet LLC,2012.U.S.CRTGlassManagement:ABellwetherforSustainabilityofElectronicsRecyclingintheUnitedStates.http://transparentplanetllc.com/us‐crt‐glass‐management/
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estimated volumes and cleanup costs; Current volumes generated in the US and capacity for CRT recycling in North America; The case against landfilling-the race to the bottom”. This study concluded that “CRT industry experts estimate that 660 million pounds of CRT glass are currently being stored at locations throughout the US. It will cost between $85 million and $360 million to responsibly recycle all of this stockpiled glass, depending upon the condition of the glass; There are currently 16 companies with 24 US facilities processing CRT tubes in preparation for final recovery. None of these are operating at capacity in spite of what would seem to be a huge market demand. They simply cannot compete with stockpiling.”
To summarize,thereislimitedcapacityfortheUSmarkettoreuseandrecycle(glasstoglass,orleadrecovery)theCRTglass. These qualitativeanalysissuggestthattheoverseasmarketdominatesthereuseandrecycling.Duringthelast5‐10years,ThereisrelativelittlequantitativestudyonworldwideCRTglassmanufacturingwerefoundintheliteratureorontheInternet,suchasthehistoricalproductiondataofCRTTVsandglass20.
Thus,theHSOTDMwhichusestheused‐newthresholdtodifferentiatetheusedelectronicsisnotappropriateforCRTTVsandrelateditems(CRTtubeandCRTglass)becausealloftheseexporteditemscanbeclassifiedasused.Asaconsequence,weassumedthattheexportsofCRTTVsarealltheusedgoods,includingthecolorandmonochromeCRTTVs(852872and852873),CRTtubes(854011and854012)andtubeglass(701120).Itisunnecessarytoidentifyandestimatetheusedandnewproducts.
However,wecanstillusetheHSOTDMtoquantifyusedFlatPanelTVswhichhaveanindependenttradecode(8528726057)andthereareindeedmanufacturersforthisitem.SincethetotaldomesticexportofFlatPanelTVs(newandpotentialused)isquitesmall,therewasinsufficientdatafortheExportNVEMthresholds,soweonlyusedtheExportPub.Methodsecondarymarketsaleprices‐basedthresholdmethodtotracktheusedTVs,whichrangedfrom$100to200perunit.
ThesamesubstitutedmethodologyhasbeenappliedtoCRTmonitor,includingdesktopcombinedCRTmonitor(tradecodes8471410110and8471500110underthedesktops),CRTmonitor(852841)andCRTvideomonitor(852849).
6.2.2 DataandIntermediateResults
6.2.2.1 Used‐NewThresholdUnitValues
Used‐New thresholds for each geographical region, country‐income groups andtransportmethodbasedonexportunitvalueswere foundusingthreemethods,ofwhichtwo involved in the neighborhood valley‐emphasismethod, and the thirdmethod usingsalesvalues(showninTable39).Asareminder,USdomesticexportdataisappliedtoUSExport NVEM, Chinese export data was utilized in China Export NVEM, and sales valueestimates in Export Pub. Method.
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Table39:SummaryandComparisonoftheThresholdsforAllElectronics(unitvalue:$/unit)
UsedElectronics USExportNVEM(USExportdata‐
based)*
ChinaExportNVEM
(ChinaExportdata‐based)*
ExportPub.Method
(Salevalues‐based)
FlatPanelTVs 120‐200 N/A 100‐200CRTTVs N/A,AllUsed N/A,AllUsed N/A,AllUsed
Mobilephone 60‐195 65‐195 75‐150Desktop 305‐395 305‐400 200‐400**Server 290‐400 195‐400 300‐400**
OtherDesktop 440‐600 500‐600 400‐600**Laptop 100‐305 100‐300 200‐250
CRTMonitors N/A,AllUsed N/A,AllUsed N/A,AllUsedFlatPanelmonitor 140‐200 115‐200 100‐200**FlatPanelvideo
monitor 115‐200 110‐200 100‐200**
*Themin.andmax.valuesforUSExportNVEMorChinaExportNVEMforaspecificproductrepresenttheminimumandmaximumofallthresholdsacrossallworldregionsandincomegroups.;
**Estimatedwithsignificantuncertaintyduethelimitationofdata.Inaddition,thethresholdsofChinaExportNVEMforFlatPanelTVsaredifficulttoobtainduetothemixtureoftradecodes.
6.2.2.1.1.1 ExportPub.Method(allelectronics)
Thesalevalued‐basedthresholds(ExportPub.Method)formobilephone,FlatPanelTVs,desktopcomputerandmonitorsareshowninTable40.Bothduetothetimeconstraintsmentionedearlieranddataavailabilityfromtheplatforms,thesalespricesarebasedthresholdarebasedoninvestigationin2013,whichmaynotaccuratelyreflect2010prices.
Figure62belowshowsanexampleforthepricesgapbetweentheusedandnewlaptopsfoundfromAmazoninAugust,2012.Thereissignificantgabbetweentheusedandnew,whichindicatedthethresholdforusedcanbesetfrom$200‐250perunits.
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Figure62:PriceGapbetweentheUsedandNewLaptopsFoundfromAmazon(Aug.2012)
Inadditional,areportfromKwak(2012)didasurveyin2011tolookatthebuy‐backsalesvalueforusedlaptopandmobilephone100.Figure63100showsthepricesrangesassociatedwiththeageoftheusedlaptop,whichimpliesthattheolderofthelaptop,thelowerpricesfortheusedlaptoptobuyback.The2‐yearsoldlaptopcanresellwithanaverageunitpriceof$250.
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Figure63:Buy‐backPriceswithExcellentCosmeticConditionandnoHardwareFailure(surveyin2011,responses367).Theerrorbarsrepresentonestandarddeviationfromthemean.
Table40:AuctionSalePricesforUsedElectronicsfromVariousSources(unitvalue:$/unit)
Source FlatPanelTV
Mobilephone Computer Server Laptop Monitor Sale
Type Status
Babbitt,etal.201131 1.30‐275 1.40‐475 1.30‐385 0.40‐125 Resale Both**
Kwak,2012100 2‐115 2‐250 Trade‐Back Both
Recycle.net 10‐100 10‐50 10‐150 10‐50 Recycle Non‐working
Alibaba.com 50‐200 100‐150 50‐100 125‐250 25‐50 Resale BothEbay.com 100‐300 50‐125 200‐600 150‐400 50‐150 Resale Used
Amazon.com 250‐600 200‐250 ResaleUsed‐Likenew
PriceGrabber.com
200‐600 100‐500 250‐1000 300‐1000 200‐1000 100‐400 Resale Likenew
Thresholdusedinthisstudy
100‐200 75‐150 200‐400 300‐400 200‐250 100‐200 Used
*Asurveyhasbeendonein2008atArizonaStateUniversitybyBabbittetal.(2013).**Includingworkingandnon‐working.