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scientificdata

oPEN

DaTaDESCrIPTor

eckfrpdate

Product,building,and

infrastructurematerialstocks

datasetfor337Chinesecities

between1978and2020

XiangLi1,2,LuluSong3,4,QianceLiu5,XinOuyang1,2,tingMao2,3,HaojieLu2,3,LitaoLiu1,2,XiaojieLiu1,2,WeiqiangChen2,3,4?&GangLiu6?

Reliablecity-levelproduct,building,andinfrastructurematerialstocksdataareessentialfor

understandinghistoricalmaterialusepatterns,benchmarkingmaterialefciency,andinforming

futurerecyclingpotentials.However,suchurbanmaterialstocksdataareoftenlimited,dueprimarily

tounavailable,inconsistent,ornoncontinuouscity-levelstatistics.Here,weprovidedsuchanUrban

Product,Building,andInfrastructureMaterialStocks(UPBIMS)datasetforChina,acountrythat

hasundergonearemarkableurbanizationprocessinthepastdecades,bycollatingdiferentofcial

statisticsandapplyingvariousgap-fllingmethods.Thisdatasetcontainsthestockof24materials

containedin10typesofproducts,buildings,andinfrastructureinall337prefecture-levelcitiesinChinafrom1978to2020.Thisqualitycontrolledandunifeddatasetisthefrstofitskindwithsuchafull

coverageofallprefecture-levelChinesecitiesandcanbeusedinavarietyofapplications,forexampleinurbangeography,industrialecology,circulareconomy,andclimatechangemitigation.Everypieceofdataistaggedwithitssourceandthedatasetwillbeperiodicallyupdated.

Background&Summary

Urbanizationisoneofthemostimportantfactorsinhumanhistorythatdrivestheglobalconsumptionofnat-uralresourcestoanever-highlevel.Forexample,thestocksofman-madematerialswereestimatedtoalreadyoverweighalllifeonearth

1

,leadingtoprofoundchangesinessentiallife-sustainingfunctionsoftheplanetEarth.TeUnitedNationsEnvironmentProgramme(UNEP)warnedthatfurtherurbanizationanddemandforurbanservicessuchasshelteringandmobilitycouldraisetheannualuseofresourcestonearly90billiontonnesby2050,a125%increasefrom40billiontonnesin2010

2

.Sustaininglong-termresourceuseandminimizingconsequentenvironmentalimpactsaccompaniedbycontinuousurbanizationrequiresthusagoodunderstand-ingofhowwehavebeenaccumulatingmaterialsinproducts,buildings,andinfrastructure(socalledin-usestocks)forurbanservices

3

.Tespatiotemporalpatternsofsuchstockscanhelprevealtheexchange,storage,andtransformationofmaterialsbetweenthenaturalenvironmentandcitiesandbenchmarkmaterialefciency

4

andinformfutureresourcedemand,wastemanagementchallenges,andurbanminingpotentials

5

–

8

.

Asthemostpopulousandworld’ssecond-largesteconomy,Chinaisanidealcaseforexploringthehistoricalmaterialstocksdevelopmentpatternatcitylevel

9

.Teenormousrural-urbanpopulationmigrationandgrowthofcitiesinChinainthepastfourdecadeshaveresultedinaprofoundexpansionofurbanbuiltenvironmentstocks

10

,

11

.Forexample,between1990and2010,China’sshareinglobalmaterialstocksincreasedfrom10%to22%

12

.TiscontinuouslyexpandingurbanresourcedemandfurtherincreasespressureonChina’salreadychal-lengingresource,waste,andclimatechallenges

13

,

14

.

1InstituteofGeographicSciencesandNaturalResourcesResearch,ChineseAcademyofSciences,Beijing,100101,china.2UniversityofChineseAcademyofSciences,Beijing,100049,China.3KeyLabofUrbanenvironmentandHealth,InstituteofUrbanEnvironment,ChineseAcademyofSciences,361021,Xiamen,Fujian,China.4XiamenKeyLabofUrbanMetabolism,361021,Xiamen,Fujian,China.5DepartmentofGreentechnology,UniversityofSouthernDenmark,Odense,5230,Denmark.6CollegeofUrbanandEnvironmentalSciences,PekingUniversity,100871,Beijing,china.?e-mail:

wqchen@

;

gangliu@

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Generally,in-usematerialstockscanbeestimatedbyeitheratop-downorabottom-upapproach

5

.Tetop-downmethodisofenemployedtoevaluatetheglobalandnationalmaterialstocksbyconsideringthedif-ferencesbetweeninfows(ofenavailablefromindustrialstatistics)andoutfows(estimatedbasedonlifetimedelay)ofmaterials

15

,

16

.However,thisisofenchallengingformaterialstockestimationontheregionalorcitylevelsduetothelackofmaterialconsumption(infow)statistics.Instead,thebottom-upmethodisofenusedtoestimatetheurbanmaterialstocksbycountingeachitemofproducts,buildings,andinfrastructureandmul-tiplyingbytheircorrespondingmaterialintensity

4

.ForChinaforexample,afewstudieshavecalculatedChina’sin-usematerialstocksatthenational

17

,

18

andprovinciallevels

18

,includingwithproduct(e.g.,asinfrastruc-tureandhouseholddurablegoods)andmaterial(e.g.,24typesofmaterialsconsideredinsomestudies

14

,

19

,

20

)resolution.Terearealsoafewattemptsoncharacterizingmaterialsstocksforlargecities(e.g.,Beijing

21

,

22

,Chongqing

23

,andXiamen

24

)inChina;yettheoverallcitycoverageisverylowandmediumandsmallcitiesareusuallyexcluded.Tisrelatesmainlytodatagapsonthecitylevelcausedby,e.g.,inconsistentornoncontinuouslocalstatisticsandchangeofadministrativeareas.Consideringthereare337prefecture-levelcitiesinChinaandtheyareatvaryingurbanizationstagesandhavedistinctdevelopmentalpathways

25

,itwouldbeimportanttodevelopacompletedatasetthatcoversallcitiesandyearstorevealthespatiotemporalpatternsofurbanproduct,building,andinfrastructurematerialstocks

20

.

Inthisstudy,weaimtoprovidesuchanUrbanProduct,Building,andInfrastructureMaterialStocks(UPBIMS)datasetforChinathathavebeencompiledbycollatingurbanmaterialstockrelatedstatisticaldatafromvariousyearbooks,bulletins,andagencies.Moreover,wehaveflledgapsformissingdata(about55%ofallthedatarecords)basedonrationalprinciplesandconsistentassumptions.Eventually,basedonabottom-upstockaccountingmethod,wepresentadatasetontotalweightand24typesofmaterialcontainedin10subtypesofproducts,buildings,andinfrastructure(whicharefurthercategorizedintoresidentialbuildings,nonresiden-tialbuildings,roads,urbanrails,pipes,otherinfrastructure,vehicles,agriculturalmachinery,industrialmachin-ery,andappliances)inactiveusein337citiesofmainlandChinafrom1978to2020.

Terestofthepapersummarizestheaccountingscopes,datasources,andgapfllingapproachesweusedandthequalityofthisdataset.Wewillmaintainandperiodicallyupdatethisdatasetinthefuture.Tiscom-prehensiveandconsistentdatasetofmaterialstocksofallChineseprefecture-levelcitiescanhelpunderstandspatiotemporalpatternsofurbanweightgrowth,informfuturematerialsdemandassociatedwithcontinu-ousurbanization,optimizeconstructionanddemolitionwastemanagement,facilitatediscussiononembod-iedemissionsofconstruction,andthussupportthecircularandlow-carbontransitionofcitiesinChinaandbeyond.

Methods

Spatialandtemporalboundary.BasedonChina’sadministrativedivisions,ourdatasetcoveredall

337majorcitiesinChina,includingfourmunicipalitiesdirectlyundertheCentralGovernment(i.e.,Beijing,Shanghai,Tianjin,andChongqing)and333prefecture-levelcitiesbelongingto23provincesand5autonomousregions.Teircodesandchangesofnamesinthepast43yearsareavailableinsheet‘Code’infle‘Datasource.xlsx’onFigshare

26

.Ourspatialaccountingscopeismunicipaldistrictsandtownships

23

.Allthese337citieshostover64%ofChina’spopulationandcoverabove75%ofbuilt-upareainChina.Tetimehorizonofourdatasetisfrom1978(whenChinastarteditsreformandopening-upandthuscitiesstartedtogrow)to2020(whenthelatestdataareaccessible).Allcomputationswereperformedintime-discretestepsofoneyear.

Materialstocksofproducts,buildings,infrastructure.Weusedabottom-upstockaccountingmethod

15

,27

andcountedallpiecesofproducts,buildings,andinfrastructureincitiesovertimetodeterminetheirembodiedmaterialstocks.Tescopeofurbanproduct,building,andinfrastructurestockitemsandcorrespond-ingestimationmethodsanddatasourcesfortheirembodiedmaterialstocksaresummarizedinsheet‘Scope’infle‘Datasource.xlsx’onFigshare

26

anddescribedindetailinthefollowingsections.

Wehaveattemptedtoincludeallproducts,buildings,andinfrastructureinthesecities.Tisaddsupto10typesofproducts,buildings,andinfrastructure(detailsinsheet‘Scope’infle‘Datasource.xlsx’onFigshare

26

).Basedonsignifcanceofembodiedmaterialsandavailablematerialintensitydata(detailedinfle‘Datasource.xlsx’and‘Materialintensity.xlsx’onFigshare

26

),weconsidered24typesofmaterials,including13typesofbasematerials(steel,copper,aluminum,timber,brick,gravel,sand,asphalt,lime,glass,cement,plastic,andrubber),3typesofpreciousmetals(gold,silver,andpalladium),4typesofraremetals(indium,neodymium,yttrium,andeuro-pium),and4typesofothermetals(lead,zinc,magnesium,andcobalt).

Datasources.Tedataonurbanproduct,building,andinfrastructurestockitemsarefromofcialstatistics

orotherwiseestimationsbaseduponrationalprinciplesandconsistentassumptions.Atotalof1259ofcialsta-tisticalbulletinsoryearbookswerecompiledandusedtoderivedataforpopulationandproducts,buildings,andinfrastructure(detailsinsheet‘References’infle‘Datasource.xlsx’onFigshare

26

).Teseoriginalstatisticaldata,however,onlydirectlyreport45%ofallpossiblestockdataacrosscity,time,andtypeofstock.Inthefollowingsections,wehavedescribeddiferentsourcesandresponsibledepartmentsofsuchstatisticsandhowwehaveflledthedatagapssystematically(detailsinsheet‘Statistics’infle‘Datasource.xlsx’onFigshare

26

).

Householdsurveydataforbuildingsandappliances.Weobtainedthestockofurbanresidentialbuildingsandhomeappliancesbymultiplyingtheperhousehold(orpercapita)stockandthenumbersoffamily(orpopulation).Tisisbecausepercapitaresidentialfoorarea(PC-RA)andtheamountofhomeappliancesper100urbanhouseholds(PH-UA)arecoveredbythehouseholdsurveyoftheNationalBureauofStatisticsofChina(NBSC).

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Suchhouseholdsurveywasbaseduponastratifedmultistagerandomsamplingmethod.Forexample,in2021,theNBSCselectedabout160,000urbanhouseholdsfrom1,800counties/districtsacrossChina.Attheendofeachquarter,thesurveyresultsareaggregatedupwardfromthecountyleveltothenationallevelandpublishedbytheNBSC.TisdatasummarymethodmeansthatthePC-RAandPH-UAdataarequarterlyandcounty/dis-trictbased.Itshouldbenotedthat,aferChinaintroducedtheurban-ruralintegrationplanin2013,thesamplingscopeaccordinglyexpandedfrommunicipaldistrictstomunicipaldistrictsandtownshipsintheurban-ruralfringe.Nevertheless,thesamplesizeoftownshipsismuchsmallerthanthatofmunicipaldistricts,sothatsam-plingscopechangeafectedonly24%ofthecities(withadecreaseorincreaseofstockbymorethan10%).Terefore,wehavedisregardedthisscopechangeforthesakeofconsistencyinstatisticalcaliber.

TeseaggregatednationalandprovincialdataareannuallypublishedintheChinaStatisticalYearbook,ChinaHouseholdSurveyStatisticalYearbook,andtheNationalStatisticalDataReleaseDatabase.However,itisofendifculttogetthedataforsuccessiveyearsatthemunicipalorcitylevel,duetolackofstrictrulesonthefrequencyofdatarelease.Telocalgovernmentsandstatisticaldepartmentspublishsurveyresultsonlyforselectedyearsintheirstatisticalbulletinsandyearbooks.

ItshouldbenotedthattherearenoofcialdataonnonresidentialbuildingfoorareasinChina.Afewprevi-ousstudiesestimatedthestockofnonresidentialbuildingssimplythesameasthatofresidentialbuildings

15

,22

,23

.Wehaveimprovedthisestimationbyapproximatingtheratiosofresidentialtononresidentialbuildingfoorareasofthesecitiesbasedontheircorresponding,andlargelyavailable,provincialratios.

Duetodatagapsandourfocusonurbanareas,thebuildingstocksinruralareaswithintheurbanmunicipaladministrativeboundariesareexcludedfromthisanalysis.Tebuildingstocksinruralareasdidnotexperienceadramaticchangecomparingtourbanbuildingstocks.Indeed,ithasgrownlessthan18%from2000to2015

28

,andsuchagrowthrateisfurtherdeclining

29

withthecontinuousurbanization.

Ministerialstatisticsforinfrastructure,machinery,andvehicles.Infrastructure,machinery,andvehiclestockdataarecollectedandmaintainedbyrespectiveministriesinChina,althoughnotalwayswithaconsistentbasis.Forexample,thestockofallvehicles(includingpassengervehicles,trucks,andmotorcycles)istrackedbytheMinistryofPublicSecurity(MPS)andtheirlocalbranches.So,thevehiclestockdataatthecity/municipalitylevelsarepublishedbythelocalstatisticalbureau,whiletheNBSCpublishesnationalandprovincialaggregateddataintheChinaStatisticalYearbook.Wewereabletogatherdataonvehiclestocksfromthelocalstatisticalyearbooksandlocalstatisticalbulletinsofall337cities.

Similarly,theMinistryofHousingandUrban-RuralDevelopment(MOHURD)isinchargeoftheinfrastruc-turedatainChina.TeMOHURDpublishestheend-of-yearinfrastructurestockdataintheChinaUrban-RuralConstructionStatisticalYearbookandChinaUrbanConstructionStatisticalYearbookatthecitylevelsince2002,whichincludesdataonroads,subways,pipelines,andstreetlamps.Tedataforpreviousyears(1978–2001)canbeobtainedfromthestatisticalbulletinsandyearbookspublishedbylocalgovernmentsandthelocalstatisticalbureau. MinistryofAgricultureandRuralAfairs(MARA)takescareoftheadministrationandcompilationofagri-culturalmachinerydata.Testock(installedcapacity)ofagriculturalmachinerycanbeobtainedfromthelocalstatisticalyearbooksandlocalstatisticalbulletinsofall337cities.Testockofindustrialmachineryisunfortu-natelynotavailableinanystatistics.Instead,weapproximatedtheirinstalledcapacitybasedonthestockofagri-culturalmachineryandthetotalpowerconsumptionbyagriculturalandindustrialmachinery.Tismethodhasbeenappliedbeforeinquiteafewsimilarstudiesduetothedataunavailabilityofindustrialmachinery

23

,24

,30

–

32

.Andmostofthemindicatedhighuncertaintiesbutlowsensitivityforthismethod

23

.

Populationandurbanization.Tedataonpopulationandthenumberoffamiliesinthecitiesarekeyto

ourresults,particularlyforscalinguppercapitaresidentialfoorareasandper100householdsappliances,andtheywereobtainedfrompopulationsurveysinitiatedbytheNBSCandlocalgovernments.Toestimatematerialstocksinmunicipaldistrictsandtownships,wechosetousetheurbanpermanentpopulationwhichreferstotheactualpopulationlivingthereforoversixmonths,asopposedtohouseholdregistrypopulation.TisisalsoconsistentwiththesamplingscopeofhouseholdsurveyoftheNBSC(sourceforourresidentialbuildingandappliancesdata).

ThepermanentpopulationdataarefromthreetypesofpopulationsurveysinChina.Thefirstisthecountry-widecensus,whichisconductedeverytenyears.TedataforthoseyearsendingaszerocomefromthiscensuswhichcanbeobtainedfromtheNBSC.Tesecondisthesamplesurveyof1%ofthenationalpopulation,whichisconductedeveryfveyears.Tedataforthoseyearsendingasfvecomesfromthissurveywhichcanbeobtainedfromtheprovincialbureauofstatistics.Tethirdisthenationalpopulationchangesurveywhichisconductedeveryyearexceptfortheyearswhenthefrsttwotypeswereconducted.Tesamplesizeaccountsforabout1‰ofthetotalpopulation.However,thesepermanentpopulationdataarenotpublishedconsist-entlyacrosscities.Weflledinthemissingdatabasedontrendextrapolationbetweentotalurbanpermanentpopulationandurbanizationrateofcities.Tisisdeemedacceptablebecauseoverallthemissingshareoftotalpopulationinall337citiesisonly11%(detailsinsheet‘Statistics’infle‘Datasource.xlsx’onFigshare

26

).Tenumberoffamiliesinthe337citieswasestimatedbaseduponperhouseholdpopulationfromhouseholdsurvey.

Datagapfllingandestimation.Signifcantamountsofmissingvaluescanbeobservedintheinitially

compileddatabase.Tisrelatesforexampletoeitherdiscontinuityinthedatareleasedbyprefecture-levelgov-ernmentsandstatisticalagencies,orthechangeofscopeofurbanadministrativeregionsovertime(seeFig.

1a

).Wehavedocumentedtheoriginaldatasourceofeachitemusedintheformulaandcalculatedthemissingratioofallitemsinstockcalculationfunctionsin‘Datasources.xlsx’onFigshare

26

.Dependingonthepatternsand

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Fig.1Patternsofmissingdataandcorrespondinggapfllingmethods:(a)theproportionsofestimateddatabasedondiferent

gapfllingmethodsbyproducts,buildings,andinfrastructure;and(b)sharesandexamplesofdatafllingmethods.

proportionsofmissingvaluesoftheseitemsacross43years(from1978to2020)in337cities,threediferentmethodswereusedeitherindividuallyorincombination(seeFig.

1b

)tofllthegaps:

?MethodIestimationisbasedpartiallyonlinearinterpolation.Weusedthismethodtoflldatagapsforthoseserieswithamissingratebelow10%ormissingdatabetweentwoyears.Tis10%issetbasedonthestatisticalprinciple

33

thatifthemissingrateismoresignifcantthan10%,theresultofsubsequentstatisticalanalysesmaybebiased.

?MethodIIestimationisbasedpartiallyontheprovincialstockgrowthrate.Weusedthismethodtofllgapsforthoseserieswithamissingrateabove10%.Tisisparticularlythecaseforcontinuouslymissingvaluesbeforethestartingyearorafertheendingyearwithvaluesintheseries.Teprovincialstockgrowthrate,whichwasderivedfromavailablestatisticsontheprovinciallevel,wasappliedtothecityleveltoestimatethesemissingvalues.

?MethodIIIestimationisbasedentirelyonproxy.Weusedthismethodtofllgapswheretherearenocity-leveldatamainlyforthreetypesofissues.Tefrstreferstomissinghouseholdsurveyvaluesforsomecitiesinrecentyears;andweassumedthemthesameastheprovincialaverages.Tesecondtypereferstomissingabsolutevolumesforsomecities;andweapproximatedthembymultiplyingprovincialdatawiththesecities’shareofGDPintheirprovinces.Tethirdtyperelatestotheconversionratioassumptionsamongproducts,asweelaboratedabovefornonresidentialbuildings(basedonresidentialbuildingsandlanduse)andindus-trialmachinery(basedonagriculturalmachinery).

Intheend,wehavesuccessfullyflledallthedatagapsthatinitiallyaccountforapproximately55%ofalldatapoints.Although17%ofthedatawerepopulatedusingMethodIII(proxy)alone,morethan50%outoftheseproxydatawerebasedactuallyonhouseholdsurveys(detailsinsheet‘Statistics’infle‘Datasource.xlsx’onFigshare

26

).Tisratiomeansthatmostofthemissingdataisflledinonthebasisofsomesortofofcialstatis-tics.Hence,oureventuallyimputeddatasetisdeemedasreasonablyaccuratetorevealtheoverallspatiotemporalpatternsofproduct,building,andinfrastructurematerialstocksamongcities.

Materialintensity.Tematerialintensities(MI)ofthe24typesofselectedmaterialswerecompiledfrom

literature

14

,

19

,

23

,

32

,

34

–

47

.DuetolimitedprimaryMIdata,quiteafewstudiesrefertothesamesourcesforMIesti-mation;andinsuchcases,weonlylistedthosereferencesthatfrstreportedtheseMIdata.TeMIdataweredescribedindetailinouropen-accessonlinedatasetFigshare

26

.

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DataRecords

Tisdatasetcontainsthreecoretables,whichareallprovidedasxlsxflesandarefreelyavailablethroughFigshare

26

.Atotalof1,741,680datarecordsarecontainedinthedataset.Ofthese,

?159,401recordsareweightintotalandby11typesofmaterialsembodiedinurbanresidentialbuildingsin337citiesfrom1978to2020[‘Urbanresidentialbuildingstocks1978–2020.xlsx’onFigshare

26

];

?159,401recordsareweightintotalandby11typesofmaterialsembodiedinurbannonresidentialbuildingsin337citiesfrom1978to2020[‘Urbannonresidentialbuildingstocks1978–2020.xlsx’onFigshare

26

];

?101,437recordsareweightintotalandby7typesofmaterialsembodiedinroadsin337citiesfrom1978to2020[‘Roadstocks1978–2020.xlsx’onFigshare

26

];

?115,928recordsareweightintotalandby8typesofmaterialsembodiedinurbanrailsin337citiesfrom1978to2020[‘Urbanrailstocks1978–2020.xlsx’onFigshare

26

];

?86,946recordsareweightintotalandby6typesofmaterialsembodiedinpipelinesin337citiesfrom1978to2020[‘Pipelinestocks1978–2020.xlsx’onFigshare

26

];

?43,473recordsareweightintotalandby3typesofmaterialsembodiedinotherinfrastructure(streetlampsandtelecommunications)in337citiesfrom1978to2020[‘Otherinfrastructurestocks1978–2020.xlsx’onFigshare

26

];

?144,910recordsareweightintotalandby10typesofmaterialsembodiedinvehiclesin337citiesfrom1978to2020[‘Vehiclestocks1978–2020.xlsx’onFigshare

26

];

?43,473recordsareweightintotalandby3typesofmaterialsembodiedinagriculturalmachineryin337citiesfrom1978to2020[‘Agriculturalmachinerystocks1978–2020.xlsx’onFigshare

26

];

?14,491recordsareweightintotalandby1typeofmaterialsembodiedinindustrialmachineryin337citiesfrom1978to2020[‘Industrialmachinerystocks1978–2020.xlsx’onFigshare

26

];

?188,383recordsareweightintotalandby13typesofmaterialsembodiedinappliancesin337citiesfrom1978to2020[‘Appliancestocks1978–2020.xlsx’onFigshare

26

];

?57,964recordsaretotalmaterialstocks,percapitamaterialstocks,urbanpopulations,andhouseholdnum-bersof337citiesfrom1978to2020[‘Materialstockandpopulation1978–2020.xlsx’onFigshare

26

];

?654recordsarematerialintensitydataandcorrespondingsourcesforthe24materialsembodiedin42typesofproducts,buildings,andinfrastructure[‘Materialintensity.xlsx’onFigshare

26

];

?625,219recordsaretheoriginaldatasourcesforthepopulationand42typesofproducts,buildings,andinfra-structureitemsinthe337citiesfrom1978to2020[‘Datasource.xlsx’onFigshare

26

].

TechnicalValidation

Dataoverview.TematerialstocksinChinesecitieshave