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24thInternationalInput-OutputConference,5-8July2016,Seoul,Korea

SpecialSession"Input-OutputVirtualLaboratories"

AnInput-OutputVirtualLaboratoryinpractice–Surveyoftheuptake,usageandapplicationofthefirst

operationalIELab

ThomasWiedmann1,2

1. SustainabilityAssessmentProgram(SAP),WaterResearchCentre,SchoolofCivilandEnvironmentalEngineering,UNSWAustralia,Sydney,NSW2052,Australia

2. ISA,SchoolofPhysicsA28,TheUniversityofSydney,NSW2006,Australia

Abstract

TheIndustrialEcologyVirtualLaboratory(IELab)isarecentlyestablishedcollaborativecloud-computingplatformforcompilinglarge-scale,high-resolution,enviro-socio-economicaccountsbasedonmulti-regioninput-output(MRIO)tablesandforconductingintegratedsustainabilityassessmentprojects.Theseinclude,forexample,publishedtriplebottomlineassessmentsofbiofuels,low-carbonconstructionmaterialsorhigh-resolutionwastemodelling.ThiscontributionprovidesastructuredreviewofIELabapplicationsthatwerepublishedineitherpeer-reviewedjournalpapersorintheformofconferenceproceedings.Themainresearchquestionposedis"WhatarethespecificfeaturesofIELabthatwereusedintheresearchandcouldtheresearchhavehappenedwithoutthem?"ItisthusinvestigatedwhethertheIELabhasactuallyandtrulyenablednewresearch.AdetailedanalysisofIELabcharacteristicsandtheirusageispresented.TheresultscanhelpwiththedesignofnewresearchprojectsandinformexistingandprospectiveusersoftheIELababouttheoptionsforacademicresearchandpracticalapplications.

Keywords

Industrialecology,virtuallaboratory,survey,input-outputanalysis,multi-regioninput-outputtables

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1. Introduction

Achievinglong-termsustainabilityrequiresregionalandindustryspecialisationstrategiesandthedevelopmentofandinvestmentinenergysystems,citiesandtransportinfrastructurewithverylowcarbonemissionsandresourcerequirements.TheseissuesareattheheartofIndustrialEcology,arapidlygrowingfieldthatsystematicallyexamineslocal,regionalandglobalmaterialsandenergyusesinproducts,processes,industrialsectorsandeconomies.WiththepublicationofaspecialsectioninPNAS,IndustrialEcologyhasbecomeamainstreamacademicdisciplineWeiszetal.,2015.

AstheresearchquestionsandapplicationsinIndustrialEcologyincrease,sodotherequirementsfordataandformoresophisticatedmethods,modelsandtoolstoenabledecision-makingbasedonquantitativeassessments(PauliukandHertwich,2016).Thisinturnnecessitatesadvancedcomputingandsoftware.Pauliuketal.,2015recentlyproposedgeneralprinciplesandpracticalguidelinesforopensoftwaredevelopmentanddistributioninIndustrialEcology.Theauthorsalsopresentedopensourcecodeforseveraloften-encountereddatahandlingandmodellingtasks.

TwomajormethodsinIndustrialEcologyresearcharebecomingincreasinglyusefulinenablingmultidisciplinarystudiesonthehumanimpactanddependencyonthenaturalenvironment:multi-regioninput-output(MRIO)analysisandHybridLCA(HLCA).TheneedforimprovedMRIOandHLCAdevelopment,synthesisandutilisationhasbeenrepeatedlyexpressedatinternationalworkshopsandconferences,inscientificarticlesandbyinternationalorganisationssuchastheOECD,UNEPandEurostat(HellwegandMilàiCanals,2014;OECD,2015;WiedmannandBarrett,2013).

GlobalMRIOmodelshaveevolvedrapidlyinthelast5-10years(TukkerandDietzenbacher,2013;Wiedmannetal.,2011)andhaveenabledsignificantnovelinsightsandapplications,publishedintop-rankingjournals,e.g.ontheinternationalresponsibilityforgreenhousegasemissions(Davisetal.,2011;Kanderetal.,2015;Petersetal.,2011;Steinbergeretal.,2012)andnitrogenpollution(Oitaetal.,2016),onthetrueextentofnations'resourceuse(Wiedmannetal.,2015b)orontheultimatedriversofglobalbiodiversityloss(Lenzenetal.,2012b).Duchinetal.,2015andDuchinandLevine,2015showedhowstaticMRIOanalysiscanbeextendedintoadynamicframework,basedonworldtrademodelling,thatenablestheexplorationofalternativescenariosaboutpossiblefuturedevelopments.Anotherdevelopmenthasbeentheanalysisofembodiedenvironmentalimpactsatsub-nationalscale,asforexampleillustratedbyFengetal.,2013forinter-provincialflowsofembodiedCO2emissionsinChina.Bachmannetal.,2014demonstratedthebenefitsofusingmulti-scaleMRIOmodelswheresub-nationalregionsofacountryarenestedinaglobalMRIOtabletoachieveabetterrepresentationoftradeflowsbetweenregionsandcountries.

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ThereisalsotheneedtointegratedatafromotherdomainsordisciplinesaspromotedbyHeijungsetal.,2013andCucurachietal.,2014forthecaseofimpactsassessmentinLCA.

Allofthesedevelopmentsrequireimprovedcomputationalstructureandcapacity,datamanagementandmodelintegration.In2012,aradicallynovelandhighlyautomatedapproachtoMRIOcompilationwasintroducedbyLenzenetal.,2012aaspartofthecreationoftheEoraglobalMRIOdatabase.ThisconceptofautomatedMRIOcompilationwasadoptedandfurtherdevelopedintheAustralianIndustrialEcologyVirtualLaboratory(IELab,https://ielab.info)whichisacollaborative,cloud-basede-researchplatformforcompilinglarge-scale,high-resolution,enviro-socio-economicaccountsandforconductingintegratedsustainabilityassessmentprojectsforawiderangeoftopics(Lenzenetal.,2014).IELabhas(a)unprecedenteddetail(upto1,284sectorswithin2,214regions)toenablemorein-depthHLCA,(b)aflexibleMRIOtablestructure,tailoredtosuitspecificresearchquestionsand(c)highlyautomatedworkflows,greatlyexpeditingruntimesonanopen-accessplatform.

TheIElabhassucceededinbringingtogetheradiversesetofsustainabilityresearchersandpractitioners,enablingtangible,inter-disciplinaryresearchoutputs.Theseincludepublishedtriplebottomlineassessmentsofindustrialbiofuelproductionandlarge-scalebiorefining,analysesoflow-carbonconstructionmaterials,electricitysupplyandcitiesandhigh-resolutionwastemodelling,amongstothers(seeTable1).TheIELabalsoprovidesamuch-usedbasisfordataandanalysisinindustry-relevant,cooperativeresearch,includingintegratedsustainabilityassessmentsandtoolsfortheconstructionandwaterindustries.

PerhapsthemostsignificantachievementoftheIELabtodateistheabilitytocontinuouslysynthesiseandmakeavailableinformationthatcapturestheinterconnectionsbetweennature,economyandsocietywithahighdegreeofdiversity.Itdoessointheformofextendedmulti-regioninput-outputtables(MRIOTs).IELabmadealeapintheautomatedcompilationofnotoriouslyscant,heterogeneous,disparate,misalignedandoftenincompletedatasets,overcomingthesignificantlimitationsofsimilardatabases(Wiedmannetal.,2011).ThankstotheefficiencyofautomateddatafeedswrittenbyusersthemselvesandthecollaborativenatureofIELab,sustainabilityresearchcanbecomemoreefficient,timelyandeffective,enablingmanymoreresearchapplicationsthanwerepreviouslypossible.The'analyticaltoolbox'inIELabincludessustainabilitybenchmarking,embodiedimpact(environmentalfootprint)calculationandsupply-chainanalysis,allsignificantlyenhancingthecapabilityforanintegratedassessmentofnewtechnological,economicorsocialapproaches.

ButhowusefulactuallyistheIELabforIndustrialEcologyresearchandapplicationsingeneral?Thisisoneofthequestionsinvestigatedinthispaper.Morespecifically,this

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contributionaimstoexplorewhatthespecificfeaturesofIELabarethatwereusedinresearchandwhethertheresearchcouldhavehappenedwithoutthesefeatures.ItisthusinvestigatedwhethertheIELabhasactuallyandtrulyenablednewresearch.Thenextsectionexplainsthemethodusedandthepublicationsthatwereinvestigated.Thisisfollowedbyapresentationanddiscussionoftheresults(section3)andanoutlineofthelimitationsofthisstudy(section4).Section5concludesandprovidesanoutlookonfuturedevelopmentsoftheIELab.

2. Methodandstudies

ThemethodusedinthispaperisasurveyamongstauthorsofpublicationsthatdescriberesearchundertakenwiththeIELabaswellasareviewofthesepublications.Mostofthemareintheformofpeer-reviewedjournalpapers,someintheformofconferencepapers.Intotal,30publishedcasestudieswereinvestigated(Table1),referredtoas"studies"inthefollowing.

Table1:PublishedworkbasedonusingtheIELabanditsspecialfeatures(inalphabeticalorderofreference)

Topic(publicationtitle) Reference SpecialIELabfeaturesusedUpdatingtheWIODdatabaseinacollaborativevirtuallaboratory

AbdRahmanetal.,2016

detailedsectors,balancing,heatmaps,diagnostics

Urbancarbontransformations:unravellingspatialandinter-sectorallinkagesforkeycityindustriesbasedonmulti-regioninput-outputanalysis

Chenetal., regionalisation,non-surveymethods,balancing,heatmaps,standarddeviationtables,satellitedata,footprintcalculations

Transnationalcitycarbonfootprintnetworks–ExploringcarbonlinksbetweenChineseandAustraliancities

Chenetal.,submitted-a

detailedsectors,regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

CityCarbonFootprintNetworks Chenetal.,submitted-b

regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

CarbonFootprintingtheGoldCoastCityconsumptionofgoodsandbuiltenvironmentproducts

Elyetal.,2015 regionalisation,non-surveymethods,satellitedata,footprintcalculations

AnewsubnationalMRIOtableforIndonesia Faturayetal.,2016

regionalisation,non-surveymethods,balancing,heatmaps,diagnostics,satellitedata,footprintcalculations

AnAustralianMulti-RegionalWasteSupply-UseFramework

Fryetal.,2015 detailedsectors,hybridisation,regionalisation,balancing,heatmaps,diagnostics,satellitedata,footprintcalculations

Constructingatime-seriesofphysicalinput-outputtablesforAustralia

Fryetal.,submitted

detailedsectors,heatmaps,satellitedata

Investigatingalternativeapproachestoharmonisemulti-regionalinput-outputdata

Geschkeetal.,2014

detailedsectors,balancing,heatmaps,diagnostics

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Topic(publicationtitle) Reference SpecialIELabfeaturesusedASupply-UseApproachtoWasteInput-OutputAnalysis

LenzenandReynolds,2014

detailedsectors,hybridisation,balancing,heatmaps,diagnostics,satellitedata,footprintcalculations

TheGlobalMRIOLab–chartingtheworldeconomy

Lenzenetal.,2016

detailedsectors,hybridisation,balancing,heatmaps,diagnostics,satellitedata,footprintcalculations,structuralpathanalysis

Simulatingtheimpactofnewindustriesontheeconomy:ThecaseofbiorefininginAustralia

Maliketal.,2014

detailedsectors,hybridisation,balancing,heatmaps,satellitedata,footprintcalculations

Hybridlife-cycleassessmentofalgalbiofuelproduction

Maliketal.,2015

detailedsectors,hybridisation,regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

Triplebottomlinestudyofalignocellulosicbiofuelindustry

Maliketal.,2016

detailedsectors,hybridisation,regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

ThecarbonfootprintofAustralia'shealthcaresector(titletbc)

Malik,2016a detailedsectors,hybridisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

Input-outputanalysisforislandeconomies Malik,2016b detailedsectors,hybridisation,regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

TheEXIOLabinaction–howvirtuallaboratoriescanhelpmakeIO-basedresearchmoretimelyandtopical

Reyesetal.,2016

detailedsectors,balancing,diagnostics,standarddeviationtables,satellitedata,footprintcalculations

AWasteSupply-UseAnalysisofAustralianWasteFlows

Reynoldsetal.,2014

detailedsectors,satellitedata

Estimatingindustrialsolidwasteandmunicipalsolidwastedataathighresolutionusingeconomicaccounts:aninput–outputapproachwithAustraliancasestudy

Reynoldsetal.,2015a

detailedsectors,satellitedata

Evaluationoftheenvironmentalimpactofweeklyfoodconsumptionindifferentsocio-economichouseholdsinAustraliausingenvironmentallyextendedinput–outputanalysis

Reynoldsetal.,2015b

detailedsectors,satellitedata,footprintcalculations

Asub-nationalEconomicComplexityanalysisofAustralia’sstatesandterritories

Reynoldsetal.,inpreparation

detailedsectors,regionalisation,non-surveymethods,balancing,standarddeviationtables

Sleep Reynolds,2015

detailedsectors,satellitedata,footprintcalculations

AccountingforTransportImpactsontheEconomy:AnIntegratedComputableGeneralEquilibriumandTransportModel

RobsonandDixit,2016

regionalisation,non-surveymethods,balancing,satellitedata

Hybridinput–outputlifecycleassessmentofwarmmixasphaltmixtures

Rodríguez-Allozaetal.,2015

detailedsectors,hybridisation,regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

IntegratedCarbonMetricsandAssessmentfortheBuiltEnvironment

Tehetal.,2015

detailedsectors,hybridisation,balancing,satellitedata,footprintcalculations

ConstructionofMulti-RegionalInput–OutputTablesUsingtheCharmMethod

TöbbenandKronenberg,2015

regionalisation,non-surveymethods,balancing,heatmaps,diagnostics,satellitedata

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Topic(publicationtitle) Reference SpecialIELabfeaturesusedConstructingaTimeSeriesofNestedMultiregionInput–OutputTables

Wangetal.,2015

detailedsectors,balancing,heatmaps,diagnostics,standarddeviationtables,satellitedata,footprintcalculations

Multi-regionalsub-nationalMRIOsforpolicymakinginChina:UsingtheChineseMRIOLab

Wang,2016 detailedsectors,regionalisation,non-surveymethods,heatmaps,satellitedata,footprintcalculations

TheConceptofCityCarbonMaps:ACaseStudyofMelbourne,Australia

Wiedmannetal.,2015a

regionalisation,non-surveymethods,balancing,heatmaps,satellitedata,footprintcalculations

CarbonFootprintScenariosforRenewableElectricityinAustralia

Wolfram,2015;Wolframetal.,2016

detailedsectors,hybridisation,balancing,satellitedata,footprintcalculations

Aquestionnaire(seeSupportingInformation,SI)wassenttothefirstauthorsofallpublicationslistedinTable1.Theresponseratewas100%.Authorswereaskedabouttheirusageoffeaturesthataretypicalfor,andspecificto,theIELab,namely(Lenzenetal.,2014):

Detailedsectors:thepossibilitytoexpandthenumberofsectorsbeyondthatofficiallypublishedbystatisticaloffices(e.g.inAustralia,theIELaballowsdisaggregatingthe111sectorspublishedbytheAustralianBureauofStatistics(ABS,2015)toupto1284sectors,basedonpublisheddetailedinformationontheuseofproducts(ABS,2012).

Hybridisation:theoptiontoinsertnewcolumnsandrowsinMRIOTswithspecificdataderivedfromprocessorcompanyinformation.

Regionalisation:thecapabilitytocreatesub-national,fullypopulatedmulti-regioninputoutputtables(MRIOTs)orsupply-and-usetables(MRSUTs)1forsmall-scaleregions(e.g.withapopulationofabout10,000peopleintheIELab-Aus;2,240regionsintotal).InLenzenetal.,2014tailored,sub-nationalMRIOTswerecalled"MotherTables"thatcouldbefurthermodifiedtoresultin"DaugtherTables".TheIELabcommunityhassincechangedtheseexpressionstothemoreneutralterms"BaseTables"and"BranchTables"(seehttps://ielab.info).

Non-surveymethods:thepossibilitytochoosefromanumberofnon-surveymethodsforregionalisation.Currently,elevennon-surveymethodsareofferedintheIELab,includinglocationquotient,cross-haulingandothermethods(Lenzenetal.,2014,SIp.4).

1 Inthefollowing,theumbrellatermMRIOTisusedwhenreferringtoeithersymmetricMRIOTsorMRSUTs.

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Balancing:theoptiontore-balanceMRIOBaseTableswithconstrainedoptimisationbasedonaRASvariantmethod.

Heatmaps:alsocalledtopographicalmaps,showtheabsolutevaluesofMRIOTelementsincolouredshadesaccordingtoalogarithmicscale(e.g.Lenzenetal.,2012a,Fig.3,p.8377).Heatmapscanbeusedforaquickqualitycheckaftertablebalancing.

Diagnostics:anumberofdiagnostictoolshasbeenimplementedintheIELabbasedonstatisticsorvisualisationsthatwereoriginallydevelopedfortheEoraglobalMRIOdatabase(Lenzenetal.,2013;Lenzenetal.,2012a).ThesediagnosticscanbeusedtoassesstheperformanceofMRIOToptimisationanduncertaintyofMRIOTelements.Fourtoolswereinvestigated:

• SizedistributionsofconstraintsandMRIOTelementscountthenumberofvaluesbylog10section(Lenzenetal.,2013,Fig.12,p.38).

• Optimiserperformancehistogramsshowthefrequencydistributionofconstraintadherencesbeforeandafteroptimisation(Lenzenetal.,2013,Fig.11,p.38).

• Rocketgraphsshowhowwellthefinal,optimisedMRIOTsatisfiedallconstraintssetduringitscreation(e.g.Lenzenetal.,2012a,Fig.4,p.8378orLenzenetal.,2013,Fig.4,p.29).

• Hillsidegraphsplottherelativestandarddeviations(RSD)ofMRIOTelementsagainsttheabsolutevalueoftheelements(Lenzenetal.,2013,Fig.6,p.32).Asinrocketgraphs,smallelementshavearelativelylargeuncertaintyastheyarelesswellconstrainedcomparedtolargertransactions.Inhillsidegraphs,RSDthereforerapidlybecomessmallerforlargeMRIOTvaluesandthegraphtakestheformofahillsideorhockeystick(whichiswhysomeauthorsrefertothegraphas'hockeygraph',e.g.Wangetal.,2015,Fig.3,p.15)

StandarddeviationtablesaccompanyeachsetofresultsinIELab,i.e.foreachcellinanMRIOtablethereisaSDvalue.

Satellitedata:anyadditional,non-IOdatasuchasenvironmental(GHGemissions,energy,water,etc.),socialdata(labour,hoursofsleep,etc.)oreconomicdata(includingthosefromtheValueAddedblockofIOtables,suchaswages/salaries,taxesetc.).

Footprintcalculations:thepossibilityofcalculatingtotal(supply-chain)factorrequirementsforfinaldemand.

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StructuralPathAnalysis(SPA):theidentificationofsignificantindividualpathsshowingtheconnectionbetweentheindustryoriginofapressure/impactandthefinaldemanddestinationwherethispressure/impactbecomesembodiedin.

Finally,surveyparticipantswereaskedwhethertheythinktheirresearchcouldhavehappenedwithoutusinganyoftheIELabfeatureslistedabove.

3. ResultsandDiscussion

Awiderangeofresearchquestionswasaddressedinthestudies,includingdetailedcarbonfootprintanalysesofAustraliancitiesandtheirindustries(Chenetal.,;Chenetal.,submitted-a;Chenetal.,submitted-b;Elyetal.,2015;Wiedmannetal.,2015a)orselectedsectorssuchaselectricity(Wolfram,2015;Wolframetal.,2016)andhealthcare(Malik,2016a);hybridlifecycleassessmentofconstructionmaterials(Rodríguez-Allozaetal.,2015;Tehetal.,2015);sustainabilityassessmentsofbiofuelindustries(Maliketal.,2014;Maliketal.,2015;Maliketal.,2016);environmentalimpactassessmentofhouseholdfoodconsumption(Reynoldsetal.,2015b);refiningwasteinput-outputcalculations(LenzenandReynolds,2014;Reynoldsetal.,2015a)andanalysisofembodiedwasteflows(Fryetal.,2015;Reynoldsetal.,2014);constructingatimeseriesofphysicalinput-outputtables(PIOTs)andanalysingtheflowsofconstructionmaterials(Fryetal.,submitted);strategictransportappraisals(RobsonandDixit,2016);economiccomplexityanalysistoassesscompetitivenessandinnovationatthesub-nationallevel(Reynoldsetal.,inpreparation)andeveninvestigatingtheeconomiccostofagoodnight'ssleep(Reynolds,2015).ThelastthreeapplicationshowthatIELabisnotonlyusedforenvironmentalinput-outputanalysisbutthateconomicandsocialresearchquestionsarealsobeingaddressed.MoststudiesfocussedonapplicationsinAustralia,buttheAustralianIELabconceptwasalsoappliedtoglobalMRIOinitiatives(Lenzenetal.,2016);usedtooptimiseMRIOconstruction(Geschkeetal.,2014)andnon-surveymethods(TöbbenandKronenberg,2015)andtoconstructanduseMRIOtablesforindividualcountries(Faturayetal.,2016;Malik,2016b;Wangetal.,2015;Wang,2016)ortoreplicateMRIOdatasets(AbdRahmanetal.,2016;Reyesetal.,2016).

3.1. UsageofIELabfeatures

ResultsofthesurveyaredepictedinFigure1.Themajorityofthestudies(23,77%)usedthemoredetailedsectorsprovidedbyIELab,i.e.informationthatismoredisaggregatedthanthestandardsetofsectorsininput-outputtablesroutinelypublishedbystatisticaloffices.Thisturnedouttobeaveryuseful,ifnotessentialfeature,whenresearchquestionswereaimedatparticularproductsorprocesses,e.g.constructionmaterials,biofuelsor

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wastetreatment.TheChinesestudiesemphasisedtheusefulnessofhavingtableswith135sectorsforregionalresearchandpolicies.Reynoldsetal.,inpreparationreliedonthefulldisaggregationoftheAustralianeconomyto1284sectorsasthekeyfeatureintheiranalysisofhoweconomiccomplexityinfluencesregionalcompetitivenessandinnovation.

Figure1:UsageofIELabfeaturesinpublishedstudies

Often,detailedsectorswereeitheraugmentedordisaggregatedevenfurtherbyusingnon-IOdatafromlife-cycleinventoriesorspecificengineeringprocesses.Thishybridisationprocedurewasusedin11ofthe30studies(37%),e.g.todistinguish16electricitysectors(fromtheoriginalthree)andninetypesofconcrete(fromtheoriginalone)ortocreatenewsectorsthatrepresenttheproductionofbiofuelsfromsugarcane,algaeorforestrybiomass;theproductionofwarm-mixasphaltmixturesoractivitiesofthehealthcaresector.Malik,2016busedhybridisationtoaugmentAustralia'sinput-outputtablewiththatofNorfolkIsland'stoanalyseenvironmentalimpactsofsmallbusinessesontheisland.

Usingdetailedsectorsseemedtobemoreimportantformostresearchquestionsthanthepossibilityofcreatingandusingsub-nationalregions.Onlyhalfofthestudies(15)madeuseoftheregionalisationfeatureinIELab.Thisisslightlysurprisingsincetheprospectofenablingregionalanalyseswithsub-nationalMRIOTswasoneofthemainreasons–

23 (77%)

11 (37%)

15 (50%)

15 (50%)

23 (77%)

20 (67%)

9 (30%)4 (13%)

27 (90%)

22 (73%)

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20 (67%)

7 (23%)

19 (63%)

15 (50%)

15 (50%)

7 (23%)

10 (33%)

21 (70%)

26 (87%)3 (10%)

8 (27%)

29 (97%)

6 (20%) 4 (13%)

Detailedsectors

Hybridisation

Regionalisation

Non-surveymethods

Balancing

Heatmaps

Diagnostics

Standarddeviationtables

Satellitedata

Footprintcalculations

Structuralpathanalysis

Wouldhavehappenedwithout IELab

USAGE OFIELAB FEATURES INPUBLISHED STUDIES

used notusednomaybeyes

↑usednotused↑

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togetherwithdetailedsectoralanalysis–tocreatethevirtuallaboratoryinthefirstplace(Lenzenetal.,2014).ThestudiesthatmadeextensiveuseoftailoringBaseTableswerethoseexploringthecarbonfootprintofAustraliancities.TheAustralianGovernmentrecentlyannouncedplanstoexpanditscarbonneutralcertificationsystem–whichsofarrecognisescarbonneutralbusinesses,products,servicesandevents–toalsoincludecities,precinctsandbuildings(DepartmentoftheEnvironment,2016).WithAdelaideandMelbournecompetingtobethefirstcarbonneutralcityinAustralia,thereisaneedforaclear,comprehensiveandconsistentevaluationofallthedirectandindirectgreenhousegasemissionsthatareassociatedwiththeactivitiesofcities.Sub-nationalMRIOanalysiswithcitiesnestedinotherregionsofthenationisparticularlysuitedtorespondtothisdemandsinceitallowsfortheunambiguousquantificationofemissionsembodiedinimportsandexportsofcities.

RegionalisationwasalsousedtocreateMRIOTsforIndonesianandChineseprovinces,countiesanddistricts.SimilartoAustralia,thesecountrieshaveverydiverseanddistinctlydifferentregions,theanalysisofwhichrequiresspecificregionaldatainordertoberelevant.TheregionalisationoftransportdemandwasthemostimportantfactorforthestudybyRobsonandDixit,2016.TheseauthorswenttotheextremeofreducingthenumbersofsectorsintheMRIOTdowntotwo,inordertoachievethemaximumnumber(249)ofregionswithapopulationof10,000peopleinthemetropolitanareaofSydney.Allsectorsotherthantransportwereaggregatedintoasinglesector,suchthatthereweretwosectors:transportandallothers.Thiswastoenablefastrunningofthemodelfordemonstrationpurposes.Thestudiesonbiofuelsusedregionalinput-outputtablesfortheanalysisbecausetheseregionsofferidealconditionsforparticularbiofuels,namelyWesternAustraliaforthecultivationandgrowthofalgaeandSouthAustraliaforhardwoodandsoftwoodplantations.

Usingsub-nationalregionalisationrequirestheuseofanon-surveymethodstodisaggregateanddistinguishsub-nationalregionsintheMRSUTframework.IELabofferselevendifferentnon-surveymethods(Lenzenetal.,2014)ofwhichtheAdjustedFlegg'sLocationQuotient(AFLQ)methodwasthemostused(in13of15studiesthatusedregionalisation).Presumably,thisisbecauseAFLQisthedefaultmethodintheIELabuserinterfaceandresearcherswhohavenoparticularpreferencefortheregionalisationmethodarelikelytojustacceptthisdefault;however,thiswasnotfurtherinvestigatedinthisstudy.Faturayetal.,2016usedthesimplelocationquotient(SLQ)methodandTöbbenandKronenberg,2015usedtheIELabforageneralisationandrefinementofthecross-haulingadjustedregionalisationmethod(CHARM)tocompileaMRIOTforGermany'sfederalstates.

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OnceMRIOTshavebeenconstructedwithaspecificnumberofsectorsandregions,theIELab'sreconciliationalgorithmprovidestheoptiontorebalancethetablesbasedonconstrainedoptimisation(Lenzenetal.,2012a;Lenzenetal.,2013;Lenzenetal.,2014).Moststudies(23,77S%)madeuseofthisfeaturewhichisessentialtoachieveconsistencyinthebalanceofmonetaryflows(e.g.forthecalibrationofcomputablegeneralequilibriummodels,asusedbyRobsonandDixit,2016)andallocatedenvironmentalimpactsinfootprintcalculations(e.g.withoutbalancing,totalglobalproduction-basedandconsumption-basedimpactswouldnotbethesame).ThestudiesbyReyesetal.,2016andAbdRahmanetal.,2016aimatreplicatingthemultiple-stepbalancingproceduresusedforEXIOBASEandWIODintheone-stepprocedureprovidedbytheIELab.

Themajorityofstudies(20,67%)usedheatmapstoascertainthegeneralcorrectnessofMRIOTsandsatelliteaccounts;oftenthisvisualaidisalsoshowninpublicationstoillustratethestructureanddimensionsofthedata.Wangetal.,2015,forexample,useaheatmaptoshowhowChineseprovincesareembeddedintheglobalEoraMRIOT,makingitpossibletodiscerntradeofprovinceswitheachotherandwithallcountriesintheworld.Chenetal.,andWang,2016showthestructureofcity-levelSUTsandhowtheylinktootherregions.

Onlyfewstudieshowever(9,30%)madefurtheruseofdiagnosticswhichillustratequantitativeinformationonuncertainty.TheislikelyduetothefactthatdiagnosticimagesonlybecameavailabletoIELabuserslaterin2015.Underlyingthediagnostictoolsarestandarddeviationtables(SDtables)thataccompanyeachsetofresultsinIELab,i.e.foreachcellinaMRIOTastandarddeviationvalueisprovided,indicatingtherangeof68%ofvaluesinanormaldistribution.

Fewstudiesmadeactiveuseofthesetables,butforthosethatdidtheerrordataprovidedvaluableinformation.Reynoldsetal.,inpreparationusedtheSDtablesfortheireconomiccomplexityprojecttotraceuncertaintyinexportdataandinvestigatedifferencesbetweenIELabdataandofficialstatistics.Chenetal.,andWangetal.,2015usedSDdatatoshowtheuncertaintyoftheMRIOTsconstructedintheirstudies.InthecaseofWangetal.,2015thiswasdonebycalculatingtherelativeSDofChineseMRIOdataforeachtableelementforthreetypicalyearsthathavedifferenttypesofconstraints.

UncertaintyinformationprovidedbytheIELabalsoprovedessentialinreplicatingEXIOBASEinthestudybyReyesetal.,2016.Theseauthorsmostlyusedthehockey-stick-shapeddiagramprovidedaspartofthediagnosticsthatplotstherelativeSDofMRIOTelementsagainsttheirabsolutevalue.TheIELabusesthesamecompilationanderrorcalculationroutinesasdevelopedintheglobalMRIOprojectEora(Lenzenetal.,2012a;Lenzenetal.,2013).SDinformationfromthelatterwasessentialtocompleteanerroranalysisforarecentglobalnitrogenfootprintstudypublishedinNatureGeoscience(Oitaetal.,2016),

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althoughthisstudydidnotusetheIELabdirectlyandwasthereforenotincludedinthesurvey.

Satellitedatawereusedbythevastmajorityofstudies(27,90%).Infact,researchquestionsfocussedontheanalysisofsatellitedata.Twenty-twoofthestudies(73%)calculatedfootprintsofsatelliteindicators,i.e.consumption-basedaccountsorsupplychaindata(cradle-to-shelflife-cycleinventoryresults)forenvironmental(GHGemissions,energy,waste),social(employment,sleep)oreconomic(valueaddedcomponents)impacts.IntwocasesthewastedatafromIELabwasusedtocrosscheckownestimatesbytheauthors(Reynoldsetal.,2014;Reynoldsetal.,2015a).

ThemainadvantageseeninusingsatellitedatawasthatIELabautomaticallyprovidesabreakdownbyrootclassification,i.e.satelliteindicatorsareallocatedpro-ratatoindustrysizeforalldetailedsectorsandregions.Suchfine-scaleddataisnotavailableinanyofthecountriesstudiedandturnedouttobeparticularlyusefulforenvironmentalfootprintstudiesofcitiesorregionsandspecifictechnologiesorproducts.AsWolframetal.,2016pointout,insomecasesamanualcorrectionoftheIELabdefaultallocationmightbenecessary,aswasdonefortheelectricitytransmissionsectorinthatstudy.Fryetal.,submittedusedthewastesatelliteaccountsfromIELabintheconstructionofphysicalinput-outputtables(PIOTs).IELabwasnotused,however,tobalancethetables.TheEXIOBASEcomparisonstudyfromReyesetal.,2016willutilisefurthersatellitedatafromtheCREEAprojectsuchasrawmaterialextractionandvolumeofbluewaterused.

FootprintresultscanbebrokendownfurtherbyperformingaStructuralPathAnalysis(SPA)thatidentifiesthemainsupplychainroutesthatconnecttheoriginofmainimpacts(e.g.theindustrywhereGHGemissionsarereleased)andthedestinationoffinaldemandofagoodorservice.SPAasnotgenerallyavailableinIELabwhenthesurveyedstudieswerecarriedoutbuttheSPAcodeispartoftheIELabMatlabscriptrepository.Lenzenetal.,2016haveadoptedandadaptedtheoriginalarchitectureandworkflowcodeoftheAustralianIELabinordertoretainandmakeavailableallIELabfeaturestotheGlobalMRIOLab.

WiththeIELabitisalsopossibletogeneratetimeseriesdatabyprovidingconstraintswithinformationthatdistinguishesaparticularyearfromthebaseyearforwhichtheinitialestimateisbuilt.Thisfeature,whilstimplementedintheIELab,wasnotyetfullyoperationalforAustraliaatthetimeofwritingbecausedatafeedsforyearsotherthanthebaseyear2009werenotfullyfinalisedyet.Someresearchers,however,generatedtimeseriesforothercountriesbycompletingthenecessarydatafeedssuchasFaturayetal.,2016forIndonesiaandWangetal.,2015forChina.

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3.2. IELabasaresearchenabler

TheprevioussectionhighlightedtheuseofspecificIELabfeaturesbutthedecisivequestioniswhethertheresearchcouldactuallyhavehappenedwithouttheIELab.WastheIELabjustaconvenientwayofgettingdataquickerthanotherwiseorwasitatrue'enabler'ofnovelresearchthatwouldnothavebeenpossiblewithoutatleastsomeofthefeaturesspecifictotheIElab?

Mostrespondents(20,67%)answeredthisquestionwith'no'(theresearchwouldnothavebeenpossible).Especiallywhereregionalandsectoraldetailwasimportant,theIELabarchitectureandworkflowsenablednewapplications.Thisistrueforthecarbonfootprintstudiesofcitiesthatreliedfundamentallyontheregionalisationtocreatecity-levelIOtablesnestedinregionalcounterparts(Chenetal.,;Chenetal.,submitted-a;Chenetal.,submitted-b;Elyetal.,2015)andfortheeconomiccomplexitystudybyReynoldsetal.,inpreparationwheretheabilitytoharmonisevariousdatasources,estimatedatatoahighresolution,andaccountfordifferentregionswereimportantpartstofacilitatethatanalysis.Otherregionalisationapproachesexistandcouldhavebeenusedinprinciple(e.g.JacksonandSchwarm,2011;Oosterhavenetal.,1986;JuniusandOosterhaven,2003;Wenzetal.,2014),butimplementingtheseapproachesinpracticewouldhavebeenoutsideofthescopeofworkformoststudies,inparticularwhereresearchersarenotfamiliarwithregionalIOAandwouldhavehadtolearnitasanewfieldofresearchfirst.

Inthetransportstudy(RobsonandDixit,2016)IELabhelpedinprovidingaconsistentmethodanddataformatforcreatingtheIOtablesusedforthecalibrationoftheintegratedspatialcomputablegeneralequilibrium(CGE)andtransportmodelused.WithoutIELab,itwouldhavebeennecessarytomanuallydisaggregatethepublishednationalIOtableusingpublicallyavailableeconomicdata,whichisnotnearlyasdetailedaswhatisavailablethroughtheIELab.However,post-processingofthedatawasstillrequiredtoincorporatetransport-specificdataintheIELab.

TöbbenandKronenberg,2015developedanewregionalisationmethodthatwassubsequentlyusedtoconstructasubnationalMRIOTforGermany.Inhisquestionnairereponse,J.Többenstated"Ingeneral,thecompilationofaMRIOforGermany'sfederalstateswouldhavebeenpossiblewithoutIELab[…],butthecompilationwouldhavebeenmuchmorecostly.ThemainreasonisthatIusedexcessiveamountsofadditionaldata(intotalabout15kdatapoints,surveydataonmanufacturersandhouseholds)withalargenumberofinformationconflictsthatwouldhaverequiredmanualadjustments.Therefore,theuseof[IELab]greatlydecreasedthecostsofcompilation."TheGermanMRIOTwasusedtoquantifytheregionaleconomicimpactsofthe2013floodinGermany(SchulteindenBäumenetal.,2015).

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Foralargernumberofsub-nationalregionsasintheIndonesian(Faturayetal.,2016)orChinese(Wangetal.,2015;Wang,2016)studiesorfortheglobalMRIOTcompilations(AbdRahmanetal.,2016;Reyesetal.,2016)amanualorlessautomatedapproachofregionalandsectoraldisaggregationcomparedtoIELabishardlyimaginable.InordertocreateanMRIOTwiththeWIODregionalandsectoralstructureplussomeofEora'scountriesplussomeofEXIOBASE'ssectors,employingavirtuallabwithaone-stepoptimiserasusedinEoraandaglobalrootstructurefollowingtheIELab'sroot-base-branchconceptcurrentlyseemstheonlyworkablesolution(Lenzenetal.,2016).

Studiesthatinsertednewsectorsand/orhybridisedMRIOTswithadditionaldatasometimesdidsooutsideoftheIELab'scloudenvironment(e.g.Tehetal.,2015andWolframetal.,2016exportedBaseTablesandtailoredthesefurtherinExcel).Allauthorsofhybridisationstudies,however,statedthattheywouldnothavebeenabletoconstructthenecessarysectoraland/orregionaldetailwithouttheconvenientfunctionoftheIELab.Aswasthecasewithregionalisation,theautomatedsectorconfigurationwithinusingIELabenabledWolframetaltofinalisetheircarbonfootprintscenariosofelectricitysupplyaspartofaMaster'sthesiswithinfivemonths'time(Wolfram,2015).

Onethirdofrespondentsansweredwith'yes'(4)or'maybe'(6),i.e.theirstudieswouldhavebeenpossiblewithouttheIELab.Insomecases,IELabsimplyacceleratedresearchbyprovidingdatathatwouldhavebeenotherwisetimeconsuming(butfeasible)tocompile(e.g.inFryetal.,2015andLenzenandReynolds,2014)orIELabprovidedaconvenientplatformtointegrateandtestnewrootanddatafeedstructuresandMRIOTcompilationtechniques(Geschkeetal.,2014;Lenzenetal.,2016).

ThestudiesbyMaliketal.,2014andReynoldsetal.,2014;Reynoldsetal.,2015a;Reynoldsetal.,2015busednationaltablesandsatellitedatafromtheEoradatabaseandonlyusedcertainfunctionsordatafromtheIELabwhichwhereconvenientbutnotnecessarilyessential,suchasbalancing,hybridisation,employment,valueaddedandwastedata.Reynoldsetal.,2014andReynoldsetal.,2015ausedIELabwastetodatacrosscheckownestimations.RespondentReynoldsstated"Thisresearch[Reynolds,2015]couldhaveoccurred[withouttheIELab],butitwouldhavebeenmuchmoreintensedataworktousejusttheEoramodel.TheIELabprovideduswithalevelofconfidenceandcontrollabilityinthisresearch."Finally,Fryetal.,submittedconstructedtheirPIOTtimeseriesoutsideoftheIELab,butusedthewastesatelliteaccountsfromIELabwherethedataisalignedandharmonised–somethingthatisnotthecasewithofficiallypublishedwastedata(atleastnotforAustralia).TheauthorsfoundtheabilitytoaligndatausingconcordancetablesaveryusefulfeatureoftheIELab.

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4. Limitationsofthisstudy

Areviewlikethisisbydefinitionasnapshotintimeanditwasnotpossibletocapturecurrentresearchthatwasnotpublishedatthetimeofwriting.Someauthorshavepublishedmorethanothersonrelatedorsimilartopics;therefore,someresultsmightbebiasedtowardstheusagepatternofthemostprolificauthors.Yet,thetotalof30publicationsshouldprovideasufficientlydiverseoverviewofIELabusagetodrawgeneralconclusions.

SomeoftheIELabfeaturesdescribedinthisreview–suchasfootprintcalculations,hybridisationandSPA–cancurrentlyonlybeperformedbyexpertusers.Theimplementationofthesefunctioninaweb-baseduserinterfacethatcanbeusedbynon-expertswasongoingatthetimeofwriting.ExpertuserseitherusedsupplementarycodeontheresearchcloudortransferredBaseTabledatatoalocalworkspaceandperformedtheanalysisoffline.Theusageofthesespecificfeatureswasthereforelimitedtoexpertswiththeappropriateknowledge.

5. ConclusionsandOutlook

ThirtypublishedstudieswereinvestigatedinthispapertoshedlightonthequestionwhethertheIndustrialEcologyVirtualLaboratoryprovideselementsthatsupportorenableinput-output-relatedresearchinanovelorevenuniqueway.Twothirds(20)ofthestudieswouldnothavebeenpossiblewithouttheIELabandafurthersixwouldhaverequiredconsiderableextraresourcestocomplete.Theuseofdetailedsectorinformationandthebalancingfunctionwerethetwomost-usedfeaturesoftheIELab.Satellitedataandfootprintcalculationswereoftenusedtoaddressthespecificresearchquestionsinthecohortofstudiesthatwasinvestigated.Perhapssurprisingly,onlyhalfofthestudiesmadeuseofregionalisation(andunderlyingnon-surveymethods).Again,thiswasduetotheparticularresearchquestionsaddressed.Onlyafewstudiesmadeuseofuncertaintyinformationanddiagnostictools;someauthorsmighthavebeenunawareofthesefeaturesordidn'tseetheneedtoincludeerrorinformationintheirpublications.WithacalltomakesuchinformationinMRIOanalysismorewidelyavailable(Wiedmannetal.,2011)andsomehigh-profilejournalsrequestingerrorestimatestobepublished,oneshouldexpectahigheruseofuncertaintydatainthefuture.

Somecriticalnotesareinplace.TheIELabiscurrentlystillmoreatoolforexpertsandnotfullydevelopedyetfornon-expertusers.Whilstthisdoesnotdiminishthepotentialusefulnessforthosewhoarewillingandabletolearntheexactworkingsofthise-researchtool,itdoesseverelyrestrictthenumberofpotentialusers.Untiltheuser-friendlyinterface

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isfullydevelopedthatallowsnon-expertuserswithlimitedtrainingtorunanalyses,theuptakeofthetheIELabwillbelimited.Oneexampleforanexistingfunctionoftheinterfaceisthepossibilitytoselectregionsfromageographicalmapratherthanhavingtocreateanduseconcordancematricesthataggregateallpossibleregionsfromtherootclassificationintotheonesusedinananalysis.

AnotherpotentialbarriertoamorewidespreadusetotheIELabisitscollaborativecharacter.Thisidiosyncrasywasintentionalandpartoftheframework'sspecificdesignfromthebeginning(Lenzenetal.,2014)butthelastcoupleofyears'experiencehasshownthatdatafeedsareonlywrittenbyresearchersiftheyareeitherpaidtodosooriftheydirectlyneedtheresultsfortheirownresearchandthereforehaveabenefitfortheirpersonalcareer.Thisisnotsurprisingsincethecompetitivecharacterofresearchinmoderntimesdoesnotleaveanyplaceforaltruisticmotivations,butitalsoprovedaproblemforthefurtherdevelopmentoftheIELab.Insomerarecases,researchersdidnotfullycompletedatafeedsthatwereinitiallyassignedtothembecausetheyeitherunderestimatedtheeffortandsimplyranoutoffundingortheymovedontootherfieldsofresearchorrolesintheirlives.Luckily,thesecasesaretheexceptionandcontinuedfundingenablesthecompletionandfurtherdevelopmentofdatafeeds.ButthisshowsthattheunconventionalsetupoftheIELabisasdependentonongoinginterestofresearchersandfundersasanyotherconventionallymanagedproject.Inthatrespect,theIELabisasmuchasocialasatechnicalexperiment.

ThereisanenormouspotentialforIELabtoenableanevenwidercollaborationofdiversedisciplines,toexploremorecomplexsustainabilityissuesandtoprovideimprovedoutcomesforresearch,industryandgovernments.Butthiswillnotbepossiblewithoutongoingsupportanddevelopment.NewprojectideasandapplicationsareincreasinglybeingformulatedbytheIELabcommunity,requiringmoresophisticatedanalyticalcapabilitiesandtools.AnewprojectfundedbytheAustralianResearchCouncil(ARC)2startedinMay2016toincreasetheprocessingcapabilityoftheIELabneededforlarge-scalemodellingandoptimisationanalysis(asparttheGlobalIELabdevelopment,AbdRahmanetal.,2016;Lenzenetal.,2016;Reyesetal.,2016)aswellastoexpanditsfunctionalcapability.Indetail,thiswill(i)boostthenumberofcountriesandhenceimprovetheresolutionoftradeanalyses,(ii)enhancetheanalyticaltoolboxforbetterproductandprocess-levelresolutionandimprovedsustainabilitybenchmarking,and(iii)integrateaneconometricmodulethatwillallowscenario-basedsimulationsofdemographicchangesandinvestmentoptions.IELabdevelopershopethatthesemajornewelementswillbenefit

2 ARCLinkageInfrastructure,EquipmentandFacilities(LIEF)grantLE160100066,titled"EnhancedmodellingcapacityfortheIndustrialEcologyVirtualLaboratory".

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researchandapplicationsintheareasofindustrialecology,regionaleconomics,transitionanalysis,triple-bottom-lineandsustainabilityassessments.

6. Acknowledgements

Abigthankyoutoallrespondentsofstudiesinvestigatedinthispaper.ThiscontributionwassupportedbytheAustralianResearchCouncil,grantnumberLE160100066,whichfundscomputinghardwareandfurthersoftwareenhancementsoftheIELab.TheIELabwasinitiallycreatedwithfundingfromAustralianGovernmentthroughitsNationaleResearchCollaborationToolsandResourcesprogram(NeCTAR).

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Wenz,L.,Willner,S.N.,Radebach,A.,Bierkandt,R.,Steckel,J.C.andLevermann,A.(2014)Regionalandsectoraldisaggregationofmulti-regionalinput-outputtables-Aflexiblealgorithm.EconomicSystemsResearch,27(2),194-212.http://dx.doi.org/10.1080/09535314.2014.987731

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22

SupportingInformationfor

AnInput-OutputVirtualLaboratoryinpractice–Surveyoftheuptake,usageandapplicationofthefirstoperationalIELab

ThomasWiedmann1,2

1. SustainabilityAssessmentProgram(SAP),WaterResearchCentre,SchoolofCivilandEnvironmental

Engineering,UNSWAustralia,Sydney,NSW2052,Australia

2. ISA,SchoolofPhysicsA28,TheUniversityofSydney,NSW2006,Australia

QuestionnaireontheusageofIELab

SentoutinMarch2016

Pleasefillinthefieldshighlightedinblue;themoredetailyoucanprovidethebetter."UsageofIELab"referstousingANYfeatureoftheIELabinthewidestsense.

DetailsoftheresearchinwhichyouhaveusedtheIELab(topic,year,teametc.).Insertcitationifpublicationexist.

Whatwasthemainresearchquestionyouaddressedinthisresearch(onesentence)?

WhichofthefollowingfeaturesoftheIELabdidyouuseinourresearchandwhy?

Detailedsectors(i.e.anysectorsBEYONDthestandardnumberofsectorspublishedbystatisticaloffices;e.g.111sectorsinAustraliapublishedbytheABS)

yes/no

Whichtypeofsectorswereofparticularinterest(particularlyusefulintheresearch)?

Anyothercomments(e.g.didyouaggregatesectors)?

Regionalisation,i.e.theabilitytocreatesub-national,fullypopulatedMRIOTs(e.g.inAustraliafor2,240regionswithapopulationofabout10,000)

yes/no

23

Whichtypeofregionswereofparticularinterest(particularlyusefulintheresearch)?

Anyothercomments?

Non-surveymethods,i.e.thepossibilitytochoosefromanumberofnon-surveymethodsforregionalisation(currentlyaboutonedozen)

yes/no

Wasanyofthemethodsofparticularinterest(particularlyusefulintheresearch)?

Anyothercomments?

Balancing,i.e.theoptiontobalanceMRIOBaseTables

yes/no

Anyothercomments?

Satellitedata,i.e.anyadditional,non-IOdatasuchasenvironmental(GHGemissions,energy,water,etc.)orsocialdata(labour,hoursofsleep,etc.)oreconomicdata(includingthosefromtheValueAddedblockofIOtables,suchaswages/salaries,taxesetc.)

yes/no

Whichdataexactlydidyouuse?

Anyothercomments?

Hybridisation,i.e.theoptiontoinsertnewcolumnsandrowsintheMRIOTs(incl.MRSUTs)withspecificdataderivedfromprocessorcompanyinformation

yes/no

Pleasedescribebrieflywhatexactlyyoudidandwhatdatayouused

Anyothercomments?

Footprintcalculations,i.e.thepossibilityofcalculatingtotal(supply-chain)factorrequirementsforfinaldemand

yes/no

24

Pleasedescribebrieflywhatexactlyyoudidandforwhichdatayoucalculatedfootprints

Anyothercomments?

StructuralPathAnalysis(SPA),i.e.theidentificationofsignificantindividualpathsshowingtheconnectionbetweentheindustryoriginofapressure/impactandthefinaldemanddestinationwherethispressure/impactbecomesembodiedin.

yes/no

Pleasedescribebrieflywhatexactlyyoudidandforwhichdatayoucalculatedpaths

Anyothercomments?

Heatmaps,diagnostictoolsandstandarddeviationtables.

Pleasedescribebrieflywhatyouused.

Anyotherfeature?

PleasedescribeanyotherfunctionorfeatureoftheIELabthatyoumighthaveusedbutisnotmentionedabove.

Pleaseanswerthefollowingquestioninanycase:

CouldthisparticularresearchhavehappenedwithoutusinganyoftheIELabfeatures(pleaseexplainwhynotif'no'andwhyandhowif'yes')?

Thankyouverymuchforyourhelp!