Report on iSCAPE socio-economic impact assessment methodology · 2018-03-13 · Report on iSCAPE socio-economic impact assessment methodology ––––––––– D5.6 08/2017

Report on iSCAPE socio-economic impactassessmentmethodology–––––––––D5.608/2017

Thisprojecthas received funding fromtheEuropeanUnion’sHorizon2020researchand innovationprogrammeundergrantagreementNo689954.

Ref. Ares(2017)4526415 - 16/09/2017

D5.6 Report on socio-economic impact assessment methodology

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Project Acronym andName

iSCAPE-ImprovingtheSmartControlofAirPollutioninEurope

Grant AgreementNumber

689954

DocumentType report

Documentversion&WPNo.

V.10 WP5

DocumentTitle ReportoniSCAPEsocio-economicimpactassessmentmethodology

Mainauthors Väinö Nurmi, Athanasios Votsis, Alessandra Prampolini, AntonellaPassaniandNadineMägdefrau

Partnerincharge T6ECO

Contributingpartners FMI,TUDO

Releasedate 08/09/2017

Thepublicationreflectstheauthor’sviews.TheEuropeanCommissionisnotliableforanyusethatmaybemadeoftheinformationcontainedtherein.

DocumentControlPage

ShortDescription Thisdeliverablepresentsthemethodologyfortheassessmentofthesocio-economicimpactsoftheiSCAPEproject.Themethodologyhasidentifiesaselectionofquali-quantitativeapproachesabletomap,describeand-toacertain extent - quantify the impact generated by the project. It buildsonliterature review of studies and researches and from a consultationprocesswiththepartnersmanagingtheinterventionsinthecitiesandtheLivingLabs.Themethodologicalframeworkisdesignedasmodularinordertoadapttothespecificitiesofeachoftheprojectpilot.

Reviewstatus Action Person Date

QualityCheck CoordinationTeam 15.09.2017

InternalReview Muhammad Adnan (UH),StefanGreiving(TUDO)

5/09/2017

Distribution Public


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Revisionhistory

Version Date Modifiedby Comments

V0.1 22/02/2017 AntonellaPassani ToC

V0.2 25/04/2017 Väinö Nurmi,AthanasiosVotsis

Firstdraftofeconomicimpactsections

V0.3 12/05/2017 AthanasiosVotsis Additionstotheeconomicsections(3.3,5.2)

V0.4 15/06/2017 AlessandraPrampolini

Chapter1,2,4

V05 27/06/2017 VäinöNurmi Additionstochapters3and5.4

V0615/07/2017

AlessandraPrampolini,AntonellaPassani

Paragraphs5.3,5.4

V07 30/07 All Integrationsandandrevisionstoseveralsections

V0915/08/2017 AntonellaPassani

5.1 and integrations to 5.3, 5.4, executivesummaryandintroduction.

V10 25/08/2017 all Finaldraftforinternalreview

Statement of originality: This deliverable contains original unpublished work except where clearly indicated otherwise. Acknowledgement of previously published material and of the work of others has been made through appropriate citation, quotation or both.


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TableofContentsTableofContents1 ExecutiveSummary......................................................................................................-6- 2 Introduction.................................................................................................................-7- 2.1 Whyasocio-economicimpactassessmentmethodologyforiSCAPE......................-9- 2.2 Structureofthedocument...................................................................................-10-

3 Literature review on socio-economic impacts of passive control system interventions,behaviouralchangeinterventionsandpolicyinterventions...............................................-12- 3.1 Socio-economicimpactofpassivecontrolsystems..............................................-13- 3.1.1 Greeninterventionsandthesocioeconomicbenefitsofecosystemservices...-13- 3.1.2 Greyinterventionsandthesocio-economicbenefits........................................-19-

3.2 Socio-economicimpactofbehaviouralinterventions...........................................-20- 3.3 Socio-economicimpactofpolicyintervention......................................................-22-

4 Literaturereviewonsocio-economicimpactsmethodologytestedininitiativessimilartoiSCAPE...............................................................................................................................-25- 5 iSCAPEsocio-economicimpactassessmentmethodology...........................................-30- 5.1 Theoverallframework........................................................................................-30- 5.2 Economicimpactassessment..............................................................................-32- 5.3 SocialImpactassessment........................................................................................43 5.4 Datagatheringanddataanalysisprocess................................................................57

6 Conclusions....................................................................................................................62 7 References/Bibliography..............................................................................................62


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ListofTablesTABLE 1: ISCAPE PLANNED INTERVENTIONS IN EACH CITY ........................................................................... - 12 - TABLE 2 –RESPONSE-FUNCTIONS FOR LONG-TERM PM2.5 .......................................................................... - 34 - TABLE 3 - RESPONSE-FUNCTIONS FOR SHORT-TERM PM2.5 ......................................................................... - 35 - TABLE 4 –LITERATURE REVIEW FOR THE ECONOMIC IMPACT ASSESSMENT (UNIT-COSTS AND META-ANALYSIS) ..... 41 TABLE 5- DIMENSIONS OF QUALITY OF LIFE: A COMPARISON BETWEEN ISTAT, EUROSTAT AND EOCD APPROACHES

............................................................................................................................................................. 46 TABLE 6 - SUB-DIMENSION RELATED TO PRODUCTIVE OR OTHER MAIN ACTIVITY ................................................. 47 TABLE 7 - ISCAPE AREAS OF IMPACT COMING FROM EUROSTAT APPROACH TO QUALITY OF LIFE ....................... 48 TABLE 8 – “SOCIAL” AREAS OF IMPACTS AND RELEVANCE FOR EACH OF THE ISCAPE PILOT ACTIONS. ................. 50 TABLE 9 –SOCIAL DIMENSIONS OF IMPACT – PRODUCT OR MAIL ACTIVITY .......................................................... 51 TABLE 10 –SOCIAL DIMENSIONS OF IMPACT – MATERIAL AND LIVING CONDITIONS .............................................. 51 TABLE 11 –SOCIAL DIMENSIONS OF IMPACT - EDUCATION ................................................................................. 52 TABLE 12 –SOCIAL DIMENSIONS OF IMPACT – LEISURE AND SOCIAL INTERACTION .............................................. 53 TABLE 13 –SOCIAL DIMENSIONS OF IMPACT – NATURAL AND LIVING ENVIRONMENT ............................................ 54 TABLE 14 –SOCIAL DIMENSIONS OF IMPACT – BEHAVIOURS .............................................................................. 55 TABLE 15 –SOCIAL DIMENSIONS OF IMPACT – POLICIES ................................................................................... 55 TABLE 16 –SOCIAL DIMENSIONS OF IMPACT – SCIENTIFIC IMPACT ..................................................................... 56 TABLE 17 –SOCIAL DIMENSIONS OF IMPACT EQUALITY ..................................................................................... 57 TABLE 18 –ECONOMIC IMPACTS AND REQUESTED DATA PER CITY AND INTERVENTION ........................................ 58 TABLE 19 –SOCIAL DIMENSIONS OF IMPACT – DATA SOURCE ............................................................................ 60

LISTOFFIGURESFIGURE 1 - DEVELOPMENT OF THE IMPACT ASSESSMENT METHODOLOGY ........................................................ - 8 - FIGURE 2 – PURPOSES AND METHODOLOGIES OF IMPACT ASSESSMENT (EVALSED: THE RESOURCE FOR THE

EVALUATION OF SOCIO-ECONOMIC DEVELOPMENT. REGIONAL POLICY - INFOREGIO) .............................. - 10 - FIGURE 3 - TYPOLOGY OF COSTS OF AIR POLLUTION (OECD, 2016) ............................................................ - 32 - FIGURE 4 – IMPACT PATHWAYS LOGICAL CHAIN ........................................................................................... - 33 - FIGURE 5 –REDUCED FORM OF IMPACT PATHWAYS ANALYSIS ....................................................................... - 37 - FIGURE 6 SOCIAL IMPACTS: AREAS OF IMPACT AND RELATED SUB-DIMENSIONS .................................................. 49


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ListofabbreviationsAcronym/Term DefinitionDoA iSCAPEDescriptionofActionPM ParticulateMatterVOCs VolatileOrganicCompoundCO2 CarbonDioxideSO2 SulphurDioxideVSL ValueofLifeGDP GrossDomesticProductES EcosystemServicesCTM ChemicalTransportModelVSLY ValueofstatisticallifeperyearPCS PassiveControlSystemPCE PerceivedCitizens’EffectivenessWTP WillingnesstoPay


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1 ExecutiveSummaryThisdeliverablepresentsthemethodologyfortheassessmentofthesocio-economicimpactsofthe iSCAPE project, which aims to develop an integrated strategy for air pollution control inEuropean cities, grounded on evidence-based analysis. The project will pursue its goal byleveraging passive control systems, behavioural change and developing policyrecommendations. Moreover, it will make these solutions accessible to local communitiesthroughtheLivingLabapproach,involvingaselectionofstakeholdersfromthecivilsocietyandfrom the institutions in awareness and dissemination activities. The expected result is theincreased visibility of the air pollution challenge and the valorisation of solution available atinfrastructuralandbehaviourallevel.Thefocusoftheassessmentisthereforeontheonehandthe impact (or the potential impact) of the intervention studied and implemented by theproject,andontheotherhandtheimpactoftheLivingLabactivitiesandoftheinvolvementofcommunitiesandinstitutions.Themethodologyhasbeendevelopedduringthefirstyearoftheprojectandithasidentifiedaselectionofquali-quantitativeapproachesabletomap,describeandquantify(whenuseful)theimpactgeneratedby theproject.Themethodological frameworkdescribed in thisdeliverableincludes the followingwell-knowand tested approaches: Impact PathwayApproach,HedonicpricingApproach,Lifesatisfactionapproach,Unit-costmodellingandmeta-analysisandQualityofLifeapproach.Theselectionof thesemethodscame fromaprocessof literature reviewofstudiesandresearchesthatdealtwiththesametopicalready,andfromaconsultationprocesswiththepartnersmanagingtheinterventionsinthecitiesandtheLivingLabs.Not all these methods/approaches will be used for analysing all the project outputs, andespeciallyallthepilotactions–whichconstitutethemainfocusoftheimpactassessment.Themethodologicalframework,infact,isdesignedasmodularinordertoadapttothespecificitiesofeachoftheprojectpilotandbestdescribeitssocio-economicbenefits.Thisdocumentmustbeconsideredaworkinprogress:beforetheprojectassessment,thatwilltakeplaceduringthelastyear,itcouldbeupdatedaccordingtotheprogressandadjustmentoftheprojectactivities.


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2 IntroductionThesocio-economicassessmentmethodologydescribed in thisdocument ispartof thewidergoalofdevelopinganapproachtoevaluatetheimpactoftheiSCAPEoutputsandpilots,whichincludealso theanalysisof theenvironmental impacts,developedwithinother tasks (5.1and5.2).Themethodologywillmapandquantify,asmuchaspossible,economicandsocialimpactoftheiSCAPEprojectfocusingmainly–butnotexclusively–ontheresultsofthesixforeseenpilotssetuptoinvolveandempowerlocalstakeholdersandthegeneralpublic.Herebelowthelistofthepilotswithasyntheticdescription1:

o Bologna(Italy):Bolognaisdevelopingtwopilots.Thefirstonewilldealwiththeroleoftrees as a Passive Control System to improve the air quality inside the urbanenvironment, relying on two field in situ measuring campaign during winter andsummer. Resultswill be sharedwith local authorities to introduce new interventions,and citizenswill be involved and informed about the experiments. In the Lazaretto (aBologna’sneighbourhood),asecondinterventionwillallowtoassesstheimpactsoftheuse of photocatalytic coatings on a campus building. The test will be conductedestimatingpollutantsconcentrationspreandpostapplicationofcoats.Eachphaseoftheprojectwillbesharedwithstudentsandcampusemployees.

o Bottrop (Germany): in Bottrop, the potted “Wandering Trees” pilot will make treestravelingaroundthecity, temporarilygreening inner-citystreetsandallowingtostudytheimpactsonairqualityandonthelocalcommunity.Theimplementationofthelivinglabwillbringabroadinvolvementoflocalstakeholdersandofthegeneralpublic.

o Dublin(Ireland):byconductingalong-termstudy,Dublinlivinglabwillprovideevidenceontheeffectivenessoflowboundarywalls(LBW).ThedeploymentofasensornetworkwillallowtoassessimpactofanalreadyexistingLBW.Moreover,citystakeholdersandcitizenswillassistinaestheticandfunctionaldesignofanewLBWtroughparticipatoryeventsandplayfulapproaches,forexample,usinglargeLego-likebricks.

o Guildford (United Kingdom): iSCAPE results in Guildford are envisioned as a portable,insightful, and user-interactive platform for raising citizens’ awareness about airpollution issues in their neighbourhood and the use of green infrastructuralinterventions(suchassuchastreesandhedges)tocombatpollutionexposure,therebyimprovingcommunity’shealthandwell-being.

o Hasselt (Belgium): the intervention will trigger and analyse behavioural changes byproviding a dedicated app to a population sample for observing their travel patterns.Interventionwillbeintheformofcustomisedinformationtoparticipantsinrelationtotheir exposure to pollutants, contribution in CO2 emissions and physical activity level,aimingtoinfluencemoresustainablelifestyles.

o Vantaa (Finland): the pilotwill focus on the influence of green roofs and parks on airquality and humanwell being and itwill establish a platform for stakeholder like cityauthoritiesandinhabitantstocombinetheircommoneffortforbettercityplanning.

1FormoredetaileddescriptionsofthepilotspleaserefertoD2.2


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To develop the methodology for the impact assessment of the pilots and the participatoryactivitiesforeseeninthesixcities,thisdeliverablebuiltonthreesources,asillustratedinfigure1:firstanin-depthliteraturereviewdedicatedtotheiSCAPEinterventionsandtheirexpectedimpacts;thenareviewofalreadyexistingmethodologiesdealingwiththesameobjectivesandof their possible adaptation to the iSCAPE scenarios. The third source is represented by theiSCAPEpartnersandtheirfeedback.The first two steps generated a draft framework of the socio-economic impact assessmentmethodology, including a selection of relevant areas of impact, variables and indicators andmethodsofevaluation.Theframeworkwassummarisedinapresentationanddiscussedduringindividual webinars with each project partner engaged in the pilots. This consultation phaseallowedvalidatingandverifyingtheconsistencyofthemethodologywiththeplannedactivities,refining and finalising the approach.Moreover, the discussionwith the partners provided anoverview of the typology of data available for each city, further narrowing the focus of theanalysis.

Figure1-Developmentoftheimpactassessmentmethodology

This process allows awide exploitationof the already available research in the same field ofinvestigation, guaranteeing at the same time the development of a tailor made frameworkalreadyalignedwithpartners’plansandexpectations.Thefollowingparagraphswillexplainthevalueandtheobjectivesofanimpactassessmentandwillprovideanoverviewofthisdocument.


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2.1 Why a socio-economic impact assessment methodologyforiSCAPE

The iSCAPE project aims to have a concrete impact on research, intervention and policiesdealingwithurbanairpollution.Moreover, throughtheLivingLabapproach, it isexpectedtoreachthewiderpublicandtoraiseawarenessamongthecitizens,providingthemknowledgeand tools toproactively contribute to the solutions.Fromthisperspective, theassessmentofthesocio-economicimpactsoftheproject isakeytooltoidentifyandvalueitsresultsanditscontributionintermsofadvancementsofacademicstudiesconcerningtheairqualityissueanditssolutions.Theassessmentallowsalsotheidentificationofrealorexpectedimpactsatsocialand economic level of the urban intervention under investigation and of the activitiesdevelopedforcitizensandotherstakeholders.TheguidetoimpactassessmentdevelopedbytheECINFOREGIOUnit(EuropeanCommission,2012b:119)definesimpactas,

“aconsequenceaffectingdirectbeneficiariesfollowingtheendoftheirparticipation inan intervention or after the completion of public facilities, or else an indirectconsequenceaffectingotherbeneficiarieswhomaybewinnersorlosers.Certainimpacts(specific impacts) canbeobserved amongdirect beneficiaries after a fewmonths andothers only in the longer term (e.g. the monitoring of assisted firms). In the field ofdevelopmentsupport, these longer-termimpactsareusuallyreferredtoassustainableresults. Some impacts appear indirectly (e.g. turnover generated for the suppliers ofassisted firms). Others can be observed at the macro-economic or macro-social level(e.g. improvement of the image of the assisted region); these are global impacts.Evaluation is frequently used to examineoneormore intermediate impacts, betweenspecific and global impacts. Impacts may be positive or negative, expected orunexpected”.

Running an impact assessment means answering the question “what is the difference theproject makes?”. For the iSCAPE project, more specifically the environmental impact will beevaluated in task 5.2 while the socio-economic impact will be covered by task 5.3. Themethodologyheredescribedrefersonlytothelatter.Itisimportanttohighlightthatanimpactassessmentcanhavedifferentscopeandtheresultscouldbeusefulfordifferentaudiences.Thefigurethatfollowsmapsthemaingoalofanimpactassessmentandtherelatedmethodologicalapproaches.


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Figure2–Purposesandmethodologiesofimpactassessment(Evalsed:theresourcefortheevaluationofsocio-economic

development.RegionalPolicy-Inforegio)

InthecaseoftheiSCAPEproject,theassessmentwillmeettwogoals:ononeside,itwillbeauseful internal management tool, facilitating the coordination, aligning the expectationsprovidingvaluablelessonstothepartners.Ontheotherside,itwillprovidesocialandeconomicresults topolicymakersandstakeholders inaconcreteandcomprehendible form,supportingfutureactionsandpolicies accordingly.As a final remark, it is important tomention, impactstend to be observable after the end of a project. For this reason, the impact assessmentactivities that will take place during the iSCAPE project life time will be only able to assessexpectedormodelledimpacts

2.2 StructureofthedocumentThis deliverable reports the results of the extensive literature review concerning theinterventions involved in the project and the studies already developed to address similarprojects. Based on this research, it illustrates the framework and the methods for theassessment the economic and the social impacts of all studies, interventions and activitiesundertakenduringtheproject.Thedocumentisarticulatedasfollows:

• Chapter 3 presents the literature review of the socio-economic impacts of the threesolutions to the air pollution issue explored by iSCAPE: passive control systems,behaviouralchangesandpolicyinterventions,withtheaimtoprovideacomprehensiveknowledgeoftheinterventions,theirapplicationandtheirexpectedeffects;


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• Chapter 4 presents an overview of socio-economic impact assessment developed forinitiativesandprojectssimilartoiSCAPE,tounderstandthedepthandtheapproachofprevious investigations in the field therefore underlying the original contributionprovidedbytheiSCAPEproject;

• Chapter 5 illustrates in detail the assessment framework, identifying dimensions,indicators andmethods of analysis for the economic and the social impacts, togetherwith the data gathering and the data analysis process thatwill be developed as nextsteps.


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3 Literature review on socio-economic impacts ofpassive control system interventions, behaviouralchangeinterventionsandpolicyinterventions.

ThischapterdescribesandanalysestheairqualitycontrolinterventionsiniSCAPE,thatcanberoughly categorized in three categories: 1) passive control systems, including both green andgreysolutions,2)interventionsthataimtochangethebehaviourofcitizensand3)directpolicyinterventions.Themaingoaloftheinterventionsistoreducetheeffectsrelatedtoairpollutants,butmanyoftheinterventionsalsobringotherbenefitstothecitizens.Inthissection,aliteraturereviewofthe socioeconomic impacts of interventions is presented. The interventions in iSCAPE,illustratedintheIntroduction,aresummarisedintable3.1.

City Intervention Green / Grey /Behavioural/Policy

Bologna Street canyon with /withouttrees

GreenPolicy

Vantaa Greenroofs GreenPolicy

Hasselt Behavioural change –warningsystems

Behavioural

Dublin Lowboundarywalls Grey

Guildford / Vantaa(MetropolitanareaofHelsinki)

Greeninfrastructure Green

Bottrop Walkingtrees GreenPolicy

Lazaretto Photocatalyticpainting Grey

Table1:iSCAPEplannedinterventionsineachcity


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3.1 Socio-economicimpactofpassivecontrolsystems.Passivecontrolsystemsareusuallymentionedintheliteratureaswaystoreducethenegativeeffects of air pollution in cities (e.g. Gallagher et al., 2012;McNabola, 2010). The aimof thepassivecontrolsystems is tomanipulatethepollutantdispersionpatterns incities inordertoreduceexposuretoairpollutants.Itcanhappene.g.withlowboundarywalls,treesoron-streetparking which block part of the dispersion from roads to pedestrian lanes. Reduction ofconcentrationsofPM2.52andharmfulVolatileOrganicCompounds(VOCs)havebeenreportedin the literature (e.g.McNabola2010).Next to thedispersion, researchhas shown that treesand other types of green interventions induce deposition of air pollutants and reduce airpollutantconcentrationlevels(e.g.Yangetal.2008).The impactassessmentof iSCAPEaims to study the social andeconomicbenefitsof reducingexposure and air pollutant concentration levels. The main impacts are naturally related tohealthbenefits,ofwhichreductionofmortalityduetoairpollutantsrepresentaround90%ofthebenefits(e.g.Heoetal.2016).However,manyoftheinterventionsbringalsoothertypesofbenefitsaswellascosts.Greeninfrastructurecanforexamplehelptomitigatetheheat-island-effect in the cities, reduce storm-water runoff to the sewage system, reducenoise pollution,bringaestheticbenefits,changethecitizensapproachandbehaviour towardstheuseof localspaces. However, opportunity costs include reduction in parking or building space andmaintenance costs. In this section, literature review of the expected benefits and costs isconducted.Basedonthis,theappropriatemethodologytostudythebenefitsandcostsofeachinterventioncanbechosen.

3.1.1 GreeninterventionsandthesocioeconomicbenefitsofecosystemservicesCitiesandurbansystemsaredependentonecosystemsexistingbothbeyondandwithinthecitylimits. Bolund and Hunhammar (1999) identified seven types of different urban ecosystems:street trees, lawns/parks, urban forests, cultivated land, wetlands, lakes/sea and streams.Alternativeclassificationsareavailablebutusuallyalmost identical.Theseecosystemsprovidebenefits to the citizens – benefits can be classified by different services provided by theecosystems.Theseservicesarecalledecosystemservices (ES).As thecompetitionof space inurbanareasisincreasing,newsolutionshaveemergedandgreenroofsandgreenwallsshouldbeaddedtothelist.Withinurbanareas,theprimaryissuefromtheperspectiveofhumanwell-beingiswhethertheurbansettlementscanprovideahealthyandsatisfyinglivingenvironmentfor residents. Living ecosystems are recognized as a key to wellbeing as ES are increasinglyacknowledgedtoincreasethequalityoflifeforurbanitese.g.byimprovingairquality,reducingnoise andproviding recreational services (e.g.Niemelä et al.,2010).At least, the followingEScanbeattributedtourbangreen:storm-watermanagement,controlofairpollution,controlofnoise pollution, aesthetics, psychological benefits, heat-island effect reduction and resulting

2ParticulateMatters2.5:foramoreextensiveexplanationpleaseseeChapter4.


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reduction in cooling energy demand, urban habitat, waste treatment, pollination, pestregulation, recreation, social cohesion, agriculture and timber. (e.g. Gomez-Baggethun et al.,2013).Foragivenecosystem,theeconomicvalueofeachEScanusuallybeestimated.Another approach for the value of a given ecosystem service is to study the total value thatpeopleattachtoalltheESprovided.Inthiscase,thebenefitsarenotcategorizedbasedonESbutratherthevalueoftotalpackageisbeinganalysed.Thisapproachisusuallythebasisforthehedonicpricingmethod, inwhichtheprices intherealestatemarketscanbeusedtoanalysethewillingness to pay in a proximity of a given ecosystem; or contingent valuation, inwhichpeopleareaskedtostatetheirwillingnesstopayforagivenecosystem.Next, we take a more elaborate look at the socio-economic benefits of the interventions iniSCAPE:trees,greenroofs,andgreeninfrastructureingeneral.GreenroofsGreenroofsareroofsthatarepartiallyor(almost)completelycoveredbyvegetationasaresultof planned action rather than neglect. Green roofs are an increasing feature of cities’ urbanplanningtoolset.Thesocioeconomicbenefitsandcostshavebeenstudiedinseveralcitiesandcountries,e.g.NewYork(Rosenzweigetal.2006,Bianchini&Hewage,2012)andBelgium(ClausandRousseau,2012).GreenroofsprovideatleastthefollowingES:

• Membrane longevity: The historic experience built up with green roofs points atapproximatelydoublingthelifespanoftheroofingmembrane.Thisamountstoanadditional20 years lifetime compared to a conventional roof. (e.g. Porche and Köhler, 2003). Thisbenefit is dependent on the saved (future) cost of the conventional roof repair 20 yearsfromnow.Inmonetaryterms,thisprotectionoftheroofESisthelargestbenefitofagreenroof,estimatedsavinginHelsinkiwasaround25€/!".(Nurmietal.2016)

• Energycostsavings:Thegreenroofscanpotentiallyreducebothcoolingandheatingenergyuse.However,dependingontheclimate,thegreenroofscanbeoptimizedinawaythatitmainlyreducescoolingenergyinhotclimatesandheatingenergyincoldclimates(Roche&Berardi,2014).Theheatingenergy reduction isa resultof the insulativepropertiesof thevegetation.Thiseffectishighlydependentonthebuildingenvelopecharacteristicsonwhichthegreenroofsareplaced.Generally,innon-insulatedbuildings,theimpactofgreenroofsismuch higher than in insulated ones: the better the insulation of the roof, the lower thecontributionofgreenroofs.Incold,heatingdominatedclimates,theinsulationpropertiesoftheroofcarrythehighestsignificanceastheheatingloadbenefitsfromalowUvalue(Uisthecoefficientofthermaltransmittance).InHelsinki,Nurmietal.(2016)showedthatthereisaround3€/!"forevery0.01decreaseinthermaltransmittancecoefficient.IncontrastinMadrid, the benefit is only around 0.25€/!" for every 0.01 decrease in thermaltransmittance coefficient. As this benefit approaches 0 in warm climates, the green roofshouldbeoptimizedtoreducecoolingenergyinthesummertime.RocheandBerardi(2014)compareddifferenttypesofgreenroofsinthreedifferentclimateconditionsforaone-storyoffice building, and recorded annual cooling load reductions between 17% and 22% foroptimal green roof designs in different climates. Saiz et al. (2006) showed similar kind ofresultsforagreenroofinMadrid.Additionally,itwasshownthatgreenroofscooldownthefivehighestfloors,butthecoolingeffectisclosetozerofrom6thhighestfloordownwards.


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Nurmietal.(2016)showedthatthisbenefitcanbe24€-30€/!"inaclimatecomparabletoMadrid. In Helsinki, Finland, the benefit was only 2€ for a residential building and atmaximumaround10€/!"foranofficebuilding.

• Noiseinsulation:Lightweightvegetatedroofsmayincreasetransmissionlossupto10dBatlowfrequencyandupto20dBatmid-rangefrequencies(Connelly&Hodgson,2013).Largeamountsofgreenroofsindowntownareasmayalsoaffectthesoundscapeoftheinnercity,generally in the sense of attenuatingmechanical noises (Irvine et al., 2009; Renterghem,Hornikx,Forssen&Botteldooren,2013).Noise insulation for the roof isneededespeciallybelow flight routes, and green roof can act as a substitute for an additional roof layer.Economic benefits are comparable tomembrane longevity benefit – around 20€/!", butonlyapplybelowflightroutes

• Storm-watermanagement:Greenroofscanreducethedemandonsewersystemcapacityby delayingwater flows and by reducing total runoff by retaining part of the rainfall andreleasing it back to the atmosphere. Results from Berlin suggest that a lightweight low-growthgreenroofon10%ofbuildingstockwouldresultinareductionof2.7%inrunofffortheregionand54%foreachbuilding(Mentensetal.2006).Rosenzweigetal.(2006)showedthatasimilargreenroof infrastructure inNewYorkcouldproducea2%reduction intotalrunoff. Theextent of economicbenefits is affectedby complicated relationships betweenrainfallpatterns(e.g.returnperiodsofextremerainfallevents)andcityspecificstorm-waterand sewage system infrastructure.An important factor is the current stateof the sewagesystem: if the system is not even capable to deal with the current rainfall, expensivemodificationsmightbeneededinthefutureduetoclimatechangeaffectingthenumberofextreme rainfall events positively (IPCC, 2014). Particularly in these cases, the economicbenefitofgreenroofscanbelarge.InHelsinki,atotalbenefitof3.9€-9.4€/!"wasfound,butall thefactorsthataffectthebenefitpositivelyareonarelatively low level inHelsinki(Nurmietal.2016).

• Airquality improvements: TanandSia (2005) found that levelsof fineparticles (#$) andsulphurdioxide (%&")decreasedby6%and37% in the immediateair-spaceafter a greenroofwasinstalled.CurrieandBass(2005)estimatedthat109haofgreenroofs inTorontocouldremoveabout8tonsofunspecifiedairpollutantsperyear.Peck(2003)estimatedthatcurrent roof greening in Toronto (cover over 6.5million) results in a 5-10% reduction innitrogendioxide('&"),andinareductionof30tonsof#$).Yangetal.(2008)showedthata totalof1675kgofairpollutantswas removedby19.8haofgreen roofs inoneyear inChicagowith the following distribution: 52%of ozone (0+),27%of'&",14%of#$./and7%of%&".Theannualtotalremovalperhaofgreenroofwasthen85kg,ofwhich44kgof0+,23kg of'&", 12kg of#$./and 6kg of%&".Yang et al. (2008) reported that theirestimatewas18%highercomparedtoanestimatefromToronto(CurrieandBass,2005).

• Thesereductionsinairpollutantscanconvertedintoeconomichealthbenefitsbyairqualitymodels that simulate the effects on the air pollutant concentration in a city, and thenresponse-functionsandeconomicestimatesofmortalityandmorbidityareusedtocalculatetheeconomicbenefit. Ifunitcosts fordifferentemissionsarealreadyknownfor thearea,thecostreductioncanbeestimatedbymultiplyingthereductionofairpollutantsbytheunitcost of emission. In this case, the reduction is in awaymodelled as a negative emissionstack.Thisapproachwasused inNurmietal. (2016)where itwasfoundthatover95%of


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thebenefitsareintheformofreductionofPM2.5and90%ofthesebenefitsarebasedonreductionofearlymortalityduetoPM2.5.

• Heat island effect: In urban environments, vegetation has largely been replaced byimpervious and often dark surfaces. These conditions contribute to an urban heat islandeffects,whereinurbanregionsaresignificantlywarmerthanthesurroundingsuburbanandruralareas,especiallyatthenight-time.Oneofthebenefitsofgreenroofsisthepossibilitytomitigatetheurbanheatislandeffect(Berardietal.2014).AstudybySantamouris(2012)reviewedurbanheatislandmitigationtechniques,andremarkedthatlarge-scaleapplicationofgreenroofscouldreducetheambienttemperaturefrom0.3-3°C.Byonlyconsideringthepriceofsavedcoolingenergy,BianchiniandHewage(2012)consideredthatextensivegreenroofscouldresultsinabenefitof1.2$-3$/!"andRosenzweigetal.(2006)thattheenergysavingsforcoolingcouldbeintheregionof0.7%-10%.

• Scenicbenefits:WhiteandGatersleben(2011)comparedtheaestheticqualityofdifferentroof types and found that people prefer view to a green roof compared to conventionalroofs. Fernandez-Canero et al. (2013) argue that green roofswith similar appearances toconventional green areas are most valued by citizens. Jungels et al. (2013) showed thatpositive preferences towards green roofs increased as the green roofs became morefamiliar. Lee et al. (2014) confirm that green roofs carry aesthetic quality over concretesurfaces,aestheticqualityishoweverstronglydependentonthegreenroofcharacteristics,suchaschoiceofvegetationanddiversity.ScenicbenefitshaveapotentialtobeasignificantfactoringreenroofCBA;theincreaseinthepropertyvaluesinthebuildingswithin30mofagreenroofwereassessedtobebetween0-1.2%withhedonicpricingmethod.Helsinkiisagreencitycomparedtomanyothercities,thebenefitsarelikelytobehigherinmanyothercitieswithlessnaturalgreencover.(Nurmietal.2016).

All in all, the literature shows that the private benefits (membrane longevity, energy costsavings,noise insulation)arenotusuallyhighenough to cover theexpensive installationof agreenroof,thesocialbenefits(privatebenefits+storm-watermanagement,scenicbenefits,airqualityimprovements,heatislandeffectmitigation)usuallysurpassthecosts.Thefactorsthathave a positive effect on the social benefits are: 1) cost of the reference roof so that higherreferenceroofpriceincreasesthebenefits,2)temperatureprofileofthelocationsothathighertemperatures increase thebenefits, 3) energyprice so thathigherenergyprice increases thebenefits,4)theaverageannualprecipitationandfrequencyofextremerainfall,5)backlogofthecurrentsewersystemand6)concentrationofparticulatematterandexposedpopulation.

UrbanStreetTreesBoththetrees inthestreetcanyonandthewalkingtreesas iSCAPE-interventionscanbebestdescribedasurban street trees rather thanurban forest. Street treesoffermanyES that thecitizens can be benefit from. The ES of street trees include at least the following: air qualityimprovement,noisereduction,aestheticandpsychologicalbenefits,storm-watermanagement,sun/heat/rain protection, reduction of urban heat island effect and resulting reduction ofcoolingenergyneed.Economicvalueforthesebenefitshavebeencalculated(e.g.Soaresetal.2011) and even software tools have been created for this purpose (e.g. STRATUM by USDAForestService).Otherbenefitshavealsobeenmentioned inthe literature including increased


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safety ofmotorized and pedestrian traffic, increased feel of security, increased business andlonger pavement life due to shading. (e.g. Burden, 2008). In iSCAPE, the focus is on the airqualityimprovementsandchangesintheexposuretoairpollutants,butliteratureisreviewedforotherbenefitsaswell.Thechoiceoftreespeciesisnottrivialeitherastheexpectedincreaseindry-spellsandheavy raineventsmustbe taken intoconsiderationwhenchoosing therighttreespeciesforagivenlocation(Brune,2016).

• Air-qualityeffects:Sometimesdirectestimatesoftheeffectsofstreettreesonmorbidityrates are estimated. Lovasi et al. (2008) found a lower prevalenceof asthma levels inareaswithmorestreet trees:adecreaseof29% in theasthma levelswas foundwhenthe tree cover was increased by 1 standard deviation (343 trees in1!")). InNetherlands, Maas et al. (2009) found that the prevalence of 15 out of 24 diseaseclusterswaslowerinareaswithmoregreencover.Donovanetal.(2013)foundoutthatadecreaseingreencoverincreasedprevalenceofcardiovascularandlower-respiratory-tractillness.However,bydirectlylookingattheillnessstatisticsandtreecoveritisnotclearwhicharetheeffectsthatcausethedecrease inmorbidityratesand it ishardtocontrol all other factors that make up a good living area. Consequently, for the air-quality effects, the analysis usually follows a path of first estimating the reduction ofpollutantsandexposure,andthentranslatingthesechangesintohealtheffects.Usuallymicro-scale models are used to evaluate the effects of the trees on air quality indifferent parts of the street (e.g. road traffic lanes, pedestrian lanes) and are thenintegratedwithlarger-scalecitylevelmodels.Also,physicalmodelsareavailable,aswellasarangeofmonitoringtechniques.(Vardoulakis,2014).Thereismixedevidenceoftheefficiencyoftreestoimproveairqualityinstreetcanyons.Whilesomestudiesindicatelargepotentialfortreesfordrydepositionofairpollutants(McPhersonetal.1994;Talliset al. 2011), more detailed dispersion models have shown that sometimes trees canaffect theairquality in anegativewaybydisturbing the flowof airpollutants furtherfrom the streets. (Vos et al. 2013) outweighing the benefits of deposition. Vos et al.(2013) found that only high impermeable screens lead pollutant reductions at thepedestrian lane. More common options appear to have an opposite effect. As theevidenceiscontradictingtheepidemiologicalstudies,moreresearchisneededandtheiSCAPEinterventionresearchisofhighrelevancefortheurbandesigners.

• Storm-water management: Trees reduce runoff by: interception of precipitation;increase of rainwater infiltration into the open soil under the canopy; increasing thewater storage capacity of soil, reducing the impacts of raindrops and decreasing soilerosion and pollutant wash-off (Tyrväinen et al. 1999). The reduction decreases theburden of sewage system and reduces the capital expenditure. The exact amount isdependent on the tree type and the soil, the precipitation pattern (including returnperiodsetc.)andtypeandconditionsofthesewagesystem(Soaresetal.2011).

• Aestheticbenefits:Theaestheticbenefitsoftreecoverhavebeenestimatedwitheitherhedonicpricingmethodorwithcontingentvaluationmethod.Usuallystudiesestimatethe value of proximity to urban green, but some studies have estimated the value ofindividualtrees(DonovanandButry,2009a),whichismorerelevantinrelationtoiSCAPEinterventions. Anderson and Cornell (1988) found that a front-yard tree in front of a


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residentialhouseinAthens,Georgiaincreasedthesalespricesbyaround400dollarsor3.5-4.5%. However, this study was not directly related to trees in street canyons.DonovanandButry(2009a)estimatedthevalueofstreettreesbystudyingthehousingprices inPortland,Oregon.Theyfoundthattreecoverandcrownarea(estimatingthe“volume” of trees)within 30.5m from a house increased the housing prices by 3% attheirmeanvalues.Inaverage,ahousehad0.558streettreesinfrontofitand84m2ofcrown area. They also estimated the aesthetic value of a single-tree: the value wasestimatedat19,958dollarsor9%ofameanhouseprice.

• Heat-island reduction and energy: Trees can cool down buildings during summer byshading the buildings and mitigate urban heat island effect, cool down the cities ingeneralandconsequentlyreducethecoolingenergyuse.Akbarietal.(1992)quantifiedthereductionofcoolingcostsinSacramento,California,andfoundareductionof26%-47%ofcoolingcostsfor16treesplantedaroundthetwotesthouses.McPhersonetal.(2005) found cooling energy cost reductions between 10-50% if trees were optimallyplantedaroundthebuilding.Donovan&Butry(2009)estimatedthatatreecouldreduceabuildingcoolingenergyby82kWhperyear,sothattheannualbenefitwouldtranslateintoabenefitof15.5dollars.Theypointoutthat this isveryclosetotheestimatesofMcPhersonetal.(2005)andareductionbetween10-50%intheannualcoolingenergycostsifmultipletreesareplantedonwestsideofthebuilding.

GreeninfrastructureIncontrastto individual interventions,suchastreesandgreenroofs,green infrastructure isamore comprehensive concept and in iSCAPE it typically includes also parks, open fields, andurban forests. The concept aims to highlight amore systematic view of urban green and itsfunctions (Renaud et al. 2009) and is a way to understand the total effects of relatedinterventions. Along these lines, it is more common to estimate the total value of maincategories of green infrastructure than to break the benefits of a singular ecosystem intoisolated ecosystem services (ES) at a time. Support for this “bundling” of ES intomain greeninfrastructurecategorieshasemergedintheliterature,withstudiesreportingthatmarketsandindividuals(orhouseholds)incorporateurbangreenintheireconomicbehaviourviacompoundcategories and received benefits (Czembrowski and Kronemberg 2016). The most commonvaluation techniques are thehedonic pricing and contingent valuationmethods. Thehedonicmethod is typically seen as the method able to capture spatially variable benefits andinterventions, since it is tightly connected to the location equilibria of households and firms,reflecting the compensation and overall utility they receive from different locations and theimpliedlocation-sensitiverisksandamenities.The meta-analysis of Brander and Koetse (2011) compared and synthesized the results ofvarious earlier contingent and hedonic valuations of open green spaces and found that thevalue increaseswhenpopulationdensity increases (connectedby the authors to scarcity andcrowdedness),thevaluedoesnotvarysignificantlywithincome,althoughregionaldifferencesinpreferences are a serious limitation in transferability of results, and thaturbanparkshavehigher value than other green types. The study concluded that, although contingent and


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hedonic valuations provide similar results, attention is needed to understand what kinds ofeconomicbenefitsarecapturedbyeachmethod.Themeta-analysisofPerinoetal.(2014)foundthatthemarginalvalueofurbangreenspaceisdecreasing indistance, incomeandpopulation,and increasing in thesizeofgreenspace.Theauthorsalsoprovidedasimulationanalysisoffutureurbangrowthandtheimpliedchangesinthe amount of green infrastructure in various UK cities, and concluded that changes in theprovisionofurbangreenspacescancreate,ordestroy,billionsofpounds’worthofbenefitstoresidents.Methodologically,theydescribedaspatially-referencedbenefit-transfermethodologyfor transferring similar results to other urban regions and demonstrated the use ofdistributionalweightsandofGISdata.ThehedonicanalysisofSiriwardenaetal. (2016) foundanon-linear relationshipbetweentheeconomicbenefitsofproperty-level treecoverand regional-level treecoverandshowed thatproperty-leveltreecoverofabout30%andcounty-leveltreecoverofabout38%maximizetheimplicit price of tree cover in property values in US locations. Moreover, they were able toconclude that, compared to the current % of tree cover in the US, the findings indicate anunder-investment, which is interesting to combine with knowledge from iSCAPE’s air qualityexperts. They offered detailed specifications on the influence of various tree-specificparameters(e.g.ageoftrees)ontheeconomicbenefits.Finally, the hedonic analysis of Votsis (2017) studied the price/m2 effects of apartments’distancetodifferenttypesofurbangreeninHelsinki(park,forest,openfield),findingthattheeconomicimpactsofdifferentgreeninterventionsvaryacrossdifferentareasanddensitiesofacity. The effect of green space is positive at 1-4% of average price per squaremeter. Urbanforestshavethehighestvalue,followedbyparksandopenfields.Theresultsappeartofavourthepreservationoftree-coveredspacesinallpartsofthecity,butparksarebeneficialfordenseareasonly,whereasopen fields in suburbanareasonly. The study confirms that thevalueofgreeninterventionsisinprinciplepositive,butconditionalonthetypeorcombinationoftypesof green and the location at which it is placed. It shows that environmental and economicobjectivesofgreen interventionscanbesynchronized ifcertainspatialplanningprinciplesarefollowed. It also shows that understanding the economic impacts of green interventionsrequires the study of a city’s agglomeration dynamics and relation between land use andresidential/firmlocationtheory.Additional indirect, cross-sectoral benefits, as well as costs, beyond those measured by thehedonic price equilibrium or contingent valuation are generated by green infrastructure andrelatedinterventions.Thesebenefitsandcostsaretypicallyhardtomeasurewithoutlarge-scaleequilibrium or microsimulation frameworks, and some of them are described in Section 3.3(Policyinterventions)below.

3.1.2 Greyinterventionsandthesocio-economicbenefitsLowboundarywallsAir quality benefits: Low boundary wall in street canyons can be used to reduce personalexposure to air pollutants on the footpaths. Thewall acts as a baffle tomodify the air flow


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pattern.The results fromGallagheretal. (2012) indicate that reductions inconcentrationarehighest inwindwardof the footpathranging from26%-50%.On leeward footpath, theresultsweremixed.McNabolaetal.(2008)foundreductionsof40%forperpendicularwinddirectionsand up to 70% parallel wind directions. The costs of these low boundary walls include theinstallationcostsandtherequiredspace,thatisthennotusablee.g.fortreesorparkinspace.Toquantifythebenefitsineithertermsofhealthormoney,moreinformationisneededaboutthe number of daily users of the footpath and the average amount of time spent in thefootpath. Epidemiological studies can then be used to predict the change in mortality andmorbidity.

PhotocatalyticpaintAirqualityeffects:KolarikandToftum(2012)evaluatedtheimpactofaphotocatalyticpaintonindoor air pollutant levels. The study showed that activation of photocatalytic paint byilluminationdidnothavepositiveeffectontheperceivedairquality.Lavfsetal.(2010)studiedthephotocatalyticreactionsofnitrogenoxidesforacommerciallyavailablephotocatalyticTi02dopedfaçadepaint.TheyshowedthatphotocatalyticpaintcanbeaneffectivesinkofNOandNO2.Also,theysimulatedtheimpactinastreetcanyon,andestimatedthatareductionof5%couldbeachievedforNOx.Thepositiveeffectcanhoweverbecompromised ifharmfulVOCsarebeingemittedfromthepaintedsurfaces,asindicatedbyAuvinenandWirtanen(2008).ThepaintmustthusbecarefullyselectedandfurtherdevelopedtoreducetheformationofharmfulVOCs.

3.2 Socio-economicimpactofbehaviouralinterventionsAs described in iSCAPE D1.3, environmental awareness and related pro-environmentalbehaviours are highly influenced by the group of belonging, which often has a key role inpushingpeopleinchangingtheirbehaviour,whenrationalmotivationsuchashealtheffectsoreconomic incentives are often not enough to influence individual behaviour. Thismakes theiSCAPELivingLabapproachakeyassettomaximisetheimpactsofthepilots.IniSCAPE,awarenessraisingandprovisionofair-qualityinformationamongcitizenshasatleastthreeobjectives:

1)Toalertpeopleofpoorairqualitysothattheycanreducetheirexposure2)Toensurethatpeoplehavealltheinformationpossibletomakeinformeddecisions3)Toencouragepeopletoreducetheirpersonalemissions

Basedonevidence,itseems–atleastonashortperspective-mucheasiertoreachobjectives1)and2)andtochangebehaviourinawaythatpeoplecanmitigatetheirownexposureratherthanreducetheoverallemissionrates(BickerstaffandWalker,1999).ISCAPE-interventionsarealsomoreaboutobjectives1and2than3.Warningsystems


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Researchrelatedtothe impactsofairquality informationdisseminationandwarningsystemshas been done for several decades as the problem of educating people how to best avoidexposure and how to reduce emissions is hardly a new one. In 1998 in UK Bickerstaff andWalker studied thepublic response to theairquality information.Theair-quality informationwas available on hourly basis from multiple sources, including internet. Also, an air qualityforecastwasavailableand itwasupdated2 timeseachday.Theresearchrevealedthatmostpeople had never received air quality information, and only around 20% of the peopleunderstoodthehealthimpactsrelatedtopoorairquality.However,abitcontradictory,70%ofthe respondents stated that they had at least sometimes tried to avoid exposure to airpollutants,closingthewindowsandreducingoutdoorsactivitybeingthemostusedoptions.Itseemsthat these responseswere relatedmore toself-perceivedairquality thanbasedonairqualityinformation.Only10%oftherespondentsclaimedthattheyhadonalongertimescaletriedtoreducetheirownemission,e.g.bychoosingnottousetheirowncar.Johnson (2003) evaluated how changes in communicating Air pollution index (PSI) inPhiladelphia,affectedthewayindividualsreceiveoruseairqualityinformation.Hereaswell,itwas concluded that neither the old nor the new format did particularly well at increasingknowledgeofairpollutionorresultinginaresponsetoreduceexposure.Theinformationwasnot foundwell trusted(only59%foundthattheairquality informationcanbetrusted)andahigh number of respondents (34%) did not agree that breathing polluted air (above the risklimits) has anegative impactonhealth.Around50%of the respondents said that they couldreducetheiroutdooractivitiesbasedontheinformation.However,addinghealthconcernsandrisk group definitions to the information were positive ways to improve the information.ResearchbyBushetal.(2001)alsoshowedthatdisseminatingbasiclevelairqualityinformationfor thepublic isnotenough.Public consultationandparticipation isnecessary inorder tobeabletomakeairqualityinformationmoremeaningfulwithrespecttohowtheyrelatetohealthandthecorrespondingactions thatshouldbetaken.The informationneeds tobetargetedattheriskgroupstohaveahigherresponselevel.Here,currentinformationtechnologyoffershighpotential,asiSCAPE-interventionswillshow.No study directly estimates the economic value of air quality information. Based on theliterature,ithasveryhighpotential,buthowtheinformationisdisseminatedtothepublic,howitisperceivedbythepublic,andhowitprovokesresponses,allleadtoinformationdecay.Onlyafractionofthebenefitsisactuallyachieved.IniSCAPE,wewilluseinformationservicechain–analysistoanalysethecurrenteconomicbenefitsofairqualityinformationandhowmuchvaluecanbecreatedwithnew informationanddisseminationsystems.Thisanalysishasbeenusedearliertoestimatetheeconomicvalueofweatherwarnings,e.g.byNurmietal.(2013)andbyPilli-Sihvola et al. (2016). We will also monitor the behavioural interventions gathering datadirectly from the participants to the pilots to assess the project impact at behavioural andawarenesslevelbeforeandaftertheinvolvementintheactivities.


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Valuingairqualityinformationandchangesinbehaviour–InformationServiceChainAnalysisEventhoughairqualityinformationisconstantlyavailableanddisseminatedtothepublic,themajorityof the citizensdoesnot listen, understandor trust air quality informationor even iftheydo,theydon’tchangetheirbehaviouraccordingly.Themajorityofthepotentialvalueofair quality information is consequently not realized. The hypothetical maximum benefitpotentialofairqualityinformationcanbeestimatedbye.g.agentbasedsimulationmodelsandpollutionresponse-functions,sothatonlyafractionofthehealthcostsremains.However,theactualvalueoftheinformationstemsfromtheuseoftheinformationandtheextenttowhichtheendusersareabletointerpretandusetheinformation.(Pilli-Sihvolaetal.2016).Atooltoestimatethecurrentlevelofbenefitrealizationandthepotentialforinnovation,usedpreviously in the relation of weather services (Nurmi et al. 2013), is an Information ServiceChain Analysis model (ISCA). It can be used in a semi-quantitative way indicating orders ofmagnitudeofimprovingpotentialperstep.ThesixstepsoftheISCAassesstheextenttowhich:

1. Informationisaccurate(accuracy)2. Informationcontainsappropriatedatafortheend-user(appropriateness)3. Theuserhas(timely)accesstotheinformation(access)4. Theenduseradequatelyunderstandstheinformation(understanding)5. Theenduserrespondstotheinformation(responsiveness)6. Reponsesactuallyhelptoavoidthedamage(responseeffectiveness)

TheoriginalmodelWeatherServiceChainAnalysis (WSCA)alsohada seventhstep indicatinghow other people benefit from the responses, but in relation to air quality information, thebenefitsaremainlyhealthbenefitsfortheagenttakingtheaction.Basedonliteraturereview,themainhurdles forthebenefit realizationarerelatedtosteps4,5and6. In iSCAPE,wewillanalyse how the iSCAPE-interventions can improve these steps, and quantify the potentialbenefitoftheinterventions.

3.3 Socio-economicimpactofpolicyinterventionPolicyinterventionsthatimproveairqualityviapassivecontrolsystemsorbehaviouralchangescan havemany definitions (depending, for instance, on sector or government level), can beclassifiedinnumerousways,andcanrangefromlocal-scalesingularinterventionstocity-widecomprehensive multi-objective strategies or even regional and national strategies. In thissection, we focus on the socioeconomic effects - or “generalized” effects, since a totalenumeration is an ambiguous issue, especially when considering long-term and indirectchannels -of green infrastructural interventions, whereas more precise social or economiceffectswerediscussedinearliersections.Thesocio-economic impactsofgreen interventions thatare targetedspecifically toairqualityare generally understood through studying the cross-sectoral impacts of green strategiesthemselves on the urbanmicroeconomic equilibrium,which in turn can be placed under theumbrella term of “green” or “sustainable” growth. From this perspective, Hallegatte et al.


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(2011)describethatthetoolboxofpolicyinstrumentsaimedatachievinggreengrowthcanbeacombination of price-based policies—which is themost widely discussed instrument—normsand regulation, public production and direct investment, information creation anddissemination,educationandmoralsuasion,orindustrialandinnovationpolicies.Although there can be alternative points of view, the main objective in green growth orsustainable urban development is achieving synergies between different environmental andsocio-economicobjectivesandbetweendifferentsectors,thegenerationofco-benefitsacrosssectorsandobjectivesfromagivenintervention,andeventuallymaintainingorboostingurbaneconomic growth by the extensive utilization of green practices (de Serres et al., 2010;Hallegatte et al., 2011). This is often described as transitioning to a sustainable urbanequilibriumandamajorquestionsurrounding the implementationofairquality interventionsshouldconcernthetrade-offsand/orcosts-benefitsoftransitioningtothatequilibrium(VerhoefandNijkamp,2002;Rode,2013).An OECD study by de Serres et al. (2010) found that green growth policies can lead to asignificantreallocationofresourceswithinandacrossbroadeconomicsectors,whereasaWorldBankstudybyHallegatteetal.(2011)substantiatedtheabovelineofthoughtbyshowinghowre-allocationsofresources,reducedenvironmentalexternalities,andincreasedefficiencyduetosustainableinnovationspushtheproductionpossibilityfrontieroutwards.Vandermeulenetal.(2011) point out that the total economic effects of green interventions can bemeasured bycombiningacost-benefitanalysisatthelocalscaleandmultiplieranalysisattheregionalscale.Theyidentifythefollowingeconomicimpactsforgreeninfrastructureprojects:

• Projectinvestmentcosts• Regionalinvestmentbenefits• Regionalexcessburden• Projectmaintenancecosts• Regionallabourbenefits• Regionalcostsoflandusechange• Avoidedcostsbynon-motorizedmeansoftransport• Projectrecreationbenefits• Regionalrecreationbenefits• Healtheffectsbynon-motorizedmeansoftransport• Environmentaleffects

Health and environmental effects have been discussed in the preceding sections and therespectivemethodologyisexplainedinSection5.Theabovelistcontainsothereffectsthatarenotexplicitlynamed.For instance, incitieswithlimitedsupplyof landandunmetdemandforhousingand/oroffice floor-space,opportunitycostswillbecome importantand,althoughnotexplicitlylisted,theseareincludedinregionalcostsoflandusechange.


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When discussing policies that will eventually affect spatial behaviour and the use of land orallocation of resources in space, it is also important to keep in mind that land is a limitedresourceandcitiesarespatiallyoptimizedsystems.Morespecifically, fromaspatialplanning,intervention implementation, and urban economic development planning viewpoint, urbaneconomic theorydescribes thaturban landuseandmorphology, transport infrastructureandmobilitypatterns,environmentalamenitiesandrisks,andresidentialandfirmlocationpatternsareelementsofaspatialequilibriumandareengagedinarecursivefeedbackstructureinthepartial(individual)equilibriaofthemarketswhichtheyaffect(Wegener,1994;Brueckneretal.,1999;Brueckner,2011).Fromthisfollowsthatwhen(a)extensivelandusechangesoccurinanurbanarea (following, for instance, extensive green infrastructural projects), or (b) a locationdemonstrateshighlevelsofenvironmentalamenities(forinstance,parks,coastalfeatures,orasustainable/greenpublicimage),thenthepropertyandtransportmarketswilltendtomovetonewequilibriamainlydueto:

• Priceanddemandchangesintheresidentialpropertymarket• Priceanddemandchangesinthetransportsector

Iftheabovechangesareextensive,theywilltendtoinfluence:

• Landusecompositionatlocalandcitywidescales• Supplyoftransportandchangesinthespatialdistributionofaccessibility• Labourmarketaspects,suchasfirmlocationandemploymentsupply

Notethatnotalloftheaforementionedchangesoccurwhenagreeninterventionhappens,anditrequiresextensiveandhigh-impactchangestoobserveshiftsintheurbanspatialequilibrium.


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4 Literature review on socio-economic impactsmethodologytestedininitiativessimilartoiSCAPE

Before further illustrating the methodology developed for the social and economic impactassessmentoftheiSCAPEactivities,thischapterprovidesanoverviewofalreadyexistingstudiesanddiscussionstomeasureandassessthesocialandeconomicimpactsofsimilarprojectsandresearch.Thisliteraturereviewhasadoubleaim:ononehand,itwillsupportthedevelopmentoftheiSCAPEmetricsidentifyingeffectiveandalreadyavailableframeworks.Ontheotherhand,itwillallowdefiningthecurrentstateoftheartofthisfieldofstudies,thereforehighlightingthecontributionprovidedbythisreport.Thereviewisbasedonpapersanalysingtheimpactsofairpollutiononcitiesandcommunitiesfrom the social and economic point of view.Most of the researches focus on some specificpollutants and on a selection of countries, working on identifying the most appropriatedimensionstoanalysethemonetaryandnon-monetaryimpactsoftheairpollutionsflows.Theanalysisandtheconclusionspresentedbytheacademicliteraturecanbegatheredinfourmainstreamsofanalysis:thequalityoflifeapproach;theselectionoftheairpollutionindicators;thedataavailability;andthehedonicpricingmethodology.Some of these topics will be addressed in detail in the following chapters, nonetheless it isrelevanttointroducethemhereinthewidercontextofthepathleadingtothedevelopmentoftheappropriatemethodology.QualityoflifeapproachMany studies dealing with air pollution impacts on societies build on the quality of lifeapproach,oftenalsoreferredtoas lifesatisfactionapproachor, fromanarrowerperspective,happinessapproach.Differentwordingstorefertothegeneralconceptofassessingsubjectivewell-being(Moro,2008)consideringvaluesandassetswhichdeeplyaffectpeopleandsocietieswithoutreflectingmonetaryoreventangiblewealth(Bullock,2008).Thisapproachisdescribedandanalysedinchapter5.3.Forthisreview,itisusefultokeepinmindtwopremisesaboutit:first, themainpurposeof using thequality of life approach is not to compare levels ofwell-beinginanabsolutesensebutrathertoseektoidentifyitsdeterminantsandtomeasure(oftenwithtailoredsurveystoasampleof localpopulation) theirvaluewithrespecttooneanotherandwithrespecttootheravailableassets(Welsh,2003).Moreover,afteryearsofinvestigatingthis fieldof studies,measuresof life satisfactionaregenerally found tohaveahigh scientificstandardintermsof internalconsistency,reliabilityandvalidity,andahighdegreeofstabilityovertime(Dieneretal.1999).Alistofindicatorsaffectinglifesatisfactionemergesfromtheliteraturereview(Brereton2007,Ferreira2013,Leuchinger2009,Streimikiene2015,Martuzzi2012,McLeod1999):age,disability


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status,maritalandpartnershipstatus,gender, labourforcestatus,occupationalposition,typeof employment contract, noise, air pollution, climate, crime rate, smell, water pollution,populationdensity, voter turnoutat the lastelections, traffic congestion, average commutingtime, proximity tomajor roads, railways and airports, educational attainment,marital statusincome,householdtenure,health.Airpollutionstudieshavealreadyprovedhowsomeofthoseindicators suchasnoise,poverty, violence,definedas stressors, areoften spatially correlatedwithindicatorsmarkingthecitizens’environmentalexposure(Clougherty,2009).Withtheaimof assessinghowairpollution impactsonpeople’squalityof life,mostpapersmakeuseof aselection of dimensions according to the object of their research and evaluating how theychangeinrelationtoairpollutionindicatorsfluctuation.Since air pollution is the core topic of the studies considered for this review, some of themdedicateaspecificattentiontotheintegrationoftheenvironmentaldimensionintothequalityoflifeassessment.Theenvironmentaldimensionisoneofthemajorinfluencesonqualityoflifeandoneofthefactorsusedtoinvestigatesubjectivewell-being.Ontopoftheindicatorslistedbefore(noise,climate,qualityofnaturalassetssuchaswater),Streimikienesuggestsapplyingthe following groups of indicators: environmental quality, environmentally responsiblebehaviour and consumption of environmental services. These groups are related becauseresponsible behaviour has a positive impact on environmental quality and leads to moresustainableconsumptionofservicesprovidedbytheenvironment(Streimikiene,2015).Moreover, by using Geographical Information Systems (GIS) further research employed datadisaggregated at the individual and local level to show that,while socio-economic and socio-demographic characteristics are important, consideration of amenities such as climate,environmentalandurbanconditions iscriticalwhenanalysingsubjectivewell-being.Location-specific factors are shown to have a direct impact on life satisfaction (Brereton, 2007).Therefore,thespatialvariablesandthedistanceplayakeyrole indeterminingtheimpactsofenvironmental factors on happiness and life satisfaction. The following quote highlights theimportanceoftranslatingthisacquiredknowledgeintoappropriatepolicymeasures:“The findings show that climatehasa significant influenceonwell-being, (…)Access tomajortransportroutesandproximitytocoastandtowastefacilitiesallinfluencewell-being.However,themanner in which they enter the happiness equation differs depending on the amenity inquestion.(…)Theseresultsmayhavepotentiallyimportantimplicationsforthesettingofpublicpolicy, suchas the locationofwaste facilities, the routingofmajor roads, locationofairportsetc.,soastohaveasminimalnegativeimpactaspossibleonwell-being.”(Brereton,2007)Onelastobservationemergingfromtheanalysisoftheliteratureconcerningairpollutionandqualityoflifeistheprominentroleplayedbythehealthindicator.Itisarecurringindicatorinmanyofthepapersfordifferentreasons:theavailabilityofmeasurabledataabouthealth incitiesandregions;theimmediateandintuitivefalloutofhealthissuesonasocietywell-being;andthepossibility to translatewhat is inprincipleanon-economicand intangibleassetofacommunity(theaverageconditionsofhealth)intomonetaryandeconomicvalues,estimatingthecostsandthesavingsoftheincreasingordecreasingofspecificdiseasesforthesociety.ItwillalsoplayacriticalrolewithintheiSCAPEmethodology.


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AirpollutionindicatorsAs anticipated,many researchesaim touncover the relationbetween someof the indicatorspresentedinthepreviousparagraph,andsomeindicatorsmarkingthestatusoftheairquality.To give a complete overviewof thematerials provided by the literature and to facilitate theunderstandingofourownmethodology,whichwillmakeuseofsomeoftheseindicators,herebelowashortdescriptionofthethreemainones,whichappear,togetherorseparately,inmostofthepapers:

• PM10(Particulatematter10):definedbytheEuropeanEnvironmentalAgencyas“anairpollutantconsistingofsmallparticleswithanaerodynamicdiameterlessthanorequaltoanominal10micrometer(about1/7thediameterofasinglehumanhair).Theirsmallsizeallowsthemtomaketheirwaytotheairpassagesdeepwithinthelungswheretheymay be deposited and result in adverse health effects. PM10 also causes visibilityreduction.”3PM includes particles directly emitted into the air such as diesel soot,agricultural and road dust, and emissions from mechanical scrapings. PM is alsoproducedthroughphotochemicalreactionsinvolvingpollutantsthatareaby-productoffuelcombustionfrommotorvehicles,powerplantsandindustrialboilers.TrafficisoneofthemainsourceofPM10,thereforetrafficpolicymeasureshaveagreatpotentialintermsofhealthbenefits,includingalsonoiseandpsychosocialeffects(Martuzzi,2002).

• SO2(Sulphurdioxide):itis“emittedwhenfuelscontainingsulphurarecombusted.Itisapollutant which contributes to acid deposition which in turn can lead to potentialchangesoccurring insoilandwaterquality.Thesubsequent impactsofaciddepositioncan be significant, including adverse effects on aquatic ecosystems in rivers and lakesanddamagetoforests,cropsandothervegetation.SO2emissionsalsocontributeasasecondaryparticulatepollutanttoformationofparticulatematterintheatmosphere,animportant air pollutant in terms of its adverse impact on human health.”4. Alreadyavailable datasets and some of the papers quoted in this chapter already prove therobustnegativeimpactofSO2concentrationsonself-reportedlifesatisfaction(Ferreira2013,Leuchinger2009).

• CO2 (Carbon dioxide): Carbon dioxide enters the atmosphere through burning fossilfuels (coal, natural gas, and oil), solidwaste, trees andwood products, and also as aresult of certain chemical reactions (e.g., manufacture of cement). Carbon dioxide isremovedfromtheatmosphere(or"sequestered")whenitisabsorbedbyplantsaspartofthebiologicalcarboncycle5.CO2emissionshaveconstantlygrownwithimprovementsinlivingstandards,andtheuseofmoreefficientcarscanhelptoreducegreenhousegas(GHG)emissionsinthetransportsector.(Streimikiene,2015)

3 https://www.eea.europa.eu/themes/air/air-quality/resources/glossary/pm104https://www.eea.europa.eu/data-and-maps/indicators/eea-32-sulphur-dioxide-so2-emissions-1/assessment-15https://www.epa.gov/ghgemissions/overview-greenhouse-gases


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DataavailabilityWithrespecttoboththeindicatorslistedintheQualityofLifeparagraphandtheoneslistedforair pollutionmeasurement, it is important to underline that data availability stands out as acommonissueformanyofthestudiestakenintoaccount.Eurostatisthemaindatasourceformostofthem,andwheneverpossibleauthorsintegrateditsdatasetswithon-the-fieldsurveys,inparticularforthedatagatheringofqualityoflifeindicators.Itstillstandsoutthatoftentheselectionofcountriesorregionsfortheanalysis,andoccasionallytheselectionoftheindicatorsareguidedbytheavailabilityofrelevantdata.AssummarisedbyFerreira:Thereareanumberof papersanalysing the relationshipbetweenair pollutionand subjectivewell-being. A common challenge to these papers is that to obtain high quality data on airpollutionwithdetailedspatialdisaggregationandlinkthesetoaspecificindividualisalmostanimpossible task. Unlike for other individual characteristics that might influence people’ssubjectivewell-being, informationonenvironmental characteristics is typicallynot collected inthe survey instrument and thus cannot bematchedwith respondents at the household level.(Ferreira,2013)The iSCAPE project is going to face the same problem and, while implementing the impactassessment,itislikelythatsomedata-wiseselectionwillbeneeded.HedonicpricingapproachThe effects of air pollutants on cities and communities tend to become tangible on physicalassetsliketreesorbuildings,framingatwo-sidedrelationwhereononehandsuchassetscansupport thecontainmentofairpollution (as illustrated in thepreviouschapter),whileon theother hand the air quality can affect the value and the conditions of local amenities andbuildings. In particular, sulphur dioxide “has been found in hedonic pricing studies to have asignificantimpactonhousingprices.”(Welsh2003).Similarly to thequalityof lifeapproach, thehedonicpricingapproach isdiscussed indetail inchapter5.2.Itistheapproachmostfrequentlyusedbystudiesconcerningairpollutionimpacts,inordertoassessthemarketeffectsoftheimprovementorthedeteriorationofairqualityonhouse pricing. Together with themonetarisation of the health impacts, to date the hedonicpricingapproachstandsoutasofoneofthemorereliablemethodstointegratetheeconomicdimension intotheoverallassessment.Accompaniedbyothermodels,necessarytomaketheframework flexible and tailored on the iSCAPE goals, the hedonic pricing approach willrepresentoneofthecornerstonesoftheeconomicimpactassessment.Thisapproachandthelifesatisfactiononeresultbypreviousresearchcomplementaryandtheirjointapplicationisthereforerecommended:


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Traditionally, the benefits of clean air have been assessed with the hedonic method (…).Research suggests that hedonic estimates indeed substantially underestimate the benefits ofcleanair.(…)Thelifesatisfactionapproachcapturestheresidualeffectofairpollutionforwhichpeoplearenotalreadycompensatedinthehousingmarket.(Leuchinger,2009)The literature reviewpresented in this chapter shows theopportunitiesand theobstaclesonthe way the development and implementation of the iSCAPE impact assessment. Previousstudiesprovideasoundbasis intermsofapproachesandmetricstoidentifyandevaluatetheprojectofimpacts.Thequalityoflifeapproachoffersawiderangeofdimensionsandindicatorsthat can be adapted to the project interventions through analysis and consultations. Thehedonicpricingapproachissimilarlyalreadytestedastheappropriateprocesstotranslateairpollutionsimpact intoeconomicones.Moreover,thetwoapproachesprovidecomplementarysetofresultsthatwillallowframingacomprehensiveassessment.Atthesametime,manyresearcheshavebeenhinderintheircompletenessandaccuratenessbythe lack of comparable, recent and available data. On the light of the diversity of iSCAPEinterventionsanddataneeded,coordinationamongpartnerstoguaranteethenecessarydataflowwillbeakeyelementtodeliverthefinalassessment.Themethodologypresented inthefollowingchaptershavebeennonethelessframedkeepinginmindthispotentialobstacle,anddevelopedinaflexibleamodularwaytoavoidthatsomemissingdatacouldaffectthewholeevaluation.


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5 iSCAPE socio-economic impact assessmentmethodology

5.1 Theoverallframework Indevelopingthefollowingmethodology,themainchallengelaysinthealignmentbetweenthequantitative and qualitative analyses, more specifically the impact that can be expressed inmonetarytermsandthosethatcannot.Moreover,themethodologyaimstoassessaresearchproject,maintainingconsistencywiththeECconceptofprojectassessment,whiletheprojectisrunning.Forthesereasonsthemethodologicalframeworkthatfollowscanbeconsideredasafirstversionofanelaborationthatwillbeupdatedthroughouttheproject,inordertobeabletodescribeinaneffectiveandreliablewaytheimpactsofallactivatesandresultsachievedbytheproject.Dependingontheprojectprogress,theassessmentreportcouldbeprecededbysomeamendmentstothemethodologyillustratedinthefollowingparagraphs.The framing of the methodology starts with the identification of the project outputs underassessment.FortheiSCAPEprojectwecanidentifythreeoverarchingoutputs:- Modificationintheconcentrationanddistributionofasetofdefinedairpollutantachieved

bymeanofdifferent instruments/processes (passivecontrol systems,behavioural changeinterventionsandpolicyinterventions).

- EngagementofcitizensandlocalstakeholdersinpilotactionsfollowingaLLapproach.- Scientificpapers,bookandotherscientificproductions.Inordertomapanddescribetheimpactsoftheabove-mentioneddifferentoutputs,indifferentlocal contexts and through different specific activities, a single methodology would not besufficient.Forthisreason,iSCAPEbuildsontheexperienceoftheSEQUOIAprojectandofthoseprojectsthatfollowedit,defininganadhocmethodology(Passaniandothers,2014)basedonthecombineduseofdifferenttechniquesinordertoovercomethelimitsofeachsinglemethod(i.e. collection of statistics, case studies, peer review, cost-benefit analysis, multi-criteriaanalysis (MCA), input-outputmodels,etc.) and inorder togatherquantitativeandqualitativedatawithinthesameanalyticalframework.Morespecifically,theSEQUOIAmethodologyisstructuredinfourmainsteps: 1.Mappingtheareasofimpact 2.Baselineidentification 3.Expostscenariodescription 4.FinalassessmentanalysisIn this document, the areas of impact mapped are described in the social impact section(paragraph5.3.1)andarebasedonthebehindGDPapproach.Thebaselineidentificationwillbe


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investigatedinTask5.2forboththeenvironmentalandsocio-economicdimensionsandallthethreearegoingtobeequallyrelevantfortheimpactassessmentactivities.Theexanteandexpostscenariosdetailedinformationwillbegatheredtoquantifytwokindsofimpacts: economic impacts and social impacts. The division between economic impacts andsocial impacts is intended only for methodological purposes. In fact, the two impacts areanalysedthroughdifferentmethodologies(seechapters5.2and5.3),themaindifferencebeingthat the formerusesmonetizedvariables,while the latterusesnon-monetizedvariables.Thisdoes not wish to create a dichotomy between them, as the two assessments are fullycomplementary,asalreadymentionedinchapter4.Moreover,theeconomicimpactwillmainlyfocusonthefirstoutputwhilethesocialimpactwillfocusonthesecondandthirdimpacts,foraspecific reason: the reductionofpollutantspromotedby the iSCAPE interventionswillhaveadirectimpactonhealthintermsofreductionofdeathandofmedicalcostsforpollution-relateddiseases. These can be expressed in monetary terms using the methodologies described inchapter3.The improvementofairquality impactsonothersocialaspects is lessdirectand isvery much dependent by the perception citizens have of air quality and its eventualimprovement.Forthisreason,thesocialimpactswillbemainlyobservedlookingatthechangesintroduced by the engagement activities and the Living Lab activities, which will promote abetterunderstandingandamoregroundedperceptionofthephenomenon.Theeconomic impact assessmentwillmainly focuson themarketable impactsonhealth andhouse pricing, relying depending on the pilot on one of four different methods: the impactpathway approach, thehedonic pricing approach, the life satisfaction approach and theunit-costmodellingandmeta-analysis,alldescribedindetailinthefollowingchapter.Thesocial impactassessment is inspiredbythefundamentalsofMulti-CriteriaAnalysis(MCA)(Köksalan et al. 2011; Dodgson et al. 2009), according to which each of the various impactsshouldbeexpressedinitsmostsuitablemetric,byusingappropriateindicators.Thisisjustifiedby the fact that most of the social impacts generated by iSCAPE pilots (e.g. the impacts oncitizens’awarenessonenvironmentalissues,changeontheirbehaviours,scientificproduction,etc.)cannotbeexpressedortransformed intomonetaryterms.Therefore, theresultofsocialimpact assessmentwill beamulti-criteria/multi-dimensionaldescriptionof thenon-monetaryimpactsofeachprojectassessed,usingasetofappropriatequalitative-quantitativeindicators.The Sequoia approach envisaged a final step in which the economic and impact assessmentresults were synthetized in a single index. At the present stage of the iSCAPE project andconsidering the lessons learned in other impact assessment exercises applied to EC researchprojects(seeBellinietal,2015), it isnotrecommendedtoplansuchasyntheticindex,evenifthepossibilitytodosoisnotexcludedatthetimeofwriting.ThisisbecausetheiSCAPEpilotsarequitedifferentintermsoftheirfocus,ofthespecificactivitiesthatwillbecarriedoutandofthe number and typology of citizens thatwill be engaged. Resulting in the fact that, for thesocialimpactassessment,aqualitative,descriptiveapproachismoreindicated.Thiswillmakeitmore difficult to translate the results of the social impact assessment in numerical terms, anecessary step to generate a single, synthetic indicator together with the results of theeconomicimpactassessment.


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5.2 EconomicimpactassessmentTheeconomicmodellingapproachstartsfromthechoicewhetherweareinterestedinvaluingthe economic effects of increase or decrease of emissions, or arewe looking at the value ofchangesinair-qualitydirectly.Also,thechoiceofimpactsthatareincludedintheanalysisaffectthechoiceofthemodellingapproach:e.g.healthimpactsareusuallymodelledwithanImpactPathwayApproach,whileifwewanttoalsoincludemarketeffectssuchaslabourproductivity,macroeconomicmodelsareneeded.Theimpactsareoftenclassifiedaseithermarketimpacts,suchascostsofprovidinghealthcareservices,ornon-marketimpactssuchaslossofutilityduetoillnessorintheworstcaseofincreasedmortality.Infigure3,thetypologyofcostsisdepicted(OECD,2016):

Figure3-Typologyofcostsofairpollution(OECD,2016)

Inthissection,wegothroughdifferentvaluationmethods,explainwhateffectscanbecapturedwith each method, and evaluate how they should be used in the context of iSCAPE-interventions.


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ImpactPathwayApproachIn figure 4, the basic logic of Impact Pathway is depicted. The phase diagram in this figurefollows the logic that we “follow” the initial emission through changes in the emissionconcentrationsinthecityallthewaytothemonetizedhealthimpacts.

Figure4–ImpactPathwayslogicalchain

ExamplesoftheuseoftheImpactPathwayApproacharenumerousandincludebothnationalandregionalassessmentsinEurope(e.g.Hollandetal.2011)inNorth-America(e.g.Heoetal.2016;Fannetal.2009)andonanationallevelforexampleintheUK(Defra2015).Theapproachwasdevelopedinthe1990sinanEU-projectcalledeXterne.Themodel in figure 4 is a one-waymodel in thatway that the causal link betweendifferentnodes only goes oneway. This results in a very useful property of conditional independencebetween a node and all its parents except its direct parent. For thosepollutants that canbemodelledthisway,e.g.PM2.5,itallowsresearchersofdifferentexpertisetomodelonlyonelinkat a time and the experts of the next link can continue the process. Next, we present therequiredmodellingandinformationforeachconsecutivenode.Emissionmodelling–concentrationbeforeandaftertheinterventionThe first step in the ImpactPathwaymodel is toestimatehow the interventionor change inemissionscenarioswillaffect theairquality in thesurroundingregions.Thisalsorequires theknowledgeofthebaseemissionsandbaseconcentrations.Thus,airqualitymodellingisthefirstphaseof theprocess.Suchairqualitymodels includechemical transportmodels (CTM)whichare state-of-the-art with high time and spatial output resolution, dispersion models which


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translatetheemissionfromasourcetoreceptorareasbutneglectmuchofthemeteorologicaland atmospheric phenomena, and reducedmodels that are CTMmodelswith limited spatialandtemporalresolutionbutrequirelesscomputationalresources(Heoetal.2016).HealthresponseAfterwe have estimated the change in the concentration levels due to the intervention,weneed to knowhow these concentration level changesare translated intohealth impacts. Thehealth impact factor knowledge is taken from epidemical studies that have studied theassociationbetweenconcentrationratesandthemortalityandmorbidityrates,andresponse-functions are estimated based on that association. The current state-of-the-art response-functions are from aWHO-project HRAPIE, that usedmeta-analysis techniques to include allcurrentknowledge.Thoseresponsefunctionstelltherelativeincreaseinmortalityormorbidityrates.Intable2,wegiveasanexampleoftheresponse-functionsforlong-termPM2.5causedmortalityandmorbidity.

Table2–Response-functionsforlong-termPM2.5

Table3isinterpretedasfollows:theexpectedincreaseinmortalityis6.2%peryearwithevery1023/!+concentrationincreaseintheannualmean.The95%confidenceinterval isbetween4% and 8.3% interval. The group “A*” indicates strong reliability of the analysis. Note thatnumerical estimates for the concentration-chronic illness does not exists. For health careexpenditure and labour productivity, some numerical values exist, but usually with lowreliability.


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Table3-Response-functionsforshort-termPM2.5

ExposedpopulationandnumberofexpecteddeathsandillnessAfterwehaveknowledgeoftheconcentrationlevelandtheresponsetotheconcentration,wecanmultiplytheexpectedchangeswiththepopulationinformation.Astheresponse-functionsgenerally forecast the same rate of change for themortality for all demographic groups, thetotal population data and mortality rates is enough if we use the statistical value of life toquantify the results. If we use the value of statistical life years, we also needmortality andpopulationdatafordifferentagegroups.Thechanges in theexposurecanbemodelledbyeithermodifying the response-functions (sothata2%decreaseinexposurecouldresultina2%decreaseinair-pollutioncausedmortality)orbymanipulatingthedataoftheexposedpopulation.EconomicvaluationofsmallchangesinrisksrelatedtomortalityandillnessAsanext step,aswehaveestimated thenumberofexcess/avoidedmortality,morbidityandother end-points in a given area,we need to decidewhich unit costs to apply for each end-point.Themostimportantend-pointistheexcessmortality.Theexcessmortalitycanbevaluedeitherbycountingthenumberofexcess/avoidedprematuredeaths,orbycountingthelifeyearsthathavebeen lost/saved. Thevalueper statistical life year (VOLY) isessentiallyanapproach foradjusting VSL estimates to reflect differences in remaining life expectancy and involvescalculating the valueof each yearof life extension. This adjustment is needed if theaffectedpopulationisofverydifferentagethantheVSLfromtheoriginalstudy.VSL(valueofstatisticallife)isbydefinitionthemonetaryvaluethatpeopleattachtosmallchangesintheriskofdeath.Thisvaluecanbeestimatede.g.fromawage-mortalityrisklabourmarketequation,wheretheratethatpeoplearewillingtotakeariskierjobandthepremiumdemandedfortheincrease,isthemonetaryvalueofthechange(e.g.Viscusi&Masterman,2017).Iftheincreaseise.g.0.01,thestatisticalvalueof life is thedemandedpremiummultipliedby100.Soas in thisexampletheVSLreflectsthevalueoflifeforwork-agepopulation,andiftheairpollutionmainlyaffectselderly, thisadjustment isneeded.As thedegreeof lifeextension isusuallyclosely relatedtotheageoftheaffectedindividuals,VSLY(Valueofstatisticallifeperyear)isofteninterpretedas


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anapproachforadjustingVSLtoreflectagedifferences(Robinson,2008).However, intheUS(e.g. executive order 12866) the approach to use VOLY instead of VSL has been politicallydisputedasitgivesdifferentvaluesforthelifeofdifferentagegroups.IniSCAPE,weuseVSLasourbasecase,butwewithsensitivityanalysis,wealsoshowhowtheresultswouldchange, iftheremaininglifeyearsareadjusted.Inameta-analysisof68papersViscusiandMasterman(2017)foundthattheaverageVSLis12million dollars and median 9.7 million dollars (2015 dollars). They recommend using U.S.publicationbiascorrectedvalueof9.7milliondollarsandadjustingtolocalincomewithincomeelasticity, found typically in the range of 0.6-1. Recommended values for European countriestendtobe lower:WHO(2012)recommendusingEUaveragevalueof2.487millioneurosand3.371millioneurosforEU27countries.OECD(2012)recommendssimilar(lower)valuesbasedontheirownmeta-analysisofvaluationstudies:ForEU-27avaluebetween1.8-5.4millionUSDisrecommendedwiththebasevalueof3.6millionUSD(USD2011).Unitvaluestoillness(valuatedatsmallrisks)andforhospitaladmissionsarealsofoundintheliterature,forexampleOECD(2016).OnaEuropeanlevel,thevaluesobtainedbyHolland(2012)intheEC4MACS-project,representthemostupdated information.Awiderangeofvalues fordifferent illnessesand fordifferentcountries are found in the report, these values will be applied in iSCAPE-project as well.However,wewillusethesamevaluesforsamelossesacrossdifferentcountries,asopposedtomanyotherstudies.This istobesure,thatwegivethepreferencesofeachindividual ineachcountry within the study the same weight, this approach is often referred as distributionalweighting: giving the samevalue for the same loss is anapproach commonlyused in climatechangeeconomics.(Azar,1998;Johansson-Stenman,2000).UncertaintiesintheanalysisFormostpartoftheanalysis,theuncertaintycanbequantified,asboththeestimatedvalueandtheconfidenceintervalarereported.Forexample,inthecaseofexcessmortality,theestimatedincrease for an increase of concentration of PM2.5 by 1023/!+ is 6.25% and the 95%confidenceintervalis4%-8.3%.Wewillassumethateachsourceofuncertaintyisindependentofeachother,e.g.theuncertaintyintheresponsefunctionsisindependentoftheuncertaintyinestablishingeconomicvaluesforlife.Ifoneinterventionhasuncertaintyonlyfromonesourceandanuncertainty fromanother source, theseuncertaintieshaveno covariance. Thisway, asimpleportfolioanalysismethodologycanbeappliedforeachcity.ReducedformimpactmodelsSometimeswecanestimate,observeorassumetheresultingchangeintheconcentrationlevel(or with the linear response-function a change in the total exposure of the population). Forexample,iniSCAPEthelow-costsensordevelopmentmightprovideenoughinformationsothatconcentrationmapscanbeadjustedfortheiSCAPE-interventions.Inthatcase,areducedformoftheimpactpathwayanalysiscanbeused.Thisisdepictedinfigure4.Therestoftheanalysisfollowstheaforementionedlogic.Thisapproachhasbeenusedbothoncity-level(e.g.KanandChen, 2004) on a national level (e.g. Roayl College of Physicians, 2016) and on a continental(OECD,2015)andgloballevel(OECD,2016).


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Figure5–Reducedformofimpactpathwaysanalysis

Theimpactmodelcanfurtherbenarroweddownbycombininghealtheffects,numberofexcessdeathandillnessandtotalbenefitintoasinglebox.Thisisdonebyamodelthatisspecificallyintended for theseuse: the response-functions,populationdataand the statistical valuesareeitherbuiltinthemodel,orrequiredasinputdata.Thesemodelsincludee.g.BeTadevelopedinEurope(HollandandWatkiss,2002)orBenMAPdevelopedinUS(EPA,2017).HedonicpricingapproachHedonic analysis is often used to capture themarket value of those attributes of the urbanenvironmentthatarenot tradedexplicitly in theirownmarketsandare furthermorespatiallyheterogeneous. The functional relationshipbetween thepriceof a differentiated commodity,suchashousing,andthevectorofitsattributescanbeinterpretedasanequilibriumoutcomefrom themarket interactionsbetween sellersandbuyers (Rosen1974;Kuminoffetal. 2010).Attributes of the natural environment enter the hedonic equilibrium as location-specificamenities.Moreover,whenapropertytransactionisrealizedinthehousingmarket,thematchbetweenthe lowerboundoftheseller’saskingpriceandtheupperboundofthebyer’sofferbid reflectsaprice thatcompensates for locationaladvantagesanddisadvantages, relative toother locations of a particular urban area (DiPasquale andWheaton 1996). In the long run,prices reflect the equilibrium between demand for hedonic attributes and supply of thoseattributes(Rosen1974),andhouseholdswillbefullycompensatedforlocationaldisadvantages–atleastintheory.Thereissubstantialdiscussiononwhatportionofthevalueofanon-marketgoodiscapturedbyhedonic analysis, which has implication for what is measured when air quality is used as ahedonic attribute. Although shadow prices are often seen as the willingness to pay for


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environmental goods, they primarily indicate the marginal loss or gain of an agent in thehousingmarketwhen amarginal change happens in one of the hedonic attributes, providedthat thesearenot substantial citywidechanges (Tyrväinen1997). It is therefore important torealize that the hedonic price reflects first and foremost the dynamics of a city’s spatialequilibrium, and one should not use it uncritically as an indication of the total value of anenvironmental attribute.Thereare indications that themarginal valuesestimatedbyhedonicanalysisunderestimatethevalueofanenvironmentalattributesincetheydonotreflectthefullcompensation of households for environmental amenities or disamenities (see Luechinger2009),butitisalsoshownthattheestimatesdonotdiffersubstantiallyfromthosederivedbycontingent valuation (Brander and Koetse 2011). Moreover, Rosen’s theory assumes perfectinformation,whichimpliesfullytransparentrisksofnaturalhazards.Thisisusuallynotthecase,whichimpliesthatrisksarenotfullyreflectedinthehedonicpriceequilibrium–sellerandbuyercurvesdonotmeetprecisely,translatingtoanexcesssurplusfortheseller(seePope2008).Air quality has been assessed with hedonic analysis and the lessons learned are mostlymethodological.AnselinandLeGallo (2006) confirm thatbadairquality is reflected inhouseprices, but find that this happens only for air quality levels that stand out clearly from theaverage (i.e. highest category of bad air quality). They also report that air quality is bestincorporated as a hedonic attribute through categorical variables derived from Kriginginterpolation.Therecommendationtousecategoricalvariablesappearstoechobestpracticesand similar recommendations from physics-based ormeteorology-based air quality research.Usefulelementscanbederivedalsofromhedonicstudiesofinterventionsaimedtoimproveairquality.When itcomesto land-basednature-basedsolutions (e.g.parks,urbanforests), thereareindicationsthatoneshouldincludethoseinterventionsintothehedonicfunction,becauseconsumers are not able to separate the individual services derived from those interventions(e.g.airqualityreduction); theyratherwillbundleseveralservicestogether intoone landusecategory(CzembrowskiandKronenberg2015).Withrespecttoairqualityanditvaluationthroughhedonicfunctions,thelessonfromhedonicprice theory and applied literature appears to be that, inmany cases, air qualitywill not beidentifiable as an individual attribute in the hedonic price equilibrium. Therefore, additionalmethods have to be used as complementarymethods if the interest is on the total welfareeffects of improving air quality, simply because the hedonic price equilibrium is a partialequilibrium and because it involves significant elements of bounded rationality and gamebehaviour. However, hedonic analysis should be employed as an indicator of the effects ofurban planning interventions surrounding air quality improvements and understanding theirrelation to important aspects of urban dynamics, such as density, scarcity of resources, andurbangrowthanddevelopment(Brueckneretal.1999;Votsis2017).LifesatisfactionapproachLifesatisfactionapproachisarelativelynovelapproachtovalueairquality.Withlifesatisfactionapproach, the self-perceived quality of life is regressed to explanatory variables, includingincomeandairqualityvariables.Usingthecoefficientof incomeandairqualityvariables,onecancalculatetheratethatanindividualwouldbewillingtotradeincomeforbetterairquality.This is equivalent to Willingness-to-pay which is the measure of monetary welfare change.However, as people tend to pay less for housingwith areas of bad air quality and is already


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compensated via lesser housing costs, the WTP must be corrected for those estimates(Luechinger, 2009). By looking at how people valuate changes in concentration levels ofpollutants,onecandirectlyvaluatethevalueofachangeinairqualitywithoutusingstatisticalvalueoflifeorillness.Thosemarketcoststhatarenotincurredbytheindividualbutarecostsforthesociety,asmajorityofthehealthcarecosts,mustbeaddedtothetotalcostestimate.Aswewillseeinchapter5.3,thisapproachiskeyforthedevelopmentofframeworkforthesocialimpactassessment.Unit-costmodellingandmeta-analysisUnit-costmodellingmeans that theexpected reductionof emissions froma given source aremultipliedbypre-existingestimatesoftheunitdamagesfromthatparticularsource.Thisisthemost straightforwardmethodwith the least amount of resources needed to capture the airqualitybenefits.However,itsolelyreliesonearlierestimatesthatareusuallynotestimatedforthatlocationorsourcethatisinquestion.Theassumptionsinthemodelareburiedverydeepintheoriginalstudieswheretheestimatesaretaken.Forthesereasons,e.g.UKgovernmentonlyadvicestousethisapproachforsmall-scaleprojectsunder50millionpoundsoftotaleffect(HMTreasurygreenbook,2013).This model can be improved dramatically by meta-analysis regression models (Stanley &Doucouliagos, 2012). With meta-analysis, the earlier literature estimates can be gatheredsystematicallyandtheeffectofdifferentassumptionscanbequantified.Moreover,theregionalcharacteristicsofemissionsources,suchaspopulationnearby,canbeincluded,andtheeffectoftheseregionalcharacteristicscanbeincludedintheanalysis.IniSCAPE,wehavegatheredallthe available damage cost estimates. The literature review can be summarized with thefollowingtable,includingallthestudiestakenintoaccount:

Study Airqualitymodelling Areaandresolution Pollutants Stack heights/Source

typesVSL/VOLYinfo Otherimpacts

Muller and Mendelsohn(2009&201)

Integrated assessmentmodel: “Air PollutionEmission Experiments andPolicy model (APEEP)” Runfor increasing ton of eachpollutant one source at atime

10,000 sources across UnitedStates, ground sourcesaggregated by county, pointsourcesindividually

PM10,PM2.5,NOx,SO2, VOC,NH3

2 million dollars,tailored to the ageof the exposedpopulation bycalculating thepresentvalueoftheremaining years –also give thedamages based onuniformVSLvalues

Morbidity, decreasedcrop yields, reducedtimber, enhanceddepreciation of man-made materials,reduced visibility andrecreation

Fannetal.(2009) Response surface model,Based on air qualitymodelling using CMAQversion 4.4. with 36kmhorizontaldomain.

Nine urban areas in the U.S:New York/Philadelphia(combined), Chicago, Atlanta,Dallas, San Joaquin, Salt LakeCity, Phoenix, Seattle andDenver

Particles(PM2.5),NOx, SOx,NH3,VOC

Industrial point sources,Electrical generatingunits, area sources,mobilesources

6.2milliondollars Morbidity

Heoetal.2016 Reduced form models ofCTMs, built from taggedCTM simulations andgeneralised via regressions,EstimatingAirQualitySocialImpacts Using, Regression(EASIUR), spatial resolution36kmx36km

County-levelestimatesinU.S. PM2.5,NOx,NH3,SO2,

Ground level, 150m,300m

VSL 8.6 milliondollars

Buonocoreetal.2014 CMAQ4.7,fullmodel. LowerGreat Lakes region,Mid-AtlanticRegionU.S.

PM2.5,NOx,SO2

Power-plants in the US,stackheight3

7.2milliondollars

Levyetal.2009 County-resolution source-receptormatrix

U.S. PM2.5,NOx,SO2

407 coal-fired powerplants in U.S, stackheight3

6milliondollars

Hollandetal.2011 Dispersion modellingapproachcalledEMEP

Europe NH3, NOx,NMVOCs,PM2.5,PM10,SO2

Industrial facilities inEurope

VOLY (lowestimate):54000€VSL(highestimate):2,08millioneuros

Morbidity, cropdamage,

Defra2015 Britain NOx, PM,moregenerally

Agriculture, Waste,Industry, Transport,Rural

VOLY: 35,000pounds


41

SOx andNH3

Schwermeretal.2014 Cost-transfer from a studybyPreissetal.(2008)

Germany PM2.5,PM10, NOx,SO2,NMVOC,NH3

Power generation,industry, small-scalecombustion,transport

Same assumptionas in Preiss et al.(2008)

Preissetal.2008 Eulerian dispersion model,Tarrason2008

Europe NH3,NMVOC,NOx, PM10,PM2.5,SO2

County average externalcostsinEurope

40,000 in 2000,47,344 in 2010,26,038 in 2020;growth rate of 2%with incomeelasticity0.85

Work loss days,restricted activity days,morbidity, crops,materials andecosystems

EPA,2013 Benefit transfer of thevalues from UK, Defra,taking also into account thedifferencesinVOLY

Australia PM2.5 Notspecified VOLY: 288,991Australiandollars

Bickeletal.2003 Gaussian dispersion modelROADPOL

Selectedcase-studiesinEurope:inland waterway transport inRhine area, road transport inHelsinki, Florence, Berlin andFlorence

NOx,PM2.5,SO2, CO,Benzene,NMVOC

Road transport, inlandwaterway transport, railtransport

VOLY:74700€ Morbidity andrestrictedactivitydays

Waltonetal.2015 London Air QualityModelling toolkit, a kernelmodellingapproach

London PM2.5,NO2 TransportinLondon VOLY:36379

NO2 is treated withHRAPIE concentration-response function, alsoprovided sensitivityanalysis results for lesscertain impacts basedonHRAPIEfunctions

Table4–Literaturereviewfortheeconomicimpactassessment(unit-costsandmeta-analysis)

The damage estimates from the literature sources have been collected for PM2.5, NOx, andNH3.IniSCAPE,wecombinethisdatawithgeographicaldatadescribingtheemissionsources,including both geo-economical and geo-physical data. Both the modelling choices, types ofsources and the spatial characteristics or emission sources (e.g. demographical information,meteorological conditions) will be coded as variables in the analysis and the extent of howvariables affect the heterogeneity of damage estimateswill be analysedwithweighted-least-squaresmethod.Bythiswaytheanalysiswillallowmoresophisticateddamagecost–methodthanusingvaluesfromasinglestudyfromadifferentlocation.EconomicimpactsandmethodologiespercityiniSCAPE

In this project, we apply combinations of the abovementioned methodologies for theassessment of economic impacts in the seven participating cities. In each city, the employedmethodologyisdetermined,firstly,bythekindofairqualityinterventionthatisbeingtested—which determines the kind of economic impacts to be expected—and, secondly, by dataavailability.The following tableprovidesanoverviewof interventions,economic impacts,andmethodspercity.

City Intervention Economicimpacts Methodology

Bologna Street canyonwith / withouttrees

[1] Change/difference in theconcentration level ofpollutants and resultingchanges in mortality andmorbidityrates[2]Aestheticbenefits[3]Psychologicalbenefits

ReducedformimpactmodelBenefit-transfer of otherbenefits based on literaturereview

Vantaa/Lazaretto Greenroofs [1]Uptakeofpollutants[2] Reduced energy use forcoolingandheating[3]Aestheticbenefits[4] Storm-water managementbenefits[5]HeatIslandeffect[6]Noiseinsulationbenefits[7]Membranelongevity[8] Reduction of heat-islandeffect

City-level meteorologicalmodels combined withavoided cost techniques, e.g.reduction in cooling degreedaysetc.Hedonic pricing to estimatethe changes in thermalcomfortindexEarlier estimates by Nurmi etal. (2016) of green roofbenefitsUnit cost modelling with thehelpofmeta-analysis

Hasselt Behavioralchange –warningsystems

[1] Reduced exposure to airpollutantsand resultinghealthbenefits

Reduced form models withsensitivity analysis of changesin the exposed population /Also information uptakemodels(WSCAmodified)


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Dublin Low boundarywalls

[1] Reduced concentrationlevelsonpedestrianwalk lane,reduced exposure, andresultinghealthbenefits[2]Costs:reducedspaceinthestreets?

Reduced form models withsensitivityanalysisofdifferentassumptionsofchangesintheexposureofpopulation

Guilford / Vantaa(MetropolitanareaofHelsinki)

Greeninfrastructure

[1] Total effect measured viarealestateprices,notincludingeffects that are not withinmarketprices[2] Green infrastructurebenefits include aestheticbenefits, psychologicalbenefits, recreational benefitsetc.[3] Indirect effects inferredqualitatively from housingmarketadjustments

Hedonic pricing / Simulationsof behavior in the housingmarket with changing greeninfrastructureparametersCity-level meteorologicalmodels combined withavoided cost techniques, e.g.reduction in cooling degreedaysetc.Hedonic pricing to estimatethe changes in thermalcomfortindexQuestionnaire based surveyson individual values fordifferentgreenspaces

Bottrop Walkingtrees [1]Airpollutionremoval[2]Aestheticbenefits

ContingentvaluationBenefit transfer of earlierbenefit estimates of urbantreesReduced formmodels relatedtoairpollutants

Lazaretto Photocatalyticwall

[1]Uptakeofpollutants Reducedformmodels

5.3 SocialImpactassessment

In the light of what illustrated in chapters 3 and 4, the assessment of iSCAPE interventions’social dimension builds on the assumption that there is no pre-exiting methodology for theevaluationofthesocialimpactsoftheprojectpilots.Moreover,theinterventionsandtheLivingLabactivitiesofeachpilotarehighlydifferentandtheyaregoingtoproducedifferentimpacts.Accordingly, this part of the methodology should be able on the one hand to capture non-monetaryimpactsandontheotherhandtobeapplicableinamodularway,allowingpilotstobeevaluatedaboutdimensions that are relevant to their goals. To fulfil theseobjectives anddevelopourassessmentframeworkwefocusedonthequalityoflifeapproach,selectingasetofdimensions and indicators that will be assessed against data provided by different actorsinvolvedintheprocess.


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QualityofLifeapproach

In recent years, a wide debate has spread about the best ways to measure well-being andprogress in modern societies capturing dimensions beyond the existing economic indicators.The necessity to overcome the role of GDP (Gross Domestic Product) as a key indicator toevaluate the overall condition of a country or a community has raised an intense debate,stimulating fruitful reflections about what is perceived as healthy, desirable and relevant bycitizensatlargefromasocialandenvironmentalperspective.Conceptssuchaswell-beingandquality of life came under the spotlights for describing the value that cannot be expresseddirectlyinmonetarytermbutstillrepresentpartofthewealthofacountryorcommunity.Thisdebate has also confirmed the growing importance of the natural environment and ofphenomenasuchasclimatechangewithinthepublicdebate(Eurostat20116).

First attempts to expand this approach include theGenuineProgress Index (GPI)7, developedacrossthe‘80sandthe‘90swiththespecificaimtoreplaceorintegratetheGDPandcurrentlyusedmostly in the USwithin the ecological economics field of studies. The final goal of theIndex is tobringclosercitizensandpolicymakers,based intheassumptionthatprogressandsustainabilityareachievableonly ifgovernmentsbase theirdecisionson indicators that reallymattersforpeople’severydaylife.TheIndexmetricincludesindicatorsasincomedistribution,housework, education, resources depletion, crime, pollution, leisure time, defensiveexpenditures,publicinfrastructureanddependenceonforeignassets.Inthesameyears,theCenterofBhutanStudiesdevelopedtheGrossNationalHappinessIndex

(GNH), to measure the collective happiness in a country in opposition to the GDP as a keyindicator.TheIndexvisionfocuseson"sustainableandequitablesocio-economicdevelopment;environmental conservation; preservation and promotion of culture; and good governance"8and it builds on nine topics: psychological well-being, health, time use, education, culturaldiversityandresilience,goodgovernance,communityvitality,ecologicaldiversityandresilience,andlivingstandards.ItisnotbychancethatacountrylikeBhutanbecomepioneerinthisfiledofstudy:infact,thecountryhaveaverylowGDPcomparedtoothercountriesbutthequalityoflifeforitscitizenscanbehigherthaninmanyso-calleddevelopedcountries.Since then, several panels and initiatives at national and international level dealt with theproblemof how to comprehensively capture progress andwell-being in advanced evaluationmetrics, leading to more technical but equally relevant debates about the availability ofstatistically relevant data formonitoring and evaluation, and eventually to support decision-makingprocesses.TheStiglitz-Sen-FitoussiCommission (SSFC) report9and theCommunicationof the European Commission on “GDP and Beyond”10challenged a range of international,nationalandregionalmetricsurgingtoimprovecurrentindicatorsformeasuringprogress,well-beingandsustainabledevelopment.Thekeyconceptaddressedandcriticisedbytheseanalyseswastheabilityofan indicatorsuchastheGDPtoprovideacorrectperceptionofpeopleand 6 http://epp.eurostat.ec.europa.eu/portal/page/portal/pgp_ess/0_DOCS/estat/SpG_Final_report_Progress_wellbeing_and_sustainable_deve.pdf7http://rprogress.org/sustainability_indicators/genuine_progress_indicator.htm8http://www.grossnationalhappiness.com/9http://ec.europa.eu/eurostat/documents/118025/118123/Fitoussi+Commission+report10https://ec.europa.eu/eurostat/cros/system/files/06_GDP%20and%20beyond.pdf


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environment conditions, therefore supporting the need for new data andmethodologies. In2011, The European Statistical System Committee (ESSC) presented a report, on MeasuringProgress, Well-being and Sustainable Development prepared by the Sponsorship Group, co-chairedbyEurostatandINSEE(France).Thereportillustrated50actionstobeadoptedbytheEuropeanStatisticalSystem(ESS),toimplementtheresultsofthe“beyondGDP”debateandtobuildnewwell-beingindicators.Accordingtothereport,qualityoflifeneedamultidimensionalmeasurementapproach,economicindicatorsshouldtakeintoaccounthouseholdperspectivesand distributional aspects of income, and environmental sustainability should be includedamong the pillars of the evaluation of well-being. In the same year, the Organization forEconomicCooperation andDevelopment (OECD) launched theBetter Life Initiative11with theaimtoidentifythecoreaspectsoflifethatmatterswhenitcomestopeople’swell-being.Theinitiative brought to the development of an index built on 11 key dimensions ranging fromtraditionalmeasures suchas incomeand jobs,health,education, tohousing,personal safety,lifesatisfaction,environment,communityandwork-lifebalance.Moreover,eachtopic isbuiltononetofourspecificindicators(i.e.theJobstopicisbasedontheemploymentrate,personalearnings, the long-termunemploymentrateand jobsecurity)andthe indexallowscomparingresults formenandwomen,andseeinghowmuchsocialandeconomicstatusaffectsresults.The index fulfils the purpose of comparing well-being across countries and of supportingnationalinstitutionsinorientingtheiragendaandtheirpolicydebates.This perspective and the indexes developed over the years with the aim to evaluate non-economicandoftenqualitativedimensionsoflifeandpoliciesrepresentedthebasistobuildtheframework of the social impact assessment of iSCAPE. Based on the review of theaforementionedindexesandontheconsultationwiththepartners,weidentifiedaselectionofdimensionsandsub-dimensionsabletocapturetheimpactsofalltheiSCAPEinterventionsandactivities,andtocomplementtheeconomicanalysisdescribedinthepreviousparagraphs.The table that followssummarizes themainareas identifiedas relevant in theanalysisof thequalityoflifebyEurostat,Istat(theItalianstatisticalofficewhichisplayingaleadingroleinthisdebate)andtheOECD.EUROSTAT ISTAT OECD

Productiveorothermainactivity Health HousingMateriallivingconditions Educationandtraining IncomeHealth EmploymentandWork-Lifebalance JobsEducation Economicwellbeing CommunityLeisureandsocialinteraction Socialrelations EducationEconomicandphysicalsafety Politicallifeandinstitutions EnvironmentGovernanceandbasicrights Safety CivicengagementNaturalandlivingenvironment Subjectivewellbeing HealthOverallexperienceoflife Landscapeandculturalheritage Lifesatisfaction 11 http://www.oecdbetterlifeindex.org/#/23224325342


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Environment Safety

Researchandinnovation Work-Lifebalance

QualityofServices

Table5-Dimensionsofqualityoflife:acomparisonbetweenIstat,EurostatandEOCDapproaches Asevidenttherearemanysimilaritiesamongthethreeframeworks,andweelectedtotaketheEurostatapproachasthemainpointofreferencebecauseitrepresentstheEuropeanstandardto the quality of life research and because it assures homogeneity of data amongst theEuropeancountries.Asdescribedinthefollowinglines,wewillnotbeabletousetheavailabledatainadirectwaybutstill,havingcountryreportsconsideringthesedimensionscanbeofhelpininterpretingtheassessmentresults.Beforedescribing theadaptationof thequalityof lifeapproachto the iSCAPEanalysis,a finalremarkconcernstheavailabledatasets.Itisimportanttonotice,infact,thatthequalityoflifedimensions are populated with national statistical data coming from different, but officialsources and with ad hoc surveys conducted by the national statistic offices of Europeancountriesonstatisticallyrepresentativesamples.Therefore,allthedataareatnational(macro)level and only some of them are available at regional or city level. On the contrary iSCAPEinterventions will be deployed at very local level and will engage citizens statistically notrepresentative of the national, regional or urban population. Furthermore, the iSCAPEinterventionswillnothaveadirectimpactontheentireurbanpopulation,astheywillengagearestrictednumberofcitizensandstakeholders.Forthisreason,itwillbenecessaryto:a)adaptthe Eurostat indicators and variables to themicro level in which the project is operating b)gatherdatadirectly from theengaged citizens and c) developamodel for generalising thosedata.Thelatterwillbeonlyfeasibleoncethedatahavebeengatheredandonacasebycasebase, evaluating the feasibility to generalise the gathered data at city level looking at theirquality,reliabilityandrepresentativeness.

5.3.1Theoverallsocialimpactassessmentframework

Drawing on the studies mentioned in the previous paragraph, we developed a frameworkconsistingonaselectionof9areasof impact,eachonearticulatedinsub-dimensionstailoredonthepilotsandtheirexpectedoutcomes.As a first step, we selected those dimensions that could be impacted by the projectinterventions considering the iSCAPE activities. We ended up excluding three dimensionsbecausenotaffectedbytheproject,atallorinameaningfulanddocumentablemeasure:

• Economicandphysicalsafety• Governanceandbasicrights• Overallexperienceoflife


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Health was then excluded because already covered by the economic impact assessmentapproachtowhich,assaid,thesocialimpactassessmentiscomplementary(seepar.5.1).The second stepwas to analyse the sub-dimensions and the related variables of each of theabove-listedmacrodimensions.Eachmacrodimensioniscomposedofseveralsub-dimensions(see table 6 as an example) and related variables, not all relevant for the purpose of ourassessment.

Productive orother mainactivity

Quantityofemployment

Employmentandunemployment

Underemployment,quantity

Underemployment,quality

Qualityofemployment

Work/lifebalance

Temporarywork

Assessmentofqualityofemployment

Othermainactivity InactivepopulationUnpaidwork

Table6-Sub-dimensionrelatedtoProductiveorothermainactivity

At the endof this process,we endedupwith the following list of areas of impacts and sub-dimensionscomingdirectlyfromtheEurostatapproachtoqualityoflife:

ProductiveormainactivityQuantityofemployment

Qualityofemployment:Work-lifebalance

Materiallivingconditions Income

EducationCompetencesandskills

Opportunitiesforeducation

Leisureandsocialinteraction

Quantityofleisure

Qualityofleisure

Socialinteraction

Socialcohesion


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Socialcapital

Communityempowerment

NaturalandlivingenvironmentPollutionAccesstogreenandrecreationalspacesLandscapeandbuiltenvironment

Table7-iSCAPEareasofimpactcomingfromEurostatapproachtoqualityoflife

Those first five dimensions and their sub-dimensions have been then further integrated.Followingasocial innovationapproach, forwhichthe innovationproducedbyan interventionshouldbenotonlymoreefficientandeffectivethanthepreviousones,butalsomoreequalandfair (Phills, Deiglmeier andMiller, 2008), we added the category of Inclusiveness and equalopportunities inorder tounderstand if the iSCAPE interventionsareable toengagedifferentsocial groups and are sensible to topics such as social exclusion and discrimination.Environmentalstudiesshowthatoftenqualityofairiscorrelatedtosocialstatussothatinthesamecity thosebelonging to lowersocial statusaremoreexposed topollution than thoseofhigher social status (Szasz and Meuser, 1997; Bulle and Pellow, 2006). Also related to theliteratureofsocialinnovation,butalsodrivenbysomeofthepilotactions(seeD2.2),weaddedtheareasof impactonBehaviours tomap the capabilityof iSCAPE topositive influencepro-environmentalbehaviours. ThenweaddedacategorytoassessthePolicyresultsplannedbytheproject,tobeenableanoverviewof theoutreachof this kindof activities. Finally, considering the very natureof theiSCAPEproject,i.e.aHorizonresearchproject,aScientificImpactareahasbeenadded.Thiswillmapthevaluegeneratedbytheprojectintermsofscientificproduction.IthastobenoticedthatthosecategorieshavebeenappliedtotheiSCAPEmethodologyevenifthevariablesselectedfortheassessmentaresometimesslightlydifferentfromtheofficialonesusedbyEurostat.Thisadaptationhastwogoals:beingabletocapturetheprojectactivitiesandoutputswitha tailor-madeanalysis;andbeingable tocapture themicro-levelof thechangesproducedbytheproject(whileEurostatvariablesoftenrefertoamacro-levelofanalysis).

Socialimpactsub-dimensions,indicatorsandvariables

Thefigurethatfollowsvisualisetheselectedareasofimpactsandtheirsub-dimensions.


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Figure6Socialimpacts:areasofimpactandrelatedsub-dimensionsAsanticipated,notall9areasofimpactareequallyapplicableandorrelevantforalltheiSCAPEpilots:therefore,wemappedtherelevanceofeachimpactareaforeachoftheiSCAPEpilots.Asthe overall methodology, pilots’ partners validated this mapping during our consultationprocess.Therelevancelevelisratesas:

• ✓:low• ✓✓:medium• ✓✓✓:high


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Thetablethatfollowsvisualisesthe9areasofimpactandtherelatedrelevanceforeachoftheiSCAPEpilotactions.

Pilots/LLsProductive

or main

activity

Material

and living

conditions

Educati

on

Leisure

and

social

interacti

ons

Natural and

living

environment

Behavi

ours Policies

Scientific

Impact

Equality

Dublin - - ✓✓✓ ✓✓✓ - tbd ✓✓ ✓✓✓ ✓✓Guilford ✓ ✓ ✓✓ ✓✓✓ ✓✓✓ tbd ✓✓ ✓✓✓ ✓✓Vantaa - - ✓✓✓ - - tbd ✓✓ ✓✓✓ ✓✓Bottrop ✓ ✓ ✓✓✓ ✓✓✓ ✓✓ tbd ✓✓ ✓✓✓ ✓✓Hasselt ✓ ✓ ✓✓✓ - - ✓✓✓ ✓✓ ✓✓✓ ✓✓Lazaretto ✓ ✓ ✓✓ ✓ ✓✓✓ tbd ✓✓ ✓✓✓ ✓✓Bologna ✓ ✓ ✓✓ ✓✓✓ tbd ✓✓ ✓✓✓ ✓✓

Table8–“social”areasofimpactsandrelevanceforeachoftheiSCAPEpilotactions.Thismappingwillbeusedwheninterpretingtheresultsoftheassessmentexercisetobesuretoconsidertheuniquenessofeachinterventionandtoassurethatspecialattentionisgiventotheareasof impact seenasmost relevant ineachpilotaction.Theparagraphsbelowdescribe indetail the nine dimensions and their indicators. The descriptions are based on the Eurostatdefinitionsofqualityoflifeindicators,andadaptedtothecontextoftheiSCAPEproject.ProductiveormainactivityThisdimensionreferstoworkinallitsaspects,paidandunpaid,fromaquantitativeandfromaqualitative perspective. It can cover aspects such asworking hours, employment rate, safetyandethicsofemployment,work-lifebalance.WithrespecttoiSCAPE,twoindicatorsaregoingto be affected by the project activities (table 9), which are “quantity of employment” and“qualityofemploymentasinwork-lifebalance”:

• Throughthefirstone,weaimtoassessifthebusiness-orientedoutputsandactivitiesofthe project (i.e. monitoring kits, photocatalytic paintings, building on greeninfrastructures, maintenance of new green infrastructures) are going to affect thecommercialentitiesintheconsortiumandatthelocallevel.

• Thesecondone,mainlyaddressedtoLivingLabparticipantsinvolvedinthebehaviouralstudiesorinthepolicy-orientedones,willassesstheimpactofthebehaviouralorpolicychangesinducesbytheprojectontheircommutingtime.Changemaybetriggedbytheuseofnewtransportmodalitiesornewtransportpaths.


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Areaofimpact Indicators Variables

Productive or mailactivity

Quantityofemployment N. of new jobs created byprojectresults’exploitation

Quality of employment:Work-lifebalance

Change in the averagesatisfaction with commutingtimeChanges in the work-lifebalance thanks to pilotactivities/outputs

Table9–Socialdimensionsofimpact–ProductormailactivityMaterialandlivingconditionsMaterialandlivingconditionsfocusesonthemorematerialassetsimpactingonpeoplequalityoflife,assetswhichrelevancecannotbeneglectedalsoinamorequalitativeandnon-monetaryevaluation. For Eurostat, this dimension deals with aspects such as income, household,consumption, poverty.Within the context of thismethodology, Income (table 10) is the onlyindicatorrelevanttotheendoftheassessmentoftheprojectactivitiesimpacts:

• Weaimtoassessiflocalinterventionortheirsimulationwillproduceanimpactontheincomeofthecommercialactivitiesintheneighbourhoodaffectedbytheproject.

• Wealsoaimtoassess ifmoresustainable lifestyleswill leadtodecreasingthecostsathouseholdlevel.

• AndwewillassesstheforeseenincreaseinincomeforiSCAPEpartnersorstakeholdersinvolvedinthedevelopmentofcommerciallyexploitableoutcomes.


Material and livingconditions Income

Change in income forcommercial activities in theareas interested in the pilotactionsChange in household tenure(costsaving)Change in income forcompanies or otherorganisations exploiting theprojecttechnicaloutputs(greenservicesproviders)

Table10–Socialdimensionsofimpact–Materialandlivingconditions


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EducationEducationisnowadaysrecognisedasakeyaspectofsocietieswell-being,sinceknowledgeandskillsaccountforanincreasedcapacityofmakingcontext-wisechoices,livingahealthierlifeandalso generating income (source needed). At a general level, this dimension can include theassessment of the education level, the typology of acquired skills and the availability ofeducationopportunities.Weexpect iSCAPEto impactontwooftheEurostat indicators (table11):

• the Opportunities for education: the Living Labs are going to organise a number ofeventsandgatheringsaimingtoraiseawarenessandtransmitknowledgeabouttheairpollutionissue.

• and theCompetencesand skills:on topof an increasedawarenessparticipants to theLivingLabswillgainaspecificsetofskillsnecessarytojoinsomeoftheactivities(i.e.airqualitymonitoringthroughthemonitoringkits).


Education

Opportunitiesforeducation

N.ofeventsprovidingknowledgeopportunitiesorganisedAverage number of participantforeachevent

Competencesandskills New skills acquired byparticipantstotheactivities

Awareness Change in awareness on qualityofair-relatedissues

Table11–Socialdimensionsofimpact-EducationLeisureandSocialInteractionSocialcohesion,socialinteractionandleisureactivitiesareallkeydimensionsofasocietywell-being.Byleisureactivitieswemeanallthoseactivitiesthatcommunitymembersundertakefortheirowndesire,pleasureandpossiblyenrichment.Theorganisationof time ina society isacriticalaspectwhenitcomestotheextenttowhichitsmembersareabletoprovidethemselveswith these kinds of activities. Social interactions, on the other side, are essential traits of allhumanlifeandtheirqualityhasastrongimpactoftheindividualoverallwell-being:theextentoftheirpersonalandcommunitynetworktendtoaffectnotonlytheirprivatelifebutalsotheirjobandhealthcondition.ForiSCAPEweidentifiedsixindicatorstoassesstheLivingLabimpactinthisdimension:

• thequantityofleisure,toassesstheleisureeventsprovidedbytheproject;


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• thequalityofleisure,abouttheparticipants’perceptionofthoseevents;• the social interaction, to evaluate whether joining the project activities impacted on

people’spersonalrelationships;• thesocialcohesion,toassesstheimpactonthecommunityleveloftrust;• thesocialcapital,whichwillmonitorifparticipatingtotheiSCAPEactivitiesenlargedthe

socialnetworksoftheparticipants;• and the community empowerment, to assess if the community strengthen itself by

gatheringinneworganisationandinformalgroups.


Leisure and socialinteraction

QuantityofleisureN.ofleisureeventorganisedAverage number of participantforeachevent

Qualityofleisure Perceived quality of the leisureactivitiesorganised

SocialinteractionFeelingoflonelinessSatisfaction with personalrelationships

Socialcohesion Ratingoftrustinothers

Socialcapital N. of new social relationsestablished

Communityempowerment

N.ofnewcommunity initiativesorganised by participants ofiSCAPELLsDescriptionandnumberofnewcivic society organisationsand/or informal groups createdatlocallevel

Table12–Socialdimensionsofimpact–Leisureandsocialinteraction


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NaturalandLivingEnvironmentAlthough,asmentionedabove,task5.2willdealindetailwiththeenvironmentalimpactsoftheprojectoutputs,theNaturalandLivingEnvironmentisahighlyrelevantdimensionforthesocialassessmentofiSCAPE.Itconcernsallthoseaspectsinfluencingtheenvironmentinwhichpeoplelive, such as pollution, local amenities, distribution of local buildings, landscape. For theassessmentofthisproject,weidentifiedthreeindicatorsthatarelikelytobeaffectedbyit:

• Air Pollution: this indicator will be calculated within task 5.2 of the project. For thepurposeofthesocialassessment,wewillusethedataproducedbythattasktoanalysethecorrelationbetweenthechange inairpollution indicatorsandthechange insocialimpactsindicators.

• Accesstogreenandrecreationalspaces:theindicatorassessestheimprovementtothegreenandrecreationalspacesavailabletocitizensbroughtbythegreeninginterventionin cities and neighbourhoods,which participants to the LL are expected to be able toevaluate.

• Landscape and built environment: the indicator assesses the usability of thearchitecturalinfrastructureandtheaccesstotheservicesinthearea.


Natural and livingenvironment

AirPollution Reduction of pollutant asanalysedintask5.2

Access to green andrecreationalspaces

Changes in average satisfactionwith recreational and greenareas

Landscape and builtenvironment

Changes in the averagesatisfaction with livingenvironment

Table13–Socialdimensionsofimpact–NaturalandlivingenvironmentBehavioursAsillustrated,oneoftheinterventionsaimstospecificallytacklethebehaviouraldimensionoftheairpollutionissue,gatheringdataaboutcitizens’transporthabitsandthenprovidingthemthe information necessary to understand how a change in such habits would impact theircontributiontoairpollutionandthedamagetheyreceivefromit.Moreover,allLivingLabswillorganiseawarenessraisingopportunitiesthatcanimpactonparticipants’behaviours.Toassesstheresultsoftheseactivitiesweidentifiedtwoindicators:

• In the impactongreenbehaviourwewillevaluatechanges inbehavioursaccording tothe activities deployed by the Living Lab, personalising the surveys and the specificquestionsforeachcity;


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• IntheImpactonPerceivedcitizens’effectivenessweassesstheperceptionsparticipantsandstakeholdershaveoftheimprovementsbroughtbythebehaviouralchanges.


Behaviours Impactongreenbehaviours

To be developed case by case:i.e. impact on mobility-relatedbehaviours,impactonelectricityconsumption, impact on greenconsumption,etc.…Impact on Perceived citizens’effectiveness(PCE)

Impactonotherbehaviours Tobedevelopedcasebycase

Table14–Socialdimensionsofimpact–BehavioursPoliciesMostof the interventionsandof thestudiesaimstoproducepolicyrecommendationsandtoseethemembeddedasmuchaspossibleinthelocalinstitutionalcontext.Forthisreasoninthefinalphasesoftheassessmentwewillinvestigateabout:

• Quantityofpoliciesdeliveredbytheproject;• Qualityofthepolicies,estimatedbyparticipantsandstakeholdersoftheLivingLabs;• And Institutional change, to assess whether some of the temporary organisations

generated during the development of iSCAPE managed to reach a sounder level ofinstitutionalisation.


Policies

Quantityofpolicies N. of new policies proposal’sdeveloped

Qualityofpolicies Average satisfaction for the newpolicyproposalsdeveloped

Institutionalchange iSCAPE living Lab level ofinstitutionalisation

Table15–Socialdimensionsofimpact–PoliciesScientificImpactSinceiSCAPEisaresearchproject,allpartnersareexpectedtocontributetotheproductionofrigorousandinnovativescientificmaterialtoenrichthewiderareaofresearchdedicatedtotheairpollution.Toassesstheacademicoutcomesoftheprojectthemethodologywillevaluateonone hand the scientific production, gathering information about papers and contents as


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presented in in table 16, and on the other hand the level of interdisciplinarity of scientificoutputs.


Scientificimpact

Scientificproduction

Number of researchers in theprojectNumber of peer reviewedarticleswithimpactfactorNumber of peer reviewedarticleswithoutimpactfactorNumber of non peer-reviewedarticlesDescriptionoftopicscoveredNumber of patent and patentapplication developed by theproject

Levelofinterdisciplinarity

N. of disciplines andsubdisciplines represented indeliverable and publishedarticles

Table16–Socialdimensionsofimpact–ScientificimpactInclusivenessandequalopportunitiesThelastdimensionofimpactintegratedintheonesoftheEurostatmetricisInclusivenessandequalopportunities,toassesshowmuchtheoutcomesoftheprojectproduceafairandequaldevelopmentaccordingtoasocialinnovationapproach.InthecontextofiSCAPE,weidentifiedtworelevantindicators:

• Inclusiveness, evaluating the inclusion of participants from different background andfrom disadvantaged social position (people with disabilities, elders, children, peoplecomingfromlow-incomefamilies,unemployed,etc.)intotheLivingLabsactivities;

• Andgenderbalance,becauseasdemonstratedbytheliterature,airpollutionisagendersensitiveissue,whichmakestherationbetweeninvolvedmenandwomenasignificantindicator.


Inclusiveness andequalopportunities

Inclusiveness

N. of cultural backgroundrepresented among LLsparticipantsN. of participants belonging tocategories at risk of social


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exclusion among LLsparticipants

Genderbalance RatiobetweenmenandwomenengagedintheLLactivities

Table17–SocialdimensionsofimpactEquality

5.4 DatagatheringanddataanalysisprocessDuringthelastyearoftheproject,themethodologydescribedinthisdeliverablewillbeusedtoassess thesocio-economic impactof thepilotsandof the iSCAPEprojectoverall.Datawillbegathered from each city involved in the project. For the economic impact assessment, theresults of the experiments run in the pilot by the scientific partners through sensors andsimulationsandtheavailablelocalstatisticwillrepresentthecoreofthedataflowelaboratedtoassessthepotentialeconomic impact.Thesocialassessment,ontheotherside,willgathermostofthedatadirectlyfromtheinvolvedactorsthroughsurveysandfocusgroups.Based on earlier sections, especially 3-3.3 and 5-5.2, the economic impact assessmentframework can be depicted in figure 5. In table 18, we list the interventions, the expectedeconomicimpactsandthemethodologywehavechosentoapplyineachcase.Dataneedsarepresentedinthelastcolumn.iSCAPESuggestedeconomicimpactsandrequesteddatapercityandintervention

City Dataneeds

Bologna [1] Estimates of the changes in the concentration levels of pollutantsfollowingtheintervention[2]Demographicinformation[3]Mortalityrates[4]Ifavailable:Illness/hospitaladmissionrates

Vantaa/Lazaretto [1]Housingtransactiondata:--Per individual property; the data should contain the selling price,geographicalcoordinates(orstreetaddress)andstructuralattributesofthesolddwelling(age,size,condition,rooms,etc.).--Alternatively, per postcode or other sub-city zone with average sellingpriceandasmanyzonedescriptorsaspossible(accessibility,commuting,%greenspace,publicservices,etc.).[2]Meteorological/climatedata

Hasselt [1] Change in theexposure rates in relative terms (e.g. 10% lessexposureforthosewhoinstalltheapp)[2]Mortalityratedata[3]Ifavailable:Illness/hospitaladmissiondata


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Dublin [1]Changeintheexposure/concentrationatstreet-level[2]Demographicinformation[3]Mortalityratedata[4]Ifavailable:Illness/hospitaladmissiondata

Guilford / Vantaa(Metropolitan area ofHelsinki)

[1]Housingtransactiondata:--Per individual property; the data should contain the selling price,geographicalcoordinates(orstreetaddress)andstructuralattributesofthesolddwelling(age,size,condition,rooms,etc.).--Alternatively, per postcode or other sub-city zone with average sellingpriceandasmanyzonedescriptorsaspossible(accessibility,commuting,%greenspace,publicservices,etc.).[2] Geographical information of the city, including green space, transportandotheramenities[3]Meteorological information, e.g. thermal comfort before and after theintervention[4]Airpollutantconcentrationmapsbeforeandaftergivenintervention[5]Surveyresults

Bottrop [1]Surveydata,includingwillingnesstopay,incomelevelofindividualsetc.[2]Meta-analysisresultstouseunit-costmodel

Lazaretto [1]Uptakeofpollutants/changesintheconcentrationlevels[2]Demographicinformation[3]Mortalityrates[4]Ifavailable:Illness/hospitaladmissiondata

Table18–EconomicimpactsandrequesteddatapercityandinterventionFor thesocial impactassessment, thesourceof thedata illustrated in thepreviouschapter isrepresented in table 19, that summarises the involvement of Living Labs, local actors andprojectpartnersintheprocess:Variables ForwhichLivingLab?

To whom at local

level?

To whom in the

consortium?

Productiveormainactivityn. of new jobs created by pilotexploitation all localstakeholders Pureti and exploitation

leaderAverage satisfaction withcommutingtime Hasselt

Changes in the work-life balancethankstopilotoutputs Hasselt

Materialandlivingconditionschange in income for commercialactivatesintheareasinterestedinthepilotaction

all commercialactivities

Change in household tenure (costsaving) all participants to the

livinglabsactivities


59

Change in income for companiesor other organisations exploitingthe project technical outputs(greenservicesproviders)

all participants to thelivinglabsactivities

Educationn. of events providing knowledgeopportunitiesorganised all none responsible of the

livinglabsaveragenumberofparticipant foreachevent all none responsible of the

livinglabsNewskillsacquiredbyparticipantstotheactivities all participants to the


Leisureandsocialinteraction

n.ofleisureeventorganised Dublin, Guildford,Bottrop responsible of the

livinglabsaveragenumberofparticipant foreachevent

Dublin, Guildford,Bottrop responsible of the

livinglabsPerceived quality of the leisureactivitiesorganised

Dublin, Guildford,Bottrop

participants to thelivinglabsactivities

Feelingofloneliness Dublin, Bottrop,Bologna


Satisfaction with personalrelationships

Dublin, Bottrop,Bologna


ratingoftrustinothers Dublin, Bottrop,Bologna


n. of new social relationsestablished



n. of new community initiativesorganised



Description and number of newcivic society organisation and/orinformal groups created at locallevel



NaturalandlivingenvironmentChanges in average satisfactionwithrecreationalandgreenareas

Guildford, Vantaa,Bottrop,Bologna


Changes in the averagesatisfaction with livingenvironment

Guildford, Vantaa,Bottrop,Bologna

Behaviour

Impactongreenbehaviour Hasselt participants to thelivinglabsactivities

Impact on citizens perceivedeffectiveness Hasselt participants to the


Policiesn. of new policies proposaldeveloped all localstakeholder responsible of the

livinglabsAverage satisfaction for the newpolicyproposalsdeveloped all localstakeholder responsible of the

livinglabs

N.ofinstitutionscreated all localstakeholder responsible of thelivinglabs

InclusivenessandequalopportunitiesN. of cultural background all participants to the


60

represented livinglabsactivitiesN. of participants belonging tocategories at risk of socialexclusion

all participants to thelivinglabsactivities

ScientificImpactNumber of researchers in theproject none none allpartners

Number of peer reviewed articleswithimpactfactor none none allpartners

Number of peer reviewed articleswithoutimpactfactor none none allpartners

Number of non peer-reviewedarticles none none allpartners

Descriptionoftopicscovered none none allpartnersNumber of patent and patentapplication developed by theproject

none none allpartners

n.ofdisciplinesandsub-disciplinesrepresented in deliverable andpublishedarticles

none none none

Table19–Socialdimensionsofimpact–DatasourceThedataaregoingtobegatheredfromalltheactorsinvolvedintotheLivingLabsactivitiesandin the deployment of the interventions: iSCAPE partners, LL responsible, citizens and otherinstitutional stakeholders. In the surveys,all externalactorswillprovidea first setofGeneralInformation necessary to categorise the participants to the impact assessment anonymisedsurveys:

• Demographic variables: they include age, gender, income, title of study, culturalbackground,familycomposition,occupation.

• Psychographic variables: soft variables investigating actors’ attitudes, interests andbehaviours.InthespecificcaseofiSCAPE,thissectionofthesurveyhasbeendevelopedin collaboration with the Hasselt University within the D4.1, and will deal withparticipants’ opinion about environmental issues and their pro-environmentalbehaviours.

• Institutionalisation level: it allows understanding at which level the new Living Lab isgoingtobeembeddedintothelocaltexture,andhowmuchisorganisationisgoingtobeformalised.

The following sectionswill be articulated inmodular andpersonalised sectionsdependingontheLivingLab,theactivitiesandthecategoryoftherespondents,investigatingtheappropriatedimensions of impact as indicated in table 19. Respondents will answer the same set ofquestions before and after the participation to the interventions and to the Living Labcomplementaryactivities,toallowtheassessmentofthesocialimpactsthroughthecomparisonof their answers before and after the project activities. In the before-activities surveysrespondentswillbeaskedtoestimatetheexpectedimpactsofthethreelastdimensions,Policy,


61

InclusivenessandEqualopportunitiesandScientificimpact,andtheiranswerswillbecomparedwiththeafter-activitiessurveys.ThetimingofthesurveyssubmissionisplannedforeachLivingLabaccordingtotheirscheduledactivities, from June 2017 (Hasselt) until April 2019 (Dublin). As explained, they are going toreceiveasurveybeforethebeginningoftheactivitiesandoneaftertheend.SincetheframingoftheLivingLabactivitiesisalwaysinprogress,withopportunitiesofmeetingsanddiscussionwith citizens and other stakeholders arising while the project unfolds, we are constantlymonitoringtheirimplementationthroughamonthlyupdatedsharedfilewhereLivingLabscanrecord their progress and their next steps. This tool is proving very useful to ensure a fullunderstandingoftheirresultsandtheirflowofactivities,thereforeallowingtoregularlyverifytheconsistencyoftheimpactassessmentmethodologywiththeirprogress.


62

6 ConclusionsiSCAPE brings together different expertise and its workflow builds on a chain of severalactivities,manyofwhicharecomplexand innovative.For this reason, thedevelopmentofanappropriatemethodologicalapproachfortheprojecttackledchallengingareasofinvestigation,aboutwhich there is noacknowledgedapproach to assess theexpectedeconomic and socialimpacts.Asalreadymentioned, theapplicationof themethodologywill require fine-tuningofsomedimensionsormethodsaccordingtotheprojectresultsduringthenextyearandahalf,toverifytowhatextentotherdimensionsaregoingtobeaffectedbytheprojectimpacts.Themajorchallengesinshapingthemethodologyhavebeenrepresentedbytheidentificationof theappropriatemetricandmethodscapableofcapturing theproject lifecycle,andbytheintegration between the assessment ofmore quantifiable impacts and non-quantifiable onesand or the impacts that could be expressed inmonetary terms and those that cannot, bothnecessarytoevaluatetheprojectdevelopmentsandimprovementsineachcityinvolved.Withrespect to the first point, the partners’ involvement represented a crucial asset to thefinalisation of this work so that this methodology could be considered as the result of acollaborativeeffort.Thesocio-economicimpactassessmentexercisewillrunduringthelastyearoftheproject.Asexplainedthedatagatheringforsomeofthedimensionsofimpactisalreadyongoingandwillcontinue during all Year2, to be finalised during the first half of Year3 and allow the dataanalysisbeforetheendofiSCAPE.


63

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Report on iSCAPE socio-economic impact assessment methodology · 2018-03-13 · Report on iSCAPE socio-economic impact assessment methodology ––––––––– D5.6 08/2017