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Health impact assessment of particulate pollution in Tallinn using fine sparesolution and modelling techniques
Environmental Health 2009, 8:7 doi:10.1186/1476-069X-8-7
Hans Orru ([email protected])Erik Teinemaa ([email protected])
Taavi Lai ([email protected])Tanel Tamm ([email protected])
Marko Kaasik ([email protected])Veljo Kimmel ([email protected])Kati Kangur ([email protected])
Eda Merisalu ([email protected])Bertil Forsberg ([email protected])
Environmental Health
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]8/14/2019 HIA of Particulate Pollution in Tallinn Using Fine Spatial Resolution and Modelling Techniques
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HealthimpactassessmentofparticulatepollutioninTallinnusingfine
spatialresolutionandmodelingtechniques
HansOrru1,2*,ErikTeinemaa3,TaaviLai1,TanelTamm4,MarkoKaasik5,VeljoKimmel6,
KatiKangur7,EdaMerisalu1,BertilForsberg2
1DepartmentofPublicHealth,UniversityofTartu,Ravila19,Tartu50411,Estonia
2DepartmentofPublicHealthandClinicalMedicine,UmeaUniversity,UmeaSE-90187,
Sweden
3EstonianEnvironmentalResearchCentre,Marja4d,Tallinn10617,Estonia
4DepartmentofPhysics,UniversityofTartu,Riia142,Tartu50414,Estonia
5
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be0.64(95%CI0.171.10)years.Whileinthepollutedcitycentrethismayreach1.17
years,intheleastpollutedneighborhoodsitremainsbetween0.1and0.3years.When
dividingtheYLLbythenumberofprematuredeaths,thedecreaseinlifeexpectancy
amongtheactualcasesisaround13years.Asforthemorbidity,theshort-termeffectsof
airpollutionwereestimatedtoresultinanadditional71(95%CI43104)respiratoryand
204(95%CI131260)cardiovascularhospitalizationsperyear.Thebiggestexternalcosts
arerelatedtothelong-termeffectsonmortality:thisisonaverage150(95%CI40260)
millionannually.Incomparison,thecostsofshort-termair-pollutiondriven
hospitalizationsaresmall0.3(95%CI0.20.4)million.
Conclusions
SectioningthecityforanalysisandusingGISsystemscanhelptoimprovetheaccuracyof
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Background
Healthimpactassessment(HIA)isacombinationofprocedures,methodsandtoolsby
whichapolicy,programmeorprojectmaybeevaluatedbasedonitspotentialeffectson
thehealthofapopulation,andthedistributionofthoseeffects[1].Knowledgeofthe
exposure,baselinemortalityormorbidityinthepopulationaswellasexposure-response
functionsfromepidemiologicalstudieshelpsustoestimatetrendsinnegativehealth
effectsassociatedwithalternativescenarios.
OneofthefirstimportantairpollutionHIAwasconductedbyKnzlietal.[2].Thisstudy
estimatedtheimpactoftrafficparticulatepollutantsinAustria,FranceandSwitzerland
whichwerefoundtocause40000prematuredeaths,25000newcasesofchronic
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deaths.Theaveragelifeexpectancyatbirthwouldincreasemorethan2yearsinheavily
pollutedcitieslikeBucharest,Rome,TelAviv[9].IftheWHOairqualityguidelines
(PM2.5annually
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duetoprematuremortalityand29billionfrommorbidity.Thisrepresentsmorethan1%
oftheUnionsGDPin2005[13].Itisalsoimportanttonotethatthemajorityofthe
morbidity-relatedexternalcostsfromairpollutionarerelatedtothepublichealthsector
andnottothehealthcaresector[17].
EventhoughseveralindicatorshavebeenusedforHIAs,themaingoalistoquantifythe
negativeeffectsofriskfactorsandprovideguidelinesforpolicymakers,developers,
planners,etc.,toassisttheminthemitigationofnegativehealtheffectsbydecreasing
exposuretoairpollution.
Tallinn
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Methods
InthecurrentHIAstudy,dataonpopulation,baselinemortalityandmorbidity,air
pollutionexposure,exposure-responsefunctions,socio-economicalconditionandhealth-
careexpensesweregatheredandanalyzed.
Baselinepopulation,mortalityandmorbiditydata
PopulationdataforTallinnisbasedonthePopulationRegister(02.02.2007)accordingto
addressandregistrationinthefollowingagegroups:06,717,1827,2837,3847,48
57,5867,68+years.Thecitizensresidencesweredividedintosectionsaccordingto
neighborhoods(regionswithsimilargeographical,socio-economic,etc.,patterns),
formingsmalladministrativeunits(smallerthancitydistricts)usedincityplanningand
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cardiovascular(I00I99)andrespiratorycauses(J00J99).Cardiacadmissions(I20I25)
andcerebrovascularadmissions(I60I69)werealsousedfortheexposure-responsework
oncardiovascularhospitalizations.Theshort-termeffectsofhighpollutionlevelson
mortalitywerenotcalculatedseparatelyasaccordingtoseveralauthors[2,9,16]theseare
alreadyincludedinexposure-responsefunctionoflong-termmortality.
Exposureassessment
Theannuallevelsoflocally-emittedPM2.5,aswellasPM10formodelvalidationwere
estimatedusingmodelAirViro[20],basedonemissiondatafortraffic,industry,localand
centralheatingalongwithmeteorologicalparameterswithgridresolution200x200meters.
Adatabaseoflocalheatingemissionswasdevelopedduringthecurrentstudy,usinga
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trainspassingbyonadailybasis.Ineachmonitoringstation,theconcentrationofPM10is
routinelymeasuredbybeta-attenuationanalyzers(ThermoAndersenFH-62).Inthe
ismestation,thePM10levelsaremeasuredbythereferencemethod(DigitelDHA-80)
aswell.ThePM2.5levelismonitoredonlyattheismestation,andthisisdonebybeta-
attenuationanalyzer(ThermoAndersenFH-62).
TheannuallevelsofPM2.5werecalculatedforall84Tallinnsectionsusingtheaverage
concentrationofmodeledgridcellsinasection.Theaverageconcentrationforeach
sectionwasthenassignedtoallresidentsofthatneighborhood.Onlyindividualsofage
28+wereincludedinanalyses,astheUScohortstudy[23].
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Thecases(mortalityandmorbidity)werecalculatedinabsoluteandrelativenumbersfor
allsectionsinTallinn.Thefollowingequationwasused:
)1()( = XO epopYY
whereY0isthebaselinerate;popthenumberofexposedpersons;theexposure-response
function(relativerisk)andXtheestimatedexcessexposure.
ThenumberofYLLwascalculatedusinglife-tablesmethodology,wherethe
hypotheticallifeexpectancyiscomparedwiththelifeexpectancyaffectedbyairpollution.
ThecalculationofYLLandchangesinlifeexpectancywerefacilitatedbyaWHOCentre
forEnvironmentandHealthdevelopedprogramAirQ2.2.3(AirQualityHealthImpact
AssessmentTool)[26].Forcalculationofhospitalizations,theshort-termeffectsmodule
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Forthecountryasawholeanditsdevelopmentprospects,thelong-termoutcomesand
costsofairpollutioneffectsareevenmoreimportantthanthedirectcosts.Thismeansthat
inacaseofprematuredeath,peoplecanlosedecadesoflife-yearsbutdirectcostsappear
onlyintheactualyearofdeath.TheconceptofStatisticalValueofLife(SVL)andValue
OfLifeYear(VOLY)areusedtoexpressthecostoflostlivesandlife-years.These
conceptsstemfrompeoplescontributiontoGDP,typicalworktime,salaryand
sometimeshealthcare(compensationanddecreasedproductivity)costs[28,29].Asthere
arenocomprehensivestatisticallifevaluationstudiesinEstonia,theconversion
coefficientbetweenGDPandthestatisticalvalueoflifewasderivedfrominternational
meta-analyses(statisticalvalueoflifebeingonaverageequalto120timesGDPper
capitainacountry)[30,28].Valueofalifeyearwascalculatedfromthestatisticalvalue
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Results
Baselinepopulation,mortalityandmorbiditydata
Altogether,388964registeredresidentsofTallinnwereidentifiedin84sectionsofthe
city.Population-wisethebiggestsectionshadmorethan15000residentswhilesomeof
thesmallesthadlessthan100.Thepopulationdensityvariedagreatdealaswell.Inthe
majorityofsections,thenumberofresidentsrangedfrom3000to16000.
Basedonmortalitydata,themortalityratesindifferentagegroupswerefound(average
1136casesper100000citizensperyear)andthenumberswerecalculatedinall84
sectionsforthereferenceyear2006.Thebaselinehospitalizationratesweredetermined
separatelyforcardiovascularandrespiratoryadmissionsper100000peopleusingthe
sameprinciples.Theanalysisshowed3945and1266annualadmissioncases
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(localsourcesandregionalbackground).SincewefoundthatTallinnitselfcontributes
approx0.4g/m
3
totheunknownregionalbackground,itwassubtractedfromthe
modeledexposurevaluesinordertocalculatehealthimpactsonlyassociatedwiththe
levelsabovethoseoutsidethecity.
ThedifferencebetweenmodeledandmeasuredmeanPM2.5valuesinismestationwas
21%in2006(Fig.2).The23g/m3variationinPM2.5annualvaluesfromthemodel
indicatesasomewhatlowerbackgroundthanexpected.Theaveragedifferenceforall
threemonitoringstationsabovemodeledPM10levelsoverthreeyearsmeasurementswas
18.8%.ThebiggestdifferencewasinRahumonitoringstation,whichisclosetoarailway
withdiesellocomotivesandlessknownemissions,wheremeasuredandmodeledPM10
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Healthimpacts
Assomeneighborhoods(sections)hadveryfewdeaths,theestimatednumberof
prematuredeathsattributedtotheadditional(local)particlepollutionispresentedatthe
levelofcitydistrict(Table1),whereasYLLisgivenatthelevelofneighborhoodsection
(Fig.3).
Ouranalysisshowsthatlocallyemittedairpollutantscouldbeestimatedtocause296
(95%CI76528)prematuredeathsperyearinTallinn.AccordingtotheAirQcalculations
usinglifetablesthesedeathscorrespondto3859(95%CI10236636)YLL,whichis
988YLLper100000citizens.Asatotalnumber,thegreatestloss(235650YLL)wasin
neighborhoodswithalargenumberofcitizens(2500050000),e.g.,Mustame,
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Discussion
Exposureassessmentandbenefitsfrommethodologicaladvances
WhilethemethodologyforHIAinthisstudyfollowsgenerallyacceptedprinciples[31],
majordifferenceshavebeenfoundintheexposureassessments.InthecaseofTallinn,air
pollutionhasbeenmeasuredinonly3monitoringsites.Thus,itwasnecessarytouse
dispersionmodelingtogainanadequatelevelofdetailforexposureassessmentbycity
sections.Themodelvalidationshowedfairlygoodagreementwiththemonitoredlevels,
althoughthemodelgenerallyunderestimatedtheparticleconcentrations.Thereasonsfor
thismaybethelackofabackgroundconcentrationandanincompleteemissiondatabase;
forexamplethehighlevelsofPMmeasuredatspringtimebecauseofroaddust.
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Theplaceofresidencewasusedastheexposurepositionpresumingthatthegreatest
portionofthedayisspentthere.Thisissimilartootherepidemiologicalstudiesfrom
whichexposure-responsecoefficientsweretaken.Furthermore,siteofdwellingwasthe
onlydataavailablefromthepopulationregister.Theamountoftimeapersonspendsin
theresidenceareaandoutsideofit(work,studies,etc.)affectsindividualexposurelevels,
howevercurrentmethodologydoesnotpermitconsiderationofthesevariations.Neither
couldtheybeconsideredinthestudiesprovidingourexposure-responsefunctions.When
doinganalysiswithsuchaccuracy(whichispossiblewithmodeling),individualfactors
suchasahomesexactdistancefromthestreet,otherpollutionsources,individual
sensibilitytopollutants,etc.couldplayanimportantrole.
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Questionsmayariseaboutthepossibilityofover(under)estimationofthehealthimpacts.
Themainbasisforoverestimationisthehighbaselinemortalityrate(drivenbyexternal
causes)inEstonia.Thismagnifiestherelativeexposureimpact.Ifthehealthofthe
populationisgenerallyweak,theresidentscouldlikelybemoresensitivetoairpollution.
Insomecases,asintheReshetin&Kazazyanstudy,whereairpollutionwassaidtocause
1517%ofmortalityinRussia[33],thehealthimpactsareprobablyoverestimated
becauseofveryhighbase-linemortality(toalargeextentrelatedtoalcoholconsumption).
Ofcourse,weshouldnotbetooconservativeinourestimations.InHelsinki,wheretheair
pollutioninfluenceofbusseswasassessed,theresultscouldbeunderestimatedbecause
onlyexhaustparticles,whichareseenasmoretoxic,weretakenintoaccount[34].
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influenceonhealthrecognizedwhenNO2wastheindicator[36].Thismeansthatwemay
haveunderestimatedthepollutionimpactinthecitycentre.OnepossibilitywouldbetoconductHIAswithseveralpollutants,sothatalternativeexposureratescenarioscouldbe
designed.However,asimpleadditionoftheeffectsofdifferentpollutantswouldleadto
overestimationandwouldbemethodologicallywrong.
Thefourthcriticalissueistheexposuredataincombinationwithanyassumedthreshold
levelofhealtheffects.Studieshaveshownthatfineparticulatemattercancausenegative
effectsonconcentrationsbelowcurrentlimitvalues[37].Inprinciple,wehaveassumed
thatthelocalcontributionhasthemainimpact.Thebackgroundconcentrationisoften
usedasthereferenceconcentration.However,asthebackgroundisherepresumed(as
3
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Theaveragelossoflifeexpectancy(atbirth)estimatedhereisslightlyless(7.7months)thantheaverageofallEUcitizens(8.6months)[13].Therateofprematuredeaths
(76/100000)isalmostthesameastheECstudywhichshowed75/100000amongEU-25
residents[12].
Thetotalexternalcostsofairpollutionestimatedhereat150.3millionmakeup2.9%of
theTallinnGDP(in2005).ThisissomewhatsmallercomparedtofindingsfromRussia
2.66.5%[14]andBeijing6.55%[38],whichareofcoursemuchmorepolluted.But
comparedtothe1.5%forEurope(WHOassessment),itisslightlyhigher[13].Themain
reasonforthatmightbequitehighdecreaseoflifeexpectancyperprematuredeathcase.
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Conclusions
Tosomeextent,allthecitizensofTallinnareaffectedbypoorairquality.Eventhoughthe
levelsonparticulatesarenotlarge,stillthenegativehealtheffectsappear.Altogether,296
prematuredeathsperyearand3859YLL,anaveragelossof7.7monthslifeexpectancy
and275hospitaladmissionsduetoairpollutionmakeparticlepollutionasignificant
environmentalhealthissueinTallinn.Peoplesufferingfromchronicdiseasesshouldbe
informedabouttheairqualityindifferentregions,sothattheycouldavoidtheseareas.
Effortsshouldbedirectedtoimprovethesituationsinthemorepollutedsections.
Themethodologyweusedhelpedtoassessthehealthimpactsofairpollutioninatown
withasparsemonitoringnetworkbutwheredispersionmodelingwasavailable.
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Competinginterests
Theauthorsdeclarethattheyhavenocompetinginterests.
Authors'contributions
HOandBFdevelopedtheoverallconceptofcurrentHIAmethodology;ETconducted
dispersionmodeling;TLmadeeconomicevaluationanddeterminedbaselinehealthdata;
TTmadeGISdesigns;MKandVKimprovedpollutionemissiondatabase;EM
contributedtogeneralhealthimpactbackgroundanalysis;KKcontributedtothe
interpretationoftheanalysisresultsandtheirapplicabilityinurbanriskregulation,and
HO performed most of the analyses and drafted the manuscript. All authors have read and
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Figures
Figure1-Modeled(200x200mgrid)annualaverageconcentrationofPM2.5
inTallinn,g/m3.
Figure2-MeasuredandmodeledPM10yearlyaverageinmonitoring
stations.
Figure3-ThetotalnumberofYLLduetoPM2.5pollutioninTallinn.
Figure4-Decreaseoflife-expectancyduetoPM2.5pollutioninTallinn.
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Pirita 13192 6.4 5(18) 0.38(0.080.61) 0.36(0.090.61)
Phja-Tallinn
53621 9.3 33(959) 0.62(0.171.10) 0.52(0.140.89)
Total 388964 11.6296(76528)
0.76(0.201.36) 0.64(0.171.10)
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Figure 1
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Figure 3
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Figure 4
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