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JournalofEnvironmentalManagement145(2014)9e23 ContentslistsavailableatScienceDirect Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman Baltic Sea nutrient reductions e What should we aim for? Heini Ahtiainen a, Janne Artell a, Ragnar Elmgren b, Linus Hasselstro€m c, Cecilia Håkansson d,* aMTTAgrifoodResearchFinland,Latokartanonkaari9,FIN-00790Helsinki,Finland bStockholmUniversity,DeptofSystemsEcology,10691Stockholm,Sweden cEnvecoLtd.,Masholmstorget3,12738Skarholmen,Sweden dKTHRoyalInstituteofTechnology,fms,DrottningKristinasva€g30,11428Stockholm,Sweden a r t i c l e i n f o a b s t r a c t Articlehistory: NutrientloadreductionsareneededtoimprovethestateoftheBalticSea,butitisstillunderdebatehow Received21November2013 theyshouldbe implemented.Inthispaper,weusedatafromanenvironmentalvaluationstudycon- Receivedinrevisedform ductedinallnineBalticSeastatestoinvestigatepublicpreferencesofrelevancetothreeoftheinvolved 17April2014 decision-dimensions:First,therolesofnitrogenversusphosphorusreductionscausingdifferenteutro- Accepted19May2014 phication effects; second, the role of time e the lag between actions to reduce nutrient loads and Availableonline27June2014 perceivedimprovements;andthird;thespatialdimensionandtherolesofactionstargetingthecoastal andopenseaenvironmentanddifferentsub-basins.Ourfindingsindicatethatrespondentsviewand Keywords: value the Baltic Sea environment as awhole, and are not focussed only on their local sea area, or a Marinepolicy Contingentvaluation particularaspectofwaterquality.Wearguethatpublicpreferencesconcerningthesethreeperspectives TheBalticSea should be one of the factors guiding marine policy. This requires considering the entire range of Eutrophication eutrophicationeffects,incoastalandopenseaareas,andincludinglong-termandshort-termmeasures. Preferences ©2014TheAuthors.PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/3.0/). 1. Introduction the Marine Strategy Framework Directive (MSFD; European Parliament,2008)legallyrequiretheEUmemberstatestotakeac- Eutrophicationofcoastalmarineareasandestuaries,inpartic- tionstoachieve“GoodEcological(Environmental)Status(GES)”in ular,isanincreasingproblemacrosstheworld(Nixonetal.,1996; coastalandmarinewaters.Theyalsocallforstakeholderinvolvement Kroezeetal.,2014),mainlyduetothehumanintensificationofthe inthemanagementdecisionsforimplementationofthedirectives. globalbiogeochemicalcyclesofnitrogen(Erismanetal.,2013)and Muchremainstobedonetofulfiltheambitionsof theEUdi- phosphorus (Elser and Bennet, 2011). Problems with nutrient rectivesandtheBSAP.Theloadofnutrientstotheseaneedstobe enrichmenthavebeenreportedinestuariessuchastheChesapeake substantially reduced in order to mitigate eutrophication effects. BayintheUS(Murphyetal.,2011),theMississippiandChangjiang However,thetermnutrientloadreductionhasseveraldimensions. estuaries(USandChina)(Zhaoetal.,2012)andthenorth-western Inthispaper,wediscussthreeofthem:First,therolesofnitrogen BlackSeashelfinEurope(Capetetal.,2013). versusphosphorusreductionscausingdifferenteutrophicationef- Eutrophication, caused by nutrient enrichment, is the most fects;second,theroleoftimeethelagbetweenthevariousactions pervasive and serious pollution problem also in the Baltic Sea toreducenutrientloadsandmeasurableimprovements;andthird; (HELCOM,2010),andhasbeenhighonpoliticalagendasduringthe thespatialdimensionandtherolesofactionsthattargetthecoastal lastdecades.Severalinitiativeshavebeentakentoreducenutrient versustheopenseaenvironment. loadstotheBaltic,themostrecentlarge-scaleagreementbeingthe Eutrophication has a range of effects on the Baltic Sea HELCOM Baltic Sea Action Plan (BSAP; HELCOM, 2007, 2013), in ecosystem,suchasincreasedwaterturbidity,increasedbloomsof whichnutrientreductiontargetswerejointlynegotiatedbythenine cyanobacteria, deterioration of underwater sea-grass meadows, coastal countries. Further, European Union directives such as the changes in fish species composition, and oxygen deficiency in WaterFrameworkDirective(WFD;EuropeanParliament,2000)and bottom sediments. These effects are linked to marine ecosystem services such as the provision of seafood, recreational opportu- * Correspondingauthor.Tel.:þ46707329196. nities,andbiodiversity.Ahtiainenetal.(2013)showedinasurvey E-mail addresses: heini.ahtiainen@mtt.fi (H. Ahtiainen), janne.artell@mtt.fi studythattheBalticSeaecosystemservicesareveryimportantto (J. Artell), [email protected] (R. Elmgren), [email protected] the citizens in the nine countries surrounding the Baltic Sea. For (L.Hasselstro€m),[email protected](C.Håkansson). http://dx.doi.org/10.1016/j.jenvman.2014.05.016 0301-4797/©2014TheAuthors.PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/3.0/). 10 H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 example, over 80 per cent of the respondents in the survey had approximately16atomsofNforeachatomofP,orintermsofmass visitedtheseaatleastoncetospendleisuretimethere. about7.2timesmoreNthanP(Redfield,1958;Grane(cid:2)lietal.,1990). Much of the debate on the importance of nitrogen versus TheannualinflowtotheBalticSeafromlandandatmospherehave phosphorus for eutrophication effects has concerned their influ- aratioofN/Pmuchgreaterthanthis(ElmgrenandLarsson,2001), enceoncyanobacterialblooms.1Anincreaseinnitrogenavailability yetwheneasilyplant-available,inorganicformsofthesenutrients canactuallyhelpreducethecyanobacterialbloomsbystimulating aremeasuredinthesurfacewatersoftheBalticSeaproperinlate thegrowthofotherphytoplanktoncompetingwithcyanobacteria winter,beforethespringbloom,theN/Patomratioismuchlower forthelimitedsupplyofphosphorus(ElmgrenandLarsson,2001). than16(Grane(cid:2)lietal.,1990).Thereasonisthatprocessesremoving Since nitrogen availability generally limits production of phyto- thenutrientfromcirculationaremuchmoreeffectiveforNthanfor planktonotherthancyanobacteriaintheBalticProper,andatleast P.Theresultisthatthespringbloomofphytoplanktonendswhen partofthetimealsointheBothnianSeaandtheGulfsofFinland the available inorganic N has been exhausted, even though inor- and Riga, increased nitrogen availability will increase phyto- ganicPisstillavailable(Ho€glanderetal.,2004). plankton biomass and hence water turbidity. This will, in turn, Thiscreatesasituationwheremostphytoplanktonislimitedbya aggravateothersymptomsofnutrientenrichment,suchaschanges shortageofnitrogen,butnitrogen-fixingcyanobacteriaareabletofill in benthic fauna and vegetation, and the areal extent of oxygen- their nitrogen need byconverting the abundant nitrogen gas dis- deficientseabottoms. solvedinthewatertobiologicallyusefulcombinedforms(thepro- Ithasbeensuggestedthatnitrogen-fixingcyanobacteriashould cessofnitrogenfixation)(Grane(cid:2)lietal.,1990).Thismeansthatthe betheprimaryconcernwhendecidingonBalticnutrientreduction mainlimitingnutrientfornitrogen-fixingcyanobacteriaintheBaltic management strategies, essentially ignoring other eutrophication is phosphorus, evenwhen other plant growth is nitrogen limited effects (Schindler, 2012). Froma policy perspective,these discus- (WalveandLarsson,2010).Thegrowthofcyanobacteriaisslowat sions are important. If the public preference is primarily for first,butpicksupspeedasthewaterwarmstowardssummer,andby reducing the cyanobacterial blooms, it can be argued that well- earlyJulyacyanobacterialbloomhasnormallydeveloped.Inwarm directedmanagementstrategiesshouldfocusonthisissue. andsunnyweather,thebloomscanaccumulateatthesurfaceand Thepurposeofthisstudyistoinvestigatepublicpreferencesin alongtheshores.Theyaretoxicandstinkwhendecomposing,andare theBalticSeastatesforreducingdifferenteutrophicationeffects,to therefore a menace to tourism and recreation. Through nitrogen- studydistributionalimpactsofdifferentmanagementoptions,and fixation,theyalsoboosteutrophicationbyaddingcombined,plant- tousetheresultstomakepolicyrecommendations. availablenitrogentoanitrogen-limitedsea(Larssonetal.,2001). Theknowledgethatnitrogenandphosphoruscancausedifferent Addingplant-availablenitrogentothewaterwillnormallyin- eutrophicationeffects,bothintimeandspace,andthatthecitizens crease the growth of plankton other than cyanobacteria, thereby intheBalticSeacountriesmaydifferintheirexposureandreaction increasingwaterturbidityanddecreasinglightpenetration.Nitro- to these effects, could lead the states to prioritize different man- genadditionwillalsohinderthegrowthofbenthicvegetation,such agementoptions.Anyactiontoreducetheeutrophicationlevelwill assea-grassmeadows,throughshadingbytheturbidwater,andby causedistributionaleffectsonthehumanpopulation,bothwithin microalgalovergrowth,stimulatedbythenitrogen.Someofthenew and between countries. In general, the literature about distribu- organicmatterproducedwiththeaddednitrogenwillsinktothe tional impacts of implementing new management plans for bottom,whereitsdecompositionwillconsumeoxygenandincrease differentenvironmentalgoodsandservicesislimited.Thisisespe- areas of oxygen-deficient, “dead” bottoms (Elmgren, 1989). The cially true with regard to non-market priced benefits of environ- sediment of such bottoms has a reduced capacity for retaining mentalgoodsandservices,somethingthathasbeenhighlightedin phosphorus(Blomqvistetal.,2004),whichleaksoutintothewater, previousstudies(e.g.Håkanssonetal.,2012).Anumberofvaluation eventually increasing phosphorus concentrations in the surface studiesonenvironmentalgoodsandserviceshavebeencarriedout water.Butnitrogenadditionalsohaseffectsthatcanbeconsidered inmorethanonecountry,buttheyhavenotfocusedonthedistri- positive,sincetheextraproductioncreatesapotentialforhigherfish butionaleffectsbetweenthecountries(Batemanetal.,2011). production (though not only of species of interest to sport and Thisstudyisbasedondatafromalarge-scalecontingentvaluation commercialfisheries)andcounteractsthedevelopmentofcyano- (CV)surveyperformedinallnineBalticSeastatesinthefallof2011, bacterialblooms(Niemi,1979).Ingeneral,salmonidsareharmed reportedbyAhtiainenetal.(2014).Thepurposeofthestudywasto wheneutrophicationreducesoxygenlevelsinthedeep,coldcoastal quantifypublicwillingnesstopay(WTP)forreducingeutrophication waters,andasimilareffectisseenforcodintheopenBaltic,while intheBalticSeaaccordingtothetargetsoftheBSAP.Weuseprevi- cyprinidswithlittlecommercialvalueincreasewithnutrientlevels ouslyunutilizeddatafromthesurveytoassesspublicpreferencesfor (Hansson,1985).Additionofphosphorustoanitrogen-limitedsea eutrophicationmanagementandpossibledistributionaleffects. will,asitsprimaryeffect,stimulatethegrowthofnitrogen-fixing Our article is organized as follows: Section 2 provides an cyanobacteria, but some of the nitrogen they fix will leak from ecologicalbackgroundtotheeutrophicationeffectsandthethree theircells(Rolffetal.,2007;Plougetal.,2011),creatingindirectly nutrientloadreductiondimensionsdiscussedinthepaper,Section alsomanyoftheeffectsofdirectnitrogenaddition. 3presentsthesurvey,theWTPquestionandthestatisticalmethods Nitrogenandphosphorusdiffernotonlyintheirprimaryeffects, used,Section4describesanddiscussestheresults,andSection5 butalsointhetimeperspectiveforloadreductions.Thewaterin drawsconclusions. theBalticSeaexchangesonlyveryslowlywiththeseaoutside,on theorderof20e25yearsforwaterandevenlongerforbiologically 2. Ecologicalbackground retainednutrients.ThePloadcomestoaconsiderableextentfrom sewage,andiscurrentlybeingeffectivelyreducedbymoreefficient The two major nutrients that influence plant growth in the sewage treatment, and by banning high-P household detergent BalticSeaarenitrogen(N)andphosphorus(P).Phytoplanktonare formulations around the Baltic Sea. Phosphorus additions to the the dominant primary producers in the Baltic Sea and use Balticaremainlyeliminatedbysequestrationinthesediments.In theBalticProper,wheremuchofthesedimentisoxygen-deficient, thisisaninefficientsink,meaningthatPalreadyinthesystemis 1 We use the terms “cyanobacterial blooms” and “blue-green algal blooms” eliminated very slowly. Even if the load to the Baltic Sea can be synonymouslythroughoutthepaper. effectivelycurtailed,itmaythereforetakethesystemalongtime, H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 11 possibly many decades, to reach a new steady state with the willingnesstopay(WTP)questionusingthecontingentvaluation reducedPload(SavchukandWulff,2009). method. The fifth posed debriefing questions regarding response Nitrogen dynamics are very different, with quite efficient certainty and motivation for willingness to pay, including which removalofaddedcombined,plant-availableNthroughitsmicro- aspectsofeutrophicationtherespondentsconsideredwhenstating bialconversionbacktoN2gas,whicheachyearremovesNcorre- their WTP. The final section included questions on the socio- spondingtomostoftheload.Thistakesplaceinthesedimentsas economicbackgroundof therespondents.Inthisstudy,wefocus well as in oxygen-deficient deep waters, and becomes more on responses to questions on eutrophication effects, spatial con- effectivewhenoxygen-deficiencyiswide-spread.Ifmostinputof siderationsandwillingnesstopayanditsmotives. combinedNtotheBalticcouldbestopped,Nconcentrationswould Ecological modelling was used to generate the eutrophication fallrapidly.Theproblemisthatitisverydifficulttosubstantially scenariospresentedtotherespondents.Thescenarioswerebased reducetheNinput(Lo€fgrenetal.,1999). on simulations of the effects of reducing nutrient loads, using a SewageisonlyaminorNsource,butitistheeasiesttoreduce basin-scale dynamic marine model (Ahlvik et al., 2014) and two, andmeasureshavealreadybeentaken.ThemajoranthropogenicN spatiallymoredetailed,biogeochemicalmodelsoftheBalticSea,the sourceisagriculture,whereleakagecanbereduced,byimproved EIA-SYKE3DmodelaspresentedbyVirtanenetal.(1986);Koponen management and decreased use of fertilisers. Atmospheric depo- et al. (1992); Kiirikki et al. (2001, 2006); and the DMI-BSHcmod sition is also a considerable N source, whichhas been somewhat -EcologicalRegionalOceanModel(ERGOM)aspresentedbyMaar reducedinrecentyearswithfurtherreductionspossible,butonlyat etal.(2011);Neumann(2000);Neumannetal.(2002);Neumann greatcost.Finally,nitrogenfixationbycyanobacteriainthewaters andSchernewski(2008).Themodelssuggestedthatthefullbene- oftheBalticSeaisamajorsourcethatcanprobablyonlybereduced fits of investments in nutrient abatementwould only be realized byloweringtheavailabilityofPinBalticwaters.ThusPinputscan after40years,andthustheyear2050wasselectedasthebaseyear bereducedratherdrasticallyinafewyears,givensufficientpolit- for the valuation survey. The ecological models predicted water icalwill,butitwilltakealongtimefortheconcentrationsinthesea qualitydevelopmentintheBalticSeawithhighspatialdetail,butthe to fall. N inputs are more difficult to reduce markedly, but suc- predictions were aggregated to the basin level to ensure their cessful reduction would likely cause a rapid fall in the nutrient comprehensibilitytotherespondentsofthevaluationsurvey. concentrations. It is also good to note that the marginal costs of The presentation of eutrophication in the survey combined a nutrientabatementdifferforNandP,andarenotconstantperunit. verbaldescriptionwithvisualmaterials.Theeutrophicationstatus Rather, the abatement costs rise heavily after initial inexpensive wasshowntorespondentsincolour-codedmaps,whichdepicted stepshavebeentaken(seee.g.Ahlviketal.,2014). the eutrophication level in each sea basin in 2050 (Fig. 1). The Considering the spatial dimension, many coastal areas of the coloursandtheirassociatedlevelofeutrophicationwereverbally BalticSeaareP-limitedeveniftheseaoutsideisN-limited,dueto describedbeforepresentingthemapsandtheWTPquestion.Inthe large local inputs of nitrogen, either from rivers or from major verbaldescription,waterqualitywasdividedintofivecolour-coded sewagetreatmentplants.Insuchareastherecanbeaquick,very levels,eachdescribedintermsoffiveeutrophicationeffects:water localizedreductionofeutrophicationthroughPinputreduction,as clarity,blue-greenalgalblooms,underwatermeadows,fishspecies showninthe1970'sintheStockholmArchipelago(Brattberg,1986), andoxygenconditionsindeepseabottoms(seeAppendixA). but at the price of greater export of nitrogen to outer, nitrogen- In the WTP elicitation stage the respondents were presented limited areas, and thus a larger area affected by eutrophication, two future scenarios: the baseline (no additional measures to albeitofalessintensivenature.Whennitrogenremovalisadded,a reduce eutrophication) and the policy scenario (eutrophication furtherreductionofeutrophicationcanbeachievedwithinayear reductioncorrespondingtotheBalticSeaActionPlantargets),and orso(SavageandElmgren,2004). askedtostatetheirwillingnesstopayforobtainingtheimproved stateoftheseainsteadofthebaselinebyyear2050. 3. Dataandmethods 3.1. Survey 3.2. Willingnesstopayquestion Thedataforthisstudycomefromanenvironmentalcontingent The willingness to pay was elicited in two steps: first the re- valuationstudy2thatwasimplementedinthefall2011inallBaltic spondentswereaskedwhethertheywouldinprinciplebewilling Sea coastal states using identical questionnaires. The survey to pay for reducing eutrophication in the Baltic Sea (this type of developmentfollowedthetailoreddesignmethod(Dillmanetal., questionisreferredtoasaspikeorin-the-marketquestion).Ifthe 2009) with extensive pre-testing of the survey instrument. The answerwasyesordon'tknow,thentherespondentwaspresented surveyswereexecutedusingInternetpanelsinDenmark,Estonia, with the maps comparing the policy scenario with the baseline Finland, Germany and Sweden, and face-to-face interviews in scenario,togetherwiththeWTPquestion. Latvia,LithuaniaandRussia.InPoland,bothface-to-faceinterviews The elicitation format was a payment card, constructed using andanInternetpanelwereused.Face-to-faceinterviewswereused theapproachoutlinedinRoweetal.(1996).Thepaymentcardwas in countries where it was evident that Internet panels could not a4x5matrix,3with18positivebids,azerobidandtheoptionto providearepresentativesampleofthepopulation. choosedon'tknow.Monetaryamountspresentedonthecardwere Thequestionnaireconsistedofsixsections.Thefirstdescribed country-specific, chosenbased onthe results of the pilot studies. theBalticSea,thesecondposedquestionsaboutleisuretimespent The WTP questionwas formulatedas follows: “What isthe most atthesea,andthethirdprovidedadescriptionof,andquestions youwouldbewillingtopayeveryyeartoreduceeutrophicationin regarding,eutrophication.Forexample,therespondentswereasked the Baltic Sea as shown in the maps? Please consider your towhichextenttheyviewedvariousaspectsofeutrophicationas disposableincomecarefullybeforeansweringthequestion.” problems.Thefourthsectionpresentedthevaluationscenarioand Thepaymentwassaidtobecollectedasanearmarkedspecial Baltic Sea tax from each individual and firm in all Baltic Sea 2 ThefullversionofthequestionnaireinEnglishispresentedinAhtiainenetal. (2012). 3 TheRussianpaymentcardwasa4x4matrixduetotechnicalissues. 12 H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 Fig.1. Mapsofthebaselinescenario(leftmap)versustheBSAPscenario(rightmap)in2050aspresentedinthesurvey. countries. Previous study results indicated that ear-marked pay- areasversuscoastalareas,wastestedforgeneraldifferencesacross mentswere,ingeneral,preferredbythecitizensofthenineBaltic the countries using the non-parametric KruskaleWallis test Sea countries in funding actions concerning the sea (So€derqvist (KruskalandWallis,1952)thatrelaxesnormalityassumptions.As et al., 2010), and the tax was deemed both credible and accept- the KruskaleWallis test only identifies that there is a difference, able based on pre-testing using focus groups and in-depth in- ratherthanwherethedifferenceslie,weusedtheSiegel-Castellan terviews. The respondentswere alsoasked tonote thate if they post-hoc analysis (Siegel and Castellan, 1988) to further analyze agreedtopayetheywouldhavetopayeveryyearforaninfinite whichcountriesgavesimilarresponses. periodandthiswouldthereforeleavelessmoneytospendonother Binarylogitregressionandordinaryleastsquares(OLS)regres- things.Further,therespondentswereremindedthattheproposed sionmodelswereestimatedtomodelthedeterminantsofwilling- actionswouldaffectonlyeutrophicationandthattheycouldhave ness to pay (Greene, 2007). The binary logit model was used to substitutesforBalticSearecreation(seee.g.Batemanetal.,2002). explain the probability of being willing to pay, while the OLS regressionanalyzedthefactorsthatinfluencethesizeoftheWTP. Theanalysiswassplitintotwomodelsasitislikelythatthedata 3.3. Statisticalanalysis generatingprocessforzerosinthepopulationisdifferentforthetwo choicesethefactorsthatexplaintheprobabilityofbeingwillingto Statisticalanalyseswereusedtotestforsignificantdifferences paymayhavedifferenteffectswhenexplainingthesizeoftheWTP. inrespondentperceptionsofeutrophicationeffectsandthespatial extentofthepublic'sconcern,andtoanalysethedeterminantsof 4. Results willingnesstopay. Perceptions of eutrophication effects were analysed based on 4.1. Descriptivestatistics responses to a survey item measuring how problematic the differenteffectswereconsidered,givenonafive-pointLikertscale from “not at all a problem” to “a very big problem”. To test for Intotal,10564interviewswereconductedintheninecountries. differencesinrespondents'perceptionswithincountries,weused The smallest country-specific sample was 505 (Estonia) and the largest2029(Poland).AsshowninTable1,theresponseratewas the Friedman test (Friedman, 1937, 1940), followed by separate generally lower (lowest in Germany, 32%) in countries where an WilcoxonSigned-RanktestswiththeBonferronicorrectionforeach internet survey was used, rather than face-to-face interviews pairwisecombinationofeffectsasthepost-hocanalysis(Conover, (highestinRussia,69%). 1971,1980). The Friedman test is the non-parametric alternative Table 1 also presents selected socio-demographic data for the to the repeated-measures analysis of variance, and it is used to sample:meanage,percentageofwomenamongtherespondents, detect differences between treatments (in this case, different ef- mean household size, mean monthly net income and the per- fectsofeutrophication)whenthedependentvariableisordinal. Weusedthenon-parametricCochran'sQtestforrelatedsam- centageofrespondentswhohaveahighlevelofeducation. The samples collected in each countryexhibited similarprop- ples(Conover,1999;Sheskin,2004)totestfordifferencesinwhich erties in terms of representativeness. Generally, respondents had effects of eutrophication were considered when answering the WTPquestionwithincountries.Cochran'sQprovidesamethodof largerhouseholds,lowerincomeandhighereducationlevelsthan therelevantnationalpopulation.Theresultsarebasedonthetotal testingfordifferencesbetweenthreeofmorematchedsetsoffre- quencieswhenresponsesarebinary(0/1).McNemar'stestwiththe sample for all countries, i.e. protest responses4 or other suchlike werenotremoved. Bonferronicorrectionwasusedinthepost-hocanalysistotestthe differencesbetweenpairedfrequencies(McNemar1947). To examine the spatial extent of respondents' concern e the wholeseaoraspecificpartoftheseaeweusedpairwisePearson's 4 Protestresponsesrefertothesituationwhererespondentsdonotreportatrue c2-tests to analyse if responses between the nine countries were valueforthegoodinquestion.Theytypicallyappearasprotestzeros,whenpeople whoactuallyvaluetheenvironmentalgoodstatethattheyarenotwillingtopayfor statisticallydifferent.TheotherspatialaspectofWTP,i.e.open-sea it.Thereisnogeneralagreementonhowtotreatprotests(Jorgensenetal.,1999). H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 13 Table1 Socio-demographicdataforthesurveysamplesbycountry.Correspondingfiguresforthepopulationinparenthesiswhereapplicable. Country Samplesize Responserate(%) Meanage Gender(%female) Householdsize Highereducation(%) Meanmonthlynetincome(in2011V)a Denmark 1061 38.2 50(46) 43(50) 2.2(2.1) 48(25) 2275(2385) Estonia 505 42.1 38(44) 50(53) 2.9(2.2) 55(31) 583(542) Finland 1645 39.4 51(45) 49(51) 2.3(2.1) 32(29) 1890(2031) Germany 1495 32.5 42(43) 50(51) 2.5(2.1) 39(25) 1641(1827) Latvia 701 45.0 44(45) 55(53) 2.8(2.5) 25(23) 311(428) Lithuania 617 60.5 43(42) 49(54) 2.8(2.5) 22(24) 205(387) Poland 2029 n/a(36)b 39(39) 50(51) 3.3(2.6) 32(18) 495(492) Russia 1508 69.3 44(39) 55(54) 3.0(2.6) 44(23) 338(462) Sweden 1003 34.0 54(41) 54(50) 2.2(2.0) 50(33) 1858(2024) Sourcesofpopulationstatistics:StatisticsDenmark2011,StatisticsEstonia2011,StatisticsFinland2010,StatistischesBundesamt2010(Germany),PopulationCensus2011 (Latvia),StatisticsLithuania2011,PolishCentralStatisticalOffice2010,Rosstat2010(Russia),StatisticsSweden2010. a n/aforface-to-faceinterviews,36%forinternetpanel. b Sourceofpopulationincome:Eurostat2013a,exceptRussia:Rosstat2010. 4.2. Motivesforwillingnesstopay differenteffectsofeutrophicationineachcountry(seeAppendixB). Pairwisecomparisonsinthepost-hocanalysisindicatedthatwater Thesharesofrespondentswhowerewillingtopayforreducing turbiditywasconsideredlessproblematicthantheothereffectsin eutrophicationareshowninTable2.Thedifferingsharesbetween allcountries.Inaddition,lackofoxygenandchangeinfishspecies countries could reflect, for example, the differences in income composition were typically seen as more problematic than the levels and geographical factors. Smallest proportions of re- other effects, especially in Germany, Latvia, Lithuania, Russia and spondentswillingtopaywerefoundinRussia,LatviaandLithuania, Sweden. In Finland, blue-green algal blooms and lack of oxygen i.e.incountrieswhichalsohadthelowestmeanincomeaccording wereconsideredmostproblematic. toTable1.Theproportionofrespondentswillingtopaywaslargest Thelowerimportanceofwaterturbiditycomparedtotheother in Sweden and Finland, both high-income countries with long effectsissomewhatsurprising,asitisoneofthemostvisibleeffects coastlines. It is worth noting that altogether, over half of the re- ofeutrophication.Sightdepth(Secchidepth,Preisendorfer,1986) spondents were willing to pay something for reducing eutrophi- orwaterturbidity hasbeen used asa eutrophication indicatorin cationintheBalticSea. severalpreviousvaluationstudiesintheBalticSeaarea(e.g.Atkins Thoserespondentswhowerewillingtocontributetothepro- andBurdon,2006;Sandstro€m,1996;Soutukorva,2001;So€derqvist tectionoftheBalticSeawererequestedtostatetheirmainmotive and Scharin, 2000), as it is easy to measureand communicate to forbeingwillingtopay(Table3).5Interestingly,almostathirdof people.However,althoughincreasedwaterturbidityisanuisance, the respondents stated that the main reasonwas that “The exis- itdoesnotpreventrecreation. tence of healthy marine ecosystems and plants and animals is In summary, all effects of eutrophication were not deemed important”.Anotherthirdchosetheresponseoption“Futuregen- equallyproblematic,butthedifferencesbetweentheeffectswere erationswillbeabletoenjoythewaterqualityimprovements”.This inmostcasessmall.Inaddition,themostimportanteffectvaried isastrongindicatorofnon-use(orpassiveuse)values,whichare betweencountries(seeAppendixBforcountry-wiseresults).Fig.2 not directly related to the individual's own use of the Baltic Sea. shows the perceptions of the respondents in total (all countries Further,fromatemporalperspective,thisalsoindicatesthatpeople summed).Theaggregate results alsosuggestthatwaterturbidity arewillingtocontributetoinvestmentsthathaveaneffectinthe was seen as less problematic and fish species change and lackof longrun,notonlytomeasuresthatimprovethestateoftheseain oxygen as somewhat more problematic than blue-green algal thenearfuture. bloomsandunderwatermeadowloss. After the WTP question, the respondents were asked which effects of eutrophication (one or many) they had in mind when 4.3. Perceptionsofeutrophicationeffects answeringhowmuchtheywerewillingtopay.Thisquestionwas, inotherwords,onlyaddressedtothosewhowerewillingtopay. Perceptions of eutrophication effects were analysed based on AccordingtotheCochran'sQtestresults,therewasanoverall responsestosurveyitemsmeasuringhowproblematicthedifferent statisticallysignificantdifferenceinconsideringtheeutrophication effectswereseen6andwhichofthemtherespondentconsideredin effects in each country (see Appendix C). In general, blue-green answering the WTP question.7 Respondents were first given a algalblooms werechosenoften andunderwater meadows rarely descriptionofthefiveeffects,i.e.waterturbidity,blue-greenalgal in all countries. Pairwise comparisons with the McNemar test blooms, underwater meadows loss, fish species composition indicated that countries also differed with respect to the eutro- change and lack of oxygen in deep sea bottoms, and then asked phication effects that were considered.8 Cyanobacterial blooms whethertheyconsideredthemproblematic.Responsesweregiven seemedmostimportantinFinlandandPoland,waterturbidityin onafive-pointLikertscalefrom“notatallaproblem”to“averybig LithuaniaandRussia,lackofoxygeninDenmarkandfishspeciesin problem”. Sweden.InLatviaandEstonia,respondentsrankedseveraleffects AccordingtotheFriedmantest,therewasastatisticallysignif- ofeutrophicationasaboutequallyimportant.Asgeneralpatterns icantdifferenceinhowproblematictherespondentsperceivedthe commontoallcountriescouldnotbefound,theresultssuggestthat alleffectsofeutrophicationareimportantontheBaltic-widelevel (seeAppendixC).Ontheaggregatelevel,theresultsshowedthat 5 Thequestionread:“Whatwasthemostimportantreasonforyoutobewilling blue-greenalgalbloomsandfishspeciescompositionchangewere topayforreducingeutrophicationintheBalticSea?” 6 Respondentswereaskedthefollowing:“Towhatextentdoyoupersonallyview thefollowingeffectsofeutrophicationintheBalticSeaasproblemsornot?” 7 Respondentswereaskedthefollowing:“Whichoftheeffectsofeutrophication didyouhaveinmindwhenansweringhowmuchyouwerewillingtopay?” 8 McNemartestresultsareavailablefromtheauthorsonrequest. 14 H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 Table2 Sharesofrespondentswillingtopaypercountry. Country Sharewillingto N payforBSAP(%) Denmark 55 1061 Estonia 58 505 Finland 63 1645 Germany 56 1495 Latvia 50 701 Lithuania 55 617 Poland 56 2029 Russia 32 1508 Sweden 75 1003 Overallaverage 55 10564 Table3 Mostimportantreasonsforbeingwillingtopay. Responseoption Frequency Shareof respondents(%) IhaveusedtheBalticSeafornature 460 8 experiencesandrecreation IplantousetheBalticSeafornature 567 10 experiencesandrecreationinthefuture Theexistenceofhealthymarineecosystems 1800 31 andplantsandanimalsisimportant Otherpeopleinmygenerationareableto 211 4 enjoythewaterqualityimprovements Futuregenerationswillbeabletoenjoy 1682 29 thewaterqualityimprovements Youcandoalotforenvironmental 914 16 Fig. 2. Percentage shares of respondents' perceptions of the eutrophication effects protectionwithasmallcontribution (country-wiseresultsavailableinAppendixB). Otherreason 220 4 Don'tknowa 11 0 Sum 5865 100.00 debriefingquestionswerepresentedaftertheWTPquestion.The a Thedon'tknowoptionwasonlyavailableintheDanishquestionnaire. firstquestionexaminedwhethertherespondentshadconsidered thewholeBalticSeaorsomespecificareaoftheBalticSea,9andthe secondtowhatextenttheyhadconsideredopen-seaversuscoastal chosen most often (Table 4). However, as previously noted, the areaswhenstatingtheirWTP10. country-wisedifferenceswerequitelarge. InthequestiononthespatialextentoftheWTPacrossthesea Itissomewhatsurprisingthattheeutrophicationeffectsseenas basins,morethanonehalfoftherespondentswhowerewillingto mostproblematicdidnot,insomecases,correspondwiththeef- payhadconsideredthewholeBalticSeawhenstatingtheirWTP. fectstherespondentstookintoconsiderationintheWTPquestion. However, Pearson's c2-test showed statistically significant differ- Cyanobacterialbloomswerechosenmostoftenbuttheywerenot encesbetweencountries.Fig.3presentstheshareofrespondents seenasthemostproblematic,whilelackofoxygenwasnottaken beingwillingtopayforreducedeutrophicationinthewholeBaltic intoconsiderationwhenstatingtheWTPasoftenalthoughitwas Sea(insteadofsomespecificareaoftheBalticSea).Thelinesabove seenasoneofthemostproblematiceffects.Aquestionthusrisesif the bars imply non-significant (p-value of difference >10%) test thisresultisduetodifferingsamples(allrespondentsversusonly results for difference between the countries. Sweden alone was those who are willing to pay). However, the previous findings of differentfromallcountrieswiththehighestproportionofpeople howproblematictherespondentsperceivedthedifferenteffectsof willingtopayforthewholesea,followedbyGermans,Danes,Finns eutrophicationineachcountryholdevenifweconsideronlythose andLithuanianswhoexpressedstatisticallysimilarpreferences.A who were willing to pay. A possible explanation for the dissimi- likely explanation of why Swedes were the most interested in laritiescouldbethedifferentcontextofthesurveyquestions:re- improvingtheconditionoftheentireBalticSeaisthatSwedenhas spondents could have interpreted the first question (how thelongestcoastline,extendingfromtheBothnianBayinthenorth problematictheeffectsare)asbeingonagenerallevel,whilethe toKattegatinthesouth. responses to the second question (which effects the respondent Inturn,Latvians,Russians,PolesandEstoniansweremoreoften had in mind) in the WTP elicitation stage could be based on the willingtopayforanimprovementinaspecificareaoftheBalticSea moretangibleeffects. thanrespondentsinothercountries.ItisunsurprisingthatRussians and Latvians preferred their contributions to go more towards specific areas, as these two countries are adjacent to the most 4.4. Spatialconsiderations Inthesurvey,therespondentswereaskedtostatetheirWTPfor thewholeBalticSeaforachangeinopen-seaconditions.However, 9 Thequestionread:”DidyouconsiderthewholeBalticSeaoracertainareaof weunderstoodthatrespondentsmightplacegreateremphasison the Baltic Sea when answering how much you were willing to pay?”. The re- somesub-regionsoftheBalticSea,andalsotakecoastalareasinto spondentswhodidnotconsidertheentireseawerethenaskedtospecify:“Which area(s)oftheBalticSeadidyouhaveinmindwhenansweringhowmuchyouwere considerationintheirWTPresponse.TheBalticSeacoversalarge willingtopay?Youmaychooseoneorseveralareas.” geographicalareaandpeoplemaycaremoreabouttheirimmediate 10 Respondentswereaskedthefollowing:“Towhatextentdidyouconsideropen surroundings than areas further away. To examine these issues, seaandcoastalareaswhenansweringhowmuchyouwerewillingtopay?” H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 15 Table4 Sharesofrespondentsconsideringtheparticulareffectsofeutrophication(country- wiseresultsinAppendixC). Eutrophicationeffect Percentage(%) Waterturbidity(n¼6148) 54 Cyanobacterialblooms(n¼6128) 68 Lossofunderwatermeadows(n¼5944) 40 Fishspeciescompositionchange(n¼6031) 59 Lackofoxygenindeepseabottomareas(n¼5913) 51 Fig.4. Emphasisofopen-seaversuscoastalareas,meanvalues. sizeoftheWTP(ordinaryleastsquaresregression).Thedescriptive statisticsforthevariablesincludedinthelogitandOLSmodelscan befoundinAppendixDTablesD1andD2. When respondents report their maximum willingness to pay using a payment card, the actual maximum WTP figure will lie somewherebetween the marked amountof moneyand the next largestsumofmoneyinthepaymentcard.Weassumedthatthe Fig.3. Sharesofrespondentsbeingwillingtopayforreducedeutrophicationinthe mid-point of the interval represents the WTP (e.g. Håkansson, wholeBalticSea. 2008).12 Inthelogitmodel,weincludedthesocio-demographicvariables eutrophiedwaterswithrelativelyshortcoastlines.Yet,themajority presentedinTable1,andbinaryvariablesindicatingwhetherthe oftherespondentsdirectedtheirWTPtowardsthewholeBalticSea respondentstatedthedifferenteutrophicationeffectstobeprob- showingthatimprovingthestateoftheentireseaareaisimportant lematic or not.13 In the OLS model, we included the socio- andthatlargenon-usevaluesarelikelytobeattributedtothesea. demographic variables as well as binary variables indicating Thesecondquestiononopen-seaversuscoastalareaswaspre- which eutrophication effects the respondents had in mind when sentedonascalefrom1(open-seaareasonly)to7(coastalareas only).11Theresultsshowedthat,onaverage,respondentsthought statingtheirWTP.Further,weaddedonenewvariableintheesti- mation,namelyWTPforthewholeBalticSea.Thevariablerepresents slightlymoreaboutthecoastalareasthanopen-seaareas,withthe exception of Lithuanian respondents. The KruskaleWallis test awillingnesstopayforthewholeBalticSeainsteadofspecificsub- indicatedthatresponsesacrosscountriesdifferedsignificantly,even basinsandwasdescribedindepthintheprevioussection. Table 5 presents the logit model results, showing that those thoughtheabsolutedifferencesintheaverageresponsesweresmall asshowninFig.4.Post-hocKruskaleWallistestsfoundgroupingsof respondentsinDenmark,Finland,andLatviawhoconsideredcya- nobacterial blooms as problematic in the Baltic Sea were more similarcountries.BarsinFig.4indicatep-valueofdifferenceless likelytobewillingtopay.Ontheotherhand,consideringunder- than 10%. There is no intuitive reason for the country groupings, water meadows as problematic raised the probability of being however.Germany,PolandandDenmarkborderthesouthernBaltic willing to pay in Germany, Poland and Russia. Those finding fish Sea,wherethewatersarewarmerforalongerperiodinthesummer, communitycompositionchangeasaproblemweremorelikelyto thus providing better water recreation opportunities than in the be willing to pay in Denmark and Sweden. A respondent who north,whichcouldleadtoalargershareofusevaluesattributedto considered a lackof oxygen in the deep sea bottomstobe prob- theseaintheseareas.Ontheotherhand,Lithuaniaisalsointhe lematicwasmorelikelytobewillingtopayinFinland,Germany south,whichdoesnotsupportthisreasoning. CombiningthefindingsofFigs.3 and4,itseems that Swedes andSweden.Asurprisingresultwasthatthoseconsideringwater turbidityimportantwerenotmorelikelytobewillingtopayinany thought more often of the entire Baltic Sea and open sea areas, country.Ingeneral,concernforoneortwoeffectsofeutrophication while Latvians were at the opposite end with more emphasis on somespecificpartsoftheBalticSeaandcoastalareas.Thesetwo influencedtheprobabilityofbeingwillingtopayinonecountry.In addition,theeffectsthatinfluencedtheprobabilityvariedbetween countriesdifferbothwithrespecttoincomelevelsandgeograph- countries. icallocationandscope,whichmayexplainthesedifferences. Table6presentstheresultsfromtheOLSmodelexplainingthe sizeoftheWTP.ThoserespondentswhoreportedapositiveWTP 4.5. WTPfunctions were requested to state the eutrophication effects (one or more) they had in mind when answering. For this sub-population, it is To gain additional insights into perceptions of eutrophication, we examined whether the different eutrophication effects influ- encedtheprobabilityofbeingwillingtopay(logitmodel)andthe 12 ThewillingnesstopayfigureswereadjustedtoEurosusingpurchasingpower parity(PPP)conversionrates,basedonPPPdatafromEurostatandOECD(Russia). 13 Thedummywasgiventhevalue1iftherespondenthadstatedthatthespecific 11 ExceptforDenmarkwhereascaleof1e10wasused.Thatscalehasbeenre- eutrophication effect was a ’rather big problem’ or a ’very big problem’, and scaledto1e7tobecomparablewithothercountries. 0otherwise. 16 H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 Table5 Theresultsofthelogitmodels,coefficientestimatesandstandarderrors. Dependentvariable:Probabilityofbeingwillingtopay Variable Denmark Estonia Finland Germany Latvia Lithuania Poland Russia Sweden Waterturbidityproblematic,binary 0.019 (cid:2)0.302 0.181 (cid:2)0.212 0.254 0.395 (cid:2)0.04 (cid:2)0.097 (cid:2)0.056 0.171 0.234 0.133 0.138 0.197 0.253 0.147 0.172 0.177 Blue-greenalgalbloomsproblematic,binary 0.423* 0.332 0.401** 0.192 0.411* (cid:2)0.201 0.166 0.151 (cid:2)0.056 0.24 0.293 0.158 0.195 0.223 0.247 0.182 0.179 0.311 Underwatermeadowslossproblematic,binary 0.137 0.268 0.166 0.532*** 0.279 0.262 0.599*** 0.326* 0.112 0.246 0.287 0.152 0.185 0.219 0.3 0.17 0.198 0.253 Fishspeciescompositionproblematic,binary 0.535** 0.315 (cid:2)0.012 0.045 0.052 0.484 0.073 (cid:2)0.125 0.803** 0.228 0.333 0.156 0.186 0.245 0.337 0.178 0.221 0.316 Lackofoxygenproblematic,binary 0.363 0.132 0.417** 0.788*** (cid:2)0.042 0.196 (cid:2)0.048 0.284 0.815** 0.285 0.344 0.166 0.258 0.248 0.37 0.197 0.219 0.349 Monthlyincome,1000(EUR2011),continuous 0.081 0.262 0.105* 0.022 1.861*** 2.757*** 1.382*** 1.139*** 0.204* 0.073 0.269 0.061 0.071 0.448 0.941 0.204 0.365 0.119 Age,continuous (cid:2)0.002 (cid:2)0.019** (cid:2)0.003 (cid:2)0.009** (cid:2)0.006 (cid:2)0.020*** (cid:2)0.006 (cid:2)0.006* 0.001 0.005 0.008 0.004 0.004 0.005 0.007 0.005 0.004 0.005 Female,binary 0.094 0.106 0.352*** 0.106 (cid:2)0.03 0.068 0.274** 0.193 0.276* 0.149 0.213 0.111 0.13 0.166 0.189 0.115 0.121 0.158 Sizeofhousehold,continuous 0.039 0.08 (cid:2)0.099** (cid:2)0.016 0.004 0.059 0.014 (cid:2)0.019 0.076 0.069 0.085 0.045 0.05 0.069 0.087 0.043 0.05 0.076 Universityeducation,binary 0.051 0.232 0.553*** 0.620*** (cid:2)0.001 0.288 0.601*** 0.108 0.191 0.148 0.21 0.124 0.133 0.21 0.241 0.13 0.121 0.154 Constant (cid:2)1.120*** (cid:2)0.149 (cid:2)0.37 (cid:2)0.808*** (cid:2)0.806** (cid:2)0.479 (cid:2)1.058*** (cid:2)1.328*** (cid:2)1.204** 0.408 0.521 0.271 0.311 0.408 0.535 0.3 .311 0.472 N 918 439 1645 1176 647 522 1484 1403 985 PseudoR2 0.057 0.033 0.054 0.048 0.054 0.083 0.075 0.021 0.045 Loglikelihood (cid:2)594 (cid:2)289 (cid:2)1025 (cid:2)763 (cid:2)424 (cid:2)328 (cid:2)939 (cid:2)860 (cid:2)534 AkaikeInformationCriteria 1211 601 2072 1549 870 678 1901 1742 1090 Statisticalsignificance,p-values:*<10%,**<5%,***<1%. interesting to examine whether the same eutrophication effects thesizeoftheWTPissomewhataffectedbymultipleeutrophica- thataffectedthetendencytobewillingtopayalsoexplainedthe tion effects and that their relative importance for the size of the size of the WTP. The OLS models on the size of the WTP have a WTPvariesamongcountries. relativelypoorfit,astheadjustedR2figuresrangefrom0.026inthe Respondents thinking about fish species composition change German model to0.22 in the Russian model. Thus, the eutrophi- had statistically significantly higher WTP in Denmark, Estonia, cationeffectsgenerallyhavequitesmallexplanatorypowerforthe Finland and Lithuania. Perhaps surprisingly, water turbidity had sizeofthewillingnesstopay.However,theresultsdosuggestthat mostlynostatisticallysignificanteffectontheWTP,exceptinLatvia Table6 TheresultsoftheOLSmodeldepictingthesizeofWTP,coefficientvalueandstandarderror. Dependentvariable:midpointoftheWTPinterval Variable Denmark Estonia Finland Germany Latvia Lithuania Poland Russia Sweden WaterturbidityareasonforWTP, (cid:2)0.015 0.198 0.085 (cid:2)0.015 0.317** (cid:2)0.106 (cid:2)0.031 (cid:2)0.700* (cid:2)0.128 binary 0.119 0.154 0.065 0.079 0.147 0.163 0.075 0.391 0.088 Blue-greenalgalbloomsareasonforWTP, 0.154 (cid:2)0.121 0.101 (cid:2)0.082 0.369** (cid:2)0.141 0.138* 1.297*** (cid:2)0.090 binary 0.117 0.175 0.073 0.081 0.152 0.158 0.081 0.373 0.088 Underwatermeadowslossareasonfor (cid:2)0.036 (cid:2)0.036 0.128 0.229*** 0.178 (cid:2)0.252 0.203** 0.086 0.125 WTP,binary 0.130 0.173 0.082 0.084 0.231 0.179 0.092 0.397 0.098 FishspeciescompositionareasonforWTP, 0.391*** 0.405** 0.204*** 0.028 (cid:2)0.028 0.357** 0.100 0.629 0.062 binary 0.116 0.166 0.067 0.080 0.160 0.175 0.078 0.388 0.088 LackofoxygenareasonforWTP,binary 0.209* 0.102 0.096 0.023 0.035 0.088 0.023 (cid:2)0.736** 0.309*** 0.121 0.169 0.067 0.082 0.206 0.168 0.090 0.373 0.087 WTPforwholeBalticSea,binary 0.240** (cid:2)0.266* 0.056 0.091 0.388*** (cid:2)0.023 (cid:2)0.018 0.380 (cid:2)0.020 0.113 0.145 0.069 0.088 0.137 0.150 0.076 0.245 0.099 Monthlyincome,1000(EUR2011), 0.212*** 0.441*** 0.250*** 0.074* 0.493 1.152* 0.314*** 1.700** 0.275*** continuous 0.055 0.165 0.036 0.043 0.358 0.629 0.101 0.722 0.060 Age,continuous 0.008** 0.011* (cid:2)0.003 0.006** (cid:2)0.010** (cid:2)0.020*** 0.007* (cid:2)0.016** 0.001 0.004 0.006 0.002 0.003 0.004 0.005 0.003 0.007 0.003 Female,binary (cid:2)0.066 (cid:2)0.095 (cid:2)0.065 (cid:2)0.017 (cid:2)0.112 0.054 (cid:2)0.115 (cid:2)0.282 (cid:2)0.413*** 0.108 0.150 0.065 0.077 0.136 0.129 0.075 0.234 0.078 Sizeofhousehold,continuous 0.057 (cid:2)0.01 (cid:2)0.004 0.013 0.081 0.015 (cid:2)0.010 0.082 0.018 0.049 0.061 0.027 0.030 0.054 0.057 0.029 0.113 0.038 Universityeducation,binary 0.049 (cid:2)0.173 0.157** 0.101 0.077 0.001 0.293*** 0.621** 0.201*** 0.110 0.146 0.068 0.079 0.166 0.148 0.077 0.240 0.077 Constant 2.301*** 2.158*** 3.248*** 2.837*** 0.761** 2.434*** 1.510*** 1.030 3.770*** 0.322 0.392 0.176 0.184 0.352 0.355 0.201 0.678 0.250 N 496 250 1023 693 312 266 826 155 724 AdjustedR2 0.086 0.065 0.098 0.026 0.098 0.081 0.060 0.225 0.120 Loglikelihood (cid:2)753 (cid:2)370 (cid:2)1420 (cid:2)953 (cid:2)485 (cid:2)377 (cid:2)1172 (cid:2)265 (cid:2)1023 AkaikeInformationCriteria 1529 763 2864 1930 995 778 2368 553 2070 Statisticalsignificance.p-values:*<10%.**<5%.***<1%. H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 17 where the effect was significantly positive and Russia where the thevalueassociatedwiththeBalticSeaisfurthersupportedbythe effect was weakly negative. In the latter two countries, however, respondentsconsideringthecoastalenvironmentandtheopensea respondents considering cyanobacterial blooms were willing to approximatelyequallywhenrespondingtothewillingnesstopay contribute significantly more than respondents thinking of other question,andthatthemotivesforbeingwillingtopayaremainly eutrophicationissues.Inothercountries,blue-greenalgalblooms related to the existence of a healthy marine ecosystem and the hadnosignificanteffect.Respondentsthinkingaboutunderwater opportunitiesoffuturegenerationstoenjoythesea. meadowshadsignificantlyhigherWTPthanothersinGermanyand Thesefindingshavebearingsonpolicy.Forexample,thereare Poland. Finally,concern aboutthelackofoxygenin the deepsea potential goal conflicts between the Water Framework Directive bottomshadasignificantandincreasingeffectonWTPinDenmark (WFD)dwithwaterqualitytargetsforcoastalareas–andtheMSFD andSwedenandanegativeeffectinRussia. ewithwaterqualitytargetsfortheopensea.Ourfindingssuggest Itisnotstraightforwardtocomparetheseresultstotheresults thatthecitizensintheBalticSealittoralcountriesvalueimprove- from other valuation studies of eutrophication effects from the mentsincoastalareasandtheopenseaaboutequally.Thismeans BalticSearegion.Thereasonisthatthedefinitionsofwaterquality thatmeasuresthatimprovethecoastalenvironmentatthecostof andeutrophicationeffectsdiffersubstantiallybetweenstudies.For thatoftheopensea,orviceversa,needcarefulevaluationtoensure example,EggertandOlsson(2009)definedwaterqualityinterms that they actually improve societal well-being. The arguments ofdaysperyearwherethebathingwaterqualityfailstomeetEU made by Schindler (2012), that policy should focus mainly on standards.InO€stbergetal.(2012)thewaterqualityattributewas eliminating cyanobacterial blooms, do not match the public's holistic,includingvegetation,waterclarityandalgalmatcoverage. preferences. Since both nitrogen and phosphorus reductions are Also, most studies have presented no results on how the re- required to achieve improvements in all our five investigated spondents rank different eutrophication effects (e.g. Atkins and eutrophication effects, both nitrogen and phosphorus reductions Burdon, 2006; Bateman et al., 2011). An exception to this is arerequiredtofulfilthepublic'spreferences. Kosenius (2010), who estimated Finns' willingness to pay for Moreover, that most of the respondents tend to care for the different attributes of eutrophication reduction in the Gulf of wholeBalticSeaimpliesthatthecitizensinthelittoralcountries Finland using the choice experiment method. The findings indi- canbeexpectedtobewillingtomakeamonetarycontributionnot cated that water clarity was most important, followed by blue- onlytofinancemeasuresintheirownpartofthesea,butalsoto green algal blooms, fish species composition and bladder wrack. finance measures in othercountries. Since a cost-efficient alloca- However,theseresultsapplyonlytotheFinnishpopulationanda tionofnutrientabatementmeasuresispoliticallydifficult,thisisa sub-regionof theBalticSea.TheonlypreviousBaltic-widestudy, promisingresult.Forexample,acapandtradesystemfornitrogen reportedine.g.So€derqvist(1996),Grenetal.(1997),Turneretal. has been on the agenda in recent years (e.g. Swedish EPA, 2009; (1999) and Markowska and Zylicz (1999), did not report results 2012). Such a system could reallocate nutrient reductions be- onthepublicpreferencesfordifferenteutrophicationeffects. tween countries. Had the respondents only cared for their own, localpartoftheBalticSea,onewouldexpectresistancetosucha 5. Discussionandconclusions policyinstrument.Importantly,suchasystemwouldneedtotake both the coastal and open sea environment into account, and This paper investigated public preferences for three policy- complywithboththeWFDandtheMSFD. relevantdimensionsofnutrientreductionsintheBalticSea:first, Concerningtime,oneaspectofourdataisimportant.Theim- nitrogenversusphosphorus;second,theroleoftime;andthird,the provements in our eutrophication reduction scenario would be spatialdimension. reachedfullyby2050eadistanttimehorizon.Infact,manyofthe Theresultsindicatethat,ingeneral,respondentscareaboutthe respondentsstatedthatoneofthereasonsforbeingwillingtopay Baltic Sea. For example, most respondents are willing to make a was that future generations should be able to enjoy the water monetary contribution to improve the Baltic Sea environment. quality improvement. This suggests that the respondents are Importantly, the respondents seem to appreciate the Baltic Sea willingtopaytofinancelong-termmeasures,notonlythosewith environment in a holistic way e that is: they tend to care about quickpay-off. eutrophicationingeneralinsteadoffocusingonaparticulareffect Betterunderstandingofpublicperceptionsandthebenefitsof ofeutrophication,andfindimprovementintheentireareaofthe nutrient load reductions can aid in forming international agree- Baltic Sea important rather than considering only their local mentsthatarebotheconomicallyefficientandequitable.Inaddi- environment. tion to the benefits, also the distribution of the costs between Ingeneral,alleffectsofeutrophicationarenotseenasequally countriesneedstobeconsideredtodesigncost-effectiveandfair problematic in all countries, and the effect of primary concern policies. differs among countries but the differences are mostly small. A Welfare maximization should be a factor when allocating similarresultisfoundconcerningwhicheutrophicationeffectthe limitedresourcesforcombatingmarineeutrophication,alongwith respondentsprimarilyconsideredwhenstatingtheirwillingnessto legal considerations, such as international agreements and the pay. There is an overall statistically significant difference among polluter-pays principle. This means that mitigation measures eutrophicationeffectsforallcountriessummed.However,asgen- should target those effects on ecosystem services that the public eralpatternscommontoallcountriescouldnotbefoundthere- valuesthemost.Ourresultsindicatethatthisrequirestakingthe sultssuggestthatalleffectsofeutrophicationareimportantonthe wholerangeofeutrophicationeffectsintoaccount,bothincoastal Baltic-widelevel.Finally,theWTPmodelsalsoshowsimilarresults andopenseaareas,andincludingalsomeasuresthatimprovethe ethemostinfluentialeutrophicationeffectfortheprobabilityof stateoftheseainthelongrun. being willing to pay and the size of the WTP differs among countries. Acknowledgements Anadditionalindicationthattherespondentsthinkholistically abouttheBalticSeaenvironmentisthatmorethanhalfofthere- Theauthorsaregratefulforthefundingandsupportprovided spondents willing to pay allocate their WTP-figure to the whole by the following projects/organizations: the research project BalticSearatherthantoaspecificarea.Thisalsosuggeststhatlarge PROBAPS,theresearchprojectManagingBalticnutrientsinrelation non-usevaluesareattributedtothesea.Thenon-usecomponentof to cyanobacterial blooms: what should we aim for? (Swedish 18 H.Ahtiainenetal./JournalofEnvironmentalManagement145(2014)9e23 Research Council for Environment, Agricultural Sciences and WewouldalsoliketothanktheBalticSTERNteamconsistingof Spatial Planning, contract 215-2009-813).; the research alliance researchersfromallthenineBalticSeastatesforjointworkindata IMAGE; The Baltic Nest Institute e Aarhus University, The Baltic- collectionandthewillingnesstosharethedata.ThanksalsotoTore STERN Secretariat at the Stockholm Resilience Centre, Stockholm So€derqvistandtwoanonymousreviewersforfruitfulcomments. University;theGermanFederalEnvironmentAgency;theSwedish Environmental Protection Agency (EPA), and PlusMinus. RE was AppendixA. Theeffectsofeutrophicationonwaterqualityin supported by Stockholm University's Strategic Marine Environ- openseaareasaspresentedinthesurvey mental Research Programme on Baltic Ecosystem Adaptive Management.

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a MTT Agrifood Research Finland, Latokartanonkaari 9, FIN-00790 Helsinki, Finland b Stockholm University, Dept of cyanobacteria, deterioration of underwater sea-grass meadows, changes in fish species .. larger households, lower income and higher education levels than the relevant national
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