Baltic Sea nutrient reductions

15 Pages·2014·1.56 MB·English

by  Heini Ahtiainen

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.