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SenseOCEAN:MarineSensorsforthe21stCentury

GrantAgreementNumber614141

Deliverablenumber D7.8Deliverablename PolicyDocument:Sensordevelopmentforthe

OceanofTomorrowDisseminationlevel PUDeliverableduedate September2017

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PolicyDocument-SensorDevelopmentfortheOceanofTomorrow(Jointprojectdeliverable)

Contributingauthors:COMMONSENSE

DeclanDunne,SergioMartínez

NeXOS

EricDelory,JoaquindelRio,SimonJirka,JayPearlman

SCHeMA

PaoloD’Angelo,AntonioNovellino,Mary-LouTercier-Waeber,MariaCuarteroBotia,EricBakker,SilviaZieger,IngoKlimant

SenseOCEAN

CaroleBarus,SergeyBorisov,JustinBuck,DougConnelly,LarsDamgaard,LouiseDarroch,VeroniqueGarcon,ThomasGardner,AlexandraKokkinaki,MattMowlem,RobinPascal,NielsPeterRevsbech,CarlaSands

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TableofContents

1.Introduction.......................................................................................................................................4

2.Stateoftheartdevelopments...........................................................................................................5

2.1.Optodesformarinemeasurements............................................................................................6

2.2.SpeciesrelevanttotheCarbonCycleSensingModule:CSM......................................................8

2.3.OpticalSensorO3–Carbonsensorsystem...............................................................................10

2.4.Labonchipchemicalsensors....................................................................................................13

2.5.TraceMetalSensingModule:TMSM........................................................................................15

2.6.NutrientsSensorsModule:NSM...............................................................................................17

2.7.ANESIS:AutonomousNutrientElectrochemicalSensorInSitu.................................................19

2.8.Electrochemicalmicrosensors...................................................................................................21

2.9.Multiparameteropticalsensor..................................................................................................23

2.10.OpticalSensorO1....................................................................................................................25

2.10.1.OpticalSensorO1Matrixflu-UVandMatrixflu-VIS..........................................................25

2.10.2.OpticalSensorO1Minifluo..............................................................................................26

2.11.Miniaturized,multi-channelAlgaeSensingModule:ASM......................................................28

2.12.OpticalSensorO2–Phytoplanktonidentificationsensor.......................................................30

2.13.AcousticSensors......................................................................................................................31

2.14.EAF-RECOPESCAsensorsystem...............................................................................................34

3.DataManagementandStandards....................................................................................................363.1.StandardsimplementedbytheOceanofTomorrowprojects..................................................38

3.1.1.StandardsimplementedbyOoTprojects...........................................................................38

3.1.2.Recommendationsonimplementedstandards.................................................................39

3.2.Emergingstandards...................................................................................................................40

3.2.1.RecommendationsonApplicablestandardsthatemergedduringtheOoTprojects........41

3.3.PrioritiesforfutureresearchidentifiedbytheOoTprojects....................................................42

3.4References..................................................................................................................................43

4.ContributionstoMSFDandSDGs.....................................................................................................45

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1.Introduction1Theoceansplayacrucialroleintheprosperityandfutureofcivilization;providingnaturalresources,food,recreationandaroutefortheglobaltransportofgoodsandservices.Theoceansplayakeyrolein climate regulation, arguably the most important environmental issue facing mankind. Thesustainableuseoftheoceansisvitalformankind.However,ourunderstandingofoceanprocessesislimitedbyapaucityofinformationaroundthekeybiogeochemicalcyclesoperatinginmarinesystems.Tounderstand,predict,protectandmanageoceanprocessesandresourcesrequiresastepchangeintheavailabledatafromthisenvironment.In2008,theEuropeanUnionestablishedtheMarineStrategyFrameworkDirective(MSFD)withagoalto protect the marine environment in Europe. Many aspects of the MSFD are common to theSustainableDevelopmentGoal14 (SDG14) from theUnitedNationswhichaims to ‘Conserveandsustainablyusetheoceans,seasandmarineresourcesforsustainabledevelopment’.In2008theEUalsoadoptedthe‘EuropeanStrategyforMarineandMaritimeResearch’toprovideaframeworkformarineandmaritimeresearchinEurope.TosupportallofthistheEuropeanCommissiondevelopedakeyinitiative,theOceanofTomorrow,to‘fostermultidisciplinaryapproachesandcross-fertilisationbetweenvariousscientificdisciplinesandeconomicsectorsonkeycrosscuttingmarineandmaritimechallenges’.TheaimofthefinalcallOCEAN-2013.2forproposalsin2013wastodevelopinnovativemarinetechnologiesforawiderangeofapplications.Thedevelopmentsoutlinedinthisdocumentaretheresultsofthefinaltopicarea–marinesensingtechnologies(includingbiosensors)tomonitorthemarineenvironment.The four projects selected from the OCEAN-2013.2 call were: COMMON SENSE – Cost-effectivesensors, interoperable with international existing ocean observing systems, to meet EU policiesrequirements;NeXOS–Nextgeneration,costeffective,compact,multifunctionalwebenabledoceansensorsystemsempoweringmarine,maritimeandfisheriesmanagement;SCHeMA– Integrated insituchemicalmappingprobesandSenseOCEAN–Marinesensorsforthe21stCentury.TheprojectsaddresskeyaspectsoftheMSFDandSDG14,bydevelopingnovelsensorsystemsforthedetermination of important aspects of the oceans’ health. Macronutrients that are importantcausative agents in both the development of harmful algal blooms and the increase of oxygenminimumzonesintheoceansaremeasuredusinganumberofdifferenttechnicalapproaches.Tracemetals (lead, cadmium, copper, mercury etc.) that are essential (micronutrients) or toxic(micropollutants)elements(dependingontheirconcentrations,chemicalspeciationandthenatureoftheorganisms)aredetectedinreal-timeusingon-chipmicrosensorarrays.Theincreasingconcernsaroundmicroplasticsintheoceans,aglobalproblem,areaddressed.Therearearangeofapproachesfor the determination of carbonate systemparameters to understand ocean acidification and theabilityoftheoceanstoameliorateclimatechangethroughCO2absorption.Someoftheprojectshavetakentheapproachofmeasuringthecompleteecosysteminordertodeterminecommunityshiftsinplantsand/oranimals.Suchcommunityshiftscanbeanindicatorofnaturaloranthropogeniceffects.Theprojectsallcombineacademicresearcherswithsmalltomediumenterprises(SME’s)involvedinaspectsofthecommercializationofmarinetechnologyandsensors.ThereisakeydriveintheOceanofTomorrowprojectstoplaceEuropeatthecuttingedgeofsensortechnologyformarineapplications,andtoallowtheexploitationofthedevelopmentsfromtheprojects.

1Pleasenote,theCOMMONSENSEprojectfinishedseveralmonthspriortotheproductionofthisdocument,hencetheirsensordevelopmentsarenotincludedinthe‘Stateoftheartdevelopments’section,However,despitetheprojectending,theymadesignificantcontributiontothe‘DataManagementandStandards’section.

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2.StateoftheartdevelopmentsThe following sectionshighlight themajor sensordevelopmentsand specific innovations from theNeXOS,SCHeMAandSenseOCEANprojects inordertogivedecisionmakersarealisticoverviewofwhatcanbeachievedintermsoftheparametersthatcanbemeasured,monitoredandassessed.TheNeXOSprojecthasimplementedsixmainscientificandtechnicalinnovations:threeinnovationsspecifictothechosenobservationframeworks(optics,acoustics,EAF)andthreethataretransversalandwill increasereliability,sensoranddatainteroperabilityfor integrationwithGOOS,GEOSSandotherinitiatives.SenseOCEAN took a holistic approach to environmental challenges such as climate change,eutrophicationandbiologicalcommunitystructure,andusedseveraltechnologicalapproaches(oftenfor thesameparameter,e.g.pH,phosphateetc.), todevelopsensorssuitable fordeployment inarange ofmarine environments (estuarine, coastal and open ocean). Individual sensors have beencombinedintoanintegratedmultifunctionalsensorpackage.SCHeMA,using innovativeanalyticalapproachesand integratingenOceantechnology,developedasuite ofmultichannel submersible sensing probes incorporatingminiature solid state sensors andanalytical platforms. The interfacing of the individual probes, via a dedicatedNetwork Controller,provideanopenandmodularsensingsolutionforgatheringspatialandtemporal informationonarangeofchemicalsandorganismsthatmayhaveanadverseeffectonmarineecosystemfunctioning.The sections are presented according to the types of parameters measured by thesensors/technologies,e.g.nutrients,carboncyclerelated,pollutantsetc.ratherthanbyproject.

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2.1.OptodesformarinemeasurementsHighlights:- apaletteofnovelopticalsensingmaterialsforO2,pH,CO2andNH3- twotypesofread-outdeviceswithopto-electronicssharedforalltheanalytes- noanalyteconsumption,lowpowerdemand,smallsizeandweight- multi-parametersensingwithscrewfitsensorcapsOptode technology relies on the ability of a sensing material to change its optical properties(absorption, luminescence etc.) depending on the concentration of the chemical beingmeasured.Over the last few decades optodes have successfully replaced other analyticalmethods formostmeasurementsofO2,andoptodetechnologyishighlypromisingforseveralotherchemicalspecies.Unfortunately, applicationof theoptodes in practicewas hinderedby a lack of high-performancesensingmaterialsandthenecessitytohavededicateddevicesforsignalread-out.

Figure1A:DeepwateroptodewithMODBUSinterface(top),shallowwaterstand-aloneoptode(bottom)andexchangeablesensorcapsfordifferentanalytes(left).B:Experimentalresultsfor

profilesmeasuredattheGotlandbasinintheBalticSeaWithintheSenseOCEANproject,theTUGrazandPyroScienceGmbHteamscombinedtheirexpertiseto create anewgenerationof optodes formonitoringofO2, pH,CO2 andNH3 in seawater.Novelluminescentindicatordyeshavebeensynthesizedandimmobilizedinvariouspolymericmatricestoobtain‘sensingchemistries’withoptimaldynamicrange,highlong-termstabilityandfastresponse(knownas‘sensorfoils’).Twotypesofcompactread-outunithavebeenproduced.Thefirsttypereliesonanopto-electronicunitinapressure-resistanttitaniumhousingandisequippedwithadeep-seaconnectorandaModbusboardallowingforshareddataloggingalongwithotherunitsdevelopedbySenseOCEANpartners.Thesecondtypeisastand-aloneversionthatincludesaloggerandabattery.Itcanbeoperatedtoadepthof500m.Maximumoptimisationoftheoptodeandloggerpowerconsumptionmeansthatthe

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batterycapacityissufficientforapproximately1.4millionsinglemeasurementpoints.Thisequatestoadeploymenttimeofoverayearwithameasurementintervalof30s.Thedevicesareequippedwithanadditionaltemperaturesensorfortemperaturecompensation.The spectral properties of the sensingmaterials have been engineered to enable read-outwith astandardizedopto-electronicsunit,whichgreatlysimplifieshandlingandminimizesthemanufacturingcosts.Screwfitsensorcapswithdifferentsensorfoilscanbeexchangedeasilytomodifyindividualdevicesaccording to the experimental demands, enabling simultaneousmonitoring of several parameterswithoutchangingtheoptoelectronics.Thechemistryoftheoxygenfoilisoptimisedforthedynamicrangeof0.2-500µMO2,howevermaterialswithdetectionlimitsdowntoseveralnmol/lcanalsobeused.ThepHoptodeshowsresponsefrompH6topH9,withhighestsensitivitybetweenpH7and8.ThepHandoxygenoptodesshowfastresponsetimesof1-10s.Thecarbondioxideoptodeshowsthedynamicsfromabout2to1000µmol×l1ofCO2butissignificantlyslowerthantheotheroptodes.Theresponseisparticularlyslowatlowtemperatures(~5°C,>1htime)thereforetheoptodeisyetnotsuitableforprofilingapplications.Theammoniaoptoderespondsfrom0.5to200µg/lofNH3withtheoptimalsensitivityaround25µg/lwhichisthetoxicitylimitformanymarineorganisms.TheresponseissimilarlyslowtothatoftheCO2sensor.Muchfastercarbondioxideandammoniasensorshavebeenpreparedaswellwiththetrade-offofsignificantlyloweroperationalstability.

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2.2.SpeciesrelevanttotheCarbonCycleSensingModule:CSMHighlights:- Accurateandrapidmeasurements- DirectdetectionofpH,carbonateandcalciuminseawater- Suitableforlong-termmonitoring- Easymaintenance

Theaccuratemeasurementof the carbonate system in seawater isof critical importance to studyoceanacidificationcausedbytheabsorptionofanthropogenicallyemittedCO2.Astheconcentrationsof the associated chemical species (CO2, pH, carbonate and bicarbonate) are interconnected bythermodynamicconstants,thecarbonatesystemcanbedescribedfromthemeasurementofjustanytwo species among the four (i.e. pH and carbonate). Additionally, the quantification of dissolvedcalciumisrelatedtothecarboncycleasitisinvolvedincarbonateprecipitation/dissolutionprocessesanditsmonitoringmaycontributetoamorecompletedescriptionofthemarinesystem.Thus,CSMisbasedonthesimultaneouspotentiometricdetectionofpH,carbonateandcalciuminseawaterusingmembraneelectrodes.Essentially,inpotentiometricsensorstheanalyticalinformationisobtainedthroughanionrecognitionevent translated into a voltage signal. Thus, a local equilibrium is established at an ion-selectivemembraneandtheactivitychangeoftheionanalyteintheaqueoussolutionresultsinachangeinmembranepotential.Thepotentiometricreadout isthedifferencebetweenthispotentialandthatprovidedbyareferenceelectrode.CSMincorporatesaflowcell(25×25×25mm) containingthree miniaturized electrodes of all-solid-state type (2 mm of diameter and 20 mm long) based onnanomaterialsandselectivemembranes2forpH,carbonateandcalciumtogetherwitha referenceelectrode(Figure2a-c).

Figure 2. 3 (a) Flow cell. (b) Electrode set-up. (c)Detection cell. (d) Fluidics design. (e) View fromoutsideoftheCSMprobe.(f)ViewfrominsideoftheCSMprobe.(g)Captoclosethesubmersiblehousingallowingthecouplingbetweeninternalandexternalconnections. (h) SCHeMA probe. 1: miniaturizedelectrode, 2: modified electrode, 3: electricalconnection, 4: fittings, 5: electronics housing, 6:housing for the fluidics system, 7: cap, 8: valve, 9:potentiometricflowcell,10:algaemodule,11:pump,12:CTDmultiparametricprobe.

Theflowconfigurationofthedetectioncellallowsforitsimplementationintoafluidicssystemdrivenby a submersible pump andmainly based on a two-position valve to select the pass of either acalibrationsolutionortheseawaterfromtheaquaticsystem(Figure2d).Thedetectioncellisplacedtogetherwiththealgaemoduleintoawater-andpressure-proofcylindricalhousing(Figure2e-g),which is connected to the electronics part (hardware for pump and valve control, potentiometric

2Anal.Chem.87(2015)8640-86453Environ.Sci.Technol.Let.(2017)Submitted

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measurements, the adjustment of the experimental protocol, data acquisition, storage andmanagement). After fixing the fluidic system containing the potentiometric sensors, closing thesubmersiblehousingandcalibratingtheCSM,thisisincorporatedintothetitaniumcagetogetherwiththerestoftheSCHeMAprobes(Figure2h).CSMiscapableofmeasuringpH,carbonateandcalciumdirectlyinseawaterwithlimitsofdetectionof3,10-5Mand10-5Mrespectively.Theprobeoperatesinanautonomousmannerwithrapiddataacquisition.Theflowmodeadoptedforthepotentiometricmeasurementsallowsthecorrectionofelectrode drift thus providing more trustable data. The use of nanomaterials in the electrodeconfiguration provides improved lifetime for the sensors. Thus, the CSM has demonstratedappropriate and validated operation during three weeks continuously measuring in the GenoaHarbour(Italy)deployedat4.3m.Theenvironmental applicationof the systemhasbeendemonstrated indifferentaquatic areasofsignificance,i.e.intheMediterraneanSeaandtheAtlanticOcean.2Asaresult,interestingbiochemicaltrendshavebeen found, suchasday/night cycles and temperaturedependenceof carbonateandcalciumlevelsinGenoaHarbour(Italy)aswellastidal-dependenceinArcachonBay(France),showninfigure3.

Figure 3.2 In situ temporal variation of pH, carbonate and calcium during a deployment in GenoaHarbour(fromApril3th,2017at07:00toApril10th,2017at12:00)andinArcachonBay(fromMay17th,2017at17:00toMay18th,2017at09:00).Lighthoursareindicatedwithgraysquares.HT=hightideandLT=lowtide.

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2.3.OpticalSensorO3–CarbonsensorsystemHighlights:- MeasureCarboncyclerelevantparameterssuchaspH,CO2,andalkalinity,dependingon

configuration,usingphotochemicalreactions.- Automatedembeddedspectrophotometryunitbasedonaminiaturizedflow-through

arrangementandabsorbancedetectionat435and596nm- Threesensorconfigurationsformeasurementsonferryboxandsailbuoyvessels- OGCSensorWebEnablement(SWE)enabledOSCAR-G2(fig.22.)uses12LEDsprovidingacontinuouslightspectrumfrom370to730nm.ThelightisguidedbyacollectinglenstothepointlightsourcewithinthecavityandlightabsorptionismeasuredbyaZeissMMSVISspectrometer(Zeiss,Germany).OSCAR-G2hasaninternaldatastoragecapacityof2GBandacomputationalmodulewhichcancalculatetheabsorptioncoefficientsbasedonthemeasuredrawlightspectraandpreviouslymeasuredandsavedcalibrationandreferencedata.Themeasurement process can be controlled via computer via a conventional web browser, thus noadditionalsoftwarehastobeinstalled.Itcanalsobetimer-controlled,whichallowsforautomatedoperation.OSCAR-G2supportsseveraltypesofprotocolssuchasModbusRTU,TriOS-protocol,ASCIIandinterfacessuchasRS232,RS485,Ethernet.The second cavity absorption spectrometer, HyAbS, is a prototype of the Helmholtz-ZentrumGeesthacht (HZG) completely automated absorption sensor dedicated for long-term usage asmonitoringinstrumentinlocationssuchasshipswithnorestrictionsregardingpowerconsumption(Fig.6).IntheHyAbS,thecompletemeasurementprotocolcanbecustomizedbytheuserandcarriedoutautomatically.Furthermore,alsothecalibrationprocedurehasbeensimplifiedbyreplacingtheneedofmeasuringaliquiddyeofknownabsorptionbythemeasurementofasolidstandard.TheultimategoaloftheNeXOSO3carbonsensorismonitoringthecalciumcarbonatesaturationstatewithenoughaccuracytoprovidetrendsofthreatstosomemarineorganismsandtheirrole intheecosystem. This is observing some of the ecosystem impacts of ocean acidification. Fullyunderstandingthecarbonatesystemdemandsnotonlymeasuringtemperatureandsalinity,butalsoknowledge of at least two of four measurable carbonate chemistry parameters: pH; dissolvedinorganiccarbon(DIC)whichisthesumofallinorganiccarbonsources(carbondioxide(CO2),carbonicacid(H2CO3),bicarbonateions(HCO3-)andcarbonateions(CO3--)insolution);totalalkalinity(TA,thebufferingcapacityofseawater);andpCO2.Iftwooftheseparametersareknown,thenthecalciumcarbonatesaturationstatecanbeestimated.

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TheNeXOSCbon2isthesystemproducedforcombinedpHandpCO2analysisandithasbeenbuiltin two version, for Sailbuoy platforms (Cbon2-sv) and for ferrybox applications (Cbon2-fb).TheAutomated Flow-through EmbeddedSpectrophotometry(AFtES) unit is basedon aminiaturizedflow-througharrangement. Absorbance detectionis supervised by aDebian based,versatileARMarchitecturewithcustomelectronicsforsignalconditioning,acquisitionandcontrollingelectromechanicalparts.Water lineisderivedfromthemainwater loopandis inparallelwiththeCO2extractionbranch.ThelightsourceisbasedoncommercialLEDscontrolledbycustomelectronicsandD/Aconvertersthataccuratelysetlightlevels.IntheCbon2-fbversionforferries(fig.4),pCO2ismeasuredbyextractionfromliquidphaseinacontinuousflow,followedbydetectioninthegasphaseby a novel, selective, solid electrolyte sensor. The sensor needs high temperature to operate andprovide enough current to be detected, resulting in limiting theapplication wherecontinuouslypoweredsystems can operate,as onboard ships of opportunity. The systemmeasures chemical-physicalparametersofseawater.IntheCbon2-svversiondesignedforoperationonaSailBuoy(fig.5),theAFtESiscoupledtoasubmersibledevicelocatedbelowthekeelofthehostingvessel.Extractionofgasphasefromwaterphaseisstillaccomplishedbyasemipermeablemembranesupportedbyatitaniumdisc. TheCO2detection in thegasphase is thenperformedbyaminiaturenear-infraredspectrometer, compensated for pressure and temperature, providing amilliAmpere output to beconditionedandacquiredbythesystem.Here,powerconstraintsarestrict,duetothelimitedpowersupplyofthehostingvessel.The Cbon3, available only for ferrybox applications, is basically a Cbon2-fb coupled with a totalalkalinityanalyserbasedonflowinjectionanalysis.Theprocedureisanalternativetothestandardoperatingprocedure,whereatitrationofthesamplewithHClinacelloccursandapHelectrodeisessentialtodeterminetheamountofhydrogenionsneededtobalancetheexcessofanionsofthesample.Here,theelectrodeisreplacedwithadyesuitedforthepHrangeduringtheanalysisandpHismeasuredspectrophotometrically.Thewholesystemtakes5minutestocarryoutasinglealkalinitymeasurement,30secondsforapHanalysisand1secondforpCO2.Precisionisdownto3μmol/kgSW,yetatpresentaccuracyisnotatthelevelofanalyticallaboratorysystems.Nevertheless,thepossibilityofmeasuring three quantities provides an outstanding advantage to refine calculations and applycorrectionfactors.

Figure4.O3sensor–Cbon2-fb

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TheO3systemsareweb-enabledusingtheOGCPUCKandSensorWebEnablement(SWE)standardprotocols.Thesettingsandsamplingstrategyofthesystemscanbemodifiedremotely,accordingtoweatherconditionsandpoweravailability.FortheSailBuoyapplication,datatransferisachievedbycompact, low data flow satellite communication and data are visible real-time by a NeXOS clientapplication.Theseensemblesimplement,forthefirsttime,novelsolutionsforprovidingresearcherswithmonitoringoceansurfaceCO2systemwithunprecedentedresolutionintimeandspacewithhighreliability and maintenance/attendance costs negligible compared to those needed for runningconventionalsystems.ThedeploymentofthesesystemsisprovidingvaluableinformationaboutthedynamicsofCO2fluxesintheocean,fundamentaltounderstandtrendsofoceanacidificationonalocalandglobalscale.

Figure5.O3sensor–Cbon2-svistheupperboxinthe sailbuoy hull. The vehicle controller is thelowerbox

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2.4.LabonchipchemicalsensorsHighlights:- Commondesignforallsensors- Provenlongtermdeployment- 6000mdepthrating- AbletomeasurepH,nitrate,nitrite,silicate,phosphate,ammonia,iron,totalalkalinityand

dissolvedinorganiccarbon Theseminiaturisedanalysersareallbasedonmicrofluidiclabonchiptechnology.Thechiptakesinasmallsampleofseawaterthroughafilter,thesampleisthenmixedwithchemicalreagents(storedseparatelyinplasticbags).Thefluidsarepumpedroundthechipusingacustomdesignedthreeorfour-barrelsyringepump,andcontrolledusingmultiplesolenoidvalves.Thesystemiscontrolledanddataisloggedusingacustomelectronicspackage.Thesensorsarehousedinanair-filledwater-tighthousingforshallowdeployments,butapressurecompensatingbladdercanbefittedandthehousingfilledwithoilfordeepseadeployments.Thephosphatesensorusestheclassiccolourimetricassay‘phosphateblue’andisbasedonalowcostopticaldetectionmethod, togetherwithanautomatedmicrofluidicdelivery systemthat isable todetectphosphatewithaLimitofDetection(LOD)of100nM.Thesilicatesensorperforms inaverysimilarway,stillusingcolourimetricanalysisbutwiththeammoniummolybdateassay.SilicateisatTRL 5 although components and previous versions have operated in coastal waters, the currentversionremainsunproveninanoperationalenvironment(thoughweexpecttodothisinthenextfewmonths).

Figure6Commonlabonchipsensordesign

TheironsensorperformscolourimetricanalysisofIron(II)andlabileiron(III).Iron(III)isreducedtoiron (II) using ascorbic acid, and iron (II) ismeasured using the ferrozinemethod. The sensor canalternatebetweeniron(II)and iron(III)measurements,or justmeasureoneoftheseparametersasdesiredbytheuser.ColourimetricanalysisusingtheGriessassayisusedforthenitratesensor.Nitrateisreducedtonitriteusingacadmiumtube.Thesensorcanbeconfiguredtomeasurejustnitritebyremovingthecadmiumreductiontube.Thelabonchipammoniasensorperformsahigh-resolutionfluorometricNH4

+analysisusingtheo-pthaldialdehyde (OPA) assay. Themethodologyof ammoniadetection isbasedon the fluorescentproduct formedbetweenOPAandNH4

+ in thepresenceof sulphite,afterNH4+ ispassed fromthe

sampletothereceivingfluid(OPA)inagasexchangechipwhichincorporatesamembranedevelopedinhouse.

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Specificationsofthesensorsaredetailedinthetablebelow(totalalkalinityanddissolvedinorganiccarbonsensorsareatalowerTRLsospecificationsarenotdetailed).Table1.Currentperformancespecificationsofthelabonchipsensors Phosphate Silicate Ammonia Nitrate/

NitriteIron pH

Samplerate(mins)

7(U)21(C)

7(U)25(C)

100(U)160(C)

5(U)15(C)

25(C) 15(S)

Limitofdetection

100nM 100nM <5nM 20nM 1.9nM

Measurement𝜎

<2.0%forconcns≥3µM

<2.0%forconcns≥3µM

n/a n/a n/a Accuracy:Betterthan0.003pHunits

Rangeoflinearity

0.1-100µM 0.1-300µM

0.005-1.1µM

0.025-1000µM

0.002-20µM

Precision:0.001pHunits

Samplevolumepermeasurement

80-280µL 80-280µL 280µL 280µL 2.5mL 550µL

TRL 7 5 4 8 8 7Environmentdemonstrated

Laboratory,estuaries,rivers,coastal

Laboratory Laboratory,estuaries,rivers,CTD,glider,benthiclanders.

Laboratory,estuaries,rivers,glacial,CTD,glider,benthiclanders,Arctic

Laboratory,estuaries,rivers.

Laboratory,coastal,deepsea,arctic,AUV

U=uncalibrated;C=calibrated;S=self-calibrating

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2.5.TraceMetalSensingModule:TMSMHighlights: - Highsensitivity,accuracyandreliability- Integratedantifoulingmembrane- Direct,simultaneousdetectionofthebioavailablefractionofarangeoftracemetals- Widerangeofapplication:surfacefreshwatertoopensea

Thegrowingnecessitytocontinuouslymonitortheleveloftracemetalslieswiththecriticalrolestheyplayinecosystemfunction.Somemetals(e.g.Hg,Cd,Pb)andmetalloids(e.g.As)exhibithightoxicityevenatlowconcentrations,whileothersareeitheressentialortoxic(e.g.Fe,Cu,Zn),dependingontheirconcentrationsandthenatureoftheorganisms.Assessingtheriskofmetalcontaminationsonecosystemandultimatelyhumanhealthisdifficult.Tracemetalsarepersistentanddistributedundervarious chemical species (speciation). 4 Only some specific metal species are bioavailable1.Bioavailability is therefore of primary concern when considering if a metal serves as nutrient ortoxicant.Whiletheglobalregulatoryenvironmentalqualitystandards(EQS)formetalsinwaterbodiesare stillmainlybasedon total (dissolved) concentrations, the revisedPrioritySubstancesDirective(2013/39/EU)suggestsmeasurementofthebioavailabilityofsometracemetals(Cd,Pb,Hg,Ni)eitherindirectlybymodellingoftheirspeciationordirectlybyapplyingspecificmeasurementmethodology.The TMSM is a new generation of submersiblemultichannel voltammetric probe5allowing direct,simultaneousmeasurementsofthebioavailablefractionofarangeoftracemetals(cadmium,lead,copper,zinc,arsenite,mercury)withsensitivityatsub-nanomolar (ng/L) levelusingantifoulingGelIntegratedMicroElectrodearrays(GIME).

Figure7TMSMreadyforoperationaldeploymentaspartoftheSCHeMAintegratedmappingsensorprobes(a)orindividually(b).DetailsofthekeycomponentsoftheTMSM(c).

GIME are based on new designed on-chip 190 to 500 interconnected iridium microdisk arrayselectrochemically plated with appropriate transducing element and covered by an antifoulingmembrane6.WhenaGIMEsensorisinterrogatedusinganodicstrippingvoltammetry,themetalflux(or current) during the electrochemical pre-concentration step selectively represents the dynamicmetalspecies(sumoffreemetalionsandsmalllabilecomplexes)whicharepotentiallybioavailable7.

4Arch.Sci.65(2012)119-1425Env.Sci.Tech.,inprep.6Sensors&Actuators,Submitted7TrAC24(2005)172-191

Mini-referenceelectrode

Inlet

Outlet

a. Potentiostat & preamplifierb. RS484 interfaces & memory boardc. Wireless moduled. Pressure & Temperature modulee. 3.4V power supply

a

a

a

bc

d

e

60 c

m

On-chip GIME and counterelectrode

Mini-referenceelectrode

Inlet

Outlet

a. Potentiostat & preamplifierb. RS484 interfaces & memory boardc. Wireless moduled. Pressure & Temperature modulee. 3.4V power supply

a

a

a

bc

d

e

On-chip GIME and counterelectrode

9 cm

a) c)

Pump

b)

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Thewholesystemiscomprisedonanelectronichousing,athree-channelflow-throughcellandanexternalmulti-channelpump.Eachindividualchanneloftheflow-throughcellincorporatesanon-chipGIME and counter electrode and amini-reference electrode. The electronic housing incorporatesthree potentiostats and pre-amplifiers, a 3.4V power supply aswell as all required hardware andfirmware for trace metal, pressure and temperature measurements; background subtraction;automaticpeakcurrentmeasurementsandtheirconversion intoconcentrations;datastoring;anddatatransmissionviawiredorwireless interface.TheTMSMcanbeusedindividuallyor interfacedwiththeotherSCHeMAsensingmodules(CSM,NSM,ASM)viaadedicatedBuoyControllerdevelopedintheproject.TheBuoyControlleralsoactsasagatewaybetweenthedeployedSCHeMAintegratedmappingprobesandtheSCHeMAwebinformationsystemgatheringandstoringthesensordataandprovidingopenaccesstothosedata.

TheTMSMwasdeployedforthreemonthsfromtheCNRplatformoftheGenoaHarbour(Italy)duringtheperiodJanuarytoApril2017.SimultaneousmeasurementsoftheCd,Pb,CuandZnbioavailablefractionwereperformedat2hourtimeintervals.AlifetimeoftypicallyonemonthwereobservedfortheGIMEsused.Duringtheirmonthoperationaldeployment,upto350simultaneousmeasurementsofthefourmetalsweresuccessfullyachieved.TheTMSMwerealsodeployedintheArcachonBayandtheGirondeEstuaryrepresentativeofthesouthwestEuropeanAtlanticCoasthostingmajorcoastalprotectedareasandeconomicactivities(seafoodproductionareas).Hg(II)levelswerelowerthanthelimitofdetectionofthedevelopedGIME(<20pM/5ng/L).Theresultsrecordedfortheothertargetedtracemetalsrevealedthat,indynamictidalcoastalecosystems,theconcentrationofthebioavailablefractionoftracemetalsmaydoubleinafewhours(ArcachonBay)andvaries,underdifferenttrendsdependingontheircomplexationproperties,inarangeuptooneorderofmagnitudeinthesalinity/turbiditygradientsoftheGirondeestuary(e.g.fig.8)

Figure8:InsiturecordedtemporalAs(III),Cd(II)andPb(II)bioavailableconcentrationsandlongitudinalprofilesofCu(II),Zn(II)andPb(II)bioavailableconcentrationsmonitoredduringaTMSMdeploymentinrespectivelytheArcachonBay(May2017)andGirondeEstuary(June2017).

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2.6.NutrientsSensorsModule:NSM Highlights:- Accuratedetectionofnitrateinseawater- Inlinecouplingofneededpre-treatments- Canbeusedfortheadditionaldetectionofchloride/salinityTheimportanceofthereliablelong-termmonitoringofnutrientsinseawaterliesintheirsignificantroleasindicatorsofanthropogenicactivitiesthatperturbaquaticecosystems.Currentlyestablishedapproachesfornutrientdetectioninvolvesampleextractionusingpowerintensivepumps,followedbyanalysisusingexpensivecentralizedlaboratoryinstrumentation.Thesamplingproceduresarelikelytoresultinundesiredalterationsofthesamplesimplyingthelossofusefulinformationandthereforetheconceptofdecentralizedsensorsfortheinsitumonitoringofnutrientshasreinforceditsinterestforenvironmentalistsinthelastyears.Importantly,potentiometricsensorsareespeciallysuitableforthispurpose8butitisnecessarytoreducetheamountofcertainmajorionsinseawater,i.e.chlorideandhydroxyl,priortothepotentiometricdetection.ThedevelopedNSMisbasedonthesamepotentiometricflowcellasinCSMbutcontainingpH,nitrateandnitritemembranepotentiometricsensors.NSMandCSMareinterchangeablemodulessharingthe same electronics. In the case of NSM, electrochemical desalination9and passive acidificationmodules10arecoupledtothedetectioncell(fig.9).Thus,thedesalinationmodulereducestheamountofchlorideinseawaterdowntomillimolarlevelsandthentheacidificationmodulelowsthepHdownto5.5.Intheseconditions,potentiometricdetectionofnitrateandnitriteinseawaterisaffordablewithlimitsofdetectionof0.9µMand0.6µMrespectively.Theincorporationofacalibrationsolutionallowstocompensateanyelectrodedrift.

Figure 9. NSM image and fluidics design. 1: desalination unit, 2: valve, 3: acidification unit, 4:potentiometricflowcell,5:submersiblehousing.TheDesalinationunit9A microfluidic custom-fabricated thin layer flat cellallowsone to electrochemically reduce the chlorideconcentrationofseawatermorethan100-fold,from600mMdownto∼5mM.Thedesalinatoroperatesby the exhaustive electrochemical plating of thehalides from the thin layer sample onto a silverelement as silver chloride (Eapp=800mV, t=300 s),whichiscoupledtothetransferofthecountercationsacrossapermselectiveionexchangemembranetoanoutersolution.Ifthedesalinationcellisinterrogatedusingcyclicvoltammetryinstead,theobtainedpeaksarechlorideconcentration-dependentandthereforeitcanbeadditionallyusedaschloridedetectorintherangeof0.5µM-600mM.Moreover,thelinearcorrelationchloride-salinitypermitstheindirect

8Curr.Opin.Electrochem.(2017)DOI:10.1016/j.coelec.2017.06.0109Anal.Chem.87(2015)808410Anal.Chem.89(2017)571

18

detection of salinity without the need of changing the probe, as in the case of conductivitymeasurements.TheAcidificationunit9The working principle of the developed acidificationunite relies on the cation-exchange process betweenthe sample and an ion-exchange Donnan exclusionmembraneinitsprotonatedform.Theresultingin-lineacidification of naturalwaterswithmillimolar sodiumchloride level (freshwater, drinking water, andaquarium water, as well as dechloridized seawater)decreases the pH down to∼5. The originality of theproposedflowcellliesinthepossibilitytoadjustthepHofthesamplebymodifyingitsexposuretimewiththemembranebyvaryingthevolumetricflowrate.TheNSMwassatisfactorilyappliedforchlorideandnitratedetectioninArcachonBay(France).Nitritelevelswerelowerthanthelimitofdetectionofthepotentiometricsensor.ThepHsensorservestocontroltheobtainedpHafterthedesalination+acidificationprocedures.IntheNSM,seawaterpassesfirstthroughthedesalinationunitforchloridedetectionandthendesalination,thereafterthroughtheacidificationmoduleand finally through thedetectioncell. Theobserved temporal trends (fig.10)clearlyshowtidal-dependenceofchlorideandnitratelevels.

Figure 10. Temporal variation recorded forsalinity (CTD), chloride and nitrate (in situ, exsitu)duringa24-hdeploymentintheArcachonbay(fromMay15th,2017at15:00toMay16th,2017at15:00). Lighthoursare indicatedwithgraysquares.HT=Hightide.LT=Lowtide.

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2.7.ANESIS:AutonomousNutrientElectrochemicalSensorInSituHighlights:- Noliquidreagents- Measuresilicateandphosphate- 600mdepthrating- Adaptabletoarangeofplatformsincludingprofilingfloats

Nutrientsarekeyplayersintheoceanicprimaryproductivity.Whendeliveredinexcesstothecoastalocean, theymay lead to eutrophication and harmful algal blooms. Observations ofmarinewaterqualityandbiogeochemistryarecurrentlypoor,especiallyforparametersthatcannotbemeasuredbyremotesensing.ANESISmeasurestwoimportantnutrients,silicateandphosphate.Essentially, electrochemical sensorsworkby reactingwith thenutrient (silicateorphosphate)andproducinganelectricalsignalproportionaltotheconcentrationofthenutrient. Infactthenutrientmustfirstbeconvertedintoacomplexthatwillreactwithanelectrode.TheSenseOCEANsilicateandphosphateelectrochemicalsensorshavebeenadaptedfromthelaboratoryprototype,whichusestwoseparatecells:thefirstoneforinsituformationofthecomplexesandthesecondforthedetectionofsilico-andphosphomolybdiccomplexesonagoldelectrode(seeboxbelowfortechnicaldetails).Themechanicaldesignsandtheset-upoftheelectrodesarecrucialstepstoensureeffectivemixingofthesolution.Theelectronicsboard(forsilicateandphosphate)hasbeendevelopedinclosecollaborationbetweenCNRS-LEGOS and nke Instrumentation to miniaturise it as far as possible, while still maintainingperformance.Instrumentsloweredintotheoceanneedtobeprotectedfromtheeffectsofpressuresoareplacedin‘housings’.Thehousingsofthesilicateandphosphatesensorsareidentical,whichwillreducethecost ofmass production. The sensors are 25 cm long (without connector) and 9 cm in diameter,weighing2.2kginair.

Figure11.Sensorshowninpressurehousing(left).Sensorandpowersupplymountedonaframe

readyfordeploymentonmooringoffthecoastofChile(right)

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Thesilicatesensorwasdeployedfortwoweeksonamooringat55metersdepth intheupwellingzoneoffChileatTalcarucaPointinApril2017.Thesilicateconcentrationwasmeasuredeveryhourand ~140 data files were successfully recorded. Separate water samples were taken to enablemeasurementbyanothermethodinordertoverifythesensorresults.The silicate sensorhas alsobeen implementedon aPROVORprofiling float togetherwithpHandoxygenoptodesensorsandanitratelabonchipsensor.ThefloatwassuccessfullydeployedoffshoreVillefranche-sur-MerintheMediterraneanSeainSpring2017.Thedeploymentwasverysuccessfulwith~40measurementsobtainedandsentbacktothelabbysatelliteforlateranalysis.

Assilicateandphosphatearenon-electroactivespecies,theirconversiontoelectroactivemolybdatecomplexesinacidicmediumisrequireda-c.

Si(OH)4+12MoO42-+24H+àH4Si(Mo12O40)+12H2O

PO43-+12MoO4

2-+27H+àH3PMo12O40+12H2O

AllthereagentsneededareformedinsitubyasimpleoxidationofmetallicmolybdenumMo+4H2OàMoO4

2-+8H++6e-

InordertoreachtheneededacidicpH,thereductionofH+onthecounter-electrodeispreventedbyisolatingthecounter-electrodebehindamembranelimitingtheprotonsdiffusion.

Because silicate is an interference to phosphate detection, a ratio of H+/MoO4

2- equal to 70 isrequired.Toreachthisratioanothercompartmentwithasecondmolybdenumelectrodeconnectedwithaproton-exchangemembraneisadded.aLacombeetal.,Talanta77(2008)744-75bJoncaetal.,Electr.Acta88(2013)165-169cBarus&Romanytsiaetal.,Talanta,160(2016),417-424

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2.8.Electrochemicalmicrosensors Highlights:- Accurateandrapidmeasurements- Non-destructive- Canbeusedforsediment-waterinterfacemeasurements- Widerangeofapplications–wastewaterplantsthroughtoopenoceanElectrochemicalmicrosensorsareneedle-shapedprobeswitha tinyactive tiparea thatallows thedirectmeasurementofspecificchemicalsintheenvironment.Thesizeofthemicrosensortips,oftenthinnerthanahumanhair,makesthemideallysuitedtostudyingthemicro-distributionofchemicalsinsidesoftmaterialsuchastissue,sedimentorbiofilms.Thetipscanpenetratethematerialwithoutdisturbanceordestruction.Theperformanceoftheelectrochemicalmicrosensorsisnotaffectedbyexternalmotion.Combinedwiththeiraccurateandrapidresponse,thismakesthemversatiletoolsformeasuringchemicalsofinterestintheoceans.InSenseOCEAN,AarhusUniversityincollaborationwithUnisenseA/Ssuccessfullydevelopedstate-of-the-artmicrosensorsfortwogloballyimportantgreenhousegases:carbondioxide(CO2)andnitrousoxide(N2O).Greenhousegases(GHGs)trapheatintheatmosphere(hencetheirname)contributingto globalwarming and climate change. CO2, themostwidely recognizedGHG is released into theatmospherefromburningfossilfuels,wasteandtreesaswellasfromthemanufactureofcementandsteel. N2O is also released via fossil fuel burning and during agricultural and industrial processes.Although smallerquantitiesofN2O thanCO2are released to theatmosphere,N2Ohasapotentialglobalwarmingeffectof>260timesthatofCO2.Atthemoment,theselargeindustrialinputsofCO2andN2Ototheatmospherearebalancedbyabsorptionintotheoceans.However,thecapacityoftheoceansisfinite,hencetheneedtomonitorthesegases.TheCO2microsensorThismicrosensorworksbyareductiveconversionof CO2 on a silver cathode. The sensor signalconsists of an amplification of the resultingcurrent. It is necessary to apply a very negativepotential to reduce CO2. This means that othercompounds such as H2O and O2 (that can bepresent inhigh concentrations)will give a signal.The challenge in constructing a functional CO2sensor was to avoid these compounds reachingand reacting on the cathode surface. This wassolved by adding an oxygen scavengingcompartmentandawater-bindingelectrolyte. Figure12StructureoftheCO2microsensorTheN2OmicrosensorTheN2OmicrosensorhasthesameschematicappearanceasshownfortheCO2sensor.Thesesensorsrespond linearlyacrossahugeconcentrationrange, fromnanomolar tomillimolarconcentrations!The sensors have operational lifetimes of several months even when analysing continuously in awastewatertreatmentplant.About100wastewatertreatmentplantsworld-widearenowequippedwithUnisenseN2Osensors.

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High-sensitivityN2Omicrosensor(STOX-N2O)At very low concentrations, it can bedifficulttodistinguishtheN2Osignalfromthe background signal. The STOX-N2OperformsaninternalreferencingbyuseofanextracathodetoperiodicallyremoveallN2Oandthusrevealaprecisezerocurrent.AsforthenormalN2OsensorthereisalsoanoxygenscavengingcompartmentbasedonO2 reductionby chromium (II) ionsorascorbate.

Figure13StructureoftheN2Omicrosensor

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2.9.MultiparameteropticalsensorHighlights:- Onedesign,severalvariants- MeasuresCDOM,ChlorophyllA,PAHs- Pollutiondetectionforoil,sewage,agriculturalrun-off- DetectsonsetofharmfulalgalbloomsFluorescence is a very sensitive technique formonitoring various compounds in the environment.Somecompoundsabsorblightatveryspecificwavelengthsandthenre-emittheenergyabsorbedasfluorescence at a longerwavelength. Fluorescence is directly proportional to concentration and istypically 1000x more sensitive than more conventional absorbance measurements. In addition,fluorescenceoffersbetterselectivity,asnotallcompoundsfluoresce.UV fluorescence typically targets aromatic hydrocarbons, heterocyclic compounds and largerconjugated aromatics associated with Coloured Dissolved Organic Matter (CDOM). Visiblefluorescenceistypicallyusedfordyetracingandchlorophylldetection.

Figure14UVandvisiblefluorescencepropertiesofdifferentcompounds

Todate,fluorometershavecombinedasingleexcitationandemissionwavelengthtotargetspecificcompoundgroups.However,ascanbeseeninfig.14,therecanbesignificantoverlapinthespectralcharacteristicsofdifferent fluorescencecompounds,making itdifficultunambiguouslytoselect foronetypeofcompound.Further,environmentalinterferences,e.g.turbidityor‘colour’inthesample,canattenuatetheexcitationlightleadingtounder-reportingofthefluorescencesignal.Toovercometheproblemsoutlinedabove,amulti-parametersensorhasbeendevelopedaspartoftheSenseOCEANprojectwheremultiplefluorescencechannelsareusedincombinationwithturbidity,absorbanceandtemperaturemeasurementstoproviderobustmonitoringinthepresenceofarangeofenvironmental interferences.Twomainvariantsof thesensorhavebeendeveloped:oneforUVfluorescenceapplicationsandtheotherforalgalstudies,monitoringchlorophyllfluorescence.IntheUVvariants,asingleexcitationwavelength isusedtoexcitefluorescence inthesample.Thesensor then isolates three different fluorescence emission wavelengths. In addition, absorbance,turbidityandtemperaturearemonitoredandalgorithmsdevelopedduringtheprojectareappliedtolinearizethefluorescenceresponseandcorrectfortheseinterferences.Thishastheaddedbenefitofsignificantlyextendingthedynamicrangeofthefluorescencemeasurementbyafactorof20.Threevariants of the UV sensor have been developed: the ‘BTEX’ sensor targets single ring aromaticcompounds associated with fuel contamination; the ‘Crude’ sensor targets polycyclic aromatichydrocarbons (PAHs);while the third targets the amino acid Tryptophan,which is associatedwith

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bacterial contamination in the environment, e.g. due to sewage or agricultural run-off. All threemonitor CDOM and chlorophyll-a fluorescence to identify potential signal interferences frombackgroundenvironmentalfluorescenceand/oralgae.

Figure15Multiparameteropticalsensor

Thealgalversionofthemulti-parametersensoroperatesinadifferentmannertotheUVvariants.Inthissensor,fourdifferentexcitationwavelengthsareusedtoexcitespecificpigmentgroupsassociatedwiththelightharvestingcomplexesinalgae.Energyabsorbedbythesepigmentsisrapidlytransferredtochlorophyll-ainPhotosystemIIandtheresultingfluorescenceisthendetected.Bymonitoringthechangingcontributionstochlorophyll-afluorescencefromthedifferentexcitationwavelengths, it ispossibletodetectshiftsinalgalcompositionofasample,e.g.todetecttheonsetofanalgalbloom.Thefourvariantsofthemulti-parameteropticalsensoraresummarisedinTable2

Parameter BTEX Crude Tryptophan AlgaeBTEX ü PAH ü

CDOM ü ü ü Tryptophan ü

Chlorophyll-a&-c ü ü üChlorophyll-b&-c ü

Phycocyanin üPhycoerythrin ü

Turbidity ü ü ü üAbsorbance ü ü ü üTemperature ü ü ü ü

Table2.ParametersmeasuredbythefourvariantsoftheopticalsensorsInadditiontothesensordevelopment,workhasalsofocussedondevelopingtraceablestandardizedcalibration for the fluorometer. Todate, ithasbeendifficult to compare theoutput fromdifferentmanufacturers’sensors,becausetheirresponseswillbehighlydependentonsensorgeometry,theexcitationandemissionwavelengthsused,thespectralcharacteristicsofthelightsourceanddetectorand thecompoundused forcalibration.This lackof standardizationhas inhibited thewideruseoffluorescence for routineenvironmentalmonitoring.A standardizationmethodhasbeendevelopedduringtheprojectthatallowsthesensortoreportfluorescenceinstandardizedandtraceable‘relativefluorescence units’. This enables the detected fluorescence to be compared directly betweenmeasurement channels and across different sensor types. Careful management and internalreferencingoftheexcitationlightsourcealsoensureslongtermcalibrationstability.

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2.10.OpticalSensorO1NeXOSO1FluorescenceSensorsarenewcompact,low-powermultifunctionalopticalsensorsystemsbasedonmulti-wavelengthfluorescenttechnology.Theiraimistoprovidedetailedinformationonbothwater constituents andother relevant contaminants that are optically active in eitherUVoropticalspectralregions.InNeXOS,threedifferentfluorescencesensortypeshavebeenconstructed.Two of them, theMatrixFlu-UV and theMatrixFlu-VIS are based on a similar system designwithdifferentinneropticaldesignsandcomplementarycapabilities.Thetwousedifferentcombinationsofthreeorfournarrowbandexcitationandemissionwavelengths.ThethirdO1system,theMiniFluo,consistsoftwoseparatesinglechannelfluorescencedetectorswithinasinglehousing.Itdetectstwodistinct parameters in the water column related to the wavelength combination of fluorescencesignalsfromhydrocarbonsinthewater.2.10.1.OpticalSensorO1MatrixFlu-UVandMatrixFlu-VISHighlights:- Fourdetectionchannelsinanultracompactseawater-resistanthousing(availableinstainless

steelandtitanium,depthratedfor300or6,000m)- IncludesanexcitationlightsourceofthreeorfourLEDssurroundedbysemiconductor

detectorscollectingfluorescencesignalsthatpassthroughadaptable,selectablenarrowbandwidthfilters

- Powerconsumptionisbelow1.8Wat12to24Vdcandweightislessthan600ginair- OGCPUCKandSensorWebEnablement(SWE)enabled- Validatedonwave-gliderandbuoyBothMatrixFlusensors(fig.16)includeanexcitationlightsourceofthreeorfourLEDssurroundedbysemiconductordetectorscollectingfluorescencesignalsthatpassthroughadaptable,selectablenarrowbandwidthfilters.The lightsourceprovidesexcitationofasamplevolume in frontof thesensor.Thedetectorsarealignedinanangleof170°comparedtoemittedlightinordertosamplethesamevolume.ThecombinationsofwavelengthscanbefoundinTable3.

Table3.WavelengthmatrixforMatrixFluUV(violet)andVIS(green)

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Bothversionshavefourdetectionchannelsinanultracompactseawater-resistanthousing(availableinstainlesssteelandtitanium,depthratedfor300or6,000m).Inbothversions,measurementsareperformedwithallpossibleexcitationemissioncombinations,thusunfoldingamatrixoffluorescentandbackscatteringsignals.Powerconsumptionisbelow1.8Wat12to24Vdcandweightislessthan600ginair.Whencombiningbothsensors,e.g.,usingacompliantfittingforgliderapplications,anunchallengedrangeacrosstheUV-VISelectromagneticspectrumisavailable.Thisallowsobservingnot only established parameters but also has the potential of observing previously unknownsubstancesthatmaybeencounteredinmultipurposeapplications.Matrixsensingobviouslyproducesmoredatathansingle-channelfluorometers.Therefore,onboardprocessingandstoragecapacitieswere included to make use of higher-level operations, such as characterizing substances frommultisensoryinformationorperformingdataqualitycheckingfromredundantinformation.Onboardcomputational power additionally enabled the easy integration of standard protocols such asMODBUS-RTUandOGC-PUCKonEthernet,RS-232andRS-485 interfaces.Sensoroperationcanbecontrolledeitherfromoutsideviatheaboveprotocolsorasaresponsetopowerup,asimplesolutionfor lesssophisticatedplatforms.Finally,cost-efficiency isachievedfromfactorssuchas integratingmultiplesensorsintoone,supportingflexibilityinthemission’stargetparameters,easeofintegrationduetoopenstandardprotocolsandenhanceddataaccessbasedonembeddingprocessingcapacitiesandanopenstandardcompliantsoftwarearchitecture.2.10.2.OpticalSensorO1MinifluoHighlights:- Candetectandquantifyfourpolycyclicaromatichydrocarbons(PAH):naphtalene(NAPH),

phenanthrene(PHE),fluorene(FLU),andpyrene(PYR)togetherwithtryptophanaromaticaminoacid

- Single-bandbandpassfiltersallowfordetectionthroughaquartzdouble-convexlens- OGCPUCKandSensorWebEnablement(SWE)enabled- Validatedondeepglider

Figure16.O1Matrixflusensors

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Thethirdopticalfluorescencesensor,theMiniFluo(fig.17),wasdevelopedandbuiltwithtwosinglechannelswhichenablethedetectionandquantificationoffourdifferentpolycyclicaromatic(PAH)asindicated in Table 4:naphtalene (NAPH), phenanthrene (PHE), fluorene (FLU), and pyrene (PYR)togetherwithtryptophan(TRY,anaromaticaminoacid).Thedesignhassingle-bandbandpassfiltersthatallowfordetectionoffluorescencesignalsthroughaquartzdouble-convexlens(UVgradefusedsilica)byaSi-photodiode.Themechanicaldesignismadeofaverycompacthousing(ØxL:75x60mm) anodized aluminium for the upper part and a copper plate for the bottom part. The mainadvantagesofMiniFluoare the simultaneousmeasurementof twopetroleumcomponentswith aminiaturized design having low power consumption of 0.36 Watt at 12 VDC. This enables theintegration on underwater platforms such as gliders. A standardized I2C protocol is used to alsosupportsensorMLandNeXOScompliantconnectivitytoSOSdatastorage.

Table4.WavelengthmatrixforMiniFluo

Excitation (nm) Emission (nm)

NAPHTALENE 275 340

TRYPTOPHANE 275 340

PHENANTHRENE 255 360

PYRENE 270 380

FLUORENE 260 315

Figure17.O1MiniFluosensor

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2.11.Miniaturized,multi-channelAlgaeSensingModule:ASMHighlights:- Flexibleandmodulardesign- Nosamplepreparation- Earlystagedetectionofarisingalgalblooms- IdentificationofharmfulalgalgroupsfromamonganalgalassemblageFluorometric measurements are sensitive methodologies that have been used extensively formonitoring of diverse compounds in the marine environment, as they are more sensitive thanconventionalabsorbancemeasurements.Phytoplanktonabsorblightatveryspecificwavelengthsandre-emit part of the absorbed energy as fluorescent light at longerwavelengths. Fluorescence canthereforebeusedasselectivetechniqueto identifyrelevantalgalgroups inanalgalassemblageofmixedcomposition. Inaddition,distinctemissionwindowsreduce interferencesfromothermarinecompounds.

Conventionalalgaefluorometerscomparethefluorescenceemitteduponexcitationattwodifferentwavelengthsaimingtoseparatecyanobacteriaandalgaeaccordingtotheirmajorspectraldifferencesas shown in figure 18. However, there can be significant overlap in the spectral characteristics ofdifferentalgaemaking itdifficult todiscriminate furthergroups. Inaddition,variousbiologicalandchemicalinterference,e.g.fromcoloreddissolvedorganicmatter(CDOM),yellowsubstancessuchashumicmatterorsuspendedparticlesinthesamplecanleadtoalterationsinthefluorescencesignalandhavetobetakenintoaccountfordataevaluationprocedures.Toaddresstheseproblems,TUGraz,aspartoftheSCHeMAproject,hasdevelopedaminiaturized,multi-channel detection module. This in-situ device enables the early stage detection ofphytoplanktonspeciesinalgalbloomsandthereal-timeidentificationoftheirtaxonomicaffiliation.Theappliancehasamodulardesigntoalloweasyreplacementofopticalcomponents.AlthoughtheASMisableto identifyvariousalgalgroups,thesystemwasoptimizedforreliable identificationoftoxinproducingcyanobacteriaanddinoflagellatesfromamongotheralgaeinanalgalassemblageofmixed composition. In addition, the ASM is able to track the biomass concentration in order todeterminetheonsetanddeteriorationofalgalblooms.

Figure18Spectralcharacteristicsofcyanobacteriacomparedtootheralgalgroups,usingdiatomsasanexample.

Figure19Renderedpictureofthealgaedetectionmodule(leftandright)andthemodularLEDmodulesusedasexcitationsources(middle).Thepictureontherightillustratesthearrangementofopticalandelectronicalcomponents.Photodetectorsarealignedwith90°angletotheexcitationsourceandcoveredwithemissionfilterstominimizecross-talkbetweenexcitationandemissionchannels.

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Inthedetectionmodule(fig.19),uptoeightdifferentwavelengthsareusedtoexcitespecificpigmentsinthephotosystemsofthephytoplanktonsample.Uponexcitation,theenergyabsorbedisrapidlytransmitted throughout the light-harvesting complex of the photosystems to chlorophyll-a in thereactioncenter.Partoftheenergyisusedtomaintainthephotosynthesisofthealgaeandsurplusenergy is emitted as fluorescent light. The resulting fluorescence and the contribution of certainexcitationwavelengthstothefluorescencesignalisdetectedbytheminiaturizedASM.Algorithmsarethenappliedtostandardizeandcorrectthefluorescencesignalaimingatgreaterinter-comparabilitywithin the detection system and between experiments. Subsequently, the recorded fluorescencepatterniscomparedtoasetofreferencedataandamultivariatepatternrecognitionalgorithmallowstheidentificationofthetaxonomicaffiliationofthesample(fig.20).

For semi-quantification of thephytoplanktonbiomass,thedetectionunit counts cell events passingthroughthesystemandcorrelatesthenumber of events with the averagefluorescence intensity at certainwavelengths. Up to a certain celldensity limit, signal spikes can beresolvedandthedetectedspikescanbecountedascellevents(seezoom-inplot of fig. 21). This approach allowsthe measurement of changes in thebiomass concentration that indicatetheonsetanddeteriorationofanalgalbloom.Signalresponsesarehighlydependentonvariousinstrumentparameters,e.g.spectralcharacteristicsoftheexcitationsourcesanddetectorandabsoluteintensityofthelightsources,amongotherthings.Thecurrentdeficitininter-calibrationstrategieshascompromisedtheutilizationoffluorometersinenvironmentalscience.Therefore,aninternalcalibrationandstandardizationstrategywasdevelopedallowing direct comparison within the multi-channel detector system and between differentmeasurementinstruments.Inaddition,workhasalsofocusedondevelopingasoftwareinterfaceforexternalanddetaileddataevaluationofindividualcellevents.Thesoftwarecombinestheacquiredknowledge of standardization procedures and data evaluationmethodologies using amultivariatepatternrecognitionalgorithm.Thisfacilitatestheapplicationofthedeviceforvariousscientificissues,forexampletheinvestigationhowtherelativefluorescencepatternofaphytoplanktonsamplevariesalongitsgrowthphase.

Figure20(A)Relativefluorescenceintensityuponexcitationatdifferentexcitationwavelengthsforamphorasp,adiatomsample.(B)Resultingscoreplotafterapplyingthemultivariatepatternrecognitionalgorithmaimingatthecomparisonoftheunknownsampletoasetofreferencedata.

Figure21Theintensityofthefluorescencesignalemittedfromthephotosystemsstronglydependsonthebiomassinthemeasurementchamber. Ifthecelldensity is lowenough,thecellevents,passingthroughthemeasurementchamber,canberesolvedandcounted.

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2.12.OpticalSensorO2–PhytoplanktonidentificationsensorHighlights:- Integratingcavityprovidingreliableidentificationofatleast7phytoplanktongroups- a)OSCAR-G2:Compact,submersible,andcommerciallyavailable.Operateasbench-topor

profilinginstrument- b)HyAbs:Completelyautomatedabsorptionsensordedicatedforlongtermusageasbench

topinstrumentinlocationwithnorestrictionofpowerconsumption- OGCSensorWebEnablement(SWE)enabled- ValidatedonferryboxBasedontheintegratingcavityapproachofthePSICAM,theNeXOSprojectdevelopedtwoautomatedsensorscapableofthecontinuous,hyperspectralmeasurementoftheabsorptioncoefficientsofwater,OSCAR-G2(fig.5)andtheHyAbS(fig.6).Bothtakeadvantageoftheuseofanintegratingcavity,sincethisavoidserrorsintroducedbylightscatteringonparticlespresentinthesampleanditincreasesthesensitivityofthemeasurements.Fromthehyperspectral(2nmresolution)absorptioncoefficientdata,whichistheprimaryoutputofthesensors,phytoplankton-relatedinformationcanbederived.Certaincoefficientscanbeusedasopticalproxiesforimportantbulkparameterslikechlorophyll-aandtotalsuspended matter (TSM), which are a quantitative measure of phytoplankton in the water.Furthermore,theshapeofthespectrumcanbeevaluatedwithrespecttotaxonomicalinformation,sinceitisdeterminedbythepresenceofaccessorypigments,whichareoftenspecificforcertaintypesofphytoplankton.Thisphytoplanktonidentificationisdonebycomparisonofthemeasuredspectrumtoadatabaseofspectrawithknownphytoplanktoncompositions.Thealgorithmsforthisapproachhavealsobeendevelopedinthecourseoftheproject.

Figure22.O2sensor–OSCARG2

Figure23.O2sensor-HyAbS

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2.13.AcousticSensorsHighlights:- Compact,lowpowerconsumptiondigitalhydrophonewithembeddedpre-processingof

acousticdata,includingMSFDdescriptor11andBioacoustics- Open-hardwareforuserprogrammingofnewprocessingroutines(ANSIC)- Highdynamicrange,downtoSea-State0- ArrayconfigurationtestedwithPrecisionTimeProtocol(IEEE1588)- Benchtesteddownto445barpressure- XPX10-800standardtestedforcold,hotstorage,moisture,vibrationandmechanicalshocks- EthernetandRS232communication,SCPIprotocol- OGCPUCKandSensorWebEnablement(SWE)enabled- Validatedonglider,profilingfloatsandfixedplatforms(cabledandmoored)

A1isacompact,lowpowerconsumptiondigitalhydrophone(fig.24)withembeddedpre-processingofacousticdata,usingtheOpenGeospatialConsortium(OGC)ProgrammableUnderwaterConnectorwithKnowledge(PUCK)andSensorWebEnablement(SWE)interoperabilitystandards.Theembeddedprocessingreducesthecommunicationbandwidthrequirementsforrealtimedataaccess.A1consistsofonetransducerandtwoA/Dconverters,simultaneouslysampled,withdifferentgain,tomeasureanddetectabroaderrangeofacousticsourcelevelsfrom50dBto180dBwithreferenceto1μPaandincludesselectableanaloggainsettingsortraceableautomatedgaincontrol,inthefrequencyrangefrom1Hzto50kHz.The architectureofA1 sensor is composedof five elements: Transducers (HYD) of different typesdependingondepthrequirementsandcost(NeptuneSonarD/70,TechnologyLimitedSQ26-01,JS-B100-C4DP), a Signal Conditioning Unit (SCU) which includes 2 channels of amplifier stage withselectablewhiteningequalizer,anti-aliasingfilter,selectablegain,samplingfrequency;amicro-powerSAR Analog to Digital Converters 16 bit ADS8867; amicrocontroller Unit (MCU) LPC4370; and anUnderwater connector 12-pin male MCBH12M. During operation, the transducer signal is pre-amplifiedwithaninputstageof20dBgain,commonforbothchannels.Thefirstchannel(CHA)hasapost-amplifierstagewithselectablegain(20or40dB)thatcanbeprecededbyan“equalizer”filterinordertooptimizethesignaltooceannoiseratioatlowfrequency.Theequalizercircuitisaone-polehighpassfilterwithacut-offfrequencyof3200HzanditcanbeenabledordisabledthroughtheMCU.

Figure24.NeXOSA1-PassiveAcoustics

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Thesecondchannel(CHB)doesnotalterthehydrophonepre-amplifiedsignal.Bothchannelshavealowpassantialiasingfilter.Theoperator,throughtheMCU,cansetthecutofffrequencyoftheanti-aliasingfilterdependingontheapplicationandonthesamplingfrequency.Thehydrophonesignalissampledbytwo16-bitSARconverterscontrolledbyanARMmicrocontroller.Theworkingsamplingfrequency(upto100kS/sfora1Hztonear50kHzacousticbandwidth)iscontrolledbytheMCUtimer.TheMCUprocessesthesampleddataandtransmitstheresultsonanEIARS-232serialport.A1 isequippedwithareal-timeclockthattagssampleddataandaPulsePerSecond(PPS)inputfortheGPSlink.FrequencyrangemaybeselectedbytheMCU,changingthefrequencyclockoftheantialiasingfilter. Threetypes (seeTable I)of transducersareavailable forA1,dependingontheirsensitivity,shapeandmaximumoperatingdepth.WithinNeXOS,aprototypeofA1foreachofthesetransducerswasmanufactured.Thereareanumberof significant technological innovations included in theA1implementations.Theseincludetheadjustabledynamicrangethatcancover50to180dBre1μPa,eithermanuallyorautomated.Thereisaprogrammablegainamplifierstagetoconfiguretheanaloguesignalconditioningstageforbothlowandhighsoundlevelmonitoring.Forinterfacewithplatforms,theA1hasaPUCKautomatedmanagementelementwhichenablesflexibilityforcontrollingsensoroperationsanddataflowtotheusers.Finally,thereisanoptionfortherawdatatobeconvertedtoreducecommunicationoverloads.Powerconsumptioninoperationisabout0.9Wat12to24Vdc.

A2 is a compacthydrophone system forobserving the volumetricenvironment, enablingreal-time measurement ofunderwater noise and of several soundscapesources. It consists ofanarrayoffourdigitalhydrophones(A2hyd)withEthernetinterfaceandoneMasterUnitfordataprocessing.(fig.25).A2hydsensorshavethesamecharacteristicsastheA1sensorregardingtheSignalConditioningUnit(SCU),theA/DConverter(ADC)andtheMicroControllerUnit(MCU),withthedifferenceofasmallerinternalmemory(32GB)andnointernalbattery.AJS-B100hydrophonetransducer has been selected for deep underwater application. Each of the four digital A2hydhydrophonestransmitsthedigitizedacousticdatatotheMasterUnitthroughEthernet.TheMasterUnit manages the timing synchronization of the four A2hyd sensor signals for simultaneoussampling.Thetimesynchronizationof theMasterUnitandtheslaveunits (A2hyd) isperformed

Figure25.A2-Passiveacousticarray

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usingtheIEEE1588PrecisionTimeProtocol(PTP)standard.TheMasterUnitprocessestheacousticdata.

ThesignalsfromthefourA2hydaretransferredtotheMasterUnitthroughfourunderwatercables,10mlong(allowingdiversegeometricconfigurations)thatareconnectedtothecapofanunderwaterhousing containing the Master Unit. Another underwater cable connects the housing to the userinterface for transmitting the data processed by the Master Unit. The A2 receives relevantoceanographic parameters (sound velocity, temperature, depth, time) via Ethernet, in order tooptimizethealgorithms.TheacousticarrayA2canalsobeequippedwithpositioningsensors(pan,tilt,compass)toallowthemeasurementofitsgeo-referencedpositiononrequest.Thus,ithasacapabilityofprovidingdirectionalsoundsourceinformationgivingreal-timewaveformstreamingwhenusedonplatformswithmedium-highpowerandcommunicationcapabilities.ConsistentwiththeopensourcephilosophyofNeXOS,A2offersprogrammable,opensourceconstructionandsoftwarewithRS232orEthernet connectivity. The embedded functions developed for these innovative sensors are noisestatistics (including EUMSFD indicators), mammal detection (PAMGUARD), and relevant raw datastorage in internalmemory for recovery beyond internally processed observations. These featuresmakethedigitalNeXOShydrophonesuniqueforoceanmonitoringapplications.NeXOSA1andA2allowbothindustrialandresearchapplicationsfromdiverseplatforms(e.g.,Gliders/AUVs/largerplatformsincludingdeepfixedobservingsystems)forenvironmentalmeasurementssuchasnoisefromhumanactivities(airguns,shippingnoise,etc.),ambientnoiseandbioacoustics,andseismicevents.

Table5.TransducerCharacteristicsForA1AndA2Sensors

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2.14.EAF-RECOPESCAsensorsystemHighlights:- MultifunctionalcostefficientsensorsystemthatbuildsupontheRECOPESCAconceptand

technologies- MeasuresDissolvedoxygen(STPO2)andFluorescence(STPFluo)- Includessensorfortemperaturemeasurementduringfishing- Robustenoughtobeplacedonfishinggear,self-poweredandautonomous- Modularandscalable.- OGCSensorWebEnablement(SWE)enabled(datalayer)The EAFmulti-functional sensor systembuilds upon the RECOPESCA concept and technologies byaddingnewobservationsrelevanttofisheriesmanagement.ThechallengeinNeXOSwastodevelopcostefficientsensorsthatdonotrequireanyeffortsbythefishermenandthusareself-poweredandautonomous.Also,thesensorsmustbetoughenoughtobeplacedoncommercialfishinggear.Theexisting RECOPESCA measures pressure, temperature, salinity and turbidity. It includes a haulercounter, specifically based on the ship weighting scale. A data concentrator is used to store andtransmitthedatatoashoremanagementcentreinnear-real-time.FortheEAFapplication,NeXOScreatedtwoadditionalsensors,oneforoxygenandtheotherforfluorescence,whichisaproxyforchlorophyll. These have application for both fish population assessments and as Essential OceanVariables for the operational oceanographic community. To achieve low cost, existing sensorcomponentswereevaluatedandinexpensivecomponentsofferingadequateaccuracywereselected.TheOEMtransducerselectedfortheoxygenmeasures(gasordissolvedoxygeninliquids)isthePico2byPyroScienceCompany.Themoduleutilizesameasuringprinciplebasedonredlightexcitationandlifetime detection in the near infrared using unique luminescent oxygen indicators (REDFLASHtechnology). The measuring principle is based on the quenching of the REDFLASH indicatorluminescence caused by collision between oxygen molecules and the REDFLASH indicatorsimmobilizedonthesensortipofsurface.TheREDFLASHindicatorsareexcitablewithredlight(moreprecisely:orange-redatawavelengthof610-630nm)andshowanoxygen-dependentluminescenceinthenearinfrared(NIR,760-790nm).Themeasuringprincipleisbasedonasinusoidallymodulatedredexcitation light.Thisresults inaphase-shiftedsinusoidallymodulatedemission intheNIR.The“Piccolo2”(a.k.abythemanufacturerandhereafterPico2)measuresthisphaseshift.ThephaseshiftisthenconvertedintooxygenunitsbasedontheStern-Vollmer-Theory.

TheOEMtransducerselectedasfluorometerismadebyTurnerDesigns.Itisasingle-channel,mini-fluorometerdesignedformonitoringfluorophoresinwater,asforexamplechlorophylla.Itisdesignedtobeintegratedintoamulti-parametersystemfromwhichitreceivespoweranddeliversavoltageoutputproportionaltofluorescencetothesystemdatalogger.Theexcitationwavelengthis460nmandtheemissionwavelengthis620–715nm.ThisOEMtransducerprovidesawidemeasurementdynamicrangeof0.03to500μg.L-1forChlorophyllathatcanbescaleddownbyuser-selectablegain.

Figure26.EAFsensor

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Voltageoutputcanbecorrelated toconcentrationvaluesbycalibratingwitha standardofknownconcentration.BothsensorshavebeenintegratedintheRECOPESCAsystemandthehousingcontainstheelectronicboard and the battery, able to power the sensors for several months (variable, depending onenvironmentalconditions)withoutbatteriesreplacement.Bothsensorssystemshavebeentestedandqualifiedforpressureof30baraccordingtotheFrenchstandardAFNORNFX10-812.

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3.DataManagementandStandardsWithincreasingdatasizeandtheneedtooperateonremoteplatformswithmultiplesensors,therearetremendousbenefitstostreamliningdatamanagement.Thisisanendtoendissueprogressingfromdatacreationbyasensortothesensorplatforminterfacetothecommunicationofdataintothehandsofusers.Anotherissueisstandardizationtofacilitatetheuseofsensorsacrossplatformsandtheapplicationofmultiplesensorsinasingleplatform.TheOceanofTomorrow(OoT)projectshaveall investigated and implemented solutions for data and metadata standardisation followinginternationalstandardsproducedbytheopengeospatialconsortium(OGC)and/ortheWorldWideWeb Consortium (W3C). The four 2013 Topic 2 projects had requirements that differed slightlybecause,insomecases,theDoW/technicalAnnexincludeddevelopmentofplatformsorinformationsystemsinadditiontosensors.Assuch,theOoTprojectscoveredabroadrangeofdatatechnologiesthat are reflected in this consolidated recommendation. The overarching requirements fromeachprojectaresummarisedinTable6.Table6.SummaryofoverarchingrequirementsfordataforeachOoTproject.

OoTproject Requirements

COMMONSENSE Interoperabilitywithindevicesandhardwareaggregator(SmartSensorUnit(SSU))byimplementingNMEA2000protocol.

Interoperability-focuseddataandinformationflowfromsensortouserbasedonOGCstandardsincludingSOS,SensorMLandO&M

Inthegateway,theNMEAdataisautomaticallyprocessedandtransformedintotheO&Mdataformat

Opensource52°NorthimplementationofSOS2.0wasdeployed 3differentconnectiontypes:A)real-timedatastream;B)offlinedataupload;C)DevicesnotconnectedtotheSSUandwhodonotsupporttheNMEAformat:atransformationtoolwasdevelopedinPython

Userinterfacetovisualizedata.ThisisbuiltusingOpenLayersandGeoServer,andalsousestheWebMapService(WMS)standard

NeXOS Interoperability-focuseddataandinformationflowfromsensortouserbasedonOGCstandardsincludingSOS,SensorMLandO&M

Integrationofmultiplesensorsonaplatform

Remotesensormanagement(OGCSPS)

Usernotificationcapabilityfordata(OGCSAS)

Plug’n’playoperationswithembeddedSensorML(OGCPUCKandSEISI)

Protocolstoreducedatatransmissionvolumethroughefficientdatacompression(EXI)

SensorMLeditorforfacilitatinguseofSensorML(Smle)

Userinterfacetovisualizedata

SCHeMA Interoperability-focuseddataandinformationflowfromsensortouserbasedonOGCstandardsincludingSOS1.0,SensorMLandO&M

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Integrationofmultipleplug&playsensorsonaplatform(OGCSWE)

Sensorcommandeditorandremotesensormanagementandplanning(SensorMLandSPS)

Notificationserviceforsystemerrorsandwarnings(SAS)

Userinterfacetovisualizedata

Userinterfacetoqualifyandflagdata(qualitycheck/qualityflag)

SenseOCEAN Exposureofmetadata&dataviaOGCSWEstandards(SOS,SensorML,O&M)

INSPIREcompliantdataandmetadataexposure

W3CLinkeddatacompliantmetadataexposure

Thecapabilitytouniquelyidentifyasensorenablingplugandplayoperationonlowbandwidthsystemsandlegacyobservationplatforms

TheOoTprojectshavemadea significantcontribution todata standardisationandservicesacrossEuropeproducing“successstories”.Highlightsare:

● TheformationofandcontributiontotheSWEMarineProfilescommunity.ThiscommunityincludesEuropean,AustralianandUSAmembershipandisformingcommondatatemplatesandstandardsforusewithinthemarinecommunity.

● SemanticenrichmentofSensorMLandO&Mmakingthesestandardstruelymachinereadableinthemarinedomain

● ThedevelopmentofcommonSWEsoftwaresolutionsby52North● ThecreationoftoolstofacilitatetheuseofSensorMLandSOSsuchasSmlePublished

controlledvocabularies.

Thesesuccess storiesexemplify the impacts that theOoThavenotonlyonEuropeanprograms inoceanobservations,butonEurope’sroleasagloballeaderindatainteroperabilityandimproveddataaccess.The impactsare in reducing thecostsandcomplexityofobservingoperationsbecause thedevelopmentsallowreadyinterfacesbetweensensorsandplatforms(reducinglaborandimprovingreliability). They also facilitate access by researchers tobothdata and information (improving theoutcomes of investment in observations). The use of OGC and W3C standards along with theinnovationsoftheOoTprojectsaddresscriticalbottlenecksintheflowofinformationfromsensorstouserssuchasthelimitationsofcommunicationbandwidthsforIridiumsatelliteservices.Ultimately,theabilitytohavedatainteroperableenhancesthecomparisonofobservationsofdiversecharacterand discipline, creating an environment for new research outcomes. These benefits come fromwidespreadadoptionoftheOoToutcomesalongwithcontinuedadvancesinthetechnologyanditsadaptationtoobservationapplications.Thedatarecommendationsreflectthenextsteps.The following text describes the data recommendations for different aspects covered by theOoTprojectsandisdividedintothefollowingsections:

● AsummaryofstandardsimplementedbytheOoTprojectswithjointrecommendationsandlessonslearned

● AsummaryofstandardsthatemergedduringtheOoTprojectwithrecommendations● AclosingsectiononresearchprioritiesbeyondtheendoftheOoTprojects

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3.1.StandardsimplementedbytheOceanofTomorrowprojects

3.1.1.StandardsimplementedbyOoTprojects

TheimplementedOGCStandardsbytheOoTprojectsintheOGCSensorWebEnablementSWEframework(http://www.opengeospatial.org/ogc/markets-technologies/swe)were:

● Observations&Measurements(O&M)–ThegeneralmodelsandXMLencodingsforobservationsandmeasurements.

● PUCKProtocolStandard–DefinesaprotocoltoretrieveaSensorMLdescription,sensor"driver"code,andotherinformationfromthedeviceitself,thusenablingautomaticsensorinstallation,configurationandoperation.

● SensorModelLanguage(SensorML)–StandardmodelsandXMLSchemafordescribingtheprocesseswithinsensorandobservationprocessingsystems.

● SensorObservationService(SOS)–Openinterfaceforawebservicetoobtainobservationsandsensorandplatformdescriptionsfromoneormoresensorsattachedtoaplatform.

● SensorPlanningService(SPS)–Anopeninterfaceforawebservicebywhichaclientcan1)determinethefeasibilityofcollectingdatafromoneormoresensorsand2)submitcollectionrequests.

● SensorAlertService(SAS)providenotificationofeventssuchasmeasurements,sensoranomalies,observationactions

● SmartSensorInterfaceforSensorsandInstruments(SEISI)-SEISISensorSystemssupportbothapull-baseddataaccessinterface(i.e.basedontheSOSstandard)aswellasapush-mechanismfordeliveringdataintoobservationdatabasesonnearrealtime.

● EfficientXMLInterchange(EXI)–BinaryencodingandcompressionofXMLforefficientexchange.

TheimplementedW3CstandardsbytheOoTprojectswere:● SemanticSensorNetwork(SSN)–Ontologyfordescribingsensorsandtheirobservations.● ResourceDescriptionFramework(RDF)-StandardmodelfordatainterchangeontheWeb.● SPARQLProtocolandRDFQueryLanguage(SPARQL)-AnRDFquerylanguage,thatis,a

semanticquerylanguagefordatabases,abletoretrieveandmanipulatedatastoredinRDFformat.

TheimplementationofthesestandardsbyOoTprojectsaredescribedinTable7.Table7.SummaryofthestandardsimplementedbytheOoTprojects OGC W3C OoTproject O

&M

PUCK

SensorML

SOS

SPS

SAS

SESI

EXI

SSN

RDF

SPARQL

COMMONSENSE ✓ ✓ ✓ NeXOS ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ SCHeMA ✓ ✓ ✓ ✓ ✓ ✓ SenseOCEAN ✓ ✓ ✓ ✓ ✓ ✓

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3.1.2.Recommendationsonimplementedstandards

MarineSWEprofilesSeveraloftheOoTprojectsmadesignificantcontributionstothedevelopmentofmarineSWEprofilesgroup (originally initiated by EU projects ODIP and ODIP2) that can harmonize how OGC SWEstandardsareappliedinmarineapplications.Thehighlevelofinterestinachievingthisisreflectedbythenumberofsubscriberstothemailinglistcoordinatingtheseefforts(ca.100users).EvolutionofMarineSWEprofileshasresultedinabroadsetofrecommendationsforfurtherSWEdevelopment:

● FurtherpromotetheapplicationofinteroperableSensorWebstandardsamongsensormanufacturers,operatorsanddataconsumer(aprojectsuchasadedicatedH2020CSAwouldbetheidealplatformforthiswork)

● Createarepositoryforbestpracticesthatallowseasydiscoveryandaccess.● EvaluatethecurrentstateofMarineSWEProfilesthroughfirstimplementations(e.g.

interoperabilitydemonstrationsbetweenprojects).Theseresultsshouldserveasinputforimportantupdatesandevolutionofprofiles

● DecideonacollaborativeplatformtoallowthedistributededitionandpublicationoftheMarineSWEProfilesdocumentation

● Maintaintheuseofvocabulariesandallowuserstocreatetheirownterms● Implementintegrationtestsfordiscoverability,interoperabilityandpresentationofthe

sensor/observationdescriptionsoriginatingfromdifferentSOSserversimplementingtheSWEMarineprofiles

● Profilesspecifictoadisciplineorapplicationarerequiredatthesyntaxicalandsemanticlevelsofinteroperability.Itisrecommendedthatworkcontinuestocoordinateand supportthecreationofamarinecommunityprofileforSOS,O&MandSensorMLtofacilitatebetterinteroperability.

● ProduceevaluationtoolsthatwilltakeintoconsiderationthecommonprofilesandtheSWEVocabularies

● ConsidertheMarineSWEProfilesineditors(generationofstandardisedcontent),servers,andclientapplications(ensuringconsistentinterpretations)

● InvestigatetheusageofREST/JSONbindingforcurrentstandards● OfficialextensionoftheINSPIREDirectivetosupporttheOGCSensorObservationService

2.0.Thefinedetailsofsensordataharmonisationandinteroperabilityareofaverytechnicalnature,whichinthelongtermfacilitatesmorecost-effectivemonitoringprogrammes,dataaccess,anddatapreservation.ThecontinuedimplementationoftheINSPIREDirectivetosupportinteroperabledatadiscovery,datavisualisation,datadelivery,anddataprocessingisaveryimportantpolicyinitiativetounderpinthis.ConsiderationshouldbegiventotheofficialextensionoftheINSPIREDirectivetosupporttheOGCSensorObservationService2.0(SOS)asadatadownloadserviceoptionwithclearimplementationguidelines.

SensorMLTheOoTprojectshaveidentifiedspecificrecommendationsforSensorML

● EnablesemanticinteroperabilityofSensorMLviatheadoptionofcontrolledvocabulariestodefinetermsandvaluesinSensorML;IntegratetheuseofvocabularyserversforselectingdefinitionsandvaluesofSensorMLelements

● ContinuetheworkonrefiningSensorMLdescriptionsaspartoftheMarineSWEProfilesWorkingGroup

● ImprovethecurrentlyavailabletoolsforeditingSensorMLbyoptimizingtheirusability● EnhancethesupportofSensorMLtemplatesforsensortypedescriptions(i.e.SensorML

typeOfelement)● Addmorecomfortablegraphicalelementstomodelpart-ofrelationships● InvestigateinteroperablesolutionsforstoringandmanagingSensorML-basedmetadata(i.e.

goingbeyondthemetadataqueryfunctionalityoftheOGCSOSinterface)

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LinkeddataTherecommendationsbeloworiginatefromtheexperiencesoftheSenseOCEANproject.

● Standardizedontologiesshouldbereusedasmuchaspossibletofacilitateinclusionandexpansionofthewebofdata.Thereareseveralwell-knownontologies,manypublishedbyW3C,thatprovidetheartefactsneededtoessentiallydescribesensordataandmetadata

● Reusecontrolledvocabulariesperdomainandcommunity● Publishmoreworkingexamples,successstoriesandapplicationsofLinkedDatato

demonstratethepowerofLinkeddata.● Createalistofproposedcommonlyusedandapprovedontologiesandcontrolled

vocabulariestobeusedbytheLinkeddatacommunity.● Usestandardisedvocabulariesforstandardtermse.g.useNERCVocabularyServerv.2.0

(NVS2.0)forthemarinedomain.Unitofmeasureandobservablepropertiesaredomainswhereuserstendtogetconfusedordissatisfied.WechosetheP01andP06vocabulariesofNVS2.0

● TomodelsensormodelsandinstancesinSSNuseW3Cgoodrelationsontologyandschema.org.Schema.orgvocabularyisbestusedthoughthroughRDFa,MicrodataorJSON-LDformats

AccesscontrolofdataandcybersecuritySignificant gapswere identified inbothaccess controlwhen focusingonopendataand the cybersecurityofwebservicesimplementedbytheOoTprojects(usingOGCandW3Cstandards).Tofurtherthisworktherearesomeoverarchingrecommendations:

● DraftrequirementsonSensorWebaccesscontrolmechanisms● EnhancetheMarineSensorWebProfilesactivitieswithrecommendationsonhowaccess

controlwithinSensorWebinfrastructuresshallbeenabled.Forthispurpose,werecommendinvestigationofpossibleapproachestoenhancetheOGCSOSinterfacewithfine-grainedaccesscontrolmechanismsatmultiplepointsinthedataflow.

PersistentIdentifiers(PIDs)forinstruments,platformsanddeploymentsTheneedtoassigngloballyuniqueandresolvablepersistentidentifierstoinstruments,platformsanddeploymentswasidentifiedandisbeingpursuedwithinanewResearchDataAllianceworkinggroup(https://www.rd-alliance.org/groups/persistent-identification-instruments). Their overarchingrecommendationsare:

● Developtheuseofauniversalpersistentidentifierschemaforactivedevices● Recommendametadataprofiletodescribeactivedevicesthatharmonisesexisting

identificationstandardsandcomplementsexistingmetadataschemas● Exploremethodology/technologytoregisterandresolvethenewPID● Operationalisethesolution,engaginginstrumentdevelopersandmanufacturersinthe

process

3.2.EmergingstandardsOverthecourseoftheOoTprojects,newstandardsandservicesemerged.ThesestandardsarecloselyrelatedtoorbuiltonthoseimplementedwithintheOoTprojects.Consequently,theOoTprojectsarewellplacedtoidentifygapsinknowledgeandrecommendelementsthatneedpursuingfurther.Asanexample,amajordevelopmentistheintroductionoftheInternetofThings(IoT).Thisreferstotheuseofintelligentlyconnecteddevicesandsystemstoleveragedatagatheredbyembeddedsensorsandactuatorsinmachinesandotherphysicalobjects.Addingintelligencetosensors(suchaswiththePUCKcapabilitymentionedearlier)isaprocessthathasbeenstartedandshouldcontinue.

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EmergingOGCstandardsandprotocolsconsideredinthecontextoftheOoTprojects:

● SWECommonDataModel–Defineslow-leveldatamodelsforexchangingsensorrelateddatabetweennodesoftheOGCSensorWebEnablement(SWE)framework.

● SWE Service Model -– Defines data types for common use across OGC Sensor WebEnablement(SWE)servicesincludingoperationrequestandresponsetypes.

● SensorThings API - OGC standard specification for providing an open and unified way tointerconnectIoTdevices,data,andapplicationsovertheWeb.

OtheremergingstandardsandprotocolsconsideredinthecontextoftheOoTprojects:

● MQTelemetryTransport(MQTT)-Itisapublish/subscribe,extremelysimpleandlightweightmessaging protocol, designed for constrained devices and low-bandwidth, high-latency orunreliablenetworks.

3.2.1.RecommendationsonApplicablestandardsthatemergedduringtheOoTprojectsLinkingtoIoTtechnologiesTherearecurrentlyseveralactivitiesintheInternetofThingscommunitywhichmaybeconsideredascomplementary enhancements of the established Sensor Web architectures. The OoT projectsrecommend that these are pursued in addition to the OGC and linked data technologies alreadyinvestigated.Specifically:

● EvaluatetheapplicabilityofIoTprotocols(e.g.MQTT,AMQP,COAP,LoRaWAN,etc.)tomarineapplications:Althoughfirstevaluationsareperformedaspartofongoingprojects(e.g.ODIPII),thecomplexityofthistopicrequiresdedicatedworkitems/workpackagesaspartofnewresearchprojects.

● EvaluatetheOGCSensorThingsAPI(http://ogc-iot.github.io/ogc-iot-api/):Thisworkshouldbeperformedonashort-termbasis.ArecommendationistoenhanceexistingSensorWebimplementations(e.g.thoseusingOGCSensorObservationService)withadditionalSensorThingsAPIsupportaswellassupportofregularREST-andJSON-bindingsoftheOGCSensorObservationServiceandISO/OGCObservationsandMeasurementsstandards.Theavailabilityofbothtypesofimplementationwouldbethebasisforascientificallysoundcomparisonandimplementation.

● EvaluatetheWebofThingsforIoT(https://www.w3.org/WoT/)● EnhancetheguidanceonMarineSensorWebProfileswithrecommendationsonInternetof

Thingstechnology:TheresultsofthepreviouslyexplainedevaluationactivitiesshouldbereflectedasdedicatedchaptersoftheMarineSensorWebProfilesBestPracticedocumentation.

SensorplugandplayTheNeXOSprojectmadeprogresswithPlugandplayusingPUCKbasedstandardswhileSenseOCEANusedGloballyUniqueIdentifiers(GUID)toimplementplugandplay.SignificantworkisneededtoaligntheseeffortswiththeIoTandenablewebresolvableuniqueidentificationofsensors.ThisworkwouldbeconsistentwiththePIDdirectionsmentionedabove,

● InvestigatemechanismsfortaskingsensorsfromthesensorwebbasedonthetransportationofaSensorMLfilefromtheusertothesensorinordertomodifysensorparameters.

● Investigatehowtotrackandimplementchangesinsensorcharacteristics(settingsforgainortiming)ontheSensorMLasafunctionoftime.IftheinstrumentconfigurationisstoredinsideasensorMLfile,whenthissensorMLfilechangesduetoachangeontheinstrumentconfiguration,ithastobereflectedonthedata.Modificationsoftheinstrumentconfigurationhavetobeavailableasmetadatawiththeinstrumentdata.DefineaprocessandsustainablerepositorytomaintainhistoryofSensorMLfiles.

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PushbasedcommunicationflowsPushtechnology,orserverpush,isastyleofInternet-basedcommunicationwheretherequestforagiven transaction is initiatedby thepublisher or central server as opposed topull/get,where therequest for the transmission of information is initiated by the receiver or client such as the SOSprotocolusedintheIoTprojects.

● InvestigateaprofilefortheOGCPublish/SubscribestandardthatistailoredtotheneedsofmarineSensorWebapplications.TheresultsofthisworkshouldbepublishedasanewtopicwithintheMarineSensorWebProfilesbestpracticedocumentation.Duetothecomplexityofthistask,thisactivitycanbeinitiatedaspartofcurrentprojects(e.g.BRIDGES).However,thisquestionshouldbeasignificanttopicinfutureresearchprojects.

● AddresstheexpansionandfurtherimplementationoftheSEISIdevelopedinNeXOS.● Evaluatetheuseofpushbasedcommunicationpatternsthroughbandwidthconstrained

links● Evaluatetheapplicabilityofeventstreamprocessingtoolstomarineapplicationscenarios

anddevelopexemplaryimplementationsforselectedusedcases.● DevelopPublish/SubscribeextensionsforexistingOGCSOSservers.

WebprocessingservicesTheIoTprojectshaveproducedOGCendpoints.CommunitiessuchasEMODnetneedtobeabletoaggregate results of these services in order to produce data products. The SWE service model,commondatamodelprovidesaframeworkforsuchaggregation.

● InvestigatethecouplingofmarineSensorWebservices(e.g.SOSserverscomplyingtotheMarineSWEProfilesrecommendations)toOGCWebProcessingServiceinstance.Thisshouldberealisedasasetofdemonstratorsshowingthedynamicintegrationofdifferentobservationdatasourcesandprocesstypes.

DiscoveryofSensorWebResourcesAnaturalextensiontotheexposureofdataandmetadatatowebviaOGCstandardsistoenablecross-disciplinary discovery via search engines. Long terms, with standardised data, would enable thegeneric aggregation andproductionof data products. There is significant development needed tomovetheworkfromOoTprojectsintobroaderusebythemarinedomain:

● DemonstratetheharvestingofmarineSensorWebmetadatabytraditional(google)andspecializedsearchenginesbybuildingdedicatedtoolsthatmakeuseoftheMarineSensorWebprofilesasmetadatafoundation.

● ExploretheuseofLinkedDatatodiscoverSensorWebresources(e.g.LinkedDatalayerontopofSensorWebinfrastructures)

● IntegratediscoveryfunctionalityintoSensorWebviewerstoenableadynamicbindingofservicesandclientapplications.

● LinkSensorWebmetadataharvesterstomarinedatainfrastructuresandportals.● Investigatelight-weightdiscoverytoolsfortheSensorWebthatofferalowcomplexityin

theiruserinterface(comparabletoaGooglesearchfortheSensorWeb).

3.3.PrioritiesforfutureresearchidentifiedbytheOoTprojectsTheOoTprojectshavemadeasignificantcontributiontothestandardisationofmetadataanddataonthewebandtherearekeyactivitiesthatwebelieveshouldbesustained.TheMarineSWEprofilesgroupshouldcontinuetosupportformalandbroaderadoptionoftheprogressmadeintheMarinedomaintoreducethelikelihoodofduplicationoftheseefforts(aprojectsuchasadedicatedH2020CSA would be the ideal platform for this work). Formulation and publication of best practicedocumentsthroughactivitiessuchasODIPorAtlantOSareamechanismtoachievethisbutnotalong-termsolution.

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The standards developed need formalisation andmaintenance to be applied on their constituentelements: maintenance and enhancement of controlled vocabularies as a base for continuedevolution;andcreationandmaintenanceofaneasilysearchableontology-basedrepositoryofmarinedata best practices for broader access and increased adoption of these practices by the marinecommunity.This work has begun and was announced on at the Plenary meeting of the Research Data Alliance (https://www.rd-alliance.org) last week and the objective is a semantic look up service of ontologies on diverse domains (https://bsceudatwp8.bsc.es/).TodatetherehasbeenlittleuptakeofOGCandW3Cstandardsbysensormanufacturersforseveralreasons.Thedataandprotocolstandardshavebeeninconstantfluxforadecade,developmentofstandardsisnotwidelyknowninthecommunitythatpurchaseequipment.Hence,standardiseddatahasnotbeenarequirementincallsfortenders,andcommontoolsforstandardformat(e.g.SensorML)editors have beenmissing. Once best practices are published, common tools exist and standardsproducesuccessstories,sensormanufacturerscanbeinvitedtoprovideinformationaboutthesensormodels they produce/sell, that will be identified by unique identifiers and resolved in standardmetadataformats.TherearealsoseveralgapsclearlyidentifiedbytheOoTprojectsthatneedresearchanddevelopmentactivity before best practice can be defined: developing persistent identifiers forsensors/platforms/deploymentstoenabletheirunambiguousandwebresolvableidentificationwithconnectionstodigitalobjectidentifiersDOIs,thatarebeingusedtoidentifydatasetsandpublications;workingtowardscommondataandservicelevelspolicy(servicelevelagreement,usersrights,datacitation,datause,securityetc.);and improvingdataavailability intomajorEU infrastructures andrepositories(e.g.EMODnet,CMEMS,SDN).Theemergingstandardssuchas IoTareata levelofmaturitysimilar to thatof theOGCandW3Cstandards prior to their enhancement by the OoT projects. Further research and development isneededtoassessthesestandardsagainsttherequirementswithinthemarinedomainandthisshouldbethepriorityforthesestandards.Thiswoulddeterminetheirapplicabilityinthemarinedomainandtheenhancementsthatwouldberequiredtoenabletheirbroaderadoption.TheOoTprojectshaverightly focusedonthemarinedomainandtheir recentdevelopmentsneedsharingtoexpandthedatadiscoverytobroadercommunitiessuchastheatmosphericcommunityorthepublic.Oneapproachmaybetoinvitesearchengineexpertslikegoogletoalignmarinestandarddevelopmentswithworkplannedinthisdomain,thiswouldrequirenewmajorresearchprojects

3.4References[1]Del-Rio-Fernandez,J.(2013).Standards-BasedPlug&WorkforInstrumentsinOceanObservingSystems.OceanEngineering,39(3),430–443.https://doi.org/10.1109/JOE.2013.2273277

[2]Jirka,S.,&Del-Rio-Fernandez,J.(2017).SWE-basedObservationDataDeliveryfromtheInstrumenttotheUser-SensorWebTechnologyintheNeXOSProject.InGeophysicalResearchAbstractsVol.19,EGU2017-7769,2017EGUGeneralAssembly2017.Retrievedfromhttp://meetingorganizer.copernicus.org/EGU2017/EGU2017-7769.pdf

[3]Toma,D.M.,DelRio,J.,Jirka,S.,Delory,E.,&Pearlman,J.(2014).Smartelectronicinterfaceforwebenabledoceansensorsystems.In2014IEEESensorSystemsforaChangingOcean,SSCO2014.https://doi.org/10.1109/SSCO.2014.7000375

[4]Del-Rio-Fernandez,J.(2017).OceanEngineering."ASensorWebArchitectureforIntegratingSmartOceanographicSensorsintotheSemanticSensorWeb”.(DOIpending).

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[5]Bigagli,Lorenzo,andMatthesRieke."ThenewOGCPublish/SubscribeStandard-applicationsintheSensorWebandtheAviationdomain."OpenGeospatialData,SoftwareandStandards2.1(2017):18.

[6]Jirka,Simon(2013).DiscoveryMechanismsfortheSensorWeb.Amsterdam(TheNetherlands)/Berlin(Germany),IOSPress/AKAVerlag.

[7]Müller,MatthiasandBenjaminProß(2015).OGCImplementationSpecification:WebProcessingService(WPS)2.0.0(14-065).Wayland,MA,USA,OpenGeospatialConsortiumInc.

[8]Stasch,C.,Pross,B.,Gräler,B.,Malewski,C.,Förster,C.,&Jirka,S.(2017).Couplingsensorobservationservicesandwebprocessingservicesforonlinegeoprocessinginwaterdammonitoring.InternationalJournalofDigitalEarth,1-15.

[9]Kokkinaki,A.,Darroch,L.,Buck,J.&Jirka,S.(2016).SemanticallyEnhancingSensorMLwithControlledVocabulariesintheMarineDomain.InProceedingsofGSWC2016,GeospatialSensorWebsConference,Munster,Germany,August29-31,2016.CEURWorkshopProceedings,ISSN1613-0073[online]http://ceur-ws.org/Vol-1762/Kokkinaki.pdf

[10]KokkinakiA.,Buck,J.&Darroch,L.(2016).Asemanticallyrichandstandardisedapproachenhancingdiscoveryofsensordataandmetadata.InGeophysicalResearchAbstractsVol.18,EGU2016-12970,2016EGUGeneralAssembly2016.Retrievedfromhttp://meetingorganizer.copernicus.org/EGU2016/EGU2016-12970.pdf

[11]J.R.Hobbs,F.Pan,TimeOntologyinOWL,WorldWideWebConsortium,2006,Availableat:http://www.w3.org/TR/owl-time/.

[12]D.Brickley,W.S.W.I.Group,BasicGeo(WGS84lat/long)Vocabulary,2004,Availableat:http://www.w3.org/2003/01/geo/.

[13]NovellinoA.,BenedettiG,D’AngeloP,ConfalonieriF,MassaF,PoveroP,Tercier-WaeberML(2016).SCHeMAweb-basedobservationdatainformationsystem.GeophysicalResearchAbstractsVol.18,EGU2016-6500,2016EGUGeneralAssembly2016.Retrievedfromhttp://meetingorganizer.copernicus.org/EGU2016/EGU2016-6500.pdf

[14]Pearlman,J.,Jirka,S.,delRio,J.,Delory,E.,Frommhold,L.,Martinez,S.,andO”Reilly,T.(2016)OceansofTomorrowSensorInteroperabilityforIn-situOceanMonitoring,Oceans2016MTS/IEEEMonterey,IEEEXplore,DOI:10.1109/OCEANS.2016.7761404

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4.ContributionstoMSFDandSDGsThefourprojectsaddressanumberofvariablesrelevanttoseveraldescriptorsoftheMarineStrategyFrameworkDirectiveandindicatorsoftheUnitedNationsSustainableDevelopmentGoals(SDG14).SDG14referstotheconservationandsustainableuseoftheoceans,seasandmarineresources.TheGoaldefinesanumberoftargetsandindicators.Theseindicatorslinktargetstoquantitativevalues,establishingclearmeansofprogressevaluation.Thecontributionsofthefourprojectsaresummarizedinthefollowingtables.ProjectsvsSDG14Indicators COMMONSENSE NeXOS SCHeMA SenseOCEAN

14.a.1Budgetallocationtoresearchinthefieldofmarinetechnologyasapercentageoftotalbudgetforresearch

4,7M€budget11(incl.3,4M€ECcontr.)

8,1M€budget(incl.5,9M€ECcontr.)

6,7M€budget(incl5,2M€contr.)

8M€budget(incl5,9M€ECcontr.)

14.2.1*Percentageofcoastalandmarinedevelopmentwithformulatedorimplementedintegratedcoastalmanagement/maritimespatialplanningplans(…),basedonanecosystemapproach(…)

Waterquality(incl.MSFDGES)Environmentalimpactmonitoring12

14.3.1Averagemarineacidity(pH)measuredatagreedsuiteofrepresentativesamplingstations

CarbonCycle CarbonCycle Carboncycle

14.5.1Coverageofprotectedareasinrelationtomarineareas Costeffectivesensors13andplatforms

ProjectsvsMSFDGESDescriptors COMMONSENSE NeXOS SCHeMA SenseOCEAN

Descriptor1Biologicaldiversityismaintained.Thequalityandoccurrenceofhabitatsandthedistributionandabundance(…)

BioacousticsPhytoplanktonFisheries(EAF)

Phytoplankton Phytoplankton

Descriptor3Populationsofallcommerciallyexploitedfishandshellfisharewithinsafebiologicallimits,exhibitinga(…)

Fisheries(EAF)

Descriptor4Allelementsofthemarinefoodwebs,totheextentthattheyareknown,occuratnormalabundanceanddiversity(…)

Nutrients PhytoplanktonCarboncycle

PhytoplanktonNutrientsCarboncycle

PhytoplanktonNutrientsCarboncycle

Descriptor5Human-inducedeutrophicationisminimised,especiallyadverseeffectsthereof,suchaslossesinbiodiversity,(…)

CDOMOxygenPhytoplankton

OxygenNutrientsPhytoplankton

OxygenNutrientsPhytoplanktonCDOM

Descriptor7Permanentalterationofhydrographicalconditionsdoesnotadverselyaffectmarineecosystems.

Pressure,TemperatureNutrients

Pressure,temperaturePhytoplanktonOxygen

TemperatureTurbidityNutrientsPhytoplankton

TemperatureNutrientsPhytoplankton

Descriptor8Concentrationsofcontaminantsareatlevelsnotgivingrisetopollutioneffects.

Heavymetals/tracemetals

Dissolvedhydrocarbons

Heavymetals/tracemetals

Hydrocarbons

Descriptor11Introductionofenergy,includingunderwaternoise,isatlevelsthatdonotadverselyaffectthemarineenvironment.

Underwaternoise

UnderwaternoiseBioacoustics

11EuropeanCommissionandMemberStates,percentageoftotalcontributionnotprovided.12Spatialplanninginvolvesobserving.Projectscontributetotheavailabilityoftechnologicalsolutionsforthemonitoringofareasbeforeactivitiestakeplace,andtocontroltheactivityonceitisinplace.13Theprovisionofcost-effectivesensorsisexpectedtocontributeincreasecoverageandresolutionthroughthescalingupofobservingsystempresenceintheocean,includingprotectedareas.