Marine phytoplankton and sea-ice initiated convection drive spatiotemporal differences in Arctic summertime mercury rebound

Domain: earth_science
Published: 2025-07-02
Editorial outcome: major_revision

Abstract
Gaseouselementalmercury(GEM)concentrationsintheArcticexhibitadistinctreboundduringthesummermonths,withnotablespatiotemporalvariationsobservedinthisphenomenon;however,theunderlyingmechanismsremainpoorlyunderstood.OnthebasisoftargetedcruiseobservationsfromtheBeringStraittotheNorthPole,thisstudycapturedthesummertimeGEMreboundinthePacificsectoroftheArcticOcean.Moreover,weidentifiedsynchronousincreasesindissolvedgaseousmercury(DGM)concentrationsduringtheGEMreboundintheMarginalIceZone(MIZ).CombinedwithGeneralizedAdditiveModel(GAM)simulations,weconfirmthatoceanicmercuryemissionsfromtheMIZcontributetothisphenomenon.Wealso-showthatthespatiotemporalvariabilityofdissolvedorganiccomponentsassociatedwithphytoplankton,alongwithlocalatmosphericconvectiontriggeredbysea-icemeltingintheMIZ,playsacrucialroleintheobservedspatiotemporaldifferencesintheGEMrebound.InthecontextofrapidArcticwarming,withexpectedincreasesinprimaryproductivityandmorefrequentlocalconvection,theair‒seaexchangeofmercuryislikelytointensify,amplifyingthesummertime“mercurysource”effectintheArcticOcean.

Introduction
Mercury(Hg)isaglobalpollutantwithsignificantneurotoxiceffects.Whenemittedintotheatmosphere,Hgcanbetransportedoverlongdistancesthroughatmosphericcirculation,leadingtoitsdepositionandbioaccumulationinbothterrestrialandaquaticecosystems.Thisposes a serious threat to the ecological environment and human health1,2.TheArcticplaysacriticalroleasasinkintheHgcyclewithin the Northern Hemisphere. The latest Arctic Monitoring and AssessmentProgram(AMAP)Report(2021)indicatesthatpeoplelivingnear theArcticCircleexperiencesomeofthehighestlevelsofHgexposure in the world3,4. Additionally, certain wildlife in the Arctic are highly vulnerabletoHgexposureduetothebioaccumulationofHginArctic foodwebs5.

TheexchangeofHgbetweentheoceanandtheatmospheresignificantlyinfluencestheHgbudgetintheArctic.AccordingtoAMAP (2021),atmosphericHgdepositioncontributes~65Mg/aofHgtothe ArcticOcean,farsurpassingriverine(41Mg/a)andcoastalerosion(39 Mg/a)inputs3.Arecentmodelingstudyreportedasimilaratmospheric Hg deposition flux in the Arctic Ocean (70.4 Mg/a), with 39 Mg/a depositedtotheopenocean,27.4Mg/adepositedtosnow,and4.0 Mg/a deposited to sea-ice. This confirms that atmospheric Hg depositionisthelargestHgsourceintheArcticOcean6.Furthermore, theopenoceanandseasonalsea-icemeltingintheArcticOceanleadto theHgevasionfluxof24.9Mg/aand27.8Mg/aintotheatmosphere, respectively,muchhigherthananthropogenicHgemissions(14Mg/a) and biomass burning Hg emissions (8.8 Mg/a) in the Arctic7. Thus, understanding the Hg cycle at the air‒sea interface and its driving mechanisms is crucial for more accurately assessing the ecological impactofHgintheArctic.

Atmosphericgaseouselementalmercury(GEMorHg(0))inthe Arctic exhibits unique seasonality, characterized by a springtime minimum due to atmospheric mercury depletion events (AMDEs), followedbyanoticeablesummertimeGEMreboundthatcanexceed NorthernHemispherebackgroundconcentrations(1.58±0.31ng/m3)8. Earlierstudiesproposedseveralpotentialmechanismsforthissummertime GEM rebound, including long-range transport of anthropogenicHg9,re-emissionofHgdepositedonsea-iceandsnowpacks duringAMDEs,andoceanicHgevasionfromterrestrialHginputs(such as rivers and coastal erosion) around the Arctic Circle10–12. A subsequentisotopicstudysuggestedthattheenhancedsummertimeGEM concentrations were primarily due to re-emissions from the Arctic cryosphere, with a minor role from terrestrial Hg emissions13. Our recentGEMobservationsduringtheMultidisciplinaryDriftingObservatoryforArcticClimate(MOSAiC)expeditionrevealedthatelevated GEM concentrations in summer are not uniform across the Arctic OceanbutarepredominantlyfoundintheMarginalIceZone(MIZ). Thisphenomenonmaybedrivenby(1)thehighloadofdivalentHg (Hg(II))intheMIZduetomeltingicewaterinput,(2)thehighreductioncapacityofHg(II)intheMIZfacilitatedbyelevatedphytoplankton biomass,and(3)increasedsea‒airexchangeduetosea-icemelting14. ThesefactorslikelycontributetothesummertimeGEMreboundinthe Arctic14. However, the simultaneous measurements of Hg(0) in the surfaceoceanoftheMIZ,akeypieceofevidenceforthismechanism, remainlacking.Additionally,thesummertimeGEMrebounddisplays clear seasonality and spatiotemporal variation, often peaking from mid-JulytoearlyAugust,followedbyagradualdeclineandlevellingoff aftermid-August14.Thereasonsforthesespatiotemporalvariationsare stillunclear.

Aspartofthe13thChineseNationalArcticResearchExpeditionin 2023,weconductedlarge-scale,synchronizedcruiseobservationsof Hg(0) in both the atmosphere and surface ocean, from the Bering StraittotheNorthPole(90°N)intheArcticOcean.Thisstudyaimsto addresstheseunresolvedquestions,contributingtoabetterunderstanding of oceanic Hg emissions in the Arctic MIZ and the atmosphericHgcyclemechanismsintheArcticmarineboundarylayer.

Results
SummertimeGEMreboundinthePacificsectoroftheArcticOcean
Regarding temporal variation, the GEM observations indicated significantconcentrationfluctuationsfromlateJulytomid-August,with several concentration peaks. The highest recorded concentration reached2.08ng/m3inlateJuly(Fig.1a).Weidentifiedthreedistinct episodesofsubstantialGEMreboundsduringthisperiod,characterizedby:(1)sustainedincreasesinGEMconcentrationswithtemporal thresholds (initial/terminal concentrations) exceeding the cruise’s meanvalue(1.28±0.20ng/m3),and(2)peakmagnitudessurpassing theNorthernHemispherebackgroundreferencelevel(1.58±0.31ng/ m3)8. These episodes are defined as the Arctic summertime “GEM rebound”phenomenoninthisstudy(grayshadedareasinFig.1a,with episode1occurringfromUTC2023/7/280:00to2023/8/10:00;episode2occurringfromUTC2023/8/320:00to2023/8/618:00;and episode3occurringfromUTC2023/8/130:00to2023/8/150:00).In late summertime (mid-August to mid-September), the GEM concentrationsstabilizedandgraduallydecreased.

Intermsofspatialdistribution,theGEMreboundwasprimarily observed in the Chukchi Sea, where concentrations were notably higherthanthoseintheBeringStrait,despitethelatterbeingcloseto landandestuaries(Fig.1b).ThisisconsistentwiththelatitudinaldistributionofGEM:boththemeanandmedianconcentrationsofGEMin the75–80°Narea,wheretheChukchiSeaislocated,werehigherthan inotherlatitudinalregionsoftheArcticOcean(Fig.1c).Incontrast, GEMconcentrationsinthehigh-latitudeArcticOcean(78–90°N)were relativelylow,withminimalspatialvariability.

TheobservationsfromthePacificsectoroftheArcticOceanin this study, when combined with previous data from the Atlantic sector14, suggest that the summertime GEM rebound is widespread acrosstheArcticOcean.

SourcesofsummertimeGEMrebound
We explored the sources of the summertime GEM rebound in the PacificsectoroftheArcticOcean.Therewasnopositivecorrelation observedbetweenNOxandGEMconcentrations(Fig.S1).NOxlevels were low during the GEM rebound at the end of July, whereas significantincreasesinNOxcoincidedwithastable,lowconcentration trendofGEMaftermid-August.Additionally,theGeneralizedAdditive Model(GAM)simulationindicatedthatNOxhadaminimalcontribution(4%)toGEMvariability(Table1),suggestingthatanthropogenic sources, such as ship emissions, had little influence on the GEM reboundobservedinthisstudy(Fig.S1).

Thefractionofthe168-hbackwardtrajectories’transporttimein marineareas(FRocean)wasgenerallynear100%duringthesummertimeGEMrebound(yellowshadedareainFig.2a).Statisticalanalysisof GEMandFRoceanrevealedthataverageFRoceanlevelswerehigher whenGEMconcentrationswereelevated(GEM>1.6ng/m3,t-testwith p<0.01),withthehighestGEMconcentrationrange(GEM>1.8ng/m3) corresponding to the maximum FRocean average (0.998±0.004, Fig.2b).Furthermore,theGAMresultsindicatedthattheopen-water fraction(Openwater,usedasaproxyforoceanicemissions)hadthe greatestcontribution(29%)toGEMvariability(Table1).Thesefindings suggestthattheGEMreboundinthePacificsectoroftheArcticOcean wasprimarilydrivenbymarineHgemissions,ratherthanship-basedor land-basedanthropogenicemissionsandtheirregionaltransport.

PSCF(potentialsourcecontributionfunction)analysiswasfurther applied to identifythepotentialsourceregionsofGEMintheArctic Ocean.HighWPSCF(weightedpotentialsourcecontributionfunction) valuesinthePacificsectorwereprimarilyconcentratedinthemarginal ice zone (MIZ) of the Chukchi Sea, indicating elevated marine Hg emissionsinthisarea.Incontrast,boththeopenoceanregionsofthe outerArcticOceanandthepackicezonesinthehigh-latitudeArctic presentedlowWPSCFvalues(Fig.3).Thepartialresponsecurveofthe GAMforOpenwaterisalsoconsistentwiththeaforementionedphenomena: high concentrations of GEM correspond to an Openwater rangeof~0.3–0.6,indicativeoftheenvironmentofthemarginalice zone(Fig.S2a).Thesefindingsalignwithourpreviousobservationsin the Atlantic sector of the Arctic Ocean14, suggesting that high Hg emissionsintheMIZareawidespreadphenomenonacrossboththe Atlantic and Pacific sectors, serving as a key driver for the Arctic summertimeHgpeakacrosstheentireArcticOcean.

Characteristicsofmarinedissolvedgaseousmercuryduringthe summertimeGEMrebound
Todirectlyobservethesourcestrengthofoceanicmercuryemissions from the MIZ during the summertime GEM rebound in the Arctic Ocean, synchronous measurements of marine dissolved gaseous mercury(DGMorHg(0))areessential.WealignedtheobservedDGM datawiththeoriginal-resolution(5-min)GEMobservationsthroughout theentirecruisebasedontheirdatapointgenerationtimes,allowing us to comprehensively characterize the variability in marine Hg(0) concentrations during the GEM rebound periods. The results show clearsynchronousincreasesinDGMconcentrationsduringtheGEM reboundintheMIZ(Fig.S3).WefurtheraveragedtheGEMdatatothe temporal resolution of the DGM data and aligned them through observationtimes,andtheresultsrevealaconsistencyintheirvariationtrendswithasignificantpositivecorrelationbetweenDGMand GEM(R2=0.28,P<0.001)(Fig.4).Itshouldbenotedthatspatialheterogeneitymayexistintheaccumulation–releasedynamicsofDGM across different sampling locations. Additionally, meteorological conditionscanalsoinfluencetheaccumulationanddiffusionofGEM, allofwhichwouldcollectivelyaffectthecorrelationbetweenDGMand GEMinthisstudy.Theobservedsynchronousincreasingtrendsand statisticallysignificantcorrelationbetweentheDGMandGEMduring the GEM rebound period further provide evidence supporting the hypothesis that the Arctic Ocean GEM rebound is predominantlydrivenbyHgemissionsfromtheMIZ.

The maximum DGM concentration observed during the GEM reboundreached87pg/L(i.e.,433fM/L).Thisconcentrationislower than the previously measured maximum instantaneous DGM concentrationsundercontiguousice(e.g.,544fM/Linref.15and670fM/L inref.16),suggestingthatDGMislikelyreleasedintotheatmosphere followingsea-icemelting.Additionally,theDGMsaturationduringthe entirecruiserangedfrom0.97to4.47,withanaverageof2.40±0.98. Arelativelyhighaveragesaturation(2.79±0.87)wasobservedduring theGEMreboundintheMIZ(Fig.S4),indicatinghighsupersaturation (greaterthan1)andhighHgevasionpotential.

The calculated real-time air‒sea exchange fluxes of Hg ranged from−0.043to6.88ng·m−2·h−1.TheaverageHg(0)fluxduringtheGEM reboundintheMIZ(1.52±1.64ng·m−2·h−1)wasnotonlyhigherthan theoverallaveragefortheentirecruise(1.09±1.42ng·m−2·h−1),butalso exceededpreviouslyreportedfluxlevelsintheopenseaoftheArctic Ocean(rangingfrom0.4±2.8ng·m−2·h−1to0.7±0.26ng·m−2·h−1)15,17. ThissuggeststhattheArcticMIZservesasasignificantsourceofHgto theatmosphere.

Insummary,onthebasisofthesynchronousobservationofGEM andDGMinthePacificsectoroftheArcticOcean,thisstudyfurther confirmsthatHgemissionfromtheMIZisacrucialsourceofatmosphericHgintheArcticOcean.ItprovidesdirectobservationalevidencesupportingthemechanismbywhichhighHgemissionsfromtheMIZdrivethesummertimeHgreboundintheArctic.Thisconclusionis alsosupportedbythemodelingresultsfromref.18,whichshowedthat oceanicevasionisthedominantsourceofthesummerGEMrebound, particularlydrivenbyseawaterHg(0)evasionfacilitatedbyseasonal icemelt18.Inref.18,bothsimulatedatmosphericandseawaterHg(0) concentrationsintheArcticOceanincreasedfromtheopenoceanto theboundarybetweenMIZandperennialicezone(PIZ).

FactorsinfluencingthespatiotemporalvariabilityofsummertimeGEMrebound
DiMento et al.15 conducted simultaneous observations of DGM and GEM in the Pacific sector of the Arctic Ocean from August to mid-October.TheirstudyfoundthathighDGMconcentrationswereprimarilydetectedinthecontiguousiceregionnorthof80°N15.Although bothref.15andthisstudyobservedsimilarsea-icegradientsintheMIZ —rangingfromice-freewaterstoareaswithover80%icecoverage— DGM concentrations in the Chukchi Sea MIZwerenotablylower in ref.15,andnodistinctGEMreboundwasobservedinthatregion15. Additionally,theHgemissionfluxreportedbyref.15intheMIZ was −3±5pmol·m−2·h−1, with a surface seawater Hg saturation of 0.39±0.46,indicatingthattheMIZfunctionedasaHgsinkratherthan asourceatthattime.Akeydifferencebetweenthetwostudiesisthe observationperiod:DiMentoetal.15conductedtheirmeasurementsin theMIZ~20dayslaterthanthoseinthisstudy.

Similarly,ref.14observedasummertimeGEMpeak(2.99ng/m3) intheMIZduringmid-July,nearlytwoweeksearlierandsignificantly higherthanthemaximumGEMconcentrationrecordedintheMIZin this study (2.08ng/m3). However, after August, their observations showed continued GEM elevations, although with a much weaker reboundeffect(<2ng/m3),whichalignswiththetrendsobservedin thisstudyduringthesameperiod.

These findings suggest a clear seasonal pattern in the ocean-driven summertime GEM rebound in the MIZ, with the most pronouncedeffectoccurringinJuly.AstheseasonprogressesintoAugust, theprocessgraduallyweakensandeventuallyfadesovertime.Thekey question that arises is: What mechanisms drive this distinct spatiotemporalvariability?

DissolvedorganiccomponentsassociatedwithprimaryproductivityintheMIZ
Previous observations have shown a significant positive correlation betweenGEMandChla(chlorophylla)insurfaceseawater14,inwhich both parameters exhibit clear seasonal trends, with the peak concentrationsoccurringaroundmid-July,followedbyasteadydecline afterAugust14.Thissuggeststhatthespatiotemporalvariabilityinthe summertimeGEMreboundacrosstheArcticOceaniscloselylinkedto theevolutionofprimaryproductivityintheMIZ.

Tofurtherinvestigatethisrelationship,weanalysedtheconnectionsbetweenGEM,Chla,andchromophoricdissolvedorganicmatter (CDOM)concentrations.Ourfindingsindicatethatthesummertime GEMreboundgenerallycoincidedwithseasonalphytoplanktonbloom events(representedbyChla)intheMIZfromlateJulytoearlyAugust, aligningwiththeobservationsofref.14.Additionally,weobserveda strongassociationbetweenGEMreboundeventsandsharpincreases inCDOMduringthisperiod(Fig.5a).BylateAugust,GEM,Chla,and CDOMlevelsallremainedlow,andtheGEMrebounddisappeared.

Statistical analysisof the entire cruise dataset further supports this connection.Duringphytoplanktonbloomperiods(Chla>1.8µmol/ L), both mean and median GEM concentrations were significantly higher (t-test with p<0.01, Fig. 5b). In addition, as the CDOM concentration increased,the meanand median GEM levels followed an elevating trend (Fig. 5c). GAM analysis revealed that CDOM contributed significantly to GEM variability (24%), second only to the Openwatervariable(29%)(Table1).TheGAMpartialresponsecurveof CDOMrevealsthatwithincreasingCDOMlevels,GEMconcentrations initiallyriseandthenstabilize(Fig.S2b),exhibitinganoverallpositive correlationbetweenthetwovariables,apatternsimilartothatshown inFig.5c.Thesefindingshighlightthecrucialroleofdissolvedorganic components related to primary productivity in driving the Arctic summertimeGEMreboundintheMIZ.

Moreover, the peak hourly-averaged GEM concentrations observedduringthethreeGEMreboundeventsinthisstudycorresponded well with peaks in solar radiation, with significant positive linearcorrelationsbetweenGEMandsolarradiationacrossallevents (Fig.S5).Laboratorystudieshavepreviouslysuggestedthatdissolved organic chromophores derived from phytoplankton exudates can enhanceHg(II)photoreduction,leadingtoincreasedDGMproduction inaquaticenvironments1,19,20.Onthebasisoftheseobservations,we concludethattheseasonaldynamicsofdissolvedorganiccomponents associatedwithphytoplanktonactivityintheMIZplayakeyroleinthe spatiotemporal variations in the summertime GEM rebound in the Arctic Ocean, primarily by facilitating the photochemical reduction ofHg(II).

InadditiontoGEM,DGMconcentrationsinsurfaceseawateralso exhibitedpeakvaluesintheMIZ,coincidingwithincreasesinCDOM and Chla. Furthermore, the increase in DGM was closely linked to increasedsolarradiation(Fig.5d).Thesecovariationpatternsamong DGM,CDOM,Chla,andsolarradiationfurthersupportthehypothesis thatphytoplanktonbloomsintheMIZenhanceHg(II)photoreduction attheseasurface,contributingtoincreasedGEMemissions.

Buildingontheseobservations,thisstudyfurtheremphasizesthe keyroleofincreasedprimaryproductivityintheArcticMIZindriving thesummertimeGEMrebound,aphenomenonobservedinboththe AtlanticandPacificsectoroftheArcticOcean.Theprominenceofthis process in the Arctic MIZ may be attributed to the shallow marine mixinglayerformedbysea-icemelting.Thisshallowlayerrestrictsthe downward transport of Hg and dissolved organic matter, keeping them concentrated near the surface, where photoreduction and subsequent re-emission of Hg are enhanced21. We propose that the temporal and spatial variability of dissolved organic components associatedwithalgalbloomsintheMIZ,combinedwithvariationsin solarradiation,arekeyfactorscontributingtothesignificantspatiotemporal differences observed in the summertime GEM rebound acrosstheArcticOcean.

Meteorologicalprocessesattheice–water–airinterface
Inadditiontochangesinprimaryproductivity,sea-icedynamicsare among the most prominent seasonal characteristics of the Arctic Ocean.InadditiontointroducingdepositedHg(II)frommeltingice, meteorologicalprocessesattheice‒water‒airinterface,whichexhibit highspatialheterogeneity,alsoplayacrucialroleinregulatingair‒sea exchange.Mooreetal.22reportedthatlead-initiatedshallowconvectioninthestableArcticboundarylayercanmixGEMfromundepleted airmassesaloft,leadingtorapidGEMrecoveryduringatmospheric mercurydepletionevents(AMDEs)inspring.Thishighlightsthe important role of local atmospheric convection, driven by sea-ice dynamics,ontheatmosphericHgcycle.

Inthisstudy,weobservedthatair‒seatemperaturedifferences (Air_sea_Temp) remained generally stable during the late-July GEM rebound events (Fig. S6), but closely followed GEM fluctuations throughoutAugust(Fig.6a).ThetwoGEMreboundepisodesinAugust coincidedwithincreasedinAir_sea_Temp,showingasignificantlinear correlationinAugust(R2=0.3,P<0.001,Fig.6b).Thissuggeststhat local atmospheric convection, facilitated by increasing air‒sea temperature differences in open water in the sea‒ice region, likely enhancedoceanicHgemissionsduringthisperiod.

Tofurtherverifythishypothesis,weexaminedevaporationfrom turbulence (EVAP) and sea–air latent heat flux (EFLUX)—both key indicatorsofatmosphericturbulenceatthesea–airinterface.Inlate July,EFLUXandEVAPvariationsshowednoclearcorrelationwithGEM, implying minimal impact from local convection on the July GEM rebound event (Fig. S6). However, in August, notable increases in EFLUXandEVAPcorrespondedwellwithGEMrebounds(Fig.6c),with asignificantpositiveexponentialcorrelationbetweenEFLUXandGEM (R2=0.33, P<0.001, Fig. 6d). GAM analysis across the entire cruise furthershowedthatEFLUXcontributed19%toGEMvariability,ranking thirdafterOpenwater(29%)andCDOM(24%)(Table1).Additionally, the GAM partial response curve of EFLUX demonstrates a pattern analogousothatobservedinFig.6d:whenEFLUXexceeds5W/m², GEMconcentrationsexhibitanoverallupwardtrendwithincreasing EFLUXvalues(Fig.S2c).Thesefindingsindicatethatlocalatmospheric convectionhadasubstantialinfluenceonmostoftheobservedGEM reboundeventsinthisstudy.

Integratingsea-icedata,weobservedthatelevatedlevelsofGEM and EFLUX generally corresponded to a moderate sea-ice fraction (0.5~0.8),whereasbothlowerGEMandEFLUXlevelswereassociated witheitherdenseicecover(sea-icefraction>0.8)ormeltingicearea (sea-icefraction<0.5)(Fig.6d).ThesefindingssuggestthattheinfluenceoflocalconvectiononoceanicHgemissionsintheArcticOceanis closelylinkedtotheextentofsea-icemelt.Whensea-icecoverageis extensive(>80%),theconsolidatediceinhibitsthereleaseofoceanic Hg15. However, as melting progresses and open water expands, the shoalingofthemixinglayercausedbymeltwaterfacilitatestheaccumulationofHgpreviouslytrappedinsea-iceattheseasurface.Additionally,theenhancedtemperaturegradientbetweentheopenwater and air immediatelyaftermelting promotedlocalatmospheric convectionandevaporation,furtherstimulatingthereleaseofoceanicHg intotheatmosphere.Onceseaicehascompletelymelted,theinputof Hgfromicediminishes,alongwithitssubsequentre-emission23. Thesefindingsindicatethatmeteorologicalprocessesattheice‒ water‒air interface, driven by dynamic and thermodynamic sea-ice changes,wouldnotonlyinfluenceAMDEsbutalsomodulateoceanic Hg emissions during the summer. This represents another key mechanismcontributingtothespatiotemporalvariationsinthesummertimeGEMreboundwithintheArcticMIZ.

Methods
Studysite
Aspartofthe13thChineseNationalArcticResearchExpedition(CHINARE), which focused on the Arctic climate and ecosystem, a large-scale, multidisciplinary observational cruise was conducted in the PacificsectoroftheArcticOcean.Theexpeditionroutebeganatthe BeringStrait,passedthroughtheChukchiSeaandtheGuckmid-ocean ridge,and extended to the North Pole (90°N),covering a latitudinal rangefrom60°Nto90°Nandalongitudinalrangefrom90°Eto150°W. Thecruiset.ThecruisetookplacefromJuly24toSeptember15,2023,andtraversed diversehydrologicalenvironments,includingopenwaters,marginalice zones,andice-coveredregions.ThecruisetrackisshowninFig.1.

Experimentalmethods
AtmosphericGEMwasautomaticallymeasuredusingaTekranTM2537B Hg analyser based oncoldvapor atomic fluorescencespectroscopy (CVAFS),withatemporalresolutionof5minperdatapoint.Theair inletofthe Hg analyserwas positioned atthe frontofthe research vessel Xuelong 2, ~30m above the sea surface, to minimize contaminationfromtheship’sexhaustplume.GEMwasalternatelycollectedontwogoldcartridgesataconstantflowrateof0.7L·min−1,then thermallydesorbedat550°CanddetectedbyCVAFS.

Toremovemoistureandcoarseparticles,twosodalimetubesand two0.45-μmTeflonfilterswereinstalledattheanalyser’sinlet.Daily calibration was performed using an internal Hg permeation source builtintotheanalyser.Inaddition,externalcalibrationwasconducted beforeandafterthecruisebymanuallyinjectingaknownGEMmass viaaTekranTM2505unit.Bothinternalandexternalcalibrationproceduresachievedanaccuracyof96%.Thedetectionlimit(DL)ofthe analyserforGEMwaslessthan0.10ng·m−3.

Dissolved gaseous mercury (DGM) in seawater was measured using a purge-trap-detect method adapted from refs. 29,30. A specifiedvolumeofsurfaceseawaterwasautomaticallydrawnfrom the onboard seawater tap into a pre-conditioned Teflon bubble chamberviaaTeflontube.TheseawatersamplewaspurgedwithHg- freeair(producedbyaTekranTMzeroairgenerator)ataflowrateof 1L·min−1for1h.Thepurgedairstreamwaspassedthroughasodalime tubetoremovemoistureandthenroutedtoanotherTekranTM2537B analyserforHgdetection.TheDLforDGMwas4.8pg·L−1,calculatedas threetimesthestandarddeviationoftheblank(1.3±1.6pg·L−1,n=17). DGM observations depend on sea-ice conditions in the Arctic Ocean.Whenthesea-icedensitywastoohigh,theonboardseawater pumpwasturnedofftopreventiceblockageinthesamplingsystem. Therefore,DGMmeasurementswereconductedonlywhenopenwater waspresentwithinthesea-icecover.

Hgsea–airfluxcalculation
ThesaturationofDGMinsurfaceseawaterandthesea–airfluxofGEM werecalculatedviathethin-filmgasexchangemodel30–33.Specifically, thesaturation(S)weredeterminedusingthefollowingequations:

S=DGM×H’(T)=GEM (1)

where T is the surface seawater temperature (K), and H’(T) is the temperature-dependent Henry’s law constant. H’(T) was calculated basedonthemethodofref.34:

H’(T)=exp((−2404.3/T)+6.29) (2)

Thesea–airflux(F,ng·m−2·h−1)wasdeterminedusingthefollowing equation:

F=Kw×(DGM−GEM/H’(T)) (3)

where KwisthegastransfervelocityofHg(0)atthewater‒airinterface (incm·h−1).Kwwascalculatedbasedonref.31:

Kw=0.31U10^2×(SHg/600)^−0.5 (4)

where SHgistheSchmidtnumberforHg,derivedfromref.30,andU10 isthe10mwindspeed(m·s−1).

Otherancillarydataandanalysis
Nitrogenoxides(NOx)werecontinuouslymeasuredonanhourlybasis usingaThermoFisherTM-42ichemiluminescenceNO-NO2-NOxanalyser.Marinebiogeochemicalparameters,includingchlorophylla(Chla) andchromophoricdissolvedorganicmatter(CDOM),weremonitored usingaWETLabsTMECO-tripletfluorometer,whichincludesdedicated sensorsforChlaandCDOM.Thetemperatureofsurfaceseawaterwas monitoredusingaSea-birdTMSBE-38DigitalOceanographicThermometer.ThesemeasurementswereconductedduringtheDGMobservations, and the corresponding raw data were averaged hourly for subsequentanalysis.

Hourlynavigationparametersandselectedmeteorologicalvariables,includingwindspeedandairtemperature,wereobtainedfrom theshipboardmonitoringsystems.Additionally,hourlydata,including sea-icefraction, solar radiation (Radiation), air‒sea temperature difference (Air_sea_Temp), evaporation due to turbulence (EVAP), and latent heat flux (EFLUX), were extracted from assimilated meteorologicaldatasets provided by the Goddard Earth Observing System (GEOS)andtheModern-EraRetrospectiveAnalysisforResearchand Applications, Version 2 (MERRA-2), with a horizontal resolution of2°×2.5°.

TheHYSPLITtransportanddispersionmodeldevelopedbythe NOAA-Air Resources Laboratory was used to generate 168-hour backward trajectories of air masses throughout the cruise. These trajectoriesenabledfurtherstatisticalanalyses of airmassorigin, includingthecalculationofthefractionofeach168-htrajectory’s transporttimespentovermarineareasrelativetothetotaltransporttime(FRocean).Themodelwasdrivenbythemeteorological datafromtheglobaldataassimilationsystem(GDAS).Onetrajectorywasgeneratedperhour,resultinginatotalof1280trajectories overthecourseofthecruise.

Evaluatingtherelativeimportanceofvariousinfluencingfactors
In this study, we employed a generalized additive model (GAM) to assesstherelativecontributionofselectedpredictorstotheobserved variabilityinGEMconcentrations.Asadata-drivenstatisticalframework, GAM accommodates nonlinear relationships between dependent and independent variables by incorporating flexible basis functions.Themodelstructureisdefinedas:

g(μ)=f1(x1)+f2(x2)+...+fn(xn)+ε (5)

wherexi(i=1,2,3,…,n)representsthepredictorvariables,fidenotes thesmoothfunctionappliedtoeachpredictor,μistheexpectedvalue oftheresponsevariable,εistheresidual,andgisthelinkfunction.To optimizemodelperformance,penalizedcubicregressionsplineswere adoptedforfi,allowingadaptiveselectionofdegreesoffreedomto mitigateoverfittingorunderfitting.GiventheGaussiandistributionof GEMvalues,theidentitylinkfunctionwaspairedwithaGaussian.All analyseswereperformedusingthe“mgcv”packageinR.

We considered four categories of predictors, including the followingparameterstoevaluatetheirrelativeimportancetoGEMvariationinthisstudy:
(1) Oceanicemissions:indicatedbytheopen-waterfraction(Openwater)duringthecruiseobservation;
(2) Anthropogenicemissions:indicatedbytheobservedNOxmixingratios;
(3) Marine biochemical conditions: indicated by chromophoric dissolvedorganicmatter(CDOM);
(4) Meteorological factors: wind speed (WS), air temperature (Temp),solarradiation(RD)andlatentheatflux(EFLUX).The correspondingresultsweredisplayedinTable1.

Previous studies have indicated that the GAM demonstrates robustperformancewhentheadjustedR²valueexceeds0.535,36.Inthis study,theGAManalysisexplains52.9%ofthevarianceinGEMconcentrations,achievingafittingR²of0.53.Thisresultunderscoresthe model’scapacitytoeffectivelycharacterizeGEMvariabilityacrossthe entireobservationalperiod,reflecting its strong applicabilityin this context(Fig.S7a).

We used the Akaike Information Criterion (AIC) to ensure the effectivenessofthepredictors’selection.Properparameterselection canbeindicatedbyhigherfittingR2valuesalongwithlowerAICvalues during the addition of each variable35,36. The corresponding results indicatethattheymetthecriterionoftheAICevaluation(Fig.S8d).

Modelvalidation
Systematic evaluation of the GAM’s performance was conducted throughmultiplevalidationtechniquestoensuremodelreliability.A fivefold cross-validation approach was applied to assess predictive accuracy14.Underthismethod,thedatasetwaspartitionedintofive random subsets, with four subsets used for model fitting and the remainingsubsetreservedforvalidationineachiteration.Thisprocess wasrepeatedfivetimes,ensuringthatallthesubsetsservedastest data.Thecross-validationresultsexhibitedstrongalignmentbetween thesimulatedandobservedvalues(slope=0.97,R²=0.93),confirmingrobustmodelperformance(Fig.S7b).

To validate the assumptions of homogeneity, normality, and independence of residuals and ensure methodological rigor, three diagnostic analyses were performed35,36: (1) quantile-quantile (Q-Q) plot (comparing sample vs. theoretical quantiles); (2) residual scatterplotsagainstlinearpredictors;and(3)residualhistograms.TheQ-Q plot revealed that GAM predictions closely matched theoretical quantiles,particularlynearthemeanconcentration.Residualscatterplotsdemonstratedresidualsclusterednearzerowithnodiscernible trend, indicating unbiased simulations. The residual histogram approximated a normal distribution, suggesting a random error structure and appropriate predictor selection. Collectively, these results underscore the validity of the model’s assumption and the reliabilityofusingtheselectedpredictorstoidentifyGEMsourcesand keyinfluencingfactorsinthisstudy(Fig.S8).

PSCFanalysis
A potential source contribution function analysis (PSCF) was performedtoidentifythepotentialsourceregionsofGEMintheArctic Oceanduringtheobservationperiod.AhighervalueofWPSCFijindicatesahigherprobabilitythatagivenregioncontributedtoelevated GEM levels at the receptor site. PSCF analysis driven by GDAS meteorologicaldatacombinesthemeasuredhourlyGEMconcentrationswith72-hHYSPLITbackwardstrajectories.Thedomainofthe72-hbackwardtrajectorieswasdividedinto0.5°×0.5°gridcells.ThePSCF valuefortheijthcellwascalculatedasfollows:

WPSCFij = Mij/Nij ×Wij (6)

inwhichMijisthenumberoftrajectorysegmentendpointsinagrid cell with a corresponding GEM concentration higher than its 90th percentileofthewholecruise,andNijisthetotalnumberoftrajectory segmentendpointsinagridcell.TheempiricalweightcoefficientWij wasincludedinthecalculationtoreducetheuncertaintiesofgridcells withsmallNijvalues,anditsvaluescanbefoundintheref.36.

Dataavailability
TheGEM,DGMconcentrationsandthecorrespondingauxiliarydata generatedinthisstudyareprovidedintheSourceDatafileandare availableatfigshare:(https://figshare.com/articles/dataset/Observed_GEM_and_DGM_data_in_the_Arctic_Ocean/28057997). Source data are providedwiththispaper.

Codeavailability
TheRcodeofthegeneralizedadditivemodel(GAM)usedinthisstudy is available at: (https://figshare.com/articles/dataset/Observed_GEM_and_DGM_data_in_the_Arctic_Ocean/28057997).ThePSCFmethodand thecorrespondingsoftwareusedinthisstudycanbeaccessedhere: (http://www.meteothink.org/).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "General Comments\nThe manuscript by Yue et al. presents a new cruise-based dataset of atmospheric gaseous elemental mercury (GEM) and\noceanic dissolved gaseous mercury (DGM) in the Arctic Ocean. The authors interpret these data, alongside ancillary\nmeasurements, to imply that oceanic Hg emitted from marginal ice zones (MIZ) are responsible for summertime peaks in\nArctic GEM. They further attribute variations in GEM emission to phytoplankton activity and atmospheric convection.\nThe new data presented by the authors are useful, particularly in the locations where DGM measurements are available, and\nhave the potential to add to our understanding of summertime Arctic mercury cycling processes. However, the analyses\npresented are insufficient to support the interpretations presented.\nA major concern is that the analysis of the relationships between variables is largely qualitative, primarily based on timing\noverlaps shown in figures. Where quantitative analysis is provided, it is not very robust, primarily using simple linear\nregression and associated correlation coefficients. A few important examples are provided below.\n(1) The conclusion that the GEM peaks are from marine emissions seems to primarily be supported by Figure 2, which\nshows timeseries of GEM and FRocean. This appears to be a major conclusion from the work, but with no statistical or other\nquantitative analysis to support this relationship. From the figure alone, it is not obvious that the peaks in GEM do in fact\ncoincide with increases in FRocean. Further, with back trajectories covering only 3 days, it is not a surprise that they were\nonly over the ocean during that period – transport from most land masses would take more than 3 days. The tracer used for\nidentifying anthropogenic sources, NOx, has a short lifetime and would only indicate local pollution sources – a longer-lived\ntracer such as CO would be more appropriate for ruling out transported anthropogenic sources.\n(2) The co-variation of GEM and DGM data is used to further justify the interpretation of a marine source, largely supported\nby Figure 4 (and to some extent Figure S2). Figure 4 raises several questions. The DGM data are clearly sparser than the\nGEM data, and presumably represent longer temporal averaging (although such information is lacking from the data\ndescription in the Materials and Methods section). How have the two datasets been compared? Are the GEM data\ntemporally averaged to match the DGM temporal resolution? If they were plotted as such in Figure 4a, would there still be an\napparent correlation? While the correlation is statistically significant, the relationship is not strong (R2 = 0.28, meaning <30%\nof the variation is explained). Is this enough to consider it an important contributor? Perhaps – but some discussion is\nneeded. Further, given that the intention is to determine whether DGM variation can explain GEM variation, the regression in\nFig. 4b should be performed with DGM as the independent variable (x-axis), not the other way around.\n(3) The primary productivity analysis is again supported only by co-incident timeseries plots (Figure 5). Again, the different\ndatasets appear to have been collected at different temporal resolutions, although this information has not been provided in\nthe Materials and Methods. Further, the relationships shown in the figure are not compelling – for example, the text states\nthat “GEM peaks corresponded well to the significant increases in CDOM”, but the biggest peak in GEM is shown to occur\nwhen CDOM is low and declining. The DGM-CDOM relationship is also a bit of a mixed bag. Without some sort of statistical\nanalysis, it is hard to have confidence that there are true relationships here.\n(4) The meteorological analyses are carried out for August only, rather than starting in July when the largest GEM peaks are\nfound. Why? This has not been justified. The scatter plot in Figure 6b does not appear to show a linear relationship, instead\nappearing to asymptote at higher EFLUX values. It may be more accurate to use a logarithmic (or other) fit in this case, or at\nleast to test the impact of different relationships.\nThe lack of more robust statistical analysis is somewhat surprising, given that this paper is a follow-up to Yue et al. 2023\n(which is heavily referenced in this manuscript). The earlier paper used a generalised additive model subjected to\nsystematic cross-validation to support their conclusions. Application of similar techniques to this newer dataset would\nsubstantially increase confidence in the results.\nOne final concern I have about this work is the lack of a clear definition of what is considered a GEM “peak”. Given much of\nthe focus is on identifying the drivers of these peaks, there needs to be some clarity over which datapoints in the dataset are\nconsidered peaks. For example – are these just the periods in late July/early August when GEM increases substantially over\na period of multiple days? Or are they short term-events? Is a single high-GEM value considered a peak? Are peaks defined\nrelative to the whole dataset, or relative to the few days before/after (i.e., would small increases in September be considered\npeaks because they are higher than the days prior, or not considered peaks because they are still lower than the July/August\nvalues)?\nTo summarise, I feel the authors have a nice dataset and have done some relevant preliminary analyses to identify relevant\nfactors that might be influencing summertime Arctic GEM enhancements. In my opinion, the following would be required for\nthe analysis to be robust enough for publication:\n1. Define what will be considered a GEM “peak” for analysis.\n2. Provide clear details on the temporal resolution of the datasets used and how datasets of different resolutions have been\nsampled for comparative analyses.\n3. Apply robust statistical techniques to identify relationships between GEM, DGM and other ancillary variables (potentially\nadopting the statistical modelling approach used in Yue et al. 2023). Co-incident timeseries alone are not sufficient.\n4. For statistical fits, consider whether linear, log, or other relationships best represent each dataset.\n5. To rule out the influence of long-range transport of anthropogenic sources, use a long-lived tracer such as CO and/or\nlonger back trajectories.\nTechnical comments\n• The manuscript would benefit from language editing. The abstract in particular is a bit difficult to follow. The word\n‘meanwhile’ is used incorrectly, and ‘unknowingly’ should be ‘unknown’.\n• The abstract is a bit misleading, as the early sentences refer to the MOSAiC expedition, and it is not clear that they are\nreferring to separately published work. I suggest rewriting to focus specifically on what is new in this work and to make it\nclear that this work uses a new cruise observation dataset (not MOSAiC).\n• Line 50: the AMAP report should be cited here and included in the reference list.\n• The three different maps shown in the main text all use different projections – this makes them very hard to compare. I\nsuggest ensuring all maps use the same projection (here and in the supplement).\n• Line 144-145: PSCF and WPSCF acronyms should be defined.\n• A few datasets have been calculated but are never shown: DGM saturation, flux. It would be good to include figures\nshowing these as they are both discussed in the text (main text or supplement).\n• Figure 4a bottom panel (sea-ice and radiation timeseries) is not explained in the caption and never referenced in the main\ntext as far as I can tell – I suggest deleting it (or refer to it in text and add to caption).\n• Line 207: “in this study” – clarify that this text is referring to the previous study, as I initially read “this study” to mean the\npresent study.\n• Line 242: define Chl-a and CDOM on first use.\n• Figure S3 is discussed in some detail – I suggest it would fit better in the main text than in the supplement.\n• Line 347: “convention” should be “convection”\n• Line 379: “alternatively” should be “alternately”\n• Line 389: a reference is missing after Fu et al. – “and .”\n• Line 410: “Nitrous oxide” should be “nitrogen oxides” (nitrous oxide is N2O).\n• Line 444: It’s not clear to me that using the mean makes sense in this instance, given there is an underlying seasonal cycle\nto GEM. Consider using a high threshold e.g. 90th percentile instead.\n• Data availability: the embedded link\n(https://figshare.com/articles/dataset/Observed_GEM_and_DGM_data_in_the_Arctic_Ocean/280454?file=609972) goes to\nthe wrong website, but the text of the link appears correct\n(https://figshare.com/articles/dataset/Observed_GEM_and_DGM_data_in_the_Arctic_Ocean/28057997?file=51294749).\nPlease fix the embedded link.\n• The calculations for saturation and flux require knowledge of surface seawater temperature (T), but this has not been\nincluded in the downloadable data file, nor is a source listed in the Methods section (air temperature is mentioned but not\nseawater temperature). Please add T data to the data file and add source to the text.\n• The flux calculation (through Kw) also requires wind speed – please add this to the data file as well.", "reviewer_2": "This manuscript reported the time series of gaseous elemental mercury (GEM) and dissolved gaseous mercury (DGM)\nduring the 13th Chinese National Arctic Research Expedition (CHINARE), and found a significant positive correlation\nbetween them. With synchronous data of the sea ice fraction, chlorophyll a, chromophoric dissolved organic matter (CDOM)\nand meteorological factors during the expedition, this study attributes the summertime GEM peaks in the Arctic to the primary\nproductivity and local atmospheric convection initiated by sea ice melting in Marginal Ice Zone (MIZ). This study provides\ncrucial data for investigating key factors contributing to the GEM seasonality in the Arctic region, and the discussion in the\nmanuscript is convincing in general. However, the three GEM peaks (together with two GEM valleys) found in this study are\nnot necessarily impacted by one dominant process, especially the GEM depletion event after the first peak. More detailed\ninvestigation could be conducted.\nTherefore, overall in my opinion, major revision is required before the manuscript is acceptable for publication on Nature\nCommunications.\nHere are some specific comments:\n1. Lines 45–58: This paragraph is a bit long. Some background information could be simplified and put into the first\nparagraph of the introduction section. The budget of mercury in the Arctic could be further introduced to address the\nimportance of the process discussed in this manuscript.\n2. Lines 59–62: The Northern Hemisphere background GEM concentration level has been updated. Please refer to\nBencardino et al. (2024).\n3. The results and discussion section: Are the results from this study consistent with the modeling results from the very\nrecent study of Huang et al. (2025)?\n4. Lines 97–100: Again, the Norther Hemisphere background GEM level could be updated.\n5. Figure 1a: The first peak seems to be followed by a Hg depletion event. It would be interesting to dig more on this event.\n6. Figure S1a: There seems to be a NOx peak during the third Hg peak time. Have the author investigated the event based\non backward trajectories? Was it impacted by Siberian wildfires, for instance? If not, what was the reason for the NOx peak?\n7. Figure 2 and Figure 4a: The GEM time series in these two figures are repetitions of Figure 1a.\n8. Figure 4a: The DGM series seems to be consistent with the overall trend of GEM, except for the depletion event after the\nfirst GEM peak (The authors could change the scale of the right Y-axis to make more low-level data points of DGM fit the\nGEM time series). This figure provides more evidence to support my previous speculation that the depletion event might\nfollow another mechanism beside the marine Hg evasion process discussed in this study.\n9. Line 207: This expression “in this study” here could raise confusion. This study of DiMento et al. could be specified here.\n10. Figure S3: Do the authors have temperature data for the July event? It would be interesting to investigate the correlation\nbetween GEM and temperature or solar radiation in July. The Hg photoreduction process at the sea surface could facilitate\nGEM elevation, while the Hg photooxidation process in the atmosphere could be a key driver for the GEM depletion event.\n11. Figure 6b: The linear regression could be performed piecewise.\n12. The implications section: A schematic diagram could be helpful to improve the understanding of the processes\ndiscussed in this manuscript.\nReferences:\nBencardino, M., D’Amore, F., Angot, H., Angiuli, L., Bertrand, Y., Cairns, W., Diéguez, M. C., Dommergue, A., Ebinghaus, R.,\nEsposito, G., Komínková, K., Labuschagne, C., Mannarino, V., Martin, L., Martino, M., Neves, L. M., Mashyanov, N., Magand,\nO., Nelson, P., Norstrom, C., Read, K., Sholupov, S., Skov, H., Tassone, A., Vítková, G., Cinnirella, S., Sprovieri, F., and\nPirrone, N.: Patterns and trends of atmospheric mercury in the GMOS network: Insights based on a decade of\nmeasurements, Environ. Pollut., 363, 125104, 2024.\nHuang, S., Yuan, T., Song, Z., Chang, R., Peng, D., Zhang, P., Li, L., Wu, P., Zhou, G., Yue, F., Xie, Z., Wang, F., and Zhang,\nY.: Oceanic evasion fuels Arctic summertime rebound of atmospheric mercury and drives transport to Arctic terrestrial\necosystems, Nat. Commun., 16, 903, 2025.", "reviewer_3": "General comments\nThe unique Arctic summertime elemental mercury (Hg0) rebound represents a complex seasonal influenced by\ninterconnected pathways such as atmospheric long-range transport, terrestrial inputs, and sea-ice dynamics. However,\nconsensus on its drivers remains elusive due to the Arctic’s rapidly evolving environment under global warming. In this\nmanuscript, Yue et al. advance our understanding of this debated process through novel field measurements from a recent\nArctic Research Expedition, proposing a compelling link between sea-ice-associated primary productivity and the summer\nHg0 rebound. This work marks meaningful progress in elucidating this critical scientific question, particularly given the\nlogistical challenges of obtaining high-quality data in such extreme environments. The study’s interdisciplinary scope and\ninnovative approach align well with the standards of Nature Communications. However, I do have a number of clarifications I\nwould like to see in the revised paper.\nKey Recommendations for Revision\nFocus on Original Findings in Results & Discussion: While contextualizing results within existing literature is commendable,\nthe current Discussion section disproportionately reviews conclusions from prior observational and laboratory studies. For\ninstance, nearly half of the paragraph addressing primary productivity’s role in the Hg0 peak is dedicated to summarizing\nearlier work. To strengthen the manuscript’s novelty, here are some suggestions: (1) Condense background reviews to 1–2\nsuccinct sentences. (2) Expand on how their own results resolve inconsistencies or fill gaps in existing knowledge.\nBesides, there are more specific comments to enhance readability and standardization of this manuscript.\nSpecific Comments:\nLine 42: I think the \"grasshopper jump\" should probably be \"grasshopper\" as defined in previous studies.\nLine 52-53: Add a specific reference to support the demonstration of high risk exposure of Hg in Arctic biota, for example\n(Louis et al., 2011).\nLine 54: A recent modeling study also calculated the Arctic Hg budget and found a similar Hg deposition flux to the Arctic\nOcean (Huang et al., 2023).\nLine 62: The background concentrations of GEM in Northern Hemisphere (1.3-1.7 ng/m3) mentioned here is also measured\nin July or the average for the whole summer. Try to be more specific here.\nLine 80: The “seasonality” here might cause confusion. Maybe a “monthly difference” would be more proper as the peak\noccurs in July or Aug, both of which belongs to summer.\nThere are some extra blank in line 90-94 and line 176\nLine 100: Why the background concentrations in the North Hemisphere mentioned here (1.3-1.5 ng/m3) is lower than that\nmentioned in Line 62 (1.3-1.7 ng/m3)?\nLine 103: \"Concentration peaks of GEM\" is not proper. Maybe clarify: \"GEM peaks\"\nLine 124-125: “The comparison between GEM and NOx revealed no positive correlation between NOx and GEM\nconcentrations” this sentence is too tedious, try to make it more concise\nLine 126: It should be noted that “Significant” is a statistical description, the usage of this phase should combine with\nstatistical test. If no, replace it with another word. This word also used in Line 150, 178, 205, 243, 264, 276 etc. Please check\nsimilar issue.\nLine 145: “WPSCE”. This abbreviation lacks of definition.\nLine 155: There are two abbreviations of elemental Hg including Hg(0) (Line 167) and Hg0 (Line 401). Please unify.\nLine 177: the saturation of Hg should also unify as the it use pure number in Line 177 , while it use percentage in Line 207.\nLine 186-192: This sentence is too long to comprehension. Please rephrase it and separate it into couple sentences.\nLine 190: The Hg0 flux measured in this study is higher than that of DiMento et al. (2019). What causes the difference?\nLine 209-210: Except for the difference in observation time, what about the difference in sea ice concentrations between this\nstudy and previous study?\nLine 224: Chal should be defined here.\nLine 229-240: Try to reduce the review content of previous studies and highlight your own results.\nLine 253: In Figure 5, the chlorophyll a is short for Chl-a which is difference from the usage in previous paragraph (Chal).\nPlease modify this issue.\nReferences mentioned above:\nSt. Louis, V. L., Derocher, A. E., Stirling, I., Graydon, J. A., Lee, C., Jocksch, E., ... & Swanson, H. K. (2011). Differences in\nmercury bioaccumulation between polar bears (Ursus maritimus) from the Canadian high-and sub-Arctic. Environmental\nscience & technology, 45(14), 5922-5928.\nHuang, S., Wang, F., Yuan, T., Song, Z., Wu, P., & Zhang, Y. (2023). Modeling the mercury cycle in the sea ice environment:\na buffer between the polar atmosphere and ocean. Environmental Science & Technology, 57(39), 145"}, "author_response": "Responses to Reviewers’ Comments\nDear Reviewers:\nThank you for your comments on our manuscript entitled “Marine phytoplankton\nand sea-ice initiated convection facilitate the spatiotemporal differences in Arctic\nsummertime mercury rebound” (manuscript ID: NCOMMS-24-84664A) and for\noffering us an opportunity for revision. We believe the constructive comments have\nhelped us improve the overall quality of the manuscript. Below are our detailed\nresponses to reviewers’ questions. Revised texts of the manuscript are marked in red\nin the responses to reviewers’ comments.\nReviewers’ Comments and responses\nReviewer #1:\n2nd Review of Marine phytoplankton and sea-ice initiated convection drive\nspatiotemporal differences in Arctic summertime mercury rebound by Yue et al.\nThe authors have substantially revised the manuscript in response to the feedback from\nreviewers. I applaud the authors on the comprehensive nature of the revisions – in my\nview, the manuscript is greatly improved and now wholly deserving of publication in\nNature Communications. In its current form, I expect this to be an impactful\npublication.\nI have only a few minor comments remaining, mostly related to clarity or typographical\nerrors.\nMinor Comments\nQ1. Line 42: I think “food webs” would be more appropriate here than “food\nchains”.\nRe. Thank you! We have revised this expression based on your comments.\nQ2. Line 60-61: “which are based on…” – I think this is referring to the NH\nbackground concentrations, but the wording is a bit awkward and I think unnecessary,\nespecially as it breaks the flow to the next sentence where the focus returns to the\nrebound. I suggest ending the sentence after “(1.58 +/- 0.31 ng/m3)” and the reference\n(8).\nRe. Thank you! We agree with you and revised it based on your comments.\nQ3. Line 75-76: the sentence is a bit hard to read, especially with the repetition of\n“Hg(0) in the surface ocean”. Suggest removing the phrase “the synchronous variation\nin Hg(0) in the surface ocean”.\nRe. Thank you！We have rephrased this sentence based on your suggestion, which\nwas also shown below:\nLine 74-75: “However, the simultaneous measurements of Hg(0) in the surface\nocean of the MIZ, a key piece of evidence for this mechanism, remains lack.”\nQ4. Line 93-96: I appreciate the additional text that makes the boundaries of the\nepisodes a bit more clear, but there is still not a clear definition of the episodes. The\nstatement is that peak values exceed the NH background, which is then given as a range\n(mean +/- standard deviation, presumably). So is it an episode if the maximum value is\nabove 1.58 (mean), or above 1.58+0.31 (mean + SD, or above 1.58-0.31 (mean - SD)?\nHow do you define the start? How do you define the end? This still needs to be\nexplained in the text (either here or in methods).\nRe. Thank you! In the revised manuscript, we have further refined the operational\ndefinitions of GEM rebound episodes, with explicit specification of the start and end\ntimes for each individual episode. The corresponding revisions were presented as\nfollows:\nLine 92-100: “We identified three distinct episodes of substantial GEM rebounds\nduring this period, characterized by: (1) sustained increases in GEM concentrations\nwith temporal thresholds (initial/terminal concentrations) exceeding the cruise's mean\nvalue (1.28 ± 0.20 ng/m3), and (2) peak magnitudes surpassing the Northern\nHemisphere background reference level (1.58 ± 0.31 ng/m3)8. These episodes are\ndefined as the Arctic summertime “GEM rebound” phenomenon in this study (grey\nshaded areas in Figure 1a, with episode 1 occurring from UTC 2023/7/28 0:00 to\n2023/8/1 0:00; episode 2 occurring from UTC 2023/8/3 20:00 to 2023/8/6 18:00; and\nepisode 3 occurring from UTC 2023/8/13 0:00 to 2023/8/15 0:00).”\nQ5. Line 184: “We also matched…” Again I appreciate the extra information but I\nam still a bit unclear as to what the authors did here. Can it be made more explicit? Did\nyou average all GEM data to the time resolution of the DGM data? Or interpolate /\nextrapolate?\nRe. Yes. We averaged the GEM data to the temporal resolution of the DGM data and\naligned them through observation times. We have also revised the corresponding\ncontents in the manuscript as above.\nQ6. Line 195-197: I don’t see a compelling rationale for excluding the 3 mentioned\ndata points. The only rationale given is around low PBLH, but then Fig S3b retains\nmany other data points with similar PBLH. If they are going to be excluded on that\nbasis, then a numerical threshold for PBLH should be used and uniformly applied.\nRe. Thank you! Considering the insufficient rigor in the aforementioned data point\nremoval process, we have eliminated the example analysis regarding data point\nexclusion and correlation fitting from the manuscript. We retained only the statements\naddressing the objective potential influence of spatial heterogeneity in the\naccumulation–release dynamics of DGM and meteorological conditions across\ndifferent observation locations on the correlation between GEM and DGM in this study\nQ7. Line 197: “In conclusion” seems odd here, in the middle of results. Suggest\nremoving this phrase.\nRe. Thank you! We have removed this phrase based on your comments.\nQ8. Line 199: It’s not obvious to me that this evidence is more “critical” than other\nevidence provided, and this word seems unnecessary in any case. Suggest removing\n“critical” here.\nRe. Thank you! We agree with you and have removed this phrase based on your\ncomments.\nQ9. Line 223: “source of Hg” could be a source to the ocean or to the atmosphere.\nSuggest adding “to the atmosphere” at the end of the sentence to make this clearer.\nRe. Thank you! We have added “to the atmosphere” at the end of the sentence to\nmake this expression clearer.\nQ10. Line 262-263: “Previous observations have shown…” – this sentence should\ncite a reference.\nRe. We have added the corresponding reference citation to this sentence.\nQ11. Line 263: “Both parameters exhibit…” – this makes it sound like you are\nreferring to the current work, but I think this might be intended to refer to the reference.\nSuggest rephrasing, and perhaps combining with the previous sentence to make it\nclearer that this refers to published findings not findings from this manuscript.\nRe. Thank you. We have combined with the previous sentence to make it clearer that\nthis refers to published findings, which was also shown below:\nLine 274-277: “Previous observations have shown a significant positive correlation\nbetween GEM and Chla (chlorophyll a) in surface seawater14, in which both\nparameters exhibit clear seasonal trends, with the peak concentrations occurring\naround mid-July, followed by a steady decline after August 14.”\nQ12. Lines 332-334: the placement of the figure parenthetical is a bit confusing as\nthey don’t show the same things. I would suggest rephrasing as: “…remained generally\nstable during the late-July GEM rebound events (Figure S6), but closely followed GEM\nfluctuations throughout August (Figure 6a).”\nRe. Thank you. We have changed the placement of the figure parenthetical based on\nyour suggestions.\nQ13. Lines 352-354: there is an inconsistency here, with the first part implying the\nboundary between moderate sea ice and open water occurs at fraction=0.55, while the\nsecond part implies it is at 0.35. This is not a problem at the other end (both refer to 0.8).\nSuggest this be rephrased for consistency. Also, it is hard to relate this text to the color\nbar in Figure 6d, as this doesn’t show values to the nearest 0.05. The color bar is also\nhard to interpret – it would be clearer if you used either a simple monotonically\nincreasing colour scale, or one with clear boundaries (and related colours) between\nyour open ocean, ice-covered, and moderate sea ice bounds.\nRe. Thank you. We unified the values of 0.55 and 0.35 in the adjacent sentences to\n0.4 to ensure content consistency based on Figure 6d. Additionally, through attempting,\nwe found that the current heterochromatic color scale would more clearly illustrate\nsea-ice differentiation compared to a monotonically increasing color scale. Therefore,\nwe retained the original color scheme without modification.\nTypographical errors\nQ14. Lines 45-53: Please use consistent units throughout (Mg/year or Mg/a) –\nincluding the first sentence where it is just “Mg”.\nRe. Thank you! We have unified the corresponding units throughout this section.\nQ15. Line 69: Missing word - “… are not uniform across the Arctic Ocean are” – add\n“and” between “Arctic Ocean” and “are”\nRe. Thank you for your carefully checking. Taking into account the comment of\nreviewer 3, We added “but” between “Arctic Ocean” and “are”.\nQ16. Line 125: trajectory’s should be trajectories’\nRe. Thank you. We have revised it based on your comments.\nQ17. Line 129: t-test<0.01 should be “t-test with p<0.01” (it is the p-value of the\nt-test that has a significance level).\nRe. Thank you. We have revised it based on your comments.\nQ18. Line 188-189: DGM has already been defined and doesn’t need to be\nre-defined here.\nRe. We have revised it based on your comments.\nQ19. Line 278: same as Line 129\nRe. Thank you! We have revised it as Q17.\nQ20. Line 424: “drived” should be “driven”\nRe. Thank you for your carefully checking. We have revised it based on your\ncomments.\nQ21. Line 469-470: the word “only” is repeated in this sentence; suggest deleting the\nfirst one and retaining the second.\nRe. Thank you. We have revised it based on your comments.\nQ22. Lines 522 and 530: line 522 refers to 7 parameters, but the list stops at 4 (and\ncombines the remaining 4 into one set). I suggest removing “7” and replacing with “the\nfollowing”\nRe. Thank you. We have revised it based on your suggestion.\nQ23. Line 523: “and the corresponding results are displayed in Table 1” is misplaced\nhere as it breaks up the information about the parameters. I suggest making this its own\nsentence that comes after the list of parameters (i.e. just before the sentence at line 532).\nRe. Thank you. We have revised it based on your suggestion.\nQ24. Line 538: “this” should be “the”\nRe. Thank you. We have revised it based on your comment.\nQ25. Line 581: “and” should not be italicised here.\nRe. Thank you for your carefully checking. We have revised it based on your\ncomments\nQ26. Lines 590 and 596: The text of the URL goes to the correct place, but the\nembedded URL (i.e. what you get if you click on the link) still goes to the wrong place.\nI suggest just removing the link from this text entirely.\nRe. Thank you. As per the requirements of Nature Communications, we need to\nclearly specify the data availability in the manuscript. Therefore, directly removing the\ndata links may not be appropriate. We have updated the links and verified that they\ncorrectly point to the designated data repository.\nReviewer #2 (Remarks to the Author):\nQ27. The manuscript has been substantially improved. Concerns from the three\nreviewers have been properly addressed. I recommend the manuscript be accepted after\nminor revision:\nThe influencing patterns of key predictors on the GEM concentration resulted from\nthe generalized additive model could be discussed to validate the model.\nRe. Thank you！We further discussed the influencing patterns of key predictors on\nthe GEM concentration resulted from the generalized additive model, which were also\nshown below:\nLine 171-174: “The partial response curve of the GAM for Openwater is also\nconsistent with the aforementioned phenomena: high concentrations of GEM\ncorrespond to an Openwater range of approximately 0.3-0.6, indicative of the\nenvironment of the Marginal Ice Zone.”\nLine 294-297: “The GAM partial response curve of CDOM reveals that with\nincreasing CDOM levels, GEM concentrations initially rise and then stabilize,\nexhibiting an overall positive correlation between the two variables, a pattern similar\nto that shown in Figure 5c.”\nLine 366-368: “Additionally, the GAM partial response curve of EFLUX\ndemonstrates a pattern analogous to that observed in Figure 6d: when EFLUX exceeds\n-5 W/m², GEM concentrations exhibit an overall upward trend with increasing EFLUX\nvalues.”\nReviewer #3 (Remarks to the Author):\nThe authors have done an excellent job addressing my previous comments, and I am\nvery pleased to see their thoughtful corrections throughout the manuscript. I have a few\nminor suggestions below to improve the clarity and readability of the text. After\naddressing these minor points, the manuscript will be ready for publication.\nQ28. Line 67-70: Please add \"but\" to clearly connect the contrasting ideas, as follows:\n“Our recent GEM observations during the Multidisciplinary drifting Observatory for\nArctic Climate (MOSAiC) expedition revealed that elevated GEM concentrations in\nsummer are not uniform across the Arctic Ocean but are predominantly found in the\nMarginal Ice Zone (MIZ)”.\nRe. Thank you for your carefully checking. We have revised it based on your\ncomments.\nQ29. Please remove the extra space appearing before citation numbers throughout\nthe manuscript.\nRe. Thank you! We have removed the extra space appearing before citation numbers\nthroughout the manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "2nd Review of Marine phytoplankton and sea-ice initiated convection drive spatiotemporal differences in Arctic\nsummertime mercury rebound by Yue et al.\nThe authors have substantially revised the manuscript in response to the feedback from reviewers. I applaud the authors on\nthe comprehensive nature of the revisions – in my view, the manuscript is greatly improved and now wholly deserving of\npublication in Nature Communications. In its current form, I expect this to be an impactful publication.\nI have only a few minor comments remaining, mostly related to clarity or typographical errors.\nMinor Comments\nLine 42: I think “food webs” would be more appropriate here than “food chains”.\nLine 60-61: “which are based on…” – I think this is referring to the NH background concentrations, but the wording is a bit\nawkward and I think unnecessary, especially as it breaks the flow to the next sentence where the focus returns to the\nrebound. I suggest ending the sentence after “(1.58 +/- 0.31 ng/m3)” and the reference (8).\nLine 75-76: the sentence is a bit hard to read, especially with the repetition of “Hg(0) in the surface ocean”. Suggest\nremoving the phrase “the synchronous variation in Hg(0) in the surface ocean”.\nLine 93-96: I appreciate the additional text that makes the boundaries of the episodes a bit more clear, but there is still not a\nclear definition of the episodes. The statement is that peak values exceed the NH background, which is then given as a\nrange (mean +/- standard deviation, presumably). So is it an episode if the maximum value is above 1.58 (mean), or above\n1.58+0.31 (mean + SD, or above 1.58-0.31 (mean - SD)? How do you define the start? How do you define the end? This still\nneeds to be explained in the text (either here or in methods).\nLine 184: “We also matched…” Again I appreciate the extra information but I am still a bit unclear as to what the authors did\nhere. Can it be made more explicit? Did you average all GEM data to the time resolution of the DGM data? Or interpolate /\nextrapolate?\nLine 195-197: I don’t see a compelling rationale for excluding the 3 mentioned data points. The only rationale given is\naround low PBLH, but then Fig S3b retains many other data points with similar PBLH. If they are going to be excluded on\nthat basis, then a numerical threshold for PBLH should be used and uniformly applied.\nLine 197: “In conclusion” seems odd here, in the middle of results. Suggest removing this phrase.\nLine 199: It’s not obvious to me that this evidence is more “critical” than other evidence provided, and this word seems\nunnecessary in any case. Suggest removing “critical” here.\nLine 223: “source of Hg” could be a source to the ocean or to the atmosphere. Suggest adding “to the atmosphere” at the end\nof the sentence to make this clearer.\nLine 262-263: “Previous observations have shown…” – this sentence should cite a reference.\nLine 263: “Both parameters exhibit…” – this makes it sound like you are referring to the current work, but I think this might be\nintended to refer to the reference. Suggest rephrasing, and perhaps combining with the previous sentence to make it clearer\nthat this refers to published findings not findings from this manuscript.\nLines 332-334: the placement of the figure parenthetical is a bit confusing as they don’t show the same things. I would\nsuggest rephrasing as: “…remained generally stable during the late-July GEM rebound events (Figure S6), but closely\nfollowed GEM fluctuations throughout August (Figure 6a).”\nLines 352-354: there is an inconsistency here, with the first part implying the boundary between moderate sea ice and open\nwater occurs at fraction=0.55, while the second part implies it is at 0.35. This is not a problem at the other end (both refer to\n0.8). Suggest this be rephrased for consistency. Also, it is hard to relate this text to the color bar in Figure 6d, as this doesn’t\nshow values to the nearest 0.05. The color bar is also hard to interpret – it would be clearer if you used either a simple\nmonotonically increasing colour scale, or one with clear boundaries (and related colours) between your open ocean, ice-\ncovered, and moderate sea ice bounds.\nTypographical errors\nLines 45-53: Please use consistent units throughout (Mg/year or Mg/a) – including the first sentence where it is just “Mg”.\nLine 69: Missing word - “… are not uniform across the Arctic Ocean are” – add “and” between “Arctic Ocean” and “are”\nLine 125: trajectory’s should be trajectories’\nLine 129: t-test<0.01 should be “t-test with p<0.01” (it is the p-value of the t-test that has a significance level).\nLine 188-189: DGM has already been defined and doesn’t need to be re-defined here.\nLine 278: same as Line 129\nLine 424: “drived” should be “driven”\nLine 469-470: the word “only” is repeated in this sentence; suggest deleting the first one and retaining the second.\nLines 522 and 530: line 522 refers to 7 parameters, but the list stops at 4 (and combines the remaining 4 into one set). I\nsuggest removing “7” and replacing with “the following”\nLine 523: “and the corresponding results are displayed in Table 1” is misplaced here as it breaks up the information about\nthe parameters. I suggest making this its own sentence that comes after the list of parameters (i.e. just before the sentence at\nline 532).\nLine 538: “this” should be “the”\nLine 581: “and” should not be italicised here.\nLines 590 and 596: The text of the URL goes to the correct place, but the embedded URL (i.e. what you get if you click on the\nlink) still goes to the wrong place. I suggest just removing the link from this text entirely.", "reviewer_2": "The manuscript has been substantially improved. Concerns from the three reviewers have been properly addressed. I\nrecommend the manuscript be accepted after minor revision:\nThe influencing patterns of key predictors on the GEM concentration resulted from the generalized additive model could be\ndiscussed to validate the model.", "reviewer_3": "The authors have done an excellent job addressing my previous comments, and I am very pleased to see their thoughtful\ncorrections throughout the manuscript. I have a few minor suggestions below to improve the clarity and readability of the text.\nAfter addressing these minor points, the manuscript will be ready for publication.\n1. Line 67-70: Please add \"but\" to clearly connect the contrasting ideas, as follows: “Our recent GEM observations during the\nMultidisciplinary drifting Observatory for Arctic Climate (MOSAiC) expedition revealed that elevated GEM concentrations in\nsummer are not uniform across the Arctic Ocean but are predominantly found in the Marginal Ice Zone (MIZ)”.\n2. Please remove the extra space appearing before citation numbers throughout the manuscript."}, "author_response": ""}]

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