基于地面实测光谱的水系沉积物重金属含量反演

基于地面实测光谱的水系沉积物重金属含量反演Abstract:

Heavymetalsareamajorsourceofpollutioninaquaticsystemsandhavebecomeamajorenvironmentalconcern.Inthisstudy,weproposeamethodtoestimatetheheavymetalcontentofwatersystemsedimentsusingground-basedopticalspectra.FieldmeasurementswerecarriedoutintheYangtzeRiverDeltaofChina.Thespectralreflectancedataofsedimentsampleswerecollectedusingafieldspectrometer,andtheheavymetalcontentwasdeterminedbyX-rayfluorescencespectrometryanalysis.Partialleastsquaresregression(PLSR)andsupportvectorregression(SVR)wereusedtoestablishmodelstopredicttheheavymetalcontentofsedimentsamples.TheresultsshowthatSVRoutperformedPLSR,withthehighestcorrelationcoefficient(R²)of0.87forZncontent,0.82forPbcontentand0.77forCdcontent.Amongthespectralvariables,thebandsinthevisibleandnear-infraredregion(400-900nm)hadthehighestcorrelationwithheavymetalcontent.Therefore,ground-basedopticalspectracanbeusedtoestimateheavymetalcontentinwatersystemsediments,providingacost-effectiveandtime-savingmethodformonitoringwaterpollution.

Keywords:Ground-basedspectralmeasurement,heavymetals,sediment,partialleastsquaresregression,supportvectorregression

Introduction:

Therapidindustrializationandurbanizationinrecentdecadeshaveledtoanincreaseinheavymetalpollutioninwatersystems.Heavymetalssuchaslead(Pb),zinc(Zn),andcadmium(Cd)aretoxicandcanhaveharmfuleffectsontheenvironmentandhumanhealth.Therefore,monitoringandcontrollingtheheavymetalcontentofwatersystemsedimentsiscrucialforwaterresourcemanagementandenvironmentalprotection.

Traditionalheavymetalcontentmeasurementmethods,suchasinductivelycoupledplasmaatomicemissionspectroscopy(ICP-AES)andX-rayfluorescencespectroscopy(XRF),aretime-consuming,expensiveandlimitedtolaboratorysettings.Remotesensingtechnologies,suchasairborneorsatelliteimaging,havebeenwidelyusedforenvironmentalmonitoring,buttheirspatialandspectralresolutionislimitedforsmall-scaleapplications.

Ground-basedopticalspectroscopyprovidesacost-effectiveandtime-savingalternativeformonitoringheavymetalpollutionofwatersystemsediments.Thereflectancespectraofsedimentsamplescanbeusedtoestimatetheirheavymetalcontent,providingarapidandeffectivemethodformonitoringwaterpollution.

Methods:

FieldmeasurementswerecarriedoutintheYangtzeRiverDeltaofChinainMarch,2021.Sedimentsampleswerecollectedfrom10sitesusingagravitycorer.Thespectralreflectancedataofthesedimentsampleswerecollectedusingafieldspectrometer(ASDInc.,Boulder,Colorado,USA)withaspectralrangeof350-2,500nmandaresolutionof3nm.TheheavymetalcontentofthesedimentsampleswasdeterminedusingXRFanalysis.

Partialleastsquaresregression(PLSR)andsupportvectorregression(SVR)wereusedtoestablishmodelsforpredictingtheheavymetalcontentofsedimentsamples.Thespectraldatawerepre-processedusingstandardnormalvariate(SNV)anddetrendednormalization(DN)methods.Thespectralvariableswereselectedusingthesuccessiveprojectionalgorithm(SPA).

Results:

TheresultsshowthatbothPLSRandSVRmodelscanpredictheavymetalcontentinsedimentsamplesusingground-basedopticalspectra.However,SVRoutperformedPLSRintermsofpredictionaccuracy.Thecorrelationcoefficients(R²)oftheSVRmodelswere0.87forZncontent,0.82forPbcontentand0.77forCdcontent.ThePLSRmodelshadcorrelationcoefficientsof0.83,0.77and0.71forZn,PbandCdcontent,respectively.

Thespectralvariableswiththehighestcorrelationwithheavymetalcontentwerelocatedinthevisibleandnear-infraredregion(400-900nm).Thebandsat531nm,557nm,690nmand745nmwerefoundtobemoststronglycorrelatedwithZncontent.Thebandsat537nm,594nm,634nm,and915nmwerefoundtobemoststronglycorrelatedwithPbcontent.Thebandsat526nm,584nm,714nmand842nmwerefoundtobemoststronglycorrelatedwithCdcontent.

Conclusion:

Ourstudydemonstratesthatground-basedopticalspectracanbeusedtoestimateheavymetalcontentinwatersystemsediments,providingacost-effectiveandtime-savingmethodformonitoringwaterpollution.SVRisasuperiormethodforthepredictionofheavymetalcontent,withhigherpredictionaccuracythanPLSR.Thespectralvariablesinthevisibleandnear-infraredregion(400-900nm)aremoststronglycorrelatedwithheavymetalcontent.Thismethodcanbefurtherappliedtootherwatersystemsforpollutionmonitoringandmanagement.Theuseofground-basedopticalspectraforestimatingheavymetalcontentinwatersystemsedimentshasseveraladvantagesovertraditionallaboratoryanalysismethods.Firstly,itisanon-destructivemethodthatdoesnotrequiresamplepreparation,thuspreservingtheintegrityofthesedimentsample.Secondly,itisacost-effectiveandtime-savingmethod,asitcanprovideon-sitemeasurementsandreducetheneedforlaboratoryanalysis.Thirdly,itcanprovidespatiallyresolvedinformation,makingitsuitableformappingthedistributionofheavymetalpollutioninwatersystems.

Theresultsofthisstudysuggestthatsupportvectorregressionisapromisingmethodforaccuratelypredictingheavymetalcontentinwatersystemsedimentsusingground-basedopticalspectra.Moreover,thespectralvariablesinthevisibleandnear-infraredregion(400-900nm)werefoundtobemoststronglycorrelatedwithheavymetalcontent.Thisinformationcanbeusedtooptimizespectraldatacollectionandanalysisinfuturestudies.

Theapplicationofthismethodcanprovidevaluableinformationforthemanagementandmonitoringofwaterresourcepollution.Itcanhelpidentifyhotspotsofheavymetalpollutioninwatersystems,prioritizepollutioncontrolmeasures,andevaluatetheeffectivenessofremediationefforts.Therefore,theuseofground-basedopticalspectraformonitoringheavymetalpollutioninwatersystemscancontributetothesustainabilityofourenvironmentandprotecthumanhealth.Inadditiontoitsadvantagesovertraditionallaboratoryanalysismethods,theuseofground-basedopticalspectraforestimatingheavymetalcontentinwatersystemsedimentsalsohasthepotentialtobeusedforreal-timemonitoringofheavymetalpollution.Thiscouldenabletimelyandeffectiveremediationeffortstobeimplementedtomitigatetheimpactofheavymetalcontaminationonaquaticlife,ecosystemservices,andhumanhealth.

Moreover,theuseofground-basedopticalspectracanalsoaidintheidentificationofthesourcesofheavymetalpollutioninwatersystems.Byanalyzingthespectraldataofsedimentsamplescollectedfromdifferentlocationswithinawatersystem,itmaybepossibletoidentifythesourcesofpollutionbasedonthespectralsignatureoftheheavymetals.Thisinformationcanthenbeusedtodeveloptargetedpollutioncontrolmeasures,suchassourcereductionorpollutantremediation,toreducetheamountsofheavymetalsenteringthewatersystem.

Overall,theuseofground-basedopticalspectraformonitoringandmanagingheavymetalpollutioninwatersystemshassignificantpotentialtoenhancethesustainabilityofourenvironmentandprotecthumanhealth.Thismethodcanprovideefficient,cost-effective,andnon-destructivemeasurementsofheavymetalcontent,whichcaninformremediationeffortsandpollutioncontrolmeasures,aswellascontributetoourunderstandingofthesourcesofpollution.Ground-basedopticalspectracanalsobeusedtostudytheimpactofheavymetalpollutiononaquaticlifeandecosystemhealth.Throughtheanalysisofspectrafromsedimentscollectedindifferentlocationsacrossawatersystem,researcherscangaininsightsintothechemicalcompositionofthesedimentsandthetypesofheavymetalspresent.Theseinsightscanhelpresearchersunderstandhowheavymetalpollutionaffectstheecosystemservicesprovidedbywatersystemsandthehealthofaquaticspecies.

Furthermore,suchstudiescanhelpidentifythekeydriversofheavymetalpollutionandassessthelong-termimpactsofthesepollutantsontheenvironment.Forinstance,byanalyzingthespectraldataofsedimentscollectedovermultipleyearsinagivenlocation,researcherscanobservetrendsinheavymetalconcentrationsovertimeanddeterminethefactorsthatcontributetothesetrends.Thisinformationcanthenbeusedtoinformpolicydecisionsanddevelopeffectiveinterventionstopreventormitigatetheimpactsofheavymetalpollution.

Inconclusion,theuseofground-basedopticalspectraforestimatingheavymetalcontentinwatersystemsedimentshassignificantadvantagesovertraditionallaboratoryanalysistechniques.Itoffersacos