




下载本文档
版权说明:本文档由用户提供并上传,收益归属内容提供方,若内容存在侵权,请进行举报或认领
文档简介
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
温馨提示
- 1. 本站所有资源如无特殊说明,都需要本地电脑安装OFFICE2007和PDF阅读器。图纸软件为CAD,CAXA,PROE,UG,SolidWorks等.压缩文件请下载最新的WinRAR软件解压。
- 2. 本站的文档不包含任何第三方提供的附件图纸等,如果需要附件,请联系上传者。文件的所有权益归上传用户所有。
- 3. 本站RAR压缩包中若带图纸,网页内容里面会有图纸预览,若没有图纸预览就没有图纸。
- 4. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途。
- 5. 人人文库网仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对用户上传分享的文档内容本身不做任何修改或编辑,并不能对任何下载内容负责。
- 6. 下载文件中如有侵权或不适当内容,请与我们联系,我们立即纠正。
- 7. 本站不保证下载资源的准确性、安全性和完整性, 同时也不承担用户因使用这些下载资源对自己和他人造成任何形式的伤害或损失。
最新文档
- 湖南省炎德英才大联考2025届高三下学期第二次质量检测试题(语文试题)含解析
- 2025年宁夏宁川市兴庆区长庆高级中学高三下学期第一次月考(4月)英语试题试卷含解析
- 辽宁商贸职业学院《中医外科学针灸》2023-2024学年第二学期期末试卷
- 吉林省延边州敦化市2025届小升初必考题数学检测卷含解析
- 武汉工程大学邮电与信息工程学院《室内类型设计》2023-2024学年第二学期期末试卷
- 山东体育学院《语言学基础》2023-2024学年第一学期期末试卷
- 七年级数学下册第9章多边形9.2多边形的内角和与外角和多边形的内角和教案2新版华东师大版
- 皖江工学院《规划手绘效果图表现技法》2023-2024学年第二学期期末试卷
- 河北省沧州市孟村回族自治县2024-2025学年七年级上学期11月期中教学质量监测数学试卷(含答案)
- 机电工程管理试题及答案
- 手工滴胶课件完整版
- (现行版)江苏省建筑与装饰工程计价定额说明及计算规则
- 汽轮发电机组轴系扭振分析与保护方式研究
- 初三数学竞赛试题及答案解析
- JJF(纺织)095-2020土工布磨损试验机校准规范
- JJG 384-2002光谱辐射照度标准灯
- 报销单填写模板
- 小学劳动 包饺子课件
- 火力发电的基本知识课件
- 教师职业道德第二节-爱岗敬业资料课件
- 临检基础知识讲解:测定血糖的临床意义
评论
0/150
提交评论