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典型持久性有机污染物在PUF--空气中分配系数的定量构效关系研究.docx

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典型持久性有机污染物在PUF--空气中分配系数的定量构效关系研究 Title:QuantitativeStructure-PropertyRelationshipStudyofPartitionCoefficientsofTypicalPersistentOrganicPollutantsinPolyurethaneFoam(PUF)-Air Abstract: Persistentorganicpollutants(POPs)areaclassofenvironmentallyharmfulcompoundsthatresistdegradationandbioaccumulateintheenvironment.Theaccurateestimationoftheirpartitioncoefficientsiscrucialforunderstandingtheirfateandtransportinvariousenvironmentalcompartments.Thisstudyaimstoestablishaquantitativestructure-propertyrelationship(QSPR)modeltopredictthepartitioncoefficientsofPOPsinpolyurethanefoam(PUF)-airsystem,whichisanimportantsteptowardsassessingtheirenvironmentalbehavior. 1.Introduction ThepresenceofPOPsintheenvironmentposessignificantriskstohumanhealthandecosystems.Theirabilitytopersist,bioaccumulate,andbiomagnifyinvariousenvironmentalmatricesmakestheirenvironmentalfateandbehaviorcomplex.PartitioncoefficientsarefundamentalparametersusedtodescribethedistributionofPOPsbetweendifferentphases,andunderstandingthefactorsinfluencingtheirpartitioningbehaviorisvitalforriskassessmentandmanagement. 2.ExperimentalMethods Inthisstudy,acomprehensivedatasetofpartitioncoefficientsofPOPsinPUF-airsystemwascompiledfromexistingliterature.Thecompoundsincludedinthedatasetwereselectedbasedontheirpersistence,toxicity,andrelevancetoenvironmentalconcerns.Moleculardescriptors,suchasmolecularweight,octanol-waterpartitioncoefficient,andtopologicalindices,werecalculatedusingsoftwaretoolstorepresentthestructuralpropertiesofthecompounds. 3.ResultsandDiscussion Statisticalanalysiswasperformedonthedatasettoidentifythekeydescriptorsaffectingthepartitioncoefficients.MultiplelinearregressionandmachinelearningalgorithmswereemployedtodevelopQSPRmodelsforpredictingthepartitioncoefficientsofPOPsinPUF-airsystem.Theperformanceofthemodelswasassessedusingcross-validationandexternalvalidationtechniques. 4.Conclusion TheQSPRmodelsdevelopedinthisstudyprovideaquantitativeframeworkforpredictingthepartitioncoefficientsofPOPsinPUF-airsys