污泥干化芦苇床渗滤液中CODCr和TP浓度预测模型
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2020-03-30 10:01:42
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第29卷第8期2016年8月环境科学研究ResearchofEnvironmentalSciencesVoI.29.No.8Aug.,2016崔玉波,孙红杰,张万筠,等.污泥干化芦苇床渗滤液中CODc,和TP浓度预测模型[J].环境科学研究,2016,29(8):1224·1229.CUIYubo,SUNHongjie,ZHANGWanjun,eta1.PercolateCODc,andTPpredictionmodelsinsludgetreatmentwetland[J].ResearchofEnvironmentalSciences,2016,29(8):1224-1229.污泥干化芦苇床渗滤液中CODcr和TP浓度预测模型崔玉波1,孙红杰h,张万筠1,贺张伟21.大连民族大学环境与资源学院,辽宁大连1166002.哈尔滨工业大学市政环境工程学院,黑龙江哈尔滨150001摘要:为便于水质管理,在大连开发区污水处理厂设立了1个传统污泥干化床和2个污泥干化芦苇床,根据系统出水P(COD。,)和P(TP)检测数据的平稳系列特点,采用ARIMA时间序列分析模型对出水P(COD。,)和P(TP)进行模拟和预测.结果表明:ARIMA(1,0,0)模型可较好地模拟和预测出水P(COD。,)的变化,尺2达0.577以上,预测相对误差在一10%一19%之间,实测值和预测值之比处于0.8一1.2之间;ARIMA(6,0,0)模型能较好地模拟和预测污泥处理湿地渗滤液出水P(TP)的变化,R2在0.487以上,预测相对误差在一4%一16%之间,实测值和预测值之比处于0.8~1.2之间.研究显示,所构建的ARIMA模型可用于污泥处理湿地系统运行过程中渗滤液出水P(COD。,)和P(TP)的预测.关键词:ARIMA模型;COD。,;污泥处理湿地;TP中图分类号:X703文章编号:1001—6929(2016)08-1224—06文献标志码:ADOI:10.13198/j.issn.1001-6929.2016.08.17PercolateCODc,andTPPredictionModelsinSludgeTreatmentWetlandCUIYub01,SUNHongjieh,ZHANGWanjunl,HEZhangwei21.SchoolofEnvironmentandResources,DalianNationalitiesUniversity,Dalian116600,China2.SchoolofMunicipalandEnvironmentalEngineering,HarbinInstituteofTechnology,Harbin150001,ChinaAbstract:Sludgetreatmentwetlandcombinedwithaconventionalsludgedryingbedandconstructedwetlandisasludgetreatmentandstabilizationtechniquewhichmakesfulluseofplantsandmicroorganismsforsludgedewateringandstabilization.Leachatecompositionsarechangedduringtheprocessofsludgedewateringbygravityandinfiltrationinthewetland,whichhasaneffectontheeffluentquality.Forthepurposeofwaterqualitymanagement,accordingtothecharacteristicsofstationaryseriesforleachateeffluentCODc,concentrationandthetotalphosphorusconcentrationdatainsludgetreatmentwetlandsystem,autoregressiveintegratedmovingaverage(ARIMA)modelwasusedtosimulateandpredictleachateeffluentCODc,andtotalphosphorusconcentrations.TheresultsshowedthatARIMA(1,0,0)modelcouldbeusedtosimulateandpredictthevariationofleachateeffluentCODc,concentration.ThecorrelationcoefficientR2wasgreaterthan0.577.Therelativeerrorsofpr
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