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Experimental Investigation On Buildingphenolic Wastewater Predictionmodelby UV-PLS Method

Posted on:2014-11-24Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y NingFull Text:PDF
GTID:2251330401973538Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
The development of the chemical and pharmaceutical industry provides unprecedented protection for human quality of life and health, the development and application of a variety of synthetic chemicals has laid a solid material foundation for human life. However, a variety of synthetic chemicals while facilitating human life, but also brought a series of environmental pollution problems. Production and use of various chemical substances into the environment, environmental quality and human health may cause serious harm. Phenolic compounds are a class is moderately toxic chemicals, widely used in gas, coke, oil refining, metallurgy, chemical organic synthesis, machinery manufacturing, glass, petrochemical, wood fibers, plastics, pharmaceuticals, pesticides, paint and other industrial fields. Most phenolic compounds with endocrine disruption and possibly carcinogenic, more harmful to plants, animals and human. Traditional phenolic compounds removal method is complex, higher cost, it takes a long time, and may cause secondary pollution, in order to further improve the efficiency in the removal of phenolic compounds to provide more technical means for the actual processing of phenolic wastewater, phenolic compounds removal of new methods of research has a very important significance.In this thesis elaborates harm the environment of industrial wastewater and wastewater containing phenol and its commonly used detection approach also highlights, in addition to the common physical treatment, chemical treatment and biological treatment method outside the three categories, three more promising new process for treatment, activated carbon supported TiO2photocatalytic degradation method, enzymatic treatment method of wastewater containing phenol and phenol-containing wastewater supercritical processing method.Phenolic detection few alternative methods, the the common phenolic wastewater phenol detection method for the4-amino antipyrine spectrophotometry, fluorescence and gas chromatography. The main drawback of the method is not large batch processing analysis of phenolic wastewater component. This paper presents a for detection method inefficient solution:UV spectrophotometer with chemometrics intermediate phenolic wastewater often (which contains phenol, benzoquinone, maleic acid,4the phenoxyphenol and2-2’biphenol) establish the mathematical prediction model. And detailed analysis of the effect of the model’s predictions. The final model to evaluate the conclusions derived as follows:when the concentration of the analytes in the unknown solution is greater than5mg/L, the model’s predictive value compared with the true value of just less than2%error, the model for the unknown solution The concentration of each component of prediction accuracy:2-2biphenol maleic acid benzoquinone> phenol>4-phenoxyphenol.The experimental model to predict the focus is to determine the degradation of phenol in different concentrations of wastewater, for other detection method, UV spectroscopy of obvious advantages:First of all common laboratory equipment. The main experimental equipment for UV spectrophotometer, the device is currently higher penetration rate, which laid the foundation for the popularity of the detection method. Followed by traditional detection methods, having the advantages of speed, high accuracy, and can handle large volumes of solution to be measured within-a very short time. And within the scope of the prediction of the model itself has a good reliability. For testing costs again, without considering its basic cost is negligible the UV spectrophotometer loss, modeling compared to other prediction methods. This is also the great advantages of this method.
Keywords/Search Tags:phenolic wastewater UV, spectrophotometer partial least squares method, mathematical model model evaluation
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