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Optimization Of Process Parameters For Thermal Desorption Of Oil-contaminated Soil

Posted on:2023-09-12Degree:MasterType:Thesis
Country:ChinaCandidate:J X WangFull Text:PDF
GTID:2531307163490684Subject:Environmental engineering
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The properties of petroleum-contaminated soil in our country are changeable,and the factors affecting thermal desorption efficiency are complex.In engineering applications,there is often a mismatch between operating parameters and soil properties,resulting in poor desorption effect,substandard remediation effect,or excessive thermal desorption.These are the key factors affecting the practical engineering application effect of thermal desorption technology.This paper focused on the factors affecting thermal desorption of oil-contaminated soil,screened out the important parameters affecting the desorption efficiency,explored the differences and influencing mechanisms of thermal desorption efficiency of different types of polluted soil.And established a thermal desorption method based on soil characteristics and pollution concentration.The process parameter prediction model was attached.The following research results were obtained:(1)Thermal desorption process parameters(desorption temperature,desorption time)and contaminated soil properties(water content,oil content,heavy component ratio,soil type)had a significant impact on the desorption efficiency.The desorption efficiency was positively correlated with the temperature,but the increase of the desorption rate caused by the heating gradually weakens,and the desorption efficiency reached 86.14% at 350 °C.Prolonged the heating time can improve the desorption rate of petroleum pollutants,but the highest desorption rate was affected by the desorption rate.With the limitation of temperature,the desorption rate remained unchanged for prolonged time.The increase of oil concentration in the soil led to a gradual decrease in the desorption efficiency.The influence of soil moisture content on the desorption efficiency showed a trend of promoting first and then inhibiting.The increase of the heavy component ratio inhibited the desorption of oil and reduced the desorption efficiency.The desorption efficiency increased with the increasing of soil particles,and the increase rate of the desorption efficiency decreased with the increase of the particle size.(2)The thermogravimetric characteristics showed that the thermal desorption of petroleum-contaminated clay minerals could be divided into three stages.The volatilization stage of light components in stage 1,the volatilization and cracking stage of light components in stage 2,and the heavy components volatilization and cracking in stage 3.Montmorillonite and chlorite promoted thermal desorption,while kaolin showed inhibition.Compared with kaolin and chlorite,montmorillonite could crack petroleum to generate a variety of C2+ light hydrocarbons at 150~350°C.The catalytic ability was the strongest among the three.The pore properties,adsorption properties and catalytic properties of clay minerals played different roles in different desorption stages.The three of them comprehensively affected the thermal desorption process of oil-contaminated soil.(3)For three soil types,sandy soil,loam soil and sandy loam soil,the thermal desorption process parameter prediction models were established respectively.The key factors affecting the thermal desorption efficiency of petroleum were determined.The key influencing factors of sand and loam types polluted soil are temperature and heavy component ratio.The p-values of the prediction equations are 0.827 and 0.91,respectively.The key influencing factors of the sandy loam type polluted soil were temperature,water content and heavy component ratio.The prediction two-factor interaction(2FI)model was established by nonlinear fitting.The p-value of the prediction equation reached 0.935.The parametric prediction model equations were validated.The errors between the actual desorption efficiency and the predicted desorption efficiency were 2.69%,6.28% and 0.92%,respectively.
Keywords/Search Tags:Thermal desorption, Oil-contaminated soil, Clay minerals, Predictive model
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