| In this work, quantitation methods for analyzing four chloroacetamide herbicides (alachlor, acetochlor, pretilachlor, butachlor) in algae (Scendesmus obliquus) and culture medium were developed. Vacuum filtration with mixed cellulose filter was applied for the purpose of separating algal cells with culture medium. Then extraction solvent, solvent volume and water content for extracting analyte from algal cells samples were optimized. The sample was extracted with20mL ethyl acetate, and then concentrated by rotary evaporator followed by addition certain amount of acetonitrile. All analytes were detected by GC-MS with internal standard calibration method. Average fortified recoveries ranged from86.4%-102.9%with relative standard deviations below15.1%in algal cells and culture medium. The LODs of four compounds in algal cells samples were not below0.005μg, while those in cluture medium were not below0.0002mg/L. The method is of good accuracy, precision, sensitivity and linear relationship. It can be used for analyzing alachlor, acetochlor, pretilachlor, butachlor and also for investigating their bioconcentration in algae.And then, the bioconcentration of alachlor, acetochlor in Scenedesmus obliquus were investigated. The results showed that the concentration of alachlor and acetochlor in culture medium remained constant from36h to96h. However the mass of the two herbicides in S. obliquus continuously increased with the time. The concentrations of alachlor and acetochlor, which were greatly influenced by growth dilution effect, were stable or decreased at initial growth stage but increased at the end of growth stage. High bioconcentration factors were obtained, ranging572-915for alachlor and376-1068for acetochlor respectively. The results suggested that S. obliquus has a great bioconcentration capability for chloroacetamide herbicides, which may cause the risk for aquatic ecosystem if the herbicides were used largely.Taking the growth of algae into account, three groups of biotic ligand models were derived based on exponential growth, linear growth, and logarithmic growth of S. obliquus, respectively. Each model was consisted of a growth curve equation and an equation about pesticide mass versus time. Logarithmic growth model acquired the best fitting results (coefficient of determination above0.9920) compared with other growth curve models. Furthermore, fitting the relationship between pesticide mass in algal cells versus time, model based on logarithmic growth acquired the best fitting results (coefficient of determination were more than0.9568). The results suggested that biotic ligand model based on logarithmic growth fits the bioconcentration kinetic of alachlor and acetochlor in S. obliquus. It was the first time for biotic ligand model applied in bioconcentration study of organic pollutants. The results suggested that mechanism of organic pollutants uptake by biont may be the same as biotic ligand model.The combined effect of alachlor and acetochlor on S. obliquus bioconcentration was also studied. Some of the data suggested combined effects of alachlor and acetochlor on the bioconcentration. For example, in the presence of alachlor or acetochlor, the bioconcentration mass of the other compound in algal cells was inhibited. However there was no consistent pattern for all results, therefore the kinetic models needed further evaluation. The combined effects reveal the complexity of organic pollutants bioconcentration, which will contribute to preciser environmental risk evaluation of organic pollutants.The combined effect results were further fitted by biotic ligand model mentioned previously. Logarithmic growth model acquired the best fitting results of growth curve of algae (coefficient of determination above0.9911) compared with others, which was consistent with the actual growth situation of algae. Considering the relationship between pesticide mass versus time, model based on logarithmic growth also acquired the best fitting results (coefficient of determination were more than0.95). The bioconcentration of alachlor and acetochlor was inhibited due to the combined effect. The uptake rate of alachlor and acetochlor decreased approximately by46%and68%, respectively. The results indicated that the combined effect on the bioconcentration of acetochlor was more than that on alachlor. Model Equation for competing study was derived, which could explain the possible mechanism of mutual antagonistic effect on bioconcentration of alachlor and acetochlor in S. obliquus in the presence of both alachlor and acetochlor. It was ratiocinated that acetochlor has a higher Michaelis constant than alachlor, which result in that the uptake rate of acetochlor by algal cells was significantly affected by alchlor, and the uptake rate of alachlor by algal cells was less significantly affected by acetochlor. This was the first study of combined effect on bioconcentration of two organic pollutants, and also the first time that biotic ligand model was applied in explaining combined effect of bioconcentration of two organic pollutants. Biotic ligand model overcame the defect of traditional toxicokinetics model which was incapable for explaining potential combined effect of bioconcentration, and provided a quantitative evaluation tool for combined effect of organic pollutants bioconcentration.Besides, the dissipation dynamics of flusilazole in mandarin and soil was investigated using different kinetic models. The samples were extracted by acetonitrile, cleaned up with PSA, and then analyzed by gas chromatography-mass spectrometry. The average recoveries were93.1%-107.7%in mandarin and soil with relative standard deviations not above5.1%. The LOD (limit of detection) was0.003μg/kg and0.001μg/kg for mandarin and soil, respectively. The method was of good accuracy, precision and sensitivity. Field trials were conducted in Hunan, Guangxi and Zhejiang province. The results showed that the dissipation of flusilazole in mandarin and soil followed first-order kinetics model more than that of second-order kinetics model. Based on first-order kinetics model, the half-lives of flusilazole were6.3-8.4days in mandarin and5.5-13.4days in soil; and flusilazole dissipated the fastest in Zhejiang, intermediate in Guangxi, and the slowest in Hunan. |
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