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土壤有机质和镉对金霉素吸附-解吸的影响
摘要点击 2701  全文点击 1388  投稿时间:2010-01-11  修订日期:2010-05-18
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中文关键词  金霉素  褐土  有机质  吸附  解吸  
英文关键词  chlortetracycline(CTC)  cinnamon soil  organic matter  sorption  desorption  cadmium
作者单位
万莹 南开大学环境科学与工程学院环境污染过程与基准教育部重点实验室, 天津300071 
鲍艳宇 南开大学环境科学与工程学院环境污染过程与基准教育部重点实验室, 天津300071 
周启星 南开大学环境科学与工程学院环境污染过程与基准教育部重点实验室, 天津300071中国科学院沈阳应用生态研究所陆地生态过程重点实验室, 沈阳110016 
中文摘要
      金霉素已经广泛应用于兽药生产和疾病治疗. 由于动物废弃物的土地应用和其它输入来源,重金属与四环素类抗生素往往共存于土壤环境中. 基于OECD 106号指导准则,采用批量平衡实验方法,研究了金霉素及其与镉复合后在褐土及去有机质褐土中的吸附和解吸行为. 结果表明,在单一和复合污染条件下,金霉素在褐土和去有机质褐土中的吸附和解吸等温线都可以用Freundlich模型进行良好地拟合. 在金霉素单一污染和金霉素 镉复合污染条件下,去除有机质能够增加金霉素在褐土中的吸附容量(Kf)和吸附强度(1/n). 金霉素在土壤上的解吸过程存在明显的滞后现象,在单一污染物情况下,金霉素在去有机质褐土的解吸滞后现象增强,其HI从0.81增加到1.06;而加镉后这种现象反而有所减弱,其HI从1.11减低到0.84.本研究为建立更加完善的模型以预测金霉素环境浓度或评价其环境风险,提供了可利用的数据和参数.
英文摘要
      Chlortetracycline (CTC) has been widely used in veterinary medicines and disease treatment. Heavy metals and antibiotics often coexist in soil due to land application of animal wastes and other sources of inputs. On the basis of the OECD Guideline 106, the batch equilibrium experimental method was employed to investigate sorption and desorption processes of CTC in cinnamon soil with and without soil organic matter (SOM) and examine the effect of Cd2+ on these processes. Results showed that the Freundlich model was the best isotherm to describe the experimental data for adsorption and desorption of CTC in soil on single and combined pollution conditions. In these a single chlortetracycline pollution and chlortetracycline-Cd combined pollution conditions, removal of SOM could increase the CTC adsorption capacity (Kf) and adsorption intensity (1/n). The apparent adsorption-desorption hysteresis was found in cinnamon soil with and without SOM. In single pollution condition, the removal of SOM could significantly increase HI in cinnamon soil from 0.81 to 1.06 In all cases of CTC combined with Cd desorption studies, it had been known that HI of CTC in soils with SOM(1.11) were higher than those without SOM(0.84). This study was provided available data and parameters to set a more complete model to predict environmental concentration of CTC and evaluation their environmental risk.

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