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土壤中砷形态提取和分析的条件改进

Improvement of Conditions for Extraction and Analysis of Arsenic Species in Soil

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【作者】 安礼航陈阳陈志良刘浩辉刘敏超张建强

【Author】 An Lihang;Chen Yang;Chen Zhiliang;Liu Haohui;Liu Minchao;Zhang Jianqiang;School of Biotechnology and Health Sciences, Wuyi University;South China Institute of Environmental Science, Ministry of Environmental Protection;Research Center for Soil Treatment and Restoration of Heavy Metal Pollution in Guangdong Province;

【通讯作者】 刘敏超;

【机构】 五邑大学生物科技与大健康学院环境保护部华南环境科学研究所广东省农田重金属污染土壤治理与修复工程技术研究中心

【摘要】 指出了通过改进砷的提取条件,以尽可能高的提取率来分析土壤和沉积物中的无机砷形态,同时可以最小化As(Ⅲ)和As(Ⅴ)之间的形态转化。选取磷酸混合盐酸作为提取剂,比较并优化了不同配比、不同的辅助提取手段、不同的预还原剂用量对提取土壤中不同形态砷的效率,并测定了土壤标准物质(GSS-32、GSS-33、GSS-35)和莲花山矿区周围农田土壤中各形态的砷含量以供参考。结果表明:使用1.5 mol/L的磷酸混合盐酸(4∶1)对土壤进行98℃水浴提取3次,每次1 h,浸取率最佳,可达91.34%。土壤标准物质和农田土壤中以As(Ⅴ)为主,占95.9%以上。精密度实验表明,相对误差小于3%(n=6,RSD,0.695~2.176%),该方法的加标回收率为94.87%~100.25%,可作为砷形态分析的理想方法。

【Abstract】 The extraction conditions of arsenic were improved, and the inorganic arsenic species in soils and sediments were analyzed with the highest possible extraction rate, while the morphological transformation between As(III) and As(V) was minimized. Phosphoric acid and hydrochloric acid were used as extractant to compare and optimize the effects of different ratios, different auxiliary extraction methods and different pre-reducing agents on the extraction of species of arsenic in soil, and the arsenic content of various forms in the soil standard materials(GSS-32、GSS-33、GSS-35) and the soil around Lianhua Mountain mining area were determined for reference. The results showed that the soil subjected to 98 ℃ water bath heating extraction with 1.5 mol/L of phosphoric acid and hydrochloric acid(4:1) 3 times for 60 min each time can get the best extraction rate, up to 91.34%. As(V) is the main component of soil standard materials and farmland soil, accounting for more than 95.9%. The measurement accuracy experiments show that the relative error was less than 3%(n=6, RSD, 0.695~2.176%). Recovery studies were carried out and the obtained values were 94.87~100.25%, which could be an ideal method for arsenic speciation analysis.

【基金】 国家重点研发计划(编号:2017YFD0801300);广东省教育厅特色创新类项目(编号:2015KTSCX142);广东省科技计划项目(编号:2017B020203001);广东省自然基金(编号:2017A030313245);江门市农业科技攻关计划项目(编号:江科[2015]274号)
  • 【文献出处】 绿色科技 ,Journal of Green Science and Technology , 编辑部邮箱 ,2019年08期
  • 【分类号】X53;X833
  • 【被引频次】3
  • 【下载频次】394
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