首页|抗生素在土壤颗粒态有机质纳米尺度上空间分布的检测方法研究

抗生素在土壤颗粒态有机质纳米尺度上空间分布的检测方法研究

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抗生素等新型污染物的环境污染与风险问题日益引起关注,土壤有机质对抗生素有重要的富集作用,传统方法无法定量检测抗生素在土壤颗粒态有机质(particulate organic matter,POM)上的空间分布是由于难以区分有机质和抗生素中的碳分布。为了解决这一难题,本试验采用纳米离子探针技术结合稳定性同位素技术建立了抗生素在POM纳米尺度上空间分布的检测方法。本方法用水做包埋剂制作POM超薄冷冻切片,用睫毛笔转移POM切片至亲水性硅片上,优化NanoSIMS测试条件,使用Image J和插件MIMI Image等进行图像数据处理。使用本方法对抗生素在黄河三角洲地区土壤POM中的空间分布进行了检测,得出在纳米尺度上分布在POM表面的抗生素占 94%,内部扩散占 6%。本试验建立的检测方法为探究土壤有机质中其他类型的有机污染物分布特征提供了方法学基础。
Method for Detecting Spatial Distribution of Antibiotics Sorption Mechanism in Soil Particulate Organic Matter at Nanoscale
Soil contamination by antibiotics and associated risks has been concerned greatly as a kind of pollution problem.Soil organic matter was major antibiotics sorbent.It's hard to quantitate the antibiotics dis-tributed in particulate organic matter(POM)by traditional methods,due to difficulties in distinguishing the carbon distribution between organic matter and antibiotics.To overcome the problems above,a method com-bined with NanoSIMS and 13 C isotopic tracer was set up to detect the spatial distribution of antibiotics onto POM at the nanoscale.Ultra-thin frozen slices of POM were made using water as embedding medium,and were transferred onto silicon wafer with an eyelash pen.Testing conditions of NanaSIMS were optimized,and image data were processed using Image J with plugin MIMI Image.The distribution of antibiotics onto POM separated from soil samples of the Yellow River Delta was detected using this established method.The results showed that 94%of total antibiotics were adsorbed on the surface of POM and 6%were diffused into POM at the nanoscale.The method established in this study could provide a new angle of view for explaining mecha-nisms of other organic pollutant adsorbed onto soil organic matter.

AntibioticsSoil particulate organic matterSpatial distributionNanoscaleNanoSIMS

谢寅雨、刘兴华

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山东省农业科学院畜牧兽医研究所/山东省畜禽疫病防治与繁育重点实验室,山东 济南 250100

抗生素 土壤颗粒态有机质 空间分布 纳米尺度 纳米离子探针

国家自然科学基金项目山东省科技型中小企业创新能力提升工程项目山东省农业科学院农业科技创新工程—优秀博士项目

420071372022TSGC1013CXGC2018E10

2024

山东农业科学
山东省农业科学院,山东农学会,山东农业大学

山东农业科学

CSTPCD北大核心
影响因子:0.578
ISSN:1001-4942
年,卷(期):2024.56(2)
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