光谱学与光谱分析, 2016, 36 (3): 827, 网络出版: 2016-12-09
激光诱导击穿光谱技术在土壤元素检测中的应用
Study on Soil Elements Detection with Laser-Induced Breakdown Spectroscopy: A Review
激光诱导击穿光谱 土壤元素 检测 研究进展 Laser-induced Breakdown Spectroscopy Soil elements Detection Research tendency
摘要
激光诱导击穿光谱(laser-induced breakdown spectroscopy, LIBS)是一种原子发射光谱, 具有对样本简单(或不需要)预处理, 多元素同步、 远距离测量, 适用性广等独特优势。 因此, LIBS分析技术被看作是未来化学分析和快速绿色分析技术领域的新兴技术。 目前, 土壤污染(重金属、 有机污染等)检测与防治已成为现代农业和农业可持续发展关注和研究的热点问题。 介绍了常见LIBS系统的结构组成以及工作原理, 综述了LIBS技术对土壤中大量营养元素, 重金属元素和土壤相关其他物质的研究现状和主要进展, 提出了LIBS检测技术在土壤元素等方面的研究方向和发展趋势。
Abstract
Laser-induced breakdown spectroscopy (LIBS), as a kind of atomic emission spectroscopy, has been considered to be a future new tool for chemical analysis due to its unique features, such as no need of sample preparation, stand-off or remote analysis. What’s more it can achieve fast and multi-element analysis.Therefore, LIBS technology is regarded as a future “SurperStar” in the field of chemical analysis and green analytical techniques. At present, rapid and accurate detection and prevention of soil contamination (mainly in pollutants of heavy metals and organic matter) is deemed to be a concerned and serious central issue in modern agriculture and agricultural sustainable development. In this paper, the reseach achievements and trends of soil elements detection based on LIBS technology were being reviewed. The structural composition and foundmental of LIBS system is first briefly introduced. And the paper offers a review of on LIBS applications and fruitsincluding the detection and analysis of major element, nutrient element and heavy metal element. Simultaneously, some studies on soil related metials and fields are briefly stated. The research tendency and developing prospects of LIBS in soil detection are presented at last.
余克强, 赵艳茹, 刘飞, 彭继宇, 何勇. 激光诱导击穿光谱技术在土壤元素检测中的应用[J]. 光谱学与光谱分析, 2016, 36(3): 827. YU Ke-qiang, ZHAO Yan-ru, LIU Fei, PENG Ji-yu, HE Yong. Study on Soil Elements Detection with Laser-Induced Breakdown Spectroscopy: A Review[J]. Spectroscopy and Spectral Analysis, 2016, 36(3): 827.