激光诱导击穿原子光谱在土壤分析中的应用

土壤分析是土壤学研究及应用的前提和基础,传统化学土壤分析方法逐渐不能适应现代土壤学海量信息数据快速获取的需求。激光诱导击穿光谱作为一种全新的、反映土壤组成元素原子信息的光谱技术,其无需对样品进行复杂前处理,可实现原位、快速、多元素连续在线检测,每条光谱记录土壤样本独一无二的特征,可以视为土壤“指纹”,成为现代土壤分析的有效技术之一。首先介绍和分析了激光诱导击穿原子光谱的原理、光谱获取的主要影响因素、光谱数据处理的化学计量学方法等;然后阐述和梳理了基于激光诱导击穿光谱技术在土壤分析方面的应用成果和进展,包括土壤鉴定、土壤养分评估、土壤重金属测定、微观/介观尺度土壤原位表征等;最后讨论和总结了激光诱导击穿光谱技术在土壤分析中所面临的挑战及其应用展望。     

含水量对LIBS检测土豆中Pb元素灵敏度的影响

农产品重金属污染问题越来越严峻,急需发展一种快速检测新方法。激光诱导击穿光谱(LIBS)是近年来兴起的物质成分快速无污染的分析方法。但由于农产品成分复杂,受到含水量、有机质元素等复杂基体的影响,导致LIBS在农产品检测方面的研究还缺乏系统的分析。本工作以实验室配置的含铅(Pb)污染的土豆样品为例,通过LIBS技术对不同含水量土豆中的Pb元素进行了检测,探讨了含水量对土豆中铅元素灵敏度的影响。试验结果表明含水量对LIBS信号有明显的干扰,样品越干燥,灵敏度越高。对完全干燥的土豆样品进行了LIBS光谱采集和Pb含量原子吸收光谱(AAS)真实浓度检测,建立了Pb元素真实浓度与其LIBS强度关系模型,定标结果显示模型具有较好的相关系数。研究说明LIBS对Pb污染严重的土豆样品具有一定的检测可行性,对于低浓度的样品,检测能力仍有很大的提升空间。     

海带中铬含量的激光诱导击穿光谱研究分析

以基于激光诱导击穿光谱技术对海带中铬元素进行快速定量检测为目的。采用1 064 nm的调Q纳秒级Nd:YAG激光器作为光源,用高精度光谱仪进行采集光谱。研究分析Cr元素激光诱导击穿光谱强度的时间演化特性,实验表明最佳延时时间为1.2μs。对含有不同的浓度Cr元素的海带样品进行测量,建立样品中Cr元素浓度与其激光诱导击穿光谱强度间的定标曲线,线性相关系数达到0.990 29,检测限为54.62μg/g。研究表明:激光诱导击穿光谱技术能够用于检测海带中铬元素含量,并具有实时快速无损的测量能力。     

激光诱导击穿光谱分析新鲜桔叶重金属元素铬

为使激光诱导击穿光谱技术(LIBS)能实际应用于环境污染相关的领域,选择新鲜桔叶片样品作初步实验研究。该实验用纳秒级Nd:YAG激光器(波长:1 064 nm)为光源,在实验室自然大气环境下诱导新鲜桔叶片产生等离子体,研究了延时时间和激光能量对新鲜桔叶片中铬元素激光诱导击穿光谱特性的影响,综合评价其信背比和信号强度得到了相应的最佳检测条件:最佳延时1.6μs,最佳激光能量120 mJ。建立了Cr元素的定标曲线,并且定量分析了在最佳实验条件下样品中铬元素浓度。结果表明Cr元素浓度在50～800μg/mL范围内,Cr元素含量和光谱相对强度之间有较好的线性关系。实验也表明LIBS技术是一种快速检测新鲜植物叶片中重金属元素含量的有效工具。     

Rapid,non-destructive carbon analysis of forest soils using neutron-induced gamma-ray spectroscopy

Forest soils are pivotal to understanding global carbon (C) cycling and evaluating policies for mitigating global change. However, they are very difficult to monitor because of the heterogeneity of soil characteristics, the difficulty of representative sampling, and the slow time scale of response to environmental change. Here we demonstrate that use of gamma-ray spectroscopy facilitates in situ non-destructive analysis of C and other elements in forest soils. In this approach the element-specific gamma-rays are induced by fast and thermal neutrons interacting with the nuclei of the elements present in the soil. Background gamma-rays emanating from naturally occurring radionuclides in the forest are recorded as well. We applied this approach in a mature northern hardwood forest on glacial till soils at the Bartlett Experimental Forest in New Hampshire, USA. The inelastic neutron scattering (INS) system yielded strong signals in gamma-ray counts/h, from C and other elements present in the soil matrix that included silicon, oxygen, hydrogen, iron, aluminum, manganese and potassium. The INS sensitivity for carbon was 20.656 counts h⁻¹ kg⁻¹ C m⁻² based on current net C gamma-ray counts and the data for the O horizon and mineral soil to a depth of 30 cm obtained from a nearby quantitative soil pit (7.35 kg C m⁻²). We estimate the minimum detectable change to be ∼0.34 kg C m⁻², which is ∼5% of the current soil C content, and the minimum detectable limit to be ∼0.23 kg C m⁻². Eight % reproducibility from 11 measurements was limited, in part, by the large variability in the system counting geometry due to the uneven forest microtopography. The INS approach has the potential to revolutionize belowground monitoring of C and other elements, because the possibility of detecting a 5% change in forest soils has not been possible with destructive sampling methods.     

A novel method for ash analysis in wheat milling fractions by using laser-induced breakdown spectroscopy

Ash content is an important quality control parameter in milling industry. Measurement of ash content is routinely performed using standard ash analysis method in which the sample is burned at 500–600 °C for 5–6 h. However, this method is not convenient for industrial applications, and thus, rapid and reliable methods are needed to be developed. The aim of this study was to develop a new method for ash analysis to be used in wheat milling fractions by using laser induced breakdown spectroscopy (LIBS). LIBS is an optic based multi-elemental, spectroscopic method which can analyze high number of samples in a considerably short time. In the study, wheat flour, whole wheat meal and semolina samples with different ash contents were analyzed using LIBS, and the spectra were evaluated with partial least squares (PLS) method. The results were correlated with the ones taken from standard ash analysis method. Calibration graph showed good linearity with the ash content between 0.48 and 2.44%, and 0.997 coefficient of determination (R²). Limit of detection for ash analysis was calculated as 0.11%. The results indicated that LIBS is a promising and reliable method with high sensitivity for routine ash analysis in milling industry.     

Pasture Vegetation Elemental Analysis by Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is a new technique for the analysis of plant material. This study investigates the application of LIBS to pasture-based plant samples. The LIBS measurements were obtained from pelletized pasture samples (100 samples) that had been also analyzed by inductively coupled plasma–optical emission spectroscopy (ICP-OES) following microwave digestion for calibration and comparison purposes. Comparisons for elements sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), boron (B), phosphorus (P), and sulfur (S) showed that LIBS could be used for almost all the standard profile total elements with concentrations down to low mg/kg levels (observed error of Na: 0.024 percent, K: 0.18 percent, Mg: 0.016 percent, Ca: 0.073 percent, P: 0.017 percent, Mn: 31 mg/kg, Fe: 150 mg/kg, Zn: 6.6 mg/kg, and B: 1.1 mg/kg). Elemental analysis at less than mg/kg levels was not possible using LIBS. The elements S and Cu were particularly difficult to analyze with reliability using LIBS at the concentration levels found in the plant samples. Replacing microwave digestion and subsequent ICP analysis with a direct analysis of dried plant samples using LIBS has the potential to improve the productivity and reduce the cost of testing.     

蔬菜中Ca含量的LIBS快速检测研究

蔬菜中矿质元素含量是评价其质量安全的一项重要指标。为了实现对蔬菜中矿质元素的快速检测,采用激光诱导击穿光谱(LIBS)装置对国家标准成分蔬菜样品中的Ca元素进行分析,获取样品的LIBS图谱,并分别建立样品Ca元素真实浓度与其LIBS特征谱线Ca II 315.887和Ca II 317.933强度之间的关联模型。结果表明,LIBS能清晰探测出样品中高浓度的元素;但对于低浓度的重金属元素,检测灵敏度达不到要求。可以看出,Ca元素定量分析模型线性相关性较好;对于高浓度的叶菜类蔬菜,Ca元素含量的预测准确度较高;但对于低浓度的根茎类和果实类蔬菜,模型预测准确度较差。该试验说明,LIBS用于检测具有复杂基体的蔬菜样品时,对元素的检测效果较好,是否单纯检测某类别(比如叶菜类)的蔬菜样品受基体效应的影响更小,从而提高检测精度,有待于进一步研究。     

水中重金属元素镉的激光诱导击穿光谱快速检测研究

以激光诱导击穿光谱技术实时检测水中的重金属镉元素为研究目的,对不同浓度的含镉水溶液进行激光诱导击穿光谱试验。确定在以361.05 nm为镉元素特征分析谱线时,较佳采集延迟时间为1 680 ns,较佳的激光能量值为110 m J。采用线性拟合的方法对镉元素进行定量分析,拟合曲线的线性相关系数为0.995 38,两验证样品的相对误差分别为9.21%、8.50%。研究表明激光诱导击穿光谱技术对水中镉元素进行实时、在线检测是可行的,但检测灵敏度还有待进一步提高。     

脐橙果皮镉铅含量激光诱导无损检测试验

为了验证激光诱导击穿光谱(LIBS)快速无损检测农产品中重金属污染物的可行性,对赣南脐橙样品进行了实验室镉铅污染处理。首先对样品LIBS试验参数进行了优化分析,根据美国NIST(National Institute of Standards and Technology)原子光谱数据库,确定试验用的最佳特征谱线位置分别为Cd226.502nm和Pb405.783nm。观测了光谱信噪比和强度随着延迟时间和激光能量的变化规律,综合考虑结果表明,最佳延迟时间和激光能量分别为1300ns和130mJ。利用优化的LIBS试验参数对镉(Cd)和铅(Pb)元素的光谱信息进行了采集。同时,采用原子吸收分光光度计对脐橙表皮中镉铅元素的真实浓度进行了检测,建立了镉铅元素特征谱线强度与真实浓度之间的关系模型,相关系数分别为0.94669和0.96059。由定标模型得到镉铅元素的检测限分别为17.375和22.782μg/g。为了验证模型的准确性,采用3个样品做了定标曲线反演分析,预测值与真实值之间的相对误差保持在10%左右。试验结果表明,LIBS技术能应用于农业安全方面的农产品重金属Cd、Pb的快速无损检测。