Fast on-site detection of potentially toxic metals in soils is crucial for soil remediation and contamination monitoring. The moisture in soils is a challenge for quantitative analysis of potentially toxic metals. Here, we used laser-induced breakdown spectroscopy (LIBS) and partial least squares regression (PLSR) for fast on-site quantitative analysis of potentially toxic metals in wet soil samples. The model offered direct measurement of the moisture content in soil samples: the coefficient of determination (R²) value and the root-mean-square error of prediction (RMSEP) of predicted moisture content were 0.98% and 1.3%, respectively. The correlation between laser ablation factor and moisture content of the samples was determined by analysing the influence of sample moisture content on laser ablation. Quantitative analysis of wet soil samples based on ablation factor was established with an R² of 0.97. Potentially toxic elemental Cu and Cr in sample 4# were verified by the quantitative analysis model through weighing and direct measurement. The relative error of concentration was within 10%, and the accuracy was improved by over 80%. The preliminary results show that the quantitative analysis model of potentially toxic metals in wet soil samples based on LIBS technology can detect potentially toxic metals in wet soil samples quickly and accurately on-site. This has important guiding significance for real-time and on-site monitoring of contaminated soils.

中文翻译：

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LIBS对湿土样中潜在有毒金属定量分析模型的建立与评价

快速现场检测土壤中潜在的有毒金属对于土壤修复和污染监测至关重要。土壤中的水分是潜在有毒金属定量分析的挑战。在这里，我们使用激光诱导击穿光谱 (LIBS) 和偏最小二乘回归 (PLSR) 对潮湿土壤样品中的潜在有毒金属进行快速现场定量分析。该模型可直接测量土壤样品中的水分含量：决定系数 ( R ²) 值和预测水分含量的均方根误差 (RMSEP) 分别为 0.98% 和 1.3%。通过分析样品水分含量对激光烧蚀的影响，确定了激光烧蚀因子与样品水分含量的相关性。基于消融因子的湿土壤样品定量分析建立与R ²0.97。4#样品中的潜在毒性元素Cu和Cr通过定量分析模型通过称重和直接测量进行验证。浓度相对误差在10%以内，准确度提高80%以上。初步结果表明，基于LIBS技术的湿土样中潜在有毒金属定量分析模型可以在现场快速准确地检测出湿土样中的潜在有毒金属。这对污染土壤的实时、现场监测具有重要的指导意义。