Institute of Chemistry, College of Science, University of the Philippines Diliman, Quezon City, Philippines.
Materials Science and Engineering Program, College of Science, University of the Philippines Diliman, Quezon City, Philippines.
Environ Sci Pollut Res Int. 2018 Jun;25(17):16620-16628. doi: 10.1007/s11356-018-1803-y. Epub 2018 Mar 29.
Monitoring of pollution index values in sediments is crucial in assessing the environmental impacts of toxic metals in a given location. These indices are typically acquired using elaborate and tedious calibration curve-dependent techniques such as (inductively coupled plasma - optical emission spectroscopy) ICP-OES and (atomic absorption spectroscopy) AAS. In this study, laser-induced breakdown spectroscopy (LIBS) was used as a simple and fast alternative method for estimating enrichment factor (EF) and contamination factor (CF) of the sediment samples obtained from selected mining sites. Quantitative analyses of three metal targets (Cd, Pb, and Zn) were done using a calibration-free LIBS method based on the Boltzmann population distribution. Both the EF and CF values calculated from classical ICP-OES method provided significantly high correspondence with the respective EF (R = 0.8862-0.9770, p < 0.01-0.05) and CF (R = 0.9454-0.9714, p < 0.01) obtained from the developed LIBS method. The intensity-based LIBS approach identified samples AC2 and CCC as the ones with the highest and lowest pollution index values, respectively. The same observation was seen using the concentration-based ICP-OES technique which showed good correlation between the two methods. The correlation results showed the potential of the curve-fitting LIBS analysis in evaluating the level of metal contamination in an area without the preparation of matrix-matched calibration curves.
监测沉积物中的污染指数值对于评估特定地点有毒金属对环境的影响至关重要。这些指数通常是通过复杂且繁琐的校准曲线依赖技术获得的,例如(电感耦合等离子体-光学发射光谱法)ICP-OES 和(原子吸收光谱法)AAS。在这项研究中,激光诱导击穿光谱(LIBS)被用作一种简单快速的替代方法,用于估算从选定采矿地点获得的沉积物样品的富集因子(EF)和污染因子(CF)。使用基于玻尔兹曼分布的无校准 LIBS 方法对三种金属靶标(Cd、Pb 和 Zn)进行定量分析。从经典 ICP-OES 方法计算出的 EF 和 CF 值与从开发的 LIBS 方法得出的相应 EF(R = 0.8862-0.9770,p < 0.01-0.05)和 CF(R = 0.9454-0.9714,p < 0.01)具有显著的高相关性。基于强度的 LIBS 方法确定样品 AC2 和 CCC 分别具有最高和最低的污染指数值。使用基于浓度的 ICP-OES 技术也观察到了相同的观察结果,两种方法之间存在良好的相关性。相关结果表明,在无需制备基质匹配校准曲线的情况下,曲线拟合 LIBS 分析在评估区域金属污染水平方面具有潜力。