Instituto Hidrográfico, R. Trinas 49, 1249-093, Lisboa, Portugal; Centro de Química Estrutural, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016, Lisboa, Portugal.
Instituto Hidrográfico, R. Trinas 49, 1249-093, Lisboa, Portugal.
Talanta. 2021 Mar 1;224:121814. doi: 10.1016/j.talanta.2020.121814. Epub 2020 Oct 27.
The assessment of microplastic contamination in an environmental compartment involves identifying and counting microplastics in a representative fraction of the compartment. Microplastics can be identified by μFTIR spectroscopy where spectra are manually examined for characteristic polymer bands or by an automatic comparison of particle spectrum with reference spectra of polymers. The automatic spectra comparison can involve calculating a correlation coefficient, CC, between particle and reference spectra where a minimum correlation above which identification is adequately reliable should be defined. Correlation can be calculated from original or transformed signals, such as taking the first derivative, and by using unweighted or weighted CC. Weighted CC can highlight the spectral features more relevant to distinguish polymers. This work describes a methodology for setting the minimum CC, P5»P, associated with a true positive result rate, TP, of 95% and for checking if this threshold allows identifications with a false positive result rate, FP, not greater than 5%. This methodology was successfully applied to the use of various CC determined from original or transformed spectra for the identification of polyethylene, PE, and polypropylene, PP, microplastics in river sediments by μFTIR. The analytical portions of sediments were digested with HO and microplastics separated from the remaining particles by density using a saturated NaCl solution. Pearson's, Spearman's and Alternative unweighted and weighted correlation coefficients were studied. The P5»P was estimated by the Bootstrap method that resamples spectra CC between a reference material and microparticle of the same polymer collected from the environment. This resampling allows simulating CC distribution required to estimate its 5th percentile (i.e. P5»P). The FP was estimated from the probability of a particle not from the same polymer type of the reference material producing a CC greater than P5»P. Some unweighted and weighted CC determined from original or transformed spectra were successfully used to identify PE or PP particles in river sediments. More particle spectra need to be collected to ensure performance is assessed from a representative diversity of aged polymers with different additives. The spreadsheets used for CC calculations and Bootstrap simulations are made available and can be used for the validation of the identification of other polymer types by μFTIR or ATR-FTIR spectroscopy.
评估环境介质中的微塑料污染需要鉴定和计数该环境介质中具有代表性的微塑料部分。微塑料可通过 μFTIR 光谱法鉴定，该方法手动检查特征聚合物谱带，或通过将颗粒光谱与聚合物参考光谱自动比较来鉴定。自动光谱比较可涉及计算颗粒与参考光谱之间的相关系数（CC），其中应定义最小相关值，高于该值可确保鉴定足够可靠。相关系数可以通过原始或转换信号（例如求导）计算，也可以使用无权重或加权 CC。加权 CC 可以突出更有助于区分聚合物的光谱特征。本工作描述了一种确定最小相关系数（P5»P）的方法，该方法与 95%的真阳性率（TP）相关联，并检查该阈值是否允许误报率（FP）不超过 5%的鉴定。该方法成功应用于使用各种从原始或转换光谱确定的 CC 来鉴定河流沉积物中的聚乙烯（PE）和聚丙烯（PP）微塑料，这些 CC 由 μFTIR 获得。将沉积物的分析部分用 HO 消解，并用饱和 NaCl 溶液通过密度分离从剩余颗粒中分离微塑料。研究了 Pearson、Spearman 以及替代的无权重和加权相关系数。通过自举法估算 P5»P，该方法对从环境中收集的同一聚合物的参考材料和微颗粒之间的光谱 CC 进行重采样。这种重采样允许模拟 CC 分布，以估计其第 5 个百分位数（即 P5»P）。FP 通过计算不是参考材料中相同聚合物类型的颗粒产生的 CC 大于 P5»P 的概率来估算。一些从原始或转换光谱确定的无权重和加权 CC 成功用于鉴定河流沉积物中的 PE 或 PP 颗粒。需要收集更多的颗粒光谱，以确保从具有不同添加剂的不同老化聚合物的代表性多样性评估性能。用于 CC 计算和自举模拟的电子表格可提供，可用于通过 μFTIR 或 ATR-FTIR 光谱法验证其他聚合物类型的鉴定。
