Aquatic Ecology and Water Quality Management Group, Wageningen University, P.O. Box 47, 6700 DDWageningen, The Netherlands.
Department Methodology and Statistics, Tilburg University, PO Box 90153, 5000 LETilburg, The Netherlands.
Environ Sci Technol. 2022 Nov 15;56(22):15552-15562. doi: 10.1021/acs.est.2c03559. Epub 2022 Oct 28.
Current methods of characterizing plastic debris use arbitrary, predetermined categorizations and assume that the properties of particles are independent. Here we introduce Gaussian mixture models (GMM), a technique suitable for describing non-normal multivariate distributions, as a method to identify mutually exclusive subsets of floating macroplastic and microplastic particles (latent class analysis) based on statistically defensible categories. Length, width, height and polymer type of 6,942 particles and items from the Atlantic Ocean were measured using infrared spectroscopy and image analysis. GMM revealed six underlying normal distributions based on length and width; two within each of the lines, films, and fragments categories. These classes differed significantly in polymer types. The results further showed that smaller films and fragments had a higher correlation between length and width, indicating that they were about the same size in two dimensions. In contrast, larger films and fragments showed low correlations of height with length and width. This demonstrates that larger particles show greater variability in shape and thus plastic fragmentation is associated with particle rounding. These results offer important opportunities for refinement of risk assessment and for modeling the fragmentation and distribution of plastic in the ocean. They further illustrate that GMM is a useful method to map ocean plastics, with advantages over approaches that use arbitrary categorizations and assume size independence or normal distributions.
目前用于描述塑料碎片的方法使用任意的、预先确定的分类，并假设颗粒的特性是独立的。在这里，我们引入了高斯混合模型（GMM），这是一种适合描述非正态多元分布的技术，可作为一种根据具有统计学意义的分类来识别互斥的浮式宏观塑料和微塑料颗粒子集（潜在类别分析）的方法。利用红外光谱和图像分析对来自大西洋的 6942 个颗粒和物品的长度、宽度、高度和聚合物类型进行了测量。GMM 根据长度和宽度揭示了六个潜在的正态分布；在线条、薄膜和碎片类别中，每个类别内都有两个。这些类别在聚合物类型上有显著差异。结果还表明，较小的薄膜和碎片的长度和宽度之间的相关性更高，这表明它们在两个维度上的尺寸大致相同。相比之下，较大的薄膜和碎片的高度与长度和宽度的相关性较低。这表明较大的颗粒在形状上表现出更大的可变性，因此塑料碎片与颗粒变圆有关。这些结果为风险评估的精细化以及海洋中塑料碎片的分布和分布建模提供了重要机会。它们进一步表明，GMM 是一种有用的海洋塑料绘图方法，优于使用任意分类和假设尺寸独立性或正态分布的方法。
