Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW 2308, Australia; Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of Newcastle, Callaghan, NSW 2308, Australia.
Flinders Institute for NanoScale Science and Technology, College of Science and Engineering, Flinders University, South Australia 5042, Australia.
J Hazard Mater. 2022 Jun 5;431:128636. doi: 10.1016/j.jhazmat.2022.128636. Epub 2022 Mar 7.
As contaminants of emerging concern, microplastics and nanoplastics are ubiquitous in not only aquatic and terrestrial environments but also household settings. While the characterisation of microplastics is still a challenge, the analysis of nanoplastics is even more difficult. In this study, we aim to examine several novel algorithmic methods intended for analysing complex Raman spectrum matrices towards visualisation of plastic particles released from a chopping board. Specifically, we compare and advance three decoding algorithms, including (i) a logic-based algorithm to merge and cross-check multiple Raman images that map the intensities of several characteristic peaks; (ii) a principal component analysis-based algorithm to generate intensity images from whole sets of spectra, not just from individual characteristic peaks; (iii) an algebra-based algorithm to merge and cross-check the loading matrix to enhance characterisation efficiency. Assisted with a scanning electron microscope, we estimate that 100-300 microplastics / nanoplastics per mm per cut along the groove formed on the chopping board, and ~3000 per mm per cut in the scratched area, may be released from a chopping board during food preparation and may be subsequently ingested by human. Overall, the Raman imaging combined with algorithms can provide effective characterisation of microplastics and nanoplastics.
作为新兴关注污染物，微塑料和纳米塑料不仅在水生和陆地环境中普遍存在，而且在家庭环境中也普遍存在。虽然微塑料的特征描述仍然是一个挑战，但纳米塑料的分析更加困难。在这项研究中，我们旨在检查几种用于分析复杂拉曼光谱矩阵的新算法方法，以期可视化从切菜板释放的塑料颗粒。具体来说，我们比较和推进了三种解码算法，包括：（i）基于逻辑的算法，用于合并和交叉检查多个映射多个特征峰强度的拉曼图像；（ii）基于主成分分析的算法，用于从整套光谱而不仅仅是单个特征峰生成强度图像；（iii）基于代数的算法，用于合并和交叉检查加载矩阵以提高特征描述效率。在扫描电子显微镜的辅助下，我们估计在准备食物过程中，每沿切菜板上形成的凹槽切割 100-300 个微塑料/纳米塑料/毫米，在刮擦区域每切割 3000 个微塑料/纳米塑料/毫米，可能会从切菜板释放出来，并可能随后被人类摄入。总体而言，拉曼成像结合算法可以有效地对微塑料和纳米塑料进行特征描述。
