Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Red Sea Research Center and Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Environ Pollut. 2020 Dec;267:115640. doi: 10.1016/j.envpol.2020.115640. Epub 2020 Sep 16.
Microfibers are reported as the most abundant microparticle type in the environment. Their small size and light weight allow easy and fast distribution, but also make it challenging to determine their chemical composition. Vibrational microspectroscopy methods as infrared and spontaneous Raman microscopy have been widely used for the identification of environmental microparticles. However, only few studies report on the identification of microfibers, mainly due to difficulties caused by their small diameter. Here we present the use of Stimulated Raman Scattering (SRS) microscopy for fast and reliable classification of microfibers from environmental samples. SRS microscopy features high sensitivity and has the potential to be faster than other vibrational microspectroscopy methods. As a proof of principle, we analyzed fibers extracted from the fish gastrointestinal (GIT) tract, deep-sea and coastal sediments, surface seawater and drinking water. Challenges were faced while measuring fibers from the fish GIT, due to the acidic degradation they undergo. However, the main vibrational peaks were still recognizable and sufficient to determine the natural or synthetic origin of the fibers. Notably, our results are in accordance to other recent studies showing that the majority of the analyzed environmental fibers has a natural origin. Our findings suggest that advanced spectroscopic methods must be used for estimation of the plastic fibers concentration in the environment.
微纤维被报道为环境中最丰富的微粒类型。它们的体积小、重量轻，易于快速分布，但也难以确定其化学组成。振动微光谱方法，如红外和自发拉曼显微镜，已被广泛用于环境微粒的识别。然而，只有少数研究报告了微纤维的识别，主要是由于其直径小而导致的困难。在这里，我们提出了使用受激拉曼散射（SRS）显微镜快速可靠地分类环境样品中的微纤维。SRS 显微镜具有高灵敏度，并且有可能比其他振动微光谱方法更快。作为原理验证，我们分析了从鱼类胃肠道（GIT）、深海和沿海沉积物、地表水和饮用水中提取的纤维。在测量鱼类 GIT 中的纤维时，由于它们经历的酸性降解，面临着挑战。然而，主要的振动峰仍然可以识别，足以确定纤维的天然或合成来源。值得注意的是，我们的结果与其他最近的研究一致，表明分析的环境纤维大多数具有天然来源。我们的研究结果表明，必须使用先进的光谱方法来估计环境中塑料纤维的浓度。
