The analysis of environmental occurrence of microplastic (MP) particles has gained notable attention within the past decade. An effective risk assessment of MP litter requires elucidating sources of MP particles, their pathways of distribution and, ultimately, sinks. Therefore, sampling has to be done in high frequency, both spatially and temporally, resulting in a high number of samples to analyze. Microspectroscopy techniques, such as FTIR imaging or Raman particle measurements allow an accurate analysis of MP particles regarding their chemical classification and size. However, these methods are time-consuming, which gives motivation to establish subsampling protocols that require measuring less particles, while still obtaining reliable results. The challenge regarding the subsampling of environmental MP samples lies in the heterogeneity of MP types and the relatively low numbers of target particles. Herein, we present a comprehensive assessment of different proposed subsampling methods on a selection of real-world samples from different environmental compartments. The methods are analyzed and compared with respect to resulting MP count errors, which eventually allows giving recommendations for staying within acceptable error margins. Our results are based on measurements with Raman microspectroscopy, but are applicable to any other analysis technique. We show that the subsampling-errors are mainly due to statistical counting errors (i.e., extrapolation from low numbers) and only in edge cases additionally impacted by inhomogeneous distribution of particles on the filters. Keeping the subsampling-errors low can mainly be realized by increasing the fraction of MP particles in the samples.

中文翻译：

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环境微塑料样品显微光谱中子采样策略的评估

在过去的十年中，对微塑料 (MP) 颗粒环境发生的分析引起了显着的关注。MP 垃圾的有效风险评估需要阐明 MP 颗粒的来源、它们的分布途径以及最终的汇。因此，必须在空间和时间上以高频率进行采样，从而导致需要分析大量样本。显微光谱技术，例如 FTIR 成像或拉曼粒子测量，可以准确分析 MP 粒子的化学分类和大小。然而，这些方法非常耗时，这促使人们建立子采样协议，要求测量更少的粒子，同时仍能获得可靠的结果。环境 MP 样本子采样的挑战在于 MP 类型的异质性和相对较少的目标粒子数量。在此，我们对来自不同环境隔间的一系列真实世界样本的不同提议的子采样方法进行了全面评估。分析和比较这些方法产生的 MP 计数误差，最终允许给出保持在可接受误差范围内的建议。我们的结果基于拉曼显微光谱测量，但适用于任何其他分析技术。我们表明，二次采样误差主要是由于统计计数​​误差（即，从低数字外推），并且仅在边缘情况下还受到过滤器上粒子不均匀分布的影响。