Environmental Health Laboratory, California Department of Public Health, Richmond, CA, USA.
Ocean P3 Systems, San Francisco, CA, USA.
Chemosphere. 2022 Oct;304:135295. doi: 10.1016/j.chemosphere.2022.135295. Epub 2022 Jun 10.
The need for improved microplastic (MP) data accuracy has been widely reported, but MP precision issues have been investigated less thoroughly. This work demonstrates how initial and continuing assessments of a laboratory's analytical precision can be used for establishing laboratory repeatability for MP analyses. These precision estimates can be reported along with MP results to ensure their quality and compare them meaningfully to other data. Re-analyses of reference MP samples can be used to assess and compare precision between different laboratories. A multi-lab precision exercise was demonstrated using infrared (IR) standard test methods performed on reference samples consisting of low-concentration MP spikes in both clean water and wastewater matrices. Each lab repeated their IR analyses 7 times and calculated relative standard deviations (RSD) for each detected polymer type using a standardized template. All labs' MP methods yielded generally repeatable results, though RSDs were consistently higher for lower MP counts. The reported range of total MP counts per sample was 8-33 particles, and the observed RSDs were 0.1-0.6. These RSDs were the same or lower than the expected imprecision due to random (Poisson) counting error alone, suggesting that these automated methods did not contribute any additional variability, and had slightly better reproducibility than expected for independent recounts. The wastewater matrix exhibited numerous interfering particles but did not yield more variability than the clean water matrix. The low-count design is a worst case for precision but is appropriate for some real-world sample concentrations. In practice, labs could generate separate references for precision assessment at multiple MP ranges (e.g., high, medium, and low.) The RSDs obtained from this data can be used to generate QC charts, detect changes in analyst performance, compare to Poisson error to identify additional sources of imprecision, and determine target filtration and instrumental parameters for MP analyses.
需要提高微塑料 (MP) 数据的准确性已经得到了广泛的报道,但 MP 精度问题的研究还不够彻底。这项工作展示了如何对实验室的分析精度进行初步和持续评估,以确定实验室对 MP 分析的重复性。这些精度估计可以与 MP 结果一起报告,以确保其质量,并与其他数据进行有意义的比较。对参考 MP 样品的重新分析可用于评估和比较不同实验室之间的精度。使用红外 (IR) 标准测试方法对由清洁水和废水基质中低浓度 MP 浓度的参考样品进行了多实验室精度测试。每个实验室重复进行了 7 次 IR 分析,并使用标准化模板为每种检测到的聚合物类型计算相对标准偏差 (RSD)。所有实验室的 MP 方法均得出了通常可重复的结果,尽管对于较低的 MP 计数,RSD 始终较高。报告的每个样品的总 MP 计数范围为 8-33 个颗粒,观察到的 RSD 为 0.1-0.6。这些 RSD 与仅由于随机(泊松)计数误差引起的预期不精密度相同或更低,这表明这些自动化方法没有增加任何额外的可变性,并且对于独立重算具有比预期更好的再现性。废水基质中存在许多干扰颗粒,但比清洁水基质产生的变异性更小。低计数设计是对精度的最坏情况,但适用于某些实际样品浓度。在实践中,实验室可以为多个 MP 范围(例如,高、中、低)生成单独的精度评估参考。从这些数据中获得的 RSD 可用于生成 QC 图表,检测分析员性能的变化,与泊松误差进行比较以识别其他不精确的来源,并确定 MP 分析的目标过滤和仪器参数。