Lao Wenjian, Wong Charles S
Southern California Coastal Water Research Project Authority, Costa Mesa, CA, 92626, USA.
Southern California Coastal Water Research Project Authority, Costa Mesa, CA, 92626, USA.
Chemosphere. 2023 Jun;327:138456. doi: 10.1016/j.chemosphere.2023.138456. Epub 2023 Mar 24.
Establishing analytical detection limits is crucial. Common methods to do so are suitable only for variables with continuous distributions. Because count data for microplastic particles is a discrete variable following the Poisson distribution, currently-used approaches for estimating the detection limit in microplastics analysis are inadequate. Here we evaluate detection limits with techniques for low-level discrete observations to develop proper approaches for estimating the minimum detectable amount (MDA) in microplastic particle analysis, using blank sample data from an interlaboratory calibration exercise for clean water (representing drinking water), dirty water (ambient water), sediment (porous media) and fish tissue (biotic tissues). Two MDAs are applicable: MDA to evaluate analytical methods, estimated with replicate blank data; and MDA for individual sample batches, calculated with a single blank count. For illustrative purposes, this dataset's overall MDA values were 164 counts (clean water), 88 (dirty water), 192 (sediment), and 379 (tissue). MDA values should be reported on a laboratory-specific basis and for individual size fractions, as this provides more useful information about capabilities of individual laboratories. This is due to wide variation in blank levels, as noted by MDA values (i.e., among different laboratories) from 14 to 158 (clean water), 9 to 86 (dirty water, 9 to 186 (sediment), and 9 to 247 (tissue). MDA values for fibers were considerably greater than for non-fibers, suggesting that separate MDA values should be reported. This study provides a guideline for estimation and application of microplastics MDA for more robust data to support research activities and environmental management decisions.
确定分析检测限至关重要。常用的方法仅适用于具有连续分布的变量。由于微塑料颗粒的计数数据是遵循泊松分布的离散变量，目前用于估计微塑料分析中检测限的方法并不充分。在此，我们使用来自一项针对清洁水（代表饮用水）、脏水（环境水）、沉积物（多孔介质）和鱼组织（生物组织）的实验室间校准实验的空白样本数据，用低水平离散观测技术评估检测限，以开发用于估计微塑料颗粒分析中最低可检测量（MDA）的合适方法。有两种MDA适用：用于评估分析方法的MDA，用重复空白数据估计；以及针对单个样本批次的MDA，用单个空白计数计算。为说明起见，该数据集的总体MDA值分别为清洁水164个计数、脏水88个、沉积物192个和组织379个。MDA值应在特定实验室基础上并针对各个尺寸分数进行报告，因为这能提供有关各个实验室能力的更有用信息。这是由于空白水平存在很大差异，如MDA值所示（即不同实验室之间），清洁水的MDA值为14至158、脏水为9至86、沉积物为9至186、组织为9至247。纤维的MDA值远高于非纤维，这表明应报告单独的MDA值。本研究为微塑料MDA的估计和应用提供了指导方针，以获得更可靠的数据来支持研究活动和环境管理决策。
