A monitoring and data analysis method for microplastics in marine sediments.
A monitoring and data analysis method for microplastics in marine sediments.
复制标题
海洋沉积物中微塑料的监测和数据分析方法。
DOI：
10.1016/j.marenvres.2022.105804
复制
发表时间：
2022
影响因子：
3.3
通讯作者：
A. Koelmans
中科院分区：
文献类型：
--
作者：
P. Bäuerlein;M. W. Erich;W. V. van Loon;S. Mintenig;A. Koelmans
在欧洲，政策框架要求监测海洋沉积物中的微塑料。在这里，我们提供了一种微塑料颗粒的监测和数据分析方法，旨在用于海洋战略框架指令 (MSFD) 和 OSPAR 政策框架。通过重复采样，对荷兰沿海和过渡水域四个不同地点的海洋沉积物中的微塑料进行了分析，以调查微空间变化。粒度分布遵循斜率 3.76 的幂律。鉴定出 13 种聚合物，其成分在人口稠密的西海岸地区和更农村的瓦登海地区附近的沉积物之间有所不同。我们使用平均值的相对标准误差 (RSEM) 量化不同地点之间微塑料浓度的微空间变化的差异。该指标提供了通过选择微空间变化相对较低的位置来优化微塑料监测网络中趋势检测灵敏度的机会。我们提供了一种方法，利用给定位置与 RSEM 的关系来优化给定位置的重复样本数量。对于相对同质的位置来说，两个重复样本似乎具有成本效益，而异质性较高的位置则需要四个重复样本。
In Europe, policy frameworks demand the monitoring of microplastics in marine sediments. Here we provide a monitoring and data analysis method for microplastic particles designed to be used in the context of Marine Strategy Framework Directive (MSFD) and OSPAR policy frameworks. Microplastics were analysed in marine sediments at four different locations in Dutch coastal and transitional waters using replicate sampling to investigate micro-spatial variation. Particle size distribution followed a power law with slope 3.76. Thirteen polymers were identified, with their composition varying between sediments near densely populated West coast areas versus the more rural Wadden Sea area. We quantify differences in the micro-spatial variation of microplastic concentrations between locations using the relative standard error of the mean (RSEM). This metric provides an opportunity to optimize the sensitivity of trend detection in microplastic monitoring networks by selecting locations with relatively low micro-spatial variation. We provide a method to optimize the number of replicate samples for a given location using its relationship with the RSEM. Two replicate samples appear to be cost-effective for relatively homogenous locations, whereas more heterogenous locations require four replicates.