Uncertainty and Consistency Assessment in Multiple Microplastic Observation Datasets in the Baltic Sea

This paper aims to quantify data uncertainties in marine microplastic measurements, including spatiotemporal sampling error and sample volume estimation error, identify impacts of varying mesh sizes, sampling and analysis methods, and evaluate consistency in multiple microplastic observation datasets. Twenty-seven datasets on surface marine microplastics with particle size >100 µm in the Baltic Sea are compiled. Results show that the trawl datasets have a spatiotemporal sampling error of 25% for microlitter concentration, 36% for microplastic fiber concentrations and 40-56% for microplastic particle concentration. By taking surface currents and wave-induced Stokes drift into account, the sample volume of the trawl measurements is corrected, leading to a mean microplastic concentration correction of 12%. The differences of microplastic concentration between datasets with varying mesh sizes from 100 – 500 µm are not statistically significant. Analysis methods, however, can lead to significant differences in microplastic datasets. The dataset consistency is further examined among the three dataset categories using trawl, pump and bulk sampling techniques. It is found that an individual dataset is often self-consistent. Most of the datasets within one monitoring category are more consistent than those from different categories. More than 70% of the datasets within individual categories are consistent, which have mean microplastic concentration significantly smaller than the rest of the datasets. Significant inconsistencies are identified between different data categories. Six out of eight highest relative standard deviations are found in the pump and bulk datasets. The median value of the mean microplastic concentration from the 10 pump datasets is about 4.5 times as much as that of the 14 trawl datasets, both for fiber and non-fiber particles. Significant differences are also identified on microplastic fiber fraction in different dataset categories. Two thirds of the 13 bulk and pump datasets have a microplastic fiber fraction >85% while the 14 trawl datasets show much lower microplastic fiber fractions between 45-70%. In addition, the particle collection efficiency, potential leakage of particles with irregular shapes, clogging, the false zero samples and related lower limit of the detectable microplastic concentration for given sampling methods and water environment, are also discussed.