Koelmans Albert A, Redondo-Hasselerharm Paula E, Mohamed Nor Nur Hazimah, Gouin Todd
Aquatic Ecology and Water Quality Management Group, Wageningen University, 6700, DD, Wageningen, the Netherlands.
IMDEA Water Institute, Science and Technology Campus of the University of Alcalá, Avenida Punto Com, 2, 28805, Alcalá de Henares, Madrid, Spain.
Environ Pollut. 2023 May 15;325:121445. doi: 10.1016/j.envpol.2023.121445. Epub 2023 Mar 14.
The Laurentian Great Lakes represent important and iconic ecosystems. Microplastic pollution has become a major problem among other anthropogenic stressors in these lakes. There is a need for policy development, however, assessing the risks of microplastics is complicated due to the uncertainty and poor quality of the data and incompatibility of exposure and effect data for microplastics with different properties. Here we provide a prospective probabilistic risk assessment for Great Lakes sediments and surface waters that corrects for the misalignment between exposure and effect data, accounts for variability due to sample volume when using trawl samples, for the random spatiotemporal variability of exposure data, for uncertainty in data quality (QA/QC), in the slope of the power law used to rescale the data, and in the HC5 threshold effect concentration obtained from Species Sensitivity Distributions (SSDs). We rank the lakes in order of the increasing likelihood of risks from microplastics, for pelagic and benthic exposures. A lake-wide risk, i.e. where each location exceeds the risk limit, is not found for any of the lakes. However, the probability of a risk from food dilution occurring in parts of the lakes is 13-15% of the benthic exposures in Lakes Erie and Huron, and 8.3-10.3% of the pelagic exposures in Lake Michigan, Lake Huron, Lake Superior, and Lake Erie, and 24% of the pelagic exposures in Lake Ontario. To reduce the identified uncertainties, we recommend that future research focuses on characterizing and quantifying environmentally relevant microplastic (ERMP) over a wider size range (ideally 1-5000 μm) so that probability density functions (PDFs) can be better calibrated for different habitats. Toxicity effect testing should use a similarly wide range of sizes and other ERMP characteristics so that complex data alignments can be minimized and assumptions regarding ecologically relevant dose metrics (ERMs) can be validated.
五大湖是重要且具有标志性的生态系统。在这些湖泊中，微塑料污染已成为除其他人为压力源之外的一个主要问题。尽管有制定政策的需求，但由于数据的不确定性和质量较差，以及不同特性微塑料的暴露数据与效应数据不匹配，评估微塑料的风险变得很复杂。在此，我们针对五大湖沉积物和地表水进行了前瞻性概率风险评估，该评估纠正了暴露数据与效应数据之间的不一致，考虑了使用拖网样本时因样本量导致的变异性、暴露数据的随机时空变异性、数据质量（质量保证/质量控制）的不确定性、用于重新缩放数据的幂律斜率的不确定性，以及从物种敏感性分布（SSD）获得的HC5阈值效应浓度的不确定性。我们按微塑料造成风险可能性增加的顺序对各湖泊进行了排名，涵盖了浮游和底栖暴露情况。未发现任何一个湖泊存在全湖范围的风险，即每个地点都超过风险限值的情况。然而，在伊利湖和休伦湖部分区域，因食物稀释产生风险的概率为底栖暴露的13 - 15%；在密歇根湖、休伦湖、苏必利尔湖和伊利湖，浮游暴露产生风险的概率为8.3 - 10.3%；在安大略湖，浮游暴露产生风险的概率为24%。为减少已识别的不确定性，我们建议未来的研究集中在更广泛尺寸范围（理想情况下为1 - 5000微米）内对环境相关微塑料（ERMP）进行表征和量化，以便能更好地校准不同栖息地的概率密度函数（PDF）。毒性效应测试应使用类似的广泛尺寸范围及其他ERMP特性，从而尽量减少复杂的数据比对，并验证关于生态相关剂量指标（ERM）的假设。
