Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, 6500 GL Nijmegen, the Netherlands.
Flanders Environment Agency (VMM), Dr. De Moorstraat 24-26, B-9300 Aalst, Belgium.
Environ Sci Technol. 2020 Nov 17;54(22):14288-14301. doi: 10.1021/acs.est.0c02855. Epub 2020 Nov 2.
The densely populated North Sea region encompasses catchments of rivers such as Scheldt and Meuse. Herein, agricultural, industrial, and household chemicals are emitted, transported by water, and deposited in sediments, posing ecological risks. Though sediment monitoring is often costly and time-intensive, modeling its toxicity to biota has received little attention. Due to high complexity of interacting variables that induce overall toxicity, monitoring data only sporadically validates current models. Via a range of concepts, we related bio-physicochemical constituents of sediment in Flanders to results from toxicity bioassays performed on the ostracod . Depending on the water body, we explain up to 90% of the variance in growth. Though variable across Flanders' main water bodies, organotin cations and ammonia dominate the observed toxicity according to toxic unit (TU) assessments. Approximately 10% relates to testing conditions/setups, species variabilities, incoherently documented pollutant concentrations, and/or bio-physicochemical sediment properties. We elucidated the influence of organotin cations and ammonia relative to other metal(oxides) and biocides. Surprisingly, the tributylin cation appeared ∼1000 times more toxic to as compared to "single-substance" bioassays for similar species. We inferred indirect mixture effects between organotin, ammonia, and phosphate. Via chemical speciation calculations, we observed strong physicochemical and biological interactions between phosphate and organotin cations. These interactions enhance bioconcentration and explain the elevated toxicity of organotin cations. Our study aids water managers and policy makers to interpret monitoring data on a mechanistic basis. As sampled sediments differ, future modeling requires more emphasis on characterizing and parametrizing the interactions between bioassay constituents. We envision that this will aid in bridging the gap between testing in the laboratory and field observations.
人口密集的北海地区包括了谢尔德特河和默兹河等流域。在这里,农业、工业和家庭化学物质被排放到水中,并在沉积物中沉积,从而带来生态风险。尽管沉积物监测通常成本高昂且费时费力,但对生物群的毒性建模却很少受到关注。由于引起整体毒性的相互作用变量的复杂性很高,因此监测数据只是偶尔验证当前模型。通过一系列概念,我们将佛兰德沉积物的生物物理化学成分与对介形虫进行的毒性生物测定结果联系起来。根据水体的不同,我们可以解释高达 90%的生长差异。尽管在佛兰德的主要水体中存在差异,但根据毒性单位 (TU) 评估,有机锡阳离子和氨是导致观察到的毒性的主要因素。大约 10%与测试条件/设置、物种变异性、记录不一致的污染物浓度以及/或生物物理化学沉积物特性有关。我们阐明了有机锡阳离子和氨与其他金属(氧化物)和杀生物剂的相对影响。令人惊讶的是,与类似物种的“单一物质”生物测定相比,三丁基锡阳离子对的毒性高约 1000 倍。我们推断出有机锡、氨和磷酸盐之间存在间接混合物效应。通过化学形态计算,我们观察到磷酸盐和有机锡阳离子之间存在强烈的物理化学和生物相互作用。这些相互作用增强了生物浓缩作用,并解释了有机锡阳离子升高毒性的原因。我们的研究有助于水管理者和政策制定者根据机制基础来解释监测数据。由于采样沉积物不同,未来的建模需要更加注重对生物测定成分之间相互作用的描述和参数化。我们设想这将有助于缩小实验室测试和现场观察之间的差距。