Key Laboratory of the Coastal and Wetland Ecosystems of Ministry of Education, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China.
Key Laboratory of the Coastal and Wetland Ecosystems of Ministry of Education, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China; Center for Marine Environmental Chemistry and Toxicology, Xiamen University, Xiamen, Fujian 361102, China.
Water Res. 2021 Jan 1;188:116548. doi: 10.1016/j.watres.2020.116548. Epub 2020 Oct 21.
In aquatic environments, the ecological risks posed by metals are greatly affected by water chemistry, thereby creating challenges for water quality management. Biotic ligand models (BLMs) have become the most widely used tools to interpret and predict water chemistry effects. Traditional BLM development methods require a large number of toxicity tests and organisms, and model predictions are limited to certain toxicity statistics (e.g., 48-h median effective concentration, 48-h EC), to which the models were calibrated. To address these limitations, we propose a new method to develop BLMs by integrating them into the toxicokinetic-toxicodynamic (TK-TD) framework. Metal bioaccumulation was predicted from metal exposure and water chemistry using the BLM-type toxicokinetics, whilst metal toxicity was predicted from metal bioaccumulation using the toxicodynamics. Using the new method, we developed a kinetic BLM of cadmium for Daphnia magna with only six toxicity tests and 1540 daphnids; this represents a 60-80% reduction compared to the traditional methods. The model was validated in the presence of commercial dissolved organic matter (DOM) and in natural waters sampled from 12 lakes. The kinetic BLM was able to accurately simulate the protective effects of the commercial DOM by employing the Stockholm humic model, whilst the complexation capabilities of some natural DOM were overestimated. We further used the model to predict Cd EC and no-effect concentrations for different waters, generating predictions close to the effect concentrations reported in the literature. Overall, our method requires fewer resources and presents an easier approach to develop BLMs; the kinetic BLM is more flexible and can serve as a useful tool for developing water quality criteria.
在水生环境中，金属对生态系统造成的风险受到水化学的极大影响，这给水质管理带来了挑战。生物配体模型（BLM）已成为解释和预测水化学效应的最广泛使用的工具。传统的 BLM 开发方法需要大量的毒性测试和生物体，并且模型预测仅限于某些毒性统计数据（例如，48 小时半数有效浓度，48 小时 EC），模型就是根据这些数据进行校准的。为了解决这些限制，我们提出了一种新的方法，即将其整合到毒代动力学-毒效动力学（TK-TD）框架中来开发 BLM。BLM 型毒代动力学用于预测金属暴露和水化学条件下的金属生物累积，而毒效动力学则用于预测金属生物累积下的金属毒性。使用新方法，我们仅用 6 次毒性测试和 1540 只水蚤，为大型溞（Daphnia magna）开发了一个镉的动力学 BLM；与传统方法相比，这一数字减少了 60-80%。该模型在商业溶解有机物（DOM）存在下和从 12 个湖泊中采集的天然水中进行了验证。动力学 BLM 通过采用斯德哥尔摩腐殖模型，能够准确模拟商业 DOM 的保护作用，而某些天然 DOM 的络合能力则被高估。我们进一步使用该模型预测不同水体中的 Cd EC 和无效应浓度，生成的预测值与文献中报道的效应浓度接近。总体而言，我们的方法需要更少的资源，并且提供了一种更简单的开发 BLM 的方法；动力学 BLM 更加灵活，可以作为开发水质标准的有用工具。
