Related Experiment Video
Updated: Mar 22, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Integrating potential bioavailable heavy metals and two-dimensional Monte Carlo simulation for a refined
Guanghui Guo1,2, Ruiqing Zhang3
1Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China. guogh@igsnrr.ac.cn.
Abstract:
Source-specific probabilistic ecological risk assessment (PERA) of heavy metals (HMs) enhances risk management strategies. However, conventional methods, relied on total concentrations and deterministic parameters, may introduce considerable bias due to ignoring bioavailability and uncertainty. To address these limitations, this study conducted both concentration- and source-specific PERAs for HMs in Poyang Lake sediments using their bioavailable fractions and two-dimensional Monte Carlo simulation. Results reveled significant Cd pollution in sediments. Chemical speciation analyses indicated Cd (58.45% acid-soluble fraction) and As (36.96% specifically adsorbed fraction) exhibited high bioavailability, whereas Cr, Cu, Ni, Pb, and Zn were predominantly associated with residual fraction (48.55%-89.07%). Source apportionment identified three primary sources: mining/smelting, mixed sources, and industrial activities, with contribution of 26.87%, 34.55%, and 38.58%, respectively. Notably, mining/smelting was identified as the primary sources (77.68%), and As, Cd, and Pb emerged as targeted elements of concern. Incorporating bioavailable HMs into PERA reduced overall ecological risks by 38.09% compared to total concentration-based PERA. Corresponding source-specific ecological risk reductions were 39.21%, 42.11%, and 47.47% for mining/smelting, mixed sources, and industrial activities, respectively. This study highlights the importance of incorporating HM bioavailability and probabilistic analysis into ecological risk assessment framework for achieving accurate and realistic evaluation.

