Iron oxide nanoparticles (IONPs) are among the most versatile and applied nanoparticles due to their unique properties. However, the distribution of these nanoparticles (NPs) in the environmental system presents a critical problem for understanding the generation of reactive oxygen species (ROS) and their unpredictable effect on micro and macro fauna/flora due to their chemical form. This study describes strategies to evaluate the dispersion of IONPs in environmental media under controlled conditions of pH (5–9), hardness (0–400 mg CaCO₃ per L), temperature (10–30 °C), and exposure time (0–48 h) in aquatic systems. For this purpose, iron-based nanoparticles (hematite, goethite, and magnetite) were synthesised and characterised using chemical and morphological analytical techniques. Subsequently, the effect of environmental parameters on the dispersion of NPs was investigated by developing a model using a central composite rotatable design (CCRD) with total Fe as the dependent variable. The three IONPs were synthesised with a size of less than 100 nm. It was observed that the nano-hematites and magnetites had spherical morphology, while goethite appeared as nanorods. The resulting models, integrating linear, quadratic, and combined effects, exhibited high predictive capacities of 76.4%, 93.6%, and an impressive 99.9% for nano-hematite, goethite, and magnetite, respectively. This research contributes to better understanding of nanoparticle behaviours in natural settings, providing essential insights to assess and potentially mitigate the adverse consequences of IONPs contamination in aquatic environments.

中文翻译：

---

了解和预测氧化铁纳米颗粒的环境分散性：合成、表征和建模的综合研究


由于其独特的特性，氧化铁纳米颗粒 （IOMP） 是用途最广、应用最广泛的纳米颗粒之一。然而，这些纳米颗粒 （NPs） 在环境系统中的分布对于理解活性氧 （ROS） 的产生及其由于其化学形式对微型和大型动植物群的不可预测的影响提出了一个关键问题。本研究描述了在 pH 值 （5-9）、硬度（0-400 mg CaCO₃/L）、温度 （10-30 °C） 和暴露时间 （0-48 h） 的受控条件下，评估 IONP 在环境介质中分散的策略水生系统。为此，使用化学和形态分析技术合成了铁基纳米颗粒（赤铁矿、针铁矿和磁铁矿）并进行了表征。随后，通过使用以总 Fe 为因变量的中心复合可旋转设计 （CCRD） 开发模型，研究了环境参数对 NPs 分散的影响。合成的 3 个 IONP 大小小于 100 nm。据观察，纳米赤铁矿和磁铁矿具有球形形态，而针铁矿则表现为纳米棒。所得模型集成了线性、二次和组合效应，对纳米赤铁矿、针铁矿和磁铁矿分别表现出 76.4%、93.6% 和 99.9% 的高预测能力。这项研究有助于更好地了解纳米颗粒在自然环境中的行为，为评估和可能减轻水生环境中 IONPs 污染的不良后果提供重要见解。