Titanium dioxide nanoparticles (TiO 2 NPs) are extensively used in water treatment processes owing to their photocatalytic properties. However, their environmental stability and resistance to degradation result in significant release and...
Heavy metal ions (HMIs) such as Pb2+, Hg2+, and Cd2+ pose a severe threat to environmental sustainability and human health due to their high toxicity, persistence, and bioaccumulation. Mining activities are major sources of HMI contamination, releasing these ions into surrounding soil and wastewater during mineral extraction and processing. These toxic ions can migrate into nearby water bodies and agricultural land, ultimately entering the food chain and posing long-term health risks specifically to mine workers. Therefore, continuous monitoring of HMIs in mining wastewater is critically important. However, existing detection systems still lack the sensitivity and selectivity required for simultaneous monitoring of multiple HMI in complex mining wastewater matrices. To address this, herein we developed a sulfur-and nitrogen-doped MnFeCo trimetallic MOF (S/N-MFC-TM-MOF). The porous framework enhances electron transfer while thiourea-derived S/N groups provide abundant binding sites for selective adsorption. Performance was further optimized through machine learning (ML), enabling identification of the best-fit parameters. The resulting ML-optimized sensor achieved a wide linear range (0.1-160 mu g L-1), ultralow LODs (Cd2+: 0.073, Hg2+: 0.069, Pb2+: 0.065 mu g L-1), and excellent recovery rates in mining wastewater. This ML-guided TM-MFC-MOF sensor effectively overcomes the mentioned challenges, providing a robust platform for the real-time monitoring of toxic heavy metal ions in mining wastewater.
Organic micropollutants (OMPs), such as pharmaceuticals and endocrine disruptors, have been recognized as threats to both ecosystems and human health. Several advanced polymeric adsorbents have been developed over the last decade to address the issue of OMP pollution. However, their efficacy in complex mixtures is rarely assessed to evaluate their applicability. This study presents the technical feasibility of an emerging covalent triazine framework (CTF) adsorbent with a high surface area (1226 m2 g-1) and nitrogen-rich triazine cores for OMP removal from water. The CTF adsorbent demonstrated ultrafast adsorption kinetics, with 85% removal of bisphenol A within 10 s, and was superior to activated carbon (AC) based on mass transfer and effective diffusion coefficients. It also exhibited remarkable durability by maintaining performance for 10 cycles without pore collapse and versatility by achieving above 99% removal of individual OMPs. However, in mixed OMP systems, the CTF exhibited a significant decline in adsorption kinetics, with the pseudo-second-order rate constant (k2) decreasing by up to 62.4-fold as compared to individual OMPs. Importantly, the presence of co-existing impurities in real water matrices inhibited both the instant and overall removal of mixed OMPs due to competitive adsorption and steric hindrance. This study is a concrete example of the significance of examining advanced polymeric adsorbents under environmentally relevant conditions.
This review systematically summarizes preparation strategies for lignin-derived carbon-based metal catalysts from nanoparticles to single atoms and further explores their catalytic enhancement mechanisms in water treatment applications.
Nanoplastic contamination of agricultural systems is an emerging threat to crop physiology and food safety, yet species-specific uptake patterns and physiological consequences remain under-researched.
