Ecotoxicological assessment of Zn, Cu and Ni based NPs contamination in Arenosols

Nanoparticles are increasingly used in many industrial fields because of their special properties. In this context, several questions arise related to possible negative consequences associated with nanoparticle (NPs) entrance into the ecosystem. The adsorption of NPs by soil can adversely influence its biological properties. In the present article, the influence of Cu, Zn, and Ni NPs on the biological characteristics of Arenosol is considered. Research aimed to study the effect of Cu, Zn, Ni NPs on the biological characteristics of sandy loam chernozem. Copper, Zn, and Ni NPs were added to the soil in concentrations of 100, 1,000, and 10,000 mg kg^-1. The effect of NPs on the biological properties of Arenosol was evaluated after 10-day incubation. The biological indices of the ecological condition of the soil, including the germination of radish, the length of the roots, the bacteria population, <em>Azotobacter</em> sp. count, the catalase activity, and dehydrogenases were studied. As a result of this study, it was revealed that the degree of indices changes depending on the concentration of Cu, Zn, and Ni NPs in the Arenosols. Microbiological characteristics (bacteria population, and <em>Azotobacter</em> sp. count) and phytotoxic feature (length of roots and radish germination) properties were most sensitive to contamination compared to the enzyme activity of Arenosol. Based on the soil integral index of a biological state, the strongest inhibitory effect on biological parameters of Arenosols relative to the control was exerted by Cu NPs (lower than control by 48-72%), while the greatest stability in Arenosol was found for Ni NPs (lower than control by 30-55%). The studied biological parameters allow characterizing the severity of nanoparticle exposure on Arenosols. Early diagnostics of the severity of soil contamination by NPs can be successfully used to quickly assess their impact on the soil condition and prevent possible adverse consequences.

Ecotoxicological assessment of two surfactant on the emryonic development

In this study, zebrafish (Danio rerio) embryos was served as a model for marine fauna to determine if there is any potential of organ-specific toxicity (neuromuscular, hepatic, cytotoxic, and cardiac) caused by Silicone-Q-22 and Ploy-Q-47. as both surfactants are considered eco-friendly corrosion inhibitors. The calculated LC50 of Silicon-Q-22 and Poly-Q-47 was 22.36 and 8.28 mg/L, respectively. At NOEC both surfactants had resulted in teratogenic defects and cardiotoxicity, but only poly Q-47 resulted in neurotoxicity.

Ecotoxicological assessment of the impact of pavement material on roadside soil pollution

The ecological safety of the use of nepheline sludge in the construction of the lower foundations of pavements is shown. Using electron microscopy and chemical analysis, the area of influence of nepheline sludge used in the construction of road pavements on the roadside soil, which is limited by a distance of 10 m, was determined. Studies have been carried out on ecotoxicity using monocotyledonous and dicotyledonous plants and soil infusories of the genus Colpoda steinii. results, which confirmed the possibility of using nepheline sludge as a component of pavement in the form of nepheline-crushed stone mixture. Keywords: NEPHELINE SLAM, PAVEMENT MATERIAL, ECOLOGY, TOXICITY, ENVIRONMENTAL SAFETY

Accelerating the pace of ecotoxicological assessment using artificial intelligence

Species Sensitivity Distribution (SSD) is a key metric for understanding the potential ecotoxicological impacts of chemicals. However, SSDs have been developed to estimate for only handful of chemicals due to the scarcity of experimental toxicity data. Here we present a novel approach to expand the chemical coverage of SSDs using Artificial Neural Network (ANN). We collected over 2000 experimental toxicity data in Lethal Concentration 50 (LC50) for 8 aquatic species and trained an ANN model for each of the 8 aquatic species based on molecular structure. The R2 values of resulting ANN models range from 0.54 to 0.75 (median R2 = 0.69). We applied the predicted LC50 values to fit SSD curves using bootstrapping method, generating SSDs for 8424 chemicals in the ToX21 database. The dataset is expected to serve as a screening-level reference SSD database for understanding potential ecotoxicological impacts of chemicals.

Trace Metal Contamination of Bottom Sediments: A Review of Assessment Measures and Geochemical Background Determination Methods

This paper provides an overview of different methods of assessing the trace metal (TM) contamination status of sediments affected by anthropogenic interference. The geochemical background determination methods are also described. A total of 25 papers covering rivers, lakes, and retention tanks sediments in areas subjected to anthropogenic pressure from the last three years (2019, 2020, and 2021) were analysed to support our examination of the assessment measures. Geochemical and ecotoxicological classifications are presented that may prove useful for sediment evaluation. Among the geochemical indices, several individual pollution indices (CF, Igeo, EF, Pi (SPI), PTT), complex pollution indices (PLI, Cdeg, mCdeg, Pisum, PIAvg, PIaAvg, PIN, PIProd, PIapProd, PIvectorM, PINemerow, IntPI, MPI), and geochemical classifications are compared. The ecotoxicological assessment includes an overview of Sediment Quality Guidelines (SQG) and classifications introduced nationally (as LAWA or modified LAWA). The ecotoxicological indices presented in this review cover individual (ERi) and complex indices (CSI, SPI, RAC, PERI, MERMQ). Biomonitoring of contaminated sites based on plant bioindicators is extensively explored as an indirect method for evaluating pollution sites. The most commonly used indices in the reviewed papers were Igeo, EF, and CF. Many authors referred to ecotoxicological assessment via SQG. Moreover, PERI, which includes the toxic response index, was just as popular. The most recognised bioindicators include the Phragmites and Salix species. Phragmites can be considered for Fe, Cu, Cd, and Ni bioindication in sites, while Salix hybrid cultivars such as Klara may be considered for phytostabilisation and rhizofiltration due to higher Cu, Zn, and Ni accumulation in roots. Vetiveria zizanoides demonstrated resistance to As stress and feasibility for the remediation of As. Moreover, bioindicators offer a feasible tool for recovering valuable elements for the development of a circular economy (e.g., rare earth elements).

Is the Synthetic Fungicide Fosetyl-Al Safe for the Ecotoxicological Models Danio rerio and Enchytraeus crypticus?

Worldwide, pesticides have contaminated the environment, affecting non-target species. The aim of this work was to evaluate the effects of fosetyl-Al (FOS) on model organisms. Based on the 3 Rs for animal research and described guidelines, the OECD 236 and 220 were applied with some modifications. The FOS test concentrations were 0.02–0.2–2–20–200 mg/L for Danio rerio and 250–500–750–1000–1250 mg/kg for Enchytraeus crypticus. Besides the standard endpoints, additional endpoints were evaluated (D. rerio: behavior and biochemical responses; E. crypticus: extension of exposure duration (28 d (days) + 28 d) and organisms’ sizes). For D. rerio, after 96 h (h), hatching was inhibited (200 mg/L), proteins’ content increased (2 and 20 mg/L), lipids’ content decreased (2 mg/L), glutathione S-transferase activity increased (2 mg/L), and, after 120 h, larvae distance swam increased (20 mg/L). For E. crypticus, after 28 d, almost all the tested concentrations enlarged the organisms’ sizes and, after 56 d, 1250 mg/kg decreased the reproduction. In general, alterations in the organisms’ biochemical responses, behavior, and growth occurred at lower concentrations than the effects observed at the standard endpoints. This ecotoxicological assessment showed that FOS may not be considered safe for the tested species, only at higher concentrations than the predicted environmental concentrations (PECs). This research highlighted the importance of a multi-endpoint approach to assess the (eco)toxic effects of the contaminants.