A previous study has revealed that the parameter k∙ECₓ, characterizing the shape of concentration-response curves (CRCs), could predict the combined toxicity of binary mixtures. This study further explored the predictability of multi-component mixtures. Eleven component mixtures were designed using the uniform design ray, and the acute toxicity of the eleven environmental pollutants and their mixtures to Vibrio fischeri was determined using microplate toxicity analysis. We used independent action (IA) and the effect residual ratio (ERRₓ) models to evaluate the combined toxicity of multi-component mixtures and ascertain the functional relationship between σ²₍ₖ∙ECₓ₎, a parameter characterizing the CRC morphological difference of multi-component mixtures, and combined toxicity. The variance σ²₍ₖ∙ECₓ₎ of each component characteristic parameter of multi-component mixtures gradually increased in the concentration range, and the relationship between σ²₍ₖ∙ECₓ₎ and ERRₓ was consistent with the exponential function. The literature verification showed that this rule is generally applicable to the acute toxicity of multi-component mixtures to luminescent bacteria. The exponential function showed the variation rule of the joint action of multi-component mixtures. In the present study, the joint toxicity of multi-component mixtures can be predicted from single toxicity and small amount of multiple toxicity, circumventing complex multi-component toxicity experiments.

Neonicotinoids are among the chemicals most widely used against insects considered agricultural pests, although they may also affect nontarget species, as has been reported for social bees. Social wasps are recognized as efficient predators of larvae of other insects, including pest species, so they may have contact with insecticides, at least indirectly. However, to date, there have been no studies investigating the consequences for social wasps of the use of neonicotinoids. Therefore, the aim of this study was to obtain the topical and oral acute lethal mean doses of the neonicotinoid thiamethoxam, as well as to evaluate the effects of sublethal contamination, for the social wasp Polybia paulista. Foraging wasps were exposed orally and topically, with monitoring of their mortality after 24 and 48 h, in order to calculate the LD₅₀ values. Other wasps were then exposed with sublethal doses, in order to evaluate the effects of contamination on their mobility. The results indicated that P. paulista workers are as sensitive to thiamethoxam contamination as several nontarget species studied previously. Exposure to a sublethal dose (LD₁₀) negatively affected their mobility. It could be concluded that social wasp colonies may be as much affected by exposure to neonicotinoids as social bees. Further toxicological studies should be conducted, evaluating other parameters and different species, in order to understand the extent of the problems faced by these insects due to the use of neonicotinoids.

Ecological risk assessment of contaminated sediment has become a fundamental component of water quality management programs, supporting decision-making for management actions or prompting additional investigations. In this study, we proposed a machine learning (ML)-based approach to assess the ecological risk of contaminated sediment as an alternative to existing index-based methods and costly toxicity testing. The performance of three widely used index-based methods (the pollution load index, potential ecological risk index, and mean probable effect concentration) and three ML algorithms (random forest, support vector machine, and extreme gradient boosting [XGB]) were compared in their prediction of sediment toxicity using 327 nationwide data sets from Korea consisting of 14 sediment quality parameters and sediment toxicity testing data. We also compared the performances of classifiers and regressors in predicting the toxicity for each of RF, SVM, and XGB algorithms. For all algorithms, the classifiers poorly classified toxic and non-toxic samples due to limited information on the sediment composition and the small training dataset. The regressors with a given classification threshold provided better classification, with the XGB regressor outperforming the other models in the classification. A permutation feature importance analysis revealed that Cr, Cu, Pb, and Zn were major contributors to toxicity prediction. The ML-based approach has the potential to be even more useful in the future with the expected increase in available sediment data.

Peracetic acid (PAA) as an emerging oxidative has been concerned increasingly due to its high oxidation capacity and low byproducts formation potential. This study was to investigate the oxidation of sulfamethazine (SMZ) by PAA activated with activated biochar (ABC) after thermal modification. The results demonstrated that PAA could be effectively activated by ABC to degrade SMZ in a wide pH range (3–9), which followed the pseudo-second-order kinetics (R² > 0.99). Both non-radicals (singlet oxygen) and free radicals (alkoxy radicals, hydroxyl radicals) existed in the ABC/PAA system, and the degradation of SMZ was dominated by singlet oxygen. Humic acid (HA), SO₄²⁻ and HCO₃⁻ slightly inhibited the degradation of SMZ in the ABC/PAA process, while Cl⁻ and Br⁻ promoted the degradation of SMZ. The cleavage of S–N, S–C bond, and SO₂ extraction reaction rearrangement was the main oxidation process of SMZ. Meanwhile, the results of the ECOSAR program showed that the acute toxicity of most by-products was significantly reduced compared to SMZ, which revealed the potential applicability of the ABC/PAA process in the treatment of antibiotics pollution and their detoxification.

Plant-based products such as essential oils and other extracts have been used for centuries due to their beneficial properties. Currently, their use is widely disseminated through a variety of industries and new applications are continuously emerging. For these reasons, they are produced industrially in large quantities and consequently they have the potential to reach the environment. However, the potential effects that these products have on the ecosystems’ health are mostly unknown. In recent years, the scientific community started to focus on the possible toxic effects of essential oils and plant extracts towards non-target organisms. As a result, an increasing body of knowledge has emerged. This review describes the current state of the art on the toxic effects that essential oils and plant extracts have towards organisms from different trophic levels, including producers, primary consumers, and secondary consumers. The majority of the studies (76.5%) focuses on the aquatic environment, particularly in aquatic invertebrates (45.1%) with only 23.5% of the studies focusing on the potential toxicity of plant-derived products on terrestrial ecosystems.While some essential oils and extracts have been described to have no toxic effects to the selected organisms or the toxic effects were only observable at high concentrations, others were reported to be toxic at concentrations below the limit set by international regulations, some of them at very low concentrations. In fact, L(E)C₅₀ values as low as 0.0336 mg.L⁻¹, 0.0005 mg.L⁻¹ and 0.0053 mg.L⁻¹ were described for microalgae, crustaceans and fish, respectively. Generally, essential oils exhibit higher toxicity than extracts. However, when the extracts are obtained from plants that are known to produce toxic metabolites, the extracts can be more toxic than essential oils.Overall, and despite being generally considered “eco-friendly” products and safer than they synthetic counterparts, some essential oils and plant extracts are toxic towards non-target organisms. Given the increasing interest from industry on these plant-based products further research using international standardized protocols is mandatory.

In this study, we treated harmful Microcystis aeruginosa cyanobacteria using chitosan-modified nanobubbles. The chitosan-modified nanobubbles (255 ± 19 nm) presented a positive zeta potential (15.36 ± 1.17 mV) and generated significantly (p < 0.05) more hydroxyl radicals than the negatively charged nanobubbles (−20.68 ± 1.11 mV). Therefore, the interaction between the positively charged chitosan-modified nanobubbles and negatively charged M. aeruginosa (−34.81 ± 1.79 mV) was favored. The chitosan-modified nanobubble treatment (2.20 × 10⁸ particles mL⁻¹) inactivated 73.16% ± 2.23% of M. aeruginosa (2.00 × 10⁶ cells mL⁻¹) for 24 h without causing significant cell lysis (≤0.25%) and completely inhibited the acute toxicity of M. aeruginosa toward Daphnia magna. The inactivation was correlated (r² = 0.97) with the formation of reactive oxygen species (ROS) in M. aeruginosa. These findings indicated that the hydroxyl radicals generated by the chitosan-modified nanobubbles disrupted cell membrane integrity and enhanced oxidative stress (ROS formation), thereby inactivating M. aeruginosa. Moreover, the penetration of the chitosan-modified nanobubbles and cell alterations in M. aeruginosa were visually confirmed. Our results suggested that the chitosan-modified nanobubble treatment is an eco-friendly method for controlling harmful algae. However, further studies are required for expanding its practical applications.

A broad-spectrum fungicide, dichlofluanid is widely used in antifouling paints and agricultural pesticides. In this study, the acute and chronic effects of sublethal concentrations, namely, no observable effect concentration (NOEC) and 50% lethal concentration (LC₅₀) of dichlofluanid (1/10 NOEC, NOEC, 1/10 LC₅₀, and LC₅₀) were evaluated on the marine mysid, Neomysis awatschensis. Acute toxicity test (96 h) showed higher sensitivity to dichlofluanid in juvenile mysids (LC₅₀ 3.1 μg L⁻¹) than adults (LC₅₀ 24.5 μg L⁻¹), with lower survival rate and reduction in food consumption. Exposure with dichlofluanid considerably induced oxidative imbalance, as NOEC (0.006 μg L⁻¹ for juveniles and 0.074 μg L⁻¹ for adults) and 1/10 LC₅₀ values increased intracellular concentrations of malondialdehyde and glutathione, and the enzymatic activities of catalase and superoxide dismutase, whereas exposure to LC₅₀ value decreased the values of oxidative parameters. Enzymatic activity of acetylcholinesterase decreased considerably when exposed to LC₅₀ value. In the case of chronic effects, exposure to NOEC for 4 weeks markedly decreased the juvenile survival rate, while adults showed tolerance. Multigenerational monitoring in response to NOEC showed a significant growth retardation with an increase in intermolt duration as well as a decrease in the number of newborn mysids from females of the third generation. Consistent exposure to environmentally relevant sublethal concentrations of dichlofluanid would be detrimental to mysid individuals and the survival of the mysid population.

It is difficult to achieve simultaneous and efficient removal of heterocyclic drugs (HCDs) and total nitrogen (TN) in conventional denitrification biofilter (DNBF). Inspired by the effective degradation of refractory organic matter by cobalt-based advanced oxidation process and the need for in-situ upgrading of DNBF, peracetic acid (PAA)/cobalt-loaded ceramsite-based DNBF system was constructed for the first time to treat biochemical tailwater containing HCDs. Results showed that PAA/Co-DNBF had relatively high removal rates for the four HCDs with the order of CBZ > TMP > SDZ > SMX, and the optimal DNBF was H2 with 150 μg L⁻¹of PAA. Overall, TN and HCDs removal increased by 178%–455% and 2.50%–40.99% respectively. When the influent concentration of NO₃⁻-N, COD and each HCDs of 20 mg/L, 60 mg/L and 20 μg/L, below 15 mg/L of effluent TN and the highest average removal rate of SMX (67.77%) could be achieved, under HRT of 4 h in H2. More even distribution of microbial species and low acute toxicity of effluent were also achieved. More even distribution of microbial species and low acute toxicity of effluent were also achieved. In addition, high extracellular polymeric substance (EPS) content and Gordonia after the addition of PAA contributed to the degradation of HCDs. This study supplied a potentially effective strategy for the treatment of biochemical tailwater containing HCDs and provided new insight into the advance of denitrification technology.

Cytochrome P450 1a (Cyp1a) is an important enzyme for metabolism of organic pollutants. To understand its reaction to polycyclic aromatic hydrocarbons (PAHs), we knocked out this gene in a marine model fish, Javanese medaka, Oryzias javanicus, using the CRISPR/Cas 9 system. A homozygous mutant (KO) strain with a four-base deletion was established using an environmental DNA (eDNA)-based genotyping technique. Subsequently, KO, heterozygous mutant (HT), and wild-type (WT) fish were exposed to model pollutants, pyrene and phenanthrene, and survivorship and swimming behavior were analyzed. Compared to WT, KO fish were more sensitive to pyrene, suggesting that Cyp1a transforms pyrene into less toxic metabolites. Conversely, WT fish were sensitive to phenanthrene, suggesting that metabolites transformed by Cyp1a are more toxic than the original compound. HT fish showed intermediate results. Thus, comparative use of KO and WT fish can distinguish modes of pollutant toxicity, providing a deeper understanding of fish catabolism of environmental pollutants.

The ecotoxicity of nitrofurazone was analyzed based on a community-based approach using periphytic protozoa. Median lethal concentrations (LC₅₀) within an exposure time of 30 min were determined by an acute toxicity test at 0, 1.5, 3, 6 and 12 mg ml⁻¹ nitrofurazone. Toxicity curve tests demonstrated a decreasing trend with increasing exposure time and was well fitted to the toxicity equation LC₅₀ = 32.85e⁻⁰.⁸¹⁴³ᵗ (t = exposure time; R² = 0.91; P < 0.05). Median inhibition concentrations (IC₅₀) for periphytic protozoan growth rates were obtained by chronic tests at 0, 1, 2, 4 and 8 mg ml⁻¹ nitrofurazone within 10 days exposure and were well fitted to the equation r% = 0.3686e⁻⁰.³⁵Cⁿⁱᵗ (Cₙᵢₜ is the concentration of nitrofurazone; R² = 0.92 and P < 0.05). These findings suggest that the LC₅₀ and IC₅₀ values of nitrofurazone can be predicted for any exposure time using periphytic protozoan communities as a bioassay model.