Environmental Science and Pollution Research最新文献

In this study, hazardous wastes including fluff, dust, and scrubbing sludge were sampled in 2019 from two metal shredding facilities located in Wallonia, Belgium. To assess the extent of the contamination, a global approach combining chemical and biological techniques was used, to better reflect the risks to health and the environment. The samples investigated induced significant in vitro aryl hydrocarbon receptor (AhR) agonistic bioactivities and estrogenic receptor (ERα) (ant)agonistic bioactivities in the respective CALUX (chemical activated luciferase gene expression) bioassays. The mutagenicity of the samples was investigated with the bacterial reverse gene mutation test using the Salmonella typhimurium TA98 and TA100 strains. Except for the sludge sample (site 3), all samples induced a mutagenic response in the TA98 strain (± S9 metabolic fraction) whereas in the TA100 strain (+ S9 metabolic fraction), only the sludge sample (site 2) showed a clear mutagenic effect. The in vivo toxicity/teratogenicity of the shredder wastes was further evaluated with zebrafish embryos. Except for the dust sample (site 2), all samples were found to be teratogenic as they returned teratogenic indexes (TIs) > 1. The high levels of contamination, the mutagenicity, and the teratogenicity of these shredder wastes raise significant concerns about their potential negative impacts on both human health and environment.

The removal kinetics of an aqueous mixture of thirteen antibiotics (i.e., ampicillin, cefuroxime, ciprofloxacin, flumequine, metronidazole, ofloxacin, oxytetracycline, sulfadimethoxine, sulfamethoxazole, sulfamethazine, tetracycline, trimethoprim and tylosin) by batch UV_C and UV_C/H₂O₂ processes has been modeled in this work. First, molar absorption coefficients (ε), direct quantum yields (Φ) and the rate constants of the reaction of antibiotics with hydroxyl radical (k_HO•) (model inputs) were determined for each antibiotic and compared with literature data. The values of these parameters range from 0.3 to 21.8 mM^-1 cm^-1 for ε, < 0.01 to 67.8 mmol·E^-1 for Φ and 3.8 × 10⁹ to 1.7 × 10¹⁰ M^-1 s^-1 for k_HO•. Second, a regression model was developed to compute the rate constants of the reactions of the antibiotics with singlet oxygen (k¹_O₂) from experimental data obtained in batch UV_C experiments treating a mixture of the antibiotics. k¹_O₂ values in the 1-50 × 10⁶ M^-1 s^-1 range were obtained for the antibiotics studied. Finally, a semi-empirical kinetic model comprising a set of ordinary differential equations was solved to simulate the evolution of the residual concentration of antibiotics and hydrogen peroxide (model outputs) in a completely mixed batch photoreactor. Model predictions were reasonably consistent with the experimental data. The kinetic model developed might be combined with computational fluid dynamics to predict process performance and energy consumption in UV_C and UV_C/H₂O₂ applications at full scale.

This work involved the preparation of pristine and iron nanoparticle-loaded biochar from a water chestnut shell to remove diclofenac sodium (DCF) containing effluent of pharmaceutical origin. To create suitable forecasting equations for the modelling of the DCF adsorption onto the adsorbent, response surface methodology (RSM) was used. The parameters, e.g. pH, adsorbent mass, DCF concentration and contact time, were used for the modeling of adsorption. The RSM model predicts that for 98.0% DCF removal, the ideal conditions are pH 6, an adsorbent dose of 0.5 g L^-1, and a contact time of 60 min with an initial adsorbate concentration of 25 mg L^-1 at 303 K. The maximum capacity deduced from the Langmuir model was 75.9 mg g^-1 for pristine water chestnut shell biochar (pWCBC) and 122.3 mg g^-1 for magnetically modified nano-Fe₂O₃ biochar (mWCBC). Under equilibrium conditions, the Langmuir model was the best-suited model compared to the Temkin and Freundlich models. The adsorption data in this investigation efficiently fitted the pseudo-second-order model, emphasizing that chemisorption or ion exchange processes may be involved in the process. The WCBC demonstrated recyclability after 10 cycles of repeated adsorption and desorption of DCF. A combined coagulation adsorption process removed COD, NH₃-N, NO₃^-, PO₄^3-, and DCF by 92.50%, 86.41%, 77.57%, 84.54%, and 97.25%, respectively. This study therefore shows that coagulation followed by adsorption onto biochar can be a cost-effective substitute for conventional pharmaceutical wastewater treatment.

CO₂ emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the environment, if the emissions are left unchecked. Several strategies have been explored of which carbon capture is considered the most suitable for faster deployment. Among different carbon capture solutions, adsorption is considered both practical and sustainable for scale-up. But the development of adsorbents that can exhibit satisfactory performance is typically done through the experimental approach. This hit and trial method is costly and time consuming and often success is not guaranteed. Machine learning (ML) and other computational tools offer an alternate to this approach and is accessible to everyone. Often, the research towards materials focuses on maximizing its performance under simulated conditions. The aim of this study is to present a holistic view on progress in material research for carbon capture and the various tools available in this regard. Thus, in this review, we first present a context on the workflow for carbon capture material development before providing various machine learning and computational tools available to support researchers at each stage of the process. The most popular application of ML models is for predicting material performance and recommends that ML approaches can be utilized wherever possible so that experimentations can be focused on the later stages of the research and development.

In this study, neodymium-doped titanium dioxide (Nd-TiO₂) nanoparticles were synthesized via a hydrothermal method for the photocatalytic degradation of Rhodamine B (RhB) under UV and sunlight conditions. The properties of these NPs were comprehensively characterized. And optimization of RhB degradation was conducted using control-variable experiment and artificial neural networks (ANN) under various operational conditions and in the presence of competing compounds. The acute toxicity of both NPs, RhB, and the environmental impact of the photocatalytic treatment effluent on Danio rerio were evaluated. The Nd modification increased the catalyst's specific surface area and thermal stability. X-ray diffraction confirmed the tetragonal anatase phase in undoped TiO₂, while Nd-doped TiO₂ exhibited shifts in peaks and the presence of brookite and rutile phases. Nd (1 mol%) doped TiO₂ demonstrated superior RhB photocatalytic degradation efficiency, achieving 95% degradation and 82% total organic carbon (TOC) removal within 60 min under UV irradiation. Optimization under sunlight conditions yielded 95.14% RhB removal with 0.28 g/L photocatalyst and 1% doping. Under UV light, 98.12% RhB removal was optimized with 0.97% doping, along with the presence of humic acid and CaCl₂. ANN modeling achieved high precision (R² of 0.99) in modeling environmental photocatalysis. Toxicity assessments indicated that the 96-h LC50 values were 681.59 mg L^-1 for both NPs, and 23.02 mg L^-1 for RhB. The treated dye solution exhibited a significant decline in toxicity, emphasizing the potential of 1% Nd-TiO₂ in wastewater treatment.

Microplastic studies investigating concentrations in water are numerous, but the majority of microplastics settle and are retained in sediment, and higher concentrations are regularly reported in sediments. Thus, MPs accumulation may be more threatening to benthic fish living in sediments than to pelagic fish. The presence, abundance and diversity of microplastics were investigated by collecting samples from two pelagic, European anchovy, and horse mackerel and two benthic fish species, red mullet, and whiting that are popularly consumed in Giresun province of Türkiye, located on the southern coast of the Black Sea. Visual classification and chemical compositions of microplastics was performed using a light microscope and ATR-FTIR spectrophotometry, consecutively. The overall incidence and mean microplastics abundance in sampled fishes were 17 and 1.7 ± 0.18 MP fish^-1, respectively. MPs were within the range of 0.026-5 mm in size. In most of the cases, the MP was black in color with 41%. With the rates of 56%, polypropylene was the predominant polymer type. The most dominant MP type was identified as fiber followed by fragments and pellets. The relationship between MP amounts in fish and Fulton condition factor was not strong enough to establish a cause-effect relationship.

In the present paper, activated nano-carbon soot is derived from atmospheric flame combustion of thymol-mustard oil followed by activation with potassium hydroxide (KOH) to produce micro- and mesoporous interiors. Different forms of activated nano-carbon soot are produced by using different weight percentage ratios 1:1, 1:3, and 1:5 of precursor carbon soot (CS) to KOH and named CS11, CS13, and CS15, respectively. An increase in specific surface area and average pore volume is observed with an increase in the amount of KOH with the hierarchical network having balanced micropores as well as mesopores in CS15. The electrochemical performance of prepared activated nano-carbon soot is further investigated by the fabrication of a symmetric electric double-layer solid-state supercapacitor (SC) device utilizing a 6 M KOH electrolyte. The CS15-based device displays the highest specific capacitance (C_sp) of 226.20 F/g at a current density of 0.5 A/g with energy density (E_d) 31.42 Wh/kg at a power density (P_d) of 250 W/kg. The C_sp, E_d, and P_d are found to be higher than activated nano-carbon soot reported in the literature. Further, three-coin cells are fabricated using CS15 which are tested in series combination with yellow light emitting diode (LED) and are found to be able to glow LED for ~ 5 min 25 s.

Crop losses to pests were the main obstacle to food security globally. Pest control was a laudable exercise, but the exercise could be hindered by the inevitable adjustment between pest reductions, operation costs as well as impacts on the environment and human health. The pest could be controlled by many methods, but biological control was the most popular technique because it addressed inevitable trade-offs between costs and side effects. In this paper, a mathematical model was developed to quantify intricate biological procedures in the context of biological control using prey-predator mechanisms. Three equilibrium points (one trivial and two non-trivial) were derived, and the stability of each equilibrium point was examined. The stability results indicated that the adoption of biological control might neutralize pest infestation but the situation might not persist (unstable trivial equilibrium). It was also discovered that pest control through biological means might fail if the predator was wrongly selected or if the population of the predator vanished while the pest remained in existence (unstable non-trivial equilibrium). The analytical results were finally justified by a means of simulation via a computer-in-built maple program.

The present paper deals with an analysis of total arsenic concentration using ICP-MS/MS and an analysis of concentration of several arsenic species, arsenite (As^III), arsenate (As^V), monomethylarsonate (MMA), dimethylarsenite (DMA), and trimethylarsine oxide (TMAO), using HPLC-ICP-MS/MS in the PM₁₀ fraction of airborne urban aerosol. The samples were collected during two campaigns, in the autumn of 2022 and in the winter of 2023, at three locations within the central European city of Brno, with the aim to evaluate the seasonal and spatial variations in the PM₁₀ composition. The results confirmed only the seasonal variability in the content of the methylated arsenic species in PM₁₀ influenced by biomethylation processes. To gain better understanding of the possible arsenic origin, a supplementary analysis of the total arsenic concentrations was performed in samples of different size fractions of particulate matter collected using ELPI + . Local emissions, including industrial activities and heating during the winter season, were suggested as the most likely predominant source contributing to the total As content in PM₁₀.