Treating sewage containing antibiotics is a complex process that needs research. An anaerobic method for organic matter removal from wastewater is the most optimal treatment option, which can provide antibiotic removal under the condition of prior adaptation of anaerobic microorganism association to antibiotic. The aims of the study were to obtain a microorganism association tolerant to antibiotics and to investigate the anaerobic association (methanogens) composition before and after adaptation. The subject of the study was the determination of microorganism association properties in conditions of high antibiotic concentration, which enables the determination of the adaptation mechanism. Adaptation of microorganism association to antibiotics was carried out by a gradual increase of antibiotic concentration in the nutrient medium (anaerobic conditions of detention, mesophilic regime). The qualitative and quantitative composition of biogas was determined by gas chromatography. DNA of microorganism associations was isolated by the agrobacteria DNA isolation method. The determination of archaeal 16SrRNA genes in DNA was performed by polymerase chain reaction (PCR). Information about gene structure was obtained by sequencing. It has been shown that the biogas output during anaerobic sewage treatment with antibiotic-adapted microorganism association increases regardless of antibiotic concentration. When enriching microorganism association with methanogens, tolerant to antibiotics, the biogas output grows by 32–38% depending on their amount. It was found that, when using tetracycline and norfloxacin, in the microorganism association methanogens of the genus Methanobacterium are dominant due to their resistance. Influence of antibiotics tetracycline and norfloxacin on raw materials leads to a decrease in the species volume of the Methanosarcinaceae family.

The most important effect of natural organic materials in water is reacting with disinfectants and creating disinfectant by-products that are mostly carcinogenic. The aim of this study was to determine the optimum conditions for removal of humic acid (HA) by zeolite coated with nZVI nanoparticles (Zeolite/nZVI) from aqueous solutions. In this study, after synthesis of zeolite/nZVI, its structure and morphology were examined using FTIR, BET, XRF, and FESEM techniques. The effects of HA concentration, composite content, pH, and reaction time were evaluated. The experimental data were analyzed by Langmuir and Freundlich isotherm and pseudo-first-order and second-order kinetic models. Finally, the thermodynamic parameters of enthalpy (ΔΗ°), entropy (ΔS°), and Gibbs free energy (ΔG°) were calculated. The results of the analyses confirmed the accuracy of the composite structure. Its specific surface area by using BET method was 203.43 m²/g. The HA removal efficiency was obtained at 92.98% in optimum conditions of 50 mg/L concentration, 2 g/L composite dose, pH = 3, and reaction time of 60 min. The results of the isotherm and kinetic study showed that the HA adsorption process follows the Langmuir isotherm (R² = 0.9707) and pseudo-second-order kinetic. The maximum adsorption capacity of the composite was determined at 23.36 mg/g by Langmuir model. Thermodynamic parameters indicate that the adsorption of HA endothermic and the reaction cannot be done spontaneously. Zeolite/nZVI composite had good removal efficiency after five times of recycling. The present study showed that zeolite/nZVI can be used as an effective adsorbent for removal of HA from aqueous solutions.

Accurate prediction of salinity concentration in the aquifer in response to fluctuating groundwater pumping pattern is an essential component of any coastal groundwater planning and management framework. Data-driven prediction models have been proved efficient in predicting groundwater salinity levels in coastal aquifers. The use of ensemble prediction models is known to be more accurate with robust prediction capabilities when compared with standalone prediction models. This study compares the performances of homogeneous and heterogeneous ensemble models for groundwater salinity predictions. A homogeneous ensemble model is composed of several standalone models of the same type (i.e. employs one machine learning tool) whereas a heterogeneous ensemble model is composed of several standalone models of different types (i.e. employs multiple machine learning tools). Specifically, homogeneous and heterogeneous ensemble models of various standalone machine learning tools such as artificial neural network (ANN), genetic programming (GP), support vector regression (SVR), and Gaussian process regression (GPR) are developed to predict groundwater salinity concentrations in a small Pacific island coastal aquifer system. Standalone and ensemble prediction models are trained and validated using identical pumping and resulting salinity concentration datasets obtained by solving numerical 3D transient density-dependent coastal aquifer flow and transport model. After validation, the ensemble models are used to predict salinity concentration at selected monitoring wells in the modelled aquifer under variable groundwater pumping conditions. Prediction capabilities of the developed ensemble models are quantified using standard statistical procedures. The performance evaluation result suggested that the predictive capabilities of the developed standalone prediction models (ANN, GP, SVR, and GPR) were comparable with the numerical groundwater variable density-dependent flow and salt transport model. However, GPR standalone models had better prediction capabilities when compared with the other standalone models. Also, SVR and GPR standalone models were more efficient (i.e. took less computational training time) than other standalone models. In terms of ensemble models, the performance of the homogeneous GPR ensemble model was established to be superior to other homogeneous and heterogeneous ensemble models. The homogeneous GPR ensemble model was favoured both in terms of efficiency. Overall, based on the limited performance evaluation result, GPR homogeneous model was considered to be the best prediction model when compared with all the standalone models, other homogeneous ensemble model, and the heterogeneous ensemble model. Therefore, it can be utilised as a reliable groundwater salinity prediction tool and also used as an approximate simulator in coupled simulation-optimization models needed for prescribing optimal groundwater management strategies.

The critical issue generated by foaming in wastewater treatment plants (WWTPs) is a problem that is currently very common and shared, but which to date is treated mainly only at the management level. In this work, an experimental study with foam tests on real and synthetic waters was conducted using a laboratory scale plant and foaming power indices were calculated. To date, the estimation of foaming potential is mainly based on these indices which give information only on height/volume of foams but not on the type of foams, in terms of consistency and therefore stability. Tests showed that foaming power indices were highly variable with the same water: it was not possible to identify a single foaming potential value for each water. Two models were proposed to estimate the percentage increase in height of chemical foams produced following the introduction of air below the surface of a liquid. In terms of determination coefficient, the results obtained from the complex model were better: R² was 0.82 for the simple linear model and 0.90 for the complex one. This approach has allowed to underline some critical aspects of foaming potential as it is determined today and the possible improvements applicable for a more objective evaluation.

The effects of different additives on the compost of Camellia oleifera shell were characterized and a maturity evaluation system for the obtained compost was established. Four treatments were designed as C. oleifera shell with C. oleifera seed meal (A1), with C. oleifera seed cake (A2), with sheep manure (A3), and with spent mushroom substrate (A4). A3 had the longest thermophilic phase (over 50 °C) and shortest cooling phase. Compared with A1, the thermophilic phase of A2 was postponed 11 days due to the high lipid content, but terminated almost at the same time. The temperature of A4 increased slowly and took longer time to reach ambient. C/N, pH, E4/E6, and NH₄⁺-N decreased along with composting process, while TN, GI, and NO₃⁻-N were opposite. Based on the Pearson correlation analysis with the Solvita maturity index as a reference, the result indicated that TN, C/N, GI, NH₄⁺-N, and pH can be used for the maturity evaluation.

Eggshells (ESs), a low-cost biosorbent rich in calcium carbonate (CaCO₃), were used to sustainably reduce the acidity and remove the Fe₍ₜₒₜₐₗ₎, Al³⁺, and Mn₍ₜₒₜₐₗ₎ ions from coal mine-impacted water (MIW). The surface area and pore volume of ES biomaterial were 5.692 m² g⁻¹ and 0.0567 cm³ g⁻¹, respectively. The remediation process was performed in two consecutive stages, with Fe₍ₜₒₜₐₗ₎ and Al³⁺ ions being removed in the first stage (treatment I) and the Mn₍ₜₒₜₐₗ₎ ions in the second one (treatment II). The best treatment conditions, statistically determined through a central composite rotatable design (CCRD), were 6.59 g L⁻¹ ES and 95 rpm agitation rate for treatment I and 28 g L⁻¹ ES and 280 rpm agitation rate for treatment II. However, the high ES dosage in treatment II, determined by extrapolation, led in practice to the formation of particle aggregates that decreased the treatment efficiency. Therefore, the best values experimentally determined for treatment II were 25 g L⁻¹ ES and 250 rpm. In these conditions, the overall treatment provided complete MIW acidity neutralization, total removal of the Fe₍ₜₒₜₐₗ₎ and Al³⁺ ions, and 58% Mn₍ₜₒₜₐₗ₎ ion removal, providing treated fluvial water adequate for non-potable use based on the analyzed parameters.

Highly efficient and effective treatments of hazardous dye-based color effluents are a major problem in the industrial sector. In this research, the cobalt ferrite (CoFe₂O₄) catalyst was produced and used for the degradation of Congo red (CR) as a model dye from aqueous solution. For a said purpose, cobalt ferrite (CoFe₂O₄) nanostructures with photocatalytic degradation potential were engineered via co-precipitation method using Fe₂(SO₄)₃, CoO₂, and triethylene glycol (as a stabilizing agent). As prepared, CoFe₂O₄ nanostructures were further surface-functionalized with 3-APTES and tested for CR degradation. The prepared CoFe₂O₄ nanostructures were characterized by X-ray diffraction, Fourier transform infra-red (FT-IR), scanning electron microscopy (SEM), and Brunauer-Emmitt-Teller (BET) analysis. UV-visible absorption was used to measure the optical band gap of prepared CoFe₂O₄ nanostructures through Tauc plots. The as-prepared CoFe₂O₄ nanostructure bandgap was found to be 2.71 EV while using an acidic medium. The degradation rates of CR dye for bs-CoFe₂O₄, as-CoFe₂O₄, and fs-CoFe₂O₄ nanostructures at pH 9 were 84, 87, and 92%, respectively. Furthermore, the influences of various process parameters, i.e., the effect of catalyst dose, contact time, dye dose/concentration, pH effect, and effect of different acids, were checked for the prepared three types of nanostructures, i.e., bs-CoFe₂O₄, as-CoFe₂O₄, and fs-CoFe₂O₄. The kinetics models properly explained that the reaction of degradation following pseudo-first-order kinetics.

In Brazil, safe drinking water is not widely available, and consequently waterborne diseases are still associated with high morbidity and mortality rates. Among waterborne bacteria, diarrheagenic Escherichia coli (DEC) should be highlighted. This study targeted the evaluation of enteropathogenic (EPEC), enterotoxigenic (ETEC), and shiga toxin-producing (STEC)/enterohemorrhagic Escherichia coli in drinking water in Southeast Brazil and the georeferencing of generated data. A total of 1185 water samples were studied. Among them 7.8% and 4.1% gave positive results for total and fecal coliforms, respectively. By employing PCR, a total of 12 diarrheagenic E. coli (DEC) isolates (6 ETEC, 4 STEC, and 2 EPEC) from eight water samples (4, 2, and 2 positives for STEC, ETEC, and EPEC, respectively) were detected including samples collected in schools and a healthcare facility where particularly susceptible hosts are found. Data generated were submitted to georeferencing. A positive correlation (r² = 0.9) between DEC detection and the rainy period was observed. The presence of DEC in drinking water samples in the studied municipalities highlights the relevance of controlling the sources of human and animal fecal pollution, as well as the management of municipal wastewater sources in order to reduce potential risks to human health. Searching for DEC and georeferencing DEC positive sites may subsidize the proposal of corrective and preventive actions by environmental surveillance agencies.

This work describes efforts to encapsulate savory (Satureja hortensis L.) essential oil (EO) with different natural polymers (i.e., Arabic gum/gelatin (AGG), apple pectin (AP), gelatin (G)) and, as a separate set of experiments, with bio cross-linkers (i.e., citric acid and transglutaminase enzyme). The phytotoxic activity of encapsulated savory EO on tomato (Lycopersicon esculentum Mill.) and amaranth weed (Amaranthus retroflexus L.) was investigated. The micro-capsules were evaluated in terms of size, polydispersity, stability, encapsulation efficiency, morphology, and release properties. The Korsmeyer–Peppas model operated when EO was being released from the micro-capsules. Carvacrol (52.5%) and γ-terpinene (30.2%) comprised the main constituents of the savory EO. Based on the results, encapsulating the EO with cross-linked biopolymers increased the stability and herbicidal activity of EO, as compared to simple EO emulsions. Maximum toxicity injuries (MTI) were caused by encapsulations of apple pectin, cross-linked with APe enzyme (15 ml/L) on both plant species. MTI were observed 2 days after using the micro-encapsulated herbicides (MCHs). However, the injury caused by MCHs on tomato was not significant. The lowest values of fresh weight (2.80 g), chlorophyll a (0.194 mg/g Fw), and total chlorophyll content (0.219 mg/g Fw) of amaranth occurred in response to APe (15 ml/L). Moreover, using AP(e) (10 ml/L) caused the lowest values of starch (0.444 mg/g Fw) and flavonoid contents (4.18 mg Cat/g Fw) in amaranth which measured as 59% and 90% reductions, respectively, in comparison with the control. The highest values of MDA (0.0109 nmol/g Fw) and H₂O₂ (0.0432 μmol/g Fw) were observed in amaranth plants treated with AP(e) (10 ml/L). In summary, cross-linked apple pectin can perform well in slow release delivery systems of agrochemicals. It can be recommended for use in the production of commercial, EO-based natural herbicides.

Surfactants are substances applicable in the removal of heavy metals from contaminated soil. This study aims to investigate the effects of surfactant mixtures, composed of nonionic, anionic, and cationic surfactants, on the removal efficiency of Cd and Zn by mixture design (MD). Central composite rotatable design (CCRD) was integrated to optimize the conditions of contaminated soil washing. However, as representatives of each type of surfactant, a single surfactant with the most effective Cd removal was selected for each type before MD and CCRD studies. Sodium dodecyl sulfate (SDS) and sodium laureth sulfate (SLES) were the most effective anionic surfactants, while dodecyl trimethyl ammonium bromide (DTAB) and polysorbate 80 (Tween 80) were chosen to represent cationic surfactants and nonionic surfactants, respectively. Two systems of SDS-DTAB-Tween 80 and SLES-DTAB-Tween 80 were studied to examine their roles in Cd and Zn removal by MD. The results indicate insignificant enhancement in mixed surfactant systems for Cd and Zn removal. DTAB was identified as an ineffective surfactant, but at present, the presence of Tween 80 in both systems compensated for the use of SDS and SLES. The system containing SLES was selected to study CCRD because of its low cost and biodegradation. Cd and Zn removal efficiencies were 45.2% and 47.7%, respectively, at 40 mmol/L of 5-mL SLES solution per gram of soil with a 200-rpm shaker speed for 8 h. The Cd concentration of treated soil met Thailand’s agricultural soil standard. However, the further increase in removal efficiency should be considered. Graphical Abstract