Comparative Study on the Removal Efficiency of Clomazone and Amitriptyline via Adsorption and Photocatalysis in Aqueous Media: Kinetic Models and Toxicity Assessment.

This study aimed to compare the effectiveness of adsorption and photocatalysis techniques at removing the herbicide clomazone (CLO) and the antidepressant known as amitriptyline (AMI) from water. This study employed kinetic models to analyze the removal processes and assess the potential toxicity of the treated water. The structure and morphology of the prepared multi-walled carbon nanotubes were characterized as adsorbents by transmission electron microscopy, X-ray diffraction, Fourier transform infrared techniques, and Raman spectroscopy. The adsorption kinetics of CLO and AMI were studied on the pristine and functionalized multi-walled carbon nanotubes. Kinetic studies were performed by modeling the obtained experimental data using three kinetic models: pseudo-first-order, pseudo-second-order, and Elovich kinetic models. On the other hand, the efficiency of CLO and AMI photodegradation was examined as a function of the type of irradiation (UV and simulated solar irradiation) and type of TiO2 photocatalyst (Aeroxide and Kronos). Under the experimental conditions employed, the reaction followed pseudo-first-order kinetics. Additionally, in order to assess the toxicity of water containing CLO, AMI, and their intermediates, toxicity assessments were conducted using human fetal lung fibroblast cells. The results obtained indicate the effectiveness of both methods and provide valuable insights into their removal mechanisms, contributing to the advancement of sustainable water treatment strategies.

Mid-Infrared Variable Selection for Soil Organic Matter Fractions Based on Soil Model Systems and Permutation Importance Algorithm.

In this research, an attempt was made to classify soil samples according to the different fractions of soil organic matter (SOM) using model systems in which the ratio of the fractions of SOM is chemically mimicked. A mixture of starch and nicotinamide was used for the labile organic matter model, while a standard of humic acid was used for the stabile organic matter. Changing the threshold value in the selected ranges after a permutation importance algorithm is conducted using train models and test data set, a list of selected important wavelengths and their importance scores were obtained. Three regions for the classification of soil fractions within the estimated probability density function are most prominent: 800-1200 cm-1, 0.48-0.55; 1800-2000 cm-1, 0.52-0.62; and 2500-3200 cm-1, 0.48-0.62, where the first component represents the spectral range while the second component covers the range of the importance score. Obtained wavelength ranges indicate the importance of the aliphatic stretching and bending vibration region, as well as the total soil reflectance (mineral content) for the characterization of organic matter fractions. A comparative evaluation with literature data found that the obtained wavelengths have a potential for application in methods of proximal and remote detection/calibration of existing and development of new sensors for Advanced Spaceborne Thermal Emission and Reflection Radiometer satellites, specifically in the shortwave infrared and thermal infrared ranges.

DRIFT spectroscopic determination of clay and organic matter in sediment by mixed soil-sediment calibration approach.

Bioavailability and movement of pollutants through land and underground flows are strongly related to some of the sediment characteristics, such as clay minerals and organic matter. Therefore, the determination of clay and organic matter content in sediment is of great importance for environmental monitoring. Clay and organic matter in sediment were determined using diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in combination with multivariate analysis methods. Sediment from different depths was used in combination with the soil samples of different texture. Using multivariate methods and DRIFT spectra, sediments from different depths were successfully grouped according to similarity to different texture soils. Also, a quantitative analysis of clay and organic matter content was performed, where a new calibration approach was used in which sediment samples combined with soil samples were used for principal component regression (PCR) calibration. PCR models for the assessment of clay and organic matter were determined for a total of 57 sediment samples and 32 soil samples, and satisfactory determination coefficients were obtained for linear models (0.7136 for clay and 0.7062 for organic matter). The obtained RPD values for both models gave very satisfactory values of 1.9 for clay, i.e., 1.8 for organic matter.

Screening of Native Trichoderma Species for Nickel and Copper Bioremediation Potential Determined by FTIR and XRF.

Soil pollution with heavy metals is a serious threat to the environment. However, soils polluted with heavy metals are considered good sources of native metal-resistant Trichoderma strains. Trichoderma spp. are free-living fungi commonly isolated from different ecosystems, establishing endophytic associations with plants. They have important ecological and biotechnological roles due to their production of a wide range of secondary metabolites, thus regulating plant growth and development or inducing resistance to plant pathogens. In this work we used indigenous Trichoderma strains that were previously isolated from different soil types to determine their tolerance to increased copper and nickel concentrations as well as mechanisms of metal removal. The concentrations of bioavailable metal concentrations were determined after extraction with diethylene-triamine pentaacetate (DTPA)-extractable metals (Cd, Cr, Co, Cu, Pb, Mn, Ni, and Zn) from the soil samples by inductively coupled plasma-optical emission spectrometry (ICP-OES). Two indigenous T. harzianum strains were selected for copper tolerance, and three indigenous T. longibrachiatum strains were selected for nickel tolerance tests. Strains were isolated from the soils with the highest and among the lowest DTPA-extractable metal concentrations to determine whether the adaptation to different concentrations of metals affects the mechanisms of remediation. Mechanisms of metal removal were determined using Fourier-transform infrared spectroscopy (FTIR) and X-ray fluorescence spectroscopy (XRF), non-destructive methods characterized by high measurement speed with little or no need for sample preparation and very low costs. Increased DTPA-extractable metal content for nickel and copper was detected in the soil samples above the target value (TV), and for nickel above the soil remediation intervention values (SRIVs), for total metal concentrations which were previously determined. The SRIV is a threshold of metal concentrations indicating a serious soil contamination, thus confirming the need for soil remediation. The use of FTIR and XRF methods revealed that the presence of both biosorption and accumulation of metals in the Trichoderma cells, providing good bioremediation potential for Ni and Cu.

Synthesis, characterization and application of magnetic nanoparticles modified with Fe-Mn binary oxide for enhanced removal of As(III) and As(V).

Arsenic contamination of drinking water sources is a widespread global problem. Of the As species commonly found in groundwater, As(III) is generally more mobile and toxic than As(V). In this work, magnetic nanoparticles (MNp) modified with Fe-Mn binary oxide (MNp-FeMn) were synthesized in order to develop a low cost adsorbent with high removal efficiency for both arsenic species which can be readily separated from water using a magnetic field. MNp-FeMn were characterized using different techniques including SEM/EDS, XRD and BET analysis. Adsorption of As(III) and As(V) on MNp-FeMn was studied as a function of initial arsenic concentration, contact time, pH, and coexisting anions. The BET specific surface area of MNp-FeMn was 109 m2/g and maghemite (γ-Fe2O3) was the dominant precipitated phase. The adsorption rate of As(III) and As(V) on MNp-FeMn was controlled by surface diffusion. FTIR analysis confirms that surface complexation through ligand exchange was the main mechanism for As(III) and As(V) removal on MNp-FeMn, with As(III) conversion to As(V) occurring on the adsorbent surface. The maximal adsorption capacity qmax of MNp for As(III) (26 mg/g) was significantly improved after modification with Fe-Mn binary oxide (56 mg/g), while qmax for As(V) was 51 and 54 mg/g, respectively. PO43-, SiO32- and CO32- reduced As(III) and As(V) uptake at higher concentrations. MNp-FeMn can be easily regenerated and reused with only a slight reduction in adsorption capacity. The high oxidation and sorption capacity of MNp-FeMn, magnetic properties and reusability, suggest this material is a highly promising adsorbent for treatment of arsenic contaminated groundwater.