The analyzed sediments were taken from the man-made reservoirs (Velka Richnava, Rozgrund and Vindsachta) located in an area intensively mined for polymetallic ores since the end of the eleventh century (Banska Stiavnica region, Central Europe). The aims of this study were to determine the radioactivity of natural (²²⁶Ra, ²²⁸Th, ²¹⁰Pb) and artificial (¹³⁷Cs and ²⁴¹Am) radionuclides, compare the radionuclides’ distribution, and indicate the correlation of radioisotopes and their origin related to sediment properties. Two analytical techniques were used. ²²⁸Th, ²²⁶Ra, ²⁴¹Am, and ¹³⁷Cs were measured by means of gamma spectrometry and ²¹⁰Pb was determined by its daughter radionuclide ²¹⁰Po using alpha spectrometry. The results showed that the highest mean level of ²²⁶Ra (42.6 Bq·kg⁻¹), ²²⁸Th (49.7 Bq·kg⁻¹) and ²¹⁰Pb (75.2 Bq·kg⁻¹) was in the sediments collected from Rozgrund. The radioactivity of ¹³⁷Cs and ²⁴¹Am were present at a higher level in the layer related to Chernobyl (1986) accident and nuclear weapon test (1950/1960). The distribution of natural radionuclides was quite similar in all reservoirs. Chemometric analysis confirmed the radionuclides’ origin and correlation between the analyzed parameters.

Neural network models have been used to predict chlorophyll-a concentration dynamics. However, as model generalization ability decreases, (i) the performance of the models gradually decreases over time; (ii) the accuracy and performance of the models need to be improved. In this study, Transfer learning (TL) is employed to optimize neural network models (including feedforward neural networks (FNN), recurrent neural networks (RNN) and long short-term memory (LTSM)) and overcome these problems. Models using TL are able to reduce the influence of mutable data distribution and enhance generalization ability. Thus, it can improve the accuracy of prediction and maintain high performance in long-term applications. Also, TL is compared with parameter norm penalties (PNP) and dropout—two other methods used to improve model generalization ability. In general, TL has a better prediction effect than PNP and dropout. All the models, including FNN with different architectures, RNN and LSTM, as well as models optimized by PNP, dropout, and TL, are applied to an estuary reservoir in eastern China to predict chlorophyll-a dynamics at 5-min intervals. According to the results of this study, (i) models with TL produce the best prediction results; (ii) the original models and the models with PNP and dropout lose their ability to predict within 3 months, while TL models retain a high prediction accuracy.

Metal pollution in urban soils due to smelting and electroplating has become a severe problem in China. In this study, the concentration, chemical fraction, and leaching behavior of typical metals (Cu, Zn, Cd, and Pb) in soil samples from ten metallurgical sites were studied. The results show that some of the soils were polluted with Cu and most were heavily polluted with multiple metals, especially Zn, Cd, and Pb. The average concentration of Cu, Zn, Cd, and Pb was 498, 4145, 89, and 5091 mg/kg, respectively. Chemical fractionation revealed that Cu, Zn, Cd, and Pb were mainly present in the acid-soluble fraction in polluted soils, but predominated in the residual fraction in unpolluted soils, demonstrating that allogenic metals in the soils were mostly present in the more labile fractions. Toxicity characteristic leaching procedure results were in agreement with the chemical fractionation study, indicating that the higher the total metal content, the higher the leachability, mobility, bioavailability, and potential toxicity to the environment, especially groundwater. Use of chemical fractionation results instead of total metal concentrations would provide better insight into the distribution and binding forms of metals for better assessment of their mobility and bioavailability. The study would provide much more important information for developing better remediation strategies for contaminated sites.

Information and communications technology (ICT) has developed economies and the way of energy consuming through the access, analysis, planning, and management of information. Such innovation, hence, explains the important direct effects on the environment and carbon dioxide (CO₂) emissions in a region or causes the spillover effects on other regions. This research examines the relationship between ICT and CO₂ emissions to have both within-region effects and spillover effects on other regions. In this way, ICT and the square of ICT were combined into the environmental Kuznets curve to specify the direct, spatial spillover, and total effects of ICT on CO₂ emissions. The dynamic spatial Durbin model was used to estimate the effects of ICT on the provinces of Iran for a period of 2001 to 2015. The results showed that the spatial spillover effects of ICT on CO₂ emissions have an inverted U-shaped relationship in short and long run. This findings show that an increase in the ICT in a province first causes to increase and then decrease the CO₂ emissions in other provinces.

Agricultural watersheds are a crucial contributor of terrestrial dissolved organic matter (DOM) for the adjacent aquatic environment. Recently, ecological engineering of the buffer zone such as a rice-paddy field was established to reduce the export of nutrients and contaminants from a small agricultural watershed. However, the potential of the rice-paddy field to reduce the terrestrial signature of DOM is unclear. Therefore, two small agricultural sub-catchments (i.e., sub-1 and sub-2) with different land uses and hill slope angles in the Three Gorges Reservoir (TGR) area of China were studied from 2014 to 2015. The results showed that the terrestrial DOM signals are indicated by optical indices (SUVA₂₅₄, SR, fluorescence index) in the steeper and more forest covered, but rice-paddy field buffered sub-catchment (i.e., sub-2) decreased significantly, as compared to the reference sub-catchment (i.e., sub-1). Regardless of seasonal variations, the rice-paddy field retained a buffering role to reduce the terrestrial property of DOM and the highest capacity was observed during the rice-growth period. However, during storm events, the differences of DOM properties for two sub-catchments were not significant, because the buffer system was weakened. Finally, environmental implications of the role of such a buffer zone in the TGR areas are discussed. These results demonstrate that rice-paddy fields are successful in mitigating the terrestrial property of exported DOM, but the weaker performance during storm events still needs to be considered.

Curcumin (Cur) effects on renal injury induced by zinc oxide nanoparticles (NZnO) in rats were investigated. NZnO at a dose of 50 mg/kg for 14 days was administered to rats as intoxicated group. In protection group, Cur at a dose of 200 mg/kg was administered for 7 days prior to NZnO treatment and followed by concomitant administration of NZnO for 14 days. Plasma concentrations of uric acid, creatinine (Cr), and blood urea nitrogen (BUN) were detected to evaluate renal injury. Malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) levels were determined for evaluation oxidative stress. TUNEL staining and histological changes were also performed. Administration of NZnO caused a significant elevation in the uric acid, Cr, and BUN levels. Oxidative stress was increased in the kidney by NZnO through enhancing MDA contents and reducing activities of SOD and GPx enzymes. According to histological examinations, treatment with NZnO caused proximal tubule damages, which was accompanied by the accumulation of red blood cells, infiltration of inflammatory cells, and reducing glomerular diameters. Significant increase was observed in the apoptotic index of the renal tubules in NZnO-treated rats. In present work, pretreatment of Cur reduced the histological changes, decreased biomarker levels, attenuated apoptotic index, and ameliorated oxidative stress by decreasing the MDA contents and increasing the activities of SOD and GPx enzymes. These findings indicate that Cur effectively protects against NZnO-induced nephrotoxicity in the rats.

Highly porous biochar (BC) structures have been prepared from inexpensive biomasses like rice straw, bamboo, sugarcane waste, and corn cob via a slow pyrolysis technique in nitrogenous atmosphere. A surface engineering technique has been applied to enhance the surface-to-volume ratio of each biochar sample and finally compared its characteristics through standard surface and elemental characterization techniques, viz. CHN (carbon, hydrogen, and nitrogen), FTIR (Fourier transform infrared spectroscopy), BET (Brunauer–Emmett–Teller), and SEM (scanning electron microscopy). All the biochar samples were observed to be highly carbonized and aromatized. Exfoliated structures were found to contain more elemental carbon (34.14–77.32%) than its native form (30.92–74.46%). Aromatic hydrocarbon, aromatic C=C, aromatics, aliphatic C–O, aliphatic hydrocarbon, and H-bonded OH groups were found to predominate in the surface of biochar structures independent of their precursor composition and extent of exfoliation. SEM micrographic images clearly ensured about the unoriented sheets like the morphology of different biochar samples. Although no significant structural difference was found to exist depending on their precursor compositions, quantitative enhancement of porosity was found to be observed after exfoliation. Both native (240.65 m²/g) and exfoliated (712.89 m²/g) biochars derived from sugarcane wastes were observed to have a maximum surface area in comparison to the biochars derived from rice straw (native, 22.08 m²/g; exfoliated, 29.92 m²/g), bamboo (native, 42.08 m²/g; exfoliated, 248.38 m²/g), and corn cob (native, 136.62 m²/g; exfoliated, 221.71 m²/g). Exfoliated biochars were found to be consistently more potent in comparison to its native form as per our comparative characterizations performed so far.

Based on field survey data of 366 traditional households (THs) and 364 family farms (FFs) from Huang-Huai-Hai Plain, a discrete-time cloglog model for parameter estimation was constructed to reveal factors that affect the two types of farms’ duration from the awareness to the adoption of green control techniques (GCTs). Differences in the influencing factors affecting the duration of the two types of farmers were also discussed. The research results are as follows. First, the duration from awareness to adoption of GCTs is significantly shorter in FFs than that in THs. Second, a higher degree of education, risk preference, family financial status, perceived ease of use and usefulness of the technique, and extension of media and supervision of agricultural technique extension departments of local governments significantly reduce the duration from awareness to adoption of GCTs by THs and FFs, whereas a male head of household prolongs the duration. Third, the age, farm size, and number of laborers exert different impacts on the duration from awareness to adoption of GCTs by THs and FFs.

This study reports the preparation of highly dispersed nanoscale zerovalent iron (nZVI) with core-shell structure decorated onto graphene nanosheets (Gr-NS) to form nZVI-Gr-NS composite. Meanwhile, its excellent performance for concentrated Zn(II) wastewater treatment is also studied. The adsorption of Zn(II) onto nZVI-Gr-NS is well simulated by the pseudo-second-order model, which indicates the adsorption is the rate-controlling step. Moreover, the adsorption isotherms of Zn(II) on the nZVI-Gr-NS can fit well with the Langmuir model. The negative thermodynamic parameters (△GƟ, △HƟ, △SƟ) calculated from the temperature-dependent isotherms indicate that the sorption reaction of Zn(II) is an exothermic and spontaneous process. The high saturation magnetization (37.4 emu g⁻¹) of the nZVI-Gr-NS makes separation of nZVI-Gr-NS-bound Zn(II) easily and quickly from aqueous solution. Most importantly, nZVI-Gr-NS composites not only remove Zn(II) but also spontaneously remove As, Se, and Cu ions from real smelting wastewater samples. This study provides a good solution for heavy metal removal in real wastewater.

High concentration of fluorine (F) in agricultural soils has got significant attention considering its impacts on human health, but little information was available about F distribution in farmland soil profiles around phosphorous chemical industry factories. In present study, farmland soil profiles and relevant medium samples were collected from farmlands around a main phosphorous chemical base in southwest China. At 0–100-cm profiles, concentrations of soil total F (Ft, 400.9–1612.0 mg kg⁻¹) and water soluble F (Fw, 3.4–26.0 mg kg⁻¹) decreased with profile depth in industrial areas. Industrial activities enhanced F concentration in soil mainly at 0–40-cm profiles. No disparity for both Ft and Fw distributions in paddy-dry land rotation field and dry land indicates short-term land utilization could not affect the F distribution in soil profiles. Correlation analysis showed soil organic matter and wind direction were important factors influencing the distribution of F in soil profiles. The shutdown of factory and government control of industrial emissions effectively decreased the ambient air F (Fa) concentrations in industrial areas. In where Fa and dustfall F concentrations were high, high soil Ft, Fw, and crop edible part F concentrations were found.