The visible light responsive graphitic nitride (g-C₃N₄) mediated photocatalysis has drawn extensive attention in water treatment field. Carbon doping could improve the photocatalytic activity of g-C₃N₄ in promoting charge separation efficiency, visible-light utilization, etc. In this paper, the g-C₃N₄ (as MC) was modified by barbituric acid (as MCB₀.₀₇) and further treated by reduced graphene oxide (rGO) (as n%GCN) and then applied to inactivate ofloxacin-resistant bacteria (OFLA) under light irradiation at UVA-visible wavelength. The results showed that the n%GCN presented strong photocatalytic activity when the GO mass ratio was 7.5% (as 7.5%GCN). The inactivation efficiencies of OFLA by MC, MCB₀.₀₇, and 7.5%GCN were 5.77 log, 8.48 log, and 8.25 log, respectively, under UVA-visible wavelength (λ > 305 nm), compared to 4.83 log, 5.56 log, and 6.08 log, respectively, within 16 h under visible wavelength (λ > 400 nm). The rGO-doping obviously improved the inactivation efficiency of MCB₀.₀₇ on OFLA under visible wavelength. Furthermore, the photoreactivation and dark repair phenomena of OFLA were examined after MC, MCB₀.₀₇, and 7.5%GCN treatment, respectively, and it was found that all approaches led to permanent damage to OFLA of which the regrowth was not observed after 24–48 h. Based on the quenching test, reactive oxygen species of O₂⁻• and hole (h⁺) exhibited dominant roles in the photocatalytic inactivation of OFLA, which may result in oxidative stress and damage to the cell membrane. This study could shed light on the inactivation of OFLA under visible light radiation by rGO modified g-C₃N₄.

Since the beginning of the last century, there has been a high demand for renewable energy sources due to the decrease in fossil-based energy sources and the intense pollution of these energy types. Bioenergy recovery from sludge biomass is an attractive renewable energy source. Electrochemical treatment is one of the investigated physicochemical methods to increase methane production from waste activated sludge (WAS) biomass. It can be used as a new and efficient pretreatment for the hydrolysis of WAS. In this study, electrochemical technology with platinum/titanium (Pt/Ti) mesh electrodes was first applied for WAS before aerobic digestion. The effects of various operating conditions such as current intensity and initial pH of the sludge were investigated. The study showed that the amount of soluble COD of WAS increased with increasing current intensity. In addition, the results obtained showed that pH values higher or lower than the pH value of WAS (6.2) are favorable for the degradation of organic substances. An approximately 358% increase in COD solubility was detected at the end of the reaction time of 30 min at a current intensity of 25 A. The conducted study showed that electrochemical pretreatment is feasible and that increasing the methane production rate for anaerobic digester-containing wastewater treatment plants in Turkey has the potential to provide environmental and economic benefits.

In this study, the eutrophication levels and nitrogen and phosphorus carrying capacities of Lake Changhu in Jingzhou, Hubei Province, China, were measured using the trophic level index (TLI) and Dillon model for the first time. The measurements were taken before (2013 and 2015) and after (2017 and 2018) the removal of pen aquaculture from the lake. The lake was divided into three districts: Lake Haizihu, Mahongtai Channel, and Lake Dahu. The results showed total nitrogen (TN), chemical oxygen demand (COD), chlorophyll a (Chl-a), and total suspended solid values were significantly higher in 2017 than in the other years. The Lake Haizihu district was predicted to be more seriously polluted than the other districts. In the sediment, the organic matter, STN (TN in sediment) and STP (TP in sediment) contents increased from 2013 to 2018. The mean TLI values ranged from 62.99 to 78.93 in the studied years, and the eutrophication level was highest in 2017. According to the Dillon model, when the target water quality was level III (GB 3838-2002, Ministry of Environmental Protection of China, 2002), the remaining TN and TP loading capacities were −1470.72 t/a and −182.74 t/a, respectively, in 2015, and 320.03 t/a and −111.14 t/a, respectively, in 2018. Our results provide valuable and integrated information about the water conditions of Lake Changhu, thus laying a foundation for the theoretical study of water eutrophication process in lakes and paving the way for informed decision-making for managing water environments to ensure the safety of ecology.

Manganese released from the piled manganese ore wastes is a great threat to the local ecosystem and human health. The mechanism and dynamic characteristics of manganese release from the manganese ore wastes were studied based on the static and dynamic experiments. The concentration of manganese in the leaching solution under the intensive state is twice that resulted from the static state; the manganese release from the waste rock increased with the increase of the solid-liquid ratio and reached 922.3 mg/L when the solid-liquid ratio was 1:5. When the particle size of waste rock was less than 180 μm, the release amount of manganese was the largest and reached 491.3 mg/L. When the pH was 7 and the rainfall intensity was 80 mL/h, the increase of leaching time contributed to the rapidly decreased amount of manganese released, and the leaching process reached equilibrium gradually. The cumulative release of manganese increased with the increase of rainfall duration. In the dynamic leaching process, the change of pH and EC of the leachate had nothing to do with the initial pH of leaching agent but has a close relationship with the hydrolysis of minerals in waste. According to the experimental results, it was found that the double constant equation model fitted the kinetic process of release process better. The purpose of this study was to provide a scientific basis for the assessment and control of manganese pollution in soil and groundwater in manganese mining area.

Mobility and toxicity of heavy metal contamination in the environment are highly dependent on its bioavailability. Most of previous studies focused on total heavy metal contents and their influence on microbial community in soils and sediments. Little were concerned about bioavailable fractions. In the current study, soil and sediment samples were collected near an abandoned realgar mine in Shimen County, China. Bioavailable heavy metals including Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, and Pb in the samples were extracted using three-step sequential extraction method. Interactions among physicochemical parameters, total and bioavailable heavy metals, and microbial community in the collected samples were investigated. The study area has been severely contaminated by As with a concentration up to 2158 mg·kg⁻¹ detected. The result of principal component analysis showed that the abundance of operational taxonomic units (OTUs) in the soils were obviously different from those in the sediments. In the soil samples, pH made a dominant contribution on the OTU abundance of microbial community. Correlation analyses revealed that the alpha diversity indices and microbial taxon were most correlated with bioavailable fractions of heavy metals in all the samples. That means bioavailable heavy metals rather than total heavy metals or physicochemical parameters played a more important role on richness and diversity of microbial community. Little connections were observed between microbial community and As no matter total concentration or bioavailable fraction. However, bioavailable Fe and Mn were recognized as the major driving force shaping the taxonomic structure of microbial community due to their relatively high concentrations and high affinity to other heavy metal contamination in soils and sediments.

An accurate NOₓ concentration prediction model plays an important role in low NOₓ emission control in power stations. Predicting NOₓ in advance is of great significance in satisfying stringent environmental policies. This study aims to accurately predict the NOₓ emission concentration at the outlet of boilers on different operating conditions to support the DeNOₓ procedure. Through mutual information analysis, suitable features are selected to build models. Long short-term memory (LSTM) models are utilized to predict NOₓ concentration at the boiler’s outlet from selected input features and exhibit power in fitting multivariable coupling, nonlinear, and large time-delay systems. Moreover, a composite LSTM model composed of models on different operating conditions, like steady-state and transient-state condition, is prosed. Results of one whole day of typical operating data show that the accuracy of the NOₓ concentration and fluctuation trend prediction based on this composite model is superior to that using a single LSTM model and other non-time-sequence models. The root mean square error (RMSE) and R² of the composite LSTM model are 3.53 mg/m³ and 0.89, respectively, which are better than those of a single LSTM (i.e., 5.50 mg/m³ and 0.78, respectively).

Ferric hydrate has been extensively applied for the removal of various types of pollutants from wastewater because of its low cost and high efficiency. However, its wide-scale application has been greatly restricted by high-dose and low-adsorption capacity. Therefore, a novel Ca-doped ferrihydrite adsorbent has been synthesized and used for the enhanced removal of fluoride from wastewater in the presence of other co-existing ions. At 5 mg/L initial fluoride concentration and pH 5, the removal efficiency of fluoride approached to 97.5% and remained stable. Similarly, with the increase of dose from 100 to 300 mg/L, the fluoride removal linearly increased to 98% and remained plateau at neutral pH. Also, the presence of co-existing ions such as NO₃⁻, SO₄²⁻, Cl⁻, and natural organic matter has not significantly influenced the removal performance of the adsorbent. Fluoride removal best fit the pseudo-second-order reaction kinetics and Langmuir isotherm model. The prepared adsorbent exhibited a maximum adsorption capacity of 53.21 mg/g for fluoride uptake from water. The SEM-EDX confirmed the doping of Ca onto the ferrihydrite where the elemental peaks of Ca and Fe emerged at the energy value of about 3.6 Kev and 7.1 Kev respectively in EDX analysis. In addition, SEM results of Ca-doped ferrihydrite adsorbent illustrated that a large microplates type of products was acquired after synthesis. The regeneration results confirmed that adsorbent could retain their original adsorption capacity after five regeneration cycles. The current study suggested that Ca-doped ferrihydrite has the application potential for the enhanced adsorption of fluoride from the water phase.

Nursery runoff may contain pesticide residues, which, if released off-site, could impair surrounding ecosystems. As a solution, nursery growers can retain runoff water on-site and recycle retained water to irrigate plants. However, concerns related to potential phytotoxicity caused by residual pesticides in recycled water can discourage growers from recycling water. To evaluate plants irrigated with recycled water, we conducted a 3-year field study simulating a commercial nursery growing practice. Irrigation treatments were applied to six ornamental taxa grown in a nursery production bed. Irrigation treatments were raw groundwater from the on-site well (control), water recycled from a separate nursery bed containing plants that were treated with nine pesticides regularly over the growing seasons, and recycled water from the nursery bed that had been remediated using heat-expanded shale aggregates and woodchip bioreactors. Plants receiving recycled water (runoff water with and without remediation) did not produce pesticide-related visual injury. However, result for growth index, chlorophyll SPAD index, dark-adapted fluorescence, and shoot biomass were irregular among raw groundwater and recycled water; for most instances, pesticides in recycled water did not reduce any of those parameters. Net photosynthesis and light-adapted fluorescence were similar for raw groundwater and recycled water. Results from this study demonstrate the possibility of using recycled water for irrigation of woody ornamental shrubs.

Present study deals with the efficacy of nanoencapsulated Homalomena aromatica essential oil (HAEO) as a potent green preservative against toxigenic Aspergillus flavus strain (AF-LHP-NS 7), storage fungi, AFB₁, and free radical-mediated deterioration of stored spices. GC–MS analysis revealed linalool (68.51%) as the major component of HAEO. HAEO was encapsulated into chitosan nanomatrix (CS-HAEO-Ne) and characterized through SEM, FTIR, and XRD. CS-HAEO-Ne completely inhibited A. flavus growth and AFB₁ biosynthesis at 1.25 μL/mL and 1.0 μL/mL, respectively in comparison to unencapsulated HAEO (1.75 μL/mL and 1.25 μL/mL, respectively). CS-HAEO-Ne caused significant reduction in ergosterol content in treated A. flavus and provoked leakage of cellular ions (Ca⁺², Mg⁺², and K⁺) as well as 260 nm and 280 nm absorbing materials. Depletion of methylglyoxal level in treated A. flavus cells illustrated the novel antiaflatoxigenic efficacy of CS-HAEO-Ne. CS-HAEO-Ne exhibited superior antioxidant efficacy (IC₅₀ ₍DPPH₎ = 4.5 μL/mL) over unencapsulated HAEO (IC₅₀ ₍DPPH₎ = 15.9 μL/mL) and phenolic content. CS-HAEO-Ne depicted excellent in situ efficacy by inhibiting fungal infestation, AFB₁ contamination, lipid peroxidation, and mineral loss with acceptable sensorial profile. Moreover, broad safety paradigm (LD₅₀ value = 7150.11 mg/kg) of CS-HAEO-Ne also suggests its application as novel green preservative to enhance shelf life of stored spices.

Numerical oil spill models, which predict the transport and behavior of oil spills, are an essential tool for risk assessment and clean-up during an actual accident. The existing numerical oil spill models are mainly applied to large-scale oil spills, while few models on small-scale oil spills exist. Therefore, this study focuses on the prediction model of small-scale oil spills. Oil diffusion experiments in seawater using different oil types, including heavy oil, light oil, and gasoline, at different addition amounts under various kinds of wind were carried out, and these diffusion processes were recorded by a camera. The experimental images were processed to obtain the spread oil film area. The oil film edge processing based on genetic algorithm (GA) and back propagation artificial neural network optimized by a particle swarm optimization (PSO-BP) is proposed. Numerical prediction models were then constructed using the BP artificial neural network, the genetic algorithm-optimized back propagation neural network (GA-BP), and the PSO-BP. Among the three methods, the PSO-BP has the fastest convergence speed and the highest stability, which can usually achieve the goal. The PSO-BP reduces the possibility of the BP-ANN and the GA-BP falling into a local optimum instead of reaching global optimization. The prediction performance evaluation data are R² = 1 and MSE = 3.58e⁻⁹ – 8.87e⁻⁸. Results show that the GA and the PSO-BP provide a new approach to small-scale oil spill prediction.