A novel visible-light-sensitive ZnVFeO₄ photocatalyst has been fabricated by the precipitation method at different pH values for the enhanced photocatalytic degradation of malachite green (MG) dye as a representative pollutant under visible light irradiation at neutral pH conditions. The structure and optical characteristics of the prepared photocatalysts were investigated by XRD, FTIR, N2 adsorption–desorption, TEM, diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) analyses. In addition, the photocatalytic activity of ZnVFeO₄ photocatalysts superior the efficiency to be more than that of the mono and bi-metal oxides of iron and iron zinc oxides, respectively. The best sample, ZnVFeO₄ at pH 3, significantly enhances the degradation rate under visible light to be 12.7 × 10⁻³ min⁻¹ and can retain a stable photodegradation efficiency of 90.1% after five cycles. The effect of the catalyst dose and the initial dye concentration on the photodegradation process were studied. This promising behavior under visible light may be attributed to the low bandgap and the decreased electron–hole recombination rate of the ZnVFeO₄ heterostructures. The scavenger experiment confirmed that the hydroxyl radicals induced the MG photodegradation process effectively. Hence, the ZnVFeO₄ is a reliable visible-light-responsive heterostructure photocatalyst with excellent potential for the photodegradation of organic pollutants in wastewater treatment.

Although environmental filtering and spatial structuring are commonly regarded as two key factors shaping community dynamics, their relative contribution remains unknown for numerous aquatic ecosystems, particularly highly dynamic floodplain lakes. This issue is here addressed by examining the seasonal metacommunity dynamics of freshwater fishes in Lake Dongting, a large subtropical lake of the middle Chang-Jiang basin in southern China. Physicochemical variables and fish assemblages were recorded at 20 sampling sites during the wet, normal, and dry seasons. Distance-based redundancy analysis and associated variation partitioning were used to examine the relative role of environmental variables and spatial factors in fish community assembly in each season. Analysis results demonstrated that the relative contribution of environmental filtering and spatial structuring varied depending on environmental features and the extent of hydrological connectivity in different seasons. Intensified physicochemical parameters in the dry season convinced the enhanced environmental filtering, whereas high hydrological connectivity in the wet season favored the stronger spatial process. Specifically, the community assembly processes were temporally dynamic; spatial structuring (or mass effects), resulting from excessively high dispersal rates, was dominant during the flooding season, and environmental filtering was stronger than spatial structuring (or dispersal limitation) during the non-flooding season. These findings highlight the importance of conserving local habitats of Lake Dongting during the dry and normal seasons, and maintaining of the flood pulse of the lake and its natural variability during the wet season. Apparently, the construction of a water-level regulation project at the Chenglingji Channel, the outlet watercourse of Lake Dongting, is not supported because it will change the flood pulse of this lake and thus impact habitat heterogeneity or variability.

High-strength concrete (HSC) is defined as concrete that meets a special combination of uniformity and performance requirements, which cannot be attained routinely via traditional constituents and normal mixing, placing, and curing procedures. It is a complex material since modeling its behavior is a difficult task. This paper intends to show the feasible applicability of optimized convolutional neural networks (CNN) for predicting the slump in HSC. The following are the parameters that given as the input for the prediction of slump: cement (kg/m³), slag (kg/m³), fly ash (kg/m³), water (kg/m³), super-plasticizer (kg/m³), coarse aggregate (kg/m³), and fine aggregate (kg/m³). In order to make the prediction more accurate, the design of CNN is assisted with optimization logic by making some fine-tuned filter size of the convolutional layer. For this optimization purpose, this work presents a new “hybrid” algorithm that incorporates the concept of sea lion optimization algorithm (SLnO) and dragonfly algorithm (DA) and is named as Levy updated-sea lion optimization algorithm (LU-SLnO). Finally, the performance of the proposed work is compared and proved over the state-of-the-art models with respect to error measure and convergence analysis.

Under the 1987 Great Lakes Water Quality Agreement, the lower Green Bay and Fox River estuary have been labeled as areas of concern due to the contamination of mercury and polychlorinated biphenyls (PCBs) from industrialization. These pollutants pose substantial health and environmental hazards for the Green Bay region. The PCBs reported in this region, including Aroclor 1242, are known to trigger carcinogenic responses in animals and mercury targets the central nervous system and vital organs. Furthermore, these compounds are extremely difficult to remove from the environment once introduced. Extensive remedial actions have been implemented including dredging sediments in the Lower Fox River from DePere to Green Bay. The purpose of this study is to assess the concentration and distribution of Aroclor 1242 and total mercury in the Green Bay region sediments and pore waters and to assess the impact of interventions and the natural rates of change previously found.

As a key input variable to many global climates, land surfaces and crop models, cropping intensity (CI) accurately assesses and predicts crops’ output, in view of the global decline in food production in recent years due to declining natural resources, urban expansion and declining quality of arable land. Hence, research on CI mapping can have a contribution to solve this problem. Unfortunately, existing remote sensing data for CI mapping research, including Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat images, are not adequate for obtaining CI information at higher spatial and temporal resolution. In this regard, we develop an algorithm to extract CI based on per-pixel physiognomy. To be specific, the algorithm is based on the Google Earth Engine (GEE) platform and constructs a high temporal (10 days) spatial (30 m) resolution dataset with the fusion of Landsat 7/8 and Sentinel-2 A/B image data and extracts CI information using a time series of peak discovery method, threshold method and phenological period feature extraction to obtain the 2018 Chinese Huai River Basin (HRB) CI map. Our results suggest that the overall accuracy (OA) of CI extraction in the HRB is 92.72%, with a kappa coefficient of 0.864. The single-season crop, double-season crop and three-season crop account for 41.6%, 57.7% and 0.7% of the total farmland area, respectively. Compared to existing CI identification and extraction methods, this approach achieves higher accuracy in the identification and extraction of CI information over a larger area.

Reference evapotranspiration ([Formula: see text]) is an important indicator for hydrometeorological change, which integrates atmospheric and surface conditions, and its downward trends have been reported in many regions over the past several decades. Cold regions constitute an important ecological barrier in China; however, few studies focus on change in [Formula: see text] in cold regions. Especially in the cold region of northeast China (CRNEC), as one of the national strategic grain bases, understanding spatial–temporal variations of [Formula: see text] is important for agriculture water management and ecological protection. This study selected the observations at 113 national meteorological stations located in CRNEC and evaluated the trends of [Formula: see text] and their driving factors from 1961 to 2017. Results indicate that annual [Formula: see text] increases from the northeast to the southwest of CRNEC and has an insignificant decreasing trend in the whole study period, in which 33 stations (29.2%) show significant decreasing trends and only 19 stations (16.8%) show significant increasing trends at the 95% confidence level. An abrupt change in [Formula: see text] data is detected from 1994. Reasons for this abrupt change in [Formula: see text] vary largely over the study areas. Analysis shows that wind speed and minimum air temperature are the two major factors that control the change of [Formula: see text] before 1994. It also shows that wind speed and actual vapor pressure are the two major controlling factors after 1994. We also found that [Formula: see text] shows a certain correlation with Pacific Decadal Oscillation and Western Pacific Index, but there is a significant correlation between meteorological factors and teleconnection factors related to [Formula: see text]. These findings will promote agricultural water management and improve water ecological protection in the CRNEC. We investigated changes in reference evapotranspiration relationships with atmospheric circulation and its attributions over the cold regions in northeast China during 1961 ~ 2017. The results indicate that the wind speed and minimum air temperature are the two major factors that control the change of ET0 before 1994, and wind speed and actual vapor pressure are the two major controlling factors after 1994. We also found that ET0 shows a certain correlation with Western Pacific Index in the whole period.

In this study, an enhanced coagulation-flocculant process incorporating magnetic powder was used to further treat the secondary effluent of domestic wastewater from a municipal wastewater treatment plant. The purpose of this work was to improve the discharged water quality to the surface water class IV standard of China. A novel approach using a combination of the response surface methodology and an artificial neural network (RSM-ANN) was used to optimize and predict the total phosphorus (TP) pollutant removal and turbidity. This work was first evaluated by RSM using the concentrations of coagulant, magnetic powder, and flocculant as the controllable operating variables to determine the optimal TP removal and turbidity. Next, an ANN model with a back-propagation algorithm was constructed from the RSM data along with the non-controllable variables, raw TP concentration, and raw water turbidity. Under the optimized experimental conditions (28.42 mg/L coagulant, 623 mg/L magnetic powder, and 0.18 mg/L flocculant), the TP and turbidity removal reached 88.79 ± 5.45% and 63.48 ± 9.60%, respectively, compared with 83.28% and 59.80%, predicted by the single RSM model, and 87.71 ± 5.74% and 64.62 ± 10.75%, predicted by the RSM-ANN model. The treated water were 0.17 ± 6.69% mg/L of TP and 2.46 ± 5.09% NTU of turbidity, respectively, which completely met the surface water class IV standard (TP < 0.3 mg/L; turbidity < 3 NTU). Therefore, this work demonstrated that the discharged water quality was completely improved using the magnetic coagulation process. In addition, the combined RSM-ANN approach could have potential application in municipal wastewater treatment plants.

The trend of economic decline for coal cities is a serious threat to the high-quality development of China’s economy, and how to improve the environmental total factor productivity (ETFP) has become an urgent issue. Based on the framework of data envelopment analysis (DEA), this paper estimates ETFP using the global Malmquist-Luenberger productivity index (GMLPI). We decompose GMLPI into environmental technical efficiency change (ETEC) and the best practice gap change (BPGC). Then, the difference-in-difference (DID) model combining propensity score matching (PSM) method is used to investigate the effect of the Sustainable Development Plan of National Resource-based Cities (2013–2020) (SDP) aiming to improve ETFP. The results indicate that (1) On average, the GMLPI and BPGC are rising, while the ETEC is decreasing in the observed sample period; the western regions have the biggest BPGC, while the eastern regions have the biggest ETEC; (2) The SDP significantly improves the GMLPI and BPGC but has little effect on the ETEC; Coal cities located in eastern and central regions have policy effect, while the western regions do not have. (3) The SDP affects ETFP through slowing down the economic growth rate and reducing population agglomeration, but promoting the optimization of industrial structure. Those findings have policy implications for improving ETFP and promoting the industrial upgrade of coal cities.

This research project aims at investigating the performance of hydroponic nutrient solutions as draw solutions for desalination using the fertilizer drawn forward osmosis (FDFO) process. Six different lettuce and leafy greens hydroponic nutrient stock solutions were prepared according to the literature and used in this study and tested on a bench-scale forward osmosis unit as draw solutions for the process. The feed solution for the process was deionized water mixed with NaCl in different concentrations, to represent different salinities of brackish groundwater. The draw efficiency of each solution was measured based on water flux, specific reverse solute flux, water recovery, and salt rejection. It was concluded that of the six tested nutrient solutions, the “Resh Florida, California” solution is the recommended solution to be used as draw solution for fertilizer drawn forward osmosis, due to its high performance in terms of water recovery (15.75%), flux (11 L/m²/h), salt rejection (92%), and SRSF (highest recorded SRSF for a specific ion (SO₄²⁻) was 7.3 g/L), as well as its low cost, relative to the other highly performing draw solution “Chekli” ($1.07/L vs. $3.73/L).

Biocides, which are found in nature as persistent pollutants, pose a great danger to the ecosystem. Methylisothiazolinone (MIT), a widely used biocide, reaches plants by mixing with water and soil. Vermicompost tea (VCT), which strengthens the plant defence mechanism and increases its growth and development, is a liquid fertiliser consisting of the cooperation of worms with microbes. In the present study, after applying 0.4 g/L (EC50/2), 0.8 g/L (EC50), and 1.6 g/L (EC50 × 2) MIT concentrations without and with VCT on forage pea (Pisum sativum), root lengths, mitotic index data, chromosome and nuclei abnormalities, and DNA damage level were determined. When VCT applied and non-applied groups were compared, it was found that, especially in the VCT applied group, they cope with the stress conditions created by MIT. In addition, positive effects were observed in root lengths, mitotic index data, and amount of cell nuclei abnormalities. In line with other study results, VCT reduces cellular damage by regulating the normal life cycle disrupted in the cell due to mutagens using the curative-regulatory feature.