The attempt of the current study is to find an eco-friendly method for managing the solid waste deposited in the landfill of used motor oil recovery factories through the fabrication of zeolite-based compounds. This toxic waste is originated from the application of natural bentonite, traditionally used as an effective adsorbent in the recovery process. The black waste was converted to zeolite structures through the fusion technique. Firstly, the collected powder was mixed with sodium hydroxide, and boehmite followed by the thermal treatment at different temperatures, 600–800 °C. Then, the obtained precursors were hydrothermally converted to zeolite A or hydroxysodalite. The effects of processing factors like alkalinity, boehmite, and sodium aluminate ratios (respect to solid waste mass), fusion temperature, and aging time on the structural characteristics, and cation exchange capacity (CEC) were studied in detail. In order to achieve a cation exchange capacity of about 190 mg g⁻¹, the alkali and boehmite ratios should be adjusted at 2.00 and 0.53, respectively. Based on the morphological observations, the fusion at 800 °C caused the formation of cubic particles with sharp edges. Besides, the hydrosodalite powder with the extended surface area, 77 m² g⁻¹, could be produced by fixing the boehmite, and sodium aluminate ratios at the levels of 0.13 and 0.40, respectively.

Monitoring water at high spatial and temporal resolutions is important for maintaining water quality because the cost of pollution remediation is often higher than the cost of early prevention or intervention. In recent decades, the availability and affordability of satellite images have regularly increased, thus supporting higher-frequency and lower-cost alternative methods for monitoring water quality. The core step in satellite remote sensing detection is inverse modeling, which is used to calibrate model parameters and enhance the similarity between the model and the real system being simulated. The reflectance values measured at water quality stations are extracted from atmosphere-corrected satellite imagery for analysis. However, various external environmental, hydrological, and meteorological factors affect the evaluation results, and the results obtained with different parameters can vary. This literature review shows that nonpoint-source pollution caused by stormwater runoff can also be monitored using satellite imagery. To improve the accuracy of satellite-based water quality prediction, the temporal resolution of field measurements can be increased, thus better considering the influence of seasonality. Then, the atmospheric correction module can be improved by using available atmospheric water content products. Moreover, because water surface ripples affect reflectance, wind speed and direction should be considered when comparing water quality scenes.

Cyphenothrin, one of the synthetic pyrethroids, developed as an alternative to organophosphorus and carbamate pesticides. It is used in veterinary medicine and household application against insects. Due to the contamination of the aquatic ecosystems, non-target aquatic organisms are affected. The current study aimed to evaluate the cyphenothrin effects on in vitro and in vivo models of freshwater mussels Unio delicatus Lea, 1863. While antioxidant enzyme (glutathione) was measured in both models, the total hemocyte counts were only detected in vivo models after exposure to cyphenothrin (1 and 10 μg/L) for 24-h and 48-h exposure times. A decrease in total hemocyte count occurred depending on the dose and duration (p < 0.001). In both in vitro and in vivo models of gill and digestive gland tissues, higher glutathione levels were obtained at a dose of 10 μg/L compared to the control groups in both exposure times (p < 0.001). The results of the study suggest that the antioxidant parameters could represent biomarkers to evaluate the effects of pollutants on in vitro and in vivo models of freshwater mussels.

Understanding the relationship among ecosystem services (ESs) is essential to promote ESs management and sustainable development. The relationship between ESs is mutual and can be expressed in terms of trade-offs, synergy, and constraints. The paper selected the InVEST model to assess the water yield (WY), soil conservation (SC), food production (FP), net primary productivity (NPP), and habitat quality (HQ) of the Yangtze River Economic Belt (YREB) and used the constraint line method to analyze the relationship of paired ecological services at three scales: landscape, watershed, and land category. The following conclusions were drawn: (1) during the study period, the spatial changes of the five ecological services in the YREB did not change much, but the spatial distribution of the ecological services was different. (2) From 2000 to 2015, the constraint line of YREB paired ecological services had a high degree of fit. Under the three levels of landscape, watershed, and land category, the YREB has a variety of constraint types, including negative lines, logarithms, paraboloids, humped shapes, and rectangles. (3) At the three levels, the constraint lines between FP, NPP, WY, and SC and HQ were stable rectangular constraints; WY-SC was hump shaped, FP-NPP, FP-SC, FP-WY, NPP-WY, and NPP-SC changed with the scale, showing different spatial scale changes. (4) The paired ESs directly determined the ecological constraint curve but under the combined effect of other factors, which would affect or change the constraint line. We discussed the effects of weather, topography, and economy on the constraint relationship, and found that all have different degrees of influence.

The growing interest of policy-makers, environmental stakeholders, and academics in rural domestic waste treatment has made it a recent focus of research in the field of rural human settlements. Many studies have been conducted to understand the related factors; however, their results are inconsistent. Therefore, different from previous studies, the study systematically analyzed and summarized empirical studies on rural domestic waste treatment and explored the key factors that fostered and impeded it. It also examined the reasons for differences in research level and trends in key factors over time. A random-effects meta-analysis of 24 studies revealed that education, political status, perceived value, behavioral attitude, subjective norm, garbage collection facilities and services, environmental knowledge and propaganda, and government policy and regulation had a significant positive correlation with rural domestic waste treatment; perceived value had the highest impact, followed by behavioral attitude. All of the variables had significant heterogeneity. Some of the heterogeneity can be explained by differences in research methods, sample size, and variable measurement methods. An increasing trend was observed in the effects of perceived value, behavioral attitude, and subjective norm. Finally, based on these results, the study provided suggestions on policy and academic aspects.

The disposal of dye-contaminated wastewater is a major concern around the world for which a variety of techniques are used for its treatment. The photocatalytic treatment of dye-contaminated wastewater is one of the treatment methods. Semiconductor-assisted photocatalytic treatment of dye-contaminated wastewater has gained pronounced attention recently. This review outlines the recent advancements in the photocatalytic treatment of dye-contaminated wastewater. The photocatalytic degradation of dyes follows three types of mechanisms: (1) dye sensitization through charge injection, (2) indirect dye degradation through oxidation/reduction, and (3) direct photolysis of dye. Several experimental parameters like initial concentration of dyes, pH, and catalyst dosage significantly affect the photocatalytic degradation of dyes. The photocatalytic materials can be categorized into three generations. The single-component (e.g., ZnO, TiO₂) and multiple component semiconductor metal oxides (e.g., ZnO–TiO₂, Bi₂O₃–ZnO) are categorized as first-generation and second-generation photocatalysts, respectively. The photocatalysts dispersed on an inert solid substrate (e.g., Ag–Al₂O₃, ZnO–C) are classified as third-generation photocatalysts. Finally, we reviewed the challenges that affect the photocatalytic degradation of dyes.

The projected increase of the global textile industry to USD1002.84 billion in 2027 indicates a simultaneous increase in water pollution due to textile dye-rich voluminous effluents highlighting the requirement of source clean-up. This review analyzes the colossal amount of literature on lab-scale nanoremediation technologies involving iron-based nanoparticles and the mechanistic aspects. However, not many studies are in place with regard to execution because there are several bottlenecks in the scale-up of the technology. This review attempts to identify the limitations of scale-up by focusing on each step of nanoremediation from synthesis of iron-based nanoparticles to their applications. The most prominent appears to be the low economic viability of physico-chemical synthesis of nanoparticles, lack of appropriate toxicity studies of iron-based nanoparticles, and dearth of studies on field applications. It is recommended that above studies should be made not only on lab scale but also on field samples preferably utilizing microbial products based green synthesized iron-based nanoparticles and conducting toxicity studies. Besides, immobilization of the nanoparticles on renewable material greatly enhances the sustainability and economic value of the process. Furthermore, since the chemical composition of dye-rich effluents varies among industries, effluent specific optimization of process parameters and kinetics thereof is also a major prerequisite for scale-up. The value of this review lies in the fact that it brings, for the first time, a comprehensive and critical systematization of various aspects needing attention in order to scale-up such effective nanoremediation processes.

To establish the carbon emission trading scheme and achieve the carbon emission reduction goals in China, it is critical to allocate the carbon emission allowance (CEA). Using the entropy method and the modified fixed cost allocation model (MFCAM), we calculated the CEA and the carbon emission intensity (CEI) reduction targets of 30 Chinese provinces in 2030, from four principles (equity-efficiency-feasibility-sustainability) and three dimensions (economy-society-environment). The results are shown as follows. First, China’s total carbon emissions in 2030 calculated in this paper are 17567.9 Mt. Second, on the whole, CEA in China’s southeast half of the Hu line is higher than that in the northwest half. Eastern China has a larger final CEA than western China and central China. Third, Henan, Guangdong, Shandong, and Jiangsu are the four provinces with the most CEA, while Gansu, Qinghai, Ningxia, and Hainan are the four regions with the least carbon allowances. Fourth, the regions of Shanxi, Shaanxi, Xinjiang, Ningxia, Inner Mongolia, Guizhou, and Anhui will take on greater responsibility for carbon reduction in the future. On the contrary, the zones of Tianjin, Qinghai, Guangxi, Jilin, Yunnan, and Beijing will be able to sell CEA in the future. Fifth, provinces are divided into three categories from the perspective of CEI reduction. Finally, we put forward relevant policy recommendations based on the conclusions.

Agricultural activities have become a major source of groundwater nitrate contamination. In this context, this study aims to analyse nitrate concentrations in a shallow aquifer of Mahdia-Kssour Essef in central-eastern Tunisia, identify the assignable sources, and predict the future levels using artificial neural network (ANN) and autoregressive integrated moving average (ARIMA) models. The results showed that nitrate concentrations measured in 21 pumping wells across the plain ranged from 17 to 521 mg L⁻¹. A total of 67% of the monitoring points greatly exceed the standard guideline value of 50 mg L⁻¹. The main relevant anthropogenic and natural factors, such as soil texture, land use, fertilizers application rates, livestock waste disposal, and groundwater table, are positively correlated with groundwater nitrate concentration. The ANN model showed good fitting between measured and simulated results with coefficient of determination (R²), root-mean-square error (RMSE), and mean absolute error (MAE) values of 0.88, 53.95, and 39.64, respectively. The ARIMA applied on annual average nitrate concentrations from 1998 to 2017 revealed that the best fitted model (p, d, q) is (1, 2, 1). The R² value is approximately 0.36, and the Theil inequality coefficient and bias proportion values are small and close to zero. These results proved the ARIMA model’s adequacy in forecasting annual average nitrate concentrations of 116 mg L⁻¹ in 2025. These findings may be useful in making groundwater management decisions, particularly in rural and semi-arid areas, and the proposed ARIMA model could be used as a managed tool to monitor and reduce the nitrate intrusion into groundwater.

Rapid urbanization is often accompanied by the irrational utilization of natural resources and environmental degradation. Ecological security pattern (ESP) is an effective way for rational allocation of resources, which is conducive to achieving sustainable development. Taking the central urban area Chongqing municipality as the study area, ecological sources were identified by integrating ecosystem services and landscape connectivity. Combining natural and anthropogenic factors, a resistance surface was constructed and modified, and four ecological function zones were determined. Ecological corridors were extracted and prioritized by Linkage Mapper and the gravity model, and ecological nodes were also obtained. A network connectivity assessment was performed to compare the connectivity of ESPs before and after optimization. The results showed that ESPs included 2453.72 km² of ecological sources, 189 ecological corridors, 69 ecological nodes and 4 ecological function zones. The ecological sources primarily consisted of forestland, cultivated land and water bodies in Jinyun, Zhongliang, Tongluo, Mingyue and other mountainous areas, with the maximum distribution index value at the tenth level of the terrain niche index gradient. The Yangtze River and Jialing River were also the most important ecological sources. Ecological corridors were mainly dominated by forestland and cultivated land. Ecological nodes were concentrated in Yubei, Banan and Jiulongpo districts. The optimized ESPs had higher network connectivity and closure, with a more uniform distribution of ecological corridors, and included 2461.95 km² of ecological sources, 218 ecological corridors and 72 ecological nodes. Finally, recommendations for sustainable development were proposed. This study provides a theoretical reference for decision-making related to ecological protection and urban planning.