Prediction of water quality is a critical aspect of water pollution control and prevention. The trend of water quality can be predicted using historical data collected from water quality monitoring and management of water environment. The present study aims to develop a long short-term memory (LSTM) network and its attention-based (AT-LSTM) model to achieve the prediction of water quality in the Burnett River of Australia. The models developed in this study introduced an attention mechanism after feature extraction of water quality data in the section of Burnett River considering the effect of the sequences on the prediction results at different moments to enhance the influence of key features on the prediction results. This study provides one-step-ahead forecasting and multistep forward forecasting of dissolved oxygen (DO) of the Burnett River utilizing LSTM and AT-LSTM models and the comparison of the results. The research outcomes demonstrated that the inclusion of the attention mechanism improves the prediction performance of the LSTM model. Therefore, the AT-LSTM-based water quality forecasting model, developed in this study, demonstrated its stronger capability than the LSTM model for informing the Water Quality Improvement Plan of Queensland, Australia, to accurately predict water quality in the Burnett River.

Traditional wastewater treatment technologies have become increasingly inefficient to meet the needs of low-consumption and sustainable wastewater treatment. Researchers are committed to seeking new wastewater treatment technologies, to reduce the pressure on the environment caused by resource shortages. Recently, a microalgal-bacterial granular sludge (MBGS) technology has attracted widespread attention due to its high efficiency wastewater treatment capacity, low energy consumption, low CO₂ emissions, potentially high added values, and resource recovery capabilities. This review focused primarily on the following aspects of microalgal-bacterial granular sludge technology: (1) MBGS culture and maintenance operating parameters, (2) MBGS application in different wastewaters, (3) MBGS additional products: biofuels and bioproducts, (4) MBGS energy saving and consumption reduction: greenhouse gas emission reduction, and (5) challenges and prospects. The information in this review will help us better understand the current progress and future direction of the MBGS technology development. It is expected that this review will provide a sound theoretical basis for the practical applications of a MBGS technology in environmentally sustainable wastewater treatment, resource recovery, and system optimization.

As highly toxic and carcinogenic substances, antimony and arsenic often coexist and cause compound pollution. Heavy metal pollution in water significantly threatens human health and the ecological environment. This article elaborates on the sources and hazards of compound antimony and arsenic contamination and systematically discusses the research progress of treatment technology to remove antimony and arsenic in water. Due to the advantages of simple operation, high removal efficiency, low economic cost, and renewable solid and sustainable utilization, adsorption technology for removing antimony and arsenic from sewage stand out among many treatment technologies. The adsorption performance of adsorbent materials is the key to removing antimony and arsenic in water. Therefore, this article focused on summarizing frontier adsorption materials’ characteristics, adsorption mechanism, and performance, including MOFs, COFs, graphene, and biomass materials. Then, the research and application progress of antimony and arsenic removal by frontier materials were described. The adsorption effects of various frontier adsorption materials were objectively analyzed and comparatively evaluated. Finally, the characteristics, advantages, and disadvantages of various frontier adsorption materials in removing antimony and arsenic from water were summarized to provide ideas for improving and innovating adsorption materials for water pollution treatment.

Cr(VI) contamination has posed great threat to both the ecosystem and human health for its carcinogenic and mutagenic nature. A highly effective adsorbent for the removal of Cr(VI) was prepared and its adsorption mechanism was thoroughly discussed in this study. In detail, magnetic BiFeO₃ and kenaf biochar were loaded on cross-linked chitosan to obtain chitosan-kenaf biochar@BiFeO₃ (CKB) for improving adsorption capacity towards Cr(VI). The adsorption process of Cr(VI) onto CKB was evaluated as a function of the pH, the existence of competing ions, the initial concentration of Cr(VI) and contact time. The results show that CKB exhibits the highest adsorption capacity under the optimal pH 2.0. The presence of competing ions such as Ca²⁺, NO₃⁻, SO₄²⁻, and Cl⁻ decreases the adsorption capacity; among them, Ca²⁺ and NO₃⁻ show the greatest hindrance. By studying the effect of initial Cr(VI) concentration on the adsorption capacity, it was found that CKB in the solution was enough to remove Cr(VI) for all treatments (10–200 mg/L). The adsorption experimental data were well fitted with pseudo-first-order model, suggesting that chemisorption is not the dominant rate-limiting step. Freundlich isotherm model can better explain the adsorption process, indicating a non-ideal adsorption towards Cr(VI) on a heterogeneous surface of CKB. A 2^5-1 Fractional Factorial Design (FFD) showed that pH and initial concentration of Cr(VI) have significant influence on Cr(VI) adsorption in our reaction system. In general, excellent adsorption efficiency of CKB indicates that it may be a good candidate for the remediation of Cr(VI)-contaminating wastewater.

This article provides a systematic review of the current research status and latest progress in the field of mine ecological restoration. Using the SCI literature indexed by the Web of Science database as the data source, the research status and hotspots in the field of mine ecological restoration are displayed through the visual analysis of CiteSpace and the progress of mine ecological restoration technology this year is systematically summarized. Through a comprehensive review of existing technological methods, it is found that whether it is physical, chemical, biological restoration, or combined restoration technology, there are respective advantages, disadvantages, and application limitations. Physical remediation is a pretreatment, chemical remediation is prone to secondary pollution, while the sustainability shown by bioremediation makes it dominant in the of mine ecological remediation, but it has a long cycle and there is a risk of heavy metals that are accumulated by plants re-entering the biosphere through the food chain. Combined remediation can integrate the advantages of different restoration technologies and is the trend for the future development of mine ecological restoration. In the future, we should further promote technological innovation, perfect monitoring and evaluation technology, and promote informatization, scientization, and the effective implementation of mine ecological restoration, to achieve the ecological restoration and sustainable development of the mine area.

To improve the water resources carrying capacity of the Xiangjiang River Basin and achieve sustainable development, this article evaluates and predicts the Xiangjiang River Basin’s water resources carrying capacity level based on county-level units. This article takes 44 county-level units in the Xiangjiang River Basin as the evaluation target, selects TOPSIS and the entropy weight method to determine weights, calculates the water resources carrying capacity level of the evaluation sample, uses a BP neural network model to calculate the predicted water resources carrying capacity level for the next 5 years, and adds the GIS method for spatiotemporal analysis.(1) The water resources carrying capacity of the Xiangjiang River Basin has remained relatively stable for a long period, with overloaded areas being the majority. (2) There are relatively significant spatial differences in the carrying capacity of water resources: Zixing City, located upstream of the tributary, is far ahead due to its possession of the Dongjiang Reservoir; the water resources carrying capacity in the middle and lower reaches (northern region) is generally higher than that in the upper reaches (southern region). (3) According to the BP neural network model prediction, the water resources carrying capacity of the Xiangjiang River Basin will maintain a stable development trend in 2022, while areas such as Changsha and Zixing City will be in a critical state, and other counties and cities will be in an overloaded state.This study has important references value for the evaluation and early warning work of the Xiangjiang River Basin and related research, providing a scientific and systematic evaluation method and providing strong support for water resource management and planning in Hunan Province and other regions.