Dissolved oxygen variation in the North China Plain river network region over 2011-2020 and the influencing factors

The potential linkage between sediment oxygen demand and microbes and its contribution to the dissolved oxygen depletion in the Gan River

The role of sediment oxygen demand (SOD) in causing dissolved oxygen (DO) depletion is widely acknowledged, with previous studies mainly focusing on chemical and biological SOD separately. However, the relationship between the putative functions of sediment microbes and SOD, and their impact on DO depletion in overlying water, remains unclear. In this study, DO depletion was observed in the downstream of the Gan River during the summer. Sediments were sampled from three downstream sites (YZ, Down1, and Down2) and one upstream site (CK) as a control. Aquatic physicochemical parameters and SOD levels were measured, and microbial functions were inferred from taxonomic genes through analyses of the 16S rRNA gene. The results showed that DO depletion sites exhibited a higher SOD rate compared to CK. The microbial community structure was influenced by the spatial variation of Proteobacteria, Chloroflexi, and Bacteroidota, with total organic carbon (TOC) content acting as a significant environmental driver. A negative correlation was observed between microbial diversity and DO concentration (p < 0.05). Aerobic microbes were more abundant in DO depletion sites, particularly Proteobacteria. Microbes involved in various biogeochemical cycles, such as carbon (methane oxidation, methanotrophs, and methylotrophs), nitrogen (nitrification and denitrification), sulfur (sulfide and sulfur compound oxidation), and manganese cycles (manganese oxidation), exhibited higher abundance in DO depletion sites, except for the iron cycle (iron oxidation). These processes were negatively correlated with DO concentration and positively with SOD (p < 0.05). Overall, the results highlight that aerobic bacteria's metabolic processes consume oxygen, increasing the SOD rate and contributing to DO depletion in the overlying water. Additionally, the study underscores the importance of targeting the removal of in situ microbial molecular mechanisms associated with toxic H2S and CH4 to support reoxygenation efforts in rehabilitating DO depletion sites in the Gan River, aiding in identifying factors controlling DO consumption and offering practical value for the river's restoration and management.

An integrated approach through controlled experiment and LCIA to evaluate water quality and ecological impacts of irrigated paddy rice

This study used an integrated approach to mainly assess the water quality of paddy field during cultivation and quantify its equivalent ecological damages. Accordingly, an isolated pilot area with 0.6 ha and subsurface drainage pipes was prepared for flow measurement and multiple pollutant examination (DO, EC, pH, COD, TKN, TN, TP, NO3, butachlor) under controlled condition during 94 days of rice cultivation. Based on life cycle impact assessment (LCIA) database, the indices of ReCiPe (2016) were used to convert the examined nutrient and herbicide pollution. Results showed that TKN and TP were significant pollutants and reached the maximum concentrations of 7.2 and 4.9 mg/L in pilot outflow, respectively. Here, their average discharged loads were 56.2 gN/day and 45.3 gP/day. These loads equal leaching 8.5% and 9.4% of applied urea and phosphate fertilizers, respectively. The nutrient export coefficients were 8.4 kgN/ha and 6.8 kgP/ha. Nevertheless, the majority of this pollution was transferred by inflow. The net export coefficients were 0.3 kgN/ha and 2.6 kgP/ha while net leaching rates were 0.3%TN and 3.3%TP. The trend of combined ecological damages also showed that the 11-17th day of cultivation imposed the highest ecological risks. The state-of-the-art index of ecological footprint per food production estimates the equivalent ratio of lost lives by impaired ecosystem against lives saved from starvation. This index showed that 7% of the potential of produced paddy rice in this area for saving lives would be spoiled by releasing pollution to the terrestrial ecosystem in the long term. Yet, it can be enhanced as a matter of direct discharge to the freshwater. Therefore, using suitable agricultural operations or improving farm management practices for pollution abatement or assimilation potential is highly recommended.

Urban river recovery: a systematic review on the effectiveness of water clean-up programs

Urban rivers are affected at different levels by the intensification of human activities, representing a serious threat to the maintenance of terrestrial life and sustainable urban development. Consequently, great efforts have been dedicated to the ecological restoration of urban rivers around the world, as a solution to recovering the environmental functionality of these environments. In this sense, the present work aimed to investigate the effectiveness of interventions carried out aimed at the recovery of urban rivers, through a systematic review of the literature between 2010 and 2022, using the search term "rivers recovery." The results showed that there have been notable advances in the implementation of river recovery programs in urban areas around the world between the years analyzed. The ecosystems studied were affected, for the most part, by the increase in the supply of nutrients from domestic and industrial effluents, in addition to having highly urbanized surroundings and with several changes in land use patterns. The preparation of this literature review made it possible to demonstrate that the effectiveness of river recovery is extremely complex, since river recovery projects are developed for different reasons, as well as being carried out in different ways according to the intended objective.

Advancements of remote data acquisition and processing in unmanned vehicle technologies for water quality monitoring: An extensive review

Regular water quality monitoring is becoming desirable due to the increase in water pollution caused by both climate change and the generation of industrial chemicals. Unmanned vehicles have emerged as key technologies for remote data acquisition, providing fast and accurate methods for water quality monitoring. However, current research on unmanned vehicles has not systematically examined their features and limitations, which are crucial for identifying future research directions and applications of unmanned vehicle technologies. Therefore, this study extensively reviews the advancements in remote data acquisition and processing using unmanned vehicle technologies for water quality monitoring to provide valuable insights for future research. First, the types of unmanned vehicles and their application ranges for water quality monitoring are summarized. Among the unmanned vehicle technologies, unmanned aerial vehicles are considered primary platforms for water quality monitoring due to their wide data acquisition range and their ability to accommodate diverse sensors and samplers. Also, the types of samplers and sensors mounted on the unmanned vehicles are analyzed based on their characteristics. It is concluded that spectral sensors offer the most cost-effective approach for acquiring real-time water quality data. Furthermore, algorithms that convert image data into water quality data are examined, focusing on data preprocessing, analysis, and validation. The findings reveal a close relationship between the analysis of spectral characteristics of each water quality parameter and the wavelength ranges of red and red-edge. Lastly, future research directions for unmanned vehicle technologies are further suggested based on the summarized technological limitations.

Highly-oxidizing Au@MnO2-X nanozymes mediated homogeneous electrochemical detection of organophosphorus independent of dissolved oxygen

Traditional oxidase-like (OXD) nanozymes rely primarily on O2-mediated superoxide anion (O2·-) process for catalytic oxidation and organophosphorus (Ops) detection. While during the actual detection process, the concentration of O2 is inconstant that can be easily changed with the external environment, distorting detection results. Herein, highly-oxidizing Au@MnO2-X nanozymes with core-shell nanostructure are designed which trigger substantial electron transfer from inner Au core to outer ultrathin MnO2-X layer. According to experimental and theoretical calculations, the core-shell nanostructure and ultrathin MnO2-X of Au@MnO2-X result in the large surface defects, high oxygen vacancies and MnIII ratios. The specially structured Au@MnO2-X nanozymes are therefore highly-oxidizing and the catalytic oxidation can be completed merely through electrons transferring instead of the O2-mediated O2·- process. Based on this, an oxygen independent and ultrasensitive nanozyme-based sensor is established using homogeneous electrochemistry (HEC), its Ops is detected at a LOD of 0.039 ng mL-1. Combined with the UV-vis spectrum of 3,3',5,5'-tetramethylbenzidine (TMB), the linear discriminant analysis of five Ops i.e., Ethion, Omethoate, Diazinon, Chlorpyrifos methyl and Dipterex has achieved superior discrimination results. Therefore, HEC based on strong oxidizing nanozymes provide a new avenue for the development of high-performance electrochemical sensors and demonstrate potential applicability to pesticide residue determination in real samples.

A spatiotemporal dissolved oxygen prediction model based on graph attention networks suitable for missing data

The accurate prediction of dissolved oxygen concentration is crucial for the effective prevention and control of water pollution. A spatiotemporal prediction model for dissolved oxygen content that is suitable for missing data is proposed in this study. The model utilizes a module based on neural controlled differential equations (NCDEs) to handle missing data and graph attention networks (GATs) to capture the spatiotemporal relationship of dissolved oxygen content. To enhance the performance of model, it is optimized from three aspects: an iterative optimization method based on the k-nearest neighbor graph is proposed to enhance the quality of graph; Shapley additive explanations model (SHAP) is used to select the main features into model, enabling it to handle multiple features; and a fusion graph attention mechanism is introduced to improve the robustness of model to noise. The model is evaluated using data from water quality monitoring sites in Hunan Province, China, from January 14, 2021, to June 16, 2022. The proposed model outperforms other models in long-term prediction (step = 18), with MAE of 0.194, NSE of 0.914, RAE of 0.219, and IA of 0.977. The results demonstrate that constructing appropriate spatial dependencies can enhance the accuracy of dissolved oxygen prediction models, and the NCDE module confers robustness to missing data in the model.

Seasonal fluctuation of water quality and ecogenomic phylogeny of novel potential microbial pollution indicators of Veshaw River Kashmir-Western Himalaya

Nearly a billion people, especially in underdeveloped nations, need safe drinking water. Indian studies suggest that most drinking water sources have high coliform levels, and quality assurance is required. This study was conducted in rural parts of South Kashmir in the Western Himalaya from February 2019 to January 2020. Standard river water sampling was done from upstream to downstream of the river. This study examined the detection, molecular identification, and chemical water quality of coliform-contaminated drinking water, which sums up river water pollution. Water quality varied significantly, indicating downstream contamination. Sangam (downstream) had the highest coliform count, showing 72.2600 cfu per litre in summer, while Kongwaton (upstream), near the Veshaw River, had no coliform count in winter. In summer, Sangam (downstream) had the highest water quality metrics (pH 6.847, Electrical conductivity (EC) 71.620 dS/m, Biological oxygen demand (BOD) 1.120 mg/L, and Chemical oxygen demand (COD) 24.637 mg/L) in all seasons. The lowest winter water quality metrics in Kongwaton were pH 8.947, EC 253.680 dS/m, BOD 4.963 mg/L, and COD 51.440 mg/L. Coliforms in water suggest faecal contamination. This study examines the water quality attributes of drinking water and associated factors to determine river pollution. Total DNA was collected and sequenced for 16 S rDNA and metagenomics. Universal primers were used to amplify the bacterial 16 S rRNA. Using BLAST, the amplified 16 S rRNA gene sequence was matched to the NCBI database. A metagenomic study revealed 27 species with different relative abundance. These species include Escherichia coli, E. fergusonii, E. albertii, Klebsiella grimontii, and Shigella dysenteriae. This study is thought to be the first to discriminate against E. fergusonii, E. albertii, K. grimontii, and S. dysenteriae from E. coli and to report on E. fergusonii and E. albertii, K. grimontii, and S. dysenteriae in the river Veshaw water sources in Kulgam, Western Himalaya.

How anthropogenic factors influence the dissolved oxygen in surface water over three decades in eastern China?

The aquatic environment, linked to the sustainable development of human existence and ecological environment, is influenced comprehensively by anthropogenic and natural activities. In light of the continuously low concentration of dissolved oxygen (DO) in surface water in plain river networks and the phenomenon of delay in the improvement of surface water quality, this research aims to introduce a method that may be utilized in identifying the critical driving forces of DO in surface water and their lagging characteristics, which will contribute to the assessment and adjustment of water quality drivers and/or policies. The research analyzes a typical small watershed in a river network region of the Yangtze River Delta plain as the study area, collecting 35-year (1986-2020) data on several water quality parameters, decades of anthropogenic activities, and two natural factors. The time series methods of vector autoregressive model, Granger causality tests, forecast error variance decompositions, and impulse response functions (hereinafter referred to as VAR+), which are rarely applied in related research, were employed in this study and proved helpful for screening out pivotal drivers and capturing the lagging responses of DO level to driving forces at each lagged time. Results show that there exists a fluctuating drop in DO level in surface water from 1986 to 2008 and a steady climb from 2008 to 2020, with the lowest DO level being present in 2008. The impulsive perturbations of phosphate fertilizer consumption (PFC), motor vessel number, and precipitation minimally increase DO concentration, while the impulsive perturbation of gross domestic product (GDP) causes the sharpest drop in DO level. With these perturbations, the driving force of PFC persists for approximately seven years, and the driving forces of water temperature, permanent population, and GDP persist for only five years. Future research could be conducted with spatial hysteresis, selection of lag order and variable quantity within the model, as well as intermediate variables between drivers and DO level for exploring driving pathways and mechanisms.

Physicochemical, structural analysis of coal discards (and sewage sludge) (co)-HTC derived biochar for a sustainable carbon economy and evaluation of the liquid by-product

This study focused on the hydrothermal treatment (HTC) of coal tailings (CT) and coal slurry (CS) and the co-hydrothermal treatment (Co-HTC) of CT, CS and sewage sludge to assess the potential for increasing the carbon content of the hydrochar produced as an enabler for a sustainable carbon economy. The optimal combination methodology and response surface methodology were used to study the relationship between the important process parameters, namely temperature, pressure, residence time, the coal-to-sewage-sludge ratio, and the carbon yield of the produced hydrochar. The optimized conditions for hydrochar from coal tailing (HCT) and hydrochar from coal slurry (HCS) (150 °C, 27 bar, 95 min) increased fixed carbon from 37.31% and 53.02% to 40.31% and 57.69%, respectively, the total carbon content improved from 42.82 to 49.80% and from 61.85 to 66.90% respectively whereas the ash content of coal discards decreased from 40.32% and 24.17% to 38.3% and 20.0% when compared CT and CS respectively. Optimized Co-HTC conditions (208 °C, 22.5bars, and 360 min) for Hydrochar from the blend of coal discards and sewage sludge (HCB) increased the fixed carbon on a dry basis and the total carbon content from 38.67% and 45.64% to 58.82% and 67.0%, when compared CT and CS respectively. Carbonization yields for HCT, HCS, and HCB were, respectively, 113.58%, 102.42%, and 129.88%. HTC and Co-HTC increase the calorific value of CT and CS, to 19.33 MJ/kg, 25.79 MJ/kg, respectively. The results further show that under Co-HTC conditions, the raw biomass undergoes dehydration and decarboxylation, resulting in a decrease in hydrogen from 3.01%, 3.56%, and 3.05% to 2.87%, 2.98%, and 2.75%, and oxygen from 8.79%, 4.78, and 8.2% to 5.83%, 2.75%, and 6.00% in the resulting HCT, HCS, and HCB, respectively. HTC and Co-HTC optimal conditions increased the specific surface area of the feedstock from 6.066 m²/g and 6.37 m²/g to 11.88 m²/g and 14.35 m²/g, for CT and CS, respectively. Total pore volume rose to 0.071 cm³/g from 0.034 cm³/g, 0.048 cm³/g, and 0.09 cm³/g proving the ability of HTC to produce high-quality hydrochar from coal discards alone or in conjunction with sewage sludge as precursors for decontamination of polluted waters, soil decontamination applications, solid combustibles, energy storage, and environmental protection.

Autochthonous sources and drought conditions drive anomalous oxygen-consuming pollution increase in a sluice-controlled reservoir in eastern China

Freshwater reservoirs are an important type of inland waterbody. However, they can suffer from oxygen-consuming pollution, which can seriously threaten drinking water safety and negatively impact the health of aquatic ecosystems. Oxygen-consuming pollutants originate from both allochthonous and autochthonous sources, and have temporally and spatially heterogeneous drivers. Datanggang Reservoir, China, is located in a small agricultural watershed; it is controlled by multiple sluice gates. Anomalously high oxygen consumption indicators were observed in this reservoir in March 2021. Here, it was hypothesized that autochthonous sources were the primary drivers of oxygen-consuming pollution in the reservoir under drought conditions. Datasets of water quality, precipitation, primary productivity, and sediment were used to analyze water quality trends in the reservoir and inflow rivers, demonstrating the effects of allochthonous inputs and autochthonous pollution. No correlation was found between reservoir oxygen consumption indicators and allochthonous inputs; reservoir oxygen consumption indicators and chlorophyll-a concentration were significantly positively correlated (p < 0.05). Substantially lower precipitation and higher water temperature and pH (compared to historical levels) were also observed before the pollution event. Therefore, during this period the hydrological conditions, water temperature, pH, and other variables caused by short-term drought conditions may have facilitated phytoplankton growth in the reservoir. This contributed to a large increase in autochthonous oxygen-consuming pollutants, as reflected by the abnormally high indicators. Sediments contaminated with organic matter may also have been an important contributor. As the effects of environmental management and pollution control continue to emerge, exogenous pollutants imported from the land to reservoirs are currently effectively controlled. However, endogenous pollutants driven by a variety of factors, such as meteorology and hydrology, will likely become the main drivers of short-term changes in oxygen-consuming pollution in freshwater reservoirs in the foreseeable future.