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Regulatory authorities in biopharmaceutical industry emphasize process design by process understanding but applicable tools that are easy to implement are still missing. Soft sensors are a promising tool for the implementation of the Quality by Design (QbD) approach and Process Analytical Technology (PAT). In particular, the correlation between viable cell counting and oxygen consumption was investigated, but problems remained: Either the process had to be modified for excluding CO 2 in pH control, or complex k L a models had to be set up for specific processes. In this work, a non-invasive soft sensor for simplified on-line cell counting based on dynamic oxygen uptake rate was developed with no need of special equipment. The dynamic oxygen uptake rates were determined by automated and periodic interruptions of gas supply in DASGIP® bioreactor systems, realized by a programmed Visual Basic script in the DASware® control software. With off-line cell counting, the two parameters were correlated based on linear regression and led to a robust model with a correlation coefficient of 0.92. Avoidance of oxygen starvation was achieved by gas flow reactivation at a certain minimum dissolved oxygen concentration. The soft sensor model was established in the exponential growth phase of a Chinese Hamster Ovary fed-batch process. Control studies showed no impact on cell growth by the discontinuous gas supply. This soft sensor is the first to be presented that does not require any specialized additional equipment as the methodology relies solely on the direct measurement of oxygen consumed by the cells in the bioreactor. • Non-invasive soft sensor method for simplified on-line cell counting. • Implemented in exponential growth phase of CHO cells. • Dynamic oxygen uptake rate as only predictor resulted in a correlation coefficient of 0.92. • No negative influences on cell growth as oxygen starvation was prevented. • 5-k cross validation showed RMSE of 0.7 × 106 cells/mL. [ABSTRACT FROM AUTHOR]

In order to create new value in biomass production using sterile Ulva with high production efficiency, we selected sterile Ulva with high culture stability from the coast of Imari City in Japan and investigated the conditions for generating high concentrations of dissolved oxygen through photosynthesis using the sterile Ulva. In the cultivation of sterile Ulva, we investigated the conditions for generating high concentrations of dissolved oxygen (DO) by controlling conditions such as aeration, NO3‐N concentration, and population density. As a result, we found that under the cultivation control conditions we found, DO reached about 3.8 times the saturation concentration after 3 h. It was found that this high level of DO can be maintained if the supersaturated DO seawater obtained here is properly sealed. Seawater containing high levels of DO is essential for the cultivation of oysters and shellfish, which also prefer a growth temperature of 20°C−25°C. Therefore, from the perspective of creating new value in biomass production, we developed a new system for simultaneously cultivating sterile Ulva and cultivating oysters. [ABSTRACT FROM AUTHOR]

Predicting the dissolved oxygen concentration and identifying its driving factors are essential for improved prevention and management of anoxia in estuaries. However, complex hydrodynamic conditions and the limitations in traditional methods result in challenges in the identification of the driving factors for the low dissolved oxygen (DO) phenomenon. The objective of our study is to develop a robust deep learning model using four-year in situ data collected from an automatic water quality monitoring station (AWQMS) in an estuary, for accurate identification and quantification of the driving factors influencing DO levels. Mitigations in hypoxia were observed during the initial two years, but a subsequent decline in DO concentrations was witnessed recently. The periodicity of DO concentrations in the Pearl River Estuary reduced with the increase in the hypoxic intensity. Maximal information coefficient (MIC) and extreme gradient boosting (XGBoost) were employed to determine the significance of input variables, which were subsequently validated by using the long- and short-term memory networks (LSTMs). The driving factors contributing to the hypoxia problem were shown as temperature, pH, conductivity, and NH4+-N concentrations. Notably, the evaluation index values of the hybrid model are MAPE = 0.0887 and R2 = 0.9208, which have been improved compared with the LSTM model by about 99.34% in MAPE reduction and 16.56% in R2 improvement, indicating that the MixUp-LSTM model was capable of effectively capturing nonlinear relationships between DO and other water quality indicators. Based on existing literature, three traditional statistical methods and four machine learning models were also performed to compare with the proposed MixUp-LSTM model, which outperformed other models in terms of prediction accuracy and robustness. Overall, the successful identification of the driving factors for the deoxygenation phenomenon would have important implications for the governance and regulation of low DO in estuaries. [ABSTRACT FROM AUTHOR]

The purpose of this research is to assess the efficacy of five distinct artificial intelligence model techniques: AdaBoost, Gradient Boosting, Tree, Random Forest, and KNN, to estimate the water quality parameters of dissolved oxygen (DO) and biochemical oxygen demand (BOD). The performance of each model was assessed using two datasets: Al-Muthanna Bridge and Al-Aammah Bridge on the Tigris River in Baghdad City. The data was randomly divided into two categories: 70% for training and 30% for testing. Principal component analysis (PCA) was used to identify the most effective input parameters for modeling DO and BOD. The four performance criteria -- coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean square error (MSE) -- were applied in order to evaluate the models' effectiveness. It was demonstrated that the AdaBoost and Gradient Boosting models were superior for predicting DO and BOD. For DO prediction, the coefficient of determination R² of Gradient Boosting (AdaBoost) at Al-Muthanna Bridge and Al-Aammah Bridge were 0.994 (0.992) and 0.994 (0.991), respectively. For BOD prediction, the correlation coefficients R² of Gradient Boosting (AdaBoost) were 0.992 (0.982) and 0.989 (0.990), respectively. This study has shown that sophisticated machine learning techniques, such as gradient boosting and AdaBoost, are suitable for predicting water quality indices. They could also be helpful for predicting and managing the water quality parameters of different water supply systems in the future in water-related communities where artificial intelligence technology is still being thoroughly investigated. [ABSTRACT FROM AUTHOR]

Hepatocytes-like cells (HLC) derived from human induced pluripotent stem cells show great promise for cell-based liver therapies and disease modelling. However, their application is currently hindered by the low production yields of existing protocols. We aim to develop a bioprocess able to generate high numbers of HLC. We used stirred-tank bioreactors with a rational control of dissolved oxygen concentration (DO) for the optimization of HLC production as 3D aggregates. We evaluated the impact of controlling DO at physiological levels (4%O2) during hepatic progenitors' stage on cell proliferation and differentiation efficiency. Whole transcriptome analysis and biochemical assays were performed to provide a detailed characterization of HLC quality attributes. When DO was controlled at 4%O2 during the hepatic progenitors' stage, cells presented an upregulation of genes associated with hypoxia-inducible factor pathway and a downregulation of oxidative stress genes. This condition promoted higher HLC production (maximum cell concentration: 2 × 106 cell/mL) and improved differentiation efficiencies (80% Albumin-positive cells) when compared to the bioreactor operated under atmospheric oxygen levels (21%O2, 0.6 × 106 cell/mL, 43% Albumin positive cells). These HLC exhibited functional characteristics of hepatocytes: capacity to metabolize drugs, ability to synthesize hepatic metabolites, and inducible cytochrome P450 activity. Bioprocess robustness was confirmed with HLC derived from different donors, including a primary hyperoxaluria type 1 (PH1) patient. The generated PH1.HLC showed metabolic features of PH1 disease with higher secretion of oxalate compared with HLC generated from healthy individuals. This work reports a reproducible bioprocess, that shows the importance of controlling DO at physiological levels to increase HLC production, and the HLC capability to display PH1 disease features. [ABSTRACT FROM AUTHOR]

To evaluate the effect of glyphosate, 2,4-D, and their combination on daily dissolved oxygen saturation percentage (DO%) in freshwater, two separate outdoor mesocosm experiments were performed. The experiments were conducted under contrasting conditions: one in clear mesotrophic status lasting 23 days, and the other in organic turbid eutrophic conditions lasting 21 days. Single concentrations were applied as commercial formulations at two levels. Samples of phytoplankton (micro + nano, picoeukaryotes, picocyanobacteria), mixotrophic algae, and heterotrophic bacteria were analyzed at four sampling dates. Increases in DO levels were consistently observed in both clear and turbid systems treated with glyphosate, either alone or in combination with 2,4-D, suggesting that DO is a sensitive indicator. DO increased in all glyphosate treatments. DO increases reflected different changes in phytoplankton communities, increasing with micro + nano phytoplankton abundance in the clear experiment but with increased picocyanobacteria in the turbid. In contrast, 2,4-D reduced DO levels, but only in the turbid system, where micro + nano phytoplankton abundance decreased. The clear system showed greater resilience by restoring DO levels before the turbid one. Mainly additive effects of the herbicide mixture were observed on dissolved oxygen levels (DO%), but a distinct synergistic decrease was detected within turbid systems, underscoring the importance of considering turbidity as a contributing factor in the freshwater impacts of herbicides. [ABSTRACT FROM AUTHOR]

Dissolved oxygen (DO) is a crucial water quality characteristic in the cultivation of vannamei shrimp. Increasing the DO concentration in shrimp ponds can be carried out using the aeration method with a tool called an aerator. In this study, types of fine-pore aeration tubes are chosen. This aerator offers multiple benefits, such as superior aeration efficiency, effortless installation, and minimal clogging. In practice, fine-pore aeration tubes can be arranged according to needs, so the layout used can influence the resulting aeration performance. This research uses the computational fluid dynamics (CFD) method to analyze DO distribution, water circulation, and aeration performance ( K L a 20 , SOTR, and SOTE) produced in various aerator layouts, namely straight-type, ring-type, and square-type, in a vannamei shrimp pond. The results show that the straight-type layout has the best DO distribution because it is spread throughout the pond area. The square-type layout has the best water circulation because it has the largest area with water velocities of less than 5 cm/s. The optimal aeration performance was achieved with the straight-type layout, which demonstrated a K L a 20 value of 3.16 h−1, SOTR value of 19.20 kg/h, and SOTE of 29.30%. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of tracking the output of an activated sludge process using fuzzy integral control. First, the dynamics of the nonlinear process are modeled with a dynamic state space fuzzy model integrating the effect of external disturbances, and then an additional integral state of the output tracking error is introduced to obtain an augmented Takagi-Sugeno (TS) fuzzy model. The TS fuzzy model is able to describe the dynamics of complex nonlinear systems with an excellent degree of accuracy. It is formulated by fuzzy if-then rules which can give local linear representation of the overall nonlinear system. Second, the design of the fuzzy integral control is performed, in which the state feedback gains are obtained by solving linear matrix inequalities (LMI). The objective is to ensure trajectory tracking of an activated sludge process (ASP) by controlling two key variables: the substrate concentration and the level of dissolved oxygen. To assess the performance of the proposed control strategy, a comparative analysis is carried out with a gain scheduling PI (GS-PI) controller. Simulation results are provided to illustrate the effectiveness of the proposed approach. Where, the fuzzy integral control reduces the high energy consumption in water treatment plants. [ABSTRACT FROM AUTHOR]

While traveling through different zones in large‐scale bioreactors, microbes are most likely subjected to fluctuating dissolved oxygen (DO) conditions at the timescales of global circulation time. In this study, to mimic industrial‐scale spatial DO gradients, we present a scale‐down setup based on dynamic feast/famine regime (150 s) that leads to repetitive cycles with rapid changes in DO availability in glucose‐limited chemostat cultures of Penicillium chrysogenum. Such DO feast/famine regime induced a stable and repetitive pattern with a reproducible metabolic response in time, and the dynamic response of intracellular metabolites featured specific differences in terms of both coverage and magnitude in comparison to other dynamic conditions, for example, substrate feast/famine cycles. Remarkably, intracellular sugar polyols were considerably increased as the hallmark metabolites along with a dynamic and higher redox state (NADH/NAD+) of the cytosol. Despite the increased availability of NADPH for penicillin production under the oscillatory DO conditions, this positive effect may be counteracted by the decreased ATP supply. Moreover, it is interesting to note that not only the penicillin productivity was reduced under such oscillating DO conditions, but also that of the unrecyclable byproduct ortho‐hydroxyphenyl acetic acid and degeneration of penicillin productivity. Furthermore, dynamic flux profiles showed the most pronounced variations in central carbon metabolism, amino acid (AA) metabolism, energy metabolism and fatty acid metabolism upon the DO oscillation. Taken together, the metabolic responses of P. chrysogenum to DO gradients reported here are important for elucidating metabolic regulation mechanisms, improving bioreactor design and scale‐up procedures as well as for constructing robust cell strains to cope with heterogenous industrial culture conditions. [ABSTRACT FROM AUTHOR]

The Tanjero River in Sulaimani City exhibits severe pollution, prompting a comprehensive water quality analysis. Physical and chemical characteristics were conducted to evaluate their contribution to contamination levels. The primary objectives of this study were to assess the degree of water quality deterioration and to evaluate the purification capacity of the river. Utilizing the Thomas graphical method, the maximum concentration of organic mass entering from the city's wastewater leading to oxygen depletion was observed in location 2, with the ultimate biochemical oxygen demand Lo 214.89 mg L−1 which exceeds the allowed limit with a deoxygenation rate k1 of 0.52 d−1. Furthermore, the Streeter-Phelps model was employed to assess the river's behavior under continuous flow conditions, focusing on dissolved oxygen deficits and reaeration dynamics. The results demonstrated that the DO values of the river water were less than the common minimum DO required for aquatic life 4 mg L−1. The maximum deficit of dissolved oxygen for the water river was too high 20.31 mg L−1 based on tc = 1.46 d, and the reaeration rate constant k2 is 1.58 d−1. Dissolved oxygen deficiencies were observed to be markedly elevated beyond location 2, indicating a constrained self-purification capability of the river and presenting a significant risk to aquatic life. This research is crucial for an international audience as it underscores the global challenges urban rivers face in managing organic pollution and maintaining ecological balance. It highlights the need for effective wastewater management practices and global strategies. Therefore, establishing a wastewater treatment facility in the city is suggested as an effective and feasible measure to prevent further deterioration of the river's water quality. [ABSTRACT FROM AUTHOR]

Effective removal of ammonia, nitrate, and intermediate nitrite is a challenge faced by highly dissolved oxygen (DO) recirculating aquaculture systems (RAS). This study investigated the effect of DO concentrations (Group A, DO 3.15 ± 0.12 mg/L, Group B, DO 4.43 ± 0.15 mg/L, Group C, DO 6.52 ± 0.35 mg/L, Group D, and DO 7.86 ± 0.55 mg/L) on the simultaneous nitrification and denitrification (SND) of aquaculture seawater using poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) as a biofilm carrier and solid-phase denitrification (SPD) carbon source. Ammonia and nitrate were simultaneously removed in all the PHBV-supported SPD systems. Ammonia in Group C had the highest removal rate (5.72 mg/(L·h)), whereas nitrate and nitrite in Group A were completely removed at 4 and 5 h, respectively. The continuous release of PHBV provided carbon sources for denitrification. High throughout sequencing showed that Proteobacteria, Bacteroidetes, Desulfobacterota, and Chloroflexi at the phylum level, and Marinobacter, Shewanella, and Pseudomonas at the genus level exhibited unique relative abundances under varying DO concentrations. The nitrification genes in Group C showed the highest expression. Denitrification genes in Group A were enriched. The relative expression of nitrogen-transforming genes further demonstrated the results for water quality and the microbial community. DO concentration affected the efficiency of the nitrogen transformation pathway in the PHBV-supported SPD system. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Location Methods Results Main Conclusions Shoaling of large oxygen minimum zones (OMZs) that form along eastern margins of the world's oceans can reduce habitat availability for some pelagic fishes. Our aim was to test the hypothesis that habitat compression caused by shoaling of the Pacific OMZ in tropical regions creates a boundary to the southern distribution of shortfin mako sharks (Isurus oxyrinchus) in the Eastern North Pacific Ocean.Eastern North Pacific and Western North Atlantic oceans.We compared environmental conditions between areas used by satellite‐tagged mako sharks in the Eastern North Pacific, encompassing the world's largest OMZ, to those used in the Western North Atlantic where no OMZ is present. In the Pacific we quantified the effects of temperature and dissolved oxygen (DO) on depth use and tested if sharks spent less time in areas with strong habitat compression over the OMZ than expected by chance.The southern distribution of sharks in the Pacific corresponded with the apex of OMZ shoaling in the North Equatorial Current. Sharks in the Atlantic occupied areas with warm surface temperatures (≥ 26°C) more often than the Pacific, and waters with these temperatures in the Atlantic had greater DO at depth. Sharks in the Pacific reduced time near the surface in warm temperatures and consistently avoided depths with low DO and spent less time in areas with strong habitat compression than expected by chance.The combination of warm surface temperatures and shoaling of the OMZ creates a soft boundary to mako shark movements in the Eastern North Pacific Ocean. The expected expansion of OMZs due to climate change could have considerable impact on future distribution of mako sharks and other pelagic fish. As such, development of species distribution models to predict the effects of climate change on pelagic fish distributions should incorporate oxygen availability. [ABSTRACT FROM AUTHOR]

Nitrospira is a common genus of nitrite-oxidising bacteria (NOB) found in wastewater treatment plants (WWTPs). To identify the key factors influencing the composition of NOB communities, research was conducted using both sequencing batch reactor (SBR) and continuous flow reactor under different conditions. High-throughput 16S rRNA gene sequencing revealed that Nitrospira (18.79% in R1 and 25.77% in R3) was the dominant NOB under low dissolved oxygen (DO) and low nitrite (${\rm NO}_2^-$ NO 2 − -N) concentrations, while Nitrobacter (21.26% in R2) was the dominant NOB under high DO and high ${\rm NO}_2^-$ NO 2 − -N concentrations. Flocculent and granule sludge were cultivated with Nitrospira as the dominant genus. Compared to Nitrospira flocculent sludge, Nitrospira granule sludge had higher inhibition threshold concentrations for free ammonia (FA) and free nitrous acid (FNA). It was more likely to resist adverse environmental disturbances. Furthermore, the effects of environmental factors such as temperature, pH, and DO on the activity of Nitrospira granular sludge were also studied. The results showed that the optimum temperature and pH for Nitrospira granular sludge were 36°C and 7.0, respectively. Additionally, Nitrospira granular sludge showed a higher dissolved oxygen half-saturation constant (Ko) of 3.67 ± 0.71 mg/L due to its morphological characteristics. However, the majority of WWTPs conditions do not meet the conditions for the Nitrospira granular sludge. Thus, it can be speculated that future development of aerobic partial nitrification granular sludge may automatically eliminate the influence of Nitrospira. This study provides a theoretical basis for a deeper understanding of Nitrospira and the development of future water treatment processes. [ABSTRACT FROM AUTHOR]

Point bars are crucial elements of river systems, significantly enhancing the nitrogen cycle in riparian zones by facilitating hyporheic exchange between surface water and riparian zones. This study investigated the impact of dissolved oxygen (DO) concentration and temperature on nitrogen transport and reactions in river point bars. A two-dimensional coupled surface water–groundwater model was developed to analyze nitrogen distribution, variations, and reaction rates in rivers with point bars. The model considered three chemical reactions controlling nitrogen transformation: aerobic respiration, nitrification, and denitrification, with DO and temperature as independent variables. The results indicated that DO variations have a limited effect on solute migration depth, whereas increased temperature reduces solute migration depth. At surface water DO concentrations of 0.1, 0.2, and 0.4 mol/m3, nitrate removal in the riparian zone was 0.022, 0.0064, and 0.0019 mol/m, respectively. At riparian temperatures of 5 °C, 15 °C, and 25 °C, nitrate removal was 0.012, 0.041, and 0.16 mol/m, respectively. Nitrogen removal is more sensitive to temperature variations than to changes in DO concentration. In this research, the decrease in DO concentrations and the temperature increase greatly enhanced the riparian zone's denitrification effect. This study improves our understanding of how riparian zones impact nitrogen cycling under various environmental conditions. [ABSTRACT FROM AUTHOR]

The tannery industry produces one of the worst contaminants, and unsafe disposal in nearby waterbodies and landfills has become an imminent threat to public health, especially when the resulting multidrug-resistant bacteria and heavy metals enter community settings and animal food chains. In this study, we have collected 10 tannery wastewater (TWW) samples and 10 additional non-tannery wastewater (NTW) samples to compare the chemical oxygen demand (COD), pH, biological oxygen demand (BOD), dissolved oxygen (DO), total dissolved solids (TDS), chromium concentration, bacterial load, and antibiotic resistance profiles. While COD, pH, and chromium concentration data were previously published from our lab, this part of the study uncovers that TWW samples had a significantly higher bacterial load, compared to the non-tannery wastewater samples (5.89 × 104 and 9.38 × 103 cfu/mL, respectively), higher BOD and TDS values, and significantly lower DO values. The results showed that 53.4, 46.7, 40.0, and 40.0% of the TWW isolates were resistant to ceftriaxone, erythromycin, nalidixic acid, and azithromycin, respectively. On the other hand, 20.0, 30.0, 50.0, and 40.0% of the NTW isolates were resistant to the same antibiotics, respectively. These findings suggest that the TWW isolates were more resistant to antibiotics than the NTW isolates. Moreover, the TWW isolates exhibited higher multidrug resistance than the NTW isolates, 33.33, and 20.00%, respectively. Furthermore, spearman correlation analysis depicts that there is a negative correlation between BOD and bacterial load up to a certain level (r = − 0.7749, p = 0.0085). In addition, there is also a consistent negative correlation between COD and bacterial load (r = − 0.7112, p = 0.0252) and TDS and bacterial load (r = − 0.7621, p = 0.0104). These findings suggest that TWW could pose a significant risk to public health and the environment and highlight the importance of proper wastewater treatment in tannery industries. [ABSTRACT FROM AUTHOR]

The production of oxygen through phytoplankton photosynthesis is a crucial phenomenon in the dynamics of marine ecosystems. A generic oxygen-phytoplankton interaction model is considered to comprehend its underlying mechanism. This paper investigates the discrete-time dynamics of oxygen and phytoplankton in aquatic ecosystems, incorporating factors that cause phytoplankton mortality due to external influences. We explore the conditions for the local stability of steady states concerning the oxygen content in dissolved water and phytoplankton density. The analysis reveals that the model undergoes a co-dimension one bifurcation, encompassing flip and Neimark–Sacker bifurcations, utilizing the center manifold theorem and bifurcation theory. To manage the chaos resulting from the Neimark–Sacker bifurcation, we apply the OGY feedback control method and a hybrid control methodology. Finally, we present numerical simulations to validate the theoretical discussion. [ABSTRACT FROM AUTHOR]

Peat particulate organic matter (POM) in the anoxic subsurface of peatlands is increasingly recognized as an important terminal electron acceptor (TEA) in anaerobic respiration. While POM reduction has been demonstrated in laboratory peat‐soil incubations and (electro‐) chemical reduction assays, direct demonstration of POM reduction in peat soils under in situ, field conditions involving quantification of transferred electrons remain missing. Herein, we demonstrate that deployment of an oxidized reference POM in the anoxic, methanogenic subsurface of three ombrotrophic bogs, followed by one year incubation, resulted in the transfer of approximately 150–170 μmol of electrons per gram POM to the deployed reference POM. The capacity of this reduced POM to accept electrons was partially restored upon subsequent exposure to dissolved oxygen. These findings provide direct evidence for POM acting as regenerable and sustainable TEA for anaerobic respiration in temporarily anoxic parts of peat soils. Based on the number of electrons transferred to POM and thermodynamic considerations, we estimate that anaerobic respiration to POM may largely suppress methanogenesis in peat soils, particularly close to the oxic‐anoxic interface across which POM is expected to undergo redox cycling. Plain Language Summary: In oxygen‐depleted peat soil, microbes slowly break down peat material to CO2 in a series of processes summarized under the term anaerobic respiration. These processes have in common that they require a chemical substance to which microbes can transfer electrons liberated in anaerobic respiration. Previous studies provided evidence that peat particulate organic matter (POM), the organic material primarily making up peat soils, can act as this electron acceptor. In this work, we buried a reference POM, placed in small mesh bags, in three Swedish peat soils. After 1 year, analysis of the recollected POM indeed showed that it had taken up electrons. Some of these electrons could be subsequently removed from the POM by bringing it in contact with dissolved oxygen. Taken together, our study supports that POM in peatlands accepts electrons, temporarily stores them, and then transfers them to oxygen when it becomes available. In this role of electron acceptor, POM may significantly decrease the formation of large amounts of methane, a gas that, when released from peatlands, largely contributes to warming of the atmosphere. Electron transfer to POM in peatland soils thus may play an important and desirable role in lowering natural methane release from peatland ecosystems. Key Points: Oxidized reference peat particulate organic matter (POM) was reduced in the anoxic subsurface of three ombrotrophic bogs over 1 yearOn average, 160 μmol electrons were transferred per gram reference POM across the three bogsThe reduced POM was partially re‐oxidized by dissolved oxygen, supporting that POM is a sustainable terminal electron acceptor [ABSTRACT FROM AUTHOR]

Iron–carbon galvanic-cell-supported autotrophic denitrification (IC-ADN) is a burgeoning efficient and cost-effective process for low-carbon wastewater treatment. This study revealed the influence of organic carbon (OC) and dissolved oxygen (DO) on IC-ADN in terms of functional and microbiological characteristics. The nitrogen removal efficiency increased to 91.6% and 94.7% with partial organic carbon source addition to COD/TN of 1 and 3, respectively. The results of 16S rRNA high-throughput sequencing with nirS and cbbL clone libraries showed that Thiobacillus was the predominant autotrophic denitrifying bacteria (ADB) in the micro-electrolysis-based autotrophic denitrification, which obtained nitrogen removal efficiency of 80.9% after 96 h. The ADBs shifted gradually to heterotrophic denitrifying bacteria Thauera with increasing COD/TN ratio. DO concentration of 0.8 rarely affected the denitrification efficiency and the denitrifying communities. When the DO concentration increased to 2.8 mg/L, the nitrogen removal efficiency decreased to 69.1%. These results demonstrated that autotrophic denitrification was notably affected by COD/TN and high DO concentration, which could be used to acquire optimum conditions for nitrogen removal. These results provided an in-depth understanding of the influential factors for galvanic-cell-based denitrification and helped us construct a stable and highly efficient treatment process for insufficient carbon source wastewater. [ABSTRACT FROM AUTHOR]

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Sea level rise (SLR) is a crucial indicator of climate change, primarily driven by greenhouse gas emissions and the subsequent increase in global temperatures. The impact of SLR, however, varies regionally due to factors such as ocean bathymetry, resulting in distinct shifts across different areas compared to the global average. Understanding the complex factors influencing SLR across diverse spatial scales, along with the associated uncertainties, is essential. This study focuses on the East Coast of the United States and Gulf of Mexico, utilizing historical SLR data from 1993 to 2023. To forecast SLR trends from 2024 to 2103, a weighted ensemble model comprising SARIMAX, LSTM, and exponential smoothing models was employed. Additionally, using historical greenhouse gas data, an ensemble of LSTM models was used to predict real-time SLR values, achieving a testing loss of 0.005. Furthermore, conductance and dissolved oxygen (DO) values were assessed for the entire forecasting period, leveraging forecasted SLR trends to evaluate the impacts on marine life, agriculture, and infrastructure. [ABSTRACT FROM AUTHOR]

Dissolved oxygen (DO) is a critical water quality constituent that governs habitat suitability for aquatic biota, biogeochemical reactions and solubility of metals in streams. Recently introduced high‐frequency sensors have increased our ability to measure DO, but we still lack the capacity to understand and predict DO concentrations at high spatial resolutions or in unmonitored locations. Machine learning (ML) has been a commonly used approach for modelling DO, however, conventional ML models have no representation of the limnological processes governing DO dynamics. Here we implement and evaluate two process‐guided deep learning (PGDL) approaches for predicting daily minimum, mean and maximum DO concentrations in rivers from the Delaware River Basin, USA. In both cases, a multi‐task approach was taken in which the PGDL models predicted stream metabolism and gas exchange rates in addition to the DO concentrations themselves. Our results showed that for these sites, the PGDL approaches did not improve upon baseline predictions in temporal and spatially similar holdout experiments. One of the approaches did, however, improve predictions when applied to spatially dissimilar sites. Although this particular PGDL approach did not improve predictive accuracy in most cases, our results suggest that process guidance, perhaps a more constrained approach, could benefit a data‐driven DO model. [ABSTRACT FROM AUTHOR]

Abstract Hepatocytes-like cells (HLC) derived from human induced pluripotent stem cells show great promise for cell-based liver therapies and disease modelling. However, their application is currently hindered by the low production yields of existing protocols. We aim to develop a bioprocess able to generate high numbers of HLC. We used stirred-tank bioreactors with a rational control of dissolved oxygen concentration (DO) for the optimization of HLC production as 3D aggregates. We evaluated the impact of controlling DO at physiological levels (4%O2) during hepatic progenitors’ stage on cell proliferation and differentiation efficiency. Whole transcriptome analysis and biochemical assays were performed to provide a detailed characterization of HLC quality attributes. When DO was controlled at 4%O2 during the hepatic progenitors’ stage, cells presented an upregulation of genes associated with hypoxia-inducible factor pathway and a downregulation of oxidative stress genes. This condition promoted higher HLC production (maximum cell concentration: 2 × 106 cell/mL) and improved differentiation efficiencies (80% Albumin-positive cells) when compared to the bioreactor operated under atmospheric oxygen levels (21%O2, 0.6 × 106 cell/mL, 43% Albumin positive cells). These HLC exhibited functional characteristics of hepatocytes: capacity to metabolize drugs, ability to synthesize hepatic metabolites, and inducible cytochrome P450 activity. Bioprocess robustness was confirmed with HLC derived from different donors, including a primary hyperoxaluria type 1 (PH1) patient. The generated PH1.HLC showed metabolic features of PH1 disease with higher secretion of oxalate compared with HLC generated from healthy individuals. This work reports a reproducible bioprocess, that shows the importance of controlling DO at physiological levels to increase HLC production, and the HLC capability to display PH1 disease features.

The dissolved oxygen in a coolant can affect the oxidation properties of structural materials. A desirable oxide phase formation is achieved by manipulating the oxygen level in the coolant, which can mitigate structural material degradation in nuclear power plants. Therefore, the role of dissolved oxygen in the corrosion of structural materials in aqueous environments needs to be understood. In this study, a short-term corrosion test (up to 300 h) of Ferritic/Martensitic steels (F/M steels; FeCrW model alloys), namely, Fe12Cr1W, Fe9Cr1W, and Fe9Cr, in stagnant water at 360 °C was performed in a pressurized autoclave with the dissolved oxygen concentration controlled to 1 ppm or a very low level (

Abstract Climate change is causing widespread impacts on seawater pH through ocean acidification (OA). Kelp forests, in some locations can buffer the effects of OA through photosynthesis. However, the factors influencing this variation remain poorly understood. To address this gap, we conducted a literature review and field deployments of pH and dissolved oxygen (DO) loggers within four habitats: intact kelp forest, moderate kelp cover, sparse kelp cover and barrens at one site in Port Phillip Bay, a wind-wave dominated coastal embayment in Victoria, Australia. Additionally, a wave logger was placed directly in front of the intact kelp forest and barrens habitats. Most studies reported that kelp increased seawater pH and DO during the day, compared to controls without kelp. This effect was more pronounced in densely populated forests, particularly in shallow, sheltered conditions. Our field study was broadly consistent with these observations, with intact kelp habitat having higher seawater pH than habitats with less kelp or barrens and higher seawater DO compared to barrens, particularly in the afternoon and during calmer wave conditions. Although kelp forests can provide local refuges to biota from OA, the benefits are variable through time and may be reduced by declines in kelp density and increased wave exposure.

The purpose of this research is to assess the efficacy of five distinct artificial intelligence model techniques: AdaBoost, Gradient Boosting, Tree, Random Forest, and KNN, to estimate the water quality parameters of dissolved oxygen (DO) and biochemical oxygen demand (BOD). The performance of each model was assessed using two datasets: Al-Muthanna Bridge and Al-Aammah Bridge on the Tigris River in Baghdad City. The data was randomly divided into two categories: 70% for training and 30% for testing. Principal component analysis (PCA) was used to identify the most effective input parameters for modeling DO and BOD. The four performance criteria—coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and mean square error (MSE)— were applied in order to evaluate the models' effectiveness. It was demonstrated that the AdaBoost and Gradient Boosting models were superior for predicting DO and BOD. For DO prediction, the coefficient of determination R2 of Gradient Boosting (AdaBoost) at Al-Muthanna Bridge and Al-Aammah Bridge were 0.994 (0.992) and 0.994 (0.991), respectively. For BOD prediction, the correlation coefficients R2 of Gradient Boosting (AdaBoost) were 0.992 (0.982) and 0.989 (0.990), respectively. This study has shown that sophisticated machine learning techniques, such as gradient boosting and AdaBoost, are suitable for predicting water quality indices. They could also be helpful for predicting and managing the water quality parameters of different water supply systems in the future in water-related communities where artificial intelligence technology is still being thoroughly investigated.

The efficacy of marine protected areas (MPAs) may be reduced when climate change disrupts the ecosystems and human communities around which they are designed. The effects of ocean warming on MPA functioning have received attention but less is known about how multiple climatic stressors may influence MPAs efficacy. Using a novel dataset incorporating 8.8 million oceanographic observations, we assess exposure to potentially stressful temperatures, dissolved oxygen concentrations, and pH levels across the California MPA network. This dataset covers more than two-thirds of California's 124 MPAs and multiple biogeographic domains. However, spatial-temporal and methodological patchiness constrains the extent to which systematic evaluation of exposure is possible across the network. Across a set of nine well-monitored MPAs, the most frequently observed combination of stressful conditions was hypoxic conditions (

Simultaneous nitrification and denitrification (SND) is an efficient method to remove nitrogen in municipal wastewater treatment. However, low dissolved oxygen (DO) concentrations are generally required, leading to serious membrane fouling in membrane bioreactors (MBRs). This study aimed to clarify the synergistic effect of biomass and DO on nitrogen removal and membrane fouling. To achieve this goal, four submerged MBRs equipped with ceramic membranes were operated with different biomass (mixed liquor suspended solids (MLSS)) concentrations (3 000 mg/L, 5 000 mg/L, 7 500 mg/L, and 12 000 mg/L) under various DO concentrations (2.0 mg/L, 1.0 mg/L, and 0.5 mg/L). As a result, increasing biomass in the MBRs enhanced total nitrogen (TN) removal via SND, and excellent TN removal efficiencies of 60.7% and 75.8% were obtained using the MBR with an MLSS concentration of 12 000 mg/L and DO concentrations of 2.0 mg/L and 1.0 mg/L. However, a further decrease in DO deteriorated TN removal due to the inhibition of nitrification. Moreover, high MLSS concentrations were beneficial to membrane fouling control for ceramic membranes in MBRs. The lowest transmembrane pressure development rate was observed for the MBR with an MLSS concentration of 12 000 mg/L. High biomass offset the adverse effect of DO decrease on membrane fouling to some extent, and improved the stability of the reactor. Therefore, biomass might be an important parameter for membrane fouling reduction in ceramic MBRs. Overall, optimal biomass and DO concentrations for TN removal were identified, providing useful information for the successful operation of MBRs with efficient TN removal and membrane fouling control.

Although online monitoring of dissolved O2, pH, and dissolved CO2 is critical in bioprocesses, nearly all existing technologies require some level of direct contact with the cell culture environment, posing risks of contamination. This study addresses the need for an accurate, and completely noninvasive technique for simultaneous measurement of these analytes. A "non-contact" technique for simultaneous monitoring of dissolved O2, pH, and dissolved CO2 was developed. Instead of direct contact with the culture media, the measurements were made through permeable membranes via either a sampling port in the culture vessel wall or a flow cell. The efficacy of the "non-contact" technique was validated in Escherichia coli (E.coli), Chinese hamster ovary (CHO) culture processes, and dynamic environments created by sparging gases in cell culture medium. The measurements obtained through the developed techniques were comparable to those obtained through control methods. The noninvasive monitoring system can offer accurate, and contamination-minimized monitoring of critical process parameters including dissolved O2, pH, and dissolved CO2. These advancements will enhance the control and optimization of cell culture processes, promising improved cell culture performance. [ABSTRACT FROM AUTHOR]

We review the negative impacts of vinasse, a byproduct of alcohol distillation, on Brazil's freshwater ecosystems. We found a total of 37 pollution events between the years 1935 and 2023, with this number almost certainly an underestimate due to underreporting and/or unassessed events. Pollution by vinasse occurred both through accidents (e.g., tank failure) and deliberately (i.e., opening of floodgates), although in many cases the causes remain undetermined. All pollution events caused fish kills, with some records reporting negative effects on other organisms as well (i.e., crustaceans and reptiles). Pollution by vinasse, and associated negative effects, was reported for 11 states, with a notable number of cases in São Paulo. Most cases of vinasse pollution and negative impacts on biodiversity were recorded in rivers, followed by streams and reservoirs. Some of the affected river systems harbour threatened freshwater fishes. Hydrological connectivity means that pollution could have propagated along watercourses. Given these consequences of vinasse pollution on biodiversity, ecosystem functioning and services, we recommend a number of remedial actions. [ABSTRACT FROM AUTHOR]

Oxygen depletion in coastal waters is increasing globally due primarily to eutrophication and warming. Hypoxia responses to nutrient loading and climate change have been extensively studied in large systems like the Chesapeake Bay and the Baltic Sea, while fewer studies have investigated smaller, shallower hypoxic zones. Thus, an improved understanding of the interactions of eutrophication and warming on hypoxia expansion (or reduction) in the wide variety of different estuarine environments is needed. We examined interannual controls on oxygen depletion in the Patuxent River estuary, a eutrophic sub-estuary of Chesapeake Bay where seasonal hypoxia develops annually. We conducted a spatial and temporal analysis of dissolved oxygen (DO) trends, timing, and several metrics of depletion over a long-term record (1985–2021). We found an internally generated hypoxic zone that initiates in the middle estuary, spreading upstream and downstream as the summer progresses, and that hypoxic volume days (HVD) have been increasing (0.11 per year, p = 0.03) over the record despite reduced watershed nitrogen loads and stable phosphorus loads. River flow and temperature have been increasing and are major drivers of increased HVD, with river flow explaining 40% of the interannual variation in HVD (temperature has increased 0.03 and 0.06 °C per year in summer and fall, respectively). Apparent oxygen utilization (AOU) is increasing in bottom waters in the fall, consistent with increasing trends of both water temperature and stratification strength. HVD was negatively related (r2 = 0.34, slope = −0.59*HVD) to the biomass of benthic invertebrates in the middle region of the estuary, suggesting that benthic forage for higher trophic levels will be limited by sustained hypoxia. These results indicate that current and future climate variability plays an important role in regulating oxygen depletion in the Patuxent River estuary, which reinforces the need to factor climate change into strategies for the restoration and management of estuaries. [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) is a crucial indicator of climate change, primarily driven by greenhouse gas emissions and the subsequent increase in global temperatures. The impact of SLR, however, varies regionally due to factors such as ocean bathymetry, resulting in distinct shifts across different areas compared to the global average. Understanding the complex factors influencing SLR across diverse spatial scales, along with the associated uncertainties, is essential. This study focuses on the East Coast of the United States and Gulf of Mexico, utilizing historical SLR data from 1993 to 2023. To forecast SLR trends from 2024 to 2103, a weighted ensemble model comprising SARIMAX, LSTM, and exponential smoothing models was employed. Additionally, using historical greenhouse gas data, an ensemble of LSTM models was used to predict real-time SLR values, achieving a testing loss of 0.005. Furthermore, conductance and dissolved oxygen (DO) values were assessed for the entire forecasting period, leveraging forecasted SLR trends to evaluate the impacts on marine life, agriculture, and infrastructure.

Highlights A clear negative correlation between the size of water clusters and the concentration of dissolved oxygen was observed. This implied that smaller clusters water exhibits higher concentrations of dissolved oxygen. Oxygen molecules are primarily existed at the surfaces or interfaces of water clusters and can rapidly traverse the gas liquid interface. A semi empirical formula relating the average number of water molecules in a cluster to 17O NMR half peak width was derived, demonstrating an approximate lin ear relationship.

High concentrations of activated sludge are an excellent biological treatment; in particular, simultaneous nitrification and denitrification play a huge role in nitrogen removal. However, the influencing factors of SND have not been fully elucidated. The effects of sludge concentration and dissolved oxygen (DO) concentration on the performance of SND in a high-concentration activated sludge reactor assisted by chemical agents were investigated, and the SND reaction effect was de-termined by analyzing the along-stream changes of elemental nitrogen in the reactor. The results showed that the SND phenomenon in the reactor was most obvious when the system activated sludge concentration (MLSS) was maintained at 7–9 g/L and DO concentration at 1–2 mg/L. When MLSS decreases within the range of 5–9 g/L, the nitrification reaction improves, but the SND phe-nomenon decreases or even disappears; the SND phenomenon diminishes with increasing DO con-centration. Thus, high sludge concentrations and low dissolved oxygen concentrations are im-portant influences associated with SND and promote unconventional nitrogen removal pathways. In addition, the average value of MLVSS/MLSS for the high-concentration activated sludge process was 0.586, which indicates that the system has a higher activated sludge volume and better sludge activity, which is very effective in enhancing SND. In addition, this study also further investigated the influencing factors of SND in the high-concentration method by exploring the kinetic modeling of the SND reaction in the high-concentration method. [ABSTRACT FROM AUTHOR]

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A large data set measuring surface stream turbidity, dissolved oxygen levels, and water temperature was developed by sampling 32 rivers and streams with forested catchments at weekly intervals for between two and three years. This was in response to allegations of possible water quality impairment by forest harvesting ("logging"). Additionally, nine rivers or streams external to the forests were sampled to form a "reference set"; concern was expressed that the water quality of these may be impaired by upstream forest harvesting. An unlogged forested control catchment was selected from the data set and used as a comparator to help reduce seasonal variation. Division of the data into "logged forested catchments" and "unlogged forested catchments" allowed for us to test the null hypothesis. The null hypothesis was that there was no difference between the means of the logged and unlogged sets by a "Student's t test of difference between means". The null hypothesis was supported for the three parameters. There was no discernible deterioration in water quality associated with the presence of logging in the stream catchments. It was concluded that logging in this environment was not a determinant of water quality, and that the presence or absence of logging in these catchments did not affect the measured water quality. Spearman rank correlation analysis was unable to detect any statistically significant correlations between the water quality parameters, suggesting they are substantially independent measures of water quality. The monitoring showed that the small upland streams had generally good-to-excellent water quality. The water quality in these was generally better than the "reference set"—this probably reflected agriculture and cultivation in the proximity of their sampling points. [ABSTRACT FROM AUTHOR]

Aerated subsurface drip irrigation (ASDI) can improve soil aeration, crop yield, water, and fertilizer use efficiency. In this study, a micronano-bubble generator was designed to stabilize the gas in water, according to the cyclonic shear fragmentation. A gas-liquid mixing flow was also introduced from the inlet runner tangent to the inner cavity. The ellipsoidal inner cavity was used to force the liquid into the cyclone and then spiral outward at the two ends of the spouting holes. As such, a shear effect was formed to crush the bubbles. A 4-factor and 3-level orthogonal test L9 (34) was designed to explore the effects of structural parameters on the generated bubbles and the performance of dissolved oxygen. The following specifications were: the major axis (40, 60, and 80 mm), the minor axis (30, 45, and 60 mm), the inlet diameters (8, 12, and 16 mm), and the spray holes diameter (2, 3, and 4 mm). High-speed photography, image processing, and nano-particle size analysis techniques were used to extract the features, such as the number, particle size, and uniformity of micro-nano-bubbles, in order to monitor the dissolved oxygen in water over time. The results show that the distribution of particle size was basically unchanged in the large bubbles from 60 to 250 μm with the operation of the device, while the average size of the small bubbles from 10 to 60 μm increased by 20% within 2 min of operation. Specifically, the large bubbles above 100 μm were basically dissipated, after the device was stopped for 1 min. Then the count of small bubbles below 60 μm in the water was reduced by about 70% after 3 min of stopping operation. The micro-nano-bubbles with diameters of less than 30 μm were finally suspended in the water. In addition, the performance of the device showed that the bubble generation during the operation depended the most significantly on the spray hole diameter and minor axis. The major axis shared the greatest effect on the average particle size and the uniformity of large bubbles above 60 μm in the water after operation, as well as on the number of small bubbles. The inlet diameter still reached a significant level, although there was the least effect on the number of microbubbles both during and after the operation. In addition, the nanoscale and microscale bubble generation behaved in the same way. Dissolved oxygen tests showed that the oxygen content in the water was divided into three stages: the oxygen enhancement during operation, the attenuation, and stabilization of dissolved oxygen. The inlet diameter dominated the increase and decay of dissolved oxygen. While the stabilized dissolved oxygen depended only significantly on the minor and major axes. The dissolved oxygen of the device was positively correlated with the bubble generation. The more the number of bubbles generated, the smaller and more uniform particle sizes were, and the better the performance of dissolved oxygen was. The dissolved oxygen was varied in water in the different stages, where the bubble indicators were generally consistent with the structural dimensions. Taking the high number of bubbles, small particle size, uniformity, and high dissolved oxygen as the objectives, the optimal combination of parameters was achieved in the 80 mm major axis, 45 mm minor axis, 12 mm inlet diameter, and 3 mm spray hole diameter. The finding can provide the equipment support to promote the application of ASDI. [ABSTRACT FROM AUTHOR]

In recent decades, hypoxic areas have rapidly expanded worldwide in estuaries and coastal zones. The Pearl River Estuary (PRE), one of China's largest estuaries, experiences frequent seasonal hypoxia due to intense human activities and eutrophication. However, the ecological effects of hypoxia in the PRE, particularly on fish communities, remain unclear. To explore these effects, we collected fish community and environmental data in July 2021 during the summer hypoxia development period. The results revealed that bottom‐layer dissolved oxygen (DO) in the PRE ranged from 0.08 to 5.71 mg/L, with extensive hypoxic zones (DO ≤ 2 mg/L) observed. Hypoxia has varied effects on fish community composition, distribution, species, and functional diversity in the PRE. A total of 104 fish species were collected in this study, with approximately 30 species (28.6%) exclusively found in hypoxic areas. Species responses to hypoxia varied: species such as Sardinella zunasi, Coilia mystus, and Nuchequula nuchalis were sensitive, while Decapterus maruadsi, Siganus fuscescens, and Lagocephalus spadiceus showed higher tolerance. Within the hypoxia area, dissolved oxygen was the main limiting factor for fish community diversity. Functional diversity (FDiv) decreased with higher dissolved oxygen levels, indicating a potential shift in the functional traits and ecological roles of fish species in response to changing oxygen conditions. Further analysis demonstrated that dissolved oxygen had a significantly stronger effect on fish community structure at hypoxic sites than in the whole PRE. Moreover, other environmental variables also had significant effects on the fish community structure and interacted with dissolved oxygen in the hypoxia area. These findings suggest that maintaining sufficient dissolved oxygen levels is essential for sustaining fish communities and ecosystem health in the PRE. This study provides novel insights into the effects of hypoxia on fish communities in estuarine ecosystems and has significant implications for the ecological health and management of the PRE. [ABSTRACT FROM AUTHOR]

The role of phenotypic plasticity during colonization remains unclear due to the shifting importance of plasticity across timescales. In the early stages of colonization, plasticity can facilitate persistence in a novel environment; but over evolutionary time, processes such as genetic assimilation may reduce variation in plastic traits such that species with a longer evolutionary history in an environment can show lower levels of plasticity than recent invaders. Therefore, comparing species in the early stages of colonization to long‐established species provides a powerful approach for uncovering the role of phenotypic plasticity during different stages of colonization. We compared gene expression between low‐dissolved oxygen (DO) and high‐DO populations of two cyprinid fish: Enteromius apleurogramma, a species that has undergone a recent range expansion, and E. neumayeri, a long‐established native species in the same region. We sampled tissue either immediately after capture from the field or after a 2‐week acclimation under high‐DO conditions, allowing us to test for both evolved and plastic differences in low‐DO vs high‐DO populations of each species. We found that most genes showing candidate‐evolved differences in gene expression did not overlap with those showing plastic differences in gene expression. However, in the genes that did overlap, there was counter‐gradient variation such that plastic and evolved gene expression responses were in opposite directions in both species. Additionally, E. apleurogramma had higher levels of plasticity and evolved divergence in gene expression between field populations. We suggest that the higher level of plasticity and counter‐gradient variation may have allowed rapid genetic adaptation in E. apleurogramma and facilitated colonization. This study shows how counter‐gradient variation may impact the colonization of divergent oxygen environments. [ABSTRACT FROM AUTHOR]

Coal is still a great source of energy, but its high sulfur content causes environmental pollution and problems in its processing. This study used a method of combined oxidation and alkali leaching to desulfurize low-grade, high-sulfur Lakhra coal at different ranges of temperature, alkali concentration, leaching time, partial pressure of oxygen, and agitation speed. The optimum values for the leaching reaction were observed to be an alkali (NaOH) concentration of 0.8 mM, a leaching time of 1.5 h, an oxygen partial pressure of 150 psi, and an agitation speed of 800 rpm. The ash content of the coal initially increased at higher values of reaction time and temperature, and then became saturated at a certain peak. The raw coal was characterized for ultimate and proximate analysis, and the product was characterized for ash content and total sulfur content. [ABSTRACT FROM AUTHOR]

The prediction of river water quality is key in water resource management. Data-driven machine learning models have been widely used for predicting river water quality. However, these models seldom consider the physical mechanisms of water quality variation, which degrades the accuracy and stability of the prediction results. Hence, we develop a physics-guided spatio–temporal neural network (PGSTNN) model to predict a critical parameter for water quality assessment, i.e. dissolved oxygen. Physical information regarding spatio–temporal interactions in a hydrological network is explicitly considered to construct the architecture of PGSTNN. Two physical rules of dissolved oxygen variation (i.e. Henry's law and power-scaling law) are established for the loss function of PGSTNN to guarantee the physical consistency of the prediction results. Experiments on the 2020–2021 water quality dataset in Atlanta, USA show that PGSTNN outperforms seven baseline neural network models in terms of prediction accuracy and stability. PGSTNN typically brings at least 10% accuracy (e.g. root mean square error and mean absolute error) improvement over the comparison methods. The proposed PGSTNN may not only improve the emergency response ability of water resource management, but also provide useful ideas for integrating scientific knowledge with machine learning. [ABSTRACT FROM AUTHOR]

In this study examining the effects of temperature and dissolved oxygen (DO) on arsenic (As) release at the sediment–water interface (SWI), it was found that an increase in temperature promoted the formation of an anaerobic environment and the reduction and desorption of As fractions within the sediments. A temperature of 32 °C was the most favorable condition for As release at the SWI, and low DO conditions aggravated this process. Even under high DO conditions, the release of sediment As was significantly accelerated under high-temperature conditions, allowing dissolved As to rapidly migrate to the overlying water. In this process, the release of As from sediments was a consequence of the transformation of As fractions in the sediments. [ABSTRACT FROM AUTHOR]

Copyright of Technology of Water Treatment is the property of Technology of Water Treatment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dissolved Oxygen (DO) is a crucial indicator in water bodies, enabling assessment of eutrophication degree, ecosystem status, self-purification capacity, and water quality health. This paper presents a hybrid model for predicting DO. The model utilizes symplectic geometric mode decomposition (SGMD) to decompose the DO data into multiple intrinsic mode functions (IMF) components, allowing extraction of trend and seasonal information. Subsequently, a hybrid deep learning model based on convolutional neural network (CNN) and Temporal Convolutional Network (TCN) is constructed to predict each IMF component and reconstruct the predicted value of DO. Comparative analysis with other benchmark models demonstrates the superior accuracy, indicating its effectiveness in DO prediction. Furthermore, the study investigates the impact of incorporating different water quality variables on DO prediction accuracy, revealing that incorporating variables with high correlation enhances accuracy. The accurate prediction of DO concentration by the SGMG-CNN-TCN model holds promise for sustainable river water management and plays a significant role in optimizing water environment management. [ABSTRACT FROM AUTHOR]

Water is one of the most essential elements in nature that forms the basis of human life and contributes to the economic growth and development of societies. Safe water is closely related to environmental health and activities. The lives of all the animals on our planet depend on water and oxygen. Moreover, sufficient Dissolved Oxygen (DO) is crucial for the survival of aquatic animals. In the present research, temperature (T) and flow (Q) variables were used to predict DO. We used monthly time series and data were related to the Cumberland River in the southern United States from 2012 to 2022. Support Vector Regression (SVR) was employed for prediction of the model in both standalone and hybrid forms. The employed hybrid models consisted of SVR combined with metaheuristic algorithms of Chicken Swarm Optimization (CSO), Social Ski-Driver (SSD) optimization, and the Algorithm of the Innovative Gunner (AIG). Pearson Correlation Coefficient (PCC) was utilized to select the best input combination. Box plots and Taylor diagrams were employed in the interpretation of the results. We observed that all the four hybrid models achieved good results. Also, according to the evaluation criteria, among the models used, SVRAIG performed better with the coefficient of determination (R2 = 0.963), the root mean square error (RMSE =0.644 mg/l), the mean absolute value of error (MAE = 0.568 mg/l), the Nash-Sutcliffe coefficient (NS = 0.864), and bias percentage (BIAS = 0.001). [ABSTRACT FROM AUTHOR]

Analysis of dissolved oxygen (O2) in the Arctic's surface ocean provides insights into gas transfer between the atmosphere‐ice‐ocean system, water mass dynamics, and biogeochemical processes. In the Arctic Ocean's Canada Basin mixed layer, higher O2 concentrations are generally observed under sea ice compared to open water regions. Annual cycles of O2 and O2 saturation, increasing from summer through spring and then sharply declining to late summer, are tightly linked to sea ice cover. The primary fluxes that influence seasonal variability of O2 are modeled and compared to Ice‐Tethered Profiler O2 observations to understand the relative role of each flux in the annual cycle. Findings suggest that sea ice melt/growth dominates seasonal variations in mixed layer O2, with minor contributions from vertical entrainment and atmospheric exchange. While the influence of biological activity on O2 variability cannot be directly assessed, indirect evidence suggests relatively minor contributions, although with significant uncertainty. Past studies show that O2 molecules are expelled from sea ice during brine rejection; sea ice cover can then inhibit air‐sea gas exchange resulting in winter mixed layers that are super‐saturated. Decreasing mixed layer O2 concentrations and saturation levels are observed during winter months between 2007 and 2019 in the Canada Basin. Only a minor portion of the decreasing trend in wintertime O2 can be attributed to decreased solubility. This suggests the O2 decline may be linked to more efficient air‐sea exchange associated with increased open water areas in the winter sea ice pack that are not necessarily detectable via satellite observations. Plain Language Summary: Dissolved oxygen (O2) is a valuable ocean property that allows us to better understand the exchange of gases between the different ocean layers, sea ice, and atmosphere, and the physical and biological processes that control its variability. Understanding how and why O2 concentrations in the Arctic Ocean mixed layer vary spatially and seasonally is crucial for interpreting its evolution over timescales of years to decades that are influenced by global warming. We use physical and thermodynamical relationships to model the main factors that influence O2 concentrations in the mixed layer of the Arctic Ocean's Canada Basin, which we compare to observations made by Ice‐Tethered Profilers. Model results indicate that seasonal variations in O2 concentrations are dominated by the effects of sea ice growth and melt. Other processes that modulate mixed layer O2, including air‐sea exchange and ocean mixing, have a lesser influence. Between 2007 and 2019, mixed‐layer O2 has decreased in winter months, which we attribute to more openings in the sea‐ice pack during wintertime in the Canada Basin. Key Points: Spatial and seasonal distributions of O2 concentrations in the Canada Basin mixed layer are linked to the seasonal evolution of sea iceModeled fluxes suggest brine rejection and meltwater dilution during sea ice melt/formation dominate seasonal variability of mixed layer O2Decreases in mixed‐layer O2 during winter (over 2007–2019) suggest outgassing, likely driven by changes in the wintertime sea ice pack [ABSTRACT FROM AUTHOR]

Microbial respiration is a critical component of the marine carbon cycle, determining the proportion of fixed carbon that is subject to remineralization as opposed to being available for export to the ocean depths. Despite its importance, methodological constraints have led to an inadequate understanding of this process, especially in low-activity oligotrophic and mesopelagic regions. Here, we quantify respiration rates as low as 0.2 µmol O2 L-1 d-1 in contrasting ocean productivity provinces using oxygen optode sensors to identify size-fractionated respiration trends. In the low productivity region of the North Pacific Ocean at Station Papa, surface whole water microbial respiration was relatively stable at 1.2 µmol O2 L-1 d-1. Below the surface, there was a decoupling between respiration and bacterial production that coincided with increased phytodetritus and small phytoplankton. Size-fractionated analysis revealed that cells <5 µm were responsible for the majority of the respiration in the Pacific, both at the surface and below the mixed layer. At the North Atlantic Porcupine Abyssal Plain, surface whole water microbial respiration was higher (1.7 µmol O2 L-1 d-1) than in the Pacific and decreased by 3-fold below the euphotic zone. The Atlantic size-fraction contributions to total respiration shifted on the order of days during the evolution of a phytoplankton bloom with regular storm disturbances. The high-resolution optode method used in the Atlantic captured these significant shifts and is consistent with coinciding stain-based respiration methods and historical site estimates. This study highlights the dynamic nature of respiration across vertical, temporal, and size-fractionated factors, emphasizing the need for sensitive, high-throughput techniques to better understand ocean ecosystem metabolism. [ABSTRACT FROM AUTHOR]

Variations in Marine Dissolved Oxygen Concentrations (MDOC) play a critical role in the study of marine ecosystems and global climate evolution. Although artificial intelligence methods, represented by deep learning, can enhance the precision of MDOC inversion, the uninterpretability of the operational mechanism involved in the "black-box" often make the process difficult to interpret. To address this issue, this paper proposes a high-precision interpretable framework (CDRP) for intelligent MDOC inversion, including Causal Discovery, Drift Detection, RuleFit Model, and Post Hoc Analysis. The entire process of the proposed framework is fully interpretable: (i) The causal relationships between various elements are further clarified. (ii) During the phase of concept drift analysis, the potential factors contributing to changes in marine data are extracted. (iii) The operational rules of RuleFit ensure computational transparency. (iv) Post hoc analysis provides a quantitative interpretation from both global and local perspectives. Furthermore, we have derived quantitative conclusions about the impacts of various marine elements, and our analysis maintains consistency with conclusions in marine literature on MDOC. Meanwhile, CDRP also ensures the precision of MDOC inversion: (i) PCMCI causal discovery eliminates the interference of weakly associated elements. (ii) Concept drift detection takes more representative key frames. (iii) RuleFit achieves higher precision than other models. Experiments demonstrate that CDRP has reached the optimal level in single point buoy data inversion task. Overall, CDRP can enhance the interpretability of the intelligent MDOC inversion process while ensuring high precision. [ABSTRACT FROM AUTHOR]