Nutrient enrichment and climate warming threaten freshwater systems. Metabolic theory and the paradox of enrichment predict that both stressors independently can lead to simpler food-webs having fewer nodes, shorter food-chains and lower connectance, but cancel each other\'s effects when simultaneously present. Yet, these theoretical predictions remain untested in complex natural systems. We inferred the food-web structure of 256 lakes and 373 streams from standardized fish community samplings in France. Contrary to theoretical predictions, we found that warming shortens fish food-chain length and that this effect was magnified in enriched streams and lakes. Additionally, lakes experiencing enrichment exhibit lower connectance in their fish food-webs. Our study suggests that warming and enrichment interact to magnify food-web simplification in nature, raising further concerns about the fate of freshwater systems as climate change effects will dramatically increase in the coming decades.

Microbial biofilms present one of the most widespread forms of life on Earth. The formation of microbial communities on various surfaces presents a major challenge in a variety of fields, including medicine, the food industry, shipping, etc. At the same time, this process can also be used for the benefit of humans-in bioremediation, wastewater treatment, and various biotechnological processes. The main direction of using electroactive microbial biofilms is their incorporation into the composition of biosensor and biofuel cells This review examines the fundamental knowledge acquired about the structure and formation of biofilms, the properties they have when used in bioelectrochemical devices, and the characteristics of the formation of these structures on different surfaces. Special attention is given to the potential of applying the latest advances in genetic engineering in order to improve the performance of microbial biofilm-based devices and to regulate the processes that take place within them. Finally, we highlight possible ways of dealing with the drawbacks of using biofilms in the creation of highly efficient biosensors and biofuel cells.

The use of microbial electrochemical sensors, with electroactive biofilms (EABs) as sensing elements, is a promising strategy to timely measure the biochemical oxygen demand (BOD) of wastewater. However, accumulation of Coulombic yield over a complete degradation cycle is time-consuming. Therefore, understanding the correlation between current output and EAB metabolism is urgently needed. Here, we recognized a tail stage (TS) on a current-time curve according to current increase rate─a period with the least electron harvesting efficiency. EAB adopted a series of metabolic compensation strategies, including slow metabolism of residual BOD, suspended growth, reduced cell activity, and consumption of carbon storage polymers, to cope with substrate deficiency in TS. The supplementary electrons provided by the decomposition of glycogen and fatty acid polymers increased the Coulombic efficiencies of TS to >100%. The tail current produced by spontaneous metabolic compensation showed a trend of convergent exponential decay, independent of BOD concentration. Therefore, we proposed the TS prediction model (TSPM) to predict Coulombic yield, which shortened BOD measurement time by 96% (to ∼0.5 h) with deviation <4 mg/L when using real domestic wastewater. Our findings on current output in TS give insights into bacterial substrate storage and consumption, as well as regulation in substrate-deficient environment, and provide a basis for developing BOD sensors.

River water quality management is a tedious job as it comprises multiple variables. The River Yamuna, Delhi\'s urban reach, is highly contaminated with very low or zero freshwater flow during the non-monsoon periods. The river quality has been appraised for pre- and post-monsoon periods of 10 years of data collected from the Delhi Pollution Control Council (DPCC). A sharp declination of dissolved oxygen and acceleration of BOD have been observed after the outfalling of drain 1. The wastewater treatment plants data for 2020-2022 have been analyzed, and the removal efficiencies of BOD and COD were found between 65 and 94%. The BIOFORE technology has shown maximum removal efficiencies, around 94% and 89% for BOD and COD, respectively. The level of treatment has been evaluated by developing a water quality model with the existing QUAL2kw framework. Twelve strategies have been generated for four levels of treatment and three different flow conditions. The severely polluted reach of Yamuna has low self-purification capacity; flow augmentation has little effect on the existing load. Hence, the level of treatment required to increase. After the introduction of outfalling drain D13-D16, a sag of DO has been observed; to improve the DO concentration, external aeration is suggested before wastewater disposal into the river. The study is a novel effort to manage the river quality by developing scenarios, including the level of treatments and flow augmentation, and keeping up the desired DO concentration assigned for this river reach.

The presence of organic matter in lakes profoundly impacts drinking water supplies, yet treatment processes involving coagulants and disinfectants can yield carcinogenic disinfection by-products. Traditional assessments of organic matter, such as chemical oxygen demand (CODMn) and biochemical oxygen demand (BOD5), are often time-consuming. Alternatively, optical measurements of dissolved organic matter (DOM) offer a rapid and reliable means of obtaining organic matter composition data. Here we employed DOM optical measurements in conjunction with parallel factor analysis to scrutinize CODMn and BOD5 variability. Validation was performed using an independent dataset encompassing six lakes on the Yungui Plateau from 2014 to 2016 (n = 256). Leveraging multiple linear regressions (MLRs) applied to DOM absorbance at 254 nm (a254) and fluorescence components C1-C5, we successfully traced CODMn and BOD5 variations across the entire plateau (68 lakes, n = 271, R2 > 0.8, P < 0.0001). Notably, DOM optical indices yielded superior estimates (higher R2) of CODMn and BOD5 during the rainy season compared to the dry season and demonstrated increased accuracy (R2 > 0.9) in mesotrophic lakes compared to oligotrophic and eutrophic lakes. This study underscores the utility of MLR-based DOM indices for inferring CODMn and BOD5 variability in plateau lakes and highlights the potential of integrating in situ and remote sensing platforms for water pollution early warning.

Biocomposite films from renewable sources are seen to be viable candidates as sustainable, zero-waste packaging materials. In this study, biocomposites films using chitosan and alginate as matrices, and pristine or acetylated cellulose nanocrystals (CNCs) as reinforcement agents, were fabricated, thoroughly characterized in terms of structure (with ATR-FTIR and XRD), morphology (SEM), thermal stability (TGA coupled with FTIR), water content and solubility and mechanical properties and subjected to controlled biological degradation in aqueous environment with added activated sludge. Biodegradation activity was followed through respirometry by measurement of change in partial O2 pressure using OxiTop® system. While the initial rate of biodegradation is higher in chitosan-based films with incorporated CNCs (both pristine and modified) compared to any other tested biocomposites, it was observed that chitosan-based films are not completely degradable in activated sludge medium, whereas alginate-based films reached complete biodegradation in 107 h to 112 h. Additional study of the aqueous medium with in situ FTIR during biodegradation offered an insight into biodegradation mechanisms. Use of advanced statistical methods indicated that selection of material (ALG vs CH) has the highest influence on biodegradability, followed by solubility of the material and its thermal stability.

Biochemical oxygen demand (BOD) is one of the most important water/wastewater quality parameters. BOD5 is the amount of oxygen consumed in 5 days by microorganisms that oxidize biodegradable organic materials in an aerobic biochemical manner. The primary objective of this research is to apply microbial fuel cells (MFCs) to reduce the time requirement of BOD5 measurements. An artificial neural network (ANN) has been created, and the predictions we obtained for BOD5 measurements were carried out within 6-24 h with an average error of 7%. The outcomes demonstrated the viability of our AI MFC/BES BOD5 sensor in real-life scenarios.

Biochemical oxygen demand (BOD) is one of the most important parameters used for water quality assessment. Alternative methods are essential for accurately prediction of this parameter because the traditional method in predicting the BOD is time-consuming and it is inaccurate due to inconstancies in microbial multiplicity. In this study, the applicability of four hybrid neuro-fuzzy (ANFIS) methods, ANFIS with genetic algorithm (GA), ANFIS with particle swarm optimization (PSO), ANFIS with sine cosine algorithm (SCA), and ANFIS with marine predators algorithm (MPA), was investigated in predicting BOD using distinct input combinations such as potential of hydrogen (pH), dissolved oxygen (DO), electrical conductivity (EC), water temperature (WT), suspended solids (SS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (T-P) acquired from two river stations, Gongreung and Gyeongan, South Korea. The applicability of multi-variate adaptive regression spline (MARS) in determination of the best input combination was examined. The ANFIS-MPA was found to be the best model with the lowest root mean square error and mean absolute error and the highest determination coefficient. It improved the root mean square error of ANFIS-PSO, ANFIS-GA, and ANFIS-SCA models by 13.8%, 12.1%, and 6.3% for Gongreung Station and by 33%, 25%, and 6.3% for Gyeongan Station in the test stage, respectively.

Microbial electrochemical sensors are promising to monitor bioavailable organics in real environments, but their application is restricted by the unpredictable performance of the electroactive biofilm (EAB), which is randomly acclimated from environmental microflora. With a long-term stable EAB as a template, we successfully designed EAB (DEAB) by the sequential growth of Geobacter anodireducens and automatched microbes, achieving a reproducible high current than those naturally acclimated from wastewater (NEAB). Pre-inoculation of planktonic aerobes as oxygen bioscavengers was necessary to ensure the colonization of Geobacter in the inner layer, and the abundant Geobacter (50%) in DEAB guaranteed 4 times higher current density with a 15-fold smaller variation among 20 replicates than those of NEAB. The sensor constructed with DEAB exhibited a shorter measuring time and a precise biochemical oxygen demand (BOD) measurement with acetate, real domestic wastewater, and supernatant of anaerobic digestion. Here, we for the first time proposed an applicable strategy to standardize EABs for BOD sensors, which is also crucial to ensure a stable performance of all bioelectrochemical technologies.

Biochemical oxygen demand (BOD) is a water quality parameter of vital importance. Rapid BOD analysis methods have emerged to simplify the five-day BOD (BOD5) measurement protocol. However, their universal implementations are restricted by the tricky environmental matrix (including environmental microbes, contaminants, ionic compositions, etc.). Here, an in situ and self-adaptive BOD bioreaction sensing system consisting of a \"gut-like\" microfluidic coil bioreactor with self-renewed biofilm was proposed for the establishment of a rapid, resilient and reliable BOD determination method. With the spontaneous surface adhesion of environmental microbial populations, the biofilm was colonized in situ on the inner surface of the microfluidic coil bioreactor. Exploiting the environmental domestication during every real sample measurement, the biofilm was capable of self-renewal to adapt to the environmental changes and exhibited representative biodegradation behaviors. The aggregated abundant, adequate and adapted microbial populations in the BOD bioreactor rendered a total organic carbon (TOC) removal rate of 67.7% within a short hydraulic retention time of 99 s. As validated by an online BOD prototype, exceptional analytical performance was achieved in terms of reproducibility (relative standard deviation of 3.7%), survivability (inhibition by pH and metal ion interference of <20%) and accuracy (relative error of -5.9% to 9.7%). This work rediscovered the interactive effects of the environmental matrix on BOD assays and demonstrated an instructive attempt by making use of the environment to develop practical online BOD monitoring devices for water quality assessments.