Methods for assessing biochemical oxygen demand (BOD): a review

Assessing river water quality for ecological risk in the context of a decaying river in India

The decay of rivers and river water pollution are common problems worldwide. However, many works have been performed on decaying rivers in India, and the status of the water quality is still unknown in Jalangi River. To this end, the present study intends to examine the water quality of the Jalangi River to assess ecological status in both the spatial and seasonal dimensions. To depict the spatiality of ecological risks, 34 water samples were collected from the source to the sink of the Jalangi River with an interval of 10 km while 119 water samples were collected from a secondary source during 2012-2022 to capture the seasonal dynamics. In this work, the seasonality and spatiality of change in the river's water quality have been explored. This study used the eutrophication index (EI), organic pollution index (OPI), and overall index of pollution (OIP) to assess the ecological risk. The results illustrated that the values of OPI range from 7.17 to 588, and the values of EI exceed the standard of 1, indicating the critical situation of the ecological status of Jalangi River. The value of OIP ranges between 2.67 and 3.91 revealing the slightly polluted condition of the river water. The study signified the ecological status of the river is in a critical situation due to elevated concentrations of biological oxygen demand, chemical oxygen demand, and low concentrations of dissolved oxygen. The present study found that stagnation of water flow in the river, primarily driven by the eastward tilting of the Bengal basin, triggered water pollution and ecological risk. Moreover, anthropogenic interventions in the form of riverbed agriculture and the discharge of untreated sewage from urban areas are playing a crucial role in deteriorating the water quality of the river. This decay needs substantial attention from the various stakeholders in a participatory manner.

Targeted Formation of Biofilms on the Surface of Graphite Electrodes as an Effective Approach to the Development of Biosensors for Early Warning Systems

Biofilms based on bacteria Pseudomonas veronii (Ps. veronii) and Escherichia coli (E. coli) and yeast Saccharomyces cerevisiae (S. cerevisiae) were used for novel biosensor creation for rapid biochemical oxygen demand (BOD) monitoring. Based on the electrochemical measurement results, it was shown that the endogenous mediator in the matrix of E. coli and Ps. veronii biofilms and ferrocene form a two-mediator system that improves electron transport in the system. Biofilms based on Ps. veronii and E. coli had a high biotechnological potential for BOD assessment; bioreceptors based on such biofilms had high sensitivity (the lower limits of detectable BOD5 concentrations were 0.61 (Ps. veronii) and 0.87 (E. coli) mg/dm3) and high efficiency of analysis (a measurement time 5-10 min). The maximum biosensor response based on bacterial biofilms has been observed in the pH range of 6.6-7.2. The greatest protective effect was found for biofilms based on E. coli, which has high long-term stability (151 days for Ps. veronii and 163 days for E. coli). The results of the BOD5 analysis of water samples obtained using the developed biosensors had a high correlation with the results of the standard 5-day method (R2 = 0.9820, number of tested samples is 10 for Ps. veronii, and R2 = 0.9862, number of tested samples is 10 for E. coli). Thus, biosensors based on Ps. veronii biofilms and E. coli biofilms could be a novel analytical system to give early warnings of pollution.

Hydrological regimes and water quality variations in the Yangtze River basin from 1998 to 2018

Understanding the long-term variations in basins that undergo large-scale hydroelectric projects is crucial for effective dam operation and watershed management. In this study, comprehensive analyses were conducted on a dataset spanning over 20 years (1998-2018) of hydrological regime and physicochemical parameters from the Yangtze River basin to evaluate the potential impacts of the Three Gorges Dam. Water level significantly increased from 128.75±58.18 m in 2002 to 136.78±55.05 m in 2005, and the mean flow velocity significantly decreased from 2004 to 2010. However, no significant change in the flow was observed in the basin. Meanwhile, remarkable fluctuations in physicochemical parameters, including dissolved oxygen, chemical oxygen demand, conductivity, hardness, and alkalinity, were mainly observed during impoundment (2003-2009). After that, the above parameters tended to stabilize, and some even returned to their original levels. The dam's retention effect significantly reduced the suspended solids (SS) in both up- and downstream, to only one-third of the pre-operation level. And total phosphorus and chemical oxygen demand also significantly decreased with the decline of SS. Particularly, ammonium also showed a significant downward trend, with the up- and downstream of the dam falling by 36.8 % and 26.1 %, respectively. However, the increasing total nitrogen (7.5 % and 20.0 % up- and downstream of the dam, respectively) still threatened the water quality of the basin, especially in the estuaries. Additionally, the significant decline in dissolved oxygen downstream (from 8.53±1.08 mg/L to 8.11±1.36 mg/L) also exacerbated the hypoxia in the Yangtze River estuary. The results demonstrated the long-term impact of the construction of the Three Gorges Dam on the environmental elements of the Yangtze River basin, which provides reference data and guidance for the construction of big dams in major rivers in the future.

Measuring effect of mutations & conditions on microbial respiratory rates

Cellular respiration is central to a wide range of cellular processes. In microorganisms, the effect of a mutation or an environmental condition on the rate of respiration is usually determined by measuring oxygen consumption in the media. We describe this method and discuss caveats and controls for the method.

Recent Developments and Applications of Microbial Electrochemical Biosensors

This chapter provides a comprehensive overview of microbial electrochemical biosensors, which are a unique class of biosensors that utilize the metabolic activity of microorganisms to convert chemical signals into electrical signals. The principles and mechanisms of these biosensors are discussed, including the different types of microorganisms that can be used. The various applications of microbial electrochemical biosensors in fields such as environmental monitoring, medical diagnostics, and food safety are also explored. The chapter concludes with a discussion of future research directions and potential advancements in the field of microbial electrochemical biosensors.

Purification mechanism of microbial metabolism in kitchen-oil wastewater enhanced by cationic vacancies on γ-Al2O3

The use of catalyst materials to mediate the enhancement of microbial degradation in wastewater is a new economic and energy saving breakthrough in water treatment technology. In this study, γ-Al2O3, which is commonly used as catalyst/carrier, is used as biological filler to treat kitchen-oil wastewater with low biodegradability, and the COD removal rate is about 50 %. It is found that the complexation of cationic vacancies on Al2O3 surface with extracellular polymeric substance (EPS) secreted by microorganisms in wastewater lead to the polarization of electron distribution on biofilm. The efficient degrading bacteria are enriched on reaction interface and obtain electrons to maintain electron dynamic balance by enhancing the transmembrane metabolism of pollutants. The aluminum vacancies on Al2O3 surface accelerate the microbial degradation of pollutants. The cationic vacancies in the structure of catalyst accelerate the acquisition of exogenous electrons by microorganisms without the addition of external energy, which provides a new idea for catalytic fillers to enhance wastewater degradation.

Instant water toxicity detection based on magnetically-constructed electrochemically active biofilm

Water toxicity determination with electrochemically active bacteria (EAB) is promising in the early warning of water pollution. However, limited by tedious biofilm formation, natural EAB biofilms are uncapable of the instant detection of water toxicity, resulting in the failure for the emergency monitoring of water pollution. To solve this problem, a novel method for the rapid construction of EAB biofilms using magnetic adsorption was established, and the performance of instant water toxicity detection with magnetically-constructed EAB biofilm was investigated. The results demonstrate that EAB biofilms were magnetically constructed in less than 30 min, and magnetically-constructed EAB biofilm generated stable currents even under continuous flow conditions. Magnetically-constructed EAB biofilms realized instant water toxicity detection, and the sensitivity increased with the decrease of magnetic field intensity. Low magnetic field intensity resulted in a loose biofilm structure, which is conducive to toxic pollutant penetration. The detection limit for Cu2+, phenol, and Cd2+ achieved 0.07 mg/L with optimal magnetic field intensity, and the detection time was less than 30 min. This study broadens the application of water toxicity determination with EAB, and establishes a foundation for the instant and continuous detection of water toxicity with EAB.

Wastewater-based epidemiology for tracking bacterial diversity and antibiotic resistance in COVID-19 isolation hospitals in Qatar

BACKGROUND

Hospitals are hotspots for antimicrobial resistance genes (ARGs), and play a significant role in their emergence and spread. Large numbers of ARGs will be ejected from hospitals via wastewater systems. Wastewater-based epidemiology has been consolidated as a tool to provide real-time information, and represents a promising approach to understanding the prevalence of bacteria and ARGs at community level.

AIMS

To determine bacterial diversity and identify ARG profiles in hospital wastewater pathogens obtained from coronavirus disease 2019 (COVID-19) isolation hospitals compared with non-COVID-19 facilities during the pandemic.

METHODS

Wastewater samples were obtained from four hospitals: three assigned to patients with COVID-19 patients and one assigned to non-COVID-19 patients. A microbial DNA quantitative polymerase chain reaction was used to determine bacterial diversity and ARGs.

FINDINGS

The assay recorded 27 different bacterial species in the samples, belonging to the following phyla: Firmicutes (44.4%), Proteobacteria (33.3%), Actinobacteria (11%), Bacteroidetes (7.4%) and Verrucomicrobiota (3.7%). In addition, 61 ARGs were detected in total. The highest number of ARGs was observed for the Hazem Mebaireek General Hospital (HMGH) COVID-19 patient site (88.5%), and the lowest number of ARGs was found for the HMGH non-patient site (24.1%).

CONCLUSION

The emergence of contaminants in sewage water, such as ARGs and high pathogen levels, poses a potential risk to public health and the aquatic ecosystem.

Rapid Method of Wastewater Classification by Electronic Nose for Performance Evaluation of Bioreactors with Activated Sludge

Currently, e-noses are used for measuring odorous compounds at wastewater treatment plants. These devices mimic the mammalian olfactory sense, comprising an array of multiple non-specific gas sensors. An array of sensors creates a unique set of signals called a "gas fingerprint", which enables it to differentiate between the analyzed samples of gas mixtures. However, appropriate advanced analyses of multidimensional data need to be conducted for this purpose. The failures of the wastewater treatment process are directly connected to the odor nuisance of bioreactors and are reflected in the level of pollution indicators. Thus, it can be assumed that using the appropriately selected methods of data analysis from a gas sensors array, it will be possible to distinguish and classify the operating states of bioreactors (i.e., phases of normal operation), as well as the occurrence of malfunction. This work focuses on developing a complete protocol for analyzing and interpreting multidimensional data from a gas sensor array measuring the properties of the air headspace in a bioreactor. These methods include dimensionality reduction and visualization in two-dimensional space using the principal component analysis (PCA) method, application of data clustering using an unsupervised method by Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, and at the last stage, application of extra trees as a supervised machine learning method to achieve the best possible accuracy and precision in data classification.

Impact of atmospheric pressure variations on aerobic biodegradation test

Biodegradation rate is an important index to evaluate the environmental risk of chemicals, which is usually determined by measuring oxygen consumption through respirometer in a biodegradation test. However, atmospheric pressure variations affect reactor oxygen concentration and oxygen volume recorded by respirometer in biodegradation test, and the parameters of reactor volume and test material amount amplify its effect. Atmospheric pressure variation >1 kPa could introduce >20% underestimation in biodegradation rate when a small amount of test material (0.04-0.2 g per 100 g of inoculum) and high reactor volume (2-4 L) were used according to the international standards. A 5 kPa drop in atmospheric pressure leads to a 6% decrease in headspace oxygen concentration in the reactor, which could subsequently inhibit biodegradation microbials and decrease the biodegradation rate by 30%. Moreover, the biodegradation process (oxygen consumption rate) could be accelerated/delayed several times by atmospheric pressure variations compared to the process without variations when the oxygen consumption rate was <5 mL h-1 in a 0.5 or 1 L reactor and <10 mL h-1 in a 2-L reactor. Mitigating the effects of atmospheric pressure variations on biodegradation test includes lowering the reactor volume, increasing the test material amount and recording atmospheric pressure for further modification.

A Two-Mediator System Based on a Nanocomposite of Redox-Active Polymer Poly(thionine) and SWCNT as an Effective Electron Carrier for Eukaryotic Microorganisms in Biosensor Analyzers

Electropolymerized thionine was used as a redox-active polymer to create a two-mediated microbial biosensor for determining biochemical oxygen demand (BOD). The electrochemical characteristics of the conducting system were studied by cyclic voltammetry and electrochemical impedance spectroscopy. It has been shown that the most promising in terms of the rate of interaction with the yeast B. adeninivorans is the system based on poly(thionine), single-walled carbon nanotubes (SWCNT), and neutral red (kint = 0.071 dm3/(g·s)). The biosensor based on this system is characterized by high sensitivity (the lower limit of determined BOD concentrations is 0.4 mgO2/dm3). Sample analysis by means of the developed analytical system showed that the results of the standard dilution method and those using the biosensor differed insignificantly. Thus, for the first time, the fundamental possibility of effectively using nanocomposite materials based on SWCNT and the redox-active polymer poly(thionine) as one of the components of two-mediator systems for electron transfer from yeast microorganisms to the electrode has been shown. It opens up prospects for creating stable and highly sensitive electrochemical systems based on eukaryotes.

Microbial Fuel Cell-Based Organic Matter Sensors: Principles, Structures and Applications

Wastewater contains a significant quantity of organic matter, continuously causing environmental pollution. Timely and accurate detection of organic content in water can facilitate improved wastewater treatment and better protect the environment. Microbial fuel cells (MFCs) are increasingly recognized as valuable biological monitoring systems, due to their ability to swiftly detect organic indicators such as biological oxygen demand (BOD) and chemical oxygen demand (COD) in water quality. Different types of MFC sensors are used for BOD and COD detection, each with unique features and benefits. This review focuses on different types of MFC sensors used for BOD and COD detection, discussing their benefits and structural optimization, as well as the influencing factors of MFC-based biomonitoring systems. Additionally, the challenges and prospects associated with the development of reliable MFC sensing systems are discussed.

Water quality assessment for organic matter load in urban rivers considering land cover dynamics

The strategy of considering a model that is comparable to the Soil Conservation Service Curve-Number (SCS-CN) method that employs land use maps to estimate the effects of land use on the water quality has considerable potential for application. This paper presents the LUPC (Land Use Pollutant Contribution) Model to estimate water pollution from the watershed land use obtained by satellite image classification (Sentinel-2). It defines that each land use produces a specific pollutant load per unit area, called Pollutant Standard Index (PSI), which undergoes degradation and/or retention until it reaches the river. This decay estimate is based on a Kernel Function. Organic matter (OM) was the pollutant chosen for the definition of the LUPC model and fractions of labile and refractory organic matter (LOM, ROM). The model was applied to the Barigüi River basin, and five samples were collected at 12 points along the river. Water quality parameters such as dissolved organic carbon (DOC) and UV-Visible absorbance in addition to chemical and biological oxygen demand (COD and BOD), dissolved oxygen (DO), and nitrogen and phosphorus fractions were the reference for modeling purposes. The results indicate that organic loads can be estimated from watershed characteristics, despite influence from seasonal influences captured by the PSI values and the basin shape parameter. Considering its versatile response, the LUPC model can be used for integrated water resources and land use planning and management and be indicator of the potential pollution of rivers by OM.

Monitor water quality through retrieving water quality parameters from hyperspectral images using graph convolution network with superposition of multi-point effect: A case study in Maozhou River

Quantitative prediction by unmanned aerial vehicle (UAV) remote sensing on water quality parameters (WQPs) including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a (Chl-a), total suspended solids (TSS), and turbidity provides a flexible and effective approach to monitor the variation in water quality. In this study, a deep learning-based method integrating graph convolution network (GCN), gravity model variant, and dual feedback machine involving parametric probability analysis and spatial distribution pattern analysis, named Graph Convolution Network with Superposition of Multi-point Effect (SMPE-GCN) has been developed to calculate concentrations of WQPs through UAV hyperspectral reflectance data on large scale efficiently. With an end-to-end structure, our proposed method has been applied to assisting environmental protection department to trace potential pollution sources in real time. The proposed method is trained on a real-world dataset and its effectiveness is validated on an equal amount of testing dataset with respect to three evaluation metrics including root of mean squared error (RMSE), mean absolute percent error (MAPE), and coefficient of determination (R²). The experimental results demonstrate that our proposed model achieves better performance in comparison with state-of-the-art baseline models in terms of RMSE, MAPE, and R². The proposed method is applicable for quantifying seven various WQPs and has achieved good performance for each WQP. The resulting MAPE ranges from 7.16% to 10.96% and R² ranges from 0.80 to 0.94 for all WQPs. This approach brings a novel and systematic insight into real-time quantitative water quality monitoring of urban rivers, and provides a unified framework for in-situ data acquisition, feature engineering, data conversion, and data modeling for further research. It provides fundamental support to assist environmental managers to efficiently monitor water quality of urban rivers.

From the problem to the solution: Chitosan valorization cycle

The problem of fisheries waste has increased in recent years and has become a global problem influenced by various biological, technical, operational and socioeconomic factors. In this context, the use of these residues as raw materials is a proven approach not only to reduce the crisis of unprecedented magnitude facing the oceans, but also to improve the management of marine resources and increase the competitiveness of the fisheries sector. However, the implementation of valorization strategies at the industrial level is being excessively slow, despite this great potential. Chitosan, a biopolymer extracted from shellfish waste, is a clear example of this because although countless chitosan-based products have been described for a wide variety of applications, commercial products are still limited. To address this drawback, it is essential to consolidate a "bluer" chitosan valorization cycle towards sustainability and circular economy. In this perspective we wanted to focus on the cycle of valorization of chitin, which allows to transform a waste product (chitin) into a material suitable for the development of useful products to solve the source of its origin as a waste product and pollutant; chitosan-based membranes for wastewater remediation.

Self-purification of actual wastewater via microbial-synergy driving of catalyst-surface microelectronic field: A pilot-scale study

High energy consumption is impedimental for eliminating refractory organics in wastewater by current technologies. Herein, we develop an efficient self-purification process for actual non-biodegradable dyeing wastewater at pilot scale, using N-doped graphene-like (CN) complexed Cu-Al₂O₃ supported Al₂O₃ ceramics (HCLL-S8-M) fixed-bed reactor without additional input. About 36% chemical oxygen demand removal was achieved within 20 min empty bed retention time and maintained stability for almost one year. The HCLL-S8-M structure feature and its interface on microbial community structure, functions, and metabolic pathways were analyzed by density-functional theory calculation, X-ray photoelectron spectroscopy, multiomics analysis of metagenome, macrotranscriptome and macroproteome. On the surface of HCLL-S8-M, a strong microelectronic field (MEF) was formed by the electron-rich/poor area due to Cu-π interaction from the complexation between phenolic hydroxy of CN and Cu species, driving the electrons of the adsorbed dye pollutants to the microorganisms through extracellular polymeric substance and the direct transfer of extracellular electrons, causing their degradation into CO₂ and intermediates, which was degraded partly via intracellular metabolism. The lower energy feeding for the microbiome produced less adenosine triphosphate, resulting in little sludge throughout reaction. The MEF from electronic polarization is greatly potential to develop low-energy wastewater treatment technology.

Mitigation of phytotoxic effect of compost by application of optimized aqueous extraction protocols

The abuse of chemical fertilizers in recent decades has led the promotion of less harmful alternatives, such as compost or aqueous extracts obtained from it. Therefore, it is essential to develop liquid biofertilizers, which in addition of being stable and useful for fertigation and foliar application in intensive agriculture had a remarkable phytostimulant extracts. For this purpose, a collection of aqueous extracts was obtained by applying four different Compost Extraction Protocols (CEP1, CEP2, CEP3, CEP4) in terms of incubation time, temperature and agitation of compost samples from agri-food waste, olive mill waste, sewage sludge and vegetable waste. Subsequently, a physicochemical characterization of the obtained set was performed in which pH, electrical conductivity and Total Organic Carbon (TOC) were measured. In addition, a biological characterization was also carried out by calculating the Germination Index (GI) and determining the Biological Oxygen Demand (BOD₅). Furthermore, functional diversity was studied using the Biolog EcoPlates technique. The results obtained confirmed the great heterogeneity of the selected raw materials. However, it was observed that the less aggressive treatments in terms of temperature and incubation time, such as CEP1 (48 h, room temperature (RT)) or CEP4 (14 days, RT), provided aqueous compost extracts with better phytostimulant characteristics than the starting composts. It was even possible to find a compost extraction protocol that maximize the beneficial effects of compost. This was the case of CEP1, which improved the GI and reduced the phytotoxicity in most of the raw materials analyzed. Therefore, the use of this type of liquid organic amendment could mitigate the phytotoxic effect of several composts being a good alternative to the use of chemical fertilizers.

In situ and self-adaptive BOD bioreaction sensing system based on environmentally domesticated microbial populations

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.

Huge anthropogenic microbial load during southwest monsoon season in coastal waters of Kakinada, Bay of Bengal

To examine the influence of anthropogenic activities on the marine ecosystem near the coastal waters of the port city, Kakinada, a study was conducted to investigate the abundance of heterotrophic, indicator and pathogenic bacteria during the spring inter monsoon (SIM) and southwest monsoon (SWM) seasons. A drastic change in the marine bacteria due to the input of allochthonous bacteria during SWM was noticed. An order of magnitude higher abundance of indicators (Escherichia coli and Enterococcus faecalis) and bacterial pathogens (Proteus mirabilis and Pseudomonas aeruginosa) was observed during SWM. In contrast, Chlorophyll-a, heterotrophic bacterial abundance, Aeromonas hydrophila and Klebsiella pneumoniae were higher during SIM. A significant increase in some of the indicator and pathogenic bacterial abundance due to moderate rainfall suggests that the improper drainage system in the city could spread these bacteria, posing a considerable threat to both environment and human health.

Enhanced purification of kitchen-oil wastewater driven synergistically by surface microelectric fields and microorganisms

The stable structure and toxic effect of refractory organic pollutants in wastewater lead to the problem of high energy consumption in water treatment technology. Herein, we propose a synergistic purification of refractory wastewater driven by microorganisms and surface microelectric fields (SMEF) over a dual-reaction-center (DRC) catalyst HCLL-S8-M prepared by an in situ growth method of carbon nitride on the Cu-Al₂O₃ surface. Characterization techniques demonstrate the successful construction of SMEF with strong electrostatic force over HCLL-S8-M based on cation-π interactions between metal copper ions and carbon nitride rings. With the catalyst as the core filler, an innovative fixed bed bioreactor is constructed to purify the actual kitchen-oil wastewater. The removal efficiency of the wastewater even with a very low biodegradability (BOD₅/COD = 0.33) can reach 60% after passing through this bioreactor. An innovative reaction mechanism is revealed for the first time that under the condition of a small amount of biodegradable organic matter, the SMEF induces the enrichment of electric active microorganisms (Desulfobulbus and Geobacter) in the wastewater, accelerates the interspecies electron transfer of intertrophic metabolism with the biodegradable bacteria through the extracellular electron transfer mechanism such as cytochrome C and self-secreted electron shuttle. The electrons of the refractory organic pollutants adsorbed on the surface of the catalyst are delocalized by the SMEF, which can be directly utilized by microorganisms through EPS conduction. The SMEF generated by electron polarization can maximize the utilization of pollutants and microorganisms in wastewater and further enhance degradation without adding any external energy, which is of great significance to the development of water self-purification technology.

Relationship, importance, and development of analytical techniques: COD, BOD, and, TOC in water—An overview through time

Analytical techniques to measure organic matter in water, such as Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5), and Total Organic Carbon (TOC) are widely used. Modifications have been proposed to make them faster, more sensitive, and more environmentally friendly. The purpose of producing a review over some time is to show the changes made on the standardized methods of each of these techniques, and to highlight the relationship between them in the process of ascertaining organic matter in water. Modifications to techniques COD and BOD entail several factors that need to be considered, namely: time, miniaturization, sensitivity, use of environmentally friendly reagents. Changes to TOC are focused on detection systems. Despite the advantages obtained by the modified techniques, traditional methods continue to be widely used, in most cases due to the lack of standardization of the new methods.

Graphic Abstract

Design, optimization and application of a highly sensitive microbial electrolytic cell-based BOD biosensor

Biochemical oxygen demand (BOD) is an important biochemical indicator for determining the degree of water pollution and guiding the design of wastewater treatment processes. BOD sensors based on microbial electrochemical technology can conduct real-time online monitoring of organic matter and have attracted extensive attention. However, research on microbial electrolytic cell (MEC)-type BOD sensors is at the stage of theoretical exploration. Here, we designed and optimized a highly sensitive MEC-type BOD sensor by screening inoculants, comparing electrode materials, and optimizing the reactor configuration. The results showed that effective means to optimize a BOD sensor for fast activation and sensitive testing included the inoculation of the MEC reactor effluent with large amounts of biomass and highly active bacteria, selection of carbon felt electrodes with excellent adsorption and permeability, miniaturization of the reactor, regulation of suitable electrode spacing, and design of the penetrating fluid structure. Then, the optimized sensing system was applied to determine the BOD concentration in model solutions of sodium acetate in a laboratory environment, where it accurately measured BOD concentrations in the range of 10-500 mg/L and maintained good parallelism during long-term operation. Next, the MEC-type BOD sensors were put into practice in the field as an alarm for accidents at an actual sewage plant. The whole BOD sensing system was quickly assembled on site and started up, and it gave an early warning shortly after the concentration of organic matter in the water suddenly increased, thus showing a high potential for engineering applications. This study broadened the domains of application of MEC-type BOD sensors in environmental monitoring, and promoted the development of technological innovation in water ecology and environmental monitoring.

Nocardioides palaemonis sp. nov. and Tessaracoccus palaemonis sp. nov., isolated from the gastrointestinal tract of lake prawn

Two novel Gram-stain-positive, non-motile and non-spore-forming bacterial strains, designated J2M5^T and J1M15^T, were isolated from the gastrointestinal tract of a lake prawn Palaemon paucidens. Strain J2M5^T was an obligately aerobic bacterium that formed milky-coloured colonies and showed a rod-coccus cell cycle, while strain J1M15^T was a facultatively aerobic bacterium that formed orangish-yellow-coloured colonies and showed rod-shaped cells. Strains J2M5^T and J1M15^T showed the highest 16S rRNA gene sequence similarity to Nocardioides ganghwensis JC2055^T (98.63 %) and Tessaracoccus flavescens SST-39^T (98.08 %), respectively. The whole-genome sequence of strain J2M5^T was 4.52 Mbp in size and the genomic G+C content directly calculated from the genome sequence of strain J2M5^T was 72.5 mol%. The whole-genome sequence of strain J1M15^T was 3.20 Mbp in size and the genomic G+C content directly calculated from the genome sequence of strain J1M15^T was 69.6mol %. Strains J2M5^T and J1M15^T showed high OrthoANI similarity to N. ganghwensis JC2055^T (83.6 %) and T. flavescens (77.2 %), respectively. We analysed the genome sequences of strains J2M5^T and J1M15^T in terms of carbohydrate-active enzymes, antibiotic resistance genes and virulence factor genes. Strains J2M5^T and J1M15^T contained MK-8 (H₄) and MK-9 (H₄) as the predominant respiratory quinones, respectively. The major polar lipids of both strains were phosphatidylglycerol and diphosphatidylglycerol. Additionally, strain J2M5^T possessed phosphatidylcholine, phosphatidylserine and phosphatidylethanolamine. The cellular sugar components of strain J2M5^T were ribose, mannose, glucose and galactose, and its cellular amino acid components were l-alanine and l-lysine. The cellular sugar components of strain J1M15^T were rhamnose, ribose, mannose and glucose, and its cellular amino acid component was l-alanine. The major cellular fatty acids of strains J2M5^T and J1M15^T were iso-C_{16 : 0} and anteiso-C_15 : 0, respectively. The multiple taxonomic analyses indicated that strains J2M5^T and J1M15^T represent novel species of the genus Nocardioides and Tessaracoccus, respectively. We propose the names Nocardioides palaemonis sp. nov. and Tessaracoccus palaemonis sp. nov. for strain J2M5^T (=KCTC 49461^T=CCUG 74767^T) and strain J1M15^T (=KCTC 49462^T=CCUG 74766^T), respectively.

Microbial Biosensors for Rapid Determination of Biochemical Oxygen Demand: Approaches, Tendencies and Development Prospects

One of the main indices of the quality of water is the biochemical oxygen demand (BOD). A little over 40 years have passed since the practical application of the first microbial sensor for the determination of BOD, presented by the Japanese professor Isao Karube. This time span has brought new knowledge to and practical developments in the use of a wide range of microbial cells based on BOD biosensors. At present, this field of biotechnology is becoming an independent discipline. The traditional BOD analysis (BOD₅) has not changed over many years; it takes no less than 5 days to carry out. Microbial biosensors can be used as an alternative technique for assessing the BOD attract attention because they can reduce hundredfold the time required to measure it. The review examines the experience of the creation and practical application of BOD biosensors accumulated by the international community. Special attention is paid to the use of multiple cell immobilization methods, signal registration techniques, mediators and cell consortia contained in the bioreceptor. We consider the use of nanomaterials in the modification of analytical devices developed for BOD evaluation and discuss the prospects of developing new practically important biosensor models.

A watershed water quality prediction model based on attention mechanism and Bi-LSTM

Accurate prediction of water quality contributes to the intelligent management and control of watershed ecology. Water Quality data has time series characteristics, but the existing models only focus on the forward time series when LSTM is introduced and do not consider the effect of the reverse time series on the model. Also did not take into account the different contributions of water quality sequences to the model at different moments. In order to solve this problem, this paper proposes a watershed water quality prediction model called AT-BILSTM. The model mainly contains a Bi-LSTM layer and a temporal attention layer and introduces an attention mechanism after bidirectional feature extraction of water quality time series data to highlight the data series that have a critical impact on the prediction results. The effectiveness of the method was verified with actual datasets from four monitoring stations in Lanzhou section of the Yellow River basin in China. After comparing with the reference model, the results show that the proposed model combines the bidirectional nonlinear mapping capability of Bi-LSTM and the feature weighting feature of the attention mechanism. Taking Fuhe Bridge as an example, compared with the original LSTM model, the RMSE and MAE of the model are reduced to 0.101 and 0.059, respectively, and the R2 is improved to 0.970, which has the best prediction performance among the four cross-sections and can provide a decision basis for the comprehensive water quality management and pollutant control in the basin.

Water quality drives the distribution of freshwater cable bacteria

Cable bacteria are a group of recently found filamentous sulfide-oxidizing Desulfobulbaceae that significantly impact biogeochemical cycling. However, the limited understanding of cable bacteria distribution patterns and the driving force hindered our abilities to evaluate and maximize their contribution to environmental health. We evaluated cable bacteria assemblages from ten river sediments in the Pearl River Delta, China. The results revealed a clear biogeographic distribution pattern of cable bacteria, and their communities were deterministically assembled through water quality-driven selection. Cable bacteria are diverse in the river sediments with a few generalists and many specialists, and the water quality IV and V environments are the "hot spot." We then provided evidence on their morphology, function, and genome to demonstrate how water quality might shape the cable bacteria assemblages. Reduced cell width, inhibited function, and water quality-related adaptive genomic traits were detected in sulfide-limited water quality III and contaminant-stressed water quality VI environments. Specifically, those genomic traits were contributed to carbon and sulfur metabolism in the water quality III environment and stress resistance in the water quality VI environment. Overall, these findings provided a helpful baseline in evaluating the contribution of cable bacteria in the freshwater ecosystem and suggested that their high diversity and flexibility in phylogeny, morphology, and genome allowed them to adapt and contribute to various environmental conditions.

The Use of Yeast in Biosensing

Yeast has been used as a model for several diseases as it is the simplest unicellular eukaryote, safe and easy to culture and harbors most of the fundamental processes that are present in almost all higher eukaryotes, including humans. From understanding the pathogenesis of disease to drug discovery studies, yeast has served as an important biosensor. It is not only due to the conservation of genetics, amenable modification of its genome and easily accessible analytical methods, but also some characteristic features such as its ability to survive with defective mitochondria, making it a highly flexible microbe for designing whole-cell biosensing systems. The aim of this review is to report on how yeasts have been utilized as biosensors, reporting on responses to various stimuli.

Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction

As an indicator measured by incubating organic material from water samples in rivers, the most typical characteristic of water quality items is biochemical oxygen demand (BOD₅) concentration, which is a stream pollutant with an extreme circumstance of organic loading and controlling aquatic behavior in the eco-environment. Leading monitoring approaches including machine leaning and deep learning have been evolved for a correct, trustworthy, and low-cost prediction of BOD₅ concentration. The addressed research investigated the efficiency of three standalone models including machine learning (extreme learning machine (ELM) and support vector regression (SVR)) and deep learning (deep echo state network (Deep ESN)). In addition, the novel double-stage synthesis models (wavelet-extreme learning machine (Wavelet-ELM), wavelet-support vector regression (Wavelet-SVR), and wavelet-deep echo state network (Wavelet-Deep ESN)) were developed by integrating wavelet transformation (WT) with the different standalone models. Five input associations were supplied for evaluating standalone and double-stage synthesis models by determining diverse water quantity and quality items. The proposed models were assessed using the coefficient of determination (R²), Nash-Sutcliffe (NS) efficiency, and root mean square error (RMSE). The significance of addressed research can be found from the overall outcomes that the predictive accuracy of double-stage synthesis models were not always superior to that of standalone models. Overall results showed that the SVR with 3^th distribution (NS = 0.915) and the Wavelet-SVR with 4^th distribution (NS = 0.915) demonstrated more correct outcomes for predicting BOD₅ concentration compared to alternative models at Hwangji station, and the Wavelet-SVR with 4^th distribution (NS = 0.917) was judged to be the most superior model at Toilchun station. In most cases for predicting BOD₅ concentration, the novel double-stage synthesis models can be utilized for efficient and organized data administration and regulation of water pollutants on both stations, South Korea.

Electroactive Biofilms of Activated Sludge Microorganisms on a Nanostructured Surface as the Basis for a Highly Sensitive Biochemical Oxygen Demand Biosensor

The possibility of the developing a biochemical oxygen demand (BOD) biosensor based on electroactive biofilms of activated sludge grown on the surface of a graphite-paste electrode modified with carbon nanotubes was studied. A complex of microscopic methods controlled biofilm formation: optical microscopy with phase contrast, scanning electron microscopy, and laser confocal microscopy. The features of charge transfer in the obtained electroactive biofilms were studied using the methods of cyclic voltammetry and electrochemical impedance spectroscopy. The rate constant of the interaction of microorganisms with the extracellular electron carrier (0.79 ± 0.03 dm³(g s)^-1) and the heterogeneous rate constant of electron transfer (0.34 ± 0.02 cm s^-1) were determined using the cyclic voltammetry method. These results revealed that the modification of the carbon nanotubes' (CNT) electrode surface makes it possible to create electroactive biofilms. An analysis of the metrological and analytical characteristics of the created biosensors showed that the lower limit of the biosensor based on an electroactive biofilm of activated sludge is 0.41 mgO₂/dm³, which makes it possible to analyze almost any water sample. Analysis of 12 surface water samples showed a high correlation (R² = 0.99) with the results of the standard method for determining biochemical oxygen demand.

A New Method for Calculating Water Quality Parameters by Integrating Space–Ground Hyperspectral Data and Spectral-In Situ Assay Data

The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed, which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity, and chlorophyll during data collection. The cross-correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to significantly reduce the UAV data noise. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regression method under five scales after the regression tests of the multiple linear regression method (MLR), support vector machine method (SVM), and neural network (NN) method. This new working mode of integrating spectral imager data with point spectrometer data will become a trend in water quality monitoring.

Recent Advancements in Electrochemical Biosensors for Monitoring the Water Quality

The release of chemicals and microorganisms from various sources, such as industry, agriculture, animal farming, wastewater treatment plants, and flooding, into water systems have caused water pollution in several parts of our world, endangering aquatic ecosystems and individual health. World Health Organization (WHO) has introduced strict standards for the maximum concentration limits for nutrients and chemicals in drinking water, surface water, and groundwater. It is crucial to have rapid, sensitive, and reliable analytical detection systems to monitor the pollution level regularly and meet the standard limit. Electrochemical biosensors are advantageous analytical devices or tools that convert a bio-signal by biorecognition elements into a significant electrical response. Thanks to the micro/nano fabrication techniques, electrochemical biosensors for sensitive, continuous, and real-time detection have attracted increasing attention among researchers and users worldwide. These devices take advantage of easy operation, portability, and rapid response. They can also be miniaturized, have a long-life span and a quick response time, and possess high sensitivity and selectivity and can be considered as portable biosensing assays. They are of special importance due to their great advantages such as affordability, simplicity, portability, and ability to detect at on-site. This review paper is concerned with the basic concepts of electrochemical biosensors and their applications in various water quality monitoring, such as inorganic chemicals, nutrients, microorganisms' pollution, and organic pollutants, especially for developing real-time/online detection systems. The basic concepts of electrochemical biosensors, different surface modification techniques, bio-recognition elements (BRE), detection methods, and specific real-time water quality monitoring applications are reviewed thoroughly in this article.

Is a compostable plastic biodegradable in the sea? A rapid standard protocol to test mineralization in marine conditions

Due to environmental persistence, lack of a proper land-based waste management, and global circulation, marine ecosystems are especially threatened by plastics. The search for alternatives to conventional oil-based polymers gave rise to novel materials commercialized under different "green" labels based on compostability. However, current international standards are not effective in predicting actual biodegradability of plastic objects in natural scenarios, and degradation of these novel bioplastics in marine conditions is unwarranted. We present a simple and rapid standard protocol based on their biological oxygen demand, intended to support policy-makers and plastic industry in the search for truly marine-biodegradable plastics. Improvements include: development of an environmentally relevant nutrient formulation following Redfield ratio (106C:16 N:1P); use of a natural inoculum representative of marine habitats (sediment pore water); standardization of the test material by grinding to particles below 250 μm to shorten the incubation period, and selection of a truly biodegradable biopolymer (PHB), used as positive control. This protocol was successfully applied to show that commercial compostable plastics are not biodegradable in marine environments.

Improved water quality monitoring indicators may increase carbon storage in the oceans

Indicators related to organic matter are important when assessing aquatic environment quality. The chemical oxygen demand (COD) is widely used as a water quality reference. However, oxidizing agents used to determine the COD can oxidize refractory organic matter that is not pollutant and can persist in the ocean for thousands of years. This means the COD can misrepresent the water quality. The actual water quality can be indicated better by the biochemical oxygen demand (BOD) than the COD, but determining the BOD is time-consuming and gives variable results. In this study, the optical properties of dissolved organic matter in water samples from the Chinese coast that had been incubated for a long time or directly oxidized using COD oxidant were analyzed. The results indicated that the oxidizing agent rapidly oxidized 22.93% ± 4.96% of refractory dissolved organic matter (RDOM) that was resistant to microbial degradation, implying that RDOM made a marked contribution to the COD. Meanwhile, size-fractional fluorescence spectroscopy and COD measurements indicated that the COD of the >0.7 μm fraction and the fluorescence intensity of the protein-like component significantly positively correlated with the BOD of the bulk sample. This indicated that, for monitoring organic pollutants in coastal waters, the COD of the >0.7 μm fraction could be used as a proxy for the standard COD and that the fluorescence intensity of the protein-like component could be used as a convenient proxy for the BOD. The method can help retain recalcitrant organic matter in seawater to act as a carbon sink.

Fast and simultaneous detection of dissolved BOD and nitrite in wastewater by using bioelectrode with bidirectional extracellular electron transport

Timely and simultaneously detecting BOD and nitrite concentrations is of great significance for curbing of water pollution and adjusting wastewater treatment strategies. However, existing BOD and nitrite biosensors cannot perform synchronous detection due to their single electroactivity and differences in detection time. This study reported a novel dual-function electrochemical biosensor (DFEB) that could perform fast, simultaneous detection of nitrite and dissolved BOD. DFEB conducted a potential-step chronoamperometry on the mixed-bacteria bioelectrode with bidirectional electron transfer ability to obtain response signals. DFEB accurately measured dissolved BOD in the range of 5 ∼ 100 mg BOD L-1 and nitrite in the range of 0.05 ∼ 16 mg NO2--N L-1 within 20 min and maintain stable performance over 200 tests. DFEB performed well in artificial wastewater, aquatic wastewater, anaerobic tank effluent and anammox effluent, with relative errors < 15.7% and 16.8% in detecting nitrite and dissolved BOD, respectively. Our study provided a feasible way to develop multifunctional biosensors for detecting pollutants with different redox properties in wastewater.

Evaluation of cytogenotoxic potential and embryotoxicity of KRS-Cauvery River water in zebrafish (Danio rerio)

In the Cauvery River (CR), indiscriminate discharge of waste causes unexplained skeletal deformity in some fish species present in the water. To investigate this phenomenon, we analyzed the biological, physical, and chemical parameters present in the water and then evaluated the toxicity effects on the zebrafish (Danio rerio) model. The zebrafish were treated with KRS-CR water samples collected from three stations (fast-flowing water [X], slow-flowing [Y], and stagnant [Z] water), before and after filtration. Firstly, we detected microscopic organisms (MO) such as Cyclops, Daphnia, Spirogyra, Spirochaeta, and total coliform (Escherichia coli), which are bioindicators of water pollution present in the samples. All physicochemical parameters analyzed, including heavy metals before and after filtration of the water with Millipore filter paper (0.45 µm), were within the acceptable limits set by standard organizations, except for decreased dissolved oxygen (DO), and increased biochemical oxygen demand (BOD), and chemical oxygen demand (COD), which are indicators of hypoxic water conditions, as well as the presence of microplastics (polybutene (< 15 µm), polyisobutene (≤ 20 µm), and polymethylpentene (≤3 mm)) and cyclohexyl in CR water samples. Zebrafish embryos treated with the water samples, both before and after filtration exerts the same cytogenotoxic effects by inducing increased reactive oxygen species (ROS) production, which triggers subcellular organelle dysfunctions, DNA damage, apoptosis, pericardial edema, skeletal deformities, and increased mortality. As a result, we observed that both water samples and zebrafish larvae had significantly less oxygen using SEM and EDS. Our findings show that KRS-CR water can induce cytogenotoxic and embryotoxic defects in zebrafish due to hypoxic water conditions triggered by the microplastics influx. The present study would provide valuable insights for health hazards evaluation and future river water treatment strategies.

Sustainable strategy on microbial fuel cell to treat the wastewater for the production of green energy

Microbial fuel cell (MFC) is one of the promising alternative energy systems where the catalytic conversion of chemical energy into electrical energy takes places with the help of microorganisms. The basic configuration of MFC consists of three major components such as electrodes (anode and cathode), catalyst (microorganism) and proton transport/exchange membrane (PEM). MFC classified into four types based on the substrate utilized for the catalytic energy conversion process such as Liquid-phase MFC, Solid-phase MFC, Plant-MFC and Algae-MFC. The core performance of MFC is organic substrate oxidation and electron transfer. Microorganisms and electrodes are the key factors that decide the efficiency of MFC system for electricity generation. Microorganism catalysis degradation of organic matters and assist the electron transfer to anode surface, the conductivity of anode material decides the rate of electron transport to cathode through external circuit where electrons are reduced with hydrogen and form water with oxygen. Not limited to electricity generation, MFC also has diverse applications in different sectors including wastewater treatment, biofuel (biohydrogen) production and used as biosensor for detection of biological oxygen demand (BOD) of wastewater and different contaminants concentration in water. This review explains different types of MFC systems and their core performance towards energy conversion and waste management. Also provides an insight on different factors that significantly affect the MFC performance and different aspects of application of MFC systems in various sectors. The challenges of MFC system design, operations and implementation in pilot scale level and the direction for future research are also described in the present review.

Technology status and trends of industrial wastewater treatment: A patent analysis

Globally, 80% of wastewater, among which 28% came from industry, returned to the ecosystem without treatment or reuse. The discharge of industrial wastewater poses public health and environmental concerns. The necessity and urgency of industrial wastewater treatment (IWT) will bring great challenges to most countries. This paper conducted the patent analysis combined with text mining to quantitatively analyze 11,840 patents related to IWT in the Derwent Innovations Index database. The results showed that: From 1973 to 2020, the number of patents related to IWT annually was increasing consistently. China ranked first in the number of patent publications. In contrast, the United States and some patent organizations, such as World Intellectual Property Organization, produced fewer patents, while they played more important roles in knowledge transfer. The core technology analysis suggested that method, device, material and related industry were hot topics. From activated sludge treatment technology, industrial wastewater treatment technology had gone through a development process from single technology treatment to combined technologies treatment. In the foreseeable future, research on devices for physical treatment, advanced oxidation processes, automated and energy-saving treatment systems were the promising directions.

Novel techniques to determine dilution ratios of raw wastewater and wastewater treatment plant effluent in the 5-day biochemical oxygen demand test

The current 5-day biochemical oxygen demand (BOD₅) test methods lack detailed information on sample dilution, which typically leads to an incorrect dilution ratio of samples and failed BOD₅ testing. This study proposed an improved dilution technique that effectively determines the dilution ratios for raw wastewater and wastewater treatment plants (WWTPs) effluent. The numbers of raw wastewater and WWTPs effluent samples used in the BOD₅ tests were 201 and 61, respectively. The experimental results demonstrated that both the raw wastewater and WWTPs effluent varied in BOD₅ values with the sample dilution ratio, and these changes were more noticeable when the dissolved oxygen consumption ratio (DOCR) was less than 20% or when the dilution ratio was large. Assuming that the BOD₅ value over the DOCR range of 40%-70% was true, the optimal DOCR range was 40%-90% for the raw wastewater and 40%-70% and 80%-90% for the WWTPs effluent, where the relative error of BOD₅ values in these DOCR ranges was less than 10% depending on the dilution ratio. The correlation between the sample dilution ratio and the BOD₅ value over the optimal DOCR range was considerably higher than that over the entire DOCR range. This was combined with the correlation equation between BOD₅ and chemical oxygen demand to propose an equation that could determine more accurate sample dilution ratios for raw wastewater and WWTPs effluent compared to the conventional sample dilution methods for the BOD₅ test.

A near-infrared optical nanosensor for measuring aerobic respiration in microbial systems

We developed a ratiometric oxygen-sensitive nanosensor and demonstrated application in monitoring metabolic oxygen consumption in microbial samples over time. Based on a near-infrared (NIR) emitting oxygen-quenched luminophore, platinum(II) octaethylporphine ketone (PtOEPK), along with a stable dioctadecyl dicarbocyanine reference dye (DiD), this nanosensor system provides an advantageous approach for overcoming imaging issues in biological systems, such as autofluorescence and optical scattering in the visible wavelength region. The dyes are encapsulated within a polymer-based nanoparticle matrix to maintain them at a constant ratio in biological samples, precluding the need for complex synthetic approaches. With this constant ratio of the two dyes, the nanosensor response can be measured as a ratio of their two signals, accounting for nanosensor concentration artifacts in measurements. The nanosensors are reversible, which enabled us to temporally monitor systems in which dissolved oxygen concentrations both increase and decrease. These sensors were applied for the monitoring of oxygen in samples of Saccharomyces cerevisiae (brewing yeast) in a 96-well optical fluorescence plate reader format over 60 h. By mixing the nanosensors directly into the sample well with the yeast, we were able to dynamically track metabolic activity changes over time due to varying cell concentration and exposure to an antimicrobial agent. This system could be a potential platform for high-throughput screening of various species or variants of microbes with unknown metabolic rates in response to external stimuli (antimicrobials, metabolites, etc.).

Reducing biogenic amine in seriflux and huangjiu by recycling of seriflux inoculated with Lactobacillus plantarum JN01

High content of biogenic amine (BA) in huangjiu could pose serious quality concerns. More than 71% of BA in huangjiu were carried over from seriflux (rice soaking wastewater), which were produced by some BA producing bacteria during rice soaking process. A BA non-producing strain, Lactobacillus plantarum JN01, was introduced to rice soaking process, which decreased BA content in seriflux by 93.8% by niche competition at bench scale. Recycling of seriflux inoculated with L. plantarum JN01 at pilot run scale for ten batches demonstrated that BA in seriflux and huangjiu were reduced by 78.4% and 87.7%, respectively. The safety of huangjiu was enormously improved without affecting on the profiles of flavor compounds. Our results demostrated that seriflux recycling technology could reduce 50% of water consumption and achieve "zero effluents" in rice soaking process, which might potentially be a "green technology" not only for huangjiu brewing industry, but also for other related traditional fermented food industries.

Propuesta de Actualización del RAOHE Incorporando Tecnologías de Fracturamiento Hidráulico, Reinyección de Recortes y Revisión de Límites Permisibles en la Gestión de Descargas Líquidas

La legislación ambiental hidrocarburífera en el Ecuador inició en los 70 con el llamado pacto de caballeros y tuvo su momento cumbre con la expedición del RAOHE en 2001. En este punto, el RAOHE se consolidó como una herramienta para la explotación sustentable de los recursos hidrocarburíferos, y un garante de la estabilidad jurídica de una inversión extranjera que reactivase el sector petrolero. Sin embargo, 20 años después, con nuevos avances tecnológicos y garantías ambientales más restrictivas, se ha generado un desfase entre aquello que se encuentra regulado y la actual tecnología empleada en las operaciones de la industria. En este documento, se analizó esta discontinuidad normativa y de procesos desde el enfoque de la tecnología relacionada con el manejo y disposición de agua. Específicamente, en la revisión y análisis de límites permisibles en el manejo de descargas líquidas, reinyección de recortes y fracturamiento hidráulico. Este ensayo se apoyó en el estudio de fuentes de investigación primaria para la definición de sugerencias generales sobre la aplicación y gestión ante la entidad de gestión ambiental, a la espera de que esta información pueda aportar a la articulación de marcos técnicos más comprensibles.

Retrieval of water quality parameters from hyperspectral images using a hybrid feedback deep factorization machine model

Environmental protection of water resources is of critical importance to daily life of human beings. In recent years, monitoring the variation of water quality using remote sensing techniques has become prevalent. Unmanned aerial vehicle (UAV) based remote sensing techniques have been applied to quantitative retrieval of concentrations of water quality parameters including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a (Chl-a), successfully and efficiently. In this study, a novel method with deep factorization machine, spatial distribution pattern analysis, and probabilistic analysis engaged, named hybrid feedback deep factorization machine (HF-DFM), has been developed to quantitatively estimate concentrations of water quality parameters based on hyperspectral reflectance data on large scale effectively. Our proposed method is a unified model for quantifying concentrations of water quality parameters with an end to end structure, which integrates UAV based optical remote sensing techniques and deep learning to estimate concentrations of water quality parameters. Furthermore, our proposed model was applied to real-time quantitative monitoring the variation of water quality of Mazhou River, Shenzhen, Guangdong, China. Finally, we evaluate the performance of proposed model on a real-world dataset in terms of root of mean squared error (RMSE), mean absolute percent error (MAPE), and coefficient of determination (R²). The experimental results show that our proposed model outperforms other state-of-the-art models with respect to RMSE, MAPE, and R², where resulting MAPEs for quantifying all water quality parameters range from 8.78% to 12.36%, and resulting R²s range from 0.81 to 0.93. It can serve as a useful tool for decision makers in effectively monitoring water quality of urban rivers.

Element Contents in Three Commercially Important Edible Mollusks Harvested off the Southwestern Coast of Crimea (Black Sea) and Assessment of Human Health Risks from Their Consumption

Mollusks are a prospective food for the world's growing population, but the contents of toxic and essential trace elements in them have not been studied comprehensively. In this work, using inductively coupled plasma mass spectrometry, the contents of 72 elements in soft tissues of the edible mollusks Mytilus galloprovincialis, Rapana venosa, and Crassostrea gigas from the coastal area of the southwestern Crimea were estimated and compared with the maximum permissible levels. Element accumulation similarities were observed in the two bivalve species. Cluster analysis applied to the non-normalized contents allowed finding an optimal number of non-overlapping element clusters: 1 group of macroelements, 1-2 groups of trace elements, and 1-2 groups of ultratrace elements. As an outcome of this analysis, the element accumulation universality index was introduced, which demonstrated the accumulation universality decrease in the order: mussel > sea snail > oyster. An original approach to estimating the mollusk consumption rate was proposed to assess human health risks. Two possible consumption scenarios were identified for Crimean residents. From the expected consumption of all species in both scenarios, there are no health risks, but they are not excluded, within the 95% probability, from high consumption of mussels and sea snails in the pessimistic scenario.

Influence of physico-chemical characteristics of rembau river, peninsular Malaysia, on congregating Pteroptyx fireflies

We studied the water quality of the riparian firefly sanctuary of Sungai Rembau, or Rembau River, in Negeri Sembilan, Malaysia, from January 2018 to November 2018 to determine the possible influence of the physico-chemical characteristics of the water on the firefly populations living within the sanctuary. We set up a total of five water quality sampling stations and 10 firefly sampling stations along the river. Dissolved oxygen (DO), temperature, pH and electrical conductivity (EC) were measured in situ, while chemical oxygen demand (COD), total suspended solids (TSS), biochemical oxygen demand (BOD) and ammonia-nitrogen (NH₃-N) were analysed in the laboratory. Firefly samples were collected using a sweep net at both day and night for 1 min. Sungai Rembau was categorized as Class II on the Malaysian water quality index (WQI), which indicates slight pollution. Except for EC and DO, the water quality parameter values were not significantly different (p > 0.05) between the sampling stations. A total of 529 firefly individuals consisting of Pteroptyx tener (n = 525, 99.24%), P. malaccae (n = 3, 0.57%) and P. asymmetria (n = 1, 0.19%) were collected. There was significant correlation between firefly abundance and BOD (r =  - 0.198, p < 0.05), NH₃-N (r =  - 0.150, p < 0.05) and pH (r = 0.408, p < 0.05). The results show that the firefly populations in Sungai Rembau are sensitive to organic compounds, which may be present in the form of pollutants from anthropogenic activities near their natural habitat.

Prediction of conotoxin type based on long short-term memory network

Aiming at the problems of the wet experiment method in identifying the types of conotoxins, such as the complexity, low efficiency and high cost, this study proposes a method that uses the sequence information of the conotoxin peptides combined with long short term memory networks (LSTM) models to predict the Methods of spirotoxin category. This method only needs to take the conotoxin peptide sequence as input, and adopts the character embedding method in text processing to automatically map the sequence to the feature vector representation, and the model extracts features for training and prediction. Experimental results show that the correct index of this method on the test set reaches 0.80, and the AUC value reaches 0.817. For the same test set, the AUC value of the KNN algorithm is 0.641, and the AUC value of the method proposed in this paper is 0.817, indicating that this method can effectively assist in identifying the type of conotoxin.

Application of organosilicate matrix based on methyltriethoxysilane, PVA and bacteria Paracoccus yeei to create a highly sensitive BOD

We have studied immobilization of Paracoccus yeei VKM B-3302 cells in an organosilica sol-gel matrix consisting of tetraethoxysilane, methyltriethoxysilane and polyvinyl alcohol as a structure-modifying agent. Optical microscopy showed that higher amounts of methyltriethoxysilane make the solid material structure softer. In addition, formation of structures, probably, with bacterial cells inside was spotted. We have analyzed the catalytic power of the immobilized bacteria and discovered that the material's catalytic potential is the highest at 50% of methyltriethoxysilane. Therefore, this seems to be the best ratio of precursors in a material for bacteria to become effectively encapsulated. Analysis of the material structure by low-temperature nitrogen absorption and scanning electron microscopy revealed that in the given conditions the material got crack-like mesopores and spherical particles of about 25 µm in diameter with immobilized bacterial cells on their surface. The study found that the fabricated organosilica material can effectively protect bacterial cells against UV radiation, pH change, high salinity and high heavy metal ion concentration.

Monitoring and water quality impacts of an herbicide treatment on an aquatic invasive plant in a drinking water reservoir

Effective treatment options are needed for the management of aquatic invasive species. An herbicide treatment was used to control an invasive aquatic plant, yellow floating heart (Nymphoides peltata) in a 3350-acre drinking water reservoir. The purpose of this research was to document the success of the treatment in an individual cove of the reservoir using in-situ sampling and reservoir-wide using remotely sensed Sentinel-2 satellite imagery. We also determined if the dying vegetation negatively impacted biological oxygen demand and dissolved oxygen concentrations in the cove. The aquatic herbicide ProcellaCOR™ (active ingredient = florpyrauxifen-benzyl) was used to treat a 55-acre infestation of YFH at a rate of 3 Prescription Dose Units (PDU)/ac-ft by a certified applicator in July 2019. Total surface coverage of yellow floating heart in the reservoir was reduced by more than 90% within 15 days after the treatment, and to less than 3.0 acres within 50 days after the treatment. No blooming flowers were observed after treatment and the surface coverage was close to 0% within 17 days after treatment in the cove. The effect of the herbicide treatment also appeared to carry over into the following growing season as the total surface coverage of yellow floating heart in the reservoir was less than 8 acres one year after the treatment in July 2020. The herbicide treatment resulted in short term increases in biological oxygen demand and decreases in dissolved oxygen at some sites in the cove within 3-10 days after the treatment. Dissolved oxygen then increased and concentrations were greater 42 days after treatment than they were before the treatment. Our results show that ProcellaCOR™ has the potential to control yellow floating heart infestations with relatively short-term negative impacts on dissolved oxygen concentrations. We also show that Sentinel-2 satellite imagery can be used to monitor the success of herbicide applications over large spatial and temporal scales that would not be possible from ground based monitoring alone.