Eutrophic Water Research Articles

Diversity, community structure, and abundance of nirS-type denitrifying bacteria on suspended particulate matter in coastal high-altitude aquaculture pond water

Denitrifying bacteria harboring the nitrate reductase S (nirS) gene convert active nitrogen into molecular nitrogen, and alleviate eutrophication in aquaculture water. Suspended particulate matter (SPM) is an important component of aquaculture water and a carrier for denitrification. SPM with different particle sizes were collected from a coastal high-altitude aquaculture pond in Maoming City, China. Diversity, community structure, abundance of nirS-type denitrifying bacteria on SPM and environmental influencing factors were studied using high-throughput sequencing, fluorescence quantitative PCR, and statistical analysis. Pseudomonas, Halomonas, and Wenzhouxiangella were the dominant genera of nirS-type denitrifying bacteria on SPM from the ponds. Network analysis revealed Pseudomonas and Halomonas as the key genera involved in the interaction of nirS-type denitrifying bacteria on SPM in the ponds. qPCR indicated a trend toward greater nirS gene abundance in progressively larger SPM. Dissolved oxygen, pH, temperature, and SPM particle size were the main environmental factors influencing changes in the nirS-type denitrifying bacterial community on SPM in coastal high-altitude aquaculture pond water. These findings increase our understanding of the microbiology of nitrogen cycle processes in aquaculture ecosystem, and will help optimize aquatic tailwater treatment strategies.

Novel Biochar/Fe-Modified Biocarriers Assisted Tidal-Flow Constructed Wetlands for Enhanced Nitrogen Removal from Eutrophic Water under Low Temperatures

Novel Biochar/Fe-Modified Biocarriers Assisted Tidal-Flow Constructed Wetlands for Enhanced Nitrogen Removal from Eutrophic Water under Low Temperatures

Effects of the catastrophic 2020 Yangtze River seasonal floods on microcystins and environmental conditions in Three Gorges Reservoir Area, China.

During July and August 2020, Three Gorges Reservoir Area (TGRA) suffered from catastrophic seasonal floods. Floods changed environmental conditions and caused increase in concentration of microcystins (MCs) which is a common and potent cyanotoxin. However, the effects and seasonal variations of MCs, cyanobacteria, and environmental conditions in TGRA after the 2020 Yangtze River extreme seasonal floods remain largely unclear, and relevant studies are lacking in the literature. A total of 12 representative sampling sites were selected to perform concentration measurement of relevant water quality objectives and MCs in the representative area of the TGRA. The sampling period was from July 2020 to October 2021, which included the flood period. Organic membrane filters were used to perform the DNA extraction and analyses of the 16S rRNA microbiome sequencing data. Results showed the seasonal floods result in significant increases in the mean values of microcystin-RR (MCRR), microcystin-YR (MCYR), and microcystin-LR (MCLR) concentration and some water quality objectives (i.e., turbidity) in the hinterland of TGRA compared with that in non-flood periods (p < 0.05). The mean values of some water quality objectives (i.e., total nitrogen (TN), total phosphorus (TP), total dissolved phosphorus (TDP), and turbidity), MC concentration (i.e., MCRR, MCYR, and MCLR), and cyanobacteria abundance (i.e., Cyanobium_PCC-6307 and Planktothrix_NIVA-CYA_15) displayed clear tendency of increasing in summer and autumn and decreasing in winter and spring in the hinterland of TGRA. The results suggest that seasonal floods lead to changes in MC concentration and environmental conditions in the hinterland of TGRA. Moreover, the increase in temperature leads to changes in water quality objectives, which may cause water eutrophication. In turn, water eutrophication results in the increase in cyanobacteria abundance and MC concentration. In particular, the increased MC concentration may further contribute to adverse effects on human health.

The Effects of Annual Compost Addition to Agricultural Green Roofs on Runoff Water Quality

Space availability is one of the largest barriers to urban agriculture. One way around this issue that urban farmers in some parts of the world are exploring is moving their farming activities to building rooftops. One method of rooftop farming in use is row agriculture using green roof technology. Vegetable crop plants, which typically require more water and more nutrients than the ornamental species found on green roofs, require irrigation and the use of fertilizers. One nutrient management practice that some rooftop farmers are using is the addition of compost, which could lead to changes over time in the water-holding capacity, organic matter content, and weight of green roof media. This practice and its long-term implications have not been well-studied. Green roof platforms were created to examine how the annual additions of compost in quantities of 0, 0.33, 0.66, and 1 kg/m2 affect runoff water quality and green roof media properties. Runoff water samples were collected and analyzed for pH, conductivity, color, turbidity, and nitrate nitrogen, ammonia nitrogen, total phosphorus, and potassium contents. Compost treatment had no effect on any water quality metric except for color, which had slightly different changes over time in the different compost treatments. The lack of difference among the treatments may be attributed to the low nutrient content of the compost and continued use of fertilizers to provide nutrients. Most samples observed in this study exceeded the US Environmental Protection Agency water quality guidelines for nitrate nitrogen and phosphorus and were similar to values observed in the green roof literature regarding agricultural and ornamental green roofs. This has potential implications for surface water quality and eutrophication, especially as green roof agriculture increases.

Soil type regulates the divergent loss characteristics of sediment associated carbon and nitrogen in different size classes during rainfall erosion on cultivated lands

Sediment associated carbon and nitrogen loss under rainfall, an important cause of soil quality degradation and water eutrophication, strongly depends on the intrinsic properties of original soil types. Relative to total loss, the transport behaviors of organic carbon and nitrogen among sediment size classes and response to soil types remain poorly understood. The concentrations of organic carbon (OC) and total nitrogen (TN) in different sediment size classes (>1, 0.25–1, 0.10–0.25, and <0.10 mm) and their contributions to total sediment load during rainfall erosion were determined under field plot rainfall simulation (at 90 mm h−1) on three contrasting soil types (Luvisol, Alisol and Ferralsol) with increased aggregate stability. During rainfall erosion, the concentrations of OC and TN in total and different sized sediments decreased first and then reached a steady state. The variability of OC and TN concentrations (coefficient of variations in 4.2–53.1% and 6.6–41.9%) among sediment size classes decreased from Luvisol to Ferralsol. Compared to original soils, sediments exhibited larger C/N ratios for Luvisol, and smaller values for Alisol, indicating the more selective transport of labile organic matter for weaker aggregated soils. Among sediment size classes, fine particles (<0.10 mm) accounted 69–88% of total OC and TN losses for Luvisol, and decreased to 30–39% for Ferralsol; and the main transport mechanisms of sediment associated OC and TN shifting from suspension-saltation (<0.10 mm) to rolling (>0.25 mm) with increased aggregate stability. Among original soil properties, inorganic cementing agents (including amorphous iron oxides and clay minerals) showed closer relationships with sediment OC and TN losses (|r| = 0.61–0.89, p < 0.001) than organic matter properties (|r| = 0.55–0.87, p < 0.001), further implying the important role of soil aggregate stability across soil types. This study provides an in-depth understanding on soil carbon and nitrogen losses and their divergent characteristics among soil types deserves consideration in the development of erosion model and land management in agricultural systems.

Application of Machine Learning to Estimate Ammonia Atmospheric Emissions and Concentrations

This paper describes an innovative method that recursively applies the machine learning Random Forest to an assumed homogeneous aerographic domain around measurement sites to predict concentrations and emissions of ammonia, an atmospheric pollutant that causes acidification and eutrophication of soil and water and contributes to secondary PM2.5. The methodology was implemented to understand the effects of weather and emission changes on atmospheric ammonia concentrations. The model was trained and tested by hourly measurements of ammonia concentrations and atmospheric turbulence parameters, starting from a constant emission scenario. The initial values of emissions were calculated based on a bottom-up emission inventory detailed at the municipal level and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations for each iteration, the emissions were modified, the model’s training and testing were repeated, and the model converged to a very high performance in predicting ammonia concentrations and establishing hourly time-varying emission profiles. The ammonia concentration predictions were extremely accurate and reliable compared to the measured values. The relationship between NH3 concentrations and the calculated emissions rates is compatible with physical atmospheric turbulence parameters. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow the identification of the effect of atmospheric turbulence on pollutant accumulation. The proposed methodology is suitable for validating and confirming emission time series and defining highly accurate emission profiles for the improvement of the performances of chemical and transport models (CTMs) in combination with in situ measurements and/or optical depth from satellite observation.

Life Cycle Assessment Comparison between an Earthbag Building and a Conventional Sahrawi Cement Blocks Building.

Growing environmental awareness has prompted a resurgence in traditional building techniques that rely on natural or recycled materials since many believe that structures made from these resources are ecologically friendly. Using Life Cycle Assessment (LCA) for construction materials offers valuable insights into the impacts produced during their production and construction processes. This study aims to assess the environmental impacts of two different constructions-an Earthbag Building (EB) and a conventional Sahrawi Cement Blocks Building (CBB). It also determines whether it is more environmentally beneficial to construct traditionally, utilizing local materials and aligning with the principles of the circular economy, which is one of the Sustainable Development Goals (SDGs) in Europe. This study specifically examines a cradle-to-gate LCA, using the software Simapro v. 9.4.0.1. Results show that in 21 out of the 22 impact categories analyzed, the CBB performs worse, in some cases presenting an impact of 70% higher than the EB. The highest impact is obtained for fine particulate matter formation and Global Warming related to Human Health categories, whilst impact categories related to water consumption and eutrophication obtained an impact of less than 0.001 for both constructions.

Innovative reverse-irradiation UV photocatalytic system for algae inactivation from eutrophic water: Limitation breakthrough of algae blocking and light decay

The particle blocking and light energy decay were major limitations in algae-rich water treatment by photo-catalysis. This study developed an effective photocatalytic system in innovative reverse-irradiation mode to overcome these limitations towards improving algae inactivation. Suitable light transmittance and reverse photocatalytic activity of TiO2 thin film were obtained by deposition and calcination optimization, with the optimal UV wavelength at 365 nm. Such reverse-irradiation photocatalytic system presented sustainable and durable algae degradation performance in long-term operation (7 cycles), which generated reactive oxygen species and increased superoxide dismutase activity in two-stage catalytic oxidation process. The algae cells were lysed for intracellular substance solubilization in 2-h treatment, followed by numerous degradation and removal of the dissolved cytoplasm in 2–4 h. Reverse-irradiation photocatalytic oxidation dominantly contributed 62.66–85.60 % of overall algae inactivation, while environment and photolysis provided feeble contributions of 0–4.80 % and 14.40–32.54 %, respectively. As such, 19.79 % of algae cells were lyzed, with the degradations of intracellular chlorophyll a (26.42 %) and proteins (58.14 %). Particularly, the innovative photo-catalysis in reverse-irradiation mode presented much greater performances in algae removal than those in traditional forward-irradiation mode at the long light transmission path (>1.75 cm) and high algae density (>2.8 × 107 cells/L). The reverse-irradiation photo-catalysis not only overcame limitations of algae blocking and light decay, but also remarkably inhibited residual algae regrowth, contributing to the continuous algae inactivation. Moreover, the energy-saving efficiency of 160 % was achievable due to photocatalytic promotion, contributing to economic benefit of 87.59 CNY/(m3 order) and carbon-emission reduction of 0.091 ton CO2/(m3 order). The findings provided novel insights into photo-catalysis promotion and limitation breakthrough from system configuration modification.

Purification Effect of Water Eutrophication Using the Mosaic System of Submerged-Emerged Plants and Growth Response.

Aquatic plants play a crucial role in the sustainable management of eutrophic water bodies, serving as a valuable tool for water purification. However, the effectiveness of using aquatic plants for improving water quality is influenced by landscape considerations. In practical applications, challenges arise concerning low purification efficiency and compromised aesthetic appeal when utilizing plants for water purification. To address these issues, this study aimed to examine the impact of aquatic plants on the purification of simulated landscape water bodies, specifically focusing on the effectiveness of the mosaic system of submerged-emerged plants in remediating eutrophic water bodies. Our findings indicated that individual aquatic plants exhibited limited efficacy in pollutant (total nitrogen, total phosphorus, ammonia nitrogen, and chemical oxygen demand) removal. However, when combined in appropriate proportions, submerged plants could enhance species growth and improve the purification efficiency of polluted water bodies. Notably, the mosaic system of submerged-emerged plants neither significantly promoted nor inhibited the growth of each other, but it effectively removed pollutants from the simulated water bodies and inhibited turbidity increase. The comprehensive evaluation ranked the purification capacity as Canna indica-submerged plants combination (C + S) > Thalia dealbata-submerged plants combination (T + S) > Iris pseudacorus-submerged plants combination (I + S) > Lythrum salicaria-submerged plants combination (L + S). Both C + S and T + S configurations effectively mitigated the rise of water turbidity and offered appealing landscape benefits, making them viable options for practical applications in urban landscape water bodies. Our study highlights that a submerged-emerged mosaic combination is a means of water purification that combines landscape aesthetics and purification efficiency.

The impact of ammonia and microcystin-LR on neurobehavior and glutamate/gamma-aminobutyric acid balance in female zebrafish (Danio rerio): ROS and inflammation as key pathways

Ammonia and microcystin-LR (MC-LR) are both toxins that can be in eutrophic waters during cyanobacterial blooms. While previous studies have focused on the effects of ammonia exposure on fish neurobehavioral toxicity, little attention has been given to the effects of MC-LR and combined exposures to both. This study exposed adult female zebrafish to ammonia (30 mg/L) and MC-LR (10 μg/L) alone and in combination for 30 days to investigate their neurotoxic effects and underlying mechanisms. Behavioral results showed that exposure to ammonia and MC-LR, both alone and in combination, led to decreased locomotor activity and increased anxiety in fish. Histomorphological analysis revealed the formation of thrombi and vacuolization in the brain across all exposure groups. Exposure to ammonia and MC-LR resulted in significant increases in MDA contents, decreases in Mn-SOD activities, and alterations in GSH contents compared to the control. Single and combined exposure to ammonia and MC-LR also induced the release of inflammatory factors (IL-1β and TNF-α) by activating the NOD/NF-κB signaling pathway. Furthermore, both ammonia and MC-LR significantly changed the expression of genes related to the glutamatergic and GABAergic systems, elevated Glu and GABA contents, as well as increased the Glu/GABA ratio, indicating that a shift towards increased Glu levels. Overall, these findings suggested that exposure to MC-LR and ammonia, individually and in combination, could decrease locomotor activity and increase anxiety of female zebrafish. This was likely due to brain damage from over-activated ROS and the release of pro-inflammatory cytokines, which led to a disruption in the balance of glutamatergic and GABAergic systems. However, there was no significant interaction between MC-LR and ammonia in fish neurobehavioral toxicity.

Optical water characterization and atmospheric correction assessment of estuarine and coastal waters around the AERONET-OC Bahia Blanca

The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.

Biofilm formation and EPS production enhances the bioremediation potential of Pseudomonas species: anovel study from eutrophic waters of Dal lake, Kashmir, India.

The present study was conducted with the aim of isolation and identification of the biofilm-forming denitrifying Pseudomonas bacterial strains from eutrophic waters of Dal lake, India, followed by the study of inter-relation of biofilm formation and denitrification potential of Pseudomonas strains. The bacterial strains were characterized by morphological observations and identified using 16S rDNA sequencing followed by the quantification of biofilm formation of these st by crystal violet (CV) assay using 96-well microtiter plate and extracellular polymeric substance (EPS) extraction. Lastly, the nitrate-reducing potential of all Pseudomonas species was studied. Our evaluation revealed that four different Pseudomonas species were observed to have the biofilm-forming potential and nitrate-reducing properties and the species which showed maximum biofilm-forming potential and maximum EPS production exhibited higher nitrate-removing capacity. Moreover, P. otitis was observed to have the highest denitrification capacity (89%) > P. cedrina (83%) > P. azotoform (79%) and the lowest for P. peli (70%). These results clearly signify a positive correlation of biofilm-forming capacity and nitrate-removing ability of Pseudomonas species. This study has for the first time successfully revealed the bioremediation potential of P. otitis, P. cedrina, P. azotoform, and P. peli species, thus contributing to the growing list of known nitrate-reducing Pseudomonas species. Based upon the results, these strains can be extrapolated to nitrate-polluted water systems for combating water pollution.

WITHDRAWN: Effects of hydraulic retention time and cultivation on nutrients removal and biomass production in wastewater by membrane photobioreactor: modeling and optimization by machine learning and response surface methodology

Discharge of excess nutrients in wastewater can potentially cause eutrophication and poor water quality in the aquatic environment. A new approach of nutrients removal in wastewater is by utilizing microalgae which grow by absorbing CO2 from air. Furthermore, the use of membrane photo-bioreactor (MPBR) that combines membranes and photo-bioreactor has emerged as a novel wastewater treatment method. This research sought to model, forecast, and optimize the behavior of dry biomass, dissolved inorganic nitrogen (DIN), and dissolved inorganic phosphorus (DIP) in MPBR by response surface methodology (RSM) and artificial neural network (ANN) algorithms, which saved time and resources of experimental work. The independent variables that have been used for modeling were hydraulic retention time (HRT) and cultivation. For this purpose, the dry biomass of algal production, DIN and DIP behavior were modeled by RSM and ANN algorithms, to identify the optimum mode of processing. RSM modeling has shown good agreement with experimental data. According to RSM optimization, the optimum mode for DIN and DIP occurred at 1.15 days of HRT and 1.92 days of cultivation. The ANN showed better performance than the RSM model, with the margin of deviation being less than 10%. Furthermore, the ANN algorithm showed higher accuracy than RSM method in predicting the dry biomass, DIN and DIP behavior in MPBR.

Ecological interruption on food web dynamics by eutrophic water discharge from the world’s longest dike at Saemangeum, Yellow Sea

The man-made sea dike has disrupted the natural link between riverine and marine ecosystems and caused eutrophication within the aquatic ecosystem. The eutrophic water discharge has also raised concerns. As a representative tidal flat with the longest dike in the world, Saemangeum has experienced the problem of eutrophication. To elucidate the discharge water effects on the benthic food web dynamics, a four-year round sampling was conducted in/outside of the Saemangeum sea dike. Stable isotope analysis was applied to benthos (a total of 54 species) and their potential diets. Water discharge tripled in period II (2021–2022) compared to the period I (2019–2020). However, there were no significant impact changes in food web structure between the two periods due to improved lake water quality in period II. A positive correlation of nutrient concentration between the inner and outer areas of the dike revealed a direct effect of the water discharge on the outer tidal flat. The water discharge altered the spatial environmental conditions and the food web structure of the outer tidal flat. High TN concentrations stimulated the biomass of microphytobenthos (MPB) near the water gates, which in turn increased MPB consumption by benthos, demonstrating the in/direct impacts of water discharge on the food web. Furthermore, filter feeders exhibited a more sensitive response to spatial organic matter distribution compared to deposit feeders in diet utilization. Overall, our novel findings on food web dynamics in a representative tidal flat with artificial structures emphasize the necessity of continuous monitoring to ensure the sustainability of coastal ecosystems.

A comparison of adenosine triphosphate with other metrics of microbial biomass in a gradient from the North Atlantic to the Chesapeake Bay

A new, simplified protocol for determining particulate adenosine triphosphate (ATP) levels allows for the assessment of microbial biomass distribution in aquatic systems at a high temporal and spatial resolution. A comparison of ATP data with related variables, such as particulate carbon, nitrogen, chlorophyll, and turbidity in pelagic samples, yielded significant and strong correlations in a gradient from the tributaries of the Chesapeake Bay (sigma-t = 8) to the open North Atlantic (sigma-t = 29). Correlations varied between ATP and biomass depending on the microscopic method employed. Despite the much greater effort involved, biomass determined by microscopy correlated poorly with other indicator variables including carbon, nitrogen, and chlorophyll. The ATP values presented here fit well within the range of ATP biomass estimates in the literature for similar environments. A compilation of prior research data from a wide range of marine habitats demonstrated that ATP values can be ranked according to broad trophic gradients, from the deep sea to eutrophic inland waters. Using a mass-based conversion factor of 250, the contribution of biomass to overall particulate organic carbon (POC) ranged from 15% to 30% along the gradient, from the open ocean to locations in the Chesapeake Bay respectively. Our data corroborate the notion that ATP, due to its consistency and simplicity, is a promising high-throughput indicator of cytoplasm volume with distinct benefits over cell counts and measures of chlorophyll or POC.

Implications of Vegetal Protein Hydrolysates for Improving Nitrogen Use Efficiency in Leafy Vegetables

Climate change and the degradation of ecosystems is an urgent issue to which the agricultural sector contributes through the overuse of productive inputs such as chemical fertilizers. A disproportionate use of nitrogenous fertilizers combined with low efficiency inevitably results in worsening environmental problems (greenhouse gas emissions, soil degradation, water eutrophication, and groundwater pollution). Nevertheless, increasing population growth puts additional pressure on the already struggling agricultural world. Awareness of these problems has pushed the world of research towards the development of more sustainable but equally efficient strategies in terms of production. The use of biostimulant substances and/or micro-organisms promoting yield, resilience to abiotic stresses in plants, and increasing the functional quality of products have been indicated as a valid strategy to improve the sustainability of agricultural practices. In modern horticulture, the use of vegetable–protein hydrolysates (V-PHs) is gaining more and more interest. These biostimulants could influence plants directly by stimulating carbon and nitrogen metabolism and interfering with hormonal activity, but also indirectly as V-PHs could improve nutrient availability in plant growth substrates and increase nutrient uptake and utilization efficiency. By exploiting this aspect, it would be possible to reduce the use of chemical fertilizers without affecting potential yields. After a brief introduction to the issues related to the intensive use of nitrogen fertilizers, this review focuses on the use of V-PHs as a strategy to increase nitrogen use efficiency (NUE). Starting with their heterogeneous origins and compositions, their effects on nitrogen metabolism, as well as the physiological and biochemical processes involved in these products, this review concludes with an in-depth discussion of the effects of V-PHs on major leafy vegetables.

A new model to estimate shallow lake nitrogen removal rate based on satellite derived variables

Lake nitrogen (N) removal, mainly resulting from bacterial denitrification that converts nitrate (NO3 −) to gaseous N (N2), is important for lake water quality and eutrophication control. However, quantifying lake N removal is challenging due to the high background atmosphere N2 concentration and the heavy burden of field surveys, leading to a decoupling of watershed N management and water quality improvement. Here, we developed and validated an innovative nonlinear model for lake N removal rate estimation by linking the N removal rates with remote sensing-derived variables (chlorophyll-a, chromophoric dissolved organic matter, and lake surface water temperature). The model was validated in shallow eutrophic Lake Taihu in the Yangtze River basin and at the global scale. Based on the new N removal model, we estimated that an annual average of 3.21 × 104 t N yr‒1 was removed in Lake Taihu from 2011 to 2020, accounting for 53%–66% of the total lake N loading. The remaining N loading after denitrification removal in Lake Taihu would be approximately 2.37 mg N l‒1, and 0.79 × 104 t N y‒1 of lake N loading still needs to be removed to meet the target of class IV water quality (1.5 mg N l‒1). This is the first study linking lake N removal in sediment microcosm incubations with reach-scale remote sensing derived variables, providing timely-much insights into lake N removal. This approach can be easily applied in other lakes with satellite derived data, to better understand lake N budget, drivers of eutrophication control, and watershed N management.

Panoptic elucidation of algicidal mechanism of Raoultella sp. S1 against the Microcystis aeruginosa by TMT quantitative proteomics

Harmful algal blooms (HABs) due to eutrophication are becoming a serious ecological disaster worldwide, threatening human health and the optimal balance of aquatic ecosystems. The traditional approaches to eradicate HABs yield several drawbacks in practical application, while microbial algicidal technology is garnering mounting recognition due to its high efficiency, eco-friendliness, and low cost. In our previous study, we isolated a bacterium strain Raoultella sp. S1 from eutrophic water with high efficiency of algicidal properties. This study further investigated the flocculation and inactivation efficiency of S1 on Microcystis aeruginosa at different eutrophic stages by customizing the algal cell densities. The supernatant extract of S1 strain exhibited remarkable flocculation and inactivation effects against low (1 × 106 cell/mL)and medium (2.7 × 106 cell/mL)concentrations of algal cells, but unexceptional for higher densities. The results further revealed that algal cells at low and medium counts manifested a more apparent antioxidant defense response, while the photosynthetic efficiency and relative electron transport rate were considerably reduced within 24 h. TEM observations confirmed the disruption of thylakoid membranes and cell structure of algal cells by algicidal substances. Moreover, TMT proteomics revealed alterations in protein metabolic pathways of algal cells during the flocculation and lysis stages at the molecular biological level. This signified that the disruption of the photosynthetic system is the core algicidal mechanism of S1 supernatant. In contrast, the photosynthetic metabolic pathways in the HABs were significantly upregulated, increasing the energy supply for the NADPH dehydrogenation process and the upregulation of ATPases in oxidative phosphorylation. Insufficient energy provided by NADPH resulted in a dwindled electron transport rate, stagnation of carbon fixation in dark reactions, and blockage of light energy conversion into chemical energy. Nonetheless, carbohydrate metabolism (gluconeogenesis and glycolysis) proteins were down-regulated and hampered DNA replication and repair. This study aided in unveiling the bacterial management of eutrophication by Raoultella sp. S1 and further arrayed the proteomic mechanism of algal apoptosis.

The cytotoxicity of microcystin-LR: ultrastructural and functional damage of cells.

Microcystin-LR (MC-LR) is a toxin produced by cyanobacteria, which is widely distributed in eutrophic water bodies and has multi-organ toxicity. Previous cytotoxicity studies have mostly elucidated the effects of MC-LR on intracellular-related factors, proteins, and DNA at the molecular level. However, there have been few studies on the adverse effects of MC-LR on cell ultrastructure and function. Therefore, research on the cytotoxicity of MC-LR in recent years was collected and summarized. It was found that MC-LR can induce a series of cytotoxic effects, including decreased cell viability, induced autophagy, apoptosis and necrosis, altered cell cycle, altered cell morphology, abnormal cell migration and invasion as well as leading to genetic damage. The above cytotoxic effects were related to the damage of various ultrastructure and functions such as cell membranes and mitochondria. Furthermore, MC-LR can disrupt cell ultrastructure and function by inducing oxidative stress and inhibiting protein phosphatase activity. In addition, the combined toxic effects of MC-LR and other environmental pollutants were investigated. This review explored the toxic targets of MC-LR at the subcellular level, which will provide new ideas for the prevention and treatment of multi-organ toxicity caused by MC-LR.

Nitrate biodegradation by indigenous bacteria strain Bacillus subtilis obtained from eutrophic waters of Dal Lake Srinagar (India): Mechanisms and optimization

The presence of elevated nitrate concentrations in natural water bodies is a cause of significant concern, owing to its potential ecological and human health ramifications. Dal lake, a eutrophic lake situated in Srinagar, India, which bears a substantial burden of nutrient pollution stemming from various sources. To tackle high nitrate levels, an indigenous bacterial strain from Dal Lake, Srinagar, India, was used for its biodegradative abilities. To enhance biodegradation, the bacterial strain's efficiency was rigorously tested across various environmental conditions, including temperature, nitrate concentration, pH, contact time, and adsorbent quantity. The active isolate, identified through genetic analysis via 16S rRNA sequencing, was determined to be Bacillus subtilis ON358108. Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), BET (Brunauer–Emmett–Teller) analysis (BET), XRD (X-ray diffraction) was employed.These methodologies were employed to scrutinize various aspects of the adsorbent, including surface area, pore volume, crystalline structure, composition, and internal structure were used in characterizing and elucidating the behaviour of functional groups engaged in the biodegradation process, both prior to and post-nitrate uptake. Adsorption mechanisms were established from experiments using the Langmuir, Freundlich, and Temkin models. We analyzed adsorption kinetics using pseudo-first- and pseudo-second-order models. To optimize the nitrate biodegradation process, we applied Response Surface Methodology (RSM) based on a central composite design approach. This approach successfully removed 91 % (±1.5) of the effluent's nitrate with Bacillus subtilis ON358108.Furthermore, our study demonstrated that the selected isotherm models fit the adsorption process in the following sequence: Langmuir > Temkin > Freundlich. In addition, thermodynamic study revealed the process is spontaneous and endothermic.