[Effects of Biochar on Growth and Pollutant Accumulation of Lettuce in Soil Co-contaminated with Tetracycline and Copper].

Through lettuce potting experiments, the effects of different types of biochar (apple branch, corn straw, and modified sorghum straw biochar with phosphoric acid modification) on lettuce growth under tetracycline (TC) and copper (Cu) co-pollution were investigated. The results showed that compared with those under CK, the addition of biochar treatment significantly increased the plant height, root length, shoot fresh weight, and root fresh weight of lettuce (P < 0.05). The addition of different biochars significantly increased the nitrate nitrogen, chlorophyll, and soluble protein content in lettuce physiological indicators to varying degrees, while also significantly decreasing the levels of malondialdehyde, proline content, and catalase activity. The effects of biochar on lettuce physiological indicators were consistent during both the seedling and mature stages. Compared with those in CK, the addition of biochar resulted in varying degrees of reduction in the TC and Cu contents of both the aboveground and underground parts of lettuce. The aboveground TC and Cu levels decreased by 2.49%-92.32% and 12.79%-36.47%, respectively. The underground TC and Cu levels decreased by 12.53%-55.64% and 22.41%-42.29%, respectively. Correlation analysis showed that nitrate nitrogen, chlorophyll, and soluble protein content of lettuce were negatively correlated with TC content, whereas malondialdehyde, proline content, and catalase activity were positively correlated with TC content. The resistance genes of lettuce were positively correlated with TC content (P < 0.05). In general, modified biochar was found to be more effective in improving lettuce growth quality and reducing pollutant accumulation compared to unmodified biochar, with modified sorghum straw biochar showing the best remediation effect.

Mechanisms of cadmium mitigation in tomato plants under orthophosphate and polyphosphate fertilization regimes.

Cadmium (Cd) is one of the most toxic elements in soil, affecting morphological, physiological, and biochemical processes in plants. Mineral plant nutrition was tested as an effective approach to mitigate Cd stress in several crop species. In this regard, the present study aimed to elucidate how different phosphorus (P) fertilization regimes can improve some bio-physiological processes in tomato plants exposed to Cd stress. In a hydroponic experiment, the impact of two phosphorus fertilizer forms (Polyphosphate (poly-P): condensed P-form with 100% polymerization rate and orthophosphate (ortho-P): from orthophosphoric acid) on the photosynthetic activity, plant growth, and nutrient uptake was assessed under three levels of Cd stress (0, 12, and 25 µM of CdCl2). The obtained results confirmed the negative effects of Cd stress on the chlorophyll content and the efficiency of the photosynthesis machinery. The application of poly-P fertilizer significantly improved the chlorophyll stability index (82%) under medium Cd stress (Cd12), as compared to the ortho-P form (55%). The analysis of the chlorophyll α fluorescence transient curve revealed that the amplitude of Cd effect on the different steps of electron transfer between PSII and PSI was significantly reduced under the poly-P fertilization regime compared to ortho-P, especially under Cd12. The evaluation of the RE0/RC parameter showed that the electron flux reducing end electron acceptors at the PSI acceptor side per reaction center was significantly improved in the poly-P treatment by 42% under Cd12 compared to the ortho-P treatment. Moreover, the use of poly-P fertilizer enhanced iron uptake and its stoichiometric homeostasis in the shoot tissue which maintained an adequate absorption of iron under Cd stress conditions. Findings from this study revealed for the first time that inorganic polyphosphate fertilizers can reduce Cd toxicity in tomato plants by enhancing photosynthesis activity, nutrient uptake, plant growth, and biomass accumulation despite the high level of cadmium accumulation in shoot tissues.

Algae development in rivers with artificially constructed weirs: Dominant influence of discharge over temperature.

Algal blooms contribute to water quality degradation, unpleasant odors, taste issues, and the presence of harmful substances in artificially constructed weirs. Mitigating these adverse effects through effective algal bloom management requires identifying the contributing factors and predicting algal concentrations. This study focused on the upstream region of the Seungchon Weir in Korea, which is characterized by elevated levels of total nitrogen and phosphorus due to a significant influx of water from a sewage treatment plant. We employed four distinct machine learning models to predict chlorophyll-a (Chl-a) concentrations and identified the influential variables linked to local algal bloom events. The gradient boosting model enabled an in-depth exploration of the intricate relationships between algal occurrence and water quality parameters, enabling accurate identification of the causal factors. The models identified the discharge flow rate (D-Flow) and water temperature as the primary determinants of Chl-a levels, with feature importance values of 0.236 and 0.212, respectively. Enhanced model precision was achieved by utilizing daily average D-Flow values, with model accuracy and significance of the D-Flow amplifying as the temporal span of daily averaging increased. Elevated Chl-a concentrations correlated with diminished D-Flow and temperature, highlighting the pivotal role of D-Flow in regulating Chl-a concentration. This trend can be attributed to the constrained discharge of the Seungchon Weir during winter. Calculating the requisite D-Flow to maintain a desirable Chl-a concentration of up to 20 mg/m3 across varying temperatures revealed an escalating demand for D-Flow with rising temperatures. Specific D-Flow ranges, corresponding to each season and temperature condition, were identified as particularly influential on Chl-a concentration. Thus, optimizing Chl-a reduction can be achieved by strategically increasing D-Flow within these specified ranges for each season and temperature variation. This study highlights the importance of maintaining sufficient D-Flow levels to mitigate algal proliferation within river systems featuring weirs.

Past environmental changes: using sedimentary photosynthetic pigments to enhance subtropical reservoir management.

The historical impacts of eutrophication processes were investigated in six subtropical reservoirs (São Paulo, Brazil) using a paleolimnological approach. We questioned whether the levels of pigment indicators of algal biomass could provide information about trophic increase and whether carotenoid pigments could offer additional insights. The following proxies were employed: organic matter, total phosphorus, total nitrogen, photosynthetic pigments (by high-performance liquid chromatography), sedimentation rates, and geochronology (by 210 Pb technique). Principal component analysis indicated a gradient of eutrophication. In eutrophic reservoirs (e.g., Rio Grande and Salto Grande), levels of lutein and zeaxanthin increased over time, suggesting growth of Chlorophyta and Cyanobacteria. These pigments were significantly associated with algal biomass, reflecting their participation in phytoplankton composition. In mesotrophic reservoirs, Broa and Itupararanga, increases and significative linear correlations (r > 0.70) between pigments and nutrients are mainly linked to agricultural and urban activities. In the oligotrophic reservoir Igaratá, lower pigment and nutrient levels reflected lesser human impact and good water quality. This study underscores eutrophication's complexity across subtropical reservoirs. Photosynthetic pigments associated with specific algal groups were informative, especially when correlated with nutrient data. The trophic increase, notably in the 1990s, may have been influenced by neoliberal policies. Integrated pigment and geochemical analysis offers a more precise understanding of eutrophication changes and their ties to human factors. Such research can aid environmental monitoring and sustainable policy development.

Study on color, aroma, and taste formation mechanism of large-leaf yellow tea during an innovative manufacturing process.

This study used samples processed with an innovative manufacturing process to explore the dynamic changes of large-leaf yellow tea (LYT) in color, aroma, and taste substances, and the quality components were most significantly affected in the stages of first pile-yellowing (FP) and over-fired drying (TD). In this process, the moisture and temperature conditions caused chlorophyll degradation, Maillard reactions, caramelization reactions, and isomerization of phenolic substances, forming the quality of LYT. Specifically, chlorophyll degradation favored the formation of color quality; the taste quality was determined by the content of soluble sugars, amino acids, catechins, etc.; the aroma quality was dependent on the content changes of alcohols and aldehydes, as well as the increase of sweet and roasting aroma substances in the third drying stage. Additionally, twelve key aroma components, including linalool, (E)-ß-ionone, 2,3-diethyl-5-methyl-pyrazine, etc., were identified as contributors to revealing LYT rice crust-like and sweet aroma formation mechanism.

The influence mechanism of water level operation on algal blooms in canyon reservoirs and bloom prevention.

The water level operation of reservoirs affects the spatiotemporal patterns of water quality, light-heat, hydrodynamics and phytoplankton, which have implications for algal bloom prevention. However, the theoretical analysis and practical applications of related research are limited. Based on prototype observations and numerical modeling, data on algae, water level operation and environmental factors in the Zipingpu Reservoir from April and September in 2015 to 2017 and 2020 to 2022 were collected. An in-depth analysis of the causal mechanisms between algal blooms and water level operation was performed, and prevention strategies with practical application assessments were developed. Water level operation control in the reservoir from April to September can be divided into five stages (falling-rising-oscillating-falling-rising), with algal blooms occurring only in the second stage. The rising water level with inflow into the middle layers shapes a closed-loop circulation in the surface waters. This distributes the nutrients that were trapped in the surface layer during the first stage, helping algae avoid to phosphorus limitation and thrive in the closed loop circulation, leading to algal blooms (chlorophyll-a exceeding 10 mg/m3). There is a significant positive correlation (p < 0.05) between algal blooms and the rapid rise in water levels in the second stage, occurring within a span of three days. To contain the algal bloom, a water level operation limit of rising waters on the third day after a two-day consecutive rise in water level was examined. This was found to be effective after its practical application to the case reservoir in 2022, with chlorophyll-a concentrations consistently below 10 mg/m3. This study unveils the mechanisms through which water level operation affects algal blooms and presents a successful case of bloom prevention. Furthermore, it serves as a valuable reference for the management of canyon reservoirs.

Analysis of Cadmium Contamination in Lettuce (Lactuca sativa L.) Using Visible-Near Infrared Reflectance Spectroscopy.

In order to rapidly and accurately monitor cadmium contamination in lettuce and understand the growth conditions of lettuce under cadmium pollution, lettuce is used as the test material. Under different concentrations of cadmium stress and at different growth stages, relative chlorophyll content of lettuce leaves, the cadmium content in the leaves, and the visible-near infrared reflectance spectra are detected and analyzed. An inversion model of the cadmium content and relative chlorophyll content in the lettuce leaves is established. The results indicate that cadmium concentrations of 1 mg/kg and 5 mg/kg promote relative chlorophyll content, while concentrations of 10 mg/kg and 20 mg/kg inhibit relative chlorophyll content. The cadmium content in the leaves increases with increasing cadmium concentrations. Cadmium stress caused a "blue shift" in the red edge position only during the mature period, while the red valley position underwent a "blue shift" during the seedling and growth periods and a "red shift" during the mature period. The green peak position exhibited a "blue shift". After model validation, it was found that the model constructed using the ratio of red edge area to yellow edge area and the normalized values of red edge area and yellow edge area effectively estimated the cadmium content in lettuce leaves. The model established using the normalized vegetation index of the red edge and the ratio of the peak green value to red shoulder amplitude can effectively estimate the relative chlorophyll content in lettuce leaves. This study demonstrates that the visible-near infrared spectroscopy technique holds great potential for monitoring cadmium contamination and estimating chlorophyll content in lettuce.

Ecological changes in subtidal macrobenthic communities of the Taean coast following the Hebei Spirit oil spill: A 10-year longitudinal study.

We examined long-term response (2008-2017) of the macrobenthos to the Hebei Spirit oil spill that occurred around the Taean coast, Korea, in December 2007. Oil concentrations were below the Korea/US environmental standards as of January 2008. Organic matter, chlorophyll-a, and zooplankton abundance dominated by Noctiluca scintillans were higher after the spill. Macrobenthic diversity recovered to pre-incident (2007) level in 2011. Biomass exceeded that level in 2011 and the increase prolonged for 5 years. Cross-correlation and regression analyses showed that chlorophyll-a at year t and zooplankton abundance at t-2 had a significant relationship with macrobenthic biomass at t (p < 0.05 for both), suggesting the transfer of increased organic matter (transformed from crude oil within the pelagic ecosystem) into the benthic ecosystem. Coastal wetlands around the incident area, vulnerable to oil pollution and slowly remobilizing accumulated oil, seemed to affect pelagic ecosystem processes and the unexpectedly increased and sustained biomass.

Spatio-temporal variation and environmental drivers of chlorophyll a concentration and diatom community in four small urban lakes of Kunming, China.

Chlorophyll a (Chla) and diatom community structure are two indicators of lake water quality. In this study, we investigated the environmental parameters, chlorophyll a, and diatom community of four small urban lakes in Kunming (Beitan, Beihu, Nanhu and Longtan lakes in the campus of Yunnan Normal University) between March 2017 and December 2019. The results showed that the concentrations of total nitrogen (TN), total phosphorus (TP), and Chla in the four lakes showed significant seasonal fluctuation. The Chla concentration in Nanhu Lake, which had the highest nutrient level among the four lakes, was significantly higher than that in the other three lakes and largely affected by TN. In comparison, water temperature significantly contributed to the increases in Chla concentration in the other three lakes. Water temperature and TN were significantly correlated with Chla across the four lakes. Diatom assemblages in Beitan, Nanhu, and Longtan lakes were dominated by planktonic diatoms, and benthic diatoms were dominant in the shallowest lake Beihu, suggesting that water depth significantly affected the proportion of planktonic diatoms and dominant taxa. Water depth, TN, TP, transparency, and water temperature affected the spatio-temporal changes of diatom community structure, with water temperature as the major factor in causing the seasonal variation in diatom community, and TN and TP as the major drivers for community variation among lakes within the same season.

The benefits of restoring urban lakes in the tropics.

Lake restoration in developing economies, particularly in the tropics, is a major challenge given the severe levels of pollution from untreated wastewater and the warm climate conducive to microbial and algal growth. Restoration goals are often ill-defined or unachievable. Here we describe the successes that can be achieved through a control, compared with intervention case study of the two urban lakes in Bengaluru, India, one of the world's largest and fastest growing mega-cities. The unrestored control, Bellandur Lake, was severely polluted by 231 million litres per day (MLD) of untreated wastewater. The restoration site, Jakkur Lake, receives 10 MLD of treated wastewater and also receives some tertiary treatment by circulating the effluent through a constructed wetland before it enters the lake. The water quality of Bellandur Lake can only be described as extremely bad. Organic pollution levels in the main inflow were high (BOD5 of 199 mg/l, faecal coliforms 6.9 Log MPN/100 ml, total suspended solids (TSS) of 285 mg/l) leading to the complete deoxygenation of lake even at the surface. The levels exceeded use-base standards for bathing water and fisheries. The high levels of organic pollution and low oxygen conditions also led to extreme levels of methane emissions that occasionally led to the lake surface catching fire. Total nitrogen (TN) and total phosphorus (TP) concentrations in the lake were extremely high (47 mg/l and 6.3 mg/l) respectively with low Secchi depth (SD). Despite the high nutrient levels, very little phytoplankton growth occurred (chlorophyll-a of 0 mg/l), most likely due to the high TSS loads which restricted light availability. In comparison, the wastewater treatment and wetland at Jakkur Lake markedly reduced organic pollution of the main inflow (BOD5 of 32 mg/l, faecal coliforms 4.1 Log MPN/100 ml, TSS of 48 mg/l). Levels of coliforms in the lake were above the standards for bathing waters. Total nitrogen (TN) and total phosphorus (TP) concentrations in the lake reduced (10.5 mg/l, 2.4 mg/l) but still classify the lake as extremely hypereutrophic. The lower TSS levels did, however, enable dense phytoplankton blooms to develop (max chlorophyll-a of 600 µg/l) which are in part responsible for the higher levels of dissolved oxygen in the lake water, albeit and as expected with large diurnal fluctuations. The comparison highlights the benefits that standard wastewater treatment provides to restore urban tropical lakes in context of rapidly urbanising catchments, and even though Jakkur Lake is by no means fully restored, it sustains water quality that allow propagation of fisheries and shore-based recreation. It also greatly contributes to greenhouse gas emission reductions. Further restoration measures are likely needed for urban tropical lakes, particularly to tackle pollutant loads in monsoon periods, but restoring community pride in the uses of a lake is an important milestone of the restoration efforts.

Relative impact of environmental variables on the lake trophic state highlights the complexity of eutrophication controls.

For the effective management of lakes apart from defining and monitoring their current state it is crucial to identify environmental variables that are mostly responsible for the nutrient input. We used interpretative machine learning to investigate the environmental parameters that influence the lake's trophic state and recognize their patterns. We analysed the influence of the 25 environmental variables on the commonly used trophic state indicators values: total phosphorus (TP), Chlorophyll-a (Chl-a) and Secchi depth (SD) of 60 lakes located in the Central European Lowlands. We attempted to delineate the lakes into groups due to the influence of common prevailing environment variable/variables on the water trophic state reflected by each indicator. The results indicated that the relative impact of environmental variables on the lake trophic state has an individual hierarchy unique for each indicator. The most important are variables related to catchment impact on the lake, Ohle ratio (L. catchment area/L. area) for TP and Schindler ratio (L. area + L. catchment area)/L. volume for Chl-a and SD. There are also few variables strongly influential only for small sub-groups of lakes that stand out: lake maximum depth, catchment slope steepness expressed by the height standard deviation. The methods used in the study enabled the assessment of the character of the influence of the environmental variables on the indicator value and revealed that most essential variables (Ohle ratio for TP and Schindler ratio for Chl-a and SD) have bimodal distribution with a clear threshold value. These findings contribute to a better understanding of the drivers shaping the lake trophic status and have implication for planning effective management strategies.

Chlorophyll-a prediction in tropical reservoirs as a function of hydroclimatic variability and water quality.

The study goal was to determine spatiotemporal variations in chlorophyll-a (Chl-a) concentration using models that combine hydroclimatic and nutrient variables in 150 tropical reservoirs in Brazil. The investigation of seasonal variability indicated that Chl-a varied in response to changes in total nitrogen (TN), total phosphorus (TP), volume (V), and daily precipitation (P). Therefore, an empirical model for Chl-a prediction based on the product of TN, TP, and normalized functions of V and P was proposed, but their individual exponents as well as a general multiplicative factor were adjusted by linear regression for each reservoir. The fitted relationships were capable of representing algal temporal dynamics and blooms, with an average coefficient of determination of R2 = 0.70. The results revealed that nutrients yielded better predictability of Chl-a than hydroclimatic variables. Chl-a blooms presented seasonal and interannual variability, being more frequent in periods of high precipitation and low volume. The equations demonstrate different Chl-a responses to the parameters. In general, Chl-a was positively related to TN and/or TP. However, in some cases (22%), high nutrient concentrations reduced Chl-a, which was attributed to limited phytoplankton growth driven by light deficiency due to increased turbidity. In 49% of the models, precipitation intensified Chl-a levels, which was related to increases in the nutrient concentration from external sources in rural watersheds. Contrastingly, 51% of the reservoirs faced a decrease in Chl-a with precipitation, which can be explained by the opposite effect of dilution of nutrient concentration at the reservoir inlet in urban watersheds. In terms of volume, in 67% of the reservoirs, water level reduction promoted an increase in Chl-a as a response to higher nutrient concentration. In the other cases, Chl-a decreased with lower water levels due to wind-induced destratification of the water column, which potentially decreased the internal nutrient release from bottom sediment. Finally, applying the model to the two largest studied reservoirs showed greater sensitivity of Chl-a to changes in water use classes regarding variations in TN, followed by TP, V, and P.

Seasonal and interannual responses of blue-green algal taxa and chlorophyll to a monsoon climate, flow regimes, and N:P ratios in a temperate drinking-water reservoir.

Blooms of blue-green algae (BGA) threaten drinking water safety and ecosystems worldwide. Understanding mechanisms and driving factors that promote BGA proliferation is crucial for effective freshwater management. This study tested the response of BGA growth to environmental variations driven by nutrients (N and P), N:P ratios, and flow regime depending on the influence of the Asian monsoon intensity and identified the critical regulatory factors in a temperate drinking-water reservoir, using weekly interval samplings collected during 2017-2022. The hydrodynamic and underwater light conditions experienced significant changes in summers due to high inflows and outflows associated with intense rainfalls, and these conditions strongly influenced the proliferation of BGA and total phytoplankton biomass (as estimated by chlorophyll-a [CHL-a]) during summer monsoons. However, the intense monsoon resulted in the post-monsoon blooms of BGA. The monsoon-induced phosphorus enrichment, facilitated through soil washing and runoff, was crucial in promoting phytoplankton blooms in early post-monsoon (September). Thus, the monomodal phytoplankton peak was evident in the system, compared to the bimodal peaks in North American and European lakes. Strong water column stability in the weak monsoon years depressed phytoplankton growth and BGA, suggesting the importance of the intensity of monsoon. The low N:P ratios and longer water residence time increased BGA abundance. The predictive model of BGA abundance accounted for the variations largely (Mallows' Cp = 0.39, adjusted R2 = 0.55, p < 0.001) by dissolved phosphorus, N:P ratios, CHL-a, and inflow volume. Overall, this study suggests that monsoon intensity was the key triggering factor regulating the interannual BGA variations and facilitated the post-monsoon blooms through increased nutrient availability.

Trophic status and lake depth play important roles in determining the nutrient-chlorophyll a relationship: Evidence from thousands of lakes globally.

A fundamental problem in lake eutrophication management is that the nutrient-chlorophyll a (Chl a) relationship shows high variability due to diverse influences of for example lake depth, lake trophic status, and latitude. To accommodate the variability induced by spatial heterogeneity, a reliable and general insight into the nutrient-Chl a relationship may be achieved by applying probabilistic methods to analyze data compiled across a broad spatial scale. Here, the roles of two critical factors determining the nutrient-Chl a relationship, lake depth and trophic status, were explored by applying Bayesian networks (BNs) and a Bayesian hierarchical linear regression model (BHM) to a compiled global dataset from 2849 lakes and 25083 observations. We categorized the lakes into three groups (shallow, transitional, and deep) according to mean and maximum depth relative to mixing depth. We found that despite a stronger effect of total phosphorus (TP) and total nitrogen (TN) on Chl a when combined, TP played a dominant role in determining Chl a, regardless of lake depth. However, when the lake was hypereutrophic and/or TP was >40 µg/L, TN had a greater impact on Chl a, especially in shallow lakes. The response curve of Chl a to TP and TN varied with lake depth, with deep lakes having the lowest yield Chl a per unit of nutrient, followed by transitional lakes, while shallow lakes had the highest ratio. Moreover, we found a decrease of TN/TP with increasing Chl a concentrations and lake depth (represented as mixing depth/mean depth). Our established BHM may help estimating lake type and/or lake-specific acceptable TN and TP concentrations that comply with target Chl a concentrations with higher certainty than can be obtained when bulking all lake types.

[Analysis of Influencing Factors of Chlorophyll-a in Lake Taihu Based on Bayesian Network].

Global warming has aggravated the problem of lake eutrophication. As a typical large, eutrophic, shallow lake in China, the issue of cyanobacterial harmful algal blooms (cyanoHABs) was particularly prominent in Lake Taihu. We took Lake Taihu as the study area, using the meteorological (temperature, wind speed, rainfall, and sunshine hours), water quality (total nitrogen, total phosphorus, conductivity, pH, and chemical oxygen demand), and biological (chlorophyll-a in phytoplankton) monitoring data from 1992 to 2020. We built a simulation model of chlorophyll-a based on the Bayesian network model with continuous variables to study the chlorophyll-a level of Lake Taihu under different meteorological and water quality conditions. The 75th percentile of chlorophyll-a concentration was used as the threshold to judge the risk of cyanobacterial bloom. When the probability of chlorophyll-a concentration below this threshold was greater than 75%, it was regarded as "low risk" of cyanobacterial bloom outbreak. The results showed that the average level of "temperature wind ratio" (ratio of air temperature to wind speed) in spring was 6.67℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.130 mg·L-1. The average "temperature wind ratio" level in summer was 10.52℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.257 mg·L-1. The average level of total phosphorus concentration in autumn was 0.154 mg·L-1, and the probability of high chlorophyll-a was less than 75% when the "temperature wind ratio" was less than 6.30℃·s·m-1. Based on the above research, the chlorophyll-a model constructed by the Bayesian network model with continuous variables was further used to simulate the nutrient control objectives under different climate change backgrounds. In order to control chlorophyll-a in Lake Taihu at the:"low risk" level of cyanoHABs, the target concentration thresholds of total phosphorus needed to be controlled under the climate level background from 1992 to 2000, 2001 to 2010, and 2011 to 2020 were given. From 1992 to 2000, the threshold value of total phosphorus concentration was 0.135 mg·L-1 in spring, 0.174 mg·L-1 in summer, and 0.171 mg·L-1 in autumn. From 2001 to 2010, the threshold value of total phosphorus concentration was 0.115 mg·L-1 in spring, 0.164 mg·L-1 in summer, and 0.162 mg·L-1 in autumn. From 2011 to 2020, the threshold value of total phosphorus concentration was 0.059 mg·L-1 in spring, 0.145 mg·L-1 in summer, and 0.145 mg·L-1 in autumn. The results showed that the control of cyanoHABs in eutrophic lakes required more stringent nutrient control strategies with global warming. It provided a reference for preventing and controlling cyanoHABs and eutrophication in Lake Taihu. Previous studies have used multiple regression models, hydrodynamic numerical models, and other methods to predict chlorophyll-a concentrations or cyanobacterial blooms in lakes. However, there has been no study on the prediction of cyanoHABs in lakes based on the Bayesian network model with continuous variables and the "dynamic" evaluation of nutrient thresholds. Therefore, based on the seasonal meteorological, water quality, and biological monitoring data of Lake Taihu from 1992 to 2020, the chlorophyll-a model of Lake Taihu was constructed for the first time based on the Bayesian network model with continuous variables to simulate the chlorophyll-a concentration of Lake Taihu under different climate indicators and total phosphorus concentrations. The weight of its influencing factors was also analyzed, and the nutrient control objectives under different climate scenarios were "dynamically" evaluated.

Eutrophication assessment in Pannonian Basin (the case of Ludas Lake Special Nature Reserve and Palic Nature Park).

Agricultural, industrial, and human activities in general threaten water quality, as well as the biotic integrity of aquatic ecosystems. The increased concentration of total nitrogen (TN) and phosphorus (TP) affects high concentrations of chlorophyll (Chl-a) in freshwater ecosystems, which causes the process of eutrophication of the waters of shallow lakes. Eutrophication, as an alarming threat to the global quality of surface waters, affects environmental degradation. This research assesses the risk of eutrophication caused by chemical oxygen demand (COD), TN, TP, Secchi disk (SD), and Chl-a using the trophic level index (TLI) in Palic and Ludas lakes. Both lakes have been nominated as potential Natura 2000 areas in 2021 because they belong to important bird areas, and Ludas Lake has the status of Ramsar site 3YU002. In the research period from 2011 to 2021, the results showed that the lake is in an extremely eutrophic state. Laboratory analyses indicate an increased concentration of Chl-a during autumn. In the paper, the normalized difference chlorophyll index (NDCI) was calculated using the Google Earth Engine platform, and the result indicates the loading of the lake throughout the year, with an emphasis on winter, summer, and autumn. By using satellite images and remote sensing, it is possible to determine the most degraded spots, which is a help to the researchers in choosing the places where the samples will be taken and thus act more efficiently on the most endangered parts, as well as reduce the costs of standard in situ methods.

Prediction and sensitivity analysis of chlorophyll a based on a support vector machine regression algorithm.

Outbreaks of planktonic algae seriously affect the water quality of rivers and are difficult to control. Based on the analysis of the temporal and spatial variation characteristics of environmental factors, this study uses a support vector machine regression (SVR) algorithm to establish a chlorophyll a (Chl-a) prediction model and conduct Chl-a sensitivity analysis. In 2018, the average Chl-a content was 126.25 ug/L. The maximum total nitrogen (TN) content was 16.68 mg/L and high year-round. The average NH4+-N and total phosphorous (TP) contents were only 0.78 and 0.18 mg/L. The content of NH4+-N was higher in spring and increased significantly along the water flow, while TP decreased slightly along the water flow. We used a radial basis function kernel SVR model and tenfold cross-validation method to optimize parameters. The penalty parameter c was 1.4142, the kernel function parameter g was 1, and the training and verification errors were only 0.032 and 0.067, respectively, indicating a good model fit. Based on a sensitivity analysis of the SVR prediction model, the maximum sensitivity coefficients of Chl-a to TP and WT were 0.571 and 0.394, respectively, and the contributions were 33% and 22%, respectively. The next highest sensitivity coefficients were those of DO (0.28, 16%) and pH (0.243, 14%). The sensitivity coefficients of TN and NH4+-N were the lowest. According to the current water environment pollution conditions, TP is the limiting factor of Chl-a in the Qingshui River, and it is also the main prevention and control factor of phytoplankton outbreak.

Assessing lake water quality during COVID-19 era using geospatial techniques and artificial neural network model.

The present study evaluates the impact of the COVID-19 lockdown on the water quality of a tropical lake (East Kolkata Wetland or EKW, India) along with seasonal change using Landsat 8 and 9 images of the Google Earth Engine (GEE) cloud computing platform. The research focuses on detecting, monitoring, and predicting water quality in the EKW region using eight parameters-normalized suspended material index (NSMI), suspended particular matter (SPM), total phosphorus (TP), electrical conductivity (EC), chlorophyll-α, floating algae index (FAI), turbidity, Secchi disk depth (SDD), and two water quality indices such as Carlson tropic state index (CTSI) and entropy­weighted water quality index (EWQI). The results demonstrate that SPM, turbidity, EC, TP, and SDD improved while the FAI and chlorophyll-α increased during the lockdown period due to the stagnation of water as well as a reduction in industrial and anthropogenic pollution. Moreover, the prediction of EWQI using an artificial neural network indicates that the overall water quality will improve more if the lockdown period is sustained for another 3 years. The outcomes of the study will help the stakeholders develop effective regulations and strategies for the timely restoration of lake water quality.

The air temperature change effect on water quality in the Kvarken Archipelago area.

The Kvarken Archipelago is Finland's World Heritage site designated by UNESCO. How climate change has affected the Kvaken Archipelago remains unclear. This study was conducted to investigate this issue by analyzing air temperature and water quality in this area. Here we use long-term historical data sets of 61 years from several monitoring stations. Water quality parameters included chlorophyll-a; total phosphorus; total nitrogen; coliform bacteria thermos tolerant; temperature; nitrate as nitrogen; nitrite-nitrate as nitrogen, and Secchi depth and correlations analysis was conducted to identify the most relevant parameters. Based on the correlation analysis of weather data and water quality parameters, air temperature showed a significant correlation with water temperature (Pearson's correlations = 0.89691, P < 0.0001). The air temperature increased in April (R2 (goodness-of-fit) = 0.2109 &P = 0.0009) and July (R2 = 0.1207 &P = 0.0155) which has indirectly increased the chlorophyll-a level (e.g. in June increasing slope = 0.39101, R2 = 0.4685, P < 0.0001) an indicator of phytoplankton growth and abundance in the water systems. The study concludes that there might be indirect effects of the likely increase in air temperature on water quality in the Kvarken Archipelago, in particular causing water temperature and chlorophyll-a concentration to increase at least in some months.

Chlorophyll Pigments of Olive Leaves and Green Tea Extracts Differentially Affect Their Antioxidant and Anticancer Properties.

Plant-based extracts possess biological potential due to their high content of phytochemicals. Nevertheless, photosynthetic pigments (e.g., chlorophylls) that are also present in plant extracts could produce undesirable pro-oxidant activity that might cause a negative impact on their eventual application. Herein, the phenolic content of olive leaf (OLE) and green tea (GTE) extracts was assayed, and their antioxidant and anticancer activities were evaluated before and after the removal of chlorophylls. Regarding phenolic content, OLE was rich in hydroxytyrosol, tyrosol as well as oleuropein, whereas the main compounds present in GTE were gallocatechin, epigallocatechin (EGC), epigallocatechin gallate (EGCG), gallocatechin gallate, and caffeine. Interestingly, fresh extracts' antioxidant ability was dependent on phenolic compounds; however, the elimination of chlorophyll compounds did not modify the antioxidant activity of extracts. In addition, both OLE and GTE had high cytotoxicity against HL-60 leukemic cell line. Of note, the removal of chlorophyll pigments remarkably reduced the cytotoxic effect in both cases. Therefore, our findings emphasize the remarkable antioxidant and anticancer potential of OLE and GTE and suggest that chlorophylls are of paramount importance for the tumor-killing ability of such plant-derived extracts.