Meteorological and hydrological conditions driving the formation and disappearance of black blooms, an ecological disaster phenomena of eutrophication and algal blooms

A critical review of microbial profiles in black and odorous waters

Black and odorous waters (BOWs) are a serious environmental problem frequently reported over the past few decades. Microorganisms are identified as implementors of the black and odorous phenomenon, which play a crucial role in the decomposition and transformation of pollutants within the BOWs. However, the information on the role of microorganisms in BOWs remains elusive. BOWs are characterized by high concentrations of organic compounds and limited oxygen inputs, which have facilitated the emergence of distinct microbial species. The algae, hydrolytic and fermentative bacterium, sulfate-reducing bacteria, Fe-reducing bacteria and other microorganisms play an important role in the process of blackening and odorization of waters. Studying these specific microbial taxonomies provides valuable insights into their adaptations and contributions to the overall functioning of BOWs. This study comprehensively reviews 1) the microbial community structure, assembly and succession in BOWs; 2) the key microbial profiles involved in BOWs formation; 3) the interspecies interactions process in the BOWs, which are the issues easily overlooked but deserve further research and development.

The response of chlorophyll a to nutrient and hydro-meteorological factors in Lake Taihu

Chlorophyll a (Chla) concentration is a key indicator of the biomass of phytoplankton such as algae in freshwater ecosystems. Understanding its response to nutrient and hydro-meteorological factors is vital for managing eutrophication in Lake Taihu, one of China's largest freshwater lakes. This study investigates Chla dynamics in relation to nutrient levels (nitrogen, phosphorus, etc.), hydro-meteorological parameters (temperature, wind, precipitation, etc.), and previous season factors (the values of the factors mentioned above in the previous season) in Lake Taihu. By using various statistical analyzing methods (such as partial least squares regression) and introducing two new indices (similarity and influence), this research witnessed an upward trend in Chla concentration over the past three decades. And the similarity index between predicted and observed results is 0.8425, if all factors are considered, while the similarity index decreases by 6.94% and 33.27% when considering only current or previous factors, respectively. This demonstrates that antecedent seasonal parameters exert some influence on the developmental trend of Chla concentrations in Lake Taihu. When temporal seasonality is abstracted from consideration, air temperature emerges as the predominant forcing factor governing Chla dynamics. Seasonal correlations indicate that, in spring and summer, to control eutrophication and algae bloom in Lake Taihu, a comprehensive approach considering multiple factors is necessary, but the most important action should be controlling biomass of phytoplankton, while in autumn, reducing phosphorus input is crucial. This study provides not only quantitative analyses of the seasonal trends in Chla concentration but also detailed and actionable insights for sustainable freshwater ecosystem management in Lake Taihu.

Explainable deep learning identifies patterns and drivers of freshwater harmful algal blooms

The escalating magnitude, frequency, and duration of harmful algal blooms (HABs) pose significant challenges to freshwater ecosystems worldwide. However, the mechanisms driving HABs remain poorly understood, in part due to the strong regional specificity of algal processes and the uneven data availability. These complexities make it difficult to generalize HAB dynamics and effectively predict their occurrence using traditional models. To address these challenges, we developed an explainable deep learning approach using long short-term memory (LSTM) models combined with explanation techniques that can capture complex patterns and provide explainable insights into key HAB drivers. We applied this approach for algal density modeling at 102 sites in China's lakes and reservoirs over three years. LSTMs effectively captured daily algal dynamics, achieving mean and maximum Nash-Sutcliffe efficiency coefficients of 0.48 and 0.95 during testing phase. Moreover, water temperature emerged as the primary driver of HABs both nationally and in over 30% of localities, with stronger water temperature sensitivity observed in mid-to low-latitudes. We also identified regional similarities that allow for the successful transferability in modeling algal dynamics. Specifically, using fine-tuned transfer learning, we improved the prediction accuracy in over 75% of poorly gauged areas. Overall, LSTM-based explainable deep learning approach effectively addresses key challenges in HAB modeling by tackling both regional specificity and data limitations. By accurately predicting algal dynamics and identifying critical drivers, this approach provides actionable insights into the mechanisms of HABs, ultimately aids in the implementation of effective mitigation measures for nationwide and regional freshwater ecosystems.

Impact of extreme rainfall and flood events on harmful cyanobacterial communities and ecological safety in the Baiyangdian Lake Basin, China

Globally, climate change has intensified extreme rainfall events, leading to substantial hydrological changes in aquatic ecosystems. These changes, in turn, have increased the frequency of harmful algal blooms, particularly those of cyanobacteria. This study examines cyanobacterial community dynamics in the Baiyangdian Lake Basin, China, after heavy rainfall and flooding events. The aim was to clarify how such extreme hydrological events affect cyanobacterial populations in floodplain ecosystems and assess related ecological risks. The results demonstrated a significant increase in cyanobacterial diversity, exemplified by an increase of the Shannon diversity index from an average of 1.72 to 2.1 (p < 0.05). Following heavy rainfall and subsequent flooding, the average relative abundance of cyanobacteria in the microbial community increased from 7.59 % to 9.62 %, along a notable rise in the abundance of harmful cyanobacteria. The community structure exhibited notable differences after flooding, showing an increase in species richness, but a decrease in community tightness and clustering, as well as a reduction in niche overlap among harmful cyanobacteria. Environmental factors such as dissolved oxygen, water temperature, and pH were identified as crucial predictors of harmful cyanobacterial community differences and abundance variations resulting from flooding. These findings provide a critical framework for predicting ecological risks associated with the expansion of bloom-forming cyanobacteria in large shallow lake basins, particularly under intensified rainfall and flooding events. This insight is essential to anticipate potential ecological disruptions in sensitive aquatic ecosystems.

Exploring Spatiotemporal Patterns of Algal Cell Density in Lake Dianchi with Explainable Machine Learning

The escalating global occurrence of algal blooms poses a growing threat to ecosystem services. In this study, the spatiotemporal heterogeneity of water quality parameters was leveraged to partition Lake Dianchi into three clusters. Considering water quality parameters and both the delayed and instantaneous effects of meteorological factors, ensemble learning, and quasi-Monte Carlo methods were employed to predict daily algal cell density (AD) between January 2021 and January 2024. Consistently, superior predictive accuracy across all three clusters was exhibited by the Stacking-Elastic-Net regularization model. Furthermore, the minimum combination of drivers that achieved near-optimal accuracy for each cluster was identified, striking a balance between accuracy and cost. The ranking of the effect of drivers on AD varied by cluster, while the delayed effect of meteorological factors on AD generally outweighed their instantaneous effect for all clusters. Additionally, the heterogeneous or homogeneous thresholds and responses between drivers and AD were explored. These findings could serve as a scientific and cost-effective basis for government agencies to develop regional sustainable strategies for managing water quality.

Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning

Algal blooms, exacerbated by climate change and eutrophication, have emerged as a global concern. In this study, we introduce a novel interpretable machine learning (ML) workflow tailored for investigating the dynamics of algal populations in grass-type lakes, Liangzi lake. Utilizing seven ML methods and incorporating the covariance matrix adaptation evolution strategy (CMA-ES), we predict algal density across three distinct time periods, resulting in the construction of a total of 30 ML models. The CMA-ES-CatBoost model consistently demonstrates superior predictive accuracy and generalization capability across these periods. Through the collective validation of various interpretable tools, we identify water temperature and permanganate index as the two most critical water quality parameters (WQIs) influencing algal density in Liangzi Lake. Additionally, we quantify the independent and interactive effects of WQIs on algal density, pinpointing key thresholds and trends. Furthermore, we determine the minimum combination of WQIs that achieves near-optimal predictive performance, striking a balance between accuracy and cost-effectiveness. These findings offer a scientific and economically efficient foundation for governmental agencies to formulate strategies for water quality management and sustainable development.

A review of the formation conditions and assessment methods of black and odorous water

Black and odorous water is an extreme pollution phenomenon. This article reviews the formation process, formation conditions, and evaluation methods of black and odorous water. The results indicate that N, P, and TOC are the key nutrients inducing black and odorous water while S, Fe, and Mn are key elements forming blackening and odorizing pollutants. In addition, Cyanobacteria, Proteobacteria, Firmicutes, Verrucomicrobia, Planctomycetes, and Actinobacteria participate in the biogeochemistry cycles of key elements and play important roles in the blackening and odorizing process of water. The black and odorous thresholds that need further verification are as follows: 1.0 g/L of organic matrix, 2.0-8.0 mg/L of NH3-N, 0.6-1.2 mg/L of TP, 0.05 mg/L of Fe2+, 0.3 mg/L of Mn2+, 1.2-2.0 mg/L of DO, and -50 to 50 mV of the ORP. In order to propose a universal assessment method, it is suggested that NH3-N, DO, COD, BOD, and TP serve as the assessment indicators, and the levels of pollutions are I (not black odor), II (mild black odor), III (moderate black odor), IV (severe black odor), and inferior IV (extremely black odor).

Vertical distribution rules and factors influencing phytoplankton in front of a drinking water reservoir outlet

The phenomenon of algal blooms caused by the excessive proliferation of phytoplankton in drinking water reservoirs is becoming increasingly frequent, seriously endangering water quality, ecosystems, water safety, and people's health. Thus, there is urgent need to conduct research on the distribution rules and factors influencing phytoplankton in drinking water reservoirs. Given that the outflows from reservoirs usually come from the middle and lower layers of the water column and the current studies on phytoplankton in drinking water reservoirs are usually carried out on the surface, an 8-month monitoring of vertical phytoplankton and the corresponding influencing factors in front of the outlet in a drinking water reservoir was conducted. Based on the monitoring results, the distribution rules of phytoplankton and the associated factors were analyzed. The results showed that phytoplankton biomass significantly decreased with increasing water depth, but the biomass near the outlet (40 m depth) still reached the WHO level 2 warning threshold for algal blooms multiple times. During the monitoring period, Cyanophyta, Chlorophyta and Bacillariophyta dominated. The selected multisource environmental factors explained 60.5 % of the spatiotemporal changes in phytoplankton, with thermal intensity (water temperature and thermal stratification intensity) being the driving factor. Meanwhile, excessive TN and TP provided necessary conditions for the growth of phytoplankton. Based on influencing factors, reducing upstream nutrient inflows and thermal stratification intensity are recommended as measures to prevent and control algal blooms. This study provides insights into the vertical distribution rules and factors influencing phytoplankton in a drinking water reservoir, which can provide a reference for the management of drinking water reservoirs and the prevention and control of algal blooms.

Temporal characteristics and trends of nitrogen loadings in lake Taihu, China and its influencing mechanism at multiple timescales

Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO3--N) and ammonium (NH4+-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH4+-N and NO3--N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH4+-N and NO3-N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH4+-N and NO3--N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH4+-N and NO3--N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH4+-N and NO3-N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.

Flow backward alleviated the river algal blooms

Mechanistic understanding and prediction of river algal blooms remain challenging. It is generally believed that these blooms are formed by the slowdown of water dynamics in tributaries due to the support of the main stream. However, few studies have investigated the impact of flow backward caused by the difference in water dynamics between the main stream and tributaries. Here, we focus on the eutrophication issue in the middle-lower reaches of the Han River, which is affected by the Middle Route of the South-to-North Water Diversion Project (SNWDP), the largest inter-basin water transfer project in Asia. We discover that the reversal of the Yangtze River water level could effectively alleviate the occurrence of Han River water blooms. The Yangtze River frequently back flows into the lower reaches of the Han River, with the probability of such events increasing as it nears the confluence (20 km from the Yangtze: 9.5 %, 10 km: 19.0 %, 8 km: 28.6 %). This flow backward carries nutrients that reduce the nitrogen to phosphorus ration (N:P), leading to a shift in the nutrient structure of the Han River. This change is concomitant with a significant decline in algae biomass (Chlorophyll-a = 11.19 µg·L-1 and algae density = 0.41×107 cells·L-1 under natural flow, Chlorophyll-a = 5.19 µg·L-1 and algae density = 0.18×107 cells·L-1 under flow backward), as well as a weakening of the correlation (R) between diatom density and chlorophyll-a concentration, i.e., R = 0.38 (p>0.05) under flow backward conditions versus R = 0.72 (p<0.01) under natural flow conditions. As phosphorus limitation typically suppresses algae growth, the correlation between diatom density and chlorophyll-a concentration can help to reveal the dominance of diatoms, with stronger correlations indicating greater diatom dominance. Consequently, our study provides evidence that the flow backward can alleviate river algal blooms by weakening the growth advantage of diatoms. This study could prove valuable in investigating the eutrophication mechanism within the complex hydrodynamic conditions of rivers. SYNOPSIS: Flow backward caused by the water level difference between the main streams and tributary alleviated the occurrence of river algal blooms in the confluence area.

Potamogeton crispus restoration increased the epiphytic microbial diversity and improved water quality in a micro-polluted urban river

Special characterization and assembly of epiphytic microbial communities remain unclear in micro-polluted water column during submersed macrophytes restoration. In this study, an in-situ enclosure area sowing with turions of Potamogeton crispus (P. crispus) was conducted in a micro-polluted urban river to investigate the characterization of P. crispus and epiphytic microbial communities and their response to water environment under different water depths. Turions completely germinated in water column with <90 cm water depth and the germination speed decreased with increasing water depth within 18 days. There were obvious differences in morphological characteristics of P. crispus between deep and shallow water layers. P. crispus restoration decreased by 12-32%, 13-36%, 9-43% and 5-36% of COD, NH₄⁺-N, TN and TP concentration, respectively, in enclosed overlying water compared to the river (P < 0.05) during 5 months of experiment. Illumina sequencing was employed to explore the epiphytic bacterial and microeukayotic communities at water depth 25-35 cm (shallow area) and 80-90 cm (deep area). A total of 9 bacterial and 12 microeukayotic dominant phyla were obtained in eight samples. It should be noted that the algae abundances were higher in shallow area than deep area but a reverse trend was observed for methanotrophs. Null model analysis revealed that dispersal limitation and undominated process was the most important assembly process, whereas stochastic processes gained more importance in shallow area than deep one. According to cooccurrence analysis (|r| > 0.6, P < 0.05), there were more strongly correlated edges in shallow area (456 edges) than deep area (340 edges). These results highlight that submerged macrophytes restoration can increase microbial diversity and improve water quality, and provide a "summer disease cured in winter" way by using could-resistant P. crispus for water purification in micro-polluted rivers in low-temperature season.

A systematic review and quantitative meta-analysis of the relationships between driving forces and cyanobacterial blooms at global scale

The global expansion of cyanobacterial blooms poses a major risk to the safety of freshwater resources. As a result, many explorations have been performed at a regional scale to determine the underlying impact mechanism of cyanobacterial blooms for one or several waterbodies. However, two questions still need to be answered quantitatively at a global scale to assist the water management. One is to specify which factors were often selected as the driving forces of cyanobacterial blooms, and the other is to estimate their quantitative relationships. For that, this paper applied a systematic literature review for 41 peer-reviewed studies published before May 2021 and a statistical meta-analysis based on the Pearson's or Spearman's correlation coefficients from 27 studies. These results showed that the water quality, hydraulic conditions, meteorological conditions and nutrient levels were often considered the driving forces of cyanobacterial blooms in global freshwater systems. Among these, meteorological conditions and nutrient level had the highest probability of being chosen as the driving force. In addition, knowledge of the quantitative relationships between these driving forces and cyanobacterial blooms was newly synthesized based on the correlation coefficients. The results indicated that, at a global scale, meteorological conditions were negatively related to cyanobacterial blooms, and other driving forces, such as water quality, hydraulic conditions and nutrient levels, were positively related to cyanobacterial blooms. In addition, the measurement indicators of these driving forces had diverse forms. For example, the nutrient level can be measured by the concentration of different forms of nitrogen or phosphorus, which may lead to different results in correlation analysis. Thus, a subgroup meta-analysis was necessary for the subdivided driving forces and cyanobacterial blooms, which had a better accuracy. Overall, the synthesized knowledge can help guide advanced cyanobacteria-centered water management, especially when the necessary cyanobacterial data of targeting waterbodies are inaccessible.

Multivariable integrated risk assessment for cyanobacterial blooms in eutrophic lakes and its spatiotemporal characteristics

Climate change has catalyzed the global expansion of cyanobacterial blooms in eutrophic , lakes and threatens water security. In most studies, the cyanobacterial bloom risk levels in lakes were evaluated using field-collected data from multiple indicators or spatially continuous data from one cyanobacteria-related indicator. Nevertheless, the occurrence of cyanobacterial blooms in lakes has clear spatial heterogeneity and is affected by numerous factors. Therefore, we developed a multivariable integrated risk assessment framework for cyanobacterial blooms in lakes using five spatially continuous datasets to estimate the risk level of cyanobacterial blooms at the pixel scale (250 m). The spatial and temporal variations in cyanobacterial bloom risk levels from May 1, 2002, to October 31, 2020, were investigated for three typical eutrophic lakes in China: Lakes Taihu, Chaohu, and Dianchi. Seasons and regions of high cyanobacterial bloom risk were identified for each lake. Environmental characteristics were discussed. A long-term investigation revealed that owing to its warm climate, the cyanobacterial risk levels in summer and autumn were much higher than those in the other two seasons. At the synoptic scale, Lake Taihu had a lower cyanobacterial bloom risk than Lakes Chaohu and Dianchi. A further comparison found that precipitation, wind speed, and temperature were responsible for the differences in cyanobacterial bloom risk levels among the three lakes. At the pixel scale, the risk map indicated that the cyanobacterial bloom risk levels of Lake Taihu were unevenly distributed, and the cyanobacterial bloom risk of the lakeshore was higher than that of the other subregions. Nutrient levels played the most critical role in the regional differences in cyanobacterial bloom risk levels in a lake. While the differences of cyanobacterial bloom risk levels in three lakes were resulted by the climates. Bloom events were defined and classified as "long-term bloom" or "flash bloom" according to their duration (over or below a year). Overall, this study can assist in advanced water management with a pixel-scale evaluation of cyanobacterial bloom risk levels.

Effects of physiologic activities of plankton on CO2 flux in the Three Gorges Reservoir after rainfall during algal blooms

The nutrient supply to the freshwater system may be changed by rainfall, which also encourages the cyclic succession of microorganisms. However, in a highly dynamic land-water reservoir, the microbial metabolic changes brought on by the changes of water nutrients following rainfall are not clearly documented. The study selected the Three Gorges Reservoir (TGR) backwater region during algal bloom seasons as the study area and time, and used the Biolog-EcoPlates technique to examine the heterotrophic metabolism conditions of the water before and after rain. The field monitoring assessed how biotic and abiotic variables affected CO₂ flux at the water-air interface. The tests conducted in the laboratory investigated the water-integrated metabolic process was affected by post-rainfall environmental changes. The results showed that the average flux of CO₂ at the water-air interface before rainfall was -489.17 ± 506.66 mg·(m²·d)^-1, while the average CO₂ flux reached 393.35 ± 793.49 mg·(m²·d)^-1 after rainfall. This is mostly explained by the heterotrophic metabolic variability of plankton in response to changes in the aqueous environment brought on by precipitation. These discoveries help us better understand how biological metabolisms after rain affect the CO₂ flux at the water-air interface and reservoir greenhouse gas (GHG) emission equivalents can be evaluated more accurately.

Influence of cyanobacterial bloom accumulation and dissipation on underwater light attenuation in a large and shallow lake

Cyanobacterial bloom accumulation and dissipation frequently occur in Lake Taihu, a typically shallow, eutrophic lake due to wind wave disturbance. However, knowledge of the driving mechanisms of cyanobacterial blooms on underwater light attenuation is still limited. In this study, we collected a high-frequency in situ monitoring of the wind field, underwater light environment, and surface water quality to elucidate how cyanobacterial bloom accumulation and dissipation affect the variations in underwater light attenuation in the littoral zone of Lake Taihu. Results showed that cyanobacterial blooms significantly increased the diffuse attenuation coefficient of ultraviolet-B (K_d(313)), ultraviolet-A (K_d(340)), and photosynthetically active radiation (K_d(PAR)); the scattering of total suspended matter (b_bp(λ)); and the absorption of phytoplankton (a_ph(λ)) and chromophoric dissolved organic matter (CDOM, a_g(λ)) (p < 0.01). The K_d(PAR) decreased quickly during the processes of bloom dissipation, but the decrease of K_d(313) and K_d(340) lagged 0.5 day. Our results suggested that cyanobacterial blooms could increase particle matters and elevated the production of autochthonous CDOM, resulting in underwater light attenuation increase. Ultraviolet radiation (UVR) and PAR attenuation both have significant responses to cyanobacterial blooms, but the response processes were distinct due to the different changes of particle and dissolved organic matters. Our study unravels the driving mechanisms of cyanobacterial blooms on underwater light attenuation, improving lake ecosystem management and protection.

A ground-based remote sensing system for high-frequency and real-time monitoring of phytoplankton blooms

The worldwide expansion of phytoplankton blooms has severely threatened water quality, food webs, habitat stability and human health. Due to the rapidity of phytoplankton migration and reproduction, high-frequency information on phytoplankton bloom dynamics is crucial for their forecasting, treatment, and management. While several approaches involving satellites, in situ observations and automated underwater monitoring stations have been widely used in the past several decades, they cannot fully provide high-frequency and continuous observations of phytoplankton blooms at low cost and with high accuracy. Thus, we propose a novel ground-based remote sensing system (GRSS) that can monitor real-time chlorophyll a concentrations (Chla) in inland waters with a high frequency. The GRSS mainly consists of three platforms: the spectral measurement platform, the data-processing platform, and the remote access control, display and storage platform. The GRSS is capable of obtaining a remote sensing irradiance ratio (R(λ)) of 400-1000 nm at a high frequency of 20 s. Eight different Chla retrieval algorithms were calibrated and validated using a dataset of 481 pairs of GRSS R(λ) and in situ Chla measurements collected from four inland waters. The results showed that random forest regression achieved the best performance in deriving Chla (R² = 0.95, root mean square error = 13.40 μg/L, and mean relative error = 25.7%). The GRSS successfully captured two typical phytoplankton bloom events in August 2021 with rapid changes in Chla from 20 μg/L to 325 μg/L at the minute level, highlighting the critical role that this GRSS can play in the high-frequency monitoring of phytoplankton blooms. Although the algorithm embedded into the GRSS may be limited by the size of the training dataset, the high-frequency, continuous and real-time data acquisition capabilities of the GRSS can effectively compensate for the limitations of traditional observations. The initial application demonstrated that the GRSS can capture rapid changes of phytoplankton blooms in a short time and thus will play a critical role in phytoplankton bloom management. From a broader perspective, this approach can be extended to other carriers, such as aircraft, ships and unmanned aerial vehicles, to achieve the networked monitoring of phytoplankton blooms.

Assessing the enhanced reduction effect with the addition of sulfate based P inactivating material during algal bloom sedimentation

The typical harm effect of algal bloom sedimentation is to increase sulfides level in surroundings, threatening aquatic organisms and human health; whereas, P inactivating materials containing sulfate are commonly attempted to be used to immobilize reactive P or to flocculate excessive algae in water columns for eutrophication control. In this study, variations in sulfate reduction during algal bloom sedimentation with the addition of sulfate based inactivating materials was comprehensively assessed based on using Al₂(SO₄)₃ with comparison to AlCl₃. The results showed that addition of Al₂(SO₄)₃ had more substantial effect on overlying water and sediment properties compared to those of ACl₃. Al₂(SO₄)₃ can enhance sulfate reduction, resulting in temporary increase of sulfides (p < 0.01) and quick decrease of various Fe (p < 0.01) in overlying water and then promoting the formation of FeS and FeS₂ (determined by EXAFS analysis) in sediments. Most importantly, the increased sulfides, as well as the physical barrier on sediment formed due to Al₂(SO₄)₃ addition, enhanced the transformation of sulfides to odorous contaminants, increasing odorous contaminants (especially methyl thiols) production by approximately one order of magnitude in overlying water. Furthermore, the increased sulfides facilitated to the enrichment of microorganisms related to S cycles (Thiobacillu with relative abundance of 23.8%) and even promoted to enrich bacterial genus potentially with pathogenicity (Treponema) in sediments. The impacts of sulfate tended to be regulated by algae concentration; however, careful management was recommended for sulfate based inactivating materials application to control eutrophication with algal blooms.

Visible light promoted the removal of tetrabromobisphenol A from water by humic acid-FeS colloid

Ferrous sulfide (FeS) and humic acid (HA) are typical black substances in black bloom water. Based on the strong reduction ability of FeS and the photosensitivity of HA, the transformation of toxic organic pollutants by the combination of FeS and HA (HA-FeS) is not clear. In order to explore this issue, the stability of HA-FeS was analyzed by measuring the hydrodynamic diameter and zeta potential of HA-FeS, and then the removal mechanism and possible degradation pathway of tetrabromobisphenol A (TBBPA) by HA-FeS under continuous illumination were discussed. The results showed that the hydrodynamic diameter of FeS was reduced and the stability of FeS was improved, and it was easily suspended after FeS combined with the HA in the water. The combination of HA and FeS promoted the removal of TBBPA in water, no matter it was in the presence or absence of light. Besides, compared with the absence of light, the removal efficiency of TBBPA was improved by HA-FeS with continuous light. There were two reasons for the increase in the removal efficiency of TBBPA by HA-FeS. On the one hand, Fe²⁺ and S^2- of HA-FeS had more stable chemical valence and obtained better reducibility under continuous light than that in the dark. On the other hand, light induced the release of active species (O₂^-, ¹O₂, and OH) in the HA-FeS composite colloid and further promoted the degradation of organic pollutants. Therefore, the black substances (FeS) of black blooms may play a beneficial role in the removal of pollutants under sunlight.

Evolution of urban black and odorous water: The characteristics of microbial community and driving-factors

Urban black blooms that are primarily caused by organic carbon are deleterious environmental problems. However, detailed studies on the microbial characteristics that form urban black blooms are lacking. In this study, we observed the composition, diversity, and function of bacterial community in the overlying water and sediments during the occurrence and remediation of urban black blooms using high-throughput 16S rRNA gene amplicon sequencing analysis. First, we found that pivotal consortia in the overlying water increased significantly during the formation of black blooms, including the genera Acidovorax, Brevundimonas, Pusillimonas, and Burkholderiales involved in the degradation of refractory organics, as well as the genera Desulfovibrio, Dechloromonas, and Rhizobium related to the production of black and odorous substances. An RDA analysis revealed that chemical oxygen demand, dissolved oxygen, and oxidation reduction potential were related to the changes in microbial community composition. Furthermore, aeration was found to accelerate the removal of ammonia nitrogen and enhance the function of microbial community by stimulating the growth of order Planktomycetes during the remediation of black blooms, but aeration substantially damaged the microbial diversity and richness. Therefore, the health of the aquatic ecosystem should be comprehensively considered when aeration is applied to restore polluted waterbodies. Notably, we observed a large number of pathogenic bacteria in urban black blooms, which emphasizes the importance of treating domestic sewage so that it is harmless. Together, these findings provide new insights and a basis to prevent and manage urban black blooms.

Effect of dredging and capping with clean soil on the mitigation of algae-induced black blooms in Lake Taihu, China: A simulation study

Sediment is an important source of matter that causes blackening and odor formation in a water body. The restoration of polluted sediment can suppress algae-induced black blooms to a certain degree. In this study, we compared the control effects of sediment dredging and capping with clean soil on algae-induced black blooms in Lake Taihu using indoor simulation experiments. In addition, we explored the driving effect of temperature on algae-induced black blooms using the method of gradual warming (18, 23, and 28 °C) during the experiment. No blackening of the water body was observed in the simulation stages I (18 °C) and II (23 °C), and the blackening and odor formation occurred within 3 d when the temperature increased to 28 °C in stage III, implying that high temperature was an important driving factor for algae-induced black blooms. Dredging and capping inhibited the blackening and odor formation to some extent, and the colorimetric values in the water columns were lower in the treatment groups than in the control group. At the end of the experiment, the colorimetric values of dredging and capping treatments were 56.5% and 96.7% of the colorimetric value of the control group, respectively. The control effect of dredging on the blackening elements, i.e., Fe²⁺ and S^2- and the main odor forming compounds, i.e., dimethyl disulfide (DMDS) and dimethyl trisulfide (DMTS) was observed in stage II (11-20 d) and stage III (21-27 d), respectively, and the inhibition ability of dredging to suppress algal-induced black blooms was superior than that of capping with clean soil.

Monitoring of cyanobacterial blooms and assessing polymer-enhanced microfiltration and ultrafiltration for microcystin removal in an Italian drinking water treatment plant

The water intake of a drinking water treatment plant (DWTP) in Central Italy was monitored over six bloom seasons for cyanotoxin severity, which supplies drinking water from an oligo-mesotrophic lake with microcystin levels up to 10.3 μg/L. The historical data showed that the water temperature did not show extreme/large seasonal variation and it was not correlated either with cyanobacterial growth or microcystin concentration. Among all parameters, the cyanobacteria growth was negatively correlated with humidity and manganese and positively correlated with atmospheric temperature. No significant correlation was found between microcystin concentration and the climatic parameters. Polymer(chitosan)-enhanced microfiltration (PEMF) and ultrafiltration (PEUF) were further tested as an alternative microcystin removal approach from dense cyanobacteria-rich flows. The dominant cyanobacteria in the water intake, Planktothrix rubescens, was isolated and enriched to simulate cyanobacterial blooms in the lake. The PEMF and PEUF were separately applied to enriched P. rubescens culture (PC) (microcystin = 1.236 μg/L) as well as to the sand filter backwash water (SFBW) of the DWTP where microcystin concentration was higher than 12 μg/L. The overall microcystin removal rates from the final effluent of PC (always <0.15 μg/L) were between 90.1-94.7% and 89.5-95.4% using 4 and 20 mg chitosan/L, respectively. Meanwhile, after the PEMF and PEUF of SFBW, the final effluent contained only 0.099 and 0.057 μg microcystin/L with an overall removal >99%. The presented results are the first from the application of chitosan to remove P. rubescens as well as the implementation of PEMF and PEUF on SFBW to remove cyanobacterial cells and associated toxins.

Dramatic temporal variations in methane levels in black bloom prone areas of a shallow eutrophic lake

Global lakes serve as a key natural source of methane (CH₄) and suffer from increasing hypoxia due to unprecedented anthropogenic activities and climate change. A black bloom is a temporary hypoxia triggered by a longstanding algal bloom, which facilitates CH₄ production by creating reducing conditions and abundant algae-sourced organic carbon. One-year investigations were conducted to examine temporal CH₄ dynamics in the water and sediment pore water in black bloom prone areas (BBPAs) in Lake Taihu, China, where there had been at least two recorded black bloom events. The CH₄ in the water changed significantly with time (p < 0.001), with the highest concentrations appearing in warm months when an abnormal lower dissolved oxygen content was observed at different sites, which were one to two orders of magnitude higher than other months. Compared with the control site, there were significantly higher CH₄ concentrations in BBPA waters (p < 0.001), which was consistent with the higher CH₄ in the sediment pore water. Methane dynamics in the water showed significant positive correlations with temperature, total phosphorus, total nitrogen, ammonia-N, and soluble reactive phosphorus (p < 0.05), but showed a significant inverse correlation with dissolved oxygen (p < 0.01). Redundancy analysis indicated dissolved oxygen made the largest contribution to CH₄ dynamics in the BBPAs. A significant increase in the CH₄ in water will turn BBPAs into temporary hot spots with substantial CH₄ emissions with the appearance of black blooms. The results provide new insights into understanding future CH₄ dynamics under globally prevailing algal blooms and climate change.

Combined impact of organic matter, phosphorus, nitrate, and ammonia nitrogen on the process of blackwater

Blackwater events are frequently reported over the world and become a serious environmental problem. However, the mechanisms of blackwater occurrence are not fully understood yet. This study simulated the process of blackwater with the combined pollution in an orthogonal experiment, which had 4 factors (TOC, TP, NH4+-N, and NO3--N) and 4 levels (None, Low, Middle, and High). Results showed that the process of water condition changes was divided into two parts, which were "exogenous" and "algae-derived" blackwater, and the influence of four different pollutants on the occurrence of the blackwater was ranked as follows: TOC > TP > NO3--N > NH4+-N. With the increase of organic matter addition, the anaerobic condition in water was prolonged and the concentration of Fe2+ had a significant increase. In addition, under the None phosphorus condition, the descent rates of DO and COD in the water were reduced, and the algae bloom was obviously deferred. Moreover, the addition of organic matter or phosphorus changed the microbial community structure and led to different water processes. Particularly, only on the condition of the high content of TOC and phosphorus, the diversity of sulfate-reducing bacteria (e.g., Pseudomonas, Paludibacter, and Bacteroides) increased significantly, which accounted for 51.4%, causing the significant production of S2- in the water. Water's lack of phosphorus showed a low rate of decomposition of organic matter, which might be the result of a considerable increase in the abundance of aerobic Trichococcus and Malikia. This study shows that organic matter and phosphorus have synergistic effect on blackwater occurrence. In the treatment of blackwater, the exogenous pollutant control should reduce the discharge of organic pollutants, and endogenous control should focus on phosphorus abatement and reduce nitrogen control.

Dynamic Change of Sedimental Microbial Community During Black Bloom-an In Situ Enclosure Simulation Study

Black bloom is a worldwide environmental problem. Sediment microbes play important roles in the process of black bloom. The dynamic change of sedimental microbial community and their potential link between taste and odor compounds during black bloom was investigated in an in situ black bloom enclosure simulation experiment. Through high-throughput sequencing and analysis, pronounced shifts of sedimental microbial community were observed on the 3rd and 7th day in the black bloom group. Microbes in Cyanobacteria, Verrucomicrobia, Planctomycetes, and Actinobacteria were obviously increased, while microbes from the phyla OP8, Chloroflexi, and Acidobacteria were decreased significantly. RDA analysis revealed that the concentrations of chlorophyll a (Chla), total phosphorus (TP), and turbidity (NTU) in the water and the TP, TN concentrations in the sediment were the main environmental factors that affect the microbial community in the sediment. Correlation analysis revealed that microbes Dechloromonas sp. (OTU003567 and OTU000093), Desulfococcus sp. (OTU000911), Chromatiaceae (OTU001222), and Methanosaeta sp. (OTU004809) were positively correlated with the taste and odor substances in the sediment, such as dimethyl sulfide (DMS), β-ionone, β-cyclocitral and geosmin. The sedimental microbial community gradually recovered in the late phase of black bloom, indicating the stability and self-recovery ability of the sedimental microbial community during black bloom. Noteworthily, we observed many possible pathogens increased significantly during the black bloom, which alerts us to keep away from contaminated sediment when black bloom occurred.

Spatio-Temporal Variations and Driving Forces of Harmful Algal Blooms in Chaohu Lake: A Multi-Source Remote Sensing Approach

Harmful algal blooms (hereafter HABs) pose significant threats to aquatic health and environmental safety. Although satellite remote sensing can monitor HABs at a large-scale, it is always a challenge to achieve both high spatial and high temporal resolution simultaneously with a single earth observation system (EOS) sensor, which is much needed for aquatic environment monitoring of inland lakes. This study proposes a multi-source remote sensing-based approach for HAB monitoring in Chaohu Lake, China, which integrates Terra/Aqua MODIS, Landsat 8 OLI, and Sentinel-2A/B MSI to attain high temporal and spatial resolution observations. According to the absorption characteristics and fluorescence peaks of HABs on remote sensing reflectance, the normalized difference vegetation index (NDVI) algorithm for MODIS, the floating algae index (FAI) and NDVI combined algorithm for Landsat 8, and the NDVI and chlorophyll reflection peak intensity index (ρchl) algorithm for Sentinel-2A/B MSI are used to extract HAB. The accuracies of the normalized difference vegetation index (NDVI), floating algae index (FAI), and chlorophyll reflection peak intensity index (ρchl) are 96.1%, 95.6%, and 93.8% with the RMSE values of 4.52, 2.43, 2.58 km2, respectively. The combination of NDVI and ρchl can effectively avoid misidentification of water and algae mixed pixels. Results revealed that the HAB in Chaohu Lake breaks out from May to November; peaks in June, July, and August; and more frequently occurs in the western region. Analysis of the HAB’s potential driving forces, including environmental and meteorological factors of temperature, rainfall, sunshine hours, and wind, indicated that higher temperatures and light rain favored this HAB. Wind is the primary factor in boosting the HAB’s growth, and the variation of a HAB’s surface in two days can reach up to 24.61%. Multi-source remote sensing provides higher observation frequency and more detailed spatial information on a HAB, particularly the HAB’s long-short term changes in their area.

River algal blooms are well predicted by antecedent environmental conditions

River algal blooms have become a challenging environmental problem worldwide due to strong interference of human activities and megaprojects (e.g., big dams and large-scale water transfer projects). Previous studies on algal blooms were mainly focused on relatively static water bodies (i.e., lakes and reservoirs), but less on the large rivers. As the largest tributary of the Yangtze River of China and the main freshwater source of the South-to-North Water Diversion Project (SNWDP), the Han River has experienced frequent algal blooms in recent decades. Here we investigated the algal blooms during a decade (2003-2014) in the Han River by two gradient boosting machine (GBM) models with k-fold cross validation, which used explanatory variables from current 10-day (GBMc model) or previous 10-day period (GBMp model). Our results advocate the use of GBMp due to its higher accuracy (median Kappa = 0.9) and practical predictability (using antecedent observations) compared to GBMc. We also revealed that the algal blooms in the Han River were significantly modulated by antecedent water levels in the Han River and the Yangtze River and water level variation in the Han River, whereas the nutrient concentrations in the Han River were usually above thresholds and not limiting algal blooms. This machine-learning-based study potentially provides scientific guidance for preemptive warning and risk management of river algal blooms through comprehensive regulation of water levels during the dry season by making use of water conservancy measures in large rivers.

Application of advanced HepG2 3D cell model for studying genotoxic activity of cyanobacterial toxin cylindrospermopsin

Cylindrospermopsin (CYN) is an emerging cyanotoxin increasingly being found in freshwater cyanobacterial blooms worldwide. Humans and animals are exposed to CYN through the consumption of contaminated water and food as well as occupational and recreational water activities; therefore, it represents a potential health threat. It exhibits genotoxic effects in metabolically active test systems, thus it is considered as pro-genotoxic. In the present study, the advanced 3D cell model developed from human hepatocellular carcinoma (HepG2) cells was used for the evaluation of CYN cyto-/genotoxic activity. Spheroids were formed by forced floating method and were cultured for three days under static conditions prior to exposure to CYN (0.125, 0.25 and 0.5 μg/mL) for 72 h. CYN influence on spheroid growth was measured daily and cell survival was determined by MTS assay and live/dead staining. The influence on cell proliferation, cell cycle alterations and induction of DNA damage (γH2AX) was determined using flow cytometry. Further, the expression of selected genes (qPCR) involved in the metabolism of xenobiotics, proliferation, DNA damage response, apoptosis and oxidative stress was studied. Results revealed that CYN dose-dependently reduced the size of spheroids and affected cell division by arresting HepG2 cells in G1 phase of the cell cycle. No induction of DNA double strand breaks compared to control was determined at applied conditions. The analysis of gene expression revealed that CYN significantly deregulated genes encoding phase I (CYP1A1, CYP1A2, CYP3A4, ALDH3A) and II (NAT1, NAT2, SULT1B1, SULT1C2, UGT1A1, UGT2B7) enzymes as well as genes involved in cell proliferation (PCNA, TOP2α), apoptosis (BBC3) and DNA damage response (GADD45a, CDKN1A, ERCC4). The advanced 3D HepG2 cell model due to its more complex structure and improved cellular interactions provides more physiologically relevant information and more predictive data for human exposure, and can thus contribute to more reliable genotoxicity assessment of chemicals including cyanotoxins.

Retrieval of Secchi Disk Depth in Turbid Lakes from GOCI Based on a New Semi-Analytical Algorithm

The accurate remote estimation of the Secchi disk depth (ZSD) in turbid waters is essential in the monitoring the ecological environment of lakes. Using the field measured ZSD and the remote sensing reflectance (Rrs(λ)) data, a new semi-analytical algorithm (denoted as ZSDZ) for retrieving ZSD was developed from Rrs(λ), and it was applied to Geostationary Ocean Color Imager (GOCI) images in extremely turbid waters. Our results are as follows: (1) the ZSDZ performs well in estimating ZSD in turbid water bodies (0.15 m < ZSD < 2.5 m). By validating with the field measured data that were collected in four turbid inland lakes, the determination coefficient (R2) is determined to be 0.89, with a mean absolute square percentage error (MAPE) of 22.39%, and root mean square error (RMSE) of 0.24 m. (2) The ZSDZ improved the retrieval accuracy of ZSD in turbid waters and outperformed the existing semi-analytical schemes. (3) The developed algorithm and GOCI data are in order to map the hourly variation of ZSD in turbid inland waters, the GOCI-derived results reveal a significant spatiotemporal variation in our study region, which are significantly driven by wind forcing. This study can provide a new approach for estimating water transparency in turbid waters, offering important support for the management of inland waters.

The role of magnetic MOFs nanoparticles in enhanced iron coagulation of aquatic dissolved organic matter

Dissolved organic matter (DOM) is not only a vector for the migration of aquatic environmental pollutants, but is also key to the control of water pollution. Economic and effective DOM removal through coagulation is essential in water treatment processes. This work investigated the role of carboxylated magnetic metal organic frameworks (MMOFs) nanoparticles in polymeric iron-based coagulation for the removal of aquatic DOM using a MMOFs-doped polyferric iron-based coagulant (MMOF-PIC). Analytical methodologies and tools used in this research included scanning electron microscopy (SEM), zeta potential, molecular weight cut off (MWCO), vibrating sample magnetometer (VSM) measurement, excitation emission matrix spectroscopy (EEMs), and X-ray photoelectron spectroscopy (XPS). The results showed that MMOF-PIC had the potential to change the structure of the polyferric iron-based coagulant (PIC) and charge, as determined by a porous surface morphology, a higher medium polymeric species distribution, and a more positive zeta potential. The MMOFs consequently enhanced PIC action on the removal of UV254 exposed DOM species with molecular weight <30 kDa, including aromatic CC based compounds, org-N as primary amines and amide/peptide bound species, water containing microbial metabolites and protein-like materials. The coagulation of DOM was enhanced by improving charge neutralization, adsorption-bridging and sweep-flocculation in the presence of MMOFs nanoparticles. This was due to hydrogen bonds, π-π bonds and covalent bonds resulting from actions of nanoparticles and pollutants. These results indicate that magnetic MOF nanoparticles can improve PIC coagulation for DOM, enhancing future removal of target pollutants.

The growth suppression effects of UV-C irradiation on Microcystis aeruginosa and Chlorella vulgaris under solo-culture and co-culture conditions in reclaimed water

Harmful algal blooms (HABs) are serious problems in landscape waters sourced from reclaimed water. In this study, the suppression effects of UV-C irradiation on microalgal growth were researched to find a possible preventive approach. Microcystis aeruginosa and Chlorella vulgaris were exposed to UV-C irradiation and then cultured in real reclaimed water for 7-18 d. UV-C irradiation at 50-200 mJ cm^-2 could inhibit the growth of M. aeruginosa, C. vulgaris, and both microalgae in co-culture for 3-14, 1-3, and 1-5 d respectively. In addition, UV-C irradiation could cause damage to the cell integrity. At 100-200 mJ cm^-2 UV-C, the proportion of microalgal membrane damage (P_md) in M. aeruginosa cells increased rapidly to 56%-76% from day 3, whereas that in C. vulgaris cells increased to 23%-62% within 3 d. The photochemical efficiency (represented by Y value) of the irradiated groups was negatively affected immediately after UV-C irradiation and recovered gradually during the incubation. The Y value of M. aeruginosa cells began to recover from days 3 to 14, whereas that of C. vulgaris recovered much more quickly, from days 0.1 to 1. Overall, the irradiation-induced suppressive effects on algal growth correlated positively with the UV-C doses. Because M. aeruginosa was more sensitive to UV-C irradiation, UV-C irradiation not only controlled the total biomass of the mixed algae but also selectively reestablished the dominance of the nontoxic C. vulgaris.

A critical review of the appearance of black-odorous waterbodies in China and treatment methods

Black-odorous rivers and lakes are a serious environmental problem and are frequently reported in China. Despite this, there have been no comprehensive in-depth reviews of black-odorous water formation mechanisms, contributing factors and potential treatment technologies. Elements such as S, C and N play an important role in the biogeochemical cycle of black-odorous waterbodies, with water blackening caused by metal sulfides such as iron sulfide (FeS) and manganese sulfide (MnS). Volatile substances such as volatile organic sulfur compounds (VOSCs) are the main contributors of odor. Microorganisms such as sulfate reducing bacteria (SRB), Bacteroidetes and Proteobacteria play important roles in blackening and odor formation processes. Effectiveness of the commonly used treatments methods for black-odorous waterbodies, such as artificial aeration, sediment dredging, microbial enhanced technologies and constructed wetlands, varies significantly under different conditions. In contrast, bio-ecological engineering technologies exhibit comprehensive, long-lasting and economical treatment effects. The causes and mechanisms of black-odorous water formation require further investigation, as well as the optimal application conditions and mechanisms of treatment technologies. This study comprehensively reviews 1) the characteristics and current distribution of black-odorous waterbodies; 2) the compounds contributing to black-odorous phenomenon; 3) black-odorous waterbody production mechanisms; 4) treatment technologies for black-odorous waterbodies. Further studies on the mechanisms of blackening and odor formation are required, with treatment application conditions and mechanisms also requiring further clarification. In addition, the long-term ecological restoration of black-odorous rivers immediately after remediation is key issue that is easily overlooked but merits further investigation and development.

Linking the molecular composition of autochthonous dissolved organic matter to source identification for freshwater lake ecosystems by combination of optical spectroscopy and FT-ICR-MS analysis

Autochthonous dissolved organic matter (DOM) is increasingly released in lakes due to eutrophication, and thus affects the composition and environmental behaviors of DOM in eutrophic lakes. However, there are only limited studies on the molecular characteristics of autochthonous DOM and its influencing mechanisms. Herein, end-member DOM samples of macrophytes, algae, sediments and freshwater DOM samples in eutrophic lakes (Ch:Taihu and Dianchi) were collected and characterized by optical spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). The results revealed the chemical structures of autochthonous DOM were more aliphatic and less oxidized, which was marked by increases in lipid compounds and decreases in the lignin components as compared to the allochthonous DOM-dominated freshwaters. More specially, algae-derived DOM contains more lipid compounds, while macrophyte-derived DOM was dominated by lignin and tannin compounds according to Van Krevelen plots. Sediment-derived DOM contained more N-containing compounds. The traditional optical indices indicated the relative aromaticity covaried with polyphenolic and polycyclic aromatics, whereas those reflecting autochthonous DOM covaried with more aliphatic compounds. Multivariate analysis of FT-ICR-MS data of end-members and freshwaters revealed the predominant terrestrial input to Lake Taihu and greater contribution of algae released DOM to Dianchi. This study provides critical information about the characteristics of autochthonous DOM at a molecular level and confirmed autochthonous DOM was compositionally distinct from allochthonous DOM. Overall autochthonous DOM should be gained more attention in the eutrophic lakes.

Spatiotemporal Relationships of Phytoplankton Blooms, Drought, and Rainstorms in Freshwater Reservoirs

Algal blooms, especially those composed of toxic phytoplankton, are a global threat to eutrophic and mesotrophic freshwater reservoirs. While extreme hydrologic events such as flooding and drought have been shown to control bloom onset and success, the spatiotemporal dynamics of these relationships are still unclear for mesotrophic reservoirs. In this study, the relationships between hydrologic events and phytoplankton in Lake Allatoona and Lake Lanier, Georgia, United States, were characterized using historical and satellite datasets from 2008 to 2017 and statistical modeling. Results showed that the impact of stormflow and rainstorm events varied systematically from riverine to lacustrine reaches of the two reservoirs on weekly and monthly scales. Precipitation duration and stormflow were the most significant and best-fitting predictors of algal bloom biomass in deeper reaches of the two reservoirs, suggesting that algal blooms in more lacustrine environments may be better equipped for wet and stormy regimes than has been previously hypothesized.

Temporal Variability of Virioplankton during a Gymnodinium catenatum Algal Bloom

Viruses are key biogeochemical engines in the regulation of the dynamics of phytoplankton. However, there has been little research on viral communities in relation to algal blooms. Using the virMine tool, we analyzed viral information from metagenomic data of field dinoflagellate (Gymnodinium catenatum) blooms at different stages. Species identification indicated that phages were the main species. Unifrac analysis showed clear temporal patterns in virioplankton dynamics. The viral community was dominated by Siphoviridae, Podoviridae, and Myoviridae throughout the whole bloom cycle. However, some changes were observed at different phases of the bloom; the relatively abundant Siphoviridae and Myoviridae dominated at pre-bloom and peak bloom stages, while at the post-bloom stage, the members of Phycodnaviridae and Microviridae were more abundant. Temperature and nutrients were the main contributors to the dynamic structure of the viral community. Some obvious correlations were found between dominant viral species and host biomass. Functional analysis indicated some functional genes had dramatic response in algal-associated viral assemblages, especially the CAZyme encoding genes. This work expands the existing knowledge of algal-associated viruses by characterizing viral composition and function across a complete algal bloom cycle. Our data provide supporting evidence that viruses participate in dinoflagellate bloom dynamics under natural conditions.

Phytoplankton response to water quality seasonality in a Brazilian neotropical river

Tropical wet-dry climate seasonality is widely recognized as an important condition to phytoplankton communities' structure in freshwater ecosystems; however, there are few studies in that field in northeast Brazilian rivers. This study aimed to evaluate the influence of water quality seasonal variability over the phytoplankton dynamics and identify seasonality in eutrophication phenomena in a poorly studied neotropical river. Water quality variables and phytoplankton were examined within the Jequitinhonha River lower course, Bahia (Brazil) from 2010 to 2012. A 3-year time series was analyzed for both rainy and dry seasons. Descriptive, inferential, and multivariate analyses (CCA) were performed. Results indicated that chemical oxygen demand, dissolved aluminum, and turbidity were the main factors which influenced phytoplankton community structure and composition. Dry season was favorable for diatoms and Chlorophyceae (chlorophylls) while rainy season was favorable for cyanobacteria. Still, it was revealed that, in dry season, lower values for turbidity, chemical oxygen demand, dissolved aluminum, and dissolved iron were related with an eutrophication phenomenon.

Long-Term Spatial and Temporal Monitoring of Cyanobacteria Blooms Using MODIS on Google Earth Engine: A Case Study in Taihu Lake

As cyanobacteria blooms occur in many types of inland water, routine monitoring that is fast and accurate is important for environment and drinking water protection. Compared to field investigations, satellite remote sensing is an efficient and effective method for monitoring cyanobacteria blooms. However, conventional remote sensing monitoring methods are labor intensive and time consuming, especially when processing long-term images. In this study, we embedded related processing procedures in Google Earth Engine, developed an operational cyanobacteria bloom monitoring workflow. Using this workflow, we measured the spatiotemporal patterns of cyanobacteria blooms in China’s Taihu Lake from 2000 to 2018. The results show that cyanobacteria bloom patterns in Taihu Lake have significant spatial and temporal differentiation: the interannual coverage of cyanobacteria blooms had two peaks, and the condition was moderate before 2006, peaked in 2007, declined rapidly after 2008, remained moderate and stable until 2015, and then reached another peak around 2017; bays and northwest lake areas had heavier cyanobacteria blooms than open lake areas; most cyanobacteria blooms primarily occurred in April, worsened in July and August, then improved after October. Our analysis of the relationship between cyanobacteria bloom characteristics and environmental driving factors indicates that: from both monthly and interannual perspectives, meteorological factors are positively correlated with cyanobacteria bloom characteristics, but as for nutrient loadings, they are only positively correlated with cyanobacteria bloom characteristics from an interannual perspective. We believe reducing total phosphorous, together with restoring macrophyte ecosystem, would be the necessary long-term management strategies for Taihu Lake. Our workflow provides an automatic and rapid approach for the long-term monitoring of cyanobacteria blooms, which can improve the automation and efficiency of routine environmental management of Taihu Lake and may be applied to other similar inland waters.

Integrating long-term dynamics of ecosystem services into restoration and management of large shallow lakes

Adequately understanding the dynamics of ecosystem services (ES), a practical framework for analyzing social-ecological systems (SES), is crucial for sustainable environmental management and decision-making. However, the interactions among multiple ES at multi-decadal scales are less explored, and many challenges remain to integrate long-term dynamics of ES into ecological restoration and management. Here, we combined socioeconomic data with synthesized paleolimnological records to assess the dynamics of 12 critical ES and regional SES in the Taihu Lake Basin (China) over the past century. Our results indicated that multiple provisioning services showed upwards trends while major regulating services in terms of water, sediment, soil and air regulation had sustained downwards trends since the 1950s, and reached dangerous status after the 1980s. This dynamic trade-off was mainly attributed to the effects of continued socioeconomic transitions including agriculture intensification, industrialization and urbanization. Anthropogenic land use change, pollution input, and climate changes are considered as major drivers of long-term environmental degradation. Regulating services exhibited various dynamical properties including different linear and nonlinear trends, and abrupt changes, which underlined the comprehensive consideration of legacy effects, ecological baseline, thresholds, and resilience into lake management. Environmental Kuznets curve analyses suggested that the regional SES started significant disorder from the 1970s driven by the transition between ES and non-ES (socioeconomic) supply, and then underpinned a gradual shift to reorganization stage after the 1990s. Our study highlights the significance of ES assessment from historical perspective to understand the major processes and underlying mechanisms of lake SES. With adaptive policy interventions on pollution control, efficient resource-use, and targeted environmental investment, the sustainability of regional SES can be expected.

Turbulence exerts nutrients uptake and assimilation of bloom-forming Dolichospermum through modulating morphological traits: Field and chemostat culture studies

Hydrodynamic conditions are closely related to the development and dissipation of cyanobacterial blooms. The morphological features of Dolichospermum under different hydrodynamic conditions were analysed during three blooms in Gaoyang Lake, which is part of the backwater area of the China Three Gorges Reservoir, from 2007 to 2010. The results showed that the length of filaments and the morphology of cells were different in relation to the turbulence caused by the difference in hydraulic retention times. Thus, it was hypothesized that turbulence could shape the morphology and physiology of cyanobacteria. To answer the question regarding what the morphological and physiological responses of cyanobacteria to turbulent mixing mean for these organisms, laboratory experiments in continuous cultivation under different dilution rates were conducted to analyse the effects of specific turbulence intensity on the growth, nutrient uptake and morphology of Dolichospermum flos-aquae. Increasing the turbulence intensity caused synchronous increases in the ratio of the cellular length to the width, in the specific surface area of the filament and the cell and in the nutrient uptake rate; at the same time, the average filament length decreased. These indicated that the turbulence, within the range of our experimental design, could stimulate the growth of Dolichospermum by increasing its nutrient uptake. Additionally, at a high specific growth rate, the nutrient uptake rate of Dolichospermum changed more noticeably with the increasing morphological indicators, indicating that the rapidly growing Dolichospermum was more sensitive to turbulence. These findings explain the role of morphological strategies in the dominance of Dolichospermum within a certain range of turbulence intensity, especially in the early growth stage of blooms. The results also facilitate a greater understanding of the hydrodynamic effects on cyanobacteria and will be instrumental in developing flow regulation to control cyanobacterial blooms in reservoirs.

Meteorological factors and water quality changes of Plateau Lake Dianchi in China (1990-2015) and their joint influences on cyanobacterial blooms

Cyanobacterial blooms (CBs) in eutrophic lakes can cause various harmful issues to both humans and animals, disturb drinking water supply, and devastate lake ecosystems. Although great progresses have been made in many lakes from China and abroad on CBs prevention, mitigation and control, systematic research on the influencing factors of CBs in hypereutrophic plateau Lake Dianchi over a long time span is so far unavailable. This study comprehensively generalized both meteorological and water quality changes in Lake Dianchi during 1990-2015 on both yearly and monthly basis, separated Caohai from Waihai of Lake Dianchi regarding water quality variations, and investigated the individual and joint influencing meteorological and water quality factors on CBs using Spearman correlation, principal component analysis, and multivariate linear stepwise regression. Four specific lake regions, i.e. Caohai, northern Waihai, central Waihai, and southern Waihai, were respectively analyzed due to significant water quality heterogeneity. Results indicated that mild temperatures, low wind velocities, and hypereutrophic water conditions all favor CBs in Lake Dianchi, and the significant temperature rising trend may exacerbate severer CBs in the future. Despite configuration differences, the first principal components on CBs in the four sub-regions of Lake Dianchi were all consisted of meteorological factors, while water quality parameters especially total phosphorus concentrations contributed to the second principal component. Quantification of joint meteorological and water quality influencing factors on CBs needs further improvement, and largely relies on the accuracy of future weather forecasts, in order to set the goal of water quality improvement in each specific lake region for effective CBs management.

Effects of cylindrospermopsin on cultured immortalized human airway epithelial cells

Anthropogenic eutrophication of freshwater bodies increases the occurrence of toxic cyanobacterial blooms. The cyanobacterial toxin cylindrospermopsin (CYN) is detected in the environment with increasing frequency, driving the scientific effort to assess emerging health risks from CYN-producing blooms. Oral exposure to CYN results primarily in hepatotoxicity. Nevertheless, extrahepatic manifestations of CYN toxicity have been reported. Furthermore, cyanotoxins have been detected in aerosols and dust particles, suggesting potential toxic effects in the respiratory tract. To assess the susceptibility of airway epithelia towards cyanotoxins, monolayers of immortalized human bronchial epithelial cells HBE1 and 16HBE14o- were exposed to a concentration range of 0.1-10 μM CYN. Cytotoxic endpoints were assessed as morphologic alterations, resazurin reduction capacity, esterase activity, neutral red uptake, and by impedimetric real-time cell analysis. Depending on the endpoint assessed, EC₅₀ values ranged between 0.7 and 1.8 μM (HBE1) and 1.6-4.8 μM (16HBE14o-). To evaluate alterations of other cellular events by subcytotoxic concentration of CYN (1 μM), phosphorylation of mitogen-activated protein kinases ERK and p38 was determined. Only a slight increase in p38 phosphorylation was induced by CYN in HBE1 cell line after 48 h, while activities of both ERK1/2 and p38 gradually and significantly increased in 16HBE14o- cells during 8-48 h exposure. This study suggests possible hazards of inhalation CYN exposures, which may severely impact the integrity of airway epithelia and epithelial cell signaling. Further research of CYN-induced toxicity and underlying mechanisms is needed, as well as more data on environmental concentrations of cyanotoxins in aerosols for exposure assessment.

Long-term observation of cyanobacteria blooms using multi-source satellite images: a case study on a cloudy and rainy lake

High-frequency and reliable data on cyanobacteria blooming over a long time period is crucial to identify the outbreak mechanism of blooms and to forecast future trends. However, in cloudy and rainy areas, it is difficult to retrieve useful satellite images, especially in the rainy season. To address this problem, we used data from the HJ-1/CCD (Chinese environment and disaster monitoring and forecasting satellite/charge coupled device), GF-1/WFV (Chinese high-resolution satellite/wide field of view), and Landsat-8/OLI (Operational Land Imager) satellites to generate a time series of the bloom area from 2009 to 2016 in Dianchi Lake, China. We then correlated the responses of bloom dynamics to meteorological factors. Several findings can be drawn: (1) a higher bloom frequency and a larger bloom area occurred in 2011, 2013, and 2016, compared to the other years; (2) the frequency of blooms peaked in April, August, and November each year and expanded from north to south starting in July; (3) air temperature in spring and sunshine hours in summer greatly correlated to the yearly bloom area; (4) wind speed and sunshine hours strongly affected the short-term expansion of blooms and thereafter influenced the monthly bloom scale; and (5) rainfall had a strong short-term influence on the occurrence of blooms. Cyanobacteria blooms often occurred when wind speeds were less than 2.35 ± 0.78 m/s in the dry season and 2.01 ± 0.75 m/s in the rainy season, when there were 48 to 72 h of sunshine in the dry season and 35 to 57 h of sunshine in the rainy season, and when there was more than 10 mm of daily precipitation.

An integrated method for controlling the offensive odor and suspended matter originating from algae-induced black blooms

Potentially toxic algae-induced black blooms can trigger crises in urban water supplies and have fatal effects on aquatic ecosystems. Urgent disposal methods to mitigate the taste and odor are imperative for ensuring the safety of the drinking water supply. In this study, we tested three oxidants and two flocculants to improve water quality after the occurrence of a black bloom. The results indicated that a two-step integrated treatment process is efficient as an urgent disposal measure. The first step is removal of volatile organic sulfide compounds (VOSCs) through the addition of H₂O₂. A total of 50 mg/L of H₂O₂ can largely decrease the concentrations of dimethyl trisulfide and related alkyl sulfide compounds in the water column. The second step is the flocculation and sedimentation of black-bloom-induced black matter via a chitosan-modified clay. The addition of 1 g/L of an attapulgite clay plus 10 mg/L of chitosan can effectively deposit suspended matter on the bottom of the water column and have a positive effect on the removal of nutrients.

Turn the potential greenhouse gases into biomass in harmful algal blooms waters: A microcosm study

Carbon sources are a critical requirement for the proliferation of algae and the occurrence of harmful algal blooms (HABs), but are often turned into methane (CH₄) after the collapse of severe HABs. Here, we attempt to remove HABs, reduce algal-derived CH₄ emissions, and repair the broken carbon biogeochemical cycle in aquatic systems using an integrated ecological approach including flocculation, capping, and submerged macrophyte induction, preliminary at a microcosm scale. This strategy sustainably reached 98% algal removal after 65 days of incubation and resulted in an aerobic microenvironment (ORP = +12 mv) at the sediment-water interface. The approach contributed to an approximate 60% decline in CH₄ released from the aquatic environment into the atmosphere jointly through assimilation of mineralized organic carbon by submerged macrophytes, production of carbon dioxide (CO₂) under aerobic conditions, and aerobic CH₄ oxidation. Some of the CO₂ produced in the aquatic phase contributed to inorganic carbon and formed the submerged macrophytes biomass. A combination of flocculation, capping, and submerged macrophyte incubation were significant contributors to altering the carbon budget and sealing nearly 99% of the carbon in the simulated ecosystem (the majority in sediment, followed by submerged macrophytes), providing a sustainable way to reuse algal-derived carbon and reduce CH₄ emissions.

The occurrence of cyanobacteria blooms in freshwater ecosystems and their link with hydro-meteorological and environmental variations in Tanzania

Cyanobacteria (blue-green algae) are photosynthetic bacteria that under favorable environmental conditions produce secondary metabolites (cyanotoxins) which are harmful to the environment, including humans. The mass proliferation of harmful cyanobacteria is termed CyanoHABs. CyanoHABs can adapt to different climatic fluctuations, therefore, understanding their dynamics in freshwater systems is crucial. Variation in climatic and hydrological processes, changing land use and economic growth all influence the occurrence and distribution of CyanoHABs. There have been inadequate CyanoHAB studies at local scales, therefore their occurrence and dynamics cannot be generalized. This study reviews and synthesizes cases of CysnoHAB occurrence, magnitude, and timing and how these are linked with climatic and hydrological variations in the United Republic of Tanzania. In this study, a scoping review approach was adopted. Research articles, reports, and databases were consulted. The most common species of toxin-producing cyanobacteria were identified in different water bodies in Tanzania, as well as the record of mass fatality of birds (Lesser Flamingo) in Lake Manyara, which in almost all cases occurred during dry years. While previous studies on CyanoHAB dynamics and their links to climate, hydrological, and environmental changes have not been undertaken in Tanzania, there are studies in Lake Victoria and Tanganyika. Therefore, there should be an immediate response from water users, managers, researchers, and water authorities to address and actively engage in monitoring and managing the risks associated with CyanoHABs in Tanzania.

Phenology of Phytoplankton Blooms in a Trophic Lake Observed from Long-Term MODIS Data

Phytoplankton phenology critically affects elements biogeochemical cycles, ecosystem structure, and productivity. However, our understanding about the phenological process and driving mechanism is still very limited due to the shortage of long-term observation data. We used all available daily MODIS-Aqua data from 2003 to 2017 to determine bloom start dates (BSDs) in a typical trophic lake (Lake Taihu) and investigate how phytoplankton BSDs respond to climate change and environmental factors. The results indicate that BSDs have advanced 29.9 days for the entire Lake Taihu from 2003 to 2017. Spatially, an earlier phytoplankton bloom was recorded in the northern bays and the littoral regions than in the center of open water. Air temperature, wind speed, and N/P ratio (N, total nitrogen; P, total phosphorus) were three important factors affecting phytoplankton phenology. Multiple linear correlation showed that air temperature, wind speed, and N/P ratio in Spring could explain 59.9% variability of BSDs for Lake Taihu. This study provides a quantitative assessment of phytoplankton phenological shifts and elucidates the inter-relationship between phenology parameters and environmental factors, thus improving our understanding on the potential impact of climate change and eutrophication on lake ecosystems. The starting earlier and lasting longer of phytoplankton are consistent with the expected effects of climate warming on aquatic ecosystem in recent decades, which will bring new challenges for algal bloom management in eutrophic Lake Taihu.

Characterization of bacterial and microbial eukaryotic communities associated with an ephemeral hypoxia event in Taihu Lake, a shallow eutrophic Chinese lake

While the important roles of microbial communities in oceanic hypoxic zones were beginning to be understood, little is known about microbial community associated with this phenomenon in shallow lakes. To address this deficit, both the bacterial and microbial eukaryotic communities of an ephemeral hypoxic area of Taihu Lake were characterized. The hypoxia provided nutritional niches for various bacteria, which results in high abundance and diversity. Specific bacterial groups, such as vadinBC27 subgroup of Bacteroidetes, Burkholderiales, Rhodocyclales, Pseudomonas, and Parcubacteria, were dominated in hypoxic sites and relevant to the fermentation, denitrification, nitrification, and sulfur metabolism. Conversely, most of microbial eukaryotes disappeared along with the decline of DO. An unexpected dominance of fungi was observed during hypoxia, which partly explained by the accumulation of toxic algae. Mucor was the single dominant genus in the hypoxic zone. We proposed that this group might cooperate with bacterial communities in the anaerobic degradation of algal biomass and woody materials. Generally, the hypoxic microbiome in shallow lakes is mainly involved in fermentative metabolism depending on phytodetritus and is potentially influenced by terrestrial sources. This study provided new insights into the unique microbiome in short-term hypoxia in shallow lakes and lays the foundation for studies that will enhance our understanding of the microbial players associated with hypoxia and their adaption strategy on the global scale.

UV-C suppression on hazardous metabolites in Microcystis aeruginosa: Unsynchronized production of microcystins and odorous compounds at population and single-cell level

The effectiveness of UV-C towards the toxin and odor of M. aeruginosa at population and single cell levels were investigated in three ways. In the absence of UV-C, MC-LR and β-cyclocitral production show similar pattern of incremental rate with growth rate on population level shown as intracellular concentrations of MC-LR (C_MC) and β-cyclocitral (C_BCC), but the cellular quota of MC-LR (Q_MC) and β-cyclocitral (Q_BCC) at single-cell level reached the maximum values, 37.5 ± 1.2 fg cell^-1 and 4.3 ± 0.1 fg cell^-1, just after the early exponential phase. Second, upon UV-C irradiation, the C_MC consistently decreased by 10-41% with increase of UV-C dosage (50-200 mJ cm^-2) while C_BCC increased by 2-14%. Third, during the 14 days' post-UV incubation, UV-C at 75-200 mJ cm^-2 induced remarkable suppressing effects on both C_MC and C_BCC for 3-14 days. The suppressing effects on Q_MC and Q_BCC were induced by UV-C at 100 mJ cm^-2 and above, with shorter suppressing periods by 1-4 days and lower decremental rates by 21%-30% than that of C_MC and C_BCC, indicating interruptions on biosynthesis processes partially contribute to suppression effects of C_MC and C_BCC. The suppression effect on either C_BCC or Q_BCC, with higher decrement rates while lower recovery rates, was more severe than C_MC and Q_MC.

Accumulation of Terrestrial Dissolved Organic Matter Potentially Enhances Dissolved Methane Levels in Eutrophic Lake Taihu, China

Inland waters play an important role for the storage of chromophoric dissolved organic matter (CDOM) and outgassing of methane (CH₄). However, to date, linkages between the optical dynamics of CDOM and dissolved CH₄ levels remain largely unknown. We used multi-year (2012-2014) seasonal data series collected from Lake Taihu and 51 connecting channels to investigate how CDOM optical dynamics may impact dissolved CH₄ levels in the lake. High dissolved CH₄ in the northwestern inflowing river mouths coincided with high underwater UV-vis light availability, dissolved organic carbon (DOC), chemical oxygen demand (COD), DOM aromaticity, terrestrial humic-rich fluorescence, in situ measured terrestrial CDOM, depleted dissolved oxygen (DO), stable isotopic δ²H, and δ¹⁸O compared with other lake regions. Our results further revealed positive relationships between dissolved CH₄ and CDOM absorption at 350 nm, i.e. a(350), COD, DOC, terrestrial humic-rich fluorophores, and DOM aromaticity, and negative relationships between dissolved CH₄ and DO, δ²H, and δ¹⁸O. The central lake samples showed a major contribution of terrestrial-sourced molecular formulas to the ultrahigh resolution mass spectrometry data, suggesting the presence of allochthonous DOM sources even here. We conclude that an elevated terrestrial CDOM input likely enhances dissolved CH₄ levels in Lake Taihu.

Distinguishing two phenotypes of blooms using the normalised difference peak-valley index (NDPI) and Cyano-Chlorophyta index (CCI)

Harmful algal blooms are now widely recognised as a severe threat to freshwater ecosystems, particularly in semi-fluvial environments created by river damming. Given the high spatial and temporal variability of cyanobacterial blooms, remote sensing is more suitable than conventional field surveys in monitoring blooms. However, the majority of existing algorithms cannot distinguish cyanobacterial blooms from eukaryotic algal blooms by extracting spectral features in the remote-sensing reflectance (R_rs). In this study, in situ R_rs spectra of cyanobacterial and green algal blooms in Lakes Gaoyang, Hanfeng and Changshou of the Three Gorges Reservoir (TGR) in China were recorded. Characteristic spectral indices, namely, the normalised difference peak-valley index and Cyano-Chlorophyta index, were used to develop an algorithm that can effectively distinguish cyanobacterial and green algal blooms. The proposed algorithm was also used to investigate the spatio-temporal dynamics of the two phenotypes of blooms derived from Huan Jing 1 charge-coupled device images. The resulting accuracy of 93.5% demonstrated that remote sensing technology, in conjunction with field observation, could efficiently differentiate bloom-forming species and assess the water quality in the TGR.