Management Of Algal Blooms Research Articles

Estimation and evaluation of auto-flocculated algae harvesting efficiency using the population balance in turbulence model in flotation process.

Algae are considered water pollutants because they form algal blooms in stagnant water. Algae harvesting technology, however, can help convert them into a useful industrial material like biomass. The core technique (flocculation) separates microalgae from other flocculants, allowing for the harvest of clean and pure algal biomass. This study aims to estimate and evaluate algal separation (removal or harvesting) efficiency (X) to concurrently obtain the objectives of algal bloom management and algal particle collection. To simulate algal separation by auto-flocculation (no flocculants) related flotation, the population balance in turbulence (PBT) model is used. Model simulations are conducted under optimal conditions provided by previous studies about the biological impact factors of algae, operating parameters of the flotation process, and so on. This modeling study determines the efficiency (X) of separating algae from the water body in the separation zone after forming auto-flocculated bubble-floc agglomerates by making them collide and attach to each other in the contact zone of the flotation tank. The X is examined as a function of size distribution of agglomerates and bubbles and of the number of initially injected bubbles. Optimal conditions for forming and harvesting the agglomerates may be found through further modeling studies.

Demonstration of a Novel Control Strategy for Prymnesium parvum Management in Fish Hatcheries

AbstractPrymnesium parvum blooms result in fish kills around the world and are devastating to fish hatcheries, where few management tools are available. Current control strategies include algaecides, nutrient management, and flocculation, which are moderately effective at best and can be toxic to nontarget organisms. A relatively new type of medium, registered by the U.S. Environmental Protection Agency for the control of fecal coliforms in storm water runoff, was evaluated as a possible P. parvum control tool. The medium, called Smart Sponge, was designed to absorb petroleum hydrocarbons; a variant, Smart Sponge Plus, is enhanced with antimicrobial properties. It is these antimicrobial properties that we investigated for possible use in algal bloom management. Our objective was to evaluate the efficacy of this type of medium on the eradication of P. parvum and its associated toxins, with a view toward advancing toxic algae control strategies. Prymnesium parvum was passed through columns of the filter medium. Algal cell counts and visual observations were used to assess mortality; fish bioassays were conducted to assess toxicity. Smart Sponge Plus successfully killed the algae, although toxins were released during filtration. After filtration, 87–100% algal removal was achieved, with the variability potentially being related to cell density at the initiation of the test. Smart Sponge was also successful in reducing associated the toxicity of P. parvum, as was a charcoal medium. Smart Sponge Plus shows promise for use in the management of golden algal blooms by reducing cell density and should be further evaluated in hatchery and field settings.

Multi-criteria decision analysis applied to harmful algal bloom management: A case study.

Harmful algal blooms (HABs) have received greater attention in recent years due to an increase in the frequency of outbreaks and a growing potential for blooms to exact considerable economic losses and negatively impact ecosystem health. Human activity has been shown to intensify HAB outbreaks through increased eutrophication, elevated local air and water temperatures, disturbance of the thermal stratification of lakes, and modification of local hydrology. With the advent of new remediation technologies and a better understanding of the ecological factors affecting HABs, mitigating the adverse effects of HABs has become more feasible than ever before but still requires balancing mitigation efficiency, environmental impacts, costs, and stakeholder needs. In the present paper, we discuss potential HAB management solutions and propose using a Multi-Criteria Decision Analysis (MCDA) framework to analyze the perspectives and priorities of various stakeholders as they pertain to 4 major considerations for HAB mitigation: human health, environmental impact, social impact, and technical feasibility. A hypothetical case study of an HAB-affected lake is used to demonstrate how stakeholders may prioritize HAB management alternatives within the MCDA framework. Integr Environ Assess Manag 2017;13:631-639. © 2016 SETAC.

Application of an Algal Bloom Control Technique using Large Zooplankton Predators in An Eutrophic Agricultural Reservoir: A Preliminary Study

AbstractMassive nuisance algal blooms are a primary concern for the management of eutrophic reservoirs. The effects of biomanipulation using trophic cascade effects in the aquatic food chain vary with the conditions of applied water bodies and are controversial. However, this mode of biomanipulation has long been considered an ecosystem‐friendly approach for the management of algal blooms. In the present study, herbivorous Daphnia similoides were artificially proliferated using a large culture system and were used to control algal blooms in a eutrophic agricultural reservoir. Introduced predators proliferated rapidly in the culture tanks, and high densities were subsequently sustained. Predators were then released into the reservoir at 1‐week intervals during early summer and autumn, and 84.4% algal removal efficiency was observed and mean values of chlorophyll a concentration decreased from 219 to 34.2 mg m−3 during the algal bloom period in autumn. However, no apparent effects were observed during early summer when fish predation and water temperatures were high. These data suggest that continuous release of predators from our culture facility efficiently facilitates early expansion of zooplankton populations and maintenance of their populations in the reservoir. The effects of introduced zooplankton may be maximized with concurrent management of resident zooplanktivorous fish. Copyright © 2016 John Wiley & Sons, Ltd.

낙동강의 환경요인이 조류군집 구성에 미치는 영향

This study was carried out to investigate algal community structures and their correlations with environmental factors on five weir areas in the Nakdong River, South Korea. Water qualities, hydrodynamics, meteorological conditions and algal species compositions were observed in studied sites from May 2010 to Dec. 2013. Results showed that average total phosphorus concentration of 2013 was decreased by 52.4% in comparing with that from 2010 to 2011. Chlorophyll.a concentrations were positive significant with water temperature, pH, total phosphorus and total nitrogen, but is not significant with turbidity and suspended solids. Seasonal successions of algae were observed that Stephanodiscus sp. was dominant species with 65.3% of dominant frequency in studied site. Large algal biomass of the low temperature-adapted diatoms were observed during temperature range of <TEX>$4{\sim}9^{\circ}C$</TEX>, but large cyanobacterial biomass mainly during high temperature period ranged from <TEX>$22^{\circ}C$</TEX> to <TEX>$32^{\circ}C$</TEX>. Microcystis sp. dominated during high water temperature in summer. The yearly correlations of algal biomass with accumulated solar radiations were not significant but seasonal correlations of summer from June to August were significant with correlation coefficient 0.33 (p<0.05). There were not significant correlations between turbidities and algal biomass. Turbidity and suspended solids concentrations were not significant correlation with algal biomass. According to the results, algal communities had strong correlation with water temperature and had partially correlation with solar radiation. For an effective management of algal blooms, water managers should survey with more long-term monitoring of various environmental factors and algal communities.

Proactive management of estuarine algal blooms using an automated monitoring buoy coupled with an artificial neural network

Algae proliferate when favourable biological, chemical and physical conditions are present. Algal blooms within the Hawkesbury River, NSW, are a regular feature of seasonal cycles and develop in response to non-periodic disturbances. To improve the understanding of processes that lead to algal blooms, an autonomous buoy has been deployed (since 2002) which has generated a high resolution, temporal data set. Parameters monitored at 15 min intervals include Chlorophyll-a, temperature (water and air), salinity and photosynthetically available radiation. This data set is used to configure an Artificial Neural Network (ANN) to predict (one, three and seven days in advance) the mean, 10th and 90th percentile, daily Chlorophyll-a concentrations. The prediction accuracy of the ANNs progressively decreased from one to seven days in advance. Incorporating predictive models coupled with near real time data sourced from automated, telemetered monitoring buoys enables environmental managers to implement proactive algal bloom management strategies.

Use of local ecological knowledge in the management of algal blooms

SUMMARYMore frequent and severe algal blooms are symptomatic of increasing ecosystem stress in coastal waters. Economic losses typically follow and local governments are forced to ‘manage’ this issue. Because many blooms are not monitored, local ecological knowledge (LEK) and oral history are the only practical tools to obtain data on bloom characteristics and identify their drivers. LEK was applied to outbreaks of brown algae on popular tourist beaches in south-east Queensland (Australia). Structured interviews with local citizens who had a close and frequent connection with the ocean provided 541 bloom records, which showed that blooms are regional (≥400 km) rather than local, and that they are a historical (≥40 years) rather than a recent phenomenon. LEK frequently cited that particular wind regimes coincided with the arrival of blooms, but this could not be verified by statistical cross-validation with empirical data. Harnessing LEK was valuable in engaging citizens, in generating testable hypotheses about plume causes, in providing a previously unrecognized historical perspective and in identifying the correct spatial scale of the issue. Multi-pronged approaches will be most effective in addressing blooms where local mitigation actions are combined with broader regional coastal environmental conservation efforts.

The use of phytoplankton patterns of diversity for algal bloom management

Many biotic and abiotic processes contribute to variability in phytoplankton diversity in aquatic ecosystems. Depending on their intensity and on their frequency, these may drive non-equilibrium dynamics and enhance the species diversity. Different studies propose that biodiversity buffers ecosystem functioning against environmental fluctuations leading to more predictable aggregate community or ecosystem properties. Salto Grande reservoir is polymictic and eutrophic with recurrent summer cyanobacterial blooms. The aim of this study was to determine the key variable(s) related with phytoplankton diversity in order to predict the possible occurrence of an algal bloom at the ecosystem. A preliminary analysis of the data matrix suggested non-linear relationships between diversity and the selected variables: phytoplankton abundance and the vertical attenuation coefficient (Kd). The best function fitting of the scatter plot of phytoplankton diversity versus phytoplankton abundance was a rational function. The inflection point of phytoplankton diversity estimated by the second derivate of this function was 2.7 bit cell −1 which corresponded to an abundance of 3000 cells ml −1. The relationship of phytoplankton diversity and vertical attenuation coefficient values also show a humped distribution pattern (Gauss function). The inflection point of this function corresponded to a diversity value of 1.9 bit cell −1 and 2.5 m −1 for Kd. These inflection points were, respectively, related with the resource competition among the present species and the light limitation conditions. The showed patterns of diversity and the estimated threshold values could be integrated to construct a predictive model for the reservoir based on phytoplankton diversity and the probable ambient conditions of the reservoir.

Estimation of submarine groundwater discharge in Plover Cove, Tolo Harbour, Hong Kong by 222Rn

Algal blooms in Tolo Harbour, Hong Kong have received much attention and submarine groundwater discharge is speculated to be a significant pathway carrying nutrients into the constricted estuary. Plover Cove, a small cove in the Harbour, was selected for SGD analysis using 222Rn budget. The volumetric SGD rates are estimated to be about 8000 m 3/day for neap tide and about 17,000 m 3/day for spring tide. Result of nutrient analysis of the porewater indicates that the nutrient loading through this pathway is speculated to be crucial for eutrophication in Tolo Harbour. Current practice for the management of algal blooms in Hong Kong, in which nutrient loading through SGD was ignored, has to be reviewed and the control measures of groundwater contamination are obviously required.

Modelling diatom growth in turbulent waters

Algal models used as tools in the management of algal blooms may be inaccurate because representation of mixing processes is often oversimplified. A testable 3-D algal model for prediction of algal growth in turbulent surface waters was developed based on the Eulerian water quality model, HYDRO-3D. Out-door mesocosm experiments on the growth of the diatom Skeletonema costatum showed no evidence that diatom growth is significantly affected by light/dark fluctuations brought about by turbulent mixing, and no direct effects of turbulence on phytoplankton physiology were required in the algal model. The algal model was successfully calibrated and validated against mesocosm data and field data from Poplar Dock, London Docklands. Application of the model gave credible results for the hypothetical growth of S. costatum in Poplar Dock under a wide range of wind speeds and surface irradiances. However, differences between the results of a full 3-D simulation and a simplified 1-D representation of Poplar Dock were minimal, and no clear conclusions could be drawn on the superiority of 3-D models over 1-D models for simulation of complex flows in natural water bodies.

Modelling diatom growth in turbulent waters

Algal models used as tools in the management of algal blooms may be inaccurate because representation of mixing processes is often oversimplified. A testable 3-D algal model for prediction of algal growth in turbulent surface waters was developed based on the Eulerian water quality model, HYDRO-3D. Out-door mesocosm experiments on the growth of the diatom Skeletonema costatum showed no evidence that diatom growth is significantly affected by light/dark fluctuations brought about by turbulent mixing, and no direct effects of turbulence on phytoplankton physiology were required in the algal model. The algal model was successfully calibrated and validated against mesocosm data and field data from Poplar Dock, London Docklands. Application of the model gave credible results for the hypothetical growth of S. costatum in Poplar Dock under a wide range of wind speeds and surface irradiances. However, differences between the results of a full 3-D simulation and a simplified 1-D representation of Poplar Dock were minimal, and no clear conclusions could be drawn on the superiority of 3-D models over 1-D models for simulation of complex flows in natural water bodies.

Use of Discriminant and Fourth-Derivative Analyses With High-resolution Absorption Spectra for Phytoplankton Research: Limitations at Varied Signal-to-Noise Ratio and Spectral Resolution

Future management efforts aimed at inhibiting harmful algal blooms will require extensive temporal and spatial monitoring of phytoplankton community composition. A cost-effective approach to delineating phytoplankton community composition may be through analysis of absorption spectra, measured in situ with instruments deployed on moorings or by remote sensing. Classification techniques relying on absorption spectra include discriminant and fourth-derivative analysis. We investigated how well these techniques performed theoretically at varied signal-to-noise ratio and spectral resolution representative of a new absorption and attenuation instrument called HiStar. Our findings suggest that discriminant analysis of absorption spectra is a highly useful technique for categorizing green algae, cyanobacteria, noxious bloom-forming dinoflagellates, diatoms, and other chrysophytes. For the purposes of discriminating dinoflagellates from the other algae groups, discriminant analysis worked well with either low- or high-resolution spectral data. The discriminant analysis technique was able to delineate a noxious bloom-forming dinoflagellate species, Prorocentrum minimum, at signal-to-noise ratios as low as ~17. The current noise level in the HiStar, however, is ~28-fold too high to allow correct classification of this dinoflagellate at concentrations where shellfisheries are closed. Improvements to the discriminant analysis (e.g., inclusion of scatter properties) or to the HiStar must be accomplished before this technique becomes useful for harmful algal bloom management applications. Fourth-derivative analysis of absorption spectra, also a useful classification technique and a possible approach to assess physiological state of some algae, required at least 4 nm spectral resolution for assessment of chlorophylls a and b. The spectral resolution of HiStar (3.3 nm) meets this requirement.