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Algal bloom significantly alters the physicochemical properties of water due to drastic pH change, dissolved oxygen depletion/super-saturation, and toxicity, which lead to ecosystem destruction. To prevent this, this study evaluated the reduction performance of algal biomass by applying a non-thermal or cold plasma process. We used chlorophyll-a (chl-a), suspended solids (SS), and turbidity as indicators of the biomass. Results demonstrated that their removal efficiencies were in the ranges 88–98%, 70%–90%, and 53%–91%, respectively. Field emission scanning electron microscopy indicated how the cell wall of microalgae was destroyed by cold plasma. Also, the removal kinetics of cold plasma confirmed the enhanced removal rate constants. The estimated required times for 99% removal were 0.4–1.2 d (chl-a), 1.3–3.4 d (SS), and 1.6–6.2 d (turbidity), respectively. Overall, cold plasma could be a useful option to effectively treat pollution associated with algal bloom in surface water.

The dimension of the separation zone in the dissolved air flotation (DAF) process is practically determined by the rise velocity of the bubble-floc agglomerates: flocs attached to several bubbles. To improve the flotation velocity and particle removal efficiency in the DAF process, many researchers have tried to attach as many bubbles as possible to flocs. In this study, the rise velocity of bubble-floc agglomerates, considered to be the most important factor in designing the separation zone of the flotation tank in the DAF process, was investigated on the basis of comparison between theoretical and observed results. The observed rise velocity measured by a particle image analyser (PIA) and the predicted value, however, did not show similarity, in contrast to what we had expected. Furthermore, the simulated results using population balance to predict the maximum number of attached bubbles on a floc were too impractical to accept under the practical condition of the surface of the floc if there was no change of bubble size. These findings led us to suggest that there were three possible causes which could conceivably explain the observations. It was suggested that the differences between predicted and observed values could be attributed to one or more of the possible causes.

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