Estimation and evaluation of auto-flocculated algae harvesting efficiency using the population balance in turbulence model in flotation process
Author(s) -
Dong-Heui Kwak,
MiSug Kim
Publication year - 2017
Publication title -
water science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 137
eISSN - 1996-9732
pISSN - 0273-1223
DOI - 10.2166/wst.2017.491
Subject(s) - flocculation , algae , agglomerate , biomass (ecology) , environmental science , environmental engineering , algal bloom , population , sedimentation , pulp and paper industry , pollutant , ecology , biology , chemical engineering , engineering , paleontology , demography , phytoplankton , sociology , sediment , nutrient
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.
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