Mathematical model is a good approach to deal with the coupling effects of governing parameters in algal bloom growth. Amongmanymodels to deal with combining factors and data-based supervised learning classifiers, the Artificial Neural Network (ANN) has the most significant impact on the development of bloom pattern.
In previous work (Hushchyna and Nguyen-Quang, 2017), we have introduced the Modified Redfield Ratio (MRR) to estimate algal blooms occurring in Mattatall Lake, Nova Scotia (Canada). The goals of this paper are to test this modified index based on nutrient level to estimate bloom patterns via field experimental data and by the mathematical simulation with a supervised learning model Artificial Neural Network.
Many waterbodies across Nova Scotia (Canada) have been experiencing algal blooms occurring in large numbers and diversity, without knowledge or understanding about their causes and effects. Algal blooms have appeared in Mattatall Lake (ML) and other lakes of the province in recent years. ML experienced severe algal blooms in 2013. During the fall of 2014, massive algal blooms appeared in ML, and persisted until late December 2014. The blooms have a pattern of being nontoxic in the summer and potentially toxic in the fall-winter season, with nutrients increasing on a monthly basis.
The article discusses the results of studies of the methane production from cyan biomass based on the data obtained in the course of a laboratory experiments. The yield of biogas was calculated from the substrate per unit volume, and its energy properties were determined. Experimental data indicates the feasibility and economic viability of this biotechnology.
We have analyzed the ecological hazard that has emerged as a result of the construction of hydropower plants on the Dnieper, which became the cause of uncontrolled development of cyanobacteria. The environmental risks that are caused by the uncontrolled development of cyanobacteria and their biodegradability were studied. The efficiency of application of the known methods of suppression of mass development of the blue-green algae was analyzed. The amount of biogas that can be synthesized from cyanobacteria biomass of Kremenchug reservoir was estimated.
Досліджено процес комплексного перероблення ціанобактерій через отримання технічного жиру, придатного для виробництва біодизеля, та біогазу. Показано перспективність застосування гідродинамічної кавітації для збільшення ефективності екстрагування технічного жиру та синтезу біогазу. Запропонована комплексна стратегія використання ціанобактерій у енергетичних та сільськогосподарських технологіях.