Biofuel production from microalgae can be both sustainable and economically viable. Particularly in the case of algal growth in wastewater an extra benefit is the removal or biotransformation of pollutants from these types of waters. A continuous monitoring system of the microalgae status and the concentration of different wastewater contaminants could be of great help in the biomass production and the water characterisation. In this study we present a system where spectral fluorescence signature (SFS) techniques are used along with absorption measurements to monitor microalgae cultures in wastewater and other mediums. This system aims to optimise the microalgae production for biofuel applications or other uses and was developed and tested in prototype indoor photo-bioreactors at the University of Vigo. SFS techniques were applied using the fluorescence analyser INSTAND-SCREENER developed by Laser Diagnostic Instruments AS. INSTAND-SCREENER permits wavelength scanning in two modes, one in UV and another in VIS. In parallel, it permits the on-line monitoring and rapid analysis of both water quality and phytoplankton status without prior treatment of the sample. Considering that different contaminants and microalgae features (density, status etc.) have different spectral signatures of fluorescence and absorption properties, it is possible to characterise them developing classification libraries. Several algorithms were used for the classification. The implementation of this system in an outdoor raceway reactor in a Spanish wastewater treatment plant is also discussed. This study was part of the Project EnerBioAlgae (http://www.enerbioalgae.com/), which was funded by the Interreg SUDOE and led by the University of Vigo.
In typical case 2 waters an accurate remote sensing retrieval of chlorophyll a (chla) is still challenging. There is a widespread understanding that universally applicable water constituent retrieval algorithms are currently not feasible, shifting the research focus to regionally specific implementations of powerful inversion methods. This study takes advantage of regionally specific chlorophyll a (chla) algorithms, which were developed by the authors of this abstract in previous works, and the characteristics of Medium Resolution Imaging Spectrometer (MERIS) in order to study harmful algal events in the optically complex waters of the Galician Rias (NW). Harmful algal events are a frequent phenomenon in this area with direct and indirect impacts to the mussel production that constitute a very important economic activity for the local community. More than 240 106 kg of mussel per year are produced in these highly primary productive upwelling systems. A MERIS archive from nine years (2003-2012) was analysed using regionally specific chla algorithms. The latter were developed based on Multilayer perceptron (MLP) artificial neural networks and fuzzy c-mean clustering techniques (FCM). FCM specifies zones (based on water leaving reflectances) where the retrieval algorithms normally provide more reliable results. Monthly chla anomalies and other statistics were calculated for the nine years MERIS archive. These results were then related to upwelling indices and other associated measurements to determine the driver forces for specific phytoplankton blooms. The distribution and changes of chla are also discussed.
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