PROJECT DESCRIPTION
BACKGROUND
Cyanobacteria are microscopic organisms found naturally in all types of water. In warm, nutrient-rich (high in phosphorus and nitrogen) environments, cyanobacteria can multiply quickly, creating blooms that spread across the water’s surface. The blooms can produce toxins (cyanotoxins), that affect the water quality. They can also be harmful to humans (causing allergic-like reactions, flu-like symptoms, and gastroenteritis), animals and the environment.
Current methods used for detecting of cyano blooms are mainly based on the in situ collection of samples followed by laboratory analysis. Infrequent sampling limits the early detection of blooms, with potential impacts on drinking water management. There exist other approaches which can support decision-making, such as satellite remote sensing, fluorescence-based probes and drones. However, these tools need to be equipped with advanced imaging solutions (i.e., multispectral, hyperspectral) to reach the precision needed. Moreover, they need to be accompanied by analytical methods to determine the actual toxicity of the blooms. Moreover, the World Health Organization (WHO) recommends introducing molecular methods for the monitoring of toxigenic cyanobacteria.
OBJECTIVES
The CYANOBLOOM project aims to demonstrate a solution for the early detection of toxic cyanobacteria blooms in public water supply reservoirs through a combination of remote monitoring (i.e., data from public and private satellites) and on-site measurements (i.e., hyperspectral field measurements with genetic analysis of collected samples). As a result, it is expected that the chance of the timely identification of a bloom will be increased from the current 0.82-1.11% to 90%.
The new solution will be tested in four water reservoirs located in Spain (2), Sweden and the Netherlands.
The project’s specific objectives are:
The collection and structuring of data obtained from very-high resolution (VHR), hyperspectral and Copernicus satellites.
The implementation of production chains for processing satellite data, including atmospheric correction and pigment detection models, for the identification of harmful cyanobacteria algal blooms (HABs).
The installation and calibration of an in situ hyperspectral system for validation and calibration of the satellite data.
The early detection of HABs through genetic analysis.
The design of a complete HAB early warning system by identification of correlations between toxic events and toxic potentiality from genetic analysis and in situ hyperspectral data and satellite data.
To set up a risk management tool for HABs on which monitoring agencies can support their decision-making: a dashboard showing the cyanobacteria cyanoHAB indicator for selected waterbodies.
To demonstrate the environmental and social benefits of the solutions from a life cycle perspective in current and future scenarios (i.e., considering climate change).
To define the business model for the commercial exploitation of the innovative schemes developed by the project.
To disseminate and communicate the results of the project, fostering social awareness of the environmental problems caused by HABs, paving the way towards the further commercialisation of the solution at European level.
RESULTS
The project’s expected results are:
Increase in the accuracy and coverage of the monitoring system (80-90% probability of detection and early warning).
Preservation of high water quality by reducing exposure time to toxic blooms by 80%.
Reduction of water supply cut-off due to blooming to 10%.
Reduce public health problems through the early warning system by 85-90%.
Reduction of economic losses from recreational activity due to cyanobacterial blooms by 80-90%.
