• Background

  The increasing energy demand in the World is drawing attention to the need for developing new supply pathways based on inexhaustible sources with reduced environmental impacts. If managed sustainably, biofuels are renewable energy resources for heat, power and transportation that can contribute to less GHG emissions and atmospheric contaminants than fossil fuels. 

  Microalgae are some of Nature’s finest examples of solar energy conversion systems, transforming carbon dioxide into complex organic molecules through photosynthesis. They are capable of achieving solar energy to biomass conversion efficiencies up to one order of magnitude higher than oleaginous crops, and there is biotechnology potential to further increase conversion efficiency. Due to their outstanding photosynthetic yields and ability to grow in non-arable lands, non-potable water sources (e.g. wastewater, seawater), and a wide range of environmental conditions, there is much interest in the use of microalgae biomass as a source of truly sustainable bioenergy feedstock. Despite this potential, no commercial facilities for biofuel production from microalgae have been implemented in the EU. The dilute concentrations of microalgae in the growth media impact negatively on the biofuel life cycle energy balance as it takes much energy to harvest, concentrate and dry the biomass.

• Objective

  The main objective of PRODIGIO is to establish a knowledge base for the development of a system failure prediction technology that increases the performance of microalgae biomass production and anaerobic digestion systems and advance towards more favourable techno-economic, environmental and social performance to achieve more sustainable microalgae biogas.

  PRODIGIO will boost the efficiency of solar energy conversion into biogas by increasing the performance of:

  1. Microalgae production systems
  2. Anaerobic digestion systems

  thanks to the development of early-warning signals for improved systems monitoring and control.

• More about the project

  Anaerobic Digestion Systems

  Anaerobic digestion (AD) is probably the most economically attractive process for the production of biofuel from microalgae since it does not require drying of biomass and it is a relatively simple procedure from an infrastructure and engineering perspective. AD is a natural biomass degradation process carried out by microorganisms, which very efficiently transform the organic matter firstly into intermediate bioproducts and finally into biogas under anaerobic conditions.

  Microalgae Production Systems

  Microalgae are some of nature’s finest examples of solar energy conversion systems, transforming carbon dioxide into complex organic molecules through photosynthesis. They are capable of achieving solar energy to biomass conversion efficiencies up to one order of magnitude higher than oleaginous crops, and there is biotechnology potential to further increase conversion efficiency4. Due to their outstanding photosynthetic yields and ability to grow in non-arable lands, non-potable water sources (e.g. wastewater, seawater), and a wide range of environmental conditions, there is much interest in the use of microalgae biomass as a source of truly sustainable bioenergy feedstock.

  Early-warning Signal

  PRODIGIO will develop an innovative and versatile methodology for the identification of early warning signals that combines causal detection methods with the analysis of interaction networks. The method sequentially calculates the interaction network over time (its topology and strength of the interactions) and, at each time step, it calculates a measure of the stability of the network. When stability approaches a critical value (or tipping point), the method evaluates the dominant eigenvalue of the interaction network, providing the best warning/s for system failure. By combining ‘big data’ acquisition from thoroughly designed perturbation experiments in bioreactor systems, advanced metaOmics and chemical fingerprint technologies, state-of-the-art bioinformatic tools, and novel methods for the analysis of causal interaction networks, PRODIGIO will decode triggers, identify early-warnings, define threshold values, and calculate warning times for critical state transitions in bioreactor systems.

Researchers

Project partners