The project unravels around the following two major impacts
Innovative biotechnology creating zero-pollution bio-based solutions
Outcome #1: Applying recent advances in computational and bioinformatics tools for accelerating and improving the design of synergistic biosystems that will be efficient for bioremediation and revitalization of polluted soil, sediments and water.
Outcome #2: Innovative enhancement strategies, such as genetic enhancement, BES, microbial microaggregation and immobilization, will be applied throughout and combined in novel hybrid systems. Moreover, the phytomanagement strategies developed offer additional opportunities for resource recycling.
Outcome #3: Providing science-based knowledge on the interaction of a wide array of contaminant classes, with the matrix and within the bioremediation system. In addition, a systematic assessment of the detoxification potential and new efficient analytical methods will be delivered, followed by site-specific risk assessments.
Outcome #4: The newly develop bioremediation methods will be validated within the timeframe of the project in lab conditions using real polluted matrices (TRL 4) while selected strategies will undergo field testing and validation (TRL 5).
Outcome #5: Advanced assessments on LCA, LCC, social LCA and Environmental Risk Assessment (ERA) will be applied to diverse technologies and bioremediation scenarios. Moreover, the methodology will follow FAIR data principles, for easing data re-use (e.g., ILCD-compliant LCA data), while contributing to the GLAD network.
Circular bio-based systems reversing climate change, restoring biodiversity & protecting air, water & soil quality
Outcome #6: New approaches for efficient bioremediation and resource recycling.
Outcome #7: Targeting to revitalize and restore several ecosystems, always via designing healthy symbiotic relationships between microbial communities and plants, which will be exploited for pollution removal, but eventually will create an ecosystem that will support additional biodiversity.
Outcome #8: Developing biotechnologies that will be gentle with the environment while recovering soil health and water quality and whose environmental performance will be thoroughly assessed through and LCA methodology as well as Environmental Risk Assessment.
Outcome #9: Optimizing the metabolic routes and symbiotic relationships of biosystems to reduce consumption of external chemicals or energy, lowering the environmental footprint of bioremediation processes. Moreover, though an (eco)toxicity assessment solid conclusions of the benefits of the bioremediation processes will be provided, identifying possible secondary toxic metabolites and taking measures to avoid those, while the application of QSAR models will greatly increase the data available for the ERA.
Outcome #1: Applying recent advances in computational and bioinformatics tools for accelerating and improving the design of synergistic biosystems that will be efficient for bioremediation and revitalisation of polluted soil, sediments and water.
Outcome #2: Innovative enhancement strategies, such as genetic enhancement, BES, microbial microaggregation and immobilisation, will be applied throughout and combined in novel hybrid systems. Moreover, the phytomanagement strategies developed offer additional opportunities for resource recycling.
Outcome #3: Providing science-based knowledge on the interaction of a wide array of contaminant classes, with the matrix and within the bioremediation system. In addition, a systematic assessment of the detoxification potential and new efficient analytical methods will be delivered, followed by site-specific risk assessments.
Outcome #4: The newly develop bioremediation methods will be validated within the timeframe of the project in lab conditions using real polluted matrices (TRL 4) while selected strategies will undergo field testing and validation (TRL 5).
Outcome #5: Advanced assessments on LCA, LCC, social LCA and Environmental Risk Assessment (ERA) will be applied to diverse technologies and bioremediation scenarios. Moreover, the methodology will follow FAIR data principles, for easing data re-use (e.g., ILCD-compliant LCA data), while contributing to the GLAD network.
Outcome #6: New approaches for efficient bioremediation and resource recycling.
Outcome #7: Targeting to revitalise and restore several ecosystems, always via designing healthy symbiotic relationships between microbial communities and plants, which will be exploited for pollution removal, but eventually will create an ecosystem that will support additional biodiversity.
Outcome #8: Developing biotechnologies that will be gentle with the environment while recovering soil health and water quality and whose environmental performance will be thoroughly assessed through and LCA methodology as well as Environmental Risk Assessment.
Outcome #9: Optimising the metabolic routes and symbiotic relationships of biosystems to reduce consumption of external chemicals or energy, lowering the environmental footprint of bioremediation processes. Moreover, though an (eco)toxicity assessment solid conclusions of the benefits of the bioremediation processes will be provided, identifying possible secondary toxic metabolites and taking measures to avoid those, while the application of QSAR models will greatly increase the data available for the ERA.