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AquaNES intends to catalyze innovations in water and waste water treatment processes and management through improved combinations of natural and engineered components. The project focuses on 13 demonstration sites in Europe, India and Israel covering a representative range of regional, climatic, and hydro geological conditions. Among the demonstrated solutions are natural treatment processes such as bank filtration (BF), managed aquifer recharge (MAR) and constructed wetlands (CW) plus engineered pre- and post-treatment options.
The AquaNES consortium (see partners) assembles at partnership of (waste)water utilities, SMEs and industries as well as high level academic partners and research institutes from seven European countries, Israel and India, representing a good balance along a technology innovation value chain.
Our SME’s and industries provide existing and new pre- or post-treatment technologies, monitoring devices or software tools which are integrated by water utilities in combined natural and engineered treatment schemes to demonstrate and validate the treatment efficacy of the combined system. The close collaboration with partnering water utilities will speed-up the deployment of successfully operating combined treatment processes.
AquaNES specific objectives are:
BDS’s main involvement is in work package 4 (WP4): Risk Assessment and Water Quality Control. This work package will design and demonstrate an efficient quantitative water quality assessment framework for cNES that is easy to use and allows integration of innovative monitoring approaches. Modules will be designed using a set of monitoring systems for a variety of emerging water quality issues such as fecal contamination, antibiotic resistance genes and biological effects of complex mixtures of chemicals. The effectiveness of cNES to remove the monitored biological and chemical contamination will be demonstrated.
The specific goals of WP4 are to:
BDS’s main tasks in the project are:
Visit www.aquanes.eu for more information.
The AquaNes Project has received funding from the Europian Union’s Horizon 2020 research innovation programme under grant agreement no. 689450