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Effective Monitoring and Modelling solutions for data-driven hOlistic management of URBAN water quality

Objective

URBAN M2O aims to create solutions to generate the crucial information that is needed to develop and implement risk-based urban water quality management plans at the city scale. Such plans will contribute to achieving sustainable urban water systems with zero pollution impact on human health and the environment. URBAN M2O will achieve this objective by:
1) Developing and benchmarking AI-enhanced, resource-effective monitoring water quality technologies;
2) Developing fit-for-purpose water quality models and harmonized data management systems;
3) Demonstrating open-access urban water digital twins assimilating monitoring data to identify hotspots and prioritize pollution control actions under current and future climate scenarios;
4) Providing tailored guidance to end users and stakeholders for the effective development of urban water quality monitoring and management plans.
Industrial partners will enhance their monitoring techniques with AI methods, benchmarking them against state-of-the-art monitoring approaches for trace organic chemicals, microbial contaminants, and microplastics in all urban water systems, namely drinking water, surface water, bathing water, wastewater effluents, groundwater, urban run-off, and sewer overflows. Monitoring and modelling solutions will be demonstrated in three real and operational case studies, selected to represent different challenges faced by urban water infrastructure. The URBAN M2O solutions will be tailored to stakeholders and end-users’ needs, addressing current and future requirements and challenges, and different resources and data availability.
URBAN M2O will enable urban water managers and regulators to make informed decisions, prioritizing actions to enhance urban water quality, and protect human health, the environment, and biodiversity at the European scale.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

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Coordinator

DANMARKS TEKNISKE UNIVERSITET
Net EU contribution
€ 910 956,00
Address
ANKER ENGELUNDS VEJ 101
2800 Kongens Lyngby
Denmark

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Region
Danmark Hovedstaden Københavns omegn
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 910 956,25

Participants (15)

Partners (4)

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