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CitiObs – Enhancing Citizen Observatories for healthy, sustainable, resilient and inclusive cities

Project details

Website: https://citiobs.eu/

Status: Ongoing

Project period: 2025–2026

Principal: EU – Horizon Europe (EC/HEU)

Coordinating institution: NILU

Collaborators: NECU – NATIONAL ECOLOGICAL CENTRE OF UKRAINE, IHE - STICHTING IHE DELFT INSTITUTE FOR WATER EDUCATION, RIVM - RIJKSINSTITUUT VOOR VOLKSGEZONDHEID EN MILIEU, UCD - UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN, DRAXIS ENVIRONMENTAL SA, DREVEN SRL, EUROCITIES, CREAF - CENTRO DE INVESTIGACION ECOLOGICA Y APLICACIONES FORESTALES, IAAC - INSTITUT D'ARQUITECTURA AVANCADA DE CATALUNYA, UNIVERSITEIT LEIDEN, AIRLY - AIRLY SPOLKA Z OGRANICZONA ODPOWIEDZIALNOSCIA, SECD - SECURE DIMENSIONS, AS - AIRSENTINELS

CitiObs seeks to revolutionize urban environmental governance by empowering citizens to become active contributors to the observation and management of their local environments. The project’s core objective is to consolidate and scale up Citizen Observatories (COs) as tools for fostering sustainability, resilience, and inclusivity in urban areas across Europe. By integrating citizen-generated data with advanced environmental observation systems, CitiObs aims to bridge the gap between local action and global environmental goals, including the European Green Deal.

The project addresses the urgent need for innovative and inclusive approaches to mitigate urban environmental challenges such as air pollution and climate change. By leveraging low-cost sensors and wearable technologies, CitiObs empowers diverse communities to monitor key environmental parameters while actively contributing to policy development and local decision-making processes.

CitiObs employs a co-creation framework, working closely with five Frontrunner cases, 30 Alliance cases, and 50 Fellow cases to develop, test, and scale its tools and methodologies. This multi-level engagement ensures that COs are adapted to diverse socio-political contexts while promoting horizontal and vertical governance models. Activities such as needs assessment workshops, capacity-building sessions, and strategic roadshows ensure the broad participation of stakeholders, from local citizens to EU policymakers.

The project’s outcomes include the development of a comprehensive knowledge platform and the CitiObs Cookbook, which will serve as resources for cities worldwide to establish or enhance their own Citizen Observatories. By formalizing the role of citizen-generated data in environmental management, CitiObs not only legitimizes but also elevates the contributions of individuals and communities to achieving sustainable urban futures.

Through collaboration, innovation, and community engagement, CitiObs envisions a future where cities are not only more resilient and sustainable but also deeply reflective of the collective input and aspirations of their citizens.

Updated: 08.04.2025

CitiObs – Enhancing Citizen Observatories for healthy, sustainable, resilient and inclusive cities has 7 publications at NILU:

A scalable framework for harmonizing, standardization, and correcting crowd-sourced low-cost sensor PM2.5 data across Europe

Hassani, Amirhossein; Salamalikis, Vasileios; Schneider, Philipp; Stebel, Kerstin; Castell, Nuria

2025

Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast

Shetty, Shobitha; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve; Hassani, Amirhossein; Berntsen, Terje Koren; Schneider, Philipp

2024

Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention

Lepioufle, Jean-Marie; Schneider, Philipp; Hamer, Paul David; Ødegård, Rune Åvar; Vallejo, Islen; Cao, Tuan-Vu; Taherkordi, Amirhosein; Wojcikowski, Marek

2024

Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning

Shetty, Shobitha; Schneider, Philipp; Stebel, Kerstin; Hamer, Paul David; Kylling, Arve; Berntsen, Terje Koren

2024

Estimating high resolution daily surface PM2.5 over Europe using CAMS PM forecast, satellite AOD, and a Machine Learning Model.

Shetty, Shobitha; Schneider, Philipp; Hamer, Paul David; Stebel, Kerstin; Kylling, Arve; Berntsen, Terje Koren

2024

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