SubsidieMeestersDeep Learning Air Quality Forecasts for Four Days
AQplus4 aims to create an advanced air quality forecasting system using deep learning to enhance accuracy and support global environmental monitoring and health warnings.
Projectdetails
Introduction
AQplus4 will develop the first scientifically sound operational air quality forecasting system based on innovative deep learning and IT technology.
Project Background
Based on the successful development of AI air quality forecasting models in the IntelliAQ advanced grant, we will explore the combination of several deep learning models into one coherent concept.
Objectives
- Test the transferability to new air pollutant species.
- Test the transferability to other world regions.
- Cover the necessary technical developments to prepare the data processing and deep learning software for operational use.
Stakeholder Engagement
We shall set up a dialogue with two identified stakeholders (UBA Germany and NIER Korea) to discuss the following:
- Data processing and forecasting requirements.
- Deployment and maintenance options.
The stakeholder exchange will also include training activities, including extended training of a Korean researcher.
Importance of Air Quality Forecasts
Timely and reliable air quality forecasts are important to issue health warnings and prepare mitigation measures.
Previous Achievements
IntelliAQ has demonstrated higher accuracy forecasts compared to conventional chemistry transport model results.
Future Impact
The AQplus4 system will therefore constitute an important breakthrough innovation that may later be adopted at several environmental monitoring agencies around the world.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 150.000 |
| Totale projectbegroting | € 150.000 |
Tijdlijn
| Startdatum | 1-11-2023 |
| Einddatum | 30-4-2025 |
| Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- FORSCHUNGSZENTRUM JULICH GMBHpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Open-Access Forecasting System of the Health Effects of Air PollutionFORECAST-AIR aims to develop innovative health early warning systems for air pollution by integrating forecasting, epidemiology, and vulnerability analysis to improve public health alerts. | ERC Proof of... | € 150.000 | 2024 | Details |
Hybrid dry–hot Extremes prediction and AdapTationThe HEAT project aims to enhance subseasonal forecasting of droughts and heatwaves using a hybrid AI-physics model to improve preparedness for heat stress and inform land adaptation strategies. | ERC Consolid... | € 1.983.000 | 2023 | Details |
Data Aware efficient models of the urbaN microclimaTEDANTE aims to develop fast, reliable urban microclimate simulation methods using machine learning and model order reduction to support sustainable city planning by 2050. | ERC Starting... | € 1.450.560 | 2024 | Details |
Advancing Subseasonal PredIctions at Reduced computational EffortASPIRE aims to enhance subseasonal weather predictions by leveraging tropical convective variability and machine learning to reduce computational costs while improving forecast accuracy. | ERC Starting... | € 1.496.246 | 2023 | Details |
DeepLearning 2.0: Meta-Learning Qualitatively New ComponentsDevelop meta-learning methods to create customized deep learning pipelines that enhance accuracy, reduce training time, and improve usability across various applications. | ERC Consolid... | € 2.000.000 | 2022 | Details |
Open-Access Forecasting System of the Health Effects of Air Pollution
FORECAST-AIR aims to develop innovative health early warning systems for air pollution by integrating forecasting, epidemiology, and vulnerability analysis to improve public health alerts.
Hybrid dry–hot Extremes prediction and AdapTation
The HEAT project aims to enhance subseasonal forecasting of droughts and heatwaves using a hybrid AI-physics model to improve preparedness for heat stress and inform land adaptation strategies.
Data Aware efficient models of the urbaN microclimaTE
DANTE aims to develop fast, reliable urban microclimate simulation methods using machine learning and model order reduction to support sustainable city planning by 2050.
Advancing Subseasonal PredIctions at Reduced computational Effort
ASPIRE aims to enhance subseasonal weather predictions by leveraging tropical convective variability and machine learning to reduce computational costs while improving forecast accuracy.
DeepLearning 2.0: Meta-Learning Qualitatively New Components
Develop meta-learning methods to create customized deep learning pipelines that enhance accuracy, reduce training time, and improve usability across various applications.
Vergelijkbare projecten uit andere regelingen
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
CaeliHet project onderzoekt de haalbaarheid van een AI-systeem voor het real-time voorspellen van klimatologische rampen en hun economische impact op overheid, gemeenten, burgers en verzekeraars. | Mkb-innovati... | € 20.000 | 2020 | Details |
TRaffic model for better Air Quality policies in citiesCityTRAQ aims to improve air quality in Flanders by integrating data, engaging communities, and providing policy tools to optimize local interventions and enhance traffic management. | LIFE Standar... | € 1.258.598 | 2022 | Details |
Serious and escape games in virtual reality to improve the capacity of decision makers and citizens for the implementation of air quality plans and actionsThe LIFE V-Air project aims to enhance air quality awareness and decision-making through gamification and VR tools, engaging citizens and policymakers to visualize impacts and drive effective actions. | LIFE Standar... | € 754.479 | 2022 | Details |
Semi-supervised learning voor dynamische geluidkaart in gebouwde omgevingMuniSense, Peutz en Embedded Acoustics ontwikkelen een dynamische geluidskaart met AI, gericht op geluidsmonitoring in de gebouwde omgeving, met nadruk op betrouwbare, mensgerichte participatie. | Mkb-innovati... | € 285.180 | 2022 | Details |
Water quality control and predictionPureAqua BV ontwikkelt een online platform dat externe sensoren koppelt voor realtime monitoring van waterkwaliteit en voorspelling van filteronderhoud. | Mkb-innovati... | € 20.000 | 2022 | Details |
Caeli
Het project onderzoekt de haalbaarheid van een AI-systeem voor het real-time voorspellen van klimatologische rampen en hun economische impact op overheid, gemeenten, burgers en verzekeraars.
TRaffic model for better Air Quality policies in cities
CityTRAQ aims to improve air quality in Flanders by integrating data, engaging communities, and providing policy tools to optimize local interventions and enhance traffic management.
Serious and escape games in virtual reality to improve the capacity of decision makers and citizens for the implementation of air quality plans and actions
The LIFE V-Air project aims to enhance air quality awareness and decision-making through gamification and VR tools, engaging citizens and policymakers to visualize impacts and drive effective actions.
Semi-supervised learning voor dynamische geluidkaart in gebouwde omgeving
MuniSense, Peutz en Embedded Acoustics ontwikkelen een dynamische geluidskaart met AI, gericht op geluidsmonitoring in de gebouwde omgeving, met nadruk op betrouwbare, mensgerichte participatie.
Water quality control and prediction
PureAqua BV ontwikkelt een online platform dat externe sensoren koppelt voor realtime monitoring van waterkwaliteit en voorspelling van filteronderhoud.