CAMS-downstream – Development of a LQ-WARN-App
The objective is to provide pilot provision of air quality information for Germany to citizens and decision-makers based on downscaled CAMS data (as a downstream service).
In order to predict air pollution concentration over Germany and especially periods of high pollution concentrations and exceedance of limit values, governmental institutions have great interest in authoritative air quality forecasts with high spatial and temporally resolutions.
So far, atmospheric chemistry transport models (CTM), as for instance offered by the Copernicus Atmosphere Monitoring Service (CAMS), already provide comprehensive operational predictions for a multitude of air quality parameters. Nevertheless, atmospheric chemistry models have systematic errors, as well as limited spatial resolution. This is due to the fact that the emission component is highly influenced by meteorological conditions and local factors. The CAMS model ensemble provides an air quality prediction for Europe with a spatial resolution of around 15x15 km², which is a good basis for downstream services. In order to improve the air quality forecast for a specific area, the pollutant forecast by CAMS might be used as boundary conditions for a higher spatial resolution simulation with CTMs. With such a model setup the spatial resolution of the air quality forecast might be increased to around 5x5km² for a specific area in a computational very efficient way. By using adjusted emissions based on meteorological conditions, such a downstream service might be further improved. Another way for significantly improving air quality forecasts is the Model Output Statistics (MOS), which combines all factors that influence air quality on local level. MOS can be applied either directly on the output of the CAMS model ensemble or on a downstream simulation.
The products to be developed in the LQ-WARN project are intended to inform citizens and to support public authorities on a daily (hourly) basis, as periods of high pollutant concentrations can be detected at an early stage and broaden the basis of information for political decision-making.
As part of LQ-WARN, an automated system will be developed that offers an improved prediction of various air quality parameters such as fine dust (PM10, PM2.5), nitrogen dioxide (NO2) and ozone (O3). Data and products provided by LQ-WARN are based on ground-based in-situ data combined with the output of the CAMS model ensemble or with the results of downstream CTM simulation by using the MOS methodology. LQ-WARN will be an essential national contribution to the CAMS downstream activities.
LQ-WARN will pilot:
- Hourly updated, location-specific forecasts of at least four air quality parameters (PM10, PM2.5, NO2, O3, later expandable) for a variety of locations with current air quality measurement stations up to four days in advance
- Area-covering, statistically optimized and interpolated air quality forecasts for the whole of Germany
- Location-specific exceedance probabilities of limit values as a scientific basis for air quality warnings
The developed interface to CAMS will be an essential element of phase 1 and 2 of the UBA schedule. UBA will test and implement the interface.
Outputs and Results
By the end of the project the LQ-WARN-app will be provided and published on the German Copernicus website (www.d-copernicus.de). Thus, this action is a development and piloting action (Type 3 in the Action Plan). The operation of this service is beyond the scope of this action. The app will be free of charge.
All LQ-WARN products can directly be used by governmental institutions to publish near real-time warnings of high air pollutant concentrations. All products developed within LQ-WARN can directly be transferred into operational mode.