Anthony Ung

Forecasting Urban Air Quality over Cities by Statistical Adaptation of Deterministic Chemistry Transport Model Outputs

Within the European CITEAIR II project, deterministic and statistical forecasting approaches are combined to forecast an air quality index in European cities. The idea is to benefit both from chemistry-transport modelling, which provides large scale information about the evolution of photo-oxidizing pollution, and from local measurements of pollution levels. In addition to usual predictors, numerical outputs from the PREV’AIR system are used in multiple linear regression to forecast O3, NO2 and PM10 concentrations at urban stations and derive the city-level forecast index. The methodology was applied to Rotterdam, Sevilla and Prague with 2008 data set and validated against 2009 one. It can be extended to any European city involved in CITEAIR II, in particular to those having not implemented their own forecasting system yet.

Ensemble Data Assimilation for Tropospheric Ozone Analysis Within the CHIMERE Regional Chemistry Transport Model

The data assimilation method Ensemble Kalman Filtering has been used with the Chimere-model for tropospheric ozone over Europe and the results are presented and discussed.

A Statistical Approach to Improve Air Quality Forecasts in the PREV’AIR System

Since 2003, the national PREV’AIR system (www.prevair.org) has been delivering daily air quality forecasts of atmospheric pollutants (O3, NO2, PM10, PM2.5) over Europe and France. Those products are based on chemistry-transport modeling and in particular on the outputs from CHIMERE model. Analysed air quality maps of the previous day are also produced by mixing observed and simulated data through a geostatistical approach.