Geostatistics for Air Quality Modeling
A one-day seminar to understand the fundamental concepts of geostatistics, its added value for classical air pollution issues
The seminar aims at presenting the fundamental concepts of geostatistics and its added value for classical air pollution issues. Real applications are provided to illustrate the concepts.
Who should attend
The seminar is designed for scientists involved in air quality monitoring and requiring a practical introduction to geostatistics for data analysis, interpolation and risk assessment.
No prior knowledge of geostatistics is required.
- Introduction: what is geostatistics? The integration of geostatistics in air quality monitoring workflows is presented. Introductive example of a typical air quality project.
- The foundation stone of geostatistics: characterization of the pollutant’s spatial continuity through the variogram analysis.
- Interpolating between data: kriging in practice. Quantification of the interpolation uncertainty with the kriging variance.
- Multivariate geostatistics, cokriging and data assimilation: refining the pollutant map using auxiliary data (correlated pollutants, meteorology, topography, soil occupation, traffic density, industrial emissions, numerical models).
- Risk analysis: Computing the probability of exceeding a pollutant threshold over a given period (day, week, year). Estimation of the population exposure to concentrations exceeding regulatory thresholds.
- Time will be available for discussion about air quality projects achieved by the participants.