Outline

1. Satellite based versus traditional air pollution monitoring: Requirements, limitations, and chancesDominik Brunner, Christoph Hueglin, Christoph Zellweger, and Brigitte BuchmannEmpa, Swiss Federal Laboratories for Materials Testing and Research Laboratory for Air Pollution and Environmental Technology8600 Dübendorf, Switzerland

2. Outline • Traditional air pollution monitoring • Network concepts, regulations • Design and applications of Swiss National AirPollution Monitoring Network NABEL • Satellites for air pollution monitoring? • Sufficient spatial resolution? • Sufficiently accurate? • How limiting is restriction to clear sky overpasses? • Analysis of hourly NABEL observations for clear and all skies • Comparison of frequency distributions, diurnal cycles, and interannual variability under clear and all skies • Conclusions Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions

3. Traditional air pollution monitoring Monitoring networks Purpose: • Representative measurement of concentrations of all major (regulated) air pollutants relevant for human health, agriculture, ecosystems, and material degradation • Characterize existing and identify new potential threats • Monitor current pollution levels and long-term trends • Support for decision makers (warnings, control of success of air quality policy (short and long-term reduction measures) Requirements • Should cover full range of pollution levels from street level (human health) to remote locations (ecosystems) • Should represent the different regions of a country or region,e.g. north and south of the Alps, different altitude levels • Use reference measurement techniques, traceable toreference standards • High accuracy across network needed for reliable trend estimates and intercomparability • Reliable and simple continuous operation • Near real-time data availability Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions

4. Swiss Air Pollution Monitoring Network (NABEL) Lägeren Tänikon Basel Dübendorf Zürich Härkingen Chaumont Rigi Bern Payerne Davos Lausanne Jungfraujoch Magadino Sion 50km Lugano N Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions Urban, near street Rural < 1000 m amsl Urban, in park Rural > 1000 m amsl Motorway Prealpine, forest Agglomeration Alpine Air Pollution/Environmental Technology

5. NABEL Measurement Programme Air Pollution & Climate Change GAW Pollutants with limit value in the Swiss ordinance PM (PM10, PM2.5, PM1) mass, EC/OC, size distribution Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions Greenhouse gases (CH4, N2O, halocarbons, SF6), VOCs Nitrogen Compouds (NH3, NH4+, N2O, HNO3) EMEP / EU Auxiliary Parameters: Meteo (p, T, RH, radiation, wind) Traffic parameter

6. Swiss Air Pollution Monitoring Network (NABEL) Application: Characterization of air pollution based on NABEL sites NABEL: annual mean values 2004

7. Swiss Air Pollution Monitoring Network (NABEL) Application: Monitoring of long-term trends, e.g. PM10 (annual means) annual limit values Switzerland 20 EU 2005 40 WHO, EU 2010 20 Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions Limit value

8. Swiss Air Pollution Monitoring Network (NABEL) Emissionsper country Annual meanconcentrationsat urban stationsand Jungfraujoch Application: Independent control for emission reportingCountry-by-country emissions reported to EMEP versus time evolution of observed concentrations Nitrogen oxides (NOx) All values normalized to 1997 Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions

9. OMI (launch 2004) up to 24  13 km2 SCIAMACHY (launch 2002) 60  40 km2 Dispersion model Grid size 400  400 m2 GOME (launch 1995) 320  40 km2 Jan 2006 – July 2007 mean PhD Y. Zhou Air pollution monitoring from satellites? Sufficient spatial resolution? Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions PhD D. Schaub Schaub, D. et al., Atmos. Chem. Phys.5, 23-37, 2005 Schaub, D. et al., Atmos. Chem. Phys.6, 3211-3229, 2006 Schaub, D. et al., Atmos. Chem. Phys. 7(23): 5971-5987, 2007

10. Air pollution monitoring from satellites? OMI NO2 VTCs vs. ground-based NO2 VTCs Sufficiently accurate? Ground-based columns using averaging kernel information (see Schaub et al., 2006) Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions All data points: r = 0.82 Precision of better than 1 x 1015 molec cm-3 highly desired

11. mean values 95% percentiles Limitations of clear-sky observations1. Frequency distributions of hourly means Bern, urban kerbside Zurich, urban background Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions Payerne, rural Annual mean limit Significant undersampling of polluted situations if restricted to clear-sky observations at urban background and rural sites

12. 13 hrs 11 hrs Limitations of clear-sky observations2. Annual average diurnal cycles Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions All observations daytime only daytime clear sky only - Evening traffic peak is missed during most time of the year ifrestricted to daytime observations - Surface level NO2 is increasedin the morning and decreasedin the evening on clear-sky days

13. Limitations of clear-sky observations3. Interannual variability of annual means Daytime clear sky only All observations Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions OMI clear sky overpasses only • Annual mean values are significantly reduced if restrictedto OMI clear sky overpasses • But: interannual variabilityreasonably well captured Annual mean limit

14. Limitations of clear-sky observations3. Interannual variability Correlations between annual means/percentiles of subsamples and full annual means 95% percentiles Annual means Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions All stations urban rural • - About 70% of variance in annual means captured with clear sky sampling • Reduced to 60% if restricted to OMI overpasses • Still 50-60% of variability in extremes captured

15. Conclusions for TROPOMI mission • Air quality monitoring requires high spatial resolution (exposures, critical loads) • Reliable long-term trends important for policy control-> continuity in satellite missions required-> large resolution and design changes from instrument to instrument causes some problems • Comparison with in-situ observations quite satisfactory • precision of better than 1 x 1015 molec/cm3 NO2 highly desired • Clear-sky observations is a significant limitation for extremes(in Switzerland) but less so for interannual and long-term variations. • Good boundary layer scheme mandatory for a-priori NO2 profiles • Spatially resolved reliable long-term trends is probably themost exciting (air quality) product from satellites so far • Models add a lot to the value of satellite missions Outline Traditionalmonitoring Air pollutionmonitoringusingsatellites? Limitationsof clear-skyoverpasses Conclusions