Measurement techniques and data analysis

1. Measurement techniques and data analysis Instrument descriptions Space instruments What does a data set tell us?

3. Ozone instruments Chemical cell: 2H+ + 2I- + O3 I2 + O2 + H2O Variant: ECC ozone sondes Electromagnetic force derived from KI solution in two different concentrations (0.06 Mol/l and >8 Mol/K). Ozone flows through cell with lower conc. and releases free iodine according to 2KI + O3 + H2O  I2 + O2 + 2KOH. The iodine is converted to 2I- at the Pt cathode (and 2I- are converted to I2 at the anode) producing an electrical current, which is then measured.

4. Ozone instruments UV absorption O3 absorption cross section ~ 1.2·10-18 cm2 at 258 nm

5. Ozone instruments Chemoluminescence O3 + C2H4 HCHO* + other HCHO*  HCHO + hn chemoluminescence spectrum

6. NOx instruments Chemoluminescence NO + O3 NO2* + O2 + other NO2*  NO2 + hn Photolytic converter In order to measure NO2, a photolytic converter is used in front of the CLD to convert NO2 to NO

7. HOx instruments LIF (laser induced fluorescence) Radical converter In order to measure HO2, a gas flow of NO is added to the sample so that HO2+NO  OH+NO2

8. Hydrocarbon instruments Gas chromatography For most gases, a cryogenic preconcentration is required

9. Sample gas chromatogram

10. CO, CO2 instruments Gas correlation radiometer c proportional to ln(I/I0)

11. spectroscopy instruments DOAS (differential optical absorption spectroscopy) I1 I2 l1 l2

12. spectroscopy instruments FTIR (fourier transform infrered spectroscopy) fixed mirror beam splitter moving mirror detector

13. FTIR spectrum

14. spectroscopy instruments TDLS (tuneable diode laser spectroscopy)

15. space instruments nadir view limb view (solar) occultation

16. GOME and SCIAMACHY

17. space borne DOAS courtesy T. Wagner, IUP Heidelberg

18. GOME SCIA OMI Pixel resolution of tropospheric satellite measurements 1996-2003 2002- 2005- courtesy T. Wagner, IUP Heidelberg

19. Dependence of GOME measurements on zenith angle and surface albedo courtesy T. Wagner, IUP Heidelberg

20. Tropospheric NO2 retrieval from GOME courtesy T. Wagner, IUP Heidelberg

21. Tropospheric NO2 retrieval from GOME courtesy T. Wagner, IUP Heidelberg

22. Weekly NO2 cycle courtesy S. Beirle, IUP Heidelberg

23. Measurement uncertainty • distinction between uncertainty (aka „accuracy“) and random error (aka „precision“) • calibration bias • digitization noise, counting statistics • error propagation

24. Uncertainty and random error true value measured distribution precision bias

25. Calibration bias Frequent sources of error: • offset problems • uncertainty of reference value • non-linearity of response curve • conditions differing from ambient measurement • instrument drift (e.g. temperature shifts)

26. Counting statistics Several instruments detect their signal by counting photons (e.g. chemoluminescence detector). Obviously, the precision of such a measurement becomes better if the number of photons (the statistical sample) increases. The population standard deviation is given by: One effect of this is the lower limit of detection (LOD) achieved by averaging signals over longer time scales.

27. Error Propagation To keep it simple:

28. Bibliography Material for this lecture comes mostly from • Brasseur, G.P., Orlando, J.J., and Tyndall, G.S., Atmospheric Chemkistry and Global Change, Oxford University Press, Oxford, New York, 1999. • Finnlayson-Pitts and Pitts, 1986. • Chemical ozone cell description fromhttp://www.fz-juelich.de/icg/icg-ii/josie/ozone_sondes/ • Error analysis: NCAR Advanced study programme course 1992 http://www.asp.ucar.edu/colloquium/1992/notes/