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

Ozone instruments Chemical cell: 2H + + 2I - + O 3  I 2 + O 2 + H 2 O 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 + O 3 + H 2 O  I 2 + O 2 + 2KOH. The iodine is converted to 2I - at the Pt cathode (and 2I - are converted to I 2 at the anode) producing an electrical current, which is then measured.

Ozone instruments O 3 absorption cross section ~ 1.2· cm 2 at 258 nm UV absorption

Ozone instruments chemoluminescence spectrum O 3 + C 2 H 4  HCHO* + other HCHO*  HCHO + h Chemoluminescence

NO x instruments Chemoluminescence NO + O 3  NO 2 * + O 2 + other NO 2 *  NO 2 + h Photolytic converter In order to measure NO 2, a photolytic converter is used in front of the CLD to convert NO 2 to NO

HO x instruments LIF (laser induced fluorescence) Radical converter In order to measure HO 2, a gas flow of NO is added to the sample so that HO 2 +NO  OH+NO 2

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

Sample gas chromatogram

CO, CO 2 instruments Gas correlation radiometer c proportional to ln(I/I 0 )

spectroscopy instruments DOAS (differential optical absorption spectroscopy) 1 2 I1I1 I2I2

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

FTIR spectrum

spectroscopy instruments TDLS (tuneable diode laser spectroscopy)

space instruments nadir viewlimb view (solar) occultation

GOME and SCIAMACHY

space borne DOAS courtesy T. Wagner, IUP Heidelberg

Pixel resolution of tropospheric satellite measurements GOME SCIA OMI courtesy T. Wagner, IUP Heidelberg

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

Tropospheric NO 2 retrieval from GOME courtesy T. Wagner, IUP Heidelberg

Tropospheric NO 2 retrieval from GOME courtesy T. Wagner, IUP Heidelberg

Weekly NO 2 cycle courtesy S. Beirle, IUP Heidelberg

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

Uncertainty and random error measured distributiontrue value bias precision

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)

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.

Error Propagation To keep it simple:

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, Finnlayson-Pitts and Pitts, Chemical ozone cell description from Error analysis: NCAR Advanced study programme course /