Global Monitoring of Tropospheric Pollution from Geostationary Orbit Kelly Chance Harvard-Smithsonian Center for Astrophysics

June 1, 2001AGU Spring Meeting2 Xiong Liu NASA/UMBC Thomas Kurosu Harvard-Smithsonian Center for Astrophysics The GeoTRACE Team: Jack Fishman, Doreen Neil, James Crawford (NASA); David Edwards (NCAR); Kelly Chance, Thomas Kurosu (Harvard-Smithsonian Center for Astrophysics); Xiong Liu (NASA/UMBC); R. Bradley Pierce (NOAA); Gary Foley, Rich Scheffe (EPA) Collaborators

June 1, 2001AGU Spring Meeting3 Outline Introduction and motivationIntroduction and motivation -NRC Decadal Survey: GeoCAPE Mission Determination of measurement requirementsDetermination of measurement requirements -UV/visible gases discussed here -Gas concentrations -Geophysical, spatial, and temporal requirements Scalable strawmanScalable strawman Future work – The two outstanding requirementsFuture work – The two outstanding requirements

June 1, 2001AGU Spring Meeting4 Introduction and Motivation Target tropospheric gases are O 3, NO 2, SO 2, HCHO, CHO-CHO (plus CO and O 3 in IR, plus aerosols, not discussed here). The aims are: 1.To retrieve tropospheric gases from geostationary orbit at high spatial and temporal resolution. 2.To integrate the results into air quality prediction, monitoring, and modeling, and climatological studies. Experience from previous satellites: Scientific and operational measurements of O 3, NO 2, SO 2, HCHO, and CHOCHO (and BrO, IO, OClO, H 2 O).Experience from previous satellites: Scientific and operational measurements of O 3, NO 2, SO 2, HCHO, and CHOCHO (and BrO, IO, OClO, H 2 O).

Requires precise (dynamic) wavelength (and often slit function) calibration, Ring effect correction, undersampling correction, and proper choices of reference spectra (HITRAN!)Requires precise (dynamic) wavelength (and often slit function) calibration, Ring effect correction, undersampling correction, and proper choices of reference spectra (HITRAN!) Remaining developments:Remaining developments: 1.Tuning PBL O 3 from UV/IR combination (demonstrated for the OMI/TES combination by SAO/UMBC + JPL) 2.Tuning direct GOME/SCIAMACHY PBL SO 2 from optimal estimation SAO/UMBC/U. Toronto) Fitting trace species

MoleculeVertical column (cm -2 ) Sensitivity Driver O3O3 2.4  ~10 ppbv in PBL; reality (profiling) more complicated NO  Distinguish clean from moderately polluted scenes SO  Distinguish structures for anthropogenic sources HCHO1.0  Distinguish clean from moderately polluted scenes CHOCHO1.0  Tracking of most urban diurnal variation Required Concentrations* * In PBL. Determined from our satellite measurements. (Future: traceability from AQ requirements and modeling)

Example: OMI Tropospheric NO 2 (July 2005)

Geostationary Minimal Case: Scalable Strawman o - 50 o N, 60 o o W (parked at 0 o N, 95 o W) Measure solar zenith angles from 0 o – 70 o

Radiative Transfer Modeling and Fitting Studies Note cloud windows: Use of Raman scattering and of the oxygen collision complex. O 2 A band

MoleculeFitting window (nm) Vertical column (cm -2 ) Slant column (cm -2 ) O3O   NO   SO   HCHO   CHOCHO   Measurement Requirements To Meet Required Concentrations The slant column measurement requirements come from full multiple scattering calculations, including gas loading, aerosols, and the GOME-derived (Koelemeijer et al., 2003) albedo database, and assume a 1 km boundary layer height.

Scalable Strawman - 2 Lat/lon limits are ~3892 km N/S and km E/W (6565 average), or about 390   10 km 2 footprints. –Measure 400 spectra N/S in two 200-spectrum integrations (each on two detector arrays – 1 UV and 1 visible). –2.5 seconds per longitude (2  1 s integration, 0.5 s step and flyback)  total sampling every < ½ hour (27 min). Detectors: Rockwell HyViSi TCM8050A CMOS/Si PIN –3  10 6 e - well depth; will need several rows (or readouts) per spectrum to reach the necessary statistical noise levels. –Complicated by brightness issues; can’t always have full wells.

Scalable Strawman spectra on each of two arrays; each spectrum uses 4 detector rows (800 total out of 1024). –Channel 1: nm sample, 0.36 nm resolution (FWHM). –Channel 2: nm sample, 0.4 nm resolution (FWHM); includes O 2 -O 477 nm. –Nyquist sampled: 4 samples per FWHM virtually eliminates undersampling for a symmetric instrument transfer (slit) function [Chance et al., 2005]. Pointing to 1 km = 1/35,800 = 6 arc second (easy). Size optics to fill sufficiently in 1 second (  1 cm 2 (GOME size)  √1.5 (GOME integration time)  35,800 km / 800 km = 55 cm “telescope” optics). More realistically ….

Mol  Rad  cm -2 px -1 RMS  px -1 a  Eff O3O     NO     SO     HCHO5.65     CHOCHO6.22     Sizing for 10  10 km 2 Footprint, 1 Second Integration Time  Rad  : Minimum clear-sky radiance, cross-section weighted (photons s -1 nm -1 sr -1 cm -2 )  cm -2 px -1 : # photons cm -2 pixel instrument in 1 second; 10  10 km 2  7.80  sr solid angle RMS: Fitting RMS required for the minimum detectable amount = 1 / required S/N  px -1 : # photons pixel -1 needed in 1 second to meet RMS-S/N requirements; includes factor of 4 for 4 detectors rows per spectrum a  Eff: Telescope collecting area (cm 2 )  overall optical efficiency

Mol  Rad  cm -2 px -1 RMSn  /4a  Eff O3O     NO     SO     HCHO5.65     CHOCHO6.22     Sizing for 10  10 km 2 Footprint, 1 Second Integration Time Formaldehyde (HCHO) is the driver for almost any conceivable choice of requirements! (Unless VOCs are considered unimportant, in which case O 3 would be the driver, with the above as a low estimate) cm 2 is a16-cm diameter 10% optical efficiency (GOME, a much simpler instrument, is 15 – 20% efficient in this wavelength range). Also, IR needs (CO, O 3 ) plus aerosols must be addressed.

Major Tradeoffs and Questions Tradeoffs: # samples (footprint) vs. sensitivity (S/N) vs. integration time vs. geographical coverage vs. max SZA: –5  5 km 2 footprints in 1/2 hour with a 32 cm diameter telescope, if the instrument is 10% efficient. Questions: Are lat and lon sampling necessarily the same? Is constant sampling necessary? Option: MODIS channels for aerosols? (TOMS absorbing aerosol index is automatic, but little else operationally.) –OMI aerosol products should be reviewed. –Should include polarization-resolved measurements; –Several such UV channels will improve PBL O 3 [Hasekamp and Landgraf, 2002a,b; Jiang et al., 2003]. Everything is debatable; this is why it is a strawman, but we must show why alternatives are better.

Outstanding Needs 1.Science Requirements (S/N, geophysical, spatial, temporal) from sensitivity and modeling studies (OSSEs), providing traceability for AQ forecast improvement and other uses. –Unless things change a lot, HCHO will be the driver for instrument requirements. Then address trade space. 2.Instrument Design. Reducing “smile”, enabling multiple readouts, increasing efficiency, optimizing ITF shape …. –GEO instrument is not just a super-OMI with CMOS/Si detectors instead of CCDs. Minimal geostationary requirements imply scanning instead of a pushbroom and they imply getting many more spectra onto a rectangular detector than OMI has obtained. –Instrument optical and spectrograph design is the single most important outstanding issue in demon- strating the feasibility of geostationary pollution measurements.

The End!