Regional Air Quality and Climate Regional Air Quality and Climate from Space – A reality?from Space – A reality?

Paul Monks & John RemediosPaul Monks & John Remedios

Space Research CentreSpace Research Centre

•In the UK, 2000 excess deaths during heatwave

•700 may have been attributable to high levels of ozone and PM10

•20-40% of all excess U.K. deaths in that period.

UK Ozone Bubble – 2pm 6UK Ozone Bubble – 2pm 6thth August 2003 August 2003

2003 summer 2003 summer heatwave heatwave

Over Europe estimates are between 22,000 and

44,000 excess deaths

100x10-12

80

60

40

20

0

HO

2+

RO

2 p

arts

00:0006/08/2003

06:00 12:00 18:00

Time of Day

250

200

150

100

50

140

120

100

80

60

40

20

ozon

e, N

O a

nd N

O2

ppb

v

806040200x10

3

ro2_min_avg_corr JO1D J218ozone J218no2 J218no

UK AQ HIGH BAND FOR OZONEUK AQ HIGH BAND FOR OZONE

2006 heat wave2006 heat wave

In situIn situ

Ground based Ground based remote sensingremote sensing

SatelliteSatellitess

Monitoring station

Distance from road (m)

Sampling height (m)

1 Abbey Lane 8 1.8

2 Basset Street 12 1.3

3 Glenhills Way 3 2

4 Imperial Avenue

7.5 1.75

5 Melton Road 3 2

6 Uppingham Road

2 1.8

7 Vaughan Way 6.5 2.6

8 St Matthews Way

2 1.7

9 AUN 35 ?

In Situ MonitorsIn Situ Monitors

1

2

3

4

5

6

78

9

CMAX-DOAS

Run by Leicester City Council - Run by Leicester City Council - Hourly averaged NOHourly averaged NO22 concentrations (ppb).concentrations (ppb).

MET . Station

2 km

55oo

1010oo1515oo

9090oo

Coated GlassCoated Glass

22oo

Plano -Plano -convex lensconvex lens

Fibre-optic to Fibre-optic to SpectrometerSpectrometer

CMAX-DOASCMAX-DOAS

Correlation Coeff: 0.460.39

Corr. coeff = 0.53

• All city centre monitoring All city centre monitoring stations show similar diurnal stations show similar diurnal variation. variation.

• Stations situated close to the Stations situated close to the roadside are influenced by roadside are influenced by traffic.traffic.

• Mean average and variability Mean average and variability of NOof NO22 from monitoring from monitoring stations calculated.stations calculated.

In situIn situ

Ground based Ground based remote sensingremote sensing

SatelliteSatellitess

OMIOMI• The Ozone Monitoring Instrument (OMI) was launched onboard the The Ozone Monitoring Instrument (OMI) was launched onboard the

NASA EOS Aura satellite in July 2004.NASA EOS Aura satellite in July 2004.

• OMI is a Nadir viewing spectrometer that measures in the spectral OMI is a Nadir viewing spectrometer that measures in the spectral range between 270 and 500 nm.range between 270 and 500 nm.

• Has a spectral resolution of 0.52 and 0.45 nm in the UV-1 and UV-2 Has a spectral resolution of 0.52 and 0.45 nm in the UV-1 and UV-2 channels and 0.63 nm in the visible channel. channels and 0.63 nm in the visible channel.

• OMI has a large swath width of OMI has a large swath width of 2600 km, to obtain this 2600 km, to obtain this viewing swath the viewing viewing swath the viewing angle is angle is 114°114°

• In the normal operation mode, In the normal operation mode, the OMI pixel size is 13 x 24 the OMI pixel size is 13 x 24 kmkm22 making it suitable for making it suitable for comparisons with comparisons with measurements on an urban measurements on an urban scale.scale.

Mean average and Mean average and variability of NOvariability of NO2 2

from all monitoring from all monitoring stations in stations in Leicester.Leicester.

NS(NONS(NO22))TotalTotal = NS(NO = NS(NO22))LeicLeic--NS(NONS(NO22))bkgbkg

Correlation between OMI NOCorrelation between OMI NO22 concentration in the PBL and the mean near-surface concentration in the PBL and the mean near-surface NONO22 concentrations across the OMI sampling area, for January 2005 to December concentrations across the OMI sampling area, for January 2005 to December 2006. The different symbols represent the seasons, autumn 2006. The different symbols represent the seasons, autumn (black circles),(black circles), winter winter (green stars),(green stars), spring spring (red triangles)(red triangles) and summer and summer (blue crosses).(blue crosses).

R=0.60-0.83 (green =0.04)

For each day of the For each day of the week the mean is week the mean is calculated and calculated and normalised to the normalised to the median weekly median weekly value. value.

A weekly cycle is A weekly cycle is evident with 20-30% evident with 20-30% lower NOlower NO2 2 vertical vertical column densities column densities observed on Sunday observed on Sunday and a 10 % reduction and a 10 % reduction on a Saturday. on a Saturday.

Weekly cycleWeekly cycle

ConclusionsConclusions

• Space-based observations have a role to play as part of a Space-based observations have a role to play as part of a system for air quality.system for air quality.

• Provide a synoptic view not available from ground-based Provide a synoptic view not available from ground-based systemssystems

• Need for greater temporal coverageNeed for greater temporal coverage

• Need to be careful in linking different observing systems Need to be careful in linking different observing systems together. together.

Considerations include spatial structure, site Considerations include spatial structure, site characteristics of in situ stations, timing of characteristics of in situ stations, timing of measurements.measurements.

AcknowledgementsAcknowledgements

Thanks to the following:Thanks to the following:• John RemediosJohn Remedios• James LawrenceJames Lawrence• Leicester City Council:Leicester City Council:

Evan Davies Evan Davies

Paul HodgesPaul Hodges• OMI validation teamOMI validation team• NERCNERC

If you would like more information:If you would like more information:Leigh, R. J., G. K. Corlett, U. Frieß, and P. S. Monks (2006), A Concurrent Multi-Leigh, R. J., G. K. Corlett, U. Frieß, and P. S. Monks (2006), A Concurrent Multi-Axis Differential Optical Absorption Spectroscopy system for the Measurement of Axis Differential Optical Absorption Spectroscopy system for the Measurement of Tropospheric Nitrogen Dioxide., Appl. Opt. , 45, 7504-7518. Tropospheric Nitrogen Dioxide., Appl. Opt. , 45, 7504-7518. Louisa J. Kramer, Roland J. Leigh, John J. Remedios and Paul S. Monks (2008), Louisa J. Kramer, Roland J. Leigh, John J. Remedios and Paul S. Monks (2008), Comparison of OMI and ground based Comparison of OMI and ground based in-situin-situ and MAX-DOAS measurements of and MAX-DOAS measurements of tropospheric nitrogen dioxide in an urban area, In press tropospheric nitrogen dioxide in an urban area, In press J.Geophys.Res.J.Geophys.Res.

The Compact Air Quality SpectrometerBreadboard demonstrator constructed and under testing as part of CEOI phase 1

Novel spectrometer designed by SSTL for space borne UV/VIS spectroscopy

Performance

• Single Channel – 300 - 450nm• Spectral resolution – 0.6 nm FWHM. • Resolution from LEO – 5x5km sub-satellite. • Full Payload Mass – 20kg• Full Payload Power – 30W• Full Payload Volume - 30 x 20 x 20 cm. • High spatial resolution available from LEO in a compact

package. • Coverage and temporal components offered by constellation

Carbon DioxideCarbon Dioxide

Can we monitor the Can we monitor the Carbon Budget from Carbon Budget from

Space?Space?

SCIAMACHY/FSI COSCIAMACHY/FSI CO22 - July 2003 - July 2003

SCIAMACHY/FSI COSCIAMACHY/FSI CO22 - October 2003 - October 2003

The FSI algorithm: OverviewThe FSI algorithm: Overview

• How do we measure atmospheric COHow do we measure atmospheric CO22??– WFM-DOAS retrieval technique (Buchwitz WFM-DOAS retrieval technique (Buchwitz

et al., JGR, 2000) designed to retrieve the et al., JGR, 2000) designed to retrieve the total columns of CHtotal columns of CH44,CO, CO,CO, CO22, H, H22O and O and NN22O from spectral measurements in NIR O from spectral measurements in NIR made by SCIAMACHYmade by SCIAMACHY

• Least squares fit of model spectrum Least squares fit of model spectrum + ‘weighting functions’ to observed + ‘weighting functions’ to observed sun-normalised radiancesun-normalised radiance

– We use WFM-DOAS to derive COWe use WFM-DOAS to derive CO22 total total columns from absorption at ~1.56 columns from absorption at ~1.56 μμmm

• Key difference to Buchwitz’s approach:Key difference to Buchwitz’s approach:– No look-up table No look-up table – Calculate a reference spectrum for every Calculate a reference spectrum for every

single SCIAMACHY observation i.e. to single SCIAMACHY observation i.e. to obtain ‘best’ linearization point – no obtain ‘best’ linearization point – no iterationsiterations

• See “Measuring atmospheric COSee “Measuring atmospheric CO22 using Full Spectral Initiation (FSI) using Full Spectral Initiation (FSI) WFM-DOAS” , WFM-DOAS” , Barkley et al., ACP, 6, 3517-Barkley et al., ACP, 6, 3517-35343534 ,2006,2006

– Computationally expensive Computationally expensive – Increased accuracy Increased accuracy

SCIAMACHY, on ENVISAT, is a passive hyper-spectral grating spectrometer covering in 8 channels the spectral range 240-2040 nm at a resolution of 0.2-1.4 nm

Typical pixel size = 60 x 30 km2

SCIAMACHYSCIAMACHY

SCIATRAN(Courtesy of IUP/IFE Bremen)

LBL mode, HITRAN 2004

CalibrationNon-linearity, dark current, ppg & etlaon

SCIAMACHY Spectrum

(I/I0)

Reference Spectrum + weighting

functions(CO2, H2O and temperature)

CO2 Column(Normalise with ECMWF Surface Pressure)

Accept only: Errors <5%, Range:340-400 ppmv

Raw Spectra

WFM-DOAS fit

I - Calibrated Spectra

I0 – Frerick (ESA)

‘A priori’ DataCO2 profiles taken from climatology (Remedios, ULeic)

ECMWF: temperature, pressure and water vapour profiles

‘A priori’ albedo - inferred from SCIAMACHY radiance as a f(SZA)

‘A priori’ aerosol (maritime/rural/urban)

SCIAMACHY

Spectra, geolocation, viewing geometry, time

Process only if : cloud free, forward scan, SZA ‹75 Process only if : cloud free, forward scan, SZA ‹75

Cloud Filter SPICI (SRON)

(Krijger et al, ACP, 2005)

Note: No scaling of FSI data

PrecisionPrecision - Validation - Validation SummarySummary• FTIRFTIR

– Park Falls Park Falls ~ -2% ~ -2%

– Egbert Egbert ~ -4% ~ -4%

• TM3TM3– Bias ~ -2%Bias ~ -2%

– SCIAMACHY overestimates seasonal cycle by factor 2-3 with respect to the SCIAMACHY overestimates seasonal cycle by factor 2-3 with respect to the TM3 – reason?TM3 – reason?

– Bias of TM3 w.r.t Egbert FTIR data ~ -2%Bias of TM3 w.r.t Egbert FTIR data ~ -2%

• Aircraft Aircraft – collocated observations in time & space– collocated observations in time & space

– Sites over Siberia (rSites over Siberia (r22 > 0.72-0.9) > 0.72-0.9)

– Best at 1.5 km Best at 1.5 km

• Surface SitesSurface Sites - monthly averages - monthly averages

– Time series comparisons (inc. aircraft)Time series comparisons (inc. aircraft)

– Out of 17, 11 have rOut of 17, 11 have r22 > 0.7 > 0.7

Collocated on same day within +/- 5 deg lon/lat of Collocated on same day within +/- 5 deg lon/lat of sitesite

22ndnd panel: horizontal lines = +/- 5 ppmv difference panel: horizontal lines = +/- 5 ppmv difference

33rdrd panel: horizontal lines = +/- 2% bias panel: horizontal lines = +/- 2% bias

Surgut Surgut

SCIAMACHY = RedSCIAMACHY = Red Aircraft = Black Aircraft = Black

Better agreement at 1.5-2.0 km

CorrelationsCorrelations

Surface COSurface CO22: USA (: USA (±5°lon/lat of site)±5°lon/lat of site)

Can we learn anything?Can we learn anything?

• Greater COGreater CO22 uptake by uptake by forests compared to forests compared to crops & grass plains?crops & grass plains?

• Identification of Identification of sub-continental COsub-continental CO22 sources/sinks?sources/sinks?

xvid_1fps.avi

Global CO2 (5% error video)

ConclusionsConclusions

• Space-based observations have a role to play as part of a system for Space-based observations have a role to play as part of a system for climate.climate.

• First views of carbon dioxide from space seem to be approaching the First views of carbon dioxide from space seem to be approaching the accuracy to look at natural variabilityaccuracy to look at natural variability

[Trends in carbon dioxide also look good][Trends in carbon dioxide also look good]

• First (tentative) steps to identify surface sources/sinksFirst (tentative) steps to identify surface sources/sinks

• Regional (continental scale) studies appropriate since global data Regional (continental scale) studies appropriate since global data quality is variablequality is variable

• Future missions may allow estimates of man-made emissions.Future missions may allow estimates of man-made emissions.

Thanks to…Thanks to…• Udo FrieUdo Frieß ß

Institute of Environmental Physics, Heidelberg, GermanyInstitute of Environmental Physics, Heidelberg, Germany

• John Burrows, V. RozanovJohn Burrows, V. RozanovInstitute of Environmental Physics, U. Bremen, GermanyInstitute of Environmental Physics, U. Bremen, Germany

• R. L. Mittermeier and H. FastR. L. Mittermeier and H. FastMeteorological Service of Canada (MSC), Ontario, CanadaMeteorological Service of Canada (MSC), Ontario, Canada

• R. Washenfelder, G. Aleks, G. Toon., P.WennbergR. Washenfelder, G. Aleks, G. Toon., P.WennbergNASA JPL & Caltech, USA.NASA JPL & Caltech, USA.

• T. MachidaT. MachidaNIES, JapanNIES, Japan

• S. Körner and M. HeimannS. Körner and M. HeimannMax Planck Institute for Biogeochemistry (MPI-BGC), Jena, GermanyMax Planck Institute for Biogeochemistry (MPI-BGC), Jena, Germany

•Richard EngelenRichard EngelenEuropean Centre for Medium-Range Weather Forecast, Reading, UKEuropean Centre for Medium-Range Weather Forecast, Reading, UK