air quality products from noaa operational satellites

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010

Image:

MODIS Land Group,

NASA GSFC

March 2000

Air Quality Products from NOAA Operational Satellites

Air Quality Products from NOAA Operational Satellites

Presented by

Shobha KondraguntaPresented by

Shobha Kondragunta

2 Center for Satellite Applications and Research (STAR) Review

09 – 11 March 2010 Center for Satellite Applications and Research (STAR) Review

09 – 11 March 2010

Requirement, Science, and BenefitRequirement, Science, and Benefit

Requirement/Objective• Weather & Water:

– Provide information to air quality decision makers and improve NOAA’s national air quality forecast capability– Improve understanding of the connection between climate and shorter-term high impact air quality events to inform

decision-makers.• Climate Variability

– Enhance NOAA’s operational decision support tools to provide climate services for national socio-economic benefits

Science• What are the optimal approaches by which satellite remote sensing, in situ

observations, and models can be integrated to provide accurate and useful decision support for air quality assessments and predictions?

• How can we best exploit satellite observations to monitor, track, and differentiate between various natural and anthropogenic emissions of gases and aerosols important to public health?

Benefit• Understand the effect of environmental factors on human health and well being

– General public (recipients of air quality warnings)– Clean Air Interstate Rule, Clean Air Act, regional haze rule, exceptional events monitoring, etc.– Development of short-term and long-term pollution mitigation strategies by state and local environmental agencies

• International users– Algorithm/product development



09 – 11 March 2010

Challenges and Path ForwardChallenges and Path Forward• Science challenges

– Retrieving vertical profiles of trace gases and aerosols– Lack of in situ data to validate GOME-2 NO2 product– Lack of in situ data to validate biomass burning emissions product

• Next steps– Continue algorithm enhancement work for current operational products– Prepare for next generation satellite sensors (GOES-R, NPP/NPOESS)– Improve coordination with users to enhance data use and develop new applications

• GOES-R air quality proving ground launched in 2009– Develop validation campaigns

• Transition Path– Research to Operations

• GEO-CAPE transition team• Collaboration with NASA and EUMETSAT in areas of algorithm development• Participation in CEOS and GEOSS

– Atmospheric composition constellation– Air quality community of practice

– Assimilation and/or model improvements based on satellite data• JCSDA air quality working group

– EPA AIRNow, Remote Sensing Information Gateway (RSIG)• Operational dissemination of air quality information which includes NOAA satellite data



09 – 11 March 2010

NOAA Operational Air Quality Products(SPSRB Approved)


• Aerosol Optical Depth: quantitative measure of atmospheric aerosol loading that has been shown to be a proxy for surface particulate matter pollution, PM2.5 (aerosol mass in µg/m3).

– Single channel retrieval using measured visible channel reflectances from GOES Imager.

– IR channels used in identifying clouds.

– Physical retrieval that separates contribution of surface from aerosols.

• Automated Smoke Detection and tracking Algorithm (ASDA): semi-quantitative retrieval of column average smoke concentration (µg/m3) using AOD and fire hot spots from GOES.

– Uses source apportionment and pattern recognition techniques to isolate smoke aerosols from other type of aerosols.



09 – 11 March 2010

NOAA Operational Air Quality Products (SPSRB Approved)

NOAA Operational Air Quality Products (SPSRB Approved)

• Tropospheric Nitrogen Dioxide: quantitative retrieval of tropospheric nitrogen dioxide (NO2) that is a precursor to photochemical smog formation.

– Differential Optical Absorption Spectroscopy (DOAS) technique takes advantage of fine absorption features of NO2 in the UV-VIS.

– Slant columns are converted to vertical column densities using air mass factors and stratospheric component is removed from the total column to obtain tropospheric NO2 amounts.



09 – 11 March 2010



• Biomass Burning Emissions Product:

– Conventional approach uses fuel load, burned area, fraction of fuel consumed, and emissions factors to determine emissions. STAR developed a new fuel load dataset using MODIS land products.

– Alternate algorithm based on fire radiative power to calculate emissions is currently being tested.

Seasonal Burned Area over Alaska from GOES-11 in 2009

Fuel Load (kgC/ha)

Emissions (g) = Burned area (ha)*fuel load (kgC/ha)*emissions factors (g/kgC)* fuel consumed (%)

Global Geostationary Based Biomass Burning Emissions of PM2.5



09 – 11 March 2010

Air Quality Applications of NOAA Operational Satellite Data


Tracking NOx Emissions using GOME-2 NO2 Data

Weekday

Weekend

Weekday/weekend differences in NOx emissions as observed by GOME-2 are expected to help evaluate and update emissions in air quality forecast models



09 – 11 March 2010



• Assimilation of GOES Aerosol Optical Depth (AOD) in a NOAA-EPA Weather and Research (WRF)/Community Multiscale Air Quality (CMAQ) model shows improved aerosol predictions for an eastcoast pollution episode

Significance: Accounting for missing sources and sinks in the model via aerosol data assimilation helps improve particulate pollution predictions. NWS is mandated to deploy nationwide PM2.5 forecasts early next decade. This research will help NWS meet its mandate.

Assimilation

No Assimilation

Assimilation

Modeling and Assimilation



09 – 11 March 2010



Integrated observations, products and synthesis to

support air quality forecasters



09 – 11 March 2010



Sample NWS Smoke Forecast Verification,

13 July 2009 17Z – 18Z Prediction

7/13/09, 17-18Z, Observation:

GOES smoke product: Confirms areal extent of peak concentrations

Threat Score = 30%, for column-averaged smoke > 1 ug/m3



09 – 11 March 2010

Challenges and Path ForwardChallenges and Path Forward• Science challenges

– Retrieving vertical profiles of trace gases and aerosols– Lack of in situ data to validate GOME-2 NO2 product– Lack of in situ data to validate biomass burning emissions product

• Next steps– Continue algorithm enhancement work for current operational products– Prepare for next generation satellite sensors (GOES-R, NPP/NPOESS)– Improve coordination with users to enhance data use and develop new applications

• GOES-R air quality proving ground launched in 2009– Develop validation campaigns

• Transition Path– Research to Operations

• GEO-CAPE transition team• Collaboration with NASA and EUMETSAT in areas of algorithm development• Participation in CEOS and GEOSS

– Atmospheric composition constellation– Air quality community of practice

– Assimilation and/or model improvements based on satellite data• JCSDA air quality working group

– EPA AIRNow, Remote Sensing Information Gateway (RSIG)• Operational dissemination of air quality information which includes NOAA satellite data

air quality products from noaa operational satellites

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