Briefing for NACAA MSC

Overview of remote sensing research during DISCOVER-AQ relevant to PAMS network Briefing for NACAA MSC Jim Szykman and Russell Long U.S. Environmenta...
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Overview of remote sensing research during DISCOVER-AQ relevant to PAMS network

Briefing for NACAA MSC Jim Szykman and Russell Long U.S. Environmental Protection Agency Office of Research and Development National Exposure Research Laboratory

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Office of Research and Development National Exposure Research Laboratory

Discussion Topics Vaisala CL-51 Ceilometer  Field evaluation of mixing height  Open source MLH algorithm - STRAT  Data considerations – full backscatter profile vs. hourly mixing height

NASA/SAO TEMPO Satellite Mission  PANDORA ground-based spectrometer and nexus with new PAMS

requirements

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Office of Research and Development National Exposure Research Laboratory

Motivation for Continuous PBL Observations  Initial interest in continuous planetary boundary layer observations driven by DISCOVER-AQ and exploring the relationship between column and surface observations of NO2

Vaisala CL-51Ceilometer

Vaisala CL-51 Ceilometer Stated Characteristics:



Cloud reporting range: 0…43,000 ft (0…13km)



Backscatter profiling range: 0…49,200 ft (0…15km)

 

Can operate in all weather

  

Reliable automatic operation

Fast measurement - 6 second measurement cycle Good data availability Eye safe diode laser (LIDAR)

CL-51 positioned next to Space Science and Engineering Center, University of Wisconsin Mobile Lab

Peer-reviewed literature contains limited evaluation of the CL-51 derived mixing layer height compared to radio-sonde boundary layer height.

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Field Evaluation of CL-51 aerosol backscatter

NASA P-3B Profiles T, RH, O3, & extinction

aerosol backscatter

NA

910

NA

532

MLH

PBL

MLH

PBL & MLH

MLH

Surface

Balloon

Surface

Aircraft

Surface

Hampton, VA, Golden and Erie, CO December 20132015; July-August 2014

Hampton, VA, Golden and Erie, CO December 20132015; July-August 2014

Erie, CO

Golden and Erie, CO

Golden, CO

July-August 2014

July-August 2014

July-August 2014

Temporal Coverage

Continual

Day/week

Continual

Flight Day

Continual

Spatial Coverage

Point

20%  Sonde 𝜽 profiles compared with 𝜽 profiles from NASA P-3B aircraft spirals over Golden and BAO Tower

STRucture of the ATmosphere (STRAT v1.04) algorithm

 STRAT is a covariance wavelet technique (CWT) currently in

use by the European Aerosol Research Lidar Network (EARLINET - http://www.earlinet.org/).  Developed under a GNU General Public License  Potential open-source alternative to BL-View  Evaluated the impact of data logging via BL-View versus raw CL-51 output  When MLH is averaged to time-scale of 1-hour, data logging method shows no significant difference  Need to do a direct comparison MLHs via BL-View and STRAT

NOAA CL-31vs. EPA CL-51 BAO Tower Site During DISCOVER-AQ Denver

 Attenuated backscatter from co-located CL-31 and CL-51 ceilometer (< 20 yards)  Data processed via STRAT algorithm  Data filtered to remove points with >0.20 km relative standard deviations  Generally poor agreement between CL-31 and CL-51 MLH  3 panel plot for July 27, 2014 at the BAO-Tower site showing CL-31 backscatter profiles and MLH, CL- 51 backscatter profiles and MLH, and the difference between the instruments and algorithms for MLH  Differences likely due to CL-51 improved signal -to-noise

Data Considerations  Mixing Height is the required variable under PAMS  CL-51 is capable of providing attenuated backscatter profiles up to 15km+  Data logging the entire backscatter profile allows for:  Alterative algorithms to derive MLH, especially if other lidars (MPL, HSRL, CL-31s) are part of any network  Visual check on the derived MLH  Use of data to better evaluate exceptional events  Consideration should be given to explore 1.) use of data systems capable to exploit the full value of any aerosol profile network, 2.) synergies with the NASA Micro-Pulse Lidar Network 11

Office of Research and Development National Exposure Research Laboratory

Example of CL-51 attenuated backscatter profile and mixing heights from DISCOVER-AQ Denver (Golden and BAO Tower) in EPA Remote Sensing Information Gateway 3D-Application

TEMPO: Hourly atmospheric pollution from geostationary Earth orbit Selected Nov. 2012 as NASA’s first Earth Venture Instrument • Instrument delivery September 2017, with expected ~2019+ launch Provides hourly daylight observations to capture rapidly varying emissions & chemistry important for air quality • UV/visible grating spectrometer to measure key elements in tropospheric ozone and aerosol pollution • Exploits extensive measurement heritage from LEO missions • North American component of a constellation for air quality observations TEMPO data and potential air quality application areas Emissions Inventories (improve or develop new methods, including mobile sources and area sources such as soil NOx) • Inform air quality model development and evaluation • Evaluation of impact of short term climate forcers (ozone, chemically produced aerosols) and climate-chemistry connections • Data on smaller spatial scales better supports AQ assessment and planning activities: Source attribution, Exceptional Event Evaluations (Wildfires and Strat. Intrusions) and Trends • Intercontinental transport of air pollution (HTAP and other activities

TEMPO PI - Kelly Chance, SAO 13

Pandora vs Surface-Colorado Pandora Diurnal variability in Column NO2 La Casa I-25

Platteville, Golden, BAO, Chatfield

Column and Surface NO2 Diurnal variability Pandora

Surface

DISCOVER-AQ observations over Colorado in August-September 2014 (L) Diurnal variability in total column NO2 observed by Pandora spectrometers. (R) Comparison of diurnal variability in total column and surface NO2 for the three sites with the highest NO2 abundances.

Trace Gas Characterization Example of NO2 remote sensing from the Colorado deployment Geo-TASO PRELIMINARY - August 11 9:08 to 10:26 local time

Credit: J. Leitch (Ball) and C. Nowlan (SAO)

New Requirements Under PAMS are Relevant to the TEMPO Mission 



Forthcoming changes in air quality monitoring requirements under the Photochemical Assessment Monitoring Station (PAMS) program by EPA present a unique opportunity to EPA, State and Local Agencies to work with NASA for satellite validation/evaluation and increase information for air quality model evaluation and analysis. Combines Ncore and PAMS Measurements:  NO, NO2, NOy, O3 (year round). SO2, CO, PM2.5 mass and speciation (At least 1-in-3 day), PM2.5 continuous, PM10-2.5 mass, basic met. parameters. 

Potential New Locations for PAMS Network

Profiling Measurements: Continue use of existing Radar wind profiler (RWP)/Radio acoustic sounding system (RASS) supplemented with use of ceilometer at new sites for continuous mixing heights.

 Some site contain optional met measurements – Vertical wind speed, solar radiation, precipitation, baro. pressure, delta-T for 2-10m.  Option to add continuous CH2O in the future as reliable commercial units are become available. Map based on 2011-2013 ozone design values PAMS requirements will be based on 2014-2016 data

Office of Research and Development National Exposure Research Laboratory

Pandora Ground-Based Spectrometers

 Developed at NASA Goddard

 Total Column O3, SO2, HCHO, BrO, NO2 and H2O every 80 seconds  NASA is exploring options to develop a PANDORA Network  New PAMS requirements (“true” NO2 and MLH) provide synergistic measurements to PANDORA

 PAMS + PANDORA (NASA) could potentially serve as a U.S. based ground-based satelltie validation network

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Office of Research and Development National Exposure Research Laboratory

Trace Gas Characterization

Examples of Pandora column-integrated observations NO2 and in situ profiles by the P-3B from the Colorado deployment

Source: Jim Crawford NASA LaRC

Acknowledgements/Disclaimer ORD DISCOVER-AQ Research Team Russell Long, Rachelle Duvall, and Melinda Beaver Travis Knepp SSAI/NASA Langley

Acknowledgements • • •

U.S. EPA, OAR/OAQPS/AAMG Alion Science and Technology NASA, NOAA, UMBC, Millersville University, SSEC/CIMSS (Univ. of Wisc.) and CDPHE

Disclaimer Although this work was reviewed by EPA and approved for presentation, it may not necessarily reflect official Agency policy. 14

Office of Research and Development National Exposure Research Laboratory