Use of Satellite Data to Support Regulatory Air Quality Decisions

Transcription

1 Use of Satellite Data to Support Regulatory Air Quality Decisions Richard Payton Scott Jackson EPA Region 8 Air Program Workshop on Satellite and Above-Boundary Layer Observations for Air Quality Management May 9-10, 2011 Disclaimer: No positions expressed here represent official EPA policy

2 Use of Satellite Data in Two Regulatory Areas 1) Review of Exceptional Event Claims 2) To Inform Nonattainment area boundaries My focus is on regulatory decisions Good Science is the basis for EPA decisions, but: The regulatory decision can be far removed from research grade science It Can be challenging for regulatory scientists to understand and incorporate space based or other research measurements 2

3 Exceptional Events Exceptional events are air pollution events not readily controlled through traditional State Implementation Plan processes Exceptional events are defined by Section 319 of the Clean Air Act affects air quality; is not reasonably controllable or preventable; is an event caused by human activity that is unlikely to recur at a particular location or a natural event; and is determined by the Administrator through the process established in the regulations... to be an exceptional event 3

4 Exceptional Events Types Where Satellite Data has been Useful Wildfires Plumes Dust Storms Stratospheric Ozone Intrusions 4

5 Wildfires Numerous websites with Satellite and derived smoke plume data Hazard Mapping System Fire and Smoke Product USFS Daily MODIS Image Subsets GOES The Experimental Wildfire ABBA Fire Product My Preferred: 5

6 NGDC Satellite Fire Detections Map Controls Accessible Archive 6

7 2008 California Wildfires Area With Fires Potential Utah Impacts 7

8 2008 California Fire Potential Impact on Utah Violating Monitor Attaining Monitors 8

9 Dust Storms Several websites with Satellite and derived dust plume data MODIS Imagery et al. NRL MODIS Dust Enhance Product Tutorial: Parent Directory: (2 week archive) 9

10 NRL Dust Enhance Example April 19, 2008 Source: Naval Research Lab NexSat 10

11 Modis Visible Image and NRL IR Image 11

12 Three Plumes, Three Source Types 12

13 Stratospheric Ozone Intrusions Historically difficult to asses With historic high NAAQS levels (120 ppb 1-hour average, 80 ppb 8-hour average) significant stratospheric impacts were very rare Lower NAAQS levels (0.075 ppb 8-hour average, or proposed 0.06 to 0.07 ppb 8-hour average), stratospheric impacts may be both more common, and harder to evaluate 13

14 Stratospheric Ozone Intrusions Example: April 15, 2011 Unusual Pattern: Elevated over entire SW No contrast between rural and urban areas 14

15 Stratospheric Ozone Intrusions: Tools Unusual Monitor Trace Ozone RH Satellite Total Ozone Column Modeled Tropopause Height Ozone Soundings 15

16 Monitored Ozone Data Predawn Ozone bump Afternoon Ozone Peak Urban Salt Lake City Site (nighttime NOx Titration) 16

17 Monitored Humidity Data General Drying Trend through 4/15 Not very conclusive 17

18 Ozone Column: April 14-15, 2011 Colorado Source: NOAA NESDIS GOME 2 Page 18

19 Modeled Tropopause Height, April 14, 2011 North American Meso 212 Output, Univ. of Utah Source: University of Utah Department of Atmospheric Sciences 19

20 Stratospheric Ozone Needs Archived Ozone Column Stratified Column Data Tropospheric O3 vs. Total Column O3 Even better, stratified tropospheric (including near surface) + Stratospheric Niceties Units? ppm, ppb vs mpa Feet/meters vs hpa 20

21 No Longer Available: HIRDLS Soundings, with coincident ozonesondes Coincident Ozonesondes Bruno Nardi, NCAR 21

22 Other Uses of Satellite Data

23 Nonattainment Area Boundaries Clean Air Act: EPA to designate areas which violate a NAAQS, as well as nearby areas which contribute to those violations. Contribute evaluated with a holistic consideration of air quality data, emissions, population, topography, meteorology and other factors. Satellite data may be able to contribute to this analysis but has not been used to date. 23

24 Uinta Basin, VERY High Winter Ozone: What areas contribute NOx? Superposition of monthly mean tropospheric NO2 from MODIS OMI Instrument, Jan. Mar., 2010 Uinta Basin, surrounded on all sides by higher elevation Power Plant NOx Source: OMI NO2 from KNMI website 24

25 Wasatch Front Wintertime PM2.5: Which counties contribute NOx? Superposition of monthly mean tropospheric NO2 from MODIS OMI Instrument, Dec Mar Instrument Artifact? Source: OMI NO2 from KNMI website 25

26 Example Nonattainment Area (NAA): Denver Ozone With violating monitors west and south of downtown Denver, EPA and Colorado agreed on an 8 county nonattainment area. Denver nonattainment area for hour ozone standard Future, lower NAAQS may lead to an area with many more violating monitors Source: Colorado Dept. of Health and Environment 26

27 Denver Front Range Summer Ozone: Which counties contribute NOx? Superposition of monthly mean tropospheric NO2 from AQUA OMI Instrument, Jun. Aug., 2008 NOx Layer Off Source: OMI NO2 from KNMI website 27

28 Identifying errors in National Emissions Inventory Source: Source: OMI NO2 from KNMI website 28

29 Satellite Support Designations Possible uses: Locating pollution sources Identifying errors or omissions in the National Emission Inventory Visual representation of urban NOx plume O3, VOC, SO2 or aerosol plumes would also be valuable Current Limitations: Lack of air quality management practitioner understanding of the interpretation satellite data. Lack of available on-demand archives. Lack of spatial or temporal coverage. Limited boundary layer information (e.g. total column ozone instead of troposphere or lower troposphere). Potential data artifacts? Users need to understand the limitations of the data 29

30 Conclusions Regulatory Use is often retrospective Accessible data archives are essential Continuity of record can be a problem OMI tropospheric NO2 not available after March 2010 Units differ for the same data in different scientific contexts ppb vs mpa or nbar; hpa vs feet or meters Interpretation at the data source desirable to avoid conversion errors Georeferencing highly desirable To be useful, users need to be able to find the data A clearinghouse would be very useful 30