Prepared by Hilary Hafner, Daniel Alrick, ShihMing Huang, and Adam Pasch Sonoma Technology, Inc. Petaluma, CA Presented at the 2010 National Air Quality Conferences Raleigh, NC March 15-18, The Importance of Meteorological Data in Exceptional Events Analysis

2 Outline Definition of an Exceptional Event Importance of meteorology in Exceptional Events; data sources and tools available Examples from past events Conclusions

3 What Are Exceptional Events? Exceptional Events are unusual or naturally occurring events that can affect air quality but are not reasonably preventable using techniques air agencies can implement to meet National Ambient Air Quality Standards (NAAQS). Three exceedance days in May 2007 were likely related to wildfires.

4 What Makes an Event Exceptional? To justify the exclusion of air quality data from NAAQS determination, the reporting agency must show –A clear causal relationship between the measured values under consideration and an identified source, –Measured value(s) are in excess of normal historical fluctuations, and –No exceedance or violation would have occurred “but-for” the event. Exceptional Events cannot be caused by air mass stagnation, temperature inversions, high temperatures, lack of precipitation, or transport from anthropogenic sources. Federal Register (72 FR ). Treatment of Data Influenced by Exceptional Events; Final Rule. Vol.72, No. 55, Pages , March 22, 2007

5 Justifying an Exceptional Event Good meteorological data and useful or appropriate analysis tools must be available and put to use. –Meteorological analyses help determine whether the event was unusual when compared to the historical record. –Tools such as diffusion models and trajectory analyses are vital in examining pollution transport from unusual sources such as volcanoes, wildfires, and stratospheric ozone. No single data set necessarily has all the pertinent information. –Surface meteorological and air quality instrumentation are usually not collocated. –Sub-hourly information can be important (i.e., wind gusts). –Surface meteorology does not represent important aloft meteorology. –Models may not be accurate.

6 Examples of Meteorological Data DataInformation ProvidedSource ASOS (Automated Surface Observing System) Hourly temperature, dew point, wind speed, wind direction, visibility, etc. NOAA (National Oceanic and Atmospheric Administration), Federal Aviation Administration, U.S. Department of Defense RAWS (Remote Access Weather System) Hourly surface observations, usually at isolated locations, to monitor fire danger U.S. Forest Service MesonetsSub-hourly surface data from networks of high spatial density Various local organizations AQS (Air Quality System)Hourly air quality and meteorological information EPA, state, local, and tribal air quality agencies RadiosondeTwice-daily vertical profiles of various meteorological fields NOAA RWP/RASS (radar wind profiler with Radio Acoustic Sounding System) Hourly vertical profiles of winds and temperature Local air districts, NOAA SatellitesMonitor cloud cover, aerosols, visual images of smoke/dust NASA/NOAA

7 Examples of Meteorology Analysis Tools Model predictions of pollution concentrations based on meteorological predictions –BlueSky Gateway –NOAA Model –NAAPS (Navy Aerosol Analysis and Prediction System) Spatial analysis tools that use meteorological and/or air quality data –AIRNow-Tech –DataFed –HYSPLIT Example of output from a 12Z run of the NOAA model depicting predicted 1-hr maximum ozone concentrations (ppb)

8 Example 1: Are Wind Speeds Outside the Historical Norm? Wind speeds during a PM 10 event Comparison to historical meteorological data indicates this event was unique. Wind speed on 4/12 was very high compared to historical records.

9 Example 1: Are Wind Speeds Outside the Historical Norm? Wind speed maximum coincided with a jump in PM 10 concentrations. Concentrations between 1400 and 1700 on 4/12 were among the highest observed over the time period.

10 4/12/2007 Interpolated gust map during cold frontal passage at LST Example 2: Do Wind Gusts Coincide with High PM 10 Concentrations?

11 4/12/2007 Interpolated gust map during cold frontal passage at LST Example 2: Do Wind Gusts Coincide with High PM 10 Concentrations?

12 Note: Wind speed data are from AQS sites different from the meteorological sites that measure gust. Example 2: Do Wind Gusts Coincide with High PM 10 Concentrations? 4/12/2007 Interpolated wind speed map during cold frontal passage at LST

13 Note: Wind speed data are from AQS sites different from the meteorological sites that measure gust. Example 2: Do Wind Gusts Coincide with High PM 10 Concentrations? 4/12/2007 Interpolated wind speed map during cold frontal passage at LST

14 Example 2: Was the Wind Direction Different During the Event? Historical April wind rose suggests stronger winds come more frequently from the southwest and west. Strongest winds on the event day came from the northwest (circled in blue on second graph), indicating unique conditions. Average April Winds Event Day Winds

15 Example 3: Was Transport of PM from Wildfires? DataFed-generated air trajectories indicate air parcels over the southeast came from a large fire in southern Georgia. The satellite-based Ozone Monitoring Instrument (OMI) shows high PM concentrations in the suspected source region. These tools help analysts make a case for an exceptional event. DataFed-generated 24-hr backward trajectories and 24-hr average PM 2.5 concentrations OMI Aerosol Index

16 Example 3: Was Transport of PM from Wildfires? Models predict various pollutant concentrations based on meteorological conditions. During this event, sulfate concentrations (important components of PM) were very low across the southeast U.S. Modeled smoke was highest at the site of fires, which affected downwind regions. Thus the PM event was most likely caused by the fire upwind rather than by anthropogenic sulfate. NAAPS (Navy Aerosol Analysis and Prediction System) from DataFed

17 Example 4: Was Pollutant Transport Important? Trajectory analysis identifies source regions and transport of pollutants. Example above includes Hazard Mapping System smoke plumes and fire locations. AIRNow-Tech allows integration and analysis of meteorology and air quality data sets.

18 Example 5: What Would Concentrations Have Been? BlueSky Gateway models fire and non-fire PM 2.5 separately. It also provides information on air quality “but-for” a wildfire; this aids Exceptional Events analysis. The accuracy of model predictions is tied in part to the quality and availability of meteorological data. + =

19 Conclusions The integration of air quality and meteorological data is vital in “telling the story” of an Exceptional Event. Properly justifying the exclusion of data due to an Exceptional Event may require multiple meteorological and air quality-related data sets, as well as a variety of analysis tools and atmospheric models. Visible satellite showing extent of smoke plume from fires over southern Georgia. Red dot represents fire location Blue dot represents receptor location Smoke

20 Selected Links to Data and Analysis Sources ASOS and Upper Air Data – AQS – BlueSky Gateway – NOAA Air Quality Forecasting – NAAPS Model and Satellite Analyses – DataFed – AIRNow-Tech – MADIS – madis.noaa.govmadis.noaa.gov