Causes of Haze Assessment Update for Fire Emissions Joint

Forum -12/9/04 Meeting

Marc Pitchford

Causes of Haze Assessment (COHA)

• Overview– Starting the third year of a 4-year contract effort to

use ambient monitoring data & some emissions information to assess haze influential factors (e.g. aerosol species, atmospheric processes, source types & regions)

– Assessment information & products are stored & distributed on the COHA web site (no paper report) http://www.coha.dri.edu/

– Primary uses of the COHA products are to support the technical assessments for SIPs & TIPs, and specifically the Attribution of Haze Workgroup effort

COHA Tasks• Completed for each Class I Area

– Emissions mapping & Descriptions (maps of NOx, SO2 & fire within 20km)

– Monitoring Site Setting Descriptions (maps of terrain, land-use, air quality & met. monitoring sites, urban & industrial locations)

– Meteorological Site Setting Descriptions (local flow patterns, site representativeness, climate data, etc.)

– Aerosol Descriptions (figures, tables, & text of typical, best & worst aerosol components, monthly distribution & composition of worst days)

– Back Trajectory Analysis (3 years of 8 per day 8-day back trajectories at 3 starting heights [>3 million trajectories], summary maps of all days, best & worst haze days, best & worst for each component days, etc [>5000 summary maps])

– Trajectory Regression Analysis (statistical relationship between transport time over source regions & air quality measured at the monitoring site, sufficient data at about 80 sites, used by the AOH workgroup to compare to WRAP modeling attribution results

Bandelier Wilderness Area : Nearby Emissions

US Fire Database

US National fire database 1970 to 2002 reported by USFS, BLM, BIA, NPS, FWS

Key Data Fields:• Lat/long• Fire start date (date

discovered & controlled on USFS land only)

• Area• Cause• QA flags (DRI)

Canadian Fire Database

Canadian Large Fire Database 1959 to1999

Large forest fires in Canada, 1959–1997, Stocks et al., 2003 J.G.R.

Key Data Fields:• Lat/long• Province• Region• Fire start date• Size• Cause

MODIS Fire Database

Key Data Fields:• Lat/long• Fire start date• Brightness temp• Pixels

2001 to present from Forest Service, Remote Sensing Application Center

The fire detections are discerned using the 1-km thermal bands of MODIS. Detections are provided as the centroids of the 1-km pixels

http://activefiremaps.fs.fed.us/

2002 fires shown here

NOAA NESDID Satellite Services Division Fire Database

• 2003 to present • Detections from GOES, AVHRR, DMSP/OLS

and MODIS• Archived visible smoke plume polygons

Key Data Fields:• Lat/long• Time

http://www.firedetect.noaa.gov

Alaska Fire Database• Alaska Forest Service• Large wildland fires from 1950 to 2003• Provides only year not day

Key Data Fields:• Lat/long• Year• Area, perimeter• Fire ID

http://agdc.usgs.gov/data/blm/fire/index.html

Example Trajectory Summary MapsBandelier National Park – residence time maps show fraction of transport hours spent over each 1o by 1o cell.

• Top map shows the residence time for the worst 20% haze days

• Bottom map shows the residence time for the best 20% haze days

Trajectory Regression Results

• Bar graphs of concentration & percent contributions associated with 15 to 20 source regions

• Source regions are based on state borders

• Includes statistical uncertainty bars & tabular regression analysis output (not shown)

• Currently applied to sulfate and aerosol extinction data

COHA Tasks• To be completed

– Episode analysis (custom assessment of causes of worst haze periods using supplemental information, examples: forest fires, regional & global dust, eastern sulfate transported west, west coast nitrates, etc) ~10 episodes completed to date

– Receptor modeling (more transport regression, CMB, etc.)

– Update previous work with additional data

Additional COHA Activities

• Tribal Causes of Haze (conduct COHA for tribal Class I Areas, assess regional haze monitoring needs for tribal lands)

• Dust Causes of Haze (develop methods to characterize dust by source type/geographic scale, apply method to several years of data)