1. Forecasting the Impacts of Wildland Fires
Yongtao Hu1, William Jackson2, M. Talat Odman1 and Armistead G. Russell1
1School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia
2USDA Forest Service, Asheville, North Carolina
Presented at the 6th Annual CMAS Conference, October 2nd, 2007
Georgia Institute of Technology

2. Wild land Fires and Air Quality
Wild land fire (wild and prescribed fires) burned ~9 million acres nationwide in US each year during the past three years.
Burning of wild land vegetation increases emissions of PM2.5, CO, VOC, NOx …, which impact air quality, visibility and potentially public health.
A severe wild land fire could cause rapid increases of both PM2.5 and O3 to extremely high levels at populated area and cause exposures to unhealthy air for several hours or even days. Such as those hit Atlanta metro area with thick smoke clouds this year:
To what degree can we forecast wild-land-fire-impacts on air quality by adopting current operational air quality forecasting system?
The prescribed fires on February 28, 2007 in Jasper County Georgia.
The Georgia-Florida wildfires lasting from April through May.
Georgia Institute of Technology

3. Georgia Institute of Technology
Hi-Res Air Quality Forecasting System Serving Metro-Atlanta Area since 2006
CMAQ
SMOKE
Emission Inventory
WRF
NAM 84-hr Forecast
Forecast Product
Meteorology
Emissions
Air Quality
Georgia Institute of Technology

4. Hi-Res Modeling Domains
4-km
12-km
36-km
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What could be done?
Hi-Res cycle allows sufficient time for extra efforts.
Hi-Res Cycle
00Z
45Z
77Z
36- & 12-km ramp up simulation
12- & 4-km forecast
8pm
0am
Forecast Day
Start Job
Finish Job
Release Product
For prescribed burning, the air quality forecast ahead of the actual igniting would help plan and conduct burns.
For existing/ongoing wildfires, the air quality forecast would warn people to avoid unhealthy air exposures at the following days.
Georgia Institute of Technology

6. Estimate Emissions of Potential Fires
Using models: the Fire Emission Production Simulator (FEPS) and the Consume 3.0 ( )
Prescribed fire: collect pre-burning information from the burning plans prepared in advance.
acreage of planned burning area, approximate locations, fuel load descriptions, igniting method and operation schedules …
Existing/ongoing wild fire: determine the most likely fire locations on the following days according to the analysis of forecast meteorological conditions combined with the information on previous days’ burning locations.
Then collect and estimate other fire information: approximate acreage of burning area, fuel consumption and expected fire temperatures …
Allocate estimated potential fire emissions to the corresponding Hi-Res grid cells according to the geographical information.
Georgia Institute of Technology

7. Wild-Land-Impacts on Air Quality
One way to calculate the air quality impacts of a fire is to run two simulations:
Run (1): “typical” emissions default in Hi-Res
Run (2): estimated potential fire emissions added in
and to take their difference:
Impact = Air Quality (2) – Air Quality (1).
A more efficient way is to estimate the contribution of the fires by calculating emission sensitivities with the Decoupled Direct Method (DDM) provided by the Hi-Res system.
Requires a single model run with potential fire emissions added in.
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8. Georgia Institute of Technology
Application to prescribed fire: forecast and hindcast the February 28th, 2007 episode
Forecast: to test the predictive capability of this system.
Forecast meteorology
Emissions estimated from pre-burning information
Hindcast: to identify key weaknesses in the system.
Re-analysis data (through FDDA) to predict the meteorology
Post-burning information to estimate emissions
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9. Georgia Institute of Technology
Smoke Detected by Geostationary Satellite (1:15-1:45 pm EST on February 28th, 2007 )
Atlanta
The circles represent other areas burned between and 0.47 km2 while the triangles represent those between 0.47 and 1.11 km2, according to data recorded by the Georgia Forestry Commission.
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10. Ambient Monitoring and Prescribed Burning Sites
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Hourly PM2.5 Mass
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12. Hourly Ozone Concentrations
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13. PM Impact of the Oconee NF and Piedmont NWR Fires
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14. Contribution from fire
Observed and Predicted Max. Concentration and Predicted Max. Impact from the Fires within Atlanta Urban Area O3
Hindcast
Forecast
Contribution from fire
PM2.5
Observed
Sensitivity analysis has shown that observed ozone peaks can only be reached at 5 times typical biogenic VOC emissions from burning areas. Bursts of fire-induced isoprenoid (isoprene and monoterpenes) emissions are reported in the literature.
Georgia Institute of Technology

15. Organic Matter to PM2.5 Ratios
Forecast
Hindcast
Observed
Smoke hit Atlanta at hour 17
Increased VOC emissions also make up part of missing secondary organic aerosol (SOA). Evaporation and re-condensation of leaf surface wax may be another source of SOA as suggested by GC/MS analysis. Also background primary OM from other fires missing in the “typical” inventory.
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16. 1-hr Exposures to Ambient PM2.5
Forecast
Hindcast
35 ug m-3
65 ug m-3
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17. Forecast, Hindcast and Observed Plumes
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18. Georgia Institute of Technology
Application to wild fires: the May 18th-23th, 2007 episode of Georgia-Florida wildfires
Observed Hourly PM2.5
MODIS aerosol optical depth (AOD) on May 21st (L) and 22nd (R), 2007
Data obtained from
G-F fires plume reached Atlanta after long-range transport through Alabama under easterly winds on 21st that turned to westerly on 22nd.
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Data obtained from
Fig 7 Observed Hourly PM2.5 during May 21-22, 2007
Fig 6 MODIS aerosol optical depth (AOD) on May 21st (L) and 22nd (R), 2007
Data obtained from
Fig 7 Observed Hourly PM2.5 during May 21-22, 2007
Fig 6 MODIS aerosol optical depth (AOD) on May 21st (L) and 22nd (R), 2007
Data obtained from
Fig 7 Observed Hourly PM2.5 during May 21-22, 2007
Fig 6 MODIS aerosol optical depth (AOD) on May 21st (L) and 22nd (R), 2007

19. Wildfire Impacts on Hourly PM25
Simulated period: May 18 – 23, Preliminary Results on May 22
Missed Atlanta
Possible reasons could be the absence of the surface thermal changes induced by the fire from the meteorological model and the coarse vertical resolution in CMAQ above 1-km from the ground.
Georgia Institute of Technology

20. Georgia Institute of Technology
Summary
We have developed and tested a modeling system to forecast wildland-fire-impacts on air quality in Atlanta, Georgia.
The application to forecast the prescribed fires on February 28, 2007 was successful and indicates that the fires could be reasonably well estimated using the system. The “forecast” predictions are in good agreement with observations, though the hindcast improves significantly on timing and location.
More efforts are needed to improve the capability of the system to simulate wildfires.
We can also report the estimates of the primary OC emissions using the same scaling.
Georgia Institute of Technology