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Available Analytical Approaches for Estimating Fire Impacts on Ozone Formation. Stephen Reid Sean Raffuse Hilary Hafner Sonoma Technology, Inc. Petaluma, CA WESTAR Wildfire and Ozone Exceptional Events Workshop Sacramento, CA March 6, 2013. 910417-5607. Presentation Outline. - PowerPoint PPT Presentation
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Available Analytical Approaches forEstimating Fire Impacts on Ozone Formation
Stephen ReidSean RaffuseHilary Hafner
Sonoma Technology, Inc.Petaluma, CA
WESTAR Wildfire and Ozone Exceptional Events WorkshopSacramento, CAMarch 6, 2013
910417-5607
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Presentation Outline
BlueSky Gateway• Overview• Sample analysis (Kansas prescribed burns)• Strengths and weaknesses• Questions and discussion
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BlueSky Gateway Overview (1 of 5)
• CMAQ-based system for providing real-time forecasts of air quality impacts from fires
• Uses outputs from the BlueSky Framework, which links models of fire information, fuel loading, consumption, emissions, and dispersion
• Demonstration project by the USDA Forest Service AirFire Team and STI
• Data and products from operational runs provided via BlueSky Gateway web portal from 2007-2012
Gridded (GRIB) AnalysisNCEP GFS or NAM
NWS Surface and Upper AirObservations
MM5Terrain, Vegetation, and
Grid Information
CMAQEPA EmissionsInventory
Hourly 3-DimensionalPrimary PM2.5
(Optional Secondary PM2.5)
Land Surface DataProcessor
Observational Data Processor (optional)
(OA/3DVAR)
Gridded DataProcessor
Photolysis Rate Processor(JPROC)
Emissions Processor (SMOKE)
Meteorology-ChemistryInterface Processor
(MCIP)
Boundary ConditionsProcessor
(BCON)
Initial ConditionsProcessor
(ICON)
TOMS Column Ozone DataFire Emissions
SMARTFIRE
BlueSkyFramework
Fire Information
DATASOURCE
Hourly PM2.5, Ozone Concentrations
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BlueSky Gateway Overview (2 of 5)
System components(2005 Demonstration System)•MM5 version 3.7 driven by NAM forecasts•MCIP version 3.1•SMOKE version 2.3•CMAQ version 4.5.1•Fire emissions from SmartFire v1 and the BlueSky Framework
BlueSky Gateway Overview (3 of 5)
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Merge fire info
Fuels
Total Consumption
TimeRate
Emissions
Gather fire info
SmartFire
BlueSky
ICS-209 reportsHMS dataGeoMACNFPORSFACTSRegionalState
Choice of:•Data sets•Weights•Algorithms
FCCSNFDRSHardyLandfireGVDS (FINN) FLAMBEObserved
CONSUME 3FOFEMFINNFLAMBEFEPSEPMObserved
FEPSWRAPFOFEMCustomObserved
FEPSFINNFOFEMCONSUMEObserved
CTM
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BlueSky Gateway Overview (4 of 5)
SmartFire•GIS-based algorithm and database for reconciling disparate fire data sets•User-defined reconciliation streams establish the data hierarchy for various parameters (e.g., fire size)•Operational system reconciles ICS-209 reports and satellite fire detects from HMS• Other data sets (e.g., GeoMAC fire perimeters) can be
used for retrospective analyses
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BlueSky Gateway Overview (5 of 5)
Gateway outputs•Maps of daily fire locations•Pollutant concentrations for two CMAQ runs: with and without fire emissions•Differences between the two runs provide an estimate of fire impacts on ozone and PM2.5 concentrations
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BlueSky Gateway Sample Analysis (1 of 6)
Kansas Department of Health and Environment (KDHE) ozone analysis•2 to 3 million acres of rangeland are burned each spring in the Flint Hills area•High ozone concentrations were reported on several days in Kansas in April 2011•Smoke from agricultural fires was believed to have caused the high ozone values•KDHE asked STI to perform analyses in support of an exceptional event submittal
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BlueSky Gateway Sample Analysis (2 of 6)
Causal analyses performed•Meteorological conditions conducive to transport of smoke to the affected monitors
•High ozone concentrations coincident with increases in PM10, decreases in visibility, and reports of smoke
•Ozone values historically unusual (above 95th percentile)
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Vis
ibili
ty (m
iles)
PM10
Conc
entr
ation
(µg/
m3 )
KICT Smoke
KICT Haze
KICT Visibility
Washington PM10
Pawnee PM10
Wichita Hlth PM10
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BlueSky Gateway Sample Analysis (3 of 6)
“But for” demonstration
ParameterApril 29, 2011
(Event Day)
May 12, 2008
(Matching Day 1)
May 4, 2011
(Matching Day 2)
Wichita High Temp (°F) 81 75 79
Wichita Low Temp (°F) 46 45 50
Wichita 6 a.m. to 12 p.m. Wind Speed (kts) 15.9 14.3 15.7
Wichita 6 a.m. to 12 p.m. Wind Direction (°) 177 168 187
Wichita 12 to 6 p.m. Wind Speed (kts) 31.4 22.8 23.5
Wichita 12 to 6 p.m. Wind Direction (°) 180 171 193
Topeka 12Z 850 Temp (°C) 11.6 11.6 7.6
Topeka 12Z 500 mb Height (m) 5670 5710 5720
Solar Radiation NA NA NA
Cloud Cover Sunny Sunny Sunny
Surface Pattern Gulf Coast high Gulf Coast high Gulf Coast high
500 mb Pattern Ridge over Kansas Ridge over Kansas Ridge over Kansas
Peck Ozone (ppm) 0.077 0.057 0.062
Sedgwick Ozone (ppm) 0.082 0.055 0.056
Method 1: Identify days with similar meteorological conditions to those on the event day, but without smoke, then compare peak 8-hr ozone levels.
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BlueSky Gateway Sample Analysis (4 of 6)
“But for” demonstration
• Burn acreage and fuel consumption data provided by KDHE for April 2011
• County-level burn acreage allocated to model grid cells based on KDHE information on typical burn practices
• Fire data fed into the BlueSky Framework; emissions calculated using the FEPS model
• FEPS diurnal profile replaced by top-hat profile that allocated emissions from 10 a.m. to 6 p.m.
• 2008 NEI used for non-fire sources
HMS fire detections for April 12, 2011
Method 2: BlueSky Gateway Modeling
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BlueSky Gateway Sample Analysis (5 of 6)
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Peak
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Ozo
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Conc
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(ppb
)
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KNI-Topeka
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Peak
8-h
r Ave
rage
Ozo
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Conc
entr
ation
(ppb
)
Date
Konza PrairieBias = 1.7 ppbError = 18%
Bias = 1.8 ppbError = 16%
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Peak
8-h
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Ozo
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(ppb
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Date
Mine CreekBias = 0.5 ppbError = 9%
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8-h
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Ozo
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Sedgwick
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8-h
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Ozo
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(ppb
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Wichita Health Dept.
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8-h
r Ave
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Ozo
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(ppb
)
Date
PeckBias = -4.5 ppbError = 12%
Bias = 0.2 ppbError = 11%
Bias = -2.7 ppbError = 12%
• Gateway captured general ozone trends for April 2011
• Mean bias = -4.5 to 1.8 ppb• Normalized mean error = 9 to
18%
Model Performance Evaluation
PredictionsObservations
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BlueSky Gateway Sample Analysis (6 of 6)
Analyzed modeling results for all ozone episodes (peak 8-hr average > 75 ppb) in April:
●●●
Monitor
Peak 8-hr Average Ozone Concentration (ppm)
ObservedBase Case (All Fires)
Without Flint Hills Fires
Impact of Flint Hills Fires
Mine Creek 0.076 0.070 0.060 0.010
Wichita Health Department 0.079 0.074 0.054 0.020
Sedgwick 0.064 0.057 0.052 0.005
KNI-Topeka 0.054 0.053 0.052 0.000
Peck 0.082 0.074 0.054 0.020
Konza Prairie 0.053 0.052 0.051 0.001
Left: Ozone difference plot for 4/6/11 representing CMAQ-modeled ozone concentrations caused by fires. Black dots show locations of impacted monitors.
Below: CMAQ-modeled impact of fires on 8-hr average ozone concentrations at Kansas monitoring sites on 4/6/11. Bold values indicate data at the impacted monitors.
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BlueSky Gateway Strengths
• Provides a quantitative estimate of fire impacts on ozone concentrations at a monitoring site
• Makes photochemical grid modeling viable by leveraging existing resources
• In operational mode, provides a screening estimate of fire impacts on ozone and establishes boundary conditions for nested analyses
• Has the flexibility to incorporate refined data on historical fire events for more robust analyses
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BlueSky Gateway Weaknesses
• Grid resolution (36-km) may not provide adequate model performance in all cases (although model results used in a relative sense)
• Framework models are largely out of date (e.g., MM5, older versions of SmartFire, BlueSky Framework, SMOKE, and CMAQ)
• Anthropogenic emissions require updating (current NEI, MOVES-based on-road emissions)
• The current configuration provides an estimate of impacts from all fires, not individual fire events
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Summary
• The BlueSky Gateway provides a potential starting point for applying photochemical grid modeling to fire-related “but for” demonstrations
• Some refinements are needed to apply Gateway to the analysis of particular fire events
• Attention must be given to model performance and associated uncertainties
