Available Analytical Approaches for Estimating Fire Impacts on Ozone Formation

1. Available Analytical Approaches forEstimating 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

2. Presentation Outline BlueSky Gateway • Overview • Sample analysis (Kansas prescribed burns) • Strengths and weaknesses • Questions and discussion

3. 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

4. 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 SmartFirev1 and the BlueSky Framework Hourly PM2.5, Ozone Concentrations

5. BlueSky Gateway Overview (3 of 5) SmartFire Gather fire info Merge fire info ICS-209 reports HMS data GeoMAC NFPORS FACTS Regional State BlueSky • Choice of: • Data sets • Weights • Algorithms Fuels Total Consumption FCCS NFDRS Hardy Landfire GVDS (FINN) FLAMBE Observed TimeRate CONSUME 3 FOFEM FINN FLAMBE FEPS EPM Observed Emissions FEPSWRAP FOFEM CustomObserved FEPSFINN FOFEM CONSUME Observed CTM

6. 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

7. 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 PM2.5concentrations

8. 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

9. 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)

10. BlueSky Gateway Sample Analysis (3 of 6) “But for” demonstration Method 1: Identify days with similar meteorological conditions to those on the event day, but without smoke, then compare peak 8-hr ozone levels.

11. BlueSky Gateway Sample Analysis (4 of 6) “But for” demonstration Method 2: BlueSky Gateway Modeling • 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

12. BlueSky Gateway Sample Analysis (5 of 6) Model Performance Evaluation • Gateway captured general ozone trends for April 2011 Observations • Mean bias = -4.5 to 1.8 ppb • Normalized mean error = 9 to 18% Predictions

13. BlueSky Gateway Sample Analysis (6 of 6) Analyzed modeling results for all ozone episodes (peak 8-hr average > 75 ppb) in April: 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.

14. 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

15. 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

16. 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

17. Contact Information Steve Reid sreid@sonomatech.com (707) 665-9900