Fire Modeling issues:Fire Modeling issues:fire effects on regional air fire effects on regional air quality under a changing quality under a changing

climateclimate

Douglas G. FoxDouglas G. Fox

dgfox@comcast.comdgfox@comcast.com

Fire activityFire activityWildfire wildland fire use prescribed fireWildfire wildland fire use prescribed fire

agricultural burningagricultural burning

ClimateClimateClimate changeClimate change

Climate Climate variabilityvariability

Fire: Climate: Air QualityFire: Climate: Air Quality

Land cover & land useLand cover & land usenatural landscapesnatural landscapesmanaged forestsmanaged forests

rangelandsrangelandsagricultural landsagricultural lands

Air QualityAir Quality Climate influences Health Climate influences Health Particulates NAAQSParticulates NAAQS SOA Visibility SOA Visibility Radiation balanceRadiation balance

Overview of predicting future Overview of predicting future fire: modeling issuesfire: modeling issues

1.1. Simulating fire emissions. Simulating fire emissions. 2.2. Predicting fire potential:Predicting fire potential:

a.a. ““Critical” weather/climate Critical” weather/climate conditions;conditions;

b.b. Fuels:Fuels:• Amount (vegetation growth & change);Amount (vegetation growth & change);• Management activity influences; Management activity influences; • Moisture content. Moisture content.

3.3. Simulating fire activity:Simulating fire activity:– Ignition, Intensity & Duration. Ignition, Intensity & Duration.

BlueSky-EM

Future Vegetation

& fuels

Fire Fire SimulatorSimulator

Future fire potential/activity data

Modifiedbiogenic

land use data

Fire Simulation & Fire Simulation & LinkagesLinkages

PnET

Met Met inputsinputs

Biogenic EmissionsFire emissions

SMOKE

BEIS 311

2a2a

2b2b

33

Overview of fire modeling Overview of fire modeling issuesissues

• Fire EmissionsFire Emissions– Models to calculate fire emissions;Models to calculate fire emissions;

• Different characterizations of fuels;Different characterizations of fuels;

• Different characterizations of consumption;Different characterizations of consumption;

– Input uncertainties:Input uncertainties:• Fire occurrence data;Fire occurrence data;

• Fire size & location uncertainties. Fire size & location uncertainties.

– Limited measured emission factors:Limited measured emission factors:• Few/no measurements of aerosol components: Few/no measurements of aerosol components:

– OC , EC, PMC OC , EC, PMC – SOA precursorsSOA precursors

Overview of fire modeling Overview of fire modeling issuesissues

• Fire EmissionsFire Emissionsii = A x B x CE x e= A x B x CE x ei i

– EmissionsEmissionsii is the emission of chemical is the emission of chemical species i (in mass units);species i (in mass units);

– A is the area burned;A is the area burned;– B is the fuel loading (biomass per B is the fuel loading (biomass per

area);area);– CE is the combustion efficiency, or CE is the combustion efficiency, or

fraction of biomass fuel burned, and;fraction of biomass fuel burned, and;– eei i is an emission factor for species i is an emission factor for species i

(mass of species per mass of biomass (mass of species per mass of biomass burned) burned)

Overview of fire modeling Overview of fire modeling issuesissues

• BlueSky Fire emissions model:BlueSky Fire emissions model:– Fuel Loading:Fuel Loading:

•National Fire Danger Rating System National Fire Danger Rating System (NFDR):(NFDR):

– Fuel models (~ 20, mixes of size classes, Fuel models (~ 20, mixes of size classes, loadings/size class); loadings/size class);

– Not representative of heavier fuel loadings;Not representative of heavier fuel loadings;– National satellite derived coverage.National satellite derived coverage.

•Fuel Characteristic Classification SystemFuel Characteristic Classification System– More detailed;More detailed;– Three dimensional, ~ 100Three dimensional, ~ 100– Don McKenzie will discuss.Don McKenzie will discuss.

NFDRS and FCCS Fuel MapsNFDRS and FCCS Fuel Maps

Overview of fire modeling Overview of fire modeling issuesissues

• BlueSky Fire emissions model:BlueSky Fire emissions model:– Fuel Consumption:Fuel Consumption:

• EPM/CONSUME v.1.02 predicts fuel consumption EPM/CONSUME v.1.02 predicts fuel consumption as f (time) & emissions:as f (time) & emissions:

– Estimates CO, CHEstimates CO, CH44 and PM10 directly and PM10 directly• Fire Emission Production Simulator (FEPS):Fire Emission Production Simulator (FEPS):

– Allows 6 fuel moisture values (v dry, dry, Allows 6 fuel moisture values (v dry, dry, moderate, moist, wet, v wet);moderate, moist, wet, v wet);

– Allows flaming, smoldering & long smoldering (>2 Allows flaming, smoldering & long smoldering (>2 hrs) emissions;hrs) emissions;

– Estimates CO, CHEstimates CO, CH44 and PM2.5 directly. and PM2.5 directly.

– Emission Factors:Emission Factors:• Additional species calculated from empirical Additional species calculated from empirical

relationships as a f (CO/COrelationships as a f (CO/CO2 2 ).).– Don McKenzie will discuss.Don McKenzie will discuss.

Fire Emission FactorsFire Emission Factors

CO2 CO2 1833*CE1833*CE

COCO 961 - (984*CE)961 - (984*CE)

CH4CH4 42.7 – 42.7 – (43.2*CE)(43.2*CE)

PM2.5PM2.5 67.4 – 67.4 – (66.8*CE)(66.8*CE)

PM10PM10 1.18*PM2.51.18*PM2.5

ECEC 0.072*PM2.50.072*PM2.5

OCOC 0.54*PM2.50.54*PM2.5

NOxNOx 16.8*MCE-13.116.8*MCE-13.1

NH4NH4 0.012*CE0.012*CE

VOCVOC 0.085*CO0.085*COEmissions in g/kgEmissions in g/kg

CE = CE = DCODCO22 / {DCO+DCO / {DCO+DCO22

+ DCH+ DCH44+D+Dotherother}}

MCE = 0.15+.86*CEMCE = 0.15+.86*CE

D= [.]D= [.]plume plume – [.]– [.]

By NFDR model loading & consumption By NFDR model loading & consumption for the national wildfire inventory (t/a)for the national wildfire inventory (t/a)

From Inter RPO fire emissions inventory, Air Sciences, 2005 for WRAPFrom Inter RPO fire emissions inventory, Air Sciences, 2005 for WRAP

By NFDR model loading & consumption By NFDR model loading & consumption for the national wildfire inventory (t/a)for the national wildfire inventory (t/a)

RPO Fire Days Acres

Burned Tons Fuel Consumed

Tons PM2.5 Emitted

CENRAP 18,067 314,594 214,381 2,976 MANE-VU 3,902 11,074 7,709 101 MRPO 3,580 13,938 14,038 188 VISTAS 32,652 297,576 434,487 5,330 WRAP 3,896 3,876,611 81,367,708 1,122,647

Total 62,097 4,513,792 82,038,323 1,131,242

Data files and documentation:Data files and documentation:

http://www.airsci.com/wrap/inter-rpo/http://www.airsci.com/wrap/inter-rpo/

Regional fire days, acres, consumption & Regional fire days, acres, consumption & emissions emissions

for the national wildfire inventory (t/a)for the national wildfire inventory (t/a)

RPO 2002 Wildfire emissions estimate

Overview of fire modeling Overview of fire modeling issuesissues

• Predicting fire potential:Predicting fire potential:– Changes in fuels:Changes in fuels:

•PnET generated landscape;PnET generated landscape;•Effects of management;Effects of management;•Extraordinary disturbances.Extraordinary disturbances.

– ““Critical” fire weather scenarios:Critical” fire weather scenarios:•MACSIP generated regional meteorology;MACSIP generated regional meteorology;•““Critical” weather /climatic events:Critical” weather /climatic events:

– Fuel moisture & drought;Fuel moisture & drought;– Winds & storms.Winds & storms.

– Identifying fire grid cells:Identifying fire grid cells:•Spatial links - fuels & weather – fire cells Spatial links - fuels & weather – fire cells

Overview of fire modeling Overview of fire modeling issuesissues

• Simulating fire activity:Simulating fire activity:– Ignitions:Ignitions:

•Date & time of fire starts;Date & time of fire starts;

•Locations on the landscape;Locations on the landscape;

– Intensity;Intensity;– Duration;Duration;– Natural vs. anthropogenic fire:Natural vs. anthropogenic fire:

• Wildfire, wildland fire use, prescribed Wildfire, wildland fire use, prescribed firefire

Overview of fire modeling Overview of fire modeling issuesissues

• What are contemporary fire What are contemporary fire contributions to regional air contributions to regional air quality?quality?– Apportionment analysis from Apportionment analysis from

IMPROVE:IMPROVE:• OC/EC ratioOC/EC ratio

• Trajectory/emissions mass balance.Trajectory/emissions mass balance.

– Regional modeling (2002)Regional modeling (2002)•WRAP / RMC results.WRAP / RMC results.

Fire Apportionment: Fire Apportionment: • OC/EC Edge analysis:OC/EC Edge analysis:

– IMPROVE Data suggest:IMPROVE Data suggest:• Urban ratio ~ 2-4 Urban ratio ~ 2-4 • Fire (& SOA) dominated ratio ~ 9 or higher.Fire (& SOA) dominated ratio ~ 9 or higher.

– Setting urban = 2.3 & fire = 9 & calculating % of fire OCSetting urban = 2.3 & fire = 9 & calculating % of fire OC– Likely to be upper bound because fire OC includes SOA.Likely to be upper bound because fire OC includes SOA.

• Trajectory mass balance regression Trajectory mass balance regression (TrMB):(TrMB):– Obtain fire occurrence data (location, size, time);Obtain fire occurrence data (location, size, time);• Parameterize fire’s contribution to site OC by summing Parameterize fire’s contribution to site OC by summing

distance weighted trajectory fire grids intersections;distance weighted trajectory fire grids intersections;• Regress OC against the fire surrogate variable; Regress OC against the fire surrogate variable; • Calculate Fire OC contribution;Calculate Fire OC contribution;• Likely to be lower bound because of limited fire Likely to be lower bound because of limited fire

occurrence data & transport approximations. occurrence data & transport approximations.

•Maps of annual OC/EC ratios for 2000 – 2002.

•Maps are scaled the same in all years, black is where OC/EC is less than 2.3, red where it is greater than 9.

2000 2001

2002

OC/EC Edge analysis: OC/EC OC/EC Edge analysis: OC/EC ratiosratios

TrMB calculationsTrMB calculations

• Gridded fire occurrence data serve as surrogates for fire emissions

• IMPROVE data provide known receptor aerosol mass concentrations

• ATAD back trajectories select fires that impact IMPROVE sites• Blue hatched regions indicate the area swept by four daily back

trajectories arriving at Gila Cliffs National Monument on IMPROVE sampling days in August, 2000.

IMPROVEsites

Fire grids

ATADTrajectories

•Fire Apportioned OC Results:Fire Apportioned OC Results:•OC/EC edge analysis (all OC/EC edge analysis (all biogenics):biogenics):

•West ~ 0.6; East ~ 0.9West ~ 0.6; East ~ 0.9•TrMB Regression (wildfires):TrMB Regression (wildfires):

•West ~ 0.3; East ~ 0.4West ~ 0.3; East ~ 0.4•Current OC from IMPROVE:Current OC from IMPROVE:

•West ~ 1.0; East ~ 1.7West ~ 1.0; East ~ 1.7•Fire contribution to OC: Fire contribution to OC:

•West ~ 30-60%; East ~ 24-West ~ 30-60%; East ~ 24-54%54%

Apportioning Fire’s contribution:Apportioning Fire’s contribution: results (ug/mresults (ug/m3)3)

OCM = 1.4*OC, avg. organic ~ 70%C

WRAP TSS results for Crater Lake NPWRAP TSS results for Crater Lake NP

AnthropogenicAnthropogenic firefire component component

Questions?