Integrated Modeling of Forest Growth, Fire Emissions, Air Quality and

Its Climate Feedbacks

L. RanL. Ran11, U. ShankarU. Shankar11, D. McKenzie, D. McKenzie22, A. Holland, A. Holland11 A. XiuA. Xiu11, , S. ArunachalamS. Arunachalam11, S. McNulty, S. McNulty33, J. Prestemon, J. Prestemon44, ,

and D. Foxand D. Fox55

2007 EastFire Conference2007 EastFire ConferenceJune 6-8June 6-8

11 Institute for the Environment, UNC-Chapel HillInstitute for the Environment, UNC-Chapel Hill2 2 USDA Forest Service,USDA Forest Service, Pacific Wildland Fire Sciences Laboratory33 USDA Forest Service, Southern Global Change Program USDA Forest Service, Southern Global Change Program4 4 USDA Forest Service, Southern Research Station, RTP, NCUSDA Forest Service, Southern Research Station, RTP, NC55 Cooperative Institute for Research in the Atmosphere, Ft. Collins, CO Cooperative Institute for Research in the Atmosphere, Ft. Collins, CO

Research Program GoalsResearch Program Goals

Project funding: EPA STAR Grant RD 83227701Project funding: EPA STAR Grant RD 83227701Aim: support the EPA Global Change Research Aim: support the EPA Global Change Research

Program goals byProgram goals byExamining consequences of climate change for wild Examining consequences of climate change for wild

fire occurrence and consequently for U.S. air qualityfire occurrence and consequently for U.S. air qualityCombining the effects of climate change with forest Combining the effects of climate change with forest

growth to examine impacts on fire frequency and growth to examine impacts on fire frequency and intensityintensity

Investigating methods to credibly project changes in Investigating methods to credibly project changes in biogenic emissions from 2002-2050 due to firesbiogenic emissions from 2002-2050 due to fires

Air Quality and Climate ImpactsAir Quality and Climate Impacts of Firesof Fires

Impacts of wild fires Impacts of wild fires felt at the regional felt at the regional and global scaleand global scale

Black carbon => positive Black carbon => positive climate feedback climate feedback (warming); SO(warming); SO22 emissions emissions => negative climate => negative climate forcing from secondarily forcing from secondarily produced SOproduced SO44

Effect of radiatively Effect of radiatively important pollutants on important pollutants on short-term climate short-term climate variability affects forest variability affects forest growth, biogenic emissions growth, biogenic emissions and future fuel loadsand future fuel loads

CO O3

Carbonaceous

Aerosol

Effects of Canadian boreal fires on CO, PM and ozone from a July 1995 simulation

Predictive Modeling IssuesPredictive Modeling Issues

Current fire inventoriesCurrent fire inventories cannot capturecannot capture

climate impacts on forest biomass and climate impacts on forest biomass and fuel loadsfuel loads

effects not reflected in biogenic land cover effects not reflected in biogenic land cover datadata

Feedback of scattering and absorbing Feedback of scattering and absorbing aerosols and ozone to atmospheric aerosols and ozone to atmospheric dynamics not captured in most air quality dynamics not captured in most air quality simulation models simulation models

Understanding these effects is essential to Understanding these effects is essential to fully assess impacts of managed vs. wild fully assess impacts of managed vs. wild fires on air quality and climate and the net fires on air quality and climate and the net benefits of fire management plansbenefits of fire management plans

Integrated Modeling SystemIntegrated Modeling System

PnETCCSM

METCHEM(MM5-MCPL /

MAQSIP)

BlueSky-EM-SMOKE-MEGAN

Monthly met.

Base & future yearfuel data

Fire Scenario Builder

Hourly met

Fireactivity data

Modifiedbiogenic

land use data

Anthropogenicinventoriedemissions

Gridded &SpeciatedEmissions

Initial &boundary

met.

PnET Forest Growth ModelPnET Forest Growth Model

Used by the USFS Southern Global Change Used by the USFS Southern Global Change Program to model 13 states in the Southeast Program to model 13 states in the Southeast Ecological process model of forest Ecological process model of forest

productivity, species composition, and productivity, species composition, and hydrology (PnET II); predictions of forest hydrology (PnET II); predictions of forest biomass scaled up from the FIA plot level to biomass scaled up from the FIA plot level to the county levelthe county level

Models the removal of forest biomass due to Models the removal of forest biomass due to disturbances including climate change disturbances including climate change impacts, ozone levels, fire, and pestsimpacts, ozone levels, fire, and pests

Climate Spatial

FIA

FIA Plot

PnET-CN

Volume1

Volume2

Volume3

Inventoryand

Harvest

SRTS

Update Acres

Calculate Acres

Harvested

Allocate HarvestCalculate

Growth

Update Inventory

Update Equilibrium

Flow Chart of PEcon

PnET ModificationsPnET Modifications

Added LAI, foliar NPP, wood NPP, root NPP, Added LAI, foliar NPP, wood NPP, root NPP, plot ID, year, month, species and other plot ID, year, month, species and other variables to outputvariables to output

Obtained DWM and FIA plot level data from Obtained DWM and FIA plot level data from Forest Services South Research Station Forest Services South Research Station (Knoxville, TN)(Knoxville, TN)

Computed county center location, elevation, Computed county center location, elevation, and water holding capacity for modeling at and water holding capacity for modeling at county levelcounty level

PnET Linkages to Fire Emissions ModelsPnET Linkages to Fire Emissions Models

Modeling period: 2000-2050; climate data Modeling period: 2000-2050; climate data will be provided by CCSMwill be provided by CCSM

BlueSky-EM uses fuel table with live fuel BlueSky-EM uses fuel table with live fuel and DWM in various size classesand DWM in various size classes

FIA inventory for DWM includes coarse and FIA inventory for DWM includes coarse and fine woody debris, litter, herb/shrubs, slash, fine woody debris, litter, herb/shrubs, slash, duff, and fuel bed depthduff, and fuel bed depth

Estimate future DWM at county level from Estimate future DWM at county level from current DWM, biomass, and related data current DWM, biomass, and related data (latitude, elevation, temperature, RH, (latitude, elevation, temperature, RH, windswinds)

Use SAS data mining tools (e.g., regression, Use SAS data mining tools (e.g., regression, clusteringclustering))

Allocate DWM to species used in BlueSky-EM Allocate DWM to species used in BlueSky-EM based on their biomass proportions at county based on their biomass proportions at county levellevel

PnET Linkages to Biogenic Emissions ModelPnET Linkages to Biogenic Emissions Model

PnET outputs monthly biomass and LAI for PnET outputs monthly biomass and LAI for 203 forest species at plot and county level203 forest species at plot and county level

Will use the MEGAN model to import PnET Will use the MEGAN model to import PnET output for estimating biogenic emissionsoutput for estimating biogenic emissions

MEGAN takes gridded monthly LAI and MEGAN takes gridded monthly LAI and climate data with plant function type and climate data with plant function type and emission factor files to estimate gridded emission factor files to estimate gridded biogenic emissionsbiogenic emissions Includes isoprene (OIncludes isoprene (O33 precursor), mono- precursor), mono-

and sesquiterpenes (PM precursors)and sesquiterpenes (PM precursors)

Fire/Smoke Emissions ModelingFire/Smoke Emissions Modeling BlueSky-EM, a smoke emissions model linked to BlueSky-EM, a smoke emissions model linked to

the Sparse Matrix Operator Kernel Emissions the Sparse Matrix Operator Kernel Emissions Model (SMOKE) for processing and merging with Model (SMOKE) for processing and merging with emissions from other sources (industry, emissions from other sources (industry, transport, biogenic, sea salt, etc.)transport, biogenic, sea salt, etc.)

Directly linked to the FCCS fuel databaseDirectly linked to the FCCS fuel database Will be run at 12-km resolution over the Will be run at 12-km resolution over the

SoutheastSoutheast Future-year fire modeling will link BlueSky-EM Future-year fire modeling will link BlueSky-EM

to:to: The Fire Scenario Builder developed by Pacific

Wildland Fire Lab, and adapted for the Southeast

Ignition Avail

Fire Scenario BuilderFire Scenario Builder

Flammability

Fire frequency & fuel maps

Management RxFire/suppression

MM5 (mesoscale model)

AtmosphericInstability- CAPE

MapTypes-500mb-700mb

Fire Generator

Fire Starts

Fire Sizes

Equations predict fuel moisture in fuel size classes that carry fire.

NFDRSHuman ignitions

(East)

Days since July 1, 2003

Are

a b

urn

ed

(h

a *

10

00

)

0

5

10

15

20

25

30

0 10 20 30 40 50 60

0

5

10

15

20

25

30

Nu

mb

er

of

fire

s

Area burnedNumber of fires

McKenzie et al. (2006) Ecol. Modell.

FSB output for the Pacific Northwest 12-km MM5 domain

Coupled Meteorology-Chemistry Model Coupled Meteorology-Chemistry Model (METCHEM)(METCHEM)

H & V Transport, Cloud Physics & Chemistry,

Gas/Particulate Chemistry, PM

Microphysics (Modal), Dry & Wet Removal (MAQSIP CTM)

Met. Couple(MCPL)

Meteorology

(MM5)

Emissions Processing(SMOKE)

Aerosol Direct Radiative FeedbackAerosol Direct Radiative Feedback

Next StepsNext Steps

ConUS METCHEM simulations for 2002 using ConUS METCHEM simulations for 2002 using best available (RPO) emissions inventorybest available (RPO) emissions inventory

Extract boundary condition inputs for SEExtract boundary condition inputs for SE 12-km Southeastern US simulations with full 12-km Southeastern US simulations with full

system integrationsystem integration Examine model performance in 2002Examine model performance in 2002 Proceed to “snap shot” simulations in 2015, Proceed to “snap shot” simulations in 2015,

2030 and 2050 to analyze effects on key 2030 and 2050 to analyze effects on key climate parametersclimate parameters