Air Quality and Health Impacts from the Colorado Wildfires in June 2012

Gabriele Pfister David Edwards, Louisa Emmons, Arthur Mizzi, Christine Wiedinmyer

National Center for Atmospheric Research, Boulder, CO

Patrick Reddy and Jane Mitchell Colorado Department of Public Health and Environment, Denver, CO

Yang Liu and Matthew Strickland

Emory University, Atlanta, GA

AQAST Tiger Team

Summer 2012: Colorado experienced one of its most costly and devastating fire seasons

Multiple events: High Park Fire (06/09), Waldo Canyon Fire (06/23), Webber Fire (06/21), Flagstaff Fire(06/26),…

Estimated damage for High Park & Waldo fires: ~ $450M (Rocky Mountain Insurance Information Association)

Event

Fort Collins, CO High Park Fire

• Establish impacts of wildfires on Human health

– Epidemiological analysis based on hospital admissions and other health data

– Bring together air quality managers, health authorities and academic and agency scientists

• Quantify fire impact on AQ

– Support Exceedance Demonstration

• Prerequisite –

Accurate information about surface AQ and exposure

Objectives

WRF-Chem over the Western U.S. 5-week 6/1-7/6, 2012 (summer) 12x12 km2 down to 4x4 km2

WRF/DART Met-Assimilation -> provide best possible meteorology

Evaluation: satellite and surface observations Challenges: Front Range AQ impacted by

• Complex topography and flow patterns • Diverse sources (urban, agriculture, oil/gas, fires….) • Long-range transport

Fires: Highly variable source; localized impacts Highly accurate representation of fire impacts needed Limited data set for evaluation

Methodology

• Surface: • CDPHE/EPA Surface Network (O3, PM2.5, PM10, NO2) • Operational Met Data (NCAR DTC)

• Research Continuous Operations: • NOAA Ozone Sonde

• Field Campaign: • NCAR/NSF/DC-3 (some sampling of high altitude fire plumes)

• Satellite Data • MOPITT CO • IASI CO and O3 • OMI NO2 • MODIS AOD • MISR AOD and Plume Height • CALIOP Extinction Coefficient and Aerosol Type Profiles

Project Status

• Modeling Studies with different emissions & meteorology • While overall nudging and assimilation provide similar statistics,

data assimilation provides a more balanced simulation and seems to perform slightly better in specific transport events

• Anthropogenic emissions: NEI 2011 projection high, improvement with 2008 Colorado specific inventory

• Fire Emissions Improvements • Standard FINN emissions too low and area burned

underestimated by factor 2 compared to independent data Improvements: Area burned calculations from SMARTFIRE

• Meeting of Project Collaborators on 16 April in Denver • CDPHE, Emory, NCAR

• Health Study • proposal submitted to Emory Institutional Review Board,

under review – approved as of this morning

Project Status

• Modeling Studies with different emissions & meteorology • While overall nudging and assimilation provide similar statistics,

data assimilation provides a more balanced simulation and seems to perform slightly better in specific transport events

DART/WRF-Chem – Met Assimilation Domain-wide Statistics

July 4 Transport Event

17 UTC

WRF-Chem Nudging

WRF-Chem DART

RAP 13 km Analysis (Credit P. Reddy, CDPHE)

High ozone conditions: Weak cool front, shallow PBL, warm temperatures, upslope flow, clear skies

“Did smoke make O3 worse or reduce it ?” Note: different model versions

Project Status

• Modeling Studies with different emissions & meteorology • While overall nudging and assimilation provide similar statistics,

data assimilation provides a more balanced simulation and seems to perform slightly better in specific transport events

• Anthropogenic emissions: NEI 2011 projection high, improvement with 2008 Colorado specific inventory

CO Inv. 2008: CDPHE, ENVIRON and Alpine Geophysics

WRF-Chem – Emissions Anthropogenic

Note: OMI data impacted by row anomaly; Filtering applied based on XTrackQualityFlag;

NEI 2011

Colorado Inv. Fire * 2

Tropospheric NO2 (1e14 cm-2)

OMI NO2

WRF-Chem

WRF-Chem – Emissions Anthropogenic

EPA CO_EI2008 NEI2011

EPA CO_EI2008 NEI2011

Adams/Welby (39.83N -104.9W)

Denver CAMP (39.75 N -104.9W)

NO2 Measurements: www.epa.gov/ttn/airs/airsaqs/detaildata/downloadaqsdata.htm

Project Status

• Modeling Studies with different emissions & meteorology • While overall nudging and assimilation provide similar statistics,

data assimilation provides a more balanced simulation and seems to perform slightly better in specific transport events

• Anthropogenic emissions: NEI 2011 projection high, improvement with 2008 Colorado specific inventory

• Fire Emissions Improvements • Standard FINN emissions too low and area burned

underestimated by factor 2 compared to independent data Improvements: Area burned calculations from SMARTFIRE

FINN – Fire Inventory from NCAR (C. Wiedinmyer) • Difference from FINN Default

– Instead of using MODIS Fire Detections and assuming area burned, used SMARTFIRE output

• SMARTFIRE – Used GEOMAC fire perimeters and HMS fire detections

(from MODIS, AVHRR and GOES) – Processed together to get daily fire location and area burned – Processed by Sean Raffuse (Sonoma Technology)

• HMS files from Mark Ruminski (NOAA)

• Land Cover data, emission factors and processing as in default FINN

WRF-Chem – Emissions Fire

Organic Carbon Fire Emissions 06/01-07/04

FINN/Standard FINN/Smartfire

WRF-Chem – Emissions Fire

High Park Fire, CO

Date Area (1e3 acres)

Contained

06/10 20 0%

06/12 43 0%

06/14 49 15%

06/16 55 45%

06/20 70 55%

06/25 83 55%

06/30 87 100%

http://fam.nwcg.gov/fam-web/hist_209/report_list_209

FINN/Std. FINN/Smartfire: High Park Fire

Surface PM2.5 Fort-Collins-CSU-E

FINN/Standard FINN/Smartfire

Surface PM2.5 All CO sites

Obs FINN/Standard FINN/Smartfire

CALIOP Ext. Coeff. - Vertical Smoke CALIOP : Maria val Martin, CSU

CALIOP Extinction Profiles over Colorado

Data Assimilation and WRF-Chem Improvements

Can modeling alone provide required accuracy for health and exceedance study?

Additional Methods:

Fusion product from WRF-Chem and other data

sources to support epidemiological studies Analysis of residual + model fire tracers

Next Steps & Methods

Fusion Product Health impacts from wildfire PM, California, Summer 2008

Collaborative Project with Colleen Reid and Mike Jerrett, UC Berkely

Land Use Regression models with monitored PM2.5 as dependent variable Predictors: • Spatiotemporal: AOD (GASP, MODIS, STI),

WRF-Chem • Other covariates: Meteorology,

land-use characteristics,elevation, traffic metrics, time and space indicators

Figures: C. Reid

Fusion Product

Figures: C. Reid

Residual Method Jaffe et al., submitted to ES & T “Impact of Wildfires on Ozone Exceptional Events in the Western U.S.”

• Statistical model to estimate MD8A as function of several meteorological and temporal variables (Data set: Jun-Sep 2000-2012)

• Statictical Model explains 60%, 52% and 27% of the variability in daily MDA8 for Salt Lake City, UT; Boise, ID; and Reno, NV

Reno, NV 2008

Observed MDA8

WRF-Chem MDA8

WRF-Chem O3 Fire Tracer

Residual

EXTRAS

Other Updates

Other Updates

Other Updates

Regional Air Quality Climate Simulations with WRF-Chem

Climate Emissions Chemistry

Present 2000 yes

Future 2050 RCP 8.5 yes

Future 2000 yes

Future none no

• 12 years/simulation • April-September • 12 x 12 km2

Other Updates

Western States Air Resources Council (WESTAR) Wildfire and Ozone Exceptional Events Meeting

March 5-6, 2012 in Sacramento, CA Goals: • Reach a common understanding of the current state of scientific knowledge about ozone

formation from wildfires. • Identify the techniques and existing data sources available to state air quality agencies to

characterize ozone exceedances as exceptional events focusing on the characteristics of fires in the western states.

http://westar.org/exceptionalevents.html

Other Updates

Smoke Modeling Workshop March 28, 2012 in Golden, CO

(U.S. Forest Service/Region 2, CDPHE/APCD, Colorado Forest Restoration Institute (CFRI),

Southern Rockies Fire Science Network(SRFSN), The Nature Conservancy, and others) Goal: develop a current understanding of smoke models and modeling capabilities, and to develop agreement on how to evaluate applicability of smoke production and dispersal models for use in Colorado. Topics: • In what way can models be used to supplement the experience-based model that currently

specifies permit conditions issued by the Air Pollution Control Division (APCD), Colorado Department of Public Health and Environment?

• In what way can models supplement the burner’s decision making processes, specifically impacting the go/no-go decision?

• What needs to be done to evaluate these models? • What is the potential of models to measure cumulative smoke impacts from multiple

burns?

Ash Creek Fire, MT

Date Area (1e3 acres)

Contained

06/26 40 0%

06/27 110 5%

06/30 157 25%

07/01 170 40%

07/04 244 50%

07/11 249 100%