Copyright 2007 Air & Waste Management Association18 em september 2007 awma.org

David M. Randall is a principal air quality scientist with Air Sciences Inc., Golden, CO. E-mail: drandall@airsci.com.

Twelve years after it was signed by the National Interagency Fire Center, the 1995 Fire Policy’s description of the wildland fire situation seems as true today as it was then: “The challenge of managing wildland fire in the United States is increasing in complexity and magnitude. Catastrophic wildfire now threatens millions of wildland acres, particularly where vegetation patterns have been altered by past land-use practices and a cen-tury of fire suppression. Serious and potentially permanent ecological deterioration is possible where fuel loads exceed historical conditions. Enormous public and private val-ues are at high risk, and our nation’s capability to respond to this threat is becoming overextended.”1

Recent analyses by Westerling et al.2 suggest that climate change will at least pro-long the validity of the 1995 Fire Policy’s description of the wildland fire situation and may justify a revision to the description that is even graver: “The overall importance of climate in wildfire activity underscores the urgency of ecological restoration and fuels management to reduce wildfire hazards to human communities and to mitigate ecological impacts of climate change in forests that have undergone substantial alterations due to past land uses.” Westerling et al. also indicate that these conditions may continue for some time.

One of the options available to land managers for ecologi-cal restoration and fuels management is prescribed fire, a fire ignited by management actions to meet specific objectives.3 Projections through 2018 of prescribed fire activity on U.S. wildlands include scenarios of treating up to 3.6 million acres annually in the western United States,4 a significant

increase from the 650,000 acres of prescribed fire in 2002.5 But while land managers continue to face mounting pres-sures to achieve ecological restoration and fuel management objectives through prescribed fires, air quality agencies are requiring land managers to address air quality impacts due to emissions from wildland fires. These air quality impacts include visibility conditions in Class I areas such as national parks and wilderness areas, contributions to exceedances

of ambient air quality standards, and nuisance impacts such as smoke intrusions on

communities.To help resolve some of these

issues, states and tribes in 14 western states are working with the Western Regional Air Partnership (WRAP) to meet the requirements of the federal Regional Haze Rule.6 A

significant amount of resources have been dedicated to characterize

visibility impacts due to fire emissions. These efforts have included the develop-

ment of several fire emissions inventories, regional dispersion modeling, and extensive review

of historical monitoring data. (Significant detail on these analyses can be found online at www.wrapair.org) The WRAP and its Fire Emissions Joint Forum (FEJF) are in the process of compiling technical papers on the major lessons learned from more than a decade of work on fire emissions and air quality. Some of the lessons appear throughout this article.

This article considers the role of smoke to visibility impacts, briefly discusses the limitations of the technical tools available to quantify emissions and impacts due to fire, and identifies a number of tools and resources that can be used to improve the decisions of federal land managers.

FIRE EMISSIONS CONTRIBUTION TO IMPAIRED VISIBILITYA review of the temporal distribution of 2002 wildland fire emissions in the western United States reveals that in summer emissions of fine particulate matter (i.e., less than 2.5 microns in diameter; PM2.5) from fire are almost entirely due to wildfires, whereas in winter, spring, and fall, prescribed fires contribute a higher percentage of PM2.5 emissions (see Figure 1).5 This distribution indicates that visibility impacts in Class I areas during summer will largely be due to unplanned emissions from wildfires, while informed decisions on the planned emissions from prescribed fires may influence visibility

emfeature

Quantitative analyses have identified that emissions from wildland fire contribute to visibility impairment in Class I areas.

Wildland Fire Emissions and Visibility Impacts in the Western United Statesby Dave Randall

Copyright 2007 Air & Waste Management Associationawma.org september 2007 em 19

in spring and fall.The WRAP’s quantitative analyses have identified

that emissions from wildland fire contribute to visibility impairment in Class I areas. Figures 2a and 2b show that light absorbing carbon (LAC) and organic matter (OMC) significantly contribute to light extinction on the 20% worst days at the Grand Canyon National Park (27%) and Mount Rainier National Park (29%).7 Figures 3a and 3b show the results of the WRAP’s Positive Matrix

Factorization analysis for the Colorado Plateau and Northwest for all sampling days. In both areas, smoke is identi-fied as a significant source of aerosols (35–41%) that contribute to regional haze.8 Trends analyses done by the WRAP suggest that the contribution of organic carbon to light extinction is on the rise in many areas of the western United States (see Figure 4).7

The WRAP has also studied the potential for emissions from small fires (i.e., less than 100 acres of tim-ber and brush vegetation types and less than 300 acres of grasslands) to contribute to impaired visibility. While the study to evaluate the sensitivity of the regional visibility modeling (using the Community Multiscale Air Quality Model) to the emissions of small fires is still considered preliminary, results indicate that even emissions due to

small, planned prescribed fire events can contribute to perceptible changes in visibility conditions.9 The model results suggest this is particularly true in cases where small fires occurring during the fall prescribed burning season were located proximate to Class I areas in the modeling domain. Figure 5 shows modeled visibility impacts due to emissions from small fires (expressed in terms of monthly average reconstructed deciviews for November 2002).10 The darker gray and black shaded areas indicate predicted

Figure 1. Temporal distribution of PM2.5 emissions (in tons) from 2002 wildland burning (wildfire and prescribed) in the WRAP.

Fig 1 – direct copy/paste from EXCEL chart too big to email

pasted special as enhanced windows metafile

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Wildfire 47 734 2,566 4,819 204,595 336,335 435,488 455,573 41,061 3,824 4,430 415

Prescribed 959 1,954 2,640 5,061 8,128 2,459 321 144 10,842 17,602 18,083 3,228

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 2. Average light extinction in 20% best, middle 60%, and 20% worst days based on 1997–2002 available data in (a) Grand Canyon and (b) Mount Rainier.

Fig 2a - direct copy/paste from EXCEL chart

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(a) (b)

Lesson Learned #1: We know what to do. Air quality planning objectives and fire emissions management policies have been defined by the WRAP and its stakeholders.

Lesson Learned #2: The crux issue: Getting more prescribed fire and wildland fire use on the landscape and demonstrating reasonable progress toward meeting regional haze goals.

Copyright 2007 Air & Waste Management Association20 em september 2007 awma.org

visibility impacts in the 0.5–1.5 deciview range. Visibility impacts in this range are considered to be perceptible to human observation.11

SOURCES OF UNCERTAINTYDuring its 10 years of working with fire activity data, fire emissions inventory development, and analyses to estimate the contribution of smoke to visibility impacts in Class I areas, the WRAP has identified several factors that create uncertainty in the analyses:

• The accuracy and availability of quality controlled fire activity data with sufficient spatial (latitude/longitude pairs or burn area

perimeters) and temporal (daily fire growth) resolution.

• The precision of fuel loading and fuel consumption estimates for wildfires and prescribed fires.

• The precision and availability of emission factors used to calculate pollutant-specific estimates of emissions.

• Uncertainty in several steps of the regional visibility modeling analyses, including estimating species of pollutants from estimates of PM2.5 and volatile organic compounds, representing plume rise of fire events, and

estimating the effects of air chemistry.

Significant work has been dedicated to increasing confi-dence in these areas. However, substantiating field measure-ments are still lacking.

EFFORTS TO REDUCE VISIBILITY IMPACTS DUE TO PLANNED FIRE EVENTSAs states and tribes in the WRAP region implement programs to meet the requirements of the Regional Haze Rule, many agencies are also develop-ing smoke management pro-grams. To facilitate this process, the WRAP has adopted the Enhanced Smoke Management Program Policy,12 which identi-fies elements of an Enhanced Smoke Management Program (ESMP) that should specifi-cally address visibility impacts. Under the pol icy, ESMPs

Figure 4. Particulate organic matter extinction trends for Class I Areas in the WRAP, 1997–2004.

Figure 3. Sources of aerosol contribution in Class I Areas in (a) the Colorado Plateau and (b) the Northwest.

Fig 3a - direct copy/paste from EXCEL chart

Sulfate-rich Secondary

22%

Urban/Diesel3%

Dust211%

Nitrate-rich Secondary

9%

Smoke35%

Dust120%

Fig 3b – direct copy/paste from EXCEL chart

Smoke41%

Sulfate-rich Secondary

20%

Mobile6%

Oil Combustion

4% Aged Sea Salt8%

Mixed (metals)1%

Nitrate-rich Secondary

8%

Dust12%

(a) (b)

Copyright 2007 Air & Waste Management Associationawma.org september 2007 em 21

meet ecosystem and visibility man-agement objectives. Continuing to augment the decision support tools is critical. Aligning the long-term ecosystem management objectives of land managers and the long-term regional haze planning objectives of the air agencies in the western United States will be a continuing challenge for land management and environmental agencies.

Decision Support Tools in Development

Fire Emissions Tracking System (FETS). Scheduled to launch later this month, the WRAP’s FETS is a database for planned and unplanned fire events. The Web-based design enables efficient data acquisition, stable data storage and availability, real-time coordination among smoke managers, and the cost-effective development of fire

emissions inventories. Included in FETS are methods to estimate fuel consumption and emissions from fire

address emissions and impacts from all types of managed fire (e.g., prescribed burning, agricultural burning) and include a number of elements, such as requirements to minimize emissions from fires, require-ments to consider/use nonburning alternatives, burn/no-burn decisions based upon avoiding visibility impacts to Class I areas using smoke management techniques, monitoring of air quality impacts, efforts to keep the public and other agencies informed about burning activities, and steps to evaluate the effectiveness of the program.

States and tribes generally work with land managers to implement ESMPs to manage day-to-day burning activities and their associated air quality impacts. These programs use real-time decision support tools (e.g., real-time acquisition of fire activity data, fuel consumption and emission estimations, smoke impact predictions, and analysis/application of emissions reduction techniques) that allow land managers to take advantage of relatively small windows of opportunity to conduct planned burns and allow air quality agencies to adequately protect vis-ibility resources in Class I areas. The WRAP and other entities are currently developing and enhancing these decision support tools. This effort will be essential as land managers and environmental managers work to

Lesson Learned #3: Planning inventories for fire have been assembled and are in the WRAP’s emis-sions inventory and modeling systems. Regional haze analyses consider fire emissions as well as emissions from other sources (e.g., industrial, on-road and non-road mobile emissions).

Figure 5. Modeled reconstructed deciview impacts in the WRAP due to emissions from small fires.

.tif @ 300 dpi

The Aerosol & Atmospheric Optics: Visual Air Quality and

Radiation conference will provide a technical forum on the

effects of aerosols on regional, continental and global

scale haze and radiation balance.

Abstracts will be accepted for the conference until

Nov. 17, 2007.

Aerosol &Atmospheric Optics

Conference

For more information on submitting an abstract,visit www.amwa.org/events.

April 28 through May 2, 2008 • Moab, Utah

Call For

Abstracts

Copyright 2007 Air & Waste Management Association22 em september 2007 awma.org

events and tools to estimate emissions averted due to the application of emissions reduction technologies. Users will be able to view fire data on-screen with a mapping tool and query the database for downloads of data into model-ready formats. (See www.wrapair.org/forums/fejf/documents/fts/fts.html.)

BlueSky. BlueSky links computer models of fuel con-sumption and emissions, fire, weather, and smoke dis-persion into one system for predicting the cumulative impacts of smoke from prescribed, wildland, and agricul-tural fires. This project is led by the U.S. Department of Agriculture Forest Service’s AirFire Team and is derived from the ClearSky agricultural burn simulation system operated by Washington State University. Every night, BlueSky obtains a regional meteorological forecast and burn information from state and federal agency burn reporting systems. The merging of these data with models of fuel consumption, emissions, dispersion, and trajectory results in a regional forecast of smoke concentrations for the next two days. (See www.fs.fed.us/pnw/airfire.)

Rapid Access INformation System (RAINS). The U.S. Environmental Protection Agency’s RAINS uses geo-graphical information system (GIS) technology to provide a Web-based window into the GIS world where users can overlay data layers of interest (e.g., topography, census data, Class I areas), zoom and pan around the domain, and query a database for additional data regarding the various layers. (See www.blueskyrains.org.)

BlueSkyRAINS. This tool merges the technology of RAINS with the smoke dispersion information from the BlueSky framework to yield an interactive Web-based regional forecast of smoke concentrations at sensitive receptors. In this way, land managers, regulators, and the general public can view the potential smoke impacts from regional burning activities. (See www.blueskyrains.org.)

Landscape Fire and Resource Management Planning Tools Project (LANDFIRE). LANDFIRE, developed by the Forest Service and U.S. Department of Interior, produces consistent and comprehensive maps and data

describing vegetation, wildland fuel, and fire regimes across the United States. LANDFIRE methodologies are based on the latest science and extensive field-referenced databases and are designed to facilitate national- and regional-level strategic planning and reporting of wildland fire management activities. LANDFIRE meets agency and partner needs for data to support large landscape fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. (See www.landfire.gov.)

SUMMARYThe lessons learned that are sprinkled throughout this article help guide air quality agencies and federal land managers to meet the challenge of introducing more planned fire events to the landscape while continuing to accomplish important regional air quality requirements. Enhancing decision-makers’ access to accurate, reliable, and near-real time fire activity and emissions information is critical. Many technical tools have been and continue to be developed that help prioritize and address planned fire events that may adversely affect air quality in Class I areas. As stakeholders increase their interest in averting air qual-ity emissions and impacts due to fire events, well-directed investment of money, time, and talent will improve the results produced by tools used for effective implementa-tion of fire, smoke, and air quality policies. em

REFERENCES1. 1995 Fire Policy; National Interagency Fire Center (NIFC), Boise, Idaho,

December 1995. See www.nifc.gov/policies/1995_fire_policy.htm.2. Westerling, A.L.; Hidalgo, H.G.; Cayan, D.R.; Swetnam, T.W. Warming and

Earlier Spring Increase Western U.S. Forest Wildfire Activity; Science 2006, 313 (5789); 940-943; DOI: 10.1126/science.1128834; available at www.sciencemag.org/cgi/content/full/313/5789/940.

3. Western Regional Air Partnership–Fire Emissions Joint Forum Workplan; Western Regional Air Partnership, Denver, CO, February 1999. See www.wrapair.org/forums/fejf/documents/group_reports/Wkpl0225.pdf.

4. Development of 2000-04 Baseline Period and 2018 Projection Year Emission Inventories; Project No. 178-8. Conducted by Air Sciences Inc. for Western Regional Air Partnership, Denver, CO, May 2007. See www.wrapair.org/forums/fejf/documents/task7/Phase3-4EI/WRAP_Fire_Ph3-4_EI_Re-port_20070515.pdf.

5. 2002 Fire Emission Inventory for the WRAP Region—Phase II. Conducted by Air Sciences Inc. for Western Regional Air Partnership, Denver, CO, July 2005. See www.wrapair.org/forums/fejf/documents/WRAP_2002_PhII_EI_Re-port_20050722.pdf.

6. Regional Haze Regulations; Final Rule; 40 CFR Part 51 (July 1, 1999). See www.epa.gov/ttn/oarpg/t1/fr_notices/rhfedreg.pdf.

7. TSS Analysis Results, 2006; WRAP Technical Support System, Western Regional Air Partnership, Denver, CO. See http://vista.cira.colostate.edu/TSS/Results/Monitoring.aspx.

8. Positive Matrix Factorization (PMF) is a statistical method that identifies a user-specified number of source profiles (i.e., relative composition particle species for each source) and source strengths for each sample period that reduce the difference between measured and PMF fitted mass concentra-tion. See www.coha.dri.edu/web/general/PMF%20modeling%20for%20WRAP%20COHA.pdf.

9. Small Fire Base A 2002 Sensitivity Scenarios; (12k CMAQ results); Regional Modeling Center, University of California, Riverside, March 2006. See http://pah.cert.ucr.edu/aqm/308/cmaq.shtml.

10. The deciview is a visibility metric based on the light-extinction coefficient that expresses incremental changes in perceived visibility. See http://vista.cira.colostate.edu/improve/Tools/ReconBext/reconBext.htm.

11. Interagency Monitoring of Protected Visual Environments (IMPROVE). See http://vista.cira.colostate.edu/improve/Tools/ReconBext/recon-Bext.htm.

12. Enhanced Smoke Management Program Policy; Western Regional Air Partner-ship, Denver, CO, November 2002. See www.wrapair.org/forums/fejf/documents/esmptt/policy/030115_ESMP_Policy.pdf.

Lesson Learned #5: Tracking fire activity (e.g., acres burned, fuel consumption, emissions, and application of emissions reduction techniques) is key.

Lesson Learned #4: Regional haze modeling reveals important information on impacts from fire and needs to be improved to be a more reliable/effective decision-making tool.