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Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities

Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities. Karsten Baumann, Mei Zheng, Michael Chang, and Ted Russell. Endangered Species Act. Clean Air Act. Measurement Sites 2000-2002. Correlations with Wind Direction: Occurrence. Period 2001+ 02

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Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities

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  1. Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities Karsten Baumann, Mei Zheng, Michael Chang, and Ted Russell

  2. Endangered Species Act Clean Air Act

  3. Measurement Sites 2000-2002

  4. Correlations with Wind Direction: Occurrence Period 2001+ 02 MAY-OCT NOV-APR

  5. Correlations with Wind Direction: Wind Speed Period 2001+ 02 MAY-OCT NOV-APR

  6. Correlations with Wind Direction: O3 Period 2001+ 02 MAY-OCT NOV-APR Daytime only

  7. Correlations with Wind Direction: PM2.5 Period 2001+ 02 MAY-OCT NOV-APR

  8. Seasonal Differences in Diurnal Cycles: O3 & PM2.5

  9. PM2.5 Eceedance for SE winds in Winter 2001

  10. Causes for PM2.5 Eceedance in Winter 2001

  11. Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities Objectives and Outlook • In this initial pilot study, establish understanding of the direct and indirect impact of current burn practices on sub-regional AQ. • Lay foundation for more comprehensive and better focused Phase II Study to optimize burn practices toward minimum AQ impact. • Create results for the benefit of LMBs on other mil installations in the SE-US and beyond. • Learn lessons that help create and implement new revised land management strategies for the benefit of other agencies and institutions that face often times devastating wild fires in other parts of the Nation.

  12. Impacts on local to global scales In the continental U.S. prescribed burns and forest fires contribute ~37 % to the total direct fine PM emissions of ~1 Mio t per year* * Nizich et al., EPA Report 454/R-00-002 (NTIS PB2000-108054), RTP, NC, 2000 • Effects on • Health • Visibility • Air Quality • Climate Do prescribed burns reduce the risk of wild fires?

  13. 45’ x 40’ Fence 4’ 11’ 33’ x 7’ level Platform ~ 1’ above ground Guy wired 8m Tower tilt down 10’ x 12’ Shelter a/c 4 additional 20 A circuit breakers 4’ 14’ 3’ Stair step 4 quadruple outlets on individual breakers 8’ 10’ Gate N OLC site upgrade Research site at Oxbow Meadows Environmental Learning Center upgraded for PM source apportionment and in situ gas phase sampling

  14. PM2.5 Sampling at OLC Table 1: PM2.5 sampler operation at OLC during prescribed burn events at Fort Benning. Table 2: Time series schematic of Hi-Vol and PCM PM2.5 sampler operation from Table 1.

  15. VOC sampling at OLC, Fts. Benning & Gordon Table 3: VOC sampling schedule for Fort Benning (top), and Fort Gordon (bottom), period Jan-Jun 2003.

  16. Difficulties • Are at the mercy of met conditions and (therefore) have to be prepared (flexible). • Sample media collection and delivery time consuming. Collaborators and Contributors CSU-OLC: Jill Whiting, Jim Trostle, site operators Becky Champion, director, “courier” Ft Benning: Polly Gustafson, EMD, reporting to J Brent Jack Greenlee, LMB, reporting to R Larimore Hugh Westbury, SERDP, contractor, reporting to D Price, US Army, Vicksburg, MS Ft Gordon: Allen Braswell, ENRMO, reporting to S Willard Augusta RP: Shari Mendrick, Col.Cty.Eng.Dept., Evans, GA

  17. 3770 acres 1256 acres 937 acres Background Preliminary PCM Results

  18. Progressively increasing fine PM mass and increasing organics fraction Preliminary PCM Results, cont’ed

  19. MorePreliminaryResults:March’03 Increased fine PM mass and organics fraction correlate with increased temperature, solar radiation, and O3, indicating increased oxidizing potential, hence formation of SOA

  20. Still To Do • Collect more samples as progressing into summer • Analyze VOC samples • Analyze POC High-Volume samples • QA/QC all met, gas and PM data • Do source apportionment for select samples • Integrate ECMI met data from Ft Benning • Merge all AQ data with fuel data • Evaluate fuel-type – AQ relationship • Prepare data for model integration • Develop strategy for phase II

  21. For more information • Dr. Karsten Baumann (PI) kb@eas.gatech.edu • Dr. Mei Zheng mzheng@eas.gatech.edu • Dr. Michael Chang chang@eas.gatech.edu • Dr. Ted Russell trussell@ce.gatech.edu Find this presentation as 030429 FAQS Col briefg in ppt-format at http://arec.gatech.edu/Presentations

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