Impacts of Wildfires on Particulate Matter in Pima County, Arizona

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1 Impacts of Wildfires on Particulate Matter in Pima County, Arizona Erika K. Wise Department of Geography and Regional Development University of Arizona Air Quality Trends in the Southwest Forum January 9, 26 Tucson, AZ

2 Project Objectives and Approach Improve understanding of the extent to which wildland fires affect particulate matter (PM) and visibility (and by extension, human health and haze) in urban areas PM-visibility links PM-weather weather-fire relationships Approach: Wildfires Tucson, AZ Permanent monitors

3 Where there s s fire Smoke Composition: PM (9%) NO x / VOC / CO PM Health, ecosystem, and visibility effects PM1 / PM2.5 Image source: Dr. Goldsmith

4 Weather and Climate Image source:

5 Previous Studies Previous studies focused on: Dispersion Modeling Monitoring at fire using temporary, portable monitors This study: Permanent monitors in populated area Image source: Jayson Coil

6 Study Area

7 Data Fire Wildfires: and 23 Bullock and Aspen Fires Meteorological Daily ; hourly PM PM1: 24hr averages ; PM1 and PM2.5: hourly Visibility Hourly nephelometer 2-24 All data limited to the May- June-July July fire season

8 Methods GIS buffer used to restrict fires to those that burned >25 acres within 45km radius of Tucson PCA, clustering, and compositing used to examine each day over the time period and each hour during the case study fires Image source: Jayson Coil Overall fire history statistically examined in conjunction with 24hr PM1 and meteorological data Detailed analyses of the Bullock (22) and Aspen (23) fires incorporated 1hr PM1, PM2.5, meteorology, and visibility data

9 Results: Fires Outcome of PCA/clustering displays progression of synoptic conditions coinciding with the MJJ fire season Percent of Days 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % May 1-1 May 11-2 Cluster Type by Date May June 1-1 June 11-2 June 21-3 Date Range July 1-1 July 11-2 July Average monsoon onset date: July 3 Spring: windy Stormy monsoon Spring: still/clear Pre-monsoon heat Calm monsoon

10 Results: Fires Highest (top 5%) of PM days were typically associated with dry/hot or dry/windy conditions Percent of Days 6% 5% 4% 3% 2% 1% PM by Cluster Type Highest PM Days Lowest PM Days All days % Spring: windy Stormy monsoon Spring: still/clear Cluster Pre-monsoon heat Calm monsoon

11 Results: Fires No significant effects of wildfire were detected in Tucson PM concentrations Average PM by Fire Size PM1 (µg/m3) No Fire Days Small Fire Days Medium Fire Days Large Fire Days Fire Category

12 Results: Case Studies 24hr PM 1 (µg/m3) 1hr PM 1 (µg/m3) June 19, 23 : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: PM1 Visibility Aspen Fire PM 1 24hr federal standard 17-Jun 19-Jun 21-Jun 23-Jun 25-Jun 27-Jun 29-Jun 1-Jul 3-Jul 5-Jul 7-Jul 9-Jul 11-Jul Date (23) Scattering Coefficient (M/m) Examining short- term (hourly) data revealed: Spikes in PM concentrations Better correlation with wind direction Fire effects on visibility Time

13 Results: Case Studies Bullock Fire Aspen Fire 3,6 acres May 21-June 5, 22 85, acres June 17-July 12, 23

14 Results: Bullock Fire 1% Bullock Fire 22: Cluster Type by Day 9% 8% Percent of Hours 7% 6% 5% 4% 3% 2% % % 21-May 23-May 25-May 27-May 29-May Date 31-May 2-Jun 4-Jun Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 typical spring hot, dry, windy muggy wind reversal cool, dry, still temperature low high low dew point temp high low relative humidity high low wind speed high low low wind direction SSW SW SW NE SW sea level pressure high low Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 typical spring hot, dry, windy muggy wind reversal cool, dry, still PM 1 Med High Very High Very Low Med PM 2.5 Med Low Very High Low Low Visibility Med Good Poor Med Med

15 Results: Bullock Fire Percent of Hours 6% 5% 4% 3% 2% Bullock Visibility by Cluster Type Poor Visibility Good Visibility All Hours Percent of Hours 6% 5% 4% 3% 2% Bullock PM1 by Cluster Type High PM1 Low PM1 All Hours 1% 1% % Cluster % Cluster Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 typical spring hot, dry, windy muggy wind reversal cool, dry, still PM 1 Med High Very High Very Low Med PM 2.5 Med Low Very High Low Low Visibility Med Good Poor Med Med

16 Results: Aspen Fire 1% Aspen Fire 23: Cluster Type by Day 9% 8% Percent of Hours 7% 6% 5% 4% 3% 2% % % 17-Jun 19-Jun 21-Jun 23-Jun 25-Jun 27-Jun 29-Jun 1-Jul Date 3-Jul 5-Jul 7-Jul 9-Jul 11-Jul Monsoon onset: July 11 Cluster Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Description dry; low pressure fairly moist hot and dry muggy/windy still; fairly cool and dry Temp high low DPTP low high RH low low high Wind Speed high low Wind Direction SSW S W SE NE SLP low high

17 Results: Aspen Fire Aspen Fire PM and Visibility by Cluster PM (µg/m 3 ) PM1 PM2.5 Visibility Visibility (M/m) 5 2 Dry/low pressure Fairly moist Hot/dry Muggy/windy Still/cooler/ dry Cluster

18 Results: PM and Visibility Results: PM and Visibility June 17, 23 PM1 Light Scattering June23 7: : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: Time PM1 (µg/m3) Scattering Coefficient (M/m) June 22, 23 PM1 Light Scattering June23 16: : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: Time PM1 (µg/m3) Scattering Coefficient (M/m) Image source: Gregg Townsend

19 Results: PM and Visibility Results: PM and Visibility June 23, : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: Time PM1 (µg/m3) Scattering Coefficient (M/m) PM1 Light Scattering 23June23 16: July 8, 23 PM1 Light Scattering July23 11: : 2: 4: 6: 8: 1: 12: 14: 16: 18: 2: 22: Time PM1 (µg/m3) Scattering Coefficient (M/m) Image source: Gregg Townsend

20 Conclusions Visibility and PM data correspond well with a few noteworthy exceptions High 24-hr PM correlated with dry conditions; 1-hr 1 PM with humid Tucson s s relatively low PM during the case study fires may have resulted from a wind direction-wind speed relationships

21 Conclusions When examined over time scales of days to years, fires burning near Tucson s s urban-wildland interface do not significantly affect PM air quality in the metropolitan area On shorter (hourly) time scales, spikes of high PM are apparent and are likely influenced by wind speed and direction Suggests fire managers may have more leeway when planning prescribed burns, but shorter- duration air pollution episodes may necessitate additional safeguards for the protection of sensitive groups

22 Current and Future Work Addition of July 25 Florida Fire Comparison to ADEQ smoke model and dispersion model estimates

23 Thank You! Acknowledgments: Climate Assessment for the Southwest project Dr. Andrew Comrie Dr. Michael Crimmins Pima Department of Environmental Quality Arizona Department of Environmental Quality UA Laboratory of Tree- Ring Research Image source: Gregg Townsend