Scholarly article on topic 'Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone'

Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone Academic research paper on "Earth and related environmental sciences"

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{Wildfire / PAH / VOC / "Fort McMurray" / Ozone / "Air quality"}

Abstract of research paper on Earth and related environmental sciences, author of scientific article — Gregory R. Wentworth, Yayne-abeba Aklilu, Matthew S. Landis, Yu-Mei Hsu

Abstract During May 2016 a very large boreal wildfire burned throughout the Athabasca Oil Sands Region (AOSR) in central Canada, and in close proximity to an extensive air quality monitoring network. This study examines speciated 24-h integrated polycyclic aromatic hydrocarbon (PAH) and volatile organic compound (VOC) measurements collected every sixth day at four and seven sites, respectively, from May to August 2016. The sum of PAHs (ΣPAH) was on average 17 times higher in fire-influenced samples (852 ng m−3, n = 8), relative to non-fire influenced samples (50 ng m−3, n = 64). Diagnostic PAH ratios in fire-influenced samples were indicative of a biomass burning source, whereas ratios in June to August samples showed additional influence from petrogenic and fossil fuel combustion. The average increase in the sum of VOCs (ΣVOC) was minor by comparison: 63 ppbv for fire-influenced samples (n = 16) versus 46 ppbv for non-fire samples (n = 90). The samples collected on August 16th and 22nd had large ΣVOC concentrations at all sites (average of 123 ppbv) that were unrelated to wildfire emissions, and composed primarily of acetaldehyde and methanol suggesting a photochemically aged air mass. Normalized excess enhancement ratios (ERs) were calculated for 20 VOCs and 23 PAHs for three fire influenced samples, and the former were generally consistent with previous observations. To our knowledge, this is the first study to report ER measurements for a number of VOCs and PAHs in fresh North American boreal wildfire plumes. During May the aged wildfire plume intercepted the cities of Edmonton (∼380 km south) or Lethbridge (∼790 km south) on four separate occasions. No enhancement in ground-level ozone (O3) was observed in these aged plumes despite an assumed increase in O3 precursors. In the AOSR, the only daily-averaged VOCs which approached or exceeded the hourly Alberta Ambient Air Quality Objectives (AAAQOs) were benzene (during the fire) and acetaldehyde (on August 16th and 22nd). Implications for local and regional air quality as well as suggestions for supplemental air monitoring during future boreal fires, are also discussed.

Academic research paper on topic "Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone"

Accepted Manuscript

Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone

Gregory R. Wentworth, Yayne-Abeba Aklilu, Matthew S. Landis, Yu-Mei Hsu

PII: S1352-2310(18)30019-0

DOI: 10.1016/j.atmosenv.2018.01.013

Reference: AEA 15772

To appear in: Atmospheric Environment

Received Date: 2 June 2017 Revised Date: 4 December 2017 Accepted Date: 7 January 2018

Please cite this article as: Wentworth, G.R., Aklilu, Y.-A., Landis, M.S., Hsu, Y.-M., Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone, Atmospheric Environment (2018), doi: 10.1016/j.atmosenv.2018.01.013.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

2016 Fort McMurray Wildfires

Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone

Gregory R. Wentwortha, Yayne-Abeba Aklilua, Matthew S. Landisb, and Yu-Mei Hsuc

^Environmental Monitoring and Science Division, Alberta Environment and Parks, 10th Floor 9888 Jasper Ave. NW, T5J 5C6, Edmonton, AB, Canada

bUS Environmental Protection Agency, Office of Research and Development, Research Triangle Park, 27709, NC, USA

cWood Buffalo Environmental Association, 100-330 Thickwood Blvd., T9K 1Y1, Fort McMurray, AB, Canada

Correspondence to: G. R. Wentworth (greg.wentworth@gov.ab.ca; T: +1-(780) 229-7236; F: +1-(780) 702-0169)

Highlights

• Atmospheric PAHs and VOCs were characterized during and after a boreal megafire

• Daily averaged EPAHs increased from ~50 ng m- up to 2900 ng m- during the fire

• EVOCs had minor-to-moderate enhancement from ~46 ppbv up to 190 ppbv

• Normalized excess enhancement ratios were calculated for 20 VOCs and 23 PAHs

• Daily benzene and acetaldehyde approached or exceeded hourly air quality objectives

Keywords

Wildfire; PAH; VOC; Fort McMurray; Ozone; Air Quality

Abstract

During May 2016 a very large boreal wildfire burned throughout the Athabasca Oil Sands Region (AOSR) in central Canada, and in close proximity to an extensive air quality monitoring network. This study examines speciated 24-hour integrated polycyclic aromatic hydrocarbon (PAH) and volatile organic compound (VOC) measurements collected every sixth day at four and seven sites, respectively, from May to August 2016. The sum of PAHs

(EPAH) was on average 17 times higher in fire-influenced samples (852 ng m- , n = 8),

1 relative to non-iire lnnuencea samples (50 ng m , n = 04). Diagnostic pah ratios in iire-

2 influenced samples were indicative of a biomass burning source, whereas ratios in June to

3 August samples showed additional influence from petrogenic and fossil fuel combustion. The

4 average increase in the sum of VOCs (EVOC) was minor by comparison: 03 ppbv for fire-

5 influenced samples (n = 10) versus 40 ppbv for non-fire samples (n = 90). The samples 0 collected on August 10th and 22nd had large EVOC concentrations at all sites (average of 123

7 ppbv) that were unrelated to wildfire emissions, and composed primarily of acetaldehyde and

8 methanol suggesting a photochemically aged air mass. Normalized excess enhancement ratios

9 (ERs) were calculated for 20 VOCs and 23 PAHs for three fire influenced samples, and the

10 former were generally consistent with previous observations. To our knowledge, this is the

11 first study to report ER measurements for a number of VOCs and PAHs in fresh North

12 American boreal wildfire plumes. During May the aged wildfire plume intercepted the cities

13 of Edmonton (~380 km south) or Lethbridge (~790 km south) on four separate occasions. No

14 enhancement in ground-level ozone (O3) was observed in these aged plumes despite an

15 assumed increase in O3 precursors. In the AOSR, the only daily-averaged VOCs which 10 approached or exceeded the hourly Alberta Ambient Air Quality Objectives (AAAQOs) were

17 benzene (during the fire) and acetaldehyde (on August 10th and 22nd). Implications for local

18 and regional air quality as well as suggestions for supplemental air monitoring during future

19 boreal fires, are also discussed.

20 1 Introduction

21 Wildfires are a common occurrence in many regions of the world and can release significant

22 quantities of trace gases and particulate matter to the atmosphere (Andreae and Merlet, 2001).

23 As a result, wildfires often degrade air quality on large spatial scales leading to observable

24 health and ecological impacts (e.g., Henderson and Johnston, 2012; Langmann et al., 2009;

25 Stephens et al., 2014). There is strong evidence for an increasing risk of very large wildfires 20 (>5,000 ha) as a result of climate change (Barbero et al., 2015 and references therein).

27 Among other pollutants, polycyclic aromatic hydrocarbons (PAHs) and volatile organic

28 compounds (VOCs) are emitted from wildfires (e.g., Hatch et al., 2017; Jenkins et al., 1990).

29 Some of these PAHs and VOCs are known or suspected carcinogens, and can be toxic at

30 relatively moderate levels. Furthermore, VOCs undergo photochemical oxidation to form

31 secondary organic aerosol (SOA) and ozone (O3), the latter of which involves a series of

32 complex, non-linear reactions involving nitrogen oxides (NOx) (Seinfeld and Pandis, 2010).

1 Numerous studies have observed significant increases in ground-level O3 in aged wildfin

2 plumes due to enhanced VOCs and NOx (Jaffe and Wigder, 2012; and references therein).

3 Despite these potential effects, a review by Reisen and Brown (2006) emphasized that the

4 majority of studies examining health impacts of wildfire smoke have focused on inhalation of

5 fine particulate matter (PM25), and generally give less attention to potential effects of PAHs

6 and VOCs.

7 The magnitude of enhancement and speciation of PAHs and VOCs near the flame front and in

8 wildfire plumes can vary greatly since both are dependent on several factors, such as fuel

9 loading, fuel type, burning conditions, distance to fire, and meteorology (Andreae and Merlet,

10 2001; Jenkins et al., 1996). For instance, Aditama (2000) measured PAH concentrations 3-65

11 times higher than normal during a smouldering peat wildfire haze episode in Jakarta,

12 Indonesia. Lower molecular weight PAHs were typically enhanced more than higher

13 molecular weight PAHs. Acetone levels were also elevated during the event, possibly due to

14 photochemical reactions of precursor VOCs or direct wildfire emissions (Akagi et al., 2011).

15 On the other hand, Ward et al. (2005) did not detect higher levels of PAHs in flaming mixed

16 forest wildfire plumes in Montana. The authors attributed this to rapid photolytic degradation

17 of PAHs during the ~100 km transport between the fire front and sampling location. Increased

18 concentrations of BTEX (benzene, toluene, ethylbenzene and xylene) were not observed

19 either, possibly due to large emissions from nearby fossil fuel sources. The authors did report

20 large increases in PM2.5 and phenolic compounds during the wildfire, yet modest increases in

21 other VOCs.

22 A wildfire haze episode in Brunei in 1998 resulted in high concentrations of benzene (up to

-3 -3 -3

23 25 |ig m- ), formaldehyde (5-22 |ig m- ), butyraldehyde (3-72 |ig m- ) and the sum of PAHs

24 (EPAHs, 1-34 |ig m- , primarily as naphthalene) (Muraleedharan et al., 2000). During the

25 event, benzene and EPAHs exceeded "available recommendations" for ambient

26 concentrations, although the levels and references for these recommendations were not

27 provided. Reinhardt and Ottmar (2004) measured several VOCs directly adjacent to a wildfire

28 flame front to assess exposure of firefighters to air pollutants in the western United States. At

29 the flame front, average mixing ratios of acrolein (7 ppb), benzene (16 ppb), and

30 formaldehyde (40 ppb) were substantial.

31 The 2016 Fort McMurray Horse River Wildfire was one of the largest wildfires in Canada,

32 eventually consuming ~589, 600 ha (nearly 6,000 km ) of land throughout Northern Alberta

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2 with the two most abundant tree species being Jack Pine (Pinus banksiana) and Black Spruce

3 (Picea mariana). The wildfire started on May 1, 2016 in the central part of the Athabasca Oil

4 Sands Region (AOSR), just southwest of Fort McMurray, Alberta. By May 3 the fire began to

5 overwhelm the city, prompting an evacuation of roughly 80, 000 people and causing a large

6 number of structural fires throughout the city. Within three weeks the fire grew to more 3, 000

7 km (Simms, 2016) by which point the fire had moved east beyond Fort McMurray towards

8 the Saskatchewan border. Around 2,400 commercial and residential structures in Fort

9 McMurray were burned, primarily during the period of May 4-5. Hence, it is unlikely that

10 samples obtained outside this timeframe were significantly influenced by emissions from

11 structural fires. Although Fort McMurray re-entry began on June 1, 2016 the wildfire was not

12 officially under control until July 4, 2016. The AOSR encompasses ~144, 000 km2 of north-

13 eastern Alberta and contains several significant oil sands mining operations surrounded by

14 boreal forest and wetlands. The Wood Buffalo Environmental Association (WBEA) operates

15 a network of over 20 air quality monitoring stations throughout the AOSR, which remained

16 operational throughout the Fort McMurray wildfire.

17 It is rare for a very large wildfire to occur adjacent to an extensive air monitoring network,

18 where it is possible to analyse near-fire pollutant levels against well-documented historical

19 (non-fire influenced) values. Motivated by the relatively fewer number of studies regarding

20 the air quality implications of PAHs and VOCs from wildfires, data from the WBEA air

21 quality monitoring network was used to examine these species during and after the Horse

22 River Wildfire. The specific goals of this study were to:

23 1) Compare concentrations, speciation, and sources of PAHs and VOCs during wildfire

24 influenced periods to non-wildfire periods (Sections 3.1 and 3.2)

25 2) Determine if the wildfire plume enhanced O3 concentrations 100s of km downwind

26 (Section 3.3)

27 3) Assess the air quality implications of PAH and VOC enhancement during and after the

28 fire by comparing observed concentrations to acute air quality metrics (Section 3.4)

29 4) Provide recommendations for sampling and analyses during subsequent boreal

30 wildfires (Section 4)

2 Materials and Method

2 2.1 Air Monitoring Stations

3 Integrated PAH and VOC samples, as well as various continuous atmospheric measurements

4 are routinely taken at the following air monitoring stations (AMS) throughout the AOSR:

5 Bertha Ganter-Fort McKay (AMS 1; 111.040° W, 57.189° N), Fort McMurray Patricia 0 Mclnnes (AMS 0; 111.470° W, 50.741° N), Fort McMurray Athabasca Valley (AMS 7;

7 111.390° W, 50.733° N), Barge Landing (AMS 9; 111.000° W, 57.198° N), Fort McKay

8 South (AMS 13; 111.053° W, 57.149° N), Anzac (AMS 14; 111.037° W, 50.449° N), and

9 CNRL Horizon (AMS 15; 111.740° W, 57.304° N). Figure 1 shows the monitoring site

10 locations, area burned by the 2010 Horse River Wildfire, and the footprint of major oil sands

11 facilities. AMS 0 and 7 are situated in Fort McMurray (pop. ~01, 000), and AMS 1 and 14 are

12 in the much smaller communities of Fort McKay (pop. ~500) and Aznac (pop. ~000),

13 respectively. The AMS 9, AMS 13 and AMS 15 sites are adjacent to oil sands facilities. For

14 the duration of the intensive wildfire period (operationally defined as May 1-25, 2010) AMS

15 0, AMS 7 and AMS 14 were in close proximity (<10 km) to the fire edge and, in some 10 instances, surrounded by the fire.

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2 Figure 1. Map of the AOSR showing the 7 monitoring stations that measure PAHs and VOCs,

3 as well as the oil sands production footprint, Fort McMurray, and Horse River Wildfire burn

4 area.

5 WBEA maintains and operates the AMS sites on behalf of Alberta Environment and Parks

6 (AEP). Quality-controlled data from the AMS sites used in this study are publicly available

7 at: http://wbea.org/network-and-data/historical-monitoring-data (WBEA, 2016). The phase of

8 the fire (smouldering versus flaming) is commonly investigated by calculating the modified

9 combustion efficiency (McMeeking et al., 2009); however, this could not be calculated since

10 none of the AMS sites monitor CO or CO2, except for a lone CO monitor at AMS 7.

11 Routine measurements of air pollutants are also conducted at air quality monitoring sites in

12 other parts of the province on behalf of AEP. Quality-controlled data from the Edmonton-

13 Woodcroft site (113.563° W, 53.564° N) and Lethbridge site (112.801° W, 49.716° N) are

14 publicly available at: http://airdata.alberta.ca/aepContent/Reports/DataReports.aspx (AEP,

15 2016a). Edmonton (pop. ~796,000) and Lethbridge (pop. ~97,000) are approximately 380 km

16 and 790 km south of Fort McMurray, respectively. These sites were chosen to examine

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concentrations as they were advected through urban centres. Quality-controlled data for this study were used at the above sites for May 1 to August 31, 2016, inclusive.

2.2 PAH and VOC Integrated Measurements

Measurements of PAHs and VOCs at the AMS sites were conducted according to the one-in-six-day sampling schedule of the National Air Pollution Surveillance (NAPS) program. PAH samples were collected at AMS 1, AMS 6, AMS 7 and AMS 14 over a 24-hour period from midnight-to-midnight every sixth day using a polyurethane foam (PUF) sampling train in a high-volume air sampler (TE-1000, Tisch Environmental) with no size cut-off. The sampling train consisted of a glass fibre filter followed by a PUF/XAD-2/PUF sandwich to capture both

particulate-bound and gas-phase PAHs at a flow rate of 316 m day- . Filters and sorbents were extracted with a 70:30 hexane:acetone mixture and quantified for 23 PAHs using a Gas Chromtograph/Mass Spectrometer (GC-MS, Agilent GC7890A and MS5975C) in accordance with EPA TO-13A (US E.P.A., 1999a). Data were blank and recovery corrected. Some PAH samples could not be collected on May 6th (AMS 1, AMS 14), May 12th (AMS 14), and May 24th (AMS 1, AMS 6, AMS 14) due to limited resources and logistical difficulties during the intensive wildfire period.

A suite of 65 VOCs were quantified at all seven AMS locations in Fig. 1 using the same one-in-six-day schedule. Samples were collected over 24-hours (midnight-to-midnight) using an evacuated canister and a flow of 10.0 mL min-1 (TE-123, Tisch Environmental). Speciated VOCs were quantified off-line using a GC-MS. Some VOC samples were not collected during the intensive wildfire period due to restricted access: May 6th (AMS 1), May 12th (AMS 14), and May 24th (AMS 9).

Method detection limits were calculated based on the U.S. Method TO-15 (U.S. EPA, 1999b) and are presented in Supplementary Tables S1 and S2 for PAHs and VOCs, respectively. PAHs reported below the method detection limit (MDL) in the data were flagged but still included in the analyses as reported, whereas VOCs below the MDL were set to zero.

2.3 Continuous Measurements

Ancillary continuous measurements were used to help unambiguously identify periods of wildfire influence at AMS sites in the Fort McMurray area (WBEA, 2016), as well as at the

1 aii quality monitoring sites in Edmonton and Lethuiidge (ae±~, 2016a). These ambient aii

2 quality data collected are subject to monitoring and reporting requirements outlined in the

3 provincial Air Monitoring Directive (AEP, 2016b). For May to August 2016, hourly averaged

4 quality assured data were used for PM25 mass (all sites, except AMS 9), ammonia (NH3; AMS

5 1 and AMS 6), non-methane hydrocarbons (NMHC; AMS 7 and AMS 14), total

6 hydrocarbons (THC; AMS 9, AMS 13 and AMS 15), carbon monoxide (CO; AMS 7), NOx

7 (Woodcroft and Lethbridge), and O3 (Woodcroft and Lethbridge). These ancillary species at

8 AMS locations were chosen because their ambient concentrations are greatly elevated in

9 wildfire plumes, especially PM25 and NH3 (Andreae and Merlet, 2001; Benedict et al., 2017;

10 Landis et al., 2017; Langmann et al., 2009). The NOx and O3 data were obtained for

11 Edmonton and Lethbridge to assess downwind O3 production. Information on the continuous

12 analysers as well as their detection limits are given in Supplementary Table S3. It should be

13 noted that the continuous NOx instruments utilized in the WBEA network may suffer from a

14 positive interference of other gaseous oxidized nitrogen species (e.g., HNO3, HONO, PAN);

15 however, in these urban locations it is likely that NOx dominates the gaseous NOy budget.

16 The photometric O3 instruments are based on UV absorption at 254 nm, and suffered from an

17 obvious large positive interference (e.g., nocturnal O3 > 250 ppbv when NO > 15 ppbv) at

18 AMS sites during periods of intense wildfire smoke which prohibited a near-flame front

19 analysis of O3 concentrations (Landis et al., 2017). This phenomenon likely results from other

20 specie(s) in the plume that absorb light at 254 nm, such as nitro- or oxidized aromatics

21 (Dunlea et al., 2006).

22 2.4 HYSPLIT back-trajectories

23 Potential wildfire plumes at the Edmonton and Lethbridge sites were identified with PM25

24 mass measurements. The Hybrid Single-Particle Lagrangian Integrated Trajectory

25 (HYSPLIT) model was then used to compute air parcel back-trajectories to aid in

26 confirmation of the Horse River Wildfire influenced periods (Stein et al., 2015). Back-

27 trajectory simulations were calculated using NARR (North American Regional Reanalysis)

28 meteorology with 32-km resolution at air parcel arrival heights of 100 m and 500 m. For days

29 potentially influenced by wildfires (e.g., large PM25 spikes) the model was run backwards for

30 120 hours starting at the peak of PM25.

NASA's Fire Inform

used to either confirm or refute the presence of wildfires along the HYSPLIT back-trajectories (NASA, 2016). The web fire mapper tool provides near-real time and historical maps of wildfires at 1 km resolution using satellite-based instruments (MODIS and VIIRS). A combination of in situ measurements, HYSPLIT and FIRMS determined whether a particular period at Edmonton or Lethbridge sites was influenced by the Horse River Wildfire plumes.

7 3 Results and Discussion

8 "Fire-influenced" samples were defined as May samples taken on a day when the hourly

9 average PM25 exceeded 25 |ig m- for at least one hour during the 24-hour PAH or VOC

10 sampling window. The same PM25 threshold was used by Bytnerowicz et al. (2016) for

11 distinguishing "fire periods" and "non-fire periods" during the 2011 Richardson fire in the

12 AOSR. It is important to note that this distinction cannot account for the degree to which a

13 sample was influenced, although a qualitative assessment can be made by examining ancillary

14 measurements in Fig. 2. Furthermore, some days with all hourly averages below 25 |ig m-

15 may still have some minor-to-moderate fire-influence. Table 1 summarizes the fire-influenced

16 VOC and PAH samples taken during May 2016 at the seven AMS sites.

17 Table 1. Fire-influenced integrated samples

Date AMS 1 AMS 6 AMS 7 AMS 9* AMS 13 AMS 14 AMS 15

May 6 Yes Yes Yes N/A Yes - Yes

May 12 No Yes Yes N/A No - No

May 18 No Yes Yes N/A No Yes Yes

May 24 Yes Yes Yes N/A Yes Yes Yes

May 30 No No No N/A No No No

18 *N/A since AMS 9 samples VOCs but does not have a continuous PM25 monitor

19 '-' indicates PM25 instrument was offline

20 3.1 PAHs

21 Figure 2 shows a time series of the sum of 23 PAHs (EPAH) at each site, as well as daily-

22 averaged ancillary measurements (PM25, NH3, NMHC) to visually indicate periods inundated

23 by wildfire smoke. Wildfire-influenced samples show a clear increase in EPAH by up to a

24 factor ~60 relative to non-fire periods (June to August). The average EPAH for fire-

25 influenced samples (n = 8) was 852 ng m- (interquartile range = 300-980 ng m- ), compared

26 to only 50 ng m- (interquartile range = 13-54 ng m- ) for non-fire influenced samples (n =

27 64). EPAH enhancement in fire-influenced samples ranged from 4-58 times, similar to the 3-

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Figure 2. Time series of 24-hour averaged ZPAH (grey bars, left axis), PM2 5 mass (red dashed line, left axis), and NH3 (orange line, right axis) or NMHC (brown line, right axis). Measurements were taken at (a) AMS 1, (b) AMS 6, (c) AMS 7 and (d) AMS 14.

3 . AMS 7_________th

at AMS 7

1 The maximum daily average SPAH was 2883 ng m-3 at AMS 7 on May 6th, shortly after the

2 fire had passed through Fort McMurray on May 4th/5th when structure fires were prevalent

3 throughout the city. The average fire influenced SPAH concentration (852 ng m- ) far

4 exceeded the 2012-2013 SPAH averages (~10-30 ng m- ) previously reported at these sites

5 (Hsu et al., 2015). However, Hsu et al. (2015) did not include naphthalene (NAP) in their total

6 because of low collection efficiency of NAP in their study. The average fire influenced SPAH

7 excluding NAP is 399 ng m- (interquartile range of 110-540 ng m- ), still well above

8 observations by Hsu et al. (2015). The PAH sampling methodology for the WBEA network

9 was altered in 2015 to improve collection efficiency for NAP, but is still likely below 100%.

10 In non-fire influenced samples, the average SPAH (without NAP) at AMS 1, 6 and 7 was16

11 ng m- (interquartile range of 6-18 ng m- ), comparable to the SPAH concentrations reported

12 by Hsu et al. (2015). The higher SPAH concentrations (upwards of 140 ng m- without NAP)

13 at AMS 14 after May 30 are likely the result of local, temperature-dependent emissions of

14 "volatile PAHs" near AMS 14, (Hsu et al., 2015). The enhancement of PAHs in fire-

15 influenced samples was relatively consistent for volatile, semi-volatile, and particulate-bound

16 PAHs (classifications defined by Hsu et al., 2015). A recent study by Schuster et al. (2015)

17 measured bimonthly averages of 17 parent PAHs as well as alkylated PAHs at 17 sites

18 throughout the AOSR for two years. Two bimonthly sampling periods in 2011 were

19 influenced by forest fires with an increase in median SPAH by ~2-5 times (upwards of ~100

20 ng m- ), which was more prevalent at sites closer to the flame front. The Schuster et al. (2015)

21 and this study provide clear evidence of the considerable influence that wildfires impart on

22 PAH concentrations in the AOSR.

23 Figure 3 shows the average relative abundance of the seven most prominent PAH species,

24 excluding NAP which was between 30-80% of SPAH mass. These species were among the

25 most abundant PAHs released from burn experiments of pine and fir biomass (Jenkins et al.,

26 1996). The remaining 17 PAHs were each <3% of the total SPAH mass in all samples.

27 Overall the relative PAH abundances in fire influenced (Fig. 3 a) and non-fire influenced

28 (Figs. 3b and 3c) samples are largely similar. This implies that the emission profiles of major

29 PAHs emitted from the wildfire were similar to other sources in the region. However, one key

30 difference in Fig. 3 is the minor contribution of acenaphthene (ACE, ~3%) in fire influenced

31 samples relative to non-fire influenced samples (~11% at AMS 1, AMS 6 and AMS 7; ~22%

32 at AMS 14). This suggests that the wildfire emitted much less ACE than acenaphthylene

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2 abundance in the fire influenced samples. Although there was an average 3-fold increase in

3 ACE in fire influenced samples, increases for ACY (25-fold), FLE (16-fold) and PHE (154 fold) were much larger. This observation differs from Jenkins et al. (1996) who reported a

5 higher emission factor for ACE than both ACY and FLE during controlled burn experiments

6 of pine and fir under a variety of flaming conditions. This difference could be due to many

7 confounding factors that affect PAH emission factors (e.g., flame intensity, oxygen

8 availability, fuel type). AMS 14 was isolated from the other sites since it was likely

9 influenced by different source(s) (Hsu et al., 2015). On average, there is a higher relative

10 contribution of FLE and ACE at AMS 14 compared to the other three sites, consistent with

11 the evidence from Hsu et al. (2015) showing local source(s) of high-volatility PAHs.

(a) Fire Influenced

Acenaphthene (3%) Acenaphthylene (39%) Anthracene (4%) Chrysene (2%) Fluoranthene (3%) Fluorene (11%) Phenanthrene (29%) Pyrene(3%) Other (5%)

(b) Non-fire Influenced (AMS 1, 6, 7)

Acenaphthene (11%) Acenaphthylene (26%) Anthracene (2%) Chrysene (2%) Fluoranthene (4%) Fluorene (12%) Phenanthrene (31%) Pyrene(4%) Other (8%)

(c) Non-fire Influenced (AMS 14)

Acenaphthene (22%) Acenaphthylene (15%) Anthracene (2%) Chrysene (1%) Fluoranthene (4%) Fluorene (20%) Phenanthrene (31%) Pyrene (2%) Other (4%)

Figure 3. Average relative abundance of PAHs by mass, excluding NAP, for (a) fire-influenced samples at all sites, (b) non-fire influenced samples at AMS 1, AMS 6 and AMS7, and (c) non-fire influenced samples at AMS 14.

PAH diagnostic ratios have been used to aid in source identification in a wide variety of media (Akre et al., 2004; Tobiszewski and Namiesnik, 2012). Table 2 lists diagnostic PAH ratios used in previous studies to distinguish between various source types, although it should be noted that these studies include analyses of multiple media samples (e.g., air, sediments, soil). Despite their utility across different media, these diagnostic ratios are subject to large uncertainties due to the variability in source material, combustion conditions, and chemical

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2 thresholds (Galarneau 2008; Zhang et al., 2005).

3 Table 2. Diagnostic PAH ratios and the typical range for source types

PAH Ratio Threshold Source Type References

FLA/(FLA+PYR) <0.4 0.4-0.5 >0.5 Petrogenic Fossil Fuel Combustion Grass, Wood, Coal Combustion De La Torre-Roche et al. (2009); Tobiszewski and Namiesnik (2012)

I[cd]P/(I[cd]P+B[ghi]P) <0.2 0.2-0.5 >0.5 Petrogenic Petroleum Combustion Grass, Wood, Coal Combustion Tobiszewski and Namiesnik (2012); Yunker et al. (2002)

PHE/ANT <10 >15 Pyrolytic Petrogenic Baumard et al., (1998); Yang (2000); Wnorowski (2017)

4 FLA = fluoranthene, PYR = pyrene, I[cd]P = indeno[1,2,3-c,d]pyrene, B[ghi]P =

5 benzo[g,h,i]perylene, PHE = phenanthrene, ANT = anthracene

6 Figure 4 shows each PAH sample taken in (a) May and (b) June at the four AMS sites plotted

7 as a function of two PAH ratios from Table 2, in addition to the approximate threshold values

8 commonly used to differentiate source types. All ratios in May (Fig. 4a), except one, are ~0.5

9 or above which indicates the dominance of grass/wood/coal combustion. Furthermore, the

10 median (mean) PHE/ANT ratio in fire-influenced samples was 7.6 (8.1) which implies a

11 strong pyrolytic (incomplete combustion) signature. Fig. 4b reveals a wider spread of ratios in

12 June (and frequently lower than ~0.5) relative to May (Fig. 4a), suggesting more impact from

13 non-coal fossil fuel combustion and petrogenic PAH sources. Furthermore, the median

14 (mean) PHE/ANT ratio for June-August samples was 14.5 (14.4). However, there is evidence

15 for contributions from lingering wildfire hotspots after May since the majority of samples in

16 Fig. 4b still have ratios greater than 0.5.

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▲ AMS 14

^ Fossil Fu^l

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Petrogenic

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1-1-1-1-1-1

1.0 0.0 0.2 0.4 0.6 0.8 1.0

l[cd]P / (l[cd]P + B[ghi]P) Ratio

2 Figure 4. FLA/(FLA+PYR) versus I[cd]P/(I[cd]P+B[ghi]P) ratios for (a) May samples and (b)

3 June 2016 samples. AMS sites are distinguished by marker shape and dashed lines denote the

4 ratios used to differentiate various sources.

6 For comparison, Evans et al. (2016) reported average summertime FLA/(FLA+PYR) and

7 I[cd]P/(I[cd]P+B[ghi]P) ratios of 0.40 and 0.35, respectively, in air samples collected near

8 upgrading facilities in the region. Similarly, Wnorowski (2017) observed an average

9 phenanthrene to anthracene (PHE/ANT) ratio of 19 in air samples collected at AMS 13 in

10 August and September 2013. Schuster et al. (2015) reported increasing FLA/(FLA+PYR) and

11 I[cd]P/(I[cd]P+B[ghi]P) ratios at sites further away from AOSR mining facilities. These

12 previous studies show a dominant summertime influence of petrogenic and petroleum PAH

13 sources throughout the AOSR. The shift of all three diagnostic ratios from petrogenic values

14 (previous studies) towards pyrolytic/biomass burning values (this study) further reiterates the

15 prevailing impact of the Horse River Wildfire on ^PAH in May 2016. Hence, these PAH

16 ratios show promise for being able to: (i) distinguish biomass burning from petrogenic

17 influence, and (ii) constrain receptor models such as positive matrix factorization (Norris et

18 al., 2014).

19 3.2 VOCs

20 Figure 5 shows the sum of the 65 VOC mixing ratios (ZVOC) at four sites, in addition to

21 ancillary continuous measurements and OVOC (oxygenated VOC) fraction. Similar figures

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2 below since it did not have a continuous PM2.5 instrument. In contrast to the dramatic increase

3 observed for EPAH in fire-influenced samples, there is only a minor-to-moderate relative

4 increase in EVOC (Fig. 5). Fire-influenced samples (n = 16) had an average EVOC of 63

5 ppbv compared to 46 ppbv for the non-fire influenced samples (n = 90, excluding August 16th

6 and 22nd, see Section 3.2.2). Interquartile ranges for the fire and non-fire influenced samples

7 were 35-79 and 32-53 ppbv, respectively, showing considerable overlap and less variability

8 compared to EPAH.

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Figure 5. Time series of daily-averaged ZVOC (green bars, left axis), PM25 (red dashed-line, left axis), and NH3 (orange line, right axis) or NMHC (brown line, right axis) for (a) AMS 1, (b) AMS 6, (c) AMS 7, and (d) AMS 14. The OVOC fraction (black circles) for VOC samples are shown at the top of each panel.

The average ZVOC for fire-influenced samples at AMS 7 was 112 ppbv - about twice as high as any other site, which could be caused by its proximity to the fire and/or its location in a

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multitude of biogenic and anthropogenic VOC sources in the AOSR (Li et al., 2017). The modest ZVOC increase in fire-influenced samples is comparable to the modest increase observed by Ward et al. (2005) in Montana wildfire plumes. In both cases, a high non-fire VOC baseline may be obscuring the relative increase during fire-influenced periods.

(a) Fire Influenced

▲ Acetaldehyde (14%) A Acetone (13%)

▲ Methanol (41%) Other OVOC(ll%)

A Benzene (3%) A Other HC (18%)

(b) Non-fire Influenced

Acetaldehyde (19%) Acetone (10%) Methanol (42%) Other O VOC (14%) Benzene (0.2%) Other HC (14%)

(c) August 16 and 22

A Acetaldehyde (38%) A Acetone (4%) A Methanol (44%)

Other OVOC (10%) A Benzene (<0.1 %) A Other HC(3%)

Figure 6. Average relative abundance of VOCs in percent v/v for (a) fire-influenced samples, (b) non-fire influenced samples excluding Aug 16 and 22, (c) the August 16 and 22 samples.

10 Figure 6 shows the average relative abundance of VOC on fire influenced days (Fig. 6a), non-

11 fire influenced days (Fig. 6b) and on August 16th and 22nd (Fig. 6c), in order to ascertain

12 whether the VOC "fingerprint" differed between fire and non-fire influenced samples. The

111 C/ 11111 Lit/llV^CLl OCIIIIJJIC/O IjJJlV^dllj lldLl 1U W ti KJ V UL 11 dV^llVJllij IGldllvt LVJ Lilt 11VJ11~111C/ Odllljjlt/O

(average of 0.79 versus 0.86). Major VOC constituents in fire-influenced samples were methanol (37-44%, v/v), acetaldehyde (14-20%), acetone (8-15%), benzene (<1-6%), 1-butene (<1-4%), and formaldehyde (<1-7%). These species are some of the most abundant VOCs emitted from extratropical forest fires and are broadly consistent with previously published emission factors (Andreae and Merlet, 2001; Urbanski 2014). One exception is the minor contribution from formaldehyde, although this could be due to its short atmospheric lifetime. Other VOCs each contributed <3% to measured EVOC.

The similarities between Figs. 6a and 6b and low contribution from HCs suggest significant atmospheric oxidation between emission and sampling. However, Yokelson et al. (1997) observed significant emissions of OVOCs including methanol, formaldehyde, acetic acid and formic acid during the heating (pre-combustion) and smouldering phases of controlled pine burning experiments. The smouldering phase involves less rigorous vertical mixing such that ground-level sampling is typically more sensitive towards smouldering conditions relative to flaming (Andreae et al., 1996). Acrolein, ethane, ethene, propyne, furan, formic acid, and acetic acid were not quantified but have emission factors from pine/spruce similar to, or greater than, methanol, acetaldehyde and acetone (Andreae and Merlet, 2001; Hatch et al., 2017). Further work is required to discern whether atmospheric processing and/or similarities in emission profiles between fire and non-fire sources resulted in comparable compositions dominated by OVOCs.

Figures 5 and S1 reveal high EVOC at all sites for the August 16th and August 22nd samples (average EVOC =123 ppbv). These mixing ratios were about twice as high as the fire-influenced samples, and between 2-5 times larger than other non-fire influenced samples. Furthermore, these two sampling days had: (i) no wildfire influence, (ii) very high OVOC fraction (average = 0.97), and (iii) all AMS sites affected. On average, methanol and acetaldehyde represented 82% of the measured EVOC (Fig. 6c). It is worthwhile to examine August 16th/22nd in detail since acetaldehyde exceeded the provincial air quality objective on these days (see Section 3.5).

In the summertime, acetaldehyde is produced primarily from photochemical reactions of >C3 alkenes, >C2 alkanes, ethanol, propanal and the decomposition of peroxyacetyl nitrate (PAN) (Luecken et al., 2012; Millet et al., 2010). Major sources of methanol include emission from vegetation, methane oxidation, and biomass decay, although the global methanol budget is

10 11 12

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throughout August 16th air arrived from due west and passed over the western coast of British Columbia three days prior while remaining near the surface. In contrast, on August 22nd air was much more locally influenced and had spent the previous three days meandering near the surface within several hundred kilometres of Fort McMurray.

Due to disparate back-trajectories and plethora of acetaldehyde, methanol and precursor sources, it is unclear what the exact origin(s) of the August 16th and 22nd EVOC peaks are. However, the lack of wildfires in late August rules out wildfires as a potential source. It is also unlikely that biogenic emissions were the primary cause since isoprene, a-pinene, and P-pinene (the main biogenic precursors for acetaldehyde) were less than 3% of EVOC. To our knowledge, the only reported acetaldehyde measurements of comparably high concentrations are in areas with large anthropogenic VOC emissions, such as Mexico City (up to 99 ppb; Baez et al., 2000) or vast industrial complexes near Edmonton, Canada (up to 74 ppb; Simpson et al., 2013) and Gumi, South Korea (up to 77 ppb; Seo and Baek, 2011). It is important to note that these previous studies employed shorter integration times (3 hours or less). In addition to direct emissions, facilities in the AOSR are known to be significant sources of acetaldehyde and methanol precursors (Li et al., 2017). Therefore, local photochemically aged anthropogenic VOCs were likely a contributing factor to the episodes of high acetaldehyde and methanol.

20 3.3 Enhancement Ratios

21 Normalizing air pollutant concentrations to a relatively inert tracer gas, such as CO

22 (atmospheric lifetime of ~2 months), is a common method for assessing pollutant emissions

23 from wildfires (e.g., Akagi et al., 2011; Hecobian et al., 2011; Landis et al., 2017; Simpson et

24 al., 2011; Singh et al., 2010). These normalized excess enhancement ratios (ER) are

25 calculated by dividing the excess of pollutant X above background (AX = Xplume - Xbackground)

26 by the excess of inert tracer Y (AY = Yplume - Ybackground). For this study, hourly CO

27 observations at AMS 7 were averaged to daily values to match the PAH and VOC

28 observations. The median CO mixing ratio on non-fire influenced sampling days (117 ppbv)

29 was used as the background CO value. Background mixing ratios for specific PAHs and

30 VOCs were calculated in the same fashion. The CO monitor was offline for six hours on May

31 12th so this fire influenced sample is excluded from ER calculations.

2 limit in all three of the remaining fire influenced samples (May 6th, 18th, and 24th). For

3 comparison, the average ERX/CO from several aircraft studies that sampled VOCs in fresh

4 boreal wildfire plumes are also given in Table 3.

5 Table 3. Comparison of VOC Enhancement Ratios (in ppb ppm-1 CO) for fire influenced

6 samples at AMS 7 to literature values for fresh North American boreal forest wildfires

VOC May 6 May 18 May 24 Average Simpson et al. (2011) Hecobian et al. (2011) Singh et al. (2010)

1,3-Butadiene 0.36 0.15 0.29 0.27 - - -

1-Butene 1.50 0.67 2.2 1.5 - - -

1-Pentene 0.18 0.069 0.27 0.17 - - -

Acetaldehyde 4.1 1.0 7.9 4.3 - - 4.9 ± 3.3

Acetone 2.6 2.6 6.3 3.8 1.6 ± 0.4 - 4.7 ± 3.3

Benzene 2.0 0.91 3.7 2.2 1.7 ± 0.3 1.3 ± 0.5 1.6 ± 0.3

cis-2-Butene 0.18 0.074 0.27 0.17 - - -

Ethylbenzene 0.082 0.010 0.19 0.094 0.058 ± 0.02 - -

Isobutane 0.53 0.28 0.97 0.59 - - -

Isopentane 0.18 0.089 0.16 0.14 - - -

m,p-Xylene 0.18 0.015 0.29 0.16 - - -

Methanol 13 2.0 9.5 8.2 9.6 ± 1.9 - 15.6 ± 9.2

Methylethylketone 0.66 0.30 0.95 0.64 0.38 ± 0.1 - -

n-Butane 0.76 0.32 1.5 0.86 0.32 ± 0.05 - -

n-Octane 0.22 A 0.015 0.17 0.14 - - -

n-Pentane 0.23 0.049 0.16 0.15 0.14 ± 0.02 - -

o-Xylene 0.071 0.0050 0.14 0.072 - - -

Toluene 1.0 0.33 2.1 1.1 0.67 ± 0.16 0.6 ± 0.3 0.7 ± 0.2

trans-2-Butene 0.23 0.069 0.32 0.21 - - -

trans-2-Pentene 0.052 0.015 0.095 0.054 - - -

8 The utility of the ERVOC/CO values from this study may be limited by the small number of

9 samples, which are reflected in the variability of the three samples. However, there are a

10 greater number of VOCs investigated here relative to previous studies and the longer sample

11 integration time may be more representative of emissions during various burning conditions

for VOCs that have been reported during short duration aircraft studies in boreal wildfire plumes (Hecobian et al., 2011; Simpson et al., 2011; Singh et al., 2010). These generally comparable ERVOC/CO results provide some confidence in the range of ERVOC/CO for species that have not yet been reported in the literature from ambient measurements of fresh boreal wildfire plumes. Nonetheless, additional measurements of ERVOC/CO in fresh plumes would improve our understanding of VOC emissions from boreal wildfires.

To our knowledge, there are no reported ERPAH/CO values reported in the literature for fresh boreal wildfire plumes. The values calculated for the fire-influenced samples at AMS 7 are given in Supplementary Table S4. The deficiency of ERPAH/CO values for boreal wildfires highlights the need for additional measurements to better understand the emissions of PAHs from wildfires and their potential health effects.

3.4 O3 Production Downwind

Numerous studies have observed production of O3 downwind of large forest fires as a result of significant NOx and VOC emissions (Brey and Fischer, 2016; Jaffe and Wigder, 2012; Morris et al., 2006; and referencies therein). Only a few studies have observed no effect of O3 in aged wildfire plumes (Alvarado et al., 2010; Tanimoto et al., 2008; Verma et al., 2009). These latter studies are almost exclusively in boreal regions and may be caused by a significant layer of optically-thick aerosols that hinders photochemistry (Verma et al., 2009) and/or the sequestration of NOx as peroxyacetyl nitrate (PAN), which is more favourable at cooler temperatures (Alvarado et al., 2010).

Figure 7 examines four separate occasions (pink boxes) on which the Horse River Wildfire plume intercepted urban centres in Alberta after ~0.5 to 2.5 days of travel. The influence from the wildfire was identified using ancillary continuous measurements from the Edmonton-Woodcroft (Fig. 7a) and Lethbridge (Fig. 7b) sites, as well as HYSPLIT back-trajectories and FIRMS web mapper tool. HYSPLIT and FIRMS show that the two PM2.5 spikes on 11 May 2016 in Lethbridge were likely from a different wildfire in British Columbia.

Despite the presence of NOx (Fig. 7) during the fire-influence periods, and an assumed increase in EVOC, there is no evidence for a substantial increase in O3 or Ox (=O3 + NO2). Although the small number of events prevented a quantitative analysis, O3 (Ox) mixing ratios never went above 56 (60) ppbv as the wildfire plumes were advected through Edmonton and

ACCEPTED MANUSCRn

1 Lethbridge. there were no discernible changes in the typical

2 a spike in Ox suggesting NO titration was minimal.

10 11 12

5/11/2016

5/23/2016

Figure 7. Continuous measurements of O3, PM25 mass, and NOx at (a) Edmonton-Woodcroft and (b) Lethbridge during May 2016. Periods during which measurements were impacted by the Horse River Wildfire are highlighted by pink boxes.

Meteorology was investigated using hourly data taken by Environment and Climate Change Canada at the Edmonton International (CYEG) and Lethbridge (CYQL) airports (ECCC, 2016). Table 4 summarizes the average air temperature, wind speed, and "weather" during the events. Rapid formation of O3 typically occurs under hot, stagnant, sunny conditions (Seinfeld and Pandis, 2016). All of the events were characterized by at least one of: cool average temperatures (< 7 °C), clouds/rain, and moderate-to-high wind speeds (>8 m s-1). These less-than-ideal conditions for O3 formation likely contributed to the absence of O3 enhancement. Cheng et al. (1998) presented a similar analysis for wildfire plumes from Northern Alberta passing through Edmonton from June 1-5, 1995. Although the authors measured increased NOx and VOCs, they only observed enhanced O3 on June 4th and 5th. This was attributed to high winds from June 1-3 followed hot, sunny and stagnant conditions on June 4-5.

Table 4. Average meteorological conditions during Horse River Wildfire plume events in Edmonton and Lethbridge

Location Duration (Local Time) Temp (°C) Wind Speed (m s-1) Weather

Edmonton May 12 - 0:00 to 12:00 6.5 3.0 Cloudy

Edmonton May 16 - 9:00 to 22:00 sasa"a3.8 rfVTW™3.3 Cloudy

Edmonton May 19 - 16:00 to 0:00 22.6 8.2 Clear

Lethbridge May 14 - 1:00 to 12:00 5.5 8.0 Rain

1 Given that previous studies did not observe high O3 concentrations downwind of boreal fires

2 (Alvarado et al., 2010; Tanimoto et al., 2008; Verma et al., 2009), and that less-than-ideal

3 meteorological conditions for O3 formation persisted during plume intercepts, it is

4 unsurprising that an O3 enhancement related to the Horse River Wildfire was not observed in

5 Edmonton or Lethbridge. The influence of the 2016 Horse River Wildfire on transboundary

6 O3 (~1000s km away) was outside the scope of our study, but warrants further investigation.

7 3.5 Consequences for Local Air Quality

8 Most epidemiological studies on wildfire smoke inhalation have focused their investigation

9 on the impacts of particulate matter (PM) (Dennekamp and Abramson, 2011; Henderson and

10 Johnston, 2012; Reisen and Brown, 2006; Youssouf et al., 2014; and references therein) while

11 PAHs, VOCs and aldehydes have received far less attention, in part because of poorly defined

12 and oftentimes lacking metrics. This section will focus on comparing ambient levels of PAHs

13 and VOCs to air quality objectives and guidelines. An in-depth analysis of the fire's impacts

14 on air quality from other pollutants (e.g., PM25, NOx, SO2) is the subject of a related

15 manuscript (Landis et al., 2017).

16 Table 5 lists the 11 VOCs for which acute Alberta Ambient Air Quality Objectives

17 (AAAQOs) exist (AEP, 2016c). A direct comparison to the hourly AAAQOs was complicated

18 by the daily-averaged VOC measurements. Although not ideal, this approach is conservative

19 since a daily average exceeding the hourly AAAQO likely had multiple hours which

20 surpassed the metric. To provide more context, observations were also compared to the daily-

21 averaged Minimal Risk Levels (MRLs) developed by the United States Agency for Toxic

22 Substances & Disease Registry (ATSDR, 2016). Exposure above the AAAQOs and MRLs

23 values does not mean negative health effects occurred. These values are set at levels which

24 might cause adverse health effects in sensitive individuals and are simply intended to identify

25 situations that require further examination.

26 Table 5. AAAQOs, MRLs and highest daily averages (May-Aug, inclusive) for 11 VOCs

Substance AAAQO (1-hr, ppbv) MRL (24-hr, ppbv) Highest Daily Average (ppbv, May-Aug 2016)

Acetaldehyde 50 N/A 196

Acetone 2,400 26,000 15

Benzene 9.0 9.0 8.7

Ethylbenzene 460 5,000 1.7

Formaldehyde 40 53 24

Isopropylalcohol 3,190 N/A 2.2

Methanol 2,000 N/A 162

n-hexane 5,960 600 15

o-xylene 530 N/A 1.5

Styrene 52 N/A 0.3

Toluene 499 2,000 4.6

2 Only acetaldehyde and benzene either approached or exceeded the AAAQO or MRL values

3 during the May-August study period. The highest benzene values occurred during wildfire

4 influenced periods and was always below 0.5 ppbv in non-fire influenced samples. Reinhardt

5 and Ottmar (2004) measured average benzene levels of 16 ppb adjacent to wildfires and

6 prescribed burns in the western United States. Both results suggest the need to better

7 understand firefighter exposure to benzene and investigate potential health risks.

8 On the other hand, although acetaldehyde was enhanced during the wildfire (up to 27 ppbv at

9 AMS 7 on May 6th), the highest mixing ratios were on August 16th and 22nd. For these two

10 sampling days, all sites had daily average acetaldehyde above 24 ppbv with four of the

11 fourteen samples exceeding the hourly AAAQO (50 ppbv). These acetaldehyde

12 concentrations in the region were unprecedented. Historical VOC data from AMS 1 from

13 2009 and 2015 showed that the highest measured daily average acetaldehyde mixing ratio

14 during this time was 23 ppbv, with the 98th percentile being 13 ppbv. Measurements of

15 acetaldehyde in the AOSR should be conducted using a more common technique, such as

16 DNPH-cartridge/HPLC (US EPA method TO-11A) or proton-transfer reaction mass

17 spectrometry (PTR-MS). The evacuated canister GC/MS method in this study has a high

18 detection limit (3 ppbv) and large uncertainty (±24%). Nonetheless, offline canister-based

19 methods have been used to measure acetaldehyde in numerous studies (e.g., Doskey, 2005;

20 Rumsey et al., 2012; Simpson et al., 2013) and have shown good agreement with co-located

21 samples collected using DNPH cartridges (Sistla and Aleksic, 2007).

22 This section is by no means a comprehensive analysis of the air quality implications from

23 VOCs and PAHs during, or after, the Horse River Wildfire. Analysis was limited by several

24 factors, including: (i) species not measured by the network, (ii) non-existent AAAQOs for

25 most VOCs/PAHs, (iii) inconsistent time resolution for measurements and AAAQOs, and (iv)

26 neglect of any potential synergistic effects of pollutants. Nonetheless, this section still

acetaldehyde (after the wildfire) that merit further attention in subsequent studies on boreal wildfires, especially those in the AOSR.

4 Conclusions

This study examined routine measurements from an extensive air quality monitoring network in the AOSR both during and after the 2016 Horse River Wildfire. In May, sites were in close proximity (<10 km) to the flame front which provided a unique situation to assess the impact of a large boreal fire on a considerable suite of air pollutants. Integrated PAH samples collected every sixth day revealed a 4-58 factor increase in EPAHs for fire-influenced samples. The major PAHs in these samples were NAP, ACY, PHE, FLE, and ACE. The relative proportion of the eight most abundant PAHs was similar between fire and non-fire influenced samples, with the exception of ACE (ACY) which had a lower relative contribution to fire influenced samples. Diagnostic PAH ratios confirmed the significant impact of biomass burning at all four sites during May. After re-entry, these ratios provided evidence of PAHs from fossil fuel combustion and petrogenic origins, in addition to biomass burning from lingering wildfire hotspots.

In contrast, integrated VOC samples only had a minor increase for EVOC in fire-influenced samples (only up to a factor of 3 greater than non-fire samples). The modest relative increase could be due, in part, to the plethora of VOC sources in the AOSR (Li et al., 2017; Simpson et al., 2010) that resulted in high EVOC concentrations during non-fire periods. Akin to the PAH samples, the relative contribution of the major VOCs (methanol, acetaldehyde and acetone) were comparable between fire and non-fire influenced samples. This phenomenon might be caused by significant atmospheric oxidation to form these short-chain OVOCs.

A EVOC increase larger than the wildfire-influenced samples occurred at all 7 sites on August 16th and 22nd. The cause(s) for these spikes are unknown, but were unique from the wildfire period due to (i) the lack of wildfires in the area, (ii) higher OVOC fraction, and (iii) presence at all monitoring sites. Due to the high OVOC fraction and abundance of acetaldehyde, aged anthropogenic emissions were likely a contributing factor.

Normalized excess enhancement ratios (ER) were calculated for 20 VOCs and 23 PAHs for three of the fire influenced samples at AMS 7. Results for VOCs were generally consistent with previously reported ER values in fresh North American boreal wildfire plumes. To our knowledge, this is the first study to report ER values for PAHs in these types of plumes.

iaentmea tne potential ior acute nealtn eiiects irom oenzene (auring tne wuarire) ana

2 Lethbridge. Despite the presence of NOx and a presumed increase in EVOC during these

3 events, no appreciable O3 enhancement was observed. This finding is likely a consequence of

4 unconducive meteorology for O3 formation on those days.

5 Benzene and acetaldehyde had daily averages that approached or exceeded the hourly

6 AAAQO metric. Benzene was only significantly elevated in fire-influenced samples and may

7 have posed an acute health risk for firefighters. On the other hand, the highest mixing ratios of

8 acetaldehyde were measured on August 16th and 22nd and exceeded the AAAQO in four

9 samples. The sources, occurrence, and possible health impacts of acetaldehyde in the AOSR

10 warrant further investigation, including measurements of higher time resolution to match the

11 AAAQO averaging period of 1 hour.

12 Higher frequency PAH and VOC sampling during wildfire events would help to better

13 characterize peak concentrations and aid in assessing potential health risks to first responders.

14 Samples should also be screened for as many fire-relevant VOCs, particularly acrolein which

15 has a daily AAAQO of 0.17 ppb. PAH oxidation products (e.g., oxo- and nitro- polycyclic

16 aromatic compounds) and retene (a common biomass burning marker) should also be

17 measured. Monitoring CO and CO2 would allow for calculation of the modified combustion

18 efficiency (MCE) and would help determine which phases of the wildfire were most

19 detrimental for degrading air quality.

20 Acknowledgements

21 The authors wish to thank Zheng Yang, Quamrul Huda, Kirk Baker, and Maribel Colon for

22 useful feedback. The content and opinions expressed in this article do not necessarily reflect

23 the views of WBEA, AEP, or WBEA membership. The EPA through its Office of Research

24 and Development contributed to this research as part of a study into emissions from wildland

25 fires and their impact on ambient air quality. The views expressed in this paper are those of

26 the authors and do not necessarily reflect the views or policies of EPA. It has been subjected

27 to Agency review and approved for publication. Mention of trade names or commercial

28 products do not constitute an endorsement or recommendation for use. Acknowledgment is

29 also extended to the various organizations that provided the air quality and meteorological

30 measurements: WBEA (www.wbea.org), ECCC (http://climate.weather.gc.ca/), and AEP

31 (http://airdata.alberta.ca/aepContent/Reports/DataReports.aspx). The NASA FIRMS web

32 mapping tool was provided by LANCE FIRMS operated by NASA/GSFC/ESDIS with

1U11U111££ JJ1UV1UCU U y I^r\Oii/riv. L/dülly, L11C dUlllUl o dlC ^IdlClUl LU 1

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sTOAA's Air Resource

2 Laboratory for the development and free use of the HYSPLIT trajectory model

3 (http ://ready .arl.noaa. gov/HYSPLIT .php).

1 References

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1 Supplemental

2 Table S1. Method detection limits for PAHs measured at the AMS sites

PAH Method Detection Limit (ng m" )

3 -Methyl chol anthrene3 0.022

7,12-Dimethylbenz(a)anthracene3 0.013

Acenaphthene 0.0064

Acenaphthylene 0.011

Acridine2 0.019

Anthracene 0.017

Benz(a)anthracene 0.014

Benzo(a)pyrene 0.016

Benzo(b)fluoranthene 0.020

Benzo(c)phenanthrene 0.015

Benzo(ghi)perylene 0.020

Benzo(k)fluoranthene 0.013

Chrysene 0.013

Dibenz(a,h)anthracene 0.020

Dib enzo(a, h)pyrene 0.020

Dibenzo(a,i)pyrene 0.025

Dibenzo(a,l)pyrene 0.024

Fluoranthene 0.0070

Fluorene 0.0071

Indeno( 123 -cd)pyrene 0.017

Naphthalene 0.0082

Phenanthrene 0.0071

Pyrene 0.0083

VOC Method Detectlon Llmlt (ppbv)

1,2,4-Trimethylbenzene 0.03

1,3,5-Trlmethylbenzene 0.02

1,3-Butadlene 0.02

1-Butene 0.02

1-Pentene 0.01

2,2,4-Trlmethylpentane 0.01

2,2-Dlmethylbutane 0.01

2,3,4-Trlmethylpentane 0.01

2,3-Dlmethylbutane 0.02

2,3-Dlmethylpentane 0.02

2,4-Dlmethylpentane 0.01

2-Methyl-1-pentene 0.3

2-Methyl-2-butene 0.3

2-Methylheptane 0.01

2-Methylhexane 0.01

2-Methylpentane 0.01

3-Methyl-1-butene 0.3

3-Methylheptane 0.02

3-Methylhexane 0.02

3-Methylpentane 0.01

4-Methyl-1 -pentene 0.3

Acetaldehyde* 3

Acetone* 0.4

a-Plnene 0.3

Benzene 0.01

P-Plnene 0.3

cls-2-Butene 0.02

cls-2-Hexene 0.3

cls-2-Pentene 0.02

Cyclohexane 0.02

Cyclopentane 0.01

Cyclopentene 0.3

Ethanol* 0.3

Ethylbenzene 0.01

Formaldehyde* 3

Isobutane 0.02

Isobutylene 0.3

Isopentane 0.03

Isoprene 0.01

Isopropylalcohol* 0.4

Isopropylbenzene 0.01

m,p-Xylene 0.03

Methanol* 3

Methylcyclohexane 0.01

Methylcyclopentane 0.02

Methylethylketone* 0.3

Methyllsobutylketone* 0.4

Methylvlnylketone* 0.3

n-Butane 0.03

n-Decane 0.06

n-Dodecane 0.4

n-Heptane 0.01

n-Hexane 0.01

n-Nonane 0.01

n-Octane 0.02

n-Pentane 0.1

n-Propylbenzene 0.05

n-Undecane 0.5

Naphthalene 0.5

o-Xylene 0.01

Styrene 0.04

Toluene 0.01

trans-2-Butene 0.01

trans-2-Hexene 0.3

trans-2-Pentene 0.02

2 *denotes OVOC

ICIUIV . XI.

1UUD ClllU VUV^ IV^V^Ll 1 111111 lO 1U1 V^WllllllLAWLAO Cll 11U* 1 V^l 11 VJ-CiLCi

Analyte Instrumental Method Approximate Detection Limit*

PM2.5 mass TEI SHARP 5030 0.5 |g m-3

NH3 TEI17C or TEI 17i 1 ppbv

NMHC TEI 55i 50 ppbv

THC TEI 51 CLT, TEI 51 iLT, or Rosemount 400A 0.05 ppm

NOx TEI 42C, TEI 42i, or Teledyne API 200A 1 ppbv

O3 TEI 49C, TEI 49i, or Teledyne API 400A 1 ppbv

CO TEI 48C 0.05 ppm

*Varies depenc

ing on status of individual analyzer

PAH May 6 May 18 May 24 Average

3 -Methyl chol anthrene 0.18 0.15 0.21 0.18

7,12-Dimethylbenz(a)anthracene 2.4 0.47 2.9 1.9

Acenaphthene 19 1.4 36 19

Acenaphthylene 110 33 760 300

Acridine 1.9 0.31 0.91 1.0

Anthracene 13 2.8 9.5 8.5

Benz(a)anthracene 5.9 0.56 3.1 3.2

Benzo(a)pyrene 2.1 0.28 1.0 1.1

Benzo(b)fluoranthene 3.4 0.37 0.89 1.6

Benzo(c)phenanthrene 1.7 0.28 1.3 1.1

Benzo(ghi)perylene 1.1 0.14 0.16 0.45

Benzo(k)fluoranthene 2.2 0.28 0.93 1.1

Chrysene 12 1.4 7.3 6.7

Dibenz(a,h)anthracene 0.66 0.13 0.59 0.46

Dib enzo(a, h)pyrene 0.038 0.032 0.061 0.044

Dibenzo(a,i)pyrene 0.041 0.18 0.041 0.087

Dibenzo(a,l)pyrene 0.20 0.10 0.055 0.12

Fluoranthene 19 1.7 11 10

Fluorene 92 ,*4.2 30 42

Indeno( 123 -cd)pyrene 1.0 0.22 0.41 0.55

Naphthalene 250 150 840 410

Phenanthrene 99 26 120 82

Pyrene 16 ^ 1.7 11 9.6

|(a) AMS 9|

300 n 5.0

i.oo -3

0.75 ~ 0.50 o

|(b) AMS 13| 300-

1.00 ^ o

0.75 g^

0.50 S.g

0.25 § O 5.0

B IVOC

• (O)VOC Fraction

|(c) AMS 15 300-

5 100 l/sl

# ! t t «

IB IVOC

— PM25

• (O)VOC Fraction

-100 Jo

-0.75 a < -0.50 § O -5.0

-4.0 H O

-3.0 |

5/12/2016 5/30/2016

6/17/2016 7/5/2016 Date

7/23/2016 8/10/2016 8/28/2016

Figure S1. Time series of daily-averaged ZVOC, PM2.5, and THC at (a) AMS 9, (b) AMS 13, and (c) AMS 15. The calculated OVOC fraction (black circles) for VOC samples are shown at the top of each panel.

00 18 12 06 00 18 12 06 00 1 8 12 06 00 18 12 08/17 08/16 08/15 08/14

2 Figure S2. HYSPLIT back-trajectories arriving at AMS 1 on (a) 16 August 2016, and (b) 22

3 August 2016 at 100 m. Back-trajectories were calculated for local arrival times of 3:00 (light

4 blue), 9:00 (green), 15:00 (dark blue), and 21:00 (red).