In mid-August through mid-September of 2017 a major wildfire smoke and haze
episode strongly impacted most of the NW US and SW Canada. During this period
our ground-based site in Missoula, Montana, experienced heavy smoke impacts
for ∼500 h (up to 471 µg m-3 hourly average
PM2.5). We measured wildfire trace gases, PM2.5 (particulate matter
≤2.5µm in diameter), and black carbon and submicron aerosol
scattering and absorption at 870 and 401 nm. This may be the most extensive
real-time data for these wildfire smoke properties to date. Our range of
trace gas ratios for ΔNH3/ΔCO and ΔC2H4/ΔCO confirmed that the smoke from mixed, multiple sources
varied in age from ∼2–3 h to ∼1–2 days. Our study-average
ΔCH4/ΔCO ratio (0.166±0.088) indicated a large
contribution to the regional burden from inefficient smoldering combustion.
Our ΔBC/ΔCO ratio (0.0012±0.0005) for our ground
site was moderately lower than observed in aircraft studies (∼0.0015)
to date, also consistent with a relatively larger contribution from
smoldering combustion. Our ΔBC/ΔPM2.5 ratio (0.0095±0.0003) was consistent with the overwhelmingly non-BC (black carbon),
mostly organic nature of the smoke observed in airborne studies of wildfire
smoke to date. Smoldering combustion is usually associated with enhanced PM
emissions, but our ΔPM2.5/ΔCO ratio (0.126±0.002)
was about half the ΔPM1.0/ΔCO measured in fresh
wildfire smoke from aircraft (∼0.266). Assuming PM2.5 is
dominated by PM1, this suggests that aerosol evaporation, at least near
the surface, can often reduce PM loading and its atmospheric/air-quality
impacts on the timescale of several days. Much of the smoke was emitted late
in the day, suggesting that nighttime processing would be important in the
early evolution of smoke. The diurnal trends show brown carbon (BrC),
PM2.5, and CO peaking in the early morning and BC peaking in the early
evening. Over the course of 1 month, the average single scattering albedo for
individual smoke peaks at 870 nm increased from ∼0.9 to ∼0.96.
Bscat401/Bscat870 was used as a proxy for the size and
“photochemical age” of the smoke particles, with this interpretation being
supported by the simultaneously observed ratios of reactive trace gases to
CO. The size and age proxy implied that the Ångström absorption
exponent decreased significantly after about 10 h of daytime smoke aging,
consistent with the only airborne measurement of the BrC lifetime in an
isolated plume. However, our results clearly show that non-BC absorption can
be important in “typical” regional haze and moderately aged smoke, with BrC
ostensibly accounting for about half the absorption at 401 nm on average for
our entire data set.
Introduction
Biomass burning (BB) emissions are an important source of trace gases and
particles that can influence local, regional, and global atmospheric
chemistry, air quality, climate forcing, and human health (Crutzen and
Andreae, 1990). BB is one of the largest sources of fine primary organic
aerosol (OA), black carbon (BC), brown carbon (BrC) (Bond et al., 2004, 2013;
Akagi et al., 2011), total greenhouse gases, and non-methane organic gases
(NMOG) (Yokelson et al., 2008, 2009), which are precursors for the formation
of ozone and OA. While the majority of BB occurs in the tropics, the small
fraction of the global BB in the western US is responsible for a significant
portion of US air quality impacts (Park et al., 2007; Liu et al., 2017;
Wilkins et al., 2018; Zhou et al., 2018) and contributes to increasing health
concerns. Wildfire smoke has been shown to have adverse respiratory and
cardiovascular health effects, is associated with mortality and morbidity,
and exhibits lung toxicity and mutagenicity (Le et al., 2014; Liu et al.,
2015; Reid et al., 2016; Adetona et al., 2016; Kim et al., 2018). In some
cases, long-range transport of biomass burning emissions can cause air
quality standards to be exceeded hundreds or thousands of kilometers downwind
of the fire source (Jaffe et al., 2013; Wigder et al., 2013). In addition to
health concerns, particulate matter from wildfires can reduce visibility,
which can have impacts on safety and transportation (United States
Environmental Protection Agency, 2019), and is
a concern in protected visual environments such as national parks and
wilderness areas, most of which are in the western US, where a majority of
wildfires occur. The Interagency Monitoring of Protected Visual Environments
(IMPROVE) program initiated in 1985 implemented long-term monitoring that
establishes current visibility conditions and has helped to improve
visibility in protected areas. However, record high temperatures, drought,
and fire-control practices over the last century have culminated into a
situation in which we can anticipate more frequent fires of a larger size and
intensity in the western US and Canada (Yue et al., 2015; Westerling et al.,
2006). These fires are expected to impact all aspects of air quality in the
US – and have other impacts, including on visibility. In fact, over the last
few decades, the annual number of wildfires in the US has not changed
significantly, but the annual area burned has increased by a factor of about
3 (United States National Interagency Fire Center, 2019), and many of the highest burned-area years have coincided
with many of the warmest years on record (United States Environmental
Protection Agency, 2019). Despite these
important issues, many of the emissions from BB remain either understudied or
completely unstudied. To date, most of the research on the emissions and
evolution of smoke from US fires in the field has targeted prescribed fires
(Burling et al., 2011; Akagi et al., 2013; Yokelson et al., 2013a; May et
al., 2014; Müller et al., 2016), and while there are studies that probe
trace gas and optical property emissions of wildfire smoke sampled in the
field (Liu et al., 2017; Lindaas et al., 2017; Landis et al., 2017; Collier
et al., 2016; Eck et al., 2013; Sahu et al., 2012; Lack et al., 2012), much
of the information is limited in temporal extent or incomplete chemically
and fails to assess important issues such as the aging and evolution of smoke
over varying and extended amounts of time, nighttime evolution and
oxidation, or the contribution of constituents of increasingly recognized
importance such as BrC (UV-absorbing OA), to name a few.
BrC emissions are typically mixed with co-emitted BC and non-absorbing OA,
which can result in some measurement difficulties and uncertainty in
isolating and evaluating the optical properties of BrC and its overall
radiative impact (Wang et al., 2017). In lab-simulated
wildfires, BrC was associated with smoldering combustion and accounted for
about 86 % of absorption by particles in the UV in the fresh smoke, which
has several implications in atmospheric chemistry, including impacts on
radiative forcing, UV-driven photochemical reactions producing ozone, and
the lifetime of NOx and HONO (Selimovic et al., 2018). In addition,
there are sources of BrC not directly emitted from BB, including the
photo-oxidation of volatile organic compounds (VOCs) and aqueous-phase
chemistry in cloud droplets. These processes produce BrC with optical
properties and lifetimes that are not yet well characterized (Graber and
Rudich, 2006; Ervens et al., 2011; Wang et al., 2014; Laskin et al., 2015; Tomaz et al., 2018).
In fact, several factors, such as chemical transformation, mixing state,
combustion conditions, and photochemical aging, can all influence the
absorption of BrC (Wang et al., 2017). Most modeling studies have found that
despite the multiple variables contributing to the absorption of BrC,
including BrC in climate models would mean the net radiative forcing of
biomass burning would move in a more positive direction. (Feng et al., 2013;
Jacobsen, 2014; Saleh et al., 2014; Forrister et al., 2015). Unfortunately,
observational constraints on BrC are scarce, making it difficult to assess
and enhance models based on observational evidence. Thus, more field
measurements are required to get an accurate estimate of the impact of BrC,
both regionally and globally.
Most of the western US, including the Rocky Mountains, constitutes a large
fire-prone region. Missoula, Montana, is the largest city completely
surrounded by the Rocky Mountains. Missoula is also located within a large
region of the inland Pacific Northwest, where wildfires have caused air
quality trends to deviate from the pattern in the rest of the US (McClure and
Jaffe, 2018). Missoula frequently experiences smoke impacts typical of much
of the urban and rural west due to local and regional western fires. A few
airborne studies have sampled western wildfires and are most sensitive to
lofted emissions (Liu et al., 2017; Yates et al., 2016), but wildfires may
produce some unlofted emissions, especially at night. Ground-based studies
could probe these unlofted emissions but have difficulty to representatively
sample lofted emissions unless advection accompanies transport. Despite these
platform-based considerations, our laboratory on the eastern edge of Missoula
is a relevant receptor for mixed-age (1–2 h to 1–2 days) western wildfire
smoke. In this study, we measured the wildfire smoke characteristics for
500 smoke-impacted hours during August–September of 2017, which constituted
a prolonged period of record-breaking air quality impacts in Missoula. This very large
sample of wildfire smoke helps address some of the afore-mentioned
observational gaps in current wildfire field data. Specifically, two
photoacoustic extinctiometers (PAXs) and a Fourier-transform-infrared
spectrometer (FTIR) characterized the smoke that entered the Missoula valley.
A Montana Department of Environmental Quality (DEQ) PM2.5 (particulate
matter ≤2.5µm in diameter) monitor
provided additional insight and verified some impacts. The PAXs provided
measurements of scattering and absorption at two wavelengths (nominal 405 nm,
actual 401 nm; 870 nm), BC, and derivations of single scattering albedo
(SSA), and Ångström absorption exponent (AAE) for PM1.0. The FTIR
measured the BB “tracer” carbon monoxide (CO) and a few other trace gases
that help estimate effective average smoke age. The main goals of this
work are to document the net combined effect of numerous fires on a heavily
impacted surface site embedded in the region and, thus, also help assess the
representativeness of field measurements, emissions inventories, and models.
In more detail, we characterize the smoke impacts on a population center and
we document the real-world regional significance of BrC. Comparisons are
possible to our time series of BC, CO, or PM, etc. or diurnal cycles for these
species for a more relaxed test. Our real-time through study-average ratios
for “inert” tracers such as ΔBC/ΔCO are compared with
ΔBC/ΔCO in the field measurements that are available to
build emissions inventories that serve as model input. The time-resolved and
study-average values of dynamic ratios (e.g., ΔPM/ΔCO) help
elucidate the net effect of secondary aerosol formation and evaporation. Our
measurements provide real-world aerosol optical properties (e.g., SSA and AAE) and can be used with the aerosol mass data at real time through
study-average resolution to probe multi-step, bottom-up calculations of
climate-relevant aerosol optical properties. We present our results and
compare them to those previously reported for wildfire field measurements and
prescribed fire field measurements.
Experimental detailsSite descriptions
Trace gases and particles were measured through co-located inlets at the
University of Montana (UM), ∼12.5 m above the ground through the
window of our laboratory on the fourth (top) floor of the Charles H. Clapp
building (CHCB). The UM campus encompasses an area of ∼0.89 km2
and is located on the eastern edge of Missoula, with the CHCB located in the
southeastern corner of campus. The CHCB is ∼1.1 km from the nearest
road that gets appreciable traffic during the summer; thus our measurements
were not significantly influenced by automobile emissions (see Sect. 3.1).
PM2.5 measurements were made by the Montana Department of Environmental
Quality via a stationary PM2.5 monitor located in Boyd Park, Missoula,
which is ∼3.2 km southwest of our UM laboratory, with both sites
being located in the Missoula valley proper.
Trace gas measurements were made using an FTIR (Midac, Corp., Westfield, MA)
with a Stirling cycle cooled mercury-cadmium-telluride (MCT) detector
(Infrared Associates, Stuart, FL; Ricor USA Inc., Salem, NH) interfaced with
a 17.22 m path closed multipass White cell (Infrared Analysis, Inc.,
Anaheim, CA) that is coated with a halocarbon wax (1500 Grade, Halocarbon
Products Corp., Norcross, GA) to minimize surface losses (Yokelson et al.,
2003). Although the system was designed for source measurements and is
described elsewhere in more detail (Akagi et al., 2013; Stockwell et al.,
2016a, b), the FTIR is convenient for ambient monitoring because the Stirling
cooled detector does not require refilling of liquid nitrogen and thus allows
for mostly autonomous operation. Ambient air was drawn through the 2.47 L
White cell at ∼6 L min-1 via a downstream IDP-3 dry scroll
vacuum pump (Agilent Technologies) using a 0.635 cm o.d. corrugated Teflon
inlet that was positioned outside the window (∼12.5 m above ground
level). Cell temperature and pressure were also logged on the system computer
(Minco TT176 TRD, MKS Baratron 722A). Spectra were collected at a resolution
of 0.50 cm-1 covering a frequency range of 600–4200 cm-1. A time
resolution of approximately 5 min was more than adequate, and sensitivity was
increased by co-adding scans at this frequency. Gas-phase species (with their
respective detection limits in parentheses), including carbon monoxide (CO,
20 ppb), methane (CH4, 20 ppb), acetylene (C2H2,
2 ppb), ethylene (C2H4, 2 ppb), methanol (CH3OH,
3 ppb), and ammonia (NH3, 2 ppb) were quantified by fitting
selected regions of the mid-IR transmission spectra with a synthetic
calibration nonlinear least-squares method (Griffith, 1996; Yokelson et al.,
2007). The uncertainties in the individual mixing ratios (ppmv) varied by
spectrum and molecule and were influenced by uncertainty in the reference
spectra (1 %–5 %) or the real-time detection limit, whichever was
larger. The procedure used to correct for gases outside of the spectrometer
cell raised the uncertainty to ∼ 20 ppb for background CO and
CH4 but did not affect the measured enhancements above the background
during smoke episodes. Calibrations with NIST-traceable standards indicate
that peak CO values had an uncertainty of less than 5 %. The FTIR system
was designed for source sampling, and the sensitivity was adequate to measure
a significant amount of usable trace gas data but not every species on every
event. In addition, an FTIR system problem caused the trace gas data to
terminate about 1 day before the smoke cleared.
Photoacoustic extinctiometers (PAXs) at 870 and 401 nm
Particle absorption and scattering coefficients (Babs, Mm-1,
Bscat, Mm-1) were measured directly at 1 s time resolution
using two photoacoustic extinctiometers (PAX, Droplet Measurement
Technologies, Inc., Longmont, CO; Lewis et al., 2008; Nakayama et al., 2015),
and single scattering albedo (SSA) at 401 (nominally a 405 nm system) and
870 nm, and the Ångström absorption exponent (AAE) were derived using those
measurements. Although the PAXs measured every second, data were averaged to
5 min, which was deemed adequate for the final analysis and matched the time
resolution used by the FTIR for the same reason. A 1 L min-1 aerosol
sample flow was drawn through each PAX using a downstream IDP-3 dry scroll
vacuum pump (Agilent Technologies) and split internally between a
nephelometer and photoacoustic resonator for simultaneous measurement of
light scattering and absorption. Both PAX instruments contain an internal
pump; however these internal pumps were bypassed to improve measurement
sensitivity, as the pumps can contribute an amount of acoustic noise that is
noticeable in clean-air ambient measurements. Scattering of the PAX laser
light was measured using the wide-angle (6–174∘) reciprocal
nephelometer that responds to all particle types regardless of chemical
makeup, mixing state, or morphology. For absorption measurements, the laser
beam was directed through the aerosol stream and modulated at a resonant
frequency of the acoustic chamber. Absorbing particles transferred heat to
the surrounding air, inducing pressure waves that were detected via a
sensitive microphone. Advantages of the PAX include direct in situ
measurements, a fast response time, continuous autonomous operation, and
elimination of the need for filter collection and the uncertainties that come
with filter artifacts (Subramanian et al., 2007).
The PAX sample line was ∼4.7 m of 0.483 cm o.d. conductive silicon
tubing positioned outside the window ∼12.5 m above ground level and
co-located with the FTIR inlet. The tubing transferred outside air to a
scrubber to remove light-absorbing gases (Purafil-SP Media, minimum removal
efficiency 99.5 %) and then a diffusion dryer (Silica Gel 4–10 mesh) to
remove water, with post-dryer relative humidity varying between 13 % and
30 %. The scrubber and dryer were refreshed before any signs of
deterioration were observed (e.g., color change). The diffusion-based designs
will cause small particle losses, but losses were not explicitly measured.
After the dryer, a splitter connected to the two instruments. After the
splitter, each sample line featured a 1.0 µm size cutoff cyclone
and two acoustic notch filters that reduced noise. Both PAX instruments were
calibrated before, during, and after the experiment using the
manufacturer-recommended scattering and absorption calibration procedures
utilizing ammonium sulfate particles and a propane torch to generate purely
scattering and strongly absorbing aerosols, respectively. The 401 nm data
were only used after 27 August because of frequent clogging of the PM1.0
cyclone before that date. The estimated uncertainty in PAX absorption and
scattering measurements has been estimated to be ∼4 %–11 %
(Nakayama et al., 2015).
In the PAX, the incident laser light is absorbed in situ by light absorbing
particles without filter or filter-loading effects that can be difficult to
correct, particularly for samples with high organic aerosol loadings (Lack
et al., 2008; Li et al., 2019). We directly measure aerosol absorption
(Babs, Mm-1) and used the literature- and manufacturer-recommended
mass absorption coefficient (MAC) (4.74±0.63 m2 g-1 at 870 nm) to calculate the BC concentration (µg m-3) at ambient
temperature and pressure (Bond and Bergstrom, 2006), but the BC mass can be
adjusted using different MAC values if supported by future work. Because the
PAXs also measured light scattering, scattering and absorption values can be
combined to directly calculate the single scattering albedo (SSA, the ratio
of scattering to total extinction). SSA is a useful input for climate
models, where an SSA closer to 1 indicates a more “cooling”
highly scattering aerosol:
SSA=Bscat(λ)Bscat(λ)+Babs(λ).
To a good approximation, sp2-hybridized carbon (including BC) absorbs
light proportional to frequency (Bond and Bergstrom, 2006). Thus, the
Babs contribution from BC at 401 nm can be calculated from
2.17 times Babs at 870 nm (an absorption Ångström
exponent of 1), where BrC absorption is expected to be negligible, and any
additional Babs at 401 nm can be assigned to BrC
(Babs, BrC) subject to limitations due to “lensing” by coatings
discussed elsewhere (Pokhrel et al., 2016, 2017; Lack and Langridge, 2013;
Lack and Cappa, 2010). Coating effects are very difficult to isolate from BrC
direct absorption effects, and this adds some uncertainty to the BrC
attribution (±25 %) but not to the absorption measurements
themselves. Additionally, the absorption Ångström exponent (AAE)
(401/870) can be calculated from the 401 and 870 data, where the AAE of pure
BC is usually close to 1, and larger values are indicative of smoke
absorption more dominated by BrC emissions:
AAE=-logBabs,1Babs,2logλ1λ2.
The AAE is useful as an indicator of BrC / BC, but in addition, the full
aerosol absorption spectrum is often approximated with a power law function
(absorption =C×λ-AAE), and thus the AAE
determined with any wavelength pair can be used to approximately calculate
the shape of absorption across the UV–VIS range (Reid et al., 2005b). An
equation similar to Eq. (2) provides the scattering Ångström exponent
(SAE), which can be used to
calculate scattering at unmeasured wavelengths.
A few other sources of uncertainty in the measurements and/or calculations
are poorly characterized; MAC increases due to coatings, potential particle
losses in the dryer or scrubber, and truncation error in the nephelometer.
Mie calculations provided by the manufacturer suggest the scattering could be
underestimated by about 1 % at 870 nm and 2.5 % at 401 nm due to
truncation error (John Walker, personal communication, 2019). This would
reduce the mass scattering coefficients (Sect. 3.5),
and, typically, a 1 % reduction in scattering would imply approximately a
tenth of a percent of value underestimate of SSA. Miyakawa et al. (2017)
reported a size-independent particle transmission up to 400 nm of 84±5 % in their diffusion dryer. Larger particles may be transmitted more
efficiently. We did not measure size distribution or transmission efficiency
in this study, and, thus, we did not adjust the data. Size-independent
particle losses would reduce scattering, absorption, and derived BC but
should only have a small impact on SSA or AAE. Unlike particle losses, an
increased MAC due to lensing via coatings could inflate BC values by up to
∼30 % (Pokhrel et al., 2017).
Montana Department of Environmental Quality PM2.5
The Montana DEQ uses beta attenuation monitors (Met One Instruments, Model
BAM-1020) in accordance with US EPA Federal Equivalent Methods (FEMs) for
continuous PM2.5 monitoring. At the beginning of each sample hour, a
constant 14C source emits beta rays though a spot of clean glass fiber
filter tape. The beta rays are measured by a photomultiplier tube to
determine a zero reading. The BAM-1020 then advances this spot of tape to the
sample nozzle, where it filters a measured amount of outside air at
16.7 L min-1. At the end of the sample hour,
the attenuation of the beta ray signal by the filter spot is used to
determine the mass (and concentration µg m-3 at ambient
temperature and pressure) of the particulate matter. Hourly detection limits
for the BAM-1020 are <2.4µg m-3 (1σ). Current and
archived air quality data for the state of Montana can be accessed using the
following link: http://svc.mt.gov/deq/todaysair/ (last access: 20 March
2019). More information on the BAM-1020 can be found at
http://metone.com/air-quality-particulate-measurement/regulatory/bam-1020/
(last access: 20 March 2019). Note the PAX size cutoff throughout this study was 1.0 µm, and the PM size cutoff is
2.5 µm. The mass in the 1.0–2.5 µm range is thought to
be a small part of the total mass (e.g., 10 %–20 % in Fig. 2 in Reid
et al., 2005a), but the size range difference does affect data interpretation
as detailed later. (PM2.5 cyclones have now been obtained for the PAXs
for ongoing studies.)
Emission ratios (ERs) and downwind enhancement ratios
Time series are useful to characterize impacts and evaluate models, but we
also used the time series of mixing ratios or concentrations for each analyte
measured to derive other values that are broadly useful for study comparisons
and implementation in local to global chemistry and climate models. As part
of this, we produced emission ratios (ERs) and enhancement ratios. The
calculation of these two types of ratios is the same, but an emission ratio
is only the appropriate term for a ratio measured directly at a source or
further downwind for relatively inert species such as BC or CO. First, an
excess mixing ratio or concentration (denoted by
“ΔX” for each species X) is calculated for all species measured
by subtracting the relatively small background value based on a sloping baseline
from before to after a smoke impact. For example, the ratio for each species
relative to CO (ΔX/ΔCO) is the ratio between the
sum of ΔX over the entire smoke impacted period relative to the sum
of ΔCO over the entire smoke impacted period. Mass or molar ratios to
CO were calculated for BC, PM, and all the gases measured by the FTIR that
exhibited enhancement above background levels for each smoke impacted period.
Emission factors (EFs), which can be derived by including the molar ER to
CO2 in the carbon mass balance method were not calculated
(Selimovic et al., 2018). The diurnal variation for CO2 is
considerable, and the smoke was mainly aged (not reflecting initial emissions
for most species) in Missoula. The prolonged “small” ΔCO2
peaks that persist for times similar to the natural, substantial variation
that CO2 has have uncertain values. For example, for CO2,
the wildfire smoke impacts in Missoula are largely diluted and protracted
enough to not completely dominate background variability, as is the case for
the other gases and for source sampling (Stockwell et al., 2016a, b; Akagi et
al., 2011, 2012). Since ΔCO2 is not as reflective of fire
impacts, then by extension, the modified combustion efficiency (MCE), which
is defined as ΔCO2/(ΔCO2+ΔCO), is not as
useful as an index of the flaming to smoldering combustion ratio in this study as measurements
closer to the source (Yokelson et al., 2013b). Other approximate indicators
of the relative amount of flaming to smoldering combustion such as
ΔBC/ΔCO or ΔCH4/ΔCO can still be
used.
Investigating smoke origin and back trajectory calculations
To investigate the sources contributing to smoke events, we used a
combination of back trajectory calculations, satellite imagery, and local
meteorological data that provided insights into mixing and smoke origin. Back
trajectories were calculated utilizing the National Oceanic and Atmospheric
Administration (NOAA) Air Resources Laboratory Hybrid Single Particle
Lagrangian Integrated Trajectory (HYSPLIT; Stein et al., 2015; Draxler, 1999;
Draxler and Hess, 1997, 1998) initialized from UM (46.8601∘ N,
113.9852∘ W) at 500, 1200, and 3000 m above ground level during the
hour at which enhancements for that particular smoke event were at a maximum.
Back trajectories were run using the High Resolution Rapid Refresh (HRRR)
operational model, which uses the Weather Research
and Forecasting (WRF) modeling system combined with observational data
assimilation and is run over the contiguous US at 3 km × 3 km
resolution (Benjamin et al., 2016). For events that spanned multiple days,
multiple back trajectories were initialized during the hour(s) at which
enhancements for the sub-events were at a maximum. Because of the complex
local topography and micrometeorology, the combination of back trajectories,
satellite imagery (GOES “loops”), and other evidence can only suggest a
most likely smoke origin and cannot provide an exact smoke age. Our best
guess at the smoke origin for each event is listed in Table S1 in the
Supplement.
Brief description of 2017 regional and selected local fires
Missoula experienced smoke impacts from local (western Montana) and regional
fires with regional fires including fires in California, Idaho, Oregon,
Washington, and British Columbia. Over ∼1.2 million ha burned in
British Columbia in 2017 (BC Wildfire Service, 2017). More than
4 million ha burned in the US during the 2017 fire season, making it one of
the largest to date. Idaho, Oregon, and Washington had burned areas over
263 000, 283 000, and 161 000 ha, respectively. California and Montana
experienced their largest burned areas to date, with both states experiencing
close to 526 000 ha burned each
(https://www.predictiveservices.nifc.gov/intelligence/2017_statssumm/fires_acres17.pdf,
last access: 21 March 2019). Although the complicated meteorology and
topography of the Missoula valley makes attributing smoke sources somewhat
difficult (as noted above), we can say with some degree of certainty that the
majority of the fresh smoke impacting Missoula came from two local fires, the
Lolo Peak Fire and the Rice Ridge Fire (Table S1). The Lolo Peak Fire started
at high elevation ∼15 km SW of Missoula (46.674∘ N,
114.268∘ W) on 15 July 2017 and burned continuously (mostly at lower
and lower elevations) until it eventually grew to over 20 000 ha. The fuel
description as given by Inciweb
(https://inciweb.nwcg.gov/incident/5375/, last access: 20 March 2019)
is summarized as containing generally sparse or patchy subalpine fir
(Abies lasiocarpa) with dead Whitebark pine (Pinus albicaulis) above ∼2100 m. Below 2100 m, fuels were mainly typical
of a variety of coniferous-dominated ecosystems with major tree species such
as ponderosa pine (Pinus ponderosa), subalpine fir (Abies lasiocarpa), and lodgepole pine (Pinus contorta). Lower elevations
near containment lines were dominated by ponderosa pine with grassy
understory. The Rice Ridge Fire started 24 July 2017 ∼52 km NE of
Missoula (47.268∘ N, 113.485∘ W). The fire eventually
burned over 64 000 ha, with a notable run on 3 September 2017, where it
doubled in size from ∼20000 to ∼40000 ha. Fuels involved
were timber (litter and understory) and brush
(https://inciweb.nwcg.gov/incident/5414/, last access: 20 March 2019).
Results and discussionOverview of 2017 fire season smoke impact in Missoula
Figure 1 shows the hourly average mixing ratios of CO, BC, and PM2.5
observed from 11 August to 10 September 2017, which includes nearly all of
the 2017 Missoula smoke impacts. There were more than 20 distinct periods of
major smoke impacts that are readily identified by large simultaneous
enhancements in CO, BC, and PM2.5. Sustained periods when PM2.5 was
elevated well above the 12.5 µg m-3 EPA standard for “good”
air quality were designated as events and assigned a letter in Fig. 1 and
Table S1. The highest hourly values were observed on 4 September 2017, the
morning after the Rice Ridge Fire doubled in size (PM2.5,
471 µg m-3, CO 2.78 ppm, BC 3.62 µg m-3).
This event is discussed in more depth as a case study in a later section
(Sect. 3.6). Numerous other PM2.5 peaks
exceeded, e.g., levels of 100 µg m-3. “Cleaner” periods
between smoke peaks became less extensive as the regional atmosphere became
increasingly polluted until widespread clearing on 10 September 2017. Overall
high correlation of CO and BC to PM2.5 suggests that the smoke was
normally well mixed on the spatial scale that separated the PM2.5 and UM
monitors. Many of the longer smoke impacts that spanned several days were
necessarily integrated as a single event for calculating ratios between
species, but we also initialized back trajectories from local maxima to
further explore the source region of the smoke, which was probably always
mixed to some extent (Table S1).
Time series of hourly CO, BC, and PM2.5 measurements from
Missoula. Sections highlighted in yellow roughly indicate smoke-impacted periods.
A few small peaks that could not be attributed to biomass burning sources were excluded from analysis.
Trace gas ratios
Table 1 reports study-average ratios weighted by event duration
(time-weighted) to CO for gases measured by the FTIR. These measurements are
representative of moderately aged regional wildfire smoke. We interpret our
results by comparing them to emission ratios measured in the lab (Selimovic
et al., 2018) and other field studies mostly in fresher smoke (Liu et al.,
2017; Landis et al., 2017; Radke et al., 1991). CO is a major pollutant in
the atmosphere, with BB as a main source. In Missoula, especially in the
summer, the CO background is not strongly influenced by non-fire sources.
CH4 on the other hand has more background variability, but at these
smoke levels the ratio of CH4 to CO, while variable, yields a study
average (0.166±0.088) that mostly reflects the real average
ΔCH4/ΔCO fire emission ratio. Yates et al. (2016)
reported a smoldering stage ΔCH4/ΔCO ER of 0.095 (±0.023) for the Rim Fire, which is lower than our study-average ER, but the
ratio reported in Yates et al. (2016) comes from airborne measurements closer
to the source and from a single fire source. Our higher study-average ER of
CH4 is indicative of smoldering (Reisen et al., 2018; Yokelson et
al., 1997). Because the measurement was not in a direct downslope flow of
smoke into Missoula, this ratio suggests that smoldering emissions from
regional fires can be and were frequently transported to the Missoula valley.
This may be why our study average is higher than observed in airborne
studies. In a consistent observation, we find that ERs for ΔCH4/ΔCO are lower when the ΔBC/ΔCO ERs are
higher (Fig. 2), which is indicative of a flaming to smoldering ratio
dependence (Christian et al., 2003). This is a useful result, because our two
metrics for combustion characteristics at the fire
sources are consistent, and it
indicates that the variability in ratios between species observed at Missoula
was partly due to variable combustion types at the regional fire sources
along with the expected effects of variable aging that are discussed next.
Time-weighted study-average enhancement ratios (ratioed to CO)
compared to emission ratios reported in other studies.
a Measured lab values at lab fire MCE.
b Calculated from EF versus MCE fit based on average wildfire MCE
reported in Liu et al. (2017). c Averages of Myrtle Fall Creek andSilver Fire.
(a) Methane emission ratio versus black carbon emission
ratio. Point shown are for events that have both a CH4/CO ratio and
a BC / CO ratio. (b) Lab average (Selimovic et al., 2018)
BC / CO ratio versus modified combustion efficiency (MCE), separated into
bins by 0.01 of MCE.
Next, we compare other measured trace gas ratios, including some more
reactive VOC, to the limited amount of data available from previous airborne
and lab studies. Liu et al. (2017) sampled smoke between 1 and 2 h old on
average and did not report an ER value for NH3. However, Liu et
al. (2017) reported an average wildfire MCE that Selimovic et al. (2018) used
with measurements of very fresh lab fire smoke to calculate an ER value for
ΔNH3/ΔCO based on the average wildfire MCE reported in
Liu et al. (2017). The predicted NH3 value (0.0279) for wildfires
based on an average wildfire MCE (0.91) is about twice our observed average
ΔNH3/ΔCO (0.0133). Radke et al. (1991) measured an
ΔNH3/ΔCO range from 0.037 for fresh smoke to 0.011 when
including samples up to 48 h old. Our 2017 individual ratios span a range
(Table S1). Near the high end we see ΔNH3/ΔCO of 0.0196
for relatively fresh smoke assigned to the nearby Lolo Peak Fire and 0.0216
for event “S” of which the origin is unclear. Our lowest ratios are about
1/4 of our highest ratios (0.0044) (Table S1). Akagi et al. (2012) measured
a midday ΔNH3/ΔCO half-life of ∼5 h, which
suggests that our average sample age is roughly equivalent to ∼5 h of
midday processing, and our oldest samples (with NH3 data) are aged
equivalent to about 10 h of midday processing (Table S1). However, the
“time since emission” is potentially longer than indicated by a
“photochemical age”, since, according to the GOES satellite, a lot of smoke
was produced in the evening and OH processing may not have started fully
until the next day. In addition, we note that the true processing ages have
potential to be even longer, since the true initial ΔNH3/ΔCO may have been higher than our highest observed ratios as we
were not immediately adjacent to sources. This possibility is supported by
the fact that NH3 and CH4 emissions have been shown to be
linked (Yokelson et al., 1997), and our “high” ΔCH4/ΔCO value for event S (∼0.14) could indicate that the real initial
ΔNH3/ΔCO was higher than ∼0.022. Finally, the
ΔNH3/ΔCO ratio is also related to the size and age of
particles, as will be discussed in future sections
(Sect. 3.4).
C2H4 has been observed to decay in isolated plumes with a
similar half-life to ammonia (Akagi et al., 2012; Hobbs et al., 2003), and
our study-average ΔC2H4/ΔCO ratio (0.011) is again
about half that in the other wildfire studies in younger smoke reported in
Table 1 (∼0.02) or listed elsewhere (Akagi et al., 2011). Our lower
ΔC2H4/ΔCO ratios tended to occur when the
ΔNH3/ΔCO ratio was also lower (Table S1), but
unfortunately there are only two events with data for both gases and not
enough measured values to warrant a detailed analysis. Methanol and acetylene
react at least an order of magnitude more slowly with OH than
C2H4. Our average methanol enhancement ratio (0.019) thus falls
in the middle of the other wildfire values (0.0148–0.024) as might be
expected when any aging effects are smaller than the natural high variability
in initial emissions (Akagi et al., 2011). In fact ΔCH3OH/ΔCO has been observed to increase or decrease slightly or
stay the same for several hours of aging (Akagi et al., 2012, 2013;
Müller et al., 2016). We only have a few data points for ΔC2H2/ΔCO, but their average is significantly lower than the
other wildfire studies. Since C2H2 is associated with flaming
combustion (Lobert et al., 1991; Yokelson et al., 2013a), this could be due to
the prevalence of smoldering that was also indicated by the high average
ΔCH4/ΔCO ratios as noted above. Another point about our
trace gas data is that our mixing ratios for CO are valuable as an inert
tracer for wildfire emissions for comparison to models, and they can be useful
for inferring the initial emissions of other gases if those gases emission
ratios to CO have been measured elsewhere (Selimovic et al., 2018; Koss et
al., 2018; Liu et al., 2017). CO can also be used as a scaling/normalizing
factor for particle emissions, which is discussed in the next section.
ΔBC/ΔPM2.5, ΔBC/ΔCO, ΔPM2.5/ΔCO
BC is estimated to be the second strongest global climate warming agent, and
BB is the main BC source (Bond et al., 2004). Accurate BC measurements are
challenging, and aerosol absorption remains poorly understood in atmospheric
models (Bond et al., 2013). In contrast, CO is measured reliably at a network
of surface sites and in aircraft campaigns and can also be retrieved by
satellite (MOPITT, IASI, AIRS, etc.). As a result, CO emissions estimates are
available for most sources, including fires, and the estimates are in
reasonable agreement for western wildfires (Liu et al., 2017). BC and
ΔBC/ΔCO measurements using modern methods for wildfires
are rare; thus, our BC, CO, and ΔBC/ΔCO measurements from
a large sample of wildfire smoke can be used with CO emissions to update BC
emissions estimates from wildfires (see below). BC is only made by flaming
combustion at a fire source, and despite the fact that its production rate
can vary strongly with flame turbulence, the ΔBC/ΔCO ratio
can serve as a rough indicator of the fire's flaming to smoldering ratio
(Vakkari et al., 2018; Christian et al., 2003;
Yokelson et al., 2009; Shaddix et al., 1994) as demonstrated earlier in
Fig. 2b. Table 2 reports our study-average ratios (time-weighted) of
ΔBC/ΔCO, ΔBC/ΔPM2.5, and
ΔPM2.5/ΔCO and compares them to the limited
measurements of wildfire smoke available in the lab (Selimovic et al., 2018)
and in the field (Liu et al., 2017; Sahu et al., 2012; Hobbs et al., 1996).
Our ΔBC/ΔCO ratio (0.0012) is a bit lower than the
aircraft-measured averages of Sahu et al. (2012) (0.0014) and Liu et
al. (2017) (0.0016) and the Selimovic et al. (2018) estimate at the field
average MCE for wildfires from Liu et al. (2017, 0.0018). The Hobbs et
al. (1996) average value for their two fires specifically identified as
wildfires is notably higher than the other values and is actually an
ΔEC/ΔCO measurement that could be biased high (Li et al.,
2019). The Selimovic et al. (2018) lab average is
also higher but obtained at the higher lab-average MCE. The uncertainty in
our value is likely asymmetric because coatings in aged PM could inflate
absorption and our BC value by a small amount. Taken together, this suite of
observations is roughly consistent with our ground-based site being impacted
by relatively more smoldering combustion (MCE ∼0.87±0.02, based on
Fig. 2b) than airborne studies on average (MCE
0.91, Liu et al., 2017; 0.90, Sahu et al., 2012; 0.883, Urbanski,
2013). Liu et al. (2017) calculated an average
annual CO production from western US wildfires for 2011–2015 of 5240±2240 Gg, which they reported was in good agreement with an EPA estimate
based on a similar burned area in the 2011 National Emissions Inventory
(4894 Gg). Ratioing to the Liu et al. (2017) estimate with the average field
study ΔBC/ΔCO in Table 2 (0.0014±0.0002) suggests
that western US wildfires emit 7.3±3.3 Gg of BC per year. This is
significantly lower than a previous estimate, but the other estimate is not
strictly comparable since it is based on EC measurements and for a different
year (2006) (Mao et al., 2015).
Time-weighted study-average enhancement ratios (g g-1 ratioed
to CO) compared to emission ratios reported in other studies.
RatiosThis workSelimovic etSelimovic etLiu et al.Sahu et al.Hobbs et al.al. (2018)aal. (2018)b(2017)c,d(2012)(1996)eBC / CO0.0012 (0.0005)0.00870.00180.0016 (0.0018)0.00140.0103BC / PM2.50.0095 (0.0003)––0.0060 (0.0054)––PM2.5/ CO0.1263 (0.0015)––0.2661 (0.1342)–0.4923
a Measured lab values at lab fire MCE.
b Calculated from EF versus MCE fit based on average wildfire MCE
reported in Liu et al. (2017). c Average of Rim Fire and Big
Windy Complex. BC data were analyzed for Liu et al. (2017) study but not
reported. d PM values reported are PM1.0. e PM
values reported are PM3.5.
Changes in the ΔPM/ΔCO ratio as a plume ages can be used
as a metric for the net effect of secondary formation or evaporation of
organic and inorganic aerosol (Yokelson et al., 2009; Akagi et al., 2012;
Jolleys et al., 2012; Vakkari et al., 2014, 2018). Table 2 indicates that our
ground-based ΔPM2.5/ΔCO (0.126±0.002) is about
half that obtained at aircraft altitudes in fresher wildfire smoke (0.266±0.134) as reported by Liu et al. (2017) and ∼4 times less than
that reported for very fresh smoke by Hobbs et al. (1996) (0.492). Further,
our lower ΔBC/ΔCO ratio suggests enhanced smoldering,
which should preclude a large drop in ΔPM/ΔCO (Reisen et
al., 2018). Liu et al. (2017) and Forrister et al. (2015) measured smoke
aging for the Rim Fire (a large California wildfire) as the plume aged and
found that the ΔOA/ΔCO ratio started high and then dropped
to a value (0.125±0.025) similar to our ΔPM2.5/ΔCO. However, Collier et al. (2016) found no age dependence for ΔOA/ΔCO for plumes intercepted at Mount Bachelor or on the G-1 aircraft
and obtained a value for ΔOA/ΔCO (0.25±0.07) close
to both the ΔOA/ΔCO and ΔPM1.0/ΔCO
of Liu et al. (2017) in fresh Rim Fire smoke. Taken together, these
observations suggest that, on timescales up to ∼1–2 days for the
wildfire smoke studied to date, aging and/or higher average ambient
temperatures at lower elevations may encourage some OA evaporation and reduce
downwind PM impacts. Some studies in other fire types have found secondary
formation to dominate at low elevation (Yokelson et al., 2009; Vakkari et
al., 2014), so it is premature to generalize this observation to all BB, and
more study is needed. However, both of the latter studies measured smoke from
smaller fires within a few hours of the source, and our lower ΔPM2.5/ΔCO indicates that evaporation of PM dominated over formation
of PM as smoke was transported to the Missoula valley in smoke that was
between several hours and several days old.
The climate impacts of smoke are strongly related to the ΔBC/ΔPM ratio and also the SSA and BrC, which are described in more
detail in other sections. The ΔBC/ΔPM ratio also allows
for a rough estimate of ambient BC from ambient PM data when BC is not
measured, but caution is needed since PM may not be conserved as long as BC,
and ΔBC/ΔPM is also variable at the source. Our
study-average ΔBC/ΔPM2.5 ratio (0.0095; Fig. 3) is
higher than the study-average ΔBC/ΔPM1.0 in Liu et
al. (2017, 0.006) but falls within the range observed for two wildfires
measured in Liu et al. (2017), despite the differences in measurement
techniques (PM2.5 versus PM1.0, etc.). It's possible that the
ΔBC/ΔPM ratio reported in this study is up to
∼30 % too high if we consider the effects of coating on BC and
lensing as a positive error (Pokhrel et al., 2017). Previous studies found
that smoldering combustion emits anywhere between 2–49 times more PM than
flaming combustion (Jen et al., 2019; Kim et al., 2018; Reisen et al., 2018;
Yokelson et al., 2013a), so the combination of our ΔBC/ΔCO
ratio that is indicative of more smoldering combustion and a BC/PM ratio that
is similar to or slightly above measurements closer to fire sources (Liu et
al., 2017) again suggests that some net evaporation of PM is occurring at
lower, warmer altitudes during transport between the wildfire sources and our
surface site. Reduced light levels at night or in thick plumes could delay secondary aerosol formation in wildfire smoke. Again, this is worth
more study since this could modify air quality and health effects.
ΔBC/ΔPM ratio based on linear regression of 1 h
data.
OA is the main component of wildfire PM, and
the ΔBC/ΔPM ratio is likely similar to the ΔBC/ΔOA ratio. Our ΔBC/ΔPM ratio (∼1 %)
then suggests that the aerosol measured was overwhelmingly organic and thus
strongly cooling, especially if the impact of BrC or lensing was small.
Further, the mass absorption coefficient (MAC) for OA scales with the
ΔBC/ΔOA ratio (Saleh et al., 2014), so we anticipate a low
MAC, which is explored more next.
UV absorption by brown carbon
While the attribution of BrC is not exact and varies across studies (Pokhrel
et al., 2017), BrC absorption will offset the climate cooling calculated for
purely scattering OA depending on the amount emitted, its MAC, and its
lifetime (Feng et al., 2013). One field study of BrC lifetime suggests a
significant decrease of BrC over the course of a day but a prolonged
persistence of BrC nonetheless (∼6 % above background even after
50 h following emission) (Forrister et al., 2015), and studies of relevant
chemical mechanisms involving BrC have shown both increases and decreases
(Lin et al., 2015; Liu et al., 2016; Xu et al., 2018). Satellite retrievals
employing reasonable a priori aerosol layer heights indicate that BrC can
have a strong impact in fresh BB plumes and a persistent significant impact
in downwind regional haze (Jethva and Torres, 2011; Hammer et al., 2016).
Here we present in situ data showing persistent widespread regional impacts
of BrC. Table 3 lists the study-average AAE and percent contribution to
absorption at 401 nm by BrC. We interpret our results by comparing them to
the limited measurements of wildfire smoke in the lab and field and
measurements for “flaming-dominated” savanna fires (Selimovic et al., 2018;
Forrister et al., 2015; Eck et al., 2013). Theoretically, aerosol absorption
that is dominated by black carbon would have an AAE close to 1.0 (Bergstrom
et al., 2002; Bond and Bergstrom, 2006; Bergstrom et al., 2007), which is the
case in Eck et al. (2013), who report an average AAE of 1.20 for measurements
of savannah fires in southern Africa. On the other hand, Selimovic et
al. (2018) and Forrister et al. (2015) calculated AAEs for fresh smoke of
3.31 and 3.75, respectively, for various mixed coniferous fuels burned in a
laboratory and in the field. Our study-average AAE (1.96±0.38) is
almost 2 times lower than the average value recommended for fresh wildfire
smoke (∼3.5) in Selimovic et al. (2018) but higher than that reported
in Eck et al. (2013). This is also the case for the percent contribution to
absorption at 401 nm by BrC, where a lower AAE corresponds to lower BrC
absorption. The AAE recommended for fresh wildfire smoke implies the %
absorption by BrC at 401 nm is close to 86 %, but we still see
significant (∼50 %) absorption by BrC at 401 nm, on average,
despite some aging of the smoke at our site.
Time-weighted study-average AAE and % BrC contribution compared
to other studies.
This workSelimovic etSelimovic etForrister etEck et al.al. (2018)aal. (2018)bal. (2015)(2013)AAE1.96 (0.38)2.80 (1.57)3.313.751.20% BrC50.7 (12.8)64.2 (17.2)78.0––
a Measured lab values at lab fire MCE.
b Calculated from average wildfire MCE reported in Liu et
al. (2017).
(a) Plot of the peak-integrated ΔNH3/ΔCO ratio versus our size and age proxy
(401 scattering/870 scattering) for smoke impacts that have an ΔNH3/ΔCO ratio. (b) Plot of the peak-integrated absorption
Ångström exponent versus our size and age proxy
(401 scattering/870 scattering) when both PAXs were operational.
Although we cannot determine precise smoke ages in this study, we can
construct an analysis of our data that probes the trend in AAE and %
absorption by BrC with aging. We start by noting that Mie scattering
calculations (John Walker, personal communication, 2017) imply that the ratio
of Bscat401/Bscat870 should decrease as average
particle size increases (e.g., Schuster et al., 2006; Eck et al., 1999;
Kaufman et al., 1994), and average particle size is well known to increase
with particle age (Akagi et al., 2012; Eck et al., 2013; Capes et al., 2008;
Carrico et al., 2016). We also show in Fig. 4a that the ΔNH3/ΔCO ratio decreases with
Bscat401/Bscat870, and we know NH3/CO
decreased with aging with a ∼5 h half-life in the fall and under
slower photochemical conditions in Table 2 in Akagi et al. (2012). Thus, the
range in Bscat401/Bscat870 shown in Fig. 4a represents
about 10 h of daytime aging. We also see a weak trend but significant
decrease in AAE over a similar range of our size and age parameter in
Fig. 4b. Our data for AAE versus a proxy for average age of mixed-age smoke
are more variable than the AAE versus known transport time for a single plume
in Forrister et al. (2015) but still support a similar conclusion: the net
effect of BrC aging is a substantial decrease in AAE over the course of
∼10 h of aging.
We also speculate that, in addition to aging, the time of day that smoke is
formed may impact BrC and AAE. We motivate that hypothesis next and then
explore the issue in subsequent sections. Selimovic et al. (2018) showed that
BrC accounted for most of the absorption at 401 nm when MCEs were in a low
range associated with dominant smoldering combustion. Benedict et al. (2017)
further observed that smoke impacts from a nearby wildfire had a much higher
smoldering to flaming ratio at night than during the day, which then suggests
the potential for increased BrC formation at night (Saide et al.,
2015). It is also known that smoldering combustion
of biomass emits many precursors, including monoterpenes, furans, and cresol
(Stockwell et al., 2015), which can react quickly with the major nighttime
oxidant, NO3, and ostensibly form UV-absorbing organic nitrates
that could augment BrC. In fact, estimates using current data strongly
suggest that a substantial nighttime secondary BrC source could exist. The EF
for primary organic aerosol (POA) produced by BB typically ranges from 3 to
30 g kg-1 (May et al., 2014; Liu et al., 2016, 2017). The EF for known
plus unidentified non-methane organic gases (NMOGs) with intermediate to low
volatility ranges from 3 to 100 g kg-1. Converting even a small
percentage of the co-emitted NMOGs that are known to react quickly with
NO3 could yield substantial amounts of BrC and build up a reservoir
of BrC during dark hours. Once daytime commences, other studies show that
some types of BrC, depending on the precursor, can experience rapid
photochemical degradation or formation via both direct photolysis and
oxidation (Zhao et al., 2015; Lee et al., 2014; Zhong and Jang, 2014; Sareen
et al., 2010). In summary, our extensive in situ measurements show that even
after 1–2 days of aging, BrC remains a significant component of ambient
smoke and that the climate properties of the regional haze have a non-BC
absorption contribution. However, the details of the formation and lifetime
of BrC are complicated and probably vary diurnally.
Single scattering albedo, mass absorption coefficient, mass scattering
coefficient
This section starts with an important reminder/caveat. Our scattering and
absorption data are measured for particles up to 1.0 µm, but the PM
mass reported by the Missoula DEQ site includes particles up to 2.5 µm. Thus, using our data to calculate mass absorption coefficients (MACs) and
mass scattering coefficients (MSCs) will produce lower limit values that are
not directly comparable to those obtained when the range for both optical
and mass measurements goes up to 2.5 µm. Nevertheless it is
potentially useful to link PM1.0 and PM2.5 measurements since
measurements at 1 µm cutoffs are common in field campaigns, but
PM2.5 still remains the common measurement in regional networks.
Our MAC and MSC values were calculated by plotting 1 h averages of
Bscat401, Babs401, Bscat870, and
Babs870 versus the 1 h PM2.5 values to calculate an
MSC(401), MAC(401), MSC(870), and MAC(870), respectively (Fig. S1). Values at
other wavelengths were calculated with a power law fit using the calculated
averages (Table 4). Our (ΔPM1.0/ΔPM2.5) MSC values are lower than those reported for
PM2.5/PM2.5 but still potentially useful. For instance, the
ΔPM1.0/ΔPM2.5 MSC at 870 nm is one to a good
approximation, which suggests a convenient way to estimate PM2.5
directly from PAX-870 scattering data. Using a 1 µm cutoff probably
isolated the combustion-generated OA and BC pretty well, but dust, ash, and
biological particles can be physically entrained in wildfire plumes (Formenti
et al., 2003; Gaudichet et al., 1995; Hungershoefer et al., 2008). The
particles in the 1.0–2.5 µm range are a small part of the total
mass in smoke emissions (Reid et al., 2005a), but they contribute
disproportionately to the scattering. The additional absorption that we might
have measured with a 2.5 µm cutoff may be less significant. Our
study-average MAC at 401 nm is only 0.19±0.08 m2 g-1,
consistent with a low BC / OA ratio (Saleh et al., 2014).
SSA, AAE, and SAE are commonly used to calculate aerosol absorption and
scattering in models and satellite retrievals (Ramanathan et al., 2001;
McComiskey et al., 2008). Uncertainty in the SSA is one of the largest
sources of uncertainty in estimating the radiative effect of aerosols (Jiang
and Feingold, 2006; McComiskey et al., 2008). Some models and satellite
(e.g., MODIS) retrievals assume a constant value of SSA for fire aerosol
throughout the biomass burning season and the entire year, which may be an
inaccurate approach. Eck et al. (2013) found an increase in SSA at 550 nm
from 0.81 in July to 0.88 in October in southern Africa. In Fig. 5 we present
evidence for an increase in the SSA for moderately aged wildfire smoke over a
prolonged period of biomass burning. While we did not directly measure SSA at
550 nm, we did measure SSA at 870 nm for the duration of the sampling
period and SSA at 401 nm for the duration that the PAX 401 was operational.
Figure 5 shows a moderate increasing trend in the SSA at
870 nm but no significant trend in the SSA at
401 nm. It could be that because the sampling period of the PAX 401 nm only
covers ∼2 weeks, any trend that may be present is not apparent within
this time frame. Table 4 shows our study-average SSA
at 870 and 401 nm, both of which are ∼0.93, which is similar to the
SSA reported at 550 nm in McMeeking et al. (2005b) of 0.92. Our SSA and the
SSA reported in McMeeking et al. (2005b) are higher than the sometimes quoted
typical surface SSA of the earth (∼0.9; Praveen et al., 2012), which
suggests that the wildfire PM1.0 in regional haze would contribute to
regional cooling (Thornhill et al., 2018; Kolusu et al., 2015). Conversely,
an SSA range like that reported in Eck et al. (2013) could contribute to
warming, which could potentially contribute to a positive-feedback cycle
associated with biomass burning (Jacobsen, 2014).
Plot of single scattering albedo over the course of the ambient
smoke-monitoring period. Points represent SSA from absorption and scattering integrated
over smoke-impacted events.
Time-weighted study-average SSA, MAC, and MSC compared to other
works.
a In this work MAC and MSC values are PM1.0
absorption and scattering divided by PM2.5 mass, and values between 401
and 870 nm are obtained from power law fits. b Measured values
at lab fire MCE. c Calculated from EF versus MCE fit based on
average wildfire MCE reported in Liu et al. (2017). d McMeeking
et al. (2005b). e McMeeking et al. (2005a).
Case study: Labor Day weekend
Figure 6 highlights our data for Labor Day weekend (LDW), spanning
∼50 h from 4 to 5 September 2017. We focus on this time period
because it includes the largest impacts in Missoula, a regional
smoke-production episode detected as far downwind as Europe (An American
Aerosol in Paris, 2019; Ansmann et al., 2018), and an opportunity to compare
what is likely smoke from one fire, subjected to different processing
scenarios. Peak “V” is smoke that was likely primarily produced at night
and transported to Missoula at night before subsequent photochemistry and
dilution in the Missoula Valley. In contrast, peak “W” is smoke that was
likely produced and transported during the day before aging in Missoula.
Surface winds observed coming from the east, our back trajectory
calculations, and satellite observations along with the high concentration
values of peak V all imply that the smoke was mostly sourced from a local
fire (Rice Ridge) and about 2–4 h old. Our peak-integrated proxy for
particle size (4.02, smaller particle size) and the peak-integrated
ΔNH3/ΔCO ratio (9.66×10-3) for peak V
suggest that the smoke retained fairly fresh characteristics even factoring
in the daytime tail on the peak (Table S2). The peak integrated AAE (2.88) is
the highest observed value for AAE from this study for any peak for which an
AAE could be derived. The same is true for the %401 absorption by BrC
(∼77 %). The UV absorption results are within the range observed
for fresh smoke reported in Selimovic et al. (2018) and reiterated again
earlier in Table 3, which lists average AAE values for fresh smoke between
2.80 and 3.75 (Forrister et al., 2015). Average values for %401 absorption
by BrC in fresh smoke ranged between 64 % and 86 % (Selimovic et al.,
2018), and again our integrated result for peak V falls in this range. In
summary, the moderately aged, strongly night-influenced peak has properties
not inconsistent with significant amounts of BrC due to smoldering combustion
or substantial nighttime BrC formation via reactions with NO3 or
O3.
High-resolution (5 min) time series of smoke impacts measured in
Missoula over Labor Day weekend (see Sect. 3.6).
While not readily apparent via satellite observations due to stacked smoke
layers, our back trajectory calculations, a similar peak shape on an upwind
monitor, visual observations of a wall of smoke arriving from the northeast,
and high concentrations of PM at the Missoula measuring site strongly suggest
that peak W, with an onset in the early evening, also mostly came from
the Rice Ridge Fire as daytime produced/processed smoke. Peak W has a
401/870 scattering ratio (2.65) that implies larger particle sizes and an
ΔNH3/ΔCO ratio (0.0044) that is ∼50 % that
of Peak V. The ratio of ΔC2H4/ΔCO decreases by
∼30 % from peak V to peak W. The AAE for peak W is 2.00,
which is ∼30 % less than the AAE for Peak V, and corresponds
to a lower %401 absorption by BrC for the evening-onset peak
(∼54 %). Taken together, these values imply larger particles and
more photochemically aged smoke. Interestingly, the ratios of ΔCH4/ΔCO and ΔBC/ΔCO are essentially similar for
peaks V and W. This implies the flaming to smoldering ratio at the source
for these events was similar (NO3 chemistry could still have been
more important for peak V). While nighttime wildland fire combustion may
normally be more smoldering-dominated, LDW was marked by an unusual lack of
nighttime RH recovery and an aggressive doubling of the fire size. Thus data
from a different, more typical period are likely needed to probe diurnal
differences in fresh smoke.
Diurnal cycles
Diurnal cycles of smoke measured in Missoula provide some insight into
regional meteorological effects and have some potential to further probe the
day versus night flaming to smoldering issues raised in the previous section
(Sect. 3.6). There is, however, a variable delay
from production to receptor. Figure 7 shows the diurnal cycle of CO and the
average hourly PM2.5 measured across the entirety of the smoke sampling
period. Levels of CO and PM2.5 peak together from about 05:00 to 11:00,
which is consistent with increased smoldering at night but would also reflect
the mixed layer height. Figure 8 shows the diurnal cycles of PM2.5,
hourly average BC, and hourly average %401 absorption by BrC
(27 August to 10 September 2017). In this case we
see that potential BrC absorption peaks in the early morning while BC peaks
in the evening. One possible explanation for this is that despite variation
in mixed layer height, there is typically an increase in the flaming to
smoldering ratio that produces more black carbon and less brown carbon during
the day. If nearby (less diluted) fires with shorter transport times strongly
influence the peak times, a signal of diurnal variation at the source could
be partially evident at our site. However, we cannot rule out that an
increase in photo-bleaching throughout the middle of the day impacts the peak
position for absorption by BrC, but even then, the absorption by BrC remains
about half of the absorption at 401 nm on average.
Diurnal plot of CO and PM2.5, shown for the entirety of the
monitoring period.
Diurnal plot of average PM2.5, hourly average
%401 absorption by BrC, and hourly average BC. BC and PM shown for the
entirety of the monitoring period but %401 absorption by BrC only shown
for when the PAX 401 was operational.
Brief comparison to prescribed fire data
Of the 718 h we sampled during August and September 2017, 500.5 h were part
of a smoke event, which is close to three-quarters (∼70 %) of the
total monitoring time period. Of the total 718 h of monitoring, over half
(56 %) violated the National Ambient Air Quality Standards (NAAQS) for
allowable PM2.5 averaged over 24 h (35 µg m-3). The
hourly average for the entire sampling period of
∼54µg m-3 of PM2.5 is an average exceedance of
the 24 h NAAQS standard by 42 %. One possible approach to minimizing
wildfire air-quality impacts is preemptive prescribed burning. Prescribed fires
reduce hazardous fuels, burn less fuel per unit area, make less smoke per
unit fuel consumption, and can be ignited when conditions are favorable for
minimizing air quality impacts (Liu et al., 2017).
Comparison of wildfire emission/enhancement ratios to prescribed
fire emission ratios (g g-1).
RatiosThis workLiu et al.May et al.May et al.(2017)a,b(2014)b(2014)b,cBC / CO0.0012 (0.0005)0.0016 (0.0018)0.013 (0.007)0.006BC / PM2.50.0095 (0.0003)0.0060 (0.0054)0.163 (0.019)0.048PM2.5/ CO0.1263 (0.0015)0.2661 (0.1342)0.080 (0.030)0.11 (0.01)
a Average of Rim Fire and Big Windy Complex. BC data
were analyzed for Liu et al. (2017) study but not reported. b PM
values reported are PM1.0. c Values for the Shaver and
Turtle fires (prescribed burns).
It is of interest to compare our large sample of ambient wildfire data to
the comparatively rare data from airborne wildfire studies and prescribed
fire data to see if our large sample size supports the earlier (Liu et al.,
2017) conclusions regarding the nature of the smoke and emissions. More
strongly supported conclusions can reinforce the land management
implications. Table 5 lists the ΔBC/ΔCO, ΔBC/ΔPM, and ΔPM/ΔCO ratios for our ambient wildfire study, the
airborne wildfire study from Liu et al. (2017), and prescribed fire values
reported in May et al. (2014). The ΔPM/ΔCO values for fresh
wildfire smoke in Liu et al. (2017) and aged wildfire smoke (this study) are
about 3 and 1.5 times higher than ΔPM/ΔCO for fresh
smoke from prescribed fires in May et al. (2014) when comparing to all their
US prescribed fires (Table 5). For only prescribed fires in western US
mountain coniferous ecosystems (last column Table 5), the ΔPM/ΔCO for fresh smoke is close to our value for aged wildfire smoke. However,
May et al. (2015) noted that ΔPM/ΔCO decreased by about a
factor of 2 after several hours of aging on at least one prescribed fire.
The ΔBC/ΔCO for prescribed fires is higher than the
wildfire average by a factor of ∼9 (all prescribed fires) or ∼4
(last column), roughly suggesting a higher MCE for prescribed fires. Ignoring
smoke age, the ΔBC/ΔPM for prescribed fires is higher than
the wildfire average by a factor of ∼20 (all prescribed fires) or
∼6 (last column). The ΔBC/ΔPM observations suggest
that wildfire smoke is overwhelmingly more organic, which is important partly
because many optical properties scale with the BC / OA ratio (Saleh et
al., 2014). In general, our ground-based wildfire study confirms the earlier
airborne indications that prescribed fires are less smoky but also less
cooling than wildfires. Differences in smoke production and chemistry between
wild and prescribed fires should be researched more and have air quality and
land management implications.
Conclusions
A major, prolonged wildfire smoke and haze episode impacted the NW US and SW
Canada during August through September of 2017. During this episode, we
collected over 500 h of data characterizing smoke and haze properties with a
FTIR and PAXs at 870 and 401 nm at a ground-based site in Missoula, Montana.
This is probably the most extensive real-time data on wildfire smoke
properties to date. Our low ΔBC/ΔPM (0.0095±0.0005)
ratio confirmed the overwhelmingly organic nature of the smoke observed in
the airborne studies of wildfire smoke to date. Our ΔBC/ΔCO ratio (0.0012±0.0005) for our ground site was moderately lower than
observed in aircraft studies, suggesting a relatively larger contribution
from smoldering combustion. Despite our lower ΔBC/ΔCO
ratio our ΔPM/ΔCO ratio was about half that measured in
fresh smoke from aircraft. Taken together with aircraft measurements in aged
wildfire smoke, this suggests that OA evaporation, at higher ambient
temperatures nearer the surface, may typically reduce wildfire PM air quality impacts on the
timescale of several hours to days. Bscat401/Bscat870
was used as a proxy for size and age of the smoke particles, with this
interpretation being supported by the trace gas data. The size and age proxy
implied that AAE decreased significantly after about 10 h of smoke aging,
consistent with the single BrC lifetime measurement in an isolated plume. The
results clearly show that non-BC absorption can be important in “typical”
regional haze and moderately aged smoke with BrC accounting for about half
the absorption at 401 nm on average for the entire data set. The diurnal
trends show BrC, PM, and CO peaking in the early morning and BC peaking in
the early evening. Over the course of 1 month, the SSA at 870 nm increased
from ∼0.9 to ∼0.96.
Data availability
Raw data used to derive ERs and other quantities reported
that are not included in the supplement can be obtained by contacting the
corresponding author.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-3905-2019-supplement.
Author contributions
VS and RJY conducted the UM measurements and the data analysis.
VS, RJY, GRM, and SC contributed to the discussion and interpretation of the
results and writing of the manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
Vanessa Selimovic and Robert J. Yokelson were supported by the NSF grants
AGS-1748266 and AGS-1349976, NOAA-CPO grant NA16OAR4310100, and NASA grant
NNX13AP46G to UM. Gavin R. McMeeking was supported by the NOAA-CPO grant
NA16OAR4310109. Purchase and preparation of the PAXs was supported by NSF
grant AGS-1349976 to Robert J. Yokelson. We thank John Walker for providing us with Mie
scattering calculations.
Review statement
This paper was edited by Ilona Riipinen and reviewed by three anonymous referees.
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