Atmos. Chem. Phys., 16, 15185–15197, 2016www.atmos-chem-phys.net/16/15185/2016/doi:10.5194/acp-16-15185-2016© Author(s) 2016. CC Attribution 3.0 License.

Physical and optical properties of aged biomass burningaerosol from wildfires in Siberia and the Western USAat the Mt. Bachelor ObservatoryJames R. Laing1, Daniel A. Jaffe1,2, and Jonathan R. Hee1

1School of Science and Technology, University of Washington Bothell, Bothell, WA, USA2Department of Atmospheric Science, University of Washington, Seattle, WA, USA

Correspondence to: Daniel A. Jaffe (djaffe@uw.edu)

Received: 15 June 2016 – Published in Atmos. Chem. Phys. Discuss.: 30 June 2016Revised: 14 October 2016 – Accepted: 17 October 2016 – Published: 8 December 2016

Abstract. The summer of 2015 was an extreme forestfire year in the Pacific Northwest. Our sample site at theMt. Bachelor Observatory (MBO, 2.7 km a.s.l.) in centralOregon observed biomass burning (BB) events more than50 % of the time during August. In this paper we charac-terize the aerosol physical and optical properties of 19 agedBB events during August 2015. Six of the 19 events were in-fluenced by Siberian fires originating near Lake Baikal thatwere transported to MBO over 4–10 days. The remainderof the events resulted from wildfires in Northern Californiaand Southwestern Oregon with transport times to MBO rang-ing from 3 to 35 h. Fine particulate matter (PM1), carbonmonoxide (CO), aerosol light scattering coefficients (σscat),aerosol light absorption coefficients (σabs), and aerosol num-ber size distributions were measured throughout the cam-paign. We found that the Siberian events had a significantlyhigher 1σabs/1CO enhancement ratio, higher mass absorp-tion efficiency (MAE; 1σabs/1PM1), lower single scatter-ing albedo (ω), and lower absorption Ångström exponent(AAE) when compared with the regional events. We sug-gest that the observed Siberian events represent that portionof the plume that has hotter flaming fire conditions and thusenabled strong pyroconvective lofting and long-range trans-port to MBO. The Siberian events observed at MBO there-fore represent a selected portion of the original plume thatwould then have preferentially higher black carbon emissionsand thus an enhancement in absorption. The lower AAE val-ues in the Siberian events compared to regional events indi-cate a lack of brown carbon (BrC) production by the Siberianfires or a loss of BrC during transport. We found that mass

scattering efficiencies (MSE) for the BB events ranged from2.50 to 4.76 m2 g−1. We measured aerosol size distributionswith a scanning mobility particle sizer (SMPS). Number sizedistributions ranged from unimodal to bimodal and had ge-ometric mean diameters (Dpm) ranging from 138 to 229 nmand geometric standard deviations (σg) ranging from 1.53 to1.89. We found MSEs for BB events to be positively corre-lated with the geometric mean of the aerosol size distribu-tions (R2

= 0.73), which agrees with Mie theory. We did notfind any dependence on event size distribution to transporttime or fire source location.

1 Introduction

Biomass burning (BB) is a major source of aerosol in theatmosphere (Andreae and Merlet, 2001; Bond et al., 2004).BB particles are predominantly organic carbon (OC) andblack carbon (BC), with some inorganic material (Reid et al.,2005b; Vakkari et al., 2014). These particles can significantlyimpact the Earth’s radiative balance and climate through di-rect and indirect aerosol effects. The direct effects on radia-tive forcing are due to the light scattering and absorption ofthe aerosol (Boucher et al., 2013; Haywood and Boucher,2000), and the indirect effects are caused by particles act-ing as cloud condensation nuclei (CCN) which affect cloudalbedo (Pierce et al., 2007; Spracklen et al., 2011). Accord-ing to the IPCC 2013 report the largest uncertainty in deter-mining global radiative forcing comes from quantifying thedirect and indirect effects of aerosols (Boucher et al., 2013).

Published by Copernicus Publications on behalf of the European Geosciences Union.

15186 J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol

Biomass burning is a major contributor to global aerosol bur-den and it has been predicted that these emissions are likelyto increase due to climate change, particularly in the borealforests of North America and Russia (Flannigan et al., 2009;Stocks et al., 1998) and in the Western USA (Y. Liu et al.,2014; Westerling et al., 2006). This makes the proper char-acterization of aged BB emissions even more important.

Currently there are few field measurements of well-agedBB emissions. Our knowledge of BB aerosol primarilycomes from laboratory experiments and near-field measure-ments taken within a few hours of a wildfire (May et al.,2015, 2014; Okoshi et al., 2014; Vakkari et al., 2014; Yokel-son et al., 2013b, 2009). Holder et al. (2016) showed that lab-oratory measurements of aerosol optical properties do not ac-curately reproduce field measurements. Freshly emitted BBparticles are small in diameter (30–100 nm) (Hosseini et al.,2010; Levin et al., 2010). As the plume ages, the aerosolundergoes rapid chemical and physical changes on the timescale of minutes to hours (Reid et al., 2005a, b; Vakkari et al.,2014). The change in particle size is due to coagulation andthe condensation of organic material onto the existing parti-cles (Reid et al., 2005b; Seinfeld and Pandis, 2006). The co-agulation rate can be very high in fresh BB plumes since thisis equivalent to the square of particle number concentration.This process increases the size of the particles while decreas-ing the number concentration. Condensation of secondaryorganic aerosol (SOA) onto particles in BB plumes also in-creases particle size. The condensation of SOA is counter-balanced by the loss of primary organic aerosol, which canevaporate during plume dilution (May et al., 2015, 2013).The net condensation/evaporation effect is highly variable.Some studies have observed an increase in mass with plumeage due to SOA production (Briggs et al., 2016; Hobbs, 2003;Vakkari et al., 2014; Yokelson et al., 2009), while others haveobserved limited SOA formation (Akagi et al., 2012; Jolleyset al., 2015). All of these uncertainties in the aging process ofbiomass burning underscores the importance of characteriz-ing the physical and optical properties of well-aged biomassburning aerosol.

In this study we analyze 19 aged BB events observed in thesummer of 2015 at Mt. Bachelor in Oregon. The BB eventsconsisted of regional events (fires in Northern California andSouthwestern Oregon; transported 3–35 h) and Siberian fireevents (fires around Lake Baikal; transported 4–10 days). Weinvestigated the aerosol optical and physical properties ofthese events and explored their variation with source loca-tion and transport time. This study addresses the followingquestions:

– What are the differences in the optical properties of re-gional and Siberian BB events observed at Mt. BachelorObservatory (MBO)?

– What is the range of mass scattering efficiencies for BBevents and what explains their variability?

– What is the range in aerosol size distributions of BBevents at MBO and how does this vary with plume age?

2 Methods

2.1 Mt. Bachelor Observatory

The Mt. Bachelor Observatory is a mountaintop site that hasbeen in operation since 2004 (Jaffe et al., 2005). It is lo-cated at the summit of Mt. Bachelor in central Oregon, USA(43.98◦ N, 121.69◦W; 2764 m a.s.l.). A suite of measure-ments (including carbon monoxide, CO, ozone, O3, aerosolscattering coefficients, and more) have been made contin-uously at the summit site. Previous studies have observedBB plumes in the free troposphere from regional and distantsources in the spring, summer, and fall (Baylon et al., 2015;Briggs et al., 2016; Collier et al., 2016; Timonen et al., 2014;Weiss-Penzias et al., 2007; Wigder et al., 2013) and long-range transport of Asian pollution in the spring (Ambrose etal., 2011; Fischer et al., 2010a, b; Gratz et al., 2014; Jaffe etal., 2005; Reidmiller et al., 2010; Timonen et al., 2014, 2013;Weiss-Penzias et al., 2006). During the summer of 2015 anintensive field campaign was performed at MBO to measureaerosol physical and optical properties of wildfire emissions.

2.2 CO, CO2, and meteorological data

CO and CO2 measurements were made using a Pi-carro G2302 cavity ring-down spectrometer. Calibrationswere performed every 8 h using three different NationalOceanographic and Atmospheric Administration (NOAA)calibration gas standards, which are referenced to the WorldMeteorological Organization’s (WMO) mole fraction cali-bration scale (Gratz et al., 2014). Total uncertainty based onthe precision of calibrations over the campaign was 3 %. Ba-sic meteorology measurements, such as temperature, humid-ity, and wind speed, were also measured continuously (Am-brose et al., 2011).

2.3 Aerosol instruments

We measured dry (relative humidity (RH) less than 35 %)aerosol scattering and absorption coefficients, aerosol num-ber size distribution, and particle mass during the 2015 sum-mer campaign in 5 min averages. An inline 1 µm impactorwas located prior to the aerosol instruments. The aerosolinstruments were located in a temperature-controlled roomwithin the summit building, situated approximately 15 m be-low the inlet. The aerosol sample line was situated such thatthe last 2.5 m was located within a space that was tempera-ture controlled at 20± 3◦ C, typically 10–20◦ C warmer thanambient. RH of the sampled air was less than 35 % through-out the campaign. The temperature increase from going out-side into the heated building reduced the RH of the sample.RH was measured in the sample airstream by the nephelome-

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J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol 15187

ter and scanning mobility particle sizer (SMPS). The averageRH during the campaign measured by the nephelometer andSMPS was 22.1 and 22.6 %, respectively. Ninety-five percentof the 5 min averaged samples had an RH less than 30 %.

We measured multi-wavelength aerosol light scatter-ing coefficients (σscat) using an integrating nephelometer(model 3563, TSI Inc., Shoreview, MN) at wavelengths 450,550, and 700 nm. During the 2015 campaign the TSI neph-elometer was periodically switched to measure both particlefree air and CO2. The measured values were corrected foroffset and calibration drift in addition to angular nonideali-ties (Anderson and Ogren, 1998). The filtered air and CO2were measured approximately every 2 weeks (Anderson andOgren, 1998). The data reduction and uncertainty analysisthat we followed for the scattering data are outlined by An-derson and Ogren (1998). Sources of uncertainties associatedwith the nephelometer include photon counting noise, zero-ing and calibration, and the correction for angular nonideali-ties. Combined these uncertainties yielded total uncertaintiesof ∼ 15 % during BB events.

We measured aerosol light absorption coefficients (σabs)

with a 3λ tricolor absorption photometer (TAP, BrechtelInc., Hayward, CA) at wavelengths 467, 528, and 660 nm.Throughout the paper σscat and σabs values represent mea-surements taken at 550 and 528 nm, respectively. The TAPis a new instrument that uses the same operating princi-ple as the Particle Soot Absorption Photometer (PSAP) andthe same filters (47 mm PALL E70-2075W). Unlike thePSAP, the TAP rotates through eight filter spots per indi-vidual filter along with two reference spots. During deploy-ment at MBO, the TAP was set to rotate to the next filter spotwhen a filter spot’s transmission reached 50 %. The absorp-tion coefficients were corrected using the filter loading andaerosol scattering correction factors derived for the 3λ PSAPby Virkkula (2010). Uncertainty calculations were based onthose used in a previous study at MBO for measurementswith a 3λ PSAP (Fischer et al., 2010a). Sources of uncer-tainty include noise, instrument drift, errors in the loadingfunction, the correction for the scattering artifact, and uncer-tainty in the flow and spot size corrections (Anderson et al.,1999; Bond et al., 1999; Virkkula et al., 2005). Combiningthese uncertainties yielded total uncertainties of ∼ 25–40 %during BB events.

Single scattering albedo (ω) for each event was calculatedas the reduced major axis (RMA) regression of scatteringand total extinction (scattering + absorption) coefficient at528 nm. To adjust the σscat value from 550 to 528 nm, a powerlaw relationship was assumed between scattering and wave-length. The 450–550 nm pair was used to adjust the 550 nmσscat measurement to 528 nm using Eq. (1):

σ 528scat = σ

550scat ×

(λ550

λ528

)SAE450,550

, (1)

where λ is wavelength and SAE is the scattering Ångströmexponent calculated with the two wavelengths specified. TheSAE values were calculated for each 5 min interval using thescattering coefficients measured at 450 and 550 nm. MeanSAE values for the BB plumes ranged from 1.61 to 2.15.Uncertainties for ω were calculated the same as the enhance-ment ratios (ERs), which is discussed in Sect. 2.4.

Absorption Ångström exponent (AAE) values were calcu-lated for the absorption coefficient pair of 467 and 660 nmusing Eq. (2):

AAE=−log

(σ 467

absσ 660

abs

)log

(467660

) . (2)

Uncertainties for AAE values were calculated by propagatingthe uncertainties from the measurements used to calculateAAE using addition in quadrature (Fischer et al., 2010a).

We measured 5 min averaged dry aerosol number size dis-tribution with a TSI 3938 SMPS. The SMPS system con-sisted of a TSI 3082 electrostatic classifier with a TSI 3081differential mobility analyzer (DMA) and a TSI 3787 water-based condensation particle counter. A total of 107 bins wereused to measure a diameter range from 14.1 to 637.8 nm. Asheath to aerosol flow ratio of 10 : 1 was used for the DMA.A multiple charge correction and diffusion loss correctionwere applied to the SMPS particle number concentration datausing the TSI software. An additional diffusion correctionfor the inlet tube (15 m, 12 L min−1) was applied assuminga laminar flow (Hinds, 1999). Prior to deployment we con-firmed the sizing accuracy of the SMPS using polystyrenelatex spheres.

We measured dry particle mass under 1 µm (PM1) withan optical particle counter (OPC, model 1.109, Grimm Tech-nologies, Douglasville, GA). This is a US EPA equivalentmethod for measuring PM2.5 mass concentration. The OPCwas factory calibrated prior to deployment.

All particle measurements (σscat, σabs, PM1, number sizedistribution) were corrected to standard temperature andpressure (STP; T = 273.15, P = 101.325 kPa).

2.4 Enhancement ratio calculations

ERs (1Y/1X) were calculated from the slope of the RMAregression of Y plotted against X. Briggs et al. (2016) cal-culated ERs of BB plumes using three different methods:one method using the RMA slope of the linear correlationof two species and two others calculating absolute enhance-ment above local background using two different definitionsof background. All three methods produced similar resultsfor 1σscat/1CO, 1NOy/1CO, and PAN /1CO but differ-ing results for 1O3/1CO. In our study we used the RMAregression method for calculating ERs of 1σscat/1CO and1σabs/1CO.

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15188 J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol

Mass scattering and mass absorption efficiencies (MSEand MAE) were calculated as the ERs of 1σscat/1PM1 and1σabs/1PM1, respectively, at 550 nm for σscat and 528 nmfor σabs. As previously mentioned, ω was calculated as theRMA regression of scattering and total extinction (scatter-ing + absorption). In all cases the enhancements (1) arelarge compared to background, thus avoiding the problemsdescribed by Briggs et al. (2016) for small enhancementsabove background.

We determined the uncertainties for the ER calculationsfrom the uncertainties in the extensive properties used in cal-culating the ERs and the uncertainty of the RMA regressionusing addition in quadrature. For example, the uncertainty in1X/1Y was calculated by adding in quadrature the uncer-tainty in the RMA regression, the uncertainty in the X mea-surement, and the uncertainty in the Y measurement.

We present both precision uncertainty and total uncer-tainty as described by Anderson et al. (1999) for all valuesderived from optical measurements. Precision uncertainty in-cludes uncertainty associated with noise and instrument drift.This is best used when comparing measurements collectedusing the same instruments and protocols. It is the appropri-ate uncertainty to consider when comparing individual BBevents seen at MBO in this study. Total uncertainty includesprecision uncertainty, the uncertainty associated with the cor-rections we applied to the data, and the uncertainty asso-ciated with the calibration method. This is the appropriateuncertainty to consider when comparing the measurementspresented in this study with data collected using other mea-surement methods.

2.5 Biomass burning event identification

We identified BB events as time periods during which 5 minambient aerosol scattering coefficients σscat > 20 Mm−1 for atleast 1 h, 5 min CO > 150 ppbv for at least 1 h, and there was astrong correlation (R2 > 0.80) between σscat and CO. To de-termine fire locations we calculated back trajectories usingthe National Oceanic and Atmospheric Administration Hy-brid Single-Particle Lagrangian Integrated Trajectory (HYS-PLIT) model, version 4 (Draxler, 1999; Draxler and Hess,1997, 1998; Stein et al., 2015). We used the Global Data As-similation System (GDAS) 1◦× 1◦ gridded meteorologicaldata from the NOAA’s Air Resources Laboratory (NOAA-ARL). Within GDAS, the grid containing MBO is locatedat ∼ 1500 m a.m.g.l. (above model ground level) so back-trajectory starting heights of 1300, 1500, and 1700 m a.m.g.l.were chosen (Ambrose et al., 2011). We identified fire loca-tions using Moderate Resolution Imaging Spectroradiome-ter (MODIS) satellite-derived active fire counts (Justice etal., 2002) and Fire INventory from NCAR (FINN) data(Wiedinmyer et al., 2011). Similar criteria for identifying BBevents have been used by Baylon et al. (2015) and Wigder etal. (2013) from data collected at MBO.

3 Results and discussion

3.1 Identified BB events and fire source identification

The summer of 2015 was a very active fire season in the Pa-cific Northwest. During the month of August 2015, 51 % ofthe 5 min averages met the criteria for a BB event, havingσscat > 20 Mm−1 and CO > 150 ppbv, including several multi-day periods (Fig. 1). We split these multi-day events up whendiscernable plumes within the event could be identified. Al-together we identified 19 events, ranging from 1.5 to 45 h induration. We use the term event, not plume, because of thelong duration of some of the events and the fact that mostBB events observed in 2015 were influenced by emissionsfrom multiple fires.

Two large multi-day events of regional BB smoke fromfires in Northern California and Southwestern Oregon dom-inated the sampling period (dotted box in Fig. 1). Transporttime from these regional fires to MBO, estimated from theback trajectories, ranged from 3 to 35 h. In between thesetwo large regional BB events there was a time period thatwas influenced by Siberian wildfires (solid box in Fig. 1).During August there were intense forest fires around LakeBaikal in Siberia, peaking on 8 August 2015 with a totalfire area of 681 km2, and an estimated CO and BC emis-sions of 3.22× 108 and 1.33× 106 kg day−1, respectively(FINN data) (Wiedinmyer et al., 2011). Transport times fromNortheast Asia to MBO during these events ranged from 4to 10 days. NASA MODIS Aqua and Terra images showthe eastward transport of smoke from the Lake Baikal firesduring this time period (NASA, 2016b). We used V3.30aerosol classification products from the Cloud-Aerosol Lidarwith Orthogonal Polarization (CALIOP) instrument on theCloud-Aerosol Lidar Infrared Pathfinder Satellite Observa-tion (CALIPSO) satellite to confirm the transport of plumesof smoke from the Siberian fires to North America (NASA,2016a; Winker et al., 2010, 2009). Aerosol plumes are iden-tified as one of six types: dust, polluted continental, polluteddust, smoke (biomass burning), clean continental, or cleanmarine aerosols (Omar et al., 2009).

3.2 Overview of summer 2015 BB events

Table 1 provides an overview of the 19 BB events from MBOduring the summer of 2015. We calculated water vapor en-hancement (1WV) to indicate the origin of the event airmass. Positive 1WV suggest the air mass ascended fromthe boundary layer (BL) to MBO, while near zero or neg-ative values mean the air mass is relatively dry and likelydescended or arrived from the free troposphere (Baylon etal., 2015; Wigder et al., 2013). All of the regional BB eventshave 1WV values≥ 1.00 g kg−1, while all of the Siberian-influenced events have 1WV values near zero or negative.The precision and total uncertainties for all of the parameters

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J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol 15189

Figure 1. Time series of CO, PM1, and aerosol scattering (σscat) at MBO during August. Threshold values (dashed black lines) used for BBevent criteria are displayed for CO (150 ppbv) and scattering (20 Mm−1). The dotted boxes represent multi-day periods of regional BB andencompasses events 2–8 and 16–19, respectively. The solid box represents the period influenced by Siberian BB and encompasses events10–15.

derived from optical measurements are provided for theseevents in Table S1 in the Supplement.

We found the1σscat/1CO (σscat at STP) ER to range from0.48 to 1.29 Mm−1 ppbv−1, with the majority of events beingbetween 0.8 and 1.25 Mm−1 ppbv−1. We found1PM1/1CO(PM1 at STP) to range from 0.18 to 0.43 µg cm−3 ppbv−1.These values are in the same range as BB plumes seen previ-ously at MBO (Baylon et al., 2015; Wigder et al., 2013).

In 2015 many fires were burning throughout the north-western USA. Thus, in contrast to previous work at MBO,we were not able to calculate transport time for any of theregional BB events observed as they were influenced by mul-tiple fires with various transport times. Figure 2 provides anexample of this and exemplifies the impossibility of deter-mining an exact transport time.

3.3 Optical properties of the BB aerosol at MBO

We observed significant differences in the optical propertiesof regional and Siberian-influenced BB events. The Siberian-influenced events had higher absorption coefficients relativeto other measurements. This resulted in higher 1σabs/1CO,higher MAE (1σabs/1PM1), and lower ω (σscat/(σscat+

σabs)) compared to regional BB events (Figs. 3 and 4). Wefound no significant differences for 1σscat/1CO or MSE(1σscat/1PM1) between regional and Siberian events. Backtrajectories for the Siberian events (events 10–15) origi-nated at high elevation over Siberia, suggesting that the BBemissions were lofted to altitudes of 4–10 km (Fig. 5). TheSiberian events at MBO were observed over the course ofa week (17–23 August 2015); therefore the back trajecto-ries in Fig. 5 represent a sustained meteorological patternthat consistently transported Siberian smoke to North Amer-ica throughout the week. Aerosol vertical profiles measuredby CALIOP corroborate the transport of BB plumes fromthe Siberian fires across the Pacific at altitudes of 4–10 km.

Figure 2. HYSPLIT back trajectories for Event 19. The blue backtrajectories have a starting height of 1700 m a.m.g.l. (above modelground level), the green a starting height of 1500 m a.m.g.l., and thered a starting height of 1300 m a.m.g.l. The squares are MODIS firespots from 27 to 29 August 2015 and are colored based on their fireradiative power (FRP).

Large BB plumes were identified over Northeast Asia and theNorth Pacific consisting primarily of BB smoke and somepolluted dust over the North Pacific from 8 to 17 August2015. Figures S1–S4 show selected CALIPSO transects from13 to 16 August 2015 over the Pacific. The location and al-titude of these plumes match the back trajectories calculatedfrom MBO for the Siberian events (Fig. 5), verifying thatevents 10–15 are heavily influenced by the Siberian fires.

We suggest that the Siberian BB events observed at MBOrepresent hotter, more flaming portions of the fires whichhave higher BC emissions and thus higher absorption en-hancements compared to the regional BB events. The hot-ter parts of the fires have more pyroconvective energy to

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15190 J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol

Table1.Identified

BB

plumes

atMB

Oduring

thesum

mer

of2015.A

llenhancementratios

areobtained

bytaking

theslope

ofa

RM

Alinear

regressionbetw

eenthe

two

species.ND

(“nodata”)indicates

missing

data.WC

inthe

MA

Ecolum

nsignifies

aw

eakcorrelation

(R2

<0.60).

Event

Eventdate

andtim

e(U

TC

)E

ventSource

fire1

WV

1σ

scat /1

CO

1σ

abs /1

CO

MSE

MA

EA

AE

ωD

pmσ

gnum

berduration

(h)location

(gkg−

1)(M

m−

1ppbv

−1)

(Mm−

1ppbv

−1)

(m2

g−

1)

(m2

g−

1)

(467–660nm

)(528

nm)

(nm)

17/31/15

15:35–17:101.58

OR

0.161.13

0.036N

DN

D3.15

0.97164

1.722

8/9/1502:55–08:55

6C

A,O

R1.62

0.89W

C3.17

0.0853.45

0.98138

1.823

8/9/1513:35–8/10/15

00:0010.42

CA

,OR

2.071.24

0.0333.29

0.0873.72

0.98156

1.74

8/10/1501:10–05:55

4.75C

A,O

R1.86

1.050.03

3.780.108

3.860.97

1821.54

58/10/15

06:05–11:405.58

CA

,OR

1.251.09

0.0343.44

0.1064.02

0.97183

1.616

8/10/1511:45–14:35

2.83C

A,O

R1.32

0.94W

C3.27

WC

4.120.99

1771.61

78/10/15

14:40–8/11/1506:15

15.58C

A,O

R1.83

1.170.032

3.640.098

3.520.98

1861.62

88/11/15

14:20–18:454.42

CA

,OR

1.111.07

0.0292.5

0.0662.74

0.98160

1.789

8/14/1510:00–15:35

5.58O

R1.12

0.480.007

2.750.042

3.060.99

1651.67

108/17/15

00:05–03:553.83

Siberia−

0.871.39

0.078N

DN

D2.48

0.95176

1.5711

8/17/1517:15–8/18/15

07:0013.75

Siberia−

0.221.06

0.060N

DN

D2.5

0.95179

1.6912

8/18/1516:05–8/19/15

16:4024.58

Siberia0.56

1.290.075

ND

ND

2.30.95

1961.64

138/19/15

17:40–8/20/1503:05

9.42Siberia

0.61.12

0.052N

DN

D2.25

0.96175

1.7614

8/22/1515:30–18:05

2.58Siberia

−3.1

1.970.078

4.760.188

3.590.96

2291.73

158/23/15

03:55–07:003.08

Siberia−

2.451.09

0.0592.84

0.1562.51

0.96162

1.8916

8/23/1509:50–8/25/15

06:5045

CA

,OR

11.13

0.0294.06

0.1073.15

0.98205

1.5817

8/25/1512:45–8/26/15

19:0030.25

CA

,OR

1.670.88

0.0273.75

0.1113.12

0.98181

1.618

8/26/1507:15–8/28/15

11:1540

CA

,OR

1.350.89

0.0313.7

0.1283.48

0.97191

1.5319

8/28/1517:40–8/29/15

06:1512.58

CA

,OR

1.540.69

ND

2.94N

DN

DN

D164

1.58R

egionalBB

events(m

ean±

SD)

1.38±

0.490.97±

0.210.03±

0.013.36±

1.030.09±

0.043.45±

1.045.71±

1.65170±

15.71.67±

0.08Siberian

BB

events(m

ean±

SD)

−0.91±

1.561.32±

0.340.07±

0.013.8±

2.050.17±

0.092.61±

0.494.16±

0.6181±

19.71.77±

0.11

WV

isw

atervaporenhancement,calculated

foreacheventby

subtractingthe

averageW

Vforthe

summ

ersampling

periodfrom

theW

Vvalue

atthetim

ew

henm

aximum

CO

was

observed.A

erosolscatteringσ

scat (550nm

)andabsorption

σabs

(528nm

)measurem

entsw

ereconverted

toST

P.M

SEand

MA

Ecalculated

asthe

1σ

scat /1

PM1

and1σ

abs /1

PM1

enhancementratios,respectively.

Dpm

isthe

geometric

mean

diameterand

σg

isthe

geometric

standarddeviation

oftheSM

PSaerosolsize

distribution.WC

indicatesa

weak

correlationin

theM

AE

column

(R2

<0.60).

ND

indicatesm

issingdata.PM

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J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol 15191

Figure 3. Scatter plots of (a) mass absorption efficiency (MAE)and (b) absorption enhancement ratio 1σabs/1CO vs. single scat-tering albedo (ω). MAE values were not calculated for four of thesix Siberian-influenced events due to missing PM1 data.

Figure 4. Box plots of (a)1σabs/1CO, (b) single scattering albedo(ω) measured at 528 nm, and (c) absorption Ångström exponent(AAE) for absorption measurements at 467 and 660 nm for regionalBB events and Siberian-influenced events. N indicates the numberof events for each box. Lower and upper whiskers represent the min-imum and maximum values, respectively. Lower and upper lines ofthe box represent the 25th and 75th percentiles, respectively. Thered line in the middle of the box represents the median, and the redplus mark represents outliers.

loft the plume high into the atmosphere where it can thenundergo long-range transport. During the ARCTAS-A flightcampaign in Alaska, Siberian fire plumes were found tohave a much larger BC /CO ratio (8.5± 5.4 ng m−3 ppbv−1)

than North American fire plumes (2.3± 2.2 ng m−3 ppbv−1)

(Kondo et al., 2011). This difference was attributed to theSiberian fires having a higher modified combustion effi-ciency (MCE). In addition, for the Siberian BB plumes theyfound MCE to increase with altitude. Jolleys et al. (2015)correspondingly found higher 1BC /1OA (1black car-bon /1organic aerosol) ratios to increase with altitude inEastern Canadian BB plumes. Intense, flaming fire plumeshave higher injection heights into the atmosphere due to en-hanced pyroconvection, whereas smoldering fires have lowthermal convective energy and are mostly contained within

Figure 5. Most of the HYSPLIT back trajectories for Siberianevents (events 10–15) plotted as a function of altitude. Roughly10 % of the back trajectories that did not follow the main transporttrack were not plotted. Forest fires from 7 to 16 August 2015 iden-tified by the Fire INventory from NCAR (FINN) fires are markedby red squares. These transects are not sequential and do not trackone plume of Siberian smoke, but rather they illustrate the extensiveeastward transport of Siberian smoke over the course of the week.The four black boxes represent the locations of smoke plumes iden-tified by CALIPSO cross sections detailed in Figs. S1–S4.

the BL. BB aerosol lofted to the free troposphere via py-roconvection is less likely to be removed and can have alonger atmospheric lifetime of up to 40 days (Bond et al.,2013). The back trajectories for the Siberian events corrobo-rate this idea. They were all relatively dry (water vapor mix-ing ratio < 5 g kg−1) with little precipitation during transport,suggesting the aerosol in the Siberian events was subjectedto very limited wet deposition, which is the main removalmechanism from the atmosphere. Flaming conditions pro-duce more BC and less OA generally, which leads to ampli-fied absorption (Vakkari et al., 2014; Yokelson et al., 2009).Flaming conditions are associated with high MCE values(Reid et al., 2005a). Unfortunately, we were not able to cal-culate MCE values for the Siberian events at MBO due toextensive dilution and boundary layer mixing during trans-port (Yokelson et al., 2013a).

While the ω values for the Siberian events are signifi-cantly lower relative to the regional events, they are all high(> 0.95) compared to typical flaming conditions measured inthe laboratory or near-field measurements (S. Liu et al., 2014;Vakkari et al., 2014). S. Liu et al. (2014) found a robust re-lationship between ω and MCE in laboratory BB emissionswhere MCE was negatively correlated with ω. However, ob-servations have found that ω increases significantly hours af-ter emission in BB plumes (Reid et al., 2005a; Vakkari et al.,2014). A previous study at MBO found that well-aged BBplumes do not follow the S. Liu et al. (2014) parameteriza-tion (Briggs et al., 2016). All of the BB plumes observed byBriggs et al. (2016) had ω > 0.91 despite MCE values as highas 0.98, and no relationship was found between ω and MCE.The high ω values typical of aged BB plumes are most likelydue to SOA formation and increased scattering efficiency asthe particles age and increase in size through coagulation and

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15192 J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol

condensation. Given this we believe the ω’s seen in theseSiberian plumes are different and significantly higher thanthe ω’s directly after emission and are therefore cannot beequated to an MCE value.

We found AAE values for the Siberian events to be signif-icantly lower than regional BB events (Figs. 3 and 4). HighAAE values are indicative of the presence of brown carbon(BrC). Brown carbon is a fraction of OA that selectively ab-sorbs short wavelengths (Andreae and Gelencsér, 2006; Chenand Bond, 2010; Kirchstetter et al., 2004). There are twopossible explanations for the difference in AAE values. Thefirst is that the flaming conditions that produced the Siberianevents seen at MBO had higher BC and lower OA emis-sions, which inherently have lower AAE as total absorptionis dominated by BC and less BrC is initially produced. Lab-oratory and field studies have corroborated this and observedan inverse relationship between MCE and AAE (Holder etal., 2016; S. Liu et al., 2014; McMeeking et al., 2014). Theother explanation is that BrC is lost during transport throughphotobleaching, volatilization, and aerosol-phase reactions.Forrister et al. (2015) determined that BrC decreased withtransport with a half-life of 9 h and that AAE decreases from∼ 4.0 to ∼ 2.5 24 h after emission. All of the regional BBevents were influenced by multiple fires that had transporttimes varying from 3 to 35 h. With each event being influ-enced by at least one fire with a transport time ≤ 6 h, thisshort transport time is consistent with the higher AAE valueswe observed.

3.4 Mass scattering efficiency

MSE is important for calculating the radiative forcing ef-fects of aerosols in global climate and chemical transportmodels. Estimates of MSE are used to convert aerosol massmeasurements to aerosol optical properties (Briggs et al.,2016; Hand and Malm, 2007; Pitchford et al., 2007). MSEis dependent on particle composition, which determines theparticle’s refractive index and hygroscopicity, and aerosolsize distribution (Hand and Malm, 2007). We calculatedMSE as the slope of the RMA regression of σscat and PM1(1σscat/1PM1). R2 values were > 0.94 for all events. Wefound MSE values ranged from 2.50 to 4.76 m2 g−1, whichare consistent with previously measured values.

During 2013 at MBO, MSE values estimated usingAerosol Mass Spectrometer (AMS) organic matter dataand the σscat for four wildfire plumes ranged from 2.8 to4.8 m2 g−1 (mean: 3.7 m2 g−1) (Briggs et al., 2016). Levin etal. (2010) calculated MSE values for fresh BB smoke from avariety of fuels to range from 1.5 to 5.7 m2 g−1, with mostof the values falling between 2.0 and 4.5 m2 g−1. Reid etal. (2005a) reviewed MSE values from BB events and founda range between 3.2 and 4.2 m2 g−1 (mean: 3.8 m2 g−1) fortemperate and boreal fresh smoke and larger values for agedsmoke (3.5–4.6 m2 g−1; mean: 4.3 m2 g−1). MSE values up-wards of∼ 6 m2 g−1 have been observed for aged BB plumes

(Hand and Malm, 2007; McMeeking et al., 2005). Due to thelarge variation in MSE values for BB events, assigning anaverage MSE value to convert aerosol mass measurements toaerosol optical properties or vice versa introduces significantuncertainties.

We investigated the cause for the variation in the MSE val-ues that we observed. We found MSE’s for BB events to bepositively correlated with Dpm (R2

= 0.73) (Fig. 6a). If twoDpm values associated with bimodal size distributions are re-moved, the correlation increases substantially (R2

= 0.88). Apositive correlation between MSE and mean particle diame-ter has previously been observed in ambient data (Lowenthaland Kumar, 2004) and laboratory studies (McMeeking et al.,2005). Theoretically according to Mie theory, MSE will in-creases as the average particle diameter grows, through co-agulation and condensation, toward the measurement wave-length (550 nm) (Seinfeld and Pandis, 2006).

3.5 BB size distributions

Figure 7 shows the BB aerosol number size distributions forthe regional events (solid lines) and Siberian events (dashedlines) we observed at MBO. We found Dpm and σg of thenumber distributions to range from 138 to 229 nm and 1.53to 1.89, respectively. The size distributions observed at MBOare similar to Janhäll et al. (2010), who compiled aged BBsize distributions. They found the accumulation mode meandiameter to range from 175 to 300 nm with geometric stan-dard deviations of 1.3–1.7. No dependence was found inDpmin plumes of regional or Siberian origins. Similarly duringthe ARCTAS-B flight campaign, aged BB plumes of West-ern Canadian and Asian origins were found to have simi-lar size distributions (Canadian: Dpm = 224± 14 nm, σg =

1.31± 0.05; Asian: Dpm = 238± 11 nm, σg = 1.31± 0.03)(Kondo et al., 2011). The BORTAS-B flight campaign inEastern Canada observed aged BB plumes with median di-ameters of 180–240 nm (Sakamoto et al., 2015).

We observed clear bimodal distributions with an accumu-lation mode (100–500 nm) and Aitken mode (20–100 nm) forfive events (2, 3, 11, 14, and 15). The Aitken mode in thesesize distributions most likely represents a secondary sourcefrom within the BL. A prominent “tail” consisting of higherthan expected number concentrations of small-diameter par-ticles (30–90 nm) was observed for most of the unimodalevents at MBO. It would be expected that particles in thissize range would grow to larger particles through coagulationrelatively quickly. Sakamoto et al. (2015) observed a similarelevation in the number concentration of small particles dur-ing the BORTAS-B campaign. They attempted to account forthe existence of the tail with a Lagrangian box model of co-agulation and dilution but were unable to do so. Coagulationshould cause a significant decrease in Aitken mode particlesin a matter of hours, and nucleation and condensation growthrates would have to be unreasonably high to maintain thesesmall particles.

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J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol 15193

Figure 6. Scatter plots of (a) MSE, (b) σscat, (c) PM1, and (d) COvs. Dpm for the BB events at MBO in the summer of 2015.

Figure 7. Event-integrated aerosol number size distributions (cor-rected to STP) in dN/dlogDp (no. cm−1). The regional BB eventshave solid colored lines and the Siberian BB events have dashedblack lines.

We observed no clear distinction between the size distri-butions from regional and Siberian events. These results areconsistent with previous studies that have not observed a de-pendence from plume age, transport time, or source locationon the BB size distribution. Kondo et al. (2011) found lit-tle difference between theDpm of Siberian and Canadian BBplumes despite different chemical composition, optical prop-erties, and transport times. Similarly, Sakamoto et al. (2015)found no trend in size distribution with plume transport dis-tance. In a study performed in the Front Range of Col-orado, Carrico et al. (2016) found no significant differencebetween the size distribution of an hours-old and a days-oldfire plume.

As previously stated, we found MSEs for BB events to bepositively correlated with Dpm. This makes physical sensedue to increased light scattering efficiency of larger parti-cles closer to the wavelength of light (550 nm). In addition,

we found event-integrated Dpm to be correlated with event-integrated σscat (R2

= 0.65) and PM1 mass (R2= 0.72), and

moderately correlated with CO (R2= 0.41) (Fig. 6b, c, d).

Dpm was not found to be correlated with any normalizedER (1σscat/1CO,1PM1/1CO). CO, σscat, and PM1 can bethought of as surrogates for plume concentration. The corre-lation between these proxies of plume concentration andDpmindicates that in general, the more concentrated BB plumeshave larger size distributions.

In a related study, Sakamoto et al. (2016) selected subsetsof the MBO BB regional events presented here and testedthem against parameterizations of the aged size distribution.The parameterizations calculateDpm and σg from inputs thatcan be derived from emissions-inventory and meteorologicalparameters. The seven inputs are emission median dry di-ameter, emission distribution modal width, mass emissionsflux, fire area, mean boundary-layer wind speed, plume mix-ing depth, and time/distance since emission. We identified 11plumes from regional events that had consistent transport toknown regional fires. The simple fits captured over half of thevariability in observed Dpm and modal width, even thoughthe freshly emitted Dpm and modal widths were unknown.The results demonstrate that the parameterizations presentedin Sakamoto et al. (2016) Sect. 3.4 can be successfully usedto estimate aged BB size distributions in regional BB plumeswith transport times up to 35 h. Using these parameteriza-tions to estimate BB plume size distribution in global andregional aerosol models is a significant improvement to as-suming fixed values for size-distribution parameters.

The Sakamoto et al. (2016) parameterizations were partic-ularly sensitive to mass emissions flux and fire area, as wellas wind speed and transport time. If mass emissions flux isinterpreted as surrogate for plume concentration, this agreeswith our conclusion that increased plume concentration re-sults in a larger size distribution.

4 Conclusions

We characterized the physical and optical properties of 19aged biomass burning events observed at the Mt. BachelorObservatory in the summer of 2015. Regional (Northern Cal-ifornia and Southwestern Oregon) and Siberian events wereobserved. Our main conclusions were as follows:

– 1σscat/1CO (σscat at STP) enhancement ratio rangedfrom 0.48 to 1.29 Mm−1 ppbv−1, with the majority ofevents being between 0.8 and 1.25 Mm−1 ppbv−1.

– Siberian-influenced events had significantly higher1σabs/1CO and MAE and lower ω compared to re-gional events. We propose this is due to MBO samplingthe portion on Siberian smoke that has been lofted tohigher elevation through pyroconvection, thereby pref-erentially sampling emissions of strong flaming com-bustion conditions. In general flaming conditions pro-

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15194 J. R. Laing et al.: Physical and optical properties of aged biomass burning aerosol

duce more BC, which would explain the amplified ab-sorption in the Siberian events.

– AAE values were significantly lower for the Siberianevents than regional events, which indicates lack ofBrC produced by the Siberian fires or loss of BrCduring transport through photobleaching, volatilization,and aerosol-phase reactions.

– Mass scattering efficiencies ranged from 2.50 to4.76 m2 g−1. MSE was positively correlated with Dpm(R2= 0.73), which agrees with Mie theory.

– Aerosol number size distribution Dpm and σg rangedfrom 138 to 229 nm and 1.53 to 1.89, respectively. Fiveof the 19 events had bimodal distributions, the rest beingunimodal. The unimodal distributions had a prominent“tail” of small-diameter particles (30–90 nm). No dis-tinction could be made between regional and Siberiansize distributions.

5 Data availability

The SMPS data from Mt. Bachelor Observatory during2015 is permanently archived at the University of Washing-ton Research Works site: http://hdl.handle.net/1773/36293,doi:10.21419/B9159X (Jaffe, 2016a).

The Mt. Bachelor Observatory 2015 dataset are per-manently archived at the University of WashingtonResearch Works site: http://hdl.handle.net/1773/37330,doi:10.21419/B9WC70 (Jaffe, 2016b).

The Supplement related to this article is available onlineat doi:10.5194/acp-16-15185-2016-supplement.

Author contributions. James R. Laing performed the data analysisand prepared the manuscript with assistance from all co-authors.

Disclaimer. The views, opinions, and findings contained in this re-port are those of the author(s) and should not be construed as anofficial National Oceanic and Atmospheric Administration or USGovernment position, policy, or decision.

Acknowledgements. Funding for research at MBO was supportedby the National Science Foundation (grant number: 1447832).MBO is also supported by a grant from the NOAA Earth System Re-search Laboratory. The authors gratefully acknowledge the NOAAAir Resources Laboratory (ARL) for the provision of the HYSPLITtransport model used in this publication. The CALIPSO satelliteproducts were supplied from the NASA Langley Research Center.

Edited by: S. A. NizkorodovReviewed by: two anonymous referees

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