chemical speciation of pm 2.5 collected during prescribed fires of the...

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Chemical Speciation of PM2.5 Collected duringPrescribed Fires of the Coconino National Forest nearFlagstaff, ArizonaMarin S. Robinson a , Jesus Chavez a , Sergio Velazquez a & R.K.M. Jayanty ba Northern Arizona University , Flagstaff , Arizona , USAb RTI International , Research Triangle Park , North Carolina , USAPublished online: 22 Feb 2012.

To cite this article: Marin S. Robinson , Jesus Chavez , Sergio Velazquez & R.K.M. Jayanty (2004) Chemical Speciation ofPM2.5 Collected during Prescribed Fires of the Coconino National Forest near Flagstaff, Arizona, Journal of the Air & WasteManagement Association, 54:9, 1112-1123, DOI: 10.1080/10473289.2004.10470985

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Chemical Speciation of PM2.5 Collected during PrescribedFires of the Coconino National Forest near Flagstaff, Arizona

Marin S. Robinson, Jesus Chavez, and Sergio VelazquezNorthern Arizona University, Flagstaff, Arizona

R.K.M. JayantyRTI International, Research Triangle Park, North Carolina

ABSTRACTThe use of prescribed fire is expected to increase in aneffort to reduce the risk of catastrophic fire, particularly aturban/forest interfaces. Fire is a well-known source ofparticulate matter (PM) with particle sizes �2.5 �m(PM2.5), small diameter PM known to affect climate, vis-ibility, and human health. In this work, PM2.5 was col-lected during seven first-entry burns (flaming and smol-dering stages) and one maintenance burn of theCoconino National Forest. Samples were analyzed for or-ganic and elemental carbon, cations (sodium, potassium[K�], and ammonium [NH4

�]), anions (nitrate [NO3�]

and sulfate), and 48 elements (with atomic weights be-tween sodium and lead). The PM2.5 contained high or-ganic carbon levels (typically �90% by mass), commonlyobserved ions (K�, NH4

�, and NO3�) and elements (K�,

chlorine, sulfur, and silicon), as well as titanium andchromium. Flaming produced higher K� and NH4

� levelsthan smoldering, and the elemental signature was morecomplex (20 versus 7 elements). Average organic car-bon � 1.4 mass fractions (� standard deviation) werelower during flaming (92 � 14%) than during smoldering(124 � 24%). The maintenance (grassland) burn produced

lower particle concentrations, lower NH4� and NO3

� lev-els, and higher K and chlorine levels than did the first-entry fires.

INTRODUCTIONThe fire suppression policies of the past century haveleft national forests in an unhealthy state characterizedby dense undergrowth and heavy fuel loads, conditionsthat have increased the likelihood of catastrophic wild-fire.1,2 The frequency and severity of wildfire has in-creased markedly in recent years, costing billions ofdollars in fire suppression, destroying millions of acresof land, and disrupting numerous ecosystems and wild-life habitats. In 2002 alone, 88,458 wildland fires werereported, and 6,937,584 acres of land were burned inthe United States.3 To reduce this threat, federal, tribal,and state land managers have agreed to increase theiruse of prescribed fire, which, in combination with me-chanical thinning, will help restore wildland ecosys-tems to their pre-1900s condition.4,5 In addition toreducing the threat of catastrophic fire, prescribed firealso will provide ecological benefits to the forests byrecycling nutrients and stimulating understorygrowth.1,2,6,7 For these reasons, the use of prescribed fireis expected to increase in the next decade, particularlyat urban/forest interfaces where fuel breaks are neededfor fire containment.

Even if the benefits of prescribed fire are achievedand the risk of stand-replacing wildfire is reduced, theincreased use of prescribed fire will pose a new set ofconcerns. Foremost among these is an expected in-crease in fine particulate matter (PM) or PM2.5, airborneparticles with aerodynamic diameters of �2.5 �m.Combustion sources are a well-known source ofPM2.5.8,9 Collectively, wildfire, prescribed fire, and openbiomass burning account for more than 35% of partic-ulate emissions to the atmosphere.10 Fire-generatedparticles exist primarily in the accumulation mode(0.1–2 �m), with the largest fraction being smaller than

IMPLICATIONSForest restoration efforts will increase the use of prescribedfire through first-entry and maintenance burns. PM2.5 gen-erated during seven first-entry fires (flaming and smolder-ing) and one maintenance fire was analyzed. Samples werepredominantly organic (affecting particle hygroscopicity,size, and light-scattering properties). Flaming increasedparticle NO3

� (associated with haze aerosols) and volatil-ized 20 elements, including titanium, chromium, lead, andzinc. Smoldering increased particle NO3

� and volatilizedseven elements. The maintenance fire produced lower par-ticle concentrations, less NH4

� and NO3�, and more K�

than the first-entry burns. These data imply that mainte-nance fires may have less atmospheric impact than first-entry burns.

TECHNICAL PAPER ISSN 1047-3289 J. Air & Waste Manage. Assoc. 54:1112–1123

Copyright 2004 Air & Waste Management Association

1112 Journal of the Air & Waste Management Association Volume 54 September 2004

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1 �m.11 Such particles are small enough to reach thealveoli in the lungs and have been linked to pulmonarydisease, morbidity, and even death.12–14 Fine particu-late also can impact climate through energy absorptionand cloud nucleation processes15 and lead to haze andvisibility impairment through light scattering.16 Visi-bility impacts will be especially important in airshedssuch as the Grand Canyon, where particle carbon emis-sions to the atmosphere are expected to increase as aresult of prescribed fire.16

To better evaluate the impact of fire-generated PM2.5

on visibility and human health, its chemical compositionmust be better understood. To this end, researchers haveexamined the size and composition of particulate from avariety of fire-generated sources, including fireplace woodburning,11,17–20 wood cooking,21 foliar fuel combustion(including fresh and decaying leaf and litter samples),22

and grassland burning.23–28 Size-speciated particulate iscommonly collected in bulk on filters11,17–27 and analyzedusing methods such as ion chromatography, gas chroma-tography/mass-spectrometry, proton-induced X-ray emis-sion, and X-ray fluorescence spectroscopy (XRF). Alterna-tively, airborne particulate can be analyzed on a single-particle basis using an aerosol time-of-flight massspectrometer.28 This latter method provides size and com-positional information for individual particles in real timeand space. Through these efforts, a great deal has beenlearned about the composition of fire-generated PM2.5. Ingeneral, the largest fraction is organic (�70% by mass);although the organic mixture is complex (�300 species),organic speciation (using techniques such as gas chroma-tography/mass-spectrometry,17–26 aerosol time-of-flightmass spectrometer,29 and Fourier transform infrared spec-troscopy30) shows the greatest potential to identify mo-lecular markers in wood smoke. Sulfate (SO4

2�), nitrate(NO3

�), and ammonium (NH4�) are commonly observed

ionic species, while potassium (K), chlorine (Cl), andsulfur (S) are commonly observed inorganic ele-ments.11,17,18,22,23,27

To date, most fire-generated PM2.5 studies have beenconducted in laboratory settings.11,17,18,22,23 Fewer studieshave analyzed PM2.5 collected on-site during authenticfires (prescribed or natural).27 In this work, the chemicalcomposition of PM2.5 generated during prescribed fires ofthe Coconino National Forest near Flagstaff, AZ, the larg-est contiguous ponderosa pine forest in North America,was investigated. To our knowledge, this is the firstanalysis of the composition of PM2.5 collected duringprescribed fires of a Southwestern ponderosa pine for-est. Samples were collected on-site during flaming andsmoldering stages of seven first-entry (no fire history for7–12 yr) broadcast burns and one grassland burn. Abroadcast burn, unlike slash or pile burns, removes

accumulated layers of downed woody material, litter,and duff over a land area between 20 and 200 acres.Initial forest restoration efforts will be largely first-entryburns; subsequent maintenance fires are expected to bepredominantly grassland burns. The chemical signatureof PM2.5 collected under these various fire conditionsare compared with one other and with literature values.These data can be used to better assess the potentialeffects prescribed fire will have on human health andthe environment.

EXPERIMENTAL METHODSPrescribed Burn Sites

All prescribed burns were conducted by the Peaks RangerDistrict of the Coconino National Forest Service duringthe fall prescribed fire season (October and November) in2001 and 2002. The prescribed burns took place in theCoconino National Forest, a predominantly ponderosapine (Pinus ponderosa) forest with an average elevation of2130 m. Eight separately ignited fires were studied. Theseeight fires took place in five different areas (I–V), allwithin a 25-km radius of Flagstaff, AZ. Emissions weremeasured during both flaming and smoldering events.Flaming emissions were measured 0–4 hr after ignition;smoldering emissions were measured 1–2 days after igni-tion. Emissions from the burning of two areas were sam-pled in October 2001: Crowley (I) and A1 Mt (II). TheCrowley area (I) involved two prescribed fires (A and B)and three measurements: a flaming event (IA, for area Iand fire A) and two smoldering events (IA and IB). TheA1 Mt area (II) involved three prescribed fires (A-C) andfive measurements: a flaming event at one fire (IIA), twosmoldering events at a second fire (IIB), and two smol-dering events at a third fire (IIC). Emissions from theburning of three areas were sampled in October andNovember 2002: Woody Mt (III), Bellemont (IV), andBonita Park (V). All three were flaming events involvingseparate ignitions.

Land areas burned varied between 25 and 100 acres.The Bonita Park fire (V) was a grassland fire designed topreserve the meadow and stop encroachment of pinetrees. Grassland fires consume largely 1- to 10-hr fuels,corresponding to 0–0.25 and 0.25–1-in.-diameter wood,respectively. This area underwent prescribed fire 6 yr ear-lier; post-fire thinning of this site was planned but neverconducted. The remaining fires were first-entry burns.First-entry burns consume larger diameter wood, includ-ing 1000-hr fuels (�3-in. diameter). Mechanical thinning(to reduce tree density and to remove tree ladders,downed branches, and logs) typically preceded the use offire. The intensity of the prescribed burns was controlledto reduce only the forest understory (tree stumps, downed

Robinson, Chavez, Velazquez, and Jayanty

Volume 54 September 2004 Journal of the Air & Waste Management Association 1113

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woody materials, and duff and litter layers) without burn-ing tree stands or crowns.

To better characterize the fuel composition in thefirst-entry burn areas, pre-fire fuel inventories of downedwoody material, litter, and duff were conducted accordingto the methods of Brown et al.31 The top litter layers(average depth 1–2 in.) consisted of loose brown pineneedles, cones, and downed woody material (twigs,branches, and logs �0.25 to �6-in. diameter). The under-lying duff layers (average depth 0.6–1.7-in.) consistedlargely of decomposing pine needles and woody materialand loose soil. Pre-fire fuel loadings were between 2.8 and3.4 tons/acre for the A1 Mt, Crowley, and Woody Mtregions and 9 t/acre for the Bellemont region. A post-firefuel inventory was conducted at the Bellemont site. Thelitter and duff layers were reduced by 90 and 27%, respec-tively. Woody materials were reduced by 23%, with thelargest reduction in the small diameter size class (�0.25in.).

PM2.5 MonitorPM2.5 samples were collected using a U.S. Environmen-tal Protection Agency (EPA)-approved chemical specia-tion monitor (Met One SuperSASS). Because no electri-cal source was available at the fire sites, the monitor wasbattery-operated. The monitor has eight independentchannels, four of which can be operated simulta-neously. Three channels were used in this work; eachchannel had its own sampling module with a dedicatedautomatic flow controller and designated filter media(47 mm). The three operative channels supported aTeflon filter, a prebaked quartz fiber filter (900 °C, 12hr), and a nylon filter (used with a MgO denuder),respectively. Each module was equipped with a sharp-cut cyclone to remove particles with aerodynamic di-ameters �2.5 �m. The sampling height of the monitoris �1.8 m. Monitoring times for fire events and back-ground measurements were between 1.3 and 2 hr. Flowrates were between 6.37 and 6.75 L/min with two ex-ceptions (4.61 and 4.86 L/min). The lower flow ratescan increase the cut point size (2.5 �m) and, thereby,result in higher calculated mass loadings (�g/m3); how-ever, because the fire-generated particles fall largely inthe submicron size range (supported by scanning elec-tron micrographs, not shown), this effect is likely to besmall. Ambient temperature during PM2.5 collectionvaried between 12 and 22 °C.

PM2.5 Collection ProceduresOn fire ignition days, the PM2.5 speciation monitor wasplaced (as required by Forest Service regulations) across afirebreak (typically a dirt road), �10–30 m from the flam-ing area. Based on the placement of the monitor relative

to the flaming fire, particle age was estimated to be �10min. On days after ignition, the monitor was placedwithin the burn area, if possible near a smoldering stumpor log. During each fire event, the monitor collected PM2.5

simultaneously on the three filter media. A fourth filter(rotated between Teflon, quartz, or nylon with denuder)served as a field blank. Unexposed filters were received inPetri dishes (Analyslide, VWR) from RTI International(RTI) in September 2001 and September 2002 and storedat ambient temperature before use. The day before sam-pling, filters and field blanks were loaded into their sam-pling modules in an air-filtered hood. On the day ofsampling, modules were transported to the field in acooler (�10 °C). Post-sampling, the modules were re-turned to the hood in the cooler, removed from theirmodules, and stored in their original Petri dishes.Teflon and nylon filters were stored at �4 °C and quartzfiber filters were stored at �20 °C. Filters were returnedto RTI (overnight) in a cooler (�10 °C) within 7 weeksof initial receipt. One trip blank of each filter mediaaccompanied filters during transport to and from RTI.Once received at RTI, exposed Teflon and nylon filterswere stored in a refrigerator (4 °C), and quartz filterswere kept in a freezer (�20 °C) until analysis.

In addition to these fire events, the chemical specia-tion monitor was used to collect three background mea-surements at areas near the A1 Mt, Woody Mt, andBellemont fire sites after the prescribed fires were extin-guished. Background measurements could not be taken atthe authentic site before the fire, because the site was onlyone of many potential sites, until the day of ignition.

PM2.5 Physical and Chemical CharacterizationThe PM2.5 mass and composition were analyzed by RTI.PM2.5 mass emissions were determined gravimetricallyfrom the mass of particulate collected on the Teflon filtercollected during each sampling event, which had beenpreweighed and conditioned in a control chamber (24 hr,20–25 °C, and 30–40% relative humidity [RH]). Errors areestimated to be �0.003 mg, based on measurements ofweighing precision and the volumes of air sampled in thisstudy. During fire events, PM2.5 Teflon filter massesranged between 0.076 and 3.759 mg. This wide rangereflects both the position of the monitor relative to thesmoke plume (some days meteorological conditions di-rected the plume toward the monitor and other days itdid not) and authentic differences in smoke densitiesamong the varied fire events. PM2.5 concentrations arereported in units of mass/volume air sampled (�g/m3),where volume was measured independently for eachfilter. The detection limit for PM2.5 (3) is 7 �g/m3, whichassumes a nominal sample volume of 0.6 m3.



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Teflon filter masses also were used to estimate theorganic carbon (OC) mass fraction (see next section),calculated by dividing the OC quartz filter mass by theco-collected PM2.5 Teflon filter mass (�g OC/�g PM2.5).This approach assumes that the quartz and Teflon filters(located �30 cm apart) sampled the same particleconcentration. (It also assumes that both filters ad-sorbed the same quantity of organic vapors, furtherdiscussed below). This assumption is reasonable for awell-mixed air sample; however, at the fire site, thesmoke was not well mixed. Error bars resulting fromdifferent particle concentrations are estimated to be atleast �20% based on a measurement taken during theWoody Mt ignition event (III), where a second Teflonfilter was used in lieu of the nylon filter; the co-collected Teflon filter masses varied by 17%.

OC and elemental carbon (EC) masses were measuredusing National Institute for Occupational Safety andHealth Method 5040, which implements thermal-opticaltransmittance (Sunset Laboratories). For fire measure-ments, the organic mass was multiplied by 1.4 (OC � 1.4)to approximate the average molecular weight per carbonof compounds comprising the organic fraction in nonur-ban aerosols.32 The multiplier may be as high as 2.1 forwood smoke, particularly if the aerosol has had time toage (oxidize) in the atmosphere.32 However, because par-ticulate was collected near the source (particle age �10min), it is likely that the multiplier should be less than2.1. OC/EC concentrations (without field or trip blankcorrection) are reported in units of mass/volume air (�g/m3) and mass fraction total carbon (weight/weight totalcarbon). Detection limits for both OC and EC were 1.75�g/m3. The OC mass fraction of the fire samples rangedbetween 69 and 166%. The large errors in these measure-ments were caused by using Teflon filter masses to esti-mate quartz filter masses. Each filter samples a differentsmoke density (see previous section); moreover, quartzfilters can absorb more volatile organic compounds (suchas benzene, naphthalene, and low-molecular-weight or-ganic acids or aldehydes) than Teflon filters, resulting inOC values �100%.

Three cations (sodium [Na�], K�, and NH4�) and two

anions (NO3� and SO4

2�) from nylon filters were ana-lyzed using ion chromatography. Ion concentrations(without field or trip blank correction) are expressed inunits of mass/volume air (�g/m3) and mass fraction totalions (weight/weight total ions). All reported values ex-ceeded detection limits (0.37, 0.17, 0.2, 0.11, and 0.14�g/m3 for Na�, K�, NH4

�, NO3�, and SO4

2�, respec-tively).

Teflon filters were analyzed for 48 elements withatomic numbers between 11 (Na) and 82 (lead [Pb]) usingQuanX XRF (Thermo Noran). Before analysis, sample

filters were covered with a 4-�m polypropylene film (Pro-lene) to prevent loss of particle matter. UniQuant V.4software (Omega Data Systems) was used in the determi-nation of blank-corrected concentrations of individualelements. Elements with concentrations �3 times theinstrumental uncertainty were considered to be belowquantifiable limits and are reported as nonquantifiable.The uncertainties shown for the elements determined byXRF are calculated by the analysis software based oncounting statistics from the spectra. Multiplying the sam-ple uncertainty by 3 gives an approximation of the detec-tion limit. For clarity, only those elements (21 of 48) withquantifiable concentrations �0.1 �g/m3 during at leastone authentic fire event (flaming or smoldering) are con-sidered. Elemental concentrations (without blank correc-tion) are reported in units of mass/volume air (�g/m3)and mass fraction total elements (weight/weight total el-ements) summed over 21 elements.

RESULTS AND DISCUSSIONPM2.5 Concentrations

PM2.5 background concentrations ranged between 19 and69 �g/m3 (Table 1). These values are higher than concen-trations reported in the literature, including the annualaverages reported in the EPA Aerometric InformationRetrieval System database for the Southwest (10–15�g/m3),33 the fine-particle concentrations measured inthe Grand Canyon through the IMPROVE monitoringnetwork (3.88 �g/m3),16 and background measurementsmade in rural-remote areas of Alberta, Canada (�10�g/m3).34 These differences can be attributed to a varietyof factors, such as the short sampling times (2 hr), theseason and time of day, meteorological factors, the posi-tion of the monitor on the forest floor (rather than on apaved surface), and residual effects of the nearby extin-guished prescribed fire.

The highest concentrations of PM2.5 were measuredduring the flaming stage of the prescribed fires (Table 2).During first-entry burns, ambient concentrations variedbetween 2541 and 6459 �g/m3, a range that reflects bothactual variations in smoke density among different flam-ing events, as well as the position of the monitor rela-tive to the plume (see previous section). Particle con-centrations were much higher during first-entry burns(�2500 �g/m3) than during the Bonita Park grasslandfire (523 �g/m3); it is believed that this reflects actualdifferences in particle concentrations and not merelythe position of the monitor. The grassland fire con-sumed largely 1-hr fuel; hence, it follows that thesmoke had a lower particle concentration and lastedfor a shorter period of time. These data suggest thatmaintenance fires will have substantially lower emis-sion rates of PM2.5.



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Particle concentrations were lower (155–904 �g/m3)during smoldering (Table 3) than during flaming (seeTable 2). Smoke intensity was visibly less after flamingsubsided. The lower density smoldering phase beganwithin 4 hr after ignition and continued for several days.Combustion studies of foliar fuels in a dilution chamber22

produced similar results; particle concentrations werehighest during flaming combustion and lower duringsmoldering. The observed decrease in smoke density dur-ing smoldering results from a slower rate of wood con-sumption; the particulate mass generated per mass woodconsumed is typically higher during smoldering than dur-ing flaming.23

OC/EC AnalysisThe results of OC/EC analysis are reported in Table 1 forbackground conditions, in Table 2 for flaming, and inTable 3 for smoldering. No carbonate species were de-tected; hence, the total carbon equaled EC � OC. By farthe largest carbon fraction was OC (�94% total carbon).Under background conditions (see Table 1), the EC valuesfell below detection limits (1.75 �g/m3), because of thesmall sample mass. The OC mass fraction exceeded 100%wt/wt PM2.5 in two of three background measurements.According to the IMPROVE database, current OC levelscomprise �40% of the fine particulate mass in the Colo-rado Plateau region,16 considerably lower than our values.These differences are attributed to uncertainties in the OCmultiplier (OC � 1.4) and to uncertainties in the data.Particle concentrations were near the detection limit (7�g/m3) in the background measurements. Short samplingtimes, forest location, meteorological factors, and residualeffects of the prescribed fire also may have contributed tothese differences.

OC mass fractions were also high during flaming andsmoldering (see Tables 2 and 3). Literature values forwood smoke typically report OC mass fractions�75%.17–26 Values often exceeded 100%. Interestingly,the estimated OC mass fraction (wt/wt PM2.5) was higherduring smoldering than during flaming. During flaming(including the grassland fire), the average OC mass frac-tion (� standard deviation [SD]) was 92 � 14%; duringsmoldering, the average was 124 � 24%. The high OClevels may reflect the close proximity to the flames; fineparticulate from freshly combusted branches, twigs, litter,and duff is likely to be mostly carbon. The carbon fractionwill decrease over time through oxidative transformationsand collisions with mineral-bearing aerosols and dust.This reasoning also may explain why smoldering valueswere higher than flaming values. The monitor was placedwithin the fire area during smoldering, sampling evenyounger particles. This close to the smoke source, it is alsolikely that higher concentrations of volatile and semi-volatile organic vapors were present. The quartz filters arelikely to absorb these vapors more efficiently than are theTeflon filters, resulting in higher OC values. In the future,the use of backup quartz filters could be used to test thishypothesis.

Table 1. Composition of PM2.5 collected for 2 hr under background conditions.

A1 Mt Woody Mt Bellemont

Area II III IV

Sampling date 10/31/01 10/21/02 11/04/02

Volume air (m3) 0.772 0.807 0.809

PM2.5 mass (mg) 0.031 0.056 0.015

Conc (�g/m3) 40 69 19

�g/m3

OC � 1.4 26.6 75.6 21

EC NQa NQ NQ

�g/m3 (wt/wt total ions)Ions

Na� 2.136 (0.549) 2.166 (0.433) 1.594 (0.608)

K� —b — —

NH4� — 0.213 (0.043) —

NO3� 0.91 (0.234) 1.034 (0.207) 0.72 (0.274)

SO42� 0.842 (0.217) 1.583 (0.317) 0.311 (0.118)

�g/m3 (� uncertainty)Elements

Na NQ � 0.146 — —

Al — — —

Si 0.141 � 0.031 1.209 � 0.062 0.558 � 0.055

P NQ � 0.02 — —

S NQ � 0.038 0.950 � 0.031 0.621 � 0.029

Cl — — —

K — NQ � 0.04 —

Ca NQ � 0.02 NQ � 0.029 NQ � 0.029

Ti — NQ � 0.019 NQ � 0.019

Cr — NQ � 0.007 NQ � 0.008

Fe 0.079 � 0.013 0.167 � 0.01 0.103 � 0.009

Cu — 0.078 � 0.009 0.081 � 0.01

Zn — NQ � 0.01 —

Br — — —

In — NQ � 0.051 —

Sn — — NQ � 0.081

Sb NQ � 0.092 — —

Cs NQ � 0.195 — NQ � 0.041

Ba NQ � 0.258 0.186 � 0.039 0.228 � 0.04

Eu — — 0.049 � 0.015

Pb — — NQ � 0.011

aNQ detected but below quantifiable limits. Quantifiable limits were 1.75 �g/m3 for EC and �3

times the instrumental uncertainty for each element; bDash (—) not detected.



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Despite the unrealistically high values and largeuncertainties, these data strongly suggest that the or-ganic fraction of particulate can be expected to increaseas a result of prescribed fire. The potential impactsof the projected increase are not well understood.

Fire-generated organic aerosols, if inhaled, can affecthealth, because of the well-documented presence ofcarcinogenic and mutagenic polyaromatic hydrocar-bons in combustion aerosols.17–26 Organic aerosols alsocan influence visibility and climate.16 These effects are

Table 2. Composition of PM2.5 during the flaming stage of prescribed fires.

AreaCrowley

IAA1 Mt

IIA

Woody MountainBellemont

IVBonita Parka

VIII III

Ignition date 10/23/01 10/24/01 10/15/02 10/15/02 10/16/02 11/06/02

Time (hr:min) 1:48 1:20 2 2 2 1:35

Vol air (m3) 0.691 0.518 0.582 0.552 0.802 0.631

PM mass (mg) 2.754 1.316 3.759 3.125 2.654 0.33

Conc (�g/m3) 3986 2541 6459 5661 3309 523

�g/m3 (wt/wt total carbon)

OC � 1.4 3893 (0.97) 2415 (0.97) 4453 (0.95) 3473 (0.98) 496 (0.95)

EC 114 (0.03) 69 (0.03) 249 (0.05) 62 (0.02) 24 (0.05)


Na� 1.015 (0.042) 1.387 (0.12) 2.133 (0.099) 1.787 (0.186) 2.249 (0.097)

K� 4.427 (0.185) 1.722 (0.149) 2.668 (0.123) —b 13.353 (0.578)

NH4� 3.192 (0.133) 0.902 (0.078) 6.475 (0.299) 0.980 (0.102) —

NO3� 10.858 (0.453) 4.862 (0.42) 5.601 (0.259) 3.639 (0.378) 2.465 (0.107)

SO42� 4.459 (0.186) 2.706 (0.234) 4.744 (0.219) 3.228 (0.335) 5.042 (0.218)


Na 3.068 � 0.634 NQ � 0.423 — 1.535 � 0.292 0.967 � 0.2 —

Al NQ � 0.07c NQ � 0.085 — — — —

Si 0.191 � 0.044 0.308 � 0.057 3.896 � 0.116 3.846 � 0.122 1.404 � 0.073 0.771 � 0.085

P NQ � 0.031 NQ � 0.035 3.075 � 0.113 2.999 � 0.115 1.605 � 0.076 —

S 3.291 � 0.392 1.936 � 0.233 4.113 � 0.071 3.923 � 0.075 2.696 � 0.049 2.721 � 0.061

Cl 8.569 � 0.999 2.732 � 0.321 6.07 � 0.088 5.001 � 0.09 1.501 � 0.051 8.053 � 0.088

K 4.721 � 0.545 2.170 � 0.249 3.669 � 0.157 3.401 � 0.16 1.474 � 0.092 14.67 � 0.279

Ca 0.33 � 0.052 0.198 � 0.042 0.729 � 0.056 1.007 � 0.066 1.703 � 0.067 2.56 � 0.068

Ti NQ � 0.016 0.079 � 0.022 NQ � 0.028 0.156 � 0.033 0.148 � 0.023 NQ � 0.023

Cr — NQ � 0.013 — NQ � 0.013 0.057 � 0.009 —

Fe 0.157 � 0.016 0.196 � 0.022 0.249 � 0.015 0.663 � 0.023 0.402 � 0.016 0.137 � 0.01

Cu NQ � 0.018 — 0.114 � 0.015 0.137 � 0.017 0.116 � 0.012 0.12 � 0.013

Zn 0.195 � 0.016 0.072 � 0.015 0.252 � 0.018 0.26 � 0.019 0.081 � 0.013 0.099 � 0.014

Br 0.209 � 0.015 0.281 � 0.02 0.347 � 0.015 0.317 � 0.015 0.119 � 0.009 0.157 � 0.01

In — — — 0.352 � 0.079 — —

Sn NQ � 0.087 NQ � 0.116 NQ � 0.113 NQ � 0.122 0.561 � 0.085 NQ � 0.095

Sb — — NQ � 0.157 NQ � 0.168 — 0.537 � 0.139

Cs — — NQ � 0.06 0.196 � 0.065 NQ � 0.045 0.295 � 0.148

Ba — NQ � 0.36 0.269 � 0.059 NQ � 0.067 — 0.289 � 0.047

Eu NQ � 0.044 NQ � 0.057 — NQ � 0.024 0.115 � 0.018 —

Pb — — 0.13 � 0.02 0.126 � 0.022 0.061 � 0.014 NQ � 0.014

aBonita Park was a grassland fire. All others were first-entry burns; bDash (—) not detected; cNQ detected but below quantifiable limits. Quantifiable limits were �3 times the

instrumental uncertainty for each element.



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related, in part, to particle hygroscopicity. Surface or-ganic layers can be hydrophilic (small chain organicacids) or hydrophobic (long-chain fatty acids or al-kenes), compositional differences that can affect the

particle’s water solubility and ability to take up water.35

These factors, in turn, can affect particle size, light-scattering properties, and the ability of the particle toserve as a cloud condensation nuclei.16 Further studies

Table 3. Composition of PM2.5 during the smoldering stage (4 –51-hr post-ignition) of prescribed fires.

Crowley Prescribed Fires A1 Mountain Prescribed Fires

Area IB IC IIB IIB IIC IIC

Sampling date 10/18/01 10/25/01 10/26/01 10/27/01 10/29/01 10/30/01

Ignition date 10/17/01 10/23/01 10/26/01 10/26/01 10/29/01 10/29/01

Hr since ignition 24 51 4 25 6 28

Time (hr:min) 2:24 1:30 2:17 1:31 1:15 1:50

Vol air (m3) 0.918 0.584 0.901 0.592 0.49 0.721

PM mass (mg) 0.567 0.11 0.468 0.394 0.076 0.652

Conc (�g/m3) 618 188 519 666 155 904

�g/m3 (wt/wt total carbon)

OC � 1.4 617 (0.94) 261 (0.96) 587 (0.96) 787 (0.98) 257 (0.98) 993 (0.96)

EC 38 (0.06) 12 (0.04) 22 (0.04) 17 (0.02) 6 (0.02) 37 (0.04)


Na� 1.234 (0.186) 2.442 (0.537) 1.86 (0.218) 1.483 (0.223) 5.455 (0.715) 1.63 (0.379)

K� —a — — — — —

NH4� 0.289 (0.044) — 0.865 (0.101) 0.332 (0.05) — 0.12 (0.028)

NO3� 4.125 (0.62) 1.688 (0.372) 2.943 (0.344) 2.092 (0.315) 1.056 (0.138) 1.513 (0.352)

SO42� 0.995 (0.15) 0.411 (0.091) 2.885 (0.337) 2.743 (0.412) 1.123 (0.147) 1.037 (0.241)


Na NQ � 0.213b NQ � 0.323 NQ � 0.232 NQ � 0.323 NQ � 0.235 NQ � 0.287

Al NQ � 0.047 NQ � 0.064 NQ � 0.051 — — 0.179 � 0.06

Si 0.300 � 0.043 0.3 � 0.05 0.549 � 0.069 0.344 � 0.055 0.224 � 0.051 0.549 � 0.072

P — — — — — —

S 0.508 � 0.068 0.261 � 0.056 1.062 � 0.127 0.764 � 0.101 0.274 � 0.067 0.400 � 0.063

Cl 0.337 � 0.054 — NQ � 0.041 — — 0.271 � 0.061

K 0.505 � 0.059 — 0.342 � 0.043 0.105 � 0.025 — —

Ca 0.145 � 0.025 0.213 � 0.037 0.256 � 0.035 0.267 � 0.042 0.115 � 0.035 0.785 � 0.031

Ti 0.043 � 0.012 0.114 � 0.021 0.064 � 0.014 NQ � 0.017 — NQ � 0.017

Cr NQ � 0.007 NQ � 0.012 — NQ � 0.011 NQ � 0.016 NQ � 0.011

Fe 0.163 � 0.015 0.149 � 0.017 0.345 � 0.023 0.120 � 0.017 0.124 � 0.021 0.328 � 0.024

Cu — NQ � 0.021 — — — —

Zn — NQ � 0.014 NQ � 0.009 NQ � 0.013 — —

Br NQ � 0.006 — NQ � 0.006 — NQ � 0.011 NQ � 0.008

In NQ � 0.057 — NQ � 0.06 — — NQ � 0.074

Sn NQ � 0.066 NQ � 0.104 NQ � 0.069 NQ � 0.101 NQ � 0.131 —

Sb NQ � 0.076 — NQ � 0.076 — — —

Cs NQ � 0.159 NQ � 0.257 — NQ � 0.241 NQ � 0.325 NQ � 0.219

Ba NQ � 0.203 NQ � 0.335 NQ � 0.216 NQ � 0.313 NQ � 0.424 NQ � 0.282

Eu NQ � 0.033 — — NQ � 0.052 — —

Pb — — NQ � 0.021 — — NQ � 0.027

aDash (—) not detected; bNQ detected but below quantifiable limits. Quantifiable limits were �3 times the instrumental uncertainty for each element.



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are needed to evaluate the impact this increased carbonloading will have on health, haze, and visibility issuesin the Southwest.

Ion AnalysisIonic concentrations and mass fractions (wt/wt total ions)are reported during background, flaming, and smolderingin Tables 1–3, respectively. In Figure 1, the average massfraction (� SD) for each ion during these three events isplotted. Because the Bonita Park grassland fire gave adistinctly different ionic signature, it is not included inFigure 1 and is discussed separately. Na� was by far themajor cation detected in the background; no K� and verylittle NH4

� were observed. NH4� (and ammonia, NH3)

concentrations are typically higher near transportationcenters and agricultural operations,36 sources not ex-pected to be important in a remote national forest. NO3

�

and SO42� were detected at low levels in the background.

NO3� and SO4

2� are formed by atmospheric oxidation ofanthropogenic oxides of nitrogen (NOx; NO and nitrogendioxide) to nitric acid and sulfur dioxide (SO2) to sulfuricacid. In NH3-rich environments, these acids are com-monly converted to particle form as neutralized ammo-nium nitrate (NH4NO3) and ammonium sulfate[(NH4)2SO4].37,38 Alternatively, in an NH3-poor regimesuch as this one, nitric acid can be partitioned to thecondensed phase by reaction with Na� or dust.38 Thecondensed phase is favored at cold temperatures and highRH;37,38 hence, the low RH in the Southwest may explainthe low particle NO3

� levels.During flaming, particle concentrations of K�, NH4

�,and NO3

� increased over background levels; the concen-trations of Na� and SO4

2� remained essentially un-changed (see Table 2 and Figure 1). K� is a well-known

tracer for wood smoke. NH4� levels also have been shown

to increase during woodburning17,18 and foliar fuel com-bustion.22 The higher NH4

� levels led to higher particleNO3

� concentrations (presumably condensed NH4NO3)during flaming. Condensed NO3

� was also favored by thehigher particle concentrations and increased local humid-ity (vaporized water) during flaming.37,38 Somewhat sur-prisingly, particle SO4

2� did not increase during flaming(see Figure 1); SO4

2� is a common component of PM2.5 inthe Southwest.33 Concentrations of elemental S did in-crease (see next section), but particle age was too young totransform reduced S to its more oxidized forms (SO2 andSO4

2�). This further supports the formation of condensedNH4NO3, because condensed (NH4)2SO4 forms preferen-tially when SO4

2� is present.During smoldering, NH4

� returned to near-backgroundlevels and K� dropped below detection limits. ParticleNO3

� levels remained slightly elevated over background;this is attributed to the increased RH and higher particleconcentrations (favoring condensation) during smoldering.

A strikingly different ionic picture was observed withthe Bonita grassland burn. The signature was dominatedby K� (�3 times the concentration of the first-entryburns) with no detectable NH4

� and correspondinglylower levels of NO3

�. These differences are important forseveral reasons. In some areas, K� is a limiting nutrient;volatilization and transport by fire may be an importantway to distribute K� to these areas. The data suggest thatmaintenance (grassland) burns will be a richer source ofK� than first-entry burns. Moreover, the absence of NH4

�

and the correspondingly lower levels of NO3� may reduce

the light-scattering properties of these particles. NO3�

and SO42� are principle components of haze aerosols in

the Southwest.

Elemental AnalysisThe concentrations of 21 elements are reported underbackground conditions and during ignition/combustionand smoldering in Tables 1–3, respectively. Six elementswere quantifiable in background measurements (silicon[Si], S, iron [Fe], copper, barium, and europium); summedtogether, three of these (Si, S, and Fe) accounted for atleast 78% of the quantifiable elemental mass. S mostlikely arises from anthropogenic SO2, as described. Siand Fe are representative of soil-dust elements whichare typically complexed with oxygen (O2), such as SiO2,FeO, and Fe2O3. Other soil-dust elements, such as alu-minum and calcium (Ca), were not observed at quanti-fiable levels.

The elemental composition was the most complexduring flaming. Of the 21 elements reported, all butone (aluminum) was detected (though not always at

Figure 1. The average ionic mass fraction (wt/wt total ions) and SD forPM2.5 collected under background (left, three samples), flaming (center,four samples), and smoldering (right, six samples). Results from thegrassland burn (Bonita Park) were not included.



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quantifiable levels). Fractional abundances of these el-ements during the six flaming events are plotted inFigure 2. Reasonable agreement was observed across thesix measurements (including very good agreement be-tween the two co-collected Teflon filter measurementsat the Woody Mt site). Of the 21 elements monitored,10 (Si, S, Cl, K, Ca, Ti, Fe, zinc [Zn], bromine [Br], andtin) were detected in 100% of the flaming events; nineof these (all but tin) exceeded quantifiable levels in �3measurements. Cl was the most abundant element inall but one first-entry burn (Bellemont), which wasdominated by S. The Bonita Park grassland fire pro-duced a much simpler elemental profile, comprised ofonly four major elements. Consistent with the K� pro-file described previously, K was the predominate ele-ment in the grassland burn (48% wt/wt total elements),followed by Cl (26%), S (9%), and Ca (8%).

Noticeably absent during flaming were elementsand heavy metals commonly associated with industrialprocesses, such as nickel, arsenic, cadmium, manga-nese, mercury, and selenium.39 Although these ele-ments were occasionally detected, their concentrationsnever exceeded 3 times the uncertainty. However, fourheavy metals were observed: chromium (Cr), Fe, Zn,and Pb. Inhalation of particles containing these metalshas been linked to short-term (such as skin rashes orfever) and long-term exposure effects (such as cancer,red lung disease, or paralysis).40 Threshold exposurelevels vary between 0.15 ppm for Pb and 10 ppm for Fe(where 1 ppm is 1 �g metal per 106 �g particulate).40

The 10-ppm level was exceeded by all four metals inone or more flaming event (see Table 2), with Fe and Zncontributing at the highest levels. Only Fe and Zn wereobserved at quantifiable levels at the Bonita Park

grassland burn (Pb was detected, Cr was not), suggest-ing that long-term maintenance fires will volatilizefewer heavy metals than first-entry burns.

The elemental composition was significantly lesscomplex during smoldering (see Table 3 and Figure 3).Only 7 (rather than 20) elements were detected, presum-ably caused by a drop in fire intensity, fire temperature,and the rate of fuel consumption. The compositionalchanges became apparent 4–6 hr after flaming subsidedand lasted for several days. In general, the elements thatdominated during smoldering were a combination of themajor elements detected during flaming (Cl, S, and K) andbackground measurements (Si, S, and Fe). Ca and Ti alsowere observed during smoldering.

The major changes in elemental composition aresummarized in Figure 4. The average fractional abun-dance of each element (� SD) during background, flam-ing (excluding the grassland fire), and smoldering isreported. In general, the major contributors duringeach event were reasonably reproducible. These aresummarized as follows: Si and S (background); S, Cl,and K (ignition/combustion); and Si, S, Ca, and Fe(smoldering).

The major elements detected in this work also havebeen observed in other wood burning studies of PM2.5

(see Table 4).11,17,18,22,23,27 S, Cl, K, Br, and Pb have beendetected more than 95% of the time (when analyzed)across a wide variety of fuel types, including litter, hard-wood, softwood, and savanna biomass. Si, Ca, Fe, and Znalso have been detected, but with slightly less frequency.Alternatively, Ti has been detected only 6 times; mostoften, it has been associated with pine wood11,22 or pre-scribed fires of savanna biomass.27 In this study, Ti was

Figure 2. Elemental composition of PM2.5 during six flaming stages offive prescribed fires. Values are reported as mass fractions (wt/wt totalelements).

Figure 3. Elemental composition of PM2.5 collected during six smol-dering stages of two prescribed fires in the Crowley area (IA and IB) andtwo prescribed fires in the A1 Mt area (IIB and IIC). The elapsed time sinceignition is shown in parentheses. Values are reported as mass fractions(wt/wt total elements).



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detected in all but one prescribed fire; together, theseresults suggest that Ti may be a useful marker for pinewood or prescribed fire. Finally, to our knowledge, we arethe first to detect Cr in a wood-burning event (see Ta-ble 4).

CONCLUSIONSThe use of prescribed fire as a forest management tech-nique is expected to increase in the next decade. Fire canvolatilize soil-bound minerals and oxidize atmosphericgases to create a complex mixture of gases and particles.These aerosols, particularly those in the micron and sub-micron size range, can be transported long distances andimpact climate; cloud nucleation; air, land, and waterquality; and human health. For these reasons, the chem-ical composition of fire-generated aerosols must be betterunderstood.

To this end, the composition of PM2.5 generated ineight prescribed fires of the Coconino National Forest wasinvestigated. In accord with other wood-burning studies,organic compounds made up the largest fraction of thePM2.5 mass. The carbon fractions were particularly high inthis work, attributed in part to the young age of the

Figure 4. A comparison of how the average (� SD) elemental massfraction (wt/wt total elements) in PM2.5 changed during backgroundconditions (three samples), flaming (five samples), and smoldering (sixsamples). Results from the grassland burn (Bonita Park) were not in-cluded.

Table 4. Summary of elements seen in fire-generated fine particulate. A check (�) indicates the element was measured and detected (at quantifiable or nonquantifiable levels), a

dash (—) indicates the element was measured but not detected, and a blank indicates that the element was not measured.

Ref Fuel Type and Methods Species Si S Cl K Ca Ti Br Cr Fe Zn Pb

11 Fireplace with dilution chamber/woods/neutron activation Pine wood � � — � � � —

Oak wood � � — — � � �

Eucalyptus wood � � � � � —

17 Fireplace with dilution chamber/NE hardwood and Red maple logs � � � � � — � — � �

softwood/XRF N. red oak logs � � � � � — � — � �

Paper birch logs � � � � � — � — � �

E. white pine logs � � � � � — � — � �

E. hemlock logs � � � � � — � — � �

Balsam fir � � � � � — � — � �

18 Fireplace with dilution chamber/Southern hardwood and Yellow poplar � � � � � — � — � �

softwood/XRF White ash � � � � � — � — � �

Sweetgum � � � � � — � — � �

Mockemut hickory � � � � � — � — � �

Loblolly pine � � � � � — � — � �

Slash pine � � � � � — � — � �

22 Firebox with dilution sampler/ Loblolly pine — � — — — — — —

Various foliar fuels/ XRF W. hemlock — � � � — — — —

Ponderosa pine — � � � � — — —

Mixed hardwood � � � � — — — —

Palmetto/slash pine � � � � � � � �

Wiregrass/longleaf pine � � � � — — — —

27 Prescribed fire, savanna biomass/PIXE, XRF Savanna (flaming) � � � � � � � �

Savanna (smoldering) � � � � � � � �

This work Prescribed fire, ponderosa pine, XRF Flaming (grassland burn) � � � � � � � — � � �

Flaming (% of 5 1st entry) 100 100 100 100 100 100 100 60 100 100 60

Smoldering (% of 6) 100 100 50 50 100 83 67 83 100 50 33



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fire-generated aerosol when collected. The impact of in-creasingly carbonaceous aerosols in the atmosphere re-mains poorly understood. Organic compounds can affectparticle hygroscopicity, which, in turn, can affect particlesize and light-scattering properties.

The flaming and smoldering stages of the first-entryburns produced particles with distinctly different ionicand elemental compositions. The flaming stage (whereparticle concentrations were the highest) resulted in in-creased levels of particle NH4

� and NO3�, ions associated

with haze and air pollution. During smoldering, NH4�

levels decreased, but NO3� levels remained slightly ele-

vated. Particle SO42� levels appeared to be unaffected by

fire; SO42� concentrations remained at near-background

levels during both flaming and smoldering. Flaming pro-duced a more complex elemental signature (20 elements)than did smoldering (7 elements), including higher levelsof heavy metals (Fe, Zn, Cr, and Pb). Together, flaming andsmoldering produced the most commonly elements ob-served in wood fire particulate (Si, S, Cl, K, Ca, Br, Fe, Zn, andPb); detectable levels of Ti and Cr were also observed.

The maintenance (grassland) fire had a strikingly dif-ferent composition than the first-entry burns. Because itconsumed largely �10-hr fuels, it produced the lowestparticle concentration. The ionic composition was pre-dominately K, with no detectable NH4

� and low NO3�

levels. Four elements (K, Cl, S, and Ca) comprised 92% ofthe elemental mass, which also included trace amounts oftwo heavy metals (Fe and Zn). Such differences will beimportant over time, as maintenance burns replace first-entry burns in long-term applications of fire as a forestrestoration technique.

ACKNOWLEDGMENTSThe authors gratefully acknowledge helpful comments byreviewers and financial support from the U.S. Departmentof Energy through contract No. DE-FC02–02-EW15254,administered through the Historically Black Colleges andUniversities/Minority Institutions Environmental Tech-nology Consortium and Howard University; the Bureau ofLand Management, administered through the EcologicalRestoration Institution; and the Minority Student Devel-opment grant funded through the National Institute ofHealth (NIH R25-GM56931). Marin S. Robinson ex-tends her grateful appreciation to Walker Thornton andthe fire crew of the Peaks Ranger District for manyuseful conversations and permission to attend the pre-scribed fires. She would also like to thank Jeff Robinson,Kara Robinson, Arisia Lee, and Jaina Moan for theirhelp with PM2.5 collection and downed woody materialinventories. The authors also gratefully acknowledgethe laboratory support provided by several staff mem-bers at RTI International.

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About the AuthorsDr. Marin Robinson is an associate professor of chemistryand environmental sciences at Northern Arizona Universityin Flagstaff, AZ. Jesus Chavez and Sergio Velazquez weregraduate students (M.S. degree) in the Department ofChemistry during this study. R.K.M. Jayanty is with theIndustrial and Environmental Chemistry Division at RTIInternational, Research Triangle Park in NC. Address cor-respondence to: Dr. Marin Robinson, Department of Chem-istry & Biochemistry, Box 5698, Flagstaff, AZ 86011-5698;e-mail: [email protected].



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chemical speciation of pm 2.5 collected during prescribed fires of the...

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