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Atmospheric Environment 73 (2013) 124e130

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Atmospheric Environment

journal homepage: www.elsevier .com/locate/atmosenv

Sources of metals and bromine-containing particles in Milwaukee

Alison M. Smyth a, Samantha L. Thompson a, Benjamin de Foy b, Michael R. Olson c,Nicholas Sager d, Jerome McGinnis d, James J. Schauer c, Deborah S. Gross a,*

aDepartment of Chemistry, Carleton College, 1 North College Street, Northfield, MN 55057, USAbDepartment of Earth and Atmospheric Sciences, Saint Louis University, O’Neil Hall, 300E, 3642 Lindell Blvd., St. Louis, MO 63108, USAcDepartment of Civil & Environmental Engineering, University of Wisconsin e Madison, 660 North Park Street, Madison, WI 53706, USAdWater Science and Engineering Laboratory, University of Wisconsin e Madison, 660 North Park Street, Madison, WI 53706, USA

h i g h l i g h t s

� Se metal in individual aerosol particles is highly correlated with Cd, Sb, and Mo.� Se in Milwaukee is emitted largely from local point sources.� Local point sources are important contributors to metals but much less so to PM.� Summertime levels of particulate Br have increased in Milwaukee in recent years.� Submicron Br-containing particles are emitted by local point sources.

a r t i c l e i n f o

Article history:Received 11 September 2012Received in revised form5 March 2013Accepted 11 March 2013

Keywords:AerosolsBromineMetal-containing aerosolsUrban air quality

* Corresponding author. Tel.: þ1 507 222 5629; faxE-mail address: dgross@carleton.edu (D.S. Gross).

1352-2310/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.atmosenv.2013.03.014

a b s t r a c t

An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was deployed in summer 2010 in centralMilwaukee as part of a study to understand the sources of primary and secondary aerosol in thenon-attainment area of Southeast Wisconsin. Measurements were made continually from mid-July tomid-August, collecting time, size, and chemical composition data on aerosol particles. Trace metalsincluding Se, Cd, Mo, and Sb were detected in the particles. These metals were found to be related andprovided information on source types in Milwaukee, generally located southwest of the sampling site,from plumes that appear to originate from point sources. Additionally, Br was detected in individualparticle mass spectra during this study, the first such observation at an inland site. Particles that con-tained Br were found in two different size modes, each of which had a different representative chemicalcomposition. In combination with an analysis of wind direction, the data suggest that the two differentsize modes of Br-containing particles originate from chemically distinct sources.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Identification of the sources of particulate matter (PM) has beenof interest to regulators, public health officials, and researchers formany years. As urban regions continue to grow and develop, thereis continued pressure to comply with National Ambient Air QualityStandards (NAAQS, http://www.epa.gov/ttn/naaqs/). This requiresregulatory authorities to have a detailed understanding of thesources which contribute to a given region’s particulate matter, inorder to determine sources which might warrant better controlsto comply with standards. Additionally, as the health effects ofparticulate matter exposures are explored in greater detail (Pope

: þ1 507 222 4400.

All rights reserved.

et al., 2006), and with a greater emphasis on correlating thechemical composition of the particles to potential health effects,a better understanding of the sources which contribute to theambient aerosol is needed.

Detailed chemical composition measurements enable statisticalrelationships to be determined between various measured chemi-cal species using methods such as Positive Matrix Factorization(PMF), which can enable the identification of sources directly. Formany industrial sources, the characteristic elements which distin-guish the factors are often metals. Observations of metals in uniquecombinations, often in combinationwith measured quantities suchas black carbon, sulfur dioxide, nitrogen oxides, etc., enable deter-mination of profiles of the sources emitting the species (Eatoughet al., 1996; Laden et al., 2000; Lee et al., 1975; Moreno et al.,2011; Pekney et al., 2006; Polissar et al., 2001). Once specificelements have been associated with particular sources, real-time

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130 125

measurements can be made which provide more detailed infor-mation about the emissions characteristics of those sources.

Selenium (Se) has been identified as a tracer for coal combustionin aerosol particles (Eatough et al., 1996; Laden et al., 2000; Polissaret al., 2001). PMF has been used to generate factors from aerosolsampling in the Eastern United States including a Midwestern coalcombustion factor which was identified in part through the sulfur-to-selenium (S/Se) ratio. Other metals, including Cu, Zn, Mn, andothers, have been used as specific tracers of various industrialsources (Laden et al., 2000). In addition, identification of shortconcentration increases of metals or other species has been shownto indicate local sources of the emitted compounds (Snyder et al.,2009). Thus, measuring the metal species with high enough timeresolution to identify these “spikes” of signal can help separatelocal emissions (short excursions from a low background) fromregional sources (higher background and fewer distinct spikes).

Metals in particulate matter, which come from anthropogenicand natural, often crustal, sources have been implicated in healtheffects of the particles, possibly through oxidative stress induced bythe metals on the surface of inhaled particles (Kelly and Fussell,2012; Lighty et al., 2000; Rohr and Wyzga, 2012). These metalscan also accumulate in the environment, which has been of interestin the Great Lakes ecosystem (Biegalski and Landsberger, 1999;Holsen et al., 1993; Lucas et al., 1970). While these trace-metals arenot themselves significant contributors to PM2.5 mass, they canserve as valuable tracers which can be used to identify the loca-tions, and in some cases the identities, of specific sources of thesespecies. By combining data about the elemental tracers of specificsources measured in real-time with meteorological modeling andmeasurements of atmospheric gases such as SO2, new opportu-nities exist to understand sourceereceptor relationships that arenot possible with 24-h integrated filter based measurements. Inrecent work, de Foy et al. (2012) investigated the impact of local airpollution plumes on nickel, vanadium and black carbon (BC) inMilwaukee, WI, which is in one of only four regions in the Envi-ronmental Protection Agency’s Region 5 to be in non-attainmentof the 2006 24-h PM2.5 standard (http://www.epa.gov/airquality/particlepollution/designations/2006standards/documents/2011-01/map.htm).

The real-time chemical composition data can also help elucidatesources corresponding to elements that have been historically hardto associatewith sources given only filter-basedmeasurements. Forexample, bromine (Br) has been observed in particles during thesummertime inMilwaukee in increasing amounts since 2004 in theChemical Speciation Network (CSN, formally STN, http://www.epa.gov/ttn/amtic/speciepg.html) data, although the analysis of the CSNfilter-based data has not been able to identify the source or sources.Bromine has been associated with lead emissions from combustionof leaded gasoline (Paciga et al., 1975), where it is used as a leadscavenger, as well as with a variety of combustion, smelting, sea,and road-salt sources (Beddows et al., 2004; Enami et al., 2007;Hara et al., 2002; Hayakawa et al., 2004; Murphy et al., 1997;Strandberg et al., 2001; Xie et al., 1999). Br-containing chemicals,including decabromodiphenyl oxide, bromoethane, and ethyl-enedibromide are emitted by a variety of industrial sources in theregion, according to the Environmental Protection Agency’s ToxicRelease Inventory (TRI, http://www.epa.gov/TRI/). None of thesesources are particularly compatible with the seasonal trends whichhave been observed in Milwaukee. Brominated organic com-pounds, in the form of adsorbable organic bromine, have also beendetected in lake water where they were associated with photo-trophic organisms (Putschew et al., 2003). These species wereobserved in the late summer with concentrations approximately5 times higher than during the rest of the year. While the season-ality of these observations more closely matches the bromine

detected in Milwaukee’s particulate matter, it does not fit theprofile of essentially no bromine detected during the autumn,winter, or spring seasons, nor is it clear that these brominatedspecies would be found associated with particulate matter. Weinvestigate the chemical composition of the Br-containing singleparticles further, in combination with examination of the meteo-rology when they were detected, to provide more insight into thepotential sources of these newly described particles.

Here we use a single-particle mass spectrometer to measuretemporal profiles of tracer species in single-particles withhourly time-resolution, in combination with gas-phase and bulkparticulate-phase measurements and meteorological modeling, toinvestigate particle sources. The current study demonstrates theutility of integrating single-particle mass spectrometry data withmeteorological data to provide a greater understanding of thesources of selenium, cadmium, antimony and molybdenum, as wellas to investigate the sources of the observed Br in particulate matterin Milwaukee. The results presented here highlight the fact thatspecies which are used as tracers for particular sources can often beemitted by multiple sources which might or might not be related.

2. Methods

2.1. Sampling

The core data used in this study were collected from July 9 toAugust 13, 2010. The sampling site was at the South East Region(SER) headquarters of the Wisconsin Department of Natural Re-sources (DNR) in central Milwaukee at 43.06�N, 87.91�W. Particleswere sampled through a copper line connected to amanifold whichincluded multiple other sampling units, including an API SO2monitor (Teledyne, San Diego, CA). Further descriptions of the in-struments used and the sampling manifold are given by de Foy(de Foy et al., 2012). This analysis focuses on observations from theAerosol Time-of-Flight Mass Spectrometer (TSI 3800 ATOFMS,Shoreview, MN) and the SO2 data collected in parallel. PM2.5 datawas obtained from the Wisconsin DNR (http://prodoasjava.dnr.wi.gov/wisards/webreports/previousDaysData.do). Speciation datawas obtained from the US EPA Chemical Speciation Network (CSN)through AirData (http://www.epa.gov/airdata/). The DNR and CSNsites are co-located. Meteorological data were from the IntegratedSurface Hourly Data from the National Climatic Data Center, whichhas hourly wind and temperature observations. The nearest site isat General Mitchell International Airport (KMKE), located 16 kmsouth of the measurement site.

2.2. Bromine

Bromine data is obtained from the Chemical Speciation Network(CSN) dataset and is determined by X-ray fluorescence. All sampleshave been blank subtracted based on average blanks reported onthe EPA data website. Years 2002e2010 were average annual blanksubtracted for the given sampling year. Years 2011 and 2012 did nothave blank results available and were blank subtracted by theentire (2002e2010) average blank values.

2.3. Aerosol Time-of-Flight Mass Spectrometer

The ATOFMS has been described in detail elsewhere (Gard et al.,1997). Briefly, a vacuum pulls particle-laden air into the inlet of themass spectrometer. There, particles are collimated into a beam andparticles traveling on the center-line of the instrument scatter lightfrom two continuous-wave lasers (532 nm), with the particles’vacuum aerodynamic diameter calibrated to the particle velocityusing polystyrene latex spheres of known size. The particles are

Milwaukee CountyWaukesha County

DNR

KMKE

88.4° W 88.2° W 88.0° W 87.8° W 42.8° N

43.0° N

43.2° N ≤ 0.26 lb/yr≤ 3 lb/yr≤ 107 lb/yr≤ 577 lb/yr

Fig. 1. Map of Milwaukee and Waukesha counties showing the sampling location(DNR) and the site of the meteorological measurements (KMKE), indicated with stars.The other symbols represent National Emissions Inventory sources of selenium, withthe symbols indicating the emission-level. Milwaukee County is on the western shoreof Lake Michigan.

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130126

then desorbed and ionized using the fourth harmonic of a Nd:YAGlaser (266 nm). Positive andnegativemass spectra are obtained fromeach particle that is ionized by the laser. The ATOFMS continuouslysampled particleswith vacuumaerodynamic diameters between 0.2and 5 microns and spectra were obtained for 529,161 particles dur-ing the 838 h of sampling during the 5-week study.

2.4. Single-particle data analysis

The total peak area detected in the ATOFMS mass spectra for themajor isotope of an atomic or molecular ion over an hour was sum-med and timelines of peak area were generated using the ENCHI-LADA software package (Gross et al., 2010). Particle count timelineswere generated for bromine-containing particles using MS-Analyze(TSI Inc., Shoreview, MN). Queries for bromine-containing particleswere written to select only particles containing peaks at �79and�81atomicmassunits (amu)andtimelines showing thenumberof particles matching the query criteria per hour were generated.

10,000

5,000

10,000

10,000

ATO

FMS

Peak

Are

a/H

our (

A.U

.)

105

7/11/2010 7/21/2010

SO2

(ppb

)

50

30

30

10

PM

(µg/

m3 )

Antimony

Cadmium

Molybdenum

Selenium

SO2

PM 2.5

Fig. 2. Timelines of summed peak area (arbitrary units) of the four correlated metals (Mo, Seon the left is a period where the spikes in metal concentration are accompanied by low SO2 las shown in the gray highlighted time on the right.

Principal component analysis (PCA) was used to identifycorrelated species, using software written in LabView (Cich et al.,2010). All ATOFMS timelines were normalized (to either the totalpeak area in a timeline or to the total number of particles) toenable different kinds of timelines to be combined in a single PCAanalysis.

Plumes in temporal data were identified using ENCHILADA; atime period was labeled as being a portion of a plume when theindividual data point exceeded a user-determined percentage ofall values in the timeline, and were confirmed manually. Plumedurations were determined by examining timelines of individualspecies with time resolution varying from 5 min to 1 h.

3. Results and discussion

3.1. Particulate metals

One of the major goals of this study was to identify and char-acterize emissions from coal-fired power plants. To this end, Se wasinvestigated, as it is a known tracer for particulate matter emissionsfrom power plants (Eatough et al., 1996; Laden et al., 2000; Polissaret al., 2001). The 2008 National Emissions Inventory data for Seemissions in the Milwaukee area (NEI, http://www.epa.gov/ttn/chief/eiinformation.html) are shown in Fig. 1, as well as the loca-tion of the sampling site in central Milwaukee (DNR), GeneralMitchell International Airport (KMKE) and Lake Michigan, to theeast. There are many sources of Se listed in the NEI, with two coal-fired power plants being the two most significant sources to thesouth of the sampling site. The locations of the Se sources shown inthis figure generally indicate the industrially zoned region of Mil-waukee (Rast, 2012), but do not necessarily indicate all of thesources operating during this study.

Timelines of a wide variety of ATOFMS ions were input into PCAto determinewhich species were temporally correlated with Se. Cd,Sb, and Mowere the ions found to be most strongly correlated withSe, suggesting that they are emitted from common sources. Thetemporal profiles of the ATOFMS signal for these four metals areshown in Fig. 2. The signal observed from these metals is concen-trated into short-duration plumes, or “spikes.” Over the course ofthe entire study, 65% of the Se signal observed in the single-particle

7/31/2010 8/10/2010

, Sb, Cd) observed in the ATOFMS spectra, PM2.5, and SO2. The time highlighted in grayevels; peaks in SO2 concentration also are also observed with low metal concentrations,

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130 127

mass spectra was observed in only 25% of the hours in which datawere acquired.

As can be seen in Fig. 2, the temporal trend exhibited by themetal ions discussed here is very different from that of PM2.5observed at the Milwaukee site (r ¼ �0.01 with Se, indicating nocorrelation). This is in contrast to other ATOFMS time-series datawhich correlate quite strongly with PM2.5, including total numberof particles and the summed peak area of m/z �48 (C4�, a proxy forelemental carbon (EC)-containing particles), which have correla-tion coefficients of r¼ 0.79 and 0.54, respectively. While this showsthat the source of the metal-containing particles is not a majorsource of the PM2.5, the investigation of these plumes can giveinsight into emissions sources which could have impacts on humanand environmental health.

There are times when short duration (from 10 min up to 10 h)increases in metals peak-areas are accompanied by 3e4 h-longspikes in SO2, which is a common indicator for local industrial stackand power plant emissions. The coincidence in timing suggests thatthere is a source common to these metals and SO2 and furthersuggests that industrial or power plant emissions contribute to theconcentrations of these metals. However, there are times whensignificant signal due to metals is observed and SO2 is not, and viceversa, as indicated in the highlighted periods in Fig. 2. Because therelative emissions contributions of Se and SO2 vary as a function oftime, we conclude that either they are emitted by a source thatoperates with different emissions characteristics at different timesor that there are multiple sources of these species.

To further characterize these metals and the SO2 episodes, eachhour-long time bin in the study was placed into one of three cat-egories based on the summed peak areas of metal species and SO2.The three categories defined were (1) hours with both SO2 and themetal peak area in the lower 50 percentile of the values (“lowmetals & SO2”), (2) hours with a ratio of metal to SO2 that was in thelower 50 percentile range of the averages (“low metal/SO2”), and(3) hours with a ratio of metal to SO2 that was above the 50percentile range of the averages (“high metal/SO2”). The averageratios were calculated using all values in the 5 to 95 percentile ofconcentrations for each species. A similar data analysis approachwas performed by de Foy to estimate the amount of coupling be-tween V and sulfur dioxide (de Foy et al., 2012). Separation of themetal signal into three categories was also carried out comparingthe metals to ATOFMS hourly peak-area timelines at m/z �48 (C4

�)and PM2.5, in place of SO2.

Fig. 3a shows the percent of observed metal peak area assignedinto each of these three categories, based on a comparison to theconcentration of SO2, EC, or PM2.5 observed in the same hour. Theresults obtained here are similar for all four metals, Se, Cd, Sb, andMo, and the uncertainty indicates one standard deviation of theaverage of these four species. During the times when the sampling

405060708090

100

X = EC

X = PM2.5

a

0102030

Low M & X Low M/X High M/XAv

era

ge

%

M

eta

l in

C

ate

go

ry

Category

Fig. 3. a) Average quantity of metal (M ¼ Se, Cd, Sb, and Mo) signal and b) average quantityM & X, low M/X, and high M/X categories.

site was impacted by metal plumes and relatively low concentra-tions of SO2 were observed (“high metal/X” where X ¼ SO2), anaverage of 54 � 4% of the peak area for each metal was detectedwhile only 10.0 � 0.4% of the total SO2 was detected. In the timeswith low metal/SO2, 67.9 � 0.7% of the SO2 was detected, whileonly 29 � 3% of each metal was detected. The lowest 50 percentileof values include 22.1 � 0.8% of SO2 and 17 � 2% of the metalssignals.

To better understand the characteristics and sources of theseplumes, we examine the particle size distributions and the windroses for all of the hours of the study, separated into these cate-gories. No significant differences in the particle size distributionswere observed when time periods assigned to the various cate-gories were compared. Because the inlet used with the ATOFMSsamples particles only in the 0.2e5 mm size range, there could besubtle differences in the particle size distribution outside of thisrange which would not be detected. A wind rose for the wholestudy is shown in de Foy et al. (2012) and shows that windoriginates from all directions during the sampling period, withslightly more hours with wind from the S to W quadrant. Windroses for the categorized hours for Se and SO2 are shown in Fig. 4.The wind was often coming from the WSW or calm when hourswere classified in the high Se/SO2 category (Fig. 4a), and thesehours were largely overnight, as shown by the color-scale in thewindrose. At times when the Se/SO2 ratio was low, the windoriginated from the SE in the afternoon or the SW in the overnighthours (Fig. 4b). This is consistent with the wind rose observed forSO2, where the highest 10% of values originate in the S during theovernight and morning hours. Times when both species were lowinclude wind coming from all directions, as seen in Fig. 4c.Together, these results suggest a local source close to the samplingsite which impacted the site during stagnant episodes, as well as asource of Se WSW of the site. A major industrial section of Mil-waukee, the Menomonee Valley, is located near the sampling site,to the SW. This is the most likely origin of point source emissionsof metals and SO2.

Analyses with EC or PM2.5 in place of SO2 also generated similarresults for the four metals in each category, as shown in Fig. 3.Times when both the metal and EC or PM2.5 are low account forless of the metal signal than times when both the metal and SO2concentrations are low, due to the smaller number of hours whichfall into this category (for Se, 43%, 36%, and 31% of the study hoursfall into this category when compared with SO2, EC, and PM2.5,respectively). The division of the rest of the study hours variesbetween species. The peak area frommetals is comparable in timescategorized as “low metal/EC” and slightly less is detected in timescategorized as “low metal/PM2.5,” as compared to the “low metal/SO2” category. The “high metals/PM2.5” category accounts for moreof the metal ion signal as well as more of the PM2.5 concentration

405060708090

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X = EC

X = PM2.5

b

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Low M & X Low M/X High M/X

Av

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%

X

in

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of SO2, EC, or PM2.5 (X) measured in hours assigned as described in the text into low

5%10%

15%N

E

S

W 25%

Calm

5%10%

15%N

E

S

W 17%

Calm

5%10%

15%N

E

S

W 8%

Calm

Fig. 4. Wind rose of the hours representing ATOFMS signal intensity for the trace metal Se in a) the high Se/SO2 category (187 h), b) the low Se/SO2 category (235 h), and c) the lowSe and SO2 category (416 h). Bars are shaded according to the time of day. Wind observations were made at Milwaukee Airport (KMKE).

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130128

than does either of the other two categories. As seen in Fig. 2, thetemporal profile of the PM2.5 signal is characterized by a highbackground and few short-duration spikes, consistent with aregional source. The signal due to the peak at m/z �48 in theATOFMS spectra has a temporal profile with some short spikes ontop of a higher background than that observed for Se or the othermetals.

An assessment of the common hours between the various cat-egories shows that there were many hours with both high metal/SO2 and high metal/EC ratios. Time periods with high metal/SO2

ratios constitute 22% of the hours in the study. Similarly, time pe-riods with high metal/EC ratios constitute 24% of the hours in thestudy; 86% of these hours are in common. This suggests that asource (or sources) of metals which accounts for nearly half themetal peak area detected by the ATOFMS emits relatively lowconcentrations of both SO2 and EC. Of these times, nearly 40% hadwinds originating in the SW, suggesting a significant source ofmetals associated with low SO2 and EC from that direction; 17% ofthese common hours had calm winds, indicating that stagnationevents were an additional significant contributor to times with highmetal concentrations.

Most of the ATOFMS signal for Se, Cd, Sb, and Mo detectedduring the study was measured with low levels of SO2, EC, or PM2.5or when the ratio of metal to the other species was high. However,the fact that 17e29% of the total metal peak area measured duringthe study was found with low ratios of metal to SO2, EC, or PM2.5again highlights the diversity of sources of these species.

3.2. Particulate bromine

Since 2004, the Milwaukee Chemical Speciation Network (CSN)site has recorded particulate Br concentrations during only the

100

80

60

40

20

01/1/2002 1/1/2004 1/1/2006

Br (n

g/m

3)

Fig. 5. Timeline of Milwaukee CSN site bromine X-ray Fluorescence (XRF) da

summers, as shown in Fig. 5, although the source is unknown.These bromine emissions were not seen at the two other CSNsites in Southeast Wisconsin, which are located in Mayville andWaukesha (approximately 100 km NW and 40 km W of Mil-waukee, respectively). The presence of bromine compounds wasalso detected with the ATOFMS during the summer 2010 Mil-waukee study. Mass spectra of representative bromine-containingparticles from the sub- and super-micron size range are shown inFig. 6. These spectra have very different ion compositions. Thesmaller particles contain organic fragments, potassium, nitrates,and sulfates, characteristic of particles originating from combus-tion or industrial sources. The larger particles contain significantamounts of calcium and nitrates, as well as species such asaluminum and magnesium. They are similar in composition tothose typically described as dust, indicating that some of thebromine could be crustal in origin (Claquin et al., 1999) or couldbe associated with contaminated dust or coarse particulatematter.

The time series and size distribution of bromine-containingparticles were also determined. Particles containing the bro-mide ion (Br-) were identified by querying a database containingsingle-particle spectral data by searching for particles with peaksat m/z values of �79 and �81 with a peak area greater than 100. Itwas found that 12,232 particles in the study matched this query(2.3% of the total number of particles sampled). The averagevacuum aerodynamic diameter of particles containing bromine isslightly larger than that of the entire population of detectedparticles.

Br-containing particles less than 1 mm and greater than 1 mm inaerodynamic diameter also had different temporal trends. In thetimelines shown in Fig. 7, the number of Br-containing particles isplotted, instead of peak area as was done for the metal ions,

1/1/2008 1/1/2010 1/1/2012

ta. Bromine has been detected over the summers since 2004 at this site.

5%10%

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Calm 0 6 912151824

Timeof Day

a) Br > 1µm

5%10%

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Calm 0 6 9 12 15 18 24

Timeof Day

b) Br < 1µm

Fig. 8. Wind roses for the top 5% of times with high levels of a) super-micrometer(36 h) and b) sub-micrometer (23 h) Br-containing particles. Bars are shadedaccording to the time of day. Wind observations were made at Milwaukee Airport(KMKE).

-200 200-100 1000m/z

HSO4-

NO3-

NO2-

NO2-

OH-

PO2-

Br-

Br-

K+

C2H3+

C2H3O+

C4H3+

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C6H5+

K+

CaO+

CaOH+Mg+

Al+

a

b

Rel

ativ

e Pe

ak A

rea

Rel

ativ

e Pe

ak A

rea

Fig. 6. Representative single-particle mass spectra from individual Br-containingparticles with vacuum aerodynamic diameters of a) 0.41 mm and b) 3.1 mm.

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130 129

because signal from the SO3� ion (�80 amu) overlaps with signal

from Br�, distorting timelines based on peak area. Note that thelarge particles, those that resemble dust, are continually presentand there are no significant spikes in the number of largeBr-containing particles detected. On the other hand, the smallBr-containing particles have a much more variable and “spiky”temporal profile. This suggests that, even if some of the bromine ispresent in the form of dust, there is another, more local sourceof bromine. This is also supported through wind roses of Br-containing particles, as shown in Fig. 8. These plots show that thetimes with high levels of the large Br-containing particles hadwinds from variable directions (Figure 8a) and 43% of the timeswith high levels of the small Br-containing particles were episodesof calmwinds (Fig. 8b). Also note that the winds during times whenthe highest number of the larger particles were observed originatedover land, while the winds when the highest number of the smallerparticles was observed originated over Lake Michigan, suggestingeither that the lake is a source or that there is a local source in thatdirection.

The one-hour time-period in which the ATOFMS observedthe largest number of sub-micron Br-containing particles, corre-sponding to 2.2% of the total Br-containing particles observed(1.5 times more than in the next-most populous hour) was on7/30/2010 from 11:00 e noon. Although only a short event, thishour was notable for having a significant spike in many observedmetals, especially lead. It included 13% of the total observed peakarea for Pb (m/z 208 isotope) over the entire 838-h study, and thePb summed peak area was 8 times larger than the next-mostpopulous hour. This coincidence in timing suggests that thesespecies could be co-emitted by the same source. The meteorology

200

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07/11/2010 7/21/2010

Br-Containing Particles, Da < 1 µm Br-Containing Particles, Da > 1 µm

Nu

mb

er o

f B

r-C

on

ta

in

in

g

Pa

rtic

le

s/H

ou

r

Fig. 7. Timeline of number of bromine containing particles observed with the ATOFMS per hat 11:00.

on this day shows that winds were calm throughout the overnighthours, increasing at approximately 10:00 am from the south. Backtrajectories show a stagnation event with air transported from thenorth changing to local transport from the south during the mid-morning, coincident with this change in the Pb and Br signal.

The coincidence of lead- and bromine-containing particlessuggests that a significant source of the bromine could potentiallybe from aviation fuel (“Avgas”), a leaded fuel used for generalaviation piston-engine aircraft. There is a known correlationbetween the emission of lead and the emission of bromine inparticles formed from combustion of leaded fuel (Paciga et al.,1975), as Br-containing compounds are used as Pb-scavengers inthe fuel. There are at least 10 general aviation airports withinapproximately 50 km of Milwaukee at which are emitted, at aminimum, more than 1481 kg of lead per year during the landing-take-off cycle (EPA, 2008), and the calm conditions under whichthese particles are most commonly observed could be consistentwith small-aircraft use.

The ATOFMS data has confirmed the results recorded by the CSNand further characterized the sources of Br in theMilwaukee area. Ithas been shown that the particle size of the Br-containing particlescorrelates to particle composition as well as to the direction fromwhich the particles originated. The larger particles (greater than1 mm in aerodynamic diameter) contain dust-related elements,suggesting a crustal origin. They were detected when winds origi-nated over the land from a variety of directions. In contrast, thesmaller particles (smaller than 1 mm in aerodynamic diameter)contain a significant amount of OC, suggesting a more industrial orcombustion-related source. These particles were detected duringcalm episodes or when the wind originated over the lake and wereassociated more frequently with plumes than were the largeBr-containing particles.

7/31/2010 8/10/2010

our. The number of Br-containing particles detected is at a maximum on July 30, 2010

A.M. Smyth et al. / Atmospheric Environment 73 (2013) 124e130130

4. Conclusions

The species Se, Cd, Sb, andMo can provide insight into sources ofparticulate matter in Milwaukee. These species are often observedin the same single-particle mass spectra and have very similartemporal profiles. They could be emitted by sources local to thesampling site as well as sources to the SW of the site. These speciesare detected in plumes, and are thereforemost likely emitted by thesame local sources. Our analysis shows that sometimes the metalsare correlated with SO2 emissions, suggesting local coal-fired po-wer plants as a potential source, while at other times, themetals aredetected in high levels while SO2 is low, indicating that there aremultiple sources of the metals or multiple operating conditions fora single source. Se and correlated metals are observed morestrongly when the winds originate to the southwest of the sam-pling site in urban Milwaukee or during stagnation events. Metalsare associated with PM2.5 and EC and we can attribute much of themetal ion signal detected to point sources.

We have also shown that Br is a significant species present inMilwaukee’s particulate matter. It is detected most frequently inthe summers and has been seen annually since 2004. The ATOFMSdata showed that there aremultiple types of Br-containing particlesemitted and that those particle types are size dependent. Thechemical composition of those particles indicated a crustal sourceof Br (larger particles) as well as an industrial one (smaller parti-cles). Wind roses for these two types of particles support that theyhave different origins. The larger Br-containing particles weredetected during episodes with winds from a variety of directionswhile the smaller particles were detected during calm episodes orwhen the air originated over LakeMichigan. Further investigation isrequired to determine specific sources of the bromine.

Acknowledgments

We thank the Bureau of Air Monitoring at the WisconsinDepartment of Natural Resources for their assistance with themonitoring measurements used in this study, and we acknowledgethe extensive support of Mary Mertes and Mark Allen. We thankSteven Drew for assistance with the Principle Component Analysis.We are grateful to the US National Climatic Data Center for themeteorological data. This research was supported by Wisconsin’sFocus on Energy Environmental and Economic Research andDevelopment Program (EERD) Grant 430 number 3104-01-10,entitled: “Contributions of Fossil Fuel-Fired Electric Power Gener-ation to PM2.5 Concentrations in WI.” Carleton College was sup-ported by a Research Opportunity Award from the National ScienceFoundation, award ATM-0810950.

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