Characterization of individual fine-fraction particles from the Arctic aerosol at Spitsbergen, May–June 1987

Atmospheric Environment Vol. 26A, No. 9, pp. 1747-1762, 1992.

0004-6981/92 $5.00+0.00 © 1992 Pcrsamon Prom Ltd

Printed in Great Britain.

CHARACTERIZATION OF INDIVIDUAL FINE-FRACTION PARTICLES FROM THE ARCTIC AEROSOL AT SPITSBERGEN, MAY-JUNE 1987 JAMES R. ANDERSON, PETER R. BUSECK a n d DANIEL A. SAUCY Departments of Chemistry and Geology, Arizona State University, Tempe, AZ 85287, U.S.A.

and JOZEF M. PACYNA Norwegian Institute for Air Research, P.O. Box 64, 2001, Lillestrom, Norway (First received 7 April 1990 and in final form 21 October 1991)

Abstract--Aerosolparticles collected in May and June 1987 at Ny Alesund, Spitsbergen, have been analysed with an automated electron microprobe for chemistry and size. Chemical data from about 30,000 individual particles in the fine fraction (0.1 to ~ 2.0 fan in average diameter) were subjected to nonhierarchical duster analysis, resulting in the definition of over 30 distinct particle types. Principal component analysis of the 22 most abundant types indicates the presence of 11 components that account for most of the variance in the aerosol composition. Some of the particle types were associated with the end of an episode of polluted air from northern Eurasia during the first few days of sampling. The remaining types do not have any clear association with air masses from industrial areas, although a number are metal-bearing (with Cr, Fe, Ni, Cu, Zn, As or Pb) and probably of anthropogenic origin. After the end of the initial episode of polluted air, the sampling period probably represented "normal" conditions for late spring in the Arctic. Silicate particle types of probable crustal origin were the dominant group by volume through most of the period. Also important were particles of probable marine origin. However, marine particles have been so extensively modified by fractionation and reaction that the combined marine aerosol components bear little resemblance to sea salt. The individual-particle data cieady demonstrate the complexity of the aerosol at this remote Arctic site and the presence of crustal and anthropogenic pollutants during an ~unpolluted" period. Key word index: Aerosol particles, marine aerosol, crustal aerosol, anthropogenic aerosol, aerosol chemistry, aerosol size distributions, Arctic.

INTRODUCTION The unique advantages of automated analysis of the chemical compositions and morphologies of individual particles make it a powerful complement to bulk-particle studies of Arctic tropospheric aerosols. In the past decade, numerous studies of bulk aerosols have significantly expanded knowledge of the seasonal cycles and episodic nature of the transport of anthropogenic and crustal components into the Arctic. Current knowledge is well summarized in several papers (e.g. Barrie, 1986; Maenhaut et al., 1989) and forms the foundation for the use of individual-particle methods on aerosols of the high Arctic. Automated electron microanalysis of large populations of individual particles allows the chemical identification of most particle types in an aerosol. Once chemically identified, the particle types can be characterized as to size and shape distributions, and temporally tracked with regard to concentrations and size distributions. Many of the practical problems involved in studying sufficiently large populations of individual particles have been removed by recent progress in methods for automated electron beam

microanalysis (e.g. Raeymaekers et al., 1984; Markowicz et al., 1986; Buscck et ai., 1986; Anderson et al., 1988; Van Borm and Adams, 1988). The analytical advances have made it possible to examine a statistically significant sampling of individual aerosol particles with submicron diameters, as small as 0.1/~m in this study. Only a few studies of Arctic aerosols have used microbeam analysis techniques, whether manual (the first was by Shaw, 1983) or automated (Saucy et al., 1987). This study focuses on individual-particle analysis of the fine fraction (0.1 to ~ 2.0/an in average diameter) from samples collected at Spitsbergen over a 30-day period in May-June 1987. After first identifying the chemically distinct types of aerosol particles present and then examining temporal variations of each type, our goal is to use the data to interpret the probable origins and histories of these fine-fraction particles. Size distributions for a few major types are also examined, although a more detailed treatment is deferred to a forthcoming paper in which the coarsefraction particles arc also discussed. The procedures for automated microanalysis of individual particles differ from those we previously

1747

1748

J.R. ANDERSON et at.

used (Anderson et al., 1988; Saucy et al., 1987) a n d from others doing similar work (e.g. Bernard et al., 1986; Van Borm et al., 1989). The current m e t h o d employs a modified version of commercial imageanalysis software for electron m i c r o p r o b e / S E M analysis of particles using stored digitized images. Better inherent spatial resolution a n d the use of nonlinear frame-averaging to reduce image noise allow automated analysis of smaller particles t h a n was previously possible; the lower size limit is now a function of declining intensity of characteristic X-rays with size rather than a limit in spatial resolution. F o r readers unfamiliar with single-particle analysis using electron-beam instruments, Raeymaekers et al. (1984) a n d Markowicz et al. (1986) provide overviews of the equipment a n d general methods. In brief, a b e a m of electrons is accelerated by a high potential, in this case 20,000 V, focused using electromagnetic lenses, and positioned o n or scanned across a sample by a system of electromagnetic scanning coils. Imaging of the particles a n d their substrate is accomplished using backscattered electrons, primary electrons from the b e a m t h a t have undergone a sufficient n u m b e r of elastic interactions with a t o m i c nuclei in the sample to have their directions altered by greater t h a n 90 ° . Chemical data are o b t a i n e d from characteristic X-rays generated by ionization of inner electron shells of atoms in the sample by primary electrons in the beam a n d other high-energy electrons a n d X-rays produced in the process. F o r the analytical conditions a n d materials used, the primary electrons penetrate a n d are scattered within a volume of the sample that has a diameter of a b o u t 1-2/am; therefore, submicron particles can be considered to be semit r a n s p a r e n t to the electron beam. The semi-transparency affects the way in which the chemical data must be handled.

EXPERIMENTAL

Sampling methods and conditions

Aerosol samples were collected at a station operated by the Norwegian Institute for Air Research (NILU) near Ny Alesund (78055, N, 11°57' E), Spitsbergen. Sampling was done with stacked holders loaded with 8.0 and 0.2-/am pore diameter, polycarbonate Nuclepore membrane filters of 47 mm diameter. Sampling extended from 13 May to 12 June 1987 with each sample collected for about 24 h. In the following, samples are labeled by the day on which their collection began. Two blank filter sets were handled in the same manner as the samples, except that no air was drawn through them. For each sampling period, the measured air volume averaged about 20 m a. The cut-size is between 1 and 2/am (see fig. 1 of Saucy et al., 1987). Temperatures measured at Ny Alesund varied from - 11 to 5°C, and the relative humidity averaged 75% over the sampling period. Surface winds were from the southeast for the first 4 days and mostly from the northwest the last 5 days. For the rest of the period wind direction was variable but was mostly either from the southeast or from the southwest to northwest.

Analytical methods

Samples were prepared for electron microprobe analysis by cutting 5 x 5 mm sections from the centers of filters and mounting them on carbon stubs with carbon paint. A carbon film of ~ 200/~ was evaporated onto each section. Mounted sections were then analysed with a JEOL Model JXA-8600 electron microprobe automated with TRACOR-Northern (TN) TN-5500 and TN-5600 systems. Backscattered electron (BSE) images were acquired using an annular, split-ring, semi-conductor detector mounted 11 mm above the sample. Images were digitized and stored in the system's 2-Mbyte image memory. X-ray spectra were acquired with a TN energy dispersive spectrometer (EDS) with a Be window. Normal operating conditions were an accelerating voltage of 20 kV and beam current of 500 pA. Counting times for Xray spectra acquisition were 100 s live-time; relative deadtimes were about 30%. Magnification was 2000 x, resulting in frames 43/am on a side. Image resolution was 512 × 512 pixels, with a relative grey-level scale of 0 to 511 (8 bits). Pixel size at this magnification and resolution is 0.08 #m; particle sizes are therefore artificially quantized into multiples of 0.08 #m. Standard X-ray spectra were acquired by analysing flat, polished samples of metals, simple oxides, simple salts and a few well-characterized minerals. Reference spectra were fitted to particle spectra using the TN program MICROQ. The values produced by MICROQ, "k-ratios", were then corrected with TN's ZAF program to obtain weight percentages of the elements, from which atomic fractions of the elements were calculated. All compositions in this study are reported as atomic fractions. The use of flat-sample corrections introduced some systematic error into the particle compositions but has little effect on clustering and characterization of particle types. Another simplification is that C, N and O were not measured; therefore speciation of most compounds can only be inferred, not directly determined. Elements routinely analysed were Na, Mg, AI, Si, P, S, CI, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Cd, Sn and Pb. For each element, the lower limit of detection was chosen to be the concentration at which the relative standard deviation determined by MICROQ is 20%. For the conditions used, this corresponds to about 0.15-0.4 wt.% for most elements. Concentrations below the detection limits were set to 0.0. The use of conservative detection limits helps to eliminate problems caused by spectral artifacts commonly encountered in EDS analysis. The location, measurement and X-ray analysis of particles were controlled by a modified version of TN's VISTA program. VISTA has been augmented and modified by us to run unattended over multiple frames (either a grid of frames or noncontiguous frames listed in a table) on one or more samples and to store spectral and size data on disk for later processing. BSE images were acquired using nonlinear averaging of 10 frames. The grey level of each of the pixels in an image was compared to a grey-level threshold, set to separate the polycarbonate substrate (relatively dark due to low average Z) from the brighter particles resting on it. Each pixel at or above the threshold was converted to a value of one and each pixel below the threshold to 0 to form a 512 × 512 pixel binary map. The particle area, maximum and minimum diameters, shape factor, perimeter, orientation, location and other parameters are calculated from the binary maps. For each particle, its projected image on the X- and Y-axes was used to position a rectangular raster of the electron beam for X-ray spectral acquisition. A 1.0-#m guard region was used to exclude particles only partially in the frame. The particle diameters listed below were calculated from measured average diameters, determined from the mean value of 32 diameter measurements on each particle. Particle volumes were estimated from measured areas multiplied by minimum diameters.

Fine-fraction particles of Arctic aerosol Cluster and principle component analysis

Clustering of particle data was done with the program EXPLOR (Saucy et al., 1987, 1991). The Forgy k-means algorithm was the basis for cluster analysis. A similarity measure that represents the angle between vectors from the origin to two points in 24-dimensional composition space was used (Killeen et al., 1981). This measure, s4, is advantageous in the cluster analysis of chemical data from submicron particles (Saucy et al., 1987) because of their semi-transparency to the electron beam. In this study the limiting value of s4 about a cluster center, the centroid, was 20° except as noted. The calculation of cluster centroids was an iterative process that continued until a stable set was determined. The unclustered data were divided into arbitrary subsets, seedpoints (initial centroids) were selected in the manner described by Saucy et al. (1987), and the data were repeatedly clustered about recalculated centroids until cluster membership became stable for each subset. The subsets were mixed, new seedpoints determined, and new centroids calculated. After several iterations of remixing subsets and reclusteringo all of the resulting centroids were themselves clustered to produce the final centroid set. These final centroids were used to make assignments of particles to clusters for each of the samples. To check on the possible presence of other significant clusters, all particles not falling within 20° of the final centroids were then reclustered by mixing, choosing seedpoints, clustering about an increased limiting value of s4 (30°), remixing~ and so on, For the samples discussed, no additional significant centroids were found. After assignment of particles to specific clusters, the concentrations of each cluster were calculated for the sampling periods. The relationships among the particle dusters were examined using principal component analysis (PCA), which employs methods described by Saucy et al. (1991). Similar procedures, derived from work by Thurston and Spengler (1985) and Keiding et al. (1986), have been described by Maenhaut and Cafmeyer (1987). Maenhaut et al. (1989) have applied PCA to bulk aerosol samples from the Norwegian Arctic. The PCA data matrix used the cluster concentrations as variables and the sequence of sample periods as time. To simplify the analysis, only the most abundant clusters were used; the least abundant clusters have high relative errors in concentration and would introduce substantial noise. The correlation matrix was calculated after the retained subset of variables were standardized by subtracting the mean and dividing by the standard deviation. The results were subjected to ordinary PCA, followed by Varimax rotation. Limitations in the uniqueness of PCA in this study may arise due to the relatively small number of samples and the effects of averaging over the 24-h sampling period, during which concentrations of individual particle types could have been highly variable. A possible result of such averaging could be the accidental apparent correlation of particle types that, when examined on a shorter time scale, were relatively uncorrelated.

RESULTS Analysed particles--introduction

Initial objectives in analysing these samples are to identify the constituent particle types of the aerosol and determine the concentration of each type in each sample. The chemistry of particle types, the statistical relationships among types, and the nature of periods of high concentration of individual types can then be used to explore origins, modifying reactions, source

1749

distances, and other characteristics of the fine-fraction aerosol components. The n u m b e r of particles analysed per sample determines the lowest detectable concentration of any particle type, which in turn directly influences how many particle types can be recognized. F r o m the 30 fine-fraction samples, 30,070 particles were located and analysed for morphology and composition; ~ 22,000 (73%) had one or more elements present in concentration above the thresholds used as the detection limits (in the following, these are "usable" particles). Those particles without any elements above the thresholds are excluded from further treatment; most are probably carbon-rich particles, but at least a small fraction are artifacts such as topographic features on the filters. Because Ga, Ge, Se, Cd and Sn were not found above the detection limits except in a very few isolated particles, in practice only 19 compositional variables were used. Analysed blanks have approximately 0.1 "usable" particles per frame, compared to an average loading of 3.0 "usable" particles per frame for the samples. However, very few of the particles in the blanks fall within the compositional ranges of the major particle types discussed below, except as noted. The contaminating particles on the blanks may have come from the filter holders, despite the holders having been cleaned prior to use; unused filters from the same lots have far fewer particles than the blanks. Cluster analysis resulted in 59 cluster types, which represent 93% of total "usable" particles. The remainder fall into cluster 0 (abbreviated CO); this cluster includes a variety of particle types of very low concentration. For C1-C59, 22 clusters have concentrations that sum to 2.0 x 104 particles per m 3 of air or greater over the 30-day sampling period (Table 1). The 22 clusters above this arbitrary threshold account for 83% of total particles; these are the clusters used for PCA. The daily concentrations by count and volume and daily mean diameter for total particles are shown in Fig. 1. The first and last sampling periods show the highest particle concentrations by count. However, because of the predominance of small particles, mostly from C41 (Fig. 2), these two periods do not have the highest volume concentrations. Some less abundant but otherwise interesting particle types are listed in Table 2. Included are several metal-bearing clusters, as well as some general categories of metal-bearing particles that fall within the unassigned group, CO; some particles of these latter types are probably polyphase aggregates. For the tabulated clusters, the concentrations are listed both by particle count and by summed particle volume. Because different clusters may have quite different size distributions, the relative contribution of a cluster to the total volume of all particles may differ substantially from its contribution of total n u m b e r of particles. The most striking example is C41; while it accounts for almost half of the total particles by count,

1750

J.R. ANDERSON et al.

Table 1. Major clusters in fine-fraction samples. Compositions are in atomic fractions. The cluster numbers reflect sorting by selected elements, but otherwise have no significance Integrated concentration* Centroid composition (.elements />0.03)

Cluster C3 C5 C6 C7 C10 C13 C25 C28 C31 C33 C34 C35 C36 C37 C38 C39 C40 C41 C42 C44 C48 C57

Si.92S.o 3

Si.57Aln 5Br.osK.osS.osFe.o 3 Si.49AI.26Fe.osMg.o 5 K.o3

Si.54AI.26K.osNa.osS.os Fe 03 Si.66S.24Ca.o6 Si.58Br. 16S ogNa.o9K.o4Fe.oa Si.4aS.2,,Br.21Ca.o3 S.s3Si.47 Fe.61Si.12Na42S.o6AI.o 5 S.,,3Ca.,~2Si.oTNa.o 5 Na.,~4S.33Ca.x6Mgo3 Cr.goSi.1 o S.61Ca.32Si.03A1.o 3 Ca.sTS.osSi.o 5 Na.6oS 4o S.,,TNa.4sMg.osAI.o3 Na.64S.aoMg.o 5 S.91Mg.o 9

Na.szCl.a6S.osMg.o5 Nal.oo S.46Mg. 3aNa. 1iA1.o3 K Loo

Particle diameter (#m)

By count

By volume

Mean

SD

Geometric

21.04 4.73 7.19 14.55 3.43 8.73 3.26 4.61 6.05 11.63 2.79 5.78 4.07 2.82 3.33 38.61 21.76 257.34 8.93 26.55 2.37 2.31

13.78 20.49 11.41 38.05 1.18 3.14 0.37 0.34 2.13 4.25 0.75 9.22 0.63 5.12 0.20 1.76 1.19 5.31 4.42 2.33 0.06 0,10

0.59 1.34 1.12 1.05 0.54 0.68 0.43 0.39 0.51 0.53 0.43 0.45 0.37 0.45 0.23 0.24 0.26 0.19 0.44 0.22 0.21 0.25

0.60 1.02 0.68 0.95 0.46 0.44 0.28 0.33 0.52 0.52 0.47 0.77 0.41 0.74 0.27 0.29 0.26 0.21 0.52 0.32 0.21 0.26

0.40 1.00 0.89 0.71 0.40 0.53 0.34 0.29 0.35 0.37 0.29 0.24 0.26 0.25 0.17 0.18 0.20 0.15 0.28 0.17 0.16 0.19

* Concentration units are (by count) number of particles x 104 per m 3 of air and (by volume) pm 3 of a particle type per m 3 of air.

[ 6 C

C)

E

Total Fine Particles: D a i l y Cone. by VoI,Jme ( / , ' × I O ' / I T Q )

20] 15

10

it c41MoiI Conc.

(part.

x l O ' / m s)

40

\_

e®

O O o

120 100

0Tx

8O

tO

E ~5

Total Fine P a r t i c l e s : D o i l y C o n c e n t r a t i o n by Count

2

1.0["

C41:

/*\

Fine F r a c t i o n

/

05[

8o

~*

,

Mean

Average

Diameter

(Hm)

>

<

60

i-

v

®

o o[

...,t~,'-.-....-~,,~,_. ,

,

5/13

5115

,

5•23

.

,

,

,

5•28

612

817

S a m p l e Date 0 o

0,

~IE ?~

> ~1 a)

1 0 10

,

,

,

.

.

,

,

•

.

FineParticles

Total Average

Mean

Diameter

(Hm)

5"

oo

. 5/13

.

. 5/18

. 5/23

. 5128

Sample

6/2

Fig. 2. Cluster 41, plots of time vs (a) concentration by count and (b) mean diameter.

6/7

Date

Fig. 1. Total fine-fraction particles, plots of time vs (a) concentration by volume, (b) concentration by count and (c) mean diameter.

it represents less than 5% of the total volume. A sense of the size differences among clusters is given in Tables 1 and 2 by the mean diameter, standard deviation about the mean diameter, and the geometric mean diameter. The compositions of centroids are expressed in atomic fractions. For some particle types, the centroid compositions facilitate reasonable assumptions about the chemical species in the particles; for instance, the

Fine-fraction particles of Arctic aerosol

1751

Table 2a. Minor clusters of interest from fine-fraction samples Integrated concentration* Cluster C19 C26 C32 C30 C46 C47 C50 C53 C52 C56 C59

Centroid composition (elements />0.03)

Particle diameter (#m)

By count

By volume

Mean

SD

Geometric

0.77 0.23 1.04 0.70 0.33 0.53 1.79 0.32 0.83 0.84 1.01

2.16 0.02 0.10 0.40 0.08 0.33 0.04 0.08 0.74 0.03 0.01

1.20 0.42 0.36 0.61 0.48 0.45 0.27 0.43 0.72 0.17 0.16

0.87 0.21 0.29 0.57 0.38 0.74 0.16 0.45 0.75 0.13 0.22

0.89 0.38 0.41 0.28 0.35 0.24 0.22 0.33 0.52 0.14 0.I1

Fe.zsAI.asMg. t 7Si 1oS.o7 Fe.z7Si.3aS 3 s

Fe.42S.42Si.16 Ti.s2Si.loS.o6 Na.,tlCa.1,tCI.2sS.19 Mg.32Na.,,tCa.xoS.31 S.,,sK.3oNa25 Pbt.oo As.36Pb.23S.22Cl.loP.o4Na.o4 Asl.oo Nil.oo

Table 2b. Fine-fraction metal-bearing particles not assigned to any cluster (These particles have compositions that lie further from any cluster centroid than is allowed by s4. They may represent composite particles or distinct particle types with few analysed members.)

Groups of unassigned particles (A) As-bearing particles (B) Pb-bearing particles (C) Ni-bearing particles (D) Cr-bearing particles (E) Cu-bearing particles (F) Zn-bearing particles

Integrated concentration (by count)* 2.64 0.80 1.45 2.62 2.45 0.78

* Concentration units are the same as in Table 1.

Si-bearing types are undoubtedly silicates. For other particle types, the species are less obvious. Atomfraction ratios of key elements in centroid compositions of many types can suggest the stoichiometry of chemical species involved. Several particle types are probably mixtures of multiple chemical species and therefore may have a considerable range of compositions. The nonhierarchical clustering methods used can artificially divide a continuous series of mixtures into two or more dusters, but such instances are easy to recognize. Another factor in considering centroid compositions is that any element that comprises no more than about 0.05 of the total by atomic fractions is only contained in some particles of the duster, not all. Each cluster consists of a population of points, each representing a particle composition, arrayed at varying distances around a centroid. Because an angular clustering metric has been used, each centroid is effectively a line emanating from the origin in positive multidimensional space. The dispersion of a cluster can be described by the distribution of angular distances to the centroid for all the points in the cluster.

One simple way to consider cluster dispersion is to examine the average angular distance between cluster points and the centroid. Clusters that contain particles with little chemical variation have small average distances to the centroid; examples in this study are C3 and C41. For C3, the range of average distances to the centroid for the 30 samples is 3.2-5.8 ° with a mean average distance of 4.4+0.8 °. For C41, the range is 3.9-4.9 ° with a mean of 4.4 + 0.3°. Clusters consisting of particles with substantial compositional variation have much larger average distances to the centroid. An example is C39 with a range of average distances of 6.2-9.9 ° and a mean average distance of 8.5 __.0.7 °. For all three examples, the dispersion is considerably larger than that which would be due to analytical error in the chemical composition. In the blank, significant numbers of particles do not fall into any dusters except for C31, an Fe-rich cluster. Calculated as if 20 m 3 of air went through the blank, the blank concentration of C31 is equivalent to 0.1 x 104 particles m-3. The largest concentration of C31 in the samples is about 0.5 x 104 m - 3, too close to the blank level to ignore contributions from the blank.

1752

J.R. ANDERSON et al.

Specific particle types In the following section we describe the particle types listed in Tables 1 and 2 grouped according to distinguishing compositional features. S-only: C41. The centroid composition for C41 particles indicates that they consist of S-bearing species containing elements undetected by EDS methods (e.g. organic sulfates and sulfides). Most daily mean diameters for C41 particles are ~0.2 #m and vary less than those of most other particle types. Silicate types. The three most abundant silicate particle types are C3, C6 and C7 (Fig. 3). The concentration time-trends for the three are similar; correlation coefficients between the different possible pairs are 0.80 to 0.86 (see Table 3). Daily variations in mean diameter for C3 and C7 (Fig. 4) are strikingly different than for C41. For C7, mean diameters range from 0.2 to 2.0 #m. Mean diameters for C3 vary by over a factor of 4, with most values around 0.6 #m. Some C3 particles have minor admixed S. Such S probably results from thin, irregular sulfate coatings (such coatings have been observed by manual observation with the electron microprobe) or from aggregation of small sulfate particles onto larger particles. Several clusters seem to represent silicates plus either Br (C5 and C13, Fig. 5) or substantial S (C10 and C28, Fig. 6). C25 (Fig. 6) contains both Br and S. In general, these correspond to the silicate particle types (C3, C6, C7) with added sulfate and Br. All significant cluster types with Br are Si-bearing. High-Na types. Particles composed of Na-bearing S-species with minor Mg or A1 are represented by C38,

C39 and C40; the cluster centroids have atomic Na/S ratios of 1.50, 0.96 and 2.13, respectively (if Mg in C39 and C40 is accounted for by subtracting out MgSO4, the adjusted Na/S ratios are 1.07 and 2.56, respect20~ 15~)

10-

i

0.5-

c5 >~ <

C7: Mean Ave. Diameter

00-

C3:

(/_zm)

Mean Ave. Diameter

(Hm)

lo

c 05 o.0 5/13

511e 5/23

5/2e

Sample

6/2

617

Date

Fig. 4. Plots of time vs mean diameter for (a) cluster 7 and (b) cluster 3.

E ,oj

g-.

b

×

C5:

Si s~AI ,6Br ask o~Sos/e o~

0.5

\

(3.

c

1o

~

05

.£

C13:

Si s, Br ,.S ogNa ogK o.Fe o~

...,,,/~.Y".

E 0.0 C

20

C3:

r

O

Si,So3

-

5/13

.

.

.

.

5118 5/23

O

5128

Sample

6/2

--

,

~

617

Date

Fig. 5. Plots of time vs concentration for (a) cluster 5 and (b) cluster 13. 1.0

~

0

1.o

111 Q-

1.01

,0

0.5

~•

0.0

C

/ 1.51 ~.o

C6:

t c10 s s.o t

[

Si 4,AI.26F'eoeMg.osK.os

X

0.0 , .

0O

'

'

C7:

"

' '

''

'

Si.s,AI.zsK.osNa.o~Sosfe.o~

.

.

.

.

Si 48S.2~r 2,Ca.o~

0.5 0.0

} 0

0.5

.

C25:

~.

v

.

C28:

S 53Si ,,

0

0.0

5/13

5/le

5123

5/2a

Sample

e/2

elf

Date

Fig. 3. Plots of time vs concentration by count for (a) cluster 3, (b) cluster 6 and (c) cluster 7.

5/~3

5~e

5~23 512e at2 Sample Date

e/7

Fig. 6. Plots of time vs concentration for (a) cluster 10, (b) cluster 25 and (c) cluster 28.

Fine-fraction particles of Arctic aerosol ively). Although C38 is intermediate to the others in composition, C39 and C40 are by far the more abundant clusters. Time-trends of concentration for the three clusters are roughly similar (Fig. 7). Two additional Na-rich clusters are C44, with Na as the only detectable element, and C42, predominantly NaC1. These are compared to the summed concentrations of C38-C40 in Fig. 8, and all have quite different time-trends. One unplotted cluster of low abundance,

E

]Z[[L

0

0.0-

5.0

:

.

.

.

C46 (Table 2), appears to be a mixture ofNaC1, CaSO¢ and Na + S species; only C46 has NaCI and significant Ca together. High- Ca types. Major Ca-bearing clusters are C33 (Ca/S=0.98), C36 (Ca/S=0.52) and C34 ([0.5Na + C a ] / S = 1.15, 0 . 5 N a / C a = 1.37) (Fig. 9). C37 is mostly Ca with only minor S and therefore probably has an

undetectable anion like carbonate. C33, C34 and C36 share common concentration peaks on 13 and 23 May, but also have differences.

High-Mg and high-K types. One Mg-rich and two K-rich clusters are shown in Fig. 10. C48 has the proper stoichiometry for a mixture of MgSO4 and

,.o.J

4.0-

w"

1753

2.0-

C33:

S ,~Ca ,2Si oTNa o~

[

C34:

Na .S.~Ca.,6Mg os

T-

X

5,o-

C39:

S.47N o,sMg.osAI.os 0.0

1.0 C .0 ,,..,

°t ~-

4.0 2.0-

X

0.5

Q-

o.0

0.oO

40

1.0j

5/13

5123

5/15

5128

($/2

~ 0

e/7

0

C36:

'

1.o

t

5/13

! X

'

"' "

C37:

5/18

'

'

Co,,S.o, Si.o,

5•23

5128

512

6/7

Sample Date

.o,,oo

Fig. 9. Plots of time vs concentration for (a) cluster 33, (b) cluster 34, (c) cluster 36 and (d)

2.0 0.0

'

~.~

Fig. 7. Plots of time vs concentration for (a) cluster 40, (b) cluster 39 and (c) cluster 38.

c.:

T

0.o

Sample Date

~o[ ~

S.6,Ca .3~Si o3AI.o3

cluster 37. ,

-,

,

,

'c 4.0 2.0

C42:

g 0.0 £ 14.0

NO ~,2CIs,S osMg os

~"

C38, C39, & C40

tQ)

1,0

~-

05t

C48:

X

0.0

/.

S ,~Mg ~aNo . A I o3

e-o\

\

O 12.0 t-

8

10.O

i1°t

8.0 6.0

!

4.0

o-ti °'°1

' "i~'i~

i '°l

2.0 ~ 0.0

C50:

S.,,K ,oNo.2s

i "i!]'"

I

~

~

c57: K,00

~

5/13 5~e

5/23 5~2e a~2

517

Sample Date

o.o, 5/13

Fig. 8. Plots of time vs concentration for (a) duster 44, (b) cluster 42 and (c) the sum of clusters 38, 39 and 40. Note that each vertical scale is different.

5/18

5/23

5/28

6/2

5/7

Sample Date

Fig. 10. Plots of time vs concentration for (a) cluster 48, (b) cluster 50 and (c) cluster 57.

1754

J.R. ANDERSONet aL

Na2SO 4. C50 is a mixture of K + S and Na + S species with a value of 1.3 for ( N a + K)/S for the centroid composition. C57 has only K as a detectable element and is similar to C44 with regard to its temporal variation. Metal-bearing types. The remaining clusters in Tables 1 and 2 have particles with As, Pb or one of several transition metals (these are collectively referred to as "metal-bearing types" to simplify discussion). The concentrations of these types are relatively low but they are easy to identify and temporally track because of their unique compositions. The Fe-bearing clusters, C19, C26, C32 and C31, all contain Si; all but one contain major S. C19, C26 and C32 have similar time-trends and have been summed together to compare with C31 (Fig. I 1). Ni-bearing particles are of interest because the major sources are anthropogenic. The two categories defined here, (1) C59 and (2) all unassigned Ni-bearing particles from CO, have similar concentration patterns (Fig. 12). Most of these particles are in the first two samples, 13 and 14 May. Because of their uni-

1.5

g

1.0

~

!

c,...6,

•

o.

I

L E • 0 X

F'e zeAl 38Mg 17~J I0~ O? F e z , S i 5.S 5s

/

Fe ,2S,zSi

..

0.SJ

Q. 10

°1

.0

O C0

C31:

Fe .,Si.,2Na

,zS o~AI os

I

0,0

5/13

5110

(D

5/23

5128

Sample

612

6/7

Date

Fig. 1I. Plots of time vs concentration for (a) the sum of clusters 19, 26 and 32 and (b) cluster 31. g-, 1.o

X

v C

C59:

Ni,~o

0.5

o e ¢ _-: : _- : _=.- : : _- _- : e e e e.4-~.4~o-e-e , , , .,

o,o

~

1.51

~n

05

~

0.0 1.0

~

05

!

C35: Cr~Si,o

Unassigned

5/13

8/18

Cr-bearing

8/23

8128

Sample

Particles

612

6/7

Date

Fig. 13. Plots of time vs concentration for (a) cluster 35 and (b) all unassigned Cr-bearing particles. formly small sizes, Ni-bearing particles contribute little to total aerosol volume. Cr is another important element because of the paucity of natural sources. C35 particles (assumed to be mostly Cr203) occur in measurable concentration in several samples (Fig. 13). A smaller number of Crbearing particles are not assigned to any cluster and have been summed for comparison to C35. The only concentration peak that the two categories have is on 19 May. Three clusters have particles containing Pb, As or Pb + As: C52, C53 and C56 (Fig. 14). The only detectable element in C53 particles is Pb, perhaps as an oxide or carbonate. C53 has one small concentration peak in the 5 June sample. The Pb-bearing particles that do not fall in C52 or C53 have a concentration trend similar to that of the Ni-bearing particles in Fig. 12. C52 has a single peak on 26 May, and C56 has low concentrations throughout the sampling period. The unassigned As-bearing particles from CO vary in concentration in a manner similar to C41 (Fig. 2). The three clusters in Fig. 14 have different mean particle diameters, from 0.17 #In for C56 to 0.72 #m for C53. Cu- and Zn-bearing particles are shown in Fig. 15. Both have low concentrations through 1 June, after which the concentration of Cu-bearing particles tends to be higher. The two types each have a wide range of compositions, too diverse to form distinct clusters. Size distributions of selected clusters

1.5

0.0

" ~ e e-e-e e'4~) • ; : ~ -- * • e ' ~ o • • ~ : ~ : -- : = = I "

5/13

s/it

6/a3 6/=a et= Sample Date

at7

Fig. 12. Plots of time vs concentration for (a) cluster 59 and (b) all unassigned Ni-bearing particles (those in duster 0).

Three daily size distributions of each of two clusters, C41 and C3, and one daily size distribution for C7 are discussed below as examples of the large base of morphologic data produced with individual particle analysis. The clusters have been selected because they have sufficient numbers of analysed particles to examine size distributions for single sampling periods and, for C41 and C3, their daily mean diameters are small compared to the cut-size. Variations in the daily size distributions of each cluster's particles may provide evidence about their transport, removal or generation.

Fine-fraction particles of Arctic aerosol

1755

tO

240'

C41:

May

13

210 180

0.0

150

1"° I

120

C56: As,~

90

0.5]%

,•,

60 X

30

1.0

t

.2

C52: As ~Pb 2~S22Cl ,oP o,Na.o,

o.5

(L ,~

8

'201. O'

.

C41:

May

C41:

June 4

,

,

•

•

28

90

0o

E

(9 O tO 0

1.0

J3

°'5" L

30

E

C53: Pb,.oo

Z

'

: : : c : : c = : : : • e ~ e • • e'a'e~ e/e~ e'*'e~-*

0.0.

;--::==-

3

•

1.0 0"5"t Unassigned

Pb-bearlng

0 01 5113

0.0

Particles

• 5/18

8123

5/28

Sample

6/2

6/7

o.s Average

1.0 ~.5 Diameter

2.0 2.s (microns)

Fig. 16. Size distributions of cluster 41 particles for 24-h sampfing periods beginning (a) 13 May, (b) 28 May and (c) 4 June•

Date

Fig. 14. Plots of time vs concentration for (a) all unassigned As-bearing particles, (b) cluster 56, (c) cluster 52, (d) cluster 53 and (e) all unassigned Pb-bearing particles.

12

6

9) e o E 0

1.o

x

0.8

All C u - b e a r i n g

Particles

.Q E -I z

0.0 e'e'el • • e'e'e e're'~ e'4"Q• • • v

1.0 All Z n - b e o r i n g

.0

n

Particles

e|I

C3: June I

12 !

6I A[ \I

C3:

oli " 0.5 o.o

1.o

June 8

o.6

E o ¢o O

o.o

. 5~3

. • -- -".~ = * ' *." - , " ~ . * ' *.~ ~ o~s 5~23 s/20 ~2 Sample Date

e;z

Fig. 15. Plots of time vs concentration for (a) all Cu-bearing particles and (b) all Zn-bearing particles. Both particle type are in cluster O. The small C41 particle sizes allow for long-term suspension in the atmosphere. For 13 May, a period of high C41 concentration, most C41 particles have average diameters of 0.24 Fm or smaller (Fig. 16). For 28 May, the concentration was lower but the size distribution is similar to that for 13 May. A small second peak occurs at 0.4/an for both 13 and 28 May. The CA1 concentration on 4 June was similar to that for 28 May, but the size distribution differs; more particles have average diameters of 0.16/tm than of 0.08/Jm and no second peak occurs.

Average

,

1.s

Diameter

2.o

2.5

(microns)

Fig. 17. Size distributions of cluster 3 particles for 24-h sampling periods beginning (a) 21 May, (b) 1 June and (c) 8 June.

m o

C7: May 22

m a.

•

o

o

C

Z

0.0

0.0

1.0

1.5

2.0

2.5

Average Diameter (microns)

Fig. 18. Size distribution of cluster 7 particles for 22 May.

J.R. ANDERSONet al.

1756

Size distributions for the silicate cluster C3 contrast with those for C41 (Fig. 17). The size range with the greatest number of particles is 0.16 to 0.24/~m for the 3 days shown. Each of the periods has a second peak at 0.32 to 0.40#m, but for the larger sizes whatever structure might be present is lost in noise. For 8 June, no particles larger than 1.2/tm were found, although for the other periods many particles are larger than 1.2/~m. The C3 concentration for 8 June was about twice that for either 21 May or l June. One of the coarsest clusters is C7, another silicate type. It also has a relatively large standard deviation (Table 1) for the average diameter. These observations are reflected in the size distribution for 22 May (Fig. 18), which for this small population is relatively fiat over the range of 0.8 to 1.2/Lm. A significant fraction of the particles are larger than 1.2/~m; a high percentage of these larger particles should have been caught on the coarse-fraction filter.

rotation. Table 4 lists the 11 PCs with eigenvalues after rotation of at least 1.0. Of the 22 clusters, 18 have coefficients greater than 0.6 in any PC. Also, C34 has a coefficient of 0.77 in a PC, not shown, with a small eigenvalue. The other three clusters, C25, C33 and C36, each have coefficients between 0.34 and 0.48 in different combinations of three PCs involving PC1, PC2, PC4 and PC5. C33 and C36 both contain C a S O , , while C25 is probably SiO 2 with substantial S and Br. The greatest variance is accounted for by PC1; the dominant clusters are all silicates, C3, C6 and C7. Clusters with high coefficients in PC2 are C5 and C13, both silicates with Br, and C31, an Fe-rich particle type. PC3 primarily consists of the three N a + S clusters, C38, C39 and C40. Two clusters with different proportions o f S to Si, C10 and C28, dominate PC4. All of the other PCs each have only one cluster with a coefficient as large as 0.6.

Correlation and principal component analysis of major clusters

Measurements of SO]- and SO 2

The relationships among the major clusters was explored by calculating the matrix of correlation coefficients for concentration vs time of the 22 clusters in Table 1; this matrix was then used for principal component analysis. Each correlation factor is a measure of how similar the concentration trend over time of one cluster is to that of another. A condensed version of the correlation matrix is shown in Table 3. All of the correlation coefficients with absolute values greater than 0.6 are positive. Of the 22 clusters in Table 1, 16 clusters have a high positive correlation with at least one other cluster. The most significant negative correlation coefficients are about - 0.40. All of the negative coefficients ~< - 0.30 involve either C35 (with C5, C10 and C28) or C41 (with C3, C6, C7, C13, C31, C33 and C37). Principal components (PCs) have been calculated from the correlation matrix and subjected to Varimax

The aerosol samples were collected immediately after an "episode" of polluted air from northern Eurasia passed over Spitsbergen, as detected by S O ,z and SO 2 measurements at Ny ,~lesund (unpublished N I L U data). The episode reached a maximum about 5 or 6 May, then gradually decreased in intensity through the next week. The high total particle and C41 concentrations on 13 May mark the final day of the episode. The increases in total particle and C41 particle concentrations at the end of our sampling period did not mark the beginning of another major episode because even though a modest rise in S O l - occurred on I1 and 12 June, SO 2 did not increase above the typical background level. DISCUSSION The samples collected after 13 May represent the aerosol from a normal period of late spring when no

Table 3. Correlation coefficients between concentration-time trends of the major clusters. Only those coefficients with absolute values greater or equal to 0.6 are listed C3 C3 C5 C6 C7 CIO CI 3 C25 C28 C31 C33 C34 C36 C38 C39 C40 C48

C5

1

C6

C7

0.80

0.85

C10

1 0.80 0.85

1 0.86

C13

C25

C28

0.64 0.90

0.75

0.75 0 . 6 2 0.76 . . 0.60 0.71 0 . 7 3 0.75 . . . . . 0.75 . . 0.63 1 . . . 1 . . ....... 1

0.86 1

0.64 0.75

0.90

0.75 0.62

0.76

.

.

1 0.66 0.60 0.60

0.71 0.73 0.65

.

.

0.69 0.75 0.75 0.60 .

C33

-

0.66 0.69 ~ 1 0.63

1

C3]

.

.

. . . . . . . . . . . . . . . .

.

. ....... 0.62

C34

C36

C38

C39

C40

. . . . . . . . . . 0.60 0.65 0.60 . . . . . . . . . . . -. . . . . . . . . . 0.67 ....... 1 0.73 . . . . . . . 0.73 1 ....... 1 0.87 0.84 0.87 1 0.75 -0.84 0.75 1 . . . . . . .

C48

0.62 -.... 1

Fine-fraction particles of Arctic aerosol

1757

Table 4. Coefficientsof major clusters in the 11 principal components for which the cigenvaluvsare greater or equal to 1.0. Coefficientswith absolute values greater than 0.6 are underlined PCI C3 C5 C6 C7 C10 C13 C25 C28 C31 C33 C34 C35 C36 C37 C38 C39 C40 C41 C42 C44 C48 C57 Eigenvalue

PC2

PC3

PC4

Principal components PC5 PC6 PC7

PC8

PC9

P C 1 0 PC11

0.751 0.475 -0.094 0.272 0.164 -0.007 -0.017 -0.018 0.028 -0.127 0.111 0.129 0.957 -0.087 0.058 -0.059 0.016 0.051 -0.122 -0.099 -0.035 -0.037 0.884 0.164 -0.057 0.159 0.023 0.205 0.032 -0.084 -0.012 -0.169 0.148 0.831 0.338 -0.041 0.146 0.248 0.022 0.059 0.001 0.134 -0.062 0.009 0.387 0.064 -0.010 0.677 0.256 -0.229 0.256 -0.138 -0.122 0.144 0.050 0.241 0.926 -0.008 0.089 0.008 -0.027 0.012 -0.047 0.155 -0.114 0.034 0.477 0.446 0.060 0.473 0.263 -0.002 0.157 -0.027 -0.025 0.134 -0.011 0.166 0.104 -0.023 0.934 0.083 -0.022 0.072 -0.172 -0.0tl 0.094 -0.123 0.473 0.709 -0.074 -0.039 0.133 0.070 0.007 -0.119 -0.083 -0.144 0.121 0.441 0.363 0.195 0.113 0.477 0.211 0.034 -0.003 0.184 -0.187 0.034 0.392 0.171 0.122 0.214 0.313 0.178 0.014 -0.113 -0.090 -0.048 0.046 -0.072 -0.181 0.119 -0.203 0.007 -0.030 -0.029 0.937 0.090 -0.114 0.041 0.421 -0.093 0.072 0.459 0.345 0.224 -0.150 -0.082 -0.026 0.057 -0.097 0.147 0.033 0.046 -0.108 0.083 0.182 0.211 0.047 0.149 -0.148 0.912 -0.009 -0.071 0.947 -0.093 0.030 0.029 -0.038 0.068 0.212 0.023 0.007 -0.141 -0.089 0.912 0.115 0.104 -0.104 -0.095 -0.008 0.008 0.232 -0.073 0.049 0.027 0.900 -0.021 -0.069 -0.064 -0.103 0.091 0.122 -0.111 0.111 -0.244 -0.221 0.141 0.193 0.049 -0.125 0.124 -0.157 -0.133 0.850 -0.182 0.136 0.010 - 0.107 - 0.071 0.108 0.950 - 0.030 - 0.027 - 0.026 - 0.090 0.164 0.062 0.012 0.306 -0.052 0.018 -0.028 -0.060 0.096 0.923 -0.103 0.144 0.234 -0.033 0.031 0.204 0.876 0.109 0.263 0.018 0.007 0.068 0.099 0.040 0.065 -0.209 0.149 0.214 -0.036 0.906 -0.034 -0.063 0.097 0.212 3.40

3.10

2.80

2.10

1.50

large air masses of polluted air with high concentrations of anthropogenic SO 2- and SO 2 were moving into the area. However, several small pulses of anthropogenic, metal-bearing particles were observed, along with silicate particles of probable crustal origin; these minor incursions of pollutants might be described as "mini-episodes". The results also show that several S-bearing species and a variety of salts of probable marine origin were present in the aerosol, but not necessarily in expected forms. Most particles fall into well-defined clusters, indicating little tendency for particle aggregation in the size range of 0.1-2.0 #m. However, reaction, deposition of coatings and other modifications of particles were significant.

Speciation and morphology of S-bearing particle components S is the dominant element in the fine-fraction partitles, being present in 17 of the 22 most abundant clusters. Given the NILU measurements of SO~-, it is assumed much of the S is present as sulfate. In some particle types, such as C33 (Ca + S) and C40 (Na + S), the stoichiometry suggests that the particles are composed entirely of simple sulfate compounds (neglecting possible carbonaceous or organic components that could be present). In types such as CI0 (probably SiO 2 and CaSO4), manual SEM inspection indicates that the sulfate occurs as a coating on non-sulfate cores. However, the position of the S-species on many other types remains undetermined. The speciation of S in some particle types also remains in question.

1.20

1.10

1.00

1.00

1.00

1.00

The high concentrations of C39 and C40 relative to C38, intermediate in composition to C39 and C40, suggests that two separate Na + S species are present, with respective Na/S values of about 1.0 and 2.0. If C38 particles are combinations of C39 and C40 particles, the process responsible for forming such combinations was of minor importance. The Na/S value for C40 strongly suggests NazSO4, but the value for C39, 1.0, is compatible with several possible species (e.g. sodium bisulfate, sodium methyl sulfate and sodium methane sulfonate). A number of studies have documented the presence of dimethyl sulfide (DMS) in the marine troposphere (e.g. Barnard et al., 1982; Andreae and Raemdonck, 1983) and its oxidation to methane sulfonic acid (MSA) (e.g. Grosjean and Lewis, 1982; Saltzman et al., 1983; Savoie and Prospero, 1989). Reaction of MSA, a relatively strong acid, with NaC! could result in sodium methane sulfonate; LMMA analyses of marine aerosol particles have been interpreted by Kolaitis et al. (1989) to show sodium and ammonium salts of MSA. MSA in the Arctic troposphere is reported by Li and Winchester (1989). The limitations of EDS prohibit anything more than speculative assignments of species in the present study, but sodium methane sulfonate is perhaps more plausible for C39 than the other species with compatible stoichiometry. The coincidence of the C39 concentration peak on 2 12 June with a rise in SO4-, but not SOz for 11 and 12 June may also have a bearing on the origin of C39 particles. If C39 particles are a salt of MSA, then either an increase in SO2 or sulfate particles should have

1758

J.R. ANDERSONet al.

occurred; an increase in the latter is indicated by total SO,z- and C41. When DMS is oxidized by reaction with OH radicals, both MSA and SO 2 are produced; the MSA may stably persist while the SO2 is further oxidized to sulfate (Savoie and Prospero, 1989). Several particle types have cation/S ratios that deviate from those expected for simple sulfates. These have either (1) S present as a species other than simple sulfate; or (2) another cation, undetected by EDS, present alone or in a mixture. For some types a likely, but undetectable cation is ammonium. The S-dominant particles of C41 could be ammonium sulfate, ammonium methane sulfonate or other ammoniumbearing species. Particle types compatible with a marine origin A number of the clusters have S- and Cl-bearing particles that are interpreted to be primarily of marine origin. In most of these clusters the S- and Cl-species are present as nearly pure end members or binary mixtures; this implies an undetermined process of separation that allowed significant fractionation and selective reaction to occur. Although NaC1 should be the most abundant species in an unaltered marine aerosol, the concentration of NaC1 in the fine-fraction (primarily as C42) is low relative to other Na-rich species. C42 concentrations vary sharply from day to day but show no obvious correlation with weather conditions. NaC1 concentrations tend to be highest when those ofC41 are lowest; a similar inverse relationship exists between C42 and the three Na + S clusters, C38, C39 and C40 (Fig. 8). Likely sources of the Na + S particles are multiple reactions involving the oxidation of anthropogenic and biogenic S-bearing species to form strong acids, followed by subsequent reactions between the acids and NaCl in solid or liquid aerosol particles. Such reactions would result in substantial production and release of HCI into the troposphere. The displacement of C1 in sea salt by SO 2- and NO ] - in both natural and experimental systems has been considered in a number of studies (e.g. Martens et al., 1973; Meinert and Winchester, 1977; Hitchcock et al., 1980; Clegg and Brimblecombe, 1985; Pacyna et al., 1985; Brimblecombe and Clegg, 1988) and used to explain the observed depletion of Cl relative to Na in the remote marine aerosol (Erickson, 1960). Because the concentrations of Na + S clusters are high even when the concentrations of clusters of clearly anthropogenic and crustal origins are low, a non-marine source of Na seems to be ruled out. Therefore the relative Cl depletion was not due to an influx of non-chloride Na. The sudden changes in trend and short duration of concentration peaks for C42 suggests that the reactions involving NaC1 occurred relatively close to Ny ~lesund (i.e. within a distance equal to that traveled by transported boundary-layer particles in a day or two). The stoichiometry ofC33 suggests CaSO, with only minor Na-bearing species. Although much of the

CaSO, in these samples is probably of marine origin, some may be non-marine. If C33 particles are marine in origin, the process by which CaSO, was separated from other sea-salt components was very efficient. C36 has an excess of S relative to CaSO 4 and therefore either has a different anion, such as methane sulfonate or an undetected cation; the stoichiometry is compatible with calcium methane sulfonate. The extent to which the marine aerosol has been modified is emphasized by the combined volume concentrations of Ca + S species; their integrated value over the sampling period exceeds that of particles with NaCl. The comparative volume concentrations of all of the marine aerosol clusters in Table 1 further indicate that fine fraction of the marine aerosol was strongly fractionated, probably mechanically; unpublished data from the coarse fraction also show fractionation of the marine aerosol. A mechanical fractionation process would require separation of different species into particle types with different size distributions; these requirements are observed in the data. For example, mean diameters range from 0.53 pm for C33 to 0.21 pm for C48. A combination of mechanical fractionation and the inferred reactions involving NaC1 would result in an aerosol particle population that bears little resemblance to sea salt. Particles with undetected anions Three clusters with Na, K and Ca (C44, C57 and C37, respectively) and no substantial amounts of detectable anions may be nitrate or carbonate compounds; other possibilities include organic species. C44 and C57 had concentrations that were high on 13 May and then declined with the declining pollution episode, but otherwise there is little correlation between each of these three or with any other cluster. In the calculated PCs, C44, C57 and C37 each has a coefficient greater than 0.9 in a separate PC, and none of these PCs have any significant contributions by other clusters. C44 and C57 have small mean diameters (0.21 and 0.25 #m, respectively) and narrow distributions, consistent with distant transport. In contrast, C37 particles are coarser (0.45-/~m mean diameter) with a much broader distribution. Anthropoffenic and crustal particle types Early pollution episode. The initial period of high concentration of C41 was clearly associated with the early episode of polluted air from northern Eurasia. The concentration trends of several other types also suggest such an association. The Ni-bearing particle types had peak values on 13 May, then rapidly declined and had later concentrations at or below the detection limit. Although relatively minor in abundance, the Pb-bearing particles other than C52 and C53 have a trend similar to the Ni-bearing particles. The silicate types C3 and C7 had their highest concentrations on 13 May and then declined sharply; however, their subsequent concentrations varied, indicating that after 13 May they probably came from Arctic

Fine-fraction particles of Arctic aerosol sources not close to emission sources of anthropogenic metal-bearing particles. Several other clusters show a high value on 13 May, followed by a sharp decline, but otherwise have divergent trends; examples are C44, C39, C50 and C57. The most like C41, with peaks at the beginning and end of the period, is the group of unassigned As-bearing particles (Fig. 14a). Metal-bearing types in "mini-episodes". None of the remaining metal-bearing types have any demonstrable relationship to the early pollution eipsode, nor do they have any significant correlations with other metalbearing types. The most abundant cluster, Cr-bearing C35, had its two highest concentration peaks on 17 May and 10 June. C52 particles (As-Pb-S) had a single concentration peak on 26 May; these particles look much like a type of smelter particle found by Anderson et al. (1988) in another study. Cu-bearing particles only appear in significant concentration after 1 June. All of these types are probably anthropogenic, but they appear to have come from separate sources. The Fe-bearing types shown in Fig. 11 have two different concentration trends, neither of which coincides with the trends of any other type. The silicaterich Fe-bearing types may be crustal dust components, whereas C31 is probably not of crustal origin. However, C31 has been found in the 1987 blanks, and similar particles were also found in blanks taken with samples at Ny Alesund in September-October 1984. Possible sources of many of the metal-bearing types are problematic. Some anthropogenic sources on or near Spitsbergen are known (Ottar et al., 1986). Possible local sources include four coal-mining towns and the administrative center at Longyearbyen, which has an international airport. In summer the traffic of fishing vessels, supply ships and tourist ships also represent potential sources of tropospheric pollution. Whether the metal-bearing particle influxes are from incursions of small masses of polluted air from northern Eurasia or are from high Arctic sources remains to be determined. Silicate types. The major silicate types, C3, C6 and C7, probably are dust particles of crustal origin, although the possibility of a non-crustal origin such as coal combustion must also be considered. Li and, Winchester (1990) analysed coarse- and fine-fraction bulk aerosol samples collected in March through April 1986 at Barrow, Alaska, They observed that both fractions contained major components that were high in Si and S, but low in A1 relative to crustal dust. These components were interpreted as products of the combustion of carbonaceous fuels, with Si volatilized during carbon reduction. In our samples, the lack of strong correlation between the silicates and S-rich species in general (including SOz and SO 2-) helps support a crustal origin for the major silicates, as do the strong correlations between AI-rich and Al-poor silicates. C3 appears to be quartz with minor sulfate coating. C6 possibly represents a group of clay minerals or clays plus chlorite. C7 could be clay or mica particles. AE(A) 26:9-N

1759

C3, C6 and C7 all share common peaks on or about 22 May, 3 and 7 June. The concentration trends indicate relatively constant proportions of the three after 15 May, suggesting a common source. Their proportions before 15 May differed from those after 15 May; therefore the source of crustal material for the early pollution episode was probably different from the later source. Further evidence is found in the variation of mean diameters for C3 and C7 (Fig. 4). Both had generally declining particle sizes as the pollution episode declined, as would be expected if they had been transported with the polluted air mass. Beginning 16 May, the particle sizes increased and then went through a series of fluctuations with no obvious correlation to fluctuations in concentration. Br-bearing silicate types. C5 and C13, Br-bearing silicate dusters without major S, have trends that have high correlations with C3 from 16 May onwards, but not before. They share the same broad concentration peaks at about 22 May, 3 and 7 June. C5 may have been compositionally similar to C6 and then had Br added. C13 may be C3 particles plus Br and minor others. Br is assumed to have reacted with silicate particles to form a species stable enough to survive through exposure to high vacuum and heating by the electron beam during analysis. It is possible that some other, more volatile Br-bearing particle types were originally present but were lost before or during analysis. The other major Br-bearing type, C25, has substantial S plus SiO2; these are, apparently, C3 particles plus Br and S. It has high correlation coefficients with C3 and C7, but not with the other Br-bearing types, C5 and C13. C25 also is similar in trend to C10 and C28, both Si plus S, after the end of the pollution episode. Br-bearing particle types had no clear association with the early pollution episode. The presence of Br in the Arctic troposphere is well documented (e.g. Berg et al., 1983; Sturges and Barrie, 1988), although tropospheric Br concentrations are considerably less in May and June than the yearly maximum that occurs in March or April. Barrie et al. (1988) postulated that the springtime depletion of 03 in the Arctic boundary layer is the result of photolytic reactions involving gaseous Br species. Oltmans et al. (1989) also observed rapid springtime destruction of 03 in the high Arctic and suggest that a concurrent process is the conversion of gaseous Br to particulate Br. To form the Br-bearing particle types, silicate particles either (1) reacted with gaseous Br species, perhaps HBr (Cicerone, 1981; Li and Winchester, 1989); or (2) reacted or aggregated with particulate Br species. Size data

C41. Analysed C41 particles associated with the pollution episode predominantly have diameters between 0.1 and 0.2 #In. A second, smaller peak at 0.4 #m defines a bimodal distribution. A similar bimodal distribution with peaks between 0.1 and 0.5 #m was

1760

J.R. ANDERSONet al.

observed for total particles measured below 2500 m by aircraft flights over and near Spitsbergen (flights C-3 (3/1/84) and C-5 (3/3/84) in fig. 5b, Pacyna and Ottar, 1988). Pacyna and Ottar concluded that the particles came from anthropogenic sources in the northern Soviet Union, about 2000km from Spitsbergen. Therefore the bimodal distribution of C41 on 13 May may be characteristic of a fine-fraction sulfate aerosol matured by long-distance transport. On 28 May, C41 particles still had a bimodal size distribution, although their concentration was less and their mean diameter slightly larger. Although the early pollution episode had long been over, long-range transport of sulfate particles from other source areas, perhaps in the high Arctic, may account for the distribution. The possibility of mixing sulfate of local marine and distant anthropogenic origin also needs to be considered. On 4 June, the size distribution for C41 particles was changed completely, so that there was no longer a bimodal distribution and the diameter peaks at a value of 0.16#m. Therefore, later in the sampling period, C41 particles were either from a different source or were modified by some process that did not act on the earlier samples. Perhaps these are sulfate particles of marine biogenic origin that formed relatively near to Spitsbergen. C3 and C7. Silicate types C3 and C7 have broad size distributions that are complicated by statistical noise inherent in small populations. The breadth of the distribution suggests that at least some of these silicate particles are from a source close to Ny ~desund. The distribution for C3 for 8 June differs from the others by the absence of particles larger than 1.3 #m. Total particles. Examination of the size data for different clusters in Tables 1 and 2 plus the mean diameter plot in Fig. 1 points out the difficulties in interpreting size distributions of total particles in aerosol samples. The total particle concentration by count is dominated by C41 particles at the beginning and end of the sampling period. However, because C41 particles have such small diameters, silicate types such as C3, C6 and C7 are dominant with regard to volume. The mean diameter of all particles varies considerably over the period, reflecting the varying mixture of particle types with a large range of mean diameters. The data for specific clusters suggests that more extensive treatment of size distributions using individual-particle methods could provide new insight into the generation, transport and deposition of aerosol particles. The size distributions discussed here indicate that the minimum particle size analysed must be 0.1/~m or smaller. The importance of attaining 0.1 #m as a minimum size is well illustrated by considering Figs 16 and 17 with the data below 0.5 #m blocked off. Statistical interrelationships of particle types Some of the clusters are strongly interrelated, as shown by the correlation coefficients and by the PC

coefficients of PC1 through PC5. Only one cluster makes a significant contribution to each of the remaining PCs and each of these clusters is significantly associated with only one PC. Presumably these latter clusters are from individual sources that are either intermittent or are geographically unique. PCI through PC5 each have one or more clusters that are largely confined to that PC and may also have one or more clusters that occur in two or more PCs. To simplify the following discussion, clusters in a PC with coefficients of 0.80 or above are considered to be members of that PC only and clusters with coefficients between 0.35 and 0.79 are considered to be nonexclusive members that are also members of other PCs. We shall ignore coefficients smaller than 0.34. PC1 has as exclusive members C6 and C7 (AIbearing silicates) and nonexclusive members C3 (SiO2), C10 (SiO 2 + S), C25 (SiO 2 + S + Br), C31 (Ferich), C33 (CaSO4), C34 (Na2SO 4 + CaSO4) and C36 ICa+S). PCI probably consists of crustal mineral particles, some of which are partially coated or reacted with S- and Br-bearing species, and accompanying CaSO4. The paucity of other particles of obvious marine origin suggests a nonsea-salt origin for the CaSO~. The Br-bearing silicates C5 and C13 are exclusively in PC2, along with nonexclusive contributions from C3, C25, C31 and C33. Therefore PC2 is similar to PC1 but has been more strongly affected by reaction or mixing with Br-bearing species. The N a + S clusters, C38, C39 and C40, are exclusive members of PC3 and are not associated with other particle types. Apparently the reactions that produced these particle types were independent of the other aerosol components. The particles probably formed in the Arctic troposphere and did not come from geographically specific sources. C28 (SiO2+S) is exclusively in PC4, with nonexclusive contributions from C10, C25 and C36. Of the major Si-bearing clusters, C28 has the lowest value of Si/S. PC4 appears to be comprised of particles similar to those of PCI that have been extensively coated or mixed with S-bearing species. PC5 has C48 (MgSO 4 +NazSO4) as an exclusive member and C33 as a nonexclusive member. This combination is not typical for a marine aerosol, although a marine origin of precursor particles that were transformed into PC5 particle types by reaction or fractionation seems likely. A PC may have only one cluster for one of several reasons. The noncorrelation of NaC1 (C42) with any other cluster may result from the independence of the processes that removed NaC1. Anthropogenic particles such as Cr-rich C35, probably had a single source area. The 11 PCs derived from only 22 cluster variables are a large number compared to PCA results of bulk aerosol samples reported in other studies. This perhaps is inherent in the use of the single-particle techniques outlined here. Many of the particle types are products of either complete or incomplete reac-

Fine-fraction particles of Arctic aerosol tion, while others are types apparently derived from distinctly separate source. Taken together, the singleparticle PCA results suggest a complex aerosol with multiple sources of particles and multiple processes that tended to change particles or fractionate the aerosol.

CONCLUSIONS The aerosol at Ny/~lesund from 13 May to 11 June 1987 was a mixture of altered and unaltered particle types from a variety of sources. Silicate types appear as relatively unaltered particles, as particles with sulfate coatings, and as particles that have reacted with Br. Most silicate particles are probably crustal in origin. Many compositional types of metal-rich particles are of probable anthropogenic origin, and most types have temporal variation patterns that are individually distinct. Only a few of the metal-rich types are associated with an episode of polluted air from northern Eurasia; other types may be from sources in the high Arctic or could be from small masses of polluted Eurasian air. Other major particle types are probably of marine origin, but extensive fractionation and reaction of the marine aerosol components is suggested. A b u n d a n t S-rich particles are of undetermined origin, probably of multiple origins, but in the early period of highest concentration were associated with the pollution episode. After the episode, a substantial fraction of the S in fine-fraction particles may have been biogenic in origin. Other than the early pollution episode, the sampling period represents normal conditions for late spring. The atomic ratios of Na to S and other cations to S in particles of several clusters indicate that not all Srich particles are simple sulfates. A possibility is that some are products of the oxidation of DMS; for instance, the Na-salt of MSA has a Na/S value similar to that of C39. EDS analysis cannot distinguish between the possible species and further work is needed. Further work is also needed on the nature and timing of reactions, the mechanism for fractionation of the marine aerosol, and the sources of some particle types. The complexity of the aerosol in this remote area during a period presumed to be relatively free of pollutants is striking. Two relatively clear findings are that (1) the Arctic aerosol at Spitsbergen has pollution products from h u m a n activity even in a normal period of spring; and (2) many of the apparent pollutant particles in the fine-fraction, S-rich species and perhaps Br-rich species, are of natural origins.

Acknowledoements--This research was supported by NSF grants ATM-9007796 and ATM-8707070. The electron microprobe was purchased with the aid of NSF grant EAR8408163. We thank T. Patterson for many helpful suggestions during the preparation of the manuscript.

1761 REFERENCES

Anderson J. R., Aggett F. J., Buseck P. R., Germani M. S. and Shattuck T. W. (1988) Chemistry of individual aerosol particles from Chandler, Arizona, an arid urban environment. Envir. Sci. Technol. 22, 811-818. Andreae M. O. and Raemdonck H. (1983) Dimethyl sulfide in the surface ocean and the marine atmosphere: a global view. Science 221, 744-747. Barrie L. A. (1986) Arctic air pollution: an overview of current knowledge. Atmospheric Environment 20, 643-663. Barrie L. A., Bottenheim J. W., Schnell R. C., Crutzen P. J. and Rasmussen R. A. (1988) Ozone destruction and photochemical reactions at polar sunrise in the lower Arctic atmosphere. Nature 334, 138-141. Barnard W. R., Andreae M. O., Watkins W. E., Bingemer H. and Georgii H.-W. (1982) The flux of dimethylsulfide from the oceans to the atmosphere. J. geophys. Res. 87, 8787-8793. Berg W. W., Sperry P. D., Rahn K. A. and Gladney E. S. (1983) Atmospheric bromine in the Arctic. J. geophys. Res. 88, 6719-6736. Bernard P. C., Van Grieken R. E. and Eisma D. (1986) Classification of estuarine particles using automated electron microprobe analysis and multivariate techniques. Envir. Sci. Technol. 20, 467-473. Brimblecombe P. and Clegg S. L. (1988) The solubility and behavior of acid gases in the marine aerosol, d. atmos. Chem. 7, 35-58. Buseck P. R., Anderson J. R., Dea J. Y., Aggett F. J., Germani M. S. and Shattuck T. W. (1986) Individual particles in atmospheric aerosols: unattended microanalysis of statistically significant populations using an automated SEM. Proc. Air Pollut. Control Ass. 86-26.1, 1-8. Cicerone R. J. (1981) Halogens in the atmosphere. Rev. Geophys. Space Phys. 19, 123-139. Clegg S. L. and Brimblecombe P. (1985) Potential degassing of hydrogen chloride from acidified sodium chloride droplets. Atmospheric Environment 19, 465-470. Erickson E. (1960) The yearly circulation of chloride and sulfur in nature: meteorological, geochemical and pedological implications. Part II. Tellus 12, 63-109. Grosjean D. and Lewis R. (1982) Atmospheric photo-oxidation of methyl sulfide. Geophys. Res. Lett. 9, 1203-1206. Hitchcock D. R., Spiller L. L. and Wilson W. E. (1980) Sulfuric acid aerosols and HC1 release in coastal atmospheres: evidence of rapid formation of sulfuric acid particulates. Atmospheric Environment 14, 165-182. Keiding K., Jensen F. P. and Heidam N. Z. (1986) Absolute modelling of urban aerosol elemental composition by factor analysis. Analytica chim. Acta 181, 79-85. Killeen T. J., Eastwood D. and Hendrick M. S. (1981) Oilmatching by using a simple vector model for fluorescence spectra. Talanta 28, 1-6. Kolaitis L. N., Bruynseels F. J. and Van Grieken, R. E. (1989) Determination of methanesulfonic acid and non-sea-salt sulfate in single marine aerosol particles. Envir. Sci. Technol. 23, 236-240. Li S.-M. and Winchester J. W. (1989) Geochemistry of organic and inorganic ions of late winter Arctic aerosols. Atmospheric Environment 23, 2387-2399. Li S.-M. and Winchester J. W. (1990) Haze and other aerosol components in late winter Arctic Alaska, 1986. J. fleophys. Res. 95, 1797-1810. Maenhaut W. and Cafmeyer J. (1987) Particle induced X-ray emission analysis and multivariate techniques: an application to the study of the sources of respirable atmospheric particles in Ghent, Belgium. J. Trace Microprobe Techn. 5, 135-158. Meanhaut W., Cornille P., Pacyna J. M. and Vitols V. (1989) Trace element composition and origin of the atmospheric aerosol in the Norwegian Arctic. Atmospheric Environment 23, 2551-2569. Markowicz A., Raeymaekers B., Van Grieken R. and Adams

1762

J.R. ANDERSON et al.

F. (1986) Analytical electron microscopy of single particles. In Physical and Chemical Characterization of Individual Airborne Particles (edited by Spurny K. R.). Ellis Horwood, Chiehester, U.K. Martens C. S., Wesolowski J. J., Harris R. C. and Kaifer R. (1973) Chlorine loss from Puerto Rican and San Francisco bay area marine aerosols. J. geophys. Res. 78, 8778-8792. Meinert D. L. and Winchester J. W. (1977) Chemical relationships in the North Atlantic marine aerosol. J. geophys. Res. 82, 1778-1781. Oltmans S. J., Schnell R. C., Sheridan P. J., Peterson R. E., Li S.-M., Winchester J. W., Tans P. P., Sturges W. T., Kahl J. D. and Barrie L. A. (1989) Seasonal surface ozone and filterable bromine relationship in the high Arctic. Atmospheric Environment 23, 2431-2441. Ottar B., Pacyna J. M. and Berg T. C. (1986) Aircraft measurements of air pollution in the Norwegian Arctic. Atmospheric Environment 20, 87-100. Pacyna J. M. and Ottar B. (1988) Vertical distribution of aerosols in the Norwegian Arctic. Atmospheric Environment 22, 2213-2222. Pacyna J. M., Vitols V. and Hanssen J. E. (1985) Chemical properties of aerosols at BP Project ground stations, Norwegian Institute for Air Research, Report OR 64-85, Lillestrom, Norway. Raeymaekers B., Van Espen P. and Adams F. (1984) The morphological characterization of particles by automated scanning electron microscopy. Mikrochim. Acta II, 437-454. Saltzman E. S., Savoie D. L., Zika R. G. and Prospero J. M.

(1983) Methane sulfonic acid in the marine atmosphere. d. geophys. Res. 88, 10987-10902. Saucy D. A., Anderson J. R. and Buseck P. R. (1987) Cluster analysis applied to atmospheric aerosol samples from the Norwegian Arctic. Atmospheric Environment 21, 1649-1657. Saucy D. A., Anderson J. R. and Buseck P. R. (1991) Aerosol particle characteristics determined by combined cluster and principal component analysis. J. geophys. Res. 96, 7407-7414. Savoie D. L. and Prospero J. M. (1989) ComparisOn of oceanic and continental sources of non-sea-salt sulfate over the Pacific ocean. Nature 339, 685-687. Shaw G. E. (1983) X-ray spectrometry of polar aerosols. Atmospheric Environment 17, 329-339. Sturges W. T. and Barrie L. A. (1988)Chlorine, bromine, and iodine in Arctic aerosols. Atmospheric Environment 22, 1179-1194.

Thurston G. D. and Spengler J. D. (1985) A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmospheric Environment 19, 9-25. Van Borm W. A. and Adams F. C. (1988) Cluster analysis of electron microprobe analysis data of individual particles for source apportionment of air particulate matter. Atmospheric Environment 22, 2297-2307. Van Borm W. A., Adams F. C. and Maenhaut W. (1989) Characterization of individual particles in the Antwerp aerosol. Atmospheric Environment 23, 1139-1151.