- Email: [email protected]
Sources and composition of aerosol from Khartoum, Sudan
Atmospheric Environment Vol. 27B, No. 1, pp. 67 76, 1993.
0957 1272/93 $6.00+0.00 © 1993 Pergamon Press Ltd
Printed in Great Britain.
SOURCES A N D COMPOSITION OF AEROSOL FROM KHARTOUM, S U D A N MOHAMED A. H. ELTAYEB,* CHRIS F. XHOFFER, PIERRE J. VAN ESPEN a n d RENt~ E. VAN GRIEKEN Department of Chemistry, University of Antwerp (UIA), B-2610 Antwerp-Wilrijk, Belgium and WILLY MAENHAUT Institute for Nuclear Sciences, University of Ghent, B-9000 Ghent, Belgium
(First received 25 June 1991 and in final form 1 Auoust 1992) Abstract--Aerosol sampling was carried out during December 1989 in Khartoum, Sudan, using Nuclepore membrane filters. Twenty-four aerosol samples were collected and analysed by X-ray fluorescence (XRF) spectrometry and particle-induced X-ray emission (PiXE). In addition, individual particle analysis was also performed on 19 samples using electron probe X-ray microanalysis (EPXMA). Good agreement between XRF and PIXE results was obtained for most of the elements. Enrichment factor calculations indicated that soil dispersion is the dominant source for most elements in the aerosol. However, certain elements showed high enrichment factors indicating the presence of anthropogenic sources. From a comparison with available literature data it appeared that the enrichment factors for the enriched elements in the Khartoum aerosol are among the lowest recorded values for urban aerosol. Absolute principal components analysis (APCA) was performed on the data and confirmed the findings from the enrichment factor calculations, i.e. a dominant soil dispersion source and an anthropogenic source for some of the elements. Because of the very limited number of important aerosol sources, the data set was reproduced by the APCA model with a reasonable degree of success. Single particle analysis also showed that most of the particles were soil dust. These particles could further be differentiated into alumino-silicates, quartz and CaCO3 particles. Some of the particles were found to originate from combustion sources. EPXMA gave clues to the process of formation for some of the particles from combustion sources.
Key word index: Aerosol, Sudan, X-ray emission analysis, single particle analysis, source apportionment.
INTRODUCTION
EXPERIMENTAL
Since the vast majority of aerosol studies have been carried out in industrialized countries, d a t a from developing countries are very limited. However, air pollution levels in developing countries could be interesting for c o m p a r i s o n purposes. F u r t h e r m o r e , because only a limited n u m b e r of industrial sources are i m p o r t a n t , aerosol studies in such countries provide a good o p p o r t u n i t y for testing e n v i r o n m e n t a l pollution control procedures a n d for receptor modelling techniques. Only o n e study so far has been published on aerosols from S u d a n (Penkett et al., 1979). Here, we report o n the c o m p o s i t i o n of aerosol samples collected at K h a r t o u m . T h e samples were analysed by energy dispersive X-ray fluorescence ( E D X R F ) spectrometry, particle-induced X-ray emission (PIXE) spectrometry a n d electron p r o b e X-ray microanalysis (EPMA).
Site The sampler was placed on the roof of a one-storey building, which houses the laboratory of the Sudan Atomic Energy Commission in the centre of Khartoum, at an elevation of about 5 m above street level. The city of Khartoum lies in the sub-Sahara region at the junction of the Blue and the White Nile rivers. The city has a few light industries: textiles, paints, car batteries, etc.
Samplin# The samples were collected on Nuclepore polycarbonate membrane filters of 0.4 #m pore size and 47 mm diameter placed in a Millipore filtration apparatus. The air was drawn through the filter by a Millipore vacuum pump, and a gas meter was used to measure the volume of the air sampled in each run. The collection time per sample was 4-11 h, and samples were taken nearly continuously from 14 to 21 December 1989. Meteorological observations indicated that, during the sampling period, the wind direction was almost always northwest and that its speed ranged between 3 and 8 knots. An overview of the sampling campaign is given in Table 1.
* On leave from the Sudan Atomic Energy Commission, National Council for Research, Khartoum, Sudan. 67
68
M . A . H . ELTAYEBet al. Table 1. Overview of the sampling campaign (December 1989); D and N indicate that the sample is classified as day or night, respectively Sample no. 1D 2D 3D 4N 5D 6D 7N 8D 9D 10 D 11 N 12 D
Date
Collection time
Sample no.
Date
Collection time
14 Dec. 14 Dec. 14 Dec. 15 Dec. 15 Dec. 15 Dec. 15-16 Dec. 16 Dec. 16 Dec. 16 Dec. 16-17 Dec. 17 Dec.
1005-1400 1405-1834 1845-0005 0012-0705 0837-1608 1635-2240 22454)613 0625-1145 1150-1545 1642-2235 2240-0643 0650-1140
13 D 14 N 15 D 16 D 17 N 18 D 19 D 20 N 21 D 22 D 23 N 24 D
17 Dec, 17-18 Dec. 18 Dec. 18 Dec. 18-19 Dec. 19 Dec. 19 Dec. 19-20 Dec. 20 Dec. 20 Dec. 20-21 Dec. 21 Dec.
1146-2115 2245-0642 0650-1455 1505-2207 22434)618 0630-1544 1550-2225 22404)624 0635-1511 1517-2113 2125-0817 0823-1422
Analytical methods
For the bulk analysis of aerosol samples both energy dispersive X-ray fluorescence analysis (EDXRF) and particle-induced X-ray emission (PIXE) were used. The EDXRF instrument and analytical procedure are described by Rojas et al. (1990) and Van Espen et a l. (1986). Concentrations of 20 elements (Mg, AI, Si, P, S, C1, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr and Pb) were determined by this technique. Details about the PIXE experimental set-up, analytical procedure, calibration and uncertainties are given elsewhere (Maenhaut et al., 1981, 1987; Maenhaut and Raemdonck, 1984: Maenhaut and Vandenhaute, 1986). A total of 27 elements were measured by PIXE (i.e. Na, Ga, As, Se, Y, Zr, Ba in addition to elements already measured by EDXRF). Single-particle analysis was performed with an automated electron probe microanalysis (EPMA) unit equipped with an energy dispersive Si(Li) detector, and secondary electron, transmission electron and backscattered electron detectors. The instrument and electron probe X-ray microanalysis procedures used are described elsewhere (Raeymaekers, 1986; Rojas et al., 1990; Bernard et al., 1986; Storms et al., 1987). Nineteen samples were thus examined. Some 300 particles were analysed for each sample. For each particle, the relative X-ray intensities for the elements detected together with the particle shape factor and diameter were acquired. Multivariate analyses
The data set with the elemental concentrations as derived from the bulk analysis was subjected to a multivariate receptor model. Our model is a modification of the A P C A model of Thurston and Spengler (1985), and was derived from the procedure described by these authors and by Keiding et al. (1986). A detailed description of it can be found in Maenhaut and Cafmeyer (1987). Cluster analysis was applied to the EPMA data set in order to classify the detected particles into groups as well as to follow the behaviour of each particle group throughout the sampling period. Following the procedure described by Bernard et al. (1986), the particles were classified by hierarchical and non-hierarchical cluster analysis on the basis of the relative characteristic X-ray intensities of the elements detected in each particle.
RESULTS A N D DISCUSSION
Bulk aerosol composition E l e m e n t a l c o n c e n t r a t i o n s . The average T S P values as derived from weighing the exposed filters were 144
Table 2. Comparison between XRF and PIXE data Element
Mg AI Si P S Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Br Rb Sr Pb
XRF + 6* (ng m -a)
PIXE_+ 6 Average (ng m -3) XRF/PIXE_+SD (n)t
602+50 990+50 4900_+40 5300_+30 10200_+80 13600_+30 80_+10 155+10 970+50 1120+ 10 1000+60 880_+20 1260-+50 1110-+10 4200_+40 3400_+10 810_+20 6 3 0 _ + 5 14-+7 16_+8 14+5 8.0-+l.4 91_+6 100_+8 5700+40 5300+10 6.1 _+7.7 8.5+3.5 6.9+1.8 4.0+1.1 109+5 100_+3 19_+1 17__+2 3.6_+0.7 5.3_+2.3 25+ 1 21 ___+3 47+3 38_+6
0.60__+0.11(22) 0.92_+0.13(24) 0.75+0.07 (24) 0.52_+0.16(23) 0.86+0.07 (24) 1.14_+0.14(23) 1.13_+0.13(24) 1.22_+0.11(24) 1.29_+0.13(24) 0.89+0.31 (18) 1.66__+0.70(21) 0.89_+0.15(23) 1.08+0.10 (24) 0.74+0.43 (24) 1.61___+0.69(19) 1.05_+0.14(22) 1.11_+0.18(24) 1.03+0.43 (12) 1.09+0.26 (20) 1.17_+0.17(20)
*6=analytical error (counting statistics) for values near the mean. tSD=standard deviation on the average ratio, (n) = number of samples used to calculate the average. + 4 5 and 4 5 + 1 2 /~g m -3 for the samples collected during the day and those collected during early morning hours, respectively. The mean elemental concentrations, as obtained by X R F and PIXE are given in Table 2. The analytical error 6, which gives an indication of the sensitivity, is the error as calculated from counting statistics and applies to a concentration value near the mean. While PIXE results show lower analytical error for the elements from Mg to Zn, X R F has a lower analytical error for the elements Sr to Pb. The last column of this table, with the average ratio (XRF/PIXE) and associated standard deviation, also provides a measure of the agreement between the results by the two techniques. G o o d agreement (ratio close to unity) is observed for most of the elements,
Sources and composition of Khartoum aerosol Exceptions are the elements near the detection limits and Mg and P which showed consistently lower concentrations in XRF. This is due to the difficulty in spectral analysis for Mg X-rays which fall at the very beginning of the fitted region and due to the spectral interference on P from Si. Comparison of the mean value in the Khartoum aerosol with available literature data (Rahn, 1976) indicated that the crustal element concentrations were almost always higher in the Khartoum aerosol, while the concentrations for the enriched elements were in most cases lower in the Khartoum aerosol. It was observed that the samples collected from about 6 a.m. to about 12 p.m. (day = group 1) exhibited higher elemental concentrations than the samples taken from about 10 p.m. to about 6 a.m. (night = group 2). Figure 1 compares the average values for the two groups. The day/night difference is a factor of 2-4 for most elements except for S which shows similar values for the two groups of samples. The higher concentrations for group 1 are most likely due to entrainment of dust particles generated by traffic during the day, and to the daytime usually being more windy than the nighttime. The fact that S does not show the same day/night variation as the lithophilic elements clearly indicates that S originates from sources other than soil dust dispersal, as will be discussed later. The fact that Br and Pb follow the same pattern as the lithophilic elements, i.e. high concentration for group 1 as compared to group 2, may again be explained by larger traffic volume during the day hours. However, the ratio of the daytime concentration to nighttime concentration for Br in the aerosol is not as high as for the other elements. The particulate Br concentration in an urban environment usually correlates with traffic volume and the fact that it is lower than expected during the day may be due to a higher volatility during the hot day hours (Sturges and Harrison, 1986). Enrichment factors and Br/Pb ratios. Enrichment factors (EFs) were calculated for each individual sample relative to the average crustal rock composition (Mason, 1966) and with AI as the reference element. The arithmetic average EF values are given in Table 3 and compared to the geometric mean enrichment factors for 29 cities (Rahn, 1976). Most of the elements show an enrichment factor close to unity indicating a soil dispersion source. The elements which are significantly enriched in Khartoum aerosol are S, C1, Zn, Br and Pb. These elements are known to be emitted from combustion sources: coal-fired power plants for S and Cl, waste incineration for Zn and automotive exhaust for Br and Pb. The high correlation coefficient of 0.94 between Br and Pb confirms the common source for these two elements. Furthermore, the observed Br/Pb ratio of 0.42 is close to the ethyl ratio of 0.38 (Harrison and Sturges, 1983). While the enrichment factors for the major crustal elements are comparable to the geometric mean of the 29 cities, the non-crustal elements are much less
69
16'
Group 1 (day) m
Group 2 (night)
)¢ 12 'E 10
II g° 4
I
I
i |
2
I L II.L
0
AI Si
K Co Fe
S
CI
il
BrAO0 TSPIIO0 Z~. tO Pb, 100
Elements
Fig. 1. Comparison of the average day and night concentrations for the various elements.
Table 3. Average enrichment factors* (relative to AI and crustal rock; Mason, 1966)and associated standard deviations in Khartoum aerosol, as compared to the geometric mean of 29 cities (Rahn, 1976) Element
This work
Mg
0.80 + 0.15
Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Rb Sr Pb
0.76 __0.04 2.6+0.6 103 __73 130+ 110 0.78 + 0.25 1.63+ 0.35 2.2 __0.2 2.0+0.5 1.31 _+0.47 1.62+0.17 1.64-+0.17 2.1 -+0.9 1.13-+0.51 27+41 160+90 0.77+0.15 1.06-+0.25 64 _+25
Geometric mean of 29 cities 2.0 0.79 2.6 490 300 1.63 2.9 1.63 15.2 6.2 3.2 2.2 10.8 149 300 1940 2.9 0.85 3800
* PIXE data were used for EF calculation for the elements Mg-Zn, while XRF data were used for Br-Pb.
enriched in Khartoum than in the city data set of Rahn (1976). Time trends. Time trends for the TSP and the crustal elements are shown in Fig. 2a, while those for the enriched elements are shown in Fig. 2b. The trends for the TSP and both types of elements are similar, with high values for day samples and low values for night samples. An exception is S which does not show
70
M.A.H. ELTAYEBet al. 1,000,000 ~'
Mg
~,,
I ca)
~
.~_
TSP
lO,00o
g c o
100
i
|
,
J
1 2 3 4
,
,
t
J
,
,
,
,
~
,
i
i
i
i
,
i
,
,
i
i
5 6 7 8 9 101112131415161718192021222524
D O D N O D N D D O N D D N D D N D D N D D N O Sample number (time)
10,0001
(b) --.)K- Zn
A m i
Br
1000:
-l'¢r- Pb
E
c
8
c
~
100
io
23456789101112131415161718192021222324 D D D N D D N D D D N D D N D D N D D N D D N D Somple number
(time)
Fig. 2. (a) Time trends for the non-enriched elements. (b) Time trends for the enriched elements.
maxima but a rather constant level throughout the entire sampling campaign. Also, C! exhibits fewer maxima than the other elements. For Zn, Br and Pb a similar trend is observed as for the TSP and the nonenriched elements. This could be the result of contaminated street dust being sampled. However, it is more likely that the similar behaviour is caused by the fact that the traffic is responsible for both the BrPb-containing particles and the airborne soil dust. Receptor modellin 0 by APCA. Of the 27 elements measured by PIXE, 22 were retained for the inclusion in the APCA receptor modelling. These elements were Na, Mg, A1, Si, P, S, CI, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Sr, Zr, Ba and Pb. Furthermore, the TSP was also included, so that the data set consisted of 23 variables in 24 samples.
Three principal components, which explained 90% of the data variance, were retained for the Varimax rotation. Table 4 gives the rotated component loadings together with the communalities, the variance and the per cent of variance explained by each component. Standard deviations for the component loadings were calculated by the procedure suggested by Heidam (1982). Loadings smaller than three times their standard deviation are given in parentheses. The communality is high for most of the elements indicating the adequacy of the component model for this data set. The first component has high loadings for the TSP, the major crustal and the non-enriched elements. Thus, this component can easily be attributed to soil dust. On the second component, the elements S, Br and Pb show high loadings. These elements are pro-
Sources and composition of Khartoum aerosol
71
Table 4. Varimax rotated component loadings for Khartoum aerosol Element
Component 1 Component 2 Component 3 Communality
Na* Mg Al Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Zr Ba Pb TSP
( - 0.008)t 0.96 0.98 0.99 0.93 (-0.089) 0.30 0.96 0.92 0.99 0.90 0.93 0.98 0.98 0.86 0.79 (0.11) 0.32 0.88 0.89 0.90 0.41 0.89
Variance Per cent of variance
15.0 73
0.80 0.17 (-0.07) (-0.007) 0.25 0.77 0.51 0.13 0.30 0.06 0.34 (0.16) 0.13 0.13 0.28 (0.22) (0.17) 0.91 0.34 (0.15) (-0.07) 0.85 (0.13)
(0.19) 0.14 (0.05) 0.06 (0.13) (0.29) 0.68 0.19 (0.13) 0.09 0.17 (0.06) 0.09 0.1 ! 0.27 (0.11) 0.93 ( - 0.004) (0.13) (-0.002) (-0.16) ( - 0.007) (0.18)
3.7 18
0.67 0.95 0.96 0.99 0.94 0.69 0.82 0.97 0.86 0.99 0.95 0.90 0.99 0.98 0.89 0.69 0.87 0.93 0.90 0.81 0.84 0.89 0.84
1.72 8
* Na data are semi-quantitative. t Loadings less than three standard deviations are placed in parentheses.
Table 5. Source profiles (in relative concentration units and associated percentage standard deviations) for Khartoum aerosol as obtained by APCA Element
Na* Mg AI Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Zr Ba Pb TS P
Component 1 (dust)
--t 15.8 _ 3 120+4 300 -I-2 2.0+5 -4.9+31 15.2+4 50+5 12.8 + 2 0.25+5 0.2 + 7 1.79-1-2 100+ 1 0.10-+8 0.09-+15 -0.07 __.18 0.32+8 0.29 + 11 0.46 + 10 0.28+ 17 1700 +__9.9
Relative concentration in crustal rock 57 40 160 550 2.1 0.52 0.26 50 70 8.8 0.27 0.20 1.90 100 0.15 0.11 0.14 0.005 0.75 0.33 0.85 0.03 --
Component 2 (combustion)
1700 + 16 480__+ 19 --90+20 1100+ 15 1400+ 18 350_+25 2700-+ 17 130-+ 33 20_+ 13 -40_+. 15 2100-+ 10 5.3-+25 --35 _+6 20-+20 --100+8 --
* Na data are semi-quantitative. t Concentration less than three standard deviations.
AE(6) 27:1-F
Component 3 (Zn and CI)
-50+25 ----280+ 13 70+ 17 -30-+ 20 1.16_+26 -3.7+22 270_+ 12 0.74-+26 -100_+7 ------
72
M.A.H. ELTAYEBet al. 160
Zn,CI
140
g ::3
120 100
g u
80
~ 6o g o
Combustion
Soil dust
t°|ttli liUitlii° Ilm l lil l l lll ll
40
20
NO' 'AI' 'P' 'CI' 'Co' 'Ti' 'Cr' 'Fe 'Cd 'Br' 'Zr ~ 'TSP Mg Si S K Bo V Mn Ni Zn Sr Pb Elements
Fig. 3. Average source apportionment for Khartoum aerosol.
duced by anthropogenic activities and they are related to various combustion processes. The third component is not so easily attributed to a known source, and only Zn and C1 show high loadings on this component. From the rotated loadings, source profiles were extracted, and they are presented in Table 5. The relative concentrations within each source were scaled relative to the element which is considered a good indicator of the source, and this element is given a relative concentration of 100. The standard deviations on the concentrations were derived on the basis of the standard deviations of the loadings and concentration values less than three standard deviations are not given. The table also compares the composition of the dust source component to that of average crustal rock (Mason, 1966). Good agreement is noticed for most of the elements. A notable exception is K, which appears to be depleted in the local soil. As to the combustion source profile, the Br/Pb ratio of 0.33 is close to the 0.35-0.39 ratios between these two elements in urban aerosol (Sturges and Harrison, 1986). Figure 3 shows the average relative contributions from the three sources as percentages of the average measured concentration. Similar to previous calculations, contributions corresponding to component loadings of less than three standard deviations were excluded. For most of the elements the percentage contributions by the three sources sum up to 100°/0 within 20%. Exceptions are C1, Cu, Zn and Pb which are overestimated by this model and S which is underestimated. These observations are probably due to the limited number of samples we are dealing with. As expected, the soil dust source dominates for all the non-enriched elements. The combustion source prevails for S, CI, Br and Pb, whereas Zn is about equally attributed to the combustion source and to the (Zn, C1) component.
Single-particle analysis The relative X-ray intensities for the elements Na, Mg, AI, Si, S, C1, K, Ca, Ti, Mn, Fe, Cu, Zn, Br and Pb, obtained by electron probe microanalysis of 300 individual particles in each of the 19 samples, were used in the cluster analysis. The results of this classification are given in Table 6, where the average relative X-ray intensities for the optimized particle classes are listed together with the particle class abundance and the possible source identification. Only the elements with relative X-ray intensity/> 5% of the sum for at least one particle group are shown. Table 7 presents the relative particle abundance of each particle group in every individual sample (particle frequency). From Table 6 it is evident that most of the particles originate from soil dust and that only few particles originate from combustion sources. Soil dust particles. The most abundant particle group of soil dust particles is the Al-rich group. These particles comprise 64% of all analysed particles and they are mainly composed of AI, Si and Fe, with relative X-ray intensities of 21, 59 and 10%, respectively. Other aluminosilicate particles are in group 5, which represents Fe-rich alumino-silicates, with an abundance of 4.4%, and in group 8, namely Ti-rich alumino-silicates, with an abundance of 1.4%. The Si-rich particles (group 2) with an abundance of 10% are almost pure quartz as they show a relative X-ray intensity for Si of 93%. The Ca-rich particles of group 3 with a 6% abundance also exhibit a relative X-ray intensity of 18% for Si. Particles with similar relative X-ray intensities have been identified as CaCO3 (Cornille et al., 1990). Particles from combustion sources. The particles in group 6 have relative X-ray intensities of 11, 41 and 39°/0 for Si, S and Ca, respectively; they can be due to
73
Sources and composition of Khartoum aerosol
O
+1 +1
+1
+1 +1 +1 +1 +1 +1 +1
I I
I
I1¥~111
/
+ll I + ~ t l
I I
I
II
I I
+l
I+MI
I I
I
Illll+l
U
I I
I
I1¥~1 I¥1
r~
I I
I
I+ll
b~
+1+1
+1
z
I I
I
.o
+It O
I+tlq
I I+l (-q
ex0
¢m
I+~ +~
~.~,
0
+l +l I ~1 I I
i L+llll
t~
._~
,<
o
~ ~'~'~
~ ~
'~ .9 ..°
~8
.~ "N
._= +1+1
+1
+1+1+1+1+1+1+1
+1 +1
+1
+1 +1 +1 +1 +1 +1 +1
-~
.<
CaSO4 from combustion sources being formed around a Si core (Shattuck et al., 1985). Other particles originating from combustion processes are clustered in group 7, with an abundance of 4%: they have relative X-ray intensities of 5% for Na, 75 % for C! and 5.5% for Zn. Also from combustion sources are the S-rich particles in group 9 with an abundance of 0.9%: they are probably (NH4)2SO 4. The K-rich particles in group 10 may also have their origin from combustion sources; they also contain S and CI. One group of particles, number 4, is identified as organic since no element has a relative X-ray intensity greater than 5%. It has an abundance of 6% and may contain soot. Table 6 further indicates that, in general, particles from combustion have a smaller size than those from soil dispersion. The fact that no Br-Pb-containing particles were detected by EPMA appears to be in contradiction with the results of bulk analysis, where both elements were clearly observed. A possible explanation is that these elements were only mainly present in particles with diameter below 0.25 #m, which was the lower threshold for the EPMA measurements. However, the absence of the Br-Pb particle group may also be the result of the fact that the cluster analysis does not allow the isolation of poorly populated clusters. Temporal variation. When the abundance of each particle is followed throughout the sampling campaign (Table 7), it is seen that the relative abundances of the particles show little variability through the 19 samples. The variation of the relative abundance of the different particle classes, with alumino-silicates and the particles of combustion origin each being summed in one group, is depicted in Fig. 4 as a stacked time series. The particle group of soil origin shows some variability from sample to sample. The aluminosilicate and quartz groups show a somewhat lower percentage contribution for the samples which were collected late in the night and in the early morning, i.e. samples 8, 11, 14, 17, 20 and 23. The organic and C a C O 3 particles exhibit the largest variability. The CaSO4 group shows the most uniform variability with largest relative abundance for the samples collected late in the night and early morning hours, possibly because the source of these particles was emitting particles in a consistent manner (the coal-fired power plant was operational 24 h a day). It is noticed that other particle groups from combustion sources, i.e S-rich particles, show peaks in the samples collected in the early morning hours. Thus, these particles do not seem to originate from traffic and the effect of the nearby coal-fired plant is more important.
CONCLUSIONS e~ ,-i o
The use of two bulk analytical techniques greatly improved the quality of the data. The EPMA analysis
Soil dust
51±3 63±3 66±3 68±3 ~±3 69±3 57±3 73±3 71±3 54±3 67±3 63±3 65±3 66±3 68±3 55±3 46±3 74±3 70±3
Sample no.
1 2 3 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Group 1
20±2 20±2 15±2 6.7±1 11±2 7.0±2.0 4.3±1.2 11±2 6.7±1.4 10±2 9.7±1.7 6.0±1.4 12±2 9.7±1.7 8.0±1.6 12±2 12±2 5.3±1.3 5.0±1.3
Soil dust (quartz)
Group 2
Group 4
7.3±1.5 3.3±1.0 4.3±1.2 7.7±1.5 5.7±1.3 6,3±1.4 7.7±1.5 9,3±1.7 5.3±1.3 8.0±1.6 5.3±1.3 9.7±1.7 6.3±1.4 5.7±1.3 5.3±1.3 8.0±1.7 4.7±1.2 6,7±1.4 5.3±1.3 3.0±1.0 1.3±0.7 3.0±1.0 3.3±1,0 3.7±1,0 2.3±0.9 11±2 17±1 1.7±1.0 1.7±1.0
17±2 9.7±1.7 9.7±1.7 5.3±1.3 3.7±1.3 7.0±L5 3.0±1.0 0.3±0.3
Soil dust (CaCO3) Organic
Group 3
2.3±1.0 1.7±0.7 1.3±0.7 6.3±1.0 3,3±1.0 5.3±1.0 4.0±1.0 3.3±1.0 9.0±2.0 5.0±1.0 3.7±1.0 5.0±1.0 3.0±1.0 3.7±1.0 4.0±1.0 6.7±1.0 4.0±1.0 6.7±1.0 4.0±1.0
Soil dust
Group 5
-0.3±0.33 2.7±1.0 1.7±0.7 4.3±1.0 1.0±0.6 9.3±2.0 2.6±1,0 4.0±1.0 3.7±1.0 10±1 2.7±0.9 6.3±1.0 4.6±1.0 3.0±1.0 3.3±1.0 8.0±2.0 2.7±1.0 8.0±2.0
CaSO4
Group 6
--0.3±0,3 1.3±0.7 5.7±1.0 1.3±0.7 13±2.0 0.3±0.3 2.3±0.9 8.7±2.0 1.0±0.6 7.0±2.0 1.0±0.6 4.0±1.0 7.0±2.0 0.7±0.5 4.3±1.0 1.7±0.7 4.0±1.0
NaCI
Group 7
2.0±0.8 2.3±0.9 1.0±0.6 1.3±0.7 1,3±0.7 2.0±0.8 1.0±0.6 0.7±0.5 1.0±0.6 1.7±0.5 0.7±0.7 1.7±0.5 1.0±0.6 1.7±0.7 1.3±0.7 1.7±0.7 0.7±0.5 1.7±0.7 1.3±0.7
Soil dust
Group 8
Table 7. Relative abundance of the particle groups in each sample
---1.0±0.6 1.0±0.6 -1.0±0.6 -0.7±0.5 4.0±1.0 1.0±0.6 0.7±0.5 1.7±0.8 0.7±0.5 1.0±0.6 1.3±0.7 2.3±0.9 -0.7±0.5
Combustion
Group 9
---0.7±0.5 -0.3±0.3 0,3±0.3 --2.0±0.8 0.3±0.3 1.0±0.6 0.3±0.3 -0.3±0.3 0.3±0.3 1.3±0.7 ---
Combustion
Group 10
m
Sources and composition of Khartoum aerosol
75
120. Ouartz CoCO 3
100.
COS04 ue 8 0 . c o
o
Combustion
10rgonlc
60.
Alumino- slilcote
40, 13_
20.
O, 1 2 3 8 9 1011 12 13 14 15 16 17 18 19 20 212~> 23 D O D D D D N D D N D D N D D N D D N
Sample number (time)
Fig. 4. Temporal variation of the relative abundances for the different particle classes in Khartoum aerosol.
confirmed the findings of the bulk analysis techniques. It also gave clues to the formation process of some particles from combustion sources. The aerosol of K h a r t o u m is dominated by a soil dispersion source, giving rise to abnormally high airborne crustal element levels, especially in samples collected during the day. Enrichment factor calculations show that S, CI, Zn, Br and Pb are enriched in K h a r t o u m aerosols. A comparison with literature values indicates that the elemental enrichment factors in the K h a r t o u m aerosol are among the lowest urban values yet recorded; this is largely due to the high dust concentration. F r o m temporal variations it appeared that Br, Pb and the crustal elements exhibited maxima in the same samples (i.e. during the day), suggesting that the airborne levels of these elements are all controlled by traffic. The data set was subjected to APCA modelling with satisfactory results. Three components were extracted: a soil dust component with high loadings for the nonenriched elements, a combustion component with high loadings for the enriched elements, and a third component with high loadings for CI and Zn. E P M A allowed the differentiation of the soil dust particles in various particle groups. The vast majority of these particles were alumino-silicates with lesser amounts of quartz and CaCO3 particles. All combustion particles consisted of sulphates. Br- or Pbcontaining particles were not detected by EPMA. Acknowledoements--P.J.V.E. and W.M. are indebted to the Belgian Nation~l Fonds voor Wetenschappelijk Onderzoek and the Interuniversitair Instituut voor Kernwetenschappen for financial support. The technical assistance of Jan Carmeyer in the PIXE analysis is greatly appreciated.
REFERENCES
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. Cornille P., Maenhaut W. and Pacyna J. M. (1990) Sources and characteristics of the atmospheric aerosol near Damascus, Syria. Atmospheric Environment 24A, 1083-1093. Harrison R. M. and Sturges W. T. (1983) The measurement and interpretation of Br/Pb ratios in airborne particles. Atmospheric Environment 17, 311-328. Heidam N. Z. (1982) Atmospheric aerosol factor models, mass and missing data. Atmospheric Environment 16, 1923-1931. Keiding K., Jensen F. P. and Heidam N. Z. (1986) Absolute modelling of urban aerosol elemental composition by factor analysis. Analyt. Chim. Acta 181, 79-85. 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 Gent, Belgium. J. Trace Micropr. Tech. 5, 135-158. Maenhaut W. and Raemdonck H. (1984) Accurate calibration of a Si(Li) detector for PIXE analysis. Nucl. Instrum. Meth. 229, 123-136. Maenhaut W. and Vandenhaute J. (1986) Accurate analytic fitting of PIXE spectra. Bull. Soc. Chim. Belg. 95, 407-419. Maenhaut W., Sden A., Van Espen P., Van Grieken R. and Winchester J.W. (1981) PIXE analysis of aerosol samples collected over the Atlantic ocean from a sailboat. Nucl. Instrum. Meth. 181, 399-405. Maenhaut W., Raemdonck H. and Andreae M. O. (1987) PIXE analysis of marine aerosol samples: accuracy and artifacts. Nucl. Instrum. Meth. B22, 248-253. Mason B. (1966) Principles of Geochemistry. Wiley, New York. Penkett S. A., Atkins D. H. F. and Unsworth M. H. (1979) Chemical composition of ambient aerosol in the Sudan, Gezira. Tellus 31, 295-307. Raeymaekers B. (1986) Ph.D. thesis, Department of Chemistry, University of Antwerp (UIA), Belgium.
76
M.A.H. ELTAYEBet aL
Rahn K. A. (1976) The chemical composition of the atmospheric aerosol. Technical report, Graduate School of Oceanography, University of Rhode Island, Kingston, RI. Rojas C. M., Artaxo P. and Van Grieken R. (1990) Aerosols in Santiago De Chile: a study using receptor modelling with X-ray fluorescence and single particle analysis. Atmospheric Environment 24B, 227-241. Shattuck T. W., Germani M. S. and Buseck P. R. (1985) Cluster analysis of chemical compositions of individual atmospheric particles data. In Environmental Application of Chemometrics (edited by Breen J. J. and Robinson P. E.), ACS Syrup. Set. 292, pp. 118-129. American Chemical Society, Washington DC. Storms H., Artaxo P., Bruynseels F. and Van Grieken R.
(1987) Individual particle analysis by automated EPMA for the improvement of source apportionment studies for remote aerosols. In Microbeam Analysis, pp. 343-345. San Francisco Press, San Francisco. Sturges W. T. and Harrison R. M. (1986) Bromine:lead ratio in airborne particles from urban and rural sites. Atmospheric Environment 20, 577-588. Thurston G. D. and Spongier J. D. (1985) A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmospheric Environment 19, 9-25. Van Espcn P., Jansscns K. and Nobels J. (1986) AXIL-PC software for the analysis of complex X-ray spectra. Chemomet. lntell. Lab. Syst. 1, 109-114.
0957 1272/93 $6.00+0.00 © 1993 Pergamon Press Ltd
Printed in Great Britain.
SOURCES A N D COMPOSITION OF AEROSOL FROM KHARTOUM, S U D A N MOHAMED A. H. ELTAYEB,* CHRIS F. XHOFFER, PIERRE J. VAN ESPEN a n d RENt~ E. VAN GRIEKEN Department of Chemistry, University of Antwerp (UIA), B-2610 Antwerp-Wilrijk, Belgium and WILLY MAENHAUT Institute for Nuclear Sciences, University of Ghent, B-9000 Ghent, Belgium
(First received 25 June 1991 and in final form 1 Auoust 1992) Abstract--Aerosol sampling was carried out during December 1989 in Khartoum, Sudan, using Nuclepore membrane filters. Twenty-four aerosol samples were collected and analysed by X-ray fluorescence (XRF) spectrometry and particle-induced X-ray emission (PiXE). In addition, individual particle analysis was also performed on 19 samples using electron probe X-ray microanalysis (EPXMA). Good agreement between XRF and PIXE results was obtained for most of the elements. Enrichment factor calculations indicated that soil dispersion is the dominant source for most elements in the aerosol. However, certain elements showed high enrichment factors indicating the presence of anthropogenic sources. From a comparison with available literature data it appeared that the enrichment factors for the enriched elements in the Khartoum aerosol are among the lowest recorded values for urban aerosol. Absolute principal components analysis (APCA) was performed on the data and confirmed the findings from the enrichment factor calculations, i.e. a dominant soil dispersion source and an anthropogenic source for some of the elements. Because of the very limited number of important aerosol sources, the data set was reproduced by the APCA model with a reasonable degree of success. Single particle analysis also showed that most of the particles were soil dust. These particles could further be differentiated into alumino-silicates, quartz and CaCO3 particles. Some of the particles were found to originate from combustion sources. EPXMA gave clues to the process of formation for some of the particles from combustion sources.
Key word index: Aerosol, Sudan, X-ray emission analysis, single particle analysis, source apportionment.
INTRODUCTION
EXPERIMENTAL
Since the vast majority of aerosol studies have been carried out in industrialized countries, d a t a from developing countries are very limited. However, air pollution levels in developing countries could be interesting for c o m p a r i s o n purposes. F u r t h e r m o r e , because only a limited n u m b e r of industrial sources are i m p o r t a n t , aerosol studies in such countries provide a good o p p o r t u n i t y for testing e n v i r o n m e n t a l pollution control procedures a n d for receptor modelling techniques. Only o n e study so far has been published on aerosols from S u d a n (Penkett et al., 1979). Here, we report o n the c o m p o s i t i o n of aerosol samples collected at K h a r t o u m . T h e samples were analysed by energy dispersive X-ray fluorescence ( E D X R F ) spectrometry, particle-induced X-ray emission (PIXE) spectrometry a n d electron p r o b e X-ray microanalysis (EPMA).
Site The sampler was placed on the roof of a one-storey building, which houses the laboratory of the Sudan Atomic Energy Commission in the centre of Khartoum, at an elevation of about 5 m above street level. The city of Khartoum lies in the sub-Sahara region at the junction of the Blue and the White Nile rivers. The city has a few light industries: textiles, paints, car batteries, etc.
Samplin# The samples were collected on Nuclepore polycarbonate membrane filters of 0.4 #m pore size and 47 mm diameter placed in a Millipore filtration apparatus. The air was drawn through the filter by a Millipore vacuum pump, and a gas meter was used to measure the volume of the air sampled in each run. The collection time per sample was 4-11 h, and samples were taken nearly continuously from 14 to 21 December 1989. Meteorological observations indicated that, during the sampling period, the wind direction was almost always northwest and that its speed ranged between 3 and 8 knots. An overview of the sampling campaign is given in Table 1.
* On leave from the Sudan Atomic Energy Commission, National Council for Research, Khartoum, Sudan. 67
68
M . A . H . ELTAYEBet al. Table 1. Overview of the sampling campaign (December 1989); D and N indicate that the sample is classified as day or night, respectively Sample no. 1D 2D 3D 4N 5D 6D 7N 8D 9D 10 D 11 N 12 D
Date
Collection time
Sample no.
Date
Collection time
14 Dec. 14 Dec. 14 Dec. 15 Dec. 15 Dec. 15 Dec. 15-16 Dec. 16 Dec. 16 Dec. 16 Dec. 16-17 Dec. 17 Dec.
1005-1400 1405-1834 1845-0005 0012-0705 0837-1608 1635-2240 22454)613 0625-1145 1150-1545 1642-2235 2240-0643 0650-1140
13 D 14 N 15 D 16 D 17 N 18 D 19 D 20 N 21 D 22 D 23 N 24 D
17 Dec, 17-18 Dec. 18 Dec. 18 Dec. 18-19 Dec. 19 Dec. 19 Dec. 19-20 Dec. 20 Dec. 20 Dec. 20-21 Dec. 21 Dec.
1146-2115 2245-0642 0650-1455 1505-2207 22434)618 0630-1544 1550-2225 22404)624 0635-1511 1517-2113 2125-0817 0823-1422
Analytical methods
For the bulk analysis of aerosol samples both energy dispersive X-ray fluorescence analysis (EDXRF) and particle-induced X-ray emission (PIXE) were used. The EDXRF instrument and analytical procedure are described by Rojas et al. (1990) and Van Espen et a l. (1986). Concentrations of 20 elements (Mg, AI, Si, P, S, C1, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr and Pb) were determined by this technique. Details about the PIXE experimental set-up, analytical procedure, calibration and uncertainties are given elsewhere (Maenhaut et al., 1981, 1987; Maenhaut and Raemdonck, 1984: Maenhaut and Vandenhaute, 1986). A total of 27 elements were measured by PIXE (i.e. Na, Ga, As, Se, Y, Zr, Ba in addition to elements already measured by EDXRF). Single-particle analysis was performed with an automated electron probe microanalysis (EPMA) unit equipped with an energy dispersive Si(Li) detector, and secondary electron, transmission electron and backscattered electron detectors. The instrument and electron probe X-ray microanalysis procedures used are described elsewhere (Raeymaekers, 1986; Rojas et al., 1990; Bernard et al., 1986; Storms et al., 1987). Nineteen samples were thus examined. Some 300 particles were analysed for each sample. For each particle, the relative X-ray intensities for the elements detected together with the particle shape factor and diameter were acquired. Multivariate analyses
The data set with the elemental concentrations as derived from the bulk analysis was subjected to a multivariate receptor model. Our model is a modification of the A P C A model of Thurston and Spengler (1985), and was derived from the procedure described by these authors and by Keiding et al. (1986). A detailed description of it can be found in Maenhaut and Cafmeyer (1987). Cluster analysis was applied to the EPMA data set in order to classify the detected particles into groups as well as to follow the behaviour of each particle group throughout the sampling period. Following the procedure described by Bernard et al. (1986), the particles were classified by hierarchical and non-hierarchical cluster analysis on the basis of the relative characteristic X-ray intensities of the elements detected in each particle.
RESULTS A N D DISCUSSION
Bulk aerosol composition E l e m e n t a l c o n c e n t r a t i o n s . The average T S P values as derived from weighing the exposed filters were 144
Table 2. Comparison between XRF and PIXE data Element
Mg AI Si P S Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Br Rb Sr Pb
XRF + 6* (ng m -a)
PIXE_+ 6 Average (ng m -3) XRF/PIXE_+SD (n)t
602+50 990+50 4900_+40 5300_+30 10200_+80 13600_+30 80_+10 155+10 970+50 1120+ 10 1000+60 880_+20 1260-+50 1110-+10 4200_+40 3400_+10 810_+20 6 3 0 _ + 5 14-+7 16_+8 14+5 8.0-+l.4 91_+6 100_+8 5700+40 5300+10 6.1 _+7.7 8.5+3.5 6.9+1.8 4.0+1.1 109+5 100_+3 19_+1 17__+2 3.6_+0.7 5.3_+2.3 25+ 1 21 ___+3 47+3 38_+6
0.60__+0.11(22) 0.92_+0.13(24) 0.75+0.07 (24) 0.52_+0.16(23) 0.86+0.07 (24) 1.14_+0.14(23) 1.13_+0.13(24) 1.22_+0.11(24) 1.29_+0.13(24) 0.89+0.31 (18) 1.66__+0.70(21) 0.89_+0.15(23) 1.08+0.10 (24) 0.74+0.43 (24) 1.61___+0.69(19) 1.05_+0.14(22) 1.11_+0.18(24) 1.03+0.43 (12) 1.09+0.26 (20) 1.17_+0.17(20)
*6=analytical error (counting statistics) for values near the mean. tSD=standard deviation on the average ratio, (n) = number of samples used to calculate the average. + 4 5 and 4 5 + 1 2 /~g m -3 for the samples collected during the day and those collected during early morning hours, respectively. The mean elemental concentrations, as obtained by X R F and PIXE are given in Table 2. The analytical error 6, which gives an indication of the sensitivity, is the error as calculated from counting statistics and applies to a concentration value near the mean. While PIXE results show lower analytical error for the elements from Mg to Zn, X R F has a lower analytical error for the elements Sr to Pb. The last column of this table, with the average ratio (XRF/PIXE) and associated standard deviation, also provides a measure of the agreement between the results by the two techniques. G o o d agreement (ratio close to unity) is observed for most of the elements,
Sources and composition of Khartoum aerosol Exceptions are the elements near the detection limits and Mg and P which showed consistently lower concentrations in XRF. This is due to the difficulty in spectral analysis for Mg X-rays which fall at the very beginning of the fitted region and due to the spectral interference on P from Si. Comparison of the mean value in the Khartoum aerosol with available literature data (Rahn, 1976) indicated that the crustal element concentrations were almost always higher in the Khartoum aerosol, while the concentrations for the enriched elements were in most cases lower in the Khartoum aerosol. It was observed that the samples collected from about 6 a.m. to about 12 p.m. (day = group 1) exhibited higher elemental concentrations than the samples taken from about 10 p.m. to about 6 a.m. (night = group 2). Figure 1 compares the average values for the two groups. The day/night difference is a factor of 2-4 for most elements except for S which shows similar values for the two groups of samples. The higher concentrations for group 1 are most likely due to entrainment of dust particles generated by traffic during the day, and to the daytime usually being more windy than the nighttime. The fact that S does not show the same day/night variation as the lithophilic elements clearly indicates that S originates from sources other than soil dust dispersal, as will be discussed later. The fact that Br and Pb follow the same pattern as the lithophilic elements, i.e. high concentration for group 1 as compared to group 2, may again be explained by larger traffic volume during the day hours. However, the ratio of the daytime concentration to nighttime concentration for Br in the aerosol is not as high as for the other elements. The particulate Br concentration in an urban environment usually correlates with traffic volume and the fact that it is lower than expected during the day may be due to a higher volatility during the hot day hours (Sturges and Harrison, 1986). Enrichment factors and Br/Pb ratios. Enrichment factors (EFs) were calculated for each individual sample relative to the average crustal rock composition (Mason, 1966) and with AI as the reference element. The arithmetic average EF values are given in Table 3 and compared to the geometric mean enrichment factors for 29 cities (Rahn, 1976). Most of the elements show an enrichment factor close to unity indicating a soil dispersion source. The elements which are significantly enriched in Khartoum aerosol are S, C1, Zn, Br and Pb. These elements are known to be emitted from combustion sources: coal-fired power plants for S and Cl, waste incineration for Zn and automotive exhaust for Br and Pb. The high correlation coefficient of 0.94 between Br and Pb confirms the common source for these two elements. Furthermore, the observed Br/Pb ratio of 0.42 is close to the ethyl ratio of 0.38 (Harrison and Sturges, 1983). While the enrichment factors for the major crustal elements are comparable to the geometric mean of the 29 cities, the non-crustal elements are much less
69
16'
Group 1 (day) m
Group 2 (night)
)¢ 12 'E 10
II g° 4
I
I
i |
2
I L II.L
0
AI Si
K Co Fe
S
CI
il
BrAO0 TSPIIO0 Z~. tO Pb, 100
Elements
Fig. 1. Comparison of the average day and night concentrations for the various elements.
Table 3. Average enrichment factors* (relative to AI and crustal rock; Mason, 1966)and associated standard deviations in Khartoum aerosol, as compared to the geometric mean of 29 cities (Rahn, 1976) Element
This work
Mg
0.80 + 0.15
Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Rb Sr Pb
0.76 __0.04 2.6+0.6 103 __73 130+ 110 0.78 + 0.25 1.63+ 0.35 2.2 __0.2 2.0+0.5 1.31 _+0.47 1.62+0.17 1.64-+0.17 2.1 -+0.9 1.13-+0.51 27+41 160+90 0.77+0.15 1.06-+0.25 64 _+25
Geometric mean of 29 cities 2.0 0.79 2.6 490 300 1.63 2.9 1.63 15.2 6.2 3.2 2.2 10.8 149 300 1940 2.9 0.85 3800
* PIXE data were used for EF calculation for the elements Mg-Zn, while XRF data were used for Br-Pb.
enriched in Khartoum than in the city data set of Rahn (1976). Time trends. Time trends for the TSP and the crustal elements are shown in Fig. 2a, while those for the enriched elements are shown in Fig. 2b. The trends for the TSP and both types of elements are similar, with high values for day samples and low values for night samples. An exception is S which does not show
70
M.A.H. ELTAYEBet al. 1,000,000 ~'
Mg
~,,
I ca)
~
.~_
TSP
lO,00o
g c o
100
i
|
,
J
1 2 3 4
,
,
t
J
,
,
,
,
~
,
i
i
i
i
,
i
,
,
i
i
5 6 7 8 9 101112131415161718192021222524
D O D N O D N D D O N D D N D D N D D N D D N O Sample number (time)
10,0001
(b) --.)K- Zn
A m i
Br
1000:
-l'¢r- Pb
E
c
8
c
~
100
io
23456789101112131415161718192021222324 D D D N D D N D D D N D D N D D N D D N D D N D Somple number
(time)
Fig. 2. (a) Time trends for the non-enriched elements. (b) Time trends for the enriched elements.
maxima but a rather constant level throughout the entire sampling campaign. Also, C! exhibits fewer maxima than the other elements. For Zn, Br and Pb a similar trend is observed as for the TSP and the nonenriched elements. This could be the result of contaminated street dust being sampled. However, it is more likely that the similar behaviour is caused by the fact that the traffic is responsible for both the BrPb-containing particles and the airborne soil dust. Receptor modellin 0 by APCA. Of the 27 elements measured by PIXE, 22 were retained for the inclusion in the APCA receptor modelling. These elements were Na, Mg, A1, Si, P, S, CI, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Sr, Zr, Ba and Pb. Furthermore, the TSP was also included, so that the data set consisted of 23 variables in 24 samples.
Three principal components, which explained 90% of the data variance, were retained for the Varimax rotation. Table 4 gives the rotated component loadings together with the communalities, the variance and the per cent of variance explained by each component. Standard deviations for the component loadings were calculated by the procedure suggested by Heidam (1982). Loadings smaller than three times their standard deviation are given in parentheses. The communality is high for most of the elements indicating the adequacy of the component model for this data set. The first component has high loadings for the TSP, the major crustal and the non-enriched elements. Thus, this component can easily be attributed to soil dust. On the second component, the elements S, Br and Pb show high loadings. These elements are pro-
Sources and composition of Khartoum aerosol
71
Table 4. Varimax rotated component loadings for Khartoum aerosol Element
Component 1 Component 2 Component 3 Communality
Na* Mg Al Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Zr Ba Pb TSP
( - 0.008)t 0.96 0.98 0.99 0.93 (-0.089) 0.30 0.96 0.92 0.99 0.90 0.93 0.98 0.98 0.86 0.79 (0.11) 0.32 0.88 0.89 0.90 0.41 0.89
Variance Per cent of variance
15.0 73
0.80 0.17 (-0.07) (-0.007) 0.25 0.77 0.51 0.13 0.30 0.06 0.34 (0.16) 0.13 0.13 0.28 (0.22) (0.17) 0.91 0.34 (0.15) (-0.07) 0.85 (0.13)
(0.19) 0.14 (0.05) 0.06 (0.13) (0.29) 0.68 0.19 (0.13) 0.09 0.17 (0.06) 0.09 0.1 ! 0.27 (0.11) 0.93 ( - 0.004) (0.13) (-0.002) (-0.16) ( - 0.007) (0.18)
3.7 18
0.67 0.95 0.96 0.99 0.94 0.69 0.82 0.97 0.86 0.99 0.95 0.90 0.99 0.98 0.89 0.69 0.87 0.93 0.90 0.81 0.84 0.89 0.84
1.72 8
* Na data are semi-quantitative. t Loadings less than three standard deviations are placed in parentheses.
Table 5. Source profiles (in relative concentration units and associated percentage standard deviations) for Khartoum aerosol as obtained by APCA Element
Na* Mg AI Si P S CI K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Zr Ba Pb TS P
Component 1 (dust)
--t 15.8 _ 3 120+4 300 -I-2 2.0+5 -4.9+31 15.2+4 50+5 12.8 + 2 0.25+5 0.2 + 7 1.79-1-2 100+ 1 0.10-+8 0.09-+15 -0.07 __.18 0.32+8 0.29 + 11 0.46 + 10 0.28+ 17 1700 +__9.9
Relative concentration in crustal rock 57 40 160 550 2.1 0.52 0.26 50 70 8.8 0.27 0.20 1.90 100 0.15 0.11 0.14 0.005 0.75 0.33 0.85 0.03 --
Component 2 (combustion)
1700 + 16 480__+ 19 --90+20 1100+ 15 1400+ 18 350_+25 2700-+ 17 130-+ 33 20_+ 13 -40_+. 15 2100-+ 10 5.3-+25 --35 _+6 20-+20 --100+8 --
* Na data are semi-quantitative. t Concentration less than three standard deviations.
AE(6) 27:1-F
Component 3 (Zn and CI)
-50+25 ----280+ 13 70+ 17 -30-+ 20 1.16_+26 -3.7+22 270_+ 12 0.74-+26 -100_+7 ------
72
M.A.H. ELTAYEBet al. 160
Zn,CI
140
g ::3
120 100
g u
80
~ 6o g o
Combustion
Soil dust
t°|ttli liUitlii° Ilm l lil l l lll ll
40
20
NO' 'AI' 'P' 'CI' 'Co' 'Ti' 'Cr' 'Fe 'Cd 'Br' 'Zr ~ 'TSP Mg Si S K Bo V Mn Ni Zn Sr Pb Elements
Fig. 3. Average source apportionment for Khartoum aerosol.
duced by anthropogenic activities and they are related to various combustion processes. The third component is not so easily attributed to a known source, and only Zn and C1 show high loadings on this component. From the rotated loadings, source profiles were extracted, and they are presented in Table 5. The relative concentrations within each source were scaled relative to the element which is considered a good indicator of the source, and this element is given a relative concentration of 100. The standard deviations on the concentrations were derived on the basis of the standard deviations of the loadings and concentration values less than three standard deviations are not given. The table also compares the composition of the dust source component to that of average crustal rock (Mason, 1966). Good agreement is noticed for most of the elements. A notable exception is K, which appears to be depleted in the local soil. As to the combustion source profile, the Br/Pb ratio of 0.33 is close to the 0.35-0.39 ratios between these two elements in urban aerosol (Sturges and Harrison, 1986). Figure 3 shows the average relative contributions from the three sources as percentages of the average measured concentration. Similar to previous calculations, contributions corresponding to component loadings of less than three standard deviations were excluded. For most of the elements the percentage contributions by the three sources sum up to 100°/0 within 20%. Exceptions are C1, Cu, Zn and Pb which are overestimated by this model and S which is underestimated. These observations are probably due to the limited number of samples we are dealing with. As expected, the soil dust source dominates for all the non-enriched elements. The combustion source prevails for S, CI, Br and Pb, whereas Zn is about equally attributed to the combustion source and to the (Zn, C1) component.
Single-particle analysis The relative X-ray intensities for the elements Na, Mg, AI, Si, S, C1, K, Ca, Ti, Mn, Fe, Cu, Zn, Br and Pb, obtained by electron probe microanalysis of 300 individual particles in each of the 19 samples, were used in the cluster analysis. The results of this classification are given in Table 6, where the average relative X-ray intensities for the optimized particle classes are listed together with the particle class abundance and the possible source identification. Only the elements with relative X-ray intensity/> 5% of the sum for at least one particle group are shown. Table 7 presents the relative particle abundance of each particle group in every individual sample (particle frequency). From Table 6 it is evident that most of the particles originate from soil dust and that only few particles originate from combustion sources. Soil dust particles. The most abundant particle group of soil dust particles is the Al-rich group. These particles comprise 64% of all analysed particles and they are mainly composed of AI, Si and Fe, with relative X-ray intensities of 21, 59 and 10%, respectively. Other aluminosilicate particles are in group 5, which represents Fe-rich alumino-silicates, with an abundance of 4.4%, and in group 8, namely Ti-rich alumino-silicates, with an abundance of 1.4%. The Si-rich particles (group 2) with an abundance of 10% are almost pure quartz as they show a relative X-ray intensity for Si of 93%. The Ca-rich particles of group 3 with a 6% abundance also exhibit a relative X-ray intensity of 18% for Si. Particles with similar relative X-ray intensities have been identified as CaCO3 (Cornille et al., 1990). Particles from combustion sources. The particles in group 6 have relative X-ray intensities of 11, 41 and 39°/0 for Si, S and Ca, respectively; they can be due to
73
Sources and composition of Khartoum aerosol
O
+1 +1
+1
+1 +1 +1 +1 +1 +1 +1
I I
I
I1¥~111
/
+ll I + ~ t l
I I
I
II
I I
+l
I+MI
I I
I
Illll+l
U
I I
I
I1¥~1 I¥1
r~
I I
I
I+ll
b~
+1+1
+1
z
I I
I
.o
+It O
I+tlq
I I+l (-q
ex0
¢m
I+~ +~
~.~,
0
+l +l I ~1 I I
i L+llll
t~
._~
,<
o
~ ~'~'~
~ ~
'~ .9 ..°
~8
.~ "N
._= +1+1
+1
+1+1+1+1+1+1+1
+1 +1
+1
+1 +1 +1 +1 +1 +1 +1
-~
.<
CaSO4 from combustion sources being formed around a Si core (Shattuck et al., 1985). Other particles originating from combustion processes are clustered in group 7, with an abundance of 4%: they have relative X-ray intensities of 5% for Na, 75 % for C! and 5.5% for Zn. Also from combustion sources are the S-rich particles in group 9 with an abundance of 0.9%: they are probably (NH4)2SO 4. The K-rich particles in group 10 may also have their origin from combustion sources; they also contain S and CI. One group of particles, number 4, is identified as organic since no element has a relative X-ray intensity greater than 5%. It has an abundance of 6% and may contain soot. Table 6 further indicates that, in general, particles from combustion have a smaller size than those from soil dispersion. The fact that no Br-Pb-containing particles were detected by EPMA appears to be in contradiction with the results of bulk analysis, where both elements were clearly observed. A possible explanation is that these elements were only mainly present in particles with diameter below 0.25 #m, which was the lower threshold for the EPMA measurements. However, the absence of the Br-Pb particle group may also be the result of the fact that the cluster analysis does not allow the isolation of poorly populated clusters. Temporal variation. When the abundance of each particle is followed throughout the sampling campaign (Table 7), it is seen that the relative abundances of the particles show little variability through the 19 samples. The variation of the relative abundance of the different particle classes, with alumino-silicates and the particles of combustion origin each being summed in one group, is depicted in Fig. 4 as a stacked time series. The particle group of soil origin shows some variability from sample to sample. The aluminosilicate and quartz groups show a somewhat lower percentage contribution for the samples which were collected late in the night and in the early morning, i.e. samples 8, 11, 14, 17, 20 and 23. The organic and C a C O 3 particles exhibit the largest variability. The CaSO4 group shows the most uniform variability with largest relative abundance for the samples collected late in the night and early morning hours, possibly because the source of these particles was emitting particles in a consistent manner (the coal-fired power plant was operational 24 h a day). It is noticed that other particle groups from combustion sources, i.e S-rich particles, show peaks in the samples collected in the early morning hours. Thus, these particles do not seem to originate from traffic and the effect of the nearby coal-fired plant is more important.
CONCLUSIONS e~ ,-i o
The use of two bulk analytical techniques greatly improved the quality of the data. The EPMA analysis
Soil dust
51±3 63±3 66±3 68±3 ~±3 69±3 57±3 73±3 71±3 54±3 67±3 63±3 65±3 66±3 68±3 55±3 46±3 74±3 70±3
Sample no.
1 2 3 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Group 1
20±2 20±2 15±2 6.7±1 11±2 7.0±2.0 4.3±1.2 11±2 6.7±1.4 10±2 9.7±1.7 6.0±1.4 12±2 9.7±1.7 8.0±1.6 12±2 12±2 5.3±1.3 5.0±1.3
Soil dust (quartz)
Group 2
Group 4
7.3±1.5 3.3±1.0 4.3±1.2 7.7±1.5 5.7±1.3 6,3±1.4 7.7±1.5 9,3±1.7 5.3±1.3 8.0±1.6 5.3±1.3 9.7±1.7 6.3±1.4 5.7±1.3 5.3±1.3 8.0±1.7 4.7±1.2 6,7±1.4 5.3±1.3 3.0±1.0 1.3±0.7 3.0±1.0 3.3±1,0 3.7±1,0 2.3±0.9 11±2 17±1 1.7±1.0 1.7±1.0
17±2 9.7±1.7 9.7±1.7 5.3±1.3 3.7±1.3 7.0±L5 3.0±1.0 0.3±0.3
Soil dust (CaCO3) Organic
Group 3
2.3±1.0 1.7±0.7 1.3±0.7 6.3±1.0 3,3±1.0 5.3±1.0 4.0±1.0 3.3±1.0 9.0±2.0 5.0±1.0 3.7±1.0 5.0±1.0 3.0±1.0 3.7±1.0 4.0±1.0 6.7±1.0 4.0±1.0 6.7±1.0 4.0±1.0
Soil dust
Group 5
-0.3±0.33 2.7±1.0 1.7±0.7 4.3±1.0 1.0±0.6 9.3±2.0 2.6±1,0 4.0±1.0 3.7±1.0 10±1 2.7±0.9 6.3±1.0 4.6±1.0 3.0±1.0 3.3±1.0 8.0±2.0 2.7±1.0 8.0±2.0
CaSO4
Group 6
--0.3±0,3 1.3±0.7 5.7±1.0 1.3±0.7 13±2.0 0.3±0.3 2.3±0.9 8.7±2.0 1.0±0.6 7.0±2.0 1.0±0.6 4.0±1.0 7.0±2.0 0.7±0.5 4.3±1.0 1.7±0.7 4.0±1.0
NaCI
Group 7
2.0±0.8 2.3±0.9 1.0±0.6 1.3±0.7 1,3±0.7 2.0±0.8 1.0±0.6 0.7±0.5 1.0±0.6 1.7±0.5 0.7±0.7 1.7±0.5 1.0±0.6 1.7±0.7 1.3±0.7 1.7±0.7 0.7±0.5 1.7±0.7 1.3±0.7
Soil dust
Group 8
Table 7. Relative abundance of the particle groups in each sample
---1.0±0.6 1.0±0.6 -1.0±0.6 -0.7±0.5 4.0±1.0 1.0±0.6 0.7±0.5 1.7±0.8 0.7±0.5 1.0±0.6 1.3±0.7 2.3±0.9 -0.7±0.5
Combustion
Group 9
---0.7±0.5 -0.3±0.3 0,3±0.3 --2.0±0.8 0.3±0.3 1.0±0.6 0.3±0.3 -0.3±0.3 0.3±0.3 1.3±0.7 ---
Combustion
Group 10
m
Sources and composition of Khartoum aerosol
75
120. Ouartz CoCO 3
100.
COS04 ue 8 0 . c o
o
Combustion
10rgonlc
60.
Alumino- slilcote
40, 13_
20.
O, 1 2 3 8 9 1011 12 13 14 15 16 17 18 19 20 212~> 23 D O D D D D N D D N D D N D D N D D N
Sample number (time)
Fig. 4. Temporal variation of the relative abundances for the different particle classes in Khartoum aerosol.
confirmed the findings of the bulk analysis techniques. It also gave clues to the formation process of some particles from combustion sources. The aerosol of K h a r t o u m is dominated by a soil dispersion source, giving rise to abnormally high airborne crustal element levels, especially in samples collected during the day. Enrichment factor calculations show that S, CI, Zn, Br and Pb are enriched in K h a r t o u m aerosols. A comparison with literature values indicates that the elemental enrichment factors in the K h a r t o u m aerosol are among the lowest urban values yet recorded; this is largely due to the high dust concentration. F r o m temporal variations it appeared that Br, Pb and the crustal elements exhibited maxima in the same samples (i.e. during the day), suggesting that the airborne levels of these elements are all controlled by traffic. The data set was subjected to APCA modelling with satisfactory results. Three components were extracted: a soil dust component with high loadings for the nonenriched elements, a combustion component with high loadings for the enriched elements, and a third component with high loadings for CI and Zn. E P M A allowed the differentiation of the soil dust particles in various particle groups. The vast majority of these particles were alumino-silicates with lesser amounts of quartz and CaCO3 particles. All combustion particles consisted of sulphates. Br- or Pbcontaining particles were not detected by EPMA. Acknowledoements--P.J.V.E. and W.M. are indebted to the Belgian Nation~l Fonds voor Wetenschappelijk Onderzoek and the Interuniversitair Instituut voor Kernwetenschappen for financial support. The technical assistance of Jan Carmeyer in the PIXE analysis is greatly appreciated.
REFERENCES
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. Cornille P., Maenhaut W. and Pacyna J. M. (1990) Sources and characteristics of the atmospheric aerosol near Damascus, Syria. Atmospheric Environment 24A, 1083-1093. Harrison R. M. and Sturges W. T. (1983) The measurement and interpretation of Br/Pb ratios in airborne particles. Atmospheric Environment 17, 311-328. Heidam N. Z. (1982) Atmospheric aerosol factor models, mass and missing data. Atmospheric Environment 16, 1923-1931. Keiding K., Jensen F. P. and Heidam N. Z. (1986) Absolute modelling of urban aerosol elemental composition by factor analysis. Analyt. Chim. Acta 181, 79-85. 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 Gent, Belgium. J. Trace Micropr. Tech. 5, 135-158. Maenhaut W. and Raemdonck H. (1984) Accurate calibration of a Si(Li) detector for PIXE analysis. Nucl. Instrum. Meth. 229, 123-136. Maenhaut W. and Vandenhaute J. (1986) Accurate analytic fitting of PIXE spectra. Bull. Soc. Chim. Belg. 95, 407-419. Maenhaut W., Sden A., Van Espen P., Van Grieken R. and Winchester J.W. (1981) PIXE analysis of aerosol samples collected over the Atlantic ocean from a sailboat. Nucl. Instrum. Meth. 181, 399-405. Maenhaut W., Raemdonck H. and Andreae M. O. (1987) PIXE analysis of marine aerosol samples: accuracy and artifacts. Nucl. Instrum. Meth. B22, 248-253. Mason B. (1966) Principles of Geochemistry. Wiley, New York. Penkett S. A., Atkins D. H. F. and Unsworth M. H. (1979) Chemical composition of ambient aerosol in the Sudan, Gezira. Tellus 31, 295-307. Raeymaekers B. (1986) Ph.D. thesis, Department of Chemistry, University of Antwerp (UIA), Belgium.
76
M.A.H. ELTAYEBet aL
Rahn K. A. (1976) The chemical composition of the atmospheric aerosol. Technical report, Graduate School of Oceanography, University of Rhode Island, Kingston, RI. Rojas C. M., Artaxo P. and Van Grieken R. (1990) Aerosols in Santiago De Chile: a study using receptor modelling with X-ray fluorescence and single particle analysis. Atmospheric Environment 24B, 227-241. Shattuck T. W., Germani M. S. and Buseck P. R. (1985) Cluster analysis of chemical compositions of individual atmospheric particles data. In Environmental Application of Chemometrics (edited by Breen J. J. and Robinson P. E.), ACS Syrup. Set. 292, pp. 118-129. American Chemical Society, Washington DC. Storms H., Artaxo P., Bruynseels F. and Van Grieken R.
(1987) Individual particle analysis by automated EPMA for the improvement of source apportionment studies for remote aerosols. In Microbeam Analysis, pp. 343-345. San Francisco Press, San Francisco. Sturges W. T. and Harrison R. M. (1986) Bromine:lead ratio in airborne particles from urban and rural sites. Atmospheric Environment 20, 577-588. Thurston G. D. and Spongier J. D. (1985) A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston. Atmospheric Environment 19, 9-25. Van Espcn P., Jansscns K. and Nobels J. (1986) AXIL-PC software for the analysis of complex X-ray spectra. Chemomet. lntell. Lab. Syst. 1, 109-114.