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A multivariate statistical analysis of the composition of rainwater near Cubatão, SP, Brazil
Environmental Pollution 79 (1993) 225 233
A MULTIVARIATE STATISTICAL ANALYSIS OF THE COMPOSITION OF RAINWATER N E A R CUBATAO, SP, BRAZIL Marilda Zanoni Mariotti Abbas, a Roy Edward Bruns. *b Ieda Spacino Scarminio c & Jose Roberto Ferrelra •
•
(/~
"Av. Santa Lidia, 461, 13.400 Piracicaba, SP, Brazil hlnstitute of Chemistry, State University of Campinas, CP 6154, 13.081 Campinas, SP, Brazil ~lnstitute of Chemistry, State University of Londrina, CP 6001, 86.051 Londrina, PR, Brazil d Research-Fishery Institute Secretary of Agriculture, Nuclear Energy Center for Agriculture USP Av. Francisco Matarazzo 455, 05001 S6o Paulo, SP, Brazil
(Received 28 October 1990; accepted 2 December 1991)
Abstract With the aim o f estimating the chemical composition o f bulk precipitation (wet + dry) in Cubat6o, rainwater samples were collected at several localities in the Cubatdo region f r o m M a y 1984 to October 1985. The levels o f some inorganic ions (Na +, Ca :+, K +, M g :÷, CI , S 0 4 , N H j , PO~ ) were measured by atomic absorption spectrophotometry, turbidimetrv and titration analysis. Correlation and Fisher discrimination indices, principal component and varimax loading and scores were determined in the multivariate statistical data treatment. The results showed that ionic concentrations in rainwater from Vila Parisi are significantly higher than those o f Cubat~o Centro, Santos and Serra do Mar. The ionic compositions o f the Vila Parisi rainwater seem to be mainly determined by local anthropogenic activities (industrial pollution). Besides the influence o f this factor on water quality, there is also a natural oceanic contribution involving Cl and Na ÷ at the other locations.
of precipitation, demonstrating their usefulness in identifying pollutant inputs (Knudson et al., 1977; Thornton & Eisenreich, 1982; Duysings et al., 1986; Moldan et al., 1987). The present paper involves the use of multivariate statistical analysis in the interpretation of the ionic compositions of rainwater falling in the vicinity of Cubat~.o, SP, Brazil. In spite of having the reputation of being the most air-polluted city in South America, little is known about the effects of pollutant sources on its rainwater. S T U D Y AREA
Cubatio, with a 160 km 2 area, occupies the southeastern portion of the state of Silo Paulo, being bordered on the north by the Serra do Mar mountain range and on the south by the cities of Silo Vicente and Santos on the Atlantic Ocean (Fig. 1). C u b a t i o presents distinct meteorological characteristics relative to the other areas in this region (Oliveira & Sagula, 1985). The ground wind velocities from the north-northeast during the night and early morning and from the south during the day are influenced by local topography with hills and crystalline elevations between 200 and 1000 m intercalated by flat low lying ocean inlets (Figs 2 and 3). The precipitation in the region is of orographic character and is influenced by the advances of frontal systems and sea breezes, with yearly variations ranging from 2400 to 2900 mm. The summer months of December through February are favored with higher precipitation quantities, between 870 and 1140 mm, whereas these amounts fall to between 230 and 335 mm in the winter. The atmospheric pressure oscillates between 1014 and 1018 rob. For the entire C u b a t i o region average temperatures are between 17 and 25°C. Temperature variations are observed for localities close to C u b a t i o indicating the occurrence of heat island
INTRODUCTION
For more than a century scientific documents have recorded interest in the investigation of the causes and consequences of variations in the chemical compositions of rainwater (Cowling, 1982). Sampling methods of this substrate have been studied with the objective of establishing secure and efficient procedures capable of minimizing the many inherent problems involved (Galloway & Likens, 1975). While the re-evaluation of sampling and chemical analysis methods adequate for rainwater studies has been undertaken, advances in the use of statistical and mathematical methods for treating and interpreting rainwater chemical compositions have been applied to the analysis of the ionic compositions * To whom correspondence should be addressed. Environ. Pollut. 0269-7491/92/$05.00 © 1992 Elsevier Science Publishers Ltd, England. Printed in Great Britain
225
226
M. Z M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira
4 \\
CUBATAO
¢,,.~ Fig. 1. Geographical location of Cubat~o. effects due to industrial concentration and urban occupation (Oliveira, 1985). Meteorological and air quality studies indicate the existence of two aerial basins: the center of Cubatfio and an outlying district called Vila Parisi. The central part is dominated by gaseous emissions resulting from the combustion of petroleum and its derivatives. On the other hand fertilizer, steel and cement complexes are common in Vila Parisi (Orsini et al., 1982; Miller et al., 1985). More than 20 base-industry complexes composed of about 110 factories, responsible for some 300 pollutant sources affecting air, water and soil (Galv~o Filho, 1987), operate in both these areas. EXPERIMENTAL
Samples collection Weekly samples of rainwater were obtained from the four localities (Fig. 4): Cubat~o Centro CC: Vila Parisi--VP; Santos--SS, and Serra do Mar SM, during the May 1984~October 1985 period (Abbas, 1989). When possible, daily samples were collected and kept at 4°C. After each weekly period, the daily samples were mixed and immediately analyzed. Chemical preservatives were not used. Although sample storage was carried out at low temperatures, samples can suffer the effects of microbial degradation which can influence the chemical speciation (Van Loon, 1985). During the entire sampling period, 48, 45, 49 and 45 weekly samples, respectively, were collected at these four sites.
Sixty centimeter diameter acrylic receptors (Ribeiro Filho, 1975) protected by white nylon cloths to prevent contamination (Koutrakis & Spengler, 1987) were used for total precipitation sample collections (Whitehead & Feth, 1964).
Analytical methods Atomic absorption spectrometry, by means of direct aspiration of the sample into the instrument nebulizer, was used for Na + and K ÷ determinations (Perkin Elmer Corporation, 1982). Ca 2+ and Mg 2+ were determined by EDTA solution titration, in the presence of eriochrome black T and murexide. The reaction of mercury thiocyanide with the consequent liberation of thiocyanide ions for free reaction with the iron (Ill) ions present in solution was used to determine CI . Total dissolved PO~ was determined with the ammonium molybdate method by means of a Technicon MT II W A T E R autoanalyzer. A turbidimetric method with barium sulfate was used to analyze for sulfate. The ammonium ion was determined by the alkaline phenol method, also using an auto-analyzer. Details of these methods can be found elsewhere (APHA, 1981). Multivariate statistical procedure A 187 x 9 data matrix was used, containing the ionic concentrations of the 187 samples collected. Each sample is described by the concentrations determined for eight chemical species (Na +, Ca 2÷, K ÷, Mg 2+, CI-, SO~-, NH~ and PO43-) and the precipitation volume
Multivariate statistical analysis of rainwater composition
227
%
o~
d3= o
\
0
I
2
3
4 Km
I~
Fig. 2. Wind directions (and relative velocities) in Cubat~o at night under high pressure conditions (anticyclone). obtained during the collection period. Since a basic objective of this paper is to characterize the variances and covariances of the various chemical measurements, the data have been autoscaled for the principal component and varimax calculations so that each measurement or variable has an average of zero and a variance of one. This standardization, besides avoiding the problem of unit selection, permits a comparison of these variances without undue inherent weighting of those variables which have higher values, even though the variations in the variable values are not that significant. Fisher indices, correlation coefficients and principal component and varimax factor scores and loadings were all calculated in the standard ways (Wold et al., 1984, Muhammed, 1986). R E S U L T S AND D I S C U S S I O N Averages, median values, and standard deviations of the chemical compositions of precipitation at the four sampling sites in the Cubat~o region are presented in Table 1 along with those values for the complete data set. Almost all ionic concentrations at all four sampling sites have standard deviations which are larger than their corresponding average values. The ionic concentrations are lowest at the Serra do Mar sampling site far from direct pollution sources. This site also has
the highest average precipitation volume, 107.90 mm, double the values observed at the other sampling stations. This inverse relationship between ionic concentrations and precipitation volumes was also observed in other studies (Silva Filho, 1985). Seasonal trends for the eight elements were investigated by constructing concentration versus precipitation volume graphs. Although not included here, the results compare well with those obtained by Pratt and Krupa (1983) at Hubbard Brook, with the higher levels of the chemical species corresponding to the lower precipitation rates. In part, seasonal variations probably explain the high standard deviations of the ionic concentrations observed and listed in Table 1 since the standard deviations for the rainfall volumes are also very high at all four sampling sites. This same tendency was observed by Dana & Easter (1987), for rainwater in the north eastern USA where seasonal variations of the ionic concentrations were larger than the variations in the precipitation volumes. In addition, although rainwater samples can have typical ionic compositions which are related to their sampling sites, differences in the ionic characteristics of rainwater samples from the same site can occur for other reasons. This indicates that inorganic species in water, are not conservative parameters (Galloway & Cowling, 1978). In general, rainwater collected from Vila Parisi had
228
M. Z. M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira b~. , j
c~
-~
too
•
o
/ I I %
\
Fig. 3. Wind directions (and relative velocities) in Cubatfio during the day under high pressure conditions (anticyclone). the highest ionic concentrations of all four sampling sites (SO~, PO 3 , Ca 2+, K +, Mg 2+ and NH~) with the exception of the Na + and CI ionic concentrations which were higher in Santos. Even though the lowest concentrations in Table 1 are for samples from the Serra do Mar station these values are among the highest yet observed (Petrenchuk & Selezneva, 1970: Galloway et al., 1982). Knowing that the chemical composition of rainwater is primarily determined by the nature of the atmospheric conditions (Junge & Werby, 1958) one might have been able to predict that the Vila Parisi rainwater would present the highest ionic concentrations when compared with rainwater samples from the other sites. Local air quality there is very poor due to high emissions of particulate material (Miller et al., 1985). Also morphological contrasts of land elevations contribute to a decrease in rainfall and a diversification of local wind velocities (Oliveira & Sagula, 1985). The ionic nature of rainwater in the region studied is probably determined by two main factors: one contribution from ions originating from the industrial pole and the other from natural emissions (Ribeiro Filho, 1975; Tavares et al., 1983). This is suggested with comparison of the C1/Na*, Mg2+fNa +, SO 2/Na +, K+/Na ~ and Ca2+/Na + ratios for rainwater at the four sampling sites with the values of these ratios found in natural sea water
(Table 2). The C I / N a + ratios are close to two at the CC, SS and SM sampling sites (using either average or median values), in good agreement with the ratio found in sea water, indicating the importance of ocean breezes on the ionic concentrations of rainwater at these locations. On the other hand, the value of this ratio is almost double at the Vila Parisi site indicating a strong regional influence which tends to mask the natural contribution from the ocean. Chloride sources are probably emissions from automobiles (Martin & Barber. 1978), cement and lime plants (Miller et al., 1985) and from the burning of fossil fuels (Laird & Miksad, 1978) for energy and fertilizer production. The sampling sites which present C 1 / N a + ratios close to the value found in sea water, also present high correlation coefficients for the Na + and CI concentrations in the samples studied: 0.98 (SS); 0.93 (CC) and 0.92 (SM). This relationship between the Na + and CI concentrations does not exist for the samples collected at Vila Parisi where the correlation coefficient is only 0-29. The values for the other ionic ratios in Table 2 for the sampling locations are much different than those found in sea-water. However the largest deviations From the seawater ratios occur for the Vila Parisi samples. It should be noted that almost all these ionic ratios are practically the same whether the calculations are made with average or median values.
Multivariate stat&tical analysis of rainwater composition
229 4 6 ° IB' W
46 ° 29'
23 ° 50' S
JARDIM CASQUEIRO
SANTOS
S.~O VICENTE
23 ° 5 8 '
O
1
2
I
I
I
ESCALA
3
I
4
I
5
km
I
GRA'FICA
Fig. 4. Locations of the sample collection stations: (1) Cubat~.o Centro; (2) Vila Parisi: (3) Santos; and (4) Serra do Mar. In an attempt to evaluate which ions are the most important in discriminating between rainwater from two different locations, Fisher indices of each variable, given in Table 3, were calculated for each pair of sampling sites. Large differences in the average values of an ionic concentration at two different sampling sites and small variances for these concentrations at each of these two sites result in large Fisher index values for this ion. Normally, large Fisher index values correspond to high discriminatory powers of the variable for the two sites being considered. Here, all ionic species present low Fisher index values (c. 6.00 × 10 3) when the sampling site pairs do not involve Vila Parisi. Thus rainwater samples from the Santos, Serra do Mar and Cubat~o Centro sites have similar ionic concentrations, at least for the ions studied here. On the other hand all sampling sites pairs involving Vila Parisi have higher Fisher index values for the SO4, Ca 2*, K +, N H L PO] and Mg 2+ ions. These values range between
6.00 × 10 3 and 21.00 × 10 3 whereas they are much smaller for Na +, C1 and the precipitation volume values, 0.01-5-17 x 10 3. As such, these index values are consistent with the relatively high average and median values found for all ionic species, except Na ÷ and C1, at the Vila Parisi sampling site and their significantly lower average and median values observed at the other sites. O f all the ionic species, SO~ and Ca -'+ have the highest average capability of discriminating between rainwater from Vila Parisi and the other sampling sites. Also, the Ca 2+ and SOl ionic concentrations are strongly correlated with each other (r = 0.81) and with Mg 2+ (r = 0.80 and r = 0.88, respectively). Working in an industrial area, Pratt et al. (1983) obtained lower correlation coefficients than those reported here, for the same chemical species associations and concluded that the major anions (SO~ and NO3) were associated with cations other than hydrogen.
M. Z. M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira
230
Table 1. Average, median and standard deviations of the average for ionic concentrations (mg liter i) and rainfall quantities of four sampling stations from May 1984 to October 1985
Variables
Total Av.
Rain (mm) Na + Ca > K+ Mg > CI SO4 NH~ PO]
Cubatgo Centro
Med.
66.75 36-60 (86-75) 3.54 2.20 (4.86) 8.54 2-50 (16.16) 1.49 0.40 (3.01) 1-64 0.80 (2-55) 8.40 5.00 (10.71) 15.50 5-00 (28.81 ) 1.30 0-41 (2.16) 8.16 0.58 (23-72)
Av.
Med.
55.19 35.65 (60.18) 3.62 2-10 (4.36) 4.32 2.16 (5.0l) 0.58 0.40 (0.60) 1.00 0.60 ( 1-01 ) 7.71 4.50 (8.14) 7.69 4.50 (9.07) 1.25 0.77 (1-63) 1.02 0-61 (1.49)
In an attempt to further interpret the rainwater compositions, principal c o m p o n e n t calculations were carried out on the complete data set and on the individual data sets o f each sampling site. Significant loadings for principal c o m p o n e n t s corresponding to eigenvalues larger than 1.0 are presented in Table 4. Since autoscaled values were used in these calculations the principal c o m p o n e n t s given in this table have variances which are statistically more significant than any o f the original variables listed in Table 1, The first two c o m p o n e n t s explain 54% and 18% o f the total variance. The first principal c o m p o n e n t has large contributions from the C a 2+, S O 4 , K + and M g 2+ concentrations, PC, = - 0 . 4 0 [ C a 2+] - 0.40[K +] - 0-42[Mg >] -0.42[SO~ ] - 0.33[PO4~] +-.. whereas the second one depends essentially on the Na ~ and C1 concentrations, P C 2 = 0-68[Na +] + 0.58[C1 ] + ... A graph o f the first principal c o m p o n e n t against the second is shown in Fig. 5. T w o different sample p o p u lations are suggested by the spreads and the directions o f the two groups o f samples. The relatively c o m p a c t
Vila Parisi Av.
Med.
56-34 28.30 (63.62) 2.95 2-40 (2-43) 24.88 15.70 (26-22) 4.55 3.30 (4.95) 3.69 1.90 (3.91 ) 10.34 6.00 (11.10) 47.29 33.00 (44.42) 3.17 1.93 (3.28) 31.00 18.42 (40.72)
Santos Av.
Med.
49-81 31.30 (52-49) 5.18 3.40 (7.58) 3.95 2.00 (4.02) 0.69 0.50 (0-76) 1.05 0.70 ( 1.26) 10.64 7-00 (15.18) 4.50 3.00 (6.17) 0.47 0.21 (0.75) 1.46 0.60 (3-56)
Serra do Mar Av.
Med.
107.90 63.90 (136.30) 2.27 1.60 (2.37) 1-73 1.00 (2.79) 0-28 0.20 (0.30) 0-90 0.51 ( 1.92) 4.67 3.50 (3.86) 4.04 2.00 (5.93) 0.36 0-18 (0.62) 0.23 0.12 (0.39)
g r o u p with an almost vertical orientation is c o m p o s e d mostly o f samples from the CC, SS and SM sites. The more disperse g r o u p contains a larger variance and is parallel to the first principal c o m p o n e n t axis. This c o m p o n e n t is strongl]¢ influenced by the values o f the Ca 2+, K +, Mg >, SO; and PO 3 concentrations, and discriminates this g r o u p o f samples from the other. In contrast, the second principal c o m p o n e n t , which depends essentially on the Na* and CI concentrations, does not differentiate between these two groups. Finally, the principal c o m p o n e n t s listed in Table 4 were subjected to varimax rotations. Varimax analysis has been shown to be useful in indicating factors which provide important contributions to rainwater ionic contributions ( K n u d s o n et al., 1977). The loadings and percentage variances for the varimax factors for all sampling sites are given in Table 5. The first factor accounting for 48'7,, of the total variance is c o m p o s e d o f large contributions from the Ca -`+, K +, M g -~+, S O 4~ and PO 3 concentrations. This factor evidently describes anthropogenic sources of the ionic concentrations in rainwater. The second varimax factor is determined principally by N a + and CI con-
Table 2. Ionic ratios for seawater and rainwater samples from the Cubatfio Centro, Vila Parisi, Santos and Serra do Mar stations collected between May 1984 and October 1985
Ions
Seawater
Precipitation Cubatfio Centro
CI/Na + Mg>/Na" SO4/Na + K~/Na * Ca2+/Na +
1.85 0.13 0.25 0.04 0.04
" Calculated using average values. h Calculated using median values.
2-13" 0.28 2.11 0.16 1.20
(2-14) h (0.28) (2-14) (0.19) (1.03)
Vila Parisi 3-50 (2.50) 1.25 (0.80) 16.03 (13.75) 1.54 (1.38) 6.29 (6-54)
Santos 2.07 0.20 0.87 0.13 0.76
(2.05) (0.21) (0.88) (0.15) (0.59)
Serra do Mar 2.06 0.40 1.78 0.12 0.76
(2.19) (0.32) (1.25) (0.13) (0.63)
Multivariate statistical analysis of rainwater composition
231
Table 3. Fisher index values (× 10 3) for ionic concentrations of precipitation collected between May 1984 and October 1985 at Cubatio Centro, Vila Parisi, Santos and Serra do Mar" Cubat~.o× Vila Centro Parisi
Cubat~.o × Santos Centro
Cubat~.o× Serra do Centro Mar
Vila x Santos Parisi
Vila × Serra do Parisi Mar
Santos × Serra do Mar
Ions
F.I. u
Ions
F.I.
Ions
F.I.
Ions
F.I.
Ions
F.I.
Ions
F.I.
SO4 K* Ca 2+ PO~
16.93 14-08 13.16 12.03 9-82 6.03 0.79 0.38 0.04
NH4+ SO 4 CI Na + K* PO 3 Rain Ca 2+ Mg 2+
3-93 1.73 0.65 0.63 0.29 0-27 0.09 0.07 0.01
NH4+ PO2 Ca -,+ K+ Rain CI SO 4 Na* Mg 2+
5.53 5.43 4-29 4.19 2.76 2.39 2-37 1.57 0.05
SO4 NH] Ca 2+ K+ PO 3 Mg 2+ Na + Rain C1
20.20
SOj Ca 2+ K+ NH4+ PO~ Mg 2+ CI Rain Na +
20.70 17.13 16.50 15.81 12.68 9-16 5.17 2.62 0.89
K+ Ca 2+ Rain C1 Na + PO~ NH4+ Mg 2+ SO4
5-31 4.29 3.48 3.07 2.75 2-40 1.29 0.92 0.06
M g 2+
N H4+ C1 Na + Rain
14-26 13.81 13.15 11.60 9.15 1.61 0.13 0-01
"The Fisher Index is defined as F.I. = ( X i - X2)/(S1 + Sff ) where X~ and 32 are the average values lbr two sampling sites and S~ and S~ their variances. c e n t r a t i o n s a n d appears to represent the influence o f sea breezes o n the ionic c o m p o s i t i o n s of the rain-water. The v a r i m a x factors for the C u b a t ~ o Centro, Santos a n d Serra do M a r data sets are all characterized by strong Na* C1 factors, whereas this factor is missing for the Vila Parisi sample data. Most certainly this factor, which represents the oceanic influence o n the ionic c o m p o s i t i o n s of the rainwater samples, has been masked by ions originating from anthropogenic sources. Oceanic spray appears to be a relevant factor c o n t r i b u t i n g to the neutrality of r a i n w a t e r samples (average p H of 6.4, m a x i m u m p H of 7-7 a n d m i n i m u m p H of 5-0) for the Santos s a m p l i n g sites. This statement is supported by the 0.98 correlation coefficient between N a ÷ a n d CI f o u n d for this s a m p l i n g location. In Vila Parisi, besides the oceanic sprays, the alkaline t e n d e n c y of the precipitation (Lopez, 1984-1985) is also due to i n l a n d element sources (Tables 2 a n d 5) such as p h o s p h a t e which is present in high c o n c e n t r a t i o n s in particulate atmospheric material (Miller et al., 1985). M o r e i r a - N o r d e m a n n et al. (1983) reported that rain-
water samples from the C u b a t ~ o C e n t r o collection site were acidic (pH = 3.6). In this case the influence of ocean spray is n o t effective in neutralizing these samples due to the existence of a n t h r o p o g e n i c activities which are more p r e d o m i n a n t in C u b a t h o than in Santos. P r o b a b l y this relatively high hydrogen ion c o n c e n t r a t i o n is due to a soil factor, in part originating from crystalline rocks which are poor in basic minerals or in dissolved metal cations ( G o r h a m , 1976). Also, the percentages of sulphate a n d chloride ions associated with cations other than h y d r o g e n m a y be i m p o r t a n t in c o n t r o l l i n g the alkalinity or acidity of rainwater samples as described by Lefohn a n d K r u p a (1988).
CONCLUSIONS The rainwater samples analyzed in this project appear to be of two distinct types. O n e type corresponds to samples from all four s a m p l i n g stations a n d seems to have ionic c o n c e n t r a t i o n s influenced by n a t u r a l a n d a n t h r o p o g e n i c sources c o m m o n to the whole region
Table 4. Principal component Ioadings from rainwater samples collected between May, 1984 and October, 1985 at Cubatho Centro, Vila Parisi, Santos and Serra do Mar" Variables
All sites 1
Rain Na + C a 2+
K~ Mg 2. CI SOj NH~ PO2 Eigenvalueh % Variance
2 . 0-68
-0.40 -0.40 -0-42 0-58 -0.42 -0.33 4.87 54.1
Cubat~.o Centro
1.61 17.9
1 .
2
. . -0.34 0.52 -0.34 -0-40 -0.36 -0.33 0.47 --0-45 0-31 -0-36 5.07 1-30 56.3 14.4
Vila Parisi 1
2
. . -0.31 -0.41 -0.38 -0-38 -0-32 0.42 -0.31 0.35 -0.41 -0.54 --0.43 5-14 1.18 57-I 13-1
Santos 1
2
Serra do Mar 3
0.48 -0-40 0.39 0-39 -0-39 -0.39 0.38 --5.31 59.0
--
---
0.35 --0.47 0-39 1.36 15.1
0.54 -0.80 1-03 11.4
1
2
0-58 -0.31 -0.33 -0.41 0.39 ---0-40 0.30 -0.39 -0.39 0-61 4-94 1.56 54-9 17.3
3 0.33 0-50
0.55
0.41 1.26 14-0
" All principal components loadings with absolute values larger than 0-3 are included in this table. The principal component loadings are normalized to one. h Only principal components with eigenvalues greater than 1 are included in this table.
M. Z. M. Abbas, R. E. Bruns, I. S, Scarminio, J. R. Ferreira
232 0,84"
Cubat6o
Centro
,
Vila Parisi
x
Santos
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Serra
do Mar
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0,63 -
0,42!
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leo X XO0000 ×QI I~ X X I ~11~110 X XIXXI XIX IO0•EO XX X Xll X O0 o •
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Fig. 5. Principal component projection (lst and 2nd principal components) of ionic concentrations of rainwater samples collected at the four sampling stations. s t u d i e d in this p r o j e c t . T h e o t h e r t y p e is c h a r a c t e r i z e d by s a m p l e s f r o m o n l y the Vila Parisi s t a t i o n . S t r o n g local influences n e a r this c o l l e c t i o n site severely m a s k the o c e a n i c i n f l u e n c e c o n t r i b u t i n g to the i o n i c c o n c e n t r a t i o n s c o n s i d e r e d in this r e p o r t . Statistical a n a l y s e s using Fisher index values and principal components a n d v a r i m a x f a c t o r s as well as the m o r e c o m m o n l y e m p l o y e d statistical e s t i m a t o r s s u c h as a v e r a g e s a n d m e d i a n values, s t a n d a r d d e v i a t i o n s a n d c o r r e l a t i o n coefficients all p r o v i d e a c o n s i s t e n t i n t e r p r e t a t i o n o f the rainwater data.
O p e r a t i o n a l difficulties h i n d e r e d the s t u d y r e p o r t e d here. M o r e s a m p l i n g s t a t i o n s w o u l d h a v e p e r m i t t e d g r e a t e r r e s o l u t i o n in o u r analysis, p e r h a p s a l l o w i n g for the i d e n t i f i c a t i o n o f specific p o l l u t i o n sources. A l s o , the chemical analysis should have included other ionic species, specially the h y d r o g e n ion. D e t e r m i n a t i o n s o f p H w d u e s w e r e o n l y c a r r i e d o u t for the s a m p l e s o b t a i n e d f r o m the S a n t o s s t a t i o n . H o w e v e r the a n t h r o p o g e n i c c h a r a c t e r i s t i c s o f the C u b a t g o r e g i o n are so p a r t i c u l a r t h a t this r e p o r t seems w a r r a n t e d in spite o f its l i m i t a t i o n s .
Table 5. Varimax factor Ioadings for rainwater samples collected between M a y 1984 and October 1985 at Cubat'~o Centro, Vila Parisi, Santos and Serra do Mar"
Variables
All sites 1
Rain Na + Ca 2+ K+ M g 2+ CI SO 4 NH2 PO2 % Variance
. -0.89 -0-91 -0.83 --. -0.92 -0-80 47.6
Cubat~o Centro
2
. 0-94 --0-91 ---24.2
1
.
. -0-79 --0.82 -0.71 -0-78 37-1
Vila Parisi
2
.
1
. 0.95 . . 0.70 0.71 0-90 -
33.6
Santos
2
. . -0.82 . . 0.88 . -0.74 -0.74 0-76 0.78 0.81 37-8 32.3
1
-0.97 .
. -0.93 -0.97 -0.85 --48.5
2
Serra do M a r 3
0-71 . .
.
.
--0.89 -22.8
---0.96 14.2
1
2
3
0-83 . 0.91 0.85 -0.96 -0.72 -0.92 -44-9
0.94 ---0.94 --24.6
-----0.88 16.5
Only varimax loadings with absolute values greater than 0.7 have been included in this table. The varimax factor loadings are normalized to the values of their respective eigenvalues.
Multivariate statistical analysis o f rainwater composition REFERENCES
Abbas, M. Z. M. (1989). T6cnicas quimiom6tricas na avaliaq~o da ~gua das chuvas em Cubat~,o SP. Escola Superior de Agricultura Luiz de Queiroz, Piracicaba, Brazil (Thesis in Portuguese, summary in English). APHA (1981). Standard Methods for the Examination o f Water and Wastewater, 15th edn. New York. American Public Health Association, Washington DC, USA, 1134 PP. Cowling, E. B. (1982). Acid precipitation in historical perspective. Environ. Sci. Technol., 16, 110A 23A. Dana, M. T. & Easter, R. C. (1987). Statistical summary and analyses of event precipitation chemistry from the MAP 3S network, 1976-1983. Atmos. Environ., 21, 113 28. Duysings, J. J. H. M., Verstraten, J. M., Bruijnzeel, L. & Bouten, W. (1986). Relationship between precipitation chemistry and some meteorological parameters in The Netherlands: a statistical evaluation. Water, Air and Soil Pollut., 28, 213 23. Galloway, J. N. & Likens, G. E. (1975). Calibration of collection procedures for the determination of precipitation chemistry. In Proceedings o f First International Symposium on Aeid Precipitation and the Forest Eeo,sTstems, ed. L. S. Dochinger and T. Seliga, 1976. USDA Forest service, Gen. Tech. Rep. (NE-23) Columbus, pp. 137 55. Galloway, J. N. & Cowling, E. B. (1978). The effects of precipitation on aquatic terrestrial ecosystems: a proposed precipitation chemistry network. J. Air Pollut. Cont. Assn.. 28, 229-35. Galloway, J. N., Likens, G. E., Keene, W. C. & Miller, J. M. (1982). The compositions of precipitation in remote areas of the world. J. Geophys. Res., 87, 8771-6. Galvao Filho, J. B. (1987). Controle de polui~.o ambiental: Cubat~_o, filosofia e conceito. Ambiente, pp. 70 73. Gorham, E. (1976). Acid precipitation and its influence upon aquatic ecosystems; an overview. In Proceedings o f the First International Symposium on Acid Precipitation and the Forest Eco~Tstem, ed L. S. Dochinger & T. Seliga. (1976). USDA Forest Service Gen. Tech. Rep. (NE-23), Columbus, pp. 425 58. Junge, C. E. & Werby, R. T. (1958). The concentration of chloride, sodium, potassium, calcium and sulfate in rainwater over the United States. Z Meteorol., 15, 417 25. Knudson, E. J., Duewer, D. L., Christian, G. D. & Larson. T. V. (1977). Application of factor analysis to the study of rain chemistry in the Puget sound region. In Chemometrics: theory and application, ed. B. R. Kowalski. ACS Symposium series 52. Washington, pp. 80-116. Koutrakis, P. & Spengler, J. D. (1987). Source apportionment of ambient particles in Steubenville, OH, using specific rotation factor analysis. Atmos. Environ., 21, 1511-19. Laird, A. R. & Miksad, R. W. (1978). Observations on the particulate chlorine distribution in the Houston--Galveston area. Atmos. Environ., 12, 1537J,7. Lefohn, A. S. & Krupa, S. V. (1988). The relationship between hydrogen and sulphate ions in precipitation a numerical analysis of rain and snowfall chemistry. Environ. Pollut., 49, 289 311. Lopes, J. C. coord. (1984-1985). Caracteriza¢~.o quimica das aguas de chuvas de Cubat~.o; impacto ambiental. S~_o Paulo, CETESB 2v. Martin, A. & Barber, F. R. (1978). Some observations of acidity and sulphur in rainwater from rural sites in central England and Wales. Atmos. Environ., 12, 1481-7.
233
Miller, E. A., Cooper, J. A., Frazier, C. A., Pritchett, L. L., Guimar~.es, F., Alonso, C. & Filho, B. (1985). Cubat~.o aerosol source apportionment study. CETESB, S~,o Paulo, 137 pp. Moldan, B., Vesely, M. & Bartnova, A. (1987). Chemical composition of atmospheric precipitation in Czechoslovakia, 1976-1984~I. Monthly samples. Atmos. Environ., 21, 2383-95. Moreira-Nordemann, L. M., Bertoli, J. L. R., Cunha, R. C. A. & Palombo, C. R. (1983). An~dise quimica preliminar das ~guas de chuva de Cubat~o; impactos ambientais. In 5 ° Simp6sio Brasileiro de Hidrologia e Recursos Hidricos. ABRH, Blumenau, pp. 339 50. Muhammed, A. S., lllman, D. L. & Kowalski, B. R. (1986). Chemometrics. John Wiley & Sons, New York, Chapter 6, p. 332. Oliveira, S. de (1985). Caracterizaq'~o meteorol6gica e aplica~.o de modelos de dispersfio. CETESB, S'~o Paulo. Oliveira, S. de & Sagula, M. A. L. A. (1985). Um estudo teorico e observacional do vento em Cubat~o. In 1Y' Congresso Brasileiro de Engenharia Sanit6ria e Amhiental, 1985, ago 18 23. Macei6, 7 pp. Orsini, C. M. Q., Artaxo Neta, P., Tabacniks, M. H., Soares, V. L. & Germano, T. M. (1982). Avalia~;ao preliminar da qualidade d o ar de Cubat~o. SEMA/IFUSP, S~o Paulo, 79 pp. Perkin Elmer Corporation (eds) (1982). Anah'tical Methods" Jor Atomic Absorption Speetrophotometrv, Perkin Elmer, Norwalk, Iv. Pratt, G. C. & Krupa, S. V. (1983). Seasonal trends in precipitation chemistry. Atmos. Environ., 17, 1845 7. Pratt, G. C., Coscio, M., Gardner, D. W., Chevone, B. I. & Krupa, S. V. (1983). An analysis of the chemical properties of rain in Minnesota. Atmos. Environ., 17, 347 55. Petrenchuk, O. P. & Selezneva, E. S. (1970). Chemical composition of precipitation in regions of the Soviet Union. J. Geophys. Res., 75, 3629-34. Ribeiro Filho, A. (1975). Comportamento do s6dio, magnesio, cfilcio e pot~issio nas precipitaq6es atmosf6ricas na Bacia do Paraguaqu--Ba. Universidade Federal da Bahia, Salvador, Brazil (Thesis in Portuguese, summary in English). Silva Filho, E. V. (1985). Estudos de chuva ficida e entradas atmosf6ricas de Na, K, Ca, Mg e C1 na bacia do alto Rio Cachoeira, Parque Nacional da Tijuca--RJ. Universidade Federal Fluminense, Niter6i, Brazil (Thesis in Portuguese, summary in English). Tavares, M. F. M., Vieira, B. M. and Moreira-Nordemann, L. M. (1983). An~ilise quimica de ions em ~iguas de chuva de regi~Ses naturais; correlaqOes corn aerossois atmosf6ricos. In 5 ° Simpfsio Brasileiro de Hidrologia e Recursos Hidricos. ABRH, Blumenau, pp. 351 76. Thornton, J. D. & Eisenreich, S. J. (1982). Impact of land use on the acid and trace element composition of precipitation in the north central US. Atmos. Environ., 16, 1945 55. Van Loon, J. C. (1985). Chemical Analysis of Inorganic Constituents o f Water. CRC Press, Boca Raton. 248 pp. Whitehead, H. C. & Feth, J. H. (1964). Chemical composition of rain, dry fallout and bulk precipitation at Menlo Park, California, 1957-1959. J. Geophys. Res., 69, 3319 33. Wold, S., Albano, C., Dunn, W. J., Edlund, V., Esbensen, K., Geladi, P., Hellberg, S.. Johansson, E., Lindberg, W. & Sjostrom, M. (1984). Multivariate data analysis in chemistry. In Chemometrics, Mathematics and Statistics in Chemistry, ed. B. R. Kowalski. D. Reidel Publishing Co., Dordrecht, pp. 17 95.
A MULTIVARIATE STATISTICAL ANALYSIS OF THE COMPOSITION OF RAINWATER N E A R CUBATAO, SP, BRAZIL Marilda Zanoni Mariotti Abbas, a Roy Edward Bruns. *b Ieda Spacino Scarminio c & Jose Roberto Ferrelra •
•
(/~
"Av. Santa Lidia, 461, 13.400 Piracicaba, SP, Brazil hlnstitute of Chemistry, State University of Campinas, CP 6154, 13.081 Campinas, SP, Brazil ~lnstitute of Chemistry, State University of Londrina, CP 6001, 86.051 Londrina, PR, Brazil d Research-Fishery Institute Secretary of Agriculture, Nuclear Energy Center for Agriculture USP Av. Francisco Matarazzo 455, 05001 S6o Paulo, SP, Brazil
(Received 28 October 1990; accepted 2 December 1991)
Abstract With the aim o f estimating the chemical composition o f bulk precipitation (wet + dry) in Cubat6o, rainwater samples were collected at several localities in the Cubatdo region f r o m M a y 1984 to October 1985. The levels o f some inorganic ions (Na +, Ca :+, K +, M g :÷, CI , S 0 4 , N H j , PO~ ) were measured by atomic absorption spectrophotometry, turbidimetrv and titration analysis. Correlation and Fisher discrimination indices, principal component and varimax loading and scores were determined in the multivariate statistical data treatment. The results showed that ionic concentrations in rainwater from Vila Parisi are significantly higher than those o f Cubat~o Centro, Santos and Serra do Mar. The ionic compositions o f the Vila Parisi rainwater seem to be mainly determined by local anthropogenic activities (industrial pollution). Besides the influence o f this factor on water quality, there is also a natural oceanic contribution involving Cl and Na ÷ at the other locations.
of precipitation, demonstrating their usefulness in identifying pollutant inputs (Knudson et al., 1977; Thornton & Eisenreich, 1982; Duysings et al., 1986; Moldan et al., 1987). The present paper involves the use of multivariate statistical analysis in the interpretation of the ionic compositions of rainwater falling in the vicinity of Cubat~.o, SP, Brazil. In spite of having the reputation of being the most air-polluted city in South America, little is known about the effects of pollutant sources on its rainwater. S T U D Y AREA
Cubatio, with a 160 km 2 area, occupies the southeastern portion of the state of Silo Paulo, being bordered on the north by the Serra do Mar mountain range and on the south by the cities of Silo Vicente and Santos on the Atlantic Ocean (Fig. 1). C u b a t i o presents distinct meteorological characteristics relative to the other areas in this region (Oliveira & Sagula, 1985). The ground wind velocities from the north-northeast during the night and early morning and from the south during the day are influenced by local topography with hills and crystalline elevations between 200 and 1000 m intercalated by flat low lying ocean inlets (Figs 2 and 3). The precipitation in the region is of orographic character and is influenced by the advances of frontal systems and sea breezes, with yearly variations ranging from 2400 to 2900 mm. The summer months of December through February are favored with higher precipitation quantities, between 870 and 1140 mm, whereas these amounts fall to between 230 and 335 mm in the winter. The atmospheric pressure oscillates between 1014 and 1018 rob. For the entire C u b a t i o region average temperatures are between 17 and 25°C. Temperature variations are observed for localities close to C u b a t i o indicating the occurrence of heat island
INTRODUCTION
For more than a century scientific documents have recorded interest in the investigation of the causes and consequences of variations in the chemical compositions of rainwater (Cowling, 1982). Sampling methods of this substrate have been studied with the objective of establishing secure and efficient procedures capable of minimizing the many inherent problems involved (Galloway & Likens, 1975). While the re-evaluation of sampling and chemical analysis methods adequate for rainwater studies has been undertaken, advances in the use of statistical and mathematical methods for treating and interpreting rainwater chemical compositions have been applied to the analysis of the ionic compositions * To whom correspondence should be addressed. Environ. Pollut. 0269-7491/92/$05.00 © 1992 Elsevier Science Publishers Ltd, England. Printed in Great Britain
225
226
M. Z M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira
4 \\
CUBATAO
¢,,.~ Fig. 1. Geographical location of Cubat~o. effects due to industrial concentration and urban occupation (Oliveira, 1985). Meteorological and air quality studies indicate the existence of two aerial basins: the center of Cubatfio and an outlying district called Vila Parisi. The central part is dominated by gaseous emissions resulting from the combustion of petroleum and its derivatives. On the other hand fertilizer, steel and cement complexes are common in Vila Parisi (Orsini et al., 1982; Miller et al., 1985). More than 20 base-industry complexes composed of about 110 factories, responsible for some 300 pollutant sources affecting air, water and soil (Galv~o Filho, 1987), operate in both these areas. EXPERIMENTAL
Samples collection Weekly samples of rainwater were obtained from the four localities (Fig. 4): Cubat~o Centro CC: Vila Parisi--VP; Santos--SS, and Serra do Mar SM, during the May 1984~October 1985 period (Abbas, 1989). When possible, daily samples were collected and kept at 4°C. After each weekly period, the daily samples were mixed and immediately analyzed. Chemical preservatives were not used. Although sample storage was carried out at low temperatures, samples can suffer the effects of microbial degradation which can influence the chemical speciation (Van Loon, 1985). During the entire sampling period, 48, 45, 49 and 45 weekly samples, respectively, were collected at these four sites.
Sixty centimeter diameter acrylic receptors (Ribeiro Filho, 1975) protected by white nylon cloths to prevent contamination (Koutrakis & Spengler, 1987) were used for total precipitation sample collections (Whitehead & Feth, 1964).
Analytical methods Atomic absorption spectrometry, by means of direct aspiration of the sample into the instrument nebulizer, was used for Na + and K ÷ determinations (Perkin Elmer Corporation, 1982). Ca 2+ and Mg 2+ were determined by EDTA solution titration, in the presence of eriochrome black T and murexide. The reaction of mercury thiocyanide with the consequent liberation of thiocyanide ions for free reaction with the iron (Ill) ions present in solution was used to determine CI . Total dissolved PO~ was determined with the ammonium molybdate method by means of a Technicon MT II W A T E R autoanalyzer. A turbidimetric method with barium sulfate was used to analyze for sulfate. The ammonium ion was determined by the alkaline phenol method, also using an auto-analyzer. Details of these methods can be found elsewhere (APHA, 1981). Multivariate statistical procedure A 187 x 9 data matrix was used, containing the ionic concentrations of the 187 samples collected. Each sample is described by the concentrations determined for eight chemical species (Na +, Ca 2÷, K ÷, Mg 2+, CI-, SO~-, NH~ and PO43-) and the precipitation volume
Multivariate statistical analysis of rainwater composition
227
%
o~
d3= o
\
0
I
2
3
4 Km
I~
Fig. 2. Wind directions (and relative velocities) in Cubat~o at night under high pressure conditions (anticyclone). obtained during the collection period. Since a basic objective of this paper is to characterize the variances and covariances of the various chemical measurements, the data have been autoscaled for the principal component and varimax calculations so that each measurement or variable has an average of zero and a variance of one. This standardization, besides avoiding the problem of unit selection, permits a comparison of these variances without undue inherent weighting of those variables which have higher values, even though the variations in the variable values are not that significant. Fisher indices, correlation coefficients and principal component and varimax factor scores and loadings were all calculated in the standard ways (Wold et al., 1984, Muhammed, 1986). R E S U L T S AND D I S C U S S I O N Averages, median values, and standard deviations of the chemical compositions of precipitation at the four sampling sites in the Cubat~o region are presented in Table 1 along with those values for the complete data set. Almost all ionic concentrations at all four sampling sites have standard deviations which are larger than their corresponding average values. The ionic concentrations are lowest at the Serra do Mar sampling site far from direct pollution sources. This site also has
the highest average precipitation volume, 107.90 mm, double the values observed at the other sampling stations. This inverse relationship between ionic concentrations and precipitation volumes was also observed in other studies (Silva Filho, 1985). Seasonal trends for the eight elements were investigated by constructing concentration versus precipitation volume graphs. Although not included here, the results compare well with those obtained by Pratt and Krupa (1983) at Hubbard Brook, with the higher levels of the chemical species corresponding to the lower precipitation rates. In part, seasonal variations probably explain the high standard deviations of the ionic concentrations observed and listed in Table 1 since the standard deviations for the rainfall volumes are also very high at all four sampling sites. This same tendency was observed by Dana & Easter (1987), for rainwater in the north eastern USA where seasonal variations of the ionic concentrations were larger than the variations in the precipitation volumes. In addition, although rainwater samples can have typical ionic compositions which are related to their sampling sites, differences in the ionic characteristics of rainwater samples from the same site can occur for other reasons. This indicates that inorganic species in water, are not conservative parameters (Galloway & Cowling, 1978). In general, rainwater collected from Vila Parisi had
228
M. Z. M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira b~. , j
c~
-~
too
•
o
/ I I %
\
Fig. 3. Wind directions (and relative velocities) in Cubatfio during the day under high pressure conditions (anticyclone). the highest ionic concentrations of all four sampling sites (SO~, PO 3 , Ca 2+, K +, Mg 2+ and NH~) with the exception of the Na + and CI ionic concentrations which were higher in Santos. Even though the lowest concentrations in Table 1 are for samples from the Serra do Mar station these values are among the highest yet observed (Petrenchuk & Selezneva, 1970: Galloway et al., 1982). Knowing that the chemical composition of rainwater is primarily determined by the nature of the atmospheric conditions (Junge & Werby, 1958) one might have been able to predict that the Vila Parisi rainwater would present the highest ionic concentrations when compared with rainwater samples from the other sites. Local air quality there is very poor due to high emissions of particulate material (Miller et al., 1985). Also morphological contrasts of land elevations contribute to a decrease in rainfall and a diversification of local wind velocities (Oliveira & Sagula, 1985). The ionic nature of rainwater in the region studied is probably determined by two main factors: one contribution from ions originating from the industrial pole and the other from natural emissions (Ribeiro Filho, 1975; Tavares et al., 1983). This is suggested with comparison of the C1/Na*, Mg2+fNa +, SO 2/Na +, K+/Na ~ and Ca2+/Na + ratios for rainwater at the four sampling sites with the values of these ratios found in natural sea water
(Table 2). The C I / N a + ratios are close to two at the CC, SS and SM sampling sites (using either average or median values), in good agreement with the ratio found in sea water, indicating the importance of ocean breezes on the ionic concentrations of rainwater at these locations. On the other hand, the value of this ratio is almost double at the Vila Parisi site indicating a strong regional influence which tends to mask the natural contribution from the ocean. Chloride sources are probably emissions from automobiles (Martin & Barber. 1978), cement and lime plants (Miller et al., 1985) and from the burning of fossil fuels (Laird & Miksad, 1978) for energy and fertilizer production. The sampling sites which present C 1 / N a + ratios close to the value found in sea water, also present high correlation coefficients for the Na + and CI concentrations in the samples studied: 0.98 (SS); 0.93 (CC) and 0.92 (SM). This relationship between the Na + and CI concentrations does not exist for the samples collected at Vila Parisi where the correlation coefficient is only 0-29. The values for the other ionic ratios in Table 2 for the sampling locations are much different than those found in sea-water. However the largest deviations From the seawater ratios occur for the Vila Parisi samples. It should be noted that almost all these ionic ratios are practically the same whether the calculations are made with average or median values.
Multivariate stat&tical analysis of rainwater composition
229 4 6 ° IB' W
46 ° 29'
23 ° 50' S
JARDIM CASQUEIRO
SANTOS
S.~O VICENTE
23 ° 5 8 '
O
1
2
I
I
I
ESCALA
3
I
4
I
5
km
I
GRA'FICA
Fig. 4. Locations of the sample collection stations: (1) Cubat~.o Centro; (2) Vila Parisi: (3) Santos; and (4) Serra do Mar. In an attempt to evaluate which ions are the most important in discriminating between rainwater from two different locations, Fisher indices of each variable, given in Table 3, were calculated for each pair of sampling sites. Large differences in the average values of an ionic concentration at two different sampling sites and small variances for these concentrations at each of these two sites result in large Fisher index values for this ion. Normally, large Fisher index values correspond to high discriminatory powers of the variable for the two sites being considered. Here, all ionic species present low Fisher index values (c. 6.00 × 10 3) when the sampling site pairs do not involve Vila Parisi. Thus rainwater samples from the Santos, Serra do Mar and Cubat~o Centro sites have similar ionic concentrations, at least for the ions studied here. On the other hand all sampling sites pairs involving Vila Parisi have higher Fisher index values for the SO4, Ca 2*, K +, N H L PO] and Mg 2+ ions. These values range between
6.00 × 10 3 and 21.00 × 10 3 whereas they are much smaller for Na +, C1 and the precipitation volume values, 0.01-5-17 x 10 3. As such, these index values are consistent with the relatively high average and median values found for all ionic species, except Na ÷ and C1, at the Vila Parisi sampling site and their significantly lower average and median values observed at the other sites. O f all the ionic species, SO~ and Ca -'+ have the highest average capability of discriminating between rainwater from Vila Parisi and the other sampling sites. Also, the Ca 2+ and SOl ionic concentrations are strongly correlated with each other (r = 0.81) and with Mg 2+ (r = 0.80 and r = 0.88, respectively). Working in an industrial area, Pratt et al. (1983) obtained lower correlation coefficients than those reported here, for the same chemical species associations and concluded that the major anions (SO~ and NO3) were associated with cations other than hydrogen.
M. Z. M. Abbas, R. E. Bruns, I. S. Scarminio, J. R. Ferreira
230
Table 1. Average, median and standard deviations of the average for ionic concentrations (mg liter i) and rainfall quantities of four sampling stations from May 1984 to October 1985
Variables
Total Av.
Rain (mm) Na + Ca > K+ Mg > CI SO4 NH~ PO]
Cubatgo Centro
Med.
66.75 36-60 (86-75) 3.54 2.20 (4.86) 8.54 2-50 (16.16) 1.49 0.40 (3.01) 1-64 0.80 (2-55) 8.40 5.00 (10.71) 15.50 5-00 (28.81 ) 1.30 0-41 (2.16) 8.16 0.58 (23-72)
Av.
Med.
55.19 35.65 (60.18) 3.62 2-10 (4.36) 4.32 2.16 (5.0l) 0.58 0.40 (0.60) 1.00 0.60 ( 1-01 ) 7.71 4.50 (8.14) 7.69 4.50 (9.07) 1.25 0.77 (1-63) 1.02 0-61 (1.49)
In an attempt to further interpret the rainwater compositions, principal c o m p o n e n t calculations were carried out on the complete data set and on the individual data sets o f each sampling site. Significant loadings for principal c o m p o n e n t s corresponding to eigenvalues larger than 1.0 are presented in Table 4. Since autoscaled values were used in these calculations the principal c o m p o n e n t s given in this table have variances which are statistically more significant than any o f the original variables listed in Table 1, The first two c o m p o n e n t s explain 54% and 18% o f the total variance. The first principal c o m p o n e n t has large contributions from the C a 2+, S O 4 , K + and M g 2+ concentrations, PC, = - 0 . 4 0 [ C a 2+] - 0.40[K +] - 0-42[Mg >] -0.42[SO~ ] - 0.33[PO4~] +-.. whereas the second one depends essentially on the Na ~ and C1 concentrations, P C 2 = 0-68[Na +] + 0.58[C1 ] + ... A graph o f the first principal c o m p o n e n t against the second is shown in Fig. 5. T w o different sample p o p u lations are suggested by the spreads and the directions o f the two groups o f samples. The relatively c o m p a c t
Vila Parisi Av.
Med.
56-34 28.30 (63.62) 2.95 2-40 (2-43) 24.88 15.70 (26-22) 4.55 3.30 (4.95) 3.69 1.90 (3.91 ) 10.34 6.00 (11.10) 47.29 33.00 (44.42) 3.17 1.93 (3.28) 31.00 18.42 (40.72)
Santos Av.
Med.
49-81 31.30 (52-49) 5.18 3.40 (7.58) 3.95 2.00 (4.02) 0.69 0.50 (0-76) 1.05 0.70 ( 1.26) 10.64 7-00 (15.18) 4.50 3.00 (6.17) 0.47 0.21 (0.75) 1.46 0.60 (3-56)
Serra do Mar Av.
Med.
107.90 63.90 (136.30) 2.27 1.60 (2.37) 1-73 1.00 (2.79) 0-28 0.20 (0.30) 0-90 0.51 ( 1.92) 4.67 3.50 (3.86) 4.04 2.00 (5.93) 0.36 0-18 (0.62) 0.23 0.12 (0.39)
g r o u p with an almost vertical orientation is c o m p o s e d mostly o f samples from the CC, SS and SM sites. The more disperse g r o u p contains a larger variance and is parallel to the first principal c o m p o n e n t axis. This c o m p o n e n t is strongl]¢ influenced by the values o f the Ca 2+, K +, Mg >, SO; and PO 3 concentrations, and discriminates this g r o u p o f samples from the other. In contrast, the second principal c o m p o n e n t , which depends essentially on the Na* and CI concentrations, does not differentiate between these two groups. Finally, the principal c o m p o n e n t s listed in Table 4 were subjected to varimax rotations. Varimax analysis has been shown to be useful in indicating factors which provide important contributions to rainwater ionic contributions ( K n u d s o n et al., 1977). The loadings and percentage variances for the varimax factors for all sampling sites are given in Table 5. The first factor accounting for 48'7,, of the total variance is c o m p o s e d o f large contributions from the Ca -`+, K +, M g -~+, S O 4~ and PO 3 concentrations. This factor evidently describes anthropogenic sources of the ionic concentrations in rainwater. The second varimax factor is determined principally by N a + and CI con-
Table 2. Ionic ratios for seawater and rainwater samples from the Cubatfio Centro, Vila Parisi, Santos and Serra do Mar stations collected between May 1984 and October 1985
Ions
Seawater
Precipitation Cubatfio Centro
CI/Na + Mg>/Na" SO4/Na + K~/Na * Ca2+/Na +
1.85 0.13 0.25 0.04 0.04
" Calculated using average values. h Calculated using median values.
2-13" 0.28 2.11 0.16 1.20
(2-14) h (0.28) (2-14) (0.19) (1.03)
Vila Parisi 3-50 (2.50) 1.25 (0.80) 16.03 (13.75) 1.54 (1.38) 6.29 (6-54)
Santos 2.07 0.20 0.87 0.13 0.76
(2.05) (0.21) (0.88) (0.15) (0.59)
Serra do Mar 2.06 0.40 1.78 0.12 0.76
(2.19) (0.32) (1.25) (0.13) (0.63)
Multivariate statistical analysis of rainwater composition
231
Table 3. Fisher index values (× 10 3) for ionic concentrations of precipitation collected between May 1984 and October 1985 at Cubatio Centro, Vila Parisi, Santos and Serra do Mar" Cubat~.o× Vila Centro Parisi
Cubat~.o × Santos Centro
Cubat~.o× Serra do Centro Mar
Vila x Santos Parisi
Vila × Serra do Parisi Mar
Santos × Serra do Mar
Ions
F.I. u
Ions
F.I.
Ions
F.I.
Ions
F.I.
Ions
F.I.
Ions
F.I.
SO4 K* Ca 2+ PO~
16.93 14-08 13.16 12.03 9-82 6.03 0.79 0.38 0.04
NH4+ SO 4 CI Na + K* PO 3 Rain Ca 2+ Mg 2+
3-93 1.73 0.65 0.63 0.29 0-27 0.09 0.07 0.01
NH4+ PO2 Ca -,+ K+ Rain CI SO 4 Na* Mg 2+
5.53 5.43 4-29 4.19 2.76 2.39 2-37 1.57 0.05
SO4 NH] Ca 2+ K+ PO 3 Mg 2+ Na + Rain C1
20.20
SOj Ca 2+ K+ NH4+ PO~ Mg 2+ CI Rain Na +
20.70 17.13 16.50 15.81 12.68 9-16 5.17 2.62 0.89
K+ Ca 2+ Rain C1 Na + PO~ NH4+ Mg 2+ SO4
5-31 4.29 3.48 3.07 2.75 2-40 1.29 0.92 0.06
M g 2+
N H4+ C1 Na + Rain
14-26 13.81 13.15 11.60 9.15 1.61 0.13 0-01
"The Fisher Index is defined as F.I. = ( X i - X2)/(S1 + Sff ) where X~ and 32 are the average values lbr two sampling sites and S~ and S~ their variances. c e n t r a t i o n s a n d appears to represent the influence o f sea breezes o n the ionic c o m p o s i t i o n s of the rain-water. The v a r i m a x factors for the C u b a t ~ o Centro, Santos a n d Serra do M a r data sets are all characterized by strong Na* C1 factors, whereas this factor is missing for the Vila Parisi sample data. Most certainly this factor, which represents the oceanic influence o n the ionic c o m p o s i t i o n s of the rainwater samples, has been masked by ions originating from anthropogenic sources. Oceanic spray appears to be a relevant factor c o n t r i b u t i n g to the neutrality of r a i n w a t e r samples (average p H of 6.4, m a x i m u m p H of 7-7 a n d m i n i m u m p H of 5-0) for the Santos s a m p l i n g sites. This statement is supported by the 0.98 correlation coefficient between N a ÷ a n d CI f o u n d for this s a m p l i n g location. In Vila Parisi, besides the oceanic sprays, the alkaline t e n d e n c y of the precipitation (Lopez, 1984-1985) is also due to i n l a n d element sources (Tables 2 a n d 5) such as p h o s p h a t e which is present in high c o n c e n t r a t i o n s in particulate atmospheric material (Miller et al., 1985). M o r e i r a - N o r d e m a n n et al. (1983) reported that rain-
water samples from the C u b a t ~ o C e n t r o collection site were acidic (pH = 3.6). In this case the influence of ocean spray is n o t effective in neutralizing these samples due to the existence of a n t h r o p o g e n i c activities which are more p r e d o m i n a n t in C u b a t h o than in Santos. P r o b a b l y this relatively high hydrogen ion c o n c e n t r a t i o n is due to a soil factor, in part originating from crystalline rocks which are poor in basic minerals or in dissolved metal cations ( G o r h a m , 1976). Also, the percentages of sulphate a n d chloride ions associated with cations other than h y d r o g e n m a y be i m p o r t a n t in c o n t r o l l i n g the alkalinity or acidity of rainwater samples as described by Lefohn a n d K r u p a (1988).
CONCLUSIONS The rainwater samples analyzed in this project appear to be of two distinct types. O n e type corresponds to samples from all four s a m p l i n g stations a n d seems to have ionic c o n c e n t r a t i o n s influenced by n a t u r a l a n d a n t h r o p o g e n i c sources c o m m o n to the whole region
Table 4. Principal component Ioadings from rainwater samples collected between May, 1984 and October, 1985 at Cubatho Centro, Vila Parisi, Santos and Serra do Mar" Variables
All sites 1
Rain Na + C a 2+
K~ Mg 2. CI SOj NH~ PO2 Eigenvalueh % Variance
2 . 0-68
-0.40 -0.40 -0-42 0-58 -0.42 -0.33 4.87 54.1
Cubat~.o Centro
1.61 17.9
1 .
2
. . -0.34 0.52 -0.34 -0-40 -0.36 -0.33 0.47 --0-45 0-31 -0-36 5.07 1-30 56.3 14.4
Vila Parisi 1
2
. . -0.31 -0.41 -0.38 -0-38 -0-32 0.42 -0.31 0.35 -0.41 -0.54 --0.43 5-14 1.18 57-I 13-1
Santos 1
2
Serra do Mar 3
0.48 -0-40 0.39 0-39 -0-39 -0.39 0.38 --5.31 59.0
--
---
0.35 --0.47 0-39 1.36 15.1
0.54 -0.80 1-03 11.4
1
2
0-58 -0.31 -0.33 -0.41 0.39 ---0-40 0.30 -0.39 -0.39 0-61 4-94 1.56 54-9 17.3
3 0.33 0-50
0.55
0.41 1.26 14-0
" All principal components loadings with absolute values larger than 0-3 are included in this table. The principal component loadings are normalized to one. h Only principal components with eigenvalues greater than 1 are included in this table.
M. Z. M. Abbas, R. E. Bruns, I. S, Scarminio, J. R. Ferreira
232 0,84"
Cubat6o
Centro
,
Vila Parisi
x
Santos
•
Serra
do Mar
o
0,63 -
0,42!
£3 13.
0,22-
I
o" I
I
•
I
• l e• o
0,01-
o
X )~ X X X
X
×
X
0,20 - 0,92
-0,48 '
-0,70 '
I
Xx X
X
X X
X X
X
-0, 2 7
leo X XO0000 ×QI I~ X X I ~11~110 X XIXXI XIX IO0•EO XX X Xll X O0 o •
X
+0,'17
-0,05 '
PC t
Fig. 5. Principal component projection (lst and 2nd principal components) of ionic concentrations of rainwater samples collected at the four sampling stations. s t u d i e d in this p r o j e c t . T h e o t h e r t y p e is c h a r a c t e r i z e d by s a m p l e s f r o m o n l y the Vila Parisi s t a t i o n . S t r o n g local influences n e a r this c o l l e c t i o n site severely m a s k the o c e a n i c i n f l u e n c e c o n t r i b u t i n g to the i o n i c c o n c e n t r a t i o n s c o n s i d e r e d in this r e p o r t . Statistical a n a l y s e s using Fisher index values and principal components a n d v a r i m a x f a c t o r s as well as the m o r e c o m m o n l y e m p l o y e d statistical e s t i m a t o r s s u c h as a v e r a g e s a n d m e d i a n values, s t a n d a r d d e v i a t i o n s a n d c o r r e l a t i o n coefficients all p r o v i d e a c o n s i s t e n t i n t e r p r e t a t i o n o f the rainwater data.
O p e r a t i o n a l difficulties h i n d e r e d the s t u d y r e p o r t e d here. M o r e s a m p l i n g s t a t i o n s w o u l d h a v e p e r m i t t e d g r e a t e r r e s o l u t i o n in o u r analysis, p e r h a p s a l l o w i n g for the i d e n t i f i c a t i o n o f specific p o l l u t i o n sources. A l s o , the chemical analysis should have included other ionic species, specially the h y d r o g e n ion. D e t e r m i n a t i o n s o f p H w d u e s w e r e o n l y c a r r i e d o u t for the s a m p l e s o b t a i n e d f r o m the S a n t o s s t a t i o n . H o w e v e r the a n t h r o p o g e n i c c h a r a c t e r i s t i c s o f the C u b a t g o r e g i o n are so p a r t i c u l a r t h a t this r e p o r t seems w a r r a n t e d in spite o f its l i m i t a t i o n s .
Table 5. Varimax factor Ioadings for rainwater samples collected between M a y 1984 and October 1985 at Cubat'~o Centro, Vila Parisi, Santos and Serra do Mar"
Variables
All sites 1
Rain Na + Ca 2+ K+ M g 2+ CI SO 4 NH2 PO2 % Variance
. -0.89 -0-91 -0.83 --. -0.92 -0-80 47.6
Cubat~o Centro
2
. 0-94 --0-91 ---24.2
1
.
. -0-79 --0.82 -0.71 -0-78 37-1
Vila Parisi
2
.
1
. 0.95 . . 0.70 0.71 0-90 -
33.6
Santos
2
. . -0.82 . . 0.88 . -0.74 -0.74 0-76 0.78 0.81 37-8 32.3
1
-0.97 .
. -0.93 -0.97 -0.85 --48.5
2
Serra do M a r 3
0-71 . .
.
.
--0.89 -22.8
---0.96 14.2
1
2
3
0-83 . 0.91 0.85 -0.96 -0.72 -0.92 -44-9
0.94 ---0.94 --24.6
-----0.88 16.5
Only varimax loadings with absolute values greater than 0.7 have been included in this table. The varimax factor loadings are normalized to the values of their respective eigenvalues.
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