Characterization of precipitation at Agra

Pergamon

Atmospheric Environment Vol. 30, No. 20, pp. 3405 3412, 1996 Copyright (C3 1996 Elsevier Science Ltd Printed in Great Britain. All fights reserved P I I : S1352-2310(96)00049--0 1352 2310/96 $15.00 + 0.00

CHARACTERIZATION OF PRECIPITATION AT AGRA A. S A X E N A , U. C. K U L S H R E S T H A , N. K U M A R , K. M. K U M A R I a n d S. S. S R I V A S T A V A * Department of Chemistry, Dayalbagh Educational Institute, Dayalbagh, Agra 282 005, India (First received 20 January 1993 and in final form 12 December 1995) Abstract--In the present study, the precipitation at Agra city was studied during July-September, 1991. Thirty two samples were collected at Dayalbagh which is a suburban area in the NW of the city with no major industrial activities and minimum traffic density. The study comprised the determination of F, C1, NO3, SO4, Na, K, Ca, Mg, NH4, Fe, Cu, Zn, and SiO2 in the wet-only samples. On the basis of the neutralizing factors and correlations, it has been determined that in our region, acid neutralization is brought about by calcium rather than the ammonium ion. The Ca/K and Ca/Mg ratios indicated that only l 0 percentile of the values in the rainwater samples correspond to local soil and the rest could be attributed to transported soil. The data were also subjected to factor analysis based on principal component analysis, using the SPSS software. The rotated factor matrix grouped the variables into four factors. The first factor includes Cu, Zn, Fe and Na which may be attributed to industrial activities and scavenging processes. Factor 2 clusters Ca, HCO 3, NO3, SO4, C1 and Mg together, all of which are soil-derived species. Factor 3 groups K and NH 4 which may be attributed to biogenic combustion emissions. Factor 4 includes F and SiO2 which are probably because of their emission in the process of lime pulverization. Copyright .(~ 1996 Elsevier Science Ltd Key word index: Precipitation, alkaline, neutralization, sources. 1. I N T R O D U C T I O N

"Emissions of alkaline substances can significantly influence precipitation acidity by neutralizing some fraction of the acids" (Placet and Streets, 1987). The inventory of sources having a possible significance in alkaline emissions include both natural and anthropogenic activities. Among the natural processes, wind blown dust from open lands, sites lacking a protective vegetative cover, construction sites etc. are the prominent sources. In the tropics however, the atmosphere has a high dust load almost throughout the year due to common occurrence of "dust devils". Dust devils are local convective circulations that arise particularly in arid and semi-arid environments: high local instability leads to thermal updrafts and stretching of vortex tubes causing locally high winds followed by efficient vertical transport (Gillete and Sinclair, 1990). When turbulent winds prevail dust can be lifted upward to a height of 1500-2000 m (Winkler, 1976). In India, soil has been considered as a major contributor of particulates in the atmosphere, owing to its dusty nature (Khemani et al., 1985; Mahadevan et al., 1989). Studies reported so far on the chemical composition of rainwater and aerosols in the Indian region relate high alkaline rainwater to low contribution of secondary aerosols (SO4 and NO3) from

* Author to whom correspondence should be addressed,

anthropogenic sources and high contribution of primary aerosols (Ca, K and Mg) from soil. The present communication deals with the analysis of rainwater to study the relative roles of natural and anthropogenic sources in determining rainwater chemistry in Agra. Agra is situated in the north central part of India. It is a semi-arid region bounded by the desert of Rajasthan on two-thirds of its peripheries. The city is known for the foundry and forging industry. The foundries use cupolas as the melting units that use common fuels like hard coke, steam coal, wood and oil. The cupola emissions include both gases and particulates. Gaseous emissions include CO, SO2 and NOr. SO2 concentrations vary between 68 and 108 m g m -3, while NO2 has been reported to vary between 0.2 and 0.6 m g m -3 (PCRI, 1988). The other industrial activities in Agra are rubber processing, lime oxidation and pulverisation, chemicals and engineering and brick and refractory kilns. Besides these the mobile sources also contribute a significant amount of CO, HC, NOx, and SO2 (CUPS, 1987). The concentration of SO2, N O x and dust are reported to be 47.1/~gm -3, 60.2/~gm -3 and 245 ~gm -3, respectively, in the ambient air (PCRI, 1988).

2. S A M P L I N G A N D A N A L Y S I S

Rainwater (wet-only) samples were collected in the monsoon season of 1991 at Dayalbagh, located to the

3405 AE 30:20"C

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A. Saxena et al.

north of the city. The site is surrounded by areas almost exclusively devoted to agriculture and has low residential density. A national highway lies about 2 km from the sampling site. Although there are no industries in the immediate vicinity of the sampling site, during the monsoon the site becomes downwind with respect to the city's pollution sources. The prominent wind directions during the monsoon are SW, SE, NW and NE, which correspond to the industrial sectors of the city. Samples were collected on the roof of the faculty building about 8 m from ground level and 1 m from the floor of the roof. Sampling was done manually on an event basis where an event may be defined as the span of rain between two dry periods of duration greater than 1 h. Polyethylene bottles and funnels properly washed with detergent and HNO3 and then with deionised water were used for sample collection. The collectors (bottles and funnels) were deployed as soon as the rain began and were retrieved immediately after the rain stopped. A total of 39 samples had

sufficient volume for analysis of the studied ions. This represented about 78% of the total rainfall of the season in the city. After retrieval, the volume of the rain collected was measured and pH and conductivity were measured in an aliquot of the sample. After these measurements, the remaining samples were filtered into two clean polyethylene bottles. One part was stored under refrigeration and was used for the analysis of anions, while the other part was acidified with HNO3 and was used for cation analysis. The anions F, CI, NO2, NO3, Br, SO4, and PO4 were analysed by Dionex 2000i/SP Ion Chromatograph using a CO3/HCO3 buffer as eluant (1.7 mM Na/CO3/1.8 mM NaHCO3) and 25 mN H2SO4 as regenerant. The cations Na, K, Ca, Mg, Zn, Cu were determined by atomic absorption and emission techniques while NH4, Fe and Si (as SiOz) were determined by colorimetric methods. The analytical precision, R.S.D., accuracy and detection limits are given in Table 1.

Table 1. Analytical protocol

Parameter Na

Ca Mg F

Fe

5i02

0.02

0.15

0.02

0.01

0.06

0.13

0.07

0.4

0.15

0.05

0.45

0.16

0.07

0.2

Dionex 2000 i/SP Ion Chromatograph Dionex 2000 i/SP Ion Chromatograph Dionex 2000 i/SP Ion Chromatograph Hitachi 2000 UV-VIS Spectrophotometer

0.17

0.89

0.5

0.06

0.03

0.12

0.04

0.02

0.12

0.1

0.05

0.25

AAS, Perkin Elmer Model 2380 AAS, Perkin Elmer Model 2380 Hitachi 2000 UV-VIS Spectrophotometer

0.18

0.08

0.2

0.006

0.002

0.01

0.05

0.01

0.13

0.14

0.08

0.4

AAS, Perkin Elmer Model 2380 AAS, Perkin Elmer Model 2380 AAS, Perkin Elmer Model 2380 AAS, Perkin Elmer Model 2380 Dionex 2000 i/SP Ion Chromatograph

Atomic emission, Air/CzH2 766.5 nm Atomic absorption, Air/CzHz 422.7 nm Atomic absorption, Air/C2H2 285.2 nm Suppressed Ion Chromatography Eluant = 1.8 mM Na2CO3/1.7 mM NaHCO3, 2 mlmin- 1; Regenerant = 25 mM H2S04, 3 5 ml rain- 1

SO4

Cu

0.05

Atomic emission,

NO3

Zn

Analytical detection limit (~tgml- 1)

Instrumentation

CI

NH4

Accuracy (rtg ml- 1)

Technique Air/CzH2 589.0 nm

K

Precision (lagml- 1)

Colorimetric, as Indo phenol blue 620 nm Atomic absorption, Air/C2H2 213.9 nm Atomic absorption, Air/CzHz 324.7 nm Colorimetric by o-phenanthroline 510 nm Colorimetric as Molybdenum blue 795 nm

Characterization of precipitation at Agra Prior to interpretation, screening of the data was done by means of (i) F-ratio test to confirm that the variation in concentration of the constituents was real, i.e. inherent in the samples. The F-ratio defined as the ratio of sample variance (s 2) to twice the analytical variance (&2) was beyond the critical limits indicating that the variation in the concentration were statistically significant (Whitehead and Feth, 1964). (ii) Check on ionic balance was used as another data filtration step. In using this as the criterion, a degree of subjectivity has been observed. Previous studies on precipitation in India have revealed a cationic excess in rainwater (ECations/ EAnions = 1.3), which has been explained to be due to several unmeasured anions (Handa et al., 1982; Khemani et al., 1985, 1987; Varma, 1989; Mahadevan et al., 1989). For this data record, a sample exhibiting a ratio greater than 1.3 was eliminated. Exclusion of

103

3407

such samples resulted in 32 samples whose cation-toanion ratio is 1.1. The anion sum here includes the ions F, NO2, Br, PO4 and HCO3 besides the major ions CI, NO3 and SO4. (iii) Finally, for the set of 32 samples considered in this study, linear regression of cation sum on anion sum gave a r value of 0.8 indicating that the quality of the edited data is good. All the regression (correlation) results referred to in this paper were calculated by the reduced major axis technique (Miller and Kahn, 1962; Hirsch and Gilroy, 1984).

3. RESULTSAND DISCUSSION For each species volume weighted concentrations have been expressed in #eqf-~. The concentration distributions are skewed showing a lognormal behaviour. Figure 1 depicts the minimum, maximum values,

Ca HCO 3

~a m

I I

A

Mg

A

K -

10 2 A

V

v_

G

sio2 NH4

Fe

I-

V

F~ V

_A _v

G

'n A

.T

V 1°1

IV

--

G

C

~.2'

A q 1"7

H

1.0

Legend Max A I Arithmetic mean ~ V o l u m e wtd. mean Geometric mean

v

0.1

i ~/~ 0.09

(N = 32)

Fig. 1. Primary statistics of chemical constituents in precipitation.

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A. Saxena et al.

arithmetic, geometric and volume-weighted means and standard deviations. Volume-weighted mean and standard deviation of volume-weighted means were calculated by the formula used by Dayan et al. (1985). The minimum recorded pH value was 6.1 and the maximum 7.3, while the volume-weighted mean pH was 6.9 all indicating an alkaline nature as compared to the reference level of 5.6 (Charlson and Rodhe, 1982). From the data, the average relative magnitude of ionic species concentration in precipitation follows the order Ca > HCO 3 > Na > SO4 > Mg > CI > NO3 > NH4 > K > F > H. This order holds for arithmetic, geometric and volume-weighted means. 3.1. Sea-salt contribution Since these samples are m o n s o o n rain samples, seasalt c o m p o s i t i o n s were d e t e r m i n e d considering N a as the sea-salt tracer. These ratios were estimated by the slope of the regression line between each of C1, SO4, Ca, Mg, K a n d N a a s s u m i n g t h a t in the absence of any c o n t r i b u t i o n o t h e r t h a n sea salt, the intercept of the regression line s h o u l d n o t be significantly different from zero a n d the slope s h o u l d equal the sea-salt ratio with respect to Na. These regression lines have been plotted in Fig. 2a-e. It is evident from the plots t h a t the calculated ratios deviate considerably from the sea water ratios, indicating a modification of the sea-salt

constituents along the trajectory of the monsoon air masses. Agra is situated about 2000 km away from both the Bay of Bengal and the Arabian Sea, the large divergence in the ratios is evidently due to the distance of the sampling location from the sea. The observed C1/Na ratio (0.60) deviates considerably from the sea water ratio (1.8) suggesting either a fractionation of C1 or enrichment of Na (Ericksson, 1959). The elevated Ca/Na, Mg/Na and K / N a ratios are indicative of the presence of some other component, probably soil. 3.2. Ionic correlations Correlation matrix for the ion pairs is presented in Table 2. The highest correlations appear for the ion pair N O 3 and SO4 (r = 0.96), followed by Na and NO3; Ca and C1 (r = 0.75); Mg and SO4 (r = 0.71); C1 and SO4 (r = 0.71); Ca and Mg (r = 0.70); Na and SO~ (r = 0.65). Other relatively good correlations were observed between NH4 and N O 3 (r = 0.59); Ca a n d N O 3 (r = 0.57); Mg and C1 (r = 0.58) and C1 and NO3 (r = 0.55). Most of these well correlated pairs have common sources or occur in precipitation as a result of atmospheric chemical reactions. The ions N O 3 and SO4 are probably well correlated because of the similarity in their behaviour in precipitation and the co-emission of their precursors

(b)

(a) 3.0

3.0-

2.5

2.5-

o 2.0 "o

o 2.0

o 1.5

_~1.5

(c) 3.0 2.8

:/

_

1.0 0.5

~ I

I

':..

I

I

I

I

0.5 1.0 1.5 2.0 2.5 3.0 3.5 Sodium

(d) 2.0

1.8 1.6 1.4 E •~ 1.2 0e~

~ 1.o

2.2

0.5 0

2.0

I~¢¢~""c"r,

I

o

I

I

I

1.8 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Sodium ~1.6

(e)

~

2.0-

1.01

../

1.4 f •~ 1.2

0.8 0.6 0.4

./ :~ o.s;

0.6

0.6

0.4

0.4 ~

0.2

• ° o/° .

o~.°°

0.2 I I I I I I 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Sodium

0

1.4 1.2

1.8~

1.6~-

N 0.8

0

2.4

I.O

;}/ I

2.6

0.2

sea s~_~._,.,_,-------

0

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Sodium

Sea salt...__..._.

I

I

I

I

I

0.5 !.0 1.5 2.0 2.5 3.0 3.5 Sodium

Fig. 2. Variation of major ions with respect to sodium ion concentration (log-log plot).

J

i

J

i

Characterization of precipitation at Agra

3409

Table 2. Ion pair correlations C1 CI NO 3 SO4 HCO 3 H Na K Ca Mg NH 4 F

NO 3

1.00 0.55** 1.00 0.71"* 0.96** 0.27 0.40 0.21 0.24 0.46 0.83** 0.13 0.24 0.75* 0.57** 0.58* 0.71"* - 0.01 0.59* 0.0007 0.23

SO,,

1.00 0.40 0.20 0.65* 0.23 0.71"* 0.73** 0.43 0.08

H

HCO 3

1.00 -- 0.11 0.41 0.09 0.43 0.22 0.51 0.06

1.00 0.35 0.08 0.16 0.08 0.13 - 0.10

Na

1.00 0.50* 0.67* 0.42* 0.66* 0.01

K

1.00 0.19 0.29 0.29 - 0.14

Ca

1.00 0.70** 0.08 0.06

Mg

1.00 0.30 - 0.01

NH 4

1.00 - 0.20

F

1.00

Note. 1-tailed signal: P = 0.05, * = 0.01, ** = 0.001.

SO2 and NOx. Ca and Mg may be correlated due to the common occurrence of these species in soil and dust. Similarly, the correlations between Ca and SO4, Mg and SO4, Ca and NO3, Mg and NO3, Ca and C1 and Mg and C1 probably result from the reaction of the acids H2SO4, HNO3 and HC1 with alkaline compounds rich in Ca and Mg carried into the atmosphere by wind blown dust. This shows that wind carried dust and soil play an important role in precipitation chemistry (Applin and Jersak, 1986; Munger, 1982; Khemani et al., 1985, 1987; Varma, 1989; Casado et al., 1992). Among the compounds of ammonium, ammonium sulphate compounds are known to predominate in the atmosphere (Seinfeld, 1986), but this does not appear to be universally true as evident from the correlations between NH4 and NO3 (r = 0.59) and NH4 and SO4 (r = 0.43). On the basis of the correlation values it may be said that in our conditions NH4NO3 appears to be in greater dominance than NH4HSO4 and (NH4)2SO4. Dominance of NH4NO3 has been reported earlier also (Sequeira, 1982). 3.3. Soil constituents The recorded pH values of rainwater correspond to values reported for dust affected rain and the various correlations also indicate the entrainment of soil and dust particles in precipitation. Local soil was analysed for the major water soluble ions to study the effects of local soil on rainwater composition. Ten soil samples were collected from separate locations spread randomly across the sampling site. 0.5 g of dry, sieved (250 ~tm) soil was shaken with 50 ml of deionised water for half-an-hour. The soil solution so obtained was filtered through Whatman 41 filter, another 50 ml of water was added in fractions during filtration to recover the maximum water soluble ions. The final volume of the solution was maintained to 100 ml. The major anions and cations in the soil extracts were determined as in the rainwater samples. The soil composition indicates that the local soil has the potential to significantly alter the composition of rain. However, a comparison of the ratios of Ca/K

and Ca/Mg in both soil and precipitation showed that only 10 percentile values in rain corresponded to the ratios in soil. Thus it is surmised that in addition to local soil, other sources also contribute a substantial amount of the above cations to precipitation. The possible contributors could be transported soil, crustal emissions from tilling operations, unpaved roads and fine particulate emissions from the local industries rich in these components. 3.4. Acid neutralization The correlations between the acid ions NO3 and SO4 and the cations NH4, Ca and Mg indicate that the acidity in precipitation is neutralized. The neutralizing action was further confirmed by establishing correlation between various anion and cation combinations as shown in Table 3. The correlation coefficient of SO4 with Ca and Mg individually is 0.71 and 0.73 and of NO3 with Ca and Mg is 0.57 and 0.71, respectively. With the sum of Ca and Mg (Ca + Mg) and SO4, the coefficient raises to 0.77, the addition of K to the sum lowers the coefficient to 0.63 while the inclusion of NH4 to the cation sum raises the coefficient to 0.82 and 0.83. A similar behaviour is observed when the sum of anions NO 3 and SO4 were correlated with the various cation combinations. These correlations therefore indicate the significance of these ions in acid neutralization.

Table 3. Correlation coefficientsfor anions vs cations combinations

Ca Mg K NH,~ (Ca + Mg) (Ca + Mg + K) (Ca + Mg + K + NH4) (K + NH4) (Ca + Mg + NH4)

NO 3

SO4

0.57 0.71 0.24 0.59 0.57 0.58 0.79 0.62 0.80

0.71 0.73 0.23 0.43 0.77 0.63 0.82 0.48 0.83

(NO3+ SO4) 0.58 0.75 0.29 0.53 0.64 0.65 0.82 0.54 0.82

3410

A. Saxena et al.

Neutralization factors were calculated to evaluate the relative neutralization of rainwater by the crustal components and ammonia. Neutralization factors (NF) were calculated as [NH4] NFNm = 2[SO4] + [NO3] (Possanzini et al., 1988) NFca =

[Ca] [SO,] + 2[NOa]

NFMg =

[Mg] [SO,] + 2[NO3]

"

The NFNH4 was less than both NFca and NFM~ the factors being 0.09 for NH4, 0.57 for Mg and 1.8 for Ca, revealing that the crustal components neutralize a larger fraction of the available acid. This order of dominance is also confirmed by a stepwise multiple regression analysis on the data taking HCOa as the dependent variable. HCO3 = C + 0.58(Ca) + 0.42(Mg) + 0.38(NH4) C = - 68.15;

Catalytic oxidation of SO2 and HNO3 by dust partides is extensively reported in literature (Winchester et al., 1986; Wolff, 1984; Casado et al., 1992; Ashu Rani et al., 1992). The possibility of SO4 and NO 3 being present as primary aerosol is supported by the fact that the local soil contains sufficient amount of SO4 and NO3 and it is also known that gypsum is added to soils in the adjoining regions of Agra to make it fertile. The abundance of SO4 and NO3 is relatively constant with altitude, while ammonia and ammonium ions diminish in concentration rapidly with height (Harrison and Pio, 1983). Therefore, it is assumed that at cloud level H2SO4, HNO3 and NH4HSO4 predominate over (NH4) 2SO4 and NH4NO3 (Possanzini et al., 1988). On the basis of the above facts, it appears that at cloud level neutralization is brought about by reaction of cloud condensation nuclei containing Ca and Mg with H2SO4 and HNO3, while below cloud level neutralization is brought by both ammonia and adsorption of SO2 by suspended particulate matter containing Ca and Mg.

r 2 = 0.98. 3.5. S o u r c e c o n t r i b u t i o n s

These correlation analyses indicate an association of SO4 and NO3 with the soil constituents, rendering alkalinity to precipitation. The following have been hypothesised to be the possible mechanisms leading to this association: (i) S O 2 and HNOa are either adsorbed on particulate matter, react with soil derived CaCO3 and MgCO3 and form secondary aerosols, (ii) SO4 and NOa are present as primary aerosol derived from either long range transport or locally eroded soil and (iii) H2SO4 and HNO 3 in the liquid aerosol react with airborne soil and ammonia.

Factor analysis was carried out on the data in an attempt to determine the factors underlying the intercorrelations between the measured species. In this analysis, concentrations of few metal ions such as Fe, Cu, Zn and Si (as SiO2) that are known to be associated with the industrial activities in the city were also included in the database. Undetectable concentrations for any species were substituted by 0.5 LOD value of the concerned species (Cohen et al., 1991). Factor analysis was carried out by the principal component method using the SPSS PC + version 3 software. Initial factors were extracted from a matrix of correlations derived from standardized variables.

Table 4. Factor solution of chemical constituents in precipitation Variable Zn Cu Fe Na Depth Ca HCO3 SO4 NO3 C1 Mg K NH4 F SiO2 Eigenvalue % Variance Cumulative % Predicted contributor

Factor 1

Factor 2

Factor 3

Factor 4

0.91 0.90 0.90 0.90 0.88 0.03 0.08 0.12 0.15 0.37 - 0.21 0.05 0.34 - 0.04 0.27

- 0.3 - 0.07 - 0.02 0.18 0.36 0.94 0.93 0.90 0.88 0.82 0.70 0.04 -- 0.32 0.05 - 0.04

0.01 0.28 0.04 - 0.18 0.03 0.04 0.15 0.09 -- 0.10 - 0.24 -- 0.02 0.84 0.74 - 0.17 - 0.69

0.08 - 0.08 0.05 - 0.02 - 0.01 0.10 - 0.06 - 0.20 -- 0.25 0.06 0.38 0.17 0.34 0.79 0.51

6.02 37.70 37.70

4.37 27.30 65.00

1.94 12.20 77.20

1.27 8.00 85.00

Industrial/ Scavenging

Soil

Biogenic/ Combustion

Communality

Lime pulverisation

0.91 0.91 0.82 0.89 0.92 0.90 0.91 0.89 0.87 0.88 0.69 0.75 0.90 0.66 0.82

Characterization of precipitation at Agra Each variable was also evaluated for its K M O value (Kaiser-Meyer-Olkin, measure of sampling adequacy) (SPSS, 1983) and was included in the matrix only if it had a K M O value greater than 0.6. Finally, factors with eigenvalues greater than one were considered for varimax rotation to obtain the final factor matrix. This analysis identified four factors that contributed 85% of the variance to the data set. Factor analysis assumes that the intercorrelations among the original variables are generated by some smaller number of unobserved factors (Kessler et al., 1992). In accordance with this assumption the grouping of elements/ions in each factor could be attributed to chemical, meteorological, physical reasons as well as to common sources. These results have been presented in Table 4, which includes loading > 0.5 that are deemed to be statistically significant (Comrey, 1973). Factor 1 having high loadings on the elements Fe, Zn and Cu indicates the influence of local anthropogenic activities on precipitation composition. Elements derived from anthropogenic and marine sources are considered to be highly soluble in precipitation as compared to those derived from crustal emissions (Graedel and Weschler, 1981). The anthropogenic influences were further corroborated by an analysis of the prevailing wind directions during these precipitation events. Our observations on wind directions showed that these precipitation events were mostly associated with winds from the southeast quadrant. This region corresponds to the industrial area of the city and with respect to them, the sampling site lies downwind. Hence emissions from the industrial areas are directed to this site. Na has grouped with the anthropogenic elements in this factor. This factor also has a good loading on rain depth. From the correlation matrix it is also evident that only Na and the elements Fe, Cu and Zn are correlated with depth. The grouping of the elements Na, Fe, Cu and Zn in factor 1 may be explained on the basis of the scavenging process. Trace elements have a low scavenging efficiency: higher concentrations are obtained in events associated with greater volume and low intensity (Seinfeld, 1986). Thus it may be said that the first factor responds to the influence of industrial activities but is governed by the scavenging process. Factor 2, being loaded on Ca, SO4, HCOa, NO3, Cl and Mg clearly indicates a soil factor. Also, the grouping of the soil derived cations with the anions CI, NOa and SO4 indicates both direct emission of these species from soil and/or neutralization reactions in the atmosphere/precipitation. Factor 3, shows high loading on NH4 and K and suggests the contribution of combustion activities. NH4 and K are considered as the chemical signatures of wood burning (Lacaux et al., 1992). On the basis of higher loadings on NH4 and K, we affiliate factor 3 to biogenic combustion, yet the contribution of NH4 from decomposition of animal wastes and manure in the adjoining agricultural fields cannot be discounted.

3411

The fourth factor has significant loading on F and SiO2 and may be attributed to the process of lime pulverization in the vicinity of the sampling site.

4. CONCLUSIONS The study reveals that rainwater is alkaline, its acidity being neutralized by soil components Ca, Mg and ammonia. The soil components have a greater neutralizing effect. Another characteristic of precipitation at Agra is an excess of Ca, Na, Mg, SO,, and C1 which are of non-sea-salt origin. The incorporation of soil material into the rain reflects a major continental influence. This has led to hypothesize that, at cloud level neutralization occurs by reaction of Ca and Mg with H2504 and HNO3 while below cloud level neutralization is brought about by both ammonia and adsorption of S02 by suspended particulate matter rich in Ca and Mg. However, further research including sampling of rainwater within individual events and monitoring of cloud water is needed to confirm this hypothesis. With regard to anthropogenic contributions, the industrial centres located in the southern and southeastern parts of the city act as sources, their influence towards the north, i.e. at the sampling site is important during the monsoon months, since the predominant surface winds come from the south and southeast regions. Acknowledgements--This study was funded by grants from

the Council of Scientific and Industrial Research and the Ministry of Environment and Forests, New Delhi (India). The authors also thank the Head of the Department at this Institute for his cooperation.

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