Chemical Composition of Acid Precipitation in Pasadena, Calif. Howard M. Liljestrand’ and James J. Morgan Environmental Engineering Science, California Institute of Technology, Pasadena, Calif. 9 1125
Wet-precipitation-only samplers were used to collect acid rainfall in Pasadena, Calif., from February 1976 to September 1977. The concentrations of the major cations (H+,NH:, K’, Ca2+,and Mg2+)and the major anions (Cl-, NO;, and SO:-) were determined. The relative importance of different sources was calculated by a chemical balance. The volume weighted mean pH was 4.06 with nitric acid being 32% more important than sulfuric acid. The p H was controlled by the interaction of bases and strong acids.
Acid precipitation is a well-described phenomenon in northern Europe. Oden (1)attributes the spread of acid rain through Europe and the increased intensity of rainfall acidity to increased anthropogenic emissions of NO, and SO2. The major acid is considered to be sulfuric acid with other acids and bases contributing to the net acidity of the precipitation. Cogbill and Likens ( 2 ) found a similar trend of increased rainfall acidity in the northeastern United States. Since measured pH or acidity values were not available, p H values were calculated from reported cation and anion data by assuming a charge balance and equilibrium of the carbonate species with the atmospheric partial pressure of carbon dioxide. The acidity in the Northeast was calculated to be due to sulfuric acid (60%), nitric acid (30%),and hydrochloric acid (5%).The spread and intensification of acid precipitation in the Northeast were attributed to industrial growth downwind to the Midwest. Using the methods of Cogbill and Likens ( 2 ) ,approximate weighted mean p H values for the Southwest can be calculated from the data of Junge ( 3 )and Junge and Werby ( 4 )and the data of Lodge et al. ( 5 ) .Calculated p H values show precipitation in the Southwest before 1970 t o be mostly above p H 5.65. As described by Stumm and Morgan ( 6 ) , p H values above 5.65 in an aqueous system in equilibrium with a 315 ppm carbon dioxide atmosphere indicate the addition of alkalinity, and values below 5.65 indicate the presence of acid(s) N B where N B is the such that ZjZ,i.a,j-CTj L equivalents per liter of base added to the solution, CT, is the total molar concentration of t h e j t h acid in ionic and nonionic forms, and cyl, is the mole fraction of the j t h acid that has ionized to donate i hydrogen ions to the solution. The samples from the Los Angeles and San Diego area may have been acidic with p H values below 5.65. T o quantify and identify an acid precipitation phenomenon in southern California, a rainfall sampling program was established in 1976 a t Caltech.
storm and manually uncovered a t the onset of precipitation. Samples were removed during and immediately after each storm event and stored a t 4 “C as suggested by Galloway and Likens (7). The samplers were located approximately 10 m above ground on the roof of the Keck Laboratory a t the California Institute of Technology. Chemical analysis of samples was performed as soon as possible after each storm. Metal ion concentrations were determined by atomic absorption spectrometry. Ammonium concentrations were determined with an Orion ammonia electrode Model 95-10 and an Orion 801a pH meter. p H was determined with a glass electrode and a double-junction reference electrode that had been standardized with dilute acid solutions to minimize junction potential effects. Anion concentrations were determined with a Dionex Model 10 ion chromatograph. The anion concentrations of some samples were also measured by methods recommended by Taylor et al. (8).Total organic carbon in the samples from the all-glass collectors was determined with the Envirotech organic analyzer. Total residue and filterable residue were determined by procedures in “Standard Methods” (9).Evaporating dishes and filters were dried to constant weight a t 103-105 “C. Samples were titrated with standard base in a closed jacketed beaker. The initial p H was recorded before high-purity nitrogen gas was bubbled through the sample to remove dissolved carbon dioxide. The titration was performed under a nitrogen atmosphere. Gran functions from the titration data were plotted to distinguish the strong and weak acid components of the rainwater as recommended by Askne and Brosset ( 1 0 ) and Krupa et al. (11).
+
Experimental Methods Rainwater was collected by both all-glass and all-plastic samplers. The collectors were set up immediately before each 0013-936X/78/0912-1271$01.00/0
@ 1978 American Chemical Society
Results Between February 1976 and September 1977,43 samples were collected during 15 rainfall events. The precipitation or volume weighted mean concentrations of the major chemical species are given in Table I. The precipitation weighted mean is defined by
[XI
Pi[xli =L
c pi 1
where Pi is the precipitation during the time the i t h sample was collected. The precipitation weighted mean represents the molar flux of species x divided by the volume flux of water during the 18-month sampling period. T o ensure that all the major chemical species had been determined in each sample, the concentration data were checked with the mass balance and charge balance constraints. In all cases, the sum of the anion equivalents divided by the sum of the cation equivalents was between 0.9 and 1.1.This indicates the charge balance is satisfied if the accuracy of the ion concentrations is 5%. The sum of the mass concentrations Volume 12, Number 12, November 1978 1271
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Table 1. Rainwater Concentrations precipitation weighted mean concn
Hf NH:
Na+ K+
Ca2+ Mgzt
Fe Mn AI
Pb
CINO,
so,'BrHCO,
Si(OH)4 organic carbon filterable residue total residue
8.7 x 10-5 M 3.3 x 10-5 M 2.5 x 10-5 M 2.1 X M 4.8 X M 3.3 X M 3.6 x 10-7 M 3.4 X M 2.8 x 10-7 M 3.6 x 10-7 M 2.9 x 10-5 M 7.5 x 10-5 M 3.0 x 10-5 M 1.5 x 10-7 M 5.8 X M 9.0 x 10-7 M 0.65 mg/L 2.3 mg/L 10.8 ma/L
IO. 0 max concn
1.6 x 10-3 M 4.7 X M M 8.7 x 10-4 M 5.2 X 3.9 x 10-4 M 9.5 x 10-7 M 4.7 x 10-5 M 1.7 x 10-7 M 4.2 x 10-5 M 2.5 x 10-7 M 2.9 x 10-5 M 1.5x 10-7 M 2.3 X M 2.5 X loW6M 3.9 x 10-7 M j ) ,a unique solution to the system of linear equations may not exist. A least-squares solution of the overdetermined system of equations will give a good estimate of the source strengths. In addition, the solution can be restricted to the tracer chemical species for which the best chemical information is known and the least loss due to fractionation during transport and raindrop scavenging processes is expected. The chemical composition of Pasadena rainwater was compared with the chemical composition of sea salt, soil dust,
fuel oil fly ash, automobile aerosol, cement dust, and gaseous air pollutants to find the contribution of each of these sources t o the rainwater. A least-squares solution of an overdetermined system of equations was used t o calculate the source strengths. The results showed 35% of the total residue due to nitrate from NO, air pollutants, 20% due to sulfate derived from SO2 air pollutants, 4.4% due to ammonium from ammonia, 17.2%due to soil dust, 13.6% due to sea salt aerosol, less that 7% due to fuel oil fly ash, 1.5%due to automobile aerosol, and less than 2% due to cement dust. The measured chemical composition and calculated chemical composition assuming the above source strengths are compared in Table 11. The model does not distinguish between raindrop scavenging of aerosol HzS04, (NH&SOd, or (NH4)HS04 species and raindrop scavenging of gaseous NH3 and SO3. The model only quantifies the strengths of the primary pollutant emissions. If chemical information within the aerosol particle size distribution were known during the storm, the model could be used with secondary aerosol of each size range and gaseous pollutants as the sources. The source strengths could then be compared with ambient concentrations and calculated scavenging efficiencies from physical-chemical models. Once the source strengths are known, the pH of the rainwater can be calculated if the alkalinity or acidity on an equivalents per mass basis is known for each source. Granat (13)proposed a simple model for calculating the pH of rainwater when the major components are derived from sea salt, soil dust, and air pollutants (ammonia, sulfur oxides, and nitrogen oxides). The contribution of each source to the rainwater chemical composition is calculated. A net acidity (or alkalinity) is calculated from the sum of the net acidity due to air pollutants and the alkalinity due to soil dust. The calculated net acidity or alkalinity is assumed to be in equilibrium with atmospheric carbon dioxide to give the pH of the rainwater. Granat’s model was applied to each rainwater sample to give a calculated pH. The agreement between the calculated pH values and the measured p H values was good; the linear correlation coefficient ( r )between the calculated and measured pH values was 0.988. This result emphasizes that the rainwater p H is controlled by the interaction of bases (“3 and metal carbonates and oxides) and strong acids (“03, HzS04). The most important acid and base in the Pasadena rainwater system are nitric acid and ammonia, respectively. The ratio of nitrate equivalents/liter to nonsea salt sulfate equivalents/liter is 1.32. Friedlander (14) reports the composition of Pasadena soil dust and cement to have negligible mass fractions of sulfate. Thus, the nonsea salt sulfate is derived from acid air pollutants. Nitric acid is the dominant acid in Pasadena, in contrast to the eastern United States where nitric acid is of increasing importance but still less important than sulfuric acid. From an air quality point of view, nitric acid might be expected to be the dominant acid. In the Los Angeles Basin more than twice as much NO, as SO2 is emitted annually on an equivalent basis (25).The ratio of the emitted NO, to SO2 on an equivalent basis from stationary sources is about 1.45. The ambient concentrations of NO, are higher than those of SO2 in Pasadena during the storms. In “Air Quality and Stationary Source Emission Control” (161,the Commission on Natural Resources of the NAS, NAE, and NRC noted that the recent rise in sulfates and nitrates in Eastern rainwater is better correlated with the rise of stationary source emissions of SO2 and NO, than with the rise of total emissions from stationary and mobile sources. Highlevel emissions from stationary source stacks are expected to be more important than ground level emissions in the processes leading to the formation and deposition of sulfates and
Table II. Mass Ratio of Chemical Species to Calculated Total Residue measured
AI Br-
C Ca2+ CIFe Kf Mg2+ Mn Naf NH: NO, Pb
Si s0:-
1.5X 9.0x 4.9 x 1.7X 7.7x 7.0x 8.7x 8.4x 3.3x 4.8x 4.4 x 3.5x 5.7 x 3.6 X 2.2x
lo-’ 10-4 10-2
lo-‘ 10-2 10-3 10-3 10-3 10-4 10-3 10-2 10-1 10-3 lop2
lo-’
Calculated
2.0x 1.4x 1.8 X 1.6X 7.5x 6.9x 4.2x 8.0x 2.1 x 4.8x 4.4x 3.5 x 5.7x 3.7 x 2.2 x
10-2 10-3
low2 10-2 10-3 10-3 10-3 10-4 10-3 10-2
lo-’ 10-3 10-2 10-1
nitrates. This hypothesis may be supported by the close similarity of the acid nitrate to sulfate ratio in Pasadena rainwater (1.32) to the NO, to SO2 equivalent emission ratio for stationary sources (1.45). Sampling is being continued to ensure the representativeness of the data. Sampling thus far has been confined to Pasadena. Other sampling stations are being set up in southern California to better characterize the rainwater chemistry of the Los Angeles Basin as a whole. The Pasadena results may be anomalous due to the unusual weather during the sampling period. Southern California is in the midst of a drought. During the sampling period two tropical storms accounted for 20% of the rain, a recordbreaking rainfall for the month of August, and a second highest rainfall for the month of September.
Literature Cited (1) Oden, S., Water Air Soil Pollut., 6 (2-4), 137-66 (1976). (2) Cogbill, C. V., Likens, G. E., Water Resources Res., 10 (6), 1133-7 (1974). ( 3 ) Junge, C. E., Trans. Am. Geophys. Union, 39 (2), 241-8 (1958). (4) Junge, C. E., Werby, R. T., J . Meteorol., 15 (51,417-25 (1958). (5) Lodge, J. R., Jr., Hill, K. C., Pate, J . B., Lorange, E., Basbergill, W., Lazrus, A. L., Swanson, G. S., “Chemistry of United States Precipitation”, National Center for Atmospheric Research, Boulder, Colo., 1968. (6) Stumm, W., Morgan, J. J., “Aquatic Chemistry”, Wiley-Interscience, New York, N.Y., 1970. (7) Galloway, J. N., Jr., Likens, G. E., Water Air Soil Pollut., 6 (2-4), 241-8 11976). (8) Taylor, JI’K., Deardorff, E. R., Durst, R. A., Maienthal, E. J., Rains, T. C., Scheide, E. P., “Simulated Precipitation Reference Materials”, National Bureau of Standards, NBSIR 75-958, 1975. (9) “Standard Methods for the Examination of Water and Wastewater’’, 13th ed, APHA, AWWA, WPCF, 1971. (10)Askne, C., Brosset, C., Atmos. Enuiron., 6,695-6 (1972). (11) Krupa, S., Coscio, M. R., Jr., Wood, F. A,, J . Air Pollut. Control ASSOC., 26 ( 3 0 ) ,221-3 (1976). (12) Miller, M. S.,Friedlander, S. K., Hidy, G. M., J . Colloid Interface Sci., 39 (l), 165-76 (1972). (13) Granat, L., Tellus, 24 (6), 550-60 (1972). (14) Friedlander, S. K., Enuiron. Sci. Technol., 7 ( 3 ) , 235-40 (1973). (15) Southern California Air Pollution Control District, “Air Quality and Meteorology”, Annual Rep. for Metropolitan Zone, 1975. (16) Commission on Natural Resources, NAS, NAE, NRC, “Air Quality and Stationary Source Emission Control”, report prepared for the Committee on Public Works, US.Senate, 94th Congress, 94-9, 1975.
Received for review December 21, 1977. Accepted M a y 22, 1978. S t u d y partially supported by E. I . du Pont de Nemours & Co., and FordlExxon Research Program. Volume 12,Number 12,November 1978
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