Environ. Scl. Technol. 1983, 17, 342-347
Arbor Science: Ann Arbor, MI, 1978; Vol. 2. (2) Schwartz, D.; Saxena, J.; Kopfler, F. Environ. Sei. Technol. 1979,13, 1138. (3) Alben, K. Environ. Sei. Technol. 1980, 14, 468. (4) Oyler, A. R.; Bodenner, D. L.; Welch, K. J.; Liukkonen, R. J.; Carlson, R. M.; Kopperman, H. L.; Caple, R. Anal. Chem. 1978, 50, 837. (5) Oyler, A. R.; Liukkonen, R. J.; Lukasewycz, M. K.; Cox, D. A.; Peake, D. A.; Carlson, R. M. Environ. Health Perspect. 1982,46,73-86. (6) Graef, W.; Nothhafft, G. Arch. Hyg. Eakteriol. 1963,59, 11102. (7) Harrison, R. M.; Perry, R.; Wellings, R. A. Enuiron. Sci. Technol. 1976,10, 1156. (8) Grimely, E.; Gordon, G. J . Phys. Chem. 1973, 77, 973. (9) Shilov, E. A. Dokl. Akad. Nauk SSSR 1952,84, 1001. (10) Rosenblatt, D. H.; Broome, G. H. J . Org. Chem. 1963,28, 1290. (11) Swain, C. G.; Crist, D. R. J . Am. Chem. SOC. 1972,94,3195. (12) Shilov, E. A.; Kupinskaya, G. V.; Yasnikov, A. A. Dokl. Akad. Nauk SSSR 1951,81,435. (13) Snider, E. H.; Alley, F. C. Environ. Sci. Technol. 1979,13, 1244. (14) Kupinskaya, G. V.; Shilov, E. A. Dokl. Akad. Nauk SSSR 1960,131. 570. (15) Lister, Mi W. Can. J . Chem. 1952, 30, 879. (16) Lister, M. W. Can. J . Chem. 1955, 34, 465. (17) Lister, M. W. Can. J . Chem. 1955,34, 479. (18) Lister, M. W.; Petterson, R. C. Can. J. Chem. 1962,40,729. (19) Nikol’skii, B. P.; Krunchak, V. G.; L’vova, T. V.; Pal’chevskii, V. V.; Sosnovskii, R. I. Dokl. Akad. Nauk SSSR 1970,191, 1324. (20) Nikol’skii, B. P.; Krunchak, V. G.; L’vova, T. V.; Pal’chevskii, V. V.; Sosnovskii, R. I. Dokl. Akad. Naus SSSR 1970.197. , , 140. (21) D’Ans, J.; Freund, H. E. 2.Electrochem. 1957, 61, 10. (22) Yokoyama, T.;Takayam, 0.Kogyo Kagaku Takayasu 1967, 70, 1619; Chem. Abstr. 1968, 68, 9909813. (23) Krech, E. I. Russ. J . Inorg. Chem. 1960, 5, 1287. (24) Buxton, G. V.; Subhani, M. S. J. Chem. SOC.,Faraday Trans 1 1972, 68, 958.
(25) Connick, R. E.; Chia, Y. J. Am. Chem. SOC. 1959,81, 1280. (26) Morris, J. C. J . Phys. Chem. 1966, 70, 3798. (27) American Public Health Association. “Standard Methods for the Examination of Water and Wastewater”, 14th ed.; Washington, D.C., 1976. (28) Krishnan, S.;Kuhn, D. G.; Hamilton, G. A. J . Am. Chem. SOC.1977, 99, 8121. (29) Booth, J.; Boyland, E.; Turner, E. J. Chem. SOC.1950,1188. (30) Chanussot, P. Anales Assoc. Quim. Argent. 1927,15,216; Chem. Abstr. 22:776. (31) Shenbar, M.; Samadrignina, M. Khim. Technol. 1968,90; Chem. Abstr. 72:90139r. (32) Newman, M.; Blum, S. J . Am. Chem. SOC.1964,86,5598. (33) Bruice, P. Y.; Bruice, T. C.; Dansette, P. M.; Selander, H. G.; Yagi, H.; Jerina, D. M. J. Am. Chem. SOC.1976,98,2965. (34) Ware, J. C.; Borchert, E. E. J . Org. Chem. 1961,26, 2267. (35) Eigen, M.; Kustin, K. J . Am. Chem. SOC.1962,84, 1355. (36) de la Mare, P. B. D.; Singh, A.; Johnson, E. A.; Koenigberger, R.; Lomas, J. S.; del Olmo, V. S.; Sexton, A. M. J . Chem. SOC.E 1969, 717. (37) Connick, R. E. J . Am. Chem. SOC.1947,69, 1509. (38) Held, A. M.; Halko, D. J. Hurst, J. K. J. Am. Chem. SOC. 1978,100,5732. (39) Goto, S.;Hori, A.; Takamuku, S.; Sakurai, H. Bull. Chem. SOC.Jpn. 1978,51, 1569. (40) Akita, H.; Tanis, S. P.; Adams, M.; Balogh-Nair, V.; Nakanishi, K. J . Am. Chem. SOC.1980,102,6372. (41) Hori, A.; Matsumoto, H.; Takamuku, S.; Sakurai, H. J . Chem. SOC.,Chem. Comm. 1978, 16. (42) Zadok, E.; Mazur, Y. Tetrahedron Lett. 1980, 21, 4955. (43) Rosenblatt, D. H., personal communication, U.S.Army Medical Bioengineering Research and Development Laboratory, Fort Detrick, Fredrick, MD, 1982.
Received for review May 26,1982. Revised manuscript received December 27,1982. Accepted February 8,1983. Financial assistance for this research was provided by the Environmental Protection Agency (R8800),Frederick Kopfler, Project Officer. The contents of this paper do not necessarily reflect the views and policies of the US EPA, and the mention of trade names and commercial products does not constitute their endorsement.
Gill Surface Interaction Model for Trace-Metal Toxicity to Fishes: Role of Complexation, pH, and Water Hardness Gordon K. Pagenkopf
Department of Chemistry, Montana State University, Bozeman, Montana 597 17
bility in trace-metal toxicity to fishes at different values of alkalinity, hardness, and pH. The model utilizes trace-metal speciation, gill surface interaction, and competitive inhibition to predict effective toxicant concentration (ETC). Copper, cadmium, lead, and zinc bioassay data have been utilized.
hardness and trace-metal complexation (1-4). This paper presents a model that combines both factors. What follows is an identification of the chemical principles that are believed necessary to couple trace-metal toxicity to pH, hardness, and trace-metal complexation. The identified principles are utilized to formulate quantitative relationships, and finally, predicted variation in trace-metal toxicity is compared to that observed in laboratory tests.
A review of the many research projects that have investigated trace-metal toxicity to fishes provides at least three general conclusions: (1)for a particular trace metal, some chemical species appear to be more toxic than others; (2) the presence of elevated concentrations of the hardness cations ions, Ca2+and Mg2+,reduces trace-metal toxicity; (3) LC50 concentrations vary from metal to metal. These are not the only generalities of course, but they do provide a basis for the development of a model that can account for changes in toxicity as a function of pH, complexation capacity, and hardness of the test waters. Currently there is disagreement regarding the relative importance of water
Basis f o r Gill Surface Interaction Model (GSIM) The following are set forth as basic to the development of GSIM: (1)For acute toxicity to fish, trace metals alter the gill function, and the fish die as a result of respiratory impairment. (2) Of the trace-metal species present in a test water, some are significantly more toxic than others. (3) The gill surfaces are capable of forming complexes with the metal species and hydrogen ion present in the test waters.
W
A model has been developed to account for the varia-
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0 1983 American Chemical Society
(4) The rates of metal exchange between the gill surfaces and test waters are fast when compared to the time required for a bioassay test. (5) The gill surfaces have a finite interaction capacity per unit weight. (6) Competitive inhibition exists between the hardness metals and the toxicants, which include the trace metals and hydrogen ion. A variety of experimental observations, both chemical and biological, will be utilized to substantiate the model.
constitutes some finite fraction of the total trace metal in solution. For Cu2+this fraction, designated by acu*+,is defined as
Model Development Excessive mucous secretions are often observed when fish are stressed by elevated concentrations of trace metals (5-7) and hydrogen ion (8). In addition trace metals may be concentrated in the gill tissues (9,10)with the mechanism of toxicity apparently being related to salt and water balances within the gill tissues (11,12). The physiology associated with the toxic action of trace metals is extremely complicated, and it is not the intent of this paper to discuss or even speculate as to the mode of action. This model utilizes competitive equilibria to predict changes in the chemical activity of metal species associated with gill surfaces. This associated ion activity correspondingly influences the physiological function of the gills. Gill membranes consisting of phospholipids could provide a surface of a net negative charge and the sites necessary for the formation of Lewis acid-base complexes with the metal ions and hydrogen ion. The interaction may be classified as surface complexation (adsorption) or absorption as long as exchange is rapid and it is reversible. A schematic representation is shown in eq 1with copper
which establishes the concentration of the surface complex in terms of speciation. Bioassay tests indicate that other species may be toxic and need to be included (2). For copper, these include CuOH+, Cu(OH),.aq, and possibily C U ~ O H ~ ~All ' . are capable of forming surface complexes with the strength of the interaction being species dependent. Generalization of eq 5 provides
cu2+ +
=Sn-
KC" + =SCU-n+2
(1)
as the Lewis acid. The surface is represented by =S"-, which designates a group of Lewis base sites that collectively is capable of forming surface complexes with the metal species. This approach permits application of chemical principles that have been successfully utilized in the interpretation of more precisely defined and controlled chemical systems. The surface complex is designated by = S C u P 2 ,and the equilibrium constant for the interaction is Kcu. Utilizing the condition that complexation reactions of this type are rapid, an equilibrium expression may be written Kcu = (=SCu-n+2]/ [Cu2+]{=Sn-) (2) where braces and brackets designate concentration of moles per kilogram and moles per liter, respectively. Rearrangement of eq 2 provides (=SCu-n+2) = Kcu(=Sn-)[Cu2+l (3) which identifies a linear relationship between the concentration of the surface complex and the concentration of Cu2+in solution, provided the concentration of =Snremains constant. A relationship of this type is in agreement with experimental observation where an increase in total toxicant concentrations decreases survival time (13). Implicit is the fact that a small fraction of the complexa1 tion sites is occupied by Cu2+,and thus ( ~ s -remains essentially constant within the experimental uncertainties of the bioassay test. Trace-metal speciation in natural water systems is dependent upon pH and which complexing ligands are present. Most bioassay test waters contain minimal amounts of organic material, and thus these complexes will not be considered. A majority of the complexes involve hydroxide and inorganic carbon. Each of these species
(YCu2+
= [cu2+]/ [CUT]
(4)
where CuT is total copper in solution. Procedures for the evaluation of a values have been presented elsewhere (14). Combination of eq 3 and 4 provides (EsCu-n+21= K Cu~=sn-~aCuz+[cuTI -
(=SCu,) = Kcu,(=S"-)aCu,[Cu~]
(5)
(6)
where (=SCui) represents the concentrations of the surface complex for the ith copper species. Similarly KcU,and ac are the surface complexation equilibrium constants an3 the fractions of total copper present as the ith species. An equation similar to eq 6 is applicable for the other trace metals. There are reports ( I , 3, 4 ) indicating that an increase in water hardness increases fish resistance to trace metals. Test water concentrations for the common hardness metals, calcium and magnesium, range from approximately 10 to 1000 mg/L as CaC03. The corresponding concentrations would be 104-10-2 M. For these metals to exhibit a pronounced protective effect, their concentration generally has to be greater than M. These metals form few complexes with the ligands found in most test waters, and therefore the aquated metal concentration is essentially equal to the total metal concentration. The GSIM model interprets the protective action of the hardness cations as a competition between these metal ions and the toxic species, in essence competitive inhibition. The total number of surface interaction sites is given by eq 7 , where =Sn- are the free sites, G S ( M ) - ~ +are ~ those
ST = =Sn-
+ E S ( M ) ~ ++~E S ( H ) - ~ ++~ =S(TM)
(7)
occupied by the hardness cations, ES(H)-~" are those occupied by hydrogen ion, and +(TM) are those occupied by the trace-metal species. Charges for =S(TM) are omitted, and since Ca2+and Mg2+exhibit similar chemistries, they are not differentiated. For test waters of pH 6 or greater there appears to be little hydrogen ion dependence, and with concentrations of hardness cations many orders of magnitude greater than the concentrations of the toxic trace-metal species, it is assumed that (=Sn- + ES(M)-~+~) >> (=S(H)+l + =S(TM)). The equilibrium expression for the hardness metal interaction is
KM = (=S(M)-n+2)/([M2+](~Sn-))
(8)
Substitution into the simplified form of eq 7 with rearrangement provides
FSn-/EST = 1/(1 KM[M~'])= CIF
(9)
which is designated as the competitive interaction factor, CIF. Substitution into eq 6 provides a relationship suitable for the interpretation of the copper toxicity data: (=sCui) = ~ c , , c U c , , [ c u ~ ] ( ~ s ~+) /KM[M"]) (1 Envlron. Scl. Technol., Vol. 17, No. 6 , 1983
(10) 343
Table I. Species Concentrations, Hardness, and ETC Values for Rainbow Trout (1 )
test no.
pH
hardness, CU," mg/L as pg/L CaCO, CIFb
1 2 3 4 5 6 7 8 9 10 11
6.0 6.0 6.0 7.0 7.0 8.0 8.0 8.0 9.0 9.0 9.0
22.2 39.5 82.2 32.5 137 16.2 138.6 83.1 14.8 35.2 16.0
a
32 101 371 101 298 31 371 360 30 98 364
0.44 0.17 0.08 0.17 0.06 0.44 0.05 0.05 0.44 0.17 0.05
ETC,C pg/L 9.77 6.72 6.58 5.50 8.22 7.13 6.93 4.16 6.51 5.98 0.8 av 6.21 * 2.29
Cu = [Cu2+]+ [CuOH+] = [Cu(OH),.aq]. CIF = 1/ ETC= CIF([Cu2+] +
(1 + K M [ M * + ] ) K , M = 5 X lo3. [CuOH'] t [Cu(OH),.aq]).
Defining {=SCui)/ ((KcuJ{=ST}) as the effective toxieant concentration, ETC, eq 10 becomes ETC = [CuT]acui/(l+ KM[M2+])= CIF[toxic species] (11)
Application of GSIM Copper. Chemical speciation has successfully accounted for variation in toxicity of some metals ( 2 , 4 , 15-1 7). In these studies the total metal concentrations is often much greater than the concentration of the most toxic species. Equation 11 is capable of accounting for the speciation; however, a value for KM has to be assigned before quantitative interpretation of the hardness can be presented. An empirical estimate of 5 X lo3 comes from observed copper toxicity. The concentration of the hardness metals has to be greater than M before a pronounced effect is observed. The data presented by Miller and Mackay (3) provides a way to estimate this constant. They determined copper toxicity as a function of hardness at constant pH and complexation capacity. As a consequence CUT may be compared directly. From these comparisons KMis calculated to be (7 f 5) X lo3. Equation 11indicates that ETC should have a constant value for a given test species and constant time of exposure. For copper ETCcu = CIF([Cu2+]+ [CuOH+] + [ C U ( O H ) ~ . ~(12) ~]) Data presented by Howarth and Sprague (1) include a change in species distribution as well as hardness (see Table I). The mean ETCcu value for rainbow trout is 6.21 pg/L with a standard deviation of 2.29. An extensive study utilizing cuttthroat trout provides another system for the application of GSIM ( 4 ) . Three hardness and three alkalinity concentrations were employed, resulting in nine combinations. The toxic species are considered to be Cu2+,CuOH+, and Cu(OH)2.aq, and the fraction of the interaction surface available is regulated by the hardness metal ion concentrations. The values of ETCcu are listed in Table 11. For comparison, the average 96-h ETCcu for rainbow trout is 6.21 pg/L, whereas the comparable value for cutthroat is 2.72 pg/L. Copper species distribution and ETC values have been calculated for the Miller and Mackay data (3), and the 344
Table 11. Predicted ETC Values for Cutthroat Trout (4)"
Environ. Sci. Technoi., Vol. 17, No. 6, 1983
hardness/ alkalinity, mg/L as CaCO,
pH
CIF
c u ,b pg/L
205/178 205/77.9 160/26.0 70/174 70170 74.3122.7 18/183 18178.3 26.4120.1
7.73 7.61 7.53 8.54 7.40 7.57 8.07 8.32 7.64
0.089 0.089 0.11 0.22 0.22 0.21 0.53 0.53 0.43
18.5 27.4 27.4 9.2 25.2 14.2 1.53 7.09 5.21
ETC,pg/L 1.65 2.44 3.04 2.02 5.54 2.98 0.81 3.75 2.24 av 2.72 * 1.33
Cu = Cu2++ CuOH' + a Data from ref 4, 96-h LC50. Cu(OH), 'aq, species distribution calculated by using for CuOH+ log K f = 6.48 and for Cu(OH), log p2 = 11.78 (It?), 96-h LC50.
Table 111. Predicted ETC Values for Rainbow Trout and Fathead Minnows hardness/ a1kalinity, mg/L as CaCO, 12/10" 99/10" 49/28" 98/28" 12/51' 97/51'"
pH 7.1 7.0 7.3 7.2 7.4 7.3
cu, pg/L
CIF
rainbow trout 0.62 12.7 0.17 38.0 0.36 17.0 0.17 30.5 0.62 3.6 0.17 21.7
ETC,pg/L
7.87 3 6.52 3 6.10 3 5.18 3 2.22 3 3.69 3 av 5.26 * 1.89 3.88 19
300/205b 7.35
0.0625
62.2
198/161b 31.4/15b 360/150b 20/gb
fathead 0.092 0.39 0.053 0.50
minnow 45.9 39.7 70.5 13.2 av
a
7.9 7.2 8.2 7.5
15-day LC50 values.
ref
4.22 15.5 3.7 6.6 7.53
20 21 22 22 f
5.48
96-h LC50 values.
results are summarized in Table 111. Values for the 15-day test are somewhat less than those observed for the 96-h test with rainblows, 5.28 vs. 6.21 pg/L. The order of resistance of the test fish to copper appears to be fathead minnows > rainbow trout > cutthroat trout. The data presented in Tables 1-111 include a variation in pH from 6 to 9, an alkalinity variation from 10 to 205 mg/L as CaC03, a hardness variation from 12 to 371 mg/L as CaC03, and a variation in total copper by more than a factor of 100. Application of the GSIM to these data has identified an effective toxicant concentration for each test animal. The variability in the predicted ETC values is equal to or less than the observed experimental variability. This model is based on the premise that trace-metal species bound to the gill surfaces cause impairment of physiological functions. The amount of trace metal bound is regulated by the chemical composition of the test waters. Specifically a competition exists between the hardness metals and the toxic species for interaction sites. Zinc. The coordination chemistry of zinc is similar to copper in many respects; however, the thermodynamic stability constants are generally not as large. Zinc speciation for a number of bioassay studies has been completed, and a correlation exists between the sum of the concen-
Table IV. Zinc Toxicity to Brook Trout and Rainbow Trout (23) fish size mean wgt,g
hardness/ alkalinity, mg/L as CaCO,
3.0 3.0 3.9 3.9 19.0 19.0
46.8/41.8 177.61170.2 47.0142.8 179.0/170.1 44.4/42.5 169,7143.0
3.9 3.9 4.9 4.9 28.4 28.4
46.8141.8 177.6/170.2 47.0142.8 179.0/170.1 44.4/42.5 169.7143.0
Zn,b mg/L
ETC , CIF mg/L
brook trout 7.63 1.55 7.41 6.14 7.58 2.12 7.17 6.98 7.38 2.42 7.31 4.98
1.42 4.83 1.94 5.91 2.27 4.71
0.30 0.43 0.10 0.48 0.30 0.58 0.10 0.59 0.31 0.70 0.11 0.44
rainbow trout 7.63 0.370 7.41 2.51 7.58 0.517 7.17 2.96 7.38 0.756 7.31 1.91
0.339 1.96 0.475 2.56 0.712 1.81
pH
96-h LC50 values.
ZnT,a mg/L
0.30 0.10 0.20 0.30 0.14 0.10 0.26 0.31 0.22 0.11 0.19 0.10
Zn = Zn2+ t ZnOH+.
Table V. Cadmium Toxicity to Rainbow Trout (25)a hardness, mg/L as CdT, CaCO, mg/L 20 80 320 320
0.091 0.358 3.69 0.677
Cd,b mg/L
CIF
0.083 0.262 1.66 0.618
0.50 0.20 0.058 0.058
a pH 7.2, 48-h LC50. Cd( OH), ‘aq.
ETC, mg/L 0.042 0.052 0.096 0.036 av 0.056
Cd = Cd2++ CdOH’
k
0.027
+
trations of Zn2+and ZnOH+ and the observed toxicity (17). Utilization of the procedures outlined for copper provide ETCz, = CIF([Zn2+]+ [ZnOH+])
(13)
A recent report by Holcombe and Andrew (23) presents additional zinc toxicity data for brook trout and rainbow trout. This study was designed to test the influence of hardness. The conditions were well regulated, and the results are presented in Table IV. Lead. A chronic bioassay study by Davies et al. (24) has established that the maximum acceptable toxicant concentration (MATC) for rainbow trout in hard water should range from 18.2 to 21.7 pg/L dissolved lead. In soft water the MATC ranges from 4.1 to 7.6 pg/L. Species distributions for the test waters indicate that soluble lead was dominated by Pb2+and PbOH+. The hardness of the test waters was 353 and 28 mg/L as CaC03, respectively. Calculated CIF values are 0.054 and 0.42, which indicates that soluble lead should be 7.8 times more effective in soft water. The MATC ratio is 4.3 with means and ranges from 2.4 to 7.7 by use of the extreme values. A majority of the
lead studies are of static design and there is sizable difference between total lead and soluble lead. Cadmium. A study designed to test the influence of hardness on cadmium toxicity to rainbow trout (25) has been reported. There is major variation in hardness, 20-320 mg/L as CaC03, and the alkalinity of the waters was not reported. Test water conditions were reported earlier (19),and these values were utilized to calculate the speciation. The results are summarized in Table V. Given the range of hardness 20-320 mg/L and the range of total cadmium 0.091-3.69 mg/L (a factor of 40), the agreement is considered to be very good. Combination of Metals. The interpretation of metal toxicity resulting from the mixture of metals is of sizable current interest and will probably become more critical as time goes on. The terminology put forth by Sprague (26, 27) is useful for discussion purposes. When the toxicity of a mixture corresponds to the sum of the fractions of the single components, the effect is referred to as “additive”. When the effect is greater than or less than, a “morethan-additive” or “less-than-additive” effect is assigned. The GSIM assumes an additive effect. This results from the linear or near linear relationship between concentration of the surface species and the corresponding concentration of these species in solution. To apply the model, the toxic unit concept (27) needs to be utilized. This may be accomplished through ratios of the ETC va!ues for the respective metals. A paper by Eaton (28) reports 72- and 96-h LC50 data for mixtures of Cu, Cd, and Zn. The data are summarized in Table VI. In a parallel study (28)it was observed that 5030 pg/L total zinc was required for the 96-h LC50. The pH, alkalinity, and hardness are the same, and thus 0.41 toxic units are assigned to zinc. This value is equal to the ratio of the zinc required in the mixed-metal study to that required when zinc was the only toxicant (2050/5030). Another study from the same laboratory (20) reported a 96-h LC50 total copper value of 430 pg/L. From these values 0.36 toxic units are assigned to copper (154/430). The contribution from cadmium is difficult to assign since the acute study for cadmium and fathead minnows reported the presence of sizable amounts of insoluble cadmium salts (29). Using the lowest total dissolved cadmium concentration, 1400 pg/L, a hardness of 201 mg/L as CaC03, a pH of 7.7, and an alkalinity of 161 mg/L as CaC03, 118 pg/L is predicted for the Cd ETC value. Coupled with the value in Table VI, 0.22 toxic units are assigned to cadmium (26.3/118). Summation of the respective contributions provides a value near unity and may be significant. There is sizable uncertainity in the cadmium contribution, however. Other trace-metal mixture studies (30,31)indicate an additive response. There are insufficient chemical data available to do chemical speciation, and thus ETC cannot be calculated. In the cases where pH, alkalinity, and hardness remain fairly constant, total concetrations may be utilized as a measure of fish response.
Table VI, Toxicity of Cu, Cd, and Zn Mixture to Fathead Minnowsa (28) metal
metal concn, Fg/L (total)
cu Cd Zn
154 320 2050
pg/L
9.52 299 1517
CIF
ETC, pg/L
0.088
0.84 26.3 133
0.088 0.088
TU 0.36 - 0.41 0.22 sum -0.99
a 96-h results, alkalinity = 154 mg/L as CaCO,, hardness = 207 mg/L as CaCO,, pH 7.7. Cu(OH),,aq; Zn = Z n Z ++ ZnOH’: Cd = CdZ++ CdOH’.
Cu = Cuz++ CuOH’
+
Environ. Sci. Technol., Vol. 17, No. 6, 1983
345
A sequence of papers (32-34) has reported the toxicity of mixtures to guppies. In these experiments copper and nickel appear additive, whereas copper and zinc appear more than additive. For the zinc studies (32),a 96-h LC50 value of 6.76 mg/L is reported. This value exceeds the calculated zinc solubility of 3.2 mg/L. A lower concentration of zinc would correspondingly decrease the degree of apparent enhanced toxicity due to the mixture of copper and zinc. Hydrogen Ion. It is difficult to precisely define the tolerance of fish toward elevated hydrogen ion concentrations since it appears to be dependent upon many variables. One report indicates that pH values near 5 may represent a lower tolerance limit, however (35). In addition, alteration of gill surface tissues is observed at pH values below 5.2 (36). The concentration ranges where the respective metals exert an influence, [Ca] N M; [CUI lO-*-lO-’ M; [Zn] N 10“ M; [Pb] CT lo-’ M; and [Cd] N lo4 M, provides an indication of the stability of the metal-surface interaction. The stability constants are, in general, the inverse of concentration where the median effect is observed. The values are in the range of the stability constants observed when these metals are complexed by multidentate carboxylate or phosphate ligands. Acid dissociation constants for carboxylic acids are often near and thus the observation that hydrogen ion becomes toxic in the pH 5 region is not unexpected. Weak acid species distribution changes rapidly as the pH varies in the range of the acid pK,. At the lower pH values the concentration =S(H)+l in eq 7 is not small when compared to the other components and thus can contribute to the observed toxicity. Hydrogen ion will compete for the interaction sites, and as a consequence trace metals should not be as toxic in the more acidic regions. Correspondingly, fish should be able to tolerate more acid in hard water.
Summary A model that includes chemical speciation and gill surface interaction has been developed to account for the variation of trace-metal toxicity to fishes under varying conditions of pH, hardness, and test water complexing capacity. The net result is a series of equations that relates water chemistry to observed fish toxicity. Trace-metal toxicity is considered to be additive. The protective action of the hardness metals is due to their sucessful competition with the trace-metal species for gill surface interaction sites. These interactions are more extensive for the divalent metal ions than for the other common cations, Na+ and K+, which do not exhibit the same protective action. The concept of effective toxicant concentration has been formulated. For a given metal and test fish, ETC exhibits a variation comparable to experimental reproducibility even though hardness, pH, alkalinity, and total metal concentration vary by several orders of magnitude. The idea of competition between the metal ions has been suggested previously (37) but not formulated this way. Applicability of GSIM. GSIM is easily applied to water suspected to contain sufficient quantities of trace metals to cause acute toxicity. The data required, pH, alkalinity, hardness, and total trace-metal content, are usually available. The first step involves calculating the species distribution. Second is an evaluation of CIF and subsequently ETC. The latter is then compared to laboratory observation. For natural waters that contain additional complexing agents such as humic and fulvic acids, a reduction in toxicity is to be expected since the tracemetal complexes with these agents appear to be nontoxic (38). The trace-metals species adsorbed by suspended 346
Environ. Scl. Technol., Vol. 17, No. 6, 1983
particulate matter are also predicted to be nontoxic.
Acknowledgments Appreciation is extended to G. R. Phillips and R V. Thurston for resource materials and to the reviewers for many helpful comments.
Appendix The following is a listing of the stability constants used to calculate the species distributions. Calculations utilized COMICS (39) and UMDEQ (40). HCO,-, log K = 10.30; CO,.aq, log K = 16.76; CuC03, log K = 6.75; C U ( C O ~ ) ~ ~ - , log pZ = 9.92; CuHC03+,log K = 2.0; CuOH+,log K = 6.48; Cu(OH),.aq, log pz = 11.78; Cuz(OH)2+,log K = 17.7; CaC03, log K = 3.15; CaHCO,+, log K = 1.0; CaOH+, log K = 1.3; ZnC03, log K = 5.0; ZnOH+, log K = 6.31; Zn(OH),.aq, log pz = 11.19; CdC03, log K = 4.0; CdOH+,log K = 4.61; Cd(OH),.aq, log p2 = 8.92. Registry No. Cu, 7440-50-8;Cd, 7440-43-9; Rb, 7439-92-1; Zn, 7440-66-6.
Literature Cited Howarth, R. S.; Sprague, J. B. Water Res. 1978,12,455-462. Pagenkopf, G. K.; Russo, R. C.; Thurston, R. V. J . Fish. Res. Board Can. 1974, 31, 462-465. Miller, T. G.; Mackay, W. C. Water Res. 1980,14,129-133. Chakoumakos, C.; Russo, R. C.; Thurston, R. V. Environ. Sei. Technol. 1979, 13, 213-219. Eider, R.; Gardner, G. R. J. Fish. Biol. 1973,5, 131-142. Eider, R. J. Fish. Biol. 1974, 6, 601-2. Skidmore, J. F.; Tovell, P. W. A. Water Res. 1972, 6, 217-230. Daye, P. G.; Garside, E. T. Can. J. Zool. 1976,54,214&55. Phillips, G. R.; Russo, R. C. “Metal Bioaccumulation in Fishes and Aquatic Invertebrates: A Literature Review”; EPA-600/3-7&103, US. Environmental Protection Agency, Duluth, MN, 1978. Brungs, W. A.; Leonard, E. N.; McKim, J. M. J.Fish Res. Board Can. 1973,30, 583-86. Packer, R. K.; Dunson, W. A. J. Exp. Zool.1970,174,65-72. Lorz, H. W.; McPhenon, B. P. J. Fish Res. Board Can. 1976, 33, 2023-30. EPA-44019-76-023,U. S. Environmental Protection Agency, Washington, DC, 1976. Pagenkopf, G. K. ”Introduction to Natural Water Chemistry”; Marcel Dekker: New York, 1978. Andrew, R. W.; Biesinger, K. E.; Glass, G. E. Water Res. 1977,11, 309-15. Sunda, W. G.; Engel, D. W.; Thuotte, R. M. Environ. Sci. Technol. 1978, 12, 409-413. Pagenkopf, G. K. In ”Zinc in the Environment, Part 2: Health Effects”; Nriagu, J. O., Ed.; Wiley-Interscience: New York, 1980; pp 353-361. Sunda, W. G.; Hanson, P. J. In “Chemical Modeling in Aqueous Systems”;Jeanne, E. A,; Ed.; American Chemical Society: Washington, DC, ACS Symp. Ser. No. 93. Calamari, D.; Marchetti, R. Water Res. 1973, 7, 1453-64. Mount, D. I. Water Res. 1968,2, 215-223. Mount, D. I.; Stephan, C. E. J. Fish Res. Board Can. 1969, 26, 2449-2457. Pickering, Q.H.; Henderson, C. Air Water Pollut. Znt. J. 1966,10, 453-463. Holcombe, G. W.; Andrew, R. W. EPA-600/3-78-094, U.S. Environmental Protection Agency, Washington, DC, 1978. Davies, P. H.; Goettl, J. P., Jr.; Sinley, J. R.; Smith, N. F. Water Res. 1976, 10, 199-206. Calamari, D.; Marchetti, R.; Vailatis, G. Water Res. 1980, 14, 1421-1426. Sprague, J. B. Water Res. 1969, 3, 793-821. Sprague, J. B. Water Res. 1970, 4, 3-32. Eaton, J. G. Water Res. 1973, 7, 1723-1736. Pickering, Q. H.; Gast, M. H. J. Fish Res. Board Can. 1972, 29, 1099-1106.
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Brown, V. M. Water Res. 1968, 2, 723-733. Brown, V. M.; Dalton, R. A. J. Fish Biol. 1970,2,211-216. Anderson, P.D.; Weber, L.J. Toxicol. Appl. Pharrnacol. 1975,33,471-483. Anderson, P.D.; Weber, L.J. Proc. Int. Conf. Heavy Met. 1973, 2, 933-953. Muska, C. F.; Weber, L. J. EPA 600/3-77-085, U.S. Environmental Protection Agency, Washington, DC, 1977, p 71-87. Jones, J. R. E. "Fish and River Pollution"; Butterworths: London, 1964; 107-116. Daye, P. G.; Garside, E.T. Can J. Zoo1 1976,54,2140-55.
(37) Zitko, V. Proceedings of Toxicity to Biota of Metal Forms in Natural Water, International Joint Commission, 1976, pp 9-32. (38) Zitko, V.; Carson, W. V.; Carson, W. G. Bull. Environ. Contam. Toxicol. 1973,10, 265. (39) Perrin, D. D.; Sayce, I. G. Talanta 1967, 14, 833-42. (40) Harriss,D. K.; Ingle, S. E.; Magnuson, V. R.; Taylor, D. K. REDEQL-UMD, Department of Chemistry, University of Minnesota-Duluth, 1982.
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Received for review November 25, 1981. Revised manuscript received October 25, 1982. Accepted February 17, 1983.
Study of the Ammonia (Gas)-Sulfuric Acid (Aerosol) Reaction Ratet Peter H. McMurry," Hlroshl Takano,t and Gary R. Anderson
Particle Technology Laboratory, 130 Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455-011 1 An experimental study of the reaction rate between monodisperse sulfuric acid aerosols and ammonia gas is described. Reactions took place in a laminar flow reactor at 24 "C and 6% relative humidity, and reaction products were sampled from the core of the flow so that reaction times were well defined. For the data reported here, the reaction time was 5.0 f 0.5 s, ammonia concentrations ranged from 13 to 63 ppb, and particle sizes ranged from 0.03 to 0.2 pm. The extent of reaction was determined by comparing the hygroscopic and deliquescent properties of the product aerosols with known properties of aerosols consisting of internal mixtures of sulfuric acid and ammonium sulfate. It was found that the average fraction of ammonia-aerosol collisions that resulted in chemical reaction during neutralization decreased from 0.40 f 0.10 for 0.058-pm particles to 0.18 f 0.03 for 0.10-pm particles. Differential mobility analyzers were used for generating the monodisperse aerosols and also for measuring the hygroscopic and deliquescent properties of the product aerosols.
Introduction The significance of the reaction between sulfuric acid (H2S04)containing aerosols and gaseous ammonia (NH,) in the atmosphere has been discussed by Huntzicker et al. ( I ) . Because NH3 tends to neutralize acidic sulfate aerosols formed by gas-to-particle conversion, this reaction may be important in moderating the acidity of atmospheric aerosols. Furthermore, liquid-phase reactions in aerosol microdroplets are probably pH dependent. Therefore, NH, neutralization may affect rates of secondary aerosol formation by liquid-phase reactions. Recent analysis of data acquired in field studies has shown that liquid-phase reactions tend to predominate for relative humidities greater than 75% (2). The NH3-H,S04 reaction is also important in the human airways, where NH3 concentrations are much higher than atmospheric levels due to release of NH3 within the oral cavity and the lungs. Dydek ( 3 ) has shown that this reaction is sufficiently fast to neutralize sulfate-containing particles before they deposit within the airways. Therefore in health effects studies it is important to consider possible 'Particle Technology Laboratory Publication No. 472 t Present address: Okuda Laboratory, Department of Chemical Engineering, Doshisha University, Karasuma Imadegawa, Kamigyo-Ku, Kyoto, 602 Japan 0013-936X/83/0917-0347$01.50/0
changes in aerosol chemical composition due to ammonia addition within the airways. Several previous investigators have studied the reaction between NH, gas and H2S04 aerosols (1, 3 , 4 ) . In these studies, experiments were conducted at a variety of humidities and reactant concentrations; the range of particle sizes collectively spanned was 0.2-1.4 pm. In all cases, the reaction rate was determined by measuring the amount of NH3 that was incorporated into the aerosols after particles of a known size were exposed to measured NH3 concentrations for a known period of time. Although experiments were done under a variety of conditions and with a variety of measurement techniques, results of the studies tended to be relatively consistent. The fraction of collisions between gaseous NH3 molecules and the aerosol particles that resulted in chemical reaction was greater than 0.1 (determined by mass-transfer theory, as discussed by Huntzicker et al. ( I ) ) . Also, reaction rates were observed to decrease as the degree of neutralization increased, particularly at low relative humidities. Robbins and Cadle ( 4 ) speculated that diffusion within the aerosol droplets might be sufficiently slow to impede absorption of gaseous "3.
In the present study, the kinetics of the NH3 (gas)-H2S04 (aerosol) reaction was also investigated. However, in this study, smaller particles (0.03-0.2 pm) were studied. Also, rather than using direct chemical techniques to determine the degree of neutralization, hygroscopic and deliquescent properties of the product aerosols were used. In interpreting the data, it was assumed that H2S04p ~ ticles that were partially neutralized by NH, behave like equivalent internal mixtures of H2S04and (NH4)2S04as discussed by Tang et al. (5). The advantage of the experimental technique used in this study is its sensitivity. Accurate measurements of hygroscopic and deliquescent properties were made with aerosol concentrations of about 1 ng m-,, which is 3-4 orders of magnitude lower than can be done by in situ measurements of aerosol chemical composition.
Experimental Section A schematic diagram of the apparatus used in these experiments is shown in Figure 1. Compressed air was passed through an oxalic acid coated filter to remove particles and ammonia. A portion of this air was used when generating monodisperse H2S04 particles with a Collison atomizer (6) and differential mobility analyzers (DMA) 1 and 2. The air-flow rates through the atomizer
0 1983 American Chemlcal Society
Envlron. Sci. Technol., Vol. 17, No. 6, 1983 347
